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various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 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For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - 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various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/.editorconfig b/.editorconfig new file mode 100644 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For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + +demo/data/ +demo/events/ +data/ +events/ +__pycache__ diff 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Generator with [Hidden] Markov Chain +# N-Back Sequence Generators -**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) 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commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + 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100644 --- a/README.md +++ b/README.md @@ -1,36 +1,10 @@ -# N-Back Sequence Generator with [Hidden] Markov Chain +# N-Back Sequence Generators -**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store 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100644 --- a/README.md +++ b/README.md @@ -1,36 +1,10 @@ -# N-Back Sequence Generator with [Hidden] Markov Chain +# N-Back Sequence Generators -**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space 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For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/.editorconfig 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For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + +demo/data/ +demo/events/ +data/ +events/ +__pycache__ diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 0000000..02e04c3 --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,10 @@ +{ + "files.exclude": { + "**/.git": true, + "**/.DS_Store": true, + "**/*.pyc": true, + "**/__pycache__": true + }, + "python.pythonPath": "/Users/morteza/miniconda3/bin/python", + "python.autoComplete.extraPaths": [".", "./tests","./generators"] 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commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf 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For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 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For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + +demo/data/ +demo/events/ +data/ +events/ +__pycache__ diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 0000000..02e04c3 --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,10 @@ +{ + "files.exclude": { + "**/.git": true, + "**/.DS_Store": true, + 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various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 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For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + +demo/data/ +demo/events/ +data/ +events/ +__pycache__ diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 0000000..02e04c3 --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,10 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it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git 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For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + +demo/data/ +demo/events/ +data/ +events/ 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100644 --- a/README.md +++ b/README.md @@ -1,36 +1,10 @@ -# N-Back Sequence Generator with [Hidden] Markov Chain +# N-Back Sequence Generators -**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 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For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + +demo/data/ +demo/events/ +data/ +events/ +__pycache__ diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 0000000..02e04c3 --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,10 @@ +{ + "files.exclude": { + "**/.git": true, + "**/.DS_Store": true, + "**/*.pyc": true, + "**/__pycache__": true + }, + "python.pythonPath": "/Users/morteza/miniconda3/bin/python", + "python.autoComplete.extraPaths": 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various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + +demo/data/ +demo/events/ +data/ +events/ +__pycache__ diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 0000000..02e04c3 --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,10 @@ +{ + "files.exclude": { + "**/.git": true, + "**/.DS_Store": true, + "**/*.pyc": true, + "**/__pycache__": true + }, + "python.pythonPath": "/Users/morteza/miniconda3/bin/python", + "python.autoComplete.extraPaths": [".", "./tests","./generators"] +} diff --git a/Pipfile b/Pipfile new file mode 100644 index 0000000..1fe2638 --- /dev/null +++ b/Pipfile @@ -0,0 +1,20 @@ +[[source]] +name = 'pypi' +url = 'https://pypi.python.org/simple' +verify_ssl = true + +[dev-packages] +pylint = "*" + +[packages] +requests = "*" +python-constraint = "*" +Numberjack = "*" +expyriment = "*" +pygame = "==1.9.5.dev0" +scipy = "*" +matplotlib = "*" +pandas = "*" + +[requires] +python_version = "3.7" diff --git a/Pipfile.lock b/Pipfile.lock new file mode 100644 index 0000000..77af3a5 --- /dev/null +++ b/Pipfile.lock @@ -0,0 +1,264 @@ +{ + "_meta": { + "hash": { + "sha256": "dd38906e3fa8df87c340f55945eb46401419dcc038ec03944585ee39d9452cdb" + }, + "pipfile-spec": 6, + 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#1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws 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100644 --- a/README.md +++ b/README.md @@ -1,36 +1,10 @@ -# N-Back Sequence Generator with [Hidden] Markov Chain +# N-Back Sequence Generators -**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ 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For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + +demo/data/ +demo/events/ +data/ +events/ +__pycache__ diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 0000000..02e04c3 --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,10 @@ +{ + "files.exclude": { + "**/.git": 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it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + +demo/data/ +demo/events/ +data/ +events/ +__pycache__ diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 0000000..02e04c3 --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,10 @@ +{ + "files.exclude": { + "**/.git": true, + "**/.DS_Store": true, + "**/*.pyc": true, + "**/__pycache__": true + }, + "python.pythonPath": "/Users/morteza/miniconda3/bin/python", + "python.autoComplete.extraPaths": [".", "./tests","./generators"] +} diff --git a/Pipfile 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commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + +demo/data/ +demo/events/ +data/ +events/ +__pycache__ diff --git a/.vscode/settings.json 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Generator with [Hidden] Markov Chain +# N-Back Sequence Generators -**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + 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100644 --- a/README.md +++ b/README.md @@ -1,36 +1,10 @@ -# N-Back Sequence Generator with [Hidden] Markov Chain +# N-Back Sequence Generators -**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + +demo/data/ +demo/events/ +data/ +events/ +__pycache__ diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 0000000..02e04c3 --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,10 @@ +{ + "files.exclude": { + "**/.git": true, + "**/.DS_Store": true, + "**/*.pyc": true, + "**/__pycache__": true + }, + "python.pythonPath": "/Users/morteza/miniconda3/bin/python", + 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various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + +demo/data/ +demo/events/ +data/ +events/ +__pycache__ diff --git a/.vscode/settings.json b/.vscode/settings.json new file 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Generator with [Hidden] Markov Chain +# N-Back Sequence Generators -**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + +demo/data/ +demo/events/ +data/ +events/ +__pycache__ diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 0000000..02e04c3 --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,10 @@ +{ + "files.exclude": { + "**/.git": true, + "**/.DS_Store": true, + "**/*.pyc": true, + "**/__pycache__": true + }, + "python.pythonPath": "/Users/morteza/miniconda3/bin/python", + "python.autoComplete.extraPaths": 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various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + +demo/data/ +demo/events/ +data/ +events/ +__pycache__ diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 0000000..02e04c3 --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,10 @@ +{ + "files.exclude": { + "**/.git": true, + "**/.DS_Store": true, + "**/*.pyc": true, + "**/__pycache__": true + }, + 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various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + 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100644 --- a/README.md +++ b/README.md @@ -1,36 +1,10 @@ -# N-Back Sequence Generator with [Hidden] Markov Chain +# N-Back Sequence Generators -**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + +demo/data/ +demo/events/ +data/ +events/ +__pycache__ diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 0000000..02e04c3 --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,10 @@ +{ + "files.exclude": { + "**/.git": true, + "**/.DS_Store": true, + "**/*.pyc": true, + "**/__pycache__": true + }, + "python.pythonPath": "/Users/morteza/miniconda3/bin/python", + "python.autoComplete.extraPaths": [".", "./tests","./generators"] +} diff --git a/Pipfile b/Pipfile new file mode 100644 index 0000000..1fe2638 --- /dev/null +++ b/Pipfile @@ -0,0 +1,20 @@ +[[source]] +name = 'pypi' +url = 'https://pypi.python.org/simple' +verify_ssl = true + +[dev-packages] +pylint = "*" + +[packages] +requests = "*" +python-constraint = "*" 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], + "markers": "python_version >= '3.7' and implementation_name == 'cpython'", + "version": "==1.3.1" + }, + "wrapt": { + "hashes": [ + "sha256:4aea003270831cceb8a90ff27c4031da6ead7ec1886023b80ce0dfe0adf61533" + ], + "version": "==1.11.1" + } + } +} diff --git a/README.md b/README.md index a24051a..1e7491b 100644 --- a/README.md +++ b/README.md @@ -1,36 +1,10 @@ -# N-Back Sequence Generator with [Hidden] Markov Chain +# N-Back Sequence Generators -**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ 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commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ 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various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ 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For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - "files.exclude": { - "**/.git": true, - "**/.DS_Store": true, - "**/*.pyc": true, - "**/__pycache__": true - }, - "python.pythonPath": "~/.local/share/virtualenvs/py-H3fe-p_n/bin/python" -} \ No newline at end of file diff --git a/py/Pipfile b/py/Pipfile deleted file mode 100644 index be22fdc..0000000 --- a/py/Pipfile +++ /dev/null @@ -1,13 +0,0 @@ -[[source]] -name = 'pypi' -url = 'https://pypi.python.org/simple' -verify_ssl = true - -[dev-packages] -pylint = "*" - -[packages] -requests = "*" - -[requires] -python_version = "3.7" diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + +demo/data/ +demo/events/ +data/ +events/ +__pycache__ diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 0000000..02e04c3 --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,10 @@ +{ + "files.exclude": { + "**/.git": true, + "**/.DS_Store": true, + "**/*.pyc": true, + "**/__pycache__": true + }, + "python.pythonPath": "/Users/morteza/miniconda3/bin/python", + "python.autoComplete.extraPaths": [".", "./tests","./generators"] +} diff --git a/Pipfile b/Pipfile new file mode 100644 index 0000000..1fe2638 --- 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For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ 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it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ 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b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + +demo/data/ +demo/events/ +data/ +events/ +__pycache__ diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 0000000..02e04c3 --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,10 @@ +{ + "files.exclude": { + "**/.git": true, + "**/.DS_Store": true, + "**/*.pyc": true, + "**/__pycache__": true + }, + "python.pythonPath": "/Users/morteza/miniconda3/bin/python", + "python.autoComplete.extraPaths": [".", "./tests","./generators"] +} diff --git a/Pipfile b/Pipfile new file mode 100644 index 0000000..1fe2638 --- /dev/null +++ b/Pipfile @@ -0,0 +1,20 @@ +[[source]] +name = 'pypi' +url = 'https://pypi.python.org/simple' +verify_ssl = true + +[dev-packages] +pylint = "*" + +[packages] +requests = "*" +python-constraint = "*" +Numberjack = "*" +expyriment = "*" +pygame = "==1.9.5.dev0" +scipy = "*" +matplotlib = "*" +pandas = "*" + +[requires] +python_version = "3.7" diff 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"==1.11.1" + } + } +} diff --git a/README.md b/README.md index a24051a..1e7491b 100644 --- a/README.md +++ b/README.md @@ -1,36 +1,10 @@ -# N-Back Sequence Generator with [Hidden] Markov Chain +# N-Back Sequence Generators -**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ 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choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + +demo/data/ +demo/events/ +data/ +events/ +__pycache__ diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 0000000..02e04c3 --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,10 @@ +{ + "files.exclude": { + "**/.git": true, + "**/.DS_Store": true, + "**/*.pyc": true, + "**/__pycache__": true + }, + "python.pythonPath": "/Users/morteza/miniconda3/bin/python", + "python.autoComplete.extraPaths": [".", "./tests","./generators"] +} diff 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commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + +demo/data/ +demo/events/ +data/ +events/ +__pycache__ diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 0000000..02e04c3 --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,10 @@ +{ + "files.exclude": { + "**/.git": true, + "**/.DS_Store": true, + "**/*.pyc": true, + "**/__pycache__": true + }, + "python.pythonPath": "/Users/morteza/miniconda3/bin/python", + "python.autoComplete.extraPaths": [".", "./tests","./generators"] +} diff --git a/Pipfile b/Pipfile new file mode 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commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + +demo/data/ +demo/events/ +data/ +events/ +__pycache__ diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 0000000..02e04c3 --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,10 @@ +{ + "files.exclude": { 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it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + +demo/data/ +demo/events/ +data/ 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100644 --- a/README.md +++ b/README.md @@ -1,36 +1,10 @@ -# N-Back Sequence Generator with [Hidden] Markov Chain +# N-Back Sequence Generators -**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ 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For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + +demo/data/ +demo/events/ +data/ +events/ +__pycache__ diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 0000000..02e04c3 --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,10 @@ +{ + "files.exclude": { + "**/.git": true, + 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it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + +demo/data/ +demo/events/ +data/ +events/ +__pycache__ diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 0000000..02e04c3 --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,10 @@ +{ + "files.exclude": { + "**/.git": true, + "**/.DS_Store": true, + "**/*.pyc": true, + "**/__pycache__": true + }, + "python.pythonPath": "/Users/morteza/miniconda3/bin/python", + "python.autoComplete.extraPaths": [".", "./tests","./generators"] +} diff --git a/Pipfile b/Pipfile new file mode 100644 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commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + +demo/data/ +demo/events/ +data/ +events/ +__pycache__ diff --git a/.vscode/settings.json 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Generator with [Hidden] Markov Chain +# N-Back Sequence Generators -**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + 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100644 --- a/README.md +++ b/README.md @@ -1,36 +1,10 @@ -# N-Back Sequence Generator with [Hidden] Markov Chain +# N-Back Sequence Generators -**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + +demo/data/ +demo/events/ +data/ +events/ +__pycache__ diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 0000000..02e04c3 --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,10 @@ +{ + "files.exclude": { + "**/.git": true, + "**/.DS_Store": true, + "**/*.pyc": true, + "**/__pycache__": true + }, + "python.pythonPath": "/Users/morteza/miniconda3/bin/python", + 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various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + +demo/data/ +demo/events/ +data/ +events/ +__pycache__ diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 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Generator with [Hidden] Markov Chain +# N-Back Sequence Generators -**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/src/main/scala/org/xcit/nback/markov/models/State.scala b/src/main/scala/org/xcit/nback/markov/models/State.scala deleted file mode 100644 index fbbd844..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/State.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * A Single state with a label in Markov chain - * @param label A simple string label, representing the state and node - */ -class State(val label: String) { - - /** - * Keep track of transitions from this state to other states. - */ - val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() -} diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + +demo/data/ +demo/events/ +data/ +events/ +__pycache__ diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 0000000..02e04c3 --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,10 @@ +{ + "files.exclude": { + "**/.git": true, + "**/.DS_Store": true, + "**/*.pyc": true, + "**/__pycache__": true + }, + "python.pythonPath": "/Users/morteza/miniconda3/bin/python", + "python.autoComplete.extraPaths": [".", "./tests","./generators"] 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commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/src/main/scala/org/xcit/nback/markov/models/State.scala b/src/main/scala/org/xcit/nback/markov/models/State.scala deleted file mode 100644 index fbbd844..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/State.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * A Single state with a label in Markov chain - * @param label A simple string label, representing the state and node - */ -class State(val label: String) { - - /** - * Keep track of transitions from this state to other states. - */ - val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() -} diff --git a/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/src/main/scala/org/xcit/nback/markov/models/Transition.scala deleted file mode 100644 index bc20a9e..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/Transition.scala +++ /dev/null @@ -1,8 +0,0 @@ -package org.xcit.nback.markov.models - -/** - * A Single transition in Markov chain graph. It is stored in "from" node. - * @param to the ending node of the edge - * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). - */ -case class Transition(to: State, probability: Double = 0.0) diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + +demo/data/ +demo/events/ +data/ +events/ +__pycache__ diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 0000000..02e04c3 --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,10 @@ +{ + "files.exclude": { + "**/.git": true, + "**/.DS_Store": true, + "**/*.pyc": true, + "**/__pycache__": true + }, + 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various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/src/main/scala/org/xcit/nback/markov/models/State.scala b/src/main/scala/org/xcit/nback/markov/models/State.scala deleted file mode 100644 index fbbd844..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/State.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * A Single state with a label in Markov chain - * @param label A simple string label, representing the state and node - */ -class State(val label: String) { - - /** - * Keep track of transitions from this state to other states. - */ - val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() -} diff --git a/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/src/main/scala/org/xcit/nback/markov/models/Transition.scala deleted file mode 100644 index bc20a9e..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/Transition.scala +++ /dev/null @@ -1,8 +0,0 @@ -package org.xcit.nback.markov.models - -/** - * A Single transition in Markov chain graph. It is stored in "from" node. - * @param to the ending node of the edge - * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). - */ -case class Transition(to: State, probability: Double = 0.0) diff --git a/src/test/scala/ThreeBackBenchmark.scala b/src/test/scala/ThreeBackBenchmark.scala deleted file mode 100644 index 0c7dad9..0000000 --- a/src/test/scala/ThreeBackBenchmark.scala +++ /dev/null @@ -1,7 +0,0 @@ - -/** - * TODO Benchmark 3-back simple sequence generator - */ -class ThreeBackBenchmark { - -} diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + +demo/data/ 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100644 --- a/README.md +++ b/README.md @@ -1,36 +1,10 @@ -# N-Back Sequence Generator with [Hidden] Markov Chain +# N-Back Sequence Generators -**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/src/main/scala/org/xcit/nback/markov/models/State.scala b/src/main/scala/org/xcit/nback/markov/models/State.scala deleted file mode 100644 index fbbd844..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/State.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * A Single state with a label in Markov chain - * @param label A simple string label, representing the state and node - */ -class State(val label: String) { - - /** - * Keep track of transitions from this state to other states. - */ - val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() -} diff --git a/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/src/main/scala/org/xcit/nback/markov/models/Transition.scala deleted file mode 100644 index bc20a9e..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/Transition.scala +++ /dev/null @@ -1,8 +0,0 @@ -package org.xcit.nback.markov.models - -/** - * A Single transition in Markov chain graph. It is stored in "from" node. - * @param to the ending node of the edge - * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). - */ -case class Transition(to: State, probability: Double = 0.0) diff --git a/src/test/scala/ThreeBackBenchmark.scala b/src/test/scala/ThreeBackBenchmark.scala deleted file mode 100644 index 0c7dad9..0000000 --- a/src/test/scala/ThreeBackBenchmark.scala +++ /dev/null @@ -1,7 +0,0 @@ - -/** - * TODO Benchmark 3-back simple sequence generator - */ -class ThreeBackBenchmark { - -} diff --git a/tests/benchmark_diagrams.py b/tests/benchmark_diagrams.py new file mode 100644 index 0000000..8fa448e --- /dev/null +++ b/tests/benchmark_diagrams.py @@ -0,0 +1,159 @@ +import pandas as pd +import numpy as np +from matplotlib import pyplot as plt + +import benchmarks.common as common + + +def tlratio(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2,ignore_index=True) + stats = [] + for trials in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == trials) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == trials) + targets2 = data[alg2].targets if alg2.shape[0] > 0 else np.nan + targets4 = data[alg4].targets if alg4.shape[0] > 0 else np.nan + lures2 = data[alg2].lures if alg2.shape[0] > 0 else np.nan + lures4 = data[alg4].lures if alg4.shape[0] > 0 else np.nan + stats.append([trials, (targets2/lures2).mean(), (targets4/lures4).mean()]) + stats = pd.DataFrame(stats, columns=['trials', 'tl2', 'tl4']) #.dropna(subset=['skewness']) + + plt.style.use('ggplot') + + plt.ylim(bottom=0, top=30) + plt.scatter(stats.trials, stats.tl2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl2[idx], 1)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.tl4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl4[idx], 2)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('T:L Ratio') + plt.ylabel('T:L Ratio') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_tlratio.png', bbox_inches='tight') + plt.show() + + +def time_per_trial(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for t in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == t) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == t) + time2 = data[alg2].time.mean() * 1000 if alg2.shape[0] > 0 else np.nan + time4 = data[alg4].time.mean() * 1000 if alg4.shape[0] > 0 else np.nan + stats.append([t, time2, time4]) + stats = pd.DataFrame(stats, columns=['trials', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.trials, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time2[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time4[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2v4_time_trials.png', bbox_inches='tight') + plt.show() + +def time_profiles(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 8): + alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + time2 = data[alg2].time.mean() * 1000 + time4 = data[alg4].time.mean() * 1000 + stats.append([ni, time2, time4]) + stats = pd.DataFrame(stats, columns=['n', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.n, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.time2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + plt.scatter(stats.n, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.time4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_time_n.png', bbox_inches='tight') + plt.show() + +def skewness(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 9): + all_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + skewed_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) & data.skewed + all_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + skewed_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) & data.skewed + num_of_sequences2 = data[all_alg2].shape[0] + skewed_sequences2 = data[skewed_alg2].shape[0] + num_of_sequences4 = data[all_alg4].shape[0] + skewed_sequences4 = data[skewed_alg4].shape[0] + skewness2 = skewed_sequences2 * 100.0 / num_of_sequences2 if (num_of_sequences2>0) else 0 + skewness4 = skewed_sequences4 * 100.0 / num_of_sequences4 if (num_of_sequences4>0) else 0 + stats.append([ni, skewness2, skewness4]) + stats = pd.DataFrame(stats, columns=['n', 'skewness2', 'skewness4']) #.dropna(subset=['skewness']) + + + plt.style.use('ggplot') + plt.scatter(stats.n, stats.skewness2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.skewness2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + + plt.scatter(stats.n, stats.skewness4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.skewness4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Skewness') + plt.ylabel('Skewed Blocks (%)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_skewness.png', bbox_inches='tight') + plt.show() + +if __name__ == "__main__": + tlratio() + skewness() + time_profiles() + time_per_trial() diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 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For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/src/main/scala/org/xcit/nback/markov/models/State.scala b/src/main/scala/org/xcit/nback/markov/models/State.scala deleted file mode 100644 index fbbd844..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/State.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * A Single state with a label in Markov chain - * @param label A simple string label, representing the state and node - */ -class State(val label: String) { - - /** - * Keep track of transitions from this state to other states. - */ - val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() -} diff --git a/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/src/main/scala/org/xcit/nback/markov/models/Transition.scala deleted file mode 100644 index bc20a9e..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/Transition.scala +++ /dev/null @@ -1,8 +0,0 @@ -package org.xcit.nback.markov.models - -/** - * A Single transition in Markov chain graph. It is stored in "from" node. - * @param to the ending node of the edge - * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). - */ -case class Transition(to: State, probability: Double = 0.0) diff --git a/src/test/scala/ThreeBackBenchmark.scala b/src/test/scala/ThreeBackBenchmark.scala deleted file mode 100644 index 0c7dad9..0000000 --- a/src/test/scala/ThreeBackBenchmark.scala +++ /dev/null @@ -1,7 +0,0 @@ - -/** - * TODO Benchmark 3-back simple sequence generator - */ -class ThreeBackBenchmark { - -} diff --git a/tests/benchmark_diagrams.py b/tests/benchmark_diagrams.py new file mode 100644 index 0000000..8fa448e --- /dev/null +++ b/tests/benchmark_diagrams.py @@ -0,0 +1,159 @@ +import pandas as pd +import numpy as np +from matplotlib import pyplot as plt + +import benchmarks.common as common + + +def tlratio(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2,ignore_index=True) + stats = [] + for trials in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == trials) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == trials) + targets2 = data[alg2].targets if alg2.shape[0] > 0 else np.nan + targets4 = data[alg4].targets if alg4.shape[0] > 0 else np.nan + lures2 = data[alg2].lures if alg2.shape[0] > 0 else np.nan + lures4 = data[alg4].lures if alg4.shape[0] > 0 else np.nan + stats.append([trials, (targets2/lures2).mean(), (targets4/lures4).mean()]) + stats = pd.DataFrame(stats, columns=['trials', 'tl2', 'tl4']) #.dropna(subset=['skewness']) + + plt.style.use('ggplot') + + plt.ylim(bottom=0, top=30) + plt.scatter(stats.trials, stats.tl2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl2[idx], 1)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.tl4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl4[idx], 2)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('T:L Ratio') + plt.ylabel('T:L Ratio') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_tlratio.png', bbox_inches='tight') + plt.show() + + +def time_per_trial(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for t in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == t) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == t) + time2 = data[alg2].time.mean() * 1000 if alg2.shape[0] > 0 else np.nan + time4 = data[alg4].time.mean() * 1000 if alg4.shape[0] > 0 else np.nan + stats.append([t, time2, time4]) + stats = pd.DataFrame(stats, columns=['trials', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.trials, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time2[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time4[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2v4_time_trials.png', bbox_inches='tight') + plt.show() + +def time_profiles(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 8): + alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + time2 = data[alg2].time.mean() * 1000 + time4 = data[alg4].time.mean() * 1000 + stats.append([ni, time2, time4]) + stats = pd.DataFrame(stats, columns=['n', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.n, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.time2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + plt.scatter(stats.n, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.time4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_time_n.png', bbox_inches='tight') + plt.show() + +def skewness(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 9): + all_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + skewed_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) & data.skewed + all_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + skewed_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) & data.skewed + num_of_sequences2 = data[all_alg2].shape[0] + skewed_sequences2 = data[skewed_alg2].shape[0] + num_of_sequences4 = data[all_alg4].shape[0] + skewed_sequences4 = data[skewed_alg4].shape[0] + skewness2 = skewed_sequences2 * 100.0 / num_of_sequences2 if (num_of_sequences2>0) else 0 + skewness4 = skewed_sequences4 * 100.0 / num_of_sequences4 if (num_of_sequences4>0) else 0 + stats.append([ni, skewness2, skewness4]) + stats = pd.DataFrame(stats, columns=['n', 'skewness2', 'skewness4']) #.dropna(subset=['skewness']) + + + plt.style.use('ggplot') + plt.scatter(stats.n, stats.skewness2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.skewness2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + + plt.scatter(stats.n, stats.skewness4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.skewness4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Skewness') + plt.ylabel('Skewed Blocks (%)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_skewness.png', bbox_inches='tight') + plt.show() + +if __name__ == "__main__": + tlratio() + skewness() + time_profiles() + time_per_trial() diff --git a/tests/benchmark_skewness.py b/tests/benchmark_skewness.py new file mode 100644 index 0000000..f468b4d --- /dev/null +++ b/tests/benchmark_skewness.py @@ -0,0 +1,97 @@ +import random +import heapq +import csv + +# Common parameters +alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'] +trials_range = (10, 40) +n = 3 +sample_size = 100 + + +def to_benchmark_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [str(ralph_skewed)] + +def benchmark_nb_gm_001(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_001') + + +def benchmark_nb_gm_002(filename): + import generators.nb_gm_002 as nb_gm_002 + + generator = nb_gm_002.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + # print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_002') + + +def benchmark_nb_gm_003(filename): + import generators.nb_gm_003 as nb_gm_003 + + generator = nb_gm_003.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + print(f"sequence {i}/{sample_size}: {trials} trials") + seq = generator.generate(trials) + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_003') + + +def show_skweness_diagram(filename, choices, title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + print(filename) + data = pd.read_csv(filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) #.dropna(subset=['skewness']) + #print(stats.trials) + #plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'{title}.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + benchmark_nb_gm_003('../benchmarks/nb_gm_003_2back.csv') diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 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], + "markers": "python_version >= '3.7' and implementation_name == 'cpython'", + "version": "==1.3.1" + }, + "wrapt": { + "hashes": [ + "sha256:4aea003270831cceb8a90ff27c4031da6ead7ec1886023b80ce0dfe0adf61533" + ], + "version": "==1.11.1" + } + } +} diff --git a/README.md b/README.md index a24051a..1e7491b 100644 --- a/README.md +++ b/README.md @@ -1,36 +1,10 @@ -# N-Back Sequence Generator with [Hidden] Markov Chain +# N-Back Sequence Generators -**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/src/main/scala/org/xcit/nback/markov/models/State.scala b/src/main/scala/org/xcit/nback/markov/models/State.scala deleted file mode 100644 index fbbd844..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/State.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * A Single state with a label in Markov chain - * @param label A simple string label, representing the state and node - */ -class State(val label: String) { - - /** - * Keep track of transitions from this state to other states. - */ - val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() -} diff --git a/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/src/main/scala/org/xcit/nback/markov/models/Transition.scala deleted file mode 100644 index bc20a9e..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/Transition.scala +++ /dev/null @@ -1,8 +0,0 @@ -package org.xcit.nback.markov.models - -/** - * A Single transition in Markov chain graph. It is stored in "from" node. - * @param to the ending node of the edge - * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). - */ -case class Transition(to: State, probability: Double = 0.0) diff --git a/src/test/scala/ThreeBackBenchmark.scala b/src/test/scala/ThreeBackBenchmark.scala deleted file mode 100644 index 0c7dad9..0000000 --- a/src/test/scala/ThreeBackBenchmark.scala +++ /dev/null @@ -1,7 +0,0 @@ - -/** - * TODO Benchmark 3-back simple sequence generator - */ -class ThreeBackBenchmark { - -} diff --git a/tests/benchmark_diagrams.py b/tests/benchmark_diagrams.py new file mode 100644 index 0000000..8fa448e --- /dev/null +++ b/tests/benchmark_diagrams.py @@ -0,0 +1,159 @@ +import pandas as pd +import numpy as np +from matplotlib import pyplot as plt + +import benchmarks.common as common + + +def tlratio(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2,ignore_index=True) + stats = [] + for trials in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == trials) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == trials) + targets2 = data[alg2].targets if alg2.shape[0] > 0 else np.nan + targets4 = data[alg4].targets if alg4.shape[0] > 0 else np.nan + lures2 = data[alg2].lures if alg2.shape[0] > 0 else np.nan + lures4 = data[alg4].lures if alg4.shape[0] > 0 else np.nan + stats.append([trials, (targets2/lures2).mean(), (targets4/lures4).mean()]) + stats = pd.DataFrame(stats, columns=['trials', 'tl2', 'tl4']) #.dropna(subset=['skewness']) + + plt.style.use('ggplot') + + plt.ylim(bottom=0, top=30) + plt.scatter(stats.trials, stats.tl2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl2[idx], 1)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.tl4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl4[idx], 2)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('T:L Ratio') + plt.ylabel('T:L Ratio') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_tlratio.png', bbox_inches='tight') + plt.show() + + +def time_per_trial(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for t in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == t) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == t) + time2 = data[alg2].time.mean() * 1000 if alg2.shape[0] > 0 else np.nan + time4 = data[alg4].time.mean() * 1000 if alg4.shape[0] > 0 else np.nan + stats.append([t, time2, time4]) + stats = pd.DataFrame(stats, columns=['trials', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.trials, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time2[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time4[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2v4_time_trials.png', bbox_inches='tight') + plt.show() + +def time_profiles(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 8): + alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + time2 = data[alg2].time.mean() * 1000 + time4 = data[alg4].time.mean() * 1000 + stats.append([ni, time2, time4]) + stats = pd.DataFrame(stats, columns=['n', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.n, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.time2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + plt.scatter(stats.n, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.time4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_time_n.png', bbox_inches='tight') + plt.show() + +def skewness(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 9): + all_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + skewed_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) & data.skewed + all_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + skewed_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) & data.skewed + num_of_sequences2 = data[all_alg2].shape[0] + skewed_sequences2 = data[skewed_alg2].shape[0] + num_of_sequences4 = data[all_alg4].shape[0] + skewed_sequences4 = data[skewed_alg4].shape[0] + skewness2 = skewed_sequences2 * 100.0 / num_of_sequences2 if (num_of_sequences2>0) else 0 + skewness4 = skewed_sequences4 * 100.0 / num_of_sequences4 if (num_of_sequences4>0) else 0 + stats.append([ni, skewness2, skewness4]) + stats = pd.DataFrame(stats, columns=['n', 'skewness2', 'skewness4']) #.dropna(subset=['skewness']) + + + plt.style.use('ggplot') + plt.scatter(stats.n, stats.skewness2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.skewness2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + + plt.scatter(stats.n, stats.skewness4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.skewness4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Skewness') + plt.ylabel('Skewed Blocks (%)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_skewness.png', bbox_inches='tight') + plt.show() + +if __name__ == "__main__": + tlratio() + skewness() + time_profiles() + time_per_trial() diff --git a/tests/benchmark_skewness.py b/tests/benchmark_skewness.py new file mode 100644 index 0000000..f468b4d --- /dev/null +++ b/tests/benchmark_skewness.py @@ -0,0 +1,97 @@ +import random +import heapq +import csv + +# Common parameters +alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'] +trials_range = (10, 40) +n = 3 +sample_size = 100 + + +def to_benchmark_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [str(ralph_skewed)] + +def benchmark_nb_gm_001(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_001') + + +def benchmark_nb_gm_002(filename): + import generators.nb_gm_002 as nb_gm_002 + + generator = nb_gm_002.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + # print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_002') + + +def benchmark_nb_gm_003(filename): + import generators.nb_gm_003 as nb_gm_003 + + generator = nb_gm_003.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + print(f"sequence {i}/{sample_size}: {trials} trials") + seq = generator.generate(trials) + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_003') + + +def show_skweness_diagram(filename, choices, title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + print(filename) + data = pd.read_csv(filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) #.dropna(subset=['skewness']) + #print(stats.trials) + #plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'{title}.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + benchmark_nb_gm_003('../benchmarks/nb_gm_003_2back.csv') diff --git a/tests/common.py b/tests/common.py new file mode 100644 index 0000000..e40c0df --- /dev/null +++ b/tests/common.py @@ -0,0 +1,27 @@ + + +# Common benchmark parameters +choices = alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F'] +trials_range = (10, 65) +n = 4 +sample_size = 100 + + +def count_targets_and_lures(seq, n): + mask = 'D'*n + for index in range(n, len(seq)): + if seq[index] == seq[index - n]: + mask += 'T' + elif seq[index] in seq[index - n - 1:index - n + 1]: + mask += 'L' + else: + mask += 'D' + return mask.count('T'), mask.count('L') + + +def skewness(seq, choices): + import heapq + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return ralph_skewed diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + +demo/data/ +demo/events/ +data/ +events/ +__pycache__ diff --git 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Generator with [Hidden] Markov Chain +# N-Back Sequence Generators -**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/src/main/scala/org/xcit/nback/markov/models/State.scala b/src/main/scala/org/xcit/nback/markov/models/State.scala deleted file mode 100644 index fbbd844..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/State.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * A Single state with a label in Markov chain - * @param label A simple string label, representing the state and node - */ -class State(val label: String) { - - /** - * Keep track of transitions from this state to other states. - */ - val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() -} diff --git a/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/src/main/scala/org/xcit/nback/markov/models/Transition.scala deleted file mode 100644 index bc20a9e..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/Transition.scala +++ /dev/null @@ -1,8 +0,0 @@ -package org.xcit.nback.markov.models - -/** - * A Single transition in Markov chain graph. It is stored in "from" node. - * @param to the ending node of the edge - * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). - */ -case class Transition(to: State, probability: Double = 0.0) diff --git a/src/test/scala/ThreeBackBenchmark.scala b/src/test/scala/ThreeBackBenchmark.scala deleted file mode 100644 index 0c7dad9..0000000 --- a/src/test/scala/ThreeBackBenchmark.scala +++ /dev/null @@ -1,7 +0,0 @@ - -/** - * TODO Benchmark 3-back simple sequence generator - */ -class ThreeBackBenchmark { - -} diff --git a/tests/benchmark_diagrams.py b/tests/benchmark_diagrams.py new file mode 100644 index 0000000..8fa448e --- /dev/null +++ b/tests/benchmark_diagrams.py @@ -0,0 +1,159 @@ +import pandas as pd +import numpy as np +from matplotlib import pyplot as plt + +import benchmarks.common as common + + +def tlratio(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2,ignore_index=True) + stats = [] + for trials in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == trials) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == trials) + targets2 = data[alg2].targets if alg2.shape[0] > 0 else np.nan + targets4 = data[alg4].targets if alg4.shape[0] > 0 else np.nan + lures2 = data[alg2].lures if alg2.shape[0] > 0 else np.nan + lures4 = data[alg4].lures if alg4.shape[0] > 0 else np.nan + stats.append([trials, (targets2/lures2).mean(), (targets4/lures4).mean()]) + stats = pd.DataFrame(stats, columns=['trials', 'tl2', 'tl4']) #.dropna(subset=['skewness']) + + plt.style.use('ggplot') + + plt.ylim(bottom=0, top=30) + plt.scatter(stats.trials, stats.tl2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl2[idx], 1)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.tl4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl4[idx], 2)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('T:L Ratio') + plt.ylabel('T:L Ratio') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_tlratio.png', bbox_inches='tight') + plt.show() + + +def time_per_trial(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for t in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == t) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == t) + time2 = data[alg2].time.mean() * 1000 if alg2.shape[0] > 0 else np.nan + time4 = data[alg4].time.mean() * 1000 if alg4.shape[0] > 0 else np.nan + stats.append([t, time2, time4]) + stats = pd.DataFrame(stats, columns=['trials', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.trials, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time2[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time4[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2v4_time_trials.png', bbox_inches='tight') + plt.show() + +def time_profiles(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 8): + alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + time2 = data[alg2].time.mean() * 1000 + time4 = data[alg4].time.mean() * 1000 + stats.append([ni, time2, time4]) + stats = pd.DataFrame(stats, columns=['n', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.n, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.time2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + plt.scatter(stats.n, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.time4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_time_n.png', bbox_inches='tight') + plt.show() + +def skewness(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 9): + all_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + skewed_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) & data.skewed + all_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + skewed_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) & data.skewed + num_of_sequences2 = data[all_alg2].shape[0] + skewed_sequences2 = data[skewed_alg2].shape[0] + num_of_sequences4 = data[all_alg4].shape[0] + skewed_sequences4 = data[skewed_alg4].shape[0] + skewness2 = skewed_sequences2 * 100.0 / num_of_sequences2 if (num_of_sequences2>0) else 0 + skewness4 = skewed_sequences4 * 100.0 / num_of_sequences4 if (num_of_sequences4>0) else 0 + stats.append([ni, skewness2, skewness4]) + stats = pd.DataFrame(stats, columns=['n', 'skewness2', 'skewness4']) #.dropna(subset=['skewness']) + + + plt.style.use('ggplot') + plt.scatter(stats.n, stats.skewness2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.skewness2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + + plt.scatter(stats.n, stats.skewness4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.skewness4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Skewness') + plt.ylabel('Skewed Blocks (%)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_skewness.png', bbox_inches='tight') + plt.show() + +if __name__ == "__main__": + tlratio() + skewness() + time_profiles() + time_per_trial() diff --git a/tests/benchmark_skewness.py b/tests/benchmark_skewness.py new file mode 100644 index 0000000..f468b4d --- /dev/null +++ b/tests/benchmark_skewness.py @@ -0,0 +1,97 @@ +import random +import heapq +import csv + +# Common parameters +alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'] +trials_range = (10, 40) +n = 3 +sample_size = 100 + + +def to_benchmark_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [str(ralph_skewed)] + +def benchmark_nb_gm_001(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_001') + + +def benchmark_nb_gm_002(filename): + import generators.nb_gm_002 as nb_gm_002 + + generator = nb_gm_002.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + # print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_002') + + +def benchmark_nb_gm_003(filename): + import generators.nb_gm_003 as nb_gm_003 + + generator = nb_gm_003.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + print(f"sequence {i}/{sample_size}: {trials} trials") + seq = generator.generate(trials) + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_003') + + +def show_skweness_diagram(filename, choices, title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + print(filename) + data = pd.read_csv(filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) #.dropna(subset=['skewness']) + #print(stats.trials) + #plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'{title}.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + benchmark_nb_gm_003('../benchmarks/nb_gm_003_2back.csv') diff --git a/tests/common.py b/tests/common.py new file mode 100644 index 0000000..e40c0df --- /dev/null +++ b/tests/common.py @@ -0,0 +1,27 @@ + + +# Common benchmark parameters +choices = alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F'] +trials_range = (10, 65) +n = 4 +sample_size = 100 + + +def count_targets_and_lures(seq, n): + mask = 'D'*n + for index in range(n, len(seq)): + if seq[index] == seq[index - n]: + mask += 'T' + elif seq[index] in seq[index - n - 1:index - n + 1]: + mask += 'L' + else: + mask += 'D' + return mask.count('T'), mask.count('L') + + +def skewness(seq, choices): + import heapq + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return ralph_skewed diff --git a/tests/nb_gm_001_bm.py b/tests/nb_gm_001_bm.py new file mode 100644 index 0000000..54f6cb3 --- /dev/null +++ b/tests/nb_gm_001_bm.py @@ -0,0 +1,75 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq) , str(ralph_skewed)] + + +def benchmark(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets / s.trials, axis=1) + plt.scatter(data.trials, data.targets_ratio, alpha=0.2) + plt.show() + +if __name__ == '__main__': + alg = 'nb_gm_001' + fn = f'results/{alg}_{n}back.csv' + benchmark(fn) + # skewness_diagram(fn, alg) + targets_ratio_diagram(fn, alg) diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + +demo/data/ +demo/events/ +data/ +events/ +__pycache__ diff --git a/.vscode/settings.json b/.vscode/settings.json 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Generator with [Hidden] Markov Chain +# N-Back Sequence Generators -**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/src/main/scala/org/xcit/nback/markov/models/State.scala b/src/main/scala/org/xcit/nback/markov/models/State.scala deleted file mode 100644 index fbbd844..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/State.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * A Single state with a label in Markov chain - * @param label A simple string label, representing the state and node - */ -class State(val label: String) { - - /** - * Keep track of transitions from this state to other states. - */ - val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() -} diff --git a/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/src/main/scala/org/xcit/nback/markov/models/Transition.scala deleted file mode 100644 index bc20a9e..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/Transition.scala +++ /dev/null @@ -1,8 +0,0 @@ -package org.xcit.nback.markov.models - -/** - * A Single transition in Markov chain graph. It is stored in "from" node. - * @param to the ending node of the edge - * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). - */ -case class Transition(to: State, probability: Double = 0.0) diff --git a/src/test/scala/ThreeBackBenchmark.scala b/src/test/scala/ThreeBackBenchmark.scala deleted file mode 100644 index 0c7dad9..0000000 --- a/src/test/scala/ThreeBackBenchmark.scala +++ /dev/null @@ -1,7 +0,0 @@ - -/** - * TODO Benchmark 3-back simple sequence generator - */ -class ThreeBackBenchmark { - -} diff --git a/tests/benchmark_diagrams.py b/tests/benchmark_diagrams.py new file mode 100644 index 0000000..8fa448e --- /dev/null +++ b/tests/benchmark_diagrams.py @@ -0,0 +1,159 @@ +import pandas as pd +import numpy as np +from matplotlib import pyplot as plt + +import benchmarks.common as common + + +def tlratio(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2,ignore_index=True) + stats = [] + for trials in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == trials) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == trials) + targets2 = data[alg2].targets if alg2.shape[0] > 0 else np.nan + targets4 = data[alg4].targets if alg4.shape[0] > 0 else np.nan + lures2 = data[alg2].lures if alg2.shape[0] > 0 else np.nan + lures4 = data[alg4].lures if alg4.shape[0] > 0 else np.nan + stats.append([trials, (targets2/lures2).mean(), (targets4/lures4).mean()]) + stats = pd.DataFrame(stats, columns=['trials', 'tl2', 'tl4']) #.dropna(subset=['skewness']) + + plt.style.use('ggplot') + + plt.ylim(bottom=0, top=30) + plt.scatter(stats.trials, stats.tl2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl2[idx], 1)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.tl4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl4[idx], 2)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('T:L Ratio') + plt.ylabel('T:L Ratio') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_tlratio.png', bbox_inches='tight') + plt.show() + + +def time_per_trial(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for t in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == t) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == t) + time2 = data[alg2].time.mean() * 1000 if alg2.shape[0] > 0 else np.nan + time4 = data[alg4].time.mean() * 1000 if alg4.shape[0] > 0 else np.nan + stats.append([t, time2, time4]) + stats = pd.DataFrame(stats, columns=['trials', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.trials, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time2[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time4[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2v4_time_trials.png', bbox_inches='tight') + plt.show() + +def time_profiles(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 8): + alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + time2 = data[alg2].time.mean() * 1000 + time4 = data[alg4].time.mean() * 1000 + stats.append([ni, time2, time4]) + stats = pd.DataFrame(stats, columns=['n', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.n, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.time2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + plt.scatter(stats.n, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.time4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_time_n.png', bbox_inches='tight') + plt.show() + +def skewness(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 9): + all_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + skewed_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) & data.skewed + all_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + skewed_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) & data.skewed + num_of_sequences2 = data[all_alg2].shape[0] + skewed_sequences2 = data[skewed_alg2].shape[0] + num_of_sequences4 = data[all_alg4].shape[0] + skewed_sequences4 = data[skewed_alg4].shape[0] + skewness2 = skewed_sequences2 * 100.0 / num_of_sequences2 if (num_of_sequences2>0) else 0 + skewness4 = skewed_sequences4 * 100.0 / num_of_sequences4 if (num_of_sequences4>0) else 0 + stats.append([ni, skewness2, skewness4]) + stats = pd.DataFrame(stats, columns=['n', 'skewness2', 'skewness4']) #.dropna(subset=['skewness']) + + + plt.style.use('ggplot') + plt.scatter(stats.n, stats.skewness2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.skewness2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + + plt.scatter(stats.n, stats.skewness4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.skewness4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Skewness') + plt.ylabel('Skewed Blocks (%)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_skewness.png', bbox_inches='tight') + plt.show() + +if __name__ == "__main__": + tlratio() + skewness() + time_profiles() + time_per_trial() diff --git a/tests/benchmark_skewness.py b/tests/benchmark_skewness.py new file mode 100644 index 0000000..f468b4d --- /dev/null +++ b/tests/benchmark_skewness.py @@ -0,0 +1,97 @@ +import random +import heapq +import csv + +# Common parameters +alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'] +trials_range = (10, 40) +n = 3 +sample_size = 100 + + +def to_benchmark_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [str(ralph_skewed)] + +def benchmark_nb_gm_001(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_001') + + +def benchmark_nb_gm_002(filename): + import generators.nb_gm_002 as nb_gm_002 + + generator = nb_gm_002.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + # print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_002') + + +def benchmark_nb_gm_003(filename): + import generators.nb_gm_003 as nb_gm_003 + + generator = nb_gm_003.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + print(f"sequence {i}/{sample_size}: {trials} trials") + seq = generator.generate(trials) + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_003') + + +def show_skweness_diagram(filename, choices, title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + print(filename) + data = pd.read_csv(filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) #.dropna(subset=['skewness']) + #print(stats.trials) + #plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'{title}.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + benchmark_nb_gm_003('../benchmarks/nb_gm_003_2back.csv') diff --git a/tests/common.py b/tests/common.py new file mode 100644 index 0000000..e40c0df --- /dev/null +++ b/tests/common.py @@ -0,0 +1,27 @@ + + +# Common benchmark parameters +choices = alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F'] +trials_range = (10, 65) +n = 4 +sample_size = 100 + + +def count_targets_and_lures(seq, n): + mask = 'D'*n + for index in range(n, len(seq)): + if seq[index] == seq[index - n]: + mask += 'T' + elif seq[index] in seq[index - n - 1:index - n + 1]: + mask += 'L' + else: + mask += 'D' + return mask.count('T'), mask.count('L') + + +def skewness(seq, choices): + import heapq + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return ralph_skewed diff --git a/tests/nb_gm_001_bm.py b/tests/nb_gm_001_bm.py new file mode 100644 index 0000000..54f6cb3 --- /dev/null +++ b/tests/nb_gm_001_bm.py @@ -0,0 +1,75 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq) , str(ralph_skewed)] + + +def benchmark(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets / s.trials, axis=1) + plt.scatter(data.trials, data.targets_ratio, alpha=0.2) + plt.show() + +if __name__ == '__main__': + alg = 'nb_gm_001' + fn = f'results/{alg}_{n}back.csv' + benchmark(fn) + # skewness_diagram(fn, alg) + targets_ratio_diagram(fn, alg) diff --git a/tests/nb_gm_002_bm.py b/tests/nb_gm_002_bm.py new file mode 100644 index 0000000..c8af543 --- /dev/null +++ b/tests/nb_gm_002_bm.py @@ -0,0 +1,105 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq), str(ralph_skewed)] + + +def benchmark(filename): + from generators.nb_gm_002 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials, int(trials/3), 0, 0) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +import time +import numpy as np +import pandas as pd + +import benchmarks.common as common + +def profile(): + from generators.nb_gm_002 import SequenceGenerator + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, int(lures/2), int(lures/2)) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('benchmarks/results/nb_gm_002_profile.csv', sep=',', encoding='utf-8') + +if __name__ == '__main__': + alg = 'nb_gm_002' + fn = f'results/{alg}_{n}back.csv' + profile() diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + +demo/data/ +demo/events/ +data/ +events/ +__pycache__ diff --git a/.vscode/settings.json 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Generator with [Hidden] Markov Chain +# N-Back Sequence Generators -**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/src/main/scala/org/xcit/nback/markov/models/State.scala b/src/main/scala/org/xcit/nback/markov/models/State.scala deleted file mode 100644 index fbbd844..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/State.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * A Single state with a label in Markov chain - * @param label A simple string label, representing the state and node - */ -class State(val label: String) { - - /** - * Keep track of transitions from this state to other states. - */ - val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() -} diff --git a/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/src/main/scala/org/xcit/nback/markov/models/Transition.scala deleted file mode 100644 index bc20a9e..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/Transition.scala +++ /dev/null @@ -1,8 +0,0 @@ -package org.xcit.nback.markov.models - -/** - * A Single transition in Markov chain graph. It is stored in "from" node. - * @param to the ending node of the edge - * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). - */ -case class Transition(to: State, probability: Double = 0.0) diff --git a/src/test/scala/ThreeBackBenchmark.scala b/src/test/scala/ThreeBackBenchmark.scala deleted file mode 100644 index 0c7dad9..0000000 --- a/src/test/scala/ThreeBackBenchmark.scala +++ /dev/null @@ -1,7 +0,0 @@ - -/** - * TODO Benchmark 3-back simple sequence generator - */ -class ThreeBackBenchmark { - -} diff --git a/tests/benchmark_diagrams.py b/tests/benchmark_diagrams.py new file mode 100644 index 0000000..8fa448e --- /dev/null +++ b/tests/benchmark_diagrams.py @@ -0,0 +1,159 @@ +import pandas as pd +import numpy as np +from matplotlib import pyplot as plt + +import benchmarks.common as common + + +def tlratio(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2,ignore_index=True) + stats = [] + for trials in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == trials) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == trials) + targets2 = data[alg2].targets if alg2.shape[0] > 0 else np.nan + targets4 = data[alg4].targets if alg4.shape[0] > 0 else np.nan + lures2 = data[alg2].lures if alg2.shape[0] > 0 else np.nan + lures4 = data[alg4].lures if alg4.shape[0] > 0 else np.nan + stats.append([trials, (targets2/lures2).mean(), (targets4/lures4).mean()]) + stats = pd.DataFrame(stats, columns=['trials', 'tl2', 'tl4']) #.dropna(subset=['skewness']) + + plt.style.use('ggplot') + + plt.ylim(bottom=0, top=30) + plt.scatter(stats.trials, stats.tl2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl2[idx], 1)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.tl4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl4[idx], 2)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('T:L Ratio') + plt.ylabel('T:L Ratio') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_tlratio.png', bbox_inches='tight') + plt.show() + + +def time_per_trial(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for t in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == t) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == t) + time2 = data[alg2].time.mean() * 1000 if alg2.shape[0] > 0 else np.nan + time4 = data[alg4].time.mean() * 1000 if alg4.shape[0] > 0 else np.nan + stats.append([t, time2, time4]) + stats = pd.DataFrame(stats, columns=['trials', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.trials, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time2[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time4[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2v4_time_trials.png', bbox_inches='tight') + plt.show() + +def time_profiles(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 8): + alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + time2 = data[alg2].time.mean() * 1000 + time4 = data[alg4].time.mean() * 1000 + stats.append([ni, time2, time4]) + stats = pd.DataFrame(stats, columns=['n', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.n, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.time2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + plt.scatter(stats.n, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.time4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_time_n.png', bbox_inches='tight') + plt.show() + +def skewness(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 9): + all_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + skewed_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) & data.skewed + all_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + skewed_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) & data.skewed + num_of_sequences2 = data[all_alg2].shape[0] + skewed_sequences2 = data[skewed_alg2].shape[0] + num_of_sequences4 = data[all_alg4].shape[0] + skewed_sequences4 = data[skewed_alg4].shape[0] + skewness2 = skewed_sequences2 * 100.0 / num_of_sequences2 if (num_of_sequences2>0) else 0 + skewness4 = skewed_sequences4 * 100.0 / num_of_sequences4 if (num_of_sequences4>0) else 0 + stats.append([ni, skewness2, skewness4]) + stats = pd.DataFrame(stats, columns=['n', 'skewness2', 'skewness4']) #.dropna(subset=['skewness']) + + + plt.style.use('ggplot') + plt.scatter(stats.n, stats.skewness2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.skewness2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + + plt.scatter(stats.n, stats.skewness4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.skewness4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Skewness') + plt.ylabel('Skewed Blocks (%)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_skewness.png', bbox_inches='tight') + plt.show() + +if __name__ == "__main__": + tlratio() + skewness() + time_profiles() + time_per_trial() diff --git a/tests/benchmark_skewness.py b/tests/benchmark_skewness.py new file mode 100644 index 0000000..f468b4d --- /dev/null +++ b/tests/benchmark_skewness.py @@ -0,0 +1,97 @@ +import random +import heapq +import csv + +# Common parameters +alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'] +trials_range = (10, 40) +n = 3 +sample_size = 100 + + +def to_benchmark_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [str(ralph_skewed)] + +def benchmark_nb_gm_001(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_001') + + +def benchmark_nb_gm_002(filename): + import generators.nb_gm_002 as nb_gm_002 + + generator = nb_gm_002.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + # print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_002') + + +def benchmark_nb_gm_003(filename): + import generators.nb_gm_003 as nb_gm_003 + + generator = nb_gm_003.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + print(f"sequence {i}/{sample_size}: {trials} trials") + seq = generator.generate(trials) + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_003') + + +def show_skweness_diagram(filename, choices, title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + print(filename) + data = pd.read_csv(filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) #.dropna(subset=['skewness']) + #print(stats.trials) + #plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'{title}.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + benchmark_nb_gm_003('../benchmarks/nb_gm_003_2back.csv') diff --git a/tests/common.py b/tests/common.py new file mode 100644 index 0000000..e40c0df --- /dev/null +++ b/tests/common.py @@ -0,0 +1,27 @@ + + +# Common benchmark parameters +choices = alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F'] +trials_range = (10, 65) +n = 4 +sample_size = 100 + + +def count_targets_and_lures(seq, n): + mask = 'D'*n + for index in range(n, len(seq)): + if seq[index] == seq[index - n]: + mask += 'T' + elif seq[index] in seq[index - n - 1:index - n + 1]: + mask += 'L' + else: + mask += 'D' + return mask.count('T'), mask.count('L') + + +def skewness(seq, choices): + import heapq + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return ralph_skewed diff --git a/tests/nb_gm_001_bm.py b/tests/nb_gm_001_bm.py new file mode 100644 index 0000000..54f6cb3 --- /dev/null +++ b/tests/nb_gm_001_bm.py @@ -0,0 +1,75 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq) , str(ralph_skewed)] + + +def benchmark(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets / s.trials, axis=1) + plt.scatter(data.trials, data.targets_ratio, alpha=0.2) + plt.show() + +if __name__ == '__main__': + alg = 'nb_gm_001' + fn = f'results/{alg}_{n}back.csv' + benchmark(fn) + # skewness_diagram(fn, alg) + targets_ratio_diagram(fn, alg) diff --git a/tests/nb_gm_002_bm.py b/tests/nb_gm_002_bm.py new file mode 100644 index 0000000..c8af543 --- /dev/null +++ b/tests/nb_gm_002_bm.py @@ -0,0 +1,105 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq), str(ralph_skewed)] + + +def benchmark(filename): + from generators.nb_gm_002 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials, int(trials/3), 0, 0) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +import time +import numpy as np +import pandas as pd + +import benchmarks.common as common + +def profile(): + from generators.nb_gm_002 import SequenceGenerator + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, int(lures/2), int(lures/2)) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('benchmarks/results/nb_gm_002_profile.csv', sep=',', encoding='utf-8') + +if __name__ == '__main__': + alg = 'nb_gm_002' + fn = f'results/{alg}_{n}back.csv' + profile() diff --git a/tests/nb_gm_003_bm.py b/tests/nb_gm_003_bm.py new file mode 100644 index 0000000..fa6c19a --- /dev/null +++ b/tests/nb_gm_003_bm.py @@ -0,0 +1,114 @@ +import heapq +import csv +import random +import time + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq, time_per_block): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [time_per_block, ''.join(seq), str(ralph_skewed)] + + +def benchmark_skewness(filename): + from generators.nb_gm_003 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['time_per_block', 'seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + targets = trials / 3 + t = time.time() + seq = generator.generate(trials, targets) + t = time.time() - t + print(f"sequence {i}/{sample_size}: {trials} trials, took {t}s.") + writer.writerow(to_csv_row(i, seq, t)) + plot_skewness(fn, 'nb_gm_003') + + +def plot_skewness(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def plot_targets_ratio(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +def benchmark_targets_ratio(): + pass + +def benchmark_chunking(): + pass + + +def benchmark_n(): + pass + + +def plot_timing(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['time_per_trial'] = data.apply(lambda s: s.time_per_block / s.trials, axis=1) + plt.style.use('ggplot') + plt.title(f"{figure_title} - average time to generate a trial") + plt.ylabel('time (s)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.time_per_trial, alpha=0.5) + + # draw fitted curve + # import numpy as np + # p = np.poly1d(np.polyfit(data.trials, data.time_per_trial, 3)) + # plt.plot(data.trials, p(data.trials), color='red') + + plt.savefig(f'results/{figure_title}_timing.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + alg = 'nb_gm_003' + fn = f'results/{alg}_{n}back.csv' + benchmark_skewness(fn) diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + +demo/data/ 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100644 --- a/README.md +++ b/README.md @@ -1,36 +1,10 @@ -# N-Back Sequence Generator with [Hidden] Markov Chain +# N-Back Sequence Generators -**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/src/main/scala/org/xcit/nback/markov/models/State.scala b/src/main/scala/org/xcit/nback/markov/models/State.scala deleted file mode 100644 index fbbd844..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/State.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * A Single state with a label in Markov chain - * @param label A simple string label, representing the state and node - */ -class State(val label: String) { - - /** - * Keep track of transitions from this state to other states. - */ - val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() -} diff --git a/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/src/main/scala/org/xcit/nback/markov/models/Transition.scala deleted file mode 100644 index bc20a9e..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/Transition.scala +++ /dev/null @@ -1,8 +0,0 @@ -package org.xcit.nback.markov.models - -/** - * A Single transition in Markov chain graph. It is stored in "from" node. - * @param to the ending node of the edge - * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). - */ -case class Transition(to: State, probability: Double = 0.0) diff --git a/src/test/scala/ThreeBackBenchmark.scala b/src/test/scala/ThreeBackBenchmark.scala deleted file mode 100644 index 0c7dad9..0000000 --- a/src/test/scala/ThreeBackBenchmark.scala +++ /dev/null @@ -1,7 +0,0 @@ - -/** - * TODO Benchmark 3-back simple sequence generator - */ -class ThreeBackBenchmark { - -} diff --git a/tests/benchmark_diagrams.py b/tests/benchmark_diagrams.py new file mode 100644 index 0000000..8fa448e --- /dev/null +++ b/tests/benchmark_diagrams.py @@ -0,0 +1,159 @@ +import pandas as pd +import numpy as np +from matplotlib import pyplot as plt + +import benchmarks.common as common + + +def tlratio(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2,ignore_index=True) + stats = [] + for trials in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == trials) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == trials) + targets2 = data[alg2].targets if alg2.shape[0] > 0 else np.nan + targets4 = data[alg4].targets if alg4.shape[0] > 0 else np.nan + lures2 = data[alg2].lures if alg2.shape[0] > 0 else np.nan + lures4 = data[alg4].lures if alg4.shape[0] > 0 else np.nan + stats.append([trials, (targets2/lures2).mean(), (targets4/lures4).mean()]) + stats = pd.DataFrame(stats, columns=['trials', 'tl2', 'tl4']) #.dropna(subset=['skewness']) + + plt.style.use('ggplot') + + plt.ylim(bottom=0, top=30) + plt.scatter(stats.trials, stats.tl2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl2[idx], 1)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.tl4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl4[idx], 2)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('T:L Ratio') + plt.ylabel('T:L Ratio') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_tlratio.png', bbox_inches='tight') + plt.show() + + +def time_per_trial(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for t in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == t) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == t) + time2 = data[alg2].time.mean() * 1000 if alg2.shape[0] > 0 else np.nan + time4 = data[alg4].time.mean() * 1000 if alg4.shape[0] > 0 else np.nan + stats.append([t, time2, time4]) + stats = pd.DataFrame(stats, columns=['trials', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.trials, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time2[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time4[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2v4_time_trials.png', bbox_inches='tight') + plt.show() + +def time_profiles(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 8): + alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + time2 = data[alg2].time.mean() * 1000 + time4 = data[alg4].time.mean() * 1000 + stats.append([ni, time2, time4]) + stats = pd.DataFrame(stats, columns=['n', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.n, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.time2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + plt.scatter(stats.n, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.time4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_time_n.png', bbox_inches='tight') + plt.show() + +def skewness(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 9): + all_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + skewed_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) & data.skewed + all_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + skewed_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) & data.skewed + num_of_sequences2 = data[all_alg2].shape[0] + skewed_sequences2 = data[skewed_alg2].shape[0] + num_of_sequences4 = data[all_alg4].shape[0] + skewed_sequences4 = data[skewed_alg4].shape[0] + skewness2 = skewed_sequences2 * 100.0 / num_of_sequences2 if (num_of_sequences2>0) else 0 + skewness4 = skewed_sequences4 * 100.0 / num_of_sequences4 if (num_of_sequences4>0) else 0 + stats.append([ni, skewness2, skewness4]) + stats = pd.DataFrame(stats, columns=['n', 'skewness2', 'skewness4']) #.dropna(subset=['skewness']) + + + plt.style.use('ggplot') + plt.scatter(stats.n, stats.skewness2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.skewness2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + + plt.scatter(stats.n, stats.skewness4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.skewness4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Skewness') + plt.ylabel('Skewed Blocks (%)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_skewness.png', bbox_inches='tight') + plt.show() + +if __name__ == "__main__": + tlratio() + skewness() + time_profiles() + time_per_trial() diff --git a/tests/benchmark_skewness.py b/tests/benchmark_skewness.py new file mode 100644 index 0000000..f468b4d --- /dev/null +++ b/tests/benchmark_skewness.py @@ -0,0 +1,97 @@ +import random +import heapq +import csv + +# Common parameters +alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'] +trials_range = (10, 40) +n = 3 +sample_size = 100 + + +def to_benchmark_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [str(ralph_skewed)] + +def benchmark_nb_gm_001(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_001') + + +def benchmark_nb_gm_002(filename): + import generators.nb_gm_002 as nb_gm_002 + + generator = nb_gm_002.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + # print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_002') + + +def benchmark_nb_gm_003(filename): + import generators.nb_gm_003 as nb_gm_003 + + generator = nb_gm_003.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + print(f"sequence {i}/{sample_size}: {trials} trials") + seq = generator.generate(trials) + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_003') + + +def show_skweness_diagram(filename, choices, title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + print(filename) + data = pd.read_csv(filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) #.dropna(subset=['skewness']) + #print(stats.trials) + #plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'{title}.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + benchmark_nb_gm_003('../benchmarks/nb_gm_003_2back.csv') diff --git a/tests/common.py b/tests/common.py new file mode 100644 index 0000000..e40c0df --- /dev/null +++ b/tests/common.py @@ -0,0 +1,27 @@ + + +# Common benchmark parameters +choices = alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F'] +trials_range = (10, 65) +n = 4 +sample_size = 100 + + +def count_targets_and_lures(seq, n): + mask = 'D'*n + for index in range(n, len(seq)): + if seq[index] == seq[index - n]: + mask += 'T' + elif seq[index] in seq[index - n - 1:index - n + 1]: + mask += 'L' + else: + mask += 'D' + return mask.count('T'), mask.count('L') + + +def skewness(seq, choices): + import heapq + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return ralph_skewed diff --git a/tests/nb_gm_001_bm.py b/tests/nb_gm_001_bm.py new file mode 100644 index 0000000..54f6cb3 --- /dev/null +++ b/tests/nb_gm_001_bm.py @@ -0,0 +1,75 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq) , str(ralph_skewed)] + + +def benchmark(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets / s.trials, axis=1) + plt.scatter(data.trials, data.targets_ratio, alpha=0.2) + plt.show() + +if __name__ == '__main__': + alg = 'nb_gm_001' + fn = f'results/{alg}_{n}back.csv' + benchmark(fn) + # skewness_diagram(fn, alg) + targets_ratio_diagram(fn, alg) diff --git a/tests/nb_gm_002_bm.py b/tests/nb_gm_002_bm.py new file mode 100644 index 0000000..c8af543 --- /dev/null +++ b/tests/nb_gm_002_bm.py @@ -0,0 +1,105 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq), str(ralph_skewed)] + + +def benchmark(filename): + from generators.nb_gm_002 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials, int(trials/3), 0, 0) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +import time +import numpy as np +import pandas as pd + +import benchmarks.common as common + +def profile(): + from generators.nb_gm_002 import SequenceGenerator + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, int(lures/2), int(lures/2)) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('benchmarks/results/nb_gm_002_profile.csv', sep=',', encoding='utf-8') + +if __name__ == '__main__': + alg = 'nb_gm_002' + fn = f'results/{alg}_{n}back.csv' + profile() diff --git a/tests/nb_gm_003_bm.py b/tests/nb_gm_003_bm.py new file mode 100644 index 0000000..fa6c19a --- /dev/null +++ b/tests/nb_gm_003_bm.py @@ -0,0 +1,114 @@ +import heapq +import csv +import random +import time + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq, time_per_block): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [time_per_block, ''.join(seq), str(ralph_skewed)] + + +def benchmark_skewness(filename): + from generators.nb_gm_003 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['time_per_block', 'seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + targets = trials / 3 + t = time.time() + seq = generator.generate(trials, targets) + t = time.time() - t + print(f"sequence {i}/{sample_size}: {trials} trials, took {t}s.") + writer.writerow(to_csv_row(i, seq, t)) + plot_skewness(fn, 'nb_gm_003') + + +def plot_skewness(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def plot_targets_ratio(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +def benchmark_targets_ratio(): + pass + +def benchmark_chunking(): + pass + + +def benchmark_n(): + pass + + +def plot_timing(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['time_per_trial'] = data.apply(lambda s: s.time_per_block / s.trials, axis=1) + plt.style.use('ggplot') + plt.title(f"{figure_title} - average time to generate a trial") + plt.ylabel('time (s)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.time_per_trial, alpha=0.5) + + # draw fitted curve + # import numpy as np + # p = np.poly1d(np.polyfit(data.trials, data.time_per_trial, 3)) + # plt.plot(data.trials, p(data.trials), color='red') + + plt.savefig(f'results/{figure_title}_timing.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + alg = 'nb_gm_003' + fn = f'results/{alg}_{n}back.csv' + benchmark_skewness(fn) diff --git a/tests/nb_gm_004_bm.py b/tests/nb_gm_004_bm.py new file mode 100644 index 0000000..b4ad4a8 --- /dev/null +++ b/tests/nb_gm_004_bm.py @@ -0,0 +1,26 @@ +import time +import numpy as np +import pandas as pd + +import tests.common as common +from generators.nb_gm_004 import SequenceGenerator + +def run(): + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, lures) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('tests/results/nb_gm_004_profile.csv', sep=',', encoding='utf-8') diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + +demo/data/ +demo/events/ +data/ +events/ +__pycache__ diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 0000000..02e04c3 --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,10 @@ +{ + "files.exclude": { + "**/.git": true, + "**/.DS_Store": true, + "**/*.pyc": true, + "**/__pycache__": true + }, + "python.pythonPath": "/Users/morteza/miniconda3/bin/python", + "python.autoComplete.extraPaths": [".", "./tests","./generators"] +} diff --git a/Pipfile b/Pipfile new file mode 100644 index 0000000..1fe2638 --- /dev/null +++ b/Pipfile @@ -0,0 +1,20 @@ +[[source]] +name = 'pypi' +url = 'https://pypi.python.org/simple' +verify_ssl = true + +[dev-packages] +pylint = "*" + +[packages] +requests = "*" +python-constraint = "*" +Numberjack = "*" +expyriment = "*" +pygame = "==1.9.5.dev0" +scipy = "*" +matplotlib = "*" +pandas = "*" + +[requires] +python_version = "3.7" diff --git 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"==1.11.1" + } + } +} diff --git a/README.md b/README.md index a24051a..1e7491b 100644 --- a/README.md +++ b/README.md @@ -1,36 +1,10 @@ -# N-Back Sequence Generator with [Hidden] Markov Chain +# N-Back Sequence Generators -**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/src/main/scala/org/xcit/nback/markov/models/State.scala b/src/main/scala/org/xcit/nback/markov/models/State.scala deleted file mode 100644 index fbbd844..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/State.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * A Single state with a label in Markov chain - * @param label A simple string label, representing the state and node - */ -class State(val label: String) { - - /** - * Keep track of transitions from this state to other states. - */ - val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() -} diff --git a/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/src/main/scala/org/xcit/nback/markov/models/Transition.scala deleted file mode 100644 index bc20a9e..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/Transition.scala +++ /dev/null @@ -1,8 +0,0 @@ -package org.xcit.nback.markov.models - -/** - * A Single transition in Markov chain graph. It is stored in "from" node. - * @param to the ending node of the edge - * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). - */ -case class Transition(to: State, probability: Double = 0.0) diff --git a/src/test/scala/ThreeBackBenchmark.scala b/src/test/scala/ThreeBackBenchmark.scala deleted file mode 100644 index 0c7dad9..0000000 --- a/src/test/scala/ThreeBackBenchmark.scala +++ /dev/null @@ -1,7 +0,0 @@ - -/** - * TODO Benchmark 3-back simple sequence generator - */ -class ThreeBackBenchmark { - -} diff --git a/tests/benchmark_diagrams.py b/tests/benchmark_diagrams.py new file mode 100644 index 0000000..8fa448e --- /dev/null +++ b/tests/benchmark_diagrams.py @@ -0,0 +1,159 @@ +import pandas as pd +import numpy as np +from matplotlib import pyplot as plt + +import benchmarks.common as common + + +def tlratio(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2,ignore_index=True) + stats = [] + for trials in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == trials) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == trials) + targets2 = data[alg2].targets if alg2.shape[0] > 0 else np.nan + targets4 = data[alg4].targets if alg4.shape[0] > 0 else np.nan + lures2 = data[alg2].lures if alg2.shape[0] > 0 else np.nan + lures4 = data[alg4].lures if alg4.shape[0] > 0 else np.nan + stats.append([trials, (targets2/lures2).mean(), (targets4/lures4).mean()]) + stats = pd.DataFrame(stats, columns=['trials', 'tl2', 'tl4']) #.dropna(subset=['skewness']) + + plt.style.use('ggplot') + + plt.ylim(bottom=0, top=30) + plt.scatter(stats.trials, stats.tl2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl2[idx], 1)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.tl4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl4[idx], 2)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('T:L Ratio') + plt.ylabel('T:L Ratio') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_tlratio.png', bbox_inches='tight') + plt.show() + + +def time_per_trial(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for t in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == t) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == t) + time2 = data[alg2].time.mean() * 1000 if alg2.shape[0] > 0 else np.nan + time4 = data[alg4].time.mean() * 1000 if alg4.shape[0] > 0 else np.nan + stats.append([t, time2, time4]) + stats = pd.DataFrame(stats, columns=['trials', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.trials, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time2[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time4[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2v4_time_trials.png', bbox_inches='tight') + plt.show() + +def time_profiles(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 8): + alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + time2 = data[alg2].time.mean() * 1000 + time4 = data[alg4].time.mean() * 1000 + stats.append([ni, time2, time4]) + stats = pd.DataFrame(stats, columns=['n', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.n, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.time2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + plt.scatter(stats.n, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.time4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_time_n.png', bbox_inches='tight') + plt.show() + +def skewness(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 9): + all_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + skewed_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) & data.skewed + all_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + skewed_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) & data.skewed + num_of_sequences2 = data[all_alg2].shape[0] + skewed_sequences2 = data[skewed_alg2].shape[0] + num_of_sequences4 = data[all_alg4].shape[0] + skewed_sequences4 = data[skewed_alg4].shape[0] + skewness2 = skewed_sequences2 * 100.0 / num_of_sequences2 if (num_of_sequences2>0) else 0 + skewness4 = skewed_sequences4 * 100.0 / num_of_sequences4 if (num_of_sequences4>0) else 0 + stats.append([ni, skewness2, skewness4]) + stats = pd.DataFrame(stats, columns=['n', 'skewness2', 'skewness4']) #.dropna(subset=['skewness']) + + + plt.style.use('ggplot') + plt.scatter(stats.n, stats.skewness2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.skewness2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + + plt.scatter(stats.n, stats.skewness4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.skewness4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Skewness') + plt.ylabel('Skewed Blocks (%)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_skewness.png', bbox_inches='tight') + plt.show() + +if __name__ == "__main__": + tlratio() + skewness() + time_profiles() + time_per_trial() diff --git a/tests/benchmark_skewness.py b/tests/benchmark_skewness.py new file mode 100644 index 0000000..f468b4d --- /dev/null +++ b/tests/benchmark_skewness.py @@ -0,0 +1,97 @@ +import random +import heapq +import csv + +# Common parameters +alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'] +trials_range = (10, 40) +n = 3 +sample_size = 100 + + +def to_benchmark_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [str(ralph_skewed)] + +def benchmark_nb_gm_001(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_001') + + +def benchmark_nb_gm_002(filename): + import generators.nb_gm_002 as nb_gm_002 + + generator = nb_gm_002.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + # print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_002') + + +def benchmark_nb_gm_003(filename): + import generators.nb_gm_003 as nb_gm_003 + + generator = nb_gm_003.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + print(f"sequence {i}/{sample_size}: {trials} trials") + seq = generator.generate(trials) + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_003') + + +def show_skweness_diagram(filename, choices, title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + print(filename) + data = pd.read_csv(filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) #.dropna(subset=['skewness']) + #print(stats.trials) + #plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'{title}.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + benchmark_nb_gm_003('../benchmarks/nb_gm_003_2back.csv') diff --git a/tests/common.py b/tests/common.py new file mode 100644 index 0000000..e40c0df --- /dev/null +++ b/tests/common.py @@ -0,0 +1,27 @@ + + +# Common benchmark parameters +choices = alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F'] +trials_range = (10, 65) +n = 4 +sample_size = 100 + + +def count_targets_and_lures(seq, n): + mask = 'D'*n + for index in range(n, len(seq)): + if seq[index] == seq[index - n]: + mask += 'T' + elif seq[index] in seq[index - n - 1:index - n + 1]: + mask += 'L' + else: + mask += 'D' + return mask.count('T'), mask.count('L') + + +def skewness(seq, choices): + import heapq + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return ralph_skewed diff --git a/tests/nb_gm_001_bm.py b/tests/nb_gm_001_bm.py new file mode 100644 index 0000000..54f6cb3 --- /dev/null +++ b/tests/nb_gm_001_bm.py @@ -0,0 +1,75 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq) , str(ralph_skewed)] + + +def benchmark(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets / s.trials, axis=1) + plt.scatter(data.trials, data.targets_ratio, alpha=0.2) + plt.show() + +if __name__ == '__main__': + alg = 'nb_gm_001' + fn = f'results/{alg}_{n}back.csv' + benchmark(fn) + # skewness_diagram(fn, alg) + targets_ratio_diagram(fn, alg) diff --git a/tests/nb_gm_002_bm.py b/tests/nb_gm_002_bm.py new file mode 100644 index 0000000..c8af543 --- /dev/null +++ b/tests/nb_gm_002_bm.py @@ -0,0 +1,105 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq), str(ralph_skewed)] + + +def benchmark(filename): + from generators.nb_gm_002 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials, int(trials/3), 0, 0) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +import time +import numpy as np +import pandas as pd + +import benchmarks.common as common + +def profile(): + from generators.nb_gm_002 import SequenceGenerator + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, int(lures/2), int(lures/2)) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('benchmarks/results/nb_gm_002_profile.csv', sep=',', encoding='utf-8') + +if __name__ == '__main__': + alg = 'nb_gm_002' + fn = f'results/{alg}_{n}back.csv' + profile() diff --git a/tests/nb_gm_003_bm.py b/tests/nb_gm_003_bm.py new file mode 100644 index 0000000..fa6c19a --- /dev/null +++ b/tests/nb_gm_003_bm.py @@ -0,0 +1,114 @@ +import heapq +import csv +import random +import time + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq, time_per_block): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [time_per_block, ''.join(seq), str(ralph_skewed)] + + +def benchmark_skewness(filename): + from generators.nb_gm_003 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['time_per_block', 'seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + targets = trials / 3 + t = time.time() + seq = generator.generate(trials, targets) + t = time.time() - t + print(f"sequence {i}/{sample_size}: {trials} trials, took {t}s.") + writer.writerow(to_csv_row(i, seq, t)) + plot_skewness(fn, 'nb_gm_003') + + +def plot_skewness(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def plot_targets_ratio(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +def benchmark_targets_ratio(): + pass + +def benchmark_chunking(): + pass + + +def benchmark_n(): + pass + + +def plot_timing(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['time_per_trial'] = data.apply(lambda s: s.time_per_block / s.trials, axis=1) + plt.style.use('ggplot') + plt.title(f"{figure_title} - average time to generate a trial") + plt.ylabel('time (s)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.time_per_trial, alpha=0.5) + + # draw fitted curve + # import numpy as np + # p = np.poly1d(np.polyfit(data.trials, data.time_per_trial, 3)) + # plt.plot(data.trials, p(data.trials), color='red') + + plt.savefig(f'results/{figure_title}_timing.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + alg = 'nb_gm_003' + fn = f'results/{alg}_{n}back.csv' + benchmark_skewness(fn) diff --git a/tests/nb_gm_004_bm.py b/tests/nb_gm_004_bm.py new file mode 100644 index 0000000..b4ad4a8 --- /dev/null +++ b/tests/nb_gm_004_bm.py @@ -0,0 +1,26 @@ +import time +import numpy as np +import pandas as pd + +import tests.common as common +from generators.nb_gm_004 import SequenceGenerator + +def run(): + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, lures) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('tests/results/nb_gm_004_profile.csv', sep=',', encoding='utf-8') diff --git a/tests/results/2v4_time_trials.png b/tests/results/2v4_time_trials.png new file mode 100644 index 0000000..9be91b4 --- /dev/null +++ b/tests/results/2v4_time_trials.png Binary files differ diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ 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For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/src/main/scala/org/xcit/nback/markov/models/State.scala b/src/main/scala/org/xcit/nback/markov/models/State.scala deleted file mode 100644 index fbbd844..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/State.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * A Single state with a label in Markov chain - * @param label A simple string label, representing the state and node - */ -class State(val label: String) { - - /** - * Keep track of transitions from this state to other states. - */ - val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() -} diff --git a/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/src/main/scala/org/xcit/nback/markov/models/Transition.scala deleted file mode 100644 index bc20a9e..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/Transition.scala +++ /dev/null @@ -1,8 +0,0 @@ -package org.xcit.nback.markov.models - -/** - * A Single transition in Markov chain graph. It is stored in "from" node. - * @param to the ending node of the edge - * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). - */ -case class Transition(to: State, probability: Double = 0.0) diff --git a/src/test/scala/ThreeBackBenchmark.scala b/src/test/scala/ThreeBackBenchmark.scala deleted file mode 100644 index 0c7dad9..0000000 --- a/src/test/scala/ThreeBackBenchmark.scala +++ /dev/null @@ -1,7 +0,0 @@ - -/** - * TODO Benchmark 3-back simple sequence generator - */ -class ThreeBackBenchmark { - -} diff --git a/tests/benchmark_diagrams.py b/tests/benchmark_diagrams.py new file mode 100644 index 0000000..8fa448e --- /dev/null +++ b/tests/benchmark_diagrams.py @@ -0,0 +1,159 @@ +import pandas as pd +import numpy as np +from matplotlib import pyplot as plt + +import benchmarks.common as common + + +def tlratio(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2,ignore_index=True) + stats = [] + for trials in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == trials) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == trials) + targets2 = data[alg2].targets if alg2.shape[0] > 0 else np.nan + targets4 = data[alg4].targets if alg4.shape[0] > 0 else np.nan + lures2 = data[alg2].lures if alg2.shape[0] > 0 else np.nan + lures4 = data[alg4].lures if alg4.shape[0] > 0 else np.nan + stats.append([trials, (targets2/lures2).mean(), (targets4/lures4).mean()]) + stats = pd.DataFrame(stats, columns=['trials', 'tl2', 'tl4']) #.dropna(subset=['skewness']) + + plt.style.use('ggplot') + + plt.ylim(bottom=0, top=30) + plt.scatter(stats.trials, stats.tl2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl2[idx], 1)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.tl4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl4[idx], 2)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('T:L Ratio') + plt.ylabel('T:L Ratio') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_tlratio.png', bbox_inches='tight') + plt.show() + + +def time_per_trial(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for t in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == t) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == t) + time2 = data[alg2].time.mean() * 1000 if alg2.shape[0] > 0 else np.nan + time4 = data[alg4].time.mean() * 1000 if alg4.shape[0] > 0 else np.nan + stats.append([t, time2, time4]) + stats = pd.DataFrame(stats, columns=['trials', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.trials, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time2[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time4[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2v4_time_trials.png', bbox_inches='tight') + plt.show() + +def time_profiles(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 8): + alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + time2 = data[alg2].time.mean() * 1000 + time4 = data[alg4].time.mean() * 1000 + stats.append([ni, time2, time4]) + stats = pd.DataFrame(stats, columns=['n', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.n, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.time2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + plt.scatter(stats.n, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.time4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_time_n.png', bbox_inches='tight') + plt.show() + +def skewness(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 9): + all_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + skewed_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) & data.skewed + all_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + skewed_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) & data.skewed + num_of_sequences2 = data[all_alg2].shape[0] + skewed_sequences2 = data[skewed_alg2].shape[0] + num_of_sequences4 = data[all_alg4].shape[0] + skewed_sequences4 = data[skewed_alg4].shape[0] + skewness2 = skewed_sequences2 * 100.0 / num_of_sequences2 if (num_of_sequences2>0) else 0 + skewness4 = skewed_sequences4 * 100.0 / num_of_sequences4 if (num_of_sequences4>0) else 0 + stats.append([ni, skewness2, skewness4]) + stats = pd.DataFrame(stats, columns=['n', 'skewness2', 'skewness4']) #.dropna(subset=['skewness']) + + + plt.style.use('ggplot') + plt.scatter(stats.n, stats.skewness2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.skewness2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + + plt.scatter(stats.n, stats.skewness4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.skewness4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Skewness') + plt.ylabel('Skewed Blocks (%)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_skewness.png', bbox_inches='tight') + plt.show() + +if __name__ == "__main__": + tlratio() + skewness() + time_profiles() + time_per_trial() diff --git a/tests/benchmark_skewness.py b/tests/benchmark_skewness.py new file mode 100644 index 0000000..f468b4d --- /dev/null +++ b/tests/benchmark_skewness.py @@ -0,0 +1,97 @@ +import random +import heapq +import csv + +# Common parameters +alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'] +trials_range = (10, 40) +n = 3 +sample_size = 100 + + +def to_benchmark_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [str(ralph_skewed)] + +def benchmark_nb_gm_001(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_001') + + +def benchmark_nb_gm_002(filename): + import generators.nb_gm_002 as nb_gm_002 + + generator = nb_gm_002.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + # print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_002') + + +def benchmark_nb_gm_003(filename): + import generators.nb_gm_003 as nb_gm_003 + + generator = nb_gm_003.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + print(f"sequence {i}/{sample_size}: {trials} trials") + seq = generator.generate(trials) + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_003') + + +def show_skweness_diagram(filename, choices, title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + print(filename) + data = pd.read_csv(filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) #.dropna(subset=['skewness']) + #print(stats.trials) + #plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'{title}.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + benchmark_nb_gm_003('../benchmarks/nb_gm_003_2back.csv') diff --git a/tests/common.py b/tests/common.py new file mode 100644 index 0000000..e40c0df --- /dev/null +++ b/tests/common.py @@ -0,0 +1,27 @@ + + +# Common benchmark parameters +choices = alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F'] +trials_range = (10, 65) +n = 4 +sample_size = 100 + + +def count_targets_and_lures(seq, n): + mask = 'D'*n + for index in range(n, len(seq)): + if seq[index] == seq[index - n]: + mask += 'T' + elif seq[index] in seq[index - n - 1:index - n + 1]: + mask += 'L' + else: + mask += 'D' + return mask.count('T'), mask.count('L') + + +def skewness(seq, choices): + import heapq + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return ralph_skewed diff --git a/tests/nb_gm_001_bm.py b/tests/nb_gm_001_bm.py new file mode 100644 index 0000000..54f6cb3 --- /dev/null +++ b/tests/nb_gm_001_bm.py @@ -0,0 +1,75 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq) , str(ralph_skewed)] + + +def benchmark(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets / s.trials, axis=1) + plt.scatter(data.trials, data.targets_ratio, alpha=0.2) + plt.show() + +if __name__ == '__main__': + alg = 'nb_gm_001' + fn = f'results/{alg}_{n}back.csv' + benchmark(fn) + # skewness_diagram(fn, alg) + targets_ratio_diagram(fn, alg) diff --git a/tests/nb_gm_002_bm.py b/tests/nb_gm_002_bm.py new file mode 100644 index 0000000..c8af543 --- /dev/null +++ b/tests/nb_gm_002_bm.py @@ -0,0 +1,105 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq), str(ralph_skewed)] + + +def benchmark(filename): + from generators.nb_gm_002 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials, int(trials/3), 0, 0) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +import time +import numpy as np +import pandas as pd + +import benchmarks.common as common + +def profile(): + from generators.nb_gm_002 import SequenceGenerator + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, int(lures/2), int(lures/2)) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('benchmarks/results/nb_gm_002_profile.csv', sep=',', encoding='utf-8') + +if __name__ == '__main__': + alg = 'nb_gm_002' + fn = f'results/{alg}_{n}back.csv' + profile() diff --git a/tests/nb_gm_003_bm.py b/tests/nb_gm_003_bm.py new file mode 100644 index 0000000..fa6c19a --- /dev/null +++ b/tests/nb_gm_003_bm.py @@ -0,0 +1,114 @@ +import heapq +import csv +import random +import time + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq, time_per_block): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [time_per_block, ''.join(seq), str(ralph_skewed)] + + +def benchmark_skewness(filename): + from generators.nb_gm_003 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['time_per_block', 'seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + targets = trials / 3 + t = time.time() + seq = generator.generate(trials, targets) + t = time.time() - t + print(f"sequence {i}/{sample_size}: {trials} trials, took {t}s.") + writer.writerow(to_csv_row(i, seq, t)) + plot_skewness(fn, 'nb_gm_003') + + +def plot_skewness(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def plot_targets_ratio(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +def benchmark_targets_ratio(): + pass + +def benchmark_chunking(): + pass + + +def benchmark_n(): + pass + + +def plot_timing(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['time_per_trial'] = data.apply(lambda s: s.time_per_block / s.trials, axis=1) + plt.style.use('ggplot') + plt.title(f"{figure_title} - average time to generate a trial") + plt.ylabel('time (s)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.time_per_trial, alpha=0.5) + + # draw fitted curve + # import numpy as np + # p = np.poly1d(np.polyfit(data.trials, data.time_per_trial, 3)) + # plt.plot(data.trials, p(data.trials), color='red') + + plt.savefig(f'results/{figure_title}_timing.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + alg = 'nb_gm_003' + fn = f'results/{alg}_{n}back.csv' + benchmark_skewness(fn) diff --git a/tests/nb_gm_004_bm.py b/tests/nb_gm_004_bm.py new file mode 100644 index 0000000..b4ad4a8 --- /dev/null +++ b/tests/nb_gm_004_bm.py @@ -0,0 +1,26 @@ +import time +import numpy as np +import pandas as pd + +import tests.common as common +from generators.nb_gm_004 import SequenceGenerator + +def run(): + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, lures) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('tests/results/nb_gm_004_profile.csv', sep=',', encoding='utf-8') diff --git a/tests/results/2v4_time_trials.png b/tests/results/2v4_time_trials.png new file mode 100644 index 0000000..9be91b4 --- /dev/null +++ b/tests/results/2v4_time_trials.png Binary files differ diff --git a/tests/results/2vs4_skewness.png b/tests/results/2vs4_skewness.png new file mode 100644 index 0000000..a488e1f --- /dev/null +++ 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commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/src/main/scala/org/xcit/nback/markov/models/State.scala b/src/main/scala/org/xcit/nback/markov/models/State.scala deleted file mode 100644 index fbbd844..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/State.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * A Single state with a label in Markov chain - * @param label A simple string label, representing the state and node - */ -class State(val label: String) { - - /** - * Keep track of transitions from this state to other states. - */ - val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() -} diff --git a/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/src/main/scala/org/xcit/nback/markov/models/Transition.scala deleted file mode 100644 index bc20a9e..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/Transition.scala +++ /dev/null @@ -1,8 +0,0 @@ -package org.xcit.nback.markov.models - -/** - * A Single transition in Markov chain graph. It is stored in "from" node. - * @param to the ending node of the edge - * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). - */ -case class Transition(to: State, probability: Double = 0.0) diff --git a/src/test/scala/ThreeBackBenchmark.scala b/src/test/scala/ThreeBackBenchmark.scala deleted file mode 100644 index 0c7dad9..0000000 --- a/src/test/scala/ThreeBackBenchmark.scala +++ /dev/null @@ -1,7 +0,0 @@ - -/** - * TODO Benchmark 3-back simple sequence generator - */ -class ThreeBackBenchmark { - -} diff --git a/tests/benchmark_diagrams.py b/tests/benchmark_diagrams.py new file mode 100644 index 0000000..8fa448e --- /dev/null +++ b/tests/benchmark_diagrams.py @@ -0,0 +1,159 @@ +import pandas as pd +import numpy as np +from matplotlib import pyplot as plt + +import benchmarks.common as common + + +def tlratio(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2,ignore_index=True) + stats = [] + for trials in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == trials) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == trials) + targets2 = data[alg2].targets if alg2.shape[0] > 0 else np.nan + targets4 = data[alg4].targets if alg4.shape[0] > 0 else np.nan + lures2 = data[alg2].lures if alg2.shape[0] > 0 else np.nan + lures4 = data[alg4].lures if alg4.shape[0] > 0 else np.nan + stats.append([trials, (targets2/lures2).mean(), (targets4/lures4).mean()]) + stats = pd.DataFrame(stats, columns=['trials', 'tl2', 'tl4']) #.dropna(subset=['skewness']) + + plt.style.use('ggplot') + + plt.ylim(bottom=0, top=30) + plt.scatter(stats.trials, stats.tl2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl2[idx], 1)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.tl4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl4[idx], 2)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('T:L Ratio') + plt.ylabel('T:L Ratio') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_tlratio.png', bbox_inches='tight') + plt.show() + + +def time_per_trial(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for t in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == t) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == t) + time2 = data[alg2].time.mean() * 1000 if alg2.shape[0] > 0 else np.nan + time4 = data[alg4].time.mean() * 1000 if alg4.shape[0] > 0 else np.nan + stats.append([t, time2, time4]) + stats = pd.DataFrame(stats, columns=['trials', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.trials, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time2[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time4[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2v4_time_trials.png', bbox_inches='tight') + plt.show() + +def time_profiles(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 8): + alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + time2 = data[alg2].time.mean() * 1000 + time4 = data[alg4].time.mean() * 1000 + stats.append([ni, time2, time4]) + stats = pd.DataFrame(stats, columns=['n', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.n, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.time2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + plt.scatter(stats.n, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.time4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_time_n.png', bbox_inches='tight') + plt.show() + +def skewness(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 9): + all_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + skewed_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) & data.skewed + all_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + skewed_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) & data.skewed + num_of_sequences2 = data[all_alg2].shape[0] + skewed_sequences2 = data[skewed_alg2].shape[0] + num_of_sequences4 = data[all_alg4].shape[0] + skewed_sequences4 = data[skewed_alg4].shape[0] + skewness2 = skewed_sequences2 * 100.0 / num_of_sequences2 if (num_of_sequences2>0) else 0 + skewness4 = skewed_sequences4 * 100.0 / num_of_sequences4 if (num_of_sequences4>0) else 0 + stats.append([ni, skewness2, skewness4]) + stats = pd.DataFrame(stats, columns=['n', 'skewness2', 'skewness4']) #.dropna(subset=['skewness']) + + + plt.style.use('ggplot') + plt.scatter(stats.n, stats.skewness2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.skewness2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + + plt.scatter(stats.n, stats.skewness4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.skewness4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Skewness') + plt.ylabel('Skewed Blocks (%)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_skewness.png', bbox_inches='tight') + plt.show() + +if __name__ == "__main__": + tlratio() + skewness() + time_profiles() + time_per_trial() diff --git a/tests/benchmark_skewness.py b/tests/benchmark_skewness.py new file mode 100644 index 0000000..f468b4d --- /dev/null +++ b/tests/benchmark_skewness.py @@ -0,0 +1,97 @@ +import random +import heapq +import csv + +# Common parameters +alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'] +trials_range = (10, 40) +n = 3 +sample_size = 100 + + +def to_benchmark_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [str(ralph_skewed)] + +def benchmark_nb_gm_001(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_001') + + +def benchmark_nb_gm_002(filename): + import generators.nb_gm_002 as nb_gm_002 + + generator = nb_gm_002.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + # print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_002') + + +def benchmark_nb_gm_003(filename): + import generators.nb_gm_003 as nb_gm_003 + + generator = nb_gm_003.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + print(f"sequence {i}/{sample_size}: {trials} trials") + seq = generator.generate(trials) + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_003') + + +def show_skweness_diagram(filename, choices, title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + print(filename) + data = pd.read_csv(filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) #.dropna(subset=['skewness']) + #print(stats.trials) + #plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'{title}.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + benchmark_nb_gm_003('../benchmarks/nb_gm_003_2back.csv') diff --git a/tests/common.py b/tests/common.py new file mode 100644 index 0000000..e40c0df --- /dev/null +++ b/tests/common.py @@ -0,0 +1,27 @@ + + +# Common benchmark parameters +choices = alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F'] +trials_range = (10, 65) +n = 4 +sample_size = 100 + + +def count_targets_and_lures(seq, n): + mask = 'D'*n + for index in range(n, len(seq)): + if seq[index] == seq[index - n]: + mask += 'T' + elif seq[index] in seq[index - n - 1:index - n + 1]: + mask += 'L' + else: + mask += 'D' + return mask.count('T'), mask.count('L') + + +def skewness(seq, choices): + import heapq + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return ralph_skewed diff --git a/tests/nb_gm_001_bm.py b/tests/nb_gm_001_bm.py new file mode 100644 index 0000000..54f6cb3 --- /dev/null +++ b/tests/nb_gm_001_bm.py @@ -0,0 +1,75 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq) , str(ralph_skewed)] + + +def benchmark(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets / s.trials, axis=1) + plt.scatter(data.trials, data.targets_ratio, alpha=0.2) + plt.show() + +if __name__ == '__main__': + alg = 'nb_gm_001' + fn = f'results/{alg}_{n}back.csv' + benchmark(fn) + # skewness_diagram(fn, alg) + targets_ratio_diagram(fn, alg) diff --git a/tests/nb_gm_002_bm.py b/tests/nb_gm_002_bm.py new file mode 100644 index 0000000..c8af543 --- /dev/null +++ b/tests/nb_gm_002_bm.py @@ -0,0 +1,105 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq), str(ralph_skewed)] + + +def benchmark(filename): + from generators.nb_gm_002 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials, int(trials/3), 0, 0) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +import time +import numpy as np +import pandas as pd + +import benchmarks.common as common + +def profile(): + from generators.nb_gm_002 import SequenceGenerator + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, int(lures/2), int(lures/2)) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('benchmarks/results/nb_gm_002_profile.csv', sep=',', encoding='utf-8') + +if __name__ == '__main__': + alg = 'nb_gm_002' + fn = f'results/{alg}_{n}back.csv' + profile() diff --git a/tests/nb_gm_003_bm.py b/tests/nb_gm_003_bm.py new file mode 100644 index 0000000..fa6c19a --- /dev/null +++ b/tests/nb_gm_003_bm.py @@ -0,0 +1,114 @@ +import heapq +import csv +import random +import time + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq, time_per_block): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [time_per_block, ''.join(seq), str(ralph_skewed)] + + +def benchmark_skewness(filename): + from generators.nb_gm_003 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['time_per_block', 'seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + targets = trials / 3 + t = time.time() + seq = generator.generate(trials, targets) + t = time.time() - t + print(f"sequence {i}/{sample_size}: {trials} trials, took {t}s.") + writer.writerow(to_csv_row(i, seq, t)) + plot_skewness(fn, 'nb_gm_003') + + +def plot_skewness(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def plot_targets_ratio(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +def benchmark_targets_ratio(): + pass + +def benchmark_chunking(): + pass + + +def benchmark_n(): + pass + + +def plot_timing(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['time_per_trial'] = data.apply(lambda s: s.time_per_block / s.trials, axis=1) + plt.style.use('ggplot') + plt.title(f"{figure_title} - average time to generate a trial") + plt.ylabel('time (s)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.time_per_trial, alpha=0.5) + + # draw fitted curve + # import numpy as np + # p = np.poly1d(np.polyfit(data.trials, data.time_per_trial, 3)) + # plt.plot(data.trials, p(data.trials), color='red') + + plt.savefig(f'results/{figure_title}_timing.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + alg = 'nb_gm_003' + fn = f'results/{alg}_{n}back.csv' + benchmark_skewness(fn) diff --git a/tests/nb_gm_004_bm.py b/tests/nb_gm_004_bm.py new file mode 100644 index 0000000..b4ad4a8 --- /dev/null +++ b/tests/nb_gm_004_bm.py @@ -0,0 +1,26 @@ +import time +import numpy as np +import pandas as pd + +import tests.common as common +from generators.nb_gm_004 import SequenceGenerator + +def run(): + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, lures) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('tests/results/nb_gm_004_profile.csv', sep=',', encoding='utf-8') diff --git a/tests/results/2v4_time_trials.png b/tests/results/2v4_time_trials.png new file mode 100644 index 0000000..9be91b4 --- /dev/null +++ b/tests/results/2v4_time_trials.png Binary files differ diff --git a/tests/results/2vs4_skewness.png b/tests/results/2vs4_skewness.png new file mode 100644 index 0000000..a488e1f --- /dev/null +++ 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various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/src/main/scala/org/xcit/nback/markov/models/State.scala b/src/main/scala/org/xcit/nback/markov/models/State.scala deleted file mode 100644 index fbbd844..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/State.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * A Single state with a label in Markov chain - * @param label A simple string label, representing the state and node - */ -class State(val label: String) { - - /** - * Keep track of transitions from this state to other states. - */ - val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() -} diff --git a/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/src/main/scala/org/xcit/nback/markov/models/Transition.scala deleted file mode 100644 index bc20a9e..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/Transition.scala +++ /dev/null @@ -1,8 +0,0 @@ -package org.xcit.nback.markov.models - -/** - * A Single transition in Markov chain graph. It is stored in "from" node. - * @param to the ending node of the edge - * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). - */ -case class Transition(to: State, probability: Double = 0.0) diff --git a/src/test/scala/ThreeBackBenchmark.scala b/src/test/scala/ThreeBackBenchmark.scala deleted file mode 100644 index 0c7dad9..0000000 --- a/src/test/scala/ThreeBackBenchmark.scala +++ /dev/null @@ -1,7 +0,0 @@ - -/** - * TODO Benchmark 3-back simple sequence generator - */ -class ThreeBackBenchmark { - -} diff --git a/tests/benchmark_diagrams.py b/tests/benchmark_diagrams.py new file mode 100644 index 0000000..8fa448e --- /dev/null +++ b/tests/benchmark_diagrams.py @@ -0,0 +1,159 @@ +import pandas as pd +import numpy as np +from matplotlib import pyplot as plt + +import benchmarks.common as common + + +def tlratio(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2,ignore_index=True) + stats = [] + for trials in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == trials) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == trials) + targets2 = data[alg2].targets if alg2.shape[0] > 0 else np.nan + targets4 = data[alg4].targets if alg4.shape[0] > 0 else np.nan + lures2 = data[alg2].lures if alg2.shape[0] > 0 else np.nan + lures4 = data[alg4].lures if alg4.shape[0] > 0 else np.nan + stats.append([trials, (targets2/lures2).mean(), (targets4/lures4).mean()]) + stats = pd.DataFrame(stats, columns=['trials', 'tl2', 'tl4']) #.dropna(subset=['skewness']) + + plt.style.use('ggplot') + + plt.ylim(bottom=0, top=30) + plt.scatter(stats.trials, stats.tl2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl2[idx], 1)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.tl4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl4[idx], 2)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('T:L Ratio') + plt.ylabel('T:L Ratio') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_tlratio.png', bbox_inches='tight') + plt.show() + + +def time_per_trial(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for t in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == t) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == t) + time2 = data[alg2].time.mean() * 1000 if alg2.shape[0] > 0 else np.nan + time4 = data[alg4].time.mean() * 1000 if alg4.shape[0] > 0 else np.nan + stats.append([t, time2, time4]) + stats = pd.DataFrame(stats, columns=['trials', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.trials, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time2[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time4[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2v4_time_trials.png', bbox_inches='tight') + plt.show() + +def time_profiles(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 8): + alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + time2 = data[alg2].time.mean() * 1000 + time4 = data[alg4].time.mean() * 1000 + stats.append([ni, time2, time4]) + stats = pd.DataFrame(stats, columns=['n', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.n, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.time2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + plt.scatter(stats.n, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.time4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_time_n.png', bbox_inches='tight') + plt.show() + +def skewness(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 9): + all_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + skewed_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) & data.skewed + all_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + skewed_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) & data.skewed + num_of_sequences2 = data[all_alg2].shape[0] + skewed_sequences2 = data[skewed_alg2].shape[0] + num_of_sequences4 = data[all_alg4].shape[0] + skewed_sequences4 = data[skewed_alg4].shape[0] + skewness2 = skewed_sequences2 * 100.0 / num_of_sequences2 if (num_of_sequences2>0) else 0 + skewness4 = skewed_sequences4 * 100.0 / num_of_sequences4 if (num_of_sequences4>0) else 0 + stats.append([ni, skewness2, skewness4]) + stats = pd.DataFrame(stats, columns=['n', 'skewness2', 'skewness4']) #.dropna(subset=['skewness']) + + + plt.style.use('ggplot') + plt.scatter(stats.n, stats.skewness2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.skewness2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + + plt.scatter(stats.n, stats.skewness4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.skewness4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Skewness') + plt.ylabel('Skewed Blocks (%)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_skewness.png', bbox_inches='tight') + plt.show() + +if __name__ == "__main__": + tlratio() + skewness() + time_profiles() + time_per_trial() diff --git a/tests/benchmark_skewness.py b/tests/benchmark_skewness.py new file mode 100644 index 0000000..f468b4d --- /dev/null +++ b/tests/benchmark_skewness.py @@ -0,0 +1,97 @@ +import random +import heapq +import csv + +# Common parameters +alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'] +trials_range = (10, 40) +n = 3 +sample_size = 100 + + +def to_benchmark_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [str(ralph_skewed)] + +def benchmark_nb_gm_001(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_001') + + +def benchmark_nb_gm_002(filename): + import generators.nb_gm_002 as nb_gm_002 + + generator = nb_gm_002.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + # print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_002') + + +def benchmark_nb_gm_003(filename): + import generators.nb_gm_003 as nb_gm_003 + + generator = nb_gm_003.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + print(f"sequence {i}/{sample_size}: {trials} trials") + seq = generator.generate(trials) + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_003') + + +def show_skweness_diagram(filename, choices, title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + print(filename) + data = pd.read_csv(filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) #.dropna(subset=['skewness']) + #print(stats.trials) + #plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'{title}.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + benchmark_nb_gm_003('../benchmarks/nb_gm_003_2back.csv') diff --git a/tests/common.py b/tests/common.py new file mode 100644 index 0000000..e40c0df --- /dev/null +++ b/tests/common.py @@ -0,0 +1,27 @@ + + +# Common benchmark parameters +choices = alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F'] +trials_range = (10, 65) +n = 4 +sample_size = 100 + + +def count_targets_and_lures(seq, n): + mask = 'D'*n + for index in range(n, len(seq)): + if seq[index] == seq[index - n]: + mask += 'T' + elif seq[index] in seq[index - n - 1:index - n + 1]: + mask += 'L' + else: + mask += 'D' + return mask.count('T'), mask.count('L') + + +def skewness(seq, choices): + import heapq + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return ralph_skewed diff --git a/tests/nb_gm_001_bm.py b/tests/nb_gm_001_bm.py new file mode 100644 index 0000000..54f6cb3 --- /dev/null +++ b/tests/nb_gm_001_bm.py @@ -0,0 +1,75 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq) , str(ralph_skewed)] + + +def benchmark(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets / s.trials, axis=1) + plt.scatter(data.trials, data.targets_ratio, alpha=0.2) + plt.show() + +if __name__ == '__main__': + alg = 'nb_gm_001' + fn = f'results/{alg}_{n}back.csv' + benchmark(fn) + # skewness_diagram(fn, alg) + targets_ratio_diagram(fn, alg) diff --git a/tests/nb_gm_002_bm.py b/tests/nb_gm_002_bm.py new file mode 100644 index 0000000..c8af543 --- /dev/null +++ b/tests/nb_gm_002_bm.py @@ -0,0 +1,105 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq), str(ralph_skewed)] + + +def benchmark(filename): + from generators.nb_gm_002 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials, int(trials/3), 0, 0) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +import time +import numpy as np +import pandas as pd + +import benchmarks.common as common + +def profile(): + from generators.nb_gm_002 import SequenceGenerator + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, int(lures/2), int(lures/2)) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('benchmarks/results/nb_gm_002_profile.csv', sep=',', encoding='utf-8') + +if __name__ == '__main__': + alg = 'nb_gm_002' + fn = f'results/{alg}_{n}back.csv' + profile() diff --git a/tests/nb_gm_003_bm.py b/tests/nb_gm_003_bm.py new file mode 100644 index 0000000..fa6c19a --- /dev/null +++ b/tests/nb_gm_003_bm.py @@ -0,0 +1,114 @@ +import heapq +import csv +import random +import time + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq, time_per_block): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [time_per_block, ''.join(seq), str(ralph_skewed)] + + +def benchmark_skewness(filename): + from generators.nb_gm_003 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['time_per_block', 'seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + targets = trials / 3 + t = time.time() + seq = generator.generate(trials, targets) + t = time.time() - t + print(f"sequence {i}/{sample_size}: {trials} trials, took {t}s.") + writer.writerow(to_csv_row(i, seq, t)) + plot_skewness(fn, 'nb_gm_003') + + +def plot_skewness(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def plot_targets_ratio(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +def benchmark_targets_ratio(): + pass + +def benchmark_chunking(): + pass + + +def benchmark_n(): + pass + + +def plot_timing(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['time_per_trial'] = data.apply(lambda s: s.time_per_block / s.trials, axis=1) + plt.style.use('ggplot') + plt.title(f"{figure_title} - average time to generate a trial") + plt.ylabel('time (s)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.time_per_trial, alpha=0.5) + + # draw fitted curve + # import numpy as np + # p = np.poly1d(np.polyfit(data.trials, data.time_per_trial, 3)) + # plt.plot(data.trials, p(data.trials), color='red') + + plt.savefig(f'results/{figure_title}_timing.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + alg = 'nb_gm_003' + fn = f'results/{alg}_{n}back.csv' + benchmark_skewness(fn) diff --git a/tests/nb_gm_004_bm.py b/tests/nb_gm_004_bm.py new file mode 100644 index 0000000..b4ad4a8 --- /dev/null +++ b/tests/nb_gm_004_bm.py @@ -0,0 +1,26 @@ +import time +import numpy as np +import pandas as pd + +import tests.common as common +from generators.nb_gm_004 import SequenceGenerator + +def run(): + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, lures) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('tests/results/nb_gm_004_profile.csv', sep=',', encoding='utf-8') diff --git a/tests/results/2v4_time_trials.png b/tests/results/2v4_time_trials.png new file mode 100644 index 0000000..9be91b4 --- /dev/null +++ b/tests/results/2v4_time_trials.png Binary files differ diff --git a/tests/results/2vs4_skewness.png b/tests/results/2vs4_skewness.png new file mode 100644 index 0000000..a488e1f --- /dev/null +++ b/tests/results/2vs4_skewness.png Binary files differ diff --git a/tests/results/2vs4_time_n.png b/tests/results/2vs4_time_n.png new file mode 100644 index 0000000..d022ed0 --- /dev/null +++ b/tests/results/2vs4_time_n.png Binary files differ diff --git a/tests/results/2vs4_tlratio.png b/tests/results/2vs4_tlratio.png new file mode 100644 index 0000000..b76f296 --- /dev/null +++ b/tests/results/2vs4_tlratio.png Binary files differ diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..5345e9e --- /dev/null +++ b/.editorconfig @@ -0,0 +1,6 @@ +[*] +charset=utf-8 +end_of_line=lf +insert_final_newline=true +indent_style=space +indent_size=4 diff --git a/.gitignore b/.gitignore index 6a4df1c..2265696 100644 --- a/.gitignore +++ b/.gitignore @@ -5,4 +5,10 @@ *.iws .DS_Store -tmp/ \ No newline at end of file +tmp/ + +demo/data/ +demo/events/ +data/ +events/ +__pycache__ diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 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Generator with [Hidden] Markov Chain +# N-Back Sequence Generators -**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/src/main/scala/org/xcit/nback/markov/models/State.scala b/src/main/scala/org/xcit/nback/markov/models/State.scala deleted file mode 100644 index fbbd844..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/State.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * A Single state with a label in Markov chain - * @param label A simple string label, representing the state and node - */ -class State(val label: String) { - - /** - * Keep track of transitions from this state to other states. - */ - val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() -} diff --git a/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/src/main/scala/org/xcit/nback/markov/models/Transition.scala deleted file mode 100644 index bc20a9e..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/Transition.scala +++ /dev/null @@ -1,8 +0,0 @@ -package org.xcit.nback.markov.models - -/** - * A Single transition in Markov chain graph. It is stored in "from" node. - * @param to the ending node of the edge - * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). - */ -case class Transition(to: State, probability: Double = 0.0) diff --git a/src/test/scala/ThreeBackBenchmark.scala b/src/test/scala/ThreeBackBenchmark.scala deleted file mode 100644 index 0c7dad9..0000000 --- a/src/test/scala/ThreeBackBenchmark.scala +++ /dev/null @@ -1,7 +0,0 @@ - -/** - * TODO Benchmark 3-back simple sequence generator - */ -class ThreeBackBenchmark { - -} diff --git a/tests/benchmark_diagrams.py b/tests/benchmark_diagrams.py new file mode 100644 index 0000000..8fa448e --- /dev/null +++ b/tests/benchmark_diagrams.py @@ -0,0 +1,159 @@ +import pandas as pd +import numpy as np +from matplotlib import pyplot as plt + +import benchmarks.common as common + + +def tlratio(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2,ignore_index=True) + stats = [] + for trials in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == trials) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == trials) + targets2 = data[alg2].targets if alg2.shape[0] > 0 else np.nan + targets4 = data[alg4].targets if alg4.shape[0] > 0 else np.nan + lures2 = data[alg2].lures if alg2.shape[0] > 0 else np.nan + lures4 = data[alg4].lures if alg4.shape[0] > 0 else np.nan + stats.append([trials, (targets2/lures2).mean(), (targets4/lures4).mean()]) + stats = pd.DataFrame(stats, columns=['trials', 'tl2', 'tl4']) #.dropna(subset=['skewness']) + + plt.style.use('ggplot') + + plt.ylim(bottom=0, top=30) + plt.scatter(stats.trials, stats.tl2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl2[idx], 1)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.tl4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl4[idx], 2)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('T:L Ratio') + plt.ylabel('T:L Ratio') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_tlratio.png', bbox_inches='tight') + plt.show() + + +def time_per_trial(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for t in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == t) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == t) + time2 = data[alg2].time.mean() * 1000 if alg2.shape[0] > 0 else np.nan + time4 = data[alg4].time.mean() * 1000 if alg4.shape[0] > 0 else np.nan + stats.append([t, time2, time4]) + stats = pd.DataFrame(stats, columns=['trials', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.trials, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time2[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time4[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2v4_time_trials.png', bbox_inches='tight') + plt.show() + +def time_profiles(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 8): + alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + time2 = data[alg2].time.mean() * 1000 + time4 = data[alg4].time.mean() * 1000 + stats.append([ni, time2, time4]) + stats = pd.DataFrame(stats, columns=['n', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.n, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.time2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + plt.scatter(stats.n, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.time4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_time_n.png', bbox_inches='tight') + plt.show() + +def skewness(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 9): + all_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + skewed_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) & data.skewed + all_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + skewed_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) & data.skewed + num_of_sequences2 = data[all_alg2].shape[0] + skewed_sequences2 = data[skewed_alg2].shape[0] + num_of_sequences4 = data[all_alg4].shape[0] + skewed_sequences4 = data[skewed_alg4].shape[0] + skewness2 = skewed_sequences2 * 100.0 / num_of_sequences2 if (num_of_sequences2>0) else 0 + skewness4 = skewed_sequences4 * 100.0 / num_of_sequences4 if (num_of_sequences4>0) else 0 + stats.append([ni, skewness2, skewness4]) + stats = pd.DataFrame(stats, columns=['n', 'skewness2', 'skewness4']) #.dropna(subset=['skewness']) + + + plt.style.use('ggplot') + plt.scatter(stats.n, stats.skewness2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.skewness2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + + plt.scatter(stats.n, stats.skewness4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.skewness4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Skewness') + plt.ylabel('Skewed Blocks (%)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_skewness.png', bbox_inches='tight') + plt.show() + +if __name__ == "__main__": + tlratio() + skewness() + time_profiles() + time_per_trial() diff --git a/tests/benchmark_skewness.py b/tests/benchmark_skewness.py new file mode 100644 index 0000000..f468b4d --- /dev/null +++ b/tests/benchmark_skewness.py @@ -0,0 +1,97 @@ +import random +import heapq +import csv + +# Common parameters +alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'] +trials_range = (10, 40) +n = 3 +sample_size = 100 + + +def to_benchmark_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [str(ralph_skewed)] + +def benchmark_nb_gm_001(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_001') + + +def benchmark_nb_gm_002(filename): + import generators.nb_gm_002 as nb_gm_002 + + generator = nb_gm_002.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + # print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_002') + + +def benchmark_nb_gm_003(filename): + import generators.nb_gm_003 as nb_gm_003 + + generator = nb_gm_003.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + print(f"sequence {i}/{sample_size}: {trials} trials") + seq = generator.generate(trials) + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_003') + + +def show_skweness_diagram(filename, choices, title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + print(filename) + data = pd.read_csv(filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) #.dropna(subset=['skewness']) + #print(stats.trials) + #plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'{title}.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + benchmark_nb_gm_003('../benchmarks/nb_gm_003_2back.csv') diff --git a/tests/common.py b/tests/common.py new file mode 100644 index 0000000..e40c0df --- /dev/null +++ b/tests/common.py @@ -0,0 +1,27 @@ + + +# Common benchmark parameters +choices = alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F'] +trials_range = (10, 65) +n = 4 +sample_size = 100 + + +def count_targets_and_lures(seq, n): + mask = 'D'*n + for index in range(n, len(seq)): + if seq[index] == seq[index - n]: + mask += 'T' + elif seq[index] in seq[index - n - 1:index - n + 1]: + mask += 'L' + else: + mask += 'D' + return mask.count('T'), mask.count('L') + + +def skewness(seq, choices): + import heapq + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return ralph_skewed diff --git a/tests/nb_gm_001_bm.py b/tests/nb_gm_001_bm.py new file mode 100644 index 0000000..54f6cb3 --- /dev/null +++ b/tests/nb_gm_001_bm.py @@ -0,0 +1,75 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq) , str(ralph_skewed)] + + +def benchmark(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets / s.trials, axis=1) + plt.scatter(data.trials, data.targets_ratio, alpha=0.2) + plt.show() + +if __name__ == '__main__': + alg = 'nb_gm_001' + fn = f'results/{alg}_{n}back.csv' + benchmark(fn) + # skewness_diagram(fn, alg) + targets_ratio_diagram(fn, alg) diff --git a/tests/nb_gm_002_bm.py b/tests/nb_gm_002_bm.py new file mode 100644 index 0000000..c8af543 --- /dev/null +++ b/tests/nb_gm_002_bm.py @@ -0,0 +1,105 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq), str(ralph_skewed)] + + +def benchmark(filename): + from generators.nb_gm_002 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials, int(trials/3), 0, 0) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +import time +import numpy as np +import pandas as pd + +import benchmarks.common as common + +def profile(): + from generators.nb_gm_002 import SequenceGenerator + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, int(lures/2), int(lures/2)) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('benchmarks/results/nb_gm_002_profile.csv', sep=',', encoding='utf-8') + +if __name__ == '__main__': + alg = 'nb_gm_002' + fn = f'results/{alg}_{n}back.csv' + profile() diff --git a/tests/nb_gm_003_bm.py b/tests/nb_gm_003_bm.py new file mode 100644 index 0000000..fa6c19a --- /dev/null +++ b/tests/nb_gm_003_bm.py @@ -0,0 +1,114 @@ +import heapq +import csv +import random +import time + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq, time_per_block): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [time_per_block, ''.join(seq), str(ralph_skewed)] + + +def benchmark_skewness(filename): + from generators.nb_gm_003 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['time_per_block', 'seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + targets = trials / 3 + t = time.time() + seq = generator.generate(trials, targets) + t = time.time() - t + print(f"sequence {i}/{sample_size}: {trials} trials, took {t}s.") + writer.writerow(to_csv_row(i, seq, t)) + plot_skewness(fn, 'nb_gm_003') + + +def plot_skewness(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def plot_targets_ratio(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +def benchmark_targets_ratio(): + pass + +def benchmark_chunking(): + pass + + +def benchmark_n(): + pass + + +def plot_timing(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['time_per_trial'] = data.apply(lambda s: s.time_per_block / s.trials, axis=1) + plt.style.use('ggplot') + plt.title(f"{figure_title} - average time to generate a trial") + plt.ylabel('time (s)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.time_per_trial, alpha=0.5) + + # draw fitted curve + # import numpy as np + # p = np.poly1d(np.polyfit(data.trials, data.time_per_trial, 3)) + # plt.plot(data.trials, p(data.trials), color='red') + + plt.savefig(f'results/{figure_title}_timing.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + alg = 'nb_gm_003' + fn = f'results/{alg}_{n}back.csv' + benchmark_skewness(fn) diff --git a/tests/nb_gm_004_bm.py b/tests/nb_gm_004_bm.py new file mode 100644 index 0000000..b4ad4a8 --- /dev/null +++ b/tests/nb_gm_004_bm.py @@ -0,0 +1,26 @@ +import time +import numpy as np +import pandas as pd + +import tests.common as common +from generators.nb_gm_004 import SequenceGenerator + +def run(): + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, lures) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('tests/results/nb_gm_004_profile.csv', sep=',', encoding='utf-8') diff --git a/tests/results/2v4_time_trials.png b/tests/results/2v4_time_trials.png new file mode 100644 index 0000000..9be91b4 --- /dev/null +++ b/tests/results/2v4_time_trials.png Binary files differ diff --git a/tests/results/2vs4_skewness.png b/tests/results/2vs4_skewness.png new file mode 100644 index 0000000..a488e1f --- /dev/null +++ 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+210,87.0,0.0,0.0,88.0,1.0,0.0,0.0,0.0,EDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +211,0.0,0.0,12.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCC,True +212,0.0,0.0,0.0,66.0,0.0,65.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +213,1.0,0.0,0.0,0.0,0.0,21.0,22.0,0.0,AGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFG,True +214,74.0,73.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +215,0.0,5.0,0.0,0.0,6.0,0.0,0.0,1.0,HEBEBEBEBEBE,True +216,0.0,1.0,0.0,0.0,0.0,53.0,0.0,54.0,BHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +217,70.0,0.0,0.0,0.0,0.0,70.0,0.0,0.0,AFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +218,0.0,0.0,0.0,0.0,0.0,0.0,36.0,35.0,GGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +219,0.0,90.0,90.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +220,0.0,0.0,0.0,0.0,0.0,0.0,37.0,38.0,HHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +221,0.0,0.0,44.0,0.0,0.0,1.0,44.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +222,0.0,0.0,0.0,67.0,67.0,0.0,0.0,1.0,HDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True 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+409,0.0,0.0,72.0,1.0,0.0,0.0,72.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +410,55.0,0.0,1.0,0.0,0.0,0.0,55.0,0.0,CAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +411,0.0,59.0,0.0,0.0,0.0,60.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +412,61.0,0.0,0.0,61.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +413,0.0,1.0,0.0,75.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +414,0.0,53.0,0.0,0.0,0.0,0.0,52.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +415,0.0,0.0,16.0,0.0,1.0,0.0,0.0,15.0,ECHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +416,0.0,0.0,0.0,39.0,0.0,0.0,0.0,38.0,DHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +417,96.0,0.0,1.0,95.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +418,28.0,0.0,1.0,27.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +419,0.0,1.0,92.0,92.0,0.0,0.0,0.0,0.0,BCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +420,1.0,0.0,20.0,0.0,20.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECE,True +421,0.0,90.0,0.0,0.0,0.0,0.0,89.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +422,10.0,0.0,0.0,0.0,0.0,1.0,11.0,0.0,FGAGAGAGAGAGAGAGAGAGAG,True +423,0.0,0.0,0.0,74.0,73.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +424,0.0,0.0,127.0,0.0,0.0,0.0,1.0,0.0,GCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +425,1.0,9.0,0.0,0.0,0.0,9.0,0.0,0.0,AFBFBFBFBFBFBFBFBFB,True +426,0.0,0.0,84.0,0.0,0.0,0.0,0.0,84.0,HCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +427,33.0,0.0,0.0,34.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +428,1.0,30.0,0.0,30.0,0.0,0.0,0.0,0.0,ABDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +429,0.0,0.0,67.0,0.0,1.0,67.0,0.0,0.0,EFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +430,62.0,0.0,0.0,63.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +431,1.0,9.0,9.0,0.0,0.0,0.0,0.0,0.0,ABCBCBCBCBCBCBCBCBC,True +432,15.0,0.0,0.0,0.0,0.0,0.0,14.0,0.0,AAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +433,0.0,1.0,0.0,65.0,66.0,0.0,0.0,0.0,BEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +434,0.0,160.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +435,0.0,0.0,1.0,0.0,42.0,42.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +436,0.0,0.0,55.0,0.0,55.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +437,0.0,0.0,0.0,1.0,0.0,73.0,0.0,73.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +438,79.0,0.0,0.0,0.0,78.0,0.0,0.0,0.0,AAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +439,0.0,0.0,67.0,0.0,0.0,0.0,66.0,1.0,HCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +440,0.0,0.0,77.0,0.0,0.0,1.0,0.0,76.0,FCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +441,0.0,0.0,0.0,0.0,153.0,0.0,0.0,1.0,HEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +442,0.0,88.0,88.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +443,0.0,0.0,0.0,20.0,22.0,0.0,0.0,0.0,EEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +444,41.0,0.0,42.0,0.0,0.0,0.0,1.0,0.0,GCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +445,0.0,0.0,0.0,47.0,0.0,46.0,0.0,1.0,HDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +446,1.0,0.0,0.0,0.0,86.0,0.0,0.0,87.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +447,56.0,56.0,0.0,0.0,0.0,0.0,0.0,1.0,HABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +448,0.0,0.0,0.0,0.0,11.0,0.0,0.0,10.0,EEHEHEHEHEHEHEHEHEHEH,True +449,0.0,0.0,0.0,0.0,0.0,1.0,92.0,92.0,FGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +450,0.0,0.0,0.0,6.0,5.0,1.0,0.0,0.0,FDEDEDEDEDED,True +451,66.0,1.0,67.0,0.0,0.0,0.0,0.0,0.0,BCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +452,0.0,0.0,0.0,13.0,0.0,1.0,12.0,0.0,FDGDGDGDGDGDGDGDGDGDGDGDGD,True +453,1.0,0.0,0.0,0.0,56.0,0.0,56.0,0.0,AEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +454,15.0,0.0,0.0,0.0,0.0,0.0,0.0,16.0,HAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +455,0.0,21.0,1.0,0.0,21.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True +456,93.0,0.0,1.0,0.0,92.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +457,1.0,0.0,0.0,0.0,35.0,0.0,0.0,35.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +458,13.0,0.0,0.0,0.0,1.0,0.0,13.0,0.0,EAGAGAGAGAGAGAGAGAGAGAGAGAG,True +459,0.0,0.0,65.0,0.0,1.0,0.0,65.0,0.0,ECGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +460,0.0,0.0,95.0,1.0,0.0,95.0,0.0,0.0,DFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +461,15.0,0.0,0.0,0.0,1.0,0.0,0.0,15.0,EHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +462,0.0,0.0,198.0,0.0,1.0,0.0,0.0,0.0,ECCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +463,84.0,84.0,0.0,0.0,1.0,0.0,0.0,0.0,EABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +464,0.0,0.0,0.0,0.0,0.0,60.0,0.0,61.0,HFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +465,0.0,179.0,0.0,1.0,0.0,0.0,0.0,0.0,DBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +466,1.0,0.0,90.0,0.0,89.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +467,0.0,35.0,0.0,0.0,0.0,34.0,0.0,0.0,BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +468,0.0,0.0,0.0,1.0,7.0,0.0,0.0,7.0,DHEHEHEHEHEHEHE,True +469,0.0,0.0,0.0,0.0,92.0,0.0,91.0,0.0,EEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +470,0.0,0.0,46.0,0.0,0.0,1.0,46.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +471,0.0,0.0,0.0,0.0,0.0,1.0,158.0,0.0,FGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +472,1.0,0.0,0.0,0.0,0.0,58.0,0.0,59.0,AHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +473,0.0,0.0,6.0,1.0,0.0,0.0,6.0,0.0,DCGCGCGCGCGCG,True +474,0.0,0.0,0.0,0.0,0.0,98.0,0.0,97.0,FFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +475,0.0,87.0,0.0,0.0,0.0,0.0,0.0,85.0,BBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +476,0.0,0.0,33.0,0.0,0.0,0.0,1.0,33.0,GHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +477,45.0,0.0,0.0,0.0,46.0,0.0,0.0,0.0,EAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +478,0.0,0.0,0.0,77.0,0.0,0.0,75.0,0.0,DDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +479,73.0,1.0,73.0,0.0,0.0,0.0,0.0,0.0,BACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +480,0.0,1.0,0.0,0.0,37.0,37.0,0.0,0.0,BEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +481,0.0,92.0,93.0,0.0,0.0,1.0,0.0,0.0,FCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +482,0.0,0.0,0.0,1.0,0.0,0.0,0.0,24.0,DHHHHHHHHHHHHHHHHHHHHHHHH,True +483,25.0,0.0,0.0,1.0,0.0,25.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +484,0.0,0.0,0.0,0.0,0.0,37.0,0.0,36.0,FHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +485,21.0,0.0,0.0,1.0,0.0,20.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +486,0.0,35.0,0.0,36.0,0.0,0.0,0.0,1.0,HDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +487,0.0,0.0,1.0,0.0,97.0,98.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +488,0.0,93.0,0.0,0.0,0.0,1.0,0.0,94.0,FHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +489,0.0,1.0,0.0,93.0,0.0,0.0,93.0,0.0,BGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +490,0.0,0.0,0.0,70.0,0.0,0.0,72.0,0.0,GGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +491,86.0,0.0,0.0,0.0,1.0,86.0,0.0,0.0,EFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +492,0.0,65.0,1.0,0.0,0.0,65.0,0.0,0.0,CBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +493,0.0,0.0,0.0,69.0,0.0,0.0,0.0,1.0,HDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +494,0.0,0.0,144.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +495,0.0,45.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True 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+599,16.0,0.0,16.0,0.0,0.0,0.0,0.0,0.0,ACACACACACACACACACACACACACACACAC,True +600,0.0,21.0,0.0,22.0,0.0,0.0,0.0,0.0,DBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +601,70.0,71.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +602,0.0,0.0,0.0,1.0,0.0,0.0,53.0,0.0,DGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +603,45.0,0.0,0.0,0.0,0.0,45.0,0.0,0.0,FAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +604,0.0,1.0,56.0,0.0,0.0,0.0,56.0,0.0,BGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +605,0.0,1.0,0.0,0.0,0.0,0.0,0.0,195.0,BHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True 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+611,0.0,0.0,86.0,0.0,88.0,0.0,0.0,0.0,EECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +612,1.0,0.0,0.0,0.0,14.0,0.0,0.0,14.0,AEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +613,0.0,0.0,35.0,0.0,0.0,35.0,1.0,0.0,GCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCF,True +614,0.0,0.0,1.0,0.0,43.0,43.0,0.0,0.0,CEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +615,0.0,0.0,0.0,0.0,0.0,1.0,67.0,66.0,FGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +616,0.0,27.0,0.0,0.0,26.0,0.0,1.0,0.0,GBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +617,0.0,88.0,1.0,87.0,0.0,0.0,0.0,0.0,CBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +618,0.0,41.0,0.0,0.0,0.0,41.0,1.0,0.0,GFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +619,0.0,27.0,27.0,0.0,0.0,0.0,0.0,0.0,CBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +620,1.0,0.0,20.0,20.0,0.0,0.0,0.0,0.0,ADCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +621,0.0,0.0,1.0,24.0,24.0,0.0,0.0,0.0,CEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +622,1.0,0.0,0.0,0.0,55.0,55.0,0.0,0.0,AEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +623,1.0,0.0,0.0,0.0,26.0,0.0,26.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +624,0.0,0.0,15.0,0.0,0.0,0.0,0.0,13.0,CCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +625,0.0,0.0,1.0,67.0,67.0,0.0,0.0,0.0,CDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +626,0.0,0.0,65.0,0.0,0.0,1.0,0.0,64.0,FCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +627,0.0,0.0,0.0,0.0,89.0,1.0,90.0,0.0,FGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +628,0.0,0.0,0.0,0.0,1.0,0.0,51.0,0.0,EGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +629,0.0,0.0,41.0,0.0,0.0,40.0,0.0,0.0,CFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +630,0.0,0.0,93.0,0.0,0.0,0.0,1.0,0.0,GCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +631,0.0,53.0,1.0,0.0,0.0,53.0,0.0,0.0,CBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +632,0.0,0.0,0.0,14.0,0.0,0.0,0.0,15.0,HHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +633,0.0,29.0,0.0,0.0,0.0,0.0,28.0,0.0,BGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +634,0.0,66.0,0.0,0.0,0.0,1.0,66.0,0.0,FGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +635,0.0,0.0,62.0,62.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +636,0.0,31.0,32.0,0.0,1.0,0.0,0.0,0.0,ECBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +637,0.0,0.0,0.0,0.0,0.0,0.0,48.0,49.0,HGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +638,1.0,0.0,0.0,0.0,0.0,0.0,54.0,53.0,AGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +639,59.0,0.0,1.0,0.0,59.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +640,0.0,0.0,0.0,0.0,1.0,0.0,27.0,27.0,EGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +641,0.0,0.0,0.0,23.0,24.0,0.0,0.0,0.0,EDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +642,0.0,0.0,0.0,91.0,0.0,0.0,91.0,0.0,DGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +643,0.0,0.0,0.0,0.0,48.0,49.0,0.0,1.0,HFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +644,14.0,0.0,0.0,0.0,0.0,14.0,1.0,0.0,GAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +645,0.0,96.0,0.0,0.0,1.0,0.0,0.0,96.0,EHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +646,0.0,0.0,0.0,50.0,48.0,0.0,0.0,0.0,DDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +647,0.0,0.0,0.0,99.0,0.0,99.0,0.0,0.0,FDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +648,49.0,0.0,1.0,0.0,0.0,0.0,0.0,48.0,CAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +649,0.0,0.0,52.0,0.0,1.0,0.0,53.0,0.0,EGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True 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+667,1.0,147.0,0.0,0.0,0.0,0.0,0.0,0.0,ABBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +668,0.0,0.0,97.0,0.0,97.0,0.0,0.0,1.0,HCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +669,0.0,0.0,1.0,0.0,0.0,0.0,53.0,52.0,CGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +670,0.0,0.0,94.0,0.0,96.0,0.0,0.0,0.0,EECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +671,99.0,0.0,1.0,0.0,98.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +672,68.0,0.0,0.0,0.0,0.0,0.0,67.0,1.0,HAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGA,True +673,0.0,0.0,0.0,26.0,27.0,0.0,1.0,0.0,GEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +674,31.0,0.0,0.0,0.0,32.0,0.0,0.0,1.0,HEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +675,0.0,0.0,0.0,0.0,42.0,0.0,41.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +676,0.0,0.0,50.0,0.0,0.0,0.0,1.0,50.0,GCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +677,0.0,25.0,0.0,24.0,0.0,0.0,0.0,0.0,BBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +678,0.0,0.0,0.0,0.0,1.0,10.0,9.0,0.0,EFGFGFGFGFGFGFGFGFGF,True +679,65.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,DAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +680,0.0,23.0,0.0,0.0,0.0,0.0,23.0,1.0,HGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +681,0.0,1.0,58.0,0.0,0.0,0.0,57.0,0.0,BCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +682,0.0,0.0,0.0,0.0,0.0,68.0,1.0,68.0,GFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +683,0.0,0.0,0.0,0.0,96.0,0.0,96.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +684,1.0,0.0,0.0,0.0,66.0,0.0,66.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +685,0.0,0.0,0.0,0.0,0.0,1.0,0.0,21.0,FHHHHHHHHHHHHHHHHHHHHH,True +686,0.0,88.0,0.0,87.0,0.0,0.0,0.0,0.0,BDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +687,0.0,0.0,19.0,19.0,0.0,0.0,1.0,0.0,GDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +688,0.0,42.0,1.0,0.0,41.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +689,0.0,0.0,0.0,0.0,0.0,60.0,61.0,0.0,GGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +690,0.0,23.0,23.0,0.0,0.0,0.0,1.0,0.0,GBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +691,86.0,86.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +692,35.0,35.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +693,57.0,0.0,0.0,0.0,0.0,58.0,1.0,0.0,GFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +694,0.0,0.0,30.0,30.0,1.0,0.0,0.0,0.0,EDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +695,19.0,18.0,0.0,1.0,0.0,0.0,0.0,0.0,DABABABABABABABABABABABABABABABABABABA,True +696,0.0,0.0,0.0,1.0,0.0,56.0,0.0,57.0,DHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +697,10.0,0.0,1.0,0.0,0.0,0.0,0.0,11.0,CHAHAHAHAHAHAHAHAHAHAH,True +698,0.0,0.0,89.0,0.0,88.0,0.0,1.0,0.0,GCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +699,0.0,0.0,87.0,0.0,86.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +700,17.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAA,True +701,0.0,0.0,66.0,65.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +702,0.0,0.0,1.0,0.0,0.0,0.0,123.0,0.0,CGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +703,0.0,118.0,0.0,0.0,1.0,0.0,0.0,0.0,EBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +704,0.0,0.0,0.0,0.0,0.0,0.0,0.0,132.0,HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +705,0.0,0.0,0.0,0.0,0.0,23.0,1.0,23.0,GHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +706,0.0,0.0,0.0,0.0,6.0,5.0,0.0,0.0,EFEFEFEFEFE,True +707,18.0,0.0,0.0,16.0,0.0,0.0,0.0,0.0,AADADADADADADADADADADADADADADADADA,True +708,0.0,72.0,0.0,0.0,0.0,71.0,0.0,1.0,HBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +709,0.0,0.0,54.0,0.0,0.0,1.0,0.0,55.0,FHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +710,0.0,1.0,87.0,0.0,87.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +711,0.0,0.0,1.0,63.0,0.0,0.0,0.0,64.0,CHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +712,78.0,0.0,78.0,0.0,0.0,1.0,0.0,0.0,FCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +713,0.0,80.0,0.0,0.0,0.0,81.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +714,0.0,1.0,0.0,0.0,0.0,0.0,40.0,39.0,BGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +715,0.0,0.0,7.0,0.0,6.0,0.0,0.0,0.0,CCECECECECECE,True +716,35.0,0.0,0.0,0.0,0.0,0.0,0.0,33.0,AAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +717,0.0,0.0,0.0,1.0,73.0,0.0,0.0,72.0,DEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +718,0.0,0.0,90.0,0.0,0.0,1.0,89.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +719,1.0,0.0,0.0,67.0,0.0,0.0,0.0,66.0,ADHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +720,56.0,0.0,0.0,0.0,56.0,0.0,1.0,0.0,GAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +721,0.0,0.0,0.0,1.0,0.0,0.0,49.0,49.0,DHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +722,0.0,0.0,0.0,117.0,0.0,1.0,0.0,0.0,FDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +723,0.0,0.0,86.0,1.0,0.0,0.0,85.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +724,0.0,0.0,31.0,0.0,0.0,0.0,0.0,30.0,CCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +725,1.0,0.0,0.0,0.0,98.0,0.0,98.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +726,1.0,84.0,84.0,0.0,0.0,0.0,0.0,0.0,ACBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +727,0.0,56.0,56.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +728,0.0,1.0,0.0,24.0,24.0,0.0,0.0,0.0,BDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +729,37.0,0.0,0.0,0.0,0.0,37.0,0.0,0.0,FAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +730,0.0,0.0,91.0,0.0,0.0,0.0,91.0,0.0,GCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True 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+772,0.0,68.0,0.0,0.0,0.0,0.0,0.0,67.0,BBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +773,60.0,1.0,0.0,0.0,0.0,61.0,0.0,0.0,BFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +774,0.0,1.0,0.0,57.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +775,0.0,78.0,0.0,0.0,1.0,0.0,0.0,0.0,EBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +776,1.0,0.0,0.0,0.0,0.0,96.0,96.0,0.0,AGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +777,43.0,0.0,0.0,0.0,0.0,1.0,44.0,0.0,FGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True 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For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/src/main/scala/org/xcit/nback/markov/models/State.scala b/src/main/scala/org/xcit/nback/markov/models/State.scala deleted file mode 100644 index fbbd844..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/State.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * A Single state with a label in Markov chain - * @param label A simple string label, representing the state and node - */ -class State(val label: String) { - - /** - * Keep track of transitions from this state to other states. - */ - val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() -} diff --git a/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/src/main/scala/org/xcit/nback/markov/models/Transition.scala deleted file mode 100644 index bc20a9e..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/Transition.scala +++ /dev/null @@ -1,8 +0,0 @@ -package org.xcit.nback.markov.models - -/** - * A Single transition in Markov chain graph. It is stored in "from" node. - * @param to the ending node of the edge - * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). - */ -case class Transition(to: State, probability: Double = 0.0) diff --git a/src/test/scala/ThreeBackBenchmark.scala b/src/test/scala/ThreeBackBenchmark.scala deleted file mode 100644 index 0c7dad9..0000000 --- a/src/test/scala/ThreeBackBenchmark.scala +++ /dev/null @@ -1,7 +0,0 @@ - -/** - * TODO Benchmark 3-back simple sequence generator - */ -class ThreeBackBenchmark { - -} diff --git a/tests/benchmark_diagrams.py b/tests/benchmark_diagrams.py new file mode 100644 index 0000000..8fa448e --- /dev/null +++ b/tests/benchmark_diagrams.py @@ -0,0 +1,159 @@ +import pandas as pd +import numpy as np +from matplotlib import pyplot as plt + +import benchmarks.common as common + + +def tlratio(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2,ignore_index=True) + stats = [] + for trials in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == trials) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == trials) + targets2 = data[alg2].targets if alg2.shape[0] > 0 else np.nan + targets4 = data[alg4].targets if alg4.shape[0] > 0 else np.nan + lures2 = data[alg2].lures if alg2.shape[0] > 0 else np.nan + lures4 = data[alg4].lures if alg4.shape[0] > 0 else np.nan + stats.append([trials, (targets2/lures2).mean(), (targets4/lures4).mean()]) + stats = pd.DataFrame(stats, columns=['trials', 'tl2', 'tl4']) #.dropna(subset=['skewness']) + + plt.style.use('ggplot') + + plt.ylim(bottom=0, top=30) + plt.scatter(stats.trials, stats.tl2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl2[idx], 1)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.tl4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl4[idx], 2)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('T:L Ratio') + plt.ylabel('T:L Ratio') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_tlratio.png', bbox_inches='tight') + plt.show() + + +def time_per_trial(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for t in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == t) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == t) + time2 = data[alg2].time.mean() * 1000 if alg2.shape[0] > 0 else np.nan + time4 = data[alg4].time.mean() * 1000 if alg4.shape[0] > 0 else np.nan + stats.append([t, time2, time4]) + stats = pd.DataFrame(stats, columns=['trials', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.trials, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time2[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time4[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2v4_time_trials.png', bbox_inches='tight') + plt.show() + +def time_profiles(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 8): + alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + time2 = data[alg2].time.mean() * 1000 + time4 = data[alg4].time.mean() * 1000 + stats.append([ni, time2, time4]) + stats = pd.DataFrame(stats, columns=['n', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.n, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.time2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + plt.scatter(stats.n, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.time4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_time_n.png', bbox_inches='tight') + plt.show() + +def skewness(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 9): + all_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + skewed_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) & data.skewed + all_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + skewed_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) & data.skewed + num_of_sequences2 = data[all_alg2].shape[0] + skewed_sequences2 = data[skewed_alg2].shape[0] + num_of_sequences4 = data[all_alg4].shape[0] + skewed_sequences4 = data[skewed_alg4].shape[0] + skewness2 = skewed_sequences2 * 100.0 / num_of_sequences2 if (num_of_sequences2>0) else 0 + skewness4 = skewed_sequences4 * 100.0 / num_of_sequences4 if (num_of_sequences4>0) else 0 + stats.append([ni, skewness2, skewness4]) + stats = pd.DataFrame(stats, columns=['n', 'skewness2', 'skewness4']) #.dropna(subset=['skewness']) + + + plt.style.use('ggplot') + plt.scatter(stats.n, stats.skewness2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.skewness2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + + plt.scatter(stats.n, stats.skewness4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.skewness4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Skewness') + plt.ylabel('Skewed Blocks (%)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_skewness.png', bbox_inches='tight') + plt.show() + +if __name__ == "__main__": + tlratio() + skewness() + time_profiles() + time_per_trial() diff --git a/tests/benchmark_skewness.py b/tests/benchmark_skewness.py new file mode 100644 index 0000000..f468b4d --- /dev/null +++ b/tests/benchmark_skewness.py @@ -0,0 +1,97 @@ +import random +import heapq +import csv + +# Common parameters +alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'] +trials_range = (10, 40) +n = 3 +sample_size = 100 + + +def to_benchmark_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [str(ralph_skewed)] + +def benchmark_nb_gm_001(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_001') + + +def benchmark_nb_gm_002(filename): + import generators.nb_gm_002 as nb_gm_002 + + generator = nb_gm_002.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + # print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_002') + + +def benchmark_nb_gm_003(filename): + import generators.nb_gm_003 as nb_gm_003 + + generator = nb_gm_003.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + print(f"sequence {i}/{sample_size}: {trials} trials") + seq = generator.generate(trials) + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_003') + + +def show_skweness_diagram(filename, choices, title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + print(filename) + data = pd.read_csv(filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) #.dropna(subset=['skewness']) + #print(stats.trials) + #plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'{title}.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + benchmark_nb_gm_003('../benchmarks/nb_gm_003_2back.csv') diff --git a/tests/common.py b/tests/common.py new file mode 100644 index 0000000..e40c0df --- /dev/null +++ b/tests/common.py @@ -0,0 +1,27 @@ + + +# Common benchmark parameters +choices = alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F'] +trials_range = (10, 65) +n = 4 +sample_size = 100 + + +def count_targets_and_lures(seq, n): + mask = 'D'*n + for index in range(n, len(seq)): + if seq[index] == seq[index - n]: + mask += 'T' + elif seq[index] in seq[index - n - 1:index - n + 1]: + mask += 'L' + else: + mask += 'D' + return mask.count('T'), mask.count('L') + + +def skewness(seq, choices): + import heapq + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return ralph_skewed diff --git a/tests/nb_gm_001_bm.py b/tests/nb_gm_001_bm.py new file mode 100644 index 0000000..54f6cb3 --- /dev/null +++ b/tests/nb_gm_001_bm.py @@ -0,0 +1,75 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq) , str(ralph_skewed)] + + +def benchmark(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets / s.trials, axis=1) + plt.scatter(data.trials, data.targets_ratio, alpha=0.2) + plt.show() + +if __name__ == '__main__': + alg = 'nb_gm_001' + fn = f'results/{alg}_{n}back.csv' + benchmark(fn) + # skewness_diagram(fn, alg) + targets_ratio_diagram(fn, alg) diff --git a/tests/nb_gm_002_bm.py b/tests/nb_gm_002_bm.py new file mode 100644 index 0000000..c8af543 --- /dev/null +++ b/tests/nb_gm_002_bm.py @@ -0,0 +1,105 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq), str(ralph_skewed)] + + +def benchmark(filename): + from generators.nb_gm_002 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials, int(trials/3), 0, 0) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +import time +import numpy as np +import pandas as pd + +import benchmarks.common as common + +def profile(): + from generators.nb_gm_002 import SequenceGenerator + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, int(lures/2), int(lures/2)) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('benchmarks/results/nb_gm_002_profile.csv', sep=',', encoding='utf-8') + +if __name__ == '__main__': + alg = 'nb_gm_002' + fn = f'results/{alg}_{n}back.csv' + profile() diff --git a/tests/nb_gm_003_bm.py b/tests/nb_gm_003_bm.py new file mode 100644 index 0000000..fa6c19a --- /dev/null +++ b/tests/nb_gm_003_bm.py @@ -0,0 +1,114 @@ +import heapq +import csv +import random +import time + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq, time_per_block): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [time_per_block, ''.join(seq), str(ralph_skewed)] + + +def benchmark_skewness(filename): + from generators.nb_gm_003 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['time_per_block', 'seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + targets = trials / 3 + t = time.time() + seq = generator.generate(trials, targets) + t = time.time() - t + print(f"sequence {i}/{sample_size}: {trials} trials, took {t}s.") + writer.writerow(to_csv_row(i, seq, t)) + plot_skewness(fn, 'nb_gm_003') + + +def plot_skewness(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def plot_targets_ratio(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +def benchmark_targets_ratio(): + pass + +def benchmark_chunking(): + pass + + +def benchmark_n(): + pass + + +def plot_timing(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['time_per_trial'] = data.apply(lambda s: s.time_per_block / s.trials, axis=1) + plt.style.use('ggplot') + plt.title(f"{figure_title} - average time to generate a trial") + plt.ylabel('time (s)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.time_per_trial, alpha=0.5) + + # draw fitted curve + # import numpy as np + # p = np.poly1d(np.polyfit(data.trials, data.time_per_trial, 3)) + # plt.plot(data.trials, p(data.trials), color='red') + + plt.savefig(f'results/{figure_title}_timing.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + alg = 'nb_gm_003' + fn = f'results/{alg}_{n}back.csv' + benchmark_skewness(fn) diff --git a/tests/nb_gm_004_bm.py b/tests/nb_gm_004_bm.py new file mode 100644 index 0000000..b4ad4a8 --- /dev/null +++ b/tests/nb_gm_004_bm.py @@ -0,0 +1,26 @@ +import time +import numpy as np +import pandas as pd + +import tests.common as common +from generators.nb_gm_004 import SequenceGenerator + +def run(): + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, lures) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('tests/results/nb_gm_004_profile.csv', sep=',', encoding='utf-8') diff --git a/tests/results/2v4_time_trials.png b/tests/results/2v4_time_trials.png new file mode 100644 index 0000000..9be91b4 --- /dev/null +++ b/tests/results/2v4_time_trials.png Binary files differ diff --git a/tests/results/2vs4_skewness.png b/tests/results/2vs4_skewness.png new file mode 100644 index 0000000..a488e1f --- /dev/null +++ b/tests/results/2vs4_skewness.png Binary files differ diff --git a/tests/results/2vs4_time_n.png b/tests/results/2vs4_time_n.png new file mode 100644 index 0000000..d022ed0 --- /dev/null +++ b/tests/results/2vs4_time_n.png Binary files differ diff --git a/tests/results/2vs4_tlratio.png b/tests/results/2vs4_tlratio.png new file mode 100644 index 0000000..b76f296 --- /dev/null +++ b/tests/results/2vs4_tlratio.png Binary files differ diff --git a/tests/results/nb_gm_001_2back.csv b/tests/results/nb_gm_001_2back.csv new file mode 100644 index 0000000..f6ad25e --- /dev/null +++ b/tests/results/nb_gm_001_2back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,0.0,1.0,0.0,55.0,56.0,0.0,0.0,0.0,BEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True 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+364,0.0,0.0,0.0,1.0,0.0,31.0,0.0,31.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +365,0.0,0.0,0.0,24.0,0.0,23.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +366,0.0,15.0,0.0,0.0,16.0,0.0,0.0,0.0,EEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +367,22.0,0.0,0.0,0.0,0.0,0.0,1.0,22.0,GHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +368,0.0,25.0,0.0,0.0,0.0,0.0,25.0,0.0,BGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +369,0.0,0.0,0.0,100.0,1.0,0.0,0.0,0.0,EDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +370,0.0,17.0,0.0,17.0,1.0,0.0,0.0,0.0,EBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +371,0.0,1.0,49.0,0.0,49.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True 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+377,27.0,0.0,0.0,29.0,0.0,0.0,0.0,0.0,DDADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +378,81.0,0.0,0.0,81.0,0.0,0.0,0.0,1.0,HADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +379,1.0,0.0,9.0,0.0,8.0,0.0,0.0,0.0,ACECECECECECECECEC,True +380,1.0,0.0,0.0,32.0,33.0,0.0,0.0,0.0,AEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +381,5.0,0.0,5.0,0.0,1.0,0.0,0.0,0.0,ECACACACACA,True +382,0.0,0.0,0.0,96.0,0.0,0.0,98.0,0.0,GGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +383,0.0,86.0,0.0,0.0,0.0,85.0,0.0,0.0,BBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +384,0.0,0.0,28.0,0.0,1.0,0.0,0.0,28.0,ECHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +385,0.0,1.0,119.0,0.0,0.0,0.0,0.0,0.0,BCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +386,0.0,0.0,93.0,0.0,0.0,93.0,1.0,0.0,GCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCF,True +387,92.0,0.0,1.0,0.0,92.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +388,0.0,186.0,0.0,0.0,0.0,0.0,0.0,0.0,BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +389,1.0,74.0,0.0,0.0,0.0,0.0,0.0,0.0,ABBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +390,0.0,0.0,0.0,0.0,1.0,86.0,0.0,87.0,EHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +391,61.0,0.0,0.0,61.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +392,0.0,0.0,0.0,1.0,16.0,0.0,0.0,15.0,DEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +393,118.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +394,0.0,0.0,0.0,0.0,0.0,75.0,0.0,1.0,HFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +395,30.0,0.0,0.0,0.0,0.0,0.0,0.0,30.0,AHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +396,65.0,0.0,0.0,0.0,0.0,1.0,0.0,65.0,FAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +397,0.0,0.0,0.0,55.0,56.0,0.0,0.0,0.0,EEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +398,26.0,0.0,0.0,25.0,1.0,0.0,0.0,0.0,EADADADADADADADADADADADADADADADADADADADADADADADADADA,True +399,0.0,0.0,60.0,0.0,0.0,0.0,1.0,59.0,GCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +400,1.0,0.0,0.0,0.0,160.0,0.0,0.0,0.0,AEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +401,1.0,0.0,31.0,0.0,0.0,31.0,0.0,0.0,AFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +402,0.0,0.0,0.0,15.0,1.0,0.0,0.0,0.0,EDDDDDDDDDDDDDDD,True +403,0.0,0.0,0.0,54.0,55.0,0.0,0.0,1.0,HEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +404,0.0,0.0,0.0,27.0,0.0,27.0,0.0,1.0,HFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +405,0.0,0.0,0.0,1.0,0.0,15.0,0.0,15.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +406,0.0,95.0,0.0,94.0,0.0,1.0,0.0,0.0,FBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +407,0.0,0.0,15.0,14.0,0.0,0.0,0.0,0.0,CCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +408,78.0,78.0,0.0,0.0,0.0,0.0,1.0,0.0,GBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +409,0.0,0.0,72.0,1.0,0.0,0.0,72.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +410,55.0,0.0,1.0,0.0,0.0,0.0,55.0,0.0,CAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +411,0.0,59.0,0.0,0.0,0.0,60.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +412,61.0,0.0,0.0,61.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +413,0.0,1.0,0.0,75.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +414,0.0,53.0,0.0,0.0,0.0,0.0,52.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +415,0.0,0.0,16.0,0.0,1.0,0.0,0.0,15.0,ECHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +416,0.0,0.0,0.0,39.0,0.0,0.0,0.0,38.0,DHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +417,96.0,0.0,1.0,95.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +418,28.0,0.0,1.0,27.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +419,0.0,1.0,92.0,92.0,0.0,0.0,0.0,0.0,BCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +420,1.0,0.0,20.0,0.0,20.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECE,True +421,0.0,90.0,0.0,0.0,0.0,0.0,89.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +422,10.0,0.0,0.0,0.0,0.0,1.0,11.0,0.0,FGAGAGAGAGAGAGAGAGAGAG,True +423,0.0,0.0,0.0,74.0,73.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +424,0.0,0.0,127.0,0.0,0.0,0.0,1.0,0.0,GCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +425,1.0,9.0,0.0,0.0,0.0,9.0,0.0,0.0,AFBFBFBFBFBFBFBFBFB,True +426,0.0,0.0,84.0,0.0,0.0,0.0,0.0,84.0,HCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +427,33.0,0.0,0.0,34.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +428,1.0,30.0,0.0,30.0,0.0,0.0,0.0,0.0,ABDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +429,0.0,0.0,67.0,0.0,1.0,67.0,0.0,0.0,EFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +430,62.0,0.0,0.0,63.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +431,1.0,9.0,9.0,0.0,0.0,0.0,0.0,0.0,ABCBCBCBCBCBCBCBCBC,True +432,15.0,0.0,0.0,0.0,0.0,0.0,14.0,0.0,AAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +433,0.0,1.0,0.0,65.0,66.0,0.0,0.0,0.0,BEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +434,0.0,160.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +435,0.0,0.0,1.0,0.0,42.0,42.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +436,0.0,0.0,55.0,0.0,55.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +437,0.0,0.0,0.0,1.0,0.0,73.0,0.0,73.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +438,79.0,0.0,0.0,0.0,78.0,0.0,0.0,0.0,AAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +439,0.0,0.0,67.0,0.0,0.0,0.0,66.0,1.0,HCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +440,0.0,0.0,77.0,0.0,0.0,1.0,0.0,76.0,FCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +441,0.0,0.0,0.0,0.0,153.0,0.0,0.0,1.0,HEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +442,0.0,88.0,88.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +443,0.0,0.0,0.0,20.0,22.0,0.0,0.0,0.0,EEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +444,41.0,0.0,42.0,0.0,0.0,0.0,1.0,0.0,GCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +445,0.0,0.0,0.0,47.0,0.0,46.0,0.0,1.0,HDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +446,1.0,0.0,0.0,0.0,86.0,0.0,0.0,87.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +447,56.0,56.0,0.0,0.0,0.0,0.0,0.0,1.0,HABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +448,0.0,0.0,0.0,0.0,11.0,0.0,0.0,10.0,EEHEHEHEHEHEHEHEHEHEH,True +449,0.0,0.0,0.0,0.0,0.0,1.0,92.0,92.0,FGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +450,0.0,0.0,0.0,6.0,5.0,1.0,0.0,0.0,FDEDEDEDEDED,True +451,66.0,1.0,67.0,0.0,0.0,0.0,0.0,0.0,BCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +452,0.0,0.0,0.0,13.0,0.0,1.0,12.0,0.0,FDGDGDGDGDGDGDGDGDGDGDGDGD,True +453,1.0,0.0,0.0,0.0,56.0,0.0,56.0,0.0,AEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +454,15.0,0.0,0.0,0.0,0.0,0.0,0.0,16.0,HAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +455,0.0,21.0,1.0,0.0,21.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True +456,93.0,0.0,1.0,0.0,92.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +457,1.0,0.0,0.0,0.0,35.0,0.0,0.0,35.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +458,13.0,0.0,0.0,0.0,1.0,0.0,13.0,0.0,EAGAGAGAGAGAGAGAGAGAGAGAGAG,True +459,0.0,0.0,65.0,0.0,1.0,0.0,65.0,0.0,ECGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +460,0.0,0.0,95.0,1.0,0.0,95.0,0.0,0.0,DFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +461,15.0,0.0,0.0,0.0,1.0,0.0,0.0,15.0,EHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +462,0.0,0.0,198.0,0.0,1.0,0.0,0.0,0.0,ECCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +463,84.0,84.0,0.0,0.0,1.0,0.0,0.0,0.0,EABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +464,0.0,0.0,0.0,0.0,0.0,60.0,0.0,61.0,HFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +465,0.0,179.0,0.0,1.0,0.0,0.0,0.0,0.0,DBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +466,1.0,0.0,90.0,0.0,89.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +467,0.0,35.0,0.0,0.0,0.0,34.0,0.0,0.0,BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +468,0.0,0.0,0.0,1.0,7.0,0.0,0.0,7.0,DHEHEHEHEHEHEHE,True +469,0.0,0.0,0.0,0.0,92.0,0.0,91.0,0.0,EEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +470,0.0,0.0,46.0,0.0,0.0,1.0,46.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +471,0.0,0.0,0.0,0.0,0.0,1.0,158.0,0.0,FGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +472,1.0,0.0,0.0,0.0,0.0,58.0,0.0,59.0,AHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +473,0.0,0.0,6.0,1.0,0.0,0.0,6.0,0.0,DCGCGCGCGCGCG,True +474,0.0,0.0,0.0,0.0,0.0,98.0,0.0,97.0,FFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +475,0.0,87.0,0.0,0.0,0.0,0.0,0.0,85.0,BBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +476,0.0,0.0,33.0,0.0,0.0,0.0,1.0,33.0,GHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +477,45.0,0.0,0.0,0.0,46.0,0.0,0.0,0.0,EAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +478,0.0,0.0,0.0,77.0,0.0,0.0,75.0,0.0,DDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +479,73.0,1.0,73.0,0.0,0.0,0.0,0.0,0.0,BACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +480,0.0,1.0,0.0,0.0,37.0,37.0,0.0,0.0,BEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +481,0.0,92.0,93.0,0.0,0.0,1.0,0.0,0.0,FCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +482,0.0,0.0,0.0,1.0,0.0,0.0,0.0,24.0,DHHHHHHHHHHHHHHHHHHHHHHHH,True +483,25.0,0.0,0.0,1.0,0.0,25.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +484,0.0,0.0,0.0,0.0,0.0,37.0,0.0,36.0,FHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +485,21.0,0.0,0.0,1.0,0.0,20.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +486,0.0,35.0,0.0,36.0,0.0,0.0,0.0,1.0,HDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +487,0.0,0.0,1.0,0.0,97.0,98.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +488,0.0,93.0,0.0,0.0,0.0,1.0,0.0,94.0,FHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +489,0.0,1.0,0.0,93.0,0.0,0.0,93.0,0.0,BGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +490,0.0,0.0,0.0,70.0,0.0,0.0,72.0,0.0,GGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +491,86.0,0.0,0.0,0.0,1.0,86.0,0.0,0.0,EFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +492,0.0,65.0,1.0,0.0,0.0,65.0,0.0,0.0,CBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +493,0.0,0.0,0.0,69.0,0.0,0.0,0.0,1.0,HDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +494,0.0,0.0,144.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +495,0.0,45.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +496,0.0,0.0,0.0,28.0,0.0,27.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +497,0.0,72.0,0.0,0.0,0.0,1.0,73.0,0.0,FGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +498,0.0,0.0,41.0,0.0,1.0,0.0,40.0,0.0,ECGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +499,0.0,1.0,0.0,0.0,0.0,131.0,0.0,0.0,BFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +500,17.0,0.0,0.0,1.0,0.0,17.0,0.0,0.0,DFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +501,19.0,0.0,0.0,19.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADA,True +502,1.0,0.0,0.0,0.0,51.0,0.0,52.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +503,1.0,0.0,0.0,0.0,0.0,0.0,29.0,29.0,AGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +504,36.0,0.0,0.0,1.0,0.0,35.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +505,0.0,0.0,0.0,20.0,0.0,0.0,1.0,20.0,GDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +506,0.0,0.0,0.0,163.0,0.0,0.0,0.0,1.0,HDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +507,22.0,23.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABAB,True +508,0.0,1.0,0.0,0.0,0.0,0.0,41.0,42.0,BHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +509,0.0,0.0,0.0,45.0,1.0,0.0,0.0,44.0,EDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True 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+671,99.0,0.0,1.0,0.0,98.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +672,68.0,0.0,0.0,0.0,0.0,0.0,67.0,1.0,HAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGA,True +673,0.0,0.0,0.0,26.0,27.0,0.0,1.0,0.0,GEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +674,31.0,0.0,0.0,0.0,32.0,0.0,0.0,1.0,HEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +675,0.0,0.0,0.0,0.0,42.0,0.0,41.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +676,0.0,0.0,50.0,0.0,0.0,0.0,1.0,50.0,GCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +677,0.0,25.0,0.0,24.0,0.0,0.0,0.0,0.0,BBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +678,0.0,0.0,0.0,0.0,1.0,10.0,9.0,0.0,EFGFGFGFGFGFGFGFGFGF,True +679,65.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,DAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +680,0.0,23.0,0.0,0.0,0.0,0.0,23.0,1.0,HGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +681,0.0,1.0,58.0,0.0,0.0,0.0,57.0,0.0,BCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +682,0.0,0.0,0.0,0.0,0.0,68.0,1.0,68.0,GFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +683,0.0,0.0,0.0,0.0,96.0,0.0,96.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +684,1.0,0.0,0.0,0.0,66.0,0.0,66.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +685,0.0,0.0,0.0,0.0,0.0,1.0,0.0,21.0,FHHHHHHHHHHHHHHHHHHHHH,True +686,0.0,88.0,0.0,87.0,0.0,0.0,0.0,0.0,BDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +687,0.0,0.0,19.0,19.0,0.0,0.0,1.0,0.0,GDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +688,0.0,42.0,1.0,0.0,41.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +689,0.0,0.0,0.0,0.0,0.0,60.0,61.0,0.0,GGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +690,0.0,23.0,23.0,0.0,0.0,0.0,1.0,0.0,GBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +691,86.0,86.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +692,35.0,35.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +693,57.0,0.0,0.0,0.0,0.0,58.0,1.0,0.0,GFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +694,0.0,0.0,30.0,30.0,1.0,0.0,0.0,0.0,EDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +695,19.0,18.0,0.0,1.0,0.0,0.0,0.0,0.0,DABABABABABABABABABABABABABABABABABABA,True +696,0.0,0.0,0.0,1.0,0.0,56.0,0.0,57.0,DHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +697,10.0,0.0,1.0,0.0,0.0,0.0,0.0,11.0,CHAHAHAHAHAHAHAHAHAHAH,True +698,0.0,0.0,89.0,0.0,88.0,0.0,1.0,0.0,GCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +699,0.0,0.0,87.0,0.0,86.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +700,17.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAA,True +701,0.0,0.0,66.0,65.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +702,0.0,0.0,1.0,0.0,0.0,0.0,123.0,0.0,CGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +703,0.0,118.0,0.0,0.0,1.0,0.0,0.0,0.0,EBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +704,0.0,0.0,0.0,0.0,0.0,0.0,0.0,132.0,HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +705,0.0,0.0,0.0,0.0,0.0,23.0,1.0,23.0,GHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +706,0.0,0.0,0.0,0.0,6.0,5.0,0.0,0.0,EFEFEFEFEFE,True +707,18.0,0.0,0.0,16.0,0.0,0.0,0.0,0.0,AADADADADADADADADADADADADADADADADA,True +708,0.0,72.0,0.0,0.0,0.0,71.0,0.0,1.0,HBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +709,0.0,0.0,54.0,0.0,0.0,1.0,0.0,55.0,FHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +710,0.0,1.0,87.0,0.0,87.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +711,0.0,0.0,1.0,63.0,0.0,0.0,0.0,64.0,CHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +712,78.0,0.0,78.0,0.0,0.0,1.0,0.0,0.0,FCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +713,0.0,80.0,0.0,0.0,0.0,81.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +714,0.0,1.0,0.0,0.0,0.0,0.0,40.0,39.0,BGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +715,0.0,0.0,7.0,0.0,6.0,0.0,0.0,0.0,CCECECECECECE,True +716,35.0,0.0,0.0,0.0,0.0,0.0,0.0,33.0,AAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +717,0.0,0.0,0.0,1.0,73.0,0.0,0.0,72.0,DEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +718,0.0,0.0,90.0,0.0,0.0,1.0,89.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +719,1.0,0.0,0.0,67.0,0.0,0.0,0.0,66.0,ADHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +720,56.0,0.0,0.0,0.0,56.0,0.0,1.0,0.0,GAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +721,0.0,0.0,0.0,1.0,0.0,0.0,49.0,49.0,DHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +722,0.0,0.0,0.0,117.0,0.0,1.0,0.0,0.0,FDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +723,0.0,0.0,86.0,1.0,0.0,0.0,85.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +724,0.0,0.0,31.0,0.0,0.0,0.0,0.0,30.0,CCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +725,1.0,0.0,0.0,0.0,98.0,0.0,98.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +726,1.0,84.0,84.0,0.0,0.0,0.0,0.0,0.0,ACBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +727,0.0,56.0,56.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +728,0.0,1.0,0.0,24.0,24.0,0.0,0.0,0.0,BDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +729,37.0,0.0,0.0,0.0,0.0,37.0,0.0,0.0,FAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +730,0.0,0.0,91.0,0.0,0.0,0.0,91.0,0.0,GCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +731,98.0,0.0,99.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +732,0.0,0.0,0.0,0.0,99.0,1.0,98.0,0.0,FEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +733,0.0,0.0,30.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +734,12.0,1.0,13.0,0.0,0.0,0.0,0.0,0.0,BCACACACACACACACACACACACAC,True +735,0.0,93.0,1.0,0.0,93.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True 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+852,0.0,1.0,0.0,0.0,136.0,0.0,0.0,0.0,BEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +853,0.0,0.0,0.0,0.0,1.0,0.0,0.0,163.0,EHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +854,74.0,0.0,75.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +855,0.0,0.0,0.0,19.0,0.0,0.0,17.0,0.0,DDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +856,0.0,73.0,0.0,1.0,0.0,0.0,74.0,0.0,DGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True 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+863,0.0,0.0,0.0,32.0,1.0,0.0,32.0,0.0,EGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +864,0.0,0.0,15.0,0.0,1.0,14.0,0.0,0.0,ECFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +865,0.0,1.0,98.0,0.0,0.0,0.0,98.0,0.0,BGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +866,1.0,0.0,0.0,0.0,19.0,0.0,0.0,0.0,AEEEEEEEEEEEEEEEEEEE,True +867,24.0,0.0,0.0,0.0,24.0,0.0,0.0,0.0,AEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +868,0.0,0.0,0.0,74.0,0.0,0.0,0.0,73.0,DHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +869,0.0,78.0,1.0,0.0,0.0,0.0,77.0,0.0,CBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +870,0.0,0.0,1.0,0.0,50.0,0.0,51.0,0.0,CGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +871,0.0,0.0,16.0,0.0,0.0,16.0,0.0,1.0,HFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +872,0.0,0.0,0.0,1.0,28.0,28.0,0.0,0.0,DFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +873,0.0,0.0,65.0,65.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +874,0.0,34.0,0.0,0.0,0.0,35.0,0.0,0.0,FBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +875,0.0,0.0,9.0,0.0,8.0,0.0,0.0,1.0,HCECECECECECECECEC,True +876,0.0,0.0,0.0,0.0,94.0,0.0,94.0,1.0,HEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +877,0.0,18.0,0.0,16.0,0.0,0.0,0.0,0.0,BBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True 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+885,0.0,0.0,0.0,93.0,0.0,93.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDF,True +886,0.0,1.0,0.0,89.0,0.0,89.0,0.0,0.0,BFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +887,0.0,1.0,0.0,0.0,42.0,0.0,0.0,42.0,BHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +888,68.0,0.0,0.0,0.0,1.0,0.0,0.0,67.0,EAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +889,55.0,0.0,0.0,0.0,0.0,57.0,0.0,0.0,FFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +890,25.0,1.0,0.0,0.0,0.0,0.0,26.0,0.0,BGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +891,81.0,0.0,0.0,0.0,80.0,0.0,0.0,0.0,AAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +892,0.0,0.0,1.0,0.0,10.0,0.0,10.0,0.0,CGEGEGEGEGEGEGEGEGEGE,True +893,1.0,0.0,43.0,42.0,0.0,0.0,0.0,0.0,ACDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +894,55.0,54.0,0.0,0.0,0.0,0.0,0.0,0.0,AABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +895,43.0,0.0,0.0,0.0,0.0,1.0,0.0,43.0,FAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +896,1.0,0.0,0.0,0.0,97.0,97.0,0.0,0.0,AEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +897,0.0,25.0,0.0,1.0,0.0,25.0,0.0,0.0,DFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +898,0.0,0.0,0.0,0.0,26.0,26.0,1.0,0.0,GEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +899,0.0,0.0,36.0,0.0,36.0,0.0,0.0,0.0,ECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +900,0.0,0.0,0.0,0.0,1.0,0.0,89.0,88.0,EGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +901,0.0,1.0,142.0,0.0,0.0,0.0,0.0,0.0,BCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +902,1.0,83.0,0.0,83.0,0.0,0.0,0.0,0.0,ABDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +903,0.0,0.0,17.0,0.0,17.0,0.0,0.0,1.0,HECECECECECECECECECECECECECECECECEC,True +904,77.0,77.0,0.0,0.0,0.0,0.0,0.0,0.0,BABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +905,0.0,0.0,0.0,0.0,0.0,0.0,164.0,0.0,GGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +906,0.0,0.0,0.0,89.0,0.0,1.0,0.0,90.0,FHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +907,0.0,0.0,41.0,0.0,0.0,0.0,42.0,0.0,GCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +908,28.0,0.0,0.0,0.0,0.0,28.0,1.0,0.0,GAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +909,0.0,0.0,94.0,0.0,1.0,0.0,95.0,0.0,EGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +910,0.0,0.0,27.0,1.0,27.0,0.0,0.0,0.0,DECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +911,0.0,0.0,0.0,100.0,0.0,1.0,0.0,0.0,FDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +912,0.0,1.0,66.0,0.0,0.0,0.0,66.0,0.0,BGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +913,0.0,23.0,23.0,0.0,0.0,1.0,0.0,0.0,FCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +914,0.0,0.0,0.0,0.0,0.0,0.0,150.0,0.0,GGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +915,0.0,0.0,0.0,0.0,0.0,0.0,1.0,42.0,GHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +916,0.0,147.0,0.0,0.0,0.0,0.0,1.0,0.0,GBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +917,0.0,56.0,0.0,1.0,0.0,0.0,0.0,56.0,DHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +918,0.0,0.0,0.0,0.0,0.0,76.0,76.0,1.0,HFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFG,True +919,0.0,53.0,0.0,0.0,0.0,0.0,0.0,52.0,BHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +920,0.0,0.0,147.0,0.0,0.0,1.0,0.0,0.0,FCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +921,0.0,0.0,0.0,40.0,40.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +922,0.0,82.0,0.0,84.0,0.0,0.0,0.0,0.0,DDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +923,1.0,0.0,0.0,0.0,0.0,0.0,0.0,97.0,AHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +924,0.0,29.0,0.0,0.0,0.0,0.0,0.0,30.0,HHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +925,25.0,0.0,0.0,1.0,0.0,0.0,0.0,25.0,DHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +926,0.0,164.0,0.0,0.0,0.0,0.0,1.0,0.0,GBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +927,89.0,0.0,0.0,0.0,1.0,0.0,90.0,0.0,EGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +928,0.0,0.0,1.0,0.0,41.0,41.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +929,0.0,0.0,1.0,19.0,18.0,0.0,0.0,0.0,CDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +930,0.0,0.0,0.0,0.0,1.0,75.0,75.0,0.0,EGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +931,0.0,0.0,21.0,0.0,0.0,22.0,0.0,0.0,FCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCF,True +932,0.0,0.0,81.0,0.0,80.0,1.0,0.0,0.0,FCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +933,20.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAAAAA,True +934,0.0,40.0,0.0,0.0,0.0,40.0,0.0,0.0,BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +935,0.0,72.0,0.0,0.0,72.0,0.0,1.0,0.0,GBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True +936,56.0,1.0,0.0,56.0,0.0,0.0,0.0,0.0,BADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +937,0.0,0.0,0.0,0.0,0.0,96.0,1.0,0.0,GFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +938,0.0,1.0,0.0,88.0,0.0,0.0,0.0,88.0,BHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +939,1.0,0.0,0.0,0.0,0.0,0.0,0.0,175.0,AHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +940,0.0,0.0,84.0,1.0,83.0,0.0,0.0,0.0,DCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +941,0.0,0.0,83.0,0.0,0.0,0.0,0.0,85.0,HHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +942,1.0,5.0,5.0,0.0,0.0,0.0,0.0,0.0,ABCBCBCBCBC,True +943,0.0,0.0,0.0,68.0,0.0,0.0,0.0,69.0,HHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +944,29.0,0.0,0.0,0.0,0.0,29.0,1.0,0.0,GAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +945,0.0,0.0,1.0,0.0,0.0,0.0,81.0,82.0,CHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +946,89.0,0.0,89.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +947,0.0,0.0,0.0,78.0,1.0,0.0,0.0,0.0,EDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +948,90.0,1.0,0.0,0.0,0.0,0.0,91.0,0.0,BGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +949,0.0,0.0,0.0,86.0,1.0,0.0,0.0,86.0,EHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +950,0.0,0.0,0.0,42.0,1.0,0.0,42.0,0.0,EDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +951,85.0,0.0,0.0,84.0,1.0,0.0,0.0,0.0,EADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +952,90.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +953,0.0,0.0,1.0,0.0,0.0,90.0,0.0,0.0,CFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +954,62.0,0.0,0.0,1.0,0.0,62.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +955,0.0,20.0,20.0,0.0,1.0,0.0,0.0,0.0,EBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +956,0.0,0.0,37.0,0.0,0.0,1.0,0.0,38.0,FHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +957,98.0,1.0,0.0,0.0,0.0,98.0,0.0,0.0,BFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +958,0.0,1.0,0.0,0.0,189.0,0.0,0.0,0.0,BEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +959,0.0,0.0,0.0,9.0,0.0,1.0,8.0,0.0,FDGDGDGDGDGDGDGDGD,True +960,0.0,68.0,0.0,0.0,0.0,0.0,0.0,69.0,HHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +961,0.0,0.0,0.0,138.0,0.0,0.0,0.0,0.0,DDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +962,0.0,0.0,0.0,0.0,1.0,30.0,0.0,30.0,EHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +963,0.0,0.0,0.0,80.0,80.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +964,77.0,0.0,0.0,1.0,0.0,0.0,0.0,78.0,DHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +965,0.0,0.0,0.0,58.0,58.0,0.0,1.0,0.0,GEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +966,0.0,0.0,0.0,1.0,35.0,34.0,0.0,0.0,DEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +967,0.0,60.0,0.0,60.0,0.0,1.0,0.0,0.0,FDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +968,0.0,1.0,80.0,0.0,81.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +969,0.0,1.0,0.0,0.0,0.0,0.0,81.0,81.0,BGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +970,16.0,0.0,0.0,16.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADA,True +971,0.0,0.0,0.0,0.0,78.0,77.0,0.0,0.0,EFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +972,0.0,0.0,10.0,1.0,0.0,10.0,0.0,0.0,DFCFCFCFCFCFCFCFCFCFC,True +973,0.0,0.0,0.0,0.0,0.0,44.0,1.0,44.0,GHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +974,0.0,36.0,0.0,0.0,0.0,36.0,1.0,0.0,GFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +975,0.0,87.0,0.0,0.0,0.0,0.0,87.0,0.0,BGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +976,42.0,0.0,42.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True 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b/tests/results/nb_gm_001_3back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,0.0,65.0,132.0,0.0,0.0,0.0,0.0,1.0,HCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCC,True +1,51.0,0.0,52.0,52.0,0.0,0.0,0.0,1.0,HCDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACD,True +2,0.0,61.0,0.0,62.0,0.0,0.0,61.0,1.0,HDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGD,True +3,40.0,0.0,0.0,1.0,0.0,0.0,0.0,80.0,DHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHA,True +4,4.0,0.0,1.0,0.0,0.0,6.0,0.0,0.0,CAFFAFFAFFA,True 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+62,0.0,1.0,0.0,0.0,59.0,0.0,60.0,59.0,BGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEG,True +63,0.0,0.0,0.0,0.0,0.0,0.0,1.0,167.0,GHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +64,48.0,0.0,0.0,0.0,1.0,0.0,0.0,95.0,EHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHA,True +65,0.0,0.0,0.0,65.0,66.0,0.0,67.0,0.0,GGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGE,True +66,35.0,71.0,0.0,0.0,0.0,0.0,0.0,0.0,BBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBAB,True +67,50.0,0.0,0.0,50.0,50.0,0.0,0.0,1.0,HAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAED,True +68,0.0,0.0,4.0,0.0,0.0,0.0,5.0,3.0,GCGHCGHCGHCG,True +69,0.0,0.0,5.0,0.0,0.0,0.0,1.0,10.0,GCHHCHHCHHCHHCHH,True +70,0.0,0.0,19.0,0.0,19.0,20.0,0.0,0.0,FECFECFECFECFECFECFECFECFECFECFECFECFECFECFECFECFECFECFECF,True +71,0.0,0.0,1.0,0.0,0.0,0.0,43.0,84.0,CGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHG,True +72,6.0,0.0,0.0,0.0,6.0,6.0,0.0,0.0,FAEFAEFAEFAEFAEFAE,True +73,0.0,0.0,35.0,35.0,35.0,0.0,0.0,1.0,HECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECD,True +74,25.0,0.0,26.0,0.0,1.0,0.0,0.0,25.0,ECAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHC,True +75,61.0,0.0,0.0,60.0,0.0,60.0,0.0,1.0,HAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDA,True +76,0.0,0.0,0.0,41.0,0.0,0.0,0.0,20.0,DHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDD,True +77,0.0,0.0,1.0,0.0,0.0,15.0,15.0,14.0,CGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGF,True +78,6.0,0.0,1.0,6.0,0.0,0.0,0.0,6.0,CHDAHDAHDAHDAHDAHDA,True +79,0.0,124.0,0.0,62.0,0.0,0.0,0.0,0.0,BBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBD,True +80,0.0,0.0,32.0,0.0,0.0,31.0,31.0,0.0,CGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCF,True 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+317,61.0,0.0,0.0,0.0,0.0,61.0,1.0,61.0,GFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHA,True +318,0.0,0.0,0.0,7.0,7.0,8.0,1.0,0.0,GFEDFEDFEDFEDFEDFEDFEDF,True +319,7.0,0.0,0.0,0.0,1.0,3.0,0.0,0.0,EAAFAAFAAFA,True +320,0.0,48.0,0.0,48.0,0.0,0.0,0.0,48.0,BHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHD,True +321,0.0,23.0,23.0,0.0,0.0,0.0,0.0,24.0,HBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCH,True +322,0.0,0.0,1.0,0.0,0.0,30.0,30.0,30.0,CGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFH,True +323,48.0,0.0,0.0,47.0,47.0,0.0,1.0,0.0,GADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEA,True 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+401,0.0,55.0,55.0,0.0,0.0,1.0,54.0,0.0,FCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCB,True +402,47.0,0.0,0.0,0.0,1.0,47.0,0.0,47.0,EAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFH,True +403,56.0,0.0,0.0,0.0,58.0,0.0,0.0,56.0,EEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAE,True +404,0.0,39.0,0.0,0.0,39.0,1.0,40.0,0.0,FGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEG,True 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it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/src/main/scala/org/xcit/nback/markov/models/State.scala b/src/main/scala/org/xcit/nback/markov/models/State.scala deleted file mode 100644 index fbbd844..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/State.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * A Single state with a label in Markov chain - * @param label A simple string label, representing the state and node - */ -class State(val label: String) { - - /** - * Keep track of transitions from this state to other states. - */ - val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() -} diff --git a/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/src/main/scala/org/xcit/nback/markov/models/Transition.scala deleted file mode 100644 index bc20a9e..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/Transition.scala +++ /dev/null @@ -1,8 +0,0 @@ -package org.xcit.nback.markov.models - -/** - * A Single transition in Markov chain graph. It is stored in "from" node. - * @param to the ending node of the edge - * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). - */ -case class Transition(to: State, probability: Double = 0.0) diff --git a/src/test/scala/ThreeBackBenchmark.scala b/src/test/scala/ThreeBackBenchmark.scala deleted file mode 100644 index 0c7dad9..0000000 --- a/src/test/scala/ThreeBackBenchmark.scala +++ /dev/null @@ -1,7 +0,0 @@ - -/** - * TODO Benchmark 3-back simple sequence generator - */ -class ThreeBackBenchmark { - -} diff --git a/tests/benchmark_diagrams.py b/tests/benchmark_diagrams.py new file mode 100644 index 0000000..8fa448e --- /dev/null +++ b/tests/benchmark_diagrams.py @@ -0,0 +1,159 @@ +import pandas as pd +import numpy as np +from matplotlib import pyplot as plt + +import benchmarks.common as common + + +def tlratio(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2,ignore_index=True) + stats = [] + for trials in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == trials) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == trials) + targets2 = data[alg2].targets if alg2.shape[0] > 0 else np.nan + targets4 = data[alg4].targets if alg4.shape[0] > 0 else np.nan + lures2 = data[alg2].lures if alg2.shape[0] > 0 else np.nan + lures4 = data[alg4].lures if alg4.shape[0] > 0 else np.nan + stats.append([trials, (targets2/lures2).mean(), (targets4/lures4).mean()]) + stats = pd.DataFrame(stats, columns=['trials', 'tl2', 'tl4']) #.dropna(subset=['skewness']) + + plt.style.use('ggplot') + + plt.ylim(bottom=0, top=30) + plt.scatter(stats.trials, stats.tl2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl2[idx], 1)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.tl4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl4[idx], 2)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('T:L Ratio') + plt.ylabel('T:L Ratio') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_tlratio.png', bbox_inches='tight') + plt.show() + + +def time_per_trial(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for t in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == t) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == t) + time2 = data[alg2].time.mean() * 1000 if alg2.shape[0] > 0 else np.nan + time4 = data[alg4].time.mean() * 1000 if alg4.shape[0] > 0 else np.nan + stats.append([t, time2, time4]) + stats = pd.DataFrame(stats, columns=['trials', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.trials, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time2[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time4[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2v4_time_trials.png', bbox_inches='tight') + plt.show() + +def time_profiles(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 8): + alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + time2 = data[alg2].time.mean() * 1000 + time4 = data[alg4].time.mean() * 1000 + stats.append([ni, time2, time4]) + stats = pd.DataFrame(stats, columns=['n', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.n, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.time2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + plt.scatter(stats.n, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.time4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_time_n.png', bbox_inches='tight') + plt.show() + +def skewness(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 9): + all_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + skewed_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) & data.skewed + all_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + skewed_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) & data.skewed + num_of_sequences2 = data[all_alg2].shape[0] + skewed_sequences2 = data[skewed_alg2].shape[0] + num_of_sequences4 = data[all_alg4].shape[0] + skewed_sequences4 = data[skewed_alg4].shape[0] + skewness2 = skewed_sequences2 * 100.0 / num_of_sequences2 if (num_of_sequences2>0) else 0 + skewness4 = skewed_sequences4 * 100.0 / num_of_sequences4 if (num_of_sequences4>0) else 0 + stats.append([ni, skewness2, skewness4]) + stats = pd.DataFrame(stats, columns=['n', 'skewness2', 'skewness4']) #.dropna(subset=['skewness']) + + + plt.style.use('ggplot') + plt.scatter(stats.n, stats.skewness2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.skewness2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + + plt.scatter(stats.n, stats.skewness4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.skewness4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Skewness') + plt.ylabel('Skewed Blocks (%)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_skewness.png', bbox_inches='tight') + plt.show() + +if __name__ == "__main__": + tlratio() + skewness() + time_profiles() + time_per_trial() diff --git a/tests/benchmark_skewness.py b/tests/benchmark_skewness.py new file mode 100644 index 0000000..f468b4d --- /dev/null +++ b/tests/benchmark_skewness.py @@ -0,0 +1,97 @@ +import random +import heapq +import csv + +# Common parameters +alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'] +trials_range = (10, 40) +n = 3 +sample_size = 100 + + +def to_benchmark_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [str(ralph_skewed)] + +def benchmark_nb_gm_001(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_001') + + +def benchmark_nb_gm_002(filename): + import generators.nb_gm_002 as nb_gm_002 + + generator = nb_gm_002.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + # print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_002') + + +def benchmark_nb_gm_003(filename): + import generators.nb_gm_003 as nb_gm_003 + + generator = nb_gm_003.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + print(f"sequence {i}/{sample_size}: {trials} trials") + seq = generator.generate(trials) + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_003') + + +def show_skweness_diagram(filename, choices, title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + print(filename) + data = pd.read_csv(filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) #.dropna(subset=['skewness']) + #print(stats.trials) + #plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'{title}.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + benchmark_nb_gm_003('../benchmarks/nb_gm_003_2back.csv') diff --git a/tests/common.py b/tests/common.py new file mode 100644 index 0000000..e40c0df --- /dev/null +++ b/tests/common.py @@ -0,0 +1,27 @@ + + +# Common benchmark parameters +choices = alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F'] +trials_range = (10, 65) +n = 4 +sample_size = 100 + + +def count_targets_and_lures(seq, n): + mask = 'D'*n + for index in range(n, len(seq)): + if seq[index] == seq[index - n]: + mask += 'T' + elif seq[index] in seq[index - n - 1:index - n + 1]: + mask += 'L' + else: + mask += 'D' + return mask.count('T'), mask.count('L') + + +def skewness(seq, choices): + import heapq + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return ralph_skewed diff --git a/tests/nb_gm_001_bm.py b/tests/nb_gm_001_bm.py new file mode 100644 index 0000000..54f6cb3 --- /dev/null +++ b/tests/nb_gm_001_bm.py @@ -0,0 +1,75 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq) , str(ralph_skewed)] + + +def benchmark(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets / s.trials, axis=1) + plt.scatter(data.trials, data.targets_ratio, alpha=0.2) + plt.show() + +if __name__ == '__main__': + alg = 'nb_gm_001' + fn = f'results/{alg}_{n}back.csv' + benchmark(fn) + # skewness_diagram(fn, alg) + targets_ratio_diagram(fn, alg) diff --git a/tests/nb_gm_002_bm.py b/tests/nb_gm_002_bm.py new file mode 100644 index 0000000..c8af543 --- /dev/null +++ b/tests/nb_gm_002_bm.py @@ -0,0 +1,105 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq), str(ralph_skewed)] + + +def benchmark(filename): + from generators.nb_gm_002 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials, int(trials/3), 0, 0) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +import time +import numpy as np +import pandas as pd + +import benchmarks.common as common + +def profile(): + from generators.nb_gm_002 import SequenceGenerator + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, int(lures/2), int(lures/2)) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('benchmarks/results/nb_gm_002_profile.csv', sep=',', encoding='utf-8') + +if __name__ == '__main__': + alg = 'nb_gm_002' + fn = f'results/{alg}_{n}back.csv' + profile() diff --git a/tests/nb_gm_003_bm.py b/tests/nb_gm_003_bm.py new file mode 100644 index 0000000..fa6c19a --- /dev/null +++ b/tests/nb_gm_003_bm.py @@ -0,0 +1,114 @@ +import heapq +import csv +import random +import time + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq, time_per_block): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [time_per_block, ''.join(seq), str(ralph_skewed)] + + +def benchmark_skewness(filename): + from generators.nb_gm_003 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['time_per_block', 'seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + targets = trials / 3 + t = time.time() + seq = generator.generate(trials, targets) + t = time.time() - t + print(f"sequence {i}/{sample_size}: {trials} trials, took {t}s.") + writer.writerow(to_csv_row(i, seq, t)) + plot_skewness(fn, 'nb_gm_003') + + +def plot_skewness(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def plot_targets_ratio(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +def benchmark_targets_ratio(): + pass + +def benchmark_chunking(): + pass + + +def benchmark_n(): + pass + + +def plot_timing(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['time_per_trial'] = data.apply(lambda s: s.time_per_block / s.trials, axis=1) + plt.style.use('ggplot') + plt.title(f"{figure_title} - average time to generate a trial") + plt.ylabel('time (s)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.time_per_trial, alpha=0.5) + + # draw fitted curve + # import numpy as np + # p = np.poly1d(np.polyfit(data.trials, data.time_per_trial, 3)) + # plt.plot(data.trials, p(data.trials), color='red') + + plt.savefig(f'results/{figure_title}_timing.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + alg = 'nb_gm_003' + fn = f'results/{alg}_{n}back.csv' + benchmark_skewness(fn) diff --git a/tests/nb_gm_004_bm.py b/tests/nb_gm_004_bm.py new file mode 100644 index 0000000..b4ad4a8 --- /dev/null +++ b/tests/nb_gm_004_bm.py @@ -0,0 +1,26 @@ +import time +import numpy as np +import pandas as pd + +import tests.common as common +from generators.nb_gm_004 import SequenceGenerator + +def run(): + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, lures) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('tests/results/nb_gm_004_profile.csv', sep=',', encoding='utf-8') diff --git a/tests/results/2v4_time_trials.png b/tests/results/2v4_time_trials.png new file mode 100644 index 0000000..9be91b4 --- /dev/null +++ b/tests/results/2v4_time_trials.png Binary files differ diff --git a/tests/results/2vs4_skewness.png b/tests/results/2vs4_skewness.png new file mode 100644 index 0000000..a488e1f --- /dev/null +++ b/tests/results/2vs4_skewness.png Binary files differ diff --git a/tests/results/2vs4_time_n.png b/tests/results/2vs4_time_n.png new file mode 100644 index 0000000..d022ed0 --- /dev/null +++ b/tests/results/2vs4_time_n.png Binary files differ diff --git a/tests/results/2vs4_tlratio.png b/tests/results/2vs4_tlratio.png new file mode 100644 index 0000000..b76f296 --- /dev/null +++ b/tests/results/2vs4_tlratio.png Binary files differ diff --git a/tests/results/nb_gm_001_2back.csv b/tests/results/nb_gm_001_2back.csv new file mode 100644 index 0000000..f6ad25e --- /dev/null +++ b/tests/results/nb_gm_001_2back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,0.0,1.0,0.0,55.0,56.0,0.0,0.0,0.0,BEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True 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+364,0.0,0.0,0.0,1.0,0.0,31.0,0.0,31.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +365,0.0,0.0,0.0,24.0,0.0,23.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +366,0.0,15.0,0.0,0.0,16.0,0.0,0.0,0.0,EEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +367,22.0,0.0,0.0,0.0,0.0,0.0,1.0,22.0,GHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +368,0.0,25.0,0.0,0.0,0.0,0.0,25.0,0.0,BGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +369,0.0,0.0,0.0,100.0,1.0,0.0,0.0,0.0,EDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +370,0.0,17.0,0.0,17.0,1.0,0.0,0.0,0.0,EBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +371,0.0,1.0,49.0,0.0,49.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True 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+377,27.0,0.0,0.0,29.0,0.0,0.0,0.0,0.0,DDADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +378,81.0,0.0,0.0,81.0,0.0,0.0,0.0,1.0,HADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +379,1.0,0.0,9.0,0.0,8.0,0.0,0.0,0.0,ACECECECECECECECEC,True +380,1.0,0.0,0.0,32.0,33.0,0.0,0.0,0.0,AEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +381,5.0,0.0,5.0,0.0,1.0,0.0,0.0,0.0,ECACACACACA,True +382,0.0,0.0,0.0,96.0,0.0,0.0,98.0,0.0,GGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +383,0.0,86.0,0.0,0.0,0.0,85.0,0.0,0.0,BBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +384,0.0,0.0,28.0,0.0,1.0,0.0,0.0,28.0,ECHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +385,0.0,1.0,119.0,0.0,0.0,0.0,0.0,0.0,BCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +386,0.0,0.0,93.0,0.0,0.0,93.0,1.0,0.0,GCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCF,True +387,92.0,0.0,1.0,0.0,92.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +388,0.0,186.0,0.0,0.0,0.0,0.0,0.0,0.0,BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +389,1.0,74.0,0.0,0.0,0.0,0.0,0.0,0.0,ABBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +390,0.0,0.0,0.0,0.0,1.0,86.0,0.0,87.0,EHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +391,61.0,0.0,0.0,61.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +392,0.0,0.0,0.0,1.0,16.0,0.0,0.0,15.0,DEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +393,118.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +394,0.0,0.0,0.0,0.0,0.0,75.0,0.0,1.0,HFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +395,30.0,0.0,0.0,0.0,0.0,0.0,0.0,30.0,AHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +396,65.0,0.0,0.0,0.0,0.0,1.0,0.0,65.0,FAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +397,0.0,0.0,0.0,55.0,56.0,0.0,0.0,0.0,EEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +398,26.0,0.0,0.0,25.0,1.0,0.0,0.0,0.0,EADADADADADADADADADADADADADADADADADADADADADADADADADA,True +399,0.0,0.0,60.0,0.0,0.0,0.0,1.0,59.0,GCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +400,1.0,0.0,0.0,0.0,160.0,0.0,0.0,0.0,AEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +401,1.0,0.0,31.0,0.0,0.0,31.0,0.0,0.0,AFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +402,0.0,0.0,0.0,15.0,1.0,0.0,0.0,0.0,EDDDDDDDDDDDDDDD,True +403,0.0,0.0,0.0,54.0,55.0,0.0,0.0,1.0,HEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +404,0.0,0.0,0.0,27.0,0.0,27.0,0.0,1.0,HFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +405,0.0,0.0,0.0,1.0,0.0,15.0,0.0,15.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +406,0.0,95.0,0.0,94.0,0.0,1.0,0.0,0.0,FBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +407,0.0,0.0,15.0,14.0,0.0,0.0,0.0,0.0,CCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +408,78.0,78.0,0.0,0.0,0.0,0.0,1.0,0.0,GBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +409,0.0,0.0,72.0,1.0,0.0,0.0,72.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +410,55.0,0.0,1.0,0.0,0.0,0.0,55.0,0.0,CAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +411,0.0,59.0,0.0,0.0,0.0,60.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +412,61.0,0.0,0.0,61.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +413,0.0,1.0,0.0,75.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +414,0.0,53.0,0.0,0.0,0.0,0.0,52.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +415,0.0,0.0,16.0,0.0,1.0,0.0,0.0,15.0,ECHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +416,0.0,0.0,0.0,39.0,0.0,0.0,0.0,38.0,DHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +417,96.0,0.0,1.0,95.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +418,28.0,0.0,1.0,27.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +419,0.0,1.0,92.0,92.0,0.0,0.0,0.0,0.0,BCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +420,1.0,0.0,20.0,0.0,20.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECE,True +421,0.0,90.0,0.0,0.0,0.0,0.0,89.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +422,10.0,0.0,0.0,0.0,0.0,1.0,11.0,0.0,FGAGAGAGAGAGAGAGAGAGAG,True +423,0.0,0.0,0.0,74.0,73.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +424,0.0,0.0,127.0,0.0,0.0,0.0,1.0,0.0,GCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +425,1.0,9.0,0.0,0.0,0.0,9.0,0.0,0.0,AFBFBFBFBFBFBFBFBFB,True +426,0.0,0.0,84.0,0.0,0.0,0.0,0.0,84.0,HCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +427,33.0,0.0,0.0,34.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +428,1.0,30.0,0.0,30.0,0.0,0.0,0.0,0.0,ABDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +429,0.0,0.0,67.0,0.0,1.0,67.0,0.0,0.0,EFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +430,62.0,0.0,0.0,63.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +431,1.0,9.0,9.0,0.0,0.0,0.0,0.0,0.0,ABCBCBCBCBCBCBCBCBC,True +432,15.0,0.0,0.0,0.0,0.0,0.0,14.0,0.0,AAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +433,0.0,1.0,0.0,65.0,66.0,0.0,0.0,0.0,BEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +434,0.0,160.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +435,0.0,0.0,1.0,0.0,42.0,42.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +436,0.0,0.0,55.0,0.0,55.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +437,0.0,0.0,0.0,1.0,0.0,73.0,0.0,73.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +438,79.0,0.0,0.0,0.0,78.0,0.0,0.0,0.0,AAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +439,0.0,0.0,67.0,0.0,0.0,0.0,66.0,1.0,HCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +440,0.0,0.0,77.0,0.0,0.0,1.0,0.0,76.0,FCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +441,0.0,0.0,0.0,0.0,153.0,0.0,0.0,1.0,HEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +442,0.0,88.0,88.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +443,0.0,0.0,0.0,20.0,22.0,0.0,0.0,0.0,EEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +444,41.0,0.0,42.0,0.0,0.0,0.0,1.0,0.0,GCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +445,0.0,0.0,0.0,47.0,0.0,46.0,0.0,1.0,HDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +446,1.0,0.0,0.0,0.0,86.0,0.0,0.0,87.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +447,56.0,56.0,0.0,0.0,0.0,0.0,0.0,1.0,HABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +448,0.0,0.0,0.0,0.0,11.0,0.0,0.0,10.0,EEHEHEHEHEHEHEHEHEHEH,True +449,0.0,0.0,0.0,0.0,0.0,1.0,92.0,92.0,FGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +450,0.0,0.0,0.0,6.0,5.0,1.0,0.0,0.0,FDEDEDEDEDED,True +451,66.0,1.0,67.0,0.0,0.0,0.0,0.0,0.0,BCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +452,0.0,0.0,0.0,13.0,0.0,1.0,12.0,0.0,FDGDGDGDGDGDGDGDGDGDGDGDGD,True +453,1.0,0.0,0.0,0.0,56.0,0.0,56.0,0.0,AEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +454,15.0,0.0,0.0,0.0,0.0,0.0,0.0,16.0,HAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +455,0.0,21.0,1.0,0.0,21.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True +456,93.0,0.0,1.0,0.0,92.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +457,1.0,0.0,0.0,0.0,35.0,0.0,0.0,35.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +458,13.0,0.0,0.0,0.0,1.0,0.0,13.0,0.0,EAGAGAGAGAGAGAGAGAGAGAGAGAG,True +459,0.0,0.0,65.0,0.0,1.0,0.0,65.0,0.0,ECGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +460,0.0,0.0,95.0,1.0,0.0,95.0,0.0,0.0,DFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +461,15.0,0.0,0.0,0.0,1.0,0.0,0.0,15.0,EHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +462,0.0,0.0,198.0,0.0,1.0,0.0,0.0,0.0,ECCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +463,84.0,84.0,0.0,0.0,1.0,0.0,0.0,0.0,EABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +464,0.0,0.0,0.0,0.0,0.0,60.0,0.0,61.0,HFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +465,0.0,179.0,0.0,1.0,0.0,0.0,0.0,0.0,DBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +466,1.0,0.0,90.0,0.0,89.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +467,0.0,35.0,0.0,0.0,0.0,34.0,0.0,0.0,BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +468,0.0,0.0,0.0,1.0,7.0,0.0,0.0,7.0,DHEHEHEHEHEHEHE,True +469,0.0,0.0,0.0,0.0,92.0,0.0,91.0,0.0,EEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +470,0.0,0.0,46.0,0.0,0.0,1.0,46.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +471,0.0,0.0,0.0,0.0,0.0,1.0,158.0,0.0,FGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +472,1.0,0.0,0.0,0.0,0.0,58.0,0.0,59.0,AHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +473,0.0,0.0,6.0,1.0,0.0,0.0,6.0,0.0,DCGCGCGCGCGCG,True +474,0.0,0.0,0.0,0.0,0.0,98.0,0.0,97.0,FFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +475,0.0,87.0,0.0,0.0,0.0,0.0,0.0,85.0,BBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +476,0.0,0.0,33.0,0.0,0.0,0.0,1.0,33.0,GHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +477,45.0,0.0,0.0,0.0,46.0,0.0,0.0,0.0,EAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +478,0.0,0.0,0.0,77.0,0.0,0.0,75.0,0.0,DDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +479,73.0,1.0,73.0,0.0,0.0,0.0,0.0,0.0,BACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +480,0.0,1.0,0.0,0.0,37.0,37.0,0.0,0.0,BEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +481,0.0,92.0,93.0,0.0,0.0,1.0,0.0,0.0,FCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +482,0.0,0.0,0.0,1.0,0.0,0.0,0.0,24.0,DHHHHHHHHHHHHHHHHHHHHHHHH,True +483,25.0,0.0,0.0,1.0,0.0,25.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +484,0.0,0.0,0.0,0.0,0.0,37.0,0.0,36.0,FHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +485,21.0,0.0,0.0,1.0,0.0,20.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +486,0.0,35.0,0.0,36.0,0.0,0.0,0.0,1.0,HDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +487,0.0,0.0,1.0,0.0,97.0,98.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +488,0.0,93.0,0.0,0.0,0.0,1.0,0.0,94.0,FHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +489,0.0,1.0,0.0,93.0,0.0,0.0,93.0,0.0,BGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +490,0.0,0.0,0.0,70.0,0.0,0.0,72.0,0.0,GGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +491,86.0,0.0,0.0,0.0,1.0,86.0,0.0,0.0,EFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +492,0.0,65.0,1.0,0.0,0.0,65.0,0.0,0.0,CBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +493,0.0,0.0,0.0,69.0,0.0,0.0,0.0,1.0,HDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +494,0.0,0.0,144.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +495,0.0,45.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +496,0.0,0.0,0.0,28.0,0.0,27.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +497,0.0,72.0,0.0,0.0,0.0,1.0,73.0,0.0,FGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +498,0.0,0.0,41.0,0.0,1.0,0.0,40.0,0.0,ECGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +499,0.0,1.0,0.0,0.0,0.0,131.0,0.0,0.0,BFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +500,17.0,0.0,0.0,1.0,0.0,17.0,0.0,0.0,DFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +501,19.0,0.0,0.0,19.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADA,True +502,1.0,0.0,0.0,0.0,51.0,0.0,52.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +503,1.0,0.0,0.0,0.0,0.0,0.0,29.0,29.0,AGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +504,36.0,0.0,0.0,1.0,0.0,35.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +505,0.0,0.0,0.0,20.0,0.0,0.0,1.0,20.0,GDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +506,0.0,0.0,0.0,163.0,0.0,0.0,0.0,1.0,HDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +507,22.0,23.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABAB,True +508,0.0,1.0,0.0,0.0,0.0,0.0,41.0,42.0,BHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +509,0.0,0.0,0.0,45.0,1.0,0.0,0.0,44.0,EDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True 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+671,99.0,0.0,1.0,0.0,98.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +672,68.0,0.0,0.0,0.0,0.0,0.0,67.0,1.0,HAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGA,True +673,0.0,0.0,0.0,26.0,27.0,0.0,1.0,0.0,GEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +674,31.0,0.0,0.0,0.0,32.0,0.0,0.0,1.0,HEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +675,0.0,0.0,0.0,0.0,42.0,0.0,41.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +676,0.0,0.0,50.0,0.0,0.0,0.0,1.0,50.0,GCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +677,0.0,25.0,0.0,24.0,0.0,0.0,0.0,0.0,BBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +678,0.0,0.0,0.0,0.0,1.0,10.0,9.0,0.0,EFGFGFGFGFGFGFGFGFGF,True +679,65.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,DAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +680,0.0,23.0,0.0,0.0,0.0,0.0,23.0,1.0,HGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +681,0.0,1.0,58.0,0.0,0.0,0.0,57.0,0.0,BCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +682,0.0,0.0,0.0,0.0,0.0,68.0,1.0,68.0,GFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +683,0.0,0.0,0.0,0.0,96.0,0.0,96.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +684,1.0,0.0,0.0,0.0,66.0,0.0,66.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +685,0.0,0.0,0.0,0.0,0.0,1.0,0.0,21.0,FHHHHHHHHHHHHHHHHHHHHH,True +686,0.0,88.0,0.0,87.0,0.0,0.0,0.0,0.0,BDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +687,0.0,0.0,19.0,19.0,0.0,0.0,1.0,0.0,GDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +688,0.0,42.0,1.0,0.0,41.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +689,0.0,0.0,0.0,0.0,0.0,60.0,61.0,0.0,GGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +690,0.0,23.0,23.0,0.0,0.0,0.0,1.0,0.0,GBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +691,86.0,86.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +692,35.0,35.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +693,57.0,0.0,0.0,0.0,0.0,58.0,1.0,0.0,GFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +694,0.0,0.0,30.0,30.0,1.0,0.0,0.0,0.0,EDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +695,19.0,18.0,0.0,1.0,0.0,0.0,0.0,0.0,DABABABABABABABABABABABABABABABABABABA,True +696,0.0,0.0,0.0,1.0,0.0,56.0,0.0,57.0,DHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +697,10.0,0.0,1.0,0.0,0.0,0.0,0.0,11.0,CHAHAHAHAHAHAHAHAHAHAH,True +698,0.0,0.0,89.0,0.0,88.0,0.0,1.0,0.0,GCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +699,0.0,0.0,87.0,0.0,86.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +700,17.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAA,True +701,0.0,0.0,66.0,65.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +702,0.0,0.0,1.0,0.0,0.0,0.0,123.0,0.0,CGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +703,0.0,118.0,0.0,0.0,1.0,0.0,0.0,0.0,EBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +704,0.0,0.0,0.0,0.0,0.0,0.0,0.0,132.0,HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +705,0.0,0.0,0.0,0.0,0.0,23.0,1.0,23.0,GHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +706,0.0,0.0,0.0,0.0,6.0,5.0,0.0,0.0,EFEFEFEFEFE,True +707,18.0,0.0,0.0,16.0,0.0,0.0,0.0,0.0,AADADADADADADADADADADADADADADADADA,True +708,0.0,72.0,0.0,0.0,0.0,71.0,0.0,1.0,HBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +709,0.0,0.0,54.0,0.0,0.0,1.0,0.0,55.0,FHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +710,0.0,1.0,87.0,0.0,87.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +711,0.0,0.0,1.0,63.0,0.0,0.0,0.0,64.0,CHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +712,78.0,0.0,78.0,0.0,0.0,1.0,0.0,0.0,FCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +713,0.0,80.0,0.0,0.0,0.0,81.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +714,0.0,1.0,0.0,0.0,0.0,0.0,40.0,39.0,BGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +715,0.0,0.0,7.0,0.0,6.0,0.0,0.0,0.0,CCECECECECECE,True +716,35.0,0.0,0.0,0.0,0.0,0.0,0.0,33.0,AAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +717,0.0,0.0,0.0,1.0,73.0,0.0,0.0,72.0,DEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +718,0.0,0.0,90.0,0.0,0.0,1.0,89.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +719,1.0,0.0,0.0,67.0,0.0,0.0,0.0,66.0,ADHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +720,56.0,0.0,0.0,0.0,56.0,0.0,1.0,0.0,GAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +721,0.0,0.0,0.0,1.0,0.0,0.0,49.0,49.0,DHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +722,0.0,0.0,0.0,117.0,0.0,1.0,0.0,0.0,FDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +723,0.0,0.0,86.0,1.0,0.0,0.0,85.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +724,0.0,0.0,31.0,0.0,0.0,0.0,0.0,30.0,CCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +725,1.0,0.0,0.0,0.0,98.0,0.0,98.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +726,1.0,84.0,84.0,0.0,0.0,0.0,0.0,0.0,ACBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +727,0.0,56.0,56.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +728,0.0,1.0,0.0,24.0,24.0,0.0,0.0,0.0,BDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +729,37.0,0.0,0.0,0.0,0.0,37.0,0.0,0.0,FAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +730,0.0,0.0,91.0,0.0,0.0,0.0,91.0,0.0,GCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +731,98.0,0.0,99.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +732,0.0,0.0,0.0,0.0,99.0,1.0,98.0,0.0,FEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +733,0.0,0.0,30.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +734,12.0,1.0,13.0,0.0,0.0,0.0,0.0,0.0,BCACACACACACACACACACACACAC,True +735,0.0,93.0,1.0,0.0,93.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True 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+852,0.0,1.0,0.0,0.0,136.0,0.0,0.0,0.0,BEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +853,0.0,0.0,0.0,0.0,1.0,0.0,0.0,163.0,EHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +854,74.0,0.0,75.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +855,0.0,0.0,0.0,19.0,0.0,0.0,17.0,0.0,DDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +856,0.0,73.0,0.0,1.0,0.0,0.0,74.0,0.0,DGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True 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+863,0.0,0.0,0.0,32.0,1.0,0.0,32.0,0.0,EGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +864,0.0,0.0,15.0,0.0,1.0,14.0,0.0,0.0,ECFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +865,0.0,1.0,98.0,0.0,0.0,0.0,98.0,0.0,BGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +866,1.0,0.0,0.0,0.0,19.0,0.0,0.0,0.0,AEEEEEEEEEEEEEEEEEEE,True +867,24.0,0.0,0.0,0.0,24.0,0.0,0.0,0.0,AEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +868,0.0,0.0,0.0,74.0,0.0,0.0,0.0,73.0,DHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +869,0.0,78.0,1.0,0.0,0.0,0.0,77.0,0.0,CBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +870,0.0,0.0,1.0,0.0,50.0,0.0,51.0,0.0,CGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +871,0.0,0.0,16.0,0.0,0.0,16.0,0.0,1.0,HFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +872,0.0,0.0,0.0,1.0,28.0,28.0,0.0,0.0,DFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +873,0.0,0.0,65.0,65.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +874,0.0,34.0,0.0,0.0,0.0,35.0,0.0,0.0,FBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +875,0.0,0.0,9.0,0.0,8.0,0.0,0.0,1.0,HCECECECECECECECEC,True +876,0.0,0.0,0.0,0.0,94.0,0.0,94.0,1.0,HEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +877,0.0,18.0,0.0,16.0,0.0,0.0,0.0,0.0,BBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True 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+885,0.0,0.0,0.0,93.0,0.0,93.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDF,True +886,0.0,1.0,0.0,89.0,0.0,89.0,0.0,0.0,BFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +887,0.0,1.0,0.0,0.0,42.0,0.0,0.0,42.0,BHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +888,68.0,0.0,0.0,0.0,1.0,0.0,0.0,67.0,EAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +889,55.0,0.0,0.0,0.0,0.0,57.0,0.0,0.0,FFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +890,25.0,1.0,0.0,0.0,0.0,0.0,26.0,0.0,BGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +891,81.0,0.0,0.0,0.0,80.0,0.0,0.0,0.0,AAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +892,0.0,0.0,1.0,0.0,10.0,0.0,10.0,0.0,CGEGEGEGEGEGEGEGEGEGE,True +893,1.0,0.0,43.0,42.0,0.0,0.0,0.0,0.0,ACDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +894,55.0,54.0,0.0,0.0,0.0,0.0,0.0,0.0,AABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +895,43.0,0.0,0.0,0.0,0.0,1.0,0.0,43.0,FAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +896,1.0,0.0,0.0,0.0,97.0,97.0,0.0,0.0,AEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +897,0.0,25.0,0.0,1.0,0.0,25.0,0.0,0.0,DFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +898,0.0,0.0,0.0,0.0,26.0,26.0,1.0,0.0,GEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +899,0.0,0.0,36.0,0.0,36.0,0.0,0.0,0.0,ECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +900,0.0,0.0,0.0,0.0,1.0,0.0,89.0,88.0,EGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +901,0.0,1.0,142.0,0.0,0.0,0.0,0.0,0.0,BCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +902,1.0,83.0,0.0,83.0,0.0,0.0,0.0,0.0,ABDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +903,0.0,0.0,17.0,0.0,17.0,0.0,0.0,1.0,HECECECECECECECECECECECECECECECECEC,True +904,77.0,77.0,0.0,0.0,0.0,0.0,0.0,0.0,BABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +905,0.0,0.0,0.0,0.0,0.0,0.0,164.0,0.0,GGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +906,0.0,0.0,0.0,89.0,0.0,1.0,0.0,90.0,FHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +907,0.0,0.0,41.0,0.0,0.0,0.0,42.0,0.0,GCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +908,28.0,0.0,0.0,0.0,0.0,28.0,1.0,0.0,GAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +909,0.0,0.0,94.0,0.0,1.0,0.0,95.0,0.0,EGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +910,0.0,0.0,27.0,1.0,27.0,0.0,0.0,0.0,DECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +911,0.0,0.0,0.0,100.0,0.0,1.0,0.0,0.0,FDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +912,0.0,1.0,66.0,0.0,0.0,0.0,66.0,0.0,BGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +913,0.0,23.0,23.0,0.0,0.0,1.0,0.0,0.0,FCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +914,0.0,0.0,0.0,0.0,0.0,0.0,150.0,0.0,GGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +915,0.0,0.0,0.0,0.0,0.0,0.0,1.0,42.0,GHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +916,0.0,147.0,0.0,0.0,0.0,0.0,1.0,0.0,GBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +917,0.0,56.0,0.0,1.0,0.0,0.0,0.0,56.0,DHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +918,0.0,0.0,0.0,0.0,0.0,76.0,76.0,1.0,HFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFG,True +919,0.0,53.0,0.0,0.0,0.0,0.0,0.0,52.0,BHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +920,0.0,0.0,147.0,0.0,0.0,1.0,0.0,0.0,FCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +921,0.0,0.0,0.0,40.0,40.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +922,0.0,82.0,0.0,84.0,0.0,0.0,0.0,0.0,DDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +923,1.0,0.0,0.0,0.0,0.0,0.0,0.0,97.0,AHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +924,0.0,29.0,0.0,0.0,0.0,0.0,0.0,30.0,HHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +925,25.0,0.0,0.0,1.0,0.0,0.0,0.0,25.0,DHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +926,0.0,164.0,0.0,0.0,0.0,0.0,1.0,0.0,GBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +927,89.0,0.0,0.0,0.0,1.0,0.0,90.0,0.0,EGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +928,0.0,0.0,1.0,0.0,41.0,41.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +929,0.0,0.0,1.0,19.0,18.0,0.0,0.0,0.0,CDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +930,0.0,0.0,0.0,0.0,1.0,75.0,75.0,0.0,EGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +931,0.0,0.0,21.0,0.0,0.0,22.0,0.0,0.0,FCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCF,True +932,0.0,0.0,81.0,0.0,80.0,1.0,0.0,0.0,FCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +933,20.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAAAAA,True +934,0.0,40.0,0.0,0.0,0.0,40.0,0.0,0.0,BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +935,0.0,72.0,0.0,0.0,72.0,0.0,1.0,0.0,GBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True +936,56.0,1.0,0.0,56.0,0.0,0.0,0.0,0.0,BADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +937,0.0,0.0,0.0,0.0,0.0,96.0,1.0,0.0,GFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +938,0.0,1.0,0.0,88.0,0.0,0.0,0.0,88.0,BHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +939,1.0,0.0,0.0,0.0,0.0,0.0,0.0,175.0,AHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +940,0.0,0.0,84.0,1.0,83.0,0.0,0.0,0.0,DCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +941,0.0,0.0,83.0,0.0,0.0,0.0,0.0,85.0,HHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +942,1.0,5.0,5.0,0.0,0.0,0.0,0.0,0.0,ABCBCBCBCBC,True +943,0.0,0.0,0.0,68.0,0.0,0.0,0.0,69.0,HHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +944,29.0,0.0,0.0,0.0,0.0,29.0,1.0,0.0,GAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +945,0.0,0.0,1.0,0.0,0.0,0.0,81.0,82.0,CHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +946,89.0,0.0,89.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +947,0.0,0.0,0.0,78.0,1.0,0.0,0.0,0.0,EDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +948,90.0,1.0,0.0,0.0,0.0,0.0,91.0,0.0,BGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +949,0.0,0.0,0.0,86.0,1.0,0.0,0.0,86.0,EHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +950,0.0,0.0,0.0,42.0,1.0,0.0,42.0,0.0,EDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +951,85.0,0.0,0.0,84.0,1.0,0.0,0.0,0.0,EADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +952,90.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +953,0.0,0.0,1.0,0.0,0.0,90.0,0.0,0.0,CFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +954,62.0,0.0,0.0,1.0,0.0,62.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +955,0.0,20.0,20.0,0.0,1.0,0.0,0.0,0.0,EBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +956,0.0,0.0,37.0,0.0,0.0,1.0,0.0,38.0,FHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +957,98.0,1.0,0.0,0.0,0.0,98.0,0.0,0.0,BFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +958,0.0,1.0,0.0,0.0,189.0,0.0,0.0,0.0,BEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +959,0.0,0.0,0.0,9.0,0.0,1.0,8.0,0.0,FDGDGDGDGDGDGDGDGD,True +960,0.0,68.0,0.0,0.0,0.0,0.0,0.0,69.0,HHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +961,0.0,0.0,0.0,138.0,0.0,0.0,0.0,0.0,DDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +962,0.0,0.0,0.0,0.0,1.0,30.0,0.0,30.0,EHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +963,0.0,0.0,0.0,80.0,80.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +964,77.0,0.0,0.0,1.0,0.0,0.0,0.0,78.0,DHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +965,0.0,0.0,0.0,58.0,58.0,0.0,1.0,0.0,GEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +966,0.0,0.0,0.0,1.0,35.0,34.0,0.0,0.0,DEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +967,0.0,60.0,0.0,60.0,0.0,1.0,0.0,0.0,FDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +968,0.0,1.0,80.0,0.0,81.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +969,0.0,1.0,0.0,0.0,0.0,0.0,81.0,81.0,BGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +970,16.0,0.0,0.0,16.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADA,True +971,0.0,0.0,0.0,0.0,78.0,77.0,0.0,0.0,EFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +972,0.0,0.0,10.0,1.0,0.0,10.0,0.0,0.0,DFCFCFCFCFCFCFCFCFCFC,True +973,0.0,0.0,0.0,0.0,0.0,44.0,1.0,44.0,GHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +974,0.0,36.0,0.0,0.0,0.0,36.0,1.0,0.0,GFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +975,0.0,87.0,0.0,0.0,0.0,0.0,87.0,0.0,BGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +976,42.0,0.0,42.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True 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b/tests/results/nb_gm_001_3back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,0.0,65.0,132.0,0.0,0.0,0.0,0.0,1.0,HCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCC,True +1,51.0,0.0,52.0,52.0,0.0,0.0,0.0,1.0,HCDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACD,True +2,0.0,61.0,0.0,62.0,0.0,0.0,61.0,1.0,HDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGD,True +3,40.0,0.0,0.0,1.0,0.0,0.0,0.0,80.0,DHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHA,True +4,4.0,0.0,1.0,0.0,0.0,6.0,0.0,0.0,CAFFAFFAFFA,True 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+62,0.0,1.0,0.0,0.0,59.0,0.0,60.0,59.0,BGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEG,True +63,0.0,0.0,0.0,0.0,0.0,0.0,1.0,167.0,GHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +64,48.0,0.0,0.0,0.0,1.0,0.0,0.0,95.0,EHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHA,True +65,0.0,0.0,0.0,65.0,66.0,0.0,67.0,0.0,GGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGE,True +66,35.0,71.0,0.0,0.0,0.0,0.0,0.0,0.0,BBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBAB,True +67,50.0,0.0,0.0,50.0,50.0,0.0,0.0,1.0,HAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAED,True +68,0.0,0.0,4.0,0.0,0.0,0.0,5.0,3.0,GCGHCGHCGHCG,True +69,0.0,0.0,5.0,0.0,0.0,0.0,1.0,10.0,GCHHCHHCHHCHHCHH,True +70,0.0,0.0,19.0,0.0,19.0,20.0,0.0,0.0,FECFECFECFECFECFECFECFECFECFECFECFECFECFECFECFECFECFECFECF,True +71,0.0,0.0,1.0,0.0,0.0,0.0,43.0,84.0,CGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHG,True +72,6.0,0.0,0.0,0.0,6.0,6.0,0.0,0.0,FAEFAEFAEFAEFAEFAE,True +73,0.0,0.0,35.0,35.0,35.0,0.0,0.0,1.0,HECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECD,True +74,25.0,0.0,26.0,0.0,1.0,0.0,0.0,25.0,ECAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHC,True +75,61.0,0.0,0.0,60.0,0.0,60.0,0.0,1.0,HAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDA,True +76,0.0,0.0,0.0,41.0,0.0,0.0,0.0,20.0,DHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDD,True +77,0.0,0.0,1.0,0.0,0.0,15.0,15.0,14.0,CGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGF,True +78,6.0,0.0,1.0,6.0,0.0,0.0,0.0,6.0,CHDAHDAHDAHDAHDAHDA,True +79,0.0,124.0,0.0,62.0,0.0,0.0,0.0,0.0,BBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBD,True +80,0.0,0.0,32.0,0.0,0.0,31.0,31.0,0.0,CGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCF,True 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+317,61.0,0.0,0.0,0.0,0.0,61.0,1.0,61.0,GFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHA,True +318,0.0,0.0,0.0,7.0,7.0,8.0,1.0,0.0,GFEDFEDFEDFEDFEDFEDFEDF,True +319,7.0,0.0,0.0,0.0,1.0,3.0,0.0,0.0,EAAFAAFAAFA,True +320,0.0,48.0,0.0,48.0,0.0,0.0,0.0,48.0,BHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHD,True +321,0.0,23.0,23.0,0.0,0.0,0.0,0.0,24.0,HBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCH,True +322,0.0,0.0,1.0,0.0,0.0,30.0,30.0,30.0,CGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFH,True +323,48.0,0.0,0.0,47.0,47.0,0.0,1.0,0.0,GADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEA,True 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+401,0.0,55.0,55.0,0.0,0.0,1.0,54.0,0.0,FCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCB,True +402,47.0,0.0,0.0,0.0,1.0,47.0,0.0,47.0,EAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFH,True +403,56.0,0.0,0.0,0.0,58.0,0.0,0.0,56.0,EEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAE,True +404,0.0,39.0,0.0,0.0,39.0,1.0,40.0,0.0,FGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEG,True 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+951,0.0,0.0,0.0,0.0,35.0,1.0,35.0,35.0,FHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEG,True +952,0.0,0.0,1.0,0.0,0.0,0.0,36.0,71.0,CHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHG,True +953,0.0,42.0,0.0,0.0,21.0,0.0,0.0,1.0,HEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBB,True +954,0.0,49.0,0.0,50.0,0.0,0.0,49.0,0.0,DDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBG,True +955,11.0,0.0,0.0,0.0,22.0,0.0,1.0,0.0,GEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAE,True +956,0.0,0.0,0.0,1.0,0.0,18.0,0.0,38.0,DHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHH,True +957,58.0,58.0,60.0,0.0,0.0,0.0,0.0,0.0,CCBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBAC,True +958,19.0,19.0,0.0,0.0,19.0,0.0,0.0,0.0,BEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEA,True +959,0.0,0.0,39.0,0.0,0.0,38.0,0.0,38.0,CFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHC,True +960,0.0,0.0,0.0,80.0,41.0,0.0,0.0,1.0,HEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDE,True +961,0.0,21.0,0.0,22.0,0.0,23.0,0.0,0.0,FDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDF,True +962,0.0,0.0,0.0,0.0,6.0,10.0,0.0,0.0,EFEFFEFFEFFEFFEF,True +963,65.0,65.0,1.0,0.0,65.0,0.0,0.0,0.0,CBEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEA,True +964,0.0,46.0,1.0,0.0,45.0,46.0,0.0,0.0,CFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFB,True +965,64.0,64.0,0.0,0.0,63.0,0.0,1.0,0.0,GABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEAB,True +966,1.0,0.0,47.0,0.0,0.0,48.0,47.0,0.0,AFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGF,True +967,54.0,0.0,54.0,53.0,0.0,0.0,0.0,0.0,ACADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADC,True +968,10.0,0.0,10.0,0.0,12.0,0.0,0.0,0.0,EEACEACEACEACEACEACEACEACEACEACE,True +969,0.0,0.0,0.0,0.0,0.0,0.0,125.0,62.0,GGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGH,True +970,0.0,8.0,1.0,9.0,0.0,0.0,8.0,0.0,CDBGDBGDBGDBGDBGDBGDBGDBGD,True +971,0.0,0.0,0.0,66.0,66.0,67.0,1.0,0.0,GFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEF,True +972,63.0,0.0,0.0,0.0,127.0,0.0,1.0,0.0,GEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAE,True +973,0.0,0.0,11.0,0.0,0.0,0.0,21.0,1.0,HCGGCGGCGGCGGCGGCGGCGGCGGCGGCGGCG,True +974,0.0,0.0,39.0,0.0,0.0,40.0,40.0,0.0,FGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFG,True +975,0.0,0.0,1.0,31.0,0.0,0.0,62.0,0.0,CDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGG,True +976,0.0,54.0,0.0,0.0,0.0,1.0,54.0,55.0,FHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBH,True +977,0.0,0.0,18.0,19.0,0.0,18.0,0.0,0.0,DFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCD,True +978,126.0,63.0,0.0,0.0,1.0,0.0,0.0,0.0,EAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAAB,True +979,19.0,0.0,0.0,0.0,0.0,1.0,0.0,9.0,FAHAAHAAHAAHAAHAAHAAHAAHAAHAA,True +980,0.0,0.0,32.0,32.0,0.0,33.0,0.0,0.0,FDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFC,True +981,15.0,0.0,15.0,0.0,16.0,0.0,0.0,0.0,ECEACEACEACEACEACEACEACEACEACEACEACEACEACEACEA,True +982,0.0,0.0,55.0,0.0,0.0,56.0,57.0,0.0,GFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFG,True +983,0.0,0.0,32.0,0.0,1.0,32.0,31.0,0.0,EFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFC,True +984,0.0,0.0,0.0,41.0,1.0,40.0,40.0,0.0,EDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGD,True +985,0.0,0.0,0.0,0.0,5.0,6.0,5.0,1.0,HFGEFGEFGEFGEFGEF,True +986,0.0,19.0,17.0,0.0,0.0,0.0,0.0,18.0,BBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBH,True +987,0.0,0.0,0.0,0.0,0.0,0.0,6.0,10.0,GHGHHGHHGHHGHHGH,True +988,0.0,0.0,69.0,0.0,36.0,0.0,0.0,0.0,ECECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCE,True +989,1.0,0.0,0.0,0.0,0.0,19.0,0.0,37.0,AHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHF,True +990,67.0,0.0,0.0,0.0,0.0,0.0,0.0,33.0,AHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAA,True +991,0.0,0.0,16.0,18.0,0.0,17.0,0.0,0.0,DFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFD,True +992,1.0,0.0,50.0,50.0,0.0,0.0,49.0,0.0,ACDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCD,True +993,0.0,40.0,39.0,0.0,39.0,0.0,0.0,1.0,HBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEB,True +994,0.0,30.0,1.0,0.0,0.0,0.0,30.0,30.0,CBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGH,True +995,126.0,0.0,1.0,0.0,0.0,0.0,0.0,63.0,CHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAA,True +996,45.0,0.0,45.0,1.0,0.0,0.0,0.0,45.0,DHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHAC,True +997,15.0,0.0,0.0,0.0,29.0,0.0,0.0,0.0,AEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEE,True +998,0.0,4.0,1.0,0.0,0.0,4.0,0.0,4.0,CHBFHBFHBFHBF,True +999,0.0,100.0,0.0,0.0,0.0,0.0,0.0,51.0,HBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBH,True diff --git a/tests/results/nb_gm_002_2back.csv b/tests/results/nb_gm_002_2back.csv new file mode 100644 index 0000000..33538c3 --- /dev/null +++ b/tests/results/nb_gm_002_2back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,4.0,2.0,2.0,2.0,2.0,1.0,0.0,5.0,BHCHDHDAEBEHAFAHAC,True +1,0.0,4.0,1.0,2.0,4.0,0.0,0.0,0.0,DBEBDBCEEBE,True +2,5.0,10.0,14.0,6.0,16.0,18.0,12.0,12.0,CFFGHCFCGHEDCCACECBGEGFGAEBGHFDCEEDCCEGEGCBBBHCCECHBHEHBHDEDAFAFAFHFGFGFGHGHEFFFEFEDHFEFEFBBB,False +3,12.0,15.0,11.0,20.0,13.0,17.0,17.0,22.0,AFAHGHGHGBEBCDDDDHHHABCEHEHEBBBAHADADCFHHHHHFEFCBDDFDGDEFCAGGFEFBDGEHECCBCFFFFFFHGEBBHHCBCACHHDDBFGGGGEGEAFDGDADGDGDGBEBAAHDDFH,False +4,4.0,4.0,8.0,8.0,5.0,7.0,4.0,2.0,FGDGECDCECGCDADAHFDFCFCGAFCDDDABEBHBEFEFBC,False +5,15.0,15.0,15.0,16.0,16.0,14.0,9.0,13.0,HGDGBFDHDADHBBBBBHBAAGBCEABCGFAFAFBGBCBFGDDDEAAAHDFACECECHFHFHFCFHEGEFEFDFDAAHDEECDABFCCCCGBEBDAHCECHCHEDEDEDAGEE,False +6,17.0,17.0,9.0,6.0,15.0,13.0,15.0,12.0,BEBEBHAGCFEHHABAHDEDGHFBFGFCAABAGFFFAFGECEBEAEAFBFCEBEGHGDBEFABABEGEHEHBGBGDADACAGHGHGBGBACGCAHFFBHAECDC,False +7,12.0,7.0,7.0,6.0,9.0,8.0,5.0,6.0,CEGBFEFEFEHCCDEBCCHBBBGAHACBGGDBDADACADHDHFEAEAEFGFAAEAHAFAF,False +8,9.0,13.0,10.0,11.0,12.0,15.0,11.0,12.0,CGCFDBDFHHEHFFGCDHEHCFCFAAEGDCEGHGCFCBBBCBGFGHGDFDBDADHBBEGAGABABHBEBEHGHADAFEFCFDBDEFEHEFEFA,False +9,13.0,26.0,23.0,14.0,20.0,18.0,19.0,27.0,HECEBEFFHFDCCFGBCBDBAHGHGCBBABHEFAFEBEBHBHGGCHBGGCCCCCFCBDDDEDHDEEEAAFAFGFDFCGBGHEHDHGHAFABCGGEHEHFBGBADEBEBEAAHBDCCFGGHHHBHBHGHBDBEEAEGCGCBCHCEFFFFCHDHCHDHABCB,False +10,14.0,18.0,15.0,13.0,15.0,19.0,18.0,11.0,AFACABDDFBBBEBECECGHFBFBECDCEEEDGDBHHGCBDDAFCBAAAGHCHCHEAFBFDHAHCFFAAAHBBBFBFBHGFBCBCFGGGHGDGDFEGEFCFEDGDGAGEGCGEGEFEFAFDGC,False +11,21.0,20.0,21.0,13.0,15.0,26.0,21.0,21.0,EECEFFHGCADHGEGEABCCFDEBABEBGGCACHFHFBFBFBAHGBGCGHDCDABHHAGABFHEBCFEGDFDFDFAFBCBCAHACFGFBFBFBFBDACCBCHFHEGEDFDFCAAAGGEBFAAACACHCHFGFBFGHGHAEAGCCEDDFHHHGHGHGDE,False +12,17.0,26.0,17.0,23.0,17.0,11.0,26.0,21.0,ABGCACGDDFHFHBCEHEAGBGBEBAHEBEBFAAHAFBCEGDGBAHGGGGFGDDDBABABHGGGCGDGHGHDACAEDEFECHGEGDABGCHCDDDDCBCBADAHCHGBGBGEHDCDBBFBABHBHBFBACHDEEHGHECDCDHDEFEDECFGHGBFBD,False +13,24.0,21.0,23.0,20.0,15.0,14.0,30.0,24.0,AHHHHAFEDHAFBFGFCFGADADCDGBBBBGDGEGBCBHGGGGCGFBFAGGGGHEEFEGHGHABCBFHGAGACBBDEDHDHDGBCACAHGCACEHECACHBHDCGCECADGDGDABADHFGCGAGAHHBGFDCHBHCAAABEEFDFDBDBEADAHGEGEHECCCBCFCAHD,False +14,1.0,0.0,2.0,1.0,1.0,1.0,2.0,2.0,DECGCGAHFH,True +15,7.0,7.0,10.0,5.0,8.0,4.0,8.0,9.0,HBABHHEEGAGAGEGHCDEECHCHGBCBCDDAEGCBCGEAEFDFBFBFAGCHCHCHAD,False +16,14.0,19.0,14.0,7.0,10.0,15.0,19.0,7.0,CEAFFGHGEGFDFDCACAGBDEAFCEDDFAHHFDFGBEACGCGBGAFECECFGHCEBAFGEGCBABEBHBHBACAGAGDGHBABCBCBGFGFGFGBBBBFBCBGA,False +17,17.0,15.0,14.0,12.0,10.0,9.0,17.0,6.0,EBACADACGBGBAFGHGHADCDGAAFFFADABAHGDGABBCBCACACECHFBFHDCACDGEBADDEGGGEDADFGFGCGFBBABCBEBDBCHGEGEGECE,False +18,14.0,22.0,17.0,9.0,14.0,10.0,25.0,20.0,EHCHAHEHAHCHCGBGCGCGAEBFBFGGCEFGBGHAHCBABABHHGHGCACHDEDBBABGGDGDEBBBHHGCAEGBFHGEGEGBCCGCDFBBGBFBDAEEHHHCFEFECEHGCGCBHDADFDAGAGAGFBB,False +19,13.0,27.0,12.0,18.0,19.0,17.0,20.0,18.0,BFGCGBHAHAHEFEDBABEBEDADGGGGBAFCGEBDFHBHGHGCBBEGEGBHDHDHBCBCACDBFHHCHBGAGAGEDADADCDCACGHEEEEBDFDFDHDCGGBGDEBBBABEHFHGEFFFBADHEFFCFDEBEBFFEBHBFBG,False +20,11.0,10.0,7.0,8.0,8.0,7.0,11.0,4.0,BGBABGHGCGFBFAEBGGEDEFAHEHACDCDADBGGAGAGADFBFBCBCEFBFDHDACCDAGAEEE,False +21,22.0,20.0,18.0,24.0,13.0,11.0,16.0,21.0,DADADHCACFCHEDAAAHGDDHAGCDEDEGBHAHBDBDBGHHHCHCECAAAEFEDECEDBHFABGBCAGDBEGEBABHFCBBABDFDGHGCBFBCCDHDHDGDHDHCHBGADAFACHEHBDCDAFAFAFAGGCGCFHGBDBEBEG,False +22,8.0,10.0,11.0,7.0,8.0,15.0,4.0,11.0,CBAEGDGEHEBGBFBFBDHCHFHBAEHFFGFCFBFCFEEHABECFFFFACAEHHDCDCDHDHAHCFCBCBAADF,False +23,32.0,19.0,21.0,23.0,13.0,27.0,21.0,27.0,GHCABDGDFFFAHHHEAEHGAGAGHEFEGBCFAFBFGCHCHFHBGCAFFDFDBACACHCHCHBFGFEACAFABEBEBHHGHFHAHGGAGAHAFCGDHDHAFGCBCHDAAAAAAFCFHGEFFBEBEDDDFDBCBDDDCGFAFADBDBEBCAGGHDFDFBCDEAGAHCCEHGHAHCDDDDABAFA,False +24,26.0,30.0,18.0,21.0,29.0,16.0,21.0,21.0,GDGDADAGAGDEHCDBDHAHEHFHAHAFBHBHGCEBHBDBHBHBEEABABABAEECEGEGAGADHDBEEGBCAADHGBFBCEAAHDEBEBFBFBFCCGCEFBABAEDBGFGBGCFCGEACDFEFBHDADFHCEAEBDHDCGBEFGCDCACDEBEGAGAEAEFDFBBEHEGEGHCACEFBHDH,False +25,17.0,15.0,10.0,21.0,16.0,11.0,16.0,22.0,BDBDBHHHAAGAEHEHCHCDADEBGHDAGEBHGAABADADEDECEHAHFBGCGBEHCGADFBHECGHHFFFHFBDDDDDFDFDFHFEDEDACAEAEBDCHHBFBABCBGDGEAECHHGHGEGHDAGGG,False +26,12.0,13.0,16.0,11.0,17.0,10.0,17.0,12.0,GEECBGFEEDHCEFGFEAEAHGEGEDDDHDCDCBHBCBCFCECEGAGAGAHECFCEAAFGFGCEHGHBBBGBGBCBDHEAEFHFHGBCDGGACHCGCDADAEBFBADH,False +27,14.0,11.0,17.0,13.0,14.0,21.0,16.0,19.0,AAECGGEGHCACACACHBHADCECBDHDHDFCFGHGDDEDHHHAHDFDACHBHAFBHHAEEECGGFGEGEBEFCFAEAEFFBFBFDGDGDGHFACCDFHFCGBBHBCGGFGEHEFFFFHFCBCAF,False +28,14.0,15.0,12.0,21.0,15.0,9.0,13.0,21.0,GGHGEDHFCFCACBCADAEEEEAHDGAGHGHEHEHBBECEDBBBDBEGDGBAEABCCABBECDDDFDFHGHGHDHGHGHDADHHCHBHCCBAFHFDDDEDHFHAABDFDFEGEAADBDCH,False +29,18.0,19.0,27.0,26.0,29.0,30.0,16.0,16.0,DEFFFAFAGDGEEBFBFGEBADACADFDCEEDEDFDCDEBBGDGHGHGFFFDFBEBEHCHFDCDCEGFGFHFEFCGBBDCHCGCDADEGEGCFAAEHEHFDACGCEABBDECBCBCEFEFBFCFCFEHEHDGACEBAGCEFEBACCCAEDHDHBCFCDEFFHDHDHDCFCAAAEBEBFDHA,False +30,5.0,11.0,5.0,8.0,3.0,2.0,5.0,1.0,BBFGGBABFGCCCDADAHBEDCDBABGEAECBDBDBDBDG,True +31,28.0,17.0,19.0,16.0,18.0,11.0,17.0,33.0,DHAFAHAEAHDHFHFAFADHCGGGDGDGHEBDHCHBHAEBCBCFEGHHHBHCAFDHEHEHCDAGBCBAAAGACCBCAFGBHEHBBEAHAHAFAEACGGEHAFABEDEDFDCGHEBGAGEEAEBBHDEDECHCGABHGHAHAHBHCHCHCHDGACACDFD,False +32,5.0,10.0,12.0,17.0,19.0,17.0,17.0,11.0,EEBHBFFFDDEDCCAGEFEGGDGDFFGEGEAEDEFCFCGCGCGFAEGECDHHCEFDDHDFDABFDECECEHEFDDGDGBBFBFHHGCECEFEHAHDHDGBBFBGHGBG,False +33,4.0,13.0,10.0,7.0,4.0,8.0,11.0,7.0,CGBHBCBCBHFHFECBADGBGBGBDBCFAGDBHGFGECEHBGBCCACFGFGFGDDDFCADHEHB,False +34,22.0,27.0,22.0,21.0,21.0,28.0,21.0,21.0,BABFBCCCCGCDCAGABAHFBAHCBDBDHDCDCDEFFHBHBCBCBEHDAGAEFBBEEEBEGAGHGDGCGEBFBDEAECCFCFGDGDGHBHAEFFFECCADHFFBGHDHEGAAEDEFEFCDCDCDEFCHADAEHFDFHBBEBEBFBFAFGFAAHGHGFFAFGGBABGHGBFBFDFHCHAHEGDA,False +35,24.0,23.0,21.0,17.0,28.0,15.0,20.0,21.0,EGHGAGEGCGDFFCEEEEEAHGEGFGFBCBGBDBACHCAGDDDDEDEHACGCECAFAFEFHCHCEFHDHEHBAEADBDBAFCHCEEEEHBHBECEAEAFGGGGCCHBHAAACABBEHFHBDFHHDHBGCAABEBGAGABBFADADEBBBBCDCACFGFHDCEHEBGADE,False +36,16.0,12.0,18.0,16.0,29.0,20.0,25.0,11.0,EEEBCFFDHDBBGHGHGEFDFACCCFCGAECECEAGFFFCFDAHAEEHGGGBGBGADDGDGEGCCBFEHEGEHACDGDGCCCFCEAFAEGEGBGFGBBBHFGDGFGAAHADADCEEEEDEAEFEAEBFFFHEGECEGEHECAFDDDB,False +37,1.0,6.0,2.0,11.0,2.0,11.0,4.0,7.0,DBFFFHHADFFEFBDBFBGDFFEBHBHFHGDGDGCCDDDDHDHF,True +38,11.0,12.0,15.0,5.0,3.0,15.0,15.0,13.0,HCCCCAEBGFCFBGAHHHHBAFGCGCGCGFGCAABFBABHBFBCAFHFAFGCDBGBGAGFCBBAADHDHDCGEGHGCGFFHFHDEFHFC,False +39,33.0,14.0,21.0,23.0,21.0,18.0,25.0,28.0,DHAHAHADGDAFAFGCHCHEHCHABACEDDDCGBHAEFFGCADADGBGCFFFGGHBAAFGGHFHFHECFCHCHBDEFGADDCGGGHEBEDEBEBEDFHCAAAACFGFBFBFADAEGBDCAGACACAFGEEECDDDDCGGGEEEEEGCADHHHHAHABAHGBBCACHEGGHDADADAHAHEHAH,False +40,9.0,21.0,8.0,6.0,13.0,11.0,9.0,15.0,HEBEGEGAGEBBBHFAFABCBCBEBCBEAFHGGGHEHCHBEDFFAFAHDBFBFBEBDFHHDHBHCHBHBDEFABGBCEDEBCACHHEAGBGF,False +41,13.0,18.0,18.0,16.0,8.0,20.0,16.0,13.0,AGDGBCDHFADAGFFFHHCFCFEBGBGFGFGCGCHHHHCGFBFGDHABCBCGDGECEFBFCACBDBDCFAFBDEDCFFBHGHBEBABDFDFDHDHACABDBAFAFDHEGACACBEECGCBDG,False +42,21.0,15.0,14.0,22.0,14.0,22.0,16.0,21.0,ACFDFDEDFDBAFDCDCDFFFFFACHCHGEDFCFEHADACEHEDEBAFAGGHGEDADFDHDHDHGADAGCCCFHBDBGBDEGEBHGFGHAHFBFBFEAABABACDDAHHGFGBGEGHFEABHBFEHHHGDFDCACABABGECHAH,False +43,17.0,19.0,23.0,19.0,19.0,21.0,20.0,22.0,GDGFGEDDDDDDFDFDFEHBHDGAECBHDEGHGEEDEBEDECGGAADAFAFADECFCDGDGFBHGCBHBACAGACFCGGGBGCHFHEHECECAHFHFGCGHBFCGCBCFEHEGEHBBAAABDHFBCCCCFFFHFCABFBHBHBEDAFEHBHACABECHCH,False +44,2.0,1.0,3.0,4.0,5.0,3.0,6.0,5.0,CHCHFGBGEHFDAGADEDEGGFGEDEHCH,True +45,17.0,20.0,26.0,20.0,18.0,24.0,15.0,12.0,BDEFBBBHHECFCFCBBFEDDADADGECEHEFCGCAFDCGCFFEDDGGHHHHHAFAFEFAFDFDFDEDFAACFCFCDCBBBCGCGDGDFCGCGBDCACBHDHEECBBEBECFCHGBGEGABCDCEFHFGACDFAFAECEBEBDACABAGFBA,False +46,5.0,7.0,11.0,5.0,5.0,3.0,8.0,10.0,CBDHFHCDCEGEHCHCHCHEGCGCGBBBBADAHGDGBACGEAHBHFGFCECAHD,False +47,5.0,4.0,4.0,5.0,0.0,1.0,5.0,3.0,ACABGBHBHBGDCACHCDAGFGAGDDD,True +48,21.0,22.0,13.0,24.0,16.0,18.0,24.0,19.0,DBDGAGBGFHFCABGFECEGBGHHEACDFDGCGBEBGDAFAHADADAHHBHBHAGABADEBFDGDBDGDGCFAFAFDDDDECGFEFEAHAHEHEHCBCDADGBFBFAEBCAHFHEDEGBBFDEHEBDHFGCGHGHGBGCDABCBDGHGBGDCEAFAF,False +49,5.0,12.0,11.0,8.0,8.0,7.0,11.0,9.0,FCFDGDHBEBECFBBHFCFCGDBCCCGCECECBDBGBEHDDBCAGAEHEDFDHGEGAHBHGAGAGFHBHBG,False +50,2.0,7.0,7.0,4.0,6.0,13.0,10.0,11.0,BBFEFEFHAHFDFGHEBABDFHBHEFGFGHEHGGGFDFEHCBGBFDFHFHCCGCGHGCCC,True +51,5.0,7.0,11.0,12.0,13.0,9.0,8.0,13.0,EFFBFDAAECCCHDHBHFEDBHBHDHDGGGGECDGHCFEFEDEDCDCDEDCCHFEFEGCGBHEHBHAHAGDFCEAEHB,False +52,15.0,6.0,11.0,6.0,11.0,16.0,3.0,8.0,BAEGCCEAHBFCCHFABEHEFDCHEBECACECEAFGFEFEFBFBFAFADADACACDFGFAFAFEFDAAHFDCAHHH,True +53,20.0,14.0,19.0,11.0,13.0,12.0,10.0,17.0,CHCECEHEGAHBFGHCHABCBCDCECEDAHACGCADDBBGFGFGFHAAACACFBEGGAGAEHCAAAFDFDCHBDBHGDFDHCBEFEBCBABHHHHDHCHDFEFABEBECAAAEACF,False +54,18.0,14.0,15.0,22.0,24.0,20.0,25.0,23.0,EGGCGCGDEDEBCBFDDDBFHDDGFBFEEEGDBDBEHFDFEACACADABEFDCECGGHBDCDBAGHGFBFECHCFEDEHEHAHEEAGCEEEEFGFHFAAGEEHHHHAHAHDEFGDGDBCGAGHFHFHAHAHDHDBFBFCEGGGGGGGHAADAGCDFFAHCB,False +55,3.0,4.0,2.0,5.0,2.0,5.0,3.0,1.0,EHAABABGBFDFGFGEDDFDCBCDF,True +56,9.0,9.0,8.0,11.0,11.0,13.0,8.0,11.0,ECFFFBCDEDAFEBEAFGFHFHFDEHEBEHEGBFEFHBABCCAGAGBGBDFHAHGHFCFDHDABADEDEDAHGGCDCHCD,False +57,10.0,13.0,10.0,15.0,7.0,9.0,16.0,11.0,HHCFEGEGEDFGABEHEADCHGHBDFDGDGHGCGBBDDCDCDBDBHCDEBAHACCFDGDFAFAFDDAGAGHGCGBGBHACBGBGAHEBFBF,False +58,15.0,15.0,14.0,21.0,27.0,24.0,20.0,28.0,FAFEFAADAGFBFACBCBHHCGFGFAFHCEGEGHHBDBFHFHBEGDGDAEEHEGCGDGHCDGDEHFHGCEEEGEGEDBDEEEEHHHHCHDAGFEBHFHAHFHFDDDCACHFBDDHDGDFDAGGEAEFBHEEEEBEHEFFCFCFDBHAFADCGCGFHDHEBABHB,False +59,11.0,16.0,18.0,17.0,22.0,31.0,15.0,17.0,FCECFCFCFBHCHBGBFHGEDADADEFEFHFDFDADEEADHGAEAECGDGCCFHFGFHFHFHFBFBFCEEEBEFFDEGGBHBEBHFCDDDDGHAFBFBFCACHCAFGCGHHEDCBFEFABCDCEGGGDAEBBBEDEFFFFECGHEHF,False +60,11.0,9.0,7.0,2.0,10.0,10.0,11.0,9.0,HGHCDCHCACBCEGEGEGEBBHCFGABEBFAEHHFBFAAGHGHFHABABCGEGFDEAAABFEFEFGFGA,False +61,23.0,23.0,21.0,24.0,24.0,17.0,27.0,24.0,EDGGCBCFCGCGCFCGCDCBAACHFHFHECACAGAHFHDBDEHAGADHGEGEBCAEAGDHAADDDDCEAEADBGFDBBBBDHDGDBBGCAAEHEGDGBGBFHCGCDBBBEFHFDAGHCDCHFHFGEHEGEGHGBEFACADAFCBGBGBFHDEDEDFBFEGHGHAHAEEEEGEDHAHACEFBHB,False +62,21.0,13.0,9.0,12.0,17.0,15.0,25.0,10.0,HFGFGBGEDEHGHAHFHGAAAFGHBFACGDBEBGAAFEGEFEFBGAHDEDECBCBFBEGAGAFCCBBDBAGABAGGGGGECDADAGAEFEDGACADDCDHDEAFHFHFGGGFGCABAEEEGE,False +63,6.0,6.0,3.0,12.0,7.0,8.0,6.0,13.0,FHEBEBHGHDAGHDCDEDEAFCFCHEEBAAFDDDFDHDAGBGFDHGHAHDHEHFHFHBDBG,False +64,6.0,15.0,15.0,8.0,14.0,13.0,8.0,8.0,CCEDEDBHHGDCBEFEFCCGCEAGFGEGECAHAHGBCFHACEBEBEGEFFFFBDBFBHBDDEDCBCBHBFGFHEAEBCBCFCBCAFD,False +65,6.0,4.0,3.0,4.0,6.0,8.0,5.0,5.0,CGCFEFAFAEEDEHCHBBDAAFAGHEHEBFDHDBAGFGFGF,False +66,17.0,8.0,15.0,6.0,16.0,16.0,11.0,12.0,AFGFGFGHGFECECECHAECCCFAHAFAEHGGCEBAFAEAEFGGHCBFAAEHFHFGBHEHGAFBFHCECEADFDBDBCACACAEAEBEDDACBDFHFHEGC,False +67,24.0,12.0,23.0,14.0,18.0,18.0,15.0,12.0,CCCFCFBHAEEDFDBAADAEAEABDBDGEHEGCCCACECHGEGEDECACFCFCHBFBAGAFFGHADBEBAAAAFAEECEDHDHECGGBHHCHDBGBABAGEFFGFAFADACADAGADCHFECGFGFHFCDCEGFCC,False +68,31.0,17.0,27.0,38.0,29.0,28.0,14.0,16.0,ACACBCFDGBHBDEGEAHDDEFEFEFEFDDHECEBDFDAEAEFECECGCHAHAHCBCDAHBDDDDEDEBEHGDDAFEFCFDDBCGAGACCECAADADABAFEDACGCAFAHDFDBDGCECBGBFFCHCGAEDFFFHADFDADGFAFADEDHABAGAGEHEFBFECEDEDCGEADADFDHBHDFDCBCFCDAFAECFCEHB,False +69,5.0,4.0,3.0,4.0,2.0,3.0,6.0,4.0,DAHAGAHAHAHFGCGEBDFDEDGGCFBBGBC,False +70,5.0,7.0,9.0,5.0,2.0,11.0,6.0,10.0,HAHDHDHBGBFCACDCHFBBHBHGDEACACEGFCDHBGFGFGFCCHBFFHFCFAF,True +71,11.0,10.0,6.0,19.0,14.0,23.0,11.0,9.0,FHFEADABECHFFDFDFHFEDECEFEFEFAFHDADAEADDCAGFGBBHGDGABDDFFFFDDDADEEGFGDABCDGGBHDHFGAGBHBHBEBEGFFFFFCCEDE,False +72,25.0,17.0,20.0,19.0,16.0,13.0,17.0,22.0,GDCDHGBEAEGDGEBDBDHDCDCBHDEAEHDCEFAAABCDCDABAGADADCFAFCGCACAFFBAHGCGCGEGEACHHECACECEHEGGFBDHFHAHAHGGDGFCECHFHFHCHFABABFDGABDEDABABHEACAFDHHGHAHBBBBEH,False +73,15.0,19.0,20.0,23.0,23.0,21.0,22.0,23.0,GFGFECGCEEGHFCBCFDDDHHGBGHGHDCDCFHAHCCCFHAADEBEHEDEDADCDCABEGEFDFHCHGGAHAHFCFCEADFFECGBDBDBDCCACADHGCGEGHFHGHGBFADEBEBEDGDBBACEEEHGBDBFFFFDGEGDGDGFBEHHHHAAEAEFBBBBEFH,False +74,3.0,11.0,6.0,11.0,10.0,12.0,5.0,7.0,ECHFHDHEFFHHDCFGEGFDBEBEFFFDBCBFEDCDCFEBBFADDBDBGBGBGBAHAHFDEDECE,True +75,21.0,13.0,22.0,19.0,30.0,19.0,18.0,19.0,HAHEEEFEDHDFDBHBGCCEEFEGGHGHCCCCCHGECEAHDBDBEFGHCACGBEFEHAFDFACAFEEEHABAGAFDGDADADAGBCBAEADAEFHCDCFGEHFHDEDCDFEFCCCEAEAEGGABFGEDBDBHBCCECEHEAEFGHGHDDAEAEHCFGFGFB,False +76,14.0,30.0,18.0,20.0,25.0,19.0,27.0,30.0,FCFBAEDEGEHEBGHGFEFCGDBDGGCGCGBEBHBHEAAAEECBCBCFHFCFDGAEHHFGGGGGHCHEHBABGBGHHDFAEBDBDBDBCCHAGGEGDGCCBCHFGFGHGHBHEFGHBFBCBHEHBBABCBHBCGEHEADDDBHFHAADEDBFHFEEGEDHDHDEDBDFEFEHCHAEGDHBFBA,False +77,25.0,17.0,30.0,29.0,22.0,22.0,23.0,24.0,CCHEAEHBBCBDADBDBDHGFEECBDFGFEAHDCGCDHHEHEHCGCFHGDGAGAGACACDDDFDFDGECCHDHCCEFAFEBAFGGHDCCGEDBDBDBCHCACDBAHCGCGAHAHAFFFHADCDCFCFHHCDCAEAGAGAGABFHGEGBGDFHEBEFCFAGBEEAABAGDGDFDFEABHCDEDEHEHEFCFCD,False +78,9.0,16.0,9.0,5.0,4.0,15.0,4.0,5.0,BCEADCBBBBABABCCEHFBDHFAAGAGHCFCBCBFDFAGAGBFBDBABFFFFFCEHEBDHFFFBFC,True +79,19.0,17.0,10.0,29.0,13.0,8.0,14.0,14.0,DEDEAEAEDDDDDDDHDGEBEFADAGBFFHDGFBBBBGBABFCHGDFDEACBBBAHADAHCGCAHDHEHABAGCGCGEDAGBDAACAHDBCBGBGBEDDDDDADGDFDHHFDAHAEEEHCDCHG,False +80,9.0,11.0,7.0,9.0,14.0,3.0,11.0,16.0,HEHEACBHBHAGEBEAEBHBHBDEDCFABCGAEABHEHDADABABGGGDGHECEHHDGDHHCHCDGFFHCBEDEGEGHGE,False +81,4.0,9.0,4.0,9.0,3.0,6.0,6.0,5.0,BGBACACHDGDFDFBFEAHFBDDEDEGHGHBBBFBADHDGCGDBFC,False +82,11.0,21.0,22.0,24.0,26.0,28.0,21.0,21.0,EDGDCDCFGEDEFFFFGEEEDEDEDADACHCEBAFAFCHEDBFEDHDCCAHGFDFDGAGEFECEDBHCECDGGGGGBGFGBHCGDGFFDCAGDBCEHEGBBBBHFHADFHCHCHCACHCBBEFAGBGBEBFFFHFBCEDFFEFHDHFHFCCECBHBDBDEDEHBHEHFBFEGAG,False +83,2.0,4.0,1.0,3.0,2.0,4.0,2.0,1.0,CBFHFBBDGDFDFEGEABA,True +84,18.0,13.0,21.0,13.0,16.0,19.0,15.0,8.0,CBCEEADAFGDCFHFHDHFACACEDGACFGGGCBABDCCCCCCBABABABDBDFACGCGCFCAGEFEFBDBCFEFEAGFDBEFEHEHBAEADAFAFGEGECAHFEDGDHHCAEDEFCFGGGBF,False +85,14.0,12.0,10.0,10.0,16.0,19.0,9.0,12.0,FGBGHDEEEGBFAEAEDHGHGFEDEFEGEDEFEFCBAHCHCFBFDGECFFFGAECBBBDGFAFACACBEDABEBFHFHFHAHAHFEDCDCFCAAHBHADAFB,False +86,14.0,13.0,10.0,16.0,18.0,7.0,14.0,15.0,GGGGHADGCGCEEEDEDBAAGBCDAEABAGAFFFDBEFEAHAHBDBDBDBGHAACDHHGHGHDHEFBCDCHCHDEEBEBDADABEFECCGHGHFHDGEEEADBEEHC,False +87,9.0,13.0,17.0,12.0,12.0,23.0,13.0,12.0,EHCHBDDCECFCFCFABABGBFDFDCDHBGDHDGBGCGCGCFCDHEHEFCHGEAFBFBFDFHCEBAFEDEDFFGHCFGBGFGCDCEBGFHFAFBEEEBGFFCFAACAHAHF,False +88,6.0,3.0,0.0,1.0,3.0,3.0,5.0,4.0,GBGAGBHAGAGFEBEFEHHAHAFAD,True +89,11.0,11.0,12.0,15.0,16.0,12.0,7.0,10.0,BHBHDDADCGCAEHHDCEAFAFBFCDEDECBGFCECHAHGCAEDDBDEAFAFHFDCHEBEGEGADBDBHEHDFGFGFDECECECAAEBEBDBFF,False +90,18.0,21.0,18.0,8.0,15.0,18.0,18.0,10.0,BCBDGCBCHGHAAFAFEFAFDFHGGGCCECEHBHFCADAFAFEGBAAAGAFBEBEBEGCBHBFADAECDGHGBGECCBCBABHFFDCEFEHGBGBGBEFGABCBFBDBEEAHACGCGEGFCFCFDA,False +91,21.0,22.0,23.0,29.0,25.0,21.0,20.0,16.0,EDECECBBDBGGGDHDFCFDFAFGBACHDHDADFDHBEAACACACEDECEDGDGEGEGEDEAFCFEGGBEBGFGEDECGFAFAFGHEDFHFCFBFBDEDFDGBHEADHDCCFBABABACGEHAHFHCEGEGHBHDACADFCCHBHDCDCFBHAGDBABEBFBGCDBEBCDDADAEEC,False +92,22.0,26.0,23.0,24.0,20.0,30.0,22.0,18.0,ADAFEGHDHFFFFDFECADDDFHBHDCBFAHCHCACHEGFBFBCDHEFEGABAFAEBGBFFFBFCFGBHBEBAACAHAEDEDEGCDCDCDCGHACFCFHFHGCFCEHEHCGCDCEFGDGBGBGEGBABGBGCCABBBDBAFGDABFBFEFEDADBFEFDBHGHDFEFECBAGGCGADDDGBHAEA,False +93,2.0,2.0,1.0,3.0,0.0,2.0,1.0,2.0,DBDCDGFFAHAHB,True +94,18.0,8.0,12.0,13.0,10.0,9.0,12.0,11.0,HHFAEHCHCHCDDAFACACACGGFEFGCHDEEGCGCGFDDADGDFDEBHCDABGBABDGAGEEBAFABGBDAHAFAFADADEHHCHCBGEAEA,False +95,4.0,5.0,6.0,3.0,5.0,4.0,4.0,3.0,AHBFEADADAGFHFGGCBCBCBCFCEHEBDCEEG,False +96,6.0,10.0,15.0,4.0,14.0,9.0,14.0,11.0,ECECEGHGHEHGDACGHHHFGFGCCCGFEEHEAAACCHCFCFEGEDHFHFDFGEABBBBEBHGCGBEBGCACBEBEGCCDBFG,False +97,3.0,4.0,3.0,4.0,3.0,2.0,2.0,6.0,BGHFHDHDCDBDECAHAHAEGBFBHCE,False +98,14.0,9.0,9.0,12.0,16.0,15.0,11.0,5.0,BGGACFEGEGEAFGFGFGFAADADACBCFDADGEBHBFDFGBBDCGAFAEEFECHCDCBFEAEAEADADCEBDDHDBGEFCHEHEFEAEFF,False +99,24.0,22.0,16.0,19.0,18.0,22.0,22.0,17.0,BABDFDEDEDEHAACABAEAFFGBHFGAHDBCAGADEDCHBBGEGAGAGAGAGFGABEDEDEFCBABDBECECEAGFGEGBGACBFEHEHAHAFBFBCHEFGDADAEEBCBHHHFHFBAGGGFFFFGHDCCHAHBCBCHFGDBCCAFBDGGFDHDFDFDC,False +100,10.0,7.0,6.0,7.0,6.0,11.0,8.0,15.0,GGHGHGFEFDCHAHFHEHEBACCBCHFHFBCBEBFFEFHAHGHDAGADAEGBGHHBAAADCFHFDADFDH,False +101,21.0,23.0,9.0,23.0,25.0,21.0,22.0,21.0,EEEEEACAHEHDDADHFBFBAHGHGBGDGFECGBBBBFBFEFHFGFGFAEHDHAHAHBHGHFBBHGGGGGEHDDDDHEAFBHHDEFEHEDDGBCDCHBGDDFFCAHADEDEGEGEAABBEBDFGEBABCDFEACFDADAGAGEGBAFABHBDGDCEEEAFAFBFC,False +102,1.0,8.0,5.0,3.0,5.0,5.0,6.0,8.0,HCGCHDEBGFEFECBBBFBFGHGHGDGBAHCFCHHHEDEBB,False +103,29.0,22.0,27.0,17.0,23.0,16.0,31.0,26.0,GGHCFGEBEDGCCDEBFFFEFHGCDCBCBCECFCHCHCHGHCEGAGCECABHEEEBEBEGAGBBBABABFBHBHDHGGDADCCFAFEDECEABGBFAFHDAGHGHADEFGBDCHHDEDCHGABABFGDEAAAEBGAAEGGGGFGHAHDBDCCHGHBDGEGHGEAEACCHCACAHGHGHAHDCACAFAGAFA,False +104,7.0,6.0,18.0,7.0,11.0,12.0,24.0,18.0,GDGEHCGGGEFECEBECGCGHGCFHFHFHCDFDFGACHHHGBGHACDCGAGADBCAHECACGHGHBBCFGHEDEFEHGHBHGGCGCGCHCEGGDGEAFFHFCF,True +105,16.0,23.0,21.0,18.0,22.0,17.0,10.0,18.0,ACEGEHEHAFACDCDCHFBFBGBHDFFFCAGHBBBHBHFABABABAHEGCAEEEFGBGBADGEBCDEHEBCFCHBHEFEBDDDDDDDGFEDEFEHAHBCACACBDBDHDCBCEDEHEGCCFEEEDHHAABCFCHAECBCBFFCFG,False +106,9.0,10.0,12.0,6.0,8.0,7.0,13.0,7.0,FABABHCEGEGBGBGCCCHCAAABGEGDGFGFAFCBCGCEHDCCAGHDHCAEHFBFAGBGBGHFDCDBEEDE,False +107,17.0,15.0,17.0,17.0,16.0,26.0,15.0,17.0,EFBHGEAFDGCGFGFGDEEAEGBDEFBGGFAHHCAFAFHBHBDGDGEGEGDFFFDFHHHAHBCDADBCBFGFCBCBGBFEHADAHCECFCECHBFFFFCDEDEDCDEFEFCHHHCACAEBCGAAAAHADAFHFBDBCFDF,False +108,20.0,24.0,27.0,23.0,19.0,28.0,19.0,18.0,AFAEGFGFGAHFCFEHEGDBBBEBEBEBCDDDHDFGFDCDCECFAFAHAGBBBEBFDEBCBAHGFGAGABDBEAGFCCCBEBHCDBDFDFBBHCHGGCDCDFHEHECGCFFFADAHHHDCDAEEBFGAEHCDDGACACACFCBEFFHAGCCCCEFEFCABDBFFFGHCHDHDFDGBGA,False +109,9.0,16.0,17.0,17.0,16.0,16.0,12.0,24.0,EGDDDAHBEAEABDCEBFFHFHFHCDGHAHCCFDFDFDFBBEBFBFEHGHGDCFCGHGHGCBCEDHBCDHFHFBFGDGACCCGAEBHBABCHHEHBDDEHEDEDEGEAHDHCECFCFCBHAHEGBHH,False +110,5.0,7.0,7.0,3.0,11.0,14.0,10.0,14.0,AHEHDHGFEFGCHFGFBBCAEFEFEFECEHFHBHAHFCBGFABHBEDEGCGFDFACGCGBFEFGHHHHEHG,True +111,20.0,16.0,22.0,22.0,11.0,17.0,13.0,10.0,ACAFFCDCDCACBFAFGDAACDCDEDEFFCBHDGDCDGDEABFEAADDCAHHDHEGACEFBCBCACACABBHDHDHEHCAAFAFCDDEDFDFBFCFBFDEDFFGGAGCCBEBCBHBAGGGGGEGACBHBDB,False +112,26.0,22.0,28.0,29.0,20.0,26.0,21.0,19.0,GCDCBAEHEHGGFABGFFFFBDBDBHCHCHAAADGFCBCDCFFFDCHCECEDEAFBFEFEGGCDCDAEAECFCEEACCBABGFDABADAFHBHFEFEAHAEADFCFHHBHAHAGGDHCCCDHBCADABHBDCGHGAGAGDDDFCAGBCBDBCFCFEHEDEBGGFGFDBCGAGDCDEDGDBDBEFEHAFADD,False +113,4.0,0.0,3.0,3.0,1.0,0.0,3.0,3.0,HAHADDGDHAGAECCCG,True +114,15.0,25.0,14.0,19.0,17.0,16.0,17.0,18.0,GDGCHHEBEBHBEFAFEFBFHFBGHEFEFEBAAAGFGDDFDFDFDBDBDBABABDHCBGDHCEBBGBCBEBAGHCHBEBGHEHEHEACACACACBBGGFGHCHDGBCDGEFDFDBEHECDGBCEHAHDHACFGADFDBAGD,False +115,4.0,7.0,3.0,5.0,3.0,0.0,6.0,6.0,HGHBHBDBABACEGDGEAHBHADGEGCHCBDGDB,True +116,18.0,19.0,11.0,27.0,26.0,22.0,18.0,28.0,FDFEHEBGBGBCFDFDFBEGFABHCHEEFAFAFAFBDHEHEABBDCHCDDGEHEADAFAFBHHCHBFBEDHGHGBFDFGECHHABDEGECEDADEHEDCAHAGEBABCDCDAHEDEDEDFFFFFBFHGAFEGEGDHDHGHGHGEDHDGEGDAHABBHHDHBCDADHEGE,False +117,9.0,10.0,11.0,5.0,12.0,11.0,5.0,12.0,HFBFCFBAAEABGHCHAFABBBBCCCHCECECHCGEHEHEHFHAHCEDDFDCEEBFFFFGEBEAFAHDGBGDEHA,False +118,1.0,8.0,6.0,3.0,6.0,11.0,9.0,8.0,BEBFGFGFBFBGBCDFEHBHAGEFHGDEFBFHHCGCDBGFGFGHCHFHCECE,True +119,16.0,21.0,23.0,14.0,8.0,20.0,24.0,21.0,EEGFBBADAFCBHFACCCFCFEFDGAFHFDABHBCGHHHBHGHCHEGCAABBGDHBHBGFGCGCGCGHFEFCFGABAGGCGAGACFCBCBHBFCFADHDHGHGFDEBEGCGCDBHBEAACHDDFDCDCFBFBGGGGCBHDHDHFABA,False +120,23.0,16.0,16.0,25.0,12.0,20.0,24.0,21.0,DFHFBBDGFFEDCHEEGGGEEADAGAGDBDAABFDFCGDGAABABABABACAGGHDHFACECBDDFDHGHGHBCBCAGFGBGCFFFDFDCGHGDEEHBCDCBHBCFGFDFDHAGCHHHHHGAFADDHEHEAGAGAGHCBAEAEDCDADCFGFDHDHF,False +121,19.0,17.0,15.0,20.0,28.0,24.0,23.0,17.0,DCDFFGAAFFFBGAGDGCACHEHDADADFEHEGGFFEFAABBHGGGFHEHACACBEEEHBAGAGFDFEBEGEBECECDCHBHGDGBEFEAEAEAECCGCEHBHCFFGBDBDCDAEEEAEFFFBHAHGEDEBGFGFGHGBGBDFDCDHEHDDDEBAFDFEGCFH,False +122,24.0,21.0,31.0,19.0,20.0,33.0,21.0,17.0,CBDGEGCBFGFHFHFEFBDAECCCBCBGHDCCCAFADHDHDEDACBDBGAHABFDGEGCHEECECDAFBGBGBFFFFHEAECHFHFHGEEBCFCFDGEGFFFFGCDCGBGBGFFBFBFAAAAAFGBAFABECAGEGBGFHFCADDCECHFAFADAHFHEDEHCFBACAEAEFDCCCCCBCHDADCG,False +123,23.0,22.0,33.0,26.0,18.0,14.0,26.0,19.0,DGDGCACABHFCADADGHGEEHGACAHAGACEDEDEDGDFCHDECFCBCGHGECHCHBEEDEDEDEDCBGBGBABCBCBHAGDGECAGDCCCFCDCFHFDABECGBGFHBBFBEBEBACEDBHHCCGCDAGGGFCCCGDDFCBCBGBGHGHGCBADHFFAHDGAAAAABAFDHDHCFCEAD,False +124,14.0,14.0,13.0,14.0,9.0,17.0,19.0,18.0,DCBFBFAFAHBHGFBABECACGGBGCGCFAFHHDGDGEBDADFFHHHHDAABHFFEGAGFDBGHGAGBGHFHFGCHCDGEGEFCGDGDCDCDCECBFAFCFHAHEBEGHBEBHHADAD,False +125,22.0,17.0,18.0,14.0,19.0,23.0,19.0,20.0,AFFEGCACEHAHBHFHECADBDEDHDHDACHCBCBHFDDAGHGHCECEAEAHBHGGCEAFAFBDGFFFFBAGAFAFHHCGDFFAEBBABADADBCGHHHGACACFCFDFBCGHGEGEGBGBCBEEAFHEBBGGECEFECEHGGEAFDFDFAF,False +126,2.0,2.0,5.0,1.0,2.0,0.0,0.0,0.0,CBABCCCECEAD,True +127,9.0,13.0,13.0,20.0,8.0,15.0,15.0,18.0,GGEFDFEHDHDHBAGABBBFFHFCFHGHGHGHGDADHDEDFCEDAGAGCBDFDHDHCBCDFDBHFHGHFBCGDDDDDABGHDHCHAAECFBDBEBCBCEGECCFFHCGAGF,False +128,26.0,16.0,20.0,13.0,15.0,14.0,8.0,14.0,AFAFGCBFDCCGCBCACACAFACECBAFAFDBBABABHECBGAHADEDCBADABABAHEHCHCHGECDHDHBHBAEDEAEAHBGFAHBBCACACAFEDCAHHEADGEGECEFFFCGHDFDEAEFFD,False +129,3.0,2.0,3.0,1.0,2.0,1.0,0.0,1.0,AHABFBEAECCDC,True +130,3.0,10.0,5.0,11.0,10.0,4.0,3.0,9.0,DBGBHBAEDEBCCEBAAFHHDHDCBEDHBHBHBDECECEDDDFDGDFBEGEHEHF,True +131,18.0,19.0,23.0,22.0,20.0,20.0,15.0,23.0,FGBCAABCBCDCDCBBAAADCEGHAFDFEBHBHAHGDAEAEAHGECHCDDFDBEBHHHDBCFCABFHHHABFHHEGEHBAFAFCDCHGEGEFBFEFEDEHCHCHDHDGFAFEBEBGBGFCDCAEDEGFFFHFBEAGACFDDDDHDCCCCDCDGEGBGCEH,False +132,27.0,13.0,16.0,13.0,20.0,12.0,27.0,15.0,HAACDHGHEBFFCDAGADAEABAGHFHDHCCAEHFHBGBECGGGGAGABACDEDCACACFGFGFHBBEBHGGGDABGGGEDECEAEAEAFCEGBBBAGAEAEABHEAEGGGCEHFHDGAGEDEDFDHDEAAGAHAFFGCCCCG,False +133,5.0,7.0,9.0,1.0,6.0,7.0,8.0,7.0,BGCFEBHHHHACABFBFHFCFGGGCCECGCGCHAEBBHFGCGDAEAEBEF,False +134,14.0,15.0,11.0,16.0,21.0,17.0,16.0,20.0,HBHDHFHDDEFEGEFEBGDFDFBBHBAGEGCFHBHDADHHFAFAHECEFADECEDDDBDBDACBEAFHFHGEGCGDECECBAGACHBHGHFHFHGEGFFHEHCHCEGEGEAEGDGEABDBABFFGECABA,False +135,8.0,3.0,1.0,2.0,4.0,6.0,9.0,3.0,GFGEGHGFEFGCGDBAHAFDEAEGBGBAAAFAGAHF,True +136,14.0,29.0,20.0,23.0,25.0,22.0,18.0,18.0,DGDCEBGFHDBFBECHFEFBDEDCACGCGHEFEFEFAFGGGDCFGFHFHAHADEBBCBCEEEFEBABCBEBACACBHHCFCEAEAGBGDCDBDEDGBACECBHEHBDGDFDGCGAFEFDBHBEBEAHGFCFBFBHEDFDGDBBBBACDBDHGBEAEGFCHBHEHDHDFD,False +137,3.0,5.0,1.0,6.0,8.0,6.0,3.0,5.0,FDFDBBBEDEHEHEFEACFFGDHDFGBHAEAEBEGDH,True +138,17.0,19.0,28.0,23.0,19.0,29.0,14.0,27.0,EEHFCDHDHBAADFECECFFFCDGBAHAHFHBCDDFDGDADBCAAHABAEGFHFHDHDEGCGHGHCFDFEFGBHAHBCBABEEECDCDEHFHFBABHCCCACHEACHDGDFHFHBHFGDGDGDFBCDCGABFFDFECHCFFFHFCDGEFCACHCHCHEGACFCFBFEEECEBBBBD,False +139,18.0,10.0,15.0,7.0,19.0,9.0,15.0,15.0,BCDGAGEBBAAFCBEFDFHCAAHABFEADAHGCCCACEDEDEDEDEHCBCFEHCHEACACHGGGGBGEGFGFEHECGFEAHGHEHEHEHACAFBGGABABHGHEAEAC,False +140,12.0,11.0,10.0,15.0,15.0,9.0,10.0,21.0,GGDEDEDHDABGBDCAFADADEEFHFEEBBAHECFCAHGHGHEBBCBABAFHHHHAFADHECEGGBGECECHBHECFCDDDEEHHHHHDHDHDHFACGDABFG,False +141,6.0,7.0,16.0,10.0,19.0,4.0,7.0,3.0,GAGEECEDBGBGFCFCHCFBDBDECEAEDBDCHBEEFAHAEAEGCBCEADDDDEGCCEEEECCCECDCGCEE,True +142,17.0,14.0,17.0,18.0,21.0,18.0,15.0,9.0,BADAGADHDGDGFHFAFDFGEEDDDADCCCGGECCCGEHAHAHEEEEAECFCDHDFABABFBGBCACEFFDADAEEHBHFDFCBEBGHGCFCDAGFDBEFFGFGEGCBAEDEBCBAACDCBEBEFEFEG,False +143,1.0,3.0,4.0,4.0,2.0,3.0,3.0,3.0,DHDCCGCGAGHBBFEFCFDHDEB,False +144,3.0,1.0,7.0,1.0,1.0,3.0,7.0,2.0,CDCFHGGFBCCCCGAGAGAEHFGCG,True +145,3.0,5.0,7.0,4.0,3.0,11.0,6.0,3.0,DHGEGBGBGCCFDFAFHCBEBEBDFCFCFGFCCAHFFFDGAF,True +146,4.0,13.0,6.0,8.0,6.0,15.0,9.0,3.0,FABGBGFGFDBBBCGEEEEBFGCBFBDBCFDFGFGFAFECCDDADAFBDGHGBFBFHFEFHCBD,True +147,16.0,16.0,22.0,23.0,21.0,20.0,35.0,29.0,FBFEECGAGFGFGHDHDFAGEGEHFHFHFEGHGCEEAHDGDEHEGEFHFCFHGHBECDBDBHHGGGGGGCBHAHACAHAGEBDCEAGGHGHGEGEBDAHHHCHADGCFBFHGBGCHDFDFDGHCBCHHAGBEBDACHCFFGGGDADEEAGCEDEDCCCGDFDBDGFBFBGBDEACACDCDCH,False +148,16.0,20.0,20.0,23.0,21.0,16.0,31.0,18.0,EBEHGGGHCACFDDDDDAFCHEGCACFCFDFAGADEGGGAGEECEGEGEGAFFDCBHBHDHEGCDCGBGBGCCCCCBDGEBCGFHCHGHAHBBCEGEGEBFBGAHABDBDAGAGFGBEEEFEDGDAFCHBABGBADADEGFFDHDCFGGDHBFBDEDEDGHHHBH,False +149,3.0,7.0,4.0,6.0,10.0,7.0,3.0,5.0,EBEHEBEDCFCBBADCHFHFGBGBDEEEECHBDADADEFFFGFHE,False +150,6.0,2.0,7.0,6.0,2.0,3.0,8.0,0.0,DDDCGCADFDFGGGACACAGBECGGDGABACFCE,True +151,5.0,2.0,2.0,0.0,5.0,4.0,2.0,3.0,GAGAFBFEFECEFHABAEHEACH,True +152,14.0,12.0,9.0,7.0,12.0,11.0,10.0,17.0,FDHDFEHDHCFCBCDGHGCFFFBFHACCHBGAGAHEHEBEAADAHBGBFBFBABABAHAHEEAFHEHBHEHABGGECDCECEAGDHAHEFGG,False +153,19.0,24.0,27.0,19.0,23.0,23.0,26.0,24.0,CDCGGGFAAGACHFHDHDHBBCCHCGFAHABGBEDHBGBGBABADECFFFFAGGCHDDGDGCGHGHGDCFHDHAFEFEFEHDCCGGBGEGAAFCEEDFDFGBEAFHFCGEBCBHBFBDCDGBCBEHADABCHCHEHEHBHDGFGAGEGBBEBHDEEHAHAEAECCFFFCCCECECEFBFBDECBA,False +154,13.0,10.0,11.0,9.0,11.0,8.0,12.0,4.0,GEAEAFAGADADAEFCGCGCGCAFBFBEECEGADADACBGBCHHBFEECACBEHEFBFBDADEDBCGGGBDFHCAGGD,False +155,23.0,15.0,20.0,21.0,22.0,13.0,16.0,23.0,FEBEBEBFDHDHCCDDBCBEGFDFGBHCHFDAEBCBFHAHGHDADCBGDHDHDFCAHHHDBCEHDFDAAECDCDCBCAFEEEEEAEAGACHCEGEAEGGGGAEABAFAFHHGEAAACHFHAHFGEAEDEDEDADHDBCGAGACBCHHBGGCHC,False +156,1.0,2.0,8.0,2.0,1.0,1.0,0.0,3.0,CCCCCHCHBACDCBHEDF,True +157,11.0,6.0,5.0,14.0,10.0,10.0,2.0,6.0,EFAHAHFBFGGABADFCBEDEDADAHAFAHBFEDEDCDEDEDEDFFCBEDFDFBACDDAEHCHA,True +158,15.0,22.0,16.0,16.0,9.0,21.0,17.0,9.0,CFCFCAEBDGDHBBFBHCAAGFFFAGGGGFGHCHDBDBECECECFHBBCBAFHFDFBCACHCAAAEFDBDBCFGAADADAGGBBBGCGBGCFBEEGHGFGFDFDFABABDFHFDBDCEFEBGDDB,False +159,3.0,6.0,10.0,6.0,2.0,3.0,4.0,5.0,GGGFDFDBCBHBHBCCHCBCEHHFCACDCBEDDDACGCA,True +160,7.0,12.0,7.0,6.0,6.0,8.0,8.0,5.0,AEFEFEBCBADCEFHHCHGBBECAABFBFBDBGBHECGDADADGBGAHFFCFCGDGBGB,False +161,25.0,18.0,13.0,27.0,15.0,21.0,17.0,28.0,HFHGDDBDFDGHGADHGFBHGCFDAECCHHEFEFEDDBEBAHAHFHFBFHAHDFDFAEDFBBCEHADGFGAHDGDGDGDFCBCEAEBCBHDHDHAHAEADHHFHFHEGBHEDABABACDCAEFDDGFGAGABAHDHDGDGDBHBFAABAGAECECHCACBFAFH,False +162,18.0,23.0,16.0,12.0,17.0,23.0,24.0,31.0,AEABABCBCHCHCFFFBHHEGBABDDDDDHHFHEECFCFCBEDDBHBHBCGHDFAFHCHFGCHHHHHHHCFGFGEHDBAAEGGHEBBHGDAHFHBHBECGFAFBGCAHEHGBBFBDCHHGEAEHGFFFADGEGBGBGCGFFCHGEGEGAGAFABABAEAEGFGF,False +163,24.0,23.0,17.0,16.0,25.0,31.0,34.0,30.0,FHFHFEFGFBAEHHHDHDHFGGDGDGFGDHACAFGDGDECECHCGAHAHBBBBBFFFCGBGEFFHFEAECGGBBAGABABAFHFHECGDECFCHDBACDEHBFBHBFEFDDGCHBHGHGHBEAGFGCEHFBAHACEHEACFCFEAEGEGAGACFEAEBGGFDBDBGEGECEAHHHAGBGHAFDFAFDFGBGHGFGAGHEE,False +164,16.0,17.0,19.0,27.0,19.0,29.0,35.0,19.0,GDGBCCGCAFBFGFDHGHBFAFGFGDDECECDGDCDFHFGFCFHFEABACFHFBFHEEECEDFDEDGGGDGCCBBDBFBABFBGDEDEGBHBDDDGGGGCFHFGFGFHFEABBDCDCHCGGGDGFGEDADHDECEAGAFAHEHADAFFGGGCABEGHCAEFGFGAGDDHDHBCEHGAEHFH,False +165,10.0,7.0,7.0,12.0,6.0,6.0,5.0,8.0,DGFFDCDCDAEGDBDCEBGACECHCECDBABDEAHDHGAAHHHFHFBFBGBHDADADAFAE,False +166,17.0,18.0,17.0,16.0,20.0,19.0,17.0,15.0,CACAHAFBDAAADADHBGFAFDGDGDGHHFHFGFGFHHCAAEBFBFCFAHEBABEEGEGEGEBAHGDCDGEBCHEGDGCFCEEFECBCFHBHBHBADDFBFBGDCBCFFEGCAEGEFBACDCECECFDDADEEEGHBHB,False +167,15.0,4.0,11.0,15.0,21.0,12.0,17.0,17.0,HHAHDEDGHFHEHCHGFGFCECEGEACFGDGDCDCHADCEHEGGAEEBEBFHHHCHCHCFDAHAGDGFGDDHEEGCAEDEABAEGEGHGDDFAAEFGAGAEAFAFDFEEBED,False +168,8.0,4.0,9.0,2.0,9.0,7.0,3.0,7.0,ECECBCHFHCGFGFEEEHEHECAAHAFFBAEAFHBGAEAHDBDACCCFC,True +169,16.0,14.0,9.0,11.0,11.0,11.0,12.0,11.0,DFDFDGAGAGAGFGHHACBHBHGFFDFGBCEAHBDAEADACCECAAEABBHEAEAEDEDCABABCBGGGGFFACHHBDBFFDFEEGBCDHEHBHB,False +170,4.0,2.0,1.0,1.0,6.0,4.0,5.0,2.0,GGDBEEEEBEAGFFCFGFHAHAEAG,True +171,28.0,14.0,20.0,10.0,8.0,25.0,20.0,36.0,HCHCDCGCDAGAGHGBABAFAFCFAFDFGFGEGHFEFHBHGFGCHEHABFGFHHHCFDACHEFBHHHCHAHGBAADCHBHBFAAAHHHFEGCGDAHAGFBFAADAEACFFGAEAGABFCHCBFDEAGAHBHBAAHHHFHFHCCACGHGHDHDHCHCFCBGF,True +172,3.0,11.0,4.0,4.0,5.0,7.0,5.0,5.0,BBBEBHHCCFEFGFGHGBBBGBDFAFACEHFGFHDBDBABCDEE,False +173,8.0,13.0,6.0,15.0,4.0,10.0,15.0,7.0,ACDCGBGFFFGEGBGFHBHDADHDFGBGBGHCDAGGGCHDHGADDDDDDEBBHBFBFGFAEADGCCBDBDGAAEFBFB,True +174,10.0,11.0,8.0,10.0,13.0,7.0,14.0,11.0,GCGCGCGFGEBCAAEEHEAEHDHDGAADADADFBEDECHCGGGHGEEHBHAHABFBEBHFADGDHEECHBBFBGEGBGDCFBFD,False +175,23.0,12.0,12.0,24.0,26.0,34.0,26.0,24.0,CDBFHAHBGAAFEGHAFGCAFGFGBGBEBEAFGDGDFDADCFGEGBFCHABFCGADHFFEFHFEFEFEDHFGCGEGEAABEGAGHGEAFAFAFCFAEDEDEDHDHDHFFFGFHACEFHHHDHDAGFDFGEGBGDHDBABAFEEEHEBGFGEEAEAHHFDDDGHGHDFCFCACHDDEDEFHC,False +176,18.0,8.0,20.0,16.0,15.0,17.0,11.0,11.0,FCFBECGAFAFABAEEEEDCDAECEDGAAADFHBDBECEHEABABCDCHBGEHAHAGAECHHHADCCCCFCDCDAGCFFEEAFAFGDDFHFHFHDBGGDGDADFGCECFCGCDCFF,False +177,13.0,12.0,13.0,12.0,6.0,11.0,5.0,9.0,DABFHGHCBDBDCFFGABAFEBACAHECGDFFHFHFDFEFCHCBCBAECGCGCHEAEADDDBDADAHHBACABACDCDBFB,False +178,7.0,14.0,10.0,12.0,19.0,22.0,10.0,9.0,FDECFBFDFDFHFGCEDEDEFHGBACCEGGAEBEGABFDFDFCHGHFFEDBFBFBFEGEHADAEFEFEFEABCFHDHDAECFCGBFBGBFBEECECDBEBHGH,False +179,2.0,2.0,2.0,1.0,5.0,4.0,1.0,6.0,HGFEHEHEFEDAFHFEABBCHCH,True +180,2.0,5.0,1.0,3.0,3.0,4.0,0.0,0.0,FAADBBBBEBEFEFDDCF,True +181,6.0,7.0,5.0,2.0,1.0,4.0,3.0,6.0,BHBDBAAGAHCHFHACAHEHBBBFCFCACGGDBF,True +182,2.0,3.0,10.0,6.0,8.0,6.0,4.0,4.0,BCBCECEAEDEDHCCCCHEHEGDGCFFFAHGBFFFECDDECGD,True +183,27.0,20.0,35.0,20.0,19.0,18.0,17.0,19.0,CHCHCFCBDEHBHEHCCCCBDBAADFFECCGCAEAFAHCFGDGAGACABFEAHCBDBDBDACGDEDEDEHEBGDGDCAGABEBEAECEGAGFGCABFGFCEAEAGACFCDCFFGFEHBDBDECACAFHBHCHBHBFAHDBCADHEHACAGDDDGCEBFBFCCCCGAHCFCACAHH,False +184,21.0,29.0,29.0,14.0,13.0,23.0,22.0,20.0,HBBEFAHAHDHCHCGCBCAFABDDHDFAAADBDBEBCBCBEACGCGFFBFAFHGHFCFEHCHDADFCFCEDBGBCCFCFGFHCHCACBEAFBECFCDAGGCGFGHGFGEGACCDCBHBACGFGFHFBFGEGBCHCBCDEBBCHGGBGBDDFAAAEBEBABHBABHGEGBHA,False +185,16.0,21.0,7.0,5.0,16.0,12.0,3.0,15.0,BBBHGHBACDBEAAAFDHEHAGAGAEEEHHCAEAFBBABFBCECAFAFBFHFEDABBBFBEBEBEBACHFHFHDHBFEAEBHAFCHEDECEHBHB,True +186,26.0,34.0,20.0,22.0,24.0,21.0,26.0,17.0,HFACACHCBBBBHBGBEHFHFEAHAEAEFDBHECAHAHDDBGEDCBEGGFGECAAADBEBGCGCFCFCFBFBFBAGCBBABEHGCGCGFGBBCHCEDAHBCEAEHDBAHGGDDDDHEADDDDDFFGBGAGBGBEBABDBDGDGBFBDBDBDHEFEFCFEAAFGEBCGEGBFFGCGAABAGCHEEEAFAEA,False +187,3.0,5.0,0.0,1.0,1.0,2.0,2.0,4.0,DEBGHGAFBFHHBHBABA,True +188,8.0,11.0,10.0,11.0,8.0,19.0,14.0,12.0,HGFBFHFBFGGAHDDEBAHFHFHFCEGFGFGFGBGEGBCEEAFDBBBHFHDBDBGACHCHFGCGFGCGFBCDCDFFAEAHAEFDFDHAECDCD,False +189,24.0,32.0,23.0,32.0,21.0,21.0,20.0,22.0,BBBABAEECDDDEDEHEBECEDEDHHHFHFDFHCDAHAHDBGBGEGFGFGFGFBAGCGDFBFHDHBBCHGHGFAEBEDCAAGFDDADADBDCFGHBABDHECBDBAAHADAGCDCBABABGBHDCGCBCGFEBDCHAHCCCFCFEBABHDDBGBHHCCCGBABDBCEEGHAFEFEDDBAFFFDFDCEAEAEGDBD,False +190,13.0,10.0,11.0,9.0,7.0,16.0,9.0,11.0,AGCHAGCBAHCBGBEBEACADADHDBFBDDAGEFCFCBHDEFEFHFHGHDFGFACAEFHAEAGGBGFCFCFHFDFCFCBBFDAHAH,False +191,14.0,3.0,6.0,9.0,14.0,7.0,4.0,6.0,EAEFDGEEFCCCFCFEAAAEADCDAEAEGGAFHHHHEAAADADEFEBDBAEGECEADFDHDHB,True +192,6.0,4.0,7.0,3.0,3.0,3.0,1.0,4.0,CFGEHCCFCBCEAEHCHDADADABBBACAFH,True +193,29.0,36.0,21.0,12.0,18.0,14.0,23.0,24.0,BBHFFFCEHEGEHDHBGBHBHDEBHBHBEAEBDBFHFHEHABADACGGGADBBHHFBBBAAAAABECDCACHCAGACFCFAEAFAFAGGDAEBDBHBEBGACBHFAFGFGBBCAGGBGHDCBBDGEHEGEACACACEBEBCACAEGDGHCBDGHGHBBABCCHCHCHGBAEAGBFBG,False +194,6.0,3.0,5.0,1.0,2.0,4.0,8.0,5.0,HBHGGFCFCACAEABGEACDCHBGGHGAGAFHFG,True +195,3.0,6.0,4.0,7.0,9.0,15.0,5.0,10.0,HAHEHFGFHHGHGFFCFCEDEFEDBGBDEDACBDFHEBFHFHFEFDFCFDFABEBGHFE,True +196,2.0,2.0,8.0,2.0,3.0,5.0,4.0,4.0,CCECHCDCDCEBHCGEHBHGAAFFFFGFGC,True +197,0.0,3.0,4.0,2.0,1.0,2.0,3.0,2.0,DBHBDFCCCGCGBGEFH,True +198,9.0,8.0,9.0,4.0,11.0,7.0,12.0,11.0,AAAFADHGGGFGCBCBCHEGEFEHDCABDHGEGEGDACBFHFBEBGBECEHAHAHGBECFCGEGAHEHCHF,False +199,9.0,8.0,10.0,11.0,7.0,10.0,5.0,6.0,ACADDFDHDABGCDEBEHAFFBECECDBBABAFAFAEAFHDDDHCCDCGCGHGDGHFCBCBFFEFE,False +200,15.0,9.0,5.0,13.0,12.0,23.0,15.0,22.0,CHGFEHBDGDHEHAHDFDFAEBDAHEFEFEGGGGAAAGEDAHGHGHECEGFGFGAGBFEFAFBFBGBDFAFHDHBHFHFHGDEDHFFCFEDBDHFFFAAHBHAHFCFDHHCHAA,False +201,8.0,4.0,6.0,6.0,2.0,3.0,2.0,2.0,AGCFBBCBCDAHABACEHDADADCDADAEFGFC,True +202,15.0,30.0,30.0,30.0,15.0,29.0,25.0,23.0,DFBBDGHBCEDBFBHBHBCBHEGGGEBEBHHEHCFFHFGBHEGBDFDFGBGDFDFHCEFHCGCFDHDFDEHADADEBCFEFDFEFECDAAHFGDDDCACACACACDBABGGEDAABBBGCACABFBGDCDAGGGGDCDFFFGFCBBBDBDHECGHGDGCGCHCHFBFHHHDHCEBFDFDFCFCGCBCBCFCDABHCG,False +203,14.0,19.0,19.0,3.0,12.0,14.0,16.0,22.0,CHAEADAHBHBHBHBGGDBHFHEAAABCBGEFCCHFEBHCHABABFHCCCHBHAGAFCFBFAAAHCFCGEGEHEHEHFHBHEGFGHBEGGGCCFGFGCDAECGCBBGBFBCHCHCGBFE,False +204,9.0,15.0,19.0,11.0,9.0,19.0,20.0,15.0,FAAACCHEGCGDGBHDCCCEBAHDGDFDBDBHCFGFCFCBCBFGFGHGBFBHHHFHEGBGBCAEBCCCFCFCHGAEFEAGCDHGHGFGFGCGBGBGFDACEBFDFDEHEDGHABFHF,False +205,20.0,16.0,16.0,34.0,30.0,20.0,29.0,29.0,CDCFGDGDEFHGHEHEGGBGBGBHBGEFECDCEBGDAHGCBDDGDHDHEBEDDDDHAFAFDEGCHEGFHFADBEEGAGDGDHFHBDEAEAHAHDDDECGBADEHEFEFDACAGEGFGBDEDECHHHEAEFFBADDDDAEAHHDHDCCFCAAAHCFCFEGHHHHGBGBDCHCHDFDGGEGBFBGHFAFEGEGEAE,False +206,20.0,18.0,16.0,14.0,21.0,4.0,6.0,11.0,ABABAFADEDBAECHGDDAAHEBBDBACECGAAAACHEFEBCDHGBCECECEBEFEAECBCEHEDGAHACADAHACECGDDEEECEHHHFECBCBEBHBDBDBDBAGDBA,True +207,1.0,3.0,2.0,6.0,1.0,4.0,1.0,1.0,FCADBDBGBFEFDFHCDDD,True +208,5.0,3.0,5.0,6.0,4.0,0.0,1.0,2.0,DCCBCDCDCAAAAHDHBGAEEDBDEE,True +209,9.0,6.0,7.0,6.0,5.0,8.0,3.0,2.0,FCFEAEGDADABCBCFGAGCFAFABABCBDHCFDFEFEACBDHEAD,False +210,21.0,21.0,15.0,16.0,11.0,15.0,20.0,12.0,CACFFACCCEHFDBGBGBFHFAGDGDADACGGDGBAACABBECECEGEDHDHCABDFDFDAGHGHGBGBFBGEGBFDFAGAEHFDAHEGABABFGAGEBCCGCHBDEDGBCACFBFAFHDBEBHBABADAH,False +211,10.0,24.0,13.0,13.0,14.0,11.0,16.0,23.0,EDEABACHGHAEGGBBBBECECEBBBAHGHGHCBCECDCBFBHBHFHFHFBBDAGFEBHAHDHGCFAGABCDDBEBEDHGHBCCACFDDBAHHHGBGBGEGEGHGFEFHHHDDBBCDEFGFHDH,False +212,19.0,7.0,17.0,13.0,17.0,11.0,21.0,24.0,FGCAHAHFGEHAAAAAHGDGHGFEEGDHHAEAEDCDFGBGDHDGFECECGGEEHGHGHCFBBHBFEEHGHGHDHFHDHDAAAHDECAAACBCECACAHFDFCCCCCCGGGGGEEEDHBHEFCGDHAHAB,False +213,10.0,20.0,7.0,7.0,13.0,11.0,10.0,5.0,HACBEBEBAGEEHEDAFABBFEEEBGBGBGBAAEBBDDFDFDFHCHDDAFECHBBAFAGGGFAFCGBEBEBEGGBFFCBCBCB,False +214,6.0,9.0,11.0,6.0,13.0,4.0,11.0,19.0,ECECBCFDGEGBHEDDHGEBHHGCGCBHHHHHEHEGACABADHFFGCGBGHDDCEEEEBEFHAECBCHGHGHBHAHAHC,True +215,3.0,0.0,0.0,3.0,3.0,2.0,6.0,5.0,HDFDHEHGGGGHAHAEGEAFDG,True +216,1.0,8.0,11.0,12.0,14.0,8.0,9.0,12.0,GEBDBDCCADDBGFGFEEGEGCDCEFEGEBEDCCFBHCEDDGEHEHDDFCHHHBHBHBCDFDEGEGCHCHEHFHF,False +217,10.0,10.0,22.0,13.0,14.0,8.0,15.0,10.0,DCHGECECEAGHEFGACFBGBECGCAEBEHHAGEGFDFDFHEDDCDBFBABACDDHDBDGCCCGHGACFCFDGCGCBCBGAGACECACBCECGDHEHEHECD,False +218,7.0,10.0,14.0,5.0,9.0,7.0,7.0,16.0,CFCECECDHHHHHHHHBBBHEFCCEBDBABAGDFDHCHGACCHCHEFEGHGDACFBGBCEEEFGHGFCBCHAAAB,False +219,15.0,20.0,16.0,12.0,13.0,12.0,14.0,14.0,AGAEAEAHGHFBFEHBHFGGEEHCFCDADACBDBFBCBFGFBBBCCAEGDGFAACAHBCBCDAFHFHECAFFEGEBCBGGCDCDCDEBBDBDBHHHHHDGAGDCHCAGEGABBEBE,False +220,0.0,1.0,1.0,0.0,3.0,3.0,1.0,3.0,HEHEHFFFGCBE,True +221,4.0,7.0,18.0,11.0,9.0,20.0,14.0,16.0,GGGBFCCCFBFDGCFCFDFHFHCDCDHHHGHFDCAGHCBAEEFEFEFHAEFCHCGEFCCCHCHEHCDCDAGBGBGCDDFDFGFHEHDHFGEGFHFGFBB,True +222,19.0,32.0,14.0,24.0,24.0,23.0,30.0,29.0,EAEAGFDFDCBHFAFADGBHBDAGCDEABDFGEEFFFEEAECHDHBHDGAHHGBGBGBGHCDFDBDBDEDADHFFAFEFGBHBGDCHEDABGBEBCDCHCBFAFBGBAHFHFGEDFHHHBBBBDBDBDBGEGBHEACCHEGEGEDEHECGHGFBHGHCBGAGHGHGEGEGEHAHAHFCCEFHFAGBGBGDADFBB,False +223,6.0,4.0,7.0,6.0,14.0,14.0,8.0,15.0,CEEFAGEBDFAHHDHFAFAHBFFHFCFEHHHHFDEGEGEDEDGAGHDFGBGBEFGFHHCHCHEHECFCACEEFE,True +224,11.0,10.0,13.0,13.0,21.0,14.0,25.0,19.0,CGBAEGEGEHHCGGHGCCBCAEBEGHCHDFDFDFEGBDFDFEFAGDGAGEGCGBHEEGCGBEEGEADACECABEDCDFFFDCAGAGHFHAHGEGEGEGBGBGHHHHHHDABCEDHHFFDHEHEGFF,False +225,6.0,19.0,5.0,11.0,12.0,6.0,9.0,5.0,GBHBDBABHBCBDEDBGBGBEBEBCCFDHDFEBBDDEAEAEAECFGFGEGABCFGBBDHDEFBGBGEEABHDD,True +226,11.0,18.0,23.0,14.0,12.0,26.0,20.0,26.0,EFEFEFGDCDFBHBHADECHHEHEFGFGHCBGACBGACFDFGFCFGFCCCHHHBHFHFHDADFFEBGFFFFFDBCCFCFHFCDGEHDFDBDCAGGHHHHHHBACGCGAGBGHAAAFFCHGBGCADGBBBCGDHEBEBEBEBHCHDHCCCG,False +227,23.0,20.0,28.0,18.0,25.0,23.0,23.0,21.0,FCCBCEFEDAGGBEHCHCHAFCCADFFHFEFAHCHDGCCHAEDEDFDGAGAGAGEFEBEBHHEFEFHFCGDFBGBDHAHBGAHFFFBFCDDADCDEEAGABHBHGHCHCABADABCHCHCDFGHGHBAFFEGECBGADCECGCGCBFEFDFCGCGDEECAGAEAGAGBBBBBCEEAEDECE,False +228,5.0,3.0,9.0,5.0,8.0,2.0,3.0,5.0,DDDACEHGFBCEAECCCCCFCEHEHEHEBCDAEBDHAGAG,True +229,15.0,19.0,18.0,23.0,23.0,15.0,10.0,23.0,HHFHGHEBFHHBCBDEEHCBGBAHAEDEDCGCGEBBDDDDEDBDHDFDEDACCEEDFCEEECBCBCBCDAFEHCFAHBEDACAGHHHHHHHAHGFACACAFBEBEFFFFFDEBEAEGCBEEDADACBHGCGBGDHDHDFDHDEABF,False +230,15.0,10.0,14.0,14.0,7.0,9.0,3.0,6.0,EDADBFADCDCDEBFBFAFEFEDCBADFBFBAHACCBCGEHEHBCCAGDCFFBAAABAGACHCHDDCCCEDHDADADA,True +231,21.0,19.0,19.0,16.0,21.0,13.0,13.0,23.0,EHBFBHBCDAEACABABEHCAAAAAEBDHDCECACAHGFCFBFBDCCBDBDECHCGCAAHHDDCDCDEEHHHADAFBFGFGDGFGHGAGEEFEHBBDBGHAHGHEBCCACACGEDEAABDBCEDEFEHBHEEEHGHFHEHFFGHB,False +232,10.0,11.0,13.0,7.0,8.0,12.0,12.0,9.0,EFGGGHCHBAEHFDFEADAHBBFBCGFGBCBCBCFHFAFAGCGCEBEDCCCHCHDGGGCGCADFEBEBDAFAFAHEFGBHDA,False +233,16.0,18.0,26.0,21.0,12.0,11.0,22.0,9.0,GBGCHBGDHEHDGAFCFCGCBBDDDHHGCEDEDCDBGBEBCCCCDBGBCACBGGEHEDGGAGACFCFCHCGGDGABDCCCGDBDEDEBBCHCDCDBDAGECECAFEFBFEAGAFAGBGAGDDDACAFAFAFCHBA,False +234,8.0,5.0,2.0,10.0,3.0,5.0,9.0,5.0,GAGBBEDFDFDBDGDAEADHGAGHBDGDFDFCGAGACABAGHHHFED,True +235,28.0,16.0,21.0,19.0,24.0,21.0,12.0,20.0,EDHFBEAFADABHFHFCFHFACCBBBHAHDHBADGDBCBDFEFDHHADACBHBEAEDDDGAGACAEHECFCECHHHEABFCFEEHGAFFFADADCDGEEEGEBECEBBCACAHAHADADFFAFAFHGDEEFEBCGCGCGCDCAHBGEEFGADECECAFAHA,False +236,13.0,6.0,14.0,8.0,9.0,13.0,7.0,14.0,FCFAFAFAHAHCDCDGFFEFECEDBCECDCFHEEFAFACHCHCEBGDHEHFHAHBHDHFCGGAGDHHACCBHDCGFGBAAEABA,False +237,4.0,7.0,4.0,12.0,6.0,4.0,7.0,10.0,DGGHBHDDDGDGCGCGADBHEDEDAGFCFEBDHDEBAHAFEHEHCHDBDBHFHB,False +238,25.0,27.0,17.0,20.0,11.0,20.0,27.0,24.0,BGGGHACECEFEAEDBDBHCGDGDHDHBHBHAHAHFBFGCGCAHFHABABEFFDDAAFHFHDAGADFDGBACCCHGHDAACHCHGBEBCCCBDAFAEGHAHGHGEDBDBCBHBGFEAGAGBGBABDHDGAGADFBFGFGCAEBGFFEHBBGDGBBBFFHFBFCDAGCGHDA,False +239,27.0,19.0,14.0,12.0,26.0,20.0,17.0,18.0,CACHFHBABHBABAHEGBDDEBFAFAEACABAFAHAHGHDFEGEFEBEBEAFCDCHABAGEGEDFBGBACAFDCDCAEHEHFHFEEEFABABCGEEEGHDHAHBHDFGEGBAAAFDHECEAGCGEBEDCDHFAFAGAGBGFFCGCEHGFEBEF,False +240,13.0,5.0,13.0,8.0,10.0,9.0,13.0,11.0,HCHAGAEFGBGAGFGCDCAGAECGCGEFEDHGFADADACHDFDGBCBCFEDEFEFBAHHHHHHAAFGCECACBCGEHEADCG,False +241,15.0,13.0,22.0,21.0,14.0,24.0,13.0,15.0,CECEBACABEFHFGBEFDCDBABGDAEADCDHGFGFDDDFDFDFGFEFGCGEAHGHGHCFCDABFEHHABCECBCHFHCACFBFBHBADFEFEFDFDHDHCHCDEDAGGECHAFDHCABFCFDFDGBGCFCACDCEA,False +242,10.0,3.0,9.0,4.0,10.0,22.0,6.0,6.0,CBAAFFFFGBDAFFFFFFFDGAGEHFGECEFEFHCHCEEEDCFAFAHAFBDEHGHCFEFCFCFEAAFAGC,True +243,16.0,18.0,13.0,25.0,8.0,14.0,16.0,17.0,CFHGHAFGFCFEDAGEBBFDGBGHDHAHBGBGBDCHHEBDBDBDCDHDHFAGGHGHABADDCDFBHAGDDDBCACECAGEGDDHDFDFHFHCGCGCDBAFAFDBDEFEACADADADBCFAHBHGEBB,False +244,14.0,10.0,26.0,18.0,17.0,28.0,19.0,21.0,HEHEHDFDFEGEGFGDCBBDAFHFHFDCEGBBDHFAGBHFHCECHCGAFCCDDADGHGCGAGBDCDHDHDACFCFGACEHEGDGFCFCFCAEFHHHFBFDFDCBCFEFCDGAGDEEFEFHFHFEECCCAAABECFHACECFAFGFCBCGHGHG,False +245,30.0,27.0,23.0,25.0,28.0,19.0,14.0,26.0,AAACACBCAEDEBEFCCHCAEGEDEFGAGCEAEADFEBBBEFAGBBBFDAEAEHHHHCFCHCHADFDEBHFACBFBGBFBCHHAHAEEGHHEAEGHGHGHGCAHADADAEAEAGDGBECHDDDDEFFDCDCACAFBFHCHEHEADFBFBGBDBCGABHBHDACCECDDBDBDFDBEEEEHCBAFHHDBBADF,False +246,9.0,17.0,16.0,9.0,17.0,6.0,11.0,16.0,HGEGACAHDHDCDEGFHBHDHECEDEDFDEEHCFCFHBEGGFABEHHHHGAABCCDBEBECHCHFBAHGCGABCBEBECCCCCEGEBBBBDBABEBHGEGA,False +247,10.0,6.0,15.0,20.0,23.0,16.0,16.0,6.0,AFDGEGEFEDCDFHEGEGFGBCACECEAEHEDDHEGEDEFGDDDCCCCGAGEDBABEFEFDGDHDGDCBHBGFFCFCEEEEFCHEFGDGFCDADCFCAEGFGBEFDADADAE,True +248,1.0,1.0,5.0,2.0,5.0,7.0,7.0,2.0,EFCFDAGFCFGFCHEHECEGGCGDGFGFBE,True +249,20.0,25.0,23.0,25.0,18.0,22.0,28.0,20.0,DGDBDAABACHGHEBDCCABFBAHGGBGEAAGDDFGFAHADADEDFHFHGGGFGFDHDEDBACDGDGBFACABBGBGEGEGECFFFEABDEDHFAFGBCBCACHHFHFBFBFHCHCHCECDGDCEHEGCGBBFBGEFEFHCGCBHGDGFHFEABCCEBDBHGDGDGBHCEDADCDCBAEAC,False +250,27.0,24.0,20.0,16.0,26.0,17.0,25.0,11.0,CHCBCACHBABAGHFEEBEGECEBEBEACDGDHHGAAFGEGABEGAGEGADADABAECFGBGAGAEBEADFGFECACGGFGEGDGFBFGCGBFBFEAEBEFAFAFEDEAAAAGBBBCDCDGECCCBCFADABHDEDEGEAHHBDEDFDFGCCCDBBHAHGBCBEHF,False +251,23.0,19.0,20.0,25.0,22.0,22.0,28.0,26.0,ACACGEBFHHCAGAGHGHGCGCGBEHFHFCAGFGCGHEHAHADDDDAEEEECCFBGHAHAHGBDECFADGCECEGEGDGAADBEAEFHFDGDGAEAFDECBGECCHDEEBGBABEHHAFFFFEFDADHBHBDDGGCGCBAGAHABDBDEFEBCBDHGHGFDFDFDFHBAFCBDBDFFGGCHHHDH,False +252,22.0,23.0,23.0,11.0,21.0,24.0,27.0,23.0,CGGAGEGECECECDBFFFHAHGEGCGAGACEDBBBFGFGHGHFCBGHFHBHGEAHAHABDHABABDBECHAHFCFEFAAGGGBGFCDCBEADADHFHDHCEABCGGGFGAHEEAECCCCGBBEHEHBHBHDCDFFAFBFCEBAGAGCCBCAGFDHHEHFFFCFEFBBEBFGEGA,False +253,21.0,15.0,11.0,10.0,10.0,18.0,15.0,19.0,CFCEEFHBGDEEFEFDAGAHAHGHFHFHGHAHAHGFFFGBDBGAAAABABGBFBFBEACGCEDHFACCFFFGECBAECDGGAFAHDHDHBCCGHAHAFAEDHDHGBBABDFCAGABHBH,False +254,16.0,7.0,14.0,11.0,13.0,17.0,11.0,13.0,CDFHFHECACEDEAECCHFHFHGHGCAHAGAGDEDFDCHCFDADFEGAAEAFFDEDCCEDBFCGCGEBEBHGAGFBABAGFHDHAHAEFFFFFBEBCGHACA,False +255,14.0,24.0,17.0,17.0,23.0,22.0,12.0,11.0,EDGFFFGBBBCACDDDBDCFCFCEEAFGFGFGFDBBBFBDCFEFADAHEDBDFHAAGHCHFGACABEDEDEAECEFEFDAABHHAHCECBFBCBFFDBDGHGHFBCDCECEDEAAGEGFBEBCBEEGEBEBEBHCEFBBH,False +256,15.0,18.0,13.0,27.0,17.0,28.0,20.0,24.0,FBDBCHCGDEDCGAGAGDDFBBBFFFFEDACGCHAGGGEGEBABFHFEDHFHFCBDGHGBGDHBCBGAEHFAFHHHDBDCHBFGFGFHFHEGEBDFFFHAHGHCHAHDHEBEFEDGDGAFABDBEHACFCFCEDADEFBDDEAEADFDFHFHFDGHEDDDDC,False +257,6.0,7.0,12.0,13.0,9.0,11.0,8.0,10.0,DDACHGHGHDHEFCCEGEGACCDCDCDADHBFEFEDEGCFBFDFBFEHCHDAGEDECBCBHFGFDFHAHCGABDBF,False +258,17.0,20.0,27.0,16.0,18.0,18.0,19.0,20.0,AGEHCDAGCGFGDCDCHCACDFEAGFGAAAADADCCHGHGHCCEEEGCADACAHECEGDGFBFBFCHCHCBBDBDBDEFCGCBBBEHFHACAGBCHFFBCBCGGGGHDBECEHEHGHBCAGEDEBFCEEBEBDFCFAFHBADDHFHFHFHECFBB,False +259,1.0,5.0,4.0,1.0,1.0,0.0,6.0,2.0,GGGGBGAHBHCGDBECCBCB,True +260,2.0,3.0,4.0,1.0,3.0,5.0,1.0,3.0,BFBCBFHEEGEHCACACHFFDF,True +261,2.0,4.0,3.0,2.0,3.0,2.0,6.0,2.0,CDCABEHHGFGFGEBABCBGDGEG,False +262,17.0,17.0,32.0,25.0,20.0,22.0,15.0,15.0,DHDCDCDGEHCBGBEBACGDFDCBCFCBCEAEAFCDEBAAEADHCEAEHECDDDBDCDBBFFEFGFBCBHAHFCCECGHDHFHAHACDEHECFCDEAAHABBCHGEGDGFHDDCDGDCCCGCACACFCFDADFGFBFBFEGEGEHDACGDFCFCFGBEBEFCF,False +263,7.0,4.0,7.0,4.0,5.0,5.0,7.0,12.0,GCACAHGHECGCHFGFEDHDHDHGHBAEAHBHFHGCCBCHEGEBHAFADAF,False +264,6.0,6.0,13.0,6.0,11.0,2.0,9.0,8.0,DCFBDBEEEEEEADAHGHGCGDHCHGEACBCGCAHEHGGAFAGCCCCCBEBHDCBCEGEHD,True +265,20.0,25.0,22.0,32.0,26.0,23.0,23.0,27.0,DCHBHBCEHHGHDCGCAHHGHDEEHEHBBECDCGBBACACADDDDDFCGEABGBABEBEBEACFHFBEGHFBABCGHGEGDDDEGAHAEFBFDGDHBFGFCDCDCDFGFHEBEHEHBDEAEACBDADHFBDDDDAFEFBGGGGHGHCHEHFCFGFGADDDDBDADHFEBEBECEADACBCFAFHFDFGFAEGHHCCFE,False +266,7.0,6.0,7.0,3.0,4.0,2.0,13.0,8.0,BGHCABHHCHGGBDBABAFCGEGDGAHCEEGEGBGCAHAHACGCGHGFGD,True +267,8.0,8.0,22.0,12.0,15.0,14.0,10.0,10.0,DCBAAGBEBEHECCCCFEDDDFGHGDEDCBCGEGEGEBFFAEHECFCHCHFHDCDCBHGGCCBCFCHHFAFGHGDFCEADCDCDCEBFAFACECAFEFE,False +268,20.0,11.0,17.0,15.0,11.0,11.0,19.0,11.0,FACAFGDHCEFHAECBCBEBEAEGBGBGFHCCBCAHDCFCDGDAEEEFBACADABACECHGGDBDGGGFHEHADAFGFGFGHGHGCFCDCDEGAAAABDDDGHBACACDGDHAGA,False +269,6.0,1.0,7.0,4.0,8.0,4.0,3.0,3.0,DBGECEAEAEAEAGDGFCHCECFAAHHFEFCCDEDC,True +270,18.0,16.0,20.0,26.0,19.0,21.0,22.0,23.0,BFBCDDGAGACDBDGDGDADHCAEACGCGDEBGDFDCDBDGHEHCFFFFFHFBFAFHDDGBHHHHFEFABGGDGDEFCDGHCHEFCFHBADHHCFCBGBFEEEEEFEDEDAFGHGDGCACDEAEACDEDHBHGHBHBHCDGAEACCEHGHAHACAGACBEBGFDF,False +271,0.0,3.0,1.0,4.0,2.0,4.0,2.0,3.0,HFHFEFDBEBHFDDBDGCG,True +272,16.0,16.0,17.0,14.0,11.0,14.0,8.0,16.0,FCHEHAFAFBFBDHGAFABBCDCDHBHEFABCHCHDAGABEBAHDHDFCEBGDFECECECEHECACDBDBDCGAGAGACAGBFBGDDACCDDBHEHBACFBFHHHFHFCFAE,False +273,13.0,11.0,14.0,14.0,11.0,17.0,18.0,16.0,CDFDGBHBFGFGFGEDABABCHHDDEDCHCGAGFBFDADHDCDCECAGEFEBEAFAEHEHGGEFBHCHFHFAFDFACGGFGHHDHGHAHCFAFGEBCBGBGCACDCDEHGFBAG,False +274,30.0,26.0,12.0,16.0,14.0,36.0,17.0,16.0,GGHCBABACFGFHFBBHAEAEACADADABABFFDABBFFEFBAGFHFBFCFBAHHHHGGDGFGBHBFEECEFDCHCHBHGEAHADDGAFAFDDBDGFGBEFFFFFGFACABGFFFAABAFACAGAGHDABABGDACFEAEADBBFBEDEAFFBFBFCFCDBHEHEDF,False +275,6.0,13.0,13.0,9.0,7.0,9.0,12.0,6.0,CEFBGCCCCHDBDBCAFDFDFGFHHCCGCGBGDGDBCBCBHFGAAEGBGBFBGBGECHCDAEGEFADAHEDEBBF,False +276,7.0,5.0,3.0,5.0,6.0,7.0,3.0,5.0,BCCDFEFEFEBADABCFDDHDHAAEAGFGFHFBAEAGHBHE,False +277,6.0,5.0,1.0,2.0,3.0,3.0,6.0,7.0,HBBFBFDHCGEGAHAHGHGFEBHBGGAEAHADA,True +278,4.0,8.0,15.0,16.0,12.0,11.0,10.0,10.0,DHCHAEEEHEHEFEHGFBHEDEGEGFCDCFCGCDCBFFFCEGDBHFDDADGGCGDEDEDGACDCFCFBGBHBDBCFCHCDDDHCAB,False +279,15.0,15.0,14.0,9.0,20.0,30.0,10.0,19.0,EAFFEFEFHBHBHBHCHCFAAACFCAHGBGBFEEBECEGEFDCEFEGCBFHFBEAFDBBGDDCGFDCBBHBHFEFEHCHFBFDGCHFHFHFGFGAAAAEECEFDBEFECEHDFCFHDHFFEAAAAAFGFHFH,False +280,20.0,27.0,17.0,23.0,26.0,20.0,26.0,25.0,AEDGCEBACABABGBGFDCEBHBCBCGHBAEACBHHHCDDEGFHAAFABCEHDBDBDFFGFCBGGGFGEEFEDEAEDEDHHHFHEEEGEGCBCBHBEBGBGECEAEHGHABBBFHEAFGBGDGFFEFDGDGDGHGDAFAGDHDECEHHHAHDDGHGCGEBEFABCBDBFCFCFHBADADFDAHH,False +281,10.0,6.0,6.0,8.0,8.0,11.0,10.0,7.0,GBFFDHAEAECDDBEGDGAEECGGGDHDAFADAEAHBHDEFFFFBCBCECAFABAHGFGFGFGHCH,False +282,21.0,33.0,19.0,20.0,21.0,12.0,19.0,26.0,CAADABABCEABHBABDCHEAEGHBBCCCCCHCBGGGGHHDHGHGDGDGDBDAAGCBHDFEEEEEEBEBAHHGHEHCCGHFBFBFBFGHBDBHAFAGACCHAHFBCCFDEDEHCHABDBEGADBBCBHEHEDDDDBDEDBBHAHBEEEDBBBBHGGGCEFBFAFBGAHAFA,False +283,12.0,9.0,6.0,10.0,12.0,16.0,15.0,10.0,CFCEDFGCGFHFBGCGFGABEGAGAGAGAFADBHGHDEFHHDGCADEGBBCHDAAAGEBEBABFDFEFEFHFHFHFHGBFEGEDDDEFEA,False +284,0.0,7.0,2.0,2.0,5.0,4.0,3.0,5.0,FBBHBHECBFDFGEHCHEHEBEBDGFGB,True +285,18.0,10.0,10.0,8.0,8.0,13.0,19.0,13.0,HHHFGFAHCCBCHCBFAGCGBABDBDGAFDCDAEAEHDADBHBAGFGFGHEFFGHGHBHAFFBFCFCAAABEEEAGGGAGCGFGAGADAGEHAHCDGEG,False +286,17.0,19.0,13.0,13.0,17.0,16.0,12.0,9.0,DBDADABCGDAFEFEFEDABCBEBGDGFEBEBEBEADBDGHCADABFDADADABGFGFCBCDCFBGGEEFCFAFEFBAGGEFHCGAFAHBHBFFEBACECACBCHAHEHEHCGBEH,False +287,11.0,13.0,8.0,14.0,5.0,10.0,1.0,11.0,ADDCHBHFDEACFDBDBABCBCDDDBAAADHFBFBABEHEHBHBCCHFDABAHCDDDCDAFHFEFEFHFHGAB,True +288,21.0,32.0,21.0,22.0,23.0,17.0,23.0,21.0,CFCBBDADEDEDBDHDADCCCEHEHBFBHADADBGBGDCBBHFAEBDHDFDFBEBHDEDBCECEGABCFGFHDHGHEHAAGHGEDEAEABGFCCBEBCFDFAEGGAGADECFFGFBBHCGEBEGAFABDBHFFAHAHAHBHBEBEBCBABDEGCGCHCHBHBGEGEGCAAGGBBFCCGDG,False +289,10.0,13.0,5.0,12.0,9.0,19.0,21.0,12.0,GBFAEDDDGGFEFDHHGHGFGFGDGFGHHHHEGDBHFGGHECBAGAEACFBBDBCADFGEGDBBBBCBHHFFBFBFDAAAEFGFAFAFDFDFHGGGGGECE,False +290,10.0,11.0,9.0,13.0,3.0,16.0,8.0,5.0,DBDBDCFFGFGABEBEDEFFGFGFAFABHCAFABCDHDADAHBGBDDDADFHCBCDCAAGHBFGFGFCCBFFCFD,False +291,22.0,19.0,25.0,28.0,18.0,24.0,23.0,17.0,FCFEFEFAGEGCGEAAAEGEHFHEGFGDGDEDBDEEECBBBEDFHFAGHCAGAFAHABFBFDDGECEBGFDFCFCDBEFABGEDACACDHDHDFFCDCACHCDBBGCDBHBHCFCDHHHBHBGFGFADDGDCDCHCDCACAGAGCDDABCEGHDHFGGDDEAFBFACACABGBGFD,False +292,22.0,21.0,17.0,19.0,16.0,16.0,15.0,29.0,EFHHAHDCDEBEHEHEHEHEHCFDBCBDHCAFEGGHDDBDFGFGHCFDDDDAFADCGCFDFBFBHGAFCCBBEEAAGAGDEDAHAHAHBHBHBHEHCABABHBCCCHCBBBDAHGFDEAEAFHGBGEHAFBGHAFAFAHABCDDECGCHHGHGAB,False +293,14.0,10.0,22.0,19.0,17.0,10.0,11.0,13.0,FDGGCACGCDCACBCDCDGHHDHBHFGGCCFBFBCBDFDAGEHAHEFECBHGDDDCEBBADCDFDADEEEEDEBHAHAGCGCBDGECEHEHAACADAHFHFEFCCECEDECCDAEA,False +294,21.0,23.0,11.0,16.0,19.0,13.0,19.0,13.0,ECDFDEAGAEAGHBFEFGHBBGBABABGDGCCAGHBHFEFGGCBDGDGDGHFHABAECEAGHFDFEFBFECECEFDHGFGABAEHEGEBBBBEBADFEHEHBDBDADADGBHADADHGAEBBBDCACECBCAAGA,False +295,16.0,21.0,15.0,23.0,14.0,18.0,17.0,12.0,DDBBHFDFGBGBHBFFFFFFFGEBCFCGHABBEHDDDDBBBBDGFHFAEDHDHCFCHCECBAHACDCDHAAADDECACAGABAGEFEBCAEACGDGFEFBGBDBCBGGDDAEFEDGCGEGEDEDGDBABADFHCHG,False +296,2.0,5.0,5.0,3.0,8.0,3.0,7.0,5.0,GHDHFBBGGCGBHEHBCACHCGCGEEEEFDADBEGEFE,False +297,8.0,7.0,6.0,6.0,3.0,4.0,7.0,7.0,GDGFBFEFAAEBDBDBAGAEHBDBHCHDGBGCGHGHAAACHCHAFCCD,False +298,10.0,8.0,9.0,8.0,12.0,10.0,12.0,8.0,AAAAAADGHGAEEEHFHEHEFFAGAFHCDCGEBCBCBFBFAFHFGGCGHEDGDFDBGEDEDCBEGEGHCBEBCCDGF,False +299,2.0,2.0,2.0,2.0,1.0,0.0,0.0,1.0,CHCEABDBDA,True +300,21.0,16.0,12.0,20.0,12.0,15.0,16.0,21.0,HFHGDDEFBFBFAGCFAGBGDHEHBHBHAEFBDGACHGHAHFFDFHFHEBBCBDBDBCFCDCACAEDEDHAHBHECABAGCEBHBGEDEGAAHAFAHADCDEGEGADFGAGAHCDAGADAHCHDDGDGDHFBF,False +301,18.0,17.0,21.0,18.0,14.0,17.0,20.0,23.0,BEBFFCAGAGAGHGHFHDHCFDFDEDEBEBEAGFBCCHCDCBCHHGHEACAEFGBGBEDEBCDADHFAADBHBHCHFDFDFHGBGBAEFGFAAEHEHEHCCGHDDDGHCCCCAABCGCGCADACABFEHDBCFHGHGDAHHDFGBGFG,False +302,17.0,9.0,16.0,15.0,18.0,20.0,16.0,20.0,CFEHGDGCGHFADAFGFBFHABACDEDEDGAEHEHCCCBCEFHGHAEAEAHAHEHEHCDFFAHDEAFDFGBGDHHFHFAGGFFBEHEAEAFFFDGBGCGEECAFFHEHEHDACBCFCDDDDCBCBHGAGCG,False +303,17.0,9.0,12.0,14.0,11.0,11.0,11.0,15.0,DFDFAGHHDEDEHEHECGFACAEADDHDEDCHCECFHBBBEGHBACGGGAGAHDHAAADEHEAFADGDBDFHFGBABABHBFCHAHACCFCGCEADFCFG,False +304,32.0,22.0,21.0,20.0,17.0,21.0,22.0,16.0,HABACGCBCGHGHADEGABAFHHGFCCGFFFHFHAHAGACFGEEAHAHABABFBAEAEDGDBDFFFFEGHGDDDCHFAFGECACECECEDFBEAAFBCGAGECECFCFCBGGADADGHACAEBHAHABGGDDADCDADBBBGHEFEDDDGEFBDBDBCBABCBAAAACFGB,False +305,22.0,14.0,10.0,9.0,20.0,15.0,19.0,12.0,GAGABHEFGHGABAEDECGAFABBEFEAECCAAHGHBEEEEEFHFGFGAEAGAGDGHGFAAAHAGAGFBECEFFBBGHGFCBCGCADEDBDBDBDFEECEBEDGAAEAFAHHBFCFCDHGH,False +306,7.0,13.0,6.0,7.0,4.0,5.0,5.0,12.0,BABAFAHDFDGBHHEHBDACHGHGDDBDHFFAFACEBEBEBHBCAHBHDHCGBHBCGCB,False +307,27.0,19.0,23.0,17.0,31.0,29.0,21.0,17.0,FADCDEGEBEGHDAEFEAEBHBCBAFAHAFGEGFBFCAHAHCCBDFHGCEFFCFEFEAEAFCBDADADHDFBFBEBADFCFEFBFBFDFCFGFEAHBBCCCCHHBHAAEGEBECEGDAEFDGECEFEHGAGEFEDGBABABHDHDCDCGHAEACAGFCECGGHEDCFAAAGAGCEHEGEGFGFE,False +308,16.0,23.0,23.0,25.0,22.0,21.0,28.0,27.0,BHGEFEDACAGADADGDGDBBFBCGGHGFCFCEHHDCDCEGFCFBEBEHDHCHCBEDDHBBEBGGFDECHCHCBFDFBGEHEGEDEGAHDBDAHGBGDGBCFCGCGBBAFAFABBBFGFHAHAEAGFFFGDDCABHECEDEBEHDGDEDEGCHCDCACHCAFGGGHFHFHGHGCAEHHHHDDBEF,False +309,11.0,10.0,14.0,4.0,9.0,15.0,8.0,17.0,CECHBGAHBHAHGCACBEFEFDCCCCCBCDCGAFFFFFBCBAFHFHFHDAEAHGHBHBHEHBHCGFBHAAGEFEFEGHAHDFFCAEHG,False +310,7.0,7.0,11.0,8.0,8.0,14.0,8.0,4.0,AFACGFEEDBGHDDADFCFCFCFDBGBHEHFAGDCACFCFEFBDBGBEBFCFCFCADGEGEAHCFGE,False +311,1.0,3.0,3.0,4.0,1.0,4.0,5.0,3.0,DHHBHDGDGCFAFGEBCBCGFGFD,False +312,9.0,6.0,12.0,3.0,7.0,3.0,4.0,5.0,AAEAECGCDFDHACECEAEBHBACCHCHEGCGCHCACBBAFAFCDGEBB,True +313,10.0,20.0,11.0,11.0,10.0,21.0,14.0,10.0,FHEBEBCAHAHBFGFGHGFAFCFDBDFDCHBECCCHEACABDGFBFEFAFAHGBFBDBDBFCCCEBFGGBGFAFABEEAEGBBFFDFBFBDBGBGCGDEDHFHDGGH,False +314,11.0,11.0,19.0,12.0,11.0,7.0,10.0,11.0,GBHBFGDABADADBDCDADHBGCECHCHCGCEAGCGCDCFEAGAEAEHECEFFBECDCGEHCBBBCGDHDBDADCFFEFCACAEBHHCHGHC,False +315,15.0,20.0,19.0,23.0,12.0,16.0,12.0,15.0,CCCCEFDBDHDCDFDCHFHFDEBACECHCGGFGAHDDDBACFFFDFBBABABDBACADAHCHDGCFFBHHDHDHGCCACEDBDECEHEBABHFDDDDGEFBFBGBEBFAGAGBGHEHDFEBABAEADBCGCG,False +316,6.0,8.0,6.0,3.0,8.0,2.0,0.0,9.0,CBCDFDHABAFEHBHBHECEBECHHBEEECEHAHCDAHABAB,True +317,5.0,12.0,12.0,7.0,8.0,8.0,7.0,11.0,CHGBGBFBFDABACAFFFCECHCEGDBBGHCCBGDGFGHEHDHCHBBCCECEBEAEAEHDCDHHBHBDFF,False +318,19.0,29.0,24.0,19.0,24.0,39.0,20.0,15.0,CFEFGHBHFHCEABFCCCFFEFEGBGBAHAHDBABCBGBGBGAGAGABHCCCFFFEHEDGBHEEDHDEDBHFDBCBGBFCFBEDFAFCFGACEFGFGAAFFFFDFEFECCGEGBDAAECECABEFDFCEAEAHFDBABDCHGBGBGBCACBCBEFGFGFCFHDDFAEHDFFEDDFDFBFBEBEBFHFCD,False +319,8.0,5.0,5.0,2.0,5.0,4.0,3.0,7.0,HAAEAHDHCBDEAHCGFGCEABAEAFAFHFHBHBCBCEG,False +320,4.0,0.0,2.0,0.0,3.0,0.0,0.0,1.0,CACAEAHAEE,True +321,19.0,25.0,20.0,14.0,21.0,25.0,19.0,10.0,ECEAHAGAGDCFHAHAHABEGAGBEBFFFFFGFDFDFGCDCBABEBGBFFFAGADFDGHGABAHAGCBABGDGEEACAEDBCBCEEFHGDDCBCEGEFEBEBFGCHBHBEDFHBCGEBCDCFCEBEFEBCBCBCBAGFFAFAFDCGEEFDCBF,False +322,4.0,3.0,7.0,8.0,3.0,3.0,6.0,6.0,AGDFDFDAGECEDDHCHGHCBFDEBCBCHCHCDDAHAGGG,True +323,20.0,23.0,10.0,13.0,14.0,23.0,24.0,21.0,AGAFFGHGEBBCDCEEEGBFAHAEGEGCGFGAAEBGHEBDGAGEBABEFCHAHADFBFDFBHBHBGBEBFBFHCACGCGBFBFAHAHFEFDBGGGBGFGBBEDHGHGHFHDHDGDHBFBFDFHFHFACADAGEFHCAADHBHCADFGA,False +324,6.0,10.0,13.0,15.0,5.0,10.0,12.0,7.0,ABBDDDDGDHDCBBHCHGDGBAEGEGHDBCFGFBEBADGCGCGHFFFFFCFCBDBDGDCAAAFDHCCCECDFDHCGEG,False +325,14.0,17.0,16.0,18.0,24.0,25.0,25.0,12.0,EAGDFBFEHEFGADABCCEGEAEGEGHGBFBDEAEDHDFEFDHCHGBGEECDCDCDCHCDEAEACCBEGAGEBFBFBFCCGFBEBCCDEDFDHHGAGAGEEFFFFFBGHGHBDECEBAFAFDFDGGGAHBEFGFGFHDGDEFGCABFBFGG,False +326,10.0,8.0,13.0,7.0,11.0,10.0,9.0,12.0,HGFCFAFCFAGADEDBHFCFCHHAHACEBECCCCEGEFEFGDBFBHBGBCEEABCECAADDEDHDHBGEGAHCHFHGAGH,False +327,13.0,9.0,7.0,7.0,11.0,9.0,9.0,4.0,EFEGEFABAFHDBFAFGGEBEFECCCEFFDADBDGEGAGABABABFBDDAEAHAHGHEAAGDECCCGCB,False +328,11.0,7.0,14.0,13.0,15.0,16.0,11.0,12.0,HHHHFDGEGFHFHGDGCCHFBFEDBAHGFCDCGGDDACACEDBGEDEHHGHEFEFCFGFAAACADHFAFCFCFCBDBAEEEEGDFBFAEAEDEDEBCCC,False +329,14.0,9.0,16.0,7.0,13.0,4.0,16.0,18.0,GCAEFCFCACAEDGGEGBGBGBHBHAHECAAAAHAHECECHGHADDCBCFCHHGAGEGDGEAECGBHDACECBHDCDGHCHGEBHBHEHCFGEGHHA,False +330,6.0,12.0,18.0,17.0,8.0,10.0,10.0,6.0,GGFCECDCDCAABEBEHEFDDADGDBDHGFBFBEDHDFBHGGCBCBCDCBCHDGCBCBEDCDGDBECADACCCFEFGFGFHDADFCC,False +331,11.0,25.0,21.0,16.0,17.0,27.0,21.0,23.0,FFFCHCBCGHHHGGCEBEDFCHAEFCFHDBDBABFBFEFBFHDHFBGCACHHFBFDFGFBHHDBEFAFAFHFEEEGEGEGEDBHCDCACHHGFGFHHBDBDBHCHGEDBDECECECFGBDBCEGGGGCCBCAAADAHBBBGBGFGHDAEFGFBBGHDCFCF,False +332,31.0,34.0,15.0,23.0,18.0,19.0,14.0,23.0,HBFBAAACBDEABCHDHAHDFEFHAAACDEBHBHBHBCBHBHBGCAFGBGBFFDFGAEAEBDFFADADACADDDHAHAEEBFDFGCCCFCAEGBCBAHCGEEEEEEBFDFEHBBBABAHADBDEDFGHHBHBDDABBHBHDHFCFCGEBAAAEGFDFDGDBBBAGAGABAGHBHCAD,False +333,20.0,17.0,9.0,14.0,13.0,13.0,13.0,14.0,ABGCECACBHDHGEEHEHBDAAAFDEDGDFAFABCCGHBABEBEGADADFDEHEHEGBGAHADDHHGHGCGFFABAFDBDHABEFDCDFFAFBEBHBAFAFABABGCECHGBG,False +334,7.0,5.0,2.0,4.0,6.0,6.0,4.0,9.0,GCGBFBHAHEBEAEDCGEAEHHFHAHABFGFHFHDEDADAFHB,False +335,17.0,13.0,10.0,10.0,9.0,12.0,9.0,20.0,AGHHAHAHCBABFGADADEFEFEDBBBBHHGHDHBCECEHFHFHBHAHDEAEAEBEHACAGADHCHBGGFFFHACBDFDAGHCDGDCFCACFHFBBHGAA,False +336,10.0,13.0,6.0,5.0,11.0,4.0,11.0,9.0,EGEBEBEGEBAHEFBCBEHGDFHFAFCBHBGDABHGGGBGCGBABADHDCEABABADAEEGAGCHCHEH,False +337,17.0,16.0,15.0,8.0,14.0,17.0,17.0,24.0,HBGBABHBHDFFAHAHAGAEAEAFACGCBCECFGDGCCEFEFHHHABGFCHDHGBCBHBDGDHEHGHCFCHGHDHFHFBFDABHBGBAFHEEGEGECBAGEHBHCHEFEADCBFGHCEFGCGFAAAAF,False +338,18.0,20.0,22.0,16.0,18.0,27.0,14.0,22.0,AEAEAEAFHDHAAEFBDHGFGFCAAAGADFFEFBADCHCHEGBBEBGFGFGEHEDCFHAEBHCDCBCGAECGCHCHBFBEBHHHGCBHFDDGHHHCHBDEDECBDFEFBFGFCFBFBCBFBFCDEAFDGABADADBFFFFECECADHHHCHCFCFCG,False +339,24.0,25.0,25.0,23.0,21.0,21.0,28.0,25.0,ABAFDFCFCGHGCDBDGEGEGCAAEBHBHGHGHDADCGCHFECEBDHDABHGCGHDHEEEBFBFBDDCDGEEEHBFFCFBFAFAFGCCCHGGFGCACHEDEHGDDBHEHDACAFHEABGCACABDBEBFDGHGHFHEAEAEADACGGBBBCGCGDGBGBFCHAHAHFBABFCEHBADGDEBACGCGFAFDHD,False +340,14.0,19.0,9.0,8.0,9.0,16.0,11.0,11.0,CAADABAEACBCBGAADHBFFFBDBDEGABHHHAEFHBCFHBEBGFDFBFBDBDBDAEGEGEFCGBFBAEGBGFGFHFHFGFCBCAAGAFEHHHCBC,False +341,2.0,6.0,2.0,4.0,1.0,4.0,1.0,1.0,ECBDBFAFDFDBGBHBCBAFD,True +342,10.0,9.0,6.0,7.0,9.0,12.0,7.0,13.0,AEAHAHFEGEGBGAEBBHFDBGBHHGHAFAFAFHFDDCDHECFCACFHFHCDCDHBEBFAFGFABEEEGBDHH,False +343,12.0,23.0,13.0,17.0,19.0,18.0,25.0,20.0,GCGCGCFABHCGAFCFDFBHBHEECDDBEHEAEABABAHHFFDFGEBEBGCABAGGEGEDEDHBCFDHDGBGDGHAEAGDHAEEECHHFBDGCFCDBDHFHBBBDHHCBEHFHGGGFGFBEBEFEFCFGFGHGDGDBHBGBABDGEG,False +344,8.0,19.0,17.0,14.0,18.0,17.0,16.0,26.0,BFBHCHCACDDFCHEHAFAFEEEDHGHBEEFADGGFGEEDEDEFEFBFBHHGHGHDEFCGCGHDHDBCHDBCFCGEBHBHEHFDEAEBEGCGBHBFBHBCBCBCBGACCHHHGHFDFCFHGDGHEHDCBAAFHBG,False +345,14.0,25.0,9.0,16.0,24.0,29.0,24.0,20.0,BDBDFDFEGEDADGGGGDFAABHGFGFEBHFECHCEDBABFBEDGGCFCEAAHGHFBBHHHHHHEBEBFAEEBEDGDCHEFBFBFBHEGEGEAEBGGCAFFGDGAGAGHFFFFFGCHAHBHDEDEFHBBBFDFHFBFBFBHDEFGBEDEGEGBAFFCACEG,False +346,20.0,21.0,26.0,20.0,28.0,15.0,21.0,20.0,EDEDFHFHEDCCECEHEHCGBBAEFDDHBGBEBGAEHECGCACECGCGCDEHCAFAECHBBDGDFCFBBHBEBEHDGDBDCAGACAHAHDHCEBEHEACDDDFFAGAFAFCGEACACGEEAHAGAGAGEFEFHFBGCHBDBHBCGDGCECHDHFBFDCGCBBEBDAEGEGE,False +347,9.0,10.0,7.0,7.0,9.0,11.0,7.0,1.0,DAFCBCBAFDEGEGEFAADGEGEAEAFGFBFEFCFGFCFHEDCBGBEBAFDDABCBABDBC,False +348,23.0,21.0,22.0,23.0,12.0,21.0,19.0,12.0,DBGBGFCCGCDHGFGFGFDCDEAEAFBFBHGHBCBABAFFFBBAFHFCDBFECCDCACAEADFDEDGCFCHBBBBDFDCGAHFGEADDGHFFDADEGEAEFEDECACACAFADCFCAGBBABEDGDHCGCACACHBDGGAGBGBHAHADDDHB,False +349,24.0,18.0,28.0,33.0,14.0,23.0,32.0,22.0,DBDACACDEGGCFCBGBHFGDGDEDHHADCFBFDFDAAFAGDGCFCECEGDGFBAGHDDCDCDGHCFFAFGDGDHDHFGGBGHDCDCAHFEDBFBFCDDEDGHAHADABHBEAAACADGBGAGAFHCCGFGCGDGAEAGDGHFHFEBAHCFCFGGGEGEGAGHBBBDCCHCHFHCHDFDBDCDEHECBCEAABC,False +350,8.0,4.0,6.0,7.0,7.0,4.0,16.0,7.0,EDGFGACAGBHBEBAGACAGEEEEEGGAGCGCDAFHGDCDHGHCHGBGAFDFDGGGDHH,False +351,14.0,22.0,13.0,15.0,4.0,11.0,14.0,13.0,ABCCHHFHCDBDBDBCCGCGFFDFBFGGBAHADDGDCDCBAHABEFHBBDBDBDBEBEBGDAEABDGFHBHGAGCBFHHHHHACGBGACFBBDGDBFAGAGACACF,False +352,23.0,10.0,18.0,19.0,18.0,25.0,14.0,15.0,GFADHDHFCGCBFFFHHEDFDHAEEFECAGBGEAHAHADAEGCBFBFEGEFHHEGGCFCHHAHAHEBAADAGBEBEDEDGFEFAFADADFGFAFCECECFFAFACACHCDFDADCDGGFDHCCCCDGDAFBFBEADBDAECF,False +353,28.0,26.0,15.0,29.0,24.0,17.0,31.0,29.0,EFGDADGCGBGBGBEAEHGHFDDEDEDEGHGEGEGHGHEHGDGBGFEAEGDCHCHDHFHEHAGDHDFEBEBEBEDCDCACAFGFCABFEGBGAGHHBDBABABHHAHAECEAGBGBHBFEDHCFCDGAFDHBEACFHHGDADHCFCBAAHFFGFDADBBEBHACABAHGDGBEAFABDBGGGGDDDAAHDDDHCHAABE,False +354,2.0,5.0,6.0,7.0,4.0,6.0,4.0,6.0,BHGHAECCCFADBDHDEDBFBHDCDCDFGCGFGFHHEFEB,False +355,6.0,5.0,6.0,6.0,6.0,7.0,2.0,4.0,HFHCGCGBFEAAAHAFBCBDEDEDEDCDFFABBCFCADFEHE,False +356,6.0,7.0,14.0,10.0,18.0,19.0,15.0,16.0,FBEHFGEHFDCDGGGEHCDCDFFFHBABDFDFHCCFEFECEHEFCAAGFGBCBFGFEBCACACDFFGHGBEHEHEHFHCCEGEGEGECAHEDEDGDGEHHHGHFF,False +357,14.0,24.0,11.0,19.0,13.0,13.0,20.0,12.0,CAHGEBBDBFBEGHAEDBDHDGDGECACACEFBDBFFGADBHBCCDCDHDEGEAFAFEGBFBABHFHAEDEDGHGBEBGBGBGFFBCGEGDAFAFAHAEBCGDDAGHHBCBDBDBFBDBDCGGGGH,False +358,14.0,23.0,16.0,16.0,14.0,16.0,6.0,16.0,HBCBHFHFHDBAGAEDCCCBFDFHFHDHDHGHABCFCFAGEGBBBFDADADBEBHFCFDFCBADDBCBCBCAEGEFCBABAFAHBFBEBEBCCEEHEDECBFAEHGADHDHEHBDEFBCDA,False +359,13.0,21.0,20.0,21.0,14.0,16.0,20.0,15.0,GFDBDCACAEBEBEBHBCBCECEGACHCHAHAGGBADADBDFCFHGDGDGEBHBDGGFGFGDBDAGABDGDGEHFDAEFFGFDHEBCCDCHCFCECHGDBCEHEFDFDABEBGDGHACFFBDCEAFGDBCGCBCFHBHBH,False +360,2.0,2.0,1.0,1.0,3.0,6.0,2.0,3.0,GFFFEFEBDBEHGCAHAHFF,True +361,14.0,17.0,14.0,17.0,23.0,22.0,11.0,18.0,DHACABDDDFEFBCAEAEAEFCFEFCFDFHFAFBCBCHGHFHEAEGBHBGCFCHAEBEFECECGFEDEFCCHAFAFAFADGHGBGDHDEDAHBHBHGEEBDHDBEEHGDEDEFBFBFHFGFBDAEBDGCHEEDCHB,False +362,7.0,7.0,14.0,4.0,6.0,6.0,6.0,3.0,CCBCGEGCAFAEADAGFGFCFCBCGHBBDBCGEAHAFCDCACBCHCEEFECBD,False +363,10.0,8.0,17.0,16.0,17.0,20.0,8.0,12.0,FEADABEGEHEBEBECFCDCHBHCAEEGHCFGFGFHHEFEFDFGFDECCACHFFFCDCGADAFGDCDCDCEFFFFAHAHBEECCDADAFFBEDEDEDHCFCDBHGHDB,False +364,8.0,4.0,4.0,12.0,13.0,9.0,10.0,11.0,FFHEHDFFAGEGEHEHFGDDDEDECEDABHFGFGDGAFADAEECGGABDBGHHCDCBGFDHDHAEAEHEHE,False +365,6.0,2.0,5.0,1.0,4.0,5.0,1.0,5.0,FEACAGFEFHCEABABAHFFEHAHCHCDC,True +366,11.0,5.0,9.0,15.0,4.0,9.0,12.0,5.0,CCFDEDFDFEFEHDBDCDHGGGGDFDAACADABFGCBCAGAFDFCGCGAHAGAHDBDHCGEBFDADADGG,True +367,22.0,11.0,14.0,10.0,20.0,19.0,35.0,19.0,DGGGBCECGDADABABHEHBHGAGHGFAFAGBGBGEEACACFEFGGGEFHCDEEBEBAHCEFFFFHAHAHGFECBHGGEGEHAHFGBDFHEEGCGFDAAAGEGAGFEFHFGAGAGDHAACAGHGCGAGDGBFHFGCGCECEHFHDGEGCD,False +368,2.0,3.0,4.0,0.0,3.0,2.0,2.0,2.0,BCECECHFHFAGEGBBCA,False +369,2.0,7.0,10.0,3.0,12.0,8.0,6.0,9.0,HHDHDCCEGEFFFHCBBHDEGEHEFEFEFEFBCBEBHBCCGCHEHBGGACECEFGAC,True +370,17.0,20.0,13.0,14.0,12.0,20.0,18.0,16.0,HEFEBECCHDECGCEBBGCDBDBDGFGFAFHGDDFDHBBBFAGDFAGACEFHGBFDFHFHFHCGBEDHFCFCFGAAEDECEFBFAHABACAGAGACAHABFBFGEGDBFBHBHDHDGBABAGCGEBAHGH,False +371,14.0,16.0,16.0,7.0,13.0,5.0,11.0,14.0,GBGBEHFHFBBBECAABDEABAGAEDEDBCEGECCACAGACACBCHCECEGABDBEBHBHFHCDAEADHCHCHFHCEABBCDHEGFGCHBGGHGHA,False +372,9.0,15.0,11.0,10.0,12.0,17.0,13.0,14.0,BEBEBGFFBFGFDFGCGCGFHDGGCFAFAFBFDHDEAEHEHAFBFEGHHEBGAGCHHHDDCECGCABFBFHFEDEDHBBCBGBCAGACAHBECEDDHBHFF,False +373,14.0,9.0,8.0,14.0,6.0,19.0,18.0,14.0,BHEFAHAHDDDDFBFDFGFEFHGBBFAAAGADHGBFCDGBEFGFCHHGFGHGHFHGEGAGEEAGDDABGGCCCBHBHCHDFAFAFAFGFDFDADADCGCGHF,False +374,13.0,6.0,13.0,5.0,8.0,10.0,12.0,6.0,CBGADAHAHAFAFGCGFGCDEAEADADCBHDFAACCCAFHBBCEGEGECFHAEBEHCGFGFGEGCGCFCGABF,False +375,8.0,5.0,6.0,3.0,11.0,9.0,8.0,4.0,EEEEHFFBFGGCGHGEBABEEFCFCBHGDBHFAFAFDFGAGDGAECECECAAAE,False +376,6.0,8.0,6.0,9.0,8.0,5.0,12.0,5.0,AEGEBACACHCGGHDBDBCEGEBEBHFDDGDCDBDBEGCAFBFGGGEHEAADFDFHGGG,False +377,2.0,3.0,2.0,5.0,6.0,4.0,2.0,2.0,EDEDECEBHBGFGAEADFHBDFEFDC,True +378,18.0,11.0,12.0,20.0,13.0,19.0,14.0,21.0,GAEHGHAADADADBFCECDCFCGDDFCGHAADFFFGHBHFDCDBFHFHGHFAGAGABADDHAEDECFFFAFAFDEDEBABFBGGHBCBAACBHHHFFEDEDADBEHFHGCGEEDHDCDGHGHEHEHCH,False +379,15.0,10.0,10.0,14.0,7.0,13.0,13.0,11.0,FHGHGHBBCDDDDABABGCEDADCHGAAHAFCFBDBDADFCFDDHCHFHAHCHCBCGGAACAHGGGGAGBEDFDFEAGDGFEBEFFAFAEBEF,False +380,20.0,20.0,27.0,28.0,18.0,28.0,19.0,15.0,FAEAEHHHHHHECBHFFFCFCDAGFGDEDCDCBGFFCGBGEGBAEAGFCADGGBEBEFHFDCBAEFDFDEDAHAHGEDAGBGFEBEGFDDDFDFAFCCCCCCBCBCGCGCACDDBFAFBCDADCDEDBCBCGHGFGBBAFDCDHBHDDBDCECACDFDGABFEDEAEFHHAAFFF,False +381,9.0,4.0,8.0,8.0,10.0,3.0,5.0,2.0,DEDECFCECEDAAACHEGDDFDFCACECGAABDGCHBEBGDGBAEAEAE,True +382,28.0,23.0,23.0,25.0,22.0,19.0,22.0,24.0,EBAHHEDEDBDHHGADFEFEHDHDGFFDFDADHDGEACBEHEFGDGAGAGEBCDCBBAFECHGGBHCHCGGGCGAFCHCHBBEBFBFHFCGCGEDEAAADABABADFEFDCDCECDCHCHCBAAAAAAHAFEGEADCCFHFEBEBFHDHFAAAGCBBBCDHDEDFBEGHCBDBGHGCGHDEAGABA,False +383,4.0,5.0,2.0,2.0,4.0,7.0,4.0,2.0,FAFBFGCGAGAGFBDEFEFHABFBDCHEBE,False +384,23.0,10.0,11.0,21.0,17.0,14.0,20.0,15.0,CBEFFDDBFAGHDAGAGAGDDBEGCCCDCBHHEAEFGFEEEHEACACAGAGBDAAHFHFAFADEHCACGDAEEFGGHEHBCDAGAEDEBFGHDHEHDHFHAGAGAGAFAFABBCDGGGDBDGDEDEDFDHD,False +385,16.0,15.0,15.0,12.0,17.0,20.0,20.0,23.0,FGBHBHAHAHBDFEFEBCAEEDEAHBHBHEFDCBAFCFAFAGHGHGACDHBCAEHGHBABFCFDGDFDFHFDBGFGHHACADACHCGBEBEHEACGEGFGFGDGEGEGECEADACBGFHHDFFHFHFGGBHCGCEEHC,False +386,22.0,28.0,19.0,25.0,19.0,24.0,12.0,27.0,BHDGBHDFDFDBABGDHAFAECECBCBCFCBEBHHHEEEBAFDFAFADECBDFDFAEHBHEHEGEADHHHFHFHDBFHAHADADFDFCAHBCGCDCBBBGBFAFCFHAGADDBFEFEAAHCDCECBDFFHFHBHBFEDCACAGEFDHGBEHGBCBHEEGAGHBDBDGHADADCBCB,False +387,16.0,23.0,23.0,12.0,27.0,6.0,20.0,14.0,EDEBGBEBCGGHCACBHBEGAGHGCGEGFCHBDCHGHBHGDADADBBCHCBEBACGEGEGEBABABDEEHECCCCBBBGAGAEAGFGHACCBBABAGFBEEEEEECGDDCDHEEEAEAECDCECGCFHFCBCEADDHEBFH,False +388,29.0,22.0,29.0,26.0,26.0,22.0,19.0,18.0,CECEGHFBFDDCDHGAFBGDFAAHACACAEEBEACFCAEECCGCGCFFFABGBGDCDGDEAEABHBHBFBHAHDCECECHFEFBACDDDEHAGABADFDFDBDBDECECEDHDAAAAEBEGAAADGFBFADACHEAACFGFGCGEHFHFCCCDGGBCEGFAFEBHCDAGBCBCDCEEGDBDBDHFHEBEHH,False +389,6.0,5.0,9.0,6.0,6.0,10.0,3.0,6.0,AFFFACCCEHHHHACDFDEGCBCDEDCFBFBDBFHFHADGCGCEFAFAEBE,False +390,5.0,5.0,8.0,6.0,3.0,4.0,2.0,9.0,CHCGBFDADACBFDFCHHDHDHCGCBFAEAEAECHCHBBDHH,False +391,17.0,18.0,29.0,20.0,13.0,16.0,17.0,22.0,GDCDGHHBEBFCFHGHAAAHBCDCDHFHEHBDDDDDCDCACHEBDBCBFDACBCBHACCDCGGGGCBCFCFBACADHHCFCADHHHGCBBGDGCGEEHEACAGGFGCABABDBEECECECFAFAGHHDHDFBFGFHECEFDFAHBHFGCACE,False +392,4.0,11.0,10.0,5.0,8.0,5.0,3.0,15.0,HHHHEEDDBGHGFABEBECCBHBCBEDECBCHCBEFEHDBDHAHBHFAGCHCHCBCAHFHF,True +393,5.0,6.0,6.0,2.0,4.0,4.0,5.0,6.0,HGFGHHHAGCGEFEBDFDAAHAFCBCBCECBGBEBHCA,False +394,21.0,28.0,17.0,22.0,17.0,15.0,15.0,14.0,DHAAAAFCDBDBDGGABBBCHCACGHFBBBBBBBAAAAFBBBBBEGEABCGFDHEHEDBAADEDEDEHCFEBEGDHFGGECDCHCHBDCEFEHDBDBDBDCECGCBFDGBADHGGFAFAFACEGEFDFBABFFEGDAACACHEHDHDCG,False +395,17.0,17.0,23.0,13.0,25.0,16.0,32.0,27.0,ACFCFGGGEEHEGGDEHBACACECEFEFHDEDFDGEGBGFHCCACEEFDACHGHGHBEEHBACCCCHCEFDAGAGEGCBHBHBGGGDGCFAHGHGHCAEFBBBHBGBHHEHEBGGEGEFHFHFHGHGCFCGHGDEDAAAGCBBBCHAEAHDHDFGGGEGBAHECDFDCAE,False +396,2.0,4.0,1.0,7.0,6.0,10.0,8.0,9.0,GCGFGFGHBFAEGFHFHGBDHEFEDHDEFEFDFEFBGHHAHGDBDHD,True +397,12.0,14.0,13.0,17.0,13.0,20.0,12.0,15.0,CEBHFCBGHGEGEACAHBHBDBGBADFDHDFDADHHEHFHBAAFACECECEDDGDGDCCCHCGBBDGFBECGDGACFFFFFFDHDHAEFEFBBGBFHFHECAFDBEHDFAFAEGFD,False +398,28.0,19.0,7.0,24.0,27.0,19.0,20.0,15.0,DHEAEADDHGAAHAGEHEBDBDHFCFEFEFEGAGHGBFHECAAGDCDADFCHDADADFDHGBGAEHDGFBFAFAFEFEFEHCAAAGGBBABDBCEADADFEGEFHADEGGGEGEGBGBDADEEBDBDHEEEDADEBBFHEEFCFEFAAAGABABDBHBG,False +399,0.0,3.0,1.0,3.0,3.0,3.0,0.0,4.0,DDHFBFEFDHBHCHEBE,True +400,14.0,15.0,8.0,10.0,12.0,16.0,15.0,13.0,BABABGHFHEHEAEBFGHDBCBGDCFFGAGDGFEFEFEFHDCAGAGHHAHACBCBGAGEGEDBDHDEBCACBHAHCFAFEBEDFFFBFGEGFABHGDADFBHG,False +401,11.0,5.0,16.0,15.0,7.0,18.0,6.0,17.0,EGDHHBGCGFFFFECHDAFAFBFDHGHAACFFFAEHBFDFHEHDFDFDABBEAFCCCCCCCFHAGADDDCCEHEHCHDHAHFHCCCFDHDHDADG,True +402,3.0,10.0,24.0,13.0,15.0,13.0,11.0,19.0,CBBEDHAHBDBDBGCECHHDHGHDCGCGEHCHCGCEEEEHFHFECEGBDDFBHEDBDADGFHCHCGCBCDCEAFGFGHGHCECFDECCCCCDHHEBFHFCFCEHFFCF,False +403,1.0,2.0,2.0,2.0,0.0,1.0,2.0,2.0,DGDABGBCHCHF,False +404,5.0,16.0,6.0,12.0,8.0,5.0,12.0,9.0,DGDHBCBCHGEEHEFGFBAGABADDCDBBBBBGAGEEDCDGHGHFHBHGGCEEDBDBDBCBDBGFAEBHFHGD,True +405,21.0,16.0,12.0,16.0,13.0,10.0,25.0,18.0,GFEFBFGGBGBGBHFHEBEBGBGFGFCEAGCDHAABHBEGCGHDHAHDCEGDGDBFGCAAAAEAGADFDGDAACACECEBFDHBAEACHGHAHDEDEFHHHBGEGACDBAGGBCBHHCDGAGDGHGHADAD,False +406,4.0,4.0,3.0,5.0,1.0,0.0,4.0,3.0,GBDDABCBCGDGDCHBHDHAGAEA,True +407,16.0,7.0,6.0,14.0,13.0,6.0,14.0,8.0,BFCAAAAAEFEBDFCFCADGDBDBDAGAHAEDEGHGHGFDBDGAEHEAEAGCEDHAEADGDAFADGGEGHGHDEBEHDGBGCCE,True +408,12.0,15.0,11.0,21.0,18.0,14.0,12.0,11.0,DBDBDBDBCBGGABCEFEFGGDBDAAAEHEFEBGBECCFCBGEEAEHCBFEFHFCEBFBHGADFDACABEBEAECDCGFDDDDDDHGEGFDHDHDHFCDDEDGAAFAFHHGHEE,False +409,20.0,21.0,28.0,22.0,20.0,26.0,20.0,22.0,FCFDFHADGDHDHBBCCHHDHDHDGAABAGCGCDCDFFFAEAFBHHGHCHEFEGBDCDAAHABBCFHFEEGEFFFCHCDBDEDEFEDAFAFABEHCCCEBHBDGDECCAAACDGFFEDHDFBHBAGAEAEFECGGGCHCDAHBGBDBCBEHGFCFCFCFCEGEGHFCBGFGCGCEABBB,False +410,3.0,1.0,3.0,3.0,0.0,0.0,1.0,2.0,DGACBHDHDCACA,True +411,10.0,24.0,18.0,15.0,16.0,10.0,24.0,18.0,HHFBFECHGHAHFGGDCBCBCEGHGBBAAGCCHCBDBGBDHHHBFBDBGGCGHGABABACEHEHCDGDECBAAEFGGDGEADDDHDHBEBEGEFEGEGCGDGDEDBCCCHCEBEDCGFGHGEGFBFBACHBBBBF,False +412,7.0,7.0,14.0,10.0,10.0,6.0,9.0,5.0,GEDFDFBAGCDABADDGAHEDEDFDCDCDFHCBCBCGCHBGCFCAEEEEEGEGCCCHHGCBEBCAGAF,False +413,1.0,1.0,2.0,0.0,2.0,2.0,3.0,2.0,FGCGCHEHEABGF,True +414,3.0,7.0,4.0,3.0,7.0,6.0,6.0,8.0,HCHGEEBABABFBEGFGAGBDFDEHEFCFBHHHFHCHCBEEGGD,False +415,17.0,22.0,23.0,22.0,24.0,17.0,20.0,16.0,BCBGBADDEHEBECCCCDGAGEGEAACEHEHGFABAEHECECFCGCECDBACAHADECGCBBFGFEHEFGDGEGCGFGDHDCBCAFGDGDAEFHFCFBEEHEBDDFHHHBAFAHDEDGDBDEDECFCFHFAGCFFAEGDGDADCBBBBCGHHABBBBBDED,False +416,23.0,23.0,29.0,23.0,28.0,15.0,36.0,18.0,HDFEEHAHFECBCGDFDFBAGABBGGADFDGEGECECGDHCECECEDEDACACGEGCGFBCBCACEEDEGGABHEDCHBGGGHGCGCBDBCCCEHEBGBCDDGGHGEFEGBBBDBAFAFAGBFFHHADEGEDBCCCACGCDCGEAHAEADGGGDGDBFBFCGCGBGBGACAHAHGEFDADEHEHAFGHBHDEAEA,False +417,6.0,3.0,6.0,6.0,13.0,9.0,7.0,12.0,HGCCECEAEHGHGCFAFHDDBDEGBGHHEEDAFGFHEHAAADBCHCGFEEEHEHEFEFDFHF,False +418,7.0,7.0,9.0,13.0,10.0,16.0,6.0,11.0,HEFFFEDECCHHBHFDFACACEDHDBDBDBDFCFDEDEBHGEFFAFADAFHGBGCGCFDEAHDFDHGHFHCGEFEFABC,False +419,6.0,2.0,4.0,3.0,3.0,0.0,2.0,0.0,EEBDBAAAACACEGGCCDAD,True +420,20.0,21.0,13.0,17.0,21.0,27.0,25.0,13.0,HAGAGAECCFDBEADDGAGFFDCBFFCABGBEBAGCGBFBGEGEFDCDEBFBEDCAHBHBDFDFBADGFFEGEGEFEFEFHFBBABAHHDGDGBGAGFGFGEEDEDAFAGDHEACACFFGFGFGEDECBFBFHHHGEAFAEAHFBEBGBCHCHGADC,False +421,9.0,14.0,14.0,8.0,6.0,14.0,12.0,12.0,FHFDFDBBBGBEBCBFDGDHFGABCGABBGEAFAHACACHDDFHCBBFHFHFGCHCHGBBHHGCGCACACHCEFEFADDFEFEGGCGCB,False +422,2.0,4.0,4.0,2.0,2.0,3.0,4.0,6.0,HFCFCECBGGGDGBEHFBAHAHBHDHC,False +423,19.0,10.0,8.0,8.0,6.0,9.0,8.0,8.0,DEABABCFEFDAAABFHFAFAFADACCGBABAGHBABABAGHEHCGDGDCDCGEHEGDAABAEHBAGACDFFCFHH,False +424,22.0,16.0,21.0,30.0,13.0,19.0,17.0,12.0,BCBEBDAEAEAHAHGHCBCAAEADGFGDGDCACFCDEGCDHBCADDDDDEABADADADAEGBGBHCGFAFDCDBDFACDBDBCFEHEHAHGFGFGFGECHFHCCGDGACDFDECFDADEBHFFDFDFBFBEHAGCGDFCBGDACBCFDAD,False +425,12.0,15.0,7.0,11.0,10.0,19.0,9.0,9.0,CADACAFHFDDCDBFBDBEBEDEHFABACFFHHGFDFDGDGHAHACCBEFDFGEGEADFFCEGBABAEHHBHBGBEBABGBEFFFFABGFFF,False +426,10.0,14.0,11.0,11.0,11.0,17.0,18.0,9.0,BFBAAEFEHCHGAFEBCFCGCGBGFHFCGGAFAFBFCFHBBFEFEFEBGCECBGBGCDFDBDBDGAGEFEGHGHAADEGCGHDBAEGDDDDCDFGFGABHH,False +427,37.0,20.0,35.0,16.0,24.0,26.0,23.0,17.0,AGAEEHGHGCCCGBGCHCHCHFGGAAAEAEAFHCHCGCACADEEECBABEFEHDFBFEEBBBCEFAFADACAFFCFDHDGBFFACDGDFDBBBCGCBAAAEAECGCDHFBDBCAAGACACAFAGGBEHECECEABFEGDFDHHAAAACHCHGHCHABEGCGFACCECFFBFBABAGFFDAECEDEFFACGCGAGCDFD,False +428,16.0,17.0,31.0,28.0,15.0,17.0,26.0,26.0,FGFCCACBEDEDBCGCGFDCAAECEAAFFGGGGHCHCAGDGDBHBHFHFHFHDHAGGDDADHDHBACGCGEDHBCDFDGDHDCCCBBBBGCCCCFBDDDBCCCHCFEHHGFBFCCAAGGDADGDHEHAGCGCBDBFBFEGAGEGHCFDHHHHEHEBEHDFDGDHAAECCCEDEDGH,False +429,8.0,4.0,6.0,7.0,12.0,5.0,7.0,6.0,AAHAGBFHFCEAEBECGFGFGEEECBCDCAEHEAEDEDHGHBCFDGEGDHDEDAA,False +430,5.0,7.0,8.0,4.0,4.0,3.0,11.0,4.0,HGDCHCBCBFGAGBGBEDHAEAEGFGCGEGAFCGCGDHDBBBCCGA,True +431,8.0,19.0,9.0,16.0,16.0,15.0,11.0,12.0,FABCEHHCGDGDFDFHFAEDGDFDFBBBBFEDEAGBEEEFEGEBEFDDGBBAAAFHFHEEDCDCGEDBDAEHEHBHBHBFGCDCHEDBFBGHGFBFBCBCGCBAHD,False +432,25.0,23.0,17.0,34.0,27.0,19.0,18.0,34.0,GBHHHFEGGFGFGHBABDBDBHGGEBBDEDHHHHAHFHEHFFFGBDDEAAAAADCDHACAFDBDCGCGDDDHAGBDHGHCHABAFEFEFEFDDBDBABGFAFEEDEDEAEBFDFDHAHABEBEDDDFHCEFEAAAECCBABHDADHCBFGDHEHAGBDHHEHEDEAECEDGCEEHDDGHCHCHEDDHBHCHCACBCG,False +433,11.0,10.0,8.0,8.0,5.0,5.0,7.0,5.0,GEEEBADHCHEBEACABDBDAHABABABCDCGCDABFDCACABGGAGHCHFFDDGFGFB,False +434,8.0,2.0,9.0,3.0,9.0,11.0,9.0,7.0,CECFFFHGHBHCFCFBFHDACEEFCGEDEDAAAGCGCEFFAAGGGHFHFHEGEGECAA,False +435,15.0,9.0,12.0,17.0,12.0,13.0,11.0,8.0,FEFHFAFEDEDBCGGFBHACGCFCHADADAFAEAEADHDBDFHEDEDBBGBDADAGAGEGECCHEAACBCDCEGFGFDADGHHFDFCCCBDGEFADB,False +436,9.0,4.0,4.0,2.0,2.0,7.0,7.0,7.0,HEFBABCEFAFABGGAAACFCFGHBHACGFGAGAGHHDHDHF,True +437,13.0,14.0,15.0,27.0,27.0,6.0,29.0,26.0,DDDEHABAHEHAHDCBGDHFCEGBBHBHADDEAGGEGDGDGCCDCDBDBHBHBAAHGGGGACECEGGGECCDGDGEGADADGFHEEDEGACAGHDDDFDFBEHCHGHFHEEEHEHEHEHEGEFDGDGHBCCEDHBCGDHEEBAGHGEGEGEDHBHCD,True +438,22.0,9.0,13.0,21.0,26.0,17.0,18.0,21.0,GAGEHFHCEGEDAFAHAHEDBDFDABAHEDGDBCAEGDDDGGGGAGEHHHGCCFHHBHBHBHAGECAGDGDGDGEHDFAGCEEFEHEAEAEFFCECFFFBDADFDADADAFEEEEAFAEEBABAHEFDGHEHFCDCDCECHCHFEAH,False +439,24.0,19.0,22.0,19.0,24.0,22.0,19.0,24.0,DCDCAAAAABAFGFDFDHGCGCGBDACCCCEHFACHEDAAEABAHABAEFHFCFCFBBHFHEHEGCGDHFECBBBGBEHEAEAHDGDGHCHFBFEFEBEDFAACDHDFBHADCCEHEHDBFGFHDHDGEGADADEDEBECHFGGAGEFCCBCGFBBAGEHFHGHEHEFECBGA,False +440,23.0,14.0,11.0,16.0,9.0,11.0,13.0,16.0,DCDGBGBAAHECEFGFGAGHHEDGBCFDFGHGEEFADAEGFBAAAABFBFDAACCCEDHHHDDAAEBHCHABCHAHAHABEDGFGBGDDDDDDGAAHACACACABFFHBHBHB,False +441,5.0,9.0,7.0,7.0,5.0,6.0,6.0,2.0,CFDBDGCADBDBDGAAEAEBFBCBFGHBEGDHDECECBCGFGFBFAC,False +442,21.0,17.0,17.0,31.0,26.0,21.0,12.0,20.0,AAAGDEAFCHCBEDDBDBDHCAAHBDBDADHFHFHFHFHFDFEADADHHCHDDCFBFACHDEEEDABADAFEFHCACFFFEFBBEHGDGEGFDDCDGEGECCCCCFCHDEEECGCFDEDGBBDBGGHBFAFEDADFDHEHDHAGDGDBAEEEBEDAHAEBEBEAE,False +443,22.0,20.0,27.0,22.0,26.0,31.0,22.0,17.0,EDEAHFDFEBGFEFHGAFAFEDEAHDFBEDACCCBCBAFADAHFCGHGHDCDCGGHBBGACADFEFEFBFBFBHBHAHAGGGEGAGACECECBAEFFDEECDFECECBCEHDFCABHBCGDHBFBFBFAEDCFFHFCFGFDEDEDGFGFGFBCHEGGCEDGCCHDGFGCCCACEDEAEABABADFDH,False +444,25.0,15.0,17.0,18.0,21.0,13.0,21.0,25.0,GCAFBBBBAFGHBACAFHCECHBEDEHHHEDAHABCGDEAAABDBHAHBEGGDGACDBGGGGHGHGCECEFHFCCGBEEEEEDFCGDGDADADCECBFFCAEAEADGDHAHAHEHDHAHEFEHDGFHFHBDDAHAGAGAGAGEFBHECFCACHDH,False +445,4.0,5.0,1.0,1.0,6.0,3.0,0.0,1.0,FEBBABEBEAFHFEAEAEBDC,True +446,3.0,5.0,3.0,4.0,0.0,2.0,5.0,1.0,DBDAGBGCGCGCBBBAGFDHDFA,True +447,27.0,17.0,19.0,29.0,21.0,26.0,19.0,16.0,AAEEEEFDFHEADAGFGFGAGHFABBBBDADAHFDGCHFDFAFGCCBFFHDHDADEBHGCAHAFCCGCHEEADCBFFDFAFACAEECDCDBHBDCCEDEAGABDBDGGGGHFHFHDEAFDCDAAABAGCGFDFEEEBGAGAHBGDGDFDFDHHACCDCEBEAECEFEFDFDBDB,False +448,12.0,3.0,7.0,7.0,6.0,6.0,10.0,15.0,GCACACAFHFHGHDHAHDDEDCFAHACAHGEFHBHBFGDEHEAAAGAGCDAEGEBHDGFGHHCHGH,False +449,27.0,20.0,31.0,20.0,16.0,31.0,25.0,16.0,CCFCACAHBDGCGCBCGCDCBBEBAGFFFCFCDCBHBEFDFDHGGDCFEDBDFDCDCFFDBAECHADBCHCHCAAAAFAFADDGFCECGCGDDEHGHFFEHGHGFGFGAEFBFEFDBHAFDGGCFAFHHHBHEAGAEAEABGHFAFACACBCACGBBAGACAFFGFGFDBCBCGEEEECFADGBGA,False +450,2.0,7.0,4.0,2.0,6.0,1.0,3.0,3.0,DGCGCBDBHCECHBEGEABFBHEAEBEB,True +451,8.0,7.0,6.0,1.0,2.0,4.0,4.0,3.0,FGFHEABCCCDBABAHCHEAGCGCBAAAABBBFGF,True +452,12.0,16.0,17.0,11.0,29.0,15.0,19.0,16.0,EGDGEGHCFCFDDBECFHFHGEBEBEBEBDBAHAHADCEEEEEEEBECCBBBGDCDCFGHHEACAGBGHFEGEAECFDEGFHCEDFDFDCBHEAEAEFBGCGBAHFHGGEEBFGFGEHAGAGAFCBHHHCCECEG,False +453,4.0,3.0,6.0,2.0,6.0,8.0,4.0,3.0,CCFCEEHCHBDEFAFAFHGDFEGEFBFBFCECGAGA,False +454,17.0,13.0,25.0,22.0,19.0,16.0,28.0,27.0,AGAHHCDEDGGGDHHFEEGEHHCGGHGABCDCDAAFCFCGAGCFFFHEEEHEBGBCFHDAEEBDCDCGCGCBHBFCFHDHGBGDHCHFHBHDHBEAFCCDEDAGCGCDCFFHGHGHGAGADACAEABFCECECEBEHAGAHHDGDGHGHGFDFDEBCHDDCDGBGEA,False +455,3.0,8.0,5.0,6.0,3.0,3.0,1.0,4.0,ADHHHDFFACBCBCHCBDDGDBDBEBEAEFCBB,True +456,17.0,25.0,25.0,21.0,21.0,26.0,24.0,21.0,GEGBFBFBFBGAHAFACDEDCCHFFGBGAACFCHGFCFGHDAEFEFGFGHEBEBDAFGFAFCCBABEHCGFEDEDGBGBFBEHEGGCDCDCBGHDCCCDFAGBHBDEDHCHCHEHCBCDDDDFBEEEEGGBFCFCHAHACGFBBHDHBABGBGDGDFAFAECECEFDFDBGCHBAAHHEH,False +457,12.0,10.0,8.0,8.0,4.0,11.0,8.0,8.0,DBDFDFCCCHBEGFBHEFACBDBGHGBFAFGHAHAHGDDDCCACGCEHGFGFBFBABABDHFAAAEAFA,False +458,20.0,11.0,18.0,22.0,26.0,28.0,20.0,28.0,BFGHCHEAEAFFFFGABCFGFECECECECHCHGHDHAHEEEFHAAFBCGHDHDHCABGHCFDGHGACFDDDBCGDDFGGGGEEABGFAFEHAFEHAFAEAEABAGFDFEEHEFECDADHDHBHEHDHCHFHDHFHGDDDDEDEFEFGDCHCECEFHFAGBFFEFCADGBGBHA,False +459,18.0,25.0,19.0,16.0,13.0,17.0,21.0,14.0,CACACDEDBCBHAAGHBHBCEDEDAGGHDFDEDCHFHECFBFACAHAGGGGGAGDFBABFFGFBHBHBGBHBACABHBGCGBGEFADCDCHAHDHDBACABBBGEGEFCFBGBEFDFABABFCEGECDCBCGDBEGFFCFDGE,False +460,21.0,19.0,19.0,30.0,29.0,19.0,23.0,32.0,FDEDECCDEEHFDFEFEFHAHDCGCGCFDDDCGAGAECDHBEBAHGCGEFEDHDHDGDBHBADCDCHHFECHBGBEHADBDHGHGHGHDHFBGAGHBFBAECGGFEFEFDGDCDAEGEBACHGGDDADFHAEABBGBABDFDFABEDAHBHAHAEDEAEHEHCFCHEHEHBHBHGGCACAHEEEEFDFCGDH,False +461,9.0,19.0,19.0,25.0,19.0,17.0,20.0,16.0,BEGCGDAEHEDBDCEHECACAEAEAFCEGHGHFHGHCEDDDHDEGGFEHEFDFGFDBDBDGDEDCFCFHECBDHACCBCBFGDGCHBHDDBGBGFCBCDDGDACFGGGGFGBEBEGHDBDFCFBFDFDBHHAHAEDFBCBEBEC,False +462,9.0,14.0,11.0,15.0,9.0,10.0,15.0,17.0,CHCHCGCBEBDHEHFBGDGDGDGDBDGEGCHHBDBDACFCHGFEAHFFDCGAGBFHEDEHHAHAEBHBHGAGBFBDBCFCBCBADAGEGHHEFDFDGDAH,False +463,15.0,16.0,16.0,16.0,13.0,12.0,15.0,14.0,EDEGEDHBHDHDACHCBCAHADGDGAEEHFGFGFAEGEDECGGAFAFDBCHCGCEBABABABDEACHCBABAFGEACFDBBCBEGEGCDCDADBDFHHHHHBDCDGBFFGFHCBCFG,False +464,20.0,13.0,10.0,7.0,14.0,12.0,14.0,15.0,HHHBDFFCHCGCGAGDFDGEBFBABAFAFHGHBAGEGEHBACFCEDBACCCABADAGBGAGEEAAFAFACGCFAHEHEDEBAGEHEHEGAGAEFHHHHABEBDBF,False +465,32.0,28.0,23.0,18.0,15.0,22.0,28.0,21.0,CAHHBFBGCACEGFGAAABABAGGCGCGEAAGCGEEDBDGDCDHDBBABAFABAEDBGCEDBDBAHABFHEDEDBFFGAGHHEGAGHEECDCFBHCGBDBDBFGFDFCFAAACACFGHGAGDCFGAGFFBHCHCEABHBFBFHFAFHFEFBABGBGBGHHHAHAGEFCCHBHCAGBCDCECADADAG,False +466,14.0,31.0,26.0,20.0,17.0,27.0,15.0,13.0,BBBBBCGFEFDFDFCCDCHHDAFADACCEAGGCGCACFFEGECEFECCACGEBAGDGHBABDBHBHFCBHFCFCAHDCDHBGFEEDEDFAFHHGBBFAFCCCFAFDFEBBABACHHBDBDBFBCCFFFFFFDBBBBBEBECEGEGDGDGEGCHEBCDFBBBDD,False +467,15.0,12.0,15.0,11.0,17.0,18.0,18.0,13.0,HAGECCBCFHEGGGGBGBDBGBAFACCFCFCBDFAAAAACEEEFECDFDCDCDHBGGGFGDABAGAFFEAEFHBEDEDEFBAHGCGCHFGFGFHHDHECEAEGFAFHHEHEBBGEHFDC,False +468,22.0,12.0,14.0,17.0,19.0,18.0,16.0,15.0,DADADADAHAGABAEHFGFGEGBHBGADHDGGACHEHCHGEFFBCGCAFGDGAEHEAAFCFGAHAHEDDFDCHFEFEDEBECABEFGBGAGCCECFCBBBBHAEBECCADEDHHHEDEDEDFFFFGDAAAFCF,False +469,18.0,26.0,29.0,20.0,29.0,19.0,16.0,15.0,CGCGCHCFCGHHCHCHCHCFAEAFFECEBFGDHDCECECHCFFDBDEDBGGEGAGEHBBCCACABEEEAEBEBACECGADBBHBDBEFEFEFCDDGCCBAHHFCBHBADAGFDBEFEFEAECBFFHABDBAEDECECEDBFBDBDBDACGEGEBADCDGBGDGACFEFBAEH,False +470,6.0,1.0,5.0,5.0,3.0,4.0,4.0,6.0,CBCAGGHDHDHDHFHFEECACADHCAFAFGEADG,False +471,8.0,12.0,3.0,4.0,7.0,8.0,8.0,2.0,GAAFBEGEFDAGEGEFEHGBCFFFFGBBBEBABABDBDBEBDHGCABACAGF,True +472,9.0,4.0,9.0,5.0,3.0,6.0,1.0,7.0,HACGCABHCEAFHBHDAAACFCBEDEDADAHFHFCFAFBCDCHC,True +473,2.0,1.0,5.0,2.0,7.0,3.0,2.0,10.0,CCHCDDGFHAEBEHHFACHHFHEHEHEHECEG,True +474,8.0,7.0,5.0,9.0,9.0,4.0,1.0,12.0,BCDHBCBADCDHHAHDHAHEDEDBHEEDHCHAFAHAHCEGDADEFEFEFABHBEB,True +475,11.0,5.0,2.0,1.0,3.0,2.0,5.0,4.0,AACDCFHAGAGAEBGBHBFEAGBGAAAHAHABE,True +476,25.0,30.0,25.0,21.0,26.0,22.0,25.0,24.0,HGHEDBDBCHEHEDEDEDEDCAHDCGCFDFGEGDGAGAGHGDGDCAAHABAFACBCBCEDEAEDEAGDFEBEBEHGHFHFCBBFGHGFEFBBBFHGBCFCEBABADHBCACGFHFACACDFABHEAEHHDGACHFBFBHBHBABGGDBABGFEFBHGHAHEBGBGCFBEBECGCACEFAGECACFDFEAECCBGHCDD,False +477,15.0,14.0,22.0,19.0,17.0,22.0,25.0,22.0,DFGGGFHHCHEHBGDEEBFBAAHGFGFGACCCGHFHBHCDEEFEFBFAFBFCGCEDEHEHEBFAFAFAFGCGCGDBCBFFCHCDDDEAEAGDEDECGDGABBHDHDFDFDGCGAHEHFHCHAACDDBHHACBGBGAGFFHCCGHHCCGDGDGCGEE,False +478,14.0,12.0,9.0,13.0,13.0,17.0,7.0,13.0,AFAFBFBDAAADFFBFBEHGFEFHAHFGDDFDHAHADABFBFHEHECCACGFBDBGAEHCDCHGHGEAECECEFECADFDBGBHBHEHDDFEFDBEAC,False +479,29.0,20.0,16.0,24.0,27.0,18.0,17.0,26.0,GEHHHAHEGBGCHCBCFGDGBFDHCCBCHFHAEFEGGDHDACEDDDCDFDFDHBAADHFHBEFEHCHCDFAFABAEGBHBABABAEHEAEAEDEAFHEDAGEBEFGCEDEFEDHBFFDFAHHDBDGDHEAEGCBDEDBAGAGAGAEAHACACAEAEBHAHGFGEBEADADBHBHFCC,False +480,11.0,14.0,7.0,9.0,18.0,15.0,6.0,9.0,FAFEGDGBBEFEDEFEFABAGEGEFFFBBCBEDABEGAAAFHFDEHHFBFDFAFCDCDEGHHCHBABCBEHEHEBEBEDEHABEFACDC,False +481,8.0,4.0,7.0,16.0,11.0,8.0,9.0,4.0,EEADADFDEAFBFGEGFGDGCHDDCDEBEGEGCFCHDAGCGDGAECFCEDDFDEABABADDDDEHFH,False +482,11.0,7.0,25.0,5.0,16.0,24.0,10.0,11.0,EAEAEACFCBCEFEGAGAGCCFFEFGBCFFHFCFAHACFCEEHCCFDFEEHBHFHAGFFEFEBDAGCGFAFEFEHECGCGCFCFHFHCCCBCDDBCCCCFDFHAECBHG,True +483,24.0,31.0,31.0,29.0,20.0,23.0,19.0,21.0,HAHEECBBBBGBECEFBFHHCHFHDBGBHEGEADAEAEBBFBCECFCACABHCHCEBFDFCFCFBFHHHEGCDCDCDHDCECGABADDDBAGAGAHEDEBBDGCBCFAFABAHCBCFHGHBDEDGBGEHCDCFCFCAHFBCDCDGDHABGFEBDBDBDGAFAGAFDDCEFABAFDDGAFEFDGCBABHCGDGDCDCAE,False +484,10.0,14.0,9.0,7.0,6.0,9.0,6.0,9.0,HCACBFBFCFCFHAHADACABDCHGHGCBFDHCBGBABFBDBFBEEHADADHBBEBADAGECEFHBGEGF,False +485,10.0,4.0,11.0,5.0,13.0,7.0,15.0,10.0,AEAEHCHCGCGCBEGEGFGBGAGFGEHAFGCHDECCAHADDFDFHFHEGEGACCBHDHAEGEGCGHBEEEGAFAC,False +486,10.0,4.0,4.0,3.0,10.0,7.0,9.0,8.0,HGHCFDHAFAECEFHFHEGECHDDACABAEEEGGAEAGAGAGAHFGFEHEFGBBB,True +487,5.0,6.0,9.0,7.0,10.0,8.0,5.0,12.0,FCFCFHFAFAFGEDCBEHHGGEHEHAGBHCHFEAEDEDBHADCBCDHDHDFBEBCCHCGEHE,False +488,11.0,11.0,11.0,8.0,15.0,8.0,13.0,12.0,CBABEBFHFGEGHCDCAGDGEABBCGGBBHEFBBABGBADEHCHCEAEAEGEFFFCGCEHDHDHECDCAFAGAGAGEHEGFDHCHEHED,False +489,22.0,25.0,26.0,26.0,18.0,25.0,28.0,23.0,BEBEBEBFFHDHDHCHDHCCGCFAGCHCHCDCGCABABAFCHEHBCBCDCGCEHAHAEGGABFDHEBECGCHCHFDADAHHEGFBHAHFDGDCCCHFFGGGGBFAFABGFEFAGGFGDBAHFEGEGEDBBEDDBHBDFDFGGCEFGFBFHGADADHCEGEGDGDFDBBCBCDGBADABAFCFAFADDDBCGAE,False +490,19.0,24.0,22.0,16.0,30.0,19.0,23.0,31.0,FGGAFEFECGHHEGEHEDEFEHAGFBFBFHAEAHAEAEACDEBBHCECACEGBBFBDBCHDHGCFEHHAHAHBEBECGGDGCHBHGFGBDFCGHGHDHBHBACACHBEAABDHEHDHFFBFHFHEBCDEDEDFDGEGAGADBCHFHABDBDCFAEAEBEBECGCGEHHCCBCHCEGEGHFCGEG,False +491,16.0,23.0,19.0,29.0,31.0,20.0,28.0,25.0,DHDBCECECAGFGBBEEEECEDEGHCDGGAFDFGFGCGCEHGHGEDFGCDFGFDDDCDEFEABDEDEBEBHBHBGGHBDBHAFABDGHCECGAEAEAGABHDHDHDHBBBGEHEFEDHBEEEGGCDEFGHGHAHAFCFGFEDCFEABHFHEBEBDHDHACBCFGAGFGHEHBGBCHFGDDADCDADFDECB,False +492,2.0,8.0,8.0,4.0,4.0,4.0,9.0,3.0,GEGFACBGAGECCHCHCBFDGHCCGCGBDBDBEBEFDFBGBG,True +493,21.0,13.0,20.0,26.0,11.0,13.0,10.0,15.0,AACGHHEEDBDBDCDCDBEBFBFEGDCEADDDFAFAEAHHHFAFADEDCHCBCAAGACDDDDDBCAGDCDBEHGHGFGABDHDHCCCCHADAEAEDHDAACAFAFBFEDGBHCCADHBGBDFCFCHCFG,False +494,4.0,3.0,5.0,3.0,3.0,7.0,4.0,3.0,AHFEBAHCHGFGFEFDADBFFCFCGCGCBEAD,False +495,0.0,4.0,1.0,1.0,4.0,0.0,2.0,1.0,BDEEBEGEGHBCB,True +496,6.0,16.0,13.0,12.0,12.0,13.0,12.0,10.0,DHFEEBAFCHCHCEFHABBCBCFGECECEGEBDCDCBBBBFAFEBEGGCGAGFHEDGBGEGCHEBDBHBHCGBHAGDFDFDFDFDHCADFDFGB,False +497,19.0,9.0,12.0,22.0,14.0,24.0,20.0,18.0,DEDAHEBAAGDBHHGABAGCHCDCACFCGCEEACBFAFAGEDDDHHHCHCGFGHBAGAFAHDDDDDGDFDFHFEEDEHFHEBFDFHBAGHGHFHFEDEDFDFDCGBFACAGAFHFEABGEGFGFGFECADAGGDGFFF,False +498,8.0,3.0,6.0,14.0,8.0,17.0,6.0,15.0,GFFDFEGGBEBHAEDGFAFEFDDDAFHCHCDCDGFHAHFHFGDHCEFHCHCFDHDHAFDFEFAFABAEHFHDHDEDH,True +499,0.0,6.0,1.0,2.0,2.0,3.0,3.0,4.0,EDECHDBGBGBHBHFGFBHBF,True +500,9.0,11.0,8.0,10.0,19.0,12.0,9.0,5.0,GCFDBACGFBFAAAAGBFAEGFGCGHEAGHDFFCEDEDEDEDECHBEGDDEAEFDFAFEBEHEHEDEBEBEBCBCBFFEGBCE,False +501,8.0,14.0,12.0,11.0,8.0,12.0,9.0,4.0,DBDBEBDBDFDAGCGFBCBCFFGCDCDEDBBBECECFBFECABDDAFAFAGEFBHAGAFCHCDCGHGHBFBEGEFCAG,False +502,5.0,5.0,5.0,5.0,9.0,6.0,4.0,8.0,FEFEBHHHAHABEBDDFDHDCAFFECEAHCBCEAEBHGHGCGFDEGE,False +503,12.0,12.0,13.0,25.0,16.0,10.0,18.0,21.0,GBGBDECCCFHHBACGDGDGDADCGCBBHDHDHDBDFDFDHEHGCEDEGEFAFHBEFFGCEHFFDDHDHGHGDAACAGBDHGHEDEDGAHCGDGDACEGAHAHDHEHEBEBCBFBEHEADDGDCAHE,False +504,10.0,15.0,9.0,13.0,14.0,7.0,8.0,9.0,CBEEFBBGBGBDBABADFBAAHEBEDEDGFCEBDBHAHBCBCBGGFDFCAGAFDGDHDHGEBEHFHECECEAHCDDEHEAEADCD,False +505,18.0,16.0,17.0,23.0,12.0,18.0,20.0,12.0,FGFABEFDHDHFHGDBDBGBGCACDDDHAHBHFFFBGCGEAEAGABHBGDGCECEDHFAGBDEAAHCEGHDEDEDFGHDDDDEFFAFGDGCFCFDFDACFCEAABGBABCBCFHGGBGEGAACCCCFCGBADADBD,False +506,22.0,16.0,25.0,22.0,25.0,11.0,27.0,18.0,AGCDCDHDBGCGAGDDCDGBGDCBCGFGHCECGHGAEFEDEAEGEFHGBCBCAAAAGGDGEHEAEDEDEBCBGFCFGDDEDECFDHDBEAEDEHGHCCCCABAFABCBAHCHGHCCDCEFAGEHAGAGHEBCHEGBHBHDHFEEEACACDEDEHGGGFBFBGDAAA,False +507,13.0,17.0,22.0,10.0,17.0,14.0,17.0,13.0,GGGCBBBEBHAEAGHDCGCDHFEAEABHCHGFGHGCCFFBCAAHEHEDCGCGCDADEHAHFDFAFCHCFCBDEEAEFHAHFCFABBDBDEGECEBGBGCGCDEEBEBFBEACBCGCGBGCFCF,False +508,17.0,21.0,24.0,12.0,17.0,20.0,19.0,17.0,ECHCHCHCGCFBGAGEBEBEBDCCFHFGCDFFHHBGBGDDDGFCFCGDGFAACACGFHDHGAAHAEBEGCCCFGFADADHBBBBABEBEBCGCHDHBGEHCACECEDDCFFAFEBACAEHEHBGBHEFAFBGHGFBCBEAEAGFFCF,False +509,4.0,0.0,5.0,5.0,1.0,0.0,3.0,4.0,GHDCDCDCDCAEHGCDHHAAAG,True +510,10.0,11.0,3.0,4.0,7.0,2.0,18.0,3.0,HAGGGGAFAGCGEGBGAEBGGEBEBDCEGDBDADEBEGAGAGBBBCGGBGAGHBHAFA,True +511,2.0,4.0,2.0,2.0,1.0,2.0,3.0,1.0,DEDFHGABBBBFAGCGC,False +512,2.0,4.0,2.0,1.0,1.0,1.0,0.0,1.0,HDBABCBCBFEA,True +513,4.0,5.0,8.0,7.0,6.0,8.0,11.0,4.0,GGHGHGDBCECECEGFHDABADEGGCGCECBFEGACFFFFBFCFHBAGGDDDD,False +514,20.0,26.0,19.0,15.0,24.0,22.0,24.0,21.0,FGFEFEFBHGHBEDHHHHEDCDEHEHCBFHGAFAFBFDCACAGGGGGGGHBBABFBFBCHGGBACGCGDFEEEEAEFFFFDECECFCBCBEAHCBADEDAGFDEDBBEBEHACAFAFABHEEDCFGHDAABEBEDGGHGHGDDFEFAHAHBGCGBGCCCABBHBAGCBHBE,False +515,22.0,23.0,26.0,33.0,16.0,30.0,25.0,23.0,GGGGCBEHCBCFEGGFADHDHCGDACCDBDGFCFHBHGAABFBAHAHDGDBDADACGCFDFGFDDHBGGGEBEBEFGFHBEFABEGCGCGHAHFHFHDBDBDCDCDCHFFFHFDFAGEGBABFEDBDCECBCDDHDBGECADEDEFFFFAFDFDECGHDFDFBCGFECHHAHAHGCBCDADAEAFCFCDHDABAHABC,False +516,17.0,13.0,13.0,12.0,15.0,20.0,10.0,20.0,FDFAGABHFHCEEAFCEGGBEBCBCBEBDHFACGHGCACACAHFHDBGFGDAEAEABFDEDHDFAFEBDHHHFHFHFHAHAHAEAFADCCFBBCEHFFFDGDGBEHHHHGCBEFEAEDFC,False +517,26.0,21.0,23.0,17.0,23.0,30.0,24.0,22.0,ABAEAEAEBGGGGGAECECEDFCEBAGHFHAEADCCGGGAGBEBEBEDCDFAFHFHGCCBHAFAFAFHFGBCDDFACGFGHDEEGEFEGBGFGADFCFCFCBAEABCDHHHCHFHFHBHAEFFFCFBECCCFFDFDBCHCADAFHBABDFDBBAHGGEAEHCGEGCDAGAHDGDFHFHFEBABEBH,False +518,7.0,13.0,9.0,12.0,7.0,6.0,7.0,5.0,CGCECBHDEBGBAFCDBDBDACEBDDGDGEGEFAFAFAHCFEHEDBCBDBDCDBBBDCHFBAGAGH,False +519,15.0,23.0,14.0,11.0,17.0,17.0,14.0,16.0,AFGEDCHBBBBBBGGECEFFBACACBCGCBHFAAABCCEEDDDHBBFBFBGEHEFDAEAFFFEHAGABAFHFBDBHHHBEBEACGCGCACDCHEEBEGGDGHGHGDDDCBGAEBEFEFAFHHHFHFB,False +520,18.0,12.0,17.0,12.0,18.0,12.0,16.0,36.0,EGEHCHDHDGDGCADAHAHFCEEBACEEEADAHHBCBEHEHEBAHCEEGCFEFAFABHBHGHDCGCGDHDHFHDHDHAHCHABCGCFBHHAHFHFHFCEHEAAHHBHGEAHHBFCCGBGFHAEAEGCHBHGDGDGAGFHHC,False +521,4.0,11.0,9.0,6.0,9.0,15.0,6.0,12.0,FFFCCHBHCFCBCBFDDGDGBFAGCFEFCHCGFBBBHCHDEDEAEBHBHGAEAFFBEGEHEHEHBHFFFFHD,False +522,17.0,10.0,12.0,14.0,22.0,13.0,17.0,18.0,EEEEDEABAGFEFEHGHBDAAABDBDAEHHAHGHGHDHAEABHHHHHBCGCFCFCDBAGACEEGCGAADGDHAFCFCEBEFDFEEACGHBEFEFEFEDCGFGHGEGDBAEGEDCHAHGDFDGC,False +523,0.0,4.0,3.0,2.0,1.0,0.0,4.0,2.0,DDEBCHCGBGCGBGBH,True +524,25.0,20.0,21.0,11.0,21.0,16.0,21.0,28.0,FGHGHEHEHBHFHFBFBDBEGDCHCGAEAFCDEAAACHEHEHBFFFFAAHCGGHGBGBHCHCDCGAGAGBHHHFDCDAEABBBCECBGGFACHCECEAFAGHFAEHGGEDEDEBHHACCCACBCHDGDGAAABAGFEBHAGBGCFEEDEAEAFBECHHAHBHB,False +525,5.0,5.0,3.0,6.0,5.0,16.0,3.0,8.0,DHFHFEFEADAGEGECBDFCBDDFHCHFAAAFEHHFBBBGDFFFFFFFHFH,True +526,1.0,0.0,1.0,1.0,2.0,0.0,4.0,6.0,HGHCHEHEGGHGDAH,True +527,14.0,26.0,15.0,11.0,16.0,18.0,25.0,17.0,BHFABADGFABCDGGECEBEFEDBDHGFCFDBDBCEFBFHAGBFEFGFHFHCHBHEHFHFHCHCEDBDBEGHGHGCBCBGDEEFCFBGBGBGBCBDBGAEAGBGAGECEAFGGGHGCCAFGGEAEDBHAGABAFAGHHCBBB,False +528,26.0,33.0,22.0,21.0,21.0,26.0,21.0,23.0,HDBFBDGDGHHEBFFCECFBABGGEBEGGAHEHABGBCCCABDFEFGFADACCGABDBFBADADBDAHAHBEGHFHBEGEBCBCBHAHABADCHBGCDEDEDHGGGGGCDBFFFFFAEECHCHCFEBEAADFBFBABDBGEEHEGEFCFCFEAEADCGFADHHFBDBAHAHACABABFBFCFHBHBHCDFGCD,False +529,19.0,28.0,16.0,26.0,16.0,17.0,19.0,17.0,ABADGCGBHDFFFGFGDGFBDGGFAFCGGFHHAAFFFEAAHAHCBCBABADDFFFABDBDBHGDACHCHGBBBBBGEDADAGCBEBHHEDBCBCBDEEGADABABADADCCBCBDFDFCBCHFEEEDEHHHGHBHDEECHGDGDBEEEDEDGDGCBBD,False +530,10.0,4.0,8.0,6.0,5.0,11.0,7.0,6.0,FFBFCDCGAGFEDCDBEGEGFCFCFCBAFDBHAHAHAGACAHAHEGDFCFADEGAFH,False +531,13.0,7.0,11.0,9.0,7.0,13.0,13.0,17.0,GCABEBFBAHHHGHGAAHCHBEBCDAFHFHBCDCDCDFGEGCHAHEHCHDFFFGFGCGAAAHGGGHFCECHHHGAAEADFBFDFDEDAGF,False +532,6.0,4.0,4.0,4.0,4.0,11.0,3.0,7.0,ABCDHFHFECEDADFGHAFCFCFBFBGADEHGBFHEHFHFAFA,False +533,14.0,30.0,24.0,27.0,22.0,23.0,21.0,29.0,CEBEDGCHDGAAABHEHGCGBFBEGDDDCDCHHDEGFHCEFBGBCCFBAEAGABEDFDCDCDHDHGFGHGCGDDFBBBBBDFDADCDGBFEFDBCFCFBDHDGFACAGFDFDEAECFBBHBHCACAHFDEHEHBDBGBHBFBEDCFEEHBHBCBCBHEFEFCHCHEAFHBHBHEHFGCAEGHGHGHGHED,False +534,7.0,14.0,11.0,10.0,12.0,6.0,11.0,7.0,ABADCBEGAGABDBHCECDBEHGCBCBCGCFCFHFHFBBCBGEGHGDGEGEDDDCDEDABAHCFEEAEFEBBGDEHBG,False +535,1.0,8.0,7.0,5.0,5.0,7.0,1.0,7.0,BHBGFHEDDFCBBBBHHHFEFHFCFCACBDBDEHEFECCCD,True +536,5.0,4.0,11.0,11.0,13.0,6.0,6.0,8.0,CDDDEBHHGHDFGCCACEDEDECEGEACACHEBFFEFEFGFGDGDHAEEEABCBHEDCDCHHDC,True +537,28.0,21.0,11.0,18.0,13.0,11.0,21.0,19.0,HGAGAGFDDHGEBDCGAAHGHEDBDFDEGAGHDECCAAAADDGBBCBHBHBHGCGCBBBFBFGABAGCHBGAFHFAACAGDFEFEGGBFHAADADFDADBBBDAEAFHGHEHEHAHAHAHAGEGDCDCHBABABECDGAEBE,False +538,3.0,5.0,4.0,4.0,5.0,2.0,1.0,6.0,HCHGHAFBEBEAEACDCHBEBFCEHBHDDD,False +539,6.0,6.0,7.0,4.0,9.0,4.0,6.0,1.0,CCAGDGDGEFBCACBCGDDBFEFCFEABABCEEEABAEGEGEH,False +540,4.0,1.0,2.0,4.0,0.0,6.0,5.0,0.0,FDDGAGFGCGAGAFFFBCDADF,True +541,9.0,14.0,13.0,6.0,8.0,6.0,10.0,5.0,CBCGEGEFEHAGEDBGEGAGHDCBCGAGAGHDFGAACBBDBDFFCFHFDACACBBEBECCCCHEACBBBBB,False +542,16.0,16.0,8.0,16.0,13.0,11.0,10.0,17.0,EAHAGFDCGCGDEHCHBAAADHDHEHEFBGBABFDAAADBDADADHDGEGCGHGBFAFEBBBBHFDFDEBEFAHEBDGFHCHCHGDFABABDHHHAEBEHEDEBCCF,False +543,21.0,26.0,17.0,27.0,29.0,23.0,26.0,18.0,GDEHHBFFAHDHDCBHBGEDBDGAGDHCEEEBFFACBBEDGFCFBEBECAFDDHBHDEFEFEFEGGCGBHFFCFEHBHEFBHBADAEAGAFBFGEGEGCGDEDEGCGCBDFDFDADABCFEBBBDBGGGFGCDCDCACFEDBGEGEGHABGEGEAAAACCHEBEDEHBABFGFHHEHADGDADADAD,False +544,22.0,22.0,21.0,19.0,23.0,23.0,21.0,20.0,CGDGDBCFDADCCGDBDHAHCHCEDFFGGGECECEAFAHCFDDEDAGCGCBDEDEAEHCHCEEECEFBFHDHGHGEGCHFEAEAEFFCFEDEABHHHGFBAGAGBDEGECECECHBHAHGBBFBGBDFDGAAFAFGBBCBGBFHEHCBDFFFHFBAAHBFBAAAFAGABDB,False +545,23.0,25.0,25.0,15.0,25.0,17.0,21.0,33.0,GAGAGEEHHHFHFHFHEHDCFHABBHBHBEBHFGBCCACACACGHBADHBECECEBABECCHCFEGHDCEBGGEBEBEFHHADCDCDFDHBHCAEEHEHFHGHGHFADCGFHCACACACBCEGDFHCABGDGEGFCDHGHAAAHBHBHBEBHBHAGABEEGEDEGFBFCGEDAGADDBBEAFCF,False +546,3.0,2.0,2.0,4.0,0.0,4.0,0.0,0.0,ADADAFCFDBBFCFD,True +547,13.0,21.0,3.0,11.0,13.0,5.0,12.0,11.0,GHBADHBHBGBEHDHEEFGHDHGFEDDDEGEAEDFAAGBBCBAGAGAEDEHBHBABABAGADBEBECEAEBBBBGBHBDFGCADBFBHG,False +548,25.0,24.0,22.0,17.0,28.0,18.0,39.0,21.0,CDCABDBHBGBGBGBCECBABGBGAHAHBFEEAEBGAGEHFACACDEGEGECHAEGEHFHFABEGHFHAHGHCDCEBEGDBFAFHGEGBGAGDBDBDBEFECHFHEBFGEGEGECAFABEBGBGHGFGEGCCCCHGFACGBHAHAECFGAEDHGHGDDDEAFADGDGDCAEGGACFBFAGEGACCEHDCDGGFG,False +549,3.0,2.0,4.0,4.0,5.0,8.0,5.0,2.0,HFEFGDGFBFDFEEEFEFGBGCCACDCAGAHFD,False +550,1.0,3.0,4.0,3.0,7.0,2.0,2.0,6.0,ECEBHBHGHBECEFDHAHECEDEDGCHF,True +551,16.0,22.0,21.0,26.0,28.0,20.0,19.0,21.0,EGEDEBEAEADDDCFCABGEFFHDBECHBBBBAHAFFCCDDDDDDHGHEFAAAAAGGBGFGBGCCHEHFBFHHDCDFFBFDGEGFCABBEBEBECDGFEECACDDBCFEDEHHDBDFHFHCHCEGGGEGEADCDCEGEFFHHGCCBCBDBEBEAEAEAGDFHCDGDHBHEHEH,False +552,4.0,5.0,6.0,11.0,3.0,11.0,11.0,5.0,GCCDFHFBDDEDECGCGDGHABDDGGGDHAHAFGFGEGFGFABDFHFCFDBDBFFC,True +553,5.0,13.0,12.0,7.0,6.0,1.0,8.0,8.0,BGDACECGDGCCCBCHCGCDBHHGBEAEAEFBCBEBDGCGDGCBABABEDCHHHHHBBDB,True +554,21.0,23.0,19.0,23.0,24.0,21.0,32.0,21.0,FAGAHAHFHGHBEEFGADABCBGBGFAHEDEFGFBHCECEHEHDGDEAAHGGGEGFFDFBCHGAGHCDGGGABDGDADHFEBHBHGGCACBCBCBGBCFADADGDEDACBGHEFDFHFHFBDDDDBHBGGGCDEFEGEGECHCBCBEBEBEFFAGBBFACECECDAEFECGAGEFDGGAADHDH,False +555,11.0,14.0,17.0,9.0,22.0,14.0,9.0,22.0,CGEEDCDADADBDBFFFHCAAEHHHEHEHAHEFFCFBGHHHFHCHDHEBGFGFBEECFCEEECGCGHEEEEADHBHAABCCACFCEDHCHCHBHBDBECGCEFFGFABBEBEGHAHBE,False +556,4.0,3.0,4.0,4.0,4.0,1.0,0.0,1.0,BABHECAAFBDCDEDEDECAC,True +557,11.0,15.0,15.0,16.0,14.0,18.0,14.0,14.0,BCBCBGDGCGEAHHEHGAFFCFHFCGAGACEBEBEBAFGCCDGBCEFDFDAEADDFDCEBFBFBEHDHEHEGEGBGHFHDDDDCCBGBCBHAHDEFFFGGCHBEAAAHFFDFDFDHC,False +558,5.0,2.0,3.0,3.0,1.0,2.0,3.0,2.0,DGDGACBFHFHAEACABACDG,False +559,29.0,26.0,17.0,17.0,20.0,26.0,24.0,23.0,DADCDFFHFAFACAFBDBACAGABFGFBHCHCFFEFEFGHGCBCAEGGGDBDBABFHFAEADDDEDEHAAGGDBHGFFFFCGAHBBGBGECEGEGEGEBEDCFFDFCCEAAFDHAEBFBFAHAGFHCCGBGBGBGAGABEDADHEBEHHAEFHAHABCBCHAEAFAEBHGHBBBAGDHHHHC,False +560,7.0,9.0,14.0,11.0,8.0,12.0,13.0,5.0,FCDCEFEFGHDAABACGCGCGDEBAHHBCCFCFGEGDBDBDBAFECDFDFEGGCAFABCFGFGEGHCDEDGDGFCBCBH,False +561,16.0,32.0,21.0,19.0,21.0,20.0,22.0,22.0,AFBGBGHGEDFAACDCDCEFEBCFCGHGHFDABABAHCCEAHBEDEDBDCCHGHEBEBEBCDEFGDGFBFEDHDHDBBBFFEGBGHEDGDFBGBACDGEBEBHBHCCGHGHGDGDGHGHBCAFHGHGFABAFAHAFCBCBFAHDHBBCBGFEBABCBCFCFEEBCFEDEAHBE,False +562,18.0,21.0,6.0,6.0,14.0,3.0,15.0,20.0,DGAAHCHBAFHBHBGCAEAEAHAEAHHHBCBGGEBDFAHAEAEBGAGAHDEGHAHBEAEGHGHBABHBHEDCGHGBEDGBGEGBGBABDBAEEHFHBCBCBHB,True +563,19.0,18.0,15.0,19.0,14.0,16.0,17.0,24.0,FAFAFABBHDCDCDFDCAABFCEDBBECDCDFFAGADBCHGGFHDHGHEECEGDADABEHHHHCHDHDFAHGFGFBDBCBFHAGABDBGBFDGGFCFCBHBHFHEHEHEGAGAHAGABAGABEECDCHHEBEDEHAGCGHDH,False +564,3.0,3.0,2.0,1.0,0.0,0.0,0.0,2.0,BABCBDAHCHA,True +565,8.0,12.0,12.0,9.0,13.0,13.0,12.0,17.0,BFBFEEHBFAFGGGCHDHDHGCDCGEHAHEEBBAEFGCGCHCFCFDBBBHCEBEHEHFGAGFFHFHABDGDFDFBHAHDHEAABCEGEGEDCHCHC,False +566,24.0,19.0,7.0,22.0,15.0,14.0,18.0,21.0,AEADAHECBGBFHGHDHAGDGHGBGBHFHBDDDHGHDHDADHDHAHDEDADGFEFGFBDBDFAAAAABEFDHHHEGBGAAEDEGEGAFAFHHBEEHCGBEADAEFFBFDFDBDBGBHAGBCBEFDHGCACBCBAAACAGE,False +567,18.0,34.0,25.0,23.0,26.0,29.0,16.0,24.0,CHFDFHBCBDBFBHEEAEABABCGAFDFDADADADBBBCBDBFCEEEFFAFDBDBGHDHBBBFFFDABFHGCABABABAHHHHDFBFEFHBCDCFCFBFEEGECFHEGEGBBDDHDEDHFHDHDFBAECCBHBEBHBCCCBDBEGHGCFCACEFAGEGEGCCFBFEHEHCGFECGFDAGFGHCCCEEEBEHAHDG,False +568,10.0,3.0,8.0,11.0,10.0,4.0,2.0,8.0,EGEDEHEHCDCEAEAEAFFEHCDDDCACHBHBDDDHAAACAEBFAGAHDCCFEDHD,True +569,16.0,11.0,9.0,12.0,15.0,17.0,17.0,12.0,EAEDEACHEAGBHHFFAGGDADADHBHAFFGDEDEHFBFCGBGFFDGHAEAFBCBEAECDADCGCGFGEGEGAGDEDBFFAFAFCBHAEAEGEGFGFDCHCGFBHBHBH,False +570,5.0,3.0,10.0,3.0,5.0,7.0,4.0,6.0,DADCHHGACACECHCFCFHDEGABAFFFFECECFGGHBCBCEH,False +571,19.0,19.0,10.0,25.0,20.0,11.0,12.0,21.0,EGEGEDDDADCBFBFCHCHGAGDHDHDADGHEDDDDHBHBHCADEEEDDHDBCEAABABFEEAEGHGHFEADDDCABHBHBHFHFEEEEFDCEEGCBCHGAEAGABFBHAHEHAFABHBFDDDBDBHAAFBBAGGCD,False +572,9.0,14.0,14.0,11.0,15.0,15.0,19.0,10.0,EFEAEGGGDGDADFHFGFBFBFGDGBBEBEADHGCBCBCGCECGFDCBCBFDFGEDBDHCAFEFEBGCHAFGFGEEHBGCGCEEEBHCHBADCCGGHAHADAGFHFE,False +573,4.0,10.0,13.0,15.0,11.0,8.0,6.0,4.0,AFCCGEEDEBEBAHAHADFBCBCBEFDGHBEGEFFBFDDBCECDCDCECEDDDDDGDCDCEBBGDHFCCGF,True +574,15.0,27.0,18.0,27.0,33.0,20.0,18.0,26.0,FACGCDEDBABABADHDBEFECGDFHHEBCBCGHHAEBHBHGDADGDGDEEEDEBCBDBEAFHFEDGDGDBCHEAADEDEAEDHCHAFDEDHDACHBHBHEHECFBABHDEEEFEGBGDDHGFBFBFCFCEBEBFFCECEGEFEDGDCBGEGHFCECEBGBHBHDHCEFFFBGBHHHEFAAHDG,False +575,16.0,17.0,13.0,14.0,16.0,19.0,22.0,14.0,HBCFCFDFEGAGAHHGEGBGDGFHEHAFBDBDCHCHGFDEDEFHFBEBHBHBEBHBDFDEDEHEGEFFACACGFHADGFADGBAEADAFBCHEFFBEBGBGBACGGFGFAABGGDGFCCACAEAECDGGGC,False +576,21.0,18.0,24.0,12.0,15.0,14.0,8.0,14.0,CDCDFBACHGHECECEDECECHHAHBGFAAHAGFEBCHAGBBBABCBADCFEGABABCGCFAFEBHAHDHECACHHFCBBBEBECFCFAFAHAFCGDFDFDBEBDCACACADBDEHEFEDGCACAC,False +577,11.0,6.0,10.0,4.0,4.0,6.0,15.0,11.0,HHGHAHGDGCEBABABGCHCGCECHCACHDFBABFHFCAHAHFFBFGGGGGGGACAGECDGAADEHG,True +578,13.0,11.0,13.0,13.0,10.0,10.0,11.0,13.0,HDHDFAHCHGEAAAACGBEEHHDEEEDADCDCACACDGDBDBCFEAGHCFCABFBFGCEFBHHHHGBGCGCGEEHAHFBFDDBDBCGDGAFAFB,False +579,16.0,20.0,17.0,10.0,16.0,13.0,17.0,18.0,HBHCDAHECCCCBHGEFCBCGFFAFACBDGDCHBHBCBEBEDGDFEHGHBHECCCEFAGAEHDGDGHBFAFAGAGBGBGBEECCAFAFDBBHFECBGHCHBHDHBHBAEEEAEHEAGAGFGFGDABA,False +580,19.0,23.0,27.0,23.0,24.0,28.0,24.0,26.0,FGFGCHDADGDHFFDCDABFFFFBCEAECEHADCDFDFABAHABDEDBAHCCCHBAAFAEGEGFGHDHGHBHGHDCFCFCADEFEHBAEEFGCDCGGGGGEHFGCGCFFHFHGHBCBDBDCCCGEBEHFBFCFEECFGHGHFHCAEBEBEGHGHFEFDCHCBCBGBDBEAAABCCEAFBHBHDHEEGABDDDED,False +581,14.0,16.0,19.0,20.0,20.0,20.0,13.0,20.0,ACAFBEAHDHEHBHCABBCHFHCEEGCHHFCDCBBEBHFABGDHFHFHBHBHBGDDDCFFHFBFGFECDCEAGAGACCCGCDCDEDEDADADFFFAFAGHCDAGHFEEGHCEEEHECECEGEFDFEEGDDDGDBBFBFBADH,False +582,13.0,15.0,13.0,20.0,21.0,19.0,19.0,16.0,EGGAGAHBFFEFEHECDCFCBGHFFGAGAGEGCGAGBFCFDDDEBEHEHCFBDDDDDDADAFAHHCFDEDBFFFFHAGCBDAFBHBEDGFGCBCBGEGEDCDCDCFHEHGHBDGEHABEGAGHFEDAHEEEEEBHB,False +583,6.0,13.0,10.0,9.0,17.0,8.0,10.0,9.0,FHFGBBBBABCCDHBEDHGFDEHCGCBEBEHCFCFBFBDBACFHGHGEEECECEDEDEHEDGCAEADFDGEAEGGGEBABEH,False +584,18.0,27.0,27.0,16.0,19.0,28.0,14.0,16.0,FHFCFAFHHBEBFBDCHBGEDBAFFCBHBCFGFGCGCEEEDEDBABGEFBGBAFAFHEGCGCDCDBHHCHAHAHGCECAHFHFDEGHBBCACABABFBFBFAFCDCDBABEBECFFGBECCCHCFAFDDDDFDBECEAEDBFCDCEFGFABABCCGEHCABGFEF,False +585,26.0,16.0,22.0,22.0,20.0,21.0,22.0,26.0,FHDHDHFCEBBDBAAAAGFGCBEDHDHGHAEAECDCBEBHCHAHGGFDAEFCFHHHEECCCDCDCDHAHABBECACADAHCDCDFBBEDAAGAFFHCEEEAFAFGFCECEFACAEAFFHEGFHCAGECFFGBGFGDBDBABAGGGGGHHHAHDDDHHHAHDGEGFGBGBFCEDGD,False +586,8.0,5.0,12.0,4.0,4.0,13.0,13.0,7.0,DFDCCCCCCFEBEBDFFAFGCGCBFDFBAAFHGHGCGAAHGFAFGFGCGAGBCHFHCGGHFHEAEG,True +587,4.0,3.0,2.0,3.0,2.0,5.0,3.0,1.0,BGGGDBDHDFCAEAFCFBFEFAA,False +588,7.0,14.0,10.0,16.0,16.0,9.0,9.0,13.0,BCDFHCGFGAEFFFDDBBHBFBHHGAEDDFDEHEGEGEHADFEEHEGEDEDEDEHHBHBDBHBDCDCDBBFBABACACEHECGHEBDGDCCCAG,False +589,41.0,28.0,27.0,20.0,22.0,14.0,25.0,23.0,EDEHHHEACAEAEGECBBHBHBEFAFEBAFHHGHAHACAGBDBEGCDEHAHADACACGEDCCCFBBBBBFAADACAGECDFHGDDBDCDCECDABAFCBEGEDFCGBGDHACABGHECBGGCDCGEFEAGCGDAAABABABDHGEAHBGAEHGBGBFCFCFEFBHGHBAAAAHABABADAGACACGCACHDHDHAFAGEG,False +590,25.0,17.0,16.0,9.0,20.0,24.0,14.0,17.0,HDFDEGEFBBECCBDBABFFAFDFCECBAGAEABGFHCACAFAFAFHEHEHECFCHEHEHECGBDBAFEBCFAFCFAGGCFCABHGABFFEGAHAGAGCHHEHFDFBEBCBEFAFAHAEFEAAHAHBHBGDGDGCEADAGEF,False +591,17.0,13.0,25.0,18.0,20.0,19.0,18.0,19.0,ADCFCHDBAEHEHEFEACAFAFDFEFECEGADHDHEBCCCCEHHGBDBDGCCFBGDDCGABAEAEDEAFAFCGCFHFEGAGDGFHCGCEHEAGCHCBDEDCFEDHCBEBFBAGEGAHCHCBCBAHACDBDCDCHFHEGFGFGDGHGFFH,False +592,4.0,14.0,3.0,5.0,17.0,15.0,9.0,5.0,HGFEEHBHFFEFHFEGBABFBGDFBBEFEDGDEDECEBEFEAEBBBBEBFAHAGFDFEFEBGCGFGBGFECE,True +593,13.0,8.0,10.0,11.0,8.0,10.0,5.0,8.0,EAEADADGFGCDDFBFHHGADABAFHHBAEABHHGBCFCFDFAFDHDCDCBFBCCCBCEEEAEAEFDAHACDG,False +594,16.0,13.0,15.0,7.0,3.0,9.0,20.0,22.0,BGBGCGHHHEHGAAFGCGBDFAFBHCHBDBCCCFDAHHBGBAAABHHHGHGBABABCCCCCDGHGHCHAHGEGDBFGFGCGAHAGFCHGGGAHAHCHFEDHDAAF,True +595,12.0,10.0,9.0,7.0,8.0,10.0,12.0,10.0,AEFDFGFGABHBHBACAHFFEECEFDFGBCAABBCDCGEBEBHHHHFBAEADGDGHGDGDCACGCACAEFHAHGGGBF,False +596,12.0,14.0,7.0,5.0,7.0,8.0,16.0,11.0,DBGBABFCGCGEGBGCHCABEEHGGGHGHFBEBABFBFBGGGGFDFCGABABAFAHHHHBEAAADDHCFEHAHBGACDGE,False +597,12.0,31.0,25.0,23.0,29.0,22.0,19.0,20.0,GBCAEDEGEDHCHGFBEGCCDCGAFBFAFEGBBDBDBDGGCEHEHFHDCDCDEDFHHBGBGCHABGCGCFHFDEBCDHDAABFBGBHDCDCEHEBFBFEFBFHEHEGEBBDBEBABCDGDBHBDFDFDACCEFBCBFHFGCEAEDFCCDCFGGEEEAEAFAFBHBEBCBCHEHCHGEEEBE,False +598,3.0,2.0,2.0,2.0,0.0,4.0,2.0,0.0,DADAGFCFCBGAFBF,True +599,18.0,18.0,17.0,19.0,19.0,25.0,24.0,26.0,EFEFADADEGEGBBHHABBHCCGAFDHDFEHHHHHHGAAADGHFHGGGGDEACHCHCFCGEGEFABEEGEHFCFDFEBGAHCHGFGFGFGFDDHEFCFEBDFEACAFHCHFBADGCGBADGDAFCHCHDDDFDFHCHBHEEEBEBGBABABABCBFFHFDGCGBGD,False +600,18.0,13.0,8.0,18.0,9.0,20.0,11.0,10.0,FAHEFAFAHDGGGGHCBEGABABFEFAAGAGAGAGAGBHBHCFFDHBHDEDEDABCFCEDEBEFADDBFFCFHFAAGDDDDDDFFFFHADFFFBBBCDADCCADHBE,False +601,28.0,16.0,18.0,22.0,25.0,31.0,31.0,28.0,DHDHCHCEGGGGGGHGHGABHGABAGDGEGBACHDHBGADFBHGAGFGDDADGEAEACHBBFFHFEGEFFAFAFGFEFAGADDFAFCFGHBFFEDBACABFHFCCCEEDFDCDAAHFHEHDDEDGHEFCAHFFBCGCGCACABAEAEHDHFHFHFCEDEDGAGAEEEEEFDAGGGHGHFHAGEBHBAEFCFBFCEHBHD,False +602,19.0,22.0,22.0,6.0,18.0,28.0,18.0,32.0,BEHEHCBFBFGAGFFFHEEGEFFGCHCHFABHHCCBFHFABBEBCACAEAFHFABHCHGBBAHEEEEAHAHBHECACAHEHEHCGBFFHFGAGCCBCBEFEGHDDGDHFHCDAHHHHDAFBFAFHFHGHGACCCACBHBGBGBCFGFHFHFGFGFAEBCGCBDEF,False +603,6.0,3.0,3.0,0.0,3.0,1.0,2.0,3.0,AAAAHHHEAEBFCEGAGCBCB,True +604,20.0,12.0,4.0,14.0,4.0,16.0,10.0,13.0,BHADGGGBAFFHAEDBAFGFCFHFHDHBHBGFFHADDEHFFBFGHAHAHABACADFFAAGADAGAGACADDEFEFDADAHBGBABDBDBDCHF,True +605,13.0,12.0,3.0,10.0,9.0,12.0,19.0,5.0,BFBFCDGDBDAGAFCHBBBDHGADCEAABAGFGFGEGEGDGFAFEGBGAGEFFGFGEDADBBGAGAGEFEBBHGHGEDDAFAH,True +606,25.0,22.0,15.0,23.0,20.0,14.0,29.0,17.0,ABABABGDEFEFEHBAAAFDDBDGDGAGEEBHFFCAHAGABACACHEGDGDFDHGGFFHFBEDECFGHCBAGDGCHBGBGCGFDADECEBEAEADAFEBEAEFCBCBCBHBABGBHAHAGAGDDEEEHBCEADGDGDHHFDGABDBDGGCGCADGGHHDHGGEGC,False +607,7.0,12.0,19.0,9.0,3.0,6.0,12.0,7.0,CHGGCADECECGBGCGCEHDAFACDBGGFABCBCBCBCBFBCGCBCBCBFHADACADHDCGGGDFCHGFCHDHDB,True +608,15.0,15.0,12.0,14.0,12.0,4.0,21.0,15.0,BGBEFEGDBCGCGHHEGCFAGEBFGHBCCEGAHACGBDBGBHAHGHGHEHEHACABADADAHACBGDAEHGHBDBDBEBAAAFCGCGDEDCDEDHDAGHGDGBGEGDC,False +609,11.0,19.0,6.0,5.0,9.0,14.0,11.0,10.0,BBBBGBFBFBABDHAHFBBAHEHFCAHGGDGDFCBCFCGAHBDBGBGFGHAHGBEEAFFFBFEFEACACEEGEAEDGFHAHBBBF,False +610,7.0,6.0,1.0,2.0,7.0,8.0,15.0,3.0,GGGGGDGFBAEAEBFHGHDFAGBEFEFGFGBHAGAGBCEAEGBGEGAFF,True +611,9.0,11.0,18.0,12.0,13.0,14.0,18.0,18.0,DABAEGBGEGEGEGFDHCGCHAHFHFCCCCHHGADFBGEHAHEHECFHEHEAGABDGEBCBFFFGDGBGACHHHDHCFCDCHHGDCHCBCDCGCBBDADGGGEDECBFFFFEF,False +612,1.0,6.0,5.0,8.0,3.0,4.0,3.0,4.0,BEBEBGBFBFDDCHBDFCHDGACHFHGDCDCDED,True +613,5.0,7.0,4.0,9.0,3.0,12.0,4.0,8.0,DEEHBFGFCHBHDHFAGDBDHDFCFEBHHHBFBABAGAGDFDCDFFFFCFDA,True +614,5.0,4.0,10.0,9.0,2.0,6.0,6.0,7.0,GCBCBCGGBFHHCFCHHDDDDCBGAEACACFDADCCAFHFHDHDEDGFG,False +615,20.0,20.0,21.0,19.0,32.0,21.0,14.0,26.0,FCCGGEHECEDEDBBECHCHCFGBEHECCCCCHCGCDCDEHAGCECEDDBEBABABEBEAAAAHAHEFAFHFEFBFBFAFGEEEAEHEBGHEHDBCBDAAEFFHCGFHHHGCEAGDBEHEFEGDFBFAHHDBCHFFBEGEGFHECEADADADBHFHAHDDFDFHEAEBDBDGH,False +616,4.0,1.0,4.0,5.0,3.0,3.0,4.0,3.0,AGAHCHBGDFDCHEDEDEFCFCDAGAG,False +617,14.0,17.0,16.0,17.0,18.0,16.0,11.0,15.0,EFEFHFABEBEGEAEBEAECBDHFEEGEGBGDHHHHHBHBHBHAFAHDBFHABDDFDHBGDECECEFEFGDABAFAFABDHFBFCGCGBEFCDCEADDDFACAHDCCGDDCBCGCFCABECGCD,False +618,29.0,30.0,26.0,14.0,18.0,25.0,13.0,17.0,HACCBHBFAFBFBFHFCBAAGAEBEFDDBDAAACACACEEDDAEFGBGFEFCABAGAGAGFGCHCAGFBBDFHAABFCFCFDHEHCFBFBHADBBBBHDDBCFABBEBFBADAEBCBHBHFHCBDDHCHGHCACAGAGDFCFEAEBECECECFCECECGHEBAFAEAGHBCF,False +619,31.0,22.0,24.0,19.0,30.0,25.0,19.0,29.0,CFHEHCGFFACEHBDEEGGACFCACAGAHAEAFDCGBACEFGAECCAGHBHBDBAEAGFBABAGACAHHHAHCHCDCDAGGGAHAEAEDGGCEHFHFHFDGBHBCEHEDEFEFEFEAADACHFBDBDBDBFBFAEHFHBHEHEGEDEDCCEBFBFCFCAHDBFEAEFEACAFADEBEHHDEGEAHBHCHDBGBCDHFGF,False +620,18.0,17.0,15.0,24.0,21.0,15.0,18.0,13.0,ECDGDBDGDGDEAEBEBCFGFGAGAGHCDEHEHBGGGFEAAFBBDFHCDCEEEEGAGAGEDFDHDHAFAFHEHDADADBDECACEDDBHFEGECADDCFHBCBCHCDDFDGBBBEAECEDEFABAHCHGDABFBFGFCBGA,False +621,0.0,2.0,1.0,1.0,4.0,1.0,0.0,1.0,FEEDEBEBHC,True +622,14.0,20.0,14.0,20.0,27.0,29.0,12.0,26.0,CDCACEHFHFHBHEFEDEBBFFFFBFECHHAHEHEDGDEEBFHFHAACEDECCCCEFEHAHBHDHFHFAFABEEEGEGEBDAHEEEEFHDDDGDEDABHBAFGFEHABFBABDBFFFHFCFHFBGCABBGBHFHFDDAHGFEFEDHCHDEBGGGBCDDDCGF,False +623,16.0,25.0,17.0,19.0,21.0,19.0,21.0,15.0,BFDFDFGBGDHBHEDCACFCEHEDEBCFDEDADBDACADDEGEGHAHBHFEBCCCAHEHEBEBAAAAGCFCFGFBEEEHBHEHGBDBDAGAEAGBDBGFEFGBCBCFGEGBGHDHGCCAADCDCBFBAGGFGEHDFBEBFBFDFCFHBGGGEB,False +624,23.0,27.0,21.0,27.0,12.0,19.0,33.0,26.0,DHAGAGFBFCCHHGGBCBFDFACGBGBGHCABACAHFHCDCDGFGFCFGFCAEGHGABABEDEDHFHFDFBGHGEGHAHBHCDAGAGAGBBAEAFGCACBFBDDHGHBHDGDGBGDAAAAEBBGBDBDCACFCHCBDBCCCBGFFHDHDHEGEDEHHDDDHBGBHDFFEBDDEEGGGGAGHCHDBAGD,False +625,17.0,22.0,27.0,7.0,24.0,19.0,26.0,18.0,GHECEGFGAGCBEEGBGHGBEBEAEFGFAFCFHGGGGEEECBFBDGGCGCEDGFBHBCBCBCAGABEGEAEABFFFBFBFHEGFGACAEFDBCBCAGAGAGFFCCBEHCCBCBDHCBEHCHCACEBFBCGDAHFCECEDACAEHHHHHDAFGHCHCEGEH,False +626,21.0,20.0,18.0,14.0,19.0,24.0,20.0,19.0,FGFGDBFGAAHHDABADDECCHFBGCEEHGHGHGAFHCHAHBCBFAFAFABBBABADDGEBBFCFCFCFCBCDCDHFAGGHGHGAGEHBFAFCHHEGEFBHDHAHAEDGAGAGEGCDEHECCCBBBAFFFEFDADBBEDEGCFBFCGAEEEEFEF,False +627,22.0,20.0,15.0,21.0,16.0,16.0,15.0,16.0,GBGEFDACFGFGHBHECCFAAAEEGBCHCBCFADHDHDBDBDFDADABAEDFBADACBCFCFEHGCEFEAEBHDHDFDEEBBHBGAGDGAEAEGGHAHDDDDFDGBBBAAAABDHGHFAFECCCECHBDBCBFEFGAGAHH,False +628,7.0,15.0,8.0,13.0,14.0,12.0,11.0,8.0,DEDBDHFHDCDCBBBCBDBFBFCGHGAGEFAFAEADBFBGBGHGDCFADBDFEFEDECEFHHCBEAGGGDEBECEABBGHGFDHEEFE,False +629,1.0,3.0,3.0,8.0,6.0,2.0,4.0,5.0,HEHDHDHDEFBGBGDDCDHBEDECGCEEFGAD,True +630,11.0,10.0,7.0,6.0,8.0,14.0,8.0,5.0,CAHAHABFCFCACFCAHAGDBCEGHFHEBDFAGAGABBBEBCFEFEFBFAFBDEDEGGDFDABFFEFGG,False +631,14.0,11.0,20.0,21.0,13.0,15.0,14.0,16.0,HCFAAHBFCFAFHFGDHFCFBBBEBEAEAEHEHGDDBHHHFHDCDEGECFHFDFDADACADHGEDADHDHDCDCGADDECEAGBBCECDGGCGCABAHFGCDCGFBHBDCDGAGCCCDCGEFEF,False +632,4.0,8.0,5.0,12.0,1.0,8.0,6.0,3.0,CAHAEDBCCFGDBDFFBFBHDDDDDADCGBGBCFAGDGFGFHDBDBF,True +633,3.0,4.0,7.0,2.0,2.0,6.0,5.0,5.0,CBCECACAFEFDAHBCGFGFBHCHDHCHGGFBFG,True +634,15.0,14.0,8.0,23.0,21.0,16.0,17.0,8.0,GDDDADADACBFGFGFAFACADAEEBEBFCGBFHFHGEDDDFCGABCBDHDHEEFHAHGEFDFEFBFAGAFEGDGDGBGDEDEBHBDCEEEEGEBCDDEAECDDDEGGGAFAEBFBGHEDAB,False +635,16.0,23.0,27.0,12.0,33.0,22.0,20.0,34.0,HEHACECAHFBGBEBHHHHFFCECEHEAEGDGDHAHBFFFFFFFGABCEFEBECECHABGCGFHEEEEEEGBCAHEHCHDFBGBCBCBHHGFBHDHCHEHEHCFCGCGEFHHHCDGDEDECBCAFEFAGHDCABHDAEACCHGHFBBHDEAGBGAFDDGCACEFEFEHEHEBEGCCEGBGBCAHBHB,False +636,18.0,21.0,19.0,22.0,14.0,15.0,21.0,26.0,GHABCDDDAGGFFEFDFHBACHDHDECGBFBFAAGECECDAFBHCDCEBGBAAAGHHEHEHEHEBAFDFCACECECEHHHCHDHAHAHCDBDGGGDHDBCCFCGHHHGDDDBEBFCFDGAFBFBDBDBGBGBABHHCHGHGDBEGAAHDCGAGBGF,False +637,7.0,11.0,15.0,9.0,7.0,9.0,10.0,13.0,DAFBFHGDGAGCDCDGHBCECFCGCDEDHDHBHBFBEGEHDADBBBBGFHHAECHGHGHBFCFAACCCFFHGACHCBCECE,False +638,23.0,18.0,27.0,21.0,18.0,14.0,17.0,30.0,DEDCHCBFEAEAEABAHGDGDADEBEHCFDGGCCCCDCBFGFCCHDHDHFBABDHEHAHFHCAFAEADHDHCHEDACCGCGCGCBAFHHHECDDDBGHHHCHBHAHECFBBGBDBFHAHGHCDGHGCGCBBBGBABFGCGAEEDFDAEHFHDHEEACAEFEACHCAAA,False +639,8.0,5.0,5.0,6.0,7.0,4.0,6.0,5.0,FGEBDBDBGHGDGCAHAHCDAGAFAFBEBEGEFDCHAEECEDACAH,False +640,25.0,30.0,19.0,18.0,18.0,25.0,21.0,28.0,DBGBFBFHFHCAFAFACGCHCHEHEGFGADHHFEAEGEGHGEAEBDADHBABDGGGGHBHDDGAEBDFCGCFFGACDHBHFHCHFAGHEDACAHBDDDAHHEBEBABACAGBDEDGHBHFHFCGCDFBFBFAHGCBDDCBAEAEFCABABACACEFHFBAEHEGBGBHBFFHBEBFBFBFHCBC,False +641,10.0,7.0,19.0,15.0,18.0,26.0,16.0,17.0,EBEBEADCFGFGAADCEFHCAEDEAEFBHEHDGDGDBHCGCFHFHCHFEFGFGCECFCGCEDAFEGDFCAEADCFEFHHHFDFGFGAGDGDFHHGACFBHDHCGFGFCHCHCHCDEECFFFFEBEBFD,False +642,17.0,19.0,31.0,20.0,20.0,27.0,31.0,22.0,EFGFHEBFAHAHFHGCFCFGFHFBFDHDAGAGBECCHCBGBFEABDEGEGFCBDDFEFADADBFEGEBBAEHEHAHAFGCGCGCBCBFGFCACHCECGCBCAGFHDBDCAFGCGCGCGCDDDCDGDGFBHGFFAHCFCFHECDGDBECCCDCEGEFBFEHHGAGCGDHAHGHEFDHAGBGBGHDECE,False +643,10.0,16.0,8.0,13.0,16.0,18.0,19.0,19.0,DBDFCEGABABHBFGAHEGFFDHCFCFBDHHACAFECHHHHGFGBEHEGEGEGFGBBDBFEFHFCEDECFAAGFGFEBAGHEHEHEGDBDFDFBEBDBDFDBGEHCAAGHGHGBGHGHD,False +644,23.0,23.0,24.0,17.0,10.0,17.0,18.0,14.0,BGGGGGEGBACCECHCHCACDBAEFEFHAHACFGGADDCDCDCDGHGCBHBAAFGFGFABBBBFBHGFAAADADCDEACDEACBHEEFCCHCHAFBCHGEGBFDFHEBBHBDBCHDBDBGFCFBDCGFGFACABBBAAAAAFDCDC,False +645,19.0,20.0,19.0,12.0,21.0,19.0,19.0,26.0,BCHEHEABABAHAHDHBEDEAEGECEBECAHDGCFEFCHHAHDHDHFBDACABGCEBHBCFHGCCCAEEDAACABBHGHGHFHBEBHDECEBDBCBFEFHHHGHGHGHFHFBDGEGACEFDFHFEFCGGGAEFDFGCGABFFCFCGBGAGFBAEA,False +646,24.0,19.0,25.0,16.0,26.0,22.0,27.0,28.0,DADGFHCDDBDHDHGGAEECHHHFCAGACFCFEDCCECEGFBFBCBGEHEACBCBGGHGAGFHCGCGEFEDAHAHFHEBBBHHAAEAECBGAAFBGBHBHAAFEEAECEGHGFCDCHHHHBDFGFGFGBEAFHFDAHAHCBCEHGHGFCDGDGCGEFABDBFBAAAHADEDEGCGHECEFEFECECG,False +647,19.0,19.0,11.0,23.0,12.0,13.0,15.0,22.0,FGFAADEGEAEADGDFHAHBHDGGGHDFBHBDDGDCDHBHBHEHECEDBDBEBHHDHEABCCGFAHGGEADAGFDAHEHDHDCDGDHHEHFFFGEGBDCACACDFDHBBBBDCGAAFAHABABACACFDFBBHB,False +648,14.0,18.0,21.0,17.0,4.0,13.0,14.0,14.0,HDCCBGAGBGFGFHCCACHCGCBCBEDEBCBDBHFCFCFGAGACBGFDFBHBADAGHCHBHFCACDFDBABAEGCHHDBDCFBECGCGBDAFFGHDBDBDADADACFDADCHHGH,False +649,18.0,10.0,20.0,21.0,15.0,23.0,20.0,19.0,CDCFFDAABAFGFDBHFHGADADAHGHGBDFCHHHCDCHAHADCDGDGDGCEFGFCECFCFCGCAAAAEAEDBDBFFHHHFECECGGEGAABHECFHDEDGHGAEADFFHGDGDGEEBDCFGEHFCGCECEDDFFFFBFBCBHHAG,False +650,2.0,8.0,12.0,4.0,7.0,2.0,3.0,2.0,BECADGCCCCCBCBCBDGGFECECDBDBHECEFABHBCEE,True +651,23.0,17.0,14.0,13.0,18.0,7.0,9.0,12.0,HGFCACACFCDEEAGBGBADADABCGDAEADGDBACFHBEDAABHBHGHCAAEBECECACEDECEGFGAAHABAEAHDHABABADEBCFCFBEEEHEBFBAEHEHDCDBGBHD,False +652,9.0,5.0,7.0,3.0,3.0,4.0,7.0,7.0,FHAHAGGGGHGCGCEHEAFAFCHDECHBABCFGBHBACDCDAABA,False +653,17.0,14.0,10.0,12.0,16.0,15.0,12.0,13.0,FFDCCCGHBHEFBAEAHDFFFHBBBBGAFABABAEADAEFCBDEEHFDACHCHDAFCFEDGBCBCBEBEGGGCHHDDAGAEAEDEDEBEHDHAHEFGFGFGHGAAEAFG,False +654,18.0,23.0,28.0,27.0,18.0,13.0,30.0,25.0,CGCBCACGBGHACACADFEBGBCAEHBDBCHAEDGDFDCCAEHDGDFDFAFBGBGEDCFBFBFDAHGCCCBGBHEHAHGGGCECEHEAGCGDGDHBBDGCECHAHDFDGEGAGDGEADHCACBGBCHAHAGBGHHCHCHGEBEAEDECHBGBGDGFGEGHCHBDDDCDHDFDHCFEHDBDBF,False +655,15.0,11.0,8.0,7.0,7.0,6.0,7.0,13.0,EFAFACBEEDCAHAHGEAEFFHBHBFBFHGAAHGHGAGDCBHHHABDBEBAGAGDDDADHBCBEACHCACACHB,False +656,23.0,17.0,14.0,15.0,23.0,23.0,21.0,14.0,DBBBEEGCGFABAGAHAHFDEEHECBHBFBEAEADGDACGFGFCFDFGFGFGBEBEDEHHCFEHAHAFAHEBABEDEFGFGBGAAECFCHCEAGDGDCBCAFHFDFDFCFEEEEECFDBGGGAAADBGBHDAGEEBHDAAAHFGCGFAFC,False +657,22.0,13.0,20.0,11.0,19.0,20.0,13.0,19.0,AAAEEECFGGCCCDBDAFHFAFCCBAAHBBBEBFBAGCGEGHCAEACDCEADBDEAFCDGECEGGAGABAHAEBHHHHHCFCFEHCHFHGHCHCFAFDFDFDHBEGEFFFFAEAECEDEDHFGABFEGCHCHAHABF,False +658,13.0,8.0,9.0,8.0,6.0,14.0,16.0,11.0,DFDAACADGHGFECCGBFFFHEAAFACAGFHCGCFAFDFBBHHFGAGABABAGEFEFGDEBFBDBGACHCHCHGDGHGHGEGDGH,False +659,24.0,22.0,11.0,20.0,12.0,19.0,20.0,10.0,ECECBBAAAFHDHDHCBGFGFACABAGGHADBEAFFDFDFDEGCGCBBBFAGABBEDGGAGFDAGHGDDAEABBGBHDGEBFBHDFGCBCBEBFDFDADADBBFEHEFEFDFHFEGDCDCDCGBGAAAAAGAFAHBGA,False +660,9.0,8.0,11.0,8.0,16.0,14.0,26.0,11.0,FEGEHCHBGBGEGHGHGEGHDEBHAFACGDGFGACHHGAFCGGFEHDFDEEGBGBGFGFGCCECFAFDFDHBGDAAHAGEGDGEGFGAGEBCCCCBEEGEFEF,False +661,21.0,16.0,26.0,12.0,16.0,24.0,13.0,16.0,AHBFGAHHBCBABABCCGBEFACECGHGFDAHHCCECFFFDFAHACACBCBGBDFEFEHEDACAEDEDEGEGDGBBBGCGAHACACEFAFDFAFBDACAFFHFCFCAGEGBFDFBFEGCFCBCFHACADDCHFHFCECEHHHCE,False +662,19.0,21.0,19.0,34.0,20.0,23.0,22.0,19.0,AFAFBGBGBABGDDADCFCECGGEAEACHDHDEFCFDFDECHHGDEDEGGFEBBBBBEFEDDFAHCBEDDBACDCDAHAHGHDCFCFDFEFEDHCHDDADBGCABDHEBBFBDCDHDEDEABDHEBFBCEAGGHFHEAGFGFGCGDGFGDGAGAGABFBFDDHDCDHHGHECDCFAF,False +663,30.0,32.0,21.0,26.0,25.0,15.0,23.0,18.0,GBDHGHGHGBGFGABAEEDBCBCAHAEEDFDADEGCCCGHDBBBEDHGGFCBBHEAACDBGAGBGFEAAAAAABADGGBGCDCFCFDFCBHAHBBBHBHGDBDEHBHBHBEAABABDDEAEDFDEBEBECEGEFAFCFCADEGCGBABABFBCEADAEGEGDCDGBFHAEAEFCDDHEHAHFDCDEDCAC,False +664,14.0,12.0,16.0,18.0,20.0,25.0,19.0,23.0,GFFDFGFDEAHBCEEHCFEEEABFGFGHGAGAGCGCFDBDBDEDEABABDBHFCFHDGAGEHEHEGDCDCFAAGAEEHFGFEDCHFHGGEHDDGBADDGHFHEHEHECFCFCDCAEFFFGFGCBHHCCFCFBFHFHEDADHHHHABB,False +665,1.0,1.0,5.0,0.0,2.0,0.0,2.0,0.0,CCCBGGAECEC,True +666,13.0,18.0,8.0,9.0,12.0,13.0,18.0,15.0,FADABCFAFAFGFGFBCBGGGFGDCDCABDHDAEHEDGDGEFFHCGEHHFHBGAGAHEGEGABFCGBGEEBEHFHBHBHBHBFBHCABBHGEEDCDBABABHGGAE,False +667,12.0,9.0,6.0,10.0,3.0,13.0,8.0,9.0,CBCHGHFADHGAGBCFDFAADDFCFHDAAAAAFCFEAAFADCDGDGHFHFHGBFBFBEBHGHGBBDFDEB,False +668,25.0,23.0,24.0,17.0,11.0,21.0,16.0,12.0,GDAFFFFHBBGCACGCECBHAEDBBFFFBCBCACACGBABEBEDDBFAHBHDAGAGBGBGAGBGAGEDBAFCCDCGAGHCDADACAEDFHACBEAACFDDBDBHBDBDFFFCFCFCFCAAAEDHFAFHCHCACHCGAGFFCEEBEBGDH,False +669,3.0,6.0,1.0,5.0,4.0,4.0,3.0,1.0,EABGBEBGBFBGDFDFDADEDBFHEAC,True +670,5.0,9.0,11.0,15.0,8.0,21.0,12.0,11.0,DFDCHCFFDHHAHACGGFBDBDCDCDAHEFFFHBDBDBEECFGDGHGBFCDADABHBHGGEGCCFFFFFDFHEBGCEFDFGFEFEHDGFGFC,False +671,9.0,14.0,11.0,13.0,12.0,14.0,11.0,23.0,HDHCHCFCFCHCFCDADADEHFHBAEGFGHCEDHFCCDEHAHFEBBBADCHHHHDHBHEDDDADHDBGBGBCBFHEBEFGBGHGFFHAHGHBAFAGBEFEBEHEGFG,False +672,3.0,4.0,0.0,0.0,2.0,6.0,4.0,2.0,HFHFAAGEGFGFABBFGFBEB,True +673,17.0,21.0,20.0,5.0,12.0,13.0,17.0,15.0,BCBDBECHCAAADCGGGGFBABABEBCBCACAGHBHDHBFEEEEAABCBCBAAHBGGCGBGHGFGAGFFCHGHGHBABFBFHCHADDFCCCECECHHEAFBFBCHHBCEGGCFAEAEGFF,False +674,14.0,34.0,17.0,24.0,19.0,23.0,30.0,24.0,BBGEGHHHEHEFABDCHCFBDAGBBBBDBFCFCFAHHEHAFGHGEGEDBDBDHCFCHCEDEDEDGCGCDDDGDGAGAGEGBHHCHADFDBBBCDDACGHGEGEHBGBGHFEFGFBBDBHBFBDGGCGCDFGCBBBDADGHFCFADGEHFCFAFGBHFHBGEAEBBBAFGGDGFEFBBHEHEBABF,False +675,22.0,22.0,20.0,24.0,22.0,17.0,36.0,34.0,CHGHGHAHAHCECDBGCADHEEGECDGBFCCHCHFGFGBBHFHFHEGFGAGCGCGDGDCBFBFEFEHEDECCHBGBDADHFHEBDBGFGBAHGHGEACGGAEAHGBDCDGDHFHBHCECBDHGGGGHBBDFDFHAAAAAHADADHGHEHAGFGDGAEDGDEEBHACFGHBHBHCGGGCAHEEAEHEFDDDGDBBBAE,False +676,5.0,3.0,7.0,7.0,6.0,1.0,5.0,6.0,EHCHEBAGEGDGDCCCCABHEGBAEDEDCDFDADAHHCHG,False +677,14.0,12.0,18.0,20.0,14.0,12.0,11.0,15.0,CCADHGFACAHGHDDDDDGFGHBADGBEBCCDDDADADABBHCFCFHBHGAGEEEEEEEGEFHCDFAFCCADBDCDCDCBBBBCHCBDAGAEHDHAHAEEHEHFFCGCDFGECFFH,False +678,20.0,18.0,16.0,16.0,18.0,22.0,18.0,25.0,DFFHFHFGFBADAGHCBCAGBCBFGFACBEFEGABBBEGHHFHFDFHEEGEBECFCEBEGGADEDEAEACHCHABEHAHAFAHAHAFBFAECECHCHGHAHBHCHFHGDCHGHEBDBDGCADEDGGFBFGDBDCFFEHDFDFDGDHCHBGAAA,False +679,13.0,13.0,11.0,11.0,12.0,13.0,13.0,10.0,DADAHACGEBDGEGEDEAACHFGEGEGFGFCFAFEBCBFEFHCCFCHCHEHAFFDBBBHGCEBGBGAAHFHGHBFDEGAGBBBBDDADADEDACFC,False +680,21.0,9.0,11.0,23.0,10.0,11.0,13.0,22.0,BHEFDAEAEGGAGBCHCBAAHAFDFGGGGBHADEDACFCFAEABHBHBAAADFFACDDDHDHCBCFHDHCHGDAHAHDDDCDADEHFFAFDEHHDHECDADAGAGBHHGHEHEHCDGDGD,False +681,29.0,26.0,19.0,24.0,29.0,20.0,27.0,23.0,AAHAECBCBAADACAFFGCEADCBGHGFEFEAEDEDBDHDEBHDHAACAHAEBCBDFFHFBFBFBFGFBEAHBCAEAGAGBEEEEEEEEDCABFGFBDHFAFAGBGHGCGEGDADHDFGBCBHBHACEBDADEDEDGGGGGGGBHBHDHCFGBBEHCCAHHFABDCGGECFBAHGDGDCEAEHECEGHDFDEDGAHA,False +682,12.0,18.0,15.0,23.0,25.0,24.0,20.0,8.0,DADHGFBFDADAEECECBFDHDBCBABAHFFFFEFEFBFBFBEDFDEAFCCHEBBGECCCCFAGBBDBGCEEDHGGEGEAEAEFDDDGDAFEGCGCGCFEDDGDFHEDGGGGGEBEDFDEDHBEBDCCEFFFEFEBABFGAGHGD,False +683,10.0,19.0,7.0,19.0,5.0,6.0,8.0,11.0,CHCGBDFEGADBBBBBEGHAFAHBGFACAGAHDBDBDADHDGDBDCCCEDDHDADADCDBBBHBFBDBDFDADEHHHBHGGEFBB,True +684,10.0,3.0,3.0,5.0,2.0,4.0,6.0,12.0,DBCHHBHEDEGAGAHFGGHFAAAGAGADBCHAHAFDFDACHHHHH,True +685,10.0,19.0,16.0,24.0,9.0,16.0,18.0,17.0,DGDFEBDHDADCDBDHFHFHAGCHCHAGEEBGBGBAFDHCBADCDHAHEEABDDFDFABBCDDADCDFDFBBGBGHECCGCGDECGDBFGGEGECHCGFFBFBDGFHBHBHBCGCGCGBDDDFHFHFHA,False +686,11.0,7.0,14.0,17.0,14.0,20.0,12.0,14.0,HDHABCEFFBEHCGCACACBHBGEGEFFFBGCECDCDEHEDEGFGFDDDDGDGAHDHDADADFFFAHAEDHFBADEDBCCGHAEEECFFEFCFHFGCGAHDFGFHFCFH,False +687,19.0,24.0,19.0,21.0,13.0,20.0,17.0,22.0,GBGCDCDHFCAHAHBFFDCAGBFBABCFFBFACBGHGHBFFGHDDADHFHFHBGGHGAFDFCGAGEDEGEADDFCBABFBABAHEDEGFGFCBCFDDADACECEBEBCHCACFEGCHBBBDDDGHHDHAHAFABDHEHEHEGEDBABCBDBHCHC,False +688,11.0,6.0,12.0,7.0,7.0,10.0,7.0,5.0,CCBGGGGFABECFADHEACFCFGFGEDFCFAFBHBCBHBDCCHCAAAAAEDDDDAFCFCEGEAEH,False +689,1.0,5.0,2.0,2.0,0.0,1.0,2.0,2.0,DHDGFGCBBBBBCHA,True +690,15.0,19.0,20.0,21.0,26.0,23.0,15.0,18.0,GBGBGEFEGECEDHDHDHDHDCGAEACGCFBFECCACGCDEDFDHDFBBBEBDHGHDCBAAAFBHADFBFHFHFHFEDDADEDEFCBBAEEGEACCHCEGACEDECECFFFFHAHEGEBABEDFBHEDEAEADFDCHFHFCGEBHCFFFGBBECGBG,False +691,16.0,20.0,16.0,13.0,21.0,17.0,19.0,17.0,EEBEDECEAEBBBBEHFBFBFDCDCBCBCAFGHGCECGGDHAHCDCFCEHDHDBBFHFGEECBGBFHDHGHEBEBEAEFBAAAAEAGGGFEFCFBABDFGFDFHAEEGHHHGDFHFGCGCGDAAACADEGBBCAHGEGH,False +692,15.0,18.0,25.0,15.0,20.0,16.0,23.0,15.0,DCAGACABGEGHGBBCAEGHHDAAAFGCBCBCGGDGCGCHCDCDAFCFGHGCGCEEEHBGGECACADEDFDFGFDBBFBCDCFCDCEEHEHFDBDBGEGFFBFBFEECHGHBAGABABEHEHGCEHBFDCCGDHEHEGBFAFAECEC,False +693,18.0,15.0,17.0,18.0,19.0,18.0,17.0,13.0,DAEAFACADHDHCFCBBBDFDEGEGEFDGBEFEBGHGHEHGGAFAFAGAEDEBHDADAEAEDEAHGHAHCECEHFHBGFAEAFBCGFDFGCACADFCGCBCBDAHFBCDEBCFCFGECDBDBGBGECECFDDHFG,False +694,7.0,11.0,9.0,10.0,9.0,4.0,5.0,10.0,CDDDBBCGFGDHDHEHBHEHEBEBEAEAFHDEGEDHBAAFHCBFEGCBCBCBAAHACCCGBHDDD,False +695,9.0,7.0,7.0,14.0,15.0,8.0,16.0,16.0,DFDCDCDEAHDDDBHHFHFCDCHCFBAEEDGAEAGGFGHAEECHGHGHEEGDGFEFEDEGBGEDDBHBHGEGFAHAEAHAHGBGHGHGDECB,False +696,24.0,23.0,24.0,22.0,20.0,19.0,26.0,26.0,ADGDAEBHCGCHCEADABGBGBFEEGFAFAFBFGDGDHHACDCHFACHCGGHGHDHCBGDHBACHBHGHGAAEBFAHGGDGHGFGDCDCGCDCAEGGGEEEEEHDFDAAAHADAFADEBBBHEHECACBEEEBABFCFCFCECFCHBHBAGABHHFHBHFCDEBCDGDFDFDCBFBCBEAGDGH,False +697,19.0,24.0,22.0,23.0,29.0,24.0,25.0,34.0,FCFEAEAHCGEDABFEFDHCHCGCGCFHABDGEGFGFGBHBCAEEHGBCBCBCGHDHFHABGHDHCCCAADDFDHDCDHFBEHEHEGFBBHHHADEEEBEBFACHHHHGHGABBBBEDCBBBEDEDFFFFFFHCHDAEFEGDGHFBDGEHHGFBDADECEDEDGFBFEGCGHHCHCHGHEFEAAGAGEGDGCAHAEAEBD,False +698,13.0,19.0,14.0,18.0,18.0,16.0,11.0,16.0,BDBFFDFDFGGHAHBHBHBHFGAGAHDHBEBDBHBFBFHCBEGEGEDCCCCBGHECDCACDBFCEDBDFDFDHDFEFHFHEHEFEBABDEHBCDDHAAADEBAGAEACGEAEFBCEGEDFCCAGE,False +699,20.0,17.0,18.0,13.0,20.0,22.0,16.0,23.0,ADHHHHFDFBFAGADBEFFFEFEGCFBDHCAEABAEAEBHFECCFDFHHHHHFHCHCHEHEAEBGHACABFCFGAGDFDFCBHGCFCBCHDEDHGHAFDFAGECECEFAGCDEGEHEAABCBGBGBGBABGEAHGEAFHFGCECADBDB,False +700,7.0,10.0,13.0,7.0,8.0,14.0,8.0,3.0,FAAEFBFCFBFBEDGHCCCCCEDEDFHECDBDGFGFADGBEFCFCGAAAHEDECACFBFBGGGFCFCBBB,False +701,16.0,27.0,21.0,29.0,23.0,22.0,14.0,18.0,ABAEADACBDBFAFDCGBDEDBBFBFADHHAABHDGABACDBDEAFCHCECHDDACAFDFDFEAEDHDFBFBFCEEBECDCDHABFBGEGFHFHGBDEDEDEDCDHDHFAGDGHGHGHBCBCBFHCEBEHCCDCBFBFBECFDGGGFCECEDHBGBCFEEDGBFBEHEDE,False +702,22.0,31.0,14.0,20.0,15.0,20.0,18.0,12.0,GHADBDAFCHAEBDBDBDFDEAAABADEDCAABBEGEGFGEGFDFBFBAEGBBCBCBEGDCDAHCHBADADGFBFBHBGBDCFGDGHCDCFCBEAGFGFHFEBECAFBFBHBHBFBEGEGEBEDAHABADABBGBCAAGDFBAGHCCFDFHF,False +703,21.0,26.0,13.0,16.0,14.0,14.0,14.0,17.0,CHABCBFGFAABAGAHAHAHACBDFHAHEHGCACDBEHDGBHCECEHFAACABHBABABECGBGAGEFCGDEFHBBFAFHFHAHEBEFEGBGBEBEDDDDDDDAHHCBCDDGEADABGBDBFGFBFBFBGEDCBB,False +704,1.0,0.0,1.0,1.0,3.0,1.0,3.0,0.0,DEECEGFGAG,True +705,7.0,6.0,9.0,6.0,4.0,3.0,8.0,5.0,AGABCBCEHFACGFHHCHEACADDDDGBGBGBCEFHBDEDACGCGCGA,False +706,6.0,5.0,9.0,7.0,4.0,10.0,8.0,4.0,BGHGEDCHCHCGCFFGDGDGCBCBAADFFAFEFGAGADFHBAFCBCEDEFCFD,False +707,10.0,10.0,4.0,9.0,12.0,8.0,9.0,7.0,EECFAEAHAHAEAEBEHFDFDAGCDHBHGGEGEGFDFDEBADDCHFDDBFGEGBGBEBEAHAGBFBABC,False +708,11.0,14.0,22.0,17.0,26.0,26.0,22.0,25.0,ADBFFHCHCHCDGFCFBHBHBAGACHDFEFHCBGECDDGEHEHDHEGEGEGECBHAECDHDCDEEFHFDFDABHGDEHEGDHDGFCCCHCHDHDHBAEEGEHEHGGGBBFEFEDEFHFCFAEHECGCAFFFCFBBCAFBCHEEGEGFFECGCGFGFGFAFAGB,False +709,20.0,25.0,16.0,17.0,13.0,14.0,18.0,22.0,CDEHBHBHAHBHBGDGEGBACAHAHGBGBGBAAAGFDEEBGBABABFGACACHGHDFDADHEFDHHECFDACABGHFHDDDAEAEDGDCDCFCBCFHBCBEBEBEBFCGCHFEGGDDBBBCEHGDACABGHGAFHHHBFAFCFHB,False +710,30.0,23.0,16.0,22.0,21.0,35.0,15.0,23.0,FAFAFAFEFEHAHAEBEFDFDBDHFCEAHHHHBEFDADHEHBCCCADEHFHFHFCGGDECGCBDBGAFAFBCDAHADBECEFHCBCBAAAFAGBFADDFDFHBGAAEABFDEDFHAGAHAGAGEGHFEFCABAFCBEBEBHFDDDFDADEEEFBFDACEGFBDBHBHBFGFBFCFGGHAHAFGFC,False +711,6.0,6.0,12.0,7.0,12.0,9.0,12.0,10.0,HGEDHDGCGCGBHBHGCFAGABCBGGEBCHCHFGDEEEHEHAHFHCGDFEFAFAFDECECDCFABCGEGFCEDE,False +712,23.0,31.0,32.0,27.0,25.0,14.0,31.0,14.0,CGABCFCEHDFDHEHBDBDECCFBDGHGAGBGCHCBAEHEHDFDBDCEFGCGCFBAGGGEFEABFBGEAAAAHAGACACECACBGDGDBHBCFGHGBCAAAFBDDDDDDFGFCECBBEEGDADCBEAEAFDGEGCCBCBCBDGCECGCGCGCECECBFBDBABDBDHDCEHEBECGAABDBGGGDEEGEBBAHGGDH,False +713,4.0,5.0,5.0,9.0,4.0,5.0,6.0,6.0,BEFEACAHDHDHGHBDCHCDEDFDGDBEFGDGDFAFBBGACHCG,False +714,18.0,19.0,22.0,14.0,25.0,27.0,18.0,19.0,GEHFCECFCAEFBFAHBCCEBFFEFECDADEDEAEFEBECECGHGAAADAGHBFGFAFHDEABBDGDEHEFEFDBCHEGCCEFBFEHHHHGHGCAFAFHFHFGEHEHCGDFEAEAGFFBADAFFCFABGBABFBCBGBGCDCDHFHCECECDHDBGBCBCGG,False +715,17.0,8.0,11.0,12.0,13.0,12.0,12.0,14.0,BAGDHBHDHABAEGHFDADFECDCGCGADHDHDHABCBHGAAFBFBEHEAFCFAGHEBCDFDFDCHCHCADAEHEGEAEGCGCFEHAGGFAFEFEAEAG,False +716,16.0,17.0,24.0,24.0,21.0,17.0,16.0,24.0,FCBCBHBCBCECDCDAFFHHHCHDBEFABAEDEDEDECFDGGGAEFEFEHCADAFACEEECFCGAEDEDGHGDGAGFBHDHFHCCGEGBDHGEBHHHEHACAEGFDFDHCECBADECHHHBBBFBFBDADCCFCDCBCDEDHHCGDDAAAHBHGHGDGF,False +717,30.0,23.0,30.0,24.0,12.0,21.0,21.0,16.0,ECEDACAHEHCACECDCGCBHAGDFACBCBAFGFGBACCCCACFGEGFHHAHABGBEFFBFDFCGABCDCBBBBBAADADGDFDFHFDCDCHFBFAAGAGAGAGFCCCHABGDGDBDCDEBHDCDCDBGFFHHGBEAAHAHDFDEDAHAGDCDBHAFGGGBABDFCACACBCFEEAE,False +718,8.0,9.0,11.0,13.0,10.0,18.0,7.0,15.0,BHBGDHDHDEAEFFAGAGABHFFFADHDHDGAFCDCAHBDECFAHDHCCBGHFCECEHEFDBDCDGEGDBHBECFCFCFHBEFFFFFHFHE,False +719,12.0,23.0,32.0,23.0,25.0,25.0,24.0,32.0,ACHDECHBHFHGHGHDADAGHCCEBEBCCGHFFGFCBEGCCDDDBGFDHDHDHGFGBCFCGCDCDCDCFGEDBDBEGGCFEFEHEBEHECBFDCDGBGEGBGEGCFEEECGFGADCFEAEADBBCECEHEBEDFHFCFCAABGHHHHHFAFABCCHCFCAHEHFBFBFHCGFBDGDEBHBHCECGDBAFHHHHHDH,False +720,9.0,6.0,1.0,2.0,6.0,3.0,3.0,2.0,AAABABDBGEHAGABCBGFHEAEDEAEFEFBA,True +721,4.0,4.0,5.0,4.0,1.0,4.0,3.0,0.0,BGBCACGCDDFDFABACECBFAFDG,True +722,16.0,8.0,13.0,19.0,18.0,17.0,9.0,17.0,DFEFCHCGADHDEDAHEDEBFHFEFEAEDEDHAHADCBAFACAHEHDCGCGCDCDHDFECEBEDEDEFGGABFBFGCACFDFAFBDGFHCADHEHEGDAEAHHHBHFHFADCFEBGA,False +723,20.0,21.0,15.0,7.0,15.0,20.0,22.0,15.0,AFCDCFCFGFGAGBCACBHAAFGFBBEEAEGHDEDBHBHEHBCGEGFACEGHGHGCGEGECAFFGEGEGEGBBFAFDCBCFCFADADBHEAEHGBGHGBAFAHCBADFBHBCBFAFHBABABAFABHFGFGEHCG,False +724,22.0,23.0,14.0,13.0,20.0,26.0,11.0,21.0,DEBABADADEGBGBEBHBCCAAEAFFDAAAAFEFAFGFCFCBHBCFFFCFBFDFEHHDHCHCFDEDHBHBGAACEFAHHFABAEEEEGBCHCECACGDHAFDFHFHFEFHAGGGFCHBBDBHBEBFBFHHEHBBBABEEFGFEDGDAHAE,False +725,21.0,25.0,25.0,29.0,21.0,32.0,25.0,20.0,FGGGCGEGDFAHHHCCCGAEABFBEBDBDHDCDEDAFGDGAEFCFCEAEADABCBGGGGGCDCDCFFFEHACBCBCGCFCFDBDFCFAHBDDFDFBEHEADCDFHEHFFEGGDGFHEGEBBBDHEAEAGAGAHBHAAGAHAHDDCBCFFFHFEDGDHDBFBEAHBFBEDFCHGFGDCFEGCHCFBFDEDFDABBFBCB,False +726,16.0,20.0,16.0,17.0,10.0,18.0,13.0,17.0,BBBBGCACACBFBABFBCDHGBCHCBADABFCFCFGAHEGBGEEEFDGDFAGAGCBCEFHFHGHFHAHFDFCHAHAGEBDBDGDCDCHFHBDDADCBFADEEEHHDGFGFHADEDHFHCBCBABADF,False +727,10.0,29.0,22.0,26.0,22.0,17.0,21.0,19.0,BCBCBCBDAFHFCECDCDCBHECFCGAGDGBHFDGDGBGBEDEDEDBCBAFAGHBHDHAADBDCGFGHDBDEGEFBBBCBEBEHECDHEGDADCDHDBBGCEHFGCAEAEBEBFBHADCECFCFEDGHGHBHFHGHBCFGBCEFDHGBGFGEBEHEFFDDBDECGD,False +728,11.0,13.0,13.0,11.0,13.0,20.0,15.0,18.0,EFFFEBCDCHCAAAADFHFHGAFDFHFCFBEBGCGAFBCACAHAHEDBBGEDEDCDGBGFGFGCHCFFDHEBBCGGGGGDFHAHDHBFFCHHDHEHEFBHBHECAGEGEFEFBH,False +729,26.0,25.0,13.0,24.0,26.0,16.0,21.0,19.0,DBDFABGGFGHEHAAAAABFBFBGBDBABAGEGCGFEEGEBEDHAEDCHABCDEFAFAGDHHAHADAFAFGBGAGHBDGCHHHBFFEAEDBDBEHDBBEDDHDHDCBCBEHCACDHFCGAGEGDDBEBEBEAGAEADABAFFFFEHGCGCEEEEBEGDHDGECEABHDCD,False +730,16.0,17.0,13.0,13.0,6.0,15.0,8.0,16.0,CCHDADACCDBABEBHDFBEAGBGFCECHBAAEAEDEGCHCHAFBHGHDBDADAFBDBGBHCHCAGAGHHCDCFFDFBFBADFBFBFHAAADBFCFGFBFHHHH,False +731,16.0,23.0,24.0,23.0,24.0,17.0,32.0,25.0,FFFFFFFDDEDGGHGHGHGFDHBCACGEGEBEBECFFBFBDECCDEHCFGEACHDHDHCFDHEGABHEGBGEAEHBAGCGHGHEEEDEDHFCGDGBAHAGAGDGBACCEAGAGAGAHFBCHCGCDCHCHBDBGBEBGCDFDBCBHEHEHGCGHBCBCGCAADDDGHGBDEDEGBBDFEAEGBCH,False +732,2.0,3.0,2.0,0.0,1.0,3.0,2.0,1.0,FCFGFHCBGBAEAB,True +733,6.0,2.0,3.0,2.0,1.0,4.0,1.0,4.0,BFFCHCHCHAAFADBGFDAHAEA,True +734,5.0,4.0,6.0,8.0,4.0,8.0,3.0,7.0,DGHGDEDEFAFBFBDDEAADFDHCHFAFBDGHHHHCCCCFCFBEA,False +735,11.0,7.0,8.0,6.0,4.0,4.0,8.0,5.0,CHCACAGAEDFDCBHDHFHBCDDHAFGGGCACAGAGBBBGBEBDFAAGAECEA,False +736,20.0,16.0,16.0,26.0,10.0,23.0,15.0,12.0,BDBHCCEBDBACHCDFGFCADHDFDHAECDAGAGCFEFCFEDDDDDDDCFHHADFDABEGGGAGAGADABAFCFAFDBEBEGACADDDHAHBECHDGBGBDDEGEGDBFCFHBADGHGHFFFBFAFAFCFCFBFCFBA,False +737,23.0,11.0,24.0,14.0,10.0,9.0,22.0,11.0,FHADCDEAAAABDBHAFADADFCGGGHGAEAHCGDDCDCDHAHCGGGGCACFCBCBCGCHAAFAHEBADAECGCGCGDGECEDGBFCDBAGACFHAEGCGEGBGCECHGGFHFABABABCCDCE,True +738,26.0,23.0,28.0,29.0,22.0,16.0,18.0,26.0,EHDFFHFHEAFFBBEHDBBBDBDCGEGEGCBCDGHAHDEDEDFAFGCCCACBDAGAEFHFHADAFHCDCDBDHAAAAAHCHCHFHFEFHCHFBAEDHCBCBCBEBDADGDAHAGACACBHEDDDEHCHBDECCGBGBHDCDHDBGCCBGDGCHHGFBAEGEAFACACBCEEEEHEGCGAADAEBGDDD,False +739,8.0,2.0,10.0,6.0,9.0,6.0,10.0,6.0,CGBDCDCHHEEAEACAEEGFHFDDDDFGFEAHCCCCCBFGAGAGEFAGAGHCEGEGH,False +740,11.0,8.0,17.0,13.0,9.0,9.0,18.0,8.0,BGAGBECGDGHFHBHBGDGDGCCCCCCFCFDFAFHBDADGDGBBCACAFEDGDHCECHAEEEBDCGGAGFGCGDAAEDEACHEHCCFGAGDGF,False +741,4.0,2.0,8.0,8.0,5.0,1.0,3.0,4.0,CECEAEHCCADDHDHGGEBHBECFCDDDDCDAGAC,True +742,2.0,9.0,1.0,2.0,5.0,5.0,1.0,4.0,CBHEDBAFFDBABEBEBHFHBHBFBGEFE,True +743,18.0,19.0,21.0,21.0,22.0,11.0,26.0,21.0,EAACDDDHDGEGBHHHHEBEBABHEHBFGCGDGEGCDCDGGCGHFFDFBBGACADADHHADCDGDGBCCCBEDECAGHGHBFCFEDEDEGGCBEFEBEBEHADBHBGGGADADFGFDAEAGBBHGDBHGHCHCACACAEFEGHCECEAFHCHBGEGECA,False +744,31.0,23.0,20.0,24.0,21.0,22.0,28.0,21.0,DADEBEBEDADABCBFGGGGGHGHAFFGBGBGCGDGFGHBCCFDEHEADABAGGBGFCFCAGAHHEDBHBHFFEHAGAGBCDFAEBHDDDDEHHACFBHDGDGACFFBDBAAADAHAHCHCEGAHAGEEEEEBHFFGADABABEBEBCDCBHFHFAADFCGCGBAADDDFCCCHFEFECEAGACAGDGFE,False +745,5.0,11.0,15.0,7.0,10.0,9.0,7.0,16.0,EFHFBCACFCEHBCBABABCECFHHHHFEFHCHCFCBHHGGEGEDDDHAFGEGCBDDDHEEAFBBCHCHEHGHBCBCDCG,False +746,1.0,0.0,6.0,5.0,2.0,2.0,2.0,0.0,GDCDCACECEDFDGCCFD,True +747,14.0,8.0,8.0,12.0,14.0,15.0,12.0,12.0,HCHDFEEGCBCDCAEEEBEFEFCABABFBFDEGFAHEHAHCHGGFCFDEDAHCHDFDGDGABHEAAFAFHFEEGAGDDFBHBHGDGEGAGAFAFD,False +748,23.0,22.0,15.0,27.0,27.0,24.0,31.0,19.0,CFEFAHGBGDEAEBEAEBHBDDGBFAHCGFHFHGEGFAFADBEFHBEBCCFCGEGADBBGGCGBGHHBEGEGABBEEEAHAGEGFGAGFCCBFAGBGFGFGFADDBDBGBFEFGFAAAABHCDDDDDDFDFHFHBGDEAEDDDEDEGEDEDECHDHCFAGAHAEAGADFGHEHDHCCGEGEDBDFCHC,False +749,18.0,23.0,17.0,19.0,17.0,23.0,21.0,21.0,EAADEDBDBFBEECFCDEGFDFHBDAFFBCCCGCHCHAFAFAGGHGECECEBEGAGDGDHEFEHCBAADAFBFBHBABGBGCFCDHFBDEDECFGFBCHHDBBCHDGDFFBFBGDGBHHAHABADADEEGHGHBHFFFFEFGCGCDEHHGHGAAAGBBH,False +750,26.0,15.0,24.0,31.0,22.0,18.0,27.0,36.0,HFCEEEDBCEHFDCDCDGDAHEDGBCCDCGHDEECFHFAFADHFCGEEAEHEHECGABAHFBFBFDACBDBDCDHDHGFBFACAHAHABAHHHCDGHGHGHAABFHFGGHADDDDDADCDEDGDEAGGGGAGBGACCHBHBFDDEEHEDDHCHCHCHGFGAHHHBHFGCGHEEDEDFBAGHGHCECGCAHAGFEADAGA,False +751,2.0,2.0,6.0,6.0,5.0,4.0,2.0,6.0,DCHAHGHCHCEBEGDFCHCDCFEFEDEFHADBD,True +752,12.0,16.0,4.0,9.0,13.0,13.0,11.0,4.0,EBEBDBDBFAHAHADAGBCBFHEEAFAEEBEFGFEFAAAGGGBAFCFCFDGEBBBBBBGAFEEDDDGAGFGCEFEGBDDFHB,False +753,20.0,22.0,13.0,25.0,23.0,25.0,27.0,11.0,DBDAFFDEDEDEFEFDBCFFHDDEEEBEFDFEFEGBGCHCEBEHEHAABAGGGDEAFDFBGGGDFAFAFACHEEBHACBFECCGGGGGGFDFAFCGEGEFHBDBACAHAEFDBDFGABFBEGCGCDHDHDGDBDBDGCFBGCAHGDGBBFAFABEGEGABADADGB,False +754,13.0,24.0,24.0,21.0,25.0,16.0,20.0,11.0,BHBDGCGFGFGFGHGHBFGCEEFEFBAHEHEHEBCDEDEDBBCBCEFECGCDBACAGDGDBBHCCGDAAEAHCEFECABABDGDGCBEDHGFEDEDBGGCACDDBEBCBDFGGGEEHECECEFDFDBBBDCHAFDCBCBCGCFFACAEAEDBFE,False +755,21.0,23.0,12.0,20.0,22.0,23.0,13.0,24.0,FBFBCBFBFECEBHBHDHBBBFBACGBGBDAGFDACHHGCGHFDBHEEEFEAEBEBFGAGAGEDDFDFEFBCAFDFEAEAEDFDBDHECDCFCEAHAFEEHAHGHGHCBDAEGHBDDDBDEHGBAHAFCHGBFHFHEHEADHFHFHFDEBCAAAAHAD,False +756,9.0,16.0,8.0,17.0,8.0,7.0,7.0,4.0,EFEFGFGCCBABHBDDDDGDABBGBFBFEACDBDEDHCGEGBCBCBFDDDEAFABADAHEBADHDCCEDGDBBBAD,False +757,15.0,20.0,18.0,27.0,18.0,16.0,16.0,19.0,GHFBGBCEEAHDBDAHAHEBFFDDDDBFBEEAGBDHDBEGHAHADDEDCFCFBHAHBHDDGDGDECECGHGFGDADEFCFCFDADBGEEBCDEDGABABHBHBHCDCECECEGACCEABFBFBCCHABGHFHFACDDDDDGHECGFGFH,False +758,24.0,10.0,20.0,10.0,13.0,18.0,25.0,18.0,HEHAHAFAHCGCGCHEBGCGHGHGFGCGEABGHGFGHCHEAACABAHACFEAGCECBGGGGGACDFHFAFDFDFDFBEEAEAECFCAADAGFCHHECFHGAGHGEAHFGCCDBDBGACAGADABBDBDCFAFHGEFCF,False +759,5.0,2.0,3.0,3.0,1.0,2.0,7.0,3.0,CFAGGHGHGHBDGDGACEDACAGABF,True +760,23.0,15.0,19.0,10.0,31.0,25.0,21.0,16.0,FGFGHGDGBHACAFAFEFEGEBFGFGFECEDBFEFEHHCFAEACFBBBAFEDCGCEAECFCBBHEGEDEAEFBFGFGADCCCBHAAEEBABAHAHACECFHFEDEABFEDEAEBECACECGFGFEAGAFEFACHGDGAEAEGHHHHGDCBEDEHFHGGCG,False +761,4.0,5.0,6.0,6.0,5.0,5.0,6.0,6.0,EFBFBFGDHCHFEFGGBDAGACHCHDHBAAECCBCDEDEDGHG,False +762,5.0,7.0,14.0,5.0,9.0,9.0,6.0,9.0,EGEFHBHFGFHCEDEBEFACAEAECHCHCHCHBGCFDFCCACBCDHDFGABHBCECDGGEFCFB,False +763,7.0,10.0,9.0,14.0,6.0,13.0,15.0,4.0,FHBHAHAFAEDCDEAEHFDDGFBFBFDGGFGBGBCBFDGDBCGEGECAGAGDGDFDCDCDFGCGEBDGFBACFBFDCG,False +764,18.0,17.0,21.0,10.0,17.0,19.0,30.0,14.0,GFCBGAFBBEFFCGHGEADAHFHEAEAHAHFGGGEGECCFAGAGFFCACBFAFAFGGGAEHGHFHBHCACHFAFDEDHGEGDFBCGCAHGCEBEHCBGBDDCAGBDAGECECACBCBCGGGBBBBBECFCFEFHGDGDGDGEGEGC,False +765,16.0,9.0,24.0,14.0,21.0,12.0,17.0,12.0,FCCCCEGDGDFBEGCBCDDDDCHFGACDHECCCEEAHGHGCCCFEAAADAHGEBEFDDDCDCEAGCGDHEAEAGADAGEFCFCFGFGEAFHEECECEGHGBFCECEBFBCAEBGBGHAHAHAHBE,False +766,2.0,5.0,3.0,5.0,5.0,3.0,5.0,14.0,GCCBCDHEEEFHHEBEHGHBHDHDHAHFGAHDGDGHHHHBFB,True +767,25.0,19.0,25.0,19.0,30.0,21.0,34.0,24.0,AABAGCCCGCDFDAEECGCHBHGHGHDAGCGDFDCEGEBAGFEEEHHAGAGAGFECEHGCECEHFHABEEEBEFEBEFEBCGGGDGABEDEDADGFGFCHHHHDDFBFBAEAEAHGFCFAAAAABAFHECGCDCGFADDBHBGCEHFBBGDHFAFHBHCHFHAGGGGGGAGCGEDEBEDECHFHGBDEDBFGCCCCE,False +768,25.0,18.0,18.0,14.0,17.0,14.0,28.0,21.0,DBBECABABAFFCHGBFEAEHGGEEEHGHGAGADAHGCCFDFDGAFCECECDBBBFBDHHGHEHBHAHGCGFGHHCCFAEAECGAGFHHCEGGGCDCEHEHEDGDHDAGABACCBCBGFFBBHBABADAGGGGHGAGAGAECFBAGAFADAEHDD,False +769,1.0,3.0,1.0,7.0,6.0,6.0,6.0,3.0,EFGFHFCEBGHFBDEDEHEAFDDGDGDGDGBEF,True +770,10.0,20.0,19.0,21.0,15.0,21.0,16.0,16.0,CDHDGGGCGEGECDCDCDABFBDBFBFDFHFHDDBEAEHBGBGCDBGBCHHDGFGCHDHCGCAAHABAFHHBDEFEFCFDFCFCFAHEFBFBGHGDDDCBEGGFEBEAEBDBHCHAEFCDCBFEFEBHCGCBFDFDEA,False +771,4.0,6.0,5.0,4.0,2.0,2.0,2.0,5.0,DBACDGDBBHBHCFDECECACAHAHGBFBH,False +772,20.0,21.0,27.0,26.0,23.0,24.0,13.0,18.0,HHGDAACADHDEDCABDHDFCFDBCFCABDCCCCFFFDFBCBHBGEGHGADACFDGAADDDDDECEHEHDFEBEFCFHFAFCFCFAFCHHHCEBEBEGECECFCHEFDCGBAFADAEAEDEDEFEHEGDAAEBCAEABBFBFBEADGCHDBGBDCDFGGBCBCBEHGHCHBF,False +773,23.0,11.0,12.0,12.0,15.0,10.0,15.0,14.0,HHBEBEDEBGBDFCECGCGEGCHDHGHGBCHAGAGAFAFAHAEEEAEAGBGEGCGAACABBHDABFDFAHADGHFBCDDHAAEAEAEAEACDFDEAAAHFDCCGCHHGDBFF,False +774,17.0,24.0,28.0,15.0,15.0,16.0,18.0,18.0,EFEFEBGCDADCEHBHBHBFBECECBFBFCGCEDEDCCFCGCGFGFACCDFHAHGHBHCHEHECCCGGFCHCADBBBGHHEGCCCGCBHGEGBBBAADCDCDCDADADABFHFAGBDBAHGBBABFEFGBEAHBGCCHFHGDABACAFDEA,False +775,3.0,0.0,2.0,1.0,0.0,2.0,2.0,3.0,AGHGHFDFCHCAA,True +776,17.0,9.0,11.0,6.0,12.0,12.0,17.0,14.0,GCGDABAFGFGCCECFABAEAEBGADHHEHAAAEDEAEABDFCGBADAEHGHFFFGAGFCFDBHBFGHHCGAGHGEGHBHCECEAEAGFCFCBHGHGH,False +777,4.0,6.0,1.0,5.0,7.0,2.0,6.0,4.0,HEFEAEAEDBBGDCDHDFEBAAHEHEDGBBBGGGG,True +778,6.0,7.0,4.0,4.0,5.0,13.0,4.0,5.0,HEHEAFGFAFAFBGBAFFFDEDECBCFGDBEHFAFBFDFHFHGBACCB,False +779,9.0,7.0,5.0,6.0,9.0,8.0,7.0,9.0,DGBEBEDHAFAFHFHFCFCEDEGEDEDGHAFBHBAGAFBCBHFAGADAECCBGEGHHEHA,False +780,19.0,21.0,16.0,16.0,23.0,19.0,26.0,22.0,FFCAGEGEGAHBBEBEGCDFEFCFGHHDHDHDBEFFAGEGAGAGAHEHFAEDBACCCEDGBEACFCFEDEABABABFHFBGBGAGEHHACBCGCHCHGHEABACDBDHEGFGEADHFBDCDCEBBAGHGHEHEHGHDHDGDGFHABECEBDGGFGBGBEFFF,False +781,15.0,24.0,23.0,18.0,23.0,14.0,17.0,21.0,FEAGCCBABABAFAHCDGHFCAEGBGBGHHBBCBFBABAEDEDADHFECGDGAHEBEBECCGCHCHEBCFEDDDCGCGDGDHEFGGCHCBEFECAHDEDFDEHEGEFBBHGGCECECFBDBDBAHAHEHDHECFBFDCECABABHBGBCHFHDHE,False +782,14.0,24.0,23.0,18.0,18.0,17.0,19.0,17.0,GAECGCBBAGAGAGFEEDDFBEEEBBGGEECCCCBEGEGFGDGCHCHCHEADBDBHBHFGADBFGDHHGAGADDDDDCBCDHFBFHDAGFHFHFHCBCFEHHHBFCFHFCGCBCAGFEBDFCECHCACBDBCEAGDBDBEBEBEBABAFC,False +783,17.0,21.0,14.0,26.0,20.0,11.0,14.0,15.0,CHAHEHDHGCCADABAEDBDBFAEABGDDCGADADBBAFCEGDBEBDHGEGFHEHEHEFCFDGHADADBDBDCDCGBABDECEDEDFDCDCDADEDBDHGBGBECDHEHFFBAEAEBEBGHGEBCGGBEFHBHCFAFA,False +784,9.0,13.0,21.0,19.0,11.0,19.0,13.0,15.0,ADHDFGEBBCCDCDCFHAGDBCBCECEAGAHCDEAHBHEFEAHHGDCHCHDHDHFBEADFCGCHDHAFBGBGBEFDFGFECACFEFGFDCDEBGBGCFBFCDGDGCFDFHFHFCFCDCDB,False +785,3.0,4.0,10.0,4.0,5.0,8.0,5.0,7.0,FCFCGCGEAAGFCECECHFFDHCACGCGEBHFEFHBHDFDBDBHHC,False +786,13.0,15.0,20.0,21.0,12.0,14.0,14.0,18.0,BFDGDGDADECHCHCEDGDBDGHCHDGCABEEFEFGGDDBDHDHDGCCEBDFDFBHBHBHFHFAECEBAAAFAEAHBHGHDFEFBHBABECCCCCDEGHGBFFGHCDCBGDCCCFHDCACAFGHADA,False +787,12.0,21.0,22.0,19.0,22.0,24.0,29.0,14.0,CGCGEECEGGBEAGCFFFCDCEEACFBFBGBGDGDHDHCBCGADEHGHBFGFGFDFDBGEGEBFCFCFCFABDBCAFFGDGBFHCHEECDFDFCBEBFHGCGEGAGAFDFCEGEGEAAHHHBGCGCGAGDGDBDFGEDBDFDBCHADEEGEHEHABBFEHBCB,False +788,17.0,13.0,19.0,20.0,16.0,16.0,19.0,15.0,BDCEGHGDAFFHFHDADAHEEEECFCGDHBHGGGAGAEFGBCADGCCCCCCGCDCBEFEFDFECADABAFEBGBGAADGEGHADABHFHFCEDHDGGCDCDFDADGHCFBBCBCEHBHFHDEDEDEGHGAAAFBF,False +789,28.0,17.0,13.0,32.0,28.0,13.0,27.0,17.0,AEADADBGBAFAEADGBAAGDDEGEBEFCFCFHFHAEGEHDHAADEDHDCFCBAEGEGDGCGAGBGBGBFDDDEDGBGBGBDDGGADCDBGAEAGDBCADEDHBABAECHCECAFEHAFACDCDGEHEHFBEHDDDDFEAABDHGHGHDAGECEGEGDHEAEGEGEAFHDHDFAE,False +790,20.0,14.0,14.0,14.0,17.0,15.0,16.0,18.0,FCFDDDHCHCEGHADCBGFEFCFEEEEBEADABHBDEFCABABAGAGEHHBHBDAECGDEAAAFAEADBHCGGBGBGBEFEFEFABAGFHHGACDBDHHGFDACEHDHGHFCFDHCHCHCEFAGAGAG,False +791,18.0,17.0,18.0,19.0,20.0,20.0,6.0,18.0,FHFHFDEAADAFBBACGHDCDFAGGFEFADEDBFBFECEAFAFACCCEFHBHFHBBACHFDGDCDHDHGBAHCDCBHBEEEEAECBABCBCEDHDFDEDEDEAEADACAHFHFHEDCCABEHEBEHCFBFGFBDHC,False +792,14.0,17.0,13.0,12.0,11.0,16.0,16.0,11.0,DDBDBDAFBDBFAFAGBDEGCCECHCHCGFABGBCFEFECHFBABAEECBDHDGDGHGHGFCFHEAEGDHBCBEFHBGAGACAHAFGFGFDEABFBABGFGFGBHCAEDC,False +793,9.0,19.0,17.0,11.0,13.0,16.0,16.0,13.0,DCGHBFFCGEEBEGGAGFDEEBFGHCHCDFDBCBCFCFCGCGBBBCBCBFHFGCAEABHBABGBDBDFDHAHFGFHBBBGHGHECFDECEGHGHDAAGDBCECDAEAEFEFCFH,False +794,18.0,14.0,23.0,18.0,18.0,15.0,28.0,20.0,GBGBGFGAEFECEBGBECECFGDEDGFCFGGHCHCFGDAHHCHCFCFCGCGCEAHAEABACDBDBAGGCGHAHBDFDHEHEGAGEGEHHDCDGFHBHGHFADECACAEABFCAHGHGBDCDFDFBAGACDGGCDBGGADHDBFHEHEAEGDCEC,False +795,2.0,6.0,5.0,6.0,3.0,1.0,4.0,1.0,GDGECBCHDEDECBBFBCBABDGDGACD,True +796,20.0,15.0,22.0,19.0,22.0,17.0,35.0,28.0,EHGHCDCDAEBCBFBACHCGEFEFEFDFHGHDCGAHDCGCDCACBGEEHEHGGGEHEFEGGAAAAHAFFECCAGHGHGHBACACDCFEAGGGGGGGCGAFCBEHHGDGHGADAHGHBDGAGBCDCABAHDDEEFGGEHHHBBBDBDHDHDHFHEHBCDCGFGECEFFGFGEGHFBEDA,False +797,22.0,14.0,14.0,13.0,13.0,14.0,15.0,9.0,HCHGGBDEFAFAGAHDCGCGCHCGFAADEDEABAGABFEFEFEBDFGABHFDAABCHCFCADBBAGDGDGDCDFEFGBDBDFFGCBCBEBGAAAAAAHEHEBEGCAAAFHECEC,False +798,15.0,14.0,14.0,26.0,14.0,22.0,16.0,23.0,DCGAADDDHDHFFDBGGFGEGBBDHAHFFFFAFCFBDDFEAEDHDHGHGDCHCFAGBDFCFEFGAGHECFCEDAHAGEBFBABDEDADCDHAFCFAFHBDFAFADEGEHEHBHGFGCGHGCDCDBBHHHHBCBCHDEDEDEDHH,False +799,27.0,20.0,19.0,24.0,17.0,17.0,26.0,21.0,GFGDGDCDFGBGBEBGBHHFDADAHEHEBBBHFFGGCADACAGHBHAAFACACHBECEFAHADGDAEHECFABCGCAHBHAHDGEEHFDFHFDFCAHDBDBFEGDGDGHBDBGAGEGBGCCECEBEHAGABADADADECGCGCAFHGHBFACACFDEDEBGACAGHGFDDD,False +800,14.0,22.0,27.0,22.0,29.0,27.0,20.0,20.0,BCBCBCACACAHDBFCHEHEFBGGCGCABBHBEEEBECECBDHDEBAACGCGFGFDFGBCDAHHHHFFEDDDDEFFHFDEGGGHEAEDEGBBDFEADFCGCGCHFHGHGEDCHFFFDFDCHFBCBCBCEEEGACAEHEFGFDFCFBAEHECGDEFGHGAFAEBBBBDCEHFCFEFDCDEDE,False +801,5.0,1.0,4.0,0.0,2.0,1.0,0.0,1.0,HCAEACAFBEACAC,True +802,15.0,14.0,17.0,11.0,11.0,11.0,14.0,5.0,DGAEAFAFCFDADEFEFCACGEHEFGCHABACABHBADDFDFCGEGEAAACHCGDGCGBEBFDCABBBBDBABFGGCCCEGFBBBEDAHCGCGCGCED,False +803,19.0,24.0,22.0,27.0,21.0,24.0,25.0,26.0,HFAFEFEFCCCHCHGDDHEHEDEACCFAFBHDEDEBGCGBFAHAHAHFGDBAGAHBHFEFBFEFABCDHDGACACBGDGHAFBDBCFHFHDHDGDADBCFGGBDACGHGCECEGGAGDGDGEGECADHDABGBDDCECEHFHBGGEGEHBFBDHFACAFBBBBHEEEGCDHGFDFDFEFHDHDCBBBC,False +804,14.0,12.0,12.0,16.0,9.0,14.0,9.0,8.0,ABCBAFDEDFDHDCDBAFCBGBDBEAEGEBCDGAACABDECECEHEAGHGDBHFFFCGDADFFFGFDBDFAHCHCHCHCBADADADABFFGGEF,False +805,10.0,5.0,7.0,4.0,17.0,8.0,9.0,3.0,AAGAGAGAGAHECEFEGEHEBEAEFDADFEEEECEDECHGFEFAFBEDFGBEACBCEFBCCGG,True +806,16.0,25.0,13.0,17.0,23.0,16.0,21.0,18.0,CBGEEFEGBBBCHGHBAAAAGAGEGCHCEDBBBBBHHHHDAFFEEDEDAAADFEBHGHDHEGEGHCECEBBDADGGGGGDGHEHEHEBBBFGFAFDFEFEBEBCFFEBHBECDBDFAFAGHDFDGBHDCFCAABCBHEGDGDEBGCCAF,False +807,3.0,8.0,5.0,8.0,9.0,8.0,9.0,9.0,HFFFBHCHEBEBEBGBDCGCECEFDFBFGAGHHDHFACHDHDEFBGDGEHEADGDBEGG,False +808,18.0,19.0,24.0,19.0,15.0,25.0,23.0,17.0,CDGFCFCAGHEAEADCGEGACBGFGDHEEECACECECFAHAFDCDHDFEBEHDFDFHFGBEBGGGBBBHBHFAEAFGFAHAGAFCGCHCHGHBCDDFDFDGDFBEBEBFAFCFGDCCHGHADCBFBGBGHFCGDGBCAHFDFCFCBCBDAEABADGFGHC,False +809,24.0,16.0,20.0,18.0,20.0,16.0,26.0,18.0,HBEFGCGHAHADGCACAFBFAFCEBGBFDGAGAEHHCDDHDFDHDHDEECGABCBFEAEHDGGGGBABGFEBCAEGBCFCHGHBHBABGBHFEFCCCCAHGEGEFHFDGAEBHDADCGHEAEAEAEAEGEDCDADGDGAGAGAEHDGCCFCFCADBGF,False +810,7.0,10.0,7.0,14.0,17.0,13.0,14.0,8.0,DEAEGEFECACABGEGEAHGHGHAEFEFECHDDFDBDBCBDBDFGCGEBECEDDDADBEFEBDFGBDFHGCFFDGGFEHEHFHBGAGEGF,False +811,11.0,12.0,11.0,18.0,16.0,11.0,15.0,16.0,EBEBABDHDHDHEHGHFAAGGCAFEDDGEFAFHDBDBDHEGGGGBCBCFDDDDDEDBHFEBHCHABEFEFGHECECBFGGGEDHCHCGEGACAEAECHABCHDADFDFHG,False +812,7.0,8.0,5.0,1.0,6.0,6.0,5.0,5.0,HHHHAEACACBEBCCAFAGEFCFDBHBFBFEGAGEGBGFABBE,False +813,7.0,6.0,14.0,17.0,20.0,8.0,11.0,16.0,BCHCAFAGAHCEFEDEHEDCHGHAEDGDFCFHGHGHAEGEGFHBBDFEHEDEDHDEDEBGDDFBEHGABCEDECCCADGHEHEHCHCDCDCDCEEGEFD,True +814,27.0,14.0,15.0,25.0,17.0,16.0,12.0,25.0,HFFCACAHFFCBCFFGDDECEFEHCBCBCDAAAGAHAHDECEFHAHAHDEABBEBCFGBGDEAEAEADGHAHACDHHHBCBEDFFAFHFEEGAAAAAHAHEHEDDDDGAGDHDBDFFAHDBACACAGHHDGBGBEDDBDHFHECGDDDHDH,False +815,9.0,8.0,11.0,6.0,5.0,16.0,9.0,7.0,DDGCCHAAADDFEFBHDFFFDFCFCFCFEBEGGGCFCGHGHEAAAFFHBCBGBEBCBFFFCFCAAGAHHGB,False +816,27.0,23.0,14.0,24.0,26.0,27.0,25.0,22.0,DABHHHEHAHAEFDBAGABDBGHDAAGAGFBAHAHEEDABFGGEEADAFBCACGCGCEFEBEBDFDCDGDEFEHEHFAGAGCBCGCBCBEDAGGBABHDFBFBDEHEHGBFEFEBDFHFHFDEECAFGFGFEADHDAGAGADCDCHFHCEADFDGEAFBFCFDBEEDGAGBEFEHDHGAGHGHFBFBF,False +817,1.0,1.0,2.0,2.0,3.0,7.0,3.0,4.0,FFFFADHDHEHEGCFBGECFHFG,True +818,10.0,14.0,17.0,5.0,12.0,5.0,16.0,9.0,CACBHAACABGDCAEAFGBEHEGCGCGEGEDBGAGFHBGCECEFEGEGBHBFGAGHEABDFDBCBCBHEHGHGBDCACBGBECCCCCH,True +819,20.0,12.0,13.0,11.0,16.0,13.0,21.0,6.0,ADCECACDCEGDFFAFBGBGBGBAAAEBEBGFDADEDAACACDCHHBGGGGGGGEGAAHFEFCGDGBCFABAFEGCDHFECEDEHABCDAHFGAGEGAGAEAGBFBCEFEFE,False +820,24.0,22.0,18.0,21.0,20.0,19.0,14.0,22.0,ECFBHAHAHAEAFBFGDGDCBCGAEAHABCBHFEDEDGBCDCDADABAEAEBHDGDHCBAHFDCDHHBHEGAAFAFCHCDDEHBFBFDGDGHBAFCEDEHFCEHEHEHGCGAHABCBEFHFGCDCDFBFBFAFGBDEDAGCHBEBCBADAGEBEAEAFFH,False +821,24.0,21.0,19.0,22.0,19.0,13.0,20.0,29.0,DAHAHAFEGCDEECECAAEHEFDDDGAGAGAGABHBGEHDHFHEHAHAHAFBHBHCAADCEBBGDECHGFGHGAGEDFDFDHHHCGAEABFDGBECECAHACFCHGFBDHGFDHBHDDDDGGHEHAHBGBGBHEABBFBDBFBDAEEBECCCCCACHCBCHAHDGDB,False +822,16.0,25.0,27.0,23.0,14.0,15.0,16.0,28.0,BHCHCDCAGFGAGBFHEHBABGDHBABFBGBDCHCHCHEHAHEHCHDBGBHACADADAFFHAADACBCBEGEFDFDFDFCHEHDDBDEGEDHHHCDEGHCFGFDEDBBGFGCGHAHBDCECHCABHFCCHCDEDCDCGBBEHDHBGBFEFCACHCBBABCBDGC,False +823,19.0,16.0,17.0,19.0,13.0,21.0,12.0,12.0,AAFGBDHDCDFDEHBBFHFCDCABBFDFGEGEBCHDDDBDGDACAGABEGECECECEFEHCHAGDDHCCDAEFFAFBFBGDAEHHBABAHADABGBFCFGDCDFHFHAGAFAFDFBACACFGFEFECBC,False +824,23.0,14.0,24.0,16.0,17.0,21.0,26.0,11.0,EEEECEBHDFDBDCFAABFDEEGGCGEGFHDGAGBCFCHCFAFAGAGFFBGAFAEABCGAEADADAHBBEHCHCBCBCDCECGHBHAFDEDEAAACACFFECEFFGACCDCFGGCGCGFDFHFGCGCGAEAGGHHFBFDADABBCGGGDGDG,False +825,16.0,23.0,19.0,19.0,25.0,21.0,19.0,16.0,BCECEGEHBGBGDACADFFBABGGEBEGCGAGDBCFCEADAEFEDDCHCDEDGBGCFHFGBEBEBEHCHCEBEDEBFBFEFHFHFGDEAEBGBEDDCBHDFGFCACAGAHBDBDBCCFCFAFDDDADHEEEFHAEAGBGCAHHHEHFGFBFGECHABF,False +826,8.0,5.0,4.0,4.0,6.0,3.0,1.0,4.0,CDGDCFEEEEABABADAHBFBHACAFHEAEAHCBD,False +827,24.0,26.0,18.0,19.0,16.0,34.0,27.0,29.0,CFAFCHHGFDHDBDBDCDCHEFBGBGBHBDADCGCGHGFDFBAHDDAFECBFFFHFAGECAHAEBEAAACGEGHGEABAFGCEAGFFHFGACBGHGAFHCHGHGBFAHGHBHBGBGAGCFBEDHBFBHEHEBFGECEADHFHFHFDABFEFHFEFBFBABDBDFDADGDGCAEAFCFCFCDAGGFGFBHHHHB,False +828,2.0,3.0,1.0,7.0,4.0,6.0,1.0,1.0,ADDDFDFEFEDEBFBEGFDADFHCB,True +829,18.0,8.0,19.0,22.0,14.0,21.0,12.0,12.0,EGEGCHAFEECHDBDBDCFAFEFDFEGEAFCFDADADCHFHEADAEHDHCCFCFDFHFDFDACACACEFDFDGBFBCGEGFGCGCAHADACEDDGCCACHBABDBHAHFFFDDHACBDEAEGGGFD,False +830,14.0,17.0,12.0,13.0,7.0,7.0,14.0,9.0,EGEBHBDCDGECBABADDGCABACFCEBDCCADADFGHGHGFGBGBGHGFDDCDAGABACHHDHDFDCBBGBAAFACEHAGAGBEBHBCBEBF,False +831,13.0,21.0,11.0,11.0,12.0,12.0,12.0,8.0,EAEDGBFBDBCHEBEBEBCHCHAFGGBCDDDCDCBADAFAFABADFCBCGEAEDBAFAEHEHADFHBBEHEFBFGEBHFGBCBCBFGGAGAGBGCGFBDB,False +832,14.0,20.0,21.0,16.0,26.0,24.0,30.0,17.0,BGGGEEEBFFFEFCDGGGGGCGABDFGHCAFFFDFEHDHAGAGAEBEBCBCAGBBDBFBFEEEDDFCCGCGEGBBDBHEDCFCHGFEEBGCFAEGEGECFCGCHEDDCBEDDDHHHCGBGEHEHGDDCGCGBGEGEBEHECGGAEABAFAHAFAFHFHCHCFFFHFBA,False +833,0.0,0.0,2.0,1.0,0.0,7.0,1.0,2.0,GFFCFHDHCFFFF,True +834,15.0,17.0,13.0,12.0,21.0,19.0,18.0,23.0,DEFBAGHEHEABHDFGFHFHCHDHECEHBHDGDGFFCGBFBEEHHCDEFECEDEBCBGEGEGACAGHGHAHDFCBHGFFFFDACEHEBFBHBHGAAEADGGADHHHHGHGFAFCFCGEDFFABABGECACABEBEBEB,False +835,9.0,17.0,15.0,12.0,13.0,15.0,12.0,18.0,AEAFDHGHGFDEDBFBABACCCFCHEHCFEDHFGFDHBHBHEFAACHEDECFCGCBCECEGHBHCABDBEGFDFDBDBEGEFFCCGHAHAHGHDFBBGBGDGHBHBCBFHE,False +836,24.0,27.0,17.0,31.0,24.0,22.0,21.0,23.0,DCGBEBCDEDADFBFEDADADBDCDCDEDFDGBGCGBHBHBHEHEDEDAGBGFDAHGHBCECADBDEDBFFAFAFAFEHHGCGFEFDDGDGFBFGEGEBAHAFDDHFABBBDADAHAGAFFFCGGEECHGAGAEECEBFBCBHHGEFDAAECFADHGHCHBBBBDEDHBBBEHHAHCHCAEFEHADGDC,False +837,8.0,2.0,11.0,12.0,11.0,8.0,3.0,11.0,BHCHEDEHFAFHDHCHFDCDFDFDAAHCFDDADHDECECACECAFEHEGDGEHEDEHFCBCGCAEA,True +838,12.0,19.0,12.0,11.0,20.0,17.0,13.0,16.0,DEFEFEHEFBFECEAEAGBGAFEBEDFGFGAHFHFCGBBBBBBHEFEBHBGBGHCHFBCDFHAACCHEHACDBFEGEDFBCBABHHCHEHACACEDDDDFDGHGHCAGFDFBEEEGEGBA,False +839,1.0,4.0,3.0,4.0,6.0,6.0,4.0,1.0,GBEECAGBFBFBEDCDFDFEEHEDGFGFC,True +840,5.0,4.0,4.0,1.0,6.0,4.0,2.0,2.0,GEBEFEHEAADACACFCFBBHCAGEBEF,True +841,15.0,12.0,13.0,8.0,18.0,15.0,11.0,15.0,FHFHFEAAHFEFCGEHEHCHCBCAEBBBCHAHAEGFGABHBEBEFCBCAHDHBEAFGBHAFEFBGCFEFCDADBDEDEDEGEFEFAACHDHAEACGEGHGCGAGFDC,False +842,17.0,27.0,15.0,15.0,25.0,21.0,18.0,18.0,DBEBDBEEGGGBGEHCACBCBABGEDEDGFAFCCBEDCGGFGBHAHDBBHBHECACEDBDHAAFAEBEDCDCHGBEDECHAFAFECECEFHGHGHBEBGBGBFFFFHFEFHFHEBEGEAEFFAFGBBBFHCHADFDFBABCGAEAGFHDADEBHBE,False +843,20.0,14.0,16.0,25.0,17.0,16.0,12.0,24.0,HBHEDGBFBCADADACHHDHDAEAHDDDDDHFFDHDGCGCBHEGABAHEDEABACDCEFGFHAGGBACGHAFFGDCAAGHDEGEGEDABACABHFDEEBEBDBDBDHDADAHCHBEFEDEDCFCFCHCHFHFHFHFCAEHHFCE,False +844,6.0,6.0,6.0,6.0,7.0,4.0,7.0,2.0,GCECFBDBDBEGHDEAEAFFECECACBGBDADGDGHFABGEGCA,False +845,14.0,10.0,13.0,17.0,13.0,16.0,16.0,22.0,DADFGHGHFHCBGAFEFCFCGDGDEDBABABECDCDBBGAFAGAHDDDDFDGDGDCEGGFHFHCHGAGDHHHFFCGCHHEFEAHHHFHGEGDAHECDCHHAHAEAEBCFHFBFCEHBBEEA,False +846,13.0,21.0,15.0,9.0,8.0,13.0,6.0,10.0,AGBCBCBDGCBFGHABCBCBEBABCGHEHBAFAFDFECDBBAAHBHBHCFCFDBABDCDFFCGHAHBHBEBEBCFCACDEHACEBFDFGFAFAED,False +847,8.0,14.0,10.0,15.0,9.0,10.0,9.0,7.0,DECFAHHBGBCEAACBCBADDEBHDHDEDFFFGEAEBGCGBGDGDFDADBDBDCFCGCBCHABFBDEDGDGBHBFFCFEAEH,False +848,10.0,5.0,6.0,10.0,12.0,17.0,10.0,11.0,DHDEDCDFDFAFAHCFGABAGFCFBGGGGAHCFDFAFEEEEBBABHFAFGFEEHDHECEHFHFEAHAHEDFDFHFDGGGEC,False +849,22.0,14.0,13.0,19.0,14.0,18.0,13.0,19.0,AACFCFBBHBGFDADADAHHCGFBCHHFHBHDGDCAHAHABDEDBDAHAGFGEBEBACHCDEGAFFDGBHFCFDDBABAEEDEGEFEAAGAGABADAHFGFCFAAGCFHEHFGFBFEEDEHEDCDCDCDHHH,False +850,12.0,11.0,24.0,25.0,18.0,37.0,27.0,36.0,GEGEAEAEDHDEDECECGGGEFEFEGCBFBFCFCDCHEHDDGEGFGDHFGEGAGCGFDHCHFHDGCCHEBBDACHCFCHGHCHCHGDFFFFDFHGHDFFFGFGHHHGCDFBFCHHFHDDBACHEEFDCAHDHBHFFFHHCHBHFHDGFGFGBEAHFHFHFCAGGDCBGDGDFFAACDCAFDFDFBHHAHE,False +851,8.0,20.0,9.0,10.0,16.0,10.0,11.0,18.0,GAGAGFFHFHCHGHEFEGADABHBHBFEEEBAHCHCEEHEDCAGGBBDBFGFHFHAHFHBABEHEBFBCHEBBBDDDCDBECEGDBCBEBEBHBGCHEDDHG,False +852,8.0,4.0,3.0,3.0,5.0,4.0,5.0,3.0,CEHEHBGFGBABDCGAGHFDCGAAAAEADAFEFEB,False +853,2.0,2.0,4.0,5.0,2.0,8.0,1.0,9.0,BHFHFHFADCCGFDFDBDEFAHHHHHFHECCFD,True +854,0.0,3.0,1.0,7.0,1.0,4.0,3.0,3.0,BGEDFDHDHGFBDBCGHDFDFD,True +855,13.0,9.0,23.0,8.0,13.0,14.0,12.0,14.0,CFCFCGHEACCCEEEGDHHAHBGBCFCDCDCFFGCAFDCABHCHCDFFCECGCGCAABFDEDACCHHAFAEBEBHGHBHFGEGCGCGAEBCBAGEFEFEFDHAHAH,False +856,10.0,14.0,21.0,25.0,13.0,22.0,18.0,15.0,HDAFAFDFBGDDCEEGEDFGBDBGCCCCDDDGDGHFDGHEFECHCHCFEDBDBACGFBFBFDCGEGCABABDEGCGCECEBAFGHHBDDDHHHGGDCDCACAFBEBECFCFAEHHFFFDGDGHGHDDFDFHFCFCBAF,False +857,5.0,7.0,6.0,6.0,3.0,6.0,3.0,6.0,HBHCDAHAFGBACABHBDBDEFGCHCHCBEFEFGFCFDDBDA,False +858,5.0,6.0,10.0,9.0,8.0,7.0,3.0,10.0,BGCHCHCBDDHDGDGABCBABFECECECDCDFHHCEDDFFFHHEHEAEAFHBEDHCAF,False +859,5.0,3.0,3.0,10.0,1.0,2.0,6.0,6.0,DADADBGHEADDDCDGHGHGCDCDBFAHHFHAGDGB,True +860,23.0,20.0,27.0,31.0,27.0,21.0,22.0,20.0,GBHCDCFCFDEDHCHGEFEFECCCCCADABAHFHFHFDGDAEEHACDDGBADFDEECFAFCFEGCGEEHFAFEFBABCDADEDEHBHGHBBAECECGBHAGFHHBGECCDEDBFHCACGCDAGAGADDDDDCDGFCFCEEEDEBHGHGHGCGCBDADHBGDDEDABABAEDEBFCDEBABGBDAFAFGEGH,False +861,7.0,7.0,14.0,4.0,11.0,5.0,11.0,5.0,GCGFGBGCCCGFAAEAECECECGBABHHCAEAHAEFEBEHDCDCGFGFBCGCGCDBEEHDGECB,True +862,12.0,3.0,10.0,5.0,8.0,8.0,5.0,6.0,GFCAHAHAGACCEHDBBAAAHADECEDECGCBCECFCFHFHAGGEDEFFCFAEAFAD,False +863,24.0,14.0,29.0,24.0,18.0,18.0,12.0,25.0,ACACHBEBEDABHBGCDCFCEDFCGCACGFADCCCCBCDEAEBDHEEGAGCDFDFDFGEHAHFEEAEHCCFHFEFCHCHDAAHGDCDAHFHEHDHDHAHADEBEBEGADAHEBFHFHACGFGCGCBCDCDCACFCFABCBADDBCBHHDHGAAHAHFFDHDEDA,False +864,12.0,14.0,8.0,8.0,15.0,8.0,10.0,15.0,EBEBGHCABAFAFDFDADGBHCEBGBGBCFCAEEDHCHGHBHDGDHEHEHEHCFGFBEEHAAAHGHGEGBFCABHFHEEBADCDABEBEA,False +865,3.0,2.0,2.0,3.0,0.0,3.0,0.0,4.0,BHDHBCFDFCAHAHAFD,True +866,5.0,8.0,8.0,6.0,13.0,7.0,15.0,8.0,FHCDEDADBEBGAGCCCEBGGFGEGEGAGAGHDHGBEHEDGAGEBECHCGFEEHEHGGFBFBFCFHEBCD,False +867,15.0,8.0,10.0,4.0,10.0,7.0,12.0,11.0,GCHHEHGBDBCGCBCFEAAHAHADFCFCFGAGAFBGAHAEGFBECEABHCHAEAEHGHGFBDCHGEGEGDACABAEA,False +868,13.0,19.0,24.0,20.0,14.0,16.0,12.0,20.0,HCHAHAGDDCDBGGHGHGCEEAEGFBFDEAEFCFHDHGFAFGEHDBDBDCECDFECHCDCFCHCHBBBBGAFDCACEDBFFAFAFBEHCACDHBCBCBHBCADDDBDHDHCHCBABHHEFGAECGCGCBDBDCFHFEE,False +869,11.0,10.0,12.0,15.0,14.0,12.0,10.0,5.0,CBGECDGDGDADCGAHDBDFFFFEAHFEFDBDGDGECECDDFDADBEACGFEBEBECCCGCBCBEAEAFGBAAAEDEGHHDHCFAFEFB,False +870,8.0,16.0,15.0,5.0,12.0,6.0,10.0,5.0,GEGAAFBCBCEGAAEBEBEFHHCBAAGACBBBBEBCGCGCECECBABCFCGCFEDEHCCDGBGFDFDEHCHBBGBDE,True +871,7.0,10.0,13.0,4.0,10.0,7.0,7.0,8.0,GAAHGCBADEDHDCCCACAFHEBBBBBCBEGEGFCHCBEGEGEHDHCFFABCFCFHGHABFECECE,False +872,5.0,6.0,11.0,4.0,5.0,6.0,7.0,6.0,FCCCACBDAFCCCFGBBHBGAGEGDGCGHGHDHDEBHCCFCBAEFEFEHA,False +873,6.0,3.0,2.0,8.0,3.0,5.0,4.0,1.0,AADDDCDCGGFFEBADADADEDGBGFFEFAHB,True +874,16.0,16.0,9.0,13.0,16.0,16.0,11.0,18.0,DGAGHBHCEFGDAAEAFAFBBDFHEDEDHBHGHGHDDEDFCFCAAADAHFBCBCGEHEBFDFAFCFAFAFBECCBEDHHEHEGBGCDFGFHHHBHBEBEBHAEADBEBAAGEGHF,False +875,10.0,10.0,11.0,9.0,10.0,8.0,13.0,16.0,AFADADEDEFHCHCFGBGEHDFGHCHEGBGHFABHEACHBHBHBHGDGBAAAHAHCHCGGGCGEDEBCDDGBGAECEFFFBCHCHDE,False +876,10.0,18.0,8.0,11.0,7.0,15.0,11.0,9.0,FCHDHBFBGCDHAGCCHDHAGFFHBHEFAFAFDBBBDBDEACGGGBGFECECACHDBABFBDBDGEADADFFFGEGEBBBFBFBGBFAH,False +877,4.0,5.0,14.0,13.0,6.0,8.0,11.0,11.0,ACACGHADGCECGGGDCCCFCFBFDFDHDHDADHDHFFBHGHCHCGCDCDHDEEBGFDEHBHGEEBDFCCGG,True +878,22.0,17.0,15.0,16.0,16.0,19.0,13.0,15.0,CCFCHHDBEGEGDCFHFBAGFEDDFDCECEGBCBABADADBGGDBACAFAEABHHHFHCHDBFBDBDBEHHCHCHEEGFGFHAEAEAEADFEAABCFCEAHFGAAADFDFBFBEGCGCDAFAFAEDGBHBGFA,False +879,11.0,12.0,5.0,10.0,10.0,9.0,11.0,9.0,BCBCEAFGFGHBHBHDDFEFGBGHGFBDCAAGEHDBDGHGHFADAEEFEDEDEAHABABACAGHEDFAGEDBGBCBF,False +880,22.0,23.0,20.0,22.0,17.0,22.0,27.0,22.0,AFEFEHDHDHDBFBGBGEGBGFGFGEHEABABGGGABAHDHEBCGCGCFCDBDFEEAAAFDCBFHGHBCGAEDFDFDBCECFBAGAGAFEHGGCGDBBCCGBDDCDBDCFCAHDBAFFHCHDHFHCEEDHDHBHCCBFBAEAEAFGDCDHAHFHEHADAGAGAFBGCGHGFBEGG,False +881,26.0,17.0,21.0,13.0,20.0,12.0,23.0,19.0,BAEAGCGHGAEADABEEEGAAHHDDBDFGAGACCHHEHEBFBHEEEDFGFEAGHCCACGEFEDCGCHCGFHHBHBGBCCCDCGBGBABABFDDHEAEFEGGGGEHAHACACDGBGBGBEAFACEHFAAAHGHGDCCECFCBCBHDAAAFAD,False +882,1.0,1.0,3.0,2.0,1.0,1.0,0.0,5.0,DHHFADEBCHCHCH,True +883,7.0,3.0,8.0,7.0,4.0,4.0,4.0,4.0,GDEDCFHFHDHDEGEACDCABBGFACACGCFCDADBCAEAH,False +884,21.0,12.0,14.0,11.0,9.0,9.0,15.0,13.0,EHEAEGDDAGGBGFFAGHDHDCDCDCFCGGGGGAAEGCHEDEAEFHFAFGCBHBCCCCADBBAGAGHBCACAHAHBFEDBGBCBEDDHHABAFAHAHFBCAAAA,False +885,16.0,26.0,24.0,20.0,25.0,24.0,19.0,20.0,DFDGGAEAEAEDHGHGCCABBEECFCFGBGBDCGFFDBDECEADADHGHFDBDCEEBCGCGAFBFBCHDFDFEFEFHFHFHBHFEFHCHCBAFDFBFCAGAECBBBBEAEBGCECFHEHDCCEGBGBGFGFHHEHCHBDACECABABDBHAEDDCGGBBEFDFDCBAEHEHECG,False +886,13.0,28.0,17.0,8.0,23.0,25.0,17.0,16.0,GFFBFBHCFBBBCGCGEEBCBABFDEBGBGCACEHFHFHBADDCGEGEBHAAACFCEHBHBDAEFFFFDFDFEFEFECEBBBHFGBBHBEGCBEAEDCHEEEFBGHGECEHFHBABFCFCFCGCEAGDGAGAFBGGAFHHHBEBEBF,False +887,12.0,16.0,10.0,18.0,15.0,11.0,14.0,8.0,EEHEFGDCAFDGDCBFBFGFBEAFBBBAGFGBGCHCHCAGADCFCDBDEHEAEDGDBHBFGEBEBDBDADCDHDEABDDEDFCAGDGAGAFDEAGCGBEBEHEH,False +888,18.0,13.0,17.0,15.0,11.0,10.0,18.0,15.0,DEGEDEFAHAHAHGHGHGCGCFDDDADFCBGDGDCBABCBEACAGAGCEDBABDHFGAGAGDEEHAFCDCBCACBEBHCGBFAHAHCDFHBGBGHFHGHFBACEGEGCHAECFCDAD,False +889,22.0,5.0,11.0,9.0,14.0,19.0,10.0,13.0,HEHFADEFGFCEHEFDFHFAFGGGGAGAFADGDFAEAHBCECEDFCFHFCFDFDAACACABBFGCHEAAABCDHEAEABFHFHEGEFHAAAAACAGDHCHEFE,False +890,27.0,36.0,17.0,27.0,26.0,14.0,25.0,25.0,FHDGFABEECADAEBECEABAGHECDCDADGDADADEHEHGHBFBCBGDEEEEEBABABHBHAGCEDEDEHAHAGGCDCDHBABHBCACAGFCFGHHFDFDGBGHGAGCGFFBHADFCECEHBDBGBABACAHEBBHGHEHBBEDEFEBGBDBCGEDBBBBBEBDHDBAHGFGAEBHAADGHGDABFCFDAGBGDHD,False +891,18.0,15.0,22.0,14.0,25.0,27.0,18.0,19.0,FHFHEHAHCFEDCDHFFFHCCCCCCFAFGEAHAFGGEGEGEGFGFAEHDCDFHGAGEBHFHCHBHBEDHDCFCACGBFCDDEHBCEGAFABEBFDEGAFDCACFEFEDEAAGAGAGCBCDFEHAHEHBCBCBFBEEFEHGGGCEFEFEBEAFFBDADB,False +892,15.0,15.0,17.0,14.0,25.0,21.0,15.0,21.0,EGAHHHDHDFEAEDEGGGGAGFHFAFEEEHHBCBGHGBGDFAAEAECEFEDDBFCFCAGFFHFHFHBCFCDHFHCHADBHFGFGBEBHHEEDDCDGBCEEEBGBHEHEDEAFCBCECEBGAAAEDCDCACABEHHCFEFCFBF,False +893,5.0,2.0,1.0,1.0,3.0,2.0,5.0,2.0,BHAHAEEEGFGFACGBDAGAG,True +894,1.0,2.0,2.0,3.0,4.0,6.0,4.0,3.0,FCFCHHEFEFGGGGHDBEBFAFDDE,True +895,12.0,25.0,10.0,17.0,18.0,19.0,18.0,17.0,CECBHFGFGEBBHFEFDBDBABDGAGAEABCBGAGAHCEEHEHEHDDCDBFHFHEDFCFBFBFAGGGGGFGEHBBBHDHBHDEBEFGDCBBBDBGCAHHEGBGBCDFDEEEDEACAFFGBBHFHFDFAFHGBADED,False +896,16.0,8.0,11.0,13.0,10.0,11.0,7.0,7.0,GEDEHEHBBDADFDADCDCAAAHFHFGFECACAEDCDGAEAEBBCBGEACAHDBDEGFHFBCDCFAADACBCHFAFAFEGGDF,False +897,11.0,6.0,9.0,7.0,10.0,14.0,15.0,10.0,HDBFBGCFCGCGBGDEDGHAHGHAAFHFCGBGCAHHGFCFAFEBGHGBDCHCHDEEFEFEAEAEFEFGDGFAFACGEFDAGA,False +898,17.0,13.0,21.0,30.0,28.0,20.0,12.0,19.0,EDDBGCECEDBCBCDHGFECBGBEHHHEHFHDGDHHAFAHCHDBEFDADCDHEEEHEGDGDGFEDCACEDEAEAEFDFDFDADCCACFEFCFEFCBBHCCFEEDHDFGEGAFCFCACABABCGDEDAHEDDDDGDGFHDHDABFCFDFAHEEBEBEHEAA,False +899,3.0,3.0,2.0,3.0,3.0,3.0,8.0,3.0,BCEFGHGHGAGBGBGDFDCHEGEFAADG,False +900,16.0,24.0,17.0,15.0,11.0,13.0,13.0,18.0,DDCDADAECDHHHCHADDHCHCBCADAECGHGEAHFHGBBHDADAEHHFHGACACFCFBEBEDCGCGBBBBGEFFHFBBGCGBABABAHFEFBBECCHGFDFBFAFAHBBEBEACDGDGCBHBGBDB,False +901,25.0,30.0,29.0,16.0,34.0,19.0,24.0,19.0,FFGCECEBBBCDCBFEEEECGCABAFEFGHBDAACECGHDFCHBFBGGGBGHCHCBCECBGBEFDHBHBHCHAHAGABABGEGFCFBEGEBBCBCDHHHCHCHDBDCFCAEDHGAGEBEGEBEDEFFDBDEFBCEFEAGGFGEGFBFHHACACAEAEAEBEHEBAGAEAECGABADDDAECECFAAEDDAGCECBG,False +902,24.0,23.0,19.0,24.0,26.0,27.0,19.0,14.0,FAAAEACAEEEGEDAHEBADAGGHEDCABGFFDFDFEBEBEDEDGAHFDGBCBFDFGECFBFGFBFEFCFEDADBEFEFACACACAHADBBBEHAHBGBFAGBEEGGFGCGCFAFDFEBHGCAAGDGFHFCFCHCDCBFBGBCBEHFHCHCBEDGDACAEBDBHFHEDDDDDEAED,False +903,29.0,29.0,25.0,18.0,19.0,26.0,26.0,24.0,GABBEDADAGFHBHFHGCBCBDADGBGDGHEDBGBGDAEBEAGFGACEBEDADFFFBBBCFCGAFAHEHEHGBAAAAAAGGCCHBGBABHEEFHFHAHFBGCHDHFEBEGEAEDFGCHBHACADBHGDGCEDFFHFEFBCBABAHAEAGGFFCFAHADGDGCBCBCGCGCBCBCFHEHDFFEFHFCFABCHCDCAC,False +904,6.0,3.0,10.0,6.0,5.0,4.0,4.0,1.0,ACGCFCACDCHCDDDEDCGGEFBCBCBFGFEEAEDCAAA,True +905,3.0,18.0,9.0,11.0,14.0,16.0,4.0,13.0,DCFBBCBEBDBFFEFDCGHBHGDCFBFDEHEFBHBFEFHFHFGCAEHFAFBEHEHEHCACHGFDCBEFEHEBDBDBHBDEDEDBCBFB,True +906,16.0,25.0,37.0,22.0,24.0,10.0,28.0,28.0,DFDCDCEAEHCHEACBHBGBHCCGCECADDDDDDCHHHAHCCCGDECECEBECHCFCFBHBACGCBABCBHGEBBBHGHGBCBCDEEAAGAGDHFCCEDEDGDGDGBGHHDFFGEEBFAGHGFCBBGEHHBCBDBABCEAGACACGBEHEHCFDHAHEGGGHGHGACEDECHCGCGCDHFHBEGEDBCGC,False +907,25.0,18.0,28.0,21.0,19.0,32.0,30.0,20.0,GCGCEBHGCGCEDDHHGCCCCGHGHDHEHACGGGBGFGBEACGHGCFDFDCCCHCFDFAFAEAGABACAGACEBHBFGFBFBDHCFAFGFACAGDEHCDBGHAHBBDFDFCFAEBDCGFAHGHGFGFGBADFEFHBDADABBEAFHDDFDFGBGDEDEFAFEFEFGFAFDFEFCACHFHBEEECGCGCAAEAC,False +908,28.0,27.0,16.0,15.0,23.0,29.0,25.0,24.0,FAFEFGFBABHFFBHDCCGAABEBCACAEFFCFAGAEEGEGFGFDFHFHBAGFGBGDHBHBHBCGEGFAAHAHAHAEGEBEAHABCBDFGFGEGBFBHBDBFBFGFGHGHBEBEBDGHGFAFCHADEEECECFBACCBCDDHGGEHEGCAAFAFBDHHHDHDFDADGFAAEAFABEECGHHDBEACB,False +909,22.0,23.0,20.0,21.0,31.0,23.0,29.0,28.0,EAGGGDCHHHHCDDEDBCHAEDGBGAGADBHAFFHGBGBDEGEGHGAGDBEGAGCCHFHFGEGHHEAEBDDDDADHCBBBCACFCGAGECEAEFEGEDDAAEFEHBHBGBFCFCHGBBDBFBFDEAEAEFCDDEGFGFCECAGHGFGFEHHDAFHFHGHGHFHFEEEHAFBBBEAECGCBCBCEEAHACBFDFEHEH,False +910,35.0,20.0,17.0,22.0,15.0,17.0,23.0,20.0,BABABADGDFFFFFADHEEAEHCBGBGDGEGCACHEFAAHAHAHBHGHBABCBCGCFDFAFCFCEAEHEDGFGBAAADBGADADBDBECGGFCBDBHCAADAHAGADCGFGFGCGCEDAAEAHDEDBAGFGBADDDCDHHHCHAHDEAHGFAEAFBDHAGAEHBBGCGA,False +911,20.0,22.0,16.0,16.0,19.0,34.0,24.0,21.0,HHBBFFAHAHEFAFCDBDBDGCEEBFBDCCBCHDFAFDBDBFCFAHGEDBGFFFDFHACEDGDBFBFCECHCHBFAFADAFFFFFFFGFBHGHGHGHAFABACHCFGGGAFHFHGGGGFAFEEGHGEEEGECDGECBCBHDGDGHEHDBAGEBEAEABABFEGACHEBGFAF,False +912,14.0,22.0,22.0,16.0,10.0,16.0,13.0,11.0,GABHDHAHACDCBFFFECHFHEBEGABCEHEBBFBACHCHCACABEFFDBACDHFADAFBFBGGCGCGCHFBFCGDFAFGBCBCBDHDGDCBCBCGDGCGAGABCBCACEDFDEEFBBDDDEDB,False +913,20.0,27.0,29.0,23.0,22.0,31.0,29.0,18.0,GFGEECFDFAGEFHFACDEGCGCGHGHDHDCGCFDBAGAGAGDGHFDFBFGFGAGHDAGAFABDCFFECECEFFDCDCBCGDBABFFHFDDDGACHHDBEBEBFCEEBEHAHECBABGGAGDHDCEEGFCFBDECACAFHFAFACBEAGGGBGBCBHFCFCFCFCHDFAEBBBHBEBECFCHEEGBGBFCDBDBDBHGC,False +914,12.0,9.0,6.0,2.0,6.0,6.0,2.0,13.0,BFBHEHEHBADCHBAGFHFEBHAAACABHBHAAACECBBACGCHFHAHAHEHEFFD,True +915,10.0,12.0,24.0,13.0,16.0,14.0,13.0,16.0,CEBDBDBDCDCDCDBDAHHBFBFCFGFGEDFHCBCFGECFCEBEBHBCCFCFDFEHAFBHAHAHFCACHCECEHACBCHCFEDEAGACDCHCGAHCDEGGHEEFHAGGGECEGEHDGG,False +916,4.0,4.0,9.0,4.0,6.0,12.0,3.0,4.0,CECDADFBACFCFDFBFGFCFGHCCGBEHEHEHEFFCACBEFFFAD,True +917,15.0,18.0,12.0,11.0,16.0,11.0,18.0,15.0,AEAEAEAEAHAHAGEEFHGHBHBEDABABADHGFGDHBCDDFHGBEFFFAFGGHBDFCBEHECECGFHBHEEGDBEGEBBGDCDHDCACGFGHGCABABHFACCCCBGBGBGDGBE,False +918,14.0,16.0,12.0,30.0,16.0,18.0,12.0,16.0,DHDAEBFADADADADADGDFAFHFHDEFGBGBGBGFHCGEHECEAACACGCDDDFEBEBHBFAFHCDDDDFCFDFGHCFDHEFEFDCHBBBHAEDEDBAAHCEFDCDBDFDBEEDBDHEBDHDGFHDHEGGGCB,False +919,5.0,11.0,3.0,9.0,10.0,8.0,8.0,5.0,BFBHEEEBCBHEHGAGAGDDBDEEEHABFCFBAGDCDGDBDGAFEFEFDBDGGFBFBHE,False +920,5.0,0.0,5.0,4.0,1.0,1.0,4.0,2.0,CGAAFADHDCACGCECGDGDHA,True +921,24.0,17.0,18.0,26.0,23.0,31.0,24.0,25.0,EDEDCDADFGBABAGGFCFDFEGCGBHHECEADGDEDFDFDBEGEFCAGFEFEFDHEADHCHAHFHFHEGEDDDDBGEGEFBCDCEAAHDBAGHDHFGGHEHAHAHAHFHFDFBGBHCGAGFEFEFADACAFEBGCCDBEBADAFBGCFAFCHCHAFEFGCGBGCAFABCDAFBFBHDHFHEGDGHFH,False +922,12.0,3.0,17.0,8.0,6.0,8.0,19.0,16.0,GDFCHCHAADGBHCHAFEHCHCBGBCHFACAFADGGGGGGCGCAADHEHECEAEDDCCEGFGFGAGAHHGHGCDADCCHHGCGFHFHGC,True +923,13.0,7.0,15.0,17.0,15.0,11.0,14.0,5.0,GDDDHCCBCDADAEABADADGHFDCCACAEAGGDEEEDFHFBDGCHBFBFDGGBCDDDFCFCFEEGCFEFADADACAGGGGEGCCAEBEHEGEFECE,False +924,19.0,22.0,14.0,20.0,28.0,12.0,19.0,18.0,CGCDHBFBHGEBEADBDGDGDCBCDCHCEBHGEGEHEGDFFCEAEDGCGEGFDEEEEEBABCBCBCBCBGFDFAEAFDHDHEHFDAAHHHHEAEADAFEFEDBABDHEFEAGCBBFHDHBHBGBADHEEDBDEGBAEAGGCGHBEGGAAAEA,False +925,20.0,23.0,18.0,19.0,19.0,27.0,21.0,22.0,FEHEHEGDGCBDBHBEBCAGACHFEFHAHADAFGBGFFEGECEHDGDAHAHEDCCEAGFDFEGCCBGBFBFHDADCBCBFBCCHBHAHBDCECDFHFGFADCFFFFBFADBGGHADFDBBCBGHHHEHEHBAEAEFGBHBHGAGEFEFGFGFDCDFBFACAGAEADGDB,False +926,8.0,4.0,5.0,5.0,6.0,5.0,4.0,8.0,FGFDECECEADFBFBHEHAHADAHAEACGDADHHHBHFACBEGCG,False +927,4.0,9.0,2.0,4.0,9.0,4.0,11.0,2.0,GHGBGDGBGBEAGFGBBBBDDEBGFGEGEDECEAEAGBFCEHFAE,True +928,19.0,13.0,20.0,26.0,25.0,21.0,11.0,20.0,DDDFAGCFCHADFCCECECFBEHDBEBEDEHEHCFAEAEAEFDFBFADAEAEAEADHDFDFGBGBADEDBHCGCFCBEEAEHECFHAGACCCDDEDHHHHAHDDDACGHBACFCFGDEFEBHFHFCDDDHDACECBDHGHEEFGBGFGFEDHFBA,False +929,31.0,26.0,25.0,22.0,30.0,19.0,16.0,16.0,GADBEEEAEAHACCCCFGFEHBGBGCFCFDDADGBAAAFEFAABEHADFDFACAHBHGEFBAAACFCGABEGFABGFGEGFBFBEBFDEDEHGFEECHAHADADADCHEHEBEDABHBEACADBDBDGDGDCDCACHEHGCEHDCEABCFAEDFDGCEBFBAAEHEDEBCBCBCBCBEEAEBCHC,False +930,5.0,6.0,16.0,9.0,2.0,8.0,6.0,8.0,FCFCBBGDGDBABHCHCGEBEDDGACFCFCFCHCGCABHCCCCHFHCAGFHHCAFDDDDD,True +931,13.0,10.0,13.0,5.0,17.0,8.0,8.0,11.0,AEAEAHAEECBHBHGHAEBFCEEAEBEGCHBFBGEGFACADAEGEDBFCCHHBHBHFHCGEGHDDCDCACAEAFBCGCFEFECEA,False +932,13.0,15.0,7.0,16.0,20.0,10.0,5.0,18.0,AEABBCHEBEHEFEDEAFBHBADFHHDBDEHBABABABACDCFEFHFEGGACEDEHEBBAFGHCEDEDBGCHHDBDBEHCHDADGDEDEDHFEEEAHAHFHFHD,False +933,4.0,6.0,3.0,4.0,2.0,6.0,4.0,5.0,AGAGAHBEEDCGBGBCBDFDFDHHAFBFHFCBHF,False +934,5.0,12.0,3.0,2.0,5.0,4.0,9.0,11.0,CEDBABACFFGFAEAGCGBGHGHBHGHEBBHBHGDFHHHHBEBEAGBBBGH,True +935,8.0,6.0,1.0,11.0,7.0,1.0,14.0,7.0,GEBHGHGDBAEEDAGGEGDGBGBHHHHDDAAAAGDGDGDADABCEGEHEDDFGGB,True +936,12.0,13.0,17.0,16.0,15.0,22.0,16.0,19.0,HHEDDDDGDGAFACACHCFEEECACADBGHGFFFFFFEHEHCAGBDFEFDFEFEHEFFBBABFCHEGFGDHBCBCBEEAHCCECDDBFBHCHFHFHDEDGGGDGBGHCBGAFDGDGCAHBCCHGHFHFAA,False +937,3.0,4.0,1.0,4.0,2.0,0.0,0.0,2.0,ADDEDEHBHBACADBB,True +938,5.0,10.0,7.0,7.0,2.0,7.0,13.0,13.0,FCGGGHHAFEFBFBGBABAEGGGGCFCFHBABHHDHDHFHACDBBGHGDGDHCBDHCHGBGDHC,True +939,0.0,2.0,2.0,0.0,2.0,1.0,2.0,1.0,CGEGEBFBHC,True +940,15.0,12.0,17.0,12.0,18.0,16.0,21.0,10.0,DADACBCEGEGCCAHFCDCDAEACDCFGDAEBEBEACABEGGGABACDFDCGGFDDHCGFGEGBCBDEDGHGFEFBFGGCBCEEFAFGFHFAFHGHGCEFEBHBHGEGEGEFAFAHACBHE,False +941,21.0,9.0,18.0,19.0,23.0,21.0,20.0,26.0,EGEDHBHBHGHGHCEAAGBHBDDDGGGDGFGFEFGFGADHEFEAEAFAHAEAHBFECDCAAGDFAFHEHCCDCEFHFHFAEAHACFCFCHCECEHDDGDHDHDADEBHFEGAAEAFBHCCEGGDEDBCHADAHFBFCFCGGEDECFHGAGHECEHFH,False +942,23.0,23.0,25.0,23.0,16.0,18.0,18.0,24.0,CAHDBDHDEGCADHGHGHGHFCDCHCDFGEDEDHDHBHFDFEEADAEABFFGFGACFBBCFCBBFAHCHCEEDCCFHACACABHBFFFDFECACHHEGDGDEDBHBCBHBHADABHBHBCGHACBCBEBABCGEEFEAEAGGCDDDDAGAGAHBHDGBCFGFDCAGACAB,False +943,9.0,5.0,6.0,3.0,2.0,3.0,4.0,6.0,DBDHCFFHCEAEGBGBGAHCHBBAGFCAHAHACADACA,True +944,1.0,5.0,5.0,2.0,2.0,3.0,5.0,5.0,EGGDGHCBBAEGHGCFCFBHBHBHCFCD,True +945,23.0,12.0,17.0,23.0,21.0,25.0,31.0,23.0,AHAHBHBHCHCEDDFCACDCDFGFBHBCCGFGHGAAHDEEGECFAHAHFHDHEADFGCGCGFGEADBEAEBEDDBCBHAAFAFAFDGDHABAEHDHGEEEHDADGFGHGFEFGFCFAFHFEFADGGEGEGECFDHCHDFGHGDGCAAGAGEGFDBGCEBGBGDEDHFFCFGAGDG,False +946,7.0,6.0,9.0,5.0,3.0,13.0,9.0,7.0,BEBECFHFHAHGCAABCCFGBGFFCFGFBFDFGGAGHGFFFFDBCGHHCHCDDADAEAC,False +947,12.0,14.0,22.0,9.0,8.0,15.0,19.0,16.0,GGGGGADFDBBBCHGACAHBFGHGHGFGCCFDACHGHEFFBCBGEGDGFHHHBHDGDCCCCGBFHACACECDCFGBHBHBCEFECHCBCBCHGFGDAAAADAEEFCFCACFFEHB,False +948,23.0,29.0,24.0,18.0,9.0,25.0,25.0,32.0,BBBHGFAEAEBEBCFCFAFAFCFDFBHBGCHFAEGDACAGBHCHFDBCBGGCCBBHHABDCFGHBDCDBDGFBCAFAHHGHFHEHACEGDABGBGHABABGHHHFBFCFHFABAEAGACBCFHHBABCBCBCACFCHGHCHBGBHDDFGAAFFFEDDDGDHDHGHGHGHDHGHGHDCDCGFGFEA,False +949,7.0,6.0,5.0,7.0,7.0,6.0,6.0,12.0,HHCHADDCGBGFFHDHBBCHCHBFADAEAGAFAEAHBHEEEEHHHBGDGEGCDFDF,False +950,24.0,23.0,22.0,11.0,20.0,30.0,30.0,14.0,EHFBFBFBCCFCAAACEGBFAEEBHCHFHEAEAGBGHGHGCGCFEFAFBEAGAEBGDGCGHGHBBGBGBFBFDFECAGGFEBEGCAEBEDGHAFBHBFBDGDGFGDACCGCECACAGFCECHDFBCGCGFFFGFGCBCGABADFBHGGFGDHDEFBHCAAAAAAFFFFFDEEAE,False +951,16.0,19.0,15.0,15.0,20.0,28.0,15.0,17.0,DGGFECEHGHFHCBCEHGDGCBCGCEEFAFAFAHEHFAABHEGDGAGBGEEBHDHBBCBCHFBDBDBHEDFCAEAFFFDFDFAGBCBDECFFFEFDFBFGFGEECECEFEFEDHGCDAHAEABBDGFBFHHBHDAFHFCFAFABA,False +952,9.0,0.0,6.0,3.0,8.0,5.0,2.0,3.0,EFACCCFAAAAHFFFDGAAEAEHGHECECEDECEAD,True +953,2.0,1.0,1.0,1.0,6.0,2.0,3.0,1.0,ECEHDAAGBGEEEEFGF,True +954,11.0,9.0,7.0,13.0,13.0,4.0,8.0,8.0,CADHDHDFDABBEACAFDBBHFHGAGECBGEGEGEBEHEDEAHBGDADADADFDEBEDDCAABHEHCGEGECC,False +955,17.0,19.0,17.0,18.0,12.0,19.0,16.0,32.0,GFGFAAGFGAHADGGHGEBABFEDBHBDFHHHHBGBHDHDEAACBFBFBEAEHCDDGDFHHEDGHGBGBGADHFHDHCCGAEACDCDCAHAHFHFHFHDBDADHCCCHBACACBHFHFEFECACGEBBFDHCHDHBHEFGCECHFFBHBH,False +956,21.0,23.0,17.0,24.0,20.0,16.0,15.0,22.0,DADEHFHDCBCBCAHGBGFDFDGBAFDFDHHFDBDBACACFEHEAEAHAEEBAGCHCFCFAHAGDGDADADHHGHGECCFCFGFCHAHGDGBCCHADBDEAHGCFBHBHBHEEEEEHEBEAEGDBBFBHHCDCEBBBDBDBAADGFABADFEEGEDDB,False +957,10.0,10.0,8.0,10.0,12.0,10.0,10.0,2.0,FGFBFDFCGGFGABBBDGAAAFHFDGDBDGDEDECECECECGBAEHECGDACEBGBDFCAEAFFEDEBABAE,False 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For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/src/main/scala/org/xcit/nback/markov/models/State.scala b/src/main/scala/org/xcit/nback/markov/models/State.scala deleted file mode 100644 index fbbd844..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/State.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * A Single state with a label in Markov chain - * @param label A simple string label, representing the state and node - */ -class State(val label: String) { - - /** - * Keep track of transitions from this state to other states. - */ - val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() -} diff --git a/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/src/main/scala/org/xcit/nback/markov/models/Transition.scala deleted file mode 100644 index bc20a9e..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/Transition.scala +++ /dev/null @@ -1,8 +0,0 @@ -package org.xcit.nback.markov.models - -/** - * A Single transition in Markov chain graph. It is stored in "from" node. - * @param to the ending node of the edge - * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). - */ -case class Transition(to: State, probability: Double = 0.0) diff --git a/src/test/scala/ThreeBackBenchmark.scala b/src/test/scala/ThreeBackBenchmark.scala deleted file mode 100644 index 0c7dad9..0000000 --- a/src/test/scala/ThreeBackBenchmark.scala +++ /dev/null @@ -1,7 +0,0 @@ - -/** - * TODO Benchmark 3-back simple sequence generator - */ -class ThreeBackBenchmark { - -} diff --git a/tests/benchmark_diagrams.py b/tests/benchmark_diagrams.py new file mode 100644 index 0000000..8fa448e --- /dev/null +++ b/tests/benchmark_diagrams.py @@ -0,0 +1,159 @@ +import pandas as pd +import numpy as np +from matplotlib import pyplot as plt + +import benchmarks.common as common + + +def tlratio(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2,ignore_index=True) + stats = [] + for trials in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == trials) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == trials) + targets2 = data[alg2].targets if alg2.shape[0] > 0 else np.nan + targets4 = data[alg4].targets if alg4.shape[0] > 0 else np.nan + lures2 = data[alg2].lures if alg2.shape[0] > 0 else np.nan + lures4 = data[alg4].lures if alg4.shape[0] > 0 else np.nan + stats.append([trials, (targets2/lures2).mean(), (targets4/lures4).mean()]) + stats = pd.DataFrame(stats, columns=['trials', 'tl2', 'tl4']) #.dropna(subset=['skewness']) + + plt.style.use('ggplot') + + plt.ylim(bottom=0, top=30) + plt.scatter(stats.trials, stats.tl2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl2[idx], 1)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.tl4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl4[idx], 2)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('T:L Ratio') + plt.ylabel('T:L Ratio') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_tlratio.png', bbox_inches='tight') + plt.show() + + +def time_per_trial(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for t in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == t) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == t) + time2 = data[alg2].time.mean() * 1000 if alg2.shape[0] > 0 else np.nan + time4 = data[alg4].time.mean() * 1000 if alg4.shape[0] > 0 else np.nan + stats.append([t, time2, time4]) + stats = pd.DataFrame(stats, columns=['trials', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.trials, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time2[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time4[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2v4_time_trials.png', bbox_inches='tight') + plt.show() + +def time_profiles(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 8): + alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + time2 = data[alg2].time.mean() * 1000 + time4 = data[alg4].time.mean() * 1000 + stats.append([ni, time2, time4]) + stats = pd.DataFrame(stats, columns=['n', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.n, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.time2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + plt.scatter(stats.n, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.time4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_time_n.png', bbox_inches='tight') + plt.show() + +def skewness(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 9): + all_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + skewed_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) & data.skewed + all_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + skewed_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) & data.skewed + num_of_sequences2 = data[all_alg2].shape[0] + skewed_sequences2 = data[skewed_alg2].shape[0] + num_of_sequences4 = data[all_alg4].shape[0] + skewed_sequences4 = data[skewed_alg4].shape[0] + skewness2 = skewed_sequences2 * 100.0 / num_of_sequences2 if (num_of_sequences2>0) else 0 + skewness4 = skewed_sequences4 * 100.0 / num_of_sequences4 if (num_of_sequences4>0) else 0 + stats.append([ni, skewness2, skewness4]) + stats = pd.DataFrame(stats, columns=['n', 'skewness2', 'skewness4']) #.dropna(subset=['skewness']) + + + plt.style.use('ggplot') + plt.scatter(stats.n, stats.skewness2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.skewness2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + + plt.scatter(stats.n, stats.skewness4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.skewness4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Skewness') + plt.ylabel('Skewed Blocks (%)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_skewness.png', bbox_inches='tight') + plt.show() + +if __name__ == "__main__": + tlratio() + skewness() + time_profiles() + time_per_trial() diff --git a/tests/benchmark_skewness.py b/tests/benchmark_skewness.py new file mode 100644 index 0000000..f468b4d --- /dev/null +++ b/tests/benchmark_skewness.py @@ -0,0 +1,97 @@ +import random +import heapq +import csv + +# Common parameters +alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'] +trials_range = (10, 40) +n = 3 +sample_size = 100 + + +def to_benchmark_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [str(ralph_skewed)] + +def benchmark_nb_gm_001(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_001') + + +def benchmark_nb_gm_002(filename): + import generators.nb_gm_002 as nb_gm_002 + + generator = nb_gm_002.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + # print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_002') + + +def benchmark_nb_gm_003(filename): + import generators.nb_gm_003 as nb_gm_003 + + generator = nb_gm_003.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + print(f"sequence {i}/{sample_size}: {trials} trials") + seq = generator.generate(trials) + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_003') + + +def show_skweness_diagram(filename, choices, title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + print(filename) + data = pd.read_csv(filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) #.dropna(subset=['skewness']) + #print(stats.trials) + #plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'{title}.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + benchmark_nb_gm_003('../benchmarks/nb_gm_003_2back.csv') diff --git a/tests/common.py b/tests/common.py new file mode 100644 index 0000000..e40c0df --- /dev/null +++ b/tests/common.py @@ -0,0 +1,27 @@ + + +# Common benchmark parameters +choices = alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F'] +trials_range = (10, 65) +n = 4 +sample_size = 100 + + +def count_targets_and_lures(seq, n): + mask = 'D'*n + for index in range(n, len(seq)): + if seq[index] == seq[index - n]: + mask += 'T' + elif seq[index] in seq[index - n - 1:index - n + 1]: + mask += 'L' + else: + mask += 'D' + return mask.count('T'), mask.count('L') + + +def skewness(seq, choices): + import heapq + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return ralph_skewed diff --git a/tests/nb_gm_001_bm.py b/tests/nb_gm_001_bm.py new file mode 100644 index 0000000..54f6cb3 --- /dev/null +++ b/tests/nb_gm_001_bm.py @@ -0,0 +1,75 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq) , str(ralph_skewed)] + + +def benchmark(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets / s.trials, axis=1) + plt.scatter(data.trials, data.targets_ratio, alpha=0.2) + plt.show() + +if __name__ == '__main__': + alg = 'nb_gm_001' + fn = f'results/{alg}_{n}back.csv' + benchmark(fn) + # skewness_diagram(fn, alg) + targets_ratio_diagram(fn, alg) diff --git a/tests/nb_gm_002_bm.py b/tests/nb_gm_002_bm.py new file mode 100644 index 0000000..c8af543 --- /dev/null +++ b/tests/nb_gm_002_bm.py @@ -0,0 +1,105 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq), str(ralph_skewed)] + + +def benchmark(filename): + from generators.nb_gm_002 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials, int(trials/3), 0, 0) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +import time +import numpy as np +import pandas as pd + +import benchmarks.common as common + +def profile(): + from generators.nb_gm_002 import SequenceGenerator + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, int(lures/2), int(lures/2)) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('benchmarks/results/nb_gm_002_profile.csv', sep=',', encoding='utf-8') + +if __name__ == '__main__': + alg = 'nb_gm_002' + fn = f'results/{alg}_{n}back.csv' + profile() diff --git a/tests/nb_gm_003_bm.py b/tests/nb_gm_003_bm.py new file mode 100644 index 0000000..fa6c19a --- /dev/null +++ b/tests/nb_gm_003_bm.py @@ -0,0 +1,114 @@ +import heapq +import csv +import random +import time + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq, time_per_block): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [time_per_block, ''.join(seq), str(ralph_skewed)] + + +def benchmark_skewness(filename): + from generators.nb_gm_003 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['time_per_block', 'seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + targets = trials / 3 + t = time.time() + seq = generator.generate(trials, targets) + t = time.time() - t + print(f"sequence {i}/{sample_size}: {trials} trials, took {t}s.") + writer.writerow(to_csv_row(i, seq, t)) + plot_skewness(fn, 'nb_gm_003') + + +def plot_skewness(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def plot_targets_ratio(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +def benchmark_targets_ratio(): + pass + +def benchmark_chunking(): + pass + + +def benchmark_n(): + pass + + +def plot_timing(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['time_per_trial'] = data.apply(lambda s: s.time_per_block / s.trials, axis=1) + plt.style.use('ggplot') + plt.title(f"{figure_title} - average time to generate a trial") + plt.ylabel('time (s)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.time_per_trial, alpha=0.5) + + # draw fitted curve + # import numpy as np + # p = np.poly1d(np.polyfit(data.trials, data.time_per_trial, 3)) + # plt.plot(data.trials, p(data.trials), color='red') + + plt.savefig(f'results/{figure_title}_timing.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + alg = 'nb_gm_003' + fn = f'results/{alg}_{n}back.csv' + benchmark_skewness(fn) diff --git a/tests/nb_gm_004_bm.py b/tests/nb_gm_004_bm.py new file mode 100644 index 0000000..b4ad4a8 --- /dev/null +++ b/tests/nb_gm_004_bm.py @@ -0,0 +1,26 @@ +import time +import numpy as np +import pandas as pd + +import tests.common as common +from generators.nb_gm_004 import SequenceGenerator + +def run(): + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, lures) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('tests/results/nb_gm_004_profile.csv', sep=',', encoding='utf-8') diff --git a/tests/results/2v4_time_trials.png b/tests/results/2v4_time_trials.png new file mode 100644 index 0000000..9be91b4 --- /dev/null +++ b/tests/results/2v4_time_trials.png Binary files differ diff --git a/tests/results/2vs4_skewness.png b/tests/results/2vs4_skewness.png new file mode 100644 index 0000000..a488e1f --- /dev/null +++ b/tests/results/2vs4_skewness.png Binary files differ diff --git a/tests/results/2vs4_time_n.png b/tests/results/2vs4_time_n.png new file mode 100644 index 0000000..d022ed0 --- /dev/null +++ b/tests/results/2vs4_time_n.png Binary files differ diff --git a/tests/results/2vs4_tlratio.png b/tests/results/2vs4_tlratio.png new file mode 100644 index 0000000..b76f296 --- /dev/null +++ b/tests/results/2vs4_tlratio.png Binary files differ diff --git a/tests/results/nb_gm_001_2back.csv b/tests/results/nb_gm_001_2back.csv new file mode 100644 index 0000000..f6ad25e --- /dev/null +++ b/tests/results/nb_gm_001_2back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,0.0,1.0,0.0,55.0,56.0,0.0,0.0,0.0,BEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True 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+364,0.0,0.0,0.0,1.0,0.0,31.0,0.0,31.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +365,0.0,0.0,0.0,24.0,0.0,23.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +366,0.0,15.0,0.0,0.0,16.0,0.0,0.0,0.0,EEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +367,22.0,0.0,0.0,0.0,0.0,0.0,1.0,22.0,GHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +368,0.0,25.0,0.0,0.0,0.0,0.0,25.0,0.0,BGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +369,0.0,0.0,0.0,100.0,1.0,0.0,0.0,0.0,EDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +370,0.0,17.0,0.0,17.0,1.0,0.0,0.0,0.0,EBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +371,0.0,1.0,49.0,0.0,49.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True 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+377,27.0,0.0,0.0,29.0,0.0,0.0,0.0,0.0,DDADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +378,81.0,0.0,0.0,81.0,0.0,0.0,0.0,1.0,HADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +379,1.0,0.0,9.0,0.0,8.0,0.0,0.0,0.0,ACECECECECECECECEC,True +380,1.0,0.0,0.0,32.0,33.0,0.0,0.0,0.0,AEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +381,5.0,0.0,5.0,0.0,1.0,0.0,0.0,0.0,ECACACACACA,True +382,0.0,0.0,0.0,96.0,0.0,0.0,98.0,0.0,GGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +383,0.0,86.0,0.0,0.0,0.0,85.0,0.0,0.0,BBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +384,0.0,0.0,28.0,0.0,1.0,0.0,0.0,28.0,ECHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +385,0.0,1.0,119.0,0.0,0.0,0.0,0.0,0.0,BCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +386,0.0,0.0,93.0,0.0,0.0,93.0,1.0,0.0,GCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCF,True +387,92.0,0.0,1.0,0.0,92.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +388,0.0,186.0,0.0,0.0,0.0,0.0,0.0,0.0,BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +389,1.0,74.0,0.0,0.0,0.0,0.0,0.0,0.0,ABBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +390,0.0,0.0,0.0,0.0,1.0,86.0,0.0,87.0,EHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +391,61.0,0.0,0.0,61.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +392,0.0,0.0,0.0,1.0,16.0,0.0,0.0,15.0,DEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +393,118.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +394,0.0,0.0,0.0,0.0,0.0,75.0,0.0,1.0,HFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +395,30.0,0.0,0.0,0.0,0.0,0.0,0.0,30.0,AHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +396,65.0,0.0,0.0,0.0,0.0,1.0,0.0,65.0,FAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +397,0.0,0.0,0.0,55.0,56.0,0.0,0.0,0.0,EEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +398,26.0,0.0,0.0,25.0,1.0,0.0,0.0,0.0,EADADADADADADADADADADADADADADADADADADADADADADADADADA,True +399,0.0,0.0,60.0,0.0,0.0,0.0,1.0,59.0,GCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +400,1.0,0.0,0.0,0.0,160.0,0.0,0.0,0.0,AEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +401,1.0,0.0,31.0,0.0,0.0,31.0,0.0,0.0,AFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +402,0.0,0.0,0.0,15.0,1.0,0.0,0.0,0.0,EDDDDDDDDDDDDDDD,True +403,0.0,0.0,0.0,54.0,55.0,0.0,0.0,1.0,HEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +404,0.0,0.0,0.0,27.0,0.0,27.0,0.0,1.0,HFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +405,0.0,0.0,0.0,1.0,0.0,15.0,0.0,15.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +406,0.0,95.0,0.0,94.0,0.0,1.0,0.0,0.0,FBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +407,0.0,0.0,15.0,14.0,0.0,0.0,0.0,0.0,CCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +408,78.0,78.0,0.0,0.0,0.0,0.0,1.0,0.0,GBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +409,0.0,0.0,72.0,1.0,0.0,0.0,72.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +410,55.0,0.0,1.0,0.0,0.0,0.0,55.0,0.0,CAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +411,0.0,59.0,0.0,0.0,0.0,60.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +412,61.0,0.0,0.0,61.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +413,0.0,1.0,0.0,75.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +414,0.0,53.0,0.0,0.0,0.0,0.0,52.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +415,0.0,0.0,16.0,0.0,1.0,0.0,0.0,15.0,ECHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +416,0.0,0.0,0.0,39.0,0.0,0.0,0.0,38.0,DHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +417,96.0,0.0,1.0,95.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +418,28.0,0.0,1.0,27.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +419,0.0,1.0,92.0,92.0,0.0,0.0,0.0,0.0,BCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +420,1.0,0.0,20.0,0.0,20.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECE,True +421,0.0,90.0,0.0,0.0,0.0,0.0,89.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +422,10.0,0.0,0.0,0.0,0.0,1.0,11.0,0.0,FGAGAGAGAGAGAGAGAGAGAG,True +423,0.0,0.0,0.0,74.0,73.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +424,0.0,0.0,127.0,0.0,0.0,0.0,1.0,0.0,GCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +425,1.0,9.0,0.0,0.0,0.0,9.0,0.0,0.0,AFBFBFBFBFBFBFBFBFB,True +426,0.0,0.0,84.0,0.0,0.0,0.0,0.0,84.0,HCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +427,33.0,0.0,0.0,34.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +428,1.0,30.0,0.0,30.0,0.0,0.0,0.0,0.0,ABDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +429,0.0,0.0,67.0,0.0,1.0,67.0,0.0,0.0,EFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +430,62.0,0.0,0.0,63.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +431,1.0,9.0,9.0,0.0,0.0,0.0,0.0,0.0,ABCBCBCBCBCBCBCBCBC,True +432,15.0,0.0,0.0,0.0,0.0,0.0,14.0,0.0,AAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +433,0.0,1.0,0.0,65.0,66.0,0.0,0.0,0.0,BEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +434,0.0,160.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +435,0.0,0.0,1.0,0.0,42.0,42.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +436,0.0,0.0,55.0,0.0,55.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +437,0.0,0.0,0.0,1.0,0.0,73.0,0.0,73.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +438,79.0,0.0,0.0,0.0,78.0,0.0,0.0,0.0,AAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +439,0.0,0.0,67.0,0.0,0.0,0.0,66.0,1.0,HCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +440,0.0,0.0,77.0,0.0,0.0,1.0,0.0,76.0,FCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +441,0.0,0.0,0.0,0.0,153.0,0.0,0.0,1.0,HEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +442,0.0,88.0,88.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +443,0.0,0.0,0.0,20.0,22.0,0.0,0.0,0.0,EEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +444,41.0,0.0,42.0,0.0,0.0,0.0,1.0,0.0,GCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +445,0.0,0.0,0.0,47.0,0.0,46.0,0.0,1.0,HDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +446,1.0,0.0,0.0,0.0,86.0,0.0,0.0,87.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +447,56.0,56.0,0.0,0.0,0.0,0.0,0.0,1.0,HABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +448,0.0,0.0,0.0,0.0,11.0,0.0,0.0,10.0,EEHEHEHEHEHEHEHEHEHEH,True +449,0.0,0.0,0.0,0.0,0.0,1.0,92.0,92.0,FGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +450,0.0,0.0,0.0,6.0,5.0,1.0,0.0,0.0,FDEDEDEDEDED,True +451,66.0,1.0,67.0,0.0,0.0,0.0,0.0,0.0,BCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +452,0.0,0.0,0.0,13.0,0.0,1.0,12.0,0.0,FDGDGDGDGDGDGDGDGDGDGDGDGD,True +453,1.0,0.0,0.0,0.0,56.0,0.0,56.0,0.0,AEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +454,15.0,0.0,0.0,0.0,0.0,0.0,0.0,16.0,HAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +455,0.0,21.0,1.0,0.0,21.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True +456,93.0,0.0,1.0,0.0,92.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +457,1.0,0.0,0.0,0.0,35.0,0.0,0.0,35.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +458,13.0,0.0,0.0,0.0,1.0,0.0,13.0,0.0,EAGAGAGAGAGAGAGAGAGAGAGAGAG,True +459,0.0,0.0,65.0,0.0,1.0,0.0,65.0,0.0,ECGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +460,0.0,0.0,95.0,1.0,0.0,95.0,0.0,0.0,DFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +461,15.0,0.0,0.0,0.0,1.0,0.0,0.0,15.0,EHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +462,0.0,0.0,198.0,0.0,1.0,0.0,0.0,0.0,ECCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +463,84.0,84.0,0.0,0.0,1.0,0.0,0.0,0.0,EABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +464,0.0,0.0,0.0,0.0,0.0,60.0,0.0,61.0,HFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +465,0.0,179.0,0.0,1.0,0.0,0.0,0.0,0.0,DBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +466,1.0,0.0,90.0,0.0,89.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +467,0.0,35.0,0.0,0.0,0.0,34.0,0.0,0.0,BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +468,0.0,0.0,0.0,1.0,7.0,0.0,0.0,7.0,DHEHEHEHEHEHEHE,True +469,0.0,0.0,0.0,0.0,92.0,0.0,91.0,0.0,EEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +470,0.0,0.0,46.0,0.0,0.0,1.0,46.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +471,0.0,0.0,0.0,0.0,0.0,1.0,158.0,0.0,FGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +472,1.0,0.0,0.0,0.0,0.0,58.0,0.0,59.0,AHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +473,0.0,0.0,6.0,1.0,0.0,0.0,6.0,0.0,DCGCGCGCGCGCG,True +474,0.0,0.0,0.0,0.0,0.0,98.0,0.0,97.0,FFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +475,0.0,87.0,0.0,0.0,0.0,0.0,0.0,85.0,BBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +476,0.0,0.0,33.0,0.0,0.0,0.0,1.0,33.0,GHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +477,45.0,0.0,0.0,0.0,46.0,0.0,0.0,0.0,EAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +478,0.0,0.0,0.0,77.0,0.0,0.0,75.0,0.0,DDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +479,73.0,1.0,73.0,0.0,0.0,0.0,0.0,0.0,BACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +480,0.0,1.0,0.0,0.0,37.0,37.0,0.0,0.0,BEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +481,0.0,92.0,93.0,0.0,0.0,1.0,0.0,0.0,FCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +482,0.0,0.0,0.0,1.0,0.0,0.0,0.0,24.0,DHHHHHHHHHHHHHHHHHHHHHHHH,True +483,25.0,0.0,0.0,1.0,0.0,25.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +484,0.0,0.0,0.0,0.0,0.0,37.0,0.0,36.0,FHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +485,21.0,0.0,0.0,1.0,0.0,20.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +486,0.0,35.0,0.0,36.0,0.0,0.0,0.0,1.0,HDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +487,0.0,0.0,1.0,0.0,97.0,98.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +488,0.0,93.0,0.0,0.0,0.0,1.0,0.0,94.0,FHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +489,0.0,1.0,0.0,93.0,0.0,0.0,93.0,0.0,BGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +490,0.0,0.0,0.0,70.0,0.0,0.0,72.0,0.0,GGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +491,86.0,0.0,0.0,0.0,1.0,86.0,0.0,0.0,EFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +492,0.0,65.0,1.0,0.0,0.0,65.0,0.0,0.0,CBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +493,0.0,0.0,0.0,69.0,0.0,0.0,0.0,1.0,HDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +494,0.0,0.0,144.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +495,0.0,45.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +496,0.0,0.0,0.0,28.0,0.0,27.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +497,0.0,72.0,0.0,0.0,0.0,1.0,73.0,0.0,FGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +498,0.0,0.0,41.0,0.0,1.0,0.0,40.0,0.0,ECGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +499,0.0,1.0,0.0,0.0,0.0,131.0,0.0,0.0,BFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +500,17.0,0.0,0.0,1.0,0.0,17.0,0.0,0.0,DFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +501,19.0,0.0,0.0,19.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADA,True +502,1.0,0.0,0.0,0.0,51.0,0.0,52.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +503,1.0,0.0,0.0,0.0,0.0,0.0,29.0,29.0,AGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +504,36.0,0.0,0.0,1.0,0.0,35.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +505,0.0,0.0,0.0,20.0,0.0,0.0,1.0,20.0,GDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +506,0.0,0.0,0.0,163.0,0.0,0.0,0.0,1.0,HDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +507,22.0,23.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABAB,True +508,0.0,1.0,0.0,0.0,0.0,0.0,41.0,42.0,BHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +509,0.0,0.0,0.0,45.0,1.0,0.0,0.0,44.0,EDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True 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+671,99.0,0.0,1.0,0.0,98.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +672,68.0,0.0,0.0,0.0,0.0,0.0,67.0,1.0,HAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGA,True +673,0.0,0.0,0.0,26.0,27.0,0.0,1.0,0.0,GEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +674,31.0,0.0,0.0,0.0,32.0,0.0,0.0,1.0,HEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +675,0.0,0.0,0.0,0.0,42.0,0.0,41.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +676,0.0,0.0,50.0,0.0,0.0,0.0,1.0,50.0,GCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +677,0.0,25.0,0.0,24.0,0.0,0.0,0.0,0.0,BBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +678,0.0,0.0,0.0,0.0,1.0,10.0,9.0,0.0,EFGFGFGFGFGFGFGFGFGF,True +679,65.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,DAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +680,0.0,23.0,0.0,0.0,0.0,0.0,23.0,1.0,HGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +681,0.0,1.0,58.0,0.0,0.0,0.0,57.0,0.0,BCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +682,0.0,0.0,0.0,0.0,0.0,68.0,1.0,68.0,GFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +683,0.0,0.0,0.0,0.0,96.0,0.0,96.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +684,1.0,0.0,0.0,0.0,66.0,0.0,66.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +685,0.0,0.0,0.0,0.0,0.0,1.0,0.0,21.0,FHHHHHHHHHHHHHHHHHHHHH,True +686,0.0,88.0,0.0,87.0,0.0,0.0,0.0,0.0,BDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +687,0.0,0.0,19.0,19.0,0.0,0.0,1.0,0.0,GDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +688,0.0,42.0,1.0,0.0,41.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +689,0.0,0.0,0.0,0.0,0.0,60.0,61.0,0.0,GGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +690,0.0,23.0,23.0,0.0,0.0,0.0,1.0,0.0,GBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +691,86.0,86.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +692,35.0,35.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +693,57.0,0.0,0.0,0.0,0.0,58.0,1.0,0.0,GFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +694,0.0,0.0,30.0,30.0,1.0,0.0,0.0,0.0,EDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +695,19.0,18.0,0.0,1.0,0.0,0.0,0.0,0.0,DABABABABABABABABABABABABABABABABABABA,True +696,0.0,0.0,0.0,1.0,0.0,56.0,0.0,57.0,DHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +697,10.0,0.0,1.0,0.0,0.0,0.0,0.0,11.0,CHAHAHAHAHAHAHAHAHAHAH,True +698,0.0,0.0,89.0,0.0,88.0,0.0,1.0,0.0,GCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +699,0.0,0.0,87.0,0.0,86.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +700,17.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAA,True +701,0.0,0.0,66.0,65.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +702,0.0,0.0,1.0,0.0,0.0,0.0,123.0,0.0,CGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +703,0.0,118.0,0.0,0.0,1.0,0.0,0.0,0.0,EBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +704,0.0,0.0,0.0,0.0,0.0,0.0,0.0,132.0,HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +705,0.0,0.0,0.0,0.0,0.0,23.0,1.0,23.0,GHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +706,0.0,0.0,0.0,0.0,6.0,5.0,0.0,0.0,EFEFEFEFEFE,True +707,18.0,0.0,0.0,16.0,0.0,0.0,0.0,0.0,AADADADADADADADADADADADADADADADADA,True +708,0.0,72.0,0.0,0.0,0.0,71.0,0.0,1.0,HBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +709,0.0,0.0,54.0,0.0,0.0,1.0,0.0,55.0,FHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +710,0.0,1.0,87.0,0.0,87.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +711,0.0,0.0,1.0,63.0,0.0,0.0,0.0,64.0,CHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +712,78.0,0.0,78.0,0.0,0.0,1.0,0.0,0.0,FCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +713,0.0,80.0,0.0,0.0,0.0,81.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +714,0.0,1.0,0.0,0.0,0.0,0.0,40.0,39.0,BGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +715,0.0,0.0,7.0,0.0,6.0,0.0,0.0,0.0,CCECECECECECE,True +716,35.0,0.0,0.0,0.0,0.0,0.0,0.0,33.0,AAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +717,0.0,0.0,0.0,1.0,73.0,0.0,0.0,72.0,DEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +718,0.0,0.0,90.0,0.0,0.0,1.0,89.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +719,1.0,0.0,0.0,67.0,0.0,0.0,0.0,66.0,ADHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +720,56.0,0.0,0.0,0.0,56.0,0.0,1.0,0.0,GAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +721,0.0,0.0,0.0,1.0,0.0,0.0,49.0,49.0,DHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +722,0.0,0.0,0.0,117.0,0.0,1.0,0.0,0.0,FDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +723,0.0,0.0,86.0,1.0,0.0,0.0,85.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +724,0.0,0.0,31.0,0.0,0.0,0.0,0.0,30.0,CCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +725,1.0,0.0,0.0,0.0,98.0,0.0,98.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +726,1.0,84.0,84.0,0.0,0.0,0.0,0.0,0.0,ACBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +727,0.0,56.0,56.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +728,0.0,1.0,0.0,24.0,24.0,0.0,0.0,0.0,BDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +729,37.0,0.0,0.0,0.0,0.0,37.0,0.0,0.0,FAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +730,0.0,0.0,91.0,0.0,0.0,0.0,91.0,0.0,GCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +731,98.0,0.0,99.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +732,0.0,0.0,0.0,0.0,99.0,1.0,98.0,0.0,FEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +733,0.0,0.0,30.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +734,12.0,1.0,13.0,0.0,0.0,0.0,0.0,0.0,BCACACACACACACACACACACACAC,True +735,0.0,93.0,1.0,0.0,93.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True 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+852,0.0,1.0,0.0,0.0,136.0,0.0,0.0,0.0,BEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +853,0.0,0.0,0.0,0.0,1.0,0.0,0.0,163.0,EHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +854,74.0,0.0,75.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +855,0.0,0.0,0.0,19.0,0.0,0.0,17.0,0.0,DDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +856,0.0,73.0,0.0,1.0,0.0,0.0,74.0,0.0,DGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True 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+863,0.0,0.0,0.0,32.0,1.0,0.0,32.0,0.0,EGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +864,0.0,0.0,15.0,0.0,1.0,14.0,0.0,0.0,ECFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +865,0.0,1.0,98.0,0.0,0.0,0.0,98.0,0.0,BGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +866,1.0,0.0,0.0,0.0,19.0,0.0,0.0,0.0,AEEEEEEEEEEEEEEEEEEE,True +867,24.0,0.0,0.0,0.0,24.0,0.0,0.0,0.0,AEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +868,0.0,0.0,0.0,74.0,0.0,0.0,0.0,73.0,DHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +869,0.0,78.0,1.0,0.0,0.0,0.0,77.0,0.0,CBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +870,0.0,0.0,1.0,0.0,50.0,0.0,51.0,0.0,CGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +871,0.0,0.0,16.0,0.0,0.0,16.0,0.0,1.0,HFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +872,0.0,0.0,0.0,1.0,28.0,28.0,0.0,0.0,DFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +873,0.0,0.0,65.0,65.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +874,0.0,34.0,0.0,0.0,0.0,35.0,0.0,0.0,FBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +875,0.0,0.0,9.0,0.0,8.0,0.0,0.0,1.0,HCECECECECECECECEC,True +876,0.0,0.0,0.0,0.0,94.0,0.0,94.0,1.0,HEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +877,0.0,18.0,0.0,16.0,0.0,0.0,0.0,0.0,BBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True 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+885,0.0,0.0,0.0,93.0,0.0,93.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDF,True +886,0.0,1.0,0.0,89.0,0.0,89.0,0.0,0.0,BFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +887,0.0,1.0,0.0,0.0,42.0,0.0,0.0,42.0,BHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +888,68.0,0.0,0.0,0.0,1.0,0.0,0.0,67.0,EAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +889,55.0,0.0,0.0,0.0,0.0,57.0,0.0,0.0,FFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +890,25.0,1.0,0.0,0.0,0.0,0.0,26.0,0.0,BGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +891,81.0,0.0,0.0,0.0,80.0,0.0,0.0,0.0,AAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +892,0.0,0.0,1.0,0.0,10.0,0.0,10.0,0.0,CGEGEGEGEGEGEGEGEGEGE,True +893,1.0,0.0,43.0,42.0,0.0,0.0,0.0,0.0,ACDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +894,55.0,54.0,0.0,0.0,0.0,0.0,0.0,0.0,AABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +895,43.0,0.0,0.0,0.0,0.0,1.0,0.0,43.0,FAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +896,1.0,0.0,0.0,0.0,97.0,97.0,0.0,0.0,AEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +897,0.0,25.0,0.0,1.0,0.0,25.0,0.0,0.0,DFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +898,0.0,0.0,0.0,0.0,26.0,26.0,1.0,0.0,GEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +899,0.0,0.0,36.0,0.0,36.0,0.0,0.0,0.0,ECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +900,0.0,0.0,0.0,0.0,1.0,0.0,89.0,88.0,EGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +901,0.0,1.0,142.0,0.0,0.0,0.0,0.0,0.0,BCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +902,1.0,83.0,0.0,83.0,0.0,0.0,0.0,0.0,ABDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +903,0.0,0.0,17.0,0.0,17.0,0.0,0.0,1.0,HECECECECECECECECECECECECECECECECEC,True +904,77.0,77.0,0.0,0.0,0.0,0.0,0.0,0.0,BABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +905,0.0,0.0,0.0,0.0,0.0,0.0,164.0,0.0,GGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +906,0.0,0.0,0.0,89.0,0.0,1.0,0.0,90.0,FHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +907,0.0,0.0,41.0,0.0,0.0,0.0,42.0,0.0,GCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +908,28.0,0.0,0.0,0.0,0.0,28.0,1.0,0.0,GAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +909,0.0,0.0,94.0,0.0,1.0,0.0,95.0,0.0,EGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +910,0.0,0.0,27.0,1.0,27.0,0.0,0.0,0.0,DECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +911,0.0,0.0,0.0,100.0,0.0,1.0,0.0,0.0,FDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +912,0.0,1.0,66.0,0.0,0.0,0.0,66.0,0.0,BGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +913,0.0,23.0,23.0,0.0,0.0,1.0,0.0,0.0,FCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +914,0.0,0.0,0.0,0.0,0.0,0.0,150.0,0.0,GGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +915,0.0,0.0,0.0,0.0,0.0,0.0,1.0,42.0,GHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +916,0.0,147.0,0.0,0.0,0.0,0.0,1.0,0.0,GBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +917,0.0,56.0,0.0,1.0,0.0,0.0,0.0,56.0,DHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +918,0.0,0.0,0.0,0.0,0.0,76.0,76.0,1.0,HFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFG,True +919,0.0,53.0,0.0,0.0,0.0,0.0,0.0,52.0,BHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +920,0.0,0.0,147.0,0.0,0.0,1.0,0.0,0.0,FCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +921,0.0,0.0,0.0,40.0,40.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +922,0.0,82.0,0.0,84.0,0.0,0.0,0.0,0.0,DDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +923,1.0,0.0,0.0,0.0,0.0,0.0,0.0,97.0,AHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +924,0.0,29.0,0.0,0.0,0.0,0.0,0.0,30.0,HHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +925,25.0,0.0,0.0,1.0,0.0,0.0,0.0,25.0,DHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +926,0.0,164.0,0.0,0.0,0.0,0.0,1.0,0.0,GBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +927,89.0,0.0,0.0,0.0,1.0,0.0,90.0,0.0,EGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +928,0.0,0.0,1.0,0.0,41.0,41.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +929,0.0,0.0,1.0,19.0,18.0,0.0,0.0,0.0,CDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +930,0.0,0.0,0.0,0.0,1.0,75.0,75.0,0.0,EGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +931,0.0,0.0,21.0,0.0,0.0,22.0,0.0,0.0,FCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCF,True +932,0.0,0.0,81.0,0.0,80.0,1.0,0.0,0.0,FCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +933,20.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAAAAA,True +934,0.0,40.0,0.0,0.0,0.0,40.0,0.0,0.0,BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +935,0.0,72.0,0.0,0.0,72.0,0.0,1.0,0.0,GBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True +936,56.0,1.0,0.0,56.0,0.0,0.0,0.0,0.0,BADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +937,0.0,0.0,0.0,0.0,0.0,96.0,1.0,0.0,GFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +938,0.0,1.0,0.0,88.0,0.0,0.0,0.0,88.0,BHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +939,1.0,0.0,0.0,0.0,0.0,0.0,0.0,175.0,AHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +940,0.0,0.0,84.0,1.0,83.0,0.0,0.0,0.0,DCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +941,0.0,0.0,83.0,0.0,0.0,0.0,0.0,85.0,HHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +942,1.0,5.0,5.0,0.0,0.0,0.0,0.0,0.0,ABCBCBCBCBC,True +943,0.0,0.0,0.0,68.0,0.0,0.0,0.0,69.0,HHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +944,29.0,0.0,0.0,0.0,0.0,29.0,1.0,0.0,GAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +945,0.0,0.0,1.0,0.0,0.0,0.0,81.0,82.0,CHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +946,89.0,0.0,89.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +947,0.0,0.0,0.0,78.0,1.0,0.0,0.0,0.0,EDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +948,90.0,1.0,0.0,0.0,0.0,0.0,91.0,0.0,BGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +949,0.0,0.0,0.0,86.0,1.0,0.0,0.0,86.0,EHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +950,0.0,0.0,0.0,42.0,1.0,0.0,42.0,0.0,EDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +951,85.0,0.0,0.0,84.0,1.0,0.0,0.0,0.0,EADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +952,90.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +953,0.0,0.0,1.0,0.0,0.0,90.0,0.0,0.0,CFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +954,62.0,0.0,0.0,1.0,0.0,62.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +955,0.0,20.0,20.0,0.0,1.0,0.0,0.0,0.0,EBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +956,0.0,0.0,37.0,0.0,0.0,1.0,0.0,38.0,FHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +957,98.0,1.0,0.0,0.0,0.0,98.0,0.0,0.0,BFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +958,0.0,1.0,0.0,0.0,189.0,0.0,0.0,0.0,BEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +959,0.0,0.0,0.0,9.0,0.0,1.0,8.0,0.0,FDGDGDGDGDGDGDGDGD,True +960,0.0,68.0,0.0,0.0,0.0,0.0,0.0,69.0,HHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +961,0.0,0.0,0.0,138.0,0.0,0.0,0.0,0.0,DDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +962,0.0,0.0,0.0,0.0,1.0,30.0,0.0,30.0,EHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +963,0.0,0.0,0.0,80.0,80.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +964,77.0,0.0,0.0,1.0,0.0,0.0,0.0,78.0,DHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +965,0.0,0.0,0.0,58.0,58.0,0.0,1.0,0.0,GEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +966,0.0,0.0,0.0,1.0,35.0,34.0,0.0,0.0,DEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +967,0.0,60.0,0.0,60.0,0.0,1.0,0.0,0.0,FDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +968,0.0,1.0,80.0,0.0,81.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +969,0.0,1.0,0.0,0.0,0.0,0.0,81.0,81.0,BGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +970,16.0,0.0,0.0,16.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADA,True +971,0.0,0.0,0.0,0.0,78.0,77.0,0.0,0.0,EFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +972,0.0,0.0,10.0,1.0,0.0,10.0,0.0,0.0,DFCFCFCFCFCFCFCFCFCFC,True +973,0.0,0.0,0.0,0.0,0.0,44.0,1.0,44.0,GHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +974,0.0,36.0,0.0,0.0,0.0,36.0,1.0,0.0,GFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +975,0.0,87.0,0.0,0.0,0.0,0.0,87.0,0.0,BGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +976,42.0,0.0,42.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True 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b/tests/results/nb_gm_001_3back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,0.0,65.0,132.0,0.0,0.0,0.0,0.0,1.0,HCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCC,True +1,51.0,0.0,52.0,52.0,0.0,0.0,0.0,1.0,HCDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACD,True +2,0.0,61.0,0.0,62.0,0.0,0.0,61.0,1.0,HDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGD,True +3,40.0,0.0,0.0,1.0,0.0,0.0,0.0,80.0,DHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHA,True +4,4.0,0.0,1.0,0.0,0.0,6.0,0.0,0.0,CAFFAFFAFFA,True 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+62,0.0,1.0,0.0,0.0,59.0,0.0,60.0,59.0,BGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEG,True +63,0.0,0.0,0.0,0.0,0.0,0.0,1.0,167.0,GHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +64,48.0,0.0,0.0,0.0,1.0,0.0,0.0,95.0,EHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHA,True +65,0.0,0.0,0.0,65.0,66.0,0.0,67.0,0.0,GGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGE,True +66,35.0,71.0,0.0,0.0,0.0,0.0,0.0,0.0,BBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBAB,True +67,50.0,0.0,0.0,50.0,50.0,0.0,0.0,1.0,HAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAED,True +68,0.0,0.0,4.0,0.0,0.0,0.0,5.0,3.0,GCGHCGHCGHCG,True +69,0.0,0.0,5.0,0.0,0.0,0.0,1.0,10.0,GCHHCHHCHHCHHCHH,True +70,0.0,0.0,19.0,0.0,19.0,20.0,0.0,0.0,FECFECFECFECFECFECFECFECFECFECFECFECFECFECFECFECFECFECFECF,True +71,0.0,0.0,1.0,0.0,0.0,0.0,43.0,84.0,CGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHG,True +72,6.0,0.0,0.0,0.0,6.0,6.0,0.0,0.0,FAEFAEFAEFAEFAEFAE,True +73,0.0,0.0,35.0,35.0,35.0,0.0,0.0,1.0,HECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECD,True +74,25.0,0.0,26.0,0.0,1.0,0.0,0.0,25.0,ECAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHC,True +75,61.0,0.0,0.0,60.0,0.0,60.0,0.0,1.0,HAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDA,True +76,0.0,0.0,0.0,41.0,0.0,0.0,0.0,20.0,DHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDD,True +77,0.0,0.0,1.0,0.0,0.0,15.0,15.0,14.0,CGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGF,True +78,6.0,0.0,1.0,6.0,0.0,0.0,0.0,6.0,CHDAHDAHDAHDAHDAHDA,True +79,0.0,124.0,0.0,62.0,0.0,0.0,0.0,0.0,BBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBD,True +80,0.0,0.0,32.0,0.0,0.0,31.0,31.0,0.0,CGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCF,True 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+317,61.0,0.0,0.0,0.0,0.0,61.0,1.0,61.0,GFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHA,True +318,0.0,0.0,0.0,7.0,7.0,8.0,1.0,0.0,GFEDFEDFEDFEDFEDFEDFEDF,True +319,7.0,0.0,0.0,0.0,1.0,3.0,0.0,0.0,EAAFAAFAAFA,True +320,0.0,48.0,0.0,48.0,0.0,0.0,0.0,48.0,BHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHD,True +321,0.0,23.0,23.0,0.0,0.0,0.0,0.0,24.0,HBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCH,True +322,0.0,0.0,1.0,0.0,0.0,30.0,30.0,30.0,CGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFH,True +323,48.0,0.0,0.0,47.0,47.0,0.0,1.0,0.0,GADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEA,True 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+401,0.0,55.0,55.0,0.0,0.0,1.0,54.0,0.0,FCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCB,True +402,47.0,0.0,0.0,0.0,1.0,47.0,0.0,47.0,EAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFH,True +403,56.0,0.0,0.0,0.0,58.0,0.0,0.0,56.0,EEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAE,True +404,0.0,39.0,0.0,0.0,39.0,1.0,40.0,0.0,FGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEG,True 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+951,0.0,0.0,0.0,0.0,35.0,1.0,35.0,35.0,FHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEG,True +952,0.0,0.0,1.0,0.0,0.0,0.0,36.0,71.0,CHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHG,True +953,0.0,42.0,0.0,0.0,21.0,0.0,0.0,1.0,HEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBB,True +954,0.0,49.0,0.0,50.0,0.0,0.0,49.0,0.0,DDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBG,True +955,11.0,0.0,0.0,0.0,22.0,0.0,1.0,0.0,GEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAE,True +956,0.0,0.0,0.0,1.0,0.0,18.0,0.0,38.0,DHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHH,True +957,58.0,58.0,60.0,0.0,0.0,0.0,0.0,0.0,CCBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBAC,True +958,19.0,19.0,0.0,0.0,19.0,0.0,0.0,0.0,BEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEA,True +959,0.0,0.0,39.0,0.0,0.0,38.0,0.0,38.0,CFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHC,True +960,0.0,0.0,0.0,80.0,41.0,0.0,0.0,1.0,HEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDE,True +961,0.0,21.0,0.0,22.0,0.0,23.0,0.0,0.0,FDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDF,True +962,0.0,0.0,0.0,0.0,6.0,10.0,0.0,0.0,EFEFFEFFEFFEFFEF,True +963,65.0,65.0,1.0,0.0,65.0,0.0,0.0,0.0,CBEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEA,True +964,0.0,46.0,1.0,0.0,45.0,46.0,0.0,0.0,CFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFB,True +965,64.0,64.0,0.0,0.0,63.0,0.0,1.0,0.0,GABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEAB,True +966,1.0,0.0,47.0,0.0,0.0,48.0,47.0,0.0,AFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGF,True +967,54.0,0.0,54.0,53.0,0.0,0.0,0.0,0.0,ACADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADC,True +968,10.0,0.0,10.0,0.0,12.0,0.0,0.0,0.0,EEACEACEACEACEACEACEACEACEACEACE,True +969,0.0,0.0,0.0,0.0,0.0,0.0,125.0,62.0,GGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGH,True +970,0.0,8.0,1.0,9.0,0.0,0.0,8.0,0.0,CDBGDBGDBGDBGDBGDBGDBGDBGD,True +971,0.0,0.0,0.0,66.0,66.0,67.0,1.0,0.0,GFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEF,True +972,63.0,0.0,0.0,0.0,127.0,0.0,1.0,0.0,GEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAE,True +973,0.0,0.0,11.0,0.0,0.0,0.0,21.0,1.0,HCGGCGGCGGCGGCGGCGGCGGCGGCGGCGGCG,True +974,0.0,0.0,39.0,0.0,0.0,40.0,40.0,0.0,FGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFG,True +975,0.0,0.0,1.0,31.0,0.0,0.0,62.0,0.0,CDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGG,True +976,0.0,54.0,0.0,0.0,0.0,1.0,54.0,55.0,FHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBH,True +977,0.0,0.0,18.0,19.0,0.0,18.0,0.0,0.0,DFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCD,True +978,126.0,63.0,0.0,0.0,1.0,0.0,0.0,0.0,EAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAAB,True +979,19.0,0.0,0.0,0.0,0.0,1.0,0.0,9.0,FAHAAHAAHAAHAAHAAHAAHAAHAAHAA,True +980,0.0,0.0,32.0,32.0,0.0,33.0,0.0,0.0,FDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFC,True +981,15.0,0.0,15.0,0.0,16.0,0.0,0.0,0.0,ECEACEACEACEACEACEACEACEACEACEACEACEACEACEACEA,True +982,0.0,0.0,55.0,0.0,0.0,56.0,57.0,0.0,GFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFG,True +983,0.0,0.0,32.0,0.0,1.0,32.0,31.0,0.0,EFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFC,True +984,0.0,0.0,0.0,41.0,1.0,40.0,40.0,0.0,EDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGD,True +985,0.0,0.0,0.0,0.0,5.0,6.0,5.0,1.0,HFGEFGEFGEFGEFGEF,True +986,0.0,19.0,17.0,0.0,0.0,0.0,0.0,18.0,BBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBH,True +987,0.0,0.0,0.0,0.0,0.0,0.0,6.0,10.0,GHGHHGHHGHHGHHGH,True +988,0.0,0.0,69.0,0.0,36.0,0.0,0.0,0.0,ECECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCE,True +989,1.0,0.0,0.0,0.0,0.0,19.0,0.0,37.0,AHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHF,True +990,67.0,0.0,0.0,0.0,0.0,0.0,0.0,33.0,AHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAA,True +991,0.0,0.0,16.0,18.0,0.0,17.0,0.0,0.0,DFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFD,True +992,1.0,0.0,50.0,50.0,0.0,0.0,49.0,0.0,ACDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCD,True +993,0.0,40.0,39.0,0.0,39.0,0.0,0.0,1.0,HBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEB,True +994,0.0,30.0,1.0,0.0,0.0,0.0,30.0,30.0,CBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGH,True +995,126.0,0.0,1.0,0.0,0.0,0.0,0.0,63.0,CHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAA,True +996,45.0,0.0,45.0,1.0,0.0,0.0,0.0,45.0,DHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHAC,True +997,15.0,0.0,0.0,0.0,29.0,0.0,0.0,0.0,AEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEE,True +998,0.0,4.0,1.0,0.0,0.0,4.0,0.0,4.0,CHBFHBFHBFHBF,True +999,0.0,100.0,0.0,0.0,0.0,0.0,0.0,51.0,HBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBH,True diff --git a/tests/results/nb_gm_002_2back.csv b/tests/results/nb_gm_002_2back.csv new file mode 100644 index 0000000..33538c3 --- /dev/null +++ b/tests/results/nb_gm_002_2back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,4.0,2.0,2.0,2.0,2.0,1.0,0.0,5.0,BHCHDHDAEBEHAFAHAC,True +1,0.0,4.0,1.0,2.0,4.0,0.0,0.0,0.0,DBEBDBCEEBE,True +2,5.0,10.0,14.0,6.0,16.0,18.0,12.0,12.0,CFFGHCFCGHEDCCACECBGEGFGAEBGHFDCEEDCCEGEGCBBBHCCECHBHEHBHDEDAFAFAFHFGFGFGHGHEFFFEFEDHFEFEFBBB,False +3,12.0,15.0,11.0,20.0,13.0,17.0,17.0,22.0,AFAHGHGHGBEBCDDDDHHHABCEHEHEBBBAHADADCFHHHHHFEFCBDDFDGDEFCAGGFEFBDGEHECCBCFFFFFFHGEBBHHCBCACHHDDBFGGGGEGEAFDGDADGDGDGBEBAAHDDFH,False +4,4.0,4.0,8.0,8.0,5.0,7.0,4.0,2.0,FGDGECDCECGCDADAHFDFCFCGAFCDDDABEBHBEFEFBC,False +5,15.0,15.0,15.0,16.0,16.0,14.0,9.0,13.0,HGDGBFDHDADHBBBBBHBAAGBCEABCGFAFAFBGBCBFGDDDEAAAHDFACECECHFHFHFCFHEGEFEFDFDAAHDEECDABFCCCCGBEBDAHCECHCHEDEDEDAGEE,False +6,17.0,17.0,9.0,6.0,15.0,13.0,15.0,12.0,BEBEBHAGCFEHHABAHDEDGHFBFGFCAABAGFFFAFGECEBEAEAFBFCEBEGHGDBEFABABEGEHEHBGBGDADACAGHGHGBGBACGCAHFFBHAECDC,False +7,12.0,7.0,7.0,6.0,9.0,8.0,5.0,6.0,CEGBFEFEFEHCCDEBCCHBBBGAHACBGGDBDADACADHDHFEAEAEFGFAAEAHAFAF,False +8,9.0,13.0,10.0,11.0,12.0,15.0,11.0,12.0,CGCFDBDFHHEHFFGCDHEHCFCFAAEGDCEGHGCFCBBBCBGFGHGDFDBDADHBBEGAGABABHBEBEHGHADAFEFCFDBDEFEHEFEFA,False +9,13.0,26.0,23.0,14.0,20.0,18.0,19.0,27.0,HECEBEFFHFDCCFGBCBDBAHGHGCBBABHEFAFEBEBHBHGGCHBGGCCCCCFCBDDDEDHDEEEAAFAFGFDFCGBGHEHDHGHAFABCGGEHEHFBGBADEBEBEAAHBDCCFGGHHHBHBHGHBDBEEAEGCGCBCHCEFFFFCHDHCHDHABCB,False +10,14.0,18.0,15.0,13.0,15.0,19.0,18.0,11.0,AFACABDDFBBBEBECECGHFBFBECDCEEEDGDBHHGCBDDAFCBAAAGHCHCHEAFBFDHAHCFFAAAHBBBFBFBHGFBCBCFGGGHGDGDFEGEFCFEDGDGAGEGCGEGEFEFAFDGC,False +11,21.0,20.0,21.0,13.0,15.0,26.0,21.0,21.0,EECEFFHGCADHGEGEABCCFDEBABEBGGCACHFHFBFBFBAHGBGCGHDCDABHHAGABFHEBCFEGDFDFDFAFBCBCAHACFGFBFBFBFBDACCBCHFHEGEDFDFCAAAGGEBFAAACACHCHFGFBFGHGHAEAGCCEDDFHHHGHGHGDE,False +12,17.0,26.0,17.0,23.0,17.0,11.0,26.0,21.0,ABGCACGDDFHFHBCEHEAGBGBEBAHEBEBFAAHAFBCEGDGBAHGGGGFGDDDBABABHGGGCGDGHGHDACAEDEFECHGEGDABGCHCDDDDCBCBADAHCHGBGBGEHDCDBBFBABHBHBFBACHDEEHGHECDCDHDEFEDECFGHGBFBD,False +13,24.0,21.0,23.0,20.0,15.0,14.0,30.0,24.0,AHHHHAFEDHAFBFGFCFGADADCDGBBBBGDGEGBCBHGGGGCGFBFAGGGGHEEFEGHGHABCBFHGAGACBBDEDHDHDGBCACAHGCACEHECACHBHDCGCECADGDGDABADHFGCGAGAHHBGFDCHBHCAAABEEFDFDBDBEADAHGEGEHECCCBCFCAHD,False +14,1.0,0.0,2.0,1.0,1.0,1.0,2.0,2.0,DECGCGAHFH,True +15,7.0,7.0,10.0,5.0,8.0,4.0,8.0,9.0,HBABHHEEGAGAGEGHCDEECHCHGBCBCDDAEGCBCGEAEFDFBFBFAGCHCHCHAD,False +16,14.0,19.0,14.0,7.0,10.0,15.0,19.0,7.0,CEAFFGHGEGFDFDCACAGBDEAFCEDDFAHHFDFGBEACGCGBGAFECECFGHCEBAFGEGCBABEBHBHBACAGAGDGHBABCBCBGFGFGFGBBBBFBCBGA,False +17,17.0,15.0,14.0,12.0,10.0,9.0,17.0,6.0,EBACADACGBGBAFGHGHADCDGAAFFFADABAHGDGABBCBCACACECHFBFHDCACDGEBADDEGGGEDADFGFGCGFBBABCBEBDBCHGEGEGECE,False +18,14.0,22.0,17.0,9.0,14.0,10.0,25.0,20.0,EHCHAHEHAHCHCGBGCGCGAEBFBFGGCEFGBGHAHCBABABHHGHGCACHDEDBBABGGDGDEBBBHHGCAEGBFHGEGEGBCCGCDFBBGBFBDAEEHHHCFEFECEHGCGCBHDADFDAGAGAGFBB,False +19,13.0,27.0,12.0,18.0,19.0,17.0,20.0,18.0,BFGCGBHAHAHEFEDBABEBEDADGGGGBAFCGEBDFHBHGHGCBBEGEGBHDHDHBCBCACDBFHHCHBGAGAGEDADADCDCACGHEEEEBDFDFDHDCGGBGDEBBBABEHFHGEFFFBADHEFFCFDEBEBFFEBHBFBG,False +20,11.0,10.0,7.0,8.0,8.0,7.0,11.0,4.0,BGBABGHGCGFBFAEBGGEDEFAHEHACDCDADBGGAGAGADFBFBCBCEFBFDHDACCDAGAEEE,False +21,22.0,20.0,18.0,24.0,13.0,11.0,16.0,21.0,DADADHCACFCHEDAAAHGDDHAGCDEDEGBHAHBDBDBGHHHCHCECAAAEFEDECEDBHFABGBCAGDBEGEBABHFCBBABDFDGHGCBFBCCDHDHDGDHDHCHBGADAFACHEHBDCDAFAFAFAGGCGCFHGBDBEBEG,False +22,8.0,10.0,11.0,7.0,8.0,15.0,4.0,11.0,CBAEGDGEHEBGBFBFBDHCHFHBAEHFFGFCFBFCFEEHABECFFFFACAEHHDCDCDHDHAHCFCBCBAADF,False +23,32.0,19.0,21.0,23.0,13.0,27.0,21.0,27.0,GHCABDGDFFFAHHHEAEHGAGAGHEFEGBCFAFBFGCHCHFHBGCAFFDFDBACACHCHCHBFGFEACAFABEBEBHHGHFHAHGGAGAHAFCGDHDHAFGCBCHDAAAAAAFCFHGEFFBEBEDDDFDBCBDDDCGFAFADBDBEBCAGGHDFDFBCDEAGAHCCEHGHAHCDDDDABAFA,False +24,26.0,30.0,18.0,21.0,29.0,16.0,21.0,21.0,GDGDADAGAGDEHCDBDHAHEHFHAHAFBHBHGCEBHBDBHBHBEEABABABAEECEGEGAGADHDBEEGBCAADHGBFBCEAAHDEBEBFBFBFCCGCEFBABAEDBGFGBGCFCGEACDFEFBHDADFHCEAEBDHDCGBEFGCDCACDEBEGAGAEAEFDFBBEHEGEGHCACEFBHDH,False +25,17.0,15.0,10.0,21.0,16.0,11.0,16.0,22.0,BDBDBHHHAAGAEHEHCHCDADEBGHDAGEBHGAABADADEDECEHAHFBGCGBEHCGADFBHECGHHFFFHFBDDDDDFDFDFHFEDEDACAEAEBDCHHBFBABCBGDGEAECHHGHGEGHDAGGG,False +26,12.0,13.0,16.0,11.0,17.0,10.0,17.0,12.0,GEECBGFEEDHCEFGFEAEAHGEGEDDDHDCDCBHBCBCFCECEGAGAGAHECFCEAAFGFGCEHGHBBBGBGBCBDHEAEFHFHGBCDGGACHCGCDADAEBFBADH,False +27,14.0,11.0,17.0,13.0,14.0,21.0,16.0,19.0,AAECGGEGHCACACACHBHADCECBDHDHDFCFGHGDDEDHHHAHDFDACHBHAFBHHAEEECGGFGEGEBEFCFAEAEFFBFBFDGDGDGHFACCDFHFCGBBHBCGGFGEHEFFFFHFCBCAF,False +28,14.0,15.0,12.0,21.0,15.0,9.0,13.0,21.0,GGHGEDHFCFCACBCADAEEEEAHDGAGHGHEHEHBBECEDBBBDBEGDGBAEABCCABBECDDDFDFHGHGHDHGHGHDADHHCHBHCCBAFHFDDDEDHFHAABDFDFEGEAADBDCH,False +29,18.0,19.0,27.0,26.0,29.0,30.0,16.0,16.0,DEFFFAFAGDGEEBFBFGEBADACADFDCEEDEDFDCDEBBGDGHGHGFFFDFBEBEHCHFDCDCEGFGFHFEFCGBBDCHCGCDADEGEGCFAAEHEHFDACGCEABBDECBCBCEFEFBFCFCFEHEHDGACEBAGCEFEBACCCAEDHDHBCFCDEFFHDHDHDCFCAAAEBEBFDHA,False +30,5.0,11.0,5.0,8.0,3.0,2.0,5.0,1.0,BBFGGBABFGCCCDADAHBEDCDBABGEAECBDBDBDBDG,True +31,28.0,17.0,19.0,16.0,18.0,11.0,17.0,33.0,DHAFAHAEAHDHFHFAFADHCGGGDGDGHEBDHCHBHAEBCBCFEGHHHBHCAFDHEHEHCDAGBCBAAAGACCBCAFGBHEHBBEAHAHAFAEACGGEHAFABEDEDFDCGHEBGAGEEAEBBHDEDECHCGABHGHAHAHBHCHCHCHDGACACDFD,False +32,5.0,10.0,12.0,17.0,19.0,17.0,17.0,11.0,EEBHBFFFDDEDCCAGEFEGGDGDFFGEGEAEDEFCFCGCGCGFAEGECDHHCEFDDHDFDABFDECECEHEFDDGDGBBFBFHHGCECEFEHAHDHDGBBFBGHGBG,False +33,4.0,13.0,10.0,7.0,4.0,8.0,11.0,7.0,CGBHBCBCBHFHFECBADGBGBGBDBCFAGDBHGFGECEHBGBCCACFGFGFGDDDFCADHEHB,False +34,22.0,27.0,22.0,21.0,21.0,28.0,21.0,21.0,BABFBCCCCGCDCAGABAHFBAHCBDBDHDCDCDEFFHBHBCBCBEHDAGAEFBBEEEBEGAGHGDGCGEBFBDEAECCFCFGDGDGHBHAEFFFECCADHFFBGHDHEGAAEDEFEFCDCDCDEFCHADAEHFDFHBBEBEBFBFAFGFAAHGHGFFAFGGBABGHGBFBFDFHCHAHEGDA,False +35,24.0,23.0,21.0,17.0,28.0,15.0,20.0,21.0,EGHGAGEGCGDFFCEEEEEAHGEGFGFBCBGBDBACHCAGDDDDEDEHACGCECAFAFEFHCHCEFHDHEHBAEADBDBAFCHCEEEEHBHBECEAEAFGGGGCCHBHAAACABBEHFHBDFHHDHBGCAABEBGAGABBFADADEBBBBCDCACFGFHDCEHEBGADE,False +36,16.0,12.0,18.0,16.0,29.0,20.0,25.0,11.0,EEEBCFFDHDBBGHGHGEFDFACCCFCGAECECEAGFFFCFDAHAEEHGGGBGBGADDGDGEGCCBFEHEGEHACDGDGCCCFCEAFAEGEGBGFGBBBHFGDGFGAAHADADCEEEEDEAEFEAEBFFFHEGECEGEHECAFDDDB,False +37,1.0,6.0,2.0,11.0,2.0,11.0,4.0,7.0,DBFFFHHADFFEFBDBFBGDFFEBHBHFHGDGDGCCDDDDHDHF,True +38,11.0,12.0,15.0,5.0,3.0,15.0,15.0,13.0,HCCCCAEBGFCFBGAHHHHBAFGCGCGCGFGCAABFBABHBFBCAFHFAFGCDBGBGAGFCBBAADHDHDCGEGHGCGFFHFHDEFHFC,False +39,33.0,14.0,21.0,23.0,21.0,18.0,25.0,28.0,DHAHAHADGDAFAFGCHCHEHCHABACEDDDCGBHAEFFGCADADGBGCFFFGGHBAAFGGHFHFHECFCHCHBDEFGADDCGGGHEBEDEBEBEDFHCAAAACFGFBFBFADAEGBDCAGACACAFGEEECDDDDCGGGEEEEEGCADHHHHAHABAHGBBCACHEGGHDADADAHAHEHAH,False +40,9.0,21.0,8.0,6.0,13.0,11.0,9.0,15.0,HEBEGEGAGEBBBHFAFABCBCBEBCBEAFHGGGHEHCHBEDFFAFAHDBFBFBEBDFHHDHBHCHBHBDEFABGBCEDEBCACHHEAGBGF,False +41,13.0,18.0,18.0,16.0,8.0,20.0,16.0,13.0,AGDGBCDHFADAGFFFHHCFCFEBGBGFGFGCGCHHHHCGFBFGDHABCBCGDGECEFBFCACBDBDCFAFBDEDCFFBHGHBEBABDFDFDHDHACABDBAFAFDHEGACACBEECGCBDG,False +42,21.0,15.0,14.0,22.0,14.0,22.0,16.0,21.0,ACFDFDEDFDBAFDCDCDFFFFFACHCHGEDFCFEHADACEHEDEBAFAGGHGEDADFDHDHDHGADAGCCCFHBDBGBDEGEBHGFGHAHFBFBFEAABABACDDAHHGFGBGEGHFEABHBFEHHHGDFDCACABABGECHAH,False +43,17.0,19.0,23.0,19.0,19.0,21.0,20.0,22.0,GDGFGEDDDDDDFDFDFEHBHDGAECBHDEGHGEEDEBEDECGGAADAFAFADECFCDGDGFBHGCBHBACAGACFCGGGBGCHFHEHECECAHFHFGCGHBFCGCBCFEHEGEHBBAAABDHFBCCCCFFFHFCABFBHBHBEDAFEHBHACABECHCH,False +44,2.0,1.0,3.0,4.0,5.0,3.0,6.0,5.0,CHCHFGBGEHFDAGADEDEGGFGEDEHCH,True +45,17.0,20.0,26.0,20.0,18.0,24.0,15.0,12.0,BDEFBBBHHECFCFCBBFEDDADADGECEHEFCGCAFDCGCFFEDDGGHHHHHAFAFEFAFDFDFDEDFAACFCFCDCBBBCGCGDGDFCGCGBDCACBHDHEECBBEBECFCHGBGEGABCDCEFHFGACDFAFAECEBEBDACABAGFBA,False +46,5.0,7.0,11.0,5.0,5.0,3.0,8.0,10.0,CBDHFHCDCEGEHCHCHCHEGCGCGBBBBADAHGDGBACGEAHBHFGFCECAHD,False +47,5.0,4.0,4.0,5.0,0.0,1.0,5.0,3.0,ACABGBHBHBGDCACHCDAGFGAGDDD,True +48,21.0,22.0,13.0,24.0,16.0,18.0,24.0,19.0,DBDGAGBGFHFCABGFECEGBGHHEACDFDGCGBEBGDAFAHADADAHHBHBHAGABADEBFDGDBDGDGCFAFAFDDDDECGFEFEAHAHEHEHCBCDADGBFBFAEBCAHFHEDEGBBFDEHEBDHFGCGHGHGBGCDABCBDGHGBGDCEAFAF,False +49,5.0,12.0,11.0,8.0,8.0,7.0,11.0,9.0,FCFDGDHBEBECFBBHFCFCGDBCCCGCECECBDBGBEHDDBCAGAEHEDFDHGEGAHBHGAGAGFHBHBG,False +50,2.0,7.0,7.0,4.0,6.0,13.0,10.0,11.0,BBFEFEFHAHFDFGHEBABDFHBHEFGFGHEHGGGFDFEHCBGBFDFHFHCCGCGHGCCC,True +51,5.0,7.0,11.0,12.0,13.0,9.0,8.0,13.0,EFFBFDAAECCCHDHBHFEDBHBHDHDGGGGECDGHCFEFEDEDCDCDEDCCHFEFEGCGBHEHBHAHAGDFCEAEHB,False +52,15.0,6.0,11.0,6.0,11.0,16.0,3.0,8.0,BAEGCCEAHBFCCHFABEHEFDCHEBECACECEAFGFEFEFBFBFAFADADACACDFGFAFAFEFDAAHFDCAHHH,True +53,20.0,14.0,19.0,11.0,13.0,12.0,10.0,17.0,CHCECEHEGAHBFGHCHABCBCDCECEDAHACGCADDBBGFGFGFHAAACACFBEGGAGAEHCAAAFDFDCHBDBHGDFDHCBEFEBCBABHHHHDHCHDFEFABEBECAAAEACF,False +54,18.0,14.0,15.0,22.0,24.0,20.0,25.0,23.0,EGGCGCGDEDEBCBFDDDBFHDDGFBFEEEGDBDBEHFDFEACACADABEFDCECGGHBDCDBAGHGFBFECHCFEDEHEHAHEEAGCEEEEFGFHFAAGEEHHHHAHAHDEFGDGDBCGAGHFHFHAHAHDHDBFBFCEGGGGGGGHAADAGCDFFAHCB,False +55,3.0,4.0,2.0,5.0,2.0,5.0,3.0,1.0,EHAABABGBFDFGFGEDDFDCBCDF,True +56,9.0,9.0,8.0,11.0,11.0,13.0,8.0,11.0,ECFFFBCDEDAFEBEAFGFHFHFDEHEBEHEGBFEFHBABCCAGAGBGBDFHAHGHFCFDHDABADEDEDAHGGCDCHCD,False +57,10.0,13.0,10.0,15.0,7.0,9.0,16.0,11.0,HHCFEGEGEDFGABEHEADCHGHBDFDGDGHGCGBBDDCDCDBDBHCDEBAHACCFDGDFAFAFDDAGAGHGCGBGBHACBGBGAHEBFBF,False +58,15.0,15.0,14.0,21.0,27.0,24.0,20.0,28.0,FAFEFAADAGFBFACBCBHHCGFGFAFHCEGEGHHBDBFHFHBEGDGDAEEHEGCGDGHCDGDEHFHGCEEEGEGEDBDEEEEHHHHCHDAGFEBHFHAHFHFDDDCACHFBDDHDGDFDAGGEAEFBHEEEEBEHEFFCFCFDBHAFADCGCGFHDHEBABHB,False +59,11.0,16.0,18.0,17.0,22.0,31.0,15.0,17.0,FCECFCFCFBHCHBGBFHGEDADADEFEFHFDFDADEEADHGAEAECGDGCCFHFGFHFHFHFBFBFCEEEBEFFDEGGBHBEBHFCDDDDGHAFBFBFCACHCAFGCGHHEDCBFEFABCDCEGGGDAEBBBEDEFFFFECGHEHF,False +60,11.0,9.0,7.0,2.0,10.0,10.0,11.0,9.0,HGHCDCHCACBCEGEGEGEBBHCFGABEBFAEHHFBFAAGHGHFHABABCGEGFDEAAABFEFEFGFGA,False +61,23.0,23.0,21.0,24.0,24.0,17.0,27.0,24.0,EDGGCBCFCGCGCFCGCDCBAACHFHFHECACAGAHFHDBDEHAGADHGEGEBCAEAGDHAADDDDCEAEADBGFDBBBBDHDGDBBGCAAEHEGDGBGBFHCGCDBBBEFHFDAGHCDCHFHFGEHEGEGHGBEFACADAFCBGBGBFHDEDEDFBFEGHGHAHAEEEEGEDHAHACEFBHB,False +62,21.0,13.0,9.0,12.0,17.0,15.0,25.0,10.0,HFGFGBGEDEHGHAHFHGAAAFGHBFACGDBEBGAAFEGEFEFBGAHDEDECBCBFBEGAGAFCCBBDBAGABAGGGGGECDADAGAEFEDGACADDCDHDEAFHFHFGGGFGCABAEEEGE,False +63,6.0,6.0,3.0,12.0,7.0,8.0,6.0,13.0,FHEBEBHGHDAGHDCDEDEAFCFCHEEBAAFDDDFDHDAGBGFDHGHAHDHEHFHFHBDBG,False +64,6.0,15.0,15.0,8.0,14.0,13.0,8.0,8.0,CCEDEDBHHGDCBEFEFCCGCEAGFGEGECAHAHGBCFHACEBEBEGEFFFFBDBFBHBDDEDCBCBHBFGFHEAEBCBCFCBCAFD,False +65,6.0,4.0,3.0,4.0,6.0,8.0,5.0,5.0,CGCFEFAFAEEDEHCHBBDAAFAGHEHEBFDHDBAGFGFGF,False +66,17.0,8.0,15.0,6.0,16.0,16.0,11.0,12.0,AFGFGFGHGFECECECHAECCCFAHAFAEHGGCEBAFAEAEFGGHCBFAAEHFHFGBHEHGAFBFHCECEADFDBDBCACACAEAEBEDDACBDFHFHEGC,False +67,24.0,12.0,23.0,14.0,18.0,18.0,15.0,12.0,CCCFCFBHAEEDFDBAADAEAEABDBDGEHEGCCCACECHGEGEDECACFCFCHBFBAGAFFGHADBEBAAAAFAEECEDHDHECGGBHHCHDBGBABAGEFFGFAFADACADAGADCHFECGFGFHFCDCEGFCC,False +68,31.0,17.0,27.0,38.0,29.0,28.0,14.0,16.0,ACACBCFDGBHBDEGEAHDDEFEFEFEFDDHECEBDFDAEAEFECECGCHAHAHCBCDAHBDDDDEDEBEHGDDAFEFCFDDBCGAGACCECAADADABAFEDACGCAFAHDFDBDGCECBGBFFCHCGAEDFFFHADFDADGFAFADEDHABAGAGEHEFBFECEDEDCGEADADFDHBHDFDCBCFCDAFAECFCEHB,False +69,5.0,4.0,3.0,4.0,2.0,3.0,6.0,4.0,DAHAGAHAHAHFGCGEBDFDEDGGCFBBGBC,False +70,5.0,7.0,9.0,5.0,2.0,11.0,6.0,10.0,HAHDHDHBGBFCACDCHFBBHBHGDEACACEGFCDHBGFGFGFCCHBFFHFCFAF,True +71,11.0,10.0,6.0,19.0,14.0,23.0,11.0,9.0,FHFEADABECHFFDFDFHFEDECEFEFEFAFHDADAEADDCAGFGBBHGDGABDDFFFFDDDADEEGFGDABCDGGBHDHFGAGBHBHBEBEGFFFFFCCEDE,False +72,25.0,17.0,20.0,19.0,16.0,13.0,17.0,22.0,GDCDHGBEAEGDGEBDBDHDCDCBHDEAEHDCEFAAABCDCDABAGADADCFAFCGCACAFFBAHGCGCGEGEACHHECACECEHEGGFBDHFHAHAHGGDGFCECHFHFHCHFABABFDGABDEDABABHEACAFDHHGHAHBBBBEH,False +73,15.0,19.0,20.0,23.0,23.0,21.0,22.0,23.0,GFGFECGCEEGHFCBCFDDDHHGBGHGHDCDCFHAHCCCFHAADEBEHEDEDADCDCABEGEFDFHCHGGAHAHFCFCEADFFECGBDBDBDCCACADHGCGEGHFHGHGBFADEBEBEDGDBBACEEEHGBDBFFFFDGEGDGDGFBEHHHHAAEAEFBBBBEFH,False +74,3.0,11.0,6.0,11.0,10.0,12.0,5.0,7.0,ECHFHDHEFFHHDCFGEGFDBEBEFFFDBCBFEDCDCFEBBFADDBDBGBGBGBAHAHFDEDECE,True +75,21.0,13.0,22.0,19.0,30.0,19.0,18.0,19.0,HAHEEEFEDHDFDBHBGCCEEFEGGHGHCCCCCHGECEAHDBDBEFGHCACGBEFEHAFDFACAFEEEHABAGAFDGDADADAGBCBAEADAEFHCDCFGEHFHDEDCDFEFCCCEAEAEGGABFGEDBDBHBCCECEHEAEFGHGHDDAEAEHCFGFGFB,False +76,14.0,30.0,18.0,20.0,25.0,19.0,27.0,30.0,FCFBAEDEGEHEBGHGFEFCGDBDGGCGCGBEBHBHEAAAEECBCBCFHFCFDGAEHHFGGGGGHCHEHBABGBGHHDFAEBDBDBDBCCHAGGEGDGCCBCHFGFGHGHBHEFGHBFBCBHEHBBABCBHBCGEHEADDDBHFHAADEDBFHFEEGEDHDHDEDBDFEFEHCHAEGDHBFBA,False +77,25.0,17.0,30.0,29.0,22.0,22.0,23.0,24.0,CCHEAEHBBCBDADBDBDHGFEECBDFGFEAHDCGCDHHEHEHCGCFHGDGAGAGACACDDDFDFDGECCHDHCCEFAFEBAFGGHDCCGEDBDBDBCHCACDBAHCGCGAHAHAFFFHADCDCFCFHHCDCAEAGAGAGABFHGEGBGDFHEBEFCFAGBEEAABAGDGDFDFEABHCDEDEHEHEFCFCD,False +78,9.0,16.0,9.0,5.0,4.0,15.0,4.0,5.0,BCEADCBBBBABABCCEHFBDHFAAGAGHCFCBCBFDFAGAGBFBDBABFFFFFCEHEBDHFFFBFC,True +79,19.0,17.0,10.0,29.0,13.0,8.0,14.0,14.0,DEDEAEAEDDDDDDDHDGEBEFADAGBFFHDGFBBBBGBABFCHGDFDEACBBBAHADAHCGCAHDHEHABAGCGCGEDAGBDAACAHDBCBGBGBEDDDDDADGDFDHHFDAHAEEEHCDCHG,False +80,9.0,11.0,7.0,9.0,14.0,3.0,11.0,16.0,HEHEACBHBHAGEBEAEBHBHBDEDCFABCGAEABHEHDADABABGGGDGHECEHHDGDHHCHCDGFFHCBEDEGEGHGE,False +81,4.0,9.0,4.0,9.0,3.0,6.0,6.0,5.0,BGBACACHDGDFDFBFEAHFBDDEDEGHGHBBBFBADHDGCGDBFC,False +82,11.0,21.0,22.0,24.0,26.0,28.0,21.0,21.0,EDGDCDCFGEDEFFFFGEEEDEDEDADACHCEBAFAFCHEDBFEDHDCCAHGFDFDGAGEFECEDBHCECDGGGGGBGFGBHCGDGFFDCAGDBCEHEGBBBBHFHADFHCHCHCACHCBBEFAGBGBEBFFFHFBCEDFFEFHDHFHFCCECBHBDBDEDEHBHEHFBFEGAG,False +83,2.0,4.0,1.0,3.0,2.0,4.0,2.0,1.0,CBFHFBBDGDFDFEGEABA,True +84,18.0,13.0,21.0,13.0,16.0,19.0,15.0,8.0,CBCEEADAFGDCFHFHDHFACACEDGACFGGGCBABDCCCCCCBABABABDBDFACGCGCFCAGEFEFBDBCFEFEAGFDBEFEHEHBAEADAFAFGEGECAHFEDGDHHCAEDEFCFGGGBF,False +85,14.0,12.0,10.0,10.0,16.0,19.0,9.0,12.0,FGBGHDEEEGBFAEAEDHGHGFEDEFEGEDEFEFCBAHCHCFBFDGECFFFGAECBBBDGFAFACACBEDABEBFHFHFHAHAHFEDCDCFCAAHBHADAFB,False +86,14.0,13.0,10.0,16.0,18.0,7.0,14.0,15.0,GGGGHADGCGCEEEDEDBAAGBCDAEABAGAFFFDBEFEAHAHBDBDBDBGHAACDHHGHGHDHEFBCDCHCHDEEBEBDADABEFECCGHGHFHDGEEEADBEEHC,False +87,9.0,13.0,17.0,12.0,12.0,23.0,13.0,12.0,EHCHBDDCECFCFCFABABGBFDFDCDHBGDHDGBGCGCGCFCDHEHEFCHGEAFBFBFDFHCEBAFEDEDFFGHCFGBGFGCDCEBGFHFAFBEEEBGFFCFAACAHAHF,False +88,6.0,3.0,0.0,1.0,3.0,3.0,5.0,4.0,GBGAGBHAGAGFEBEFEHHAHAFAD,True +89,11.0,11.0,12.0,15.0,16.0,12.0,7.0,10.0,BHBHDDADCGCAEHHDCEAFAFBFCDEDECBGFCECHAHGCAEDDBDEAFAFHFDCHEBEGEGADBDBHEHDFGFGFDECECECAAEBEBDBFF,False +90,18.0,21.0,18.0,8.0,15.0,18.0,18.0,10.0,BCBDGCBCHGHAAFAFEFAFDFHGGGCCECEHBHFCADAFAFEGBAAAGAFBEBEBEGCBHBFADAECDGHGBGECCBCBABHFFDCEFEHGBGBGBEFGABCBFBDBEEAHACGCGEGFCFCFDA,False +91,21.0,22.0,23.0,29.0,25.0,21.0,20.0,16.0,EDECECBBDBGGGDHDFCFDFAFGBACHDHDADFDHBEAACACACEDECEDGDGEGEGEDEAFCFEGGBEBGFGEDECGFAFAFGHEDFHFCFBFBDEDFDGBHEADHDCCFBABABACGEHAHFHCEGEGHBHDACADFCCHBHDCDCFBHAGDBABEBFBGCDBEBCDDADAEEC,False +92,22.0,26.0,23.0,24.0,20.0,30.0,22.0,18.0,ADAFEGHDHFFFFDFECADDDFHBHDCBFAHCHCACHEGFBFBCDHEFEGABAFAEBGBFFFBFCFGBHBEBAACAHAEDEDEGCDCDCDCGHACFCFHFHGCFCEHEHCGCDCEFGDGBGBGEGBABGBGCCABBBDBAFGDABFBFEFEDADBFEFDBHGHDFEFECBAGGCGADDDGBHAEA,False +93,2.0,2.0,1.0,3.0,0.0,2.0,1.0,2.0,DBDCDGFFAHAHB,True +94,18.0,8.0,12.0,13.0,10.0,9.0,12.0,11.0,HHFAEHCHCHCDDAFACACACGGFEFGCHDEEGCGCGFDDADGDFDEBHCDABGBABDGAGEEBAFABGBDAHAFAFADADEHHCHCBGEAEA,False +95,4.0,5.0,6.0,3.0,5.0,4.0,4.0,3.0,AHBFEADADAGFHFGGCBCBCBCFCEHEBDCEEG,False +96,6.0,10.0,15.0,4.0,14.0,9.0,14.0,11.0,ECECEGHGHEHGDACGHHHFGFGCCCGFEEHEAAACCHCFCFEGEDHFHFDFGEABBBBEBHGCGBEBGCACBEBEGCCDBFG,False +97,3.0,4.0,3.0,4.0,3.0,2.0,2.0,6.0,BGHFHDHDCDBDECAHAHAEGBFBHCE,False +98,14.0,9.0,9.0,12.0,16.0,15.0,11.0,5.0,BGGACFEGEGEAFGFGFGFAADADACBCFDADGEBHBFDFGBBDCGAFAEEFECHCDCBFEAEAEADADCEBDDHDBGEFCHEHEFEAEFF,False +99,24.0,22.0,16.0,19.0,18.0,22.0,22.0,17.0,BABDFDEDEDEHAACABAEAFFGBHFGAHDBCAGADEDCHBBGEGAGAGAGAGFGABEDEDEFCBABDBECECEAGFGEGBGACBFEHEHAHAFBFBCHEFGDADAEEBCBHHHFHFBAGGGFFFFGHDCCHAHBCBCHFGDBCCAFBDGGFDHDFDFDC,False +100,10.0,7.0,6.0,7.0,6.0,11.0,8.0,15.0,GGHGHGFEFDCHAHFHEHEBACCBCHFHFBCBEBFFEFHAHGHDAGADAEGBGHHBAAADCFHFDADFDH,False +101,21.0,23.0,9.0,23.0,25.0,21.0,22.0,21.0,EEEEEACAHEHDDADHFBFBAHGHGBGDGFECGBBBBFBFEFHFGFGFAEHDHAHAHBHGHFBBHGGGGGEHDDDDHEAFBHHDEFEHEDDGBCDCHBGDDFFCAHADEDEGEGEAABBEBDFGEBABCDFEACFDADAGAGEGBAFABHBDGDCEEEAFAFBFC,False +102,1.0,8.0,5.0,3.0,5.0,5.0,6.0,8.0,HCGCHDEBGFEFECBBBFBFGHGHGDGBAHCFCHHHEDEBB,False +103,29.0,22.0,27.0,17.0,23.0,16.0,31.0,26.0,GGHCFGEBEDGCCDEBFFFEFHGCDCBCBCECFCHCHCHGHCEGAGCECABHEEEBEBEGAGBBBABABFBHBHDHGGDADCCFAFEDECEABGBFAFHDAGHGHADEFGBDCHHDEDCHGABABFGDEAAAEBGAAEGGGGFGHAHDBDCCHGHBDGEGHGEAEACCHCACAHGHGHAHDCACAFAGAFA,False +104,7.0,6.0,18.0,7.0,11.0,12.0,24.0,18.0,GDGEHCGGGEFECEBECGCGHGCFHFHFHCDFDFGACHHHGBGHACDCGAGADBCAHECACGHGHBBCFGHEDEFEHGHBHGGCGCGCHCEGGDGEAFFHFCF,True +105,16.0,23.0,21.0,18.0,22.0,17.0,10.0,18.0,ACEGEHEHAFACDCDCHFBFBGBHDFFFCAGHBBBHBHFABABABAHEGCAEEEFGBGBADGEBCDEHEBCFCHBHEFEBDDDDDDDGFEDEFEHAHBCACACBDBDHDCBCEDEHEGCCFEEEDHHAABCFCHAECBCBFFCFG,False +106,9.0,10.0,12.0,6.0,8.0,7.0,13.0,7.0,FABABHCEGEGBGBGCCCHCAAABGEGDGFGFAFCBCGCEHDCCAGHDHCAEHFBFAGBGBGHFDCDBEEDE,False +107,17.0,15.0,17.0,17.0,16.0,26.0,15.0,17.0,EFBHGEAFDGCGFGFGDEEAEGBDEFBGGFAHHCAFAFHBHBDGDGEGEGDFFFDFHHHAHBCDADBCBFGFCBCBGBFEHADAHCECFCECHBFFFFCDEDEDCDEFEFCHHHCACAEBCGAAAAHADAFHFBDBCFDF,False +108,20.0,24.0,27.0,23.0,19.0,28.0,19.0,18.0,AFAEGFGFGAHFCFEHEGDBBBEBEBEBCDDDHDFGFDCDCECFAFAHAGBBBEBFDEBCBAHGFGAGABDBEAGFCCCBEBHCDBDFDFBBHCHGGCDCDFHEHECGCFFFADAHHHDCDAEEBFGAEHCDDGACACACFCBEFFHAGCCCCEFEFCABDBFFFGHCHDHDFDGBGA,False +109,9.0,16.0,17.0,17.0,16.0,16.0,12.0,24.0,EGDDDAHBEAEABDCEBFFHFHFHCDGHAHCCFDFDFDFBBEBFBFEHGHGDCFCGHGHGCBCEDHBCDHFHFBFGDGACCCGAEBHBABCHHEHBDDEHEDEDEGEAHDHCECFCFCBHAHEGBHH,False +110,5.0,7.0,7.0,3.0,11.0,14.0,10.0,14.0,AHEHDHGFEFGCHFGFBBCAEFEFEFECEHFHBHAHFCBGFABHBEDEGCGFDFACGCGBFEFGHHHHEHG,True +111,20.0,16.0,22.0,22.0,11.0,17.0,13.0,10.0,ACAFFCDCDCACBFAFGDAACDCDEDEFFCBHDGDCDGDEABFEAADDCAHHDHEGACEFBCBCACACABBHDHDHEHCAAFAFCDDEDFDFBFCFBFDEDFFGGAGCCBEBCBHBAGGGGGEGACBHBDB,False +112,26.0,22.0,28.0,29.0,20.0,26.0,21.0,19.0,GCDCBAEHEHGGFABGFFFFBDBDBHCHCHAAADGFCBCDCFFFDCHCECEDEAFBFEFEGGCDCDAEAECFCEEACCBABGFDABADAFHBHFEFEAHAEADFCFHHBHAHAGGDHCCCDHBCADABHBDCGHGAGAGDDDFCAGBCBDBCFCFEHEDEBGGFGFDBCGAGDCDEDGDBDBEFEHAFADD,False +113,4.0,0.0,3.0,3.0,1.0,0.0,3.0,3.0,HAHADDGDHAGAECCCG,True +114,15.0,25.0,14.0,19.0,17.0,16.0,17.0,18.0,GDGCHHEBEBHBEFAFEFBFHFBGHEFEFEBAAAGFGDDFDFDFDBDBDBABABDHCBGDHCEBBGBCBEBAGHCHBEBGHEHEHEACACACACBBGGFGHCHDGBCDGEFDFDBEHECDGBCEHAHDHACFGADFDBAGD,False +115,4.0,7.0,3.0,5.0,3.0,0.0,6.0,6.0,HGHBHBDBABACEGDGEAHBHADGEGCHCBDGDB,True +116,18.0,19.0,11.0,27.0,26.0,22.0,18.0,28.0,FDFEHEBGBGBCFDFDFBEGFABHCHEEFAFAFAFBDHEHEABBDCHCDDGEHEADAFAFBHHCHBFBEDHGHGBFDFGECHHABDEGECEDADEHEDCAHAGEBABCDCDAHEDEDEDFFFFFBFHGAFEGEGDHDHGHGHGEDHDGEGDAHABBHHDHBCDADHEGE,False +117,9.0,10.0,11.0,5.0,12.0,11.0,5.0,12.0,HFBFCFBAAEABGHCHAFABBBBCCCHCECECHCGEHEHEHFHAHCEDDFDCEEBFFFFGEBEAFAHDGBGDEHA,False +118,1.0,8.0,6.0,3.0,6.0,11.0,9.0,8.0,BEBFGFGFBFBGBCDFEHBHAGEFHGDEFBFHHCGCDBGFGFGHCHFHCECE,True +119,16.0,21.0,23.0,14.0,8.0,20.0,24.0,21.0,EEGFBBADAFCBHFACCCFCFEFDGAFHFDABHBCGHHHBHGHCHEGCAABBGDHBHBGFGCGCGCGHFEFCFGABAGGCGAGACFCBCBHBFCFADHDHGHGFDEBEGCGCDBHBEAACHDDFDCDCFBFBGGGGCBHDHDHFABA,False +120,23.0,16.0,16.0,25.0,12.0,20.0,24.0,21.0,DFHFBBDGFFEDCHEEGGGEEADAGAGDBDAABFDFCGDGAABABABABACAGGHDHFACECBDDFDHGHGHBCBCAGFGBGCFFFDFDCGHGDEEHBCDCBHBCFGFDFDHAGCHHHHHGAFADDHEHEAGAGAGHCBAEAEDCDADCFGFDHDHF,False +121,19.0,17.0,15.0,20.0,28.0,24.0,23.0,17.0,DCDFFGAAFFFBGAGDGCACHEHDADADFEHEGGFFEFAABBHGGGFHEHACACBEEEHBAGAGFDFEBEGEBECECDCHBHGDGBEFEAEAEAECCGCEHBHCFFGBDBDCDAEEEAEFFFBHAHGEDEBGFGFGHGBGBDFDCDHEHDDDEBAFDFEGCFH,False +122,24.0,21.0,31.0,19.0,20.0,33.0,21.0,17.0,CBDGEGCBFGFHFHFEFBDAECCCBCBGHDCCCAFADHDHDEDACBDBGAHABFDGEGCHEECECDAFBGBGBFFFFHEAECHFHFHGEEBCFCFDGEGFFFFGCDCGBGBGFFBFBFAAAAAFGBAFABECAGEGBGFHFCADDCECHFAFADAHFHEDEHCFBACAEAEFDCCCCCBCHDADCG,False +123,23.0,22.0,33.0,26.0,18.0,14.0,26.0,19.0,DGDGCACABHFCADADGHGEEHGACAHAGACEDEDEDGDFCHDECFCBCGHGECHCHBEEDEDEDEDCBGBGBABCBCBHAGDGECAGDCCCFCDCFHFDABECGBGFHBBFBEBEBACEDBHHCCGCDAGGGFCCCGDDFCBCBGBGHGHGCBADHFFAHDGAAAAABAFDHDHCFCEAD,False +124,14.0,14.0,13.0,14.0,9.0,17.0,19.0,18.0,DCBFBFAFAHBHGFBABECACGGBGCGCFAFHHDGDGEBDADFFHHHHDAABHFFEGAGFDBGHGAGBGHFHFGCHCDGEGEFCGDGDCDCDCECBFAFCFHAHEBEGHBEBHHADAD,False +125,22.0,17.0,18.0,14.0,19.0,23.0,19.0,20.0,AFFEGCACEHAHBHFHECADBDEDHDHDACHCBCBHFDDAGHGHCECEAEAHBHGGCEAFAFBDGFFFFBAGAFAFHHCGDFFAEBBABADADBCGHHHGACACFCFDFBCGHGEGEGBGBCBEEAFHEBBGGECEFECEHGGEAFDFDFAF,False +126,2.0,2.0,5.0,1.0,2.0,0.0,0.0,0.0,CBABCCCECEAD,True +127,9.0,13.0,13.0,20.0,8.0,15.0,15.0,18.0,GGEFDFEHDHDHBAGABBBFFHFCFHGHGHGHGDADHDEDFCEDAGAGCBDFDHDHCBCDFDBHFHGHFBCGDDDDDABGHDHCHAAECFBDBEBCBCEGECCFFHCGAGF,False +128,26.0,16.0,20.0,13.0,15.0,14.0,8.0,14.0,AFAFGCBFDCCGCBCACACAFACECBAFAFDBBABABHECBGAHADEDCBADABABAHEHCHCHGECDHDHBHBAEDEAEAHBGFAHBBCACACAFEDCAHHEADGEGECEFFFCGHDFDEAEFFD,False +129,3.0,2.0,3.0,1.0,2.0,1.0,0.0,1.0,AHABFBEAECCDC,True +130,3.0,10.0,5.0,11.0,10.0,4.0,3.0,9.0,DBGBHBAEDEBCCEBAAFHHDHDCBEDHBHBHBDECECEDDDFDGDFBEGEHEHF,True +131,18.0,19.0,23.0,22.0,20.0,20.0,15.0,23.0,FGBCAABCBCDCDCBBAAADCEGHAFDFEBHBHAHGDAEAEAHGECHCDDFDBEBHHHDBCFCABFHHHABFHHEGEHBAFAFCDCHGEGEFBFEFEDEHCHCHDHDGFAFEBEBGBGFCDCAEDEGFFFHFBEAGACFDDDDHDCCCCDCDGEGBGCEH,False +132,27.0,13.0,16.0,13.0,20.0,12.0,27.0,15.0,HAACDHGHEBFFCDAGADAEABAGHFHDHCCAEHFHBGBECGGGGAGABACDEDCACACFGFGFHBBEBHGGGDABGGGEDECEAEAEAFCEGBBBAGAEAEABHEAEGGGCEHFHDGAGEDEDFDHDEAAGAHAFFGCCCCG,False +133,5.0,7.0,9.0,1.0,6.0,7.0,8.0,7.0,BGCFEBHHHHACABFBFHFCFGGGCCECGCGCHAEBBHFGCGDAEAEBEF,False +134,14.0,15.0,11.0,16.0,21.0,17.0,16.0,20.0,HBHDHFHDDEFEGEFEBGDFDFBBHBAGEGCFHBHDADHHFAFAHECEFADECEDDDBDBDACBEAFHFHGEGCGDECECBAGACHBHGHFHFHGEGFFHEHCHCEGEGEAEGDGEABDBABFFGECABA,False +135,8.0,3.0,1.0,2.0,4.0,6.0,9.0,3.0,GFGEGHGFEFGCGDBAHAFDEAEGBGBAAAFAGAHF,True +136,14.0,29.0,20.0,23.0,25.0,22.0,18.0,18.0,DGDCEBGFHDBFBECHFEFBDEDCACGCGHEFEFEFAFGGGDCFGFHFHAHADEBBCBCEEEFEBABCBEBACACBHHCFCEAEAGBGDCDBDEDGBACECBHEHBDGDFDGCGAFEFDBHBEBEAHGFCFBFBHEDFDGDBBBBACDBDHGBEAEGFCHBHEHDHDFD,False +137,3.0,5.0,1.0,6.0,8.0,6.0,3.0,5.0,FDFDBBBEDEHEHEFEACFFGDHDFGBHAEAEBEGDH,True +138,17.0,19.0,28.0,23.0,19.0,29.0,14.0,27.0,EEHFCDHDHBAADFECECFFFCDGBAHAHFHBCDDFDGDADBCAAHABAEGFHFHDHDEGCGHGHCFDFEFGBHAHBCBABEEECDCDEHFHFBABHCCCACHEACHDGDFHFHBHFGDGDGDFBCDCGABFFDFECHCFFFHFCDGEFCACHCHCHEGACFCFBFEEECEBBBBD,False +139,18.0,10.0,15.0,7.0,19.0,9.0,15.0,15.0,BCDGAGEBBAAFCBEFDFHCAAHABFEADAHGCCCACEDEDEDEDEHCBCFEHCHEACACHGGGGBGEGFGFEHECGFEAHGHEHEHEHACAFBGGABABHGHEAEAC,False +140,12.0,11.0,10.0,15.0,15.0,9.0,10.0,21.0,GGDEDEDHDABGBDCAFADADEEFHFEEBBAHECFCAHGHGHEBBCBABAFHHHHAFADHECEGGBGECECHBHECFCDDDEEHHHHHDHDHDHFACGDABFG,False +141,6.0,7.0,16.0,10.0,19.0,4.0,7.0,3.0,GAGEECEDBGBGFCFCHCFBDBDECEAEDBDCHBEEFAHAEAEGCBCEADDDDEGCCEEEECCCECDCGCEE,True +142,17.0,14.0,17.0,18.0,21.0,18.0,15.0,9.0,BADAGADHDGDGFHFAFDFGEEDDDADCCCGGECCCGEHAHAHEEEEAECFCDHDFABABFBGBCACEFFDADAEEHBHFDFCBEBGHGCFCDAGFDBEFFGFGEGCBAEDEBCBAACDCBEBEFEFEG,False +143,1.0,3.0,4.0,4.0,2.0,3.0,3.0,3.0,DHDCCGCGAGHBBFEFCFDHDEB,False +144,3.0,1.0,7.0,1.0,1.0,3.0,7.0,2.0,CDCFHGGFBCCCCGAGAGAEHFGCG,True +145,3.0,5.0,7.0,4.0,3.0,11.0,6.0,3.0,DHGEGBGBGCCFDFAFHCBEBEBDFCFCFGFCCAHFFFDGAF,True +146,4.0,13.0,6.0,8.0,6.0,15.0,9.0,3.0,FABGBGFGFDBBBCGEEEEBFGCBFBDBCFDFGFGFAFECCDDADAFBDGHGBFBFHFEFHCBD,True +147,16.0,16.0,22.0,23.0,21.0,20.0,35.0,29.0,FBFEECGAGFGFGHDHDFAGEGEHFHFHFEGHGCEEAHDGDEHEGEFHFCFHGHBECDBDBHHGGGGGGCBHAHACAHAGEBDCEAGGHGHGEGEBDAHHHCHADGCFBFHGBGCHDFDFDGHCBCHHAGBEBDACHCFFGGGDADEEAGCEDEDCCCGDFDBDGFBFBGBDEACACDCDCH,False +148,16.0,20.0,20.0,23.0,21.0,16.0,31.0,18.0,EBEHGGGHCACFDDDDDAFCHEGCACFCFDFAGADEGGGAGEECEGEGEGAFFDCBHBHDHEGCDCGBGBGCCCCCBDGEBCGFHCHGHAHBBCEGEGEBFBGAHABDBDAGAGFGBEEEFEDGDAFCHBABGBADADEGFFDHDCFGGDHBFBDEDEDGHHHBH,False +149,3.0,7.0,4.0,6.0,10.0,7.0,3.0,5.0,EBEHEBEDCFCBBADCHFHFGBGBDEEEECHBDADADEFFFGFHE,False +150,6.0,2.0,7.0,6.0,2.0,3.0,8.0,0.0,DDDCGCADFDFGGGACACAGBECGGDGABACFCE,True +151,5.0,2.0,2.0,0.0,5.0,4.0,2.0,3.0,GAGAFBFEFECEFHABAEHEACH,True +152,14.0,12.0,9.0,7.0,12.0,11.0,10.0,17.0,FDHDFEHDHCFCBCDGHGCFFFBFHACCHBGAGAHEHEBEAADAHBGBFBFBABABAHAHEEAFHEHBHEHABGGECDCECEAGDHAHEFGG,False +153,19.0,24.0,27.0,19.0,23.0,23.0,26.0,24.0,CDCGGGFAAGACHFHDHDHBBCCHCGFAHABGBEDHBGBGBABADECFFFFAGGCHDDGDGCGHGHGDCFHDHAFEFEFEHDCCGGBGEGAAFCEEDFDFGBEAFHFCGEBCBHBFBDCDGBCBEHADABCHCHEHEHBHDGFGAGEGBBEBHDEEHAHAEAECCFFFCCCECECEFBFBDECBA,False +154,13.0,10.0,11.0,9.0,11.0,8.0,12.0,4.0,GEAEAFAGADADAEFCGCGCGCAFBFBEECEGADADACBGBCHHBFEECACBEHEFBFBDADEDBCGGGBDFHCAGGD,False +155,23.0,15.0,20.0,21.0,22.0,13.0,16.0,23.0,FEBEBEBFDHDHCCDDBCBEGFDFGBHCHFDAEBCBFHAHGHDADCBGDHDHDFCAHHHDBCEHDFDAAECDCDCBCAFEEEEEAEAGACHCEGEAEGGGGAEABAFAFHHGEAAACHFHAHFGEAEDEDEDADHDBCGAGACBCHHBGGCHC,False +156,1.0,2.0,8.0,2.0,1.0,1.0,0.0,3.0,CCCCCHCHBACDCBHEDF,True +157,11.0,6.0,5.0,14.0,10.0,10.0,2.0,6.0,EFAHAHFBFGGABADFCBEDEDADAHAFAHBFEDEDCDEDEDEDFFCBEDFDFBACDDAEHCHA,True +158,15.0,22.0,16.0,16.0,9.0,21.0,17.0,9.0,CFCFCAEBDGDHBBFBHCAAGFFFAGGGGFGHCHDBDBECECECFHBBCBAFHFDFBCACHCAAAEFDBDBCFGAADADAGGBBBGCGBGCFBEEGHGFGFDFDFABABDFHFDBDCEFEBGDDB,False +159,3.0,6.0,10.0,6.0,2.0,3.0,4.0,5.0,GGGFDFDBCBHBHBCCHCBCEHHFCACDCBEDDDACGCA,True +160,7.0,12.0,7.0,6.0,6.0,8.0,8.0,5.0,AEFEFEBCBADCEFHHCHGBBECAABFBFBDBGBHECGDADADGBGAHFFCFCGDGBGB,False +161,25.0,18.0,13.0,27.0,15.0,21.0,17.0,28.0,HFHGDDBDFDGHGADHGFBHGCFDAECCHHEFEFEDDBEBAHAHFHFBFHAHDFDFAEDFBBCEHADGFGAHDGDGDGDFCBCEAEBCBHDHDHAHAEADHHFHFHEGBHEDABABACDCAEFDDGFGAGABAHDHDGDGDBHBFAABAGAECECHCACBFAFH,False +162,18.0,23.0,16.0,12.0,17.0,23.0,24.0,31.0,AEABABCBCHCHCFFFBHHEGBABDDDDDHHFHEECFCFCBEDDBHBHBCGHDFAFHCHFGCHHHHHHHCFGFGEHDBAAEGGHEBBHGDAHFHBHBECGFAFBGCAHEHGBBFBDCHHGEAEHGFFFADGEGBGBGCGFFCHGEGEGAGAFABABAEAEGFGF,False +163,24.0,23.0,17.0,16.0,25.0,31.0,34.0,30.0,FHFHFEFGFBAEHHHDHDHFGGDGDGFGDHACAFGDGDECECHCGAHAHBBBBBFFFCGBGEFFHFEAECGGBBAGABABAFHFHECGDECFCHDBACDEHBFBHBFEFDDGCHBHGHGHBEAGFGCEHFBAHACEHEACFCFEAEGEGAGACFEAEBGGFDBDBGEGECEAHHHAGBGHAFDFAFDFGBGHGFGAGHEE,False +164,16.0,17.0,19.0,27.0,19.0,29.0,35.0,19.0,GDGBCCGCAFBFGFDHGHBFAFGFGDDECECDGDCDFHFGFCFHFEABACFHFBFHEEECEDFDEDGGGDGCCBBDBFBABFBGDEDEGBHBDDDGGGGCFHFGFGFHFEABBDCDCHCGGGDGFGEDADHDECEAGAFAHEHADAFFGGGCABEGHCAEFGFGAGDDHDHBCEHGAEHFH,False +165,10.0,7.0,7.0,12.0,6.0,6.0,5.0,8.0,DGFFDCDCDAEGDBDCEBGACECHCECDBABDEAHDHGAAHHHFHFBFBGBHDADADAFAE,False +166,17.0,18.0,17.0,16.0,20.0,19.0,17.0,15.0,CACAHAFBDAAADADHBGFAFDGDGDGHHFHFGFGFHHCAAEBFBFCFAHEBABEEGEGEGEBAHGDCDGEBCHEGDGCFCEEFECBCFHBHBHBADDFBFBGDCBCFFEGCAEGEFBACDCECECFDDADEEEGHBHB,False +167,15.0,4.0,11.0,15.0,21.0,12.0,17.0,17.0,HHAHDEDGHFHEHCHGFGFCECEGEACFGDGDCDCHADCEHEGGAEEBEBFHHHCHCHCFDAHAGDGFGDDHEEGCAEDEABAEGEGHGDDFAAEFGAGAEAFAFDFEEBED,False +168,8.0,4.0,9.0,2.0,9.0,7.0,3.0,7.0,ECECBCHFHCGFGFEEEHEHECAAHAFFBAEAFHBGAEAHDBDACCCFC,True +169,16.0,14.0,9.0,11.0,11.0,11.0,12.0,11.0,DFDFDGAGAGAGFGHHACBHBHGFFDFGBCEAHBDAEADACCECAAEABBHEAEAEDEDCABABCBGGGGFFACHHBDBFFDFEEGBCDHEHBHB,False +170,4.0,2.0,1.0,1.0,6.0,4.0,5.0,2.0,GGDBEEEEBEAGFFCFGFHAHAEAG,True +171,28.0,14.0,20.0,10.0,8.0,25.0,20.0,36.0,HCHCDCGCDAGAGHGBABAFAFCFAFDFGFGEGHFEFHBHGFGCHEHABFGFHHHCFDACHEFBHHHCHAHGBAADCHBHBFAAAHHHFEGCGDAHAGFBFAADAEACFFGAEAGABFCHCBFDEAGAHBHBAAHHHFHFHCCACGHGHDHDHCHCFCBGF,True +172,3.0,11.0,4.0,4.0,5.0,7.0,5.0,5.0,BBBEBHHCCFEFGFGHGBBBGBDFAFACEHFGFHDBDBABCDEE,False +173,8.0,13.0,6.0,15.0,4.0,10.0,15.0,7.0,ACDCGBGFFFGEGBGFHBHDADHDFGBGBGHCDAGGGCHDHGADDDDDDEBBHBFBFGFAEADGCCBDBDGAAEFBFB,True +174,10.0,11.0,8.0,10.0,13.0,7.0,14.0,11.0,GCGCGCGFGEBCAAEEHEAEHDHDGAADADADFBEDECHCGGGHGEEHBHAHABFBEBHFADGDHEECHBBFBGEGBGDCFBFD,False +175,23.0,12.0,12.0,24.0,26.0,34.0,26.0,24.0,CDBFHAHBGAAFEGHAFGCAFGFGBGBEBEAFGDGDFDADCFGEGBFCHABFCGADHFFEFHFEFEFEDHFGCGEGEAABEGAGHGEAFAFAFCFAEDEDEDHDHDHFFFGFHACEFHHHDHDAGFDFGEGBGDHDBABAFEEEHEBGFGEEAEAHHFDDDGHGHDFCFCACHDDEDEFHC,False +176,18.0,8.0,20.0,16.0,15.0,17.0,11.0,11.0,FCFBECGAFAFABAEEEEDCDAECEDGAAADFHBDBECEHEABABCDCHBGEHAHAGAECHHHADCCCCFCDCDAGCFFEEAFAFGDDFHFHFHDBGGDGDADFGCECFCGCDCFF,False +177,13.0,12.0,13.0,12.0,6.0,11.0,5.0,9.0,DABFHGHCBDBDCFFGABAFEBACAHECGDFFHFHFDFEFCHCBCBAECGCGCHEAEADDDBDADAHHBACABACDCDBFB,False +178,7.0,14.0,10.0,12.0,19.0,22.0,10.0,9.0,FDECFBFDFDFHFGCEDEDEFHGBACCEGGAEBEGABFDFDFCHGHFFEDBFBFBFEGEHADAEFEFEFEABCFHDHDAECFCGBFBGBFBEECECDBEBHGH,False +179,2.0,2.0,2.0,1.0,5.0,4.0,1.0,6.0,HGFEHEHEFEDAFHFEABBCHCH,True +180,2.0,5.0,1.0,3.0,3.0,4.0,0.0,0.0,FAADBBBBEBEFEFDDCF,True +181,6.0,7.0,5.0,2.0,1.0,4.0,3.0,6.0,BHBDBAAGAHCHFHACAHEHBBBFCFCACGGDBF,True +182,2.0,3.0,10.0,6.0,8.0,6.0,4.0,4.0,BCBCECEAEDEDHCCCCHEHEGDGCFFFAHGBFFFECDDECGD,True +183,27.0,20.0,35.0,20.0,19.0,18.0,17.0,19.0,CHCHCFCBDEHBHEHCCCCBDBAADFFECCGCAEAFAHCFGDGAGACABFEAHCBDBDBDACGDEDEDEHEBGDGDCAGABEBEAECEGAGFGCABFGFCEAEAGACFCDCFFGFEHBDBDECACAFHBHCHBHBFAHDBCADHEHACAGDDDGCEBFBFCCCCGAHCFCACAHH,False +184,21.0,29.0,29.0,14.0,13.0,23.0,22.0,20.0,HBBEFAHAHDHCHCGCBCAFABDDHDFAAADBDBEBCBCBEACGCGFFBFAFHGHFCFEHCHDADFCFCEDBGBCCFCFGFHCHCACBEAFBECFCDAGGCGFGHGFGEGACCDCBHBACGFGFHFBFGEGBCHCBCDEBBCHGGBGBDDFAAAEBEBABHBABHGEGBHA,False +185,16.0,21.0,7.0,5.0,16.0,12.0,3.0,15.0,BBBHGHBACDBEAAAFDHEHAGAGAEEEHHCAEAFBBABFBCECAFAFBFHFEDABBBFBEBEBEBACHFHFHDHBFEAEBHAFCHEDECEHBHB,True +186,26.0,34.0,20.0,22.0,24.0,21.0,26.0,17.0,HFACACHCBBBBHBGBEHFHFEAHAEAEFDBHECAHAHDDBGEDCBEGGFGECAAADBEBGCGCFCFCFBFBFBAGCBBABEHGCGCGFGBBCHCEDAHBCEAEHDBAHGGDDDDHEADDDDDFFGBGAGBGBEBABDBDGDGBFBDBDBDHEFEFCFEAAFGEBCGEGBFFGCGAABAGCHEEEAFAEA,False +187,3.0,5.0,0.0,1.0,1.0,2.0,2.0,4.0,DEBGHGAFBFHHBHBABA,True +188,8.0,11.0,10.0,11.0,8.0,19.0,14.0,12.0,HGFBFHFBFGGAHDDEBAHFHFHFCEGFGFGFGBGEGBCEEAFDBBBHFHDBDBGACHCHFGCGFGCGFBCDCDFFAEAHAEFDFDHAECDCD,False +189,24.0,32.0,23.0,32.0,21.0,21.0,20.0,22.0,BBBABAEECDDDEDEHEBECEDEDHHHFHFDFHCDAHAHDBGBGEGFGFGFGFBAGCGDFBFHDHBBCHGHGFAEBEDCAAGFDDADADBDCFGHBABDHECBDBAAHADAGCDCBABABGBHDCGCBCGFEBDCHAHCCCFCFEBABHDDBGBHHCCCGBABDBCEEGHAFEFEDDBAFFFDFDCEAEAEGDBD,False +190,13.0,10.0,11.0,9.0,7.0,16.0,9.0,11.0,AGCHAGCBAHCBGBEBEACADADHDBFBDDAGEFCFCBHDEFEFHFHGHDFGFACAEFHAEAGGBGFCFCFHFDFCFCBBFDAHAH,False +191,14.0,3.0,6.0,9.0,14.0,7.0,4.0,6.0,EAEFDGEEFCCCFCFEAAAEADCDAEAEGGAFHHHHEAAADADEFEBDBAEGECEADFDHDHB,True +192,6.0,4.0,7.0,3.0,3.0,3.0,1.0,4.0,CFGEHCCFCBCEAEHCHDADADABBBACAFH,True +193,29.0,36.0,21.0,12.0,18.0,14.0,23.0,24.0,BBHFFFCEHEGEHDHBGBHBHDEBHBHBEAEBDBFHFHEHABADACGGGADBBHHFBBBAAAAABECDCACHCAGACFCFAEAFAFAGGDAEBDBHBEBGACBHFAFGFGBBCAGGBGHDCBBDGEHEGEACACACEBEBCACAEGDGHCBDGHGHBBABCCHCHCHGBAEAGBFBG,False +194,6.0,3.0,5.0,1.0,2.0,4.0,8.0,5.0,HBHGGFCFCACAEABGEACDCHBGGHGAGAFHFG,True +195,3.0,6.0,4.0,7.0,9.0,15.0,5.0,10.0,HAHEHFGFHHGHGFFCFCEDEFEDBGBDEDACBDFHEBFHFHFEFDFCFDFABEBGHFE,True +196,2.0,2.0,8.0,2.0,3.0,5.0,4.0,4.0,CCECHCDCDCEBHCGEHBHGAAFFFFGFGC,True +197,0.0,3.0,4.0,2.0,1.0,2.0,3.0,2.0,DBHBDFCCCGCGBGEFH,True +198,9.0,8.0,9.0,4.0,11.0,7.0,12.0,11.0,AAAFADHGGGFGCBCBCHEGEFEHDCABDHGEGEGDACBFHFBEBGBECEHAHAHGBECFCGEGAHEHCHF,False +199,9.0,8.0,10.0,11.0,7.0,10.0,5.0,6.0,ACADDFDHDABGCDEBEHAFFBECECDBBABAFAFAEAFHDDDHCCDCGCGHGDGHFCBCBFFEFE,False +200,15.0,9.0,5.0,13.0,12.0,23.0,15.0,22.0,CHGFEHBDGDHEHAHDFDFAEBDAHEFEFEGGGGAAAGEDAHGHGHECEGFGFGAGBFEFAFBFBGBDFAFHDHBHFHFHGDEDHFFCFEDBDHFFFAAHBHAHFCFDHHCHAA,False +201,8.0,4.0,6.0,6.0,2.0,3.0,2.0,2.0,AGCFBBCBCDAHABACEHDADADCDADAEFGFC,True +202,15.0,30.0,30.0,30.0,15.0,29.0,25.0,23.0,DFBBDGHBCEDBFBHBHBCBHEGGGEBEBHHEHCFFHFGBHEGBDFDFGBGDFDFHCEFHCGCFDHDFDEHADADEBCFEFDFEFECDAAHFGDDDCACACACACDBABGGEDAABBBGCACABFBGDCDAGGGGDCDFFFGFCBBBDBDHECGHGDGCGCHCHFBFHHHDHCEBFDFDFCFCGCBCBCFCDABHCG,False +203,14.0,19.0,19.0,3.0,12.0,14.0,16.0,22.0,CHAEADAHBHBHBHBGGDBHFHEAAABCBGEFCCHFEBHCHABABFHCCCHBHAGAFCFBFAAAHCFCGEGEHEHEHFHBHEGFGHBEGGGCCFGFGCDAECGCBBGBFBCHCHCGBFE,False +204,9.0,15.0,19.0,11.0,9.0,19.0,20.0,15.0,FAAACCHEGCGDGBHDCCCEBAHDGDFDBDBHCFGFCFCBCBFGFGHGBFBHHHFHEGBGBCAEBCCCFCFCHGAEFEAGCDHGHGFGFGCGBGBGFDACEBFDFDEHEDGHABFHF,False +205,20.0,16.0,16.0,34.0,30.0,20.0,29.0,29.0,CDCFGDGDEFHGHEHEGGBGBGBHBGEFECDCEBGDAHGCBDDGDHDHEBEDDDDHAFAFDEGCHEGFHFADBEEGAGDGDHFHBDEAEAHAHDDDECGBADEHEFEFDACAGEGFGBDEDECHHHEAEFFBADDDDAEAHHDHDCCFCAAAHCFCFEGHHHHGBGBDCHCHDFDGGEGBFBGHFAFEGEGEAE,False +206,20.0,18.0,16.0,14.0,21.0,4.0,6.0,11.0,ABABAFADEDBAECHGDDAAHEBBDBACECGAAAACHEFEBCDHGBCECECEBEFEAECBCEHEDGAHACADAHACECGDDEEECEHHHFECBCBEBHBDBDBDBAGDBA,True +207,1.0,3.0,2.0,6.0,1.0,4.0,1.0,1.0,FCADBDBGBFEFDFHCDDD,True +208,5.0,3.0,5.0,6.0,4.0,0.0,1.0,2.0,DCCBCDCDCAAAAHDHBGAEEDBDEE,True +209,9.0,6.0,7.0,6.0,5.0,8.0,3.0,2.0,FCFEAEGDADABCBCFGAGCFAFABABCBDHCFDFEFEACBDHEAD,False +210,21.0,21.0,15.0,16.0,11.0,15.0,20.0,12.0,CACFFACCCEHFDBGBGBFHFAGDGDADACGGDGBAACABBECECEGEDHDHCABDFDFDAGHGHGBGBFBGEGBFDFAGAEHFDAHEGABABFGAGEBCCGCHBDEDGBCACFBFAFHDBEBHBABADAH,False +211,10.0,24.0,13.0,13.0,14.0,11.0,16.0,23.0,EDEABACHGHAEGGBBBBECECEBBBAHGHGHCBCECDCBFBHBHFHFHFBBDAGFEBHAHDHGCFAGABCDDBEBEDHGHBCCACFDDBAHHHGBGBGEGEGHGFEFHHHDDBBCDEFGFHDH,False +212,19.0,7.0,17.0,13.0,17.0,11.0,21.0,24.0,FGCAHAHFGEHAAAAAHGDGHGFEEGDHHAEAEDCDFGBGDHDGFECECGGEEHGHGHCFBBHBFEEHGHGHDHFHDHDAAAHDECAAACBCECACAHFDFCCCCCCGGGGGEEEDHBHEFCGDHAHAB,False +213,10.0,20.0,7.0,7.0,13.0,11.0,10.0,5.0,HACBEBEBAGEEHEDAFABBFEEEBGBGBGBAAEBBDDFDFDFHCHDDAFECHBBAFAGGGFAFCGBEBEBEGGBFFCBCBCB,False +214,6.0,9.0,11.0,6.0,13.0,4.0,11.0,19.0,ECECBCFDGEGBHEDDHGEBHHGCGCBHHHHHEHEGACABADHFFGCGBGHDDCEEEEBEFHAECBCHGHGHBHAHAHC,True +215,3.0,0.0,0.0,3.0,3.0,2.0,6.0,5.0,HDFDHEHGGGGHAHAEGEAFDG,True +216,1.0,8.0,11.0,12.0,14.0,8.0,9.0,12.0,GEBDBDCCADDBGFGFEEGEGCDCEFEGEBEDCCFBHCEDDGEHEHDDFCHHHBHBHBCDFDEGEGCHCHEHFHF,False +217,10.0,10.0,22.0,13.0,14.0,8.0,15.0,10.0,DCHGECECEAGHEFGACFBGBECGCAEBEHHAGEGFDFDFHEDDCDBFBABACDDHDBDGCCCGHGACFCFDGCGCBCBGAGACECACBCECGDHEHEHECD,False +218,7.0,10.0,14.0,5.0,9.0,7.0,7.0,16.0,CFCECECDHHHHHHHHBBBHEFCCEBDBABAGDFDHCHGACCHCHEFEGHGDACFBGBCEEEFGHGFCBCHAAAB,False +219,15.0,20.0,16.0,12.0,13.0,12.0,14.0,14.0,AGAEAEAHGHFBFEHBHFGGEEHCFCDADACBDBFBCBFGFBBBCCAEGDGFAACAHBCBCDAFHFHECAFFEGEBCBGGCDCDCDEBBDBDBHHHHHDGAGDCHCAGEGABBEBE,False +220,0.0,1.0,1.0,0.0,3.0,3.0,1.0,3.0,HEHEHFFFGCBE,True +221,4.0,7.0,18.0,11.0,9.0,20.0,14.0,16.0,GGGBFCCCFBFDGCFCFDFHFHCDCDHHHGHFDCAGHCBAEEFEFEFHAEFCHCGEFCCCHCHEHCDCDAGBGBGCDDFDFGFHEHDHFGEGFHFGFBB,True +222,19.0,32.0,14.0,24.0,24.0,23.0,30.0,29.0,EAEAGFDFDCBHFAFADGBHBDAGCDEABDFGEEFFFEEAECHDHBHDGAHHGBGBGBGHCDFDBDBDEDADHFFAFEFGBHBGDCHEDABGBEBCDCHCBFAFBGBAHFHFGEDFHHHBBBBDBDBDBGEGBHEACCHEGEGEDEHECGHGFBHGHCBGAGHGHGEGEGEHAHAHFCCEFHFAGBGBGDADFBB,False +223,6.0,4.0,7.0,6.0,14.0,14.0,8.0,15.0,CEEFAGEBDFAHHDHFAFAHBFFHFCFEHHHHFDEGEGEDEDGAGHDFGBGBEFGFHHCHCHEHECFCACEEFE,True +224,11.0,10.0,13.0,13.0,21.0,14.0,25.0,19.0,CGBAEGEGEHHCGGHGCCBCAEBEGHCHDFDFDFEGBDFDFEFAGDGAGEGCGBHEEGCGBEEGEADACECABEDCDFFFDCAGAGHFHAHGEGEGEGBGBGHHHHHHDABCEDHHFFDHEHEGFF,False +225,6.0,19.0,5.0,11.0,12.0,6.0,9.0,5.0,GBHBDBABHBCBDEDBGBGBEBEBCCFDHDFEBBDDEAEAEAECFGFGEGABCFGBBDHDEFBGBGEEABHDD,True +226,11.0,18.0,23.0,14.0,12.0,26.0,20.0,26.0,EFEFEFGDCDFBHBHADECHHEHEFGFGHCBGACBGACFDFGFCFGFCCCHHHBHFHFHDADFFEBGFFFFFDBCCFCFHFCDGEHDFDBDCAGGHHHHHHBACGCGAGBGHAAAFFCHGBGCADGBBBCGDHEBEBEBEBHCHDHCCCG,False +227,23.0,20.0,28.0,18.0,25.0,23.0,23.0,21.0,FCCBCEFEDAGGBEHCHCHAFCCADFFHFEFAHCHDGCCHAEDEDFDGAGAGAGEFEBEBHHEFEFHFCGDFBGBDHAHBGAHFFFBFCDDADCDEEAGABHBHGHCHCABADABCHCHCDFGHGHBAFFEGECBGADCECGCGCBFEFDFCGCGDEECAGAEAGAGBBBBBCEEAEDECE,False +228,5.0,3.0,9.0,5.0,8.0,2.0,3.0,5.0,DDDACEHGFBCEAECCCCCFCEHEHEHEBCDAEBDHAGAG,True +229,15.0,19.0,18.0,23.0,23.0,15.0,10.0,23.0,HHFHGHEBFHHBCBDEEHCBGBAHAEDEDCGCGEBBDDDDEDBDHDFDEDACCEEDFCEEECBCBCBCDAFEHCFAHBEDACAGHHHHHHHAHGFACACAFBEBEFFFFFDEBEAEGCBEEDADACBHGCGBGDHDHDFDHDEABF,False +230,15.0,10.0,14.0,14.0,7.0,9.0,3.0,6.0,EDADBFADCDCDEBFBFAFEFEDCBADFBFBAHACCBCGEHEHBCCAGDCFFBAAABAGACHCHDDCCCEDHDADADA,True +231,21.0,19.0,19.0,16.0,21.0,13.0,13.0,23.0,EHBFBHBCDAEACABABEHCAAAAAEBDHDCECACAHGFCFBFBDCCBDBDECHCGCAAHHDDCDCDEEHHHADAFBFGFGDGFGHGAGEEFEHBBDBGHAHGHEBCCACACGEDEAABDBCEDEFEHBHEEEHGHFHEHFFGHB,False +232,10.0,11.0,13.0,7.0,8.0,12.0,12.0,9.0,EFGGGHCHBAEHFDFEADAHBBFBCGFGBCBCBCFHFAFAGCGCEBEDCCCHCHDGGGCGCADFEBEBDAFAFAHEFGBHDA,False +233,16.0,18.0,26.0,21.0,12.0,11.0,22.0,9.0,GBGCHBGDHEHDGAFCFCGCBBDDDHHGCEDEDCDBGBEBCCCCDBGBCACBGGEHEDGGAGACFCFCHCGGDGABDCCCGDBDEDEBBCHCDCDBDAGECECAFEFBFEAGAFAGBGAGDDDACAFAFAFCHBA,False +234,8.0,5.0,2.0,10.0,3.0,5.0,9.0,5.0,GAGBBEDFDFDBDGDAEADHGAGHBDGDFDFCGAGACABAGHHHFED,True +235,28.0,16.0,21.0,19.0,24.0,21.0,12.0,20.0,EDHFBEAFADABHFHFCFHFACCBBBHAHDHBADGDBCBDFEFDHHADACBHBEAEDDDGAGACAEHECFCECHHHEABFCFEEHGAFFFADADCDGEEEGEBECEBBCACAHAHADADFFAFAFHGDEEFEBCGCGCGCDCAHBGEEFGADECECAFAHA,False +236,13.0,6.0,14.0,8.0,9.0,13.0,7.0,14.0,FCFAFAFAHAHCDCDGFFEFECEDBCECDCFHEEFAFACHCHCEBGDHEHFHAHBHDHFCGGAGDHHACCBHDCGFGBAAEABA,False +237,4.0,7.0,4.0,12.0,6.0,4.0,7.0,10.0,DGGHBHDDDGDGCGCGADBHEDEDAGFCFEBDHDEBAHAFEHEHCHDBDBHFHB,False +238,25.0,27.0,17.0,20.0,11.0,20.0,27.0,24.0,BGGGHACECEFEAEDBDBHCGDGDHDHBHBHAHAHFBFGCGCAHFHABABEFFDDAAFHFHDAGADFDGBACCCHGHDAACHCHGBEBCCCBDAFAEGHAHGHGEDBDBCBHBGFEAGAGBGBABDHDGAGADFBFGFGCAEBGFFEHBBGDGBBBFFHFBFCDAGCGHDA,False +239,27.0,19.0,14.0,12.0,26.0,20.0,17.0,18.0,CACHFHBABHBABAHEGBDDEBFAFAEACABAFAHAHGHDFEGEFEBEBEAFCDCHABAGEGEDFBGBACAFDCDCAEHEHFHFEEEFABABCGEEEGHDHAHBHDFGEGBAAAFDHECEAGCGEBEDCDHFAFAGAGBGFFCGCEHGFEBEF,False +240,13.0,5.0,13.0,8.0,10.0,9.0,13.0,11.0,HCHAGAEFGBGAGFGCDCAGAECGCGEFEDHGFADADACHDFDGBCBCFEDEFEFBAHHHHHHAAFGCECACBCGEHEADCG,False +241,15.0,13.0,22.0,21.0,14.0,24.0,13.0,15.0,CECEBACABEFHFGBEFDCDBABGDAEADCDHGFGFDDDFDFDFGFEFGCGEAHGHGHCFCDABFEHHABCECBCHFHCACFBFBHBADFEFEFDFDHDHCHCDEDAGGECHAFDHCABFCFDFDGBGCFCACDCEA,False +242,10.0,3.0,9.0,4.0,10.0,22.0,6.0,6.0,CBAAFFFFGBDAFFFFFFFDGAGEHFGECEFEFHCHCEEEDCFAFAHAFBDEHGHCFEFCFCFEAAFAGC,True +243,16.0,18.0,13.0,25.0,8.0,14.0,16.0,17.0,CFHGHAFGFCFEDAGEBBFDGBGHDHAHBGBGBDCHHEBDBDBDCDHDHFAGGHGHABADDCDFBHAGDDDBCACECAGEGDDHDFDFHFHCGCGCDBAFAFDBDEFEACADADADBCFAHBHGEBB,False +244,14.0,10.0,26.0,18.0,17.0,28.0,19.0,21.0,HEHEHDFDFEGEGFGDCBBDAFHFHFDCEGBBDHFAGBHFHCECHCGAFCCDDADGHGCGAGBDCDHDHDACFCFGACEHEGDGFCFCFCAEFHHHFBFDFDCBCFEFCDGAGDEEFEFHFHFEECCCAAABECFHACECFAFGFCBCGHGHG,False +245,30.0,27.0,23.0,25.0,28.0,19.0,14.0,26.0,AAACACBCAEDEBEFCCHCAEGEDEFGAGCEAEADFEBBBEFAGBBBFDAEAEHHHHCFCHCHADFDEBHFACBFBGBFBCHHAHAEEGHHEAEGHGHGHGCAHADADAEAEAGDGBECHDDDDEFFDCDCACAFBFHCHEHEADFBFBGBDBCGABHBHDACCECDDBDBDFDBEEEEHCBAFHHDBBADF,False +246,9.0,17.0,16.0,9.0,17.0,6.0,11.0,16.0,HGEGACAHDHDCDEGFHBHDHECEDEDFDEEHCFCFHBEGGFABEHHHHGAABCCDBEBECHCHFBAHGCGABCBEBECCCCCEGEBBBBDBABEBHGEGA,False +247,10.0,6.0,15.0,20.0,23.0,16.0,16.0,6.0,AFDGEGEFEDCDFHEGEGFGBCACECEAEHEDDHEGEDEFGDDDCCCCGAGEDBABEFEFDGDHDGDCBHBGFFCFCEEEEFCHEFGDGFCDADCFCAEGFGBEFDADADAE,True +248,1.0,1.0,5.0,2.0,5.0,7.0,7.0,2.0,EFCFDAGFCFGFCHEHECEGGCGDGFGFBE,True +249,20.0,25.0,23.0,25.0,18.0,22.0,28.0,20.0,DGDBDAABACHGHEBDCCABFBAHGGBGEAAGDDFGFAHADADEDFHFHGGGFGFDHDEDBACDGDGBFACABBGBGEGEGECFFFEABDEDHFAFGBCBCACHHFHFBFBFHCHCHCECDGDCEHEGCGBBFBGEFEFHCGCBHGDGFHFEABCCEBDBHGDGDGBHCEDADCDCBAEAC,False +250,27.0,24.0,20.0,16.0,26.0,17.0,25.0,11.0,CHCBCACHBABAGHFEEBEGECEBEBEACDGDHHGAAFGEGABEGAGEGADADABAECFGBGAGAEBEADFGFECACGGFGEGDGFBFGCGBFBFEAEBEFAFAFEDEAAAAGBBBCDCDGECCCBCFADABHDEDEGEAHHBDEDFDFGCCCDBBHAHGBCBEHF,False +251,23.0,19.0,20.0,25.0,22.0,22.0,28.0,26.0,ACACGEBFHHCAGAGHGHGCGCGBEHFHFCAGFGCGHEHAHADDDDAEEEECCFBGHAHAHGBDECFADGCECEGEGDGAADBEAEFHFDGDGAEAFDECBGECCHDEEBGBABEHHAFFFFEFDADHBHBDDGGCGCBAGAHABDBDEFEBCBDHGHGFDFDFDFHBAFCBDBDFFGGCHHHDH,False +252,22.0,23.0,23.0,11.0,21.0,24.0,27.0,23.0,CGGAGEGECECECDBFFFHAHGEGCGAGACEDBBBFGFGHGHFCBGHFHBHGEAHAHABDHABABDBECHAHFCFEFAAGGGBGFCDCBEADADHFHDHCEABCGGGFGAHEEAECCCCGBBEHEHBHBHDCDFFAFBFCEBAGAGCCBCAGFDHHEHFFFCFEFBBEBFGEGA,False +253,21.0,15.0,11.0,10.0,10.0,18.0,15.0,19.0,CFCEEFHBGDEEFEFDAGAHAHGHFHFHGHAHAHGFFFGBDBGAAAABABGBFBFBEACGCEDHFACCFFFGECBAECDGGAFAHDHDHBCCGHAHAFAEDHDHGBBABDFCAGABHBH,False +254,16.0,7.0,14.0,11.0,13.0,17.0,11.0,13.0,CDFHFHECACEDEAECCHFHFHGHGCAHAGAGDEDFDCHCFDADFEGAAEAFFDEDCCEDBFCGCGEBEBHGAGFBABAGFHDHAHAEFFFFFBEBCGHACA,False +255,14.0,24.0,17.0,17.0,23.0,22.0,12.0,11.0,EDGFFFGBBBCACDDDBDCFCFCEEAFGFGFGFDBBBFBDCFEFADAHEDBDFHAAGHCHFGACABEDEDEAECEFEFDAABHHAHCECBFBCBFFDBDGHGHFBCDCECEDEAAGEGFBEBCBEEGEBEBEBHCEFBBH,False +256,15.0,18.0,13.0,27.0,17.0,28.0,20.0,24.0,FBDBCHCGDEDCGAGAGDDFBBBFFFFEDACGCHAGGGEGEBABFHFEDHFHFCBDGHGBGDHBCBGAEHFAFHHHDBDCHBFGFGFHFHEGEBDFFFHAHGHCHAHDHEBEFEDGDGAFABDBEHACFCFCEDADEFBDDEAEADFDFHFHFDGHEDDDDC,False +257,6.0,7.0,12.0,13.0,9.0,11.0,8.0,10.0,DDACHGHGHDHEFCCEGEGACCDCDCDADHBFEFEDEGCFBFDFBFEHCHDAGEDECBCBHFGFDFHAHCGABDBF,False +258,17.0,20.0,27.0,16.0,18.0,18.0,19.0,20.0,AGEHCDAGCGFGDCDCHCACDFEAGFGAAAADADCCHGHGHCCEEEGCADACAHECEGDGFBFBFCHCHCBBDBDBDEFCGCBBBEHFHACAGBCHFFBCBCGGGGHDBECEHEHGHBCAGEDEBFCEEBEBDFCFAFHBADDHFHFHFHECFBB,False +259,1.0,5.0,4.0,1.0,1.0,0.0,6.0,2.0,GGGGBGAHBHCGDBECCBCB,True +260,2.0,3.0,4.0,1.0,3.0,5.0,1.0,3.0,BFBCBFHEEGEHCACACHFFDF,True +261,2.0,4.0,3.0,2.0,3.0,2.0,6.0,2.0,CDCABEHHGFGFGEBABCBGDGEG,False +262,17.0,17.0,32.0,25.0,20.0,22.0,15.0,15.0,DHDCDCDGEHCBGBEBACGDFDCBCFCBCEAEAFCDEBAAEADHCEAEHECDDDBDCDBBFFEFGFBCBHAHFCCECGHDHFHAHACDEHECFCDEAAHABBCHGEGDGFHDDCDGDCCCGCACACFCFDADFGFBFBFEGEGEHDACGDFCFCFGBEBEFCF,False +263,7.0,4.0,7.0,4.0,5.0,5.0,7.0,12.0,GCACAHGHECGCHFGFEDHDHDHGHBAEAHBHFHGCCBCHEGEBHAFADAF,False +264,6.0,6.0,13.0,6.0,11.0,2.0,9.0,8.0,DCFBDBEEEEEEADAHGHGCGDHCHGEACBCGCAHEHGGAFAGCCCCCBEBHDCBCEGEHD,True +265,20.0,25.0,22.0,32.0,26.0,23.0,23.0,27.0,DCHBHBCEHHGHDCGCAHHGHDEEHEHBBECDCGBBACACADDDDDFCGEABGBABEBEBEACFHFBEGHFBABCGHGEGDDDEGAHAEFBFDGDHBFGFCDCDCDFGFHEBEHEHBDEAEACBDADHFBDDDDAFEFBGGGGHGHCHEHFCFGFGADDDDBDADHFEBEBECEADACBCFAFHFDFGFAEGHHCCFE,False +266,7.0,6.0,7.0,3.0,4.0,2.0,13.0,8.0,BGHCABHHCHGGBDBABAFCGEGDGAHCEEGEGBGCAHAHACGCGHGFGD,True +267,8.0,8.0,22.0,12.0,15.0,14.0,10.0,10.0,DCBAAGBEBEHECCCCFEDDDFGHGDEDCBCGEGEGEBFFAEHECFCHCHFHDCDCBHGGCCBCFCHHFAFGHGDFCEADCDCDCEBFAFACECAFEFE,False +268,20.0,11.0,17.0,15.0,11.0,11.0,19.0,11.0,FACAFGDHCEFHAECBCBEBEAEGBGBGFHCCBCAHDCFCDGDAEEEFBACADABACECHGGDBDGGGFHEHADAFGFGFGHGHGCFCDCDEGAAAABDDDGHBACACDGDHAGA,False +269,6.0,1.0,7.0,4.0,8.0,4.0,3.0,3.0,DBGECEAEAEAEAGDGFCHCECFAAHHFEFCCDEDC,True +270,18.0,16.0,20.0,26.0,19.0,21.0,22.0,23.0,BFBCDDGAGACDBDGDGDADHCAEACGCGDEBGDFDCDBDGHEHCFFFFFHFBFAFHDDGBHHHHFEFABGGDGDEFCDGHCHEFCFHBADHHCFCBGBFEEEEEFEDEDAFGHGDGCACDEAEACDEDHBHGHBHBHCDGAEACCEHGHAHACAGACBEBGFDF,False +271,0.0,3.0,1.0,4.0,2.0,4.0,2.0,3.0,HFHFEFDBEBHFDDBDGCG,True +272,16.0,16.0,17.0,14.0,11.0,14.0,8.0,16.0,FCHEHAFAFBFBDHGAFABBCDCDHBHEFABCHCHDAGABEBAHDHDFCEBGDFECECECEHECACDBDBDCGAGAGACAGBFBGDDACCDDBHEHBACFBFHHHFHFCFAE,False +273,13.0,11.0,14.0,14.0,11.0,17.0,18.0,16.0,CDFDGBHBFGFGFGEDABABCHHDDEDCHCGAGFBFDADHDCDCECAGEFEBEAFAEHEHGGEFBHCHFHFAFDFACGGFGHHDHGHAHCFAFGEBCBGBGCACDCDEHGFBAG,False +274,30.0,26.0,12.0,16.0,14.0,36.0,17.0,16.0,GGHCBABACFGFHFBBHAEAEACADADABABFFDABBFFEFBAGFHFBFCFBAHHHHGGDGFGBHBFEECEFDCHCHBHGEAHADDGAFAFDDBDGFGBEFFFFFGFACABGFFFAABAFACAGAGHDABABGDACFEAEADBBFBEDEAFFBFBFCFCDBHEHEDF,False +275,6.0,13.0,13.0,9.0,7.0,9.0,12.0,6.0,CEFBGCCCCHDBDBCAFDFDFGFHHCCGCGBGDGDBCBCBHFGAAEGBGBFBGBGECHCDAEGEFADAHEDEBBF,False +276,7.0,5.0,3.0,5.0,6.0,7.0,3.0,5.0,BCCDFEFEFEBADABCFDDHDHAAEAGFGFHFBAEAGHBHE,False +277,6.0,5.0,1.0,2.0,3.0,3.0,6.0,7.0,HBBFBFDHCGEGAHAHGHGFEBHBGGAEAHADA,True +278,4.0,8.0,15.0,16.0,12.0,11.0,10.0,10.0,DHCHAEEEHEHEFEHGFBHEDEGEGFCDCFCGCDCBFFFCEGDBHFDDADGGCGDEDEDGACDCFCFBGBHBDBCFCHCDDDHCAB,False +279,15.0,15.0,14.0,9.0,20.0,30.0,10.0,19.0,EAFFEFEFHBHBHBHCHCFAAACFCAHGBGBFEEBECEGEFDCEFEGCBFHFBEAFDBBGDDCGFDCBBHBHFEFEHCHFBFDGCHFHFHFGFGAAAAEECEFDBEFECEHDFCFHDHFFEAAAAAFGFHFH,False +280,20.0,27.0,17.0,23.0,26.0,20.0,26.0,25.0,AEDGCEBACABABGBGFDCEBHBCBCGHBAEACBHHHCDDEGFHAAFABCEHDBDBDFFGFCBGGGFGEEFEDEAEDEDHHHFHEEEGEGCBCBHBEBGBGECEAEHGHABBBFHEAFGBGDGFFEFDGDGDGHGDAFAGDHDECEHHHAHDDGHGCGEBEFABCBDBFCFCFHBADADFDAHH,False +281,10.0,6.0,6.0,8.0,8.0,11.0,10.0,7.0,GBFFDHAEAECDDBEGDGAEECGGGDHDAFADAEAHBHDEFFFFBCBCECAFABAHGFGFGFGHCH,False +282,21.0,33.0,19.0,20.0,21.0,12.0,19.0,26.0,CAADABABCEABHBABDCHEAEGHBBCCCCCHCBGGGGHHDHGHGDGDGDBDAAGCBHDFEEEEEEBEBAHHGHEHCCGHFBFBFBFGHBDBHAFAGACCHAHFBCCFDEDEHCHABDBEGADBBCBHEHEDDDDBDEDBBHAHBEEEDBBBBHGGGCEFBFAFBGAHAFA,False +283,12.0,9.0,6.0,10.0,12.0,16.0,15.0,10.0,CFCEDFGCGFHFBGCGFGABEGAGAGAGAFADBHGHDEFHHDGCADEGBBCHDAAAGEBEBABFDFEFEFHFHFHFHGBFEGEDDDEFEA,False +284,0.0,7.0,2.0,2.0,5.0,4.0,3.0,5.0,FBBHBHECBFDFGEHCHEHEBEBDGFGB,True +285,18.0,10.0,10.0,8.0,8.0,13.0,19.0,13.0,HHHFGFAHCCBCHCBFAGCGBABDBDGAFDCDAEAEHDADBHBAGFGFGHEFFGHGHBHAFFBFCFCAAABEEEAGGGAGCGFGAGADAGEHAHCDGEG,False +286,17.0,19.0,13.0,13.0,17.0,16.0,12.0,9.0,DBDADABCGDAFEFEFEDABCBEBGDGFEBEBEBEADBDGHCADABFDADADABGFGFCBCDCFBGGEEFCFAFEFBAGGEFHCGAFAHBHBFFEBACECACBCHAHEHEHCGBEH,False +287,11.0,13.0,8.0,14.0,5.0,10.0,1.0,11.0,ADDCHBHFDEACFDBDBABCBCDDDBAAADHFBFBABEHEHBHBCCHFDABAHCDDDCDAFHFEFEFHFHGAB,True +288,21.0,32.0,21.0,22.0,23.0,17.0,23.0,21.0,CFCBBDADEDEDBDHDADCCCEHEHBFBHADADBGBGDCBBHFAEBDHDFDFBEBHDEDBCECEGABCFGFHDHGHEHAAGHGEDEAEABGFCCBEBCFDFAEGGAGADECFFGFBBHCGEBEGAFABDBHFFAHAHAHBHBEBEBCBABDEGCGCHCHBHBGEGEGCAAGGBBFCCGDG,False +289,10.0,13.0,5.0,12.0,9.0,19.0,21.0,12.0,GBFAEDDDGGFEFDHHGHGFGFGDGFGHHHHEGDBHFGGHECBAGAEACFBBDBCADFGEGDBBBBCBHHFFBFBFDAAAEFGFAFAFDFDFHGGGGGECE,False +290,10.0,11.0,9.0,13.0,3.0,16.0,8.0,5.0,DBDBDCFFGFGABEBEDEFFGFGFAFABHCAFABCDHDADAHBGBDDDADFHCBCDCAAGHBFGFGFCCBFFCFD,False +291,22.0,19.0,25.0,28.0,18.0,24.0,23.0,17.0,FCFEFEFAGEGCGEAAAEGEHFHEGFGDGDEDBDEEECBBBEDFHFAGHCAGAFAHABFBFDDGECEBGFDFCFCDBEFABGEDACACDHDHDFFCDCACHCDBBGCDBHBHCFCDHHHBHBGFGFADDGDCDCHCDCACAGAGCDDABCEGHDHFGGDDEAFBFACACABGBGFD,False +292,22.0,21.0,17.0,19.0,16.0,16.0,15.0,29.0,EFHHAHDCDEBEHEHEHEHEHCFDBCBDHCAFEGGHDDBDFGFGHCFDDDDAFADCGCFDFBFBHGAFCCBBEEAAGAGDEDAHAHAHBHBHBHEHCABABHBCCCHCBBBDAHGFDEAEAFHGBGEHAFBGHAFAFAHABCDDECGCHHGHGAB,False +293,14.0,10.0,22.0,19.0,17.0,10.0,11.0,13.0,FDGGCACGCDCACBCDCDGHHDHBHFGGCCFBFBCBDFDAGEHAHEFECBHGDDDCEBBADCDFDADEEEEDEBHAHAGCGCBDGECEHEHAACADAHFHFEFCCECEDECCDAEA,False +294,21.0,23.0,11.0,16.0,19.0,13.0,19.0,13.0,ECDFDEAGAEAGHBFEFGHBBGBABABGDGCCAGHBHFEFGGCBDGDGDGHFHABAECEAGHFDFEFBFECECEFDHGFGABAEHEGEBBBBEBADFEHEHBDBDADADGBHADADHGAEBBBDCACECBCAAGA,False +295,16.0,21.0,15.0,23.0,14.0,18.0,17.0,12.0,DDBBHFDFGBGBHBFFFFFFFGEBCFCGHABBEHDDDDBBBBDGFHFAEDHDHCFCHCECBAHACDCDHAAADDECACAGABAGEFEBCAEACGDGFEFBGBDBCBGGDDAEFEDGCGEGEDEDGDBABADFHCHG,False +296,2.0,5.0,5.0,3.0,8.0,3.0,7.0,5.0,GHDHFBBGGCGBHEHBCACHCGCGEEEEFDADBEGEFE,False +297,8.0,7.0,6.0,6.0,3.0,4.0,7.0,7.0,GDGFBFEFAAEBDBDBAGAEHBDBHCHDGBGCGHGHAAACHCHAFCCD,False +298,10.0,8.0,9.0,8.0,12.0,10.0,12.0,8.0,AAAAAADGHGAEEEHFHEHEFFAGAFHCDCGEBCBCBFBFAFHFGGCGHEDGDFDBGEDEDCBEGEGHCBEBCCDGF,False +299,2.0,2.0,2.0,2.0,1.0,0.0,0.0,1.0,CHCEABDBDA,True +300,21.0,16.0,12.0,20.0,12.0,15.0,16.0,21.0,HFHGDDEFBFBFAGCFAGBGDHEHBHBHAEFBDGACHGHAHFFDFHFHEBBCBDBDBCFCDCACAEDEDHAHBHECABAGCEBHBGEDEGAAHAFAHADCDEGEGADFGAGAHCDAGADAHCHDDGDGDHFBF,False +301,18.0,17.0,21.0,18.0,14.0,17.0,20.0,23.0,BEBFFCAGAGAGHGHFHDHCFDFDEDEBEBEAGFBCCHCDCBCHHGHEACAEFGBGBEDEBCDADHFAADBHBHCHFDFDFHGBGBAEFGFAAEHEHEHCCGHDDDGHCCCCAABCGCGCADACABFEHDBCFHGHGDAHHDFGBGFG,False +302,17.0,9.0,16.0,15.0,18.0,20.0,16.0,20.0,CFEHGDGCGHFADAFGFBFHABACDEDEDGAEHEHCCCBCEFHGHAEAEAHAHEHEHCDFFAHDEAFDFGBGDHHFHFAGGFFBEHEAEAFFFDGBGCGEECAFFHEHEHDACBCFCDDDDCBCBHGAGCG,False +303,17.0,9.0,12.0,14.0,11.0,11.0,11.0,15.0,DFDFAGHHDEDEHEHECGFACAEADDHDEDCHCECFHBBBEGHBACGGGAGAHDHAAADEHEAFADGDBDFHFGBABABHBFCHAHACCFCGCEADFCFG,False +304,32.0,22.0,21.0,20.0,17.0,21.0,22.0,16.0,HABACGCBCGHGHADEGABAFHHGFCCGFFFHFHAHAGACFGEEAHAHABABFBAEAEDGDBDFFFFEGHGDDDCHFAFGECACECECEDFBEAAFBCGAGECECFCFCBGGADADGHACAEBHAHABGGDDADCDADBBBGHEFEDDDGEFBDBDBCBABCBAAAACFGB,False +305,22.0,14.0,10.0,9.0,20.0,15.0,19.0,12.0,GAGABHEFGHGABAEDECGAFABBEFEAECCAAHGHBEEEEEFHFGFGAEAGAGDGHGFAAAHAGAGFBECEFFBBGHGFCBCGCADEDBDBDBDFEECEBEDGAAEAFAHHBFCFCDHGH,False +306,7.0,13.0,6.0,7.0,4.0,5.0,5.0,12.0,BABAFAHDFDGBHHEHBDACHGHGDDBDHFFAFACEBEBEBHBCAHBHDHCGBHBCGCB,False +307,27.0,19.0,23.0,17.0,31.0,29.0,21.0,17.0,FADCDEGEBEGHDAEFEAEBHBCBAFAHAFGEGFBFCAHAHCCBDFHGCEFFCFEFEAEAFCBDADADHDFBFBEBADFCFEFBFBFDFCFGFEAHBBCCCCHHBHAAEGEBECEGDAEFDGECEFEHGAGEFEDGBABABHDHDCDCGHAEACAGFCECGGHEDCFAAAGAGCEHEGEGFGFE,False +308,16.0,23.0,23.0,25.0,22.0,21.0,28.0,27.0,BHGEFEDACAGADADGDGDBBFBCGGHGFCFCEHHDCDCEGFCFBEBEHDHCHCBEDDHBBEBGGFDECHCHCBFDFBGEHEGEDEGAHDBDAHGBGDGBCFCGCGBBAFAFABBBFGFHAHAEAGFFFGDDCABHECEDEBEHDGDEDEGCHCDCACHCAFGGGHFHFHGHGCAEHHHHDDBEF,False +309,11.0,10.0,14.0,4.0,9.0,15.0,8.0,17.0,CECHBGAHBHAHGCACBEFEFDCCCCCBCDCGAFFFFFBCBAFHFHFHDAEAHGHBHBHEHBHCGFBHAAGEFEFEGHAHDFFCAEHG,False +310,7.0,7.0,11.0,8.0,8.0,14.0,8.0,4.0,AFACGFEEDBGHDDADFCFCFCFDBGBHEHFAGDCACFCFEFBDBGBEBFCFCFCADGEGEAHCFGE,False +311,1.0,3.0,3.0,4.0,1.0,4.0,5.0,3.0,DHHBHDGDGCFAFGEBCBCGFGFD,False +312,9.0,6.0,12.0,3.0,7.0,3.0,4.0,5.0,AAEAECGCDFDHACECEAEBHBACCHCHEGCGCHCACBBAFAFCDGEBB,True +313,10.0,20.0,11.0,11.0,10.0,21.0,14.0,10.0,FHEBEBCAHAHBFGFGHGFAFCFDBDFDCHBECCCHEACABDGFBFEFAFAHGBFBDBDBFCCCEBFGGBGFAFABEEAEGBBFFDFBFBDBGBGCGDEDHFHDGGH,False +314,11.0,11.0,19.0,12.0,11.0,7.0,10.0,11.0,GBHBFGDABADADBDCDADHBGCECHCHCGCEAGCGCDCFEAGAEAEHECEFFBECDCGEHCBBBCGDHDBDADCFFEFCACAEBHHCHGHC,False +315,15.0,20.0,19.0,23.0,12.0,16.0,12.0,15.0,CCCCEFDBDHDCDFDCHFHFDEBACECHCGGFGAHDDDBACFFFDFBBABABDBACADAHCHDGCFFBHHDHDHGCCACEDBDECEHEBABHFDDDDGEFBFBGBEBFAGAGBGHEHDFEBABAEADBCGCG,False +316,6.0,8.0,6.0,3.0,8.0,2.0,0.0,9.0,CBCDFDHABAFEHBHBHECEBECHHBEEECEHAHCDAHABAB,True +317,5.0,12.0,12.0,7.0,8.0,8.0,7.0,11.0,CHGBGBFBFDABACAFFFCECHCEGDBBGHCCBGDGFGHEHDHCHBBCCECEBEAEAEHDCDHHBHBDFF,False +318,19.0,29.0,24.0,19.0,24.0,39.0,20.0,15.0,CFEFGHBHFHCEABFCCCFFEFEGBGBAHAHDBABCBGBGBGAGAGABHCCCFFFEHEDGBHEEDHDEDBHFDBCBGBFCFBEDFAFCFGACEFGFGAAFFFFDFEFECCGEGBDAAECECABEFDFCEAEAHFDBABDCHGBGBGBCACBCBEFGFGFCFHDDFAEHDFFEDDFDFBFBEBEBFHFCD,False +319,8.0,5.0,5.0,2.0,5.0,4.0,3.0,7.0,HAAEAHDHCBDEAHCGFGCEABAEAFAFHFHBHBCBCEG,False +320,4.0,0.0,2.0,0.0,3.0,0.0,0.0,1.0,CACAEAHAEE,True +321,19.0,25.0,20.0,14.0,21.0,25.0,19.0,10.0,ECEAHAGAGDCFHAHAHABEGAGBEBFFFFFGFDFDFGCDCBABEBGBFFFAGADFDGHGABAHAGCBABGDGEEACAEDBCBCEEFHGDDCBCEGEFEBEBFGCHBHBEDFHBCGEBCDCFCEBEFEBCBCBCBAGFFAFAFDCGEEFDCBF,False +322,4.0,3.0,7.0,8.0,3.0,3.0,6.0,6.0,AGDFDFDAGECEDDHCHGHCBFDEBCBCHCHCDDAHAGGG,True +323,20.0,23.0,10.0,13.0,14.0,23.0,24.0,21.0,AGAFFGHGEBBCDCEEEGBFAHAEGEGCGFGAAEBGHEBDGAGEBABEFCHAHADFBFDFBHBHBGBEBFBFHCACGCGBFBFAHAHFEFDBGGGBGFGBBEDHGHGHFHDHDGDHBFBFDFHFHFACADAGEFHCAADHBHCADFGA,False +324,6.0,10.0,13.0,15.0,5.0,10.0,12.0,7.0,ABBDDDDGDHDCBBHCHGDGBAEGEGHDBCFGFBEBADGCGCGHFFFFFCFCBDBDGDCAAAFDHCCCECDFDHCGEG,False +325,14.0,17.0,16.0,18.0,24.0,25.0,25.0,12.0,EAGDFBFEHEFGADABCCEGEAEGEGHGBFBDEAEDHDFEFDHCHGBGEECDCDCDCHCDEAEACCBEGAGEBFBFBFCCGFBEBCCDEDFDHHGAGAGEEFFFFFBGHGHBDECEBAFAFDFDGGGAHBEFGFGFHDGDEFGCABFBFGG,False +326,10.0,8.0,13.0,7.0,11.0,10.0,9.0,12.0,HGFCFAFCFAGADEDBHFCFCHHAHACEBECCCCEGEFEFGDBFBHBGBCEEABCECAADDEDHDHBGEGAHCHFHGAGH,False +327,13.0,9.0,7.0,7.0,11.0,9.0,9.0,4.0,EFEGEFABAFHDBFAFGGEBEFECCCEFFDADBDGEGAGABABABFBDDAEAHAHGHEAAGDECCCGCB,False +328,11.0,7.0,14.0,13.0,15.0,16.0,11.0,12.0,HHHHFDGEGFHFHGDGCCHFBFEDBAHGFCDCGGDDACACEDBGEDEHHGHEFEFCFGFAAACADHFAFCFCFCBDBAEEEEGDFBFAEAEDEDEBCCC,False +329,14.0,9.0,16.0,7.0,13.0,4.0,16.0,18.0,GCAEFCFCACAEDGGEGBGBGBHBHAHECAAAAHAHECECHGHADDCBCFCHHGAGEGDGEAECGBHDACECBHDCDGHCHGEBHBHEHCFGEGHHA,False +330,6.0,12.0,18.0,17.0,8.0,10.0,10.0,6.0,GGFCECDCDCAABEBEHEFDDADGDBDHGFBFBEDHDFBHGGCBCBCDCBCHDGCBCBEDCDGDBECADACCCFEFGFGFHDADFCC,False +331,11.0,25.0,21.0,16.0,17.0,27.0,21.0,23.0,FFFCHCBCGHHHGGCEBEDFCHAEFCFHDBDBABFBFEFBFHDHFBGCACHHFBFDFGFBHHDBEFAFAFHFEEEGEGEGEDBHCDCACHHGFGFHHBDBDBHCHGEDBDECECECFGBDBCEGGGGCCBCAAADAHBBBGBGFGHDAEFGFBBGHDCFCF,False +332,31.0,34.0,15.0,23.0,18.0,19.0,14.0,23.0,HBFBAAACBDEABCHDHAHDFEFHAAACDEBHBHBHBCBHBHBGCAFGBGBFFDFGAEAEBDFFADADACADDDHAHAEEBFDFGCCCFCAEGBCBAHCGEEEEEEBFDFEHBBBABAHADBDEDFGHHBHBDDABBHBHDHFCFCGEBAAAEGFDFDGDBBBAGAGABAGHBHCAD,False +333,20.0,17.0,9.0,14.0,13.0,13.0,13.0,14.0,ABGCECACBHDHGEEHEHBDAAAFDEDGDFAFABCCGHBABEBEGADADFDEHEHEGBGAHADDHHGHGCGFFABAFDBDHABEFDCDFFAFBEBHBAFAFABABGCECHGBG,False +334,7.0,5.0,2.0,4.0,6.0,6.0,4.0,9.0,GCGBFBHAHEBEAEDCGEAEHHFHAHABFGFHFHDEDADAFHB,False +335,17.0,13.0,10.0,10.0,9.0,12.0,9.0,20.0,AGHHAHAHCBABFGADADEFEFEDBBBBHHGHDHBCECEHFHFHBHAHDEAEAEBEHACAGADHCHBGGFFFHACBDFDAGHCDGDCFCACFHFBBHGAA,False +336,10.0,13.0,6.0,5.0,11.0,4.0,11.0,9.0,EGEBEBEGEBAHEFBCBEHGDFHFAFCBHBGDABHGGGBGCGBABADHDCEABABADAEEGAGCHCHEH,False +337,17.0,16.0,15.0,8.0,14.0,17.0,17.0,24.0,HBGBABHBHDFFAHAHAGAEAEAFACGCBCECFGDGCCEFEFHHHABGFCHDHGBCBHBDGDHEHGHCFCHGHDHFHFBFDABHBGBAFHEEGEGECBAGEHBHCHEFEADCBFGHCEFGCGFAAAAF,False +338,18.0,20.0,22.0,16.0,18.0,27.0,14.0,22.0,AEAEAEAFHDHAAEFBDHGFGFCAAAGADFFEFBADCHCHEGBBEBGFGFGEHEDCFHAEBHCDCBCGAECGCHCHBFBEBHHHGCBHFDDGHHHCHBDEDECBDFEFBFGFCFBFBCBFBFCDEAFDGABADADBFFFFECECADHHHCHCFCFCG,False +339,24.0,25.0,25.0,23.0,21.0,21.0,28.0,25.0,ABAFDFCFCGHGCDBDGEGEGCAAEBHBHGHGHDADCGCHFECEBDHDABHGCGHDHEEEBFBFBDDCDGEEEHBFFCFBFAFAFGCCCHGGFGCACHEDEHGDDBHEHDACAFHEABGCACABDBEBFDGHGHFHEAEAEADACGGBBBCGCGDGBGBFCHAHAHFBABFCEHBADGDEBACGCGFAFDHD,False +340,14.0,19.0,9.0,8.0,9.0,16.0,11.0,11.0,CAADABAEACBCBGAADHBFFFBDBDEGABHHHAEFHBCFHBEBGFDFBFBDBDBDAEGEGEFCGBFBAEGBGFGFHFHFGFCBCAAGAFEHHHCBC,False +341,2.0,6.0,2.0,4.0,1.0,4.0,1.0,1.0,ECBDBFAFDFDBGBHBCBAFD,True +342,10.0,9.0,6.0,7.0,9.0,12.0,7.0,13.0,AEAHAHFEGEGBGAEBBHFDBGBHHGHAFAFAFHFDDCDHECFCACFHFHCDCDHBEBFAFGFABEEEGBDHH,False +343,12.0,23.0,13.0,17.0,19.0,18.0,25.0,20.0,GCGCGCFABHCGAFCFDFBHBHEECDDBEHEAEABABAHHFFDFGEBEBGCABAGGEGEDEDHBCFDHDGBGDGHAEAGDHAEEECHHFBDGCFCDBDHFHBBBDHHCBEHFHGGGFGFBEBEFEFCFGFGHGDGDBHBGBABDGEG,False +344,8.0,19.0,17.0,14.0,18.0,17.0,16.0,26.0,BFBHCHCACDDFCHEHAFAFEEEDHGHBEEFADGGFGEEDEDEFEFBFBHHGHGHDEFCGCGHDHDBCHDBCFCGEBHBHEHFDEAEBEGCGBHBFBHBCBCBCBGACCHHHGHFDFCFHGDGHEHDCBAAFHBG,False +345,14.0,25.0,9.0,16.0,24.0,29.0,24.0,20.0,BDBDFDFEGEDADGGGGDFAABHGFGFEBHFECHCEDBABFBEDGGCFCEAAHGHFBBHHHHHHEBEBFAEEBEDGDCHEFBFBFBHEGEGEAEBGGCAFFGDGAGAGHFFFFFGCHAHBHDEDEFHBBBFDFHFBFBFBHDEFGBEDEGEGBAFFCACEG,False +346,20.0,21.0,26.0,20.0,28.0,15.0,21.0,20.0,EDEDFHFHEDCCECEHEHCGBBAEFDDHBGBEBGAEHECGCACECGCGCDEHCAFAECHBBDGDFCFBBHBEBEHDGDBDCAGACAHAHDHCEBEHEACDDDFFAGAFAFCGEACACGEEAHAGAGAGEFEFHFBGCHBDBHBCGDGCECHDHFBFDCGCBBEBDAEGEGE,False +347,9.0,10.0,7.0,7.0,9.0,11.0,7.0,1.0,DAFCBCBAFDEGEGEFAADGEGEAEAFGFBFEFCFGFCFHEDCBGBEBAFDDABCBABDBC,False +348,23.0,21.0,22.0,23.0,12.0,21.0,19.0,12.0,DBGBGFCCGCDHGFGFGFDCDEAEAFBFBHGHBCBABAFFFBBAFHFCDBFECCDCACAEADFDEDGCFCHBBBBDFDCGAHFGEADDGHFFDADEGEAEFEDECACACAFADCFCAGBBABEDGDHCGCACACHBDGGAGBGBHAHADDDHB,False +349,24.0,18.0,28.0,33.0,14.0,23.0,32.0,22.0,DBDACACDEGGCFCBGBHFGDGDEDHHADCFBFDFDAAFAGDGCFCECEGDGFBAGHDDCDCDGHCFFAFGDGDHDHFGGBGHDCDCAHFEDBFBFCDDEDGHAHADABHBEAAACADGBGAGAFHCCGFGCGDGAEAGDGHFHFEBAHCFCFGGGEGEGAGHBBBDCCHCHFHCHDFDBDCDEHECBCEAABC,False +350,8.0,4.0,6.0,7.0,7.0,4.0,16.0,7.0,EDGFGACAGBHBEBAGACAGEEEEEGGAGCGCDAFHGDCDHGHCHGBGAFDFDGGGDHH,False +351,14.0,22.0,13.0,15.0,4.0,11.0,14.0,13.0,ABCCHHFHCDBDBDBCCGCGFFDFBFGGBAHADDGDCDCBAHABEFHBBDBDBDBEBEBGDAEABDGFHBHGAGCBFHHHHHACGBGACFBBDGDBFAGAGACACF,False +352,23.0,10.0,18.0,19.0,18.0,25.0,14.0,15.0,GFADHDHFCGCBFFFHHEDFDHAEEFECAGBGEAHAHADAEGCBFBFEGEFHHEGGCFCHHAHAHEBAADAGBEBEDEDGFEFAFADADFGFAFCECECFFAFACACHCDFDADCDGGFDHCCCCDGDAFBFBEADBDAECF,False +353,28.0,26.0,15.0,29.0,24.0,17.0,31.0,29.0,EFGDADGCGBGBGBEAEHGHFDDEDEDEGHGEGEGHGHEHGDGBGFEAEGDCHCHDHFHEHAGDHDFEBEBEBEDCDCACAFGFCABFEGBGAGHHBDBABABHHAHAECEAGBGBHBFEDHCFCDGAFDHBEACFHHGDADHCFCBAAHFFGFDADBBEBHACABAHGDGBEAFABDBGGGGDDDAAHDDDHCHAABE,False +354,2.0,5.0,6.0,7.0,4.0,6.0,4.0,6.0,BHGHAECCCFADBDHDEDBFBHDCDCDFGCGFGFHHEFEB,False +355,6.0,5.0,6.0,6.0,6.0,7.0,2.0,4.0,HFHCGCGBFEAAAHAFBCBDEDEDEDCDFFABBCFCADFEHE,False +356,6.0,7.0,14.0,10.0,18.0,19.0,15.0,16.0,FBEHFGEHFDCDGGGEHCDCDFFFHBABDFDFHCCFEFECEHEFCAAGFGBCBFGFEBCACACDFFGHGBEHEHEHFHCCEGEGEGECAHEDEDGDGEHHHGHFF,False +357,14.0,24.0,11.0,19.0,13.0,13.0,20.0,12.0,CAHGEBBDBFBEGHAEDBDHDGDGECACACEFBDBFFGADBHBCCDCDHDEGEAFAFEGBFBABHFHAEDEDGHGBEBGBGBGFFBCGEGDAFAFAHAEBCGDDAGHHBCBDBDBFBDBDCGGGGH,False +358,14.0,23.0,16.0,16.0,14.0,16.0,6.0,16.0,HBCBHFHFHDBAGAEDCCCBFDFHFHDHDHGHABCFCFAGEGBBBFDADADBEBHFCFDFCBADDBCBCBCAEGEFCBABAFAHBFBEBEBCCEEHEDECBFAEHGADHDHEHBDEFBCDA,False +359,13.0,21.0,20.0,21.0,14.0,16.0,20.0,15.0,GFDBDCACAEBEBEBHBCBCECEGACHCHAHAGGBADADBDFCFHGDGDGEBHBDGGFGFGDBDAGABDGDGEHFDAEFFGFDHEBCCDCHCFCECHGDBCEHEFDFDABEBGDGHACFFBDCEAFGDBCGCBCFHBHBH,False +360,2.0,2.0,1.0,1.0,3.0,6.0,2.0,3.0,GFFFEFEBDBEHGCAHAHFF,True +361,14.0,17.0,14.0,17.0,23.0,22.0,11.0,18.0,DHACABDDDFEFBCAEAEAEFCFEFCFDFHFAFBCBCHGHFHEAEGBHBGCFCHAEBEFECECGFEDEFCCHAFAFAFADGHGBGDHDEDAHBHBHGEEBDHDBEEHGDEDEFBFBFHFGFBDAEBDGCHEEDCHB,False +362,7.0,7.0,14.0,4.0,6.0,6.0,6.0,3.0,CCBCGEGCAFAEADAGFGFCFCBCGHBBDBCGEAHAFCDCACBCHCEEFECBD,False +363,10.0,8.0,17.0,16.0,17.0,20.0,8.0,12.0,FEADABEGEHEBEBECFCDCHBHCAEEGHCFGFGFHHEFEFDFGFDECCACHFFFCDCGADAFGDCDCDCEFFFFAHAHBEECCDADAFFBEDEDEDHCFCDBHGHDB,False +364,8.0,4.0,4.0,12.0,13.0,9.0,10.0,11.0,FFHEHDFFAGEGEHEHFGDDDEDECEDABHFGFGDGAFADAEECGGABDBGHHCDCBGFDHDHAEAEHEHE,False +365,6.0,2.0,5.0,1.0,4.0,5.0,1.0,5.0,FEACAGFEFHCEABABAHFFEHAHCHCDC,True +366,11.0,5.0,9.0,15.0,4.0,9.0,12.0,5.0,CCFDEDFDFEFEHDBDCDHGGGGDFDAACADABFGCBCAGAFDFCGCGAHAGAHDBDHCGEBFDADADGG,True +367,22.0,11.0,14.0,10.0,20.0,19.0,35.0,19.0,DGGGBCECGDADABABHEHBHGAGHGFAFAGBGBGEEACACFEFGGGEFHCDEEBEBAHCEFFFFHAHAHGFECBHGGEGEHAHFGBDFHEEGCGFDAAAGEGAGFEFHFGAGAGDHAACAGHGCGAGDGBFHFGCGCECEHFHDGEGCD,False +368,2.0,3.0,4.0,0.0,3.0,2.0,2.0,2.0,BCECECHFHFAGEGBBCA,False +369,2.0,7.0,10.0,3.0,12.0,8.0,6.0,9.0,HHDHDCCEGEFFFHCBBHDEGEHEFEFEFEFBCBEBHBCCGCHEHBGGACECEFGAC,True +370,17.0,20.0,13.0,14.0,12.0,20.0,18.0,16.0,HEFEBECCHDECGCEBBGCDBDBDGFGFAFHGDDFDHBBBFAGDFAGACEFHGBFDFHFHFHCGBEDHFCFCFGAAEDECEFBFAHABACAGAGACAHABFBFGEGDBFBHBHDHDGBABAGCGEBAHGH,False +371,14.0,16.0,16.0,7.0,13.0,5.0,11.0,14.0,GBGBEHFHFBBBECAABDEABAGAEDEDBCEGECCACAGACACBCHCECEGABDBEBHBHFHCDAEADHCHCHFHCEABBCDHEGFGCHBGGHGHA,False +372,9.0,15.0,11.0,10.0,12.0,17.0,13.0,14.0,BEBEBGFFBFGFDFGCGCGFHDGGCFAFAFBFDHDEAEHEHAFBFEGHHEBGAGCHHHDDCECGCABFBFHFEDEDHBBCBGBCAGACAHBECEDDHBHFF,False +373,14.0,9.0,8.0,14.0,6.0,19.0,18.0,14.0,BHEFAHAHDDDDFBFDFGFEFHGBBFAAAGADHGBFCDGBEFGFCHHGFGHGHFHGEGAGEEAGDDABGGCCCBHBHCHDFAFAFAFGFDFDADADCGCGHF,False +374,13.0,6.0,13.0,5.0,8.0,10.0,12.0,6.0,CBGADAHAHAFAFGCGFGCDEAEADADCBHDFAACCCAFHBBCEGEGECFHAEBEHCGFGFGEGCGCFCGABF,False +375,8.0,5.0,6.0,3.0,11.0,9.0,8.0,4.0,EEEEHFFBFGGCGHGEBABEEFCFCBHGDBHFAFAFDFGAGDGAECECECAAAE,False +376,6.0,8.0,6.0,9.0,8.0,5.0,12.0,5.0,AEGEBACACHCGGHDBDBCEGEBEBHFDDGDCDBDBEGCAFBFGGGEHEAADFDFHGGG,False +377,2.0,3.0,2.0,5.0,6.0,4.0,2.0,2.0,EDEDECEBHBGFGAEADFHBDFEFDC,True +378,18.0,11.0,12.0,20.0,13.0,19.0,14.0,21.0,GAEHGHAADADADBFCECDCFCGDDFCGHAADFFFGHBHFDCDBFHFHGHFAGAGABADDHAEDECFFFAFAFDEDEBABFBGGHBCBAACBHHHFFEDEDADBEHFHGCGEEDHDCDGHGHEHEHCH,False +379,15.0,10.0,10.0,14.0,7.0,13.0,13.0,11.0,FHGHGHBBCDDDDABABGCEDADCHGAAHAFCFBDBDADFCFDDHCHFHAHCHCBCGGAACAHGGGGAGBEDFDFEAGDGFEBEFFAFAEBEF,False +380,20.0,20.0,27.0,28.0,18.0,28.0,19.0,15.0,FAEAEHHHHHHECBHFFFCFCDAGFGDEDCDCBGFFCGBGEGBAEAGFCADGGBEBEFHFDCBAEFDFDEDAHAHGEDAGBGFEBEGFDDDFDFAFCCCCCCBCBCGCGCACDDBFAFBCDADCDEDBCBCGHGFGBBAFDCDHBHDDBDCECACDFDGABFEDEAEFHHAAFFF,False +381,9.0,4.0,8.0,8.0,10.0,3.0,5.0,2.0,DEDECFCECEDAAACHEGDDFDFCACECGAABDGCHBEBGDGBAEAEAE,True +382,28.0,23.0,23.0,25.0,22.0,19.0,22.0,24.0,EBAHHEDEDBDHHGADFEFEHDHDGFFDFDADHDGEACBEHEFGDGAGAGEBCDCBBAFECHGGBHCHCGGGCGAFCHCHBBEBFBFHFCGCGEDEAAADABABADFEFDCDCECDCHCHCBAAAAAAHAFEGEADCCFHFEBEBFHDHFAAAGCBBBCDHDEDFBEGHCBDBGHGCGHDEAGABA,False +383,4.0,5.0,2.0,2.0,4.0,7.0,4.0,2.0,FAFBFGCGAGAGFBDEFEFHABFBDCHEBE,False +384,23.0,10.0,11.0,21.0,17.0,14.0,20.0,15.0,CBEFFDDBFAGHDAGAGAGDDBEGCCCDCBHHEAEFGFEEEHEACACAGAGBDAAHFHFAFADEHCACGDAEEFGGHEHBCDAGAEDEBFGHDHEHDHFHAGAGAGAFAFABBCDGGGDBDGDEDEDFDHD,False +385,16.0,15.0,15.0,12.0,17.0,20.0,20.0,23.0,FGBHBHAHAHBDFEFEBCAEEDEAHBHBHEFDCBAFCFAFAGHGHGACDHBCAEHGHBABFCFDGDFDFHFDBGFGHHACADACHCGBEBEHEACGEGFGFGDGEGEGECEADACBGFHHDFFHFHFGGBHCGCEEHC,False +386,22.0,28.0,19.0,25.0,19.0,24.0,12.0,27.0,BHDGBHDFDFDBABGDHAFAECECBCBCFCBEBHHHEEEBAFDFAFADECBDFDFAEHBHEHEGEADHHHFHFHDBFHAHADADFDFCAHBCGCDCBBBGBFAFCFHAGADDBFEFEAAHCDCECBDFFHFHBHBFEDCACAGEFDHGBEHGBCBHEEGAGHBDBDGHADADCBCB,False +387,16.0,23.0,23.0,12.0,27.0,6.0,20.0,14.0,EDEBGBEBCGGHCACBHBEGAGHGCGEGFCHBDCHGHBHGDADADBBCHCBEBACGEGEGEBABABDEEHECCCCBBBGAGAEAGFGHACCBBABAGFBEEEEEECGDDCDHEEEAEAECDCECGCFHFCBCEADDHEBFH,False +388,29.0,22.0,29.0,26.0,26.0,22.0,19.0,18.0,CECEGHFBFDDCDHGAFBGDFAAHACACAEEBEACFCAEECCGCGCFFFABGBGDCDGDEAEABHBHBFBHAHDCECECHFEFBACDDDEHAGABADFDFDBDBDECECEDHDAAAAEBEGAAADGFBFADACHEAACFGFGCGEHFHFCCCDGGBCEGFAFEBHCDAGBCBCDCEEGDBDBDHFHEBEHH,False +389,6.0,5.0,9.0,6.0,6.0,10.0,3.0,6.0,AFFFACCCEHHHHACDFDEGCBCDEDCFBFBDBFHFHADGCGCEFAFAEBE,False +390,5.0,5.0,8.0,6.0,3.0,4.0,2.0,9.0,CHCGBFDADACBFDFCHHDHDHCGCBFAEAEAECHCHBBDHH,False +391,17.0,18.0,29.0,20.0,13.0,16.0,17.0,22.0,GDCDGHHBEBFCFHGHAAAHBCDCDHFHEHBDDDDDCDCACHEBDBCBFDACBCBHACCDCGGGGCBCFCFBACADHHCFCADHHHGCBBGDGCGEEHEACAGGFGCABABDBEECECECFAFAGHHDHDFBFGFHECEFDFAHBHFGCACE,False +392,4.0,11.0,10.0,5.0,8.0,5.0,3.0,15.0,HHHHEEDDBGHGFABEBECCBHBCBEDECBCHCBEFEHDBDHAHBHFAGCHCHCBCAHFHF,True +393,5.0,6.0,6.0,2.0,4.0,4.0,5.0,6.0,HGFGHHHAGCGEFEBDFDAAHAFCBCBCECBGBEBHCA,False +394,21.0,28.0,17.0,22.0,17.0,15.0,15.0,14.0,DHAAAAFCDBDBDGGABBBCHCACGHFBBBBBBBAAAAFBBBBBEGEABCGFDHEHEDBAADEDEDEHCFEBEGDHFGGECDCHCHBDCEFEHDBDBDBDCECGCBFDGBADHGGFAFAFACEGEFDFBABFFEGDAACACHEHDHDCG,False +395,17.0,17.0,23.0,13.0,25.0,16.0,32.0,27.0,ACFCFGGGEEHEGGDEHBACACECEFEFHDEDFDGEGBGFHCCACEEFDACHGHGHBEEHBACCCCHCEFDAGAGEGCBHBHBGGGDGCFAHGHGHCAEFBBBHBGBHHEHEBGGEGEFHFHFHGHGCFCGHGDEDAAAGCBBBCHAEAHDHDFGGGEGBAHECDFDCAE,False +396,2.0,4.0,1.0,7.0,6.0,10.0,8.0,9.0,GCGFGFGHBFAEGFHFHGBDHEFEDHDEFEFDFEFBGHHAHGDBDHD,True +397,12.0,14.0,13.0,17.0,13.0,20.0,12.0,15.0,CEBHFCBGHGEGEACAHBHBDBGBADFDHDFDADHHEHFHBAAFACECECEDDGDGDCCCHCGBBDGFBECGDGACFFFFFFDHDHAEFEFBBGBFHFHECAFDBEHDFAFAEGFD,False +398,28.0,19.0,7.0,24.0,27.0,19.0,20.0,15.0,DHEAEADDHGAAHAGEHEBDBDHFCFEFEFEGAGHGBFHECAAGDCDADFCHDADADFDHGBGAEHDGFBFAFAFEFEFEHCAAAGGBBABDBCEADADFEGEFHADEGGGEGEGBGBDADEEBDBDHEEEDADEBBFHEEFCFEFAAAGABABDBHBG,False +399,0.0,3.0,1.0,3.0,3.0,3.0,0.0,4.0,DDHFBFEFDHBHCHEBE,True +400,14.0,15.0,8.0,10.0,12.0,16.0,15.0,13.0,BABABGHFHEHEAEBFGHDBCBGDCFFGAGDGFEFEFEFHDCAGAGHHAHACBCBGAGEGEDBDHDEBCACBHAHCFAFEBEDFFFBFGEGFABHGDADFBHG,False +401,11.0,5.0,16.0,15.0,7.0,18.0,6.0,17.0,EGDHHBGCGFFFFECHDAFAFBFDHGHAACFFFAEHBFDFHEHDFDFDABBEAFCCCCCCCFHAGADDDCCEHEHCHDHAHFHCCCFDHDHDADG,True +402,3.0,10.0,24.0,13.0,15.0,13.0,11.0,19.0,CBBEDHAHBDBDBGCECHHDHGHDCGCGEHCHCGCEEEEHFHFECEGBDDFBHEDBDADGFHCHCGCBCDCEAFGFGHGHCECFDECCCCCDHHEBFHFCFCEHFFCF,False +403,1.0,2.0,2.0,2.0,0.0,1.0,2.0,2.0,DGDABGBCHCHF,False +404,5.0,16.0,6.0,12.0,8.0,5.0,12.0,9.0,DGDHBCBCHGEEHEFGFBAGABADDCDBBBBBGAGEEDCDGHGHFHBHGGCEEDBDBDBCBDBGFAEBHFHGD,True +405,21.0,16.0,12.0,16.0,13.0,10.0,25.0,18.0,GFEFBFGGBGBGBHFHEBEBGBGFGFCEAGCDHAABHBEGCGHDHAHDCEGDGDBFGCAAAAEAGADFDGDAACACECEBFDHBAEACHGHAHDEDEFHHHBGEGACDBAGGBCBHHCDGAGDGHGHADAD,False +406,4.0,4.0,3.0,5.0,1.0,0.0,4.0,3.0,GBDDABCBCGDGDCHBHDHAGAEA,True +407,16.0,7.0,6.0,14.0,13.0,6.0,14.0,8.0,BFCAAAAAEFEBDFCFCADGDBDBDAGAHAEDEGHGHGFDBDGAEHEAEAGCEDHAEADGDAFADGGEGHGHDEBEHDGBGCCE,True +408,12.0,15.0,11.0,21.0,18.0,14.0,12.0,11.0,DBDBDBDBCBGGABCEFEFGGDBDAAAEHEFEBGBECCFCBGEEAEHCBFEFHFCEBFBHGADFDACABEBEAECDCGFDDDDDDHGEGFDHDHDHFCDDEDGAAFAFHHGHEE,False +409,20.0,21.0,28.0,22.0,20.0,26.0,20.0,22.0,FCFDFHADGDHDHBBCCHHDHDHDGAABAGCGCDCDFFFAEAFBHHGHCHEFEGBDCDAAHABBCFHFEEGEFFFCHCDBDEDEFEDAFAFABEHCCCEBHBDGDECCAAACDGFFEDHDFBHBAGAEAEFECGGGCHCDAHBGBDBCBEHGFCFCFCFCEGEGHFCBGFGCGCEABBB,False +410,3.0,1.0,3.0,3.0,0.0,0.0,1.0,2.0,DGACBHDHDCACA,True +411,10.0,24.0,18.0,15.0,16.0,10.0,24.0,18.0,HHFBFECHGHAHFGGDCBCBCEGHGBBAAGCCHCBDBGBDHHHBFBDBGGCGHGABABACEHEHCDGDECBAAEFGGDGEADDDHDHBEBEGEFEGEGCGDGDEDBCCCHCEBEDCGFGHGEGFBFBACHBBBBF,False +412,7.0,7.0,14.0,10.0,10.0,6.0,9.0,5.0,GEDFDFBAGCDABADDGAHEDEDFDCDCDFHCBCBCGCHBGCFCAEEEEEGEGCCCHHGCBEBCAGAF,False +413,1.0,1.0,2.0,0.0,2.0,2.0,3.0,2.0,FGCGCHEHEABGF,True +414,3.0,7.0,4.0,3.0,7.0,6.0,6.0,8.0,HCHGEEBABABFBEGFGAGBDFDEHEFCFBHHHFHCHCBEEGGD,False +415,17.0,22.0,23.0,22.0,24.0,17.0,20.0,16.0,BCBGBADDEHEBECCCCDGAGEGEAACEHEHGFABAEHECECFCGCECDBACAHADECGCBBFGFEHEFGDGEGCGFGDHDCBCAFGDGDAEFHFCFBEEHEBDDFHHHBAFAHDEDGDBDEDECFCFHFAGCFFAEGDGDADCBBBBCGHHABBBBBDED,False +416,23.0,23.0,29.0,23.0,28.0,15.0,36.0,18.0,HDFEEHAHFECBCGDFDFBAGABBGGADFDGEGECECGDHCECECEDEDACACGEGCGFBCBCACEEDEGGABHEDCHBGGGHGCGCBDBCCCEHEBGBCDDGGHGEFEGBBBDBAFAFAGBFFHHADEGEDBCCCACGCDCGEAHAEADGGGDGDBFBFCGCGBGBGACAHAHGEFDADEHEHAFGHBHDEAEA,False +417,6.0,3.0,6.0,6.0,13.0,9.0,7.0,12.0,HGCCECEAEHGHGCFAFHDDBDEGBGHHEEDAFGFHEHAAADBCHCGFEEEHEHEFEFDFHF,False +418,7.0,7.0,9.0,13.0,10.0,16.0,6.0,11.0,HEFFFEDECCHHBHFDFACACEDHDBDBDBDFCFDEDEBHGEFFAFADAFHGBGCGCFDEAHDFDHGHFHCGEFEFABC,False +419,6.0,2.0,4.0,3.0,3.0,0.0,2.0,0.0,EEBDBAAAACACEGGCCDAD,True +420,20.0,21.0,13.0,17.0,21.0,27.0,25.0,13.0,HAGAGAECCFDBEADDGAGFFDCBFFCABGBEBAGCGBFBGEGEFDCDEBFBEDCAHBHBDFDFBADGFFEGEGEFEFEFHFBBABAHHDGDGBGAGFGFGEEDEDAFAGDHEACACFFGFGFGEDECBFBFHHHGEAFAEAHFBEBGBCHCHGADC,False +421,9.0,14.0,14.0,8.0,6.0,14.0,12.0,12.0,FHFDFDBBBGBEBCBFDGDHFGABCGABBGEAFAHACACHDDFHCBBFHFHFGCHCHGBBHHGCGCACACHCEFEFADDFEFEGGCGCB,False +422,2.0,4.0,4.0,2.0,2.0,3.0,4.0,6.0,HFCFCECBGGGDGBEHFBAHAHBHDHC,False +423,19.0,10.0,8.0,8.0,6.0,9.0,8.0,8.0,DEABABCFEFDAAABFHFAFAFADACCGBABAGHBABABAGHEHCGDGDCDCGEHEGDAABAEHBAGACDFFCFHH,False +424,22.0,16.0,21.0,30.0,13.0,19.0,17.0,12.0,BCBEBDAEAEAHAHGHCBCAAEADGFGDGDCACFCDEGCDHBCADDDDDEABADADADAEGBGBHCGFAFDCDBDFACDBDBCFEHEHAHGFGFGFGECHFHCCGDGACDFDECFDADEBHFFDFDFBFBEHAGCGDFCBGDACBCFDAD,False +425,12.0,15.0,7.0,11.0,10.0,19.0,9.0,9.0,CADACAFHFDDCDBFBDBEBEDEHFABACFFHHGFDFDGDGHAHACCBEFDFGEGEADFFCEGBABAEHHBHBGBEBABGBEFFFFABGFFF,False +426,10.0,14.0,11.0,11.0,11.0,17.0,18.0,9.0,BFBAAEFEHCHGAFEBCFCGCGBGFHFCGGAFAFBFCFHBBFEFEFEBGCECBGBGCDFDBDBDGAGEFEGHGHAADEGCGHDBAEGDDDDCDFGFGABHH,False +427,37.0,20.0,35.0,16.0,24.0,26.0,23.0,17.0,AGAEEHGHGCCCGBGCHCHCHFGGAAAEAEAFHCHCGCACADEEECBABEFEHDFBFEEBBBCEFAFADACAFFCFDHDGBFFACDGDFDBBBCGCBAAAEAECGCDHFBDBCAAGACACAFAGGBEHECECEABFEGDFDHHAAAACHCHGHCHABEGCGFACCECFFBFBABAGFFDAECEDEFFACGCGAGCDFD,False +428,16.0,17.0,31.0,28.0,15.0,17.0,26.0,26.0,FGFCCACBEDEDBCGCGFDCAAECEAAFFGGGGHCHCAGDGDBHBHFHFHFHDHAGGDDADHDHBACGCGEDHBCDFDGDHDCCCBBBBGCCCCFBDDDBCCCHCFEHHGFBFCCAAGGDADGDHEHAGCGCBDBFBFEGAGEGHCFDHHHHEHEBEHDFDGDHAAECCCEDEDGH,False +429,8.0,4.0,6.0,7.0,12.0,5.0,7.0,6.0,AAHAGBFHFCEAEBECGFGFGEEECBCDCAEHEAEDEDHGHBCFDGEGDHDEDAA,False +430,5.0,7.0,8.0,4.0,4.0,3.0,11.0,4.0,HGDCHCBCBFGAGBGBEDHAEAEGFGCGEGAFCGCGDHDBBBCCGA,True +431,8.0,19.0,9.0,16.0,16.0,15.0,11.0,12.0,FABCEHHCGDGDFDFHFAEDGDFDFBBBBFEDEAGBEEEFEGEBEFDDGBBAAAFHFHEEDCDCGEDBDAEHEHBHBHBFGCDCHEDBFBGHGFBFBCBCGCBAHD,False +432,25.0,23.0,17.0,34.0,27.0,19.0,18.0,34.0,GBHHHFEGGFGFGHBABDBDBHGGEBBDEDHHHHAHFHEHFFFGBDDEAAAAADCDHACAFDBDCGCGDDDHAGBDHGHCHABAFEFEFEFDDBDBABGFAFEEDEDEAEBFDFDHAHABEBEDDDFHCEFEAAAECCBABHDADHCBFGDHEHAGBDHHEHEDEAECEDGCEEHDDGHCHCHEDDHBHCHCACBCG,False +433,11.0,10.0,8.0,8.0,5.0,5.0,7.0,5.0,GEEEBADHCHEBEACABDBDAHABABABCDCGCDABFDCACABGGAGHCHFFDDGFGFB,False +434,8.0,2.0,9.0,3.0,9.0,11.0,9.0,7.0,CECFFFHGHBHCFCFBFHDACEEFCGEDEDAAAGCGCEFFAAGGGHFHFHEGEGECAA,False +435,15.0,9.0,12.0,17.0,12.0,13.0,11.0,8.0,FEFHFAFEDEDBCGGFBHACGCFCHADADAFAEAEADHDBDFHEDEDBBGBDADAGAGEGECCHEAACBCDCEGFGFDADGHHFDFCCCBDGEFADB,False +436,9.0,4.0,4.0,2.0,2.0,7.0,7.0,7.0,HEFBABCEFAFABGGAAACFCFGHBHACGFGAGAGHHDHDHF,True +437,13.0,14.0,15.0,27.0,27.0,6.0,29.0,26.0,DDDEHABAHEHAHDCBGDHFCEGBBHBHADDEAGGEGDGDGCCDCDBDBHBHBAAHGGGGACECEGGGECCDGDGEGADADGFHEEDEGACAGHDDDFDFBEHCHGHFHEEEHEHEHEHEGEFDGDGHBCCEDHBCGDHEEBAGHGEGEGEDHBHCD,True +438,22.0,9.0,13.0,21.0,26.0,17.0,18.0,21.0,GAGEHFHCEGEDAFAHAHEDBDFDABAHEDGDBCAEGDDDGGGGAGEHHHGCCFHHBHBHBHAGECAGDGDGDGEHDFAGCEEFEHEAEAEFFCECFFFBDADFDADADAFEEEEAFAEEBABAHEFDGHEHFCDCDCECHCHFEAH,False +439,24.0,19.0,22.0,19.0,24.0,22.0,19.0,24.0,DCDCAAAAABAFGFDFDHGCGCGBDACCCCEHFACHEDAAEABAHABAEFHFCFCFBBHFHEHEGCGDHFECBBBGBEHEAEAHDGDGHCHFBFEFEBEDFAACDHDFBHADCCEHEHDBFGFHDHDGEGADADEDEBECHFGGAGEFCCBCGFBBAGEHFHGHEHEFECBGA,False +440,23.0,14.0,11.0,16.0,9.0,11.0,13.0,16.0,DCDGBGBAAHECEFGFGAGHHEDGBCFDFGHGEEFADAEGFBAAAABFBFDAACCCEDHHHDDAAEBHCHABCHAHAHABEDGFGBGDDDDDDGAAHACACACABFFHBHBHB,False +441,5.0,9.0,7.0,7.0,5.0,6.0,6.0,2.0,CFDBDGCADBDBDGAAEAEBFBCBFGHBEGDHDECECBCGFGFBFAC,False +442,21.0,17.0,17.0,31.0,26.0,21.0,12.0,20.0,AAAGDEAFCHCBEDDBDBDHCAAHBDBDADHFHFHFHFHFDFEADADHHCHDDCFBFACHDEEEDABADAFEFHCACFFFEFBBEHGDGEGFDDCDGEGECCCCCFCHDEEECGCFDEDGBBDBGGHBFAFEDADFDHEHDHAGDGDBAEEEBEDAHAEBEBEAE,False +443,22.0,20.0,27.0,22.0,26.0,31.0,22.0,17.0,EDEAHFDFEBGFEFHGAFAFEDEAHDFBEDACCCBCBAFADAHFCGHGHDCDCGGHBBGACADFEFEFBFBFBHBHAHAGGGEGAGACECECBAEFFDEECDFECECBCEHDFCABHBCGDHBFBFBFAEDCFFHFCFGFDEDEDGFGFGFBCHEGGCEDGCCHDGFGCCCACEDEAEABABADFDH,False +444,25.0,15.0,17.0,18.0,21.0,13.0,21.0,25.0,GCAFBBBBAFGHBACAFHCECHBEDEHHHEDAHABCGDEAAABDBHAHBEGGDGACDBGGGGHGHGCECEFHFCCGBEEEEEDFCGDGDADADCECBFFCAEAEADGDHAHAHEHDHAHEFEHDGFHFHBDDAHAGAGAGAGEFBHECFCACHDH,False +445,4.0,5.0,1.0,1.0,6.0,3.0,0.0,1.0,FEBBABEBEAFHFEAEAEBDC,True +446,3.0,5.0,3.0,4.0,0.0,2.0,5.0,1.0,DBDAGBGCGCGCBBBAGFDHDFA,True +447,27.0,17.0,19.0,29.0,21.0,26.0,19.0,16.0,AAEEEEFDFHEADAGFGFGAGHFABBBBDADAHFDGCHFDFAFGCCBFFHDHDADEBHGCAHAFCCGCHEEADCBFFDFAFACAEECDCDBHBDCCEDEAGABDBDGGGGHFHFHDEAFDCDAAABAGCGFDFEEEBGAGAHBGDGDFDFDHHACCDCEBEAECEFEFDFDBDB,False +448,12.0,3.0,7.0,7.0,6.0,6.0,10.0,15.0,GCACACAFHFHGHDHAHDDEDCFAHACAHGEFHBHBFGDEHEAAAGAGCDAEGEBHDGFGHHCHGH,False +449,27.0,20.0,31.0,20.0,16.0,31.0,25.0,16.0,CCFCACAHBDGCGCBCGCDCBBEBAGFFFCFCDCBHBEFDFDHGGDCFEDBDFDCDCFFDBAECHADBCHCHCAAAAFAFADDGFCECGCGDDEHGHFFEHGHGFGFGAEFBFEFDBHAFDGGCFAFHHHBHEAGAEAEABGHFAFACACBCACGBBAGACAFFGFGFDBCBCGEEEECFADGBGA,False +450,2.0,7.0,4.0,2.0,6.0,1.0,3.0,3.0,DGCGCBDBHCECHBEGEABFBHEAEBEB,True +451,8.0,7.0,6.0,1.0,2.0,4.0,4.0,3.0,FGFHEABCCCDBABAHCHEAGCGCBAAAABBBFGF,True +452,12.0,16.0,17.0,11.0,29.0,15.0,19.0,16.0,EGDGEGHCFCFDDBECFHFHGEBEBEBEBDBAHAHADCEEEEEEEBECCBBBGDCDCFGHHEACAGBGHFEGEAECFDEGFHCEDFDFDCBHEAEAEFBGCGBAHFHGGEEBFGFGEHAGAGAFCBHHHCCECEG,False +453,4.0,3.0,6.0,2.0,6.0,8.0,4.0,3.0,CCFCEEHCHBDEFAFAFHGDFEGEFBFBFCECGAGA,False +454,17.0,13.0,25.0,22.0,19.0,16.0,28.0,27.0,AGAHHCDEDGGGDHHFEEGEHHCGGHGABCDCDAAFCFCGAGCFFFHEEEHEBGBCFHDAEEBDCDCGCGCBHBFCFHDHGBGDHCHFHBHDHBEAFCCDEDAGCGCDCFFHGHGHGAGADACAEABFCECECEBEHAGAHHDGDGHGHGFDFDEBCHDDCDGBGEA,False +455,3.0,8.0,5.0,6.0,3.0,3.0,1.0,4.0,ADHHHDFFACBCBCHCBDDGDBDBEBEAEFCBB,True +456,17.0,25.0,25.0,21.0,21.0,26.0,24.0,21.0,GEGBFBFBFBGAHAFACDEDCCHFFGBGAACFCHGFCFGHDAEFEFGFGHEBEBDAFGFAFCCBABEHCGFEDEDGBGBFBEHEGGCDCDCBGHDCCCDFAGBHBDEDHCHCHEHCBCDDDDFBEEEEGGBFCFCHAHACGFBBHDHBABGBGDGDFAFAECECEFDFDBGCHBAAHHEH,False +457,12.0,10.0,8.0,8.0,4.0,11.0,8.0,8.0,DBDFDFCCCHBEGFBHEFACBDBGHGBFAFGHAHAHGDDDCCACGCEHGFGFBFBABABDHFAAAEAFA,False +458,20.0,11.0,18.0,22.0,26.0,28.0,20.0,28.0,BFGHCHEAEAFFFFGABCFGFECECECECHCHGHDHAHEEEFHAAFBCGHDHDHCABGHCFDGHGACFDDDBCGDDFGGGGEEABGFAFEHAFEHAFAEAEABAGFDFEEHEFECDADHDHBHEHDHCHFHDHFHGDDDDEDEFEFGDCHCECEFHFAGBFFEFCADGBGBHA,False +459,18.0,25.0,19.0,16.0,13.0,17.0,21.0,14.0,CACACDEDBCBHAAGHBHBCEDEDAGGHDFDEDCHFHECFBFACAHAGGGGGAGDFBABFFGFBHBHBGBHBACABHBGCGBGEFADCDCHAHDHDBACABBBGEGEFCFBGBEFDFABABFCEGECDCBCGDBEGFFCFDGE,False +460,21.0,19.0,19.0,30.0,29.0,19.0,23.0,32.0,FDEDECCDEEHFDFEFEFHAHDCGCGCFDDDCGAGAECDHBEBAHGCGEFEDHDHDGDBHBADCDCHHFECHBGBEHADBDHGHGHGHDHFBGAGHBFBAECGGFEFEFDGDCDAEGEBACHGGDDADFHAEABBGBABDFDFABEDAHBHAHAEDEAEHEHCFCHEHEHBHBHGGCACAHEEEEFDFCGDH,False +461,9.0,19.0,19.0,25.0,19.0,17.0,20.0,16.0,BEGCGDAEHEDBDCEHECACAEAEAFCEGHGHFHGHCEDDDHDEGGFEHEFDFGFDBDBDGDEDCFCFHECBDHACCBCBFGDGCHBHDDBGBGFCBCDDGDACFGGGGFGBEBEGHDBDFCFBFDFDBHHAHAEDFBCBEBEC,False +462,9.0,14.0,11.0,15.0,9.0,10.0,15.0,17.0,CHCHCGCBEBDHEHFBGDGDGDGDBDGEGCHHBDBDACFCHGFEAHFFDCGAGBFHEDEHHAHAEBHBHGAGBFBDBCFCBCBADAGEGHHEFDFDGDAH,False +463,15.0,16.0,16.0,16.0,13.0,12.0,15.0,14.0,EDEGEDHBHDHDACHCBCAHADGDGAEEHFGFGFAEGEDECGGAFAFDBCHCGCEBABABABDEACHCBABAFGEACFDBBCBEGEGCDCDADBDFHHHHHBDCDGBFFGFHCBCFG,False +464,20.0,13.0,10.0,7.0,14.0,12.0,14.0,15.0,HHHBDFFCHCGCGAGDFDGEBFBABAFAFHGHBAGEGEHBACFCEDBACCCABADAGBGAGEEAAFAFACGCFAHEHEDEBAGEHEHEGAGAEFHHHHABEBDBF,False +465,32.0,28.0,23.0,18.0,15.0,22.0,28.0,21.0,CAHHBFBGCACEGFGAAABABAGGCGCGEAAGCGEEDBDGDCDHDBBABAFABAEDBGCEDBDBAHABFHEDEDBFFGAGHHEGAGHEECDCFBHCGBDBDBFGFDFCFAAACACFGHGAGDCFGAGFFBHCHCEABHBFBFHFAFHFEFBABGBGBGHHHAHAGEFCCHBHCAGBCDCECADADAG,False +466,14.0,31.0,26.0,20.0,17.0,27.0,15.0,13.0,BBBBBCGFEFDFDFCCDCHHDAFADACCEAGGCGCACFFEGECEFECCACGEBAGDGHBABDBHBHFCBHFCFCAHDCDHBGFEEDEDFAFHHGBBFAFCCCFAFDFEBBABACHHBDBDBFBCCFFFFFFDBBBBBEBECEGEGDGDGEGCHEBCDFBBBDD,False +467,15.0,12.0,15.0,11.0,17.0,18.0,18.0,13.0,HAGECCBCFHEGGGGBGBDBGBAFACCFCFCBDFAAAAACEEEFECDFDCDCDHBGGGFGDABAGAFFEAEFHBEDEDEFBAHGCGCHFGFGFHHDHECEAEGFAFHHEHEBBGEHFDC,False +468,22.0,12.0,14.0,17.0,19.0,18.0,16.0,15.0,DADADADAHAGABAEHFGFGEGBHBGADHDGGACHEHCHGEFFBCGCAFGDGAEHEAAFCFGAHAHEDDFDCHFEFEDEBECABEFGBGAGCCECFCBBBBHAEBECCADEDHHHEDEDEDFFFFGDAAAFCF,False +469,18.0,26.0,29.0,20.0,29.0,19.0,16.0,15.0,CGCGCHCFCGHHCHCHCHCFAEAFFECEBFGDHDCECECHCFFDBDEDBGGEGAGEHBBCCACABEEEAEBEBACECGADBBHBDBEFEFEFCDDGCCBAHHFCBHBADAGFDBEFEFEAECBFFHABDBAEDECECEDBFBDBDBDACGEGEBADCDGBGDGACFEFBAEH,False +470,6.0,1.0,5.0,5.0,3.0,4.0,4.0,6.0,CBCAGGHDHDHDHFHFEECACADHCAFAFGEADG,False +471,8.0,12.0,3.0,4.0,7.0,8.0,8.0,2.0,GAAFBEGEFDAGEGEFEHGBCFFFFGBBBEBABABDBDBEBDHGCABACAGF,True +472,9.0,4.0,9.0,5.0,3.0,6.0,1.0,7.0,HACGCABHCEAFHBHDAAACFCBEDEDADAHFHFCFAFBCDCHC,True +473,2.0,1.0,5.0,2.0,7.0,3.0,2.0,10.0,CCHCDDGFHAEBEHHFACHHFHEHEHEHECEG,True +474,8.0,7.0,5.0,9.0,9.0,4.0,1.0,12.0,BCDHBCBADCDHHAHDHAHEDEDBHEEDHCHAFAHAHCEGDADEFEFEFABHBEB,True +475,11.0,5.0,2.0,1.0,3.0,2.0,5.0,4.0,AACDCFHAGAGAEBGBHBFEAGBGAAAHAHABE,True +476,25.0,30.0,25.0,21.0,26.0,22.0,25.0,24.0,HGHEDBDBCHEHEDEDEDEDCAHDCGCFDFGEGDGAGAGHGDGDCAAHABAFACBCBCEDEAEDEAGDFEBEBEHGHFHFCBBFGHGFEFBBBFHGBCFCEBABADHBCACGFHFACACDFABHEAEHHDGACHFBFBHBHBABGGDBABGFEFBHGHAHEBGBGCFBEBECGCACEFAGECACFDFEAECCBGHCDD,False +477,15.0,14.0,22.0,19.0,17.0,22.0,25.0,22.0,DFGGGFHHCHEHBGDEEBFBAAHGFGFGACCCGHFHBHCDEEFEFBFAFBFCGCEDEHEHEBFAFAFAFGCGCGDBCBFFCHCDDDEAEAGDEDECGDGABBHDHDFDFDGCGAHEHFHCHAACDDBHHACBGBGAGFFHCCGHHCCGDGDGCGEE,False +478,14.0,12.0,9.0,13.0,13.0,17.0,7.0,13.0,AFAFBFBDAAADFFBFBEHGFEFHAHFGDDFDHAHADABFBFHEHECCACGFBDBGAEHCDCHGHGEAECECEFECADFDBGBHBHEHDDFEFDBEAC,False +479,29.0,20.0,16.0,24.0,27.0,18.0,17.0,26.0,GEHHHAHEGBGCHCBCFGDGBFDHCCBCHFHAEFEGGDHDACEDDDCDFDFDHBAADHFHBEFEHCHCDFAFABAEGBHBABABAEHEAEAEDEAFHEDAGEBEFGCEDEFEDHBFFDFAHHDBDGDHEAEGCBDEDBAGAGAGAEAHACACAEAEBHAHGFGEBEADADBHBHFCC,False +480,11.0,14.0,7.0,9.0,18.0,15.0,6.0,9.0,FAFEGDGBBEFEDEFEFABAGEGEFFFBBCBEDABEGAAAFHFDEHHFBFDFAFCDCDEGHHCHBABCBEHEHEBEBEDEHABEFACDC,False +481,8.0,4.0,7.0,16.0,11.0,8.0,9.0,4.0,EEADADFDEAFBFGEGFGDGCHDDCDEBEGEGCFCHDAGCGDGAECFCEDDFDEABABADDDDEHFH,False +482,11.0,7.0,25.0,5.0,16.0,24.0,10.0,11.0,EAEAEACFCBCEFEGAGAGCCFFEFGBCFFHFCFAHACFCEEHCCFDFEEHBHFHAGFFEFEBDAGCGFAFEFEHECGCGCFCFHFHCCCBCDDBCCCCFDFHAECBHG,True +483,24.0,31.0,31.0,29.0,20.0,23.0,19.0,21.0,HAHEECBBBBGBECEFBFHHCHFHDBGBHEGEADAEAEBBFBCECFCACABHCHCEBFDFCFCFBFHHHEGCDCDCDHDCECGABADDDBAGAGAHEDEBBDGCBCFAFABAHCBCFHGHBDEDGBGEHCDCFCFCAHFBCDCDGDHABGFEBDBDBDGAFAGAFDDCEFABAFDDGAFEFDGCBABHCGDGDCDCAE,False +484,10.0,14.0,9.0,7.0,6.0,9.0,6.0,9.0,HCACBFBFCFCFHAHADACABDCHGHGCBFDHCBGBABFBDBFBEEHADADHBBEBADAGECEFHBGEGF,False +485,10.0,4.0,11.0,5.0,13.0,7.0,15.0,10.0,AEAEHCHCGCGCBEGEGFGBGAGFGEHAFGCHDECCAHADDFDFHFHEGEGACCBHDHAEGEGCGHBEEEGAFAC,False +486,10.0,4.0,4.0,3.0,10.0,7.0,9.0,8.0,HGHCFDHAFAECEFHFHEGECHDDACABAEEEGGAEAGAGAGAHFGFEHEFGBBB,True +487,5.0,6.0,9.0,7.0,10.0,8.0,5.0,12.0,FCFCFHFAFAFGEDCBEHHGGEHEHAGBHCHFEAEDEDBHADCBCDHDHDFBEBCCHCGEHE,False +488,11.0,11.0,11.0,8.0,15.0,8.0,13.0,12.0,CBABEBFHFGEGHCDCAGDGEABBCGGBBHEFBBABGBADEHCHCEAEAEGEFFFCGCEHDHDHECDCAFAGAGAGEHEGFDHCHEHED,False +489,22.0,25.0,26.0,26.0,18.0,25.0,28.0,23.0,BEBEBEBFFHDHDHCHDHCCGCFAGCHCHCDCGCABABAFCHEHBCBCDCGCEHAHAEGGABFDHEBECGCHCHFDADAHHEGFBHAHFDGDCCCHFFGGGGBFAFABGFEFAGGFGDBAHFEGEGEDBBEDDBHBDFDFGGCEFGFBFHGADADHCEGEGDGDFDBBCBCDGBADABAFCFAFADDDBCGAE,False +490,19.0,24.0,22.0,16.0,30.0,19.0,23.0,31.0,FGGAFEFECGHHEGEHEDEFEHAGFBFBFHAEAHAEAEACDEBBHCECACEGBBFBDBCHDHGCFEHHAHAHBEBECGGDGCHBHGFGBDFCGHGHDHBHBACACHBEAABDHEHDHFFBFHFHEBCDEDEDFDGEGAGADBCHFHABDBDCFAEAEBEBECGCGEHHCCBCHCEGEGHFCGEG,False +491,16.0,23.0,19.0,29.0,31.0,20.0,28.0,25.0,DHDBCECECAGFGBBEEEECEDEGHCDGGAFDFGFGCGCEHGHGEDFGCDFGFDDDCDEFEABDEDEBEBHBHBGGHBDBHAFABDGHCECGAEAEAGABHDHDHDHBBBGEHEFEDHBEEEGGCDEFGHGHAHAFCFGFEDCFEABHFHEBEBDHDHACBCFGAGFGHEHBGBCHFGDDADCDADFDECB,False +492,2.0,8.0,8.0,4.0,4.0,4.0,9.0,3.0,GEGFACBGAGECCHCHCBFDGHCCGCGBDBDBEBEFDFBGBG,True +493,21.0,13.0,20.0,26.0,11.0,13.0,10.0,15.0,AACGHHEEDBDBDCDCDBEBFBFEGDCEADDDFAFAEAHHHFAFADEDCHCBCAAGACDDDDDBCAGDCDBEHGHGFGABDHDHCCCCHADAEAEDHDAACAFAFBFEDGBHCCADHBGBDFCFCHCFG,False +494,4.0,3.0,5.0,3.0,3.0,7.0,4.0,3.0,AHFEBAHCHGFGFEFDADBFFCFCGCGCBEAD,False +495,0.0,4.0,1.0,1.0,4.0,0.0,2.0,1.0,BDEEBEGEGHBCB,True +496,6.0,16.0,13.0,12.0,12.0,13.0,12.0,10.0,DHFEEBAFCHCHCEFHABBCBCFGECECEGEBDCDCBBBBFAFEBEGGCGAGFHEDGBGEGCHEBDBHBHCGBHAGDFDFDFDFDHCADFDFGB,False +497,19.0,9.0,12.0,22.0,14.0,24.0,20.0,18.0,DEDAHEBAAGDBHHGABAGCHCDCACFCGCEEACBFAFAGEDDDHHHCHCGFGHBAGAFAHDDDDDGDFDFHFEEDEHFHEBFDFHBAGHGHFHFEDEDFDFDCGBFACAGAFHFEABGEGFGFGFECADAGGDGFFF,False +498,8.0,3.0,6.0,14.0,8.0,17.0,6.0,15.0,GFFDFEGGBEBHAEDGFAFEFDDDAFHCHCDCDGFHAHFHFGDHCEFHCHCFDHDHAFDFEFAFABAEHFHDHDEDH,True +499,0.0,6.0,1.0,2.0,2.0,3.0,3.0,4.0,EDECHDBGBGBHBHFGFBHBF,True +500,9.0,11.0,8.0,10.0,19.0,12.0,9.0,5.0,GCFDBACGFBFAAAAGBFAEGFGCGHEAGHDFFCEDEDEDEDECHBEGDDEAEFDFAFEBEHEHEDEBEBEBCBCBFFEGBCE,False +501,8.0,14.0,12.0,11.0,8.0,12.0,9.0,4.0,DBDBEBDBDFDAGCGFBCBCFFGCDCDEDBBBECECFBFECABDDAFAFAGEFBHAGAFCHCDCGHGHBFBEGEFCAG,False +502,5.0,5.0,5.0,5.0,9.0,6.0,4.0,8.0,FEFEBHHHAHABEBDDFDHDCAFFECEAHCBCEAEBHGHGCGFDEGE,False +503,12.0,12.0,13.0,25.0,16.0,10.0,18.0,21.0,GBGBDECCCFHHBACGDGDGDADCGCBBHDHDHDBDFDFDHEHGCEDEGEFAFHBEFFGCEHFFDDHDHGHGDAACAGBDHGHEDEDGAHCGDGDACEGAHAHDHEHEBEBCBFBEHEADDGDCAHE,False +504,10.0,15.0,9.0,13.0,14.0,7.0,8.0,9.0,CBEEFBBGBGBDBABADFBAAHEBEDEDGFCEBDBHAHBCBCBGGFDFCAGAFDGDHDHGEBEHFHECECEAHCDDEHEAEADCD,False +505,18.0,16.0,17.0,23.0,12.0,18.0,20.0,12.0,FGFABEFDHDHFHGDBDBGBGCACDDDHAHBHFFFBGCGEAEAGABHBGDGCECEDHFAGBDEAAHCEGHDEDEDFGHDDDDEFFAFGDGCFCFDFDACFCEAABGBABCBCFHGGBGEGAACCCCFCGBADADBD,False +506,22.0,16.0,25.0,22.0,25.0,11.0,27.0,18.0,AGCDCDHDBGCGAGDDCDGBGDCBCGFGHCECGHGAEFEDEAEGEFHGBCBCAAAAGGDGEHEAEDEDEBCBGFCFGDDEDECFDHDBEAEDEHGHCCCCABAFABCBAHCHGHCCDCEFAGEHAGAGHEBCHEGBHBHDHFEEEACACDEDEHGGGFBFBGDAAA,False +507,13.0,17.0,22.0,10.0,17.0,14.0,17.0,13.0,GGGCBBBEBHAEAGHDCGCDHFEAEABHCHGFGHGCCFFBCAAHEHEDCGCGCDADEHAHFDFAFCHCFCBDEEAEFHAHFCFABBDBDEGECEBGBGCGCDEEBEBFBEACBCGCGBGCFCF,False +508,17.0,21.0,24.0,12.0,17.0,20.0,19.0,17.0,ECHCHCHCGCFBGAGEBEBEBDCCFHFGCDFFHHBGBGDDDGFCFCGDGFAACACGFHDHGAAHAEBEGCCCFGFADADHBBBBABEBEBCGCHDHBGEHCACECEDDCFFAFEBACAEHEHBGBHEFAFBGHGFBCBEAEAGFFCF,False +509,4.0,0.0,5.0,5.0,1.0,0.0,3.0,4.0,GHDCDCDCDCAEHGCDHHAAAG,True +510,10.0,11.0,3.0,4.0,7.0,2.0,18.0,3.0,HAGGGGAFAGCGEGBGAEBGGEBEBDCEGDBDADEBEGAGAGBBBCGGBGAGHBHAFA,True +511,2.0,4.0,2.0,2.0,1.0,2.0,3.0,1.0,DEDFHGABBBBFAGCGC,False +512,2.0,4.0,2.0,1.0,1.0,1.0,0.0,1.0,HDBABCBCBFEA,True +513,4.0,5.0,8.0,7.0,6.0,8.0,11.0,4.0,GGHGHGDBCECECEGFHDABADEGGCGCECBFEGACFFFFBFCFHBAGGDDDD,False +514,20.0,26.0,19.0,15.0,24.0,22.0,24.0,21.0,FGFEFEFBHGHBEDHHHHEDCDEHEHCBFHGAFAFBFDCACAGGGGGGGHBBABFBFBCHGGBACGCGDFEEEEAEFFFFDECECFCBCBEAHCBADEDAGFDEDBBEBEHACAFAFABHEEDCFGHDAABEBEDGGHGHGDDFEFAHAHBGCGBGCCCABBHBAGCBHBE,False +515,22.0,23.0,26.0,33.0,16.0,30.0,25.0,23.0,GGGGCBEHCBCFEGGFADHDHCGDACCDBDGFCFHBHGAABFBAHAHDGDBDADACGCFDFGFDDHBGGGEBEBEFGFHBEFABEGCGCGHAHFHFHDBDBDCDCDCHFFFHFDFAGEGBABFEDBDCECBCDDHDBGECADEDEFFFFAFDFDECGHDFDFBCGFECHHAHAHGCBCDADAEAFCFCDHDABAHABC,False +516,17.0,13.0,13.0,12.0,15.0,20.0,10.0,20.0,FDFAGABHFHCEEAFCEGGBEBCBCBEBDHFACGHGCACACAHFHDBGFGDAEAEABFDEDHDFAFEBDHHHFHFHFHAHAHAEAFADCCFBBCEHFFFDGDGBEHHHHGCBEFEAEDFC,False +517,26.0,21.0,23.0,17.0,23.0,30.0,24.0,22.0,ABAEAEAEBGGGGGAECECEDFCEBAGHFHAEADCCGGGAGBEBEBEDCDFAFHFHGCCBHAFAFAFHFGBCDDFACGFGHDEEGEFEGBGFGADFCFCFCBAEABCDHHHCHFHFHBHAEFFFCFBECCCFFDFDBCHCADAFHBABDFDBBAHGGEAEHCGEGCDAGAHDGDFHFHFEBABEBH,False +518,7.0,13.0,9.0,12.0,7.0,6.0,7.0,5.0,CGCECBHDEBGBAFCDBDBDACEBDDGDGEGEFAFAFAHCFEHEDBCBDBDCDBBBDCHFBAGAGH,False +519,15.0,23.0,14.0,11.0,17.0,17.0,14.0,16.0,AFGEDCHBBBBBBGGECEFFBACACBCGCBHFAAABCCEEDDDHBBFBFBGEHEFDAEAFFFEHAGABAFHFBDBHHHBEBEACGCGCACDCHEEBEGGDGHGHGDDDCBGAEBEFEFAFHHHFHFB,False +520,18.0,12.0,17.0,12.0,18.0,12.0,16.0,36.0,EGEHCHDHDGDGCADAHAHFCEEBACEEEADAHHBCBEHEHEBAHCEEGCFEFAFABHBHGHDCGCGDHDHFHDHDHAHCHABCGCFBHHAHFHFHFCEHEAAHHBHGEAHHBFCCGBGFHAEAEGCHBHGDGDGAGFHHC,False +521,4.0,11.0,9.0,6.0,9.0,15.0,6.0,12.0,FFFCCHBHCFCBCBFDDGDGBFAGCFEFCHCGFBBBHCHDEDEAEBHBHGAEAFFBEGEHEHEHBHFFFFHD,False +522,17.0,10.0,12.0,14.0,22.0,13.0,17.0,18.0,EEEEDEABAGFEFEHGHBDAAABDBDAEHHAHGHGHDHAEABHHHHHBCGCFCFCDBAGACEEGCGAADGDHAFCFCEBEFDFEEACGHBEFEFEFEDCGFGHGEGDBAEGEDCHAHGDFDGC,False +523,0.0,4.0,3.0,2.0,1.0,0.0,4.0,2.0,DDEBCHCGBGCGBGBH,True +524,25.0,20.0,21.0,11.0,21.0,16.0,21.0,28.0,FGHGHEHEHBHFHFBFBDBEGDCHCGAEAFCDEAAACHEHEHBFFFFAAHCGGHGBGBHCHCDCGAGAGBHHHFDCDAEABBBCECBGGFACHCECEAFAGHFAEHGGEDEDEBHHACCCACBCHDGDGAAABAGFEBHAGBGCFEEDEAEAFBECHHAHBHB,False +525,5.0,5.0,3.0,6.0,5.0,16.0,3.0,8.0,DHFHFEFEADAGEGECBDFCBDDFHCHFAAAFEHHFBBBGDFFFFFFFHFH,True +526,1.0,0.0,1.0,1.0,2.0,0.0,4.0,6.0,HGHCHEHEGGHGDAH,True +527,14.0,26.0,15.0,11.0,16.0,18.0,25.0,17.0,BHFABADGFABCDGGECEBEFEDBDHGFCFDBDBCEFBFHAGBFEFGFHFHCHBHEHFHFHCHCEDBDBEGHGHGCBCBGDEEFCFBGBGBGBCBDBGAEAGBGAGECEAFGGGHGCCAFGGEAEDBHAGABAFAGHHCBBB,False +528,26.0,33.0,22.0,21.0,21.0,26.0,21.0,23.0,HDBFBDGDGHHEBFFCECFBABGGEBEGGAHEHABGBCCCABDFEFGFADACCGABDBFBADADBDAHAHBEGHFHBEGEBCBCBHAHABADCHBGCDEDEDHGGGGGCDBFFFFFAEECHCHCFEBEAADFBFBABDBGEEHEGEFCFCFEAEADCGFADHHFBDBAHAHACABABFBFCFHBHBHCDFGCD,False +529,19.0,28.0,16.0,26.0,16.0,17.0,19.0,17.0,ABADGCGBHDFFFGFGDGFBDGGFAFCGGFHHAAFFFEAAHAHCBCBABADDFFFABDBDBHGDACHCHGBBBBBGEDADAGCBEBHHEDBCBCBDEEGADABABADADCCBCBDFDFCBCHFEEEDEHHHGHBHDEECHGDGDBEEEDEDGDGCBBD,False +530,10.0,4.0,8.0,6.0,5.0,11.0,7.0,6.0,FFBFCDCGAGFEDCDBEGEGFCFCFCBAFDBHAHAHAGACAHAHEGDFCFADEGAFH,False +531,13.0,7.0,11.0,9.0,7.0,13.0,13.0,17.0,GCABEBFBAHHHGHGAAHCHBEBCDAFHFHBCDCDCDFGEGCHAHEHCHDFFFGFGCGAAAHGGGHFCECHHHGAAEADFBFDFDEDAGF,False +532,6.0,4.0,4.0,4.0,4.0,11.0,3.0,7.0,ABCDHFHFECEDADFGHAFCFCFBFBGADEHGBFHEHFHFAFA,False +533,14.0,30.0,24.0,27.0,22.0,23.0,21.0,29.0,CEBEDGCHDGAAABHEHGCGBFBEGDDDCDCHHDEGFHCEFBGBCCFBAEAGABEDFDCDCDHDHGFGHGCGDDFBBBBBDFDADCDGBFEFDBCFCFBDHDGFACAGFDFDEAECFBBHBHCACAHFDEHEHBDBGBHBFBEDCFEEHBHBCBCBHEFEFCHCHEAFHBHBHEHFGCAEGHGHGHGHED,False +534,7.0,14.0,11.0,10.0,12.0,6.0,11.0,7.0,ABADCBEGAGABDBHCECDBEHGCBCBCGCFCFHFHFBBCBGEGHGDGEGEDDDCDEDABAHCFEEAEFEBBGDEHBG,False +535,1.0,8.0,7.0,5.0,5.0,7.0,1.0,7.0,BHBGFHEDDFCBBBBHHHFEFHFCFCACBDBDEHEFECCCD,True +536,5.0,4.0,11.0,11.0,13.0,6.0,6.0,8.0,CDDDEBHHGHDFGCCACEDEDECEGEACACHEBFFEFEFGFGDGDHAEEEABCBHEDCDCHHDC,True +537,28.0,21.0,11.0,18.0,13.0,11.0,21.0,19.0,HGAGAGFDDHGEBDCGAAHGHEDBDFDEGAGHDECCAAAADDGBBCBHBHBHGCGCBBBFBFGABAGCHBGAFHFAACAGDFEFEGGBFHAADADFDADBBBDAEAFHGHEHEHAHAHAHAGEGDCDCHBABABECDGAEBE,False +538,3.0,5.0,4.0,4.0,5.0,2.0,1.0,6.0,HCHGHAFBEBEAEACDCHBEBFCEHBHDDD,False +539,6.0,6.0,7.0,4.0,9.0,4.0,6.0,1.0,CCAGDGDGEFBCACBCGDDBFEFCFEABABCEEEABAEGEGEH,False +540,4.0,1.0,2.0,4.0,0.0,6.0,5.0,0.0,FDDGAGFGCGAGAFFFBCDADF,True +541,9.0,14.0,13.0,6.0,8.0,6.0,10.0,5.0,CBCGEGEFEHAGEDBGEGAGHDCBCGAGAGHDFGAACBBDBDFFCFHFDACACBBEBECCCCHEACBBBBB,False +542,16.0,16.0,8.0,16.0,13.0,11.0,10.0,17.0,EAHAGFDCGCGDEHCHBAAADHDHEHEFBGBABFDAAADBDADADHDGEGCGHGBFAFEBBBBHFDFDEBEFAHEBDGFHCHCHGDFABABDHHHAEBEHEDEBCCF,False +543,21.0,26.0,17.0,27.0,29.0,23.0,26.0,18.0,GDEHHBFFAHDHDCBHBGEDBDGAGDHCEEEBFFACBBEDGFCFBEBECAFDDHBHDEFEFEFEGGCGBHFFCFEHBHEFBHBADAEAGAFBFGEGEGCGDEDEGCGCBDFDFDADABCFEBBBDBGGGFGCDCDCACFEDBGEGEGHABGEGEAAAACCHEBEDEHBABFGFHHEHADGDADADAD,False +544,22.0,22.0,21.0,19.0,23.0,23.0,21.0,20.0,CGDGDBCFDADCCGDBDHAHCHCEDFFGGGECECEAFAHCFDDEDAGCGCBDEDEAEHCHCEEECEFBFHDHGHGEGCHFEAEAEFFCFEDEABHHHGFBAGAGBDEGECECECHBHAHGBBFBGBDFDGAAFAFGBBCBGBFHEHCBDFFFHFBAAHBFBAAAFAGABDB,False +545,23.0,25.0,25.0,15.0,25.0,17.0,21.0,33.0,GAGAGEEHHHFHFHFHEHDCFHABBHBHBEBHFGBCCACACACGHBADHBECECEBABECCHCFEGHDCEBGGEBEBEFHHADCDCDFDHBHCAEEHEHFHGHGHFADCGFHCACACACBCEGDFHCABGDGEGFCDHGHAAAHBHBHBEBHBHAGABEEGEDEGFBFCGEDAGADDBBEAFCF,False +546,3.0,2.0,2.0,4.0,0.0,4.0,0.0,0.0,ADADAFCFDBBFCFD,True +547,13.0,21.0,3.0,11.0,13.0,5.0,12.0,11.0,GHBADHBHBGBEHDHEEFGHDHGFEDDDEGEAEDFAAGBBCBAGAGAEDEHBHBABABAGADBEBECEAEBBBBGBHBDFGCADBFBHG,False +548,25.0,24.0,22.0,17.0,28.0,18.0,39.0,21.0,CDCABDBHBGBGBGBCECBABGBGAHAHBFEEAEBGAGEHFACACDEGEGECHAEGEHFHFABEGHFHAHGHCDCEBEGDBFAFHGEGBGAGDBDBDBEFECHFHEBFGEGEGECAFABEBGBGHGFGEGCCCCHGFACGBHAHAECFGAEDHGHGDDDEAFADGDGDCAEGGACFBFAGEGACCEHDCDGGFG,False +549,3.0,2.0,4.0,4.0,5.0,8.0,5.0,2.0,HFEFGDGFBFDFEEEFEFGBGCCACDCAGAHFD,False +550,1.0,3.0,4.0,3.0,7.0,2.0,2.0,6.0,ECEBHBHGHBECEFDHAHECEDEDGCHF,True +551,16.0,22.0,21.0,26.0,28.0,20.0,19.0,21.0,EGEDEBEAEADDDCFCABGEFFHDBECHBBBBAHAFFCCDDDDDDHGHEFAAAAAGGBGFGBGCCHEHFBFHHDCDFFBFDGEGFCABBEBEBECDGFEECACDDBCFEDEHHDBDFHFHCHCEGGGEGEADCDCEGEFFHHGCCBCBDBEBEAEAEAGDFHCDGDHBHEHEH,False +552,4.0,5.0,6.0,11.0,3.0,11.0,11.0,5.0,GCCDFHFBDDEDECGCGDGHABDDGGGDHAHAFGFGEGFGFABDFHFCFDBDBFFC,True +553,5.0,13.0,12.0,7.0,6.0,1.0,8.0,8.0,BGDACECGDGCCCBCHCGCDBHHGBEAEAEFBCBEBDGCGDGCBABABEDCHHHHHBBDB,True +554,21.0,23.0,19.0,23.0,24.0,21.0,32.0,21.0,FAGAHAHFHGHBEEFGADABCBGBGFAHEDEFGFBHCECEHEHDGDEAAHGGGEGFFDFBCHGAGHCDGGGABDGDADHFEBHBHGGCACBCBCBGBCFADADGDEDACBGHEFDFHFHFBDDDDBHBGGGCDEFEGEGECHCBCBEBEBEFFAGBBFACECECDAEFECGAGEFDGGAADHDH,False +555,11.0,14.0,17.0,9.0,22.0,14.0,9.0,22.0,CGEEDCDADADBDBFFFHCAAEHHHEHEHAHEFFCFBGHHHFHCHDHEBGFGFBEECFCEEECGCGHEEEEADHBHAABCCACFCEDHCHCHBHBDBECGCEFFGFABBEBEGHAHBE,False +556,4.0,3.0,4.0,4.0,4.0,1.0,0.0,1.0,BABHECAAFBDCDEDEDECAC,True +557,11.0,15.0,15.0,16.0,14.0,18.0,14.0,14.0,BCBCBGDGCGEAHHEHGAFFCFHFCGAGACEBEBEBAFGCCDGBCEFDFDAEADDFDCEBFBFBEHDHEHEGEGBGHFHDDDDCCBGBCBHAHDEFFFGGCHBEAAAHFFDFDFDHC,False +558,5.0,2.0,3.0,3.0,1.0,2.0,3.0,2.0,DGDGACBFHFHAEACABACDG,False +559,29.0,26.0,17.0,17.0,20.0,26.0,24.0,23.0,DADCDFFHFAFACAFBDBACAGABFGFBHCHCFFEFEFGHGCBCAEGGGDBDBABFHFAEADDDEDEHAAGGDBHGFFFFCGAHBBGBGECEGEGEGEBEDCFFDFCCEAAFDHAEBFBFAHAGFHCCGBGBGBGAGABEDADHEBEHHAEFHAHABCBCHAEAFAEBHGHBBBAGDHHHHC,False +560,7.0,9.0,14.0,11.0,8.0,12.0,13.0,5.0,FCDCEFEFGHDAABACGCGCGDEBAHHBCCFCFGEGDBDBDBAFECDFDFEGGCAFABCFGFGEGHCDEDGDGFCBCBH,False +561,16.0,32.0,21.0,19.0,21.0,20.0,22.0,22.0,AFBGBGHGEDFAACDCDCEFEBCFCGHGHFDABABAHCCEAHBEDEDBDCCHGHEBEBEBCDEFGDGFBFEDHDHDBBBFFEGBGHEDGDFBGBACDGEBEBHBHCCGHGHGDGDGHGHBCAFHGHGFABAFAHAFCBCBFAHDHBBCBGFEBABCBCFCFEEBCFEDEAHBE,False +562,18.0,21.0,6.0,6.0,14.0,3.0,15.0,20.0,DGAAHCHBAFHBHBGCAEAEAHAEAHHHBCBGGEBDFAHAEAEBGAGAHDEGHAHBEAEGHGHBABHBHEDCGHGBEDGBGEGBGBABDBAEEHFHBCBCBHB,True +563,19.0,18.0,15.0,19.0,14.0,16.0,17.0,24.0,FAFAFABBHDCDCDFDCAABFCEDBBECDCDFFAGADBCHGGFHDHGHEECEGDADABEHHHHCHDHDFAHGFGFBDBCBFHAGABDBGBFDGGFCFCBHBHFHEHEHEGAGAHAGABAGABEECDCHHEBEDEHAGCGHDH,False +564,3.0,3.0,2.0,1.0,0.0,0.0,0.0,2.0,BABCBDAHCHA,True +565,8.0,12.0,12.0,9.0,13.0,13.0,12.0,17.0,BFBFEEHBFAFGGGCHDHDHGCDCGEHAHEEBBAEFGCGCHCFCFDBBBHCEBEHEHFGAGFFHFHABDGDFDFBHAHDHEAABCEGEGEDCHCHC,False +566,24.0,19.0,7.0,22.0,15.0,14.0,18.0,21.0,AEADAHECBGBFHGHDHAGDGHGBGBHFHBDDDHGHDHDADHDHAHDEDADGFEFGFBDBDFAAAAABEFDHHHEGBGAAEDEGEGAFAFHHBEEHCGBEADAEFFBFDFDBDBGBHAGBCBEFDHGCACBCBAAACAGE,False +567,18.0,34.0,25.0,23.0,26.0,29.0,16.0,24.0,CHFDFHBCBDBFBHEEAEABABCGAFDFDADADADBBBCBDBFCEEEFFAFDBDBGHDHBBBFFFDABFHGCABABABAHHHHDFBFEFHBCDCFCFBFEEGECFHEGEGBBDDHDEDHFHDHDFBAECCBHBEBHBCCCBDBEGHGCFCACEFAGEGEGCCFBFEHEHCGFECGFDAGFGHCCCEEEBEHAHDG,False +568,10.0,3.0,8.0,11.0,10.0,4.0,2.0,8.0,EGEDEHEHCDCEAEAEAFFEHCDDDCACHBHBDDDHAAACAEBFAGAHDCCFEDHD,True +569,16.0,11.0,9.0,12.0,15.0,17.0,17.0,12.0,EAEDEACHEAGBHHFFAGGDADADHBHAFFGDEDEHFBFCGBGFFDGHAEAFBCBEAECDADCGCGFGEGEGAGDEDBFFAFAFCBHAEAEGEGFGFDCHCGFBHBHBH,False +570,5.0,3.0,10.0,3.0,5.0,7.0,4.0,6.0,DADCHHGACACECHCFCFHDEGABAFFFFECECFGGHBCBCEH,False +571,19.0,19.0,10.0,25.0,20.0,11.0,12.0,21.0,EGEGEDDDADCBFBFCHCHGAGDHDHDADGHEDDDDHBHBHCADEEEDDHDBCEAABABFEEAEGHGHFEADDDCABHBHBHFHFEEEEFDCEEGCBCHGAEAGABFBHAHEHAFABHBFDDDBDBHAAFBBAGGCD,False +572,9.0,14.0,14.0,11.0,15.0,15.0,19.0,10.0,EFEAEGGGDGDADFHFGFBFBFGDGBBEBEADHGCBCBCGCECGFDCBCBFDFGEDBDHCAFEFEBGCHAFGFGEEHBGCGCEEEBHCHBADCCGGHAHADAGFHFE,False +573,4.0,10.0,13.0,15.0,11.0,8.0,6.0,4.0,AFCCGEEDEBEBAHAHADFBCBCBEFDGHBEGEFFBFDDBCECDCDCECEDDDDDGDCDCEBBGDHFCCGF,True +574,15.0,27.0,18.0,27.0,33.0,20.0,18.0,26.0,FACGCDEDBABABADHDBEFECGDFHHEBCBCGHHAEBHBHGDADGDGDEEEDEBCBDBEAFHFEDGDGDBCHEAADEDEAEDHCHAFDEDHDACHBHBHEHECFBABHDEEEFEGBGDDHGFBFBFCFCEBEBFFCECEGEFEDGDCBGEGHFCECEBGBHBHDHCEFFFBGBHHHEFAAHDG,False +575,16.0,17.0,13.0,14.0,16.0,19.0,22.0,14.0,HBCFCFDFEGAGAHHGEGBGDGFHEHAFBDBDCHCHGFDEDEFHFBEBHBHBEBHBDFDEDEHEGEFFACACGFHADGFADGBAEADAFBCHEFFBEBGBGBACGGFGFAABGGDGFCCACAEAECDGGGC,False +576,21.0,18.0,24.0,12.0,15.0,14.0,8.0,14.0,CDCDFBACHGHECECEDECECHHAHBGFAAHAGFEBCHAGBBBABCBADCFEGABABCGCFAFEBHAHDHECACHHFCBBBEBECFCFAFAHAFCGDFDFDBEBDCACACADBDEHEFEDGCACAC,False +577,11.0,6.0,10.0,4.0,4.0,6.0,15.0,11.0,HHGHAHGDGCEBABABGCHCGCECHCACHDFBABFHFCAHAHFFBFGGGGGGGACAGECDGAADEHG,True +578,13.0,11.0,13.0,13.0,10.0,10.0,11.0,13.0,HDHDFAHCHGEAAAACGBEEHHDEEEDADCDCACACDGDBDBCFEAGHCFCABFBFGCEFBHHHHGBGCGCGEEHAHFBFDDBDBCGDGAFAFB,False +579,16.0,20.0,17.0,10.0,16.0,13.0,17.0,18.0,HBHCDAHECCCCBHGEFCBCGFFAFACBDGDCHBHBCBEBEDGDFEHGHBHECCCEFAGAEHDGDGHBFAFAGAGBGBGBEECCAFAFDBBHFECBGHCHBHDHBHBAEEEAEHEAGAGFGFGDABA,False +580,19.0,23.0,27.0,23.0,24.0,28.0,24.0,26.0,FGFGCHDADGDHFFDCDABFFFFBCEAECEHADCDFDFABAHABDEDBAHCCCHBAAFAEGEGFGHDHGHBHGHDCFCFCADEFEHBAEEFGCDCGGGGGEHFGCGCFFHFHGHBCBDBDCCCGEBEHFBFCFEECFGHGHFHCAEBEBEGHGHFEFDCHCBCBGBDBEAAABCCEAFBHBHDHEEGABDDDED,False +581,14.0,16.0,19.0,20.0,20.0,20.0,13.0,20.0,ACAFBEAHDHEHBHCABBCHFHCEEGCHHFCDCBBEBHFABGDHFHFHBHBHBGDDDCFFHFBFGFECDCEAGAGACCCGCDCDEDEDADADFFFAFAGHCDAGHFEEGHCEEEHECECEGEFDFEEGDDDGDBBFBFBADH,False +582,13.0,15.0,13.0,20.0,21.0,19.0,19.0,16.0,EGGAGAHBFFEFEHECDCFCBGHFFGAGAGEGCGAGBFCFDDDEBEHEHCFBDDDDDDADAFAHHCFDEDBFFFFHAGCBDAFBHBEDGFGCBCBGEGEDCDCDCFHEHGHBDGEHABEGAGHFEDAHEEEEEBHB,False +583,6.0,13.0,10.0,9.0,17.0,8.0,10.0,9.0,FHFGBBBBABCCDHBEDHGFDEHCGCBEBEHCFCFBFBDBACFHGHGEEECECEDEDEHEDGCAEADFDGEAEGGGEBABEH,False +584,18.0,27.0,27.0,16.0,19.0,28.0,14.0,16.0,FHFCFAFHHBEBFBDCHBGEDBAFFCBHBCFGFGCGCEEEDEDBABGEFBGBAFAFHEGCGCDCDBHHCHAHAHGCECAHFHFDEGHBBCACABABFBFBFAFCDCDBABEBECFFGBECCCHCFAFDDDDFDBECEAEDBFCDCEFGFABABCCGEHCABGFEF,False +585,26.0,16.0,22.0,22.0,20.0,21.0,22.0,26.0,FHDHDHFCEBBDBAAAAGFGCBEDHDHGHAEAECDCBEBHCHAHGGFDAEFCFHHHEECCCDCDCDHAHABBECACADAHCDCDFBBEDAAGAFFHCEEEAFAFGFCECEFACAEAFFHEGFHCAGECFFGBGFGDBDBABAGGGGGHHHAHDDDHHHAHDGEGFGBGBFCEDGD,False +586,8.0,5.0,12.0,4.0,4.0,13.0,13.0,7.0,DFDCCCCCCFEBEBDFFAFGCGCBFDFBAAFHGHGCGAAHGFAFGFGCGAGBCHFHCGGHFHEAEG,True +587,4.0,3.0,2.0,3.0,2.0,5.0,3.0,1.0,BGGGDBDHDFCAEAFCFBFEFAA,False +588,7.0,14.0,10.0,16.0,16.0,9.0,9.0,13.0,BCDFHCGFGAEFFFDDBBHBFBHHGAEDDFDEHEGEGEHADFEEHEGEDEDEDEHHBHBDBHBDCDCDBBFBABACACEHECGHEBDGDCCCAG,False +589,41.0,28.0,27.0,20.0,22.0,14.0,25.0,23.0,EDEHHHEACAEAEGECBBHBHBEFAFEBAFHHGHAHACAGBDBEGCDEHAHADACACGEDCCCFBBBBBFAADACAGECDFHGDDBDCDCECDABAFCBEGEDFCGBGDHACABGHECBGGCDCGEFEAGCGDAAABABABDHGEAHBGAEHGBGBFCFCFEFBHGHBAAAAHABABADAGACACGCACHDHDHAFAGEG,False +590,25.0,17.0,16.0,9.0,20.0,24.0,14.0,17.0,HDFDEGEFBBECCBDBABFFAFDFCECBAGAEABGFHCACAFAFAFHEHEHECFCHEHEHECGBDBAFEBCFAFCFAGGCFCABHGABFFEGAHAGAGCHHEHFDFBEBCBEFAFAHAEFEAAHAHBHBGDGDGCEADAGEF,False +591,17.0,13.0,25.0,18.0,20.0,19.0,18.0,19.0,ADCFCHDBAEHEHEFEACAFAFDFEFECEGADHDHEBCCCCEHHGBDBDGCCFBGDDCGABAEAEDEAFAFCGCFHFEGAGDGFHCGCEHEAGCHCBDEDCFEDHCBEBFBAGEGAHCHCBCBAHACDBDCDCHFHEGFGFGDGHGFFH,False +592,4.0,14.0,3.0,5.0,17.0,15.0,9.0,5.0,HGFEEHBHFFEFHFEGBABFBGDFBBEFEDGDEDECEBEFEAEBBBBEBFAHAGFDFEFEBGCGFGBGFECE,True +593,13.0,8.0,10.0,11.0,8.0,10.0,5.0,8.0,EAEADADGFGCDDFBFHHGADABAFHHBAEABHHGBCFCFDFAFDHDCDCBFBCCCBCEEEAEAEFDAHACDG,False +594,16.0,13.0,15.0,7.0,3.0,9.0,20.0,22.0,BGBGCGHHHEHGAAFGCGBDFAFBHCHBDBCCCFDAHHBGBAAABHHHGHGBABABCCCCCDGHGHCHAHGEGDBFGFGCGAHAGFCHGGGAHAHCHFEDHDAAF,True +595,12.0,10.0,9.0,7.0,8.0,10.0,12.0,10.0,AEFDFGFGABHBHBACAHFFEECEFDFGBCAABBCDCGEBEBHHHHFBAEADGDGHGDGDCACGCACAEFHAHGGGBF,False +596,12.0,14.0,7.0,5.0,7.0,8.0,16.0,11.0,DBGBABFCGCGEGBGCHCABEEHGGGHGHFBEBABFBFBGGGGFDFCGABABAFAHHHHBEAAADDHCFEHAHBGACDGE,False +597,12.0,31.0,25.0,23.0,29.0,22.0,19.0,20.0,GBCAEDEGEDHCHGFBEGCCDCGAFBFAFEGBBDBDBDGGCEHEHFHDCDCDEDFHHBGBGCHABGCGCFHFDEBCDHDAABFBGBHDCDCEHEBFBFEFBFHEHEGEBBDBEBABCDGDBHBDFDFDACCEFBCBFHFGCEAEDFCCDCFGGEEEAEAFAFBHBEBCBCHEHCHGEEEBE,False +598,3.0,2.0,2.0,2.0,0.0,4.0,2.0,0.0,DADAGFCFCBGAFBF,True +599,18.0,18.0,17.0,19.0,19.0,25.0,24.0,26.0,EFEFADADEGEGBBHHABBHCCGAFDHDFEHHHHHHGAAADGHFHGGGGDEACHCHCFCGEGEFABEEGEHFCFDFEBGAHCHGFGFGFGFDDHEFCFEBDFEACAFHCHFBADGCGBADGDAFCHCHDDDFDFHCHBHEEEBEBGBABABABCBFFHFDGCGBGD,False +600,18.0,13.0,8.0,18.0,9.0,20.0,11.0,10.0,FAHEFAFAHDGGGGHCBEGABABFEFAAGAGAGAGAGBHBHCFFDHBHDEDEDABCFCEDEBEFADDBFFCFHFAAGDDDDDDFFFFHADFFFBBBCDADCCADHBE,False +601,28.0,16.0,18.0,22.0,25.0,31.0,31.0,28.0,DHDHCHCEGGGGGGHGHGABHGABAGDGEGBACHDHBGADFBHGAGFGDDADGEAEACHBBFFHFEGEFFAFAFGFEFAGADDFAFCFGHBFFEDBACABFHFCCCEEDFDCDAAHFHEHDDEDGHEFCAHFFBCGCGCACABAEAEHDHFHFHFCEDEDGAGAEEEEEFDAGGGHGHFHAGEBHBAEFCFBFCEHBHD,False +602,19.0,22.0,22.0,6.0,18.0,28.0,18.0,32.0,BEHEHCBFBFGAGFFFHEEGEFFGCHCHFABHHCCBFHFABBEBCACAEAFHFABHCHGBBAHEEEEAHAHBHECACAHEHEHCGBFFHFGAGCCBCBEFEGHDDGDHFHCDAHHHHDAFBFAFHFHGHGACCCACBHBGBGBCFGFHFHFGFGFAEBCGCBDEF,False +603,6.0,3.0,3.0,0.0,3.0,1.0,2.0,3.0,AAAAHHHEAEBFCEGAGCBCB,True +604,20.0,12.0,4.0,14.0,4.0,16.0,10.0,13.0,BHADGGGBAFFHAEDBAFGFCFHFHDHBHBGFFHADDEHFFBFGHAHAHABACADFFAAGADAGAGACADDEFEFDADAHBGBABDBDBDCHF,True +605,13.0,12.0,3.0,10.0,9.0,12.0,19.0,5.0,BFBFCDGDBDAGAFCHBBBDHGADCEAABAGFGFGEGEGDGFAFEGBGAGEFFGFGEDADBBGAGAGEFEBBHGHGEDDAFAH,True +606,25.0,22.0,15.0,23.0,20.0,14.0,29.0,17.0,ABABABGDEFEFEHBAAAFDDBDGDGAGEEBHFFCAHAGABACACHEGDGDFDHGGFFHFBEDECFGHCBAGDGCHBGBGCGFDADECEBEAEADAFEBEAEFCBCBCBHBABGBHAHAGAGDDEEEHBCEADGDGDHHFDGABDBDGGCGCADGGHHDHGGEGC,False +607,7.0,12.0,19.0,9.0,3.0,6.0,12.0,7.0,CHGGCADECECGBGCGCEHDAFACDBGGFABCBCBCBCBFBCGCBCBCBFHADACADHDCGGGDFCHGFCHDHDB,True +608,15.0,15.0,12.0,14.0,12.0,4.0,21.0,15.0,BGBEFEGDBCGCGHHEGCFAGEBFGHBCCEGAHACGBDBGBHAHGHGHEHEHACABADADAHACBGDAEHGHBDBDBEBAAAFCGCGDEDCDEDHDAGHGDGBGEGDC,False +609,11.0,19.0,6.0,5.0,9.0,14.0,11.0,10.0,BBBBGBFBFBABDHAHFBBAHEHFCAHGGDGDFCBCFCGAHBDBGBGFGHAHGBEEAFFFBFEFEACACEEGEAEDGFHAHBBBF,False +610,7.0,6.0,1.0,2.0,7.0,8.0,15.0,3.0,GGGGGDGFBAEAEBFHGHDFAGBEFEFGFGBHAGAGBCEAEGBGEGAFF,True +611,9.0,11.0,18.0,12.0,13.0,14.0,18.0,18.0,DABAEGBGEGEGEGFDHCGCHAHFHFCCCCHHGADFBGEHAHEHECFHEHEAGABDGEBCBFFFGDGBGACHHHDHCFCDCHHGDCHCBCDCGCBBDADGGGEDECBFFFFEF,False +612,1.0,6.0,5.0,8.0,3.0,4.0,3.0,4.0,BEBEBGBFBFDDCHBDFCHDGACHFHGDCDCDED,True +613,5.0,7.0,4.0,9.0,3.0,12.0,4.0,8.0,DEEHBFGFCHBHDHFAGDBDHDFCFEBHHHBFBABAGAGDFDCDFFFFCFDA,True +614,5.0,4.0,10.0,9.0,2.0,6.0,6.0,7.0,GCBCBCGGBFHHCFCHHDDDDCBGAEACACFDADCCAFHFHDHDEDGFG,False +615,20.0,20.0,21.0,19.0,32.0,21.0,14.0,26.0,FCCGGEHECEDEDBBECHCHCFGBEHECCCCCHCGCDCDEHAGCECEDDBEBABABEBEAAAAHAHEFAFHFEFBFBFAFGEEEAEHEBGHEHDBCBDAAEFFHCGFHHHGCEAGDBEHEFEGDFBFAHHDBCHFFBEGEGFHECEADADADBHFHAHDDFDFHEAEBDBDGH,False +616,4.0,1.0,4.0,5.0,3.0,3.0,4.0,3.0,AGAHCHBGDFDCHEDEDEFCFCDAGAG,False +617,14.0,17.0,16.0,17.0,18.0,16.0,11.0,15.0,EFEFHFABEBEGEAEBEAECBDHFEEGEGBGDHHHHHBHBHBHAFAHDBFHABDDFDHBGDECECEFEFGDABAFAFABDHFBFCGCGBEFCDCEADDDFACAHDCCGDDCBCGCFCABECGCD,False +618,29.0,30.0,26.0,14.0,18.0,25.0,13.0,17.0,HACCBHBFAFBFBFHFCBAAGAEBEFDDBDAAACACACEEDDAEFGBGFEFCABAGAGAGFGCHCAGFBBDFHAABFCFCFDHEHCFBFBHADBBBBHDDBCFABBEBFBADAEBCBHBHFHCBDDHCHGHCACAGAGDFCFEAEBECECECFCECECGHEBAFAEAGHBCF,False +619,31.0,22.0,24.0,19.0,30.0,25.0,19.0,29.0,CFHEHCGFFACEHBDEEGGACFCACAGAHAEAFDCGBACEFGAECCAGHBHBDBAEAGFBABAGACAHHHAHCHCDCDAGGGAHAEAEDGGCEHFHFHFDGBHBCEHEDEFEFEFEAADACHFBDBDBDBFBFAEHFHBHEHEGEDEDCCEBFBFCFCAHDBFEAEFEACAFADEBEHHDEGEAHBHCHDBGBCDHFGF,False +620,18.0,17.0,15.0,24.0,21.0,15.0,18.0,13.0,ECDGDBDGDGDEAEBEBCFGFGAGAGHCDEHEHBGGGFEAAFBBDFHCDCEEEEGAGAGEDFDHDHAFAFHEHDADADBDECACEDDBHFEGECADDCFHBCBCHCDDFDGBBBEAECEDEFABAHCHGDABFBFGFCBGA,False +621,0.0,2.0,1.0,1.0,4.0,1.0,0.0,1.0,FEEDEBEBHC,True +622,14.0,20.0,14.0,20.0,27.0,29.0,12.0,26.0,CDCACEHFHFHBHEFEDEBBFFFFBFECHHAHEHEDGDEEBFHFHAACEDECCCCEFEHAHBHDHFHFAFABEEEGEGEBDAHEEEEFHDDDGDEDABHBAFGFEHABFBABDBFFFHFCFHFBGCABBGBHFHFDDAHGFEFEDHCHDEBGGGBCDDDCGF,False +623,16.0,25.0,17.0,19.0,21.0,19.0,21.0,15.0,BFDFDFGBGDHBHEDCACFCEHEDEBCFDEDADBDACADDEGEGHAHBHFEBCCCAHEHEBEBAAAAGCFCFGFBEEEHBHEHGBDBDAGAEAGBDBGFEFGBCBCFGEGBGHDHGCCAADCDCBFBAGGFGEHDFBEBFBFDFCFHBGGGEB,False +624,23.0,27.0,21.0,27.0,12.0,19.0,33.0,26.0,DHAGAGFBFCCHHGGBCBFDFACGBGBGHCABACAHFHCDCDGFGFCFGFCAEGHGABABEDEDHFHFDFBGHGEGHAHBHCDAGAGAGBBAEAFGCACBFBDDHGHBHDGDGBGDAAAAEBBGBDBDCACFCHCBDBCCCBGFFHDHDHEGEDEHHDDDHBGBHDFFEBDDEEGGGGAGHCHDBAGD,False +625,17.0,22.0,27.0,7.0,24.0,19.0,26.0,18.0,GHECEGFGAGCBEEGBGHGBEBEAEFGFAFCFHGGGGEEECBFBDGGCGCEDGFBHBCBCBCAGABEGEAEABFFFBFBFHEGFGACAEFDBCBCAGAGAGFFCCBEHCCBCBDHCBEHCHCACEBFBCGDAHFCECEDACAEHHHHHDAFGHCHCEGEH,False +626,21.0,20.0,18.0,14.0,19.0,24.0,20.0,19.0,FGFGDBFGAAHHDABADDECCHFBGCEEHGHGHGAFHCHAHBCBFAFAFABBBABADDGEBBFCFCFCFCBCDCDHFAGGHGHGAGEHBFAFCHHEGEFBHDHAHAEDGAGAGEGCDEHECCCBBBAFFFEFDADBBEDEGCFBFCGAEEEEFEF,False +627,22.0,20.0,15.0,21.0,16.0,16.0,15.0,16.0,GBGEFDACFGFGHBHECCFAAAEEGBCHCBCFADHDHDBDBDFDADABAEDFBADACBCFCFEHGCEFEAEBHDHDFDEEBBHBGAGDGAEAEGGHAHDDDDFDGBBBAAAABDHGHFAFECCCECHBDBCBFEFGAGAHH,False +628,7.0,15.0,8.0,13.0,14.0,12.0,11.0,8.0,DEDBDHFHDCDCBBBCBDBFBFCGHGAGEFAFAEADBFBGBGHGDCFADBDFEFEDECEFHHCBEAGGGDEBECEABBGHGFDHEEFE,False +629,1.0,3.0,3.0,8.0,6.0,2.0,4.0,5.0,HEHDHDHDEFBGBGDDCDHBEDECGCEEFGAD,True +630,11.0,10.0,7.0,6.0,8.0,14.0,8.0,5.0,CAHAHABFCFCACFCAHAGDBCEGHFHEBDFAGAGABBBEBCFEFEFBFAFBDEDEGGDFDABFFEFGG,False +631,14.0,11.0,20.0,21.0,13.0,15.0,14.0,16.0,HCFAAHBFCFAFHFGDHFCFBBBEBEAEAEHEHGDDBHHHFHDCDEGECFHFDFDADACADHGEDADHDHDCDCGADDECEAGBBCECDGGCGCABAHFGCDCGFBHBDCDGAGCCCDCGEFEF,False +632,4.0,8.0,5.0,12.0,1.0,8.0,6.0,3.0,CAHAEDBCCFGDBDFFBFBHDDDDDADCGBGBCFAGDGFGFHDBDBF,True +633,3.0,4.0,7.0,2.0,2.0,6.0,5.0,5.0,CBCECACAFEFDAHBCGFGFBHCHDHCHGGFBFG,True +634,15.0,14.0,8.0,23.0,21.0,16.0,17.0,8.0,GDDDADADACBFGFGFAFACADAEEBEBFCGBFHFHGEDDDFCGABCBDHDHEEFHAHGEFDFEFBFAGAFEGDGDGBGDEDEBHBDCEEEEGEBCDDEAECDDDEGGGAFAEBFBGHEDAB,False +635,16.0,23.0,27.0,12.0,33.0,22.0,20.0,34.0,HEHACECAHFBGBEBHHHHFFCECEHEAEGDGDHAHBFFFFFFFGABCEFEBECECHABGCGFHEEEEEEGBCAHEHCHDFBGBCBCBHHGFBHDHCHEHEHCFCGCGEFHHHCDGDEDECBCAFEFAGHDCABHDAEACCHGHFBBHDEAGBGAFDDGCACEFEFEHEHEBEGCCEGBGBCAHBHB,False +636,18.0,21.0,19.0,22.0,14.0,15.0,21.0,26.0,GHABCDDDAGGFFEFDFHBACHDHDECGBFBFAAGECECDAFBHCDCEBGBAAAGHHEHEHEHEBAFDFCACECECEHHHCHDHAHAHCDBDGGGDHDBCCFCGHHHGDDDBEBFCFDGAFBFBDBDBGBGBABHHCHGHGDBEGAAHDCGAGBGF,False +637,7.0,11.0,15.0,9.0,7.0,9.0,10.0,13.0,DAFBFHGDGAGCDCDGHBCECFCGCDEDHDHBHBFBEGEHDADBBBBGFHHAECHGHGHBFCFAACCCFFHGACHCBCECE,False +638,23.0,18.0,27.0,21.0,18.0,14.0,17.0,30.0,DEDCHCBFEAEAEABAHGDGDADEBEHCFDGGCCCCDCBFGFCCHDHDHFBABDHEHAHFHCAFAEADHDHCHEDACCGCGCGCBAFHHHECDDDBGHHHCHBHAHECFBBGBDBFHAHGHCDGHGCGCBBBGBABFGCGAEEDFDAEHFHDHEEACAEFEACHCAAA,False +639,8.0,5.0,5.0,6.0,7.0,4.0,6.0,5.0,FGEBDBDBGHGDGCAHAHCDAGAFAFBEBEGEFDCHAEECEDACAH,False +640,25.0,30.0,19.0,18.0,18.0,25.0,21.0,28.0,DBGBFBFHFHCAFAFACGCHCHEHEGFGADHHFEAEGEGHGEAEBDADHBABDGGGGHBHDDGAEBDFCGCFFGACDHBHFHCHFAGHEDACAHBDDDAHHEBEBABACAGBDEDGHBHFHFCGCDFBFBFAHGCBDDCBAEAEFCABABACACEFHFBAEHEGBGBHBFFHBEBFBFBFHCBC,False +641,10.0,7.0,19.0,15.0,18.0,26.0,16.0,17.0,EBEBEADCFGFGAADCEFHCAEDEAEFBHEHDGDGDBHCGCFHFHCHFEFGFGCECFCGCEDAFEGDFCAEADCFEFHHHFDFGFGAGDGDFHHGACFBHDHCGFGFCHCHCHCDEECFFFFEBEBFD,False +642,17.0,19.0,31.0,20.0,20.0,27.0,31.0,22.0,EFGFHEBFAHAHFHGCFCFGFHFBFDHDAGAGBECCHCBGBFEABDEGEGFCBDDFEFADADBFEGEBBAEHEHAHAFGCGCGCBCBFGFCACHCECGCBCAGFHDBDCAFGCGCGCGCDDDCDGDGFBHGFFAHCFCFHECDGDBECCCDCEGEFBFEHHGAGCGDHAHGHEFDHAGBGBGHDECE,False +643,10.0,16.0,8.0,13.0,16.0,18.0,19.0,19.0,DBDFCEGABABHBFGAHEGFFDHCFCFBDHHACAFECHHHHGFGBEHEGEGEGFGBBDBFEFHFCEDECFAAGFGFEBAGHEHEHEGDBDFDFBEBDBDFDBGEHCAAGHGHGBGHGHD,False +644,23.0,23.0,24.0,17.0,10.0,17.0,18.0,14.0,BGGGGGEGBACCECHCHCACDBAEFEFHAHACFGGADDCDCDCDGHGCBHBAAFGFGFABBBBFBHGFAAADADCDEACDEACBHEEFCCHCHAFBCHGEGBFDFHEBBHBDBCHDBDBGFCFBDCGFGFACABBBAAAAAFDCDC,False +645,19.0,20.0,19.0,12.0,21.0,19.0,19.0,26.0,BCHEHEABABAHAHDHBEDEAEGECEBECAHDGCFEFCHHAHDHDHFBDACABGCEBHBCFHGCCCAEEDAACABBHGHGHFHBEBHDECEBDBCBFEFHHHGHGHGHFHFBDGEGACEFDFHFEFCGGGAEFDFGCGABFFCFCGBGAGFBAEA,False +646,24.0,19.0,25.0,16.0,26.0,22.0,27.0,28.0,DADGFHCDDBDHDHGGAEECHHHFCAGACFCFEDCCECEGFBFBCBGEHEACBCBGGHGAGFHCGCGEFEDAHAHFHEBBBHHAAEAECBGAAFBGBHBHAAFEEAECEGHGFCDCHHHHBDFGFGFGBEAFHFDAHAHCBCEHGHGFCDGDGCGEFABDBFBAAAHADEDEGCGHECEFEFECECG,False +647,19.0,19.0,11.0,23.0,12.0,13.0,15.0,22.0,FGFAADEGEAEADGDFHAHBHDGGGHDFBHBDDGDCDHBHBHEHECEDBDBEBHHDHEABCCGFAHGGEADAGFDAHEHDHDCDGDHHEHFFFGEGBDCACACDFDHBBBBDCGAAFAHABABACACFDFBBHB,False +648,14.0,18.0,21.0,17.0,4.0,13.0,14.0,14.0,HDCCBGAGBGFGFHCCACHCGCBCBEDEBCBDBHFCFCFGAGACBGFDFBHBADAGHCHBHFCACDFDBABAEGCHHDBDCFBECGCGBDAFFGHDBDBDADADACFDADCHHGH,False +649,18.0,10.0,20.0,21.0,15.0,23.0,20.0,19.0,CDCFFDAABAFGFDBHFHGADADAHGHGBDFCHHHCDCHAHADCDGDGDGCEFGFCECFCFCGCAAAAEAEDBDBFFHHHFECECGGEGAABHECFHDEDGHGAEADFFHGDGDGEEBDCFGEHFCGCECEDDFFFFBFBCBHHAG,False +650,2.0,8.0,12.0,4.0,7.0,2.0,3.0,2.0,BECADGCCCCCBCBCBDGGFECECDBDBHECEFABHBCEE,True +651,23.0,17.0,14.0,13.0,18.0,7.0,9.0,12.0,HGFCACACFCDEEAGBGBADADABCGDAEADGDBACFHBEDAABHBHGHCAAEBECECACEDECEGFGAAHABAEAHDHABABADEBCFCFBEEEHEBFBAEHEHDCDBGBHD,False +652,9.0,5.0,7.0,3.0,3.0,4.0,7.0,7.0,FHAHAGGGGHGCGCEHEAFAFCHDECHBABCFGBHBACDCDAABA,False +653,17.0,14.0,10.0,12.0,16.0,15.0,12.0,13.0,FFDCCCGHBHEFBAEAHDFFFHBBBBGAFABABAEADAEFCBDEEHFDACHCHDAFCFEDGBCBCBEBEGGGCHHDDAGAEAEDEDEBEHDHAHEFGFGFGHGAAEAFG,False +654,18.0,23.0,28.0,27.0,18.0,13.0,30.0,25.0,CGCBCACGBGHACACADFEBGBCAEHBDBCHAEDGDFDCCAEHDGDFDFAFBGBGEDCFBFBFDAHGCCCBGBHEHAHGGGCECEHEAGCGDGDHBBDGCECHAHDFDGEGAGDGEADHCACBGBCHAHAGBGHHCHCHGEBEAEDECHBGBGDGFGEGHCHBDDDCDHDFDHCFEHDBDBF,False +655,15.0,11.0,8.0,7.0,7.0,6.0,7.0,13.0,EFAFACBEEDCAHAHGEAEFFHBHBFBFHGAAHGHGAGDCBHHHABDBEBAGAGDDDADHBCBEACHCACACHB,False +656,23.0,17.0,14.0,15.0,23.0,23.0,21.0,14.0,DBBBEEGCGFABAGAHAHFDEEHECBHBFBEAEADGDACGFGFCFDFGFGFGBEBEDEHHCFEHAHAFAHEBABEDEFGFGBGAAECFCHCEAGDGDCBCAFHFDFDFCFEEEEECFDBGGGAAADBGBHDAGEEBHDAAAHFGCGFAFC,False +657,22.0,13.0,20.0,11.0,19.0,20.0,13.0,19.0,AAAEEECFGGCCCDBDAFHFAFCCBAAHBBBEBFBAGCGEGHCAEACDCEADBDEAFCDGECEGGAGABAHAEBHHHHHCFCFEHCHFHGHCHCFAFDFDFDHBEGEFFFFAEAECEDEDHFGABFEGCHCHAHABF,False +658,13.0,8.0,9.0,8.0,6.0,14.0,16.0,11.0,DFDAACADGHGFECCGBFFFHEAAFACAGFHCGCFAFDFBBHHFGAGABABAGEFEFGDEBFBDBGACHCHCHGDGHGHGEGDGH,False +659,24.0,22.0,11.0,20.0,12.0,19.0,20.0,10.0,ECECBBAAAFHDHDHCBGFGFACABAGGHADBEAFFDFDFDEGCGCBBBFAGABBEDGGAGFDAGHGDDAEABBGBHDGEBFBHDFGCBCBEBFDFDADADBBFEHEFEFDFHFEGDCDCDCGBGAAAAAGAFAHBGA,False +660,9.0,8.0,11.0,8.0,16.0,14.0,26.0,11.0,FEGEHCHBGBGEGHGHGEGHDEBHAFACGDGFGACHHGAFCGGFEHDFDEEGBGBGFGFGCCECFAFDFDHBGDAAHAGEGDGEGFGAGEBCCCCBEEGEFEF,False +661,21.0,16.0,26.0,12.0,16.0,24.0,13.0,16.0,AHBFGAHHBCBABABCCGBEFACECGHGFDAHHCCECFFFDFAHACACBCBGBDFEFEHEDACAEDEDEGEGDGBBBGCGAHACACEFAFDFAFBDACAFFHFCFCAGEGBFDFBFEGCFCBCFHACADDCHFHFCECEHHHCE,False +662,19.0,21.0,19.0,34.0,20.0,23.0,22.0,19.0,AFAFBGBGBABGDDADCFCECGGEAEACHDHDEFCFDFDECHHGDEDEGGFEBBBBBEFEDDFAHCBEDDBACDCDAHAHGHDCFCFDFEFEDHCHDDADBGCABDHEBBFBDCDHDEDEABDHEBFBCEAGGHFHEAGFGFGCGDGFGDGAGAGABFBFDDHDCDHHGHECDCFAF,False +663,30.0,32.0,21.0,26.0,25.0,15.0,23.0,18.0,GBDHGHGHGBGFGABAEEDBCBCAHAEEDFDADEGCCCGHDBBBEDHGGFCBBHEAACDBGAGBGFEAAAAAABADGGBGCDCFCFDFCBHAHBBBHBHGDBDEHBHBHBEAABABDDEAEDFDEBEBECEGEFAFCFCADEGCGBABABFBCEADAEGEGDCDGBFHAEAEFCDDHEHAHFDCDEDCAC,False +664,14.0,12.0,16.0,18.0,20.0,25.0,19.0,23.0,GFFDFGFDEAHBCEEHCFEEEABFGFGHGAGAGCGCFDBDBDEDEABABDBHFCFHDGAGEHEHEGDCDCFAAGAEEHFGFEDCHFHGGEHDDGBADDGHFHEHEHECFCFCDCAEFFFGFGCBHHCCFCFBFHFHEDADHHHHABB,False +665,1.0,1.0,5.0,0.0,2.0,0.0,2.0,0.0,CCCBGGAECEC,True +666,13.0,18.0,8.0,9.0,12.0,13.0,18.0,15.0,FADABCFAFAFGFGFBCBGGGFGDCDCABDHDAEHEDGDGEFFHCGEHHFHBGAGAHEGEGABFCGBGEEBEHFHBHBHBHBFBHCABBHGEEDCDBABABHGGAE,False +667,12.0,9.0,6.0,10.0,3.0,13.0,8.0,9.0,CBCHGHFADHGAGBCFDFAADDFCFHDAAAAAFCFEAAFADCDGDGHFHFHGBFBFBEBHGHGBBDFDEB,False +668,25.0,23.0,24.0,17.0,11.0,21.0,16.0,12.0,GDAFFFFHBBGCACGCECBHAEDBBFFFBCBCACACGBABEBEDDBFAHBHDAGAGBGBGAGBGAGEDBAFCCDCGAGHCDADACAEDFHACBEAACFDDBDBHBDBDFFFCFCFCFCAAAEDHFAFHCHCACHCGAGFFCEEBEBGDH,False +669,3.0,6.0,1.0,5.0,4.0,4.0,3.0,1.0,EABGBEBGBFBGDFDFDADEDBFHEAC,True +670,5.0,9.0,11.0,15.0,8.0,21.0,12.0,11.0,DFDCHCFFDHHAHACGGFBDBDCDCDAHEFFFHBDBDBEECFGDGHGBFCDADABHBHGGEGCCFFFFFDFHEBGCEFDFGFEFEHDGFGFC,False +671,9.0,14.0,11.0,13.0,12.0,14.0,11.0,23.0,HDHCHCFCFCHCFCDADADEHFHBAEGFGHCEDHFCCDEHAHFEBBBADCHHHHDHBHEDDDADHDBGBGBCBFHEBEFGBGHGFFHAHGHBAFAGBEFEBEHEGFG,False +672,3.0,4.0,0.0,0.0,2.0,6.0,4.0,2.0,HFHFAAGEGFGFABBFGFBEB,True +673,17.0,21.0,20.0,5.0,12.0,13.0,17.0,15.0,BCBDBECHCAAADCGGGGFBABABEBCBCACAGHBHDHBFEEEEAABCBCBAAHBGGCGBGHGFGAGFFCHGHGHBABFBFHCHADDFCCCECECHHEAFBFBCHHBCEGGCFAEAEGFF,False +674,14.0,34.0,17.0,24.0,19.0,23.0,30.0,24.0,BBGEGHHHEHEFABDCHCFBDAGBBBBDBFCFCFAHHEHAFGHGEGEDBDBDHCFCHCEDEDEDGCGCDDDGDGAGAGEGBHHCHADFDBBBCDDACGHGEGEHBGBGHFEFGFBBDBHBFBDGGCGCDFGCBBBDADGHFCFADGEHFCFAFGBHFHBGEAEBBBAFGGDGFEFBBHEHEBABF,False +675,22.0,22.0,20.0,24.0,22.0,17.0,36.0,34.0,CHGHGHAHAHCECDBGCADHEEGECDGBFCCHCHFGFGBBHFHFHEGFGAGCGCGDGDCBFBFEFEHEDECCHBGBDADHFHEBDBGFGBAHGHGEACGGAEAHGBDCDGDHFHBHCECBDHGGGGHBBDFDFHAAAAAHADADHGHEHAGFGDGAEDGDEEBHACFGHBHBHCGGGCAHEEAEHEFDDDGDBBBAE,False +676,5.0,3.0,7.0,7.0,6.0,1.0,5.0,6.0,EHCHEBAGEGDGDCCCCABHEGBAEDEDCDFDADAHHCHG,False +677,14.0,12.0,18.0,20.0,14.0,12.0,11.0,15.0,CCADHGFACAHGHDDDDDGFGHBADGBEBCCDDDADADABBHCFCFHBHGAGEEEEEEEGEFHCDFAFCCADBDCDCDCBBBBCHCBDAGAEHDHAHAEEHEHFFCGCDFGECFFH,False +678,20.0,18.0,16.0,16.0,18.0,22.0,18.0,25.0,DFFHFHFGFBADAGHCBCAGBCBFGFACBEFEGABBBEGHHFHFDFHEEGEBECFCEBEGGADEDEAEACHCHABEHAHAFAHAHAFBFAECECHCHGHAHBHCHFHGDCHGHEBDBDGCADEDGGFBFGDBDCFFEHDFDFDGDHCHBGAAA,False +679,13.0,13.0,11.0,11.0,12.0,13.0,13.0,10.0,DADAHACGEBDGEGEDEAACHFGEGEGFGFCFAFEBCBFEFHCCFCHCHEHAFFDBBBHGCEBGBGAAHFHGHBFDEGAGBBBBDDADADEDACFC,False +680,21.0,9.0,11.0,23.0,10.0,11.0,13.0,22.0,BHEFDAEAEGGAGBCHCBAAHAFDFGGGGBHADEDACFCFAEABHBHBAAADFFACDDDHDHCBCFHDHCHGDAHAHDDDCDADEHFFAFDEHHDHECDADAGAGBHHGHEHEHCDGDGD,False +681,29.0,26.0,19.0,24.0,29.0,20.0,27.0,23.0,AAHAECBCBAADACAFFGCEADCBGHGFEFEAEDEDBDHDEBHDHAACAHAEBCBDFFHFBFBFBFGFBEAHBCAEAGAGBEEEEEEEEDCABFGFBDHFAFAGBGHGCGEGDADHDFGBCBHBHACEBDADEDEDGGGGGGGBHBHDHCFGBBEHCCAHHFABDCGGECFBAHGDGDCEAEHECEGHDFDEDGAHA,False +682,12.0,18.0,15.0,23.0,25.0,24.0,20.0,8.0,DADHGFBFDADAEECECBFDHDBCBABAHFFFFEFEFBFBFBEDFDEAFCCHEBBGECCCCFAGBBDBGCEEDHGGEGEAEAEFDDDGDAFEGCGCGCFEDDGDFHEDGGGGGEBEDFDEDHBEBDCCEFFFEFEBABFGAGHGD,False +683,10.0,19.0,7.0,19.0,5.0,6.0,8.0,11.0,CHCGBDFEGADBBBBBEGHAFAHBGFACAGAHDBDBDADHDGDBDCCCEDDHDADADCDBBBHBFBDBDFDADEHHHBHGGEFBB,True +684,10.0,3.0,3.0,5.0,2.0,4.0,6.0,12.0,DBCHHBHEDEGAGAHFGGHFAAAGAGADBCHAHAFDFDACHHHHH,True +685,10.0,19.0,16.0,24.0,9.0,16.0,18.0,17.0,DGDFEBDHDADCDBDHFHFHAGCHCHAGEEBGBGBAFDHCBADCDHAHEEABDDFDFABBCDDADCDFDFBBGBGHECCGCGDECGDBFGGEGECHCGFFBFBDGFHBHBHBCGCGCGBDDDFHFHFHA,False +686,11.0,7.0,14.0,17.0,14.0,20.0,12.0,14.0,HDHABCEFFBEHCGCACACBHBGEGEFFFBGCECDCDEHEDEGFGFDDDDGDGAHDHDADADFFFAHAEDHFBADEDBCCGHAEEECFFEFCFHFGCGAHDFGFHFCFH,False +687,19.0,24.0,19.0,21.0,13.0,20.0,17.0,22.0,GBGCDCDHFCAHAHBFFDCAGBFBABCFFBFACBGHGHBFFGHDDADHFHFHBGGHGAFDFCGAGEDEGEADDFCBABFBABAHEDEGFGFCBCFDDADACECEBEBCHCACFEGCHBBBDDDGHHDHAHAFABDHEHEHEGEDBABCBDBHCHC,False +688,11.0,6.0,12.0,7.0,7.0,10.0,7.0,5.0,CCBGGGGFABECFADHEACFCFGFGEDFCFAFBHBCBHBDCCHCAAAAAEDDDDAFCFCEGEAEH,False +689,1.0,5.0,2.0,2.0,0.0,1.0,2.0,2.0,DHDGFGCBBBBBCHA,True +690,15.0,19.0,20.0,21.0,26.0,23.0,15.0,18.0,GBGBGEFEGECEDHDHDHDHDCGAEACGCFBFECCACGCDEDFDHDFBBBEBDHGHDCBAAAFBHADFBFHFHFHFEDDADEDEFCBBAEEGEACCHCEGACEDECECFFFFHAHEGEBABEDFBHEDEAEADFDCHFHFCGEBHCFFFGBBECGBG,False +691,16.0,20.0,16.0,13.0,21.0,17.0,19.0,17.0,EEBEDECEAEBBBBEHFBFBFDCDCBCBCAFGHGCECGGDHAHCDCFCEHDHDBBFHFGEECBGBFHDHGHEBEBEAEFBAAAAEAGGGFEFCFBABDFGFDFHAEEGHHHGDFHFGCGCGDAAACADEGBBCAHGEGH,False +692,15.0,18.0,25.0,15.0,20.0,16.0,23.0,15.0,DCAGACABGEGHGBBCAEGHHDAAAFGCBCBCGGDGCGCHCDCDAFCFGHGCGCEEEHBGGECACADEDFDFGFDBBFBCDCFCDCEEHEHFDBDBGEGFFBFBFEECHGHBAGABABEHEHGCEHBFDCCGDHEHEGBFAFAECEC,False +693,18.0,15.0,17.0,18.0,19.0,18.0,17.0,13.0,DAEAFACADHDHCFCBBBDFDEGEGEFDGBEFEBGHGHEHGGAFAFAGAEDEBHDADAEAEDEAHGHAHCECEHFHBGFAEAFBCGFDFGCACADFCGCBCBDAHFBCDEBCFCFGECDBDBGBGECECFDDHFG,False +694,7.0,11.0,9.0,10.0,9.0,4.0,5.0,10.0,CDDDBBCGFGDHDHEHBHEHEBEBEAEAFHDEGEDHBAAFHCBFEGCBCBCBAAHACCCGBHDDD,False +695,9.0,7.0,7.0,14.0,15.0,8.0,16.0,16.0,DFDCDCDEAHDDDBHHFHFCDCHCFBAEEDGAEAGGFGHAEECHGHGHEEGDGFEFEDEGBGEDDBHBHGEGFAHAEAHAHGBGHGHGDECB,False +696,24.0,23.0,24.0,22.0,20.0,19.0,26.0,26.0,ADGDAEBHCGCHCEADABGBGBFEEGFAFAFBFGDGDHHACDCHFACHCGGHGHDHCBGDHBACHBHGHGAAEBFAHGGDGHGFGDCDCGCDCAEGGGEEEEEHDFDAAAHADAFADEBBBHEHECACBEEEBABFCFCFCECFCHBHBAGABHHFHBHFCDEBCDGDFDFDCBFBCBEAGDGH,False +697,19.0,24.0,22.0,23.0,29.0,24.0,25.0,34.0,FCFEAEAHCGEDABFEFDHCHCGCGCFHABDGEGFGFGBHBCAEEHGBCBCBCGHDHFHABGHDHCCCAADDFDHDCDHFBEHEHEGFBBHHHADEEEBEBFACHHHHGHGABBBBEDCBBBEDEDFFFFFFHCHDAEFEGDGHFBDGEHHGFBDADECEDEDGFBFEGCGHHCHCHGHEFEAAGAGEGDGCAHAEAEBD,False +698,13.0,19.0,14.0,18.0,18.0,16.0,11.0,16.0,BDBFFDFDFGGHAHBHBHBHFGAGAHDHBEBDBHBFBFHCBEGEGEDCCCCBGHECDCACDBFCEDBDFDFDHDFEFHFHEHEFEBABDEHBCDDHAAADEBAGAEACGEAEFBCEGEDFCCAGE,False +699,20.0,17.0,18.0,13.0,20.0,22.0,16.0,23.0,ADHHHHFDFBFAGADBEFFFEFEGCFBDHCAEABAEAEBHFECCFDFHHHHHFHCHCHEHEAEBGHACABFCFGAGDFDFCBHGCFCBCHDEDHGHAFDFAGECECEFAGCDEGEHEAABCBGBGBGBABGEAHGEAFHFGCECADBDB,False +700,7.0,10.0,13.0,7.0,8.0,14.0,8.0,3.0,FAAEFBFCFBFBEDGHCCCCCEDEDFHECDBDGFGFADGBEFCFCGAAAHEDECACFBFBGGGFCFCBBB,False +701,16.0,27.0,21.0,29.0,23.0,22.0,14.0,18.0,ABAEADACBDBFAFDCGBDEDBBFBFADHHAABHDGABACDBDEAFCHCECHDDACAFDFDFEAEDHDFBFBFCEEBECDCDHABFBGEGFHFHGBDEDEDEDCDHDHFAGDGHGHGHBCBCBFHCEBEHCCDCBFBFBECFDGGGFCECEDHBGBCFEEDGBFBEHEDE,False +702,22.0,31.0,14.0,20.0,15.0,20.0,18.0,12.0,GHADBDAFCHAEBDBDBDFDEAAABADEDCAABBEGEGFGEGFDFBFBAEGBBCBCBEGDCDAHCHBADADGFBFBHBGBDCFGDGHCDCFCBEAGFGFHFEBECAFBFBHBHBFBEGEGEBEDAHABADABBGBCAAGDFBAGHCCFDFHF,False +703,21.0,26.0,13.0,16.0,14.0,14.0,14.0,17.0,CHABCBFGFAABAGAHAHAHACBDFHAHEHGCACDBEHDGBHCECEHFAACABHBABABECGBGAGEFCGDEFHBBFAFHFHAHEBEFEGBGBEBEDDDDDDDAHHCBCDDGEADABGBDBFGFBFBFBGEDCBB,False +704,1.0,0.0,1.0,1.0,3.0,1.0,3.0,0.0,DEECEGFGAG,True +705,7.0,6.0,9.0,6.0,4.0,3.0,8.0,5.0,AGABCBCEHFACGFHHCHEACADDDDGBGBGBCEFHBDEDACGCGCGA,False +706,6.0,5.0,9.0,7.0,4.0,10.0,8.0,4.0,BGHGEDCHCHCGCFFGDGDGCBCBAADFFAFEFGAGADFHBAFCBCEDEFCFD,False +707,10.0,10.0,4.0,9.0,12.0,8.0,9.0,7.0,EECFAEAHAHAEAEBEHFDFDAGCDHBHGGEGEGFDFDEBADDCHFDDBFGEGBGBEBEAHAGBFBABC,False +708,11.0,14.0,22.0,17.0,26.0,26.0,22.0,25.0,ADBFFHCHCHCDGFCFBHBHBAGACHDFEFHCBGECDDGEHEHDHEGEGEGECBHAECDHDCDEEFHFDFDABHGDEHEGDHDGFCCCHCHDHDHBAEEGEHEHGGGBBFEFEDEFHFCFAEHECGCAFFFCFBBCAFBCHEEGEGFFECGCGFGFGFAFAGB,False +709,20.0,25.0,16.0,17.0,13.0,14.0,18.0,22.0,CDEHBHBHAHBHBGDGEGBACAHAHGBGBGBAAAGFDEEBGBABABFGACACHGHDFDADHEFDHHECFDACABGHFHDDDAEAEDGDCDCFCBCFHBCBEBEBEBFCGCHFEGGDDBBBCEHGDACABGHGAFHHHBFAFCFHB,False +710,30.0,23.0,16.0,22.0,21.0,35.0,15.0,23.0,FAFAFAFEFEHAHAEBEFDFDBDHFCEAHHHHBEFDADHEHBCCCADEHFHFHFCGGDECGCBDBGAFAFBCDAHADBECEFHCBCBAAAFAGBFADDFDFHBGAAEABFDEDFHAGAHAGAGEGHFEFCABAFCBEBEBHFDDDFDADEEEFBFDACEGFBDBHBHBFGFBFCFGGHAHAFGFC,False +711,6.0,6.0,12.0,7.0,12.0,9.0,12.0,10.0,HGEDHDGCGCGBHBHGCFAGABCBGGEBCHCHFGDEEEHEHAHFHCGDFEFAFAFDECECDCFABCGEGFCEDE,False +712,23.0,31.0,32.0,27.0,25.0,14.0,31.0,14.0,CGABCFCEHDFDHEHBDBDECCFBDGHGAGBGCHCBAEHEHDFDBDCEFGCGCFBAGGGEFEABFBGEAAAAHAGACACECACBGDGDBHBCFGHGBCAAAFBDDDDDDFGFCECBBEEGDADCBEAEAFDGEGCCBCBCBDGCECGCGCGCECECBFBDBABDBDHDCEHEBECGAABDBGGGDEEGEBBAHGGDH,False +713,4.0,5.0,5.0,9.0,4.0,5.0,6.0,6.0,BEFEACAHDHDHGHBDCHCDEDFDGDBEFGDGDFAFBBGACHCG,False +714,18.0,19.0,22.0,14.0,25.0,27.0,18.0,19.0,GEHFCECFCAEFBFAHBCCEBFFEFECDADEDEAEFEBECECGHGAAADAGHBFGFAFHDEABBDGDEHEFEFDBCHEGCCEFBFEHHHHGHGCAFAFHFHFGEHEHCGDFEAEAGFFBADAFFCFABGBABFBCBGBGCDCDHFHCECECDHDBGBCBCGG,False +715,17.0,8.0,11.0,12.0,13.0,12.0,12.0,14.0,BAGDHBHDHABAEGHFDADFECDCGCGADHDHDHABCBHGAAFBFBEHEAFCFAGHEBCDFDFDCHCHCADAEHEGEAEGCGCFEHAGGFAFEFEAEAG,False +716,16.0,17.0,24.0,24.0,21.0,17.0,16.0,24.0,FCBCBHBCBCECDCDAFFHHHCHDBEFABAEDEDEDECFDGGGAEFEFEHCADAFACEEECFCGAEDEDGHGDGAGFBHDHFHCCGEGBDHGEBHHHEHACAEGFDFDHCECBADECHHHBBBFBFBDADCCFCDCBCDEDHHCGDDAAAHBHGHGDGF,False +717,30.0,23.0,30.0,24.0,12.0,21.0,21.0,16.0,ECEDACAHEHCACECDCGCBHAGDFACBCBAFGFGBACCCCACFGEGFHHAHABGBEFFBFDFCGABCDCBBBBBAADADGDFDFHFDCDCHFBFAAGAGAGAGFCCCHABGDGDBDCDEBHDCDCDBGFFHHGBEAAHAHDFDEDAHAGDCDBHAFGGGBABDFCACACBCFEEAE,False +718,8.0,9.0,11.0,13.0,10.0,18.0,7.0,15.0,BHBGDHDHDEAEFFAGAGABHFFFADHDHDGAFCDCAHBDECFAHDHCCBGHFCECEHEFDBDCDGEGDBHBECFCFCFHBEFFFFFHFHE,False +719,12.0,23.0,32.0,23.0,25.0,25.0,24.0,32.0,ACHDECHBHFHGHGHDADAGHCCEBEBCCGHFFGFCBEGCCDDDBGFDHDHDHGFGBCFCGCDCDCDCFGEDBDBEGGCFEFEHEBEHECBFDCDGBGEGBGEGCFEEECGFGADCFEAEADBBCECEHEBEDFHFCFCAABGHHHHHFAFABCCHCFCAHEHFBFBFHCGFBDGDEBHBHCECGDBAFHHHHHDH,False +720,9.0,6.0,1.0,2.0,6.0,3.0,3.0,2.0,AAABABDBGEHAGABCBGFHEAEDEAEFEFBA,True +721,4.0,4.0,5.0,4.0,1.0,4.0,3.0,0.0,BGBCACGCDDFDFABACECBFAFDG,True +722,16.0,8.0,13.0,19.0,18.0,17.0,9.0,17.0,DFEFCHCGADHDEDAHEDEBFHFEFEAEDEDHAHADCBAFACAHEHDCGCGCDCDHDFECEBEDEDEFGGABFBFGCACFDFAFBDGFHCADHEHEGDAEAHHHBHFHFADCFEBGA,False +723,20.0,21.0,15.0,7.0,15.0,20.0,22.0,15.0,AFCDCFCFGFGAGBCACBHAAFGFBBEEAEGHDEDBHBHEHBCGEGFACEGHGHGCGEGECAFFGEGEGEGBBFAFDCBCFCFADADBHEAEHGBGHGBAFAHCBADFBHBCBFAFHBABABAFABHFGFGEHCG,False +724,22.0,23.0,14.0,13.0,20.0,26.0,11.0,21.0,DEBABADADEGBGBEBHBCCAAEAFFDAAAAFEFAFGFCFCBHBCFFFCFBFDFEHHDHCHCFDEDHBHBGAACEFAHHFABAEEEEGBCHCECACGDHAFDFHFHFEFHAGGGFCHBBDBHBEBFBFHHEHBBBABEEFGFEDGDAHAE,False +725,21.0,25.0,25.0,29.0,21.0,32.0,25.0,20.0,FGGGCGEGDFAHHHCCCGAEABFBEBDBDHDCDEDAFGDGAEFCFCEAEADABCBGGGGGCDCDCFFFEHACBCBCGCFCFDBDFCFAHBDDFDFBEHEADCDFHEHFFEGGDGFHEGEBBBDHEAEAGAGAHBHAAGAHAHDDCBCFFFHFEDGDHDBFBEAHBFBEDFCHGFGDCFEGCHCFBFDEDFDABBFBCB,False +726,16.0,20.0,16.0,17.0,10.0,18.0,13.0,17.0,BBBBGCACACBFBABFBCDHGBCHCBADABFCFCFGAHEGBGEEEFDGDFAGAGCBCEFHFHGHFHAHFDFCHAHAGEBDBDGDCDCHFHBDDADCBFADEEEHHDGFGFHADEDHFHCBCBABADF,False +727,10.0,29.0,22.0,26.0,22.0,17.0,21.0,19.0,BCBCBCBDAFHFCECDCDCBHECFCGAGDGBHFDGDGBGBEDEDEDBCBAFAGHBHDHAADBDCGFGHDBDEGEFBBBCBEBEHECDHEGDADCDHDBBGCEHFGCAEAEBEBFBHADCECFCFEDGHGHBHFHGHBCFGBCEFDHGBGFGEBEHEFFDDBDECGD,False +728,11.0,13.0,13.0,11.0,13.0,20.0,15.0,18.0,EFFFEBCDCHCAAAADFHFHGAFDFHFCFBEBGCGAFBCACAHAHEDBBGEDEDCDGBGFGFGCHCFFDHEBBCGGGGGDFHAHDHBFFCHHDHEHEFBHBHECAGEGEFEFBH,False +729,26.0,25.0,13.0,24.0,26.0,16.0,21.0,19.0,DBDFABGGFGHEHAAAAABFBFBGBDBABAGEGCGFEEGEBEDHAEDCHABCDEFAFAGDHHAHADAFAFGBGAGHBDGCHHHBFFEAEDBDBEHDBBEDDHDHDCBCBEHCACDHFCGAGEGDDBEBEBEAGAEADABAFFFFEHGCGCEEEEBEGDHDGECEABHDCD,False +730,16.0,17.0,13.0,13.0,6.0,15.0,8.0,16.0,CCHDADACCDBABEBHDFBEAGBGFCECHBAAEAEDEGCHCHAFBHGHDBDADAFBDBGBHCHCAGAGHHCDCFFDFBFBADFBFBFHAAADBFCFGFBFHHHH,False +731,16.0,23.0,24.0,23.0,24.0,17.0,32.0,25.0,FFFFFFFDDEDGGHGHGHGFDHBCACGEGEBEBECFFBFBDECCDEHCFGEACHDHDHCFDHEGABHEGBGEAEHBAGCGHGHEEEDEDHFCGDGBAHAGAGDGBACCEAGAGAGAHFBCHCGCDCHCHBDBGBEBGCDFDBCBHEHEHGCGHBCBCGCAADDDGHGBDEDEGBBDFEAEGBCH,False +732,2.0,3.0,2.0,0.0,1.0,3.0,2.0,1.0,FCFGFHCBGBAEAB,True +733,6.0,2.0,3.0,2.0,1.0,4.0,1.0,4.0,BFFCHCHCHAAFADBGFDAHAEA,True +734,5.0,4.0,6.0,8.0,4.0,8.0,3.0,7.0,DGHGDEDEFAFBFBDDEAADFDHCHFAFBDGHHHHCCCCFCFBEA,False +735,11.0,7.0,8.0,6.0,4.0,4.0,8.0,5.0,CHCACAGAEDFDCBHDHFHBCDDHAFGGGCACAGAGBBBGBEBDFAAGAECEA,False +736,20.0,16.0,16.0,26.0,10.0,23.0,15.0,12.0,BDBHCCEBDBACHCDFGFCADHDFDHAECDAGAGCFEFCFEDDDDDDDCFHHADFDABEGGGAGAGADABAFCFAFDBEBEGACADDDHAHBECHDGBGBDDEGEGDBFCFHBADGHGHFFFBFAFAFCFCFBFCFBA,False +737,23.0,11.0,24.0,14.0,10.0,9.0,22.0,11.0,FHADCDEAAAABDBHAFADADFCGGGHGAEAHCGDDCDCDHAHCGGGGCACFCBCBCGCHAAFAHEBADAECGCGCGDGECEDGBFCDBAGACFHAEGCGEGBGCECHGGFHFABABABCCDCE,True +738,26.0,23.0,28.0,29.0,22.0,16.0,18.0,26.0,EHDFFHFHEAFFBBEHDBBBDBDCGEGEGCBCDGHAHDEDEDFAFGCCCACBDAGAEFHFHADAFHCDCDBDHAAAAAHCHCHFHFEFHCHFBAEDHCBCBCBEBDADGDAHAGACACBHEDDDEHCHBDECCGBGBHDCDHDBGCCBGDGCHHGFBAEGEAFACACBCEEEEHEGCGAADAEBGDDD,False +739,8.0,2.0,10.0,6.0,9.0,6.0,10.0,6.0,CGBDCDCHHEEAEACAEEGFHFDDDDFGFEAHCCCCCBFGAGAGEFAGAGHCEGEGH,False +740,11.0,8.0,17.0,13.0,9.0,9.0,18.0,8.0,BGAGBECGDGHFHBHBGDGDGCCCCCCFCFDFAFHBDADGDGBBCACAFEDGDHCECHAEEEBDCGGAGFGCGDAAEDEACHEHCCFGAGDGF,False +741,4.0,2.0,8.0,8.0,5.0,1.0,3.0,4.0,CECEAEHCCADDHDHGGEBHBECFCDDDDCDAGAC,True +742,2.0,9.0,1.0,2.0,5.0,5.0,1.0,4.0,CBHEDBAFFDBABEBEBHFHBHBFBGEFE,True +743,18.0,19.0,21.0,21.0,22.0,11.0,26.0,21.0,EAACDDDHDGEGBHHHHEBEBABHEHBFGCGDGEGCDCDGGCGHFFDFBBGACADADHHADCDGDGBCCCBEDECAGHGHBFCFEDEDEGGCBEFEBEBEHADBHBGGGADADFGFDAEAGBBHGDBHGHCHCACACAEFEGHCECEAFHCHBGEGECA,False +744,31.0,23.0,20.0,24.0,21.0,22.0,28.0,21.0,DADEBEBEDADABCBFGGGGGHGHAFFGBGBGCGDGFGHBCCFDEHEADABAGGBGFCFCAGAHHEDBHBHFFEHAGAGBCDFAEBHDDDDEHHACFBHDGDGACFFBDBAAADAHAHCHCEGAHAGEEEEEBHFFGADABABEBEBCDCBHFHFAADFCGCGBAADDDFCCCHFEFECEAGACAGDGFE,False +745,5.0,11.0,15.0,7.0,10.0,9.0,7.0,16.0,EFHFBCACFCEHBCBABABCECFHHHHFEFHCHCFCBHHGGEGEDDDHAFGEGCBDDDHEEAFBBCHCHEHGHBCBCDCG,False +746,1.0,0.0,6.0,5.0,2.0,2.0,2.0,0.0,GDCDCACECEDFDGCCFD,True +747,14.0,8.0,8.0,12.0,14.0,15.0,12.0,12.0,HCHDFEEGCBCDCAEEEBEFEFCABABFBFDEGFAHEHAHCHGGFCFDEDAHCHDFDGDGABHEAAFAFHFEEGAGDDFBHBHGDGEGAGAFAFD,False +748,23.0,22.0,15.0,27.0,27.0,24.0,31.0,19.0,CFEFAHGBGDEAEBEAEBHBDDGBFAHCGFHFHGEGFAFADBEFHBEBCCFCGEGADBBGGCGBGHHBEGEGABBEEEAHAGEGFGAGFCCBFAGBGFGFGFADDBDBGBFEFGFAAAABHCDDDDDDFDFHFHBGDEAEDDDEDEGEDEDECHDHCFAGAHAEAGADFGHEHDHCCGEGEDBDFCHC,False +749,18.0,23.0,17.0,19.0,17.0,23.0,21.0,21.0,EAADEDBDBFBEECFCDEGFDFHBDAFFBCCCGCHCHAFAFAGGHGECECEBEGAGDGDHEFEHCBAADAFBFBHBABGBGCFCDHFBDEDECFGFBCHHDBBCHDGDFFBFBGDGBHHAHABADADEEGHGHBHFFFFEFGCGCDEHHGHGAAAGBBH,False +750,26.0,15.0,24.0,31.0,22.0,18.0,27.0,36.0,HFCEEEDBCEHFDCDCDGDAHEDGBCCDCGHDEECFHFAFADHFCGEEAEHEHECGABAHFBFBFDACBDBDCDHDHGFBFACAHAHABAHHHCDGHGHGHAABFHFGGHADDDDDADCDEDGDEAGGGGAGBGACCHBHBFDDEEHEDDHCHCHCHGFGAHHHBHFGCGHEEDEDFBAGHGHCECGCAHAGFEADAGA,False +751,2.0,2.0,6.0,6.0,5.0,4.0,2.0,6.0,DCHAHGHCHCEBEGDFCHCDCFEFEDEFHADBD,True +752,12.0,16.0,4.0,9.0,13.0,13.0,11.0,4.0,EBEBDBDBFAHAHADAGBCBFHEEAFAEEBEFGFEFAAAGGGBAFCFCFDGEBBBBBBGAFEEDDDGAGFGCEFEGBDDFHB,False +753,20.0,22.0,13.0,25.0,23.0,25.0,27.0,11.0,DBDAFFDEDEDEFEFDBCFFHDDEEEBEFDFEFEGBGCHCEBEHEHAABAGGGDEAFDFBGGGDFAFAFACHEEBHACBFECCGGGGGGFDFAFCGEGEFHBDBACAHAEFDBDFGABFBEGCGCDHDHDGDBDBDGCFBGCAHGDGBBFAFABEGEGABADADGB,False +754,13.0,24.0,24.0,21.0,25.0,16.0,20.0,11.0,BHBDGCGFGFGFGHGHBFGCEEFEFBAHEHEHEBCDEDEDBBCBCEFECGCDBACAGDGDBBHCCGDAAEAHCEFECABABDGDGCBEDHGFEDEDBGGCACDDBEBCBDFGGGEEHECECEFDFDBBBDCHAFDCBCBCGCFFACAEAEDBFE,False +755,21.0,23.0,12.0,20.0,22.0,23.0,13.0,24.0,FBFBCBFBFECEBHBHDHBBBFBACGBGBDAGFDACHHGCGHFDBHEEEFEAEBEBFGAGAGEDDFDFEFBCAFDFEAEAEDFDBDHECDCFCEAHAFEEHAHGHGHCBDAEGHBDDDBDEHGBAHAFCHGBFHFHEHEADHFHFHFDEBCAAAAHAD,False +756,9.0,16.0,8.0,17.0,8.0,7.0,7.0,4.0,EFEFGFGCCBABHBDDDDGDABBGBFBFEACDBDEDHCGEGBCBCBFDDDEAFABADAHEBADHDCCEDGDBBBAD,False +757,15.0,20.0,18.0,27.0,18.0,16.0,16.0,19.0,GHFBGBCEEAHDBDAHAHEBFFDDDDBFBEEAGBDHDBEGHAHADDEDCFCFBHAHBHDDGDGDECECGHGFGDADEFCFCFDADBGEEBCDEDGABABHBHBHCDCECECEGACCEABFBFBCCHABGHFHFACDDDDDGHECGFGFH,False +758,24.0,10.0,20.0,10.0,13.0,18.0,25.0,18.0,HEHAHAFAHCGCGCHEBGCGHGHGFGCGEABGHGFGHCHEAACABAHACFEAGCECBGGGGGACDFHFAFDFDFDFBEEAEAECFCAADAGFCHHECFHGAGHGEAHFGCCDBDBGACAGADABBDBDCFAFHGEFCF,False +759,5.0,2.0,3.0,3.0,1.0,2.0,7.0,3.0,CFAGGHGHGHBDGDGACEDACAGABF,True +760,23.0,15.0,19.0,10.0,31.0,25.0,21.0,16.0,FGFGHGDGBHACAFAFEFEGEBFGFGFECEDBFEFEHHCFAEACFBBBAFEDCGCEAECFCBBHEGEDEAEFBFGFGADCCCBHAAEEBABAHAHACECFHFEDEABFEDEAEBECACECGFGFEAGAFEFACHGDGAEAEGHHHHGDCBEDEHFHGGCG,False +761,4.0,5.0,6.0,6.0,5.0,5.0,6.0,6.0,EFBFBFGDHCHFEFGGBDAGACHCHDHBAAECCBCDEDEDGHG,False +762,5.0,7.0,14.0,5.0,9.0,9.0,6.0,9.0,EGEFHBHFGFHCEDEBEFACAEAECHCHCHCHBGCFDFCCACBCDHDFGABHBCECDGGEFCFB,False +763,7.0,10.0,9.0,14.0,6.0,13.0,15.0,4.0,FHBHAHAFAEDCDEAEHFDDGFBFBFDGGFGBGBCBFDGDBCGEGECAGAGDGDFDCDCDFGCGEBDGFBACFBFDCG,False +764,18.0,17.0,21.0,10.0,17.0,19.0,30.0,14.0,GFCBGAFBBEFFCGHGEADAHFHEAEAHAHFGGGEGECCFAGAGFFCACBFAFAFGGGAEHGHFHBHCACHFAFDEDHGEGDFBCGCAHGCEBEHCBGBDDCAGBDAGECECACBCBCGGGBBBBBECFCFEFHGDGDGDGEGEGC,False +765,16.0,9.0,24.0,14.0,21.0,12.0,17.0,12.0,FCCCCEGDGDFBEGCBCDDDDCHFGACDHECCCEEAHGHGCCCFEAAADAHGEBEFDDDCDCEAGCGDHEAEAGADAGEFCFCFGFGEAFHEECECEGHGBFCECEBFBCAEBGBGHAHAHAHBE,False +766,2.0,5.0,3.0,5.0,5.0,3.0,5.0,14.0,GCCBCDHEEEFHHEBEHGHBHDHDHAHFGAHDGDGHHHHBFB,True +767,25.0,19.0,25.0,19.0,30.0,21.0,34.0,24.0,AABAGCCCGCDFDAEECGCHBHGHGHDAGCGDFDCEGEBAGFEEEHHAGAGAGFECEHGCECEHFHABEEEBEFEBEFEBCGGGDGABEDEDADGFGFCHHHHDDFBFBAEAEAHGFCFAAAAABAFHECGCDCGFADDBHBGCEHFBBGDHFAFHBHCHFHAGGGGGGAGCGEDEBEDECHFHGBDEDBFGCCCCE,False +768,25.0,18.0,18.0,14.0,17.0,14.0,28.0,21.0,DBBECABABAFFCHGBFEAEHGGEEEHGHGAGADAHGCCFDFDGAFCECECDBBBFBDHHGHEHBHAHGCGFGHHCCFAEAECGAGFHHCEGGGCDCEHEHEDGDHDAGABACCBCBGFFBBHBABADAGGGGHGAGAGAECFBAGAFADAEHDD,False +769,1.0,3.0,1.0,7.0,6.0,6.0,6.0,3.0,EFGFHFCEBGHFBDEDEHEAFDDGDGDGDGBEF,True +770,10.0,20.0,19.0,21.0,15.0,21.0,16.0,16.0,CDHDGGGCGEGECDCDCDABFBDBFBFDFHFHDDBEAEHBGBGCDBGBCHHDGFGCHDHCGCAAHABAFHHBDEFEFCFDFCFCFAHEFBFBGHGDDDCBEGGFEBEAEBDBHCHAEFCDCBFEFEBHCGCBFDFDEA,False +771,4.0,6.0,5.0,4.0,2.0,2.0,2.0,5.0,DBACDGDBBHBHCFDECECACAHAHGBFBH,False +772,20.0,21.0,27.0,26.0,23.0,24.0,13.0,18.0,HHGDAACADHDEDCABDHDFCFDBCFCABDCCCCFFFDFBCBHBGEGHGADACFDGAADDDDDECEHEHDFEBEFCFHFAFCFCFAFCHHHCEBEBEGECECFCHEFDCGBAFADAEAEDEDEFEHEGDAAEBCAEABBFBFBEADGCHDBGBDCDFGGBCBCBEHGHCHBF,False +773,23.0,11.0,12.0,12.0,15.0,10.0,15.0,14.0,HHBEBEDEBGBDFCECGCGEGCHDHGHGBCHAGAGAFAFAHAEEEAEAGBGEGCGAACABBHDABFDFAHADGHFBCDDHAAEAEAEAEACDFDEAAAHFDCCGCHHGDBFF,False +774,17.0,24.0,28.0,15.0,15.0,16.0,18.0,18.0,EFEFEBGCDADCEHBHBHBFBECECBFBFCGCEDEDCCFCGCGFGFACCDFHAHGHBHCHEHECCCGGFCHCADBBBGHHEGCCCGCBHGEGBBBAADCDCDCDADADABFHFAGBDBAHGBBABFEFGBEAHBGCCHFHGDABACAFDEA,False +775,3.0,0.0,2.0,1.0,0.0,2.0,2.0,3.0,AGHGHFDFCHCAA,True +776,17.0,9.0,11.0,6.0,12.0,12.0,17.0,14.0,GCGDABAFGFGCCECFABAEAEBGADHHEHAAAEDEAEABDFCGBADAEHGHFFFGAGFCFDBHBFGHHCGAGHGEGHBHCECEAEAGFCFCBHGHGH,False +777,4.0,6.0,1.0,5.0,7.0,2.0,6.0,4.0,HEFEAEAEDBBGDCDHDFEBAAHEHEDGBBBGGGG,True +778,6.0,7.0,4.0,4.0,5.0,13.0,4.0,5.0,HEHEAFGFAFAFBGBAFFFDEDECBCFGDBEHFAFBFDFHFHGBACCB,False +779,9.0,7.0,5.0,6.0,9.0,8.0,7.0,9.0,DGBEBEDHAFAFHFHFCFCEDEGEDEDGHAFBHBAGAFBCBHFAGADAECCBGEGHHEHA,False +780,19.0,21.0,16.0,16.0,23.0,19.0,26.0,22.0,FFCAGEGEGAHBBEBEGCDFEFCFGHHDHDHDBEFFAGEGAGAGAHEHFAEDBACCCEDGBEACFCFEDEABABABFHFBGBGAGEHHACBCGCHCHGHEABACDBDHEGFGEADHFBDCDCEBBAGHGHEHEHGHDHDGDGFHABECEBDGGFGBGBEFFF,False +781,15.0,24.0,23.0,18.0,23.0,14.0,17.0,21.0,FEAGCCBABABAFAHCDGHFCAEGBGBGHHBBCBFBABAEDEDADHFECGDGAHEBEBECCGCHCHEBCFEDDDCGCGDGDHEFGGCHCBEFECAHDEDFDEHEGEFBBHGGCECECFBDBDBAHAHEHDHECFBFDCECABABHBGBCHFHDHE,False +782,14.0,24.0,23.0,18.0,18.0,17.0,19.0,17.0,GAECGCBBAGAGAGFEEDDFBEEEBBGGEECCCCBEGEGFGDGCHCHCHEADBDBHBHFGADBFGDHHGAGADDDDDCBCDHFBFHDAGFHFHFHCBCFEHHHBFCFHFCGCBCAGFEBDFCECHCACBDBCEAGDBDBEBEBEBABAFC,False +783,17.0,21.0,14.0,26.0,20.0,11.0,14.0,15.0,CHAHEHDHGCCADABAEDBDBFAEABGDDCGADADBBAFCEGDBEBDHGEGFHEHEHEFCFDGHADADBDBDCDCGBABDECEDEDFDCDCDADEDBDHGBGBECDHEHFFBAEAEBEBGHGEBCGGBEFHBHCFAFA,False +784,9.0,13.0,21.0,19.0,11.0,19.0,13.0,15.0,ADHDFGEBBCCDCDCFHAGDBCBCECEAGAHCDEAHBHEFEAHHGDCHCHDHDHFBEADFCGCHDHAFBGBGBEFDFGFECACFEFGFDCDEBGBGCFBFCDGDGCFDFHFHFCFCDCDB,False +785,3.0,4.0,10.0,4.0,5.0,8.0,5.0,7.0,FCFCGCGEAAGFCECECHFFDHCACGCGEBHFEFHBHDFDBDBHHC,False +786,13.0,15.0,20.0,21.0,12.0,14.0,14.0,18.0,BFDGDGDADECHCHCEDGDBDGHCHDGCABEEFEFGGDDBDHDHDGCCEBDFDFBHBHBHFHFAECEBAAAFAEAHBHGHDFEFBHBABECCCCCDEGHGBFFGHCDCBGDCCCFHDCACAFGHADA,False +787,12.0,21.0,22.0,19.0,22.0,24.0,29.0,14.0,CGCGEECEGGBEAGCFFFCDCEEACFBFBGBGDGDHDHCBCGADEHGHBFGFGFDFDBGEGEBFCFCFCFABDBCAFFGDGBFHCHEECDFDFCBEBFHGCGEGAGAFDFCEGEGEAAHHHBGCGCGAGDGDBDFGEDBDFDBCHADEEGEHEHABBFEHBCB,False +788,17.0,13.0,19.0,20.0,16.0,16.0,19.0,15.0,BDCEGHGDAFFHFHDADAHEEEECFCGDHBHGGGAGAEFGBCADGCCCCCCGCDCBEFEFDFECADABAFEBGBGAADGEGHADABHFHFCEDHDGGCDCDFDADGHCFBBCBCEHBHFHDEDEDEGHGAAAFBF,False +789,28.0,17.0,13.0,32.0,28.0,13.0,27.0,17.0,AEADADBGBAFAEADGBAAGDDEGEBEFCFCFHFHAEGEHDHAADEDHDCFCBAEGEGDGCGAGBGBGBFDDDEDGBGBGBDDGGADCDBGAEAGDBCADEDHBABAECHCECAFEHAFACDCDGEHEHFBEHDDDDFEAABDHGHGHDAGECEGEGDHEAEGEGEAFHDHDFAE,False +790,20.0,14.0,14.0,14.0,17.0,15.0,16.0,18.0,FCFDDDHCHCEGHADCBGFEFCFEEEEBEADABHBDEFCABABAGAGEHHBHBDAECGDEAAAFAEADBHCGGBGBGBEFEFEFABAGFHHGACDBDHHGFDACEHDHGHFCFDHCHCHCEFAGAGAG,False +791,18.0,17.0,18.0,19.0,20.0,20.0,6.0,18.0,FHFHFDEAADAFBBACGHDCDFAGGFEFADEDBFBFECEAFAFACCCEFHBHFHBBACHFDGDCDHDHGBAHCDCBHBEEEEAECBABCBCEDHDFDEDEDEAEADACAHFHFHEDCCABEHEBEHCFBFGFBDHC,False +792,14.0,17.0,13.0,12.0,11.0,16.0,16.0,11.0,DDBDBDAFBDBFAFAGBDEGCCECHCHCGFABGBCFEFECHFBABAEECBDHDGDGHGHGFCFHEAEGDHBCBEFHBGAGACAHAFGFGFDEABFBABGFGFGBHCAEDC,False +793,9.0,19.0,17.0,11.0,13.0,16.0,16.0,13.0,DCGHBFFCGEEBEGGAGFDEEBFGHCHCDFDBCBCFCFCGCGBBBCBCBFHFGCAEABHBABGBDBDFDHAHFGFHBBBGHGHECFDECEGHGHDAAGDBCECDAEAEFEFCFH,False +794,18.0,14.0,23.0,18.0,18.0,15.0,28.0,20.0,GBGBGFGAEFECEBGBECECFGDEDGFCFGGHCHCFGDAHHCHCFCFCGCGCEAHAEABACDBDBAGGCGHAHBDFDHEHEGAGEGEHHDCDGFHBHGHFADECACAEABFCAHGHGBDCDFDFBAGACDGGCDBGGADHDBFHEHEAEGDCEC,False +795,2.0,6.0,5.0,6.0,3.0,1.0,4.0,1.0,GDGECBCHDEDECBBFBCBABDGDGACD,True +796,20.0,15.0,22.0,19.0,22.0,17.0,35.0,28.0,EHGHCDCDAEBCBFBACHCGEFEFEFDFHGHDCGAHDCGCDCACBGEEHEHGGGEHEFEGGAAAAHAFFECCAGHGHGHBACACDCFEAGGGGGGGCGAFCBEHHGDGHGADAHGHBDGAGBCDCABAHDDEEFGGEHHHBBBDBDHDHDHFHEHBCDCGFGECEFFGFGEGHFBEDA,False +797,22.0,14.0,14.0,13.0,13.0,14.0,15.0,9.0,HCHGGBDEFAFAGAHDCGCGCHCGFAADEDEABAGABFEFEFEBDFGABHFDAABCHCFCADBBAGDGDGDCDFEFGBDBDFFGCBCBEBGAAAAAAHEHEBEGCAAAFHECEC,False +798,15.0,14.0,14.0,26.0,14.0,22.0,16.0,23.0,DCGAADDDHDHFFDBGGFGEGBBDHAHFFFFAFCFBDDFEAEDHDHGHGDCHCFAGBDFCFEFGAGHECFCEDAHAGEBFBABDEDADCDHAFCFAFHBDFAFADEGEHEHBHGFGCGHGCDCDBBHHHHBCBCHDEDEDEDHH,False +799,27.0,20.0,19.0,24.0,17.0,17.0,26.0,21.0,GFGDGDCDFGBGBEBGBHHFDADAHEHEBBBHFFGGCADACAGHBHAAFACACHBECEFAHADGDAEHECFABCGCAHBHAHDGEEHFDFHFDFCAHDBDBFEGDGDGHBDBGAGEGBGCCECEBEHAGABADADADECGCGCAFHGHBFACACFDEDEBGACAGHGFDDD,False +800,14.0,22.0,27.0,22.0,29.0,27.0,20.0,20.0,BCBCBCACACAHDBFCHEHEFBGGCGCABBHBEEEBECECBDHDEBAACGCGFGFDFGBCDAHHHHFFEDDDDEFFHFDEGGGHEAEDEGBBDFEADFCGCGCHFHGHGEDCHFFFDFDCHFBCBCBCEEEGACAEHEFGFDFCFBAEHECGDEFGHGAFAEBBBBDCEHFCFEFDCDEDE,False +801,5.0,1.0,4.0,0.0,2.0,1.0,0.0,1.0,HCAEACAFBEACAC,True +802,15.0,14.0,17.0,11.0,11.0,11.0,14.0,5.0,DGAEAFAFCFDADEFEFCACGEHEFGCHABACABHBADDFDFCGEGEAAACHCGDGCGBEBFDCABBBBDBABFGGCCCEGFBBBEDAHCGCGCGCED,False +803,19.0,24.0,22.0,27.0,21.0,24.0,25.0,26.0,HFAFEFEFCCCHCHGDDHEHEDEACCFAFBHDEDEBGCGBFAHAHAHFGDBAGAHBHFEFBFEFABCDHDGACACBGDGHAFBDBCFHFHDHDGDADBCFGGBDACGHGCECEGGAGDGDGEGECADHDABGBDDCECEHFHBGGEGEHBFBDHFACAFBBBBHEEEGCDHGFDFDFEFHDHDCBBBC,False +804,14.0,12.0,12.0,16.0,9.0,14.0,9.0,8.0,ABCBAFDEDFDHDCDBAFCBGBDBEAEGEBCDGAACABDECECEHEAGHGDBHFFFCGDADFFFGFDBDFAHCHCHCHCBADADADABFFGGEF,False +805,10.0,5.0,7.0,4.0,17.0,8.0,9.0,3.0,AAGAGAGAGAHECEFEGEHEBEAEFDADFEEEECEDECHGFEFAFBEDFGBEACBCEFBCCGG,True +806,16.0,25.0,13.0,17.0,23.0,16.0,21.0,18.0,CBGEEFEGBBBCHGHBAAAAGAGEGCHCEDBBBBBHHHHDAFFEEDEDAAADFEBHGHDHEGEGHCECEBBDADGGGGGDGHEHEHEBBBFGFAFDFEFEBEBCFFEBHBECDBDFAFAGHDFDGBHDCFCAABCBHEGDGDEBGCCAF,False +807,3.0,8.0,5.0,8.0,9.0,8.0,9.0,9.0,HFFFBHCHEBEBEBGBDCGCECEFDFBFGAGHHDHFACHDHDEFBGDGEHEADGDBEGG,False +808,18.0,19.0,24.0,19.0,15.0,25.0,23.0,17.0,CDGFCFCAGHEAEADCGEGACBGFGDHEEECACECECFAHAFDCDHDFEBEHDFDFHFGBEBGGGBBBHBHFAEAFGFAHAGAFCGCHCHGHBCDDFDFDGDFBEBEBFAFCFGDCCHGHADCBFBGBGHFCGDGBCAHFDFCFCBCBDAEABADGFGHC,False +809,24.0,16.0,20.0,18.0,20.0,16.0,26.0,18.0,HBEFGCGHAHADGCACAFBFAFCEBGBFDGAGAEHHCDDHDFDHDHDEECGABCBFEAEHDGGGGBABGFEBCAEGBCFCHGHBHBABGBHFEFCCCCAHGEGEFHFDGAEBHDADCGHEAEAEAEAEGEDCDADGDGAGAGAEHDGCCFCFCADBGF,False +810,7.0,10.0,7.0,14.0,17.0,13.0,14.0,8.0,DEAEGEFECACABGEGEAHGHGHAEFEFECHDDFDBDBCBDBDFGCGEBECEDDDADBEFEBDFGBDFHGCFFDGGFEHEHFHBGAGEGF,False +811,11.0,12.0,11.0,18.0,16.0,11.0,15.0,16.0,EBEBABDHDHDHEHGHFAAGGCAFEDDGEFAFHDBDBDHEGGGGBCBCFDDDDDEDBHFEBHCHABEFEFGHECECBFGGGEDHCHCGEGACAEAECHABCHDADFDFHG,False +812,7.0,8.0,5.0,1.0,6.0,6.0,5.0,5.0,HHHHAEACACBEBCCAFAGEFCFDBHBFBFEGAGEGBGFABBE,False +813,7.0,6.0,14.0,17.0,20.0,8.0,11.0,16.0,BCHCAFAGAHCEFEDEHEDCHGHAEDGDFCFHGHGHAEGEGFHBBDFEHEDEDHDEDEBGDDFBEHGABCEDECCCADGHEHEHCHCDCDCDCEEGEFD,True +814,27.0,14.0,15.0,25.0,17.0,16.0,12.0,25.0,HFFCACAHFFCBCFFGDDECEFEHCBCBCDAAAGAHAHDECEFHAHAHDEABBEBCFGBGDEAEAEADGHAHACDHHHBCBEDFFAFHFEEGAAAAAHAHEHEDDDDGAGDHDBDFFAHDBACACAGHHDGBGBEDDBDHFHECGDDDHDH,False +815,9.0,8.0,11.0,6.0,5.0,16.0,9.0,7.0,DDGCCHAAADDFEFBHDFFFDFCFCFCFEBEGGGCFCGHGHEAAAFFHBCBGBEBCBFFFCFCAAGAHHGB,False +816,27.0,23.0,14.0,24.0,26.0,27.0,25.0,22.0,DABHHHEHAHAEFDBAGABDBGHDAAGAGFBAHAHEEDABFGGEEADAFBCACGCGCEFEBEBDFDCDGDEFEHEHFAGAGCBCGCBCBEDAGGBABHDFBFBDEHEHGBFEFEBDFHFHFDEECAFGFGFEADHDAGAGADCDCHFHCEADFDGEAFBFCFDBEEDGAGBEFEHDHGAGHGHFBFBF,False +817,1.0,1.0,2.0,2.0,3.0,7.0,3.0,4.0,FFFFADHDHEHEGCFBGECFHFG,True +818,10.0,14.0,17.0,5.0,12.0,5.0,16.0,9.0,CACBHAACABGDCAEAFGBEHEGCGCGEGEDBGAGFHBGCECEFEGEGBHBFGAGHEABDFDBCBCBHEHGHGBDCACBGBECCCCCH,True +819,20.0,12.0,13.0,11.0,16.0,13.0,21.0,6.0,ADCECACDCEGDFFAFBGBGBGBAAAEBEBGFDADEDAACACDCHHBGGGGGGGEGAAHFEFCGDGBCFABAFEGCDHFECEDEHABCDAHFGAGEGAGAEAGBFBCEFEFE,False +820,24.0,22.0,18.0,21.0,20.0,19.0,14.0,22.0,ECFBHAHAHAEAFBFGDGDCBCGAEAHABCBHFEDEDGBCDCDADABAEAEBHDGDHCBAHFDCDHHBHEGAAFAFCHCDDEHBFBFDGDGHBAFCEDEHFCEHEHEHGCGAHABCBEFHFGCDCDFBFBFAFGBDEDAGCHBEBCBADAGEBEAEAFFH,False +821,24.0,21.0,19.0,22.0,19.0,13.0,20.0,29.0,DAHAHAFEGCDEECECAAEHEFDDDGAGAGAGABHBGEHDHFHEHAHAHAFBHBHCAADCEBBGDECHGFGHGAGEDFDFDHHHCGAEABFDGBECECAHACFCHGFBDHGFDHBHDDDDGGHEHAHBGBGBHEABBFBDBFBDAEEBECCCCCACHCBCHAHDGDB,False +822,16.0,25.0,27.0,23.0,14.0,15.0,16.0,28.0,BHCHCDCAGFGAGBFHEHBABGDHBABFBGBDCHCHCHEHAHEHCHDBGBHACADADAFFHAADACBCBEGEFDFDFDFCHEHDDBDEGEDHHHCDEGHCFGFDEDBBGFGCGHAHBDCECHCABHFCCHCDEDCDCGBBEHDHBGBFEFCACHCBBABCBDGC,False +823,19.0,16.0,17.0,19.0,13.0,21.0,12.0,12.0,AAFGBDHDCDFDEHBBFHFCDCABBFDFGEGEBCHDDDBDGDACAGABEGECECECEFEHCHAGDDHCCDAEFFAFBFBGDAEHHBABAHADABGBFCFGDCDFHFHAGAFAFDFBACACFGFEFECBC,False +824,23.0,14.0,24.0,16.0,17.0,21.0,26.0,11.0,EEEECEBHDFDBDCFAABFDEEGGCGEGFHDGAGBCFCHCFAFAGAGFFBGAFAEABCGAEADADAHBBEHCHCBCBCDCECGHBHAFDEDEAAACACFFECEFFGACCDCFGGCGCGFDFHFGCGCGAEAGGHHFBFDADABBCGGGDGDG,False +825,16.0,23.0,19.0,19.0,25.0,21.0,19.0,16.0,BCECEGEHBGBGDACADFFBABGGEBEGCGAGDBCFCEADAEFEDDCHCDEDGBGCFHFGBEBEBEHCHCEBEDEBFBFEFHFHFGDEAEBGBEDDCBHDFGFCACAGAHBDBDBCCFCFAFDDDADHEEEFHAEAGBGCAHHHEHFGFBFGECHABF,False +826,8.0,5.0,4.0,4.0,6.0,3.0,1.0,4.0,CDGDCFEEEEABABADAHBFBHACAFHEAEAHCBD,False +827,24.0,26.0,18.0,19.0,16.0,34.0,27.0,29.0,CFAFCHHGFDHDBDBDCDCHEFBGBGBHBDADCGCGHGFDFBAHDDAFECBFFFHFAGECAHAEBEAAACGEGHGEABAFGCEAGFFHFGACBGHGAFHCHGHGBFAHGHBHBGBGAGCFBEDHBFBHEHEBFGECEADHFHFHFDABFEFHFEFBFBABDBDFDADGDGCAEAFCFCFCDAGGFGFBHHHHB,False +828,2.0,3.0,1.0,7.0,4.0,6.0,1.0,1.0,ADDDFDFEFEDEBFBEGFDADFHCB,True +829,18.0,8.0,19.0,22.0,14.0,21.0,12.0,12.0,EGEGCHAFEECHDBDBDCFAFEFDFEGEAFCFDADADCHFHEADAEHDHCCFCFDFHFDFDACACACEFDFDGBFBCGEGFGCGCAHADACEDDGCCACHBABDBHAHFFFDDHACBDEAEGGGFD,False +830,14.0,17.0,12.0,13.0,7.0,7.0,14.0,9.0,EGEBHBDCDGECBABADDGCABACFCEBDCCADADFGHGHGFGBGBGHGFDDCDAGABACHHDHDFDCBBGBAAFACEHAGAGBEBHBCBEBF,False +831,13.0,21.0,11.0,11.0,12.0,12.0,12.0,8.0,EAEDGBFBDBCHEBEBEBCHCHAFGGBCDDDCDCBADAFAFABADFCBCGEAEDBAFAEHEHADFHBBEHEFBFGEBHFGBCBCBFGGAGAGBGCGFBDB,False +832,14.0,20.0,21.0,16.0,26.0,24.0,30.0,17.0,BGGGEEEBFFFEFCDGGGGGCGABDFGHCAFFFDFEHDHAGAGAEBEBCBCAGBBDBFBFEEEDDFCCGCGEGBBDBHEDCFCHGFEEBGCFAEGEGECFCGCHEDDCBEDDDHHHCGBGEHEHGDDCGCGBGEGEBEHECGGAEABAFAHAFAFHFHCHCFFFHFBA,False +833,0.0,0.0,2.0,1.0,0.0,7.0,1.0,2.0,GFFCFHDHCFFFF,True +834,15.0,17.0,13.0,12.0,21.0,19.0,18.0,23.0,DEFBAGHEHEABHDFGFHFHCHDHECEHBHDGDGFFCGBFBEEHHCDEFECEDEBCBGEGEGACAGHGHAHDFCBHGFFFFDACEHEBFBHBHGAAEADGGADHHHHGHGFAFCFCGEDFFABABGECACABEBEBEB,False +835,9.0,17.0,15.0,12.0,13.0,15.0,12.0,18.0,AEAFDHGHGFDEDBFBABACCCFCHEHCFEDHFGFDHBHBHEFAACHEDECFCGCBCECEGHBHCABDBEGFDFDBDBEGEFFCCGHAHAHGHDFBBGBGDGHBHBCBFHE,False +836,24.0,27.0,17.0,31.0,24.0,22.0,21.0,23.0,DCGBEBCDEDADFBFEDADADBDCDCDEDFDGBGCGBHBHBHEHEDEDAGBGFDAHGHBCECADBDEDBFFAFAFAFEHHGCGFEFDDGDGFBFGEGEBAHAFDDHFABBBDADAHAGAFFFCGGEECHGAGAEECEBFBCBHHGEFDAAECFADHGHCHBBBBDEDHBBBEHHAHCHCAEFEHADGDC,False +837,8.0,2.0,11.0,12.0,11.0,8.0,3.0,11.0,BHCHEDEHFAFHDHCHFDCDFDFDAAHCFDDADHDECECACECAFEHEGDGEHEDEHFCBCGCAEA,True +838,12.0,19.0,12.0,11.0,20.0,17.0,13.0,16.0,DEFEFEHEFBFECEAEAGBGAFEBEDFGFGAHFHFCGBBBBBBHEFEBHBGBGHCHFBCDFHAACCHEHACDBFEGEDFBCBABHHCHEHACACEDDDDFDGHGHCAGFDFBEEEGEGBA,False +839,1.0,4.0,3.0,4.0,6.0,6.0,4.0,1.0,GBEECAGBFBFBEDCDFDFEEHEDGFGFC,True +840,5.0,4.0,4.0,1.0,6.0,4.0,2.0,2.0,GEBEFEHEAADACACFCFBBHCAGEBEF,True +841,15.0,12.0,13.0,8.0,18.0,15.0,11.0,15.0,FHFHFEAAHFEFCGEHEHCHCBCAEBBBCHAHAEGFGABHBEBEFCBCAHDHBEAFGBHAFEFBGCFEFCDADBDEDEDEGEFEFAACHDHAEACGEGHGCGAGFDC,False +842,17.0,27.0,15.0,15.0,25.0,21.0,18.0,18.0,DBEBDBEEGGGBGEHCACBCBABGEDEDGFAFCCBEDCGGFGBHAHDBBHBHECACEDBDHAAFAEBEDCDCHGBEDECHAFAFECECEFHGHGHBEBGBGBFFFFHFEFHFHEBEGEAEFFAFGBBBFHCHADFDFBABCGAEAGFHDADEBHBE,False +843,20.0,14.0,16.0,25.0,17.0,16.0,12.0,24.0,HBHEDGBFBCADADACHHDHDAEAHDDDDDHFFDHDGCGCBHEGABAHEDEABACDCEFGFHAGGBACGHAFFGDCAAGHDEGEGEDABACABHFDEEBEBDBDBDHDADAHCHBEFEDEDCFCFCHCHFHFHFHFCAEHHFCE,False +844,6.0,6.0,6.0,6.0,7.0,4.0,7.0,2.0,GCECFBDBDBEGHDEAEAFFECECACBGBDADGDGHFABGEGCA,False +845,14.0,10.0,13.0,17.0,13.0,16.0,16.0,22.0,DADFGHGHFHCBGAFEFCFCGDGDEDBABABECDCDBBGAFAGAHDDDDFDGDGDCEGGFHFHCHGAGDHHHFFCGCHHEFEAHHHFHGEGDAHECDCHHAHAEAEBCFHFBFCEHBBEEA,False +846,13.0,21.0,15.0,9.0,8.0,13.0,6.0,10.0,AGBCBCBDGCBFGHABCBCBEBABCGHEHBAFAFDFECDBBAAHBHBHCFCFDBABDCDFFCGHAHBHBEBEBCFCACDEHACEBFDFGFAFAED,False +847,8.0,14.0,10.0,15.0,9.0,10.0,9.0,7.0,DECFAHHBGBCEAACBCBADDEBHDHDEDFFFGEAEBGCGBGDGDFDADBDBDCFCGCBCHABFBDEDGDGBHBFFCFEAEH,False +848,10.0,5.0,6.0,10.0,12.0,17.0,10.0,11.0,DHDEDCDFDFAFAHCFGABAGFCFBGGGGAHCFDFAFEEEEBBABHFAFGFEEHDHECEHFHFEAHAHEDFDFHFDGGGEC,False +849,22.0,14.0,13.0,19.0,14.0,18.0,13.0,19.0,AACFCFBBHBGFDADADAHHCGFBCHHFHBHDGDCAHAHABDEDBDAHAGFGEBEBACHCDEGAFFDGBHFCFDDBABAEEDEGEFEAAGAGABADAHFGFCFAAGCFHEHFGFBFEEDEHEDCDCDCDHHH,False +850,12.0,11.0,24.0,25.0,18.0,37.0,27.0,36.0,GEGEAEAEDHDEDECECGGGEFEFEGCBFBFCFCDCHEHDDGEGFGDHFGEGAGCGFDHCHFHDGCCHEBBDACHCFCHGHCHCHGDFFFFDFHGHDFFFGFGHHHGCDFBFCHHFHDDBACHEEFDCAHDHBHFFFHHCHBHFHDGFGFGBEAHFHFHFCAGGDCBGDGDFFAACDCAFDFDFBHHAHE,False +851,8.0,20.0,9.0,10.0,16.0,10.0,11.0,18.0,GAGAGFFHFHCHGHEFEGADABHBHBFEEEBAHCHCEEHEDCAGGBBDBFGFHFHAHFHBABEHEBFBCHEBBBDDDCDBECEGDBCBEBEBHBGCHEDDHG,False +852,8.0,4.0,3.0,3.0,5.0,4.0,5.0,3.0,CEHEHBGFGBABDCGAGHFDCGAAAAEADAFEFEB,False +853,2.0,2.0,4.0,5.0,2.0,8.0,1.0,9.0,BHFHFHFADCCGFDFDBDEFAHHHHHFHECCFD,True +854,0.0,3.0,1.0,7.0,1.0,4.0,3.0,3.0,BGEDFDHDHGFBDBCGHDFDFD,True +855,13.0,9.0,23.0,8.0,13.0,14.0,12.0,14.0,CFCFCGHEACCCEEEGDHHAHBGBCFCDCDCFFGCAFDCABHCHCDFFCECGCGCAABFDEDACCHHAFAEBEBHGHBHFGEGCGCGAEBCBAGEFEFEFDHAHAH,False +856,10.0,14.0,21.0,25.0,13.0,22.0,18.0,15.0,HDAFAFDFBGDDCEEGEDFGBDBGCCCCDDDGDGHFDGHEFECHCHCFEDBDBACGFBFBFDCGEGCABABDEGCGCECEBAFGHHBDDDHHHGGDCDCACAFBEBECFCFAEHHFFFDGDGHGHDDFDFHFCFCBAF,False +857,5.0,7.0,6.0,6.0,3.0,6.0,3.0,6.0,HBHCDAHAFGBACABHBDBDEFGCHCHCBEFEFGFCFDDBDA,False +858,5.0,6.0,10.0,9.0,8.0,7.0,3.0,10.0,BGCHCHCBDDHDGDGABCBABFECECECDCDFHHCEDDFFFHHEHEAEAFHBEDHCAF,False +859,5.0,3.0,3.0,10.0,1.0,2.0,6.0,6.0,DADADBGHEADDDCDGHGHGCDCDBFAHHFHAGDGB,True +860,23.0,20.0,27.0,31.0,27.0,21.0,22.0,20.0,GBHCDCFCFDEDHCHGEFEFECCCCCADABAHFHFHFDGDAEEHACDDGBADFDEECFAFCFEGCGEEHFAFEFBABCDADEDEHBHGHBBAECECGBHAGFHHBGECCDEDBFHCACGCDAGAGADDDDDCDGFCFCEEEDEBHGHGHGCGCBDADHBGDDEDABABAEDEBFCDEBABGBDAFAFGEGH,False +861,7.0,7.0,14.0,4.0,11.0,5.0,11.0,5.0,GCGFGBGCCCGFAAEAECECECGBABHHCAEAHAEFEBEHDCDCGFGFBCGCGCDBEEHDGECB,True +862,12.0,3.0,10.0,5.0,8.0,8.0,5.0,6.0,GFCAHAHAGACCEHDBBAAAHADECEDECGCBCECFCFHFHAGGEDEFFCFAEAFAD,False +863,24.0,14.0,29.0,24.0,18.0,18.0,12.0,25.0,ACACHBEBEDABHBGCDCFCEDFCGCACGFADCCCCBCDEAEBDHEEGAGCDFDFDFGEHAHFEEAEHCCFHFEFCHCHDAAHGDCDAHFHEHDHDHAHADEBEBEGADAHEBFHFHACGFGCGCBCDCDCACFCFABCBADDBCBHHDHGAAHAHFFDHDEDA,False +864,12.0,14.0,8.0,8.0,15.0,8.0,10.0,15.0,EBEBGHCABAFAFDFDADGBHCEBGBGBCFCAEEDHCHGHBHDGDHEHEHEHCFGFBEEHAAAHGHGEGBFCABHFHEEBADCDABEBEA,False +865,3.0,2.0,2.0,3.0,0.0,3.0,0.0,4.0,BHDHBCFDFCAHAHAFD,True +866,5.0,8.0,8.0,6.0,13.0,7.0,15.0,8.0,FHCDEDADBEBGAGCCCEBGGFGEGEGAGAGHDHGBEHEDGAGEBECHCGFEEHEHGGFBFBFCFHEBCD,False +867,15.0,8.0,10.0,4.0,10.0,7.0,12.0,11.0,GCHHEHGBDBCGCBCFEAAHAHADFCFCFGAGAFBGAHAEGFBECEABHCHAEAEHGHGFBDCHGEGEGDACABAEA,False +868,13.0,19.0,24.0,20.0,14.0,16.0,12.0,20.0,HCHAHAGDDCDBGGHGHGCEEAEGFBFDEAEFCFHDHGFAFGEHDBDBDCECDFECHCDCFCHCHBBBBGAFDCACEDBFFAFAFBEHCACDHBCBCBHBCADDDBDHDHCHCBABHHEFGAECGCGCBDBDCFHFEE,False +869,11.0,10.0,12.0,15.0,14.0,12.0,10.0,5.0,CBGECDGDGDADCGAHDBDFFFFEAHFEFDBDGDGECECDDFDADBEACGFEBEBECCCGCBCBEAEAFGBAAAEDEGHHDHCFAFEFB,False +870,8.0,16.0,15.0,5.0,12.0,6.0,10.0,5.0,GEGAAFBCBCEGAAEBEBEFHHCBAAGACBBBBEBCGCGCECECBABCFCGCFEDEHCCDGBGFDFDEHCHBBGBDE,True +871,7.0,10.0,13.0,4.0,10.0,7.0,7.0,8.0,GAAHGCBADEDHDCCCACAFHEBBBBBCBEGEGFCHCBEGEGEHDHCFFABCFCFHGHABFECECE,False +872,5.0,6.0,11.0,4.0,5.0,6.0,7.0,6.0,FCCCACBDAFCCCFGBBHBGAGEGDGCGHGHDHDEBHCCFCBAEFEFEHA,False +873,6.0,3.0,2.0,8.0,3.0,5.0,4.0,1.0,AADDDCDCGGFFEBADADADEDGBGFFEFAHB,True +874,16.0,16.0,9.0,13.0,16.0,16.0,11.0,18.0,DGAGHBHCEFGDAAEAFAFBBDFHEDEDHBHGHGHDDEDFCFCAAADAHFBCBCGEHEBFDFAFCFAFAFBECCBEDHHEHEGBGCDFGFHHHBHBEBEBHAEADBEBAAGEGHF,False +875,10.0,10.0,11.0,9.0,10.0,8.0,13.0,16.0,AFADADEDEFHCHCFGBGEHDFGHCHEGBGHFABHEACHBHBHBHGDGBAAAHAHCHCGGGCGEDEBCDDGBGAECEFFFBCHCHDE,False +876,10.0,18.0,8.0,11.0,7.0,15.0,11.0,9.0,FCHDHBFBGCDHAGCCHDHAGFFHBHEFAFAFDBBBDBDEACGGGBGFECECACHDBABFBDBDGEADADFFFGEGEBBBFBFBGBFAH,False +877,4.0,5.0,14.0,13.0,6.0,8.0,11.0,11.0,ACACGHADGCECGGGDCCCFCFBFDFDHDHDADHDHFFBHGHCHCGCDCDHDEEBGFDEHBHGEEBDFCCGG,True +878,22.0,17.0,15.0,16.0,16.0,19.0,13.0,15.0,CCFCHHDBEGEGDCFHFBAGFEDDFDCECEGBCBABADADBGGDBACAFAEABHHHFHCHDBFBDBDBEHHCHCHEEGFGFHAEAEAEADFEAABCFCEAHFGAAADFDFBFBEGCGCDAFAFAEDGBHBGFA,False +879,11.0,12.0,5.0,10.0,10.0,9.0,11.0,9.0,BCBCEAFGFGHBHBHDDFEFGBGHGFBDCAAGEHDBDGHGHFADAEEFEDEDEAHABABACAGHEDFAGEDBGBCBF,False +880,22.0,23.0,20.0,22.0,17.0,22.0,27.0,22.0,AFEFEHDHDHDBFBGBGEGBGFGFGEHEABABGGGABAHDHEBCGCGCFCDBDFEEAAAFDCBFHGHBCGAEDFDFDBCECFBAGAGAFEHGGCGDBBCCGBDDCDBDCFCAHDBAFFHCHDHFHCEEDHDHBHCCBFBAEAEAFGDCDHAHFHEHADAGAGAFBGCGHGFBEGG,False +881,26.0,17.0,21.0,13.0,20.0,12.0,23.0,19.0,BAEAGCGHGAEADABEEEGAAHHDDBDFGAGACCHHEHEBFBHEEEDFGFEAGHCCACGEFEDCGCHCGFHHBHBGBCCCDCGBGBABABFDDHEAEFEGGGGEHAHACACDGBGBGBEAFACEHFAAAHGHGDCCECFCBCBHDAAAFAD,False +882,1.0,1.0,3.0,2.0,1.0,1.0,0.0,5.0,DHHFADEBCHCHCH,True +883,7.0,3.0,8.0,7.0,4.0,4.0,4.0,4.0,GDEDCFHFHDHDEGEACDCABBGFACACGCFCDADBCAEAH,False +884,21.0,12.0,14.0,11.0,9.0,9.0,15.0,13.0,EHEAEGDDAGGBGFFAGHDHDCDCDCFCGGGGGAAEGCHEDEAEFHFAFGCBHBCCCCADBBAGAGHBCACAHAHBFEDBGBCBEDDHHABAFAHAHFBCAAAA,False +885,16.0,26.0,24.0,20.0,25.0,24.0,19.0,20.0,DFDGGAEAEAEDHGHGCCABBEECFCFGBGBDCGFFDBDECEADADHGHFDBDCEEBCGCGAFBFBCHDFDFEFEFHFHFHBHFEFHCHCBAFDFBFCAGAECBBBBEAEBGCECFHEHDCCEGBGBGFGFHHEHCHBDACECABABDBHAEDDCGGBBEFDFDCBAEHEHECG,False +886,13.0,28.0,17.0,8.0,23.0,25.0,17.0,16.0,GFFBFBHCFBBBCGCGEEBCBABFDEBGBGCACEHFHFHBADDCGEGEBHAAACFCEHBHBDAEFFFFDFDFEFEFECEBBBHFGBBHBEGCBEAEDCHEEEFBGHGECEHFHBABFCFCFCGCEAGDGAGAFBGGAFHHHBEBEBF,False +887,12.0,16.0,10.0,18.0,15.0,11.0,14.0,8.0,EEHEFGDCAFDGDCBFBFGFBEAFBBBAGFGBGCHCHCAGADCFCDBDEHEAEDGDBHBFGEBEBDBDADCDHDEABDDEDFCAGDGAGAFDEAGCGBEBEHEH,False +888,18.0,13.0,17.0,15.0,11.0,10.0,18.0,15.0,DEGEDEFAHAHAHGHGHGCGCFDDDADFCBGDGDCBABCBEACAGAGCEDBABDHFGAGAGDEEHAFCDCBCACBEBHCGBFAHAHCDFHBGBGHFHGHFBACEGEGCHAECFCDAD,False +889,22.0,5.0,11.0,9.0,14.0,19.0,10.0,13.0,HEHFADEFGFCEHEFDFHFAFGGGGAGAFADGDFAEAHBCECEDFCFHFCFDFDAACACABBFGCHEAAABCDHEAEABFHFHEGEFHAAAAACAGDHCHEFE,False +890,27.0,36.0,17.0,27.0,26.0,14.0,25.0,25.0,FHDGFABEECADAEBECEABAGHECDCDADGDADADEHEHGHBFBCBGDEEEEEBABABHBHAGCEDEDEHAHAGGCDCDHBABHBCACAGFCFGHHFDFDGBGHGAGCGFFBHADFCECEHBDBGBABACAHEBBHGHEHBBEDEFEBGBDBCGEDBBBBBEBDHDBAHGFGAEBHAADGHGDABFCFDAGBGDHD,False +891,18.0,15.0,22.0,14.0,25.0,27.0,18.0,19.0,FHFHEHAHCFEDCDHFFFHCCCCCCFAFGEAHAFGGEGEGEGFGFAEHDCDFHGAGEBHFHCHBHBEDHDCFCACGBFCDDEHBCEGAFABEBFDEGAFDCACFEFEDEAAGAGAGCBCDFEHAHEHBCBCBFBEEFEHGGGCEFEFEBEAFFBDADB,False +892,15.0,15.0,17.0,14.0,25.0,21.0,15.0,21.0,EGAHHHDHDFEAEDEGGGGAGFHFAFEEEHHBCBGHGBGDFAAEAECEFEDDBFCFCAGFFHFHFHBCFCDHFHCHADBHFGFGBEBHHEEDDCDGBCEEEBGBHEHEDEAFCBCECEBGAAAEDCDCACABEHHCFEFCFBF,False +893,5.0,2.0,1.0,1.0,3.0,2.0,5.0,2.0,BHAHAEEEGFGFACGBDAGAG,True +894,1.0,2.0,2.0,3.0,4.0,6.0,4.0,3.0,FCFCHHEFEFGGGGHDBEBFAFDDE,True +895,12.0,25.0,10.0,17.0,18.0,19.0,18.0,17.0,CECBHFGFGEBBHFEFDBDBABDGAGAEABCBGAGAHCEEHEHEHDDCDBFHFHEDFCFBFBFAGGGGGFGEHBBBHDHBHDEBEFGDCBBBDBGCAHHEGBGBCDFDEEEDEACAFFGBBHFHFDFAFHGBADED,False +896,16.0,8.0,11.0,13.0,10.0,11.0,7.0,7.0,GEDEHEHBBDADFDADCDCAAAHFHFGFECACAEDCDGAEAEBBCBGEACAHDBDEGFHFBCDCFAADACBCHFAFAFEGGDF,False +897,11.0,6.0,9.0,7.0,10.0,14.0,15.0,10.0,HDBFBGCFCGCGBGDEDGHAHGHAAFHFCGBGCAHHGFCFAFEBGHGBDCHCHDEEFEFEAEAEFEFGDGFAFACGEFDAGA,False +898,17.0,13.0,21.0,30.0,28.0,20.0,12.0,19.0,EDDBGCECEDBCBCDHGFECBGBEHHHEHFHDGDHHAFAHCHDBEFDADCDHEEEHEGDGDGFEDCACEDEAEAEFDFDFDADCCACFEFCFEFCBBHCCFEEDHDFGEGAFCFCACABABCGDEDAHEDDDDGDGFHDHDABFCFDFAHEEBEBEHEAA,False +899,3.0,3.0,2.0,3.0,3.0,3.0,8.0,3.0,BCEFGHGHGAGBGBGDFDCHEGEFAADG,False +900,16.0,24.0,17.0,15.0,11.0,13.0,13.0,18.0,DDCDADAECDHHHCHADDHCHCBCADAECGHGEAHFHGBBHDADAEHHFHGACACFCFBEBEDCGCGBBBBGEFFHFBBGCGBABABAHFEFBBECCHGFDFBFAFAHBBEBEACDGDGCBHBGBDB,False +901,25.0,30.0,29.0,16.0,34.0,19.0,24.0,19.0,FFGCECEBBBCDCBFEEEECGCABAFEFGHBDAACECGHDFCHBFBGGGBGHCHCBCECBGBEFDHBHBHCHAHAGABABGEGFCFBEGEBBCBCDHHHCHCHDBDCFCAEDHGAGEBEGEBEDEFFDBDEFBCEFEAGGFGEGFBFHHACACAEAEAEBEHEBAGAEAECGABADDDAECECFAAEDDAGCECBG,False +902,24.0,23.0,19.0,24.0,26.0,27.0,19.0,14.0,FAAAEACAEEEGEDAHEBADAGGHEDCABGFFDFDFEBEBEDEDGAHFDGBCBFDFGECFBFGFBFEFCFEDADBEFEFACACACAHADBBBEHAHBGBFAGBEEGGFGCGCFAFDFEBHGCAAGDGFHFCFCHCDCBFBGBCBEHFHCHCBEDGDACAEBDBHFHEDDDDDEAED,False +903,29.0,29.0,25.0,18.0,19.0,26.0,26.0,24.0,GABBEDADAGFHBHFHGCBCBDADGBGDGHEDBGBGDAEBEAGFGACEBEDADFFFBBBCFCGAFAHEHEHGBAAAAAAGGCCHBGBABHEEFHFHAHFBGCHDHFEBEGEAEDFGCHBHACADBHGDGCEDFFHFEFBCBABAHAEAGGFFCFAHADGDGCBCBCGCGCBCBCFHEHDFFEFHFCFABCHCDCAC,False +904,6.0,3.0,10.0,6.0,5.0,4.0,4.0,1.0,ACGCFCACDCHCDDDEDCGGEFBCBCBFGFEEAEDCAAA,True +905,3.0,18.0,9.0,11.0,14.0,16.0,4.0,13.0,DCFBBCBEBDBFFEFDCGHBHGDCFBFDEHEFBHBFEFHFHFGCAEHFAFBEHEHEHCACHGFDCBEFEHEBDBDBHBDEDEDBCBFB,True +906,16.0,25.0,37.0,22.0,24.0,10.0,28.0,28.0,DFDCDCEAEHCHEACBHBGBHCCGCECADDDDDDCHHHAHCCCGDECECEBECHCFCFBHBACGCBABCBHGEBBBHGHGBCBCDEEAAGAGDHFCCEDEDGDGDGBGHHDFFGEEBFAGHGFCBBGEHHBCBDBABCEAGACACGBEHEHCFDHAHEGGGHGHGACEDECHCGCGCDHFHBEGEDBCGC,False +907,25.0,18.0,28.0,21.0,19.0,32.0,30.0,20.0,GCGCEBHGCGCEDDHHGCCCCGHGHDHEHACGGGBGFGBEACGHGCFDFDCCCHCFDFAFAEAGABACAGACEBHBFGFBFBDHCFAFGFACAGDEHCDBGHAHBBDFDFCFAEBDCGFAHGHGFGFGBADFEFHBDADABBEAFHDDFDFGBGDEDEFAFEFEFGFAFDFEFCACHFHBEEECGCGCAAEAC,False +908,28.0,27.0,16.0,15.0,23.0,29.0,25.0,24.0,FAFEFGFBABHFFBHDCCGAABEBCACAEFFCFAGAEEGEGFGFDFHFHBAGFGBGDHBHBHBCGEGFAAHAHAHAEGEBEAHABCBDFGFGEGBFBHBDBFBFGFGHGHBEBEBDGHGFAFCHADEEECECFBACCBCDDHGGEHEGCAAFAFBDHHHDHDFDADGFAAEAFABEECGHHDBEACB,False +909,22.0,23.0,20.0,21.0,31.0,23.0,29.0,28.0,EAGGGDCHHHHCDDEDBCHAEDGBGAGADBHAFFHGBGBDEGEGHGAGDBEGAGCCHFHFGEGHHEAEBDDDDADHCBBBCACFCGAGECEAEFEGEDDAAEFEHBHBGBFCFCHGBBDBFBFDEAEAEFCDDEGFGFCECAGHGFGFEHHDAFHFHGHGHFHFEEEHAFBBBEAECGCBCBCEEAHACBFDFEHEH,False +910,35.0,20.0,17.0,22.0,15.0,17.0,23.0,20.0,BABABADGDFFFFFADHEEAEHCBGBGDGEGCACHEFAAHAHAHBHGHBABCBCGCFDFAFCFCEAEHEDGFGBAAADBGADADBDBECGGFCBDBHCAADAHAGADCGFGFGCGCEDAAEAHDEDBAGFGBADDDCDHHHCHAHDEAHGFAEAFBDHAGAEHBBGCGA,False +911,20.0,22.0,16.0,16.0,19.0,34.0,24.0,21.0,HHBBFFAHAHEFAFCDBDBDGCEEBFBDCCBCHDFAFDBDBFCFAHGEDBGFFFDFHACEDGDBFBFCECHCHBFAFADAFFFFFFFGFBHGHGHGHAFABACHCFGGGAFHFHGGGGFAFEEGHGEEEGECDGECBCBHDGDGHEHDBAGEBEAEABABFEGACHEBGFAF,False +912,14.0,22.0,22.0,16.0,10.0,16.0,13.0,11.0,GABHDHAHACDCBFFFECHFHEBEGABCEHEBBFBACHCHCACABEFFDBACDHFADAFBFBGGCGCGCHFBFCGDFAFGBCBCBDHDGDCBCBCGDGCGAGABCBCACEDFDEEFBBDDDEDB,False +913,20.0,27.0,29.0,23.0,22.0,31.0,29.0,18.0,GFGEECFDFAGEFHFACDEGCGCGHGHDHDCGCFDBAGAGAGDGHFDFBFGFGAGHDAGAFABDCFFECECEFFDCDCBCGDBABFFHFDDDGACHHDBEBEBFCEEBEHAHECBABGGAGDHDCEEGFCFBDECACAFHFAFACBEAGGGBGBCBHFCFCFCFCHDFAEBBBHBEBECFCHEEGBGBFCDBDBDBHGC,False +914,12.0,9.0,6.0,2.0,6.0,6.0,2.0,13.0,BFBHEHEHBADCHBAGFHFEBHAAACABHBHAAACECBBACGCHFHAHAHEHEFFD,True +915,10.0,12.0,24.0,13.0,16.0,14.0,13.0,16.0,CEBDBDBDCDCDCDBDAHHBFBFCFGFGEDFHCBCFGECFCEBEBHBCCFCFDFEHAFBHAHAHFCACHCECEHACBCHCFEDEAGACDCHCGAHCDEGGHEEFHAGGGECEGEHDGG,False +916,4.0,4.0,9.0,4.0,6.0,12.0,3.0,4.0,CECDADFBACFCFDFBFGFCFGHCCGBEHEHEHEFFCACBEFFFAD,True +917,15.0,18.0,12.0,11.0,16.0,11.0,18.0,15.0,AEAEAEAEAHAHAGEEFHGHBHBEDABABADHGFGDHBCDDFHGBEFFFAFGGHBDFCBEHECECGFHBHEEGDBEGEBBGDCDHDCACGFGHGCABABHFACCCCBGBGBGDGBE,False +918,14.0,16.0,12.0,30.0,16.0,18.0,12.0,16.0,DHDAEBFADADADADADGDFAFHFHDEFGBGBGBGFHCGEHECEAACACGCDDDFEBEBHBFAFHCDDDDFCFDFGHCFDHEFEFDCHBBBHAEDEDBAAHCEFDCDBDFDBEEDBDHEBDHDGFHDHEGGGCB,False +919,5.0,11.0,3.0,9.0,10.0,8.0,8.0,5.0,BFBHEEEBCBHEHGAGAGDDBDEEEHABFCFBAGDCDGDBDGAFEFEFDBDGGFBFBHE,False +920,5.0,0.0,5.0,4.0,1.0,1.0,4.0,2.0,CGAAFADHDCACGCECGDGDHA,True +921,24.0,17.0,18.0,26.0,23.0,31.0,24.0,25.0,EDEDCDADFGBABAGGFCFDFEGCGBHHECEADGDEDFDFDBEGEFCAGFEFEFDHEADHCHAHFHFHEGEDDDDBGEGEFBCDCEAAHDBAGHDHFGGHEHAHAHAHFHFDFBGBHCGAGFEFEFADACAFEBGCCDBEBADAFBGCFAFCHCHAFEFGCGBGCAFABCDAFBFBHDHFHEGDGHFH,False +922,12.0,3.0,17.0,8.0,6.0,8.0,19.0,16.0,GDFCHCHAADGBHCHAFEHCHCBGBCHFACAFADGGGGGGCGCAADHEHECEAEDDCCEGFGFGAGAHHGHGCDADCCHHGCGFHFHGC,True +923,13.0,7.0,15.0,17.0,15.0,11.0,14.0,5.0,GDDDHCCBCDADAEABADADGHFDCCACAEAGGDEEEDFHFBDGCHBFBFDGGBCDDDFCFCFEEGCFEFADADACAGGGGEGCCAEBEHEGEFECE,False +924,19.0,22.0,14.0,20.0,28.0,12.0,19.0,18.0,CGCDHBFBHGEBEADBDGDGDCBCDCHCEBHGEGEHEGDFFCEAEDGCGEGFDEEEEEBABCBCBCBCBGFDFAEAFDHDHEHFDAAHHHHEAEADAFEFEDBABDHEFEAGCBBFHDHBHBGBADHEEDBDEGBAEAGGCGHBEGGAAAEA,False +925,20.0,23.0,18.0,19.0,19.0,27.0,21.0,22.0,FEHEHEGDGCBDBHBEBCAGACHFEFHAHADAFGBGFFEGECEHDGDAHAHEDCCEAGFDFEGCCBGBFBFHDADCBCBFBCCHBHAHBDCECDFHFGFADCFFFFBFADBGGHADFDBBCBGHHHEHEHBAEAEFGBHBHGAGEFEFGFGFDCDFBFACAGAEADGDB,False +926,8.0,4.0,5.0,5.0,6.0,5.0,4.0,8.0,FGFDECECEADFBFBHEHAHADAHAEACGDADHHHBHFACBEGCG,False +927,4.0,9.0,2.0,4.0,9.0,4.0,11.0,2.0,GHGBGDGBGBEAGFGBBBBDDEBGFGEGEDECEAEAGBFCEHFAE,True +928,19.0,13.0,20.0,26.0,25.0,21.0,11.0,20.0,DDDFAGCFCHADFCCECECFBEHDBEBEDEHEHCFAEAEAEFDFBFADAEAEAEADHDFDFGBGBADEDBHCGCFCBEEAEHECFHAGACCCDDEDHHHHAHDDDACGHBACFCFGDEFEBHFHFCDDDHDACECBDHGHEEFGBGFGFEDHFBA,False +929,31.0,26.0,25.0,22.0,30.0,19.0,16.0,16.0,GADBEEEAEAHACCCCFGFEHBGBGCFCFDDADGBAAAFEFAABEHADFDFACAHBHGEFBAAACFCGABEGFABGFGEGFBFBEBFDEDEHGFEECHAHADADADCHEHEBEDABHBEACADBDBDGDGDCDCACHEHGCEHDCEABCFAEDFDGCEBFBAAEHEDEBCBCBCBCBEEAEBCHC,False +930,5.0,6.0,16.0,9.0,2.0,8.0,6.0,8.0,FCFCBBGDGDBABHCHCGEBEDDGACFCFCFCHCGCABHCCCCHFHCAGFHHCAFDDDDD,True +931,13.0,10.0,13.0,5.0,17.0,8.0,8.0,11.0,AEAEAHAEECBHBHGHAEBFCEEAEBEGCHBFBGEGFACADAEGEDBFCCHHBHBHFHCGEGHDDCDCACAEAFBCGCFEFECEA,False +932,13.0,15.0,7.0,16.0,20.0,10.0,5.0,18.0,AEABBCHEBEHEFEDEAFBHBADFHHDBDEHBABABABACDCFEFHFEGGACEDEHEBBAFGHCEDEDBGCHHDBDBEHCHDADGDEDEDHFEEEAHAHFHFHD,False +933,4.0,6.0,3.0,4.0,2.0,6.0,4.0,5.0,AGAGAHBEEDCGBGBCBDFDFDHHAFBFHFCBHF,False +934,5.0,12.0,3.0,2.0,5.0,4.0,9.0,11.0,CEDBABACFFGFAEAGCGBGHGHBHGHEBBHBHGDFHHHHBEBEAGBBBGH,True +935,8.0,6.0,1.0,11.0,7.0,1.0,14.0,7.0,GEBHGHGDBAEEDAGGEGDGBGBHHHHDDAAAAGDGDGDADABCEGEHEDDFGGB,True +936,12.0,13.0,17.0,16.0,15.0,22.0,16.0,19.0,HHEDDDDGDGAFACACHCFEEECACADBGHGFFFFFFEHEHCAGBDFEFDFEFEHEFFBBABFCHEGFGDHBCBCBEEAHCCECDDBFBHCHFHFHDEDGGGDGBGHCBGAFDGDGCAHBCCHGHFHFAA,False +937,3.0,4.0,1.0,4.0,2.0,0.0,0.0,2.0,ADDEDEHBHBACADBB,True +938,5.0,10.0,7.0,7.0,2.0,7.0,13.0,13.0,FCGGGHHAFEFBFBGBABAEGGGGCFCFHBABHHDHDHFHACDBBGHGDGDHCBDHCHGBGDHC,True +939,0.0,2.0,2.0,0.0,2.0,1.0,2.0,1.0,CGEGEBFBHC,True +940,15.0,12.0,17.0,12.0,18.0,16.0,21.0,10.0,DADACBCEGEGCCAHFCDCDAEACDCFGDAEBEBEACABEGGGABACDFDCGGFDDHCGFGEGBCBDEDGHGFEFBFGGCBCEEFAFGFHFAFHGHGCEFEBHBHGEGEGEFAFAHACBHE,False +941,21.0,9.0,18.0,19.0,23.0,21.0,20.0,26.0,EGEDHBHBHGHGHCEAAGBHBDDDGGGDGFGFEFGFGADHEFEAEAFAHAEAHBFECDCAAGDFAFHEHCCDCEFHFHFAEAHACFCFCHCECEHDDGDHDHDADEBHFEGAAEAFBHCCEGGDEDBCHADAHFBFCFCGGEDECFHGAGHECEHFH,False +942,23.0,23.0,25.0,23.0,16.0,18.0,18.0,24.0,CAHDBDHDEGCADHGHGHGHFCDCHCDFGEDEDHDHBHFDFEEADAEABFFGFGACFBBCFCBBFAHCHCEEDCCFHACACABHBFFFDFECACHHEGDGDEDBHBCBHBHADABHBHBCGHACBCBEBABCGEEFEAEAGGCDDDDAGAGAHBHDGBCFGFDCAGACAB,False +943,9.0,5.0,6.0,3.0,2.0,3.0,4.0,6.0,DBDHCFFHCEAEGBGBGAHCHBBAGFCAHAHACADACA,True +944,1.0,5.0,5.0,2.0,2.0,3.0,5.0,5.0,EGGDGHCBBAEGHGCFCFBHBHBHCFCD,True +945,23.0,12.0,17.0,23.0,21.0,25.0,31.0,23.0,AHAHBHBHCHCEDDFCACDCDFGFBHBCCGFGHGAAHDEEGECFAHAHFHDHEADFGCGCGFGEADBEAEBEDDBCBHAAFAFAFDGDHABAEHDHGEEEHDADGFGHGFEFGFCFAFHFEFADGGEGEGECFDHCHDFGHGDGCAAGAGEGFDBGCEBGBGDEDHFFCFGAGDG,False +946,7.0,6.0,9.0,5.0,3.0,13.0,9.0,7.0,BEBECFHFHAHGCAABCCFGBGFFCFGFBFDFGGAGHGFFFFDBCGHHCHCDDADAEAC,False +947,12.0,14.0,22.0,9.0,8.0,15.0,19.0,16.0,GGGGGADFDBBBCHGACAHBFGHGHGFGCCFDACHGHEFFBCBGEGDGFHHHBHDGDCCCCGBFHACACECDCFGBHBHBCEFECHCBCBCHGFGDAAAADAEEFCFCACFFEHB,False +948,23.0,29.0,24.0,18.0,9.0,25.0,25.0,32.0,BBBHGFAEAEBEBCFCFAFAFCFDFBHBGCHFAEGDACAGBHCHFDBCBGGCCBBHHABDCFGHBDCDBDGFBCAFAHHGHFHEHACEGDABGBGHABABGHHHFBFCFHFABAEAGACBCFHHBABCBCBCACFCHGHCHBGBHDDFGAAFFFEDDDGDHDHGHGHGHDHGHGHDCDCGFGFEA,False +949,7.0,6.0,5.0,7.0,7.0,6.0,6.0,12.0,HHCHADDCGBGFFHDHBBCHCHBFADAEAGAFAEAHBHEEEEHHHBGDGEGCDFDF,False +950,24.0,23.0,22.0,11.0,20.0,30.0,30.0,14.0,EHFBFBFBCCFCAAACEGBFAEEBHCHFHEAEAGBGHGHGCGCFEFAFBEAGAEBGDGCGHGHBBGBGBFBFDFECAGGFEBEGCAEBEDGHAFBHBFBDGDGFGDACCGCECACAGFCECHDFBCGCGFFFGFGCBCGABADFBHGGFGDHDEFBHCAAAAAAFFFFFDEEAE,False +951,16.0,19.0,15.0,15.0,20.0,28.0,15.0,17.0,DGGFECEHGHFHCBCEHGDGCBCGCEEFAFAFAHEHFAABHEGDGAGBGEEBHDHBBCBCHFBDBDBHEDFCAEAFFFDFDFAGBCBDECFFFEFDFBFGFGEECECEFEFEDHGCDAHAEABBDGFBFHHBHDAFHFCFAFABA,False +952,9.0,0.0,6.0,3.0,8.0,5.0,2.0,3.0,EFACCCFAAAAHFFFDGAAEAEHGHECECEDECEAD,True +953,2.0,1.0,1.0,1.0,6.0,2.0,3.0,1.0,ECEHDAAGBGEEEEFGF,True +954,11.0,9.0,7.0,13.0,13.0,4.0,8.0,8.0,CADHDHDFDABBEACAFDBBHFHGAGECBGEGEGEBEHEDEAHBGDADADADFDEBEDDCAABHEHCGEGECC,False +955,17.0,19.0,17.0,18.0,12.0,19.0,16.0,32.0,GFGFAAGFGAHADGGHGEBABFEDBHBDFHHHHBGBHDHDEAACBFBFBEAEHCDDGDFHHEDGHGBGBGADHFHDHCCGAEACDCDCAHAHFHFHFHDBDADHCCCHBACACBHFHFEFECACGEBBFDHCHDHBHEFGCECHFFBHBH,False +956,21.0,23.0,17.0,24.0,20.0,16.0,15.0,22.0,DADEHFHDCBCBCAHGBGFDFDGBAFDFDHHFDBDBACACFEHEAEAHAEEBAGCHCFCFAHAGDGDADADHHGHGECCFCFGFCHAHGDGBCCHADBDEAHGCFBHBHBHEEEEEHEBEAEGDBBFBHHCDCEBBBDBDBAADGFABADFEEGEDDB,False +957,10.0,10.0,8.0,10.0,12.0,10.0,10.0,2.0,FGFBFDFCGGFGABBBDGAAAFHFDGDBDGDEDECECECECGBAEHECGDACEBGBDFCAEAFFEDEBABAE,False +958,23.0,37.0,29.0,27.0,20.0,20.0,23.0,19.0,ADBDBAFABHBADGGCCCHFHGBBDDCACACBBAGDHDHCHFECBHFEGEBEDCCFEDEFBFBCBCBHEHBGDCDGBGAGAFFGCGEGAADACADBGFEDGBGFDBHBCAHEEFFDCDADBDBACDCDCDBHBHFEFHFDBGBGEFHFHBACECEDEBCBCBCGCGBBACAGEFBFBABGDGDHEHEGBCDCBHEAAA,False +959,12.0,18.0,18.0,8.0,12.0,10.0,17.0,15.0,BEBEBGBGBHBCBCECGCGCDCFGGHGBCHEACCCEFGAAAEHBHEHBGBHAEABHGFCFCDCEABACAHEHCGCHFEAEGDBDHDCGFDCDAHBHGFDFGGGHFBBBAF,False +960,6.0,8.0,14.0,11.0,10.0,8.0,6.0,15.0,EADADHGFDEEHFHDHBHBHCECDFDBDECHFFAFGFBEDECBCECHHHHGCGDGDHCCCCCCEEDHHAHABCGFABB,False +961,20.0,29.0,25.0,20.0,25.0,26.0,26.0,18.0,BHBEFEABGFAEGDGDFFBDHDGBGBFFFHEEEEEDFAFADABGGCGCBCBAFCFABCCHEHGDDEDEGFFAAEEEEAGCGAGHGFDCCBCHGACACEDHGHGAFBFBFAHEBEBEDGBHCCEAEADDDHDCBCFHAHCHBHBFBFBGGGBHECGFGECBCBCDHDBBFDCACACBFGFGEGCDEBFBF,False +962,27.0,19.0,27.0,18.0,20.0,32.0,29.0,28.0,GEGECAFAHHHHEAEBDBDCHHGHFEFHDBFAFBFDGDBCBCGHGHFCFCFCFDEGADHHCCADADAGEHEHGACCHGHBHEHCHCHFECGCFAFBFAFGFBCAEFCDHAGFBFHGEGAAHGFGEDEACDCFHDDCDCFCHCGCEDGHBDAAFAGBFBFHEGAFACADEFEBEGGGCGCBBFBFGAGAGAFABAGFBEHF,False +963,18.0,20.0,27.0,19.0,14.0,17.0,15.0,25.0,FFACCGCGCDDHCHCDGGGEHFBCBHFCAAAAHAGFGDGAGDGHFBDEDHCBCACACGCGAFEBBCECEAEHEHBBCHHHHAACDCDBDFCFBFBHCHBHDGCEEEHEDGBBBFEFHFHDCDBDADAHFBCBABDCEAHHDACFCGHBHFHDCFE,False +964,12.0,10.0,8.0,9.0,12.0,10.0,10.0,9.0,FGFAEAEAGADFEECEHBBBAHAEBECECAGGHBAAGEHFHDHAEFDFECDCBFBFBABDDFDGGFGCCCEHAHBHGDGD,False +965,17.0,22.0,24.0,31.0,26.0,22.0,22.0,27.0,CGCEHFCFCEBDBDBEHEHGHGHFABABHEHFBEBGHDHDFCBDBEBGGCHCFDFHEHDHDGDFFBCAHAHGEEFHBHBEBADFFAFAHDHGAGAHEDDHDEBEFEBEFHFHACADDDFDEEEECCCDAGADBGAGFEHBGGHDCCCDEDGHCECDDABFBEBCGEGCGCFCDCAAEDCBGHGDFDGDCDF,False +966,27.0,18.0,26.0,14.0,26.0,27.0,37.0,24.0,AACDCHCFGHAHAGAGACFHEHABFHFAGHBCBDBFBFBABFHHHFHFCEDEFACHCECFGFEFECGDGHGCGFGEHECDCBCBGBECEDFAEECAGGFAFBHEFDGBGEGHFEEGEHCGEGDGDGDFCCCCHBAEACHGHGAGHGAGEHEGEGBCAGGGFABHDADADAGAFHBEDCFAEECFGFGFGCGABEFGABA,False +967,19.0,30.0,23.0,20.0,26.0,19.0,25.0,21.0,BBABCBGGAGFDFGHDHEGBGCGBBAFDCBCEFHDCDFBCBGEFBHBEEEEEBADAHAHBGGGEDBFBHCCCECBGHDHDFGBDCDFBEHECGBGBGFCFAHEHDGEGEFDFDECCCHCHEGEGHGBCEAGABEBABABABADADABAEADCCEFBABFECDFHFHCHFEFCGGEHEHGDADH,False +968,22.0,15.0,29.0,26.0,37.0,20.0,22.0,24.0,AEGBABEFGGEGDHDHAHEFECEFACEEACHBECFBABCDCACAHGHDEEFECECDAAAEHGHGHDHDFGFHCADFDBDEDEAEDEDEDEDGGECEABBGFADADEHGHFECBCAEAEGECECAGDBEGAACCCCCCBHEGECDCDFHFHFHFHFCGEGHBDFEBBBGECHDEFEHHGDADCGHGDDCEFHFCFC,False +969,16.0,6.0,14.0,15.0,9.0,8.0,13.0,13.0,HHHHFEFDDCAHGGEGDGDCBBHCCDADGGHAAADADFDFDGDGDGABEBAFABECDHAAFAFEFGDGCHEHCDCGCEEHHHAEACCCCBCGAA,False +970,21.0,25.0,9.0,17.0,8.0,13.0,18.0,16.0,GBGHGACACAFHFBCADGGGFGFGAGAGBBDBGCHHEHEBFDEABGDGDGBHBCDFFFFHFHAHBDACAHDHCCGAEADBHBDFABABABEBEAECGGBHBHDFBBBBAFDDAGBHHABDDADADBE,False +971,9.0,10.0,11.0,9.0,15.0,9.0,14.0,12.0,EAEDFCFBFBAGHGHGDGBHBGFHEHCFAFAGHECGCHCADAHCEGDGCGBBBBDBDEGFGCCFHEEEHEDEAEDBCGHGCADHEFEAE,False +972,18.0,16.0,12.0,13.0,15.0,19.0,12.0,21.0,BEHFBBABAHGEEAEAFAFCDEHFHAHCGCFBEAAFGCABHHFHFHCHBGADCDHDHCHCEEAGBFDFGADFFFFBFBGDGAGAEADHDHDAEEEBCBCBHBDEEHGFGFBFBDEHCHGHAHFCAD,False +973,27.0,25.0,26.0,28.0,24.0,17.0,20.0,27.0,HCHEFEACGCFDFGCBCHADFCFBADCGHBHCDDDCBAAHAEEDADGDGHGHGHGDAAEBEHAHGDADADEBEHHCEBADAHHHHCHCAAAHBFBDCGBFCHEEFBFBFHAEADDBFBFBDGDEHEHBHGCGAHACECAFBFBEEEBECEFDCCABDBDEDEGAGADEDEDCFBBACHGGFGBGCGDADCHCBC,False +974,2.0,9.0,5.0,14.0,10.0,16.0,13.0,8.0,HBEGFBDBDHEEFHFEGDBFBFBGHFAFDFGFCFDBDBDHDHBGGCFFEGEGECADGFECEHFGDCDHDEDGFGFGD,True +975,7.0,10.0,11.0,8.0,6.0,8.0,11.0,11.0,CECFCDCHGGGGHGAFCECEAECDCGHHBADHDHDBDBFBFDAHGBBBBBBGCFFFAAEHDFCHGAGHCHGE,False +976,22.0,16.0,20.0,24.0,18.0,27.0,21.0,14.0,GDBDHEGEBFHFHDDCFCDAAGEFBFEDBAHGBGBGDFEBBADGHGFABAFAFDCDCBCAHADDDCAHECCDAAFAFGHCCECFGECECEFDHCHAHGBGBGDECECECEAEAEBFBFGHGHAADDFDBDGAFCFBHACAEEFGFAFDFDFGFGDCDGGFFF,False +977,16.0,17.0,23.0,22.0,27.0,15.0,19.0,22.0,EEGGFDFHCHEEAEDEHEHGCEFGBEBEBHBDDCBAHAHDGDAEGEGDHFECBDDDHDCGCFAAAAAFCEHBBEECEFDFDBDBCCCCEFEGAFFCFCFCEBEAHAHAHAGGHGHCHCBGEDBDGEEHCDGHBCBDAHFHBHFGGDHDEDAGECECBCDCG,False +978,5.0,8.0,11.0,18.0,14.0,13.0,11.0,18.0,HFHDBAGHGEFEHCGGEGDAAFHFEFEFDHDGCECHHEHEDEDHGHDFBFCDHHHAHEHBCBCBCDCDGDECEDGDEBFGDCDEBGHFBFDCDFHFDA,False +979,22.0,10.0,19.0,14.0,19.0,26.0,19.0,18.0,HBGDGHGCGBGEFEAEFBDEHEAAHGGGGHDHDHFGEABAFAHEHCACFFDFDFAFECGCDCDCDCFCHCFCHAHFDCBGAGDEHBGEAFAHAHEFAGHEAGACEEEFFFFEFHFBFCFBACGCAFAFCBEFEGEFCGBDDDCAAAH,False +980,9.0,10.0,16.0,13.0,13.0,13.0,17.0,6.0,CDCEBDGFGFACEBDHFCEHACADBDBHBCBGACCECEFEFGFGACHCACDEEGGGEGEGDGCFFFGFDBDFGGAGAHACDDDDGEGFCFCEHBBEB,False +981,19.0,23.0,15.0,12.0,16.0,18.0,17.0,17.0,ECEDHFHFHFAGAHBHDAEFGFBEHGBGBCBHBCEDGDCBHEAGADEGHFHDBBABEBAGAGCCDADHDCGBBBEGAGAGEBBBGFGFCCBFBFEGHAEGHFCFCFCACEDHDAAAAAHDBFFHFEFCBCBEBEFHA,False +982,21.0,16.0,13.0,14.0,20.0,12.0,19.0,12.0,EBEBGBGDGEGECHCHFAAEHBCAEBHBECECACGCDCDCDBABAFABGHGHAAEAHABDEDEFHFGBCDAEAGFGECDHGFGDDDEHAGGGEGBCFDFAFBEGECEHAFDFGABADAGAEBHFAEB,False +983,22.0,16.0,20.0,28.0,16.0,18.0,28.0,14.0,CGCGBDCDCGHACGFDFDGDBDCFEFEFADAECBDDDEAEAEAHAHABGDFAAGFGFGCAAGEDEGFDFDCGBGAGBGHHHGABCBDBDFDFCFDFGCAHAGACABAFEFAGEEDEHBCCHEGBBBDBDHGEDCHCEFAHHGCDHGGFGDGDGDBEGACDCD,False +984,26.0,22.0,19.0,22.0,24.0,27.0,32.0,24.0,ADHHEFAFADABADAFABCGCGAGFGFEDADABEFHFHGHDFGEGADCCFHHHGHGEFCFCEBDGEFEFEGAFBFBFAHGBEBEAGDFAHABAEGHGCECEHBHBDCFFHBAAGAEAGBCCDCDHDHDBDBGBEDDDCBBFBGEDFDHGEGEGEAFAGGBGBHEGBGFGDECHFAFEHHFCGCGEGCCHCHAAFDG,False +985,7.0,9.0,7.0,9.0,13.0,11.0,7.0,5.0,FCBCHEDFAFHEGBGFAEAEAEAFGDGDBDBABAFGEGDCHCHEEBFCEEHEBEDEFFDFGBDBCCFD,False +986,8.0,13.0,17.0,13.0,13.0,11.0,14.0,10.0,HGEDFDFDFDHDHDHDBFEFAGAEBEDGDHHFBBEEABBBFBHGHCCBCEEGECFBACDCDAAGCFCGBGFFEAGDGHCCDGEGCGCGCHCECBCACEB,False +987,20.0,12.0,18.0,25.0,18.0,18.0,21.0,30.0,AAADFHFAADFECBCECEHEHADCDGDGDCFHFHGCGCGFGFCFHDCAHEEGDGCECHCHEBFBHGHGEFHBHFGDADEDHDAFADEHBBBEGEFHADFDBCGDHHGHGHGDGDHDGDFCFEGGFGCAAEAEBHAHADBHEAADHDCECHDADHCHBHFHAB,False +988,20.0,13.0,12.0,16.0,10.0,14.0,25.0,12.0,BBBCHGHGAGFGHGDCACHCHCAAAAAAEHBDBAFDGDGDFCGGEBAFDEDEHEDGDEDADABCBFDGAGAGHGAEDBGGGGDGBFBHAAGBGHDFEFGAEECCGFFBFGFGHCHAFFCACD,False +989,12.0,14.0,12.0,10.0,10.0,5.0,11.0,8.0,AEFEBABAHACGFBABGBGDEDGDEBBCBCHCECBCACDCGHGHGEACFCBBBEFGDDDCDBDADGEHAACHEGAGFBEHAH,False +990,22.0,22.0,18.0,21.0,13.0,23.0,11.0,18.0,AHAHEFFDDCDFGHDFDECHDHABEBCBCEAFBGGGGFCHCBCHHBEDFAFABCHCBCBCBABDDGHHDBFGEEDADFECGBAECEADADADAFFDFBFBFBFAHDFDBHBDEAEFHFGAHAHAHACCBBABGCGCFHFAFDFDEBCA,False +991,10.0,6.0,7.0,9.0,6.0,4.0,5.0,5.0,FDCBCGFHFHBBBABGDFDAGACACEEECAHDDGDEAAADADAECECHDBGH,False +992,9.0,13.0,4.0,15.0,7.0,15.0,17.0,13.0,DEAHFHGHBEGEBBGFFFAFDFDHDGDGHGHFHFDDDCEGBACGDBDGDEHEHGHGBGBGHFBABABFFFAGADHDGGGHFACBFEDDBCAFB,False +993,1.0,1.0,4.0,3.0,4.0,6.0,1.0,3.0,EFEFEFAFCEGDFHHHDFCBCDC,True +994,16.0,14.0,21.0,15.0,11.0,19.0,16.0,24.0,AHACCCDCAAFBFEFBDBAAGAHHCHDHEHAHEHEBGAGAFHFCGCEFEFEDACHCHCGGGFDFCHCDDDHDHAECHGBGBEHCFBDBGGFHFGBAFHFCDADCFCBCBCEHAHFHBCEGGGFAHBHDCDFHFGDB,False +995,7.0,6.0,13.0,6.0,12.0,13.0,4.0,9.0,CEAFHCHFHECCHEACFCFGGAGFCHCHFAFEDHHCECFBDBDGECHDFEEEEEEBABACFCFDFDFBAB,True +996,4.0,9.0,13.0,8.0,5.0,3.0,3.0,5.0,AGAEADDCACBCBCDCDEHECCFHEDBCBCDDDFEBHBHCCCBBFHGCGB,True +997,3.0,1.0,1.0,6.0,4.0,5.0,7.0,3.0,DDDFHEHCGFGFGFGEDAGAEHFDEDBGAG,True +998,18.0,17.0,15.0,15.0,11.0,15.0,12.0,20.0,EBCFCHHAACHCHCHGBCBCBCHDADAFAFEFDFDGHGHCBCFFHCACDFAFAHAEAEAEFEBCHAFBHBFGAEDBDHDHFBCDEAGABBHGADDBDBDHHHEBAGCEEHFHBGGDGFGAGDB,False +999,6.0,13.0,8.0,13.0,6.0,19.0,12.0,12.0,GDGCGCHCAFGFEFBFDEDHFBFBDBGFDADBFBACGBGDGEFBHHHHBDAFGFGBGHCFFECEFEFBAHFDFBFDAHCHDHCHDFDGB,False diff --git a/tests/results/nb_gm_002_2back_240trials.csv b/tests/results/nb_gm_002_2back_240trials.csv new file mode 100644 index 0000000..1c50201 --- /dev/null +++ b/tests/results/nb_gm_002_2back_240trials.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,ralph_skewed +0,30.0,39.0,31.0,30.0,32.0,24.0,27.0,27.0,False +1,33.0,23.0,27.0,32.0,37.0,34.0,25.0,29.0,False +2,31.0,20.0,37.0,28.0,31.0,32.0,26.0,35.0,False +3,27.0,32.0,39.0,24.0,25.0,34.0,35.0,24.0,False +4,34.0,24.0,38.0,28.0,31.0,29.0,28.0,28.0,False +5,29.0,24.0,36.0,31.0,32.0,32.0,31.0,25.0,False +6,25.0,38.0,28.0,30.0,33.0,30.0,26.0,30.0,False +7,27.0,30.0,30.0,29.0,32.0,26.0,33.0,33.0,False +8,24.0,36.0,32.0,23.0,30.0,29.0,35.0,31.0,False +9,35.0,34.0,30.0,29.0,35.0,26.0,23.0,28.0,False +10,30.0,25.0,33.0,31.0,27.0,37.0,30.0,27.0,False +11,28.0,28.0,29.0,26.0,28.0,27.0,34.0,40.0,False +12,35.0,27.0,30.0,29.0,26.0,30.0,36.0,27.0,False +13,38.0,27.0,31.0,27.0,34.0,23.0,27.0,33.0,False +14,29.0,30.0,28.0,35.0,19.0,30.0,37.0,32.0,False 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100644 --- a/README.md +++ b/README.md @@ -1,36 +1,10 @@ -# N-Back Sequence Generator with [Hidden] Markov Chain +# N-Back Sequence Generators -**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/src/main/scala/org/xcit/nback/markov/models/State.scala b/src/main/scala/org/xcit/nback/markov/models/State.scala deleted file mode 100644 index fbbd844..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/State.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * A Single state with a label in Markov chain - * @param label A simple string label, representing the state and node - */ -class State(val label: String) { - - /** - * Keep track of transitions from this state to other states. - */ - val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() -} diff --git a/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/src/main/scala/org/xcit/nback/markov/models/Transition.scala deleted file mode 100644 index bc20a9e..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/Transition.scala +++ /dev/null @@ -1,8 +0,0 @@ -package org.xcit.nback.markov.models - -/** - * A Single transition in Markov chain graph. It is stored in "from" node. - * @param to the ending node of the edge - * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). - */ -case class Transition(to: State, probability: Double = 0.0) diff --git a/src/test/scala/ThreeBackBenchmark.scala b/src/test/scala/ThreeBackBenchmark.scala deleted file mode 100644 index 0c7dad9..0000000 --- a/src/test/scala/ThreeBackBenchmark.scala +++ /dev/null @@ -1,7 +0,0 @@ - -/** - * TODO Benchmark 3-back simple sequence generator - */ -class ThreeBackBenchmark { - -} diff --git a/tests/benchmark_diagrams.py b/tests/benchmark_diagrams.py new file mode 100644 index 0000000..8fa448e --- /dev/null +++ b/tests/benchmark_diagrams.py @@ -0,0 +1,159 @@ +import pandas as pd +import numpy as np +from matplotlib import pyplot as plt + +import benchmarks.common as common + + +def tlratio(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2,ignore_index=True) + stats = [] + for trials in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == trials) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == trials) + targets2 = data[alg2].targets if alg2.shape[0] > 0 else np.nan + targets4 = data[alg4].targets if alg4.shape[0] > 0 else np.nan + lures2 = data[alg2].lures if alg2.shape[0] > 0 else np.nan + lures4 = data[alg4].lures if alg4.shape[0] > 0 else np.nan + stats.append([trials, (targets2/lures2).mean(), (targets4/lures4).mean()]) + stats = pd.DataFrame(stats, columns=['trials', 'tl2', 'tl4']) #.dropna(subset=['skewness']) + + plt.style.use('ggplot') + + plt.ylim(bottom=0, top=30) + plt.scatter(stats.trials, stats.tl2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl2[idx], 1)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.tl4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl4[idx], 2)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('T:L Ratio') + plt.ylabel('T:L Ratio') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_tlratio.png', bbox_inches='tight') + plt.show() + + +def time_per_trial(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for t in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == t) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == t) + time2 = data[alg2].time.mean() * 1000 if alg2.shape[0] > 0 else np.nan + time4 = data[alg4].time.mean() * 1000 if alg4.shape[0] > 0 else np.nan + stats.append([t, time2, time4]) + stats = pd.DataFrame(stats, columns=['trials', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.trials, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time2[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time4[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2v4_time_trials.png', bbox_inches='tight') + plt.show() + +def time_profiles(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 8): + alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + time2 = data[alg2].time.mean() * 1000 + time4 = data[alg4].time.mean() * 1000 + stats.append([ni, time2, time4]) + stats = pd.DataFrame(stats, columns=['n', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.n, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.time2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + plt.scatter(stats.n, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.time4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_time_n.png', bbox_inches='tight') + plt.show() + +def skewness(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 9): + all_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + skewed_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) & data.skewed + all_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + skewed_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) & data.skewed + num_of_sequences2 = data[all_alg2].shape[0] + skewed_sequences2 = data[skewed_alg2].shape[0] + num_of_sequences4 = data[all_alg4].shape[0] + skewed_sequences4 = data[skewed_alg4].shape[0] + skewness2 = skewed_sequences2 * 100.0 / num_of_sequences2 if (num_of_sequences2>0) else 0 + skewness4 = skewed_sequences4 * 100.0 / num_of_sequences4 if (num_of_sequences4>0) else 0 + stats.append([ni, skewness2, skewness4]) + stats = pd.DataFrame(stats, columns=['n', 'skewness2', 'skewness4']) #.dropna(subset=['skewness']) + + + plt.style.use('ggplot') + plt.scatter(stats.n, stats.skewness2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.skewness2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + + plt.scatter(stats.n, stats.skewness4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.skewness4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Skewness') + plt.ylabel('Skewed Blocks (%)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_skewness.png', bbox_inches='tight') + plt.show() + +if __name__ == "__main__": + tlratio() + skewness() + time_profiles() + time_per_trial() diff --git a/tests/benchmark_skewness.py b/tests/benchmark_skewness.py new file mode 100644 index 0000000..f468b4d --- /dev/null +++ b/tests/benchmark_skewness.py @@ -0,0 +1,97 @@ +import random +import heapq +import csv + +# Common parameters +alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'] +trials_range = (10, 40) +n = 3 +sample_size = 100 + + +def to_benchmark_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [str(ralph_skewed)] + +def benchmark_nb_gm_001(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_001') + + +def benchmark_nb_gm_002(filename): + import generators.nb_gm_002 as nb_gm_002 + + generator = nb_gm_002.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + # print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_002') + + +def benchmark_nb_gm_003(filename): + import generators.nb_gm_003 as nb_gm_003 + + generator = nb_gm_003.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + print(f"sequence {i}/{sample_size}: {trials} trials") + seq = generator.generate(trials) + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_003') + + +def show_skweness_diagram(filename, choices, title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + print(filename) + data = pd.read_csv(filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) #.dropna(subset=['skewness']) + #print(stats.trials) + #plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'{title}.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + benchmark_nb_gm_003('../benchmarks/nb_gm_003_2back.csv') diff --git a/tests/common.py b/tests/common.py new file mode 100644 index 0000000..e40c0df --- /dev/null +++ b/tests/common.py @@ -0,0 +1,27 @@ + + +# Common benchmark parameters +choices = alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F'] +trials_range = (10, 65) +n = 4 +sample_size = 100 + + +def count_targets_and_lures(seq, n): + mask = 'D'*n + for index in range(n, len(seq)): + if seq[index] == seq[index - n]: + mask += 'T' + elif seq[index] in seq[index - n - 1:index - n + 1]: + mask += 'L' + else: + mask += 'D' + return mask.count('T'), mask.count('L') + + +def skewness(seq, choices): + import heapq + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return ralph_skewed diff --git a/tests/nb_gm_001_bm.py b/tests/nb_gm_001_bm.py new file mode 100644 index 0000000..54f6cb3 --- /dev/null +++ b/tests/nb_gm_001_bm.py @@ -0,0 +1,75 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq) , str(ralph_skewed)] + + +def benchmark(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets / s.trials, axis=1) + plt.scatter(data.trials, data.targets_ratio, alpha=0.2) + plt.show() + +if __name__ == '__main__': + alg = 'nb_gm_001' + fn = f'results/{alg}_{n}back.csv' + benchmark(fn) + # skewness_diagram(fn, alg) + targets_ratio_diagram(fn, alg) diff --git a/tests/nb_gm_002_bm.py b/tests/nb_gm_002_bm.py new file mode 100644 index 0000000..c8af543 --- /dev/null +++ b/tests/nb_gm_002_bm.py @@ -0,0 +1,105 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq), str(ralph_skewed)] + + +def benchmark(filename): + from generators.nb_gm_002 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials, int(trials/3), 0, 0) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +import time +import numpy as np +import pandas as pd + +import benchmarks.common as common + +def profile(): + from generators.nb_gm_002 import SequenceGenerator + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, int(lures/2), int(lures/2)) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('benchmarks/results/nb_gm_002_profile.csv', sep=',', encoding='utf-8') + +if __name__ == '__main__': + alg = 'nb_gm_002' + fn = f'results/{alg}_{n}back.csv' + profile() diff --git a/tests/nb_gm_003_bm.py b/tests/nb_gm_003_bm.py new file mode 100644 index 0000000..fa6c19a --- /dev/null +++ b/tests/nb_gm_003_bm.py @@ -0,0 +1,114 @@ +import heapq +import csv +import random +import time + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq, time_per_block): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [time_per_block, ''.join(seq), str(ralph_skewed)] + + +def benchmark_skewness(filename): + from generators.nb_gm_003 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['time_per_block', 'seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + targets = trials / 3 + t = time.time() + seq = generator.generate(trials, targets) + t = time.time() - t + print(f"sequence {i}/{sample_size}: {trials} trials, took {t}s.") + writer.writerow(to_csv_row(i, seq, t)) + plot_skewness(fn, 'nb_gm_003') + + +def plot_skewness(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def plot_targets_ratio(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +def benchmark_targets_ratio(): + pass + +def benchmark_chunking(): + pass + + +def benchmark_n(): + pass + + +def plot_timing(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['time_per_trial'] = data.apply(lambda s: s.time_per_block / s.trials, axis=1) + plt.style.use('ggplot') + plt.title(f"{figure_title} - average time to generate a trial") + plt.ylabel('time (s)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.time_per_trial, alpha=0.5) + + # draw fitted curve + # import numpy as np + # p = np.poly1d(np.polyfit(data.trials, data.time_per_trial, 3)) + # plt.plot(data.trials, p(data.trials), color='red') + + plt.savefig(f'results/{figure_title}_timing.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + alg = 'nb_gm_003' + fn = f'results/{alg}_{n}back.csv' + benchmark_skewness(fn) diff --git a/tests/nb_gm_004_bm.py b/tests/nb_gm_004_bm.py new file mode 100644 index 0000000..b4ad4a8 --- /dev/null +++ b/tests/nb_gm_004_bm.py @@ -0,0 +1,26 @@ +import time +import numpy as np +import pandas as pd + +import tests.common as common +from generators.nb_gm_004 import SequenceGenerator + +def run(): + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, lures) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('tests/results/nb_gm_004_profile.csv', sep=',', encoding='utf-8') diff --git a/tests/results/2v4_time_trials.png b/tests/results/2v4_time_trials.png new file mode 100644 index 0000000..9be91b4 --- /dev/null +++ b/tests/results/2v4_time_trials.png Binary files differ diff --git a/tests/results/2vs4_skewness.png b/tests/results/2vs4_skewness.png new file mode 100644 index 0000000..a488e1f --- /dev/null +++ b/tests/results/2vs4_skewness.png Binary files differ diff --git a/tests/results/2vs4_time_n.png b/tests/results/2vs4_time_n.png new file mode 100644 index 0000000..d022ed0 --- /dev/null +++ b/tests/results/2vs4_time_n.png Binary files differ diff --git a/tests/results/2vs4_tlratio.png b/tests/results/2vs4_tlratio.png new file mode 100644 index 0000000..b76f296 --- /dev/null +++ b/tests/results/2vs4_tlratio.png Binary files differ diff --git a/tests/results/nb_gm_001_2back.csv b/tests/results/nb_gm_001_2back.csv new file mode 100644 index 0000000..f6ad25e --- /dev/null +++ b/tests/results/nb_gm_001_2back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,0.0,1.0,0.0,55.0,56.0,0.0,0.0,0.0,BEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True 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+364,0.0,0.0,0.0,1.0,0.0,31.0,0.0,31.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +365,0.0,0.0,0.0,24.0,0.0,23.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +366,0.0,15.0,0.0,0.0,16.0,0.0,0.0,0.0,EEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +367,22.0,0.0,0.0,0.0,0.0,0.0,1.0,22.0,GHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +368,0.0,25.0,0.0,0.0,0.0,0.0,25.0,0.0,BGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +369,0.0,0.0,0.0,100.0,1.0,0.0,0.0,0.0,EDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +370,0.0,17.0,0.0,17.0,1.0,0.0,0.0,0.0,EBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +371,0.0,1.0,49.0,0.0,49.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True 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+377,27.0,0.0,0.0,29.0,0.0,0.0,0.0,0.0,DDADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +378,81.0,0.0,0.0,81.0,0.0,0.0,0.0,1.0,HADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +379,1.0,0.0,9.0,0.0,8.0,0.0,0.0,0.0,ACECECECECECECECEC,True +380,1.0,0.0,0.0,32.0,33.0,0.0,0.0,0.0,AEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +381,5.0,0.0,5.0,0.0,1.0,0.0,0.0,0.0,ECACACACACA,True +382,0.0,0.0,0.0,96.0,0.0,0.0,98.0,0.0,GGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +383,0.0,86.0,0.0,0.0,0.0,85.0,0.0,0.0,BBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +384,0.0,0.0,28.0,0.0,1.0,0.0,0.0,28.0,ECHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +385,0.0,1.0,119.0,0.0,0.0,0.0,0.0,0.0,BCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +386,0.0,0.0,93.0,0.0,0.0,93.0,1.0,0.0,GCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCF,True +387,92.0,0.0,1.0,0.0,92.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +388,0.0,186.0,0.0,0.0,0.0,0.0,0.0,0.0,BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +389,1.0,74.0,0.0,0.0,0.0,0.0,0.0,0.0,ABBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +390,0.0,0.0,0.0,0.0,1.0,86.0,0.0,87.0,EHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +391,61.0,0.0,0.0,61.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +392,0.0,0.0,0.0,1.0,16.0,0.0,0.0,15.0,DEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +393,118.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +394,0.0,0.0,0.0,0.0,0.0,75.0,0.0,1.0,HFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +395,30.0,0.0,0.0,0.0,0.0,0.0,0.0,30.0,AHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +396,65.0,0.0,0.0,0.0,0.0,1.0,0.0,65.0,FAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +397,0.0,0.0,0.0,55.0,56.0,0.0,0.0,0.0,EEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +398,26.0,0.0,0.0,25.0,1.0,0.0,0.0,0.0,EADADADADADADADADADADADADADADADADADADADADADADADADADA,True +399,0.0,0.0,60.0,0.0,0.0,0.0,1.0,59.0,GCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +400,1.0,0.0,0.0,0.0,160.0,0.0,0.0,0.0,AEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +401,1.0,0.0,31.0,0.0,0.0,31.0,0.0,0.0,AFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +402,0.0,0.0,0.0,15.0,1.0,0.0,0.0,0.0,EDDDDDDDDDDDDDDD,True +403,0.0,0.0,0.0,54.0,55.0,0.0,0.0,1.0,HEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +404,0.0,0.0,0.0,27.0,0.0,27.0,0.0,1.0,HFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +405,0.0,0.0,0.0,1.0,0.0,15.0,0.0,15.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +406,0.0,95.0,0.0,94.0,0.0,1.0,0.0,0.0,FBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +407,0.0,0.0,15.0,14.0,0.0,0.0,0.0,0.0,CCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +408,78.0,78.0,0.0,0.0,0.0,0.0,1.0,0.0,GBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +409,0.0,0.0,72.0,1.0,0.0,0.0,72.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +410,55.0,0.0,1.0,0.0,0.0,0.0,55.0,0.0,CAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +411,0.0,59.0,0.0,0.0,0.0,60.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +412,61.0,0.0,0.0,61.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +413,0.0,1.0,0.0,75.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +414,0.0,53.0,0.0,0.0,0.0,0.0,52.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +415,0.0,0.0,16.0,0.0,1.0,0.0,0.0,15.0,ECHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +416,0.0,0.0,0.0,39.0,0.0,0.0,0.0,38.0,DHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +417,96.0,0.0,1.0,95.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +418,28.0,0.0,1.0,27.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +419,0.0,1.0,92.0,92.0,0.0,0.0,0.0,0.0,BCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +420,1.0,0.0,20.0,0.0,20.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECE,True +421,0.0,90.0,0.0,0.0,0.0,0.0,89.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +422,10.0,0.0,0.0,0.0,0.0,1.0,11.0,0.0,FGAGAGAGAGAGAGAGAGAGAG,True +423,0.0,0.0,0.0,74.0,73.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +424,0.0,0.0,127.0,0.0,0.0,0.0,1.0,0.0,GCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +425,1.0,9.0,0.0,0.0,0.0,9.0,0.0,0.0,AFBFBFBFBFBFBFBFBFB,True +426,0.0,0.0,84.0,0.0,0.0,0.0,0.0,84.0,HCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +427,33.0,0.0,0.0,34.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +428,1.0,30.0,0.0,30.0,0.0,0.0,0.0,0.0,ABDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +429,0.0,0.0,67.0,0.0,1.0,67.0,0.0,0.0,EFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +430,62.0,0.0,0.0,63.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +431,1.0,9.0,9.0,0.0,0.0,0.0,0.0,0.0,ABCBCBCBCBCBCBCBCBC,True +432,15.0,0.0,0.0,0.0,0.0,0.0,14.0,0.0,AAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +433,0.0,1.0,0.0,65.0,66.0,0.0,0.0,0.0,BEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +434,0.0,160.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +435,0.0,0.0,1.0,0.0,42.0,42.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +436,0.0,0.0,55.0,0.0,55.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +437,0.0,0.0,0.0,1.0,0.0,73.0,0.0,73.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +438,79.0,0.0,0.0,0.0,78.0,0.0,0.0,0.0,AAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +439,0.0,0.0,67.0,0.0,0.0,0.0,66.0,1.0,HCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +440,0.0,0.0,77.0,0.0,0.0,1.0,0.0,76.0,FCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +441,0.0,0.0,0.0,0.0,153.0,0.0,0.0,1.0,HEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +442,0.0,88.0,88.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +443,0.0,0.0,0.0,20.0,22.0,0.0,0.0,0.0,EEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +444,41.0,0.0,42.0,0.0,0.0,0.0,1.0,0.0,GCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +445,0.0,0.0,0.0,47.0,0.0,46.0,0.0,1.0,HDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +446,1.0,0.0,0.0,0.0,86.0,0.0,0.0,87.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +447,56.0,56.0,0.0,0.0,0.0,0.0,0.0,1.0,HABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +448,0.0,0.0,0.0,0.0,11.0,0.0,0.0,10.0,EEHEHEHEHEHEHEHEHEHEH,True +449,0.0,0.0,0.0,0.0,0.0,1.0,92.0,92.0,FGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +450,0.0,0.0,0.0,6.0,5.0,1.0,0.0,0.0,FDEDEDEDEDED,True +451,66.0,1.0,67.0,0.0,0.0,0.0,0.0,0.0,BCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +452,0.0,0.0,0.0,13.0,0.0,1.0,12.0,0.0,FDGDGDGDGDGDGDGDGDGDGDGDGD,True +453,1.0,0.0,0.0,0.0,56.0,0.0,56.0,0.0,AEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +454,15.0,0.0,0.0,0.0,0.0,0.0,0.0,16.0,HAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +455,0.0,21.0,1.0,0.0,21.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True +456,93.0,0.0,1.0,0.0,92.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +457,1.0,0.0,0.0,0.0,35.0,0.0,0.0,35.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +458,13.0,0.0,0.0,0.0,1.0,0.0,13.0,0.0,EAGAGAGAGAGAGAGAGAGAGAGAGAG,True +459,0.0,0.0,65.0,0.0,1.0,0.0,65.0,0.0,ECGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +460,0.0,0.0,95.0,1.0,0.0,95.0,0.0,0.0,DFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +461,15.0,0.0,0.0,0.0,1.0,0.0,0.0,15.0,EHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +462,0.0,0.0,198.0,0.0,1.0,0.0,0.0,0.0,ECCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +463,84.0,84.0,0.0,0.0,1.0,0.0,0.0,0.0,EABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +464,0.0,0.0,0.0,0.0,0.0,60.0,0.0,61.0,HFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +465,0.0,179.0,0.0,1.0,0.0,0.0,0.0,0.0,DBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +466,1.0,0.0,90.0,0.0,89.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +467,0.0,35.0,0.0,0.0,0.0,34.0,0.0,0.0,BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +468,0.0,0.0,0.0,1.0,7.0,0.0,0.0,7.0,DHEHEHEHEHEHEHE,True +469,0.0,0.0,0.0,0.0,92.0,0.0,91.0,0.0,EEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +470,0.0,0.0,46.0,0.0,0.0,1.0,46.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +471,0.0,0.0,0.0,0.0,0.0,1.0,158.0,0.0,FGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +472,1.0,0.0,0.0,0.0,0.0,58.0,0.0,59.0,AHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +473,0.0,0.0,6.0,1.0,0.0,0.0,6.0,0.0,DCGCGCGCGCGCG,True +474,0.0,0.0,0.0,0.0,0.0,98.0,0.0,97.0,FFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +475,0.0,87.0,0.0,0.0,0.0,0.0,0.0,85.0,BBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +476,0.0,0.0,33.0,0.0,0.0,0.0,1.0,33.0,GHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +477,45.0,0.0,0.0,0.0,46.0,0.0,0.0,0.0,EAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +478,0.0,0.0,0.0,77.0,0.0,0.0,75.0,0.0,DDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +479,73.0,1.0,73.0,0.0,0.0,0.0,0.0,0.0,BACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +480,0.0,1.0,0.0,0.0,37.0,37.0,0.0,0.0,BEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +481,0.0,92.0,93.0,0.0,0.0,1.0,0.0,0.0,FCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +482,0.0,0.0,0.0,1.0,0.0,0.0,0.0,24.0,DHHHHHHHHHHHHHHHHHHHHHHHH,True +483,25.0,0.0,0.0,1.0,0.0,25.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +484,0.0,0.0,0.0,0.0,0.0,37.0,0.0,36.0,FHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +485,21.0,0.0,0.0,1.0,0.0,20.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +486,0.0,35.0,0.0,36.0,0.0,0.0,0.0,1.0,HDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +487,0.0,0.0,1.0,0.0,97.0,98.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +488,0.0,93.0,0.0,0.0,0.0,1.0,0.0,94.0,FHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +489,0.0,1.0,0.0,93.0,0.0,0.0,93.0,0.0,BGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +490,0.0,0.0,0.0,70.0,0.0,0.0,72.0,0.0,GGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +491,86.0,0.0,0.0,0.0,1.0,86.0,0.0,0.0,EFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +492,0.0,65.0,1.0,0.0,0.0,65.0,0.0,0.0,CBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +493,0.0,0.0,0.0,69.0,0.0,0.0,0.0,1.0,HDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +494,0.0,0.0,144.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +495,0.0,45.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +496,0.0,0.0,0.0,28.0,0.0,27.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +497,0.0,72.0,0.0,0.0,0.0,1.0,73.0,0.0,FGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +498,0.0,0.0,41.0,0.0,1.0,0.0,40.0,0.0,ECGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +499,0.0,1.0,0.0,0.0,0.0,131.0,0.0,0.0,BFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +500,17.0,0.0,0.0,1.0,0.0,17.0,0.0,0.0,DFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +501,19.0,0.0,0.0,19.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADA,True +502,1.0,0.0,0.0,0.0,51.0,0.0,52.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +503,1.0,0.0,0.0,0.0,0.0,0.0,29.0,29.0,AGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +504,36.0,0.0,0.0,1.0,0.0,35.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +505,0.0,0.0,0.0,20.0,0.0,0.0,1.0,20.0,GDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +506,0.0,0.0,0.0,163.0,0.0,0.0,0.0,1.0,HDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +507,22.0,23.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABAB,True +508,0.0,1.0,0.0,0.0,0.0,0.0,41.0,42.0,BHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +509,0.0,0.0,0.0,45.0,1.0,0.0,0.0,44.0,EDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True 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+671,99.0,0.0,1.0,0.0,98.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +672,68.0,0.0,0.0,0.0,0.0,0.0,67.0,1.0,HAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGA,True +673,0.0,0.0,0.0,26.0,27.0,0.0,1.0,0.0,GEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +674,31.0,0.0,0.0,0.0,32.0,0.0,0.0,1.0,HEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +675,0.0,0.0,0.0,0.0,42.0,0.0,41.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +676,0.0,0.0,50.0,0.0,0.0,0.0,1.0,50.0,GCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +677,0.0,25.0,0.0,24.0,0.0,0.0,0.0,0.0,BBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +678,0.0,0.0,0.0,0.0,1.0,10.0,9.0,0.0,EFGFGFGFGFGFGFGFGFGF,True +679,65.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,DAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +680,0.0,23.0,0.0,0.0,0.0,0.0,23.0,1.0,HGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +681,0.0,1.0,58.0,0.0,0.0,0.0,57.0,0.0,BCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +682,0.0,0.0,0.0,0.0,0.0,68.0,1.0,68.0,GFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +683,0.0,0.0,0.0,0.0,96.0,0.0,96.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +684,1.0,0.0,0.0,0.0,66.0,0.0,66.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +685,0.0,0.0,0.0,0.0,0.0,1.0,0.0,21.0,FHHHHHHHHHHHHHHHHHHHHH,True +686,0.0,88.0,0.0,87.0,0.0,0.0,0.0,0.0,BDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +687,0.0,0.0,19.0,19.0,0.0,0.0,1.0,0.0,GDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +688,0.0,42.0,1.0,0.0,41.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +689,0.0,0.0,0.0,0.0,0.0,60.0,61.0,0.0,GGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +690,0.0,23.0,23.0,0.0,0.0,0.0,1.0,0.0,GBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +691,86.0,86.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +692,35.0,35.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +693,57.0,0.0,0.0,0.0,0.0,58.0,1.0,0.0,GFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +694,0.0,0.0,30.0,30.0,1.0,0.0,0.0,0.0,EDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +695,19.0,18.0,0.0,1.0,0.0,0.0,0.0,0.0,DABABABABABABABABABABABABABABABABABABA,True +696,0.0,0.0,0.0,1.0,0.0,56.0,0.0,57.0,DHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +697,10.0,0.0,1.0,0.0,0.0,0.0,0.0,11.0,CHAHAHAHAHAHAHAHAHAHAH,True +698,0.0,0.0,89.0,0.0,88.0,0.0,1.0,0.0,GCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +699,0.0,0.0,87.0,0.0,86.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +700,17.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAA,True +701,0.0,0.0,66.0,65.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +702,0.0,0.0,1.0,0.0,0.0,0.0,123.0,0.0,CGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +703,0.0,118.0,0.0,0.0,1.0,0.0,0.0,0.0,EBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +704,0.0,0.0,0.0,0.0,0.0,0.0,0.0,132.0,HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +705,0.0,0.0,0.0,0.0,0.0,23.0,1.0,23.0,GHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +706,0.0,0.0,0.0,0.0,6.0,5.0,0.0,0.0,EFEFEFEFEFE,True +707,18.0,0.0,0.0,16.0,0.0,0.0,0.0,0.0,AADADADADADADADADADADADADADADADADA,True +708,0.0,72.0,0.0,0.0,0.0,71.0,0.0,1.0,HBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +709,0.0,0.0,54.0,0.0,0.0,1.0,0.0,55.0,FHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +710,0.0,1.0,87.0,0.0,87.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +711,0.0,0.0,1.0,63.0,0.0,0.0,0.0,64.0,CHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +712,78.0,0.0,78.0,0.0,0.0,1.0,0.0,0.0,FCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +713,0.0,80.0,0.0,0.0,0.0,81.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +714,0.0,1.0,0.0,0.0,0.0,0.0,40.0,39.0,BGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +715,0.0,0.0,7.0,0.0,6.0,0.0,0.0,0.0,CCECECECECECE,True +716,35.0,0.0,0.0,0.0,0.0,0.0,0.0,33.0,AAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +717,0.0,0.0,0.0,1.0,73.0,0.0,0.0,72.0,DEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +718,0.0,0.0,90.0,0.0,0.0,1.0,89.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +719,1.0,0.0,0.0,67.0,0.0,0.0,0.0,66.0,ADHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +720,56.0,0.0,0.0,0.0,56.0,0.0,1.0,0.0,GAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +721,0.0,0.0,0.0,1.0,0.0,0.0,49.0,49.0,DHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +722,0.0,0.0,0.0,117.0,0.0,1.0,0.0,0.0,FDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +723,0.0,0.0,86.0,1.0,0.0,0.0,85.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +724,0.0,0.0,31.0,0.0,0.0,0.0,0.0,30.0,CCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +725,1.0,0.0,0.0,0.0,98.0,0.0,98.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +726,1.0,84.0,84.0,0.0,0.0,0.0,0.0,0.0,ACBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +727,0.0,56.0,56.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +728,0.0,1.0,0.0,24.0,24.0,0.0,0.0,0.0,BDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +729,37.0,0.0,0.0,0.0,0.0,37.0,0.0,0.0,FAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +730,0.0,0.0,91.0,0.0,0.0,0.0,91.0,0.0,GCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +731,98.0,0.0,99.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +732,0.0,0.0,0.0,0.0,99.0,1.0,98.0,0.0,FEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +733,0.0,0.0,30.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +734,12.0,1.0,13.0,0.0,0.0,0.0,0.0,0.0,BCACACACACACACACACACACACAC,True +735,0.0,93.0,1.0,0.0,93.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True 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+852,0.0,1.0,0.0,0.0,136.0,0.0,0.0,0.0,BEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +853,0.0,0.0,0.0,0.0,1.0,0.0,0.0,163.0,EHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +854,74.0,0.0,75.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +855,0.0,0.0,0.0,19.0,0.0,0.0,17.0,0.0,DDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +856,0.0,73.0,0.0,1.0,0.0,0.0,74.0,0.0,DGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True 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+863,0.0,0.0,0.0,32.0,1.0,0.0,32.0,0.0,EGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +864,0.0,0.0,15.0,0.0,1.0,14.0,0.0,0.0,ECFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +865,0.0,1.0,98.0,0.0,0.0,0.0,98.0,0.0,BGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +866,1.0,0.0,0.0,0.0,19.0,0.0,0.0,0.0,AEEEEEEEEEEEEEEEEEEE,True +867,24.0,0.0,0.0,0.0,24.0,0.0,0.0,0.0,AEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +868,0.0,0.0,0.0,74.0,0.0,0.0,0.0,73.0,DHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +869,0.0,78.0,1.0,0.0,0.0,0.0,77.0,0.0,CBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +870,0.0,0.0,1.0,0.0,50.0,0.0,51.0,0.0,CGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +871,0.0,0.0,16.0,0.0,0.0,16.0,0.0,1.0,HFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +872,0.0,0.0,0.0,1.0,28.0,28.0,0.0,0.0,DFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +873,0.0,0.0,65.0,65.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +874,0.0,34.0,0.0,0.0,0.0,35.0,0.0,0.0,FBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +875,0.0,0.0,9.0,0.0,8.0,0.0,0.0,1.0,HCECECECECECECECEC,True +876,0.0,0.0,0.0,0.0,94.0,0.0,94.0,1.0,HEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +877,0.0,18.0,0.0,16.0,0.0,0.0,0.0,0.0,BBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True 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+885,0.0,0.0,0.0,93.0,0.0,93.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDF,True +886,0.0,1.0,0.0,89.0,0.0,89.0,0.0,0.0,BFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +887,0.0,1.0,0.0,0.0,42.0,0.0,0.0,42.0,BHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +888,68.0,0.0,0.0,0.0,1.0,0.0,0.0,67.0,EAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +889,55.0,0.0,0.0,0.0,0.0,57.0,0.0,0.0,FFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +890,25.0,1.0,0.0,0.0,0.0,0.0,26.0,0.0,BGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +891,81.0,0.0,0.0,0.0,80.0,0.0,0.0,0.0,AAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +892,0.0,0.0,1.0,0.0,10.0,0.0,10.0,0.0,CGEGEGEGEGEGEGEGEGEGE,True +893,1.0,0.0,43.0,42.0,0.0,0.0,0.0,0.0,ACDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +894,55.0,54.0,0.0,0.0,0.0,0.0,0.0,0.0,AABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +895,43.0,0.0,0.0,0.0,0.0,1.0,0.0,43.0,FAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +896,1.0,0.0,0.0,0.0,97.0,97.0,0.0,0.0,AEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +897,0.0,25.0,0.0,1.0,0.0,25.0,0.0,0.0,DFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +898,0.0,0.0,0.0,0.0,26.0,26.0,1.0,0.0,GEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +899,0.0,0.0,36.0,0.0,36.0,0.0,0.0,0.0,ECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +900,0.0,0.0,0.0,0.0,1.0,0.0,89.0,88.0,EGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +901,0.0,1.0,142.0,0.0,0.0,0.0,0.0,0.0,BCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +902,1.0,83.0,0.0,83.0,0.0,0.0,0.0,0.0,ABDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +903,0.0,0.0,17.0,0.0,17.0,0.0,0.0,1.0,HECECECECECECECECECECECECECECECECEC,True +904,77.0,77.0,0.0,0.0,0.0,0.0,0.0,0.0,BABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +905,0.0,0.0,0.0,0.0,0.0,0.0,164.0,0.0,GGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +906,0.0,0.0,0.0,89.0,0.0,1.0,0.0,90.0,FHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +907,0.0,0.0,41.0,0.0,0.0,0.0,42.0,0.0,GCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +908,28.0,0.0,0.0,0.0,0.0,28.0,1.0,0.0,GAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +909,0.0,0.0,94.0,0.0,1.0,0.0,95.0,0.0,EGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +910,0.0,0.0,27.0,1.0,27.0,0.0,0.0,0.0,DECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +911,0.0,0.0,0.0,100.0,0.0,1.0,0.0,0.0,FDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +912,0.0,1.0,66.0,0.0,0.0,0.0,66.0,0.0,BGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +913,0.0,23.0,23.0,0.0,0.0,1.0,0.0,0.0,FCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +914,0.0,0.0,0.0,0.0,0.0,0.0,150.0,0.0,GGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +915,0.0,0.0,0.0,0.0,0.0,0.0,1.0,42.0,GHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +916,0.0,147.0,0.0,0.0,0.0,0.0,1.0,0.0,GBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +917,0.0,56.0,0.0,1.0,0.0,0.0,0.0,56.0,DHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +918,0.0,0.0,0.0,0.0,0.0,76.0,76.0,1.0,HFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFG,True +919,0.0,53.0,0.0,0.0,0.0,0.0,0.0,52.0,BHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +920,0.0,0.0,147.0,0.0,0.0,1.0,0.0,0.0,FCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +921,0.0,0.0,0.0,40.0,40.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +922,0.0,82.0,0.0,84.0,0.0,0.0,0.0,0.0,DDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +923,1.0,0.0,0.0,0.0,0.0,0.0,0.0,97.0,AHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +924,0.0,29.0,0.0,0.0,0.0,0.0,0.0,30.0,HHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +925,25.0,0.0,0.0,1.0,0.0,0.0,0.0,25.0,DHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +926,0.0,164.0,0.0,0.0,0.0,0.0,1.0,0.0,GBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +927,89.0,0.0,0.0,0.0,1.0,0.0,90.0,0.0,EGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +928,0.0,0.0,1.0,0.0,41.0,41.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +929,0.0,0.0,1.0,19.0,18.0,0.0,0.0,0.0,CDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +930,0.0,0.0,0.0,0.0,1.0,75.0,75.0,0.0,EGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +931,0.0,0.0,21.0,0.0,0.0,22.0,0.0,0.0,FCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCF,True +932,0.0,0.0,81.0,0.0,80.0,1.0,0.0,0.0,FCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +933,20.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAAAAA,True +934,0.0,40.0,0.0,0.0,0.0,40.0,0.0,0.0,BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +935,0.0,72.0,0.0,0.0,72.0,0.0,1.0,0.0,GBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True +936,56.0,1.0,0.0,56.0,0.0,0.0,0.0,0.0,BADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +937,0.0,0.0,0.0,0.0,0.0,96.0,1.0,0.0,GFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +938,0.0,1.0,0.0,88.0,0.0,0.0,0.0,88.0,BHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +939,1.0,0.0,0.0,0.0,0.0,0.0,0.0,175.0,AHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +940,0.0,0.0,84.0,1.0,83.0,0.0,0.0,0.0,DCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +941,0.0,0.0,83.0,0.0,0.0,0.0,0.0,85.0,HHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +942,1.0,5.0,5.0,0.0,0.0,0.0,0.0,0.0,ABCBCBCBCBC,True +943,0.0,0.0,0.0,68.0,0.0,0.0,0.0,69.0,HHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +944,29.0,0.0,0.0,0.0,0.0,29.0,1.0,0.0,GAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +945,0.0,0.0,1.0,0.0,0.0,0.0,81.0,82.0,CHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +946,89.0,0.0,89.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +947,0.0,0.0,0.0,78.0,1.0,0.0,0.0,0.0,EDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +948,90.0,1.0,0.0,0.0,0.0,0.0,91.0,0.0,BGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +949,0.0,0.0,0.0,86.0,1.0,0.0,0.0,86.0,EHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +950,0.0,0.0,0.0,42.0,1.0,0.0,42.0,0.0,EDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +951,85.0,0.0,0.0,84.0,1.0,0.0,0.0,0.0,EADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +952,90.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +953,0.0,0.0,1.0,0.0,0.0,90.0,0.0,0.0,CFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +954,62.0,0.0,0.0,1.0,0.0,62.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +955,0.0,20.0,20.0,0.0,1.0,0.0,0.0,0.0,EBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +956,0.0,0.0,37.0,0.0,0.0,1.0,0.0,38.0,FHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +957,98.0,1.0,0.0,0.0,0.0,98.0,0.0,0.0,BFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +958,0.0,1.0,0.0,0.0,189.0,0.0,0.0,0.0,BEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +959,0.0,0.0,0.0,9.0,0.0,1.0,8.0,0.0,FDGDGDGDGDGDGDGDGD,True +960,0.0,68.0,0.0,0.0,0.0,0.0,0.0,69.0,HHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +961,0.0,0.0,0.0,138.0,0.0,0.0,0.0,0.0,DDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +962,0.0,0.0,0.0,0.0,1.0,30.0,0.0,30.0,EHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +963,0.0,0.0,0.0,80.0,80.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +964,77.0,0.0,0.0,1.0,0.0,0.0,0.0,78.0,DHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +965,0.0,0.0,0.0,58.0,58.0,0.0,1.0,0.0,GEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +966,0.0,0.0,0.0,1.0,35.0,34.0,0.0,0.0,DEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +967,0.0,60.0,0.0,60.0,0.0,1.0,0.0,0.0,FDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +968,0.0,1.0,80.0,0.0,81.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +969,0.0,1.0,0.0,0.0,0.0,0.0,81.0,81.0,BGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +970,16.0,0.0,0.0,16.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADA,True +971,0.0,0.0,0.0,0.0,78.0,77.0,0.0,0.0,EFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +972,0.0,0.0,10.0,1.0,0.0,10.0,0.0,0.0,DFCFCFCFCFCFCFCFCFCFC,True +973,0.0,0.0,0.0,0.0,0.0,44.0,1.0,44.0,GHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +974,0.0,36.0,0.0,0.0,0.0,36.0,1.0,0.0,GFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +975,0.0,87.0,0.0,0.0,0.0,0.0,87.0,0.0,BGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +976,42.0,0.0,42.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True 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b/tests/results/nb_gm_001_3back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,0.0,65.0,132.0,0.0,0.0,0.0,0.0,1.0,HCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCC,True +1,51.0,0.0,52.0,52.0,0.0,0.0,0.0,1.0,HCDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACD,True +2,0.0,61.0,0.0,62.0,0.0,0.0,61.0,1.0,HDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGD,True +3,40.0,0.0,0.0,1.0,0.0,0.0,0.0,80.0,DHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHA,True +4,4.0,0.0,1.0,0.0,0.0,6.0,0.0,0.0,CAFFAFFAFFA,True 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+62,0.0,1.0,0.0,0.0,59.0,0.0,60.0,59.0,BGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEG,True +63,0.0,0.0,0.0,0.0,0.0,0.0,1.0,167.0,GHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +64,48.0,0.0,0.0,0.0,1.0,0.0,0.0,95.0,EHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHA,True +65,0.0,0.0,0.0,65.0,66.0,0.0,67.0,0.0,GGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGE,True +66,35.0,71.0,0.0,0.0,0.0,0.0,0.0,0.0,BBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBAB,True +67,50.0,0.0,0.0,50.0,50.0,0.0,0.0,1.0,HAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAED,True +68,0.0,0.0,4.0,0.0,0.0,0.0,5.0,3.0,GCGHCGHCGHCG,True +69,0.0,0.0,5.0,0.0,0.0,0.0,1.0,10.0,GCHHCHHCHHCHHCHH,True +70,0.0,0.0,19.0,0.0,19.0,20.0,0.0,0.0,FECFECFECFECFECFECFECFECFECFECFECFECFECFECFECFECFECFECFECF,True +71,0.0,0.0,1.0,0.0,0.0,0.0,43.0,84.0,CGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHG,True +72,6.0,0.0,0.0,0.0,6.0,6.0,0.0,0.0,FAEFAEFAEFAEFAEFAE,True +73,0.0,0.0,35.0,35.0,35.0,0.0,0.0,1.0,HECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECD,True +74,25.0,0.0,26.0,0.0,1.0,0.0,0.0,25.0,ECAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHC,True +75,61.0,0.0,0.0,60.0,0.0,60.0,0.0,1.0,HAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDA,True +76,0.0,0.0,0.0,41.0,0.0,0.0,0.0,20.0,DHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDD,True +77,0.0,0.0,1.0,0.0,0.0,15.0,15.0,14.0,CGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGF,True +78,6.0,0.0,1.0,6.0,0.0,0.0,0.0,6.0,CHDAHDAHDAHDAHDAHDA,True +79,0.0,124.0,0.0,62.0,0.0,0.0,0.0,0.0,BBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBD,True +80,0.0,0.0,32.0,0.0,0.0,31.0,31.0,0.0,CGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCF,True 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+317,61.0,0.0,0.0,0.0,0.0,61.0,1.0,61.0,GFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHA,True +318,0.0,0.0,0.0,7.0,7.0,8.0,1.0,0.0,GFEDFEDFEDFEDFEDFEDFEDF,True +319,7.0,0.0,0.0,0.0,1.0,3.0,0.0,0.0,EAAFAAFAAFA,True +320,0.0,48.0,0.0,48.0,0.0,0.0,0.0,48.0,BHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHD,True +321,0.0,23.0,23.0,0.0,0.0,0.0,0.0,24.0,HBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCH,True +322,0.0,0.0,1.0,0.0,0.0,30.0,30.0,30.0,CGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFH,True +323,48.0,0.0,0.0,47.0,47.0,0.0,1.0,0.0,GADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEA,True 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+401,0.0,55.0,55.0,0.0,0.0,1.0,54.0,0.0,FCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCB,True +402,47.0,0.0,0.0,0.0,1.0,47.0,0.0,47.0,EAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFH,True +403,56.0,0.0,0.0,0.0,58.0,0.0,0.0,56.0,EEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAE,True +404,0.0,39.0,0.0,0.0,39.0,1.0,40.0,0.0,FGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEG,True 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+951,0.0,0.0,0.0,0.0,35.0,1.0,35.0,35.0,FHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEG,True +952,0.0,0.0,1.0,0.0,0.0,0.0,36.0,71.0,CHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHG,True +953,0.0,42.0,0.0,0.0,21.0,0.0,0.0,1.0,HEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBB,True +954,0.0,49.0,0.0,50.0,0.0,0.0,49.0,0.0,DDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBG,True +955,11.0,0.0,0.0,0.0,22.0,0.0,1.0,0.0,GEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAE,True +956,0.0,0.0,0.0,1.0,0.0,18.0,0.0,38.0,DHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHH,True +957,58.0,58.0,60.0,0.0,0.0,0.0,0.0,0.0,CCBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBAC,True +958,19.0,19.0,0.0,0.0,19.0,0.0,0.0,0.0,BEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEA,True +959,0.0,0.0,39.0,0.0,0.0,38.0,0.0,38.0,CFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHC,True +960,0.0,0.0,0.0,80.0,41.0,0.0,0.0,1.0,HEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDE,True +961,0.0,21.0,0.0,22.0,0.0,23.0,0.0,0.0,FDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDF,True +962,0.0,0.0,0.0,0.0,6.0,10.0,0.0,0.0,EFEFFEFFEFFEFFEF,True +963,65.0,65.0,1.0,0.0,65.0,0.0,0.0,0.0,CBEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEA,True +964,0.0,46.0,1.0,0.0,45.0,46.0,0.0,0.0,CFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFB,True +965,64.0,64.0,0.0,0.0,63.0,0.0,1.0,0.0,GABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEAB,True +966,1.0,0.0,47.0,0.0,0.0,48.0,47.0,0.0,AFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGF,True +967,54.0,0.0,54.0,53.0,0.0,0.0,0.0,0.0,ACADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADC,True +968,10.0,0.0,10.0,0.0,12.0,0.0,0.0,0.0,EEACEACEACEACEACEACEACEACEACEACE,True +969,0.0,0.0,0.0,0.0,0.0,0.0,125.0,62.0,GGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGH,True +970,0.0,8.0,1.0,9.0,0.0,0.0,8.0,0.0,CDBGDBGDBGDBGDBGDBGDBGDBGD,True +971,0.0,0.0,0.0,66.0,66.0,67.0,1.0,0.0,GFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEF,True +972,63.0,0.0,0.0,0.0,127.0,0.0,1.0,0.0,GEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAE,True +973,0.0,0.0,11.0,0.0,0.0,0.0,21.0,1.0,HCGGCGGCGGCGGCGGCGGCGGCGGCGGCGGCG,True +974,0.0,0.0,39.0,0.0,0.0,40.0,40.0,0.0,FGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFG,True +975,0.0,0.0,1.0,31.0,0.0,0.0,62.0,0.0,CDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGG,True +976,0.0,54.0,0.0,0.0,0.0,1.0,54.0,55.0,FHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBH,True +977,0.0,0.0,18.0,19.0,0.0,18.0,0.0,0.0,DFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCD,True +978,126.0,63.0,0.0,0.0,1.0,0.0,0.0,0.0,EAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAAB,True +979,19.0,0.0,0.0,0.0,0.0,1.0,0.0,9.0,FAHAAHAAHAAHAAHAAHAAHAAHAAHAA,True +980,0.0,0.0,32.0,32.0,0.0,33.0,0.0,0.0,FDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFC,True +981,15.0,0.0,15.0,0.0,16.0,0.0,0.0,0.0,ECEACEACEACEACEACEACEACEACEACEACEACEACEACEACEA,True +982,0.0,0.0,55.0,0.0,0.0,56.0,57.0,0.0,GFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFG,True +983,0.0,0.0,32.0,0.0,1.0,32.0,31.0,0.0,EFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFC,True +984,0.0,0.0,0.0,41.0,1.0,40.0,40.0,0.0,EDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGD,True +985,0.0,0.0,0.0,0.0,5.0,6.0,5.0,1.0,HFGEFGEFGEFGEFGEF,True +986,0.0,19.0,17.0,0.0,0.0,0.0,0.0,18.0,BBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBH,True +987,0.0,0.0,0.0,0.0,0.0,0.0,6.0,10.0,GHGHHGHHGHHGHHGH,True +988,0.0,0.0,69.0,0.0,36.0,0.0,0.0,0.0,ECECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCE,True +989,1.0,0.0,0.0,0.0,0.0,19.0,0.0,37.0,AHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHF,True +990,67.0,0.0,0.0,0.0,0.0,0.0,0.0,33.0,AHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAA,True +991,0.0,0.0,16.0,18.0,0.0,17.0,0.0,0.0,DFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFD,True +992,1.0,0.0,50.0,50.0,0.0,0.0,49.0,0.0,ACDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCD,True +993,0.0,40.0,39.0,0.0,39.0,0.0,0.0,1.0,HBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEB,True +994,0.0,30.0,1.0,0.0,0.0,0.0,30.0,30.0,CBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGH,True +995,126.0,0.0,1.0,0.0,0.0,0.0,0.0,63.0,CHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAA,True +996,45.0,0.0,45.0,1.0,0.0,0.0,0.0,45.0,DHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHAC,True +997,15.0,0.0,0.0,0.0,29.0,0.0,0.0,0.0,AEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEE,True +998,0.0,4.0,1.0,0.0,0.0,4.0,0.0,4.0,CHBFHBFHBFHBF,True +999,0.0,100.0,0.0,0.0,0.0,0.0,0.0,51.0,HBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBH,True diff --git a/tests/results/nb_gm_002_2back.csv b/tests/results/nb_gm_002_2back.csv new file mode 100644 index 0000000..33538c3 --- /dev/null +++ b/tests/results/nb_gm_002_2back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,4.0,2.0,2.0,2.0,2.0,1.0,0.0,5.0,BHCHDHDAEBEHAFAHAC,True +1,0.0,4.0,1.0,2.0,4.0,0.0,0.0,0.0,DBEBDBCEEBE,True +2,5.0,10.0,14.0,6.0,16.0,18.0,12.0,12.0,CFFGHCFCGHEDCCACECBGEGFGAEBGHFDCEEDCCEGEGCBBBHCCECHBHEHBHDEDAFAFAFHFGFGFGHGHEFFFEFEDHFEFEFBBB,False +3,12.0,15.0,11.0,20.0,13.0,17.0,17.0,22.0,AFAHGHGHGBEBCDDDDHHHABCEHEHEBBBAHADADCFHHHHHFEFCBDDFDGDEFCAGGFEFBDGEHECCBCFFFFFFHGEBBHHCBCACHHDDBFGGGGEGEAFDGDADGDGDGBEBAAHDDFH,False +4,4.0,4.0,8.0,8.0,5.0,7.0,4.0,2.0,FGDGECDCECGCDADAHFDFCFCGAFCDDDABEBHBEFEFBC,False +5,15.0,15.0,15.0,16.0,16.0,14.0,9.0,13.0,HGDGBFDHDADHBBBBBHBAAGBCEABCGFAFAFBGBCBFGDDDEAAAHDFACECECHFHFHFCFHEGEFEFDFDAAHDEECDABFCCCCGBEBDAHCECHCHEDEDEDAGEE,False +6,17.0,17.0,9.0,6.0,15.0,13.0,15.0,12.0,BEBEBHAGCFEHHABAHDEDGHFBFGFCAABAGFFFAFGECEBEAEAFBFCEBEGHGDBEFABABEGEHEHBGBGDADACAGHGHGBGBACGCAHFFBHAECDC,False +7,12.0,7.0,7.0,6.0,9.0,8.0,5.0,6.0,CEGBFEFEFEHCCDEBCCHBBBGAHACBGGDBDADACADHDHFEAEAEFGFAAEAHAFAF,False +8,9.0,13.0,10.0,11.0,12.0,15.0,11.0,12.0,CGCFDBDFHHEHFFGCDHEHCFCFAAEGDCEGHGCFCBBBCBGFGHGDFDBDADHBBEGAGABABHBEBEHGHADAFEFCFDBDEFEHEFEFA,False +9,13.0,26.0,23.0,14.0,20.0,18.0,19.0,27.0,HECEBEFFHFDCCFGBCBDBAHGHGCBBABHEFAFEBEBHBHGGCHBGGCCCCCFCBDDDEDHDEEEAAFAFGFDFCGBGHEHDHGHAFABCGGEHEHFBGBADEBEBEAAHBDCCFGGHHHBHBHGHBDBEEAEGCGCBCHCEFFFFCHDHCHDHABCB,False +10,14.0,18.0,15.0,13.0,15.0,19.0,18.0,11.0,AFACABDDFBBBEBECECGHFBFBECDCEEEDGDBHHGCBDDAFCBAAAGHCHCHEAFBFDHAHCFFAAAHBBBFBFBHGFBCBCFGGGHGDGDFEGEFCFEDGDGAGEGCGEGEFEFAFDGC,False +11,21.0,20.0,21.0,13.0,15.0,26.0,21.0,21.0,EECEFFHGCADHGEGEABCCFDEBABEBGGCACHFHFBFBFBAHGBGCGHDCDABHHAGABFHEBCFEGDFDFDFAFBCBCAHACFGFBFBFBFBDACCBCHFHEGEDFDFCAAAGGEBFAAACACHCHFGFBFGHGHAEAGCCEDDFHHHGHGHGDE,False +12,17.0,26.0,17.0,23.0,17.0,11.0,26.0,21.0,ABGCACGDDFHFHBCEHEAGBGBEBAHEBEBFAAHAFBCEGDGBAHGGGGFGDDDBABABHGGGCGDGHGHDACAEDEFECHGEGDABGCHCDDDDCBCBADAHCHGBGBGEHDCDBBFBABHBHBFBACHDEEHGHECDCDHDEFEDECFGHGBFBD,False +13,24.0,21.0,23.0,20.0,15.0,14.0,30.0,24.0,AHHHHAFEDHAFBFGFCFGADADCDGBBBBGDGEGBCBHGGGGCGFBFAGGGGHEEFEGHGHABCBFHGAGACBBDEDHDHDGBCACAHGCACEHECACHBHDCGCECADGDGDABADHFGCGAGAHHBGFDCHBHCAAABEEFDFDBDBEADAHGEGEHECCCBCFCAHD,False +14,1.0,0.0,2.0,1.0,1.0,1.0,2.0,2.0,DECGCGAHFH,True +15,7.0,7.0,10.0,5.0,8.0,4.0,8.0,9.0,HBABHHEEGAGAGEGHCDEECHCHGBCBCDDAEGCBCGEAEFDFBFBFAGCHCHCHAD,False +16,14.0,19.0,14.0,7.0,10.0,15.0,19.0,7.0,CEAFFGHGEGFDFDCACAGBDEAFCEDDFAHHFDFGBEACGCGBGAFECECFGHCEBAFGEGCBABEBHBHBACAGAGDGHBABCBCBGFGFGFGBBBBFBCBGA,False +17,17.0,15.0,14.0,12.0,10.0,9.0,17.0,6.0,EBACADACGBGBAFGHGHADCDGAAFFFADABAHGDGABBCBCACACECHFBFHDCACDGEBADDEGGGEDADFGFGCGFBBABCBEBDBCHGEGEGECE,False +18,14.0,22.0,17.0,9.0,14.0,10.0,25.0,20.0,EHCHAHEHAHCHCGBGCGCGAEBFBFGGCEFGBGHAHCBABABHHGHGCACHDEDBBABGGDGDEBBBHHGCAEGBFHGEGEGBCCGCDFBBGBFBDAEEHHHCFEFECEHGCGCBHDADFDAGAGAGFBB,False +19,13.0,27.0,12.0,18.0,19.0,17.0,20.0,18.0,BFGCGBHAHAHEFEDBABEBEDADGGGGBAFCGEBDFHBHGHGCBBEGEGBHDHDHBCBCACDBFHHCHBGAGAGEDADADCDCACGHEEEEBDFDFDHDCGGBGDEBBBABEHFHGEFFFBADHEFFCFDEBEBFFEBHBFBG,False +20,11.0,10.0,7.0,8.0,8.0,7.0,11.0,4.0,BGBABGHGCGFBFAEBGGEDEFAHEHACDCDADBGGAGAGADFBFBCBCEFBFDHDACCDAGAEEE,False +21,22.0,20.0,18.0,24.0,13.0,11.0,16.0,21.0,DADADHCACFCHEDAAAHGDDHAGCDEDEGBHAHBDBDBGHHHCHCECAAAEFEDECEDBHFABGBCAGDBEGEBABHFCBBABDFDGHGCBFBCCDHDHDGDHDHCHBGADAFACHEHBDCDAFAFAFAGGCGCFHGBDBEBEG,False +22,8.0,10.0,11.0,7.0,8.0,15.0,4.0,11.0,CBAEGDGEHEBGBFBFBDHCHFHBAEHFFGFCFBFCFEEHABECFFFFACAEHHDCDCDHDHAHCFCBCBAADF,False +23,32.0,19.0,21.0,23.0,13.0,27.0,21.0,27.0,GHCABDGDFFFAHHHEAEHGAGAGHEFEGBCFAFBFGCHCHFHBGCAFFDFDBACACHCHCHBFGFEACAFABEBEBHHGHFHAHGGAGAHAFCGDHDHAFGCBCHDAAAAAAFCFHGEFFBEBEDDDFDBCBDDDCGFAFADBDBEBCAGGHDFDFBCDEAGAHCCEHGHAHCDDDDABAFA,False +24,26.0,30.0,18.0,21.0,29.0,16.0,21.0,21.0,GDGDADAGAGDEHCDBDHAHEHFHAHAFBHBHGCEBHBDBHBHBEEABABABAEECEGEGAGADHDBEEGBCAADHGBFBCEAAHDEBEBFBFBFCCGCEFBABAEDBGFGBGCFCGEACDFEFBHDADFHCEAEBDHDCGBEFGCDCACDEBEGAGAEAEFDFBBEHEGEGHCACEFBHDH,False +25,17.0,15.0,10.0,21.0,16.0,11.0,16.0,22.0,BDBDBHHHAAGAEHEHCHCDADEBGHDAGEBHGAABADADEDECEHAHFBGCGBEHCGADFBHECGHHFFFHFBDDDDDFDFDFHFEDEDACAEAEBDCHHBFBABCBGDGEAECHHGHGEGHDAGGG,False +26,12.0,13.0,16.0,11.0,17.0,10.0,17.0,12.0,GEECBGFEEDHCEFGFEAEAHGEGEDDDHDCDCBHBCBCFCECEGAGAGAHECFCEAAFGFGCEHGHBBBGBGBCBDHEAEFHFHGBCDGGACHCGCDADAEBFBADH,False +27,14.0,11.0,17.0,13.0,14.0,21.0,16.0,19.0,AAECGGEGHCACACACHBHADCECBDHDHDFCFGHGDDEDHHHAHDFDACHBHAFBHHAEEECGGFGEGEBEFCFAEAEFFBFBFDGDGDGHFACCDFHFCGBBHBCGGFGEHEFFFFHFCBCAF,False +28,14.0,15.0,12.0,21.0,15.0,9.0,13.0,21.0,GGHGEDHFCFCACBCADAEEEEAHDGAGHGHEHEHBBECEDBBBDBEGDGBAEABCCABBECDDDFDFHGHGHDHGHGHDADHHCHBHCCBAFHFDDDEDHFHAABDFDFEGEAADBDCH,False +29,18.0,19.0,27.0,26.0,29.0,30.0,16.0,16.0,DEFFFAFAGDGEEBFBFGEBADACADFDCEEDEDFDCDEBBGDGHGHGFFFDFBEBEHCHFDCDCEGFGFHFEFCGBBDCHCGCDADEGEGCFAAEHEHFDACGCEABBDECBCBCEFEFBFCFCFEHEHDGACEBAGCEFEBACCCAEDHDHBCFCDEFFHDHDHDCFCAAAEBEBFDHA,False +30,5.0,11.0,5.0,8.0,3.0,2.0,5.0,1.0,BBFGGBABFGCCCDADAHBEDCDBABGEAECBDBDBDBDG,True +31,28.0,17.0,19.0,16.0,18.0,11.0,17.0,33.0,DHAFAHAEAHDHFHFAFADHCGGGDGDGHEBDHCHBHAEBCBCFEGHHHBHCAFDHEHEHCDAGBCBAAAGACCBCAFGBHEHBBEAHAHAFAEACGGEHAFABEDEDFDCGHEBGAGEEAEBBHDEDECHCGABHGHAHAHBHCHCHCHDGACACDFD,False +32,5.0,10.0,12.0,17.0,19.0,17.0,17.0,11.0,EEBHBFFFDDEDCCAGEFEGGDGDFFGEGEAEDEFCFCGCGCGFAEGECDHHCEFDDHDFDABFDECECEHEFDDGDGBBFBFHHGCECEFEHAHDHDGBBFBGHGBG,False +33,4.0,13.0,10.0,7.0,4.0,8.0,11.0,7.0,CGBHBCBCBHFHFECBADGBGBGBDBCFAGDBHGFGECEHBGBCCACFGFGFGDDDFCADHEHB,False +34,22.0,27.0,22.0,21.0,21.0,28.0,21.0,21.0,BABFBCCCCGCDCAGABAHFBAHCBDBDHDCDCDEFFHBHBCBCBEHDAGAEFBBEEEBEGAGHGDGCGEBFBDEAECCFCFGDGDGHBHAEFFFECCADHFFBGHDHEGAAEDEFEFCDCDCDEFCHADAEHFDFHBBEBEBFBFAFGFAAHGHGFFAFGGBABGHGBFBFDFHCHAHEGDA,False +35,24.0,23.0,21.0,17.0,28.0,15.0,20.0,21.0,EGHGAGEGCGDFFCEEEEEAHGEGFGFBCBGBDBACHCAGDDDDEDEHACGCECAFAFEFHCHCEFHDHEHBAEADBDBAFCHCEEEEHBHBECEAEAFGGGGCCHBHAAACABBEHFHBDFHHDHBGCAABEBGAGABBFADADEBBBBCDCACFGFHDCEHEBGADE,False +36,16.0,12.0,18.0,16.0,29.0,20.0,25.0,11.0,EEEBCFFDHDBBGHGHGEFDFACCCFCGAECECEAGFFFCFDAHAEEHGGGBGBGADDGDGEGCCBFEHEGEHACDGDGCCCFCEAFAEGEGBGFGBBBHFGDGFGAAHADADCEEEEDEAEFEAEBFFFHEGECEGEHECAFDDDB,False +37,1.0,6.0,2.0,11.0,2.0,11.0,4.0,7.0,DBFFFHHADFFEFBDBFBGDFFEBHBHFHGDGDGCCDDDDHDHF,True +38,11.0,12.0,15.0,5.0,3.0,15.0,15.0,13.0,HCCCCAEBGFCFBGAHHHHBAFGCGCGCGFGCAABFBABHBFBCAFHFAFGCDBGBGAGFCBBAADHDHDCGEGHGCGFFHFHDEFHFC,False +39,33.0,14.0,21.0,23.0,21.0,18.0,25.0,28.0,DHAHAHADGDAFAFGCHCHEHCHABACEDDDCGBHAEFFGCADADGBGCFFFGGHBAAFGGHFHFHECFCHCHBDEFGADDCGGGHEBEDEBEBEDFHCAAAACFGFBFBFADAEGBDCAGACACAFGEEECDDDDCGGGEEEEEGCADHHHHAHABAHGBBCACHEGGHDADADAHAHEHAH,False +40,9.0,21.0,8.0,6.0,13.0,11.0,9.0,15.0,HEBEGEGAGEBBBHFAFABCBCBEBCBEAFHGGGHEHCHBEDFFAFAHDBFBFBEBDFHHDHBHCHBHBDEFABGBCEDEBCACHHEAGBGF,False +41,13.0,18.0,18.0,16.0,8.0,20.0,16.0,13.0,AGDGBCDHFADAGFFFHHCFCFEBGBGFGFGCGCHHHHCGFBFGDHABCBCGDGECEFBFCACBDBDCFAFBDEDCFFBHGHBEBABDFDFDHDHACABDBAFAFDHEGACACBEECGCBDG,False +42,21.0,15.0,14.0,22.0,14.0,22.0,16.0,21.0,ACFDFDEDFDBAFDCDCDFFFFFACHCHGEDFCFEHADACEHEDEBAFAGGHGEDADFDHDHDHGADAGCCCFHBDBGBDEGEBHGFGHAHFBFBFEAABABACDDAHHGFGBGEGHFEABHBFEHHHGDFDCACABABGECHAH,False +43,17.0,19.0,23.0,19.0,19.0,21.0,20.0,22.0,GDGFGEDDDDDDFDFDFEHBHDGAECBHDEGHGEEDEBEDECGGAADAFAFADECFCDGDGFBHGCBHBACAGACFCGGGBGCHFHEHECECAHFHFGCGHBFCGCBCFEHEGEHBBAAABDHFBCCCCFFFHFCABFBHBHBEDAFEHBHACABECHCH,False +44,2.0,1.0,3.0,4.0,5.0,3.0,6.0,5.0,CHCHFGBGEHFDAGADEDEGGFGEDEHCH,True +45,17.0,20.0,26.0,20.0,18.0,24.0,15.0,12.0,BDEFBBBHHECFCFCBBFEDDADADGECEHEFCGCAFDCGCFFEDDGGHHHHHAFAFEFAFDFDFDEDFAACFCFCDCBBBCGCGDGDFCGCGBDCACBHDHEECBBEBECFCHGBGEGABCDCEFHFGACDFAFAECEBEBDACABAGFBA,False +46,5.0,7.0,11.0,5.0,5.0,3.0,8.0,10.0,CBDHFHCDCEGEHCHCHCHEGCGCGBBBBADAHGDGBACGEAHBHFGFCECAHD,False +47,5.0,4.0,4.0,5.0,0.0,1.0,5.0,3.0,ACABGBHBHBGDCACHCDAGFGAGDDD,True +48,21.0,22.0,13.0,24.0,16.0,18.0,24.0,19.0,DBDGAGBGFHFCABGFECEGBGHHEACDFDGCGBEBGDAFAHADADAHHBHBHAGABADEBFDGDBDGDGCFAFAFDDDDECGFEFEAHAHEHEHCBCDADGBFBFAEBCAHFHEDEGBBFDEHEBDHFGCGHGHGBGCDABCBDGHGBGDCEAFAF,False +49,5.0,12.0,11.0,8.0,8.0,7.0,11.0,9.0,FCFDGDHBEBECFBBHFCFCGDBCCCGCECECBDBGBEHDDBCAGAEHEDFDHGEGAHBHGAGAGFHBHBG,False +50,2.0,7.0,7.0,4.0,6.0,13.0,10.0,11.0,BBFEFEFHAHFDFGHEBABDFHBHEFGFGHEHGGGFDFEHCBGBFDFHFHCCGCGHGCCC,True +51,5.0,7.0,11.0,12.0,13.0,9.0,8.0,13.0,EFFBFDAAECCCHDHBHFEDBHBHDHDGGGGECDGHCFEFEDEDCDCDEDCCHFEFEGCGBHEHBHAHAGDFCEAEHB,False +52,15.0,6.0,11.0,6.0,11.0,16.0,3.0,8.0,BAEGCCEAHBFCCHFABEHEFDCHEBECACECEAFGFEFEFBFBFAFADADACACDFGFAFAFEFDAAHFDCAHHH,True +53,20.0,14.0,19.0,11.0,13.0,12.0,10.0,17.0,CHCECEHEGAHBFGHCHABCBCDCECEDAHACGCADDBBGFGFGFHAAACACFBEGGAGAEHCAAAFDFDCHBDBHGDFDHCBEFEBCBABHHHHDHCHDFEFABEBECAAAEACF,False +54,18.0,14.0,15.0,22.0,24.0,20.0,25.0,23.0,EGGCGCGDEDEBCBFDDDBFHDDGFBFEEEGDBDBEHFDFEACACADABEFDCECGGHBDCDBAGHGFBFECHCFEDEHEHAHEEAGCEEEEFGFHFAAGEEHHHHAHAHDEFGDGDBCGAGHFHFHAHAHDHDBFBFCEGGGGGGGHAADAGCDFFAHCB,False +55,3.0,4.0,2.0,5.0,2.0,5.0,3.0,1.0,EHAABABGBFDFGFGEDDFDCBCDF,True +56,9.0,9.0,8.0,11.0,11.0,13.0,8.0,11.0,ECFFFBCDEDAFEBEAFGFHFHFDEHEBEHEGBFEFHBABCCAGAGBGBDFHAHGHFCFDHDABADEDEDAHGGCDCHCD,False +57,10.0,13.0,10.0,15.0,7.0,9.0,16.0,11.0,HHCFEGEGEDFGABEHEADCHGHBDFDGDGHGCGBBDDCDCDBDBHCDEBAHACCFDGDFAFAFDDAGAGHGCGBGBHACBGBGAHEBFBF,False +58,15.0,15.0,14.0,21.0,27.0,24.0,20.0,28.0,FAFEFAADAGFBFACBCBHHCGFGFAFHCEGEGHHBDBFHFHBEGDGDAEEHEGCGDGHCDGDEHFHGCEEEGEGEDBDEEEEHHHHCHDAGFEBHFHAHFHFDDDCACHFBDDHDGDFDAGGEAEFBHEEEEBEHEFFCFCFDBHAFADCGCGFHDHEBABHB,False +59,11.0,16.0,18.0,17.0,22.0,31.0,15.0,17.0,FCECFCFCFBHCHBGBFHGEDADADEFEFHFDFDADEEADHGAEAECGDGCCFHFGFHFHFHFBFBFCEEEBEFFDEGGBHBEBHFCDDDDGHAFBFBFCACHCAFGCGHHEDCBFEFABCDCEGGGDAEBBBEDEFFFFECGHEHF,False +60,11.0,9.0,7.0,2.0,10.0,10.0,11.0,9.0,HGHCDCHCACBCEGEGEGEBBHCFGABEBFAEHHFBFAAGHGHFHABABCGEGFDEAAABFEFEFGFGA,False +61,23.0,23.0,21.0,24.0,24.0,17.0,27.0,24.0,EDGGCBCFCGCGCFCGCDCBAACHFHFHECACAGAHFHDBDEHAGADHGEGEBCAEAGDHAADDDDCEAEADBGFDBBBBDHDGDBBGCAAEHEGDGBGBFHCGCDBBBEFHFDAGHCDCHFHFGEHEGEGHGBEFACADAFCBGBGBFHDEDEDFBFEGHGHAHAEEEEGEDHAHACEFBHB,False +62,21.0,13.0,9.0,12.0,17.0,15.0,25.0,10.0,HFGFGBGEDEHGHAHFHGAAAFGHBFACGDBEBGAAFEGEFEFBGAHDEDECBCBFBEGAGAFCCBBDBAGABAGGGGGECDADAGAEFEDGACADDCDHDEAFHFHFGGGFGCABAEEEGE,False +63,6.0,6.0,3.0,12.0,7.0,8.0,6.0,13.0,FHEBEBHGHDAGHDCDEDEAFCFCHEEBAAFDDDFDHDAGBGFDHGHAHDHEHFHFHBDBG,False +64,6.0,15.0,15.0,8.0,14.0,13.0,8.0,8.0,CCEDEDBHHGDCBEFEFCCGCEAGFGEGECAHAHGBCFHACEBEBEGEFFFFBDBFBHBDDEDCBCBHBFGFHEAEBCBCFCBCAFD,False +65,6.0,4.0,3.0,4.0,6.0,8.0,5.0,5.0,CGCFEFAFAEEDEHCHBBDAAFAGHEHEBFDHDBAGFGFGF,False +66,17.0,8.0,15.0,6.0,16.0,16.0,11.0,12.0,AFGFGFGHGFECECECHAECCCFAHAFAEHGGCEBAFAEAEFGGHCBFAAEHFHFGBHEHGAFBFHCECEADFDBDBCACACAEAEBEDDACBDFHFHEGC,False +67,24.0,12.0,23.0,14.0,18.0,18.0,15.0,12.0,CCCFCFBHAEEDFDBAADAEAEABDBDGEHEGCCCACECHGEGEDECACFCFCHBFBAGAFFGHADBEBAAAAFAEECEDHDHECGGBHHCHDBGBABAGEFFGFAFADACADAGADCHFECGFGFHFCDCEGFCC,False +68,31.0,17.0,27.0,38.0,29.0,28.0,14.0,16.0,ACACBCFDGBHBDEGEAHDDEFEFEFEFDDHECEBDFDAEAEFECECGCHAHAHCBCDAHBDDDDEDEBEHGDDAFEFCFDDBCGAGACCECAADADABAFEDACGCAFAHDFDBDGCECBGBFFCHCGAEDFFFHADFDADGFAFADEDHABAGAGEHEFBFECEDEDCGEADADFDHBHDFDCBCFCDAFAECFCEHB,False +69,5.0,4.0,3.0,4.0,2.0,3.0,6.0,4.0,DAHAGAHAHAHFGCGEBDFDEDGGCFBBGBC,False +70,5.0,7.0,9.0,5.0,2.0,11.0,6.0,10.0,HAHDHDHBGBFCACDCHFBBHBHGDEACACEGFCDHBGFGFGFCCHBFFHFCFAF,True +71,11.0,10.0,6.0,19.0,14.0,23.0,11.0,9.0,FHFEADABECHFFDFDFHFEDECEFEFEFAFHDADAEADDCAGFGBBHGDGABDDFFFFDDDADEEGFGDABCDGGBHDHFGAGBHBHBEBEGFFFFFCCEDE,False +72,25.0,17.0,20.0,19.0,16.0,13.0,17.0,22.0,GDCDHGBEAEGDGEBDBDHDCDCBHDEAEHDCEFAAABCDCDABAGADADCFAFCGCACAFFBAHGCGCGEGEACHHECACECEHEGGFBDHFHAHAHGGDGFCECHFHFHCHFABABFDGABDEDABABHEACAFDHHGHAHBBBBEH,False +73,15.0,19.0,20.0,23.0,23.0,21.0,22.0,23.0,GFGFECGCEEGHFCBCFDDDHHGBGHGHDCDCFHAHCCCFHAADEBEHEDEDADCDCABEGEFDFHCHGGAHAHFCFCEADFFECGBDBDBDCCACADHGCGEGHFHGHGBFADEBEBEDGDBBACEEEHGBDBFFFFDGEGDGDGFBEHHHHAAEAEFBBBBEFH,False +74,3.0,11.0,6.0,11.0,10.0,12.0,5.0,7.0,ECHFHDHEFFHHDCFGEGFDBEBEFFFDBCBFEDCDCFEBBFADDBDBGBGBGBAHAHFDEDECE,True +75,21.0,13.0,22.0,19.0,30.0,19.0,18.0,19.0,HAHEEEFEDHDFDBHBGCCEEFEGGHGHCCCCCHGECEAHDBDBEFGHCACGBEFEHAFDFACAFEEEHABAGAFDGDADADAGBCBAEADAEFHCDCFGEHFHDEDCDFEFCCCEAEAEGGABFGEDBDBHBCCECEHEAEFGHGHDDAEAEHCFGFGFB,False +76,14.0,30.0,18.0,20.0,25.0,19.0,27.0,30.0,FCFBAEDEGEHEBGHGFEFCGDBDGGCGCGBEBHBHEAAAEECBCBCFHFCFDGAEHHFGGGGGHCHEHBABGBGHHDFAEBDBDBDBCCHAGGEGDGCCBCHFGFGHGHBHEFGHBFBCBHEHBBABCBHBCGEHEADDDBHFHAADEDBFHFEEGEDHDHDEDBDFEFEHCHAEGDHBFBA,False +77,25.0,17.0,30.0,29.0,22.0,22.0,23.0,24.0,CCHEAEHBBCBDADBDBDHGFEECBDFGFEAHDCGCDHHEHEHCGCFHGDGAGAGACACDDDFDFDGECCHDHCCEFAFEBAFGGHDCCGEDBDBDBCHCACDBAHCGCGAHAHAFFFHADCDCFCFHHCDCAEAGAGAGABFHGEGBGDFHEBEFCFAGBEEAABAGDGDFDFEABHCDEDEHEHEFCFCD,False +78,9.0,16.0,9.0,5.0,4.0,15.0,4.0,5.0,BCEADCBBBBABABCCEHFBDHFAAGAGHCFCBCBFDFAGAGBFBDBABFFFFFCEHEBDHFFFBFC,True +79,19.0,17.0,10.0,29.0,13.0,8.0,14.0,14.0,DEDEAEAEDDDDDDDHDGEBEFADAGBFFHDGFBBBBGBABFCHGDFDEACBBBAHADAHCGCAHDHEHABAGCGCGEDAGBDAACAHDBCBGBGBEDDDDDADGDFDHHFDAHAEEEHCDCHG,False +80,9.0,11.0,7.0,9.0,14.0,3.0,11.0,16.0,HEHEACBHBHAGEBEAEBHBHBDEDCFABCGAEABHEHDADABABGGGDGHECEHHDGDHHCHCDGFFHCBEDEGEGHGE,False +81,4.0,9.0,4.0,9.0,3.0,6.0,6.0,5.0,BGBACACHDGDFDFBFEAHFBDDEDEGHGHBBBFBADHDGCGDBFC,False +82,11.0,21.0,22.0,24.0,26.0,28.0,21.0,21.0,EDGDCDCFGEDEFFFFGEEEDEDEDADACHCEBAFAFCHEDBFEDHDCCAHGFDFDGAGEFECEDBHCECDGGGGGBGFGBHCGDGFFDCAGDBCEHEGBBBBHFHADFHCHCHCACHCBBEFAGBGBEBFFFHFBCEDFFEFHDHFHFCCECBHBDBDEDEHBHEHFBFEGAG,False +83,2.0,4.0,1.0,3.0,2.0,4.0,2.0,1.0,CBFHFBBDGDFDFEGEABA,True +84,18.0,13.0,21.0,13.0,16.0,19.0,15.0,8.0,CBCEEADAFGDCFHFHDHFACACEDGACFGGGCBABDCCCCCCBABABABDBDFACGCGCFCAGEFEFBDBCFEFEAGFDBEFEHEHBAEADAFAFGEGECAHFEDGDHHCAEDEFCFGGGBF,False +85,14.0,12.0,10.0,10.0,16.0,19.0,9.0,12.0,FGBGHDEEEGBFAEAEDHGHGFEDEFEGEDEFEFCBAHCHCFBFDGECFFFGAECBBBDGFAFACACBEDABEBFHFHFHAHAHFEDCDCFCAAHBHADAFB,False +86,14.0,13.0,10.0,16.0,18.0,7.0,14.0,15.0,GGGGHADGCGCEEEDEDBAAGBCDAEABAGAFFFDBEFEAHAHBDBDBDBGHAACDHHGHGHDHEFBCDCHCHDEEBEBDADABEFECCGHGHFHDGEEEADBEEHC,False +87,9.0,13.0,17.0,12.0,12.0,23.0,13.0,12.0,EHCHBDDCECFCFCFABABGBFDFDCDHBGDHDGBGCGCGCFCDHEHEFCHGEAFBFBFDFHCEBAFEDEDFFGHCFGBGFGCDCEBGFHFAFBEEEBGFFCFAACAHAHF,False +88,6.0,3.0,0.0,1.0,3.0,3.0,5.0,4.0,GBGAGBHAGAGFEBEFEHHAHAFAD,True +89,11.0,11.0,12.0,15.0,16.0,12.0,7.0,10.0,BHBHDDADCGCAEHHDCEAFAFBFCDEDECBGFCECHAHGCAEDDBDEAFAFHFDCHEBEGEGADBDBHEHDFGFGFDECECECAAEBEBDBFF,False +90,18.0,21.0,18.0,8.0,15.0,18.0,18.0,10.0,BCBDGCBCHGHAAFAFEFAFDFHGGGCCECEHBHFCADAFAFEGBAAAGAFBEBEBEGCBHBFADAECDGHGBGECCBCBABHFFDCEFEHGBGBGBEFGABCBFBDBEEAHACGCGEGFCFCFDA,False +91,21.0,22.0,23.0,29.0,25.0,21.0,20.0,16.0,EDECECBBDBGGGDHDFCFDFAFGBACHDHDADFDHBEAACACACEDECEDGDGEGEGEDEAFCFEGGBEBGFGEDECGFAFAFGHEDFHFCFBFBDEDFDGBHEADHDCCFBABABACGEHAHFHCEGEGHBHDACADFCCHBHDCDCFBHAGDBABEBFBGCDBEBCDDADAEEC,False +92,22.0,26.0,23.0,24.0,20.0,30.0,22.0,18.0,ADAFEGHDHFFFFDFECADDDFHBHDCBFAHCHCACHEGFBFBCDHEFEGABAFAEBGBFFFBFCFGBHBEBAACAHAEDEDEGCDCDCDCGHACFCFHFHGCFCEHEHCGCDCEFGDGBGBGEGBABGBGCCABBBDBAFGDABFBFEFEDADBFEFDBHGHDFEFECBAGGCGADDDGBHAEA,False +93,2.0,2.0,1.0,3.0,0.0,2.0,1.0,2.0,DBDCDGFFAHAHB,True +94,18.0,8.0,12.0,13.0,10.0,9.0,12.0,11.0,HHFAEHCHCHCDDAFACACACGGFEFGCHDEEGCGCGFDDADGDFDEBHCDABGBABDGAGEEBAFABGBDAHAFAFADADEHHCHCBGEAEA,False +95,4.0,5.0,6.0,3.0,5.0,4.0,4.0,3.0,AHBFEADADAGFHFGGCBCBCBCFCEHEBDCEEG,False +96,6.0,10.0,15.0,4.0,14.0,9.0,14.0,11.0,ECECEGHGHEHGDACGHHHFGFGCCCGFEEHEAAACCHCFCFEGEDHFHFDFGEABBBBEBHGCGBEBGCACBEBEGCCDBFG,False +97,3.0,4.0,3.0,4.0,3.0,2.0,2.0,6.0,BGHFHDHDCDBDECAHAHAEGBFBHCE,False +98,14.0,9.0,9.0,12.0,16.0,15.0,11.0,5.0,BGGACFEGEGEAFGFGFGFAADADACBCFDADGEBHBFDFGBBDCGAFAEEFECHCDCBFEAEAEADADCEBDDHDBGEFCHEHEFEAEFF,False +99,24.0,22.0,16.0,19.0,18.0,22.0,22.0,17.0,BABDFDEDEDEHAACABAEAFFGBHFGAHDBCAGADEDCHBBGEGAGAGAGAGFGABEDEDEFCBABDBECECEAGFGEGBGACBFEHEHAHAFBFBCHEFGDADAEEBCBHHHFHFBAGGGFFFFGHDCCHAHBCBCHFGDBCCAFBDGGFDHDFDFDC,False +100,10.0,7.0,6.0,7.0,6.0,11.0,8.0,15.0,GGHGHGFEFDCHAHFHEHEBACCBCHFHFBCBEBFFEFHAHGHDAGADAEGBGHHBAAADCFHFDADFDH,False +101,21.0,23.0,9.0,23.0,25.0,21.0,22.0,21.0,EEEEEACAHEHDDADHFBFBAHGHGBGDGFECGBBBBFBFEFHFGFGFAEHDHAHAHBHGHFBBHGGGGGEHDDDDHEAFBHHDEFEHEDDGBCDCHBGDDFFCAHADEDEGEGEAABBEBDFGEBABCDFEACFDADAGAGEGBAFABHBDGDCEEEAFAFBFC,False +102,1.0,8.0,5.0,3.0,5.0,5.0,6.0,8.0,HCGCHDEBGFEFECBBBFBFGHGHGDGBAHCFCHHHEDEBB,False +103,29.0,22.0,27.0,17.0,23.0,16.0,31.0,26.0,GGHCFGEBEDGCCDEBFFFEFHGCDCBCBCECFCHCHCHGHCEGAGCECABHEEEBEBEGAGBBBABABFBHBHDHGGDADCCFAFEDECEABGBFAFHDAGHGHADEFGBDCHHDEDCHGABABFGDEAAAEBGAAEGGGGFGHAHDBDCCHGHBDGEGHGEAEACCHCACAHGHGHAHDCACAFAGAFA,False +104,7.0,6.0,18.0,7.0,11.0,12.0,24.0,18.0,GDGEHCGGGEFECEBECGCGHGCFHFHFHCDFDFGACHHHGBGHACDCGAGADBCAHECACGHGHBBCFGHEDEFEHGHBHGGCGCGCHCEGGDGEAFFHFCF,True +105,16.0,23.0,21.0,18.0,22.0,17.0,10.0,18.0,ACEGEHEHAFACDCDCHFBFBGBHDFFFCAGHBBBHBHFABABABAHEGCAEEEFGBGBADGEBCDEHEBCFCHBHEFEBDDDDDDDGFEDEFEHAHBCACACBDBDHDCBCEDEHEGCCFEEEDHHAABCFCHAECBCBFFCFG,False +106,9.0,10.0,12.0,6.0,8.0,7.0,13.0,7.0,FABABHCEGEGBGBGCCCHCAAABGEGDGFGFAFCBCGCEHDCCAGHDHCAEHFBFAGBGBGHFDCDBEEDE,False +107,17.0,15.0,17.0,17.0,16.0,26.0,15.0,17.0,EFBHGEAFDGCGFGFGDEEAEGBDEFBGGFAHHCAFAFHBHBDGDGEGEGDFFFDFHHHAHBCDADBCBFGFCBCBGBFEHADAHCECFCECHBFFFFCDEDEDCDEFEFCHHHCACAEBCGAAAAHADAFHFBDBCFDF,False +108,20.0,24.0,27.0,23.0,19.0,28.0,19.0,18.0,AFAEGFGFGAHFCFEHEGDBBBEBEBEBCDDDHDFGFDCDCECFAFAHAGBBBEBFDEBCBAHGFGAGABDBEAGFCCCBEBHCDBDFDFBBHCHGGCDCDFHEHECGCFFFADAHHHDCDAEEBFGAEHCDDGACACACFCBEFFHAGCCCCEFEFCABDBFFFGHCHDHDFDGBGA,False +109,9.0,16.0,17.0,17.0,16.0,16.0,12.0,24.0,EGDDDAHBEAEABDCEBFFHFHFHCDGHAHCCFDFDFDFBBEBFBFEHGHGDCFCGHGHGCBCEDHBCDHFHFBFGDGACCCGAEBHBABCHHEHBDDEHEDEDEGEAHDHCECFCFCBHAHEGBHH,False +110,5.0,7.0,7.0,3.0,11.0,14.0,10.0,14.0,AHEHDHGFEFGCHFGFBBCAEFEFEFECEHFHBHAHFCBGFABHBEDEGCGFDFACGCGBFEFGHHHHEHG,True +111,20.0,16.0,22.0,22.0,11.0,17.0,13.0,10.0,ACAFFCDCDCACBFAFGDAACDCDEDEFFCBHDGDCDGDEABFEAADDCAHHDHEGACEFBCBCACACABBHDHDHEHCAAFAFCDDEDFDFBFCFBFDEDFFGGAGCCBEBCBHBAGGGGGEGACBHBDB,False +112,26.0,22.0,28.0,29.0,20.0,26.0,21.0,19.0,GCDCBAEHEHGGFABGFFFFBDBDBHCHCHAAADGFCBCDCFFFDCHCECEDEAFBFEFEGGCDCDAEAECFCEEACCBABGFDABADAFHBHFEFEAHAEADFCFHHBHAHAGGDHCCCDHBCADABHBDCGHGAGAGDDDFCAGBCBDBCFCFEHEDEBGGFGFDBCGAGDCDEDGDBDBEFEHAFADD,False +113,4.0,0.0,3.0,3.0,1.0,0.0,3.0,3.0,HAHADDGDHAGAECCCG,True +114,15.0,25.0,14.0,19.0,17.0,16.0,17.0,18.0,GDGCHHEBEBHBEFAFEFBFHFBGHEFEFEBAAAGFGDDFDFDFDBDBDBABABDHCBGDHCEBBGBCBEBAGHCHBEBGHEHEHEACACACACBBGGFGHCHDGBCDGEFDFDBEHECDGBCEHAHDHACFGADFDBAGD,False +115,4.0,7.0,3.0,5.0,3.0,0.0,6.0,6.0,HGHBHBDBABACEGDGEAHBHADGEGCHCBDGDB,True +116,18.0,19.0,11.0,27.0,26.0,22.0,18.0,28.0,FDFEHEBGBGBCFDFDFBEGFABHCHEEFAFAFAFBDHEHEABBDCHCDDGEHEADAFAFBHHCHBFBEDHGHGBFDFGECHHABDEGECEDADEHEDCAHAGEBABCDCDAHEDEDEDFFFFFBFHGAFEGEGDHDHGHGHGEDHDGEGDAHABBHHDHBCDADHEGE,False +117,9.0,10.0,11.0,5.0,12.0,11.0,5.0,12.0,HFBFCFBAAEABGHCHAFABBBBCCCHCECECHCGEHEHEHFHAHCEDDFDCEEBFFFFGEBEAFAHDGBGDEHA,False +118,1.0,8.0,6.0,3.0,6.0,11.0,9.0,8.0,BEBFGFGFBFBGBCDFEHBHAGEFHGDEFBFHHCGCDBGFGFGHCHFHCECE,True +119,16.0,21.0,23.0,14.0,8.0,20.0,24.0,21.0,EEGFBBADAFCBHFACCCFCFEFDGAFHFDABHBCGHHHBHGHCHEGCAABBGDHBHBGFGCGCGCGHFEFCFGABAGGCGAGACFCBCBHBFCFADHDHGHGFDEBEGCGCDBHBEAACHDDFDCDCFBFBGGGGCBHDHDHFABA,False +120,23.0,16.0,16.0,25.0,12.0,20.0,24.0,21.0,DFHFBBDGFFEDCHEEGGGEEADAGAGDBDAABFDFCGDGAABABABABACAGGHDHFACECBDDFDHGHGHBCBCAGFGBGCFFFDFDCGHGDEEHBCDCBHBCFGFDFDHAGCHHHHHGAFADDHEHEAGAGAGHCBAEAEDCDADCFGFDHDHF,False +121,19.0,17.0,15.0,20.0,28.0,24.0,23.0,17.0,DCDFFGAAFFFBGAGDGCACHEHDADADFEHEGGFFEFAABBHGGGFHEHACACBEEEHBAGAGFDFEBEGEBECECDCHBHGDGBEFEAEAEAECCGCEHBHCFFGBDBDCDAEEEAEFFFBHAHGEDEBGFGFGHGBGBDFDCDHEHDDDEBAFDFEGCFH,False +122,24.0,21.0,31.0,19.0,20.0,33.0,21.0,17.0,CBDGEGCBFGFHFHFEFBDAECCCBCBGHDCCCAFADHDHDEDACBDBGAHABFDGEGCHEECECDAFBGBGBFFFFHEAECHFHFHGEEBCFCFDGEGFFFFGCDCGBGBGFFBFBFAAAAAFGBAFABECAGEGBGFHFCADDCECHFAFADAHFHEDEHCFBACAEAEFDCCCCCBCHDADCG,False +123,23.0,22.0,33.0,26.0,18.0,14.0,26.0,19.0,DGDGCACABHFCADADGHGEEHGACAHAGACEDEDEDGDFCHDECFCBCGHGECHCHBEEDEDEDEDCBGBGBABCBCBHAGDGECAGDCCCFCDCFHFDABECGBGFHBBFBEBEBACEDBHHCCGCDAGGGFCCCGDDFCBCBGBGHGHGCBADHFFAHDGAAAAABAFDHDHCFCEAD,False +124,14.0,14.0,13.0,14.0,9.0,17.0,19.0,18.0,DCBFBFAFAHBHGFBABECACGGBGCGCFAFHHDGDGEBDADFFHHHHDAABHFFEGAGFDBGHGAGBGHFHFGCHCDGEGEFCGDGDCDCDCECBFAFCFHAHEBEGHBEBHHADAD,False +125,22.0,17.0,18.0,14.0,19.0,23.0,19.0,20.0,AFFEGCACEHAHBHFHECADBDEDHDHDACHCBCBHFDDAGHGHCECEAEAHBHGGCEAFAFBDGFFFFBAGAFAFHHCGDFFAEBBABADADBCGHHHGACACFCFDFBCGHGEGEGBGBCBEEAFHEBBGGECEFECEHGGEAFDFDFAF,False +126,2.0,2.0,5.0,1.0,2.0,0.0,0.0,0.0,CBABCCCECEAD,True +127,9.0,13.0,13.0,20.0,8.0,15.0,15.0,18.0,GGEFDFEHDHDHBAGABBBFFHFCFHGHGHGHGDADHDEDFCEDAGAGCBDFDHDHCBCDFDBHFHGHFBCGDDDDDABGHDHCHAAECFBDBEBCBCEGECCFFHCGAGF,False +128,26.0,16.0,20.0,13.0,15.0,14.0,8.0,14.0,AFAFGCBFDCCGCBCACACAFACECBAFAFDBBABABHECBGAHADEDCBADABABAHEHCHCHGECDHDHBHBAEDEAEAHBGFAHBBCACACAFEDCAHHEADGEGECEFFFCGHDFDEAEFFD,False +129,3.0,2.0,3.0,1.0,2.0,1.0,0.0,1.0,AHABFBEAECCDC,True +130,3.0,10.0,5.0,11.0,10.0,4.0,3.0,9.0,DBGBHBAEDEBCCEBAAFHHDHDCBEDHBHBHBDECECEDDDFDGDFBEGEHEHF,True +131,18.0,19.0,23.0,22.0,20.0,20.0,15.0,23.0,FGBCAABCBCDCDCBBAAADCEGHAFDFEBHBHAHGDAEAEAHGECHCDDFDBEBHHHDBCFCABFHHHABFHHEGEHBAFAFCDCHGEGEFBFEFEDEHCHCHDHDGFAFEBEBGBGFCDCAEDEGFFFHFBEAGACFDDDDHDCCCCDCDGEGBGCEH,False +132,27.0,13.0,16.0,13.0,20.0,12.0,27.0,15.0,HAACDHGHEBFFCDAGADAEABAGHFHDHCCAEHFHBGBECGGGGAGABACDEDCACACFGFGFHBBEBHGGGDABGGGEDECEAEAEAFCEGBBBAGAEAEABHEAEGGGCEHFHDGAGEDEDFDHDEAAGAHAFFGCCCCG,False +133,5.0,7.0,9.0,1.0,6.0,7.0,8.0,7.0,BGCFEBHHHHACABFBFHFCFGGGCCECGCGCHAEBBHFGCGDAEAEBEF,False +134,14.0,15.0,11.0,16.0,21.0,17.0,16.0,20.0,HBHDHFHDDEFEGEFEBGDFDFBBHBAGEGCFHBHDADHHFAFAHECEFADECEDDDBDBDACBEAFHFHGEGCGDECECBAGACHBHGHFHFHGEGFFHEHCHCEGEGEAEGDGEABDBABFFGECABA,False +135,8.0,3.0,1.0,2.0,4.0,6.0,9.0,3.0,GFGEGHGFEFGCGDBAHAFDEAEGBGBAAAFAGAHF,True +136,14.0,29.0,20.0,23.0,25.0,22.0,18.0,18.0,DGDCEBGFHDBFBECHFEFBDEDCACGCGHEFEFEFAFGGGDCFGFHFHAHADEBBCBCEEEFEBABCBEBACACBHHCFCEAEAGBGDCDBDEDGBACECBHEHBDGDFDGCGAFEFDBHBEBEAHGFCFBFBHEDFDGDBBBBACDBDHGBEAEGFCHBHEHDHDFD,False +137,3.0,5.0,1.0,6.0,8.0,6.0,3.0,5.0,FDFDBBBEDEHEHEFEACFFGDHDFGBHAEAEBEGDH,True +138,17.0,19.0,28.0,23.0,19.0,29.0,14.0,27.0,EEHFCDHDHBAADFECECFFFCDGBAHAHFHBCDDFDGDADBCAAHABAEGFHFHDHDEGCGHGHCFDFEFGBHAHBCBABEEECDCDEHFHFBABHCCCACHEACHDGDFHFHBHFGDGDGDFBCDCGABFFDFECHCFFFHFCDGEFCACHCHCHEGACFCFBFEEECEBBBBD,False +139,18.0,10.0,15.0,7.0,19.0,9.0,15.0,15.0,BCDGAGEBBAAFCBEFDFHCAAHABFEADAHGCCCACEDEDEDEDEHCBCFEHCHEACACHGGGGBGEGFGFEHECGFEAHGHEHEHEHACAFBGGABABHGHEAEAC,False +140,12.0,11.0,10.0,15.0,15.0,9.0,10.0,21.0,GGDEDEDHDABGBDCAFADADEEFHFEEBBAHECFCAHGHGHEBBCBABAFHHHHAFADHECEGGBGECECHBHECFCDDDEEHHHHHDHDHDHFACGDABFG,False +141,6.0,7.0,16.0,10.0,19.0,4.0,7.0,3.0,GAGEECEDBGBGFCFCHCFBDBDECEAEDBDCHBEEFAHAEAEGCBCEADDDDEGCCEEEECCCECDCGCEE,True +142,17.0,14.0,17.0,18.0,21.0,18.0,15.0,9.0,BADAGADHDGDGFHFAFDFGEEDDDADCCCGGECCCGEHAHAHEEEEAECFCDHDFABABFBGBCACEFFDADAEEHBHFDFCBEBGHGCFCDAGFDBEFFGFGEGCBAEDEBCBAACDCBEBEFEFEG,False +143,1.0,3.0,4.0,4.0,2.0,3.0,3.0,3.0,DHDCCGCGAGHBBFEFCFDHDEB,False +144,3.0,1.0,7.0,1.0,1.0,3.0,7.0,2.0,CDCFHGGFBCCCCGAGAGAEHFGCG,True +145,3.0,5.0,7.0,4.0,3.0,11.0,6.0,3.0,DHGEGBGBGCCFDFAFHCBEBEBDFCFCFGFCCAHFFFDGAF,True +146,4.0,13.0,6.0,8.0,6.0,15.0,9.0,3.0,FABGBGFGFDBBBCGEEEEBFGCBFBDBCFDFGFGFAFECCDDADAFBDGHGBFBFHFEFHCBD,True +147,16.0,16.0,22.0,23.0,21.0,20.0,35.0,29.0,FBFEECGAGFGFGHDHDFAGEGEHFHFHFEGHGCEEAHDGDEHEGEFHFCFHGHBECDBDBHHGGGGGGCBHAHACAHAGEBDCEAGGHGHGEGEBDAHHHCHADGCFBFHGBGCHDFDFDGHCBCHHAGBEBDACHCFFGGGDADEEAGCEDEDCCCGDFDBDGFBFBGBDEACACDCDCH,False +148,16.0,20.0,20.0,23.0,21.0,16.0,31.0,18.0,EBEHGGGHCACFDDDDDAFCHEGCACFCFDFAGADEGGGAGEECEGEGEGAFFDCBHBHDHEGCDCGBGBGCCCCCBDGEBCGFHCHGHAHBBCEGEGEBFBGAHABDBDAGAGFGBEEEFEDGDAFCHBABGBADADEGFFDHDCFGGDHBFBDEDEDGHHHBH,False +149,3.0,7.0,4.0,6.0,10.0,7.0,3.0,5.0,EBEHEBEDCFCBBADCHFHFGBGBDEEEECHBDADADEFFFGFHE,False +150,6.0,2.0,7.0,6.0,2.0,3.0,8.0,0.0,DDDCGCADFDFGGGACACAGBECGGDGABACFCE,True +151,5.0,2.0,2.0,0.0,5.0,4.0,2.0,3.0,GAGAFBFEFECEFHABAEHEACH,True +152,14.0,12.0,9.0,7.0,12.0,11.0,10.0,17.0,FDHDFEHDHCFCBCDGHGCFFFBFHACCHBGAGAHEHEBEAADAHBGBFBFBABABAHAHEEAFHEHBHEHABGGECDCECEAGDHAHEFGG,False +153,19.0,24.0,27.0,19.0,23.0,23.0,26.0,24.0,CDCGGGFAAGACHFHDHDHBBCCHCGFAHABGBEDHBGBGBABADECFFFFAGGCHDDGDGCGHGHGDCFHDHAFEFEFEHDCCGGBGEGAAFCEEDFDFGBEAFHFCGEBCBHBFBDCDGBCBEHADABCHCHEHEHBHDGFGAGEGBBEBHDEEHAHAEAECCFFFCCCECECEFBFBDECBA,False +154,13.0,10.0,11.0,9.0,11.0,8.0,12.0,4.0,GEAEAFAGADADAEFCGCGCGCAFBFBEECEGADADACBGBCHHBFEECACBEHEFBFBDADEDBCGGGBDFHCAGGD,False +155,23.0,15.0,20.0,21.0,22.0,13.0,16.0,23.0,FEBEBEBFDHDHCCDDBCBEGFDFGBHCHFDAEBCBFHAHGHDADCBGDHDHDFCAHHHDBCEHDFDAAECDCDCBCAFEEEEEAEAGACHCEGEAEGGGGAEABAFAFHHGEAAACHFHAHFGEAEDEDEDADHDBCGAGACBCHHBGGCHC,False +156,1.0,2.0,8.0,2.0,1.0,1.0,0.0,3.0,CCCCCHCHBACDCBHEDF,True +157,11.0,6.0,5.0,14.0,10.0,10.0,2.0,6.0,EFAHAHFBFGGABADFCBEDEDADAHAFAHBFEDEDCDEDEDEDFFCBEDFDFBACDDAEHCHA,True +158,15.0,22.0,16.0,16.0,9.0,21.0,17.0,9.0,CFCFCAEBDGDHBBFBHCAAGFFFAGGGGFGHCHDBDBECECECFHBBCBAFHFDFBCACHCAAAEFDBDBCFGAADADAGGBBBGCGBGCFBEEGHGFGFDFDFABABDFHFDBDCEFEBGDDB,False +159,3.0,6.0,10.0,6.0,2.0,3.0,4.0,5.0,GGGFDFDBCBHBHBCCHCBCEHHFCACDCBEDDDACGCA,True +160,7.0,12.0,7.0,6.0,6.0,8.0,8.0,5.0,AEFEFEBCBADCEFHHCHGBBECAABFBFBDBGBHECGDADADGBGAHFFCFCGDGBGB,False +161,25.0,18.0,13.0,27.0,15.0,21.0,17.0,28.0,HFHGDDBDFDGHGADHGFBHGCFDAECCHHEFEFEDDBEBAHAHFHFBFHAHDFDFAEDFBBCEHADGFGAHDGDGDGDFCBCEAEBCBHDHDHAHAEADHHFHFHEGBHEDABABACDCAEFDDGFGAGABAHDHDGDGDBHBFAABAGAECECHCACBFAFH,False +162,18.0,23.0,16.0,12.0,17.0,23.0,24.0,31.0,AEABABCBCHCHCFFFBHHEGBABDDDDDHHFHEECFCFCBEDDBHBHBCGHDFAFHCHFGCHHHHHHHCFGFGEHDBAAEGGHEBBHGDAHFHBHBECGFAFBGCAHEHGBBFBDCHHGEAEHGFFFADGEGBGBGCGFFCHGEGEGAGAFABABAEAEGFGF,False +163,24.0,23.0,17.0,16.0,25.0,31.0,34.0,30.0,FHFHFEFGFBAEHHHDHDHFGGDGDGFGDHACAFGDGDECECHCGAHAHBBBBBFFFCGBGEFFHFEAECGGBBAGABABAFHFHECGDECFCHDBACDEHBFBHBFEFDDGCHBHGHGHBEAGFGCEHFBAHACEHEACFCFEAEGEGAGACFEAEBGGFDBDBGEGECEAHHHAGBGHAFDFAFDFGBGHGFGAGHEE,False +164,16.0,17.0,19.0,27.0,19.0,29.0,35.0,19.0,GDGBCCGCAFBFGFDHGHBFAFGFGDDECECDGDCDFHFGFCFHFEABACFHFBFHEEECEDFDEDGGGDGCCBBDBFBABFBGDEDEGBHBDDDGGGGCFHFGFGFHFEABBDCDCHCGGGDGFGEDADHDECEAGAFAHEHADAFFGGGCABEGHCAEFGFGAGDDHDHBCEHGAEHFH,False +165,10.0,7.0,7.0,12.0,6.0,6.0,5.0,8.0,DGFFDCDCDAEGDBDCEBGACECHCECDBABDEAHDHGAAHHHFHFBFBGBHDADADAFAE,False +166,17.0,18.0,17.0,16.0,20.0,19.0,17.0,15.0,CACAHAFBDAAADADHBGFAFDGDGDGHHFHFGFGFHHCAAEBFBFCFAHEBABEEGEGEGEBAHGDCDGEBCHEGDGCFCEEFECBCFHBHBHBADDFBFBGDCBCFFEGCAEGEFBACDCECECFDDADEEEGHBHB,False +167,15.0,4.0,11.0,15.0,21.0,12.0,17.0,17.0,HHAHDEDGHFHEHCHGFGFCECEGEACFGDGDCDCHADCEHEGGAEEBEBFHHHCHCHCFDAHAGDGFGDDHEEGCAEDEABAEGEGHGDDFAAEFGAGAEAFAFDFEEBED,False +168,8.0,4.0,9.0,2.0,9.0,7.0,3.0,7.0,ECECBCHFHCGFGFEEEHEHECAAHAFFBAEAFHBGAEAHDBDACCCFC,True +169,16.0,14.0,9.0,11.0,11.0,11.0,12.0,11.0,DFDFDGAGAGAGFGHHACBHBHGFFDFGBCEAHBDAEADACCECAAEABBHEAEAEDEDCABABCBGGGGFFACHHBDBFFDFEEGBCDHEHBHB,False +170,4.0,2.0,1.0,1.0,6.0,4.0,5.0,2.0,GGDBEEEEBEAGFFCFGFHAHAEAG,True +171,28.0,14.0,20.0,10.0,8.0,25.0,20.0,36.0,HCHCDCGCDAGAGHGBABAFAFCFAFDFGFGEGHFEFHBHGFGCHEHABFGFHHHCFDACHEFBHHHCHAHGBAADCHBHBFAAAHHHFEGCGDAHAGFBFAADAEACFFGAEAGABFCHCBFDEAGAHBHBAAHHHFHFHCCACGHGHDHDHCHCFCBGF,True +172,3.0,11.0,4.0,4.0,5.0,7.0,5.0,5.0,BBBEBHHCCFEFGFGHGBBBGBDFAFACEHFGFHDBDBABCDEE,False +173,8.0,13.0,6.0,15.0,4.0,10.0,15.0,7.0,ACDCGBGFFFGEGBGFHBHDADHDFGBGBGHCDAGGGCHDHGADDDDDDEBBHBFBFGFAEADGCCBDBDGAAEFBFB,True +174,10.0,11.0,8.0,10.0,13.0,7.0,14.0,11.0,GCGCGCGFGEBCAAEEHEAEHDHDGAADADADFBEDECHCGGGHGEEHBHAHABFBEBHFADGDHEECHBBFBGEGBGDCFBFD,False +175,23.0,12.0,12.0,24.0,26.0,34.0,26.0,24.0,CDBFHAHBGAAFEGHAFGCAFGFGBGBEBEAFGDGDFDADCFGEGBFCHABFCGADHFFEFHFEFEFEDHFGCGEGEAABEGAGHGEAFAFAFCFAEDEDEDHDHDHFFFGFHACEFHHHDHDAGFDFGEGBGDHDBABAFEEEHEBGFGEEAEAHHFDDDGHGHDFCFCACHDDEDEFHC,False +176,18.0,8.0,20.0,16.0,15.0,17.0,11.0,11.0,FCFBECGAFAFABAEEEEDCDAECEDGAAADFHBDBECEHEABABCDCHBGEHAHAGAECHHHADCCCCFCDCDAGCFFEEAFAFGDDFHFHFHDBGGDGDADFGCECFCGCDCFF,False +177,13.0,12.0,13.0,12.0,6.0,11.0,5.0,9.0,DABFHGHCBDBDCFFGABAFEBACAHECGDFFHFHFDFEFCHCBCBAECGCGCHEAEADDDBDADAHHBACABACDCDBFB,False +178,7.0,14.0,10.0,12.0,19.0,22.0,10.0,9.0,FDECFBFDFDFHFGCEDEDEFHGBACCEGGAEBEGABFDFDFCHGHFFEDBFBFBFEGEHADAEFEFEFEABCFHDHDAECFCGBFBGBFBEECECDBEBHGH,False +179,2.0,2.0,2.0,1.0,5.0,4.0,1.0,6.0,HGFEHEHEFEDAFHFEABBCHCH,True +180,2.0,5.0,1.0,3.0,3.0,4.0,0.0,0.0,FAADBBBBEBEFEFDDCF,True +181,6.0,7.0,5.0,2.0,1.0,4.0,3.0,6.0,BHBDBAAGAHCHFHACAHEHBBBFCFCACGGDBF,True +182,2.0,3.0,10.0,6.0,8.0,6.0,4.0,4.0,BCBCECEAEDEDHCCCCHEHEGDGCFFFAHGBFFFECDDECGD,True +183,27.0,20.0,35.0,20.0,19.0,18.0,17.0,19.0,CHCHCFCBDEHBHEHCCCCBDBAADFFECCGCAEAFAHCFGDGAGACABFEAHCBDBDBDACGDEDEDEHEBGDGDCAGABEBEAECEGAGFGCABFGFCEAEAGACFCDCFFGFEHBDBDECACAFHBHCHBHBFAHDBCADHEHACAGDDDGCEBFBFCCCCGAHCFCACAHH,False +184,21.0,29.0,29.0,14.0,13.0,23.0,22.0,20.0,HBBEFAHAHDHCHCGCBCAFABDDHDFAAADBDBEBCBCBEACGCGFFBFAFHGHFCFEHCHDADFCFCEDBGBCCFCFGFHCHCACBEAFBECFCDAGGCGFGHGFGEGACCDCBHBACGFGFHFBFGEGBCHCBCDEBBCHGGBGBDDFAAAEBEBABHBABHGEGBHA,False +185,16.0,21.0,7.0,5.0,16.0,12.0,3.0,15.0,BBBHGHBACDBEAAAFDHEHAGAGAEEEHHCAEAFBBABFBCECAFAFBFHFEDABBBFBEBEBEBACHFHFHDHBFEAEBHAFCHEDECEHBHB,True +186,26.0,34.0,20.0,22.0,24.0,21.0,26.0,17.0,HFACACHCBBBBHBGBEHFHFEAHAEAEFDBHECAHAHDDBGEDCBEGGFGECAAADBEBGCGCFCFCFBFBFBAGCBBABEHGCGCGFGBBCHCEDAHBCEAEHDBAHGGDDDDHEADDDDDFFGBGAGBGBEBABDBDGDGBFBDBDBDHEFEFCFEAAFGEBCGEGBFFGCGAABAGCHEEEAFAEA,False +187,3.0,5.0,0.0,1.0,1.0,2.0,2.0,4.0,DEBGHGAFBFHHBHBABA,True +188,8.0,11.0,10.0,11.0,8.0,19.0,14.0,12.0,HGFBFHFBFGGAHDDEBAHFHFHFCEGFGFGFGBGEGBCEEAFDBBBHFHDBDBGACHCHFGCGFGCGFBCDCDFFAEAHAEFDFDHAECDCD,False +189,24.0,32.0,23.0,32.0,21.0,21.0,20.0,22.0,BBBABAEECDDDEDEHEBECEDEDHHHFHFDFHCDAHAHDBGBGEGFGFGFGFBAGCGDFBFHDHBBCHGHGFAEBEDCAAGFDDADADBDCFGHBABDHECBDBAAHADAGCDCBABABGBHDCGCBCGFEBDCHAHCCCFCFEBABHDDBGBHHCCCGBABDBCEEGHAFEFEDDBAFFFDFDCEAEAEGDBD,False +190,13.0,10.0,11.0,9.0,7.0,16.0,9.0,11.0,AGCHAGCBAHCBGBEBEACADADHDBFBDDAGEFCFCBHDEFEFHFHGHDFGFACAEFHAEAGGBGFCFCFHFDFCFCBBFDAHAH,False +191,14.0,3.0,6.0,9.0,14.0,7.0,4.0,6.0,EAEFDGEEFCCCFCFEAAAEADCDAEAEGGAFHHHHEAAADADEFEBDBAEGECEADFDHDHB,True +192,6.0,4.0,7.0,3.0,3.0,3.0,1.0,4.0,CFGEHCCFCBCEAEHCHDADADABBBACAFH,True +193,29.0,36.0,21.0,12.0,18.0,14.0,23.0,24.0,BBHFFFCEHEGEHDHBGBHBHDEBHBHBEAEBDBFHFHEHABADACGGGADBBHHFBBBAAAAABECDCACHCAGACFCFAEAFAFAGGDAEBDBHBEBGACBHFAFGFGBBCAGGBGHDCBBDGEHEGEACACACEBEBCACAEGDGHCBDGHGHBBABCCHCHCHGBAEAGBFBG,False +194,6.0,3.0,5.0,1.0,2.0,4.0,8.0,5.0,HBHGGFCFCACAEABGEACDCHBGGHGAGAFHFG,True +195,3.0,6.0,4.0,7.0,9.0,15.0,5.0,10.0,HAHEHFGFHHGHGFFCFCEDEFEDBGBDEDACBDFHEBFHFHFEFDFCFDFABEBGHFE,True +196,2.0,2.0,8.0,2.0,3.0,5.0,4.0,4.0,CCECHCDCDCEBHCGEHBHGAAFFFFGFGC,True +197,0.0,3.0,4.0,2.0,1.0,2.0,3.0,2.0,DBHBDFCCCGCGBGEFH,True +198,9.0,8.0,9.0,4.0,11.0,7.0,12.0,11.0,AAAFADHGGGFGCBCBCHEGEFEHDCABDHGEGEGDACBFHFBEBGBECEHAHAHGBECFCGEGAHEHCHF,False +199,9.0,8.0,10.0,11.0,7.0,10.0,5.0,6.0,ACADDFDHDABGCDEBEHAFFBECECDBBABAFAFAEAFHDDDHCCDCGCGHGDGHFCBCBFFEFE,False +200,15.0,9.0,5.0,13.0,12.0,23.0,15.0,22.0,CHGFEHBDGDHEHAHDFDFAEBDAHEFEFEGGGGAAAGEDAHGHGHECEGFGFGAGBFEFAFBFBGBDFAFHDHBHFHFHGDEDHFFCFEDBDHFFFAAHBHAHFCFDHHCHAA,False +201,8.0,4.0,6.0,6.0,2.0,3.0,2.0,2.0,AGCFBBCBCDAHABACEHDADADCDADAEFGFC,True +202,15.0,30.0,30.0,30.0,15.0,29.0,25.0,23.0,DFBBDGHBCEDBFBHBHBCBHEGGGEBEBHHEHCFFHFGBHEGBDFDFGBGDFDFHCEFHCGCFDHDFDEHADADEBCFEFDFEFECDAAHFGDDDCACACACACDBABGGEDAABBBGCACABFBGDCDAGGGGDCDFFFGFCBBBDBDHECGHGDGCGCHCHFBFHHHDHCEBFDFDFCFCGCBCBCFCDABHCG,False +203,14.0,19.0,19.0,3.0,12.0,14.0,16.0,22.0,CHAEADAHBHBHBHBGGDBHFHEAAABCBGEFCCHFEBHCHABABFHCCCHBHAGAFCFBFAAAHCFCGEGEHEHEHFHBHEGFGHBEGGGCCFGFGCDAECGCBBGBFBCHCHCGBFE,False +204,9.0,15.0,19.0,11.0,9.0,19.0,20.0,15.0,FAAACCHEGCGDGBHDCCCEBAHDGDFDBDBHCFGFCFCBCBFGFGHGBFBHHHFHEGBGBCAEBCCCFCFCHGAEFEAGCDHGHGFGFGCGBGBGFDACEBFDFDEHEDGHABFHF,False +205,20.0,16.0,16.0,34.0,30.0,20.0,29.0,29.0,CDCFGDGDEFHGHEHEGGBGBGBHBGEFECDCEBGDAHGCBDDGDHDHEBEDDDDHAFAFDEGCHEGFHFADBEEGAGDGDHFHBDEAEAHAHDDDECGBADEHEFEFDACAGEGFGBDEDECHHHEAEFFBADDDDAEAHHDHDCCFCAAAHCFCFEGHHHHGBGBDCHCHDFDGGEGBFBGHFAFEGEGEAE,False +206,20.0,18.0,16.0,14.0,21.0,4.0,6.0,11.0,ABABAFADEDBAECHGDDAAHEBBDBACECGAAAACHEFEBCDHGBCECECEBEFEAECBCEHEDGAHACADAHACECGDDEEECEHHHFECBCBEBHBDBDBDBAGDBA,True +207,1.0,3.0,2.0,6.0,1.0,4.0,1.0,1.0,FCADBDBGBFEFDFHCDDD,True +208,5.0,3.0,5.0,6.0,4.0,0.0,1.0,2.0,DCCBCDCDCAAAAHDHBGAEEDBDEE,True +209,9.0,6.0,7.0,6.0,5.0,8.0,3.0,2.0,FCFEAEGDADABCBCFGAGCFAFABABCBDHCFDFEFEACBDHEAD,False +210,21.0,21.0,15.0,16.0,11.0,15.0,20.0,12.0,CACFFACCCEHFDBGBGBFHFAGDGDADACGGDGBAACABBECECEGEDHDHCABDFDFDAGHGHGBGBFBGEGBFDFAGAEHFDAHEGABABFGAGEBCCGCHBDEDGBCACFBFAFHDBEBHBABADAH,False +211,10.0,24.0,13.0,13.0,14.0,11.0,16.0,23.0,EDEABACHGHAEGGBBBBECECEBBBAHGHGHCBCECDCBFBHBHFHFHFBBDAGFEBHAHDHGCFAGABCDDBEBEDHGHBCCACFDDBAHHHGBGBGEGEGHGFEFHHHDDBBCDEFGFHDH,False +212,19.0,7.0,17.0,13.0,17.0,11.0,21.0,24.0,FGCAHAHFGEHAAAAAHGDGHGFEEGDHHAEAEDCDFGBGDHDGFECECGGEEHGHGHCFBBHBFEEHGHGHDHFHDHDAAAHDECAAACBCECACAHFDFCCCCCCGGGGGEEEDHBHEFCGDHAHAB,False +213,10.0,20.0,7.0,7.0,13.0,11.0,10.0,5.0,HACBEBEBAGEEHEDAFABBFEEEBGBGBGBAAEBBDDFDFDFHCHDDAFECHBBAFAGGGFAFCGBEBEBEGGBFFCBCBCB,False +214,6.0,9.0,11.0,6.0,13.0,4.0,11.0,19.0,ECECBCFDGEGBHEDDHGEBHHGCGCBHHHHHEHEGACABADHFFGCGBGHDDCEEEEBEFHAECBCHGHGHBHAHAHC,True +215,3.0,0.0,0.0,3.0,3.0,2.0,6.0,5.0,HDFDHEHGGGGHAHAEGEAFDG,True +216,1.0,8.0,11.0,12.0,14.0,8.0,9.0,12.0,GEBDBDCCADDBGFGFEEGEGCDCEFEGEBEDCCFBHCEDDGEHEHDDFCHHHBHBHBCDFDEGEGCHCHEHFHF,False +217,10.0,10.0,22.0,13.0,14.0,8.0,15.0,10.0,DCHGECECEAGHEFGACFBGBECGCAEBEHHAGEGFDFDFHEDDCDBFBABACDDHDBDGCCCGHGACFCFDGCGCBCBGAGACECACBCECGDHEHEHECD,False +218,7.0,10.0,14.0,5.0,9.0,7.0,7.0,16.0,CFCECECDHHHHHHHHBBBHEFCCEBDBABAGDFDHCHGACCHCHEFEGHGDACFBGBCEEEFGHGFCBCHAAAB,False +219,15.0,20.0,16.0,12.0,13.0,12.0,14.0,14.0,AGAEAEAHGHFBFEHBHFGGEEHCFCDADACBDBFBCBFGFBBBCCAEGDGFAACAHBCBCDAFHFHECAFFEGEBCBGGCDCDCDEBBDBDBHHHHHDGAGDCHCAGEGABBEBE,False +220,0.0,1.0,1.0,0.0,3.0,3.0,1.0,3.0,HEHEHFFFGCBE,True +221,4.0,7.0,18.0,11.0,9.0,20.0,14.0,16.0,GGGBFCCCFBFDGCFCFDFHFHCDCDHHHGHFDCAGHCBAEEFEFEFHAEFCHCGEFCCCHCHEHCDCDAGBGBGCDDFDFGFHEHDHFGEGFHFGFBB,True +222,19.0,32.0,14.0,24.0,24.0,23.0,30.0,29.0,EAEAGFDFDCBHFAFADGBHBDAGCDEABDFGEEFFFEEAECHDHBHDGAHHGBGBGBGHCDFDBDBDEDADHFFAFEFGBHBGDCHEDABGBEBCDCHCBFAFBGBAHFHFGEDFHHHBBBBDBDBDBGEGBHEACCHEGEGEDEHECGHGFBHGHCBGAGHGHGEGEGEHAHAHFCCEFHFAGBGBGDADFBB,False +223,6.0,4.0,7.0,6.0,14.0,14.0,8.0,15.0,CEEFAGEBDFAHHDHFAFAHBFFHFCFEHHHHFDEGEGEDEDGAGHDFGBGBEFGFHHCHCHEHECFCACEEFE,True +224,11.0,10.0,13.0,13.0,21.0,14.0,25.0,19.0,CGBAEGEGEHHCGGHGCCBCAEBEGHCHDFDFDFEGBDFDFEFAGDGAGEGCGBHEEGCGBEEGEADACECABEDCDFFFDCAGAGHFHAHGEGEGEGBGBGHHHHHHDABCEDHHFFDHEHEGFF,False +225,6.0,19.0,5.0,11.0,12.0,6.0,9.0,5.0,GBHBDBABHBCBDEDBGBGBEBEBCCFDHDFEBBDDEAEAEAECFGFGEGABCFGBBDHDEFBGBGEEABHDD,True +226,11.0,18.0,23.0,14.0,12.0,26.0,20.0,26.0,EFEFEFGDCDFBHBHADECHHEHEFGFGHCBGACBGACFDFGFCFGFCCCHHHBHFHFHDADFFEBGFFFFFDBCCFCFHFCDGEHDFDBDCAGGHHHHHHBACGCGAGBGHAAAFFCHGBGCADGBBBCGDHEBEBEBEBHCHDHCCCG,False +227,23.0,20.0,28.0,18.0,25.0,23.0,23.0,21.0,FCCBCEFEDAGGBEHCHCHAFCCADFFHFEFAHCHDGCCHAEDEDFDGAGAGAGEFEBEBHHEFEFHFCGDFBGBDHAHBGAHFFFBFCDDADCDEEAGABHBHGHCHCABADABCHCHCDFGHGHBAFFEGECBGADCECGCGCBFEFDFCGCGDEECAGAEAGAGBBBBBCEEAEDECE,False +228,5.0,3.0,9.0,5.0,8.0,2.0,3.0,5.0,DDDACEHGFBCEAECCCCCFCEHEHEHEBCDAEBDHAGAG,True +229,15.0,19.0,18.0,23.0,23.0,15.0,10.0,23.0,HHFHGHEBFHHBCBDEEHCBGBAHAEDEDCGCGEBBDDDDEDBDHDFDEDACCEEDFCEEECBCBCBCDAFEHCFAHBEDACAGHHHHHHHAHGFACACAFBEBEFFFFFDEBEAEGCBEEDADACBHGCGBGDHDHDFDHDEABF,False +230,15.0,10.0,14.0,14.0,7.0,9.0,3.0,6.0,EDADBFADCDCDEBFBFAFEFEDCBADFBFBAHACCBCGEHEHBCCAGDCFFBAAABAGACHCHDDCCCEDHDADADA,True +231,21.0,19.0,19.0,16.0,21.0,13.0,13.0,23.0,EHBFBHBCDAEACABABEHCAAAAAEBDHDCECACAHGFCFBFBDCCBDBDECHCGCAAHHDDCDCDEEHHHADAFBFGFGDGFGHGAGEEFEHBBDBGHAHGHEBCCACACGEDEAABDBCEDEFEHBHEEEHGHFHEHFFGHB,False +232,10.0,11.0,13.0,7.0,8.0,12.0,12.0,9.0,EFGGGHCHBAEHFDFEADAHBBFBCGFGBCBCBCFHFAFAGCGCEBEDCCCHCHDGGGCGCADFEBEBDAFAFAHEFGBHDA,False +233,16.0,18.0,26.0,21.0,12.0,11.0,22.0,9.0,GBGCHBGDHEHDGAFCFCGCBBDDDHHGCEDEDCDBGBEBCCCCDBGBCACBGGEHEDGGAGACFCFCHCGGDGABDCCCGDBDEDEBBCHCDCDBDAGECECAFEFBFEAGAFAGBGAGDDDACAFAFAFCHBA,False +234,8.0,5.0,2.0,10.0,3.0,5.0,9.0,5.0,GAGBBEDFDFDBDGDAEADHGAGHBDGDFDFCGAGACABAGHHHFED,True +235,28.0,16.0,21.0,19.0,24.0,21.0,12.0,20.0,EDHFBEAFADABHFHFCFHFACCBBBHAHDHBADGDBCBDFEFDHHADACBHBEAEDDDGAGACAEHECFCECHHHEABFCFEEHGAFFFADADCDGEEEGEBECEBBCACAHAHADADFFAFAFHGDEEFEBCGCGCGCDCAHBGEEFGADECECAFAHA,False +236,13.0,6.0,14.0,8.0,9.0,13.0,7.0,14.0,FCFAFAFAHAHCDCDGFFEFECEDBCECDCFHEEFAFACHCHCEBGDHEHFHAHBHDHFCGGAGDHHACCBHDCGFGBAAEABA,False +237,4.0,7.0,4.0,12.0,6.0,4.0,7.0,10.0,DGGHBHDDDGDGCGCGADBHEDEDAGFCFEBDHDEBAHAFEHEHCHDBDBHFHB,False +238,25.0,27.0,17.0,20.0,11.0,20.0,27.0,24.0,BGGGHACECEFEAEDBDBHCGDGDHDHBHBHAHAHFBFGCGCAHFHABABEFFDDAAFHFHDAGADFDGBACCCHGHDAACHCHGBEBCCCBDAFAEGHAHGHGEDBDBCBHBGFEAGAGBGBABDHDGAGADFBFGFGCAEBGFFEHBBGDGBBBFFHFBFCDAGCGHDA,False +239,27.0,19.0,14.0,12.0,26.0,20.0,17.0,18.0,CACHFHBABHBABAHEGBDDEBFAFAEACABAFAHAHGHDFEGEFEBEBEAFCDCHABAGEGEDFBGBACAFDCDCAEHEHFHFEEEFABABCGEEEGHDHAHBHDFGEGBAAAFDHECEAGCGEBEDCDHFAFAGAGBGFFCGCEHGFEBEF,False +240,13.0,5.0,13.0,8.0,10.0,9.0,13.0,11.0,HCHAGAEFGBGAGFGCDCAGAECGCGEFEDHGFADADACHDFDGBCBCFEDEFEFBAHHHHHHAAFGCECACBCGEHEADCG,False +241,15.0,13.0,22.0,21.0,14.0,24.0,13.0,15.0,CECEBACABEFHFGBEFDCDBABGDAEADCDHGFGFDDDFDFDFGFEFGCGEAHGHGHCFCDABFEHHABCECBCHFHCACFBFBHBADFEFEFDFDHDHCHCDEDAGGECHAFDHCABFCFDFDGBGCFCACDCEA,False +242,10.0,3.0,9.0,4.0,10.0,22.0,6.0,6.0,CBAAFFFFGBDAFFFFFFFDGAGEHFGECEFEFHCHCEEEDCFAFAHAFBDEHGHCFEFCFCFEAAFAGC,True +243,16.0,18.0,13.0,25.0,8.0,14.0,16.0,17.0,CFHGHAFGFCFEDAGEBBFDGBGHDHAHBGBGBDCHHEBDBDBDCDHDHFAGGHGHABADDCDFBHAGDDDBCACECAGEGDDHDFDFHFHCGCGCDBAFAFDBDEFEACADADADBCFAHBHGEBB,False +244,14.0,10.0,26.0,18.0,17.0,28.0,19.0,21.0,HEHEHDFDFEGEGFGDCBBDAFHFHFDCEGBBDHFAGBHFHCECHCGAFCCDDADGHGCGAGBDCDHDHDACFCFGACEHEGDGFCFCFCAEFHHHFBFDFDCBCFEFCDGAGDEEFEFHFHFEECCCAAABECFHACECFAFGFCBCGHGHG,False +245,30.0,27.0,23.0,25.0,28.0,19.0,14.0,26.0,AAACACBCAEDEBEFCCHCAEGEDEFGAGCEAEADFEBBBEFAGBBBFDAEAEHHHHCFCHCHADFDEBHFACBFBGBFBCHHAHAEEGHHEAEGHGHGHGCAHADADAEAEAGDGBECHDDDDEFFDCDCACAFBFHCHEHEADFBFBGBDBCGABHBHDACCECDDBDBDFDBEEEEHCBAFHHDBBADF,False +246,9.0,17.0,16.0,9.0,17.0,6.0,11.0,16.0,HGEGACAHDHDCDEGFHBHDHECEDEDFDEEHCFCFHBEGGFABEHHHHGAABCCDBEBECHCHFBAHGCGABCBEBECCCCCEGEBBBBDBABEBHGEGA,False +247,10.0,6.0,15.0,20.0,23.0,16.0,16.0,6.0,AFDGEGEFEDCDFHEGEGFGBCACECEAEHEDDHEGEDEFGDDDCCCCGAGEDBABEFEFDGDHDGDCBHBGFFCFCEEEEFCHEFGDGFCDADCFCAEGFGBEFDADADAE,True +248,1.0,1.0,5.0,2.0,5.0,7.0,7.0,2.0,EFCFDAGFCFGFCHEHECEGGCGDGFGFBE,True +249,20.0,25.0,23.0,25.0,18.0,22.0,28.0,20.0,DGDBDAABACHGHEBDCCABFBAHGGBGEAAGDDFGFAHADADEDFHFHGGGFGFDHDEDBACDGDGBFACABBGBGEGEGECFFFEABDEDHFAFGBCBCACHHFHFBFBFHCHCHCECDGDCEHEGCGBBFBGEFEFHCGCBHGDGFHFEABCCEBDBHGDGDGBHCEDADCDCBAEAC,False +250,27.0,24.0,20.0,16.0,26.0,17.0,25.0,11.0,CHCBCACHBABAGHFEEBEGECEBEBEACDGDHHGAAFGEGABEGAGEGADADABAECFGBGAGAEBEADFGFECACGGFGEGDGFBFGCGBFBFEAEBEFAFAFEDEAAAAGBBBCDCDGECCCBCFADABHDEDEGEAHHBDEDFDFGCCCDBBHAHGBCBEHF,False +251,23.0,19.0,20.0,25.0,22.0,22.0,28.0,26.0,ACACGEBFHHCAGAGHGHGCGCGBEHFHFCAGFGCGHEHAHADDDDAEEEECCFBGHAHAHGBDECFADGCECEGEGDGAADBEAEFHFDGDGAEAFDECBGECCHDEEBGBABEHHAFFFFEFDADHBHBDDGGCGCBAGAHABDBDEFEBCBDHGHGFDFDFDFHBAFCBDBDFFGGCHHHDH,False +252,22.0,23.0,23.0,11.0,21.0,24.0,27.0,23.0,CGGAGEGECECECDBFFFHAHGEGCGAGACEDBBBFGFGHGHFCBGHFHBHGEAHAHABDHABABDBECHAHFCFEFAAGGGBGFCDCBEADADHFHDHCEABCGGGFGAHEEAECCCCGBBEHEHBHBHDCDFFAFBFCEBAGAGCCBCAGFDHHEHFFFCFEFBBEBFGEGA,False +253,21.0,15.0,11.0,10.0,10.0,18.0,15.0,19.0,CFCEEFHBGDEEFEFDAGAHAHGHFHFHGHAHAHGFFFGBDBGAAAABABGBFBFBEACGCEDHFACCFFFGECBAECDGGAFAHDHDHBCCGHAHAFAEDHDHGBBABDFCAGABHBH,False +254,16.0,7.0,14.0,11.0,13.0,17.0,11.0,13.0,CDFHFHECACEDEAECCHFHFHGHGCAHAGAGDEDFDCHCFDADFEGAAEAFFDEDCCEDBFCGCGEBEBHGAGFBABAGFHDHAHAEFFFFFBEBCGHACA,False +255,14.0,24.0,17.0,17.0,23.0,22.0,12.0,11.0,EDGFFFGBBBCACDDDBDCFCFCEEAFGFGFGFDBBBFBDCFEFADAHEDBDFHAAGHCHFGACABEDEDEAECEFEFDAABHHAHCECBFBCBFFDBDGHGHFBCDCECEDEAAGEGFBEBCBEEGEBEBEBHCEFBBH,False +256,15.0,18.0,13.0,27.0,17.0,28.0,20.0,24.0,FBDBCHCGDEDCGAGAGDDFBBBFFFFEDACGCHAGGGEGEBABFHFEDHFHFCBDGHGBGDHBCBGAEHFAFHHHDBDCHBFGFGFHFHEGEBDFFFHAHGHCHAHDHEBEFEDGDGAFABDBEHACFCFCEDADEFBDDEAEADFDFHFHFDGHEDDDDC,False +257,6.0,7.0,12.0,13.0,9.0,11.0,8.0,10.0,DDACHGHGHDHEFCCEGEGACCDCDCDADHBFEFEDEGCFBFDFBFEHCHDAGEDECBCBHFGFDFHAHCGABDBF,False +258,17.0,20.0,27.0,16.0,18.0,18.0,19.0,20.0,AGEHCDAGCGFGDCDCHCACDFEAGFGAAAADADCCHGHGHCCEEEGCADACAHECEGDGFBFBFCHCHCBBDBDBDEFCGCBBBEHFHACAGBCHFFBCBCGGGGHDBECEHEHGHBCAGEDEBFCEEBEBDFCFAFHBADDHFHFHFHECFBB,False +259,1.0,5.0,4.0,1.0,1.0,0.0,6.0,2.0,GGGGBGAHBHCGDBECCBCB,True +260,2.0,3.0,4.0,1.0,3.0,5.0,1.0,3.0,BFBCBFHEEGEHCACACHFFDF,True +261,2.0,4.0,3.0,2.0,3.0,2.0,6.0,2.0,CDCABEHHGFGFGEBABCBGDGEG,False +262,17.0,17.0,32.0,25.0,20.0,22.0,15.0,15.0,DHDCDCDGEHCBGBEBACGDFDCBCFCBCEAEAFCDEBAAEADHCEAEHECDDDBDCDBBFFEFGFBCBHAHFCCECGHDHFHAHACDEHECFCDEAAHABBCHGEGDGFHDDCDGDCCCGCACACFCFDADFGFBFBFEGEGEHDACGDFCFCFGBEBEFCF,False +263,7.0,4.0,7.0,4.0,5.0,5.0,7.0,12.0,GCACAHGHECGCHFGFEDHDHDHGHBAEAHBHFHGCCBCHEGEBHAFADAF,False +264,6.0,6.0,13.0,6.0,11.0,2.0,9.0,8.0,DCFBDBEEEEEEADAHGHGCGDHCHGEACBCGCAHEHGGAFAGCCCCCBEBHDCBCEGEHD,True +265,20.0,25.0,22.0,32.0,26.0,23.0,23.0,27.0,DCHBHBCEHHGHDCGCAHHGHDEEHEHBBECDCGBBACACADDDDDFCGEABGBABEBEBEACFHFBEGHFBABCGHGEGDDDEGAHAEFBFDGDHBFGFCDCDCDFGFHEBEHEHBDEAEACBDADHFBDDDDAFEFBGGGGHGHCHEHFCFGFGADDDDBDADHFEBEBECEADACBCFAFHFDFGFAEGHHCCFE,False +266,7.0,6.0,7.0,3.0,4.0,2.0,13.0,8.0,BGHCABHHCHGGBDBABAFCGEGDGAHCEEGEGBGCAHAHACGCGHGFGD,True +267,8.0,8.0,22.0,12.0,15.0,14.0,10.0,10.0,DCBAAGBEBEHECCCCFEDDDFGHGDEDCBCGEGEGEBFFAEHECFCHCHFHDCDCBHGGCCBCFCHHFAFGHGDFCEADCDCDCEBFAFACECAFEFE,False +268,20.0,11.0,17.0,15.0,11.0,11.0,19.0,11.0,FACAFGDHCEFHAECBCBEBEAEGBGBGFHCCBCAHDCFCDGDAEEEFBACADABACECHGGDBDGGGFHEHADAFGFGFGHGHGCFCDCDEGAAAABDDDGHBACACDGDHAGA,False +269,6.0,1.0,7.0,4.0,8.0,4.0,3.0,3.0,DBGECEAEAEAEAGDGFCHCECFAAHHFEFCCDEDC,True +270,18.0,16.0,20.0,26.0,19.0,21.0,22.0,23.0,BFBCDDGAGACDBDGDGDADHCAEACGCGDEBGDFDCDBDGHEHCFFFFFHFBFAFHDDGBHHHHFEFABGGDGDEFCDGHCHEFCFHBADHHCFCBGBFEEEEEFEDEDAFGHGDGCACDEAEACDEDHBHGHBHBHCDGAEACCEHGHAHACAGACBEBGFDF,False +271,0.0,3.0,1.0,4.0,2.0,4.0,2.0,3.0,HFHFEFDBEBHFDDBDGCG,True +272,16.0,16.0,17.0,14.0,11.0,14.0,8.0,16.0,FCHEHAFAFBFBDHGAFABBCDCDHBHEFABCHCHDAGABEBAHDHDFCEBGDFECECECEHECACDBDBDCGAGAGACAGBFBGDDACCDDBHEHBACFBFHHHFHFCFAE,False +273,13.0,11.0,14.0,14.0,11.0,17.0,18.0,16.0,CDFDGBHBFGFGFGEDABABCHHDDEDCHCGAGFBFDADHDCDCECAGEFEBEAFAEHEHGGEFBHCHFHFAFDFACGGFGHHDHGHAHCFAFGEBCBGBGCACDCDEHGFBAG,False +274,30.0,26.0,12.0,16.0,14.0,36.0,17.0,16.0,GGHCBABACFGFHFBBHAEAEACADADABABFFDABBFFEFBAGFHFBFCFBAHHHHGGDGFGBHBFEECEFDCHCHBHGEAHADDGAFAFDDBDGFGBEFFFFFGFACABGFFFAABAFACAGAGHDABABGDACFEAEADBBFBEDEAFFBFBFCFCDBHEHEDF,False +275,6.0,13.0,13.0,9.0,7.0,9.0,12.0,6.0,CEFBGCCCCHDBDBCAFDFDFGFHHCCGCGBGDGDBCBCBHFGAAEGBGBFBGBGECHCDAEGEFADAHEDEBBF,False +276,7.0,5.0,3.0,5.0,6.0,7.0,3.0,5.0,BCCDFEFEFEBADABCFDDHDHAAEAGFGFHFBAEAGHBHE,False +277,6.0,5.0,1.0,2.0,3.0,3.0,6.0,7.0,HBBFBFDHCGEGAHAHGHGFEBHBGGAEAHADA,True +278,4.0,8.0,15.0,16.0,12.0,11.0,10.0,10.0,DHCHAEEEHEHEFEHGFBHEDEGEGFCDCFCGCDCBFFFCEGDBHFDDADGGCGDEDEDGACDCFCFBGBHBDBCFCHCDDDHCAB,False +279,15.0,15.0,14.0,9.0,20.0,30.0,10.0,19.0,EAFFEFEFHBHBHBHCHCFAAACFCAHGBGBFEEBECEGEFDCEFEGCBFHFBEAFDBBGDDCGFDCBBHBHFEFEHCHFBFDGCHFHFHFGFGAAAAEECEFDBEFECEHDFCFHDHFFEAAAAAFGFHFH,False +280,20.0,27.0,17.0,23.0,26.0,20.0,26.0,25.0,AEDGCEBACABABGBGFDCEBHBCBCGHBAEACBHHHCDDEGFHAAFABCEHDBDBDFFGFCBGGGFGEEFEDEAEDEDHHHFHEEEGEGCBCBHBEBGBGECEAEHGHABBBFHEAFGBGDGFFEFDGDGDGHGDAFAGDHDECEHHHAHDDGHGCGEBEFABCBDBFCFCFHBADADFDAHH,False +281,10.0,6.0,6.0,8.0,8.0,11.0,10.0,7.0,GBFFDHAEAECDDBEGDGAEECGGGDHDAFADAEAHBHDEFFFFBCBCECAFABAHGFGFGFGHCH,False +282,21.0,33.0,19.0,20.0,21.0,12.0,19.0,26.0,CAADABABCEABHBABDCHEAEGHBBCCCCCHCBGGGGHHDHGHGDGDGDBDAAGCBHDFEEEEEEBEBAHHGHEHCCGHFBFBFBFGHBDBHAFAGACCHAHFBCCFDEDEHCHABDBEGADBBCBHEHEDDDDBDEDBBHAHBEEEDBBBBHGGGCEFBFAFBGAHAFA,False +283,12.0,9.0,6.0,10.0,12.0,16.0,15.0,10.0,CFCEDFGCGFHFBGCGFGABEGAGAGAGAFADBHGHDEFHHDGCADEGBBCHDAAAGEBEBABFDFEFEFHFHFHFHGBFEGEDDDEFEA,False +284,0.0,7.0,2.0,2.0,5.0,4.0,3.0,5.0,FBBHBHECBFDFGEHCHEHEBEBDGFGB,True +285,18.0,10.0,10.0,8.0,8.0,13.0,19.0,13.0,HHHFGFAHCCBCHCBFAGCGBABDBDGAFDCDAEAEHDADBHBAGFGFGHEFFGHGHBHAFFBFCFCAAABEEEAGGGAGCGFGAGADAGEHAHCDGEG,False +286,17.0,19.0,13.0,13.0,17.0,16.0,12.0,9.0,DBDADABCGDAFEFEFEDABCBEBGDGFEBEBEBEADBDGHCADABFDADADABGFGFCBCDCFBGGEEFCFAFEFBAGGEFHCGAFAHBHBFFEBACECACBCHAHEHEHCGBEH,False +287,11.0,13.0,8.0,14.0,5.0,10.0,1.0,11.0,ADDCHBHFDEACFDBDBABCBCDDDBAAADHFBFBABEHEHBHBCCHFDABAHCDDDCDAFHFEFEFHFHGAB,True +288,21.0,32.0,21.0,22.0,23.0,17.0,23.0,21.0,CFCBBDADEDEDBDHDADCCCEHEHBFBHADADBGBGDCBBHFAEBDHDFDFBEBHDEDBCECEGABCFGFHDHGHEHAAGHGEDEAEABGFCCBEBCFDFAEGGAGADECFFGFBBHCGEBEGAFABDBHFFAHAHAHBHBEBEBCBABDEGCGCHCHBHBGEGEGCAAGGBBFCCGDG,False +289,10.0,13.0,5.0,12.0,9.0,19.0,21.0,12.0,GBFAEDDDGGFEFDHHGHGFGFGDGFGHHHHEGDBHFGGHECBAGAEACFBBDBCADFGEGDBBBBCBHHFFBFBFDAAAEFGFAFAFDFDFHGGGGGECE,False +290,10.0,11.0,9.0,13.0,3.0,16.0,8.0,5.0,DBDBDCFFGFGABEBEDEFFGFGFAFABHCAFABCDHDADAHBGBDDDADFHCBCDCAAGHBFGFGFCCBFFCFD,False +291,22.0,19.0,25.0,28.0,18.0,24.0,23.0,17.0,FCFEFEFAGEGCGEAAAEGEHFHEGFGDGDEDBDEEECBBBEDFHFAGHCAGAFAHABFBFDDGECEBGFDFCFCDBEFABGEDACACDHDHDFFCDCACHCDBBGCDBHBHCFCDHHHBHBGFGFADDGDCDCHCDCACAGAGCDDABCEGHDHFGGDDEAFBFACACABGBGFD,False +292,22.0,21.0,17.0,19.0,16.0,16.0,15.0,29.0,EFHHAHDCDEBEHEHEHEHEHCFDBCBDHCAFEGGHDDBDFGFGHCFDDDDAFADCGCFDFBFBHGAFCCBBEEAAGAGDEDAHAHAHBHBHBHEHCABABHBCCCHCBBBDAHGFDEAEAFHGBGEHAFBGHAFAFAHABCDDECGCHHGHGAB,False +293,14.0,10.0,22.0,19.0,17.0,10.0,11.0,13.0,FDGGCACGCDCACBCDCDGHHDHBHFGGCCFBFBCBDFDAGEHAHEFECBHGDDDCEBBADCDFDADEEEEDEBHAHAGCGCBDGECEHEHAACADAHFHFEFCCECEDECCDAEA,False +294,21.0,23.0,11.0,16.0,19.0,13.0,19.0,13.0,ECDFDEAGAEAGHBFEFGHBBGBABABGDGCCAGHBHFEFGGCBDGDGDGHFHABAECEAGHFDFEFBFECECEFDHGFGABAEHEGEBBBBEBADFEHEHBDBDADADGBHADADHGAEBBBDCACECBCAAGA,False +295,16.0,21.0,15.0,23.0,14.0,18.0,17.0,12.0,DDBBHFDFGBGBHBFFFFFFFGEBCFCGHABBEHDDDDBBBBDGFHFAEDHDHCFCHCECBAHACDCDHAAADDECACAGABAGEFEBCAEACGDGFEFBGBDBCBGGDDAEFEDGCGEGEDEDGDBABADFHCHG,False +296,2.0,5.0,5.0,3.0,8.0,3.0,7.0,5.0,GHDHFBBGGCGBHEHBCACHCGCGEEEEFDADBEGEFE,False +297,8.0,7.0,6.0,6.0,3.0,4.0,7.0,7.0,GDGFBFEFAAEBDBDBAGAEHBDBHCHDGBGCGHGHAAACHCHAFCCD,False +298,10.0,8.0,9.0,8.0,12.0,10.0,12.0,8.0,AAAAAADGHGAEEEHFHEHEFFAGAFHCDCGEBCBCBFBFAFHFGGCGHEDGDFDBGEDEDCBEGEGHCBEBCCDGF,False +299,2.0,2.0,2.0,2.0,1.0,0.0,0.0,1.0,CHCEABDBDA,True +300,21.0,16.0,12.0,20.0,12.0,15.0,16.0,21.0,HFHGDDEFBFBFAGCFAGBGDHEHBHBHAEFBDGACHGHAHFFDFHFHEBBCBDBDBCFCDCACAEDEDHAHBHECABAGCEBHBGEDEGAAHAFAHADCDEGEGADFGAGAHCDAGADAHCHDDGDGDHFBF,False +301,18.0,17.0,21.0,18.0,14.0,17.0,20.0,23.0,BEBFFCAGAGAGHGHFHDHCFDFDEDEBEBEAGFBCCHCDCBCHHGHEACAEFGBGBEDEBCDADHFAADBHBHCHFDFDFHGBGBAEFGFAAEHEHEHCCGHDDDGHCCCCAABCGCGCADACABFEHDBCFHGHGDAHHDFGBGFG,False +302,17.0,9.0,16.0,15.0,18.0,20.0,16.0,20.0,CFEHGDGCGHFADAFGFBFHABACDEDEDGAEHEHCCCBCEFHGHAEAEAHAHEHEHCDFFAHDEAFDFGBGDHHFHFAGGFFBEHEAEAFFFDGBGCGEECAFFHEHEHDACBCFCDDDDCBCBHGAGCG,False +303,17.0,9.0,12.0,14.0,11.0,11.0,11.0,15.0,DFDFAGHHDEDEHEHECGFACAEADDHDEDCHCECFHBBBEGHBACGGGAGAHDHAAADEHEAFADGDBDFHFGBABABHBFCHAHACCFCGCEADFCFG,False +304,32.0,22.0,21.0,20.0,17.0,21.0,22.0,16.0,HABACGCBCGHGHADEGABAFHHGFCCGFFFHFHAHAGACFGEEAHAHABABFBAEAEDGDBDFFFFEGHGDDDCHFAFGECACECECEDFBEAAFBCGAGECECFCFCBGGADADGHACAEBHAHABGGDDADCDADBBBGHEFEDDDGEFBDBDBCBABCBAAAACFGB,False +305,22.0,14.0,10.0,9.0,20.0,15.0,19.0,12.0,GAGABHEFGHGABAEDECGAFABBEFEAECCAAHGHBEEEEEFHFGFGAEAGAGDGHGFAAAHAGAGFBECEFFBBGHGFCBCGCADEDBDBDBDFEECEBEDGAAEAFAHHBFCFCDHGH,False +306,7.0,13.0,6.0,7.0,4.0,5.0,5.0,12.0,BABAFAHDFDGBHHEHBDACHGHGDDBDHFFAFACEBEBEBHBCAHBHDHCGBHBCGCB,False +307,27.0,19.0,23.0,17.0,31.0,29.0,21.0,17.0,FADCDEGEBEGHDAEFEAEBHBCBAFAHAFGEGFBFCAHAHCCBDFHGCEFFCFEFEAEAFCBDADADHDFBFBEBADFCFEFBFBFDFCFGFEAHBBCCCCHHBHAAEGEBECEGDAEFDGECEFEHGAGEFEDGBABABHDHDCDCGHAEACAGFCECGGHEDCFAAAGAGCEHEGEGFGFE,False +308,16.0,23.0,23.0,25.0,22.0,21.0,28.0,27.0,BHGEFEDACAGADADGDGDBBFBCGGHGFCFCEHHDCDCEGFCFBEBEHDHCHCBEDDHBBEBGGFDECHCHCBFDFBGEHEGEDEGAHDBDAHGBGDGBCFCGCGBBAFAFABBBFGFHAHAEAGFFFGDDCABHECEDEBEHDGDEDEGCHCDCACHCAFGGGHFHFHGHGCAEHHHHDDBEF,False +309,11.0,10.0,14.0,4.0,9.0,15.0,8.0,17.0,CECHBGAHBHAHGCACBEFEFDCCCCCBCDCGAFFFFFBCBAFHFHFHDAEAHGHBHBHEHBHCGFBHAAGEFEFEGHAHDFFCAEHG,False +310,7.0,7.0,11.0,8.0,8.0,14.0,8.0,4.0,AFACGFEEDBGHDDADFCFCFCFDBGBHEHFAGDCACFCFEFBDBGBEBFCFCFCADGEGEAHCFGE,False +311,1.0,3.0,3.0,4.0,1.0,4.0,5.0,3.0,DHHBHDGDGCFAFGEBCBCGFGFD,False +312,9.0,6.0,12.0,3.0,7.0,3.0,4.0,5.0,AAEAECGCDFDHACECEAEBHBACCHCHEGCGCHCACBBAFAFCDGEBB,True +313,10.0,20.0,11.0,11.0,10.0,21.0,14.0,10.0,FHEBEBCAHAHBFGFGHGFAFCFDBDFDCHBECCCHEACABDGFBFEFAFAHGBFBDBDBFCCCEBFGGBGFAFABEEAEGBBFFDFBFBDBGBGCGDEDHFHDGGH,False +314,11.0,11.0,19.0,12.0,11.0,7.0,10.0,11.0,GBHBFGDABADADBDCDADHBGCECHCHCGCEAGCGCDCFEAGAEAEHECEFFBECDCGEHCBBBCGDHDBDADCFFEFCACAEBHHCHGHC,False +315,15.0,20.0,19.0,23.0,12.0,16.0,12.0,15.0,CCCCEFDBDHDCDFDCHFHFDEBACECHCGGFGAHDDDBACFFFDFBBABABDBACADAHCHDGCFFBHHDHDHGCCACEDBDECEHEBABHFDDDDGEFBFBGBEBFAGAGBGHEHDFEBABAEADBCGCG,False +316,6.0,8.0,6.0,3.0,8.0,2.0,0.0,9.0,CBCDFDHABAFEHBHBHECEBECHHBEEECEHAHCDAHABAB,True +317,5.0,12.0,12.0,7.0,8.0,8.0,7.0,11.0,CHGBGBFBFDABACAFFFCECHCEGDBBGHCCBGDGFGHEHDHCHBBCCECEBEAEAEHDCDHHBHBDFF,False +318,19.0,29.0,24.0,19.0,24.0,39.0,20.0,15.0,CFEFGHBHFHCEABFCCCFFEFEGBGBAHAHDBABCBGBGBGAGAGABHCCCFFFEHEDGBHEEDHDEDBHFDBCBGBFCFBEDFAFCFGACEFGFGAAFFFFDFEFECCGEGBDAAECECABEFDFCEAEAHFDBABDCHGBGBGBCACBCBEFGFGFCFHDDFAEHDFFEDDFDFBFBEBEBFHFCD,False +319,8.0,5.0,5.0,2.0,5.0,4.0,3.0,7.0,HAAEAHDHCBDEAHCGFGCEABAEAFAFHFHBHBCBCEG,False +320,4.0,0.0,2.0,0.0,3.0,0.0,0.0,1.0,CACAEAHAEE,True +321,19.0,25.0,20.0,14.0,21.0,25.0,19.0,10.0,ECEAHAGAGDCFHAHAHABEGAGBEBFFFFFGFDFDFGCDCBABEBGBFFFAGADFDGHGABAHAGCBABGDGEEACAEDBCBCEEFHGDDCBCEGEFEBEBFGCHBHBEDFHBCGEBCDCFCEBEFEBCBCBCBAGFFAFAFDCGEEFDCBF,False +322,4.0,3.0,7.0,8.0,3.0,3.0,6.0,6.0,AGDFDFDAGECEDDHCHGHCBFDEBCBCHCHCDDAHAGGG,True +323,20.0,23.0,10.0,13.0,14.0,23.0,24.0,21.0,AGAFFGHGEBBCDCEEEGBFAHAEGEGCGFGAAEBGHEBDGAGEBABEFCHAHADFBFDFBHBHBGBEBFBFHCACGCGBFBFAHAHFEFDBGGGBGFGBBEDHGHGHFHDHDGDHBFBFDFHFHFACADAGEFHCAADHBHCADFGA,False +324,6.0,10.0,13.0,15.0,5.0,10.0,12.0,7.0,ABBDDDDGDHDCBBHCHGDGBAEGEGHDBCFGFBEBADGCGCGHFFFFFCFCBDBDGDCAAAFDHCCCECDFDHCGEG,False +325,14.0,17.0,16.0,18.0,24.0,25.0,25.0,12.0,EAGDFBFEHEFGADABCCEGEAEGEGHGBFBDEAEDHDFEFDHCHGBGEECDCDCDCHCDEAEACCBEGAGEBFBFBFCCGFBEBCCDEDFDHHGAGAGEEFFFFFBGHGHBDECEBAFAFDFDGGGAHBEFGFGFHDGDEFGCABFBFGG,False +326,10.0,8.0,13.0,7.0,11.0,10.0,9.0,12.0,HGFCFAFCFAGADEDBHFCFCHHAHACEBECCCCEGEFEFGDBFBHBGBCEEABCECAADDEDHDHBGEGAHCHFHGAGH,False +327,13.0,9.0,7.0,7.0,11.0,9.0,9.0,4.0,EFEGEFABAFHDBFAFGGEBEFECCCEFFDADBDGEGAGABABABFBDDAEAHAHGHEAAGDECCCGCB,False +328,11.0,7.0,14.0,13.0,15.0,16.0,11.0,12.0,HHHHFDGEGFHFHGDGCCHFBFEDBAHGFCDCGGDDACACEDBGEDEHHGHEFEFCFGFAAACADHFAFCFCFCBDBAEEEEGDFBFAEAEDEDEBCCC,False +329,14.0,9.0,16.0,7.0,13.0,4.0,16.0,18.0,GCAEFCFCACAEDGGEGBGBGBHBHAHECAAAAHAHECECHGHADDCBCFCHHGAGEGDGEAECGBHDACECBHDCDGHCHGEBHBHEHCFGEGHHA,False +330,6.0,12.0,18.0,17.0,8.0,10.0,10.0,6.0,GGFCECDCDCAABEBEHEFDDADGDBDHGFBFBEDHDFBHGGCBCBCDCBCHDGCBCBEDCDGDBECADACCCFEFGFGFHDADFCC,False +331,11.0,25.0,21.0,16.0,17.0,27.0,21.0,23.0,FFFCHCBCGHHHGGCEBEDFCHAEFCFHDBDBABFBFEFBFHDHFBGCACHHFBFDFGFBHHDBEFAFAFHFEEEGEGEGEDBHCDCACHHGFGFHHBDBDBHCHGEDBDECECECFGBDBCEGGGGCCBCAAADAHBBBGBGFGHDAEFGFBBGHDCFCF,False +332,31.0,34.0,15.0,23.0,18.0,19.0,14.0,23.0,HBFBAAACBDEABCHDHAHDFEFHAAACDEBHBHBHBCBHBHBGCAFGBGBFFDFGAEAEBDFFADADACADDDHAHAEEBFDFGCCCFCAEGBCBAHCGEEEEEEBFDFEHBBBABAHADBDEDFGHHBHBDDABBHBHDHFCFCGEBAAAEGFDFDGDBBBAGAGABAGHBHCAD,False +333,20.0,17.0,9.0,14.0,13.0,13.0,13.0,14.0,ABGCECACBHDHGEEHEHBDAAAFDEDGDFAFABCCGHBABEBEGADADFDEHEHEGBGAHADDHHGHGCGFFABAFDBDHABEFDCDFFAFBEBHBAFAFABABGCECHGBG,False +334,7.0,5.0,2.0,4.0,6.0,6.0,4.0,9.0,GCGBFBHAHEBEAEDCGEAEHHFHAHABFGFHFHDEDADAFHB,False +335,17.0,13.0,10.0,10.0,9.0,12.0,9.0,20.0,AGHHAHAHCBABFGADADEFEFEDBBBBHHGHDHBCECEHFHFHBHAHDEAEAEBEHACAGADHCHBGGFFFHACBDFDAGHCDGDCFCACFHFBBHGAA,False +336,10.0,13.0,6.0,5.0,11.0,4.0,11.0,9.0,EGEBEBEGEBAHEFBCBEHGDFHFAFCBHBGDABHGGGBGCGBABADHDCEABABADAEEGAGCHCHEH,False +337,17.0,16.0,15.0,8.0,14.0,17.0,17.0,24.0,HBGBABHBHDFFAHAHAGAEAEAFACGCBCECFGDGCCEFEFHHHABGFCHDHGBCBHBDGDHEHGHCFCHGHDHFHFBFDABHBGBAFHEEGEGECBAGEHBHCHEFEADCBFGHCEFGCGFAAAAF,False +338,18.0,20.0,22.0,16.0,18.0,27.0,14.0,22.0,AEAEAEAFHDHAAEFBDHGFGFCAAAGADFFEFBADCHCHEGBBEBGFGFGEHEDCFHAEBHCDCBCGAECGCHCHBFBEBHHHGCBHFDDGHHHCHBDEDECBDFEFBFGFCFBFBCBFBFCDEAFDGABADADBFFFFECECADHHHCHCFCFCG,False +339,24.0,25.0,25.0,23.0,21.0,21.0,28.0,25.0,ABAFDFCFCGHGCDBDGEGEGCAAEBHBHGHGHDADCGCHFECEBDHDABHGCGHDHEEEBFBFBDDCDGEEEHBFFCFBFAFAFGCCCHGGFGCACHEDEHGDDBHEHDACAFHEABGCACABDBEBFDGHGHFHEAEAEADACGGBBBCGCGDGBGBFCHAHAHFBABFCEHBADGDEBACGCGFAFDHD,False +340,14.0,19.0,9.0,8.0,9.0,16.0,11.0,11.0,CAADABAEACBCBGAADHBFFFBDBDEGABHHHAEFHBCFHBEBGFDFBFBDBDBDAEGEGEFCGBFBAEGBGFGFHFHFGFCBCAAGAFEHHHCBC,False +341,2.0,6.0,2.0,4.0,1.0,4.0,1.0,1.0,ECBDBFAFDFDBGBHBCBAFD,True +342,10.0,9.0,6.0,7.0,9.0,12.0,7.0,13.0,AEAHAHFEGEGBGAEBBHFDBGBHHGHAFAFAFHFDDCDHECFCACFHFHCDCDHBEBFAFGFABEEEGBDHH,False +343,12.0,23.0,13.0,17.0,19.0,18.0,25.0,20.0,GCGCGCFABHCGAFCFDFBHBHEECDDBEHEAEABABAHHFFDFGEBEBGCABAGGEGEDEDHBCFDHDGBGDGHAEAGDHAEEECHHFBDGCFCDBDHFHBBBDHHCBEHFHGGGFGFBEBEFEFCFGFGHGDGDBHBGBABDGEG,False +344,8.0,19.0,17.0,14.0,18.0,17.0,16.0,26.0,BFBHCHCACDDFCHEHAFAFEEEDHGHBEEFADGGFGEEDEDEFEFBFBHHGHGHDEFCGCGHDHDBCHDBCFCGEBHBHEHFDEAEBEGCGBHBFBHBCBCBCBGACCHHHGHFDFCFHGDGHEHDCBAAFHBG,False +345,14.0,25.0,9.0,16.0,24.0,29.0,24.0,20.0,BDBDFDFEGEDADGGGGDFAABHGFGFEBHFECHCEDBABFBEDGGCFCEAAHGHFBBHHHHHHEBEBFAEEBEDGDCHEFBFBFBHEGEGEAEBGGCAFFGDGAGAGHFFFFFGCHAHBHDEDEFHBBBFDFHFBFBFBHDEFGBEDEGEGBAFFCACEG,False +346,20.0,21.0,26.0,20.0,28.0,15.0,21.0,20.0,EDEDFHFHEDCCECEHEHCGBBAEFDDHBGBEBGAEHECGCACECGCGCDEHCAFAECHBBDGDFCFBBHBEBEHDGDBDCAGACAHAHDHCEBEHEACDDDFFAGAFAFCGEACACGEEAHAGAGAGEFEFHFBGCHBDBHBCGDGCECHDHFBFDCGCBBEBDAEGEGE,False +347,9.0,10.0,7.0,7.0,9.0,11.0,7.0,1.0,DAFCBCBAFDEGEGEFAADGEGEAEAFGFBFEFCFGFCFHEDCBGBEBAFDDABCBABDBC,False +348,23.0,21.0,22.0,23.0,12.0,21.0,19.0,12.0,DBGBGFCCGCDHGFGFGFDCDEAEAFBFBHGHBCBABAFFFBBAFHFCDBFECCDCACAEADFDEDGCFCHBBBBDFDCGAHFGEADDGHFFDADEGEAEFEDECACACAFADCFCAGBBABEDGDHCGCACACHBDGGAGBGBHAHADDDHB,False +349,24.0,18.0,28.0,33.0,14.0,23.0,32.0,22.0,DBDACACDEGGCFCBGBHFGDGDEDHHADCFBFDFDAAFAGDGCFCECEGDGFBAGHDDCDCDGHCFFAFGDGDHDHFGGBGHDCDCAHFEDBFBFCDDEDGHAHADABHBEAAACADGBGAGAFHCCGFGCGDGAEAGDGHFHFEBAHCFCFGGGEGEGAGHBBBDCCHCHFHCHDFDBDCDEHECBCEAABC,False +350,8.0,4.0,6.0,7.0,7.0,4.0,16.0,7.0,EDGFGACAGBHBEBAGACAGEEEEEGGAGCGCDAFHGDCDHGHCHGBGAFDFDGGGDHH,False +351,14.0,22.0,13.0,15.0,4.0,11.0,14.0,13.0,ABCCHHFHCDBDBDBCCGCGFFDFBFGGBAHADDGDCDCBAHABEFHBBDBDBDBEBEBGDAEABDGFHBHGAGCBFHHHHHACGBGACFBBDGDBFAGAGACACF,False +352,23.0,10.0,18.0,19.0,18.0,25.0,14.0,15.0,GFADHDHFCGCBFFFHHEDFDHAEEFECAGBGEAHAHADAEGCBFBFEGEFHHEGGCFCHHAHAHEBAADAGBEBEDEDGFEFAFADADFGFAFCECECFFAFACACHCDFDADCDGGFDHCCCCDGDAFBFBEADBDAECF,False +353,28.0,26.0,15.0,29.0,24.0,17.0,31.0,29.0,EFGDADGCGBGBGBEAEHGHFDDEDEDEGHGEGEGHGHEHGDGBGFEAEGDCHCHDHFHEHAGDHDFEBEBEBEDCDCACAFGFCABFEGBGAGHHBDBABABHHAHAECEAGBGBHBFEDHCFCDGAFDHBEACFHHGDADHCFCBAAHFFGFDADBBEBHACABAHGDGBEAFABDBGGGGDDDAAHDDDHCHAABE,False +354,2.0,5.0,6.0,7.0,4.0,6.0,4.0,6.0,BHGHAECCCFADBDHDEDBFBHDCDCDFGCGFGFHHEFEB,False +355,6.0,5.0,6.0,6.0,6.0,7.0,2.0,4.0,HFHCGCGBFEAAAHAFBCBDEDEDEDCDFFABBCFCADFEHE,False +356,6.0,7.0,14.0,10.0,18.0,19.0,15.0,16.0,FBEHFGEHFDCDGGGEHCDCDFFFHBABDFDFHCCFEFECEHEFCAAGFGBCBFGFEBCACACDFFGHGBEHEHEHFHCCEGEGEGECAHEDEDGDGEHHHGHFF,False +357,14.0,24.0,11.0,19.0,13.0,13.0,20.0,12.0,CAHGEBBDBFBEGHAEDBDHDGDGECACACEFBDBFFGADBHBCCDCDHDEGEAFAFEGBFBABHFHAEDEDGHGBEBGBGBGFFBCGEGDAFAFAHAEBCGDDAGHHBCBDBDBFBDBDCGGGGH,False +358,14.0,23.0,16.0,16.0,14.0,16.0,6.0,16.0,HBCBHFHFHDBAGAEDCCCBFDFHFHDHDHGHABCFCFAGEGBBBFDADADBEBHFCFDFCBADDBCBCBCAEGEFCBABAFAHBFBEBEBCCEEHEDECBFAEHGADHDHEHBDEFBCDA,False +359,13.0,21.0,20.0,21.0,14.0,16.0,20.0,15.0,GFDBDCACAEBEBEBHBCBCECEGACHCHAHAGGBADADBDFCFHGDGDGEBHBDGGFGFGDBDAGABDGDGEHFDAEFFGFDHEBCCDCHCFCECHGDBCEHEFDFDABEBGDGHACFFBDCEAFGDBCGCBCFHBHBH,False +360,2.0,2.0,1.0,1.0,3.0,6.0,2.0,3.0,GFFFEFEBDBEHGCAHAHFF,True +361,14.0,17.0,14.0,17.0,23.0,22.0,11.0,18.0,DHACABDDDFEFBCAEAEAEFCFEFCFDFHFAFBCBCHGHFHEAEGBHBGCFCHAEBEFECECGFEDEFCCHAFAFAFADGHGBGDHDEDAHBHBHGEEBDHDBEEHGDEDEFBFBFHFGFBDAEBDGCHEEDCHB,False +362,7.0,7.0,14.0,4.0,6.0,6.0,6.0,3.0,CCBCGEGCAFAEADAGFGFCFCBCGHBBDBCGEAHAFCDCACBCHCEEFECBD,False +363,10.0,8.0,17.0,16.0,17.0,20.0,8.0,12.0,FEADABEGEHEBEBECFCDCHBHCAEEGHCFGFGFHHEFEFDFGFDECCACHFFFCDCGADAFGDCDCDCEFFFFAHAHBEECCDADAFFBEDEDEDHCFCDBHGHDB,False +364,8.0,4.0,4.0,12.0,13.0,9.0,10.0,11.0,FFHEHDFFAGEGEHEHFGDDDEDECEDABHFGFGDGAFADAEECGGABDBGHHCDCBGFDHDHAEAEHEHE,False +365,6.0,2.0,5.0,1.0,4.0,5.0,1.0,5.0,FEACAGFEFHCEABABAHFFEHAHCHCDC,True +366,11.0,5.0,9.0,15.0,4.0,9.0,12.0,5.0,CCFDEDFDFEFEHDBDCDHGGGGDFDAACADABFGCBCAGAFDFCGCGAHAGAHDBDHCGEBFDADADGG,True +367,22.0,11.0,14.0,10.0,20.0,19.0,35.0,19.0,DGGGBCECGDADABABHEHBHGAGHGFAFAGBGBGEEACACFEFGGGEFHCDEEBEBAHCEFFFFHAHAHGFECBHGGEGEHAHFGBDFHEEGCGFDAAAGEGAGFEFHFGAGAGDHAACAGHGCGAGDGBFHFGCGCECEHFHDGEGCD,False +368,2.0,3.0,4.0,0.0,3.0,2.0,2.0,2.0,BCECECHFHFAGEGBBCA,False +369,2.0,7.0,10.0,3.0,12.0,8.0,6.0,9.0,HHDHDCCEGEFFFHCBBHDEGEHEFEFEFEFBCBEBHBCCGCHEHBGGACECEFGAC,True +370,17.0,20.0,13.0,14.0,12.0,20.0,18.0,16.0,HEFEBECCHDECGCEBBGCDBDBDGFGFAFHGDDFDHBBBFAGDFAGACEFHGBFDFHFHFHCGBEDHFCFCFGAAEDECEFBFAHABACAGAGACAHABFBFGEGDBFBHBHDHDGBABAGCGEBAHGH,False +371,14.0,16.0,16.0,7.0,13.0,5.0,11.0,14.0,GBGBEHFHFBBBECAABDEABAGAEDEDBCEGECCACAGACACBCHCECEGABDBEBHBHFHCDAEADHCHCHFHCEABBCDHEGFGCHBGGHGHA,False +372,9.0,15.0,11.0,10.0,12.0,17.0,13.0,14.0,BEBEBGFFBFGFDFGCGCGFHDGGCFAFAFBFDHDEAEHEHAFBFEGHHEBGAGCHHHDDCECGCABFBFHFEDEDHBBCBGBCAGACAHBECEDDHBHFF,False +373,14.0,9.0,8.0,14.0,6.0,19.0,18.0,14.0,BHEFAHAHDDDDFBFDFGFEFHGBBFAAAGADHGBFCDGBEFGFCHHGFGHGHFHGEGAGEEAGDDABGGCCCBHBHCHDFAFAFAFGFDFDADADCGCGHF,False +374,13.0,6.0,13.0,5.0,8.0,10.0,12.0,6.0,CBGADAHAHAFAFGCGFGCDEAEADADCBHDFAACCCAFHBBCEGEGECFHAEBEHCGFGFGEGCGCFCGABF,False +375,8.0,5.0,6.0,3.0,11.0,9.0,8.0,4.0,EEEEHFFBFGGCGHGEBABEEFCFCBHGDBHFAFAFDFGAGDGAECECECAAAE,False +376,6.0,8.0,6.0,9.0,8.0,5.0,12.0,5.0,AEGEBACACHCGGHDBDBCEGEBEBHFDDGDCDBDBEGCAFBFGGGEHEAADFDFHGGG,False +377,2.0,3.0,2.0,5.0,6.0,4.0,2.0,2.0,EDEDECEBHBGFGAEADFHBDFEFDC,True +378,18.0,11.0,12.0,20.0,13.0,19.0,14.0,21.0,GAEHGHAADADADBFCECDCFCGDDFCGHAADFFFGHBHFDCDBFHFHGHFAGAGABADDHAEDECFFFAFAFDEDEBABFBGGHBCBAACBHHHFFEDEDADBEHFHGCGEEDHDCDGHGHEHEHCH,False +379,15.0,10.0,10.0,14.0,7.0,13.0,13.0,11.0,FHGHGHBBCDDDDABABGCEDADCHGAAHAFCFBDBDADFCFDDHCHFHAHCHCBCGGAACAHGGGGAGBEDFDFEAGDGFEBEFFAFAEBEF,False +380,20.0,20.0,27.0,28.0,18.0,28.0,19.0,15.0,FAEAEHHHHHHECBHFFFCFCDAGFGDEDCDCBGFFCGBGEGBAEAGFCADGGBEBEFHFDCBAEFDFDEDAHAHGEDAGBGFEBEGFDDDFDFAFCCCCCCBCBCGCGCACDDBFAFBCDADCDEDBCBCGHGFGBBAFDCDHBHDDBDCECACDFDGABFEDEAEFHHAAFFF,False +381,9.0,4.0,8.0,8.0,10.0,3.0,5.0,2.0,DEDECFCECEDAAACHEGDDFDFCACECGAABDGCHBEBGDGBAEAEAE,True +382,28.0,23.0,23.0,25.0,22.0,19.0,22.0,24.0,EBAHHEDEDBDHHGADFEFEHDHDGFFDFDADHDGEACBEHEFGDGAGAGEBCDCBBAFECHGGBHCHCGGGCGAFCHCHBBEBFBFHFCGCGEDEAAADABABADFEFDCDCECDCHCHCBAAAAAAHAFEGEADCCFHFEBEBFHDHFAAAGCBBBCDHDEDFBEGHCBDBGHGCGHDEAGABA,False +383,4.0,5.0,2.0,2.0,4.0,7.0,4.0,2.0,FAFBFGCGAGAGFBDEFEFHABFBDCHEBE,False +384,23.0,10.0,11.0,21.0,17.0,14.0,20.0,15.0,CBEFFDDBFAGHDAGAGAGDDBEGCCCDCBHHEAEFGFEEEHEACACAGAGBDAAHFHFAFADEHCACGDAEEFGGHEHBCDAGAEDEBFGHDHEHDHFHAGAGAGAFAFABBCDGGGDBDGDEDEDFDHD,False +385,16.0,15.0,15.0,12.0,17.0,20.0,20.0,23.0,FGBHBHAHAHBDFEFEBCAEEDEAHBHBHEFDCBAFCFAFAGHGHGACDHBCAEHGHBABFCFDGDFDFHFDBGFGHHACADACHCGBEBEHEACGEGFGFGDGEGEGECEADACBGFHHDFFHFHFGGBHCGCEEHC,False +386,22.0,28.0,19.0,25.0,19.0,24.0,12.0,27.0,BHDGBHDFDFDBABGDHAFAECECBCBCFCBEBHHHEEEBAFDFAFADECBDFDFAEHBHEHEGEADHHHFHFHDBFHAHADADFDFCAHBCGCDCBBBGBFAFCFHAGADDBFEFEAAHCDCECBDFFHFHBHBFEDCACAGEFDHGBEHGBCBHEEGAGHBDBDGHADADCBCB,False +387,16.0,23.0,23.0,12.0,27.0,6.0,20.0,14.0,EDEBGBEBCGGHCACBHBEGAGHGCGEGFCHBDCHGHBHGDADADBBCHCBEBACGEGEGEBABABDEEHECCCCBBBGAGAEAGFGHACCBBABAGFBEEEEEECGDDCDHEEEAEAECDCECGCFHFCBCEADDHEBFH,False +388,29.0,22.0,29.0,26.0,26.0,22.0,19.0,18.0,CECEGHFBFDDCDHGAFBGDFAAHACACAEEBEACFCAEECCGCGCFFFABGBGDCDGDEAEABHBHBFBHAHDCECECHFEFBACDDDEHAGABADFDFDBDBDECECEDHDAAAAEBEGAAADGFBFADACHEAACFGFGCGEHFHFCCCDGGBCEGFAFEBHCDAGBCBCDCEEGDBDBDHFHEBEHH,False +389,6.0,5.0,9.0,6.0,6.0,10.0,3.0,6.0,AFFFACCCEHHHHACDFDEGCBCDEDCFBFBDBFHFHADGCGCEFAFAEBE,False +390,5.0,5.0,8.0,6.0,3.0,4.0,2.0,9.0,CHCGBFDADACBFDFCHHDHDHCGCBFAEAEAECHCHBBDHH,False +391,17.0,18.0,29.0,20.0,13.0,16.0,17.0,22.0,GDCDGHHBEBFCFHGHAAAHBCDCDHFHEHBDDDDDCDCACHEBDBCBFDACBCBHACCDCGGGGCBCFCFBACADHHCFCADHHHGCBBGDGCGEEHEACAGGFGCABABDBEECECECFAFAGHHDHDFBFGFHECEFDFAHBHFGCACE,False +392,4.0,11.0,10.0,5.0,8.0,5.0,3.0,15.0,HHHHEEDDBGHGFABEBECCBHBCBEDECBCHCBEFEHDBDHAHBHFAGCHCHCBCAHFHF,True +393,5.0,6.0,6.0,2.0,4.0,4.0,5.0,6.0,HGFGHHHAGCGEFEBDFDAAHAFCBCBCECBGBEBHCA,False +394,21.0,28.0,17.0,22.0,17.0,15.0,15.0,14.0,DHAAAAFCDBDBDGGABBBCHCACGHFBBBBBBBAAAAFBBBBBEGEABCGFDHEHEDBAADEDEDEHCFEBEGDHFGGECDCHCHBDCEFEHDBDBDBDCECGCBFDGBADHGGFAFAFACEGEFDFBABFFEGDAACACHEHDHDCG,False +395,17.0,17.0,23.0,13.0,25.0,16.0,32.0,27.0,ACFCFGGGEEHEGGDEHBACACECEFEFHDEDFDGEGBGFHCCACEEFDACHGHGHBEEHBACCCCHCEFDAGAGEGCBHBHBGGGDGCFAHGHGHCAEFBBBHBGBHHEHEBGGEGEFHFHFHGHGCFCGHGDEDAAAGCBBBCHAEAHDHDFGGGEGBAHECDFDCAE,False +396,2.0,4.0,1.0,7.0,6.0,10.0,8.0,9.0,GCGFGFGHBFAEGFHFHGBDHEFEDHDEFEFDFEFBGHHAHGDBDHD,True +397,12.0,14.0,13.0,17.0,13.0,20.0,12.0,15.0,CEBHFCBGHGEGEACAHBHBDBGBADFDHDFDADHHEHFHBAAFACECECEDDGDGDCCCHCGBBDGFBECGDGACFFFFFFDHDHAEFEFBBGBFHFHECAFDBEHDFAFAEGFD,False +398,28.0,19.0,7.0,24.0,27.0,19.0,20.0,15.0,DHEAEADDHGAAHAGEHEBDBDHFCFEFEFEGAGHGBFHECAAGDCDADFCHDADADFDHGBGAEHDGFBFAFAFEFEFEHCAAAGGBBABDBCEADADFEGEFHADEGGGEGEGBGBDADEEBDBDHEEEDADEBBFHEEFCFEFAAAGABABDBHBG,False +399,0.0,3.0,1.0,3.0,3.0,3.0,0.0,4.0,DDHFBFEFDHBHCHEBE,True +400,14.0,15.0,8.0,10.0,12.0,16.0,15.0,13.0,BABABGHFHEHEAEBFGHDBCBGDCFFGAGDGFEFEFEFHDCAGAGHHAHACBCBGAGEGEDBDHDEBCACBHAHCFAFEBEDFFFBFGEGFABHGDADFBHG,False +401,11.0,5.0,16.0,15.0,7.0,18.0,6.0,17.0,EGDHHBGCGFFFFECHDAFAFBFDHGHAACFFFAEHBFDFHEHDFDFDABBEAFCCCCCCCFHAGADDDCCEHEHCHDHAHFHCCCFDHDHDADG,True +402,3.0,10.0,24.0,13.0,15.0,13.0,11.0,19.0,CBBEDHAHBDBDBGCECHHDHGHDCGCGEHCHCGCEEEEHFHFECEGBDDFBHEDBDADGFHCHCGCBCDCEAFGFGHGHCECFDECCCCCDHHEBFHFCFCEHFFCF,False +403,1.0,2.0,2.0,2.0,0.0,1.0,2.0,2.0,DGDABGBCHCHF,False +404,5.0,16.0,6.0,12.0,8.0,5.0,12.0,9.0,DGDHBCBCHGEEHEFGFBAGABADDCDBBBBBGAGEEDCDGHGHFHBHGGCEEDBDBDBCBDBGFAEBHFHGD,True +405,21.0,16.0,12.0,16.0,13.0,10.0,25.0,18.0,GFEFBFGGBGBGBHFHEBEBGBGFGFCEAGCDHAABHBEGCGHDHAHDCEGDGDBFGCAAAAEAGADFDGDAACACECEBFDHBAEACHGHAHDEDEFHHHBGEGACDBAGGBCBHHCDGAGDGHGHADAD,False +406,4.0,4.0,3.0,5.0,1.0,0.0,4.0,3.0,GBDDABCBCGDGDCHBHDHAGAEA,True +407,16.0,7.0,6.0,14.0,13.0,6.0,14.0,8.0,BFCAAAAAEFEBDFCFCADGDBDBDAGAHAEDEGHGHGFDBDGAEHEAEAGCEDHAEADGDAFADGGEGHGHDEBEHDGBGCCE,True +408,12.0,15.0,11.0,21.0,18.0,14.0,12.0,11.0,DBDBDBDBCBGGABCEFEFGGDBDAAAEHEFEBGBECCFCBGEEAEHCBFEFHFCEBFBHGADFDACABEBEAECDCGFDDDDDDHGEGFDHDHDHFCDDEDGAAFAFHHGHEE,False +409,20.0,21.0,28.0,22.0,20.0,26.0,20.0,22.0,FCFDFHADGDHDHBBCCHHDHDHDGAABAGCGCDCDFFFAEAFBHHGHCHEFEGBDCDAAHABBCFHFEEGEFFFCHCDBDEDEFEDAFAFABEHCCCEBHBDGDECCAAACDGFFEDHDFBHBAGAEAEFECGGGCHCDAHBGBDBCBEHGFCFCFCFCEGEGHFCBGFGCGCEABBB,False +410,3.0,1.0,3.0,3.0,0.0,0.0,1.0,2.0,DGACBHDHDCACA,True +411,10.0,24.0,18.0,15.0,16.0,10.0,24.0,18.0,HHFBFECHGHAHFGGDCBCBCEGHGBBAAGCCHCBDBGBDHHHBFBDBGGCGHGABABACEHEHCDGDECBAAEFGGDGEADDDHDHBEBEGEFEGEGCGDGDEDBCCCHCEBEDCGFGHGEGFBFBACHBBBBF,False +412,7.0,7.0,14.0,10.0,10.0,6.0,9.0,5.0,GEDFDFBAGCDABADDGAHEDEDFDCDCDFHCBCBCGCHBGCFCAEEEEEGEGCCCHHGCBEBCAGAF,False +413,1.0,1.0,2.0,0.0,2.0,2.0,3.0,2.0,FGCGCHEHEABGF,True +414,3.0,7.0,4.0,3.0,7.0,6.0,6.0,8.0,HCHGEEBABABFBEGFGAGBDFDEHEFCFBHHHFHCHCBEEGGD,False +415,17.0,22.0,23.0,22.0,24.0,17.0,20.0,16.0,BCBGBADDEHEBECCCCDGAGEGEAACEHEHGFABAEHECECFCGCECDBACAHADECGCBBFGFEHEFGDGEGCGFGDHDCBCAFGDGDAEFHFCFBEEHEBDDFHHHBAFAHDEDGDBDEDECFCFHFAGCFFAEGDGDADCBBBBCGHHABBBBBDED,False +416,23.0,23.0,29.0,23.0,28.0,15.0,36.0,18.0,HDFEEHAHFECBCGDFDFBAGABBGGADFDGEGECECGDHCECECEDEDACACGEGCGFBCBCACEEDEGGABHEDCHBGGGHGCGCBDBCCCEHEBGBCDDGGHGEFEGBBBDBAFAFAGBFFHHADEGEDBCCCACGCDCGEAHAEADGGGDGDBFBFCGCGBGBGACAHAHGEFDADEHEHAFGHBHDEAEA,False +417,6.0,3.0,6.0,6.0,13.0,9.0,7.0,12.0,HGCCECEAEHGHGCFAFHDDBDEGBGHHEEDAFGFHEHAAADBCHCGFEEEHEHEFEFDFHF,False +418,7.0,7.0,9.0,13.0,10.0,16.0,6.0,11.0,HEFFFEDECCHHBHFDFACACEDHDBDBDBDFCFDEDEBHGEFFAFADAFHGBGCGCFDEAHDFDHGHFHCGEFEFABC,False +419,6.0,2.0,4.0,3.0,3.0,0.0,2.0,0.0,EEBDBAAAACACEGGCCDAD,True +420,20.0,21.0,13.0,17.0,21.0,27.0,25.0,13.0,HAGAGAECCFDBEADDGAGFFDCBFFCABGBEBAGCGBFBGEGEFDCDEBFBEDCAHBHBDFDFBADGFFEGEGEFEFEFHFBBABAHHDGDGBGAGFGFGEEDEDAFAGDHEACACFFGFGFGEDECBFBFHHHGEAFAEAHFBEBGBCHCHGADC,False +421,9.0,14.0,14.0,8.0,6.0,14.0,12.0,12.0,FHFDFDBBBGBEBCBFDGDHFGABCGABBGEAFAHACACHDDFHCBBFHFHFGCHCHGBBHHGCGCACACHCEFEFADDFEFEGGCGCB,False +422,2.0,4.0,4.0,2.0,2.0,3.0,4.0,6.0,HFCFCECBGGGDGBEHFBAHAHBHDHC,False +423,19.0,10.0,8.0,8.0,6.0,9.0,8.0,8.0,DEABABCFEFDAAABFHFAFAFADACCGBABAGHBABABAGHEHCGDGDCDCGEHEGDAABAEHBAGACDFFCFHH,False +424,22.0,16.0,21.0,30.0,13.0,19.0,17.0,12.0,BCBEBDAEAEAHAHGHCBCAAEADGFGDGDCACFCDEGCDHBCADDDDDEABADADADAEGBGBHCGFAFDCDBDFACDBDBCFEHEHAHGFGFGFGECHFHCCGDGACDFDECFDADEBHFFDFDFBFBEHAGCGDFCBGDACBCFDAD,False +425,12.0,15.0,7.0,11.0,10.0,19.0,9.0,9.0,CADACAFHFDDCDBFBDBEBEDEHFABACFFHHGFDFDGDGHAHACCBEFDFGEGEADFFCEGBABAEHHBHBGBEBABGBEFFFFABGFFF,False +426,10.0,14.0,11.0,11.0,11.0,17.0,18.0,9.0,BFBAAEFEHCHGAFEBCFCGCGBGFHFCGGAFAFBFCFHBBFEFEFEBGCECBGBGCDFDBDBDGAGEFEGHGHAADEGCGHDBAEGDDDDCDFGFGABHH,False +427,37.0,20.0,35.0,16.0,24.0,26.0,23.0,17.0,AGAEEHGHGCCCGBGCHCHCHFGGAAAEAEAFHCHCGCACADEEECBABEFEHDFBFEEBBBCEFAFADACAFFCFDHDGBFFACDGDFDBBBCGCBAAAEAECGCDHFBDBCAAGACACAFAGGBEHECECEABFEGDFDHHAAAACHCHGHCHABEGCGFACCECFFBFBABAGFFDAECEDEFFACGCGAGCDFD,False +428,16.0,17.0,31.0,28.0,15.0,17.0,26.0,26.0,FGFCCACBEDEDBCGCGFDCAAECEAAFFGGGGHCHCAGDGDBHBHFHFHFHDHAGGDDADHDHBACGCGEDHBCDFDGDHDCCCBBBBGCCCCFBDDDBCCCHCFEHHGFBFCCAAGGDADGDHEHAGCGCBDBFBFEGAGEGHCFDHHHHEHEBEHDFDGDHAAECCCEDEDGH,False +429,8.0,4.0,6.0,7.0,12.0,5.0,7.0,6.0,AAHAGBFHFCEAEBECGFGFGEEECBCDCAEHEAEDEDHGHBCFDGEGDHDEDAA,False +430,5.0,7.0,8.0,4.0,4.0,3.0,11.0,4.0,HGDCHCBCBFGAGBGBEDHAEAEGFGCGEGAFCGCGDHDBBBCCGA,True +431,8.0,19.0,9.0,16.0,16.0,15.0,11.0,12.0,FABCEHHCGDGDFDFHFAEDGDFDFBBBBFEDEAGBEEEFEGEBEFDDGBBAAAFHFHEEDCDCGEDBDAEHEHBHBHBFGCDCHEDBFBGHGFBFBCBCGCBAHD,False +432,25.0,23.0,17.0,34.0,27.0,19.0,18.0,34.0,GBHHHFEGGFGFGHBABDBDBHGGEBBDEDHHHHAHFHEHFFFGBDDEAAAAADCDHACAFDBDCGCGDDDHAGBDHGHCHABAFEFEFEFDDBDBABGFAFEEDEDEAEBFDFDHAHABEBEDDDFHCEFEAAAECCBABHDADHCBFGDHEHAGBDHHEHEDEAECEDGCEEHDDGHCHCHEDDHBHCHCACBCG,False +433,11.0,10.0,8.0,8.0,5.0,5.0,7.0,5.0,GEEEBADHCHEBEACABDBDAHABABABCDCGCDABFDCACABGGAGHCHFFDDGFGFB,False +434,8.0,2.0,9.0,3.0,9.0,11.0,9.0,7.0,CECFFFHGHBHCFCFBFHDACEEFCGEDEDAAAGCGCEFFAAGGGHFHFHEGEGECAA,False +435,15.0,9.0,12.0,17.0,12.0,13.0,11.0,8.0,FEFHFAFEDEDBCGGFBHACGCFCHADADAFAEAEADHDBDFHEDEDBBGBDADAGAGEGECCHEAACBCDCEGFGFDADGHHFDFCCCBDGEFADB,False +436,9.0,4.0,4.0,2.0,2.0,7.0,7.0,7.0,HEFBABCEFAFABGGAAACFCFGHBHACGFGAGAGHHDHDHF,True +437,13.0,14.0,15.0,27.0,27.0,6.0,29.0,26.0,DDDEHABAHEHAHDCBGDHFCEGBBHBHADDEAGGEGDGDGCCDCDBDBHBHBAAHGGGGACECEGGGECCDGDGEGADADGFHEEDEGACAGHDDDFDFBEHCHGHFHEEEHEHEHEHEGEFDGDGHBCCEDHBCGDHEEBAGHGEGEGEDHBHCD,True +438,22.0,9.0,13.0,21.0,26.0,17.0,18.0,21.0,GAGEHFHCEGEDAFAHAHEDBDFDABAHEDGDBCAEGDDDGGGGAGEHHHGCCFHHBHBHBHAGECAGDGDGDGEHDFAGCEEFEHEAEAEFFCECFFFBDADFDADADAFEEEEAFAEEBABAHEFDGHEHFCDCDCECHCHFEAH,False +439,24.0,19.0,22.0,19.0,24.0,22.0,19.0,24.0,DCDCAAAAABAFGFDFDHGCGCGBDACCCCEHFACHEDAAEABAHABAEFHFCFCFBBHFHEHEGCGDHFECBBBGBEHEAEAHDGDGHCHFBFEFEBEDFAACDHDFBHADCCEHEHDBFGFHDHDGEGADADEDEBECHFGGAGEFCCBCGFBBAGEHFHGHEHEFECBGA,False +440,23.0,14.0,11.0,16.0,9.0,11.0,13.0,16.0,DCDGBGBAAHECEFGFGAGHHEDGBCFDFGHGEEFADAEGFBAAAABFBFDAACCCEDHHHDDAAEBHCHABCHAHAHABEDGFGBGDDDDDDGAAHACACACABFFHBHBHB,False +441,5.0,9.0,7.0,7.0,5.0,6.0,6.0,2.0,CFDBDGCADBDBDGAAEAEBFBCBFGHBEGDHDECECBCGFGFBFAC,False +442,21.0,17.0,17.0,31.0,26.0,21.0,12.0,20.0,AAAGDEAFCHCBEDDBDBDHCAAHBDBDADHFHFHFHFHFDFEADADHHCHDDCFBFACHDEEEDABADAFEFHCACFFFEFBBEHGDGEGFDDCDGEGECCCCCFCHDEEECGCFDEDGBBDBGGHBFAFEDADFDHEHDHAGDGDBAEEEBEDAHAEBEBEAE,False +443,22.0,20.0,27.0,22.0,26.0,31.0,22.0,17.0,EDEAHFDFEBGFEFHGAFAFEDEAHDFBEDACCCBCBAFADAHFCGHGHDCDCGGHBBGACADFEFEFBFBFBHBHAHAGGGEGAGACECECBAEFFDEECDFECECBCEHDFCABHBCGDHBFBFBFAEDCFFHFCFGFDEDEDGFGFGFBCHEGGCEDGCCHDGFGCCCACEDEAEABABADFDH,False +444,25.0,15.0,17.0,18.0,21.0,13.0,21.0,25.0,GCAFBBBBAFGHBACAFHCECHBEDEHHHEDAHABCGDEAAABDBHAHBEGGDGACDBGGGGHGHGCECEFHFCCGBEEEEEDFCGDGDADADCECBFFCAEAEADGDHAHAHEHDHAHEFEHDGFHFHBDDAHAGAGAGAGEFBHECFCACHDH,False +445,4.0,5.0,1.0,1.0,6.0,3.0,0.0,1.0,FEBBABEBEAFHFEAEAEBDC,True +446,3.0,5.0,3.0,4.0,0.0,2.0,5.0,1.0,DBDAGBGCGCGCBBBAGFDHDFA,True +447,27.0,17.0,19.0,29.0,21.0,26.0,19.0,16.0,AAEEEEFDFHEADAGFGFGAGHFABBBBDADAHFDGCHFDFAFGCCBFFHDHDADEBHGCAHAFCCGCHEEADCBFFDFAFACAEECDCDBHBDCCEDEAGABDBDGGGGHFHFHDEAFDCDAAABAGCGFDFEEEBGAGAHBGDGDFDFDHHACCDCEBEAECEFEFDFDBDB,False +448,12.0,3.0,7.0,7.0,6.0,6.0,10.0,15.0,GCACACAFHFHGHDHAHDDEDCFAHACAHGEFHBHBFGDEHEAAAGAGCDAEGEBHDGFGHHCHGH,False +449,27.0,20.0,31.0,20.0,16.0,31.0,25.0,16.0,CCFCACAHBDGCGCBCGCDCBBEBAGFFFCFCDCBHBEFDFDHGGDCFEDBDFDCDCFFDBAECHADBCHCHCAAAAFAFADDGFCECGCGDDEHGHFFEHGHGFGFGAEFBFEFDBHAFDGGCFAFHHHBHEAGAEAEABGHFAFACACBCACGBBAGACAFFGFGFDBCBCGEEEECFADGBGA,False +450,2.0,7.0,4.0,2.0,6.0,1.0,3.0,3.0,DGCGCBDBHCECHBEGEABFBHEAEBEB,True +451,8.0,7.0,6.0,1.0,2.0,4.0,4.0,3.0,FGFHEABCCCDBABAHCHEAGCGCBAAAABBBFGF,True +452,12.0,16.0,17.0,11.0,29.0,15.0,19.0,16.0,EGDGEGHCFCFDDBECFHFHGEBEBEBEBDBAHAHADCEEEEEEEBECCBBBGDCDCFGHHEACAGBGHFEGEAECFDEGFHCEDFDFDCBHEAEAEFBGCGBAHFHGGEEBFGFGEHAGAGAFCBHHHCCECEG,False +453,4.0,3.0,6.0,2.0,6.0,8.0,4.0,3.0,CCFCEEHCHBDEFAFAFHGDFEGEFBFBFCECGAGA,False +454,17.0,13.0,25.0,22.0,19.0,16.0,28.0,27.0,AGAHHCDEDGGGDHHFEEGEHHCGGHGABCDCDAAFCFCGAGCFFFHEEEHEBGBCFHDAEEBDCDCGCGCBHBFCFHDHGBGDHCHFHBHDHBEAFCCDEDAGCGCDCFFHGHGHGAGADACAEABFCECECEBEHAGAHHDGDGHGHGFDFDEBCHDDCDGBGEA,False +455,3.0,8.0,5.0,6.0,3.0,3.0,1.0,4.0,ADHHHDFFACBCBCHCBDDGDBDBEBEAEFCBB,True +456,17.0,25.0,25.0,21.0,21.0,26.0,24.0,21.0,GEGBFBFBFBGAHAFACDEDCCHFFGBGAACFCHGFCFGHDAEFEFGFGHEBEBDAFGFAFCCBABEHCGFEDEDGBGBFBEHEGGCDCDCBGHDCCCDFAGBHBDEDHCHCHEHCBCDDDDFBEEEEGGBFCFCHAHACGFBBHDHBABGBGDGDFAFAECECEFDFDBGCHBAAHHEH,False +457,12.0,10.0,8.0,8.0,4.0,11.0,8.0,8.0,DBDFDFCCCHBEGFBHEFACBDBGHGBFAFGHAHAHGDDDCCACGCEHGFGFBFBABABDHFAAAEAFA,False +458,20.0,11.0,18.0,22.0,26.0,28.0,20.0,28.0,BFGHCHEAEAFFFFGABCFGFECECECECHCHGHDHAHEEEFHAAFBCGHDHDHCABGHCFDGHGACFDDDBCGDDFGGGGEEABGFAFEHAFEHAFAEAEABAGFDFEEHEFECDADHDHBHEHDHCHFHDHFHGDDDDEDEFEFGDCHCECEFHFAGBFFEFCADGBGBHA,False +459,18.0,25.0,19.0,16.0,13.0,17.0,21.0,14.0,CACACDEDBCBHAAGHBHBCEDEDAGGHDFDEDCHFHECFBFACAHAGGGGGAGDFBABFFGFBHBHBGBHBACABHBGCGBGEFADCDCHAHDHDBACABBBGEGEFCFBGBEFDFABABFCEGECDCBCGDBEGFFCFDGE,False +460,21.0,19.0,19.0,30.0,29.0,19.0,23.0,32.0,FDEDECCDEEHFDFEFEFHAHDCGCGCFDDDCGAGAECDHBEBAHGCGEFEDHDHDGDBHBADCDCHHFECHBGBEHADBDHGHGHGHDHFBGAGHBFBAECGGFEFEFDGDCDAEGEBACHGGDDADFHAEABBGBABDFDFABEDAHBHAHAEDEAEHEHCFCHEHEHBHBHGGCACAHEEEEFDFCGDH,False +461,9.0,19.0,19.0,25.0,19.0,17.0,20.0,16.0,BEGCGDAEHEDBDCEHECACAEAEAFCEGHGHFHGHCEDDDHDEGGFEHEFDFGFDBDBDGDEDCFCFHECBDHACCBCBFGDGCHBHDDBGBGFCBCDDGDACFGGGGFGBEBEGHDBDFCFBFDFDBHHAHAEDFBCBEBEC,False +462,9.0,14.0,11.0,15.0,9.0,10.0,15.0,17.0,CHCHCGCBEBDHEHFBGDGDGDGDBDGEGCHHBDBDACFCHGFEAHFFDCGAGBFHEDEHHAHAEBHBHGAGBFBDBCFCBCBADAGEGHHEFDFDGDAH,False +463,15.0,16.0,16.0,16.0,13.0,12.0,15.0,14.0,EDEGEDHBHDHDACHCBCAHADGDGAEEHFGFGFAEGEDECGGAFAFDBCHCGCEBABABABDEACHCBABAFGEACFDBBCBEGEGCDCDADBDFHHHHHBDCDGBFFGFHCBCFG,False +464,20.0,13.0,10.0,7.0,14.0,12.0,14.0,15.0,HHHBDFFCHCGCGAGDFDGEBFBABAFAFHGHBAGEGEHBACFCEDBACCCABADAGBGAGEEAAFAFACGCFAHEHEDEBAGEHEHEGAGAEFHHHHABEBDBF,False +465,32.0,28.0,23.0,18.0,15.0,22.0,28.0,21.0,CAHHBFBGCACEGFGAAABABAGGCGCGEAAGCGEEDBDGDCDHDBBABAFABAEDBGCEDBDBAHABFHEDEDBFFGAGHHEGAGHEECDCFBHCGBDBDBFGFDFCFAAACACFGHGAGDCFGAGFFBHCHCEABHBFBFHFAFHFEFBABGBGBGHHHAHAGEFCCHBHCAGBCDCECADADAG,False +466,14.0,31.0,26.0,20.0,17.0,27.0,15.0,13.0,BBBBBCGFEFDFDFCCDCHHDAFADACCEAGGCGCACFFEGECEFECCACGEBAGDGHBABDBHBHFCBHFCFCAHDCDHBGFEEDEDFAFHHGBBFAFCCCFAFDFEBBABACHHBDBDBFBCCFFFFFFDBBBBBEBECEGEGDGDGEGCHEBCDFBBBDD,False +467,15.0,12.0,15.0,11.0,17.0,18.0,18.0,13.0,HAGECCBCFHEGGGGBGBDBGBAFACCFCFCBDFAAAAACEEEFECDFDCDCDHBGGGFGDABAGAFFEAEFHBEDEDEFBAHGCGCHFGFGFHHDHECEAEGFAFHHEHEBBGEHFDC,False +468,22.0,12.0,14.0,17.0,19.0,18.0,16.0,15.0,DADADADAHAGABAEHFGFGEGBHBGADHDGGACHEHCHGEFFBCGCAFGDGAEHEAAFCFGAHAHEDDFDCHFEFEDEBECABEFGBGAGCCECFCBBBBHAEBECCADEDHHHEDEDEDFFFFGDAAAFCF,False +469,18.0,26.0,29.0,20.0,29.0,19.0,16.0,15.0,CGCGCHCFCGHHCHCHCHCFAEAFFECEBFGDHDCECECHCFFDBDEDBGGEGAGEHBBCCACABEEEAEBEBACECGADBBHBDBEFEFEFCDDGCCBAHHFCBHBADAGFDBEFEFEAECBFFHABDBAEDECECEDBFBDBDBDACGEGEBADCDGBGDGACFEFBAEH,False +470,6.0,1.0,5.0,5.0,3.0,4.0,4.0,6.0,CBCAGGHDHDHDHFHFEECACADHCAFAFGEADG,False +471,8.0,12.0,3.0,4.0,7.0,8.0,8.0,2.0,GAAFBEGEFDAGEGEFEHGBCFFFFGBBBEBABABDBDBEBDHGCABACAGF,True +472,9.0,4.0,9.0,5.0,3.0,6.0,1.0,7.0,HACGCABHCEAFHBHDAAACFCBEDEDADAHFHFCFAFBCDCHC,True +473,2.0,1.0,5.0,2.0,7.0,3.0,2.0,10.0,CCHCDDGFHAEBEHHFACHHFHEHEHEHECEG,True +474,8.0,7.0,5.0,9.0,9.0,4.0,1.0,12.0,BCDHBCBADCDHHAHDHAHEDEDBHEEDHCHAFAHAHCEGDADEFEFEFABHBEB,True +475,11.0,5.0,2.0,1.0,3.0,2.0,5.0,4.0,AACDCFHAGAGAEBGBHBFEAGBGAAAHAHABE,True +476,25.0,30.0,25.0,21.0,26.0,22.0,25.0,24.0,HGHEDBDBCHEHEDEDEDEDCAHDCGCFDFGEGDGAGAGHGDGDCAAHABAFACBCBCEDEAEDEAGDFEBEBEHGHFHFCBBFGHGFEFBBBFHGBCFCEBABADHBCACGFHFACACDFABHEAEHHDGACHFBFBHBHBABGGDBABGFEFBHGHAHEBGBGCFBEBECGCACEFAGECACFDFEAECCBGHCDD,False +477,15.0,14.0,22.0,19.0,17.0,22.0,25.0,22.0,DFGGGFHHCHEHBGDEEBFBAAHGFGFGACCCGHFHBHCDEEFEFBFAFBFCGCEDEHEHEBFAFAFAFGCGCGDBCBFFCHCDDDEAEAGDEDECGDGABBHDHDFDFDGCGAHEHFHCHAACDDBHHACBGBGAGFFHCCGHHCCGDGDGCGEE,False +478,14.0,12.0,9.0,13.0,13.0,17.0,7.0,13.0,AFAFBFBDAAADFFBFBEHGFEFHAHFGDDFDHAHADABFBFHEHECCACGFBDBGAEHCDCHGHGEAECECEFECADFDBGBHBHEHDDFEFDBEAC,False +479,29.0,20.0,16.0,24.0,27.0,18.0,17.0,26.0,GEHHHAHEGBGCHCBCFGDGBFDHCCBCHFHAEFEGGDHDACEDDDCDFDFDHBAADHFHBEFEHCHCDFAFABAEGBHBABABAEHEAEAEDEAFHEDAGEBEFGCEDEFEDHBFFDFAHHDBDGDHEAEGCBDEDBAGAGAGAEAHACACAEAEBHAHGFGEBEADADBHBHFCC,False +480,11.0,14.0,7.0,9.0,18.0,15.0,6.0,9.0,FAFEGDGBBEFEDEFEFABAGEGEFFFBBCBEDABEGAAAFHFDEHHFBFDFAFCDCDEGHHCHBABCBEHEHEBEBEDEHABEFACDC,False +481,8.0,4.0,7.0,16.0,11.0,8.0,9.0,4.0,EEADADFDEAFBFGEGFGDGCHDDCDEBEGEGCFCHDAGCGDGAECFCEDDFDEABABADDDDEHFH,False +482,11.0,7.0,25.0,5.0,16.0,24.0,10.0,11.0,EAEAEACFCBCEFEGAGAGCCFFEFGBCFFHFCFAHACFCEEHCCFDFEEHBHFHAGFFEFEBDAGCGFAFEFEHECGCGCFCFHFHCCCBCDDBCCCCFDFHAECBHG,True +483,24.0,31.0,31.0,29.0,20.0,23.0,19.0,21.0,HAHEECBBBBGBECEFBFHHCHFHDBGBHEGEADAEAEBBFBCECFCACABHCHCEBFDFCFCFBFHHHEGCDCDCDHDCECGABADDDBAGAGAHEDEBBDGCBCFAFABAHCBCFHGHBDEDGBGEHCDCFCFCAHFBCDCDGDHABGFEBDBDBDGAFAGAFDDCEFABAFDDGAFEFDGCBABHCGDGDCDCAE,False +484,10.0,14.0,9.0,7.0,6.0,9.0,6.0,9.0,HCACBFBFCFCFHAHADACABDCHGHGCBFDHCBGBABFBDBFBEEHADADHBBEBADAGECEFHBGEGF,False +485,10.0,4.0,11.0,5.0,13.0,7.0,15.0,10.0,AEAEHCHCGCGCBEGEGFGBGAGFGEHAFGCHDECCAHADDFDFHFHEGEGACCBHDHAEGEGCGHBEEEGAFAC,False +486,10.0,4.0,4.0,3.0,10.0,7.0,9.0,8.0,HGHCFDHAFAECEFHFHEGECHDDACABAEEEGGAEAGAGAGAHFGFEHEFGBBB,True +487,5.0,6.0,9.0,7.0,10.0,8.0,5.0,12.0,FCFCFHFAFAFGEDCBEHHGGEHEHAGBHCHFEAEDEDBHADCBCDHDHDFBEBCCHCGEHE,False +488,11.0,11.0,11.0,8.0,15.0,8.0,13.0,12.0,CBABEBFHFGEGHCDCAGDGEABBCGGBBHEFBBABGBADEHCHCEAEAEGEFFFCGCEHDHDHECDCAFAGAGAGEHEGFDHCHEHED,False +489,22.0,25.0,26.0,26.0,18.0,25.0,28.0,23.0,BEBEBEBFFHDHDHCHDHCCGCFAGCHCHCDCGCABABAFCHEHBCBCDCGCEHAHAEGGABFDHEBECGCHCHFDADAHHEGFBHAHFDGDCCCHFFGGGGBFAFABGFEFAGGFGDBAHFEGEGEDBBEDDBHBDFDFGGCEFGFBFHGADADHCEGEGDGDFDBBCBCDGBADABAFCFAFADDDBCGAE,False +490,19.0,24.0,22.0,16.0,30.0,19.0,23.0,31.0,FGGAFEFECGHHEGEHEDEFEHAGFBFBFHAEAHAEAEACDEBBHCECACEGBBFBDBCHDHGCFEHHAHAHBEBECGGDGCHBHGFGBDFCGHGHDHBHBACACHBEAABDHEHDHFFBFHFHEBCDEDEDFDGEGAGADBCHFHABDBDCFAEAEBEBECGCGEHHCCBCHCEGEGHFCGEG,False +491,16.0,23.0,19.0,29.0,31.0,20.0,28.0,25.0,DHDBCECECAGFGBBEEEECEDEGHCDGGAFDFGFGCGCEHGHGEDFGCDFGFDDDCDEFEABDEDEBEBHBHBGGHBDBHAFABDGHCECGAEAEAGABHDHDHDHBBBGEHEFEDHBEEEGGCDEFGHGHAHAFCFGFEDCFEABHFHEBEBDHDHACBCFGAGFGHEHBGBCHFGDDADCDADFDECB,False +492,2.0,8.0,8.0,4.0,4.0,4.0,9.0,3.0,GEGFACBGAGECCHCHCBFDGHCCGCGBDBDBEBEFDFBGBG,True +493,21.0,13.0,20.0,26.0,11.0,13.0,10.0,15.0,AACGHHEEDBDBDCDCDBEBFBFEGDCEADDDFAFAEAHHHFAFADEDCHCBCAAGACDDDDDBCAGDCDBEHGHGFGABDHDHCCCCHADAEAEDHDAACAFAFBFEDGBHCCADHBGBDFCFCHCFG,False +494,4.0,3.0,5.0,3.0,3.0,7.0,4.0,3.0,AHFEBAHCHGFGFEFDADBFFCFCGCGCBEAD,False +495,0.0,4.0,1.0,1.0,4.0,0.0,2.0,1.0,BDEEBEGEGHBCB,True +496,6.0,16.0,13.0,12.0,12.0,13.0,12.0,10.0,DHFEEBAFCHCHCEFHABBCBCFGECECEGEBDCDCBBBBFAFEBEGGCGAGFHEDGBGEGCHEBDBHBHCGBHAGDFDFDFDFDHCADFDFGB,False +497,19.0,9.0,12.0,22.0,14.0,24.0,20.0,18.0,DEDAHEBAAGDBHHGABAGCHCDCACFCGCEEACBFAFAGEDDDHHHCHCGFGHBAGAFAHDDDDDGDFDFHFEEDEHFHEBFDFHBAGHGHFHFEDEDFDFDCGBFACAGAFHFEABGEGFGFGFECADAGGDGFFF,False +498,8.0,3.0,6.0,14.0,8.0,17.0,6.0,15.0,GFFDFEGGBEBHAEDGFAFEFDDDAFHCHCDCDGFHAHFHFGDHCEFHCHCFDHDHAFDFEFAFABAEHFHDHDEDH,True +499,0.0,6.0,1.0,2.0,2.0,3.0,3.0,4.0,EDECHDBGBGBHBHFGFBHBF,True +500,9.0,11.0,8.0,10.0,19.0,12.0,9.0,5.0,GCFDBACGFBFAAAAGBFAEGFGCGHEAGHDFFCEDEDEDEDECHBEGDDEAEFDFAFEBEHEHEDEBEBEBCBCBFFEGBCE,False +501,8.0,14.0,12.0,11.0,8.0,12.0,9.0,4.0,DBDBEBDBDFDAGCGFBCBCFFGCDCDEDBBBECECFBFECABDDAFAFAGEFBHAGAFCHCDCGHGHBFBEGEFCAG,False +502,5.0,5.0,5.0,5.0,9.0,6.0,4.0,8.0,FEFEBHHHAHABEBDDFDHDCAFFECEAHCBCEAEBHGHGCGFDEGE,False +503,12.0,12.0,13.0,25.0,16.0,10.0,18.0,21.0,GBGBDECCCFHHBACGDGDGDADCGCBBHDHDHDBDFDFDHEHGCEDEGEFAFHBEFFGCEHFFDDHDHGHGDAACAGBDHGHEDEDGAHCGDGDACEGAHAHDHEHEBEBCBFBEHEADDGDCAHE,False +504,10.0,15.0,9.0,13.0,14.0,7.0,8.0,9.0,CBEEFBBGBGBDBABADFBAAHEBEDEDGFCEBDBHAHBCBCBGGFDFCAGAFDGDHDHGEBEHFHECECEAHCDDEHEAEADCD,False +505,18.0,16.0,17.0,23.0,12.0,18.0,20.0,12.0,FGFABEFDHDHFHGDBDBGBGCACDDDHAHBHFFFBGCGEAEAGABHBGDGCECEDHFAGBDEAAHCEGHDEDEDFGHDDDDEFFAFGDGCFCFDFDACFCEAABGBABCBCFHGGBGEGAACCCCFCGBADADBD,False +506,22.0,16.0,25.0,22.0,25.0,11.0,27.0,18.0,AGCDCDHDBGCGAGDDCDGBGDCBCGFGHCECGHGAEFEDEAEGEFHGBCBCAAAAGGDGEHEAEDEDEBCBGFCFGDDEDECFDHDBEAEDEHGHCCCCABAFABCBAHCHGHCCDCEFAGEHAGAGHEBCHEGBHBHDHFEEEACACDEDEHGGGFBFBGDAAA,False +507,13.0,17.0,22.0,10.0,17.0,14.0,17.0,13.0,GGGCBBBEBHAEAGHDCGCDHFEAEABHCHGFGHGCCFFBCAAHEHEDCGCGCDADEHAHFDFAFCHCFCBDEEAEFHAHFCFABBDBDEGECEBGBGCGCDEEBEBFBEACBCGCGBGCFCF,False +508,17.0,21.0,24.0,12.0,17.0,20.0,19.0,17.0,ECHCHCHCGCFBGAGEBEBEBDCCFHFGCDFFHHBGBGDDDGFCFCGDGFAACACGFHDHGAAHAEBEGCCCFGFADADHBBBBABEBEBCGCHDHBGEHCACECEDDCFFAFEBACAEHEHBGBHEFAFBGHGFBCBEAEAGFFCF,False +509,4.0,0.0,5.0,5.0,1.0,0.0,3.0,4.0,GHDCDCDCDCAEHGCDHHAAAG,True +510,10.0,11.0,3.0,4.0,7.0,2.0,18.0,3.0,HAGGGGAFAGCGEGBGAEBGGEBEBDCEGDBDADEBEGAGAGBBBCGGBGAGHBHAFA,True +511,2.0,4.0,2.0,2.0,1.0,2.0,3.0,1.0,DEDFHGABBBBFAGCGC,False +512,2.0,4.0,2.0,1.0,1.0,1.0,0.0,1.0,HDBABCBCBFEA,True +513,4.0,5.0,8.0,7.0,6.0,8.0,11.0,4.0,GGHGHGDBCECECEGFHDABADEGGCGCECBFEGACFFFFBFCFHBAGGDDDD,False +514,20.0,26.0,19.0,15.0,24.0,22.0,24.0,21.0,FGFEFEFBHGHBEDHHHHEDCDEHEHCBFHGAFAFBFDCACAGGGGGGGHBBABFBFBCHGGBACGCGDFEEEEAEFFFFDECECFCBCBEAHCBADEDAGFDEDBBEBEHACAFAFABHEEDCFGHDAABEBEDGGHGHGDDFEFAHAHBGCGBGCCCABBHBAGCBHBE,False +515,22.0,23.0,26.0,33.0,16.0,30.0,25.0,23.0,GGGGCBEHCBCFEGGFADHDHCGDACCDBDGFCFHBHGAABFBAHAHDGDBDADACGCFDFGFDDHBGGGEBEBEFGFHBEFABEGCGCGHAHFHFHDBDBDCDCDCHFFFHFDFAGEGBABFEDBDCECBCDDHDBGECADEDEFFFFAFDFDECGHDFDFBCGFECHHAHAHGCBCDADAEAFCFCDHDABAHABC,False +516,17.0,13.0,13.0,12.0,15.0,20.0,10.0,20.0,FDFAGABHFHCEEAFCEGGBEBCBCBEBDHFACGHGCACACAHFHDBGFGDAEAEABFDEDHDFAFEBDHHHFHFHFHAHAHAEAFADCCFBBCEHFFFDGDGBEHHHHGCBEFEAEDFC,False +517,26.0,21.0,23.0,17.0,23.0,30.0,24.0,22.0,ABAEAEAEBGGGGGAECECEDFCEBAGHFHAEADCCGGGAGBEBEBEDCDFAFHFHGCCBHAFAFAFHFGBCDDFACGFGHDEEGEFEGBGFGADFCFCFCBAEABCDHHHCHFHFHBHAEFFFCFBECCCFFDFDBCHCADAFHBABDFDBBAHGGEAEHCGEGCDAGAHDGDFHFHFEBABEBH,False +518,7.0,13.0,9.0,12.0,7.0,6.0,7.0,5.0,CGCECBHDEBGBAFCDBDBDACEBDDGDGEGEFAFAFAHCFEHEDBCBDBDCDBBBDCHFBAGAGH,False +519,15.0,23.0,14.0,11.0,17.0,17.0,14.0,16.0,AFGEDCHBBBBBBGGECEFFBACACBCGCBHFAAABCCEEDDDHBBFBFBGEHEFDAEAFFFEHAGABAFHFBDBHHHBEBEACGCGCACDCHEEBEGGDGHGHGDDDCBGAEBEFEFAFHHHFHFB,False +520,18.0,12.0,17.0,12.0,18.0,12.0,16.0,36.0,EGEHCHDHDGDGCADAHAHFCEEBACEEEADAHHBCBEHEHEBAHCEEGCFEFAFABHBHGHDCGCGDHDHFHDHDHAHCHABCGCFBHHAHFHFHFCEHEAAHHBHGEAHHBFCCGBGFHAEAEGCHBHGDGDGAGFHHC,False +521,4.0,11.0,9.0,6.0,9.0,15.0,6.0,12.0,FFFCCHBHCFCBCBFDDGDGBFAGCFEFCHCGFBBBHCHDEDEAEBHBHGAEAFFBEGEHEHEHBHFFFFHD,False +522,17.0,10.0,12.0,14.0,22.0,13.0,17.0,18.0,EEEEDEABAGFEFEHGHBDAAABDBDAEHHAHGHGHDHAEABHHHHHBCGCFCFCDBAGACEEGCGAADGDHAFCFCEBEFDFEEACGHBEFEFEFEDCGFGHGEGDBAEGEDCHAHGDFDGC,False +523,0.0,4.0,3.0,2.0,1.0,0.0,4.0,2.0,DDEBCHCGBGCGBGBH,True +524,25.0,20.0,21.0,11.0,21.0,16.0,21.0,28.0,FGHGHEHEHBHFHFBFBDBEGDCHCGAEAFCDEAAACHEHEHBFFFFAAHCGGHGBGBHCHCDCGAGAGBHHHFDCDAEABBBCECBGGFACHCECEAFAGHFAEHGGEDEDEBHHACCCACBCHDGDGAAABAGFEBHAGBGCFEEDEAEAFBECHHAHBHB,False +525,5.0,5.0,3.0,6.0,5.0,16.0,3.0,8.0,DHFHFEFEADAGEGECBDFCBDDFHCHFAAAFEHHFBBBGDFFFFFFFHFH,True +526,1.0,0.0,1.0,1.0,2.0,0.0,4.0,6.0,HGHCHEHEGGHGDAH,True +527,14.0,26.0,15.0,11.0,16.0,18.0,25.0,17.0,BHFABADGFABCDGGECEBEFEDBDHGFCFDBDBCEFBFHAGBFEFGFHFHCHBHEHFHFHCHCEDBDBEGHGHGCBCBGDEEFCFBGBGBGBCBDBGAEAGBGAGECEAFGGGHGCCAFGGEAEDBHAGABAFAGHHCBBB,False +528,26.0,33.0,22.0,21.0,21.0,26.0,21.0,23.0,HDBFBDGDGHHEBFFCECFBABGGEBEGGAHEHABGBCCCABDFEFGFADACCGABDBFBADADBDAHAHBEGHFHBEGEBCBCBHAHABADCHBGCDEDEDHGGGGGCDBFFFFFAEECHCHCFEBEAADFBFBABDBGEEHEGEFCFCFEAEADCGFADHHFBDBAHAHACABABFBFCFHBHBHCDFGCD,False +529,19.0,28.0,16.0,26.0,16.0,17.0,19.0,17.0,ABADGCGBHDFFFGFGDGFBDGGFAFCGGFHHAAFFFEAAHAHCBCBABADDFFFABDBDBHGDACHCHGBBBBBGEDADAGCBEBHHEDBCBCBDEEGADABABADADCCBCBDFDFCBCHFEEEDEHHHGHBHDEECHGDGDBEEEDEDGDGCBBD,False +530,10.0,4.0,8.0,6.0,5.0,11.0,7.0,6.0,FFBFCDCGAGFEDCDBEGEGFCFCFCBAFDBHAHAHAGACAHAHEGDFCFADEGAFH,False +531,13.0,7.0,11.0,9.0,7.0,13.0,13.0,17.0,GCABEBFBAHHHGHGAAHCHBEBCDAFHFHBCDCDCDFGEGCHAHEHCHDFFFGFGCGAAAHGGGHFCECHHHGAAEADFBFDFDEDAGF,False +532,6.0,4.0,4.0,4.0,4.0,11.0,3.0,7.0,ABCDHFHFECEDADFGHAFCFCFBFBGADEHGBFHEHFHFAFA,False +533,14.0,30.0,24.0,27.0,22.0,23.0,21.0,29.0,CEBEDGCHDGAAABHEHGCGBFBEGDDDCDCHHDEGFHCEFBGBCCFBAEAGABEDFDCDCDHDHGFGHGCGDDFBBBBBDFDADCDGBFEFDBCFCFBDHDGFACAGFDFDEAECFBBHBHCACAHFDEHEHBDBGBHBFBEDCFEEHBHBCBCBHEFEFCHCHEAFHBHBHEHFGCAEGHGHGHGHED,False +534,7.0,14.0,11.0,10.0,12.0,6.0,11.0,7.0,ABADCBEGAGABDBHCECDBEHGCBCBCGCFCFHFHFBBCBGEGHGDGEGEDDDCDEDABAHCFEEAEFEBBGDEHBG,False +535,1.0,8.0,7.0,5.0,5.0,7.0,1.0,7.0,BHBGFHEDDFCBBBBHHHFEFHFCFCACBDBDEHEFECCCD,True +536,5.0,4.0,11.0,11.0,13.0,6.0,6.0,8.0,CDDDEBHHGHDFGCCACEDEDECEGEACACHEBFFEFEFGFGDGDHAEEEABCBHEDCDCHHDC,True +537,28.0,21.0,11.0,18.0,13.0,11.0,21.0,19.0,HGAGAGFDDHGEBDCGAAHGHEDBDFDEGAGHDECCAAAADDGBBCBHBHBHGCGCBBBFBFGABAGCHBGAFHFAACAGDFEFEGGBFHAADADFDADBBBDAEAFHGHEHEHAHAHAHAGEGDCDCHBABABECDGAEBE,False +538,3.0,5.0,4.0,4.0,5.0,2.0,1.0,6.0,HCHGHAFBEBEAEACDCHBEBFCEHBHDDD,False +539,6.0,6.0,7.0,4.0,9.0,4.0,6.0,1.0,CCAGDGDGEFBCACBCGDDBFEFCFEABABCEEEABAEGEGEH,False +540,4.0,1.0,2.0,4.0,0.0,6.0,5.0,0.0,FDDGAGFGCGAGAFFFBCDADF,True +541,9.0,14.0,13.0,6.0,8.0,6.0,10.0,5.0,CBCGEGEFEHAGEDBGEGAGHDCBCGAGAGHDFGAACBBDBDFFCFHFDACACBBEBECCCCHEACBBBBB,False +542,16.0,16.0,8.0,16.0,13.0,11.0,10.0,17.0,EAHAGFDCGCGDEHCHBAAADHDHEHEFBGBABFDAAADBDADADHDGEGCGHGBFAFEBBBBHFDFDEBEFAHEBDGFHCHCHGDFABABDHHHAEBEHEDEBCCF,False +543,21.0,26.0,17.0,27.0,29.0,23.0,26.0,18.0,GDEHHBFFAHDHDCBHBGEDBDGAGDHCEEEBFFACBBEDGFCFBEBECAFDDHBHDEFEFEFEGGCGBHFFCFEHBHEFBHBADAEAGAFBFGEGEGCGDEDEGCGCBDFDFDADABCFEBBBDBGGGFGCDCDCACFEDBGEGEGHABGEGEAAAACCHEBEDEHBABFGFHHEHADGDADADAD,False +544,22.0,22.0,21.0,19.0,23.0,23.0,21.0,20.0,CGDGDBCFDADCCGDBDHAHCHCEDFFGGGECECEAFAHCFDDEDAGCGCBDEDEAEHCHCEEECEFBFHDHGHGEGCHFEAEAEFFCFEDEABHHHGFBAGAGBDEGECECECHBHAHGBBFBGBDFDGAAFAFGBBCBGBFHEHCBDFFFHFBAAHBFBAAAFAGABDB,False +545,23.0,25.0,25.0,15.0,25.0,17.0,21.0,33.0,GAGAGEEHHHFHFHFHEHDCFHABBHBHBEBHFGBCCACACACGHBADHBECECEBABECCHCFEGHDCEBGGEBEBEFHHADCDCDFDHBHCAEEHEHFHGHGHFADCGFHCACACACBCEGDFHCABGDGEGFCDHGHAAAHBHBHBEBHBHAGABEEGEDEGFBFCGEDAGADDBBEAFCF,False +546,3.0,2.0,2.0,4.0,0.0,4.0,0.0,0.0,ADADAFCFDBBFCFD,True +547,13.0,21.0,3.0,11.0,13.0,5.0,12.0,11.0,GHBADHBHBGBEHDHEEFGHDHGFEDDDEGEAEDFAAGBBCBAGAGAEDEHBHBABABAGADBEBECEAEBBBBGBHBDFGCADBFBHG,False +548,25.0,24.0,22.0,17.0,28.0,18.0,39.0,21.0,CDCABDBHBGBGBGBCECBABGBGAHAHBFEEAEBGAGEHFACACDEGEGECHAEGEHFHFABEGHFHAHGHCDCEBEGDBFAFHGEGBGAGDBDBDBEFECHFHEBFGEGEGECAFABEBGBGHGFGEGCCCCHGFACGBHAHAECFGAEDHGHGDDDEAFADGDGDCAEGGACFBFAGEGACCEHDCDGGFG,False +549,3.0,2.0,4.0,4.0,5.0,8.0,5.0,2.0,HFEFGDGFBFDFEEEFEFGBGCCACDCAGAHFD,False +550,1.0,3.0,4.0,3.0,7.0,2.0,2.0,6.0,ECEBHBHGHBECEFDHAHECEDEDGCHF,True +551,16.0,22.0,21.0,26.0,28.0,20.0,19.0,21.0,EGEDEBEAEADDDCFCABGEFFHDBECHBBBBAHAFFCCDDDDDDHGHEFAAAAAGGBGFGBGCCHEHFBFHHDCDFFBFDGEGFCABBEBEBECDGFEECACDDBCFEDEHHDBDFHFHCHCEGGGEGEADCDCEGEFFHHGCCBCBDBEBEAEAEAGDFHCDGDHBHEHEH,False +552,4.0,5.0,6.0,11.0,3.0,11.0,11.0,5.0,GCCDFHFBDDEDECGCGDGHABDDGGGDHAHAFGFGEGFGFABDFHFCFDBDBFFC,True +553,5.0,13.0,12.0,7.0,6.0,1.0,8.0,8.0,BGDACECGDGCCCBCHCGCDBHHGBEAEAEFBCBEBDGCGDGCBABABEDCHHHHHBBDB,True +554,21.0,23.0,19.0,23.0,24.0,21.0,32.0,21.0,FAGAHAHFHGHBEEFGADABCBGBGFAHEDEFGFBHCECEHEHDGDEAAHGGGEGFFDFBCHGAGHCDGGGABDGDADHFEBHBHGGCACBCBCBGBCFADADGDEDACBGHEFDFHFHFBDDDDBHBGGGCDEFEGEGECHCBCBEBEBEFFAGBBFACECECDAEFECGAGEFDGGAADHDH,False +555,11.0,14.0,17.0,9.0,22.0,14.0,9.0,22.0,CGEEDCDADADBDBFFFHCAAEHHHEHEHAHEFFCFBGHHHFHCHDHEBGFGFBEECFCEEECGCGHEEEEADHBHAABCCACFCEDHCHCHBHBDBECGCEFFGFABBEBEGHAHBE,False +556,4.0,3.0,4.0,4.0,4.0,1.0,0.0,1.0,BABHECAAFBDCDEDEDECAC,True +557,11.0,15.0,15.0,16.0,14.0,18.0,14.0,14.0,BCBCBGDGCGEAHHEHGAFFCFHFCGAGACEBEBEBAFGCCDGBCEFDFDAEADDFDCEBFBFBEHDHEHEGEGBGHFHDDDDCCBGBCBHAHDEFFFGGCHBEAAAHFFDFDFDHC,False +558,5.0,2.0,3.0,3.0,1.0,2.0,3.0,2.0,DGDGACBFHFHAEACABACDG,False +559,29.0,26.0,17.0,17.0,20.0,26.0,24.0,23.0,DADCDFFHFAFACAFBDBACAGABFGFBHCHCFFEFEFGHGCBCAEGGGDBDBABFHFAEADDDEDEHAAGGDBHGFFFFCGAHBBGBGECEGEGEGEBEDCFFDFCCEAAFDHAEBFBFAHAGFHCCGBGBGBGAGABEDADHEBEHHAEFHAHABCBCHAEAFAEBHGHBBBAGDHHHHC,False +560,7.0,9.0,14.0,11.0,8.0,12.0,13.0,5.0,FCDCEFEFGHDAABACGCGCGDEBAHHBCCFCFGEGDBDBDBAFECDFDFEGGCAFABCFGFGEGHCDEDGDGFCBCBH,False +561,16.0,32.0,21.0,19.0,21.0,20.0,22.0,22.0,AFBGBGHGEDFAACDCDCEFEBCFCGHGHFDABABAHCCEAHBEDEDBDCCHGHEBEBEBCDEFGDGFBFEDHDHDBBBFFEGBGHEDGDFBGBACDGEBEBHBHCCGHGHGDGDGHGHBCAFHGHGFABAFAHAFCBCBFAHDHBBCBGFEBABCBCFCFEEBCFEDEAHBE,False +562,18.0,21.0,6.0,6.0,14.0,3.0,15.0,20.0,DGAAHCHBAFHBHBGCAEAEAHAEAHHHBCBGGEBDFAHAEAEBGAGAHDEGHAHBEAEGHGHBABHBHEDCGHGBEDGBGEGBGBABDBAEEHFHBCBCBHB,True +563,19.0,18.0,15.0,19.0,14.0,16.0,17.0,24.0,FAFAFABBHDCDCDFDCAABFCEDBBECDCDFFAGADBCHGGFHDHGHEECEGDADABEHHHHCHDHDFAHGFGFBDBCBFHAGABDBGBFDGGFCFCBHBHFHEHEHEGAGAHAGABAGABEECDCHHEBEDEHAGCGHDH,False +564,3.0,3.0,2.0,1.0,0.0,0.0,0.0,2.0,BABCBDAHCHA,True +565,8.0,12.0,12.0,9.0,13.0,13.0,12.0,17.0,BFBFEEHBFAFGGGCHDHDHGCDCGEHAHEEBBAEFGCGCHCFCFDBBBHCEBEHEHFGAGFFHFHABDGDFDFBHAHDHEAABCEGEGEDCHCHC,False +566,24.0,19.0,7.0,22.0,15.0,14.0,18.0,21.0,AEADAHECBGBFHGHDHAGDGHGBGBHFHBDDDHGHDHDADHDHAHDEDADGFEFGFBDBDFAAAAABEFDHHHEGBGAAEDEGEGAFAFHHBEEHCGBEADAEFFBFDFDBDBGBHAGBCBEFDHGCACBCBAAACAGE,False +567,18.0,34.0,25.0,23.0,26.0,29.0,16.0,24.0,CHFDFHBCBDBFBHEEAEABABCGAFDFDADADADBBBCBDBFCEEEFFAFDBDBGHDHBBBFFFDABFHGCABABABAHHHHDFBFEFHBCDCFCFBFEEGECFHEGEGBBDDHDEDHFHDHDFBAECCBHBEBHBCCCBDBEGHGCFCACEFAGEGEGCCFBFEHEHCGFECGFDAGFGHCCCEEEBEHAHDG,False +568,10.0,3.0,8.0,11.0,10.0,4.0,2.0,8.0,EGEDEHEHCDCEAEAEAFFEHCDDDCACHBHBDDDHAAACAEBFAGAHDCCFEDHD,True +569,16.0,11.0,9.0,12.0,15.0,17.0,17.0,12.0,EAEDEACHEAGBHHFFAGGDADADHBHAFFGDEDEHFBFCGBGFFDGHAEAFBCBEAECDADCGCGFGEGEGAGDEDBFFAFAFCBHAEAEGEGFGFDCHCGFBHBHBH,False +570,5.0,3.0,10.0,3.0,5.0,7.0,4.0,6.0,DADCHHGACACECHCFCFHDEGABAFFFFECECFGGHBCBCEH,False +571,19.0,19.0,10.0,25.0,20.0,11.0,12.0,21.0,EGEGEDDDADCBFBFCHCHGAGDHDHDADGHEDDDDHBHBHCADEEEDDHDBCEAABABFEEAEGHGHFEADDDCABHBHBHFHFEEEEFDCEEGCBCHGAEAGABFBHAHEHAFABHBFDDDBDBHAAFBBAGGCD,False +572,9.0,14.0,14.0,11.0,15.0,15.0,19.0,10.0,EFEAEGGGDGDADFHFGFBFBFGDGBBEBEADHGCBCBCGCECGFDCBCBFDFGEDBDHCAFEFEBGCHAFGFGEEHBGCGCEEEBHCHBADCCGGHAHADAGFHFE,False +573,4.0,10.0,13.0,15.0,11.0,8.0,6.0,4.0,AFCCGEEDEBEBAHAHADFBCBCBEFDGHBEGEFFBFDDBCECDCDCECEDDDDDGDCDCEBBGDHFCCGF,True +574,15.0,27.0,18.0,27.0,33.0,20.0,18.0,26.0,FACGCDEDBABABADHDBEFECGDFHHEBCBCGHHAEBHBHGDADGDGDEEEDEBCBDBEAFHFEDGDGDBCHEAADEDEAEDHCHAFDEDHDACHBHBHEHECFBABHDEEEFEGBGDDHGFBFBFCFCEBEBFFCECEGEFEDGDCBGEGHFCECEBGBHBHDHCEFFFBGBHHHEFAAHDG,False +575,16.0,17.0,13.0,14.0,16.0,19.0,22.0,14.0,HBCFCFDFEGAGAHHGEGBGDGFHEHAFBDBDCHCHGFDEDEFHFBEBHBHBEBHBDFDEDEHEGEFFACACGFHADGFADGBAEADAFBCHEFFBEBGBGBACGGFGFAABGGDGFCCACAEAECDGGGC,False +576,21.0,18.0,24.0,12.0,15.0,14.0,8.0,14.0,CDCDFBACHGHECECEDECECHHAHBGFAAHAGFEBCHAGBBBABCBADCFEGABABCGCFAFEBHAHDHECACHHFCBBBEBECFCFAFAHAFCGDFDFDBEBDCACACADBDEHEFEDGCACAC,False +577,11.0,6.0,10.0,4.0,4.0,6.0,15.0,11.0,HHGHAHGDGCEBABABGCHCGCECHCACHDFBABFHFCAHAHFFBFGGGGGGGACAGECDGAADEHG,True +578,13.0,11.0,13.0,13.0,10.0,10.0,11.0,13.0,HDHDFAHCHGEAAAACGBEEHHDEEEDADCDCACACDGDBDBCFEAGHCFCABFBFGCEFBHHHHGBGCGCGEEHAHFBFDDBDBCGDGAFAFB,False +579,16.0,20.0,17.0,10.0,16.0,13.0,17.0,18.0,HBHCDAHECCCCBHGEFCBCGFFAFACBDGDCHBHBCBEBEDGDFEHGHBHECCCEFAGAEHDGDGHBFAFAGAGBGBGBEECCAFAFDBBHFECBGHCHBHDHBHBAEEEAEHEAGAGFGFGDABA,False +580,19.0,23.0,27.0,23.0,24.0,28.0,24.0,26.0,FGFGCHDADGDHFFDCDABFFFFBCEAECEHADCDFDFABAHABDEDBAHCCCHBAAFAEGEGFGHDHGHBHGHDCFCFCADEFEHBAEEFGCDCGGGGGEHFGCGCFFHFHGHBCBDBDCCCGEBEHFBFCFEECFGHGHFHCAEBEBEGHGHFEFDCHCBCBGBDBEAAABCCEAFBHBHDHEEGABDDDED,False +581,14.0,16.0,19.0,20.0,20.0,20.0,13.0,20.0,ACAFBEAHDHEHBHCABBCHFHCEEGCHHFCDCBBEBHFABGDHFHFHBHBHBGDDDCFFHFBFGFECDCEAGAGACCCGCDCDEDEDADADFFFAFAGHCDAGHFEEGHCEEEHECECEGEFDFEEGDDDGDBBFBFBADH,False +582,13.0,15.0,13.0,20.0,21.0,19.0,19.0,16.0,EGGAGAHBFFEFEHECDCFCBGHFFGAGAGEGCGAGBFCFDDDEBEHEHCFBDDDDDDADAFAHHCFDEDBFFFFHAGCBDAFBHBEDGFGCBCBGEGEDCDCDCFHEHGHBDGEHABEGAGHFEDAHEEEEEBHB,False +583,6.0,13.0,10.0,9.0,17.0,8.0,10.0,9.0,FHFGBBBBABCCDHBEDHGFDEHCGCBEBEHCFCFBFBDBACFHGHGEEECECEDEDEHEDGCAEADFDGEAEGGGEBABEH,False +584,18.0,27.0,27.0,16.0,19.0,28.0,14.0,16.0,FHFCFAFHHBEBFBDCHBGEDBAFFCBHBCFGFGCGCEEEDEDBABGEFBGBAFAFHEGCGCDCDBHHCHAHAHGCECAHFHFDEGHBBCACABABFBFBFAFCDCDBABEBECFFGBECCCHCFAFDDDDFDBECEAEDBFCDCEFGFABABCCGEHCABGFEF,False +585,26.0,16.0,22.0,22.0,20.0,21.0,22.0,26.0,FHDHDHFCEBBDBAAAAGFGCBEDHDHGHAEAECDCBEBHCHAHGGFDAEFCFHHHEECCCDCDCDHAHABBECACADAHCDCDFBBEDAAGAFFHCEEEAFAFGFCECEFACAEAFFHEGFHCAGECFFGBGFGDBDBABAGGGGGHHHAHDDDHHHAHDGEGFGBGBFCEDGD,False +586,8.0,5.0,12.0,4.0,4.0,13.0,13.0,7.0,DFDCCCCCCFEBEBDFFAFGCGCBFDFBAAFHGHGCGAAHGFAFGFGCGAGBCHFHCGGHFHEAEG,True +587,4.0,3.0,2.0,3.0,2.0,5.0,3.0,1.0,BGGGDBDHDFCAEAFCFBFEFAA,False +588,7.0,14.0,10.0,16.0,16.0,9.0,9.0,13.0,BCDFHCGFGAEFFFDDBBHBFBHHGAEDDFDEHEGEGEHADFEEHEGEDEDEDEHHBHBDBHBDCDCDBBFBABACACEHECGHEBDGDCCCAG,False +589,41.0,28.0,27.0,20.0,22.0,14.0,25.0,23.0,EDEHHHEACAEAEGECBBHBHBEFAFEBAFHHGHAHACAGBDBEGCDEHAHADACACGEDCCCFBBBBBFAADACAGECDFHGDDBDCDCECDABAFCBEGEDFCGBGDHACABGHECBGGCDCGEFEAGCGDAAABABABDHGEAHBGAEHGBGBFCFCFEFBHGHBAAAAHABABADAGACACGCACHDHDHAFAGEG,False +590,25.0,17.0,16.0,9.0,20.0,24.0,14.0,17.0,HDFDEGEFBBECCBDBABFFAFDFCECBAGAEABGFHCACAFAFAFHEHEHECFCHEHEHECGBDBAFEBCFAFCFAGGCFCABHGABFFEGAHAGAGCHHEHFDFBEBCBEFAFAHAEFEAAHAHBHBGDGDGCEADAGEF,False +591,17.0,13.0,25.0,18.0,20.0,19.0,18.0,19.0,ADCFCHDBAEHEHEFEACAFAFDFEFECEGADHDHEBCCCCEHHGBDBDGCCFBGDDCGABAEAEDEAFAFCGCFHFEGAGDGFHCGCEHEAGCHCBDEDCFEDHCBEBFBAGEGAHCHCBCBAHACDBDCDCHFHEGFGFGDGHGFFH,False +592,4.0,14.0,3.0,5.0,17.0,15.0,9.0,5.0,HGFEEHBHFFEFHFEGBABFBGDFBBEFEDGDEDECEBEFEAEBBBBEBFAHAGFDFEFEBGCGFGBGFECE,True +593,13.0,8.0,10.0,11.0,8.0,10.0,5.0,8.0,EAEADADGFGCDDFBFHHGADABAFHHBAEABHHGBCFCFDFAFDHDCDCBFBCCCBCEEEAEAEFDAHACDG,False +594,16.0,13.0,15.0,7.0,3.0,9.0,20.0,22.0,BGBGCGHHHEHGAAFGCGBDFAFBHCHBDBCCCFDAHHBGBAAABHHHGHGBABABCCCCCDGHGHCHAHGEGDBFGFGCGAHAGFCHGGGAHAHCHFEDHDAAF,True +595,12.0,10.0,9.0,7.0,8.0,10.0,12.0,10.0,AEFDFGFGABHBHBACAHFFEECEFDFGBCAABBCDCGEBEBHHHHFBAEADGDGHGDGDCACGCACAEFHAHGGGBF,False +596,12.0,14.0,7.0,5.0,7.0,8.0,16.0,11.0,DBGBABFCGCGEGBGCHCABEEHGGGHGHFBEBABFBFBGGGGFDFCGABABAFAHHHHBEAAADDHCFEHAHBGACDGE,False +597,12.0,31.0,25.0,23.0,29.0,22.0,19.0,20.0,GBCAEDEGEDHCHGFBEGCCDCGAFBFAFEGBBDBDBDGGCEHEHFHDCDCDEDFHHBGBGCHABGCGCFHFDEBCDHDAABFBGBHDCDCEHEBFBFEFBFHEHEGEBBDBEBABCDGDBHBDFDFDACCEFBCBFHFGCEAEDFCCDCFGGEEEAEAFAFBHBEBCBCHEHCHGEEEBE,False +598,3.0,2.0,2.0,2.0,0.0,4.0,2.0,0.0,DADAGFCFCBGAFBF,True +599,18.0,18.0,17.0,19.0,19.0,25.0,24.0,26.0,EFEFADADEGEGBBHHABBHCCGAFDHDFEHHHHHHGAAADGHFHGGGGDEACHCHCFCGEGEFABEEGEHFCFDFEBGAHCHGFGFGFGFDDHEFCFEBDFEACAFHCHFBADGCGBADGDAFCHCHDDDFDFHCHBHEEEBEBGBABABABCBFFHFDGCGBGD,False +600,18.0,13.0,8.0,18.0,9.0,20.0,11.0,10.0,FAHEFAFAHDGGGGHCBEGABABFEFAAGAGAGAGAGBHBHCFFDHBHDEDEDABCFCEDEBEFADDBFFCFHFAAGDDDDDDFFFFHADFFFBBBCDADCCADHBE,False +601,28.0,16.0,18.0,22.0,25.0,31.0,31.0,28.0,DHDHCHCEGGGGGGHGHGABHGABAGDGEGBACHDHBGADFBHGAGFGDDADGEAEACHBBFFHFEGEFFAFAFGFEFAGADDFAFCFGHBFFEDBACABFHFCCCEEDFDCDAAHFHEHDDEDGHEFCAHFFBCGCGCACABAEAEHDHFHFHFCEDEDGAGAEEEEEFDAGGGHGHFHAGEBHBAEFCFBFCEHBHD,False +602,19.0,22.0,22.0,6.0,18.0,28.0,18.0,32.0,BEHEHCBFBFGAGFFFHEEGEFFGCHCHFABHHCCBFHFABBEBCACAEAFHFABHCHGBBAHEEEEAHAHBHECACAHEHEHCGBFFHFGAGCCBCBEFEGHDDGDHFHCDAHHHHDAFBFAFHFHGHGACCCACBHBGBGBCFGFHFHFGFGFAEBCGCBDEF,False +603,6.0,3.0,3.0,0.0,3.0,1.0,2.0,3.0,AAAAHHHEAEBFCEGAGCBCB,True +604,20.0,12.0,4.0,14.0,4.0,16.0,10.0,13.0,BHADGGGBAFFHAEDBAFGFCFHFHDHBHBGFFHADDEHFFBFGHAHAHABACADFFAAGADAGAGACADDEFEFDADAHBGBABDBDBDCHF,True +605,13.0,12.0,3.0,10.0,9.0,12.0,19.0,5.0,BFBFCDGDBDAGAFCHBBBDHGADCEAABAGFGFGEGEGDGFAFEGBGAGEFFGFGEDADBBGAGAGEFEBBHGHGEDDAFAH,True +606,25.0,22.0,15.0,23.0,20.0,14.0,29.0,17.0,ABABABGDEFEFEHBAAAFDDBDGDGAGEEBHFFCAHAGABACACHEGDGDFDHGGFFHFBEDECFGHCBAGDGCHBGBGCGFDADECEBEAEADAFEBEAEFCBCBCBHBABGBHAHAGAGDDEEEHBCEADGDGDHHFDGABDBDGGCGCADGGHHDHGGEGC,False +607,7.0,12.0,19.0,9.0,3.0,6.0,12.0,7.0,CHGGCADECECGBGCGCEHDAFACDBGGFABCBCBCBCBFBCGCBCBCBFHADACADHDCGGGDFCHGFCHDHDB,True +608,15.0,15.0,12.0,14.0,12.0,4.0,21.0,15.0,BGBEFEGDBCGCGHHEGCFAGEBFGHBCCEGAHACGBDBGBHAHGHGHEHEHACABADADAHACBGDAEHGHBDBDBEBAAAFCGCGDEDCDEDHDAGHGDGBGEGDC,False +609,11.0,19.0,6.0,5.0,9.0,14.0,11.0,10.0,BBBBGBFBFBABDHAHFBBAHEHFCAHGGDGDFCBCFCGAHBDBGBGFGHAHGBEEAFFFBFEFEACACEEGEAEDGFHAHBBBF,False +610,7.0,6.0,1.0,2.0,7.0,8.0,15.0,3.0,GGGGGDGFBAEAEBFHGHDFAGBEFEFGFGBHAGAGBCEAEGBGEGAFF,True +611,9.0,11.0,18.0,12.0,13.0,14.0,18.0,18.0,DABAEGBGEGEGEGFDHCGCHAHFHFCCCCHHGADFBGEHAHEHECFHEHEAGABDGEBCBFFFGDGBGACHHHDHCFCDCHHGDCHCBCDCGCBBDADGGGEDECBFFFFEF,False +612,1.0,6.0,5.0,8.0,3.0,4.0,3.0,4.0,BEBEBGBFBFDDCHBDFCHDGACHFHGDCDCDED,True +613,5.0,7.0,4.0,9.0,3.0,12.0,4.0,8.0,DEEHBFGFCHBHDHFAGDBDHDFCFEBHHHBFBABAGAGDFDCDFFFFCFDA,True +614,5.0,4.0,10.0,9.0,2.0,6.0,6.0,7.0,GCBCBCGGBFHHCFCHHDDDDCBGAEACACFDADCCAFHFHDHDEDGFG,False +615,20.0,20.0,21.0,19.0,32.0,21.0,14.0,26.0,FCCGGEHECEDEDBBECHCHCFGBEHECCCCCHCGCDCDEHAGCECEDDBEBABABEBEAAAAHAHEFAFHFEFBFBFAFGEEEAEHEBGHEHDBCBDAAEFFHCGFHHHGCEAGDBEHEFEGDFBFAHHDBCHFFBEGEGFHECEADADADBHFHAHDDFDFHEAEBDBDGH,False +616,4.0,1.0,4.0,5.0,3.0,3.0,4.0,3.0,AGAHCHBGDFDCHEDEDEFCFCDAGAG,False +617,14.0,17.0,16.0,17.0,18.0,16.0,11.0,15.0,EFEFHFABEBEGEAEBEAECBDHFEEGEGBGDHHHHHBHBHBHAFAHDBFHABDDFDHBGDECECEFEFGDABAFAFABDHFBFCGCGBEFCDCEADDDFACAHDCCGDDCBCGCFCABECGCD,False +618,29.0,30.0,26.0,14.0,18.0,25.0,13.0,17.0,HACCBHBFAFBFBFHFCBAAGAEBEFDDBDAAACACACEEDDAEFGBGFEFCABAGAGAGFGCHCAGFBBDFHAABFCFCFDHEHCFBFBHADBBBBHDDBCFABBEBFBADAEBCBHBHFHCBDDHCHGHCACAGAGDFCFEAEBECECECFCECECGHEBAFAEAGHBCF,False +619,31.0,22.0,24.0,19.0,30.0,25.0,19.0,29.0,CFHEHCGFFACEHBDEEGGACFCACAGAHAEAFDCGBACEFGAECCAGHBHBDBAEAGFBABAGACAHHHAHCHCDCDAGGGAHAEAEDGGCEHFHFHFDGBHBCEHEDEFEFEFEAADACHFBDBDBDBFBFAEHFHBHEHEGEDEDCCEBFBFCFCAHDBFEAEFEACAFADEBEHHDEGEAHBHCHDBGBCDHFGF,False +620,18.0,17.0,15.0,24.0,21.0,15.0,18.0,13.0,ECDGDBDGDGDEAEBEBCFGFGAGAGHCDEHEHBGGGFEAAFBBDFHCDCEEEEGAGAGEDFDHDHAFAFHEHDADADBDECACEDDBHFEGECADDCFHBCBCHCDDFDGBBBEAECEDEFABAHCHGDABFBFGFCBGA,False +621,0.0,2.0,1.0,1.0,4.0,1.0,0.0,1.0,FEEDEBEBHC,True +622,14.0,20.0,14.0,20.0,27.0,29.0,12.0,26.0,CDCACEHFHFHBHEFEDEBBFFFFBFECHHAHEHEDGDEEBFHFHAACEDECCCCEFEHAHBHDHFHFAFABEEEGEGEBDAHEEEEFHDDDGDEDABHBAFGFEHABFBABDBFFFHFCFHFBGCABBGBHFHFDDAHGFEFEDHCHDEBGGGBCDDDCGF,False +623,16.0,25.0,17.0,19.0,21.0,19.0,21.0,15.0,BFDFDFGBGDHBHEDCACFCEHEDEBCFDEDADBDACADDEGEGHAHBHFEBCCCAHEHEBEBAAAAGCFCFGFBEEEHBHEHGBDBDAGAEAGBDBGFEFGBCBCFGEGBGHDHGCCAADCDCBFBAGGFGEHDFBEBFBFDFCFHBGGGEB,False +624,23.0,27.0,21.0,27.0,12.0,19.0,33.0,26.0,DHAGAGFBFCCHHGGBCBFDFACGBGBGHCABACAHFHCDCDGFGFCFGFCAEGHGABABEDEDHFHFDFBGHGEGHAHBHCDAGAGAGBBAEAFGCACBFBDDHGHBHDGDGBGDAAAAEBBGBDBDCACFCHCBDBCCCBGFFHDHDHEGEDEHHDDDHBGBHDFFEBDDEEGGGGAGHCHDBAGD,False +625,17.0,22.0,27.0,7.0,24.0,19.0,26.0,18.0,GHECEGFGAGCBEEGBGHGBEBEAEFGFAFCFHGGGGEEECBFBDGGCGCEDGFBHBCBCBCAGABEGEAEABFFFBFBFHEGFGACAEFDBCBCAGAGAGFFCCBEHCCBCBDHCBEHCHCACEBFBCGDAHFCECEDACAEHHHHHDAFGHCHCEGEH,False +626,21.0,20.0,18.0,14.0,19.0,24.0,20.0,19.0,FGFGDBFGAAHHDABADDECCHFBGCEEHGHGHGAFHCHAHBCBFAFAFABBBABADDGEBBFCFCFCFCBCDCDHFAGGHGHGAGEHBFAFCHHEGEFBHDHAHAEDGAGAGEGCDEHECCCBBBAFFFEFDADBBEDEGCFBFCGAEEEEFEF,False +627,22.0,20.0,15.0,21.0,16.0,16.0,15.0,16.0,GBGEFDACFGFGHBHECCFAAAEEGBCHCBCFADHDHDBDBDFDADABAEDFBADACBCFCFEHGCEFEAEBHDHDFDEEBBHBGAGDGAEAEGGHAHDDDDFDGBBBAAAABDHGHFAFECCCECHBDBCBFEFGAGAHH,False +628,7.0,15.0,8.0,13.0,14.0,12.0,11.0,8.0,DEDBDHFHDCDCBBBCBDBFBFCGHGAGEFAFAEADBFBGBGHGDCFADBDFEFEDECEFHHCBEAGGGDEBECEABBGHGFDHEEFE,False +629,1.0,3.0,3.0,8.0,6.0,2.0,4.0,5.0,HEHDHDHDEFBGBGDDCDHBEDECGCEEFGAD,True +630,11.0,10.0,7.0,6.0,8.0,14.0,8.0,5.0,CAHAHABFCFCACFCAHAGDBCEGHFHEBDFAGAGABBBEBCFEFEFBFAFBDEDEGGDFDABFFEFGG,False +631,14.0,11.0,20.0,21.0,13.0,15.0,14.0,16.0,HCFAAHBFCFAFHFGDHFCFBBBEBEAEAEHEHGDDBHHHFHDCDEGECFHFDFDADACADHGEDADHDHDCDCGADDECEAGBBCECDGGCGCABAHFGCDCGFBHBDCDGAGCCCDCGEFEF,False +632,4.0,8.0,5.0,12.0,1.0,8.0,6.0,3.0,CAHAEDBCCFGDBDFFBFBHDDDDDADCGBGBCFAGDGFGFHDBDBF,True +633,3.0,4.0,7.0,2.0,2.0,6.0,5.0,5.0,CBCECACAFEFDAHBCGFGFBHCHDHCHGGFBFG,True +634,15.0,14.0,8.0,23.0,21.0,16.0,17.0,8.0,GDDDADADACBFGFGFAFACADAEEBEBFCGBFHFHGEDDDFCGABCBDHDHEEFHAHGEFDFEFBFAGAFEGDGDGBGDEDEBHBDCEEEEGEBCDDEAECDDDEGGGAFAEBFBGHEDAB,False +635,16.0,23.0,27.0,12.0,33.0,22.0,20.0,34.0,HEHACECAHFBGBEBHHHHFFCECEHEAEGDGDHAHBFFFFFFFGABCEFEBECECHABGCGFHEEEEEEGBCAHEHCHDFBGBCBCBHHGFBHDHCHEHEHCFCGCGEFHHHCDGDEDECBCAFEFAGHDCABHDAEACCHGHFBBHDEAGBGAFDDGCACEFEFEHEHEBEGCCEGBGBCAHBHB,False +636,18.0,21.0,19.0,22.0,14.0,15.0,21.0,26.0,GHABCDDDAGGFFEFDFHBACHDHDECGBFBFAAGECECDAFBHCDCEBGBAAAGHHEHEHEHEBAFDFCACECECEHHHCHDHAHAHCDBDGGGDHDBCCFCGHHHGDDDBEBFCFDGAFBFBDBDBGBGBABHHCHGHGDBEGAAHDCGAGBGF,False +637,7.0,11.0,15.0,9.0,7.0,9.0,10.0,13.0,DAFBFHGDGAGCDCDGHBCECFCGCDEDHDHBHBFBEGEHDADBBBBGFHHAECHGHGHBFCFAACCCFFHGACHCBCECE,False +638,23.0,18.0,27.0,21.0,18.0,14.0,17.0,30.0,DEDCHCBFEAEAEABAHGDGDADEBEHCFDGGCCCCDCBFGFCCHDHDHFBABDHEHAHFHCAFAEADHDHCHEDACCGCGCGCBAFHHHECDDDBGHHHCHBHAHECFBBGBDBFHAHGHCDGHGCGCBBBGBABFGCGAEEDFDAEHFHDHEEACAEFEACHCAAA,False +639,8.0,5.0,5.0,6.0,7.0,4.0,6.0,5.0,FGEBDBDBGHGDGCAHAHCDAGAFAFBEBEGEFDCHAEECEDACAH,False +640,25.0,30.0,19.0,18.0,18.0,25.0,21.0,28.0,DBGBFBFHFHCAFAFACGCHCHEHEGFGADHHFEAEGEGHGEAEBDADHBABDGGGGHBHDDGAEBDFCGCFFGACDHBHFHCHFAGHEDACAHBDDDAHHEBEBABACAGBDEDGHBHFHFCGCDFBFBFAHGCBDDCBAEAEFCABABACACEFHFBAEHEGBGBHBFFHBEBFBFBFHCBC,False +641,10.0,7.0,19.0,15.0,18.0,26.0,16.0,17.0,EBEBEADCFGFGAADCEFHCAEDEAEFBHEHDGDGDBHCGCFHFHCHFEFGFGCECFCGCEDAFEGDFCAEADCFEFHHHFDFGFGAGDGDFHHGACFBHDHCGFGFCHCHCHCDEECFFFFEBEBFD,False +642,17.0,19.0,31.0,20.0,20.0,27.0,31.0,22.0,EFGFHEBFAHAHFHGCFCFGFHFBFDHDAGAGBECCHCBGBFEABDEGEGFCBDDFEFADADBFEGEBBAEHEHAHAFGCGCGCBCBFGFCACHCECGCBCAGFHDBDCAFGCGCGCGCDDDCDGDGFBHGFFAHCFCFHECDGDBECCCDCEGEFBFEHHGAGCGDHAHGHEFDHAGBGBGHDECE,False +643,10.0,16.0,8.0,13.0,16.0,18.0,19.0,19.0,DBDFCEGABABHBFGAHEGFFDHCFCFBDHHACAFECHHHHGFGBEHEGEGEGFGBBDBFEFHFCEDECFAAGFGFEBAGHEHEHEGDBDFDFBEBDBDFDBGEHCAAGHGHGBGHGHD,False +644,23.0,23.0,24.0,17.0,10.0,17.0,18.0,14.0,BGGGGGEGBACCECHCHCACDBAEFEFHAHACFGGADDCDCDCDGHGCBHBAAFGFGFABBBBFBHGFAAADADCDEACDEACBHEEFCCHCHAFBCHGEGBFDFHEBBHBDBCHDBDBGFCFBDCGFGFACABBBAAAAAFDCDC,False +645,19.0,20.0,19.0,12.0,21.0,19.0,19.0,26.0,BCHEHEABABAHAHDHBEDEAEGECEBECAHDGCFEFCHHAHDHDHFBDACABGCEBHBCFHGCCCAEEDAACABBHGHGHFHBEBHDECEBDBCBFEFHHHGHGHGHFHFBDGEGACEFDFHFEFCGGGAEFDFGCGABFFCFCGBGAGFBAEA,False +646,24.0,19.0,25.0,16.0,26.0,22.0,27.0,28.0,DADGFHCDDBDHDHGGAEECHHHFCAGACFCFEDCCECEGFBFBCBGEHEACBCBGGHGAGFHCGCGEFEDAHAHFHEBBBHHAAEAECBGAAFBGBHBHAAFEEAECEGHGFCDCHHHHBDFGFGFGBEAFHFDAHAHCBCEHGHGFCDGDGCGEFABDBFBAAAHADEDEGCGHECEFEFECECG,False +647,19.0,19.0,11.0,23.0,12.0,13.0,15.0,22.0,FGFAADEGEAEADGDFHAHBHDGGGHDFBHBDDGDCDHBHBHEHECEDBDBEBHHDHEABCCGFAHGGEADAGFDAHEHDHDCDGDHHEHFFFGEGBDCACACDFDHBBBBDCGAAFAHABABACACFDFBBHB,False +648,14.0,18.0,21.0,17.0,4.0,13.0,14.0,14.0,HDCCBGAGBGFGFHCCACHCGCBCBEDEBCBDBHFCFCFGAGACBGFDFBHBADAGHCHBHFCACDFDBABAEGCHHDBDCFBECGCGBDAFFGHDBDBDADADACFDADCHHGH,False +649,18.0,10.0,20.0,21.0,15.0,23.0,20.0,19.0,CDCFFDAABAFGFDBHFHGADADAHGHGBDFCHHHCDCHAHADCDGDGDGCEFGFCECFCFCGCAAAAEAEDBDBFFHHHFECECGGEGAABHECFHDEDGHGAEADFFHGDGDGEEBDCFGEHFCGCECEDDFFFFBFBCBHHAG,False +650,2.0,8.0,12.0,4.0,7.0,2.0,3.0,2.0,BECADGCCCCCBCBCBDGGFECECDBDBHECEFABHBCEE,True +651,23.0,17.0,14.0,13.0,18.0,7.0,9.0,12.0,HGFCACACFCDEEAGBGBADADABCGDAEADGDBACFHBEDAABHBHGHCAAEBECECACEDECEGFGAAHABAEAHDHABABADEBCFCFBEEEHEBFBAEHEHDCDBGBHD,False +652,9.0,5.0,7.0,3.0,3.0,4.0,7.0,7.0,FHAHAGGGGHGCGCEHEAFAFCHDECHBABCFGBHBACDCDAABA,False +653,17.0,14.0,10.0,12.0,16.0,15.0,12.0,13.0,FFDCCCGHBHEFBAEAHDFFFHBBBBGAFABABAEADAEFCBDEEHFDACHCHDAFCFEDGBCBCBEBEGGGCHHDDAGAEAEDEDEBEHDHAHEFGFGFGHGAAEAFG,False +654,18.0,23.0,28.0,27.0,18.0,13.0,30.0,25.0,CGCBCACGBGHACACADFEBGBCAEHBDBCHAEDGDFDCCAEHDGDFDFAFBGBGEDCFBFBFDAHGCCCBGBHEHAHGGGCECEHEAGCGDGDHBBDGCECHAHDFDGEGAGDGEADHCACBGBCHAHAGBGHHCHCHGEBEAEDECHBGBGDGFGEGHCHBDDDCDHDFDHCFEHDBDBF,False +655,15.0,11.0,8.0,7.0,7.0,6.0,7.0,13.0,EFAFACBEEDCAHAHGEAEFFHBHBFBFHGAAHGHGAGDCBHHHABDBEBAGAGDDDADHBCBEACHCACACHB,False +656,23.0,17.0,14.0,15.0,23.0,23.0,21.0,14.0,DBBBEEGCGFABAGAHAHFDEEHECBHBFBEAEADGDACGFGFCFDFGFGFGBEBEDEHHCFEHAHAFAHEBABEDEFGFGBGAAECFCHCEAGDGDCBCAFHFDFDFCFEEEEECFDBGGGAAADBGBHDAGEEBHDAAAHFGCGFAFC,False +657,22.0,13.0,20.0,11.0,19.0,20.0,13.0,19.0,AAAEEECFGGCCCDBDAFHFAFCCBAAHBBBEBFBAGCGEGHCAEACDCEADBDEAFCDGECEGGAGABAHAEBHHHHHCFCFEHCHFHGHCHCFAFDFDFDHBEGEFFFFAEAECEDEDHFGABFEGCHCHAHABF,False +658,13.0,8.0,9.0,8.0,6.0,14.0,16.0,11.0,DFDAACADGHGFECCGBFFFHEAAFACAGFHCGCFAFDFBBHHFGAGABABAGEFEFGDEBFBDBGACHCHCHGDGHGHGEGDGH,False +659,24.0,22.0,11.0,20.0,12.0,19.0,20.0,10.0,ECECBBAAAFHDHDHCBGFGFACABAGGHADBEAFFDFDFDEGCGCBBBFAGABBEDGGAGFDAGHGDDAEABBGBHDGEBFBHDFGCBCBEBFDFDADADBBFEHEFEFDFHFEGDCDCDCGBGAAAAAGAFAHBGA,False +660,9.0,8.0,11.0,8.0,16.0,14.0,26.0,11.0,FEGEHCHBGBGEGHGHGEGHDEBHAFACGDGFGACHHGAFCGGFEHDFDEEGBGBGFGFGCCECFAFDFDHBGDAAHAGEGDGEGFGAGEBCCCCBEEGEFEF,False +661,21.0,16.0,26.0,12.0,16.0,24.0,13.0,16.0,AHBFGAHHBCBABABCCGBEFACECGHGFDAHHCCECFFFDFAHACACBCBGBDFEFEHEDACAEDEDEGEGDGBBBGCGAHACACEFAFDFAFBDACAFFHFCFCAGEGBFDFBFEGCFCBCFHACADDCHFHFCECEHHHCE,False +662,19.0,21.0,19.0,34.0,20.0,23.0,22.0,19.0,AFAFBGBGBABGDDADCFCECGGEAEACHDHDEFCFDFDECHHGDEDEGGFEBBBBBEFEDDFAHCBEDDBACDCDAHAHGHDCFCFDFEFEDHCHDDADBGCABDHEBBFBDCDHDEDEABDHEBFBCEAGGHFHEAGFGFGCGDGFGDGAGAGABFBFDDHDCDHHGHECDCFAF,False +663,30.0,32.0,21.0,26.0,25.0,15.0,23.0,18.0,GBDHGHGHGBGFGABAEEDBCBCAHAEEDFDADEGCCCGHDBBBEDHGGFCBBHEAACDBGAGBGFEAAAAAABADGGBGCDCFCFDFCBHAHBBBHBHGDBDEHBHBHBEAABABDDEAEDFDEBEBECEGEFAFCFCADEGCGBABABFBCEADAEGEGDCDGBFHAEAEFCDDHEHAHFDCDEDCAC,False +664,14.0,12.0,16.0,18.0,20.0,25.0,19.0,23.0,GFFDFGFDEAHBCEEHCFEEEABFGFGHGAGAGCGCFDBDBDEDEABABDBHFCFHDGAGEHEHEGDCDCFAAGAEEHFGFEDCHFHGGEHDDGBADDGHFHEHEHECFCFCDCAEFFFGFGCBHHCCFCFBFHFHEDADHHHHABB,False +665,1.0,1.0,5.0,0.0,2.0,0.0,2.0,0.0,CCCBGGAECEC,True +666,13.0,18.0,8.0,9.0,12.0,13.0,18.0,15.0,FADABCFAFAFGFGFBCBGGGFGDCDCABDHDAEHEDGDGEFFHCGEHHFHBGAGAHEGEGABFCGBGEEBEHFHBHBHBHBFBHCABBHGEEDCDBABABHGGAE,False +667,12.0,9.0,6.0,10.0,3.0,13.0,8.0,9.0,CBCHGHFADHGAGBCFDFAADDFCFHDAAAAAFCFEAAFADCDGDGHFHFHGBFBFBEBHGHGBBDFDEB,False +668,25.0,23.0,24.0,17.0,11.0,21.0,16.0,12.0,GDAFFFFHBBGCACGCECBHAEDBBFFFBCBCACACGBABEBEDDBFAHBHDAGAGBGBGAGBGAGEDBAFCCDCGAGHCDADACAEDFHACBEAACFDDBDBHBDBDFFFCFCFCFCAAAEDHFAFHCHCACHCGAGFFCEEBEBGDH,False +669,3.0,6.0,1.0,5.0,4.0,4.0,3.0,1.0,EABGBEBGBFBGDFDFDADEDBFHEAC,True +670,5.0,9.0,11.0,15.0,8.0,21.0,12.0,11.0,DFDCHCFFDHHAHACGGFBDBDCDCDAHEFFFHBDBDBEECFGDGHGBFCDADABHBHGGEGCCFFFFFDFHEBGCEFDFGFEFEHDGFGFC,False +671,9.0,14.0,11.0,13.0,12.0,14.0,11.0,23.0,HDHCHCFCFCHCFCDADADEHFHBAEGFGHCEDHFCCDEHAHFEBBBADCHHHHDHBHEDDDADHDBGBGBCBFHEBEFGBGHGFFHAHGHBAFAGBEFEBEHEGFG,False +672,3.0,4.0,0.0,0.0,2.0,6.0,4.0,2.0,HFHFAAGEGFGFABBFGFBEB,True +673,17.0,21.0,20.0,5.0,12.0,13.0,17.0,15.0,BCBDBECHCAAADCGGGGFBABABEBCBCACAGHBHDHBFEEEEAABCBCBAAHBGGCGBGHGFGAGFFCHGHGHBABFBFHCHADDFCCCECECHHEAFBFBCHHBCEGGCFAEAEGFF,False +674,14.0,34.0,17.0,24.0,19.0,23.0,30.0,24.0,BBGEGHHHEHEFABDCHCFBDAGBBBBDBFCFCFAHHEHAFGHGEGEDBDBDHCFCHCEDEDEDGCGCDDDGDGAGAGEGBHHCHADFDBBBCDDACGHGEGEHBGBGHFEFGFBBDBHBFBDGGCGCDFGCBBBDADGHFCFADGEHFCFAFGBHFHBGEAEBBBAFGGDGFEFBBHEHEBABF,False +675,22.0,22.0,20.0,24.0,22.0,17.0,36.0,34.0,CHGHGHAHAHCECDBGCADHEEGECDGBFCCHCHFGFGBBHFHFHEGFGAGCGCGDGDCBFBFEFEHEDECCHBGBDADHFHEBDBGFGBAHGHGEACGGAEAHGBDCDGDHFHBHCECBDHGGGGHBBDFDFHAAAAAHADADHGHEHAGFGDGAEDGDEEBHACFGHBHBHCGGGCAHEEAEHEFDDDGDBBBAE,False +676,5.0,3.0,7.0,7.0,6.0,1.0,5.0,6.0,EHCHEBAGEGDGDCCCCABHEGBAEDEDCDFDADAHHCHG,False +677,14.0,12.0,18.0,20.0,14.0,12.0,11.0,15.0,CCADHGFACAHGHDDDDDGFGHBADGBEBCCDDDADADABBHCFCFHBHGAGEEEEEEEGEFHCDFAFCCADBDCDCDCBBBBCHCBDAGAEHDHAHAEEHEHFFCGCDFGECFFH,False +678,20.0,18.0,16.0,16.0,18.0,22.0,18.0,25.0,DFFHFHFGFBADAGHCBCAGBCBFGFACBEFEGABBBEGHHFHFDFHEEGEBECFCEBEGGADEDEAEACHCHABEHAHAFAHAHAFBFAECECHCHGHAHBHCHFHGDCHGHEBDBDGCADEDGGFBFGDBDCFFEHDFDFDGDHCHBGAAA,False +679,13.0,13.0,11.0,11.0,12.0,13.0,13.0,10.0,DADAHACGEBDGEGEDEAACHFGEGEGFGFCFAFEBCBFEFHCCFCHCHEHAFFDBBBHGCEBGBGAAHFHGHBFDEGAGBBBBDDADADEDACFC,False +680,21.0,9.0,11.0,23.0,10.0,11.0,13.0,22.0,BHEFDAEAEGGAGBCHCBAAHAFDFGGGGBHADEDACFCFAEABHBHBAAADFFACDDDHDHCBCFHDHCHGDAHAHDDDCDADEHFFAFDEHHDHECDADAGAGBHHGHEHEHCDGDGD,False +681,29.0,26.0,19.0,24.0,29.0,20.0,27.0,23.0,AAHAECBCBAADACAFFGCEADCBGHGFEFEAEDEDBDHDEBHDHAACAHAEBCBDFFHFBFBFBFGFBEAHBCAEAGAGBEEEEEEEEDCABFGFBDHFAFAGBGHGCGEGDADHDFGBCBHBHACEBDADEDEDGGGGGGGBHBHDHCFGBBEHCCAHHFABDCGGECFBAHGDGDCEAEHECEGHDFDEDGAHA,False +682,12.0,18.0,15.0,23.0,25.0,24.0,20.0,8.0,DADHGFBFDADAEECECBFDHDBCBABAHFFFFEFEFBFBFBEDFDEAFCCHEBBGECCCCFAGBBDBGCEEDHGGEGEAEAEFDDDGDAFEGCGCGCFEDDGDFHEDGGGGGEBEDFDEDHBEBDCCEFFFEFEBABFGAGHGD,False +683,10.0,19.0,7.0,19.0,5.0,6.0,8.0,11.0,CHCGBDFEGADBBBBBEGHAFAHBGFACAGAHDBDBDADHDGDBDCCCEDDHDADADCDBBBHBFBDBDFDADEHHHBHGGEFBB,True +684,10.0,3.0,3.0,5.0,2.0,4.0,6.0,12.0,DBCHHBHEDEGAGAHFGGHFAAAGAGADBCHAHAFDFDACHHHHH,True +685,10.0,19.0,16.0,24.0,9.0,16.0,18.0,17.0,DGDFEBDHDADCDBDHFHFHAGCHCHAGEEBGBGBAFDHCBADCDHAHEEABDDFDFABBCDDADCDFDFBBGBGHECCGCGDECGDBFGGEGECHCGFFBFBDGFHBHBHBCGCGCGBDDDFHFHFHA,False +686,11.0,7.0,14.0,17.0,14.0,20.0,12.0,14.0,HDHABCEFFBEHCGCACACBHBGEGEFFFBGCECDCDEHEDEGFGFDDDDGDGAHDHDADADFFFAHAEDHFBADEDBCCGHAEEECFFEFCFHFGCGAHDFGFHFCFH,False +687,19.0,24.0,19.0,21.0,13.0,20.0,17.0,22.0,GBGCDCDHFCAHAHBFFDCAGBFBABCFFBFACBGHGHBFFGHDDADHFHFHBGGHGAFDFCGAGEDEGEADDFCBABFBABAHEDEGFGFCBCFDDADACECEBEBCHCACFEGCHBBBDDDGHHDHAHAFABDHEHEHEGEDBABCBDBHCHC,False +688,11.0,6.0,12.0,7.0,7.0,10.0,7.0,5.0,CCBGGGGFABECFADHEACFCFGFGEDFCFAFBHBCBHBDCCHCAAAAAEDDDDAFCFCEGEAEH,False +689,1.0,5.0,2.0,2.0,0.0,1.0,2.0,2.0,DHDGFGCBBBBBCHA,True +690,15.0,19.0,20.0,21.0,26.0,23.0,15.0,18.0,GBGBGEFEGECEDHDHDHDHDCGAEACGCFBFECCACGCDEDFDHDFBBBEBDHGHDCBAAAFBHADFBFHFHFHFEDDADEDEFCBBAEEGEACCHCEGACEDECECFFFFHAHEGEBABEDFBHEDEAEADFDCHFHFCGEBHCFFFGBBECGBG,False +691,16.0,20.0,16.0,13.0,21.0,17.0,19.0,17.0,EEBEDECEAEBBBBEHFBFBFDCDCBCBCAFGHGCECGGDHAHCDCFCEHDHDBBFHFGEECBGBFHDHGHEBEBEAEFBAAAAEAGGGFEFCFBABDFGFDFHAEEGHHHGDFHFGCGCGDAAACADEGBBCAHGEGH,False +692,15.0,18.0,25.0,15.0,20.0,16.0,23.0,15.0,DCAGACABGEGHGBBCAEGHHDAAAFGCBCBCGGDGCGCHCDCDAFCFGHGCGCEEEHBGGECACADEDFDFGFDBBFBCDCFCDCEEHEHFDBDBGEGFFBFBFEECHGHBAGABABEHEHGCEHBFDCCGDHEHEGBFAFAECEC,False +693,18.0,15.0,17.0,18.0,19.0,18.0,17.0,13.0,DAEAFACADHDHCFCBBBDFDEGEGEFDGBEFEBGHGHEHGGAFAFAGAEDEBHDADAEAEDEAHGHAHCECEHFHBGFAEAFBCGFDFGCACADFCGCBCBDAHFBCDEBCFCFGECDBDBGBGECECFDDHFG,False +694,7.0,11.0,9.0,10.0,9.0,4.0,5.0,10.0,CDDDBBCGFGDHDHEHBHEHEBEBEAEAFHDEGEDHBAAFHCBFEGCBCBCBAAHACCCGBHDDD,False +695,9.0,7.0,7.0,14.0,15.0,8.0,16.0,16.0,DFDCDCDEAHDDDBHHFHFCDCHCFBAEEDGAEAGGFGHAEECHGHGHEEGDGFEFEDEGBGEDDBHBHGEGFAHAEAHAHGBGHGHGDECB,False +696,24.0,23.0,24.0,22.0,20.0,19.0,26.0,26.0,ADGDAEBHCGCHCEADABGBGBFEEGFAFAFBFGDGDHHACDCHFACHCGGHGHDHCBGDHBACHBHGHGAAEBFAHGGDGHGFGDCDCGCDCAEGGGEEEEEHDFDAAAHADAFADEBBBHEHECACBEEEBABFCFCFCECFCHBHBAGABHHFHBHFCDEBCDGDFDFDCBFBCBEAGDGH,False +697,19.0,24.0,22.0,23.0,29.0,24.0,25.0,34.0,FCFEAEAHCGEDABFEFDHCHCGCGCFHABDGEGFGFGBHBCAEEHGBCBCBCGHDHFHABGHDHCCCAADDFDHDCDHFBEHEHEGFBBHHHADEEEBEBFACHHHHGHGABBBBEDCBBBEDEDFFFFFFHCHDAEFEGDGHFBDGEHHGFBDADECEDEDGFBFEGCGHHCHCHGHEFEAAGAGEGDGCAHAEAEBD,False +698,13.0,19.0,14.0,18.0,18.0,16.0,11.0,16.0,BDBFFDFDFGGHAHBHBHBHFGAGAHDHBEBDBHBFBFHCBEGEGEDCCCCBGHECDCACDBFCEDBDFDFDHDFEFHFHEHEFEBABDEHBCDDHAAADEBAGAEACGEAEFBCEGEDFCCAGE,False +699,20.0,17.0,18.0,13.0,20.0,22.0,16.0,23.0,ADHHHHFDFBFAGADBEFFFEFEGCFBDHCAEABAEAEBHFECCFDFHHHHHFHCHCHEHEAEBGHACABFCFGAGDFDFCBHGCFCBCHDEDHGHAFDFAGECECEFAGCDEGEHEAABCBGBGBGBABGEAHGEAFHFGCECADBDB,False +700,7.0,10.0,13.0,7.0,8.0,14.0,8.0,3.0,FAAEFBFCFBFBEDGHCCCCCEDEDFHECDBDGFGFADGBEFCFCGAAAHEDECACFBFBGGGFCFCBBB,False +701,16.0,27.0,21.0,29.0,23.0,22.0,14.0,18.0,ABAEADACBDBFAFDCGBDEDBBFBFADHHAABHDGABACDBDEAFCHCECHDDACAFDFDFEAEDHDFBFBFCEEBECDCDHABFBGEGFHFHGBDEDEDEDCDHDHFAGDGHGHGHBCBCBFHCEBEHCCDCBFBFBECFDGGGFCECEDHBGBCFEEDGBFBEHEDE,False +702,22.0,31.0,14.0,20.0,15.0,20.0,18.0,12.0,GHADBDAFCHAEBDBDBDFDEAAABADEDCAABBEGEGFGEGFDFBFBAEGBBCBCBEGDCDAHCHBADADGFBFBHBGBDCFGDGHCDCFCBEAGFGFHFEBECAFBFBHBHBFBEGEGEBEDAHABADABBGBCAAGDFBAGHCCFDFHF,False +703,21.0,26.0,13.0,16.0,14.0,14.0,14.0,17.0,CHABCBFGFAABAGAHAHAHACBDFHAHEHGCACDBEHDGBHCECEHFAACABHBABABECGBGAGEFCGDEFHBBFAFHFHAHEBEFEGBGBEBEDDDDDDDAHHCBCDDGEADABGBDBFGFBFBFBGEDCBB,False +704,1.0,0.0,1.0,1.0,3.0,1.0,3.0,0.0,DEECEGFGAG,True +705,7.0,6.0,9.0,6.0,4.0,3.0,8.0,5.0,AGABCBCEHFACGFHHCHEACADDDDGBGBGBCEFHBDEDACGCGCGA,False +706,6.0,5.0,9.0,7.0,4.0,10.0,8.0,4.0,BGHGEDCHCHCGCFFGDGDGCBCBAADFFAFEFGAGADFHBAFCBCEDEFCFD,False +707,10.0,10.0,4.0,9.0,12.0,8.0,9.0,7.0,EECFAEAHAHAEAEBEHFDFDAGCDHBHGGEGEGFDFDEBADDCHFDDBFGEGBGBEBEAHAGBFBABC,False +708,11.0,14.0,22.0,17.0,26.0,26.0,22.0,25.0,ADBFFHCHCHCDGFCFBHBHBAGACHDFEFHCBGECDDGEHEHDHEGEGEGECBHAECDHDCDEEFHFDFDABHGDEHEGDHDGFCCCHCHDHDHBAEEGEHEHGGGBBFEFEDEFHFCFAEHECGCAFFFCFBBCAFBCHEEGEGFFECGCGFGFGFAFAGB,False +709,20.0,25.0,16.0,17.0,13.0,14.0,18.0,22.0,CDEHBHBHAHBHBGDGEGBACAHAHGBGBGBAAAGFDEEBGBABABFGACACHGHDFDADHEFDHHECFDACABGHFHDDDAEAEDGDCDCFCBCFHBCBEBEBEBFCGCHFEGGDDBBBCEHGDACABGHGAFHHHBFAFCFHB,False +710,30.0,23.0,16.0,22.0,21.0,35.0,15.0,23.0,FAFAFAFEFEHAHAEBEFDFDBDHFCEAHHHHBEFDADHEHBCCCADEHFHFHFCGGDECGCBDBGAFAFBCDAHADBECEFHCBCBAAAFAGBFADDFDFHBGAAEABFDEDFHAGAHAGAGEGHFEFCABAFCBEBEBHFDDDFDADEEEFBFDACEGFBDBHBHBFGFBFCFGGHAHAFGFC,False +711,6.0,6.0,12.0,7.0,12.0,9.0,12.0,10.0,HGEDHDGCGCGBHBHGCFAGABCBGGEBCHCHFGDEEEHEHAHFHCGDFEFAFAFDECECDCFABCGEGFCEDE,False +712,23.0,31.0,32.0,27.0,25.0,14.0,31.0,14.0,CGABCFCEHDFDHEHBDBDECCFBDGHGAGBGCHCBAEHEHDFDBDCEFGCGCFBAGGGEFEABFBGEAAAAHAGACACECACBGDGDBHBCFGHGBCAAAFBDDDDDDFGFCECBBEEGDADCBEAEAFDGEGCCBCBCBDGCECGCGCGCECECBFBDBABDBDHDCEHEBECGAABDBGGGDEEGEBBAHGGDH,False +713,4.0,5.0,5.0,9.0,4.0,5.0,6.0,6.0,BEFEACAHDHDHGHBDCHCDEDFDGDBEFGDGDFAFBBGACHCG,False +714,18.0,19.0,22.0,14.0,25.0,27.0,18.0,19.0,GEHFCECFCAEFBFAHBCCEBFFEFECDADEDEAEFEBECECGHGAAADAGHBFGFAFHDEABBDGDEHEFEFDBCHEGCCEFBFEHHHHGHGCAFAFHFHFGEHEHCGDFEAEAGFFBADAFFCFABGBABFBCBGBGCDCDHFHCECECDHDBGBCBCGG,False +715,17.0,8.0,11.0,12.0,13.0,12.0,12.0,14.0,BAGDHBHDHABAEGHFDADFECDCGCGADHDHDHABCBHGAAFBFBEHEAFCFAGHEBCDFDFDCHCHCADAEHEGEAEGCGCFEHAGGFAFEFEAEAG,False +716,16.0,17.0,24.0,24.0,21.0,17.0,16.0,24.0,FCBCBHBCBCECDCDAFFHHHCHDBEFABAEDEDEDECFDGGGAEFEFEHCADAFACEEECFCGAEDEDGHGDGAGFBHDHFHCCGEGBDHGEBHHHEHACAEGFDFDHCECBADECHHHBBBFBFBDADCCFCDCBCDEDHHCGDDAAAHBHGHGDGF,False +717,30.0,23.0,30.0,24.0,12.0,21.0,21.0,16.0,ECEDACAHEHCACECDCGCBHAGDFACBCBAFGFGBACCCCACFGEGFHHAHABGBEFFBFDFCGABCDCBBBBBAADADGDFDFHFDCDCHFBFAAGAGAGAGFCCCHABGDGDBDCDEBHDCDCDBGFFHHGBEAAHAHDFDEDAHAGDCDBHAFGGGBABDFCACACBCFEEAE,False +718,8.0,9.0,11.0,13.0,10.0,18.0,7.0,15.0,BHBGDHDHDEAEFFAGAGABHFFFADHDHDGAFCDCAHBDECFAHDHCCBGHFCECEHEFDBDCDGEGDBHBECFCFCFHBEFFFFFHFHE,False +719,12.0,23.0,32.0,23.0,25.0,25.0,24.0,32.0,ACHDECHBHFHGHGHDADAGHCCEBEBCCGHFFGFCBEGCCDDDBGFDHDHDHGFGBCFCGCDCDCDCFGEDBDBEGGCFEFEHEBEHECBFDCDGBGEGBGEGCFEEECGFGADCFEAEADBBCECEHEBEDFHFCFCAABGHHHHHFAFABCCHCFCAHEHFBFBFHCGFBDGDEBHBHCECGDBAFHHHHHDH,False +720,9.0,6.0,1.0,2.0,6.0,3.0,3.0,2.0,AAABABDBGEHAGABCBGFHEAEDEAEFEFBA,True +721,4.0,4.0,5.0,4.0,1.0,4.0,3.0,0.0,BGBCACGCDDFDFABACECBFAFDG,True +722,16.0,8.0,13.0,19.0,18.0,17.0,9.0,17.0,DFEFCHCGADHDEDAHEDEBFHFEFEAEDEDHAHADCBAFACAHEHDCGCGCDCDHDFECEBEDEDEFGGABFBFGCACFDFAFBDGFHCADHEHEGDAEAHHHBHFHFADCFEBGA,False +723,20.0,21.0,15.0,7.0,15.0,20.0,22.0,15.0,AFCDCFCFGFGAGBCACBHAAFGFBBEEAEGHDEDBHBHEHBCGEGFACEGHGHGCGEGECAFFGEGEGEGBBFAFDCBCFCFADADBHEAEHGBGHGBAFAHCBADFBHBCBFAFHBABABAFABHFGFGEHCG,False +724,22.0,23.0,14.0,13.0,20.0,26.0,11.0,21.0,DEBABADADEGBGBEBHBCCAAEAFFDAAAAFEFAFGFCFCBHBCFFFCFBFDFEHHDHCHCFDEDHBHBGAACEFAHHFABAEEEEGBCHCECACGDHAFDFHFHFEFHAGGGFCHBBDBHBEBFBFHHEHBBBABEEFGFEDGDAHAE,False +725,21.0,25.0,25.0,29.0,21.0,32.0,25.0,20.0,FGGGCGEGDFAHHHCCCGAEABFBEBDBDHDCDEDAFGDGAEFCFCEAEADABCBGGGGGCDCDCFFFEHACBCBCGCFCFDBDFCFAHBDDFDFBEHEADCDFHEHFFEGGDGFHEGEBBBDHEAEAGAGAHBHAAGAHAHDDCBCFFFHFEDGDHDBFBEAHBFBEDFCHGFGDCFEGCHCFBFDEDFDABBFBCB,False +726,16.0,20.0,16.0,17.0,10.0,18.0,13.0,17.0,BBBBGCACACBFBABFBCDHGBCHCBADABFCFCFGAHEGBGEEEFDGDFAGAGCBCEFHFHGHFHAHFDFCHAHAGEBDBDGDCDCHFHBDDADCBFADEEEHHDGFGFHADEDHFHCBCBABADF,False +727,10.0,29.0,22.0,26.0,22.0,17.0,21.0,19.0,BCBCBCBDAFHFCECDCDCBHECFCGAGDGBHFDGDGBGBEDEDEDBCBAFAGHBHDHAADBDCGFGHDBDEGEFBBBCBEBEHECDHEGDADCDHDBBGCEHFGCAEAEBEBFBHADCECFCFEDGHGHBHFHGHBCFGBCEFDHGBGFGEBEHEFFDDBDECGD,False +728,11.0,13.0,13.0,11.0,13.0,20.0,15.0,18.0,EFFFEBCDCHCAAAADFHFHGAFDFHFCFBEBGCGAFBCACAHAHEDBBGEDEDCDGBGFGFGCHCFFDHEBBCGGGGGDFHAHDHBFFCHHDHEHEFBHBHECAGEGEFEFBH,False +729,26.0,25.0,13.0,24.0,26.0,16.0,21.0,19.0,DBDFABGGFGHEHAAAAABFBFBGBDBABAGEGCGFEEGEBEDHAEDCHABCDEFAFAGDHHAHADAFAFGBGAGHBDGCHHHBFFEAEDBDBEHDBBEDDHDHDCBCBEHCACDHFCGAGEGDDBEBEBEAGAEADABAFFFFEHGCGCEEEEBEGDHDGECEABHDCD,False +730,16.0,17.0,13.0,13.0,6.0,15.0,8.0,16.0,CCHDADACCDBABEBHDFBEAGBGFCECHBAAEAEDEGCHCHAFBHGHDBDADAFBDBGBHCHCAGAGHHCDCFFDFBFBADFBFBFHAAADBFCFGFBFHHHH,False +731,16.0,23.0,24.0,23.0,24.0,17.0,32.0,25.0,FFFFFFFDDEDGGHGHGHGFDHBCACGEGEBEBECFFBFBDECCDEHCFGEACHDHDHCFDHEGABHEGBGEAEHBAGCGHGHEEEDEDHFCGDGBAHAGAGDGBACCEAGAGAGAHFBCHCGCDCHCHBDBGBEBGCDFDBCBHEHEHGCGHBCBCGCAADDDGHGBDEDEGBBDFEAEGBCH,False +732,2.0,3.0,2.0,0.0,1.0,3.0,2.0,1.0,FCFGFHCBGBAEAB,True +733,6.0,2.0,3.0,2.0,1.0,4.0,1.0,4.0,BFFCHCHCHAAFADBGFDAHAEA,True +734,5.0,4.0,6.0,8.0,4.0,8.0,3.0,7.0,DGHGDEDEFAFBFBDDEAADFDHCHFAFBDGHHHHCCCCFCFBEA,False +735,11.0,7.0,8.0,6.0,4.0,4.0,8.0,5.0,CHCACAGAEDFDCBHDHFHBCDDHAFGGGCACAGAGBBBGBEBDFAAGAECEA,False +736,20.0,16.0,16.0,26.0,10.0,23.0,15.0,12.0,BDBHCCEBDBACHCDFGFCADHDFDHAECDAGAGCFEFCFEDDDDDDDCFHHADFDABEGGGAGAGADABAFCFAFDBEBEGACADDDHAHBECHDGBGBDDEGEGDBFCFHBADGHGHFFFBFAFAFCFCFBFCFBA,False +737,23.0,11.0,24.0,14.0,10.0,9.0,22.0,11.0,FHADCDEAAAABDBHAFADADFCGGGHGAEAHCGDDCDCDHAHCGGGGCACFCBCBCGCHAAFAHEBADAECGCGCGDGECEDGBFCDBAGACFHAEGCGEGBGCECHGGFHFABABABCCDCE,True +738,26.0,23.0,28.0,29.0,22.0,16.0,18.0,26.0,EHDFFHFHEAFFBBEHDBBBDBDCGEGEGCBCDGHAHDEDEDFAFGCCCACBDAGAEFHFHADAFHCDCDBDHAAAAAHCHCHFHFEFHCHFBAEDHCBCBCBEBDADGDAHAGACACBHEDDDEHCHBDECCGBGBHDCDHDBGCCBGDGCHHGFBAEGEAFACACBCEEEEHEGCGAADAEBGDDD,False +739,8.0,2.0,10.0,6.0,9.0,6.0,10.0,6.0,CGBDCDCHHEEAEACAEEGFHFDDDDFGFEAHCCCCCBFGAGAGEFAGAGHCEGEGH,False +740,11.0,8.0,17.0,13.0,9.0,9.0,18.0,8.0,BGAGBECGDGHFHBHBGDGDGCCCCCCFCFDFAFHBDADGDGBBCACAFEDGDHCECHAEEEBDCGGAGFGCGDAAEDEACHEHCCFGAGDGF,False +741,4.0,2.0,8.0,8.0,5.0,1.0,3.0,4.0,CECEAEHCCADDHDHGGEBHBECFCDDDDCDAGAC,True +742,2.0,9.0,1.0,2.0,5.0,5.0,1.0,4.0,CBHEDBAFFDBABEBEBHFHBHBFBGEFE,True +743,18.0,19.0,21.0,21.0,22.0,11.0,26.0,21.0,EAACDDDHDGEGBHHHHEBEBABHEHBFGCGDGEGCDCDGGCGHFFDFBBGACADADHHADCDGDGBCCCBEDECAGHGHBFCFEDEDEGGCBEFEBEBEHADBHBGGGADADFGFDAEAGBBHGDBHGHCHCACACAEFEGHCECEAFHCHBGEGECA,False +744,31.0,23.0,20.0,24.0,21.0,22.0,28.0,21.0,DADEBEBEDADABCBFGGGGGHGHAFFGBGBGCGDGFGHBCCFDEHEADABAGGBGFCFCAGAHHEDBHBHFFEHAGAGBCDFAEBHDDDDEHHACFBHDGDGACFFBDBAAADAHAHCHCEGAHAGEEEEEBHFFGADABABEBEBCDCBHFHFAADFCGCGBAADDDFCCCHFEFECEAGACAGDGFE,False +745,5.0,11.0,15.0,7.0,10.0,9.0,7.0,16.0,EFHFBCACFCEHBCBABABCECFHHHHFEFHCHCFCBHHGGEGEDDDHAFGEGCBDDDHEEAFBBCHCHEHGHBCBCDCG,False +746,1.0,0.0,6.0,5.0,2.0,2.0,2.0,0.0,GDCDCACECEDFDGCCFD,True +747,14.0,8.0,8.0,12.0,14.0,15.0,12.0,12.0,HCHDFEEGCBCDCAEEEBEFEFCABABFBFDEGFAHEHAHCHGGFCFDEDAHCHDFDGDGABHEAAFAFHFEEGAGDDFBHBHGDGEGAGAFAFD,False +748,23.0,22.0,15.0,27.0,27.0,24.0,31.0,19.0,CFEFAHGBGDEAEBEAEBHBDDGBFAHCGFHFHGEGFAFADBEFHBEBCCFCGEGADBBGGCGBGHHBEGEGABBEEEAHAGEGFGAGFCCBFAGBGFGFGFADDBDBGBFEFGFAAAABHCDDDDDDFDFHFHBGDEAEDDDEDEGEDEDECHDHCFAGAHAEAGADFGHEHDHCCGEGEDBDFCHC,False +749,18.0,23.0,17.0,19.0,17.0,23.0,21.0,21.0,EAADEDBDBFBEECFCDEGFDFHBDAFFBCCCGCHCHAFAFAGGHGECECEBEGAGDGDHEFEHCBAADAFBFBHBABGBGCFCDHFBDEDECFGFBCHHDBBCHDGDFFBFBGDGBHHAHABADADEEGHGHBHFFFFEFGCGCDEHHGHGAAAGBBH,False +750,26.0,15.0,24.0,31.0,22.0,18.0,27.0,36.0,HFCEEEDBCEHFDCDCDGDAHEDGBCCDCGHDEECFHFAFADHFCGEEAEHEHECGABAHFBFBFDACBDBDCDHDHGFBFACAHAHABAHHHCDGHGHGHAABFHFGGHADDDDDADCDEDGDEAGGGGAGBGACCHBHBFDDEEHEDDHCHCHCHGFGAHHHBHFGCGHEEDEDFBAGHGHCECGCAHAGFEADAGA,False +751,2.0,2.0,6.0,6.0,5.0,4.0,2.0,6.0,DCHAHGHCHCEBEGDFCHCDCFEFEDEFHADBD,True +752,12.0,16.0,4.0,9.0,13.0,13.0,11.0,4.0,EBEBDBDBFAHAHADAGBCBFHEEAFAEEBEFGFEFAAAGGGBAFCFCFDGEBBBBBBGAFEEDDDGAGFGCEFEGBDDFHB,False +753,20.0,22.0,13.0,25.0,23.0,25.0,27.0,11.0,DBDAFFDEDEDEFEFDBCFFHDDEEEBEFDFEFEGBGCHCEBEHEHAABAGGGDEAFDFBGGGDFAFAFACHEEBHACBFECCGGGGGGFDFAFCGEGEFHBDBACAHAEFDBDFGABFBEGCGCDHDHDGDBDBDGCFBGCAHGDGBBFAFABEGEGABADADGB,False +754,13.0,24.0,24.0,21.0,25.0,16.0,20.0,11.0,BHBDGCGFGFGFGHGHBFGCEEFEFBAHEHEHEBCDEDEDBBCBCEFECGCDBACAGDGDBBHCCGDAAEAHCEFECABABDGDGCBEDHGFEDEDBGGCACDDBEBCBDFGGGEEHECECEFDFDBBBDCHAFDCBCBCGCFFACAEAEDBFE,False +755,21.0,23.0,12.0,20.0,22.0,23.0,13.0,24.0,FBFBCBFBFECEBHBHDHBBBFBACGBGBDAGFDACHHGCGHFDBHEEEFEAEBEBFGAGAGEDDFDFEFBCAFDFEAEAEDFDBDHECDCFCEAHAFEEHAHGHGHCBDAEGHBDDDBDEHGBAHAFCHGBFHFHEHEADHFHFHFDEBCAAAAHAD,False +756,9.0,16.0,8.0,17.0,8.0,7.0,7.0,4.0,EFEFGFGCCBABHBDDDDGDABBGBFBFEACDBDEDHCGEGBCBCBFDDDEAFABADAHEBADHDCCEDGDBBBAD,False +757,15.0,20.0,18.0,27.0,18.0,16.0,16.0,19.0,GHFBGBCEEAHDBDAHAHEBFFDDDDBFBEEAGBDHDBEGHAHADDEDCFCFBHAHBHDDGDGDECECGHGFGDADEFCFCFDADBGEEBCDEDGABABHBHBHCDCECECEGACCEABFBFBCCHABGHFHFACDDDDDGHECGFGFH,False +758,24.0,10.0,20.0,10.0,13.0,18.0,25.0,18.0,HEHAHAFAHCGCGCHEBGCGHGHGFGCGEABGHGFGHCHEAACABAHACFEAGCECBGGGGGACDFHFAFDFDFDFBEEAEAECFCAADAGFCHHECFHGAGHGEAHFGCCDBDBGACAGADABBDBDCFAFHGEFCF,False +759,5.0,2.0,3.0,3.0,1.0,2.0,7.0,3.0,CFAGGHGHGHBDGDGACEDACAGABF,True +760,23.0,15.0,19.0,10.0,31.0,25.0,21.0,16.0,FGFGHGDGBHACAFAFEFEGEBFGFGFECEDBFEFEHHCFAEACFBBBAFEDCGCEAECFCBBHEGEDEAEFBFGFGADCCCBHAAEEBABAHAHACECFHFEDEABFEDEAEBECACECGFGFEAGAFEFACHGDGAEAEGHHHHGDCBEDEHFHGGCG,False +761,4.0,5.0,6.0,6.0,5.0,5.0,6.0,6.0,EFBFBFGDHCHFEFGGBDAGACHCHDHBAAECCBCDEDEDGHG,False +762,5.0,7.0,14.0,5.0,9.0,9.0,6.0,9.0,EGEFHBHFGFHCEDEBEFACAEAECHCHCHCHBGCFDFCCACBCDHDFGABHBCECDGGEFCFB,False +763,7.0,10.0,9.0,14.0,6.0,13.0,15.0,4.0,FHBHAHAFAEDCDEAEHFDDGFBFBFDGGFGBGBCBFDGDBCGEGECAGAGDGDFDCDCDFGCGEBDGFBACFBFDCG,False +764,18.0,17.0,21.0,10.0,17.0,19.0,30.0,14.0,GFCBGAFBBEFFCGHGEADAHFHEAEAHAHFGGGEGECCFAGAGFFCACBFAFAFGGGAEHGHFHBHCACHFAFDEDHGEGDFBCGCAHGCEBEHCBGBDDCAGBDAGECECACBCBCGGGBBBBBECFCFEFHGDGDGDGEGEGC,False +765,16.0,9.0,24.0,14.0,21.0,12.0,17.0,12.0,FCCCCEGDGDFBEGCBCDDDDCHFGACDHECCCEEAHGHGCCCFEAAADAHGEBEFDDDCDCEAGCGDHEAEAGADAGEFCFCFGFGEAFHEECECEGHGBFCECEBFBCAEBGBGHAHAHAHBE,False +766,2.0,5.0,3.0,5.0,5.0,3.0,5.0,14.0,GCCBCDHEEEFHHEBEHGHBHDHDHAHFGAHDGDGHHHHBFB,True +767,25.0,19.0,25.0,19.0,30.0,21.0,34.0,24.0,AABAGCCCGCDFDAEECGCHBHGHGHDAGCGDFDCEGEBAGFEEEHHAGAGAGFECEHGCECEHFHABEEEBEFEBEFEBCGGGDGABEDEDADGFGFCHHHHDDFBFBAEAEAHGFCFAAAAABAFHECGCDCGFADDBHBGCEHFBBGDHFAFHBHCHFHAGGGGGGAGCGEDEBEDECHFHGBDEDBFGCCCCE,False +768,25.0,18.0,18.0,14.0,17.0,14.0,28.0,21.0,DBBECABABAFFCHGBFEAEHGGEEEHGHGAGADAHGCCFDFDGAFCECECDBBBFBDHHGHEHBHAHGCGFGHHCCFAEAECGAGFHHCEGGGCDCEHEHEDGDHDAGABACCBCBGFFBBHBABADAGGGGHGAGAGAECFBAGAFADAEHDD,False +769,1.0,3.0,1.0,7.0,6.0,6.0,6.0,3.0,EFGFHFCEBGHFBDEDEHEAFDDGDGDGDGBEF,True +770,10.0,20.0,19.0,21.0,15.0,21.0,16.0,16.0,CDHDGGGCGEGECDCDCDABFBDBFBFDFHFHDDBEAEHBGBGCDBGBCHHDGFGCHDHCGCAAHABAFHHBDEFEFCFDFCFCFAHEFBFBGHGDDDCBEGGFEBEAEBDBHCHAEFCDCBFEFEBHCGCBFDFDEA,False +771,4.0,6.0,5.0,4.0,2.0,2.0,2.0,5.0,DBACDGDBBHBHCFDECECACAHAHGBFBH,False +772,20.0,21.0,27.0,26.0,23.0,24.0,13.0,18.0,HHGDAACADHDEDCABDHDFCFDBCFCABDCCCCFFFDFBCBHBGEGHGADACFDGAADDDDDECEHEHDFEBEFCFHFAFCFCFAFCHHHCEBEBEGECECFCHEFDCGBAFADAEAEDEDEFEHEGDAAEBCAEABBFBFBEADGCHDBGBDCDFGGBCBCBEHGHCHBF,False +773,23.0,11.0,12.0,12.0,15.0,10.0,15.0,14.0,HHBEBEDEBGBDFCECGCGEGCHDHGHGBCHAGAGAFAFAHAEEEAEAGBGEGCGAACABBHDABFDFAHADGHFBCDDHAAEAEAEAEACDFDEAAAHFDCCGCHHGDBFF,False +774,17.0,24.0,28.0,15.0,15.0,16.0,18.0,18.0,EFEFEBGCDADCEHBHBHBFBECECBFBFCGCEDEDCCFCGCGFGFACCDFHAHGHBHCHEHECCCGGFCHCADBBBGHHEGCCCGCBHGEGBBBAADCDCDCDADADABFHFAGBDBAHGBBABFEFGBEAHBGCCHFHGDABACAFDEA,False +775,3.0,0.0,2.0,1.0,0.0,2.0,2.0,3.0,AGHGHFDFCHCAA,True +776,17.0,9.0,11.0,6.0,12.0,12.0,17.0,14.0,GCGDABAFGFGCCECFABAEAEBGADHHEHAAAEDEAEABDFCGBADAEHGHFFFGAGFCFDBHBFGHHCGAGHGEGHBHCECEAEAGFCFCBHGHGH,False +777,4.0,6.0,1.0,5.0,7.0,2.0,6.0,4.0,HEFEAEAEDBBGDCDHDFEBAAHEHEDGBBBGGGG,True +778,6.0,7.0,4.0,4.0,5.0,13.0,4.0,5.0,HEHEAFGFAFAFBGBAFFFDEDECBCFGDBEHFAFBFDFHFHGBACCB,False +779,9.0,7.0,5.0,6.0,9.0,8.0,7.0,9.0,DGBEBEDHAFAFHFHFCFCEDEGEDEDGHAFBHBAGAFBCBHFAGADAECCBGEGHHEHA,False +780,19.0,21.0,16.0,16.0,23.0,19.0,26.0,22.0,FFCAGEGEGAHBBEBEGCDFEFCFGHHDHDHDBEFFAGEGAGAGAHEHFAEDBACCCEDGBEACFCFEDEABABABFHFBGBGAGEHHACBCGCHCHGHEABACDBDHEGFGEADHFBDCDCEBBAGHGHEHEHGHDHDGDGFHABECEBDGGFGBGBEFFF,False +781,15.0,24.0,23.0,18.0,23.0,14.0,17.0,21.0,FEAGCCBABABAFAHCDGHFCAEGBGBGHHBBCBFBABAEDEDADHFECGDGAHEBEBECCGCHCHEBCFEDDDCGCGDGDHEFGGCHCBEFECAHDEDFDEHEGEFBBHGGCECECFBDBDBAHAHEHDHECFBFDCECABABHBGBCHFHDHE,False +782,14.0,24.0,23.0,18.0,18.0,17.0,19.0,17.0,GAECGCBBAGAGAGFEEDDFBEEEBBGGEECCCCBEGEGFGDGCHCHCHEADBDBHBHFGADBFGDHHGAGADDDDDCBCDHFBFHDAGFHFHFHCBCFEHHHBFCFHFCGCBCAGFEBDFCECHCACBDBCEAGDBDBEBEBEBABAFC,False +783,17.0,21.0,14.0,26.0,20.0,11.0,14.0,15.0,CHAHEHDHGCCADABAEDBDBFAEABGDDCGADADBBAFCEGDBEBDHGEGFHEHEHEFCFDGHADADBDBDCDCGBABDECEDEDFDCDCDADEDBDHGBGBECDHEHFFBAEAEBEBGHGEBCGGBEFHBHCFAFA,False +784,9.0,13.0,21.0,19.0,11.0,19.0,13.0,15.0,ADHDFGEBBCCDCDCFHAGDBCBCECEAGAHCDEAHBHEFEAHHGDCHCHDHDHFBEADFCGCHDHAFBGBGBEFDFGFECACFEFGFDCDEBGBGCFBFCDGDGCFDFHFHFCFCDCDB,False +785,3.0,4.0,10.0,4.0,5.0,8.0,5.0,7.0,FCFCGCGEAAGFCECECHFFDHCACGCGEBHFEFHBHDFDBDBHHC,False +786,13.0,15.0,20.0,21.0,12.0,14.0,14.0,18.0,BFDGDGDADECHCHCEDGDBDGHCHDGCABEEFEFGGDDBDHDHDGCCEBDFDFBHBHBHFHFAECEBAAAFAEAHBHGHDFEFBHBABECCCCCDEGHGBFFGHCDCBGDCCCFHDCACAFGHADA,False +787,12.0,21.0,22.0,19.0,22.0,24.0,29.0,14.0,CGCGEECEGGBEAGCFFFCDCEEACFBFBGBGDGDHDHCBCGADEHGHBFGFGFDFDBGEGEBFCFCFCFABDBCAFFGDGBFHCHEECDFDFCBEBFHGCGEGAGAFDFCEGEGEAAHHHBGCGCGAGDGDBDFGEDBDFDBCHADEEGEHEHABBFEHBCB,False +788,17.0,13.0,19.0,20.0,16.0,16.0,19.0,15.0,BDCEGHGDAFFHFHDADAHEEEECFCGDHBHGGGAGAEFGBCADGCCCCCCGCDCBEFEFDFECADABAFEBGBGAADGEGHADABHFHFCEDHDGGCDCDFDADGHCFBBCBCEHBHFHDEDEDEGHGAAAFBF,False +789,28.0,17.0,13.0,32.0,28.0,13.0,27.0,17.0,AEADADBGBAFAEADGBAAGDDEGEBEFCFCFHFHAEGEHDHAADEDHDCFCBAEGEGDGCGAGBGBGBFDDDEDGBGBGBDDGGADCDBGAEAGDBCADEDHBABAECHCECAFEHAFACDCDGEHEHFBEHDDDDFEAABDHGHGHDAGECEGEGDHEAEGEGEAFHDHDFAE,False +790,20.0,14.0,14.0,14.0,17.0,15.0,16.0,18.0,FCFDDDHCHCEGHADCBGFEFCFEEEEBEADABHBDEFCABABAGAGEHHBHBDAECGDEAAAFAEADBHCGGBGBGBEFEFEFABAGFHHGACDBDHHGFDACEHDHGHFCFDHCHCHCEFAGAGAG,False +791,18.0,17.0,18.0,19.0,20.0,20.0,6.0,18.0,FHFHFDEAADAFBBACGHDCDFAGGFEFADEDBFBFECEAFAFACCCEFHBHFHBBACHFDGDCDHDHGBAHCDCBHBEEEEAECBABCBCEDHDFDEDEDEAEADACAHFHFHEDCCABEHEBEHCFBFGFBDHC,False +792,14.0,17.0,13.0,12.0,11.0,16.0,16.0,11.0,DDBDBDAFBDBFAFAGBDEGCCECHCHCGFABGBCFEFECHFBABAEECBDHDGDGHGHGFCFHEAEGDHBCBEFHBGAGACAHAFGFGFDEABFBABGFGFGBHCAEDC,False +793,9.0,19.0,17.0,11.0,13.0,16.0,16.0,13.0,DCGHBFFCGEEBEGGAGFDEEBFGHCHCDFDBCBCFCFCGCGBBBCBCBFHFGCAEABHBABGBDBDFDHAHFGFHBBBGHGHECFDECEGHGHDAAGDBCECDAEAEFEFCFH,False +794,18.0,14.0,23.0,18.0,18.0,15.0,28.0,20.0,GBGBGFGAEFECEBGBECECFGDEDGFCFGGHCHCFGDAHHCHCFCFCGCGCEAHAEABACDBDBAGGCGHAHBDFDHEHEGAGEGEHHDCDGFHBHGHFADECACAEABFCAHGHGBDCDFDFBAGACDGGCDBGGADHDBFHEHEAEGDCEC,False +795,2.0,6.0,5.0,6.0,3.0,1.0,4.0,1.0,GDGECBCHDEDECBBFBCBABDGDGACD,True +796,20.0,15.0,22.0,19.0,22.0,17.0,35.0,28.0,EHGHCDCDAEBCBFBACHCGEFEFEFDFHGHDCGAHDCGCDCACBGEEHEHGGGEHEFEGGAAAAHAFFECCAGHGHGHBACACDCFEAGGGGGGGCGAFCBEHHGDGHGADAHGHBDGAGBCDCABAHDDEEFGGEHHHBBBDBDHDHDHFHEHBCDCGFGECEFFGFGEGHFBEDA,False +797,22.0,14.0,14.0,13.0,13.0,14.0,15.0,9.0,HCHGGBDEFAFAGAHDCGCGCHCGFAADEDEABAGABFEFEFEBDFGABHFDAABCHCFCADBBAGDGDGDCDFEFGBDBDFFGCBCBEBGAAAAAAHEHEBEGCAAAFHECEC,False +798,15.0,14.0,14.0,26.0,14.0,22.0,16.0,23.0,DCGAADDDHDHFFDBGGFGEGBBDHAHFFFFAFCFBDDFEAEDHDHGHGDCHCFAGBDFCFEFGAGHECFCEDAHAGEBFBABDEDADCDHAFCFAFHBDFAFADEGEHEHBHGFGCGHGCDCDBBHHHHBCBCHDEDEDEDHH,False +799,27.0,20.0,19.0,24.0,17.0,17.0,26.0,21.0,GFGDGDCDFGBGBEBGBHHFDADAHEHEBBBHFFGGCADACAGHBHAAFACACHBECEFAHADGDAEHECFABCGCAHBHAHDGEEHFDFHFDFCAHDBDBFEGDGDGHBDBGAGEGBGCCECEBEHAGABADADADECGCGCAFHGHBFACACFDEDEBGACAGHGFDDD,False +800,14.0,22.0,27.0,22.0,29.0,27.0,20.0,20.0,BCBCBCACACAHDBFCHEHEFBGGCGCABBHBEEEBECECBDHDEBAACGCGFGFDFGBCDAHHHHFFEDDDDEFFHFDEGGGHEAEDEGBBDFEADFCGCGCHFHGHGEDCHFFFDFDCHFBCBCBCEEEGACAEHEFGFDFCFBAEHECGDEFGHGAFAEBBBBDCEHFCFEFDCDEDE,False +801,5.0,1.0,4.0,0.0,2.0,1.0,0.0,1.0,HCAEACAFBEACAC,True +802,15.0,14.0,17.0,11.0,11.0,11.0,14.0,5.0,DGAEAFAFCFDADEFEFCACGEHEFGCHABACABHBADDFDFCGEGEAAACHCGDGCGBEBFDCABBBBDBABFGGCCCEGFBBBEDAHCGCGCGCED,False +803,19.0,24.0,22.0,27.0,21.0,24.0,25.0,26.0,HFAFEFEFCCCHCHGDDHEHEDEACCFAFBHDEDEBGCGBFAHAHAHFGDBAGAHBHFEFBFEFABCDHDGACACBGDGHAFBDBCFHFHDHDGDADBCFGGBDACGHGCECEGGAGDGDGEGECADHDABGBDDCECEHFHBGGEGEHBFBDHFACAFBBBBHEEEGCDHGFDFDFEFHDHDCBBBC,False +804,14.0,12.0,12.0,16.0,9.0,14.0,9.0,8.0,ABCBAFDEDFDHDCDBAFCBGBDBEAEGEBCDGAACABDECECEHEAGHGDBHFFFCGDADFFFGFDBDFAHCHCHCHCBADADADABFFGGEF,False +805,10.0,5.0,7.0,4.0,17.0,8.0,9.0,3.0,AAGAGAGAGAHECEFEGEHEBEAEFDADFEEEECEDECHGFEFAFBEDFGBEACBCEFBCCGG,True +806,16.0,25.0,13.0,17.0,23.0,16.0,21.0,18.0,CBGEEFEGBBBCHGHBAAAAGAGEGCHCEDBBBBBHHHHDAFFEEDEDAAADFEBHGHDHEGEGHCECEBBDADGGGGGDGHEHEHEBBBFGFAFDFEFEBEBCFFEBHBECDBDFAFAGHDFDGBHDCFCAABCBHEGDGDEBGCCAF,False +807,3.0,8.0,5.0,8.0,9.0,8.0,9.0,9.0,HFFFBHCHEBEBEBGBDCGCECEFDFBFGAGHHDHFACHDHDEFBGDGEHEADGDBEGG,False +808,18.0,19.0,24.0,19.0,15.0,25.0,23.0,17.0,CDGFCFCAGHEAEADCGEGACBGFGDHEEECACECECFAHAFDCDHDFEBEHDFDFHFGBEBGGGBBBHBHFAEAFGFAHAGAFCGCHCHGHBCDDFDFDGDFBEBEBFAFCFGDCCHGHADCBFBGBGHFCGDGBCAHFDFCFCBCBDAEABADGFGHC,False +809,24.0,16.0,20.0,18.0,20.0,16.0,26.0,18.0,HBEFGCGHAHADGCACAFBFAFCEBGBFDGAGAEHHCDDHDFDHDHDEECGABCBFEAEHDGGGGBABGFEBCAEGBCFCHGHBHBABGBHFEFCCCCAHGEGEFHFDGAEBHDADCGHEAEAEAEAEGEDCDADGDGAGAGAEHDGCCFCFCADBGF,False +810,7.0,10.0,7.0,14.0,17.0,13.0,14.0,8.0,DEAEGEFECACABGEGEAHGHGHAEFEFECHDDFDBDBCBDBDFGCGEBECEDDDADBEFEBDFGBDFHGCFFDGGFEHEHFHBGAGEGF,False +811,11.0,12.0,11.0,18.0,16.0,11.0,15.0,16.0,EBEBABDHDHDHEHGHFAAGGCAFEDDGEFAFHDBDBDHEGGGGBCBCFDDDDDEDBHFEBHCHABEFEFGHECECBFGGGEDHCHCGEGACAEAECHABCHDADFDFHG,False +812,7.0,8.0,5.0,1.0,6.0,6.0,5.0,5.0,HHHHAEACACBEBCCAFAGEFCFDBHBFBFEGAGEGBGFABBE,False +813,7.0,6.0,14.0,17.0,20.0,8.0,11.0,16.0,BCHCAFAGAHCEFEDEHEDCHGHAEDGDFCFHGHGHAEGEGFHBBDFEHEDEDHDEDEBGDDFBEHGABCEDECCCADGHEHEHCHCDCDCDCEEGEFD,True +814,27.0,14.0,15.0,25.0,17.0,16.0,12.0,25.0,HFFCACAHFFCBCFFGDDECEFEHCBCBCDAAAGAHAHDECEFHAHAHDEABBEBCFGBGDEAEAEADGHAHACDHHHBCBEDFFAFHFEEGAAAAAHAHEHEDDDDGAGDHDBDFFAHDBACACAGHHDGBGBEDDBDHFHECGDDDHDH,False +815,9.0,8.0,11.0,6.0,5.0,16.0,9.0,7.0,DDGCCHAAADDFEFBHDFFFDFCFCFCFEBEGGGCFCGHGHEAAAFFHBCBGBEBCBFFFCFCAAGAHHGB,False +816,27.0,23.0,14.0,24.0,26.0,27.0,25.0,22.0,DABHHHEHAHAEFDBAGABDBGHDAAGAGFBAHAHEEDABFGGEEADAFBCACGCGCEFEBEBDFDCDGDEFEHEHFAGAGCBCGCBCBEDAGGBABHDFBFBDEHEHGBFEFEBDFHFHFDEECAFGFGFEADHDAGAGADCDCHFHCEADFDGEAFBFCFDBEEDGAGBEFEHDHGAGHGHFBFBF,False +817,1.0,1.0,2.0,2.0,3.0,7.0,3.0,4.0,FFFFADHDHEHEGCFBGECFHFG,True +818,10.0,14.0,17.0,5.0,12.0,5.0,16.0,9.0,CACBHAACABGDCAEAFGBEHEGCGCGEGEDBGAGFHBGCECEFEGEGBHBFGAGHEABDFDBCBCBHEHGHGBDCACBGBECCCCCH,True +819,20.0,12.0,13.0,11.0,16.0,13.0,21.0,6.0,ADCECACDCEGDFFAFBGBGBGBAAAEBEBGFDADEDAACACDCHHBGGGGGGGEGAAHFEFCGDGBCFABAFEGCDHFECEDEHABCDAHFGAGEGAGAEAGBFBCEFEFE,False +820,24.0,22.0,18.0,21.0,20.0,19.0,14.0,22.0,ECFBHAHAHAEAFBFGDGDCBCGAEAHABCBHFEDEDGBCDCDADABAEAEBHDGDHCBAHFDCDHHBHEGAAFAFCHCDDEHBFBFDGDGHBAFCEDEHFCEHEHEHGCGAHABCBEFHFGCDCDFBFBFAFGBDEDAGCHBEBCBADAGEBEAEAFFH,False +821,24.0,21.0,19.0,22.0,19.0,13.0,20.0,29.0,DAHAHAFEGCDEECECAAEHEFDDDGAGAGAGABHBGEHDHFHEHAHAHAFBHBHCAADCEBBGDECHGFGHGAGEDFDFDHHHCGAEABFDGBECECAHACFCHGFBDHGFDHBHDDDDGGHEHAHBGBGBHEABBFBDBFBDAEEBECCCCCACHCBCHAHDGDB,False +822,16.0,25.0,27.0,23.0,14.0,15.0,16.0,28.0,BHCHCDCAGFGAGBFHEHBABGDHBABFBGBDCHCHCHEHAHEHCHDBGBHACADADAFFHAADACBCBEGEFDFDFDFCHEHDDBDEGEDHHHCDEGHCFGFDEDBBGFGCGHAHBDCECHCABHFCCHCDEDCDCGBBEHDHBGBFEFCACHCBBABCBDGC,False +823,19.0,16.0,17.0,19.0,13.0,21.0,12.0,12.0,AAFGBDHDCDFDEHBBFHFCDCABBFDFGEGEBCHDDDBDGDACAGABEGECECECEFEHCHAGDDHCCDAEFFAFBFBGDAEHHBABAHADABGBFCFGDCDFHFHAGAFAFDFBACACFGFEFECBC,False +824,23.0,14.0,24.0,16.0,17.0,21.0,26.0,11.0,EEEECEBHDFDBDCFAABFDEEGGCGEGFHDGAGBCFCHCFAFAGAGFFBGAFAEABCGAEADADAHBBEHCHCBCBCDCECGHBHAFDEDEAAACACFFECEFFGACCDCFGGCGCGFDFHFGCGCGAEAGGHHFBFDADABBCGGGDGDG,False +825,16.0,23.0,19.0,19.0,25.0,21.0,19.0,16.0,BCECEGEHBGBGDACADFFBABGGEBEGCGAGDBCFCEADAEFEDDCHCDEDGBGCFHFGBEBEBEHCHCEBEDEBFBFEFHFHFGDEAEBGBEDDCBHDFGFCACAGAHBDBDBCCFCFAFDDDADHEEEFHAEAGBGCAHHHEHFGFBFGECHABF,False +826,8.0,5.0,4.0,4.0,6.0,3.0,1.0,4.0,CDGDCFEEEEABABADAHBFBHACAFHEAEAHCBD,False +827,24.0,26.0,18.0,19.0,16.0,34.0,27.0,29.0,CFAFCHHGFDHDBDBDCDCHEFBGBGBHBDADCGCGHGFDFBAHDDAFECBFFFHFAGECAHAEBEAAACGEGHGEABAFGCEAGFFHFGACBGHGAFHCHGHGBFAHGHBHBGBGAGCFBEDHBFBHEHEBFGECEADHFHFHFDABFEFHFEFBFBABDBDFDADGDGCAEAFCFCFCDAGGFGFBHHHHB,False +828,2.0,3.0,1.0,7.0,4.0,6.0,1.0,1.0,ADDDFDFEFEDEBFBEGFDADFHCB,True +829,18.0,8.0,19.0,22.0,14.0,21.0,12.0,12.0,EGEGCHAFEECHDBDBDCFAFEFDFEGEAFCFDADADCHFHEADAEHDHCCFCFDFHFDFDACACACEFDFDGBFBCGEGFGCGCAHADACEDDGCCACHBABDBHAHFFFDDHACBDEAEGGGFD,False +830,14.0,17.0,12.0,13.0,7.0,7.0,14.0,9.0,EGEBHBDCDGECBABADDGCABACFCEBDCCADADFGHGHGFGBGBGHGFDDCDAGABACHHDHDFDCBBGBAAFACEHAGAGBEBHBCBEBF,False +831,13.0,21.0,11.0,11.0,12.0,12.0,12.0,8.0,EAEDGBFBDBCHEBEBEBCHCHAFGGBCDDDCDCBADAFAFABADFCBCGEAEDBAFAEHEHADFHBBEHEFBFGEBHFGBCBCBFGGAGAGBGCGFBDB,False +832,14.0,20.0,21.0,16.0,26.0,24.0,30.0,17.0,BGGGEEEBFFFEFCDGGGGGCGABDFGHCAFFFDFEHDHAGAGAEBEBCBCAGBBDBFBFEEEDDFCCGCGEGBBDBHEDCFCHGFEEBGCFAEGEGECFCGCHEDDCBEDDDHHHCGBGEHEHGDDCGCGBGEGEBEHECGGAEABAFAHAFAFHFHCHCFFFHFBA,False +833,0.0,0.0,2.0,1.0,0.0,7.0,1.0,2.0,GFFCFHDHCFFFF,True +834,15.0,17.0,13.0,12.0,21.0,19.0,18.0,23.0,DEFBAGHEHEABHDFGFHFHCHDHECEHBHDGDGFFCGBFBEEHHCDEFECEDEBCBGEGEGACAGHGHAHDFCBHGFFFFDACEHEBFBHBHGAAEADGGADHHHHGHGFAFCFCGEDFFABABGECACABEBEBEB,False +835,9.0,17.0,15.0,12.0,13.0,15.0,12.0,18.0,AEAFDHGHGFDEDBFBABACCCFCHEHCFEDHFGFDHBHBHEFAACHEDECFCGCBCECEGHBHCABDBEGFDFDBDBEGEFFCCGHAHAHGHDFBBGBGDGHBHBCBFHE,False +836,24.0,27.0,17.0,31.0,24.0,22.0,21.0,23.0,DCGBEBCDEDADFBFEDADADBDCDCDEDFDGBGCGBHBHBHEHEDEDAGBGFDAHGHBCECADBDEDBFFAFAFAFEHHGCGFEFDDGDGFBFGEGEBAHAFDDHFABBBDADAHAGAFFFCGGEECHGAGAEECEBFBCBHHGEFDAAECFADHGHCHBBBBDEDHBBBEHHAHCHCAEFEHADGDC,False +837,8.0,2.0,11.0,12.0,11.0,8.0,3.0,11.0,BHCHEDEHFAFHDHCHFDCDFDFDAAHCFDDADHDECECACECAFEHEGDGEHEDEHFCBCGCAEA,True +838,12.0,19.0,12.0,11.0,20.0,17.0,13.0,16.0,DEFEFEHEFBFECEAEAGBGAFEBEDFGFGAHFHFCGBBBBBBHEFEBHBGBGHCHFBCDFHAACCHEHACDBFEGEDFBCBABHHCHEHACACEDDDDFDGHGHCAGFDFBEEEGEGBA,False +839,1.0,4.0,3.0,4.0,6.0,6.0,4.0,1.0,GBEECAGBFBFBEDCDFDFEEHEDGFGFC,True +840,5.0,4.0,4.0,1.0,6.0,4.0,2.0,2.0,GEBEFEHEAADACACFCFBBHCAGEBEF,True +841,15.0,12.0,13.0,8.0,18.0,15.0,11.0,15.0,FHFHFEAAHFEFCGEHEHCHCBCAEBBBCHAHAEGFGABHBEBEFCBCAHDHBEAFGBHAFEFBGCFEFCDADBDEDEDEGEFEFAACHDHAEACGEGHGCGAGFDC,False +842,17.0,27.0,15.0,15.0,25.0,21.0,18.0,18.0,DBEBDBEEGGGBGEHCACBCBABGEDEDGFAFCCBEDCGGFGBHAHDBBHBHECACEDBDHAAFAEBEDCDCHGBEDECHAFAFECECEFHGHGHBEBGBGBFFFFHFEFHFHEBEGEAEFFAFGBBBFHCHADFDFBABCGAEAGFHDADEBHBE,False +843,20.0,14.0,16.0,25.0,17.0,16.0,12.0,24.0,HBHEDGBFBCADADACHHDHDAEAHDDDDDHFFDHDGCGCBHEGABAHEDEABACDCEFGFHAGGBACGHAFFGDCAAGHDEGEGEDABACABHFDEEBEBDBDBDHDADAHCHBEFEDEDCFCFCHCHFHFHFHFCAEHHFCE,False +844,6.0,6.0,6.0,6.0,7.0,4.0,7.0,2.0,GCECFBDBDBEGHDEAEAFFECECACBGBDADGDGHFABGEGCA,False +845,14.0,10.0,13.0,17.0,13.0,16.0,16.0,22.0,DADFGHGHFHCBGAFEFCFCGDGDEDBABABECDCDBBGAFAGAHDDDDFDGDGDCEGGFHFHCHGAGDHHHFFCGCHHEFEAHHHFHGEGDAHECDCHHAHAEAEBCFHFBFCEHBBEEA,False +846,13.0,21.0,15.0,9.0,8.0,13.0,6.0,10.0,AGBCBCBDGCBFGHABCBCBEBABCGHEHBAFAFDFECDBBAAHBHBHCFCFDBABDCDFFCGHAHBHBEBEBCFCACDEHACEBFDFGFAFAED,False +847,8.0,14.0,10.0,15.0,9.0,10.0,9.0,7.0,DECFAHHBGBCEAACBCBADDEBHDHDEDFFFGEAEBGCGBGDGDFDADBDBDCFCGCBCHABFBDEDGDGBHBFFCFEAEH,False +848,10.0,5.0,6.0,10.0,12.0,17.0,10.0,11.0,DHDEDCDFDFAFAHCFGABAGFCFBGGGGAHCFDFAFEEEEBBABHFAFGFEEHDHECEHFHFEAHAHEDFDFHFDGGGEC,False +849,22.0,14.0,13.0,19.0,14.0,18.0,13.0,19.0,AACFCFBBHBGFDADADAHHCGFBCHHFHBHDGDCAHAHABDEDBDAHAGFGEBEBACHCDEGAFFDGBHFCFDDBABAEEDEGEFEAAGAGABADAHFGFCFAAGCFHEHFGFBFEEDEHEDCDCDCDHHH,False +850,12.0,11.0,24.0,25.0,18.0,37.0,27.0,36.0,GEGEAEAEDHDEDECECGGGEFEFEGCBFBFCFCDCHEHDDGEGFGDHFGEGAGCGFDHCHFHDGCCHEBBDACHCFCHGHCHCHGDFFFFDFHGHDFFFGFGHHHGCDFBFCHHFHDDBACHEEFDCAHDHBHFFFHHCHBHFHDGFGFGBEAHFHFHFCAGGDCBGDGDFFAACDCAFDFDFBHHAHE,False +851,8.0,20.0,9.0,10.0,16.0,10.0,11.0,18.0,GAGAGFFHFHCHGHEFEGADABHBHBFEEEBAHCHCEEHEDCAGGBBDBFGFHFHAHFHBABEHEBFBCHEBBBDDDCDBECEGDBCBEBEBHBGCHEDDHG,False +852,8.0,4.0,3.0,3.0,5.0,4.0,5.0,3.0,CEHEHBGFGBABDCGAGHFDCGAAAAEADAFEFEB,False +853,2.0,2.0,4.0,5.0,2.0,8.0,1.0,9.0,BHFHFHFADCCGFDFDBDEFAHHHHHFHECCFD,True +854,0.0,3.0,1.0,7.0,1.0,4.0,3.0,3.0,BGEDFDHDHGFBDBCGHDFDFD,True +855,13.0,9.0,23.0,8.0,13.0,14.0,12.0,14.0,CFCFCGHEACCCEEEGDHHAHBGBCFCDCDCFFGCAFDCABHCHCDFFCECGCGCAABFDEDACCHHAFAEBEBHGHBHFGEGCGCGAEBCBAGEFEFEFDHAHAH,False +856,10.0,14.0,21.0,25.0,13.0,22.0,18.0,15.0,HDAFAFDFBGDDCEEGEDFGBDBGCCCCDDDGDGHFDGHEFECHCHCFEDBDBACGFBFBFDCGEGCABABDEGCGCECEBAFGHHBDDDHHHGGDCDCACAFBEBECFCFAEHHFFFDGDGHGHDDFDFHFCFCBAF,False +857,5.0,7.0,6.0,6.0,3.0,6.0,3.0,6.0,HBHCDAHAFGBACABHBDBDEFGCHCHCBEFEFGFCFDDBDA,False +858,5.0,6.0,10.0,9.0,8.0,7.0,3.0,10.0,BGCHCHCBDDHDGDGABCBABFECECECDCDFHHCEDDFFFHHEHEAEAFHBEDHCAF,False +859,5.0,3.0,3.0,10.0,1.0,2.0,6.0,6.0,DADADBGHEADDDCDGHGHGCDCDBFAHHFHAGDGB,True +860,23.0,20.0,27.0,31.0,27.0,21.0,22.0,20.0,GBHCDCFCFDEDHCHGEFEFECCCCCADABAHFHFHFDGDAEEHACDDGBADFDEECFAFCFEGCGEEHFAFEFBABCDADEDEHBHGHBBAECECGBHAGFHHBGECCDEDBFHCACGCDAGAGADDDDDCDGFCFCEEEDEBHGHGHGCGCBDADHBGDDEDABABAEDEBFCDEBABGBDAFAFGEGH,False +861,7.0,7.0,14.0,4.0,11.0,5.0,11.0,5.0,GCGFGBGCCCGFAAEAECECECGBABHHCAEAHAEFEBEHDCDCGFGFBCGCGCDBEEHDGECB,True +862,12.0,3.0,10.0,5.0,8.0,8.0,5.0,6.0,GFCAHAHAGACCEHDBBAAAHADECEDECGCBCECFCFHFHAGGEDEFFCFAEAFAD,False +863,24.0,14.0,29.0,24.0,18.0,18.0,12.0,25.0,ACACHBEBEDABHBGCDCFCEDFCGCACGFADCCCCBCDEAEBDHEEGAGCDFDFDFGEHAHFEEAEHCCFHFEFCHCHDAAHGDCDAHFHEHDHDHAHADEBEBEGADAHEBFHFHACGFGCGCBCDCDCACFCFABCBADDBCBHHDHGAAHAHFFDHDEDA,False +864,12.0,14.0,8.0,8.0,15.0,8.0,10.0,15.0,EBEBGHCABAFAFDFDADGBHCEBGBGBCFCAEEDHCHGHBHDGDHEHEHEHCFGFBEEHAAAHGHGEGBFCABHFHEEBADCDABEBEA,False +865,3.0,2.0,2.0,3.0,0.0,3.0,0.0,4.0,BHDHBCFDFCAHAHAFD,True +866,5.0,8.0,8.0,6.0,13.0,7.0,15.0,8.0,FHCDEDADBEBGAGCCCEBGGFGEGEGAGAGHDHGBEHEDGAGEBECHCGFEEHEHGGFBFBFCFHEBCD,False +867,15.0,8.0,10.0,4.0,10.0,7.0,12.0,11.0,GCHHEHGBDBCGCBCFEAAHAHADFCFCFGAGAFBGAHAEGFBECEABHCHAEAEHGHGFBDCHGEGEGDACABAEA,False +868,13.0,19.0,24.0,20.0,14.0,16.0,12.0,20.0,HCHAHAGDDCDBGGHGHGCEEAEGFBFDEAEFCFHDHGFAFGEHDBDBDCECDFECHCDCFCHCHBBBBGAFDCACEDBFFAFAFBEHCACDHBCBCBHBCADDDBDHDHCHCBABHHEFGAECGCGCBDBDCFHFEE,False +869,11.0,10.0,12.0,15.0,14.0,12.0,10.0,5.0,CBGECDGDGDADCGAHDBDFFFFEAHFEFDBDGDGECECDDFDADBEACGFEBEBECCCGCBCBEAEAFGBAAAEDEGHHDHCFAFEFB,False +870,8.0,16.0,15.0,5.0,12.0,6.0,10.0,5.0,GEGAAFBCBCEGAAEBEBEFHHCBAAGACBBBBEBCGCGCECECBABCFCGCFEDEHCCDGBGFDFDEHCHBBGBDE,True +871,7.0,10.0,13.0,4.0,10.0,7.0,7.0,8.0,GAAHGCBADEDHDCCCACAFHEBBBBBCBEGEGFCHCBEGEGEHDHCFFABCFCFHGHABFECECE,False +872,5.0,6.0,11.0,4.0,5.0,6.0,7.0,6.0,FCCCACBDAFCCCFGBBHBGAGEGDGCGHGHDHDEBHCCFCBAEFEFEHA,False +873,6.0,3.0,2.0,8.0,3.0,5.0,4.0,1.0,AADDDCDCGGFFEBADADADEDGBGFFEFAHB,True +874,16.0,16.0,9.0,13.0,16.0,16.0,11.0,18.0,DGAGHBHCEFGDAAEAFAFBBDFHEDEDHBHGHGHDDEDFCFCAAADAHFBCBCGEHEBFDFAFCFAFAFBECCBEDHHEHEGBGCDFGFHHHBHBEBEBHAEADBEBAAGEGHF,False +875,10.0,10.0,11.0,9.0,10.0,8.0,13.0,16.0,AFADADEDEFHCHCFGBGEHDFGHCHEGBGHFABHEACHBHBHBHGDGBAAAHAHCHCGGGCGEDEBCDDGBGAECEFFFBCHCHDE,False +876,10.0,18.0,8.0,11.0,7.0,15.0,11.0,9.0,FCHDHBFBGCDHAGCCHDHAGFFHBHEFAFAFDBBBDBDEACGGGBGFECECACHDBABFBDBDGEADADFFFGEGEBBBFBFBGBFAH,False +877,4.0,5.0,14.0,13.0,6.0,8.0,11.0,11.0,ACACGHADGCECGGGDCCCFCFBFDFDHDHDADHDHFFBHGHCHCGCDCDHDEEBGFDEHBHGEEBDFCCGG,True +878,22.0,17.0,15.0,16.0,16.0,19.0,13.0,15.0,CCFCHHDBEGEGDCFHFBAGFEDDFDCECEGBCBABADADBGGDBACAFAEABHHHFHCHDBFBDBDBEHHCHCHEEGFGFHAEAEAEADFEAABCFCEAHFGAAADFDFBFBEGCGCDAFAFAEDGBHBGFA,False +879,11.0,12.0,5.0,10.0,10.0,9.0,11.0,9.0,BCBCEAFGFGHBHBHDDFEFGBGHGFBDCAAGEHDBDGHGHFADAEEFEDEDEAHABABACAGHEDFAGEDBGBCBF,False +880,22.0,23.0,20.0,22.0,17.0,22.0,27.0,22.0,AFEFEHDHDHDBFBGBGEGBGFGFGEHEABABGGGABAHDHEBCGCGCFCDBDFEEAAAFDCBFHGHBCGAEDFDFDBCECFBAGAGAFEHGGCGDBBCCGBDDCDBDCFCAHDBAFFHCHDHFHCEEDHDHBHCCBFBAEAEAFGDCDHAHFHEHADAGAGAFBGCGHGFBEGG,False +881,26.0,17.0,21.0,13.0,20.0,12.0,23.0,19.0,BAEAGCGHGAEADABEEEGAAHHDDBDFGAGACCHHEHEBFBHEEEDFGFEAGHCCACGEFEDCGCHCGFHHBHBGBCCCDCGBGBABABFDDHEAEFEGGGGEHAHACACDGBGBGBEAFACEHFAAAHGHGDCCECFCBCBHDAAAFAD,False +882,1.0,1.0,3.0,2.0,1.0,1.0,0.0,5.0,DHHFADEBCHCHCH,True +883,7.0,3.0,8.0,7.0,4.0,4.0,4.0,4.0,GDEDCFHFHDHDEGEACDCABBGFACACGCFCDADBCAEAH,False +884,21.0,12.0,14.0,11.0,9.0,9.0,15.0,13.0,EHEAEGDDAGGBGFFAGHDHDCDCDCFCGGGGGAAEGCHEDEAEFHFAFGCBHBCCCCADBBAGAGHBCACAHAHBFEDBGBCBEDDHHABAFAHAHFBCAAAA,False +885,16.0,26.0,24.0,20.0,25.0,24.0,19.0,20.0,DFDGGAEAEAEDHGHGCCABBEECFCFGBGBDCGFFDBDECEADADHGHFDBDCEEBCGCGAFBFBCHDFDFEFEFHFHFHBHFEFHCHCBAFDFBFCAGAECBBBBEAEBGCECFHEHDCCEGBGBGFGFHHEHCHBDACECABABDBHAEDDCGGBBEFDFDCBAEHEHECG,False +886,13.0,28.0,17.0,8.0,23.0,25.0,17.0,16.0,GFFBFBHCFBBBCGCGEEBCBABFDEBGBGCACEHFHFHBADDCGEGEBHAAACFCEHBHBDAEFFFFDFDFEFEFECEBBBHFGBBHBEGCBEAEDCHEEEFBGHGECEHFHBABFCFCFCGCEAGDGAGAFBGGAFHHHBEBEBF,False +887,12.0,16.0,10.0,18.0,15.0,11.0,14.0,8.0,EEHEFGDCAFDGDCBFBFGFBEAFBBBAGFGBGCHCHCAGADCFCDBDEHEAEDGDBHBFGEBEBDBDADCDHDEABDDEDFCAGDGAGAFDEAGCGBEBEHEH,False +888,18.0,13.0,17.0,15.0,11.0,10.0,18.0,15.0,DEGEDEFAHAHAHGHGHGCGCFDDDADFCBGDGDCBABCBEACAGAGCEDBABDHFGAGAGDEEHAFCDCBCACBEBHCGBFAHAHCDFHBGBGHFHGHFBACEGEGCHAECFCDAD,False +889,22.0,5.0,11.0,9.0,14.0,19.0,10.0,13.0,HEHFADEFGFCEHEFDFHFAFGGGGAGAFADGDFAEAHBCECEDFCFHFCFDFDAACACABBFGCHEAAABCDHEAEABFHFHEGEFHAAAAACAGDHCHEFE,False +890,27.0,36.0,17.0,27.0,26.0,14.0,25.0,25.0,FHDGFABEECADAEBECEABAGHECDCDADGDADADEHEHGHBFBCBGDEEEEEBABABHBHAGCEDEDEHAHAGGCDCDHBABHBCACAGFCFGHHFDFDGBGHGAGCGFFBHADFCECEHBDBGBABACAHEBBHGHEHBBEDEFEBGBDBCGEDBBBBBEBDHDBAHGFGAEBHAADGHGDABFCFDAGBGDHD,False +891,18.0,15.0,22.0,14.0,25.0,27.0,18.0,19.0,FHFHEHAHCFEDCDHFFFHCCCCCCFAFGEAHAFGGEGEGEGFGFAEHDCDFHGAGEBHFHCHBHBEDHDCFCACGBFCDDEHBCEGAFABEBFDEGAFDCACFEFEDEAAGAGAGCBCDFEHAHEHBCBCBFBEEFEHGGGCEFEFEBEAFFBDADB,False +892,15.0,15.0,17.0,14.0,25.0,21.0,15.0,21.0,EGAHHHDHDFEAEDEGGGGAGFHFAFEEEHHBCBGHGBGDFAAEAECEFEDDBFCFCAGFFHFHFHBCFCDHFHCHADBHFGFGBEBHHEEDDCDGBCEEEBGBHEHEDEAFCBCECEBGAAAEDCDCACABEHHCFEFCFBF,False +893,5.0,2.0,1.0,1.0,3.0,2.0,5.0,2.0,BHAHAEEEGFGFACGBDAGAG,True +894,1.0,2.0,2.0,3.0,4.0,6.0,4.0,3.0,FCFCHHEFEFGGGGHDBEBFAFDDE,True +895,12.0,25.0,10.0,17.0,18.0,19.0,18.0,17.0,CECBHFGFGEBBHFEFDBDBABDGAGAEABCBGAGAHCEEHEHEHDDCDBFHFHEDFCFBFBFAGGGGGFGEHBBBHDHBHDEBEFGDCBBBDBGCAHHEGBGBCDFDEEEDEACAFFGBBHFHFDFAFHGBADED,False +896,16.0,8.0,11.0,13.0,10.0,11.0,7.0,7.0,GEDEHEHBBDADFDADCDCAAAHFHFGFECACAEDCDGAEAEBBCBGEACAHDBDEGFHFBCDCFAADACBCHFAFAFEGGDF,False +897,11.0,6.0,9.0,7.0,10.0,14.0,15.0,10.0,HDBFBGCFCGCGBGDEDGHAHGHAAFHFCGBGCAHHGFCFAFEBGHGBDCHCHDEEFEFEAEAEFEFGDGFAFACGEFDAGA,False +898,17.0,13.0,21.0,30.0,28.0,20.0,12.0,19.0,EDDBGCECEDBCBCDHGFECBGBEHHHEHFHDGDHHAFAHCHDBEFDADCDHEEEHEGDGDGFEDCACEDEAEAEFDFDFDADCCACFEFCFEFCBBHCCFEEDHDFGEGAFCFCACABABCGDEDAHEDDDDGDGFHDHDABFCFDFAHEEBEBEHEAA,False +899,3.0,3.0,2.0,3.0,3.0,3.0,8.0,3.0,BCEFGHGHGAGBGBGDFDCHEGEFAADG,False +900,16.0,24.0,17.0,15.0,11.0,13.0,13.0,18.0,DDCDADAECDHHHCHADDHCHCBCADAECGHGEAHFHGBBHDADAEHHFHGACACFCFBEBEDCGCGBBBBGEFFHFBBGCGBABABAHFEFBBECCHGFDFBFAFAHBBEBEACDGDGCBHBGBDB,False +901,25.0,30.0,29.0,16.0,34.0,19.0,24.0,19.0,FFGCECEBBBCDCBFEEEECGCABAFEFGHBDAACECGHDFCHBFBGGGBGHCHCBCECBGBEFDHBHBHCHAHAGABABGEGFCFBEGEBBCBCDHHHCHCHDBDCFCAEDHGAGEBEGEBEDEFFDBDEFBCEFEAGGFGEGFBFHHACACAEAEAEBEHEBAGAEAECGABADDDAECECFAAEDDAGCECBG,False +902,24.0,23.0,19.0,24.0,26.0,27.0,19.0,14.0,FAAAEACAEEEGEDAHEBADAGGHEDCABGFFDFDFEBEBEDEDGAHFDGBCBFDFGECFBFGFBFEFCFEDADBEFEFACACACAHADBBBEHAHBGBFAGBEEGGFGCGCFAFDFEBHGCAAGDGFHFCFCHCDCBFBGBCBEHFHCHCBEDGDACAEBDBHFHEDDDDDEAED,False +903,29.0,29.0,25.0,18.0,19.0,26.0,26.0,24.0,GABBEDADAGFHBHFHGCBCBDADGBGDGHEDBGBGDAEBEAGFGACEBEDADFFFBBBCFCGAFAHEHEHGBAAAAAAGGCCHBGBABHEEFHFHAHFBGCHDHFEBEGEAEDFGCHBHACADBHGDGCEDFFHFEFBCBABAHAEAGGFFCFAHADGDGCBCBCGCGCBCBCFHEHDFFEFHFCFABCHCDCAC,False +904,6.0,3.0,10.0,6.0,5.0,4.0,4.0,1.0,ACGCFCACDCHCDDDEDCGGEFBCBCBFGFEEAEDCAAA,True +905,3.0,18.0,9.0,11.0,14.0,16.0,4.0,13.0,DCFBBCBEBDBFFEFDCGHBHGDCFBFDEHEFBHBFEFHFHFGCAEHFAFBEHEHEHCACHGFDCBEFEHEBDBDBHBDEDEDBCBFB,True +906,16.0,25.0,37.0,22.0,24.0,10.0,28.0,28.0,DFDCDCEAEHCHEACBHBGBHCCGCECADDDDDDCHHHAHCCCGDECECEBECHCFCFBHBACGCBABCBHGEBBBHGHGBCBCDEEAAGAGDHFCCEDEDGDGDGBGHHDFFGEEBFAGHGFCBBGEHHBCBDBABCEAGACACGBEHEHCFDHAHEGGGHGHGACEDECHCGCGCDHFHBEGEDBCGC,False +907,25.0,18.0,28.0,21.0,19.0,32.0,30.0,20.0,GCGCEBHGCGCEDDHHGCCCCGHGHDHEHACGGGBGFGBEACGHGCFDFDCCCHCFDFAFAEAGABACAGACEBHBFGFBFBDHCFAFGFACAGDEHCDBGHAHBBDFDFCFAEBDCGFAHGHGFGFGBADFEFHBDADABBEAFHDDFDFGBGDEDEFAFEFEFGFAFDFEFCACHFHBEEECGCGCAAEAC,False +908,28.0,27.0,16.0,15.0,23.0,29.0,25.0,24.0,FAFEFGFBABHFFBHDCCGAABEBCACAEFFCFAGAEEGEGFGFDFHFHBAGFGBGDHBHBHBCGEGFAAHAHAHAEGEBEAHABCBDFGFGEGBFBHBDBFBFGFGHGHBEBEBDGHGFAFCHADEEECECFBACCBCDDHGGEHEGCAAFAFBDHHHDHDFDADGFAAEAFABEECGHHDBEACB,False +909,22.0,23.0,20.0,21.0,31.0,23.0,29.0,28.0,EAGGGDCHHHHCDDEDBCHAEDGBGAGADBHAFFHGBGBDEGEGHGAGDBEGAGCCHFHFGEGHHEAEBDDDDADHCBBBCACFCGAGECEAEFEGEDDAAEFEHBHBGBFCFCHGBBDBFBFDEAEAEFCDDEGFGFCECAGHGFGFEHHDAFHFHGHGHFHFEEEHAFBBBEAECGCBCBCEEAHACBFDFEHEH,False +910,35.0,20.0,17.0,22.0,15.0,17.0,23.0,20.0,BABABADGDFFFFFADHEEAEHCBGBGDGEGCACHEFAAHAHAHBHGHBABCBCGCFDFAFCFCEAEHEDGFGBAAADBGADADBDBECGGFCBDBHCAADAHAGADCGFGFGCGCEDAAEAHDEDBAGFGBADDDCDHHHCHAHDEAHGFAEAFBDHAGAEHBBGCGA,False +911,20.0,22.0,16.0,16.0,19.0,34.0,24.0,21.0,HHBBFFAHAHEFAFCDBDBDGCEEBFBDCCBCHDFAFDBDBFCFAHGEDBGFFFDFHACEDGDBFBFCECHCHBFAFADAFFFFFFFGFBHGHGHGHAFABACHCFGGGAFHFHGGGGFAFEEGHGEEEGECDGECBCBHDGDGHEHDBAGEBEAEABABFEGACHEBGFAF,False +912,14.0,22.0,22.0,16.0,10.0,16.0,13.0,11.0,GABHDHAHACDCBFFFECHFHEBEGABCEHEBBFBACHCHCACABEFFDBACDHFADAFBFBGGCGCGCHFBFCGDFAFGBCBCBDHDGDCBCBCGDGCGAGABCBCACEDFDEEFBBDDDEDB,False +913,20.0,27.0,29.0,23.0,22.0,31.0,29.0,18.0,GFGEECFDFAGEFHFACDEGCGCGHGHDHDCGCFDBAGAGAGDGHFDFBFGFGAGHDAGAFABDCFFECECEFFDCDCBCGDBABFFHFDDDGACHHDBEBEBFCEEBEHAHECBABGGAGDHDCEEGFCFBDECACAFHFAFACBEAGGGBGBCBHFCFCFCFCHDFAEBBBHBEBECFCHEEGBGBFCDBDBDBHGC,False +914,12.0,9.0,6.0,2.0,6.0,6.0,2.0,13.0,BFBHEHEHBADCHBAGFHFEBHAAACABHBHAAACECBBACGCHFHAHAHEHEFFD,True +915,10.0,12.0,24.0,13.0,16.0,14.0,13.0,16.0,CEBDBDBDCDCDCDBDAHHBFBFCFGFGEDFHCBCFGECFCEBEBHBCCFCFDFEHAFBHAHAHFCACHCECEHACBCHCFEDEAGACDCHCGAHCDEGGHEEFHAGGGECEGEHDGG,False +916,4.0,4.0,9.0,4.0,6.0,12.0,3.0,4.0,CECDADFBACFCFDFBFGFCFGHCCGBEHEHEHEFFCACBEFFFAD,True +917,15.0,18.0,12.0,11.0,16.0,11.0,18.0,15.0,AEAEAEAEAHAHAGEEFHGHBHBEDABABADHGFGDHBCDDFHGBEFFFAFGGHBDFCBEHECECGFHBHEEGDBEGEBBGDCDHDCACGFGHGCABABHFACCCCBGBGBGDGBE,False +918,14.0,16.0,12.0,30.0,16.0,18.0,12.0,16.0,DHDAEBFADADADADADGDFAFHFHDEFGBGBGBGFHCGEHECEAACACGCDDDFEBEBHBFAFHCDDDDFCFDFGHCFDHEFEFDCHBBBHAEDEDBAAHCEFDCDBDFDBEEDBDHEBDHDGFHDHEGGGCB,False +919,5.0,11.0,3.0,9.0,10.0,8.0,8.0,5.0,BFBHEEEBCBHEHGAGAGDDBDEEEHABFCFBAGDCDGDBDGAFEFEFDBDGGFBFBHE,False +920,5.0,0.0,5.0,4.0,1.0,1.0,4.0,2.0,CGAAFADHDCACGCECGDGDHA,True +921,24.0,17.0,18.0,26.0,23.0,31.0,24.0,25.0,EDEDCDADFGBABAGGFCFDFEGCGBHHECEADGDEDFDFDBEGEFCAGFEFEFDHEADHCHAHFHFHEGEDDDDBGEGEFBCDCEAAHDBAGHDHFGGHEHAHAHAHFHFDFBGBHCGAGFEFEFADACAFEBGCCDBEBADAFBGCFAFCHCHAFEFGCGBGCAFABCDAFBFBHDHFHEGDGHFH,False +922,12.0,3.0,17.0,8.0,6.0,8.0,19.0,16.0,GDFCHCHAADGBHCHAFEHCHCBGBCHFACAFADGGGGGGCGCAADHEHECEAEDDCCEGFGFGAGAHHGHGCDADCCHHGCGFHFHGC,True +923,13.0,7.0,15.0,17.0,15.0,11.0,14.0,5.0,GDDDHCCBCDADAEABADADGHFDCCACAEAGGDEEEDFHFBDGCHBFBFDGGBCDDDFCFCFEEGCFEFADADACAGGGGEGCCAEBEHEGEFECE,False +924,19.0,22.0,14.0,20.0,28.0,12.0,19.0,18.0,CGCDHBFBHGEBEADBDGDGDCBCDCHCEBHGEGEHEGDFFCEAEDGCGEGFDEEEEEBABCBCBCBCBGFDFAEAFDHDHEHFDAAHHHHEAEADAFEFEDBABDHEFEAGCBBFHDHBHBGBADHEEDBDEGBAEAGGCGHBEGGAAAEA,False +925,20.0,23.0,18.0,19.0,19.0,27.0,21.0,22.0,FEHEHEGDGCBDBHBEBCAGACHFEFHAHADAFGBGFFEGECEHDGDAHAHEDCCEAGFDFEGCCBGBFBFHDADCBCBFBCCHBHAHBDCECDFHFGFADCFFFFBFADBGGHADFDBBCBGHHHEHEHBAEAEFGBHBHGAGEFEFGFGFDCDFBFACAGAEADGDB,False +926,8.0,4.0,5.0,5.0,6.0,5.0,4.0,8.0,FGFDECECEADFBFBHEHAHADAHAEACGDADHHHBHFACBEGCG,False +927,4.0,9.0,2.0,4.0,9.0,4.0,11.0,2.0,GHGBGDGBGBEAGFGBBBBDDEBGFGEGEDECEAEAGBFCEHFAE,True +928,19.0,13.0,20.0,26.0,25.0,21.0,11.0,20.0,DDDFAGCFCHADFCCECECFBEHDBEBEDEHEHCFAEAEAEFDFBFADAEAEAEADHDFDFGBGBADEDBHCGCFCBEEAEHECFHAGACCCDDEDHHHHAHDDDACGHBACFCFGDEFEBHFHFCDDDHDACECBDHGHEEFGBGFGFEDHFBA,False +929,31.0,26.0,25.0,22.0,30.0,19.0,16.0,16.0,GADBEEEAEAHACCCCFGFEHBGBGCFCFDDADGBAAAFEFAABEHADFDFACAHBHGEFBAAACFCGABEGFABGFGEGFBFBEBFDEDEHGFEECHAHADADADCHEHEBEDABHBEACADBDBDGDGDCDCACHEHGCEHDCEABCFAEDFDGCEBFBAAEHEDEBCBCBCBCBEEAEBCHC,False +930,5.0,6.0,16.0,9.0,2.0,8.0,6.0,8.0,FCFCBBGDGDBABHCHCGEBEDDGACFCFCFCHCGCABHCCCCHFHCAGFHHCAFDDDDD,True +931,13.0,10.0,13.0,5.0,17.0,8.0,8.0,11.0,AEAEAHAEECBHBHGHAEBFCEEAEBEGCHBFBGEGFACADAEGEDBFCCHHBHBHFHCGEGHDDCDCACAEAFBCGCFEFECEA,False +932,13.0,15.0,7.0,16.0,20.0,10.0,5.0,18.0,AEABBCHEBEHEFEDEAFBHBADFHHDBDEHBABABABACDCFEFHFEGGACEDEHEBBAFGHCEDEDBGCHHDBDBEHCHDADGDEDEDHFEEEAHAHFHFHD,False +933,4.0,6.0,3.0,4.0,2.0,6.0,4.0,5.0,AGAGAHBEEDCGBGBCBDFDFDHHAFBFHFCBHF,False +934,5.0,12.0,3.0,2.0,5.0,4.0,9.0,11.0,CEDBABACFFGFAEAGCGBGHGHBHGHEBBHBHGDFHHHHBEBEAGBBBGH,True +935,8.0,6.0,1.0,11.0,7.0,1.0,14.0,7.0,GEBHGHGDBAEEDAGGEGDGBGBHHHHDDAAAAGDGDGDADABCEGEHEDDFGGB,True +936,12.0,13.0,17.0,16.0,15.0,22.0,16.0,19.0,HHEDDDDGDGAFACACHCFEEECACADBGHGFFFFFFEHEHCAGBDFEFDFEFEHEFFBBABFCHEGFGDHBCBCBEEAHCCECDDBFBHCHFHFHDEDGGGDGBGHCBGAFDGDGCAHBCCHGHFHFAA,False +937,3.0,4.0,1.0,4.0,2.0,0.0,0.0,2.0,ADDEDEHBHBACADBB,True +938,5.0,10.0,7.0,7.0,2.0,7.0,13.0,13.0,FCGGGHHAFEFBFBGBABAEGGGGCFCFHBABHHDHDHFHACDBBGHGDGDHCBDHCHGBGDHC,True +939,0.0,2.0,2.0,0.0,2.0,1.0,2.0,1.0,CGEGEBFBHC,True +940,15.0,12.0,17.0,12.0,18.0,16.0,21.0,10.0,DADACBCEGEGCCAHFCDCDAEACDCFGDAEBEBEACABEGGGABACDFDCGGFDDHCGFGEGBCBDEDGHGFEFBFGGCBCEEFAFGFHFAFHGHGCEFEBHBHGEGEGEFAFAHACBHE,False +941,21.0,9.0,18.0,19.0,23.0,21.0,20.0,26.0,EGEDHBHBHGHGHCEAAGBHBDDDGGGDGFGFEFGFGADHEFEAEAFAHAEAHBFECDCAAGDFAFHEHCCDCEFHFHFAEAHACFCFCHCECEHDDGDHDHDADEBHFEGAAEAFBHCCEGGDEDBCHADAHFBFCFCGGEDECFHGAGHECEHFH,False +942,23.0,23.0,25.0,23.0,16.0,18.0,18.0,24.0,CAHDBDHDEGCADHGHGHGHFCDCHCDFGEDEDHDHBHFDFEEADAEABFFGFGACFBBCFCBBFAHCHCEEDCCFHACACABHBFFFDFECACHHEGDGDEDBHBCBHBHADABHBHBCGHACBCBEBABCGEEFEAEAGGCDDDDAGAGAHBHDGBCFGFDCAGACAB,False +943,9.0,5.0,6.0,3.0,2.0,3.0,4.0,6.0,DBDHCFFHCEAEGBGBGAHCHBBAGFCAHAHACADACA,True +944,1.0,5.0,5.0,2.0,2.0,3.0,5.0,5.0,EGGDGHCBBAEGHGCFCFBHBHBHCFCD,True +945,23.0,12.0,17.0,23.0,21.0,25.0,31.0,23.0,AHAHBHBHCHCEDDFCACDCDFGFBHBCCGFGHGAAHDEEGECFAHAHFHDHEADFGCGCGFGEADBEAEBEDDBCBHAAFAFAFDGDHABAEHDHGEEEHDADGFGHGFEFGFCFAFHFEFADGGEGEGECFDHCHDFGHGDGCAAGAGEGFDBGCEBGBGDEDHFFCFGAGDG,False +946,7.0,6.0,9.0,5.0,3.0,13.0,9.0,7.0,BEBECFHFHAHGCAABCCFGBGFFCFGFBFDFGGAGHGFFFFDBCGHHCHCDDADAEAC,False +947,12.0,14.0,22.0,9.0,8.0,15.0,19.0,16.0,GGGGGADFDBBBCHGACAHBFGHGHGFGCCFDACHGHEFFBCBGEGDGFHHHBHDGDCCCCGBFHACACECDCFGBHBHBCEFECHCBCBCHGFGDAAAADAEEFCFCACFFEHB,False +948,23.0,29.0,24.0,18.0,9.0,25.0,25.0,32.0,BBBHGFAEAEBEBCFCFAFAFCFDFBHBGCHFAEGDACAGBHCHFDBCBGGCCBBHHABDCFGHBDCDBDGFBCAFAHHGHFHEHACEGDABGBGHABABGHHHFBFCFHFABAEAGACBCFHHBABCBCBCACFCHGHCHBGBHDDFGAAFFFEDDDGDHDHGHGHGHDHGHGHDCDCGFGFEA,False +949,7.0,6.0,5.0,7.0,7.0,6.0,6.0,12.0,HHCHADDCGBGFFHDHBBCHCHBFADAEAGAFAEAHBHEEEEHHHBGDGEGCDFDF,False +950,24.0,23.0,22.0,11.0,20.0,30.0,30.0,14.0,EHFBFBFBCCFCAAACEGBFAEEBHCHFHEAEAGBGHGHGCGCFEFAFBEAGAEBGDGCGHGHBBGBGBFBFDFECAGGFEBEGCAEBEDGHAFBHBFBDGDGFGDACCGCECACAGFCECHDFBCGCGFFFGFGCBCGABADFBHGGFGDHDEFBHCAAAAAAFFFFFDEEAE,False +951,16.0,19.0,15.0,15.0,20.0,28.0,15.0,17.0,DGGFECEHGHFHCBCEHGDGCBCGCEEFAFAFAHEHFAABHEGDGAGBGEEBHDHBBCBCHFBDBDBHEDFCAEAFFFDFDFAGBCBDECFFFEFDFBFGFGEECECEFEFEDHGCDAHAEABBDGFBFHHBHDAFHFCFAFABA,False +952,9.0,0.0,6.0,3.0,8.0,5.0,2.0,3.0,EFACCCFAAAAHFFFDGAAEAEHGHECECEDECEAD,True +953,2.0,1.0,1.0,1.0,6.0,2.0,3.0,1.0,ECEHDAAGBGEEEEFGF,True +954,11.0,9.0,7.0,13.0,13.0,4.0,8.0,8.0,CADHDHDFDABBEACAFDBBHFHGAGECBGEGEGEBEHEDEAHBGDADADADFDEBEDDCAABHEHCGEGECC,False +955,17.0,19.0,17.0,18.0,12.0,19.0,16.0,32.0,GFGFAAGFGAHADGGHGEBABFEDBHBDFHHHHBGBHDHDEAACBFBFBEAEHCDDGDFHHEDGHGBGBGADHFHDHCCGAEACDCDCAHAHFHFHFHDBDADHCCCHBACACBHFHFEFECACGEBBFDHCHDHBHEFGCECHFFBHBH,False +956,21.0,23.0,17.0,24.0,20.0,16.0,15.0,22.0,DADEHFHDCBCBCAHGBGFDFDGBAFDFDHHFDBDBACACFEHEAEAHAEEBAGCHCFCFAHAGDGDADADHHGHGECCFCFGFCHAHGDGBCCHADBDEAHGCFBHBHBHEEEEEHEBEAEGDBBFBHHCDCEBBBDBDBAADGFABADFEEGEDDB,False +957,10.0,10.0,8.0,10.0,12.0,10.0,10.0,2.0,FGFBFDFCGGFGABBBDGAAAFHFDGDBDGDEDECECECECGBAEHECGDACEBGBDFCAEAFFEDEBABAE,False +958,23.0,37.0,29.0,27.0,20.0,20.0,23.0,19.0,ADBDBAFABHBADGGCCCHFHGBBDDCACACBBAGDHDHCHFECBHFEGEBEDCCFEDEFBFBCBCBHEHBGDCDGBGAGAFFGCGEGAADACADBGFEDGBGFDBHBCAHEEFFDCDADBDBACDCDCDBHBHFEFHFDBGBGEFHFHBACECEDEBCBCBCGCGBBACAGEFBFBABGDGDHEHEGBCDCBHEAAA,False +959,12.0,18.0,18.0,8.0,12.0,10.0,17.0,15.0,BEBEBGBGBHBCBCECGCGCDCFGGHGBCHEACCCEFGAAAEHBHEHBGBHAEABHGFCFCDCEABACAHEHCGCHFEAEGDBDHDCGFDCDAHBHGFDFGGGHFBBBAF,False +960,6.0,8.0,14.0,11.0,10.0,8.0,6.0,15.0,EADADHGFDEEHFHDHBHBHCECDFDBDECHFFAFGFBEDECBCECHHHHGCGDGDHCCCCCCEEDHHAHABCGFABB,False +961,20.0,29.0,25.0,20.0,25.0,26.0,26.0,18.0,BHBEFEABGFAEGDGDFFBDHDGBGBFFFHEEEEEDFAFADABGGCGCBCBAFCFABCCHEHGDDEDEGFFAAEEEEAGCGAGHGFDCCBCHGACACEDHGHGAFBFBFAHEBEBEDGBHCCEAEADDDHDCBCFHAHCHBHBFBFBGGGBHECGFGECBCBCDHDBBFDCACACBFGFGEGCDEBFBF,False +962,27.0,19.0,27.0,18.0,20.0,32.0,29.0,28.0,GEGECAFAHHHHEAEBDBDCHHGHFEFHDBFAFBFDGDBCBCGHGHFCFCFCFDEGADHHCCADADAGEHEHGACCHGHBHEHCHCHFECGCFAFBFAFGFBCAEFCDHAGFBFHGEGAAHGFGEDEACDCFHDDCDCFCHCGCEDGHBDAAFAGBFBFHEGAFACADEFEBEGGGCGCBBFBFGAGAGAFABAGFBEHF,False +963,18.0,20.0,27.0,19.0,14.0,17.0,15.0,25.0,FFACCGCGCDDHCHCDGGGEHFBCBHFCAAAAHAGFGDGAGDGHFBDEDHCBCACACGCGAFEBBCECEAEHEHBBCHHHHAACDCDBDFCFBFBHCHBHDGCEEEHEDGBBBFEFHFHDCDBDADAHFBCBABDCEAHHDACFCGHBHFHDCFE,False +964,12.0,10.0,8.0,9.0,12.0,10.0,10.0,9.0,FGFAEAEAGADFEECEHBBBAHAEBECECAGGHBAAGEHFHDHAEFDFECDCBFBFBABDDFDGGFGCCCEHAHBHGDGD,False +965,17.0,22.0,24.0,31.0,26.0,22.0,22.0,27.0,CGCEHFCFCEBDBDBEHEHGHGHFABABHEHFBEBGHDHDFCBDBEBGGCHCFDFHEHDHDGDFFBCAHAHGEEFHBHBEBADFFAFAHDHGAGAHEDDHDEBEFEBEFHFHACADDDFDEEEECCCDAGADBGAGFEHBGGHDCCCDEDGHCECDDABFBEBCGEGCGCFCDCAAEDCBGHGDFDGDCDF,False +966,27.0,18.0,26.0,14.0,26.0,27.0,37.0,24.0,AACDCHCFGHAHAGAGACFHEHABFHFAGHBCBDBFBFBABFHHHFHFCEDEFACHCECFGFEFECGDGHGCGFGEHECDCBCBGBECEDFAEECAGGFAFBHEFDGBGEGHFEEGEHCGEGDGDGDFCCCCHBAEACHGHGAGHGAGEHEGEGBCAGGGFABHDADADAGAFHBEDCFAEECFGFGFGCGABEFGABA,False +967,19.0,30.0,23.0,20.0,26.0,19.0,25.0,21.0,BBABCBGGAGFDFGHDHEGBGCGBBAFDCBCEFHDCDFBCBGEFBHBEEEEEBADAHAHBGGGEDBFBHCCCECBGHDHDFGBDCDFBEHECGBGBGFCFAHEHDGEGEFDFDECCCHCHEGEGHGBCEAGABEBABABABADADABAEADCCEFBABFECDFHFHCHFEFCGGEHEHGDADH,False +968,22.0,15.0,29.0,26.0,37.0,20.0,22.0,24.0,AEGBABEFGGEGDHDHAHEFECEFACEEACHBECFBABCDCACAHGHDEEFECECDAAAEHGHGHDHDFGFHCADFDBDEDEAEDEDEDEDGGECEABBGFADADEHGHFECBCAEAEGECECAGDBEGAACCCCCCBHEGECDCDFHFHFHFHFCGEGHBDFEBBBGECHDEFEHHGDADCGHGDDCEFHFCFC,False +969,16.0,6.0,14.0,15.0,9.0,8.0,13.0,13.0,HHHHFEFDDCAHGGEGDGDCBBHCCDADGGHAAADADFDFDGDGDGABEBAFABECDHAAFAFEFGDGCHEHCDCGCEEHHHAEACCCCBCGAA,False +970,21.0,25.0,9.0,17.0,8.0,13.0,18.0,16.0,GBGHGACACAFHFBCADGGGFGFGAGAGBBDBGCHHEHEBFDEABGDGDGBHBCDFFFFHFHAHBDACAHDHCCGAEADBHBDFABABABEBEAECGGBHBHDFBBBBAFDDAGBHHABDDADADBE,False +971,9.0,10.0,11.0,9.0,15.0,9.0,14.0,12.0,EAEDFCFBFBAGHGHGDGBHBGFHEHCFAFAGHECGCHCADAHCEGDGCGBBBBDBDEGFGCCFHEEEHEDEAEDBCGHGCADHEFEAE,False +972,18.0,16.0,12.0,13.0,15.0,19.0,12.0,21.0,BEHFBBABAHGEEAEAFAFCDEHFHAHCGCFBEAAFGCABHHFHFHCHBGADCDHDHCHCEEAGBFDFGADFFFFBFBGDGAGAEADHDHDAEEEBCBCBHBDEEHGFGFBFBDEHCHGHAHFCAD,False +973,27.0,25.0,26.0,28.0,24.0,17.0,20.0,27.0,HCHEFEACGCFDFGCBCHADFCFBADCGHBHCDDDCBAAHAEEDADGDGHGHGHGDAAEBEHAHGDADADEBEHHCEBADAHHHHCHCAAAHBFBDCGBFCHEEFBFBFHAEADDBFBFBDGDEHEHBHGCGAHACECAFBFBEEEBECEFDCCABDBDEDEGAGADEDEDCFBBACHGGFGBGCGDADCHCBC,False +974,2.0,9.0,5.0,14.0,10.0,16.0,13.0,8.0,HBEGFBDBDHEEFHFEGDBFBFBGHFAFDFGFCFDBDBDHDHBGGCFFEGEGECADGFECEHFGDCDHDEDGFGFGD,True +975,7.0,10.0,11.0,8.0,6.0,8.0,11.0,11.0,CECFCDCHGGGGHGAFCECEAECDCGHHBADHDHDBDBFBFDAHGBBBBBBGCFFFAAEHDFCHGAGHCHGE,False +976,22.0,16.0,20.0,24.0,18.0,27.0,21.0,14.0,GDBDHEGEBFHFHDDCFCDAAGEFBFEDBAHGBGBGDFEBBADGHGFABAFAFDCDCBCAHADDDCAHECCDAAFAFGHCCECFGECECEFDHCHAHGBGBGDECECECEAEAEBFBFGHGHAADDFDBDGAFCFBHACAEEFGFAFDFDFGFGDCDGGFFF,False +977,16.0,17.0,23.0,22.0,27.0,15.0,19.0,22.0,EEGGFDFHCHEEAEDEHEHGCEFGBEBEBHBDDCBAHAHDGDAEGEGDHFECBDDDHDCGCFAAAAAFCEHBBEECEFDFDBDBCCCCEFEGAFFCFCFCEBEAHAHAHAGGHGHCHCBGEDBDGEEHCDGHBCBDAHFHBHFGGDHDEDAGECECBCDCG,False +978,5.0,8.0,11.0,18.0,14.0,13.0,11.0,18.0,HFHDBAGHGEFEHCGGEGDAAFHFEFEFDHDGCECHHEHEDEDHGHDFBFCDHHHAHEHBCBCBCDCDGDECEDGDEBFGDCDEBGHFBFDCDFHFDA,False +979,22.0,10.0,19.0,14.0,19.0,26.0,19.0,18.0,HBGDGHGCGBGEFEAEFBDEHEAAHGGGGHDHDHFGEABAFAHEHCACFFDFDFAFECGCDCDCDCFCHCFCHAHFDCBGAGDEHBGEAFAHAHEFAGHEAGACEEEFFFFEFHFBFCFBACGCAFAFCBEFEGEFCGBDDDCAAAH,False +980,9.0,10.0,16.0,13.0,13.0,13.0,17.0,6.0,CDCEBDGFGFACEBDHFCEHACADBDBHBCBGACCECEFEFGFGACHCACDEEGGGEGEGDGCFFFGFDBDFGGAGAHACDDDDGEGFCFCEHBBEB,False +981,19.0,23.0,15.0,12.0,16.0,18.0,17.0,17.0,ECEDHFHFHFAGAHBHDAEFGFBEHGBGBCBHBCEDGDCBHEAGADEGHFHDBBABEBAGAGCCDADHDCGBBBEGAGAGEBBBGFGFCCBFBFEGHAEGHFCFCFCACEDHDAAAAAHDBFFHFEFCBCBEBEFHA,False +982,21.0,16.0,13.0,14.0,20.0,12.0,19.0,12.0,EBEBGBGDGEGECHCHFAAEHBCAEBHBECECACGCDCDCDBABAFABGHGHAAEAHABDEDEFHFGBCDAEAGFGECDHGFGDDDEHAGGGEGBCFDFAFBEGECEHAFDFGABADAGAEBHFAEB,False +983,22.0,16.0,20.0,28.0,16.0,18.0,28.0,14.0,CGCGBDCDCGHACGFDFDGDBDCFEFEFADAECBDDDEAEAEAHAHABGDFAAGFGFGCAAGEDEGFDFDCGBGAGBGHHHGABCBDBDFDFCFDFGCAHAGACABAFEFAGEEDEHBCCHEGBBBDBDHGEDCHCEFAHHGCDHGGFGDGDGDBEGACDCD,False +984,26.0,22.0,19.0,22.0,24.0,27.0,32.0,24.0,ADHHEFAFADABADAFABCGCGAGFGFEDADABEFHFHGHDFGEGADCCFHHHGHGEFCFCEBDGEFEFEGAFBFBFAHGBEBEAGDFAHABAEGHGCECEHBHBDCFFHBAAGAEAGBCCDCDHDHDBDBGBEDDDCBBFBGEDFDHGEGEGEAFAGGBGBHEGBGFGDECHFAFEHHFCGCGEGCCHCHAAFDG,False +985,7.0,9.0,7.0,9.0,13.0,11.0,7.0,5.0,FCBCHEDFAFHEGBGFAEAEAEAFGDGDBDBABAFGEGDCHCHEEBFCEEHEBEDEFFDFGBDBCCFD,False +986,8.0,13.0,17.0,13.0,13.0,11.0,14.0,10.0,HGEDFDFDFDHDHDHDBFEFAGAEBEDGDHHFBBEEABBBFBHGHCCBCEEGECFBACDCDAAGCFCGBGFFEAGDGHCCDGEGCGCGCHCECBCACEB,False +987,20.0,12.0,18.0,25.0,18.0,18.0,21.0,30.0,AAADFHFAADFECBCECEHEHADCDGDGDCFHFHGCGCGFGFCFHDCAHEEGDGCECHCHEBFBHGHGEFHBHFGDADEDHDAFADEHBBBEGEFHADFDBCGDHHGHGHGDGDHDGDFCFEGGFGCAAEAEBHAHADBHEAADHDCECHDADHCHBHFHAB,False +988,20.0,13.0,12.0,16.0,10.0,14.0,25.0,12.0,BBBCHGHGAGFGHGDCACHCHCAAAAAAEHBDBAFDGDGDFCGGEBAFDEDEHEDGDEDADABCBFDGAGAGHGAEDBGGGGDGBFBHAAGBGHDFEFGAEECCGFFBFGFGHCHAFFCACD,False +989,12.0,14.0,12.0,10.0,10.0,5.0,11.0,8.0,AEFEBABAHACGFBABGBGDEDGDEBBCBCHCECBCACDCGHGHGEACFCBBBEFGDDDCDBDADGEHAACHEGAGFBEHAH,False +990,22.0,22.0,18.0,21.0,13.0,23.0,11.0,18.0,AHAHEFFDDCDFGHDFDECHDHABEBCBCEAFBGGGGFCHCBCHHBEDFAFABCHCBCBCBABDDGHHDBFGEEDADFECGBAECEADADADAFFDFBFBFBFAHDFDBHBDEAEFHFGAHAHAHACCBBABGCGCFHFAFDFDEBCA,False +991,10.0,6.0,7.0,9.0,6.0,4.0,5.0,5.0,FDCBCGFHFHBBBABGDFDAGACACEEECAHDDGDEAAADADAECECHDBGH,False +992,9.0,13.0,4.0,15.0,7.0,15.0,17.0,13.0,DEAHFHGHBEGEBBGFFFAFDFDHDGDGHGHFHFDDDCEGBACGDBDGDEHEHGHGBGBGHFBABABFFFAGADHDGGGHFACBFEDDBCAFB,False +993,1.0,1.0,4.0,3.0,4.0,6.0,1.0,3.0,EFEFEFAFCEGDFHHHDFCBCDC,True +994,16.0,14.0,21.0,15.0,11.0,19.0,16.0,24.0,AHACCCDCAAFBFEFBDBAAGAHHCHDHEHAHEHEBGAGAFHFCGCEFEFEDACHCHCGGGFDFCHCDDDHDHAECHGBGBEHCFBDBGGFHFGBAFHFCDADCFCBCBCEHAHFHBCEGGGFAHBHDCDFHFGDB,False +995,7.0,6.0,13.0,6.0,12.0,13.0,4.0,9.0,CEAFHCHFHECCHEACFCFGGAGFCHCHFAFEDHHCECFBDBDGECHDFEEEEEEBABACFCFDFDFBAB,True +996,4.0,9.0,13.0,8.0,5.0,3.0,3.0,5.0,AGAEADDCACBCBCDCDEHECCFHEDBCBCDDDFEBHBHCCCBBFHGCGB,True +997,3.0,1.0,1.0,6.0,4.0,5.0,7.0,3.0,DDDFHEHCGFGFGFGEDAGAEHFDEDBGAG,True +998,18.0,17.0,15.0,15.0,11.0,15.0,12.0,20.0,EBCFCHHAACHCHCHGBCBCBCHDADAFAFEFDFDGHGHCBCFFHCACDFAFAHAEAEAEFEBCHAFBHBFGAEDBDHDHFBCDEAGABBHGADDBDBDHHHEBAGCEEHFHBGGDGFGAGDB,False +999,6.0,13.0,8.0,13.0,6.0,19.0,12.0,12.0,GDGCGCHCAFGFEFBFDEDHFBFBDBGFDADBFBACGBGDGEFBHHHHBDAFGFGBGHCFFECEFEFBAHFDFBFDAHCHDHCHDFDGB,False diff --git a/tests/results/nb_gm_002_2back_240trials.csv b/tests/results/nb_gm_002_2back_240trials.csv new file mode 100644 index 0000000..1c50201 --- /dev/null +++ b/tests/results/nb_gm_002_2back_240trials.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,ralph_skewed +0,30.0,39.0,31.0,30.0,32.0,24.0,27.0,27.0,False +1,33.0,23.0,27.0,32.0,37.0,34.0,25.0,29.0,False +2,31.0,20.0,37.0,28.0,31.0,32.0,26.0,35.0,False +3,27.0,32.0,39.0,24.0,25.0,34.0,35.0,24.0,False +4,34.0,24.0,38.0,28.0,31.0,29.0,28.0,28.0,False +5,29.0,24.0,36.0,31.0,32.0,32.0,31.0,25.0,False +6,25.0,38.0,28.0,30.0,33.0,30.0,26.0,30.0,False +7,27.0,30.0,30.0,29.0,32.0,26.0,33.0,33.0,False +8,24.0,36.0,32.0,23.0,30.0,29.0,35.0,31.0,False +9,35.0,34.0,30.0,29.0,35.0,26.0,23.0,28.0,False +10,30.0,25.0,33.0,31.0,27.0,37.0,30.0,27.0,False +11,28.0,28.0,29.0,26.0,28.0,27.0,34.0,40.0,False +12,35.0,27.0,30.0,29.0,26.0,30.0,36.0,27.0,False +13,38.0,27.0,31.0,27.0,34.0,23.0,27.0,33.0,False +14,29.0,30.0,28.0,35.0,19.0,30.0,37.0,32.0,False 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various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/src/main/scala/org/xcit/nback/markov/models/State.scala b/src/main/scala/org/xcit/nback/markov/models/State.scala deleted file mode 100644 index fbbd844..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/State.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * A Single state with a label in Markov chain - * @param label A simple string label, representing the state and node - */ -class State(val label: String) { - - /** - * Keep track of transitions from this state to other states. - */ - val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() -} diff --git a/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/src/main/scala/org/xcit/nback/markov/models/Transition.scala deleted file mode 100644 index bc20a9e..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/Transition.scala +++ /dev/null @@ -1,8 +0,0 @@ -package org.xcit.nback.markov.models - -/** - * A Single transition in Markov chain graph. It is stored in "from" node. - * @param to the ending node of the edge - * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). - */ -case class Transition(to: State, probability: Double = 0.0) diff --git a/src/test/scala/ThreeBackBenchmark.scala b/src/test/scala/ThreeBackBenchmark.scala deleted file mode 100644 index 0c7dad9..0000000 --- a/src/test/scala/ThreeBackBenchmark.scala +++ /dev/null @@ -1,7 +0,0 @@ - -/** - * TODO Benchmark 3-back simple sequence generator - */ -class ThreeBackBenchmark { - -} diff --git a/tests/benchmark_diagrams.py b/tests/benchmark_diagrams.py new file mode 100644 index 0000000..8fa448e --- /dev/null +++ b/tests/benchmark_diagrams.py @@ -0,0 +1,159 @@ +import pandas as pd +import numpy as np +from matplotlib import pyplot as plt + +import benchmarks.common as common + + +def tlratio(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2,ignore_index=True) + stats = [] + for trials in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == trials) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == trials) + targets2 = data[alg2].targets if alg2.shape[0] > 0 else np.nan + targets4 = data[alg4].targets if alg4.shape[0] > 0 else np.nan + lures2 = data[alg2].lures if alg2.shape[0] > 0 else np.nan + lures4 = data[alg4].lures if alg4.shape[0] > 0 else np.nan + stats.append([trials, (targets2/lures2).mean(), (targets4/lures4).mean()]) + stats = pd.DataFrame(stats, columns=['trials', 'tl2', 'tl4']) #.dropna(subset=['skewness']) + + plt.style.use('ggplot') + + plt.ylim(bottom=0, top=30) + plt.scatter(stats.trials, stats.tl2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl2[idx], 1)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.tl4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl4[idx], 2)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('T:L Ratio') + plt.ylabel('T:L Ratio') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_tlratio.png', bbox_inches='tight') + plt.show() + + +def time_per_trial(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for t in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == t) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == t) + time2 = data[alg2].time.mean() * 1000 if alg2.shape[0] > 0 else np.nan + time4 = data[alg4].time.mean() * 1000 if alg4.shape[0] > 0 else np.nan + stats.append([t, time2, time4]) + stats = pd.DataFrame(stats, columns=['trials', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.trials, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time2[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time4[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2v4_time_trials.png', bbox_inches='tight') + plt.show() + +def time_profiles(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 8): + alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + time2 = data[alg2].time.mean() * 1000 + time4 = data[alg4].time.mean() * 1000 + stats.append([ni, time2, time4]) + stats = pd.DataFrame(stats, columns=['n', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.n, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.time2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + plt.scatter(stats.n, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.time4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_time_n.png', bbox_inches='tight') + plt.show() + +def skewness(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 9): + all_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + skewed_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) & data.skewed + all_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + skewed_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) & data.skewed + num_of_sequences2 = data[all_alg2].shape[0] + skewed_sequences2 = data[skewed_alg2].shape[0] + num_of_sequences4 = data[all_alg4].shape[0] + skewed_sequences4 = data[skewed_alg4].shape[0] + skewness2 = skewed_sequences2 * 100.0 / num_of_sequences2 if (num_of_sequences2>0) else 0 + skewness4 = skewed_sequences4 * 100.0 / num_of_sequences4 if (num_of_sequences4>0) else 0 + stats.append([ni, skewness2, skewness4]) + stats = pd.DataFrame(stats, columns=['n', 'skewness2', 'skewness4']) #.dropna(subset=['skewness']) + + + plt.style.use('ggplot') + plt.scatter(stats.n, stats.skewness2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.skewness2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + + plt.scatter(stats.n, stats.skewness4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.skewness4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Skewness') + plt.ylabel('Skewed Blocks (%)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_skewness.png', bbox_inches='tight') + plt.show() + +if __name__ == "__main__": + tlratio() + skewness() + time_profiles() + time_per_trial() diff --git a/tests/benchmark_skewness.py b/tests/benchmark_skewness.py new file mode 100644 index 0000000..f468b4d --- /dev/null +++ b/tests/benchmark_skewness.py @@ -0,0 +1,97 @@ +import random +import heapq +import csv + +# Common parameters +alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'] +trials_range = (10, 40) +n = 3 +sample_size = 100 + + +def to_benchmark_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [str(ralph_skewed)] + +def benchmark_nb_gm_001(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_001') + + +def benchmark_nb_gm_002(filename): + import generators.nb_gm_002 as nb_gm_002 + + generator = nb_gm_002.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + # print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_002') + + +def benchmark_nb_gm_003(filename): + import generators.nb_gm_003 as nb_gm_003 + + generator = nb_gm_003.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + print(f"sequence {i}/{sample_size}: {trials} trials") + seq = generator.generate(trials) + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_003') + + +def show_skweness_diagram(filename, choices, title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + print(filename) + data = pd.read_csv(filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) #.dropna(subset=['skewness']) + #print(stats.trials) + #plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'{title}.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + benchmark_nb_gm_003('../benchmarks/nb_gm_003_2back.csv') diff --git a/tests/common.py b/tests/common.py new file mode 100644 index 0000000..e40c0df --- /dev/null +++ b/tests/common.py @@ -0,0 +1,27 @@ + + +# Common benchmark parameters +choices = alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F'] +trials_range = (10, 65) +n = 4 +sample_size = 100 + + +def count_targets_and_lures(seq, n): + mask = 'D'*n + for index in range(n, len(seq)): + if seq[index] == seq[index - n]: + mask += 'T' + elif seq[index] in seq[index - n - 1:index - n + 1]: + mask += 'L' + else: + mask += 'D' + return mask.count('T'), mask.count('L') + + +def skewness(seq, choices): + import heapq + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return ralph_skewed diff --git a/tests/nb_gm_001_bm.py b/tests/nb_gm_001_bm.py new file mode 100644 index 0000000..54f6cb3 --- /dev/null +++ b/tests/nb_gm_001_bm.py @@ -0,0 +1,75 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq) , str(ralph_skewed)] + + +def benchmark(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets / s.trials, axis=1) + plt.scatter(data.trials, data.targets_ratio, alpha=0.2) + plt.show() + +if __name__ == '__main__': + alg = 'nb_gm_001' + fn = f'results/{alg}_{n}back.csv' + benchmark(fn) + # skewness_diagram(fn, alg) + targets_ratio_diagram(fn, alg) diff --git a/tests/nb_gm_002_bm.py b/tests/nb_gm_002_bm.py new file mode 100644 index 0000000..c8af543 --- /dev/null +++ b/tests/nb_gm_002_bm.py @@ -0,0 +1,105 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq), str(ralph_skewed)] + + +def benchmark(filename): + from generators.nb_gm_002 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials, int(trials/3), 0, 0) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +import time +import numpy as np +import pandas as pd + +import benchmarks.common as common + +def profile(): + from generators.nb_gm_002 import SequenceGenerator + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, int(lures/2), int(lures/2)) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('benchmarks/results/nb_gm_002_profile.csv', sep=',', encoding='utf-8') + +if __name__ == '__main__': + alg = 'nb_gm_002' + fn = f'results/{alg}_{n}back.csv' + profile() diff --git a/tests/nb_gm_003_bm.py b/tests/nb_gm_003_bm.py new file mode 100644 index 0000000..fa6c19a --- /dev/null +++ b/tests/nb_gm_003_bm.py @@ -0,0 +1,114 @@ +import heapq +import csv +import random +import time + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq, time_per_block): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [time_per_block, ''.join(seq), str(ralph_skewed)] + + +def benchmark_skewness(filename): + from generators.nb_gm_003 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['time_per_block', 'seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + targets = trials / 3 + t = time.time() + seq = generator.generate(trials, targets) + t = time.time() - t + print(f"sequence {i}/{sample_size}: {trials} trials, took {t}s.") + writer.writerow(to_csv_row(i, seq, t)) + plot_skewness(fn, 'nb_gm_003') + + +def plot_skewness(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def plot_targets_ratio(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +def benchmark_targets_ratio(): + pass + +def benchmark_chunking(): + pass + + +def benchmark_n(): + pass + + +def plot_timing(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['time_per_trial'] = data.apply(lambda s: s.time_per_block / s.trials, axis=1) + plt.style.use('ggplot') + plt.title(f"{figure_title} - average time to generate a trial") + plt.ylabel('time (s)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.time_per_trial, alpha=0.5) + + # draw fitted curve + # import numpy as np + # p = np.poly1d(np.polyfit(data.trials, data.time_per_trial, 3)) + # plt.plot(data.trials, p(data.trials), color='red') + + plt.savefig(f'results/{figure_title}_timing.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + alg = 'nb_gm_003' + fn = f'results/{alg}_{n}back.csv' + benchmark_skewness(fn) diff --git a/tests/nb_gm_004_bm.py b/tests/nb_gm_004_bm.py new file mode 100644 index 0000000..b4ad4a8 --- /dev/null +++ b/tests/nb_gm_004_bm.py @@ -0,0 +1,26 @@ +import time +import numpy as np +import pandas as pd + +import tests.common as common +from generators.nb_gm_004 import SequenceGenerator + +def run(): + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, lures) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('tests/results/nb_gm_004_profile.csv', sep=',', encoding='utf-8') diff --git a/tests/results/2v4_time_trials.png b/tests/results/2v4_time_trials.png new file mode 100644 index 0000000..9be91b4 --- /dev/null +++ b/tests/results/2v4_time_trials.png Binary files differ diff --git a/tests/results/2vs4_skewness.png b/tests/results/2vs4_skewness.png new file mode 100644 index 0000000..a488e1f --- /dev/null +++ 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+210,87.0,0.0,0.0,88.0,1.0,0.0,0.0,0.0,EDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +211,0.0,0.0,12.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCC,True +212,0.0,0.0,0.0,66.0,0.0,65.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +213,1.0,0.0,0.0,0.0,0.0,21.0,22.0,0.0,AGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFG,True +214,74.0,73.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +215,0.0,5.0,0.0,0.0,6.0,0.0,0.0,1.0,HEBEBEBEBEBE,True +216,0.0,1.0,0.0,0.0,0.0,53.0,0.0,54.0,BHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +217,70.0,0.0,0.0,0.0,0.0,70.0,0.0,0.0,AFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +218,0.0,0.0,0.0,0.0,0.0,0.0,36.0,35.0,GGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +219,0.0,90.0,90.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +220,0.0,0.0,0.0,0.0,0.0,0.0,37.0,38.0,HHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +221,0.0,0.0,44.0,0.0,0.0,1.0,44.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +222,0.0,0.0,0.0,67.0,67.0,0.0,0.0,1.0,HDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True 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+409,0.0,0.0,72.0,1.0,0.0,0.0,72.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +410,55.0,0.0,1.0,0.0,0.0,0.0,55.0,0.0,CAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +411,0.0,59.0,0.0,0.0,0.0,60.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +412,61.0,0.0,0.0,61.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +413,0.0,1.0,0.0,75.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +414,0.0,53.0,0.0,0.0,0.0,0.0,52.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +415,0.0,0.0,16.0,0.0,1.0,0.0,0.0,15.0,ECHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +416,0.0,0.0,0.0,39.0,0.0,0.0,0.0,38.0,DHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +417,96.0,0.0,1.0,95.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +418,28.0,0.0,1.0,27.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +419,0.0,1.0,92.0,92.0,0.0,0.0,0.0,0.0,BCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +420,1.0,0.0,20.0,0.0,20.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECE,True +421,0.0,90.0,0.0,0.0,0.0,0.0,89.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +422,10.0,0.0,0.0,0.0,0.0,1.0,11.0,0.0,FGAGAGAGAGAGAGAGAGAGAG,True +423,0.0,0.0,0.0,74.0,73.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +424,0.0,0.0,127.0,0.0,0.0,0.0,1.0,0.0,GCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +425,1.0,9.0,0.0,0.0,0.0,9.0,0.0,0.0,AFBFBFBFBFBFBFBFBFB,True +426,0.0,0.0,84.0,0.0,0.0,0.0,0.0,84.0,HCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +427,33.0,0.0,0.0,34.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +428,1.0,30.0,0.0,30.0,0.0,0.0,0.0,0.0,ABDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +429,0.0,0.0,67.0,0.0,1.0,67.0,0.0,0.0,EFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +430,62.0,0.0,0.0,63.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +431,1.0,9.0,9.0,0.0,0.0,0.0,0.0,0.0,ABCBCBCBCBCBCBCBCBC,True +432,15.0,0.0,0.0,0.0,0.0,0.0,14.0,0.0,AAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +433,0.0,1.0,0.0,65.0,66.0,0.0,0.0,0.0,BEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +434,0.0,160.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +435,0.0,0.0,1.0,0.0,42.0,42.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +436,0.0,0.0,55.0,0.0,55.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +437,0.0,0.0,0.0,1.0,0.0,73.0,0.0,73.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +438,79.0,0.0,0.0,0.0,78.0,0.0,0.0,0.0,AAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +439,0.0,0.0,67.0,0.0,0.0,0.0,66.0,1.0,HCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +440,0.0,0.0,77.0,0.0,0.0,1.0,0.0,76.0,FCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +441,0.0,0.0,0.0,0.0,153.0,0.0,0.0,1.0,HEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +442,0.0,88.0,88.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +443,0.0,0.0,0.0,20.0,22.0,0.0,0.0,0.0,EEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +444,41.0,0.0,42.0,0.0,0.0,0.0,1.0,0.0,GCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +445,0.0,0.0,0.0,47.0,0.0,46.0,0.0,1.0,HDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +446,1.0,0.0,0.0,0.0,86.0,0.0,0.0,87.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +447,56.0,56.0,0.0,0.0,0.0,0.0,0.0,1.0,HABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +448,0.0,0.0,0.0,0.0,11.0,0.0,0.0,10.0,EEHEHEHEHEHEHEHEHEHEH,True +449,0.0,0.0,0.0,0.0,0.0,1.0,92.0,92.0,FGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +450,0.0,0.0,0.0,6.0,5.0,1.0,0.0,0.0,FDEDEDEDEDED,True +451,66.0,1.0,67.0,0.0,0.0,0.0,0.0,0.0,BCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +452,0.0,0.0,0.0,13.0,0.0,1.0,12.0,0.0,FDGDGDGDGDGDGDGDGDGDGDGDGD,True +453,1.0,0.0,0.0,0.0,56.0,0.0,56.0,0.0,AEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +454,15.0,0.0,0.0,0.0,0.0,0.0,0.0,16.0,HAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +455,0.0,21.0,1.0,0.0,21.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True +456,93.0,0.0,1.0,0.0,92.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +457,1.0,0.0,0.0,0.0,35.0,0.0,0.0,35.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +458,13.0,0.0,0.0,0.0,1.0,0.0,13.0,0.0,EAGAGAGAGAGAGAGAGAGAGAGAGAG,True +459,0.0,0.0,65.0,0.0,1.0,0.0,65.0,0.0,ECGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +460,0.0,0.0,95.0,1.0,0.0,95.0,0.0,0.0,DFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +461,15.0,0.0,0.0,0.0,1.0,0.0,0.0,15.0,EHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +462,0.0,0.0,198.0,0.0,1.0,0.0,0.0,0.0,ECCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +463,84.0,84.0,0.0,0.0,1.0,0.0,0.0,0.0,EABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +464,0.0,0.0,0.0,0.0,0.0,60.0,0.0,61.0,HFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +465,0.0,179.0,0.0,1.0,0.0,0.0,0.0,0.0,DBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +466,1.0,0.0,90.0,0.0,89.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +467,0.0,35.0,0.0,0.0,0.0,34.0,0.0,0.0,BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +468,0.0,0.0,0.0,1.0,7.0,0.0,0.0,7.0,DHEHEHEHEHEHEHE,True +469,0.0,0.0,0.0,0.0,92.0,0.0,91.0,0.0,EEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +470,0.0,0.0,46.0,0.0,0.0,1.0,46.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +471,0.0,0.0,0.0,0.0,0.0,1.0,158.0,0.0,FGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +472,1.0,0.0,0.0,0.0,0.0,58.0,0.0,59.0,AHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +473,0.0,0.0,6.0,1.0,0.0,0.0,6.0,0.0,DCGCGCGCGCGCG,True +474,0.0,0.0,0.0,0.0,0.0,98.0,0.0,97.0,FFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +475,0.0,87.0,0.0,0.0,0.0,0.0,0.0,85.0,BBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +476,0.0,0.0,33.0,0.0,0.0,0.0,1.0,33.0,GHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +477,45.0,0.0,0.0,0.0,46.0,0.0,0.0,0.0,EAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +478,0.0,0.0,0.0,77.0,0.0,0.0,75.0,0.0,DDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +479,73.0,1.0,73.0,0.0,0.0,0.0,0.0,0.0,BACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +480,0.0,1.0,0.0,0.0,37.0,37.0,0.0,0.0,BEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +481,0.0,92.0,93.0,0.0,0.0,1.0,0.0,0.0,FCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +482,0.0,0.0,0.0,1.0,0.0,0.0,0.0,24.0,DHHHHHHHHHHHHHHHHHHHHHHHH,True +483,25.0,0.0,0.0,1.0,0.0,25.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +484,0.0,0.0,0.0,0.0,0.0,37.0,0.0,36.0,FHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +485,21.0,0.0,0.0,1.0,0.0,20.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +486,0.0,35.0,0.0,36.0,0.0,0.0,0.0,1.0,HDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +487,0.0,0.0,1.0,0.0,97.0,98.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +488,0.0,93.0,0.0,0.0,0.0,1.0,0.0,94.0,FHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +489,0.0,1.0,0.0,93.0,0.0,0.0,93.0,0.0,BGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +490,0.0,0.0,0.0,70.0,0.0,0.0,72.0,0.0,GGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +491,86.0,0.0,0.0,0.0,1.0,86.0,0.0,0.0,EFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +492,0.0,65.0,1.0,0.0,0.0,65.0,0.0,0.0,CBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +493,0.0,0.0,0.0,69.0,0.0,0.0,0.0,1.0,HDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +494,0.0,0.0,144.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +495,0.0,45.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True 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+599,16.0,0.0,16.0,0.0,0.0,0.0,0.0,0.0,ACACACACACACACACACACACACACACACAC,True +600,0.0,21.0,0.0,22.0,0.0,0.0,0.0,0.0,DBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +601,70.0,71.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +602,0.0,0.0,0.0,1.0,0.0,0.0,53.0,0.0,DGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +603,45.0,0.0,0.0,0.0,0.0,45.0,0.0,0.0,FAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +604,0.0,1.0,56.0,0.0,0.0,0.0,56.0,0.0,BGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +605,0.0,1.0,0.0,0.0,0.0,0.0,0.0,195.0,BHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True 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+611,0.0,0.0,86.0,0.0,88.0,0.0,0.0,0.0,EECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +612,1.0,0.0,0.0,0.0,14.0,0.0,0.0,14.0,AEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +613,0.0,0.0,35.0,0.0,0.0,35.0,1.0,0.0,GCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCF,True +614,0.0,0.0,1.0,0.0,43.0,43.0,0.0,0.0,CEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +615,0.0,0.0,0.0,0.0,0.0,1.0,67.0,66.0,FGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +616,0.0,27.0,0.0,0.0,26.0,0.0,1.0,0.0,GBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +617,0.0,88.0,1.0,87.0,0.0,0.0,0.0,0.0,CBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +618,0.0,41.0,0.0,0.0,0.0,41.0,1.0,0.0,GFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +619,0.0,27.0,27.0,0.0,0.0,0.0,0.0,0.0,CBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +620,1.0,0.0,20.0,20.0,0.0,0.0,0.0,0.0,ADCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +621,0.0,0.0,1.0,24.0,24.0,0.0,0.0,0.0,CEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +622,1.0,0.0,0.0,0.0,55.0,55.0,0.0,0.0,AEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +623,1.0,0.0,0.0,0.0,26.0,0.0,26.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +624,0.0,0.0,15.0,0.0,0.0,0.0,0.0,13.0,CCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +625,0.0,0.0,1.0,67.0,67.0,0.0,0.0,0.0,CDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +626,0.0,0.0,65.0,0.0,0.0,1.0,0.0,64.0,FCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +627,0.0,0.0,0.0,0.0,89.0,1.0,90.0,0.0,FGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +628,0.0,0.0,0.0,0.0,1.0,0.0,51.0,0.0,EGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +629,0.0,0.0,41.0,0.0,0.0,40.0,0.0,0.0,CFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +630,0.0,0.0,93.0,0.0,0.0,0.0,1.0,0.0,GCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +631,0.0,53.0,1.0,0.0,0.0,53.0,0.0,0.0,CBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +632,0.0,0.0,0.0,14.0,0.0,0.0,0.0,15.0,HHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +633,0.0,29.0,0.0,0.0,0.0,0.0,28.0,0.0,BGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +634,0.0,66.0,0.0,0.0,0.0,1.0,66.0,0.0,FGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +635,0.0,0.0,62.0,62.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +636,0.0,31.0,32.0,0.0,1.0,0.0,0.0,0.0,ECBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +637,0.0,0.0,0.0,0.0,0.0,0.0,48.0,49.0,HGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +638,1.0,0.0,0.0,0.0,0.0,0.0,54.0,53.0,AGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +639,59.0,0.0,1.0,0.0,59.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +640,0.0,0.0,0.0,0.0,1.0,0.0,27.0,27.0,EGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +641,0.0,0.0,0.0,23.0,24.0,0.0,0.0,0.0,EDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +642,0.0,0.0,0.0,91.0,0.0,0.0,91.0,0.0,DGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +643,0.0,0.0,0.0,0.0,48.0,49.0,0.0,1.0,HFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +644,14.0,0.0,0.0,0.0,0.0,14.0,1.0,0.0,GAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +645,0.0,96.0,0.0,0.0,1.0,0.0,0.0,96.0,EHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +646,0.0,0.0,0.0,50.0,48.0,0.0,0.0,0.0,DDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +647,0.0,0.0,0.0,99.0,0.0,99.0,0.0,0.0,FDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +648,49.0,0.0,1.0,0.0,0.0,0.0,0.0,48.0,CAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +649,0.0,0.0,52.0,0.0,1.0,0.0,53.0,0.0,EGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True 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+667,1.0,147.0,0.0,0.0,0.0,0.0,0.0,0.0,ABBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +668,0.0,0.0,97.0,0.0,97.0,0.0,0.0,1.0,HCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +669,0.0,0.0,1.0,0.0,0.0,0.0,53.0,52.0,CGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +670,0.0,0.0,94.0,0.0,96.0,0.0,0.0,0.0,EECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +671,99.0,0.0,1.0,0.0,98.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +672,68.0,0.0,0.0,0.0,0.0,0.0,67.0,1.0,HAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGA,True +673,0.0,0.0,0.0,26.0,27.0,0.0,1.0,0.0,GEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +674,31.0,0.0,0.0,0.0,32.0,0.0,0.0,1.0,HEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +675,0.0,0.0,0.0,0.0,42.0,0.0,41.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +676,0.0,0.0,50.0,0.0,0.0,0.0,1.0,50.0,GCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +677,0.0,25.0,0.0,24.0,0.0,0.0,0.0,0.0,BBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +678,0.0,0.0,0.0,0.0,1.0,10.0,9.0,0.0,EFGFGFGFGFGFGFGFGFGF,True +679,65.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,DAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +680,0.0,23.0,0.0,0.0,0.0,0.0,23.0,1.0,HGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +681,0.0,1.0,58.0,0.0,0.0,0.0,57.0,0.0,BCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +682,0.0,0.0,0.0,0.0,0.0,68.0,1.0,68.0,GFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +683,0.0,0.0,0.0,0.0,96.0,0.0,96.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +684,1.0,0.0,0.0,0.0,66.0,0.0,66.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +685,0.0,0.0,0.0,0.0,0.0,1.0,0.0,21.0,FHHHHHHHHHHHHHHHHHHHHH,True +686,0.0,88.0,0.0,87.0,0.0,0.0,0.0,0.0,BDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +687,0.0,0.0,19.0,19.0,0.0,0.0,1.0,0.0,GDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +688,0.0,42.0,1.0,0.0,41.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +689,0.0,0.0,0.0,0.0,0.0,60.0,61.0,0.0,GGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +690,0.0,23.0,23.0,0.0,0.0,0.0,1.0,0.0,GBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +691,86.0,86.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +692,35.0,35.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +693,57.0,0.0,0.0,0.0,0.0,58.0,1.0,0.0,GFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +694,0.0,0.0,30.0,30.0,1.0,0.0,0.0,0.0,EDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +695,19.0,18.0,0.0,1.0,0.0,0.0,0.0,0.0,DABABABABABABABABABABABABABABABABABABA,True +696,0.0,0.0,0.0,1.0,0.0,56.0,0.0,57.0,DHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +697,10.0,0.0,1.0,0.0,0.0,0.0,0.0,11.0,CHAHAHAHAHAHAHAHAHAHAH,True +698,0.0,0.0,89.0,0.0,88.0,0.0,1.0,0.0,GCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +699,0.0,0.0,87.0,0.0,86.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +700,17.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAA,True +701,0.0,0.0,66.0,65.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +702,0.0,0.0,1.0,0.0,0.0,0.0,123.0,0.0,CGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +703,0.0,118.0,0.0,0.0,1.0,0.0,0.0,0.0,EBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +704,0.0,0.0,0.0,0.0,0.0,0.0,0.0,132.0,HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +705,0.0,0.0,0.0,0.0,0.0,23.0,1.0,23.0,GHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +706,0.0,0.0,0.0,0.0,6.0,5.0,0.0,0.0,EFEFEFEFEFE,True +707,18.0,0.0,0.0,16.0,0.0,0.0,0.0,0.0,AADADADADADADADADADADADADADADADADA,True +708,0.0,72.0,0.0,0.0,0.0,71.0,0.0,1.0,HBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +709,0.0,0.0,54.0,0.0,0.0,1.0,0.0,55.0,FHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +710,0.0,1.0,87.0,0.0,87.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +711,0.0,0.0,1.0,63.0,0.0,0.0,0.0,64.0,CHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +712,78.0,0.0,78.0,0.0,0.0,1.0,0.0,0.0,FCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +713,0.0,80.0,0.0,0.0,0.0,81.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +714,0.0,1.0,0.0,0.0,0.0,0.0,40.0,39.0,BGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +715,0.0,0.0,7.0,0.0,6.0,0.0,0.0,0.0,CCECECECECECE,True +716,35.0,0.0,0.0,0.0,0.0,0.0,0.0,33.0,AAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +717,0.0,0.0,0.0,1.0,73.0,0.0,0.0,72.0,DEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +718,0.0,0.0,90.0,0.0,0.0,1.0,89.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +719,1.0,0.0,0.0,67.0,0.0,0.0,0.0,66.0,ADHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +720,56.0,0.0,0.0,0.0,56.0,0.0,1.0,0.0,GAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +721,0.0,0.0,0.0,1.0,0.0,0.0,49.0,49.0,DHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +722,0.0,0.0,0.0,117.0,0.0,1.0,0.0,0.0,FDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +723,0.0,0.0,86.0,1.0,0.0,0.0,85.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +724,0.0,0.0,31.0,0.0,0.0,0.0,0.0,30.0,CCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +725,1.0,0.0,0.0,0.0,98.0,0.0,98.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +726,1.0,84.0,84.0,0.0,0.0,0.0,0.0,0.0,ACBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +727,0.0,56.0,56.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +728,0.0,1.0,0.0,24.0,24.0,0.0,0.0,0.0,BDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +729,37.0,0.0,0.0,0.0,0.0,37.0,0.0,0.0,FAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +730,0.0,0.0,91.0,0.0,0.0,0.0,91.0,0.0,GCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True 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+772,0.0,68.0,0.0,0.0,0.0,0.0,0.0,67.0,BBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +773,60.0,1.0,0.0,0.0,0.0,61.0,0.0,0.0,BFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +774,0.0,1.0,0.0,57.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +775,0.0,78.0,0.0,0.0,1.0,0.0,0.0,0.0,EBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +776,1.0,0.0,0.0,0.0,0.0,96.0,96.0,0.0,AGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +777,43.0,0.0,0.0,0.0,0.0,1.0,44.0,0.0,FGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True 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+989,93.0,0.0,92.0,0.0,0.0,0.0,0.0,1.0,HACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +990,0.0,1.0,0.0,0.0,60.0,0.0,0.0,61.0,BHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +991,0.0,1.0,0.0,0.0,0.0,0.0,32.0,32.0,BHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +992,0.0,0.0,34.0,35.0,0.0,0.0,1.0,0.0,GDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +993,0.0,0.0,0.0,0.0,54.0,0.0,54.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +994,0.0,0.0,0.0,1.0,0.0,39.0,0.0,38.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +995,0.0,0.0,0.0,0.0,99.0,98.0,0.0,1.0,HEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +996,86.0,1.0,0.0,0.0,0.0,86.0,0.0,0.0,BFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +997,0.0,76.0,77.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +998,0.0,0.0,19.0,0.0,0.0,0.0,0.0,1.0,HCCCCCCCCCCCCCCCCCCC,True +999,0.0,0.0,37.0,1.0,0.0,0.0,38.0,0.0,DGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True diff --git a/tests/results/nb_gm_001_3back.csv b/tests/results/nb_gm_001_3back.csv new file mode 100644 index 0000000..b2f89a4 --- /dev/null +++ b/tests/results/nb_gm_001_3back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,0.0,65.0,132.0,0.0,0.0,0.0,0.0,1.0,HCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCC,True +1,51.0,0.0,52.0,52.0,0.0,0.0,0.0,1.0,HCDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACD,True +2,0.0,61.0,0.0,62.0,0.0,0.0,61.0,1.0,HDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGD,True +3,40.0,0.0,0.0,1.0,0.0,0.0,0.0,80.0,DHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHA,True +4,4.0,0.0,1.0,0.0,0.0,6.0,0.0,0.0,CAFFAFFAFFA,True 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+401,0.0,55.0,55.0,0.0,0.0,1.0,54.0,0.0,FCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCB,True +402,47.0,0.0,0.0,0.0,1.0,47.0,0.0,47.0,EAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFH,True +403,56.0,0.0,0.0,0.0,58.0,0.0,0.0,56.0,EEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAE,True +404,0.0,39.0,0.0,0.0,39.0,1.0,40.0,0.0,FGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEG,True 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+3,12.0,15.0,11.0,20.0,13.0,17.0,17.0,22.0,AFAHGHGHGBEBCDDDDHHHABCEHEHEBBBAHADADCFHHHHHFEFCBDDFDGDEFCAGGFEFBDGEHECCBCFFFFFFHGEBBHHCBCACHHDDBFGGGGEGEAFDGDADGDGDGBEBAAHDDFH,False +4,4.0,4.0,8.0,8.0,5.0,7.0,4.0,2.0,FGDGECDCECGCDADAHFDFCFCGAFCDDDABEBHBEFEFBC,False +5,15.0,15.0,15.0,16.0,16.0,14.0,9.0,13.0,HGDGBFDHDADHBBBBBHBAAGBCEABCGFAFAFBGBCBFGDDDEAAAHDFACECECHFHFHFCFHEGEFEFDFDAAHDEECDABFCCCCGBEBDAHCECHCHEDEDEDAGEE,False +6,17.0,17.0,9.0,6.0,15.0,13.0,15.0,12.0,BEBEBHAGCFEHHABAHDEDGHFBFGFCAABAGFFFAFGECEBEAEAFBFCEBEGHGDBEFABABEGEHEHBGBGDADACAGHGHGBGBACGCAHFFBHAECDC,False +7,12.0,7.0,7.0,6.0,9.0,8.0,5.0,6.0,CEGBFEFEFEHCCDEBCCHBBBGAHACBGGDBDADACADHDHFEAEAEFGFAAEAHAFAF,False +8,9.0,13.0,10.0,11.0,12.0,15.0,11.0,12.0,CGCFDBDFHHEHFFGCDHEHCFCFAAEGDCEGHGCFCBBBCBGFGHGDFDBDADHBBEGAGABABHBEBEHGHADAFEFCFDBDEFEHEFEFA,False +9,13.0,26.0,23.0,14.0,20.0,18.0,19.0,27.0,HECEBEFFHFDCCFGBCBDBAHGHGCBBABHEFAFEBEBHBHGGCHBGGCCCCCFCBDDDEDHDEEEAAFAFGFDFCGBGHEHDHGHAFABCGGEHEHFBGBADEBEBEAAHBDCCFGGHHHBHBHGHBDBEEAEGCGCBCHCEFFFFCHDHCHDHABCB,False +10,14.0,18.0,15.0,13.0,15.0,19.0,18.0,11.0,AFACABDDFBBBEBECECGHFBFBECDCEEEDGDBHHGCBDDAFCBAAAGHCHCHEAFBFDHAHCFFAAAHBBBFBFBHGFBCBCFGGGHGDGDFEGEFCFEDGDGAGEGCGEGEFEFAFDGC,False +11,21.0,20.0,21.0,13.0,15.0,26.0,21.0,21.0,EECEFFHGCADHGEGEABCCFDEBABEBGGCACHFHFBFBFBAHGBGCGHDCDABHHAGABFHEBCFEGDFDFDFAFBCBCAHACFGFBFBFBFBDACCBCHFHEGEDFDFCAAAGGEBFAAACACHCHFGFBFGHGHAEAGCCEDDFHHHGHGHGDE,False +12,17.0,26.0,17.0,23.0,17.0,11.0,26.0,21.0,ABGCACGDDFHFHBCEHEAGBGBEBAHEBEBFAAHAFBCEGDGBAHGGGGFGDDDBABABHGGGCGDGHGHDACAEDEFECHGEGDABGCHCDDDDCBCBADAHCHGBGBGEHDCDBBFBABHBHBFBACHDEEHGHECDCDHDEFEDECFGHGBFBD,False +13,24.0,21.0,23.0,20.0,15.0,14.0,30.0,24.0,AHHHHAFEDHAFBFGFCFGADADCDGBBBBGDGEGBCBHGGGGCGFBFAGGGGHEEFEGHGHABCBFHGAGACBBDEDHDHDGBCACAHGCACEHECACHBHDCGCECADGDGDABADHFGCGAGAHHBGFDCHBHCAAABEEFDFDBDBEADAHGEGEHECCCBCFCAHD,False +14,1.0,0.0,2.0,1.0,1.0,1.0,2.0,2.0,DECGCGAHFH,True +15,7.0,7.0,10.0,5.0,8.0,4.0,8.0,9.0,HBABHHEEGAGAGEGHCDEECHCHGBCBCDDAEGCBCGEAEFDFBFBFAGCHCHCHAD,False +16,14.0,19.0,14.0,7.0,10.0,15.0,19.0,7.0,CEAFFGHGEGFDFDCACAGBDEAFCEDDFAHHFDFGBEACGCGBGAFECECFGHCEBAFGEGCBABEBHBHBACAGAGDGHBABCBCBGFGFGFGBBBBFBCBGA,False +17,17.0,15.0,14.0,12.0,10.0,9.0,17.0,6.0,EBACADACGBGBAFGHGHADCDGAAFFFADABAHGDGABBCBCACACECHFBFHDCACDGEBADDEGGGEDADFGFGCGFBBABCBEBDBCHGEGEGECE,False +18,14.0,22.0,17.0,9.0,14.0,10.0,25.0,20.0,EHCHAHEHAHCHCGBGCGCGAEBFBFGGCEFGBGHAHCBABABHHGHGCACHDEDBBABGGDGDEBBBHHGCAEGBFHGEGEGBCCGCDFBBGBFBDAEEHHHCFEFECEHGCGCBHDADFDAGAGAGFBB,False +19,13.0,27.0,12.0,18.0,19.0,17.0,20.0,18.0,BFGCGBHAHAHEFEDBABEBEDADGGGGBAFCGEBDFHBHGHGCBBEGEGBHDHDHBCBCACDBFHHCHBGAGAGEDADADCDCACGHEEEEBDFDFDHDCGGBGDEBBBABEHFHGEFFFBADHEFFCFDEBEBFFEBHBFBG,False +20,11.0,10.0,7.0,8.0,8.0,7.0,11.0,4.0,BGBABGHGCGFBFAEBGGEDEFAHEHACDCDADBGGAGAGADFBFBCBCEFBFDHDACCDAGAEEE,False +21,22.0,20.0,18.0,24.0,13.0,11.0,16.0,21.0,DADADHCACFCHEDAAAHGDDHAGCDEDEGBHAHBDBDBGHHHCHCECAAAEFEDECEDBHFABGBCAGDBEGEBABHFCBBABDFDGHGCBFBCCDHDHDGDHDHCHBGADAFACHEHBDCDAFAFAFAGGCGCFHGBDBEBEG,False +22,8.0,10.0,11.0,7.0,8.0,15.0,4.0,11.0,CBAEGDGEHEBGBFBFBDHCHFHBAEHFFGFCFBFCFEEHABECFFFFACAEHHDCDCDHDHAHCFCBCBAADF,False +23,32.0,19.0,21.0,23.0,13.0,27.0,21.0,27.0,GHCABDGDFFFAHHHEAEHGAGAGHEFEGBCFAFBFGCHCHFHBGCAFFDFDBACACHCHCHBFGFEACAFABEBEBHHGHFHAHGGAGAHAFCGDHDHAFGCBCHDAAAAAAFCFHGEFFBEBEDDDFDBCBDDDCGFAFADBDBEBCAGGHDFDFBCDEAGAHCCEHGHAHCDDDDABAFA,False +24,26.0,30.0,18.0,21.0,29.0,16.0,21.0,21.0,GDGDADAGAGDEHCDBDHAHEHFHAHAFBHBHGCEBHBDBHBHBEEABABABAEECEGEGAGADHDBEEGBCAADHGBFBCEAAHDEBEBFBFBFCCGCEFBABAEDBGFGBGCFCGEACDFEFBHDADFHCEAEBDHDCGBEFGCDCACDEBEGAGAEAEFDFBBEHEGEGHCACEFBHDH,False +25,17.0,15.0,10.0,21.0,16.0,11.0,16.0,22.0,BDBDBHHHAAGAEHEHCHCDADEBGHDAGEBHGAABADADEDECEHAHFBGCGBEHCGADFBHECGHHFFFHFBDDDDDFDFDFHFEDEDACAEAEBDCHHBFBABCBGDGEAECHHGHGEGHDAGGG,False +26,12.0,13.0,16.0,11.0,17.0,10.0,17.0,12.0,GEECBGFEEDHCEFGFEAEAHGEGEDDDHDCDCBHBCBCFCECEGAGAGAHECFCEAAFGFGCEHGHBBBGBGBCBDHEAEFHFHGBCDGGACHCGCDADAEBFBADH,False +27,14.0,11.0,17.0,13.0,14.0,21.0,16.0,19.0,AAECGGEGHCACACACHBHADCECBDHDHDFCFGHGDDEDHHHAHDFDACHBHAFBHHAEEECGGFGEGEBEFCFAEAEFFBFBFDGDGDGHFACCDFHFCGBBHBCGGFGEHEFFFFHFCBCAF,False +28,14.0,15.0,12.0,21.0,15.0,9.0,13.0,21.0,GGHGEDHFCFCACBCADAEEEEAHDGAGHGHEHEHBBECEDBBBDBEGDGBAEABCCABBECDDDFDFHGHGHDHGHGHDADHHCHBHCCBAFHFDDDEDHFHAABDFDFEGEAADBDCH,False +29,18.0,19.0,27.0,26.0,29.0,30.0,16.0,16.0,DEFFFAFAGDGEEBFBFGEBADACADFDCEEDEDFDCDEBBGDGHGHGFFFDFBEBEHCHFDCDCEGFGFHFEFCGBBDCHCGCDADEGEGCFAAEHEHFDACGCEABBDECBCBCEFEFBFCFCFEHEHDGACEBAGCEFEBACCCAEDHDHBCFCDEFFHDHDHDCFCAAAEBEBFDHA,False +30,5.0,11.0,5.0,8.0,3.0,2.0,5.0,1.0,BBFGGBABFGCCCDADAHBEDCDBABGEAECBDBDBDBDG,True +31,28.0,17.0,19.0,16.0,18.0,11.0,17.0,33.0,DHAFAHAEAHDHFHFAFADHCGGGDGDGHEBDHCHBHAEBCBCFEGHHHBHCAFDHEHEHCDAGBCBAAAGACCBCAFGBHEHBBEAHAHAFAEACGGEHAFABEDEDFDCGHEBGAGEEAEBBHDEDECHCGABHGHAHAHBHCHCHCHDGACACDFD,False +32,5.0,10.0,12.0,17.0,19.0,17.0,17.0,11.0,EEBHBFFFDDEDCCAGEFEGGDGDFFGEGEAEDEFCFCGCGCGFAEGECDHHCEFDDHDFDABFDECECEHEFDDGDGBBFBFHHGCECEFEHAHDHDGBBFBGHGBG,False +33,4.0,13.0,10.0,7.0,4.0,8.0,11.0,7.0,CGBHBCBCBHFHFECBADGBGBGBDBCFAGDBHGFGECEHBGBCCACFGFGFGDDDFCADHEHB,False +34,22.0,27.0,22.0,21.0,21.0,28.0,21.0,21.0,BABFBCCCCGCDCAGABAHFBAHCBDBDHDCDCDEFFHBHBCBCBEHDAGAEFBBEEEBEGAGHGDGCGEBFBDEAECCFCFGDGDGHBHAEFFFECCADHFFBGHDHEGAAEDEFEFCDCDCDEFCHADAEHFDFHBBEBEBFBFAFGFAAHGHGFFAFGGBABGHGBFBFDFHCHAHEGDA,False +35,24.0,23.0,21.0,17.0,28.0,15.0,20.0,21.0,EGHGAGEGCGDFFCEEEEEAHGEGFGFBCBGBDBACHCAGDDDDEDEHACGCECAFAFEFHCHCEFHDHEHBAEADBDBAFCHCEEEEHBHBECEAEAFGGGGCCHBHAAACABBEHFHBDFHHDHBGCAABEBGAGABBFADADEBBBBCDCACFGFHDCEHEBGADE,False +36,16.0,12.0,18.0,16.0,29.0,20.0,25.0,11.0,EEEBCFFDHDBBGHGHGEFDFACCCFCGAECECEAGFFFCFDAHAEEHGGGBGBGADDGDGEGCCBFEHEGEHACDGDGCCCFCEAFAEGEGBGFGBBBHFGDGFGAAHADADCEEEEDEAEFEAEBFFFHEGECEGEHECAFDDDB,False +37,1.0,6.0,2.0,11.0,2.0,11.0,4.0,7.0,DBFFFHHADFFEFBDBFBGDFFEBHBHFHGDGDGCCDDDDHDHF,True +38,11.0,12.0,15.0,5.0,3.0,15.0,15.0,13.0,HCCCCAEBGFCFBGAHHHHBAFGCGCGCGFGCAABFBABHBFBCAFHFAFGCDBGBGAGFCBBAADHDHDCGEGHGCGFFHFHDEFHFC,False +39,33.0,14.0,21.0,23.0,21.0,18.0,25.0,28.0,DHAHAHADGDAFAFGCHCHEHCHABACEDDDCGBHAEFFGCADADGBGCFFFGGHBAAFGGHFHFHECFCHCHBDEFGADDCGGGHEBEDEBEBEDFHCAAAACFGFBFBFADAEGBDCAGACACAFGEEECDDDDCGGGEEEEEGCADHHHHAHABAHGBBCACHEGGHDADADAHAHEHAH,False +40,9.0,21.0,8.0,6.0,13.0,11.0,9.0,15.0,HEBEGEGAGEBBBHFAFABCBCBEBCBEAFHGGGHEHCHBEDFFAFAHDBFBFBEBDFHHDHBHCHBHBDEFABGBCEDEBCACHHEAGBGF,False +41,13.0,18.0,18.0,16.0,8.0,20.0,16.0,13.0,AGDGBCDHFADAGFFFHHCFCFEBGBGFGFGCGCHHHHCGFBFGDHABCBCGDGECEFBFCACBDBDCFAFBDEDCFFBHGHBEBABDFDFDHDHACABDBAFAFDHEGACACBEECGCBDG,False +42,21.0,15.0,14.0,22.0,14.0,22.0,16.0,21.0,ACFDFDEDFDBAFDCDCDFFFFFACHCHGEDFCFEHADACEHEDEBAFAGGHGEDADFDHDHDHGADAGCCCFHBDBGBDEGEBHGFGHAHFBFBFEAABABACDDAHHGFGBGEGHFEABHBFEHHHGDFDCACABABGECHAH,False +43,17.0,19.0,23.0,19.0,19.0,21.0,20.0,22.0,GDGFGEDDDDDDFDFDFEHBHDGAECBHDEGHGEEDEBEDECGGAADAFAFADECFCDGDGFBHGCBHBACAGACFCGGGBGCHFHEHECECAHFHFGCGHBFCGCBCFEHEGEHBBAAABDHFBCCCCFFFHFCABFBHBHBEDAFEHBHACABECHCH,False +44,2.0,1.0,3.0,4.0,5.0,3.0,6.0,5.0,CHCHFGBGEHFDAGADEDEGGFGEDEHCH,True +45,17.0,20.0,26.0,20.0,18.0,24.0,15.0,12.0,BDEFBBBHHECFCFCBBFEDDADADGECEHEFCGCAFDCGCFFEDDGGHHHHHAFAFEFAFDFDFDEDFAACFCFCDCBBBCGCGDGDFCGCGBDCACBHDHEECBBEBECFCHGBGEGABCDCEFHFGACDFAFAECEBEBDACABAGFBA,False +46,5.0,7.0,11.0,5.0,5.0,3.0,8.0,10.0,CBDHFHCDCEGEHCHCHCHEGCGCGBBBBADAHGDGBACGEAHBHFGFCECAHD,False +47,5.0,4.0,4.0,5.0,0.0,1.0,5.0,3.0,ACABGBHBHBGDCACHCDAGFGAGDDD,True +48,21.0,22.0,13.0,24.0,16.0,18.0,24.0,19.0,DBDGAGBGFHFCABGFECEGBGHHEACDFDGCGBEBGDAFAHADADAHHBHBHAGABADEBFDGDBDGDGCFAFAFDDDDECGFEFEAHAHEHEHCBCDADGBFBFAEBCAHFHEDEGBBFDEHEBDHFGCGHGHGBGCDABCBDGHGBGDCEAFAF,False +49,5.0,12.0,11.0,8.0,8.0,7.0,11.0,9.0,FCFDGDHBEBECFBBHFCFCGDBCCCGCECECBDBGBEHDDBCAGAEHEDFDHGEGAHBHGAGAGFHBHBG,False +50,2.0,7.0,7.0,4.0,6.0,13.0,10.0,11.0,BBFEFEFHAHFDFGHEBABDFHBHEFGFGHEHGGGFDFEHCBGBFDFHFHCCGCGHGCCC,True +51,5.0,7.0,11.0,12.0,13.0,9.0,8.0,13.0,EFFBFDAAECCCHDHBHFEDBHBHDHDGGGGECDGHCFEFEDEDCDCDEDCCHFEFEGCGBHEHBHAHAGDFCEAEHB,False +52,15.0,6.0,11.0,6.0,11.0,16.0,3.0,8.0,BAEGCCEAHBFCCHFABEHEFDCHEBECACECEAFGFEFEFBFBFAFADADACACDFGFAFAFEFDAAHFDCAHHH,True +53,20.0,14.0,19.0,11.0,13.0,12.0,10.0,17.0,CHCECEHEGAHBFGHCHABCBCDCECEDAHACGCADDBBGFGFGFHAAACACFBEGGAGAEHCAAAFDFDCHBDBHGDFDHCBEFEBCBABHHHHDHCHDFEFABEBECAAAEACF,False +54,18.0,14.0,15.0,22.0,24.0,20.0,25.0,23.0,EGGCGCGDEDEBCBFDDDBFHDDGFBFEEEGDBDBEHFDFEACACADABEFDCECGGHBDCDBAGHGFBFECHCFEDEHEHAHEEAGCEEEEFGFHFAAGEEHHHHAHAHDEFGDGDBCGAGHFHFHAHAHDHDBFBFCEGGGGGGGHAADAGCDFFAHCB,False +55,3.0,4.0,2.0,5.0,2.0,5.0,3.0,1.0,EHAABABGBFDFGFGEDDFDCBCDF,True +56,9.0,9.0,8.0,11.0,11.0,13.0,8.0,11.0,ECFFFBCDEDAFEBEAFGFHFHFDEHEBEHEGBFEFHBABCCAGAGBGBDFHAHGHFCFDHDABADEDEDAHGGCDCHCD,False +57,10.0,13.0,10.0,15.0,7.0,9.0,16.0,11.0,HHCFEGEGEDFGABEHEADCHGHBDFDGDGHGCGBBDDCDCDBDBHCDEBAHACCFDGDFAFAFDDAGAGHGCGBGBHACBGBGAHEBFBF,False +58,15.0,15.0,14.0,21.0,27.0,24.0,20.0,28.0,FAFEFAADAGFBFACBCBHHCGFGFAFHCEGEGHHBDBFHFHBEGDGDAEEHEGCGDGHCDGDEHFHGCEEEGEGEDBDEEEEHHHHCHDAGFEBHFHAHFHFDDDCACHFBDDHDGDFDAGGEAEFBHEEEEBEHEFFCFCFDBHAFADCGCGFHDHEBABHB,False +59,11.0,16.0,18.0,17.0,22.0,31.0,15.0,17.0,FCECFCFCFBHCHBGBFHGEDADADEFEFHFDFDADEEADHGAEAECGDGCCFHFGFHFHFHFBFBFCEEEBEFFDEGGBHBEBHFCDDDDGHAFBFBFCACHCAFGCGHHEDCBFEFABCDCEGGGDAEBBBEDEFFFFECGHEHF,False +60,11.0,9.0,7.0,2.0,10.0,10.0,11.0,9.0,HGHCDCHCACBCEGEGEGEBBHCFGABEBFAEHHFBFAAGHGHFHABABCGEGFDEAAABFEFEFGFGA,False +61,23.0,23.0,21.0,24.0,24.0,17.0,27.0,24.0,EDGGCBCFCGCGCFCGCDCBAACHFHFHECACAGAHFHDBDEHAGADHGEGEBCAEAGDHAADDDDCEAEADBGFDBBBBDHDGDBBGCAAEHEGDGBGBFHCGCDBBBEFHFDAGHCDCHFHFGEHEGEGHGBEFACADAFCBGBGBFHDEDEDFBFEGHGHAHAEEEEGEDHAHACEFBHB,False +62,21.0,13.0,9.0,12.0,17.0,15.0,25.0,10.0,HFGFGBGEDEHGHAHFHGAAAFGHBFACGDBEBGAAFEGEFEFBGAHDEDECBCBFBEGAGAFCCBBDBAGABAGGGGGECDADAGAEFEDGACADDCDHDEAFHFHFGGGFGCABAEEEGE,False +63,6.0,6.0,3.0,12.0,7.0,8.0,6.0,13.0,FHEBEBHGHDAGHDCDEDEAFCFCHEEBAAFDDDFDHDAGBGFDHGHAHDHEHFHFHBDBG,False +64,6.0,15.0,15.0,8.0,14.0,13.0,8.0,8.0,CCEDEDBHHGDCBEFEFCCGCEAGFGEGECAHAHGBCFHACEBEBEGEFFFFBDBFBHBDDEDCBCBHBFGFHEAEBCBCFCBCAFD,False +65,6.0,4.0,3.0,4.0,6.0,8.0,5.0,5.0,CGCFEFAFAEEDEHCHBBDAAFAGHEHEBFDHDBAGFGFGF,False +66,17.0,8.0,15.0,6.0,16.0,16.0,11.0,12.0,AFGFGFGHGFECECECHAECCCFAHAFAEHGGCEBAFAEAEFGGHCBFAAEHFHFGBHEHGAFBFHCECEADFDBDBCACACAEAEBEDDACBDFHFHEGC,False +67,24.0,12.0,23.0,14.0,18.0,18.0,15.0,12.0,CCCFCFBHAEEDFDBAADAEAEABDBDGEHEGCCCACECHGEGEDECACFCFCHBFBAGAFFGHADBEBAAAAFAEECEDHDHECGGBHHCHDBGBABAGEFFGFAFADACADAGADCHFECGFGFHFCDCEGFCC,False +68,31.0,17.0,27.0,38.0,29.0,28.0,14.0,16.0,ACACBCFDGBHBDEGEAHDDEFEFEFEFDDHECEBDFDAEAEFECECGCHAHAHCBCDAHBDDDDEDEBEHGDDAFEFCFDDBCGAGACCECAADADABAFEDACGCAFAHDFDBDGCECBGBFFCHCGAEDFFFHADFDADGFAFADEDHABAGAGEHEFBFECEDEDCGEADADFDHBHDFDCBCFCDAFAECFCEHB,False +69,5.0,4.0,3.0,4.0,2.0,3.0,6.0,4.0,DAHAGAHAHAHFGCGEBDFDEDGGCFBBGBC,False +70,5.0,7.0,9.0,5.0,2.0,11.0,6.0,10.0,HAHDHDHBGBFCACDCHFBBHBHGDEACACEGFCDHBGFGFGFCCHBFFHFCFAF,True +71,11.0,10.0,6.0,19.0,14.0,23.0,11.0,9.0,FHFEADABECHFFDFDFHFEDECEFEFEFAFHDADAEADDCAGFGBBHGDGABDDFFFFDDDADEEGFGDABCDGGBHDHFGAGBHBHBEBEGFFFFFCCEDE,False +72,25.0,17.0,20.0,19.0,16.0,13.0,17.0,22.0,GDCDHGBEAEGDGEBDBDHDCDCBHDEAEHDCEFAAABCDCDABAGADADCFAFCGCACAFFBAHGCGCGEGEACHHECACECEHEGGFBDHFHAHAHGGDGFCECHFHFHCHFABABFDGABDEDABABHEACAFDHHGHAHBBBBEH,False +73,15.0,19.0,20.0,23.0,23.0,21.0,22.0,23.0,GFGFECGCEEGHFCBCFDDDHHGBGHGHDCDCFHAHCCCFHAADEBEHEDEDADCDCABEGEFDFHCHGGAHAHFCFCEADFFECGBDBDBDCCACADHGCGEGHFHGHGBFADEBEBEDGDBBACEEEHGBDBFFFFDGEGDGDGFBEHHHHAAEAEFBBBBEFH,False +74,3.0,11.0,6.0,11.0,10.0,12.0,5.0,7.0,ECHFHDHEFFHHDCFGEGFDBEBEFFFDBCBFEDCDCFEBBFADDBDBGBGBGBAHAHFDEDECE,True +75,21.0,13.0,22.0,19.0,30.0,19.0,18.0,19.0,HAHEEEFEDHDFDBHBGCCEEFEGGHGHCCCCCHGECEAHDBDBEFGHCACGBEFEHAFDFACAFEEEHABAGAFDGDADADAGBCBAEADAEFHCDCFGEHFHDEDCDFEFCCCEAEAEGGABFGEDBDBHBCCECEHEAEFGHGHDDAEAEHCFGFGFB,False +76,14.0,30.0,18.0,20.0,25.0,19.0,27.0,30.0,FCFBAEDEGEHEBGHGFEFCGDBDGGCGCGBEBHBHEAAAEECBCBCFHFCFDGAEHHFGGGGGHCHEHBABGBGHHDFAEBDBDBDBCCHAGGEGDGCCBCHFGFGHGHBHEFGHBFBCBHEHBBABCBHBCGEHEADDDBHFHAADEDBFHFEEGEDHDHDEDBDFEFEHCHAEGDHBFBA,False +77,25.0,17.0,30.0,29.0,22.0,22.0,23.0,24.0,CCHEAEHBBCBDADBDBDHGFEECBDFGFEAHDCGCDHHEHEHCGCFHGDGAGAGACACDDDFDFDGECCHDHCCEFAFEBAFGGHDCCGEDBDBDBCHCACDBAHCGCGAHAHAFFFHADCDCFCFHHCDCAEAGAGAGABFHGEGBGDFHEBEFCFAGBEEAABAGDGDFDFEABHCDEDEHEHEFCFCD,False +78,9.0,16.0,9.0,5.0,4.0,15.0,4.0,5.0,BCEADCBBBBABABCCEHFBDHFAAGAGHCFCBCBFDFAGAGBFBDBABFFFFFCEHEBDHFFFBFC,True +79,19.0,17.0,10.0,29.0,13.0,8.0,14.0,14.0,DEDEAEAEDDDDDDDHDGEBEFADAGBFFHDGFBBBBGBABFCHGDFDEACBBBAHADAHCGCAHDHEHABAGCGCGEDAGBDAACAHDBCBGBGBEDDDDDADGDFDHHFDAHAEEEHCDCHG,False +80,9.0,11.0,7.0,9.0,14.0,3.0,11.0,16.0,HEHEACBHBHAGEBEAEBHBHBDEDCFABCGAEABHEHDADABABGGGDGHECEHHDGDHHCHCDGFFHCBEDEGEGHGE,False +81,4.0,9.0,4.0,9.0,3.0,6.0,6.0,5.0,BGBACACHDGDFDFBFEAHFBDDEDEGHGHBBBFBADHDGCGDBFC,False +82,11.0,21.0,22.0,24.0,26.0,28.0,21.0,21.0,EDGDCDCFGEDEFFFFGEEEDEDEDADACHCEBAFAFCHEDBFEDHDCCAHGFDFDGAGEFECEDBHCECDGGGGGBGFGBHCGDGFFDCAGDBCEHEGBBBBHFHADFHCHCHCACHCBBEFAGBGBEBFFFHFBCEDFFEFHDHFHFCCECBHBDBDEDEHBHEHFBFEGAG,False +83,2.0,4.0,1.0,3.0,2.0,4.0,2.0,1.0,CBFHFBBDGDFDFEGEABA,True +84,18.0,13.0,21.0,13.0,16.0,19.0,15.0,8.0,CBCEEADAFGDCFHFHDHFACACEDGACFGGGCBABDCCCCCCBABABABDBDFACGCGCFCAGEFEFBDBCFEFEAGFDBEFEHEHBAEADAFAFGEGECAHFEDGDHHCAEDEFCFGGGBF,False +85,14.0,12.0,10.0,10.0,16.0,19.0,9.0,12.0,FGBGHDEEEGBFAEAEDHGHGFEDEFEGEDEFEFCBAHCHCFBFDGECFFFGAECBBBDGFAFACACBEDABEBFHFHFHAHAHFEDCDCFCAAHBHADAFB,False +86,14.0,13.0,10.0,16.0,18.0,7.0,14.0,15.0,GGGGHADGCGCEEEDEDBAAGBCDAEABAGAFFFDBEFEAHAHBDBDBDBGHAACDHHGHGHDHEFBCDCHCHDEEBEBDADABEFECCGHGHFHDGEEEADBEEHC,False +87,9.0,13.0,17.0,12.0,12.0,23.0,13.0,12.0,EHCHBDDCECFCFCFABABGBFDFDCDHBGDHDGBGCGCGCFCDHEHEFCHGEAFBFBFDFHCEBAFEDEDFFGHCFGBGFGCDCEBGFHFAFBEEEBGFFCFAACAHAHF,False +88,6.0,3.0,0.0,1.0,3.0,3.0,5.0,4.0,GBGAGBHAGAGFEBEFEHHAHAFAD,True +89,11.0,11.0,12.0,15.0,16.0,12.0,7.0,10.0,BHBHDDADCGCAEHHDCEAFAFBFCDEDECBGFCECHAHGCAEDDBDEAFAFHFDCHEBEGEGADBDBHEHDFGFGFDECECECAAEBEBDBFF,False +90,18.0,21.0,18.0,8.0,15.0,18.0,18.0,10.0,BCBDGCBCHGHAAFAFEFAFDFHGGGCCECEHBHFCADAFAFEGBAAAGAFBEBEBEGCBHBFADAECDGHGBGECCBCBABHFFDCEFEHGBGBGBEFGABCBFBDBEEAHACGCGEGFCFCFDA,False +91,21.0,22.0,23.0,29.0,25.0,21.0,20.0,16.0,EDECECBBDBGGGDHDFCFDFAFGBACHDHDADFDHBEAACACACEDECEDGDGEGEGEDEAFCFEGGBEBGFGEDECGFAFAFGHEDFHFCFBFBDEDFDGBHEADHDCCFBABABACGEHAHFHCEGEGHBHDACADFCCHBHDCDCFBHAGDBABEBFBGCDBEBCDDADAEEC,False +92,22.0,26.0,23.0,24.0,20.0,30.0,22.0,18.0,ADAFEGHDHFFFFDFECADDDFHBHDCBFAHCHCACHEGFBFBCDHEFEGABAFAEBGBFFFBFCFGBHBEBAACAHAEDEDEGCDCDCDCGHACFCFHFHGCFCEHEHCGCDCEFGDGBGBGEGBABGBGCCABBBDBAFGDABFBFEFEDADBFEFDBHGHDFEFECBAGGCGADDDGBHAEA,False +93,2.0,2.0,1.0,3.0,0.0,2.0,1.0,2.0,DBDCDGFFAHAHB,True +94,18.0,8.0,12.0,13.0,10.0,9.0,12.0,11.0,HHFAEHCHCHCDDAFACACACGGFEFGCHDEEGCGCGFDDADGDFDEBHCDABGBABDGAGEEBAFABGBDAHAFAFADADEHHCHCBGEAEA,False +95,4.0,5.0,6.0,3.0,5.0,4.0,4.0,3.0,AHBFEADADAGFHFGGCBCBCBCFCEHEBDCEEG,False +96,6.0,10.0,15.0,4.0,14.0,9.0,14.0,11.0,ECECEGHGHEHGDACGHHHFGFGCCCGFEEHEAAACCHCFCFEGEDHFHFDFGEABBBBEBHGCGBEBGCACBEBEGCCDBFG,False +97,3.0,4.0,3.0,4.0,3.0,2.0,2.0,6.0,BGHFHDHDCDBDECAHAHAEGBFBHCE,False +98,14.0,9.0,9.0,12.0,16.0,15.0,11.0,5.0,BGGACFEGEGEAFGFGFGFAADADACBCFDADGEBHBFDFGBBDCGAFAEEFECHCDCBFEAEAEADADCEBDDHDBGEFCHEHEFEAEFF,False +99,24.0,22.0,16.0,19.0,18.0,22.0,22.0,17.0,BABDFDEDEDEHAACABAEAFFGBHFGAHDBCAGADEDCHBBGEGAGAGAGAGFGABEDEDEFCBABDBECECEAGFGEGBGACBFEHEHAHAFBFBCHEFGDADAEEBCBHHHFHFBAGGGFFFFGHDCCHAHBCBCHFGDBCCAFBDGGFDHDFDFDC,False +100,10.0,7.0,6.0,7.0,6.0,11.0,8.0,15.0,GGHGHGFEFDCHAHFHEHEBACCBCHFHFBCBEBFFEFHAHGHDAGADAEGBGHHBAAADCFHFDADFDH,False +101,21.0,23.0,9.0,23.0,25.0,21.0,22.0,21.0,EEEEEACAHEHDDADHFBFBAHGHGBGDGFECGBBBBFBFEFHFGFGFAEHDHAHAHBHGHFBBHGGGGGEHDDDDHEAFBHHDEFEHEDDGBCDCHBGDDFFCAHADEDEGEGEAABBEBDFGEBABCDFEACFDADAGAGEGBAFABHBDGDCEEEAFAFBFC,False +102,1.0,8.0,5.0,3.0,5.0,5.0,6.0,8.0,HCGCHDEBGFEFECBBBFBFGHGHGDGBAHCFCHHHEDEBB,False +103,29.0,22.0,27.0,17.0,23.0,16.0,31.0,26.0,GGHCFGEBEDGCCDEBFFFEFHGCDCBCBCECFCHCHCHGHCEGAGCECABHEEEBEBEGAGBBBABABFBHBHDHGGDADCCFAFEDECEABGBFAFHDAGHGHADEFGBDCHHDEDCHGABABFGDEAAAEBGAAEGGGGFGHAHDBDCCHGHBDGEGHGEAEACCHCACAHGHGHAHDCACAFAGAFA,False +104,7.0,6.0,18.0,7.0,11.0,12.0,24.0,18.0,GDGEHCGGGEFECEBECGCGHGCFHFHFHCDFDFGACHHHGBGHACDCGAGADBCAHECACGHGHBBCFGHEDEFEHGHBHGGCGCGCHCEGGDGEAFFHFCF,True +105,16.0,23.0,21.0,18.0,22.0,17.0,10.0,18.0,ACEGEHEHAFACDCDCHFBFBGBHDFFFCAGHBBBHBHFABABABAHEGCAEEEFGBGBADGEBCDEHEBCFCHBHEFEBDDDDDDDGFEDEFEHAHBCACACBDBDHDCBCEDEHEGCCFEEEDHHAABCFCHAECBCBFFCFG,False +106,9.0,10.0,12.0,6.0,8.0,7.0,13.0,7.0,FABABHCEGEGBGBGCCCHCAAABGEGDGFGFAFCBCGCEHDCCAGHDHCAEHFBFAGBGBGHFDCDBEEDE,False +107,17.0,15.0,17.0,17.0,16.0,26.0,15.0,17.0,EFBHGEAFDGCGFGFGDEEAEGBDEFBGGFAHHCAFAFHBHBDGDGEGEGDFFFDFHHHAHBCDADBCBFGFCBCBGBFEHADAHCECFCECHBFFFFCDEDEDCDEFEFCHHHCACAEBCGAAAAHADAFHFBDBCFDF,False +108,20.0,24.0,27.0,23.0,19.0,28.0,19.0,18.0,AFAEGFGFGAHFCFEHEGDBBBEBEBEBCDDDHDFGFDCDCECFAFAHAGBBBEBFDEBCBAHGFGAGABDBEAGFCCCBEBHCDBDFDFBBHCHGGCDCDFHEHECGCFFFADAHHHDCDAEEBFGAEHCDDGACACACFCBEFFHAGCCCCEFEFCABDBFFFGHCHDHDFDGBGA,False +109,9.0,16.0,17.0,17.0,16.0,16.0,12.0,24.0,EGDDDAHBEAEABDCEBFFHFHFHCDGHAHCCFDFDFDFBBEBFBFEHGHGDCFCGHGHGCBCEDHBCDHFHFBFGDGACCCGAEBHBABCHHEHBDDEHEDEDEGEAHDHCECFCFCBHAHEGBHH,False +110,5.0,7.0,7.0,3.0,11.0,14.0,10.0,14.0,AHEHDHGFEFGCHFGFBBCAEFEFEFECEHFHBHAHFCBGFABHBEDEGCGFDFACGCGBFEFGHHHHEHG,True +111,20.0,16.0,22.0,22.0,11.0,17.0,13.0,10.0,ACAFFCDCDCACBFAFGDAACDCDEDEFFCBHDGDCDGDEABFEAADDCAHHDHEGACEFBCBCACACABBHDHDHEHCAAFAFCDDEDFDFBFCFBFDEDFFGGAGCCBEBCBHBAGGGGGEGACBHBDB,False +112,26.0,22.0,28.0,29.0,20.0,26.0,21.0,19.0,GCDCBAEHEHGGFABGFFFFBDBDBHCHCHAAADGFCBCDCFFFDCHCECEDEAFBFEFEGGCDCDAEAECFCEEACCBABGFDABADAFHBHFEFEAHAEADFCFHHBHAHAGGDHCCCDHBCADABHBDCGHGAGAGDDDFCAGBCBDBCFCFEHEDEBGGFGFDBCGAGDCDEDGDBDBEFEHAFADD,False +113,4.0,0.0,3.0,3.0,1.0,0.0,3.0,3.0,HAHADDGDHAGAECCCG,True +114,15.0,25.0,14.0,19.0,17.0,16.0,17.0,18.0,GDGCHHEBEBHBEFAFEFBFHFBGHEFEFEBAAAGFGDDFDFDFDBDBDBABABDHCBGDHCEBBGBCBEBAGHCHBEBGHEHEHEACACACACBBGGFGHCHDGBCDGEFDFDBEHECDGBCEHAHDHACFGADFDBAGD,False +115,4.0,7.0,3.0,5.0,3.0,0.0,6.0,6.0,HGHBHBDBABACEGDGEAHBHADGEGCHCBDGDB,True +116,18.0,19.0,11.0,27.0,26.0,22.0,18.0,28.0,FDFEHEBGBGBCFDFDFBEGFABHCHEEFAFAFAFBDHEHEABBDCHCDDGEHEADAFAFBHHCHBFBEDHGHGBFDFGECHHABDEGECEDADEHEDCAHAGEBABCDCDAHEDEDEDFFFFFBFHGAFEGEGDHDHGHGHGEDHDGEGDAHABBHHDHBCDADHEGE,False +117,9.0,10.0,11.0,5.0,12.0,11.0,5.0,12.0,HFBFCFBAAEABGHCHAFABBBBCCCHCECECHCGEHEHEHFHAHCEDDFDCEEBFFFFGEBEAFAHDGBGDEHA,False +118,1.0,8.0,6.0,3.0,6.0,11.0,9.0,8.0,BEBFGFGFBFBGBCDFEHBHAGEFHGDEFBFHHCGCDBGFGFGHCHFHCECE,True +119,16.0,21.0,23.0,14.0,8.0,20.0,24.0,21.0,EEGFBBADAFCBHFACCCFCFEFDGAFHFDABHBCGHHHBHGHCHEGCAABBGDHBHBGFGCGCGCGHFEFCFGABAGGCGAGACFCBCBHBFCFADHDHGHGFDEBEGCGCDBHBEAACHDDFDCDCFBFBGGGGCBHDHDHFABA,False +120,23.0,16.0,16.0,25.0,12.0,20.0,24.0,21.0,DFHFBBDGFFEDCHEEGGGEEADAGAGDBDAABFDFCGDGAABABABABACAGGHDHFACECBDDFDHGHGHBCBCAGFGBGCFFFDFDCGHGDEEHBCDCBHBCFGFDFDHAGCHHHHHGAFADDHEHEAGAGAGHCBAEAEDCDADCFGFDHDHF,False +121,19.0,17.0,15.0,20.0,28.0,24.0,23.0,17.0,DCDFFGAAFFFBGAGDGCACHEHDADADFEHEGGFFEFAABBHGGGFHEHACACBEEEHBAGAGFDFEBEGEBECECDCHBHGDGBEFEAEAEAECCGCEHBHCFFGBDBDCDAEEEAEFFFBHAHGEDEBGFGFGHGBGBDFDCDHEHDDDEBAFDFEGCFH,False +122,24.0,21.0,31.0,19.0,20.0,33.0,21.0,17.0,CBDGEGCBFGFHFHFEFBDAECCCBCBGHDCCCAFADHDHDEDACBDBGAHABFDGEGCHEECECDAFBGBGBFFFFHEAECHFHFHGEEBCFCFDGEGFFFFGCDCGBGBGFFBFBFAAAAAFGBAFABECAGEGBGFHFCADDCECHFAFADAHFHEDEHCFBACAEAEFDCCCCCBCHDADCG,False +123,23.0,22.0,33.0,26.0,18.0,14.0,26.0,19.0,DGDGCACABHFCADADGHGEEHGACAHAGACEDEDEDGDFCHDECFCBCGHGECHCHBEEDEDEDEDCBGBGBABCBCBHAGDGECAGDCCCFCDCFHFDABECGBGFHBBFBEBEBACEDBHHCCGCDAGGGFCCCGDDFCBCBGBGHGHGCBADHFFAHDGAAAAABAFDHDHCFCEAD,False +124,14.0,14.0,13.0,14.0,9.0,17.0,19.0,18.0,DCBFBFAFAHBHGFBABECACGGBGCGCFAFHHDGDGEBDADFFHHHHDAABHFFEGAGFDBGHGAGBGHFHFGCHCDGEGEFCGDGDCDCDCECBFAFCFHAHEBEGHBEBHHADAD,False +125,22.0,17.0,18.0,14.0,19.0,23.0,19.0,20.0,AFFEGCACEHAHBHFHECADBDEDHDHDACHCBCBHFDDAGHGHCECEAEAHBHGGCEAFAFBDGFFFFBAGAFAFHHCGDFFAEBBABADADBCGHHHGACACFCFDFBCGHGEGEGBGBCBEEAFHEBBGGECEFECEHGGEAFDFDFAF,False +126,2.0,2.0,5.0,1.0,2.0,0.0,0.0,0.0,CBABCCCECEAD,True +127,9.0,13.0,13.0,20.0,8.0,15.0,15.0,18.0,GGEFDFEHDHDHBAGABBBFFHFCFHGHGHGHGDADHDEDFCEDAGAGCBDFDHDHCBCDFDBHFHGHFBCGDDDDDABGHDHCHAAECFBDBEBCBCEGECCFFHCGAGF,False +128,26.0,16.0,20.0,13.0,15.0,14.0,8.0,14.0,AFAFGCBFDCCGCBCACACAFACECBAFAFDBBABABHECBGAHADEDCBADABABAHEHCHCHGECDHDHBHBAEDEAEAHBGFAHBBCACACAFEDCAHHEADGEGECEFFFCGHDFDEAEFFD,False +129,3.0,2.0,3.0,1.0,2.0,1.0,0.0,1.0,AHABFBEAECCDC,True +130,3.0,10.0,5.0,11.0,10.0,4.0,3.0,9.0,DBGBHBAEDEBCCEBAAFHHDHDCBEDHBHBHBDECECEDDDFDGDFBEGEHEHF,True +131,18.0,19.0,23.0,22.0,20.0,20.0,15.0,23.0,FGBCAABCBCDCDCBBAAADCEGHAFDFEBHBHAHGDAEAEAHGECHCDDFDBEBHHHDBCFCABFHHHABFHHEGEHBAFAFCDCHGEGEFBFEFEDEHCHCHDHDGFAFEBEBGBGFCDCAEDEGFFFHFBEAGACFDDDDHDCCCCDCDGEGBGCEH,False +132,27.0,13.0,16.0,13.0,20.0,12.0,27.0,15.0,HAACDHGHEBFFCDAGADAEABAGHFHDHCCAEHFHBGBECGGGGAGABACDEDCACACFGFGFHBBEBHGGGDABGGGEDECEAEAEAFCEGBBBAGAEAEABHEAEGGGCEHFHDGAGEDEDFDHDEAAGAHAFFGCCCCG,False +133,5.0,7.0,9.0,1.0,6.0,7.0,8.0,7.0,BGCFEBHHHHACABFBFHFCFGGGCCECGCGCHAEBBHFGCGDAEAEBEF,False +134,14.0,15.0,11.0,16.0,21.0,17.0,16.0,20.0,HBHDHFHDDEFEGEFEBGDFDFBBHBAGEGCFHBHDADHHFAFAHECEFADECEDDDBDBDACBEAFHFHGEGCGDECECBAGACHBHGHFHFHGEGFFHEHCHCEGEGEAEGDGEABDBABFFGECABA,False +135,8.0,3.0,1.0,2.0,4.0,6.0,9.0,3.0,GFGEGHGFEFGCGDBAHAFDEAEGBGBAAAFAGAHF,True +136,14.0,29.0,20.0,23.0,25.0,22.0,18.0,18.0,DGDCEBGFHDBFBECHFEFBDEDCACGCGHEFEFEFAFGGGDCFGFHFHAHADEBBCBCEEEFEBABCBEBACACBHHCFCEAEAGBGDCDBDEDGBACECBHEHBDGDFDGCGAFEFDBHBEBEAHGFCFBFBHEDFDGDBBBBACDBDHGBEAEGFCHBHEHDHDFD,False +137,3.0,5.0,1.0,6.0,8.0,6.0,3.0,5.0,FDFDBBBEDEHEHEFEACFFGDHDFGBHAEAEBEGDH,True +138,17.0,19.0,28.0,23.0,19.0,29.0,14.0,27.0,EEHFCDHDHBAADFECECFFFCDGBAHAHFHBCDDFDGDADBCAAHABAEGFHFHDHDEGCGHGHCFDFEFGBHAHBCBABEEECDCDEHFHFBABHCCCACHEACHDGDFHFHBHFGDGDGDFBCDCGABFFDFECHCFFFHFCDGEFCACHCHCHEGACFCFBFEEECEBBBBD,False +139,18.0,10.0,15.0,7.0,19.0,9.0,15.0,15.0,BCDGAGEBBAAFCBEFDFHCAAHABFEADAHGCCCACEDEDEDEDEHCBCFEHCHEACACHGGGGBGEGFGFEHECGFEAHGHEHEHEHACAFBGGABABHGHEAEAC,False +140,12.0,11.0,10.0,15.0,15.0,9.0,10.0,21.0,GGDEDEDHDABGBDCAFADADEEFHFEEBBAHECFCAHGHGHEBBCBABAFHHHHAFADHECEGGBGECECHBHECFCDDDEEHHHHHDHDHDHFACGDABFG,False +141,6.0,7.0,16.0,10.0,19.0,4.0,7.0,3.0,GAGEECEDBGBGFCFCHCFBDBDECEAEDBDCHBEEFAHAEAEGCBCEADDDDEGCCEEEECCCECDCGCEE,True +142,17.0,14.0,17.0,18.0,21.0,18.0,15.0,9.0,BADAGADHDGDGFHFAFDFGEEDDDADCCCGGECCCGEHAHAHEEEEAECFCDHDFABABFBGBCACEFFDADAEEHBHFDFCBEBGHGCFCDAGFDBEFFGFGEGCBAEDEBCBAACDCBEBEFEFEG,False +143,1.0,3.0,4.0,4.0,2.0,3.0,3.0,3.0,DHDCCGCGAGHBBFEFCFDHDEB,False +144,3.0,1.0,7.0,1.0,1.0,3.0,7.0,2.0,CDCFHGGFBCCCCGAGAGAEHFGCG,True +145,3.0,5.0,7.0,4.0,3.0,11.0,6.0,3.0,DHGEGBGBGCCFDFAFHCBEBEBDFCFCFGFCCAHFFFDGAF,True +146,4.0,13.0,6.0,8.0,6.0,15.0,9.0,3.0,FABGBGFGFDBBBCGEEEEBFGCBFBDBCFDFGFGFAFECCDDADAFBDGHGBFBFHFEFHCBD,True +147,16.0,16.0,22.0,23.0,21.0,20.0,35.0,29.0,FBFEECGAGFGFGHDHDFAGEGEHFHFHFEGHGCEEAHDGDEHEGEFHFCFHGHBECDBDBHHGGGGGGCBHAHACAHAGEBDCEAGGHGHGEGEBDAHHHCHADGCFBFHGBGCHDFDFDGHCBCHHAGBEBDACHCFFGGGDADEEAGCEDEDCCCGDFDBDGFBFBGBDEACACDCDCH,False +148,16.0,20.0,20.0,23.0,21.0,16.0,31.0,18.0,EBEHGGGHCACFDDDDDAFCHEGCACFCFDFAGADEGGGAGEECEGEGEGAFFDCBHBHDHEGCDCGBGBGCCCCCBDGEBCGFHCHGHAHBBCEGEGEBFBGAHABDBDAGAGFGBEEEFEDGDAFCHBABGBADADEGFFDHDCFGGDHBFBDEDEDGHHHBH,False +149,3.0,7.0,4.0,6.0,10.0,7.0,3.0,5.0,EBEHEBEDCFCBBADCHFHFGBGBDEEEECHBDADADEFFFGFHE,False +150,6.0,2.0,7.0,6.0,2.0,3.0,8.0,0.0,DDDCGCADFDFGGGACACAGBECGGDGABACFCE,True +151,5.0,2.0,2.0,0.0,5.0,4.0,2.0,3.0,GAGAFBFEFECEFHABAEHEACH,True +152,14.0,12.0,9.0,7.0,12.0,11.0,10.0,17.0,FDHDFEHDHCFCBCDGHGCFFFBFHACCHBGAGAHEHEBEAADAHBGBFBFBABABAHAHEEAFHEHBHEHABGGECDCECEAGDHAHEFGG,False +153,19.0,24.0,27.0,19.0,23.0,23.0,26.0,24.0,CDCGGGFAAGACHFHDHDHBBCCHCGFAHABGBEDHBGBGBABADECFFFFAGGCHDDGDGCGHGHGDCFHDHAFEFEFEHDCCGGBGEGAAFCEEDFDFGBEAFHFCGEBCBHBFBDCDGBCBEHADABCHCHEHEHBHDGFGAGEGBBEBHDEEHAHAEAECCFFFCCCECECEFBFBDECBA,False +154,13.0,10.0,11.0,9.0,11.0,8.0,12.0,4.0,GEAEAFAGADADAEFCGCGCGCAFBFBEECEGADADACBGBCHHBFEECACBEHEFBFBDADEDBCGGGBDFHCAGGD,False +155,23.0,15.0,20.0,21.0,22.0,13.0,16.0,23.0,FEBEBEBFDHDHCCDDBCBEGFDFGBHCHFDAEBCBFHAHGHDADCBGDHDHDFCAHHHDBCEHDFDAAECDCDCBCAFEEEEEAEAGACHCEGEAEGGGGAEABAFAFHHGEAAACHFHAHFGEAEDEDEDADHDBCGAGACBCHHBGGCHC,False +156,1.0,2.0,8.0,2.0,1.0,1.0,0.0,3.0,CCCCCHCHBACDCBHEDF,True +157,11.0,6.0,5.0,14.0,10.0,10.0,2.0,6.0,EFAHAHFBFGGABADFCBEDEDADAHAFAHBFEDEDCDEDEDEDFFCBEDFDFBACDDAEHCHA,True +158,15.0,22.0,16.0,16.0,9.0,21.0,17.0,9.0,CFCFCAEBDGDHBBFBHCAAGFFFAGGGGFGHCHDBDBECECECFHBBCBAFHFDFBCACHCAAAEFDBDBCFGAADADAGGBBBGCGBGCFBEEGHGFGFDFDFABABDFHFDBDCEFEBGDDB,False +159,3.0,6.0,10.0,6.0,2.0,3.0,4.0,5.0,GGGFDFDBCBHBHBCCHCBCEHHFCACDCBEDDDACGCA,True +160,7.0,12.0,7.0,6.0,6.0,8.0,8.0,5.0,AEFEFEBCBADCEFHHCHGBBECAABFBFBDBGBHECGDADADGBGAHFFCFCGDGBGB,False +161,25.0,18.0,13.0,27.0,15.0,21.0,17.0,28.0,HFHGDDBDFDGHGADHGFBHGCFDAECCHHEFEFEDDBEBAHAHFHFBFHAHDFDFAEDFBBCEHADGFGAHDGDGDGDFCBCEAEBCBHDHDHAHAEADHHFHFHEGBHEDABABACDCAEFDDGFGAGABAHDHDGDGDBHBFAABAGAECECHCACBFAFH,False +162,18.0,23.0,16.0,12.0,17.0,23.0,24.0,31.0,AEABABCBCHCHCFFFBHHEGBABDDDDDHHFHEECFCFCBEDDBHBHBCGHDFAFHCHFGCHHHHHHHCFGFGEHDBAAEGGHEBBHGDAHFHBHBECGFAFBGCAHEHGBBFBDCHHGEAEHGFFFADGEGBGBGCGFFCHGEGEGAGAFABABAEAEGFGF,False +163,24.0,23.0,17.0,16.0,25.0,31.0,34.0,30.0,FHFHFEFGFBAEHHHDHDHFGGDGDGFGDHACAFGDGDECECHCGAHAHBBBBBFFFCGBGEFFHFEAECGGBBAGABABAFHFHECGDECFCHDBACDEHBFBHBFEFDDGCHBHGHGHBEAGFGCEHFBAHACEHEACFCFEAEGEGAGACFEAEBGGFDBDBGEGECEAHHHAGBGHAFDFAFDFGBGHGFGAGHEE,False +164,16.0,17.0,19.0,27.0,19.0,29.0,35.0,19.0,GDGBCCGCAFBFGFDHGHBFAFGFGDDECECDGDCDFHFGFCFHFEABACFHFBFHEEECEDFDEDGGGDGCCBBDBFBABFBGDEDEGBHBDDDGGGGCFHFGFGFHFEABBDCDCHCGGGDGFGEDADHDECEAGAFAHEHADAFFGGGCABEGHCAEFGFGAGDDHDHBCEHGAEHFH,False +165,10.0,7.0,7.0,12.0,6.0,6.0,5.0,8.0,DGFFDCDCDAEGDBDCEBGACECHCECDBABDEAHDHGAAHHHFHFBFBGBHDADADAFAE,False +166,17.0,18.0,17.0,16.0,20.0,19.0,17.0,15.0,CACAHAFBDAAADADHBGFAFDGDGDGHHFHFGFGFHHCAAEBFBFCFAHEBABEEGEGEGEBAHGDCDGEBCHEGDGCFCEEFECBCFHBHBHBADDFBFBGDCBCFFEGCAEGEFBACDCECECFDDADEEEGHBHB,False +167,15.0,4.0,11.0,15.0,21.0,12.0,17.0,17.0,HHAHDEDGHFHEHCHGFGFCECEGEACFGDGDCDCHADCEHEGGAEEBEBFHHHCHCHCFDAHAGDGFGDDHEEGCAEDEABAEGEGHGDDFAAEFGAGAEAFAFDFEEBED,False +168,8.0,4.0,9.0,2.0,9.0,7.0,3.0,7.0,ECECBCHFHCGFGFEEEHEHECAAHAFFBAEAFHBGAEAHDBDACCCFC,True +169,16.0,14.0,9.0,11.0,11.0,11.0,12.0,11.0,DFDFDGAGAGAGFGHHACBHBHGFFDFGBCEAHBDAEADACCECAAEABBHEAEAEDEDCABABCBGGGGFFACHHBDBFFDFEEGBCDHEHBHB,False +170,4.0,2.0,1.0,1.0,6.0,4.0,5.0,2.0,GGDBEEEEBEAGFFCFGFHAHAEAG,True +171,28.0,14.0,20.0,10.0,8.0,25.0,20.0,36.0,HCHCDCGCDAGAGHGBABAFAFCFAFDFGFGEGHFEFHBHGFGCHEHABFGFHHHCFDACHEFBHHHCHAHGBAADCHBHBFAAAHHHFEGCGDAHAGFBFAADAEACFFGAEAGABFCHCBFDEAGAHBHBAAHHHFHFHCCACGHGHDHDHCHCFCBGF,True +172,3.0,11.0,4.0,4.0,5.0,7.0,5.0,5.0,BBBEBHHCCFEFGFGHGBBBGBDFAFACEHFGFHDBDBABCDEE,False +173,8.0,13.0,6.0,15.0,4.0,10.0,15.0,7.0,ACDCGBGFFFGEGBGFHBHDADHDFGBGBGHCDAGGGCHDHGADDDDDDEBBHBFBFGFAEADGCCBDBDGAAEFBFB,True +174,10.0,11.0,8.0,10.0,13.0,7.0,14.0,11.0,GCGCGCGFGEBCAAEEHEAEHDHDGAADADADFBEDECHCGGGHGEEHBHAHABFBEBHFADGDHEECHBBFBGEGBGDCFBFD,False +175,23.0,12.0,12.0,24.0,26.0,34.0,26.0,24.0,CDBFHAHBGAAFEGHAFGCAFGFGBGBEBEAFGDGDFDADCFGEGBFCHABFCGADHFFEFHFEFEFEDHFGCGEGEAABEGAGHGEAFAFAFCFAEDEDEDHDHDHFFFGFHACEFHHHDHDAGFDFGEGBGDHDBABAFEEEHEBGFGEEAEAHHFDDDGHGHDFCFCACHDDEDEFHC,False +176,18.0,8.0,20.0,16.0,15.0,17.0,11.0,11.0,FCFBECGAFAFABAEEEEDCDAECEDGAAADFHBDBECEHEABABCDCHBGEHAHAGAECHHHADCCCCFCDCDAGCFFEEAFAFGDDFHFHFHDBGGDGDADFGCECFCGCDCFF,False +177,13.0,12.0,13.0,12.0,6.0,11.0,5.0,9.0,DABFHGHCBDBDCFFGABAFEBACAHECGDFFHFHFDFEFCHCBCBAECGCGCHEAEADDDBDADAHHBACABACDCDBFB,False +178,7.0,14.0,10.0,12.0,19.0,22.0,10.0,9.0,FDECFBFDFDFHFGCEDEDEFHGBACCEGGAEBEGABFDFDFCHGHFFEDBFBFBFEGEHADAEFEFEFEABCFHDHDAECFCGBFBGBFBEECECDBEBHGH,False +179,2.0,2.0,2.0,1.0,5.0,4.0,1.0,6.0,HGFEHEHEFEDAFHFEABBCHCH,True +180,2.0,5.0,1.0,3.0,3.0,4.0,0.0,0.0,FAADBBBBEBEFEFDDCF,True +181,6.0,7.0,5.0,2.0,1.0,4.0,3.0,6.0,BHBDBAAGAHCHFHACAHEHBBBFCFCACGGDBF,True +182,2.0,3.0,10.0,6.0,8.0,6.0,4.0,4.0,BCBCECEAEDEDHCCCCHEHEGDGCFFFAHGBFFFECDDECGD,True +183,27.0,20.0,35.0,20.0,19.0,18.0,17.0,19.0,CHCHCFCBDEHBHEHCCCCBDBAADFFECCGCAEAFAHCFGDGAGACABFEAHCBDBDBDACGDEDEDEHEBGDGDCAGABEBEAECEGAGFGCABFGFCEAEAGACFCDCFFGFEHBDBDECACAFHBHCHBHBFAHDBCADHEHACAGDDDGCEBFBFCCCCGAHCFCACAHH,False +184,21.0,29.0,29.0,14.0,13.0,23.0,22.0,20.0,HBBEFAHAHDHCHCGCBCAFABDDHDFAAADBDBEBCBCBEACGCGFFBFAFHGHFCFEHCHDADFCFCEDBGBCCFCFGFHCHCACBEAFBECFCDAGGCGFGHGFGEGACCDCBHBACGFGFHFBFGEGBCHCBCDEBBCHGGBGBDDFAAAEBEBABHBABHGEGBHA,False +185,16.0,21.0,7.0,5.0,16.0,12.0,3.0,15.0,BBBHGHBACDBEAAAFDHEHAGAGAEEEHHCAEAFBBABFBCECAFAFBFHFEDABBBFBEBEBEBACHFHFHDHBFEAEBHAFCHEDECEHBHB,True +186,26.0,34.0,20.0,22.0,24.0,21.0,26.0,17.0,HFACACHCBBBBHBGBEHFHFEAHAEAEFDBHECAHAHDDBGEDCBEGGFGECAAADBEBGCGCFCFCFBFBFBAGCBBABEHGCGCGFGBBCHCEDAHBCEAEHDBAHGGDDDDHEADDDDDFFGBGAGBGBEBABDBDGDGBFBDBDBDHEFEFCFEAAFGEBCGEGBFFGCGAABAGCHEEEAFAEA,False +187,3.0,5.0,0.0,1.0,1.0,2.0,2.0,4.0,DEBGHGAFBFHHBHBABA,True +188,8.0,11.0,10.0,11.0,8.0,19.0,14.0,12.0,HGFBFHFBFGGAHDDEBAHFHFHFCEGFGFGFGBGEGBCEEAFDBBBHFHDBDBGACHCHFGCGFGCGFBCDCDFFAEAHAEFDFDHAECDCD,False +189,24.0,32.0,23.0,32.0,21.0,21.0,20.0,22.0,BBBABAEECDDDEDEHEBECEDEDHHHFHFDFHCDAHAHDBGBGEGFGFGFGFBAGCGDFBFHDHBBCHGHGFAEBEDCAAGFDDADADBDCFGHBABDHECBDBAAHADAGCDCBABABGBHDCGCBCGFEBDCHAHCCCFCFEBABHDDBGBHHCCCGBABDBCEEGHAFEFEDDBAFFFDFDCEAEAEGDBD,False +190,13.0,10.0,11.0,9.0,7.0,16.0,9.0,11.0,AGCHAGCBAHCBGBEBEACADADHDBFBDDAGEFCFCBHDEFEFHFHGHDFGFACAEFHAEAGGBGFCFCFHFDFCFCBBFDAHAH,False +191,14.0,3.0,6.0,9.0,14.0,7.0,4.0,6.0,EAEFDGEEFCCCFCFEAAAEADCDAEAEGGAFHHHHEAAADADEFEBDBAEGECEADFDHDHB,True +192,6.0,4.0,7.0,3.0,3.0,3.0,1.0,4.0,CFGEHCCFCBCEAEHCHDADADABBBACAFH,True +193,29.0,36.0,21.0,12.0,18.0,14.0,23.0,24.0,BBHFFFCEHEGEHDHBGBHBHDEBHBHBEAEBDBFHFHEHABADACGGGADBBHHFBBBAAAAABECDCACHCAGACFCFAEAFAFAGGDAEBDBHBEBGACBHFAFGFGBBCAGGBGHDCBBDGEHEGEACACACEBEBCACAEGDGHCBDGHGHBBABCCHCHCHGBAEAGBFBG,False +194,6.0,3.0,5.0,1.0,2.0,4.0,8.0,5.0,HBHGGFCFCACAEABGEACDCHBGGHGAGAFHFG,True +195,3.0,6.0,4.0,7.0,9.0,15.0,5.0,10.0,HAHEHFGFHHGHGFFCFCEDEFEDBGBDEDACBDFHEBFHFHFEFDFCFDFABEBGHFE,True +196,2.0,2.0,8.0,2.0,3.0,5.0,4.0,4.0,CCECHCDCDCEBHCGEHBHGAAFFFFGFGC,True +197,0.0,3.0,4.0,2.0,1.0,2.0,3.0,2.0,DBHBDFCCCGCGBGEFH,True +198,9.0,8.0,9.0,4.0,11.0,7.0,12.0,11.0,AAAFADHGGGFGCBCBCHEGEFEHDCABDHGEGEGDACBFHFBEBGBECEHAHAHGBECFCGEGAHEHCHF,False +199,9.0,8.0,10.0,11.0,7.0,10.0,5.0,6.0,ACADDFDHDABGCDEBEHAFFBECECDBBABAFAFAEAFHDDDHCCDCGCGHGDGHFCBCBFFEFE,False +200,15.0,9.0,5.0,13.0,12.0,23.0,15.0,22.0,CHGFEHBDGDHEHAHDFDFAEBDAHEFEFEGGGGAAAGEDAHGHGHECEGFGFGAGBFEFAFBFBGBDFAFHDHBHFHFHGDEDHFFCFEDBDHFFFAAHBHAHFCFDHHCHAA,False +201,8.0,4.0,6.0,6.0,2.0,3.0,2.0,2.0,AGCFBBCBCDAHABACEHDADADCDADAEFGFC,True +202,15.0,30.0,30.0,30.0,15.0,29.0,25.0,23.0,DFBBDGHBCEDBFBHBHBCBHEGGGEBEBHHEHCFFHFGBHEGBDFDFGBGDFDFHCEFHCGCFDHDFDEHADADEBCFEFDFEFECDAAHFGDDDCACACACACDBABGGEDAABBBGCACABFBGDCDAGGGGDCDFFFGFCBBBDBDHECGHGDGCGCHCHFBFHHHDHCEBFDFDFCFCGCBCBCFCDABHCG,False +203,14.0,19.0,19.0,3.0,12.0,14.0,16.0,22.0,CHAEADAHBHBHBHBGGDBHFHEAAABCBGEFCCHFEBHCHABABFHCCCHBHAGAFCFBFAAAHCFCGEGEHEHEHFHBHEGFGHBEGGGCCFGFGCDAECGCBBGBFBCHCHCGBFE,False +204,9.0,15.0,19.0,11.0,9.0,19.0,20.0,15.0,FAAACCHEGCGDGBHDCCCEBAHDGDFDBDBHCFGFCFCBCBFGFGHGBFBHHHFHEGBGBCAEBCCCFCFCHGAEFEAGCDHGHGFGFGCGBGBGFDACEBFDFDEHEDGHABFHF,False +205,20.0,16.0,16.0,34.0,30.0,20.0,29.0,29.0,CDCFGDGDEFHGHEHEGGBGBGBHBGEFECDCEBGDAHGCBDDGDHDHEBEDDDDHAFAFDEGCHEGFHFADBEEGAGDGDHFHBDEAEAHAHDDDECGBADEHEFEFDACAGEGFGBDEDECHHHEAEFFBADDDDAEAHHDHDCCFCAAAHCFCFEGHHHHGBGBDCHCHDFDGGEGBFBGHFAFEGEGEAE,False +206,20.0,18.0,16.0,14.0,21.0,4.0,6.0,11.0,ABABAFADEDBAECHGDDAAHEBBDBACECGAAAACHEFEBCDHGBCECECEBEFEAECBCEHEDGAHACADAHACECGDDEEECEHHHFECBCBEBHBDBDBDBAGDBA,True +207,1.0,3.0,2.0,6.0,1.0,4.0,1.0,1.0,FCADBDBGBFEFDFHCDDD,True +208,5.0,3.0,5.0,6.0,4.0,0.0,1.0,2.0,DCCBCDCDCAAAAHDHBGAEEDBDEE,True +209,9.0,6.0,7.0,6.0,5.0,8.0,3.0,2.0,FCFEAEGDADABCBCFGAGCFAFABABCBDHCFDFEFEACBDHEAD,False +210,21.0,21.0,15.0,16.0,11.0,15.0,20.0,12.0,CACFFACCCEHFDBGBGBFHFAGDGDADACGGDGBAACABBECECEGEDHDHCABDFDFDAGHGHGBGBFBGEGBFDFAGAEHFDAHEGABABFGAGEBCCGCHBDEDGBCACFBFAFHDBEBHBABADAH,False +211,10.0,24.0,13.0,13.0,14.0,11.0,16.0,23.0,EDEABACHGHAEGGBBBBECECEBBBAHGHGHCBCECDCBFBHBHFHFHFBBDAGFEBHAHDHGCFAGABCDDBEBEDHGHBCCACFDDBAHHHGBGBGEGEGHGFEFHHHDDBBCDEFGFHDH,False +212,19.0,7.0,17.0,13.0,17.0,11.0,21.0,24.0,FGCAHAHFGEHAAAAAHGDGHGFEEGDHHAEAEDCDFGBGDHDGFECECGGEEHGHGHCFBBHBFEEHGHGHDHFHDHDAAAHDECAAACBCECACAHFDFCCCCCCGGGGGEEEDHBHEFCGDHAHAB,False +213,10.0,20.0,7.0,7.0,13.0,11.0,10.0,5.0,HACBEBEBAGEEHEDAFABBFEEEBGBGBGBAAEBBDDFDFDFHCHDDAFECHBBAFAGGGFAFCGBEBEBEGGBFFCBCBCB,False +214,6.0,9.0,11.0,6.0,13.0,4.0,11.0,19.0,ECECBCFDGEGBHEDDHGEBHHGCGCBHHHHHEHEGACABADHFFGCGBGHDDCEEEEBEFHAECBCHGHGHBHAHAHC,True +215,3.0,0.0,0.0,3.0,3.0,2.0,6.0,5.0,HDFDHEHGGGGHAHAEGEAFDG,True +216,1.0,8.0,11.0,12.0,14.0,8.0,9.0,12.0,GEBDBDCCADDBGFGFEEGEGCDCEFEGEBEDCCFBHCEDDGEHEHDDFCHHHBHBHBCDFDEGEGCHCHEHFHF,False +217,10.0,10.0,22.0,13.0,14.0,8.0,15.0,10.0,DCHGECECEAGHEFGACFBGBECGCAEBEHHAGEGFDFDFHEDDCDBFBABACDDHDBDGCCCGHGACFCFDGCGCBCBGAGACECACBCECGDHEHEHECD,False +218,7.0,10.0,14.0,5.0,9.0,7.0,7.0,16.0,CFCECECDHHHHHHHHBBBHEFCCEBDBABAGDFDHCHGACCHCHEFEGHGDACFBGBCEEEFGHGFCBCHAAAB,False +219,15.0,20.0,16.0,12.0,13.0,12.0,14.0,14.0,AGAEAEAHGHFBFEHBHFGGEEHCFCDADACBDBFBCBFGFBBBCCAEGDGFAACAHBCBCDAFHFHECAFFEGEBCBGGCDCDCDEBBDBDBHHHHHDGAGDCHCAGEGABBEBE,False +220,0.0,1.0,1.0,0.0,3.0,3.0,1.0,3.0,HEHEHFFFGCBE,True +221,4.0,7.0,18.0,11.0,9.0,20.0,14.0,16.0,GGGBFCCCFBFDGCFCFDFHFHCDCDHHHGHFDCAGHCBAEEFEFEFHAEFCHCGEFCCCHCHEHCDCDAGBGBGCDDFDFGFHEHDHFGEGFHFGFBB,True +222,19.0,32.0,14.0,24.0,24.0,23.0,30.0,29.0,EAEAGFDFDCBHFAFADGBHBDAGCDEABDFGEEFFFEEAECHDHBHDGAHHGBGBGBGHCDFDBDBDEDADHFFAFEFGBHBGDCHEDABGBEBCDCHCBFAFBGBAHFHFGEDFHHHBBBBDBDBDBGEGBHEACCHEGEGEDEHECGHGFBHGHCBGAGHGHGEGEGEHAHAHFCCEFHFAGBGBGDADFBB,False +223,6.0,4.0,7.0,6.0,14.0,14.0,8.0,15.0,CEEFAGEBDFAHHDHFAFAHBFFHFCFEHHHHFDEGEGEDEDGAGHDFGBGBEFGFHHCHCHEHECFCACEEFE,True +224,11.0,10.0,13.0,13.0,21.0,14.0,25.0,19.0,CGBAEGEGEHHCGGHGCCBCAEBEGHCHDFDFDFEGBDFDFEFAGDGAGEGCGBHEEGCGBEEGEADACECABEDCDFFFDCAGAGHFHAHGEGEGEGBGBGHHHHHHDABCEDHHFFDHEHEGFF,False +225,6.0,19.0,5.0,11.0,12.0,6.0,9.0,5.0,GBHBDBABHBCBDEDBGBGBEBEBCCFDHDFEBBDDEAEAEAECFGFGEGABCFGBBDHDEFBGBGEEABHDD,True +226,11.0,18.0,23.0,14.0,12.0,26.0,20.0,26.0,EFEFEFGDCDFBHBHADECHHEHEFGFGHCBGACBGACFDFGFCFGFCCCHHHBHFHFHDADFFEBGFFFFFDBCCFCFHFCDGEHDFDBDCAGGHHHHHHBACGCGAGBGHAAAFFCHGBGCADGBBBCGDHEBEBEBEBHCHDHCCCG,False +227,23.0,20.0,28.0,18.0,25.0,23.0,23.0,21.0,FCCBCEFEDAGGBEHCHCHAFCCADFFHFEFAHCHDGCCHAEDEDFDGAGAGAGEFEBEBHHEFEFHFCGDFBGBDHAHBGAHFFFBFCDDADCDEEAGABHBHGHCHCABADABCHCHCDFGHGHBAFFEGECBGADCECGCGCBFEFDFCGCGDEECAGAEAGAGBBBBBCEEAEDECE,False +228,5.0,3.0,9.0,5.0,8.0,2.0,3.0,5.0,DDDACEHGFBCEAECCCCCFCEHEHEHEBCDAEBDHAGAG,True +229,15.0,19.0,18.0,23.0,23.0,15.0,10.0,23.0,HHFHGHEBFHHBCBDEEHCBGBAHAEDEDCGCGEBBDDDDEDBDHDFDEDACCEEDFCEEECBCBCBCDAFEHCFAHBEDACAGHHHHHHHAHGFACACAFBEBEFFFFFDEBEAEGCBEEDADACBHGCGBGDHDHDFDHDEABF,False +230,15.0,10.0,14.0,14.0,7.0,9.0,3.0,6.0,EDADBFADCDCDEBFBFAFEFEDCBADFBFBAHACCBCGEHEHBCCAGDCFFBAAABAGACHCHDDCCCEDHDADADA,True +231,21.0,19.0,19.0,16.0,21.0,13.0,13.0,23.0,EHBFBHBCDAEACABABEHCAAAAAEBDHDCECACAHGFCFBFBDCCBDBDECHCGCAAHHDDCDCDEEHHHADAFBFGFGDGFGHGAGEEFEHBBDBGHAHGHEBCCACACGEDEAABDBCEDEFEHBHEEEHGHFHEHFFGHB,False +232,10.0,11.0,13.0,7.0,8.0,12.0,12.0,9.0,EFGGGHCHBAEHFDFEADAHBBFBCGFGBCBCBCFHFAFAGCGCEBEDCCCHCHDGGGCGCADFEBEBDAFAFAHEFGBHDA,False +233,16.0,18.0,26.0,21.0,12.0,11.0,22.0,9.0,GBGCHBGDHEHDGAFCFCGCBBDDDHHGCEDEDCDBGBEBCCCCDBGBCACBGGEHEDGGAGACFCFCHCGGDGABDCCCGDBDEDEBBCHCDCDBDAGECECAFEFBFEAGAFAGBGAGDDDACAFAFAFCHBA,False +234,8.0,5.0,2.0,10.0,3.0,5.0,9.0,5.0,GAGBBEDFDFDBDGDAEADHGAGHBDGDFDFCGAGACABAGHHHFED,True +235,28.0,16.0,21.0,19.0,24.0,21.0,12.0,20.0,EDHFBEAFADABHFHFCFHFACCBBBHAHDHBADGDBCBDFEFDHHADACBHBEAEDDDGAGACAEHECFCECHHHEABFCFEEHGAFFFADADCDGEEEGEBECEBBCACAHAHADADFFAFAFHGDEEFEBCGCGCGCDCAHBGEEFGADECECAFAHA,False +236,13.0,6.0,14.0,8.0,9.0,13.0,7.0,14.0,FCFAFAFAHAHCDCDGFFEFECEDBCECDCFHEEFAFACHCHCEBGDHEHFHAHBHDHFCGGAGDHHACCBHDCGFGBAAEABA,False +237,4.0,7.0,4.0,12.0,6.0,4.0,7.0,10.0,DGGHBHDDDGDGCGCGADBHEDEDAGFCFEBDHDEBAHAFEHEHCHDBDBHFHB,False +238,25.0,27.0,17.0,20.0,11.0,20.0,27.0,24.0,BGGGHACECEFEAEDBDBHCGDGDHDHBHBHAHAHFBFGCGCAHFHABABEFFDDAAFHFHDAGADFDGBACCCHGHDAACHCHGBEBCCCBDAFAEGHAHGHGEDBDBCBHBGFEAGAGBGBABDHDGAGADFBFGFGCAEBGFFEHBBGDGBBBFFHFBFCDAGCGHDA,False +239,27.0,19.0,14.0,12.0,26.0,20.0,17.0,18.0,CACHFHBABHBABAHEGBDDEBFAFAEACABAFAHAHGHDFEGEFEBEBEAFCDCHABAGEGEDFBGBACAFDCDCAEHEHFHFEEEFABABCGEEEGHDHAHBHDFGEGBAAAFDHECEAGCGEBEDCDHFAFAGAGBGFFCGCEHGFEBEF,False +240,13.0,5.0,13.0,8.0,10.0,9.0,13.0,11.0,HCHAGAEFGBGAGFGCDCAGAECGCGEFEDHGFADADACHDFDGBCBCFEDEFEFBAHHHHHHAAFGCECACBCGEHEADCG,False +241,15.0,13.0,22.0,21.0,14.0,24.0,13.0,15.0,CECEBACABEFHFGBEFDCDBABGDAEADCDHGFGFDDDFDFDFGFEFGCGEAHGHGHCFCDABFEHHABCECBCHFHCACFBFBHBADFEFEFDFDHDHCHCDEDAGGECHAFDHCABFCFDFDGBGCFCACDCEA,False +242,10.0,3.0,9.0,4.0,10.0,22.0,6.0,6.0,CBAAFFFFGBDAFFFFFFFDGAGEHFGECEFEFHCHCEEEDCFAFAHAFBDEHGHCFEFCFCFEAAFAGC,True +243,16.0,18.0,13.0,25.0,8.0,14.0,16.0,17.0,CFHGHAFGFCFEDAGEBBFDGBGHDHAHBGBGBDCHHEBDBDBDCDHDHFAGGHGHABADDCDFBHAGDDDBCACECAGEGDDHDFDFHFHCGCGCDBAFAFDBDEFEACADADADBCFAHBHGEBB,False +244,14.0,10.0,26.0,18.0,17.0,28.0,19.0,21.0,HEHEHDFDFEGEGFGDCBBDAFHFHFDCEGBBDHFAGBHFHCECHCGAFCCDDADGHGCGAGBDCDHDHDACFCFGACEHEGDGFCFCFCAEFHHHFBFDFDCBCFEFCDGAGDEEFEFHFHFEECCCAAABECFHACECFAFGFCBCGHGHG,False +245,30.0,27.0,23.0,25.0,28.0,19.0,14.0,26.0,AAACACBCAEDEBEFCCHCAEGEDEFGAGCEAEADFEBBBEFAGBBBFDAEAEHHHHCFCHCHADFDEBHFACBFBGBFBCHHAHAEEGHHEAEGHGHGHGCAHADADAEAEAGDGBECHDDDDEFFDCDCACAFBFHCHEHEADFBFBGBDBCGABHBHDACCECDDBDBDFDBEEEEHCBAFHHDBBADF,False +246,9.0,17.0,16.0,9.0,17.0,6.0,11.0,16.0,HGEGACAHDHDCDEGFHBHDHECEDEDFDEEHCFCFHBEGGFABEHHHHGAABCCDBEBECHCHFBAHGCGABCBEBECCCCCEGEBBBBDBABEBHGEGA,False +247,10.0,6.0,15.0,20.0,23.0,16.0,16.0,6.0,AFDGEGEFEDCDFHEGEGFGBCACECEAEHEDDHEGEDEFGDDDCCCCGAGEDBABEFEFDGDHDGDCBHBGFFCFCEEEEFCHEFGDGFCDADCFCAEGFGBEFDADADAE,True +248,1.0,1.0,5.0,2.0,5.0,7.0,7.0,2.0,EFCFDAGFCFGFCHEHECEGGCGDGFGFBE,True +249,20.0,25.0,23.0,25.0,18.0,22.0,28.0,20.0,DGDBDAABACHGHEBDCCABFBAHGGBGEAAGDDFGFAHADADEDFHFHGGGFGFDHDEDBACDGDGBFACABBGBGEGEGECFFFEABDEDHFAFGBCBCACHHFHFBFBFHCHCHCECDGDCEHEGCGBBFBGEFEFHCGCBHGDGFHFEABCCEBDBHGDGDGBHCEDADCDCBAEAC,False +250,27.0,24.0,20.0,16.0,26.0,17.0,25.0,11.0,CHCBCACHBABAGHFEEBEGECEBEBEACDGDHHGAAFGEGABEGAGEGADADABAECFGBGAGAEBEADFGFECACGGFGEGDGFBFGCGBFBFEAEBEFAFAFEDEAAAAGBBBCDCDGECCCBCFADABHDEDEGEAHHBDEDFDFGCCCDBBHAHGBCBEHF,False +251,23.0,19.0,20.0,25.0,22.0,22.0,28.0,26.0,ACACGEBFHHCAGAGHGHGCGCGBEHFHFCAGFGCGHEHAHADDDDAEEEECCFBGHAHAHGBDECFADGCECEGEGDGAADBEAEFHFDGDGAEAFDECBGECCHDEEBGBABEHHAFFFFEFDADHBHBDDGGCGCBAGAHABDBDEFEBCBDHGHGFDFDFDFHBAFCBDBDFFGGCHHHDH,False +252,22.0,23.0,23.0,11.0,21.0,24.0,27.0,23.0,CGGAGEGECECECDBFFFHAHGEGCGAGACEDBBBFGFGHGHFCBGHFHBHGEAHAHABDHABABDBECHAHFCFEFAAGGGBGFCDCBEADADHFHDHCEABCGGGFGAHEEAECCCCGBBEHEHBHBHDCDFFAFBFCEBAGAGCCBCAGFDHHEHFFFCFEFBBEBFGEGA,False +253,21.0,15.0,11.0,10.0,10.0,18.0,15.0,19.0,CFCEEFHBGDEEFEFDAGAHAHGHFHFHGHAHAHGFFFGBDBGAAAABABGBFBFBEACGCEDHFACCFFFGECBAECDGGAFAHDHDHBCCGHAHAFAEDHDHGBBABDFCAGABHBH,False +254,16.0,7.0,14.0,11.0,13.0,17.0,11.0,13.0,CDFHFHECACEDEAECCHFHFHGHGCAHAGAGDEDFDCHCFDADFEGAAEAFFDEDCCEDBFCGCGEBEBHGAGFBABAGFHDHAHAEFFFFFBEBCGHACA,False +255,14.0,24.0,17.0,17.0,23.0,22.0,12.0,11.0,EDGFFFGBBBCACDDDBDCFCFCEEAFGFGFGFDBBBFBDCFEFADAHEDBDFHAAGHCHFGACABEDEDEAECEFEFDAABHHAHCECBFBCBFFDBDGHGHFBCDCECEDEAAGEGFBEBCBEEGEBEBEBHCEFBBH,False +256,15.0,18.0,13.0,27.0,17.0,28.0,20.0,24.0,FBDBCHCGDEDCGAGAGDDFBBBFFFFEDACGCHAGGGEGEBABFHFEDHFHFCBDGHGBGDHBCBGAEHFAFHHHDBDCHBFGFGFHFHEGEBDFFFHAHGHCHAHDHEBEFEDGDGAFABDBEHACFCFCEDADEFBDDEAEADFDFHFHFDGHEDDDDC,False +257,6.0,7.0,12.0,13.0,9.0,11.0,8.0,10.0,DDACHGHGHDHEFCCEGEGACCDCDCDADHBFEFEDEGCFBFDFBFEHCHDAGEDECBCBHFGFDFHAHCGABDBF,False +258,17.0,20.0,27.0,16.0,18.0,18.0,19.0,20.0,AGEHCDAGCGFGDCDCHCACDFEAGFGAAAADADCCHGHGHCCEEEGCADACAHECEGDGFBFBFCHCHCBBDBDBDEFCGCBBBEHFHACAGBCHFFBCBCGGGGHDBECEHEHGHBCAGEDEBFCEEBEBDFCFAFHBADDHFHFHFHECFBB,False +259,1.0,5.0,4.0,1.0,1.0,0.0,6.0,2.0,GGGGBGAHBHCGDBECCBCB,True +260,2.0,3.0,4.0,1.0,3.0,5.0,1.0,3.0,BFBCBFHEEGEHCACACHFFDF,True +261,2.0,4.0,3.0,2.0,3.0,2.0,6.0,2.0,CDCABEHHGFGFGEBABCBGDGEG,False +262,17.0,17.0,32.0,25.0,20.0,22.0,15.0,15.0,DHDCDCDGEHCBGBEBACGDFDCBCFCBCEAEAFCDEBAAEADHCEAEHECDDDBDCDBBFFEFGFBCBHAHFCCECGHDHFHAHACDEHECFCDEAAHABBCHGEGDGFHDDCDGDCCCGCACACFCFDADFGFBFBFEGEGEHDACGDFCFCFGBEBEFCF,False +263,7.0,4.0,7.0,4.0,5.0,5.0,7.0,12.0,GCACAHGHECGCHFGFEDHDHDHGHBAEAHBHFHGCCBCHEGEBHAFADAF,False +264,6.0,6.0,13.0,6.0,11.0,2.0,9.0,8.0,DCFBDBEEEEEEADAHGHGCGDHCHGEACBCGCAHEHGGAFAGCCCCCBEBHDCBCEGEHD,True +265,20.0,25.0,22.0,32.0,26.0,23.0,23.0,27.0,DCHBHBCEHHGHDCGCAHHGHDEEHEHBBECDCGBBACACADDDDDFCGEABGBABEBEBEACFHFBEGHFBABCGHGEGDDDEGAHAEFBFDGDHBFGFCDCDCDFGFHEBEHEHBDEAEACBDADHFBDDDDAFEFBGGGGHGHCHEHFCFGFGADDDDBDADHFEBEBECEADACBCFAFHFDFGFAEGHHCCFE,False +266,7.0,6.0,7.0,3.0,4.0,2.0,13.0,8.0,BGHCABHHCHGGBDBABAFCGEGDGAHCEEGEGBGCAHAHACGCGHGFGD,True +267,8.0,8.0,22.0,12.0,15.0,14.0,10.0,10.0,DCBAAGBEBEHECCCCFEDDDFGHGDEDCBCGEGEGEBFFAEHECFCHCHFHDCDCBHGGCCBCFCHHFAFGHGDFCEADCDCDCEBFAFACECAFEFE,False +268,20.0,11.0,17.0,15.0,11.0,11.0,19.0,11.0,FACAFGDHCEFHAECBCBEBEAEGBGBGFHCCBCAHDCFCDGDAEEEFBACADABACECHGGDBDGGGFHEHADAFGFGFGHGHGCFCDCDEGAAAABDDDGHBACACDGDHAGA,False +269,6.0,1.0,7.0,4.0,8.0,4.0,3.0,3.0,DBGECEAEAEAEAGDGFCHCECFAAHHFEFCCDEDC,True +270,18.0,16.0,20.0,26.0,19.0,21.0,22.0,23.0,BFBCDDGAGACDBDGDGDADHCAEACGCGDEBGDFDCDBDGHEHCFFFFFHFBFAFHDDGBHHHHFEFABGGDGDEFCDGHCHEFCFHBADHHCFCBGBFEEEEEFEDEDAFGHGDGCACDEAEACDEDHBHGHBHBHCDGAEACCEHGHAHACAGACBEBGFDF,False +271,0.0,3.0,1.0,4.0,2.0,4.0,2.0,3.0,HFHFEFDBEBHFDDBDGCG,True +272,16.0,16.0,17.0,14.0,11.0,14.0,8.0,16.0,FCHEHAFAFBFBDHGAFABBCDCDHBHEFABCHCHDAGABEBAHDHDFCEBGDFECECECEHECACDBDBDCGAGAGACAGBFBGDDACCDDBHEHBACFBFHHHFHFCFAE,False +273,13.0,11.0,14.0,14.0,11.0,17.0,18.0,16.0,CDFDGBHBFGFGFGEDABABCHHDDEDCHCGAGFBFDADHDCDCECAGEFEBEAFAEHEHGGEFBHCHFHFAFDFACGGFGHHDHGHAHCFAFGEBCBGBGCACDCDEHGFBAG,False +274,30.0,26.0,12.0,16.0,14.0,36.0,17.0,16.0,GGHCBABACFGFHFBBHAEAEACADADABABFFDABBFFEFBAGFHFBFCFBAHHHHGGDGFGBHBFEECEFDCHCHBHGEAHADDGAFAFDDBDGFGBEFFFFFGFACABGFFFAABAFACAGAGHDABABGDACFEAEADBBFBEDEAFFBFBFCFCDBHEHEDF,False +275,6.0,13.0,13.0,9.0,7.0,9.0,12.0,6.0,CEFBGCCCCHDBDBCAFDFDFGFHHCCGCGBGDGDBCBCBHFGAAEGBGBFBGBGECHCDAEGEFADAHEDEBBF,False +276,7.0,5.0,3.0,5.0,6.0,7.0,3.0,5.0,BCCDFEFEFEBADABCFDDHDHAAEAGFGFHFBAEAGHBHE,False +277,6.0,5.0,1.0,2.0,3.0,3.0,6.0,7.0,HBBFBFDHCGEGAHAHGHGFEBHBGGAEAHADA,True +278,4.0,8.0,15.0,16.0,12.0,11.0,10.0,10.0,DHCHAEEEHEHEFEHGFBHEDEGEGFCDCFCGCDCBFFFCEGDBHFDDADGGCGDEDEDGACDCFCFBGBHBDBCFCHCDDDHCAB,False +279,15.0,15.0,14.0,9.0,20.0,30.0,10.0,19.0,EAFFEFEFHBHBHBHCHCFAAACFCAHGBGBFEEBECEGEFDCEFEGCBFHFBEAFDBBGDDCGFDCBBHBHFEFEHCHFBFDGCHFHFHFGFGAAAAEECEFDBEFECEHDFCFHDHFFEAAAAAFGFHFH,False +280,20.0,27.0,17.0,23.0,26.0,20.0,26.0,25.0,AEDGCEBACABABGBGFDCEBHBCBCGHBAEACBHHHCDDEGFHAAFABCEHDBDBDFFGFCBGGGFGEEFEDEAEDEDHHHFHEEEGEGCBCBHBEBGBGECEAEHGHABBBFHEAFGBGDGFFEFDGDGDGHGDAFAGDHDECEHHHAHDDGHGCGEBEFABCBDBFCFCFHBADADFDAHH,False +281,10.0,6.0,6.0,8.0,8.0,11.0,10.0,7.0,GBFFDHAEAECDDBEGDGAEECGGGDHDAFADAEAHBHDEFFFFBCBCECAFABAHGFGFGFGHCH,False +282,21.0,33.0,19.0,20.0,21.0,12.0,19.0,26.0,CAADABABCEABHBABDCHEAEGHBBCCCCCHCBGGGGHHDHGHGDGDGDBDAAGCBHDFEEEEEEBEBAHHGHEHCCGHFBFBFBFGHBDBHAFAGACCHAHFBCCFDEDEHCHABDBEGADBBCBHEHEDDDDBDEDBBHAHBEEEDBBBBHGGGCEFBFAFBGAHAFA,False +283,12.0,9.0,6.0,10.0,12.0,16.0,15.0,10.0,CFCEDFGCGFHFBGCGFGABEGAGAGAGAFADBHGHDEFHHDGCADEGBBCHDAAAGEBEBABFDFEFEFHFHFHFHGBFEGEDDDEFEA,False +284,0.0,7.0,2.0,2.0,5.0,4.0,3.0,5.0,FBBHBHECBFDFGEHCHEHEBEBDGFGB,True +285,18.0,10.0,10.0,8.0,8.0,13.0,19.0,13.0,HHHFGFAHCCBCHCBFAGCGBABDBDGAFDCDAEAEHDADBHBAGFGFGHEFFGHGHBHAFFBFCFCAAABEEEAGGGAGCGFGAGADAGEHAHCDGEG,False +286,17.0,19.0,13.0,13.0,17.0,16.0,12.0,9.0,DBDADABCGDAFEFEFEDABCBEBGDGFEBEBEBEADBDGHCADABFDADADABGFGFCBCDCFBGGEEFCFAFEFBAGGEFHCGAFAHBHBFFEBACECACBCHAHEHEHCGBEH,False +287,11.0,13.0,8.0,14.0,5.0,10.0,1.0,11.0,ADDCHBHFDEACFDBDBABCBCDDDBAAADHFBFBABEHEHBHBCCHFDABAHCDDDCDAFHFEFEFHFHGAB,True +288,21.0,32.0,21.0,22.0,23.0,17.0,23.0,21.0,CFCBBDADEDEDBDHDADCCCEHEHBFBHADADBGBGDCBBHFAEBDHDFDFBEBHDEDBCECEGABCFGFHDHGHEHAAGHGEDEAEABGFCCBEBCFDFAEGGAGADECFFGFBBHCGEBEGAFABDBHFFAHAHAHBHBEBEBCBABDEGCGCHCHBHBGEGEGCAAGGBBFCCGDG,False +289,10.0,13.0,5.0,12.0,9.0,19.0,21.0,12.0,GBFAEDDDGGFEFDHHGHGFGFGDGFGHHHHEGDBHFGGHECBAGAEACFBBDBCADFGEGDBBBBCBHHFFBFBFDAAAEFGFAFAFDFDFHGGGGGECE,False +290,10.0,11.0,9.0,13.0,3.0,16.0,8.0,5.0,DBDBDCFFGFGABEBEDEFFGFGFAFABHCAFABCDHDADAHBGBDDDADFHCBCDCAAGHBFGFGFCCBFFCFD,False +291,22.0,19.0,25.0,28.0,18.0,24.0,23.0,17.0,FCFEFEFAGEGCGEAAAEGEHFHEGFGDGDEDBDEEECBBBEDFHFAGHCAGAFAHABFBFDDGECEBGFDFCFCDBEFABGEDACACDHDHDFFCDCACHCDBBGCDBHBHCFCDHHHBHBGFGFADDGDCDCHCDCACAGAGCDDABCEGHDHFGGDDEAFBFACACABGBGFD,False +292,22.0,21.0,17.0,19.0,16.0,16.0,15.0,29.0,EFHHAHDCDEBEHEHEHEHEHCFDBCBDHCAFEGGHDDBDFGFGHCFDDDDAFADCGCFDFBFBHGAFCCBBEEAAGAGDEDAHAHAHBHBHBHEHCABABHBCCCHCBBBDAHGFDEAEAFHGBGEHAFBGHAFAFAHABCDDECGCHHGHGAB,False +293,14.0,10.0,22.0,19.0,17.0,10.0,11.0,13.0,FDGGCACGCDCACBCDCDGHHDHBHFGGCCFBFBCBDFDAGEHAHEFECBHGDDDCEBBADCDFDADEEEEDEBHAHAGCGCBDGECEHEHAACADAHFHFEFCCECEDECCDAEA,False +294,21.0,23.0,11.0,16.0,19.0,13.0,19.0,13.0,ECDFDEAGAEAGHBFEFGHBBGBABABGDGCCAGHBHFEFGGCBDGDGDGHFHABAECEAGHFDFEFBFECECEFDHGFGABAEHEGEBBBBEBADFEHEHBDBDADADGBHADADHGAEBBBDCACECBCAAGA,False +295,16.0,21.0,15.0,23.0,14.0,18.0,17.0,12.0,DDBBHFDFGBGBHBFFFFFFFGEBCFCGHABBEHDDDDBBBBDGFHFAEDHDHCFCHCECBAHACDCDHAAADDECACAGABAGEFEBCAEACGDGFEFBGBDBCBGGDDAEFEDGCGEGEDEDGDBABADFHCHG,False +296,2.0,5.0,5.0,3.0,8.0,3.0,7.0,5.0,GHDHFBBGGCGBHEHBCACHCGCGEEEEFDADBEGEFE,False +297,8.0,7.0,6.0,6.0,3.0,4.0,7.0,7.0,GDGFBFEFAAEBDBDBAGAEHBDBHCHDGBGCGHGHAAACHCHAFCCD,False +298,10.0,8.0,9.0,8.0,12.0,10.0,12.0,8.0,AAAAAADGHGAEEEHFHEHEFFAGAFHCDCGEBCBCBFBFAFHFGGCGHEDGDFDBGEDEDCBEGEGHCBEBCCDGF,False +299,2.0,2.0,2.0,2.0,1.0,0.0,0.0,1.0,CHCEABDBDA,True +300,21.0,16.0,12.0,20.0,12.0,15.0,16.0,21.0,HFHGDDEFBFBFAGCFAGBGDHEHBHBHAEFBDGACHGHAHFFDFHFHEBBCBDBDBCFCDCACAEDEDHAHBHECABAGCEBHBGEDEGAAHAFAHADCDEGEGADFGAGAHCDAGADAHCHDDGDGDHFBF,False +301,18.0,17.0,21.0,18.0,14.0,17.0,20.0,23.0,BEBFFCAGAGAGHGHFHDHCFDFDEDEBEBEAGFBCCHCDCBCHHGHEACAEFGBGBEDEBCDADHFAADBHBHCHFDFDFHGBGBAEFGFAAEHEHEHCCGHDDDGHCCCCAABCGCGCADACABFEHDBCFHGHGDAHHDFGBGFG,False +302,17.0,9.0,16.0,15.0,18.0,20.0,16.0,20.0,CFEHGDGCGHFADAFGFBFHABACDEDEDGAEHEHCCCBCEFHGHAEAEAHAHEHEHCDFFAHDEAFDFGBGDHHFHFAGGFFBEHEAEAFFFDGBGCGEECAFFHEHEHDACBCFCDDDDCBCBHGAGCG,False +303,17.0,9.0,12.0,14.0,11.0,11.0,11.0,15.0,DFDFAGHHDEDEHEHECGFACAEADDHDEDCHCECFHBBBEGHBACGGGAGAHDHAAADEHEAFADGDBDFHFGBABABHBFCHAHACCFCGCEADFCFG,False +304,32.0,22.0,21.0,20.0,17.0,21.0,22.0,16.0,HABACGCBCGHGHADEGABAFHHGFCCGFFFHFHAHAGACFGEEAHAHABABFBAEAEDGDBDFFFFEGHGDDDCHFAFGECACECECEDFBEAAFBCGAGECECFCFCBGGADADGHACAEBHAHABGGDDADCDADBBBGHEFEDDDGEFBDBDBCBABCBAAAACFGB,False +305,22.0,14.0,10.0,9.0,20.0,15.0,19.0,12.0,GAGABHEFGHGABAEDECGAFABBEFEAECCAAHGHBEEEEEFHFGFGAEAGAGDGHGFAAAHAGAGFBECEFFBBGHGFCBCGCADEDBDBDBDFEECEBEDGAAEAFAHHBFCFCDHGH,False +306,7.0,13.0,6.0,7.0,4.0,5.0,5.0,12.0,BABAFAHDFDGBHHEHBDACHGHGDDBDHFFAFACEBEBEBHBCAHBHDHCGBHBCGCB,False +307,27.0,19.0,23.0,17.0,31.0,29.0,21.0,17.0,FADCDEGEBEGHDAEFEAEBHBCBAFAHAFGEGFBFCAHAHCCBDFHGCEFFCFEFEAEAFCBDADADHDFBFBEBADFCFEFBFBFDFCFGFEAHBBCCCCHHBHAAEGEBECEGDAEFDGECEFEHGAGEFEDGBABABHDHDCDCGHAEACAGFCECGGHEDCFAAAGAGCEHEGEGFGFE,False +308,16.0,23.0,23.0,25.0,22.0,21.0,28.0,27.0,BHGEFEDACAGADADGDGDBBFBCGGHGFCFCEHHDCDCEGFCFBEBEHDHCHCBEDDHBBEBGGFDECHCHCBFDFBGEHEGEDEGAHDBDAHGBGDGBCFCGCGBBAFAFABBBFGFHAHAEAGFFFGDDCABHECEDEBEHDGDEDEGCHCDCACHCAFGGGHFHFHGHGCAEHHHHDDBEF,False +309,11.0,10.0,14.0,4.0,9.0,15.0,8.0,17.0,CECHBGAHBHAHGCACBEFEFDCCCCCBCDCGAFFFFFBCBAFHFHFHDAEAHGHBHBHEHBHCGFBHAAGEFEFEGHAHDFFCAEHG,False +310,7.0,7.0,11.0,8.0,8.0,14.0,8.0,4.0,AFACGFEEDBGHDDADFCFCFCFDBGBHEHFAGDCACFCFEFBDBGBEBFCFCFCADGEGEAHCFGE,False +311,1.0,3.0,3.0,4.0,1.0,4.0,5.0,3.0,DHHBHDGDGCFAFGEBCBCGFGFD,False +312,9.0,6.0,12.0,3.0,7.0,3.0,4.0,5.0,AAEAECGCDFDHACECEAEBHBACCHCHEGCGCHCACBBAFAFCDGEBB,True +313,10.0,20.0,11.0,11.0,10.0,21.0,14.0,10.0,FHEBEBCAHAHBFGFGHGFAFCFDBDFDCHBECCCHEACABDGFBFEFAFAHGBFBDBDBFCCCEBFGGBGFAFABEEAEGBBFFDFBFBDBGBGCGDEDHFHDGGH,False +314,11.0,11.0,19.0,12.0,11.0,7.0,10.0,11.0,GBHBFGDABADADBDCDADHBGCECHCHCGCEAGCGCDCFEAGAEAEHECEFFBECDCGEHCBBBCGDHDBDADCFFEFCACAEBHHCHGHC,False +315,15.0,20.0,19.0,23.0,12.0,16.0,12.0,15.0,CCCCEFDBDHDCDFDCHFHFDEBACECHCGGFGAHDDDBACFFFDFBBABABDBACADAHCHDGCFFBHHDHDHGCCACEDBDECEHEBABHFDDDDGEFBFBGBEBFAGAGBGHEHDFEBABAEADBCGCG,False +316,6.0,8.0,6.0,3.0,8.0,2.0,0.0,9.0,CBCDFDHABAFEHBHBHECEBECHHBEEECEHAHCDAHABAB,True +317,5.0,12.0,12.0,7.0,8.0,8.0,7.0,11.0,CHGBGBFBFDABACAFFFCECHCEGDBBGHCCBGDGFGHEHDHCHBBCCECEBEAEAEHDCDHHBHBDFF,False +318,19.0,29.0,24.0,19.0,24.0,39.0,20.0,15.0,CFEFGHBHFHCEABFCCCFFEFEGBGBAHAHDBABCBGBGBGAGAGABHCCCFFFEHEDGBHEEDHDEDBHFDBCBGBFCFBEDFAFCFGACEFGFGAAFFFFDFEFECCGEGBDAAECECABEFDFCEAEAHFDBABDCHGBGBGBCACBCBEFGFGFCFHDDFAEHDFFEDDFDFBFBEBEBFHFCD,False +319,8.0,5.0,5.0,2.0,5.0,4.0,3.0,7.0,HAAEAHDHCBDEAHCGFGCEABAEAFAFHFHBHBCBCEG,False +320,4.0,0.0,2.0,0.0,3.0,0.0,0.0,1.0,CACAEAHAEE,True +321,19.0,25.0,20.0,14.0,21.0,25.0,19.0,10.0,ECEAHAGAGDCFHAHAHABEGAGBEBFFFFFGFDFDFGCDCBABEBGBFFFAGADFDGHGABAHAGCBABGDGEEACAEDBCBCEEFHGDDCBCEGEFEBEBFGCHBHBEDFHBCGEBCDCFCEBEFEBCBCBCBAGFFAFAFDCGEEFDCBF,False +322,4.0,3.0,7.0,8.0,3.0,3.0,6.0,6.0,AGDFDFDAGECEDDHCHGHCBFDEBCBCHCHCDDAHAGGG,True +323,20.0,23.0,10.0,13.0,14.0,23.0,24.0,21.0,AGAFFGHGEBBCDCEEEGBFAHAEGEGCGFGAAEBGHEBDGAGEBABEFCHAHADFBFDFBHBHBGBEBFBFHCACGCGBFBFAHAHFEFDBGGGBGFGBBEDHGHGHFHDHDGDHBFBFDFHFHFACADAGEFHCAADHBHCADFGA,False +324,6.0,10.0,13.0,15.0,5.0,10.0,12.0,7.0,ABBDDDDGDHDCBBHCHGDGBAEGEGHDBCFGFBEBADGCGCGHFFFFFCFCBDBDGDCAAAFDHCCCECDFDHCGEG,False +325,14.0,17.0,16.0,18.0,24.0,25.0,25.0,12.0,EAGDFBFEHEFGADABCCEGEAEGEGHGBFBDEAEDHDFEFDHCHGBGEECDCDCDCHCDEAEACCBEGAGEBFBFBFCCGFBEBCCDEDFDHHGAGAGEEFFFFFBGHGHBDECEBAFAFDFDGGGAHBEFGFGFHDGDEFGCABFBFGG,False +326,10.0,8.0,13.0,7.0,11.0,10.0,9.0,12.0,HGFCFAFCFAGADEDBHFCFCHHAHACEBECCCCEGEFEFGDBFBHBGBCEEABCECAADDEDHDHBGEGAHCHFHGAGH,False +327,13.0,9.0,7.0,7.0,11.0,9.0,9.0,4.0,EFEGEFABAFHDBFAFGGEBEFECCCEFFDADBDGEGAGABABABFBDDAEAHAHGHEAAGDECCCGCB,False +328,11.0,7.0,14.0,13.0,15.0,16.0,11.0,12.0,HHHHFDGEGFHFHGDGCCHFBFEDBAHGFCDCGGDDACACEDBGEDEHHGHEFEFCFGFAAACADHFAFCFCFCBDBAEEEEGDFBFAEAEDEDEBCCC,False +329,14.0,9.0,16.0,7.0,13.0,4.0,16.0,18.0,GCAEFCFCACAEDGGEGBGBGBHBHAHECAAAAHAHECECHGHADDCBCFCHHGAGEGDGEAECGBHDACECBHDCDGHCHGEBHBHEHCFGEGHHA,False +330,6.0,12.0,18.0,17.0,8.0,10.0,10.0,6.0,GGFCECDCDCAABEBEHEFDDADGDBDHGFBFBEDHDFBHGGCBCBCDCBCHDGCBCBEDCDGDBECADACCCFEFGFGFHDADFCC,False +331,11.0,25.0,21.0,16.0,17.0,27.0,21.0,23.0,FFFCHCBCGHHHGGCEBEDFCHAEFCFHDBDBABFBFEFBFHDHFBGCACHHFBFDFGFBHHDBEFAFAFHFEEEGEGEGEDBHCDCACHHGFGFHHBDBDBHCHGEDBDECECECFGBDBCEGGGGCCBCAAADAHBBBGBGFGHDAEFGFBBGHDCFCF,False +332,31.0,34.0,15.0,23.0,18.0,19.0,14.0,23.0,HBFBAAACBDEABCHDHAHDFEFHAAACDEBHBHBHBCBHBHBGCAFGBGBFFDFGAEAEBDFFADADACADDDHAHAEEBFDFGCCCFCAEGBCBAHCGEEEEEEBFDFEHBBBABAHADBDEDFGHHBHBDDABBHBHDHFCFCGEBAAAEGFDFDGDBBBAGAGABAGHBHCAD,False +333,20.0,17.0,9.0,14.0,13.0,13.0,13.0,14.0,ABGCECACBHDHGEEHEHBDAAAFDEDGDFAFABCCGHBABEBEGADADFDEHEHEGBGAHADDHHGHGCGFFABAFDBDHABEFDCDFFAFBEBHBAFAFABABGCECHGBG,False +334,7.0,5.0,2.0,4.0,6.0,6.0,4.0,9.0,GCGBFBHAHEBEAEDCGEAEHHFHAHABFGFHFHDEDADAFHB,False +335,17.0,13.0,10.0,10.0,9.0,12.0,9.0,20.0,AGHHAHAHCBABFGADADEFEFEDBBBBHHGHDHBCECEHFHFHBHAHDEAEAEBEHACAGADHCHBGGFFFHACBDFDAGHCDGDCFCACFHFBBHGAA,False +336,10.0,13.0,6.0,5.0,11.0,4.0,11.0,9.0,EGEBEBEGEBAHEFBCBEHGDFHFAFCBHBGDABHGGGBGCGBABADHDCEABABADAEEGAGCHCHEH,False +337,17.0,16.0,15.0,8.0,14.0,17.0,17.0,24.0,HBGBABHBHDFFAHAHAGAEAEAFACGCBCECFGDGCCEFEFHHHABGFCHDHGBCBHBDGDHEHGHCFCHGHDHFHFBFDABHBGBAFHEEGEGECBAGEHBHCHEFEADCBFGHCEFGCGFAAAAF,False +338,18.0,20.0,22.0,16.0,18.0,27.0,14.0,22.0,AEAEAEAFHDHAAEFBDHGFGFCAAAGADFFEFBADCHCHEGBBEBGFGFGEHEDCFHAEBHCDCBCGAECGCHCHBFBEBHHHGCBHFDDGHHHCHBDEDECBDFEFBFGFCFBFBCBFBFCDEAFDGABADADBFFFFECECADHHHCHCFCFCG,False +339,24.0,25.0,25.0,23.0,21.0,21.0,28.0,25.0,ABAFDFCFCGHGCDBDGEGEGCAAEBHBHGHGHDADCGCHFECEBDHDABHGCGHDHEEEBFBFBDDCDGEEEHBFFCFBFAFAFGCCCHGGFGCACHEDEHGDDBHEHDACAFHEABGCACABDBEBFDGHGHFHEAEAEADACGGBBBCGCGDGBGBFCHAHAHFBABFCEHBADGDEBACGCGFAFDHD,False +340,14.0,19.0,9.0,8.0,9.0,16.0,11.0,11.0,CAADABAEACBCBGAADHBFFFBDBDEGABHHHAEFHBCFHBEBGFDFBFBDBDBDAEGEGEFCGBFBAEGBGFGFHFHFGFCBCAAGAFEHHHCBC,False +341,2.0,6.0,2.0,4.0,1.0,4.0,1.0,1.0,ECBDBFAFDFDBGBHBCBAFD,True +342,10.0,9.0,6.0,7.0,9.0,12.0,7.0,13.0,AEAHAHFEGEGBGAEBBHFDBGBHHGHAFAFAFHFDDCDHECFCACFHFHCDCDHBEBFAFGFABEEEGBDHH,False +343,12.0,23.0,13.0,17.0,19.0,18.0,25.0,20.0,GCGCGCFABHCGAFCFDFBHBHEECDDBEHEAEABABAHHFFDFGEBEBGCABAGGEGEDEDHBCFDHDGBGDGHAEAGDHAEEECHHFBDGCFCDBDHFHBBBDHHCBEHFHGGGFGFBEBEFEFCFGFGHGDGDBHBGBABDGEG,False +344,8.0,19.0,17.0,14.0,18.0,17.0,16.0,26.0,BFBHCHCACDDFCHEHAFAFEEEDHGHBEEFADGGFGEEDEDEFEFBFBHHGHGHDEFCGCGHDHDBCHDBCFCGEBHBHEHFDEAEBEGCGBHBFBHBCBCBCBGACCHHHGHFDFCFHGDGHEHDCBAAFHBG,False +345,14.0,25.0,9.0,16.0,24.0,29.0,24.0,20.0,BDBDFDFEGEDADGGGGDFAABHGFGFEBHFECHCEDBABFBEDGGCFCEAAHGHFBBHHHHHHEBEBFAEEBEDGDCHEFBFBFBHEGEGEAEBGGCAFFGDGAGAGHFFFFFGCHAHBHDEDEFHBBBFDFHFBFBFBHDEFGBEDEGEGBAFFCACEG,False +346,20.0,21.0,26.0,20.0,28.0,15.0,21.0,20.0,EDEDFHFHEDCCECEHEHCGBBAEFDDHBGBEBGAEHECGCACECGCGCDEHCAFAECHBBDGDFCFBBHBEBEHDGDBDCAGACAHAHDHCEBEHEACDDDFFAGAFAFCGEACACGEEAHAGAGAGEFEFHFBGCHBDBHBCGDGCECHDHFBFDCGCBBEBDAEGEGE,False +347,9.0,10.0,7.0,7.0,9.0,11.0,7.0,1.0,DAFCBCBAFDEGEGEFAADGEGEAEAFGFBFEFCFGFCFHEDCBGBEBAFDDABCBABDBC,False +348,23.0,21.0,22.0,23.0,12.0,21.0,19.0,12.0,DBGBGFCCGCDHGFGFGFDCDEAEAFBFBHGHBCBABAFFFBBAFHFCDBFECCDCACAEADFDEDGCFCHBBBBDFDCGAHFGEADDGHFFDADEGEAEFEDECACACAFADCFCAGBBABEDGDHCGCACACHBDGGAGBGBHAHADDDHB,False +349,24.0,18.0,28.0,33.0,14.0,23.0,32.0,22.0,DBDACACDEGGCFCBGBHFGDGDEDHHADCFBFDFDAAFAGDGCFCECEGDGFBAGHDDCDCDGHCFFAFGDGDHDHFGGBGHDCDCAHFEDBFBFCDDEDGHAHADABHBEAAACADGBGAGAFHCCGFGCGDGAEAGDGHFHFEBAHCFCFGGGEGEGAGHBBBDCCHCHFHCHDFDBDCDEHECBCEAABC,False +350,8.0,4.0,6.0,7.0,7.0,4.0,16.0,7.0,EDGFGACAGBHBEBAGACAGEEEEEGGAGCGCDAFHGDCDHGHCHGBGAFDFDGGGDHH,False +351,14.0,22.0,13.0,15.0,4.0,11.0,14.0,13.0,ABCCHHFHCDBDBDBCCGCGFFDFBFGGBAHADDGDCDCBAHABEFHBBDBDBDBEBEBGDAEABDGFHBHGAGCBFHHHHHACGBGACFBBDGDBFAGAGACACF,False +352,23.0,10.0,18.0,19.0,18.0,25.0,14.0,15.0,GFADHDHFCGCBFFFHHEDFDHAEEFECAGBGEAHAHADAEGCBFBFEGEFHHEGGCFCHHAHAHEBAADAGBEBEDEDGFEFAFADADFGFAFCECECFFAFACACHCDFDADCDGGFDHCCCCDGDAFBFBEADBDAECF,False +353,28.0,26.0,15.0,29.0,24.0,17.0,31.0,29.0,EFGDADGCGBGBGBEAEHGHFDDEDEDEGHGEGEGHGHEHGDGBGFEAEGDCHCHDHFHEHAGDHDFEBEBEBEDCDCACAFGFCABFEGBGAGHHBDBABABHHAHAECEAGBGBHBFEDHCFCDGAFDHBEACFHHGDADHCFCBAAHFFGFDADBBEBHACABAHGDGBEAFABDBGGGGDDDAAHDDDHCHAABE,False +354,2.0,5.0,6.0,7.0,4.0,6.0,4.0,6.0,BHGHAECCCFADBDHDEDBFBHDCDCDFGCGFGFHHEFEB,False +355,6.0,5.0,6.0,6.0,6.0,7.0,2.0,4.0,HFHCGCGBFEAAAHAFBCBDEDEDEDCDFFABBCFCADFEHE,False +356,6.0,7.0,14.0,10.0,18.0,19.0,15.0,16.0,FBEHFGEHFDCDGGGEHCDCDFFFHBABDFDFHCCFEFECEHEFCAAGFGBCBFGFEBCACACDFFGHGBEHEHEHFHCCEGEGEGECAHEDEDGDGEHHHGHFF,False +357,14.0,24.0,11.0,19.0,13.0,13.0,20.0,12.0,CAHGEBBDBFBEGHAEDBDHDGDGECACACEFBDBFFGADBHBCCDCDHDEGEAFAFEGBFBABHFHAEDEDGHGBEBGBGBGFFBCGEGDAFAFAHAEBCGDDAGHHBCBDBDBFBDBDCGGGGH,False +358,14.0,23.0,16.0,16.0,14.0,16.0,6.0,16.0,HBCBHFHFHDBAGAEDCCCBFDFHFHDHDHGHABCFCFAGEGBBBFDADADBEBHFCFDFCBADDBCBCBCAEGEFCBABAFAHBFBEBEBCCEEHEDECBFAEHGADHDHEHBDEFBCDA,False +359,13.0,21.0,20.0,21.0,14.0,16.0,20.0,15.0,GFDBDCACAEBEBEBHBCBCECEGACHCHAHAGGBADADBDFCFHGDGDGEBHBDGGFGFGDBDAGABDGDGEHFDAEFFGFDHEBCCDCHCFCECHGDBCEHEFDFDABEBGDGHACFFBDCEAFGDBCGCBCFHBHBH,False +360,2.0,2.0,1.0,1.0,3.0,6.0,2.0,3.0,GFFFEFEBDBEHGCAHAHFF,True +361,14.0,17.0,14.0,17.0,23.0,22.0,11.0,18.0,DHACABDDDFEFBCAEAEAEFCFEFCFDFHFAFBCBCHGHFHEAEGBHBGCFCHAEBEFECECGFEDEFCCHAFAFAFADGHGBGDHDEDAHBHBHGEEBDHDBEEHGDEDEFBFBFHFGFBDAEBDGCHEEDCHB,False +362,7.0,7.0,14.0,4.0,6.0,6.0,6.0,3.0,CCBCGEGCAFAEADAGFGFCFCBCGHBBDBCGEAHAFCDCACBCHCEEFECBD,False +363,10.0,8.0,17.0,16.0,17.0,20.0,8.0,12.0,FEADABEGEHEBEBECFCDCHBHCAEEGHCFGFGFHHEFEFDFGFDECCACHFFFCDCGADAFGDCDCDCEFFFFAHAHBEECCDADAFFBEDEDEDHCFCDBHGHDB,False +364,8.0,4.0,4.0,12.0,13.0,9.0,10.0,11.0,FFHEHDFFAGEGEHEHFGDDDEDECEDABHFGFGDGAFADAEECGGABDBGHHCDCBGFDHDHAEAEHEHE,False +365,6.0,2.0,5.0,1.0,4.0,5.0,1.0,5.0,FEACAGFEFHCEABABAHFFEHAHCHCDC,True +366,11.0,5.0,9.0,15.0,4.0,9.0,12.0,5.0,CCFDEDFDFEFEHDBDCDHGGGGDFDAACADABFGCBCAGAFDFCGCGAHAGAHDBDHCGEBFDADADGG,True +367,22.0,11.0,14.0,10.0,20.0,19.0,35.0,19.0,DGGGBCECGDADABABHEHBHGAGHGFAFAGBGBGEEACACFEFGGGEFHCDEEBEBAHCEFFFFHAHAHGFECBHGGEGEHAHFGBDFHEEGCGFDAAAGEGAGFEFHFGAGAGDHAACAGHGCGAGDGBFHFGCGCECEHFHDGEGCD,False +368,2.0,3.0,4.0,0.0,3.0,2.0,2.0,2.0,BCECECHFHFAGEGBBCA,False +369,2.0,7.0,10.0,3.0,12.0,8.0,6.0,9.0,HHDHDCCEGEFFFHCBBHDEGEHEFEFEFEFBCBEBHBCCGCHEHBGGACECEFGAC,True +370,17.0,20.0,13.0,14.0,12.0,20.0,18.0,16.0,HEFEBECCHDECGCEBBGCDBDBDGFGFAFHGDDFDHBBBFAGDFAGACEFHGBFDFHFHFHCGBEDHFCFCFGAAEDECEFBFAHABACAGAGACAHABFBFGEGDBFBHBHDHDGBABAGCGEBAHGH,False +371,14.0,16.0,16.0,7.0,13.0,5.0,11.0,14.0,GBGBEHFHFBBBECAABDEABAGAEDEDBCEGECCACAGACACBCHCECEGABDBEBHBHFHCDAEADHCHCHFHCEABBCDHEGFGCHBGGHGHA,False +372,9.0,15.0,11.0,10.0,12.0,17.0,13.0,14.0,BEBEBGFFBFGFDFGCGCGFHDGGCFAFAFBFDHDEAEHEHAFBFEGHHEBGAGCHHHDDCECGCABFBFHFEDEDHBBCBGBCAGACAHBECEDDHBHFF,False +373,14.0,9.0,8.0,14.0,6.0,19.0,18.0,14.0,BHEFAHAHDDDDFBFDFGFEFHGBBFAAAGADHGBFCDGBEFGFCHHGFGHGHFHGEGAGEEAGDDABGGCCCBHBHCHDFAFAFAFGFDFDADADCGCGHF,False +374,13.0,6.0,13.0,5.0,8.0,10.0,12.0,6.0,CBGADAHAHAFAFGCGFGCDEAEADADCBHDFAACCCAFHBBCEGEGECFHAEBEHCGFGFGEGCGCFCGABF,False +375,8.0,5.0,6.0,3.0,11.0,9.0,8.0,4.0,EEEEHFFBFGGCGHGEBABEEFCFCBHGDBHFAFAFDFGAGDGAECECECAAAE,False +376,6.0,8.0,6.0,9.0,8.0,5.0,12.0,5.0,AEGEBACACHCGGHDBDBCEGEBEBHFDDGDCDBDBEGCAFBFGGGEHEAADFDFHGGG,False +377,2.0,3.0,2.0,5.0,6.0,4.0,2.0,2.0,EDEDECEBHBGFGAEADFHBDFEFDC,True +378,18.0,11.0,12.0,20.0,13.0,19.0,14.0,21.0,GAEHGHAADADADBFCECDCFCGDDFCGHAADFFFGHBHFDCDBFHFHGHFAGAGABADDHAEDECFFFAFAFDEDEBABFBGGHBCBAACBHHHFFEDEDADBEHFHGCGEEDHDCDGHGHEHEHCH,False +379,15.0,10.0,10.0,14.0,7.0,13.0,13.0,11.0,FHGHGHBBCDDDDABABGCEDADCHGAAHAFCFBDBDADFCFDDHCHFHAHCHCBCGGAACAHGGGGAGBEDFDFEAGDGFEBEFFAFAEBEF,False +380,20.0,20.0,27.0,28.0,18.0,28.0,19.0,15.0,FAEAEHHHHHHECBHFFFCFCDAGFGDEDCDCBGFFCGBGEGBAEAGFCADGGBEBEFHFDCBAEFDFDEDAHAHGEDAGBGFEBEGFDDDFDFAFCCCCCCBCBCGCGCACDDBFAFBCDADCDEDBCBCGHGFGBBAFDCDHBHDDBDCECACDFDGABFEDEAEFHHAAFFF,False +381,9.0,4.0,8.0,8.0,10.0,3.0,5.0,2.0,DEDECFCECEDAAACHEGDDFDFCACECGAABDGCHBEBGDGBAEAEAE,True +382,28.0,23.0,23.0,25.0,22.0,19.0,22.0,24.0,EBAHHEDEDBDHHGADFEFEHDHDGFFDFDADHDGEACBEHEFGDGAGAGEBCDCBBAFECHGGBHCHCGGGCGAFCHCHBBEBFBFHFCGCGEDEAAADABABADFEFDCDCECDCHCHCBAAAAAAHAFEGEADCCFHFEBEBFHDHFAAAGCBBBCDHDEDFBEGHCBDBGHGCGHDEAGABA,False +383,4.0,5.0,2.0,2.0,4.0,7.0,4.0,2.0,FAFBFGCGAGAGFBDEFEFHABFBDCHEBE,False +384,23.0,10.0,11.0,21.0,17.0,14.0,20.0,15.0,CBEFFDDBFAGHDAGAGAGDDBEGCCCDCBHHEAEFGFEEEHEACACAGAGBDAAHFHFAFADEHCACGDAEEFGGHEHBCDAGAEDEBFGHDHEHDHFHAGAGAGAFAFABBCDGGGDBDGDEDEDFDHD,False +385,16.0,15.0,15.0,12.0,17.0,20.0,20.0,23.0,FGBHBHAHAHBDFEFEBCAEEDEAHBHBHEFDCBAFCFAFAGHGHGACDHBCAEHGHBABFCFDGDFDFHFDBGFGHHACADACHCGBEBEHEACGEGFGFGDGEGEGECEADACBGFHHDFFHFHFGGBHCGCEEHC,False +386,22.0,28.0,19.0,25.0,19.0,24.0,12.0,27.0,BHDGBHDFDFDBABGDHAFAECECBCBCFCBEBHHHEEEBAFDFAFADECBDFDFAEHBHEHEGEADHHHFHFHDBFHAHADADFDFCAHBCGCDCBBBGBFAFCFHAGADDBFEFEAAHCDCECBDFFHFHBHBFEDCACAGEFDHGBEHGBCBHEEGAGHBDBDGHADADCBCB,False +387,16.0,23.0,23.0,12.0,27.0,6.0,20.0,14.0,EDEBGBEBCGGHCACBHBEGAGHGCGEGFCHBDCHGHBHGDADADBBCHCBEBACGEGEGEBABABDEEHECCCCBBBGAGAEAGFGHACCBBABAGFBEEEEEECGDDCDHEEEAEAECDCECGCFHFCBCEADDHEBFH,False +388,29.0,22.0,29.0,26.0,26.0,22.0,19.0,18.0,CECEGHFBFDDCDHGAFBGDFAAHACACAEEBEACFCAEECCGCGCFFFABGBGDCDGDEAEABHBHBFBHAHDCECECHFEFBACDDDEHAGABADFDFDBDBDECECEDHDAAAAEBEGAAADGFBFADACHEAACFGFGCGEHFHFCCCDGGBCEGFAFEBHCDAGBCBCDCEEGDBDBDHFHEBEHH,False +389,6.0,5.0,9.0,6.0,6.0,10.0,3.0,6.0,AFFFACCCEHHHHACDFDEGCBCDEDCFBFBDBFHFHADGCGCEFAFAEBE,False +390,5.0,5.0,8.0,6.0,3.0,4.0,2.0,9.0,CHCGBFDADACBFDFCHHDHDHCGCBFAEAEAECHCHBBDHH,False +391,17.0,18.0,29.0,20.0,13.0,16.0,17.0,22.0,GDCDGHHBEBFCFHGHAAAHBCDCDHFHEHBDDDDDCDCACHEBDBCBFDACBCBHACCDCGGGGCBCFCFBACADHHCFCADHHHGCBBGDGCGEEHEACAGGFGCABABDBEECECECFAFAGHHDHDFBFGFHECEFDFAHBHFGCACE,False +392,4.0,11.0,10.0,5.0,8.0,5.0,3.0,15.0,HHHHEEDDBGHGFABEBECCBHBCBEDECBCHCBEFEHDBDHAHBHFAGCHCHCBCAHFHF,True +393,5.0,6.0,6.0,2.0,4.0,4.0,5.0,6.0,HGFGHHHAGCGEFEBDFDAAHAFCBCBCECBGBEBHCA,False +394,21.0,28.0,17.0,22.0,17.0,15.0,15.0,14.0,DHAAAAFCDBDBDGGABBBCHCACGHFBBBBBBBAAAAFBBBBBEGEABCGFDHEHEDBAADEDEDEHCFEBEGDHFGGECDCHCHBDCEFEHDBDBDBDCECGCBFDGBADHGGFAFAFACEGEFDFBABFFEGDAACACHEHDHDCG,False +395,17.0,17.0,23.0,13.0,25.0,16.0,32.0,27.0,ACFCFGGGEEHEGGDEHBACACECEFEFHDEDFDGEGBGFHCCACEEFDACHGHGHBEEHBACCCCHCEFDAGAGEGCBHBHBGGGDGCFAHGHGHCAEFBBBHBGBHHEHEBGGEGEFHFHFHGHGCFCGHGDEDAAAGCBBBCHAEAHDHDFGGGEGBAHECDFDCAE,False +396,2.0,4.0,1.0,7.0,6.0,10.0,8.0,9.0,GCGFGFGHBFAEGFHFHGBDHEFEDHDEFEFDFEFBGHHAHGDBDHD,True +397,12.0,14.0,13.0,17.0,13.0,20.0,12.0,15.0,CEBHFCBGHGEGEACAHBHBDBGBADFDHDFDADHHEHFHBAAFACECECEDDGDGDCCCHCGBBDGFBECGDGACFFFFFFDHDHAEFEFBBGBFHFHECAFDBEHDFAFAEGFD,False +398,28.0,19.0,7.0,24.0,27.0,19.0,20.0,15.0,DHEAEADDHGAAHAGEHEBDBDHFCFEFEFEGAGHGBFHECAAGDCDADFCHDADADFDHGBGAEHDGFBFAFAFEFEFEHCAAAGGBBABDBCEADADFEGEFHADEGGGEGEGBGBDADEEBDBDHEEEDADEBBFHEEFCFEFAAAGABABDBHBG,False +399,0.0,3.0,1.0,3.0,3.0,3.0,0.0,4.0,DDHFBFEFDHBHCHEBE,True +400,14.0,15.0,8.0,10.0,12.0,16.0,15.0,13.0,BABABGHFHEHEAEBFGHDBCBGDCFFGAGDGFEFEFEFHDCAGAGHHAHACBCBGAGEGEDBDHDEBCACBHAHCFAFEBEDFFFBFGEGFABHGDADFBHG,False +401,11.0,5.0,16.0,15.0,7.0,18.0,6.0,17.0,EGDHHBGCGFFFFECHDAFAFBFDHGHAACFFFAEHBFDFHEHDFDFDABBEAFCCCCCCCFHAGADDDCCEHEHCHDHAHFHCCCFDHDHDADG,True +402,3.0,10.0,24.0,13.0,15.0,13.0,11.0,19.0,CBBEDHAHBDBDBGCECHHDHGHDCGCGEHCHCGCEEEEHFHFECEGBDDFBHEDBDADGFHCHCGCBCDCEAFGFGHGHCECFDECCCCCDHHEBFHFCFCEHFFCF,False +403,1.0,2.0,2.0,2.0,0.0,1.0,2.0,2.0,DGDABGBCHCHF,False +404,5.0,16.0,6.0,12.0,8.0,5.0,12.0,9.0,DGDHBCBCHGEEHEFGFBAGABADDCDBBBBBGAGEEDCDGHGHFHBHGGCEEDBDBDBCBDBGFAEBHFHGD,True +405,21.0,16.0,12.0,16.0,13.0,10.0,25.0,18.0,GFEFBFGGBGBGBHFHEBEBGBGFGFCEAGCDHAABHBEGCGHDHAHDCEGDGDBFGCAAAAEAGADFDGDAACACECEBFDHBAEACHGHAHDEDEFHHHBGEGACDBAGGBCBHHCDGAGDGHGHADAD,False +406,4.0,4.0,3.0,5.0,1.0,0.0,4.0,3.0,GBDDABCBCGDGDCHBHDHAGAEA,True +407,16.0,7.0,6.0,14.0,13.0,6.0,14.0,8.0,BFCAAAAAEFEBDFCFCADGDBDBDAGAHAEDEGHGHGFDBDGAEHEAEAGCEDHAEADGDAFADGGEGHGHDEBEHDGBGCCE,True +408,12.0,15.0,11.0,21.0,18.0,14.0,12.0,11.0,DBDBDBDBCBGGABCEFEFGGDBDAAAEHEFEBGBECCFCBGEEAEHCBFEFHFCEBFBHGADFDACABEBEAECDCGFDDDDDDHGEGFDHDHDHFCDDEDGAAFAFHHGHEE,False +409,20.0,21.0,28.0,22.0,20.0,26.0,20.0,22.0,FCFDFHADGDHDHBBCCHHDHDHDGAABAGCGCDCDFFFAEAFBHHGHCHEFEGBDCDAAHABBCFHFEEGEFFFCHCDBDEDEFEDAFAFABEHCCCEBHBDGDECCAAACDGFFEDHDFBHBAGAEAEFECGGGCHCDAHBGBDBCBEHGFCFCFCFCEGEGHFCBGFGCGCEABBB,False +410,3.0,1.0,3.0,3.0,0.0,0.0,1.0,2.0,DGACBHDHDCACA,True +411,10.0,24.0,18.0,15.0,16.0,10.0,24.0,18.0,HHFBFECHGHAHFGGDCBCBCEGHGBBAAGCCHCBDBGBDHHHBFBDBGGCGHGABABACEHEHCDGDECBAAEFGGDGEADDDHDHBEBEGEFEGEGCGDGDEDBCCCHCEBEDCGFGHGEGFBFBACHBBBBF,False +412,7.0,7.0,14.0,10.0,10.0,6.0,9.0,5.0,GEDFDFBAGCDABADDGAHEDEDFDCDCDFHCBCBCGCHBGCFCAEEEEEGEGCCCHHGCBEBCAGAF,False +413,1.0,1.0,2.0,0.0,2.0,2.0,3.0,2.0,FGCGCHEHEABGF,True +414,3.0,7.0,4.0,3.0,7.0,6.0,6.0,8.0,HCHGEEBABABFBEGFGAGBDFDEHEFCFBHHHFHCHCBEEGGD,False +415,17.0,22.0,23.0,22.0,24.0,17.0,20.0,16.0,BCBGBADDEHEBECCCCDGAGEGEAACEHEHGFABAEHECECFCGCECDBACAHADECGCBBFGFEHEFGDGEGCGFGDHDCBCAFGDGDAEFHFCFBEEHEBDDFHHHBAFAHDEDGDBDEDECFCFHFAGCFFAEGDGDADCBBBBCGHHABBBBBDED,False +416,23.0,23.0,29.0,23.0,28.0,15.0,36.0,18.0,HDFEEHAHFECBCGDFDFBAGABBGGADFDGEGECECGDHCECECEDEDACACGEGCGFBCBCACEEDEGGABHEDCHBGGGHGCGCBDBCCCEHEBGBCDDGGHGEFEGBBBDBAFAFAGBFFHHADEGEDBCCCACGCDCGEAHAEADGGGDGDBFBFCGCGBGBGACAHAHGEFDADEHEHAFGHBHDEAEA,False +417,6.0,3.0,6.0,6.0,13.0,9.0,7.0,12.0,HGCCECEAEHGHGCFAFHDDBDEGBGHHEEDAFGFHEHAAADBCHCGFEEEHEHEFEFDFHF,False +418,7.0,7.0,9.0,13.0,10.0,16.0,6.0,11.0,HEFFFEDECCHHBHFDFACACEDHDBDBDBDFCFDEDEBHGEFFAFADAFHGBGCGCFDEAHDFDHGHFHCGEFEFABC,False +419,6.0,2.0,4.0,3.0,3.0,0.0,2.0,0.0,EEBDBAAAACACEGGCCDAD,True +420,20.0,21.0,13.0,17.0,21.0,27.0,25.0,13.0,HAGAGAECCFDBEADDGAGFFDCBFFCABGBEBAGCGBFBGEGEFDCDEBFBEDCAHBHBDFDFBADGFFEGEGEFEFEFHFBBABAHHDGDGBGAGFGFGEEDEDAFAGDHEACACFFGFGFGEDECBFBFHHHGEAFAEAHFBEBGBCHCHGADC,False +421,9.0,14.0,14.0,8.0,6.0,14.0,12.0,12.0,FHFDFDBBBGBEBCBFDGDHFGABCGABBGEAFAHACACHDDFHCBBFHFHFGCHCHGBBHHGCGCACACHCEFEFADDFEFEGGCGCB,False +422,2.0,4.0,4.0,2.0,2.0,3.0,4.0,6.0,HFCFCECBGGGDGBEHFBAHAHBHDHC,False +423,19.0,10.0,8.0,8.0,6.0,9.0,8.0,8.0,DEABABCFEFDAAABFHFAFAFADACCGBABAGHBABABAGHEHCGDGDCDCGEHEGDAABAEHBAGACDFFCFHH,False +424,22.0,16.0,21.0,30.0,13.0,19.0,17.0,12.0,BCBEBDAEAEAHAHGHCBCAAEADGFGDGDCACFCDEGCDHBCADDDDDEABADADADAEGBGBHCGFAFDCDBDFACDBDBCFEHEHAHGFGFGFGECHFHCCGDGACDFDECFDADEBHFFDFDFBFBEHAGCGDFCBGDACBCFDAD,False +425,12.0,15.0,7.0,11.0,10.0,19.0,9.0,9.0,CADACAFHFDDCDBFBDBEBEDEHFABACFFHHGFDFDGDGHAHACCBEFDFGEGEADFFCEGBABAEHHBHBGBEBABGBEFFFFABGFFF,False +426,10.0,14.0,11.0,11.0,11.0,17.0,18.0,9.0,BFBAAEFEHCHGAFEBCFCGCGBGFHFCGGAFAFBFCFHBBFEFEFEBGCECBGBGCDFDBDBDGAGEFEGHGHAADEGCGHDBAEGDDDDCDFGFGABHH,False +427,37.0,20.0,35.0,16.0,24.0,26.0,23.0,17.0,AGAEEHGHGCCCGBGCHCHCHFGGAAAEAEAFHCHCGCACADEEECBABEFEHDFBFEEBBBCEFAFADACAFFCFDHDGBFFACDGDFDBBBCGCBAAAEAECGCDHFBDBCAAGACACAFAGGBEHECECEABFEGDFDHHAAAACHCHGHCHABEGCGFACCECFFBFBABAGFFDAECEDEFFACGCGAGCDFD,False +428,16.0,17.0,31.0,28.0,15.0,17.0,26.0,26.0,FGFCCACBEDEDBCGCGFDCAAECEAAFFGGGGHCHCAGDGDBHBHFHFHFHDHAGGDDADHDHBACGCGEDHBCDFDGDHDCCCBBBBGCCCCFBDDDBCCCHCFEHHGFBFCCAAGGDADGDHEHAGCGCBDBFBFEGAGEGHCFDHHHHEHEBEHDFDGDHAAECCCEDEDGH,False +429,8.0,4.0,6.0,7.0,12.0,5.0,7.0,6.0,AAHAGBFHFCEAEBECGFGFGEEECBCDCAEHEAEDEDHGHBCFDGEGDHDEDAA,False +430,5.0,7.0,8.0,4.0,4.0,3.0,11.0,4.0,HGDCHCBCBFGAGBGBEDHAEAEGFGCGEGAFCGCGDHDBBBCCGA,True +431,8.0,19.0,9.0,16.0,16.0,15.0,11.0,12.0,FABCEHHCGDGDFDFHFAEDGDFDFBBBBFEDEAGBEEEFEGEBEFDDGBBAAAFHFHEEDCDCGEDBDAEHEHBHBHBFGCDCHEDBFBGHGFBFBCBCGCBAHD,False +432,25.0,23.0,17.0,34.0,27.0,19.0,18.0,34.0,GBHHHFEGGFGFGHBABDBDBHGGEBBDEDHHHHAHFHEHFFFGBDDEAAAAADCDHACAFDBDCGCGDDDHAGBDHGHCHABAFEFEFEFDDBDBABGFAFEEDEDEAEBFDFDHAHABEBEDDDFHCEFEAAAECCBABHDADHCBFGDHEHAGBDHHEHEDEAECEDGCEEHDDGHCHCHEDDHBHCHCACBCG,False +433,11.0,10.0,8.0,8.0,5.0,5.0,7.0,5.0,GEEEBADHCHEBEACABDBDAHABABABCDCGCDABFDCACABGGAGHCHFFDDGFGFB,False +434,8.0,2.0,9.0,3.0,9.0,11.0,9.0,7.0,CECFFFHGHBHCFCFBFHDACEEFCGEDEDAAAGCGCEFFAAGGGHFHFHEGEGECAA,False +435,15.0,9.0,12.0,17.0,12.0,13.0,11.0,8.0,FEFHFAFEDEDBCGGFBHACGCFCHADADAFAEAEADHDBDFHEDEDBBGBDADAGAGEGECCHEAACBCDCEGFGFDADGHHFDFCCCBDGEFADB,False +436,9.0,4.0,4.0,2.0,2.0,7.0,7.0,7.0,HEFBABCEFAFABGGAAACFCFGHBHACGFGAGAGHHDHDHF,True +437,13.0,14.0,15.0,27.0,27.0,6.0,29.0,26.0,DDDEHABAHEHAHDCBGDHFCEGBBHBHADDEAGGEGDGDGCCDCDBDBHBHBAAHGGGGACECEGGGECCDGDGEGADADGFHEEDEGACAGHDDDFDFBEHCHGHFHEEEHEHEHEHEGEFDGDGHBCCEDHBCGDHEEBAGHGEGEGEDHBHCD,True +438,22.0,9.0,13.0,21.0,26.0,17.0,18.0,21.0,GAGEHFHCEGEDAFAHAHEDBDFDABAHEDGDBCAEGDDDGGGGAGEHHHGCCFHHBHBHBHAGECAGDGDGDGEHDFAGCEEFEHEAEAEFFCECFFFBDADFDADADAFEEEEAFAEEBABAHEFDGHEHFCDCDCECHCHFEAH,False +439,24.0,19.0,22.0,19.0,24.0,22.0,19.0,24.0,DCDCAAAAABAFGFDFDHGCGCGBDACCCCEHFACHEDAAEABAHABAEFHFCFCFBBHFHEHEGCGDHFECBBBGBEHEAEAHDGDGHCHFBFEFEBEDFAACDHDFBHADCCEHEHDBFGFHDHDGEGADADEDEBECHFGGAGEFCCBCGFBBAGEHFHGHEHEFECBGA,False +440,23.0,14.0,11.0,16.0,9.0,11.0,13.0,16.0,DCDGBGBAAHECEFGFGAGHHEDGBCFDFGHGEEFADAEGFBAAAABFBFDAACCCEDHHHDDAAEBHCHABCHAHAHABEDGFGBGDDDDDDGAAHACACACABFFHBHBHB,False +441,5.0,9.0,7.0,7.0,5.0,6.0,6.0,2.0,CFDBDGCADBDBDGAAEAEBFBCBFGHBEGDHDECECBCGFGFBFAC,False +442,21.0,17.0,17.0,31.0,26.0,21.0,12.0,20.0,AAAGDEAFCHCBEDDBDBDHCAAHBDBDADHFHFHFHFHFDFEADADHHCHDDCFBFACHDEEEDABADAFEFHCACFFFEFBBEHGDGEGFDDCDGEGECCCCCFCHDEEECGCFDEDGBBDBGGHBFAFEDADFDHEHDHAGDGDBAEEEBEDAHAEBEBEAE,False +443,22.0,20.0,27.0,22.0,26.0,31.0,22.0,17.0,EDEAHFDFEBGFEFHGAFAFEDEAHDFBEDACCCBCBAFADAHFCGHGHDCDCGGHBBGACADFEFEFBFBFBHBHAHAGGGEGAGACECECBAEFFDEECDFECECBCEHDFCABHBCGDHBFBFBFAEDCFFHFCFGFDEDEDGFGFGFBCHEGGCEDGCCHDGFGCCCACEDEAEABABADFDH,False +444,25.0,15.0,17.0,18.0,21.0,13.0,21.0,25.0,GCAFBBBBAFGHBACAFHCECHBEDEHHHEDAHABCGDEAAABDBHAHBEGGDGACDBGGGGHGHGCECEFHFCCGBEEEEEDFCGDGDADADCECBFFCAEAEADGDHAHAHEHDHAHEFEHDGFHFHBDDAHAGAGAGAGEFBHECFCACHDH,False +445,4.0,5.0,1.0,1.0,6.0,3.0,0.0,1.0,FEBBABEBEAFHFEAEAEBDC,True +446,3.0,5.0,3.0,4.0,0.0,2.0,5.0,1.0,DBDAGBGCGCGCBBBAGFDHDFA,True +447,27.0,17.0,19.0,29.0,21.0,26.0,19.0,16.0,AAEEEEFDFHEADAGFGFGAGHFABBBBDADAHFDGCHFDFAFGCCBFFHDHDADEBHGCAHAFCCGCHEEADCBFFDFAFACAEECDCDBHBDCCEDEAGABDBDGGGGHFHFHDEAFDCDAAABAGCGFDFEEEBGAGAHBGDGDFDFDHHACCDCEBEAECEFEFDFDBDB,False +448,12.0,3.0,7.0,7.0,6.0,6.0,10.0,15.0,GCACACAFHFHGHDHAHDDEDCFAHACAHGEFHBHBFGDEHEAAAGAGCDAEGEBHDGFGHHCHGH,False +449,27.0,20.0,31.0,20.0,16.0,31.0,25.0,16.0,CCFCACAHBDGCGCBCGCDCBBEBAGFFFCFCDCBHBEFDFDHGGDCFEDBDFDCDCFFDBAECHADBCHCHCAAAAFAFADDGFCECGCGDDEHGHFFEHGHGFGFGAEFBFEFDBHAFDGGCFAFHHHBHEAGAEAEABGHFAFACACBCACGBBAGACAFFGFGFDBCBCGEEEECFADGBGA,False +450,2.0,7.0,4.0,2.0,6.0,1.0,3.0,3.0,DGCGCBDBHCECHBEGEABFBHEAEBEB,True +451,8.0,7.0,6.0,1.0,2.0,4.0,4.0,3.0,FGFHEABCCCDBABAHCHEAGCGCBAAAABBBFGF,True +452,12.0,16.0,17.0,11.0,29.0,15.0,19.0,16.0,EGDGEGHCFCFDDBECFHFHGEBEBEBEBDBAHAHADCEEEEEEEBECCBBBGDCDCFGHHEACAGBGHFEGEAECFDEGFHCEDFDFDCBHEAEAEFBGCGBAHFHGGEEBFGFGEHAGAGAFCBHHHCCECEG,False +453,4.0,3.0,6.0,2.0,6.0,8.0,4.0,3.0,CCFCEEHCHBDEFAFAFHGDFEGEFBFBFCECGAGA,False +454,17.0,13.0,25.0,22.0,19.0,16.0,28.0,27.0,AGAHHCDEDGGGDHHFEEGEHHCGGHGABCDCDAAFCFCGAGCFFFHEEEHEBGBCFHDAEEBDCDCGCGCBHBFCFHDHGBGDHCHFHBHDHBEAFCCDEDAGCGCDCFFHGHGHGAGADACAEABFCECECEBEHAGAHHDGDGHGHGFDFDEBCHDDCDGBGEA,False +455,3.0,8.0,5.0,6.0,3.0,3.0,1.0,4.0,ADHHHDFFACBCBCHCBDDGDBDBEBEAEFCBB,True +456,17.0,25.0,25.0,21.0,21.0,26.0,24.0,21.0,GEGBFBFBFBGAHAFACDEDCCHFFGBGAACFCHGFCFGHDAEFEFGFGHEBEBDAFGFAFCCBABEHCGFEDEDGBGBFBEHEGGCDCDCBGHDCCCDFAGBHBDEDHCHCHEHCBCDDDDFBEEEEGGBFCFCHAHACGFBBHDHBABGBGDGDFAFAECECEFDFDBGCHBAAHHEH,False +457,12.0,10.0,8.0,8.0,4.0,11.0,8.0,8.0,DBDFDFCCCHBEGFBHEFACBDBGHGBFAFGHAHAHGDDDCCACGCEHGFGFBFBABABDHFAAAEAFA,False +458,20.0,11.0,18.0,22.0,26.0,28.0,20.0,28.0,BFGHCHEAEAFFFFGABCFGFECECECECHCHGHDHAHEEEFHAAFBCGHDHDHCABGHCFDGHGACFDDDBCGDDFGGGGEEABGFAFEHAFEHAFAEAEABAGFDFEEHEFECDADHDHBHEHDHCHFHDHFHGDDDDEDEFEFGDCHCECEFHFAGBFFEFCADGBGBHA,False +459,18.0,25.0,19.0,16.0,13.0,17.0,21.0,14.0,CACACDEDBCBHAAGHBHBCEDEDAGGHDFDEDCHFHECFBFACAHAGGGGGAGDFBABFFGFBHBHBGBHBACABHBGCGBGEFADCDCHAHDHDBACABBBGEGEFCFBGBEFDFABABFCEGECDCBCGDBEGFFCFDGE,False +460,21.0,19.0,19.0,30.0,29.0,19.0,23.0,32.0,FDEDECCDEEHFDFEFEFHAHDCGCGCFDDDCGAGAECDHBEBAHGCGEFEDHDHDGDBHBADCDCHHFECHBGBEHADBDHGHGHGHDHFBGAGHBFBAECGGFEFEFDGDCDAEGEBACHGGDDADFHAEABBGBABDFDFABEDAHBHAHAEDEAEHEHCFCHEHEHBHBHGGCACAHEEEEFDFCGDH,False +461,9.0,19.0,19.0,25.0,19.0,17.0,20.0,16.0,BEGCGDAEHEDBDCEHECACAEAEAFCEGHGHFHGHCEDDDHDEGGFEHEFDFGFDBDBDGDEDCFCFHECBDHACCBCBFGDGCHBHDDBGBGFCBCDDGDACFGGGGFGBEBEGHDBDFCFBFDFDBHHAHAEDFBCBEBEC,False +462,9.0,14.0,11.0,15.0,9.0,10.0,15.0,17.0,CHCHCGCBEBDHEHFBGDGDGDGDBDGEGCHHBDBDACFCHGFEAHFFDCGAGBFHEDEHHAHAEBHBHGAGBFBDBCFCBCBADAGEGHHEFDFDGDAH,False +463,15.0,16.0,16.0,16.0,13.0,12.0,15.0,14.0,EDEGEDHBHDHDACHCBCAHADGDGAEEHFGFGFAEGEDECGGAFAFDBCHCGCEBABABABDEACHCBABAFGEACFDBBCBEGEGCDCDADBDFHHHHHBDCDGBFFGFHCBCFG,False +464,20.0,13.0,10.0,7.0,14.0,12.0,14.0,15.0,HHHBDFFCHCGCGAGDFDGEBFBABAFAFHGHBAGEGEHBACFCEDBACCCABADAGBGAGEEAAFAFACGCFAHEHEDEBAGEHEHEGAGAEFHHHHABEBDBF,False +465,32.0,28.0,23.0,18.0,15.0,22.0,28.0,21.0,CAHHBFBGCACEGFGAAABABAGGCGCGEAAGCGEEDBDGDCDHDBBABAFABAEDBGCEDBDBAHABFHEDEDBFFGAGHHEGAGHEECDCFBHCGBDBDBFGFDFCFAAACACFGHGAGDCFGAGFFBHCHCEABHBFBFHFAFHFEFBABGBGBGHHHAHAGEFCCHBHCAGBCDCECADADAG,False +466,14.0,31.0,26.0,20.0,17.0,27.0,15.0,13.0,BBBBBCGFEFDFDFCCDCHHDAFADACCEAGGCGCACFFEGECEFECCACGEBAGDGHBABDBHBHFCBHFCFCAHDCDHBGFEEDEDFAFHHGBBFAFCCCFAFDFEBBABACHHBDBDBFBCCFFFFFFDBBBBBEBECEGEGDGDGEGCHEBCDFBBBDD,False +467,15.0,12.0,15.0,11.0,17.0,18.0,18.0,13.0,HAGECCBCFHEGGGGBGBDBGBAFACCFCFCBDFAAAAACEEEFECDFDCDCDHBGGGFGDABAGAFFEAEFHBEDEDEFBAHGCGCHFGFGFHHDHECEAEGFAFHHEHEBBGEHFDC,False +468,22.0,12.0,14.0,17.0,19.0,18.0,16.0,15.0,DADADADAHAGABAEHFGFGEGBHBGADHDGGACHEHCHGEFFBCGCAFGDGAEHEAAFCFGAHAHEDDFDCHFEFEDEBECABEFGBGAGCCECFCBBBBHAEBECCADEDHHHEDEDEDFFFFGDAAAFCF,False +469,18.0,26.0,29.0,20.0,29.0,19.0,16.0,15.0,CGCGCHCFCGHHCHCHCHCFAEAFFECEBFGDHDCECECHCFFDBDEDBGGEGAGEHBBCCACABEEEAEBEBACECGADBBHBDBEFEFEFCDDGCCBAHHFCBHBADAGFDBEFEFEAECBFFHABDBAEDECECEDBFBDBDBDACGEGEBADCDGBGDGACFEFBAEH,False +470,6.0,1.0,5.0,5.0,3.0,4.0,4.0,6.0,CBCAGGHDHDHDHFHFEECACADHCAFAFGEADG,False +471,8.0,12.0,3.0,4.0,7.0,8.0,8.0,2.0,GAAFBEGEFDAGEGEFEHGBCFFFFGBBBEBABABDBDBEBDHGCABACAGF,True +472,9.0,4.0,9.0,5.0,3.0,6.0,1.0,7.0,HACGCABHCEAFHBHDAAACFCBEDEDADAHFHFCFAFBCDCHC,True +473,2.0,1.0,5.0,2.0,7.0,3.0,2.0,10.0,CCHCDDGFHAEBEHHFACHHFHEHEHEHECEG,True +474,8.0,7.0,5.0,9.0,9.0,4.0,1.0,12.0,BCDHBCBADCDHHAHDHAHEDEDBHEEDHCHAFAHAHCEGDADEFEFEFABHBEB,True +475,11.0,5.0,2.0,1.0,3.0,2.0,5.0,4.0,AACDCFHAGAGAEBGBHBFEAGBGAAAHAHABE,True +476,25.0,30.0,25.0,21.0,26.0,22.0,25.0,24.0,HGHEDBDBCHEHEDEDEDEDCAHDCGCFDFGEGDGAGAGHGDGDCAAHABAFACBCBCEDEAEDEAGDFEBEBEHGHFHFCBBFGHGFEFBBBFHGBCFCEBABADHBCACGFHFACACDFABHEAEHHDGACHFBFBHBHBABGGDBABGFEFBHGHAHEBGBGCFBEBECGCACEFAGECACFDFEAECCBGHCDD,False +477,15.0,14.0,22.0,19.0,17.0,22.0,25.0,22.0,DFGGGFHHCHEHBGDEEBFBAAHGFGFGACCCGHFHBHCDEEFEFBFAFBFCGCEDEHEHEBFAFAFAFGCGCGDBCBFFCHCDDDEAEAGDEDECGDGABBHDHDFDFDGCGAHEHFHCHAACDDBHHACBGBGAGFFHCCGHHCCGDGDGCGEE,False +478,14.0,12.0,9.0,13.0,13.0,17.0,7.0,13.0,AFAFBFBDAAADFFBFBEHGFEFHAHFGDDFDHAHADABFBFHEHECCACGFBDBGAEHCDCHGHGEAECECEFECADFDBGBHBHEHDDFEFDBEAC,False +479,29.0,20.0,16.0,24.0,27.0,18.0,17.0,26.0,GEHHHAHEGBGCHCBCFGDGBFDHCCBCHFHAEFEGGDHDACEDDDCDFDFDHBAADHFHBEFEHCHCDFAFABAEGBHBABABAEHEAEAEDEAFHEDAGEBEFGCEDEFEDHBFFDFAHHDBDGDHEAEGCBDEDBAGAGAGAEAHACACAEAEBHAHGFGEBEADADBHBHFCC,False +480,11.0,14.0,7.0,9.0,18.0,15.0,6.0,9.0,FAFEGDGBBEFEDEFEFABAGEGEFFFBBCBEDABEGAAAFHFDEHHFBFDFAFCDCDEGHHCHBABCBEHEHEBEBEDEHABEFACDC,False +481,8.0,4.0,7.0,16.0,11.0,8.0,9.0,4.0,EEADADFDEAFBFGEGFGDGCHDDCDEBEGEGCFCHDAGCGDGAECFCEDDFDEABABADDDDEHFH,False +482,11.0,7.0,25.0,5.0,16.0,24.0,10.0,11.0,EAEAEACFCBCEFEGAGAGCCFFEFGBCFFHFCFAHACFCEEHCCFDFEEHBHFHAGFFEFEBDAGCGFAFEFEHECGCGCFCFHFHCCCBCDDBCCCCFDFHAECBHG,True +483,24.0,31.0,31.0,29.0,20.0,23.0,19.0,21.0,HAHEECBBBBGBECEFBFHHCHFHDBGBHEGEADAEAEBBFBCECFCACABHCHCEBFDFCFCFBFHHHEGCDCDCDHDCECGABADDDBAGAGAHEDEBBDGCBCFAFABAHCBCFHGHBDEDGBGEHCDCFCFCAHFBCDCDGDHABGFEBDBDBDGAFAGAFDDCEFABAFDDGAFEFDGCBABHCGDGDCDCAE,False +484,10.0,14.0,9.0,7.0,6.0,9.0,6.0,9.0,HCACBFBFCFCFHAHADACABDCHGHGCBFDHCBGBABFBDBFBEEHADADHBBEBADAGECEFHBGEGF,False +485,10.0,4.0,11.0,5.0,13.0,7.0,15.0,10.0,AEAEHCHCGCGCBEGEGFGBGAGFGEHAFGCHDECCAHADDFDFHFHEGEGACCBHDHAEGEGCGHBEEEGAFAC,False +486,10.0,4.0,4.0,3.0,10.0,7.0,9.0,8.0,HGHCFDHAFAECEFHFHEGECHDDACABAEEEGGAEAGAGAGAHFGFEHEFGBBB,True +487,5.0,6.0,9.0,7.0,10.0,8.0,5.0,12.0,FCFCFHFAFAFGEDCBEHHGGEHEHAGBHCHFEAEDEDBHADCBCDHDHDFBEBCCHCGEHE,False +488,11.0,11.0,11.0,8.0,15.0,8.0,13.0,12.0,CBABEBFHFGEGHCDCAGDGEABBCGGBBHEFBBABGBADEHCHCEAEAEGEFFFCGCEHDHDHECDCAFAGAGAGEHEGFDHCHEHED,False +489,22.0,25.0,26.0,26.0,18.0,25.0,28.0,23.0,BEBEBEBFFHDHDHCHDHCCGCFAGCHCHCDCGCABABAFCHEHBCBCDCGCEHAHAEGGABFDHEBECGCHCHFDADAHHEGFBHAHFDGDCCCHFFGGGGBFAFABGFEFAGGFGDBAHFEGEGEDBBEDDBHBDFDFGGCEFGFBFHGADADHCEGEGDGDFDBBCBCDGBADABAFCFAFADDDBCGAE,False +490,19.0,24.0,22.0,16.0,30.0,19.0,23.0,31.0,FGGAFEFECGHHEGEHEDEFEHAGFBFBFHAEAHAEAEACDEBBHCECACEGBBFBDBCHDHGCFEHHAHAHBEBECGGDGCHBHGFGBDFCGHGHDHBHBACACHBEAABDHEHDHFFBFHFHEBCDEDEDFDGEGAGADBCHFHABDBDCFAEAEBEBECGCGEHHCCBCHCEGEGHFCGEG,False +491,16.0,23.0,19.0,29.0,31.0,20.0,28.0,25.0,DHDBCECECAGFGBBEEEECEDEGHCDGGAFDFGFGCGCEHGHGEDFGCDFGFDDDCDEFEABDEDEBEBHBHBGGHBDBHAFABDGHCECGAEAEAGABHDHDHDHBBBGEHEFEDHBEEEGGCDEFGHGHAHAFCFGFEDCFEABHFHEBEBDHDHACBCFGAGFGHEHBGBCHFGDDADCDADFDECB,False +492,2.0,8.0,8.0,4.0,4.0,4.0,9.0,3.0,GEGFACBGAGECCHCHCBFDGHCCGCGBDBDBEBEFDFBGBG,True +493,21.0,13.0,20.0,26.0,11.0,13.0,10.0,15.0,AACGHHEEDBDBDCDCDBEBFBFEGDCEADDDFAFAEAHHHFAFADEDCHCBCAAGACDDDDDBCAGDCDBEHGHGFGABDHDHCCCCHADAEAEDHDAACAFAFBFEDGBHCCADHBGBDFCFCHCFG,False +494,4.0,3.0,5.0,3.0,3.0,7.0,4.0,3.0,AHFEBAHCHGFGFEFDADBFFCFCGCGCBEAD,False +495,0.0,4.0,1.0,1.0,4.0,0.0,2.0,1.0,BDEEBEGEGHBCB,True +496,6.0,16.0,13.0,12.0,12.0,13.0,12.0,10.0,DHFEEBAFCHCHCEFHABBCBCFGECECEGEBDCDCBBBBFAFEBEGGCGAGFHEDGBGEGCHEBDBHBHCGBHAGDFDFDFDFDHCADFDFGB,False +497,19.0,9.0,12.0,22.0,14.0,24.0,20.0,18.0,DEDAHEBAAGDBHHGABAGCHCDCACFCGCEEACBFAFAGEDDDHHHCHCGFGHBAGAFAHDDDDDGDFDFHFEEDEHFHEBFDFHBAGHGHFHFEDEDFDFDCGBFACAGAFHFEABGEGFGFGFECADAGGDGFFF,False +498,8.0,3.0,6.0,14.0,8.0,17.0,6.0,15.0,GFFDFEGGBEBHAEDGFAFEFDDDAFHCHCDCDGFHAHFHFGDHCEFHCHCFDHDHAFDFEFAFABAEHFHDHDEDH,True +499,0.0,6.0,1.0,2.0,2.0,3.0,3.0,4.0,EDECHDBGBGBHBHFGFBHBF,True +500,9.0,11.0,8.0,10.0,19.0,12.0,9.0,5.0,GCFDBACGFBFAAAAGBFAEGFGCGHEAGHDFFCEDEDEDEDECHBEGDDEAEFDFAFEBEHEHEDEBEBEBCBCBFFEGBCE,False +501,8.0,14.0,12.0,11.0,8.0,12.0,9.0,4.0,DBDBEBDBDFDAGCGFBCBCFFGCDCDEDBBBECECFBFECABDDAFAFAGEFBHAGAFCHCDCGHGHBFBEGEFCAG,False +502,5.0,5.0,5.0,5.0,9.0,6.0,4.0,8.0,FEFEBHHHAHABEBDDFDHDCAFFECEAHCBCEAEBHGHGCGFDEGE,False +503,12.0,12.0,13.0,25.0,16.0,10.0,18.0,21.0,GBGBDECCCFHHBACGDGDGDADCGCBBHDHDHDBDFDFDHEHGCEDEGEFAFHBEFFGCEHFFDDHDHGHGDAACAGBDHGHEDEDGAHCGDGDACEGAHAHDHEHEBEBCBFBEHEADDGDCAHE,False +504,10.0,15.0,9.0,13.0,14.0,7.0,8.0,9.0,CBEEFBBGBGBDBABADFBAAHEBEDEDGFCEBDBHAHBCBCBGGFDFCAGAFDGDHDHGEBEHFHECECEAHCDDEHEAEADCD,False +505,18.0,16.0,17.0,23.0,12.0,18.0,20.0,12.0,FGFABEFDHDHFHGDBDBGBGCACDDDHAHBHFFFBGCGEAEAGABHBGDGCECEDHFAGBDEAAHCEGHDEDEDFGHDDDDEFFAFGDGCFCFDFDACFCEAABGBABCBCFHGGBGEGAACCCCFCGBADADBD,False +506,22.0,16.0,25.0,22.0,25.0,11.0,27.0,18.0,AGCDCDHDBGCGAGDDCDGBGDCBCGFGHCECGHGAEFEDEAEGEFHGBCBCAAAAGGDGEHEAEDEDEBCBGFCFGDDEDECFDHDBEAEDEHGHCCCCABAFABCBAHCHGHCCDCEFAGEHAGAGHEBCHEGBHBHDHFEEEACACDEDEHGGGFBFBGDAAA,False +507,13.0,17.0,22.0,10.0,17.0,14.0,17.0,13.0,GGGCBBBEBHAEAGHDCGCDHFEAEABHCHGFGHGCCFFBCAAHEHEDCGCGCDADEHAHFDFAFCHCFCBDEEAEFHAHFCFABBDBDEGECEBGBGCGCDEEBEBFBEACBCGCGBGCFCF,False +508,17.0,21.0,24.0,12.0,17.0,20.0,19.0,17.0,ECHCHCHCGCFBGAGEBEBEBDCCFHFGCDFFHHBGBGDDDGFCFCGDGFAACACGFHDHGAAHAEBEGCCCFGFADADHBBBBABEBEBCGCHDHBGEHCACECEDDCFFAFEBACAEHEHBGBHEFAFBGHGFBCBEAEAGFFCF,False +509,4.0,0.0,5.0,5.0,1.0,0.0,3.0,4.0,GHDCDCDCDCAEHGCDHHAAAG,True +510,10.0,11.0,3.0,4.0,7.0,2.0,18.0,3.0,HAGGGGAFAGCGEGBGAEBGGEBEBDCEGDBDADEBEGAGAGBBBCGGBGAGHBHAFA,True +511,2.0,4.0,2.0,2.0,1.0,2.0,3.0,1.0,DEDFHGABBBBFAGCGC,False +512,2.0,4.0,2.0,1.0,1.0,1.0,0.0,1.0,HDBABCBCBFEA,True +513,4.0,5.0,8.0,7.0,6.0,8.0,11.0,4.0,GGHGHGDBCECECEGFHDABADEGGCGCECBFEGACFFFFBFCFHBAGGDDDD,False +514,20.0,26.0,19.0,15.0,24.0,22.0,24.0,21.0,FGFEFEFBHGHBEDHHHHEDCDEHEHCBFHGAFAFBFDCACAGGGGGGGHBBABFBFBCHGGBACGCGDFEEEEAEFFFFDECECFCBCBEAHCBADEDAGFDEDBBEBEHACAFAFABHEEDCFGHDAABEBEDGGHGHGDDFEFAHAHBGCGBGCCCABBHBAGCBHBE,False +515,22.0,23.0,26.0,33.0,16.0,30.0,25.0,23.0,GGGGCBEHCBCFEGGFADHDHCGDACCDBDGFCFHBHGAABFBAHAHDGDBDADACGCFDFGFDDHBGGGEBEBEFGFHBEFABEGCGCGHAHFHFHDBDBDCDCDCHFFFHFDFAGEGBABFEDBDCECBCDDHDBGECADEDEFFFFAFDFDECGHDFDFBCGFECHHAHAHGCBCDADAEAFCFCDHDABAHABC,False +516,17.0,13.0,13.0,12.0,15.0,20.0,10.0,20.0,FDFAGABHFHCEEAFCEGGBEBCBCBEBDHFACGHGCACACAHFHDBGFGDAEAEABFDEDHDFAFEBDHHHFHFHFHAHAHAEAFADCCFBBCEHFFFDGDGBEHHHHGCBEFEAEDFC,False +517,26.0,21.0,23.0,17.0,23.0,30.0,24.0,22.0,ABAEAEAEBGGGGGAECECEDFCEBAGHFHAEADCCGGGAGBEBEBEDCDFAFHFHGCCBHAFAFAFHFGBCDDFACGFGHDEEGEFEGBGFGADFCFCFCBAEABCDHHHCHFHFHBHAEFFFCFBECCCFFDFDBCHCADAFHBABDFDBBAHGGEAEHCGEGCDAGAHDGDFHFHFEBABEBH,False +518,7.0,13.0,9.0,12.0,7.0,6.0,7.0,5.0,CGCECBHDEBGBAFCDBDBDACEBDDGDGEGEFAFAFAHCFEHEDBCBDBDCDBBBDCHFBAGAGH,False +519,15.0,23.0,14.0,11.0,17.0,17.0,14.0,16.0,AFGEDCHBBBBBBGGECEFFBACACBCGCBHFAAABCCEEDDDHBBFBFBGEHEFDAEAFFFEHAGABAFHFBDBHHHBEBEACGCGCACDCHEEBEGGDGHGHGDDDCBGAEBEFEFAFHHHFHFB,False +520,18.0,12.0,17.0,12.0,18.0,12.0,16.0,36.0,EGEHCHDHDGDGCADAHAHFCEEBACEEEADAHHBCBEHEHEBAHCEEGCFEFAFABHBHGHDCGCGDHDHFHDHDHAHCHABCGCFBHHAHFHFHFCEHEAAHHBHGEAHHBFCCGBGFHAEAEGCHBHGDGDGAGFHHC,False +521,4.0,11.0,9.0,6.0,9.0,15.0,6.0,12.0,FFFCCHBHCFCBCBFDDGDGBFAGCFEFCHCGFBBBHCHDEDEAEBHBHGAEAFFBEGEHEHEHBHFFFFHD,False +522,17.0,10.0,12.0,14.0,22.0,13.0,17.0,18.0,EEEEDEABAGFEFEHGHBDAAABDBDAEHHAHGHGHDHAEABHHHHHBCGCFCFCDBAGACEEGCGAADGDHAFCFCEBEFDFEEACGHBEFEFEFEDCGFGHGEGDBAEGEDCHAHGDFDGC,False +523,0.0,4.0,3.0,2.0,1.0,0.0,4.0,2.0,DDEBCHCGBGCGBGBH,True +524,25.0,20.0,21.0,11.0,21.0,16.0,21.0,28.0,FGHGHEHEHBHFHFBFBDBEGDCHCGAEAFCDEAAACHEHEHBFFFFAAHCGGHGBGBHCHCDCGAGAGBHHHFDCDAEABBBCECBGGFACHCECEAFAGHFAEHGGEDEDEBHHACCCACBCHDGDGAAABAGFEBHAGBGCFEEDEAEAFBECHHAHBHB,False +525,5.0,5.0,3.0,6.0,5.0,16.0,3.0,8.0,DHFHFEFEADAGEGECBDFCBDDFHCHFAAAFEHHFBBBGDFFFFFFFHFH,True +526,1.0,0.0,1.0,1.0,2.0,0.0,4.0,6.0,HGHCHEHEGGHGDAH,True +527,14.0,26.0,15.0,11.0,16.0,18.0,25.0,17.0,BHFABADGFABCDGGECEBEFEDBDHGFCFDBDBCEFBFHAGBFEFGFHFHCHBHEHFHFHCHCEDBDBEGHGHGCBCBGDEEFCFBGBGBGBCBDBGAEAGBGAGECEAFGGGHGCCAFGGEAEDBHAGABAFAGHHCBBB,False +528,26.0,33.0,22.0,21.0,21.0,26.0,21.0,23.0,HDBFBDGDGHHEBFFCECFBABGGEBEGGAHEHABGBCCCABDFEFGFADACCGABDBFBADADBDAHAHBEGHFHBEGEBCBCBHAHABADCHBGCDEDEDHGGGGGCDBFFFFFAEECHCHCFEBEAADFBFBABDBGEEHEGEFCFCFEAEADCGFADHHFBDBAHAHACABABFBFCFHBHBHCDFGCD,False +529,19.0,28.0,16.0,26.0,16.0,17.0,19.0,17.0,ABADGCGBHDFFFGFGDGFBDGGFAFCGGFHHAAFFFEAAHAHCBCBABADDFFFABDBDBHGDACHCHGBBBBBGEDADAGCBEBHHEDBCBCBDEEGADABABADADCCBCBDFDFCBCHFEEEDEHHHGHBHDEECHGDGDBEEEDEDGDGCBBD,False +530,10.0,4.0,8.0,6.0,5.0,11.0,7.0,6.0,FFBFCDCGAGFEDCDBEGEGFCFCFCBAFDBHAHAHAGACAHAHEGDFCFADEGAFH,False +531,13.0,7.0,11.0,9.0,7.0,13.0,13.0,17.0,GCABEBFBAHHHGHGAAHCHBEBCDAFHFHBCDCDCDFGEGCHAHEHCHDFFFGFGCGAAAHGGGHFCECHHHGAAEADFBFDFDEDAGF,False +532,6.0,4.0,4.0,4.0,4.0,11.0,3.0,7.0,ABCDHFHFECEDADFGHAFCFCFBFBGADEHGBFHEHFHFAFA,False +533,14.0,30.0,24.0,27.0,22.0,23.0,21.0,29.0,CEBEDGCHDGAAABHEHGCGBFBEGDDDCDCHHDEGFHCEFBGBCCFBAEAGABEDFDCDCDHDHGFGHGCGDDFBBBBBDFDADCDGBFEFDBCFCFBDHDGFACAGFDFDEAECFBBHBHCACAHFDEHEHBDBGBHBFBEDCFEEHBHBCBCBHEFEFCHCHEAFHBHBHEHFGCAEGHGHGHGHED,False +534,7.0,14.0,11.0,10.0,12.0,6.0,11.0,7.0,ABADCBEGAGABDBHCECDBEHGCBCBCGCFCFHFHFBBCBGEGHGDGEGEDDDCDEDABAHCFEEAEFEBBGDEHBG,False +535,1.0,8.0,7.0,5.0,5.0,7.0,1.0,7.0,BHBGFHEDDFCBBBBHHHFEFHFCFCACBDBDEHEFECCCD,True +536,5.0,4.0,11.0,11.0,13.0,6.0,6.0,8.0,CDDDEBHHGHDFGCCACEDEDECEGEACACHEBFFEFEFGFGDGDHAEEEABCBHEDCDCHHDC,True +537,28.0,21.0,11.0,18.0,13.0,11.0,21.0,19.0,HGAGAGFDDHGEBDCGAAHGHEDBDFDEGAGHDECCAAAADDGBBCBHBHBHGCGCBBBFBFGABAGCHBGAFHFAACAGDFEFEGGBFHAADADFDADBBBDAEAFHGHEHEHAHAHAHAGEGDCDCHBABABECDGAEBE,False +538,3.0,5.0,4.0,4.0,5.0,2.0,1.0,6.0,HCHGHAFBEBEAEACDCHBEBFCEHBHDDD,False +539,6.0,6.0,7.0,4.0,9.0,4.0,6.0,1.0,CCAGDGDGEFBCACBCGDDBFEFCFEABABCEEEABAEGEGEH,False +540,4.0,1.0,2.0,4.0,0.0,6.0,5.0,0.0,FDDGAGFGCGAGAFFFBCDADF,True +541,9.0,14.0,13.0,6.0,8.0,6.0,10.0,5.0,CBCGEGEFEHAGEDBGEGAGHDCBCGAGAGHDFGAACBBDBDFFCFHFDACACBBEBECCCCHEACBBBBB,False +542,16.0,16.0,8.0,16.0,13.0,11.0,10.0,17.0,EAHAGFDCGCGDEHCHBAAADHDHEHEFBGBABFDAAADBDADADHDGEGCGHGBFAFEBBBBHFDFDEBEFAHEBDGFHCHCHGDFABABDHHHAEBEHEDEBCCF,False +543,21.0,26.0,17.0,27.0,29.0,23.0,26.0,18.0,GDEHHBFFAHDHDCBHBGEDBDGAGDHCEEEBFFACBBEDGFCFBEBECAFDDHBHDEFEFEFEGGCGBHFFCFEHBHEFBHBADAEAGAFBFGEGEGCGDEDEGCGCBDFDFDADABCFEBBBDBGGGFGCDCDCACFEDBGEGEGHABGEGEAAAACCHEBEDEHBABFGFHHEHADGDADADAD,False +544,22.0,22.0,21.0,19.0,23.0,23.0,21.0,20.0,CGDGDBCFDADCCGDBDHAHCHCEDFFGGGECECEAFAHCFDDEDAGCGCBDEDEAEHCHCEEECEFBFHDHGHGEGCHFEAEAEFFCFEDEABHHHGFBAGAGBDEGECECECHBHAHGBBFBGBDFDGAAFAFGBBCBGBFHEHCBDFFFHFBAAHBFBAAAFAGABDB,False +545,23.0,25.0,25.0,15.0,25.0,17.0,21.0,33.0,GAGAGEEHHHFHFHFHEHDCFHABBHBHBEBHFGBCCACACACGHBADHBECECEBABECCHCFEGHDCEBGGEBEBEFHHADCDCDFDHBHCAEEHEHFHGHGHFADCGFHCACACACBCEGDFHCABGDGEGFCDHGHAAAHBHBHBEBHBHAGABEEGEDEGFBFCGEDAGADDBBEAFCF,False +546,3.0,2.0,2.0,4.0,0.0,4.0,0.0,0.0,ADADAFCFDBBFCFD,True +547,13.0,21.0,3.0,11.0,13.0,5.0,12.0,11.0,GHBADHBHBGBEHDHEEFGHDHGFEDDDEGEAEDFAAGBBCBAGAGAEDEHBHBABABAGADBEBECEAEBBBBGBHBDFGCADBFBHG,False +548,25.0,24.0,22.0,17.0,28.0,18.0,39.0,21.0,CDCABDBHBGBGBGBCECBABGBGAHAHBFEEAEBGAGEHFACACDEGEGECHAEGEHFHFABEGHFHAHGHCDCEBEGDBFAFHGEGBGAGDBDBDBEFECHFHEBFGEGEGECAFABEBGBGHGFGEGCCCCHGFACGBHAHAECFGAEDHGHGDDDEAFADGDGDCAEGGACFBFAGEGACCEHDCDGGFG,False +549,3.0,2.0,4.0,4.0,5.0,8.0,5.0,2.0,HFEFGDGFBFDFEEEFEFGBGCCACDCAGAHFD,False +550,1.0,3.0,4.0,3.0,7.0,2.0,2.0,6.0,ECEBHBHGHBECEFDHAHECEDEDGCHF,True +551,16.0,22.0,21.0,26.0,28.0,20.0,19.0,21.0,EGEDEBEAEADDDCFCABGEFFHDBECHBBBBAHAFFCCDDDDDDHGHEFAAAAAGGBGFGBGCCHEHFBFHHDCDFFBFDGEGFCABBEBEBECDGFEECACDDBCFEDEHHDBDFHFHCHCEGGGEGEADCDCEGEFFHHGCCBCBDBEBEAEAEAGDFHCDGDHBHEHEH,False +552,4.0,5.0,6.0,11.0,3.0,11.0,11.0,5.0,GCCDFHFBDDEDECGCGDGHABDDGGGDHAHAFGFGEGFGFABDFHFCFDBDBFFC,True +553,5.0,13.0,12.0,7.0,6.0,1.0,8.0,8.0,BGDACECGDGCCCBCHCGCDBHHGBEAEAEFBCBEBDGCGDGCBABABEDCHHHHHBBDB,True +554,21.0,23.0,19.0,23.0,24.0,21.0,32.0,21.0,FAGAHAHFHGHBEEFGADABCBGBGFAHEDEFGFBHCECEHEHDGDEAAHGGGEGFFDFBCHGAGHCDGGGABDGDADHFEBHBHGGCACBCBCBGBCFADADGDEDACBGHEFDFHFHFBDDDDBHBGGGCDEFEGEGECHCBCBEBEBEFFAGBBFACECECDAEFECGAGEFDGGAADHDH,False +555,11.0,14.0,17.0,9.0,22.0,14.0,9.0,22.0,CGEEDCDADADBDBFFFHCAAEHHHEHEHAHEFFCFBGHHHFHCHDHEBGFGFBEECFCEEECGCGHEEEEADHBHAABCCACFCEDHCHCHBHBDBECGCEFFGFABBEBEGHAHBE,False +556,4.0,3.0,4.0,4.0,4.0,1.0,0.0,1.0,BABHECAAFBDCDEDEDECAC,True +557,11.0,15.0,15.0,16.0,14.0,18.0,14.0,14.0,BCBCBGDGCGEAHHEHGAFFCFHFCGAGACEBEBEBAFGCCDGBCEFDFDAEADDFDCEBFBFBEHDHEHEGEGBGHFHDDDDCCBGBCBHAHDEFFFGGCHBEAAAHFFDFDFDHC,False +558,5.0,2.0,3.0,3.0,1.0,2.0,3.0,2.0,DGDGACBFHFHAEACABACDG,False +559,29.0,26.0,17.0,17.0,20.0,26.0,24.0,23.0,DADCDFFHFAFACAFBDBACAGABFGFBHCHCFFEFEFGHGCBCAEGGGDBDBABFHFAEADDDEDEHAAGGDBHGFFFFCGAHBBGBGECEGEGEGEBEDCFFDFCCEAAFDHAEBFBFAHAGFHCCGBGBGBGAGABEDADHEBEHHAEFHAHABCBCHAEAFAEBHGHBBBAGDHHHHC,False +560,7.0,9.0,14.0,11.0,8.0,12.0,13.0,5.0,FCDCEFEFGHDAABACGCGCGDEBAHHBCCFCFGEGDBDBDBAFECDFDFEGGCAFABCFGFGEGHCDEDGDGFCBCBH,False +561,16.0,32.0,21.0,19.0,21.0,20.0,22.0,22.0,AFBGBGHGEDFAACDCDCEFEBCFCGHGHFDABABAHCCEAHBEDEDBDCCHGHEBEBEBCDEFGDGFBFEDHDHDBBBFFEGBGHEDGDFBGBACDGEBEBHBHCCGHGHGDGDGHGHBCAFHGHGFABAFAHAFCBCBFAHDHBBCBGFEBABCBCFCFEEBCFEDEAHBE,False +562,18.0,21.0,6.0,6.0,14.0,3.0,15.0,20.0,DGAAHCHBAFHBHBGCAEAEAHAEAHHHBCBGGEBDFAHAEAEBGAGAHDEGHAHBEAEGHGHBABHBHEDCGHGBEDGBGEGBGBABDBAEEHFHBCBCBHB,True +563,19.0,18.0,15.0,19.0,14.0,16.0,17.0,24.0,FAFAFABBHDCDCDFDCAABFCEDBBECDCDFFAGADBCHGGFHDHGHEECEGDADABEHHHHCHDHDFAHGFGFBDBCBFHAGABDBGBFDGGFCFCBHBHFHEHEHEGAGAHAGABAGABEECDCHHEBEDEHAGCGHDH,False +564,3.0,3.0,2.0,1.0,0.0,0.0,0.0,2.0,BABCBDAHCHA,True +565,8.0,12.0,12.0,9.0,13.0,13.0,12.0,17.0,BFBFEEHBFAFGGGCHDHDHGCDCGEHAHEEBBAEFGCGCHCFCFDBBBHCEBEHEHFGAGFFHFHABDGDFDFBHAHDHEAABCEGEGEDCHCHC,False +566,24.0,19.0,7.0,22.0,15.0,14.0,18.0,21.0,AEADAHECBGBFHGHDHAGDGHGBGBHFHBDDDHGHDHDADHDHAHDEDADGFEFGFBDBDFAAAAABEFDHHHEGBGAAEDEGEGAFAFHHBEEHCGBEADAEFFBFDFDBDBGBHAGBCBEFDHGCACBCBAAACAGE,False +567,18.0,34.0,25.0,23.0,26.0,29.0,16.0,24.0,CHFDFHBCBDBFBHEEAEABABCGAFDFDADADADBBBCBDBFCEEEFFAFDBDBGHDHBBBFFFDABFHGCABABABAHHHHDFBFEFHBCDCFCFBFEEGECFHEGEGBBDDHDEDHFHDHDFBAECCBHBEBHBCCCBDBEGHGCFCACEFAGEGEGCCFBFEHEHCGFECGFDAGFGHCCCEEEBEHAHDG,False +568,10.0,3.0,8.0,11.0,10.0,4.0,2.0,8.0,EGEDEHEHCDCEAEAEAFFEHCDDDCACHBHBDDDHAAACAEBFAGAHDCCFEDHD,True +569,16.0,11.0,9.0,12.0,15.0,17.0,17.0,12.0,EAEDEACHEAGBHHFFAGGDADADHBHAFFGDEDEHFBFCGBGFFDGHAEAFBCBEAECDADCGCGFGEGEGAGDEDBFFAFAFCBHAEAEGEGFGFDCHCGFBHBHBH,False +570,5.0,3.0,10.0,3.0,5.0,7.0,4.0,6.0,DADCHHGACACECHCFCFHDEGABAFFFFECECFGGHBCBCEH,False +571,19.0,19.0,10.0,25.0,20.0,11.0,12.0,21.0,EGEGEDDDADCBFBFCHCHGAGDHDHDADGHEDDDDHBHBHCADEEEDDHDBCEAABABFEEAEGHGHFEADDDCABHBHBHFHFEEEEFDCEEGCBCHGAEAGABFBHAHEHAFABHBFDDDBDBHAAFBBAGGCD,False +572,9.0,14.0,14.0,11.0,15.0,15.0,19.0,10.0,EFEAEGGGDGDADFHFGFBFBFGDGBBEBEADHGCBCBCGCECGFDCBCBFDFGEDBDHCAFEFEBGCHAFGFGEEHBGCGCEEEBHCHBADCCGGHAHADAGFHFE,False +573,4.0,10.0,13.0,15.0,11.0,8.0,6.0,4.0,AFCCGEEDEBEBAHAHADFBCBCBEFDGHBEGEFFBFDDBCECDCDCECEDDDDDGDCDCEBBGDHFCCGF,True +574,15.0,27.0,18.0,27.0,33.0,20.0,18.0,26.0,FACGCDEDBABABADHDBEFECGDFHHEBCBCGHHAEBHBHGDADGDGDEEEDEBCBDBEAFHFEDGDGDBCHEAADEDEAEDHCHAFDEDHDACHBHBHEHECFBABHDEEEFEGBGDDHGFBFBFCFCEBEBFFCECEGEFEDGDCBGEGHFCECEBGBHBHDHCEFFFBGBHHHEFAAHDG,False +575,16.0,17.0,13.0,14.0,16.0,19.0,22.0,14.0,HBCFCFDFEGAGAHHGEGBGDGFHEHAFBDBDCHCHGFDEDEFHFBEBHBHBEBHBDFDEDEHEGEFFACACGFHADGFADGBAEADAFBCHEFFBEBGBGBACGGFGFAABGGDGFCCACAEAECDGGGC,False +576,21.0,18.0,24.0,12.0,15.0,14.0,8.0,14.0,CDCDFBACHGHECECEDECECHHAHBGFAAHAGFEBCHAGBBBABCBADCFEGABABCGCFAFEBHAHDHECACHHFCBBBEBECFCFAFAHAFCGDFDFDBEBDCACACADBDEHEFEDGCACAC,False +577,11.0,6.0,10.0,4.0,4.0,6.0,15.0,11.0,HHGHAHGDGCEBABABGCHCGCECHCACHDFBABFHFCAHAHFFBFGGGGGGGACAGECDGAADEHG,True +578,13.0,11.0,13.0,13.0,10.0,10.0,11.0,13.0,HDHDFAHCHGEAAAACGBEEHHDEEEDADCDCACACDGDBDBCFEAGHCFCABFBFGCEFBHHHHGBGCGCGEEHAHFBFDDBDBCGDGAFAFB,False +579,16.0,20.0,17.0,10.0,16.0,13.0,17.0,18.0,HBHCDAHECCCCBHGEFCBCGFFAFACBDGDCHBHBCBEBEDGDFEHGHBHECCCEFAGAEHDGDGHBFAFAGAGBGBGBEECCAFAFDBBHFECBGHCHBHDHBHBAEEEAEHEAGAGFGFGDABA,False +580,19.0,23.0,27.0,23.0,24.0,28.0,24.0,26.0,FGFGCHDADGDHFFDCDABFFFFBCEAECEHADCDFDFABAHABDEDBAHCCCHBAAFAEGEGFGHDHGHBHGHDCFCFCADEFEHBAEEFGCDCGGGGGEHFGCGCFFHFHGHBCBDBDCCCGEBEHFBFCFEECFGHGHFHCAEBEBEGHGHFEFDCHCBCBGBDBEAAABCCEAFBHBHDHEEGABDDDED,False +581,14.0,16.0,19.0,20.0,20.0,20.0,13.0,20.0,ACAFBEAHDHEHBHCABBCHFHCEEGCHHFCDCBBEBHFABGDHFHFHBHBHBGDDDCFFHFBFGFECDCEAGAGACCCGCDCDEDEDADADFFFAFAGHCDAGHFEEGHCEEEHECECEGEFDFEEGDDDGDBBFBFBADH,False +582,13.0,15.0,13.0,20.0,21.0,19.0,19.0,16.0,EGGAGAHBFFEFEHECDCFCBGHFFGAGAGEGCGAGBFCFDDDEBEHEHCFBDDDDDDADAFAHHCFDEDBFFFFHAGCBDAFBHBEDGFGCBCBGEGEDCDCDCFHEHGHBDGEHABEGAGHFEDAHEEEEEBHB,False +583,6.0,13.0,10.0,9.0,17.0,8.0,10.0,9.0,FHFGBBBBABCCDHBEDHGFDEHCGCBEBEHCFCFBFBDBACFHGHGEEECECEDEDEHEDGCAEADFDGEAEGGGEBABEH,False +584,18.0,27.0,27.0,16.0,19.0,28.0,14.0,16.0,FHFCFAFHHBEBFBDCHBGEDBAFFCBHBCFGFGCGCEEEDEDBABGEFBGBAFAFHEGCGCDCDBHHCHAHAHGCECAHFHFDEGHBBCACABABFBFBFAFCDCDBABEBECFFGBECCCHCFAFDDDDFDBECEAEDBFCDCEFGFABABCCGEHCABGFEF,False +585,26.0,16.0,22.0,22.0,20.0,21.0,22.0,26.0,FHDHDHFCEBBDBAAAAGFGCBEDHDHGHAEAECDCBEBHCHAHGGFDAEFCFHHHEECCCDCDCDHAHABBECACADAHCDCDFBBEDAAGAFFHCEEEAFAFGFCECEFACAEAFFHEGFHCAGECFFGBGFGDBDBABAGGGGGHHHAHDDDHHHAHDGEGFGBGBFCEDGD,False +586,8.0,5.0,12.0,4.0,4.0,13.0,13.0,7.0,DFDCCCCCCFEBEBDFFAFGCGCBFDFBAAFHGHGCGAAHGFAFGFGCGAGBCHFHCGGHFHEAEG,True +587,4.0,3.0,2.0,3.0,2.0,5.0,3.0,1.0,BGGGDBDHDFCAEAFCFBFEFAA,False +588,7.0,14.0,10.0,16.0,16.0,9.0,9.0,13.0,BCDFHCGFGAEFFFDDBBHBFBHHGAEDDFDEHEGEGEHADFEEHEGEDEDEDEHHBHBDBHBDCDCDBBFBABACACEHECGHEBDGDCCCAG,False +589,41.0,28.0,27.0,20.0,22.0,14.0,25.0,23.0,EDEHHHEACAEAEGECBBHBHBEFAFEBAFHHGHAHACAGBDBEGCDEHAHADACACGEDCCCFBBBBBFAADACAGECDFHGDDBDCDCECDABAFCBEGEDFCGBGDHACABGHECBGGCDCGEFEAGCGDAAABABABDHGEAHBGAEHGBGBFCFCFEFBHGHBAAAAHABABADAGACACGCACHDHDHAFAGEG,False +590,25.0,17.0,16.0,9.0,20.0,24.0,14.0,17.0,HDFDEGEFBBECCBDBABFFAFDFCECBAGAEABGFHCACAFAFAFHEHEHECFCHEHEHECGBDBAFEBCFAFCFAGGCFCABHGABFFEGAHAGAGCHHEHFDFBEBCBEFAFAHAEFEAAHAHBHBGDGDGCEADAGEF,False +591,17.0,13.0,25.0,18.0,20.0,19.0,18.0,19.0,ADCFCHDBAEHEHEFEACAFAFDFEFECEGADHDHEBCCCCEHHGBDBDGCCFBGDDCGABAEAEDEAFAFCGCFHFEGAGDGFHCGCEHEAGCHCBDEDCFEDHCBEBFBAGEGAHCHCBCBAHACDBDCDCHFHEGFGFGDGHGFFH,False +592,4.0,14.0,3.0,5.0,17.0,15.0,9.0,5.0,HGFEEHBHFFEFHFEGBABFBGDFBBEFEDGDEDECEBEFEAEBBBBEBFAHAGFDFEFEBGCGFGBGFECE,True +593,13.0,8.0,10.0,11.0,8.0,10.0,5.0,8.0,EAEADADGFGCDDFBFHHGADABAFHHBAEABHHGBCFCFDFAFDHDCDCBFBCCCBCEEEAEAEFDAHACDG,False +594,16.0,13.0,15.0,7.0,3.0,9.0,20.0,22.0,BGBGCGHHHEHGAAFGCGBDFAFBHCHBDBCCCFDAHHBGBAAABHHHGHGBABABCCCCCDGHGHCHAHGEGDBFGFGCGAHAGFCHGGGAHAHCHFEDHDAAF,True +595,12.0,10.0,9.0,7.0,8.0,10.0,12.0,10.0,AEFDFGFGABHBHBACAHFFEECEFDFGBCAABBCDCGEBEBHHHHFBAEADGDGHGDGDCACGCACAEFHAHGGGBF,False +596,12.0,14.0,7.0,5.0,7.0,8.0,16.0,11.0,DBGBABFCGCGEGBGCHCABEEHGGGHGHFBEBABFBFBGGGGFDFCGABABAFAHHHHBEAAADDHCFEHAHBGACDGE,False +597,12.0,31.0,25.0,23.0,29.0,22.0,19.0,20.0,GBCAEDEGEDHCHGFBEGCCDCGAFBFAFEGBBDBDBDGGCEHEHFHDCDCDEDFHHBGBGCHABGCGCFHFDEBCDHDAABFBGBHDCDCEHEBFBFEFBFHEHEGEBBDBEBABCDGDBHBDFDFDACCEFBCBFHFGCEAEDFCCDCFGGEEEAEAFAFBHBEBCBCHEHCHGEEEBE,False +598,3.0,2.0,2.0,2.0,0.0,4.0,2.0,0.0,DADAGFCFCBGAFBF,True +599,18.0,18.0,17.0,19.0,19.0,25.0,24.0,26.0,EFEFADADEGEGBBHHABBHCCGAFDHDFEHHHHHHGAAADGHFHGGGGDEACHCHCFCGEGEFABEEGEHFCFDFEBGAHCHGFGFGFGFDDHEFCFEBDFEACAFHCHFBADGCGBADGDAFCHCHDDDFDFHCHBHEEEBEBGBABABABCBFFHFDGCGBGD,False +600,18.0,13.0,8.0,18.0,9.0,20.0,11.0,10.0,FAHEFAFAHDGGGGHCBEGABABFEFAAGAGAGAGAGBHBHCFFDHBHDEDEDABCFCEDEBEFADDBFFCFHFAAGDDDDDDFFFFHADFFFBBBCDADCCADHBE,False +601,28.0,16.0,18.0,22.0,25.0,31.0,31.0,28.0,DHDHCHCEGGGGGGHGHGABHGABAGDGEGBACHDHBGADFBHGAGFGDDADGEAEACHBBFFHFEGEFFAFAFGFEFAGADDFAFCFGHBFFEDBACABFHFCCCEEDFDCDAAHFHEHDDEDGHEFCAHFFBCGCGCACABAEAEHDHFHFHFCEDEDGAGAEEEEEFDAGGGHGHFHAGEBHBAEFCFBFCEHBHD,False +602,19.0,22.0,22.0,6.0,18.0,28.0,18.0,32.0,BEHEHCBFBFGAGFFFHEEGEFFGCHCHFABHHCCBFHFABBEBCACAEAFHFABHCHGBBAHEEEEAHAHBHECACAHEHEHCGBFFHFGAGCCBCBEFEGHDDGDHFHCDAHHHHDAFBFAFHFHGHGACCCACBHBGBGBCFGFHFHFGFGFAEBCGCBDEF,False +603,6.0,3.0,3.0,0.0,3.0,1.0,2.0,3.0,AAAAHHHEAEBFCEGAGCBCB,True +604,20.0,12.0,4.0,14.0,4.0,16.0,10.0,13.0,BHADGGGBAFFHAEDBAFGFCFHFHDHBHBGFFHADDEHFFBFGHAHAHABACADFFAAGADAGAGACADDEFEFDADAHBGBABDBDBDCHF,True +605,13.0,12.0,3.0,10.0,9.0,12.0,19.0,5.0,BFBFCDGDBDAGAFCHBBBDHGADCEAABAGFGFGEGEGDGFAFEGBGAGEFFGFGEDADBBGAGAGEFEBBHGHGEDDAFAH,True +606,25.0,22.0,15.0,23.0,20.0,14.0,29.0,17.0,ABABABGDEFEFEHBAAAFDDBDGDGAGEEBHFFCAHAGABACACHEGDGDFDHGGFFHFBEDECFGHCBAGDGCHBGBGCGFDADECEBEAEADAFEBEAEFCBCBCBHBABGBHAHAGAGDDEEEHBCEADGDGDHHFDGABDBDGGCGCADGGHHDHGGEGC,False +607,7.0,12.0,19.0,9.0,3.0,6.0,12.0,7.0,CHGGCADECECGBGCGCEHDAFACDBGGFABCBCBCBCBFBCGCBCBCBFHADACADHDCGGGDFCHGFCHDHDB,True +608,15.0,15.0,12.0,14.0,12.0,4.0,21.0,15.0,BGBEFEGDBCGCGHHEGCFAGEBFGHBCCEGAHACGBDBGBHAHGHGHEHEHACABADADAHACBGDAEHGHBDBDBEBAAAFCGCGDEDCDEDHDAGHGDGBGEGDC,False +609,11.0,19.0,6.0,5.0,9.0,14.0,11.0,10.0,BBBBGBFBFBABDHAHFBBAHEHFCAHGGDGDFCBCFCGAHBDBGBGFGHAHGBEEAFFFBFEFEACACEEGEAEDGFHAHBBBF,False +610,7.0,6.0,1.0,2.0,7.0,8.0,15.0,3.0,GGGGGDGFBAEAEBFHGHDFAGBEFEFGFGBHAGAGBCEAEGBGEGAFF,True +611,9.0,11.0,18.0,12.0,13.0,14.0,18.0,18.0,DABAEGBGEGEGEGFDHCGCHAHFHFCCCCHHGADFBGEHAHEHECFHEHEAGABDGEBCBFFFGDGBGACHHHDHCFCDCHHGDCHCBCDCGCBBDADGGGEDECBFFFFEF,False +612,1.0,6.0,5.0,8.0,3.0,4.0,3.0,4.0,BEBEBGBFBFDDCHBDFCHDGACHFHGDCDCDED,True +613,5.0,7.0,4.0,9.0,3.0,12.0,4.0,8.0,DEEHBFGFCHBHDHFAGDBDHDFCFEBHHHBFBABAGAGDFDCDFFFFCFDA,True +614,5.0,4.0,10.0,9.0,2.0,6.0,6.0,7.0,GCBCBCGGBFHHCFCHHDDDDCBGAEACACFDADCCAFHFHDHDEDGFG,False +615,20.0,20.0,21.0,19.0,32.0,21.0,14.0,26.0,FCCGGEHECEDEDBBECHCHCFGBEHECCCCCHCGCDCDEHAGCECEDDBEBABABEBEAAAAHAHEFAFHFEFBFBFAFGEEEAEHEBGHEHDBCBDAAEFFHCGFHHHGCEAGDBEHEFEGDFBFAHHDBCHFFBEGEGFHECEADADADBHFHAHDDFDFHEAEBDBDGH,False +616,4.0,1.0,4.0,5.0,3.0,3.0,4.0,3.0,AGAHCHBGDFDCHEDEDEFCFCDAGAG,False +617,14.0,17.0,16.0,17.0,18.0,16.0,11.0,15.0,EFEFHFABEBEGEAEBEAECBDHFEEGEGBGDHHHHHBHBHBHAFAHDBFHABDDFDHBGDECECEFEFGDABAFAFABDHFBFCGCGBEFCDCEADDDFACAHDCCGDDCBCGCFCABECGCD,False +618,29.0,30.0,26.0,14.0,18.0,25.0,13.0,17.0,HACCBHBFAFBFBFHFCBAAGAEBEFDDBDAAACACACEEDDAEFGBGFEFCABAGAGAGFGCHCAGFBBDFHAABFCFCFDHEHCFBFBHADBBBBHDDBCFABBEBFBADAEBCBHBHFHCBDDHCHGHCACAGAGDFCFEAEBECECECFCECECGHEBAFAEAGHBCF,False +619,31.0,22.0,24.0,19.0,30.0,25.0,19.0,29.0,CFHEHCGFFACEHBDEEGGACFCACAGAHAEAFDCGBACEFGAECCAGHBHBDBAEAGFBABAGACAHHHAHCHCDCDAGGGAHAEAEDGGCEHFHFHFDGBHBCEHEDEFEFEFEAADACHFBDBDBDBFBFAEHFHBHEHEGEDEDCCEBFBFCFCAHDBFEAEFEACAFADEBEHHDEGEAHBHCHDBGBCDHFGF,False +620,18.0,17.0,15.0,24.0,21.0,15.0,18.0,13.0,ECDGDBDGDGDEAEBEBCFGFGAGAGHCDEHEHBGGGFEAAFBBDFHCDCEEEEGAGAGEDFDHDHAFAFHEHDADADBDECACEDDBHFEGECADDCFHBCBCHCDDFDGBBBEAECEDEFABAHCHGDABFBFGFCBGA,False +621,0.0,2.0,1.0,1.0,4.0,1.0,0.0,1.0,FEEDEBEBHC,True +622,14.0,20.0,14.0,20.0,27.0,29.0,12.0,26.0,CDCACEHFHFHBHEFEDEBBFFFFBFECHHAHEHEDGDEEBFHFHAACEDECCCCEFEHAHBHDHFHFAFABEEEGEGEBDAHEEEEFHDDDGDEDABHBAFGFEHABFBABDBFFFHFCFHFBGCABBGBHFHFDDAHGFEFEDHCHDEBGGGBCDDDCGF,False +623,16.0,25.0,17.0,19.0,21.0,19.0,21.0,15.0,BFDFDFGBGDHBHEDCACFCEHEDEBCFDEDADBDACADDEGEGHAHBHFEBCCCAHEHEBEBAAAAGCFCFGFBEEEHBHEHGBDBDAGAEAGBDBGFEFGBCBCFGEGBGHDHGCCAADCDCBFBAGGFGEHDFBEBFBFDFCFHBGGGEB,False +624,23.0,27.0,21.0,27.0,12.0,19.0,33.0,26.0,DHAGAGFBFCCHHGGBCBFDFACGBGBGHCABACAHFHCDCDGFGFCFGFCAEGHGABABEDEDHFHFDFBGHGEGHAHBHCDAGAGAGBBAEAFGCACBFBDDHGHBHDGDGBGDAAAAEBBGBDBDCACFCHCBDBCCCBGFFHDHDHEGEDEHHDDDHBGBHDFFEBDDEEGGGGAGHCHDBAGD,False +625,17.0,22.0,27.0,7.0,24.0,19.0,26.0,18.0,GHECEGFGAGCBEEGBGHGBEBEAEFGFAFCFHGGGGEEECBFBDGGCGCEDGFBHBCBCBCAGABEGEAEABFFFBFBFHEGFGACAEFDBCBCAGAGAGFFCCBEHCCBCBDHCBEHCHCACEBFBCGDAHFCECEDACAEHHHHHDAFGHCHCEGEH,False +626,21.0,20.0,18.0,14.0,19.0,24.0,20.0,19.0,FGFGDBFGAAHHDABADDECCHFBGCEEHGHGHGAFHCHAHBCBFAFAFABBBABADDGEBBFCFCFCFCBCDCDHFAGGHGHGAGEHBFAFCHHEGEFBHDHAHAEDGAGAGEGCDEHECCCBBBAFFFEFDADBBEDEGCFBFCGAEEEEFEF,False +627,22.0,20.0,15.0,21.0,16.0,16.0,15.0,16.0,GBGEFDACFGFGHBHECCFAAAEEGBCHCBCFADHDHDBDBDFDADABAEDFBADACBCFCFEHGCEFEAEBHDHDFDEEBBHBGAGDGAEAEGGHAHDDDDFDGBBBAAAABDHGHFAFECCCECHBDBCBFEFGAGAHH,False +628,7.0,15.0,8.0,13.0,14.0,12.0,11.0,8.0,DEDBDHFHDCDCBBBCBDBFBFCGHGAGEFAFAEADBFBGBGHGDCFADBDFEFEDECEFHHCBEAGGGDEBECEABBGHGFDHEEFE,False +629,1.0,3.0,3.0,8.0,6.0,2.0,4.0,5.0,HEHDHDHDEFBGBGDDCDHBEDECGCEEFGAD,True +630,11.0,10.0,7.0,6.0,8.0,14.0,8.0,5.0,CAHAHABFCFCACFCAHAGDBCEGHFHEBDFAGAGABBBEBCFEFEFBFAFBDEDEGGDFDABFFEFGG,False +631,14.0,11.0,20.0,21.0,13.0,15.0,14.0,16.0,HCFAAHBFCFAFHFGDHFCFBBBEBEAEAEHEHGDDBHHHFHDCDEGECFHFDFDADACADHGEDADHDHDCDCGADDECEAGBBCECDGGCGCABAHFGCDCGFBHBDCDGAGCCCDCGEFEF,False +632,4.0,8.0,5.0,12.0,1.0,8.0,6.0,3.0,CAHAEDBCCFGDBDFFBFBHDDDDDADCGBGBCFAGDGFGFHDBDBF,True +633,3.0,4.0,7.0,2.0,2.0,6.0,5.0,5.0,CBCECACAFEFDAHBCGFGFBHCHDHCHGGFBFG,True +634,15.0,14.0,8.0,23.0,21.0,16.0,17.0,8.0,GDDDADADACBFGFGFAFACADAEEBEBFCGBFHFHGEDDDFCGABCBDHDHEEFHAHGEFDFEFBFAGAFEGDGDGBGDEDEBHBDCEEEEGEBCDDEAECDDDEGGGAFAEBFBGHEDAB,False +635,16.0,23.0,27.0,12.0,33.0,22.0,20.0,34.0,HEHACECAHFBGBEBHHHHFFCECEHEAEGDGDHAHBFFFFFFFGABCEFEBECECHABGCGFHEEEEEEGBCAHEHCHDFBGBCBCBHHGFBHDHCHEHEHCFCGCGEFHHHCDGDEDECBCAFEFAGHDCABHDAEACCHGHFBBHDEAGBGAFDDGCACEFEFEHEHEBEGCCEGBGBCAHBHB,False +636,18.0,21.0,19.0,22.0,14.0,15.0,21.0,26.0,GHABCDDDAGGFFEFDFHBACHDHDECGBFBFAAGECECDAFBHCDCEBGBAAAGHHEHEHEHEBAFDFCACECECEHHHCHDHAHAHCDBDGGGDHDBCCFCGHHHGDDDBEBFCFDGAFBFBDBDBGBGBABHHCHGHGDBEGAAHDCGAGBGF,False +637,7.0,11.0,15.0,9.0,7.0,9.0,10.0,13.0,DAFBFHGDGAGCDCDGHBCECFCGCDEDHDHBHBFBEGEHDADBBBBGFHHAECHGHGHBFCFAACCCFFHGACHCBCECE,False +638,23.0,18.0,27.0,21.0,18.0,14.0,17.0,30.0,DEDCHCBFEAEAEABAHGDGDADEBEHCFDGGCCCCDCBFGFCCHDHDHFBABDHEHAHFHCAFAEADHDHCHEDACCGCGCGCBAFHHHECDDDBGHHHCHBHAHECFBBGBDBFHAHGHCDGHGCGCBBBGBABFGCGAEEDFDAEHFHDHEEACAEFEACHCAAA,False +639,8.0,5.0,5.0,6.0,7.0,4.0,6.0,5.0,FGEBDBDBGHGDGCAHAHCDAGAFAFBEBEGEFDCHAEECEDACAH,False +640,25.0,30.0,19.0,18.0,18.0,25.0,21.0,28.0,DBGBFBFHFHCAFAFACGCHCHEHEGFGADHHFEAEGEGHGEAEBDADHBABDGGGGHBHDDGAEBDFCGCFFGACDHBHFHCHFAGHEDACAHBDDDAHHEBEBABACAGBDEDGHBHFHFCGCDFBFBFAHGCBDDCBAEAEFCABABACACEFHFBAEHEGBGBHBFFHBEBFBFBFHCBC,False +641,10.0,7.0,19.0,15.0,18.0,26.0,16.0,17.0,EBEBEADCFGFGAADCEFHCAEDEAEFBHEHDGDGDBHCGCFHFHCHFEFGFGCECFCGCEDAFEGDFCAEADCFEFHHHFDFGFGAGDGDFHHGACFBHDHCGFGFCHCHCHCDEECFFFFEBEBFD,False +642,17.0,19.0,31.0,20.0,20.0,27.0,31.0,22.0,EFGFHEBFAHAHFHGCFCFGFHFBFDHDAGAGBECCHCBGBFEABDEGEGFCBDDFEFADADBFEGEBBAEHEHAHAFGCGCGCBCBFGFCACHCECGCBCAGFHDBDCAFGCGCGCGCDDDCDGDGFBHGFFAHCFCFHECDGDBECCCDCEGEFBFEHHGAGCGDHAHGHEFDHAGBGBGHDECE,False +643,10.0,16.0,8.0,13.0,16.0,18.0,19.0,19.0,DBDFCEGABABHBFGAHEGFFDHCFCFBDHHACAFECHHHHGFGBEHEGEGEGFGBBDBFEFHFCEDECFAAGFGFEBAGHEHEHEGDBDFDFBEBDBDFDBGEHCAAGHGHGBGHGHD,False +644,23.0,23.0,24.0,17.0,10.0,17.0,18.0,14.0,BGGGGGEGBACCECHCHCACDBAEFEFHAHACFGGADDCDCDCDGHGCBHBAAFGFGFABBBBFBHGFAAADADCDEACDEACBHEEFCCHCHAFBCHGEGBFDFHEBBHBDBCHDBDBGFCFBDCGFGFACABBBAAAAAFDCDC,False +645,19.0,20.0,19.0,12.0,21.0,19.0,19.0,26.0,BCHEHEABABAHAHDHBEDEAEGECEBECAHDGCFEFCHHAHDHDHFBDACABGCEBHBCFHGCCCAEEDAACABBHGHGHFHBEBHDECEBDBCBFEFHHHGHGHGHFHFBDGEGACEFDFHFEFCGGGAEFDFGCGABFFCFCGBGAGFBAEA,False +646,24.0,19.0,25.0,16.0,26.0,22.0,27.0,28.0,DADGFHCDDBDHDHGGAEECHHHFCAGACFCFEDCCECEGFBFBCBGEHEACBCBGGHGAGFHCGCGEFEDAHAHFHEBBBHHAAEAECBGAAFBGBHBHAAFEEAECEGHGFCDCHHHHBDFGFGFGBEAFHFDAHAHCBCEHGHGFCDGDGCGEFABDBFBAAAHADEDEGCGHECEFEFECECG,False +647,19.0,19.0,11.0,23.0,12.0,13.0,15.0,22.0,FGFAADEGEAEADGDFHAHBHDGGGHDFBHBDDGDCDHBHBHEHECEDBDBEBHHDHEABCCGFAHGGEADAGFDAHEHDHDCDGDHHEHFFFGEGBDCACACDFDHBBBBDCGAAFAHABABACACFDFBBHB,False +648,14.0,18.0,21.0,17.0,4.0,13.0,14.0,14.0,HDCCBGAGBGFGFHCCACHCGCBCBEDEBCBDBHFCFCFGAGACBGFDFBHBADAGHCHBHFCACDFDBABAEGCHHDBDCFBECGCGBDAFFGHDBDBDADADACFDADCHHGH,False +649,18.0,10.0,20.0,21.0,15.0,23.0,20.0,19.0,CDCFFDAABAFGFDBHFHGADADAHGHGBDFCHHHCDCHAHADCDGDGDGCEFGFCECFCFCGCAAAAEAEDBDBFFHHHFECECGGEGAABHECFHDEDGHGAEADFFHGDGDGEEBDCFGEHFCGCECEDDFFFFBFBCBHHAG,False +650,2.0,8.0,12.0,4.0,7.0,2.0,3.0,2.0,BECADGCCCCCBCBCBDGGFECECDBDBHECEFABHBCEE,True +651,23.0,17.0,14.0,13.0,18.0,7.0,9.0,12.0,HGFCACACFCDEEAGBGBADADABCGDAEADGDBACFHBEDAABHBHGHCAAEBECECACEDECEGFGAAHABAEAHDHABABADEBCFCFBEEEHEBFBAEHEHDCDBGBHD,False +652,9.0,5.0,7.0,3.0,3.0,4.0,7.0,7.0,FHAHAGGGGHGCGCEHEAFAFCHDECHBABCFGBHBACDCDAABA,False +653,17.0,14.0,10.0,12.0,16.0,15.0,12.0,13.0,FFDCCCGHBHEFBAEAHDFFFHBBBBGAFABABAEADAEFCBDEEHFDACHCHDAFCFEDGBCBCBEBEGGGCHHDDAGAEAEDEDEBEHDHAHEFGFGFGHGAAEAFG,False +654,18.0,23.0,28.0,27.0,18.0,13.0,30.0,25.0,CGCBCACGBGHACACADFEBGBCAEHBDBCHAEDGDFDCCAEHDGDFDFAFBGBGEDCFBFBFDAHGCCCBGBHEHAHGGGCECEHEAGCGDGDHBBDGCECHAHDFDGEGAGDGEADHCACBGBCHAHAGBGHHCHCHGEBEAEDECHBGBGDGFGEGHCHBDDDCDHDFDHCFEHDBDBF,False +655,15.0,11.0,8.0,7.0,7.0,6.0,7.0,13.0,EFAFACBEEDCAHAHGEAEFFHBHBFBFHGAAHGHGAGDCBHHHABDBEBAGAGDDDADHBCBEACHCACACHB,False +656,23.0,17.0,14.0,15.0,23.0,23.0,21.0,14.0,DBBBEEGCGFABAGAHAHFDEEHECBHBFBEAEADGDACGFGFCFDFGFGFGBEBEDEHHCFEHAHAFAHEBABEDEFGFGBGAAECFCHCEAGDGDCBCAFHFDFDFCFEEEEECFDBGGGAAADBGBHDAGEEBHDAAAHFGCGFAFC,False +657,22.0,13.0,20.0,11.0,19.0,20.0,13.0,19.0,AAAEEECFGGCCCDBDAFHFAFCCBAAHBBBEBFBAGCGEGHCAEACDCEADBDEAFCDGECEGGAGABAHAEBHHHHHCFCFEHCHFHGHCHCFAFDFDFDHBEGEFFFFAEAECEDEDHFGABFEGCHCHAHABF,False +658,13.0,8.0,9.0,8.0,6.0,14.0,16.0,11.0,DFDAACADGHGFECCGBFFFHEAAFACAGFHCGCFAFDFBBHHFGAGABABAGEFEFGDEBFBDBGACHCHCHGDGHGHGEGDGH,False +659,24.0,22.0,11.0,20.0,12.0,19.0,20.0,10.0,ECECBBAAAFHDHDHCBGFGFACABAGGHADBEAFFDFDFDEGCGCBBBFAGABBEDGGAGFDAGHGDDAEABBGBHDGEBFBHDFGCBCBEBFDFDADADBBFEHEFEFDFHFEGDCDCDCGBGAAAAAGAFAHBGA,False +660,9.0,8.0,11.0,8.0,16.0,14.0,26.0,11.0,FEGEHCHBGBGEGHGHGEGHDEBHAFACGDGFGACHHGAFCGGFEHDFDEEGBGBGFGFGCCECFAFDFDHBGDAAHAGEGDGEGFGAGEBCCCCBEEGEFEF,False +661,21.0,16.0,26.0,12.0,16.0,24.0,13.0,16.0,AHBFGAHHBCBABABCCGBEFACECGHGFDAHHCCECFFFDFAHACACBCBGBDFEFEHEDACAEDEDEGEGDGBBBGCGAHACACEFAFDFAFBDACAFFHFCFCAGEGBFDFBFEGCFCBCFHACADDCHFHFCECEHHHCE,False +662,19.0,21.0,19.0,34.0,20.0,23.0,22.0,19.0,AFAFBGBGBABGDDADCFCECGGEAEACHDHDEFCFDFDECHHGDEDEGGFEBBBBBEFEDDFAHCBEDDBACDCDAHAHGHDCFCFDFEFEDHCHDDADBGCABDHEBBFBDCDHDEDEABDHEBFBCEAGGHFHEAGFGFGCGDGFGDGAGAGABFBFDDHDCDHHGHECDCFAF,False +663,30.0,32.0,21.0,26.0,25.0,15.0,23.0,18.0,GBDHGHGHGBGFGABAEEDBCBCAHAEEDFDADEGCCCGHDBBBEDHGGFCBBHEAACDBGAGBGFEAAAAAABADGGBGCDCFCFDFCBHAHBBBHBHGDBDEHBHBHBEAABABDDEAEDFDEBEBECEGEFAFCFCADEGCGBABABFBCEADAEGEGDCDGBFHAEAEFCDDHEHAHFDCDEDCAC,False +664,14.0,12.0,16.0,18.0,20.0,25.0,19.0,23.0,GFFDFGFDEAHBCEEHCFEEEABFGFGHGAGAGCGCFDBDBDEDEABABDBHFCFHDGAGEHEHEGDCDCFAAGAEEHFGFEDCHFHGGEHDDGBADDGHFHEHEHECFCFCDCAEFFFGFGCBHHCCFCFBFHFHEDADHHHHABB,False +665,1.0,1.0,5.0,0.0,2.0,0.0,2.0,0.0,CCCBGGAECEC,True +666,13.0,18.0,8.0,9.0,12.0,13.0,18.0,15.0,FADABCFAFAFGFGFBCBGGGFGDCDCABDHDAEHEDGDGEFFHCGEHHFHBGAGAHEGEGABFCGBGEEBEHFHBHBHBHBFBHCABBHGEEDCDBABABHGGAE,False +667,12.0,9.0,6.0,10.0,3.0,13.0,8.0,9.0,CBCHGHFADHGAGBCFDFAADDFCFHDAAAAAFCFEAAFADCDGDGHFHFHGBFBFBEBHGHGBBDFDEB,False +668,25.0,23.0,24.0,17.0,11.0,21.0,16.0,12.0,GDAFFFFHBBGCACGCECBHAEDBBFFFBCBCACACGBABEBEDDBFAHBHDAGAGBGBGAGBGAGEDBAFCCDCGAGHCDADACAEDFHACBEAACFDDBDBHBDBDFFFCFCFCFCAAAEDHFAFHCHCACHCGAGFFCEEBEBGDH,False +669,3.0,6.0,1.0,5.0,4.0,4.0,3.0,1.0,EABGBEBGBFBGDFDFDADEDBFHEAC,True +670,5.0,9.0,11.0,15.0,8.0,21.0,12.0,11.0,DFDCHCFFDHHAHACGGFBDBDCDCDAHEFFFHBDBDBEECFGDGHGBFCDADABHBHGGEGCCFFFFFDFHEBGCEFDFGFEFEHDGFGFC,False +671,9.0,14.0,11.0,13.0,12.0,14.0,11.0,23.0,HDHCHCFCFCHCFCDADADEHFHBAEGFGHCEDHFCCDEHAHFEBBBADCHHHHDHBHEDDDADHDBGBGBCBFHEBEFGBGHGFFHAHGHBAFAGBEFEBEHEGFG,False +672,3.0,4.0,0.0,0.0,2.0,6.0,4.0,2.0,HFHFAAGEGFGFABBFGFBEB,True +673,17.0,21.0,20.0,5.0,12.0,13.0,17.0,15.0,BCBDBECHCAAADCGGGGFBABABEBCBCACAGHBHDHBFEEEEAABCBCBAAHBGGCGBGHGFGAGFFCHGHGHBABFBFHCHADDFCCCECECHHEAFBFBCHHBCEGGCFAEAEGFF,False +674,14.0,34.0,17.0,24.0,19.0,23.0,30.0,24.0,BBGEGHHHEHEFABDCHCFBDAGBBBBDBFCFCFAHHEHAFGHGEGEDBDBDHCFCHCEDEDEDGCGCDDDGDGAGAGEGBHHCHADFDBBBCDDACGHGEGEHBGBGHFEFGFBBDBHBFBDGGCGCDFGCBBBDADGHFCFADGEHFCFAFGBHFHBGEAEBBBAFGGDGFEFBBHEHEBABF,False +675,22.0,22.0,20.0,24.0,22.0,17.0,36.0,34.0,CHGHGHAHAHCECDBGCADHEEGECDGBFCCHCHFGFGBBHFHFHEGFGAGCGCGDGDCBFBFEFEHEDECCHBGBDADHFHEBDBGFGBAHGHGEACGGAEAHGBDCDGDHFHBHCECBDHGGGGHBBDFDFHAAAAAHADADHGHEHAGFGDGAEDGDEEBHACFGHBHBHCGGGCAHEEAEHEFDDDGDBBBAE,False +676,5.0,3.0,7.0,7.0,6.0,1.0,5.0,6.0,EHCHEBAGEGDGDCCCCABHEGBAEDEDCDFDADAHHCHG,False +677,14.0,12.0,18.0,20.0,14.0,12.0,11.0,15.0,CCADHGFACAHGHDDDDDGFGHBADGBEBCCDDDADADABBHCFCFHBHGAGEEEEEEEGEFHCDFAFCCADBDCDCDCBBBBCHCBDAGAEHDHAHAEEHEHFFCGCDFGECFFH,False +678,20.0,18.0,16.0,16.0,18.0,22.0,18.0,25.0,DFFHFHFGFBADAGHCBCAGBCBFGFACBEFEGABBBEGHHFHFDFHEEGEBECFCEBEGGADEDEAEACHCHABEHAHAFAHAHAFBFAECECHCHGHAHBHCHFHGDCHGHEBDBDGCADEDGGFBFGDBDCFFEHDFDFDGDHCHBGAAA,False +679,13.0,13.0,11.0,11.0,12.0,13.0,13.0,10.0,DADAHACGEBDGEGEDEAACHFGEGEGFGFCFAFEBCBFEFHCCFCHCHEHAFFDBBBHGCEBGBGAAHFHGHBFDEGAGBBBBDDADADEDACFC,False +680,21.0,9.0,11.0,23.0,10.0,11.0,13.0,22.0,BHEFDAEAEGGAGBCHCBAAHAFDFGGGGBHADEDACFCFAEABHBHBAAADFFACDDDHDHCBCFHDHCHGDAHAHDDDCDADEHFFAFDEHHDHECDADAGAGBHHGHEHEHCDGDGD,False +681,29.0,26.0,19.0,24.0,29.0,20.0,27.0,23.0,AAHAECBCBAADACAFFGCEADCBGHGFEFEAEDEDBDHDEBHDHAACAHAEBCBDFFHFBFBFBFGFBEAHBCAEAGAGBEEEEEEEEDCABFGFBDHFAFAGBGHGCGEGDADHDFGBCBHBHACEBDADEDEDGGGGGGGBHBHDHCFGBBEHCCAHHFABDCGGECFBAHGDGDCEAEHECEGHDFDEDGAHA,False +682,12.0,18.0,15.0,23.0,25.0,24.0,20.0,8.0,DADHGFBFDADAEECECBFDHDBCBABAHFFFFEFEFBFBFBEDFDEAFCCHEBBGECCCCFAGBBDBGCEEDHGGEGEAEAEFDDDGDAFEGCGCGCFEDDGDFHEDGGGGGEBEDFDEDHBEBDCCEFFFEFEBABFGAGHGD,False +683,10.0,19.0,7.0,19.0,5.0,6.0,8.0,11.0,CHCGBDFEGADBBBBBEGHAFAHBGFACAGAHDBDBDADHDGDBDCCCEDDHDADADCDBBBHBFBDBDFDADEHHHBHGGEFBB,True +684,10.0,3.0,3.0,5.0,2.0,4.0,6.0,12.0,DBCHHBHEDEGAGAHFGGHFAAAGAGADBCHAHAFDFDACHHHHH,True +685,10.0,19.0,16.0,24.0,9.0,16.0,18.0,17.0,DGDFEBDHDADCDBDHFHFHAGCHCHAGEEBGBGBAFDHCBADCDHAHEEABDDFDFABBCDDADCDFDFBBGBGHECCGCGDECGDBFGGEGECHCGFFBFBDGFHBHBHBCGCGCGBDDDFHFHFHA,False +686,11.0,7.0,14.0,17.0,14.0,20.0,12.0,14.0,HDHABCEFFBEHCGCACACBHBGEGEFFFBGCECDCDEHEDEGFGFDDDDGDGAHDHDADADFFFAHAEDHFBADEDBCCGHAEEECFFEFCFHFGCGAHDFGFHFCFH,False +687,19.0,24.0,19.0,21.0,13.0,20.0,17.0,22.0,GBGCDCDHFCAHAHBFFDCAGBFBABCFFBFACBGHGHBFFGHDDADHFHFHBGGHGAFDFCGAGEDEGEADDFCBABFBABAHEDEGFGFCBCFDDADACECEBEBCHCACFEGCHBBBDDDGHHDHAHAFABDHEHEHEGEDBABCBDBHCHC,False +688,11.0,6.0,12.0,7.0,7.0,10.0,7.0,5.0,CCBGGGGFABECFADHEACFCFGFGEDFCFAFBHBCBHBDCCHCAAAAAEDDDDAFCFCEGEAEH,False +689,1.0,5.0,2.0,2.0,0.0,1.0,2.0,2.0,DHDGFGCBBBBBCHA,True +690,15.0,19.0,20.0,21.0,26.0,23.0,15.0,18.0,GBGBGEFEGECEDHDHDHDHDCGAEACGCFBFECCACGCDEDFDHDFBBBEBDHGHDCBAAAFBHADFBFHFHFHFEDDADEDEFCBBAEEGEACCHCEGACEDECECFFFFHAHEGEBABEDFBHEDEAEADFDCHFHFCGEBHCFFFGBBECGBG,False +691,16.0,20.0,16.0,13.0,21.0,17.0,19.0,17.0,EEBEDECEAEBBBBEHFBFBFDCDCBCBCAFGHGCECGGDHAHCDCFCEHDHDBBFHFGEECBGBFHDHGHEBEBEAEFBAAAAEAGGGFEFCFBABDFGFDFHAEEGHHHGDFHFGCGCGDAAACADEGBBCAHGEGH,False +692,15.0,18.0,25.0,15.0,20.0,16.0,23.0,15.0,DCAGACABGEGHGBBCAEGHHDAAAFGCBCBCGGDGCGCHCDCDAFCFGHGCGCEEEHBGGECACADEDFDFGFDBBFBCDCFCDCEEHEHFDBDBGEGFFBFBFEECHGHBAGABABEHEHGCEHBFDCCGDHEHEGBFAFAECEC,False +693,18.0,15.0,17.0,18.0,19.0,18.0,17.0,13.0,DAEAFACADHDHCFCBBBDFDEGEGEFDGBEFEBGHGHEHGGAFAFAGAEDEBHDADAEAEDEAHGHAHCECEHFHBGFAEAFBCGFDFGCACADFCGCBCBDAHFBCDEBCFCFGECDBDBGBGECECFDDHFG,False +694,7.0,11.0,9.0,10.0,9.0,4.0,5.0,10.0,CDDDBBCGFGDHDHEHBHEHEBEBEAEAFHDEGEDHBAAFHCBFEGCBCBCBAAHACCCGBHDDD,False +695,9.0,7.0,7.0,14.0,15.0,8.0,16.0,16.0,DFDCDCDEAHDDDBHHFHFCDCHCFBAEEDGAEAGGFGHAEECHGHGHEEGDGFEFEDEGBGEDDBHBHGEGFAHAEAHAHGBGHGHGDECB,False +696,24.0,23.0,24.0,22.0,20.0,19.0,26.0,26.0,ADGDAEBHCGCHCEADABGBGBFEEGFAFAFBFGDGDHHACDCHFACHCGGHGHDHCBGDHBACHBHGHGAAEBFAHGGDGHGFGDCDCGCDCAEGGGEEEEEHDFDAAAHADAFADEBBBHEHECACBEEEBABFCFCFCECFCHBHBAGABHHFHBHFCDEBCDGDFDFDCBFBCBEAGDGH,False +697,19.0,24.0,22.0,23.0,29.0,24.0,25.0,34.0,FCFEAEAHCGEDABFEFDHCHCGCGCFHABDGEGFGFGBHBCAEEHGBCBCBCGHDHFHABGHDHCCCAADDFDHDCDHFBEHEHEGFBBHHHADEEEBEBFACHHHHGHGABBBBEDCBBBEDEDFFFFFFHCHDAEFEGDGHFBDGEHHGFBDADECEDEDGFBFEGCGHHCHCHGHEFEAAGAGEGDGCAHAEAEBD,False +698,13.0,19.0,14.0,18.0,18.0,16.0,11.0,16.0,BDBFFDFDFGGHAHBHBHBHFGAGAHDHBEBDBHBFBFHCBEGEGEDCCCCBGHECDCACDBFCEDBDFDFDHDFEFHFHEHEFEBABDEHBCDDHAAADEBAGAEACGEAEFBCEGEDFCCAGE,False +699,20.0,17.0,18.0,13.0,20.0,22.0,16.0,23.0,ADHHHHFDFBFAGADBEFFFEFEGCFBDHCAEABAEAEBHFECCFDFHHHHHFHCHCHEHEAEBGHACABFCFGAGDFDFCBHGCFCBCHDEDHGHAFDFAGECECEFAGCDEGEHEAABCBGBGBGBABGEAHGEAFHFGCECADBDB,False +700,7.0,10.0,13.0,7.0,8.0,14.0,8.0,3.0,FAAEFBFCFBFBEDGHCCCCCEDEDFHECDBDGFGFADGBEFCFCGAAAHEDECACFBFBGGGFCFCBBB,False +701,16.0,27.0,21.0,29.0,23.0,22.0,14.0,18.0,ABAEADACBDBFAFDCGBDEDBBFBFADHHAABHDGABACDBDEAFCHCECHDDACAFDFDFEAEDHDFBFBFCEEBECDCDHABFBGEGFHFHGBDEDEDEDCDHDHFAGDGHGHGHBCBCBFHCEBEHCCDCBFBFBECFDGGGFCECEDHBGBCFEEDGBFBEHEDE,False +702,22.0,31.0,14.0,20.0,15.0,20.0,18.0,12.0,GHADBDAFCHAEBDBDBDFDEAAABADEDCAABBEGEGFGEGFDFBFBAEGBBCBCBEGDCDAHCHBADADGFBFBHBGBDCFGDGHCDCFCBEAGFGFHFEBECAFBFBHBHBFBEGEGEBEDAHABADABBGBCAAGDFBAGHCCFDFHF,False +703,21.0,26.0,13.0,16.0,14.0,14.0,14.0,17.0,CHABCBFGFAABAGAHAHAHACBDFHAHEHGCACDBEHDGBHCECEHFAACABHBABABECGBGAGEFCGDEFHBBFAFHFHAHEBEFEGBGBEBEDDDDDDDAHHCBCDDGEADABGBDBFGFBFBFBGEDCBB,False +704,1.0,0.0,1.0,1.0,3.0,1.0,3.0,0.0,DEECEGFGAG,True +705,7.0,6.0,9.0,6.0,4.0,3.0,8.0,5.0,AGABCBCEHFACGFHHCHEACADDDDGBGBGBCEFHBDEDACGCGCGA,False +706,6.0,5.0,9.0,7.0,4.0,10.0,8.0,4.0,BGHGEDCHCHCGCFFGDGDGCBCBAADFFAFEFGAGADFHBAFCBCEDEFCFD,False +707,10.0,10.0,4.0,9.0,12.0,8.0,9.0,7.0,EECFAEAHAHAEAEBEHFDFDAGCDHBHGGEGEGFDFDEBADDCHFDDBFGEGBGBEBEAHAGBFBABC,False +708,11.0,14.0,22.0,17.0,26.0,26.0,22.0,25.0,ADBFFHCHCHCDGFCFBHBHBAGACHDFEFHCBGECDDGEHEHDHEGEGEGECBHAECDHDCDEEFHFDFDABHGDEHEGDHDGFCCCHCHDHDHBAEEGEHEHGGGBBFEFEDEFHFCFAEHECGCAFFFCFBBCAFBCHEEGEGFFECGCGFGFGFAFAGB,False +709,20.0,25.0,16.0,17.0,13.0,14.0,18.0,22.0,CDEHBHBHAHBHBGDGEGBACAHAHGBGBGBAAAGFDEEBGBABABFGACACHGHDFDADHEFDHHECFDACABGHFHDDDAEAEDGDCDCFCBCFHBCBEBEBEBFCGCHFEGGDDBBBCEHGDACABGHGAFHHHBFAFCFHB,False +710,30.0,23.0,16.0,22.0,21.0,35.0,15.0,23.0,FAFAFAFEFEHAHAEBEFDFDBDHFCEAHHHHBEFDADHEHBCCCADEHFHFHFCGGDECGCBDBGAFAFBCDAHADBECEFHCBCBAAAFAGBFADDFDFHBGAAEABFDEDFHAGAHAGAGEGHFEFCABAFCBEBEBHFDDDFDADEEEFBFDACEGFBDBHBHBFGFBFCFGGHAHAFGFC,False +711,6.0,6.0,12.0,7.0,12.0,9.0,12.0,10.0,HGEDHDGCGCGBHBHGCFAGABCBGGEBCHCHFGDEEEHEHAHFHCGDFEFAFAFDECECDCFABCGEGFCEDE,False +712,23.0,31.0,32.0,27.0,25.0,14.0,31.0,14.0,CGABCFCEHDFDHEHBDBDECCFBDGHGAGBGCHCBAEHEHDFDBDCEFGCGCFBAGGGEFEABFBGEAAAAHAGACACECACBGDGDBHBCFGHGBCAAAFBDDDDDDFGFCECBBEEGDADCBEAEAFDGEGCCBCBCBDGCECGCGCGCECECBFBDBABDBDHDCEHEBECGAABDBGGGDEEGEBBAHGGDH,False +713,4.0,5.0,5.0,9.0,4.0,5.0,6.0,6.0,BEFEACAHDHDHGHBDCHCDEDFDGDBEFGDGDFAFBBGACHCG,False +714,18.0,19.0,22.0,14.0,25.0,27.0,18.0,19.0,GEHFCECFCAEFBFAHBCCEBFFEFECDADEDEAEFEBECECGHGAAADAGHBFGFAFHDEABBDGDEHEFEFDBCHEGCCEFBFEHHHHGHGCAFAFHFHFGEHEHCGDFEAEAGFFBADAFFCFABGBABFBCBGBGCDCDHFHCECECDHDBGBCBCGG,False +715,17.0,8.0,11.0,12.0,13.0,12.0,12.0,14.0,BAGDHBHDHABAEGHFDADFECDCGCGADHDHDHABCBHGAAFBFBEHEAFCFAGHEBCDFDFDCHCHCADAEHEGEAEGCGCFEHAGGFAFEFEAEAG,False +716,16.0,17.0,24.0,24.0,21.0,17.0,16.0,24.0,FCBCBHBCBCECDCDAFFHHHCHDBEFABAEDEDEDECFDGGGAEFEFEHCADAFACEEECFCGAEDEDGHGDGAGFBHDHFHCCGEGBDHGEBHHHEHACAEGFDFDHCECBADECHHHBBBFBFBDADCCFCDCBCDEDHHCGDDAAAHBHGHGDGF,False +717,30.0,23.0,30.0,24.0,12.0,21.0,21.0,16.0,ECEDACAHEHCACECDCGCBHAGDFACBCBAFGFGBACCCCACFGEGFHHAHABGBEFFBFDFCGABCDCBBBBBAADADGDFDFHFDCDCHFBFAAGAGAGAGFCCCHABGDGDBDCDEBHDCDCDBGFFHHGBEAAHAHDFDEDAHAGDCDBHAFGGGBABDFCACACBCFEEAE,False +718,8.0,9.0,11.0,13.0,10.0,18.0,7.0,15.0,BHBGDHDHDEAEFFAGAGABHFFFADHDHDGAFCDCAHBDECFAHDHCCBGHFCECEHEFDBDCDGEGDBHBECFCFCFHBEFFFFFHFHE,False +719,12.0,23.0,32.0,23.0,25.0,25.0,24.0,32.0,ACHDECHBHFHGHGHDADAGHCCEBEBCCGHFFGFCBEGCCDDDBGFDHDHDHGFGBCFCGCDCDCDCFGEDBDBEGGCFEFEHEBEHECBFDCDGBGEGBGEGCFEEECGFGADCFEAEADBBCECEHEBEDFHFCFCAABGHHHHHFAFABCCHCFCAHEHFBFBFHCGFBDGDEBHBHCECGDBAFHHHHHDH,False +720,9.0,6.0,1.0,2.0,6.0,3.0,3.0,2.0,AAABABDBGEHAGABCBGFHEAEDEAEFEFBA,True +721,4.0,4.0,5.0,4.0,1.0,4.0,3.0,0.0,BGBCACGCDDFDFABACECBFAFDG,True +722,16.0,8.0,13.0,19.0,18.0,17.0,9.0,17.0,DFEFCHCGADHDEDAHEDEBFHFEFEAEDEDHAHADCBAFACAHEHDCGCGCDCDHDFECEBEDEDEFGGABFBFGCACFDFAFBDGFHCADHEHEGDAEAHHHBHFHFADCFEBGA,False +723,20.0,21.0,15.0,7.0,15.0,20.0,22.0,15.0,AFCDCFCFGFGAGBCACBHAAFGFBBEEAEGHDEDBHBHEHBCGEGFACEGHGHGCGEGECAFFGEGEGEGBBFAFDCBCFCFADADBHEAEHGBGHGBAFAHCBADFBHBCBFAFHBABABAFABHFGFGEHCG,False +724,22.0,23.0,14.0,13.0,20.0,26.0,11.0,21.0,DEBABADADEGBGBEBHBCCAAEAFFDAAAAFEFAFGFCFCBHBCFFFCFBFDFEHHDHCHCFDEDHBHBGAACEFAHHFABAEEEEGBCHCECACGDHAFDFHFHFEFHAGGGFCHBBDBHBEBFBFHHEHBBBABEEFGFEDGDAHAE,False +725,21.0,25.0,25.0,29.0,21.0,32.0,25.0,20.0,FGGGCGEGDFAHHHCCCGAEABFBEBDBDHDCDEDAFGDGAEFCFCEAEADABCBGGGGGCDCDCFFFEHACBCBCGCFCFDBDFCFAHBDDFDFBEHEADCDFHEHFFEGGDGFHEGEBBBDHEAEAGAGAHBHAAGAHAHDDCBCFFFHFEDGDHDBFBEAHBFBEDFCHGFGDCFEGCHCFBFDEDFDABBFBCB,False +726,16.0,20.0,16.0,17.0,10.0,18.0,13.0,17.0,BBBBGCACACBFBABFBCDHGBCHCBADABFCFCFGAHEGBGEEEFDGDFAGAGCBCEFHFHGHFHAHFDFCHAHAGEBDBDGDCDCHFHBDDADCBFADEEEHHDGFGFHADEDHFHCBCBABADF,False +727,10.0,29.0,22.0,26.0,22.0,17.0,21.0,19.0,BCBCBCBDAFHFCECDCDCBHECFCGAGDGBHFDGDGBGBEDEDEDBCBAFAGHBHDHAADBDCGFGHDBDEGEFBBBCBEBEHECDHEGDADCDHDBBGCEHFGCAEAEBEBFBHADCECFCFEDGHGHBHFHGHBCFGBCEFDHGBGFGEBEHEFFDDBDECGD,False +728,11.0,13.0,13.0,11.0,13.0,20.0,15.0,18.0,EFFFEBCDCHCAAAADFHFHGAFDFHFCFBEBGCGAFBCACAHAHEDBBGEDEDCDGBGFGFGCHCFFDHEBBCGGGGGDFHAHDHBFFCHHDHEHEFBHBHECAGEGEFEFBH,False +729,26.0,25.0,13.0,24.0,26.0,16.0,21.0,19.0,DBDFABGGFGHEHAAAAABFBFBGBDBABAGEGCGFEEGEBEDHAEDCHABCDEFAFAGDHHAHADAFAFGBGAGHBDGCHHHBFFEAEDBDBEHDBBEDDHDHDCBCBEHCACDHFCGAGEGDDBEBEBEAGAEADABAFFFFEHGCGCEEEEBEGDHDGECEABHDCD,False +730,16.0,17.0,13.0,13.0,6.0,15.0,8.0,16.0,CCHDADACCDBABEBHDFBEAGBGFCECHBAAEAEDEGCHCHAFBHGHDBDADAFBDBGBHCHCAGAGHHCDCFFDFBFBADFBFBFHAAADBFCFGFBFHHHH,False +731,16.0,23.0,24.0,23.0,24.0,17.0,32.0,25.0,FFFFFFFDDEDGGHGHGHGFDHBCACGEGEBEBECFFBFBDECCDEHCFGEACHDHDHCFDHEGABHEGBGEAEHBAGCGHGHEEEDEDHFCGDGBAHAGAGDGBACCEAGAGAGAHFBCHCGCDCHCHBDBGBEBGCDFDBCBHEHEHGCGHBCBCGCAADDDGHGBDEDEGBBDFEAEGBCH,False +732,2.0,3.0,2.0,0.0,1.0,3.0,2.0,1.0,FCFGFHCBGBAEAB,True +733,6.0,2.0,3.0,2.0,1.0,4.0,1.0,4.0,BFFCHCHCHAAFADBGFDAHAEA,True +734,5.0,4.0,6.0,8.0,4.0,8.0,3.0,7.0,DGHGDEDEFAFBFBDDEAADFDHCHFAFBDGHHHHCCCCFCFBEA,False +735,11.0,7.0,8.0,6.0,4.0,4.0,8.0,5.0,CHCACAGAEDFDCBHDHFHBCDDHAFGGGCACAGAGBBBGBEBDFAAGAECEA,False +736,20.0,16.0,16.0,26.0,10.0,23.0,15.0,12.0,BDBHCCEBDBACHCDFGFCADHDFDHAECDAGAGCFEFCFEDDDDDDDCFHHADFDABEGGGAGAGADABAFCFAFDBEBEGACADDDHAHBECHDGBGBDDEGEGDBFCFHBADGHGHFFFBFAFAFCFCFBFCFBA,False +737,23.0,11.0,24.0,14.0,10.0,9.0,22.0,11.0,FHADCDEAAAABDBHAFADADFCGGGHGAEAHCGDDCDCDHAHCGGGGCACFCBCBCGCHAAFAHEBADAECGCGCGDGECEDGBFCDBAGACFHAEGCGEGBGCECHGGFHFABABABCCDCE,True +738,26.0,23.0,28.0,29.0,22.0,16.0,18.0,26.0,EHDFFHFHEAFFBBEHDBBBDBDCGEGEGCBCDGHAHDEDEDFAFGCCCACBDAGAEFHFHADAFHCDCDBDHAAAAAHCHCHFHFEFHCHFBAEDHCBCBCBEBDADGDAHAGACACBHEDDDEHCHBDECCGBGBHDCDHDBGCCBGDGCHHGFBAEGEAFACACBCEEEEHEGCGAADAEBGDDD,False +739,8.0,2.0,10.0,6.0,9.0,6.0,10.0,6.0,CGBDCDCHHEEAEACAEEGFHFDDDDFGFEAHCCCCCBFGAGAGEFAGAGHCEGEGH,False +740,11.0,8.0,17.0,13.0,9.0,9.0,18.0,8.0,BGAGBECGDGHFHBHBGDGDGCCCCCCFCFDFAFHBDADGDGBBCACAFEDGDHCECHAEEEBDCGGAGFGCGDAAEDEACHEHCCFGAGDGF,False +741,4.0,2.0,8.0,8.0,5.0,1.0,3.0,4.0,CECEAEHCCADDHDHGGEBHBECFCDDDDCDAGAC,True +742,2.0,9.0,1.0,2.0,5.0,5.0,1.0,4.0,CBHEDBAFFDBABEBEBHFHBHBFBGEFE,True +743,18.0,19.0,21.0,21.0,22.0,11.0,26.0,21.0,EAACDDDHDGEGBHHHHEBEBABHEHBFGCGDGEGCDCDGGCGHFFDFBBGACADADHHADCDGDGBCCCBEDECAGHGHBFCFEDEDEGGCBEFEBEBEHADBHBGGGADADFGFDAEAGBBHGDBHGHCHCACACAEFEGHCECEAFHCHBGEGECA,False +744,31.0,23.0,20.0,24.0,21.0,22.0,28.0,21.0,DADEBEBEDADABCBFGGGGGHGHAFFGBGBGCGDGFGHBCCFDEHEADABAGGBGFCFCAGAHHEDBHBHFFEHAGAGBCDFAEBHDDDDEHHACFBHDGDGACFFBDBAAADAHAHCHCEGAHAGEEEEEBHFFGADABABEBEBCDCBHFHFAADFCGCGBAADDDFCCCHFEFECEAGACAGDGFE,False +745,5.0,11.0,15.0,7.0,10.0,9.0,7.0,16.0,EFHFBCACFCEHBCBABABCECFHHHHFEFHCHCFCBHHGGEGEDDDHAFGEGCBDDDHEEAFBBCHCHEHGHBCBCDCG,False +746,1.0,0.0,6.0,5.0,2.0,2.0,2.0,0.0,GDCDCACECEDFDGCCFD,True +747,14.0,8.0,8.0,12.0,14.0,15.0,12.0,12.0,HCHDFEEGCBCDCAEEEBEFEFCABABFBFDEGFAHEHAHCHGGFCFDEDAHCHDFDGDGABHEAAFAFHFEEGAGDDFBHBHGDGEGAGAFAFD,False +748,23.0,22.0,15.0,27.0,27.0,24.0,31.0,19.0,CFEFAHGBGDEAEBEAEBHBDDGBFAHCGFHFHGEGFAFADBEFHBEBCCFCGEGADBBGGCGBGHHBEGEGABBEEEAHAGEGFGAGFCCBFAGBGFGFGFADDBDBGBFEFGFAAAABHCDDDDDDFDFHFHBGDEAEDDDEDEGEDEDECHDHCFAGAHAEAGADFGHEHDHCCGEGEDBDFCHC,False +749,18.0,23.0,17.0,19.0,17.0,23.0,21.0,21.0,EAADEDBDBFBEECFCDEGFDFHBDAFFBCCCGCHCHAFAFAGGHGECECEBEGAGDGDHEFEHCBAADAFBFBHBABGBGCFCDHFBDEDECFGFBCHHDBBCHDGDFFBFBGDGBHHAHABADADEEGHGHBHFFFFEFGCGCDEHHGHGAAAGBBH,False +750,26.0,15.0,24.0,31.0,22.0,18.0,27.0,36.0,HFCEEEDBCEHFDCDCDGDAHEDGBCCDCGHDEECFHFAFADHFCGEEAEHEHECGABAHFBFBFDACBDBDCDHDHGFBFACAHAHABAHHHCDGHGHGHAABFHFGGHADDDDDADCDEDGDEAGGGGAGBGACCHBHBFDDEEHEDDHCHCHCHGFGAHHHBHFGCGHEEDEDFBAGHGHCECGCAHAGFEADAGA,False +751,2.0,2.0,6.0,6.0,5.0,4.0,2.0,6.0,DCHAHGHCHCEBEGDFCHCDCFEFEDEFHADBD,True +752,12.0,16.0,4.0,9.0,13.0,13.0,11.0,4.0,EBEBDBDBFAHAHADAGBCBFHEEAFAEEBEFGFEFAAAGGGBAFCFCFDGEBBBBBBGAFEEDDDGAGFGCEFEGBDDFHB,False +753,20.0,22.0,13.0,25.0,23.0,25.0,27.0,11.0,DBDAFFDEDEDEFEFDBCFFHDDEEEBEFDFEFEGBGCHCEBEHEHAABAGGGDEAFDFBGGGDFAFAFACHEEBHACBFECCGGGGGGFDFAFCGEGEFHBDBACAHAEFDBDFGABFBEGCGCDHDHDGDBDBDGCFBGCAHGDGBBFAFABEGEGABADADGB,False +754,13.0,24.0,24.0,21.0,25.0,16.0,20.0,11.0,BHBDGCGFGFGFGHGHBFGCEEFEFBAHEHEHEBCDEDEDBBCBCEFECGCDBACAGDGDBBHCCGDAAEAHCEFECABABDGDGCBEDHGFEDEDBGGCACDDBEBCBDFGGGEEHECECEFDFDBBBDCHAFDCBCBCGCFFACAEAEDBFE,False +755,21.0,23.0,12.0,20.0,22.0,23.0,13.0,24.0,FBFBCBFBFECEBHBHDHBBBFBACGBGBDAGFDACHHGCGHFDBHEEEFEAEBEBFGAGAGEDDFDFEFBCAFDFEAEAEDFDBDHECDCFCEAHAFEEHAHGHGHCBDAEGHBDDDBDEHGBAHAFCHGBFHFHEHEADHFHFHFDEBCAAAAHAD,False +756,9.0,16.0,8.0,17.0,8.0,7.0,7.0,4.0,EFEFGFGCCBABHBDDDDGDABBGBFBFEACDBDEDHCGEGBCBCBFDDDEAFABADAHEBADHDCCEDGDBBBAD,False +757,15.0,20.0,18.0,27.0,18.0,16.0,16.0,19.0,GHFBGBCEEAHDBDAHAHEBFFDDDDBFBEEAGBDHDBEGHAHADDEDCFCFBHAHBHDDGDGDECECGHGFGDADEFCFCFDADBGEEBCDEDGABABHBHBHCDCECECEGACCEABFBFBCCHABGHFHFACDDDDDGHECGFGFH,False +758,24.0,10.0,20.0,10.0,13.0,18.0,25.0,18.0,HEHAHAFAHCGCGCHEBGCGHGHGFGCGEABGHGFGHCHEAACABAHACFEAGCECBGGGGGACDFHFAFDFDFDFBEEAEAECFCAADAGFCHHECFHGAGHGEAHFGCCDBDBGACAGADABBDBDCFAFHGEFCF,False +759,5.0,2.0,3.0,3.0,1.0,2.0,7.0,3.0,CFAGGHGHGHBDGDGACEDACAGABF,True +760,23.0,15.0,19.0,10.0,31.0,25.0,21.0,16.0,FGFGHGDGBHACAFAFEFEGEBFGFGFECEDBFEFEHHCFAEACFBBBAFEDCGCEAECFCBBHEGEDEAEFBFGFGADCCCBHAAEEBABAHAHACECFHFEDEABFEDEAEBECACECGFGFEAGAFEFACHGDGAEAEGHHHHGDCBEDEHFHGGCG,False +761,4.0,5.0,6.0,6.0,5.0,5.0,6.0,6.0,EFBFBFGDHCHFEFGGBDAGACHCHDHBAAECCBCDEDEDGHG,False +762,5.0,7.0,14.0,5.0,9.0,9.0,6.0,9.0,EGEFHBHFGFHCEDEBEFACAEAECHCHCHCHBGCFDFCCACBCDHDFGABHBCECDGGEFCFB,False +763,7.0,10.0,9.0,14.0,6.0,13.0,15.0,4.0,FHBHAHAFAEDCDEAEHFDDGFBFBFDGGFGBGBCBFDGDBCGEGECAGAGDGDFDCDCDFGCGEBDGFBACFBFDCG,False +764,18.0,17.0,21.0,10.0,17.0,19.0,30.0,14.0,GFCBGAFBBEFFCGHGEADAHFHEAEAHAHFGGGEGECCFAGAGFFCACBFAFAFGGGAEHGHFHBHCACHFAFDEDHGEGDFBCGCAHGCEBEHCBGBDDCAGBDAGECECACBCBCGGGBBBBBECFCFEFHGDGDGDGEGEGC,False +765,16.0,9.0,24.0,14.0,21.0,12.0,17.0,12.0,FCCCCEGDGDFBEGCBCDDDDCHFGACDHECCCEEAHGHGCCCFEAAADAHGEBEFDDDCDCEAGCGDHEAEAGADAGEFCFCFGFGEAFHEECECEGHGBFCECEBFBCAEBGBGHAHAHAHBE,False +766,2.0,5.0,3.0,5.0,5.0,3.0,5.0,14.0,GCCBCDHEEEFHHEBEHGHBHDHDHAHFGAHDGDGHHHHBFB,True +767,25.0,19.0,25.0,19.0,30.0,21.0,34.0,24.0,AABAGCCCGCDFDAEECGCHBHGHGHDAGCGDFDCEGEBAGFEEEHHAGAGAGFECEHGCECEHFHABEEEBEFEBEFEBCGGGDGABEDEDADGFGFCHHHHDDFBFBAEAEAHGFCFAAAAABAFHECGCDCGFADDBHBGCEHFBBGDHFAFHBHCHFHAGGGGGGAGCGEDEBEDECHFHGBDEDBFGCCCCE,False +768,25.0,18.0,18.0,14.0,17.0,14.0,28.0,21.0,DBBECABABAFFCHGBFEAEHGGEEEHGHGAGADAHGCCFDFDGAFCECECDBBBFBDHHGHEHBHAHGCGFGHHCCFAEAECGAGFHHCEGGGCDCEHEHEDGDHDAGABACCBCBGFFBBHBABADAGGGGHGAGAGAECFBAGAFADAEHDD,False +769,1.0,3.0,1.0,7.0,6.0,6.0,6.0,3.0,EFGFHFCEBGHFBDEDEHEAFDDGDGDGDGBEF,True +770,10.0,20.0,19.0,21.0,15.0,21.0,16.0,16.0,CDHDGGGCGEGECDCDCDABFBDBFBFDFHFHDDBEAEHBGBGCDBGBCHHDGFGCHDHCGCAAHABAFHHBDEFEFCFDFCFCFAHEFBFBGHGDDDCBEGGFEBEAEBDBHCHAEFCDCBFEFEBHCGCBFDFDEA,False +771,4.0,6.0,5.0,4.0,2.0,2.0,2.0,5.0,DBACDGDBBHBHCFDECECACAHAHGBFBH,False +772,20.0,21.0,27.0,26.0,23.0,24.0,13.0,18.0,HHGDAACADHDEDCABDHDFCFDBCFCABDCCCCFFFDFBCBHBGEGHGADACFDGAADDDDDECEHEHDFEBEFCFHFAFCFCFAFCHHHCEBEBEGECECFCHEFDCGBAFADAEAEDEDEFEHEGDAAEBCAEABBFBFBEADGCHDBGBDCDFGGBCBCBEHGHCHBF,False +773,23.0,11.0,12.0,12.0,15.0,10.0,15.0,14.0,HHBEBEDEBGBDFCECGCGEGCHDHGHGBCHAGAGAFAFAHAEEEAEAGBGEGCGAACABBHDABFDFAHADGHFBCDDHAAEAEAEAEACDFDEAAAHFDCCGCHHGDBFF,False +774,17.0,24.0,28.0,15.0,15.0,16.0,18.0,18.0,EFEFEBGCDADCEHBHBHBFBECECBFBFCGCEDEDCCFCGCGFGFACCDFHAHGHBHCHEHECCCGGFCHCADBBBGHHEGCCCGCBHGEGBBBAADCDCDCDADADABFHFAGBDBAHGBBABFEFGBEAHBGCCHFHGDABACAFDEA,False +775,3.0,0.0,2.0,1.0,0.0,2.0,2.0,3.0,AGHGHFDFCHCAA,True +776,17.0,9.0,11.0,6.0,12.0,12.0,17.0,14.0,GCGDABAFGFGCCECFABAEAEBGADHHEHAAAEDEAEABDFCGBADAEHGHFFFGAGFCFDBHBFGHHCGAGHGEGHBHCECEAEAGFCFCBHGHGH,False +777,4.0,6.0,1.0,5.0,7.0,2.0,6.0,4.0,HEFEAEAEDBBGDCDHDFEBAAHEHEDGBBBGGGG,True +778,6.0,7.0,4.0,4.0,5.0,13.0,4.0,5.0,HEHEAFGFAFAFBGBAFFFDEDECBCFGDBEHFAFBFDFHFHGBACCB,False +779,9.0,7.0,5.0,6.0,9.0,8.0,7.0,9.0,DGBEBEDHAFAFHFHFCFCEDEGEDEDGHAFBHBAGAFBCBHFAGADAECCBGEGHHEHA,False +780,19.0,21.0,16.0,16.0,23.0,19.0,26.0,22.0,FFCAGEGEGAHBBEBEGCDFEFCFGHHDHDHDBEFFAGEGAGAGAHEHFAEDBACCCEDGBEACFCFEDEABABABFHFBGBGAGEHHACBCGCHCHGHEABACDBDHEGFGEADHFBDCDCEBBAGHGHEHEHGHDHDGDGFHABECEBDGGFGBGBEFFF,False +781,15.0,24.0,23.0,18.0,23.0,14.0,17.0,21.0,FEAGCCBABABAFAHCDGHFCAEGBGBGHHBBCBFBABAEDEDADHFECGDGAHEBEBECCGCHCHEBCFEDDDCGCGDGDHEFGGCHCBEFECAHDEDFDEHEGEFBBHGGCECECFBDBDBAHAHEHDHECFBFDCECABABHBGBCHFHDHE,False +782,14.0,24.0,23.0,18.0,18.0,17.0,19.0,17.0,GAECGCBBAGAGAGFEEDDFBEEEBBGGEECCCCBEGEGFGDGCHCHCHEADBDBHBHFGADBFGDHHGAGADDDDDCBCDHFBFHDAGFHFHFHCBCFEHHHBFCFHFCGCBCAGFEBDFCECHCACBDBCEAGDBDBEBEBEBABAFC,False +783,17.0,21.0,14.0,26.0,20.0,11.0,14.0,15.0,CHAHEHDHGCCADABAEDBDBFAEABGDDCGADADBBAFCEGDBEBDHGEGFHEHEHEFCFDGHADADBDBDCDCGBABDECEDEDFDCDCDADEDBDHGBGBECDHEHFFBAEAEBEBGHGEBCGGBEFHBHCFAFA,False +784,9.0,13.0,21.0,19.0,11.0,19.0,13.0,15.0,ADHDFGEBBCCDCDCFHAGDBCBCECEAGAHCDEAHBHEFEAHHGDCHCHDHDHFBEADFCGCHDHAFBGBGBEFDFGFECACFEFGFDCDEBGBGCFBFCDGDGCFDFHFHFCFCDCDB,False +785,3.0,4.0,10.0,4.0,5.0,8.0,5.0,7.0,FCFCGCGEAAGFCECECHFFDHCACGCGEBHFEFHBHDFDBDBHHC,False +786,13.0,15.0,20.0,21.0,12.0,14.0,14.0,18.0,BFDGDGDADECHCHCEDGDBDGHCHDGCABEEFEFGGDDBDHDHDGCCEBDFDFBHBHBHFHFAECEBAAAFAEAHBHGHDFEFBHBABECCCCCDEGHGBFFGHCDCBGDCCCFHDCACAFGHADA,False +787,12.0,21.0,22.0,19.0,22.0,24.0,29.0,14.0,CGCGEECEGGBEAGCFFFCDCEEACFBFBGBGDGDHDHCBCGADEHGHBFGFGFDFDBGEGEBFCFCFCFABDBCAFFGDGBFHCHEECDFDFCBEBFHGCGEGAGAFDFCEGEGEAAHHHBGCGCGAGDGDBDFGEDBDFDBCHADEEGEHEHABBFEHBCB,False +788,17.0,13.0,19.0,20.0,16.0,16.0,19.0,15.0,BDCEGHGDAFFHFHDADAHEEEECFCGDHBHGGGAGAEFGBCADGCCCCCCGCDCBEFEFDFECADABAFEBGBGAADGEGHADABHFHFCEDHDGGCDCDFDADGHCFBBCBCEHBHFHDEDEDEGHGAAAFBF,False +789,28.0,17.0,13.0,32.0,28.0,13.0,27.0,17.0,AEADADBGBAFAEADGBAAGDDEGEBEFCFCFHFHAEGEHDHAADEDHDCFCBAEGEGDGCGAGBGBGBFDDDEDGBGBGBDDGGADCDBGAEAGDBCADEDHBABAECHCECAFEHAFACDCDGEHEHFBEHDDDDFEAABDHGHGHDAGECEGEGDHEAEGEGEAFHDHDFAE,False +790,20.0,14.0,14.0,14.0,17.0,15.0,16.0,18.0,FCFDDDHCHCEGHADCBGFEFCFEEEEBEADABHBDEFCABABAGAGEHHBHBDAECGDEAAAFAEADBHCGGBGBGBEFEFEFABAGFHHGACDBDHHGFDACEHDHGHFCFDHCHCHCEFAGAGAG,False +791,18.0,17.0,18.0,19.0,20.0,20.0,6.0,18.0,FHFHFDEAADAFBBACGHDCDFAGGFEFADEDBFBFECEAFAFACCCEFHBHFHBBACHFDGDCDHDHGBAHCDCBHBEEEEAECBABCBCEDHDFDEDEDEAEADACAHFHFHEDCCABEHEBEHCFBFGFBDHC,False +792,14.0,17.0,13.0,12.0,11.0,16.0,16.0,11.0,DDBDBDAFBDBFAFAGBDEGCCECHCHCGFABGBCFEFECHFBABAEECBDHDGDGHGHGFCFHEAEGDHBCBEFHBGAGACAHAFGFGFDEABFBABGFGFGBHCAEDC,False +793,9.0,19.0,17.0,11.0,13.0,16.0,16.0,13.0,DCGHBFFCGEEBEGGAGFDEEBFGHCHCDFDBCBCFCFCGCGBBBCBCBFHFGCAEABHBABGBDBDFDHAHFGFHBBBGHGHECFDECEGHGHDAAGDBCECDAEAEFEFCFH,False +794,18.0,14.0,23.0,18.0,18.0,15.0,28.0,20.0,GBGBGFGAEFECEBGBECECFGDEDGFCFGGHCHCFGDAHHCHCFCFCGCGCEAHAEABACDBDBAGGCGHAHBDFDHEHEGAGEGEHHDCDGFHBHGHFADECACAEABFCAHGHGBDCDFDFBAGACDGGCDBGGADHDBFHEHEAEGDCEC,False +795,2.0,6.0,5.0,6.0,3.0,1.0,4.0,1.0,GDGECBCHDEDECBBFBCBABDGDGACD,True +796,20.0,15.0,22.0,19.0,22.0,17.0,35.0,28.0,EHGHCDCDAEBCBFBACHCGEFEFEFDFHGHDCGAHDCGCDCACBGEEHEHGGGEHEFEGGAAAAHAFFECCAGHGHGHBACACDCFEAGGGGGGGCGAFCBEHHGDGHGADAHGHBDGAGBCDCABAHDDEEFGGEHHHBBBDBDHDHDHFHEHBCDCGFGECEFFGFGEGHFBEDA,False +797,22.0,14.0,14.0,13.0,13.0,14.0,15.0,9.0,HCHGGBDEFAFAGAHDCGCGCHCGFAADEDEABAGABFEFEFEBDFGABHFDAABCHCFCADBBAGDGDGDCDFEFGBDBDFFGCBCBEBGAAAAAAHEHEBEGCAAAFHECEC,False +798,15.0,14.0,14.0,26.0,14.0,22.0,16.0,23.0,DCGAADDDHDHFFDBGGFGEGBBDHAHFFFFAFCFBDDFEAEDHDHGHGDCHCFAGBDFCFEFGAGHECFCEDAHAGEBFBABDEDADCDHAFCFAFHBDFAFADEGEHEHBHGFGCGHGCDCDBBHHHHBCBCHDEDEDEDHH,False +799,27.0,20.0,19.0,24.0,17.0,17.0,26.0,21.0,GFGDGDCDFGBGBEBGBHHFDADAHEHEBBBHFFGGCADACAGHBHAAFACACHBECEFAHADGDAEHECFABCGCAHBHAHDGEEHFDFHFDFCAHDBDBFEGDGDGHBDBGAGEGBGCCECEBEHAGABADADADECGCGCAFHGHBFACACFDEDEBGACAGHGFDDD,False +800,14.0,22.0,27.0,22.0,29.0,27.0,20.0,20.0,BCBCBCACACAHDBFCHEHEFBGGCGCABBHBEEEBECECBDHDEBAACGCGFGFDFGBCDAHHHHFFEDDDDEFFHFDEGGGHEAEDEGBBDFEADFCGCGCHFHGHGEDCHFFFDFDCHFBCBCBCEEEGACAEHEFGFDFCFBAEHECGDEFGHGAFAEBBBBDCEHFCFEFDCDEDE,False +801,5.0,1.0,4.0,0.0,2.0,1.0,0.0,1.0,HCAEACAFBEACAC,True +802,15.0,14.0,17.0,11.0,11.0,11.0,14.0,5.0,DGAEAFAFCFDADEFEFCACGEHEFGCHABACABHBADDFDFCGEGEAAACHCGDGCGBEBFDCABBBBDBABFGGCCCEGFBBBEDAHCGCGCGCED,False +803,19.0,24.0,22.0,27.0,21.0,24.0,25.0,26.0,HFAFEFEFCCCHCHGDDHEHEDEACCFAFBHDEDEBGCGBFAHAHAHFGDBAGAHBHFEFBFEFABCDHDGACACBGDGHAFBDBCFHFHDHDGDADBCFGGBDACGHGCECEGGAGDGDGEGECADHDABGBDDCECEHFHBGGEGEHBFBDHFACAFBBBBHEEEGCDHGFDFDFEFHDHDCBBBC,False +804,14.0,12.0,12.0,16.0,9.0,14.0,9.0,8.0,ABCBAFDEDFDHDCDBAFCBGBDBEAEGEBCDGAACABDECECEHEAGHGDBHFFFCGDADFFFGFDBDFAHCHCHCHCBADADADABFFGGEF,False +805,10.0,5.0,7.0,4.0,17.0,8.0,9.0,3.0,AAGAGAGAGAHECEFEGEHEBEAEFDADFEEEECEDECHGFEFAFBEDFGBEACBCEFBCCGG,True +806,16.0,25.0,13.0,17.0,23.0,16.0,21.0,18.0,CBGEEFEGBBBCHGHBAAAAGAGEGCHCEDBBBBBHHHHDAFFEEDEDAAADFEBHGHDHEGEGHCECEBBDADGGGGGDGHEHEHEBBBFGFAFDFEFEBEBCFFEBHBECDBDFAFAGHDFDGBHDCFCAABCBHEGDGDEBGCCAF,False +807,3.0,8.0,5.0,8.0,9.0,8.0,9.0,9.0,HFFFBHCHEBEBEBGBDCGCECEFDFBFGAGHHDHFACHDHDEFBGDGEHEADGDBEGG,False +808,18.0,19.0,24.0,19.0,15.0,25.0,23.0,17.0,CDGFCFCAGHEAEADCGEGACBGFGDHEEECACECECFAHAFDCDHDFEBEHDFDFHFGBEBGGGBBBHBHFAEAFGFAHAGAFCGCHCHGHBCDDFDFDGDFBEBEBFAFCFGDCCHGHADCBFBGBGHFCGDGBCAHFDFCFCBCBDAEABADGFGHC,False +809,24.0,16.0,20.0,18.0,20.0,16.0,26.0,18.0,HBEFGCGHAHADGCACAFBFAFCEBGBFDGAGAEHHCDDHDFDHDHDEECGABCBFEAEHDGGGGBABGFEBCAEGBCFCHGHBHBABGBHFEFCCCCAHGEGEFHFDGAEBHDADCGHEAEAEAEAEGEDCDADGDGAGAGAEHDGCCFCFCADBGF,False +810,7.0,10.0,7.0,14.0,17.0,13.0,14.0,8.0,DEAEGEFECACABGEGEAHGHGHAEFEFECHDDFDBDBCBDBDFGCGEBECEDDDADBEFEBDFGBDFHGCFFDGGFEHEHFHBGAGEGF,False +811,11.0,12.0,11.0,18.0,16.0,11.0,15.0,16.0,EBEBABDHDHDHEHGHFAAGGCAFEDDGEFAFHDBDBDHEGGGGBCBCFDDDDDEDBHFEBHCHABEFEFGHECECBFGGGEDHCHCGEGACAEAECHABCHDADFDFHG,False +812,7.0,8.0,5.0,1.0,6.0,6.0,5.0,5.0,HHHHAEACACBEBCCAFAGEFCFDBHBFBFEGAGEGBGFABBE,False +813,7.0,6.0,14.0,17.0,20.0,8.0,11.0,16.0,BCHCAFAGAHCEFEDEHEDCHGHAEDGDFCFHGHGHAEGEGFHBBDFEHEDEDHDEDEBGDDFBEHGABCEDECCCADGHEHEHCHCDCDCDCEEGEFD,True +814,27.0,14.0,15.0,25.0,17.0,16.0,12.0,25.0,HFFCACAHFFCBCFFGDDECEFEHCBCBCDAAAGAHAHDECEFHAHAHDEABBEBCFGBGDEAEAEADGHAHACDHHHBCBEDFFAFHFEEGAAAAAHAHEHEDDDDGAGDHDBDFFAHDBACACAGHHDGBGBEDDBDHFHECGDDDHDH,False +815,9.0,8.0,11.0,6.0,5.0,16.0,9.0,7.0,DDGCCHAAADDFEFBHDFFFDFCFCFCFEBEGGGCFCGHGHEAAAFFHBCBGBEBCBFFFCFCAAGAHHGB,False +816,27.0,23.0,14.0,24.0,26.0,27.0,25.0,22.0,DABHHHEHAHAEFDBAGABDBGHDAAGAGFBAHAHEEDABFGGEEADAFBCACGCGCEFEBEBDFDCDGDEFEHEHFAGAGCBCGCBCBEDAGGBABHDFBFBDEHEHGBFEFEBDFHFHFDEECAFGFGFEADHDAGAGADCDCHFHCEADFDGEAFBFCFDBEEDGAGBEFEHDHGAGHGHFBFBF,False +817,1.0,1.0,2.0,2.0,3.0,7.0,3.0,4.0,FFFFADHDHEHEGCFBGECFHFG,True +818,10.0,14.0,17.0,5.0,12.0,5.0,16.0,9.0,CACBHAACABGDCAEAFGBEHEGCGCGEGEDBGAGFHBGCECEFEGEGBHBFGAGHEABDFDBCBCBHEHGHGBDCACBGBECCCCCH,True +819,20.0,12.0,13.0,11.0,16.0,13.0,21.0,6.0,ADCECACDCEGDFFAFBGBGBGBAAAEBEBGFDADEDAACACDCHHBGGGGGGGEGAAHFEFCGDGBCFABAFEGCDHFECEDEHABCDAHFGAGEGAGAEAGBFBCEFEFE,False +820,24.0,22.0,18.0,21.0,20.0,19.0,14.0,22.0,ECFBHAHAHAEAFBFGDGDCBCGAEAHABCBHFEDEDGBCDCDADABAEAEBHDGDHCBAHFDCDHHBHEGAAFAFCHCDDEHBFBFDGDGHBAFCEDEHFCEHEHEHGCGAHABCBEFHFGCDCDFBFBFAFGBDEDAGCHBEBCBADAGEBEAEAFFH,False +821,24.0,21.0,19.0,22.0,19.0,13.0,20.0,29.0,DAHAHAFEGCDEECECAAEHEFDDDGAGAGAGABHBGEHDHFHEHAHAHAFBHBHCAADCEBBGDECHGFGHGAGEDFDFDHHHCGAEABFDGBECECAHACFCHGFBDHGFDHBHDDDDGGHEHAHBGBGBHEABBFBDBFBDAEEBECCCCCACHCBCHAHDGDB,False +822,16.0,25.0,27.0,23.0,14.0,15.0,16.0,28.0,BHCHCDCAGFGAGBFHEHBABGDHBABFBGBDCHCHCHEHAHEHCHDBGBHACADADAFFHAADACBCBEGEFDFDFDFCHEHDDBDEGEDHHHCDEGHCFGFDEDBBGFGCGHAHBDCECHCABHFCCHCDEDCDCGBBEHDHBGBFEFCACHCBBABCBDGC,False +823,19.0,16.0,17.0,19.0,13.0,21.0,12.0,12.0,AAFGBDHDCDFDEHBBFHFCDCABBFDFGEGEBCHDDDBDGDACAGABEGECECECEFEHCHAGDDHCCDAEFFAFBFBGDAEHHBABAHADABGBFCFGDCDFHFHAGAFAFDFBACACFGFEFECBC,False +824,23.0,14.0,24.0,16.0,17.0,21.0,26.0,11.0,EEEECEBHDFDBDCFAABFDEEGGCGEGFHDGAGBCFCHCFAFAGAGFFBGAFAEABCGAEADADAHBBEHCHCBCBCDCECGHBHAFDEDEAAACACFFECEFFGACCDCFGGCGCGFDFHFGCGCGAEAGGHHFBFDADABBCGGGDGDG,False +825,16.0,23.0,19.0,19.0,25.0,21.0,19.0,16.0,BCECEGEHBGBGDACADFFBABGGEBEGCGAGDBCFCEADAEFEDDCHCDEDGBGCFHFGBEBEBEHCHCEBEDEBFBFEFHFHFGDEAEBGBEDDCBHDFGFCACAGAHBDBDBCCFCFAFDDDADHEEEFHAEAGBGCAHHHEHFGFBFGECHABF,False +826,8.0,5.0,4.0,4.0,6.0,3.0,1.0,4.0,CDGDCFEEEEABABADAHBFBHACAFHEAEAHCBD,False +827,24.0,26.0,18.0,19.0,16.0,34.0,27.0,29.0,CFAFCHHGFDHDBDBDCDCHEFBGBGBHBDADCGCGHGFDFBAHDDAFECBFFFHFAGECAHAEBEAAACGEGHGEABAFGCEAGFFHFGACBGHGAFHCHGHGBFAHGHBHBGBGAGCFBEDHBFBHEHEBFGECEADHFHFHFDABFEFHFEFBFBABDBDFDADGDGCAEAFCFCFCDAGGFGFBHHHHB,False +828,2.0,3.0,1.0,7.0,4.0,6.0,1.0,1.0,ADDDFDFEFEDEBFBEGFDADFHCB,True +829,18.0,8.0,19.0,22.0,14.0,21.0,12.0,12.0,EGEGCHAFEECHDBDBDCFAFEFDFEGEAFCFDADADCHFHEADAEHDHCCFCFDFHFDFDACACACEFDFDGBFBCGEGFGCGCAHADACEDDGCCACHBABDBHAHFFFDDHACBDEAEGGGFD,False +830,14.0,17.0,12.0,13.0,7.0,7.0,14.0,9.0,EGEBHBDCDGECBABADDGCABACFCEBDCCADADFGHGHGFGBGBGHGFDDCDAGABACHHDHDFDCBBGBAAFACEHAGAGBEBHBCBEBF,False +831,13.0,21.0,11.0,11.0,12.0,12.0,12.0,8.0,EAEDGBFBDBCHEBEBEBCHCHAFGGBCDDDCDCBADAFAFABADFCBCGEAEDBAFAEHEHADFHBBEHEFBFGEBHFGBCBCBFGGAGAGBGCGFBDB,False +832,14.0,20.0,21.0,16.0,26.0,24.0,30.0,17.0,BGGGEEEBFFFEFCDGGGGGCGABDFGHCAFFFDFEHDHAGAGAEBEBCBCAGBBDBFBFEEEDDFCCGCGEGBBDBHEDCFCHGFEEBGCFAEGEGECFCGCHEDDCBEDDDHHHCGBGEHEHGDDCGCGBGEGEBEHECGGAEABAFAHAFAFHFHCHCFFFHFBA,False +833,0.0,0.0,2.0,1.0,0.0,7.0,1.0,2.0,GFFCFHDHCFFFF,True +834,15.0,17.0,13.0,12.0,21.0,19.0,18.0,23.0,DEFBAGHEHEABHDFGFHFHCHDHECEHBHDGDGFFCGBFBEEHHCDEFECEDEBCBGEGEGACAGHGHAHDFCBHGFFFFDACEHEBFBHBHGAAEADGGADHHHHGHGFAFCFCGEDFFABABGECACABEBEBEB,False +835,9.0,17.0,15.0,12.0,13.0,15.0,12.0,18.0,AEAFDHGHGFDEDBFBABACCCFCHEHCFEDHFGFDHBHBHEFAACHEDECFCGCBCECEGHBHCABDBEGFDFDBDBEGEFFCCGHAHAHGHDFBBGBGDGHBHBCBFHE,False +836,24.0,27.0,17.0,31.0,24.0,22.0,21.0,23.0,DCGBEBCDEDADFBFEDADADBDCDCDEDFDGBGCGBHBHBHEHEDEDAGBGFDAHGHBCECADBDEDBFFAFAFAFEHHGCGFEFDDGDGFBFGEGEBAHAFDDHFABBBDADAHAGAFFFCGGEECHGAGAEECEBFBCBHHGEFDAAECFADHGHCHBBBBDEDHBBBEHHAHCHCAEFEHADGDC,False +837,8.0,2.0,11.0,12.0,11.0,8.0,3.0,11.0,BHCHEDEHFAFHDHCHFDCDFDFDAAHCFDDADHDECECACECAFEHEGDGEHEDEHFCBCGCAEA,True +838,12.0,19.0,12.0,11.0,20.0,17.0,13.0,16.0,DEFEFEHEFBFECEAEAGBGAFEBEDFGFGAHFHFCGBBBBBBHEFEBHBGBGHCHFBCDFHAACCHEHACDBFEGEDFBCBABHHCHEHACACEDDDDFDGHGHCAGFDFBEEEGEGBA,False +839,1.0,4.0,3.0,4.0,6.0,6.0,4.0,1.0,GBEECAGBFBFBEDCDFDFEEHEDGFGFC,True +840,5.0,4.0,4.0,1.0,6.0,4.0,2.0,2.0,GEBEFEHEAADACACFCFBBHCAGEBEF,True +841,15.0,12.0,13.0,8.0,18.0,15.0,11.0,15.0,FHFHFEAAHFEFCGEHEHCHCBCAEBBBCHAHAEGFGABHBEBEFCBCAHDHBEAFGBHAFEFBGCFEFCDADBDEDEDEGEFEFAACHDHAEACGEGHGCGAGFDC,False +842,17.0,27.0,15.0,15.0,25.0,21.0,18.0,18.0,DBEBDBEEGGGBGEHCACBCBABGEDEDGFAFCCBEDCGGFGBHAHDBBHBHECACEDBDHAAFAEBEDCDCHGBEDECHAFAFECECEFHGHGHBEBGBGBFFFFHFEFHFHEBEGEAEFFAFGBBBFHCHADFDFBABCGAEAGFHDADEBHBE,False +843,20.0,14.0,16.0,25.0,17.0,16.0,12.0,24.0,HBHEDGBFBCADADACHHDHDAEAHDDDDDHFFDHDGCGCBHEGABAHEDEABACDCEFGFHAGGBACGHAFFGDCAAGHDEGEGEDABACABHFDEEBEBDBDBDHDADAHCHBEFEDEDCFCFCHCHFHFHFHFCAEHHFCE,False +844,6.0,6.0,6.0,6.0,7.0,4.0,7.0,2.0,GCECFBDBDBEGHDEAEAFFECECACBGBDADGDGHFABGEGCA,False +845,14.0,10.0,13.0,17.0,13.0,16.0,16.0,22.0,DADFGHGHFHCBGAFEFCFCGDGDEDBABABECDCDBBGAFAGAHDDDDFDGDGDCEGGFHFHCHGAGDHHHFFCGCHHEFEAHHHFHGEGDAHECDCHHAHAEAEBCFHFBFCEHBBEEA,False +846,13.0,21.0,15.0,9.0,8.0,13.0,6.0,10.0,AGBCBCBDGCBFGHABCBCBEBABCGHEHBAFAFDFECDBBAAHBHBHCFCFDBABDCDFFCGHAHBHBEBEBCFCACDEHACEBFDFGFAFAED,False +847,8.0,14.0,10.0,15.0,9.0,10.0,9.0,7.0,DECFAHHBGBCEAACBCBADDEBHDHDEDFFFGEAEBGCGBGDGDFDADBDBDCFCGCBCHABFBDEDGDGBHBFFCFEAEH,False +848,10.0,5.0,6.0,10.0,12.0,17.0,10.0,11.0,DHDEDCDFDFAFAHCFGABAGFCFBGGGGAHCFDFAFEEEEBBABHFAFGFEEHDHECEHFHFEAHAHEDFDFHFDGGGEC,False +849,22.0,14.0,13.0,19.0,14.0,18.0,13.0,19.0,AACFCFBBHBGFDADADAHHCGFBCHHFHBHDGDCAHAHABDEDBDAHAGFGEBEBACHCDEGAFFDGBHFCFDDBABAEEDEGEFEAAGAGABADAHFGFCFAAGCFHEHFGFBFEEDEHEDCDCDCDHHH,False +850,12.0,11.0,24.0,25.0,18.0,37.0,27.0,36.0,GEGEAEAEDHDEDECECGGGEFEFEGCBFBFCFCDCHEHDDGEGFGDHFGEGAGCGFDHCHFHDGCCHEBBDACHCFCHGHCHCHGDFFFFDFHGHDFFFGFGHHHGCDFBFCHHFHDDBACHEEFDCAHDHBHFFFHHCHBHFHDGFGFGBEAHFHFHFCAGGDCBGDGDFFAACDCAFDFDFBHHAHE,False +851,8.0,20.0,9.0,10.0,16.0,10.0,11.0,18.0,GAGAGFFHFHCHGHEFEGADABHBHBFEEEBAHCHCEEHEDCAGGBBDBFGFHFHAHFHBABEHEBFBCHEBBBDDDCDBECEGDBCBEBEBHBGCHEDDHG,False +852,8.0,4.0,3.0,3.0,5.0,4.0,5.0,3.0,CEHEHBGFGBABDCGAGHFDCGAAAAEADAFEFEB,False +853,2.0,2.0,4.0,5.0,2.0,8.0,1.0,9.0,BHFHFHFADCCGFDFDBDEFAHHHHHFHECCFD,True +854,0.0,3.0,1.0,7.0,1.0,4.0,3.0,3.0,BGEDFDHDHGFBDBCGHDFDFD,True +855,13.0,9.0,23.0,8.0,13.0,14.0,12.0,14.0,CFCFCGHEACCCEEEGDHHAHBGBCFCDCDCFFGCAFDCABHCHCDFFCECGCGCAABFDEDACCHHAFAEBEBHGHBHFGEGCGCGAEBCBAGEFEFEFDHAHAH,False +856,10.0,14.0,21.0,25.0,13.0,22.0,18.0,15.0,HDAFAFDFBGDDCEEGEDFGBDBGCCCCDDDGDGHFDGHEFECHCHCFEDBDBACGFBFBFDCGEGCABABDEGCGCECEBAFGHHBDDDHHHGGDCDCACAFBEBECFCFAEHHFFFDGDGHGHDDFDFHFCFCBAF,False +857,5.0,7.0,6.0,6.0,3.0,6.0,3.0,6.0,HBHCDAHAFGBACABHBDBDEFGCHCHCBEFEFGFCFDDBDA,False +858,5.0,6.0,10.0,9.0,8.0,7.0,3.0,10.0,BGCHCHCBDDHDGDGABCBABFECECECDCDFHHCEDDFFFHHEHEAEAFHBEDHCAF,False +859,5.0,3.0,3.0,10.0,1.0,2.0,6.0,6.0,DADADBGHEADDDCDGHGHGCDCDBFAHHFHAGDGB,True +860,23.0,20.0,27.0,31.0,27.0,21.0,22.0,20.0,GBHCDCFCFDEDHCHGEFEFECCCCCADABAHFHFHFDGDAEEHACDDGBADFDEECFAFCFEGCGEEHFAFEFBABCDADEDEHBHGHBBAECECGBHAGFHHBGECCDEDBFHCACGCDAGAGADDDDDCDGFCFCEEEDEBHGHGHGCGCBDADHBGDDEDABABAEDEBFCDEBABGBDAFAFGEGH,False +861,7.0,7.0,14.0,4.0,11.0,5.0,11.0,5.0,GCGFGBGCCCGFAAEAECECECGBABHHCAEAHAEFEBEHDCDCGFGFBCGCGCDBEEHDGECB,True +862,12.0,3.0,10.0,5.0,8.0,8.0,5.0,6.0,GFCAHAHAGACCEHDBBAAAHADECEDECGCBCECFCFHFHAGGEDEFFCFAEAFAD,False +863,24.0,14.0,29.0,24.0,18.0,18.0,12.0,25.0,ACACHBEBEDABHBGCDCFCEDFCGCACGFADCCCCBCDEAEBDHEEGAGCDFDFDFGEHAHFEEAEHCCFHFEFCHCHDAAHGDCDAHFHEHDHDHAHADEBEBEGADAHEBFHFHACGFGCGCBCDCDCACFCFABCBADDBCBHHDHGAAHAHFFDHDEDA,False +864,12.0,14.0,8.0,8.0,15.0,8.0,10.0,15.0,EBEBGHCABAFAFDFDADGBHCEBGBGBCFCAEEDHCHGHBHDGDHEHEHEHCFGFBEEHAAAHGHGEGBFCABHFHEEBADCDABEBEA,False +865,3.0,2.0,2.0,3.0,0.0,3.0,0.0,4.0,BHDHBCFDFCAHAHAFD,True +866,5.0,8.0,8.0,6.0,13.0,7.0,15.0,8.0,FHCDEDADBEBGAGCCCEBGGFGEGEGAGAGHDHGBEHEDGAGEBECHCGFEEHEHGGFBFBFCFHEBCD,False +867,15.0,8.0,10.0,4.0,10.0,7.0,12.0,11.0,GCHHEHGBDBCGCBCFEAAHAHADFCFCFGAGAFBGAHAEGFBECEABHCHAEAEHGHGFBDCHGEGEGDACABAEA,False +868,13.0,19.0,24.0,20.0,14.0,16.0,12.0,20.0,HCHAHAGDDCDBGGHGHGCEEAEGFBFDEAEFCFHDHGFAFGEHDBDBDCECDFECHCDCFCHCHBBBBGAFDCACEDBFFAFAFBEHCACDHBCBCBHBCADDDBDHDHCHCBABHHEFGAECGCGCBDBDCFHFEE,False +869,11.0,10.0,12.0,15.0,14.0,12.0,10.0,5.0,CBGECDGDGDADCGAHDBDFFFFEAHFEFDBDGDGECECDDFDADBEACGFEBEBECCCGCBCBEAEAFGBAAAEDEGHHDHCFAFEFB,False +870,8.0,16.0,15.0,5.0,12.0,6.0,10.0,5.0,GEGAAFBCBCEGAAEBEBEFHHCBAAGACBBBBEBCGCGCECECBABCFCGCFEDEHCCDGBGFDFDEHCHBBGBDE,True +871,7.0,10.0,13.0,4.0,10.0,7.0,7.0,8.0,GAAHGCBADEDHDCCCACAFHEBBBBBCBEGEGFCHCBEGEGEHDHCFFABCFCFHGHABFECECE,False +872,5.0,6.0,11.0,4.0,5.0,6.0,7.0,6.0,FCCCACBDAFCCCFGBBHBGAGEGDGCGHGHDHDEBHCCFCBAEFEFEHA,False +873,6.0,3.0,2.0,8.0,3.0,5.0,4.0,1.0,AADDDCDCGGFFEBADADADEDGBGFFEFAHB,True +874,16.0,16.0,9.0,13.0,16.0,16.0,11.0,18.0,DGAGHBHCEFGDAAEAFAFBBDFHEDEDHBHGHGHDDEDFCFCAAADAHFBCBCGEHEBFDFAFCFAFAFBECCBEDHHEHEGBGCDFGFHHHBHBEBEBHAEADBEBAAGEGHF,False +875,10.0,10.0,11.0,9.0,10.0,8.0,13.0,16.0,AFADADEDEFHCHCFGBGEHDFGHCHEGBGHFABHEACHBHBHBHGDGBAAAHAHCHCGGGCGEDEBCDDGBGAECEFFFBCHCHDE,False +876,10.0,18.0,8.0,11.0,7.0,15.0,11.0,9.0,FCHDHBFBGCDHAGCCHDHAGFFHBHEFAFAFDBBBDBDEACGGGBGFECECACHDBABFBDBDGEADADFFFGEGEBBBFBFBGBFAH,False +877,4.0,5.0,14.0,13.0,6.0,8.0,11.0,11.0,ACACGHADGCECGGGDCCCFCFBFDFDHDHDADHDHFFBHGHCHCGCDCDHDEEBGFDEHBHGEEBDFCCGG,True +878,22.0,17.0,15.0,16.0,16.0,19.0,13.0,15.0,CCFCHHDBEGEGDCFHFBAGFEDDFDCECEGBCBABADADBGGDBACAFAEABHHHFHCHDBFBDBDBEHHCHCHEEGFGFHAEAEAEADFEAABCFCEAHFGAAADFDFBFBEGCGCDAFAFAEDGBHBGFA,False +879,11.0,12.0,5.0,10.0,10.0,9.0,11.0,9.0,BCBCEAFGFGHBHBHDDFEFGBGHGFBDCAAGEHDBDGHGHFADAEEFEDEDEAHABABACAGHEDFAGEDBGBCBF,False +880,22.0,23.0,20.0,22.0,17.0,22.0,27.0,22.0,AFEFEHDHDHDBFBGBGEGBGFGFGEHEABABGGGABAHDHEBCGCGCFCDBDFEEAAAFDCBFHGHBCGAEDFDFDBCECFBAGAGAFEHGGCGDBBCCGBDDCDBDCFCAHDBAFFHCHDHFHCEEDHDHBHCCBFBAEAEAFGDCDHAHFHEHADAGAGAFBGCGHGFBEGG,False +881,26.0,17.0,21.0,13.0,20.0,12.0,23.0,19.0,BAEAGCGHGAEADABEEEGAAHHDDBDFGAGACCHHEHEBFBHEEEDFGFEAGHCCACGEFEDCGCHCGFHHBHBGBCCCDCGBGBABABFDDHEAEFEGGGGEHAHACACDGBGBGBEAFACEHFAAAHGHGDCCECFCBCBHDAAAFAD,False +882,1.0,1.0,3.0,2.0,1.0,1.0,0.0,5.0,DHHFADEBCHCHCH,True +883,7.0,3.0,8.0,7.0,4.0,4.0,4.0,4.0,GDEDCFHFHDHDEGEACDCABBGFACACGCFCDADBCAEAH,False +884,21.0,12.0,14.0,11.0,9.0,9.0,15.0,13.0,EHEAEGDDAGGBGFFAGHDHDCDCDCFCGGGGGAAEGCHEDEAEFHFAFGCBHBCCCCADBBAGAGHBCACAHAHBFEDBGBCBEDDHHABAFAHAHFBCAAAA,False +885,16.0,26.0,24.0,20.0,25.0,24.0,19.0,20.0,DFDGGAEAEAEDHGHGCCABBEECFCFGBGBDCGFFDBDECEADADHGHFDBDCEEBCGCGAFBFBCHDFDFEFEFHFHFHBHFEFHCHCBAFDFBFCAGAECBBBBEAEBGCECFHEHDCCEGBGBGFGFHHEHCHBDACECABABDBHAEDDCGGBBEFDFDCBAEHEHECG,False +886,13.0,28.0,17.0,8.0,23.0,25.0,17.0,16.0,GFFBFBHCFBBBCGCGEEBCBABFDEBGBGCACEHFHFHBADDCGEGEBHAAACFCEHBHBDAEFFFFDFDFEFEFECEBBBHFGBBHBEGCBEAEDCHEEEFBGHGECEHFHBABFCFCFCGCEAGDGAGAFBGGAFHHHBEBEBF,False +887,12.0,16.0,10.0,18.0,15.0,11.0,14.0,8.0,EEHEFGDCAFDGDCBFBFGFBEAFBBBAGFGBGCHCHCAGADCFCDBDEHEAEDGDBHBFGEBEBDBDADCDHDEABDDEDFCAGDGAGAFDEAGCGBEBEHEH,False +888,18.0,13.0,17.0,15.0,11.0,10.0,18.0,15.0,DEGEDEFAHAHAHGHGHGCGCFDDDADFCBGDGDCBABCBEACAGAGCEDBABDHFGAGAGDEEHAFCDCBCACBEBHCGBFAHAHCDFHBGBGHFHGHFBACEGEGCHAECFCDAD,False +889,22.0,5.0,11.0,9.0,14.0,19.0,10.0,13.0,HEHFADEFGFCEHEFDFHFAFGGGGAGAFADGDFAEAHBCECEDFCFHFCFDFDAACACABBFGCHEAAABCDHEAEABFHFHEGEFHAAAAACAGDHCHEFE,False +890,27.0,36.0,17.0,27.0,26.0,14.0,25.0,25.0,FHDGFABEECADAEBECEABAGHECDCDADGDADADEHEHGHBFBCBGDEEEEEBABABHBHAGCEDEDEHAHAGGCDCDHBABHBCACAGFCFGHHFDFDGBGHGAGCGFFBHADFCECEHBDBGBABACAHEBBHGHEHBBEDEFEBGBDBCGEDBBBBBEBDHDBAHGFGAEBHAADGHGDABFCFDAGBGDHD,False +891,18.0,15.0,22.0,14.0,25.0,27.0,18.0,19.0,FHFHEHAHCFEDCDHFFFHCCCCCCFAFGEAHAFGGEGEGEGFGFAEHDCDFHGAGEBHFHCHBHBEDHDCFCACGBFCDDEHBCEGAFABEBFDEGAFDCACFEFEDEAAGAGAGCBCDFEHAHEHBCBCBFBEEFEHGGGCEFEFEBEAFFBDADB,False +892,15.0,15.0,17.0,14.0,25.0,21.0,15.0,21.0,EGAHHHDHDFEAEDEGGGGAGFHFAFEEEHHBCBGHGBGDFAAEAECEFEDDBFCFCAGFFHFHFHBCFCDHFHCHADBHFGFGBEBHHEEDDCDGBCEEEBGBHEHEDEAFCBCECEBGAAAEDCDCACABEHHCFEFCFBF,False +893,5.0,2.0,1.0,1.0,3.0,2.0,5.0,2.0,BHAHAEEEGFGFACGBDAGAG,True +894,1.0,2.0,2.0,3.0,4.0,6.0,4.0,3.0,FCFCHHEFEFGGGGHDBEBFAFDDE,True +895,12.0,25.0,10.0,17.0,18.0,19.0,18.0,17.0,CECBHFGFGEBBHFEFDBDBABDGAGAEABCBGAGAHCEEHEHEHDDCDBFHFHEDFCFBFBFAGGGGGFGEHBBBHDHBHDEBEFGDCBBBDBGCAHHEGBGBCDFDEEEDEACAFFGBBHFHFDFAFHGBADED,False +896,16.0,8.0,11.0,13.0,10.0,11.0,7.0,7.0,GEDEHEHBBDADFDADCDCAAAHFHFGFECACAEDCDGAEAEBBCBGEACAHDBDEGFHFBCDCFAADACBCHFAFAFEGGDF,False +897,11.0,6.0,9.0,7.0,10.0,14.0,15.0,10.0,HDBFBGCFCGCGBGDEDGHAHGHAAFHFCGBGCAHHGFCFAFEBGHGBDCHCHDEEFEFEAEAEFEFGDGFAFACGEFDAGA,False +898,17.0,13.0,21.0,30.0,28.0,20.0,12.0,19.0,EDDBGCECEDBCBCDHGFECBGBEHHHEHFHDGDHHAFAHCHDBEFDADCDHEEEHEGDGDGFEDCACEDEAEAEFDFDFDADCCACFEFCFEFCBBHCCFEEDHDFGEGAFCFCACABABCGDEDAHEDDDDGDGFHDHDABFCFDFAHEEBEBEHEAA,False +899,3.0,3.0,2.0,3.0,3.0,3.0,8.0,3.0,BCEFGHGHGAGBGBGDFDCHEGEFAADG,False +900,16.0,24.0,17.0,15.0,11.0,13.0,13.0,18.0,DDCDADAECDHHHCHADDHCHCBCADAECGHGEAHFHGBBHDADAEHHFHGACACFCFBEBEDCGCGBBBBGEFFHFBBGCGBABABAHFEFBBECCHGFDFBFAFAHBBEBEACDGDGCBHBGBDB,False +901,25.0,30.0,29.0,16.0,34.0,19.0,24.0,19.0,FFGCECEBBBCDCBFEEEECGCABAFEFGHBDAACECGHDFCHBFBGGGBGHCHCBCECBGBEFDHBHBHCHAHAGABABGEGFCFBEGEBBCBCDHHHCHCHDBDCFCAEDHGAGEBEGEBEDEFFDBDEFBCEFEAGGFGEGFBFHHACACAEAEAEBEHEBAGAEAECGABADDDAECECFAAEDDAGCECBG,False +902,24.0,23.0,19.0,24.0,26.0,27.0,19.0,14.0,FAAAEACAEEEGEDAHEBADAGGHEDCABGFFDFDFEBEBEDEDGAHFDGBCBFDFGECFBFGFBFEFCFEDADBEFEFACACACAHADBBBEHAHBGBFAGBEEGGFGCGCFAFDFEBHGCAAGDGFHFCFCHCDCBFBGBCBEHFHCHCBEDGDACAEBDBHFHEDDDDDEAED,False +903,29.0,29.0,25.0,18.0,19.0,26.0,26.0,24.0,GABBEDADAGFHBHFHGCBCBDADGBGDGHEDBGBGDAEBEAGFGACEBEDADFFFBBBCFCGAFAHEHEHGBAAAAAAGGCCHBGBABHEEFHFHAHFBGCHDHFEBEGEAEDFGCHBHACADBHGDGCEDFFHFEFBCBABAHAEAGGFFCFAHADGDGCBCBCGCGCBCBCFHEHDFFEFHFCFABCHCDCAC,False +904,6.0,3.0,10.0,6.0,5.0,4.0,4.0,1.0,ACGCFCACDCHCDDDEDCGGEFBCBCBFGFEEAEDCAAA,True +905,3.0,18.0,9.0,11.0,14.0,16.0,4.0,13.0,DCFBBCBEBDBFFEFDCGHBHGDCFBFDEHEFBHBFEFHFHFGCAEHFAFBEHEHEHCACHGFDCBEFEHEBDBDBHBDEDEDBCBFB,True +906,16.0,25.0,37.0,22.0,24.0,10.0,28.0,28.0,DFDCDCEAEHCHEACBHBGBHCCGCECADDDDDDCHHHAHCCCGDECECEBECHCFCFBHBACGCBABCBHGEBBBHGHGBCBCDEEAAGAGDHFCCEDEDGDGDGBGHHDFFGEEBFAGHGFCBBGEHHBCBDBABCEAGACACGBEHEHCFDHAHEGGGHGHGACEDECHCGCGCDHFHBEGEDBCGC,False +907,25.0,18.0,28.0,21.0,19.0,32.0,30.0,20.0,GCGCEBHGCGCEDDHHGCCCCGHGHDHEHACGGGBGFGBEACGHGCFDFDCCCHCFDFAFAEAGABACAGACEBHBFGFBFBDHCFAFGFACAGDEHCDBGHAHBBDFDFCFAEBDCGFAHGHGFGFGBADFEFHBDADABBEAFHDDFDFGBGDEDEFAFEFEFGFAFDFEFCACHFHBEEECGCGCAAEAC,False +908,28.0,27.0,16.0,15.0,23.0,29.0,25.0,24.0,FAFEFGFBABHFFBHDCCGAABEBCACAEFFCFAGAEEGEGFGFDFHFHBAGFGBGDHBHBHBCGEGFAAHAHAHAEGEBEAHABCBDFGFGEGBFBHBDBFBFGFGHGHBEBEBDGHGFAFCHADEEECECFBACCBCDDHGGEHEGCAAFAFBDHHHDHDFDADGFAAEAFABEECGHHDBEACB,False +909,22.0,23.0,20.0,21.0,31.0,23.0,29.0,28.0,EAGGGDCHHHHCDDEDBCHAEDGBGAGADBHAFFHGBGBDEGEGHGAGDBEGAGCCHFHFGEGHHEAEBDDDDADHCBBBCACFCGAGECEAEFEGEDDAAEFEHBHBGBFCFCHGBBDBFBFDEAEAEFCDDEGFGFCECAGHGFGFEHHDAFHFHGHGHFHFEEEHAFBBBEAECGCBCBCEEAHACBFDFEHEH,False +910,35.0,20.0,17.0,22.0,15.0,17.0,23.0,20.0,BABABADGDFFFFFADHEEAEHCBGBGDGEGCACHEFAAHAHAHBHGHBABCBCGCFDFAFCFCEAEHEDGFGBAAADBGADADBDBECGGFCBDBHCAADAHAGADCGFGFGCGCEDAAEAHDEDBAGFGBADDDCDHHHCHAHDEAHGFAEAFBDHAGAEHBBGCGA,False +911,20.0,22.0,16.0,16.0,19.0,34.0,24.0,21.0,HHBBFFAHAHEFAFCDBDBDGCEEBFBDCCBCHDFAFDBDBFCFAHGEDBGFFFDFHACEDGDBFBFCECHCHBFAFADAFFFFFFFGFBHGHGHGHAFABACHCFGGGAFHFHGGGGFAFEEGHGEEEGECDGECBCBHDGDGHEHDBAGEBEAEABABFEGACHEBGFAF,False +912,14.0,22.0,22.0,16.0,10.0,16.0,13.0,11.0,GABHDHAHACDCBFFFECHFHEBEGABCEHEBBFBACHCHCACABEFFDBACDHFADAFBFBGGCGCGCHFBFCGDFAFGBCBCBDHDGDCBCBCGDGCGAGABCBCACEDFDEEFBBDDDEDB,False +913,20.0,27.0,29.0,23.0,22.0,31.0,29.0,18.0,GFGEECFDFAGEFHFACDEGCGCGHGHDHDCGCFDBAGAGAGDGHFDFBFGFGAGHDAGAFABDCFFECECEFFDCDCBCGDBABFFHFDDDGACHHDBEBEBFCEEBEHAHECBABGGAGDHDCEEGFCFBDECACAFHFAFACBEAGGGBGBCBHFCFCFCFCHDFAEBBBHBEBECFCHEEGBGBFCDBDBDBHGC,False +914,12.0,9.0,6.0,2.0,6.0,6.0,2.0,13.0,BFBHEHEHBADCHBAGFHFEBHAAACABHBHAAACECBBACGCHFHAHAHEHEFFD,True +915,10.0,12.0,24.0,13.0,16.0,14.0,13.0,16.0,CEBDBDBDCDCDCDBDAHHBFBFCFGFGEDFHCBCFGECFCEBEBHBCCFCFDFEHAFBHAHAHFCACHCECEHACBCHCFEDEAGACDCHCGAHCDEGGHEEFHAGGGECEGEHDGG,False +916,4.0,4.0,9.0,4.0,6.0,12.0,3.0,4.0,CECDADFBACFCFDFBFGFCFGHCCGBEHEHEHEFFCACBEFFFAD,True +917,15.0,18.0,12.0,11.0,16.0,11.0,18.0,15.0,AEAEAEAEAHAHAGEEFHGHBHBEDABABADHGFGDHBCDDFHGBEFFFAFGGHBDFCBEHECECGFHBHEEGDBEGEBBGDCDHDCACGFGHGCABABHFACCCCBGBGBGDGBE,False +918,14.0,16.0,12.0,30.0,16.0,18.0,12.0,16.0,DHDAEBFADADADADADGDFAFHFHDEFGBGBGBGFHCGEHECEAACACGCDDDFEBEBHBFAFHCDDDDFCFDFGHCFDHEFEFDCHBBBHAEDEDBAAHCEFDCDBDFDBEEDBDHEBDHDGFHDHEGGGCB,False +919,5.0,11.0,3.0,9.0,10.0,8.0,8.0,5.0,BFBHEEEBCBHEHGAGAGDDBDEEEHABFCFBAGDCDGDBDGAFEFEFDBDGGFBFBHE,False +920,5.0,0.0,5.0,4.0,1.0,1.0,4.0,2.0,CGAAFADHDCACGCECGDGDHA,True +921,24.0,17.0,18.0,26.0,23.0,31.0,24.0,25.0,EDEDCDADFGBABAGGFCFDFEGCGBHHECEADGDEDFDFDBEGEFCAGFEFEFDHEADHCHAHFHFHEGEDDDDBGEGEFBCDCEAAHDBAGHDHFGGHEHAHAHAHFHFDFBGBHCGAGFEFEFADACAFEBGCCDBEBADAFBGCFAFCHCHAFEFGCGBGCAFABCDAFBFBHDHFHEGDGHFH,False +922,12.0,3.0,17.0,8.0,6.0,8.0,19.0,16.0,GDFCHCHAADGBHCHAFEHCHCBGBCHFACAFADGGGGGGCGCAADHEHECEAEDDCCEGFGFGAGAHHGHGCDADCCHHGCGFHFHGC,True +923,13.0,7.0,15.0,17.0,15.0,11.0,14.0,5.0,GDDDHCCBCDADAEABADADGHFDCCACAEAGGDEEEDFHFBDGCHBFBFDGGBCDDDFCFCFEEGCFEFADADACAGGGGEGCCAEBEHEGEFECE,False +924,19.0,22.0,14.0,20.0,28.0,12.0,19.0,18.0,CGCDHBFBHGEBEADBDGDGDCBCDCHCEBHGEGEHEGDFFCEAEDGCGEGFDEEEEEBABCBCBCBCBGFDFAEAFDHDHEHFDAAHHHHEAEADAFEFEDBABDHEFEAGCBBFHDHBHBGBADHEEDBDEGBAEAGGCGHBEGGAAAEA,False +925,20.0,23.0,18.0,19.0,19.0,27.0,21.0,22.0,FEHEHEGDGCBDBHBEBCAGACHFEFHAHADAFGBGFFEGECEHDGDAHAHEDCCEAGFDFEGCCBGBFBFHDADCBCBFBCCHBHAHBDCECDFHFGFADCFFFFBFADBGGHADFDBBCBGHHHEHEHBAEAEFGBHBHGAGEFEFGFGFDCDFBFACAGAEADGDB,False +926,8.0,4.0,5.0,5.0,6.0,5.0,4.0,8.0,FGFDECECEADFBFBHEHAHADAHAEACGDADHHHBHFACBEGCG,False +927,4.0,9.0,2.0,4.0,9.0,4.0,11.0,2.0,GHGBGDGBGBEAGFGBBBBDDEBGFGEGEDECEAEAGBFCEHFAE,True +928,19.0,13.0,20.0,26.0,25.0,21.0,11.0,20.0,DDDFAGCFCHADFCCECECFBEHDBEBEDEHEHCFAEAEAEFDFBFADAEAEAEADHDFDFGBGBADEDBHCGCFCBEEAEHECFHAGACCCDDEDHHHHAHDDDACGHBACFCFGDEFEBHFHFCDDDHDACECBDHGHEEFGBGFGFEDHFBA,False +929,31.0,26.0,25.0,22.0,30.0,19.0,16.0,16.0,GADBEEEAEAHACCCCFGFEHBGBGCFCFDDADGBAAAFEFAABEHADFDFACAHBHGEFBAAACFCGABEGFABGFGEGFBFBEBFDEDEHGFEECHAHADADADCHEHEBEDABHBEACADBDBDGDGDCDCACHEHGCEHDCEABCFAEDFDGCEBFBAAEHEDEBCBCBCBCBEEAEBCHC,False +930,5.0,6.0,16.0,9.0,2.0,8.0,6.0,8.0,FCFCBBGDGDBABHCHCGEBEDDGACFCFCFCHCGCABHCCCCHFHCAGFHHCAFDDDDD,True +931,13.0,10.0,13.0,5.0,17.0,8.0,8.0,11.0,AEAEAHAEECBHBHGHAEBFCEEAEBEGCHBFBGEGFACADAEGEDBFCCHHBHBHFHCGEGHDDCDCACAEAFBCGCFEFECEA,False +932,13.0,15.0,7.0,16.0,20.0,10.0,5.0,18.0,AEABBCHEBEHEFEDEAFBHBADFHHDBDEHBABABABACDCFEFHFEGGACEDEHEBBAFGHCEDEDBGCHHDBDBEHCHDADGDEDEDHFEEEAHAHFHFHD,False +933,4.0,6.0,3.0,4.0,2.0,6.0,4.0,5.0,AGAGAHBEEDCGBGBCBDFDFDHHAFBFHFCBHF,False +934,5.0,12.0,3.0,2.0,5.0,4.0,9.0,11.0,CEDBABACFFGFAEAGCGBGHGHBHGHEBBHBHGDFHHHHBEBEAGBBBGH,True +935,8.0,6.0,1.0,11.0,7.0,1.0,14.0,7.0,GEBHGHGDBAEEDAGGEGDGBGBHHHHDDAAAAGDGDGDADABCEGEHEDDFGGB,True +936,12.0,13.0,17.0,16.0,15.0,22.0,16.0,19.0,HHEDDDDGDGAFACACHCFEEECACADBGHGFFFFFFEHEHCAGBDFEFDFEFEHEFFBBABFCHEGFGDHBCBCBEEAHCCECDDBFBHCHFHFHDEDGGGDGBGHCBGAFDGDGCAHBCCHGHFHFAA,False +937,3.0,4.0,1.0,4.0,2.0,0.0,0.0,2.0,ADDEDEHBHBACADBB,True +938,5.0,10.0,7.0,7.0,2.0,7.0,13.0,13.0,FCGGGHHAFEFBFBGBABAEGGGGCFCFHBABHHDHDHFHACDBBGHGDGDHCBDHCHGBGDHC,True +939,0.0,2.0,2.0,0.0,2.0,1.0,2.0,1.0,CGEGEBFBHC,True +940,15.0,12.0,17.0,12.0,18.0,16.0,21.0,10.0,DADACBCEGEGCCAHFCDCDAEACDCFGDAEBEBEACABEGGGABACDFDCGGFDDHCGFGEGBCBDEDGHGFEFBFGGCBCEEFAFGFHFAFHGHGCEFEBHBHGEGEGEFAFAHACBHE,False +941,21.0,9.0,18.0,19.0,23.0,21.0,20.0,26.0,EGEDHBHBHGHGHCEAAGBHBDDDGGGDGFGFEFGFGADHEFEAEAFAHAEAHBFECDCAAGDFAFHEHCCDCEFHFHFAEAHACFCFCHCECEHDDGDHDHDADEBHFEGAAEAFBHCCEGGDEDBCHADAHFBFCFCGGEDECFHGAGHECEHFH,False +942,23.0,23.0,25.0,23.0,16.0,18.0,18.0,24.0,CAHDBDHDEGCADHGHGHGHFCDCHCDFGEDEDHDHBHFDFEEADAEABFFGFGACFBBCFCBBFAHCHCEEDCCFHACACABHBFFFDFECACHHEGDGDEDBHBCBHBHADABHBHBCGHACBCBEBABCGEEFEAEAGGCDDDDAGAGAHBHDGBCFGFDCAGACAB,False +943,9.0,5.0,6.0,3.0,2.0,3.0,4.0,6.0,DBDHCFFHCEAEGBGBGAHCHBBAGFCAHAHACADACA,True +944,1.0,5.0,5.0,2.0,2.0,3.0,5.0,5.0,EGGDGHCBBAEGHGCFCFBHBHBHCFCD,True +945,23.0,12.0,17.0,23.0,21.0,25.0,31.0,23.0,AHAHBHBHCHCEDDFCACDCDFGFBHBCCGFGHGAAHDEEGECFAHAHFHDHEADFGCGCGFGEADBEAEBEDDBCBHAAFAFAFDGDHABAEHDHGEEEHDADGFGHGFEFGFCFAFHFEFADGGEGEGECFDHCHDFGHGDGCAAGAGEGFDBGCEBGBGDEDHFFCFGAGDG,False +946,7.0,6.0,9.0,5.0,3.0,13.0,9.0,7.0,BEBECFHFHAHGCAABCCFGBGFFCFGFBFDFGGAGHGFFFFDBCGHHCHCDDADAEAC,False +947,12.0,14.0,22.0,9.0,8.0,15.0,19.0,16.0,GGGGGADFDBBBCHGACAHBFGHGHGFGCCFDACHGHEFFBCBGEGDGFHHHBHDGDCCCCGBFHACACECDCFGBHBHBCEFECHCBCBCHGFGDAAAADAEEFCFCACFFEHB,False +948,23.0,29.0,24.0,18.0,9.0,25.0,25.0,32.0,BBBHGFAEAEBEBCFCFAFAFCFDFBHBGCHFAEGDACAGBHCHFDBCBGGCCBBHHABDCFGHBDCDBDGFBCAFAHHGHFHEHACEGDABGBGHABABGHHHFBFCFHFABAEAGACBCFHHBABCBCBCACFCHGHCHBGBHDDFGAAFFFEDDDGDHDHGHGHGHDHGHGHDCDCGFGFEA,False +949,7.0,6.0,5.0,7.0,7.0,6.0,6.0,12.0,HHCHADDCGBGFFHDHBBCHCHBFADAEAGAFAEAHBHEEEEHHHBGDGEGCDFDF,False +950,24.0,23.0,22.0,11.0,20.0,30.0,30.0,14.0,EHFBFBFBCCFCAAACEGBFAEEBHCHFHEAEAGBGHGHGCGCFEFAFBEAGAEBGDGCGHGHBBGBGBFBFDFECAGGFEBEGCAEBEDGHAFBHBFBDGDGFGDACCGCECACAGFCECHDFBCGCGFFFGFGCBCGABADFBHGGFGDHDEFBHCAAAAAAFFFFFDEEAE,False +951,16.0,19.0,15.0,15.0,20.0,28.0,15.0,17.0,DGGFECEHGHFHCBCEHGDGCBCGCEEFAFAFAHEHFAABHEGDGAGBGEEBHDHBBCBCHFBDBDBHEDFCAEAFFFDFDFAGBCBDECFFFEFDFBFGFGEECECEFEFEDHGCDAHAEABBDGFBFHHBHDAFHFCFAFABA,False +952,9.0,0.0,6.0,3.0,8.0,5.0,2.0,3.0,EFACCCFAAAAHFFFDGAAEAEHGHECECEDECEAD,True +953,2.0,1.0,1.0,1.0,6.0,2.0,3.0,1.0,ECEHDAAGBGEEEEFGF,True +954,11.0,9.0,7.0,13.0,13.0,4.0,8.0,8.0,CADHDHDFDABBEACAFDBBHFHGAGECBGEGEGEBEHEDEAHBGDADADADFDEBEDDCAABHEHCGEGECC,False +955,17.0,19.0,17.0,18.0,12.0,19.0,16.0,32.0,GFGFAAGFGAHADGGHGEBABFEDBHBDFHHHHBGBHDHDEAACBFBFBEAEHCDDGDFHHEDGHGBGBGADHFHDHCCGAEACDCDCAHAHFHFHFHDBDADHCCCHBACACBHFHFEFECACGEBBFDHCHDHBHEFGCECHFFBHBH,False +956,21.0,23.0,17.0,24.0,20.0,16.0,15.0,22.0,DADEHFHDCBCBCAHGBGFDFDGBAFDFDHHFDBDBACACFEHEAEAHAEEBAGCHCFCFAHAGDGDADADHHGHGECCFCFGFCHAHGDGBCCHADBDEAHGCFBHBHBHEEEEEHEBEAEGDBBFBHHCDCEBBBDBDBAADGFABADFEEGEDDB,False +957,10.0,10.0,8.0,10.0,12.0,10.0,10.0,2.0,FGFBFDFCGGFGABBBDGAAAFHFDGDBDGDEDECECECECGBAEHECGDACEBGBDFCAEAFFEDEBABAE,False +958,23.0,37.0,29.0,27.0,20.0,20.0,23.0,19.0,ADBDBAFABHBADGGCCCHFHGBBDDCACACBBAGDHDHCHFECBHFEGEBEDCCFEDEFBFBCBCBHEHBGDCDGBGAGAFFGCGEGAADACADBGFEDGBGFDBHBCAHEEFFDCDADBDBACDCDCDBHBHFEFHFDBGBGEFHFHBACECEDEBCBCBCGCGBBACAGEFBFBABGDGDHEHEGBCDCBHEAAA,False +959,12.0,18.0,18.0,8.0,12.0,10.0,17.0,15.0,BEBEBGBGBHBCBCECGCGCDCFGGHGBCHEACCCEFGAAAEHBHEHBGBHAEABHGFCFCDCEABACAHEHCGCHFEAEGDBDHDCGFDCDAHBHGFDFGGGHFBBBAF,False +960,6.0,8.0,14.0,11.0,10.0,8.0,6.0,15.0,EADADHGFDEEHFHDHBHBHCECDFDBDECHFFAFGFBEDECBCECHHHHGCGDGDHCCCCCCEEDHHAHABCGFABB,False +961,20.0,29.0,25.0,20.0,25.0,26.0,26.0,18.0,BHBEFEABGFAEGDGDFFBDHDGBGBFFFHEEEEEDFAFADABGGCGCBCBAFCFABCCHEHGDDEDEGFFAAEEEEAGCGAGHGFDCCBCHGACACEDHGHGAFBFBFAHEBEBEDGBHCCEAEADDDHDCBCFHAHCHBHBFBFBGGGBHECGFGECBCBCDHDBBFDCACACBFGFGEGCDEBFBF,False +962,27.0,19.0,27.0,18.0,20.0,32.0,29.0,28.0,GEGECAFAHHHHEAEBDBDCHHGHFEFHDBFAFBFDGDBCBCGHGHFCFCFCFDEGADHHCCADADAGEHEHGACCHGHBHEHCHCHFECGCFAFBFAFGFBCAEFCDHAGFBFHGEGAAHGFGEDEACDCFHDDCDCFCHCGCEDGHBDAAFAGBFBFHEGAFACADEFEBEGGGCGCBBFBFGAGAGAFABAGFBEHF,False +963,18.0,20.0,27.0,19.0,14.0,17.0,15.0,25.0,FFACCGCGCDDHCHCDGGGEHFBCBHFCAAAAHAGFGDGAGDGHFBDEDHCBCACACGCGAFEBBCECEAEHEHBBCHHHHAACDCDBDFCFBFBHCHBHDGCEEEHEDGBBBFEFHFHDCDBDADAHFBCBABDCEAHHDACFCGHBHFHDCFE,False +964,12.0,10.0,8.0,9.0,12.0,10.0,10.0,9.0,FGFAEAEAGADFEECEHBBBAHAEBECECAGGHBAAGEHFHDHAEFDFECDCBFBFBABDDFDGGFGCCCEHAHBHGDGD,False +965,17.0,22.0,24.0,31.0,26.0,22.0,22.0,27.0,CGCEHFCFCEBDBDBEHEHGHGHFABABHEHFBEBGHDHDFCBDBEBGGCHCFDFHEHDHDGDFFBCAHAHGEEFHBHBEBADFFAFAHDHGAGAHEDDHDEBEFEBEFHFHACADDDFDEEEECCCDAGADBGAGFEHBGGHDCCCDEDGHCECDDABFBEBCGEGCGCFCDCAAEDCBGHGDFDGDCDF,False +966,27.0,18.0,26.0,14.0,26.0,27.0,37.0,24.0,AACDCHCFGHAHAGAGACFHEHABFHFAGHBCBDBFBFBABFHHHFHFCEDEFACHCECFGFEFECGDGHGCGFGEHECDCBCBGBECEDFAEECAGGFAFBHEFDGBGEGHFEEGEHCGEGDGDGDFCCCCHBAEACHGHGAGHGAGEHEGEGBCAGGGFABHDADADAGAFHBEDCFAEECFGFGFGCGABEFGABA,False +967,19.0,30.0,23.0,20.0,26.0,19.0,25.0,21.0,BBABCBGGAGFDFGHDHEGBGCGBBAFDCBCEFHDCDFBCBGEFBHBEEEEEBADAHAHBGGGEDBFBHCCCECBGHDHDFGBDCDFBEHECGBGBGFCFAHEHDGEGEFDFDECCCHCHEGEGHGBCEAGABEBABABABADADABAEADCCEFBABFECDFHFHCHFEFCGGEHEHGDADH,False +968,22.0,15.0,29.0,26.0,37.0,20.0,22.0,24.0,AEGBABEFGGEGDHDHAHEFECEFACEEACHBECFBABCDCACAHGHDEEFECECDAAAEHGHGHDHDFGFHCADFDBDEDEAEDEDEDEDGGECEABBGFADADEHGHFECBCAEAEGECECAGDBEGAACCCCCCBHEGECDCDFHFHFHFHFCGEGHBDFEBBBGECHDEFEHHGDADCGHGDDCEFHFCFC,False +969,16.0,6.0,14.0,15.0,9.0,8.0,13.0,13.0,HHHHFEFDDCAHGGEGDGDCBBHCCDADGGHAAADADFDFDGDGDGABEBAFABECDHAAFAFEFGDGCHEHCDCGCEEHHHAEACCCCBCGAA,False +970,21.0,25.0,9.0,17.0,8.0,13.0,18.0,16.0,GBGHGACACAFHFBCADGGGFGFGAGAGBBDBGCHHEHEBFDEABGDGDGBHBCDFFFFHFHAHBDACAHDHCCGAEADBHBDFABABABEBEAECGGBHBHDFBBBBAFDDAGBHHABDDADADBE,False +971,9.0,10.0,11.0,9.0,15.0,9.0,14.0,12.0,EAEDFCFBFBAGHGHGDGBHBGFHEHCFAFAGHECGCHCADAHCEGDGCGBBBBDBDEGFGCCFHEEEHEDEAEDBCGHGCADHEFEAE,False +972,18.0,16.0,12.0,13.0,15.0,19.0,12.0,21.0,BEHFBBABAHGEEAEAFAFCDEHFHAHCGCFBEAAFGCABHHFHFHCHBGADCDHDHCHCEEAGBFDFGADFFFFBFBGDGAGAEADHDHDAEEEBCBCBHBDEEHGFGFBFBDEHCHGHAHFCAD,False +973,27.0,25.0,26.0,28.0,24.0,17.0,20.0,27.0,HCHEFEACGCFDFGCBCHADFCFBADCGHBHCDDDCBAAHAEEDADGDGHGHGHGDAAEBEHAHGDADADEBEHHCEBADAHHHHCHCAAAHBFBDCGBFCHEEFBFBFHAEADDBFBFBDGDEHEHBHGCGAHACECAFBFBEEEBECEFDCCABDBDEDEGAGADEDEDCFBBACHGGFGBGCGDADCHCBC,False +974,2.0,9.0,5.0,14.0,10.0,16.0,13.0,8.0,HBEGFBDBDHEEFHFEGDBFBFBGHFAFDFGFCFDBDBDHDHBGGCFFEGEGECADGFECEHFGDCDHDEDGFGFGD,True +975,7.0,10.0,11.0,8.0,6.0,8.0,11.0,11.0,CECFCDCHGGGGHGAFCECEAECDCGHHBADHDHDBDBFBFDAHGBBBBBBGCFFFAAEHDFCHGAGHCHGE,False +976,22.0,16.0,20.0,24.0,18.0,27.0,21.0,14.0,GDBDHEGEBFHFHDDCFCDAAGEFBFEDBAHGBGBGDFEBBADGHGFABAFAFDCDCBCAHADDDCAHECCDAAFAFGHCCECFGECECEFDHCHAHGBGBGDECECECEAEAEBFBFGHGHAADDFDBDGAFCFBHACAEEFGFAFDFDFGFGDCDGGFFF,False +977,16.0,17.0,23.0,22.0,27.0,15.0,19.0,22.0,EEGGFDFHCHEEAEDEHEHGCEFGBEBEBHBDDCBAHAHDGDAEGEGDHFECBDDDHDCGCFAAAAAFCEHBBEECEFDFDBDBCCCCEFEGAFFCFCFCEBEAHAHAHAGGHGHCHCBGEDBDGEEHCDGHBCBDAHFHBHFGGDHDEDAGECECBCDCG,False +978,5.0,8.0,11.0,18.0,14.0,13.0,11.0,18.0,HFHDBAGHGEFEHCGGEGDAAFHFEFEFDHDGCECHHEHEDEDHGHDFBFCDHHHAHEHBCBCBCDCDGDECEDGDEBFGDCDEBGHFBFDCDFHFDA,False +979,22.0,10.0,19.0,14.0,19.0,26.0,19.0,18.0,HBGDGHGCGBGEFEAEFBDEHEAAHGGGGHDHDHFGEABAFAHEHCACFFDFDFAFECGCDCDCDCFCHCFCHAHFDCBGAGDEHBGEAFAHAHEFAGHEAGACEEEFFFFEFHFBFCFBACGCAFAFCBEFEGEFCGBDDDCAAAH,False +980,9.0,10.0,16.0,13.0,13.0,13.0,17.0,6.0,CDCEBDGFGFACEBDHFCEHACADBDBHBCBGACCECEFEFGFGACHCACDEEGGGEGEGDGCFFFGFDBDFGGAGAHACDDDDGEGFCFCEHBBEB,False +981,19.0,23.0,15.0,12.0,16.0,18.0,17.0,17.0,ECEDHFHFHFAGAHBHDAEFGFBEHGBGBCBHBCEDGDCBHEAGADEGHFHDBBABEBAGAGCCDADHDCGBBBEGAGAGEBBBGFGFCCBFBFEGHAEGHFCFCFCACEDHDAAAAAHDBFFHFEFCBCBEBEFHA,False +982,21.0,16.0,13.0,14.0,20.0,12.0,19.0,12.0,EBEBGBGDGEGECHCHFAAEHBCAEBHBECECACGCDCDCDBABAFABGHGHAAEAHABDEDEFHFGBCDAEAGFGECDHGFGDDDEHAGGGEGBCFDFAFBEGECEHAFDFGABADAGAEBHFAEB,False +983,22.0,16.0,20.0,28.0,16.0,18.0,28.0,14.0,CGCGBDCDCGHACGFDFDGDBDCFEFEFADAECBDDDEAEAEAHAHABGDFAAGFGFGCAAGEDEGFDFDCGBGAGBGHHHGABCBDBDFDFCFDFGCAHAGACABAFEFAGEEDEHBCCHEGBBBDBDHGEDCHCEFAHHGCDHGGFGDGDGDBEGACDCD,False +984,26.0,22.0,19.0,22.0,24.0,27.0,32.0,24.0,ADHHEFAFADABADAFABCGCGAGFGFEDADABEFHFHGHDFGEGADCCFHHHGHGEFCFCEBDGEFEFEGAFBFBFAHGBEBEAGDFAHABAEGHGCECEHBHBDCFFHBAAGAEAGBCCDCDHDHDBDBGBEDDDCBBFBGEDFDHGEGEGEAFAGGBGBHEGBGFGDECHFAFEHHFCGCGEGCCHCHAAFDG,False +985,7.0,9.0,7.0,9.0,13.0,11.0,7.0,5.0,FCBCHEDFAFHEGBGFAEAEAEAFGDGDBDBABAFGEGDCHCHEEBFCEEHEBEDEFFDFGBDBCCFD,False +986,8.0,13.0,17.0,13.0,13.0,11.0,14.0,10.0,HGEDFDFDFDHDHDHDBFEFAGAEBEDGDHHFBBEEABBBFBHGHCCBCEEGECFBACDCDAAGCFCGBGFFEAGDGHCCDGEGCGCGCHCECBCACEB,False +987,20.0,12.0,18.0,25.0,18.0,18.0,21.0,30.0,AAADFHFAADFECBCECEHEHADCDGDGDCFHFHGCGCGFGFCFHDCAHEEGDGCECHCHEBFBHGHGEFHBHFGDADEDHDAFADEHBBBEGEFHADFDBCGDHHGHGHGDGDHDGDFCFEGGFGCAAEAEBHAHADBHEAADHDCECHDADHCHBHFHAB,False +988,20.0,13.0,12.0,16.0,10.0,14.0,25.0,12.0,BBBCHGHGAGFGHGDCACHCHCAAAAAAEHBDBAFDGDGDFCGGEBAFDEDEHEDGDEDADABCBFDGAGAGHGAEDBGGGGDGBFBHAAGBGHDFEFGAEECCGFFBFGFGHCHAFFCACD,False +989,12.0,14.0,12.0,10.0,10.0,5.0,11.0,8.0,AEFEBABAHACGFBABGBGDEDGDEBBCBCHCECBCACDCGHGHGEACFCBBBEFGDDDCDBDADGEHAACHEGAGFBEHAH,False +990,22.0,22.0,18.0,21.0,13.0,23.0,11.0,18.0,AHAHEFFDDCDFGHDFDECHDHABEBCBCEAFBGGGGFCHCBCHHBEDFAFABCHCBCBCBABDDGHHDBFGEEDADFECGBAECEADADADAFFDFBFBFBFAHDFDBHBDEAEFHFGAHAHAHACCBBABGCGCFHFAFDFDEBCA,False +991,10.0,6.0,7.0,9.0,6.0,4.0,5.0,5.0,FDCBCGFHFHBBBABGDFDAGACACEEECAHDDGDEAAADADAECECHDBGH,False +992,9.0,13.0,4.0,15.0,7.0,15.0,17.0,13.0,DEAHFHGHBEGEBBGFFFAFDFDHDGDGHGHFHFDDDCEGBACGDBDGDEHEHGHGBGBGHFBABABFFFAGADHDGGGHFACBFEDDBCAFB,False +993,1.0,1.0,4.0,3.0,4.0,6.0,1.0,3.0,EFEFEFAFCEGDFHHHDFCBCDC,True +994,16.0,14.0,21.0,15.0,11.0,19.0,16.0,24.0,AHACCCDCAAFBFEFBDBAAGAHHCHDHEHAHEHEBGAGAFHFCGCEFEFEDACHCHCGGGFDFCHCDDDHDHAECHGBGBEHCFBDBGGFHFGBAFHFCDADCFCBCBCEHAHFHBCEGGGFAHBHDCDFHFGDB,False +995,7.0,6.0,13.0,6.0,12.0,13.0,4.0,9.0,CEAFHCHFHECCHEACFCFGGAGFCHCHFAFEDHHCECFBDBDGECHDFEEEEEEBABACFCFDFDFBAB,True +996,4.0,9.0,13.0,8.0,5.0,3.0,3.0,5.0,AGAEADDCACBCBCDCDEHECCFHEDBCBCDDDFEBHBHCCCBBFHGCGB,True +997,3.0,1.0,1.0,6.0,4.0,5.0,7.0,3.0,DDDFHEHCGFGFGFGEDAGAEHFDEDBGAG,True +998,18.0,17.0,15.0,15.0,11.0,15.0,12.0,20.0,EBCFCHHAACHCHCHGBCBCBCHDADAFAFEFDFDGHGHCBCFFHCACDFAFAHAEAEAEFEBCHAFBHBFGAEDBDHDHFBCDEAGABBHGADDBDBDHHHEBAGCEEHFHBGGDGFGAGDB,False +999,6.0,13.0,8.0,13.0,6.0,19.0,12.0,12.0,GDGCGCHCAFGFEFBFDEDHFBFBDBGFDADBFBACGBGDGEFBHHHHBDAFGFGBGHCFFECEFEFBAHFDFBFDAHCHDHCHDFDGB,False diff --git a/tests/results/nb_gm_002_2back_240trials.csv b/tests/results/nb_gm_002_2back_240trials.csv new file mode 100644 index 0000000..1c50201 --- /dev/null +++ b/tests/results/nb_gm_002_2back_240trials.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,ralph_skewed +0,30.0,39.0,31.0,30.0,32.0,24.0,27.0,27.0,False +1,33.0,23.0,27.0,32.0,37.0,34.0,25.0,29.0,False +2,31.0,20.0,37.0,28.0,31.0,32.0,26.0,35.0,False +3,27.0,32.0,39.0,24.0,25.0,34.0,35.0,24.0,False +4,34.0,24.0,38.0,28.0,31.0,29.0,28.0,28.0,False +5,29.0,24.0,36.0,31.0,32.0,32.0,31.0,25.0,False +6,25.0,38.0,28.0,30.0,33.0,30.0,26.0,30.0,False +7,27.0,30.0,30.0,29.0,32.0,26.0,33.0,33.0,False +8,24.0,36.0,32.0,23.0,30.0,29.0,35.0,31.0,False +9,35.0,34.0,30.0,29.0,35.0,26.0,23.0,28.0,False +10,30.0,25.0,33.0,31.0,27.0,37.0,30.0,27.0,False +11,28.0,28.0,29.0,26.0,28.0,27.0,34.0,40.0,False +12,35.0,27.0,30.0,29.0,26.0,30.0,36.0,27.0,False +13,38.0,27.0,31.0,27.0,34.0,23.0,27.0,33.0,False +14,29.0,30.0,28.0,35.0,19.0,30.0,37.0,32.0,False 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+9,11.0,23.0,19.0,24.0,13.0,20.0,28.0,13.0,DFDDFDGFDGCDFFDFEDCCDEGDAHEEDGGGGDAGHFBHFGEDAFGCHGFDBCDBDEBCHDEBGEAFBCHEFEAFBHFCCGEDGADGBCBCDACGCCGFAGBBDCGDBBBEBBECHACFAGFBGABCBBGFHHFHHFGHGGDGGBGBCDB,False +10,10.0,15.0,13.0,9.0,5.0,13.0,10.0,23.0,CAHCFDCFBGFGCFHBHAGHABAAHGFBAFDFBDBHDHCBGEFGDCBDHDEABHHHHGCFCEFCDHCFHBHHGHHGFHGBBABCABCABHEHEFHDCH,False +11,29.0,21.0,32.0,27.0,25.0,25.0,8.0,18.0,HEFAEFGCBEBDCBEADAADADCADABDHHFFEDFBCHACAAFBAFDAFDBCCCFDCEACAACEABFDCFDCFHHFBHDEFDAFCABGAEFDCDCCBCCDCDFAEFDCGCCECCBCBHDEGACBAHBEBEEFDBDHAFHAEAEECEGGHDBHDHCDEADEAHEHFEBFCBAHBHDEGAEFFCFCG,False +12,28.0,27.0,32.0,14.0,15.0,33.0,26.0,13.0,FFFAAFBAHCHHDHGCBBCEBFDGEGBFAACBACBACBAGBGBAGFFGFAHDGHEEFCAAHAHHECFBBFACFACAACDBCAEAHDFHFFCFFEFCAFBEFBFCBCABDBGGFECFGCBCDGGBGFDGDABBCCBEFBEFBAFDACGCCEHGAFCABDGEDFFDCFDGFGGCGGEEGCBGAAGCCCHC,False +13,29.0,16.0,17.0,15.0,16.0,11.0,15.0,11.0,CBECBEFBDDCDCAACAABFAGFEGACCECBEHBEGADFADFBBABCAHCABAABHEEEACEHHAGHABACGDHGDFGCHGCAGDAFAAFCCFEAEBAEDFDDGEABHAGAAGDGBAEDHHGABFEGDCD,False +14,17.0,24.0,25.0,11.0,18.0,20.0,15.0,30.0,DDCDHHAABGECDACBCCFHGEDGAHBABBHFBFFBCFHCHECHECACABHHBHEBHBHDCHCFBAHBFHBEBEDCEDEABCHCHFCHCAFBFBBHGEHGEHGHFCHACHCGGCGCDECFEGHEDFBAFGEFDAAHAHHGFHFABGEBGABGFFEFCEBC,False +15,8.0,6.0,1.0,3.0,4.0,2.0,2.0,6.0,EHBEDEHGEGFABBADBAHCAHAABDAHHABF,True +16,20.0,17.0,20.0,17.0,21.0,21.0,26.0,21.0,DEHCHAEHFEDFDHFCHGCGGCGAFBDDBDCFGEFGEFCEFHDHEFFAGDGDEGAHGFECFACFEEHBEHBGHBGHBGCECEDAHHBGFCCCADHAGHDEDBADGHEBDCHCCFAGEAFAABGABAHBAHBGHCACBEFEGAEFCECBGFDGFDGAGBAGBFG,False +17,12.0,3.0,7.0,9.0,7.0,12.0,9.0,8.0,ADGAGCADCFDFHEFDGHCEHAGGCDAHDCHDAHAFDAFEGFACFECFEBFGBAGAFFAEBDEHGHF,False +18,18.0,19.0,24.0,16.0,21.0,13.0,23.0,20.0,GGEGFBDFGDGEDAHGFBGHAGCDGCAAAHACECDECEBBEDEEDECDFDHBCCDHBHHACBACFHEAEEGHEGDEGAHBAFBEEHCBHCBGGFCGECGECBCAFCGHCBHFHHFHDGGAAEBFCBFDBCBECDCADCACGBHGEHGBFGADHA,False +19,10.0,14.0,15.0,8.0,25.0,14.0,11.0,20.0,EEEEBEEFHEHEEFEEGHEAFFAFHACGDCDDCFDCBDCBFFBCEAHEAHGCGGHGCHEEAEAHEAHEHHCCFGHABHGFGCHGCFDFHEHBBBDFBFBCEAEBHCDGCEEEHBBHB,False +20,16.0,9.0,19.0,17.0,10.0,22.0,10.0,24.0,HFGDDAFEAFEDCGHAADEHDBHAHDCGBAHBECEFFFFFEFEEDHEDCACEGHBGCFGAGGABDHFCHFCHCCDCFHHADFCFFCFFCBFCDHHHHDFFGHHDACDAFDACDCBHCHHAGHABHAB,False +21,6.0,10.0,3.0,4.0,7.0,3.0,3.0,4.0,EABBAEFHEFABAACHDCDDEFBEGHEGBDABHBBCBGEB,True +22,6.0,11.0,12.0,6.0,9.0,6.0,9.0,10.0,AEDBCDECBCHBCBBGFBGFHGEHACHAGAEFBDAECHCFHFDCCECGBCGECGAHGBHBHEBHDFGDE,False +23,11.0,8.0,12.0,13.0,7.0,5.0,13.0,9.0,EAAGACDACDHEEGGGGGBEGEABEAHGCHCCAFCFFGDHGDGCBGBDDEAFAADCDDCDDHBCGBCAFCBDDHHBHH,False +24,36.0,26.0,18.0,26.0,33.0,19.0,21.0,15.0,GBCHFHAAHAFFGBBEFBCFAEFDFGEGEEBECBEBBABBAEBEEAEEABGDBADBACFFBEFCECGACFADABCFDCDBCBBHDHHACGGEHDEGDEGAHAAFAAEDCCHHDDGDDBDGBDBDDCDAGAAFHEDHGDACDACDBGEEACGAEEBEHAFHBGAAAAAAAEEFBEDCDAEEEFGEGGHGFEAFED,False +25,11.0,17.0,16.0,9.0,15.0,15.0,6.0,9.0,CEEFABDBGDBFDFFDGADECBFCBCCACFABEABFABEGBEHBAHEAHEAECCFFCHDCBBBFGBAGCDFHHFBDFDCCHHEHAEBEGCCBFEECEF,False +26,8.0,5.0,15.0,9.0,10.0,7.0,11.0,5.0,ECAGCHDBBDCCDCGHBBEEFDHFEEEHBHGADADGFDEFGAFGAFCCCCCACCDCDGGECGECGEAGFA,False +27,9.0,11.0,8.0,5.0,8.0,4.0,2.0,4.0,FCAFDBEDBABAABAEEAEHDBHCEHCDBCFBABEEGECGBDABFCCAHCB,True +28,6.0,8.0,11.0,7.0,10.0,5.0,9.0,9.0,CFBCBCCBACBEHBEGCADHDGFEGFHGHDAFBAFBEDCDGCHGAACHCHBCEEEEDHEDGEGGH,False +29,24.0,16.0,18.0,25.0,13.0,19.0,26.0,18.0,HEFHCDEGDHFBACGGDEHDGHDGFDEAHFDHGBHEBGEGADFFGCCGDHFBFABDACDABAGFGDAGDAGCAFFAGHHCDHCHACEDDAFDCCDCAECAEDGEDGAFGFCGFAGBBGFBDBBAABAAGADGAFCHBEEGHBGCBFCGFAHHCHDBDDE,False +30,6.0,5.0,2.0,9.0,2.0,4.0,3.0,8.0,DADBAFBDFHDHHBAHEADGFBHFGHEAHDHBDGDCADC,True +31,19.0,18.0,16.0,13.0,19.0,13.0,14.0,15.0,FCHGCAEHAEBDEBABAABHAFEBDCBDCBHCGEAGEFBAFCCECCBCFHEHGEGAEDAECBECEAFEBDHBDEAGFGHDGCDGADFAHGCFCBFDEHEGCEABFADHAFHGBHABHBHDAEBGDFG,False +32,7.0,12.0,12.0,10.0,7.0,5.0,5.0,9.0,EBDGBGBBDCBACGHBDAAHEBGCBFHBFGAFEHFCCCHDCHDCHDAHDCDDEBDEAFECBAHBECC,False +33,1.0,4.0,8.0,1.0,4.0,4.0,5.0,3.0,GAECEGFBHFGHBGCBFCECCECCBCHDGF,True +34,5.0,4.0,6.0,9.0,13.0,13.0,5.0,7.0,CHHEFFDFFDFFDFDGGDFGDHCEAEAHEAFEBFCFEEFEECAECHCHFDEBDBGEGABDEH,True +35,3.0,2.0,3.0,3.0,5.0,4.0,0.0,6.0,CBDEEHHEAHCAEBDFADFHFCHFEH,True +36,13.0,2.0,13.0,8.0,7.0,6.0,16.0,9.0,DEGDECDHGAHGEDGEGACAFCADGACGACHFDACHCCHCEECGHDHBEGGGGCADCAFAGFGGBAGCAHFHFA,True +37,18.0,19.0,17.0,17.0,13.0,17.0,15.0,23.0,HBCABCGHCEEADEDCEDGAGFFFHDFADHHBHHGCHFHHAGHEHEBBBDEFECFEBHCDAADFGDFHDCDCCDCCFACAACHGGBGGBFBCFBFFCFGEDABDBBDAAGAABACBEGBAHAHHFGEDGHDHHEBHBHF,False +38,4.0,6.0,5.0,9.0,6.0,4.0,4.0,6.0,AGDAGHABHCEEFBEFDEHDBHDECDFCDBHDEGBBGCCADFDH,False +39,3.0,5.0,6.0,8.0,8.0,2.0,8.0,6.0,DCEDEEGEEGAAFEHFGHDGDBHDBGBBGECECDGHBGCDDCHCAH,False +40,0.0,0.0,1.0,3.0,1.0,3.0,5.0,1.0,GDGGDCEHFGFDGF,True +41,20.0,19.0,22.0,21.0,30.0,22.0,10.0,26.0,BADBABGCFGFDDDADEFHAAHAAHEAHBBHECFGFDEHDCDBBBHGEDEECCDCCDGCHHBGHCHACFDCFCFEDFEDAHHHBHAECABDABAAEHFEADCFEBFAGFGEABECFEFFECEEFEHFEHEEHDHDCHBBHBDHCEHCDHBDCFAEFAGHEGECBCFEEFE,False +42,3.0,7.0,4.0,4.0,5.0,2.0,5.0,3.0,EBBEAEEHDCHDCGDGGBACBEHBDGBAFBFCG,False +43,21.0,15.0,21.0,27.0,18.0,33.0,14.0,23.0,DDDDDDBCGFEFFABFDHDAGCEFHHACHGBHGBEFEHFEHFCFFCHDGHDFHDAGFECCCAAEAAGHGDFCHFCHBBBFABDEFDFFBBDBAAFDAFAGHACHACEFFEFDHABCAFGDFEDCGACFADFDDFBHFAFFBEHBEHFCHEADEGHEGCDGHDHDEECCFCCD,False +44,27.0,34.0,20.0,19.0,15.0,29.0,27.0,26.0,FGCFGADGADGDDBDBAFGAFDHHHAFBAEEAGGBDBFCEFAHFAHFAECDCBBCGBHAFHABHDCHAHHGBCGECFDCEHCFBCHBGHCABFBCFBEHBECBAHBGDECHFDFBDEAFBBGECGEBBHDBHDBEABEBFCDFHHFGHFAFFGCACFGDGGHGAABCDBHBGGBGGFHGHGGBEADABFABAAFAFF,False +45,15.0,12.0,15.0,7.0,7.0,15.0,11.0,5.0,CAFCDGCFACFCCFACGBBGCAEAEGAHFADBCHACHFCFBEFGEGBDGBDGBEGEHAEFGBFCDFBFBHACAFCAFGABDAFACDB,False +46,12.0,10.0,7.0,5.0,4.0,11.0,11.0,13.0,ECFFHGFGGFCGACGFGGAHFABBHDEDCHABFBHGAHGAHCAHDABDFHDFGCHGBEABAHEHBFHBFCBAA,False +47,15.0,6.0,13.0,11.0,17.0,21.0,13.0,9.0,EDCEFAEFAFFAGHCFCEEAFGFFHFDECECCEGCDGHDGHDGHACFFCFFCDFEHEEFEEGHEDAFBGEAAHAAGCABAEFAFDABGFCFHCDEDBABFGBGGD,False +48,11.0,17.0,17.0,9.0,17.0,17.0,13.0,15.0,GAFGHHGCHBCACCFBCFHHECHBHAFHEEGBAFCAGHGEFGEDGFCBBEBGABCFDCFDCFDBEEEGAAHDAEDFECBGCBHDBFEGHHBFGBFEBFCBCCHEFAEDAEDCEFHB,False +49,13.0,16.0,15.0,12.0,16.0,9.0,12.0,15.0,BGCBAEBCDBEDBECBDCBABDCDFCDBCEGDABDFFEHCEDGECHACHEBDECDGHFFHFHEAHAHHEFFBAGAGHCHCCHGCEEAAAAGEEGDEGBFGBAGBHHBH,False +50,13.0,6.0,16.0,14.0,12.0,13.0,9.0,12.0,DAEAAGAAGCHCCHDFHEFCCBEGFEGFHAHEAGBGCBFCBFCDACDAFDCHECEBFBAFCFFDEHAGHDEFDGCDECEHCHDGADEHHFADCDD,False +51,22.0,27.0,26.0,19.0,24.0,22.0,28.0,20.0,FDCGDAACFACHGCDGEBFCBDCBGBEGBEGAGGFGGCHGDHGDCAACHADHCFHAAEEBBCBCCBAEDAGBFGAFGEGGDGHCEEEDEHCBBCDECEBGEFCCHCFBCFBHFEABEBDEDHABHDBFFFCEFCEDHFFHBFABHAGGECAEADBGGEGAABHAGHAGEFGBFBFHHDHBEGBFCCDD,False +52,19.0,24.0,24.0,17.0,11.0,20.0,12.0,18.0,FBDFCFECGDCFBBFHBFHBAHECHAAHAFCAHCHCFBDFCDHCDBDDBAGAAGAGHFGBDABCFEEAHHGDHBDCCGCCDAEBAEFEBCHBHECHDABFFBHECFDCBDBFDGGDBFABGHBGFCFCBDCBACBFGHEACEACA,False +53,11.0,13.0,7.0,11.0,11.0,7.0,5.0,12.0,HABDABEADFFDABBHBEDAEDACBEHBEGBDDEAAHAHGBHBDEBAEDECCHFDHFGHFGHFDCCEBHEBHGCACF,False +54,11.0,20.0,14.0,17.0,12.0,15.0,15.0,22.0,DFABFDGCDCDDCBHCBECBDHHHBEFBGFEGHGFHEFEAFAHDBHDGDGEDFBAFBGFBGAGGHHCHHEDBDDBCFFCGFCHEEECDDADHBHHCDHCBHFAEGBCBBAHBAGEFGAHABHCBHG,False +55,17.0,24.0,24.0,12.0,23.0,20.0,17.0,26.0,GAECBGBFHAHHEFEGCGFBGBCHHADCACHBGGBHBAHBAEFAFGGFBCCAFCFHCGHCFHCBEFBEFBCHBGFECFGDHBEHCCACGFHEDAEBAEDDEDCEHBEBBEGEEHHACHECBDFFDFADFAEFHCFHCBECDEHDEHCBAGBAGADGBCBHHEH,False +56,17.0,25.0,29.0,22.0,21.0,19.0,27.0,22.0,FFFFFGGHDEHDFGAFGEEAFEGCEADDBBDHDCHECDGCDAAFCDHBGCBGBBECCDCCDAHGBHCBGCHCCEFEGFAABBEHFEHBCGFHGCHBDHCDHCFBDEBEABEDBCDGCHCCFGCFDAGGBGBBCBFABFEGGADGHEGHEDFBBCBCGACDAEEABDADGGEGHEGCCHHAHH,False +57,12.0,11.0,4.0,15.0,9.0,3.0,6.0,8.0,HABCEHAECBEDEDDHBDGAAFHAGCBGBEAAABADEADGHDFBAFBDEBEEBGDCDDGDDHDAHDBH,True +58,9.0,8.0,9.0,9.0,4.0,9.0,12.0,13.0,CAGCGGCBAHDEFDHHGHDFDBFBBFGAFEBFECHABGGDGDEGDHGBHADGFDCACAACHBFHFGHCHHCHA,False +59,15.0,19.0,20.0,23.0,14.0,16.0,21.0,18.0,GDGGBGGCFGABBABFGEFGCDDCFBCDBEBACHABGEBCDCCDFDDFDAACEBCEGGGFHHFDHGGHFGADHFHHGDHDFFGHGGHDEBDCAACGACFADDHDDCBDBBFEBHDDHFCEGBEHCABEAHEAHEFCCHBAEBCEDC,False +60,9.0,8.0,2.0,6.0,8.0,11.0,5.0,10.0,FEBDCDFHFEHFEHEGHBHFBHFEDCHBBBAGEAGEAGHADABFHFFDBFAEFADAAHG,False +61,26.0,25.0,20.0,16.0,13.0,13.0,17.0,12.0,CBACHGCFDHEBHBBEBBFAHCCEAEEABDDBDGEGADGHDAHEABBBEFCFFDEFDAGDADBBHGGCEGBAADABCHGCHGBDBBGCBGCHFAEFCHFBFDDCAACHACFACAACABFEBFAAEGGCGBCGBAGBDDACAA,False +62,9.0,9.0,5.0,7.0,5.0,5.0,11.0,6.0,FAADDAGBGGBGBCHBCAGEADACGAHGACFECDABBFEFDGGDFGHBGHDEHBEHB,False +63,7.0,8.0,8.0,6.0,13.0,12.0,11.0,4.0,GGBDGFEGCEGCECHDCFGFGABGFEHFCGGBHFBHEGEEAEEAFEDBCFBDFDEADACBABFACFEEF,False +64,20.0,11.0,23.0,13.0,16.0,11.0,12.0,18.0,AEDAHACHEFAEFAHCAEDAEDCBAGGCBGFBCHCHFCEACHCEHCFHCEAEAAEAHCAGBDCDHCEHEGBFCHHCGHFBHFAAGEADHBDCADCFDGFDCHDCBGCGAAHCGFGDEBDEBECB,False +65,19.0,12.0,22.0,18.0,18.0,14.0,20.0,17.0,CCDCCAFHAECADDGDGACGADGHDFHEBGEFEAFDHBDGBCGCFHBGHEGAEGBDHFDFDCGDHGDAGDCBHEBHEBGBAFHGCGCCFEEFCDCCDCHECHFCFAAAGECHBBEEBHDAGAAEAAEAHEGHCFCEFGAD,False +66,26.0,13.0,22.0,33.0,10.0,21.0,25.0,20.0,CDFGDFAHFEHDHBBCDECDAHDGGGFBCDBADHHDGADEBDEGDHFFCFFDHDGADHCFHDAGEGCEACGBGGEAGFAGBBDABCABGADGAHADDADCADHAFCFGDGEFBEAHDCGDHDCADFADFGHCCHGFHCFHGDHGHGECCCCCADBFDGAABAFDAFDAFC,False +67,3.0,0.0,0.0,5.0,2.0,3.0,2.0,1.0,FDFEDHDGAFGADEAD,True +68,21.0,30.0,10.0,18.0,20.0,13.0,15.0,10.0,ABBHBEEEHDEHDGFFGDBDBBCABFGDCCDHFHHAAAAABFAEEDBEDBGBBEABEABFBBFBBDDAEEAGCFHEBAFAGDGGBBEDBHDFEFEEBEEBABDHBFBGCBGCGGBGCCGCEGAADAABCDDADEAHF,False +69,23.0,30.0,20.0,17.0,29.0,22.0,24.0,20.0,BHBBFBBEEAEGAEHBCABCBGCGEFHEGHFFBFCBFCHEEDEGCCGBCHFHBAACDGBFBEAEAFEHFEHGHGGACBEDDDBDFBGBAGBAGEDGEHAEDDHGDFEDFEHFACCAEHFBCGBCECFGFFAEGAEAHHBGABGAEGDCGDCHDBBEFAECDHCDHABAFBACBAFBFGEDEEHGB,False +70,16.0,21.0,23.0,21.0,35.0,31.0,21.0,19.0,FEGHEGHEHFBHEBDEGDABDAGFAGCDGCEAEABGGEFEBAEBHDFEFACFEHFHHEBFGGDGBAGBAEEAFBACBCBDFFDGEECFEDFEAFEFFEDFBBFHFFCGFBFCECEHCHFFHGFDGFHECEGCDDBDDEECCBDHADHADEEEECDBCBFHGFHGBCGFCHCCBGDEEAEHAECDCCF,False +71,21.0,21.0,25.0,23.0,34.0,29.0,19.0,27.0,CGCABAFBECCEGAEFEEHEDHEFBAFBFFGFDCBDFHDFDDHCCAEGAEGEECFCDFGDHCDAFDFFHBAEGDECFHHFHHEAABFABAAHCCCCHHGBBCBHGGHEFDFFCGFDGHDAHAGHCEEBBEDBEGEHBEGCHAEHDEHFEBDECFHABHABAAFDDFDDFBEFGHGCEECFDCDCEECEEAHEGHEFBBG,False +72,26.0,9.0,19.0,24.0,24.0,27.0,21.0,27.0,DDGBDCADHEDABHHHAEHAHDCHDBFFEEFAEFAHGACFFEEDHACFCCFGCDACDCCDCEDBADHFEGDHDFHGCHFAEFHDFGFGEFGEGGEHEHHAHFEHCAAEAFCHDCFFFGABAFEAGGBGHCHDFHDAAGAFCADGADHAGHBGBBEEEGEEFAEFAEFCGDCFDHGDH,False +73,24.0,24.0,23.0,19.0,22.0,18.0,26.0,30.0,HGFHGHHBBHDBAGCEDEHDHCDAAGCBCCHCCDGGHAGHGHHFAEFGEGBEBFDFAEAHBBHBDCBDCBCCDECHHFHDDHCGAAAAEAEEDBGDBGCFACGAHGDFGCGHABBACBAHGHHBHGBEDDACFACFEBFGHCAEBGEBGEDGEDHEFFECEEAEFGGHHFBBFCHFBAFGAEHACD,False +74,26.0,17.0,19.0,17.0,28.0,19.0,13.0,23.0,EGCAHEHHEHABADBADECBECEEABEACFACACFFBFGBFBDFCFCCACAHEBHEGHDBHBBAFEADEHBCHEEHEGBFGBFDCGDEFDEADEDHEAAFFEFFHHFACDCCEAHDADDEEEFAFGADBHEBEAGAGDAHBCHCGHCAHGACGEEFAHGHHD,False +75,3.0,1.0,2.0,0.0,2.0,1.0,0.0,4.0,EAHBCHCAHEAHF,True +76,10.0,5.0,4.0,6.0,10.0,5.0,10.0,8.0,HGHHAEEAEDAECGDCAHGFBGAGEFGFBEFAFCGCEAEEBGEBGDDHDBHDAHGAHA,False +77,6.0,2.0,4.0,1.0,4.0,1.0,1.0,0.0,AACCDECAEBAEBAGFECA,True +78,26.0,21.0,24.0,22.0,21.0,23.0,16.0,22.0,AEAFDAFGAFHAHCGFCGFHDCBDCBABADBCDGGFGHEBBDFBFFDCDEAEEGGFHAHDCDDBGEHCEFCHFGEFDADGFHFBDFCCCBCGBCABDFHAEBCHBCHBCDECEGFFAHFAHFCHFDDCAEHAGHBGHBAEECDDDDAABAHECHEBHEAHABGEBAEACEACEAF,False +79,23.0,23.0,29.0,21.0,13.0,23.0,22.0,17.0,CDHBACEAHEFDEGHAGAAGFAHFADFCBBBEFBCDGFBCDBDHGGGGCGFBDBBCFBFDEGEEHEGGBGEHFCCFCBDCEDAEABFDHHBFBBCAGDDCHDCHDAHBACAGCAGCADDBDFHAFCAFCGHDEBGHBCHGCHFBEGBFACFCCACAADACFACFCCFGFDG,False +80,12.0,12.0,23.0,9.0,27.0,13.0,18.0,19.0,EGFECEECHEBEEHHFBDCGCAACFBCGEHEEGCEACEGDEADAGBAGBCDBFBHFHACHCDHCDHCECCEGFHGFBABCGDCBDCEACHBCGGAEEAECFEHHAFFEEFHFCEFCHGGGGDHBEHGGHEEHE,False +81,25.0,15.0,14.0,17.0,20.0,16.0,15.0,15.0,DGDFFBFFCAFHADGAEEAFDABDEGGEBGDGEDEBAHAAEGABAHCACEACAHBAGGECFCDDEDBEFHEBGAFCAFCAHDEHDAFAGFCDBCHCCHCEDBGFGHBADBHGBEAAHAAHAEFECFEDFEDHEBHGB,False +82,23.0,16.0,15.0,28.0,9.0,16.0,15.0,26.0,FAHGHHFHGDHGDHDHCCHFBHEDGDGADGBDFDHFBBEDBADEDDBDHFDACDBFGBFAHCDDDGDBGBBGAAADCHFCHCDGABFHDDHDAEDCEDCGDFEAAEACHHGHDGCFFCHABHAHHAFCFHAAHAACBABBHFEAGEAC,False +83,16.0,17.0,21.0,14.0,11.0,17.0,24.0,19.0,EGHCBBCBBHFAHAAGAFGHBCDFAGFBDABDADEEDBCDBCHBCBGEGFFGFGGCHGCGGHHADHDHCDHAFGACCEHDGHFFCDFEDAHDFFAFFHEGBDGCGCBECECHBGHGGHCGBCHBCEGFGGFCACAABAE,False +84,25.0,24.0,34.0,20.0,21.0,23.0,18.0,22.0,GCCGAFHHFBGFBCFBDFBGFCGDEGCAHEBCAFCBFHEFEDCGFCAFCHCHBCHEAHAFBAFDAHBHBDGAABAFBACACHHCFDAFDGBAHBEBBEDFCFECAEBGFHECCCCCCHHEEHAAFDGFDHBDGBEFBEDDHDDEBHECCECCEBAEBAGACGEDGADCBCCGGCDEAGCADCAFHHD,False +85,14.0,17.0,15.0,14.0,15.0,14.0,16.0,10.0,GGCGDDEBFFHGFBGFBHFHHEDAACAABGFFFCDBGBEHBEDBFDBCDCDGCDEFBCHBEGBEGBEFHGFBAEBCEFAAGGCHCCFCCBCHEHEAACADDEDDAGDAGEAEBAG,False +86,5.0,2.0,1.0,1.0,1.0,1.0,3.0,1.0,ADFAGGAHGBEABCA,True +87,28.0,33.0,23.0,19.0,20.0,25.0,30.0,22.0,FFGDBGHBGEGAADDHGEEDEHBBACDFCGFCGEHFBBFHBFBCCGCCFHDFCGHBECBAAFFDBBCBECGGFEGECCAGABBABHAEHBBHBHDEFDCHDBAFFDDFAAHAAHCDFCAHEAHGAHFAHAGHAGAAGEEDFGBEBECBGCBAFBGCCGAFAAFHAGGFGGBGGBDEEGEGBFGBFHBCHBDDBDDBECCA,False +88,27.0,30.0,28.0,20.0,23.0,12.0,23.0,29.0,EGBCBBCEBCHHGDBECBCDBEDGEHGAGACGEHGCDACFECFCBHBBFDAHCACBACBEFGGAGGADAAEBAHDFHDCDBAHCHHBHABGCBEEDHGHHGFHAHDAEDABDGCDECDBADBHHGHHGFGECBEABDHFDGAHEACFGCAGCABCHBFECHCBFCBFAEABDAGEHEEAECABDHBHHCEBG,False +89,14.0,15.0,7.0,17.0,10.0,11.0,15.0,9.0,CHBADFABGHBGFGGAGGADGDEBHADHGHGFDFDDCDBGAAGHAGFAEEBBEDBEBCEBFAFDAFDFGDEADEGDFACCCGBHBBHABHDEDCBDFE,False +90,5.0,3.0,3.0,1.0,8.0,0.0,6.0,3.0,CCACEGHEGDEGBBAHEHGBAGEAEEAEG,True +91,0.0,0.0,4.0,2.0,4.0,2.0,2.0,1.0,GDCFDCEECGEHFEC,True +92,14.0,4.0,7.0,10.0,8.0,6.0,12.0,5.0,DCDAEFAFCECEEAFEDFEGCCGACBDGHFAHBGEBGAGGAGGDGAEGHHGAADAFDADDCBAHDA,False +93,10.0,8.0,8.0,3.0,8.0,14.0,16.0,15.0,FAGFDGHDHHEHEEGGFFACFHEHACCACHFGHFGHCGCAGCGBCFFEGFGBHABHFDHGBGBHABHAFFAGFEHEEBBAGG,True +94,21.0,25.0,21.0,30.0,27.0,13.0,12.0,17.0,HHBEBCAACEABDGDGBDFBGFCAEHGDCADCHDCEDFEDCEDGDCEDAEGEHAADBBDAADHCDHDFHBEEBEEBCEGAECDEBBCGAHEBBFFHEBHEHDAHDAECFFDFEDFBDABDCCACEDEBDHDDAGFAEABECBHGFDDFEDCCBHCBHGBEGBACBA,False +95,4.0,6.0,6.0,8.0,7.0,6.0,6.0,9.0,EDGEBHEFHACBBCFEGHCHDAHDEHDBHDBDDEHFCGECGFGBFACFAHGD,False +96,8.0,5.0,5.0,6.0,5.0,8.0,12.0,12.0,AFACCAGAGGFBEHEGHECFDFFDGFHGAHGHHFDGAGCAGEFGHBBHEBHDDHDHHGCBA,False +97,20.0,25.0,21.0,20.0,27.0,26.0,25.0,26.0,BFCFGDFBECHDCEBGEFGBABHGDDGAFBEBCEFEEFGDAHFBHEHHCHDDHGEFDFFBGBBAEGCCFDDABEBBEBFHBHHBCCECEDCAFCGFGHFCBGHBEAFCBFDEEAEEAFECEBBGGAGHBDHFHHFHHFHHFHHEEHGCDABGABGACGAFGAGGDDEDDCADCFGAFGDCAHEAHEAEGC,False +98,4.0,3.0,1.0,1.0,6.0,1.0,5.0,3.0,BBAHAEDECGEAGBAGEEGHEGHF,True +99,21.0,17.0,15.0,21.0,17.0,23.0,10.0,21.0,AHDDHEDGFFGCFHDHAGHGHHDDFADFABHDBCCACAAHGDDFDDFGBHEBHBHEEHEFCFFBBDDBAABCEEHDACDHCEEAAEBHBFABFABCABFFFFDFFDFEEFCEHCEBDEBFCAGAGGDGCHBCHAAHEFFECAADH,False +100,21.0,17.0,13.0,22.0,21.0,22.0,21.0,31.0,GCAADDGBDEBDABDGDGGEADEDDFHHHEHDGHFGHFDHGAFAHEHDCHDHFEBGEACDACGABGABGFGGDGBHEEHEFFGHFABDHEDAECBFHAGHAHBAEAAEAFEHFEBGGBCFDFEEAHCHHCFDAFDCFDBFHBAHCHHFFGEHDECCGCBHFHHFBHBE,False +101,3.0,4.0,2.0,2.0,2.0,1.0,2.0,2.0,BCFBEABEABHADGCHGD,False +102,3.0,5.0,4.0,4.0,2.0,1.0,3.0,10.0,BGHBGHCCHCDHEHHABDFHDBHEGCDAHBAH,True +103,22.0,16.0,17.0,17.0,11.0,10.0,13.0,12.0,DECDFCDFEDCCBCCBCADGAGFAEAAHHCGECAAFHAHBAGEFDEFHHGGFBFCBACBABDACDAHDAGDGBDBADHFDBCEHGEHGDHABGBCEDEEHBAABADCGGCFCABDABA,False +104,12.0,15.0,10.0,16.0,25.0,15.0,20.0,17.0,GBFDCFDGDDBHDAADEBGBDEBEEFGHFGHFGHCGHEGDEADHBDHGGBGHEDCFHAAHACHGGEGGEFEBFGADCCEBHEGFEHDEHEEFAGDCHFEEAEEBCEGEDBEDBECBFFBHHCAFAEGAFB,False +105,7.0,10.0,8.0,8.0,6.0,8.0,6.0,10.0,HBEHAGHFGHBGDBAAGCDEHFEBEHBEBCABAACDFHBCHDFGDFGDFHCHCCACBFDBEDF,False +106,17.0,20.0,9.0,15.0,13.0,17.0,14.0,15.0,FBEAGDAGAABAHBGEFFBFFEDHEGHEGHEFHFDBBCBBDBCHCAHGAHCHBEGFDGFAEBAEGADCAHBDFBDFDFBABHEFGBCDAFDBCAGCFBHFBAFAEDHEDCEDHBDGGHGA,False +107,5.0,5.0,1.0,5.0,1.0,5.0,5.0,2.0,FABAAGDGFDFHBFEBAGBAGBFDDHGDC,True +108,17.0,16.0,20.0,15.0,16.0,19.0,21.0,30.0,CBHCHHDDDGADGAFCEHEBHEFEAAEBHFHCBGFAEDHEFEFFCFFAHEHHAHBGCDCHFGHBGFCGFBEABFBHHGHHGCHEAHEADABGHBHHBDHGDHGAGGBGGEFCFFCDBGDFDAECEECGCAGCGDCFDFHHAHHDHBBCCACGAC,False +109,19.0,26.0,19.0,10.0,27.0,23.0,8.0,14.0,EBCAAAGFADFADFEFBBBCBEABEABEAEEHEEHEECEBGACCAFCBHCDCCECFBCAGGAFEAFEFBHHBDFAHEHFEGFHCFBBHCCABCHFFBFFBDGCEGEBAEGCFFEEDHFFBFBADBDBBDBBEHEEFCHACBAHDEE,False +110,19.0,10.0,10.0,17.0,15.0,14.0,13.0,9.0,EACEADEDDGDAEBCFACEAEBFHFFGDFEDBBGBHGCADCFBBBHCAHEAHFAHAAHCDGCDGAEGAEGEDDFGEAEBAGFCGDGDDABDFCDFGFFAAEDFEHAH,False +111,6.0,10.0,13.0,9.0,4.0,7.0,3.0,10.0,CCCAFBAFBEHDFBCCBCHBCBCGHDAHDAGDCDFCHCEHDAFDFHDHHDEEBFBAGBCHBC,True +112,14.0,15.0,18.0,9.0,20.0,11.0,10.0,7.0,DEFDEFBEACFGEFCACCBGGBHAAEBEHCEGGEDEEFEEDBECBABGADFADFADGCHCCHCHACEDHEGAFAEFBFBAEACCAEBBGBBGEBEBHCCDCCFC,False +113,18.0,25.0,13.0,24.0,29.0,22.0,19.0,30.0,HCAHEABDACHBBDDHADBEHEEHCABCFBHFBABBABDHBEHFGAFGFHCHGCAEFHEFHGHCGCEHDDFEBFEFFDDHDEEDGEFCBGBDGAHHCHDCFDEEDGCFHHFEEFGBGGEEHBFAGFDHBEGFEDCEDEBDEFHEAHEAHABBEDBGFBGEHGAHFADBADHADHEDBGGB,False +114,13.0,9.0,15.0,32.0,17.0,18.0,11.0,14.0,HDHDDAGGFDDFHBFBCAEDGEDCEACDDEEDFHFAGFDECDCCDFADECFECHDCHDGAGAHGHDFEDCEDCEHBHDAHDCFDBFHHGDBDAFCGFAHFDCCDAEDGEDEEFADFAGFBBDEBDEBDF,False +115,21.0,18.0,26.0,25.0,21.0,27.0,25.0,34.0,AACCECDFFBBDABHAGHGFHGHAFHBFHFEHCBHFDAGHAGEDBEACHDCAGCDCCDBEDBDDEGGEHGAHFAHDBFGHFGCDCCFCBFCBHCHHFFDFGEEEDHFHHFHDFEDFDCBHAGAAGHBEEDCFFCHEDAEBAGDEGDEDBFBGCBECHCGHCDAGGAHGHCGHCFHBFHCFHDADAEGEGHCGAFFEH,False +116,25.0,15.0,25.0,18.0,19.0,11.0,22.0,30.0,BGGBGDHGBAECHEFABDHBHHBHDADBEEGFGGDGCCGFCHHHAHAFHBFEEGEAHCGEAGDCCHCGDAGBAGBAEADBADHADFCGHEDHCABCHHEHDFHFAHEAHCHCAHBDHBGHFGEFCAGCHGAAACAACHHDHCCGECEDDFCDACDACBCCEEGEE,False +117,28.0,24.0,15.0,28.0,23.0,30.0,14.0,19.0,CHACHAGEBEFDCFAGFADDEDDBDGBDBFEBEDHHDGDECDEBFABFAFFABAAHHAHHDFHFBHDBEDADCBGHEDFFDEDDEBEBAGADDFFFBDFBFFBFFBHACFDBFDFAEBACBACGEGGCFAFEHEAHECHBDGGFCAECFEFHEHHAGACBDCBAHAAEAAEDECDAFGGFB,False +118,0.0,3.0,1.0,0.0,4.0,1.0,0.0,2.0,FHBBEEBEECH,True +119,15.0,14.0,10.0,15.0,7.0,12.0,18.0,9.0,BGDBGBFEBDCFAFFADCGGAGDABAAHHAHHACEBCDDCBDAGDGBBGDGDDACEFCFFCGFHGBEFCGACHAGAGHAGDABBEEFHGFBFDBEDGHDG,False +120,18.0,23.0,21.0,12.0,21.0,14.0,26.0,15.0,GBBHAAEBAEHEEFEGFGCAECABAGCADBEFAAGDABCAGGFGGCHGCHGAHEAHFFCEHCEBBFBBEHBCGECGACGDCGDHGCGGHGGDDGHACBBGDBDECDCFABECFEBFECEBGBBEDDEGFCDFEGBHGBHAHFACEBCHBF,False +121,18.0,17.0,15.0,11.0,14.0,12.0,17.0,17.0,AGGAFDDFCDBBHECHBCHADHCBACFACDDGFACEBCBBGBHAAHEAEEHGFGCFGBHEBAFHAHHADHBEGBHHCEFEEFGHFGFGCBDCADGBDHHEBEBBAADAAFCAGCGGEGGEC,False +122,19.0,12.0,14.0,16.0,13.0,13.0,22.0,12.0,DFAEFDEBHGFEEDAEDFGGCGGFGGFGGAGGAFFDEAGEAGDBBABDHHCHHBDHBDGCGGDHDAGCACCBFCBABHEFHCCHECBCGDDAHDCEEFACFBCAGDAGAAGAEFAGDBEHA,False +123,3.0,8.0,5.0,11.0,9.0,10.0,4.0,11.0,EBFFHHFADFCHFGHEGHFGFACDEDDEGHFAEDHBDEBDECDCDDFHBFEBHHBCEBHDB,True +124,4.0,5.0,6.0,11.0,9.0,6.0,5.0,8.0,ACEACEADEDEHDCFFCDCCEHHEHEBHGBDGHDFDFEGFEDBHDHDBBGFAGD,False +125,11.0,14.0,19.0,12.0,21.0,14.0,17.0,9.0,CCDCBDBEDHEGHAFEECDGCFGCEGCBGEFAEDACCHCDHGFEFFBBEABEAHHAFCCFBFFCFCBEGDACDGCAEBAEGGEDGEDCAGGEDHEBHBBACBHGFEGEGDEGEFCBF,False +126,7.0,15.0,16.0,15.0,17.0,19.0,21.0,17.0,CHHHDBCCEFEEBEGBHFEDGEBFFBGFGHHGHHGEHDHCDHCDFAFFDCABAFBHGBCGBFHBDHCEGAGGHHGDEAFECHDBFGBDBCDECGEFEEBECBDFFDECGGCGADGEDGFGCFGCFAF,False +127,1.0,2.0,2.0,2.0,3.0,3.0,7.0,2.0,BEGGGGACFHCFHEFDGGDEGB,True +128,24.0,27.0,28.0,25.0,25.0,12.0,31.0,20.0,GGGBGGBDBCDHGACGEHDCHDCBDCHHEHBGHADDADDEBGGHGDDEADFAHFAGGEGEEABEHDEHCEBAEBECBACBACGACGADFADBBBBFCCAEGHFBEBCAAHBCHFCEFCDFCDCCBAEGEGCAGCGCCGEHFEHGCCACAACBDDBHGBEBDAFGEFGBBGHHEDGDABCGFHDEGGEDEADB,False +129,8.0,19.0,18.0,15.0,11.0,19.0,15.0,9.0,BEEBFHGAACFBCEBFHFADFCDHCDBCGBGGEGBDAADFDCHECHECEGCFGCFGFBCFGCAGDFGFFHHBDDFCDFBBEDBFDGDBBFBHABCEBCDAEGCBFHBFCGECGD,False +130,19.0,16.0,11.0,13.0,12.0,17.0,19.0,19.0,AGFEGFGGEGDAFDBFDBCGACBHEHHAHHDFADABHAGHBFHDFCDCADEEFEGBDGBEGADBAHFGBDGBAEFAGFBCAECHGBGFBGBBFBHAHHAHDEGEFAHADCACCHCEHGAHFHGFCF,False +131,4.0,4.0,2.0,0.0,2.0,2.0,3.0,2.0,FBECAGHAHCAGBAGBEFB,True +132,21.0,22.0,26.0,22.0,19.0,22.0,19.0,31.0,HHACHAGHDFHCACFECAECGDFFDFCAACEBEDHHAHDCGBCBBCAHCAFCDBGFGDCHBHECHCFACFGCHECBBCFBGHDGHEGHDGFBAADFGBGGFCGHCBHAGHFEEEDAEDAHHABFABHAHHGHBFDAFDGDDFEDGBDFEDHDDHCEHEAHECEECEADBGCBFFHCFBBBBH,False +133,16.0,18.0,20.0,18.0,16.0,13.0,27.0,16.0,DGGBCEDCEFHDGHFBDCHFHHBACBADAAHADEACBGHFGEDGCBCABGAGFCGDCGDGBEGBEGBECEEHGEHGHHDAAGGACBDGBGCBACDEBDBGCFHFEHCEGCEAEFCHFABFEGGCDHFDCDDCDBFGBFGAGHAG,False +134,19.0,21.0,15.0,10.0,12.0,12.0,10.0,11.0,DAGDAGAAHHFHABCBBCEBCFBCGDCGEEACACBACEAFGBDAAFEAFEHBBBFECDEADGFFACGECBBCBBGEBFEBDAACHADHFEFBCHBFGBHDBCGBHADHAH,False +135,13.0,9.0,13.0,6.0,13.0,9.0,17.0,10.0,ACEEHFBHFBGFCHABEADHHCGACGDHBCABEGBEDBGGCGHHAHCEDAEFAEGCEACEAGGFCGCDGBFGAFGAFBEGCEGAFGECHD,False +136,12.0,12.0,9.0,6.0,6.0,6.0,7.0,12.0,DGFDCFBCHHHHHHHBHBBABEAFGBEGCFDFGCCBDABAAEAAHACCAGHADEACGHGEBEFBCDBHAB,False +137,8.0,7.0,7.0,10.0,12.0,16.0,11.0,8.0,EEHEGHGAHFFEFEDBGDBEBBGGFGDCGFCFCGFDDFHDFHAFCFDGAAFFAEHAEDFEGFEDCEGAEFBHBCDBCHA,False +138,16.0,20.0,15.0,26.0,16.0,10.0,21.0,11.0,BCEFDBCDBAHBEFBCAHCAEBDCCDHGHHCHDDDEGBFDFGCACAEEDGADGEDBEGCEHCHBGHBEDDADDGBDGBCGBDHCFGCGGFGGAAEAADAEDGEDBEBADDADGCDGBAGBDGBHGFFBEDAEFBF,False +139,13.0,8.0,3.0,6.0,6.0,4.0,5.0,4.0,EDGABAADGAECAGAAGAACHFFHABGFBABBEDBEHBAHCABDFDEED,True +140,3.0,7.0,9.0,8.0,11.0,8.0,12.0,4.0,FGFCGCCEEDFEBFEBDACHADEBCEDFBDEHEFBEHCEDCGGBGFBEFCGGDGHDGCGGAG,False +141,7.0,6.0,3.0,11.0,10.0,4.0,8.0,7.0,EEAAECEEGHEHDFDCHCGHEAAEHBDFBDBGDBADBEHFEAFGGDHDDGBDGADG,False +142,25.0,23.0,17.0,19.0,29.0,25.0,18.0,29.0,EEBEEBHHHHBCHEFDGCDECDEDBEFHAFGBFBHFBHFCHFEDFBBFEAEGBCBAAAADAHEEFAEFDFACHHCHBEHBHHDGECFEFBEGHEGHAFHCDBCAGHEGHGDHGEGGFAAFAHEEHBFABDACHABDCDAFGFFGCFECFHBFEEDDGDBFCAHAEDDEACEAGDBGAAGAHCBHB,False +143,1.0,2.0,2.0,3.0,4.0,5.0,2.0,3.0,CFDCBDHGEEGAEDFEFFBHFH,True +144,9.0,4.0,7.0,5.0,3.0,7.0,3.0,7.0,EFAFABHACHECHGCBADBADAADGCFFAHGHDFHDCHFCBECAF,False +145,21.0,27.0,26.0,22.0,15.0,22.0,16.0,17.0,FCDFDDECEHCFGCEGDABBGHCGBBFABAEFEEFACHBGFEABEDBHCCFGAFEEFHAFECFHCEBCDBCBAHFAHFCFFCFFBFAGGAECDCCBBDDCDDCABBAGGAGBAGHCHECDACBAFHECGBGGBAGBHBACCADDDDCHHHFHHBDDBDDBDBADBF,False +146,23.0,23.0,27.0,18.0,23.0,27.0,25.0,28.0,DEGHEGFDBFGHDEACECDFDDFDBBBGCEAFHFFHFEBGEBDEBFBBFHFFEFCGFCGCHGAHBCFGAAECGEGDDGCHGAHAAHAADDADCAFBFFBHBHEGCAHCHHBEACCBBABBDBHCBDFAHAEBCEGEGCBHEHFAGCAFCACEFHEFADBCGGCGHAGHGEHEFHCAHCGHDGHCEHCEFCGFDF,False +147,19.0,22.0,21.0,22.0,15.0,18.0,18.0,18.0,ADDADEFBADAHFBBFBBCHGCGBCBHEDCCDHDDACGEGBEACEBCGCFABFHEAHFGDCDDCGFCGHEHHEHBFHDFBFFBAFAABAADACDFCEFHADGADCCECDBHDBCGBAEBAHDHHDHACFCGFGEFHEGGCGEFGBDGBGBBDE,False +148,23.0,18.0,18.0,17.0,20.0,20.0,23.0,19.0,GHBGCBDAFDAFHCBEFGACAECHHGEGFEGDEDDBCAAGFAGCGECAEFBEACEHGEHAEAFEAFBCGCCFCBBGHBAFBFCBFAEHBEHBEGAACFABGEDGHAGBCGCEBDGDDHEAHCADFFGHAHDGHDGHDGBDABHAEDDFHDFCFFHGFE,False +149,11.0,9.0,14.0,14.0,12.0,13.0,8.0,11.0,CCFCGFCDFHHHGGHEDDFHDFEEGCEAHAHCADFEBBBCBFCAHBAHEACDDCDACDADDBDDBEGBDFFCEHEFBEFEAGEGFCGFCAHA,False +150,20.0,17.0,22.0,21.0,18.0,23.0,27.0,26.0,FDDHHBGAEAABAAFAHBGFFHEHCEBEBBEDBGDCGHCGHCFFEGFEDFCDACDAEBFEDAEDHHHFGHGDHGAEFCFGBEDAADCCGFGGAAGCHCDDBDCGGFGGFGGFHGFBGBCGECHFHHACHABDFHDHCAEBBEBGCCFHEHGFHFEHFEHBCACCACGAGHDDDD,False +151,25.0,32.0,23.0,18.0,29.0,30.0,21.0,16.0,CHFAFBDBCEHGEHEEFEACEFCFHHFCAGAEGBCABCAECHDDFDFFEFFGHABFFEHBBDBGABGACGACEDCGDEBDEBCEBFDCHBADBFDAADEFBFHGAACAACHDEADHCBGCAFBFFBFFBEBBGBEEBHDBFDGDAGFEGCABEEBEHBGHBGFBGBAGFGCEGCACFDGAEBEEFCEFAFHBCE,False +152,2.0,5.0,8.0,6.0,3.0,7.0,7.0,3.0,ECBDCEGFFGHCGCGGFBDFDDADDHEBFCBCCBFCGFGAH,True +153,20.0,20.0,31.0,26.0,22.0,23.0,14.0,22.0,GBGFBFFBHCBHCBHGBEFCGFHHHHEHDCHCCDGCFFCDDHFDEDGEGCHHADHCEECFECHECDGCDGADCAGAAHEDHCFBEFEDCHFFAADEADHADCGBCFBCFEEEEBGBCCCCBCDBDHBAHDABCAGCBCFBEHDEBDCFDHFEFDAACAEDADAFGEFABFDCEDAFAB,False +154,14.0,22.0,13.0,6.0,19.0,16.0,15.0,9.0,EEBFEFCBFDAAGAHBCCBGCEEAEEAEEAEEAEGGFHBCHBCBCHBCFACFGDECBAGFFDBHBBHGGFAGBGCBEHGADBFBBGGAFCAFCEGBEGBEFBDFBHEHEFDAFB,False +155,13.0,9.0,8.0,9.0,16.0,11.0,16.0,26.0,HGHDBHECHGCDGAEGFEHDEGGHHFBHFGHBGBEFEAHEAHBFHFDHADHBCHEAHEAHDGHDHHEFFACDCEBFGGEGAEHEGHEGCCGFHGAAAHAFHAHDEBBC,False +156,21.0,23.0,28.0,17.0,32.0,20.0,26.0,33.0,AGBGFFGFGGCEFCBFGBECECGECBECAGHDHEDHCBHEEAEEBFGGHEEHAGFFGFHHCCHADABEGBHGCHGCFBHEHHEHHGFHFFHEFAEHADCEDCHAADBADHEDAFHEDDCCDCFEHBHGGHEFHEBHEBHGBCGCADAAHACBDFBGCBECBCCEHEADEGEEAFCDBHGBCGBCDFAGEAEHAHDCBBCG,False +157,3.0,5.0,10.0,12.0,6.0,7.0,9.0,8.0,CDDCFDCHDGGFGDBGDHFHHEGCCHDCADCAGBFHEGEEGCEDEFDBFDHAHGCBFCBD,False +158,27.0,19.0,22.0,22.0,21.0,22.0,30.0,32.0,AEAADDGDGHBHDGHBGHBHHBCHCAHCABEEBDBDHGFHGHHGBBAHAGFGBAGAGGAGHHCFFBHHGDHAACAGCAHDADGAFHCCHGHHCHGCFGEEDEDBECGAFEDFEDBEGBCACHFCDFGDCDCCBGCFGDFGHFAAEDHFBHFGFFEAEEHEDBECFEABGAFEEEAFDCFDAFDBCGHCGHAEHAG,False +159,6.0,10.0,10.0,5.0,6.0,6.0,5.0,10.0,HCEECDECAFABHBBFADFCGACGABHFEHCBBCBBHFHCDCEDCHGGHEGHFBHABD,False +160,18.0,20.0,20.0,17.0,21.0,19.0,20.0,20.0,FEDBECCGDCDBGDBGDGGDCDFCAHCEHAGAABACFCFFCAACHADAACEGEEGBFBHEHHBGHBACGFDFCHFCHEAEBBEDFFGCFGBEBBEHDDHABGEEEEFABHABHGEHGEHGEHBFDFDHGDHGBEGBECCFCAFHFGCCDAFAHDB,False +161,12.0,21.0,28.0,20.0,19.0,21.0,30.0,23.0,BEBCAAFGAFGBFGEEEFCCHCGHFGHGDDCCHBCGACGEHGHCEHCFCBHCBHDAHDHHDCHEABGHFGBGGCGHCGCEGFDGDDEFGEAHBGEADDCFDGBDGDCFECFCGFCHEGAFCDFCDGDFFEHFBHFCCBECHEBHCBFDBFBBGBDAEDGECGBHEBDABGGGAH,False +162,21.0,14.0,18.0,20.0,18.0,17.0,19.0,20.0,GHBEAFEGBGGHDEEDEABEBBEFECFCCABAAEAAEACBAFBHFHHAEDBCDECDAFBAFBAGEHEHGDAAHGAEDCCDHDDHGAHAFCCECAFCHHCHEGBCDCCBFFEFFGBFDDDDDGGCGDAFDGCGFHHDHHDHGFHGAGG,False +163,7.0,8.0,10.0,9.0,10.0,6.0,9.0,12.0,FBCCDDCAHADHEHHAGCGGHECHECHGBFABFADFGDHBDHDDCDHCEBFHGECEEAEFHECEBGBGGBA,False +164,2.0,1.0,4.0,3.0,2.0,6.0,3.0,7.0,CHCFEGFCGHHEABGAHDFHDFHCFHFD,True +165,27.0,21.0,24.0,26.0,31.0,11.0,22.0,21.0,CAADGACHHEAHDFHCAHCFBCFBEBHGCEFCHCGECDEABEACDDGHDAFCCDCADCAGBDGBEGBCDEHAHHAEFBEGDEFCEABBDBGAHAACAAEACBFBBFGEEHEBDEGDEGDCCDCABHEEEGCDGCDGHEGEEGEHDEGDHDAEFEGBDGADHFDGCDGBAAAAHHEEHDEBABB,False +166,7.0,16.0,7.0,13.0,4.0,10.0,9.0,15.0,BDDEDDGCAHEFHCFHCBHAGFDBDDBDDGFFBAHAHHFGBBDFBDHACHBCEBFEHHGHHBADBCFBHDGABGHBGFBGC,False +167,15.0,15.0,9.0,10.0,9.0,15.0,18.0,14.0,GGABCADCGHHGEHBDHCDHDEGGGFGGAGAABECBCFBEABEBEGAACBBFEAFBHFBHFBGFCAFGHFGHDGCBCEHFFGBFEDFBDAHHAHHGFDDAGDAFA,False +168,21.0,14.0,14.0,15.0,25.0,21.0,7.0,17.0,FDABDAHCHHFDACBGCBGCHFAACGEEBCBFABAEEAEEAFEADDHFAHFEHAHHCEHEFDGFEHFEGFDFHCCAEAAEADBHCFHEBBCFACFDEADFAECAEBBEDBEGFDAFEFDHFDHFEEBCEBGEHD,False +169,11.0,25.0,11.0,15.0,12.0,14.0,16.0,19.0,CDFBBCHGCEBDBACBDCGHFHHFHDFHBEGBEDBFDAFCAHBACFAGGAGEAGBAGBHBBDEBHGHHGHFEABDHFCBECBFDFEGHDFHBFHAEHECHBHBGDBGBCEBABDEGDGGDFDB,False +170,11.0,10.0,15.0,10.0,14.0,10.0,14.0,13.0,EEGCEHAGADCDEADGBDBHDFGDHCDFCDHBAEAHEHCGFCGFCEFDHGHHGHFGCAACHACHAEGEBDCFGCFBBFBBEEBGACGFHEECEBCGA,False +171,15.0,14.0,17.0,21.0,14.0,11.0,20.0,12.0,CBGBFHBCEACEAGAACBDBBDCDDCDDAGGAFGFGDHADEDDEFFAFFCBFCBFCFAHDDBGGGEADHHBHBBDEEGEEGCAGCDCCGCEBHHCGGCDBCHHEAHGAEGHEFADGDGEDGDDA,False +172,6.0,4.0,6.0,6.0,3.0,10.0,5.0,4.0,GBFGHFGDEDFCDAGDHCDACBECDECAHAFFAFBCBHAFFGFF,False +173,2.0,0.0,4.0,3.0,0.0,0.0,1.0,0.0,DDGDCCACCA,True +174,3.0,6.0,8.0,12.0,9.0,8.0,4.0,7.0,FGBDDHHDCFABFABCBCCHDEHEFAEFEBFEDDHDBCDECFHCFGEGGEDDCDDHE,False +175,4.0,4.0,3.0,0.0,0.0,0.0,2.0,1.0,GACGABHBBAABCC,True +176,4.0,2.0,4.0,1.0,2.0,1.0,1.0,1.0,HCDACAAEABCFBCEG,True +177,22.0,20.0,10.0,18.0,13.0,13.0,19.0,20.0,CBHCGHGEHEEADBHGAEGFEGFBAEBCFAFEGHCBABFADFDDCHBCHDHAGGADBAHFEEFHBBHBGDDDHDGHGFHAFAAEGBBDAADHGBEGBAGBADBAHCHHADHDGGDFGDFDCABCABCABEFHEGA,False +178,22.0,19.0,25.0,28.0,26.0,27.0,22.0,13.0,CCCCCCCDCAGHEHCGDGHCADEADBADHFDGGGBDACFHCFHDGBDGDAGDCDDBBCEBFBAABDCDDEDFEFEECDEBAFBDDBFEHEEAEFGEFGEAGBFFBFFBCFCFDGHEFCAFCAHEEGEEBEAHDGEFBFHDFEDCDHCDACGGBGCAGDAFAAFEAFHDFEGECBBGFAEFAG,False +179,3.0,7.0,11.0,8.0,19.0,13.0,15.0,4.0,BEEBAEFHEBGCBCEBFHFDECDCGHGFEGEEBECGFCGFDGDDGFAFFAEGCEFCEFDECEEGDEGCGGFGEBDHCEGF,True +180,23.0,18.0,16.0,19.0,17.0,9.0,16.0,16.0,DACDHCDECEHCBACDAFDAFABCEDHDGHBCFFABCDDFDDHCAHBAEDABHABDGDFCBECAEAAHGEFABFGBGBHABHCEAEGAEGEHGFHEAAEAHGCEGCHGAEGCBGCDGDEGHHADBAGBEDBDBB,False +181,7.0,4.0,3.0,4.0,1.0,4.0,0.0,2.0,CDDAFABHAECADFHCFABFABDAB,True +182,7.0,17.0,14.0,12.0,11.0,8.0,17.0,16.0,ECEECHEGDCFDCFDCEDBBGBGECGBHGFFGCBHEBHABAGBHFBHDGHBECBEHHGCGCCGCFGHABADDDHGDHEBHBCGGFFACHAEADBHDGHBGDB,False +183,18.0,19.0,14.0,22.0,20.0,25.0,20.0,18.0,FBAHCEHGHHGAEDEDDHDHGFACFDBFGCCBHGHHGBHGECBHFDEFBEBHECHFGDFHDEHAGGEGDBGAADFADAADGADGHFFEGCABDGFDBDECDFAFAEFCEFCADGFDFFBFFBHFCECGEBGEBHEADBBDFBCFDCFAAEGBEABE,False +184,9.0,17.0,14.0,14.0,12.0,19.0,15.0,10.0,DBDDHCBBBBGGFEBFEAFGCFDCADCDFEFGHFDHBDCECCFDCAEBEDHFDCBDGBACACGECFEHDBACBFFBFFGGDEGHHGCHFBHFBEFAEAABGFBGEGGFGH,False +185,5.0,15.0,12.0,28.0,11.0,16.0,11.0,13.0,FBEBDDHEDCEGFGGBGEBDBBHCDGDDHBDHECBDFBDEGHEFHEFEDCDHGDADDABHABDCBDBFDHGDFDCGHCGDCHHGDADDEDDAFDFFHFFECDCBBFFCFFC,False +186,3.0,2.0,0.0,4.0,2.0,3.0,6.0,2.0,EGADGADADBGHFGBDGHFGEF,True +187,7.0,12.0,9.0,16.0,4.0,16.0,12.0,10.0,BDFDFFBBBEBBFCHHCHHFFEGDADDFDFHAFDAFBBGDBGDBDDGCDFFDGDGCBCADGEHGDHCCHACABHAHGCFGFFGEFG,False +188,9.0,14.0,12.0,11.0,9.0,6.0,5.0,4.0,DFBEFDCDCBAFBADEFDEGCEBCGFCECHDBADBADBEEBABGHBACBACBECGACBBCADDHFGHECD,False +189,15.0,22.0,16.0,23.0,11.0,18.0,13.0,25.0,CHGBHDEHBEHDGCDFHFHHCHHGHEDDBGHACHECHBHGDHDCHDEAGEABFAEFACBBDDBDBADACDABFAHDABACBHHDHCAHFFBBDBGAFGFFBBABCGEEFEDCCDCBDBFDBFEFGGFHHFHDCADBDGFCGFH,False +190,23.0,11.0,18.0,25.0,19.0,12.0,19.0,38.0,DEHHAGHADHGCHACEDCAGEGFDADHADHDDGEEEEHFHGCAGEDDFHHEHHDHDGBDADHECEEGAFHDBHGBHGBDAHAEHABHBBFDDCDAHHGHHEHFGHCHDDECBFCADCGDCGHCGHGAHGABFHFHHFHHEHHBBAEDAEDFCCECAAGACCACAF,False +191,5.0,6.0,1.0,7.0,12.0,13.0,5.0,13.0,HEEFEHAEHFFHFGDFEDGEGAFGFHGEHDBHAFHFFEAHEBEBDFADBHHHEHBECFDBFD,True +192,14.0,9.0,19.0,16.0,17.0,13.0,14.0,12.0,FBCCBDDFFDHDDHGEFGEFGFHGFBDFCEEHACCAEEDBFDEDCHFCBAEFCGGAHFADGAHEHHAHBACBCEDEEDCCDCGACGCCGCEGDECAECAFGABGBHGDDEAEHA,False +193,13.0,11.0,10.0,13.0,18.0,18.0,16.0,24.0,BFHBGDBGHEFHEGEEGAAFHDFECFEAHEAHDFHCHHEHFAGEGCCHHEDHEDCCDAGGAGGBDCBDAFHFFAFDAFHGCHGCFGHGHHCHDBHBFFADFEDEBHGGFBADHAEEEHEEBFB,False +194,4.0,3.0,4.0,0.0,0.0,3.0,1.0,3.0,HCHBAHBAGFABCAFCFC,True +195,5.0,5.0,1.0,2.0,4.0,4.0,7.0,2.0,EFBGHBGABGADGABHAGDBECGAFGFFEE,True +196,16.0,12.0,12.0,7.0,4.0,7.0,9.0,12.0,ACGACAHFFCEACGGDEADCAGCFHBFBEFDHDBHAAAAGHBBHCBHGBAGBACBDCBHCBACDECHHAGHFHBGADFA,False +197,11.0,6.0,8.0,7.0,7.0,10.0,12.0,14.0,GHFFHACEECGEGGDBGBBFAGFGCHGHDGAEGCCBHCBHAFHAHDAFGAFADCADHAHHBCDFGEAHEHHFDEF,False +198,21.0,16.0,17.0,15.0,22.0,24.0,21.0,20.0,AEFABCDCDABGHHEHDFBBFCAGGAEFCGGCGABGACGHHGDGBDBBCFACBDFHHEHFCHFCECHFCHGEHGBFFECFBHFGHFEDFDCFCEAEEADDGDEGFEGFABFHBFAEHEDDADAAGAACEACBHEBFEDFAAAGGEGGBHEEHFEHF,False +199,3.0,4.0,1.0,2.0,7.0,5.0,9.0,5.0,HFFFEGEEGAHGBHGAHDADCBGGEEGEGBEGBFFH,True +200,27.0,17.0,26.0,18.0,16.0,17.0,15.0,13.0,BDEBEEBCBBCDFCHCCABDEGCGACGACACFGDDGAACBACEEDBDDCCCHCDFAHBGEBCHGGFCGHHHABHBGAEHCBGCDAEDFEFBEAHEAFFGDFHDHHDFDBFEBAAGAAGAGFCBCCEACEACECFAFAAFAADCFDAFDA,False +201,14.0,18.0,22.0,18.0,23.0,25.0,18.0,25.0,EHGEHCBHCHHAEHDEHDEAEBCEBCEGFAHFAHCEHBFHBHHBHEBCFADGHFGCFBAFBDHCHCEHADGBDFBFFBHBGGEFFFDFEBCDFDHCDHBECDEHECBECEFAGFCGCAGEHGEDEFHFCGCCDACAAFDAHDFFDBGDGAFGCBCDFEGFGGE,False +202,6.0,4.0,6.0,6.0,4.0,7.0,2.0,1.0,BADGAEAACFACGEFBACCEFCEFBDHDDFDBFDCF,True +203,4.0,8.0,7.0,5.0,6.0,6.0,6.0,7.0,EHAECAEHBEHBFHBCDBAEFEGGCFGDGHHACBBCGBDHCDFCDFGBF,False +204,6.0,15.0,10.0,9.0,18.0,10.0,16.0,17.0,EHHEDFBDFGDGEDGHFEEDDBGFADFCBHCBHFEEFAECGHHGBCEDCEHFACGHEGHEGCBGHBCHBEFFEHADBAGBGHCHEEBEAGEBGBHGBHCBG,False +205,6.0,8.0,4.0,6.0,11.0,10.0,4.0,7.0,BDFBFFCHFBADBGFCGCCEEAAHFAHFGFEEFBEAHEBDEBDFHDHEGEEBEHDA,False +206,7.0,11.0,7.0,14.0,12.0,11.0,11.0,15.0,DFFHFBABAHBEHBEHDHGCHFDFAGCGHEBADHGDHCEHCEFCEFGFFGHGCDAADGBBGDBGEBFEDHABHDBCDHHEFDEGDEDE,False +207,14.0,19.0,19.0,16.0,15.0,16.0,25.0,15.0,BHBBDBDDGDAHEGEGGECDCCBCDAEBGEDGHDCHFEHACACCEDCGFGFEGDGGAGGAGGHFBEGCEGCEBCAFGHEBHDAEGAFHHCADFBBFBFFDHFCHFBBGBBCBACGFDAFHBCGFCGEDGADEAHFCHBG,False +208,14.0,24.0,23.0,25.0,20.0,23.0,13.0,19.0,CGFHBECCCACGAFFHDFHDAHCCFBDFBCCBGFDAHDABGABGHBFHCDGDDHBHEBCEDEFFEFFEFFCDDGGECDEFDADDHEACEAHEAEEBFBFGBDBBFCBDCFDGFHBBDBCGCDAHDCCDHCEEFEGGECBBABDCBDEFEHHEHHBHBADFA,False +209,5.0,7.0,7.0,12.0,11.0,5.0,6.0,4.0,BEEGAGCAHCFDCAHCEFCAFGGDDEDCBDBEFBEDDADDHDDBBDBEEEGCEGHEF,False +210,21.0,21.0,29.0,26.0,25.0,22.0,25.0,25.0,HGGGCBGCBGFDHCEGCBADBADBDFHCBHDBEBBEHBEFBCABCACCFCEFHAFHGFGDDGDDHHDEDDHCBEDDEDCBGGFAADADGACHAFDBEBEECDECEFGGHECHEFHEBHEDGCDCABCEFGEGHFGHEECDBHDFDFGCAEAGEAHCHFAHDGHACFACGHHGDHGCAAEFAFBCBECGFCFFCA,False +211,25.0,20.0,15.0,18.0,16.0,31.0,22.0,17.0,GDHFDBEDFEFGAHDFFDBECFDAFDBFGBDAEGAEGFDCFDCEACBAFHGHHFBFFBHHEAFBAFDCFBGAGGACBACFCEACEACHHGDHGCGFHGHAGABGBGDFHHFCACEBHEDDAFDAGCADBEGBFGBFEFFEAFGCFBHFEHGABAABAEGAFDFB,False +212,11.0,12.0,15.0,21.0,14.0,13.0,13.0,22.0,FDHBAHAHFDBFDFCHHEFHDFAGBADBADCHDFFDABDHCDHCGAGFHDDHEEHBHHEHBCBGDGCDCDECDEGEBHEHHGHDFBCFDAGCAGCACCEFCDBGEBGEDEFGHCGHEDHEA,False +213,26.0,25.0,22.0,24.0,22.0,21.0,23.0,28.0,DGGABBFFGEFGHFBHBHFAGAHGECGEBAACCADCHDBGDHCDFEDCCCFBFAHDEGGBGECFEABGHDEADGBGGFDEFAABAAHAAHCAHGFHBFABFAEHHCHHCFBEEDEEFEGDEHDHHDHCBEABAGGAFGDFDCBCHBCHBHEBAAGCADCHFCFDBBDBCDECHACHDBEDHEFGADGHDBE,False +214,17.0,18.0,21.0,25.0,26.0,17.0,17.0,17.0,FEFAEAHHABBGBGGCDGDEEDAEBGFHHCADDHDDEDDEAFECGGAGGEBGBACEEDEEDHDDHGBHEBCBHADFEDEGGCDDBDCFCHFEFAHFHDBHDBHAGCFEFFEBEEBEEDGEACFABBCBFDBFHFECGHCGACDCCDCCECFHAACADC,False +215,3.0,8.0,12.0,3.0,11.0,1.0,8.0,8.0,ECHEGGEHEEBCEHGGHBAADGCHBCBBCHBCHBCEDFEGHEDCGCCECEBCGA,True +216,3.0,7.0,2.0,4.0,7.0,5.0,4.0,9.0,EEBACHABHEFDEHHEBHAFHFCHEDGEBBDFBHGBHGFDG,True +217,24.0,19.0,23.0,32.0,19.0,19.0,18.0,19.0,BDFHFFHEAGCGGEHGAHGADAEDAEGACABCBFDEDDEHDGDDEDDGCDGAFBBEBHFBDEADCDDCHBCEAHDBHCBHCACBGCGFCGFCGDHFABCACCABHEEHDGBFFDFFBHADDDCAAHDAEFEEFBDFADGADHADFGDCGCCBECADAHHCFDCGBEFEEDHBA,False +218,15.0,9.0,15.0,14.0,9.0,15.0,10.0,14.0,EDDHBDCEDAHHCDHCDEFECFDDBDEGDCAFCAGCHCFHBFBDFCABCEGEEHHGFHAFCABHABDAFAHBHHGFCGFHGBAAFDAFAAFEDFAGGCCGC,False +219,24.0,26.0,20.0,28.0,17.0,21.0,17.0,23.0,FBGGAGHAGHGGBGGFFDAFDHDCFBFFHFDHDDHFDHFHCFGDHBEFCEACHFEHCBADHDBADCEBCDDAGDAFDAEDEHCAFDAFDFBBAGBGHBCHAFECHDCEBBEABGFHEBHDGCEFCBACBACBCCBHBFGDADAAHAHBGDBDEBGECEDHDAEBAEBAEHADCDBC,False +220,10.0,6.0,12.0,8.0,3.0,8.0,5.0,9.0,DEDDFFBCFCCAGBFHBACAACAHFAHBEGGAGCDCCDFCDFCAHCACDHEHHABGDBHFH,False +221,18.0,20.0,25.0,20.0,16.0,11.0,30.0,25.0,BFFBEGBGFBGHBEFEDHBDCAAHAGHFGDADCBDBBDECAEBAHGHGABBHHBGCGECEECADDDGHDGBBGBCGHHGCHCCHCFHGGHAAHAHGAHGEHGDHBEGFHFAHGADFEGBDHFDGCDGCFGAGCCGACGHEGDCCCABCECGEHDEDDCCECADCB,False +222,19.0,19.0,21.0,28.0,17.0,28.0,23.0,16.0,FFFFGGBAGBFCDFCBFDGDDEDDFDEFCHDCHACAAFFDGFHCFBCDGEGEECCCBBAHHDEHDECFGGGDDGDDGDDCBACBABHCDCFDCEBEGBCHEFHGBHABAGFGFADHAGFAEFHEBBFBEFCGFHAFGADGAFHBCABDEDDCHFEHFEGAEDCGDFADBAG,False +223,23.0,19.0,28.0,13.0,18.0,28.0,23.0,33.0,GHBCHBGHEHEAHDHGDCFBHGCHGCFGCBGBGCDHEFAGHEGAABBHECFCFGDEHCEHAFCADAGDFGDHACBACHACHCHFBEFCFGCHHHHCHBCBEDBFHBEHBAGEACHACFAGGHGDHFFAFEADEAHFAHCCHEFGEFBFCBHDFGFFGAFDACDECECBEBFHBAGCHGCAFFAFF,False +224,3.0,2.0,2.0,3.0,1.0,3.0,0.0,0.0,DAADFBDFBCACFE,True +225,18.0,28.0,26.0,15.0,16.0,22.0,28.0,24.0,CCBGHAGAEGAFGBHGCHGBBBHBBHCBDDBFDFGECEECAGHEBBGBAGBFGCHCCDGCDHEAGCBBFBBFCBGGAGBDGHGGHGHHFHDCEDAFGHBGABHBEAACGCCHCCHBHHFFFFGCFHCFEDACFGEFCAAGDCDDHDBAABFACDABEGCEGFEHFEFCEDBFHBEHF,False +226,0.0,1.0,4.0,5.0,1.0,5.0,5.0,2.0,DBGCFGDHGFCGDHGEFCFDCFD,True +227,9.0,11.0,5.0,9.0,13.0,8.0,7.0,11.0,DGHBGEBGHACBAFHAFHFHDDHCGEAGEDEEBEAGFDFBDFBHFHCDHCEEAFBABBEEBEBDHADHGEEAC,False +228,3.0,5.0,4.0,5.0,8.0,4.0,5.0,8.0,DCEDEHGEHGFCEFGBDHBDCBDHFFHEAHEACGBGHAEHEB,False +229,5.0,2.0,1.0,1.0,0.0,2.0,0.0,0.0,ABABFACFADA,True +230,17.0,15.0,18.0,10.0,25.0,10.0,12.0,11.0,ECCHCABEAEAABAEBGEBCEBGAAGBBDFHDEHDEHCHHCHCEHEEHCGBAFCDEEFGEGGCFDEFBBADBEEFHEAHECGFCDAAAFBBCCCACBGGBAEDDEGDECCEFAEFAEG,False +231,31.0,18.0,29.0,27.0,23.0,14.0,25.0,29.0,DGBAGHGHDGCGACBADBDDEADFCHGDBFEBHEBHEFHFCDFCDACFGHDDDDDCGCEAEEADCBDBGGHCAACAEDACHEHHAHDDFDEHCEHCECEHHEAFEABCGEGABHEDHEFAGCGGCGACDAGDACAAHACBBCDACAACHCDHGAHGFBDAACEACECFEHGGHBGHBCFFGDBGHBEFEHHAHBAG,False +232,9.0,27.0,30.0,27.0,17.0,16.0,18.0,20.0,HDBHDCCCHHCHECBBCGCEDCHCADGDBBEBGEGGFDFDDGDBBFHCEEDFFFHFHHDGCEBCABABDEHDHCDHFDHFDHBDHGGEECBEHBDFDDBCDCCBCCGCAHDBBBBFBEHBEGBEDDGAAHCBECBCCBCFFEDFEDCCGBAGACGDCAFCGFGG,False +233,13.0,14.0,9.0,12.0,10.0,11.0,7.0,12.0,CACBADGHDGHDFHDFHDEEDGEBBEDHACHABBFCFAEHACFDCEAHEABFFBFEAAEBCHDGBDBBGCBFEAFGDCDHHABHABGF,False +234,27.0,12.0,19.0,20.0,14.0,11.0,16.0,19.0,DCEACEBHDGHAGFBGABGABGABCHFEADDADAHDHDGBFAECCBCHHFADFEFAHDAEDCHCHADBFDCGDCHECGAAAAGBAEEHGCCGEAGEFCDFDGGCGACHCEHCEHDEHBCADAADADDFHGAHBAHBAF,False +235,10.0,14.0,16.0,10.0,22.0,13.0,14.0,12.0,BCEFFEFBBGBBGEDGEABFACCDCCDHEGHCBDGHEEEFAGBHGBEEHEEHDEFDEFCECDECHGGAGFFEDGHBECBHCGFEAAEAHGBHGBHEBAFACCEDCACFDCF,False +236,7.0,11.0,9.0,8.0,13.0,11.0,4.0,12.0,AEBEHFHFFGFHBFHFAHBHHBHFEFABBEBAEFCEACHHDGDEGABCCBCEBDEDCEACFHCFDCHDEEDBGDE,False +237,23.0,30.0,14.0,18.0,17.0,26.0,17.0,30.0,DGDDFCEFCGCBBHACAFCEEEEAADADEHFABBADHADHFDBFHHFHDFDAFEADBADCAFAFBEBBEBBCBBCFBEFBGFBHBBFFHFAHABHEFHBFHEGHAAHBAGBGFHAFABEGEGGDCGBHBCHGHFGHGHHCDEFFHCBHBBHGEHGDHFDHCDBDAHGHBEAACFG,False +238,19.0,27.0,27.0,14.0,19.0,23.0,28.0,21.0,CCCACCFBHFGEBABBGFFGBCHBFAAFBAHCAHCBGABGADDABDAFDBCGECFEHBCHGHHGHEGDEBFBBCGBGHBGFBCCBDGDCHACHADFADEHDEHEGADGAFBFGBEGHFHEADFCCGCCGFCEFGHFEFBCDBGHHECGBCFAEBBCDGAGCAGFFEHGEGFEGBECHE,False +239,12.0,6.0,10.0,11.0,16.0,6.0,12.0,10.0,DBDGGDGCDECGHCHEAHGDEFEEFEBBHABCCDACGFEGHECAFAEDAHAGCBGAHGAGFABFDEEDGEHEECEDCEAHDAH,False +240,12.0,11.0,10.0,12.0,15.0,7.0,12.0,8.0,EHCEBGEBCADCDFCEGBEBCEBHDGAAGDGHDCFDEEGBEFEEFGEHGHBEABEAFCFHCGHCBADAADADGAEBBDDHDFGACGA,False +241,24.0,20.0,23.0,18.0,18.0,16.0,33.0,12.0,DCADHACHFFHADCCDEEDCEDCFAAFGBCGACGAGGACHBBDBCCBEFBGCDGHFECABCACGAEFAECBFFFHGCAECAGHEHBFHBAGEFGECGHBABCADDGGDGGDGGCGCFFHGGEAGEGEEBBEGAGFFGDGGBGDBGDCGHAAABGEBEBDDBDAA,False +242,2.0,5.0,2.0,2.0,7.0,2.0,2.0,4.0,EHCHBDECDEGFEAHHABBEBFEBGE,True +243,5.0,8.0,9.0,5.0,11.0,13.0,13.0,9.0,ECEEGBGFFHFBEFHFDBGDBGFHFFHGHCGHEACEABBFEEEEGCGGCFBCDCCEHCDHGAFGABGHFGAFD,False +244,8.0,13.0,8.0,11.0,10.0,14.0,17.0,10.0,EGDHGCEDHEAHFBCGBAABGEDAEDAEGGDDFDCFGCEGCGFADFCFEBBCBFDGFAGFEDFBGFGHBBHEDHGGHBAFBFHCFHGBHGB,False +245,10.0,16.0,19.0,10.0,13.0,11.0,21.0,15.0,BEEBGHAGHCCFEDFGFHBHHDFDDHCFAGFAHABFABGAFAACBECGGGHGCAGCHCEFGEHBEHBGFGEFCHDHHDEBCABDGBGGCGGCBGEBGDCCCCDCBDEBGEBECCH,False +246,9.0,13.0,8.0,9.0,4.0,11.0,15.0,3.0,BDDBDDBAGAEGABGEDFCBCCFCDABHCBGDGGEGCEFAGBAFBGGBGGBDFFAFBCGDHGHFFCFAGFAB,False +247,24.0,29.0,19.0,27.0,21.0,19.0,25.0,36.0,AGGDCEDBEDGADBCBEDBHDFHDBEFHEFEEGEGDEABEFHDBHBHHFFAFBGGHCFFEAFDABEAFCHDCABBBCBEEBFBGAGHBGHCABCAFHDGHCHHCDGADHADGFHGFCGDBHBCHBDAEGHHGHHAHCAHDDBGHBGCEAHGADDHDECGEHHEDEGFEDABHABHABCABDABDACHGCBGDHHFHFFGC,False +248,23.0,15.0,19.0,20.0,20.0,17.0,12.0,20.0,AEDAEDAEFADFAHFAHEEHBBCBBDBCAFAAGCCGACEHEADFHDFCDAHGBEFFEFDAFGACGECEHHGADGBCAFCGCHDDDGCFFDBCHECFEHEABEABDCBHFDHECAFDABDAGEBGHGEHDBADBADCHCHHCFHEEH,False +249,5.0,8.0,8.0,6.0,8.0,12.0,5.0,4.0,DDADDFEDFHACECHGGHCDBBFFBEEBGEBCECCGBEAAGAEBFCFFHFFBFFCF,False +250,9.0,9.0,5.0,9.0,9.0,5.0,9.0,6.0,EBGEGDECAEBBGBFDBACGCBBCBBFDADDACDGEDGHDHDAHEFHFGAEGHFGAAEHAE,False +251,3.0,4.0,6.0,7.0,2.0,6.0,5.0,5.0,FCHFEBDGHDHADFGGFGFFEDBCCBCCHGCHDBDDAA,False +252,23.0,16.0,22.0,22.0,17.0,24.0,15.0,22.0,GDGADAHGFBBFBCHBDHBDCCDHEGADCHBBDFHCGGCEFBECHECEACFDBADEACEDFFDFFDFCEFCGFCHFGAFADGAFHAEABFDEDHHBAAAAHGABGDBFEHFHHFCHDCEAEEAEDCFFAFHCHHADHACHAEDABDCCGGCGFCBFGEHBD,False +253,28.0,21.0,24.0,17.0,16.0,23.0,19.0,22.0,HBGAFCHGAFDHGAHGHGDDGADGECAACFACBDGFCBAHBHDBFDEFABFACAEGFHGBDGBFHDFHCGBAGCABEGHEFHECCEAEHADHFDCCDCCEAFBDDBFHHFGHFCHCDHCFFCBAEFAEFEEAAEBFCBAABAAHEABBAFBGCBGCBDFGAGCCDECAHH,False +254,22.0,21.0,35.0,22.0,18.0,16.0,18.0,17.0,CGFCBBCBBCFBDHEGBFDEHCCAECAHAFDEEDAEHAEBCHFHBFHCHBGEACCCCDCABFABCDBDHCGCCGDCDDADDGGEHFEGCCBCBAFDEFDAADFAGGHECHECHECHAHGCFBBBBAGGEDBFDAFDCEDCEDCADCBHEFCAGCAGCBGFDACAACGGH,False +255,16.0,23.0,16.0,16.0,20.0,17.0,25.0,22.0,FBDCDGFHBEHADAEBABHAGDEEDGEAABDDEEFEEDBCGGDHHDHGDABBCBBCDHCDBGDBGCHGHAGFECEEBEHFGDFACHGHHGBHCEHCECABHADHACFBBAEFCEHAGHGEHGFHGFGGFGBFBFCBGCFGEFGEHBBGFCAFGAB,False +256,4.0,5.0,1.0,1.0,3.0,4.0,5.0,7.0,BHFAGFAFHABDAEHHGHHGEGBEGBCBHF,True +257,15.0,16.0,15.0,21.0,14.0,16.0,23.0,29.0,BBAHCCDBGFHGFGFFCFGCGHCGHDGAGHDCHDEABEBGGFDDFHDHHGHBAHDGCAGBGEBHBCHGEFGEHGEBFECHEDGEHBAHBEHDACDHHHBCHBCHAFHDCHAHGAGGDDBDDEACBAEEAHDDFFHGFHFFDAEDACDFG,False +258,25.0,18.0,28.0,20.0,16.0,20.0,26.0,30.0,GBDGBHAEEAHBAHBCHCCHCEBCECDEAAFHHCGGCFFDFBAGBHGFHDAHBACCADCAECAFFAFFGGEGCEACECCFCBEAAGFCFFGGHCDECBGHBHACAAFDGHDCHDCFDHFEHFDGDGHDCHAEADGGEADCHDHBGBDGAGGFFHHFHAGHCHHCDBGHBEHDEHGABBADBCG,False +259,10.0,4.0,2.0,8.0,6.0,7.0,4.0,6.0,BFAHHADDBDEBDAHFACEADEFDEHDGAGFDGFAEFBGFEAACHAH,False +260,17.0,18.0,20.0,22.0,23.0,26.0,23.0,18.0,CGCHEEDEBDHDGEGFEFFCAHGBHBEHBACAAFAFFDBFDCFAEFADFAEGBBHADAGGHFGCCGCGFBDFEEEEADHGDCEDFGDEBDHBGHBFFCAFCECGEDADDBHGBECFEBFEDFDDEGDHCAHCFFGFFGAHCDHADCBECBHHBHCGFGGABGCEGFE,False +261,27.0,24.0,20.0,19.0,30.0,32.0,21.0,26.0,GEHGECEEBEDACCACGBFGFCDBHEFEEFGEFBFACFACFAFFAGDACBAGDEBABFAEDAGHAHBAECAFDFEEBBBFEBDEFCHFHBFHFEHDGHBGHCCFDDAADEAEECGGHGFECFEDFEAFACHACEFBEFHHBHHFEAFHBFBBFBHFCAGHHFHHGHDCHDCHFGAGDDGCAGDEEAGEBEDAGHADBBB,False +262,24.0,26.0,23.0,23.0,21.0,23.0,28.0,24.0,CFDHHBBHEEHEHHEFHBDAADAFDBCDHDDFGAFCACEADGBEGCGCHEAHGADGABGADCFFBFEDDAFDCFHBBCFBGDGCHECBEBBCABDAECAHAHHAHEBHDHHFAHGEBEHFAAGBAGBGGCAFAFBAFBDCDCCDGGDGBHBBCBGFGEEGECGEHECDFCBFGBDGCACEFGEGGFHGFDGF,False +263,0.0,1.0,9.0,1.0,3.0,4.0,6.0,1.0,CHCCEFCGGBGFDGEGCECCFCFGC,True +264,6.0,5.0,5.0,2.0,0.0,4.0,6.0,0.0,CCAGBBGDBGDBACACGAGGFFFAFBAC,True +265,4.0,10.0,10.0,7.0,1.0,8.0,4.0,4.0,BEFBDFGDFABCABCHFCDGBHBCAFCAFDBDBGGBDFCCBCFHCDHC,True +266,22.0,29.0,31.0,16.0,20.0,28.0,16.0,14.0,EHAHCBHCBECFGBBCHEEBAFBHHAFGBFDBFCBFCBFCBFCGFGECBBGFCEFBEFDEDDGFCFCAGCAFCEGAAGAACDCFGAFGAFHBGABDAGAHCAECABBBCFBCDEAAEBFBBFCCFCCFABFDDFBEHBFGEDBEDEHAECBGCFHCDECACCDEFDADEHCGDBHH,False +267,19.0,18.0,7.0,10.0,13.0,13.0,13.0,11.0,HAHCGEBDCBCBBEGHFGBCGAAGBGGFDGCAEADBAHBFEFFEAGEHCHHBAHAADEFGEAGFFEFAEFCBAABAABEAFGAEGDEDBBABBFBHHDDHDBFD,False +268,17.0,10.0,10.0,7.0,8.0,5.0,14.0,9.0,DCADHDGHAGBAEHECHCGADHCGAEGBEGAEGAEGACAHGHDCBGHBGFBCAAAACBBEEBGBCFCAFDAFDHFGABGA,False +269,1.0,3.0,0.0,1.0,3.0,4.0,3.0,1.0,GHGGEBEFBFABFEDF,True +270,23.0,19.0,18.0,18.0,15.0,13.0,11.0,15.0,AHDAFCAECAFBHBCEFDEFCEFEDAADBADCDDFDAFGEHGEAGHADBBEACFGBDHADGCCABHHGHFBEDGHFEACEFCBAGAAEABEABGABHBEABGABFCBACGDDHFCHBCHBHHCEDCDDCDBC,False +271,7.0,9.0,4.0,6.0,4.0,10.0,14.0,6.0,GDDGADGAHAAHABDGFFFECFBHBEGEGHEGDCABGGFFHFFHFBGABGDBGCBGFGCB,False +272,9.0,5.0,1.0,2.0,6.0,2.0,1.0,1.0,EDAEAFECFGHAABAEDEBBEBAABAA,True +273,6.0,7.0,5.0,6.0,3.0,4.0,5.0,6.0,DBGDAGHAGECGFBHFBGDDFEDFHCBBEHHCAHBACBACAD,False +274,13.0,30.0,20.0,14.0,22.0,14.0,15.0,16.0,HBGBBDCBAHEFEBDBCABCGFGEHGECGCDECDBFDECGHBFHACDCBBHEHGGHFGBBBBHBBHBBGBEABHDBGDEGEFDECCFHEBHEHGEFCFBCFCDABAAHEECEECEDCEDGEBFEBAABGABCBCAAFDAFDHFC,False +275,5.0,8.0,10.0,12.0,2.0,10.0,10.0,5.0,HGDDCDFCDBGFCGDBGEAFACFDBDDBHDBCDCCFGCHGDFGCFDABHGBAGCGFABFEHF,True +276,5.0,1.0,0.0,3.0,1.0,2.0,0.0,3.0,BDDHFAHAAHAFEAD,True +277,24.0,23.0,18.0,24.0,16.0,33.0,19.0,28.0,ADCABCHCAHCAHEADEAHBGBCGFGFFGAFBDFGFBGDEGDGHHGHHACDDGFFAFFBFFEFADHDDADDFFAFGBFBBFHFCHBDADEAHECEDFDGFDFFDCBBHDAHBBHCEGEBHHBFFCCHHHHCHBBHDHAGCAGEDEHDGHDAFAFBBFABFAEAAGABGFEHCCBCHECFEDFGFE,False +278,12.0,29.0,23.0,26.0,19.0,18.0,23.0,13.0,BEBBEHBCAFAHEDDCDBBDBBDAFFAFCADCGGBGGCGHCFECEBDECGEHGEADBFDHFDGCDGCBCCHDBEABDCBDEBEEBDCGECBDHBEHEAGAFGHFHEFBBDBGEBFHGGHFGFDGCDGDDCFFFDFECCGCGGFBDBAACHEDBDDBGCAGBBC,False +279,16.0,11.0,17.0,16.0,19.0,22.0,19.0,14.0,GFAAFDCCEGCHGBEGDABFBDFEFEEBEBGFCGHHHFHAFDADEAHACBFCDFHFGCDACDFCGFEDFEGADGAFCEHCAHBBHEGCDDHDCAFCAFGEEGEEFBEFEHAHFDEFDBGDBGAFCAGCGGCGHE,False +280,10.0,14.0,13.0,11.0,22.0,14.0,17.0,12.0,EHCECEHBFGCGGCAHCDGCGGEDBBBFHCFBFBBFGHGHFABEAEGACGACBFDBCEECDEBFEBDGHDEBEGGECGEHGEDEEHFEHFEGFAADGADEHDAFDHFEEFCBA,False +281,32.0,31.0,18.0,18.0,36.0,28.0,25.0,12.0,GAHFABEGCGAEFADGADFABCADAEBAEFEHFGBGCBHDAHAABBBECFEAEEFEEFEDAEBAECADCDDBBBCBBEDBFAAFHEEGFCGEEGEFGEFAFDABCABDAFGFBGFEGBEACGGHFGAFHBBDEEEGGBHGFFAFFGEFGEBGDCHCHGBBGABEABEFEDADCEEFDCDHCDBGABAACAHCEFCEFBEB,False +282,19.0,24.0,17.0,28.0,20.0,14.0,18.0,11.0,CEGDBCDFGFGCADCEEGFABEDBDBBDEFDEADBGBEGBACDDFDHFBHGGCGAEGHEGHECDDGDFGEFABAEEHDFBDFBEEBHCDCCEHHDCGDBHDFDDADDEEDBBBBABHAHDABAAGADBCFBCBECDAGECGACGACFABFA,False +283,26.0,21.0,30.0,21.0,22.0,23.0,22.0,14.0,ABEAFHABHEFEEFBHDAHFBHFBAFBCBGGHGDHFDHFBEBBACCAECAECACGBCFFEFCEGGACBCDFAAHABGDEGDEGDACFEGDEGAFAACCBEABGAFDCFDFFGACHCEGCFGABCHGAHCDHCDCCDCGABDFBDEDCGFFBFEACCDCHDGGCGEEAEBAGDCDDCEEB,False +284,14.0,18.0,15.0,12.0,15.0,14.0,12.0,12.0,DHBFHFFADGAHCABFABEEFDEAGEAGDDBACBCCBGCBEEBEAHEHCFFCEFCBCGDCGDEGHGGABADBEEBEHCHHDBEGGFFEFDADHAHBBDFBCCBGABCFHCFA,False +285,16.0,15.0,17.0,12.0,11.0,20.0,18.0,11.0,HGHCBHCECFEHFEGDAFFGFEGFEAFGFBGABDBBGBACBGFBECAAFDAHHFGGAGGAEGCBDBBDHEFGGDGEHAHADEADEFCCFCFADDBCCBCABHAFFCFGCFDCFACDBCGH,False +286,11.0,13.0,7.0,7.0,10.0,17.0,12.0,13.0,FDGFDGFHABDDHFAHBHFFGCFHBGAGFFGFHHAGHEGHCGBCECDECDBHBEHBEHCAFGABAFBGFBEFGEABFBFDEFAEAHEABC,False +287,8.0,6.0,3.0,14.0,2.0,6.0,4.0,6.0,BGDFDCCDGAFBADBDHHDHCDHAAFAADBADBFDEFABDGHEGDDFHD,True +288,13.0,9.0,15.0,13.0,19.0,11.0,16.0,13.0,GGEDADGABGCBHAGACCFCHECDDCBAFEEHEBBEABEACFACEDHEAFEGFGDAEAAECDEFEHHEHBFFDCFDCDAGDHEBHCGHGGHCEFCGFEGEDGDCGHBGH,False +289,21.0,24.0,27.0,24.0,13.0,22.0,21.0,28.0,EBFBBCGBDHCAHFAHBBHBDHBDHADECDCAHCGHGFHADHDCHFBBAHBDHECABFBFFCDFGDFECBECBCHEAHFHHEHGGFAGBDCEHCFHCGGBEGFHBFGAFCADDFDDBDFCAFCHFDDACGACGDCGAGGHDEDECDAGHBFABABBEFBCCDEAHGAHGCCGCFAHDGHC,False +290,11.0,5.0,20.0,12.0,8.0,15.0,4.0,7.0,CBCCHDDHADEADEFDAACCCFFDFCAFCADCGDFEDCECCECFFHFFAGFCEDEBFFHCHGCDBHGCFDAFBAEHACCACB,True +291,20.0,16.0,14.0,23.0,25.0,13.0,17.0,18.0,GBEGBEGFEGFBFDBFDBADHAFBDFGDEGDGGECCECAEAADAACHHHHBHEGDADDBHAAAEHEBDEBGEAEHDGHAAHFABCEGDFGFCECDGDABDHBDECCABFBEEDEGFEHFEHGAHBDCDAEHAECDCFDCEDHGHEC,False +292,22.0,21.0,19.0,22.0,30.0,26.0,23.0,31.0,AHGAHGABADGFGGEEAEFDCABCFBCGBCBHCBCFEDFEDHADEFDFBHCBHAHEAHEHHEHEBGEAGEDCEHGACGDCFCEFDEBDEBDFHACEEHBDDGGEBCEBCGHFGEABFAEEBHABGAHGAHDHHDHEABEGBFAEGHEHCADFFDFGAFCDDGFHFFGFFDEBCHFEGFCDFHHCHFBEGHHADH,False +293,16.0,24.0,24.0,18.0,24.0,17.0,14.0,18.0,BDDACEACHABHABHECHGHEGEEFCHFAFAGFBBBGBEECEEHEFDBDDBDDGCGBCEHCEDCBFABFBBCCECCGBEBAABHECEGCEDDECFECFHCFHCGBCFFDDFADFAHHCGBBBCAFEBHGDGADGAHCBEAAFGDBHHEDCEDFEH,False +294,32.0,23.0,12.0,12.0,9.0,21.0,14.0,23.0,BCGBDHDCGGGDAFDFFBCABCABCFGGFAAFBHEBHGBGGDAFAACABHBFFDAFAHHBHHDHGDEADBHGBHBBHBBFACCBECAAAHABHAEAEDFGCCEAFFHEBHFHHEHDABAAGAGHADAAHAACEAHAAFFBFFBFFH,True +295,25.0,28.0,34.0,29.0,21.0,15.0,21.0,21.0,GBBDDFEAEADECDAGBCFBADECDBBDCCGCAGCDBCBBCBDCBGCEHCGACACFBHFDDBCHFCGAGGECFFABDEGDEFDHFHHBBHDAEDBEDCDDCDDCDAADFACEDHHGACGBBGAGAEGFGGHCACCDHGEHGEHGHCEACBHFEAAEACEACHHCHBCBECHHFEBBDCBFCBDDBDABAEFAHG,False +296,10.0,5.0,3.0,10.0,3.0,6.0,4.0,2.0,FCDBCACHBFABDAGEAGDADEBDFDAFGABAADEADHGDFFD,True +297,18.0,24.0,24.0,26.0,29.0,26.0,24.0,26.0,HAEHBEAEEHCACDDCFDHFGCBHCBCDHFDEADBBGCBGABFAFGGHGEAGDBCCGCBDFDDFBEFBEGDEGAADHADHBHADHCDFEFFEGGEBAHBCFGCEGEBGBFGEAAEDHFDAAGHFGEEGEEDHECGEDFEBBDCCDBDECFCBBEFHFCGFEHHEHHAGHCEHCDFCDFCDHCHGGHFEFFBFHBADB,False +298,13.0,9.0,11.0,21.0,12.0,21.0,9.0,8.0,DDADBAGGAGEAGECGEFHFCCFBCABCABHAEFABFDFCHHDDEDDHADHCHABFFFEAEDCFDEGGFDDFCDFEFFEDFEBADFDDFBDFCHBGFCEDDAFG,False +299,9.0,10.0,7.0,5.0,4.0,5.0,9.0,5.0,AEBFBGFGGAGGADCADGDHGHEBHBBGEBGFCHBCHAAFAABCECCFDDBCAB,False +300,9.0,10.0,14.0,12.0,10.0,5.0,22.0,10.0,GBDGFGGEGEHGDGGEGCCGACBDBBDABDAEFABBCEAEHAGCFHDGHGGDGADGHGGBFCDHCDGCGBDAACEHCEGCEGDHCHECHCBF,False +301,23.0,15.0,14.0,8.0,21.0,17.0,19.0,20.0,FGCEGAEGEDHEDBGGECFFHEBBBFDAHHEBAEBHCHEGAAHABEEFEEFGBHGCHCAHDAFGGHGDHGFAGBABFAFHEEGEAAEDAGFAEFACFACBHFDCEHBAHCAHGAHCCGCCGEAGEACFADFHBBHBF,False +302,27.0,23.0,30.0,20.0,17.0,18.0,24.0,20.0,AACCCBGDBFHBAECFFHBHHGHAACGCHDDBFBGGCHGAFGAGGAGGAHGCHGCDGCHBHABFDBDDEEDEEDBCFCCFCHBHFBAFBDFHFBAAAFCCGHCDBADAFCABEACGBFBEEBAEHAEGAHGACBBDACDFCDGCDGHDEEDEBCFFCAACHECGCBGCEGCDAAEEHGD,False +303,30.0,27.0,22.0,22.0,20.0,20.0,25.0,21.0,FCHFDBBDBGCAADEBGFBGABGFEGHAHBADAEDACBECFFCFFGDBGAHHAEHFCAFAACEDCFFBEFAEABHDGAEHDDBGCBGEBGEAEEFBEBDHDAAACCHCCHGDAGDFCFABFHBFHBGBBDHBDHEEHECHDCADAEDGBCCBAGEHGEBGFBGCCACCAGAADAHGHHGFDABGGGD,False +304,29.0,17.0,17.0,22.0,14.0,23.0,28.0,17.0,DABGFCFHAEGAFGFBCCBEDDHFCADEHDEHGHDGADGHGGCCFFFFCCEGHEGBDDDDDFDFGDFGCEABADBCHADBGDCDAHFFBGFGGHAGHAGAEGEGCAAHAAGAAEBAGBGFBHBBHBGDCGFCDFBAEBHCFEAAEAAHGAHGAGFACFDCFEAFDAB,False +305,11.0,12.0,13.0,10.0,10.0,17.0,17.0,13.0,BFDDADEGGFGEFBEAGHAGBACAECAFFBBFHBCHGFHGHGFFGCFCBBAGCDGDDGCGHCBHDGGFHFFHGDECDFCDEAGFAFBAECAECHBHHEHCEBF,False +306,7.0,10.0,4.0,3.0,5.0,2.0,7.0,5.0,BHBHADABBABGABHDGHDBCEFEEFCEBCEHGGCGBAABGAG,True +307,17.0,17.0,13.0,19.0,19.0,19.0,22.0,12.0,FDEAAHFFBFBGFBDFGDFGDBGDBGFBFFHFFABEGGGHAAHEAFEDFCBFCEDCDAGBAFBGHDHCGHGDEGDGCBBDHGABCDHCFHEGGDBCHECEECEADEAEGAGBAEEDDEGCEGCHACBAFBDEDAFGAE,False +308,16.0,19.0,32.0,19.0,25.0,21.0,28.0,24.0,BCGCCBFCFGGDHGDADAACACGGBADDGDDGFBCHHCFECDGGAEBAEGHCDBCHEEHAEHFEFFEGFEHDCCCEGHFHHGBGDEGFHCFBFHBGEGFCGFCBHGBHEBEEBGBAGEEGHEAHEBFEBHCBGGDGDCHCCACCADBAHEDFGCACCHHCHHFBAFAEEDCECCDFCDFCDFEG,False +309,12.0,7.0,7.0,14.0,8.0,9.0,9.0,23.0,HFHHBHGACFAHHHHHDHBGHCEHEHCFHCBHDAHDAHFGDDHEBGFDDHADHBDGEEGDACDAHDAHCGHAADAECBEGEFFAFBDFG,False +310,7.0,9.0,2.0,2.0,5.0,3.0,5.0,9.0,BBABAGEAHBGHFEHBEHBHHAHBEGBGGBDACFCHFDHAAE,True +311,26.0,28.0,24.0,21.0,11.0,21.0,26.0,17.0,BFBEHBHGFHFHDDGADGADGFDCFBCHGFAEAAEAAEAABDDGHDBEDCCGFCFFCBBGGBFHCGGGDBGDBDEBCFBCABGDBGDFGEGCCAAHBGHGGFFBAHBAEGCFBCECHFADGGCECCFCBACBGBBGCCDAEHABFADDADDAFBHFCHAAFAABHHCHBCDBGA,False +312,23.0,13.0,12.0,13.0,21.0,13.0,8.0,13.0,FBAFBAECDHHEEEEAACADHEDAEAEFAEFAEGAEGAEAAEAGGBCDDFHAHHFFHFCCACAEFAHFAECHEAEDDHDGBBCBDFEHEAHBAHBAGCCDDDFGEGEFBBDBBCCB,False +313,3.0,1.0,2.0,0.0,2.0,1.0,1.0,1.0,HACAACEFGEB,True +314,19.0,17.0,14.0,10.0,16.0,21.0,10.0,13.0,AHDAHEEFAEAGCADFEHCEBCGCCGADDADFADFAHAAHFEHFEHFEFFCBFEBAAHEHBEBCCGHEBHCBFCFFGEAHEACBABBABFFGFFGBBBFBGDGCCBEDADAFBFFCHEDG,False +315,3.0,8.0,4.0,7.0,12.0,10.0,4.0,14.0,DHEDBEDBECHEFFFCHDAEBAHHFHFEGFECEEDEGHBGFBAHBHEBEDCFHHFHFDHGBH,True +316,19.0,13.0,26.0,20.0,13.0,13.0,16.0,14.0,AFCBGBFCAFCEECHBBAGCDGCFGHEBHEDCCAHCFEAEDDEDAGCAFCACCADCGDEBFAGDHGDCBACHAGHBFHCGECDCAGCADADFGDCGDGEDFADCADFFDAEDHCCHCBHGBHEBFGBCABHHDE,False +317,16.0,18.0,21.0,25.0,22.0,16.0,21.0,17.0,GDDGDDEDFEGFEDEEDHBDHBCHDHBBBBBBCCBCCHFCHBCHEHADGCDGCBGAFABCEDFFAEBCHBDDEADCGDEFAEGAGCCDCCGFDFBDHCGHGAAFEADAAHEBHEAHFCCDCEAHEAFGBGEBGDGEFGFHGEHFAFDGEDGECEDG,False +318,23.0,22.0,20.0,24.0,12.0,20.0,16.0,25.0,AABCHBFHCDHCGFGHDHHFGAGHBGHBGCEECAEHGBCGDDDHCFHGBHGBHEBHDCCAHCAHAHCAFCDFHHEBDDBGDGEABBAEBCDDFDDFEDFACFABFCHHCHHGBFAEFBCGBDHFDBFDFDAADAFDCEHCBBDFAAAAGECDABDAEFABFG,False +319,9.0,5.0,11.0,3.0,6.0,3.0,10.0,12.0,HABHDEGCCCDFCBHCHHGHAGHCGHCDHCEGCGCEGHEAHFABAECGBBAAFGAEHAG,True +320,31.0,18.0,28.0,29.0,18.0,25.0,23.0,22.0,ADEFDADBAGBEGHEGDCAHAAHCFGCHGFEGFHGCGBFDAFDCFCEBABHDBAFAFFDGDAAHABGGCAFCACCDEBDCCGCCDCCAFGGCHBDHGCHAHBBBBBCCGAADCBDEFDHCAHCHHFHAECDCHDGHDEADEDFADBADEEDGCBGCBGDGEFHAFEAFAAFGEEDCFDHFAHFAFFAEFHEDGD,False +321,11.0,11.0,8.0,16.0,26.0,18.0,18.0,26.0,HFGEAHHHHDBHGEHDFAGGDEFDEFDEFAEFBDFHDEEDEEBGEHEHHEHACGGEBHEGHEFHEHAEGFDGDDGBCEAEGAECDHCGHFEHGAGFCHHEHHFGDFEFFHBFABHDGFFBCEBAECGDABDHBC,False +322,6.0,3.0,4.0,2.0,1.0,1.0,3.0,2.0,CAAFAEHAGBDHCDBCGBAGCA,True +323,10.0,11.0,20.0,18.0,16.0,14.0,16.0,14.0,FCGBEHDGCCHABGBCGACFEFEEFEDCCCBGCFHCDAGDAGDEDFHGBAGEDFECGACGEFGEFEHCDHCDEFHGBHGEFDEFDEADBAEHFCBGCHDCHDCBDCFHBDABGAHDHCD,False +324,14.0,16.0,12.0,17.0,15.0,23.0,16.0,14.0,HDEBDGFAFHDDHDHECHEBHGHEGEGFADHGEFGDFBCEBGAFFAGFHBDHGDCGDCACFECFEHFAFBCEHCFBEFCEADHABCBBCFBAFAGFAEEAGBBECBDGBFGHGBFDDFDDFGAFDAF,False +325,15.0,13.0,7.0,9.0,15.0,10.0,11.0,11.0,BDABDCBEEECAECHCFHBBHDHEAHEAGEDEABEDHEGGFGGFEFBEHEEFBHAAAAAADAADFAEFGHHDFHGAGBBBBCDCGBFGFCG,False +326,18.0,22.0,21.0,20.0,18.0,16.0,22.0,11.0,FAHEBHABFAHGAEGHHBBBCBGCBECAAGDACFBCFEHGDHDDCDDFFCEGHEBHCFCDFCDGCHBAGCEBCBDGBDCBDHGEFADGEFABFGCFCDBCGACGABFACDEDEBDAFAFFABGEBGEGEEDEGDAGAGGEBGCBDCED,False +327,13.0,17.0,20.0,5.0,21.0,19.0,14.0,10.0,CACCAECGEGAFABCCDFAFFHFCEFCHAHBGEECEECGEFDECDECEEABFBEAEEBEDHCAHAADBABFGFFGFGGFBGBHEBHGFGEFBBGCBCCBCBECBCGFEHFHBGHACEFF,False +328,21.0,20.0,17.0,13.0,23.0,15.0,20.0,19.0,HECGCCHADAADGADBEGBEABEHFGFGGFGCBECFHBAAEAHDFHFFBGEBGCBFHAABAABDCBDCAFAAHCGDCGEEGHGDEGCHGHBFHDHCDBCFEAGCAHCEHEEFEFBDHHDEBEEDEBGGAHGAHBEFBECEFABGABEC,False +329,24.0,23.0,29.0,30.0,30.0,21.0,23.0,19.0,HADHFBHFEHCEHDHCDFCBABEEBDEHDACBGDBCDBGDBADCCDABAGCEGBDGBEGCDFAFFGEFGAGEAGEADCGHGBDEDAADEHBAHCAEGBGFBFHBGEBDBBAEEDEEFAEDGCABCEDGFFGECCDACHBDGBDFCHECHECEACEADDDEDFADFAFHCFGCADCEECFCCFCCAEBGGHHCHFDHFEG,False +330,7.0,6.0,9.0,9.0,7.0,8.0,16.0,10.0,HGGAAGEEFBEDHFDAFBAEDFGHFAHGDHEECGHCGCCACGFGHFAHEBHCGGCBGDHGDCGDCGBGDBDF,False +331,15.0,22.0,24.0,18.0,22.0,22.0,16.0,24.0,ABAFBECDEDAHCCGCAAHHCHHGBBGBAGBDGEDEHAECACBBFHHEHHEHHFHDCHDCBGFHFFHAEBFEFGDHAECEECBEFEGCCFBCGBCDEGHBGHFAHFGDBGEAGFADCBCCHCFFDEFEEFBEFHEHDCDDBHDBGFAFFBCCBCFBDADCGDE,False +332,9.0,18.0,16.0,12.0,7.0,14.0,10.0,14.0,AADCABGADACDAEDCHGCBFHBFHBEHGEFGHGECFBCDDGDAECHBCEBCFBCHHFDHDHHFFDFBGFGHBGECCFDFHDBHGBCFFABBACBCBBCB,False +333,24.0,10.0,12.0,14.0,8.0,11.0,24.0,18.0,AHAAHAADADGFHEEGBECBDCEACAHEGHEFHADAADFHGBHGBGBCGAGADGADGAHCAHFHFGEGGBACDCCDGFGBHCFGAFGBGEHACHAGGCDDHDAADGHDGFCGAHBAHBGFF,False +334,17.0,19.0,16.0,21.0,12.0,28.0,7.0,21.0,BCEAFGACAHCFEBBDBBDFFDBCDBFDFFDHFABDGBDFFGFDHFCGFGHCBHAFCEFHHBHHAHFADFBFCBFCBDCHEHDCADFDDEHDECDFCAFAAHABFBDFHFCDGHDHHCHECBEAEHAEFABDEFAFBGHEA,False +335,5.0,1.0,17.0,8.0,5.0,13.0,6.0,9.0,HFEEFACCHDCHDCHFBHDDCACCFCCGCFFDEFAFGCFHAEGFEGFDCCAFCHCGDCGDCHFH,True +336,7.0,5.0,7.0,10.0,4.0,6.0,4.0,9.0,CABCEBDDFADCAFCFGCEGEHDDBFGBFHCHHGHHDFDEHDAACAADHBDH,False +337,17.0,14.0,20.0,15.0,14.0,12.0,26.0,25.0,FEFFADAGDAGFCHHBHHBAFEECECAFCDFDDGGCHGCHFCGDGGBBGDAHDHECHGCBBBHDEHCCHFGHFCHBCHDAHCAGCAGEBHEBAAACEECEGGDHCEBFEHGHCGHCGDABAGHGGBBGFGGDGHHEHDDAAGA,False +338,17.0,17.0,8.0,23.0,13.0,10.0,15.0,13.0,DFFDBGEBEBCDBFDBAEEAFGAHDDDBBDEBGEBGBAGBGBCGEDEAHHADHDDHEDHGGHADDBDHHDCHDAGAECADCHDFBBFABDAFCAGDFFCAEGAEGEFGBDGCHAHA,False +339,18.0,24.0,23.0,25.0,16.0,22.0,30.0,24.0,DGBDGDDCDGCBGFEHEAAFCACGBFEBGCGCABCAFAGEAGEAHDCHBFEGHEBDDBDDBGABGFDGFBHCAEEAGDHEHFEFEHFGHFBFFGCAGCACCDHDDHBDFGDFGEEGBFDHHBCHDFFDCCABGBDGECBEGGGHDCHACHBHHGGHBGABDABHFCHFHHDBABGFCGFCDC,False +340,2.0,2.0,13.0,7.0,3.0,3.0,2.0,4.0,ECCCDCCACCBDCDFCDGAHHFEDFBDCDCCHGCHE,True +341,4.0,3.0,4.0,1.0,4.0,2.0,6.0,4.0,GAEGBCHBCFGAHGAHBACEECEGHGDF,False +342,10.0,14.0,13.0,18.0,10.0,15.0,4.0,7.0,BFBBADBAGACCABFAECCFCCEDEHDABBAFGGBDBCEBFDBFDEHDGHFAEECCDCCFHBFDEDDFDDCDDEHDEFFBDFBDFACHAFH,False +343,2.0,3.0,3.0,5.0,8.0,5.0,2.0,1.0,EAFDCDDCHEBFEFDEFEABECBFGEDGE,True +344,16.0,17.0,10.0,12.0,19.0,14.0,18.0,24.0,DGDFEBGECFCBBGFFEFHEHBEHGCBACBEGFGGHCBHGBHAEFBFFBHHBEHAGAADFAGFAHFAHGACGAEHABFGEGHEHHEHCABDAHEABCDHGEHGAHDDHDDBEFBGDBADGCHECHDHEEE,False +345,12.0,6.0,8.0,11.0,11.0,7.0,6.0,8.0,EEABBCDDGADCAECADHABGABECBECFEFFECDEGHAFHDGHFHAFAABDAHCEHAEHFDCDEGDGD,False +346,14.0,12.0,14.0,18.0,13.0,23.0,16.0,8.0,ECHBFBAFEFGCCDDGFDBFEGFEAFECFEHFEGBDDCHDHAAGAAGFBDBGDADDHGDCFFHEEHCEBGDGCFECFEBFDACDFGDAGDGGCGBABDCBCBAFFAFFAFEAFDHFCG,False +347,13.0,9.0,9.0,6.0,6.0,16.0,14.0,5.0,GEACFCDFGAFGAFCFFDDGGDBGDEGBAAHGAHFFBFFEEFBFFBFCEGBGGCECCAAHAGHAFAAHACGGFBCBBD,False +348,2.0,2.0,2.0,3.0,4.0,6.0,4.0,5.0,EFGDDADHEFBAFECFECFHBFGGHHGH,True +349,25.0,25.0,26.0,14.0,12.0,22.0,23.0,17.0,GCCGCCGEEDFADFDCCEHCBHCBGBBCBFGBAGFGHBGABFAGFBFFACCHHFHABAABCABGHEGBCGBFFAFGACCDDCBFGFAAAAAEACEFCEFCADCAGHAFABFDGADHHGBBCHGEBGCBHCBFDHGHHCEHBBBBEFAFHDDGFDCAGCAGDEDE,False +350,26.0,15.0,7.0,12.0,18.0,16.0,17.0,8.0,GFECAAAAAHFADABEGCECDGDAGEABEGBGBBGBBGCHEFFDFFAAAGEAFBAGDHHFGGAGEADFAEEBEFCGFDDFGDFDBFBEHHAHEAGEABEABEBBADAADAFFCEGCHAE,False +351,19.0,24.0,27.0,20.0,25.0,23.0,28.0,19.0,HHCHFCDGDBGDFGCBGDFGBFEDFBGABHABCABGBGAHGBHGBABCCEEBDFGDHGDBGHFGCFGCBHFBHECGCCBCGBFGACGDCHEEDFBGABFAFFGHDAEAAHDAFDEFDEDEECFEGHECAGCECCFCBABFADCAEGEDDFHFECFEGABGAHDHECBACDGHEEEEHECBECGFC,False +352,11.0,14.0,21.0,19.0,18.0,15.0,12.0,19.0,CGFBDFCAEDFEHEHCEACEAEEFGDAGBACBFCBFABDDGHDEHFGADGHDHCBHCEHCDHBBEFGFBADCGBHEADECDCBDCBACBACBDCHFHHCHFDGCDECGHCEEGHEHFFFFGEHDCHDED,False +353,14.0,12.0,11.0,22.0,22.0,10.0,7.0,14.0,BDEBEHDFDDCDEADEHCFHCAACAABBCDBHHEDHEFBAFDACABGEEDEADFADFBGFAGCGHCFEAEDGDDFDEEBEEBEHHEHHEDEEBHHCADCACHDDGGBFEDDE,False +354,25.0,23.0,25.0,17.0,15.0,24.0,9.0,25.0,FHABBAFCCFBCFBEDDHCHGBAEHCEBDAADFADFHFHHFHBFBCHBHHEHDACDFFAGBGDEGHHGDDCCCAHCEECAEDECFBBHDFCEFBAHAAHAFHAFHBFAAFAGGACEAEDAFDHEGFCFFCDFHGFHACHABBABECCCCACCBBCDBEBBHDB,False +355,17.0,20.0,28.0,20.0,27.0,26.0,18.0,20.0,FCDHEAHEGECAEDAEFCHFEFCCCCBECHEHEDHDHHEGHEDFEHAEDGEDGEFEECECHGCDGCBEDDEDDFDDBGGCGBHHAACABGGBCGBCGDCFHCFBCFBHFAHFEFFCFFBDACFCHBHEEFBGFBHFDGGCECAAFACFBBBABBDBEHCAFFEGCADEADFFBCGA,False +356,11.0,9.0,19.0,9.0,17.0,23.0,24.0,22.0,DCFDCHHGFEAECFFCFFGEFGFFGAHGBHAADAACEFFGGEHCAHCBDFFDGGHHBFHBHHAHFFGGFEGFCGFCHCGGGGEEEFCDHCDECHECEBCFGCHBCHAEHCEGFDGCHBEHBGHBGHFAEAEGGD,False +357,15.0,19.0,23.0,15.0,30.0,8.0,15.0,12.0,EDGEGBEGAEFADGHEFEEDEDDEGGFDAEEAGDAEEADEAEBBCFBCGECBEGGACEFBGDHECHEAHEHGGABCEDDFDDEDBHDBCBACACCGCABEGHCHCCBCCAFCHBEHEHHCCBCEBCEBCEBFBBECA,False +358,8.0,10.0,3.0,16.0,6.0,11.0,10.0,8.0,EADHDFFDBFEGFGCCAFCBHDGEDHDDFBBFEBHHDAHDHEDHGDAGDAEDGDGFBGABGFDGFABBADBF,False +359,20.0,14.0,12.0,8.0,11.0,4.0,10.0,13.0,BAHGAEDBEDCADCAHBABAAFAACGBHGBHABHEHCCHBCGAEACGDCADCHGAECADFAEBDEHFCHEAADHAGHFBEBCEAGEBGBGHB,False +360,26.0,15.0,17.0,18.0,13.0,10.0,21.0,9.0,HCBGGBGGBCCDDCDCCHCHHEGGEAFEDFAGEBDHBGAFGDGAABCADCEGCFGAEABEADHABGAEGFEAFAFCACGADDBEAGAABAHGDCDEADECDBCDBCBHCFDDFAGAEGAHGAGAAFBDB,False +361,15.0,32.0,16.0,34.0,25.0,18.0,29.0,23.0,HDFHFFDABBBBEEBGEBGEDEEGAHGBGBBHDAEGCDACHECHBGDBGDBGDGDDFBGGDEBFAHHHHEHHAHDADDEDBEBBHABHAFGDDBEDHEDHDDHGCHCEFDGGDGGBCFCCFEHFGGFHAEDFDFFCAEGABDFEDGBAGBGDBCFBCHEDADDCDCBBBDEBDEBGHCGBEABFCGGEFCEG,False +362,22.0,28.0,20.0,25.0,21.0,16.0,11.0,16.0,BHCHFBFFBDDBHHBAHBADBAHBAHGCCFCBBDBBECAEFEDHHBCCFDCBBBEBHEBFGBHGDHCFFCFAHHAGAGDBFDGFDBCGEADBFBBAAFEDGEDFDAAGBAGAABEDDACBECBEFDAHCCCCGCEEHAEADEDDEDCEACEAEDDEDDE,False +363,11.0,11.0,7.0,6.0,9.0,8.0,12.0,8.0,FBADHHEHFGGCGAFEAFEGFGGHGHCCHCCBCABAEBAHDDCGFABEABFABABDEBDBHAGGFBGEEGDE,False +364,5.0,2.0,8.0,2.0,1.0,2.0,9.0,6.0,AHGACBAGHCGHGBEFDAFGACHCCGCDGCHGHGC,True +365,33.0,17.0,16.0,24.0,25.0,19.0,21.0,11.0,GDDGDDGBDBAABAFECGEDGEDFAGCACCFHCGHCDAADBACFCHEDAEHABGGHCEEEBAEFEDFDCFDHFDAFAGFBCDAFGEDDEHBEDBDCBHCAGFHFDACAGDABEABGABGAHCAGDAFFGEFDEFGFGEEEAEAAEAAEAEFBBAHBABCEGEDGAA,False +366,24.0,28.0,22.0,9.0,23.0,15.0,15.0,17.0,HEGHECCBBCBBFAEDHBFCBFBBFABGEGCFDCHCCBAAHAADABBBBAECHECEEHEEBAECDDAGDFGDFCDCGBCEBCABEABAAEHGCHEFHEDHFGGAGEHGCBBAFBAHCFEEGAEGABAABAHFHBCCCEHAEBBEGCGFFBHFA,False +367,22.0,19.0,28.0,25.0,31.0,21.0,23.0,26.0,HGHDGHDGEBCDDCAEEADEDEEHAHBDCEEBEFGAHAADGDHBHFCEGEDBFDEFEEBEBCEFCEFCBACBADHADEGDAHCCEDDEDHFAHECDDCBEFBEGBDCHCHAABAACCHCCHCDHAGCAGEBEEAFECHBCHGCGGHFCFAGGEDAFDCBECBEHDEFFGFDGFHGFGGFGFFBFHBCCGAGHAHH,False +368,19.0,23.0,22.0,14.0,18.0,18.0,13.0,20.0,GAHHDGFBGDBFFBHGADABEHCCFDCBDAGDBFBBFBBFBFFEFFAHCAFGAHADHEBFBAFBECCEBCDDAEDGEHBBBBACBAEBDECHEGFCHACFDBGCHHCHGEHCCHCGHCGECEAGACHFCHFCHDEEEEEBDACAAHA,False +369,8.0,9.0,10.0,4.0,11.0,7.0,17.0,8.0,GEHGEBGFGGFCGEHAFBBFCBHCFDCGEHAEGCCGAEGBBCHBHFEAFGBCGADGADEADCGCHGEBAEGHEG,False +370,14.0,14.0,22.0,16.0,19.0,13.0,17.0,12.0,AEAAGFACECCFHBFDEGEAGADCEHCECCADHDEGFGGCCGBHGBHGBAFDGECGECGHBDHBABFACDDEBFECFEFFCAFGEGEEGHGCBACBCBDABCGBDFEDEDDHDFBDHCCHCCHEADE,False +371,24.0,19.0,21.0,13.0,20.0,18.0,17.0,23.0,GEGEADCDGEHBDCBDHAHCEFCEFEEFCDFBEGAGFHGFCCHCCFFCFFAADAFCABBBHGCHDHEAAGCAGDABHHCHHCHGBEFAAFHAFHGHHGDADEABEGBCGCDBADEHHEHACDABGECFEFEEABEBBHBBABCAGCFGEFABHAH,False +372,3.0,3.0,3.0,4.0,0.0,2.0,1.0,2.0,DDFDDBCABHABACFGCH,True +373,11.0,27.0,14.0,16.0,27.0,12.0,14.0,25.0,BGEGGBDBADECHGHHEHADHDGAEAHEFHBFHEEDGEDECBHFEHEBHDDCEABEAHEAHEBEEBEGAHCHHCBBBBBBBCCGDFGEBBEFHFDHFDHFDEFDEDEHGEAEEFBBHBBADBCBCCBGFDGHEFABBGHCCCGCHH,False +374,3.0,9.0,10.0,10.0,8.0,7.0,11.0,11.0,GCGGBBHHCCGFDGFDHDDHFDBFEGEEBECDDAECCBBCHGCHGFHADHACBEFHEBHDBHDGGFGEC,False +375,23.0,33.0,18.0,22.0,30.0,18.0,26.0,23.0,EBDEBDHHGCCGCFGADGBCGHCEHFEHDEHBEGDDGBHGAHDAHDBCBAABCFBCHEFDADCAEBBBBHBAFBAEBAHBHFBCAGCFHDADEAFECEECEFBBGGCCGEHHBBHEDCAFAHEEFFEAGABGCDGBBGBDFBDFGDBEDBHFBGDDGAEBAGAFGEEBEECEABEHGGADGDGFHGFEAEHHE,False +376,26.0,12.0,16.0,23.0,9.0,18.0,21.0,30.0,ADDFFDFFDFFHCFCBFAGFBGHEDHEAHECHCABFAEAAGAAGDDDDCFGCAHABDEGFHBCBCADGHDGADGHEGHDGHFBHGDHCDEABHGEHBDADAACHHHHFHAGHEGHDGHDHHCCCAHDHHGGFAAAAFABFHCFGBHGAACBGCDD,False +377,14.0,10.0,11.0,6.0,8.0,8.0,6.0,11.0,FCEFBBABDCHECFBCGBHGFHECGCFAFAEFDBACADCABCHHEAHGAEBAHAAHAAGFDCBDCBDGAEHHEH,False +378,10.0,13.0,11.0,8.0,10.0,9.0,5.0,12.0,ADCHBEECEEADBACBGBBAHBGHCCHGBHCCACCFHCDBDDFFDFFBFEAEHABHDBDAFHECBAHEGHEGHEFBAF,False +379,26.0,14.0,13.0,28.0,14.0,24.0,18.0,23.0,ACEAFGAGABGAGGEHAFHDCDDFFCGHCDHAAAEFFEGABGAHHADFGDFBCAGCAGBACDDDBDDEADCCHGEAGEABHHFHCCBDABHFEEDGHBGBBHFDFCDFBDADDEDDEDHFDHFDHEDHAAFAHDGDBGEFFABAECAHHFFHFFHDFHFG,False +380,21.0,15.0,24.0,10.0,21.0,16.0,24.0,20.0,GBFFDHFBFGEFHHHHHECHEDEEBCAFAABGACGBCAECBCCBEDFCDGCEEEAEGAGGACDAFDCGBBGBBCAFFDFHBAGGDGGCCHEAFEAFCAFCAHCGGAHCACCAEGHEHEEGEEGDCHDHHGCEGAFHHEHACBCFGHBGBAG,False +381,15.0,21.0,27.0,23.0,28.0,27.0,27.0,20.0,BCBHCAFBBGEBDEDHCDGCGGCGDCFECDECEBCEBFEBFGCGGBGABFAEHCFDCHEGEFFFBGFECCEHCGFFGFHGBECCFCFAEDAGAHDAGEFFFAFDACCHCHBBHFCDAGDHGDEGDBDEHDHHFHFBHDBFDEAGCADBDDBDDEEFEEAGEGGBCGEFEEFDGHHCHFEHCAGGABCE,False +382,0.0,4.0,3.0,2.0,1.0,1.0,2.0,3.0,BCDBHDBHFEHGGCBC,True +383,1.0,2.0,2.0,6.0,6.0,2.0,4.0,2.0,CHDAEDGEDCEGEBGEFDEDGHDFB,True +384,12.0,14.0,12.0,10.0,21.0,16.0,19.0,20.0,GDHEBFGHDHCEABECBDCAHGAEGCEBCEHDEAEBHEBHFHHBBFFAFDCGHAGDCBFHGHCADBAHBGHBGADHFCHFDHCHECEECEGFEGEAGEGGEBFEGAEBAFFFEGFGGDGHFEHF,False +385,9.0,9.0,5.0,9.0,10.0,4.0,7.0,7.0,BCCBABGHBGDEGDACDBEFBHDGADGAEHHCFCEFDEBDBBDAAEEAEHADAGEHGFHE,False +386,15.0,9.0,11.0,11.0,15.0,15.0,12.0,13.0,EGCFFCFGCFHFDHCHCCHACHECAGHFFABEAHEFHEDDEBDHBDHBECDEADGFGFBGFAGFAFAHEEEBDCDGEHGAGGABAAGDFDBEABEHECFAA,False +387,17.0,16.0,9.0,11.0,9.0,4.0,15.0,11.0,DADCFEBAEAGCBBHBEGBDABFBDFDHCAFEGGEAGEACHABHAGHDGHBHHBGDEGHCAAGDAHACEGBBGABAACGACGBDGBDHBDCE,False +388,10.0,3.0,8.0,5.0,5.0,8.0,6.0,3.0,BDDGGCAECAFGAFCACADCEGCAHCADCBFFAFFHHFADEGFEGBEA,False +389,17.0,13.0,28.0,32.0,15.0,31.0,24.0,29.0,HGHCCHGBFDBGAAAAEDAFHHDEGFECFHGFCFFEHFDHGDCCFCHFCFDCFDGEHBEHGHHAACAEDAHDACGEGFEBHDHCFHEFHGFAGFACDACBHCDHCDCCDEFDEFDHFECDHDDCGDGBBCCFDHBDFBDFCGBBHAEHCDGGFHGHAGFBDBDCGFCGFDGDDFDHGHAFFAGDCEDCF,False +390,23.0,24.0,19.0,26.0,25.0,15.0,25.0,27.0,FADECFEGAEGHCFDCBGCBDDHDDHDDAGAHHAEBAGDAHBHGBFGBGGFGDCADCBHBEHDEAEHGEHDBHGBHEBDGBHECAEDADDAEHFFHFHGGCCHHEFECCGDEACEHHAHGAFAADBBDCBGABDACCADABFABEHFEBEEBDDACDEEDGGGGBHGBHCFGCFHFBHCBEGEE,False +391,4.0,5.0,5.0,5.0,10.0,9.0,7.0,10.0,FGGFGCEGEEHHDHGDCEDAHBFHFGDFEBHBHHAHFCCFACFGBFEEHEEDEAB,False +392,2.0,1.0,3.0,2.0,5.0,3.0,4.0,3.0,FBGCCGDCAHEFHFDHAGEEGEE,False +393,32.0,34.0,23.0,23.0,23.0,22.0,17.0,26.0,AABCCBCADCAHAAEFAFBABBHCCFBFGDHDHCAHFGBBCCBHCBHBFCDFBHBEABEAGEDGECBEBHEBAEFHEBEBDHAHHBGCCFDDFDFBDHBGAAACEACDACHADFAGFAGFHGFDFADFAHEAEEBEAGDDHCDEFDBHCGGDGDAHABHEBHEBEEBEHFABAHBGEBHCFDGFGFEDADCACHACBGBB,False +394,10.0,5.0,5.0,10.0,12.0,9.0,5.0,11.0,DCDEADHACFADFADABDHGHHDAHGAGEEBEFFCFAEDAGBAEBCEHDBHFFCEFHEHHEGEEDHF,False +395,9.0,8.0,7.0,6.0,6.0,3.0,2.0,9.0,BAGBECDECDCHEAHAFGBFHBAHDHHAACAACHHFHBDDBEEAEDBCCB,False +396,28.0,25.0,16.0,17.0,19.0,17.0,23.0,14.0,FBGFAAAHBHHGFCGDGGBGGEGGEFCEHCDGBBHEACEGBEADCADGEGHDGAAAAABFABFADFCCBHCADEFGEDDBDACAABAAHHHFACFBDAADBAGBGEHDEDBBFBBFBBCEAGEBHEBHEBEFBCFECFEGDGBAGDACDHCFCFGAGAE,False +397,11.0,7.0,11.0,10.0,5.0,9.0,10.0,7.0,BCHBAHFDBFCHFCDDBHGAGCHGCGGCGGFGEAEECDDFADEBFCHDCHBGABGEFDCFDFAAADAACA,False +398,21.0,30.0,21.0,28.0,27.0,13.0,18.0,24.0,CBDCAGAAEHGBHBHHFHHAHHCGHDBDABFBEHDEBCEDFDCFDCFBCEDCBAEBEDBEBBABEDGFBGFEEAEBGHBGCBACBDCEECBDCDDCAAGDGEAGEAFEGEEBEHFDHDGCEBFEBDGDFHAFHFDHECHGCDGHEGDBDBHEBHGBDAAAAEADDDCABHDCHCEHCHGBBA,False +399,8.0,12.0,5.0,5.0,7.0,5.0,5.0,13.0,HHGHBAEGABBCBBCBBCFBCBHADAAFBAEBEBFHDECEEFHGAHGHHDFHDGHAHHED,False +400,7.0,6.0,11.0,5.0,6.0,14.0,10.0,3.0,AEFAEBCFDCFCFAEFCGGCGECHFGADCBDFGCHCCABCAGGEFHEFGAFBFBGFDGFDBF,True +401,5.0,2.0,3.0,1.0,8.0,3.0,7.0,1.0,BAGCFGEEAEBHEGFAGFDGEEGECAEGAC,True +402,7.0,14.0,22.0,10.0,18.0,10.0,12.0,15.0,GHECCAABBCBBEEBEGBDCEECFGGHCHACHAHFBGGCCCCHCEFCFDCHDCHDFHECHACDBCBAEBDEBDGGEGHDCEGHECEECEEHBEHDFBFBAFHDFGFCG,False +403,14.0,14.0,19.0,22.0,20.0,22.0,14.0,19.0,ECCEDFDGEDEEBCBHDAFBAFAAECCFDCEBBEBDAHCADCFDHEBFEDFEFEGFEAFHAFHGCHEEHDDFEDFDCFDCFCBAHFAHFHHFBDFDDEHCGGBGHBAHCAGCEGAHBHCGCEDEFDFGDHGFCGBBGCHGHDDA,False +404,9.0,11.0,17.0,12.0,11.0,7.0,12.0,10.0,BCBDCEGCECEGCDCCDGGAHGEBGBHCFCAFHAFHADEAHFDHEBCCDCCDCBDHEDHADBAHCHDDGBEGFGGBECFEFEGBAGCAB,False +405,5.0,5.0,3.0,4.0,12.0,4.0,3.0,6.0,DBGAEGEEDAEHAEBBEBEEHFDCBEFGEFCAFCEHHAHEDH,False +406,15.0,17.0,23.0,27.0,15.0,22.0,16.0,20.0,EFCEGEFDBFHCCACBDDHDCFBHFHGFCECAEABGBGDHCDBCABGADFDDFECCACFAEFHDGHDBHDAHDHHDHBFEFDEADFADBDCHDEHFCHFGGFHGHHEAACAFCFBDDCEBCGBDGDEGDBGDHFCCFDEHCBBCBGDFGAFEAGC,False +407,11.0,16.0,12.0,20.0,16.0,15.0,13.0,15.0,HBGBDGBDGFGEFCCHCDHCDHFFCDBCFBEEECEFCEABEHDEDBEFHFDAFDBHBBHDACAHFAFBAEBDDDADDAFDGGGEEGHEGDFHBFHGDBGCBGBACDAHHCEAEEDHGF,False +408,16.0,12.0,20.0,13.0,15.0,13.0,22.0,14.0,HACHAGEAGFHHDDCEDCBFEDFEACBBFHBFHBCGBCACCBDDGDDBEFEGGHDBDDGGFHGAHFEGAEACDACGABAAHEABECECCECGGCAHFAHFGGFEECEHAFDGGGGCFHCGGCGBC,False +409,4.0,7.0,9.0,5.0,9.0,7.0,4.0,6.0,EFCBHCFAFFACFDHHBHCBGBBGBCEHGECBAGDCEFCDFCDEEHEEAED,False +410,12.0,11.0,9.0,6.0,6.0,6.0,2.0,5.0,DDCDHBBABBACFACEBDEHDHBFBAFBAGCAEAEEFHCBCCFHCAAEAABDABGFC,False +411,10.0,13.0,4.0,12.0,8.0,3.0,7.0,11.0,BBHBBDDDDDEEAAHAAHBAHGEHGHHAEDEEDACDBBDGCDBBABHHCGCFGFEGBAGBFDDAEHBH,True +412,2.0,7.0,4.0,0.0,2.0,6.0,5.0,2.0,BGBFGBFGBCGCEACFBHFEABHCBGFF,True +413,28.0,23.0,16.0,19.0,25.0,12.0,17.0,19.0,BHADEAEEHEEAGEFBBCDDAGHHGHAEBDFBAFBAHAEHBECBDCGDGBFGEEAEEDBDDBHDEHGECAACGACABCABFABCADEAHEDBCGFEBFEADEBEGADAAFAFHADBACHABHCCDCDBFABGAEGCGFHACDEGHHGHGDHFBHEBEGC,False +414,4.0,13.0,10.0,10.0,10.0,2.0,11.0,8.0,EEGCECCGBBGBCGDEEAGEDBHCHHADHDBHEHCFBDBGDBDDBDEADEHBCAGCBGEGCBGCBGFH,False +415,13.0,21.0,20.0,13.0,22.0,19.0,15.0,24.0,HFDBGDBHHBCCFHHFBHFBHFBHACEFEHFCBGBBFBHFDGECGFCAABGCFGCHHBHHEGFEABCBECEECGDCHHFEDAHBAEEDECDHDGHFGHFAECAFBAGBDECDCHBHHDCEFCAFEHEEGEAGEAFEDEBACBDCBGG,False +416,21.0,17.0,11.0,9.0,12.0,14.0,19.0,7.0,CGHHGBDBAGBAGBDGACGAHFFBFAGCACDAGAAEAEFCCAEFBCFGCAACGEFFBDAEDABDCEGEFCEBBHFBHEBHEAGGBGFAHFEBFBBDABFAGGAGGDGADE,False +417,6.0,8.0,8.0,1.0,1.0,6.0,7.0,5.0,BADAECHCCHCCHAAFCGFBGBBHBBGFCFHCGGBGGBFFAA,True +418,11.0,22.0,19.0,15.0,20.0,16.0,14.0,28.0,CCEHHDBHECHCGAGDCCABHFHHEHDEGBEGBDDBDEBHBBGFFCFFHBDHBCHBEHBAHFFGFCDHHDCHBEABHDBHCBAAEFDCBCCDFHEFGBDABGFBCADEFDGFAGEHGBHCBCGFAAHEEHEFHEGEEHEEHCGHC,False +419,25.0,19.0,13.0,15.0,18.0,30.0,15.0,15.0,FHCDCFBEHCABEAFAFHEFDGFDCDEHAFGAFBDBBFBBGBAHFAGFBFFBDBDDEGFBDEBHCBFCEFCEFAECAEFECGADBABAEHFDGFGGBGFBGDAAAHAAHDFHGCHFCAFEAEEDECDHBFAGHAGFEEFAFFAFAHCAHG,False +420,5.0,4.0,3.0,9.0,10.0,5.0,4.0,4.0,DEBDADFEFCEHEABEAEEFEDHGDHEDCFGCFDDGBDGBEAAH,False +421,21.0,22.0,19.0,21.0,16.0,23.0,24.0,24.0,BGGDDGBHHHHGHHDAGFAGFBBFGGFGEHBAHECFACAGHEFCEADEAEBAHBGBBACDACDHCDHCHBCDBDDGCFHHFHHAHEEHCGCBGAADFBGEGFCCFCGFDHHDHCBFDAADABBCBFCFGDECBEFDEGDEDFABFADFGBFGFAGFADHHEGABCFBGEE,False +422,5.0,3.0,3.0,1.0,0.0,2.0,1.0,4.0,ABCABCBGAHHHFHAFCAD,True +423,8.0,5.0,10.0,3.0,2.0,6.0,4.0,7.0,CAHCAGAAEDGFCGDCFHCAHCAHBBDFAFFGBFBBCCCHCEHAH,True +424,4.0,2.0,3.0,3.0,3.0,5.0,4.0,1.0,GDFGCGACDACDEBFEGHEFFAAFB,False +425,20.0,29.0,28.0,22.0,37.0,21.0,18.0,23.0,DCDEFDAGCHCHFDAFEFFEHDEDBEABEHBEBFCBEDBCDCCEGCEBCEAHDHHDAHGAHBBBFABFABACBADHEEHEEAEAAEACDCHBCEDEEBEGGEBEFDGCBBBAFDAFCAFCHEDBEDGECHBHGFGECEDGDFECFDCFGHECEEHFEBCABCADEAFEGBBHBFGBEHCCHBCGBEFCHHCHGGGGDF,False +426,3.0,6.0,6.0,5.0,11.0,8.0,8.0,8.0,ECEBAECEDDEBDGBGHDGEBGECGFHGFHACHFGHFCFBEFHHBHEADEFGCFE,False +427,9.0,21.0,17.0,17.0,18.0,17.0,9.0,12.0,BHBBHBBAFBCCHEBDECFECDEFFGHCEFCAFAEHDGHDBHABEEBEEDAECBDCECABDAFDHDGEDBBDBFAFFCCBHCDHDBFDGFGBFCHACDBCGGDGGCBFFBFEEFHECEED,False +428,13.0,9.0,6.0,7.0,7.0,9.0,7.0,6.0,HDAAECHEGFFGFGCFHCBGAADAADAAFABFBEEAFFBBCBBEABECGHDGEDGDABDAFHCH,False +429,8.0,15.0,19.0,18.0,20.0,20.0,16.0,22.0,FGDFDDFHDGAFGFHEBABCDBHFGHFCHACACCECEACEBCFGDBHFEHFBHGHHEHEBGEAFFHCFDEFDADDBDGHFBDFBCFBGAHFBECHECBECHECECCEDCHGEEGEGFDFEDBEHBHCDGDHCHHGGDG,False +430,13.0,25.0,20.0,21.0,26.0,17.0,24.0,16.0,EFFGFCDFCEHCGHDGEECAEBBEGBECFEGHAADDAFCAFCBCEECFFCFCAGDACHBHHBGDCGDGGDEEDBHHGCHEDBEGEECEEBEBBDBAEEFDGBGGBDAEDHEFCGBCGFCGAHGFHDBGGBFBFFHEHBCDBADCEDEBBGAAGHBGHBDBDD,False +431,13.0,21.0,18.0,12.0,10.0,10.0,17.0,15.0,GAFBBBBFHGFAFBGCGGBBCABCAGDHGDHBCHBHBAHGGHEGHDCDBCFBCGECAEDDHBAEBDHBDHBDACECGEGGDHADBEFCDBGACEAHBCFBEHAEHAFGCCGCCFFC,False +432,14.0,11.0,9.0,15.0,14.0,12.0,12.0,18.0,DFAFFAHDHEDFEHHEDHCFHCECBABBDGEFGEDCDCGDHHFCHFCGGCEGABGDBEABAAHAEBDEBHEGHFGHDHEBADGADBAEHCEHDDHBFAGAAFFGH,False +433,16.0,16.0,12.0,20.0,13.0,18.0,9.0,14.0,FDCFDADDBDDAHDCBDCDDCDAEHAFAABADBECFAFBCFADAGCAGCDBAFCFFEHFHBFBEHGCGGDFGDABDEECGGDFEFBHCBHBEHBEABEHBAHGAEFBEHHHFEHFDFD,False +434,15.0,21.0,15.0,6.0,12.0,5.0,12.0,17.0,CBBDBGABGCDGCEADBCCADEFCCAHCHCDHCAHCHHABHBBHABEFCGCBGAFAAHEAFGAEGAHGEEGHEGBFBEECHEBBAHHCHDBHBBHBBABBGEG,False +435,0.0,0.0,3.0,2.0,2.0,2.0,2.0,3.0,CHDCEDEHCGHFGF,True +436,22.0,21.0,21.0,13.0,7.0,14.0,20.0,13.0,BHBGDAADEDFGCFGDHGAGGAFDCCACCHEADBCFBCGBFABEHDCHCEGBGDAGAADCAHGHHGHFFDEHAGAGGABCAFAFFACHACGBDGBDCBDHAGCFEBFACHBCABCGFCAFGBEBBCBBCBB,False +437,18.0,12.0,15.0,15.0,9.0,15.0,19.0,9.0,BEAEFBCFAADCBFGDGGHFCADAADGADHCBHDGDBGDBGDCGAHEFHGFAEBAHBADGCDGCGFCHFDEFEHFCAAAFBAHAEGDEGFEDCCBCGBFGBFGACGCCADFG,False +438,9.0,15.0,11.0,10.0,6.0,5.0,12.0,8.0,CBBCECABBAHBHBCHGGEGGDAEBEDCDFADBGDBGDBGBBCDGABHCFGBFGHFGHFEAAEAABHDDCGCCDCH,False +439,21.0,34.0,13.0,20.0,9.0,14.0,18.0,22.0,DBGDFCCFEAGHBHHCHHCBHBGHBDABCCBAFBAGBDCBDBBGBAFFDHEHGCBACBAEFGHBGAFGCFBAGHAHHAGHGCDEAHABHBDFEDBDDADDHFBHFBEABEABADBHFHDBABBHBAEBGCDCFHGGGBBGFDGDABDABDE,False +440,5.0,7.0,4.0,9.0,2.0,7.0,1.0,7.0,DEBHHHHHHDFAAFGADHABBFFDFFDBEDCCCCFBDDBDAB,True +441,9.0,3.0,11.0,9.0,5.0,3.0,13.0,6.0,GCHGCHBCDDAEAHEAGAGGCGEAEHACDFBDBDGCDGDGGHGCFGCAHCACDGCAEFD,True +442,26.0,15.0,9.0,16.0,20.0,21.0,20.0,20.0,EEHEFAFDDHDDBDEEFFEDFCHFAAGHAEHADBAGHAGBADAAEABCGBCBBFGCFGEFGEFGHDEAEEAFHFGHDGFAGACGCHBCHEAHGABGBGADGFFGEEBCFDHAEBAGBADAABBHFHHCEEFFEDFHAHHAHADDGFG,False +443,5.0,11.0,13.0,10.0,14.0,14.0,10.0,14.0,FCEHCEHCEDGDBBDGEDHEABEFGAFGAFCCFHFFHFBAEEGDFFAHECHGCHDCHBGFEHFHFFBBCBBEHCHHBECDEDBEDCGGGDC,False +444,9.0,3.0,12.0,6.0,9.0,11.0,10.0,6.0,GACGCGACGBHABFCEFCEFCAFGFEGDCFBCHHHHGAAAEADCDGAGEEEEECFFCDFGDFCDFH,False +445,9.0,10.0,13.0,13.0,17.0,11.0,15.0,15.0,DGCDBCDFEFHEHHEDDEGCCFCFFCGDEECEFHHFAHFAEDGGBBGHHGCHGBACAAHEEHEEDGGDGGDGEEFEBGHBCDCAACAHDHBFEFCEDBHBBAG,False +446,4.0,1.0,6.0,9.0,11.0,4.0,5.0,7.0,GACEFGGACGDFDECDEHDEHDEHEEDAHDCDFCDBEHAGFCHEEHE,True +447,26.0,19.0,18.0,11.0,16.0,16.0,12.0,21.0,EEHFFHCBABHABHAEHAEHEFFGFAGHBHAEEAEEAGAAGCCGABDACECFHGHHEDHCBHCBHCBAGDABDCHAHEFHFHHDDFBFFAFCACABEDFEDAGDBFCBDAGFACEACAGHABBFBBEBACCCGHCDBAG,False +448,6.0,5.0,7.0,6.0,1.0,1.0,3.0,5.0,HADHAHCACGDGBDGBAECACBABDCHDBHDCCF,True +449,11.0,2.0,6.0,6.0,9.0,16.0,8.0,5.0,AGAAHAAGFDFEEFBEDGEGEEFEAFCCDEDFFGFFGFFCFAEFAFHDFCBHADHFGHACCAG,True +450,11.0,4.0,8.0,12.0,7.0,9.0,7.0,8.0,FDEFCADCGCEBAHBGECHEFHCDACDABHGBFFDFAEFAEADGADFEDHCAHGDHDFCDAGDAGH,False +451,31.0,20.0,20.0,33.0,22.0,23.0,32.0,17.0,BCCAGAAGFAGCEGDBGDACDHDHGFBGBBDBFGBHBAHECEECDEDHHDFADFEDCEGHAFBCCBFADGCBADDFEFGEHGEFGDHECAEAGEDDEBDEADAADBCBGEDHDDFCEAAHBGBGFAGFDGFDEFEGHBAHFAGFDGDDFDFABCABCAFCAFCAGCAHEGHGDAADAGEFGHDGCDGBGHCFAGDEGA,False +452,6.0,6.0,6.0,10.0,8.0,9.0,9.0,6.0,AFEABEBDGBAFEDHGFHGEDGEHCHAGHECHCCFDADDFEDFEBAGCFGFFGCBGDBDD,False +453,13.0,18.0,14.0,23.0,17.0,19.0,19.0,12.0,DCGDCDDCADEBFFBFFCAACDACDCCABCDDFDFAAEGFHFADCBGCDGEDAFGGEHHEFBFFBFFBGFCDFCGAGDDHDDHFEHGEBGHDGHAEHBGBDEFCBDDEABHAGEBEEBHEDEGBHGBFGBGEEGB,False +454,18.0,22.0,18.0,14.0,25.0,31.0,12.0,21.0,FHADBACFDHAHHDGHBFFFCFGCBGDHFFFGFFGFGGFAHCHEEHFHDFHFFHFAHAHEACEGEEBDEDFAFFBFFBFBEFDCBBEAEHDFDEEEBBGCBFCFCBGBBFEHGCDEHDECDECBADEAEEACEACECCABBECBECBFAFAGHEHHABHAB,False +455,8.0,7.0,7.0,9.0,13.0,7.0,12.0,7.0,AGEBFEADAAGFABFHDEAFFCGFDEHGABGCBHCBGBDHBDFDEGCEGCEDCEHEDHGDAGEHEEGCEG,False +456,26.0,25.0,17.0,12.0,23.0,17.0,8.0,10.0,BCAFCEBDBGCAAFAAFGCBEAEDDBADBADCHEFFEADEAEEFEEGAEGEHBEGAFHAFHDFBBAEACCAECBBBBBFABEABDBBDABDCEDFECACHFHAFHGHDCCAGFEEACEABFABFBEFAEBBGHBCHCC,False +457,17.0,13.0,15.0,8.0,13.0,12.0,8.0,11.0,HFCEBGABGABDAECBBCBBEBEEBFEAADACFHFEHFBACAACDAFHHFAHGAHAAEAHGHCGFCDFDAEEBDECCHCCFFGBEGCDFCBCAEDHG,False +458,4.0,0.0,3.0,1.0,6.0,6.0,4.0,0.0,FEEFEFFGCFAEAGCAGEADEFGC,True +459,21.0,25.0,18.0,16.0,17.0,17.0,23.0,17.0,HDAGCGGBBGBCEDCBBBEGFEGFEGFAFFCGFCBECBFFBEBBGBFABCAFAHEHEDHGDCCEAAGAAGBCGHCBHCAEDHHDFFDABEFECCABHABEDBEGBEGDGDFGAFEAGCDGCBHHDHCAHGABFDEADBADBHGAGAHFHGCHDB,False +460,10.0,14.0,5.0,9.0,15.0,9.0,9.0,8.0,EDEEGEAGEGBEDBDFGDEABFAFDAGEBBABDAGDBGFFHAEHDEABGBHABEACEFBDFBCHGCEBCEBEHHHFHCF,False +461,5.0,3.0,5.0,6.0,2.0,12.0,7.0,4.0,CEAFFGFFGFFDFHDFBDADACCGGCABAHGFBFFDGHDGHEFC,True +462,6.0,6.0,14.0,9.0,5.0,9.0,18.0,19.0,FGCDHCHHGHDGADGECGHCGCGHCEDGEFFHHFHFGBAHEFGBCGHFDHFHHCGHCGHEGBCCBDAHDHGBHACGCGFCDABDAG,True +463,3.0,5.0,4.0,8.0,5.0,3.0,5.0,5.0,DGAFBBFAHGEGGEGBECECCAHHDDDEDDHFDHBDCB,False +464,8.0,5.0,4.0,6.0,7.0,4.0,8.0,3.0,DACBACHAGHBEHDEFEADGGCFEDGEBGEAGBAGFDGFDAAEBC,False +465,13.0,13.0,10.0,12.0,11.0,18.0,10.0,10.0,DFBGFDFFDGBBBEDGEDBECEEDFHAAACAAHHHHHBGGAAAFHACDACEFFHFFHAGCBEFBEBAFGAHGDEGFFBFDBFDECCECCGBCDBFDF,False +466,1.0,7.0,5.0,6.0,4.0,4.0,5.0,8.0,DHBECBCDBGDBHDBHFHECAECFFGHDGBBGHCGHDHFE,False +467,8.0,10.0,7.0,7.0,13.0,10.0,14.0,7.0,GGBEGHAGEGBEDBCAFFBHEEAEFBEGCFGCFHBFEGFEBFHFCHFDGDDGHDGDCHAEGCEGAEDCEBAABABG,False +468,7.0,9.0,14.0,4.0,4.0,10.0,8.0,4.0,FECAECBDFBGFCCFECFDCBGCBGBFDAHGAFGBBEBCHBCAAHGAGCCCFHCFGCDAF,True +469,11.0,8.0,10.0,17.0,9.0,15.0,9.0,16.0,FHDFDDEACFHCFCAHDEHAGHACHDGBAGBEGBAGEHHDGHFEHADHAEFAGGCFECFBCDGDHHDADBCDBEDFFDFFCCBEDHFHAFHDFDB,False +470,1.0,3.0,1.0,1.0,2.0,1.0,2.0,3.0,CHADBEEBGHBGHF,True +471,17.0,15.0,26.0,18.0,19.0,21.0,23.0,27.0,GFFCCCHCDHAGAEGFGCBGCBFCFFHDFBDCHDGHFEAFEAEEAEGDHGHCGABGDCGDGGFFFACHBEAEEDEAHFAHDHHGCHFHHGGHBBECGECEEDAHCACCBBCFBCHGCHACFDCEDAHCAHFFFDABEEBCBAHFCHBHBGDGECGEHDHGDHGDFD,False +472,2.0,5.0,3.0,5.0,4.0,6.0,6.0,2.0,EGHFGBFEBFEDFHGCCFEABDADDBDGBGCFG,False +473,20.0,30.0,26.0,33.0,27.0,26.0,18.0,15.0,CGAHFAGFAFDBCDEGDEHBEGBEBFDGFECFHBFHBEEFEECCEFEFFHCDGAHABDFBAGBADBADBDGFGCDCABGAEGDDDDACFACEAFEBEGDCGCEFDEBEEDFEFFDABDHBDEBCHBHHFDDBCDFGDAGHBDABFBDDDFFBBACBCCBCABCACCHGCBFBDDEEBCGDCGDCEDCHFEHEAHE,False +474,19.0,17.0,14.0,18.0,11.0,17.0,20.0,12.0,GAGCCFFCGFEDEBFFAFCGDHGEHGEHGHGFDFAAFDADDADCACCBFBDGBGGBFEBCABDAGHGBDBBHFGEAGCDGFDCFCHFAGCBBABBABAEBCFCDEDHGHAEHAEDAEDGFDGDAHHAB,False +475,29.0,21.0,29.0,16.0,8.0,11.0,32.0,19.0,GGHBGAGFAHFBGAHFBHGBHGCEACHGBAAAFHHFHHCBGCGAHBDCCDGAAGHHDBDCBDFBDBEACAFCEDCBGABGAFEACGACGCCGBCGHAGADEAHGDCGCBBAFBADCGBEGBEGBAGCGGAGABCCHCDACGHDGEAHAADFCCHACDGCDGCDFC,True +476,1.0,0.0,5.0,0.0,0.0,3.0,1.0,0.0,CCCGCCFFAF,True +477,12.0,12.0,12.0,10.0,3.0,21.0,15.0,7.0,FDFAGACBDCBGCEFEFDGAGGBBDBBAFCADCADCFCGFCFFHFFHBFCCDAGAAGBFDCFCAFHDBBGHDGHFGBFBEFGFFAHGAGGFH,False +478,17.0,16.0,18.0,22.0,16.0,25.0,17.0,21.0,ACEFGEHAECACCHBGAFFBCFECADCEFAEDEFAECBCGBCHFGHGEBAEAADHGDGAFGDDCEHCHAEHDEFGHHHBHABFABFHCFHCFHCFBDFBHBEFFEDFCDBGDAFDGBHFBHAEDCFHBDDGADGDFCDFGDGBDGDFHDFHG,False +479,10.0,7.0,13.0,9.0,7.0,6.0,9.0,3.0,HGCDGCAGAEGAGCCBCCFCEFEAFEACGGCHDABDECHFABFEBEBADBDDBAACGCFDCDDG,False +480,1.0,0.0,4.0,0.0,2.0,0.0,5.0,0.0,GCEGEGGCCGCA,True +481,21.0,16.0,14.0,17.0,11.0,10.0,25.0,16.0,FDGEEGBBDHAHGDHBHGBGCBCCFACEAEGAHHDHBGFDGADAAEAAFHCFHDFABGCBGAGGADCHDCECEDBDACDAHDAGDBHHBAGFAEFGBFGBGHAGAAEDCBCEBHEGHDDBGGGGCAGCFG,False +482,12.0,17.0,21.0,17.0,21.0,22.0,20.0,24.0,HCBHEEHCEHCBHADGBCGBEEHHFGHFDHFCHCGHGGHBGCBCHGDDACDFFFFFGBACFECGCFHFAEDHDDBDDHDEGDECAGCAGHAEHAHFEFDEACCDGGGFGCEBCEDHFCHBHBEHDDABHFFFAFFBFEBEBBGAEGCEGCEBFE,False +483,19.0,21.0,17.0,13.0,22.0,21.0,20.0,24.0,GDGGEGFHAHAEHADHCEHDAACCBEFBEAAFFAFGHHBHDBFDFFACBGDDGDHHBACBFDHFDBFEFFGABDACDFFHGFCCAEBBHGBHBBEBGCDGCHGCHEFHEAHEHHGACCACGAHHEBGECGACFEEEBEFBCFEEGEHGEAGBFHBEB,False +484,14.0,17.0,19.0,19.0,23.0,9.0,30.0,14.0,DBADEECEEGGGCGGCHGAEDCGDCDDHDGGDEBHBBCAHHADGGGEGCECCACHAGHAEDABCHGGHAGDADBEFHHFBCEAGAGGDGGHGGACFFBFGCFGBBDBECBEDBGFEHDEBDEFHEBCEBAEGEECEGBGFCDECD,False +485,23.0,20.0,17.0,18.0,15.0,7.0,16.0,20.0,ADAADBBFAFFAFAAGCDHCHABGABCAGHBGHCAHEECBECGDHHAHDEFBGDGDBGDBAAEABGHBDCECCBGGHCEHBFABFABCACAECBCDDCBEEADEADHHDHDDGEHGEHGEDCBDCHAAGGBHHBHE,False +486,19.0,15.0,16.0,14.0,11.0,13.0,25.0,19.0,GDCGHFGHCBDBAAAAAACAGHBGADDCCHEGBCBDAFDBGDBDEAAGAHBAHADCDDEHHFHEAGCGGCGGBGHCGCBGCBDCGGGFEGBEDFHCFEBFEAFGAEGCFGCFGDEGAHFEHABFFBHHHHHH,False +487,17.0,28.0,19.0,19.0,12.0,13.0,19.0,22.0,DBDEFAHAGFBGHEGHDDBBEBHEBHDCHFEHGEHGBBACBAGAAGEBBHBDFBDFBDCCHCCAEBGDGDCEBCACFAEGAHDFCCBHCEHDEGCBGABGBDFHCFDDFDBFGAGGFHBCHCABDABHAHCAGCHGBBBCBHFDHADHG,False +488,11.0,5.0,10.0,9.0,17.0,10.0,8.0,12.0,HFEBAGAEFADDEHDEHAEHDEHAEDEEDGBCHCFECFBCHGCHGEDBEABGAHFAHFHEEGFHACECCADEDCEFCAFGFG,False +489,15.0,27.0,19.0,19.0,24.0,16.0,18.0,23.0,GDHCDCEEBEBBHABHFBGFEGDDHDFACCAGGADEBDEHABHAFHGBHAFCAFCBFCFHCHDEHDBBFABDEGCECHDDDDGEAGHAFHFEBBEAHCAHFGHABEFEHDHHDCGBEHBEBCCBGDGEBGEBEECEGBECBEBDEBFGHABHFFDGCCGBC,False +490,3.0,2.0,6.0,3.0,7.0,0.0,1.0,4.0,CBCEHEADEACEADEDBCGHHECHEC,True +491,14.0,16.0,16.0,14.0,17.0,13.0,22.0,10.0,FADFCGFCEFCEBCGBCBBCBBAFBGGBGBEEEFDBBDHEEHGHAGHAGDDGBEAAGDFCHADHGDHGHFBDEDDEFECCEGGGGGADGCBEEHDCGCCGABHDBFAFEEECCAGAFGAFCA,False +492,26.0,18.0,20.0,24.0,26.0,19.0,29.0,28.0,DCADFADCEHGDGGFGEAHEHHAHFCCCGHBAHEAECBBGGBHGBHDBAAFECHEBHGFHCAHDAHDAHACHCGHCAAEGGGDBGDGGDEGHHDCGEEGEDAEDCGFCDFEFFADHGBCABHDBEGBGBHCHFGDFEFFEBBEDBEAAEFEBFGBAHAAHECDGDDFDACCAFAEHGEDGEDCEHFGHFA,False +493,1.0,0.0,2.0,1.0,4.0,2.0,0.0,0.0,ECEECEAFFD,True +494,11.0,16.0,14.0,24.0,25.0,15.0,20.0,16.0,HFCEDHDDCEGCFADBEDCEDAFBACGFFGHDDDGBDFEAFCAFHDFHEFBAFBDEBEHCEDBHDGHDFAEFCECCBGGBFDBCDHAHBGEBEEHGGHABDGDGGDHADGAEEBFECEECGEGGEBEEBHGCHGDHGDEDE,False +495,15.0,21.0,13.0,15.0,18.0,25.0,20.0,12.0,GFGGDGBFFFDCCDGCDECAEFFFHCECCEDEEAEEBEFHDHBGGBGGEGHAGEAGBGEAFAHFACFCHGBBGBBCCDEGDFFFFABBBEBDAGDAHFACFAFDABDBBEFDEFAFBBFBBFEHHGHDDHBFGAFHEGC,False +496,14.0,17.0,8.0,12.0,24.0,10.0,23.0,11.0,GBFGBDGAFGBGEBFEHDGAFEBCGGGBABDAEDGEFBAFHEFHBFHEEBGEBAEGGEFGEABAHBGHBCFGEGCAGCEHEGHDDEBAGCAGBECDECDEGDEGDBDHEEHAEHDCAAE,False +497,8.0,11.0,13.0,8.0,7.0,15.0,9.0,16.0,EHBHFAFCAGEGGCCGCAGBAGHDFFCFHBHHDDHFCAECHDBHCBHAFFDFEHCGDFGAFCAFCGFEBBCBBCFHDHEDHFBHEBH,False +498,3.0,6.0,8.0,3.0,3.0,7.0,4.0,5.0,CHECBEABACCGCBGFHFFBGDBFDAFDEFCGBCHFHHC,False +499,7.0,4.0,9.0,5.0,5.0,8.0,3.0,3.0,ECEEFHFFACFAHAABEABDCCGFDGFCCFCCFGDABDCDEBAH,False +500,7.0,8.0,5.0,8.0,4.0,3.0,2.0,4.0,CAEFHGBDDBDDBDDBCGBCFDFDHCAEAEHBEABAAHACB,True +501,22.0,26.0,22.0,26.0,16.0,25.0,21.0,27.0,EBHCGHBFHBFBAEEAHFAHEADFGDFBFHCHCCHGAAAAAHAGBBBDBCHCEHBHHGDDFBEFDECDBFFHFFDDDDDFDAACHBDABDHGCEGCGHFGAFDCFGCFGBBGFACDAGHFGHEEAEEAHHBDDAABBCBCDDCDCGHFGHEBHABGFCGCEGCBCHBCHDGFFBFGEFDEHDBAD,False +502,10.0,11.0,12.0,13.0,8.0,15.0,13.0,13.0,GFHHEHDCHDEFDADGCDGBDFADFHFACFACACBFCGFCAFEECBECBACAFDEHBGGAAFDGHCBDCBHGBHDFHDHGEFGFHGFHDBEBGGB,False +503,5.0,6.0,10.0,4.0,4.0,8.0,9.0,0.0,FEDCEDCGBGGBCFCFEDBEGAACABCGCCGFFGFFDAGGBCABCF,True +504,7.0,14.0,10.0,11.0,12.0,9.0,6.0,15.0,BDBBGBFCEDCHDCHEFFECHGDEEHEDHDBCDHGABFABFBBDBBCEECHEGFAHCGFBHFAHFAHDCEAHBDCBDHGEHAEH,False +505,21.0,9.0,16.0,11.0,15.0,16.0,15.0,15.0,DFAGEAGEAFCCECCECFEGFHGDHAFBCHEDHEHBEAGFCHDHGAHFFCAAGAAGAAGAFEDGCDFHGEHFEDFBDCAHGAHBABEABGABEDFFHGFCEACHADEBCCBGFDCCHA,False +506,17.0,15.0,12.0,11.0,15.0,5.0,18.0,14.0,BHGDHFBGBBABHAEGAEDAEAEDBEDGCGHADCFEHAGHAHHAFADCBBGEGGBDBBDEHHHGGBGADGACHCEGCEHAABFAEHAECAECEECFBCGDCGBCGDG,False +507,23.0,16.0,18.0,17.0,15.0,30.0,19.0,16.0,CAHCHFAHFDGFDGEHAABDAFCAFBAGBHGHCDBAAFGFFGADAHDGDGGFEDFEDCCCCDHGFFGFFCHFAFEAFEFHGBEFEEFEECDBGGHHGHCEHEGCADCEBAFBFDBGBCHBFFBFFBCDBDGAGFABEAEAAFFCBFCADCADHA,False +508,2.0,2.0,6.0,5.0,8.0,2.0,3.0,4.0,AECAHCEDEEGEDCFFCBECDDGGDHECHEBH,True +509,10.0,15.0,13.0,10.0,20.0,25.0,8.0,14.0,BFFFFGHDGHBEECGECGEHFEFAGBHGBEDEGAEAHHFFHCFCFFHEFADFBCEHCEGFAHFHEFECBDCBDABDCBFCBDHBEFCEFCHFEBEBFEAFACFHFBAFEADDDBE,False +510,9.0,6.0,15.0,8.0,8.0,15.0,8.0,4.0,CGFCHFDFCDFADGADECCCFCAFBFFCCFEGFDGFCGCCEBBEAEEAEFGHDGDFCHFEFAGDABBCBCAHA,False +511,1.0,1.0,2.0,5.0,3.0,1.0,4.0,3.0,GDDGCBGCHDEEDHEDFAGH,True +512,16.0,13.0,8.0,20.0,20.0,20.0,19.0,18.0,GEEGAEDHBDFBGBGGHGEEDHEHEGFEGBEGFHGEDBBAHGFDAFDAEDGFFHFFHEEHDEHDGDGADCADFADABFHDFCEFCHFDGAGABHAFHGHCBFCHEHBEAAEAAEBCEDFGABDCHFCBFDFDDG,False +513,2.0,0.0,0.0,0.0,3.0,1.0,1.0,4.0,HHEHHEAGAFE,True +514,16.0,32.0,27.0,32.0,20.0,18.0,31.0,18.0,FFCEHGEAGHCGDDGHDFEDFDDBDCHDAABHAGDEGDEGEFCBDAEABBAGBCGHEEDCCBCCAECAGBDFBCHGHHDHADGGGCCFFAGBGFDGACBHCBDAEDBEDAGDHCDGCEGFGCEGDADDCHBGHBAHBEGBEFBFGBHDHGEBBDBBFCCCDEBDFBDBBGFBGFBGFBGFHDBCCCEBCGDCED,False +515,26.0,15.0,26.0,29.0,17.0,18.0,23.0,22.0,GFHDAEAAEGAEGCEDCDDCAHCABBAEBECGEBHHGAADFECFBCFECEDGDDCDCGDBDFGCGHDAHFADDAHCADDGDFGDEAAGAFDHGCHDCBDCGCBGCBFABGAHHBHDFHDFDDGDCFFAHBEHECCFCBACHACEGCEHHBHFGHCGDAGDAGECBFHAAGFFDEAH,False +516,12.0,12.0,20.0,17.0,22.0,17.0,13.0,11.0,EEBEADDAFDADAHHEEBGEBFFBEBCCDFCEFCEFCEFCABEFHEFCEFGFCGCGHCHDCGFBECACAGDAHDGGDHFDHADEADBFHBFABDHECFDCHCEGGDCDDCGBEAFEBECGECGE,False +517,17.0,18.0,11.0,13.0,13.0,9.0,14.0,20.0,BEFHACHEDBAAHAHHAGBAGCGGHAADEHDEHBBHGEHAEHGEDGEBCEBCHAAHBCHADHCDBGFBGHAABBFFFCCFACBGDBGDBFDCFDCBEHFHHEGBADEDHEGGABD,False +518,20.0,13.0,17.0,15.0,17.0,19.0,27.0,13.0,CFECBCGACDECDHCHAGGAGGAGGAGEAGHBGFFGHHDEHDHDDGAAGDDGDHBEFDAGBABEECEAABAAFAGFGDFCDCEFGECBCGGEGHEGHBGEFHFFDCCAFGAFEAEEFCFACFGBDCBCAHGBEGFDFHBFB,False +519,4.0,10.0,8.0,8.0,7.0,6.0,3.0,5.0,EABADFAHCBFGDFCDCCBACBEFDGBHGBHFEHFECEDHBCCBEDBEDBD,False +520,21.0,21.0,12.0,9.0,4.0,4.0,12.0,8.0,FAACBBBAABGAFADBABBDBBABHACGACBABBHHCECAACAHGDHGABCBDABAGBDGDAEDGCDGCABFEHEAHFBHGADGCCGBCGB,True +521,7.0,6.0,5.0,6.0,9.0,6.0,4.0,9.0,HDFFDAFDAFBFEAGABCHCHHBFHBGEBHEHHEHEDAECEEGACDECDBGA,False +522,7.0,13.0,6.0,12.0,9.0,15.0,17.0,9.0,FEHCDBCDGGDGGDHFBHAEFDEFDFGEAABAFBHCBEFBACDGBDGHHBFGDFEDEEGGBGGBHGFGFEGHCFBFFBGFGHBADCAD,False +523,13.0,18.0,26.0,23.0,24.0,18.0,20.0,22.0,HDCHAFHBBHAEFFCCGDFGAFCFDBHGFGEFBEGCEHDHHEGCEGEDBDDBGAFHCFHCAECHBFHADHFDHECFBCBBEEDGBCGEEEDGHFGECCECDACDGFBCACCDDGDDEBDGBDGAACABCABCFBEFEDHEDHDGHEFHECDECGAHGEHGCCBH,False +524,23.0,26.0,27.0,25.0,18.0,14.0,25.0,20.0,AHEABADDECBHGBEGDCHHCEDCECAFCACEFEEGGDGGDGEDGCFBAEAHFGDFCACHEBDDBADBADBDDACFAFAGCBBHBGGFDBFDGAAGAHGDHFBEEDCCDCBACHHCHECFDDHABAACAAGHHGBGGBGFBGFHDCBDCBHBHHCDFCDEBGHBGACGCCGECBBBEE,False +525,9.0,5.0,7.0,9.0,10.0,14.0,16.0,12.0,GDEGFEHFGFFECEBCBHHAHAGHAGDFCDHBDAFFFGFGGHBDHFDCFDCDGFEGEGCEGAGAAHAGEGHEHFEHFGCDBA,False +526,21.0,20.0,28.0,24.0,24.0,22.0,22.0,28.0,FBFFHFFDFEBCDDDFBEABCGECGECFHFFCFDAACAAHAHCDHGHHFHCBHBDHGDGDHAHCDHGABAABGCGAAFBGFCDFCDFCABEHDEAGHABHEBAEFHCAEABHGHHACFEGEEFEEGDFGDCCDCEDHHGBHGEHGECGDHDDAFCEBDHBGGECBDCBGCAGCEBCECEBCEHCDHEDF,False +527,20.0,11.0,8.0,13.0,17.0,8.0,13.0,14.0,DDHGDHCDHDDHEGFEDECAEHFFHAABEGBEHBCAGADGACFACECDEAHGABBCEAAEAGFABAABAHGFHEEGGDCEBAFGFHGAEDHEDHEABEABDHBG,False +528,9.0,13.0,8.0,10.0,8.0,6.0,9.0,7.0,ECDBCHEGHFFBEDBGDBHDBHDFHFEBBCDFDACACCBEHBAGBAGFDGADGACHABDAEABGGEGCEB,False +529,2.0,5.0,6.0,3.0,4.0,6.0,5.0,4.0,FCBFCBFCDCHDEHBFGFFGAEAHEGBCGCHDEBG,False +530,5.0,3.0,3.0,2.0,4.0,2.0,5.0,5.0,AFBAEGACGFGHCEHEBGEHGHDAHDACB,False +531,14.0,18.0,15.0,23.0,16.0,17.0,15.0,32.0,HBAHEDHGDHCDHDEHDEHDEHDHFAGADFEEHBBDFHDAEDEEHHHBHDFHDFHCFCFECABGGBEGCEBFBBDBDCCHCAACFACFHEEHCHHDHGFHGFHDCDDBEBGHAFFCGBAEBAHBGHAGFBGAHCFFBDGDCBDHGHGDHA,False +532,8.0,6.0,17.0,12.0,9.0,14.0,14.0,11.0,DEGAFHFDCCDGCHHBHCFDCFDCEGGFHHCAGEGBFGBDGDAGHCGCCGDCHDGEDBEFFCFDCGHCEHEGHACCAFAFFDFFAEBAEBC,False +533,15.0,11.0,12.0,12.0,16.0,22.0,21.0,18.0,GAAFFACGGFHDCBDFBAFBAGEAFEBFGGFDDEGFEACHFFBDFGEGDFFAHFHHAHHEHHFHFABECBDHHDCHDGGDGGEFGEHACGACGECEECEEBDBHDHHFHEFGGCABCAFEFCGGGBA,False +534,6.0,6.0,12.0,13.0,5.0,12.0,12.0,8.0,HDGAGHFGHFCHABHFEHFACCCBCEGCGDCDEADCFDHGDGFDGFBGCDCHFFEGFAFDDFDDGADCBECBGB,False +535,22.0,16.0,25.0,15.0,17.0,33.0,16.0,16.0,FBFFEECEEDFEFEEBGGDGFEAAEFCGFDGHDGDEGAAAHACFECDACDCHFCHFAFFAFEGFBDFECHHBACBCCACDAGFGDFEDFCCFHCBCCFACAAGADGHEFFCBFHDFCDHBHGECAFFGBGBFGAAAFBHFHHFEBFCDFCBACBHCBHAB,False +536,20.0,17.0,26.0,15.0,22.0,17.0,17.0,16.0,BHHBAFEEFAEFAEDBBDFEEBCEHHAAHAGBDGBHBECECCBFFAFEACEGCEFEECDDDGBDABEEBEHAAHCFCCEACDAHAGHBGFACFHCGHCFCCBCFGHDHCDHCDGCEAHGAFBADGGFCBFCGDCGCCFADECDGGEGAEB,False +537,13.0,10.0,5.0,5.0,10.0,8.0,9.0,7.0,EADEDEAAGAEEBGGHHBFFBFEBFBBDEAHEABCAHCAEFAGDAEDBFFGFAGAHGCHGHABCGBC,False +538,10.0,10.0,16.0,12.0,12.0,14.0,12.0,13.0,DFCGBCDFCDGBDCFCFFCFDAHDCBECEEBEDBEHECFECGAHGDHEAHAHHGFHGDHFFCGGCEGFGGCGCAAHHAEHCBDFBDEBAFADFAEBCBH,False +539,2.0,2.0,4.0,2.0,0.0,2.0,1.0,0.0,ACCFCAFCBDDBG,True +540,3.0,8.0,6.0,4.0,2.0,10.0,5.0,6.0,FGBFBFDBFDBFHFFGCEAFHCCBFCBECFABGDGHDGHBHHAC,True +541,4.0,4.0,3.0,5.0,9.0,9.0,6.0,7.0,HHFDFBDFAFFAEFEHGEHGEBGEAHFDEBCGHGGFEAFDDHCEBCE,False +542,1.0,6.0,4.0,1.0,3.0,1.0,2.0,0.0,EGEEDACCFCCBBBBBGB,True +543,11.0,8.0,11.0,8.0,8.0,12.0,13.0,10.0,CGFCHFHAFHGCGCCHCGHGACBDDBCDFADFADFBBEDAEGACFAHHGBHGDAEFGEAGEABHBGFBAEEGEHDFCGFCF,False +544,1.0,2.0,1.0,1.0,0.0,0.0,2.0,3.0,GDAHBCHBGH,True +545,20.0,18.0,24.0,26.0,24.0,22.0,18.0,33.0,CBHDDADAHFAEFCEHCEHEBHCBGCHAAHAFHFFEAFDAFBEEGHAGDDDACDHCEECEGDEGDEGBADBEDBAACEECHFBFCHFHHEEDBHHAEFCCHHFDBFDHCHHAHHAHGCHCCGFCGBGGFGDFBHFDGGDCEDADDADCFBCHBCBFHEHBEGAFHCCBEFFHDHGAEGDBGDEHD,False +546,29.0,23.0,21.0,19.0,21.0,27.0,25.0,20.0,BHEADFCDFGBFAFFACEAGFABFACFACFHEBHBFHDFGEGCEHCGDCDFCACAGDEBDEFAEFGEGGHCEHEAFEGECAAGAAEFFFFDFGGGCDGBGEBGHBGEBADFGCAGEADDBDDBACCCBDBBHAAABAHBACGECDDHGHHGBFEACHBFHEDCFDAHEAGCBGBAHFAHFBHFBH,False +547,8.0,14.0,13.0,15.0,21.0,12.0,10.0,20.0,CHCHGGHDDADDEGDBGFHCBECDEFBGHEECEGCFAEHHEHHCHHCHFFAAEDAHDEGBEHAAGBEHDEDBCFFEFCEFCHHEHBEHBEHEDDEGDGABCEBDBBCBFFBDF,False +548,5.0,4.0,1.0,2.0,4.0,2.0,2.0,2.0,ACBADGEEGEEBAFBFHDAHBA,True +549,14.0,13.0,9.0,11.0,17.0,24.0,19.0,14.0,EHAEHGEDBEDCEGGEHFBFBBGBGGFHAFHBFEACBACEADGFEACGFEGFADHGDAGCBGHGCFEBAHBGHAHADDAFDHGGHGFFGFFCFFEAFEGEEFFHFDBBDCBEHFFDFAEFC,False +550,8.0,20.0,16.0,21.0,30.0,20.0,19.0,15.0,FHEAEECEEGBBBBBHBBDDCDDCDBCBFFEGFBCEHEEHEEBEEHFDCEECGBBGAGAHCAFCAFGDEGCEFEHCDBEDHGCGFFGEEGEECBEFEHFHCDHBDFDDGGDHEFHGDECDEHEGACFAFFGFBGBGAFGDDDDDBEFBH,False +551,8.0,3.0,13.0,5.0,6.0,13.0,5.0,7.0,BDFEDFGCFCHFCGCAFFAFFHFGCAGHAEHCBCCEHCHDCADCFFAEFCCDHGEFAEBA,True +552,10.0,10.0,17.0,16.0,16.0,11.0,4.0,13.0,CABEDBDDCCDFHBACBAEEDFGACHECHECEDHDDBDDHAHCBHEFHEFHEDDGACAECHEFBEFDEDDHCBHCHFGBFEBDCFACEGCAACFCEF,False +553,29.0,25.0,19.0,15.0,29.0,33.0,22.0,26.0,EABECBEDDEFBHACGBHHEHFFAFFEDBAGFCHDGEDEHDGDDCADHAFFABHCFEEBAECAECHHHACCAEABEABCCECFECEGCHGCFFBFFBEFDGGAGAECHEHHDHHABDEHAEFFEAFAFFAGFHGEAGFFGFAACAEFFEGBAABFGBEGDFHDFHEFBBHDHHGHBCABABBFBBGBGGEAGBFGCFH,False +554,19.0,13.0,14.0,11.0,11.0,13.0,12.0,8.0,ABGABGBBFEBEDGCDFCEAGEAGHAGFAGHACHCDHADCADFGDCDDAFEGFEDHHAGCGCFDEHBEFCFFCFEABGABFCHEBABBACADEAFBABACC,False +555,4.0,7.0,2.0,2.0,5.0,4.0,2.0,1.0,ABBABDFBHFBEFEGBAGEAEEFDCCB,True +556,33.0,24.0,13.0,22.0,28.0,22.0,18.0,30.0,EEFABBCDBADEGEHHHCAHGEHABDDBDAGAABDGBABBAGBEBHEFDEDCHDAEDBFHEAHFAHFABFCBEHBEHAEHCHHFEHBEHFEFFHAFHAGHEGDDHBCEDGAFGECHHDHFAEFAECAGAGCEGADDAEBABAAHHAHGAHFEEECAACGFCDFDDFAFEBBGHBGBAFBEHDFGDCGDFA,False +557,21.0,20.0,17.0,15.0,9.0,13.0,11.0,17.0,FFFCCBHDBHDBDDBDDHDCGFBAHBHCCDAADHAHHADGADCCHBCFECEACECCFDABDCEHEHHEBHDFFABAABAGBEGAHGACGCGGFBBHBAFBABAGHAFHFGCGDEFBBCABAAE,False +558,17.0,17.0,12.0,11.0,13.0,15.0,10.0,21.0,AACABFAEFAEGCEBAFBFHBDHEAHEBEEHDHHBHCBFGAFGFCACBFBDFADFCDBHHBHDACECHHDABGBBGFGHDACEBCEBCAFHDEBDCAAHHFHHFGHEGAEGHFGHD,False +559,14.0,31.0,29.0,20.0,24.0,28.0,19.0,25.0,CBHCBFCBGABHAFHAGDBEEHABFAEDGEDECFFCBFDFFDEAEHDDCECEHCBACBDFBCEECGGCGFCFHEABDABDGBDAHFHHGADGEFHDGHEFHEBBEBGCBFBBDCEGFFAHGBHAFFGFFHEFHCCHBBHFEHGBDDHCBCFBCFBCADCDBCGCCBBCBECGDCHDFHBGHFGFCEEHEE,False +560,11.0,11.0,9.0,9.0,7.0,8.0,12.0,11.0,FDCFDGECEACDHCFAFGAFAFECFCHECHABHGBHBBHBGEGGAGGAFDBHDCHDBEDGABEAGACHBHDBDABGHG,False +561,17.0,20.0,22.0,24.0,12.0,25.0,33.0,19.0,GFGGFCGFGDHGBCGHGHHGHCGHDGCGCDDCHGCFGFAHCHFDFCDEBDEBGFCEFCFFGAFCCGCHACBFDFGEEBBDDBECAFGAFGADGADGDDGADGFDEBDBBDBGCAGHGGDGGBBDFHCCDCEFABHHBHEEHBDHAFAGEAGDABFAHHAFBFGDCEBCBFFA,False +562,11.0,10.0,11.0,8.0,5.0,15.0,7.0,5.0,GBAGDDBFDHFDGFAACAACBBGFGEBGFFCFFCEFBEFBCBACFFCAHCAHEEDBAHFCFFCDDAGCAHDB,False +563,20.0,11.0,17.0,13.0,14.0,9.0,14.0,23.0,BAGDHGEHCAGCGEFAEFBCCHCCBDADHBDHADHCGHAGAFEAHHAHHACGCEACAHCDHBDGGDFEBFHHDHHCAHGAHFEEDGFDECDHHEHACFGHFECEGBBCAACAABDABEGBE,False +564,25.0,13.0,20.0,11.0,13.0,16.0,8.0,5.0,AAAAFFCFFBBFABDAGEAGAHGACCFEFGEGAEAACACEFCFFCDCHFBBCBCCADFBHFDCCBGABGCBABBDFACAAFGACACDEEDECDBDAEDAHDAECAECEEHF,False +565,28.0,15.0,20.0,25.0,16.0,15.0,18.0,16.0,AADAACACCACGGBEGAEGBEGFHCHCCEBCEBDBBDBCDAEDEBDABDFFHHEAADAHHGHGBDGCAGFADAADADFHEFHFGDEBDFCAFEHFBBFDHCDADDACDHFHAGCGDAGCABADCADEAGEGCHDDBDCAGFHGHCGAEFFECE,False +566,7.0,8.0,2.0,9.0,6.0,8.0,0.0,5.0,HEFHDFDDHDBEDBEFBDBBECBAFBFDAFHAFEDDBCEAAAFHA,True +567,12.0,8.0,8.0,9.0,5.0,12.0,6.0,5.0,DADDAGBGGBCHFGFDAFCACAEFADFGBFABCDDFEDFECHECDBAEAHCAHBACBFFAFFBGH,False +568,27.0,25.0,25.0,24.0,19.0,25.0,34.0,18.0,GGBDADGGGAGEFFECFEBGEADDADDAFHBBHBCFBCGGEGEDHDHBDFBACBGCFACBCGBEGHHGCAGHGBAFAHHBFHAFECHCABFGHCDHEFEFCEDCEGBGGDAGFFGFFGAFBEFEAFEGFDBFCAGCAGCABAHHHCEACBGEBDEAACCFGGFGDBGDCCDBEGBCDFADBAGBADDADHCDHCDGA,False +569,17.0,19.0,19.0,27.0,20.0,24.0,19.0,16.0,DCECCEHDBFDEDGEAGFGFBCHBCAGAHGFDAFDBHAGEADCHDCDGCBHCEFCHFCGFAADABFABFEECGFHHDHBDEBDBCFEEFEEAECGDBFCBDHBDEBDAFDAHCGDEBDEHDFADFDDFGAFEFCAFHDBEBBDGGACDBCHGFFGFGGEGH,False +570,14.0,23.0,26.0,22.0,21.0,32.0,13.0,35.0,DEACHFHFDHEHFCHFCEFBFHBECFECHDGEDFFDEFHFBCCACCHGDFCHFEHCAHCHHCEHEEHCHHCAHDDGFBHCBEAGGDBGFBEHBHFBADBFDAFGGGABHAGHABDFBFHCFDCFDHEHCEAAEGCBGDFCFFEFDBFBBFBCHBHDBEDHDDBAFFCFHAEHCEHCBHDBCDEGFH,False +571,12.0,18.0,32.0,29.0,10.0,22.0,15.0,20.0,DAHAAEGCCHHEBCEBHDDGDDFFCCCCCHCFHDDHDHADBEFBECBCDBCDFEDGHDHCECGACDAEGGDGDBFHCFDGDDGAEFDCFDAADAADHBCBBCGEDBBHCFHCABFDHFBFCBCCBCCHCFFDGCGGCHCBFDFFDFFCFHHBHGFCGD,False +572,19.0,12.0,16.0,19.0,24.0,11.0,17.0,21.0,AEAGEAEEBDEGDECBBDAHDAFECHEFHGFGGDEHDECGGCAEHEHHCBHDDHDEGCEGAHGFEGEEGEECFADFEDEGCCABAGBAHAHHAEHACACHAFHBCBBAEAFBHDDADDGDBFHGCHFCHCCGFDHDDBE,False +573,5.0,2.0,3.0,2.0,1.0,4.0,3.0,2.0,ACEFDDFABGAGGACFAHFCHB,True +574,17.0,18.0,22.0,17.0,4.0,9.0,12.0,14.0,CCBCGGAHDAEDBCFCCHCFACFAEDAHDAHGBGDFDDCACAAFBBDDBDBBFCBECADDACBFCBHCHHABCAHGBBGBADDACHAGHDGHDHBEHBGBGGCFDAGCCCFHC,False +575,13.0,19.0,23.0,32.0,16.0,20.0,25.0,19.0,GGDDGDDCHDBGDFDDHBBHGBHBFHCEAFEHFGFEGEGGDGDFCHFAEFBCFGHDGDEGDBHDAAGHDDADEBCEGCEFCEFEDBACHAHFDEFCGFGHBBBABDCBFCHDCFFCHDDGDDGECGEDAAHAADDAFDCGCHBCGBCEHDEGFFHBDCBDBGCCGCC,False +576,9.0,9.0,12.0,4.0,5.0,6.0,12.0,11.0,BHFCHFGHEGHBGEFHADCDCGGCFGCBDABAEBACGHEGFBGBAHCDHCGHAGEAHHCCFCBGABCA,False +577,6.0,7.0,11.0,9.0,9.0,12.0,13.0,8.0,EDDGBABEGCGACGECECCBCCHGEFDEFGGFGBCGDAGHGCHBFGBFDEFCFFAGFDHBDADFADFHHFHEEHC,False +578,0.0,1.0,2.0,1.0,0.0,2.0,4.0,0.0,GCGDCGFFGB,True +579,5.0,1.0,1.0,3.0,1.0,1.0,1.0,4.0,HGAHAACAAEHDFDDHB,True +580,23.0,6.0,7.0,14.0,17.0,10.0,20.0,6.0,EEAEEHDHGCBEABGFBGEACAADADGADHCGFGGEHGAGGDEAFEAGEDEAAAAAAEGCFGDFGDEGAEAFBAHBAGDFGDFECCECGDBAAGDEGHAFDDF,True +581,26.0,18.0,18.0,18.0,15.0,22.0,19.0,23.0,FFFAFECGECGHCGACGACAFFGHGEHADHFDHBDHCACGABGAFHHGAFGABDABAFBHEBAEAHFAGCAGCGFAEDGHFGAEBAEHDDHBDFAFBHDBFCHEHHGFDDBAEHAECAHGHECDFDDHHBFHBFCBADFFDCCDBCABGEBCEBDEGAC,False +582,21.0,17.0,16.0,25.0,18.0,9.0,13.0,8.0,GAHDCGBCBACDDBDGADCEDBFDAFDADEAEEBEHADFAHEGDBGFHGHCBAAHDEHEEACDACDECFEAHAGGAEGAEFADBGEBGCDDCFDABDCCAGBADBDFFDGDECDBCDCCEEBBEBBA,False +583,3.0,13.0,7.0,7.0,6.0,7.0,7.0,14.0,CGGBGGBGFBHBBHCAEBHEBHFFFDFADCDBFEBGCBCHHHDHHDBHEGDECBAHFDHBEHCH,False +584,19.0,16.0,23.0,16.0,22.0,21.0,12.0,29.0,CGHFFHFFHCFGDFDEECFDCDDABFAEAADFBEAECAEGAECHHCHAEHFECCHGCHGEGGEDHBABFAHEEBGEHHHBHHCDBCDBADCACABCBCCBHBGHDFHBFHCABGDCFCCADHAHHEHHEHFEABEGGAFDFEEFEAFCDDEHFBHCHF,False +585,5.0,14.0,11.0,11.0,4.0,5.0,12.0,10.0,DGDBCBFGBDAEHACCEHCDCCBHFBHFBHCAHGGGCGGBGCBEDBGBAGHFCHDCGDBHABEFBDDBDDHG,False +586,11.0,24.0,18.0,11.0,8.0,6.0,17.0,13.0,GBBGABCCDDEGDFGAHEAHCAEGBEGAEABEAHHCHBBHCBHCBGGGGGGBHCBCCBDDDCGGBEFFADFGBCABGBBDCBDBHABHBBHFBDFCHCBGDHACCCEC,False +587,14.0,18.0,17.0,13.0,15.0,17.0,25.0,21.0,ECCAFEAGBAGCGFCGHADHEBGCGGCBDCGABDHBEGBCGHHGFHGHHGHDGCACAEHBBBABGFHGFDGFDBDGBAHHGGBCEFCFHHFEHFEFFAFFAGFCHCHGABCHEFHCFEBDEBDACGAEGEEHBBDEDDGD,False +588,13.0,15.0,14.0,18.0,15.0,14.0,13.0,9.0,EFAHGBHGDHGDCADGDDEEEECFACDGDGHCCFCEDCBHFBGDBCDBCGFCGBCEDDEAFEAECAFCDFDDBHABHFEEBBHBACBADBGDEABFGFFADGAGFAEFEBH,False +589,12.0,8.0,10.0,3.0,6.0,15.0,8.0,10.0,FDAFCFFHFGHFGBFHAHAADACFCCBBCBBHADHACFAHBBCGGEBECHGAHEAEEAFFFCFFHGFCGAEG,False +590,17.0,15.0,7.0,14.0,11.0,14.0,9.0,6.0,HEAFCADCHBHAFEFFEDAAFBABCGDDFAAGDGDCBEBFEBDEBAEAEBAEBAFBGFBHFCGCHGHDGFAAFCADBDDBDDGFAGFABEDBE,False +591,10.0,3.0,10.0,5.0,10.0,14.0,7.0,11.0,CFGCFEAFHGFCGAHACGFEADCAECAEBEDGFDHFEHFEHBEHFECFAAFHAECDHGDBFHHFAHCCFG,False +592,19.0,16.0,12.0,22.0,13.0,29.0,15.0,13.0,GHBEBBFBGFCCFDDECDGGDFGAFABCHFAFFABBCHBAFGHFBEFDEFGEFGDDGDDACDBCEAFEACEDDFFAHEAEDDHHFFDFBGFHGDBFHECCCFBDEBAHFAEFAGFBGDHADAFDAFDAFHAFGAGCHDB,False +593,7.0,6.0,8.0,6.0,8.0,9.0,6.0,6.0,DCHBFDCFDGACEACBBCBGHAGHFEHFEHDEGAEAACGFBFCHFCAEDFEBEDGF,False +594,30.0,31.0,17.0,16.0,20.0,23.0,18.0,23.0,ECHGCHGBBGFBGABGCDGHFFBFABDADAFEAFEHGBAABEABHABHACFACBEFADDADFBCGHHABFEBEGBCGEHFEFEBGEHGDAFBHDAFBAHBAHFAFACGDCHDCHDGBEBHEFEAFEDHACEBCFBCHBFHBAACFCBAHGHDDEADHAECACGBBABAFBFEBGEHGD,False +595,9.0,14.0,16.0,12.0,7.0,14.0,15.0,6.0,FEGFGGFDBAGEFGEFCCHCBEFBCGACBACFCCBCAFCAGGFFCBHGBHDBADADHADGBDGBDEBCHFCFCCGBDGDHEDADDFEBGGCFB,False +596,26.0,34.0,20.0,24.0,21.0,26.0,22.0,25.0,FEEBEHGEHEFHEFEEACGABBDHDDHGCGFDACBGBHGFHDADCFGCGBDAHHCFHGFEEFEAHEBHGBAABDABFAHFHDDADDFDBGGBFHBAEBAEBAHBAFACFADADDAGGBBGBBCCACFFBDFHDFHDBCBCABAECDFGDGHHEECCAFDBDEFCEFGDBBHBBHGGHFBHEGGEBCABCFBCFCAHBA,False +597,16.0,18.0,17.0,23.0,22.0,17.0,16.0,28.0,EECBEAGEDFCFADAHFCHFCHECDBGDBHDCHAAHDDBDDCDHHFHBAHBEHDEHAFHAHHEEGEEGDEBDEDDHBEBGEHGEHCACFHBDBACHECEBCACCGCGGEHHDHBFGEABFDFFDGFAHCGHCFHBGHGDABDAFGBEGFDFBDEHFA,False +598,14.0,9.0,12.0,11.0,20.0,14.0,7.0,8.0,EEAFAGFHFFBEAGHBCFFFFDFFBAFCEGEEGDCGDCBAADAHFFHAGHACDECBEDBEAACDGCEACHDDADBECBECHEAHFDEEEEEEEBC,False +599,31.0,15.0,28.0,34.0,25.0,28.0,16.0,23.0,EADADBADCDDCGEGGEAFEFGBDDCFACDECFECFBCHAEHABGFCCAECDEDGCDGCDGEAHDBBDBACEAFBFEBEDBEBEEFGAAGADGDFFCEFAFAABDFHDFHDGCDGHDFCDFHEFAEGCFDAFDAFDEFHBCDAFEECHHDDHDCFFAHHHHCHADEADADBADBCGCCHFAFCEHHAFHAHHAEGACCCH,False +600,10.0,11.0,5.0,10.0,8.0,10.0,7.0,10.0,HBFHBHGFGEFGEFAAFAGFGEBBHBDGBHHAHCDHEHBEAFDDBBABDFDCFHEBCECCADGADFADAED,False +601,1.0,4.0,4.0,5.0,1.0,4.0,5.0,0.0,EGCDDCBDCFDFBGBDGCAGFBGF,True +602,4.0,2.0,2.0,6.0,6.0,0.0,2.0,3.0,EDEEBAEDHEAGEABCHDCDDADGH,True +603,22.0,28.0,15.0,26.0,22.0,27.0,16.0,24.0,EADBBCFGEFEAGAFEACAHCDBABGHBHAEDGGDCGFBBFHFCEFCEFEDAEGEHGABFHBFDBGDBABGGCGBCGBABHAFDDFBDFBGFHFCHFCHFHECHDFFDFABFDBHDFDCFDCABHABHEHADCDDCDHFEEDAEDFEBHHAFHGBHBBEEBDHDHEDABDABAEGEEHAF,False +604,21.0,11.0,14.0,19.0,11.0,12.0,18.0,29.0,GHHGHHAHADHAHCGBCGBDGBDHDFAABAEHFCDDAACAFHBHHDEBEGAGGEBGEHDEGFGGCHGDBDHHDAAAACFACFHBHEAAEHADHGCHGHDBCFHEFHEFECDDHFDCGDFGAFHAHHCHBCGDCAD,False +605,9.0,11.0,6.0,10.0,8.0,6.0,9.0,4.0,DCGDAGDABEBBEBGEBGDDGHAHHBCCECAHAFFAEDCEFFEDCBGBBGEGDFGDBAAFDAB,False +606,28.0,22.0,23.0,19.0,24.0,23.0,22.0,23.0,GHDEEDGFDEHCEBCEBAGAAGEGGEGABFHGFAGAHGDCCDHFBADBDDBCDBFHFDGEEGCEHFFHCCHAGHABEACCACDFEEFAFGEFBCGBCBFAFFBFFDGEEGBEHBHHDCACFHCACAABAABAECCDFHHFHBDAEFHEFEECGFBGCDGEHCBGDBAAAHCAHDEHDBHABAAG,False +607,13.0,16.0,14.0,14.0,17.0,12.0,10.0,10.0,BGHBGADGDDGCECBEDBECAECGECGECFACFBEEBEADEDHFAHAAHBFEBHDCFDGDBFFBEGCAFADDHCABDACDABDHGFFGEEBFEBABCEFEHCHHCB,False +608,9.0,17.0,16.0,8.0,12.0,15.0,18.0,16.0,BGGGDCHHBHGBEACEACEGCEHFHCBGBBGFBGFAHCDGCFFCFGCBGBBGBFGBFAHFBGFBABCEGCEADHHEHHCHFEGEDHDDCDABGHECCFCFFGBADEAEHFH,False +609,34.0,28.0,25.0,20.0,27.0,20.0,18.0,15.0,FHGFEGEBBEGBEGHFHDFDAAEAAEDCFDBFEFCDCDDGEAFEADBCCACCDFHHBCHFEDABBABBABHAFGACGEEEACCACDDCBFCDHBFGBAGCGFADEADGABFABAGEEEBHBFDBFEBGEBEBHCCDCAGCAECAECAFCHGEEBFEAGEDECAHHABABBABDFDAHCABCAGHAGA,False +610,27.0,20.0,29.0,19.0,16.0,20.0,23.0,16.0,EDGGDCDCCDCCFAHFACFEEAAGGAHFADGADAEDCEACDAGDAHDCHFAFFHCGHCGDEBAEBAFHADHCBFBBDAECAECACGGGGFFCDGBHGECFBABDABGECGEFBFCBHDBHAHGACBAHEACCACHBHEFCBDCGDBGCBGHGCBFCADEFBFFGABGCEF,False +611,22.0,21.0,24.0,24.0,11.0,17.0,21.0,18.0,CGCHDBGDBABGACGAEAACCDDCDGCDGFDEHBABFCHACHAFGDEBDEBDABHGBCFBCBAHBDFBHFCFECFECGAGEAEBDGCGGCHGDFGDFCFBHFAFGAGHHFBHDAADCAHCAGEABCCBDDEDDHCCAAHFHHDADDBGHCGBFFBEDG,False +612,15.0,15.0,16.0,7.0,8.0,15.0,11.0,10.0,BBGABCABCFCHFCBCAGHHFHFFBFAAFAGBAGDEFFCFECACDACAFCABEEGCEGCAGDBCHBDDFDDFAFHACBGBHGBHCEEEGHCGFBHBA,False +613,1.0,6.0,10.0,13.0,4.0,6.0,8.0,9.0,GCDDCDCAHCHEDFDCCDGGDBHDCHDBHCGGFGCFGHFGFFHHCBBEEBDEDDBDH,True +614,10.0,16.0,11.0,12.0,14.0,10.0,10.0,10.0,DECEGBDAEDAEGGGHGAAEBAEHDGHGEBCHBCHBFEBCBFCBAHEDFEDFGAFDCFBCFBDFBCHCCHDHBDBBABFDGEEEDCEGAHBAF,False +615,1.0,1.0,2.0,4.0,6.0,3.0,0.0,3.0,HDEHFEDCEABEHFEDDECF,True +616,10.0,6.0,9.0,12.0,6.0,14.0,6.0,4.0,DFHDFBBECCFCCFBCDGAFFABDAGEADBDDACECFECGAAGHFHFFHFFDGDAFDEFDEBDAAGC,True +617,6.0,1.0,4.0,3.0,5.0,2.0,0.0,4.0,BDEHDAAFACHECHECDEFHCAAEA,True +618,22.0,16.0,36.0,14.0,21.0,16.0,20.0,16.0,BBGEBEHHHHHACECCGBEDBCDHHAHDCHDCECAFHAFDAFCAECGCCACCGFFDEGACGCCGCEGCGGEGACGACBDGGDEAEBAEGFECAECFBGECAEFFHBCCBCHEFADFDECDBCBFDHDECDGAABHCFGCAGCFGABEABCABCECCFFAHH,False +619,26.0,17.0,24.0,18.0,27.0,15.0,23.0,23.0,ADFABEBGDCGDEAEHBHDBCGECBECEEGAHGCCECGFCAFCHECFACBAHBACBAEBDEHFEDDEHGHHGHHGAHGAHFADAAGEAEDAFAADADHEGHEGHGBHDBCEECGFCHEBHBBFAHDCGAEGEEGECGHCFCFGCDDFDCBCFEAAAFEAHGBGDCDBEFCHAG,False +620,7.0,2.0,1.0,9.0,6.0,2.0,5.0,5.0,GBEGBDDHGCFGDGHEEHDEFAADAAHAAEAHEDDDD,True +621,16.0,26.0,22.0,21.0,29.0,29.0,17.0,19.0,EAFBDDEEGGEGGEGDFBBFADADCGDCBCCHCDDEDFEDFADFEDFGBFHBECAHCDBCGFCFECEEHAFHAFCGFBEHGFHEEHFEBCGBGGHABFGDAGCABFDBFDFFDEFBBBDHBEECFEHEACBFBDFHAHHEHHEHCCHGBAEBDCCEEFBBFAFCBDCBFBAFEACEGHE,False +622,7.0,7.0,8.0,11.0,8.0,4.0,10.0,8.0,DAGDCGDHGDACDBCFHHEGDEDEFHCBHEBHFDHEHBCGGEGBCGDCFDGEDCAABAABEAG,False +623,28.0,16.0,21.0,17.0,19.0,16.0,21.0,15.0,DEHGEHCAACGFGGBEFBEGGGBGFADAEDADDCCHGGACAACEBDGFCBDAAFBCCCCCAEEEECHDCEDAEFAHFABFACFGHHBEGCEFBAHCDHDBCEBCEAHAAHAABEDGECGFAGFABFAHFAHEAHDHBFCBDDAFDAGBGGDGG,False +624,3.0,1.0,2.0,2.0,0.0,4.0,3.0,0.0,GAAFDAFGGFCDFCB,True +625,2.0,3.0,2.0,8.0,3.0,1.0,2.0,1.0,DHDDBDABEGDDGBFAEDCEDC,True +626,25.0,22.0,16.0,18.0,24.0,24.0,24.0,13.0,EBGFHAFDBGEBGEFGEDHADHADAAFCAFCHGEAGACBDGBFBDFEDGEHGEHGDHGCFCEFBEACEBHGFHEBHEGFEBAECFBABCACCABAEDEDGEGCABEEDGEAGAAGCFFDBCGHAGCAFFGFDAFHFFGEBBBHBDAGDABDBDGBAFEDFCAFCEF,False +627,29.0,21.0,28.0,24.0,31.0,21.0,20.0,20.0,FAHFBGFACEAEHGHHCFHGAGFFCCDDBDGBDGBDBHEBHECCEHCAFEGEHGEHGEGGBCABADDACDEEBCHCGAAEAFCABCEBDABEABCAECAEAHHFCFGDFHDFHBCECEDCDFCDACEFBEDBFDBEBEHHECCEDAFDGFDHEEHEGHCDDADAAEGAFADCGCGFEGFEABACFAEBACBGDA,False +628,12.0,14.0,20.0,9.0,14.0,5.0,7.0,10.0,BAHEECEFDEACFADDABAECEHFDHCCCACBAEDHEBHEBHFHCFCCGCDACAADGEGCCGCGBCBBCGBCEBEHBEDCADBEGBCABHH,False +629,5.0,5.0,7.0,3.0,4.0,2.0,2.0,2.0,EFAECAECHGHFCDABDBCDBCBCABCGEA,True +630,23.0,22.0,17.0,29.0,22.0,31.0,12.0,12.0,CCDECDBBHBBHBGFACDAEHBFBGFCCEHGEHEECEFDDFDDBEDBAFEHBDHBFFFFFFFAFFAFHDFAEFACFCCGAFAAFGADGADFFEBHEGEAAFBDGBDADDAGEACECCFBBEEGGEBDBBCAADFEDCADFFDFAEFBHDDDDBCCBFGDAEHEHDDAD,False +631,27.0,22.0,17.0,34.0,24.0,29.0,22.0,24.0,FFDCFDCHHBFADFAGECGECGBFBAFBGGACBFCBACHEFEEFBEFEEFCBAEECEHAEGAEFACFADFDBFBHHDHAFHADDGHHEHDDGEBEEGFFDDGEDGADGBDHFDHFBHFHAABAADHAEHBHGDFGEAADDFDCCDCDDFBAGCFDCGDHBDHEAFDGBEGBADEFGCDBADGADHEHGFHBDHADGACB,False +632,14.0,22.0,9.0,14.0,13.0,13.0,20.0,23.0,BCFBCFAHGDHGAHEDGEBBCBHEGHDDDBAGBAGCECBBGBDABAGHDGHEFFBHEEEEHDEBDEFAAFAHGDGCDAFHAHGADGAGCDDHHFHGFHEBHBGHBFBBFGBFHHFAHCHHBECBGBGG,False +633,24.0,22.0,20.0,25.0,23.0,16.0,19.0,23.0,DBBDHHDHHEFEEFGABGFEGADFACHGEHGEHAFFAHECCEACEBBHBEFADDDDGGHGGHAABCFDCFBGFAECDGBDABEAFECFEHBAHFDBFDBDEFCBCCGDEACAAGBBGBDEAEAAGAAHBGHACCAECGCCDCGDEHAHGBDDEDDHDBHDHHFCHDBHEBCE,False +634,17.0,21.0,22.0,24.0,23.0,23.0,16.0,18.0,CBHDBHCEHCHBGDBECHEHFBCFDFBDFCGFCACCACCGDEAFGADEADFCDFBAHAGHGEBDDBDEBDHBGBDAEDBEDCEFCEFHBHCGDAHAAEDEEGGECBEHDGDBGEHFEFGEFBFFAFFCCFECEDHEGCAGBACFDGFDHFBABHADFBEFHADC,False +635,16.0,6.0,8.0,5.0,5.0,8.0,8.0,4.0,FFABFACAAFAAHAFHCEACEABFCDGCFACABGGDGCABAEBGEAGBAGHACHFEDDDG,False +636,0.0,0.0,0.0,2.0,3.0,1.0,3.0,2.0,EHGEHDEDGFG,True +637,9.0,16.0,10.0,10.0,13.0,11.0,8.0,12.0,FEDBEDBEBBEFBEHBFBFCBEGBAGBHGHDBDDEGBECEFHDDHCFHGBHEBCGBEFAACBDEFCGFAAHAHHFFAADAHDCHGCECC,False +638,12.0,9.0,9.0,12.0,9.0,15.0,8.0,15.0,EFGFDCDAGDHFCBFEAFHACHBGADEEHEFGEDHFDGDDGAECCFHBFHBCACHACHACFAFBGDBGDBHBHHBHDEHDAAAEFFFHF,False +639,14.0,20.0,11.0,14.0,9.0,16.0,14.0,14.0,BFBHEBAEDADCGDAGDAFBHCBACBAEAHHCGBCGFCGAABFCBFGADBFFFDFCDFEAGGDHDDEFFHGHHGHHEFEBHBBGDBCHBEHBEFBCABDGGDCGAFHBFABD,False +640,8.0,6.0,17.0,2.0,13.0,12.0,17.0,7.0,HCFFGFCHCCACAADFGBFCFFCGFCABGBEABGCEGCEGCACCFGDGECGHCAEGBEGEEGHBGEAFEHFEHGHGEECCGF,True +641,14.0,17.0,15.0,14.0,30.0,13.0,21.0,15.0,BBGEDAHDBBEHBCBEHAEGAFGECGACGADAFGFFGFEGDBCCBFCHDHABHEBGEDADDHEGHBBHEGCGCHEEHEEHGEHACACCEGCGGEDGFGAFDBFCAFBAFEEEHGEGFEBEEBHEFDECEEDEBGEDCAD,False +642,26.0,25.0,28.0,26.0,13.0,16.0,19.0,13.0,EBDECDGCAACBAHFACDCCBCDDHDFBDBDAHGAHGBHGBCFDEADGADGHFGBAHBCCDHBDFDFHAEEFDCGGCFCAFGACGCCFADBAEBGBGGBFGDFBFCAACAACECBBHBBGABGFCAHCDFGDCCEBCDACHBCAAEDEEDFEHEDABDACDAGDBB,False +643,14.0,19.0,17.0,9.0,14.0,22.0,18.0,8.0,GCCFBFFBEABEHDEBDGBDFAHFBHCBDEBDGBDHHFFGAFGCGHCACFBGGAGGFEGFCAFCADGGCFECECGFAGFAGACHAFHDCBBCBFABFEBCCBGFEAECDBBFFBAEEEEFG,False +644,15.0,27.0,16.0,22.0,21.0,27.0,27.0,18.0,EDFEFFDFBDGBEGBHCFHCFHFAHFGFFEHGEBGEBGABGCGEBGFFHADEDGEBFABGAEFEGFGGAGFDHFBHCBADAEFBCFCCHDFBEADEDBBBGDBDCACCFCEFDDFBHHAGHGGBGBEGCFCBFEGDAGDEHCEHEBHEBADHDHHDGCDGBAFBDCGAFGDBB,False +645,14.0,11.0,10.0,13.0,16.0,12.0,10.0,15.0,EEHEEHGEFGEDEDBGCBHHFHBFDBEEBEBAHBDGACGADGHEHHECDFHDFDFAEFACFBEBHEHAGDCHDCDGCFAAFAAGCDGCAAAHHFBCDBAFE,False +646,3.0,5.0,2.0,4.0,7.0,6.0,2.0,5.0,EEDEFDFHDFHGFHCBHFBEEEABHABFDBGCEA,True +647,17.0,19.0,20.0,19.0,12.0,18.0,17.0,19.0,HCFBAFBDFDHBCACEAFHCGGCAHBHHBHFECADGBGCDACAECGDCFDFEHBABGADGACGBEFHGFBDBCCBCFBDFADFGGFEGFHGFEBDDBDDADBFGCFGHECHCHHGGBECECCEBDEDHADHADHAFHAHAB,False +648,10.0,10.0,6.0,7.0,5.0,10.0,7.0,10.0,CHGDHGHAECAEAGBCGCEDFBGFCGBCFBHAEAFHDFBEHBGFAFFDDABDABDFBHFHHABHA,False +649,23.0,19.0,18.0,23.0,11.0,22.0,22.0,16.0,DFGDAGAEGAEDABBFDGADBHHAEGECAFDAEDACGBCGDCGHCGBCHEGACCAFDBFHBGGGDBGBFCBEGFHAHHCEDAEDBBAFAFFAFGAHCHCCDCCGBDEFHFFDBFBCFDCDDAAAGDEBDBBHBFHGFHFFHFAHGDGGDACDAF,False +650,4.0,5.0,4.0,4.0,6.0,3.0,2.0,5.0,DDHGDFGEFAECAFCDBCHEEAEEHHBACBHBB,False +651,29.0,15.0,14.0,25.0,15.0,16.0,23.0,19.0,GAFBABHAGGACGAGGAGHABDGFCGDEGEFDFACFBDAHAAHCGECDHFEHCDDEDDECGFDDFEDADAFDBFDBEGHFBAGBADBCDGAFFCEDEHAAHAACGAGDFDDFDAADCAFHBEHGEHGCGEBBHHBCDBCDHEBAEGGHGHHAAHAA,False +652,17.0,19.0,21.0,19.0,20.0,33.0,24.0,19.0,EBHGBHEFHAFCFFEAFEADEBHCBFCEFDEFHBGHGFDGDAHEGFEABBBBFBBFBBFAFEBDHBCBCGFEHACDCFDBGHGEFGACCFFFFDADGFDCFGEGHHGEHFFHEFHCFAGFBGCCGDCDDCGECGHAHEAGEDBCDEHDGHFGFCCDAAFAAFGAFDCGECGD,False +653,4.0,2.0,1.0,5.0,5.0,3.0,4.0,8.0,GBFEDEDGEDEADHGHHGHHDBHAHEFHCFAA,True +654,20.0,23.0,22.0,29.0,18.0,18.0,13.0,18.0,EDEBAEGHHFAHFBDDBGFBGDDABDABDADCCBBCEHGFCGFCDEHDFDGHDCBDHFDCBHBFHECCADGHGGEGBCBACHAEGEEFDEHDCHBEHFDBFCEACFAEDAFBGDBDDBDDBFDCFDCHDAACAABACGFCACDHHAFBAFBHEDCEBEEAC,False +655,7.0,8.0,11.0,11.0,11.0,5.0,11.0,11.0,CHBCHDCHBAHBCGDEGDACDEBAAAFBEFHFBGFEDEEAEEGDGGDGHDAHDHBEEGDECCBHCGCCGHCFHDG,False +656,23.0,22.0,23.0,10.0,19.0,19.0,24.0,14.0,FCGFCGAAEBHECHECHCGABAAFFEHBAHBCBBDEBEFDFADFGDFACFAFAHFBCEACECCDGBFEBFCCCCEGAAHAGEBGABCFBAAGFDFCEABEABECDGCGAHGHCCHBAFBHEEHCGBFGBAHBGGEGGEDBEDBDFGGGGGGACH,False +657,17.0,18.0,13.0,17.0,9.0,17.0,17.0,24.0,BDHBDGBFEBCHBDFBDHBAHBHHAAGABHACFFHHBBDDHHDHGFCFFCGHHBAHADGFDCFHCHCCBDFFGAFGAEEAGEHHBGFFGFAGHADHDCBDEFDECGAGADCAGCHGEHBEHFDABDGBCGAE,False +658,8.0,8.0,5.0,2.0,2.0,4.0,5.0,8.0,CEGBBGBHCFHBHBBABGEBHHGCFAAHADHAHGACFACFAD,True +659,34.0,21.0,21.0,17.0,21.0,20.0,30.0,25.0,HAFHDCDEGEEGAAGBGCBEAGEBGEAHCAHEAHCAHAAHFBHECECABCAHGGFGHHGEHDADFACFACFCGFCGFBBFAAHAAHBFFDAFDGFCAEAGFAEDBGBCEEFFFDEAGGADGCDFHGGHBCABCABCABHDGDGGEGGEGHEAHBDGBHHBCHDFAECGDBHAGHADABBACEFHBDEGC,False +660,14.0,30.0,12.0,19.0,8.0,11.0,20.0,13.0,DEBHHDCGGHGCHBFBFGBFDDFDDGDGBDBBABHDBHACECCACEABBAEBDBBGGGCGDAHCADCABHEFHBFDCDCGGFBGDBDBBGGBCGBEBBEBBHHBHFFHFAADGBBGBGADDFEAAGA,False +661,11.0,26.0,15.0,26.0,16.0,14.0,18.0,26.0,FEBHBBCBDCEDFABGAGEABBHBGCDGFDEBBEBBDBEGBEDDHHDHFBHEBEEGAHHDHHCBHCAHDHCAACEGBEGBDGBHBHDFHDHDFHECHCHEAHBGCFCFHDDHDDFDDAGEGGCCGDFGFAGFGDBBBHBDHFDACDCHFGDE,False +662,5.0,2.0,4.0,1.0,4.0,3.0,0.0,4.0,HCDFCFHCACAEEAEFBHABHAE,True +663,14.0,22.0,18.0,13.0,14.0,22.0,18.0,29.0,DHBHHBGHGDDFFFCBHCBFCHGCGGHHHHABCCBAFAEGBBDBFCFECFADFHBCHADBADGHDGCDACFHBFGFFBFGCFAAEACHAFHEEEEHGEHAEBGBGGBFCBFBGGBGAHDHHBECEHCHBFECFHAFHDCHDEHDEHGFHB,False +664,22.0,13.0,19.0,20.0,21.0,19.0,24.0,26.0,AACFEGGECAHDGHDGDBEHBGDGGCBEAGEFEAGBGGBFFBGGGGDCEEAAFFAHEBFEFACFECEABEFHGFHDAHCBHCFGDFHDAHGEHEAHEAGCCCHDAHFCEFCDCAFCGCHFCHGCHGCBGFBGHHDAHEAHDHHDHEEADEFDHADADDHDBADB,False +665,19.0,16.0,20.0,18.0,23.0,17.0,22.0,24.0,DAACFCEFCEHBFHAEHDBHBHABHABHAHCCGGCGCEDBDHBACCCCCAEDHEACEHEDGECGEFGCGDEFHCAHADFDEEDBECEACDGEDGFHFAEFAGBHHAHHDHAGBBFCGFEGHBHFDEFDHFHHABGABGEDGEDGEGGBCEBGDFGFFGA,False +666,21.0,15.0,10.0,14.0,9.0,13.0,18.0,9.0,ACFGBACCACCADCDGADGADGHBABGDFEDEGAGFADADDBEABDABEABAFBAFBGFGGACGBFEBFEHFHGACGCFEDGBGABCEHFGBAGFEDADBAFHHGHHDH,False +667,8.0,7.0,10.0,12.0,11.0,15.0,18.0,9.0,FAGEGGDGEAGDFCFFHBFDBGDFGBAGHCGFCDBCGBDFHGFHEACECCECAEFGCFGHFEDGHGBHFCHAEDAEDGDFGFGEBEDHAD,False +668,10.0,9.0,8.0,13.0,5.0,7.0,10.0,7.0,GFDGECCECCFHAGBGDBDFADGEDAADAADAADCGBGHBHBDHFGHFAHFACDEHBEBDDCGGCDFBB,False +669,7.0,12.0,7.0,12.0,9.0,2.0,15.0,14.0,HBGHAGHEGBCADABEEHFCCGHGGEGGCDGCHGEDGDBADBHDBGEAGAACEDDFBHBBHBDHBDHGCHGHDEEBHD,True +670,0.0,5.0,2.0,3.0,7.0,4.0,3.0,4.0,FGCFHFEDBHBBHFBGEBEEDEEGEHCD,True +671,5.0,12.0,12.0,3.0,8.0,4.0,5.0,4.0,BBCBBAECHCGHCHFCFCCBDBECBEBFEBCGHCEFGGBAGEAEEACCBDABD,True +672,11.0,18.0,12.0,10.0,18.0,18.0,25.0,17.0,AGBBGFGCFCEFCBHCADEBHCHDEBGGGGGAGGCGFHFBHDBFFAFHAEHFEFFAGBEDHHHHBBCFHAFCGCCBEHBEHGDBFEAGEHGEAGEAGEGDBGDCGDGGDFHEFEBBCBAGBEDHEFGEF,False +673,9.0,13.0,14.0,18.0,14.0,11.0,8.0,15.0,CGDBHCCHGBFGAFEEHEHCEHCACCADCDDCGBCDBHDHCBHEHABHEEGDFHDGACBAGDFEDFEDECDBDHFEHBEFFEBCEBDABAAGFHFDDFDDHB,False +674,8.0,13.0,7.0,9.0,11.0,13.0,8.0,11.0,GHHFHFCGFBEFDEDDBFDBAHFHHFCHEDGEHGCBDBHHAEGAEAAEBAGBAEFCFGCFAHBGEFECBCBBDBBDEFDF,False +675,1.0,9.0,5.0,1.0,4.0,4.0,4.0,4.0,BECBCFDGHHBEBBFBBFBCFBHGAHGCEECG,True +676,7.0,7.0,1.0,4.0,6.0,8.0,6.0,3.0,ECHEDFEAHHDFABGEBEABEDGFAGBAFBAFGFGGFABFDB,False +677,14.0,18.0,19.0,11.0,14.0,16.0,16.0,25.0,EEHFECBGCECHDBHGHHGHHGABBDFBDFBAFHAGDABCABFHHABGAEGDBHHGHFFHDFEDFHFGACBCCGCAAFFAHACDGCDBCHBFGBHEFHAFCCEBBDHCHFAHEGHEGCEHCECCHGEGBECBD,False +678,9.0,12.0,6.0,10.0,11.0,11.0,13.0,11.0,CDEAGGDGGCGBCGBAGBGEBDCAFGHFGBFEHEEACFAGFDEFGBHHFHHEHFCGDADHHDHEDAADFBFBBFBEEHEABBD,False +679,27.0,20.0,25.0,20.0,31.0,18.0,23.0,23.0,EFHEDHDDBECBDAFEEFEEAADGGCGEBGADEECEEFEECAFCGEGGBFCBFABGACDAEHBHCFGCHGCHGCFDCBHHBEABAHBABAHEAHGADGCCFECDHDFAGECHAFBADBGDBCABHADDBHCEHCEHBFHGFEEDCDHCEECGCDBCAHGHBGEAGEAFFAFGAEEAFAHGEHGDACD,False +680,27.0,26.0,27.0,28.0,20.0,19.0,14.0,25.0,GDCFDCFHCBAEGAFACFAGFDBEABDBCAHCGFFFCFBBBADBGFCDACDGDDHCEHAEHBFGBHECDEGAACBHCHEAHEFCGACDBHDACGACHAHHAHDEHFCBBABBABCHBFDCGBCHBCHFDHEEBDEHEEHGEFABHAHCAEDBCDBCDEEDCBDBHAFAGEADDADFADFDDHGDEC,False +681,3.0,1.0,1.0,3.0,4.0,8.0,7.0,1.0,HGFEDDABGFGGFGFFGCGAFDAFEEFE,True +682,15.0,12.0,11.0,14.0,15.0,27.0,23.0,14.0,FHFFHFCHGEDCEDGABGDBGFFGFHGDDFFDGCHECAEGEBCEFCEAAAAGACFAGGGBEGBFBAFBAGGAEHAEHBDGGDFDAHGGEGGHAFHGCEFDBFEHDDBGFBCFAFFEHFCHFHDFCFFDEFB,False +683,3.0,2.0,5.0,6.0,4.0,4.0,5.0,2.0,GGFDFADFADECDCGBCGEDHEDHGCBCAEF,False +684,13.0,18.0,21.0,19.0,20.0,13.0,21.0,11.0,FEEGGCAGBEGFECBEGBDHBDCCGACGFBFEHHEHBCHCCFDCDDCEACEAFHHFCFDEBBGBDCBDBADEDEGCFDHABEDGEGFDCFECDEAHEDGEAGFAEAAGHADABDBGCGGBGFBDCBDGBCGECGHC,False +685,10.0,7.0,12.0,11.0,9.0,18.0,8.0,9.0,HDHAGFAFFAFFAEBDCBDBEAFEACEACDGDDGFCHFCBCCACHGCFFCGDEFDFHEFHDCBEHGEGFFDFAAFBEFCDGHBH,False +686,6.0,12.0,8.0,11.0,9.0,7.0,20.0,10.0,BCEBCDBHAGDAGDHGDEDAGDGHBEHDDFGDGEDAEGGGCEBCBGGGCHECBFHHGGFGGFGGHGAHFBBCBECBHABFDEF,False +687,12.0,20.0,16.0,25.0,15.0,20.0,20.0,33.0,DFDHAGHAEHBHBFCFFDHFDBGGCCBDABHGGHBBCBFCHCEEADDACDFCAFBHBHDBHFBADGHDGHDGFEEBHHGGHGHFGDFCDHEEHCECCHDBDAGDABDCBFHAGEAHEHHEHFDHFDHFDEFDCCGBCHEDHBDGEHGBBGFDHAHHFEFGG,False +688,3.0,9.0,2.0,3.0,7.0,7.0,3.0,4.0,CFEHFBFBBEDBCHAFABFEBEEBDEHFEDFHBGGBGA,True +689,15.0,26.0,20.0,34.0,29.0,23.0,27.0,17.0,GAAGDABHABEGDEBDFFDHFEHFBFCBGCBCCDGFDEHDCFDBHEBEFBEBCGCDGADBDGGGAAFCEDCEDBHGBDDBEDFFGFEHBEFFCAHCHHGFDDBCDBDFEHFGAFHFFDBEABEFBGFAGHGGEECCGABDDBEEBECBEAGCHGDHGDEDHFDHDAECAECDEDGEDEBCEDDGGDEGBCG,False +690,2.0,5.0,5.0,7.0,3.0,8.0,3.0,2.0,GFGFFGFDHHAEBCCBCDFCDEADFDBFDCEDBBF,True +691,11.0,14.0,14.0,3.0,13.0,5.0,13.0,10.0,ABGFGEEGEEGEHAHBCHBDDGHBBABACBCEEGECGECGHCABCABCHBEGAEFCCGBFGCAEFGECBFHACHACHDHBGBA,False +692,17.0,27.0,23.0,13.0,20.0,16.0,15.0,12.0,BCCBCGFCGFADAABEDHEHBEADCFFEFFCABCGBABBEGBADBABBFCACGEDBEBBGFBGHBGHDEHBEHBCHACHFGEECHGFHGCCGECGDBBDGAEADFCGECDEFEFCCFAHFEHEABAFCCECEBDDBADBABBC,False +693,27.0,22.0,19.0,22.0,14.0,28.0,28.0,25.0,FCDFEDBEDFECFBHAAHEACBFDEGDCGFFHHFADGABFAFAAGGBHFECAECAGCGBDGBDHBHCBHFEHBBAFAAFAFFCHFGGFHAADCCGCCGBHGDDGFDGBDGBABHAGFDBFGBHAEFFDGFDGCAACAGGHDGAGCDEHDHBGHEFCEFADHEHABHAFHEHHDBGGBFCBGCHAD,False +694,18.0,13.0,19.0,10.0,11.0,15.0,13.0,6.0,GDGHAABAGDGHFBFGBCGACGAEAFDAFDECHECACBFCBACBEBDGBFACEEBEDCEACEBBDDBGFAFFDCFECDHCACCGBFGHGCEGCAAHAAFCAFCFF,False +695,10.0,11.0,11.0,10.0,20.0,12.0,15.0,5.0,DBDBFDEGDBGEEGEGFAAEGDFCFECEEAEEBHGGHCGHCFACGHEGEEGAEFCEFBAFBAEEACCGFDBFCHACEDFADFGBGCBDEBEGBD,False +696,11.0,15.0,9.0,15.0,19.0,14.0,16.0,14.0,BBEABEBFEDFHBEDCFCEDEFDECCEFGFGBHGBCGHGFHEBDGBFGCFGDGDACDAFBFHBHGECGEHDEHBBFDEEDGEFCAAHEABEHHEAHEAHDAHDGGDBGFAGAD,False +697,4.0,10.0,3.0,4.0,4.0,9.0,13.0,9.0,EFFBHHHHHCADDEGDFGBBGHFGBBBBHBACEHCFBEGDGGFGGFGAFGAGHFGB,True +698,8.0,6.0,6.0,10.0,3.0,3.0,10.0,9.0,CHGBHGEHGAAGHDGDAGDBDHADHBDHDAFACBCFBGEHCEFCGABGAGDCDDH,True +699,23.0,20.0,26.0,25.0,24.0,29.0,20.0,24.0,CDBFFGEGEACCACDGBDCHACHACHBGDBCFBHFHHFHHAGHAGHCHAEEGCEHEEFFCDFDDFDFAAEEFEEFBEDAEDFGDFGDHHDBCBBCEBEABADDAEDGGGCEHAGBEFBCFDHFBEFADFDCEHFEHFHADCFDAFHAFBFCEDDBCAHAACGCBFCDHBFHDAGFEGFGGCCGCBBCAHGE,False +700,29.0,20.0,21.0,24.0,24.0,23.0,13.0,26.0,EBHEBHBADGAHAAEEACGAFAAFBBFCHDBHAGCDEBDCDDAHHBCEAAFHAFCABDDEDEEDFHDFCDFBEGCFGEFAFGCHGDHFFEFHEDDEADBACACEFCBHCEHCAAEAECAEBFDAFHAHGAHGBGCBDHBDABDHBDHADFGEBABHFCFFAHFDECHHCHHCFCGDEGEE,False +701,3.0,7.0,7.0,3.0,6.0,6.0,4.0,11.0,CEFCFHGFHBHEAHECHEBBAHAEECHCDHCFFCHBGFBDDBGHBGH,False +702,9.0,6.0,16.0,15.0,12.0,8.0,10.0,9.0,FDCFDCDAHDGHFAACBCHDEHEGDEDDFDDEGCGCDBCDEAFCBCCBCGACGACHHEEHADDAEDCECFECFAGGBBEHFGHEG,False +703,6.0,1.0,3.0,5.0,2.0,9.0,6.0,6.0,DABEAHCFGGFAGFHHFCFFHDFHDCGFFGDEGDHAAA,True +704,4.0,1.0,0.0,2.0,2.0,1.0,3.0,0.0,BGGAAGEADEFDA,True +705,18.0,19.0,12.0,21.0,25.0,19.0,18.0,24.0,FDAHBFHDCHACHAEAEEBDDDDDGFHHFEHDDBDAAAFHAGGAGDABCHGCEGCFDBGCBEFHFDHFHHEGCFABHEBHCAHBBHEAEEAEGAEDEBGFCDHEEHGEFGEFBDFEGFGHFDHFBHDBGDACBAFBDFEHEECBEGBDGAEGEHBC,False +706,17.0,12.0,10.0,18.0,25.0,13.0,22.0,21.0,AGEHCDCDAEDAEBAGGHGGHDCHEHEFCEABEGBEBHAGABHABFFGGFGAFGDBGAEDAGFAHEEBFFAEFBEHCEFDEFEHDCHDCHDGAEGAHHFHEBEEGABGDHGDHBDHDHGCEDCHFCEEDDEHDGAGGE,False +707,18.0,24.0,22.0,26.0,29.0,18.0,27.0,19.0,HFHHGDEGFHCDHCEGFEGBDCEDEEFFBFCAEBBGABHADAAGABFDCGCBHABAGHDEDEEHBAHDAGDBGCBDHHDBEEGCFGCHCFHBFDEGDHDFHAEDAGDFGEFCEGGEBGCCCCECGECGCHACEGCEFCDFBDFBGBEABECBEBBGAHGDHDDAABGGBEGAEBEDFDDFEDE,False +708,20.0,10.0,10.0,16.0,13.0,13.0,19.0,23.0,FFHDFHCCACGGGHEEHDGGAGEAGHAEBAHDGHGGHBGAGFCBDCDDADDCEHADDDHBAHBAHBGGAFAAGAGGBGFHAHHDHGEHEFHCFHCBACEDBDDFCEFAHFAHEAEFHFABEDHE,False +709,5.0,8.0,2.0,9.0,7.0,8.0,16.0,8.0,CGDAGDFHDGABHDEFFBFFBEDGGAGGCEGHHGADEFDEDHEDGFBGHGGHGGBGBBAHEFB,False +710,2.0,0.0,1.0,2.0,0.0,3.0,1.0,3.0,FGHDDHAFHAFC,True +711,11.0,11.0,7.0,14.0,11.0,15.0,19.0,23.0,DHDDADGHBGFBGHHGDGAHHHGHHGBCEDCHDHDECGGFDDAGBHGBGDAHBFFBFFCHFCFFHBFHEHHGAFGAHGHDCDDAGEHGEHBFHEGBAGFAEFCEABEAEEF,False +712,22.0,16.0,19.0,9.0,22.0,12.0,19.0,16.0,HDGBAGAAGFEEFADBADHGCGCDBCABEACGHGEABEAFGHFEHFGHFGHCGEFGEFHHACDAHFCGECEABEAEEBBABHEFEAGEDGBCEHDEADCBDABCHCCHBCGAGHACEACHFCEEBAEBAGBGFCC,False +713,10.0,16.0,20.0,25.0,19.0,11.0,23.0,14.0,FDCDDBFDGCEFFEBBEBBFDBHCFAAHGDHDBFFGFDACDAEDGEGGDCADCDDGEDGEGCEGDADCGDCBBHEBDECEHCEHGBHACEGGDCGHHGHDGCGGCGCDHHDECCEBEEDABBAGBGEAGEFDHFBHCC,False +714,7.0,8.0,11.0,9.0,14.0,8.0,8.0,14.0,AADAFBHGCCGCDHHFHBCHDCHDEHEEBFBAFHDGHDHHEAFEFCEGDHBEHCCFCHBBEDEEAFEAECGECGEGDBG,False +715,4.0,5.0,2.0,4.0,4.0,2.0,5.0,7.0,BEEHHBHHCDHCGEBGDBDHEFHFAAGAAGBDG,False +716,2.0,4.0,4.0,2.0,5.0,4.0,1.0,3.0,GBACBHFFEFFDHBDHEAEECECCB,True +717,15.0,12.0,19.0,9.0,14.0,21.0,18.0,23.0,DBHAHHEFBFAGHAGHAEHFEAAGCGHBFHBAHDCHCCDAGGHGFDAFEEEGECHCCEBGDAGCAGHGFACDHBDGBAFCFFCDFCFFCEGCBGFBCHBHAGHFHCBHAFHCFGCEGCEHFEBEEFFHDFH,False +718,21.0,29.0,17.0,17.0,19.0,12.0,14.0,21.0,BHBBDDFDBFDBDHADHBCABAHFADGBECCFDBADGEHHBBEGHEDHCHEBHBHHBEEBCABFBBFBFDAFABDGCEGCEGBEACEBBBBCDCHGEDEEGGHGAFGABGABAAHAHHAHGAHGEHCDCFDCFEEDEBHCCCACAAFABE,False +719,15.0,18.0,17.0,14.0,22.0,18.0,20.0,22.0,GGECFCHFHBEHBEDBEFBEHBDHBGAGFAHFAFECFDFHGFBGDEHECDGCAEFHEFBDGHDGDBGBBGBHGCCGCCGCHHEBBBBEEAHHBFEACADDACGCFEHFEHFAGAHGEHFAAFCHDCEGCEFDEGBHGDHEECAADA,False +720,4.0,4.0,3.0,2.0,1.0,3.0,4.0,4.0,BFBBFHBCHAHDAGEAFCADCGGGH,False +721,22.0,14.0,33.0,22.0,22.0,16.0,25.0,18.0,EGACBDEEDAADHAHBABBAEGAEGBHCBADGFBCFBAACFEEFEDHBDCGECHHHAGEAFECFEGFGAFGHCGAFGEFECFGCABEEGGDAGDCCHCCHGDEGBEDBACAHDACCCBHCAHCHDGHAECDDCDHCFCDAHHCECGECGDCGFGECCCFCCDDGDDGDFGBF,False +722,15.0,12.0,9.0,7.0,14.0,11.0,9.0,13.0,HFDHFEHEGDBCFBCAAHFAEFGGDBADEAFEAHEAHFBGFHEAGEDGBBABHGEHGECCABCEHDBADCFEEFAHFGHEAHACCABCBB,False +723,25.0,27.0,19.0,19.0,29.0,24.0,29.0,27.0,CHBDGEDBEGCHBAGECBACBGCEACAGCAGEFHHHGHAGAEDHGCGBBACHDGDAGDAGBFFBGFBDFEAFBABACDEFFEAHHAEHGHHBFABFACHHHEBGBBEABEAHEDGEDBFDCHDBGGEHHEGHFCHFHAFDAFEGGHGECDFGGBGCFEAGECBECBECFEAFEBFEHFEHBDDAEDADDFCBFEBFGHG,False +724,7.0,6.0,4.0,4.0,2.0,2.0,7.0,4.0,BACDABGAGDBGHFGHFCHAEGADGBEGBAADCBHC,False +725,13.0,14.0,14.0,9.0,9.0,11.0,7.0,5.0,ADEDDFDEGBCACCABCADGAFGFGAEGAGBAFCFFHBBHCBDBFEGAEDBDFHCEECEAFBAFHCFCCDBCABCABHBBEC,False +726,6.0,1.0,2.0,1.0,0.0,2.0,3.0,0.0,ADAAGACFACFBGGA,True +727,22.0,23.0,26.0,27.0,23.0,28.0,17.0,22.0,ECCBCCADCDDGGAHBAHFHCGHEGHCAHGHHGBEFCAFBAFHDFAFCCBACDGCBGHGEAGCDECFEBEEDFDFBHGBAGBADFEDAHDACDGEFEEHGEHFAHFAEBDBBEBFEDAEDHDDCFDGDABEGDFHBCBFDFFACFAFHEFHABDCCEABEFFHCFBFFBFCBDCBDCEDGDAHDCHCE,False +728,0.0,0.0,3.0,1.0,3.0,4.0,2.0,2.0,CEHCFCGFHDFEGFE,True +729,17.0,19.0,22.0,26.0,19.0,16.0,18.0,23.0,GFHGAGFACDAEAGFDCBCCBCBBGBDGEGCEHDDADHEDBADHDEFBEDBDGBCGAHHAEAAEBDGDGGDGABBECDEFDEFHCAHBDHBHGGDFFEFDCCDACBAHEABCHEEFCEFHGFHDEBGEBHHHHCFHEAHBAHCDDDDCGFCHFCHCCFCD,False +730,10.0,12.0,10.0,12.0,5.0,3.0,7.0,9.0,GGBHAHCBEBDABDCEDEGDCGDAFAHGAHDADDACHACGECADHABCCGCBBCBBHHBFDEHDBDFB,False +731,8.0,9.0,15.0,9.0,17.0,19.0,15.0,6.0,BHGBCGBCDBCFBCBACFAFEGFECFEGFGCEGCGADEFECHEDEEFFEFFGFFGDFCEGCACBAFADCGEEGDBADFAHHDGHGFEEDCEHFFBGEC,True +732,15.0,25.0,16.0,23.0,8.0,23.0,16.0,19.0,CCGCCHDFHDFABAHDHGDBFDHDDBBDHBGHGFDDFGGHEHABDFCHFAFCACBBDDBDFBDABHABGBEDBEDAFCFBCFGEBBHCBABGABGHBGHFGCFGCFGEBEFADCHFHFFCDDCHAEHBDGADAADGFCFFBFEBH,False +733,26.0,12.0,25.0,16.0,6.0,12.0,11.0,16.0,DDEFFEHBCBCAGCHGBHAAHCAHAHHBHHGGHCFDCADCADABFCCGAFDAGHCCCACFADFADAHBGBCFFDBCHAFAAEDEBAHBAEFAFBADBDDADCCCCCCCACCGCDGADGAEAHGH,True +734,24.0,26.0,16.0,18.0,21.0,14.0,24.0,22.0,HGDGADCHDBBAEBDEBDEBEEDECFBCAGCBCHGDBGEBDEBEEBDGBGHHFCDDHGDAGHADEBDAAHBGBAHAEEGEBGEBAACFHCFACFHFAHFAHFDHCBEAHEHBCHAHAEDGFBGDBGFBHBEGDGGACEACACBACFAGGEGBFBHAGHAGCFGHF,False +735,22.0,22.0,29.0,19.0,27.0,26.0,31.0,18.0,FACFCCFCAHCGBBDADAGDFEEFAEFAHADEGDACBFCBFBHGCGGCFFBGFGFBBHHBCAADGCDECGGCGGCAGCEGEGGDDGAGHAGHFCFCEGDGCFFBDEBDFBFEEEHEHBEAEEAEEAGEFDEGDBBEHGAGFDGEDHBCHGAAAAABCECCECCHCCDFHBFCEGEDGFBFCBFHBFHDHHCGEB,False +736,3.0,2.0,3.0,3.0,1.0,1.0,2.0,0.0,DCBDCBGCAGADEAF,True +737,25.0,20.0,13.0,20.0,9.0,15.0,15.0,17.0,BBCBGDDHBCECEDCBDHGDAGDAEAACDBCDAAHFAEFDCFAFBAGAGBABHABDABFAFFDDHHHHBFHDFGGHDCFGGHHGAAEAABCAGCBGCEGABCADEBBEFBDFHGFHDFHCFHAADEBDGADABH,False +738,15.0,21.0,15.0,20.0,23.0,14.0,16.0,14.0,HBDCBCCDFDDBDABDABDFDHHBEGEFGEFGECGECGECABBEGFEGFGFBABDGBHGBHCAEBBEBEDDDBHDAFCACCEBHGGDEDAEACFBFFBGFGEEHHEHEAHADFCDCAFCDEBDCDEGEHGAHAHEABE,False +739,6.0,4.0,7.0,3.0,11.0,9.0,13.0,4.0,CEEGFEGFDGBBEFGGDEDHCCEAFEAFBAFGACCAGAFEBFEGFGCHGEHGECGHG,True +740,18.0,18.0,17.0,21.0,22.0,23.0,24.0,19.0,CHFCHDGHDGBDCFEEFEDGHDAHDAECAFGFFHFCDEGAHBDBEDHEGAEGAEFBEHAEHABBAHFGECAHBFCDFDEEDEGDACBFHDFBGFGFEEFAEFCFBCHBDFAGGAGGAGBAGBEGEGDDGCDBBDBGEFGDDGHBBECHFCHCCFAGHCFCAH,False +741,9.0,8.0,14.0,9.0,12.0,8.0,10.0,8.0,HHAGBAGCACBHFBHFDEADGBFGCDABDCEDCEFABGECCEBCDGEEEEECECCFACHAEFGGFCGFDGDACDHHBH,False +742,12.0,15.0,13.0,8.0,14.0,16.0,4.0,12.0,AFFFBFFBCEAFAAEBHDAEAHBCHFCHBDHBFHBDEBAHGFHFBEGCFHCEAFEAHABDBEDEEFECHECGECFHCFCCDCCGBDABDBBEFA,False +743,10.0,6.0,7.0,8.0,13.0,10.0,9.0,5.0,AFAAEBGEBEECEEDFCGGHDGDFCFGHFBHEHDDAADEDDECBEFBECHCGAAFFAFEAGEAGFBGC,False +744,4.0,4.0,4.0,5.0,4.0,3.0,5.0,8.0,FHDHHGAHBHDDHGDAFEACEACEGGFHBCHBCGEDB,False +745,5.0,2.0,6.0,1.0,2.0,4.0,4.0,5.0,CHHCFFGFGAAGAHGCHABEACEHCBFCD,True +746,6.0,7.0,9.0,8.0,5.0,5.0,6.0,0.0,GDGGFGCEDBEDACDCCFACFCDABDACAACBEBBCFBFEEGBDGD,False +747,23.0,21.0,27.0,20.0,27.0,21.0,28.0,26.0,DEADBCCGHHGHDBADBADBEEBFEBEBGGCAEDAHDFDGHEAHEAGEDGEFGBAGHFHECBCAEEBEGFFFHHHDHHGACGEEDCADBAFBHGBAFBDFCDCBGHFHAFCCDCGACGAFGCEGCHBBDGCHFDAFGGGBHGBHAAHCAGEDCCGCCHBCHFFHEFCEFAAGACGCEECECHEBHEGEDFEDF,False +748,3.0,5.0,1.0,5.0,3.0,2.0,3.0,3.0,DBGHEAHDADDADECFEGBGHBFBB,False +749,11.0,7.0,13.0,10.0,10.0,9.0,18.0,6.0,AGEGGFDHECGGCGBCGECBCCEFCADCGHCGEGBEBDECGGCAFHDDHGDAGDAEAEFDGADGAFCCFBAFEFDGFAGBAHBH,False +750,19.0,21.0,8.0,26.0,26.0,23.0,18.0,20.0,FEHFHBCHBCHAAHDGEABEDCECBDDAFFAFDGDHCDEGDFADCHDEDEEGHAGDFGCFGDFAEBDFBAGHAEEAEAAFAFBAFBEBBDDBDHEFHEHDEBDEFEBBAAEAEGBEDFHDHGBEGEFBHCHFBHEGGEFGEFGDFHFHGDBGDBFDBHDGA,False +751,10.0,15.0,9.0,6.0,11.0,12.0,12.0,15.0,GDEEDHHBBFGBHHBEHFHFBDCEGGEGCBCCAFCEFBECHEHEBHBAABFABFABFGFEGAEBDHCGHAGHAFCACGAHDHFDHGBBGF,False +752,16.0,16.0,21.0,19.0,22.0,24.0,24.0,17.0,HHEEFGDFCDFCDFGHFHABEGECBCGBCGBFGDFBCBAFFGCAGCAGBAGHGDHDDHGDHGEHAECADCEFFAFFDEGBAGBCEBAHFACCDCBGEHDEGAEFCEDBEHFHAEDBGAGFECFGGAGGEFHDHECHECFECFCBDCGABDBHDFEFFED,False +753,5.0,5.0,9.0,7.0,8.0,5.0,5.0,7.0,DHCDCBFEBACFGCHGCHGEDGDDEDHAGEACFACEAHEFCCFBDHBHBEE,False +754,1.0,1.0,2.0,5.0,0.0,0.0,2.0,1.0,GGBCDDCDDADH,True +755,3.0,4.0,2.0,11.0,7.0,7.0,7.0,3.0,DDGGDGFFEFFGGDECDEDFEDFBBHBGFBHDAGCADHDDEAEE,True +756,13.0,13.0,9.0,10.0,17.0,10.0,13.0,12.0,CGAEDBDFGGHCGBCFAEEAGFBFFBFFBEGEEBEEHEECDEGACGEHAFGADHABHAHHCGHFGHEHEAHGDDCAHFAEBAEDCBBCBBGBDEDDA,False +757,8.0,8.0,4.0,5.0,4.0,3.0,10.0,2.0,BDEBGHGGFDGFDAFCGGCEBBAACEDCADHABGGBGBAABGAE,True +758,26.0,19.0,23.0,17.0,12.0,22.0,20.0,22.0,DDGDEFCHCHHDHHCHGGHDBAFBFGBFEBCAFCAFHFFDCCDCEACACBFEGGHGGDFGDHCBGAFCAFEDBEAEEBDFGDAGBHBHHADGCDFCAHCHFCGFCGHCBHABDABAACHAFAAHCBHBFABFAGFDBFHBEECGAGAAGFAEDABACCEGH,False +759,4.0,1.0,4.0,4.0,4.0,6.0,8.0,4.0,GDFGAFGDGCFGCFCAHAHDFHEEHEEGDGAFGCB,False +760,2.0,2.0,0.0,1.0,4.0,1.0,5.0,1.0,ABEDBHAEGFGGEGGE,True +761,21.0,26.0,28.0,30.0,24.0,24.0,21.0,23.0,FDCHDHHDFHCCGFFAFAAGABBDGBCGBHGEHFHFBCEACEHEHBEABDBBABAGBFFBHDEEDBGFCGFCGFBBCBBDBGGGCDECDCFECFEABGCDAEHEHBEDDADFADGAEEAEFDCFHCFBCHBCHAEDDEBGEDGFHEDCBACDGFFCEGCDACABEGCDGHEECFCFHDFBDHADHADHACGDCDDHH,False +762,24.0,12.0,13.0,17.0,17.0,14.0,9.0,11.0,CEAAEBDEFDBCCBABBACBDBDDADGCGHAEHAEHBEFAEFAFCACHBHFEHADHFEFAGFGCDADDACDEDGEBGECAEBFEBEADGACFAHAACAAEADDFFGAFGCDHDHEFH,False +763,6.0,8.0,13.0,10.0,5.0,9.0,19.0,14.0,HGDFBDFGCHDCBGCEGCEGHGHHGACGFCAEEHBBGDHGCCGFAGHADHBCGDDBEAFDHFBHFDGCAGCGFFGHBGHCGHCD,False +764,27.0,23.0,30.0,22.0,19.0,28.0,33.0,17.0,AACCCCCCFBCDCCGCFBEFDGGDCGFCFFCAECBGBFCBGEHDEFGHFGHACHGFAGEAFFFCHFDGCHGDGCFGCFGCAGDBFFBECEGCGGBGHBDAEDABFABFDBDDBDAADGHHFBAECEBHAHHEFADFADFACAACGECEEAGEABADBDHEGEDGEDBFAHGAHGAGCDFBAGBGFFDCHBHEACGGBGB,False +765,18.0,15.0,16.0,11.0,14.0,19.0,16.0,15.0,CEFGFFADDDDCFAFGAFEEEAEHBEHCECAEBAECABHACHFCFGBGGBDABCFFFGFHGHGDEDABBABBAHFACGDFGDFGCBEEDFHACHGCHGBHFEGFAACECDGCHGBHCBHBAHAF,False +766,2.0,0.0,3.0,2.0,3.0,1.0,2.0,7.0,HHEHHCCHDGHDFCEHAEGA,True +767,17.0,7.0,6.0,11.0,18.0,9.0,7.0,8.0,HEEBEFBEBEEGHEFCEACFABFHBGEAEAACAADAADADDAFABDAGDEDAGDEDHCHFABEGDEFDEAEECEGHHHFGFAC,False +768,7.0,8.0,17.0,12.0,13.0,9.0,9.0,18.0,EBDDBCDHEEEGCEFDAFDABCBBHFGHGGHDCHFEHFAHAEHCFHCAHEHBEGECHEGDECCCCDCBHCGHCBFGECACHAFHDCDDHFDHG,False +769,20.0,21.0,9.0,15.0,21.0,8.0,21.0,20.0,HEDAEDGBFGHEDHEDHEBCGAEAAFAABHDHAEHGGGBEFDFFAAEAEHCHBCHACDBFGBGABHBBEBBAHBHHDABDAGDHEFEGBGGDCGEBGCHECHECHGBEDBEDBAAFGADBAGAHGBGDCGEEGEH,False +770,21.0,9.0,20.0,15.0,18.0,14.0,11.0,20.0,AGHAHEGHACBCDEHDEHEECGABBADBFCHFEABCBDEAGEAFEAFECFDCHDBDFADCAGCADCHDEADAAHFABFEDCEGCHFHHCEACGDDGHFGAFGAHHHECAEHDHHABCEFCHFCGCCEF,False +771,4.0,4.0,4.0,6.0,5.0,8.0,8.0,13.0,HGCHGCEBAEDFEDHAHHGEHDDBGDEGBHGFHGFCFFCHADFFBHGAHFHH,True +772,4.0,7.0,15.0,14.0,7.0,5.0,7.0,12.0,FCECCEHCHDDHEFHDDAEHECCGDDBDDBEDBFCGHHHBHHBCABCHBCDEDGCHFDACDFCDGCGGAGC,True +773,15.0,15.0,19.0,12.0,10.0,13.0,9.0,11.0,CDFCAAHAADAADBHCGEAHFBGCBCCEGCDCCDEAGHAGECHFHFFBFBHFBADCADEHBECBABBHFECAGCDDCFFFHDFHDFAEGAEGBCCBCEDGBBCB,False +774,17.0,15.0,18.0,13.0,14.0,14.0,9.0,11.0,BDADABGFCGHCGAGHAGFFDCCBAGFHDFHCFHCBACEACBAGBACBECFEBGABFBFFBHHBDEEDEAHEAGFDEFAFFBDHBECCCCDCEACEHCEAADDCBAEDDEH,False +775,12.0,10.0,12.0,10.0,14.0,18.0,9.0,17.0,FFDFGDFEBAEBHFHFFBFCBFCBACEGDDCHCHDGBEEAEHAEBACCCCCAHEAFFFFFHGBHDAADAHEFHGFHEDCAHHADHGFGCHGFEEHDEHBEGB,False +776,15.0,9.0,14.0,7.0,14.0,8.0,10.0,14.0,FGGCGFEGFEGEBBABCCDCHEHHCHGFDGAEHCEFCEGCAACEACADHABADBFDCEDAABEACDGCHHCHAFAGHEHBEFEAHBAHBEH,False +777,3.0,5.0,7.0,4.0,6.0,7.0,4.0,2.0,ACHDGDFECAEGAFGEBDFBCFCCFHCEECDBGFBEFB,False +778,13.0,16.0,17.0,23.0,18.0,12.0,11.0,15.0,HGEDGCCFHBDHDDECFEHAEBAEBHDCCDFCDCHGHFGHAABCAFCGHCGCEFFEBAEBABBEHBGHBFFDDGDAEDAEABBHBBHEDFEFCDCEDCEDHHCGDDDDDAGFEBBCDDADCAEEG,False +779,0.0,0.0,2.0,3.0,0.0,5.0,2.0,1.0,DCFGFFCDFHDFG,True +780,4.0,14.0,9.0,15.0,13.0,16.0,18.0,13.0,GFHBCDDGGEFBDFGDFEDHCBBGEFEAFEHBDHGFFECCDHGHCGBBGBEDHDDEDEEDBCFHGDHGFHGFHGFGGFGBFGAFHCDCAECAEBBEDBGFBH,False +781,14.0,11.0,9.0,17.0,16.0,19.0,16.0,13.0,AHAEEAEBDCFCAFEACDFGBGHHFBHDBFDCHDHHEHFDGFAFEABDGEEEFHFABFCGFGGBCHBEGBHACEADGACGCFGBFGAFDAGBAGFDHEDEEDEFDEFDGHDGDDF,False +782,17.0,30.0,15.0,20.0,20.0,24.0,22.0,25.0,GBEGHHGHFDDAEABGCBGDDCCHFEBFGBGDBGDBGCAAFGAFDEFGEFEFAEFACBGEBAEBHBBHBCHEHHEAHDDCBCFDADDHDGHFEHBHFBDBDHAFHFFHGGAFCFGCHEEHEDFAGBCHBFGBCGDCGBHBBCFBDBDEBFEFHHCBHGBEBAEBHEFAAFDAG,False +783,18.0,12.0,19.0,16.0,8.0,23.0,23.0,21.0,CAEAGEACHFBBCABCACFADGBFCCFGDFGFBGHEGHCCHABHGBHFBGEAGCCFDAFDCHBGHCGHDFEGEHGEHFDHBDFAHFAHCGGCGDBFAGFHHFHGFDDHGHFDAGBHFHEDDDDCCGCCGADFAFGAFAAF,False +784,26.0,24.0,29.0,15.0,21.0,16.0,22.0,14.0,GEEGAEGABFAFGEBBHCCCGGBHGBFDAADAAGAFGBEBBCCGCAAHAAHDBEEBGEDADDADDAECAECBEBHEFFADBCGECGCCDCGACBACFDCFHFDHGHBBHDBCECEGCBGEBCEFAECCCHFGECGCBACBFFBGFHCECAFBAHBHHAFDAGDECAG,False +785,1.0,0.0,2.0,2.0,2.0,6.0,1.0,1.0,FFFEFFEDFCDCGAH,True +786,20.0,28.0,18.0,25.0,30.0,17.0,20.0,19.0,ECEDCEBGECGBDDAGEBEEHHADHDECGEDEEFEADEAFEAGDBDFCEFBDHBHAGAAGCAGCHHCHDBDFFEECADBAGFCBBEBDEHHEBHFAHFBCEBFEGEHADBDHBDHCDBGDBHDCGBFEADEADHAEAGBBCBACEACFDCBDHBDGEGGEBGEFGBFCBGHFGFFAB,False +787,5.0,3.0,2.0,6.0,9.0,8.0,2.0,4.0,DAEDAECHGCHBEFFEFEDFEDADHEDAEFBFABFHFEG,True +788,5.0,9.0,7.0,1.0,4.0,3.0,1.0,5.0,EBABAACHBEHFACBBFBBEABCDECHGCHBCHFC,True +789,12.0,4.0,13.0,8.0,13.0,16.0,10.0,11.0,ADAAEBAEGDFGHFGEBGADFAFFAFFEFCECEEFEGFEDFCCECHHAFDCFGHEHBBFAGFGHACECGHCDCCHCCHDFHDGAAEH,False +790,6.0,10.0,8.0,9.0,9.0,8.0,9.0,13.0,CEAHHCFHCFHBEACFACDBGDBEHBGGCGGAFDHFCHFEHBABBHDHGDEAHGBEBEGBEDHEDGCDFHDF,False +791,8.0,14.0,12.0,15.0,11.0,8.0,8.0,8.0,EBHEBDCADCAGCABCGDEADEAEECBEDADFEHECHDBHGEGCFDCFBBBHBBDGHDFFDFFGBGHBACBFCHGCDCDDEBDA,False +792,10.0,22.0,18.0,14.0,21.0,20.0,16.0,23.0,DBGEHGFDGFECFHGFEGFBAECAHFHECBABHGFACEBDGBCGHCECAEGBBCDBEGEEGHEAAECGBFHBFHAFHCFBCDHCDHDBHEAEEBHHBCCBFHBCCBHCEDDEDDEFFHHFHFFHEFDAGBFEBHCBHDBFDGGG,False +793,23.0,21.0,27.0,21.0,31.0,27.0,29.0,18.0,AGFCEBGEFGHCGECBEFEGFCBFDBFHCCHCBEDDAGFBDCCDCCDEGHEGHAFHGGHDGDBADBAGEAEAGFFCDACFACFGCFGHFHEFHEDECBEBHFGDEGCEGDBAFCCFACEEBDDHCECDEADFGBBEABHACFAEFAEHAEHEGBFCAHGEFDEAAHACGDBEFBDBBCBCEHGEFGFGGFAGDAGEG,False +794,24.0,20.0,28.0,18.0,24.0,31.0,23.0,26.0,HHAHBAHDAHGAHECHECDEHEEGEFCECEFDEDDFCDFCHBBHBHFCGGEHCAHCDGAGADGCHGHFGEEGAEBABBAEFDGDHFFEGCBFBGHBGABDBCAGCEFEBFCFAAAGAGBABCAEAAFFBFFBEBDDFFCFFHFFECFHDFGCCACFAFHCFECECCFGHFGBAGBCDHHHCCHDCEDAEDGHFG,False +795,31.0,20.0,15.0,24.0,20.0,24.0,18.0,24.0,DDFDGFDGAGEBGEBGFHEDHBDBGHCFHBDCEACAGHADHGHFGBFHCDHDHEEHGGDGGEGDFGAEAEECGFCBFABFADAADAHGCFFHBFBAFDAFDBEBAAHAAHAAHAAFABCABEBEFDHDHEFHEDABHCDDDHBHCCGDHAECAEBEHAFBACEADFBFFEAFCAFC,False +796,6.0,5.0,4.0,8.0,8.0,11.0,14.0,10.0,AGGGDBHDBEDHHCHFAGFGEECFFAFFAEDAEFEGDBGHHFHDFGCGHAGHGGHGEBCEBDFGDF,False +797,13.0,13.0,14.0,16.0,20.0,20.0,14.0,14.0,FDCFDCDGCDGAFFFFHFBDGAEEFDHFGHGBFDAFHGFHGDEDDEADCHGBHGBACAHBECACHEEEEBBDFCEBBEBFEHAGCEBAEFCEFAGFAHFGHFGCFECADCGEADEHDEBDECHB,False +798,16.0,22.0,7.0,24.0,22.0,17.0,26.0,9.0,EFHFGCFGEDGFBGFBHACDACDAGBBGECEBBBDDADDADHGGGBGGBFEEDEFDEAGEAGEAFEDDBDGCDBBBGHGDHCDBDDEGEAFEADEABABBHFBFDBFDFEEFADGADECHBGEGFFGBBHEGGFDGAGAHGEE,False +799,20.0,13.0,23.0,31.0,20.0,22.0,27.0,27.0,ACCDDCDDCHDEGDBGEBHAHGDDDCDAHDGFAGHAEBFECFBCDECBAHEACGAEGFEFFGHADDGDDACEACECCFFFDFGHBHDBHDCFGCGACFCDHCBHEFDBDGCDCDEFDEFAGHAFHAHHCEGGDBGFEGHEHHAGFEBFGAHCBHCAHDADFGDEHDHHAGHFEHGEGGDGGBF,False +800,7.0,7.0,4.0,8.0,5.0,4.0,9.0,2.0,BFADCAGBDGDDGDDAEDEFBEABEBECGDGHAGHAGFGBABCGFC,True +801,27.0,24.0,11.0,26.0,22.0,20.0,24.0,21.0,FDEFHBBHDBDFECFEGGEGBBBFGBAGBGFBAEHFGHCAACHBBHBDHEABEFBAFGEDECDEGFGGHDGAGGAHCBHEEEFHEDHADFDHGEGFAAACDFDDFBDCEAHEBHEAAEFBDABAABHABDAGDADFAHFGHFGHCGDFGEBCDBDAGDBGHAHDADAGECDACDE,False +802,24.0,16.0,21.0,28.0,24.0,24.0,17.0,24.0,EHGDHECEADBDCGFCGDCFDEFDHFEEBHECAGBDHDDAAAAGEHGCCGBEGCEGEFDEBDAAGEFCAFABFBEAGEAFECCDDCDDHDHFDEFGAACEEEHGHHADHFHADHFCCAHGACGAHECBEBBDFBCFBHADDAGDCDFAHFAHFABFEBFECFHDBHDBHDGHFHFCDF,False +803,20.0,21.0,21.0,27.0,21.0,19.0,21.0,15.0,CHCDAADHHDHFEEFGGDBGABGCBCFAHFHFFGBDEBFEAFEHBEFDEFDAHCGGCDFCGCGECGEAGDBCEBGAADFADFCDAEDBDAHAEHAEGGEGAHGADFCHCCHBDBBGEADDADDBFDBCBBCBEGDDCEEAGDCGDFDEGBEBBFBAHCEHCFCFD,False +804,1.0,2.0,0.0,1.0,3.0,0.0,1.0,2.0,HBEHBEDEAG,True +805,17.0,17.0,12.0,11.0,12.0,11.0,11.0,14.0,CACCACHGBBBBABBDBGEGCAGFBEFAEBAECGBHHHHHHHFDEFGCGGBBBAFFAFFACAACGACDDEFEEDEADHAHCBHDGHABHEBGCFAHBEDDDFEDA,False +806,8.0,5.0,13.0,9.0,8.0,4.0,5.0,7.0,AABDACCACDACDBCBEEHEHCDHEDGEDADGFFCCBCGBEHCHHDGHECCFDCFAEGA,False +807,2.0,3.0,6.0,1.0,2.0,2.0,5.0,2.0,CCGFCGCAGEGGHBBHBDCFECA,True +808,8.0,11.0,13.0,11.0,20.0,5.0,10.0,7.0,EDGEBEBGEBGECCCADEEEBCEGEDBECBCCDAEDHECHAGHGCDDFDBFEBFEBEEGEFHAAGABGDFHDCHACBEDGECAHC,False +809,19.0,18.0,17.0,18.0,21.0,24.0,23.0,21.0,GGGGAGFDDEHDEHAEFAGHHHHCBECAGCEGEBGABGFBDCHDBHEHHGHFAHGCBGFDCFDCFBEFHHDAGFFGCEEDHGDCADAAHEEDEBHHFAFFABFACCBCABHGCGDBEDFEGFCGFBFBBCBBDFEGFECFAHDAEDAEAEEDCBGGFFFHA,False +810,20.0,16.0,11.0,12.0,13.0,19.0,22.0,18.0,AGFCHFDDFBEHGEHGBHGDCGFCHEGAGADFAGGAHAFBABBFBBGGAABAAEADEBDGCHHEBGCAEAHEGCAGFHDFHFEHAGDGFDBFBBFADCGDBGHFGHCCCGCDGBBAAFFAFHHFEHFEHEE,False +811,17.0,22.0,15.0,31.0,25.0,25.0,18.0,24.0,HAFEGGECCHDGGGHDGCDGDEAAEHGEFGBGGHGBEFEEBCHAEHCFHDFHDFGDGDBGDAFBFFBFHEECEDBEDHDBEDBFDBFABDEFCHAEFEDHCDAFDCBDABDABFCBCDHEHFCAFCDBEDACDEHFFHFFEEEBDEHEBHBHHAHGBHDHGDBCABDADDFDAFGAF,False +812,13.0,7.0,5.0,13.0,10.0,18.0,4.0,11.0,FGEADHABHAEHFCHFAAEEAFEAFDAFABEGGHFFBBDBHCAHADHBFADCCHEDFGDFDDBDFEDFEHFDAFDFFEHFC,True +813,30.0,25.0,17.0,27.0,18.0,16.0,23.0,20.0,DGAGBDGFDGFAAACAGCEFHDAHDBHCBACFACFGHFEFBHHBDHBAEDAHCEFDGCAADABGABDEGDGCAGCEGBABEABDFGDFADFABGBHGAFGDDGHDAHDCDDEDGECHEHGFBBFHBEBBCBDGGHHCEHBEGBCGADAADBHEFDEFHEAADCCHEDECAAABABB,False +814,24.0,14.0,14.0,18.0,16.0,18.0,16.0,21.0,ACBABDDGDGCCHAEHAEFDEFGHFGHFGDCGEBFDBGGBFACACFAGEHGBAFBAEAAEFHEGHCAEAADDHCABFHHEDHDHACHAGHACHGCHCHDDHABAAFADDBBABFHCFGCFEDDEDDHFEHFEGFBGEAFEB,False +815,13.0,9.0,13.0,16.0,13.0,6.0,10.0,11.0,EBHEDEGACDDCDGCDACHFCECCHGBHGBHCBEDAEDHFAFEAHEADAAEADDFFEGBDGEHHABGGHGCCADCDDCDHCABEFBEDBAG,False +816,3.0,7.0,5.0,5.0,0.0,0.0,5.0,2.0,DDCDBADBHGBGBBGCCCACBAGBDGH,True +817,5.0,5.0,2.0,2.0,3.0,8.0,12.0,6.0,HCHGCGFHGAEAFGHFGHFGFEADEHDFBGGGGGGFBFABABB,True +818,1.0,11.0,9.0,4.0,7.0,7.0,8.0,7.0,GABGHBHDBHCBECBFGHFGBCBBFEBECCEFCDFCGHCFCDHEFGEGBEBHDG,False +819,2.0,2.0,5.0,5.0,0.0,2.0,1.0,5.0,CDACFHHFAHDBHCCDCHDBGD,True +820,11.0,24.0,12.0,20.0,8.0,10.0,7.0,16.0,DDBDDECFEFFEBFBBABHAFHGGCCADEHHABDDDDCGHFABFABFHDCBDBGDBCDBFEHHCBHADHADBADCHDCBDHBEHBHABCGBEGBCDCGHBDAEFBBBH,False +821,9.0,5.0,8.0,7.0,7.0,2.0,8.0,6.0,DCDGGAGGCHGCHBBEEAGEGEFCEDADAADAAFCABCEHCBHBEHCAHDDG,False +822,4.0,6.0,4.0,6.0,8.0,10.0,6.0,8.0,DGEHGBHAFDDFEAHBFCBFCDFADFCDHGEHGBFCBHEHGEBEEHEFGFFA,False +823,11.0,21.0,15.0,29.0,14.0,28.0,25.0,13.0,GCBACBGFGGFADDGDDHCCBEGFEGBDBBDFFEFECFBCFBFFGFFGDDHHDFHEFDEDDAFAGFDEBEBBDDHDEHGCHFCGCAGCFGDGGHCFBBFBDCGGEGDEBAHFDEADEADFCDGABFDDFGDCGBFADABDGBHGHGFHFDHFEBCB,False +824,9.0,9.0,18.0,17.0,22.0,11.0,12.0,16.0,HDHHDBHCFHEEAEBDEDAEDBEDBHHAFFDDFCHGCHECDDCEEEFEDGADGCDCCHCAHCAHCEHGECGEGGHFDCCEECACBGCEGFGDEBAFFAGCGBEEEFDEFDBHBH,False +825,13.0,14.0,23.0,11.0,13.0,29.0,17.0,16.0,CFBCFDDFBDFBHFHGFAGEAFFBHFCCFCFACFACFDCAEBHFGGBAGDEEHBGFAGFHEDHGFEBFHHFGFDCFCBHEEGGCFGEFBCADHHDBFDBHDHACHCCGCEGAGGFFACCAECFHCGBCEFCEFCAB,False +826,5.0,8.0,5.0,6.0,10.0,4.0,3.0,7.0,DDEDAGAAGAHCDDBBHBGEEFHECEFHEBHEFHECEECBBCHBDFBA,False +827,20.0,17.0,26.0,28.0,18.0,27.0,26.0,26.0,ECFEGFEHFHHFABFABFEHABHAGDBHDBHDBGDGCDGHABHAFCEHDBHGCDCEFEEADECDAFBGFEGFBAAGDGDDEEDHDABDABFAGFDGDDADCBDAHGHHGHHFFFFFGCDEDGGCBCFEDGCCGCCDCEFFHHAHDBHAFCCFDGBCCHACHDEGGEGCCDCCHCBGFAAFEGFGCHHF,False +828,10.0,8.0,14.0,9.0,25.0,17.0,21.0,17.0,ECHGCHBCGEFDEFDECDEGBECBHBHHFFGGFGGHDGHACCAHHBDCFGAFGAGEEHEAHECEEHEEBEEGDECFEBFECFHFFGGGAEGHEGFCFBAGAHEEGDAAHFHCFGEEDFGDC,False +829,3.0,3.0,1.0,2.0,3.0,6.0,4.0,4.0,DHEHHDFHGGBAGAFEACEGFBFFBF,False +830,13.0,14.0,5.0,14.0,12.0,16.0,14.0,22.0,GDABFFCGFEHEGFFBHCBHEDHFGFBBFEDEHDHHGFHAEHAEHCEHABHADGEDGAFGHBCHAGHADHEFHFFGFGBAABAABDGBDCHDGBEAFHHDDBDHBFHDEG,False +831,30.0,21.0,25.0,25.0,16.0,20.0,17.0,32.0,ABDAGCAGBEEEEFEEFGBFGACGBHGBHCAACAACGCHGHADHACEECHDHACHFEGEAGDAHDAHDGBBHBFHGCHEHHAFGFFDDBGHHDHDEHABBACBHCADFDDHBDHBDCDCBDAHFFHDDBFHAGCDBFFEECCECCGHAHCAHBEHDACDAHDFCDAHDBBFFBAFCFFCAHAAGAC,False +832,25.0,27.0,23.0,20.0,26.0,20.0,20.0,27.0,AADBAGBCFACEEGDFBFFBFHCGDBHEFHCFBFBEEBHCCHCHBEBGABDAHDFHDHHFEHGECGFCBHDFHABBDDBDFHDGCGCCGCDGCHBHEEDEHDHBDEEHEGHBBHFBHFBGCEGEDAEGAECCEAAEACBAHDEBAEBFGACGAFAHDABAHDGCDEAHEAFECFGAACBACHAGBFGE,False +833,25.0,13.0,14.0,24.0,17.0,12.0,19.0,18.0,AEBDEBFCFGAEEHEAHBAHDCFDHFBFAGFAGAEGCCDCAAGAHEHHGAHEACFDEGDCFBAGGABGADGCDGFEBFEAAAGAAECBGDFCDBEDHEBCDDHDDHDGHDHHGCHGEBGHCAHDEEDCDDBADAAGABHDDF,False +834,15.0,10.0,18.0,19.0,15.0,14.0,14.0,17.0,GFDGHHGDHFHCFDBEBGADGACECCHHCHFAHCEHCHHDEHAEBADDGDBGDEEDECDFCAFEEFEDDHDCGAHBAGBDEADGHEFDFABCEBFGBCABCFGCFACGDHDEHACACCAFGF,False +835,20.0,10.0,18.0,14.0,16.0,28.0,23.0,12.0,CBFFGFCHEDBFHGFEGFEGFEDCEDAEHAGGGGFGGCCCDGCFGCFHAFBAFBDFCFFHAAGCEGAEGHEGDFAFFCDFADECHEAHGFGEHGEBDDBABFABABECHCFGCDDFFGFAACAAEDHGGHECDBAFCAFAF,False +836,30.0,20.0,19.0,16.0,19.0,13.0,25.0,21.0,GEHGEGBFGFCGFAGHHGFGGFDHAAHECBAGGAGHCGBCABFHBECAAHAFCEBCEACEADDADCGHBDHGFEDBCAEGAHGHCGHCGEBBHGDHEDHDFBEBBFADEAHEACBAEGFDCAABAABAABGAEACHBHDGADHAEBACHDGDAGCEDCEFCBF,False +837,11.0,6.0,11.0,21.0,12.0,11.0,14.0,20.0,CCGFFHDFDCHECHGCEGCGGDDGABGAEHDEHGGHGHDDHDABDHBHFFGEFHDAEDFEDFGFAHHHCFHAEDGEHCHFDADDGDBADAHDAHDCDCCBEHBEAE,False +838,2.0,11.0,5.0,5.0,5.0,11.0,2.0,7.0,HHAFDBFCBFHBFCBHCFEBHEBCFBFEBEHBDDDEDCABBFFGFFGH,True +839,10.0,18.0,12.0,15.0,22.0,22.0,14.0,20.0,GHGGHDGHEHCFHBHHGHGFDFFBHGBDFBCFBFEBAHAACAEBAFCEFHEABGAHCBCCADAEHFDHFEFFEHFEHCECGHFEBFGCFDBBDBDDCEDEEDEEFBFFGDBBEBGEAEHFDCEGEEDHGDHBF,False +840,6.0,5.0,3.0,4.0,8.0,4.0,5.0,6.0,HFAHFAGABEEHFEBBEABCGBGAFGAECDEDHEHHEDGDC,False +841,22.0,25.0,12.0,20.0,30.0,18.0,24.0,19.0,CFDABGGBGGDGGBGDBGDFEHGEHAEDEEDEEAEGABBABHABFEGAAAAFAAGHFEEEAHFBBFBDHEHAGHADHFDHEDHEDCFAHFEHGEHEEHCBBDBBGBGEBCEBFEHDCFAGFECABGDHEFFEBEACCHEGEGCAFDACECDGDBHEFCGFGGBBBDBDDA,False +842,26.0,32.0,18.0,28.0,33.0,16.0,26.0,21.0,BDFEACGAHGEHBEFBDDCDDEBGFBAHCGBBGCEDEHBAFGGFBDFDABCCBFCBHEBEAFGAEGFEGEDGAABBHBDCAAEAEEBEBGDGGDGHDHHCACBEGGDHADHGEFEBDEBDHBDHBEHBHDDCDFCDCGAGGEGGEGFECAEABEAHDAHCFFCDHAAHAACAABFEEEBDEBDGBDBCEEHDBGEBEAHF,False +843,17.0,15.0,21.0,18.0,10.0,19.0,19.0,11.0,GCGCCGCDBAAFCFFCGCCFCBGCBHBGADGFEEEBEDCFDCFBEFAEGDDDDDAGACDEFDBFGCFGEFDDHCGGGGGAFACHACHACGADGHHCHBFAAFDFFDABBEBFHBHEBHCAHBADGABFDC,False +844,28.0,20.0,25.0,32.0,29.0,10.0,34.0,16.0,GCBGCEAHBHHGHCGADBHDGAFGCFEEFDEAABAAFACGACHAGEEEEEBDBDDGEAEBGCFGAFGCGACGAGFEDAGDAGDBGDFEBECDGBDHBDBBDAEHADAAHGDCGDEBAHBEDCGBEGHEDHCCEDDEDCEGCDHDACAABADGEEFCEFGGAHGCCGCBECECBDHDCADAGDGGDGGDECHEBD,False +845,9.0,18.0,18.0,15.0,16.0,16.0,18.0,30.0,FHHFCHBCEBFEBFBHCGHEGFEDEHABHBHCEHCGGEGGCGGDGHDFHBFHAGACEDBBBBBFHEDHAHHBHEGHEHFDHEBHDDHCDCDHCACADBHDAAEGHFCCECCFHHBHGDHCDHFDGFBGFGGECAFBFCEG,False +846,25.0,21.0,20.0,25.0,14.0,20.0,19.0,27.0,DHHAHHGHBEBFFBHACHBCHFEAFHAGEAGEDFFDHACGDCGEBDDBGEAFAAGAAHAAFCFDCAEFBEGHGDCFAEDABDABHGBHGFHFDGDDGDDHFBABCADDACHBCHCGECACDBCGBCFHEHCCBBHHHFHFBHECEDHDAHDFDDFBBFDBEGACGACGADG,False +847,19.0,22.0,26.0,32.0,24.0,20.0,17.0,30.0,FFFFFBEBBCDDHBEHDHHFHCDHCDBCDAFBHDGHDECDEDGEDCBFEFEHAHHAEDBDGHDCHECDEFHHADHCHBCHCDDCHBBHBEECCDFEDFDBGDBDFBEBAEFAHAGFECCACDHCEHCGGCGGCAGABCAGAGCDBADGEDFEGAEGAEHACHCBHABDBEDEDDHADGGFBFFHEFHCAH,False +848,9.0,6.0,11.0,10.0,14.0,15.0,7.0,8.0,EBECBHGDFECFDGFDHFDCEAAGDEFDEFDFFHCAHGBDDHDHFEGEGBAFCEFCAFCACCACBAFHFEHEEFEGAEBC,False +849,4.0,12.0,3.0,4.0,4.0,6.0,9.0,4.0,BADBFBBDBCDAGGEGGAHFBHFECBBGGCGGBBGBDFFHFEHAEB,True +850,11.0,16.0,15.0,13.0,9.0,18.0,8.0,14.0,AHEFHEDHAHCBEFAEABEBBDHGAGCECCECCEDGADFFBFFBFFACACDFCDECHHFDFFHFFGFBAHBCDBGDBGHHGHFBDBHDBCCFHDACABDGBCBF,False +851,14.0,6.0,9.0,8.0,8.0,11.0,8.0,4.0,CADAAFAFGGBDGBECHEGAEGCEGHEAFCGCCAFCAFDBEHBAAAFAFFECEDADGACFBDFHDFBD,False +852,13.0,17.0,14.0,11.0,14.0,23.0,28.0,19.0,AHFBHFEDBHCBHGDHDDBEFGAFBEDCEDCGGCAGCHGCHGCDCEEGFBBFHCGHAGDCFEGABFCBECBAFBAFHHGHEBCFAEGGEGAFBFGGGDGBDBFAEEBGAGHAFHCFHFFAGFHGFHFFHGGBGGHDGFE,False +853,17.0,14.0,15.0,18.0,12.0,25.0,14.0,18.0,FEEDCEDAEDABFABGHCGEGBAFBAFADFDDFBDFGDGEEAEHDGHCFHCHGBHFHFACAEBGHHGHAGAAFFDCCDHCGGCFDCFHCGECADCFDBFEBFBDGHDCHCHDAFFFHFBBEAFADFHBFHFAB,False +854,4.0,8.0,7.0,9.0,7.0,13.0,4.0,5.0,HAHBAEBCEFDHFGBFDDFDDFCGFBBCBFCFFCAFEDFBCGCDGEHEEDFDHFEBA,False +855,8.0,9.0,7.0,8.0,14.0,11.0,8.0,11.0,FCGGHEGHCAHEGDGCDHEBHEGEEFAEFCEAAFAHDEHFEHBGFBFFBFEAHEADCBBCBBCEGDDHFDFBHEAD,False +856,15.0,19.0,19.0,21.0,20.0,23.0,9.0,21.0,EHCABCEDCEDCHDBADEFFEAHGADFHBFEBFEHFEGCHGBBFBDFDCFHCFCGHCDHEHADFFEFHCGHCBABEEBEFBCDBCEHDACDBBDCBACBAEBDDCADFAEFEEHDGHDEEFBFFDHGHFGAFAHFCGFHBHDADAHC,False +857,8.0,14.0,12.0,26.0,12.0,12.0,24.0,18.0,DDGDGFHGDEEDEHGEDDCHGCAGDGBBHHAHDBHDBGACHCCHFCHGGHDGHDBFABCHGHGFDCEAGEADEGDADEGHBCFBGFGDCGBFDFFDCBDCGDGBEGBFGEHHEFHDFGDAEDBDDB,False +858,3.0,12.0,7.0,10.0,7.0,11.0,5.0,6.0,EHBFDFFCEGCEBFAFCCFECFHDGCEHAEFDBFDBAHBGHBGEBCDFDDFBDBDGBHBBD,False +859,15.0,8.0,5.0,5.0,11.0,6.0,8.0,9.0,AFHEGGEGBEDBACAADADGGHGFEGCEHCDAFECBBABHHEHAECFHBAHGABDEBAEFAEFAHAA,False +860,24.0,23.0,16.0,29.0,25.0,13.0,28.0,31.0,ABDBGHHDBEAACAHBDDDDHHGAHBDHDAHCGHCAEGFECFECGHAGBBDBDDBDGBDBAEBACDAHDBGDBCEBGEDDEBDBBABGGGGGEHAEGGGDFHDAHAHFAFDCHDCHEFBEAGECHFCHGGEGGAGFDHADEGHAFHBGHEFBCAGCAEBHEDHEDEEDFEGFHCEHDHHFCHEAGECHA,False +861,19.0,16.0,16.0,18.0,22.0,19.0,15.0,18.0,HBDHADGAFFFCFDCFDHFAEEDEEABBABHHEAEDAHDEHCGFEECHECEFGHFDHFEEGCBDFDGHDGHDCBDCAECAHBACGEFBFFAFBAFBEDHDAHBBDGEGCEGBGDFGAFGAHCHGFECAEGABAHBACBECECD,False +862,23.0,28.0,34.0,23.0,21.0,19.0,19.0,23.0,AADEFDECBCFBFEGCHHCBCAHCAEDAEDFGBAHBGBBGEDGEFBAFBABEABFAHFAHADGBHAAHAAHCFCAECBEHBACDDCDCHDHHDAHDAHCFBCDHCBBGDEDEHFBCCCCCDGEDEEBCBHCDEBEHBCGCDECGCCGBCGBCFAGGACBHBFCAGCFBDHBFHFECFGHEGCEFDDFGDG,False +863,11.0,5.0,11.0,10.0,13.0,17.0,9.0,9.0,HGFAGHEGFFAEFGCHCCHCFACEAFEAFBFFBEEDDDGGDFEBHDFEDFEFCEHCDAAFBAFHCFECHEDDABDAGCCGAHGEF,False +864,8.0,4.0,8.0,5.0,6.0,11.0,2.0,13.0,CGDDADAFHFEHACHFFHAFHAGABEFBHHCHFCFBEHCEHDEFDCFEFHCAHCAHB,True +865,6.0,7.0,13.0,8.0,5.0,5.0,10.0,8.0,EBBEADDABHGBFBHDAHDFCCCCCGDCGACEFCEGCGGCDHHBGHCGCGBFDDFEAHCAHG,False +866,13.0,18.0,13.0,24.0,13.0,21.0,16.0,22.0,CECHEHGAHDBHAACGDDGDDGBGFBACBAFGCFGEBHHBHBBFBBFGDFEBHDBAEEAGEHFEDGEDFFHFADDADFHCHEADCFDBEDCDDFFBFFHFGEFGHCDFBHADHFDHFHCGCAGDACEBDHBDGDHGCHBH,False +867,3.0,4.0,1.0,1.0,0.0,0.0,2.0,1.0,BGHBGBAABACD,True +868,12.0,15.0,8.0,11.0,24.0,11.0,16.0,16.0,GBGAFGAHEABDAHEEHEGHFBEGHCHHCBDFECAADDGHFHFGEAGEBCDGEDBEFEEFGDGGAHGDHEEHBEHGEAGECGEAHECHBBEFBHBBDBBDCBFEFEEFECAAD,False +869,14.0,6.0,19.0,11.0,20.0,15.0,11.0,18.0,AFHAEHAEHGFHACHADFFGGFEGFEGDEDBAFBDECHHGHCCDBCFECHCHFBEDEECHACDGFDCHCEHFHCFACEACEACBCGBGEADECEEGFEHFACEDHEDHAGHFCA,False +870,7.0,10.0,10.0,16.0,6.0,4.0,11.0,16.0,HCBDCBHCBACDCCDHFHAGHCCDECGEDGDAFHGHGBDDFADHGDHBDHBGHFHEAABGBDHEDHEHHEGDDGADGCBB,False +871,6.0,1.0,1.0,3.0,2.0,4.0,9.0,6.0,AHCGEDGAHEAHAFGAGGBHGAHGFGDFGFHD,True +872,3.0,5.0,3.0,3.0,6.0,1.0,1.0,2.0,BBBDCBEGHEFHDBADAECAECEE,True +873,2.0,1.0,1.0,2.0,5.0,1.0,2.0,3.0,HEGAEHAEBCFDEHDEG,True +874,7.0,21.0,14.0,14.0,9.0,12.0,13.0,10.0,FDBFBBDBADBHBAGDHHCGEFDEBGEGGFGBCGEADAGGADHBDFCDECGBCEDFHFGHFEAFGHEDCEDCBFCBCCBHBBHBBDCBFGBCBHDBCAFC,False +875,6.0,6.0,10.0,12.0,5.0,8.0,13.0,6.0,GCGGCGGHBFDDADDBDFBDGCFGAEGAFBBCBHHFDHADHAGCDGEDEFGGCECCHDCEACGDFF,False +876,19.0,14.0,14.0,17.0,5.0,8.0,26.0,9.0,ADBACAGCHGCFGHDADABGEDABDABAFGCFDCADGGGGGGGGGBGGBACCHHAAGAADAGDAGDCGDBFFBCFBEBCEBGBBHEGDDCCCBHHAFGDGADGDDAFCGHHE,True +877,11.0,23.0,26.0,15.0,25.0,13.0,27.0,20.0,DHHEHGFGGCEHCGDGEDHCDHBFEDFEAFHBDGFCBHCEECEECBHCACGACACHGBHGBGGECGBDHCFEEEHCGHCGHCEBEFBGABCDDEGGEGGEGFEDBEBBGBCGBHABGEDCABCFECAHHBBCBDCAGBDGBAGCAHFHEBCEGCDFFDEF,False +878,10.0,21.0,12.0,20.0,16.0,27.0,18.0,16.0,EGCEHFAFAEBBGACGEEDEBDEFDBBDCBDEDFFAFGHBDFBHBGHBEBEGDDGDGBHGBHBFFGDFCFGCFAEGHEDEEDEAFFFFFFCHGGDGAFGAFHDBHEBCAGHBFDFFBHFCHFCHCCDCFDHBDGBDBHFA,False +879,13.0,7.0,15.0,3.0,11.0,11.0,9.0,9.0,CHBCFBFGEFEHCCAFAAFCEECBBHEEGEFBEABAADGAGGFGFCGACEHCHCFECADCACCACFAHFHDGHGAHEB,False +880,18.0,17.0,11.0,7.0,12.0,11.0,12.0,19.0,GACGHHGCCDAEAEBAFGHFGHEHABHBDHGCHGCHBABEEBECDDBABBHFHGCBGCBFAAGDAGHHHCAFCABAABAABHAFDAFBGDCHFEBEEHEFHEFBFHE,False +881,15.0,14.0,12.0,18.0,16.0,16.0,10.0,24.0,EFDEFDHBEHAEFFBHEBGEFABHGEHDFHAFEBCDGDAFDAHAACDACDGCEHDBBBBHDHEAEFAHGDFDABHABHAEHFEHFHHFHBFHAFHAEDCGBGGDDHDEHCBCCHCEFDGGHCDCC,False +882,1.0,3.0,4.0,5.0,7.0,5.0,2.0,5.0,HDHBCGDFACFECFEFBDFDGHEEHEBHEDCE,True +883,10.0,19.0,13.0,15.0,16.0,14.0,11.0,10.0,FDEBDAHCBEFHFHGGHGEBGCHCEECDACEFBAFHCBCEBAGBFGCEGBEHDDHBDHCDAFDEBDFBDEADBADBAECAGDABCGDCFBGFBDFBEFBFGBEHEECF,False +884,4.0,20.0,14.0,12.0,17.0,18.0,12.0,16.0,DHCFHCBHGFHFEDFEDBCDBFHHGCDFADCGHFBDCBDHAGEFBEHBEDCEGCABFHBHCCCCBHCGGFGFFBFBBEGFEBBBCGEGHHHFDAFDEFBEFHEGDEBEEBEEB,False +885,4.0,5.0,7.0,5.0,3.0,5.0,11.0,4.0,GBBEAFCABHGBGEFGDDCBDCFGCAGCDGCGHEGHFCHFGAGD,False +886,4.0,2.0,5.0,6.0,4.0,7.0,8.0,6.0,DEGFEGHBGCGHBGHDFAFFAFDADGCHECDECFFCHADHGG,False +887,7.0,10.0,2.0,12.0,7.0,8.0,10.0,7.0,HDGHAEDCDDBGDBAEBGCBDAEGFGFBGFBDDBFHBEHADFGDFHHFHEDGADGAFEAGEBB,False +888,22.0,21.0,26.0,15.0,24.0,25.0,19.0,23.0,HFHEFEAADAGDBCEBGEBEFHEGHAGEDGADFEBFCBFBBFCEHADFEHGHHFDFCHFCHDBGDHAAHFCFAEBAEGCEGCFFAHHGHHFHHCHCBABGDHHDFABGCFACFECDEAGEAGFBCFGCEGCBBBEBAGHGGCBAFACFDCDDCFCAHCACCBEEBEEBEADCCEF,False +889,14.0,18.0,14.0,7.0,16.0,10.0,10.0,16.0,FHAHHEDDECCCHBCBBFBFCBACDAGHAGHBFHBCHBEGEEGBBGBBGEAEAHHBEFFEAFEDHECEEGABGBDGCABEABAFCHCAACGBHHAHCDHFECFED,False +890,18.0,20.0,25.0,21.0,23.0,27.0,22.0,23.0,ECFEGEBFABFABCDBFHBHABHBDHGFGBFGECGCFHADHDEACCBHFEGFACHECHFBACCCBEBBDFDAEAABDAECCCFCFFCFFCEGCHBEGDEDFBDEGHFCHFCFDCFEGGEGDDGHDHHCGHFDFBDHGHHAAHAEHFGAFGAEADEFCEFBEGBGGHDAEDCEHCDGBDG,False +891,21.0,17.0,16.0,20.0,21.0,17.0,22.0,30.0,GEDGFABBHBBHFAGAEEAEAAECAEHHHBDDCABHGGHGCBAAFABFBFCGEBFEGEHHEHHDDHFGEEHDGHCAHFADBADCCGACHDGHAGHAFHAFBECBEDHGCHGAHGBDCEDCDBFDEGHGADGDHGFHCDGDFHBHHBHAECFECFEGFHFEDCED,False +892,2.0,4.0,1.0,8.0,1.0,2.0,5.0,5.0,HHHHBDABDGBDFFDCAHGGGBDGDDED,True +893,15.0,5.0,9.0,8.0,9.0,2.0,15.0,5.0,GGEGEEDAFGECACCAGFGEEDECDBAEGADGABAACCACCAHGAHADHGDGGHGBACBHBDEGAAGD,True +894,15.0,20.0,23.0,20.0,17.0,18.0,26.0,16.0,FGDFCFCCGBFEBEEDACGECGHCFFEDBBCHBFHBDAFHBGCFCCFAGHDGDGGBFEEGCEGAFGAEAFEDFEDBBDHBHGGGGCFDCEHBEHGCAAAAAGHCHHCHBGDDCDBGBBCABCABADBADBFDGGCCEDEEDGCGGDDGHCFHEFH,False +895,17.0,14.0,14.0,9.0,18.0,14.0,9.0,18.0,BGCDCCFADADBGDGCAEEAGEBEFBHHAEFFEHFEBEBCGCEBCEDAGGAHEABEABDAFDHBHHAAHBAHAHBAHCEHCAHFHBEHFCFFCEFCEHCHHCAEDFEDBGFGF,False +896,10.0,10.0,7.0,13.0,14.0,14.0,10.0,8.0,HCBCDHHGEAFHFCDGHEBDEAFBCFEDFADEADEADABBHCAEDGDDGFDAFHHFDGFGGFABFBCDBCEAGBBGEFGEFEEFEE,False +897,1.0,6.0,2.0,6.0,4.0,12.0,5.0,5.0,FBDGCGGDFEBFEFFEGFBGFHFFDFHBAHFEDFCHBBHDD,True +898,8.0,2.0,6.0,2.0,1.0,5.0,2.0,3.0,CFFCHDCFEHHAADAACCABAACGAFGBF,True +899,13.0,11.0,11.0,13.0,12.0,11.0,12.0,9.0,FCCGCABEBEEFCBGCDGCAECEEHAEGDCFFHDBCABDABEAFCBHABHADHGDFGDFBDFEDGHBGDGDAGAFECHEGDEGHFAHDABAF,False +900,11.0,8.0,16.0,15.0,15.0,12.0,12.0,10.0,HFDECDECFHCHGDEDEEBGHDAHDABCCDDFGDCGBCACCDGGFCGFEHEAGEAGEAFCCHCCAFEAFADEADHGDBFBBFBBFGCEAHFCDEEDHEG,False +901,6.0,5.0,13.0,12.0,14.0,4.0,0.0,2.0,DEEDEFCACAAEHEECDECAHCBDDECCBCFFDBFBCDECEECEDCADEDDEDACB,True +902,5.0,2.0,3.0,0.0,2.0,4.0,3.0,0.0,CFECFBAGAACAAGFFGBE,True +903,1.0,3.0,5.0,2.0,2.0,3.0,3.0,5.0,HEAGEFBCDBCBCFHCFHCDHGHG,False +904,8.0,10.0,8.0,10.0,10.0,10.0,8.0,8.0,HAEHAEDAEDGHFGFFAFFBFFGDABDECDEGGEGHBHBBCCFEDGECBCCBACHDCAFBDDEEDAHGBHBF,False +905,19.0,35.0,22.0,16.0,17.0,18.0,22.0,17.0,BEDEDGGBEBBDBGHBCBBCBHCAEAHBAGBCBHDBHDCHGCBGDAGDCCAGDGCDFCBFCBDBBDHAAEAGEGGEGBAFBHFGFGBFHEACECCGHCFFEFBCFBAFAABBBBBHDBEFBHFAGBEFCDGCFCDEEHBBFBDCGDEGFHGACAACAHHFGHEABE,False +906,6.0,6.0,11.0,1.0,5.0,2.0,8.0,3.0,GGECBACGCCGHCBFEGGAACAACDACBBCHCEFCEHBEGBG,True +907,10.0,11.0,15.0,22.0,12.0,15.0,10.0,11.0,CBDCFAHHHHCHDBDDBEDHCAECDFFDACDGBDABCFBCFBGDCFFCFEEHGGHGADGDFAFACGDCADFBCFGDFEDFDDADGAHEBHFCHDCDEEBEEDEGBE,False +908,4.0,0.0,2.0,5.0,3.0,0.0,2.0,3.0,GHACDADAEDAEDEGDHHC,True +909,1.0,4.0,0.0,5.0,2.0,3.0,1.0,1.0,FDHBDABFEBDDBDEGF,True +910,9.0,19.0,26.0,20.0,13.0,12.0,16.0,22.0,BHDCHGCHBCHDCBGCAEDFEBFBHDBHDGHEGECGCFDCHHGHHBHGFGCCBCCDCHAADFFDFFHEDCFBCEHCEHCDDFAGECGDBDBGFGEECBHCBACBACHCDEFDAHBCHCEGBGGCDDHDEHBAGBADB,False +911,5.0,1.0,2.0,3.0,2.0,3.0,0.0,2.0,HAHAADAFBAFEFCEDCD,True +912,26.0,20.0,25.0,15.0,11.0,21.0,19.0,28.0,BGFDDHABFAGCACFBCDBGDCCAAAHAAHFCHCEGGFFHHFBCABCGGGGBHEAHCAHBAHAHHACHFDHDAHABHCBFEBFADFGDCGFFHCGBCFBDFEDCHBBHBCGECGEHGFHAEHACHADAABHFDECEGBAGDHFDHCCFGAEGAECABFFBHCCHD,False +913,7.0,7.0,5.0,3.0,0.0,6.0,1.0,6.0,CDFCAFHACADCBBHBFHBFHFDGCABBABFHHAA,True +914,20.0,24.0,25.0,24.0,19.0,23.0,23.0,19.0,BDHFDGCHCAHFAHFGGCHBCHDFEDAEHCBFEBCGHCGFEACCAHDFGDFDBFBEFBEBGDBGDBCDECBFHEEEBCGBDDFDECHEHBFCAFADGADAHFCFFGFAGFEGEHGADDHDCHDBDDGEDBHABGGBEGBAHBHBDCFDCACCGEAACCACGAEGBEFBAFCCFGBAG,False +915,6.0,10.0,1.0,9.0,16.0,12.0,5.0,11.0,BFGFHGADDEEEEBEEHEHHEHFEBEGHFDHFBHFBDFDFFEBGDHCEBEEBEAGDADHAFAAFHBBEDF,True +916,19.0,25.0,17.0,15.0,26.0,25.0,27.0,16.0,EBBHBCGEEAEBCECGECHHCGDCECGECDBCDBAGCHGBFDBDBCEBFAAGAAHBGDFGAEGAEHEEHECGFFAFBEEAEEABEHBGHBFHDGCCFEFFCFFGFDHBAHAGFDGFDGHGGEDGEBGHGFFECBAFBHGEFBFGDFHDAADGGBAGBFCBFDEFAFBABE,False +917,1.0,1.0,0.0,2.0,5.0,1.0,1.0,0.0,DABDEEEEGFE,True +918,3.0,4.0,4.0,5.0,6.0,2.0,1.0,2.0,FCHDCBDCDEADEBDEBFBGACAEHEE,True +919,29.0,30.0,27.0,23.0,18.0,16.0,15.0,25.0,CECCDDBFGBEHCFACFCCAAAAABGDBDCBDABFBCEACABCGBHGDCGFBGHCDHCEHCBAFBFGHFHHDHFEHFEHCDBDDACBACGACGACFEDEBDHBDHAAEEGFBHHBHDAHBGBCGDAAHAFEBCCBDBEEAHEHFGHAHAABBABDHBDADDAECGBCEDCDCGEHAEHABBFF,False +920,6.0,8.0,6.0,2.0,10.0,1.0,2.0,2.0,ABABBFGBDGEECCEACECHEHBEABDBEEEACEACB,True +921,9.0,6.0,2.0,9.0,10.0,5.0,13.0,15.0,EBEDHGAHGFHGFBDEDDGCDGDHFAEABEGEGAHGAFEAGHAHHEHDEHDABDBGEGGBGHHACHFHH,True +922,0.0,4.0,4.0,4.0,5.0,3.0,8.0,5.0,BFCBHEBHDBCDFGGEGFEGEHGHCDHGDGGEC,False +923,9.0,18.0,18.0,28.0,20.0,33.0,20.0,19.0,FCFHEFDEBCBBCFACFDCDCAFCAHBDHBFGFHAFEAFEHGCHGDHCDHCFCGDCHBEGFFGDFGBHGDFGDFGFAHDBGGHHABEDFFDFFDFFEBFHDCEDFEFHEHHDGACFFGHBBHBADDDDCDEGDGGCEFCDBEBGEDEEBCEFGFFBEDGEDBFDE,False +924,2.0,5.0,0.0,7.0,6.0,1.0,0.0,3.0,EEDEEHEBAEBDDDADBHDFHBBD,True +925,12.0,20.0,17.0,18.0,18.0,15.0,13.0,21.0,GHHFHBACCFFHHFHHABHGDHFDEBABDDBCAEHABDEDCGDGDDGCDFFDHEBAEBAEBDCBGCEGBEHBFCEFDBGBFGBHBHHFFEEGECGECGECBHGBHDCHDAFDCFDEAHAHEAHACCEEFBBDCC,False 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+976,27.0,32.0,25.0,20.0,17.0,19.0,24.0,36.0,HCFABFDBGEFGFDCBDCAEBHEDADCADCGBCDACDBBHBBDAHAHHFFGEFHHBBHEFAEDHEHHBHHDAHCACCDDDAHCEECBBHBHHBGDBGBBGHCAHCFHFHGCHGAEGFFBBHCBHAAABACEGCGGCGACFACGHBDCBHCGGEHEBGAFFAEHHDFHDFEGFABDABGBBECBEBGAAFAACGHGHHGDH,False +977,21.0,23.0,33.0,29.0,26.0,21.0,26.0,19.0,BFCBCBEGFEGDEGFEBDACFGCDGADCDDCBBCGCDDCGCCGDDGBFBEEBAABAACFCCFHDDHDEBDEFCEBBGBEEDAEAHFCHFHHEBEEFFEFHEADEGEGGCGGADDFBCADDDCCGCCGCDGEDFADGDFGFFBCAAHAHEFHECAGFGDCEDCADBAHHHHEHHEFHBCCCCBBAABCAHHDGBEGCGG,False +978,7.0,8.0,10.0,5.0,10.0,5.0,5.0,1.0,DECDEBFCGFADFEBAECABABEGGECDFCGBEGCEHCBDCBCABCAEAFE,True +979,1.0,2.0,1.0,6.0,0.0,1.0,0.0,1.0,DCADFBDHDDBD,True +980,24.0,21.0,18.0,12.0,17.0,7.0,12.0,18.0,BBAHBHDDHBHFAHACBEBBCBAEEACHAHHEGBBGBCDCCAECAHCAGGAFFACFAHHEEAEHFGCACEACHFCHDDEDDEDDCBCCHEBHBAHEABBGBBADBGBBEAAGAADHEGEGGEGAFDACC,False +981,22.0,33.0,18.0,23.0,27.0,28.0,28.0,13.0,EAEDGBCFBAFBGFDAFAAGHAEBFHFFHFFGACDBDFCDFGDBEBBDHCFBEEGGDAGECGEFABFGBEDAEAHEGDDBEGCDABHBBGBDFBDHBGBBEBBHABAABDCEFGAFGAFBFCEFBGGHAGAFEDGEDCHFHBFGDHCFHCAGFDGCGECFECBECBECECABCAEFBEFEEGDBGDEGDBGD,False +982,22.0,20.0,15.0,16.0,27.0,17.0,27.0,21.0,GDFGHEGBEHCEBCHBEHBAHGCGGEGBBFDEADFFHADHEBHGDACDACDEBEEGEHBEGBEGHEBFAAFGFFGDFGDFABGHFHCEECHDGBDCBFFBGCBDDHDCGBCFAFHGGHEGACHECAEAAHCABAACAHEEDEADEFEGBGGEGAAGEBGFAHHAE,False +983,6.0,5.0,6.0,11.0,8.0,8.0,5.0,7.0,HBFHDFCEABBADECDEGDFCDFHBFEDECCFGHFAHGHHADEADFCDGDDGEBAE,False +984,9.0,13.0,13.0,13.0,32.0,25.0,15.0,18.0,EEAEEGEABEGHGFDADEEFAHHCBFGDCBBCHBCFDCFDCFDEFDEFCHFEFECFEHFHGFHGFHEBBCGECBDHHEEDEFCEGAADEFEHGEDFEHFEDFEGBHHFHGEEGEGAACFABFGFDGBEECEEFHBFHB,False +985,14.0,10.0,10.0,7.0,7.0,11.0,13.0,6.0,FAFAHGABAACAAGAFCDDCGCEFDBGBGACHECAECAEBAHDDFDBFDBFGBAGCHBEHBAGBECFFCEFGGGGGFH,False 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100644 --- a/README.md +++ b/README.md @@ -1,36 +1,10 @@ -# N-Back Sequence Generator with [Hidden] Markov Chain +# N-Back Sequence Generators -**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/src/main/scala/org/xcit/nback/markov/models/State.scala b/src/main/scala/org/xcit/nback/markov/models/State.scala deleted file mode 100644 index fbbd844..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/State.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * A Single state with a label in Markov chain - * @param label A simple string label, representing the state and node - */ -class State(val label: String) { - - /** - * Keep track of transitions from this state to other states. - */ - val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() -} diff --git a/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/src/main/scala/org/xcit/nback/markov/models/Transition.scala deleted file mode 100644 index bc20a9e..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/Transition.scala +++ /dev/null @@ -1,8 +0,0 @@ -package org.xcit.nback.markov.models - -/** - * A Single transition in Markov chain graph. It is stored in "from" node. - * @param to the ending node of the edge - * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). - */ -case class Transition(to: State, probability: Double = 0.0) diff --git a/src/test/scala/ThreeBackBenchmark.scala b/src/test/scala/ThreeBackBenchmark.scala deleted file mode 100644 index 0c7dad9..0000000 --- a/src/test/scala/ThreeBackBenchmark.scala +++ /dev/null @@ -1,7 +0,0 @@ - -/** - * TODO Benchmark 3-back simple sequence generator - */ -class ThreeBackBenchmark { - -} diff --git a/tests/benchmark_diagrams.py b/tests/benchmark_diagrams.py new file mode 100644 index 0000000..8fa448e --- /dev/null +++ b/tests/benchmark_diagrams.py @@ -0,0 +1,159 @@ +import pandas as pd +import numpy as np +from matplotlib import pyplot as plt + +import benchmarks.common as common + + +def tlratio(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2,ignore_index=True) + stats = [] + for trials in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == trials) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == trials) + targets2 = data[alg2].targets if alg2.shape[0] > 0 else np.nan + targets4 = data[alg4].targets if alg4.shape[0] > 0 else np.nan + lures2 = data[alg2].lures if alg2.shape[0] > 0 else np.nan + lures4 = data[alg4].lures if alg4.shape[0] > 0 else np.nan + stats.append([trials, (targets2/lures2).mean(), (targets4/lures4).mean()]) + stats = pd.DataFrame(stats, columns=['trials', 'tl2', 'tl4']) #.dropna(subset=['skewness']) + + plt.style.use('ggplot') + + plt.ylim(bottom=0, top=30) + plt.scatter(stats.trials, stats.tl2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl2[idx], 1)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.tl4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl4[idx], 2)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('T:L Ratio') + plt.ylabel('T:L Ratio') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_tlratio.png', bbox_inches='tight') + plt.show() + + +def time_per_trial(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for t in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == t) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == t) + time2 = data[alg2].time.mean() * 1000 if alg2.shape[0] > 0 else np.nan + time4 = data[alg4].time.mean() * 1000 if alg4.shape[0] > 0 else np.nan + stats.append([t, time2, time4]) + stats = pd.DataFrame(stats, columns=['trials', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.trials, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time2[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time4[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2v4_time_trials.png', bbox_inches='tight') + plt.show() + +def time_profiles(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 8): + alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + time2 = data[alg2].time.mean() * 1000 + time4 = data[alg4].time.mean() * 1000 + stats.append([ni, time2, time4]) + stats = pd.DataFrame(stats, columns=['n', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.n, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.time2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + plt.scatter(stats.n, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.time4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_time_n.png', bbox_inches='tight') + plt.show() + +def skewness(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 9): + all_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + skewed_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) & data.skewed + all_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + skewed_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) & data.skewed + num_of_sequences2 = data[all_alg2].shape[0] + skewed_sequences2 = data[skewed_alg2].shape[0] + num_of_sequences4 = data[all_alg4].shape[0] + skewed_sequences4 = data[skewed_alg4].shape[0] + skewness2 = skewed_sequences2 * 100.0 / num_of_sequences2 if (num_of_sequences2>0) else 0 + skewness4 = skewed_sequences4 * 100.0 / num_of_sequences4 if (num_of_sequences4>0) else 0 + stats.append([ni, skewness2, skewness4]) + stats = pd.DataFrame(stats, columns=['n', 'skewness2', 'skewness4']) #.dropna(subset=['skewness']) + + + plt.style.use('ggplot') + plt.scatter(stats.n, stats.skewness2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.skewness2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + + plt.scatter(stats.n, stats.skewness4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.skewness4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Skewness') + plt.ylabel('Skewed Blocks (%)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_skewness.png', bbox_inches='tight') + plt.show() + +if __name__ == "__main__": + tlratio() + skewness() + time_profiles() + time_per_trial() diff --git a/tests/benchmark_skewness.py b/tests/benchmark_skewness.py new file mode 100644 index 0000000..f468b4d --- /dev/null +++ b/tests/benchmark_skewness.py @@ -0,0 +1,97 @@ +import random +import heapq +import csv + +# Common parameters +alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'] +trials_range = (10, 40) +n = 3 +sample_size = 100 + + +def to_benchmark_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [str(ralph_skewed)] + +def benchmark_nb_gm_001(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_001') + + +def benchmark_nb_gm_002(filename): + import generators.nb_gm_002 as nb_gm_002 + + generator = nb_gm_002.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + # print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_002') + + +def benchmark_nb_gm_003(filename): + import generators.nb_gm_003 as nb_gm_003 + + generator = nb_gm_003.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + print(f"sequence {i}/{sample_size}: {trials} trials") + seq = generator.generate(trials) + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_003') + + +def show_skweness_diagram(filename, choices, title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + print(filename) + data = pd.read_csv(filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) #.dropna(subset=['skewness']) + #print(stats.trials) + #plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'{title}.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + benchmark_nb_gm_003('../benchmarks/nb_gm_003_2back.csv') diff --git a/tests/common.py b/tests/common.py new file mode 100644 index 0000000..e40c0df --- /dev/null +++ b/tests/common.py @@ -0,0 +1,27 @@ + + +# Common benchmark parameters +choices = alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F'] +trials_range = (10, 65) +n = 4 +sample_size = 100 + + +def count_targets_and_lures(seq, n): + mask = 'D'*n + for index in range(n, len(seq)): + if seq[index] == seq[index - n]: + mask += 'T' + elif seq[index] in seq[index - n - 1:index - n + 1]: + mask += 'L' + else: + mask += 'D' + return mask.count('T'), mask.count('L') + + +def skewness(seq, choices): + import heapq + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return ralph_skewed diff --git a/tests/nb_gm_001_bm.py b/tests/nb_gm_001_bm.py new file mode 100644 index 0000000..54f6cb3 --- /dev/null +++ b/tests/nb_gm_001_bm.py @@ -0,0 +1,75 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq) , str(ralph_skewed)] + + +def benchmark(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets / s.trials, axis=1) + plt.scatter(data.trials, data.targets_ratio, alpha=0.2) + plt.show() + +if __name__ == '__main__': + alg = 'nb_gm_001' + fn = f'results/{alg}_{n}back.csv' + benchmark(fn) + # skewness_diagram(fn, alg) + targets_ratio_diagram(fn, alg) diff --git a/tests/nb_gm_002_bm.py b/tests/nb_gm_002_bm.py new file mode 100644 index 0000000..c8af543 --- /dev/null +++ b/tests/nb_gm_002_bm.py @@ -0,0 +1,105 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq), str(ralph_skewed)] + + +def benchmark(filename): + from generators.nb_gm_002 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials, int(trials/3), 0, 0) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +import time +import numpy as np +import pandas as pd + +import benchmarks.common as common + +def profile(): + from generators.nb_gm_002 import SequenceGenerator + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, int(lures/2), int(lures/2)) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('benchmarks/results/nb_gm_002_profile.csv', sep=',', encoding='utf-8') + +if __name__ == '__main__': + alg = 'nb_gm_002' + fn = f'results/{alg}_{n}back.csv' + profile() diff --git a/tests/nb_gm_003_bm.py b/tests/nb_gm_003_bm.py new file mode 100644 index 0000000..fa6c19a --- /dev/null +++ b/tests/nb_gm_003_bm.py @@ -0,0 +1,114 @@ +import heapq +import csv +import random +import time + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq, time_per_block): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [time_per_block, ''.join(seq), str(ralph_skewed)] + + +def benchmark_skewness(filename): + from generators.nb_gm_003 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['time_per_block', 'seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + targets = trials / 3 + t = time.time() + seq = generator.generate(trials, targets) + t = time.time() - t + print(f"sequence {i}/{sample_size}: {trials} trials, took {t}s.") + writer.writerow(to_csv_row(i, seq, t)) + plot_skewness(fn, 'nb_gm_003') + + +def plot_skewness(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def plot_targets_ratio(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +def benchmark_targets_ratio(): + pass + +def benchmark_chunking(): + pass + + +def benchmark_n(): + pass + + +def plot_timing(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['time_per_trial'] = data.apply(lambda s: s.time_per_block / s.trials, axis=1) + plt.style.use('ggplot') + plt.title(f"{figure_title} - average time to generate a trial") + plt.ylabel('time (s)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.time_per_trial, alpha=0.5) + + # draw fitted curve + # import numpy as np + # p = np.poly1d(np.polyfit(data.trials, data.time_per_trial, 3)) + # plt.plot(data.trials, p(data.trials), color='red') + + plt.savefig(f'results/{figure_title}_timing.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + alg = 'nb_gm_003' + fn = f'results/{alg}_{n}back.csv' + benchmark_skewness(fn) diff --git a/tests/nb_gm_004_bm.py b/tests/nb_gm_004_bm.py new file mode 100644 index 0000000..b4ad4a8 --- /dev/null +++ b/tests/nb_gm_004_bm.py @@ -0,0 +1,26 @@ +import time +import numpy as np +import pandas as pd + +import tests.common as common +from generators.nb_gm_004 import SequenceGenerator + +def run(): + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, lures) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('tests/results/nb_gm_004_profile.csv', sep=',', encoding='utf-8') diff --git a/tests/results/2v4_time_trials.png b/tests/results/2v4_time_trials.png new file mode 100644 index 0000000..9be91b4 --- /dev/null +++ b/tests/results/2v4_time_trials.png Binary files differ diff --git a/tests/results/2vs4_skewness.png b/tests/results/2vs4_skewness.png new file mode 100644 index 0000000..a488e1f --- /dev/null +++ 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+210,87.0,0.0,0.0,88.0,1.0,0.0,0.0,0.0,EDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +211,0.0,0.0,12.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCC,True +212,0.0,0.0,0.0,66.0,0.0,65.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +213,1.0,0.0,0.0,0.0,0.0,21.0,22.0,0.0,AGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFG,True +214,74.0,73.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +215,0.0,5.0,0.0,0.0,6.0,0.0,0.0,1.0,HEBEBEBEBEBE,True +216,0.0,1.0,0.0,0.0,0.0,53.0,0.0,54.0,BHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +217,70.0,0.0,0.0,0.0,0.0,70.0,0.0,0.0,AFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +218,0.0,0.0,0.0,0.0,0.0,0.0,36.0,35.0,GGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +219,0.0,90.0,90.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +220,0.0,0.0,0.0,0.0,0.0,0.0,37.0,38.0,HHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +221,0.0,0.0,44.0,0.0,0.0,1.0,44.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +222,0.0,0.0,0.0,67.0,67.0,0.0,0.0,1.0,HDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True 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+409,0.0,0.0,72.0,1.0,0.0,0.0,72.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +410,55.0,0.0,1.0,0.0,0.0,0.0,55.0,0.0,CAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +411,0.0,59.0,0.0,0.0,0.0,60.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +412,61.0,0.0,0.0,61.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +413,0.0,1.0,0.0,75.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +414,0.0,53.0,0.0,0.0,0.0,0.0,52.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +415,0.0,0.0,16.0,0.0,1.0,0.0,0.0,15.0,ECHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +416,0.0,0.0,0.0,39.0,0.0,0.0,0.0,38.0,DHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +417,96.0,0.0,1.0,95.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +418,28.0,0.0,1.0,27.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +419,0.0,1.0,92.0,92.0,0.0,0.0,0.0,0.0,BCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +420,1.0,0.0,20.0,0.0,20.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECE,True +421,0.0,90.0,0.0,0.0,0.0,0.0,89.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +422,10.0,0.0,0.0,0.0,0.0,1.0,11.0,0.0,FGAGAGAGAGAGAGAGAGAGAG,True +423,0.0,0.0,0.0,74.0,73.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +424,0.0,0.0,127.0,0.0,0.0,0.0,1.0,0.0,GCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +425,1.0,9.0,0.0,0.0,0.0,9.0,0.0,0.0,AFBFBFBFBFBFBFBFBFB,True +426,0.0,0.0,84.0,0.0,0.0,0.0,0.0,84.0,HCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +427,33.0,0.0,0.0,34.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +428,1.0,30.0,0.0,30.0,0.0,0.0,0.0,0.0,ABDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +429,0.0,0.0,67.0,0.0,1.0,67.0,0.0,0.0,EFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +430,62.0,0.0,0.0,63.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +431,1.0,9.0,9.0,0.0,0.0,0.0,0.0,0.0,ABCBCBCBCBCBCBCBCBC,True +432,15.0,0.0,0.0,0.0,0.0,0.0,14.0,0.0,AAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +433,0.0,1.0,0.0,65.0,66.0,0.0,0.0,0.0,BEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +434,0.0,160.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +435,0.0,0.0,1.0,0.0,42.0,42.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +436,0.0,0.0,55.0,0.0,55.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +437,0.0,0.0,0.0,1.0,0.0,73.0,0.0,73.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +438,79.0,0.0,0.0,0.0,78.0,0.0,0.0,0.0,AAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +439,0.0,0.0,67.0,0.0,0.0,0.0,66.0,1.0,HCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +440,0.0,0.0,77.0,0.0,0.0,1.0,0.0,76.0,FCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +441,0.0,0.0,0.0,0.0,153.0,0.0,0.0,1.0,HEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +442,0.0,88.0,88.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +443,0.0,0.0,0.0,20.0,22.0,0.0,0.0,0.0,EEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +444,41.0,0.0,42.0,0.0,0.0,0.0,1.0,0.0,GCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +445,0.0,0.0,0.0,47.0,0.0,46.0,0.0,1.0,HDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +446,1.0,0.0,0.0,0.0,86.0,0.0,0.0,87.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +447,56.0,56.0,0.0,0.0,0.0,0.0,0.0,1.0,HABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +448,0.0,0.0,0.0,0.0,11.0,0.0,0.0,10.0,EEHEHEHEHEHEHEHEHEHEH,True +449,0.0,0.0,0.0,0.0,0.0,1.0,92.0,92.0,FGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +450,0.0,0.0,0.0,6.0,5.0,1.0,0.0,0.0,FDEDEDEDEDED,True +451,66.0,1.0,67.0,0.0,0.0,0.0,0.0,0.0,BCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +452,0.0,0.0,0.0,13.0,0.0,1.0,12.0,0.0,FDGDGDGDGDGDGDGDGDGDGDGDGD,True +453,1.0,0.0,0.0,0.0,56.0,0.0,56.0,0.0,AEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +454,15.0,0.0,0.0,0.0,0.0,0.0,0.0,16.0,HAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +455,0.0,21.0,1.0,0.0,21.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True +456,93.0,0.0,1.0,0.0,92.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +457,1.0,0.0,0.0,0.0,35.0,0.0,0.0,35.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +458,13.0,0.0,0.0,0.0,1.0,0.0,13.0,0.0,EAGAGAGAGAGAGAGAGAGAGAGAGAG,True +459,0.0,0.0,65.0,0.0,1.0,0.0,65.0,0.0,ECGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +460,0.0,0.0,95.0,1.0,0.0,95.0,0.0,0.0,DFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +461,15.0,0.0,0.0,0.0,1.0,0.0,0.0,15.0,EHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +462,0.0,0.0,198.0,0.0,1.0,0.0,0.0,0.0,ECCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +463,84.0,84.0,0.0,0.0,1.0,0.0,0.0,0.0,EABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +464,0.0,0.0,0.0,0.0,0.0,60.0,0.0,61.0,HFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +465,0.0,179.0,0.0,1.0,0.0,0.0,0.0,0.0,DBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +466,1.0,0.0,90.0,0.0,89.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +467,0.0,35.0,0.0,0.0,0.0,34.0,0.0,0.0,BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +468,0.0,0.0,0.0,1.0,7.0,0.0,0.0,7.0,DHEHEHEHEHEHEHE,True +469,0.0,0.0,0.0,0.0,92.0,0.0,91.0,0.0,EEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +470,0.0,0.0,46.0,0.0,0.0,1.0,46.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +471,0.0,0.0,0.0,0.0,0.0,1.0,158.0,0.0,FGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +472,1.0,0.0,0.0,0.0,0.0,58.0,0.0,59.0,AHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +473,0.0,0.0,6.0,1.0,0.0,0.0,6.0,0.0,DCGCGCGCGCGCG,True +474,0.0,0.0,0.0,0.0,0.0,98.0,0.0,97.0,FFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +475,0.0,87.0,0.0,0.0,0.0,0.0,0.0,85.0,BBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +476,0.0,0.0,33.0,0.0,0.0,0.0,1.0,33.0,GHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +477,45.0,0.0,0.0,0.0,46.0,0.0,0.0,0.0,EAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +478,0.0,0.0,0.0,77.0,0.0,0.0,75.0,0.0,DDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +479,73.0,1.0,73.0,0.0,0.0,0.0,0.0,0.0,BACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +480,0.0,1.0,0.0,0.0,37.0,37.0,0.0,0.0,BEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +481,0.0,92.0,93.0,0.0,0.0,1.0,0.0,0.0,FCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +482,0.0,0.0,0.0,1.0,0.0,0.0,0.0,24.0,DHHHHHHHHHHHHHHHHHHHHHHHH,True +483,25.0,0.0,0.0,1.0,0.0,25.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +484,0.0,0.0,0.0,0.0,0.0,37.0,0.0,36.0,FHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +485,21.0,0.0,0.0,1.0,0.0,20.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +486,0.0,35.0,0.0,36.0,0.0,0.0,0.0,1.0,HDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +487,0.0,0.0,1.0,0.0,97.0,98.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +488,0.0,93.0,0.0,0.0,0.0,1.0,0.0,94.0,FHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +489,0.0,1.0,0.0,93.0,0.0,0.0,93.0,0.0,BGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +490,0.0,0.0,0.0,70.0,0.0,0.0,72.0,0.0,GGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +491,86.0,0.0,0.0,0.0,1.0,86.0,0.0,0.0,EFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +492,0.0,65.0,1.0,0.0,0.0,65.0,0.0,0.0,CBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +493,0.0,0.0,0.0,69.0,0.0,0.0,0.0,1.0,HDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +494,0.0,0.0,144.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +495,0.0,45.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True 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+599,16.0,0.0,16.0,0.0,0.0,0.0,0.0,0.0,ACACACACACACACACACACACACACACACAC,True +600,0.0,21.0,0.0,22.0,0.0,0.0,0.0,0.0,DBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +601,70.0,71.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +602,0.0,0.0,0.0,1.0,0.0,0.0,53.0,0.0,DGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +603,45.0,0.0,0.0,0.0,0.0,45.0,0.0,0.0,FAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +604,0.0,1.0,56.0,0.0,0.0,0.0,56.0,0.0,BGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +605,0.0,1.0,0.0,0.0,0.0,0.0,0.0,195.0,BHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True 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+611,0.0,0.0,86.0,0.0,88.0,0.0,0.0,0.0,EECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +612,1.0,0.0,0.0,0.0,14.0,0.0,0.0,14.0,AEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +613,0.0,0.0,35.0,0.0,0.0,35.0,1.0,0.0,GCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCF,True +614,0.0,0.0,1.0,0.0,43.0,43.0,0.0,0.0,CEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +615,0.0,0.0,0.0,0.0,0.0,1.0,67.0,66.0,FGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +616,0.0,27.0,0.0,0.0,26.0,0.0,1.0,0.0,GBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +617,0.0,88.0,1.0,87.0,0.0,0.0,0.0,0.0,CBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +618,0.0,41.0,0.0,0.0,0.0,41.0,1.0,0.0,GFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +619,0.0,27.0,27.0,0.0,0.0,0.0,0.0,0.0,CBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +620,1.0,0.0,20.0,20.0,0.0,0.0,0.0,0.0,ADCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +621,0.0,0.0,1.0,24.0,24.0,0.0,0.0,0.0,CEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +622,1.0,0.0,0.0,0.0,55.0,55.0,0.0,0.0,AEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +623,1.0,0.0,0.0,0.0,26.0,0.0,26.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +624,0.0,0.0,15.0,0.0,0.0,0.0,0.0,13.0,CCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +625,0.0,0.0,1.0,67.0,67.0,0.0,0.0,0.0,CDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +626,0.0,0.0,65.0,0.0,0.0,1.0,0.0,64.0,FCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +627,0.0,0.0,0.0,0.0,89.0,1.0,90.0,0.0,FGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +628,0.0,0.0,0.0,0.0,1.0,0.0,51.0,0.0,EGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +629,0.0,0.0,41.0,0.0,0.0,40.0,0.0,0.0,CFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +630,0.0,0.0,93.0,0.0,0.0,0.0,1.0,0.0,GCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +631,0.0,53.0,1.0,0.0,0.0,53.0,0.0,0.0,CBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +632,0.0,0.0,0.0,14.0,0.0,0.0,0.0,15.0,HHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +633,0.0,29.0,0.0,0.0,0.0,0.0,28.0,0.0,BGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +634,0.0,66.0,0.0,0.0,0.0,1.0,66.0,0.0,FGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +635,0.0,0.0,62.0,62.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +636,0.0,31.0,32.0,0.0,1.0,0.0,0.0,0.0,ECBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +637,0.0,0.0,0.0,0.0,0.0,0.0,48.0,49.0,HGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +638,1.0,0.0,0.0,0.0,0.0,0.0,54.0,53.0,AGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +639,59.0,0.0,1.0,0.0,59.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +640,0.0,0.0,0.0,0.0,1.0,0.0,27.0,27.0,EGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +641,0.0,0.0,0.0,23.0,24.0,0.0,0.0,0.0,EDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +642,0.0,0.0,0.0,91.0,0.0,0.0,91.0,0.0,DGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +643,0.0,0.0,0.0,0.0,48.0,49.0,0.0,1.0,HFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +644,14.0,0.0,0.0,0.0,0.0,14.0,1.0,0.0,GAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +645,0.0,96.0,0.0,0.0,1.0,0.0,0.0,96.0,EHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +646,0.0,0.0,0.0,50.0,48.0,0.0,0.0,0.0,DDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +647,0.0,0.0,0.0,99.0,0.0,99.0,0.0,0.0,FDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +648,49.0,0.0,1.0,0.0,0.0,0.0,0.0,48.0,CAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +649,0.0,0.0,52.0,0.0,1.0,0.0,53.0,0.0,EGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True 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+667,1.0,147.0,0.0,0.0,0.0,0.0,0.0,0.0,ABBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +668,0.0,0.0,97.0,0.0,97.0,0.0,0.0,1.0,HCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +669,0.0,0.0,1.0,0.0,0.0,0.0,53.0,52.0,CGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +670,0.0,0.0,94.0,0.0,96.0,0.0,0.0,0.0,EECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +671,99.0,0.0,1.0,0.0,98.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +672,68.0,0.0,0.0,0.0,0.0,0.0,67.0,1.0,HAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGA,True +673,0.0,0.0,0.0,26.0,27.0,0.0,1.0,0.0,GEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +674,31.0,0.0,0.0,0.0,32.0,0.0,0.0,1.0,HEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +675,0.0,0.0,0.0,0.0,42.0,0.0,41.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +676,0.0,0.0,50.0,0.0,0.0,0.0,1.0,50.0,GCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +677,0.0,25.0,0.0,24.0,0.0,0.0,0.0,0.0,BBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +678,0.0,0.0,0.0,0.0,1.0,10.0,9.0,0.0,EFGFGFGFGFGFGFGFGFGF,True +679,65.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,DAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +680,0.0,23.0,0.0,0.0,0.0,0.0,23.0,1.0,HGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +681,0.0,1.0,58.0,0.0,0.0,0.0,57.0,0.0,BCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +682,0.0,0.0,0.0,0.0,0.0,68.0,1.0,68.0,GFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +683,0.0,0.0,0.0,0.0,96.0,0.0,96.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +684,1.0,0.0,0.0,0.0,66.0,0.0,66.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +685,0.0,0.0,0.0,0.0,0.0,1.0,0.0,21.0,FHHHHHHHHHHHHHHHHHHHHH,True +686,0.0,88.0,0.0,87.0,0.0,0.0,0.0,0.0,BDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +687,0.0,0.0,19.0,19.0,0.0,0.0,1.0,0.0,GDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +688,0.0,42.0,1.0,0.0,41.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +689,0.0,0.0,0.0,0.0,0.0,60.0,61.0,0.0,GGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +690,0.0,23.0,23.0,0.0,0.0,0.0,1.0,0.0,GBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +691,86.0,86.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +692,35.0,35.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +693,57.0,0.0,0.0,0.0,0.0,58.0,1.0,0.0,GFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +694,0.0,0.0,30.0,30.0,1.0,0.0,0.0,0.0,EDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +695,19.0,18.0,0.0,1.0,0.0,0.0,0.0,0.0,DABABABABABABABABABABABABABABABABABABA,True +696,0.0,0.0,0.0,1.0,0.0,56.0,0.0,57.0,DHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +697,10.0,0.0,1.0,0.0,0.0,0.0,0.0,11.0,CHAHAHAHAHAHAHAHAHAHAH,True +698,0.0,0.0,89.0,0.0,88.0,0.0,1.0,0.0,GCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +699,0.0,0.0,87.0,0.0,86.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +700,17.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAA,True +701,0.0,0.0,66.0,65.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +702,0.0,0.0,1.0,0.0,0.0,0.0,123.0,0.0,CGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +703,0.0,118.0,0.0,0.0,1.0,0.0,0.0,0.0,EBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +704,0.0,0.0,0.0,0.0,0.0,0.0,0.0,132.0,HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +705,0.0,0.0,0.0,0.0,0.0,23.0,1.0,23.0,GHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +706,0.0,0.0,0.0,0.0,6.0,5.0,0.0,0.0,EFEFEFEFEFE,True +707,18.0,0.0,0.0,16.0,0.0,0.0,0.0,0.0,AADADADADADADADADADADADADADADADADA,True +708,0.0,72.0,0.0,0.0,0.0,71.0,0.0,1.0,HBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +709,0.0,0.0,54.0,0.0,0.0,1.0,0.0,55.0,FHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +710,0.0,1.0,87.0,0.0,87.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +711,0.0,0.0,1.0,63.0,0.0,0.0,0.0,64.0,CHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +712,78.0,0.0,78.0,0.0,0.0,1.0,0.0,0.0,FCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +713,0.0,80.0,0.0,0.0,0.0,81.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +714,0.0,1.0,0.0,0.0,0.0,0.0,40.0,39.0,BGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +715,0.0,0.0,7.0,0.0,6.0,0.0,0.0,0.0,CCECECECECECE,True +716,35.0,0.0,0.0,0.0,0.0,0.0,0.0,33.0,AAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +717,0.0,0.0,0.0,1.0,73.0,0.0,0.0,72.0,DEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +718,0.0,0.0,90.0,0.0,0.0,1.0,89.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +719,1.0,0.0,0.0,67.0,0.0,0.0,0.0,66.0,ADHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +720,56.0,0.0,0.0,0.0,56.0,0.0,1.0,0.0,GAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +721,0.0,0.0,0.0,1.0,0.0,0.0,49.0,49.0,DHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +722,0.0,0.0,0.0,117.0,0.0,1.0,0.0,0.0,FDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +723,0.0,0.0,86.0,1.0,0.0,0.0,85.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +724,0.0,0.0,31.0,0.0,0.0,0.0,0.0,30.0,CCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +725,1.0,0.0,0.0,0.0,98.0,0.0,98.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +726,1.0,84.0,84.0,0.0,0.0,0.0,0.0,0.0,ACBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +727,0.0,56.0,56.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +728,0.0,1.0,0.0,24.0,24.0,0.0,0.0,0.0,BDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +729,37.0,0.0,0.0,0.0,0.0,37.0,0.0,0.0,FAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +730,0.0,0.0,91.0,0.0,0.0,0.0,91.0,0.0,GCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True 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+772,0.0,68.0,0.0,0.0,0.0,0.0,0.0,67.0,BBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +773,60.0,1.0,0.0,0.0,0.0,61.0,0.0,0.0,BFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +774,0.0,1.0,0.0,57.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +775,0.0,78.0,0.0,0.0,1.0,0.0,0.0,0.0,EBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +776,1.0,0.0,0.0,0.0,0.0,96.0,96.0,0.0,AGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +777,43.0,0.0,0.0,0.0,0.0,1.0,44.0,0.0,FGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True 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+989,93.0,0.0,92.0,0.0,0.0,0.0,0.0,1.0,HACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +990,0.0,1.0,0.0,0.0,60.0,0.0,0.0,61.0,BHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +991,0.0,1.0,0.0,0.0,0.0,0.0,32.0,32.0,BHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +992,0.0,0.0,34.0,35.0,0.0,0.0,1.0,0.0,GDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +993,0.0,0.0,0.0,0.0,54.0,0.0,54.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +994,0.0,0.0,0.0,1.0,0.0,39.0,0.0,38.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +995,0.0,0.0,0.0,0.0,99.0,98.0,0.0,1.0,HEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +996,86.0,1.0,0.0,0.0,0.0,86.0,0.0,0.0,BFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +997,0.0,76.0,77.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +998,0.0,0.0,19.0,0.0,0.0,0.0,0.0,1.0,HCCCCCCCCCCCCCCCCCCC,True +999,0.0,0.0,37.0,1.0,0.0,0.0,38.0,0.0,DGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True diff --git a/tests/results/nb_gm_001_3back.csv b/tests/results/nb_gm_001_3back.csv new file mode 100644 index 0000000..b2f89a4 --- /dev/null +++ b/tests/results/nb_gm_001_3back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,0.0,65.0,132.0,0.0,0.0,0.0,0.0,1.0,HCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCC,True +1,51.0,0.0,52.0,52.0,0.0,0.0,0.0,1.0,HCDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACD,True +2,0.0,61.0,0.0,62.0,0.0,0.0,61.0,1.0,HDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGD,True +3,40.0,0.0,0.0,1.0,0.0,0.0,0.0,80.0,DHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHA,True +4,4.0,0.0,1.0,0.0,0.0,6.0,0.0,0.0,CAFFAFFAFFA,True 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+401,0.0,55.0,55.0,0.0,0.0,1.0,54.0,0.0,FCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCB,True +402,47.0,0.0,0.0,0.0,1.0,47.0,0.0,47.0,EAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFH,True +403,56.0,0.0,0.0,0.0,58.0,0.0,0.0,56.0,EEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAE,True +404,0.0,39.0,0.0,0.0,39.0,1.0,40.0,0.0,FGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEG,True 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+3,12.0,15.0,11.0,20.0,13.0,17.0,17.0,22.0,AFAHGHGHGBEBCDDDDHHHABCEHEHEBBBAHADADCFHHHHHFEFCBDDFDGDEFCAGGFEFBDGEHECCBCFFFFFFHGEBBHHCBCACHHDDBFGGGGEGEAFDGDADGDGDGBEBAAHDDFH,False +4,4.0,4.0,8.0,8.0,5.0,7.0,4.0,2.0,FGDGECDCECGCDADAHFDFCFCGAFCDDDABEBHBEFEFBC,False +5,15.0,15.0,15.0,16.0,16.0,14.0,9.0,13.0,HGDGBFDHDADHBBBBBHBAAGBCEABCGFAFAFBGBCBFGDDDEAAAHDFACECECHFHFHFCFHEGEFEFDFDAAHDEECDABFCCCCGBEBDAHCECHCHEDEDEDAGEE,False +6,17.0,17.0,9.0,6.0,15.0,13.0,15.0,12.0,BEBEBHAGCFEHHABAHDEDGHFBFGFCAABAGFFFAFGECEBEAEAFBFCEBEGHGDBEFABABEGEHEHBGBGDADACAGHGHGBGBACGCAHFFBHAECDC,False +7,12.0,7.0,7.0,6.0,9.0,8.0,5.0,6.0,CEGBFEFEFEHCCDEBCCHBBBGAHACBGGDBDADACADHDHFEAEAEFGFAAEAHAFAF,False +8,9.0,13.0,10.0,11.0,12.0,15.0,11.0,12.0,CGCFDBDFHHEHFFGCDHEHCFCFAAEGDCEGHGCFCBBBCBGFGHGDFDBDADHBBEGAGABABHBEBEHGHADAFEFCFDBDEFEHEFEFA,False +9,13.0,26.0,23.0,14.0,20.0,18.0,19.0,27.0,HECEBEFFHFDCCFGBCBDBAHGHGCBBABHEFAFEBEBHBHGGCHBGGCCCCCFCBDDDEDHDEEEAAFAFGFDFCGBGHEHDHGHAFABCGGEHEHFBGBADEBEBEAAHBDCCFGGHHHBHBHGHBDBEEAEGCGCBCHCEFFFFCHDHCHDHABCB,False +10,14.0,18.0,15.0,13.0,15.0,19.0,18.0,11.0,AFACABDDFBBBEBECECGHFBFBECDCEEEDGDBHHGCBDDAFCBAAAGHCHCHEAFBFDHAHCFFAAAHBBBFBFBHGFBCBCFGGGHGDGDFEGEFCFEDGDGAGEGCGEGEFEFAFDGC,False +11,21.0,20.0,21.0,13.0,15.0,26.0,21.0,21.0,EECEFFHGCADHGEGEABCCFDEBABEBGGCACHFHFBFBFBAHGBGCGHDCDABHHAGABFHEBCFEGDFDFDFAFBCBCAHACFGFBFBFBFBDACCBCHFHEGEDFDFCAAAGGEBFAAACACHCHFGFBFGHGHAEAGCCEDDFHHHGHGHGDE,False +12,17.0,26.0,17.0,23.0,17.0,11.0,26.0,21.0,ABGCACGDDFHFHBCEHEAGBGBEBAHEBEBFAAHAFBCEGDGBAHGGGGFGDDDBABABHGGGCGDGHGHDACAEDEFECHGEGDABGCHCDDDDCBCBADAHCHGBGBGEHDCDBBFBABHBHBFBACHDEEHGHECDCDHDEFEDECFGHGBFBD,False +13,24.0,21.0,23.0,20.0,15.0,14.0,30.0,24.0,AHHHHAFEDHAFBFGFCFGADADCDGBBBBGDGEGBCBHGGGGCGFBFAGGGGHEEFEGHGHABCBFHGAGACBBDEDHDHDGBCACAHGCACEHECACHBHDCGCECADGDGDABADHFGCGAGAHHBGFDCHBHCAAABEEFDFDBDBEADAHGEGEHECCCBCFCAHD,False +14,1.0,0.0,2.0,1.0,1.0,1.0,2.0,2.0,DECGCGAHFH,True +15,7.0,7.0,10.0,5.0,8.0,4.0,8.0,9.0,HBABHHEEGAGAGEGHCDEECHCHGBCBCDDAEGCBCGEAEFDFBFBFAGCHCHCHAD,False +16,14.0,19.0,14.0,7.0,10.0,15.0,19.0,7.0,CEAFFGHGEGFDFDCACAGBDEAFCEDDFAHHFDFGBEACGCGBGAFECECFGHCEBAFGEGCBABEBHBHBACAGAGDGHBABCBCBGFGFGFGBBBBFBCBGA,False +17,17.0,15.0,14.0,12.0,10.0,9.0,17.0,6.0,EBACADACGBGBAFGHGHADCDGAAFFFADABAHGDGABBCBCACACECHFBFHDCACDGEBADDEGGGEDADFGFGCGFBBABCBEBDBCHGEGEGECE,False +18,14.0,22.0,17.0,9.0,14.0,10.0,25.0,20.0,EHCHAHEHAHCHCGBGCGCGAEBFBFGGCEFGBGHAHCBABABHHGHGCACHDEDBBABGGDGDEBBBHHGCAEGBFHGEGEGBCCGCDFBBGBFBDAEEHHHCFEFECEHGCGCBHDADFDAGAGAGFBB,False +19,13.0,27.0,12.0,18.0,19.0,17.0,20.0,18.0,BFGCGBHAHAHEFEDBABEBEDADGGGGBAFCGEBDFHBHGHGCBBEGEGBHDHDHBCBCACDBFHHCHBGAGAGEDADADCDCACGHEEEEBDFDFDHDCGGBGDEBBBABEHFHGEFFFBADHEFFCFDEBEBFFEBHBFBG,False +20,11.0,10.0,7.0,8.0,8.0,7.0,11.0,4.0,BGBABGHGCGFBFAEBGGEDEFAHEHACDCDADBGGAGAGADFBFBCBCEFBFDHDACCDAGAEEE,False +21,22.0,20.0,18.0,24.0,13.0,11.0,16.0,21.0,DADADHCACFCHEDAAAHGDDHAGCDEDEGBHAHBDBDBGHHHCHCECAAAEFEDECEDBHFABGBCAGDBEGEBABHFCBBABDFDGHGCBFBCCDHDHDGDHDHCHBGADAFACHEHBDCDAFAFAFAGGCGCFHGBDBEBEG,False +22,8.0,10.0,11.0,7.0,8.0,15.0,4.0,11.0,CBAEGDGEHEBGBFBFBDHCHFHBAEHFFGFCFBFCFEEHABECFFFFACAEHHDCDCDHDHAHCFCBCBAADF,False +23,32.0,19.0,21.0,23.0,13.0,27.0,21.0,27.0,GHCABDGDFFFAHHHEAEHGAGAGHEFEGBCFAFBFGCHCHFHBGCAFFDFDBACACHCHCHBFGFEACAFABEBEBHHGHFHAHGGAGAHAFCGDHDHAFGCBCHDAAAAAAFCFHGEFFBEBEDDDFDBCBDDDCGFAFADBDBEBCAGGHDFDFBCDEAGAHCCEHGHAHCDDDDABAFA,False +24,26.0,30.0,18.0,21.0,29.0,16.0,21.0,21.0,GDGDADAGAGDEHCDBDHAHEHFHAHAFBHBHGCEBHBDBHBHBEEABABABAEECEGEGAGADHDBEEGBCAADHGBFBCEAAHDEBEBFBFBFCCGCEFBABAEDBGFGBGCFCGEACDFEFBHDADFHCEAEBDHDCGBEFGCDCACDEBEGAGAEAEFDFBBEHEGEGHCACEFBHDH,False +25,17.0,15.0,10.0,21.0,16.0,11.0,16.0,22.0,BDBDBHHHAAGAEHEHCHCDADEBGHDAGEBHGAABADADEDECEHAHFBGCGBEHCGADFBHECGHHFFFHFBDDDDDFDFDFHFEDEDACAEAEBDCHHBFBABCBGDGEAECHHGHGEGHDAGGG,False +26,12.0,13.0,16.0,11.0,17.0,10.0,17.0,12.0,GEECBGFEEDHCEFGFEAEAHGEGEDDDHDCDCBHBCBCFCECEGAGAGAHECFCEAAFGFGCEHGHBBBGBGBCBDHEAEFHFHGBCDGGACHCGCDADAEBFBADH,False +27,14.0,11.0,17.0,13.0,14.0,21.0,16.0,19.0,AAECGGEGHCACACACHBHADCECBDHDHDFCFGHGDDEDHHHAHDFDACHBHAFBHHAEEECGGFGEGEBEFCFAEAEFFBFBFDGDGDGHFACCDFHFCGBBHBCGGFGEHEFFFFHFCBCAF,False +28,14.0,15.0,12.0,21.0,15.0,9.0,13.0,21.0,GGHGEDHFCFCACBCADAEEEEAHDGAGHGHEHEHBBECEDBBBDBEGDGBAEABCCABBECDDDFDFHGHGHDHGHGHDADHHCHBHCCBAFHFDDDEDHFHAABDFDFEGEAADBDCH,False +29,18.0,19.0,27.0,26.0,29.0,30.0,16.0,16.0,DEFFFAFAGDGEEBFBFGEBADACADFDCEEDEDFDCDEBBGDGHGHGFFFDFBEBEHCHFDCDCEGFGFHFEFCGBBDCHCGCDADEGEGCFAAEHEHFDACGCEABBDECBCBCEFEFBFCFCFEHEHDGACEBAGCEFEBACCCAEDHDHBCFCDEFFHDHDHDCFCAAAEBEBFDHA,False +30,5.0,11.0,5.0,8.0,3.0,2.0,5.0,1.0,BBFGGBABFGCCCDADAHBEDCDBABGEAECBDBDBDBDG,True +31,28.0,17.0,19.0,16.0,18.0,11.0,17.0,33.0,DHAFAHAEAHDHFHFAFADHCGGGDGDGHEBDHCHBHAEBCBCFEGHHHBHCAFDHEHEHCDAGBCBAAAGACCBCAFGBHEHBBEAHAHAFAEACGGEHAFABEDEDFDCGHEBGAGEEAEBBHDEDECHCGABHGHAHAHBHCHCHCHDGACACDFD,False +32,5.0,10.0,12.0,17.0,19.0,17.0,17.0,11.0,EEBHBFFFDDEDCCAGEFEGGDGDFFGEGEAEDEFCFCGCGCGFAEGECDHHCEFDDHDFDABFDECECEHEFDDGDGBBFBFHHGCECEFEHAHDHDGBBFBGHGBG,False +33,4.0,13.0,10.0,7.0,4.0,8.0,11.0,7.0,CGBHBCBCBHFHFECBADGBGBGBDBCFAGDBHGFGECEHBGBCCACFGFGFGDDDFCADHEHB,False +34,22.0,27.0,22.0,21.0,21.0,28.0,21.0,21.0,BABFBCCCCGCDCAGABAHFBAHCBDBDHDCDCDEFFHBHBCBCBEHDAGAEFBBEEEBEGAGHGDGCGEBFBDEAECCFCFGDGDGHBHAEFFFECCADHFFBGHDHEGAAEDEFEFCDCDCDEFCHADAEHFDFHBBEBEBFBFAFGFAAHGHGFFAFGGBABGHGBFBFDFHCHAHEGDA,False +35,24.0,23.0,21.0,17.0,28.0,15.0,20.0,21.0,EGHGAGEGCGDFFCEEEEEAHGEGFGFBCBGBDBACHCAGDDDDEDEHACGCECAFAFEFHCHCEFHDHEHBAEADBDBAFCHCEEEEHBHBECEAEAFGGGGCCHBHAAACABBEHFHBDFHHDHBGCAABEBGAGABBFADADEBBBBCDCACFGFHDCEHEBGADE,False +36,16.0,12.0,18.0,16.0,29.0,20.0,25.0,11.0,EEEBCFFDHDBBGHGHGEFDFACCCFCGAECECEAGFFFCFDAHAEEHGGGBGBGADDGDGEGCCBFEHEGEHACDGDGCCCFCEAFAEGEGBGFGBBBHFGDGFGAAHADADCEEEEDEAEFEAEBFFFHEGECEGEHECAFDDDB,False +37,1.0,6.0,2.0,11.0,2.0,11.0,4.0,7.0,DBFFFHHADFFEFBDBFBGDFFEBHBHFHGDGDGCCDDDDHDHF,True +38,11.0,12.0,15.0,5.0,3.0,15.0,15.0,13.0,HCCCCAEBGFCFBGAHHHHBAFGCGCGCGFGCAABFBABHBFBCAFHFAFGCDBGBGAGFCBBAADHDHDCGEGHGCGFFHFHDEFHFC,False +39,33.0,14.0,21.0,23.0,21.0,18.0,25.0,28.0,DHAHAHADGDAFAFGCHCHEHCHABACEDDDCGBHAEFFGCADADGBGCFFFGGHBAAFGGHFHFHECFCHCHBDEFGADDCGGGHEBEDEBEBEDFHCAAAACFGFBFBFADAEGBDCAGACACAFGEEECDDDDCGGGEEEEEGCADHHHHAHABAHGBBCACHEGGHDADADAHAHEHAH,False +40,9.0,21.0,8.0,6.0,13.0,11.0,9.0,15.0,HEBEGEGAGEBBBHFAFABCBCBEBCBEAFHGGGHEHCHBEDFFAFAHDBFBFBEBDFHHDHBHCHBHBDEFABGBCEDEBCACHHEAGBGF,False +41,13.0,18.0,18.0,16.0,8.0,20.0,16.0,13.0,AGDGBCDHFADAGFFFHHCFCFEBGBGFGFGCGCHHHHCGFBFGDHABCBCGDGECEFBFCACBDBDCFAFBDEDCFFBHGHBEBABDFDFDHDHACABDBAFAFDHEGACACBEECGCBDG,False +42,21.0,15.0,14.0,22.0,14.0,22.0,16.0,21.0,ACFDFDEDFDBAFDCDCDFFFFFACHCHGEDFCFEHADACEHEDEBAFAGGHGEDADFDHDHDHGADAGCCCFHBDBGBDEGEBHGFGHAHFBFBFEAABABACDDAHHGFGBGEGHFEABHBFEHHHGDFDCACABABGECHAH,False +43,17.0,19.0,23.0,19.0,19.0,21.0,20.0,22.0,GDGFGEDDDDDDFDFDFEHBHDGAECBHDEGHGEEDEBEDECGGAADAFAFADECFCDGDGFBHGCBHBACAGACFCGGGBGCHFHEHECECAHFHFGCGHBFCGCBCFEHEGEHBBAAABDHFBCCCCFFFHFCABFBHBHBEDAFEHBHACABECHCH,False +44,2.0,1.0,3.0,4.0,5.0,3.0,6.0,5.0,CHCHFGBGEHFDAGADEDEGGFGEDEHCH,True +45,17.0,20.0,26.0,20.0,18.0,24.0,15.0,12.0,BDEFBBBHHECFCFCBBFEDDADADGECEHEFCGCAFDCGCFFEDDGGHHHHHAFAFEFAFDFDFDEDFAACFCFCDCBBBCGCGDGDFCGCGBDCACBHDHEECBBEBECFCHGBGEGABCDCEFHFGACDFAFAECEBEBDACABAGFBA,False +46,5.0,7.0,11.0,5.0,5.0,3.0,8.0,10.0,CBDHFHCDCEGEHCHCHCHEGCGCGBBBBADAHGDGBACGEAHBHFGFCECAHD,False +47,5.0,4.0,4.0,5.0,0.0,1.0,5.0,3.0,ACABGBHBHBGDCACHCDAGFGAGDDD,True +48,21.0,22.0,13.0,24.0,16.0,18.0,24.0,19.0,DBDGAGBGFHFCABGFECEGBGHHEACDFDGCGBEBGDAFAHADADAHHBHBHAGABADEBFDGDBDGDGCFAFAFDDDDECGFEFEAHAHEHEHCBCDADGBFBFAEBCAHFHEDEGBBFDEHEBDHFGCGHGHGBGCDABCBDGHGBGDCEAFAF,False +49,5.0,12.0,11.0,8.0,8.0,7.0,11.0,9.0,FCFDGDHBEBECFBBHFCFCGDBCCCGCECECBDBGBEHDDBCAGAEHEDFDHGEGAHBHGAGAGFHBHBG,False +50,2.0,7.0,7.0,4.0,6.0,13.0,10.0,11.0,BBFEFEFHAHFDFGHEBABDFHBHEFGFGHEHGGGFDFEHCBGBFDFHFHCCGCGHGCCC,True +51,5.0,7.0,11.0,12.0,13.0,9.0,8.0,13.0,EFFBFDAAECCCHDHBHFEDBHBHDHDGGGGECDGHCFEFEDEDCDCDEDCCHFEFEGCGBHEHBHAHAGDFCEAEHB,False +52,15.0,6.0,11.0,6.0,11.0,16.0,3.0,8.0,BAEGCCEAHBFCCHFABEHEFDCHEBECACECEAFGFEFEFBFBFAFADADACACDFGFAFAFEFDAAHFDCAHHH,True +53,20.0,14.0,19.0,11.0,13.0,12.0,10.0,17.0,CHCECEHEGAHBFGHCHABCBCDCECEDAHACGCADDBBGFGFGFHAAACACFBEGGAGAEHCAAAFDFDCHBDBHGDFDHCBEFEBCBABHHHHDHCHDFEFABEBECAAAEACF,False +54,18.0,14.0,15.0,22.0,24.0,20.0,25.0,23.0,EGGCGCGDEDEBCBFDDDBFHDDGFBFEEEGDBDBEHFDFEACACADABEFDCECGGHBDCDBAGHGFBFECHCFEDEHEHAHEEAGCEEEEFGFHFAAGEEHHHHAHAHDEFGDGDBCGAGHFHFHAHAHDHDBFBFCEGGGGGGGHAADAGCDFFAHCB,False +55,3.0,4.0,2.0,5.0,2.0,5.0,3.0,1.0,EHAABABGBFDFGFGEDDFDCBCDF,True +56,9.0,9.0,8.0,11.0,11.0,13.0,8.0,11.0,ECFFFBCDEDAFEBEAFGFHFHFDEHEBEHEGBFEFHBABCCAGAGBGBDFHAHGHFCFDHDABADEDEDAHGGCDCHCD,False +57,10.0,13.0,10.0,15.0,7.0,9.0,16.0,11.0,HHCFEGEGEDFGABEHEADCHGHBDFDGDGHGCGBBDDCDCDBDBHCDEBAHACCFDGDFAFAFDDAGAGHGCGBGBHACBGBGAHEBFBF,False +58,15.0,15.0,14.0,21.0,27.0,24.0,20.0,28.0,FAFEFAADAGFBFACBCBHHCGFGFAFHCEGEGHHBDBFHFHBEGDGDAEEHEGCGDGHCDGDEHFHGCEEEGEGEDBDEEEEHHHHCHDAGFEBHFHAHFHFDDDCACHFBDDHDGDFDAGGEAEFBHEEEEBEHEFFCFCFDBHAFADCGCGFHDHEBABHB,False +59,11.0,16.0,18.0,17.0,22.0,31.0,15.0,17.0,FCECFCFCFBHCHBGBFHGEDADADEFEFHFDFDADEEADHGAEAECGDGCCFHFGFHFHFHFBFBFCEEEBEFFDEGGBHBEBHFCDDDDGHAFBFBFCACHCAFGCGHHEDCBFEFABCDCEGGGDAEBBBEDEFFFFECGHEHF,False +60,11.0,9.0,7.0,2.0,10.0,10.0,11.0,9.0,HGHCDCHCACBCEGEGEGEBBHCFGABEBFAEHHFBFAAGHGHFHABABCGEGFDEAAABFEFEFGFGA,False +61,23.0,23.0,21.0,24.0,24.0,17.0,27.0,24.0,EDGGCBCFCGCGCFCGCDCBAACHFHFHECACAGAHFHDBDEHAGADHGEGEBCAEAGDHAADDDDCEAEADBGFDBBBBDHDGDBBGCAAEHEGDGBGBFHCGCDBBBEFHFDAGHCDCHFHFGEHEGEGHGBEFACADAFCBGBGBFHDEDEDFBFEGHGHAHAEEEEGEDHAHACEFBHB,False +62,21.0,13.0,9.0,12.0,17.0,15.0,25.0,10.0,HFGFGBGEDEHGHAHFHGAAAFGHBFACGDBEBGAAFEGEFEFBGAHDEDECBCBFBEGAGAFCCBBDBAGABAGGGGGECDADAGAEFEDGACADDCDHDEAFHFHFGGGFGCABAEEEGE,False +63,6.0,6.0,3.0,12.0,7.0,8.0,6.0,13.0,FHEBEBHGHDAGHDCDEDEAFCFCHEEBAAFDDDFDHDAGBGFDHGHAHDHEHFHFHBDBG,False +64,6.0,15.0,15.0,8.0,14.0,13.0,8.0,8.0,CCEDEDBHHGDCBEFEFCCGCEAGFGEGECAHAHGBCFHACEBEBEGEFFFFBDBFBHBDDEDCBCBHBFGFHEAEBCBCFCBCAFD,False +65,6.0,4.0,3.0,4.0,6.0,8.0,5.0,5.0,CGCFEFAFAEEDEHCHBBDAAFAGHEHEBFDHDBAGFGFGF,False +66,17.0,8.0,15.0,6.0,16.0,16.0,11.0,12.0,AFGFGFGHGFECECECHAECCCFAHAFAEHGGCEBAFAEAEFGGHCBFAAEHFHFGBHEHGAFBFHCECEADFDBDBCACACAEAEBEDDACBDFHFHEGC,False +67,24.0,12.0,23.0,14.0,18.0,18.0,15.0,12.0,CCCFCFBHAEEDFDBAADAEAEABDBDGEHEGCCCACECHGEGEDECACFCFCHBFBAGAFFGHADBEBAAAAFAEECEDHDHECGGBHHCHDBGBABAGEFFGFAFADACADAGADCHFECGFGFHFCDCEGFCC,False +68,31.0,17.0,27.0,38.0,29.0,28.0,14.0,16.0,ACACBCFDGBHBDEGEAHDDEFEFEFEFDDHECEBDFDAEAEFECECGCHAHAHCBCDAHBDDDDEDEBEHGDDAFEFCFDDBCGAGACCECAADADABAFEDACGCAFAHDFDBDGCECBGBFFCHCGAEDFFFHADFDADGFAFADEDHABAGAGEHEFBFECEDEDCGEADADFDHBHDFDCBCFCDAFAECFCEHB,False +69,5.0,4.0,3.0,4.0,2.0,3.0,6.0,4.0,DAHAGAHAHAHFGCGEBDFDEDGGCFBBGBC,False +70,5.0,7.0,9.0,5.0,2.0,11.0,6.0,10.0,HAHDHDHBGBFCACDCHFBBHBHGDEACACEGFCDHBGFGFGFCCHBFFHFCFAF,True +71,11.0,10.0,6.0,19.0,14.0,23.0,11.0,9.0,FHFEADABECHFFDFDFHFEDECEFEFEFAFHDADAEADDCAGFGBBHGDGABDDFFFFDDDADEEGFGDABCDGGBHDHFGAGBHBHBEBEGFFFFFCCEDE,False +72,25.0,17.0,20.0,19.0,16.0,13.0,17.0,22.0,GDCDHGBEAEGDGEBDBDHDCDCBHDEAEHDCEFAAABCDCDABAGADADCFAFCGCACAFFBAHGCGCGEGEACHHECACECEHEGGFBDHFHAHAHGGDGFCECHFHFHCHFABABFDGABDEDABABHEACAFDHHGHAHBBBBEH,False +73,15.0,19.0,20.0,23.0,23.0,21.0,22.0,23.0,GFGFECGCEEGHFCBCFDDDHHGBGHGHDCDCFHAHCCCFHAADEBEHEDEDADCDCABEGEFDFHCHGGAHAHFCFCEADFFECGBDBDBDCCACADHGCGEGHFHGHGBFADEBEBEDGDBBACEEEHGBDBFFFFDGEGDGDGFBEHHHHAAEAEFBBBBEFH,False +74,3.0,11.0,6.0,11.0,10.0,12.0,5.0,7.0,ECHFHDHEFFHHDCFGEGFDBEBEFFFDBCBFEDCDCFEBBFADDBDBGBGBGBAHAHFDEDECE,True +75,21.0,13.0,22.0,19.0,30.0,19.0,18.0,19.0,HAHEEEFEDHDFDBHBGCCEEFEGGHGHCCCCCHGECEAHDBDBEFGHCACGBEFEHAFDFACAFEEEHABAGAFDGDADADAGBCBAEADAEFHCDCFGEHFHDEDCDFEFCCCEAEAEGGABFGEDBDBHBCCECEHEAEFGHGHDDAEAEHCFGFGFB,False +76,14.0,30.0,18.0,20.0,25.0,19.0,27.0,30.0,FCFBAEDEGEHEBGHGFEFCGDBDGGCGCGBEBHBHEAAAEECBCBCFHFCFDGAEHHFGGGGGHCHEHBABGBGHHDFAEBDBDBDBCCHAGGEGDGCCBCHFGFGHGHBHEFGHBFBCBHEHBBABCBHBCGEHEADDDBHFHAADEDBFHFEEGEDHDHDEDBDFEFEHCHAEGDHBFBA,False +77,25.0,17.0,30.0,29.0,22.0,22.0,23.0,24.0,CCHEAEHBBCBDADBDBDHGFEECBDFGFEAHDCGCDHHEHEHCGCFHGDGAGAGACACDDDFDFDGECCHDHCCEFAFEBAFGGHDCCGEDBDBDBCHCACDBAHCGCGAHAHAFFFHADCDCFCFHHCDCAEAGAGAGABFHGEGBGDFHEBEFCFAGBEEAABAGDGDFDFEABHCDEDEHEHEFCFCD,False +78,9.0,16.0,9.0,5.0,4.0,15.0,4.0,5.0,BCEADCBBBBABABCCEHFBDHFAAGAGHCFCBCBFDFAGAGBFBDBABFFFFFCEHEBDHFFFBFC,True +79,19.0,17.0,10.0,29.0,13.0,8.0,14.0,14.0,DEDEAEAEDDDDDDDHDGEBEFADAGBFFHDGFBBBBGBABFCHGDFDEACBBBAHADAHCGCAHDHEHABAGCGCGEDAGBDAACAHDBCBGBGBEDDDDDADGDFDHHFDAHAEEEHCDCHG,False +80,9.0,11.0,7.0,9.0,14.0,3.0,11.0,16.0,HEHEACBHBHAGEBEAEBHBHBDEDCFABCGAEABHEHDADABABGGGDGHECEHHDGDHHCHCDGFFHCBEDEGEGHGE,False +81,4.0,9.0,4.0,9.0,3.0,6.0,6.0,5.0,BGBACACHDGDFDFBFEAHFBDDEDEGHGHBBBFBADHDGCGDBFC,False +82,11.0,21.0,22.0,24.0,26.0,28.0,21.0,21.0,EDGDCDCFGEDEFFFFGEEEDEDEDADACHCEBAFAFCHEDBFEDHDCCAHGFDFDGAGEFECEDBHCECDGGGGGBGFGBHCGDGFFDCAGDBCEHEGBBBBHFHADFHCHCHCACHCBBEFAGBGBEBFFFHFBCEDFFEFHDHFHFCCECBHBDBDEDEHBHEHFBFEGAG,False +83,2.0,4.0,1.0,3.0,2.0,4.0,2.0,1.0,CBFHFBBDGDFDFEGEABA,True +84,18.0,13.0,21.0,13.0,16.0,19.0,15.0,8.0,CBCEEADAFGDCFHFHDHFACACEDGACFGGGCBABDCCCCCCBABABABDBDFACGCGCFCAGEFEFBDBCFEFEAGFDBEFEHEHBAEADAFAFGEGECAHFEDGDHHCAEDEFCFGGGBF,False +85,14.0,12.0,10.0,10.0,16.0,19.0,9.0,12.0,FGBGHDEEEGBFAEAEDHGHGFEDEFEGEDEFEFCBAHCHCFBFDGECFFFGAECBBBDGFAFACACBEDABEBFHFHFHAHAHFEDCDCFCAAHBHADAFB,False +86,14.0,13.0,10.0,16.0,18.0,7.0,14.0,15.0,GGGGHADGCGCEEEDEDBAAGBCDAEABAGAFFFDBEFEAHAHBDBDBDBGHAACDHHGHGHDHEFBCDCHCHDEEBEBDADABEFECCGHGHFHDGEEEADBEEHC,False +87,9.0,13.0,17.0,12.0,12.0,23.0,13.0,12.0,EHCHBDDCECFCFCFABABGBFDFDCDHBGDHDGBGCGCGCFCDHEHEFCHGEAFBFBFDFHCEBAFEDEDFFGHCFGBGFGCDCEBGFHFAFBEEEBGFFCFAACAHAHF,False +88,6.0,3.0,0.0,1.0,3.0,3.0,5.0,4.0,GBGAGBHAGAGFEBEFEHHAHAFAD,True +89,11.0,11.0,12.0,15.0,16.0,12.0,7.0,10.0,BHBHDDADCGCAEHHDCEAFAFBFCDEDECBGFCECHAHGCAEDDBDEAFAFHFDCHEBEGEGADBDBHEHDFGFGFDECECECAAEBEBDBFF,False +90,18.0,21.0,18.0,8.0,15.0,18.0,18.0,10.0,BCBDGCBCHGHAAFAFEFAFDFHGGGCCECEHBHFCADAFAFEGBAAAGAFBEBEBEGCBHBFADAECDGHGBGECCBCBABHFFDCEFEHGBGBGBEFGABCBFBDBEEAHACGCGEGFCFCFDA,False +91,21.0,22.0,23.0,29.0,25.0,21.0,20.0,16.0,EDECECBBDBGGGDHDFCFDFAFGBACHDHDADFDHBEAACACACEDECEDGDGEGEGEDEAFCFEGGBEBGFGEDECGFAFAFGHEDFHFCFBFBDEDFDGBHEADHDCCFBABABACGEHAHFHCEGEGHBHDACADFCCHBHDCDCFBHAGDBABEBFBGCDBEBCDDADAEEC,False +92,22.0,26.0,23.0,24.0,20.0,30.0,22.0,18.0,ADAFEGHDHFFFFDFECADDDFHBHDCBFAHCHCACHEGFBFBCDHEFEGABAFAEBGBFFFBFCFGBHBEBAACAHAEDEDEGCDCDCDCGHACFCFHFHGCFCEHEHCGCDCEFGDGBGBGEGBABGBGCCABBBDBAFGDABFBFEFEDADBFEFDBHGHDFEFECBAGGCGADDDGBHAEA,False +93,2.0,2.0,1.0,3.0,0.0,2.0,1.0,2.0,DBDCDGFFAHAHB,True +94,18.0,8.0,12.0,13.0,10.0,9.0,12.0,11.0,HHFAEHCHCHCDDAFACACACGGFEFGCHDEEGCGCGFDDADGDFDEBHCDABGBABDGAGEEBAFABGBDAHAFAFADADEHHCHCBGEAEA,False +95,4.0,5.0,6.0,3.0,5.0,4.0,4.0,3.0,AHBFEADADAGFHFGGCBCBCBCFCEHEBDCEEG,False +96,6.0,10.0,15.0,4.0,14.0,9.0,14.0,11.0,ECECEGHGHEHGDACGHHHFGFGCCCGFEEHEAAACCHCFCFEGEDHFHFDFGEABBBBEBHGCGBEBGCACBEBEGCCDBFG,False +97,3.0,4.0,3.0,4.0,3.0,2.0,2.0,6.0,BGHFHDHDCDBDECAHAHAEGBFBHCE,False +98,14.0,9.0,9.0,12.0,16.0,15.0,11.0,5.0,BGGACFEGEGEAFGFGFGFAADADACBCFDADGEBHBFDFGBBDCGAFAEEFECHCDCBFEAEAEADADCEBDDHDBGEFCHEHEFEAEFF,False +99,24.0,22.0,16.0,19.0,18.0,22.0,22.0,17.0,BABDFDEDEDEHAACABAEAFFGBHFGAHDBCAGADEDCHBBGEGAGAGAGAGFGABEDEDEFCBABDBECECEAGFGEGBGACBFEHEHAHAFBFBCHEFGDADAEEBCBHHHFHFBAGGGFFFFGHDCCHAHBCBCHFGDBCCAFBDGGFDHDFDFDC,False +100,10.0,7.0,6.0,7.0,6.0,11.0,8.0,15.0,GGHGHGFEFDCHAHFHEHEBACCBCHFHFBCBEBFFEFHAHGHDAGADAEGBGHHBAAADCFHFDADFDH,False +101,21.0,23.0,9.0,23.0,25.0,21.0,22.0,21.0,EEEEEACAHEHDDADHFBFBAHGHGBGDGFECGBBBBFBFEFHFGFGFAEHDHAHAHBHGHFBBHGGGGGEHDDDDHEAFBHHDEFEHEDDGBCDCHBGDDFFCAHADEDEGEGEAABBEBDFGEBABCDFEACFDADAGAGEGBAFABHBDGDCEEEAFAFBFC,False +102,1.0,8.0,5.0,3.0,5.0,5.0,6.0,8.0,HCGCHDEBGFEFECBBBFBFGHGHGDGBAHCFCHHHEDEBB,False +103,29.0,22.0,27.0,17.0,23.0,16.0,31.0,26.0,GGHCFGEBEDGCCDEBFFFEFHGCDCBCBCECFCHCHCHGHCEGAGCECABHEEEBEBEGAGBBBABABFBHBHDHGGDADCCFAFEDECEABGBFAFHDAGHGHADEFGBDCHHDEDCHGABABFGDEAAAEBGAAEGGGGFGHAHDBDCCHGHBDGEGHGEAEACCHCACAHGHGHAHDCACAFAGAFA,False +104,7.0,6.0,18.0,7.0,11.0,12.0,24.0,18.0,GDGEHCGGGEFECEBECGCGHGCFHFHFHCDFDFGACHHHGBGHACDCGAGADBCAHECACGHGHBBCFGHEDEFEHGHBHGGCGCGCHCEGGDGEAFFHFCF,True +105,16.0,23.0,21.0,18.0,22.0,17.0,10.0,18.0,ACEGEHEHAFACDCDCHFBFBGBHDFFFCAGHBBBHBHFABABABAHEGCAEEEFGBGBADGEBCDEHEBCFCHBHEFEBDDDDDDDGFEDEFEHAHBCACACBDBDHDCBCEDEHEGCCFEEEDHHAABCFCHAECBCBFFCFG,False +106,9.0,10.0,12.0,6.0,8.0,7.0,13.0,7.0,FABABHCEGEGBGBGCCCHCAAABGEGDGFGFAFCBCGCEHDCCAGHDHCAEHFBFAGBGBGHFDCDBEEDE,False +107,17.0,15.0,17.0,17.0,16.0,26.0,15.0,17.0,EFBHGEAFDGCGFGFGDEEAEGBDEFBGGFAHHCAFAFHBHBDGDGEGEGDFFFDFHHHAHBCDADBCBFGFCBCBGBFEHADAHCECFCECHBFFFFCDEDEDCDEFEFCHHHCACAEBCGAAAAHADAFHFBDBCFDF,False +108,20.0,24.0,27.0,23.0,19.0,28.0,19.0,18.0,AFAEGFGFGAHFCFEHEGDBBBEBEBEBCDDDHDFGFDCDCECFAFAHAGBBBEBFDEBCBAHGFGAGABDBEAGFCCCBEBHCDBDFDFBBHCHGGCDCDFHEHECGCFFFADAHHHDCDAEEBFGAEHCDDGACACACFCBEFFHAGCCCCEFEFCABDBFFFGHCHDHDFDGBGA,False +109,9.0,16.0,17.0,17.0,16.0,16.0,12.0,24.0,EGDDDAHBEAEABDCEBFFHFHFHCDGHAHCCFDFDFDFBBEBFBFEHGHGDCFCGHGHGCBCEDHBCDHFHFBFGDGACCCGAEBHBABCHHEHBDDEHEDEDEGEAHDHCECFCFCBHAHEGBHH,False +110,5.0,7.0,7.0,3.0,11.0,14.0,10.0,14.0,AHEHDHGFEFGCHFGFBBCAEFEFEFECEHFHBHAHFCBGFABHBEDEGCGFDFACGCGBFEFGHHHHEHG,True +111,20.0,16.0,22.0,22.0,11.0,17.0,13.0,10.0,ACAFFCDCDCACBFAFGDAACDCDEDEFFCBHDGDCDGDEABFEAADDCAHHDHEGACEFBCBCACACABBHDHDHEHCAAFAFCDDEDFDFBFCFBFDEDFFGGAGCCBEBCBHBAGGGGGEGACBHBDB,False +112,26.0,22.0,28.0,29.0,20.0,26.0,21.0,19.0,GCDCBAEHEHGGFABGFFFFBDBDBHCHCHAAADGFCBCDCFFFDCHCECEDEAFBFEFEGGCDCDAEAECFCEEACCBABGFDABADAFHBHFEFEAHAEADFCFHHBHAHAGGDHCCCDHBCADABHBDCGHGAGAGDDDFCAGBCBDBCFCFEHEDEBGGFGFDBCGAGDCDEDGDBDBEFEHAFADD,False +113,4.0,0.0,3.0,3.0,1.0,0.0,3.0,3.0,HAHADDGDHAGAECCCG,True +114,15.0,25.0,14.0,19.0,17.0,16.0,17.0,18.0,GDGCHHEBEBHBEFAFEFBFHFBGHEFEFEBAAAGFGDDFDFDFDBDBDBABABDHCBGDHCEBBGBCBEBAGHCHBEBGHEHEHEACACACACBBGGFGHCHDGBCDGEFDFDBEHECDGBCEHAHDHACFGADFDBAGD,False +115,4.0,7.0,3.0,5.0,3.0,0.0,6.0,6.0,HGHBHBDBABACEGDGEAHBHADGEGCHCBDGDB,True +116,18.0,19.0,11.0,27.0,26.0,22.0,18.0,28.0,FDFEHEBGBGBCFDFDFBEGFABHCHEEFAFAFAFBDHEHEABBDCHCDDGEHEADAFAFBHHCHBFBEDHGHGBFDFGECHHABDEGECEDADEHEDCAHAGEBABCDCDAHEDEDEDFFFFFBFHGAFEGEGDHDHGHGHGEDHDGEGDAHABBHHDHBCDADHEGE,False +117,9.0,10.0,11.0,5.0,12.0,11.0,5.0,12.0,HFBFCFBAAEABGHCHAFABBBBCCCHCECECHCGEHEHEHFHAHCEDDFDCEEBFFFFGEBEAFAHDGBGDEHA,False +118,1.0,8.0,6.0,3.0,6.0,11.0,9.0,8.0,BEBFGFGFBFBGBCDFEHBHAGEFHGDEFBFHHCGCDBGFGFGHCHFHCECE,True +119,16.0,21.0,23.0,14.0,8.0,20.0,24.0,21.0,EEGFBBADAFCBHFACCCFCFEFDGAFHFDABHBCGHHHBHGHCHEGCAABBGDHBHBGFGCGCGCGHFEFCFGABAGGCGAGACFCBCBHBFCFADHDHGHGFDEBEGCGCDBHBEAACHDDFDCDCFBFBGGGGCBHDHDHFABA,False +120,23.0,16.0,16.0,25.0,12.0,20.0,24.0,21.0,DFHFBBDGFFEDCHEEGGGEEADAGAGDBDAABFDFCGDGAABABABABACAGGHDHFACECBDDFDHGHGHBCBCAGFGBGCFFFDFDCGHGDEEHBCDCBHBCFGFDFDHAGCHHHHHGAFADDHEHEAGAGAGHCBAEAEDCDADCFGFDHDHF,False +121,19.0,17.0,15.0,20.0,28.0,24.0,23.0,17.0,DCDFFGAAFFFBGAGDGCACHEHDADADFEHEGGFFEFAABBHGGGFHEHACACBEEEHBAGAGFDFEBEGEBECECDCHBHGDGBEFEAEAEAECCGCEHBHCFFGBDBDCDAEEEAEFFFBHAHGEDEBGFGFGHGBGBDFDCDHEHDDDEBAFDFEGCFH,False +122,24.0,21.0,31.0,19.0,20.0,33.0,21.0,17.0,CBDGEGCBFGFHFHFEFBDAECCCBCBGHDCCCAFADHDHDEDACBDBGAHABFDGEGCHEECECDAFBGBGBFFFFHEAECHFHFHGEEBCFCFDGEGFFFFGCDCGBGBGFFBFBFAAAAAFGBAFABECAGEGBGFHFCADDCECHFAFADAHFHEDEHCFBACAEAEFDCCCCCBCHDADCG,False +123,23.0,22.0,33.0,26.0,18.0,14.0,26.0,19.0,DGDGCACABHFCADADGHGEEHGACAHAGACEDEDEDGDFCHDECFCBCGHGECHCHBEEDEDEDEDCBGBGBABCBCBHAGDGECAGDCCCFCDCFHFDABECGBGFHBBFBEBEBACEDBHHCCGCDAGGGFCCCGDDFCBCBGBGHGHGCBADHFFAHDGAAAAABAFDHDHCFCEAD,False +124,14.0,14.0,13.0,14.0,9.0,17.0,19.0,18.0,DCBFBFAFAHBHGFBABECACGGBGCGCFAFHHDGDGEBDADFFHHHHDAABHFFEGAGFDBGHGAGBGHFHFGCHCDGEGEFCGDGDCDCDCECBFAFCFHAHEBEGHBEBHHADAD,False +125,22.0,17.0,18.0,14.0,19.0,23.0,19.0,20.0,AFFEGCACEHAHBHFHECADBDEDHDHDACHCBCBHFDDAGHGHCECEAEAHBHGGCEAFAFBDGFFFFBAGAFAFHHCGDFFAEBBABADADBCGHHHGACACFCFDFBCGHGEGEGBGBCBEEAFHEBBGGECEFECEHGGEAFDFDFAF,False +126,2.0,2.0,5.0,1.0,2.0,0.0,0.0,0.0,CBABCCCECEAD,True +127,9.0,13.0,13.0,20.0,8.0,15.0,15.0,18.0,GGEFDFEHDHDHBAGABBBFFHFCFHGHGHGHGDADHDEDFCEDAGAGCBDFDHDHCBCDFDBHFHGHFBCGDDDDDABGHDHCHAAECFBDBEBCBCEGECCFFHCGAGF,False +128,26.0,16.0,20.0,13.0,15.0,14.0,8.0,14.0,AFAFGCBFDCCGCBCACACAFACECBAFAFDBBABABHECBGAHADEDCBADABABAHEHCHCHGECDHDHBHBAEDEAEAHBGFAHBBCACACAFEDCAHHEADGEGECEFFFCGHDFDEAEFFD,False +129,3.0,2.0,3.0,1.0,2.0,1.0,0.0,1.0,AHABFBEAECCDC,True +130,3.0,10.0,5.0,11.0,10.0,4.0,3.0,9.0,DBGBHBAEDEBCCEBAAFHHDHDCBEDHBHBHBDECECEDDDFDGDFBEGEHEHF,True +131,18.0,19.0,23.0,22.0,20.0,20.0,15.0,23.0,FGBCAABCBCDCDCBBAAADCEGHAFDFEBHBHAHGDAEAEAHGECHCDDFDBEBHHHDBCFCABFHHHABFHHEGEHBAFAFCDCHGEGEFBFEFEDEHCHCHDHDGFAFEBEBGBGFCDCAEDEGFFFHFBEAGACFDDDDHDCCCCDCDGEGBGCEH,False +132,27.0,13.0,16.0,13.0,20.0,12.0,27.0,15.0,HAACDHGHEBFFCDAGADAEABAGHFHDHCCAEHFHBGBECGGGGAGABACDEDCACACFGFGFHBBEBHGGGDABGGGEDECEAEAEAFCEGBBBAGAEAEABHEAEGGGCEHFHDGAGEDEDFDHDEAAGAHAFFGCCCCG,False +133,5.0,7.0,9.0,1.0,6.0,7.0,8.0,7.0,BGCFEBHHHHACABFBFHFCFGGGCCECGCGCHAEBBHFGCGDAEAEBEF,False +134,14.0,15.0,11.0,16.0,21.0,17.0,16.0,20.0,HBHDHFHDDEFEGEFEBGDFDFBBHBAGEGCFHBHDADHHFAFAHECEFADECEDDDBDBDACBEAFHFHGEGCGDECECBAGACHBHGHFHFHGEGFFHEHCHCEGEGEAEGDGEABDBABFFGECABA,False +135,8.0,3.0,1.0,2.0,4.0,6.0,9.0,3.0,GFGEGHGFEFGCGDBAHAFDEAEGBGBAAAFAGAHF,True +136,14.0,29.0,20.0,23.0,25.0,22.0,18.0,18.0,DGDCEBGFHDBFBECHFEFBDEDCACGCGHEFEFEFAFGGGDCFGFHFHAHADEBBCBCEEEFEBABCBEBACACBHHCFCEAEAGBGDCDBDEDGBACECBHEHBDGDFDGCGAFEFDBHBEBEAHGFCFBFBHEDFDGDBBBBACDBDHGBEAEGFCHBHEHDHDFD,False +137,3.0,5.0,1.0,6.0,8.0,6.0,3.0,5.0,FDFDBBBEDEHEHEFEACFFGDHDFGBHAEAEBEGDH,True +138,17.0,19.0,28.0,23.0,19.0,29.0,14.0,27.0,EEHFCDHDHBAADFECECFFFCDGBAHAHFHBCDDFDGDADBCAAHABAEGFHFHDHDEGCGHGHCFDFEFGBHAHBCBABEEECDCDEHFHFBABHCCCACHEACHDGDFHFHBHFGDGDGDFBCDCGABFFDFECHCFFFHFCDGEFCACHCHCHEGACFCFBFEEECEBBBBD,False +139,18.0,10.0,15.0,7.0,19.0,9.0,15.0,15.0,BCDGAGEBBAAFCBEFDFHCAAHABFEADAHGCCCACEDEDEDEDEHCBCFEHCHEACACHGGGGBGEGFGFEHECGFEAHGHEHEHEHACAFBGGABABHGHEAEAC,False +140,12.0,11.0,10.0,15.0,15.0,9.0,10.0,21.0,GGDEDEDHDABGBDCAFADADEEFHFEEBBAHECFCAHGHGHEBBCBABAFHHHHAFADHECEGGBGECECHBHECFCDDDEEHHHHHDHDHDHFACGDABFG,False +141,6.0,7.0,16.0,10.0,19.0,4.0,7.0,3.0,GAGEECEDBGBGFCFCHCFBDBDECEAEDBDCHBEEFAHAEAEGCBCEADDDDEGCCEEEECCCECDCGCEE,True +142,17.0,14.0,17.0,18.0,21.0,18.0,15.0,9.0,BADAGADHDGDGFHFAFDFGEEDDDADCCCGGECCCGEHAHAHEEEEAECFCDHDFABABFBGBCACEFFDADAEEHBHFDFCBEBGHGCFCDAGFDBEFFGFGEGCBAEDEBCBAACDCBEBEFEFEG,False +143,1.0,3.0,4.0,4.0,2.0,3.0,3.0,3.0,DHDCCGCGAGHBBFEFCFDHDEB,False +144,3.0,1.0,7.0,1.0,1.0,3.0,7.0,2.0,CDCFHGGFBCCCCGAGAGAEHFGCG,True +145,3.0,5.0,7.0,4.0,3.0,11.0,6.0,3.0,DHGEGBGBGCCFDFAFHCBEBEBDFCFCFGFCCAHFFFDGAF,True +146,4.0,13.0,6.0,8.0,6.0,15.0,9.0,3.0,FABGBGFGFDBBBCGEEEEBFGCBFBDBCFDFGFGFAFECCDDADAFBDGHGBFBFHFEFHCBD,True +147,16.0,16.0,22.0,23.0,21.0,20.0,35.0,29.0,FBFEECGAGFGFGHDHDFAGEGEHFHFHFEGHGCEEAHDGDEHEGEFHFCFHGHBECDBDBHHGGGGGGCBHAHACAHAGEBDCEAGGHGHGEGEBDAHHHCHADGCFBFHGBGCHDFDFDGHCBCHHAGBEBDACHCFFGGGDADEEAGCEDEDCCCGDFDBDGFBFBGBDEACACDCDCH,False +148,16.0,20.0,20.0,23.0,21.0,16.0,31.0,18.0,EBEHGGGHCACFDDDDDAFCHEGCACFCFDFAGADEGGGAGEECEGEGEGAFFDCBHBHDHEGCDCGBGBGCCCCCBDGEBCGFHCHGHAHBBCEGEGEBFBGAHABDBDAGAGFGBEEEFEDGDAFCHBABGBADADEGFFDHDCFGGDHBFBDEDEDGHHHBH,False +149,3.0,7.0,4.0,6.0,10.0,7.0,3.0,5.0,EBEHEBEDCFCBBADCHFHFGBGBDEEEECHBDADADEFFFGFHE,False +150,6.0,2.0,7.0,6.0,2.0,3.0,8.0,0.0,DDDCGCADFDFGGGACACAGBECGGDGABACFCE,True +151,5.0,2.0,2.0,0.0,5.0,4.0,2.0,3.0,GAGAFBFEFECEFHABAEHEACH,True +152,14.0,12.0,9.0,7.0,12.0,11.0,10.0,17.0,FDHDFEHDHCFCBCDGHGCFFFBFHACCHBGAGAHEHEBEAADAHBGBFBFBABABAHAHEEAFHEHBHEHABGGECDCECEAGDHAHEFGG,False +153,19.0,24.0,27.0,19.0,23.0,23.0,26.0,24.0,CDCGGGFAAGACHFHDHDHBBCCHCGFAHABGBEDHBGBGBABADECFFFFAGGCHDDGDGCGHGHGDCFHDHAFEFEFEHDCCGGBGEGAAFCEEDFDFGBEAFHFCGEBCBHBFBDCDGBCBEHADABCHCHEHEHBHDGFGAGEGBBEBHDEEHAHAEAECCFFFCCCECECEFBFBDECBA,False +154,13.0,10.0,11.0,9.0,11.0,8.0,12.0,4.0,GEAEAFAGADADAEFCGCGCGCAFBFBEECEGADADACBGBCHHBFEECACBEHEFBFBDADEDBCGGGBDFHCAGGD,False +155,23.0,15.0,20.0,21.0,22.0,13.0,16.0,23.0,FEBEBEBFDHDHCCDDBCBEGFDFGBHCHFDAEBCBFHAHGHDADCBGDHDHDFCAHHHDBCEHDFDAAECDCDCBCAFEEEEEAEAGACHCEGEAEGGGGAEABAFAFHHGEAAACHFHAHFGEAEDEDEDADHDBCGAGACBCHHBGGCHC,False +156,1.0,2.0,8.0,2.0,1.0,1.0,0.0,3.0,CCCCCHCHBACDCBHEDF,True +157,11.0,6.0,5.0,14.0,10.0,10.0,2.0,6.0,EFAHAHFBFGGABADFCBEDEDADAHAFAHBFEDEDCDEDEDEDFFCBEDFDFBACDDAEHCHA,True +158,15.0,22.0,16.0,16.0,9.0,21.0,17.0,9.0,CFCFCAEBDGDHBBFBHCAAGFFFAGGGGFGHCHDBDBECECECFHBBCBAFHFDFBCACHCAAAEFDBDBCFGAADADAGGBBBGCGBGCFBEEGHGFGFDFDFABABDFHFDBDCEFEBGDDB,False +159,3.0,6.0,10.0,6.0,2.0,3.0,4.0,5.0,GGGFDFDBCBHBHBCCHCBCEHHFCACDCBEDDDACGCA,True +160,7.0,12.0,7.0,6.0,6.0,8.0,8.0,5.0,AEFEFEBCBADCEFHHCHGBBECAABFBFBDBGBHECGDADADGBGAHFFCFCGDGBGB,False +161,25.0,18.0,13.0,27.0,15.0,21.0,17.0,28.0,HFHGDDBDFDGHGADHGFBHGCFDAECCHHEFEFEDDBEBAHAHFHFBFHAHDFDFAEDFBBCEHADGFGAHDGDGDGDFCBCEAEBCBHDHDHAHAEADHHFHFHEGBHEDABABACDCAEFDDGFGAGABAHDHDGDGDBHBFAABAGAECECHCACBFAFH,False +162,18.0,23.0,16.0,12.0,17.0,23.0,24.0,31.0,AEABABCBCHCHCFFFBHHEGBABDDDDDHHFHEECFCFCBEDDBHBHBCGHDFAFHCHFGCHHHHHHHCFGFGEHDBAAEGGHEBBHGDAHFHBHBECGFAFBGCAHEHGBBFBDCHHGEAEHGFFFADGEGBGBGCGFFCHGEGEGAGAFABABAEAEGFGF,False +163,24.0,23.0,17.0,16.0,25.0,31.0,34.0,30.0,FHFHFEFGFBAEHHHDHDHFGGDGDGFGDHACAFGDGDECECHCGAHAHBBBBBFFFCGBGEFFHFEAECGGBBAGABABAFHFHECGDECFCHDBACDEHBFBHBFEFDDGCHBHGHGHBEAGFGCEHFBAHACEHEACFCFEAEGEGAGACFEAEBGGFDBDBGEGECEAHHHAGBGHAFDFAFDFGBGHGFGAGHEE,False +164,16.0,17.0,19.0,27.0,19.0,29.0,35.0,19.0,GDGBCCGCAFBFGFDHGHBFAFGFGDDECECDGDCDFHFGFCFHFEABACFHFBFHEEECEDFDEDGGGDGCCBBDBFBABFBGDEDEGBHBDDDGGGGCFHFGFGFHFEABBDCDCHCGGGDGFGEDADHDECEAGAFAHEHADAFFGGGCABEGHCAEFGFGAGDDHDHBCEHGAEHFH,False +165,10.0,7.0,7.0,12.0,6.0,6.0,5.0,8.0,DGFFDCDCDAEGDBDCEBGACECHCECDBABDEAHDHGAAHHHFHFBFBGBHDADADAFAE,False +166,17.0,18.0,17.0,16.0,20.0,19.0,17.0,15.0,CACAHAFBDAAADADHBGFAFDGDGDGHHFHFGFGFHHCAAEBFBFCFAHEBABEEGEGEGEBAHGDCDGEBCHEGDGCFCEEFECBCFHBHBHBADDFBFBGDCBCFFEGCAEGEFBACDCECECFDDADEEEGHBHB,False +167,15.0,4.0,11.0,15.0,21.0,12.0,17.0,17.0,HHAHDEDGHFHEHCHGFGFCECEGEACFGDGDCDCHADCEHEGGAEEBEBFHHHCHCHCFDAHAGDGFGDDHEEGCAEDEABAEGEGHGDDFAAEFGAGAEAFAFDFEEBED,False +168,8.0,4.0,9.0,2.0,9.0,7.0,3.0,7.0,ECECBCHFHCGFGFEEEHEHECAAHAFFBAEAFHBGAEAHDBDACCCFC,True +169,16.0,14.0,9.0,11.0,11.0,11.0,12.0,11.0,DFDFDGAGAGAGFGHHACBHBHGFFDFGBCEAHBDAEADACCECAAEABBHEAEAEDEDCABABCBGGGGFFACHHBDBFFDFEEGBCDHEHBHB,False +170,4.0,2.0,1.0,1.0,6.0,4.0,5.0,2.0,GGDBEEEEBEAGFFCFGFHAHAEAG,True +171,28.0,14.0,20.0,10.0,8.0,25.0,20.0,36.0,HCHCDCGCDAGAGHGBABAFAFCFAFDFGFGEGHFEFHBHGFGCHEHABFGFHHHCFDACHEFBHHHCHAHGBAADCHBHBFAAAHHHFEGCGDAHAGFBFAADAEACFFGAEAGABFCHCBFDEAGAHBHBAAHHHFHFHCCACGHGHDHDHCHCFCBGF,True +172,3.0,11.0,4.0,4.0,5.0,7.0,5.0,5.0,BBBEBHHCCFEFGFGHGBBBGBDFAFACEHFGFHDBDBABCDEE,False +173,8.0,13.0,6.0,15.0,4.0,10.0,15.0,7.0,ACDCGBGFFFGEGBGFHBHDADHDFGBGBGHCDAGGGCHDHGADDDDDDEBBHBFBFGFAEADGCCBDBDGAAEFBFB,True +174,10.0,11.0,8.0,10.0,13.0,7.0,14.0,11.0,GCGCGCGFGEBCAAEEHEAEHDHDGAADADADFBEDECHCGGGHGEEHBHAHABFBEBHFADGDHEECHBBFBGEGBGDCFBFD,False +175,23.0,12.0,12.0,24.0,26.0,34.0,26.0,24.0,CDBFHAHBGAAFEGHAFGCAFGFGBGBEBEAFGDGDFDADCFGEGBFCHABFCGADHFFEFHFEFEFEDHFGCGEGEAABEGAGHGEAFAFAFCFAEDEDEDHDHDHFFFGFHACEFHHHDHDAGFDFGEGBGDHDBABAFEEEHEBGFGEEAEAHHFDDDGHGHDFCFCACHDDEDEFHC,False +176,18.0,8.0,20.0,16.0,15.0,17.0,11.0,11.0,FCFBECGAFAFABAEEEEDCDAECEDGAAADFHBDBECEHEABABCDCHBGEHAHAGAECHHHADCCCCFCDCDAGCFFEEAFAFGDDFHFHFHDBGGDGDADFGCECFCGCDCFF,False +177,13.0,12.0,13.0,12.0,6.0,11.0,5.0,9.0,DABFHGHCBDBDCFFGABAFEBACAHECGDFFHFHFDFEFCHCBCBAECGCGCHEAEADDDBDADAHHBACABACDCDBFB,False +178,7.0,14.0,10.0,12.0,19.0,22.0,10.0,9.0,FDECFBFDFDFHFGCEDEDEFHGBACCEGGAEBEGABFDFDFCHGHFFEDBFBFBFEGEHADAEFEFEFEABCFHDHDAECFCGBFBGBFBEECECDBEBHGH,False +179,2.0,2.0,2.0,1.0,5.0,4.0,1.0,6.0,HGFEHEHEFEDAFHFEABBCHCH,True +180,2.0,5.0,1.0,3.0,3.0,4.0,0.0,0.0,FAADBBBBEBEFEFDDCF,True +181,6.0,7.0,5.0,2.0,1.0,4.0,3.0,6.0,BHBDBAAGAHCHFHACAHEHBBBFCFCACGGDBF,True +182,2.0,3.0,10.0,6.0,8.0,6.0,4.0,4.0,BCBCECEAEDEDHCCCCHEHEGDGCFFFAHGBFFFECDDECGD,True +183,27.0,20.0,35.0,20.0,19.0,18.0,17.0,19.0,CHCHCFCBDEHBHEHCCCCBDBAADFFECCGCAEAFAHCFGDGAGACABFEAHCBDBDBDACGDEDEDEHEBGDGDCAGABEBEAECEGAGFGCABFGFCEAEAGACFCDCFFGFEHBDBDECACAFHBHCHBHBFAHDBCADHEHACAGDDDGCEBFBFCCCCGAHCFCACAHH,False +184,21.0,29.0,29.0,14.0,13.0,23.0,22.0,20.0,HBBEFAHAHDHCHCGCBCAFABDDHDFAAADBDBEBCBCBEACGCGFFBFAFHGHFCFEHCHDADFCFCEDBGBCCFCFGFHCHCACBEAFBECFCDAGGCGFGHGFGEGACCDCBHBACGFGFHFBFGEGBCHCBCDEBBCHGGBGBDDFAAAEBEBABHBABHGEGBHA,False +185,16.0,21.0,7.0,5.0,16.0,12.0,3.0,15.0,BBBHGHBACDBEAAAFDHEHAGAGAEEEHHCAEAFBBABFBCECAFAFBFHFEDABBBFBEBEBEBACHFHFHDHBFEAEBHAFCHEDECEHBHB,True +186,26.0,34.0,20.0,22.0,24.0,21.0,26.0,17.0,HFACACHCBBBBHBGBEHFHFEAHAEAEFDBHECAHAHDDBGEDCBEGGFGECAAADBEBGCGCFCFCFBFBFBAGCBBABEHGCGCGFGBBCHCEDAHBCEAEHDBAHGGDDDDHEADDDDDFFGBGAGBGBEBABDBDGDGBFBDBDBDHEFEFCFEAAFGEBCGEGBFFGCGAABAGCHEEEAFAEA,False +187,3.0,5.0,0.0,1.0,1.0,2.0,2.0,4.0,DEBGHGAFBFHHBHBABA,True +188,8.0,11.0,10.0,11.0,8.0,19.0,14.0,12.0,HGFBFHFBFGGAHDDEBAHFHFHFCEGFGFGFGBGEGBCEEAFDBBBHFHDBDBGACHCHFGCGFGCGFBCDCDFFAEAHAEFDFDHAECDCD,False +189,24.0,32.0,23.0,32.0,21.0,21.0,20.0,22.0,BBBABAEECDDDEDEHEBECEDEDHHHFHFDFHCDAHAHDBGBGEGFGFGFGFBAGCGDFBFHDHBBCHGHGFAEBEDCAAGFDDADADBDCFGHBABDHECBDBAAHADAGCDCBABABGBHDCGCBCGFEBDCHAHCCCFCFEBABHDDBGBHHCCCGBABDBCEEGHAFEFEDDBAFFFDFDCEAEAEGDBD,False +190,13.0,10.0,11.0,9.0,7.0,16.0,9.0,11.0,AGCHAGCBAHCBGBEBEACADADHDBFBDDAGEFCFCBHDEFEFHFHGHDFGFACAEFHAEAGGBGFCFCFHFDFCFCBBFDAHAH,False +191,14.0,3.0,6.0,9.0,14.0,7.0,4.0,6.0,EAEFDGEEFCCCFCFEAAAEADCDAEAEGGAFHHHHEAAADADEFEBDBAEGECEADFDHDHB,True +192,6.0,4.0,7.0,3.0,3.0,3.0,1.0,4.0,CFGEHCCFCBCEAEHCHDADADABBBACAFH,True +193,29.0,36.0,21.0,12.0,18.0,14.0,23.0,24.0,BBHFFFCEHEGEHDHBGBHBHDEBHBHBEAEBDBFHFHEHABADACGGGADBBHHFBBBAAAAABECDCACHCAGACFCFAEAFAFAGGDAEBDBHBEBGACBHFAFGFGBBCAGGBGHDCBBDGEHEGEACACACEBEBCACAEGDGHCBDGHGHBBABCCHCHCHGBAEAGBFBG,False +194,6.0,3.0,5.0,1.0,2.0,4.0,8.0,5.0,HBHGGFCFCACAEABGEACDCHBGGHGAGAFHFG,True +195,3.0,6.0,4.0,7.0,9.0,15.0,5.0,10.0,HAHEHFGFHHGHGFFCFCEDEFEDBGBDEDACBDFHEBFHFHFEFDFCFDFABEBGHFE,True +196,2.0,2.0,8.0,2.0,3.0,5.0,4.0,4.0,CCECHCDCDCEBHCGEHBHGAAFFFFGFGC,True +197,0.0,3.0,4.0,2.0,1.0,2.0,3.0,2.0,DBHBDFCCCGCGBGEFH,True +198,9.0,8.0,9.0,4.0,11.0,7.0,12.0,11.0,AAAFADHGGGFGCBCBCHEGEFEHDCABDHGEGEGDACBFHFBEBGBECEHAHAHGBECFCGEGAHEHCHF,False +199,9.0,8.0,10.0,11.0,7.0,10.0,5.0,6.0,ACADDFDHDABGCDEBEHAFFBECECDBBABAFAFAEAFHDDDHCCDCGCGHGDGHFCBCBFFEFE,False +200,15.0,9.0,5.0,13.0,12.0,23.0,15.0,22.0,CHGFEHBDGDHEHAHDFDFAEBDAHEFEFEGGGGAAAGEDAHGHGHECEGFGFGAGBFEFAFBFBGBDFAFHDHBHFHFHGDEDHFFCFEDBDHFFFAAHBHAHFCFDHHCHAA,False +201,8.0,4.0,6.0,6.0,2.0,3.0,2.0,2.0,AGCFBBCBCDAHABACEHDADADCDADAEFGFC,True +202,15.0,30.0,30.0,30.0,15.0,29.0,25.0,23.0,DFBBDGHBCEDBFBHBHBCBHEGGGEBEBHHEHCFFHFGBHEGBDFDFGBGDFDFHCEFHCGCFDHDFDEHADADEBCFEFDFEFECDAAHFGDDDCACACACACDBABGGEDAABBBGCACABFBGDCDAGGGGDCDFFFGFCBBBDBDHECGHGDGCGCHCHFBFHHHDHCEBFDFDFCFCGCBCBCFCDABHCG,False +203,14.0,19.0,19.0,3.0,12.0,14.0,16.0,22.0,CHAEADAHBHBHBHBGGDBHFHEAAABCBGEFCCHFEBHCHABABFHCCCHBHAGAFCFBFAAAHCFCGEGEHEHEHFHBHEGFGHBEGGGCCFGFGCDAECGCBBGBFBCHCHCGBFE,False +204,9.0,15.0,19.0,11.0,9.0,19.0,20.0,15.0,FAAACCHEGCGDGBHDCCCEBAHDGDFDBDBHCFGFCFCBCBFGFGHGBFBHHHFHEGBGBCAEBCCCFCFCHGAEFEAGCDHGHGFGFGCGBGBGFDACEBFDFDEHEDGHABFHF,False +205,20.0,16.0,16.0,34.0,30.0,20.0,29.0,29.0,CDCFGDGDEFHGHEHEGGBGBGBHBGEFECDCEBGDAHGCBDDGDHDHEBEDDDDHAFAFDEGCHEGFHFADBEEGAGDGDHFHBDEAEAHAHDDDECGBADEHEFEFDACAGEGFGBDEDECHHHEAEFFBADDDDAEAHHDHDCCFCAAAHCFCFEGHHHHGBGBDCHCHDFDGGEGBFBGHFAFEGEGEAE,False +206,20.0,18.0,16.0,14.0,21.0,4.0,6.0,11.0,ABABAFADEDBAECHGDDAAHEBBDBACECGAAAACHEFEBCDHGBCECECEBEFEAECBCEHEDGAHACADAHACECGDDEEECEHHHFECBCBEBHBDBDBDBAGDBA,True +207,1.0,3.0,2.0,6.0,1.0,4.0,1.0,1.0,FCADBDBGBFEFDFHCDDD,True +208,5.0,3.0,5.0,6.0,4.0,0.0,1.0,2.0,DCCBCDCDCAAAAHDHBGAEEDBDEE,True +209,9.0,6.0,7.0,6.0,5.0,8.0,3.0,2.0,FCFEAEGDADABCBCFGAGCFAFABABCBDHCFDFEFEACBDHEAD,False +210,21.0,21.0,15.0,16.0,11.0,15.0,20.0,12.0,CACFFACCCEHFDBGBGBFHFAGDGDADACGGDGBAACABBECECEGEDHDHCABDFDFDAGHGHGBGBFBGEGBFDFAGAEHFDAHEGABABFGAGEBCCGCHBDEDGBCACFBFAFHDBEBHBABADAH,False +211,10.0,24.0,13.0,13.0,14.0,11.0,16.0,23.0,EDEABACHGHAEGGBBBBECECEBBBAHGHGHCBCECDCBFBHBHFHFHFBBDAGFEBHAHDHGCFAGABCDDBEBEDHGHBCCACFDDBAHHHGBGBGEGEGHGFEFHHHDDBBCDEFGFHDH,False +212,19.0,7.0,17.0,13.0,17.0,11.0,21.0,24.0,FGCAHAHFGEHAAAAAHGDGHGFEEGDHHAEAEDCDFGBGDHDGFECECGGEEHGHGHCFBBHBFEEHGHGHDHFHDHDAAAHDECAAACBCECACAHFDFCCCCCCGGGGGEEEDHBHEFCGDHAHAB,False +213,10.0,20.0,7.0,7.0,13.0,11.0,10.0,5.0,HACBEBEBAGEEHEDAFABBFEEEBGBGBGBAAEBBDDFDFDFHCHDDAFECHBBAFAGGGFAFCGBEBEBEGGBFFCBCBCB,False +214,6.0,9.0,11.0,6.0,13.0,4.0,11.0,19.0,ECECBCFDGEGBHEDDHGEBHHGCGCBHHHHHEHEGACABADHFFGCGBGHDDCEEEEBEFHAECBCHGHGHBHAHAHC,True +215,3.0,0.0,0.0,3.0,3.0,2.0,6.0,5.0,HDFDHEHGGGGHAHAEGEAFDG,True +216,1.0,8.0,11.0,12.0,14.0,8.0,9.0,12.0,GEBDBDCCADDBGFGFEEGEGCDCEFEGEBEDCCFBHCEDDGEHEHDDFCHHHBHBHBCDFDEGEGCHCHEHFHF,False +217,10.0,10.0,22.0,13.0,14.0,8.0,15.0,10.0,DCHGECECEAGHEFGACFBGBECGCAEBEHHAGEGFDFDFHEDDCDBFBABACDDHDBDGCCCGHGACFCFDGCGCBCBGAGACECACBCECGDHEHEHECD,False +218,7.0,10.0,14.0,5.0,9.0,7.0,7.0,16.0,CFCECECDHHHHHHHHBBBHEFCCEBDBABAGDFDHCHGACCHCHEFEGHGDACFBGBCEEEFGHGFCBCHAAAB,False +219,15.0,20.0,16.0,12.0,13.0,12.0,14.0,14.0,AGAEAEAHGHFBFEHBHFGGEEHCFCDADACBDBFBCBFGFBBBCCAEGDGFAACAHBCBCDAFHFHECAFFEGEBCBGGCDCDCDEBBDBDBHHHHHDGAGDCHCAGEGABBEBE,False +220,0.0,1.0,1.0,0.0,3.0,3.0,1.0,3.0,HEHEHFFFGCBE,True +221,4.0,7.0,18.0,11.0,9.0,20.0,14.0,16.0,GGGBFCCCFBFDGCFCFDFHFHCDCDHHHGHFDCAGHCBAEEFEFEFHAEFCHCGEFCCCHCHEHCDCDAGBGBGCDDFDFGFHEHDHFGEGFHFGFBB,True +222,19.0,32.0,14.0,24.0,24.0,23.0,30.0,29.0,EAEAGFDFDCBHFAFADGBHBDAGCDEABDFGEEFFFEEAECHDHBHDGAHHGBGBGBGHCDFDBDBDEDADHFFAFEFGBHBGDCHEDABGBEBCDCHCBFAFBGBAHFHFGEDFHHHBBBBDBDBDBGEGBHEACCHEGEGEDEHECGHGFBHGHCBGAGHGHGEGEGEHAHAHFCCEFHFAGBGBGDADFBB,False +223,6.0,4.0,7.0,6.0,14.0,14.0,8.0,15.0,CEEFAGEBDFAHHDHFAFAHBFFHFCFEHHHHFDEGEGEDEDGAGHDFGBGBEFGFHHCHCHEHECFCACEEFE,True +224,11.0,10.0,13.0,13.0,21.0,14.0,25.0,19.0,CGBAEGEGEHHCGGHGCCBCAEBEGHCHDFDFDFEGBDFDFEFAGDGAGEGCGBHEEGCGBEEGEADACECABEDCDFFFDCAGAGHFHAHGEGEGEGBGBGHHHHHHDABCEDHHFFDHEHEGFF,False +225,6.0,19.0,5.0,11.0,12.0,6.0,9.0,5.0,GBHBDBABHBCBDEDBGBGBEBEBCCFDHDFEBBDDEAEAEAECFGFGEGABCFGBBDHDEFBGBGEEABHDD,True +226,11.0,18.0,23.0,14.0,12.0,26.0,20.0,26.0,EFEFEFGDCDFBHBHADECHHEHEFGFGHCBGACBGACFDFGFCFGFCCCHHHBHFHFHDADFFEBGFFFFFDBCCFCFHFCDGEHDFDBDCAGGHHHHHHBACGCGAGBGHAAAFFCHGBGCADGBBBCGDHEBEBEBEBHCHDHCCCG,False +227,23.0,20.0,28.0,18.0,25.0,23.0,23.0,21.0,FCCBCEFEDAGGBEHCHCHAFCCADFFHFEFAHCHDGCCHAEDEDFDGAGAGAGEFEBEBHHEFEFHFCGDFBGBDHAHBGAHFFFBFCDDADCDEEAGABHBHGHCHCABADABCHCHCDFGHGHBAFFEGECBGADCECGCGCBFEFDFCGCGDEECAGAEAGAGBBBBBCEEAEDECE,False +228,5.0,3.0,9.0,5.0,8.0,2.0,3.0,5.0,DDDACEHGFBCEAECCCCCFCEHEHEHEBCDAEBDHAGAG,True +229,15.0,19.0,18.0,23.0,23.0,15.0,10.0,23.0,HHFHGHEBFHHBCBDEEHCBGBAHAEDEDCGCGEBBDDDDEDBDHDFDEDACCEEDFCEEECBCBCBCDAFEHCFAHBEDACAGHHHHHHHAHGFACACAFBEBEFFFFFDEBEAEGCBEEDADACBHGCGBGDHDHDFDHDEABF,False +230,15.0,10.0,14.0,14.0,7.0,9.0,3.0,6.0,EDADBFADCDCDEBFBFAFEFEDCBADFBFBAHACCBCGEHEHBCCAGDCFFBAAABAGACHCHDDCCCEDHDADADA,True +231,21.0,19.0,19.0,16.0,21.0,13.0,13.0,23.0,EHBFBHBCDAEACABABEHCAAAAAEBDHDCECACAHGFCFBFBDCCBDBDECHCGCAAHHDDCDCDEEHHHADAFBFGFGDGFGHGAGEEFEHBBDBGHAHGHEBCCACACGEDEAABDBCEDEFEHBHEEEHGHFHEHFFGHB,False +232,10.0,11.0,13.0,7.0,8.0,12.0,12.0,9.0,EFGGGHCHBAEHFDFEADAHBBFBCGFGBCBCBCFHFAFAGCGCEBEDCCCHCHDGGGCGCADFEBEBDAFAFAHEFGBHDA,False +233,16.0,18.0,26.0,21.0,12.0,11.0,22.0,9.0,GBGCHBGDHEHDGAFCFCGCBBDDDHHGCEDEDCDBGBEBCCCCDBGBCACBGGEHEDGGAGACFCFCHCGGDGABDCCCGDBDEDEBBCHCDCDBDAGECECAFEFBFEAGAFAGBGAGDDDACAFAFAFCHBA,False +234,8.0,5.0,2.0,10.0,3.0,5.0,9.0,5.0,GAGBBEDFDFDBDGDAEADHGAGHBDGDFDFCGAGACABAGHHHFED,True +235,28.0,16.0,21.0,19.0,24.0,21.0,12.0,20.0,EDHFBEAFADABHFHFCFHFACCBBBHAHDHBADGDBCBDFEFDHHADACBHBEAEDDDGAGACAEHECFCECHHHEABFCFEEHGAFFFADADCDGEEEGEBECEBBCACAHAHADADFFAFAFHGDEEFEBCGCGCGCDCAHBGEEFGADECECAFAHA,False +236,13.0,6.0,14.0,8.0,9.0,13.0,7.0,14.0,FCFAFAFAHAHCDCDGFFEFECEDBCECDCFHEEFAFACHCHCEBGDHEHFHAHBHDHFCGGAGDHHACCBHDCGFGBAAEABA,False +237,4.0,7.0,4.0,12.0,6.0,4.0,7.0,10.0,DGGHBHDDDGDGCGCGADBHEDEDAGFCFEBDHDEBAHAFEHEHCHDBDBHFHB,False +238,25.0,27.0,17.0,20.0,11.0,20.0,27.0,24.0,BGGGHACECEFEAEDBDBHCGDGDHDHBHBHAHAHFBFGCGCAHFHABABEFFDDAAFHFHDAGADFDGBACCCHGHDAACHCHGBEBCCCBDAFAEGHAHGHGEDBDBCBHBGFEAGAGBGBABDHDGAGADFBFGFGCAEBGFFEHBBGDGBBBFFHFBFCDAGCGHDA,False +239,27.0,19.0,14.0,12.0,26.0,20.0,17.0,18.0,CACHFHBABHBABAHEGBDDEBFAFAEACABAFAHAHGHDFEGEFEBEBEAFCDCHABAGEGEDFBGBACAFDCDCAEHEHFHFEEEFABABCGEEEGHDHAHBHDFGEGBAAAFDHECEAGCGEBEDCDHFAFAGAGBGFFCGCEHGFEBEF,False +240,13.0,5.0,13.0,8.0,10.0,9.0,13.0,11.0,HCHAGAEFGBGAGFGCDCAGAECGCGEFEDHGFADADACHDFDGBCBCFEDEFEFBAHHHHHHAAFGCECACBCGEHEADCG,False +241,15.0,13.0,22.0,21.0,14.0,24.0,13.0,15.0,CECEBACABEFHFGBEFDCDBABGDAEADCDHGFGFDDDFDFDFGFEFGCGEAHGHGHCFCDABFEHHABCECBCHFHCACFBFBHBADFEFEFDFDHDHCHCDEDAGGECHAFDHCABFCFDFDGBGCFCACDCEA,False +242,10.0,3.0,9.0,4.0,10.0,22.0,6.0,6.0,CBAAFFFFGBDAFFFFFFFDGAGEHFGECEFEFHCHCEEEDCFAFAHAFBDEHGHCFEFCFCFEAAFAGC,True +243,16.0,18.0,13.0,25.0,8.0,14.0,16.0,17.0,CFHGHAFGFCFEDAGEBBFDGBGHDHAHBGBGBDCHHEBDBDBDCDHDHFAGGHGHABADDCDFBHAGDDDBCACECAGEGDDHDFDFHFHCGCGCDBAFAFDBDEFEACADADADBCFAHBHGEBB,False +244,14.0,10.0,26.0,18.0,17.0,28.0,19.0,21.0,HEHEHDFDFEGEGFGDCBBDAFHFHFDCEGBBDHFAGBHFHCECHCGAFCCDDADGHGCGAGBDCDHDHDACFCFGACEHEGDGFCFCFCAEFHHHFBFDFDCBCFEFCDGAGDEEFEFHFHFEECCCAAABECFHACECFAFGFCBCGHGHG,False +245,30.0,27.0,23.0,25.0,28.0,19.0,14.0,26.0,AAACACBCAEDEBEFCCHCAEGEDEFGAGCEAEADFEBBBEFAGBBBFDAEAEHHHHCFCHCHADFDEBHFACBFBGBFBCHHAHAEEGHHEAEGHGHGHGCAHADADAEAEAGDGBECHDDDDEFFDCDCACAFBFHCHEHEADFBFBGBDBCGABHBHDACCECDDBDBDFDBEEEEHCBAFHHDBBADF,False +246,9.0,17.0,16.0,9.0,17.0,6.0,11.0,16.0,HGEGACAHDHDCDEGFHBHDHECEDEDFDEEHCFCFHBEGGFABEHHHHGAABCCDBEBECHCHFBAHGCGABCBEBECCCCCEGEBBBBDBABEBHGEGA,False +247,10.0,6.0,15.0,20.0,23.0,16.0,16.0,6.0,AFDGEGEFEDCDFHEGEGFGBCACECEAEHEDDHEGEDEFGDDDCCCCGAGEDBABEFEFDGDHDGDCBHBGFFCFCEEEEFCHEFGDGFCDADCFCAEGFGBEFDADADAE,True +248,1.0,1.0,5.0,2.0,5.0,7.0,7.0,2.0,EFCFDAGFCFGFCHEHECEGGCGDGFGFBE,True +249,20.0,25.0,23.0,25.0,18.0,22.0,28.0,20.0,DGDBDAABACHGHEBDCCABFBAHGGBGEAAGDDFGFAHADADEDFHFHGGGFGFDHDEDBACDGDGBFACABBGBGEGEGECFFFEABDEDHFAFGBCBCACHHFHFBFBFHCHCHCECDGDCEHEGCGBBFBGEFEFHCGCBHGDGFHFEABCCEBDBHGDGDGBHCEDADCDCBAEAC,False +250,27.0,24.0,20.0,16.0,26.0,17.0,25.0,11.0,CHCBCACHBABAGHFEEBEGECEBEBEACDGDHHGAAFGEGABEGAGEGADADABAECFGBGAGAEBEADFGFECACGGFGEGDGFBFGCGBFBFEAEBEFAFAFEDEAAAAGBBBCDCDGECCCBCFADABHDEDEGEAHHBDEDFDFGCCCDBBHAHGBCBEHF,False +251,23.0,19.0,20.0,25.0,22.0,22.0,28.0,26.0,ACACGEBFHHCAGAGHGHGCGCGBEHFHFCAGFGCGHEHAHADDDDAEEEECCFBGHAHAHGBDECFADGCECEGEGDGAADBEAEFHFDGDGAEAFDECBGECCHDEEBGBABEHHAFFFFEFDADHBHBDDGGCGCBAGAHABDBDEFEBCBDHGHGFDFDFDFHBAFCBDBDFFGGCHHHDH,False +252,22.0,23.0,23.0,11.0,21.0,24.0,27.0,23.0,CGGAGEGECECECDBFFFHAHGEGCGAGACEDBBBFGFGHGHFCBGHFHBHGEAHAHABDHABABDBECHAHFCFEFAAGGGBGFCDCBEADADHFHDHCEABCGGGFGAHEEAECCCCGBBEHEHBHBHDCDFFAFBFCEBAGAGCCBCAGFDHHEHFFFCFEFBBEBFGEGA,False +253,21.0,15.0,11.0,10.0,10.0,18.0,15.0,19.0,CFCEEFHBGDEEFEFDAGAHAHGHFHFHGHAHAHGFFFGBDBGAAAABABGBFBFBEACGCEDHFACCFFFGECBAECDGGAFAHDHDHBCCGHAHAFAEDHDHGBBABDFCAGABHBH,False +254,16.0,7.0,14.0,11.0,13.0,17.0,11.0,13.0,CDFHFHECACEDEAECCHFHFHGHGCAHAGAGDEDFDCHCFDADFEGAAEAFFDEDCCEDBFCGCGEBEBHGAGFBABAGFHDHAHAEFFFFFBEBCGHACA,False +255,14.0,24.0,17.0,17.0,23.0,22.0,12.0,11.0,EDGFFFGBBBCACDDDBDCFCFCEEAFGFGFGFDBBBFBDCFEFADAHEDBDFHAAGHCHFGACABEDEDEAECEFEFDAABHHAHCECBFBCBFFDBDGHGHFBCDCECEDEAAGEGFBEBCBEEGEBEBEBHCEFBBH,False +256,15.0,18.0,13.0,27.0,17.0,28.0,20.0,24.0,FBDBCHCGDEDCGAGAGDDFBBBFFFFEDACGCHAGGGEGEBABFHFEDHFHFCBDGHGBGDHBCBGAEHFAFHHHDBDCHBFGFGFHFHEGEBDFFFHAHGHCHAHDHEBEFEDGDGAFABDBEHACFCFCEDADEFBDDEAEADFDFHFHFDGHEDDDDC,False +257,6.0,7.0,12.0,13.0,9.0,11.0,8.0,10.0,DDACHGHGHDHEFCCEGEGACCDCDCDADHBFEFEDEGCFBFDFBFEHCHDAGEDECBCBHFGFDFHAHCGABDBF,False +258,17.0,20.0,27.0,16.0,18.0,18.0,19.0,20.0,AGEHCDAGCGFGDCDCHCACDFEAGFGAAAADADCCHGHGHCCEEEGCADACAHECEGDGFBFBFCHCHCBBDBDBDEFCGCBBBEHFHACAGBCHFFBCBCGGGGHDBECEHEHGHBCAGEDEBFCEEBEBDFCFAFHBADDHFHFHFHECFBB,False +259,1.0,5.0,4.0,1.0,1.0,0.0,6.0,2.0,GGGGBGAHBHCGDBECCBCB,True +260,2.0,3.0,4.0,1.0,3.0,5.0,1.0,3.0,BFBCBFHEEGEHCACACHFFDF,True +261,2.0,4.0,3.0,2.0,3.0,2.0,6.0,2.0,CDCABEHHGFGFGEBABCBGDGEG,False +262,17.0,17.0,32.0,25.0,20.0,22.0,15.0,15.0,DHDCDCDGEHCBGBEBACGDFDCBCFCBCEAEAFCDEBAAEADHCEAEHECDDDBDCDBBFFEFGFBCBHAHFCCECGHDHFHAHACDEHECFCDEAAHABBCHGEGDGFHDDCDGDCCCGCACACFCFDADFGFBFBFEGEGEHDACGDFCFCFGBEBEFCF,False +263,7.0,4.0,7.0,4.0,5.0,5.0,7.0,12.0,GCACAHGHECGCHFGFEDHDHDHGHBAEAHBHFHGCCBCHEGEBHAFADAF,False +264,6.0,6.0,13.0,6.0,11.0,2.0,9.0,8.0,DCFBDBEEEEEEADAHGHGCGDHCHGEACBCGCAHEHGGAFAGCCCCCBEBHDCBCEGEHD,True +265,20.0,25.0,22.0,32.0,26.0,23.0,23.0,27.0,DCHBHBCEHHGHDCGCAHHGHDEEHEHBBECDCGBBACACADDDDDFCGEABGBABEBEBEACFHFBEGHFBABCGHGEGDDDEGAHAEFBFDGDHBFGFCDCDCDFGFHEBEHEHBDEAEACBDADHFBDDDDAFEFBGGGGHGHCHEHFCFGFGADDDDBDADHFEBEBECEADACBCFAFHFDFGFAEGHHCCFE,False +266,7.0,6.0,7.0,3.0,4.0,2.0,13.0,8.0,BGHCABHHCHGGBDBABAFCGEGDGAHCEEGEGBGCAHAHACGCGHGFGD,True +267,8.0,8.0,22.0,12.0,15.0,14.0,10.0,10.0,DCBAAGBEBEHECCCCFEDDDFGHGDEDCBCGEGEGEBFFAEHECFCHCHFHDCDCBHGGCCBCFCHHFAFGHGDFCEADCDCDCEBFAFACECAFEFE,False +268,20.0,11.0,17.0,15.0,11.0,11.0,19.0,11.0,FACAFGDHCEFHAECBCBEBEAEGBGBGFHCCBCAHDCFCDGDAEEEFBACADABACECHGGDBDGGGFHEHADAFGFGFGHGHGCFCDCDEGAAAABDDDGHBACACDGDHAGA,False +269,6.0,1.0,7.0,4.0,8.0,4.0,3.0,3.0,DBGECEAEAEAEAGDGFCHCECFAAHHFEFCCDEDC,True +270,18.0,16.0,20.0,26.0,19.0,21.0,22.0,23.0,BFBCDDGAGACDBDGDGDADHCAEACGCGDEBGDFDCDBDGHEHCFFFFFHFBFAFHDDGBHHHHFEFABGGDGDEFCDGHCHEFCFHBADHHCFCBGBFEEEEEFEDEDAFGHGDGCACDEAEACDEDHBHGHBHBHCDGAEACCEHGHAHACAGACBEBGFDF,False +271,0.0,3.0,1.0,4.0,2.0,4.0,2.0,3.0,HFHFEFDBEBHFDDBDGCG,True +272,16.0,16.0,17.0,14.0,11.0,14.0,8.0,16.0,FCHEHAFAFBFBDHGAFABBCDCDHBHEFABCHCHDAGABEBAHDHDFCEBGDFECECECEHECACDBDBDCGAGAGACAGBFBGDDACCDDBHEHBACFBFHHHFHFCFAE,False +273,13.0,11.0,14.0,14.0,11.0,17.0,18.0,16.0,CDFDGBHBFGFGFGEDABABCHHDDEDCHCGAGFBFDADHDCDCECAGEFEBEAFAEHEHGGEFBHCHFHFAFDFACGGFGHHDHGHAHCFAFGEBCBGBGCACDCDEHGFBAG,False +274,30.0,26.0,12.0,16.0,14.0,36.0,17.0,16.0,GGHCBABACFGFHFBBHAEAEACADADABABFFDABBFFEFBAGFHFBFCFBAHHHHGGDGFGBHBFEECEFDCHCHBHGEAHADDGAFAFDDBDGFGBEFFFFFGFACABGFFFAABAFACAGAGHDABABGDACFEAEADBBFBEDEAFFBFBFCFCDBHEHEDF,False +275,6.0,13.0,13.0,9.0,7.0,9.0,12.0,6.0,CEFBGCCCCHDBDBCAFDFDFGFHHCCGCGBGDGDBCBCBHFGAAEGBGBFBGBGECHCDAEGEFADAHEDEBBF,False +276,7.0,5.0,3.0,5.0,6.0,7.0,3.0,5.0,BCCDFEFEFEBADABCFDDHDHAAEAGFGFHFBAEAGHBHE,False +277,6.0,5.0,1.0,2.0,3.0,3.0,6.0,7.0,HBBFBFDHCGEGAHAHGHGFEBHBGGAEAHADA,True +278,4.0,8.0,15.0,16.0,12.0,11.0,10.0,10.0,DHCHAEEEHEHEFEHGFBHEDEGEGFCDCFCGCDCBFFFCEGDBHFDDADGGCGDEDEDGACDCFCFBGBHBDBCFCHCDDDHCAB,False +279,15.0,15.0,14.0,9.0,20.0,30.0,10.0,19.0,EAFFEFEFHBHBHBHCHCFAAACFCAHGBGBFEEBECEGEFDCEFEGCBFHFBEAFDBBGDDCGFDCBBHBHFEFEHCHFBFDGCHFHFHFGFGAAAAEECEFDBEFECEHDFCFHDHFFEAAAAAFGFHFH,False +280,20.0,27.0,17.0,23.0,26.0,20.0,26.0,25.0,AEDGCEBACABABGBGFDCEBHBCBCGHBAEACBHHHCDDEGFHAAFABCEHDBDBDFFGFCBGGGFGEEFEDEAEDEDHHHFHEEEGEGCBCBHBEBGBGECEAEHGHABBBFHEAFGBGDGFFEFDGDGDGHGDAFAGDHDECEHHHAHDDGHGCGEBEFABCBDBFCFCFHBADADFDAHH,False +281,10.0,6.0,6.0,8.0,8.0,11.0,10.0,7.0,GBFFDHAEAECDDBEGDGAEECGGGDHDAFADAEAHBHDEFFFFBCBCECAFABAHGFGFGFGHCH,False +282,21.0,33.0,19.0,20.0,21.0,12.0,19.0,26.0,CAADABABCEABHBABDCHEAEGHBBCCCCCHCBGGGGHHDHGHGDGDGDBDAAGCBHDFEEEEEEBEBAHHGHEHCCGHFBFBFBFGHBDBHAFAGACCHAHFBCCFDEDEHCHABDBEGADBBCBHEHEDDDDBDEDBBHAHBEEEDBBBBHGGGCEFBFAFBGAHAFA,False +283,12.0,9.0,6.0,10.0,12.0,16.0,15.0,10.0,CFCEDFGCGFHFBGCGFGABEGAGAGAGAFADBHGHDEFHHDGCADEGBBCHDAAAGEBEBABFDFEFEFHFHFHFHGBFEGEDDDEFEA,False +284,0.0,7.0,2.0,2.0,5.0,4.0,3.0,5.0,FBBHBHECBFDFGEHCHEHEBEBDGFGB,True +285,18.0,10.0,10.0,8.0,8.0,13.0,19.0,13.0,HHHFGFAHCCBCHCBFAGCGBABDBDGAFDCDAEAEHDADBHBAGFGFGHEFFGHGHBHAFFBFCFCAAABEEEAGGGAGCGFGAGADAGEHAHCDGEG,False +286,17.0,19.0,13.0,13.0,17.0,16.0,12.0,9.0,DBDADABCGDAFEFEFEDABCBEBGDGFEBEBEBEADBDGHCADABFDADADABGFGFCBCDCFBGGEEFCFAFEFBAGGEFHCGAFAHBHBFFEBACECACBCHAHEHEHCGBEH,False +287,11.0,13.0,8.0,14.0,5.0,10.0,1.0,11.0,ADDCHBHFDEACFDBDBABCBCDDDBAAADHFBFBABEHEHBHBCCHFDABAHCDDDCDAFHFEFEFHFHGAB,True +288,21.0,32.0,21.0,22.0,23.0,17.0,23.0,21.0,CFCBBDADEDEDBDHDADCCCEHEHBFBHADADBGBGDCBBHFAEBDHDFDFBEBHDEDBCECEGABCFGFHDHGHEHAAGHGEDEAEABGFCCBEBCFDFAEGGAGADECFFGFBBHCGEBEGAFABDBHFFAHAHAHBHBEBEBCBABDEGCGCHCHBHBGEGEGCAAGGBBFCCGDG,False +289,10.0,13.0,5.0,12.0,9.0,19.0,21.0,12.0,GBFAEDDDGGFEFDHHGHGFGFGDGFGHHHHEGDBHFGGHECBAGAEACFBBDBCADFGEGDBBBBCBHHFFBFBFDAAAEFGFAFAFDFDFHGGGGGECE,False +290,10.0,11.0,9.0,13.0,3.0,16.0,8.0,5.0,DBDBDCFFGFGABEBEDEFFGFGFAFABHCAFABCDHDADAHBGBDDDADFHCBCDCAAGHBFGFGFCCBFFCFD,False +291,22.0,19.0,25.0,28.0,18.0,24.0,23.0,17.0,FCFEFEFAGEGCGEAAAEGEHFHEGFGDGDEDBDEEECBBBEDFHFAGHCAGAFAHABFBFDDGECEBGFDFCFCDBEFABGEDACACDHDHDFFCDCACHCDBBGCDBHBHCFCDHHHBHBGFGFADDGDCDCHCDCACAGAGCDDABCEGHDHFGGDDEAFBFACACABGBGFD,False +292,22.0,21.0,17.0,19.0,16.0,16.0,15.0,29.0,EFHHAHDCDEBEHEHEHEHEHCFDBCBDHCAFEGGHDDBDFGFGHCFDDDDAFADCGCFDFBFBHGAFCCBBEEAAGAGDEDAHAHAHBHBHBHEHCABABHBCCCHCBBBDAHGFDEAEAFHGBGEHAFBGHAFAFAHABCDDECGCHHGHGAB,False +293,14.0,10.0,22.0,19.0,17.0,10.0,11.0,13.0,FDGGCACGCDCACBCDCDGHHDHBHFGGCCFBFBCBDFDAGEHAHEFECBHGDDDCEBBADCDFDADEEEEDEBHAHAGCGCBDGECEHEHAACADAHFHFEFCCECEDECCDAEA,False +294,21.0,23.0,11.0,16.0,19.0,13.0,19.0,13.0,ECDFDEAGAEAGHBFEFGHBBGBABABGDGCCAGHBHFEFGGCBDGDGDGHFHABAECEAGHFDFEFBFECECEFDHGFGABAEHEGEBBBBEBADFEHEHBDBDADADGBHADADHGAEBBBDCACECBCAAGA,False +295,16.0,21.0,15.0,23.0,14.0,18.0,17.0,12.0,DDBBHFDFGBGBHBFFFFFFFGEBCFCGHABBEHDDDDBBBBDGFHFAEDHDHCFCHCECBAHACDCDHAAADDECACAGABAGEFEBCAEACGDGFEFBGBDBCBGGDDAEFEDGCGEGEDEDGDBABADFHCHG,False +296,2.0,5.0,5.0,3.0,8.0,3.0,7.0,5.0,GHDHFBBGGCGBHEHBCACHCGCGEEEEFDADBEGEFE,False +297,8.0,7.0,6.0,6.0,3.0,4.0,7.0,7.0,GDGFBFEFAAEBDBDBAGAEHBDBHCHDGBGCGHGHAAACHCHAFCCD,False +298,10.0,8.0,9.0,8.0,12.0,10.0,12.0,8.0,AAAAAADGHGAEEEHFHEHEFFAGAFHCDCGEBCBCBFBFAFHFGGCGHEDGDFDBGEDEDCBEGEGHCBEBCCDGF,False +299,2.0,2.0,2.0,2.0,1.0,0.0,0.0,1.0,CHCEABDBDA,True +300,21.0,16.0,12.0,20.0,12.0,15.0,16.0,21.0,HFHGDDEFBFBFAGCFAGBGDHEHBHBHAEFBDGACHGHAHFFDFHFHEBBCBDBDBCFCDCACAEDEDHAHBHECABAGCEBHBGEDEGAAHAFAHADCDEGEGADFGAGAHCDAGADAHCHDDGDGDHFBF,False +301,18.0,17.0,21.0,18.0,14.0,17.0,20.0,23.0,BEBFFCAGAGAGHGHFHDHCFDFDEDEBEBEAGFBCCHCDCBCHHGHEACAEFGBGBEDEBCDADHFAADBHBHCHFDFDFHGBGBAEFGFAAEHEHEHCCGHDDDGHCCCCAABCGCGCADACABFEHDBCFHGHGDAHHDFGBGFG,False +302,17.0,9.0,16.0,15.0,18.0,20.0,16.0,20.0,CFEHGDGCGHFADAFGFBFHABACDEDEDGAEHEHCCCBCEFHGHAEAEAHAHEHEHCDFFAHDEAFDFGBGDHHFHFAGGFFBEHEAEAFFFDGBGCGEECAFFHEHEHDACBCFCDDDDCBCBHGAGCG,False +303,17.0,9.0,12.0,14.0,11.0,11.0,11.0,15.0,DFDFAGHHDEDEHEHECGFACAEADDHDEDCHCECFHBBBEGHBACGGGAGAHDHAAADEHEAFADGDBDFHFGBABABHBFCHAHACCFCGCEADFCFG,False +304,32.0,22.0,21.0,20.0,17.0,21.0,22.0,16.0,HABACGCBCGHGHADEGABAFHHGFCCGFFFHFHAHAGACFGEEAHAHABABFBAEAEDGDBDFFFFEGHGDDDCHFAFGECACECECEDFBEAAFBCGAGECECFCFCBGGADADGHACAEBHAHABGGDDADCDADBBBGHEFEDDDGEFBDBDBCBABCBAAAACFGB,False +305,22.0,14.0,10.0,9.0,20.0,15.0,19.0,12.0,GAGABHEFGHGABAEDECGAFABBEFEAECCAAHGHBEEEEEFHFGFGAEAGAGDGHGFAAAHAGAGFBECEFFBBGHGFCBCGCADEDBDBDBDFEECEBEDGAAEAFAHHBFCFCDHGH,False +306,7.0,13.0,6.0,7.0,4.0,5.0,5.0,12.0,BABAFAHDFDGBHHEHBDACHGHGDDBDHFFAFACEBEBEBHBCAHBHDHCGBHBCGCB,False +307,27.0,19.0,23.0,17.0,31.0,29.0,21.0,17.0,FADCDEGEBEGHDAEFEAEBHBCBAFAHAFGEGFBFCAHAHCCBDFHGCEFFCFEFEAEAFCBDADADHDFBFBEBADFCFEFBFBFDFCFGFEAHBBCCCCHHBHAAEGEBECEGDAEFDGECEFEHGAGEFEDGBABABHDHDCDCGHAEACAGFCECGGHEDCFAAAGAGCEHEGEGFGFE,False +308,16.0,23.0,23.0,25.0,22.0,21.0,28.0,27.0,BHGEFEDACAGADADGDGDBBFBCGGHGFCFCEHHDCDCEGFCFBEBEHDHCHCBEDDHBBEBGGFDECHCHCBFDFBGEHEGEDEGAHDBDAHGBGDGBCFCGCGBBAFAFABBBFGFHAHAEAGFFFGDDCABHECEDEBEHDGDEDEGCHCDCACHCAFGGGHFHFHGHGCAEHHHHDDBEF,False +309,11.0,10.0,14.0,4.0,9.0,15.0,8.0,17.0,CECHBGAHBHAHGCACBEFEFDCCCCCBCDCGAFFFFFBCBAFHFHFHDAEAHGHBHBHEHBHCGFBHAAGEFEFEGHAHDFFCAEHG,False +310,7.0,7.0,11.0,8.0,8.0,14.0,8.0,4.0,AFACGFEEDBGHDDADFCFCFCFDBGBHEHFAGDCACFCFEFBDBGBEBFCFCFCADGEGEAHCFGE,False +311,1.0,3.0,3.0,4.0,1.0,4.0,5.0,3.0,DHHBHDGDGCFAFGEBCBCGFGFD,False +312,9.0,6.0,12.0,3.0,7.0,3.0,4.0,5.0,AAEAECGCDFDHACECEAEBHBACCHCHEGCGCHCACBBAFAFCDGEBB,True +313,10.0,20.0,11.0,11.0,10.0,21.0,14.0,10.0,FHEBEBCAHAHBFGFGHGFAFCFDBDFDCHBECCCHEACABDGFBFEFAFAHGBFBDBDBFCCCEBFGGBGFAFABEEAEGBBFFDFBFBDBGBGCGDEDHFHDGGH,False +314,11.0,11.0,19.0,12.0,11.0,7.0,10.0,11.0,GBHBFGDABADADBDCDADHBGCECHCHCGCEAGCGCDCFEAGAEAEHECEFFBECDCGEHCBBBCGDHDBDADCFFEFCACAEBHHCHGHC,False +315,15.0,20.0,19.0,23.0,12.0,16.0,12.0,15.0,CCCCEFDBDHDCDFDCHFHFDEBACECHCGGFGAHDDDBACFFFDFBBABABDBACADAHCHDGCFFBHHDHDHGCCACEDBDECEHEBABHFDDDDGEFBFBGBEBFAGAGBGHEHDFEBABAEADBCGCG,False +316,6.0,8.0,6.0,3.0,8.0,2.0,0.0,9.0,CBCDFDHABAFEHBHBHECEBECHHBEEECEHAHCDAHABAB,True +317,5.0,12.0,12.0,7.0,8.0,8.0,7.0,11.0,CHGBGBFBFDABACAFFFCECHCEGDBBGHCCBGDGFGHEHDHCHBBCCECEBEAEAEHDCDHHBHBDFF,False +318,19.0,29.0,24.0,19.0,24.0,39.0,20.0,15.0,CFEFGHBHFHCEABFCCCFFEFEGBGBAHAHDBABCBGBGBGAGAGABHCCCFFFEHEDGBHEEDHDEDBHFDBCBGBFCFBEDFAFCFGACEFGFGAAFFFFDFEFECCGEGBDAAECECABEFDFCEAEAHFDBABDCHGBGBGBCACBCBEFGFGFCFHDDFAEHDFFEDDFDFBFBEBEBFHFCD,False +319,8.0,5.0,5.0,2.0,5.0,4.0,3.0,7.0,HAAEAHDHCBDEAHCGFGCEABAEAFAFHFHBHBCBCEG,False +320,4.0,0.0,2.0,0.0,3.0,0.0,0.0,1.0,CACAEAHAEE,True +321,19.0,25.0,20.0,14.0,21.0,25.0,19.0,10.0,ECEAHAGAGDCFHAHAHABEGAGBEBFFFFFGFDFDFGCDCBABEBGBFFFAGADFDGHGABAHAGCBABGDGEEACAEDBCBCEEFHGDDCBCEGEFEBEBFGCHBHBEDFHBCGEBCDCFCEBEFEBCBCBCBAGFFAFAFDCGEEFDCBF,False +322,4.0,3.0,7.0,8.0,3.0,3.0,6.0,6.0,AGDFDFDAGECEDDHCHGHCBFDEBCBCHCHCDDAHAGGG,True +323,20.0,23.0,10.0,13.0,14.0,23.0,24.0,21.0,AGAFFGHGEBBCDCEEEGBFAHAEGEGCGFGAAEBGHEBDGAGEBABEFCHAHADFBFDFBHBHBGBEBFBFHCACGCGBFBFAHAHFEFDBGGGBGFGBBEDHGHGHFHDHDGDHBFBFDFHFHFACADAGEFHCAADHBHCADFGA,False +324,6.0,10.0,13.0,15.0,5.0,10.0,12.0,7.0,ABBDDDDGDHDCBBHCHGDGBAEGEGHDBCFGFBEBADGCGCGHFFFFFCFCBDBDGDCAAAFDHCCCECDFDHCGEG,False +325,14.0,17.0,16.0,18.0,24.0,25.0,25.0,12.0,EAGDFBFEHEFGADABCCEGEAEGEGHGBFBDEAEDHDFEFDHCHGBGEECDCDCDCHCDEAEACCBEGAGEBFBFBFCCGFBEBCCDEDFDHHGAGAGEEFFFFFBGHGHBDECEBAFAFDFDGGGAHBEFGFGFHDGDEFGCABFBFGG,False +326,10.0,8.0,13.0,7.0,11.0,10.0,9.0,12.0,HGFCFAFCFAGADEDBHFCFCHHAHACEBECCCCEGEFEFGDBFBHBGBCEEABCECAADDEDHDHBGEGAHCHFHGAGH,False +327,13.0,9.0,7.0,7.0,11.0,9.0,9.0,4.0,EFEGEFABAFHDBFAFGGEBEFECCCEFFDADBDGEGAGABABABFBDDAEAHAHGHEAAGDECCCGCB,False +328,11.0,7.0,14.0,13.0,15.0,16.0,11.0,12.0,HHHHFDGEGFHFHGDGCCHFBFEDBAHGFCDCGGDDACACEDBGEDEHHGHEFEFCFGFAAACADHFAFCFCFCBDBAEEEEGDFBFAEAEDEDEBCCC,False +329,14.0,9.0,16.0,7.0,13.0,4.0,16.0,18.0,GCAEFCFCACAEDGGEGBGBGBHBHAHECAAAAHAHECECHGHADDCBCFCHHGAGEGDGEAECGBHDACECBHDCDGHCHGEBHBHEHCFGEGHHA,False +330,6.0,12.0,18.0,17.0,8.0,10.0,10.0,6.0,GGFCECDCDCAABEBEHEFDDADGDBDHGFBFBEDHDFBHGGCBCBCDCBCHDGCBCBEDCDGDBECADACCCFEFGFGFHDADFCC,False +331,11.0,25.0,21.0,16.0,17.0,27.0,21.0,23.0,FFFCHCBCGHHHGGCEBEDFCHAEFCFHDBDBABFBFEFBFHDHFBGCACHHFBFDFGFBHHDBEFAFAFHFEEEGEGEGEDBHCDCACHHGFGFHHBDBDBHCHGEDBDECECECFGBDBCEGGGGCCBCAAADAHBBBGBGFGHDAEFGFBBGHDCFCF,False +332,31.0,34.0,15.0,23.0,18.0,19.0,14.0,23.0,HBFBAAACBDEABCHDHAHDFEFHAAACDEBHBHBHBCBHBHBGCAFGBGBFFDFGAEAEBDFFADADACADDDHAHAEEBFDFGCCCFCAEGBCBAHCGEEEEEEBFDFEHBBBABAHADBDEDFGHHBHBDDABBHBHDHFCFCGEBAAAEGFDFDGDBBBAGAGABAGHBHCAD,False +333,20.0,17.0,9.0,14.0,13.0,13.0,13.0,14.0,ABGCECACBHDHGEEHEHBDAAAFDEDGDFAFABCCGHBABEBEGADADFDEHEHEGBGAHADDHHGHGCGFFABAFDBDHABEFDCDFFAFBEBHBAFAFABABGCECHGBG,False +334,7.0,5.0,2.0,4.0,6.0,6.0,4.0,9.0,GCGBFBHAHEBEAEDCGEAEHHFHAHABFGFHFHDEDADAFHB,False +335,17.0,13.0,10.0,10.0,9.0,12.0,9.0,20.0,AGHHAHAHCBABFGADADEFEFEDBBBBHHGHDHBCECEHFHFHBHAHDEAEAEBEHACAGADHCHBGGFFFHACBDFDAGHCDGDCFCACFHFBBHGAA,False +336,10.0,13.0,6.0,5.0,11.0,4.0,11.0,9.0,EGEBEBEGEBAHEFBCBEHGDFHFAFCBHBGDABHGGGBGCGBABADHDCEABABADAEEGAGCHCHEH,False +337,17.0,16.0,15.0,8.0,14.0,17.0,17.0,24.0,HBGBABHBHDFFAHAHAGAEAEAFACGCBCECFGDGCCEFEFHHHABGFCHDHGBCBHBDGDHEHGHCFCHGHDHFHFBFDABHBGBAFHEEGEGECBAGEHBHCHEFEADCBFGHCEFGCGFAAAAF,False +338,18.0,20.0,22.0,16.0,18.0,27.0,14.0,22.0,AEAEAEAFHDHAAEFBDHGFGFCAAAGADFFEFBADCHCHEGBBEBGFGFGEHEDCFHAEBHCDCBCGAECGCHCHBFBEBHHHGCBHFDDGHHHCHBDEDECBDFEFBFGFCFBFBCBFBFCDEAFDGABADADBFFFFECECADHHHCHCFCFCG,False +339,24.0,25.0,25.0,23.0,21.0,21.0,28.0,25.0,ABAFDFCFCGHGCDBDGEGEGCAAEBHBHGHGHDADCGCHFECEBDHDABHGCGHDHEEEBFBFBDDCDGEEEHBFFCFBFAFAFGCCCHGGFGCACHEDEHGDDBHEHDACAFHEABGCACABDBEBFDGHGHFHEAEAEADACGGBBBCGCGDGBGBFCHAHAHFBABFCEHBADGDEBACGCGFAFDHD,False +340,14.0,19.0,9.0,8.0,9.0,16.0,11.0,11.0,CAADABAEACBCBGAADHBFFFBDBDEGABHHHAEFHBCFHBEBGFDFBFBDBDBDAEGEGEFCGBFBAEGBGFGFHFHFGFCBCAAGAFEHHHCBC,False +341,2.0,6.0,2.0,4.0,1.0,4.0,1.0,1.0,ECBDBFAFDFDBGBHBCBAFD,True +342,10.0,9.0,6.0,7.0,9.0,12.0,7.0,13.0,AEAHAHFEGEGBGAEBBHFDBGBHHGHAFAFAFHFDDCDHECFCACFHFHCDCDHBEBFAFGFABEEEGBDHH,False +343,12.0,23.0,13.0,17.0,19.0,18.0,25.0,20.0,GCGCGCFABHCGAFCFDFBHBHEECDDBEHEAEABABAHHFFDFGEBEBGCABAGGEGEDEDHBCFDHDGBGDGHAEAGDHAEEECHHFBDGCFCDBDHFHBBBDHHCBEHFHGGGFGFBEBEFEFCFGFGHGDGDBHBGBABDGEG,False +344,8.0,19.0,17.0,14.0,18.0,17.0,16.0,26.0,BFBHCHCACDDFCHEHAFAFEEEDHGHBEEFADGGFGEEDEDEFEFBFBHHGHGHDEFCGCGHDHDBCHDBCFCGEBHBHEHFDEAEBEGCGBHBFBHBCBCBCBGACCHHHGHFDFCFHGDGHEHDCBAAFHBG,False +345,14.0,25.0,9.0,16.0,24.0,29.0,24.0,20.0,BDBDFDFEGEDADGGGGDFAABHGFGFEBHFECHCEDBABFBEDGGCFCEAAHGHFBBHHHHHHEBEBFAEEBEDGDCHEFBFBFBHEGEGEAEBGGCAFFGDGAGAGHFFFFFGCHAHBHDEDEFHBBBFDFHFBFBFBHDEFGBEDEGEGBAFFCACEG,False +346,20.0,21.0,26.0,20.0,28.0,15.0,21.0,20.0,EDEDFHFHEDCCECEHEHCGBBAEFDDHBGBEBGAEHECGCACECGCGCDEHCAFAECHBBDGDFCFBBHBEBEHDGDBDCAGACAHAHDHCEBEHEACDDDFFAGAFAFCGEACACGEEAHAGAGAGEFEFHFBGCHBDBHBCGDGCECHDHFBFDCGCBBEBDAEGEGE,False +347,9.0,10.0,7.0,7.0,9.0,11.0,7.0,1.0,DAFCBCBAFDEGEGEFAADGEGEAEAFGFBFEFCFGFCFHEDCBGBEBAFDDABCBABDBC,False +348,23.0,21.0,22.0,23.0,12.0,21.0,19.0,12.0,DBGBGFCCGCDHGFGFGFDCDEAEAFBFBHGHBCBABAFFFBBAFHFCDBFECCDCACAEADFDEDGCFCHBBBBDFDCGAHFGEADDGHFFDADEGEAEFEDECACACAFADCFCAGBBABEDGDHCGCACACHBDGGAGBGBHAHADDDHB,False +349,24.0,18.0,28.0,33.0,14.0,23.0,32.0,22.0,DBDACACDEGGCFCBGBHFGDGDEDHHADCFBFDFDAAFAGDGCFCECEGDGFBAGHDDCDCDGHCFFAFGDGDHDHFGGBGHDCDCAHFEDBFBFCDDEDGHAHADABHBEAAACADGBGAGAFHCCGFGCGDGAEAGDGHFHFEBAHCFCFGGGEGEGAGHBBBDCCHCHFHCHDFDBDCDEHECBCEAABC,False +350,8.0,4.0,6.0,7.0,7.0,4.0,16.0,7.0,EDGFGACAGBHBEBAGACAGEEEEEGGAGCGCDAFHGDCDHGHCHGBGAFDFDGGGDHH,False +351,14.0,22.0,13.0,15.0,4.0,11.0,14.0,13.0,ABCCHHFHCDBDBDBCCGCGFFDFBFGGBAHADDGDCDCBAHABEFHBBDBDBDBEBEBGDAEABDGFHBHGAGCBFHHHHHACGBGACFBBDGDBFAGAGACACF,False +352,23.0,10.0,18.0,19.0,18.0,25.0,14.0,15.0,GFADHDHFCGCBFFFHHEDFDHAEEFECAGBGEAHAHADAEGCBFBFEGEFHHEGGCFCHHAHAHEBAADAGBEBEDEDGFEFAFADADFGFAFCECECFFAFACACHCDFDADCDGGFDHCCCCDGDAFBFBEADBDAECF,False +353,28.0,26.0,15.0,29.0,24.0,17.0,31.0,29.0,EFGDADGCGBGBGBEAEHGHFDDEDEDEGHGEGEGHGHEHGDGBGFEAEGDCHCHDHFHEHAGDHDFEBEBEBEDCDCACAFGFCABFEGBGAGHHBDBABABHHAHAECEAGBGBHBFEDHCFCDGAFDHBEACFHHGDADHCFCBAAHFFGFDADBBEBHACABAHGDGBEAFABDBGGGGDDDAAHDDDHCHAABE,False +354,2.0,5.0,6.0,7.0,4.0,6.0,4.0,6.0,BHGHAECCCFADBDHDEDBFBHDCDCDFGCGFGFHHEFEB,False +355,6.0,5.0,6.0,6.0,6.0,7.0,2.0,4.0,HFHCGCGBFEAAAHAFBCBDEDEDEDCDFFABBCFCADFEHE,False +356,6.0,7.0,14.0,10.0,18.0,19.0,15.0,16.0,FBEHFGEHFDCDGGGEHCDCDFFFHBABDFDFHCCFEFECEHEFCAAGFGBCBFGFEBCACACDFFGHGBEHEHEHFHCCEGEGEGECAHEDEDGDGEHHHGHFF,False +357,14.0,24.0,11.0,19.0,13.0,13.0,20.0,12.0,CAHGEBBDBFBEGHAEDBDHDGDGECACACEFBDBFFGADBHBCCDCDHDEGEAFAFEGBFBABHFHAEDEDGHGBEBGBGBGFFBCGEGDAFAFAHAEBCGDDAGHHBCBDBDBFBDBDCGGGGH,False +358,14.0,23.0,16.0,16.0,14.0,16.0,6.0,16.0,HBCBHFHFHDBAGAEDCCCBFDFHFHDHDHGHABCFCFAGEGBBBFDADADBEBHFCFDFCBADDBCBCBCAEGEFCBABAFAHBFBEBEBCCEEHEDECBFAEHGADHDHEHBDEFBCDA,False +359,13.0,21.0,20.0,21.0,14.0,16.0,20.0,15.0,GFDBDCACAEBEBEBHBCBCECEGACHCHAHAGGBADADBDFCFHGDGDGEBHBDGGFGFGDBDAGABDGDGEHFDAEFFGFDHEBCCDCHCFCECHGDBCEHEFDFDABEBGDGHACFFBDCEAFGDBCGCBCFHBHBH,False +360,2.0,2.0,1.0,1.0,3.0,6.0,2.0,3.0,GFFFEFEBDBEHGCAHAHFF,True +361,14.0,17.0,14.0,17.0,23.0,22.0,11.0,18.0,DHACABDDDFEFBCAEAEAEFCFEFCFDFHFAFBCBCHGHFHEAEGBHBGCFCHAEBEFECECGFEDEFCCHAFAFAFADGHGBGDHDEDAHBHBHGEEBDHDBEEHGDEDEFBFBFHFGFBDAEBDGCHEEDCHB,False +362,7.0,7.0,14.0,4.0,6.0,6.0,6.0,3.0,CCBCGEGCAFAEADAGFGFCFCBCGHBBDBCGEAHAFCDCACBCHCEEFECBD,False +363,10.0,8.0,17.0,16.0,17.0,20.0,8.0,12.0,FEADABEGEHEBEBECFCDCHBHCAEEGHCFGFGFHHEFEFDFGFDECCACHFFFCDCGADAFGDCDCDCEFFFFAHAHBEECCDADAFFBEDEDEDHCFCDBHGHDB,False +364,8.0,4.0,4.0,12.0,13.0,9.0,10.0,11.0,FFHEHDFFAGEGEHEHFGDDDEDECEDABHFGFGDGAFADAEECGGABDBGHHCDCBGFDHDHAEAEHEHE,False +365,6.0,2.0,5.0,1.0,4.0,5.0,1.0,5.0,FEACAGFEFHCEABABAHFFEHAHCHCDC,True +366,11.0,5.0,9.0,15.0,4.0,9.0,12.0,5.0,CCFDEDFDFEFEHDBDCDHGGGGDFDAACADABFGCBCAGAFDFCGCGAHAGAHDBDHCGEBFDADADGG,True +367,22.0,11.0,14.0,10.0,20.0,19.0,35.0,19.0,DGGGBCECGDADABABHEHBHGAGHGFAFAGBGBGEEACACFEFGGGEFHCDEEBEBAHCEFFFFHAHAHGFECBHGGEGEHAHFGBDFHEEGCGFDAAAGEGAGFEFHFGAGAGDHAACAGHGCGAGDGBFHFGCGCECEHFHDGEGCD,False +368,2.0,3.0,4.0,0.0,3.0,2.0,2.0,2.0,BCECECHFHFAGEGBBCA,False +369,2.0,7.0,10.0,3.0,12.0,8.0,6.0,9.0,HHDHDCCEGEFFFHCBBHDEGEHEFEFEFEFBCBEBHBCCGCHEHBGGACECEFGAC,True +370,17.0,20.0,13.0,14.0,12.0,20.0,18.0,16.0,HEFEBECCHDECGCEBBGCDBDBDGFGFAFHGDDFDHBBBFAGDFAGACEFHGBFDFHFHFHCGBEDHFCFCFGAAEDECEFBFAHABACAGAGACAHABFBFGEGDBFBHBHDHDGBABAGCGEBAHGH,False +371,14.0,16.0,16.0,7.0,13.0,5.0,11.0,14.0,GBGBEHFHFBBBECAABDEABAGAEDEDBCEGECCACAGACACBCHCECEGABDBEBHBHFHCDAEADHCHCHFHCEABBCDHEGFGCHBGGHGHA,False +372,9.0,15.0,11.0,10.0,12.0,17.0,13.0,14.0,BEBEBGFFBFGFDFGCGCGFHDGGCFAFAFBFDHDEAEHEHAFBFEGHHEBGAGCHHHDDCECGCABFBFHFEDEDHBBCBGBCAGACAHBECEDDHBHFF,False +373,14.0,9.0,8.0,14.0,6.0,19.0,18.0,14.0,BHEFAHAHDDDDFBFDFGFEFHGBBFAAAGADHGBFCDGBEFGFCHHGFGHGHFHGEGAGEEAGDDABGGCCCBHBHCHDFAFAFAFGFDFDADADCGCGHF,False +374,13.0,6.0,13.0,5.0,8.0,10.0,12.0,6.0,CBGADAHAHAFAFGCGFGCDEAEADADCBHDFAACCCAFHBBCEGEGECFHAEBEHCGFGFGEGCGCFCGABF,False +375,8.0,5.0,6.0,3.0,11.0,9.0,8.0,4.0,EEEEHFFBFGGCGHGEBABEEFCFCBHGDBHFAFAFDFGAGDGAECECECAAAE,False +376,6.0,8.0,6.0,9.0,8.0,5.0,12.0,5.0,AEGEBACACHCGGHDBDBCEGEBEBHFDDGDCDBDBEGCAFBFGGGEHEAADFDFHGGG,False +377,2.0,3.0,2.0,5.0,6.0,4.0,2.0,2.0,EDEDECEBHBGFGAEADFHBDFEFDC,True +378,18.0,11.0,12.0,20.0,13.0,19.0,14.0,21.0,GAEHGHAADADADBFCECDCFCGDDFCGHAADFFFGHBHFDCDBFHFHGHFAGAGABADDHAEDECFFFAFAFDEDEBABFBGGHBCBAACBHHHFFEDEDADBEHFHGCGEEDHDCDGHGHEHEHCH,False +379,15.0,10.0,10.0,14.0,7.0,13.0,13.0,11.0,FHGHGHBBCDDDDABABGCEDADCHGAAHAFCFBDBDADFCFDDHCHFHAHCHCBCGGAACAHGGGGAGBEDFDFEAGDGFEBEFFAFAEBEF,False +380,20.0,20.0,27.0,28.0,18.0,28.0,19.0,15.0,FAEAEHHHHHHECBHFFFCFCDAGFGDEDCDCBGFFCGBGEGBAEAGFCADGGBEBEFHFDCBAEFDFDEDAHAHGEDAGBGFEBEGFDDDFDFAFCCCCCCBCBCGCGCACDDBFAFBCDADCDEDBCBCGHGFGBBAFDCDHBHDDBDCECACDFDGABFEDEAEFHHAAFFF,False +381,9.0,4.0,8.0,8.0,10.0,3.0,5.0,2.0,DEDECFCECEDAAACHEGDDFDFCACECGAABDGCHBEBGDGBAEAEAE,True +382,28.0,23.0,23.0,25.0,22.0,19.0,22.0,24.0,EBAHHEDEDBDHHGADFEFEHDHDGFFDFDADHDGEACBEHEFGDGAGAGEBCDCBBAFECHGGBHCHCGGGCGAFCHCHBBEBFBFHFCGCGEDEAAADABABADFEFDCDCECDCHCHCBAAAAAAHAFEGEADCCFHFEBEBFHDHFAAAGCBBBCDHDEDFBEGHCBDBGHGCGHDEAGABA,False +383,4.0,5.0,2.0,2.0,4.0,7.0,4.0,2.0,FAFBFGCGAGAGFBDEFEFHABFBDCHEBE,False +384,23.0,10.0,11.0,21.0,17.0,14.0,20.0,15.0,CBEFFDDBFAGHDAGAGAGDDBEGCCCDCBHHEAEFGFEEEHEACACAGAGBDAAHFHFAFADEHCACGDAEEFGGHEHBCDAGAEDEBFGHDHEHDHFHAGAGAGAFAFABBCDGGGDBDGDEDEDFDHD,False +385,16.0,15.0,15.0,12.0,17.0,20.0,20.0,23.0,FGBHBHAHAHBDFEFEBCAEEDEAHBHBHEFDCBAFCFAFAGHGHGACDHBCAEHGHBABFCFDGDFDFHFDBGFGHHACADACHCGBEBEHEACGEGFGFGDGEGEGECEADACBGFHHDFFHFHFGGBHCGCEEHC,False +386,22.0,28.0,19.0,25.0,19.0,24.0,12.0,27.0,BHDGBHDFDFDBABGDHAFAECECBCBCFCBEBHHHEEEBAFDFAFADECBDFDFAEHBHEHEGEADHHHFHFHDBFHAHADADFDFCAHBCGCDCBBBGBFAFCFHAGADDBFEFEAAHCDCECBDFFHFHBHBFEDCACAGEFDHGBEHGBCBHEEGAGHBDBDGHADADCBCB,False +387,16.0,23.0,23.0,12.0,27.0,6.0,20.0,14.0,EDEBGBEBCGGHCACBHBEGAGHGCGEGFCHBDCHGHBHGDADADBBCHCBEBACGEGEGEBABABDEEHECCCCBBBGAGAEAGFGHACCBBABAGFBEEEEEECGDDCDHEEEAEAECDCECGCFHFCBCEADDHEBFH,False +388,29.0,22.0,29.0,26.0,26.0,22.0,19.0,18.0,CECEGHFBFDDCDHGAFBGDFAAHACACAEEBEACFCAEECCGCGCFFFABGBGDCDGDEAEABHBHBFBHAHDCECECHFEFBACDDDEHAGABADFDFDBDBDECECEDHDAAAAEBEGAAADGFBFADACHEAACFGFGCGEHFHFCCCDGGBCEGFAFEBHCDAGBCBCDCEEGDBDBDHFHEBEHH,False +389,6.0,5.0,9.0,6.0,6.0,10.0,3.0,6.0,AFFFACCCEHHHHACDFDEGCBCDEDCFBFBDBFHFHADGCGCEFAFAEBE,False +390,5.0,5.0,8.0,6.0,3.0,4.0,2.0,9.0,CHCGBFDADACBFDFCHHDHDHCGCBFAEAEAECHCHBBDHH,False +391,17.0,18.0,29.0,20.0,13.0,16.0,17.0,22.0,GDCDGHHBEBFCFHGHAAAHBCDCDHFHEHBDDDDDCDCACHEBDBCBFDACBCBHACCDCGGGGCBCFCFBACADHHCFCADHHHGCBBGDGCGEEHEACAGGFGCABABDBEECECECFAFAGHHDHDFBFGFHECEFDFAHBHFGCACE,False +392,4.0,11.0,10.0,5.0,8.0,5.0,3.0,15.0,HHHHEEDDBGHGFABEBECCBHBCBEDECBCHCBEFEHDBDHAHBHFAGCHCHCBCAHFHF,True +393,5.0,6.0,6.0,2.0,4.0,4.0,5.0,6.0,HGFGHHHAGCGEFEBDFDAAHAFCBCBCECBGBEBHCA,False +394,21.0,28.0,17.0,22.0,17.0,15.0,15.0,14.0,DHAAAAFCDBDBDGGABBBCHCACGHFBBBBBBBAAAAFBBBBBEGEABCGFDHEHEDBAADEDEDEHCFEBEGDHFGGECDCHCHBDCEFEHDBDBDBDCECGCBFDGBADHGGFAFAFACEGEFDFBABFFEGDAACACHEHDHDCG,False +395,17.0,17.0,23.0,13.0,25.0,16.0,32.0,27.0,ACFCFGGGEEHEGGDEHBACACECEFEFHDEDFDGEGBGFHCCACEEFDACHGHGHBEEHBACCCCHCEFDAGAGEGCBHBHBGGGDGCFAHGHGHCAEFBBBHBGBHHEHEBGGEGEFHFHFHGHGCFCGHGDEDAAAGCBBBCHAEAHDHDFGGGEGBAHECDFDCAE,False +396,2.0,4.0,1.0,7.0,6.0,10.0,8.0,9.0,GCGFGFGHBFAEGFHFHGBDHEFEDHDEFEFDFEFBGHHAHGDBDHD,True +397,12.0,14.0,13.0,17.0,13.0,20.0,12.0,15.0,CEBHFCBGHGEGEACAHBHBDBGBADFDHDFDADHHEHFHBAAFACECECEDDGDGDCCCHCGBBDGFBECGDGACFFFFFFDHDHAEFEFBBGBFHFHECAFDBEHDFAFAEGFD,False +398,28.0,19.0,7.0,24.0,27.0,19.0,20.0,15.0,DHEAEADDHGAAHAGEHEBDBDHFCFEFEFEGAGHGBFHECAAGDCDADFCHDADADFDHGBGAEHDGFBFAFAFEFEFEHCAAAGGBBABDBCEADADFEGEFHADEGGGEGEGBGBDADEEBDBDHEEEDADEBBFHEEFCFEFAAAGABABDBHBG,False +399,0.0,3.0,1.0,3.0,3.0,3.0,0.0,4.0,DDHFBFEFDHBHCHEBE,True +400,14.0,15.0,8.0,10.0,12.0,16.0,15.0,13.0,BABABGHFHEHEAEBFGHDBCBGDCFFGAGDGFEFEFEFHDCAGAGHHAHACBCBGAGEGEDBDHDEBCACBHAHCFAFEBEDFFFBFGEGFABHGDADFBHG,False +401,11.0,5.0,16.0,15.0,7.0,18.0,6.0,17.0,EGDHHBGCGFFFFECHDAFAFBFDHGHAACFFFAEHBFDFHEHDFDFDABBEAFCCCCCCCFHAGADDDCCEHEHCHDHAHFHCCCFDHDHDADG,True +402,3.0,10.0,24.0,13.0,15.0,13.0,11.0,19.0,CBBEDHAHBDBDBGCECHHDHGHDCGCGEHCHCGCEEEEHFHFECEGBDDFBHEDBDADGFHCHCGCBCDCEAFGFGHGHCECFDECCCCCDHHEBFHFCFCEHFFCF,False +403,1.0,2.0,2.0,2.0,0.0,1.0,2.0,2.0,DGDABGBCHCHF,False +404,5.0,16.0,6.0,12.0,8.0,5.0,12.0,9.0,DGDHBCBCHGEEHEFGFBAGABADDCDBBBBBGAGEEDCDGHGHFHBHGGCEEDBDBDBCBDBGFAEBHFHGD,True +405,21.0,16.0,12.0,16.0,13.0,10.0,25.0,18.0,GFEFBFGGBGBGBHFHEBEBGBGFGFCEAGCDHAABHBEGCGHDHAHDCEGDGDBFGCAAAAEAGADFDGDAACACECEBFDHBAEACHGHAHDEDEFHHHBGEGACDBAGGBCBHHCDGAGDGHGHADAD,False +406,4.0,4.0,3.0,5.0,1.0,0.0,4.0,3.0,GBDDABCBCGDGDCHBHDHAGAEA,True +407,16.0,7.0,6.0,14.0,13.0,6.0,14.0,8.0,BFCAAAAAEFEBDFCFCADGDBDBDAGAHAEDEGHGHGFDBDGAEHEAEAGCEDHAEADGDAFADGGEGHGHDEBEHDGBGCCE,True +408,12.0,15.0,11.0,21.0,18.0,14.0,12.0,11.0,DBDBDBDBCBGGABCEFEFGGDBDAAAEHEFEBGBECCFCBGEEAEHCBFEFHFCEBFBHGADFDACABEBEAECDCGFDDDDDDHGEGFDHDHDHFCDDEDGAAFAFHHGHEE,False +409,20.0,21.0,28.0,22.0,20.0,26.0,20.0,22.0,FCFDFHADGDHDHBBCCHHDHDHDGAABAGCGCDCDFFFAEAFBHHGHCHEFEGBDCDAAHABBCFHFEEGEFFFCHCDBDEDEFEDAFAFABEHCCCEBHBDGDECCAAACDGFFEDHDFBHBAGAEAEFECGGGCHCDAHBGBDBCBEHGFCFCFCFCEGEGHFCBGFGCGCEABBB,False +410,3.0,1.0,3.0,3.0,0.0,0.0,1.0,2.0,DGACBHDHDCACA,True +411,10.0,24.0,18.0,15.0,16.0,10.0,24.0,18.0,HHFBFECHGHAHFGGDCBCBCEGHGBBAAGCCHCBDBGBDHHHBFBDBGGCGHGABABACEHEHCDGDECBAAEFGGDGEADDDHDHBEBEGEFEGEGCGDGDEDBCCCHCEBEDCGFGHGEGFBFBACHBBBBF,False +412,7.0,7.0,14.0,10.0,10.0,6.0,9.0,5.0,GEDFDFBAGCDABADDGAHEDEDFDCDCDFHCBCBCGCHBGCFCAEEEEEGEGCCCHHGCBEBCAGAF,False +413,1.0,1.0,2.0,0.0,2.0,2.0,3.0,2.0,FGCGCHEHEABGF,True +414,3.0,7.0,4.0,3.0,7.0,6.0,6.0,8.0,HCHGEEBABABFBEGFGAGBDFDEHEFCFBHHHFHCHCBEEGGD,False +415,17.0,22.0,23.0,22.0,24.0,17.0,20.0,16.0,BCBGBADDEHEBECCCCDGAGEGEAACEHEHGFABAEHECECFCGCECDBACAHADECGCBBFGFEHEFGDGEGCGFGDHDCBCAFGDGDAEFHFCFBEEHEBDDFHHHBAFAHDEDGDBDEDECFCFHFAGCFFAEGDGDADCBBBBCGHHABBBBBDED,False +416,23.0,23.0,29.0,23.0,28.0,15.0,36.0,18.0,HDFEEHAHFECBCGDFDFBAGABBGGADFDGEGECECGDHCECECEDEDACACGEGCGFBCBCACEEDEGGABHEDCHBGGGHGCGCBDBCCCEHEBGBCDDGGHGEFEGBBBDBAFAFAGBFFHHADEGEDBCCCACGCDCGEAHAEADGGGDGDBFBFCGCGBGBGACAHAHGEFDADEHEHAFGHBHDEAEA,False +417,6.0,3.0,6.0,6.0,13.0,9.0,7.0,12.0,HGCCECEAEHGHGCFAFHDDBDEGBGHHEEDAFGFHEHAAADBCHCGFEEEHEHEFEFDFHF,False +418,7.0,7.0,9.0,13.0,10.0,16.0,6.0,11.0,HEFFFEDECCHHBHFDFACACEDHDBDBDBDFCFDEDEBHGEFFAFADAFHGBGCGCFDEAHDFDHGHFHCGEFEFABC,False +419,6.0,2.0,4.0,3.0,3.0,0.0,2.0,0.0,EEBDBAAAACACEGGCCDAD,True +420,20.0,21.0,13.0,17.0,21.0,27.0,25.0,13.0,HAGAGAECCFDBEADDGAGFFDCBFFCABGBEBAGCGBFBGEGEFDCDEBFBEDCAHBHBDFDFBADGFFEGEGEFEFEFHFBBABAHHDGDGBGAGFGFGEEDEDAFAGDHEACACFFGFGFGEDECBFBFHHHGEAFAEAHFBEBGBCHCHGADC,False +421,9.0,14.0,14.0,8.0,6.0,14.0,12.0,12.0,FHFDFDBBBGBEBCBFDGDHFGABCGABBGEAFAHACACHDDFHCBBFHFHFGCHCHGBBHHGCGCACACHCEFEFADDFEFEGGCGCB,False +422,2.0,4.0,4.0,2.0,2.0,3.0,4.0,6.0,HFCFCECBGGGDGBEHFBAHAHBHDHC,False +423,19.0,10.0,8.0,8.0,6.0,9.0,8.0,8.0,DEABABCFEFDAAABFHFAFAFADACCGBABAGHBABABAGHEHCGDGDCDCGEHEGDAABAEHBAGACDFFCFHH,False +424,22.0,16.0,21.0,30.0,13.0,19.0,17.0,12.0,BCBEBDAEAEAHAHGHCBCAAEADGFGDGDCACFCDEGCDHBCADDDDDEABADADADAEGBGBHCGFAFDCDBDFACDBDBCFEHEHAHGFGFGFGECHFHCCGDGACDFDECFDADEBHFFDFDFBFBEHAGCGDFCBGDACBCFDAD,False +425,12.0,15.0,7.0,11.0,10.0,19.0,9.0,9.0,CADACAFHFDDCDBFBDBEBEDEHFABACFFHHGFDFDGDGHAHACCBEFDFGEGEADFFCEGBABAEHHBHBGBEBABGBEFFFFABGFFF,False +426,10.0,14.0,11.0,11.0,11.0,17.0,18.0,9.0,BFBAAEFEHCHGAFEBCFCGCGBGFHFCGGAFAFBFCFHBBFEFEFEBGCECBGBGCDFDBDBDGAGEFEGHGHAADEGCGHDBAEGDDDDCDFGFGABHH,False +427,37.0,20.0,35.0,16.0,24.0,26.0,23.0,17.0,AGAEEHGHGCCCGBGCHCHCHFGGAAAEAEAFHCHCGCACADEEECBABEFEHDFBFEEBBBCEFAFADACAFFCFDHDGBFFACDGDFDBBBCGCBAAAEAECGCDHFBDBCAAGACACAFAGGBEHECECEABFEGDFDHHAAAACHCHGHCHABEGCGFACCECFFBFBABAGFFDAECEDEFFACGCGAGCDFD,False +428,16.0,17.0,31.0,28.0,15.0,17.0,26.0,26.0,FGFCCACBEDEDBCGCGFDCAAECEAAFFGGGGHCHCAGDGDBHBHFHFHFHDHAGGDDADHDHBACGCGEDHBCDFDGDHDCCCBBBBGCCCCFBDDDBCCCHCFEHHGFBFCCAAGGDADGDHEHAGCGCBDBFBFEGAGEGHCFDHHHHEHEBEHDFDGDHAAECCCEDEDGH,False +429,8.0,4.0,6.0,7.0,12.0,5.0,7.0,6.0,AAHAGBFHFCEAEBECGFGFGEEECBCDCAEHEAEDEDHGHBCFDGEGDHDEDAA,False +430,5.0,7.0,8.0,4.0,4.0,3.0,11.0,4.0,HGDCHCBCBFGAGBGBEDHAEAEGFGCGEGAFCGCGDHDBBBCCGA,True +431,8.0,19.0,9.0,16.0,16.0,15.0,11.0,12.0,FABCEHHCGDGDFDFHFAEDGDFDFBBBBFEDEAGBEEEFEGEBEFDDGBBAAAFHFHEEDCDCGEDBDAEHEHBHBHBFGCDCHEDBFBGHGFBFBCBCGCBAHD,False +432,25.0,23.0,17.0,34.0,27.0,19.0,18.0,34.0,GBHHHFEGGFGFGHBABDBDBHGGEBBDEDHHHHAHFHEHFFFGBDDEAAAAADCDHACAFDBDCGCGDDDHAGBDHGHCHABAFEFEFEFDDBDBABGFAFEEDEDEAEBFDFDHAHABEBEDDDFHCEFEAAAECCBABHDADHCBFGDHEHAGBDHHEHEDEAECEDGCEEHDDGHCHCHEDDHBHCHCACBCG,False +433,11.0,10.0,8.0,8.0,5.0,5.0,7.0,5.0,GEEEBADHCHEBEACABDBDAHABABABCDCGCDABFDCACABGGAGHCHFFDDGFGFB,False +434,8.0,2.0,9.0,3.0,9.0,11.0,9.0,7.0,CECFFFHGHBHCFCFBFHDACEEFCGEDEDAAAGCGCEFFAAGGGHFHFHEGEGECAA,False +435,15.0,9.0,12.0,17.0,12.0,13.0,11.0,8.0,FEFHFAFEDEDBCGGFBHACGCFCHADADAFAEAEADHDBDFHEDEDBBGBDADAGAGEGECCHEAACBCDCEGFGFDADGHHFDFCCCBDGEFADB,False +436,9.0,4.0,4.0,2.0,2.0,7.0,7.0,7.0,HEFBABCEFAFABGGAAACFCFGHBHACGFGAGAGHHDHDHF,True +437,13.0,14.0,15.0,27.0,27.0,6.0,29.0,26.0,DDDEHABAHEHAHDCBGDHFCEGBBHBHADDEAGGEGDGDGCCDCDBDBHBHBAAHGGGGACECEGGGECCDGDGEGADADGFHEEDEGACAGHDDDFDFBEHCHGHFHEEEHEHEHEHEGEFDGDGHBCCEDHBCGDHEEBAGHGEGEGEDHBHCD,True +438,22.0,9.0,13.0,21.0,26.0,17.0,18.0,21.0,GAGEHFHCEGEDAFAHAHEDBDFDABAHEDGDBCAEGDDDGGGGAGEHHHGCCFHHBHBHBHAGECAGDGDGDGEHDFAGCEEFEHEAEAEFFCECFFFBDADFDADADAFEEEEAFAEEBABAHEFDGHEHFCDCDCECHCHFEAH,False +439,24.0,19.0,22.0,19.0,24.0,22.0,19.0,24.0,DCDCAAAAABAFGFDFDHGCGCGBDACCCCEHFACHEDAAEABAHABAEFHFCFCFBBHFHEHEGCGDHFECBBBGBEHEAEAHDGDGHCHFBFEFEBEDFAACDHDFBHADCCEHEHDBFGFHDHDGEGADADEDEBECHFGGAGEFCCBCGFBBAGEHFHGHEHEFECBGA,False +440,23.0,14.0,11.0,16.0,9.0,11.0,13.0,16.0,DCDGBGBAAHECEFGFGAGHHEDGBCFDFGHGEEFADAEGFBAAAABFBFDAACCCEDHHHDDAAEBHCHABCHAHAHABEDGFGBGDDDDDDGAAHACACACABFFHBHBHB,False +441,5.0,9.0,7.0,7.0,5.0,6.0,6.0,2.0,CFDBDGCADBDBDGAAEAEBFBCBFGHBEGDHDECECBCGFGFBFAC,False +442,21.0,17.0,17.0,31.0,26.0,21.0,12.0,20.0,AAAGDEAFCHCBEDDBDBDHCAAHBDBDADHFHFHFHFHFDFEADADHHCHDDCFBFACHDEEEDABADAFEFHCACFFFEFBBEHGDGEGFDDCDGEGECCCCCFCHDEEECGCFDEDGBBDBGGHBFAFEDADFDHEHDHAGDGDBAEEEBEDAHAEBEBEAE,False +443,22.0,20.0,27.0,22.0,26.0,31.0,22.0,17.0,EDEAHFDFEBGFEFHGAFAFEDEAHDFBEDACCCBCBAFADAHFCGHGHDCDCGGHBBGACADFEFEFBFBFBHBHAHAGGGEGAGACECECBAEFFDEECDFECECBCEHDFCABHBCGDHBFBFBFAEDCFFHFCFGFDEDEDGFGFGFBCHEGGCEDGCCHDGFGCCCACEDEAEABABADFDH,False +444,25.0,15.0,17.0,18.0,21.0,13.0,21.0,25.0,GCAFBBBBAFGHBACAFHCECHBEDEHHHEDAHABCGDEAAABDBHAHBEGGDGACDBGGGGHGHGCECEFHFCCGBEEEEEDFCGDGDADADCECBFFCAEAEADGDHAHAHEHDHAHEFEHDGFHFHBDDAHAGAGAGAGEFBHECFCACHDH,False +445,4.0,5.0,1.0,1.0,6.0,3.0,0.0,1.0,FEBBABEBEAFHFEAEAEBDC,True +446,3.0,5.0,3.0,4.0,0.0,2.0,5.0,1.0,DBDAGBGCGCGCBBBAGFDHDFA,True +447,27.0,17.0,19.0,29.0,21.0,26.0,19.0,16.0,AAEEEEFDFHEADAGFGFGAGHFABBBBDADAHFDGCHFDFAFGCCBFFHDHDADEBHGCAHAFCCGCHEEADCBFFDFAFACAEECDCDBHBDCCEDEAGABDBDGGGGHFHFHDEAFDCDAAABAGCGFDFEEEBGAGAHBGDGDFDFDHHACCDCEBEAECEFEFDFDBDB,False +448,12.0,3.0,7.0,7.0,6.0,6.0,10.0,15.0,GCACACAFHFHGHDHAHDDEDCFAHACAHGEFHBHBFGDEHEAAAGAGCDAEGEBHDGFGHHCHGH,False +449,27.0,20.0,31.0,20.0,16.0,31.0,25.0,16.0,CCFCACAHBDGCGCBCGCDCBBEBAGFFFCFCDCBHBEFDFDHGGDCFEDBDFDCDCFFDBAECHADBCHCHCAAAAFAFADDGFCECGCGDDEHGHFFEHGHGFGFGAEFBFEFDBHAFDGGCFAFHHHBHEAGAEAEABGHFAFACACBCACGBBAGACAFFGFGFDBCBCGEEEECFADGBGA,False +450,2.0,7.0,4.0,2.0,6.0,1.0,3.0,3.0,DGCGCBDBHCECHBEGEABFBHEAEBEB,True +451,8.0,7.0,6.0,1.0,2.0,4.0,4.0,3.0,FGFHEABCCCDBABAHCHEAGCGCBAAAABBBFGF,True +452,12.0,16.0,17.0,11.0,29.0,15.0,19.0,16.0,EGDGEGHCFCFDDBECFHFHGEBEBEBEBDBAHAHADCEEEEEEEBECCBBBGDCDCFGHHEACAGBGHFEGEAECFDEGFHCEDFDFDCBHEAEAEFBGCGBAHFHGGEEBFGFGEHAGAGAFCBHHHCCECEG,False +453,4.0,3.0,6.0,2.0,6.0,8.0,4.0,3.0,CCFCEEHCHBDEFAFAFHGDFEGEFBFBFCECGAGA,False +454,17.0,13.0,25.0,22.0,19.0,16.0,28.0,27.0,AGAHHCDEDGGGDHHFEEGEHHCGGHGABCDCDAAFCFCGAGCFFFHEEEHEBGBCFHDAEEBDCDCGCGCBHBFCFHDHGBGDHCHFHBHDHBEAFCCDEDAGCGCDCFFHGHGHGAGADACAEABFCECECEBEHAGAHHDGDGHGHGFDFDEBCHDDCDGBGEA,False +455,3.0,8.0,5.0,6.0,3.0,3.0,1.0,4.0,ADHHHDFFACBCBCHCBDDGDBDBEBEAEFCBB,True +456,17.0,25.0,25.0,21.0,21.0,26.0,24.0,21.0,GEGBFBFBFBGAHAFACDEDCCHFFGBGAACFCHGFCFGHDAEFEFGFGHEBEBDAFGFAFCCBABEHCGFEDEDGBGBFBEHEGGCDCDCBGHDCCCDFAGBHBDEDHCHCHEHCBCDDDDFBEEEEGGBFCFCHAHACGFBBHDHBABGBGDGDFAFAECECEFDFDBGCHBAAHHEH,False +457,12.0,10.0,8.0,8.0,4.0,11.0,8.0,8.0,DBDFDFCCCHBEGFBHEFACBDBGHGBFAFGHAHAHGDDDCCACGCEHGFGFBFBABABDHFAAAEAFA,False +458,20.0,11.0,18.0,22.0,26.0,28.0,20.0,28.0,BFGHCHEAEAFFFFGABCFGFECECECECHCHGHDHAHEEEFHAAFBCGHDHDHCABGHCFDGHGACFDDDBCGDDFGGGGEEABGFAFEHAFEHAFAEAEABAGFDFEEHEFECDADHDHBHEHDHCHFHDHFHGDDDDEDEFEFGDCHCECEFHFAGBFFEFCADGBGBHA,False +459,18.0,25.0,19.0,16.0,13.0,17.0,21.0,14.0,CACACDEDBCBHAAGHBHBCEDEDAGGHDFDEDCHFHECFBFACAHAGGGGGAGDFBABFFGFBHBHBGBHBACABHBGCGBGEFADCDCHAHDHDBACABBBGEGEFCFBGBEFDFABABFCEGECDCBCGDBEGFFCFDGE,False +460,21.0,19.0,19.0,30.0,29.0,19.0,23.0,32.0,FDEDECCDEEHFDFEFEFHAHDCGCGCFDDDCGAGAECDHBEBAHGCGEFEDHDHDGDBHBADCDCHHFECHBGBEHADBDHGHGHGHDHFBGAGHBFBAECGGFEFEFDGDCDAEGEBACHGGDDADFHAEABBGBABDFDFABEDAHBHAHAEDEAEHEHCFCHEHEHBHBHGGCACAHEEEEFDFCGDH,False +461,9.0,19.0,19.0,25.0,19.0,17.0,20.0,16.0,BEGCGDAEHEDBDCEHECACAEAEAFCEGHGHFHGHCEDDDHDEGGFEHEFDFGFDBDBDGDEDCFCFHECBDHACCBCBFGDGCHBHDDBGBGFCBCDDGDACFGGGGFGBEBEGHDBDFCFBFDFDBHHAHAEDFBCBEBEC,False +462,9.0,14.0,11.0,15.0,9.0,10.0,15.0,17.0,CHCHCGCBEBDHEHFBGDGDGDGDBDGEGCHHBDBDACFCHGFEAHFFDCGAGBFHEDEHHAHAEBHBHGAGBFBDBCFCBCBADAGEGHHEFDFDGDAH,False +463,15.0,16.0,16.0,16.0,13.0,12.0,15.0,14.0,EDEGEDHBHDHDACHCBCAHADGDGAEEHFGFGFAEGEDECGGAFAFDBCHCGCEBABABABDEACHCBABAFGEACFDBBCBEGEGCDCDADBDFHHHHHBDCDGBFFGFHCBCFG,False +464,20.0,13.0,10.0,7.0,14.0,12.0,14.0,15.0,HHHBDFFCHCGCGAGDFDGEBFBABAFAFHGHBAGEGEHBACFCEDBACCCABADAGBGAGEEAAFAFACGCFAHEHEDEBAGEHEHEGAGAEFHHHHABEBDBF,False +465,32.0,28.0,23.0,18.0,15.0,22.0,28.0,21.0,CAHHBFBGCACEGFGAAABABAGGCGCGEAAGCGEEDBDGDCDHDBBABAFABAEDBGCEDBDBAHABFHEDEDBFFGAGHHEGAGHEECDCFBHCGBDBDBFGFDFCFAAACACFGHGAGDCFGAGFFBHCHCEABHBFBFHFAFHFEFBABGBGBGHHHAHAGEFCCHBHCAGBCDCECADADAG,False +466,14.0,31.0,26.0,20.0,17.0,27.0,15.0,13.0,BBBBBCGFEFDFDFCCDCHHDAFADACCEAGGCGCACFFEGECEFECCACGEBAGDGHBABDBHBHFCBHFCFCAHDCDHBGFEEDEDFAFHHGBBFAFCCCFAFDFEBBABACHHBDBDBFBCCFFFFFFDBBBBBEBECEGEGDGDGEGCHEBCDFBBBDD,False +467,15.0,12.0,15.0,11.0,17.0,18.0,18.0,13.0,HAGECCBCFHEGGGGBGBDBGBAFACCFCFCBDFAAAAACEEEFECDFDCDCDHBGGGFGDABAGAFFEAEFHBEDEDEFBAHGCGCHFGFGFHHDHECEAEGFAFHHEHEBBGEHFDC,False +468,22.0,12.0,14.0,17.0,19.0,18.0,16.0,15.0,DADADADAHAGABAEHFGFGEGBHBGADHDGGACHEHCHGEFFBCGCAFGDGAEHEAAFCFGAHAHEDDFDCHFEFEDEBECABEFGBGAGCCECFCBBBBHAEBECCADEDHHHEDEDEDFFFFGDAAAFCF,False +469,18.0,26.0,29.0,20.0,29.0,19.0,16.0,15.0,CGCGCHCFCGHHCHCHCHCFAEAFFECEBFGDHDCECECHCFFDBDEDBGGEGAGEHBBCCACABEEEAEBEBACECGADBBHBDBEFEFEFCDDGCCBAHHFCBHBADAGFDBEFEFEAECBFFHABDBAEDECECEDBFBDBDBDACGEGEBADCDGBGDGACFEFBAEH,False +470,6.0,1.0,5.0,5.0,3.0,4.0,4.0,6.0,CBCAGGHDHDHDHFHFEECACADHCAFAFGEADG,False +471,8.0,12.0,3.0,4.0,7.0,8.0,8.0,2.0,GAAFBEGEFDAGEGEFEHGBCFFFFGBBBEBABABDBDBEBDHGCABACAGF,True +472,9.0,4.0,9.0,5.0,3.0,6.0,1.0,7.0,HACGCABHCEAFHBHDAAACFCBEDEDADAHFHFCFAFBCDCHC,True +473,2.0,1.0,5.0,2.0,7.0,3.0,2.0,10.0,CCHCDDGFHAEBEHHFACHHFHEHEHEHECEG,True +474,8.0,7.0,5.0,9.0,9.0,4.0,1.0,12.0,BCDHBCBADCDHHAHDHAHEDEDBHEEDHCHAFAHAHCEGDADEFEFEFABHBEB,True +475,11.0,5.0,2.0,1.0,3.0,2.0,5.0,4.0,AACDCFHAGAGAEBGBHBFEAGBGAAAHAHABE,True +476,25.0,30.0,25.0,21.0,26.0,22.0,25.0,24.0,HGHEDBDBCHEHEDEDEDEDCAHDCGCFDFGEGDGAGAGHGDGDCAAHABAFACBCBCEDEAEDEAGDFEBEBEHGHFHFCBBFGHGFEFBBBFHGBCFCEBABADHBCACGFHFACACDFABHEAEHHDGACHFBFBHBHBABGGDBABGFEFBHGHAHEBGBGCFBEBECGCACEFAGECACFDFEAECCBGHCDD,False +477,15.0,14.0,22.0,19.0,17.0,22.0,25.0,22.0,DFGGGFHHCHEHBGDEEBFBAAHGFGFGACCCGHFHBHCDEEFEFBFAFBFCGCEDEHEHEBFAFAFAFGCGCGDBCBFFCHCDDDEAEAGDEDECGDGABBHDHDFDFDGCGAHEHFHCHAACDDBHHACBGBGAGFFHCCGHHCCGDGDGCGEE,False +478,14.0,12.0,9.0,13.0,13.0,17.0,7.0,13.0,AFAFBFBDAAADFFBFBEHGFEFHAHFGDDFDHAHADABFBFHEHECCACGFBDBGAEHCDCHGHGEAECECEFECADFDBGBHBHEHDDFEFDBEAC,False +479,29.0,20.0,16.0,24.0,27.0,18.0,17.0,26.0,GEHHHAHEGBGCHCBCFGDGBFDHCCBCHFHAEFEGGDHDACEDDDCDFDFDHBAADHFHBEFEHCHCDFAFABAEGBHBABABAEHEAEAEDEAFHEDAGEBEFGCEDEFEDHBFFDFAHHDBDGDHEAEGCBDEDBAGAGAGAEAHACACAEAEBHAHGFGEBEADADBHBHFCC,False +480,11.0,14.0,7.0,9.0,18.0,15.0,6.0,9.0,FAFEGDGBBEFEDEFEFABAGEGEFFFBBCBEDABEGAAAFHFDEHHFBFDFAFCDCDEGHHCHBABCBEHEHEBEBEDEHABEFACDC,False +481,8.0,4.0,7.0,16.0,11.0,8.0,9.0,4.0,EEADADFDEAFBFGEGFGDGCHDDCDEBEGEGCFCHDAGCGDGAECFCEDDFDEABABADDDDEHFH,False +482,11.0,7.0,25.0,5.0,16.0,24.0,10.0,11.0,EAEAEACFCBCEFEGAGAGCCFFEFGBCFFHFCFAHACFCEEHCCFDFEEHBHFHAGFFEFEBDAGCGFAFEFEHECGCGCFCFHFHCCCBCDDBCCCCFDFHAECBHG,True +483,24.0,31.0,31.0,29.0,20.0,23.0,19.0,21.0,HAHEECBBBBGBECEFBFHHCHFHDBGBHEGEADAEAEBBFBCECFCACABHCHCEBFDFCFCFBFHHHEGCDCDCDHDCECGABADDDBAGAGAHEDEBBDGCBCFAFABAHCBCFHGHBDEDGBGEHCDCFCFCAHFBCDCDGDHABGFEBDBDBDGAFAGAFDDCEFABAFDDGAFEFDGCBABHCGDGDCDCAE,False +484,10.0,14.0,9.0,7.0,6.0,9.0,6.0,9.0,HCACBFBFCFCFHAHADACABDCHGHGCBFDHCBGBABFBDBFBEEHADADHBBEBADAGECEFHBGEGF,False +485,10.0,4.0,11.0,5.0,13.0,7.0,15.0,10.0,AEAEHCHCGCGCBEGEGFGBGAGFGEHAFGCHDECCAHADDFDFHFHEGEGACCBHDHAEGEGCGHBEEEGAFAC,False +486,10.0,4.0,4.0,3.0,10.0,7.0,9.0,8.0,HGHCFDHAFAECEFHFHEGECHDDACABAEEEGGAEAGAGAGAHFGFEHEFGBBB,True +487,5.0,6.0,9.0,7.0,10.0,8.0,5.0,12.0,FCFCFHFAFAFGEDCBEHHGGEHEHAGBHCHFEAEDEDBHADCBCDHDHDFBEBCCHCGEHE,False +488,11.0,11.0,11.0,8.0,15.0,8.0,13.0,12.0,CBABEBFHFGEGHCDCAGDGEABBCGGBBHEFBBABGBADEHCHCEAEAEGEFFFCGCEHDHDHECDCAFAGAGAGEHEGFDHCHEHED,False +489,22.0,25.0,26.0,26.0,18.0,25.0,28.0,23.0,BEBEBEBFFHDHDHCHDHCCGCFAGCHCHCDCGCABABAFCHEHBCBCDCGCEHAHAEGGABFDHEBECGCHCHFDADAHHEGFBHAHFDGDCCCHFFGGGGBFAFABGFEFAGGFGDBAHFEGEGEDBBEDDBHBDFDFGGCEFGFBFHGADADHCEGEGDGDFDBBCBCDGBADABAFCFAFADDDBCGAE,False +490,19.0,24.0,22.0,16.0,30.0,19.0,23.0,31.0,FGGAFEFECGHHEGEHEDEFEHAGFBFBFHAEAHAEAEACDEBBHCECACEGBBFBDBCHDHGCFEHHAHAHBEBECGGDGCHBHGFGBDFCGHGHDHBHBACACHBEAABDHEHDHFFBFHFHEBCDEDEDFDGEGAGADBCHFHABDBDCFAEAEBEBECGCGEHHCCBCHCEGEGHFCGEG,False +491,16.0,23.0,19.0,29.0,31.0,20.0,28.0,25.0,DHDBCECECAGFGBBEEEECEDEGHCDGGAFDFGFGCGCEHGHGEDFGCDFGFDDDCDEFEABDEDEBEBHBHBGGHBDBHAFABDGHCECGAEAEAGABHDHDHDHBBBGEHEFEDHBEEEGGCDEFGHGHAHAFCFGFEDCFEABHFHEBEBDHDHACBCFGAGFGHEHBGBCHFGDDADCDADFDECB,False +492,2.0,8.0,8.0,4.0,4.0,4.0,9.0,3.0,GEGFACBGAGECCHCHCBFDGHCCGCGBDBDBEBEFDFBGBG,True +493,21.0,13.0,20.0,26.0,11.0,13.0,10.0,15.0,AACGHHEEDBDBDCDCDBEBFBFEGDCEADDDFAFAEAHHHFAFADEDCHCBCAAGACDDDDDBCAGDCDBEHGHGFGABDHDHCCCCHADAEAEDHDAACAFAFBFEDGBHCCADHBGBDFCFCHCFG,False +494,4.0,3.0,5.0,3.0,3.0,7.0,4.0,3.0,AHFEBAHCHGFGFEFDADBFFCFCGCGCBEAD,False +495,0.0,4.0,1.0,1.0,4.0,0.0,2.0,1.0,BDEEBEGEGHBCB,True +496,6.0,16.0,13.0,12.0,12.0,13.0,12.0,10.0,DHFEEBAFCHCHCEFHABBCBCFGECECEGEBDCDCBBBBFAFEBEGGCGAGFHEDGBGEGCHEBDBHBHCGBHAGDFDFDFDFDHCADFDFGB,False +497,19.0,9.0,12.0,22.0,14.0,24.0,20.0,18.0,DEDAHEBAAGDBHHGABAGCHCDCACFCGCEEACBFAFAGEDDDHHHCHCGFGHBAGAFAHDDDDDGDFDFHFEEDEHFHEBFDFHBAGHGHFHFEDEDFDFDCGBFACAGAFHFEABGEGFGFGFECADAGGDGFFF,False +498,8.0,3.0,6.0,14.0,8.0,17.0,6.0,15.0,GFFDFEGGBEBHAEDGFAFEFDDDAFHCHCDCDGFHAHFHFGDHCEFHCHCFDHDHAFDFEFAFABAEHFHDHDEDH,True +499,0.0,6.0,1.0,2.0,2.0,3.0,3.0,4.0,EDECHDBGBGBHBHFGFBHBF,True +500,9.0,11.0,8.0,10.0,19.0,12.0,9.0,5.0,GCFDBACGFBFAAAAGBFAEGFGCGHEAGHDFFCEDEDEDEDECHBEGDDEAEFDFAFEBEHEHEDEBEBEBCBCBFFEGBCE,False +501,8.0,14.0,12.0,11.0,8.0,12.0,9.0,4.0,DBDBEBDBDFDAGCGFBCBCFFGCDCDEDBBBECECFBFECABDDAFAFAGEFBHAGAFCHCDCGHGHBFBEGEFCAG,False +502,5.0,5.0,5.0,5.0,9.0,6.0,4.0,8.0,FEFEBHHHAHABEBDDFDHDCAFFECEAHCBCEAEBHGHGCGFDEGE,False +503,12.0,12.0,13.0,25.0,16.0,10.0,18.0,21.0,GBGBDECCCFHHBACGDGDGDADCGCBBHDHDHDBDFDFDHEHGCEDEGEFAFHBEFFGCEHFFDDHDHGHGDAACAGBDHGHEDEDGAHCGDGDACEGAHAHDHEHEBEBCBFBEHEADDGDCAHE,False +504,10.0,15.0,9.0,13.0,14.0,7.0,8.0,9.0,CBEEFBBGBGBDBABADFBAAHEBEDEDGFCEBDBHAHBCBCBGGFDFCAGAFDGDHDHGEBEHFHECECEAHCDDEHEAEADCD,False +505,18.0,16.0,17.0,23.0,12.0,18.0,20.0,12.0,FGFABEFDHDHFHGDBDBGBGCACDDDHAHBHFFFBGCGEAEAGABHBGDGCECEDHFAGBDEAAHCEGHDEDEDFGHDDDDEFFAFGDGCFCFDFDACFCEAABGBABCBCFHGGBGEGAACCCCFCGBADADBD,False +506,22.0,16.0,25.0,22.0,25.0,11.0,27.0,18.0,AGCDCDHDBGCGAGDDCDGBGDCBCGFGHCECGHGAEFEDEAEGEFHGBCBCAAAAGGDGEHEAEDEDEBCBGFCFGDDEDECFDHDBEAEDEHGHCCCCABAFABCBAHCHGHCCDCEFAGEHAGAGHEBCHEGBHBHDHFEEEACACDEDEHGGGFBFBGDAAA,False +507,13.0,17.0,22.0,10.0,17.0,14.0,17.0,13.0,GGGCBBBEBHAEAGHDCGCDHFEAEABHCHGFGHGCCFFBCAAHEHEDCGCGCDADEHAHFDFAFCHCFCBDEEAEFHAHFCFABBDBDEGECEBGBGCGCDEEBEBFBEACBCGCGBGCFCF,False +508,17.0,21.0,24.0,12.0,17.0,20.0,19.0,17.0,ECHCHCHCGCFBGAGEBEBEBDCCFHFGCDFFHHBGBGDDDGFCFCGDGFAACACGFHDHGAAHAEBEGCCCFGFADADHBBBBABEBEBCGCHDHBGEHCACECEDDCFFAFEBACAEHEHBGBHEFAFBGHGFBCBEAEAGFFCF,False +509,4.0,0.0,5.0,5.0,1.0,0.0,3.0,4.0,GHDCDCDCDCAEHGCDHHAAAG,True +510,10.0,11.0,3.0,4.0,7.0,2.0,18.0,3.0,HAGGGGAFAGCGEGBGAEBGGEBEBDCEGDBDADEBEGAGAGBBBCGGBGAGHBHAFA,True +511,2.0,4.0,2.0,2.0,1.0,2.0,3.0,1.0,DEDFHGABBBBFAGCGC,False +512,2.0,4.0,2.0,1.0,1.0,1.0,0.0,1.0,HDBABCBCBFEA,True +513,4.0,5.0,8.0,7.0,6.0,8.0,11.0,4.0,GGHGHGDBCECECEGFHDABADEGGCGCECBFEGACFFFFBFCFHBAGGDDDD,False +514,20.0,26.0,19.0,15.0,24.0,22.0,24.0,21.0,FGFEFEFBHGHBEDHHHHEDCDEHEHCBFHGAFAFBFDCACAGGGGGGGHBBABFBFBCHGGBACGCGDFEEEEAEFFFFDECECFCBCBEAHCBADEDAGFDEDBBEBEHACAFAFABHEEDCFGHDAABEBEDGGHGHGDDFEFAHAHBGCGBGCCCABBHBAGCBHBE,False +515,22.0,23.0,26.0,33.0,16.0,30.0,25.0,23.0,GGGGCBEHCBCFEGGFADHDHCGDACCDBDGFCFHBHGAABFBAHAHDGDBDADACGCFDFGFDDHBGGGEBEBEFGFHBEFABEGCGCGHAHFHFHDBDBDCDCDCHFFFHFDFAGEGBABFEDBDCECBCDDHDBGECADEDEFFFFAFDFDECGHDFDFBCGFECHHAHAHGCBCDADAEAFCFCDHDABAHABC,False +516,17.0,13.0,13.0,12.0,15.0,20.0,10.0,20.0,FDFAGABHFHCEEAFCEGGBEBCBCBEBDHFACGHGCACACAHFHDBGFGDAEAEABFDEDHDFAFEBDHHHFHFHFHAHAHAEAFADCCFBBCEHFFFDGDGBEHHHHGCBEFEAEDFC,False +517,26.0,21.0,23.0,17.0,23.0,30.0,24.0,22.0,ABAEAEAEBGGGGGAECECEDFCEBAGHFHAEADCCGGGAGBEBEBEDCDFAFHFHGCCBHAFAFAFHFGBCDDFACGFGHDEEGEFEGBGFGADFCFCFCBAEABCDHHHCHFHFHBHAEFFFCFBECCCFFDFDBCHCADAFHBABDFDBBAHGGEAEHCGEGCDAGAHDGDFHFHFEBABEBH,False +518,7.0,13.0,9.0,12.0,7.0,6.0,7.0,5.0,CGCECBHDEBGBAFCDBDBDACEBDDGDGEGEFAFAFAHCFEHEDBCBDBDCDBBBDCHFBAGAGH,False +519,15.0,23.0,14.0,11.0,17.0,17.0,14.0,16.0,AFGEDCHBBBBBBGGECEFFBACACBCGCBHFAAABCCEEDDDHBBFBFBGEHEFDAEAFFFEHAGABAFHFBDBHHHBEBEACGCGCACDCHEEBEGGDGHGHGDDDCBGAEBEFEFAFHHHFHFB,False +520,18.0,12.0,17.0,12.0,18.0,12.0,16.0,36.0,EGEHCHDHDGDGCADAHAHFCEEBACEEEADAHHBCBEHEHEBAHCEEGCFEFAFABHBHGHDCGCGDHDHFHDHDHAHCHABCGCFBHHAHFHFHFCEHEAAHHBHGEAHHBFCCGBGFHAEAEGCHBHGDGDGAGFHHC,False +521,4.0,11.0,9.0,6.0,9.0,15.0,6.0,12.0,FFFCCHBHCFCBCBFDDGDGBFAGCFEFCHCGFBBBHCHDEDEAEBHBHGAEAFFBEGEHEHEHBHFFFFHD,False +522,17.0,10.0,12.0,14.0,22.0,13.0,17.0,18.0,EEEEDEABAGFEFEHGHBDAAABDBDAEHHAHGHGHDHAEABHHHHHBCGCFCFCDBAGACEEGCGAADGDHAFCFCEBEFDFEEACGHBEFEFEFEDCGFGHGEGDBAEGEDCHAHGDFDGC,False +523,0.0,4.0,3.0,2.0,1.0,0.0,4.0,2.0,DDEBCHCGBGCGBGBH,True +524,25.0,20.0,21.0,11.0,21.0,16.0,21.0,28.0,FGHGHEHEHBHFHFBFBDBEGDCHCGAEAFCDEAAACHEHEHBFFFFAAHCGGHGBGBHCHCDCGAGAGBHHHFDCDAEABBBCECBGGFACHCECEAFAGHFAEHGGEDEDEBHHACCCACBCHDGDGAAABAGFEBHAGBGCFEEDEAEAFBECHHAHBHB,False +525,5.0,5.0,3.0,6.0,5.0,16.0,3.0,8.0,DHFHFEFEADAGEGECBDFCBDDFHCHFAAAFEHHFBBBGDFFFFFFFHFH,True +526,1.0,0.0,1.0,1.0,2.0,0.0,4.0,6.0,HGHCHEHEGGHGDAH,True +527,14.0,26.0,15.0,11.0,16.0,18.0,25.0,17.0,BHFABADGFABCDGGECEBEFEDBDHGFCFDBDBCEFBFHAGBFEFGFHFHCHBHEHFHFHCHCEDBDBEGHGHGCBCBGDEEFCFBGBGBGBCBDBGAEAGBGAGECEAFGGGHGCCAFGGEAEDBHAGABAFAGHHCBBB,False +528,26.0,33.0,22.0,21.0,21.0,26.0,21.0,23.0,HDBFBDGDGHHEBFFCECFBABGGEBEGGAHEHABGBCCCABDFEFGFADACCGABDBFBADADBDAHAHBEGHFHBEGEBCBCBHAHABADCHBGCDEDEDHGGGGGCDBFFFFFAEECHCHCFEBEAADFBFBABDBGEEHEGEFCFCFEAEADCGFADHHFBDBAHAHACABABFBFCFHBHBHCDFGCD,False +529,19.0,28.0,16.0,26.0,16.0,17.0,19.0,17.0,ABADGCGBHDFFFGFGDGFBDGGFAFCGGFHHAAFFFEAAHAHCBCBABADDFFFABDBDBHGDACHCHGBBBBBGEDADAGCBEBHHEDBCBCBDEEGADABABADADCCBCBDFDFCBCHFEEEDEHHHGHBHDEECHGDGDBEEEDEDGDGCBBD,False +530,10.0,4.0,8.0,6.0,5.0,11.0,7.0,6.0,FFBFCDCGAGFEDCDBEGEGFCFCFCBAFDBHAHAHAGACAHAHEGDFCFADEGAFH,False +531,13.0,7.0,11.0,9.0,7.0,13.0,13.0,17.0,GCABEBFBAHHHGHGAAHCHBEBCDAFHFHBCDCDCDFGEGCHAHEHCHDFFFGFGCGAAAHGGGHFCECHHHGAAEADFBFDFDEDAGF,False +532,6.0,4.0,4.0,4.0,4.0,11.0,3.0,7.0,ABCDHFHFECEDADFGHAFCFCFBFBGADEHGBFHEHFHFAFA,False +533,14.0,30.0,24.0,27.0,22.0,23.0,21.0,29.0,CEBEDGCHDGAAABHEHGCGBFBEGDDDCDCHHDEGFHCEFBGBCCFBAEAGABEDFDCDCDHDHGFGHGCGDDFBBBBBDFDADCDGBFEFDBCFCFBDHDGFACAGFDFDEAECFBBHBHCACAHFDEHEHBDBGBHBFBEDCFEEHBHBCBCBHEFEFCHCHEAFHBHBHEHFGCAEGHGHGHGHED,False +534,7.0,14.0,11.0,10.0,12.0,6.0,11.0,7.0,ABADCBEGAGABDBHCECDBEHGCBCBCGCFCFHFHFBBCBGEGHGDGEGEDDDCDEDABAHCFEEAEFEBBGDEHBG,False +535,1.0,8.0,7.0,5.0,5.0,7.0,1.0,7.0,BHBGFHEDDFCBBBBHHHFEFHFCFCACBDBDEHEFECCCD,True +536,5.0,4.0,11.0,11.0,13.0,6.0,6.0,8.0,CDDDEBHHGHDFGCCACEDEDECEGEACACHEBFFEFEFGFGDGDHAEEEABCBHEDCDCHHDC,True +537,28.0,21.0,11.0,18.0,13.0,11.0,21.0,19.0,HGAGAGFDDHGEBDCGAAHGHEDBDFDEGAGHDECCAAAADDGBBCBHBHBHGCGCBBBFBFGABAGCHBGAFHFAACAGDFEFEGGBFHAADADFDADBBBDAEAFHGHEHEHAHAHAHAGEGDCDCHBABABECDGAEBE,False +538,3.0,5.0,4.0,4.0,5.0,2.0,1.0,6.0,HCHGHAFBEBEAEACDCHBEBFCEHBHDDD,False +539,6.0,6.0,7.0,4.0,9.0,4.0,6.0,1.0,CCAGDGDGEFBCACBCGDDBFEFCFEABABCEEEABAEGEGEH,False +540,4.0,1.0,2.0,4.0,0.0,6.0,5.0,0.0,FDDGAGFGCGAGAFFFBCDADF,True +541,9.0,14.0,13.0,6.0,8.0,6.0,10.0,5.0,CBCGEGEFEHAGEDBGEGAGHDCBCGAGAGHDFGAACBBDBDFFCFHFDACACBBEBECCCCHEACBBBBB,False +542,16.0,16.0,8.0,16.0,13.0,11.0,10.0,17.0,EAHAGFDCGCGDEHCHBAAADHDHEHEFBGBABFDAAADBDADADHDGEGCGHGBFAFEBBBBHFDFDEBEFAHEBDGFHCHCHGDFABABDHHHAEBEHEDEBCCF,False +543,21.0,26.0,17.0,27.0,29.0,23.0,26.0,18.0,GDEHHBFFAHDHDCBHBGEDBDGAGDHCEEEBFFACBBEDGFCFBEBECAFDDHBHDEFEFEFEGGCGBHFFCFEHBHEFBHBADAEAGAFBFGEGEGCGDEDEGCGCBDFDFDADABCFEBBBDBGGGFGCDCDCACFEDBGEGEGHABGEGEAAAACCHEBEDEHBABFGFHHEHADGDADADAD,False +544,22.0,22.0,21.0,19.0,23.0,23.0,21.0,20.0,CGDGDBCFDADCCGDBDHAHCHCEDFFGGGECECEAFAHCFDDEDAGCGCBDEDEAEHCHCEEECEFBFHDHGHGEGCHFEAEAEFFCFEDEABHHHGFBAGAGBDEGECECECHBHAHGBBFBGBDFDGAAFAFGBBCBGBFHEHCBDFFFHFBAAHBFBAAAFAGABDB,False +545,23.0,25.0,25.0,15.0,25.0,17.0,21.0,33.0,GAGAGEEHHHFHFHFHEHDCFHABBHBHBEBHFGBCCACACACGHBADHBECECEBABECCHCFEGHDCEBGGEBEBEFHHADCDCDFDHBHCAEEHEHFHGHGHFADCGFHCACACACBCEGDFHCABGDGEGFCDHGHAAAHBHBHBEBHBHAGABEEGEDEGFBFCGEDAGADDBBEAFCF,False +546,3.0,2.0,2.0,4.0,0.0,4.0,0.0,0.0,ADADAFCFDBBFCFD,True +547,13.0,21.0,3.0,11.0,13.0,5.0,12.0,11.0,GHBADHBHBGBEHDHEEFGHDHGFEDDDEGEAEDFAAGBBCBAGAGAEDEHBHBABABAGADBEBECEAEBBBBGBHBDFGCADBFBHG,False +548,25.0,24.0,22.0,17.0,28.0,18.0,39.0,21.0,CDCABDBHBGBGBGBCECBABGBGAHAHBFEEAEBGAGEHFACACDEGEGECHAEGEHFHFABEGHFHAHGHCDCEBEGDBFAFHGEGBGAGDBDBDBEFECHFHEBFGEGEGECAFABEBGBGHGFGEGCCCCHGFACGBHAHAECFGAEDHGHGDDDEAFADGDGDCAEGGACFBFAGEGACCEHDCDGGFG,False +549,3.0,2.0,4.0,4.0,5.0,8.0,5.0,2.0,HFEFGDGFBFDFEEEFEFGBGCCACDCAGAHFD,False +550,1.0,3.0,4.0,3.0,7.0,2.0,2.0,6.0,ECEBHBHGHBECEFDHAHECEDEDGCHF,True +551,16.0,22.0,21.0,26.0,28.0,20.0,19.0,21.0,EGEDEBEAEADDDCFCABGEFFHDBECHBBBBAHAFFCCDDDDDDHGHEFAAAAAGGBGFGBGCCHEHFBFHHDCDFFBFDGEGFCABBEBEBECDGFEECACDDBCFEDEHHDBDFHFHCHCEGGGEGEADCDCEGEFFHHGCCBCBDBEBEAEAEAGDFHCDGDHBHEHEH,False +552,4.0,5.0,6.0,11.0,3.0,11.0,11.0,5.0,GCCDFHFBDDEDECGCGDGHABDDGGGDHAHAFGFGEGFGFABDFHFCFDBDBFFC,True +553,5.0,13.0,12.0,7.0,6.0,1.0,8.0,8.0,BGDACECGDGCCCBCHCGCDBHHGBEAEAEFBCBEBDGCGDGCBABABEDCHHHHHBBDB,True +554,21.0,23.0,19.0,23.0,24.0,21.0,32.0,21.0,FAGAHAHFHGHBEEFGADABCBGBGFAHEDEFGFBHCECEHEHDGDEAAHGGGEGFFDFBCHGAGHCDGGGABDGDADHFEBHBHGGCACBCBCBGBCFADADGDEDACBGHEFDFHFHFBDDDDBHBGGGCDEFEGEGECHCBCBEBEBEFFAGBBFACECECDAEFECGAGEFDGGAADHDH,False +555,11.0,14.0,17.0,9.0,22.0,14.0,9.0,22.0,CGEEDCDADADBDBFFFHCAAEHHHEHEHAHEFFCFBGHHHFHCHDHEBGFGFBEECFCEEECGCGHEEEEADHBHAABCCACFCEDHCHCHBHBDBECGCEFFGFABBEBEGHAHBE,False +556,4.0,3.0,4.0,4.0,4.0,1.0,0.0,1.0,BABHECAAFBDCDEDEDECAC,True +557,11.0,15.0,15.0,16.0,14.0,18.0,14.0,14.0,BCBCBGDGCGEAHHEHGAFFCFHFCGAGACEBEBEBAFGCCDGBCEFDFDAEADDFDCEBFBFBEHDHEHEGEGBGHFHDDDDCCBGBCBHAHDEFFFGGCHBEAAAHFFDFDFDHC,False +558,5.0,2.0,3.0,3.0,1.0,2.0,3.0,2.0,DGDGACBFHFHAEACABACDG,False +559,29.0,26.0,17.0,17.0,20.0,26.0,24.0,23.0,DADCDFFHFAFACAFBDBACAGABFGFBHCHCFFEFEFGHGCBCAEGGGDBDBABFHFAEADDDEDEHAAGGDBHGFFFFCGAHBBGBGECEGEGEGEBEDCFFDFCCEAAFDHAEBFBFAHAGFHCCGBGBGBGAGABEDADHEBEHHAEFHAHABCBCHAEAFAEBHGHBBBAGDHHHHC,False +560,7.0,9.0,14.0,11.0,8.0,12.0,13.0,5.0,FCDCEFEFGHDAABACGCGCGDEBAHHBCCFCFGEGDBDBDBAFECDFDFEGGCAFABCFGFGEGHCDEDGDGFCBCBH,False +561,16.0,32.0,21.0,19.0,21.0,20.0,22.0,22.0,AFBGBGHGEDFAACDCDCEFEBCFCGHGHFDABABAHCCEAHBEDEDBDCCHGHEBEBEBCDEFGDGFBFEDHDHDBBBFFEGBGHEDGDFBGBACDGEBEBHBHCCGHGHGDGDGHGHBCAFHGHGFABAFAHAFCBCBFAHDHBBCBGFEBABCBCFCFEEBCFEDEAHBE,False +562,18.0,21.0,6.0,6.0,14.0,3.0,15.0,20.0,DGAAHCHBAFHBHBGCAEAEAHAEAHHHBCBGGEBDFAHAEAEBGAGAHDEGHAHBEAEGHGHBABHBHEDCGHGBEDGBGEGBGBABDBAEEHFHBCBCBHB,True +563,19.0,18.0,15.0,19.0,14.0,16.0,17.0,24.0,FAFAFABBHDCDCDFDCAABFCEDBBECDCDFFAGADBCHGGFHDHGHEECEGDADABEHHHHCHDHDFAHGFGFBDBCBFHAGABDBGBFDGGFCFCBHBHFHEHEHEGAGAHAGABAGABEECDCHHEBEDEHAGCGHDH,False +564,3.0,3.0,2.0,1.0,0.0,0.0,0.0,2.0,BABCBDAHCHA,True +565,8.0,12.0,12.0,9.0,13.0,13.0,12.0,17.0,BFBFEEHBFAFGGGCHDHDHGCDCGEHAHEEBBAEFGCGCHCFCFDBBBHCEBEHEHFGAGFFHFHABDGDFDFBHAHDHEAABCEGEGEDCHCHC,False +566,24.0,19.0,7.0,22.0,15.0,14.0,18.0,21.0,AEADAHECBGBFHGHDHAGDGHGBGBHFHBDDDHGHDHDADHDHAHDEDADGFEFGFBDBDFAAAAABEFDHHHEGBGAAEDEGEGAFAFHHBEEHCGBEADAEFFBFDFDBDBGBHAGBCBEFDHGCACBCBAAACAGE,False +567,18.0,34.0,25.0,23.0,26.0,29.0,16.0,24.0,CHFDFHBCBDBFBHEEAEABABCGAFDFDADADADBBBCBDBFCEEEFFAFDBDBGHDHBBBFFFDABFHGCABABABAHHHHDFBFEFHBCDCFCFBFEEGECFHEGEGBBDDHDEDHFHDHDFBAECCBHBEBHBCCCBDBEGHGCFCACEFAGEGEGCCFBFEHEHCGFECGFDAGFGHCCCEEEBEHAHDG,False +568,10.0,3.0,8.0,11.0,10.0,4.0,2.0,8.0,EGEDEHEHCDCEAEAEAFFEHCDDDCACHBHBDDDHAAACAEBFAGAHDCCFEDHD,True +569,16.0,11.0,9.0,12.0,15.0,17.0,17.0,12.0,EAEDEACHEAGBHHFFAGGDADADHBHAFFGDEDEHFBFCGBGFFDGHAEAFBCBEAECDADCGCGFGEGEGAGDEDBFFAFAFCBHAEAEGEGFGFDCHCGFBHBHBH,False +570,5.0,3.0,10.0,3.0,5.0,7.0,4.0,6.0,DADCHHGACACECHCFCFHDEGABAFFFFECECFGGHBCBCEH,False +571,19.0,19.0,10.0,25.0,20.0,11.0,12.0,21.0,EGEGEDDDADCBFBFCHCHGAGDHDHDADGHEDDDDHBHBHCADEEEDDHDBCEAABABFEEAEGHGHFEADDDCABHBHBHFHFEEEEFDCEEGCBCHGAEAGABFBHAHEHAFABHBFDDDBDBHAAFBBAGGCD,False +572,9.0,14.0,14.0,11.0,15.0,15.0,19.0,10.0,EFEAEGGGDGDADFHFGFBFBFGDGBBEBEADHGCBCBCGCECGFDCBCBFDFGEDBDHCAFEFEBGCHAFGFGEEHBGCGCEEEBHCHBADCCGGHAHADAGFHFE,False +573,4.0,10.0,13.0,15.0,11.0,8.0,6.0,4.0,AFCCGEEDEBEBAHAHADFBCBCBEFDGHBEGEFFBFDDBCECDCDCECEDDDDDGDCDCEBBGDHFCCGF,True +574,15.0,27.0,18.0,27.0,33.0,20.0,18.0,26.0,FACGCDEDBABABADHDBEFECGDFHHEBCBCGHHAEBHBHGDADGDGDEEEDEBCBDBEAFHFEDGDGDBCHEAADEDEAEDHCHAFDEDHDACHBHBHEHECFBABHDEEEFEGBGDDHGFBFBFCFCEBEBFFCECEGEFEDGDCBGEGHFCECEBGBHBHDHCEFFFBGBHHHEFAAHDG,False +575,16.0,17.0,13.0,14.0,16.0,19.0,22.0,14.0,HBCFCFDFEGAGAHHGEGBGDGFHEHAFBDBDCHCHGFDEDEFHFBEBHBHBEBHBDFDEDEHEGEFFACACGFHADGFADGBAEADAFBCHEFFBEBGBGBACGGFGFAABGGDGFCCACAEAECDGGGC,False +576,21.0,18.0,24.0,12.0,15.0,14.0,8.0,14.0,CDCDFBACHGHECECEDECECHHAHBGFAAHAGFEBCHAGBBBABCBADCFEGABABCGCFAFEBHAHDHECACHHFCBBBEBECFCFAFAHAFCGDFDFDBEBDCACACADBDEHEFEDGCACAC,False +577,11.0,6.0,10.0,4.0,4.0,6.0,15.0,11.0,HHGHAHGDGCEBABABGCHCGCECHCACHDFBABFHFCAHAHFFBFGGGGGGGACAGECDGAADEHG,True +578,13.0,11.0,13.0,13.0,10.0,10.0,11.0,13.0,HDHDFAHCHGEAAAACGBEEHHDEEEDADCDCACACDGDBDBCFEAGHCFCABFBFGCEFBHHHHGBGCGCGEEHAHFBFDDBDBCGDGAFAFB,False +579,16.0,20.0,17.0,10.0,16.0,13.0,17.0,18.0,HBHCDAHECCCCBHGEFCBCGFFAFACBDGDCHBHBCBEBEDGDFEHGHBHECCCEFAGAEHDGDGHBFAFAGAGBGBGBEECCAFAFDBBHFECBGHCHBHDHBHBAEEEAEHEAGAGFGFGDABA,False +580,19.0,23.0,27.0,23.0,24.0,28.0,24.0,26.0,FGFGCHDADGDHFFDCDABFFFFBCEAECEHADCDFDFABAHABDEDBAHCCCHBAAFAEGEGFGHDHGHBHGHDCFCFCADEFEHBAEEFGCDCGGGGGEHFGCGCFFHFHGHBCBDBDCCCGEBEHFBFCFEECFGHGHFHCAEBEBEGHGHFEFDCHCBCBGBDBEAAABCCEAFBHBHDHEEGABDDDED,False +581,14.0,16.0,19.0,20.0,20.0,20.0,13.0,20.0,ACAFBEAHDHEHBHCABBCHFHCEEGCHHFCDCBBEBHFABGDHFHFHBHBHBGDDDCFFHFBFGFECDCEAGAGACCCGCDCDEDEDADADFFFAFAGHCDAGHFEEGHCEEEHECECEGEFDFEEGDDDGDBBFBFBADH,False +582,13.0,15.0,13.0,20.0,21.0,19.0,19.0,16.0,EGGAGAHBFFEFEHECDCFCBGHFFGAGAGEGCGAGBFCFDDDEBEHEHCFBDDDDDDADAFAHHCFDEDBFFFFHAGCBDAFBHBEDGFGCBCBGEGEDCDCDCFHEHGHBDGEHABEGAGHFEDAHEEEEEBHB,False +583,6.0,13.0,10.0,9.0,17.0,8.0,10.0,9.0,FHFGBBBBABCCDHBEDHGFDEHCGCBEBEHCFCFBFBDBACFHGHGEEECECEDEDEHEDGCAEADFDGEAEGGGEBABEH,False +584,18.0,27.0,27.0,16.0,19.0,28.0,14.0,16.0,FHFCFAFHHBEBFBDCHBGEDBAFFCBHBCFGFGCGCEEEDEDBABGEFBGBAFAFHEGCGCDCDBHHCHAHAHGCECAHFHFDEGHBBCACABABFBFBFAFCDCDBABEBECFFGBECCCHCFAFDDDDFDBECEAEDBFCDCEFGFABABCCGEHCABGFEF,False +585,26.0,16.0,22.0,22.0,20.0,21.0,22.0,26.0,FHDHDHFCEBBDBAAAAGFGCBEDHDHGHAEAECDCBEBHCHAHGGFDAEFCFHHHEECCCDCDCDHAHABBECACADAHCDCDFBBEDAAGAFFHCEEEAFAFGFCECEFACAEAFFHEGFHCAGECFFGBGFGDBDBABAGGGGGHHHAHDDDHHHAHDGEGFGBGBFCEDGD,False +586,8.0,5.0,12.0,4.0,4.0,13.0,13.0,7.0,DFDCCCCCCFEBEBDFFAFGCGCBFDFBAAFHGHGCGAAHGFAFGFGCGAGBCHFHCGGHFHEAEG,True +587,4.0,3.0,2.0,3.0,2.0,5.0,3.0,1.0,BGGGDBDHDFCAEAFCFBFEFAA,False +588,7.0,14.0,10.0,16.0,16.0,9.0,9.0,13.0,BCDFHCGFGAEFFFDDBBHBFBHHGAEDDFDEHEGEGEHADFEEHEGEDEDEDEHHBHBDBHBDCDCDBBFBABACACEHECGHEBDGDCCCAG,False +589,41.0,28.0,27.0,20.0,22.0,14.0,25.0,23.0,EDEHHHEACAEAEGECBBHBHBEFAFEBAFHHGHAHACAGBDBEGCDEHAHADACACGEDCCCFBBBBBFAADACAGECDFHGDDBDCDCECDABAFCBEGEDFCGBGDHACABGHECBGGCDCGEFEAGCGDAAABABABDHGEAHBGAEHGBGBFCFCFEFBHGHBAAAAHABABADAGACACGCACHDHDHAFAGEG,False +590,25.0,17.0,16.0,9.0,20.0,24.0,14.0,17.0,HDFDEGEFBBECCBDBABFFAFDFCECBAGAEABGFHCACAFAFAFHEHEHECFCHEHEHECGBDBAFEBCFAFCFAGGCFCABHGABFFEGAHAGAGCHHEHFDFBEBCBEFAFAHAEFEAAHAHBHBGDGDGCEADAGEF,False +591,17.0,13.0,25.0,18.0,20.0,19.0,18.0,19.0,ADCFCHDBAEHEHEFEACAFAFDFEFECEGADHDHEBCCCCEHHGBDBDGCCFBGDDCGABAEAEDEAFAFCGCFHFEGAGDGFHCGCEHEAGCHCBDEDCFEDHCBEBFBAGEGAHCHCBCBAHACDBDCDCHFHEGFGFGDGHGFFH,False +592,4.0,14.0,3.0,5.0,17.0,15.0,9.0,5.0,HGFEEHBHFFEFHFEGBABFBGDFBBEFEDGDEDECEBEFEAEBBBBEBFAHAGFDFEFEBGCGFGBGFECE,True +593,13.0,8.0,10.0,11.0,8.0,10.0,5.0,8.0,EAEADADGFGCDDFBFHHGADABAFHHBAEABHHGBCFCFDFAFDHDCDCBFBCCCBCEEEAEAEFDAHACDG,False +594,16.0,13.0,15.0,7.0,3.0,9.0,20.0,22.0,BGBGCGHHHEHGAAFGCGBDFAFBHCHBDBCCCFDAHHBGBAAABHHHGHGBABABCCCCCDGHGHCHAHGEGDBFGFGCGAHAGFCHGGGAHAHCHFEDHDAAF,True +595,12.0,10.0,9.0,7.0,8.0,10.0,12.0,10.0,AEFDFGFGABHBHBACAHFFEECEFDFGBCAABBCDCGEBEBHHHHFBAEADGDGHGDGDCACGCACAEFHAHGGGBF,False +596,12.0,14.0,7.0,5.0,7.0,8.0,16.0,11.0,DBGBABFCGCGEGBGCHCABEEHGGGHGHFBEBABFBFBGGGGFDFCGABABAFAHHHHBEAAADDHCFEHAHBGACDGE,False +597,12.0,31.0,25.0,23.0,29.0,22.0,19.0,20.0,GBCAEDEGEDHCHGFBEGCCDCGAFBFAFEGBBDBDBDGGCEHEHFHDCDCDEDFHHBGBGCHABGCGCFHFDEBCDHDAABFBGBHDCDCEHEBFBFEFBFHEHEGEBBDBEBABCDGDBHBDFDFDACCEFBCBFHFGCEAEDFCCDCFGGEEEAEAFAFBHBEBCBCHEHCHGEEEBE,False +598,3.0,2.0,2.0,2.0,0.0,4.0,2.0,0.0,DADAGFCFCBGAFBF,True +599,18.0,18.0,17.0,19.0,19.0,25.0,24.0,26.0,EFEFADADEGEGBBHHABBHCCGAFDHDFEHHHHHHGAAADGHFHGGGGDEACHCHCFCGEGEFABEEGEHFCFDFEBGAHCHGFGFGFGFDDHEFCFEBDFEACAFHCHFBADGCGBADGDAFCHCHDDDFDFHCHBHEEEBEBGBABABABCBFFHFDGCGBGD,False +600,18.0,13.0,8.0,18.0,9.0,20.0,11.0,10.0,FAHEFAFAHDGGGGHCBEGABABFEFAAGAGAGAGAGBHBHCFFDHBHDEDEDABCFCEDEBEFADDBFFCFHFAAGDDDDDDFFFFHADFFFBBBCDADCCADHBE,False +601,28.0,16.0,18.0,22.0,25.0,31.0,31.0,28.0,DHDHCHCEGGGGGGHGHGABHGABAGDGEGBACHDHBGADFBHGAGFGDDADGEAEACHBBFFHFEGEFFAFAFGFEFAGADDFAFCFGHBFFEDBACABFHFCCCEEDFDCDAAHFHEHDDEDGHEFCAHFFBCGCGCACABAEAEHDHFHFHFCEDEDGAGAEEEEEFDAGGGHGHFHAGEBHBAEFCFBFCEHBHD,False +602,19.0,22.0,22.0,6.0,18.0,28.0,18.0,32.0,BEHEHCBFBFGAGFFFHEEGEFFGCHCHFABHHCCBFHFABBEBCACAEAFHFABHCHGBBAHEEEEAHAHBHECACAHEHEHCGBFFHFGAGCCBCBEFEGHDDGDHFHCDAHHHHDAFBFAFHFHGHGACCCACBHBGBGBCFGFHFHFGFGFAEBCGCBDEF,False +603,6.0,3.0,3.0,0.0,3.0,1.0,2.0,3.0,AAAAHHHEAEBFCEGAGCBCB,True +604,20.0,12.0,4.0,14.0,4.0,16.0,10.0,13.0,BHADGGGBAFFHAEDBAFGFCFHFHDHBHBGFFHADDEHFFBFGHAHAHABACADFFAAGADAGAGACADDEFEFDADAHBGBABDBDBDCHF,True +605,13.0,12.0,3.0,10.0,9.0,12.0,19.0,5.0,BFBFCDGDBDAGAFCHBBBDHGADCEAABAGFGFGEGEGDGFAFEGBGAGEFFGFGEDADBBGAGAGEFEBBHGHGEDDAFAH,True +606,25.0,22.0,15.0,23.0,20.0,14.0,29.0,17.0,ABABABGDEFEFEHBAAAFDDBDGDGAGEEBHFFCAHAGABACACHEGDGDFDHGGFFHFBEDECFGHCBAGDGCHBGBGCGFDADECEBEAEADAFEBEAEFCBCBCBHBABGBHAHAGAGDDEEEHBCEADGDGDHHFDGABDBDGGCGCADGGHHDHGGEGC,False +607,7.0,12.0,19.0,9.0,3.0,6.0,12.0,7.0,CHGGCADECECGBGCGCEHDAFACDBGGFABCBCBCBCBFBCGCBCBCBFHADACADHDCGGGDFCHGFCHDHDB,True +608,15.0,15.0,12.0,14.0,12.0,4.0,21.0,15.0,BGBEFEGDBCGCGHHEGCFAGEBFGHBCCEGAHACGBDBGBHAHGHGHEHEHACABADADAHACBGDAEHGHBDBDBEBAAAFCGCGDEDCDEDHDAGHGDGBGEGDC,False +609,11.0,19.0,6.0,5.0,9.0,14.0,11.0,10.0,BBBBGBFBFBABDHAHFBBAHEHFCAHGGDGDFCBCFCGAHBDBGBGFGHAHGBEEAFFFBFEFEACACEEGEAEDGFHAHBBBF,False +610,7.0,6.0,1.0,2.0,7.0,8.0,15.0,3.0,GGGGGDGFBAEAEBFHGHDFAGBEFEFGFGBHAGAGBCEAEGBGEGAFF,True +611,9.0,11.0,18.0,12.0,13.0,14.0,18.0,18.0,DABAEGBGEGEGEGFDHCGCHAHFHFCCCCHHGADFBGEHAHEHECFHEHEAGABDGEBCBFFFGDGBGACHHHDHCFCDCHHGDCHCBCDCGCBBDADGGGEDECBFFFFEF,False +612,1.0,6.0,5.0,8.0,3.0,4.0,3.0,4.0,BEBEBGBFBFDDCHBDFCHDGACHFHGDCDCDED,True +613,5.0,7.0,4.0,9.0,3.0,12.0,4.0,8.0,DEEHBFGFCHBHDHFAGDBDHDFCFEBHHHBFBABAGAGDFDCDFFFFCFDA,True +614,5.0,4.0,10.0,9.0,2.0,6.0,6.0,7.0,GCBCBCGGBFHHCFCHHDDDDCBGAEACACFDADCCAFHFHDHDEDGFG,False +615,20.0,20.0,21.0,19.0,32.0,21.0,14.0,26.0,FCCGGEHECEDEDBBECHCHCFGBEHECCCCCHCGCDCDEHAGCECEDDBEBABABEBEAAAAHAHEFAFHFEFBFBFAFGEEEAEHEBGHEHDBCBDAAEFFHCGFHHHGCEAGDBEHEFEGDFBFAHHDBCHFFBEGEGFHECEADADADBHFHAHDDFDFHEAEBDBDGH,False +616,4.0,1.0,4.0,5.0,3.0,3.0,4.0,3.0,AGAHCHBGDFDCHEDEDEFCFCDAGAG,False +617,14.0,17.0,16.0,17.0,18.0,16.0,11.0,15.0,EFEFHFABEBEGEAEBEAECBDHFEEGEGBGDHHHHHBHBHBHAFAHDBFHABDDFDHBGDECECEFEFGDABAFAFABDHFBFCGCGBEFCDCEADDDFACAHDCCGDDCBCGCFCABECGCD,False +618,29.0,30.0,26.0,14.0,18.0,25.0,13.0,17.0,HACCBHBFAFBFBFHFCBAAGAEBEFDDBDAAACACACEEDDAEFGBGFEFCABAGAGAGFGCHCAGFBBDFHAABFCFCFDHEHCFBFBHADBBBBHDDBCFABBEBFBADAEBCBHBHFHCBDDHCHGHCACAGAGDFCFEAEBECECECFCECECGHEBAFAEAGHBCF,False +619,31.0,22.0,24.0,19.0,30.0,25.0,19.0,29.0,CFHEHCGFFACEHBDEEGGACFCACAGAHAEAFDCGBACEFGAECCAGHBHBDBAEAGFBABAGACAHHHAHCHCDCDAGGGAHAEAEDGGCEHFHFHFDGBHBCEHEDEFEFEFEAADACHFBDBDBDBFBFAEHFHBHEHEGEDEDCCEBFBFCFCAHDBFEAEFEACAFADEBEHHDEGEAHBHCHDBGBCDHFGF,False +620,18.0,17.0,15.0,24.0,21.0,15.0,18.0,13.0,ECDGDBDGDGDEAEBEBCFGFGAGAGHCDEHEHBGGGFEAAFBBDFHCDCEEEEGAGAGEDFDHDHAFAFHEHDADADBDECACEDDBHFEGECADDCFHBCBCHCDDFDGBBBEAECEDEFABAHCHGDABFBFGFCBGA,False +621,0.0,2.0,1.0,1.0,4.0,1.0,0.0,1.0,FEEDEBEBHC,True +622,14.0,20.0,14.0,20.0,27.0,29.0,12.0,26.0,CDCACEHFHFHBHEFEDEBBFFFFBFECHHAHEHEDGDEEBFHFHAACEDECCCCEFEHAHBHDHFHFAFABEEEGEGEBDAHEEEEFHDDDGDEDABHBAFGFEHABFBABDBFFFHFCFHFBGCABBGBHFHFDDAHGFEFEDHCHDEBGGGBCDDDCGF,False +623,16.0,25.0,17.0,19.0,21.0,19.0,21.0,15.0,BFDFDFGBGDHBHEDCACFCEHEDEBCFDEDADBDACADDEGEGHAHBHFEBCCCAHEHEBEBAAAAGCFCFGFBEEEHBHEHGBDBDAGAEAGBDBGFEFGBCBCFGEGBGHDHGCCAADCDCBFBAGGFGEHDFBEBFBFDFCFHBGGGEB,False +624,23.0,27.0,21.0,27.0,12.0,19.0,33.0,26.0,DHAGAGFBFCCHHGGBCBFDFACGBGBGHCABACAHFHCDCDGFGFCFGFCAEGHGABABEDEDHFHFDFBGHGEGHAHBHCDAGAGAGBBAEAFGCACBFBDDHGHBHDGDGBGDAAAAEBBGBDBDCACFCHCBDBCCCBGFFHDHDHEGEDEHHDDDHBGBHDFFEBDDEEGGGGAGHCHDBAGD,False +625,17.0,22.0,27.0,7.0,24.0,19.0,26.0,18.0,GHECEGFGAGCBEEGBGHGBEBEAEFGFAFCFHGGGGEEECBFBDGGCGCEDGFBHBCBCBCAGABEGEAEABFFFBFBFHEGFGACAEFDBCBCAGAGAGFFCCBEHCCBCBDHCBEHCHCACEBFBCGDAHFCECEDACAEHHHHHDAFGHCHCEGEH,False +626,21.0,20.0,18.0,14.0,19.0,24.0,20.0,19.0,FGFGDBFGAAHHDABADDECCHFBGCEEHGHGHGAFHCHAHBCBFAFAFABBBABADDGEBBFCFCFCFCBCDCDHFAGGHGHGAGEHBFAFCHHEGEFBHDHAHAEDGAGAGEGCDEHECCCBBBAFFFEFDADBBEDEGCFBFCGAEEEEFEF,False +627,22.0,20.0,15.0,21.0,16.0,16.0,15.0,16.0,GBGEFDACFGFGHBHECCFAAAEEGBCHCBCFADHDHDBDBDFDADABAEDFBADACBCFCFEHGCEFEAEBHDHDFDEEBBHBGAGDGAEAEGGHAHDDDDFDGBBBAAAABDHGHFAFECCCECHBDBCBFEFGAGAHH,False +628,7.0,15.0,8.0,13.0,14.0,12.0,11.0,8.0,DEDBDHFHDCDCBBBCBDBFBFCGHGAGEFAFAEADBFBGBGHGDCFADBDFEFEDECEFHHCBEAGGGDEBECEABBGHGFDHEEFE,False +629,1.0,3.0,3.0,8.0,6.0,2.0,4.0,5.0,HEHDHDHDEFBGBGDDCDHBEDECGCEEFGAD,True +630,11.0,10.0,7.0,6.0,8.0,14.0,8.0,5.0,CAHAHABFCFCACFCAHAGDBCEGHFHEBDFAGAGABBBEBCFEFEFBFAFBDEDEGGDFDABFFEFGG,False +631,14.0,11.0,20.0,21.0,13.0,15.0,14.0,16.0,HCFAAHBFCFAFHFGDHFCFBBBEBEAEAEHEHGDDBHHHFHDCDEGECFHFDFDADACADHGEDADHDHDCDCGADDECEAGBBCECDGGCGCABAHFGCDCGFBHBDCDGAGCCCDCGEFEF,False +632,4.0,8.0,5.0,12.0,1.0,8.0,6.0,3.0,CAHAEDBCCFGDBDFFBFBHDDDDDADCGBGBCFAGDGFGFHDBDBF,True +633,3.0,4.0,7.0,2.0,2.0,6.0,5.0,5.0,CBCECACAFEFDAHBCGFGFBHCHDHCHGGFBFG,True +634,15.0,14.0,8.0,23.0,21.0,16.0,17.0,8.0,GDDDADADACBFGFGFAFACADAEEBEBFCGBFHFHGEDDDFCGABCBDHDHEEFHAHGEFDFEFBFAGAFEGDGDGBGDEDEBHBDCEEEEGEBCDDEAECDDDEGGGAFAEBFBGHEDAB,False +635,16.0,23.0,27.0,12.0,33.0,22.0,20.0,34.0,HEHACECAHFBGBEBHHHHFFCECEHEAEGDGDHAHBFFFFFFFGABCEFEBECECHABGCGFHEEEEEEGBCAHEHCHDFBGBCBCBHHGFBHDHCHEHEHCFCGCGEFHHHCDGDEDECBCAFEFAGHDCABHDAEACCHGHFBBHDEAGBGAFDDGCACEFEFEHEHEBEGCCEGBGBCAHBHB,False +636,18.0,21.0,19.0,22.0,14.0,15.0,21.0,26.0,GHABCDDDAGGFFEFDFHBACHDHDECGBFBFAAGECECDAFBHCDCEBGBAAAGHHEHEHEHEBAFDFCACECECEHHHCHDHAHAHCDBDGGGDHDBCCFCGHHHGDDDBEBFCFDGAFBFBDBDBGBGBABHHCHGHGDBEGAAHDCGAGBGF,False +637,7.0,11.0,15.0,9.0,7.0,9.0,10.0,13.0,DAFBFHGDGAGCDCDGHBCECFCGCDEDHDHBHBFBEGEHDADBBBBGFHHAECHGHGHBFCFAACCCFFHGACHCBCECE,False +638,23.0,18.0,27.0,21.0,18.0,14.0,17.0,30.0,DEDCHCBFEAEAEABAHGDGDADEBEHCFDGGCCCCDCBFGFCCHDHDHFBABDHEHAHFHCAFAEADHDHCHEDACCGCGCGCBAFHHHECDDDBGHHHCHBHAHECFBBGBDBFHAHGHCDGHGCGCBBBGBABFGCGAEEDFDAEHFHDHEEACAEFEACHCAAA,False +639,8.0,5.0,5.0,6.0,7.0,4.0,6.0,5.0,FGEBDBDBGHGDGCAHAHCDAGAFAFBEBEGEFDCHAEECEDACAH,False +640,25.0,30.0,19.0,18.0,18.0,25.0,21.0,28.0,DBGBFBFHFHCAFAFACGCHCHEHEGFGADHHFEAEGEGHGEAEBDADHBABDGGGGHBHDDGAEBDFCGCFFGACDHBHFHCHFAGHEDACAHBDDDAHHEBEBABACAGBDEDGHBHFHFCGCDFBFBFAHGCBDDCBAEAEFCABABACACEFHFBAEHEGBGBHBFFHBEBFBFBFHCBC,False +641,10.0,7.0,19.0,15.0,18.0,26.0,16.0,17.0,EBEBEADCFGFGAADCEFHCAEDEAEFBHEHDGDGDBHCGCFHFHCHFEFGFGCECFCGCEDAFEGDFCAEADCFEFHHHFDFGFGAGDGDFHHGACFBHDHCGFGFCHCHCHCDEECFFFFEBEBFD,False +642,17.0,19.0,31.0,20.0,20.0,27.0,31.0,22.0,EFGFHEBFAHAHFHGCFCFGFHFBFDHDAGAGBECCHCBGBFEABDEGEGFCBDDFEFADADBFEGEBBAEHEHAHAFGCGCGCBCBFGFCACHCECGCBCAGFHDBDCAFGCGCGCGCDDDCDGDGFBHGFFAHCFCFHECDGDBECCCDCEGEFBFEHHGAGCGDHAHGHEFDHAGBGBGHDECE,False +643,10.0,16.0,8.0,13.0,16.0,18.0,19.0,19.0,DBDFCEGABABHBFGAHEGFFDHCFCFBDHHACAFECHHHHGFGBEHEGEGEGFGBBDBFEFHFCEDECFAAGFGFEBAGHEHEHEGDBDFDFBEBDBDFDBGEHCAAGHGHGBGHGHD,False +644,23.0,23.0,24.0,17.0,10.0,17.0,18.0,14.0,BGGGGGEGBACCECHCHCACDBAEFEFHAHACFGGADDCDCDCDGHGCBHBAAFGFGFABBBBFBHGFAAADADCDEACDEACBHEEFCCHCHAFBCHGEGBFDFHEBBHBDBCHDBDBGFCFBDCGFGFACABBBAAAAAFDCDC,False +645,19.0,20.0,19.0,12.0,21.0,19.0,19.0,26.0,BCHEHEABABAHAHDHBEDEAEGECEBECAHDGCFEFCHHAHDHDHFBDACABGCEBHBCFHGCCCAEEDAACABBHGHGHFHBEBHDECEBDBCBFEFHHHGHGHGHFHFBDGEGACEFDFHFEFCGGGAEFDFGCGABFFCFCGBGAGFBAEA,False +646,24.0,19.0,25.0,16.0,26.0,22.0,27.0,28.0,DADGFHCDDBDHDHGGAEECHHHFCAGACFCFEDCCECEGFBFBCBGEHEACBCBGGHGAGFHCGCGEFEDAHAHFHEBBBHHAAEAECBGAAFBGBHBHAAFEEAECEGHGFCDCHHHHBDFGFGFGBEAFHFDAHAHCBCEHGHGFCDGDGCGEFABDBFBAAAHADEDEGCGHECEFEFECECG,False +647,19.0,19.0,11.0,23.0,12.0,13.0,15.0,22.0,FGFAADEGEAEADGDFHAHBHDGGGHDFBHBDDGDCDHBHBHEHECEDBDBEBHHDHEABCCGFAHGGEADAGFDAHEHDHDCDGDHHEHFFFGEGBDCACACDFDHBBBBDCGAAFAHABABACACFDFBBHB,False +648,14.0,18.0,21.0,17.0,4.0,13.0,14.0,14.0,HDCCBGAGBGFGFHCCACHCGCBCBEDEBCBDBHFCFCFGAGACBGFDFBHBADAGHCHBHFCACDFDBABAEGCHHDBDCFBECGCGBDAFFGHDBDBDADADACFDADCHHGH,False +649,18.0,10.0,20.0,21.0,15.0,23.0,20.0,19.0,CDCFFDAABAFGFDBHFHGADADAHGHGBDFCHHHCDCHAHADCDGDGDGCEFGFCECFCFCGCAAAAEAEDBDBFFHHHFECECGGEGAABHECFHDEDGHGAEADFFHGDGDGEEBDCFGEHFCGCECEDDFFFFBFBCBHHAG,False +650,2.0,8.0,12.0,4.0,7.0,2.0,3.0,2.0,BECADGCCCCCBCBCBDGGFECECDBDBHECEFABHBCEE,True +651,23.0,17.0,14.0,13.0,18.0,7.0,9.0,12.0,HGFCACACFCDEEAGBGBADADABCGDAEADGDBACFHBEDAABHBHGHCAAEBECECACEDECEGFGAAHABAEAHDHABABADEBCFCFBEEEHEBFBAEHEHDCDBGBHD,False +652,9.0,5.0,7.0,3.0,3.0,4.0,7.0,7.0,FHAHAGGGGHGCGCEHEAFAFCHDECHBABCFGBHBACDCDAABA,False +653,17.0,14.0,10.0,12.0,16.0,15.0,12.0,13.0,FFDCCCGHBHEFBAEAHDFFFHBBBBGAFABABAEADAEFCBDEEHFDACHCHDAFCFEDGBCBCBEBEGGGCHHDDAGAEAEDEDEBEHDHAHEFGFGFGHGAAEAFG,False +654,18.0,23.0,28.0,27.0,18.0,13.0,30.0,25.0,CGCBCACGBGHACACADFEBGBCAEHBDBCHAEDGDFDCCAEHDGDFDFAFBGBGEDCFBFBFDAHGCCCBGBHEHAHGGGCECEHEAGCGDGDHBBDGCECHAHDFDGEGAGDGEADHCACBGBCHAHAGBGHHCHCHGEBEAEDECHBGBGDGFGEGHCHBDDDCDHDFDHCFEHDBDBF,False +655,15.0,11.0,8.0,7.0,7.0,6.0,7.0,13.0,EFAFACBEEDCAHAHGEAEFFHBHBFBFHGAAHGHGAGDCBHHHABDBEBAGAGDDDADHBCBEACHCACACHB,False +656,23.0,17.0,14.0,15.0,23.0,23.0,21.0,14.0,DBBBEEGCGFABAGAHAHFDEEHECBHBFBEAEADGDACGFGFCFDFGFGFGBEBEDEHHCFEHAHAFAHEBABEDEFGFGBGAAECFCHCEAGDGDCBCAFHFDFDFCFEEEEECFDBGGGAAADBGBHDAGEEBHDAAAHFGCGFAFC,False +657,22.0,13.0,20.0,11.0,19.0,20.0,13.0,19.0,AAAEEECFGGCCCDBDAFHFAFCCBAAHBBBEBFBAGCGEGHCAEACDCEADBDEAFCDGECEGGAGABAHAEBHHHHHCFCFEHCHFHGHCHCFAFDFDFDHBEGEFFFFAEAECEDEDHFGABFEGCHCHAHABF,False +658,13.0,8.0,9.0,8.0,6.0,14.0,16.0,11.0,DFDAACADGHGFECCGBFFFHEAAFACAGFHCGCFAFDFBBHHFGAGABABAGEFEFGDEBFBDBGACHCHCHGDGHGHGEGDGH,False +659,24.0,22.0,11.0,20.0,12.0,19.0,20.0,10.0,ECECBBAAAFHDHDHCBGFGFACABAGGHADBEAFFDFDFDEGCGCBBBFAGABBEDGGAGFDAGHGDDAEABBGBHDGEBFBHDFGCBCBEBFDFDADADBBFEHEFEFDFHFEGDCDCDCGBGAAAAAGAFAHBGA,False +660,9.0,8.0,11.0,8.0,16.0,14.0,26.0,11.0,FEGEHCHBGBGEGHGHGEGHDEBHAFACGDGFGACHHGAFCGGFEHDFDEEGBGBGFGFGCCECFAFDFDHBGDAAHAGEGDGEGFGAGEBCCCCBEEGEFEF,False +661,21.0,16.0,26.0,12.0,16.0,24.0,13.0,16.0,AHBFGAHHBCBABABCCGBEFACECGHGFDAHHCCECFFFDFAHACACBCBGBDFEFEHEDACAEDEDEGEGDGBBBGCGAHACACEFAFDFAFBDACAFFHFCFCAGEGBFDFBFEGCFCBCFHACADDCHFHFCECEHHHCE,False +662,19.0,21.0,19.0,34.0,20.0,23.0,22.0,19.0,AFAFBGBGBABGDDADCFCECGGEAEACHDHDEFCFDFDECHHGDEDEGGFEBBBBBEFEDDFAHCBEDDBACDCDAHAHGHDCFCFDFEFEDHCHDDADBGCABDHEBBFBDCDHDEDEABDHEBFBCEAGGHFHEAGFGFGCGDGFGDGAGAGABFBFDDHDCDHHGHECDCFAF,False +663,30.0,32.0,21.0,26.0,25.0,15.0,23.0,18.0,GBDHGHGHGBGFGABAEEDBCBCAHAEEDFDADEGCCCGHDBBBEDHGGFCBBHEAACDBGAGBGFEAAAAAABADGGBGCDCFCFDFCBHAHBBBHBHGDBDEHBHBHBEAABABDDEAEDFDEBEBECEGEFAFCFCADEGCGBABABFBCEADAEGEGDCDGBFHAEAEFCDDHEHAHFDCDEDCAC,False +664,14.0,12.0,16.0,18.0,20.0,25.0,19.0,23.0,GFFDFGFDEAHBCEEHCFEEEABFGFGHGAGAGCGCFDBDBDEDEABABDBHFCFHDGAGEHEHEGDCDCFAAGAEEHFGFEDCHFHGGEHDDGBADDGHFHEHEHECFCFCDCAEFFFGFGCBHHCCFCFBFHFHEDADHHHHABB,False +665,1.0,1.0,5.0,0.0,2.0,0.0,2.0,0.0,CCCBGGAECEC,True +666,13.0,18.0,8.0,9.0,12.0,13.0,18.0,15.0,FADABCFAFAFGFGFBCBGGGFGDCDCABDHDAEHEDGDGEFFHCGEHHFHBGAGAHEGEGABFCGBGEEBEHFHBHBHBHBFBHCABBHGEEDCDBABABHGGAE,False +667,12.0,9.0,6.0,10.0,3.0,13.0,8.0,9.0,CBCHGHFADHGAGBCFDFAADDFCFHDAAAAAFCFEAAFADCDGDGHFHFHGBFBFBEBHGHGBBDFDEB,False +668,25.0,23.0,24.0,17.0,11.0,21.0,16.0,12.0,GDAFFFFHBBGCACGCECBHAEDBBFFFBCBCACACGBABEBEDDBFAHBHDAGAGBGBGAGBGAGEDBAFCCDCGAGHCDADACAEDFHACBEAACFDDBDBHBDBDFFFCFCFCFCAAAEDHFAFHCHCACHCGAGFFCEEBEBGDH,False +669,3.0,6.0,1.0,5.0,4.0,4.0,3.0,1.0,EABGBEBGBFBGDFDFDADEDBFHEAC,True +670,5.0,9.0,11.0,15.0,8.0,21.0,12.0,11.0,DFDCHCFFDHHAHACGGFBDBDCDCDAHEFFFHBDBDBEECFGDGHGBFCDADABHBHGGEGCCFFFFFDFHEBGCEFDFGFEFEHDGFGFC,False +671,9.0,14.0,11.0,13.0,12.0,14.0,11.0,23.0,HDHCHCFCFCHCFCDADADEHFHBAEGFGHCEDHFCCDEHAHFEBBBADCHHHHDHBHEDDDADHDBGBGBCBFHEBEFGBGHGFFHAHGHBAFAGBEFEBEHEGFG,False +672,3.0,4.0,0.0,0.0,2.0,6.0,4.0,2.0,HFHFAAGEGFGFABBFGFBEB,True +673,17.0,21.0,20.0,5.0,12.0,13.0,17.0,15.0,BCBDBECHCAAADCGGGGFBABABEBCBCACAGHBHDHBFEEEEAABCBCBAAHBGGCGBGHGFGAGFFCHGHGHBABFBFHCHADDFCCCECECHHEAFBFBCHHBCEGGCFAEAEGFF,False +674,14.0,34.0,17.0,24.0,19.0,23.0,30.0,24.0,BBGEGHHHEHEFABDCHCFBDAGBBBBDBFCFCFAHHEHAFGHGEGEDBDBDHCFCHCEDEDEDGCGCDDDGDGAGAGEGBHHCHADFDBBBCDDACGHGEGEHBGBGHFEFGFBBDBHBFBDGGCGCDFGCBBBDADGHFCFADGEHFCFAFGBHFHBGEAEBBBAFGGDGFEFBBHEHEBABF,False +675,22.0,22.0,20.0,24.0,22.0,17.0,36.0,34.0,CHGHGHAHAHCECDBGCADHEEGECDGBFCCHCHFGFGBBHFHFHEGFGAGCGCGDGDCBFBFEFEHEDECCHBGBDADHFHEBDBGFGBAHGHGEACGGAEAHGBDCDGDHFHBHCECBDHGGGGHBBDFDFHAAAAAHADADHGHEHAGFGDGAEDGDEEBHACFGHBHBHCGGGCAHEEAEHEFDDDGDBBBAE,False +676,5.0,3.0,7.0,7.0,6.0,1.0,5.0,6.0,EHCHEBAGEGDGDCCCCABHEGBAEDEDCDFDADAHHCHG,False +677,14.0,12.0,18.0,20.0,14.0,12.0,11.0,15.0,CCADHGFACAHGHDDDDDGFGHBADGBEBCCDDDADADABBHCFCFHBHGAGEEEEEEEGEFHCDFAFCCADBDCDCDCBBBBCHCBDAGAEHDHAHAEEHEHFFCGCDFGECFFH,False +678,20.0,18.0,16.0,16.0,18.0,22.0,18.0,25.0,DFFHFHFGFBADAGHCBCAGBCBFGFACBEFEGABBBEGHHFHFDFHEEGEBECFCEBEGGADEDEAEACHCHABEHAHAFAHAHAFBFAECECHCHGHAHBHCHFHGDCHGHEBDBDGCADEDGGFBFGDBDCFFEHDFDFDGDHCHBGAAA,False +679,13.0,13.0,11.0,11.0,12.0,13.0,13.0,10.0,DADAHACGEBDGEGEDEAACHFGEGEGFGFCFAFEBCBFEFHCCFCHCHEHAFFDBBBHGCEBGBGAAHFHGHBFDEGAGBBBBDDADADEDACFC,False +680,21.0,9.0,11.0,23.0,10.0,11.0,13.0,22.0,BHEFDAEAEGGAGBCHCBAAHAFDFGGGGBHADEDACFCFAEABHBHBAAADFFACDDDHDHCBCFHDHCHGDAHAHDDDCDADEHFFAFDEHHDHECDADAGAGBHHGHEHEHCDGDGD,False +681,29.0,26.0,19.0,24.0,29.0,20.0,27.0,23.0,AAHAECBCBAADACAFFGCEADCBGHGFEFEAEDEDBDHDEBHDHAACAHAEBCBDFFHFBFBFBFGFBEAHBCAEAGAGBEEEEEEEEDCABFGFBDHFAFAGBGHGCGEGDADHDFGBCBHBHACEBDADEDEDGGGGGGGBHBHDHCFGBBEHCCAHHFABDCGGECFBAHGDGDCEAEHECEGHDFDEDGAHA,False +682,12.0,18.0,15.0,23.0,25.0,24.0,20.0,8.0,DADHGFBFDADAEECECBFDHDBCBABAHFFFFEFEFBFBFBEDFDEAFCCHEBBGECCCCFAGBBDBGCEEDHGGEGEAEAEFDDDGDAFEGCGCGCFEDDGDFHEDGGGGGEBEDFDEDHBEBDCCEFFFEFEBABFGAGHGD,False +683,10.0,19.0,7.0,19.0,5.0,6.0,8.0,11.0,CHCGBDFEGADBBBBBEGHAFAHBGFACAGAHDBDBDADHDGDBDCCCEDDHDADADCDBBBHBFBDBDFDADEHHHBHGGEFBB,True +684,10.0,3.0,3.0,5.0,2.0,4.0,6.0,12.0,DBCHHBHEDEGAGAHFGGHFAAAGAGADBCHAHAFDFDACHHHHH,True +685,10.0,19.0,16.0,24.0,9.0,16.0,18.0,17.0,DGDFEBDHDADCDBDHFHFHAGCHCHAGEEBGBGBAFDHCBADCDHAHEEABDDFDFABBCDDADCDFDFBBGBGHECCGCGDECGDBFGGEGECHCGFFBFBDGFHBHBHBCGCGCGBDDDFHFHFHA,False +686,11.0,7.0,14.0,17.0,14.0,20.0,12.0,14.0,HDHABCEFFBEHCGCACACBHBGEGEFFFBGCECDCDEHEDEGFGFDDDDGDGAHDHDADADFFFAHAEDHFBADEDBCCGHAEEECFFEFCFHFGCGAHDFGFHFCFH,False +687,19.0,24.0,19.0,21.0,13.0,20.0,17.0,22.0,GBGCDCDHFCAHAHBFFDCAGBFBABCFFBFACBGHGHBFFGHDDADHFHFHBGGHGAFDFCGAGEDEGEADDFCBABFBABAHEDEGFGFCBCFDDADACECEBEBCHCACFEGCHBBBDDDGHHDHAHAFABDHEHEHEGEDBABCBDBHCHC,False +688,11.0,6.0,12.0,7.0,7.0,10.0,7.0,5.0,CCBGGGGFABECFADHEACFCFGFGEDFCFAFBHBCBHBDCCHCAAAAAEDDDDAFCFCEGEAEH,False +689,1.0,5.0,2.0,2.0,0.0,1.0,2.0,2.0,DHDGFGCBBBBBCHA,True +690,15.0,19.0,20.0,21.0,26.0,23.0,15.0,18.0,GBGBGEFEGECEDHDHDHDHDCGAEACGCFBFECCACGCDEDFDHDFBBBEBDHGHDCBAAAFBHADFBFHFHFHFEDDADEDEFCBBAEEGEACCHCEGACEDECECFFFFHAHEGEBABEDFBHEDEAEADFDCHFHFCGEBHCFFFGBBECGBG,False +691,16.0,20.0,16.0,13.0,21.0,17.0,19.0,17.0,EEBEDECEAEBBBBEHFBFBFDCDCBCBCAFGHGCECGGDHAHCDCFCEHDHDBBFHFGEECBGBFHDHGHEBEBEAEFBAAAAEAGGGFEFCFBABDFGFDFHAEEGHHHGDFHFGCGCGDAAACADEGBBCAHGEGH,False +692,15.0,18.0,25.0,15.0,20.0,16.0,23.0,15.0,DCAGACABGEGHGBBCAEGHHDAAAFGCBCBCGGDGCGCHCDCDAFCFGHGCGCEEEHBGGECACADEDFDFGFDBBFBCDCFCDCEEHEHFDBDBGEGFFBFBFEECHGHBAGABABEHEHGCEHBFDCCGDHEHEGBFAFAECEC,False +693,18.0,15.0,17.0,18.0,19.0,18.0,17.0,13.0,DAEAFACADHDHCFCBBBDFDEGEGEFDGBEFEBGHGHEHGGAFAFAGAEDEBHDADAEAEDEAHGHAHCECEHFHBGFAEAFBCGFDFGCACADFCGCBCBDAHFBCDEBCFCFGECDBDBGBGECECFDDHFG,False +694,7.0,11.0,9.0,10.0,9.0,4.0,5.0,10.0,CDDDBBCGFGDHDHEHBHEHEBEBEAEAFHDEGEDHBAAFHCBFEGCBCBCBAAHACCCGBHDDD,False +695,9.0,7.0,7.0,14.0,15.0,8.0,16.0,16.0,DFDCDCDEAHDDDBHHFHFCDCHCFBAEEDGAEAGGFGHAEECHGHGHEEGDGFEFEDEGBGEDDBHBHGEGFAHAEAHAHGBGHGHGDECB,False +696,24.0,23.0,24.0,22.0,20.0,19.0,26.0,26.0,ADGDAEBHCGCHCEADABGBGBFEEGFAFAFBFGDGDHHACDCHFACHCGGHGHDHCBGDHBACHBHGHGAAEBFAHGGDGHGFGDCDCGCDCAEGGGEEEEEHDFDAAAHADAFADEBBBHEHECACBEEEBABFCFCFCECFCHBHBAGABHHFHBHFCDEBCDGDFDFDCBFBCBEAGDGH,False +697,19.0,24.0,22.0,23.0,29.0,24.0,25.0,34.0,FCFEAEAHCGEDABFEFDHCHCGCGCFHABDGEGFGFGBHBCAEEHGBCBCBCGHDHFHABGHDHCCCAADDFDHDCDHFBEHEHEGFBBHHHADEEEBEBFACHHHHGHGABBBBEDCBBBEDEDFFFFFFHCHDAEFEGDGHFBDGEHHGFBDADECEDEDGFBFEGCGHHCHCHGHEFEAAGAGEGDGCAHAEAEBD,False +698,13.0,19.0,14.0,18.0,18.0,16.0,11.0,16.0,BDBFFDFDFGGHAHBHBHBHFGAGAHDHBEBDBHBFBFHCBEGEGEDCCCCBGHECDCACDBFCEDBDFDFDHDFEFHFHEHEFEBABDEHBCDDHAAADEBAGAEACGEAEFBCEGEDFCCAGE,False +699,20.0,17.0,18.0,13.0,20.0,22.0,16.0,23.0,ADHHHHFDFBFAGADBEFFFEFEGCFBDHCAEABAEAEBHFECCFDFHHHHHFHCHCHEHEAEBGHACABFCFGAGDFDFCBHGCFCBCHDEDHGHAFDFAGECECEFAGCDEGEHEAABCBGBGBGBABGEAHGEAFHFGCECADBDB,False +700,7.0,10.0,13.0,7.0,8.0,14.0,8.0,3.0,FAAEFBFCFBFBEDGHCCCCCEDEDFHECDBDGFGFADGBEFCFCGAAAHEDECACFBFBGGGFCFCBBB,False +701,16.0,27.0,21.0,29.0,23.0,22.0,14.0,18.0,ABAEADACBDBFAFDCGBDEDBBFBFADHHAABHDGABACDBDEAFCHCECHDDACAFDFDFEAEDHDFBFBFCEEBECDCDHABFBGEGFHFHGBDEDEDEDCDHDHFAGDGHGHGHBCBCBFHCEBEHCCDCBFBFBECFDGGGFCECEDHBGBCFEEDGBFBEHEDE,False +702,22.0,31.0,14.0,20.0,15.0,20.0,18.0,12.0,GHADBDAFCHAEBDBDBDFDEAAABADEDCAABBEGEGFGEGFDFBFBAEGBBCBCBEGDCDAHCHBADADGFBFBHBGBDCFGDGHCDCFCBEAGFGFHFEBECAFBFBHBHBFBEGEGEBEDAHABADABBGBCAAGDFBAGHCCFDFHF,False +703,21.0,26.0,13.0,16.0,14.0,14.0,14.0,17.0,CHABCBFGFAABAGAHAHAHACBDFHAHEHGCACDBEHDGBHCECEHFAACABHBABABECGBGAGEFCGDEFHBBFAFHFHAHEBEFEGBGBEBEDDDDDDDAHHCBCDDGEADABGBDBFGFBFBFBGEDCBB,False +704,1.0,0.0,1.0,1.0,3.0,1.0,3.0,0.0,DEECEGFGAG,True +705,7.0,6.0,9.0,6.0,4.0,3.0,8.0,5.0,AGABCBCEHFACGFHHCHEACADDDDGBGBGBCEFHBDEDACGCGCGA,False +706,6.0,5.0,9.0,7.0,4.0,10.0,8.0,4.0,BGHGEDCHCHCGCFFGDGDGCBCBAADFFAFEFGAGADFHBAFCBCEDEFCFD,False +707,10.0,10.0,4.0,9.0,12.0,8.0,9.0,7.0,EECFAEAHAHAEAEBEHFDFDAGCDHBHGGEGEGFDFDEBADDCHFDDBFGEGBGBEBEAHAGBFBABC,False +708,11.0,14.0,22.0,17.0,26.0,26.0,22.0,25.0,ADBFFHCHCHCDGFCFBHBHBAGACHDFEFHCBGECDDGEHEHDHEGEGEGECBHAECDHDCDEEFHFDFDABHGDEHEGDHDGFCCCHCHDHDHBAEEGEHEHGGGBBFEFEDEFHFCFAEHECGCAFFFCFBBCAFBCHEEGEGFFECGCGFGFGFAFAGB,False +709,20.0,25.0,16.0,17.0,13.0,14.0,18.0,22.0,CDEHBHBHAHBHBGDGEGBACAHAHGBGBGBAAAGFDEEBGBABABFGACACHGHDFDADHEFDHHECFDACABGHFHDDDAEAEDGDCDCFCBCFHBCBEBEBEBFCGCHFEGGDDBBBCEHGDACABGHGAFHHHBFAFCFHB,False +710,30.0,23.0,16.0,22.0,21.0,35.0,15.0,23.0,FAFAFAFEFEHAHAEBEFDFDBDHFCEAHHHHBEFDADHEHBCCCADEHFHFHFCGGDECGCBDBGAFAFBCDAHADBECEFHCBCBAAAFAGBFADDFDFHBGAAEABFDEDFHAGAHAGAGEGHFEFCABAFCBEBEBHFDDDFDADEEEFBFDACEGFBDBHBHBFGFBFCFGGHAHAFGFC,False +711,6.0,6.0,12.0,7.0,12.0,9.0,12.0,10.0,HGEDHDGCGCGBHBHGCFAGABCBGGEBCHCHFGDEEEHEHAHFHCGDFEFAFAFDECECDCFABCGEGFCEDE,False +712,23.0,31.0,32.0,27.0,25.0,14.0,31.0,14.0,CGABCFCEHDFDHEHBDBDECCFBDGHGAGBGCHCBAEHEHDFDBDCEFGCGCFBAGGGEFEABFBGEAAAAHAGACACECACBGDGDBHBCFGHGBCAAAFBDDDDDDFGFCECBBEEGDADCBEAEAFDGEGCCBCBCBDGCECGCGCGCECECBFBDBABDBDHDCEHEBECGAABDBGGGDEEGEBBAHGGDH,False +713,4.0,5.0,5.0,9.0,4.0,5.0,6.0,6.0,BEFEACAHDHDHGHBDCHCDEDFDGDBEFGDGDFAFBBGACHCG,False +714,18.0,19.0,22.0,14.0,25.0,27.0,18.0,19.0,GEHFCECFCAEFBFAHBCCEBFFEFECDADEDEAEFEBECECGHGAAADAGHBFGFAFHDEABBDGDEHEFEFDBCHEGCCEFBFEHHHHGHGCAFAFHFHFGEHEHCGDFEAEAGFFBADAFFCFABGBABFBCBGBGCDCDHFHCECECDHDBGBCBCGG,False +715,17.0,8.0,11.0,12.0,13.0,12.0,12.0,14.0,BAGDHBHDHABAEGHFDADFECDCGCGADHDHDHABCBHGAAFBFBEHEAFCFAGHEBCDFDFDCHCHCADAEHEGEAEGCGCFEHAGGFAFEFEAEAG,False +716,16.0,17.0,24.0,24.0,21.0,17.0,16.0,24.0,FCBCBHBCBCECDCDAFFHHHCHDBEFABAEDEDEDECFDGGGAEFEFEHCADAFACEEECFCGAEDEDGHGDGAGFBHDHFHCCGEGBDHGEBHHHEHACAEGFDFDHCECBADECHHHBBBFBFBDADCCFCDCBCDEDHHCGDDAAAHBHGHGDGF,False +717,30.0,23.0,30.0,24.0,12.0,21.0,21.0,16.0,ECEDACAHEHCACECDCGCBHAGDFACBCBAFGFGBACCCCACFGEGFHHAHABGBEFFBFDFCGABCDCBBBBBAADADGDFDFHFDCDCHFBFAAGAGAGAGFCCCHABGDGDBDCDEBHDCDCDBGFFHHGBEAAHAHDFDEDAHAGDCDBHAFGGGBABDFCACACBCFEEAE,False +718,8.0,9.0,11.0,13.0,10.0,18.0,7.0,15.0,BHBGDHDHDEAEFFAGAGABHFFFADHDHDGAFCDCAHBDECFAHDHCCBGHFCECEHEFDBDCDGEGDBHBECFCFCFHBEFFFFFHFHE,False +719,12.0,23.0,32.0,23.0,25.0,25.0,24.0,32.0,ACHDECHBHFHGHGHDADAGHCCEBEBCCGHFFGFCBEGCCDDDBGFDHDHDHGFGBCFCGCDCDCDCFGEDBDBEGGCFEFEHEBEHECBFDCDGBGEGBGEGCFEEECGFGADCFEAEADBBCECEHEBEDFHFCFCAABGHHHHHFAFABCCHCFCAHEHFBFBFHCGFBDGDEBHBHCECGDBAFHHHHHDH,False +720,9.0,6.0,1.0,2.0,6.0,3.0,3.0,2.0,AAABABDBGEHAGABCBGFHEAEDEAEFEFBA,True +721,4.0,4.0,5.0,4.0,1.0,4.0,3.0,0.0,BGBCACGCDDFDFABACECBFAFDG,True +722,16.0,8.0,13.0,19.0,18.0,17.0,9.0,17.0,DFEFCHCGADHDEDAHEDEBFHFEFEAEDEDHAHADCBAFACAHEHDCGCGCDCDHDFECEBEDEDEFGGABFBFGCACFDFAFBDGFHCADHEHEGDAEAHHHBHFHFADCFEBGA,False +723,20.0,21.0,15.0,7.0,15.0,20.0,22.0,15.0,AFCDCFCFGFGAGBCACBHAAFGFBBEEAEGHDEDBHBHEHBCGEGFACEGHGHGCGEGECAFFGEGEGEGBBFAFDCBCFCFADADBHEAEHGBGHGBAFAHCBADFBHBCBFAFHBABABAFABHFGFGEHCG,False +724,22.0,23.0,14.0,13.0,20.0,26.0,11.0,21.0,DEBABADADEGBGBEBHBCCAAEAFFDAAAAFEFAFGFCFCBHBCFFFCFBFDFEHHDHCHCFDEDHBHBGAACEFAHHFABAEEEEGBCHCECACGDHAFDFHFHFEFHAGGGFCHBBDBHBEBFBFHHEHBBBABEEFGFEDGDAHAE,False +725,21.0,25.0,25.0,29.0,21.0,32.0,25.0,20.0,FGGGCGEGDFAHHHCCCGAEABFBEBDBDHDCDEDAFGDGAEFCFCEAEADABCBGGGGGCDCDCFFFEHACBCBCGCFCFDBDFCFAHBDDFDFBEHEADCDFHEHFFEGGDGFHEGEBBBDHEAEAGAGAHBHAAGAHAHDDCBCFFFHFEDGDHDBFBEAHBFBEDFCHGFGDCFEGCHCFBFDEDFDABBFBCB,False +726,16.0,20.0,16.0,17.0,10.0,18.0,13.0,17.0,BBBBGCACACBFBABFBCDHGBCHCBADABFCFCFGAHEGBGEEEFDGDFAGAGCBCEFHFHGHFHAHFDFCHAHAGEBDBDGDCDCHFHBDDADCBFADEEEHHDGFGFHADEDHFHCBCBABADF,False +727,10.0,29.0,22.0,26.0,22.0,17.0,21.0,19.0,BCBCBCBDAFHFCECDCDCBHECFCGAGDGBHFDGDGBGBEDEDEDBCBAFAGHBHDHAADBDCGFGHDBDEGEFBBBCBEBEHECDHEGDADCDHDBBGCEHFGCAEAEBEBFBHADCECFCFEDGHGHBHFHGHBCFGBCEFDHGBGFGEBEHEFFDDBDECGD,False +728,11.0,13.0,13.0,11.0,13.0,20.0,15.0,18.0,EFFFEBCDCHCAAAADFHFHGAFDFHFCFBEBGCGAFBCACAHAHEDBBGEDEDCDGBGFGFGCHCFFDHEBBCGGGGGDFHAHDHBFFCHHDHEHEFBHBHECAGEGEFEFBH,False +729,26.0,25.0,13.0,24.0,26.0,16.0,21.0,19.0,DBDFABGGFGHEHAAAAABFBFBGBDBABAGEGCGFEEGEBEDHAEDCHABCDEFAFAGDHHAHADAFAFGBGAGHBDGCHHHBFFEAEDBDBEHDBBEDDHDHDCBCBEHCACDHFCGAGEGDDBEBEBEAGAEADABAFFFFEHGCGCEEEEBEGDHDGECEABHDCD,False +730,16.0,17.0,13.0,13.0,6.0,15.0,8.0,16.0,CCHDADACCDBABEBHDFBEAGBGFCECHBAAEAEDEGCHCHAFBHGHDBDADAFBDBGBHCHCAGAGHHCDCFFDFBFBADFBFBFHAAADBFCFGFBFHHHH,False +731,16.0,23.0,24.0,23.0,24.0,17.0,32.0,25.0,FFFFFFFDDEDGGHGHGHGFDHBCACGEGEBEBECFFBFBDECCDEHCFGEACHDHDHCFDHEGABHEGBGEAEHBAGCGHGHEEEDEDHFCGDGBAHAGAGDGBACCEAGAGAGAHFBCHCGCDCHCHBDBGBEBGCDFDBCBHEHEHGCGHBCBCGCAADDDGHGBDEDEGBBDFEAEGBCH,False +732,2.0,3.0,2.0,0.0,1.0,3.0,2.0,1.0,FCFGFHCBGBAEAB,True +733,6.0,2.0,3.0,2.0,1.0,4.0,1.0,4.0,BFFCHCHCHAAFADBGFDAHAEA,True +734,5.0,4.0,6.0,8.0,4.0,8.0,3.0,7.0,DGHGDEDEFAFBFBDDEAADFDHCHFAFBDGHHHHCCCCFCFBEA,False +735,11.0,7.0,8.0,6.0,4.0,4.0,8.0,5.0,CHCACAGAEDFDCBHDHFHBCDDHAFGGGCACAGAGBBBGBEBDFAAGAECEA,False +736,20.0,16.0,16.0,26.0,10.0,23.0,15.0,12.0,BDBHCCEBDBACHCDFGFCADHDFDHAECDAGAGCFEFCFEDDDDDDDCFHHADFDABEGGGAGAGADABAFCFAFDBEBEGACADDDHAHBECHDGBGBDDEGEGDBFCFHBADGHGHFFFBFAFAFCFCFBFCFBA,False +737,23.0,11.0,24.0,14.0,10.0,9.0,22.0,11.0,FHADCDEAAAABDBHAFADADFCGGGHGAEAHCGDDCDCDHAHCGGGGCACFCBCBCGCHAAFAHEBADAECGCGCGDGECEDGBFCDBAGACFHAEGCGEGBGCECHGGFHFABABABCCDCE,True +738,26.0,23.0,28.0,29.0,22.0,16.0,18.0,26.0,EHDFFHFHEAFFBBEHDBBBDBDCGEGEGCBCDGHAHDEDEDFAFGCCCACBDAGAEFHFHADAFHCDCDBDHAAAAAHCHCHFHFEFHCHFBAEDHCBCBCBEBDADGDAHAGACACBHEDDDEHCHBDECCGBGBHDCDHDBGCCBGDGCHHGFBAEGEAFACACBCEEEEHEGCGAADAEBGDDD,False +739,8.0,2.0,10.0,6.0,9.0,6.0,10.0,6.0,CGBDCDCHHEEAEACAEEGFHFDDDDFGFEAHCCCCCBFGAGAGEFAGAGHCEGEGH,False +740,11.0,8.0,17.0,13.0,9.0,9.0,18.0,8.0,BGAGBECGDGHFHBHBGDGDGCCCCCCFCFDFAFHBDADGDGBBCACAFEDGDHCECHAEEEBDCGGAGFGCGDAAEDEACHEHCCFGAGDGF,False +741,4.0,2.0,8.0,8.0,5.0,1.0,3.0,4.0,CECEAEHCCADDHDHGGEBHBECFCDDDDCDAGAC,True +742,2.0,9.0,1.0,2.0,5.0,5.0,1.0,4.0,CBHEDBAFFDBABEBEBHFHBHBFBGEFE,True +743,18.0,19.0,21.0,21.0,22.0,11.0,26.0,21.0,EAACDDDHDGEGBHHHHEBEBABHEHBFGCGDGEGCDCDGGCGHFFDFBBGACADADHHADCDGDGBCCCBEDECAGHGHBFCFEDEDEGGCBEFEBEBEHADBHBGGGADADFGFDAEAGBBHGDBHGHCHCACACAEFEGHCECEAFHCHBGEGECA,False +744,31.0,23.0,20.0,24.0,21.0,22.0,28.0,21.0,DADEBEBEDADABCBFGGGGGHGHAFFGBGBGCGDGFGHBCCFDEHEADABAGGBGFCFCAGAHHEDBHBHFFEHAGAGBCDFAEBHDDDDEHHACFBHDGDGACFFBDBAAADAHAHCHCEGAHAGEEEEEBHFFGADABABEBEBCDCBHFHFAADFCGCGBAADDDFCCCHFEFECEAGACAGDGFE,False +745,5.0,11.0,15.0,7.0,10.0,9.0,7.0,16.0,EFHFBCACFCEHBCBABABCECFHHHHFEFHCHCFCBHHGGEGEDDDHAFGEGCBDDDHEEAFBBCHCHEHGHBCBCDCG,False +746,1.0,0.0,6.0,5.0,2.0,2.0,2.0,0.0,GDCDCACECEDFDGCCFD,True +747,14.0,8.0,8.0,12.0,14.0,15.0,12.0,12.0,HCHDFEEGCBCDCAEEEBEFEFCABABFBFDEGFAHEHAHCHGGFCFDEDAHCHDFDGDGABHEAAFAFHFEEGAGDDFBHBHGDGEGAGAFAFD,False +748,23.0,22.0,15.0,27.0,27.0,24.0,31.0,19.0,CFEFAHGBGDEAEBEAEBHBDDGBFAHCGFHFHGEGFAFADBEFHBEBCCFCGEGADBBGGCGBGHHBEGEGABBEEEAHAGEGFGAGFCCBFAGBGFGFGFADDBDBGBFEFGFAAAABHCDDDDDDFDFHFHBGDEAEDDDEDEGEDEDECHDHCFAGAHAEAGADFGHEHDHCCGEGEDBDFCHC,False +749,18.0,23.0,17.0,19.0,17.0,23.0,21.0,21.0,EAADEDBDBFBEECFCDEGFDFHBDAFFBCCCGCHCHAFAFAGGHGECECEBEGAGDGDHEFEHCBAADAFBFBHBABGBGCFCDHFBDEDECFGFBCHHDBBCHDGDFFBFBGDGBHHAHABADADEEGHGHBHFFFFEFGCGCDEHHGHGAAAGBBH,False +750,26.0,15.0,24.0,31.0,22.0,18.0,27.0,36.0,HFCEEEDBCEHFDCDCDGDAHEDGBCCDCGHDEECFHFAFADHFCGEEAEHEHECGABAHFBFBFDACBDBDCDHDHGFBFACAHAHABAHHHCDGHGHGHAABFHFGGHADDDDDADCDEDGDEAGGGGAGBGACCHBHBFDDEEHEDDHCHCHCHGFGAHHHBHFGCGHEEDEDFBAGHGHCECGCAHAGFEADAGA,False +751,2.0,2.0,6.0,6.0,5.0,4.0,2.0,6.0,DCHAHGHCHCEBEGDFCHCDCFEFEDEFHADBD,True +752,12.0,16.0,4.0,9.0,13.0,13.0,11.0,4.0,EBEBDBDBFAHAHADAGBCBFHEEAFAEEBEFGFEFAAAGGGBAFCFCFDGEBBBBBBGAFEEDDDGAGFGCEFEGBDDFHB,False +753,20.0,22.0,13.0,25.0,23.0,25.0,27.0,11.0,DBDAFFDEDEDEFEFDBCFFHDDEEEBEFDFEFEGBGCHCEBEHEHAABAGGGDEAFDFBGGGDFAFAFACHEEBHACBFECCGGGGGGFDFAFCGEGEFHBDBACAHAEFDBDFGABFBEGCGCDHDHDGDBDBDGCFBGCAHGDGBBFAFABEGEGABADADGB,False +754,13.0,24.0,24.0,21.0,25.0,16.0,20.0,11.0,BHBDGCGFGFGFGHGHBFGCEEFEFBAHEHEHEBCDEDEDBBCBCEFECGCDBACAGDGDBBHCCGDAAEAHCEFECABABDGDGCBEDHGFEDEDBGGCACDDBEBCBDFGGGEEHECECEFDFDBBBDCHAFDCBCBCGCFFACAEAEDBFE,False +755,21.0,23.0,12.0,20.0,22.0,23.0,13.0,24.0,FBFBCBFBFECEBHBHDHBBBFBACGBGBDAGFDACHHGCGHFDBHEEEFEAEBEBFGAGAGEDDFDFEFBCAFDFEAEAEDFDBDHECDCFCEAHAFEEHAHGHGHCBDAEGHBDDDBDEHGBAHAFCHGBFHFHEHEADHFHFHFDEBCAAAAHAD,False +756,9.0,16.0,8.0,17.0,8.0,7.0,7.0,4.0,EFEFGFGCCBABHBDDDDGDABBGBFBFEACDBDEDHCGEGBCBCBFDDDEAFABADAHEBADHDCCEDGDBBBAD,False +757,15.0,20.0,18.0,27.0,18.0,16.0,16.0,19.0,GHFBGBCEEAHDBDAHAHEBFFDDDDBFBEEAGBDHDBEGHAHADDEDCFCFBHAHBHDDGDGDECECGHGFGDADEFCFCFDADBGEEBCDEDGABABHBHBHCDCECECEGACCEABFBFBCCHABGHFHFACDDDDDGHECGFGFH,False +758,24.0,10.0,20.0,10.0,13.0,18.0,25.0,18.0,HEHAHAFAHCGCGCHEBGCGHGHGFGCGEABGHGFGHCHEAACABAHACFEAGCECBGGGGGACDFHFAFDFDFDFBEEAEAECFCAADAGFCHHECFHGAGHGEAHFGCCDBDBGACAGADABBDBDCFAFHGEFCF,False +759,5.0,2.0,3.0,3.0,1.0,2.0,7.0,3.0,CFAGGHGHGHBDGDGACEDACAGABF,True +760,23.0,15.0,19.0,10.0,31.0,25.0,21.0,16.0,FGFGHGDGBHACAFAFEFEGEBFGFGFECEDBFEFEHHCFAEACFBBBAFEDCGCEAECFCBBHEGEDEAEFBFGFGADCCCBHAAEEBABAHAHACECFHFEDEABFEDEAEBECACECGFGFEAGAFEFACHGDGAEAEGHHHHGDCBEDEHFHGGCG,False +761,4.0,5.0,6.0,6.0,5.0,5.0,6.0,6.0,EFBFBFGDHCHFEFGGBDAGACHCHDHBAAECCBCDEDEDGHG,False +762,5.0,7.0,14.0,5.0,9.0,9.0,6.0,9.0,EGEFHBHFGFHCEDEBEFACAEAECHCHCHCHBGCFDFCCACBCDHDFGABHBCECDGGEFCFB,False +763,7.0,10.0,9.0,14.0,6.0,13.0,15.0,4.0,FHBHAHAFAEDCDEAEHFDDGFBFBFDGGFGBGBCBFDGDBCGEGECAGAGDGDFDCDCDFGCGEBDGFBACFBFDCG,False +764,18.0,17.0,21.0,10.0,17.0,19.0,30.0,14.0,GFCBGAFBBEFFCGHGEADAHFHEAEAHAHFGGGEGECCFAGAGFFCACBFAFAFGGGAEHGHFHBHCACHFAFDEDHGEGDFBCGCAHGCEBEHCBGBDDCAGBDAGECECACBCBCGGGBBBBBECFCFEFHGDGDGDGEGEGC,False +765,16.0,9.0,24.0,14.0,21.0,12.0,17.0,12.0,FCCCCEGDGDFBEGCBCDDDDCHFGACDHECCCEEAHGHGCCCFEAAADAHGEBEFDDDCDCEAGCGDHEAEAGADAGEFCFCFGFGEAFHEECECEGHGBFCECEBFBCAEBGBGHAHAHAHBE,False +766,2.0,5.0,3.0,5.0,5.0,3.0,5.0,14.0,GCCBCDHEEEFHHEBEHGHBHDHDHAHFGAHDGDGHHHHBFB,True +767,25.0,19.0,25.0,19.0,30.0,21.0,34.0,24.0,AABAGCCCGCDFDAEECGCHBHGHGHDAGCGDFDCEGEBAGFEEEHHAGAGAGFECEHGCECEHFHABEEEBEFEBEFEBCGGGDGABEDEDADGFGFCHHHHDDFBFBAEAEAHGFCFAAAAABAFHECGCDCGFADDBHBGCEHFBBGDHFAFHBHCHFHAGGGGGGAGCGEDEBEDECHFHGBDEDBFGCCCCE,False +768,25.0,18.0,18.0,14.0,17.0,14.0,28.0,21.0,DBBECABABAFFCHGBFEAEHGGEEEHGHGAGADAHGCCFDFDGAFCECECDBBBFBDHHGHEHBHAHGCGFGHHCCFAEAECGAGFHHCEGGGCDCEHEHEDGDHDAGABACCBCBGFFBBHBABADAGGGGHGAGAGAECFBAGAFADAEHDD,False +769,1.0,3.0,1.0,7.0,6.0,6.0,6.0,3.0,EFGFHFCEBGHFBDEDEHEAFDDGDGDGDGBEF,True +770,10.0,20.0,19.0,21.0,15.0,21.0,16.0,16.0,CDHDGGGCGEGECDCDCDABFBDBFBFDFHFHDDBEAEHBGBGCDBGBCHHDGFGCHDHCGCAAHABAFHHBDEFEFCFDFCFCFAHEFBFBGHGDDDCBEGGFEBEAEBDBHCHAEFCDCBFEFEBHCGCBFDFDEA,False +771,4.0,6.0,5.0,4.0,2.0,2.0,2.0,5.0,DBACDGDBBHBHCFDECECACAHAHGBFBH,False +772,20.0,21.0,27.0,26.0,23.0,24.0,13.0,18.0,HHGDAACADHDEDCABDHDFCFDBCFCABDCCCCFFFDFBCBHBGEGHGADACFDGAADDDDDECEHEHDFEBEFCFHFAFCFCFAFCHHHCEBEBEGECECFCHEFDCGBAFADAEAEDEDEFEHEGDAAEBCAEABBFBFBEADGCHDBGBDCDFGGBCBCBEHGHCHBF,False +773,23.0,11.0,12.0,12.0,15.0,10.0,15.0,14.0,HHBEBEDEBGBDFCECGCGEGCHDHGHGBCHAGAGAFAFAHAEEEAEAGBGEGCGAACABBHDABFDFAHADGHFBCDDHAAEAEAEAEACDFDEAAAHFDCCGCHHGDBFF,False +774,17.0,24.0,28.0,15.0,15.0,16.0,18.0,18.0,EFEFEBGCDADCEHBHBHBFBECECBFBFCGCEDEDCCFCGCGFGFACCDFHAHGHBHCHEHECCCGGFCHCADBBBGHHEGCCCGCBHGEGBBBAADCDCDCDADADABFHFAGBDBAHGBBABFEFGBEAHBGCCHFHGDABACAFDEA,False +775,3.0,0.0,2.0,1.0,0.0,2.0,2.0,3.0,AGHGHFDFCHCAA,True +776,17.0,9.0,11.0,6.0,12.0,12.0,17.0,14.0,GCGDABAFGFGCCECFABAEAEBGADHHEHAAAEDEAEABDFCGBADAEHGHFFFGAGFCFDBHBFGHHCGAGHGEGHBHCECEAEAGFCFCBHGHGH,False +777,4.0,6.0,1.0,5.0,7.0,2.0,6.0,4.0,HEFEAEAEDBBGDCDHDFEBAAHEHEDGBBBGGGG,True +778,6.0,7.0,4.0,4.0,5.0,13.0,4.0,5.0,HEHEAFGFAFAFBGBAFFFDEDECBCFGDBEHFAFBFDFHFHGBACCB,False +779,9.0,7.0,5.0,6.0,9.0,8.0,7.0,9.0,DGBEBEDHAFAFHFHFCFCEDEGEDEDGHAFBHBAGAFBCBHFAGADAECCBGEGHHEHA,False +780,19.0,21.0,16.0,16.0,23.0,19.0,26.0,22.0,FFCAGEGEGAHBBEBEGCDFEFCFGHHDHDHDBEFFAGEGAGAGAHEHFAEDBACCCEDGBEACFCFEDEABABABFHFBGBGAGEHHACBCGCHCHGHEABACDBDHEGFGEADHFBDCDCEBBAGHGHEHEHGHDHDGDGFHABECEBDGGFGBGBEFFF,False +781,15.0,24.0,23.0,18.0,23.0,14.0,17.0,21.0,FEAGCCBABABAFAHCDGHFCAEGBGBGHHBBCBFBABAEDEDADHFECGDGAHEBEBECCGCHCHEBCFEDDDCGCGDGDHEFGGCHCBEFECAHDEDFDEHEGEFBBHGGCECECFBDBDBAHAHEHDHECFBFDCECABABHBGBCHFHDHE,False +782,14.0,24.0,23.0,18.0,18.0,17.0,19.0,17.0,GAECGCBBAGAGAGFEEDDFBEEEBBGGEECCCCBEGEGFGDGCHCHCHEADBDBHBHFGADBFGDHHGAGADDDDDCBCDHFBFHDAGFHFHFHCBCFEHHHBFCFHFCGCBCAGFEBDFCECHCACBDBCEAGDBDBEBEBEBABAFC,False +783,17.0,21.0,14.0,26.0,20.0,11.0,14.0,15.0,CHAHEHDHGCCADABAEDBDBFAEABGDDCGADADBBAFCEGDBEBDHGEGFHEHEHEFCFDGHADADBDBDCDCGBABDECEDEDFDCDCDADEDBDHGBGBECDHEHFFBAEAEBEBGHGEBCGGBEFHBHCFAFA,False +784,9.0,13.0,21.0,19.0,11.0,19.0,13.0,15.0,ADHDFGEBBCCDCDCFHAGDBCBCECEAGAHCDEAHBHEFEAHHGDCHCHDHDHFBEADFCGCHDHAFBGBGBEFDFGFECACFEFGFDCDEBGBGCFBFCDGDGCFDFHFHFCFCDCDB,False +785,3.0,4.0,10.0,4.0,5.0,8.0,5.0,7.0,FCFCGCGEAAGFCECECHFFDHCACGCGEBHFEFHBHDFDBDBHHC,False +786,13.0,15.0,20.0,21.0,12.0,14.0,14.0,18.0,BFDGDGDADECHCHCEDGDBDGHCHDGCABEEFEFGGDDBDHDHDGCCEBDFDFBHBHBHFHFAECEBAAAFAEAHBHGHDFEFBHBABECCCCCDEGHGBFFGHCDCBGDCCCFHDCACAFGHADA,False +787,12.0,21.0,22.0,19.0,22.0,24.0,29.0,14.0,CGCGEECEGGBEAGCFFFCDCEEACFBFBGBGDGDHDHCBCGADEHGHBFGFGFDFDBGEGEBFCFCFCFABDBCAFFGDGBFHCHEECDFDFCBEBFHGCGEGAGAFDFCEGEGEAAHHHBGCGCGAGDGDBDFGEDBDFDBCHADEEGEHEHABBFEHBCB,False +788,17.0,13.0,19.0,20.0,16.0,16.0,19.0,15.0,BDCEGHGDAFFHFHDADAHEEEECFCGDHBHGGGAGAEFGBCADGCCCCCCGCDCBEFEFDFECADABAFEBGBGAADGEGHADABHFHFCEDHDGGCDCDFDADGHCFBBCBCEHBHFHDEDEDEGHGAAAFBF,False +789,28.0,17.0,13.0,32.0,28.0,13.0,27.0,17.0,AEADADBGBAFAEADGBAAGDDEGEBEFCFCFHFHAEGEHDHAADEDHDCFCBAEGEGDGCGAGBGBGBFDDDEDGBGBGBDDGGADCDBGAEAGDBCADEDHBABAECHCECAFEHAFACDCDGEHEHFBEHDDDDFEAABDHGHGHDAGECEGEGDHEAEGEGEAFHDHDFAE,False +790,20.0,14.0,14.0,14.0,17.0,15.0,16.0,18.0,FCFDDDHCHCEGHADCBGFEFCFEEEEBEADABHBDEFCABABAGAGEHHBHBDAECGDEAAAFAEADBHCGGBGBGBEFEFEFABAGFHHGACDBDHHGFDACEHDHGHFCFDHCHCHCEFAGAGAG,False +791,18.0,17.0,18.0,19.0,20.0,20.0,6.0,18.0,FHFHFDEAADAFBBACGHDCDFAGGFEFADEDBFBFECEAFAFACCCEFHBHFHBBACHFDGDCDHDHGBAHCDCBHBEEEEAECBABCBCEDHDFDEDEDEAEADACAHFHFHEDCCABEHEBEHCFBFGFBDHC,False +792,14.0,17.0,13.0,12.0,11.0,16.0,16.0,11.0,DDBDBDAFBDBFAFAGBDEGCCECHCHCGFABGBCFEFECHFBABAEECBDHDGDGHGHGFCFHEAEGDHBCBEFHBGAGACAHAFGFGFDEABFBABGFGFGBHCAEDC,False +793,9.0,19.0,17.0,11.0,13.0,16.0,16.0,13.0,DCGHBFFCGEEBEGGAGFDEEBFGHCHCDFDBCBCFCFCGCGBBBCBCBFHFGCAEABHBABGBDBDFDHAHFGFHBBBGHGHECFDECEGHGHDAAGDBCECDAEAEFEFCFH,False +794,18.0,14.0,23.0,18.0,18.0,15.0,28.0,20.0,GBGBGFGAEFECEBGBECECFGDEDGFCFGGHCHCFGDAHHCHCFCFCGCGCEAHAEABACDBDBAGGCGHAHBDFDHEHEGAGEGEHHDCDGFHBHGHFADECACAEABFCAHGHGBDCDFDFBAGACDGGCDBGGADHDBFHEHEAEGDCEC,False +795,2.0,6.0,5.0,6.0,3.0,1.0,4.0,1.0,GDGECBCHDEDECBBFBCBABDGDGACD,True +796,20.0,15.0,22.0,19.0,22.0,17.0,35.0,28.0,EHGHCDCDAEBCBFBACHCGEFEFEFDFHGHDCGAHDCGCDCACBGEEHEHGGGEHEFEGGAAAAHAFFECCAGHGHGHBACACDCFEAGGGGGGGCGAFCBEHHGDGHGADAHGHBDGAGBCDCABAHDDEEFGGEHHHBBBDBDHDHDHFHEHBCDCGFGECEFFGFGEGHFBEDA,False +797,22.0,14.0,14.0,13.0,13.0,14.0,15.0,9.0,HCHGGBDEFAFAGAHDCGCGCHCGFAADEDEABAGABFEFEFEBDFGABHFDAABCHCFCADBBAGDGDGDCDFEFGBDBDFFGCBCBEBGAAAAAAHEHEBEGCAAAFHECEC,False +798,15.0,14.0,14.0,26.0,14.0,22.0,16.0,23.0,DCGAADDDHDHFFDBGGFGEGBBDHAHFFFFAFCFBDDFEAEDHDHGHGDCHCFAGBDFCFEFGAGHECFCEDAHAGEBFBABDEDADCDHAFCFAFHBDFAFADEGEHEHBHGFGCGHGCDCDBBHHHHBCBCHDEDEDEDHH,False +799,27.0,20.0,19.0,24.0,17.0,17.0,26.0,21.0,GFGDGDCDFGBGBEBGBHHFDADAHEHEBBBHFFGGCADACAGHBHAAFACACHBECEFAHADGDAEHECFABCGCAHBHAHDGEEHFDFHFDFCAHDBDBFEGDGDGHBDBGAGEGBGCCECEBEHAGABADADADECGCGCAFHGHBFACACFDEDEBGACAGHGFDDD,False +800,14.0,22.0,27.0,22.0,29.0,27.0,20.0,20.0,BCBCBCACACAHDBFCHEHEFBGGCGCABBHBEEEBECECBDHDEBAACGCGFGFDFGBCDAHHHHFFEDDDDEFFHFDEGGGHEAEDEGBBDFEADFCGCGCHFHGHGEDCHFFFDFDCHFBCBCBCEEEGACAEHEFGFDFCFBAEHECGDEFGHGAFAEBBBBDCEHFCFEFDCDEDE,False +801,5.0,1.0,4.0,0.0,2.0,1.0,0.0,1.0,HCAEACAFBEACAC,True +802,15.0,14.0,17.0,11.0,11.0,11.0,14.0,5.0,DGAEAFAFCFDADEFEFCACGEHEFGCHABACABHBADDFDFCGEGEAAACHCGDGCGBEBFDCABBBBDBABFGGCCCEGFBBBEDAHCGCGCGCED,False +803,19.0,24.0,22.0,27.0,21.0,24.0,25.0,26.0,HFAFEFEFCCCHCHGDDHEHEDEACCFAFBHDEDEBGCGBFAHAHAHFGDBAGAHBHFEFBFEFABCDHDGACACBGDGHAFBDBCFHFHDHDGDADBCFGGBDACGHGCECEGGAGDGDGEGECADHDABGBDDCECEHFHBGGEGEHBFBDHFACAFBBBBHEEEGCDHGFDFDFEFHDHDCBBBC,False +804,14.0,12.0,12.0,16.0,9.0,14.0,9.0,8.0,ABCBAFDEDFDHDCDBAFCBGBDBEAEGEBCDGAACABDECECEHEAGHGDBHFFFCGDADFFFGFDBDFAHCHCHCHCBADADADABFFGGEF,False +805,10.0,5.0,7.0,4.0,17.0,8.0,9.0,3.0,AAGAGAGAGAHECEFEGEHEBEAEFDADFEEEECEDECHGFEFAFBEDFGBEACBCEFBCCGG,True +806,16.0,25.0,13.0,17.0,23.0,16.0,21.0,18.0,CBGEEFEGBBBCHGHBAAAAGAGEGCHCEDBBBBBHHHHDAFFEEDEDAAADFEBHGHDHEGEGHCECEBBDADGGGGGDGHEHEHEBBBFGFAFDFEFEBEBCFFEBHBECDBDFAFAGHDFDGBHDCFCAABCBHEGDGDEBGCCAF,False +807,3.0,8.0,5.0,8.0,9.0,8.0,9.0,9.0,HFFFBHCHEBEBEBGBDCGCECEFDFBFGAGHHDHFACHDHDEFBGDGEHEADGDBEGG,False +808,18.0,19.0,24.0,19.0,15.0,25.0,23.0,17.0,CDGFCFCAGHEAEADCGEGACBGFGDHEEECACECECFAHAFDCDHDFEBEHDFDFHFGBEBGGGBBBHBHFAEAFGFAHAGAFCGCHCHGHBCDDFDFDGDFBEBEBFAFCFGDCCHGHADCBFBGBGHFCGDGBCAHFDFCFCBCBDAEABADGFGHC,False +809,24.0,16.0,20.0,18.0,20.0,16.0,26.0,18.0,HBEFGCGHAHADGCACAFBFAFCEBGBFDGAGAEHHCDDHDFDHDHDEECGABCBFEAEHDGGGGBABGFEBCAEGBCFCHGHBHBABGBHFEFCCCCAHGEGEFHFDGAEBHDADCGHEAEAEAEAEGEDCDADGDGAGAGAEHDGCCFCFCADBGF,False +810,7.0,10.0,7.0,14.0,17.0,13.0,14.0,8.0,DEAEGEFECACABGEGEAHGHGHAEFEFECHDDFDBDBCBDBDFGCGEBECEDDDADBEFEBDFGBDFHGCFFDGGFEHEHFHBGAGEGF,False +811,11.0,12.0,11.0,18.0,16.0,11.0,15.0,16.0,EBEBABDHDHDHEHGHFAAGGCAFEDDGEFAFHDBDBDHEGGGGBCBCFDDDDDEDBHFEBHCHABEFEFGHECECBFGGGEDHCHCGEGACAEAECHABCHDADFDFHG,False +812,7.0,8.0,5.0,1.0,6.0,6.0,5.0,5.0,HHHHAEACACBEBCCAFAGEFCFDBHBFBFEGAGEGBGFABBE,False +813,7.0,6.0,14.0,17.0,20.0,8.0,11.0,16.0,BCHCAFAGAHCEFEDEHEDCHGHAEDGDFCFHGHGHAEGEGFHBBDFEHEDEDHDEDEBGDDFBEHGABCEDECCCADGHEHEHCHCDCDCDCEEGEFD,True +814,27.0,14.0,15.0,25.0,17.0,16.0,12.0,25.0,HFFCACAHFFCBCFFGDDECEFEHCBCBCDAAAGAHAHDECEFHAHAHDEABBEBCFGBGDEAEAEADGHAHACDHHHBCBEDFFAFHFEEGAAAAAHAHEHEDDDDGAGDHDBDFFAHDBACACAGHHDGBGBEDDBDHFHECGDDDHDH,False +815,9.0,8.0,11.0,6.0,5.0,16.0,9.0,7.0,DDGCCHAAADDFEFBHDFFFDFCFCFCFEBEGGGCFCGHGHEAAAFFHBCBGBEBCBFFFCFCAAGAHHGB,False +816,27.0,23.0,14.0,24.0,26.0,27.0,25.0,22.0,DABHHHEHAHAEFDBAGABDBGHDAAGAGFBAHAHEEDABFGGEEADAFBCACGCGCEFEBEBDFDCDGDEFEHEHFAGAGCBCGCBCBEDAGGBABHDFBFBDEHEHGBFEFEBDFHFHFDEECAFGFGFEADHDAGAGADCDCHFHCEADFDGEAFBFCFDBEEDGAGBEFEHDHGAGHGHFBFBF,False +817,1.0,1.0,2.0,2.0,3.0,7.0,3.0,4.0,FFFFADHDHEHEGCFBGECFHFG,True +818,10.0,14.0,17.0,5.0,12.0,5.0,16.0,9.0,CACBHAACABGDCAEAFGBEHEGCGCGEGEDBGAGFHBGCECEFEGEGBHBFGAGHEABDFDBCBCBHEHGHGBDCACBGBECCCCCH,True +819,20.0,12.0,13.0,11.0,16.0,13.0,21.0,6.0,ADCECACDCEGDFFAFBGBGBGBAAAEBEBGFDADEDAACACDCHHBGGGGGGGEGAAHFEFCGDGBCFABAFEGCDHFECEDEHABCDAHFGAGEGAGAEAGBFBCEFEFE,False +820,24.0,22.0,18.0,21.0,20.0,19.0,14.0,22.0,ECFBHAHAHAEAFBFGDGDCBCGAEAHABCBHFEDEDGBCDCDADABAEAEBHDGDHCBAHFDCDHHBHEGAAFAFCHCDDEHBFBFDGDGHBAFCEDEHFCEHEHEHGCGAHABCBEFHFGCDCDFBFBFAFGBDEDAGCHBEBCBADAGEBEAEAFFH,False +821,24.0,21.0,19.0,22.0,19.0,13.0,20.0,29.0,DAHAHAFEGCDEECECAAEHEFDDDGAGAGAGABHBGEHDHFHEHAHAHAFBHBHCAADCEBBGDECHGFGHGAGEDFDFDHHHCGAEABFDGBECECAHACFCHGFBDHGFDHBHDDDDGGHEHAHBGBGBHEABBFBDBFBDAEEBECCCCCACHCBCHAHDGDB,False +822,16.0,25.0,27.0,23.0,14.0,15.0,16.0,28.0,BHCHCDCAGFGAGBFHEHBABGDHBABFBGBDCHCHCHEHAHEHCHDBGBHACADADAFFHAADACBCBEGEFDFDFDFCHEHDDBDEGEDHHHCDEGHCFGFDEDBBGFGCGHAHBDCECHCABHFCCHCDEDCDCGBBEHDHBGBFEFCACHCBBABCBDGC,False +823,19.0,16.0,17.0,19.0,13.0,21.0,12.0,12.0,AAFGBDHDCDFDEHBBFHFCDCABBFDFGEGEBCHDDDBDGDACAGABEGECECECEFEHCHAGDDHCCDAEFFAFBFBGDAEHHBABAHADABGBFCFGDCDFHFHAGAFAFDFBACACFGFEFECBC,False +824,23.0,14.0,24.0,16.0,17.0,21.0,26.0,11.0,EEEECEBHDFDBDCFAABFDEEGGCGEGFHDGAGBCFCHCFAFAGAGFFBGAFAEABCGAEADADAHBBEHCHCBCBCDCECGHBHAFDEDEAAACACFFECEFFGACCDCFGGCGCGFDFHFGCGCGAEAGGHHFBFDADABBCGGGDGDG,False +825,16.0,23.0,19.0,19.0,25.0,21.0,19.0,16.0,BCECEGEHBGBGDACADFFBABGGEBEGCGAGDBCFCEADAEFEDDCHCDEDGBGCFHFGBEBEBEHCHCEBEDEBFBFEFHFHFGDEAEBGBEDDCBHDFGFCACAGAHBDBDBCCFCFAFDDDADHEEEFHAEAGBGCAHHHEHFGFBFGECHABF,False +826,8.0,5.0,4.0,4.0,6.0,3.0,1.0,4.0,CDGDCFEEEEABABADAHBFBHACAFHEAEAHCBD,False +827,24.0,26.0,18.0,19.0,16.0,34.0,27.0,29.0,CFAFCHHGFDHDBDBDCDCHEFBGBGBHBDADCGCGHGFDFBAHDDAFECBFFFHFAGECAHAEBEAAACGEGHGEABAFGCEAGFFHFGACBGHGAFHCHGHGBFAHGHBHBGBGAGCFBEDHBFBHEHEBFGECEADHFHFHFDABFEFHFEFBFBABDBDFDADGDGCAEAFCFCFCDAGGFGFBHHHHB,False +828,2.0,3.0,1.0,7.0,4.0,6.0,1.0,1.0,ADDDFDFEFEDEBFBEGFDADFHCB,True +829,18.0,8.0,19.0,22.0,14.0,21.0,12.0,12.0,EGEGCHAFEECHDBDBDCFAFEFDFEGEAFCFDADADCHFHEADAEHDHCCFCFDFHFDFDACACACEFDFDGBFBCGEGFGCGCAHADACEDDGCCACHBABDBHAHFFFDDHACBDEAEGGGFD,False +830,14.0,17.0,12.0,13.0,7.0,7.0,14.0,9.0,EGEBHBDCDGECBABADDGCABACFCEBDCCADADFGHGHGFGBGBGHGFDDCDAGABACHHDHDFDCBBGBAAFACEHAGAGBEBHBCBEBF,False +831,13.0,21.0,11.0,11.0,12.0,12.0,12.0,8.0,EAEDGBFBDBCHEBEBEBCHCHAFGGBCDDDCDCBADAFAFABADFCBCGEAEDBAFAEHEHADFHBBEHEFBFGEBHFGBCBCBFGGAGAGBGCGFBDB,False +832,14.0,20.0,21.0,16.0,26.0,24.0,30.0,17.0,BGGGEEEBFFFEFCDGGGGGCGABDFGHCAFFFDFEHDHAGAGAEBEBCBCAGBBDBFBFEEEDDFCCGCGEGBBDBHEDCFCHGFEEBGCFAEGEGECFCGCHEDDCBEDDDHHHCGBGEHEHGDDCGCGBGEGEBEHECGGAEABAFAHAFAFHFHCHCFFFHFBA,False +833,0.0,0.0,2.0,1.0,0.0,7.0,1.0,2.0,GFFCFHDHCFFFF,True +834,15.0,17.0,13.0,12.0,21.0,19.0,18.0,23.0,DEFBAGHEHEABHDFGFHFHCHDHECEHBHDGDGFFCGBFBEEHHCDEFECEDEBCBGEGEGACAGHGHAHDFCBHGFFFFDACEHEBFBHBHGAAEADGGADHHHHGHGFAFCFCGEDFFABABGECACABEBEBEB,False +835,9.0,17.0,15.0,12.0,13.0,15.0,12.0,18.0,AEAFDHGHGFDEDBFBABACCCFCHEHCFEDHFGFDHBHBHEFAACHEDECFCGCBCECEGHBHCABDBEGFDFDBDBEGEFFCCGHAHAHGHDFBBGBGDGHBHBCBFHE,False +836,24.0,27.0,17.0,31.0,24.0,22.0,21.0,23.0,DCGBEBCDEDADFBFEDADADBDCDCDEDFDGBGCGBHBHBHEHEDEDAGBGFDAHGHBCECADBDEDBFFAFAFAFEHHGCGFEFDDGDGFBFGEGEBAHAFDDHFABBBDADAHAGAFFFCGGEECHGAGAEECEBFBCBHHGEFDAAECFADHGHCHBBBBDEDHBBBEHHAHCHCAEFEHADGDC,False +837,8.0,2.0,11.0,12.0,11.0,8.0,3.0,11.0,BHCHEDEHFAFHDHCHFDCDFDFDAAHCFDDADHDECECACECAFEHEGDGEHEDEHFCBCGCAEA,True +838,12.0,19.0,12.0,11.0,20.0,17.0,13.0,16.0,DEFEFEHEFBFECEAEAGBGAFEBEDFGFGAHFHFCGBBBBBBHEFEBHBGBGHCHFBCDFHAACCHEHACDBFEGEDFBCBABHHCHEHACACEDDDDFDGHGHCAGFDFBEEEGEGBA,False +839,1.0,4.0,3.0,4.0,6.0,6.0,4.0,1.0,GBEECAGBFBFBEDCDFDFEEHEDGFGFC,True +840,5.0,4.0,4.0,1.0,6.0,4.0,2.0,2.0,GEBEFEHEAADACACFCFBBHCAGEBEF,True +841,15.0,12.0,13.0,8.0,18.0,15.0,11.0,15.0,FHFHFEAAHFEFCGEHEHCHCBCAEBBBCHAHAEGFGABHBEBEFCBCAHDHBEAFGBHAFEFBGCFEFCDADBDEDEDEGEFEFAACHDHAEACGEGHGCGAGFDC,False +842,17.0,27.0,15.0,15.0,25.0,21.0,18.0,18.0,DBEBDBEEGGGBGEHCACBCBABGEDEDGFAFCCBEDCGGFGBHAHDBBHBHECACEDBDHAAFAEBEDCDCHGBEDECHAFAFECECEFHGHGHBEBGBGBFFFFHFEFHFHEBEGEAEFFAFGBBBFHCHADFDFBABCGAEAGFHDADEBHBE,False +843,20.0,14.0,16.0,25.0,17.0,16.0,12.0,24.0,HBHEDGBFBCADADACHHDHDAEAHDDDDDHFFDHDGCGCBHEGABAHEDEABACDCEFGFHAGGBACGHAFFGDCAAGHDEGEGEDABACABHFDEEBEBDBDBDHDADAHCHBEFEDEDCFCFCHCHFHFHFHFCAEHHFCE,False +844,6.0,6.0,6.0,6.0,7.0,4.0,7.0,2.0,GCECFBDBDBEGHDEAEAFFECECACBGBDADGDGHFABGEGCA,False +845,14.0,10.0,13.0,17.0,13.0,16.0,16.0,22.0,DADFGHGHFHCBGAFEFCFCGDGDEDBABABECDCDBBGAFAGAHDDDDFDGDGDCEGGFHFHCHGAGDHHHFFCGCHHEFEAHHHFHGEGDAHECDCHHAHAEAEBCFHFBFCEHBBEEA,False +846,13.0,21.0,15.0,9.0,8.0,13.0,6.0,10.0,AGBCBCBDGCBFGHABCBCBEBABCGHEHBAFAFDFECDBBAAHBHBHCFCFDBABDCDFFCGHAHBHBEBEBCFCACDEHACEBFDFGFAFAED,False +847,8.0,14.0,10.0,15.0,9.0,10.0,9.0,7.0,DECFAHHBGBCEAACBCBADDEBHDHDEDFFFGEAEBGCGBGDGDFDADBDBDCFCGCBCHABFBDEDGDGBHBFFCFEAEH,False +848,10.0,5.0,6.0,10.0,12.0,17.0,10.0,11.0,DHDEDCDFDFAFAHCFGABAGFCFBGGGGAHCFDFAFEEEEBBABHFAFGFEEHDHECEHFHFEAHAHEDFDFHFDGGGEC,False +849,22.0,14.0,13.0,19.0,14.0,18.0,13.0,19.0,AACFCFBBHBGFDADADAHHCGFBCHHFHBHDGDCAHAHABDEDBDAHAGFGEBEBACHCDEGAFFDGBHFCFDDBABAEEDEGEFEAAGAGABADAHFGFCFAAGCFHEHFGFBFEEDEHEDCDCDCDHHH,False +850,12.0,11.0,24.0,25.0,18.0,37.0,27.0,36.0,GEGEAEAEDHDEDECECGGGEFEFEGCBFBFCFCDCHEHDDGEGFGDHFGEGAGCGFDHCHFHDGCCHEBBDACHCFCHGHCHCHGDFFFFDFHGHDFFFGFGHHHGCDFBFCHHFHDDBACHEEFDCAHDHBHFFFHHCHBHFHDGFGFGBEAHFHFHFCAGGDCBGDGDFFAACDCAFDFDFBHHAHE,False +851,8.0,20.0,9.0,10.0,16.0,10.0,11.0,18.0,GAGAGFFHFHCHGHEFEGADABHBHBFEEEBAHCHCEEHEDCAGGBBDBFGFHFHAHFHBABEHEBFBCHEBBBDDDCDBECEGDBCBEBEBHBGCHEDDHG,False +852,8.0,4.0,3.0,3.0,5.0,4.0,5.0,3.0,CEHEHBGFGBABDCGAGHFDCGAAAAEADAFEFEB,False +853,2.0,2.0,4.0,5.0,2.0,8.0,1.0,9.0,BHFHFHFADCCGFDFDBDEFAHHHHHFHECCFD,True +854,0.0,3.0,1.0,7.0,1.0,4.0,3.0,3.0,BGEDFDHDHGFBDBCGHDFDFD,True +855,13.0,9.0,23.0,8.0,13.0,14.0,12.0,14.0,CFCFCGHEACCCEEEGDHHAHBGBCFCDCDCFFGCAFDCABHCHCDFFCECGCGCAABFDEDACCHHAFAEBEBHGHBHFGEGCGCGAEBCBAGEFEFEFDHAHAH,False +856,10.0,14.0,21.0,25.0,13.0,22.0,18.0,15.0,HDAFAFDFBGDDCEEGEDFGBDBGCCCCDDDGDGHFDGHEFECHCHCFEDBDBACGFBFBFDCGEGCABABDEGCGCECEBAFGHHBDDDHHHGGDCDCACAFBEBECFCFAEHHFFFDGDGHGHDDFDFHFCFCBAF,False +857,5.0,7.0,6.0,6.0,3.0,6.0,3.0,6.0,HBHCDAHAFGBACABHBDBDEFGCHCHCBEFEFGFCFDDBDA,False +858,5.0,6.0,10.0,9.0,8.0,7.0,3.0,10.0,BGCHCHCBDDHDGDGABCBABFECECECDCDFHHCEDDFFFHHEHEAEAFHBEDHCAF,False +859,5.0,3.0,3.0,10.0,1.0,2.0,6.0,6.0,DADADBGHEADDDCDGHGHGCDCDBFAHHFHAGDGB,True +860,23.0,20.0,27.0,31.0,27.0,21.0,22.0,20.0,GBHCDCFCFDEDHCHGEFEFECCCCCADABAHFHFHFDGDAEEHACDDGBADFDEECFAFCFEGCGEEHFAFEFBABCDADEDEHBHGHBBAECECGBHAGFHHBGECCDEDBFHCACGCDAGAGADDDDDCDGFCFCEEEDEBHGHGHGCGCBDADHBGDDEDABABAEDEBFCDEBABGBDAFAFGEGH,False +861,7.0,7.0,14.0,4.0,11.0,5.0,11.0,5.0,GCGFGBGCCCGFAAEAECECECGBABHHCAEAHAEFEBEHDCDCGFGFBCGCGCDBEEHDGECB,True +862,12.0,3.0,10.0,5.0,8.0,8.0,5.0,6.0,GFCAHAHAGACCEHDBBAAAHADECEDECGCBCECFCFHFHAGGEDEFFCFAEAFAD,False +863,24.0,14.0,29.0,24.0,18.0,18.0,12.0,25.0,ACACHBEBEDABHBGCDCFCEDFCGCACGFADCCCCBCDEAEBDHEEGAGCDFDFDFGEHAHFEEAEHCCFHFEFCHCHDAAHGDCDAHFHEHDHDHAHADEBEBEGADAHEBFHFHACGFGCGCBCDCDCACFCFABCBADDBCBHHDHGAAHAHFFDHDEDA,False +864,12.0,14.0,8.0,8.0,15.0,8.0,10.0,15.0,EBEBGHCABAFAFDFDADGBHCEBGBGBCFCAEEDHCHGHBHDGDHEHEHEHCFGFBEEHAAAHGHGEGBFCABHFHEEBADCDABEBEA,False +865,3.0,2.0,2.0,3.0,0.0,3.0,0.0,4.0,BHDHBCFDFCAHAHAFD,True +866,5.0,8.0,8.0,6.0,13.0,7.0,15.0,8.0,FHCDEDADBEBGAGCCCEBGGFGEGEGAGAGHDHGBEHEDGAGEBECHCGFEEHEHGGFBFBFCFHEBCD,False +867,15.0,8.0,10.0,4.0,10.0,7.0,12.0,11.0,GCHHEHGBDBCGCBCFEAAHAHADFCFCFGAGAFBGAHAEGFBECEABHCHAEAEHGHGFBDCHGEGEGDACABAEA,False +868,13.0,19.0,24.0,20.0,14.0,16.0,12.0,20.0,HCHAHAGDDCDBGGHGHGCEEAEGFBFDEAEFCFHDHGFAFGEHDBDBDCECDFECHCDCFCHCHBBBBGAFDCACEDBFFAFAFBEHCACDHBCBCBHBCADDDBDHDHCHCBABHHEFGAECGCGCBDBDCFHFEE,False +869,11.0,10.0,12.0,15.0,14.0,12.0,10.0,5.0,CBGECDGDGDADCGAHDBDFFFFEAHFEFDBDGDGECECDDFDADBEACGFEBEBECCCGCBCBEAEAFGBAAAEDEGHHDHCFAFEFB,False +870,8.0,16.0,15.0,5.0,12.0,6.0,10.0,5.0,GEGAAFBCBCEGAAEBEBEFHHCBAAGACBBBBEBCGCGCECECBABCFCGCFEDEHCCDGBGFDFDEHCHBBGBDE,True +871,7.0,10.0,13.0,4.0,10.0,7.0,7.0,8.0,GAAHGCBADEDHDCCCACAFHEBBBBBCBEGEGFCHCBEGEGEHDHCFFABCFCFHGHABFECECE,False +872,5.0,6.0,11.0,4.0,5.0,6.0,7.0,6.0,FCCCACBDAFCCCFGBBHBGAGEGDGCGHGHDHDEBHCCFCBAEFEFEHA,False +873,6.0,3.0,2.0,8.0,3.0,5.0,4.0,1.0,AADDDCDCGGFFEBADADADEDGBGFFEFAHB,True +874,16.0,16.0,9.0,13.0,16.0,16.0,11.0,18.0,DGAGHBHCEFGDAAEAFAFBBDFHEDEDHBHGHGHDDEDFCFCAAADAHFBCBCGEHEBFDFAFCFAFAFBECCBEDHHEHEGBGCDFGFHHHBHBEBEBHAEADBEBAAGEGHF,False +875,10.0,10.0,11.0,9.0,10.0,8.0,13.0,16.0,AFADADEDEFHCHCFGBGEHDFGHCHEGBGHFABHEACHBHBHBHGDGBAAAHAHCHCGGGCGEDEBCDDGBGAECEFFFBCHCHDE,False +876,10.0,18.0,8.0,11.0,7.0,15.0,11.0,9.0,FCHDHBFBGCDHAGCCHDHAGFFHBHEFAFAFDBBBDBDEACGGGBGFECECACHDBABFBDBDGEADADFFFGEGEBBBFBFBGBFAH,False +877,4.0,5.0,14.0,13.0,6.0,8.0,11.0,11.0,ACACGHADGCECGGGDCCCFCFBFDFDHDHDADHDHFFBHGHCHCGCDCDHDEEBGFDEHBHGEEBDFCCGG,True +878,22.0,17.0,15.0,16.0,16.0,19.0,13.0,15.0,CCFCHHDBEGEGDCFHFBAGFEDDFDCECEGBCBABADADBGGDBACAFAEABHHHFHCHDBFBDBDBEHHCHCHEEGFGFHAEAEAEADFEAABCFCEAHFGAAADFDFBFBEGCGCDAFAFAEDGBHBGFA,False +879,11.0,12.0,5.0,10.0,10.0,9.0,11.0,9.0,BCBCEAFGFGHBHBHDDFEFGBGHGFBDCAAGEHDBDGHGHFADAEEFEDEDEAHABABACAGHEDFAGEDBGBCBF,False +880,22.0,23.0,20.0,22.0,17.0,22.0,27.0,22.0,AFEFEHDHDHDBFBGBGEGBGFGFGEHEABABGGGABAHDHEBCGCGCFCDBDFEEAAAFDCBFHGHBCGAEDFDFDBCECFBAGAGAFEHGGCGDBBCCGBDDCDBDCFCAHDBAFFHCHDHFHCEEDHDHBHCCBFBAEAEAFGDCDHAHFHEHADAGAGAFBGCGHGFBEGG,False +881,26.0,17.0,21.0,13.0,20.0,12.0,23.0,19.0,BAEAGCGHGAEADABEEEGAAHHDDBDFGAGACCHHEHEBFBHEEEDFGFEAGHCCACGEFEDCGCHCGFHHBHBGBCCCDCGBGBABABFDDHEAEFEGGGGEHAHACACDGBGBGBEAFACEHFAAAHGHGDCCECFCBCBHDAAAFAD,False +882,1.0,1.0,3.0,2.0,1.0,1.0,0.0,5.0,DHHFADEBCHCHCH,True +883,7.0,3.0,8.0,7.0,4.0,4.0,4.0,4.0,GDEDCFHFHDHDEGEACDCABBGFACACGCFCDADBCAEAH,False +884,21.0,12.0,14.0,11.0,9.0,9.0,15.0,13.0,EHEAEGDDAGGBGFFAGHDHDCDCDCFCGGGGGAAEGCHEDEAEFHFAFGCBHBCCCCADBBAGAGHBCACAHAHBFEDBGBCBEDDHHABAFAHAHFBCAAAA,False +885,16.0,26.0,24.0,20.0,25.0,24.0,19.0,20.0,DFDGGAEAEAEDHGHGCCABBEECFCFGBGBDCGFFDBDECEADADHGHFDBDCEEBCGCGAFBFBCHDFDFEFEFHFHFHBHFEFHCHCBAFDFBFCAGAECBBBBEAEBGCECFHEHDCCEGBGBGFGFHHEHCHBDACECABABDBHAEDDCGGBBEFDFDCBAEHEHECG,False +886,13.0,28.0,17.0,8.0,23.0,25.0,17.0,16.0,GFFBFBHCFBBBCGCGEEBCBABFDEBGBGCACEHFHFHBADDCGEGEBHAAACFCEHBHBDAEFFFFDFDFEFEFECEBBBHFGBBHBEGCBEAEDCHEEEFBGHGECEHFHBABFCFCFCGCEAGDGAGAFBGGAFHHHBEBEBF,False +887,12.0,16.0,10.0,18.0,15.0,11.0,14.0,8.0,EEHEFGDCAFDGDCBFBFGFBEAFBBBAGFGBGCHCHCAGADCFCDBDEHEAEDGDBHBFGEBEBDBDADCDHDEABDDEDFCAGDGAGAFDEAGCGBEBEHEH,False +888,18.0,13.0,17.0,15.0,11.0,10.0,18.0,15.0,DEGEDEFAHAHAHGHGHGCGCFDDDADFCBGDGDCBABCBEACAGAGCEDBABDHFGAGAGDEEHAFCDCBCACBEBHCGBFAHAHCDFHBGBGHFHGHFBACEGEGCHAECFCDAD,False +889,22.0,5.0,11.0,9.0,14.0,19.0,10.0,13.0,HEHFADEFGFCEHEFDFHFAFGGGGAGAFADGDFAEAHBCECEDFCFHFCFDFDAACACABBFGCHEAAABCDHEAEABFHFHEGEFHAAAAACAGDHCHEFE,False +890,27.0,36.0,17.0,27.0,26.0,14.0,25.0,25.0,FHDGFABEECADAEBECEABAGHECDCDADGDADADEHEHGHBFBCBGDEEEEEBABABHBHAGCEDEDEHAHAGGCDCDHBABHBCACAGFCFGHHFDFDGBGHGAGCGFFBHADFCECEHBDBGBABACAHEBBHGHEHBBEDEFEBGBDBCGEDBBBBBEBDHDBAHGFGAEBHAADGHGDABFCFDAGBGDHD,False +891,18.0,15.0,22.0,14.0,25.0,27.0,18.0,19.0,FHFHEHAHCFEDCDHFFFHCCCCCCFAFGEAHAFGGEGEGEGFGFAEHDCDFHGAGEBHFHCHBHBEDHDCFCACGBFCDDEHBCEGAFABEBFDEGAFDCACFEFEDEAAGAGAGCBCDFEHAHEHBCBCBFBEEFEHGGGCEFEFEBEAFFBDADB,False +892,15.0,15.0,17.0,14.0,25.0,21.0,15.0,21.0,EGAHHHDHDFEAEDEGGGGAGFHFAFEEEHHBCBGHGBGDFAAEAECEFEDDBFCFCAGFFHFHFHBCFCDHFHCHADBHFGFGBEBHHEEDDCDGBCEEEBGBHEHEDEAFCBCECEBGAAAEDCDCACABEHHCFEFCFBF,False +893,5.0,2.0,1.0,1.0,3.0,2.0,5.0,2.0,BHAHAEEEGFGFACGBDAGAG,True +894,1.0,2.0,2.0,3.0,4.0,6.0,4.0,3.0,FCFCHHEFEFGGGGHDBEBFAFDDE,True +895,12.0,25.0,10.0,17.0,18.0,19.0,18.0,17.0,CECBHFGFGEBBHFEFDBDBABDGAGAEABCBGAGAHCEEHEHEHDDCDBFHFHEDFCFBFBFAGGGGGFGEHBBBHDHBHDEBEFGDCBBBDBGCAHHEGBGBCDFDEEEDEACAFFGBBHFHFDFAFHGBADED,False +896,16.0,8.0,11.0,13.0,10.0,11.0,7.0,7.0,GEDEHEHBBDADFDADCDCAAAHFHFGFECACAEDCDGAEAEBBCBGEACAHDBDEGFHFBCDCFAADACBCHFAFAFEGGDF,False +897,11.0,6.0,9.0,7.0,10.0,14.0,15.0,10.0,HDBFBGCFCGCGBGDEDGHAHGHAAFHFCGBGCAHHGFCFAFEBGHGBDCHCHDEEFEFEAEAEFEFGDGFAFACGEFDAGA,False +898,17.0,13.0,21.0,30.0,28.0,20.0,12.0,19.0,EDDBGCECEDBCBCDHGFECBGBEHHHEHFHDGDHHAFAHCHDBEFDADCDHEEEHEGDGDGFEDCACEDEAEAEFDFDFDADCCACFEFCFEFCBBHCCFEEDHDFGEGAFCFCACABABCGDEDAHEDDDDGDGFHDHDABFCFDFAHEEBEBEHEAA,False +899,3.0,3.0,2.0,3.0,3.0,3.0,8.0,3.0,BCEFGHGHGAGBGBGDFDCHEGEFAADG,False +900,16.0,24.0,17.0,15.0,11.0,13.0,13.0,18.0,DDCDADAECDHHHCHADDHCHCBCADAECGHGEAHFHGBBHDADAEHHFHGACACFCFBEBEDCGCGBBBBGEFFHFBBGCGBABABAHFEFBBECCHGFDFBFAFAHBBEBEACDGDGCBHBGBDB,False +901,25.0,30.0,29.0,16.0,34.0,19.0,24.0,19.0,FFGCECEBBBCDCBFEEEECGCABAFEFGHBDAACECGHDFCHBFBGGGBGHCHCBCECBGBEFDHBHBHCHAHAGABABGEGFCFBEGEBBCBCDHHHCHCHDBDCFCAEDHGAGEBEGEBEDEFFDBDEFBCEFEAGGFGEGFBFHHACACAEAEAEBEHEBAGAEAECGABADDDAECECFAAEDDAGCECBG,False +902,24.0,23.0,19.0,24.0,26.0,27.0,19.0,14.0,FAAAEACAEEEGEDAHEBADAGGHEDCABGFFDFDFEBEBEDEDGAHFDGBCBFDFGECFBFGFBFEFCFEDADBEFEFACACACAHADBBBEHAHBGBFAGBEEGGFGCGCFAFDFEBHGCAAGDGFHFCFCHCDCBFBGBCBEHFHCHCBEDGDACAEBDBHFHEDDDDDEAED,False +903,29.0,29.0,25.0,18.0,19.0,26.0,26.0,24.0,GABBEDADAGFHBHFHGCBCBDADGBGDGHEDBGBGDAEBEAGFGACEBEDADFFFBBBCFCGAFAHEHEHGBAAAAAAGGCCHBGBABHEEFHFHAHFBGCHDHFEBEGEAEDFGCHBHACADBHGDGCEDFFHFEFBCBABAHAEAGGFFCFAHADGDGCBCBCGCGCBCBCFHEHDFFEFHFCFABCHCDCAC,False +904,6.0,3.0,10.0,6.0,5.0,4.0,4.0,1.0,ACGCFCACDCHCDDDEDCGGEFBCBCBFGFEEAEDCAAA,True +905,3.0,18.0,9.0,11.0,14.0,16.0,4.0,13.0,DCFBBCBEBDBFFEFDCGHBHGDCFBFDEHEFBHBFEFHFHFGCAEHFAFBEHEHEHCACHGFDCBEFEHEBDBDBHBDEDEDBCBFB,True +906,16.0,25.0,37.0,22.0,24.0,10.0,28.0,28.0,DFDCDCEAEHCHEACBHBGBHCCGCECADDDDDDCHHHAHCCCGDECECEBECHCFCFBHBACGCBABCBHGEBBBHGHGBCBCDEEAAGAGDHFCCEDEDGDGDGBGHHDFFGEEBFAGHGFCBBGEHHBCBDBABCEAGACACGBEHEHCFDHAHEGGGHGHGACEDECHCGCGCDHFHBEGEDBCGC,False +907,25.0,18.0,28.0,21.0,19.0,32.0,30.0,20.0,GCGCEBHGCGCEDDHHGCCCCGHGHDHEHACGGGBGFGBEACGHGCFDFDCCCHCFDFAFAEAGABACAGACEBHBFGFBFBDHCFAFGFACAGDEHCDBGHAHBBDFDFCFAEBDCGFAHGHGFGFGBADFEFHBDADABBEAFHDDFDFGBGDEDEFAFEFEFGFAFDFEFCACHFHBEEECGCGCAAEAC,False +908,28.0,27.0,16.0,15.0,23.0,29.0,25.0,24.0,FAFEFGFBABHFFBHDCCGAABEBCACAEFFCFAGAEEGEGFGFDFHFHBAGFGBGDHBHBHBCGEGFAAHAHAHAEGEBEAHABCBDFGFGEGBFBHBDBFBFGFGHGHBEBEBDGHGFAFCHADEEECECFBACCBCDDHGGEHEGCAAFAFBDHHHDHDFDADGFAAEAFABEECGHHDBEACB,False +909,22.0,23.0,20.0,21.0,31.0,23.0,29.0,28.0,EAGGGDCHHHHCDDEDBCHAEDGBGAGADBHAFFHGBGBDEGEGHGAGDBEGAGCCHFHFGEGHHEAEBDDDDADHCBBBCACFCGAGECEAEFEGEDDAAEFEHBHBGBFCFCHGBBDBFBFDEAEAEFCDDEGFGFCECAGHGFGFEHHDAFHFHGHGHFHFEEEHAFBBBEAECGCBCBCEEAHACBFDFEHEH,False +910,35.0,20.0,17.0,22.0,15.0,17.0,23.0,20.0,BABABADGDFFFFFADHEEAEHCBGBGDGEGCACHEFAAHAHAHBHGHBABCBCGCFDFAFCFCEAEHEDGFGBAAADBGADADBDBECGGFCBDBHCAADAHAGADCGFGFGCGCEDAAEAHDEDBAGFGBADDDCDHHHCHAHDEAHGFAEAFBDHAGAEHBBGCGA,False +911,20.0,22.0,16.0,16.0,19.0,34.0,24.0,21.0,HHBBFFAHAHEFAFCDBDBDGCEEBFBDCCBCHDFAFDBDBFCFAHGEDBGFFFDFHACEDGDBFBFCECHCHBFAFADAFFFFFFFGFBHGHGHGHAFABACHCFGGGAFHFHGGGGFAFEEGHGEEEGECDGECBCBHDGDGHEHDBAGEBEAEABABFEGACHEBGFAF,False +912,14.0,22.0,22.0,16.0,10.0,16.0,13.0,11.0,GABHDHAHACDCBFFFECHFHEBEGABCEHEBBFBACHCHCACABEFFDBACDHFADAFBFBGGCGCGCHFBFCGDFAFGBCBCBDHDGDCBCBCGDGCGAGABCBCACEDFDEEFBBDDDEDB,False +913,20.0,27.0,29.0,23.0,22.0,31.0,29.0,18.0,GFGEECFDFAGEFHFACDEGCGCGHGHDHDCGCFDBAGAGAGDGHFDFBFGFGAGHDAGAFABDCFFECECEFFDCDCBCGDBABFFHFDDDGACHHDBEBEBFCEEBEHAHECBABGGAGDHDCEEGFCFBDECACAFHFAFACBEAGGGBGBCBHFCFCFCFCHDFAEBBBHBEBECFCHEEGBGBFCDBDBDBHGC,False +914,12.0,9.0,6.0,2.0,6.0,6.0,2.0,13.0,BFBHEHEHBADCHBAGFHFEBHAAACABHBHAAACECBBACGCHFHAHAHEHEFFD,True +915,10.0,12.0,24.0,13.0,16.0,14.0,13.0,16.0,CEBDBDBDCDCDCDBDAHHBFBFCFGFGEDFHCBCFGECFCEBEBHBCCFCFDFEHAFBHAHAHFCACHCECEHACBCHCFEDEAGACDCHCGAHCDEGGHEEFHAGGGECEGEHDGG,False +916,4.0,4.0,9.0,4.0,6.0,12.0,3.0,4.0,CECDADFBACFCFDFBFGFCFGHCCGBEHEHEHEFFCACBEFFFAD,True +917,15.0,18.0,12.0,11.0,16.0,11.0,18.0,15.0,AEAEAEAEAHAHAGEEFHGHBHBEDABABADHGFGDHBCDDFHGBEFFFAFGGHBDFCBEHECECGFHBHEEGDBEGEBBGDCDHDCACGFGHGCABABHFACCCCBGBGBGDGBE,False +918,14.0,16.0,12.0,30.0,16.0,18.0,12.0,16.0,DHDAEBFADADADADADGDFAFHFHDEFGBGBGBGFHCGEHECEAACACGCDDDFEBEBHBFAFHCDDDDFCFDFGHCFDHEFEFDCHBBBHAEDEDBAAHCEFDCDBDFDBEEDBDHEBDHDGFHDHEGGGCB,False +919,5.0,11.0,3.0,9.0,10.0,8.0,8.0,5.0,BFBHEEEBCBHEHGAGAGDDBDEEEHABFCFBAGDCDGDBDGAFEFEFDBDGGFBFBHE,False +920,5.0,0.0,5.0,4.0,1.0,1.0,4.0,2.0,CGAAFADHDCACGCECGDGDHA,True +921,24.0,17.0,18.0,26.0,23.0,31.0,24.0,25.0,EDEDCDADFGBABAGGFCFDFEGCGBHHECEADGDEDFDFDBEGEFCAGFEFEFDHEADHCHAHFHFHEGEDDDDBGEGEFBCDCEAAHDBAGHDHFGGHEHAHAHAHFHFDFBGBHCGAGFEFEFADACAFEBGCCDBEBADAFBGCFAFCHCHAFEFGCGBGCAFABCDAFBFBHDHFHEGDGHFH,False +922,12.0,3.0,17.0,8.0,6.0,8.0,19.0,16.0,GDFCHCHAADGBHCHAFEHCHCBGBCHFACAFADGGGGGGCGCAADHEHECEAEDDCCEGFGFGAGAHHGHGCDADCCHHGCGFHFHGC,True +923,13.0,7.0,15.0,17.0,15.0,11.0,14.0,5.0,GDDDHCCBCDADAEABADADGHFDCCACAEAGGDEEEDFHFBDGCHBFBFDGGBCDDDFCFCFEEGCFEFADADACAGGGGEGCCAEBEHEGEFECE,False +924,19.0,22.0,14.0,20.0,28.0,12.0,19.0,18.0,CGCDHBFBHGEBEADBDGDGDCBCDCHCEBHGEGEHEGDFFCEAEDGCGEGFDEEEEEBABCBCBCBCBGFDFAEAFDHDHEHFDAAHHHHEAEADAFEFEDBABDHEFEAGCBBFHDHBHBGBADHEEDBDEGBAEAGGCGHBEGGAAAEA,False +925,20.0,23.0,18.0,19.0,19.0,27.0,21.0,22.0,FEHEHEGDGCBDBHBEBCAGACHFEFHAHADAFGBGFFEGECEHDGDAHAHEDCCEAGFDFEGCCBGBFBFHDADCBCBFBCCHBHAHBDCECDFHFGFADCFFFFBFADBGGHADFDBBCBGHHHEHEHBAEAEFGBHBHGAGEFEFGFGFDCDFBFACAGAEADGDB,False +926,8.0,4.0,5.0,5.0,6.0,5.0,4.0,8.0,FGFDECECEADFBFBHEHAHADAHAEACGDADHHHBHFACBEGCG,False +927,4.0,9.0,2.0,4.0,9.0,4.0,11.0,2.0,GHGBGDGBGBEAGFGBBBBDDEBGFGEGEDECEAEAGBFCEHFAE,True +928,19.0,13.0,20.0,26.0,25.0,21.0,11.0,20.0,DDDFAGCFCHADFCCECECFBEHDBEBEDEHEHCFAEAEAEFDFBFADAEAEAEADHDFDFGBGBADEDBHCGCFCBEEAEHECFHAGACCCDDEDHHHHAHDDDACGHBACFCFGDEFEBHFHFCDDDHDACECBDHGHEEFGBGFGFEDHFBA,False +929,31.0,26.0,25.0,22.0,30.0,19.0,16.0,16.0,GADBEEEAEAHACCCCFGFEHBGBGCFCFDDADGBAAAFEFAABEHADFDFACAHBHGEFBAAACFCGABEGFABGFGEGFBFBEBFDEDEHGFEECHAHADADADCHEHEBEDABHBEACADBDBDGDGDCDCACHEHGCEHDCEABCFAEDFDGCEBFBAAEHEDEBCBCBCBCBEEAEBCHC,False +930,5.0,6.0,16.0,9.0,2.0,8.0,6.0,8.0,FCFCBBGDGDBABHCHCGEBEDDGACFCFCFCHCGCABHCCCCHFHCAGFHHCAFDDDDD,True +931,13.0,10.0,13.0,5.0,17.0,8.0,8.0,11.0,AEAEAHAEECBHBHGHAEBFCEEAEBEGCHBFBGEGFACADAEGEDBFCCHHBHBHFHCGEGHDDCDCACAEAFBCGCFEFECEA,False +932,13.0,15.0,7.0,16.0,20.0,10.0,5.0,18.0,AEABBCHEBEHEFEDEAFBHBADFHHDBDEHBABABABACDCFEFHFEGGACEDEHEBBAFGHCEDEDBGCHHDBDBEHCHDADGDEDEDHFEEEAHAHFHFHD,False +933,4.0,6.0,3.0,4.0,2.0,6.0,4.0,5.0,AGAGAHBEEDCGBGBCBDFDFDHHAFBFHFCBHF,False +934,5.0,12.0,3.0,2.0,5.0,4.0,9.0,11.0,CEDBABACFFGFAEAGCGBGHGHBHGHEBBHBHGDFHHHHBEBEAGBBBGH,True +935,8.0,6.0,1.0,11.0,7.0,1.0,14.0,7.0,GEBHGHGDBAEEDAGGEGDGBGBHHHHDDAAAAGDGDGDADABCEGEHEDDFGGB,True +936,12.0,13.0,17.0,16.0,15.0,22.0,16.0,19.0,HHEDDDDGDGAFACACHCFEEECACADBGHGFFFFFFEHEHCAGBDFEFDFEFEHEFFBBABFCHEGFGDHBCBCBEEAHCCECDDBFBHCHFHFHDEDGGGDGBGHCBGAFDGDGCAHBCCHGHFHFAA,False +937,3.0,4.0,1.0,4.0,2.0,0.0,0.0,2.0,ADDEDEHBHBACADBB,True +938,5.0,10.0,7.0,7.0,2.0,7.0,13.0,13.0,FCGGGHHAFEFBFBGBABAEGGGGCFCFHBABHHDHDHFHACDBBGHGDGDHCBDHCHGBGDHC,True +939,0.0,2.0,2.0,0.0,2.0,1.0,2.0,1.0,CGEGEBFBHC,True +940,15.0,12.0,17.0,12.0,18.0,16.0,21.0,10.0,DADACBCEGEGCCAHFCDCDAEACDCFGDAEBEBEACABEGGGABACDFDCGGFDDHCGFGEGBCBDEDGHGFEFBFGGCBCEEFAFGFHFAFHGHGCEFEBHBHGEGEGEFAFAHACBHE,False +941,21.0,9.0,18.0,19.0,23.0,21.0,20.0,26.0,EGEDHBHBHGHGHCEAAGBHBDDDGGGDGFGFEFGFGADHEFEAEAFAHAEAHBFECDCAAGDFAFHEHCCDCEFHFHFAEAHACFCFCHCECEHDDGDHDHDADEBHFEGAAEAFBHCCEGGDEDBCHADAHFBFCFCGGEDECFHGAGHECEHFH,False +942,23.0,23.0,25.0,23.0,16.0,18.0,18.0,24.0,CAHDBDHDEGCADHGHGHGHFCDCHCDFGEDEDHDHBHFDFEEADAEABFFGFGACFBBCFCBBFAHCHCEEDCCFHACACABHBFFFDFECACHHEGDGDEDBHBCBHBHADABHBHBCGHACBCBEBABCGEEFEAEAGGCDDDDAGAGAHBHDGBCFGFDCAGACAB,False +943,9.0,5.0,6.0,3.0,2.0,3.0,4.0,6.0,DBDHCFFHCEAEGBGBGAHCHBBAGFCAHAHACADACA,True +944,1.0,5.0,5.0,2.0,2.0,3.0,5.0,5.0,EGGDGHCBBAEGHGCFCFBHBHBHCFCD,True +945,23.0,12.0,17.0,23.0,21.0,25.0,31.0,23.0,AHAHBHBHCHCEDDFCACDCDFGFBHBCCGFGHGAAHDEEGECFAHAHFHDHEADFGCGCGFGEADBEAEBEDDBCBHAAFAFAFDGDHABAEHDHGEEEHDADGFGHGFEFGFCFAFHFEFADGGEGEGECFDHCHDFGHGDGCAAGAGEGFDBGCEBGBGDEDHFFCFGAGDG,False +946,7.0,6.0,9.0,5.0,3.0,13.0,9.0,7.0,BEBECFHFHAHGCAABCCFGBGFFCFGFBFDFGGAGHGFFFFDBCGHHCHCDDADAEAC,False +947,12.0,14.0,22.0,9.0,8.0,15.0,19.0,16.0,GGGGGADFDBBBCHGACAHBFGHGHGFGCCFDACHGHEFFBCBGEGDGFHHHBHDGDCCCCGBFHACACECDCFGBHBHBCEFECHCBCBCHGFGDAAAADAEEFCFCACFFEHB,False +948,23.0,29.0,24.0,18.0,9.0,25.0,25.0,32.0,BBBHGFAEAEBEBCFCFAFAFCFDFBHBGCHFAEGDACAGBHCHFDBCBGGCCBBHHABDCFGHBDCDBDGFBCAFAHHGHFHEHACEGDABGBGHABABGHHHFBFCFHFABAEAGACBCFHHBABCBCBCACFCHGHCHBGBHDDFGAAFFFEDDDGDHDHGHGHGHDHGHGHDCDCGFGFEA,False +949,7.0,6.0,5.0,7.0,7.0,6.0,6.0,12.0,HHCHADDCGBGFFHDHBBCHCHBFADAEAGAFAEAHBHEEEEHHHBGDGEGCDFDF,False +950,24.0,23.0,22.0,11.0,20.0,30.0,30.0,14.0,EHFBFBFBCCFCAAACEGBFAEEBHCHFHEAEAGBGHGHGCGCFEFAFBEAGAEBGDGCGHGHBBGBGBFBFDFECAGGFEBEGCAEBEDGHAFBHBFBDGDGFGDACCGCECACAGFCECHDFBCGCGFFFGFGCBCGABADFBHGGFGDHDEFBHCAAAAAAFFFFFDEEAE,False +951,16.0,19.0,15.0,15.0,20.0,28.0,15.0,17.0,DGGFECEHGHFHCBCEHGDGCBCGCEEFAFAFAHEHFAABHEGDGAGBGEEBHDHBBCBCHFBDBDBHEDFCAEAFFFDFDFAGBCBDECFFFEFDFBFGFGEECECEFEFEDHGCDAHAEABBDGFBFHHBHDAFHFCFAFABA,False +952,9.0,0.0,6.0,3.0,8.0,5.0,2.0,3.0,EFACCCFAAAAHFFFDGAAEAEHGHECECEDECEAD,True +953,2.0,1.0,1.0,1.0,6.0,2.0,3.0,1.0,ECEHDAAGBGEEEEFGF,True +954,11.0,9.0,7.0,13.0,13.0,4.0,8.0,8.0,CADHDHDFDABBEACAFDBBHFHGAGECBGEGEGEBEHEDEAHBGDADADADFDEBEDDCAABHEHCGEGECC,False +955,17.0,19.0,17.0,18.0,12.0,19.0,16.0,32.0,GFGFAAGFGAHADGGHGEBABFEDBHBDFHHHHBGBHDHDEAACBFBFBEAEHCDDGDFHHEDGHGBGBGADHFHDHCCGAEACDCDCAHAHFHFHFHDBDADHCCCHBACACBHFHFEFECACGEBBFDHCHDHBHEFGCECHFFBHBH,False +956,21.0,23.0,17.0,24.0,20.0,16.0,15.0,22.0,DADEHFHDCBCBCAHGBGFDFDGBAFDFDHHFDBDBACACFEHEAEAHAEEBAGCHCFCFAHAGDGDADADHHGHGECCFCFGFCHAHGDGBCCHADBDEAHGCFBHBHBHEEEEEHEBEAEGDBBFBHHCDCEBBBDBDBAADGFABADFEEGEDDB,False +957,10.0,10.0,8.0,10.0,12.0,10.0,10.0,2.0,FGFBFDFCGGFGABBBDGAAAFHFDGDBDGDEDECECECECGBAEHECGDACEBGBDFCAEAFFEDEBABAE,False +958,23.0,37.0,29.0,27.0,20.0,20.0,23.0,19.0,ADBDBAFABHBADGGCCCHFHGBBDDCACACBBAGDHDHCHFECBHFEGEBEDCCFEDEFBFBCBCBHEHBGDCDGBGAGAFFGCGEGAADACADBGFEDGBGFDBHBCAHEEFFDCDADBDBACDCDCDBHBHFEFHFDBGBGEFHFHBACECEDEBCBCBCGCGBBACAGEFBFBABGDGDHEHEGBCDCBHEAAA,False +959,12.0,18.0,18.0,8.0,12.0,10.0,17.0,15.0,BEBEBGBGBHBCBCECGCGCDCFGGHGBCHEACCCEFGAAAEHBHEHBGBHAEABHGFCFCDCEABACAHEHCGCHFEAEGDBDHDCGFDCDAHBHGFDFGGGHFBBBAF,False +960,6.0,8.0,14.0,11.0,10.0,8.0,6.0,15.0,EADADHGFDEEHFHDHBHBHCECDFDBDECHFFAFGFBEDECBCECHHHHGCGDGDHCCCCCCEEDHHAHABCGFABB,False +961,20.0,29.0,25.0,20.0,25.0,26.0,26.0,18.0,BHBEFEABGFAEGDGDFFBDHDGBGBFFFHEEEEEDFAFADABGGCGCBCBAFCFABCCHEHGDDEDEGFFAAEEEEAGCGAGHGFDCCBCHGACACEDHGHGAFBFBFAHEBEBEDGBHCCEAEADDDHDCBCFHAHCHBHBFBFBGGGBHECGFGECBCBCDHDBBFDCACACBFGFGEGCDEBFBF,False +962,27.0,19.0,27.0,18.0,20.0,32.0,29.0,28.0,GEGECAFAHHHHEAEBDBDCHHGHFEFHDBFAFBFDGDBCBCGHGHFCFCFCFDEGADHHCCADADAGEHEHGACCHGHBHEHCHCHFECGCFAFBFAFGFBCAEFCDHAGFBFHGEGAAHGFGEDEACDCFHDDCDCFCHCGCEDGHBDAAFAGBFBFHEGAFACADEFEBEGGGCGCBBFBFGAGAGAFABAGFBEHF,False +963,18.0,20.0,27.0,19.0,14.0,17.0,15.0,25.0,FFACCGCGCDDHCHCDGGGEHFBCBHFCAAAAHAGFGDGAGDGHFBDEDHCBCACACGCGAFEBBCECEAEHEHBBCHHHHAACDCDBDFCFBFBHCHBHDGCEEEHEDGBBBFEFHFHDCDBDADAHFBCBABDCEAHHDACFCGHBHFHDCFE,False +964,12.0,10.0,8.0,9.0,12.0,10.0,10.0,9.0,FGFAEAEAGADFEECEHBBBAHAEBECECAGGHBAAGEHFHDHAEFDFECDCBFBFBABDDFDGGFGCCCEHAHBHGDGD,False +965,17.0,22.0,24.0,31.0,26.0,22.0,22.0,27.0,CGCEHFCFCEBDBDBEHEHGHGHFABABHEHFBEBGHDHDFCBDBEBGGCHCFDFHEHDHDGDFFBCAHAHGEEFHBHBEBADFFAFAHDHGAGAHEDDHDEBEFEBEFHFHACADDDFDEEEECCCDAGADBGAGFEHBGGHDCCCDEDGHCECDDABFBEBCGEGCGCFCDCAAEDCBGHGDFDGDCDF,False +966,27.0,18.0,26.0,14.0,26.0,27.0,37.0,24.0,AACDCHCFGHAHAGAGACFHEHABFHFAGHBCBDBFBFBABFHHHFHFCEDEFACHCECFGFEFECGDGHGCGFGEHECDCBCBGBECEDFAEECAGGFAFBHEFDGBGEGHFEEGEHCGEGDGDGDFCCCCHBAEACHGHGAGHGAGEHEGEGBCAGGGFABHDADADAGAFHBEDCFAEECFGFGFGCGABEFGABA,False +967,19.0,30.0,23.0,20.0,26.0,19.0,25.0,21.0,BBABCBGGAGFDFGHDHEGBGCGBBAFDCBCEFHDCDFBCBGEFBHBEEEEEBADAHAHBGGGEDBFBHCCCECBGHDHDFGBDCDFBEHECGBGBGFCFAHEHDGEGEFDFDECCCHCHEGEGHGBCEAGABEBABABABADADABAEADCCEFBABFECDFHFHCHFEFCGGEHEHGDADH,False +968,22.0,15.0,29.0,26.0,37.0,20.0,22.0,24.0,AEGBABEFGGEGDHDHAHEFECEFACEEACHBECFBABCDCACAHGHDEEFECECDAAAEHGHGHDHDFGFHCADFDBDEDEAEDEDEDEDGGECEABBGFADADEHGHFECBCAEAEGECECAGDBEGAACCCCCCBHEGECDCDFHFHFHFHFCGEGHBDFEBBBGECHDEFEHHGDADCGHGDDCEFHFCFC,False +969,16.0,6.0,14.0,15.0,9.0,8.0,13.0,13.0,HHHHFEFDDCAHGGEGDGDCBBHCCDADGGHAAADADFDFDGDGDGABEBAFABECDHAAFAFEFGDGCHEHCDCGCEEHHHAEACCCCBCGAA,False +970,21.0,25.0,9.0,17.0,8.0,13.0,18.0,16.0,GBGHGACACAFHFBCADGGGFGFGAGAGBBDBGCHHEHEBFDEABGDGDGBHBCDFFFFHFHAHBDACAHDHCCGAEADBHBDFABABABEBEAECGGBHBHDFBBBBAFDDAGBHHABDDADADBE,False +971,9.0,10.0,11.0,9.0,15.0,9.0,14.0,12.0,EAEDFCFBFBAGHGHGDGBHBGFHEHCFAFAGHECGCHCADAHCEGDGCGBBBBDBDEGFGCCFHEEEHEDEAEDBCGHGCADHEFEAE,False +972,18.0,16.0,12.0,13.0,15.0,19.0,12.0,21.0,BEHFBBABAHGEEAEAFAFCDEHFHAHCGCFBEAAFGCABHHFHFHCHBGADCDHDHCHCEEAGBFDFGADFFFFBFBGDGAGAEADHDHDAEEEBCBCBHBDEEHGFGFBFBDEHCHGHAHFCAD,False +973,27.0,25.0,26.0,28.0,24.0,17.0,20.0,27.0,HCHEFEACGCFDFGCBCHADFCFBADCGHBHCDDDCBAAHAEEDADGDGHGHGHGDAAEBEHAHGDADADEBEHHCEBADAHHHHCHCAAAHBFBDCGBFCHEEFBFBFHAEADDBFBFBDGDEHEHBHGCGAHACECAFBFBEEEBECEFDCCABDBDEDEGAGADEDEDCFBBACHGGFGBGCGDADCHCBC,False +974,2.0,9.0,5.0,14.0,10.0,16.0,13.0,8.0,HBEGFBDBDHEEFHFEGDBFBFBGHFAFDFGFCFDBDBDHDHBGGCFFEGEGECADGFECEHFGDCDHDEDGFGFGD,True +975,7.0,10.0,11.0,8.0,6.0,8.0,11.0,11.0,CECFCDCHGGGGHGAFCECEAECDCGHHBADHDHDBDBFBFDAHGBBBBBBGCFFFAAEHDFCHGAGHCHGE,False +976,22.0,16.0,20.0,24.0,18.0,27.0,21.0,14.0,GDBDHEGEBFHFHDDCFCDAAGEFBFEDBAHGBGBGDFEBBADGHGFABAFAFDCDCBCAHADDDCAHECCDAAFAFGHCCECFGECECEFDHCHAHGBGBGDECECECEAEAEBFBFGHGHAADDFDBDGAFCFBHACAEEFGFAFDFDFGFGDCDGGFFF,False +977,16.0,17.0,23.0,22.0,27.0,15.0,19.0,22.0,EEGGFDFHCHEEAEDEHEHGCEFGBEBEBHBDDCBAHAHDGDAEGEGDHFECBDDDHDCGCFAAAAAFCEHBBEECEFDFDBDBCCCCEFEGAFFCFCFCEBEAHAHAHAGGHGHCHCBGEDBDGEEHCDGHBCBDAHFHBHFGGDHDEDAGECECBCDCG,False +978,5.0,8.0,11.0,18.0,14.0,13.0,11.0,18.0,HFHDBAGHGEFEHCGGEGDAAFHFEFEFDHDGCECHHEHEDEDHGHDFBFCDHHHAHEHBCBCBCDCDGDECEDGDEBFGDCDEBGHFBFDCDFHFDA,False +979,22.0,10.0,19.0,14.0,19.0,26.0,19.0,18.0,HBGDGHGCGBGEFEAEFBDEHEAAHGGGGHDHDHFGEABAFAHEHCACFFDFDFAFECGCDCDCDCFCHCFCHAHFDCBGAGDEHBGEAFAHAHEFAGHEAGACEEEFFFFEFHFBFCFBACGCAFAFCBEFEGEFCGBDDDCAAAH,False +980,9.0,10.0,16.0,13.0,13.0,13.0,17.0,6.0,CDCEBDGFGFACEBDHFCEHACADBDBHBCBGACCECEFEFGFGACHCACDEEGGGEGEGDGCFFFGFDBDFGGAGAHACDDDDGEGFCFCEHBBEB,False +981,19.0,23.0,15.0,12.0,16.0,18.0,17.0,17.0,ECEDHFHFHFAGAHBHDAEFGFBEHGBGBCBHBCEDGDCBHEAGADEGHFHDBBABEBAGAGCCDADHDCGBBBEGAGAGEBBBGFGFCCBFBFEGHAEGHFCFCFCACEDHDAAAAAHDBFFHFEFCBCBEBEFHA,False +982,21.0,16.0,13.0,14.0,20.0,12.0,19.0,12.0,EBEBGBGDGEGECHCHFAAEHBCAEBHBECECACGCDCDCDBABAFABGHGHAAEAHABDEDEFHFGBCDAEAGFGECDHGFGDDDEHAGGGEGBCFDFAFBEGECEHAFDFGABADAGAEBHFAEB,False +983,22.0,16.0,20.0,28.0,16.0,18.0,28.0,14.0,CGCGBDCDCGHACGFDFDGDBDCFEFEFADAECBDDDEAEAEAHAHABGDFAAGFGFGCAAGEDEGFDFDCGBGAGBGHHHGABCBDBDFDFCFDFGCAHAGACABAFEFAGEEDEHBCCHEGBBBDBDHGEDCHCEFAHHGCDHGGFGDGDGDBEGACDCD,False +984,26.0,22.0,19.0,22.0,24.0,27.0,32.0,24.0,ADHHEFAFADABADAFABCGCGAGFGFEDADABEFHFHGHDFGEGADCCFHHHGHGEFCFCEBDGEFEFEGAFBFBFAHGBEBEAGDFAHABAEGHGCECEHBHBDCFFHBAAGAEAGBCCDCDHDHDBDBGBEDDDCBBFBGEDFDHGEGEGEAFAGGBGBHEGBGFGDECHFAFEHHFCGCGEGCCHCHAAFDG,False +985,7.0,9.0,7.0,9.0,13.0,11.0,7.0,5.0,FCBCHEDFAFHEGBGFAEAEAEAFGDGDBDBABAFGEGDCHCHEEBFCEEHEBEDEFFDFGBDBCCFD,False +986,8.0,13.0,17.0,13.0,13.0,11.0,14.0,10.0,HGEDFDFDFDHDHDHDBFEFAGAEBEDGDHHFBBEEABBBFBHGHCCBCEEGECFBACDCDAAGCFCGBGFFEAGDGHCCDGEGCGCGCHCECBCACEB,False +987,20.0,12.0,18.0,25.0,18.0,18.0,21.0,30.0,AAADFHFAADFECBCECEHEHADCDGDGDCFHFHGCGCGFGFCFHDCAHEEGDGCECHCHEBFBHGHGEFHBHFGDADEDHDAFADEHBBBEGEFHADFDBCGDHHGHGHGDGDHDGDFCFEGGFGCAAEAEBHAHADBHEAADHDCECHDADHCHBHFHAB,False +988,20.0,13.0,12.0,16.0,10.0,14.0,25.0,12.0,BBBCHGHGAGFGHGDCACHCHCAAAAAAEHBDBAFDGDGDFCGGEBAFDEDEHEDGDEDADABCBFDGAGAGHGAEDBGGGGDGBFBHAAGBGHDFEFGAEECCGFFBFGFGHCHAFFCACD,False +989,12.0,14.0,12.0,10.0,10.0,5.0,11.0,8.0,AEFEBABAHACGFBABGBGDEDGDEBBCBCHCECBCACDCGHGHGEACFCBBBEFGDDDCDBDADGEHAACHEGAGFBEHAH,False +990,22.0,22.0,18.0,21.0,13.0,23.0,11.0,18.0,AHAHEFFDDCDFGHDFDECHDHABEBCBCEAFBGGGGFCHCBCHHBEDFAFABCHCBCBCBABDDGHHDBFGEEDADFECGBAECEADADADAFFDFBFBFBFAHDFDBHBDEAEFHFGAHAHAHACCBBABGCGCFHFAFDFDEBCA,False +991,10.0,6.0,7.0,9.0,6.0,4.0,5.0,5.0,FDCBCGFHFHBBBABGDFDAGACACEEECAHDDGDEAAADADAECECHDBGH,False +992,9.0,13.0,4.0,15.0,7.0,15.0,17.0,13.0,DEAHFHGHBEGEBBGFFFAFDFDHDGDGHGHFHFDDDCEGBACGDBDGDEHEHGHGBGBGHFBABABFFFAGADHDGGGHFACBFEDDBCAFB,False +993,1.0,1.0,4.0,3.0,4.0,6.0,1.0,3.0,EFEFEFAFCEGDFHHHDFCBCDC,True +994,16.0,14.0,21.0,15.0,11.0,19.0,16.0,24.0,AHACCCDCAAFBFEFBDBAAGAHHCHDHEHAHEHEBGAGAFHFCGCEFEFEDACHCHCGGGFDFCHCDDDHDHAECHGBGBEHCFBDBGGFHFGBAFHFCDADCFCBCBCEHAHFHBCEGGGFAHBHDCDFHFGDB,False +995,7.0,6.0,13.0,6.0,12.0,13.0,4.0,9.0,CEAFHCHFHECCHEACFCFGGAGFCHCHFAFEDHHCECFBDBDGECHDFEEEEEEBABACFCFDFDFBAB,True +996,4.0,9.0,13.0,8.0,5.0,3.0,3.0,5.0,AGAEADDCACBCBCDCDEHECCFHEDBCBCDDDFEBHBHCCCBBFHGCGB,True +997,3.0,1.0,1.0,6.0,4.0,5.0,7.0,3.0,DDDFHEHCGFGFGFGEDAGAEHFDEDBGAG,True +998,18.0,17.0,15.0,15.0,11.0,15.0,12.0,20.0,EBCFCHHAACHCHCHGBCBCBCHDADAFAFEFDFDGHGHCBCFFHCACDFAFAHAEAEAEFEBCHAFBHBFGAEDBDHDHFBCDEAGABBHGADDBDBDHHHEBAGCEEHFHBGGDGFGAGDB,False +999,6.0,13.0,8.0,13.0,6.0,19.0,12.0,12.0,GDGCGCHCAFGFEFBFDEDHFBFBDBGFDADBFBACGBGDGEFBHHHHBDAFGFGBGHCFFECEFEFBAHFDFBFDAHCHDHCHDFDGB,False diff --git a/tests/results/nb_gm_002_2back_240trials.csv b/tests/results/nb_gm_002_2back_240trials.csv new file mode 100644 index 0000000..1c50201 --- /dev/null +++ b/tests/results/nb_gm_002_2back_240trials.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,ralph_skewed +0,30.0,39.0,31.0,30.0,32.0,24.0,27.0,27.0,False +1,33.0,23.0,27.0,32.0,37.0,34.0,25.0,29.0,False +2,31.0,20.0,37.0,28.0,31.0,32.0,26.0,35.0,False +3,27.0,32.0,39.0,24.0,25.0,34.0,35.0,24.0,False +4,34.0,24.0,38.0,28.0,31.0,29.0,28.0,28.0,False +5,29.0,24.0,36.0,31.0,32.0,32.0,31.0,25.0,False +6,25.0,38.0,28.0,30.0,33.0,30.0,26.0,30.0,False +7,27.0,30.0,30.0,29.0,32.0,26.0,33.0,33.0,False +8,24.0,36.0,32.0,23.0,30.0,29.0,35.0,31.0,False +9,35.0,34.0,30.0,29.0,35.0,26.0,23.0,28.0,False +10,30.0,25.0,33.0,31.0,27.0,37.0,30.0,27.0,False +11,28.0,28.0,29.0,26.0,28.0,27.0,34.0,40.0,False +12,35.0,27.0,30.0,29.0,26.0,30.0,36.0,27.0,False +13,38.0,27.0,31.0,27.0,34.0,23.0,27.0,33.0,False +14,29.0,30.0,28.0,35.0,19.0,30.0,37.0,32.0,False 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+9,11.0,23.0,19.0,24.0,13.0,20.0,28.0,13.0,DFDDFDGFDGCDFFDFEDCCDEGDAHEEDGGGGDAGHFBHFGEDAFGCHGFDBCDBDEBCHDEBGEAFBCHEFEAFBHFCCGEDGADGBCBCDACGCCGFAGBBDCGDBBBEBBECHACFAGFBGABCBBGFHHFHHFGHGGDGGBGBCDB,False +10,10.0,15.0,13.0,9.0,5.0,13.0,10.0,23.0,CAHCFDCFBGFGCFHBHAGHABAAHGFBAFDFBDBHDHCBGEFGDCBDHDEABHHHHGCFCEFCDHCFHBHHGHHGFHGBBABCABCABHEHEFHDCH,False +11,29.0,21.0,32.0,27.0,25.0,25.0,8.0,18.0,HEFAEFGCBEBDCBEADAADADCADABDHHFFEDFBCHACAAFBAFDAFDBCCCFDCEACAACEABFDCFDCFHHFBHDEFDAFCABGAEFDCDCCBCCDCDFAEFDCGCCECCBCBHDEGACBAHBEBEEFDBDHAFHAEAEECEGGHDBHDHCDEADEAHEHFEBFCBAHBHDEGAEFFCFCG,False +12,28.0,27.0,32.0,14.0,15.0,33.0,26.0,13.0,FFFAAFBAHCHHDHGCBBCEBFDGEGBFAACBACBACBAGBGBAGFFGFAHDGHEEFCAAHAHHECFBBFACFACAACDBCAEAHDFHFFCFFEFCAFBEFBFCBCABDBGGFECFGCBCDGGBGFDGDABBCCBEFBEFBAFDACGCCEHGAFCABDGEDFFDCFDGFGGCGGEEGCBGAAGCCCHC,False +13,29.0,16.0,17.0,15.0,16.0,11.0,15.0,11.0,CBECBEFBDDCDCAACAABFAGFEGACCECBEHBEGADFADFBBABCAHCABAABHEEEACEHHAGHABACGDHGDFGCHGCAGDAFAAFCCFEAEBAEDFDDGEABHAGAAGDGBAEDHHGABFEGDCD,False +14,17.0,24.0,25.0,11.0,18.0,20.0,15.0,30.0,DDCDHHAABGECDACBCCFHGEDGAHBABBHFBFFBCFHCHECHECACABHHBHEBHBHDCHCFBAHBFHBEBEDCEDEABCHCHFCHCAFBFBBHGEHGEHGHFCHACHCGGCGCDECFEGHEDFBAFGEFDAAHAHHGFHFABGEBGABGFFEFCEBC,False +15,8.0,6.0,1.0,3.0,4.0,2.0,2.0,6.0,EHBEDEHGEGFABBADBAHCAHAABDAHHABF,True +16,20.0,17.0,20.0,17.0,21.0,21.0,26.0,21.0,DEHCHAEHFEDFDHFCHGCGGCGAFBDDBDCFGEFGEFCEFHDHEFFAGDGDEGAHGFECFACFEEHBEHBGHBGHBGCECEDAHHBGFCCCADHAGHDEDBADGHEBDCHCCFAGEAFAABGABAHBAHBGHCACBEFEGAEFCECBGFDGFDGAGBAGBFG,False +17,12.0,3.0,7.0,9.0,7.0,12.0,9.0,8.0,ADGAGCADCFDFHEFDGHCEHAGGCDAHDCHDAHAFDAFEGFACFECFEBFGBAGAFFAEBDEHGHF,False +18,18.0,19.0,24.0,16.0,21.0,13.0,23.0,20.0,GGEGFBDFGDGEDAHGFBGHAGCDGCAAAHACECDECEBBEDEEDECDFDHBCCDHBHHACBACFHEAEEGHEGDEGAHBAFBEEHCBHCBGGFCGECGECBCAFCGHCBHFHHFHDGGAAEBFCBFDBCBECDCADCACGBHGEHGBFGADHA,False +19,10.0,14.0,15.0,8.0,25.0,14.0,11.0,20.0,EEEEBEEFHEHEEFEEGHEAFFAFHACGDCDDCFDCBDCBFFBCEAHEAHGCGGHGCHEEAEAHEAHEHHCCFGHABHGFGCHGCFDFHEHBBBDFBFBCEAEBHCDGCEEEHBBHB,False +20,16.0,9.0,19.0,17.0,10.0,22.0,10.0,24.0,HFGDDAFEAFEDCGHAADEHDBHAHDCGBAHBECEFFFFFEFEEDHEDCACEGHBGCFGAGGABDHFCHFCHCCDCFHHADFCFFCFFCBFCDHHHHDFFGHHDACDAFDACDCBHCHHAGHABHAB,False +21,6.0,10.0,3.0,4.0,7.0,3.0,3.0,4.0,EABBAEFHEFABAACHDCDDEFBEGHEGBDABHBBCBGEB,True +22,6.0,11.0,12.0,6.0,9.0,6.0,9.0,10.0,AEDBCDECBCHBCBBGFBGFHGEHACHAGAEFBDAECHCFHFDCCECGBCGECGAHGBHBHEBHDFGDE,False +23,11.0,8.0,12.0,13.0,7.0,5.0,13.0,9.0,EAAGACDACDHEEGGGGGBEGEABEAHGCHCCAFCFFGDHGDGCBGBDDEAFAADCDDCDDHBCGBCAFCBDDHHBHH,False +24,36.0,26.0,18.0,26.0,33.0,19.0,21.0,15.0,GBCHFHAAHAFFGBBEFBCFAEFDFGEGEEBECBEBBABBAEBEEAEEABGDBADBACFFBEFCECGACFADABCFDCDBCBBHDHHACGGEHDEGDEGAHAAFAAEDCCHHDDGDDBDGBDBDDCDAGAAFHEDHGDACDACDBGEEACGAEEBEHAFHBGAAAAAAAEEFBEDCDAEEEFGEGGHGFEAFED,False +25,11.0,17.0,16.0,9.0,15.0,15.0,6.0,9.0,CEEFABDBGDBFDFFDGADECBFCBCCACFABEABFABEGBEHBAHEAHEAECCFFCHDCBBBFGBAGCDFHHFBDFDCCHHEHAEBEGCCBFEECEF,False +26,8.0,5.0,15.0,9.0,10.0,7.0,11.0,5.0,ECAGCHDBBDCCDCGHBBEEFDHFEEEHBHGADADGFDEFGAFGAFCCCCCACCDCDGGECGECGEAGFA,False +27,9.0,11.0,8.0,5.0,8.0,4.0,2.0,4.0,FCAFDBEDBABAABAEEAEHDBHCEHCDBCFBABEEGECGBDABFCCAHCB,True +28,6.0,8.0,11.0,7.0,10.0,5.0,9.0,9.0,CFBCBCCBACBEHBEGCADHDGFEGFHGHDAFBAFBEDCDGCHGAACHCHBCEEEEDHEDGEGGH,False +29,24.0,16.0,18.0,25.0,13.0,19.0,26.0,18.0,HEFHCDEGDHFBACGGDEHDGHDGFDEAHFDHGBHEBGEGADFFGCCGDHFBFABDACDABAGFGDAGDAGCAFFAGHHCDHCHACEDDAFDCCDCAECAEDGEDGAFGFCGFAGBBGFBDBBAABAAGADGAFCHBEEGHBGCBFCGFAHHCHDBDDE,False +30,6.0,5.0,2.0,9.0,2.0,4.0,3.0,8.0,DADBAFBDFHDHHBAHEADGFBHFGHEAHDHBDGDCADC,True +31,19.0,18.0,16.0,13.0,19.0,13.0,14.0,15.0,FCHGCAEHAEBDEBABAABHAFEBDCBDCBHCGEAGEFBAFCCECCBCFHEHGEGAEDAECBECEAFEBDHBDEAGFGHDGCDGADFAHGCFCBFDEHEGCEABFADHAFHGBHABHBHDAEBGDFG,False +32,7.0,12.0,12.0,10.0,7.0,5.0,5.0,9.0,EBDGBGBBDCBACGHBDAAHEBGCBFHBFGAFEHFCCCHDCHDCHDAHDCDDEBDEAFECBAHBECC,False +33,1.0,4.0,8.0,1.0,4.0,4.0,5.0,3.0,GAECEGFBHFGHBGCBFCECCECCBCHDGF,True +34,5.0,4.0,6.0,9.0,13.0,13.0,5.0,7.0,CHHEFFDFFDFFDFDGGDFGDHCEAEAHEAFEBFCFEEFEECAECHCHFDEBDBGEGABDEH,True +35,3.0,2.0,3.0,3.0,5.0,4.0,0.0,6.0,CBDEEHHEAHCAEBDFADFHFCHFEH,True +36,13.0,2.0,13.0,8.0,7.0,6.0,16.0,9.0,DEGDECDHGAHGEDGEGACAFCADGACGACHFDACHCCHCEECGHDHBEGGGGCADCAFAGFGGBAGCAHFHFA,True +37,18.0,19.0,17.0,17.0,13.0,17.0,15.0,23.0,HBCABCGHCEEADEDCEDGAGFFFHDFADHHBHHGCHFHHAGHEHEBBBDEFECFEBHCDAADFGDFHDCDCCDCCFACAACHGGBGGBFBCFBFFCFGEDABDBBDAAGAABACBEGBAHAHHFGEDGHDHHEBHBHF,False +38,4.0,6.0,5.0,9.0,6.0,4.0,4.0,6.0,AGDAGHABHCEEFBEFDEHDBHDECDFCDBHDEGBBGCCADFDH,False +39,3.0,5.0,6.0,8.0,8.0,2.0,8.0,6.0,DCEDEEGEEGAAFEHFGHDGDBHDBGBBGECECDGHBGCDDCHCAH,False +40,0.0,0.0,1.0,3.0,1.0,3.0,5.0,1.0,GDGGDCEHFGFDGF,True +41,20.0,19.0,22.0,21.0,30.0,22.0,10.0,26.0,BADBABGCFGFDDDADEFHAAHAAHEAHBBHECFGFDEHDCDBBBHGEDEECCDCCDGCHHBGHCHACFDCFCFEDFEDAHHHBHAECABDABAAEHFEADCFEBFAGFGEABECFEFFECEEFEHFEHEEHDHDCHBBHBDHCEHCDHBDCFAEFAGHEGECBCFEEFE,False +42,3.0,7.0,4.0,4.0,5.0,2.0,5.0,3.0,EBBEAEEHDCHDCGDGGBACBEHBDGBAFBFCG,False +43,21.0,15.0,21.0,27.0,18.0,33.0,14.0,23.0,DDDDDDBCGFEFFABFDHDAGCEFHHACHGBHGBEFEHFEHFCFFCHDGHDFHDAGFECCCAAEAAGHGDFCHFCHBBBFABDEFDFFBBDBAAFDAFAGHACHACEFFEFDHABCAFGDFEDCGACFADFDDFBHFAFFBEHBEHFCHEADEGHEGCDGHDHDEECCFCCD,False +44,27.0,34.0,20.0,19.0,15.0,29.0,27.0,26.0,FGCFGADGADGDDBDBAFGAFDHHHAFBAEEAGGBDBFCEFAHFAHFAECDCBBCGBHAFHABHDCHAHHGBCGECFDCEHCFBCHBGHCABFBCFBEHBECBAHBGDECHFDFBDEAFBBGECGEBBHDBHDBEABEBFCDFHHFGHFAFFGCACFGDGGHGAABCDBHBGGBGGFHGHGGBEADABFABAAFAFF,False +45,15.0,12.0,15.0,7.0,7.0,15.0,11.0,5.0,CAFCDGCFACFCCFACGBBGCAEAEGAHFADBCHACHFCFBEFGEGBDGBDGBEGEHAEFGBFCDFBFBHACAFCAFGABDAFACDB,False +46,12.0,10.0,7.0,5.0,4.0,11.0,11.0,13.0,ECFFHGFGGFCGACGFGGAHFABBHDEDCHABFBHGAHGAHCAHDABDFHDFGCHGBEABAHEHBFHBFCBAA,False +47,15.0,6.0,13.0,11.0,17.0,21.0,13.0,9.0,EDCEFAEFAFFAGHCFCEEAFGFFHFDECECCEGCDGHDGHDGHACFFCFFCDFEHEEFEEGHEDAFBGEAAHAAGCABAEFAFDABGFCFHCDEDBABFGBGGD,False +48,11.0,17.0,17.0,9.0,17.0,17.0,13.0,15.0,GAFGHHGCHBCACCFBCFHHECHBHAFHEEGBAFCAGHGEFGEDGFCBBEBGABCFDCFDCFDBEEEGAAHDAEDFECBGCBHDBFEGHHBFGBFEBFCBCCHEFAEDAEDCEFHB,False +49,13.0,16.0,15.0,12.0,16.0,9.0,12.0,15.0,BGCBAEBCDBEDBECBDCBABDCDFCDBCEGDABDFFEHCEDGECHACHEBDECDGHFFHFHEAHAHHEFFBAGAGHCHCCHGCEEAAAAGEEGDEGBFGBAGBHHBH,False +50,13.0,6.0,16.0,14.0,12.0,13.0,9.0,12.0,DAEAAGAAGCHCCHDFHEFCCBEGFEGFHAHEAGBGCBFCBFCDACDAFDCHECEBFBAFCFFDEHAGHDEFDGCDECEHCHDGADEHHFADCDD,False +51,22.0,27.0,26.0,19.0,24.0,22.0,28.0,20.0,FDCGDAACFACHGCDGEBFCBDCBGBEGBEGAGGFGGCHGDHGDCAACHADHCFHAAEEBBCBCCBAEDAGBFGAFGEGGDGHCEEEDEHCBBCDECEBGEFCCHCFBCFBHFEABEBDEDHABHDBFFFCEFCEDHFFHBFABHAGGECAEADBGGEGAABHAGHAGEFGBFBFHHDHBEGBFCCDD,False +52,19.0,24.0,24.0,17.0,11.0,20.0,12.0,18.0,FBDFCFECGDCFBBFHBFHBAHECHAAHAFCAHCHCFBDFCDHCDBDDBAGAAGAGHFGBDABCFEEAHHGDHBDCCGCCDAEBAEFEBCHBHECHDABFFBHECFDCBDBFDGGDBFABGHBGFCFCBDCBACBFGHEACEACA,False +53,11.0,13.0,7.0,11.0,11.0,7.0,5.0,12.0,HABDABEADFFDABBHBEDAEDACBEHBEGBDDEAAHAHGBHBDEBAEDECCHFDHFGHFGHFDCCEBHEBHGCACF,False +54,11.0,20.0,14.0,17.0,12.0,15.0,15.0,22.0,DFABFDGCDCDDCBHCBECBDHHHBEFBGFEGHGFHEFEAFAHDBHDGDGEDFBAFBGFBGAGGHHCHHEDBDDBCFFCGFCHEEECDDADHBHHCDHCBHFAEGBCBBAHBAGEFGAHABHCBHG,False +55,17.0,24.0,24.0,12.0,23.0,20.0,17.0,26.0,GAECBGBFHAHHEFEGCGFBGBCHHADCACHBGGBHBAHBAEFAFGGFBCCAFCFHCGHCFHCBEFBEFBCHBGFECFGDHBEHCCACGFHEDAEBAEDDEDCEHBEBBEGEEHHACHECBDFFDFADFAEFHCFHCBECDEHDEHCBAGBAGADGBCBHHEH,False +56,17.0,25.0,29.0,22.0,21.0,19.0,27.0,22.0,FFFFFGGHDEHDFGAFGEEAFEGCEADDBBDHDCHECDGCDAAFCDHBGCBGBBECCDCCDAHGBHCBGCHCCEFEGFAABBEHFEHBCGFHGCHBDHCDHCFBDEBEABEDBCDGCHCCFGCFDAGGBGBBCBFABFEGGADGHEGHEDFBBCBCGACDAEEABDADGGEGHEGCCHHAHH,False +57,12.0,11.0,4.0,15.0,9.0,3.0,6.0,8.0,HABCEHAECBEDEDDHBDGAAFHAGCBGBEAAABADEADGHDFBAFBDEBEEBGDCDDGDDHDAHDBH,True +58,9.0,8.0,9.0,9.0,4.0,9.0,12.0,13.0,CAGCGGCBAHDEFDHHGHDFDBFBBFGAFEBFECHABGGDGDEGDHGBHADGFDCACAACHBFHFGHCHHCHA,False +59,15.0,19.0,20.0,23.0,14.0,16.0,21.0,18.0,GDGGBGGCFGABBABFGEFGCDDCFBCDBEBACHABGEBCDCCDFDDFDAACEBCEGGGFHHFDHGGHFGADHFHHGDHDFFGHGGHDEBDCAACGACFADDHDDCBDBBFEBHDDHFCEGBEHCABEAHEAHEFCCHBAEBCEDC,False +60,9.0,8.0,2.0,6.0,8.0,11.0,5.0,10.0,FEBDCDFHFEHFEHEGHBHFBHFEDCHBBBAGEAGEAGHADABFHFFDBFAEFADAAHG,False +61,26.0,25.0,20.0,16.0,13.0,13.0,17.0,12.0,CBACHGCFDHEBHBBEBBFAHCCEAEEABDDBDGEGADGHDAHEABBBEFCFFDEFDAGDADBBHGGCEGBAADABCHGCHGBDBBGCBGCHFAEFCHFBFDDCAACHACFACAACABFEBFAAEGGCGBCGBAGBDDACAA,False +62,9.0,9.0,5.0,7.0,5.0,5.0,11.0,6.0,FAADDAGBGGBGBCHBCAGEADACGAHGACFECDABBFEFDGGDFGHBGHDEHBEHB,False +63,7.0,8.0,8.0,6.0,13.0,12.0,11.0,4.0,GGBDGFEGCEGCECHDCFGFGABGFEHFCGGBHFBHEGEEAEEAFEDBCFBDFDEADACBABFACFEEF,False +64,20.0,11.0,23.0,13.0,16.0,11.0,12.0,18.0,AEDAHACHEFAEFAHCAEDAEDCBAGGCBGFBCHCHFCEACHCEHCFHCEAEAAEAHCAGBDCDHCEHEGBFCHHCGHFBHFAAGEADHBDCADCFDGFDCHDCBGCGAAHCGFGDEBDEBECB,False +65,19.0,12.0,22.0,18.0,18.0,14.0,20.0,17.0,CCDCCAFHAECADDGDGACGADGHDFHEBGEFEAFDHBDGBCGCFHBGHEGAEGBDHFDFDCGDHGDAGDCBHEBHEBGBAFHGCGCCFEEFCDCCDCHECHFCFAAAGECHBBEEBHDAGAAEAAEAHEGHCFCEFGAD,False +66,26.0,13.0,22.0,33.0,10.0,21.0,25.0,20.0,CDFGDFAHFEHDHBBCDECDAHDGGGFBCDBADHHDGADEBDEGDHFFCFFDHDGADHCFHDAGEGCEACGBGGEAGFAGBBDABCABGADGAHADDADCADHAFCFGDGEFBEAHDCGDHDCADFADFGHCCHGFHCFHGDHGHGECCCCCADBFDGAABAFDAFDAFC,False +67,3.0,0.0,0.0,5.0,2.0,3.0,2.0,1.0,FDFEDHDGAFGADEAD,True +68,21.0,30.0,10.0,18.0,20.0,13.0,15.0,10.0,ABBHBEEEHDEHDGFFGDBDBBCABFGDCCDHFHHAAAAABFAEEDBEDBGBBEABEABFBBFBBDDAEEAGCFHEBAFAGDGGBBEDBHDFEFEEBEEBABDHBFBGCBGCGGBGCCGCEGAADAABCDDADEAHF,False +69,23.0,30.0,20.0,17.0,29.0,22.0,24.0,20.0,BHBBFBBEEAEGAEHBCABCBGCGEFHEGHFFBFCBFCHEEDEGCCGBCHFHBAACDGBFBEAEAFEHFEHGHGGACBEDDDBDFBGBAGBAGEDGEHAEDDHGDFEDFEHFACCAEHFBCGBCECFGFFAEGAEAHHBGABGAEGDCGDCHDBBEFAECDHCDHABAFBACBAFBFGEDEEHGB,False +70,16.0,21.0,23.0,21.0,35.0,31.0,21.0,19.0,FEGHEGHEHFBHEBDEGDABDAGFAGCDGCEAEABGGEFEBAEBHDFEFACFEHFHHEBFGGDGBAGBAEEAFBACBCBDFFDGEECFEDFEAFEFFEDFBBFHFFCGFBFCECEHCHFFHGFDGFHECEGCDDBDDEECCBDHADHADEEEECDBCBFHGFHGBCGFCHCCBGDEEAEHAECDCCF,False +71,21.0,21.0,25.0,23.0,34.0,29.0,19.0,27.0,CGCABAFBECCEGAEFEEHEDHEFBAFBFFGFDCBDFHDFDDHCCAEGAEGEECFCDFGDHCDAFDFFHBAEGDECFHHFHHEAABFABAAHCCCCHHGBBCBHGGHEFDFFCGFDGHDAHAGHCEEBBEDBEGEHBEGCHAEHDEHFEBDECFHABHABAAFDDFDDFBEFGHGCEECFDCDCEECEEAHEGHEFBBG,False +72,26.0,9.0,19.0,24.0,24.0,27.0,21.0,27.0,DDGBDCADHEDABHHHAEHAHDCHDBFFEEFAEFAHGACFFEEDHACFCCFGCDACDCCDCEDBADHFEGDHDFHGCHFAEFHDFGFGEFGEGGEHEHHAHFEHCAAEAFCHDCFFFGABAFEAGGBGHCHDFHDAAGAFCADGADHAGHBGBBEEEGEEFAEFAEFCGDCFDHGDH,False +73,24.0,24.0,23.0,19.0,22.0,18.0,26.0,30.0,HGFHGHHBBHDBAGCEDEHDHCDAAGCBCCHCCDGGHAGHGHHFAEFGEGBEBFDFAEAHBBHBDCBDCBCCDECHHFHDDHCGAAAAEAEEDBGDBGCFACGAHGDFGCGHABBACBAHGHHBHGBEDDACFACFEBFGHCAEBGEBGEDGEDHEFFECEEAEFGGHHFBBFCHFBAFGAEHACD,False +74,26.0,17.0,19.0,17.0,28.0,19.0,13.0,23.0,EGCAHEHHEHABADBADECBECEEABEACFACACFFBFGBFBDFCFCCACAHEBHEGHDBHBBAFEADEHBCHEEHEGBFGBFDCGDEFDEADEDHEAAFFEFFHHFACDCCEAHDADDEEEFAFGADBHEBEAGAGDAHBCHCGHCAHGACGEEFAHGHHD,False +75,3.0,1.0,2.0,0.0,2.0,1.0,0.0,4.0,EAHBCHCAHEAHF,True +76,10.0,5.0,4.0,6.0,10.0,5.0,10.0,8.0,HGHHAEEAEDAECGDCAHGFBGAGEFGFBEFAFCGCEAEEBGEBGDDHDBHDAHGAHA,False +77,6.0,2.0,4.0,1.0,4.0,1.0,1.0,0.0,AACCDECAEBAEBAGFECA,True +78,26.0,21.0,24.0,22.0,21.0,23.0,16.0,22.0,AEAFDAFGAFHAHCGFCGFHDCBDCBABADBCDGGFGHEBBDFBFFDCDEAEEGGFHAHDCDDBGEHCEFCHFGEFDADGFHFBDFCCCBCGBCABDFHAEBCHBCHBCDECEGFFAHFAHFCHFDDCAEHAGHBGHBAEECDDDDAABAHECHEBHEAHABGEBAEACEACEAF,False +79,23.0,23.0,29.0,21.0,13.0,23.0,22.0,17.0,CDHBACEAHEFDEGHAGAAGFAHFADFCBBBEFBCDGFBCDBDHGGGGCGFBDBBCFBFDEGEEHEGGBGEHFCCFCBDCEDAEABFDHHBFBBCAGDDCHDCHDAHBACAGCAGCADDBDFHAFCAFCGHDEBGHBCHGCHFBEGBFACFCCACAADACFACFCCFGFDG,False +80,12.0,12.0,23.0,9.0,27.0,13.0,18.0,19.0,EGFECEECHEBEEHHFBDCGCAACFBCGEHEEGCEACEGDEADAGBAGBCDBFBHFHACHCDHCDHCECCEGFHGFBABCGDCBDCEACHBCGGAEEAECFEHHAFFEEFHFCEFCHGGGGDHBEHGGHEEHE,False +81,25.0,15.0,14.0,17.0,20.0,16.0,15.0,15.0,DGDFFBFFCAFHADGAEEAFDABDEGGEBGDGEDEBAHAAEGABAHCACEACAHBAGGECFCDDEDBEFHEBGAFCAFCAHDEHDAFAGFCDBCHCCHCEDBGFGHBADBHGBEAAHAAHAEFECFEDFEDHEBHGB,False +82,23.0,16.0,15.0,28.0,9.0,16.0,15.0,26.0,FAHGHHFHGDHGDHDHCCHFBHEDGDGADGBDFDHFBBEDBADEDDBDHFDACDBFGBFAHCDDDGDBGBBGAAADCHFCHCDGABFHDDHDAEDCEDCGDFEAAEACHHGHDGCFFCHABHAHHAFCFHAAHAACBABBHFEAGEAC,False +83,16.0,17.0,21.0,14.0,11.0,17.0,24.0,19.0,EGHCBBCBBHFAHAAGAFGHBCDFAGFBDABDADEEDBCDBCHBCBGEGFFGFGGCHGCGGHHADHDHCDHAFGACCEHDGHFFCDFEDAHDFFAFFHEGBDGCGCBECECHBGHGGHCGBCHBCEGFGGFCACAABAE,False +84,25.0,24.0,34.0,20.0,21.0,23.0,18.0,22.0,GCCGAFHHFBGFBCFBDFBGFCGDEGCAHEBCAFCBFHEFEDCGFCAFCHCHBCHEAHAFBAFDAHBHBDGAABAFBACACHHCFDAFDGBAHBEBBEDFCFECAEBGFHECCCCCCHHEEHAAFDGFDHBDGBEFBEDDHDDEBHECCECCEBAEBAGACGEDGADCBCCGGCDEAGCADCAFHHD,False +85,14.0,17.0,15.0,14.0,15.0,14.0,16.0,10.0,GGCGDDEBFFHGFBGFBHFHHEDAACAABGFFFCDBGBEHBEDBFDBCDCDGCDEFBCHBEGBEGBEFHGFBAEBCEFAAGGCHCCFCCBCHEHEAACADDEDDAGDAGEAEBAG,False +86,5.0,2.0,1.0,1.0,1.0,1.0,3.0,1.0,ADFAGGAHGBEABCA,True +87,28.0,33.0,23.0,19.0,20.0,25.0,30.0,22.0,FFGDBGHBGEGAADDHGEEDEHBBACDFCGFCGEHFBBFHBFBCCGCCFHDFCGHBECBAAFFDBBCBECGGFEGECCAGABBABHAEHBBHBHDEFDCHDBAFFDDFAAHAAHCDFCAHEAHGAHFAHAGHAGAAGEEDFGBEBECBGCBAFBGCCGAFAAFHAGGFGGBGGBDEEGEGBFGBFHBCHBDDBDDBECCA,False +88,27.0,30.0,28.0,20.0,23.0,12.0,23.0,29.0,EGBCBBCEBCHHGDBECBCDBEDGEHGAGACGEHGCDACFECFCBHBBFDAHCACBACBEFGGAGGADAAEBAHDFHDCDBAHCHHBHABGCBEEDHGHHGFHAHDAEDABDGCDECDBADBHHGHHGFGECBEABDHFDGAHEACFGCAGCABCHBFECHCBFCBFAEABDAGEHEEAECABDHBHHCEBG,False +89,14.0,15.0,7.0,17.0,10.0,11.0,15.0,9.0,CHBADFABGHBGFGGAGGADGDEBHADHGHGFDFDDCDBGAAGHAGFAEEBBEDBEBCEBFAFDAFDFGDEADEGDFACCCGBHBBHABHDEDCBDFE,False +90,5.0,3.0,3.0,1.0,8.0,0.0,6.0,3.0,CCACEGHEGDEGBBAHEHGBAGEAEEAEG,True +91,0.0,0.0,4.0,2.0,4.0,2.0,2.0,1.0,GDCFDCEECGEHFEC,True +92,14.0,4.0,7.0,10.0,8.0,6.0,12.0,5.0,DCDAEFAFCECEEAFEDFEGCCGACBDGHFAHBGEBGAGGAGGDGAEGHHGAADAFDADDCBAHDA,False +93,10.0,8.0,8.0,3.0,8.0,14.0,16.0,15.0,FAGFDGHDHHEHEEGGFFACFHEHACCACHFGHFGHCGCAGCGBCFFEGFGBHABHFDHGBGBHABHAFFAGFEHEEBBAGG,True +94,21.0,25.0,21.0,30.0,27.0,13.0,12.0,17.0,HHBEBCAACEABDGDGBDFBGFCAEHGDCADCHDCEDFEDCEDGDCEDAEGEHAADBBDAADHCDHDFHBEEBEEBCEGAECDEBBCGAHEBBFFHEBHEHDAHDAECFFDFEDFBDABDCCACEDEBDHDDAGFAEABECBHGFDDFEDCCBHCBHGBEGBACBA,False +95,4.0,6.0,6.0,8.0,7.0,6.0,6.0,9.0,EDGEBHEFHACBBCFEGHCHDAHDEHDBHDBDDEHFCGECGFGBFACFAHGD,False +96,8.0,5.0,5.0,6.0,5.0,8.0,12.0,12.0,AFACCAGAGGFBEHEGHECFDFFDGFHGAHGHHFDGAGCAGEFGHBBHEBHDDHDHHGCBA,False +97,20.0,25.0,21.0,20.0,27.0,26.0,25.0,26.0,BFCFGDFBECHDCEBGEFGBABHGDDGAFBEBCEFEEFGDAHFBHEHHCHDDHGEFDFFBGBBAEGCCFDDABEBBEBFHBHHBCCECEDCAFCGFGHFCBGHBEAFCBFDEEAEEAFECEBBGGAGHBDHFHHFHHFHHFHHEEHGCDABGABGACGAFGAGGDDEDDCADCFGAFGDCAHEAHEAEGC,False +98,4.0,3.0,1.0,1.0,6.0,1.0,5.0,3.0,BBAHAEDECGEAGBAGEEGHEGHF,True +99,21.0,17.0,15.0,21.0,17.0,23.0,10.0,21.0,AHDDHEDGFFGCFHDHAGHGHHDDFADFABHDBCCACAAHGDDFDDFGBHEBHBHEEHEFCFFBBDDBAABCEEHDACDHCEEAAEBHBFABFABCABFFFFDFFDFEEFCEHCEBDEBFCAGAGGDGCHBCHAAHEFFECAADH,False +100,21.0,17.0,13.0,22.0,21.0,22.0,21.0,31.0,GCAADDGBDEBDABDGDGGEADEDDFHHHEHDGHFGHFDHGAFAHEHDCHDHFEBGEACDACGABGABGFGGDGBHEEHEFFGHFABDHEDAECBFHAGHAHBAEAAEAFEHFEBGGBCFDFEEAHCHHCFDAFDCFDBFHBAHCHHFFGEHDECCGCBHFHHFBHBE,False +101,3.0,4.0,2.0,2.0,2.0,1.0,2.0,2.0,BCFBEABEABHADGCHGD,False +102,3.0,5.0,4.0,4.0,2.0,1.0,3.0,10.0,BGHBGHCCHCDHEHHABDFHDBHEGCDAHBAH,True +103,22.0,16.0,17.0,17.0,11.0,10.0,13.0,12.0,DECDFCDFEDCCBCCBCADGAGFAEAAHHCGECAAFHAHBAGEFDEFHHGGFBFCBACBABDACDAHDAGDGBDBADHFDBCEHGEHGDHABGBCEDEEHBAABADCGGCFCABDABA,False +104,12.0,15.0,10.0,16.0,25.0,15.0,20.0,17.0,GBFDCFDGDDBHDAADEBGBDEBEEFGHFGHFGHCGHEGDEADHBDHGGBGHEDCFHAAHACHGGEGGEFEBFGADCCEBHEGFEHDEHEEFAGDCHFEEAEEBCEGEDBEDBECBFFBHHCAFAEGAFB,False +105,7.0,10.0,8.0,8.0,6.0,8.0,6.0,10.0,HBEHAGHFGHBGDBAAGCDEHFEBEHBEBCABAACDFHBCHDFGDFGDFHCHCCACBFDBEDF,False +106,17.0,20.0,9.0,15.0,13.0,17.0,14.0,15.0,FBEAGDAGAABAHBGEFFBFFEDHEGHEGHEFHFDBBCBBDBCHCAHGAHCHBEGFDGFAEBAEGADCAHBDFBDFDFBABHEFGBCDAFDBCAGCFBHFBAFAEDHEDCEDHBDGGHGA,False +107,5.0,5.0,1.0,5.0,1.0,5.0,5.0,2.0,FABAAGDGFDFHBFEBAGBAGBFDDHGDC,True +108,17.0,16.0,20.0,15.0,16.0,19.0,21.0,30.0,CBHCHHDDDGADGAFCEHEBHEFEAAEBHFHCBGFAEDHEFEFFCFFAHEHHAHBGCDCHFGHBGFCGFBEABFBHHGHHGCHEAHEADABGHBHHBDHGDHGAGGBGGEFCFFCDBGDFDAECEECGCAGCGDCFDFHHAHHDHBBCCACGAC,False +109,19.0,26.0,19.0,10.0,27.0,23.0,8.0,14.0,EBCAAAGFADFADFEFBBBCBEABEABEAEEHEEHEECEBGACCAFCBHCDCCECFBCAGGAFEAFEFBHHBDFAHEHFEGFHCFBBHCCABCHFFBFFBDGCEGEBAEGCFFEEDHFFBFBADBDBBDBBEHEEFCHACBAHDEE,False +110,19.0,10.0,10.0,17.0,15.0,14.0,13.0,9.0,EACEADEDDGDAEBCFACEAEBFHFFGDFEDBBGBHGCADCFBBBHCAHEAHFAHAAHCDGCDGAEGAEGEDDFGEAEBAGFCGDGDDABDFCDFGFFAAEDFEHAH,False +111,6.0,10.0,13.0,9.0,4.0,7.0,3.0,10.0,CCCAFBAFBEHDFBCCBCHBCBCGHDAHDAGDCDFCHCEHDAFDFHDHHDEEBFBAGBCHBC,True +112,14.0,15.0,18.0,9.0,20.0,11.0,10.0,7.0,DEFDEFBEACFGEFCACCBGGBHAAEBEHCEGGEDEEFEEDBECBABGADFADFADGCHCCHCHACEDHEGAFAEFBFBAEACCAEBBGBBGEBEBHCCDCCFC,False +113,18.0,25.0,13.0,24.0,29.0,22.0,19.0,30.0,HCAHEABDACHBBDDHADBEHEEHCABCFBHFBABBABDHBEHFGAFGFHCHGCAEFHEFHGHCGCEHDDFEBFEFFDDHDEEDGEFCBGBDGAHHCHDCFDEEDGCFHHFEEFGBGGEEHBFAGFDHBEGFEDCEDEBDEFHEAHEAHABBEDBGFBGEHGAHFADBADHADHEDBGGB,False +114,13.0,9.0,15.0,32.0,17.0,18.0,11.0,14.0,HDHDDAGGFDDFHBFBCAEDGEDCEACDDEEDFHFAGFDECDCCDFADECFECHDCHDGAGAHGHDFEDCEDCEHBHDAHDCFDBFHHGDBDAFCGFAHFDCCDAEDGEDEEFADFAGFBBDEBDEBDF,False +115,21.0,18.0,26.0,25.0,21.0,27.0,25.0,34.0,AACCECDFFBBDABHAGHGFHGHAFHBFHFEHCBHFDAGHAGEDBEACHDCAGCDCCDBEDBDDEGGEHGAHFAHDBFGHFGCDCCFCBFCBHCHHFFDFGEEEDHFHHFHDFEDFDCBHAGAAGHBEEDCFFCHEDAEBAGDEGDEDBFBGCBECHCGHCDAGGAHGHCGHCFHBFHCFHDADAEGEGHCGAFFEH,False +116,25.0,15.0,25.0,18.0,19.0,11.0,22.0,30.0,BGGBGDHGBAECHEFABDHBHHBHDADBEEGFGGDGCCGFCHHHAHAFHBFEEGEAHCGEAGDCCHCGDAGBAGBAEADBADHADFCGHEDHCABCHHEHDFHFAHEAHCHCAHBDHBGHFGEFCAGCHGAAACAACHHDHCCGECEDDFCDACDACBCCEEGEE,False +117,28.0,24.0,15.0,28.0,23.0,30.0,14.0,19.0,CHACHAGEBEFDCFAGFADDEDDBDGBDBFEBEDHHDGDECDEBFABFAFFABAAHHAHHDFHFBHDBEDADCBGHEDFFDEDDEBEBAGADDFFFBDFBFFBFFBHACFDBFDFAEBACBACGEGGCFAFEHEAHECHBDGGFCAECFEFHEHHAGACBDCBAHAAEAAEDECDAFGGFB,False +118,0.0,3.0,1.0,0.0,4.0,1.0,0.0,2.0,FHBBEEBEECH,True +119,15.0,14.0,10.0,15.0,7.0,12.0,18.0,9.0,BGDBGBFEBDCFAFFADCGGAGDABAAHHAHHACEBCDDCBDAGDGBBGDGDDACEFCFFCGFHGBEFCGACHAGAGHAGDABBEEFHGFBFDBEDGHDG,False +120,18.0,23.0,21.0,12.0,21.0,14.0,26.0,15.0,GBBHAAEBAEHEEFEGFGCAECABAGCADBEFAAGDABCAGGFGGCHGCHGAHEAHFFCEHCEBBFBBEHBCGECGACGDCGDHGCGGHGGDDGHACBBGDBDECDCFABECFEBFECEBGBBEDDEGFCDFEGBHGBHAHFACEBCHBF,False +121,18.0,17.0,15.0,11.0,14.0,12.0,17.0,17.0,AGGAFDDFCDBBHECHBCHADHCBACFACDDGFACEBCBBGBHAAHEAEEHGFGCFGBHEBAFHAHHADHBEGBHHCEFEEFGHFGFGCBDCADGBDHHEBEBBAADAAFCAGCGGEGGEC,False +122,19.0,12.0,14.0,16.0,13.0,13.0,22.0,12.0,DFAEFDEBHGFEEDAEDFGGCGGFGGFGGAGGAFFDEAGEAGDBBABDHHCHHBDHBDGCGGDHDAGCACCBFCBABHEFHCCHECBCGDDAHDCEEFACFBCAGDAGAAGAEFAGDBEHA,False +123,3.0,8.0,5.0,11.0,9.0,10.0,4.0,11.0,EBFFHHFADFCHFGHEGHFGFACDEDDEGHFAEDHBDEBDECDCDDFHBFEBHHBCEBHDB,True +124,4.0,5.0,6.0,11.0,9.0,6.0,5.0,8.0,ACEACEADEDEHDCFFCDCCEHHEHEBHGBDGHDFDFEGFEDBHDHDBBGFAGD,False +125,11.0,14.0,19.0,12.0,21.0,14.0,17.0,9.0,CCDCBDBEDHEGHAFEECDGCFGCEGCBGEFAEDACCHCDHGFEFFBBEABEAHHAFCCFBFFCFCBEGDACDGCAEBAEGGEDGEDCAGGEDHEBHBBACBHGFEGEGDEGEFCBF,False +126,7.0,15.0,16.0,15.0,17.0,19.0,21.0,17.0,CHHHDBCCEFEEBEGBHFEDGEBFFBGFGHHGHHGEHDHCDHCDFAFFDCABAFBHGBCGBFHBDHCEGAGGHHGDEAFECHDBFGBDBCDECGEFEEBECBDFFDECGGCGADGEDGFGCFGCFAF,False +127,1.0,2.0,2.0,2.0,3.0,3.0,7.0,2.0,BEGGGGACFHCFHEFDGGDEGB,True +128,24.0,27.0,28.0,25.0,25.0,12.0,31.0,20.0,GGGBGGBDBCDHGACGEHDCHDCBDCHHEHBGHADDADDEBGGHGDDEADFAHFAGGEGEEABEHDEHCEBAEBECBACBACGACGADFADBBBBFCCAEGHFBEBCAAHBCHFCEFCDFCDCCBAEGEGCAGCGCCGEHFEHGCCACAACBDDBHGBEBDAFGEFGBBGHHEDGDABCGFHDEGGEDEADB,False +129,8.0,19.0,18.0,15.0,11.0,19.0,15.0,9.0,BEEBFHGAACFBCEBFHFADFCDHCDBCGBGGEGBDAADFDCHECHECEGCFGCFGFBCFGCAGDFGFFHHBDDFCDFBBEDBFDGDBBFBHABCEBCDAEGCBFHBFCGECGD,False +130,19.0,16.0,11.0,13.0,12.0,17.0,19.0,19.0,AGFEGFGGEGDAFDBFDBCGACBHEHHAHHDFADABHAGHBFHDFCDCADEEFEGBDGBEGADBAHFGBDGBAEFAGFBCAECHGBGFBGBBFBHAHHAHDEGEFAHADCACCHCEHGAHFHGFCF,False +131,4.0,4.0,2.0,0.0,2.0,2.0,3.0,2.0,FBECAGHAHCAGBAGBEFB,True +132,21.0,22.0,26.0,22.0,19.0,22.0,19.0,31.0,HHACHAGHDFHCACFECAECGDFFDFCAACEBEDHHAHDCGBCBBCAHCAFCDBGFGDCHBHECHCFACFGCHECBBCFBGHDGHEGHDGFBAADFGBGGFCGHCBHAGHFEEEDAEDAHHABFABHAHHGHBFDAFDGDDFEDGBDFEDHDDHCEHEAHECEECEADBGCBFFHCFBBBBH,False +133,16.0,18.0,20.0,18.0,16.0,13.0,27.0,16.0,DGGBCEDCEFHDGHFBDCHFHHBACBADAAHADEACBGHFGEDGCBCABGAGFCGDCGDGBEGBEGBECEEHGEHGHHDAAGGACBDGBGCBACDEBDBGCFHFEHCEGCEAEFCHFABFEGGCDHFDCDDCDBFGBFGAGHAG,False +134,19.0,21.0,15.0,10.0,12.0,12.0,10.0,11.0,DAGDAGAAHHFHABCBBCEBCFBCGDCGEEACACBACEAFGBDAAFEAFEHBBBFECDEADGFFACGECBBCBBGEBFEBDAACHADHFEFBCHBFGBHDBCGBHADHAH,False +135,13.0,9.0,13.0,6.0,13.0,9.0,17.0,10.0,ACEEHFBHFBGFCHABEADHHCGACGDHBCABEGBEDBGGCGHHAHCEDAEFAEGCEACEAGGFCGCDGBFGAFGAFBEGCEGAFGECHD,False +136,12.0,12.0,9.0,6.0,6.0,6.0,7.0,12.0,DGFDCFBCHHHHHHHBHBBABEAFGBEGCFDFGCCBDABAAEAAHACCAGHADEACGHGEBEFBCDBHAB,False +137,8.0,7.0,7.0,10.0,12.0,16.0,11.0,8.0,EEHEGHGAHFFEFEDBGDBEBBGGFGDCGFCFCGFDDFHDFHAFCFDGAAFFAEHAEDFEGFEDCEGAEFBHBCDBCHA,False +138,16.0,20.0,15.0,26.0,16.0,10.0,21.0,11.0,BCEFDBCDBAHBEFBCAHCAEBDCCDHGHHCHDDDEGBFDFGCACAEEDGADGEDBEGCEHCHBGHBEDDADDGBDGBCGBDHCFGCGGFGGAAEAADAEDGEDBEBADDADGCDGBAGBDGBHGFFBEDAEFBF,False +139,13.0,8.0,3.0,6.0,6.0,4.0,5.0,4.0,EDGABAADGAECAGAAGAACHFFHABGFBABBEDBEHBAHCABDFDEED,True +140,3.0,7.0,9.0,8.0,11.0,8.0,12.0,4.0,FGFCGCCEEDFEBFEBDACHADEBCEDFBDEHEFBEHCEDCGGBGFBEFCGGDGHDGCGGAG,False +141,7.0,6.0,3.0,11.0,10.0,4.0,8.0,7.0,EEAAECEEGHEHDFDCHCGHEAAEHBDFBDBGDBADBEHFEAFGGDHDDGBDGADG,False +142,25.0,23.0,17.0,19.0,29.0,25.0,18.0,29.0,EEBEEBHHHHBCHEFDGCDECDEDBEFHAFGBFBHFBHFCHFEDFBBFEAEGBCBAAAADAHEEFAEFDFACHHCHBEHBHHDGECFEFBEGHEGHAFHCDBCAGHEGHGDHGEGGFAAFAHEEHBFABDACHABDCDAFGFFGCFECFHBFEEDDGDBFCAHAEDDEACEAGDBGAAGAHCBHB,False +143,1.0,2.0,2.0,3.0,4.0,5.0,2.0,3.0,CFDCBDHGEEGAEDFEFFBHFH,True +144,9.0,4.0,7.0,5.0,3.0,7.0,3.0,7.0,EFAFABHACHECHGCBADBADAADGCFFAHGHDFHDCHFCBECAF,False +145,21.0,27.0,26.0,22.0,15.0,22.0,16.0,17.0,FCDFDDECEHCFGCEGDABBGHCGBBFABAEFEEFACHBGFEABEDBHCCFGAFEEFHAFECFHCEBCDBCBAHFAHFCFFCFFBFAGGAECDCCBBDDCDDCABBAGGAGBAGHCHECDACBAFHECGBGGBAGBHBACCADDDDCHHHFHHBDDBDDBDBADBF,False +146,23.0,23.0,27.0,18.0,23.0,27.0,25.0,28.0,DEGHEGFDBFGHDEACECDFDDFDBBBGCEAFHFFHFEBGEBDEBFBBFHFFEFCGFCGCHGAHBCFGAAECGEGDDGCHGAHAAHAADDADCAFBFFBHBHEGCAHCHHBEACCBBABBDBHCBDFAHAEBCEGEGCBHEHFAGCAFCACEFHEFADBCGGCGHAGHGEHEFHCAHCGHDGHCEHCEFCGFDF,False +147,19.0,22.0,21.0,22.0,15.0,18.0,18.0,18.0,ADDADEFBADAHFBBFBBCHGCGBCBHEDCCDHDDACGEGBEACEBCGCFABFHEAHFGDCDDCGFCGHEHHEHBFHDFBFFBAFAABAADACDFCEFHADGADCCECDBHDBCGBAEBAHDHHDHACFCGFGEFHEGGCGEFGBDGBGBBDE,False +148,23.0,18.0,18.0,17.0,20.0,20.0,23.0,19.0,GHBGCBDAFDAFHCBEFGACAECHHGEGFEGDEDDBCAAGFAGCGECAEFBEACEHGEHAEAFEAFBCGCCFCBBGHBAFBFCBFAEHBEHBEGAACFABGEDGHAGBCGCEBDGDDHEAHCADFFGHAHDGHDGHDGBDABHAEDDFHDFCFFHGFE,False +149,11.0,9.0,14.0,14.0,12.0,13.0,8.0,11.0,CCFCGFCDFHHHGGHEDDFHDFEEGCEAHAHCADFEBBBCBFCAHBAHEACDDCDACDADDBDDBEGBDFFCEHEFBEFEAGEGFCGFCAHA,False +150,20.0,17.0,22.0,21.0,18.0,23.0,27.0,26.0,FDDHHBGAEAABAAFAHBGFFHEHCEBEBBEDBGDCGHCGHCFFEGFEDFCDACDAEBFEDAEDHHHFGHGDHGAEFCFGBEDAADCCGFGGAAGCHCDDBDCGGFGGFGGFHGFBGBCGECHFHHACHABDFHDHCAEBBEBGCCFHEHGFHFEHFEHBCACCACGAGHDDDD,False +151,25.0,32.0,23.0,18.0,29.0,30.0,21.0,16.0,CHFAFBDBCEHGEHEEFEACEFCFHHFCAGAEGBCABCAECHDDFDFFEFFGHABFFEHBBDBGABGACGACEDCGDEBDEBCEBFDCHBADBFDAADEFBFHGAACAACHDEADHCBGCAFBFFBFFBEBBGBEEBHDBFDGDAGFEGCABEEBEHBGHBGFBGBAGFGCEGCACFDGAEBEEFCEFAFHBCE,False +152,2.0,5.0,8.0,6.0,3.0,7.0,7.0,3.0,ECBDCEGFFGHCGCGGFBDFDDADDHEBFCBCCBFCGFGAH,True +153,20.0,20.0,31.0,26.0,22.0,23.0,14.0,22.0,GBGFBFFBHCBHCBHGBEFCGFHHHHEHDCHCCDGCFFCDDHFDEDGEGCHHADHCEECFECHECDGCDGADCAGAAHEDHCFBEFEDCHFFAADEADHADCGBCFBCFEEEEBGBCCCCBCDBDHBAHDABCAGCBCFBEHDEBDCFDHFEFDAACAEDADAFGEFABFDCEDAFAB,False +154,14.0,22.0,13.0,6.0,19.0,16.0,15.0,9.0,EEBFEFCBFDAAGAHBCCBGCEEAEEAEEAEEAEGGFHBCHBCBCHBCFACFGDECBAGFFDBHBBHGGFAGBGCBEHGADBFBBGGAFCAFCEGBEGBEFBDFBHEHEFDAFB,False +155,13.0,9.0,8.0,9.0,16.0,11.0,16.0,26.0,HGHDBHECHGCDGAEGFEHDEGGHHFBHFGHBGBEFEAHEAHBFHFDHADHBCHEAHEAHDGHDHHEFFACDCEBFGGEGAEHEGHEGCCGFHGAAAHAFHAHDEBBC,False +156,21.0,23.0,28.0,17.0,32.0,20.0,26.0,33.0,AGBGFFGFGGCEFCBFGBECECGECBECAGHDHEDHCBHEEAEEBFGGHEEHAGFFGFHHCCHADABEGBHGCHGCFBHEHHEHHGFHFFHEFAEHADCEDCHAADBADHEDAFHEDDCCDCFEHBHGGHEFHEBHEBHGBCGCADAAHACBDFBGCBECBCCEHEADEGEEAFCDBHGBCGBCDFAGEAEHAHDCBBCG,False +157,3.0,5.0,10.0,12.0,6.0,7.0,9.0,8.0,CDDCFDCHDGGFGDBGDHFHHEGCCHDCADCAGBFHEGEEGCEDEFDBFDHAHGCBFCBD,False +158,27.0,19.0,22.0,22.0,21.0,22.0,30.0,32.0,AEAADDGDGHBHDGHBGHBHHBCHCAHCABEEBDBDHGFHGHHGBBAHAGFGBAGAGGAGHHCFFBHHGDHAACAGCAHDADGAFHCCHGHHCHGCFGEEDEDBECGAFEDFEDBEGBCACHFCDFGDCDCCBGCFGDFGHFAAEDHFBHFGFFEAEEHEDBECFEABGAFEEEAFDCFDAFDBCGHCGHAEHAG,False +159,6.0,10.0,10.0,5.0,6.0,6.0,5.0,10.0,HCEECDECAFABHBBFADFCGACGABHFEHCBBCBBHFHCDCEDCHGGHEGHFBHABD,False +160,18.0,20.0,20.0,17.0,21.0,19.0,20.0,20.0,FEDBECCGDCDBGDBGDGGDCDFCAHCEHAGAABACFCFFCAACHADAACEGEEGBFBHEHHBGHBACGFDFCHFCHEAEBBEDFFGCFGBEBBEHDDHABGEEEEFABHABHGEHGEHGEHBFDFDHGDHGBEGBECCFCAFHFGCCDAFAHDB,False +161,12.0,21.0,28.0,20.0,19.0,21.0,30.0,23.0,BEBCAAFGAFGBFGEEEFCCHCGHFGHGDDCCHBCGACGEHGHCEHCFCBHCBHDAHDHHDCHEABGHFGBGGCGHCGCEGFDGDDEFGEAHBGEADDCFDGBDGDCFECFCGFCHEGAFCDFCDGDFFEHFBHFCCBECHEBHCBFDBFBBGBDAEDGECGBHEBDABGGGAH,False +162,21.0,14.0,18.0,20.0,18.0,17.0,19.0,20.0,GHBEAFEGBGGHDEEDEABEBBEFECFCCABAAEAAEACBAFBHFHHAEDBCDECDAFBAFBAGEHEHGDAAHGAEDCCDHDDHGAHAFCCECAFCHHCHEGBCDCCBFFEFFGBFDDDDDGGCGDAFDGCGFHHDHHDHGFHGAGG,False +163,7.0,8.0,10.0,9.0,10.0,6.0,9.0,12.0,FBCCDDCAHADHEHHAGCGGHECHECHGBFABFADFGDHBDHDDCDHCEBFHGECEEAEFHECEBGBGGBA,False +164,2.0,1.0,4.0,3.0,2.0,6.0,3.0,7.0,CHCFEGFCGHHEABGAHDFHDFHCFHFD,True +165,27.0,21.0,24.0,26.0,31.0,11.0,22.0,21.0,CAADGACHHEAHDFHCAHCFBCFBEBHGCEFCHCGECDEABEACDDGHDAFCCDCADCAGBDGBEGBCDEHAHHAEFBEGDEFCEABBDBGAHAACAAEACBFBBFGEEHEBDEGDEGDCCDCABHEEEGCDGCDGHEGEEGEHDEGDHDAEFEGBDGADHFDGCDGBAAAAHHEEHDEBABB,False +166,7.0,16.0,7.0,13.0,4.0,10.0,9.0,15.0,BDDEDDGCAHEFHCFHCBHAGFDBDDBDDGFFBAHAHHFGBBDFBDHACHBCEBFEHHGHHBADBCFBHDGABGHBGFBGC,False +167,15.0,15.0,9.0,10.0,9.0,15.0,18.0,14.0,GGABCADCGHHGEHBDHCDHDEGGGFGGAGAABECBCFBEABEBEGAACBBFEAFBHFBHFBGFCAFGHFGHDGCBCEHFFGBFEDFBDAHHAHHGFDDAGDAFA,False +168,21.0,14.0,14.0,15.0,25.0,21.0,7.0,17.0,FDABDAHCHHFDACBGCBGCHFAACGEEBCBFABAEEAEEAFEADDHFAHFEHAHHCEHEFDGFEHFEGFDFHCCAEAAEADBHCFHEBBCFACFDEADFAECAEBBEDBEGFDAFEFDHFDHFEEBCEBGEHD,False +169,11.0,25.0,11.0,15.0,12.0,14.0,16.0,19.0,CDFBBCHGCEBDBACBDCGHFHHFHDFHBEGBEDBFDAFCAHBACFAGGAGEAGBAGBHBBDEBHGHHGHFEABDHFCBECBFDFEGHDFHBFHAEHECHBHBGDBGBCEBABDEGDGGDFDB,False +170,11.0,10.0,15.0,10.0,14.0,10.0,14.0,13.0,EEGCEHAGADCDEADGBDBHDFGDHCDFCDHBAEAHEHCGFCGFCEFDHGHHGHFGCAACHACHAEGEBDCFGCFBBFBBEEBGACGFHEECEBCGA,False +171,15.0,14.0,17.0,21.0,14.0,11.0,20.0,12.0,CBGBFHBCEACEAGAACBDBBDCDDCDDAGGAFGFGDHADEDDEFFAFFCBFCBFCFAHDDBGGGEADHHBHBBDEEGEEGCAGCDCCGCEBHHCGGCDBCHHEAHGAEGHEFADGDGEDGDDA,False +172,6.0,4.0,6.0,6.0,3.0,10.0,5.0,4.0,GBFGHFGDEDFCDAGDHCDACBECDECAHAFFAFBCBHAFFGFF,False +173,2.0,0.0,4.0,3.0,0.0,0.0,1.0,0.0,DDGDCCACCA,True +174,3.0,6.0,8.0,12.0,9.0,8.0,4.0,7.0,FGBDDHHDCFABFABCBCCHDEHEFAEFEBFEDDHDBCDECFHCFGEGGEDDCDDHE,False +175,4.0,4.0,3.0,0.0,0.0,0.0,2.0,1.0,GACGABHBBAABCC,True +176,4.0,2.0,4.0,1.0,2.0,1.0,1.0,1.0,HCDACAAEABCFBCEG,True +177,22.0,20.0,10.0,18.0,13.0,13.0,19.0,20.0,CBHCGHGEHEEADBHGAEGFEGFBAEBCFAFEGHCBABFADFDDCHBCHDHAGGADBAHFEEFHBBHBGDDDHDGHGFHAFAAEGBBDAADHGBEGBAGBADBAHCHHADHDGGDFGDFDCABCABCABEFHEGA,False +178,22.0,19.0,25.0,28.0,26.0,27.0,22.0,13.0,CCCCCCCDCAGHEHCGDGHCADEADBADHFDGGGBDACFHCFHDGBDGDAGDCDDBBCEBFBAABDCDDEDFEFEECDEBAFBDDBFEHEEAEFGEFGEAGBFFBFFBCFCFDGHEFCAFCAHEEGEEBEAHDGEFBFHDFEDCDHCDACGGBGCAGDAFAAFEAFHDFEGECBBGFAEFAG,False +179,3.0,7.0,11.0,8.0,19.0,13.0,15.0,4.0,BEEBAEFHEBGCBCEBFHFDECDCGHGFEGEEBECGFCGFDGDDGFAFFAEGCEFCEFDECEEGDEGCGGFGEBDHCEGF,True +180,23.0,18.0,16.0,19.0,17.0,9.0,16.0,16.0,DACDHCDECEHCBACDAFDAFABCEDHDGHBCFFABCDDFDDHCAHBAEDABHABDGDFCBECAEAAHGEFABFGBGBHABHCEAEGAEGEHGFHEAAEAHGCEGCHGAEGCBGCDGDEGHHADBAGBEDBDBB,False +181,7.0,4.0,3.0,4.0,1.0,4.0,0.0,2.0,CDDAFABHAECADFHCFABFABDAB,True +182,7.0,17.0,14.0,12.0,11.0,8.0,17.0,16.0,ECEECHEGDCFDCFDCEDBBGBGECGBHGFFGCBHEBHABAGBHFBHDGHBECBEHHGCGCCGCFGHABADDDHGDHEBHBCGGFFACHAEADBHDGHBGDB,False +183,18.0,19.0,14.0,22.0,20.0,25.0,20.0,18.0,FBAHCEHGHHGAEDEDDHDHGFACFDBFGCCBHGHHGBHGECBHFDEFBEBHECHFGDFHDEHAGGEGDBGAADFADAADGADGHFFEGCABDGFDBDECDFAFAEFCEFCADGFDFFBFFBHFCECGEBGEBHEADBBDFBCFDCFAAEGBEABE,False +184,9.0,17.0,14.0,14.0,12.0,19.0,15.0,10.0,DBDDHCBBBBGGFEBFEAFGCFDCADCDFEFGHFDHBDCECCFDCAEBEDHFDCBDGBACACGECFEHDBACBFFBFFGGDEGHHGCHFBHFBEFAEAABGFBGEGGFGH,False +185,5.0,15.0,12.0,28.0,11.0,16.0,11.0,13.0,FBEBDDHEDCEGFGGBGEBDBBHCDGDDHBDHECBDFBDEGHEFHEFEDCDHGDADDABHABDCBDBFDHGDFDCGHCGDCHHGDADDEDDAFDFFHFFECDCBBFFCFFC,False +186,3.0,2.0,0.0,4.0,2.0,3.0,6.0,2.0,EGADGADADBGHFGBDGHFGEF,True +187,7.0,12.0,9.0,16.0,4.0,16.0,12.0,10.0,BDFDFFBBBEBBFCHHCHHFFEGDADDFDFHAFDAFBBGDBGDBDDGCDFFDGDGCBCADGEHGDHCCHACABHAHGCFGFFGEFG,False +188,9.0,14.0,12.0,11.0,9.0,6.0,5.0,4.0,DFBEFDCDCBAFBADEFDEGCEBCGFCECHDBADBADBEEBABGHBACBACBECGACBBCADDHFGHECD,False +189,15.0,22.0,16.0,23.0,11.0,18.0,13.0,25.0,CHGBHDEHBEHDGCDFHFHHCHHGHEDDBGHACHECHBHGDHDCHDEAGEABFAEFACBBDDBDBADACDABFAHDABACBHHDHCAHFFBBDBGAFGFFBBABCGEEFEDCCDCBDBFDBFEFGGFHHFHDCADBDGFCGFH,False +190,23.0,11.0,18.0,25.0,19.0,12.0,19.0,38.0,DEHHAGHADHGCHACEDCAGEGFDADHADHDDGEEEEHFHGCAGEDDFHHEHHDHDGBDADHECEEGAFHDBHGBHGBDAHAEHABHBBFDDCDAHHGHHEHFGHCHDDECBFCADCGDCGHCGHGAHGABFHFHHFHHEHHBBAEDAEDFCCECAAGACCACAF,False +191,5.0,6.0,1.0,7.0,12.0,13.0,5.0,13.0,HEEFEHAEHFFHFGDFEDGEGAFGFHGEHDBHAFHFFEAHEBEBDFADBHHHEHBECFDBFD,True +192,14.0,9.0,19.0,16.0,17.0,13.0,14.0,12.0,FBCCBDDFFDHDDHGEFGEFGFHGFBDFCEEHACCAEEDBFDEDCHFCBAEFCGGAHFADGAHEHHAHBACBCEDEEDCCDCGACGCCGCEGDECAECAFGABGBHGDDEAEHA,False +193,13.0,11.0,10.0,13.0,18.0,18.0,16.0,24.0,BFHBGDBGHEFHEGEEGAAFHDFECFEAHEAHDFHCHHEHFAGEGCCHHEDHEDCCDAGGAGGBDCBDAFHFFAFDAFHGCHGCFGHGHHCHDBHBFFADFEDEBHGGFBADHAEEEHEEBFB,False +194,4.0,3.0,4.0,0.0,0.0,3.0,1.0,3.0,HCHBAHBAGFABCAFCFC,True +195,5.0,5.0,1.0,2.0,4.0,4.0,7.0,2.0,EFBGHBGABGADGABHAGDBECGAFGFFEE,True +196,16.0,12.0,12.0,7.0,4.0,7.0,9.0,12.0,ACGACAHFFCEACGGDEADCAGCFHBFBEFDHDBHAAAAGHBBHCBHGBAGBACBDCBHCBACDECHHAGHFHBGADFA,False +197,11.0,6.0,8.0,7.0,7.0,10.0,12.0,14.0,GHFFHACEECGEGGDBGBBFAGFGCHGHDGAEGCCBHCBHAFHAHDAFGAFADCADHAHHBCDFGEAHEHHFDEF,False +198,21.0,16.0,17.0,15.0,22.0,24.0,21.0,20.0,AEFABCDCDABGHHEHDFBBFCAGGAEFCGGCGABGACGHHGDGBDBBCFACBDFHHEHFCHFCECHFCHGEHGBFFECFBHFGHFEDFDCFCEAEEADDGDEGFEGFABFHBFAEHEDDADAAGAACEACBHEBFEDFAAAGGEGGBHEEHFEHF,False +199,3.0,4.0,1.0,2.0,7.0,5.0,9.0,5.0,HFFFEGEEGAHGBHGAHDADCBGGEEGEGBEGBFFH,True +200,27.0,17.0,26.0,18.0,16.0,17.0,15.0,13.0,BDEBEEBCBBCDFCHCCABDEGCGACGACACFGDDGAACBACEEDBDDCCCHCDFAHBGEBCHGGFCGHHHABHBGAEHCBGCDAEDFEFBEAHEAFFGDFHDHHDFDBFEBAAGAAGAGFCBCCEACEACECFAFAAFAADCFDAFDA,False +201,14.0,18.0,22.0,18.0,23.0,25.0,18.0,25.0,EHGEHCBHCHHAEHDEHDEAEBCEBCEGFAHFAHCEHBFHBHHBHEBCFADGHFGCFBAFBDHCHCEHADGBDFBFFBHBGGEFFFDFEBCDFDHCDHBECDEHECBECEFAGFCGCAGEHGEDEFHFCGCCDACAAFDAHDFFDBGDGAFGCBCDFEGFGGE,False +202,6.0,4.0,6.0,6.0,4.0,7.0,2.0,1.0,BADGAEAACFACGEFBACCEFCEFBDHDDFDBFDCF,True +203,4.0,8.0,7.0,5.0,6.0,6.0,6.0,7.0,EHAECAEHBEHBFHBCDBAEFEGGCFGDGHHACBBCGBDHCDFCDFGBF,False +204,6.0,15.0,10.0,9.0,18.0,10.0,16.0,17.0,EHHEDFBDFGDGEDGHFEEDDBGFADFCBHCBHFEEFAECGHHGBCEDCEHFACGHEGHEGCBGHBCHBEFFEHADBAGBGHCHEEBEAGEBGBHGBHCBG,False +205,6.0,8.0,4.0,6.0,11.0,10.0,4.0,7.0,BDFBFFCHFBADBGFCGCCEEAAHFAHFGFEEFBEAHEBDEBDFHDHEGEEBEHDA,False +206,7.0,11.0,7.0,14.0,12.0,11.0,11.0,15.0,DFFHFBABAHBEHBEHDHGCHFDFAGCGHEBADHGDHCEHCEFCEFGFFGHGCDAADGBBGDBGEBFEDHABHDBCDHHEFDEGDEDE,False +207,14.0,19.0,19.0,16.0,15.0,16.0,25.0,15.0,BHBBDBDDGDAHEGEGGECDCCBCDAEBGEDGHDCHFEHACACCEDCGFGFEGDGGAGGAGGHFBEGCEGCEBCAFGHEBHDAEGAFHHCADFBBFBFFDHFCHFBBGBBCBACGFDAFHBCGFCGEDGADEAHFCHBG,False +208,14.0,24.0,23.0,25.0,20.0,23.0,13.0,19.0,CGFHBECCCACGAFFHDFHDAHCCFBDFBCCBGFDAHDABGABGHBFHCDGDDHBHEBCEDEFFEFFEFFCDDGGECDEFDADDHEACEAHEAEEBFBFGBDBBFCBDCFDGFHBBDBCGCDAHDCCDHCEEFEGGECBBABDCBDEFEHHEHHBHBADFA,False +209,5.0,7.0,7.0,12.0,11.0,5.0,6.0,4.0,BEEGAGCAHCFDCAHCEFCAFGGDDEDCBDBEFBEDDADDHDDBBDBEEEGCEGHEF,False +210,21.0,21.0,29.0,26.0,25.0,22.0,25.0,25.0,HGGGCBGCBGFDHCEGCBADBADBDFHCBHDBEBBEHBEFBCABCACCFCEFHAFHGFGDDGDDHHDEDDHCBEDDEDCBGGFAADADGACHAFDBEBEECDECEFGGHECHEFHEBHEDGCDCABCEFGEGHFGHEECDBHDFDFGCAEAGEAHCHFAHDGHACFACGHHGDHGCAAEFAFBCBECGFCFFCA,False +211,25.0,20.0,15.0,18.0,16.0,31.0,22.0,17.0,GDHFDBEDFEFGAHDFFDBECFDAFDBFGBDAEGAEGFDCFDCEACBAFHGHHFBFFBHHEAFBAFDCFBGAGGACBACFCEACEACHHGDHGCGFHGHAGABGBGDFHHFCACEBHEDDAFDAGCADBEGBFGBFEFFEAFGCFBHFEHGABAABAEGAFDFB,False +212,11.0,12.0,15.0,21.0,14.0,13.0,13.0,22.0,FDHBAHAHFDBFDFCHHEFHDFAGBADBADCHDFFDABDHCDHCGAGFHDDHEEHBHHEHBCBGDGCDCDECDEGEBHEHHGHDFBCFDAGCAGCACCEFCDBGEBGEDEFGHCGHEDHEA,False +213,26.0,25.0,22.0,24.0,22.0,21.0,23.0,28.0,DGGABBFFGEFGHFBHBHFAGAHGECGEBAACCADCHDBGDHCDFEDCCCFBFAHDEGGBGECFEABGHDEADGBGGFDEFAABAAHAAHCAHGFHBFABFAEHHCHHCFBEEDEEFEGDEHDHHDHCBEABAGGAFGDFDCBCHBCHBHEBAAGCADCHFCFDBBDBCDECHACHDBEDHEFGADGHDBE,False +214,17.0,18.0,21.0,25.0,26.0,17.0,17.0,17.0,FEFAEAHHABBGBGGCDGDEEDAEBGFHHCADDHDDEDDEAFECGGAGGEBGBACEEDEEDHDDHGBHEBCBHADFEDEGGCDDBDCFCHFEFAHFHDBHDBHAGCFEFFEBEEBEEDGEACFABBCBFDBFHFECGHCGACDCCDCCECFHAACADC,False +215,3.0,8.0,12.0,3.0,11.0,1.0,8.0,8.0,ECHEGGEHEEBCEHGGHBAADGCHBCBBCHBCHBCEDFEGHEDCGCCECEBCGA,True +216,3.0,7.0,2.0,4.0,7.0,5.0,4.0,9.0,EEBACHABHEFDEHHEBHAFHFCHEDGEBBDFBHGBHGFDG,True +217,24.0,19.0,23.0,32.0,19.0,19.0,18.0,19.0,BDFHFFHEAGCGGEHGAHGADAEDAEGACABCBFDEDDEHDGDDEDDGCDGAFBBEBHFBDEADCDDCHBCEAHDBHCBHCACBGCGFCGFCGDHFABCACCABHEEHDGBFFDFFBHADDDCAAHDAEFEEFBDFADGADHADFGDCGCCBECADAHHCFDCGBEFEEDHBA,False +218,15.0,9.0,15.0,14.0,9.0,15.0,10.0,14.0,EDDHBDCEDAHHCDHCDEFECFDDBDEGDCAFCAGCHCFHBFBDFCABCEGEEHHGFHAFCABHABDAFAHBHHGFCGFHGBAAFDAFAAFEDFAGGCCGC,False +219,24.0,26.0,20.0,28.0,17.0,21.0,17.0,23.0,FBGGAGHAGHGGBGGFFDAFDHDCFBFFHFDHDDHFDHFHCFGDHBEFCEACHFEHCBADHDBADCEBCDDAGDAFDAEDEHCAFDAFDFBBAGBGHBCHAFECHDCEBBEABGFHEBHDGCEFCBACBACBCCBHBFGDADAAHAHBGDBDEBGECEDHDAEBAEBAEHADCDBC,False +220,10.0,6.0,12.0,8.0,3.0,8.0,5.0,9.0,DEDDFFBCFCCAGBFHBACAACAHFAHBEGGAGCDCCDFCDFCAHCACDHEHHABGDBHFH,False +221,18.0,20.0,25.0,20.0,16.0,11.0,30.0,25.0,BFFBEGBGFBGHBEFEDHBDCAAHAGHFGDADCBDBBDECAEBAHGHGABBHHBGCGECEECADDDGHDGBBGBCGHHGCHCCHCFHGGHAAHAHGAHGEHGDHBEGFHFAHGADFEGBDHFDGCDGCFGAGCCGACGHEGDCCCABCECGEHDEDDCCECADCB,False +222,19.0,19.0,21.0,28.0,17.0,28.0,23.0,16.0,FFFFGGBAGBFCDFCBFDGDDEDDFDEFCHDCHACAAFFDGFHCFBCDGEGEECCCBBAHHDEHDECFGGGDDGDDGDDCBACBABHCDCFDCEBEGBCHEFHGBHABAGFGFADHAGFAEFHEBBFBEFCGFHAFGADGAFHBCABDEDDCHFEHFEGAEDCGDFADBAG,False +223,23.0,19.0,28.0,13.0,18.0,28.0,23.0,33.0,GHBCHBGHEHEAHDHGDCFBHGCHGCFGCBGBGCDHEFAGHEGAABBHECFCFGDEHCEHAFCADAGDFGDHACBACHACHCHFBEFCFGCHHHHCHBCBEDBFHBEHBAGEACHACFAGGHGDHFFAFEADEAHFAHCCHEFGEFBFCBHDFGFFGAFDACDECECBEBFHBAGCHGCAFFAFF,False +224,3.0,2.0,2.0,3.0,1.0,3.0,0.0,0.0,DAADFBDFBCACFE,True +225,18.0,28.0,26.0,15.0,16.0,22.0,28.0,24.0,CCBGHAGAEGAFGBHGCHGBBBHBBHCBDDBFDFGECEECAGHEBBGBAGBFGCHCCDGCDHEAGCBBFBBFCBGGAGBDGHGGHGHHFHDCEDAFGHBGABHBEAACGCCHCCHBHHFFFFGCFHCFEDACFGEFCAAGDCDDHDBAABFACDABEGCEGFEHFEFCEDBFHBEHF,False +226,0.0,1.0,4.0,5.0,1.0,5.0,5.0,2.0,DBGCFGDHGFCGDHGEFCFDCFD,True +227,9.0,11.0,5.0,9.0,13.0,8.0,7.0,11.0,DGHBGEBGHACBAFHAFHFHDDHCGEAGEDEEBEAGFDFBDFBHFHCDHCEEAFBABBEEBEBDHADHGEEAC,False +228,3.0,5.0,4.0,5.0,8.0,4.0,5.0,8.0,DCEDEHGEHGFCEFGBDHBDCBDHFFHEAHEACGBGHAEHEB,False +229,5.0,2.0,1.0,1.0,0.0,2.0,0.0,0.0,ABABFACFADA,True +230,17.0,15.0,18.0,10.0,25.0,10.0,12.0,11.0,ECCHCABEAEAABAEBGEBCEBGAAGBBDFHDEHDEHCHHCHCEHEEHCGBAFCDEEFGEGGCFDEFBBADBEEFHEAHECGFCDAAAFBBCCCACBGGBAEDDEGDECCEFAEFAEG,False +231,31.0,18.0,29.0,27.0,23.0,14.0,25.0,29.0,DGBAGHGHDGCGACBADBDDEADFCHGDBFEBHEBHEFHFCDFCDACFGHDDDDDCGCEAEEADCBDBGGHCAACAEDACHEHHAHDDFDEHCEHCECEHHEAFEABCGEGABHEDHEFAGCGGCGACDAGDACAAHACBBCDACAACHCDHGAHGFBDAACEACECFEHGGHBGHBCFFGDBGHBEFEHHAHBAG,False +232,9.0,27.0,30.0,27.0,17.0,16.0,18.0,20.0,HDBHDCCCHHCHECBBCGCEDCHCADGDBBEBGEGGFDFDDGDBBFHCEEDFFFHFHHDGCEBCABABDEHDHCDHFDHFDHBDHGGEECBEHBDFDDBCDCCBCCGCAHDBBBBFBEHBEGBEDDGAAHCBECBCCBCFFEDFEDCCGBAGACGDCAFCGFGG,False +233,13.0,14.0,9.0,12.0,10.0,11.0,7.0,12.0,CACBADGHDGHDFHDFHDEEDGEBBEDHACHABBFCFAEHACFDCEAHEABFFBFEAAEBCHDGBDBBGCBFEAFGDCDHHABHABGF,False +234,27.0,12.0,19.0,20.0,14.0,11.0,16.0,19.0,DCEACEBHDGHAGFBGABGABGABCHFEADDADAHDHDGBFAECCBCHHFADFEFAHDAEDCHCHADBFDCGDCHECGAAAAGBAEEHGCCGEAGEFCDFDGGCGACHCEHCEHDEHBCADAADADDFHGAHBAHBAF,False +235,10.0,14.0,16.0,10.0,22.0,13.0,14.0,12.0,BCEFFEFBBGBBGEDGEABFACCDCCDHEGHCBDGHEEEFAGBHGBEEHEEHDEFDEFCECDECHGGAGFFEDGHBECBHCGFEAAEAHGBHGBHEBAFACCEDCACFDCF,False +236,7.0,11.0,9.0,8.0,13.0,11.0,4.0,12.0,AEBEHFHFFGFHBFHFAHBHHBHFEFABBEBAEFCEACHHDGDEGABCCBCEBDEDCEACFHCFDCHDEEDBGDE,False +237,23.0,30.0,14.0,18.0,17.0,26.0,17.0,30.0,DGDDFCEFCGCBBHACAFCEEEEAADADEHFABBADHADHFDBFHHFHDFDAFEADBADCAFAFBEBBEBBCBBCFBEFBGFBHBBFFHFAHABHEFHBFHEGHAAHBAGBGFHAFABEGEGGDCGBHBCHGHFGHGHHCDEFFHCBHBBHGEHGDHFDHCDBDAHGHBEAACFG,False +238,19.0,27.0,27.0,14.0,19.0,23.0,28.0,21.0,CCCACCFBHFGEBABBGFFGBCHBFAAFBAHCAHCBGABGADDABDAFDBCGECFEHBCHGHHGHEGDEBFBBCGBGHBGFBCCBDGDCHACHADFADEHDEHEGADGAFBFGBEGHFHEADFCCGCCGFCEFGHFEFBCDBGHHECGBCFAEBBCDGAGCAGFFEHGEGFEGBECHE,False +239,12.0,6.0,10.0,11.0,16.0,6.0,12.0,10.0,DBDGGDGCDECGHCHEAHGDEFEEFEBBHABCCDACGFEGHECAFAEDAHAGCBGAHGAGFABFDEEDGEHEECEDCEAHDAH,False +240,12.0,11.0,10.0,12.0,15.0,7.0,12.0,8.0,EHCEBGEBCADCDFCEGBEBCEBHDGAAGDGHDCFDEEGBEFEEFGEHGHBEABEAFCFHCGHCBADAADADGAEBBDDHDFGACGA,False +241,24.0,20.0,23.0,18.0,18.0,16.0,33.0,12.0,DCADHACHFFHADCCDEEDCEDCFAAFGBCGACGAGGACHBBDBCCBEFBGCDGHFECABCACGAEFAECBFFFHGCAECAGHEHBFHBAGEFGECGHBABCADDGGDGGDGGCGCFFHGGEAGEGEEBBEGAGFFGDGGBGDBGDCGHAAABGEBEBDDBDAA,False +242,2.0,5.0,2.0,2.0,7.0,2.0,2.0,4.0,EHCHBDECDEGFEAHHABBEBFEBGE,True +243,5.0,8.0,9.0,5.0,11.0,13.0,13.0,9.0,ECEEGBGFFHFBEFHFDBGDBGFHFFHGHCGHEACEABBFEEEEGCGGCFBCDCCEHCDHGAFGABGHFGAFD,False +244,8.0,13.0,8.0,11.0,10.0,14.0,17.0,10.0,EGDHGCEDHEAHFBCGBAABGEDAEDAEGGDDFDCFGCEGCGFADFCFEBBCBFDGFAGFEDFBGFGHBBHEDHGGHBAFBFHCFHGBHGB,False +245,10.0,16.0,19.0,10.0,13.0,11.0,21.0,15.0,BEEBGHAGHCCFEDFGFHBHHDFDDHCFAGFAHABFABGAFAACBECGGGHGCAGCHCEFGEHBEHBGFGEFCHDHHDEBCABDGBGGCGGCBGEBGDCCCCDCBDEBGEBECCH,False +246,9.0,13.0,8.0,9.0,4.0,11.0,15.0,3.0,BDDBDDBAGAEGABGEDFCBCCFCDABHCBGDGGEGCEFAGBAFBGGBGGBDFFAFBCGDHGHFFCFAGFAB,False +247,24.0,29.0,19.0,27.0,21.0,19.0,25.0,36.0,AGGDCEDBEDGADBCBEDBHDFHDBEFHEFEEGEGDEABEFHDBHBHHFFAFBGGHCFFEAFDABEAFCHDCABBBCBEEBFBGAGHBGHCABCAFHDGHCHHCDGADHADGFHGFCGDBHBCHBDAEGHHGHHAHCAHDDBGHBGCEAHGADDHDECGEHHEDEGFEDABHABHABCABDABDACHGCBGDHHFHFFGC,False +248,23.0,15.0,19.0,20.0,20.0,17.0,12.0,20.0,AEDAEDAEFADFAHFAHEEHBBCBBDBCAFAAGCCGACEHEADFHDFCDAHGBEFFEFDAFGACGECEHHGADGBCAFCGCHDDDGCFFDBCHECFEHEABEABDCBHFDHECAFDABDAGEBGHGEHDBADBADCHCHHCFHEEH,False +249,5.0,8.0,8.0,6.0,8.0,12.0,5.0,4.0,DDADDFEDFHACECHGGHCDBBFFBEEBGEBCECCGBEAAGAEBFCFFHFFBFFCF,False +250,9.0,9.0,5.0,9.0,9.0,5.0,9.0,6.0,EBGEGDECAEBBGBFDBACGCBBCBBFDADDACDGEDGHDHDAHEFHFGAEGHFGAAEHAE,False +251,3.0,4.0,6.0,7.0,2.0,6.0,5.0,5.0,FCHFEBDGHDHADFGGFGFFEDBCCBCCHGCHDBDDAA,False +252,23.0,16.0,22.0,22.0,17.0,24.0,15.0,22.0,GDGADAHGFBBFBCHBDHBDCCDHEGADCHBBDFHCGGCEFBECHECEACFDBADEACEDFFDFFDFCEFCGFCHFGAFADGAFHAEABFDEDHHBAAAAHGABGDBFEHFHHFCHDCEAEEAEDCFFAFHCHHADHACHAEDABDCCGGCGFCBFGEHBD,False +253,28.0,21.0,24.0,17.0,16.0,23.0,19.0,22.0,HBGAFCHGAFDHGAHGHGDDGADGECAACFACBDGFCBAHBHDBFDEFABFACAEGFHGBDGBFHDFHCGBAGCABEGHEFHECCEAEHADHFDCCDCCEAFBDDBFHHFGHFCHCDHCFFCBAEFAEFEEAAEBFCBAABAAHEABBAFBGCBGCBDFGAGCCDECAHH,False +254,22.0,21.0,35.0,22.0,18.0,16.0,18.0,17.0,CGFCBBCBBCFBDHEGBFDEHCCAECAHAFDEEDAEHAEBCHFHBFHCHBGEACCCCDCABFABCDBDHCGCCGDCDDADDGGEHFEGCCBCBAFDEFDAADFAGGHECHECHECHAHGCFBBBBAGGEDBFDAFDCEDCEDCADCBHEFCAGCAGCBGFDACAACGGH,False +255,16.0,23.0,16.0,16.0,20.0,17.0,25.0,22.0,FBDCDGFHBEHADAEBABHAGDEEDGEAABDDEEFEEDBCGGDHHDHGDABBCBBCDHCDBGDBGCHGHAGFECEEBEHFGDFACHGHHGBHCEHCECABHADHACFBBAEFCEHAGHGEHGFHGFGGFGBFBFCBGCFGEFGEHBBGFCAFGAB,False +256,4.0,5.0,1.0,1.0,3.0,4.0,5.0,7.0,BHFAGFAFHABDAEHHGHHGEGBEGBCBHF,True +257,15.0,16.0,15.0,21.0,14.0,16.0,23.0,29.0,BBAHCCDBGFHGFGFFCFGCGHCGHDGAGHDCHDEABEBGGFDDFHDHHGHBAHDGCAGBGEBHBCHGEFGEHGEBFECHEDGEHBAHBEHDACDHHHBCHBCHAFHDCHAHGAGGDDBDDEACBAEEAHDDFFHGFHFFDAEDACDFG,False +258,25.0,18.0,28.0,20.0,16.0,20.0,26.0,30.0,GBDGBHAEEAHBAHBCHCCHCEBCECDEAAFHHCGGCFFDFBAGBHGFHDAHBACCADCAECAFFAFFGGEGCEACECCFCBEAAGFCFFGGHCDECBGHBHACAAFDGHDCHDCFDHFEHFDGDGHDCHAEADGGEADCHDHBGBDGAGGFFHHFHAGHCHHCDBGHBEHDEHGABBADBCG,False +259,10.0,4.0,2.0,8.0,6.0,7.0,4.0,6.0,BFAHHADDBDEBDAHFACEADEFDEHDGAGFDGFAEFBGFEAACHAH,False +260,17.0,18.0,20.0,22.0,23.0,26.0,23.0,18.0,CGCHEEDEBDHDGEGFEFFCAHGBHBEHBACAAFAFFDBFDCFAEFADFAEGBBHADAGGHFGCCGCGFBDFEEEEADHGDCEDFGDEBDHBGHBFFCAFCECGEDADDBHGBECFEBFEDFDDEGDHCAHCFFGFFGAHCDHADCBECBHHBHCGFGGABGCEGFE,False +261,27.0,24.0,20.0,19.0,30.0,32.0,21.0,26.0,GEHGECEEBEDACCACGBFGFCDBHEFEEFGEFBFACFACFAFFAGDACBAGDEBABFAEDAGHAHBAECAFDFEEBBBFEBDEFCHFHBFHFEHDGHBGHCCFDDAADEAEECGGHGFECFEDFEAFACHACEFBEFHHBHHFEAFHBFBBFBHFCAGHHFHHGHDCHDCHFGAGDDGCAGDEEAGEBEDAGHADBBB,False +262,24.0,26.0,23.0,23.0,21.0,23.0,28.0,24.0,CFDHHBBHEEHEHHEFHBDAADAFDBCDHDDFGAFCACEADGBEGCGCHEAHGADGABGADCFFBFEDDAFDCFHBBCFBGDGCHECBEBBCABDAECAHAHHAHEBHDHHFAHGEBEHFAAGBAGBGGCAFAFBAFBDCDCCDGGDGBHBBCBGFGEEGECGEHECDFCBFGBDGCACEFGEGGFHGFDGF,False +263,0.0,1.0,9.0,1.0,3.0,4.0,6.0,1.0,CHCCEFCGGBGFDGEGCECCFCFGC,True +264,6.0,5.0,5.0,2.0,0.0,4.0,6.0,0.0,CCAGBBGDBGDBACACGAGGFFFAFBAC,True +265,4.0,10.0,10.0,7.0,1.0,8.0,4.0,4.0,BEFBDFGDFABCABCHFCDGBHBCAFCAFDBDBGGBDFCCBCFHCDHC,True +266,22.0,29.0,31.0,16.0,20.0,28.0,16.0,14.0,EHAHCBHCBECFGBBCHEEBAFBHHAFGBFDBFCBFCBFCBFCGFGECBBGFCEFBEFDEDDGFCFCAGCAFCEGAAGAACDCFGAFGAFHBGABDAGAHCAECABBBCFBCDEAAEBFBBFCCFCCFABFDDFBEHBFGEDBEDEHAECBGCFHCDECACCDEFDADEHCGDBHH,False +267,19.0,18.0,7.0,10.0,13.0,13.0,13.0,11.0,HAHCGEBDCBCBBEGHFGBCGAAGBGGFDGCAEADBAHBFEFFEAGEHCHHBAHAADEFGEAGFFEFAEFCBAABAABEAFGAEGDEDBBABBFBHHDDHDBFD,False +268,17.0,10.0,10.0,7.0,8.0,5.0,14.0,9.0,DCADHDGHAGBAEHECHCGADHCGAEGBEGAEGAEGACAHGHDCBGHBGFBCAAAACBBEEBGBCFCAFDAFDHFGABGA,False +269,1.0,3.0,0.0,1.0,3.0,4.0,3.0,1.0,GHGGEBEFBFABFEDF,True +270,23.0,19.0,18.0,18.0,15.0,13.0,11.0,15.0,AHDAFCAECAFBHBCEFDEFCEFEDAADBADCDDFDAFGEHGEAGHADBBEACFGBDHADGCCABHHGHFBEDGHFEACEFCBAGAAEABEABGABHBEABGABFCBACGDDHFCHBCHBHHCEDCDDCDBC,False +271,7.0,9.0,4.0,6.0,4.0,10.0,14.0,6.0,GDDGADGAHAAHABDGFFFECFBHBEGEGHEGDCABGGFFHFFHFBGABGDBGCBGFGCB,False +272,9.0,5.0,1.0,2.0,6.0,2.0,1.0,1.0,EDAEAFECFGHAABAEDEBBEBAABAA,True +273,6.0,7.0,5.0,6.0,3.0,4.0,5.0,6.0,DBGDAGHAGECGFBHFBGDDFEDFHCBBEHHCAHBACBACAD,False +274,13.0,30.0,20.0,14.0,22.0,14.0,15.0,16.0,HBGBBDCBAHEFEBDBCABCGFGEHGECGCDECDBFDECGHBFHACDCBBHEHGGHFGBBBBHBBHBBGBEABHDBGDEGEFDECCFHEBHEHGEFCFBCFCDABAAHEECEECEDCEDGEBFEBAABGABCBCAAFDAFDHFC,False +275,5.0,8.0,10.0,12.0,2.0,10.0,10.0,5.0,HGDDCDFCDBGFCGDBGEAFACFDBDDBHDBCDCCFGCHGDFGCFDABHGBAGCGFABFEHF,True +276,5.0,1.0,0.0,3.0,1.0,2.0,0.0,3.0,BDDHFAHAAHAFEAD,True +277,24.0,23.0,18.0,24.0,16.0,33.0,19.0,28.0,ADCABCHCAHCAHEADEAHBGBCGFGFFGAFBDFGFBGDEGDGHHGHHACDDGFFAFFBFFEFADHDDADDFFAFGBFBBFHFCHBDADEAHECEDFDGFDFFDCBBHDAHBBHCEGEBHHBFFCCHHHHCHBBHDHAGCAGEDEHDGHDAFAFBBFABFAEAAGABGFEHCCBCHECFEDFGFE,False +278,12.0,29.0,23.0,26.0,19.0,18.0,23.0,13.0,BEBBEHBCAFAHEDDCDBBDBBDAFFAFCADCGGBGGCGHCFECEBDECGEHGEADBFDHFDGCDGCBCCHDBEABDCBDEBEEBDCGECBDHBEHEAGAFGHFHEFBBDBGEBFHGGHFGFDGCDGDDCFFFDFECCGCGGFBDBAACHEDBDDBGCAGBBC,False +279,16.0,11.0,17.0,16.0,19.0,22.0,19.0,14.0,GFAAFDCCEGCHGBEGDABFBDFEFEEBEBGFCGHHHFHAFDADEAHACBFCDFHFGCDACDFCGFEDFEGADGAFCEHCAHBBHEGCDDHDCAFCAFGEEGEEFBEFEHAHFDEFDBGDBGAFCAGCGGCGHE,False +280,10.0,14.0,13.0,11.0,22.0,14.0,17.0,12.0,EHCECEHBFGCGGCAHCDGCGGEDBBBFHCFBFBBFGHGHFABEAEGACGACBFDBCEECDEBFEBDGHDEBEGGECGEHGEDEEHFEHFEGFAADGADEHDAFDHFEEFCBA,False +281,32.0,31.0,18.0,18.0,36.0,28.0,25.0,12.0,GAHFABEGCGAEFADGADFABCADAEBAEFEHFGBGCBHDAHAABBBECFEAEEFEEFEDAEBAECADCDDBBBCBBEDBFAAFHEEGFCGEEGEFGEFAFDABCABDAFGFBGFEGBEACGGHFGAFHBBDEEEGGBHGFFAFFGEFGEBGDCHCHGBBGABEABEFEDADCEEFDCDHCDBGABAACAHCEFCEFBEB,False +282,19.0,24.0,17.0,28.0,20.0,14.0,18.0,11.0,CEGDBCDFGFGCADCEEGFABEDBDBBDEFDEADBGBEGBACDDFDHFBHGGCGAEGHEGHECDDGDFGEFABAEEHDFBDFBEEBHCDCCEHHDCGDBHDFDDADDEEDBBBBABHAHDABAAGADBCFBCBECDAGECGACGACFABFA,False +283,26.0,21.0,30.0,21.0,22.0,23.0,22.0,14.0,ABEAFHABHEFEEFBHDAHFBHFBAFBCBGGHGDHFDHFBEBBACCAECAECACGBCFFEFCEGGACBCDFAAHABGDEGDEGDACFEGDEGAFAACCBEABGAFDCFDFFGACHCEGCFGABCHGAHCDHCDCCDCGABDFBDEDCGFFBFEACCDCHDGGCGEEAEBAGDCDDCEEB,False +284,14.0,18.0,15.0,12.0,15.0,14.0,12.0,12.0,DHBFHFFADGAHCABFABEEFDEAGEAGDDBACBCCBGCBEEBEAHEHCFFCEFCBCGDCGDEGHGGABADBEEBEHCHHDBEGGFFEFDADHAHBBDFBCCBGABCFHCFA,False +285,16.0,15.0,17.0,12.0,11.0,20.0,18.0,11.0,HGHCBHCECFEHFEGDAFFGFEGFEAFGFBGABDBBGBACBGFBECAAFDAHHFGGAGGAEGCBDBBDHEFGGDGEHAHADEADEFCCFCFADDBCCBCABHAFFCFGCFDCFACDBCGH,False +286,11.0,13.0,7.0,7.0,10.0,17.0,12.0,13.0,FDGFDGFHABDDHFAHBHFFGCFHBGAGFFGFHHAGHEGHCGBCECDECDBHBEHBEHCAFGABAFBGFBEFGEABFBFDEFAEAHEABC,False +287,8.0,6.0,3.0,14.0,2.0,6.0,4.0,6.0,BGDFDCCDGAFBADBDHHDHCDHAAFAADBADBFDEFABDGHEGDDFHD,True +288,13.0,9.0,15.0,13.0,19.0,11.0,16.0,13.0,GGEDADGABGCBHAGACCFCHECDDCBAFEEHEBBEABEACFACEDHEAFEGFGDAEAAECDEFEHHEHBFFDCFDCDAGDHEBHCGHGGHCEFCGFEGEDGDCGHBGH,False +289,21.0,24.0,27.0,24.0,13.0,22.0,21.0,28.0,EBFBBCGBDHCAHFAHBBHBDHBDHADECDCAHCGHGFHADHDCHFBBAHBDHECABFBFFCDFGDFECBECBCHEAHFHHEHGGFAGBDCEHCFHCGGBEGFHBFGAFCADDFDDBDFCAFCHFDDACGACGDCGAGGHDEDECDAGHBFABABBEFBCCDEAHGAHGCCGCFAHDGHC,False +290,11.0,5.0,20.0,12.0,8.0,15.0,4.0,7.0,CBCCHDDHADEADEFDAACCCFFDFCAFCADCGDFEDCECCECFFHFFAGFCEDEBFFHCHGCDBHGCFDAFBAEHACCACB,True +291,20.0,16.0,14.0,23.0,25.0,13.0,17.0,18.0,GBEGBEGFEGFBFDBFDBADHAFBDFGDEGDGGECCECAEAADAACHHHHBHEGDADDBHAAAEHEBDEBGEAEHDGHAAHFABCEGDFGFCECDGDABDHBDECCABFBEEDEGFEHFEHGAHBDCDAEHAECDCFDCEDHGHEC,False +292,22.0,21.0,19.0,22.0,30.0,26.0,23.0,31.0,AHGAHGABADGFGGEEAEFDCABCFBCGBCBHCBCFEDFEDHADEFDFBHCBHAHEAHEHHEHEBGEAGEDCEHGACGDCFCEFDEBDEBDFHACEEHBDDGGEBCEBCGHFGEABFAEEBHABGAHGAHDHHDHEABEGBFAEGHEHCADFFDFGAFCDDGFHFFGFFDEBCHFEGFCDFHHCHFBEGHHADH,False +293,16.0,24.0,24.0,18.0,24.0,17.0,14.0,18.0,BDDACEACHABHABHECHGHEGEEFCHFAFAGFBBBGBEECEEHEFDBDDBDDGCGBCEHCEDCBFABFBBCCECCGBEBAABHECEGCEDDECFECFHCFHCGBCFFDDFADFAHHCGBBBCAFEBHGDGADGAHCBEAAFGDBHHEDCEDFEH,False +294,32.0,23.0,12.0,12.0,9.0,21.0,14.0,23.0,BCGBDHDCGGGDAFDFFBCABCABCFGGFAAFBHEBHGBGGDAFAACABHBFFDAFAHHBHHDHGDEADBHGBHBBHBBFACCBECAAAHABHAEAEDFGCCEAFFHEBHFHHEHDABAAGAGHADAAHAACEAHAAFFBFFBFFH,True +295,25.0,28.0,34.0,29.0,21.0,15.0,21.0,21.0,GBBDDFEAEADECDAGBCFBADECDBBDCCGCAGCDBCBBCBDCBGCEHCGACACFBHFDDBCHFCGAGGECFFABDEGDEFDHFHHBBHDAEDBEDCDDCDDCDAADFACEDHHGACGBBGAGAEGFGGHCACCDHGEHGEHGHCEACBHFEAAEACEACHHCHBCBECHHFEBBDCBFCBDDBDABAEFAHG,False +296,10.0,5.0,3.0,10.0,3.0,6.0,4.0,2.0,FCDBCACHBFABDAGEAGDADEBDFDAFGABAADEADHGDFFD,True +297,18.0,24.0,24.0,26.0,29.0,26.0,24.0,26.0,HAEHBEAEEHCACDDCFDHFGCBHCBCDHFDEADBBGCBGABFAFGGHGEAGDBCCGCBDFDDFBEFBEGDEGAADHADHBHADHCDFEFFEGGEBAHBCFGCEGEBGBFGEAAEDHFDAAGHFGEEGEEDHECGEDFEBBDCCDBDECFCBBEFHFCGFEHHEHHAGHCEHCDFCDFCDHCHGGHFEFFBFHBADB,False +298,13.0,9.0,11.0,21.0,12.0,21.0,9.0,8.0,DDADBAGGAGEAGECGEFHFCCFBCABCABHAEFABFDFCHHDDEDDHADHCHABFFFEAEDCFDEGGFDDFCDFEFFEDFEBADFDDFBDFCHBGFCEDDAFG,False +299,9.0,10.0,7.0,5.0,4.0,5.0,9.0,5.0,AEBFBGFGGAGGADCADGDHGHEBHBBGEBGFCHBCHAAFAABCECCFDDBCAB,False +300,9.0,10.0,14.0,12.0,10.0,5.0,22.0,10.0,GBDGFGGEGEHGDGGEGCCGACBDBBDABDAEFABBCEAEHAGCFHDGHGGDGADGHGGBFCDHCDGCGBDAACEHCEGCEGDHCHECHCBF,False +301,23.0,15.0,14.0,8.0,21.0,17.0,19.0,20.0,FGCEGAEGEDHEDBGGECFFHEBBBFDAHHEBAEBHCHEGAAHABEEFEEFGBHGCHCAHDAFGGHGDHGFAGBABFAFHEEGEAAEDAGFAEFACFACBHFDCEHBAHCAHGAHCCGCCGEAGEACFADFHBBHBF,False +302,27.0,23.0,30.0,20.0,17.0,18.0,24.0,20.0,AACCCBGDBFHBAECFFHBHHGHAACGCHDDBFBGGCHGAFGAGGAGGAHGCHGCDGCHBHABFDBDDEEDEEDBCFCCFCHBHFBAFBDFHFBAAAFCCGHCDBADAFCABEACGBFBEEBAEHAEGAHGACBBDACDFCDGCDGHDEEDEBCFFCAACHECGCBGCEGCDAAEEHGD,False +303,30.0,27.0,22.0,22.0,20.0,20.0,25.0,21.0,FCHFDBBDBGCAADEBGFBGABGFEGHAHBADAEDACBECFFCFFGDBGAHHAEHFCAFAACEDCFFBEFAEABHDGAEHDDBGCBGEBGEAEEFBEBDHDAAACCHCCHGDAGDFCFABFHBFHBGBBDHBDHEEHECHDCADAEDGBCCBAGEHGEBGFBGCCACCAGAADAHGHHGFDABGGGD,False +304,29.0,17.0,17.0,22.0,14.0,23.0,28.0,17.0,DABGFCFHAEGAFGFBCCBEDDHFCADEHDEHGHDGADGHGGCCFFFFCCEGHEGBDDDDDFDFGDFGCEABADBCHADBGDCDAHFFBGFGGHAGHAGAEGEGCAAHAAGAAEBAGBGFBHBBHBGDCGFCDFBAEBHCFEAAEAAHGAHGAGFACFDCFEAFDAB,False +305,11.0,12.0,13.0,10.0,10.0,17.0,17.0,13.0,BFDDADEGGFGEFBEAGHAGBACAECAFFBBFHBCHGFHGHGFFGCFCBBAGCDGDDGCGHCBHDGGFHFFHGDECDFCDEAGFAFBAECAECHBHHEHCEBF,False +306,7.0,10.0,4.0,3.0,5.0,2.0,7.0,5.0,BHBHADABBABGABHDGHDBCEFEEFCEBCEHGGCGBAABGAG,True +307,17.0,17.0,13.0,19.0,19.0,19.0,22.0,12.0,FDEAAHFFBFBGFBDFGDFGDBGDBGFBFFHFFABEGGGHAAHEAFEDFCBFCEDCDAGBAFBGHDHCGHGDEGDGCBBDHGABCDHCFHEGGDBCHECEECEADEAEGAGBAEEDDEGCEGCHACBAFBDEDAFGAE,False +308,16.0,19.0,32.0,19.0,25.0,21.0,28.0,24.0,BCGCCBFCFGGDHGDADAACACGGBADDGDDGFBCHHCFECDGGAEBAEGHCDBCHEEHAEHFEFFEGFEHDCCCEGHFHHGBGDEGFHCFBFHBGEGFCGFCBHGBHEBEEBGBAGEEGHEAHEBFEBHCBGGDGDCHCCACCADBAHEDFGCACCHHCHHFBAFAEEDCECCDFCDFCDFEG,False +309,12.0,7.0,7.0,14.0,8.0,9.0,9.0,23.0,HFHHBHGACFAHHHHHDHBGHCEHEHCFHCBHDAHDAHFGDDHEBGFDDHADHBDGEEGDACDAHDAHCGHAADAECBEGEFFAFBDFG,False +310,7.0,9.0,2.0,2.0,5.0,3.0,5.0,9.0,BBABAGEAHBGHFEHBEHBHHAHBEGBGGBDACFCHFDHAAE,True +311,26.0,28.0,24.0,21.0,11.0,21.0,26.0,17.0,BFBEHBHGFHFHDDGADGADGFDCFBCHGFAEAAEAAEAABDDGHDBEDCCGFCFFCBBGGBFHCGGGDBGDBDEBCFBCABGDBGDFGEGCCAAHBGHGGFFBAHBAEGCFBCECHFADGGCECCFCBACBGBBGCCDAEHABFADDADDAFBHFCHAAFAABHHCHBCDBGA,False +312,23.0,13.0,12.0,13.0,21.0,13.0,8.0,13.0,FBAFBAECDHHEEEEAACADHEDAEAEFAEFAEGAEGAEAAEAGGBCDDFHAHHFFHFCCACAEFAHFAECHEAEDDHDGBBCBDFEHEAHBAHBAGCCDDDFGEGEFBBDBBCCB,False +313,3.0,1.0,2.0,0.0,2.0,1.0,1.0,1.0,HACAACEFGEB,True +314,19.0,17.0,14.0,10.0,16.0,21.0,10.0,13.0,AHDAHEEFAEAGCADFEHCEBCGCCGADDADFADFAHAAHFEHFEHFEFFCBFEBAAHEHBEBCCGHEBHCBFCFFGEAHEACBABBABFFGFFGBBBFBGDGCCBEDADAFBFFCHEDG,False +315,3.0,8.0,4.0,7.0,12.0,10.0,4.0,14.0,DHEDBEDBECHEFFFCHDAEBAHHFHFEGFECEEDEGHBGFBAHBHEBEDCFHHFHFDHGBH,True +316,19.0,13.0,26.0,20.0,13.0,13.0,16.0,14.0,AFCBGBFCAFCEECHBBAGCDGCFGHEBHEDCCAHCFEAEDDEDAGCAFCACCADCGDEBFAGDHGDCBACHAGHBFHCGECDCAGCADADFGDCGDGEDFADCADFFDAEDHCCHCBHGBHEBFGBCABHHDE,False +317,16.0,18.0,21.0,25.0,22.0,16.0,21.0,17.0,GDDGDDEDFEGFEDEEDHBDHBCHDHBBBBBBCCBCCHFCHBCHEHADGCDGCBGAFABCEDFFAEBCHBDDEADCGDEFAEGAGCCDCCGFDFBDHCGHGAAFEADAAHEBHEAHFCCDCEAHEAFGBGEBGDGEFGFHGEHFAFDGEDGECEDG,False +318,23.0,22.0,20.0,24.0,12.0,20.0,16.0,25.0,AABCHBFHCDHCGFGHDHHFGAGHBGHBGCEECAEHGBCGDDDHCFHGBHGBHEBHDCCAHCAHAHCAFCDFHHEBDDBGDGEABBAEBCDDFDDFEDFACFABFCHHCHHGBFAEFBCGBDHFDBFDFDAADAFDCEHCBBDFAAAAGECDABDAEFABFG,False +319,9.0,5.0,11.0,3.0,6.0,3.0,10.0,12.0,HABHDEGCCCDFCBHCHHGHAGHCGHCDHCEGCGCEGHEAHFABAECGBBAAFGAEHAG,True +320,31.0,18.0,28.0,29.0,18.0,25.0,23.0,22.0,ADEFDADBAGBEGHEGDCAHAAHCFGCHGFEGFHGCGBFDAFDCFCEBABHDBAFAFFDGDAAHABGGCAFCACCDEBDCCGCCDCCAFGGCHBDHGCHAHBBBBBCCGAADCBDEFDHCAHCHHFHAECDCHDGHDEADEDFADBADEEDGCBGCBGDGEFHAFEAFAAFGEEDCFDHFAHFAFFAEFHEDGD,False +321,11.0,11.0,8.0,16.0,26.0,18.0,18.0,26.0,HFGEAHHHHDBHGEHDFAGGDEFDEFDEFAEFBDFHDEEDEEBGEHEHHEHACGGEBHEGHEFHEHAEGFDGDDGBCEAEGAECDHCGHFEHGAGFCHHEHHFGDFEFFHBFABHDGFFBCEBAECGDABDHBC,False +322,6.0,3.0,4.0,2.0,1.0,1.0,3.0,2.0,CAAFAEHAGBDHCDBCGBAGCA,True +323,10.0,11.0,20.0,18.0,16.0,14.0,16.0,14.0,FCGBEHDGCCHABGBCGACFEFEEFEDCCCBGCFHCDAGDAGDEDFHGBAGEDFECGACGEFGEFEHCDHCDEFHGBHGEFDEFDEADBAEHFCBGCHDCHDCBDCFHBDABGAHDHCD,False +324,14.0,16.0,12.0,17.0,15.0,23.0,16.0,14.0,HDEBDGFAFHDDHDHECHEBHGHEGEGFADHGEFGDFBCEBGAFFAGFHBDHGDCGDCACFECFEHFAFBCEHCFBEFCEADHABCBBCFBAFAGFAEEAGBBECBDGBFGHGBFDDFDDFGAFDAF,False +325,15.0,13.0,7.0,9.0,15.0,10.0,11.0,11.0,BDABDCBEEECAECHCFHBBHDHEAHEAGEDEABEDHEGGFGGFEFBEHEEFBHAAAAAADAADFAEFGHHDFHGAGBBBBCDCGBFGFCG,False +326,18.0,22.0,21.0,20.0,18.0,16.0,22.0,11.0,FAHEBHABFAHGAEGHHBBBCBGCBECAAGDACFBCFEHGDHDDCDDFFCEGHEBHCFCDFCDGCHBAGCEBCBDGBDCBDHGEFADGEFABFGCFCDBCGACGABFACDEDEBDAFAFFABGEBGEGEEDEGDAGAGGEBGCBDCED,False +327,13.0,17.0,20.0,5.0,21.0,19.0,14.0,10.0,CACCAECGEGAFABCCDFAFFHFCEFCHAHBGEECEECGEFDECDECEEABFBEAEEBEDHCAHAADBABFGFFGFGGFBGBHEBHGFGEFBBGCBCCBCBECBCGFEHFHBGHACEFF,False +328,21.0,20.0,17.0,13.0,23.0,15.0,20.0,19.0,HECGCCHADAADGADBEGBEABEHFGFGGFGCBECFHBAAEAHDFHFFBGEBGCBFHAABAABDCBDCAFAAHCGDCGEEGHGDEGCHGHBFHDHCDBCFEAGCAHCEHEEFEFBDHHDEBEEDEBGGAHGAHBEFBECEFABGABEC,False +329,24.0,23.0,29.0,30.0,30.0,21.0,23.0,19.0,HADHFBHFEHCEHDHCDFCBABEEBDEHDACBGDBCDBGDBADCCDABAGCEGBDGBEGCDFAFFGEFGAGEAGEADCGHGBDEDAADEHBAHCAEGBGFBFHBGEBDBBAEEDEEFAEDGCABCEDGFFGECCDACHBDGBDFCHECHECEACEADDDEDFADFAFHCFGCADCEECFCCFCCAEBGGHHCHFDHFEG,False +330,7.0,6.0,9.0,9.0,7.0,8.0,16.0,10.0,HGGAAGEEFBEDHFDAFBAEDFGHFAHGDHEECGHCGCCACGFGHFAHEBHCGGCBGDHGDCGDCGBGDBDF,False +331,15.0,22.0,24.0,18.0,22.0,22.0,16.0,24.0,ABAFBECDEDAHCCGCAAHHCHHGBBGBAGBDGEDEHAECACBBFHHEHHEHHFHDCHDCBGFHFFHAEBFEFGDHAECEECBEFEGCCFBCGBCDEGHBGHFAHFGDBGEAGFADCBCCHCFFDEFEEFBEFHEHDCDDBHDBGFAFFBCCBCFBDADCGDE,False +332,9.0,18.0,16.0,12.0,7.0,14.0,10.0,14.0,AADCABGADACDAEDCHGCBFHBFHBEHGEFGHGECFBCDDGDAECHBCEBCFBCHHFDHDHHFFDFBGFGHBGECCFDFHDBHGBCFFABBACBCBBCB,False +333,24.0,10.0,12.0,14.0,8.0,11.0,24.0,18.0,AHAAHAADADGFHEEGBECBDCEACAHEGHEFHADAADFHGBHGBGBCGAGADGADGAHCAHFHFGEGGBACDCCDGFGBHCFGAFGBGEHACHAGGCDDHDAADGHDGFCGAHBAHBGFF,False +334,17.0,19.0,16.0,21.0,12.0,28.0,7.0,21.0,BCEAFGACAHCFEBBDBBDFFDBCDBFDFFDHFABDGBDFFGFDHFCGFGHCBHAFCEFHHBHHAHFADFBFCBFCBDCHEHDCADFDDEHDECDFCAFAAHABFBDFHFCDGHDHHCHECBEAEHAEFABDEFAFBGHEA,False +335,5.0,1.0,17.0,8.0,5.0,13.0,6.0,9.0,HFEEFACCHDCHDCHFBHDDCACCFCCGCFFDEFAFGCFHAEGFEGFDCCAFCHCGDCGDCHFH,True +336,7.0,5.0,7.0,10.0,4.0,6.0,4.0,9.0,CABCEBDDFADCAFCFGCEGEHDDBFGBFHCHHGHHDFDEHDAACAADHBDH,False +337,17.0,14.0,20.0,15.0,14.0,12.0,26.0,25.0,FEFFADAGDAGFCHHBHHBAFEECECAFCDFDDGGCHGCHFCGDGGBBGDAHDHECHGCBBBHDEHCCHFGHFCHBCHDAHCAGCAGEBHEBAAACEECEGGDHCEBFEHGHCGHCGDABAGHGGBBGFGGDGHHEHDDAAGA,False +338,17.0,17.0,8.0,23.0,13.0,10.0,15.0,13.0,DFFDBGEBEBCDBFDBAEEAFGAHDDDBBDEBGEBGBAGBGBCGEDEAHHADHDDHEDHGGHADDBDHHDCHDAGAECADCHDFBBFABDAFCAGDFFCAEGAEGEFGBDGCHAHA,False +339,18.0,24.0,23.0,25.0,16.0,22.0,30.0,24.0,DGBDGDDCDGCBGFEHEAAFCACGBFEBGCGCABCAFAGEAGEAHDCHBFEGHEBDDBDDBGABGFDGFBHCAEEAGDHEHFEFEHFGHFBFFGCAGCACCDHDDHBDFGDFGEEGBFDHHBCHDFFDCCABGBDGECBEGGGHDCHACHBHHGGHBGABDABHFCHFHHDBABGFCGFCDC,False +340,2.0,2.0,13.0,7.0,3.0,3.0,2.0,4.0,ECCCDCCACCBDCDFCDGAHHFEDFBDCDCCHGCHE,True +341,4.0,3.0,4.0,1.0,4.0,2.0,6.0,4.0,GAEGBCHBCFGAHGAHBACEECEGHGDF,False +342,10.0,14.0,13.0,18.0,10.0,15.0,4.0,7.0,BFBBADBAGACCABFAECCFCCEDEHDABBAFGGBDBCEBFDBFDEHDGHFAEECCDCCFHBFDEDDFDDCDDEHDEFFBDFBDFACHAFH,False +343,2.0,3.0,3.0,5.0,8.0,5.0,2.0,1.0,EAFDCDDCHEBFEFDEFEABECBFGEDGE,True +344,16.0,17.0,10.0,12.0,19.0,14.0,18.0,24.0,DGDFEBGECFCBBGFFEFHEHBEHGCBACBEGFGGHCBHGBHAEFBFFBHHBEHAGAADFAGFAHFAHGACGAEHABFGEGHEHHEHCABDAHEABCDHGEHGAHDDHDDBEFBGDBADGCHECHDHEEE,False +345,12.0,6.0,8.0,11.0,11.0,7.0,6.0,8.0,EEABBCDDGADCAECADHABGABECBECFEFFECDEGHAFHDGHFHAFAABDAHCEHAEHFDCDEGDGD,False +346,14.0,12.0,14.0,18.0,13.0,23.0,16.0,8.0,ECHBFBAFEFGCCDDGFDBFEGFEAFECFEHFEGBDDCHDHAAGAAGFBDBGDADDHGDCFFHEEHCEBGDGCFECFEBFDACDFGDAGDGGCGBABDCBCBAFFAFFAFEAFDHFCG,False +347,13.0,9.0,9.0,6.0,6.0,16.0,14.0,5.0,GEACFCDFGAFGAFCFFDDGGDBGDEGBAAHGAHFFBFFEEFBFFBFCEGBGGCECCAAHAGHAFAAHACGGFBCBBD,False +348,2.0,2.0,2.0,3.0,4.0,6.0,4.0,5.0,EFGDDADHEFBAFECFECFHBFGGHHGH,True +349,25.0,25.0,26.0,14.0,12.0,22.0,23.0,17.0,GCCGCCGEEDFADFDCCEHCBHCBGBBCBFGBAGFGHBGABFAGFBFFACCHHFHABAABCABGHEGBCGBFFAFGACCDDCBFGFAAAAAEACEFCEFCADCAGHAFABFDGADHHGBBCHGEBGCBHCBFDHGHHCEHBBBBEFAFHDDGFDCAGCAGDEDE,False +350,26.0,15.0,7.0,12.0,18.0,16.0,17.0,8.0,GFECAAAAAHFADABEGCECDGDAGEABEGBGBBGBBGCHEFFDFFAAAGEAFBAGDHHFGGAGEADFAEEBEFCGFDDFGDFDBFBEHHAHEAGEABEABEBBADAADAFFCEGCHAE,False +351,19.0,24.0,27.0,20.0,25.0,23.0,28.0,19.0,HHCHFCDGDBGDFGCBGDFGBFEDFBGABHABCABGBGAHGBHGBABCCEEBDFGDHGDBGHFGCFGCBHFBHECGCCBCGBFGACGDCHEEDFBGABFAFFGHDAEAAHDAFDEFDEDEECFEGHECAGCECCFCBABFADCAEGEDDFHFECFEGABGAHDHECBACDGHEEEEHECBECGFC,False +352,11.0,14.0,21.0,19.0,18.0,15.0,12.0,19.0,CGFBDFCAEDFEHEHCEACEAEEFGDAGBACBFCBFABDDGHDEHFGADGHDHCBHCEHCDHBBEFGFBADCGBHEADECDCBDCBACBACBDCHFHHCHFDGCDECGHCEEGHEHFFFFGEHDCHDED,False +353,14.0,12.0,11.0,22.0,22.0,10.0,7.0,14.0,BDEBEHDFDDCDEADEHCFHCAACAABBCDBHHEDHEFBAFDACABGEEDEADFADFBGFAGCGHCFEAEDGDDFDEEBEEBEHHEHHEDEEBHHCADCACHDDGGBFEDDE,False +354,25.0,23.0,25.0,17.0,15.0,24.0,9.0,25.0,FHABBAFCCFBCFBEDDHCHGBAEHCEBDAADFADFHFHHFHBFBCHBHHEHDACDFFAGBGDEGHHGDDCCCAHCEECAEDECFBBHDFCEFBAHAAHAFHAFHBFAAFAGGACEAEDAFDHEGFCFFCDFHGFHACHABBABECCCCACCBBCDBEBBHDB,False +355,17.0,20.0,28.0,20.0,27.0,26.0,18.0,20.0,FCDHEAHEGECAEDAEFCHFEFCCCCBECHEHEDHDHHEGHEDFEHAEDGEDGEFEECECHGCDGCBEDDEDDFDDBGGCGBHHAACABGGBCGBCGDCFHCFBCFBHFAHFEFFCFFBDACFCHBHEEFBGFBHFDGGCECAAFACFBBBABBDBEHCAFFEGCADEADFFBCGA,False +356,11.0,9.0,19.0,9.0,17.0,23.0,24.0,22.0,DCFDCHHGFEAECFFCFFGEFGFFGAHGBHAADAACEFFGGEHCAHCBDFFDGGHHBFHBHHAHFFGGFEGFCGFCHCGGGGEEEFCDHCDECHECEBCFGCHBCHAEHCEGFDGCHBEHBGHBGHFAEAEGGD,False +357,15.0,19.0,23.0,15.0,30.0,8.0,15.0,12.0,EDGEGBEGAEFADGHEFEEDEDDEGGFDAEEAGDAEEADEAEBBCFBCGECBEGGACEFBGDHECHEAHEHGGABCEDDFDDEDBHDBCBACACCGCABEGHCHCCBCCAFCHBEHEHHCCBCEBCEBCEBFBBECA,False +358,8.0,10.0,3.0,16.0,6.0,11.0,10.0,8.0,EADHDFFDBFEGFGCCAFCBHDGEDHDDFBBFEBHHDAHDHEDHGDAGDAEDGDGFBGABGFDGFABBADBF,False +359,20.0,14.0,12.0,8.0,11.0,4.0,10.0,13.0,BAHGAEDBEDCADCAHBABAAFAACGBHGBHABHEHCCHBCGAEACGDCADCHGAECADFAEBDEHFCHEAADHAGHFBEBCEAGEBGBGHB,False +360,26.0,15.0,17.0,18.0,13.0,10.0,21.0,9.0,HCBGGBGGBCCDDCDCCHCHHEGGEAFEDFAGEBDHBGAFGDGAABCADCEGCFGAEABEADHABGAEGFEAFAFCACGADDBEAGAABAHGDCDEADECDBCDBCBHCFDDFAGAEGAHGAGAAFBDB,False +361,15.0,32.0,16.0,34.0,25.0,18.0,29.0,23.0,HDFHFFDABBBBEEBGEBGEDEEGAHGBGBBHDAEGCDACHECHBGDBGDBGDGDDFBGGDEBFAHHHHEHHAHDADDEDBEBBHABHAFGDDBEDHEDHDDHGCHCEFDGGDGGBCFCCFEHFGGFHAEDFDFFCAEGABDFEDGBAGBGDBCFBCHEDADDCDCBBBDEBDEBGHCGBEABFCGGEFCEG,False +362,22.0,28.0,20.0,25.0,21.0,16.0,11.0,16.0,BHCHFBFFBDDBHHBAHBADBAHBAHGCCFCBBDBBECAEFEDHHBCCFDCBBBEBHEBFGBHGDHCFFCFAHHAGAGDBFDGFDBCGEADBFBBAAFEDGEDFDAAGBAGAABEDDACBECBEFDAHCCCCGCEEHAEADEDDEDCEACEAEDDEDDE,False +363,11.0,11.0,7.0,6.0,9.0,8.0,12.0,8.0,FBADHHEHFGGCGAFEAFEGFGGHGHCCHCCBCABAEBAHDDCGFABEABFABABDEBDBHAGGFBGEEGDE,False +364,5.0,2.0,8.0,2.0,1.0,2.0,9.0,6.0,AHGACBAGHCGHGBEFDAFGACHCCGCDGCHGHGC,True +365,33.0,17.0,16.0,24.0,25.0,19.0,21.0,11.0,GDDGDDGBDBAABAFECGEDGEDFAGCACCFHCGHCDAADBACFCHEDAEHABGGHCEEEBAEFEDFDCFDHFDAFAGFBCDAFGEDDEHBEDBDCBHCAGFHFDACAGDABEABGABGAHCAGDAFFGEFDEFGFGEEEAEAAEAAEAEFBBAHBABCEGEDGAA,False +366,24.0,28.0,22.0,9.0,23.0,15.0,15.0,17.0,HEGHECCBBCBBFAEDHBFCBFBBFABGEGCFDCHCCBAAHAADABBBBAECHECEEHEEBAECDDAGDFGDFCDCGBCEBCABEABAAEHGCHEFHEDHFGGAGEHGCBBAFBAHCFEEGAEGABAABAHFHBCCCEHAEBBEGCGFFBHFA,False +367,22.0,19.0,28.0,25.0,31.0,21.0,23.0,26.0,HGHDGHDGEBCDDCAEEADEDEEHAHBDCEEBEFGAHAADGDHBHFCEGEDBFDEFEEBEBCEFCEFCBACBADHADEGDAHCCEDDEDHFAHECDDCBEFBEGBDCHCHAABAACCHCCHCDHAGCAGEBEEAFECHBCHGCGGHFCFAGGEDAFDCBECBEHDEFFGFDGFHGFGGFGFFBFHBCCGAGHAHH,False +368,19.0,23.0,22.0,14.0,18.0,18.0,13.0,20.0,GAHHDGFBGDBFFBHGADABEHCCFDCBDAGDBFBBFBBFBFFEFFAHCAFGAHADHEBFBAFBECCEBCDDAEDGEHBBBBACBAEBDECHEGFCHACFDBGCHHCHGEHCCHCGHCGECEAGACHFCHFCHDEEEEEBDACAAHA,False +369,8.0,9.0,10.0,4.0,11.0,7.0,17.0,8.0,GEHGEBGFGGFCGEHAFBBFCBHCFDCGEHAEGCCGAEGBBCHBHFEAFGBCGADGADEADCGCHGEBAEGHEG,False +370,14.0,14.0,22.0,16.0,19.0,13.0,17.0,12.0,AEAAGFACECCFHBFDEGEAGADCEHCECCADHDEGFGGCCGBHGBHGBAFDGECGECGHBDHBABFACDDEBFECFEFFCAFGEGEEGHGCBACBCBDABCGBDFEDEDDHDFBDHCCHCCHEADE,False +371,24.0,19.0,21.0,13.0,20.0,18.0,17.0,23.0,GEGEADCDGEHBDCBDHAHCEFCEFEEFCDFBEGAGFHGFCCHCCFFCFFAADAFCABBBHGCHDHEAAGCAGDABHHCHHCHGBEFAAFHAFHGHHGDADEABEGBCGCDBADEHHEHACDABGECFEFEEABEBBHBBABCAGCFGEFABHAH,False +372,3.0,3.0,3.0,4.0,0.0,2.0,1.0,2.0,DDFDDBCABHABACFGCH,True +373,11.0,27.0,14.0,16.0,27.0,12.0,14.0,25.0,BGEGGBDBADECHGHHEHADHDGAEAHEFHBFHEEDGEDECBHFEHEBHDDCEABEAHEAHEBEEBEGAHCHHCBBBBBBBCCGDFGEBBEFHFDHFDHFDEFDEDEHGEAEEFBBHBBADBCBCCBGFDGHEFABBGHCCCGCHH,False +374,3.0,9.0,10.0,10.0,8.0,7.0,11.0,11.0,GCGGBBHHCCGFDGFDHDDHFDBFEGEEBECDDAECCBBCHGCHGFHADHACBEFHEBHDBHDGGFGEC,False +375,23.0,33.0,18.0,22.0,30.0,18.0,26.0,23.0,EBDEBDHHGCCGCFGADGBCGHCEHFEHDEHBEGDDGBHGAHDAHDBCBAABCFBCHEFDADCAEBBBBHBAFBAEBAHBHFBCAGCFHDADEAFECEECEFBBGGCCGEHHBBHEDCAFAHEEFFEAGABGCDGBBGBDFBDFGDBEDBHFBGDDGAEBAGAFGEEBEECEABEHGGADGDGFHGFEAEHHE,False +376,26.0,12.0,16.0,23.0,9.0,18.0,21.0,30.0,ADDFFDFFDFFHCFCBFAGFBGHEDHEAHECHCABFAEAAGAAGDDDDCFGCAHABDEGFHBCBCADGHDGADGHEGHDGHFBHGDHCDEABHGEHBDADAACHHHHFHAGHEGHDGHDHHCCCAHDHHGGFAAAAFABFHCFGBHGAACBGCDD,False +377,14.0,10.0,11.0,6.0,8.0,8.0,6.0,11.0,FCEFBBABDCHECFBCGBHGFHECGCFAFAEFDBACADCABCHHEAHGAEBAHAAHAAGFDCBDCBDGAEHHEH,False +378,10.0,13.0,11.0,8.0,10.0,9.0,5.0,12.0,ADCHBEECEEADBACBGBBAHBGHCCHGBHCCACCFHCDBDDFFDFFBFEAEHABHDBDAFHECBAHEGHEGHEFBAF,False +379,26.0,14.0,13.0,28.0,14.0,24.0,18.0,23.0,ACEAFGAGABGAGGEHAFHDCDDFFCGHCDHAAAEFFEGABGAHHADFGDFBCAGCAGBACDDDBDDEADCCHGEAGEABHHFHCCBDABHFEEDGHBGBBHFDFCDFBDADDEDDEDHFDHFDHEDHAAFAHDGDBGEFFABAECAHHFFHFFHDFHFG,False +380,21.0,15.0,24.0,10.0,21.0,16.0,24.0,20.0,GBFFDHFBFGEFHHHHHECHEDEEBCAFAABGACGBCAECBCCBEDFCDGCEEEAEGAGGACDAFDCGBBGBBCAFFDFHBAGGDGGCCHEAFEAFCAFCAHCGGAHCACCAEGHEHEEGEEGDCHDHHGCEGAFHHEHACBCFGHBGBAG,False +381,15.0,21.0,27.0,23.0,28.0,27.0,27.0,20.0,BCBHCAFBBGEBDEDHCDGCGGCGDCFECDECEBCEBFEBFGCGGBGABFAEHCFDCHEGEFFFBGFECCEHCGFFGFHGBECCFCFAEDAGAHDAGEFFFAFDACCHCHBBHFCDAGDHGDEGDBDEHDHHFHFBHDBFDEAGCADBDDBDDEEFEEAGEGGBCGEFEEFDGHHCHFEHCAGGABCE,False +382,0.0,4.0,3.0,2.0,1.0,1.0,2.0,3.0,BCDBHDBHFEHGGCBC,True +383,1.0,2.0,2.0,6.0,6.0,2.0,4.0,2.0,CHDAEDGEDCEGEBGEFDEDGHDFB,True +384,12.0,14.0,12.0,10.0,21.0,16.0,19.0,20.0,GDHEBFGHDHCEABECBDCAHGAEGCEBCEHDEAEBHEBHFHHBBFFAFDCGHAGDCBFHGHCADBAHBGHBGADHFCHFDHCHECEECEGFEGEAGEGGEBFEGAEBAFFFEGFGGDGHFEHF,False +385,9.0,9.0,5.0,9.0,10.0,4.0,7.0,7.0,BCCBABGHBGDEGDACDBEFBHDGADGAEHHCFCEFDEBDBBDAAEEAEHADAGEHGFHE,False +386,15.0,9.0,11.0,11.0,15.0,15.0,12.0,13.0,EGCFFCFGCFHFDHCHCCHACHECAGHFFABEAHEFHEDDEBDHBDHBECDEADGFGFBGFAGFAFAHEEEBDCDGEHGAGGABAAGDFDBEABEHECFAA,False +387,17.0,16.0,9.0,11.0,9.0,4.0,15.0,11.0,DADCFEBAEAGCBBHBEGBDABFBDFDHCAFEGGEAGEACHABHAGHDGHBHHBGDEGHCAAGDAHACEGBBGABAACGACGBDGBDHBDCE,False +388,10.0,3.0,8.0,5.0,5.0,8.0,6.0,3.0,BDDGGCAECAFGAFCACADCEGCAHCADCBFFAFFHHFADEGFEGBEA,False +389,17.0,13.0,28.0,32.0,15.0,31.0,24.0,29.0,HGHCCHGBFDBGAAAAEDAFHHDEGFECFHGFCFFEHFDHGDCCFCHFCFDCFDGEHBEHGHHAACAEDAHDACGEGFEBHDHCFHEFHGFAGFACDACBHCDHCDCCDEFDEFDHFECDHDDCGDGBBCCFDHBDFBDFCGBBHAEHCDGGFHGHAGFBDBDCGFCGFDGDDFDHGHAFFAGDCEDCF,False +390,23.0,24.0,19.0,26.0,25.0,15.0,25.0,27.0,FADECFEGAEGHCFDCBGCBDDHDDHDDAGAHHAEBAGDAHBHGBFGBGGFGDCADCBHBEHDEAEHGEHDBHGBHEBDGBHECAEDADDAEHFFHFHGGCCHHEFECCGDEACEHHAHGAFAADBBDCBGABDACCADABFABEHFEBEEBDDACDEEDGGGGBHGBHCFGCFHFBHCBEGEE,False +391,4.0,5.0,5.0,5.0,10.0,9.0,7.0,10.0,FGGFGCEGEEHHDHGDCEDAHBFHFGDFEBHBHHAHFCCFACFGBFEEHEEDEAB,False +392,2.0,1.0,3.0,2.0,5.0,3.0,4.0,3.0,FBGCCGDCAHEFHFDHAGEEGEE,False +393,32.0,34.0,23.0,23.0,23.0,22.0,17.0,26.0,AABCCBCADCAHAAEFAFBABBHCCFBFGDHDHCAHFGBBCCBHCBHBFCDFBHBEABEAGEDGECBEBHEBAEFHEBEBDHAHHBGCCFDDFDFBDHBGAAACEACDACHADFAGFAGFHGFDFADFAHEAEEBEAGDDHCDEFDBHCGGDGDAHABHEBHEBEEBEHFABAHBGEBHCFDGFGFEDADCACHACBGBB,False +394,10.0,5.0,5.0,10.0,12.0,9.0,5.0,11.0,DCDEADHACFADFADABDHGHHDAHGAGEEBEFFCFAEDAGBAEBCEHDBHFFCEFHEHHEGEEDHF,False +395,9.0,8.0,7.0,6.0,6.0,3.0,2.0,9.0,BAGBECDECDCHEAHAFGBFHBAHDHHAACAACHHFHBDDBEEAEDBCCB,False +396,28.0,25.0,16.0,17.0,19.0,17.0,23.0,14.0,FBGFAAAHBHHGFCGDGGBGGEGGEFCEHCDGBBHEACEGBEADCADGEGHDGAAAAABFABFADFCCBHCADEFGEDDBDACAABAAHHHFACFBDAADBAGBGEHDEDBBFBBFBBCEAGEBHEBHEBEFBCFECFEGDGBAGDACDHCFCFGAGAE,False +397,11.0,7.0,11.0,10.0,5.0,9.0,10.0,7.0,BCHBAHFDBFCHFCDDBHGAGCHGCGGCGGFGEAEECDDFADEBFCHDCHBGABGEFDCFDFAAADAACA,False +398,21.0,30.0,21.0,28.0,27.0,13.0,18.0,24.0,CBDCAGAAEHGBHBHHFHHAHHCGHDBDABFBEHDEBCEDFDCFDCFBCEDCBAEBEDBEBBABEDGFBGFEEAEBGHBGCBACBDCEECBDCDDCAAGDGEAGEAFEGEEBEHFDHDGCEBFEBDGDFHAFHFDHECHGCDGHEGDBDBHEBHGBDAAAAEADDDCABHDCHCEHCHGBBA,False +399,8.0,12.0,5.0,5.0,7.0,5.0,5.0,13.0,HHGHBAEGABBCBBCBBCFBCBHADAAFBAEBEBFHDECEEFHGAHGHHDFHDGHAHHED,False +400,7.0,6.0,11.0,5.0,6.0,14.0,10.0,3.0,AEFAEBCFDCFCFAEFCGGCGECHFGADCBDFGCHCCABCAGGEFHEFGAFBFBGFDGFDBF,True +401,5.0,2.0,3.0,1.0,8.0,3.0,7.0,1.0,BAGCFGEEAEBHEGFAGFDGEEGECAEGAC,True +402,7.0,14.0,22.0,10.0,18.0,10.0,12.0,15.0,GHECCAABBCBBEEBEGBDCEECFGGHCHACHAHFBGGCCCCHCEFCFDCHDCHDFHECHACDBCBAEBDEBDGGEGHDCEGHECEECEEHBEHDFBFBAFHDFGFCG,False +403,14.0,14.0,19.0,22.0,20.0,22.0,14.0,19.0,ECCEDFDGEDEEBCBHDAFBAFAAECCFDCEBBEBDAHCADCFDHEBFEDFEFEGFEAFHAFHGCHEEHDDFEDFDCFDCFCBAHFAHFHHFBDFDDEHCGGBGHBAHCAGCEGAHBHCGCEDEFDFGDHGFCGBBGCHGHDDA,False +404,9.0,11.0,17.0,12.0,11.0,7.0,12.0,10.0,BCBDCEGCECEGCDCCDGGAHGEBGBHCFCAFHAFHADEAHFDHEBCCDCCDCBDHEDHADBAHCHDDGBEGFGGBECFEFEGBAGCAB,False +405,5.0,5.0,3.0,4.0,12.0,4.0,3.0,6.0,DBGAEGEEDAEHAEBBEBEEHFDCBEFGEFCAFCEHHAHEDH,False +406,15.0,17.0,23.0,27.0,15.0,22.0,16.0,20.0,EFCEGEFDBFHCCACBDDHDCFBHFHGFCECAEABGBGDHCDBCABGADFDDFECCACFAEFHDGHDBHDAHDHHDHBFEFDEADFADBDCHDEHFCHFGGFHGHHEAACAFCFBDDCEBCGBDGDEGDBGDHFCCFDEHCBBCBGDFGAFEAGC,False +407,11.0,16.0,12.0,20.0,16.0,15.0,13.0,15.0,HBGBDGBDGFGEFCCHCDHCDHFFCDBCFBEEECEFCEABEHDEDBEFHFDAFDBHBBHDACAHFAFBAEBDDDADDAFDGGGEEGHEGDFHBFHGDBGCBGBACDAHHCEAEEDHGF,False +408,16.0,12.0,20.0,13.0,15.0,13.0,22.0,14.0,HACHAGEAGFHHDDCEDCBFEDFEACBBFHBFHBCGBCACCBDDGDDBEFEGGHDBDDGGFHGAHFEGAEACDACGABAAHEABECECCECGGCAHFAHFGGFEECEHAFDGGGGCFHCGGCGBC,False +409,4.0,7.0,9.0,5.0,9.0,7.0,4.0,6.0,EFCBHCFAFFACFDHHBHCBGBBGBCEHGECBAGDCEFCDFCDEEHEEAED,False +410,12.0,11.0,9.0,6.0,6.0,6.0,2.0,5.0,DDCDHBBABBACFACEBDEHDHBFBAFBAGCAEAEEFHCBCCFHCAAEAABDABGFC,False +411,10.0,13.0,4.0,12.0,8.0,3.0,7.0,11.0,BBHBBDDDDDEEAAHAAHBAHGEHGHHAEDEEDACDBBDGCDBBABHHCGCFGFEGBAGBFDDAEHBH,True +412,2.0,7.0,4.0,0.0,2.0,6.0,5.0,2.0,BGBFGBFGBCGCEACFBHFEABHCBGFF,True +413,28.0,23.0,16.0,19.0,25.0,12.0,17.0,19.0,BHADEAEEHEEAGEFBBCDDAGHHGHAEBDFBAFBAHAEHBECBDCGDGBFGEEAEEDBDDBHDEHGECAACGACABCABFABCADEAHEDBCGFEBFEADEBEGADAAFAFHADBACHABHCCDCDBFABGAEGCGFHACDEGHHGHGDHFBHEBEGC,False +414,4.0,13.0,10.0,10.0,10.0,2.0,11.0,8.0,EEGCECCGBBGBCGDEEAGEDBHCHHADHDBHEHCFBDBGDBDDBDEADEHBCAGCBGEGCBGCBGFH,False +415,13.0,21.0,20.0,13.0,22.0,19.0,15.0,24.0,HFDBGDBHHBCCFHHFBHFBHFBHACEFEHFCBGBBFBHFDGECGFCAABGCFGCHHBHHEGFEABCBECEECGDCHHFEDAHBAEEDECDHDGHFGHFAECAFBAGBDECDCHBHHDCEFCAFEHEEGEAGEAFEDEBACBDCBGG,False +416,21.0,17.0,11.0,9.0,12.0,14.0,19.0,7.0,CGHHGBDBAGBAGBDGACGAHFFBFAGCACDAGAAEAEFCCAEFBCFGCAACGEFFBDAEDABDCEGEFCEBBHFBHEBHEAGGBGFAHFEBFBBDABFAGGAGGDGADE,False +417,6.0,8.0,8.0,1.0,1.0,6.0,7.0,5.0,BADAECHCCHCCHAAFCGFBGBBHBBGFCFHCGGBGGBFFAA,True +418,11.0,22.0,19.0,15.0,20.0,16.0,14.0,28.0,CCEHHDBHECHCGAGDCCABHFHHEHDEGBEGBDDBDEBHBBGFFCFFHBDHBCHBEHBAHFFGFCDHHDCHBEABHDBHCBAAEFDCBCCDFHEFGBDABGFBCADEFDGFAGEHGBHCBCGFAAHEEHEFHEGEEHEEHCGHC,False +419,25.0,19.0,13.0,15.0,18.0,30.0,15.0,15.0,FHCDCFBEHCABEAFAFHEFDGFDCDEHAFGAFBDBBFBBGBAHFAGFBFFBDBDDEGFBDEBHCBFCEFCEFAECAEFECGADBABAEHFDGFGGBGFBGDAAAHAAHDFHGCHFCAFEAEEDECDHBFAGHAGFEEFAFFAFAHCAHG,False +420,5.0,4.0,3.0,9.0,10.0,5.0,4.0,4.0,DEBDADFEFCEHEABEAEEFEDHGDHEDCFGCFDDGBDGBEAAH,False +421,21.0,22.0,19.0,21.0,16.0,23.0,24.0,24.0,BGGDDGBHHHHGHHDAGFAGFBBFGGFGEHBAHECFACAGHEFCEADEAEBAHBGBBACDACDHCDHCHBCDBDDGCFHHFHHAHEEHCGCBGAADFBGEGFCCFCGFDHHDHCBFDAADABBCBFCFGDECBEFDEGDEDFABFADFGBFGFAGFADHHEGABCFBGEE,False +422,5.0,3.0,3.0,1.0,0.0,2.0,1.0,4.0,ABCABCBGAHHHFHAFCAD,True +423,8.0,5.0,10.0,3.0,2.0,6.0,4.0,7.0,CAHCAGAAEDGFCGDCFHCAHCAHBBDFAFFGBFBBCCCHCEHAH,True +424,4.0,2.0,3.0,3.0,3.0,5.0,4.0,1.0,GDFGCGACDACDEBFEGHEFFAAFB,False +425,20.0,29.0,28.0,22.0,37.0,21.0,18.0,23.0,DCDEFDAGCHCHFDAFEFFEHDEDBEABEHBEBFCBEDBCDCCEGCEBCEAHDHHDAHGAHBBBFABFABACBADHEEHEEAEAAEACDCHBCEDEEBEGGEBEFDGCBBBAFDAFCAFCHEDBEDGECHBHGFGECEDGDFECFDCFGHECEEHFEBCABCADEAFEGBBHBFGBEHCCHBCGBEFCHHCHGGGGDF,False +426,3.0,6.0,6.0,5.0,11.0,8.0,8.0,8.0,ECEBAECEDDEBDGBGHDGEBGECGFHGFHACHFGHFCFBEFHHBHEADEFGCFE,False +427,9.0,21.0,17.0,17.0,18.0,17.0,9.0,12.0,BHBBHBBAFBCCHEBDECFECDEFFGHCEFCAFAEHDGHDBHABEEBEEDAECBDCECABDAFDHDGEDBBDBFAFFCCBHCDHDBFDGFGBFCHACDBCGGDGGCBFFBFEEFHECEED,False +428,13.0,9.0,6.0,7.0,7.0,9.0,7.0,6.0,HDAAECHEGFFGFGCFHCBGAADAADAAFABFBEEAFFBBCBBEABECGHDGEDGDABDAFHCH,False +429,8.0,15.0,19.0,18.0,20.0,20.0,16.0,22.0,FGDFDDFHDGAFGFHEBABCDBHFGHFCHACACCECEACEBCFGDBHFEHFBHGHHEHEBGEAFFHCFDEFDADDBDGHFBDFBCFBGAHFBECHECBECHECECCEDCHGEEGEGFDFEDBEHBHCDGDHCHHGGDG,False +430,13.0,25.0,20.0,21.0,26.0,17.0,24.0,16.0,EFFGFCDFCEHCGHDGEECAEBBEGBECFEGHAADDAFCAFCBCEECFFCFCAGDACHBHHBGDCGDGGDEEDBHHGCHEDBEGEECEEBEBBDBAEEFDGBGGBDAEDHEFCGBCGFCGAHGFHDBGGBFBFFHEHBCDBADCEDEBBGAAGHBGHBDBDD,False +431,13.0,21.0,18.0,12.0,10.0,10.0,17.0,15.0,GAFBBBBFHGFAFBGCGGBBCABCAGDHGDHBCHBHBAHGGHEGHDCDBCFBCGECAEDDHBAEBDHBDHBDACECGEGGDHADBEFCDBGACEAHBCFBEHAEHAFGCCGCCFFC,False +432,14.0,11.0,9.0,15.0,14.0,12.0,12.0,18.0,DFAFFAHDHEDFEHHEDHCFHCECBABBDGEFGEDCDCGDHHFCHFCGGCEGABGDBEABAAHAEBDEBHEGHFGHDHEBADGADBAEHCEHDDHBFAGAAFFGH,False +433,16.0,16.0,12.0,20.0,13.0,18.0,9.0,14.0,FDCFDADDBDDAHDCBDCDDCDAEHAFAABADBECFAFBCFADAGCAGCDBAFCFFEHFHBFBEHGCGGDFGDABDEECGGDFEFBHCBHBEHBEABEHBAHGAEFBEHHHFEHFDFD,False +434,15.0,21.0,15.0,6.0,12.0,5.0,12.0,17.0,CBBDBGABGCDGCEADBCCADEFCCAHCHCDHCAHCHHABHBBHABEFCGCBGAFAAHEAFGAEGAHGEEGHEGBFBEECHEBBAHHCHDBHBBHBBABBGEG,False +435,0.0,0.0,3.0,2.0,2.0,2.0,2.0,3.0,CHDCEDEHCGHFGF,True +436,22.0,21.0,21.0,13.0,7.0,14.0,20.0,13.0,BHBGDAADEDFGCFGDHGAGGAFDCCACCHEADBCFBCGBFABEHDCHCEGBGDAGAADCAHGHHGHFFDEHAGAGGABCAFAFFACHACGBDGBDCBDHAGCFEBFACHBCABCGFCAFGBEBBCBBCBB,False +437,18.0,12.0,15.0,15.0,9.0,15.0,19.0,9.0,BEAEFBCFAADCBFGDGGHFCADAADGADHCBHDGDBGDBGDCGAHEFHGFAEBAHBADGCDGCGFCHFDEFEHFCAAAFBAHAEGDEGFEDCCBCGBFGBFGACGCCADFG,False +438,9.0,15.0,11.0,10.0,6.0,5.0,12.0,8.0,CBBCECABBAHBHBCHGGEGGDAEBEDCDFADBGDBGDBGBBCDGABHCFGBFGHFGHFEAAEAABHDDCGCCDCH,False +439,21.0,34.0,13.0,20.0,9.0,14.0,18.0,22.0,DBGDFCCFEAGHBHHCHHCBHBGHBDABCCBAFBAGBDCBDBBGBAFFDHEHGCBACBAEFGHBGAFGCFBAGHAHHAGHGCDEAHABHBDFEDBDDADDHFBHFBEABEABADBHFHDBABBHBAEBGCDCFHGGGBBGFDGDABDABDE,False +440,5.0,7.0,4.0,9.0,2.0,7.0,1.0,7.0,DEBHHHHHHDFAAFGADHABBFFDFFDBEDCCCCFBDDBDAB,True +441,9.0,3.0,11.0,9.0,5.0,3.0,13.0,6.0,GCHGCHBCDDAEAHEAGAGGCGEAEHACDFBDBDGCDGDGGHGCFGCAHCACDGCAEFD,True +442,26.0,15.0,9.0,16.0,20.0,21.0,20.0,20.0,EEHEFAFDDHDDBDEEFFEDFCHFAAGHAEHADBAGHAGBADAAEABCGBCBBFGCFGEFGEFGHDEAEEAFHFGHDGFAGACGCHBCHEAHGABGBGADGFFGEEBCFDHAEBAGBADAABBHFHHCEEFFEDFHAHHAHADDGFG,False +443,5.0,11.0,13.0,10.0,14.0,14.0,10.0,14.0,FCEHCEHCEDGDBBDGEDHEABEFGAFGAFCCFHFFHFBAEEGDFFAHECHGCHDCHBGFEHFHFFBBCBBEHCHHBECDEDBEDCGGGDC,False +444,9.0,3.0,12.0,6.0,9.0,11.0,10.0,6.0,GACGCGACGBHABFCEFCEFCAFGFEGDCFBCHHHHGAAAEADCDGAGEEEEECFFCDFGDFCDFH,False +445,9.0,10.0,13.0,13.0,17.0,11.0,15.0,15.0,DGCDBCDFEFHEHHEDDEGCCFCFFCGDEECEFHHFAHFAEDGGBBGHHGCHGBACAAHEEHEEDGGDGGDGEEFEBGHBCDCAACAHDHBFEFCEDBHBBAG,False +446,4.0,1.0,6.0,9.0,11.0,4.0,5.0,7.0,GACEFGGACGDFDECDEHDEHDEHEEDAHDCDFCDBEHAGFCHEEHE,True +447,26.0,19.0,18.0,11.0,16.0,16.0,12.0,21.0,EEHFFHCBABHABHAEHAEHEFFGFAGHBHAEEAEEAGAAGCCGABDACECFHGHHEDHCBHCBHCBAGDABDCHAHEFHFHHDDFBFFAFCACABEDFEDAGDBFCBDAGFACEACAGHABBFBBEBACCCGHCDBAG,False +448,6.0,5.0,7.0,6.0,1.0,1.0,3.0,5.0,HADHAHCACGDGBDGBAECACBABDCHDBHDCCF,True +449,11.0,2.0,6.0,6.0,9.0,16.0,8.0,5.0,AGAAHAAGFDFEEFBEDGEGEEFEAFCCDEDFFGFFGFFCFAEFAFHDFCBHADHFGHACCAG,True +450,11.0,4.0,8.0,12.0,7.0,9.0,7.0,8.0,FDEFCADCGCEBAHBGECHEFHCDACDABHGBFFDFAEFAEADGADFEDHCAHGDHDFCDAGDAGH,False +451,31.0,20.0,20.0,33.0,22.0,23.0,32.0,17.0,BCCAGAAGFAGCEGDBGDACDHDHGFBGBBDBFGBHBAHECEECDEDHHDFADFEDCEGHAFBCCBFADGCBADDFEFGEHGEFGDHECAEAGEDDEBDEADAADBCBGEDHDDFCEAAHBGBGFAGFDGFDEFEGHBAHFAGFDGDDFDFABCABCAFCAFCAGCAHEGHGDAADAGEFGHDGCDGBGHCFAGDEGA,False +452,6.0,6.0,6.0,10.0,8.0,9.0,9.0,6.0,AFEABEBDGBAFEDHGFHGEDGEHCHAGHECHCCFDADDFEDFEBAGCFGFFGCBGDBDD,False +453,13.0,18.0,14.0,23.0,17.0,19.0,19.0,12.0,DCGDCDDCADEBFFBFFCAACDACDCCABCDDFDFAAEGFHFADCBGCDGEDAFGGEHHEFBFFBFFBGFCDFCGAGDDHDDHFEHGEBGHDGHAEHBGBDEFCBDDEABHAGEBEEBHEDEGBHGBFGBGEEGB,False +454,18.0,22.0,18.0,14.0,25.0,31.0,12.0,21.0,FHADBACFDHAHHDGHBFFFCFGCBGDHFFFGFFGFGGFAHCHEEHFHDFHFFHFAHAHEACEGEEBDEDFAFFBFFBFBEFDCBBEAEHDFDEEEBBGCBFCFCBGBBFEHGCDEHDECDECBADEAEEACEACECCABBECBECBFAFAGHEHHABHAB,False +455,8.0,7.0,7.0,9.0,13.0,7.0,12.0,7.0,AGEBFEADAAGFABFHDEAFFCGFDEHGABGCBHCBGBDHBDFDEGCEGCEDCEHEDHGDAGEHEEGCEG,False +456,26.0,25.0,17.0,12.0,23.0,17.0,8.0,10.0,BCAFCEBDBGCAAFAAFGCBEAEDDBADBADCHEFFEADEAEEFEEGAEGEHBEGAFHAFHDFBBAEACCAECBBBBBFABEABDBBDABDCEDFECACHFHAFHGHDCCAGFEEACEABFABFBEFAEBBGHBCHCC,False +457,17.0,13.0,15.0,8.0,13.0,12.0,8.0,11.0,HFCEBGABGABDAECBBCBBEBEEBFEAADACFHFEHFBACAACDAFHHFAHGAHAAEAHGHCGFCDFDAEEBDECCHCCFFGBEGCDFCBCAEDHG,False +458,4.0,0.0,3.0,1.0,6.0,6.0,4.0,0.0,FEEFEFFGCFAEAGCAGEADEFGC,True +459,21.0,25.0,18.0,16.0,17.0,17.0,23.0,17.0,HDAGCGGBBGBCEDCBBBEGFEGFEGFAFFCGFCBECBFFBEBBGBFABCAFAHEHEDHGDCCEAAGAAGBCGHCBHCAEDHHDFFDABEFECCABHABEDBEGBEGDGDFGAFEAGCDGCBHHDHCAHGABFDEADBADBHGAGAHFHGCHDB,False +460,10.0,14.0,5.0,9.0,15.0,9.0,9.0,8.0,EDEEGEAGEGBEDBDFGDEABFAFDAGEBBABDAGDBGFFHAEHDEABGBHABEACEFBDFBCHGCEBCEBEHHHFHCF,False +461,5.0,3.0,5.0,6.0,2.0,12.0,7.0,4.0,CEAFFGFFGFFDFHDFBDADACCGGCABAHGFBFFDGHDGHEFC,True +462,6.0,6.0,14.0,9.0,5.0,9.0,18.0,19.0,FGCDHCHHGHDGADGECGHCGCGHCEDGEFFHHFHFGBAHEFGBCGHFDHFHHCGHCGHEGBCCBDAHDHGBHACGCGFCDABDAG,True +463,3.0,5.0,4.0,8.0,5.0,3.0,5.0,5.0,DGAFBBFAHGEGGEGBECECCAHHDDDEDDHFDHBDCB,False +464,8.0,5.0,4.0,6.0,7.0,4.0,8.0,3.0,DACBACHAGHBEHDEFEADGGCFEDGEBGEAGBAGFDGFDAAEBC,False +465,13.0,13.0,10.0,12.0,11.0,18.0,10.0,10.0,DFBGFDFFDGBBBEDGEDBECEEDFHAAACAAHHHHHBGGAAAFHACDACEFFHFFHAGCBEFBEBAFGAHGDEGFFBFDBFDECCECCGBCDBFDF,False +466,1.0,7.0,5.0,6.0,4.0,4.0,5.0,8.0,DHBECBCDBGDBHDBHFHECAECFFGHDGBBGHCGHDHFE,False +467,8.0,10.0,7.0,7.0,13.0,10.0,14.0,7.0,GGBEGHAGEGBEDBCAFFBHEEAEFBEGCFGCFHBFEGFEBFHFCHFDGDDGHDGDCHAEGCEGAEDCEBAABABG,False +468,7.0,9.0,14.0,4.0,4.0,10.0,8.0,4.0,FECAECBDFBGFCCFECFDCBGCBGBFDAHGAFGBBEBCHBCAAHGAGCCCFHCFGCDAF,True +469,11.0,8.0,10.0,17.0,9.0,15.0,9.0,16.0,FHDFDDEACFHCFCAHDEHAGHACHDGBAGBEGBAGEHHDGHFEHADHAEFAGGCFECFBCDGDHHDADBCDBEDFFDFFCCBEDHFHAFHDFDB,False +470,1.0,3.0,1.0,1.0,2.0,1.0,2.0,3.0,CHADBEEBGHBGHF,True +471,17.0,15.0,26.0,18.0,19.0,21.0,23.0,27.0,GFFCCCHCDHAGAEGFGCBGCBFCFFHDFBDCHDGHFEAFEAEEAEGDHGHCGABGDCGDGGFFFACHBEAEEDEAHFAHDHHGCHFHHGGHBBECGECEEDAHCACCBBCFBCHGCHACFDCEDAHCAHFFFDABEEBCBAHFCHBHBGDGECGEHDHGDHGDFD,False +472,2.0,5.0,3.0,5.0,4.0,6.0,6.0,2.0,EGHFGBFEBFEDFHGCCFEABDADDBDGBGCFG,False +473,20.0,30.0,26.0,33.0,27.0,26.0,18.0,15.0,CGAHFAGFAFDBCDEGDEHBEGBEBFDGFECFHBFHBEEFEECCEFEFFHCDGAHABDFBAGBADBADBDGFGCDCABGAEGDDDDACFACEAFEBEGDCGCEFDEBEEDFEFFDABDHBDEBCHBHHFDDBCDFGDAGHBDABFBDDDFFBBACBCCBCABCACCHGCBFBDDEEBCGDCGDCEDCHFEHEAHE,False +474,19.0,17.0,14.0,18.0,11.0,17.0,20.0,12.0,GAGCCFFCGFEDEBFFAFCGDHGEHGEHGHGFDFAAFDADDADCACCBFBDGBGGBFEBCABDAGHGBDBBHFGEAGCDGFDCFCHFAGCBBABBABAEBCFCDEDHGHAEHAEDAEDGFDGDAHHAB,False +475,29.0,21.0,29.0,16.0,8.0,11.0,32.0,19.0,GGHBGAGFAHFBGAHFBHGBHGCEACHGBAAAFHHFHHCBGCGAHBDCCDGAAGHHDBDCBDFBDBEACAFCEDCBGABGAFEACGACGCCGBCGHAGADEAHGDCGCBBAFBADCGBEGBEGBAGCGGAGABCCHCDACGHDGEAHAADFCCHACDGCDGCDFC,True +476,1.0,0.0,5.0,0.0,0.0,3.0,1.0,0.0,CCCGCCFFAF,True +477,12.0,12.0,12.0,10.0,3.0,21.0,15.0,7.0,FDFAGACBDCBGCEFEFDGAGGBBDBBAFCADCADCFCGFCFFHFFHBFCCDAGAAGBFDCFCAFHDBBGHDGHFGBFBEFGFFAHGAGGFH,False +478,17.0,16.0,18.0,22.0,16.0,25.0,17.0,21.0,ACEFGEHAECACCHBGAFFBCFECADCEFAEDEFAECBCGBCHFGHGEBAEAADHGDGAFGDDCEHCHAEHDEFGHHHBHABFABFHCFHCFHCFBDFBHBEFFEDFCDBGDAFDGBHFBHAEDCFHBDDGADGDFCDFGDGBDGDFHDFHG,False +479,10.0,7.0,13.0,9.0,7.0,6.0,9.0,3.0,HGCDGCAGAEGAGCCBCCFCEFEAFEACGGCHDABDECHFABFEBEBADBDDBAACGCFDCDDG,False +480,1.0,0.0,4.0,0.0,2.0,0.0,5.0,0.0,GCEGEGGCCGCA,True +481,21.0,16.0,14.0,17.0,11.0,10.0,25.0,16.0,FDGEEGBBDHAHGDHBHGBGCBCCFACEAEGAHHDHBGFDGADAAEAAFHCFHDFABGCBGAGGADCHDCECEDBDACDAHDAGDBHHBAGFAEFGBFGBGHAGAAEDCBCEBHEGHDDBGGGGCAGCFG,False +482,12.0,17.0,21.0,17.0,21.0,22.0,20.0,24.0,HCBHEEHCEHCBHADGBCGBEEHHFGHFDHFCHCGHGGHBGCBCHGDDACDFFFFFGBACFECGCFHFAEDHDDBDDHDEGDECAGCAGHAEHAHFEFDEACCDGGGFGCEBCEDHFCHBHBEHDDABHFFFAFFBFEBEBBGAEGCEGCEBFE,False +483,19.0,21.0,17.0,13.0,22.0,21.0,20.0,24.0,GDGGEGFHAHAEHADHCEHDAACCBEFBEAAFFAFGHHBHDBFDFFACBGDDGDHHBACBFDHFDBFEFFGABDACDFFHGFCCAEBBHGBHBBEBGCDGCHGCHEFHEAHEHHGACCACGAHHEBGECGACFEEEBEFBCFEEGEHGEAGBFHBEB,False +484,14.0,17.0,19.0,19.0,23.0,9.0,30.0,14.0,DBADEECEEGGGCGGCHGAEDCGDCDDHDGGDEBHBBCAHHADGGGEGCECCACHAGHAEDABCHGGHAGDADBEFHHFBCEAGAGGDGGHGGACFFBFGCFGBBDBECBEDBGFEHDEBDEFHEBCEBAEGEECEGBGFCDECD,False +485,23.0,20.0,17.0,18.0,15.0,7.0,16.0,20.0,ADAADBBFAFFAFAAGCDHCHABGABCAGHBGHCAHEECBECGDHHAHDEFBGDGDBGDBAAEABGHBDCECCBGGHCEHBFABFABCACAECBCDDCBEEADEADHHDHDDGEHGEHGEDCBDCHAAGGBHHBHE,False +486,19.0,15.0,16.0,14.0,11.0,13.0,25.0,19.0,GDCGHFGHCBDBAAAAAACAGHBGADDCCHEGBCBDAFDBGDBDEAAGAHBAHADCDDEHHFHEAGCGGCGGBGHCGCBGCBDCGGGFEGBEDFHCFEBFEAFGAEGCFGCFGDEGAHFEHABFFBHHHHHH,False +487,17.0,28.0,19.0,19.0,12.0,13.0,19.0,22.0,DBDEFAHAGFBGHEGHDDBBEBHEBHDCHFEHGEHGBBACBAGAAGEBBHBDFBDFBDCCHCCAEBGDGDCEBCACFAEGAHDFCCBHCEHDEGCBGABGBDFHCFDDFDBFGAGGFHBCHCABDABHAHCAGCHGBBBCBHFDHADHG,False +488,11.0,5.0,10.0,9.0,17.0,10.0,8.0,12.0,HFEBAGAEFADDEHDEHAEHDEHAEDEEDGBCHCFECFBCHGCHGEDBEABGAHFAHFHEEGFHACECCADEDCEFCAFGFG,False +489,15.0,27.0,19.0,19.0,24.0,16.0,18.0,23.0,GDHCDCEEBEBBHABHFBGFEGDDHDFACCAGGADEBDEHABHAFHGBHAFCAFCBFCFHCHDEHDBBFABDEGCECHDDDDGEAGHAFHFEBBEAHCAHFGHABEFEHDHHDCGBEHBEBCCBGDGEBGEBEECEGBECBEBDEBFGHABHFFDGCCGBC,False +490,3.0,2.0,6.0,3.0,7.0,0.0,1.0,4.0,CBCEHEADEACEADEDBCGHHECHEC,True +491,14.0,16.0,16.0,14.0,17.0,13.0,22.0,10.0,FADFCGFCEFCEBCGBCBBCBBAFBGGBGBEEEFDBBDHEEHGHAGHAGDDGBEAAGDFCHADHGDHGHFBDEDDEFECCEGGGGGADGCBEEHDCGCCGABHDBFAFEEECCAGAFGAFCA,False +492,26.0,18.0,20.0,24.0,26.0,19.0,29.0,28.0,DCADFADCEHGDGGFGEAHEHHAHFCCCGHBAHEAECBBGGBHGBHDBAAFECHEBHGFHCAHDAHDAHACHCGHCAAEGGGDBGDGGDEGHHDCGEEGEDAEDCGFCDFEFFADHGBCABHDBEGBGBHCHFGDFEFFEBBEDBEAAEFEBFGBAHAAHECDGDDFDACCAFAEHGEDGEDCEHFGHFA,False +493,1.0,0.0,2.0,1.0,4.0,2.0,0.0,0.0,ECEECEAFFD,True +494,11.0,16.0,14.0,24.0,25.0,15.0,20.0,16.0,HFCEDHDDCEGCFADBEDCEDAFBACGFFGHDDDGBDFEAFCAFHDFHEFBAFBDEBEHCEDBHDGHDFAEFCECCBGGBFDBCDHAHBGEBEEHGGHABDGDGGDHADGAEEBFECEECGEGGEBEEBHGCHGDHGDEDE,False +495,15.0,21.0,13.0,15.0,18.0,25.0,20.0,12.0,GFGGDGBFFFDCCDGCDECAEFFFHCECCEDEEAEEBEFHDHBGGBGGEGHAGEAGBGEAFAHFACFCHGBBGBBCCDEGDFFFFABBBEBDAGDAHFACFAFDABDBBEFDEFAFBBFBBFEHHGHDDHBFGAFHEGC,False +496,14.0,17.0,8.0,12.0,24.0,10.0,23.0,11.0,GBFGBDGAFGBGEBFEHDGAFEBCGGGBABDAEDGEFBAFHEFHBFHEEBGEBAEGGEFGEABAHBGHBCFGEGCAGCEHEGHDDEBAGCAGBECDECDEGDEGDBDHEEHAEHDCAAE,False +497,8.0,11.0,13.0,8.0,7.0,15.0,9.0,16.0,EHBHFAFCAGEGGCCGCAGBAGHDFFCFHBHHDDHFCAECHDBHCBHAFFDFEHCGDFGAFCAFCGFEBBCBBCFHDHEDHFBHEBH,False +498,3.0,6.0,8.0,3.0,3.0,7.0,4.0,5.0,CHECBEABACCGCBGFHFFBGDBFDAFDEFCGBCHFHHC,False +499,7.0,4.0,9.0,5.0,5.0,8.0,3.0,3.0,ECEEFHFFACFAHAABEABDCCGFDGFCCFCCFGDABDCDEBAH,False +500,7.0,8.0,5.0,8.0,4.0,3.0,2.0,4.0,CAEFHGBDDBDDBDDBCGBCFDFDHCAEAEHBEABAAHACB,True +501,22.0,26.0,22.0,26.0,16.0,25.0,21.0,27.0,EBHCGHBFHBFBAEEAHFAHEADFGDFBFHCHCCHGAAAAAHAGBBBDBCHCEHBHHGDDFBEFDECDBFFHFFDDDDDFDAACHBDABDHGCEGCGHFGAFDCFGCFGBBGFACDAGHFGHEEAEEAHHBDDAABBCBCDDCDCGHFGHEBHABGFCGCEGCBCHBCHDGFFBFGEFDEHDBAD,False +502,10.0,11.0,12.0,13.0,8.0,15.0,13.0,13.0,GFHHEHDCHDEFDADGCDGBDFADFHFACFACACBFCGFCAFEECBECBACAFDEHBGGAAFDGHCBDCBHGBHDFHDHGEFGFHGFHDBEBGGB,False +503,5.0,6.0,10.0,4.0,4.0,8.0,9.0,0.0,FEDCEDCGBGGBCFCFEDBEGAACABCGCCGFFGFFDAGGBCABCF,True +504,7.0,14.0,10.0,11.0,12.0,9.0,6.0,15.0,BDBBGBFCEDCHDCHEFFECHGDEEHEDHDBCDHGABFABFBBDBBCEECHEGFAHCGFBHFAHFAHDCEAHBDCBDHGEHAEH,False +505,21.0,9.0,16.0,11.0,15.0,16.0,15.0,15.0,DFAGEAGEAFCCECCECFEGFHGDHAFBCHEDHEHBEAGFCHDHGAHFFCAAGAAGAAGAFEDGCDFHGEHFEDFBDCAHGAHBABEABGABEDFFHGFCEACHADEBCCBGFDCCHA,False +506,17.0,15.0,12.0,11.0,15.0,5.0,18.0,14.0,BHGDHFBGBBABHAEGAEDAEAEDBEDGCGHADCFEHAGHAHHAFADCBBGEGGBDBBDEHHHGGBGADGACHCEGCEHAABFAEHAECAECEECFBCGDCGBCGDG,False +507,23.0,16.0,18.0,17.0,15.0,30.0,19.0,16.0,CAHCHFAHFDGFDGEHAABDAFCAFBAGBHGHCDBAAFGFFGADAHDGDGGFEDFEDCCCCDHGFFGFFCHFAFEAFEFHGBEFEEFEECDBGGHHGHCEHEGCADCEBAFBFDBGBCHBFFBFFBCDBDGAGFABEAEAAFFCBFCADCADHA,False +508,2.0,2.0,6.0,5.0,8.0,2.0,3.0,4.0,AECAHCEDEEGEDCFFCBECDDGGDHECHEBH,True +509,10.0,15.0,13.0,10.0,20.0,25.0,8.0,14.0,BFFFFGHDGHBEECGECGEHFEFAGBHGBEDEGAEAHHFFHCFCFFHEFADFBCEHCEGFAHFHEFECBDCBDABDCBFCBDHBEFCEFCHFEBEBFEAFACFHFBAFEADDDBE,False +510,9.0,6.0,15.0,8.0,8.0,15.0,8.0,4.0,CGFCHFDFCDFADGADECCCFCAFBFFCCFEGFDGFCGCCEBBEAEEAEFGHDGDFCHFEFAGDABBCBCAHA,False +511,1.0,1.0,2.0,5.0,3.0,1.0,4.0,3.0,GDDGCBGCHDEEDHEDFAGH,True +512,16.0,13.0,8.0,20.0,20.0,20.0,19.0,18.0,GEEGAEDHBDFBGBGGHGEEDHEHEGFEGBEGFHGEDBBAHGFDAFDAEDGFFHFFHEEHDEHDGDGADCADFADABFHDFCEFCHFDGAGABHAFHGHCBFCHEHBEAAEAAEBCEDFGABDCHFCBFDFDDG,False +513,2.0,0.0,0.0,0.0,3.0,1.0,1.0,4.0,HHEHHEAGAFE,True +514,16.0,32.0,27.0,32.0,20.0,18.0,31.0,18.0,FFCEHGEAGHCGDDGHDFEDFDDBDCHDAABHAGDEGDEGEFCBDAEABBAGBCGHEEDCCBCCAECAGBDFBCHGHHDHADGGGCCFFAGBGFDGACBHCBDAEDBEDAGDHCDGCEGFGCEGDADDCHBGHBAHBEGBEFBFGBHDHGEBBDBBFCCCDEBDFBDBBGFBGFBGFBGFHDBCCCEBCGDCED,False +515,26.0,15.0,26.0,29.0,17.0,18.0,23.0,22.0,GFHDAEAAEGAEGCEDCDDCAHCABBAEBECGEBHHGAADFECFBCFECEDGDDCDCGDBDFGCGHDAHFADDAHCADDGDFGDEAAGAFDHGCHDCBDCGCBGCBFABGAHHBHDFHDFDDGDCFFAHBEHECCFCBACHACEGCEHHBHFGHCGDAGDAGECBFHAAGFFDEAH,False +516,12.0,12.0,20.0,17.0,22.0,17.0,13.0,11.0,EEBEADDAFDADAHHEEBGEBFFBEBCCDFCEFCEFCEFCABEFHEFCEFGFCGCGHCHDCGFBECACAGDAHDGGDHFDHADEADBFHBFABDHECFDCHCEGGDCDDCGBEAFEBECGECGE,False +517,17.0,18.0,11.0,13.0,13.0,9.0,14.0,20.0,BEFHACHEDBAAHAHHAGBAGCGGHAADEHDEHBBHGEHAEHGEDGEBCEBCHAAHBCHADHCDBGFBGHAABBFFFCCFACBGDBGDBFDCFDCBEHFHHEGBADEDHEGGABD,False +518,20.0,13.0,17.0,15.0,17.0,19.0,27.0,13.0,CFECBCGACDECDHCHAGGAGGAGGAGEAGHBGFFGHHDEHDHDDGAAGDDGDHBEFDAGBABEECEAABAAFAGFGDFCDCEFGECBCGGEGHEGHBGEFHFFDCCAFGAFEAEEFCFACFGBDCBCAHGBEGFDFHBFB,False +519,4.0,10.0,8.0,8.0,7.0,6.0,3.0,5.0,EABADFAHCBFGDFCDCCBACBEFDGBHGBHFEHFECEDHBCCBEDBEDBD,False +520,21.0,21.0,12.0,9.0,4.0,4.0,12.0,8.0,FAACBBBAABGAFADBABBDBBABHACGACBABBHHCECAACAHGDHGABCBDABAGBDGDAEDGCDGCABFEHEAHFBHGADGCCGBCGB,True +521,7.0,6.0,5.0,6.0,9.0,6.0,4.0,9.0,HDFFDAFDAFBFEAGABCHCHHBFHBGEBHEHHEHEDAECEEGACDECDBGA,False +522,7.0,13.0,6.0,12.0,9.0,15.0,17.0,9.0,FEHCDBCDGGDGGDHFBHAEFDEFDFGEAABAFBHCBEFBACDGBDGHHBFGDFEDEEGGBGGBHGFGFEGHCFBFFBGFGHBADCAD,False +523,13.0,18.0,26.0,23.0,24.0,18.0,20.0,22.0,HDCHAFHBBHAEFFCCGDFGAFCFDBHGFGEFBEGCEHDHHEGCEGEDBDDBGAFHCFHCAECHBFHADHFDHECFBCBBEEDGBCGEEEDGHFGECCECDACDGFBCACCDDGDDEBDGBDGAACABCABCFBEFEDHEDHDGHEFHECDECGAHGEHGCCBH,False +524,23.0,26.0,27.0,25.0,18.0,14.0,25.0,20.0,AHEABADDECBHGBEGDCHHCEDCECAFCACEFEEGGDGGDGEDGCFBAEAHFGDFCACHEBDDBADBADBDDACFAFAGCBBHBGGFDBFDGAAGAHGDHFBEEDCCDCBACHHCHECFDDHABAACAAGHHGBGGBGFBGFHDCBDCBHBHHCDFCDEBGHBGACGCCGECBBBEE,False +525,9.0,5.0,7.0,9.0,10.0,14.0,16.0,12.0,GDEGFEHFGFFECEBCBHHAHAGHAGDFCDHBDAFFFGFGGHBDHFDCFDCDGFEGEGCEGAGAAHAGEGHEHFEHFGCDBA,False +526,21.0,20.0,28.0,24.0,24.0,22.0,22.0,28.0,FBFFHFFDFEBCDDDFBEABCGECGECFHFFCFDAACAAHAHCDHGHHFHCBHBDHGDGDHAHCDHGABAABGCGAAFBGFCDFCDFCABEHDEAGHABHEBAEFHCAEABHGHHACFEGEEFEEGDFGDCCDCEDHHGBHGEHGECGDHDDAFCEBDHBGGECBDCBGCAGCEBCECEBCEHCDHEDF,False +527,20.0,11.0,8.0,13.0,17.0,8.0,13.0,14.0,DDHGDHCDHDDHEGFEDECAEHFFHAABEGBEHBCAGADGACFACECDEAHGABBCEAAEAGFABAABAHGFHEEGGDCEBAFGFHGAEDHEDHEABEABDHBG,False +528,9.0,13.0,8.0,10.0,8.0,6.0,9.0,7.0,ECDBCHEGHFFBEDBGDBHDBHDFHFEBBCDFDACACCBEHBAGBAGFDGADGACHABDAEABGGEGCEB,False +529,2.0,5.0,6.0,3.0,4.0,6.0,5.0,4.0,FCBFCBFCDCHDEHBFGFFGAEAHEGBCGCHDEBG,False +530,5.0,3.0,3.0,2.0,4.0,2.0,5.0,5.0,AFBAEGACGFGHCEHEBGEHGHDAHDACB,False +531,14.0,18.0,15.0,23.0,16.0,17.0,15.0,32.0,HBAHEDHGDHCDHDEHDEHDEHDHFAGADFEEHBBDFHDAEDEEHHHBHDFHDFHCFCFECABGGBEGCEBFBBDBDCCHCAACFACFHEEHCHHDHGFHGFHDCDDBEBGHAFFCGBAEBAHBGHAGFBGAHCFFBDGDCBDHGHGDHA,False +532,8.0,6.0,17.0,12.0,9.0,14.0,14.0,11.0,DEGAFHFDCCDGCHHBHCFDCFDCEGGFHHCAGEGBFGBDGDAGHCGCCGDCHDGEDBEFFCFDCGHCEHEGHACCAFAFFDFFAEBAEBC,False +533,15.0,11.0,12.0,12.0,16.0,22.0,21.0,18.0,GAAFFACGGFHDCBDFBAFBAGEAFEBFGGFDDEGFEACHFFBDFGEGDFFAHFHHAHHEHHFHFABECBDHHDCHDGGDGGEFGEHACGACGECEECEEBDBHDHHFHEFGGCABCAFEFCGGGBA,False +534,6.0,6.0,12.0,13.0,5.0,12.0,12.0,8.0,HDGAGHFGHFCHABHFEHFACCCBCEGCGDCDEADCFDHGDGFDGFBGCDCHFFEGFAFDDFDDGADCBECBGB,False +535,22.0,16.0,25.0,15.0,17.0,33.0,16.0,16.0,FBFFEECEEDFEFEEBGGDGFEAAEFCGFDGHDGDEGAAAHACFECDACDCHFCHFAFFAFEGFBDFECHHBACBCCACDAGFGDFEDFCCFHCBCCFACAAGADGHEFFCBFHDFCDHBHGECAFFGBGBFGAAAFBHFHHFEBFCDFCBACBHCBHAB,False +536,20.0,17.0,26.0,15.0,22.0,17.0,17.0,16.0,BHHBAFEEFAEFAEDBBDFEEBCEHHAAHAGBDGBHBECECCBFFAFEACEGCEFEECDDDGBDABEEBEHAAHCFCCEACDAHAGHBGFACFHCGHCFCCBCFGHDHCDHCDGCEAHGAFBADGGFCBFCGDCGCCFADECDGGEGAEB,False +537,13.0,10.0,5.0,5.0,10.0,8.0,9.0,7.0,EADEDEAAGAEEBGGHHBFFBFEBFBBDEAHEABCAHCAEFAGDAEDBFFGFAGAHGCHGHABCGBC,False +538,10.0,10.0,16.0,12.0,12.0,14.0,12.0,13.0,DFCGBCDFCDGBDCFCFFCFDAHDCBECEEBEDBEHECFECGAHGDHEAHAHHGFHGDHFFCGGCEGFGGCGCAAHHAEHCBDFBDEBAFADFAEBCBH,False +539,2.0,2.0,4.0,2.0,0.0,2.0,1.0,0.0,ACCFCAFCBDDBG,True +540,3.0,8.0,6.0,4.0,2.0,10.0,5.0,6.0,FGBFBFDBFDBFHFFGCEAFHCCBFCBECFABGDGHDGHBHHAC,True +541,4.0,4.0,3.0,5.0,9.0,9.0,6.0,7.0,HHFDFBDFAFFAEFEHGEHGEBGEAHFDEBCGHGGFEAFDDHCEBCE,False +542,1.0,6.0,4.0,1.0,3.0,1.0,2.0,0.0,EGEEDACCFCCBBBBBGB,True +543,11.0,8.0,11.0,8.0,8.0,12.0,13.0,10.0,CGFCHFHAFHGCGCCHCGHGACBDDBCDFADFADFBBEDAEGACFAHHGBHGDAEFGEAGEABHBGFBAEEGEHDFCGFCF,False +544,1.0,2.0,1.0,1.0,0.0,0.0,2.0,3.0,GDAHBCHBGH,True +545,20.0,18.0,24.0,26.0,24.0,22.0,18.0,33.0,CBHDDADAHFAEFCEHCEHEBHCBGCHAAHAFHFFEAFDAFBEEGHAGDDDACDHCEECEGDEGDEGBADBEDBAACEECHFBFCHFHHEEDBHHAEFCCHHFDBFDHCHHAHHAHGCHCCGFCGBGGFGDFBHFDGGDCEDADDADCFBCHBCBFHEHBEGAFHCCBEFFHDHGAEGDBGDEHD,False +546,29.0,23.0,21.0,19.0,21.0,27.0,25.0,20.0,BHEADFCDFGBFAFFACEAGFABFACFACFHEBHBFHDFGEGCEHCGDCDFCACAGDEBDEFAEFGEGGHCEHEAFEGECAAGAAEFFFFDFGGGCDGBGEBGHBGEBADFGCAGEADDBDDBACCCBDBBHAAABAHBACGECDDHGHHGBFEACHBFHEDCFDAHEAGCBGBAHFAHFBHFBH,False +547,8.0,14.0,13.0,15.0,21.0,12.0,10.0,20.0,CHCHGGHDDADDEGDBGFHCBECDEFBGHEECEGCFAEHHEHHCHHCHFFAAEDAHDEGBEHAAGBEHDEDBCFFEFCEFCHHEHBEHBEHEDDEGDGABCEBDBBCBFFBDF,False +548,5.0,4.0,1.0,2.0,4.0,2.0,2.0,2.0,ACBADGEEGEEBAFBFHDAHBA,True +549,14.0,13.0,9.0,11.0,17.0,24.0,19.0,14.0,EHAEHGEDBEDCEGGEHFBFBBGBGGFHAFHBFEACBACEADGFEACGFEGFADHGDAGCBGHGCFEBAHBGHAHADDAFDHGGHGFFGFFCFFEAFEGEEFFHFDBBDCBEHFFDFAEFC,False +550,8.0,20.0,16.0,21.0,30.0,20.0,19.0,15.0,FHEAEECEEGBBBBBHBBDDCDDCDBCBFFEGFBCEHEEHEEBEEHFDCEECGBBGAGAHCAFCAFGDEGCEFEHCDBEDHGCGFFGEEGEECBEFEHFHCDHBDFDDGGDHEFHGDECDEHEGACFAFFGFBGBGAFGDDDDDBEFBH,False +551,8.0,3.0,13.0,5.0,6.0,13.0,5.0,7.0,BDFEDFGCFCHFCGCAFFAFFHFGCAGHAEHCBCCEHCHDCADCFFAEFCCDHGEFAEBA,True +552,10.0,10.0,17.0,16.0,16.0,11.0,4.0,13.0,CABEDBDDCCDFHBACBAEEDFGACHECHECEDHDDBDDHAHCBHEFHEFHEDDGACAECHEFBEFDEDDHCBHCHFGBFEBDCFACEGCAACFCEF,False +553,29.0,25.0,19.0,15.0,29.0,33.0,22.0,26.0,EABECBEDDEFBHACGBHHEHFFAFFEDBAGFCHDGEDEHDGDDCADHAFFABHCFEEBAECAECHHHACCAEABEABCCECFECEGCHGCFFBFFBEFDGGAGAECHEHHDHHABDEHAEFFEAFAFFAGFHGEAGFFGFAACAEFFEGBAABFGBEGDFHDFHEFBBHDHHGHBCABABBFBBGBGGEAGBFGCFH,False +554,19.0,13.0,14.0,11.0,11.0,13.0,12.0,8.0,ABGABGBBFEBEDGCDFCEAGEAGHAGFAGHACHCDHADCADFGDCDDAFEGFEDHHAGCGCFDEHBEFCFFCFEABGABFCHEBABBACADEAFBABACC,False +555,4.0,7.0,2.0,2.0,5.0,4.0,2.0,1.0,ABBABDFBHFBEFEGBAGEAEEFDCCB,True +556,33.0,24.0,13.0,22.0,28.0,22.0,18.0,30.0,EEFABBCDBADEGEHHHCAHGEHABDDBDAGAABDGBABBAGBEBHEFDEDCHDAEDBFHEAHFAHFABFCBEHBEHAEHCHHFEHBEHFEFFHAFHAGHEGDDHBCEDGAFGECHHDHFAEFAECAGAGCEGADDAEBABAAHHAHGAHFEEECAACGFCDFDDFAFEBBGHBGBAFBEHDFGDCGDFA,False +557,21.0,20.0,17.0,15.0,9.0,13.0,11.0,17.0,FFFCCBHDBHDBDDBDDHDCGFBAHBHCCDAADHAHHADGADCCHBCFECEACECCFDABDCEHEHHEBHDFFABAABAGBEGAHGACGCGGFBBHBAFBABAGHAFHFGCGDEFBBCABAAE,False +558,17.0,17.0,12.0,11.0,13.0,15.0,10.0,21.0,AACABFAEFAEGCEBAFBFHBDHEAHEBEEHDHHBHCBFGAFGFCACBFBDFADFCDBHHBHDACECHHDABGBBGFGHDACEBCEBCAFHDEBDCAAHHFHHFGHEGAEGHFGHD,False +559,14.0,31.0,29.0,20.0,24.0,28.0,19.0,25.0,CBHCBFCBGABHAFHAGDBEEHABFAEDGEDECFFCBFDFFDEAEHDDCECEHCBACBDFBCEECGGCGFCFHEABDABDGBDAHFHHGADGEFHDGHEFHEBBEBGCBFBBDCEGFFAHGBHAFFGFFHEFHCCHBBHFEHGBDDHCBCFBCFBCADCDBCGCCBBCBECGDCHDFHBGHFGFCEEHEE,False +560,11.0,11.0,9.0,9.0,7.0,8.0,12.0,11.0,FDCFDGECEACDHCFAFGAFAFECFCHECHABHGBHBBHBGEGGAGGAFDBHDCHDBEDGABEAGACHBHDBDABGHG,False +561,17.0,20.0,22.0,24.0,12.0,25.0,33.0,19.0,GFGGFCGFGDHGBCGHGHHGHCGHDGCGCDDCHGCFGFAHCHFDFCDEBDEBGFCEFCFFGAFCCGCHACBFDFGEEBBDDBECAFGAFGADGADGDDGADGFDEBDBBDBGCAGHGGDGGBBDFHCCDCEFABHHBHEEHBDHAFAGEAGDABFAHHAFBFGDCEBCBFFA,False +562,11.0,10.0,11.0,8.0,5.0,15.0,7.0,5.0,GBAGDDBFDHFDGFAACAACBBGFGEBGFFCFFCEFBEFBCBACFFCAHCAHEEDBAHFCFFCDDAGCAHDB,False +563,20.0,11.0,17.0,13.0,14.0,9.0,14.0,23.0,BAGDHGEHCAGCGEFAEFBCCHCCBDADHBDHADHCGHAGAFEAHHAHHACGCEACAHCDHBDGGDFEBFHHDHHCAHGAHFEEDGFDECDHHEHACFGHFECEGBBCAACAABDABEGBE,False +564,25.0,13.0,20.0,11.0,13.0,16.0,8.0,5.0,AAAAFFCFFBBFABDAGEAGAHGACCFEFGEGAEAACACEFCFFCDCHFBBCBCCADFBHFDCCBGABGCBABBDFACAAFGACACDEEDECDBDAEDAHDAECAECEEHF,False +565,28.0,15.0,20.0,25.0,16.0,15.0,18.0,16.0,AADAACACCACGGBEGAEGBEGFHCHCCEBCEBDBBDBCDAEDEBDABDFFHHEAADAHHGHGBDGCAGFADAADADFHEFHFGDEBDFCAFEHFBBFDHCDADDACDHFHAGCGDAGCABADCADEAGEGCHDDBDCAGFHGHCGAEFFECE,False +566,7.0,8.0,2.0,9.0,6.0,8.0,0.0,5.0,HEFHDFDDHDBEDBEFBDBBECBAFBFDAFHAFEDDBCEAAAFHA,True +567,12.0,8.0,8.0,9.0,5.0,12.0,6.0,5.0,DADDAGBGGBCHFGFDAFCACAEFADFGBFABCDDFEDFECHECDBAEAHCAHBACBFFAFFBGH,False +568,27.0,25.0,25.0,24.0,19.0,25.0,34.0,18.0,GGBDADGGGAGEFFECFEBGEADDADDAFHBBHBCFBCGGEGEDHDHBDFBACBGCFACBCGBEGHHGCAGHGBAFAHHBFHAFECHCABFGHCDHEFEFCEDCEGBGGDAGFFGFFGAFBEFEAFEGFDBFCAGCAGCABAHHHCEACBGEBDEAACCFGGFGDBGDCCDBEGBCDFADBAGBADDADHCDHCDGA,False +569,17.0,19.0,19.0,27.0,20.0,24.0,19.0,16.0,DCECCEHDBFDEDGEAGFGFBCHBCAGAHGFDAFDBHAGEADCHDCDGCBHCEFCHFCGFAADABFABFEECGFHHDHBDEBDBCFEEFEEAECGDBFCBDHBDEBDAFDAHCGDEBDEHDFADFDDFGAFEFCAFHDBEBBDGGACDBCHGFFGFGGEGH,False +570,14.0,23.0,26.0,22.0,21.0,32.0,13.0,35.0,DEACHFHFDHEHFCHFCEFBFHBECFECHDGEDFFDEFHFBCCACCHGDFCHFEHCAHCHHCEHEEHCHHCAHDDGFBHCBEAGGDBGFBEHBHFBADBFDAFGGGABHAGHABDFBFHCFDCFDHEHCEAAEGCBGDFCFFEFDBFBBFBCHBHDBEDHDDBAFFCFHAEHCEHCBHDBCDEGFH,False +571,12.0,18.0,32.0,29.0,10.0,22.0,15.0,20.0,DAHAAEGCCHHEBCEBHDDGDDFFCCCCCHCFHDDHDHADBEFBECBCDBCDFEDGHDHCECGACDAEGGDGDBFHCFDGDDGAEFDCFDAADAADHBCBBCGEDBBHCFHCABFDHFBFCBCCBCCHCFFDGCGGCHCBFDFFDFFCFHHBHGFCGD,False +572,19.0,12.0,16.0,19.0,24.0,11.0,17.0,21.0,AEAGEAEEBDEGDECBBDAHDAFECHEFHGFGGDEHDECGGCAEHEHHCBHDDHDEGCEGAHGFEGEEGEECFADFEDEGCCABAGBAHAHHAEHACACHAFHBCBBAEAFBHDDADDGDBFHGCHFCHCCGFDHDDBE,False +573,5.0,2.0,3.0,2.0,1.0,4.0,3.0,2.0,ACEFDDFABGAGGACFAHFCHB,True +574,17.0,18.0,22.0,17.0,4.0,9.0,12.0,14.0,CCBCGGAHDAEDBCFCCHCFACFAEDAHDAHGBGDFDDCACAAFBBDDBDBBFCBECADDACBFCBHCHHABCAHGBBGBADDACHAGHDGHDHBEHBGBGGCFDAGCCCFHC,False +575,13.0,19.0,23.0,32.0,16.0,20.0,25.0,19.0,GGDDGDDCHDBGDFDDHBBHGBHBFHCEAFEHFGFEGEGGDGDFCHFAEFBCFGHDGDEGDBHDAAGHDDADEBCEGCEFCEFEDBACHAHFDEFCGFGHBBBABDCBFCHDCFFCHDDGDDGECGEDAAHAADDAFDCGCHBCGBCEHDEGFFHBDCBDBGCCGCC,False +576,9.0,9.0,12.0,4.0,5.0,6.0,12.0,11.0,BHFCHFGHEGHBGEFHADCDCGGCFGCBDABAEBACGHEGFBGBAHCDHCGHAGEAHHCCFCBGABCA,False +577,6.0,7.0,11.0,9.0,9.0,12.0,13.0,8.0,EDDGBABEGCGACGECECCBCCHGEFDEFGGFGBCGDAGHGCHBFGBFDEFCFFAGFDHBDADFADFHHFHEEHC,False +578,0.0,1.0,2.0,1.0,0.0,2.0,4.0,0.0,GCGDCGFFGB,True +579,5.0,1.0,1.0,3.0,1.0,1.0,1.0,4.0,HGAHAACAAEHDFDDHB,True +580,23.0,6.0,7.0,14.0,17.0,10.0,20.0,6.0,EEAEEHDHGCBEABGFBGEACAADADGADHCGFGGEHGAGGDEAFEAGEDEAAAAAAEGCFGDFGDEGAEAFBAHBAGDFGDFECCECGDBAAGDEGHAFDDF,True +581,26.0,18.0,18.0,18.0,15.0,22.0,19.0,23.0,FFFAFECGECGHCGACGACAFFGHGEHADHFDHBDHCACGABGAFHHGAFGABDABAFBHEBAEAHFAGCAGCGFAEDGHFGAEBAEHDDHBDFAFBHDBFCHEHHGFDDBAEHAECAHGHECDFDDHHBFHBFCBADFFDCCDBCABGEBCEBDEGAC,False +582,21.0,17.0,16.0,25.0,18.0,9.0,13.0,8.0,GAHDCGBCBACDDBDGADCEDBFDAFDADEAEEBEHADFAHEGDBGFHGHCBAAHDEHEEACDACDECFEAHAGGAEGAEFADBGEBGCDDCFDABDCCAGBADBDFFDGDECDBCDCCEEBBEBBA,False +583,3.0,13.0,7.0,7.0,6.0,7.0,7.0,14.0,CGGBGGBGFBHBBHCAEBHEBHFFFDFADCDBFEBGCBCHHHDHHDBHEGDECBAHFDHBEHCH,False +584,19.0,16.0,23.0,16.0,22.0,21.0,12.0,29.0,CGHFFHFFHCFGDFDEECFDCDDABFAEAADFBEAECAEGAECHHCHAEHFECCHGCHGEGGEDHBABFAHEEBGEHHHBHHCDBCDBADCACABCBCCBHBGHDFHBFHCABGDCFCCADHAHHEHHEHFEABEGGAFDFEEFEAFCDDEHFBHCHF,False +585,5.0,14.0,11.0,11.0,4.0,5.0,12.0,10.0,DGDBCBFGBDAEHACCEHCDCCBHFBHFBHCAHGGGCGGBGCBEDBGBAGHFCHDCGDBHABEFBDDBDDHG,False +586,11.0,24.0,18.0,11.0,8.0,6.0,17.0,13.0,GBBGABCCDDEGDFGAHEAHCAEGBEGAEABEAHHCHBBHCBHCBGGGGGGBHCBCCBDDDCGGBEFFADFGBCABGBBDCBDBHABHBBHFBDFCHCBGDHACCCEC,False +587,14.0,18.0,17.0,13.0,15.0,17.0,25.0,21.0,ECCAFEAGBAGCGFCGHADHEBGCGGCBDCGABDHBEGBCGHHGFHGHHGHDGCACAEHBBBABGFHGFDGFDBDGBAHHGGBCEFCFHHFEHFEFFAFFAGFCHCHGABCHEFHCFEBDEBDACGAEGEEHBBDEDDGD,False +588,13.0,15.0,14.0,18.0,15.0,14.0,13.0,9.0,EFAHGBHGDHGDCADGDDEEEECFACDGDGHCCFCEDCBHFBGDBCDBCGFCGBCEDDEAFEAECAFCDFDDBHABHFEEBBHBACBADBGDEABFGFFADGAGFAEFEBH,False +589,12.0,8.0,10.0,3.0,6.0,15.0,8.0,10.0,FDAFCFFHFGHFGBFHAHAADACFCCBBCBBHADHACFAHBBCGGEBECHGAHEAEEAFFFCFFHGFCGAEG,False +590,17.0,15.0,7.0,14.0,11.0,14.0,9.0,6.0,HEAFCADCHBHAFEFFEDAAFBABCGDDFAAGDGDCBEBFEBDEBAEAEBAEBAFBGFBHFCGCHGHDGFAAFCADBDDBDDGFAGFABEDBE,False +591,10.0,3.0,10.0,5.0,10.0,14.0,7.0,11.0,CFGCFEAFHGFCGAHACGFEADCAECAEBEDGFDHFEHFEHBEHFECFAAFHAECDHGDBFHHFAHCCFG,False +592,19.0,16.0,12.0,22.0,13.0,29.0,15.0,13.0,GHBEBBFBGFCCFDDECDGGDFGAFABCHFAFFABBCHBAFGHFBEFDEFGEFGDDGDDACDBCEAFEACEDDFFAHEAEDDHHFFDFBGFHGDBFHECCCFBDEBAHFAEFAGFBGDHADAFDAFDAFHAFGAGCHDB,False +593,7.0,6.0,8.0,6.0,8.0,9.0,6.0,6.0,DCHBFDCFDGACEACBBCBGHAGHFEHFEHDEGAEAACGFBFCHFCAEDFEBEDGF,False +594,30.0,31.0,17.0,16.0,20.0,23.0,18.0,23.0,ECHGCHGBBGFBGABGCDGHFFBFABDADAFEAFEHGBAABEABHABHACFACBEFADDADFBCGHHABFEBEGBCGEHFEFEBGEHGDAFBHDAFBAHBAHFAFACGDCHDCHDGBEBHEFEAFEDHACEBCFBCHBFHBAACFCBAHGHDDEADHAECACGBBABAFBFEBGEHGD,False +595,9.0,14.0,16.0,12.0,7.0,14.0,15.0,6.0,FEGFGGFDBAGEFGEFCCHCBEFBCGACBACFCCBCAFCAGGFFCBHGBHDBADADHADGBDGBDEBCHFCFCCGBDGDHEDADDFEBGGCFB,False +596,26.0,34.0,20.0,24.0,21.0,26.0,22.0,25.0,FEEBEHGEHEFHEFEEACGABBDHDDHGCGFDACBGBHGFHDADCFGCGBDAHHCFHGFEEFEAHEBHGBAABDABFAHFHDDADDFDBGGBFHBAEBAEBAHBAFACFADADDAGGBBGBBCCACFFBDFHDFHDBCBCABAECDFGDGHHEECCAFDBDEFCEFGDBBHBBHGGHFBHEGGEBCABCFBCFCAHBA,False +597,16.0,18.0,17.0,23.0,22.0,17.0,16.0,28.0,EECBEAGEDFCFADAHFCHFCHECDBGDBHDCHAAHDDBDDCDHHFHBAHBEHDEHAFHAHHEEGEEGDEBDEDDHBEBGEHGEHCACFHBDBACHECEBCACCGCGGEHHDHBFGEABFDFFDGFAHCGHCFHBGHGDABDAFGBEGFDFBDEHFA,False +598,14.0,9.0,12.0,11.0,20.0,14.0,7.0,8.0,EEAFAGFHFFBEAGHBCFFFFDFFBAFCEGEEGDCGDCBAADAHFFHAGHACDECBEDBEAACDGCEACHDDADBECBECHEAHFDEEEEEEEBC,False +599,31.0,15.0,28.0,34.0,25.0,28.0,16.0,23.0,EADADBADCDDCGEGGEAFEFGBDDCFACDECFECFBCHAEHABGFCCAECDEDGCDGCDGEAHDBBDBACEAFBFEBEDBEBEEFGAAGADGDFFCEFAFAABDFHDFHDGCDGHDFCDFHEFAEGCFDAFDAFDEFHBCDAFEECHHDDHDCFFAHHHHCHADEADADBADBCGCCHFAFCEHHAFHAHHAEGACCCH,False +600,10.0,11.0,5.0,10.0,8.0,10.0,7.0,10.0,HBFHBHGFGEFGEFAAFAGFGEBBHBDGBHHAHCDHEHBEAFDDBBABDFDCFHEBCECCADGADFADAED,False +601,1.0,4.0,4.0,5.0,1.0,4.0,5.0,0.0,EGCDDCBDCFDFBGBDGCAGFBGF,True +602,4.0,2.0,2.0,6.0,6.0,0.0,2.0,3.0,EDEEBAEDHEAGEABCHDCDDADGH,True +603,22.0,28.0,15.0,26.0,22.0,27.0,16.0,24.0,EADBBCFGEFEAGAFEACAHCDBABGHBHAEDGGDCGFBBFHFCEFCEFEDAEGEHGABFHBFDBGDBABGGCGBCGBABHAFDDFBDFBGFHFCHFCHFHECHDFFDFABFDBHDFDCFDCABHABHEHADCDDCDHFEEDAEDFEBHHAFHGBHBBEEBDHDHEDABDABAEGEEHAF,False +604,21.0,11.0,14.0,19.0,11.0,12.0,18.0,29.0,GHHGHHAHADHAHCGBCGBDGBDHDFAABAEHFCDDAACAFHBHHDEBEGAGGEBGEHDEGFGGCHGDBDHHDAAAACFACFHBHEAAEHADHGCHGHDBCFHEFHEFECDDHFDCGDFGAFHAHHCHBCGDCAD,False +605,9.0,11.0,6.0,10.0,8.0,6.0,9.0,4.0,DCGDAGDABEBBEBGEBGDDGHAHHBCCECAHAFFAEDCEFFEDCBGBBGEGDFGDBAAFDAB,False +606,28.0,22.0,23.0,19.0,24.0,23.0,22.0,23.0,GHDEEDGFDEHCEBCEBAGAAGEGGEGABFHGFAGAHGDCCDHFBADBDDBCDBFHFDGEEGCEHFFHCCHAGHABEACCACDFEEFAFGEFBCGBCBFAFFBFFDGEEGBEHBHHDCACFHCACAABAABAECCDFHHFHBDAEFHEFEECGFBGCDGEHCBGDBAAAHCAHDEHDBHABAAG,False +607,13.0,16.0,14.0,14.0,17.0,12.0,10.0,10.0,BGHBGADGDDGCECBEDBECAECGECGECFACFBEEBEADEDHFAHAAHBFEBHDCFDGDBFFBEGCAFADDHCABDACDABDHGFFGEEBFEBABCEFEHCHHCB,False +608,9.0,17.0,16.0,8.0,12.0,15.0,18.0,16.0,BGGGDCHHBHGBEACEACEGCEHFHCBGBBGFBGFAHCDGCFFCFGCBGBBGBFGBFAHFBGFBABCEGCEADHHEHHCHFEGEDHDDCDABGHECCFCFFGBADEAEHFH,False +609,34.0,28.0,25.0,20.0,27.0,20.0,18.0,15.0,FHGFEGEBBEGBEGHFHDFDAAEAAEDCFDBFEFCDCDDGEAFEADBCCACCDFHHBCHFEDABBABBABHAFGACGEEEACCACDDCBFCDHBFGBAGCGFADEADGABFABAGEEEBHBFDBFEBGEBEBHCCDCAGCAECAECAFCHGEEBFEAGEDECAHHABABBABDFDAHCABCAGHAGA,False +610,27.0,20.0,29.0,19.0,16.0,20.0,23.0,16.0,EDGGDCDCCDCCFAHFACFEEAAGGAHFADGADAEDCEACDAGDAHDCHFAFFHCGHCGDEBAEBAFHADHCBFBBDAECAECACGGGGFFCDGBHGECFBABDABGECGEFBFCBHDBHAHGACBAHEACCACHBHEFCBDCGDBGCBGHGCBFCADEFBFFGABGCEF,False +611,22.0,21.0,24.0,24.0,11.0,17.0,21.0,18.0,CGCHDBGDBABGACGAEAACCDDCDGCDGFDEHBABFCHACHAFGDEBDEBDABHGBCFBCBAHBDFBHFCFECFECGAGEAEBDGCGGCHGDFGDFCFBHFAFGAGHHFBHDAADCAHCAGEABCCBDDEDDHCCAAHFHHDADDBGHCGBFFBEDG,False +612,15.0,15.0,16.0,7.0,8.0,15.0,11.0,10.0,BBGABCABCFCHFCBCAGHHFHFFBFAAFAGBAGDEFFCFECACDACAFCABEEGCEGCAGDBCHBDDFDDFAFHACBGBHGBHCEEEGHCGFBHBA,False +613,1.0,6.0,10.0,13.0,4.0,6.0,8.0,9.0,GCDDCDCAHCHEDFDCCDGGDBHDCHDBHCGGFGCFGHFGFFHHCBBEEBDEDDBDH,True +614,10.0,16.0,11.0,12.0,14.0,10.0,10.0,10.0,DECEGBDAEDAEGGGHGAAEBAEHDGHGEBCHBCHBFEBCBFCBAHEDFEDFGAFDCFBCFBDFBCHCCHDHBDBBABFDGEEEDCEGAHBAF,False +615,1.0,1.0,2.0,4.0,6.0,3.0,0.0,3.0,HDEHFEDCEABEHFEDDECF,True +616,10.0,6.0,9.0,12.0,6.0,14.0,6.0,4.0,DFHDFBBECCFCCFBCDGAFFABDAGEADBDDACECFECGAAGHFHFFHFFDGDAFDEFDEBDAAGC,True +617,6.0,1.0,4.0,3.0,5.0,2.0,0.0,4.0,BDEHDAAFACHECHECDEFHCAAEA,True +618,22.0,16.0,36.0,14.0,21.0,16.0,20.0,16.0,BBGEBEHHHHHACECCGBEDBCDHHAHDCHDCECAFHAFDAFCAECGCCACCGFFDEGACGCCGCEGCGGEGACGACBDGGDEAEBAEGFECAECFBGECAEFFHBCCBCHEFADFDECDBCBFDHDECDGAABHCFGCAGCFGABEABCABCECCFFAHH,False +619,26.0,17.0,24.0,18.0,27.0,15.0,23.0,23.0,ADFABEBGDCGDEAEHBHDBCGECBECEEGAHGCCECGFCAFCHECFACBAHBACBAEBDEHFEDDEHGHHGHHGAHGAHFADAAGEAEDAFAADADHEGHEGHGBHDBCEECGFCHEBHBBFAHDCGAEGEEGECGHCFCFGCDDFDCBCFEAAAFEAHGBGDCDBEFCHAG,False +620,7.0,2.0,1.0,9.0,6.0,2.0,5.0,5.0,GBEGBDDHGCFGDGHEEHDEFAADAAHAAEAHEDDDD,True +621,16.0,26.0,22.0,21.0,29.0,29.0,17.0,19.0,EAFBDDEEGGEGGEGDFBBFADADCGDCBCCHCDDEDFEDFADFEDFGBFHBECAHCDBCGFCFECEEHAFHAFCGFBEHGFHEEHFEBCGBGGHABFGDAGCABFDBFDFFDEFBBBDHBEECFEHEACBFBDFHAHHEHHEHCCHGBAEBDCCEEFBBFAFCBDCBFBAFEACEGHE,False +622,7.0,7.0,8.0,11.0,8.0,4.0,10.0,8.0,DAGDCGDHGDACDBCFHHEGDEDEFHCBHEBHFDHEHBCGGEGBCGDCFDGEDCAABAABEAG,False +623,28.0,16.0,21.0,17.0,19.0,16.0,21.0,15.0,DEHGEHCAACGFGGBEFBEGGGBGFADAEDADDCCHGGACAACEBDGFCBDAAFBCCCCCAEEEECHDCEDAEFAHFABFACFGHHBEGCEFBAHCDHDBCEBCEAHAAHAABEDGECGFAGFABFAHFAHEAHDHBFCBDDAFDAGBGGDGG,False +624,3.0,1.0,2.0,2.0,0.0,4.0,3.0,0.0,GAAFDAFGGFCDFCB,True +625,2.0,3.0,2.0,8.0,3.0,1.0,2.0,1.0,DHDDBDABEGDDGBFAEDCEDC,True +626,25.0,22.0,16.0,18.0,24.0,24.0,24.0,13.0,EBGFHAFDBGEBGEFGEDHADHADAAFCAFCHGEAGACBDGBFBDFEDGEHGEHGDHGCFCEFBEACEBHGFHEBHEGFEBAECFBABCACCABAEDEDGEGCABEEDGEAGAAGCFFDBCGHAGCAFFGFDAFHFFGEBBBHBDAGDABDBDGBAFEDFCAFCEF,False +627,29.0,21.0,28.0,24.0,31.0,21.0,20.0,20.0,FAHFBGFACEAEHGHHCFHGAGFFCCDDBDGBDGBDBHEBHECCEHCAFEGEHGEHGEGGBCABADDACDEEBCHCGAAEAFCABCEBDABEABCAECAEAHHFCFGDFHDFHBCECEDCDFCDACEFBEDBFDBEBEHHECCEDAFDGFDHEEHEGHCDDADAAEGAFADCGCGFEGFEABACFAEBACBGDA,False +628,12.0,14.0,20.0,9.0,14.0,5.0,7.0,10.0,BAHEECEFDEACFADDABAECEHFDHCCCACBAEDHEBHEBHFHCFCCGCDACAADGEGCCGCGBCBBCGBCEBEHBEDCADBEGBCABHH,False +629,5.0,5.0,7.0,3.0,4.0,2.0,2.0,2.0,EFAECAECHGHFCDABDBCDBCBCABCGEA,True +630,23.0,22.0,17.0,29.0,22.0,31.0,12.0,12.0,CCDECDBBHBBHBGFACDAEHBFBGFCCEHGEHEECEFDDFDDBEDBAFEHBDHBFFFFFFFAFFAFHDFAEFACFCCGAFAAFGADGADFFEBHEGEAAFBDGBDADDAGEACECCFBBEEGGEBDBBCAADFEDCADFFDFAEFBHDDDDBCCBFGDAEHEHDDAD,False +631,27.0,22.0,17.0,34.0,24.0,29.0,22.0,24.0,FFDCFDCHHBFADFAGECGECGBFBAFBGGACBFCBACHEFEEFBEFEEFCBAEECEHAEGAEFACFADFDBFBHHDHAFHADDGHHEHDDGEBEEGFFDDGEDGADGBDHFDHFBHFHAABAADHAEHBHGDFGEAADDFDCCDCDDFBAGCFDCGDHBDHEAFDGBEGBADEFGCDBADGADHEHGFHBDHADGACB,False +632,14.0,22.0,9.0,14.0,13.0,13.0,20.0,23.0,BCFBCFAHGDHGAHEDGEBBCBHEGHDDDBAGBAGCECBBGBDABAGHDGHEFFBHEEEEHDEBDEFAAFAHGDGCDAFHAHGADGAGCDDHHFHGFHEBHBGHBFBBFGBFHHFAHCHHBECBGBGG,False +633,24.0,22.0,20.0,25.0,23.0,16.0,19.0,23.0,DBBDHHDHHEFEEFGABGFEGADFACHGEHGEHAFFAHECCEACEBBHBEFADDDDGGHGGHAABCFDCFBGFAECDGBDABEAFECFEHBAHFDBFDBDEFCBCCGDEACAAGBBGBDEAEAAGAAHBGHACCAECGCCDCGDEHAHGBDDEDDHDBHDHHFCHDBHEBCE,False +634,17.0,21.0,22.0,24.0,23.0,23.0,16.0,18.0,CBHDBHCEHCHBGDBECHEHFBCFDFBDFCGFCACCACCGDEAFGADEADFCDFBAHAGHGEBDDBDEBDHBGBDAEDBEDCEFCEFHBHCGDAHAAEDEEGGECBEHDGDBGEHFEFGEFBFFAFFCCFECEDHEGCAGBACFDGFDHFBABHADFBEFHADC,False +635,16.0,6.0,8.0,5.0,5.0,8.0,8.0,4.0,FFABFACAAFAAHAFHCEACEABFCDGCFACABGGDGCABAEBGEAGBAGHACHFEDDDG,False +636,0.0,0.0,0.0,2.0,3.0,1.0,3.0,2.0,EHGEHDEDGFG,True +637,9.0,16.0,10.0,10.0,13.0,11.0,8.0,12.0,FEDBEDBEBBEFBEHBFBFCBEGBAGBHGHDBDDEGBECEFHDDHCFHGBHEBCGBEFAACBDEFCGFAAHAHHFFAADAHDCHGCECC,False +638,12.0,9.0,9.0,12.0,9.0,15.0,8.0,15.0,EFGFDCDAGDHFCBFEAFHACHBGADEEHEFGEDHFDGDDGAECCFHBFHBCACHACHACFAFBGDBGDBHBHHBHDEHDAAAEFFFHF,False +639,14.0,20.0,11.0,14.0,9.0,16.0,14.0,14.0,BFBHEBAEDADCGDAGDAFBHCBACBAEAHHCGBCGFCGAABFCBFGADBFFFDFCDFEAGGDHDDEFFHGHHGHHEFEBHBBGDBCHBEHBEFBCABDGGDCGAFHBFABD,False +640,8.0,6.0,17.0,2.0,13.0,12.0,17.0,7.0,HCFFGFCHCCACAADFGBFCFFCGFCABGBEABGCEGCEGCACCFGDGECGHCAEGBEGEEGHBGEAFEHFEHGHGEECCGF,True +641,14.0,17.0,15.0,14.0,30.0,13.0,21.0,15.0,BBGEDAHDBBEHBCBEHAEGAFGECGACGADAFGFFGFEGDBCCBFCHDHABHEBGEDADDHEGHBBHEGCGCHEEHEEHGEHACACCEGCGGEDGFGAFDBFCAFBAFEEEHGEGFEBEEBHEFDECEEDEBGEDCAD,False +642,26.0,25.0,28.0,26.0,13.0,16.0,19.0,13.0,EBDECDGCAACBAHFACDCCBCDDHDFBDBDAHGAHGBHGBCFDEADGADGHFGBAHBCCDHBDFDFHAEEFDCGGCFCAFGACGCCFADBAEBGBGGBFGDFBFCAACAACECBBHBBGABGFCAHCDFGDCCEBCDACHBCAAEDEEDFEHEDABDACDAGDBB,False +643,14.0,19.0,17.0,9.0,14.0,22.0,18.0,8.0,GCCFBFFBEABEHDEBDGBDFAHFBHCBDEBDGBDHHFFGAFGCGHCACFBGGAGGFEGFCAFCADGGCFECECGFAGFAGACHAFHDCBBCBFABFEBCCBGFEAECDBBFFBAEEEEFG,False +644,15.0,27.0,16.0,22.0,21.0,27.0,27.0,18.0,EDFEFFDFBDGBEGBHCFHCFHFAHFGFFEHGEBGEBGABGCGEBGFFHADEDGEBFABGAEFEGFGGAGFDHFBHCBADAEFBCFCCHDFBEADEDBBBGDBDCACCFCEFDDFBHHAGHGGBGBEGCFCBFEGDAGDEHCEHEBHEBADHDHHDGCDGBAFBDCGAFGDBB,False +645,14.0,11.0,10.0,13.0,16.0,12.0,10.0,15.0,EEHEEHGEFGEDEDBGCBHHFHBFDBEEBEBAHBDGACGADGHEHHECDFHDFDFAEFACFBEBHEHAGDCHDCDGCFAAFAAGCDGCAAAHHFBCDBAFE,False +646,3.0,5.0,2.0,4.0,7.0,6.0,2.0,5.0,EEDEFDFHDFHGFHCBHFBEEEABHABFDBGCEA,True +647,17.0,19.0,20.0,19.0,12.0,18.0,17.0,19.0,HCFBAFBDFDHBCACEAFHCGGCAHBHHBHFECADGBGCDACAECGDCFDFEHBABGADGACGBEFHGFBDBCCBCFBDFADFGGFEGFHGFEBDDBDDADBFGCFGHECHCHHGGBECECCEBDEDHADHADHAFHAHAB,False +648,10.0,10.0,6.0,7.0,5.0,10.0,7.0,10.0,CHGDHGHAECAEAGBCGCEDFBGFCGBCFBHAEAFHDFBEHBGFAFFDDABDABDFBHFHHABHA,False +649,23.0,19.0,18.0,23.0,11.0,22.0,22.0,16.0,DFGDAGAEGAEDABBFDGADBHHAEGECAFDAEDACGBCGDCGHCGBCHEGACCAFDBFHBGGGDBGBFCBEGFHAHHCEDAEDBBAFAFFAFGAHCHCCDCCGBDEFHFFDBFBCFDCDDAAAGDEBDBBHBFHGFHFFHFAHGDGGDACDAF,False +650,4.0,5.0,4.0,4.0,6.0,3.0,2.0,5.0,DDHGDFGEFAECAFCDBCHEEAEEHHBACBHBB,False +651,29.0,15.0,14.0,25.0,15.0,16.0,23.0,19.0,GAFBABHAGGACGAGGAGHABDGFCGDEGEFDFACFBDAHAAHCGECDHFEHCDDEDDECGFDDFEDADAFDBFDBEGHFBAGBADBCDGAFFCEDEHAAHAACGAGDFDDFDAADCAFHBEHGEHGCGEBBHHBCDBCDHEBAEGGHGHHAAHAA,False +652,17.0,19.0,21.0,19.0,20.0,33.0,24.0,19.0,EBHGBHEFHAFCFFEAFEADEBHCBFCEFDEFHBGHGFDGDAHEGFEABBBBFBBFBBFAFEBDHBCBCGFEHACDCFDBGHGEFGACCFFFFDADGFDCFGEGHHGEHFFHEFHCFAGFBGCCGDCDDCGECGHAHEAGEDBCDEHDGHFGFCCDAAFAAFGAFDCGECGD,False +653,4.0,2.0,1.0,5.0,5.0,3.0,4.0,8.0,GBFEDEDGEDEADHGHHGHHDBHAHEFHCFAA,True +654,20.0,23.0,22.0,29.0,18.0,18.0,13.0,18.0,EDEBAEGHHFAHFBDDBGFBGDDABDABDADCCBBCEHGFCGFCDEHDFDGHDCBDHFDCBHBFHECCADGHGGEGBCBACHAEGEEFDEHDCHBEHFDBFCEACFAEDAFBGDBDDBDDBFDCFDCHDAACAABACGFCACDHHAFBAFBHEDCEBEEAC,False +655,7.0,8.0,11.0,11.0,11.0,5.0,11.0,11.0,CHBCHDCHBAHBCGDEGDACDEBAAAFBEFHFBGFEDEEAEEGDGGDGHDAHDHBEEGDECCBHCGCCGHCFHDG,False +656,23.0,22.0,23.0,10.0,19.0,19.0,24.0,14.0,FCGFCGAAEBHECHECHCGABAAFFEHBAHBCBBDEBEFDFADFGDFACFAFAHFBCEACECCDGBFEBFCCCCEGAAHAGEBGABCFBAAGFDFCEABEABECDGCGAHGHCCHBAFBHEEHCGBFGBAHBGGEGGEDBEDBDFGGGGGGACH,False +657,17.0,18.0,13.0,17.0,9.0,17.0,17.0,24.0,BDHBDGBFEBCHBDFBDHBAHBHHAAGABHACFFHHBBDDHHDHGFCFFCGHHBAHADGFDCFHCHCCBDFFGAFGAEEAGEHHBGFFGFAGHADHDCBDEFDECGAGADCAGCHGEHBEHFDABDGBCGAE,False +658,8.0,8.0,5.0,2.0,2.0,4.0,5.0,8.0,CEGBBGBHCFHBHBBABGEBHHGCFAAHADHAHGACFACFAD,True +659,34.0,21.0,21.0,17.0,21.0,20.0,30.0,25.0,HAFHDCDEGEEGAAGBGCBEAGEBGEAHCAHEAHCAHAAHFBHECECABCAHGGFGHHGEHDADFACFACFCGFCGFBBFAAHAAHBFFDAFDGFCAEAGFAEDBGBCEEFFFDEAGGADGCDFHGGHBCABCABCABHDGDGGEGGEGHEAHBDGBHHBCHDFAECGDBHAGHADABBACEFHBDEGC,False +660,14.0,30.0,12.0,19.0,8.0,11.0,20.0,13.0,DEBHHDCGGHGCHBFBFGBFDDFDDGDGBDBBABHDBHACECCACEABBAEBDBBGGGCGDAHCADCABHEFHBFDCDCGGFBGDBDBBGGBCGBEBBEBBHHBHFFHFAADGBBGBGADDFEAAGA,False +661,11.0,26.0,15.0,26.0,16.0,14.0,18.0,26.0,FEBHBBCBDCEDFABGAGEABBHBGCDGFDEBBEBBDBEGBEDDHHDHFBHEBEEGAHHDHHCBHCAHDHCAACEGBEGBDGBHBHDFHDHDFHECHCHEAHBGCFCFHDDHDDFDDAGEGGCCGDFGFAGFGDBBBHBDHFDACDCHFGDE,False +662,5.0,2.0,4.0,1.0,4.0,3.0,0.0,4.0,HCDFCFHCACAEEAEFBHABHAE,True +663,14.0,22.0,18.0,13.0,14.0,22.0,18.0,29.0,DHBHHBGHGDDFFFCBHCBFCHGCGGHHHHABCCBAFAEGBBDBFCFECFADFHBCHADBADGHDGCDACFHBFGFFBFGCFAAEACHAFHEEEEHGEHAEBGBGGBFCBFBGGBGAHDHHBECEHCHBFECFHAFHDCHDEHDEHGFHB,False +664,22.0,13.0,19.0,20.0,21.0,19.0,24.0,26.0,AACFEGGECAHDGHDGDBEHBGDGGCBEAGEFEAGBGGBFFBGGGGDCEEAAFFAHEBFEFACFECEABEFHGFHDAHCBHCFGDFHDAHGEHEAHEAGCCCHDAHFCEFCDCAFCGCHFCHGCHGCBGFBGHHDAHEAHDHHDHEEADEFDHADADDHDBADB,False +665,19.0,16.0,20.0,18.0,23.0,17.0,22.0,24.0,DAACFCEFCEHBFHAEHDBHBHABHABHAHCCGGCGCEDBDHBACCCCCAEDHEACEHEDGECGEFGCGDEFHCAHADFDEEDBECEACDGEDGFHFAEFAGBHHAHHDHAGBBFCGFEGHBHFDEFDHFHHABGABGEDGEDGEGGBCEBGDFGFFGA,False +666,21.0,15.0,10.0,14.0,9.0,13.0,18.0,9.0,ACFGBACCACCADCDGADGADGHBABGDFEDEGAGFADADDBEABDABEABAFBAFBGFGGACGBFEBFEHFHGACGCFEDGBGABCEHFGBAGFEDADBAFHHGHHDH,False +667,8.0,7.0,10.0,12.0,11.0,15.0,18.0,9.0,FAGEGGDGEAGDFCFFHBFDBGDFGBAGHCGFCDBCGBDFHGFHEACECCECAEFGCFGHFEDGHGBHFCHAEDAEDGDFGFGEBEDHAD,False +668,10.0,9.0,8.0,13.0,5.0,7.0,10.0,7.0,GFDGECCECCFHAGBGDBDFADGEDAADAADAADCGBGHBHBDHFGHFAHFACDEHBEBDDCGGCDFBB,False +669,7.0,12.0,7.0,12.0,9.0,2.0,15.0,14.0,HBGHAGHEGBCADABEEHFCCGHGGEGGCDGCHGEDGDBADBHDBGEAGAACEDDFBHBBHBDHBDHGCHGHDEEBHD,True +670,0.0,5.0,2.0,3.0,7.0,4.0,3.0,4.0,FGCFHFEDBHBBHFBGEBEEDEEGEHCD,True +671,5.0,12.0,12.0,3.0,8.0,4.0,5.0,4.0,BBCBBAECHCGHCHFCFCCBDBECBEBFEBCGHCEFGGBAGEAEEACCBDABD,True +672,11.0,18.0,12.0,10.0,18.0,18.0,25.0,17.0,AGBBGFGCFCEFCBHCADEBHCHDEBGGGGGAGGCGFHFBHDBFFAFHAEHFEFFAGBEDHHHHBBCFHAFCGCCBEHBEHGDBFEAGEHGEAGEAGEGDBGDCGDGGDFHEFEBBCBAGBEDHEFGEF,False +673,9.0,13.0,14.0,18.0,14.0,11.0,8.0,15.0,CGDBHCCHGBFGAFEEHEHCEHCACCADCDDCGBCDBHDHCBHEHABHEEGDFHDGACBAGDFEDFEDECDBDHFEHBEFFEBCEBDABAAGFHFDDFDDHB,False +674,8.0,13.0,7.0,9.0,11.0,13.0,8.0,11.0,GHHFHFCGFBEFDEDDBFDBAHFHHFCHEDGEHGCBDBHHAEGAEAAEBAGBAEFCFGCFAHBGEFECBCBBDBBDEFDF,False +675,1.0,9.0,5.0,1.0,4.0,4.0,4.0,4.0,BECBCFDGHHBEBBFBBFBCFBHGAHGCEECG,True +676,7.0,7.0,1.0,4.0,6.0,8.0,6.0,3.0,ECHEDFEAHHDFABGEBEABEDGFAGBAFBAFGFGGFABFDB,False +677,14.0,18.0,19.0,11.0,14.0,16.0,16.0,25.0,EEHFECBGCECHDBHGHHGHHGABBDFBDFBAFHAGDABCABFHHABGAEGDBHHGHFFHDFEDFHFGACBCCGCAAFFAHACDGCDBCHBFGBHEFHAFCCEBBDHCHFAHEGHEGCEHCECCHGEGBECBD,False +678,9.0,12.0,6.0,10.0,11.0,11.0,13.0,11.0,CDEAGGDGGCGBCGBAGBGEBDCAFGHFGBFEHEEACFAGFDEFGBHHFHHEHFCGDADHHDHEDAADFBFBBFBEEHEABBD,False +679,27.0,20.0,25.0,20.0,31.0,18.0,23.0,23.0,EFHEDHDDBECBDAFEEFEEAADGGCGEBGADEECEEFEECAFCGEGGBFCBFABGACDAEHBHCFGCHGCHGCFDCBHHBEABAHBABAHEAHGADGCCFECDHDFAGECHAFBADBGDBCABHADDBHCEHCEHBFHGFEEDCDHCEECGCDBCAHGHBGEAGEAFFAFGAEEAFAHGEHGDACD,False +680,27.0,26.0,27.0,28.0,20.0,19.0,14.0,25.0,GDCFDCFHCBAEGAFACFAGFDBEABDBCAHCGFFFCFBBBADBGFCDACDGDDHCEHAEHBFGBHECDEGAACBHCHEAHEFCGACDBHDACGACHAHHAHDEHFCBBABBABCHBFDCGBCHBCHFDHEEBDEHEEHGEFABHAHCAEDBCDBCDEEDCBDBHAFAGEADDADFADFDDHGDEC,False +681,3.0,1.0,1.0,3.0,4.0,8.0,7.0,1.0,HGFEDDABGFGGFGFFGCGAFDAFEEFE,True +682,15.0,12.0,11.0,14.0,15.0,27.0,23.0,14.0,FHFFHFCHGEDCEDGABGDBGFFGFHGDDFFDGCHECAEGEBCEFCEAAAAGACFAGGGBEGBFBAFBAGGAEHAEHBDGGDFDAHGGEGGHAFHGCEFDBFEHDDBGFBCFAFFEHFCHFHDFCFFDEFB,False +683,3.0,2.0,5.0,6.0,4.0,4.0,5.0,2.0,GGFDFADFADECDCGBCGEDHEDHGCBCAEF,False +684,13.0,18.0,21.0,19.0,20.0,13.0,21.0,11.0,FEEGGCAGBEGFECBEGBDHBDCCGACGFBFEHHEHBCHCCFDCDDCEACEAFHHFCFDEBBGBDCBDBADEDEGCFDHABEDGEGFDCFECDEAHEDGEAGFAEAAGHADABDBGCGGBGFBDCBDGBCGECGHC,False +685,10.0,7.0,12.0,11.0,9.0,18.0,8.0,9.0,HDHAGFAFFAFFAEBDCBDBEAFEACEACDGDDGFCHFCBCCACHGCFFCGDEFDFHEFHDCBEHGEGFFDFAAFBEFCDGHBH,False +686,6.0,12.0,8.0,11.0,9.0,7.0,20.0,10.0,BCEBCDBHAGDAGDHGDEDAGDGHBEHDDFGDGEDAEGGGCEBCBGGGCHECBFHHGGFGGFGGHGAHFBBCBECBHABFDEF,False +687,12.0,20.0,16.0,25.0,15.0,20.0,20.0,33.0,DFDHAGHAEHBHBFCFFDHFDBGGCCBDABHGGHBBCBFCHCEEADDACDFCAFBHBHDBHFBADGHDGHDGFEEBHHGGHGHFGDFCDHEEHCECCHDBDAGDABDCBFHAGEAHEHHEHFDHFDHFDEFDCCGBCHEDHBDGEHGBBGFDHAHHFEFGG,False +688,3.0,9.0,2.0,3.0,7.0,7.0,3.0,4.0,CFEHFBFBBEDBCHAFABFEBEEBDEHFEDFHBGGBGA,True +689,15.0,26.0,20.0,34.0,29.0,23.0,27.0,17.0,GAAGDABHABEGDEBDFFDHFEHFBFCBGCBCCDGFDEHDCFDBHEBEFBEBCGCDGADBDGGGAAFCEDCEDBHGBDDBEDFFGFEHBEFFCAHCHHGFDDBCDBDFEHFGAFHFFDBEABEFBGFAGHGGEECCGABDDBEEBECBEAGCHGDHGDEDHFDHDAECAECDEDGEDEBCEDDGGDEGBCG,False +690,2.0,5.0,5.0,7.0,3.0,8.0,3.0,2.0,GFGFFGFDHHAEBCCBCDFCDEADFDBFDCEDBBF,True +691,11.0,14.0,14.0,3.0,13.0,5.0,13.0,10.0,ABGFGEEGEEGEHAHBCHBDDGHBBABACBCEEGECGECGHCABCABCHBEGAEFCCGBFGCAEFGECBFHACHACHDHBGBA,False +692,17.0,27.0,23.0,13.0,20.0,16.0,15.0,12.0,BCCBCGFCGFADAABEDHEHBEADCFFEFFCABCGBABBEGBADBABBFCACGEDBEBBGFBGHBGHDEHBEHBCHACHFGEECHGFHGCCGECGDBBDGAEADFCGECDEFEFCCFAHFEHEABAFCCECEBDDBADBABBC,False +693,27.0,22.0,19.0,22.0,14.0,28.0,28.0,25.0,FCDFEDBEDFECFBHAAHEACBFDEGDCGFFHHFADGABFAFAAGGBHFECAECAGCGBDGBDHBHCBHFEHBBAFAAFAFFCHFGGFHAADCCGCCGBHGDDGFDGBDGBABHAGFDBFGBHAEFFDGFDGCAACAGGHDGAGCDEHDHBGHEFCEFADHEHABHAFHEHHDBGGBFCBGCHAD,False +694,18.0,13.0,19.0,10.0,11.0,15.0,13.0,6.0,GDGHAABAGDGHFBFGBCGACGAEAFDAFDECHECACBFCBACBEBDGBFACEEBEDCEACEBBDDBGFAFFDCFECDHCACCGBFGHGCEGCAAHAAFCAFCFF,False +695,10.0,11.0,11.0,10.0,20.0,12.0,15.0,5.0,DBDBFDEGDBGEEGEGFAAEGDFCFECEEAEEBHGGHCGHCFACGHEGEEGAEFCEFBAFBAEEACCGFDBFCHACEDFADFGBGCBDEBEGBD,False +696,11.0,15.0,9.0,15.0,19.0,14.0,16.0,14.0,BBEABEBFEDFHBEDCFCEDEFDECCEFGFGBHGBCGHGFHEBDGBFGCFGDGDACDAFBFHBHGECGEHDEHBBFDEEDGEFCAAHEABEHHEAHEAHDAHDGGDBGFAGAD,False +697,4.0,10.0,3.0,4.0,4.0,9.0,13.0,9.0,EFFBHHHHHCADDEGDFGBBGHFGBBBBHBACEHCFBEGDGGFGGFGAFGAGHFGB,True +698,8.0,6.0,6.0,10.0,3.0,3.0,10.0,9.0,CHGBHGEHGAAGHDGDAGDBDHADHBDHDAFACBCFBGEHCEFCGABGAGDCDDH,True +699,23.0,20.0,26.0,25.0,24.0,29.0,20.0,24.0,CDBFFGEGEACCACDGBDCHACHACHBGDBCFBHFHHFHHAGHAGHCHAEEGCEHEEFFCDFDDFDFAAEEFEEFBEDAEDFGDFGDHHDBCBBCEBEABADDAEDGGGCEHAGBEFBCFDHFBEFADFDCEHFEHFHADCFDAFHAFBFCEDDBCAHAACGCBFCDHBFHDAGFEGFGGCCGCBBCAHGE,False +700,29.0,20.0,21.0,24.0,24.0,23.0,13.0,26.0,EBHEBHBADGAHAAEEACGAFAAFBBFCHDBHAGCDEBDCDDAHHBCEAAFHAFCABDDEDEEDFHDFCDFBEGCFGEFAFGCHGDHFFEFHEDDEADBACACEFCBHCEHCAAEAECAEBFDAFHAHGAHGBGCBDHBDABDHBDHADFGEBABHFCFFAHFDECHHCHHCFCGDEGEE,False +701,3.0,7.0,7.0,3.0,6.0,6.0,4.0,11.0,CEFCFHGFHBHEAHECHEBBAHAEECHCDHCFFCHBGFBDDBGHBGH,False +702,9.0,6.0,16.0,15.0,12.0,8.0,10.0,9.0,FDCFDCDAHDGHFAACBCHDEHEGDEDDFDDEGCGCDBCDEAFCBCCBCGACGACHHEEHADDAEDCECFECFAGGBBEHFGHEG,False +703,6.0,1.0,3.0,5.0,2.0,9.0,6.0,6.0,DABEAHCFGGFAGFHHFCFFHDFHDCGFFGDEGDHAAA,True +704,4.0,1.0,0.0,2.0,2.0,1.0,3.0,0.0,BGGAAGEADEFDA,True +705,18.0,19.0,12.0,21.0,25.0,19.0,18.0,24.0,FDAHBFHDCHACHAEAEEBDDDDDGFHHFEHDDBDAAAFHAGGAGDABCHGCEGCFDBGCBEFHFDHFHHEGCFABHEBHCAHBBHEAEEAEGAEDEBGFCDHEEHGEFGEFBDFEGFGHFDHFBHDBGDACBAFBDFEHEECBEGBDGAEGEHBC,False +706,17.0,12.0,10.0,18.0,25.0,13.0,22.0,21.0,AGEHCDCDAEDAEBAGGHGGHDCHEHEFCEABEGBEBHAGABHABFFGGFGAFGDBGAEDAGFAHEEBFFAEFBEHCEFDEFEHDCHDCHDGAEGAHHFHEBEEGABGDHGDHBDHDHGCEDCHFCEEDDEHDGAGGE,False +707,18.0,24.0,22.0,26.0,29.0,18.0,27.0,19.0,HFHHGDEGFHCDHCEGFEGBDCEDEEFFBFCAEBBGABHADAAGABFDCGCBHABAGHDEDEEHBAHDAGDBGCBDHHDBEEGCFGCHCFHBFDEGDHDFHAEDAGDFGEFCEGGEBGCCCCECGECGCHACEGCEFCDFBDFBGBEABECBEBBGAHGDHDDAABGGBEGAEBEDFDDFEDE,False +708,20.0,10.0,10.0,16.0,13.0,13.0,19.0,23.0,FFHDFHCCACGGGHEEHDGGAGEAGHAEBAHDGHGGHBGAGFCBDCDDADDCEHADDDHBAHBAHBGGAFAAGAGGBGFHAHHDHGEHEFHCFHCBACEDBDDFCEFAHFAHEAEFHFABEDHE,False +709,5.0,8.0,2.0,9.0,7.0,8.0,16.0,8.0,CGDAGDFHDGABHDEFFBFFBEDGGAGGCEGHHGADEFDEDHEDGFBGHGGHGGBGBBAHEFB,False +710,2.0,0.0,1.0,2.0,0.0,3.0,1.0,3.0,FGHDDHAFHAFC,True +711,11.0,11.0,7.0,14.0,11.0,15.0,19.0,23.0,DHDDADGHBGFBGHHGDGAHHHGHHGBCEDCHDHDECGGFDDAGBHGBGDAHBFFBFFCHFCFFHBFHEHHGAFGAHGHDCDDAGEHGEHBFHEGBAGFAEFCEABEAEEF,False +712,22.0,16.0,19.0,9.0,22.0,12.0,19.0,16.0,HDGBAGAAGFEEFADBADHGCGCDBCABEACGHGEABEAFGHFEHFGHFGHCGEFGEFHHACDAHFCGECEABEAEEBBABHEFEAGEDGBCEHDEADCBDABCHCCHBCGAGHACEACHFCEEBAEBAGBGFCC,False +713,10.0,16.0,20.0,25.0,19.0,11.0,23.0,14.0,FDCDDBFDGCEFFEBBEBBFDBHCFAAHGDHDBFFGFDACDAEDGEGGDCADCDDGEDGEGCEGDADCGDCBBHEBDECEHCEHGBHACEGGDCGHHGHDGCGGCGCDHHDECCEBEEDABBAGBGEAGEFDHFBHCC,False +714,7.0,8.0,11.0,9.0,14.0,8.0,8.0,14.0,AADAFBHGCCGCDHHFHBCHDCHDEHEEBFBAFHDGHDHHEAFEFCEGDHBEHCCFCHBBEDEEAFEAECGECGEGDBG,False +715,4.0,5.0,2.0,4.0,4.0,2.0,5.0,7.0,BEEHHBHHCDHCGEBGDBDHEFHFAAGAAGBDG,False +716,2.0,4.0,4.0,2.0,5.0,4.0,1.0,3.0,GBACBHFFEFFDHBDHEAEECECCB,True +717,15.0,12.0,19.0,9.0,14.0,21.0,18.0,23.0,DBHAHHEFBFAGHAGHAEHFEAAGCGHBFHBAHDCHCCDAGGHGFDAFEEEGECHCCEBGDAGCAGHGFACDHBDGBAFCFFCDFCFFCEGCBGFBCHBHAGHFHCBHAFHCFGCEGCEHFEBEEFFHDFH,False +718,21.0,29.0,17.0,17.0,19.0,12.0,14.0,21.0,BHBBDDFDBFDBDHADHBCABAHFADGBECCFDBADGEHHBBEGHEDHCHEBHBHHBEEBCABFBBFBFDAFABDGCEGCEGBEACEBBBBCDCHGEDEEGGHGAFGABGABAAHAHHAHGAHGEHCDCFDCFEEDEBHCCCACAAFABE,False +719,15.0,18.0,17.0,14.0,22.0,18.0,20.0,22.0,GGECFCHFHBEHBEDBEFBEHBDHBGAGFAHFAFECFDFHGFBGDEHECDGCAEFHEFBDGHDGDBGBBGBHGCCGCCGCHHEBBBBEEAHHBFEACADDACGCFEHFEHFAGAHGEHFAAFCHDCEGCEFDEGBHGDHEECAADA,False +720,4.0,4.0,3.0,2.0,1.0,3.0,4.0,4.0,BFBBFHBCHAHDAGEAFCADCGGGH,False +721,22.0,14.0,33.0,22.0,22.0,16.0,25.0,18.0,EGACBDEEDAADHAHBABBAEGAEGBHCBADGFBCFBAACFEEFEDHBDCGECHHHAGEAFECFEGFGAFGHCGAFGEFECFGCABEEGGDAGDCCHCCHGDEGBEDBACAHDACCCBHCAHCHDGHAECDDCDHCFCDAHHCECGECGDCGFGECCCFCCDDGDDGDFGBF,False +722,15.0,12.0,9.0,7.0,14.0,11.0,9.0,13.0,HFDHFEHEGDBCFBCAAHFAEFGGDBADEAFEAHEAHFBGFHEAGEDGBBABHGEHGECCABCEHDBADCFEEFAHFGHEAHACCABCBB,False +723,25.0,27.0,19.0,19.0,29.0,24.0,29.0,27.0,CHBDGEDBEGCHBAGECBACBGCEACAGCAGEFHHHGHAGAEDHGCGBBACHDGDAGDAGBFFBGFBDFEAFBABACDEFFEAHHAEHGHHBFABFACHHHEBGBBEABEAHEDGEDBFDCHDBGGEHHEGHFCHFHAFDAFEGGHGECDFGGBGCFEAGECBECBECFEAFEBFEHFEHBDDAEDADDFCBFEBFGHG,False +724,7.0,6.0,4.0,4.0,2.0,2.0,7.0,4.0,BACDABGAGDBGHFGHFCHAEGADGBEGBAADCBHC,False +725,13.0,14.0,14.0,9.0,9.0,11.0,7.0,5.0,ADEDDFDEGBCACCABCADGAFGFGAEGAGBAFCFFHBBHCBDBFEGAEDBDFHCEECEAFBAFHCFCCDBCABCABHBBEC,False +726,6.0,1.0,2.0,1.0,0.0,2.0,3.0,0.0,ADAAGACFACFBGGA,True +727,22.0,23.0,26.0,27.0,23.0,28.0,17.0,22.0,ECCBCCADCDDGGAHBAHFHCGHEGHCAHGHHGBEFCAFBAFHDFAFCCBACDGCBGHGEAGCDECFEBEEDFDFBHGBAGBADFEDAHDACDGEFEEHGEHFAHFAEBDBBEBFEDAEDHDDCFDGDABEGDFHBCBFDFFACFAFHEFHABDCCEABEFFHCFBFFBFCBDCBDCEDGDAHDCHCE,False +728,0.0,0.0,3.0,1.0,3.0,4.0,2.0,2.0,CEHCFCGFHDFEGFE,True +729,17.0,19.0,22.0,26.0,19.0,16.0,18.0,23.0,GFHGAGFACDAEAGFDCBCCBCBBGBDGEGCEHDDADHEDBADHDEFBEDBDGBCGAHHAEAAEBDGDGGDGABBECDEFDEFHCAHBDHBHGGDFFEFDCCDACBAHEABCHEEFCEFHGFHDEBGEBHHHHCFHEAHBAHCDDDDCGFCHFCHCCFCD,False +730,10.0,12.0,10.0,12.0,5.0,3.0,7.0,9.0,GGBHAHCBEBDABDCEDEGDCGDAFAHGAHDADDACHACGECADHABCCGCBBCBBHHBFDEHDBDFB,False +731,8.0,9.0,15.0,9.0,17.0,19.0,15.0,6.0,BHGBCGBCDBCFBCBACFAFEGFECFEGFGCEGCGADEFECHEDEEFFEFFGFFGDFCEGCACBAFADCGEEGDBADFAHHDGHGFEEDCEHFFBGEC,True +732,15.0,25.0,16.0,23.0,8.0,23.0,16.0,19.0,CCGCCHDFHDFABAHDHGDBFDHDDBBDHBGHGFDDFGGHEHABDFCHFAFCACBBDDBDFBDABHABGBEDBEDAFCFBCFGEBBHCBABGABGHBGHFGCFGCFGEBEFADCHFHFFCDDCHAEHBDGADAADGFCFFBFEBH,False +733,26.0,12.0,25.0,16.0,6.0,12.0,11.0,16.0,DDEFFEHBCBCAGCHGBHAAHCAHAHHBHHGGHCFDCADCADABFCCGAFDAGHCCCACFADFADAHBGBCFFDBCHAFAAEDEBAHBAEFAFBADBDDADCCCCCCCACCGCDGADGAEAHGH,True +734,24.0,26.0,16.0,18.0,21.0,14.0,24.0,22.0,HGDGADCHDBBAEBDEBDEBEEDECFBCAGCBCHGDBGEBDEBEEBDGBGHHFCDDHGDAGHADEBDAAHBGBAHAEEGEBGEBAACFHCFACFHFAHFAHFDHCBEAHEHBCHAHAEDGFBGDBGFBHBEGDGGACEACACBACFAGGEGBFBHAGHAGCFGHF,False +735,22.0,22.0,29.0,19.0,27.0,26.0,31.0,18.0,FACFCCFCAHCGBBDADAGDFEEFAEFAHADEGDACBFCBFBHGCGGCFFBGFGFBBHHBCAADGCDECGGCGGCAGCEGEGGDDGAGHAGHFCFCEGDGCFFBDEBDFBFEEEHEHBEAEEAEEAGEFDEGDBBEHGAGFDGEDHBCHGAAAAABCECCECCHCCDFHBFCEGEDGFBFCBFHBFHDHHCGEB,False +736,3.0,2.0,3.0,3.0,1.0,1.0,2.0,0.0,DCBDCBGCAGADEAF,True +737,25.0,20.0,13.0,20.0,9.0,15.0,15.0,17.0,BBCBGDDHBCECEDCBDHGDAGDAEAACDBCDAAHFAEFDCFAFBAGAGBABHABDABFAFFDDHHHHBFHDFGGHDCFGGHHGAAEAABCAGCBGCEGABCADEBBEFBDFHGFHDFHCFHAADEBDGADABH,False +738,15.0,21.0,15.0,20.0,23.0,14.0,16.0,14.0,HBDCBCCDFDDBDABDABDFDHHBEGEFGEFGECGECGECABBEGFEGFGFBABDGBHGBHCAEBBEBEDDDBHDAFCACCEBHGGDEDAEACFBFFBGFGEEHHEHEAHADFCDCAFCDEBDCDEGEHGAHAHEABE,False +739,6.0,4.0,7.0,3.0,11.0,9.0,13.0,4.0,CEEGFEGFDGBBEFGGDEDHCCEAFEAFBAFGACCAGAFEBFEGFGCHGEHGECGHG,True +740,18.0,18.0,17.0,21.0,22.0,23.0,24.0,19.0,CHFCHDGHDGBDCFEEFEDGHDAHDAECAFGFFHFCDEGAHBDBEDHEGAEGAEFBEHAEHABBAHFGECAHBFCDFDEEDEGDACBFHDFBGFGFEEFAEFCFBCHBDFAGGAGGAGBAGBEGEGDDGCDBBDBGEFGDDGHBBECHFCHCCFAGHCFCAH,False +741,9.0,8.0,14.0,9.0,12.0,8.0,10.0,8.0,HHAGBAGCACBHFBHFDEADGBFGCDABDCEDCEFABGECCEBCDGEEEEECECCFACHAEFGGFCGFDGDACDHHBH,False +742,12.0,15.0,13.0,8.0,14.0,16.0,4.0,12.0,AFFFBFFBCEAFAAEBHDAEAHBCHFCHBDHBFHBDEBAHGFHFBEGCFHCEAFEAHABDBEDEEFECHECGECFHCFCCDCCGBDABDBBEFA,False +743,10.0,6.0,7.0,8.0,13.0,10.0,9.0,5.0,AFAAEBGEBEECEEDFCGGHDGDFCFGHFBHEHDDAADEDDECBEFBECHCGAAFFAFEAGEAGFBGC,False +744,4.0,4.0,4.0,5.0,4.0,3.0,5.0,8.0,FHDHHGAHBHDDHGDAFEACEACEGGFHBCHBCGEDB,False +745,5.0,2.0,6.0,1.0,2.0,4.0,4.0,5.0,CHHCFFGFGAAGAHGCHABEACEHCBFCD,True +746,6.0,7.0,9.0,8.0,5.0,5.0,6.0,0.0,GDGGFGCEDBEDACDCCFACFCDABDACAACBEBBCFBFEEGBDGD,False +747,23.0,21.0,27.0,20.0,27.0,21.0,28.0,26.0,DEADBCCGHHGHDBADBADBEEBFEBEBGGCAEDAHDFDGHEAHEAGEDGEFGBAGHFHECBCAEEBEGFFFHHHDHHGACGEEDCADBAFBHGBAFBDFCDCBGHFHAFCCDCGACGAFGCEGCHBBDGCHFDAFGGGBHGBHAAHCAGEDCCGCCHBCHFFHEFCEFAAGACGCEECECHEBHEGEDFEDF,False +748,3.0,5.0,1.0,5.0,3.0,2.0,3.0,3.0,DBGHEAHDADDADECFEGBGHBFBB,False +749,11.0,7.0,13.0,10.0,10.0,9.0,18.0,6.0,AGEGGFDHECGGCGBCGECBCCEFCADCGHCGEGBEBDECGGCAFHDDHGDAGDAEAEFDGADGAFCCFBAFEFDGFAGBAHBH,False +750,19.0,21.0,8.0,26.0,26.0,23.0,18.0,20.0,FEHFHBCHBCHAAHDGEABEDCECBDDAFFAFDGDHCDEGDFADCHDEDEEGHAGDFGCFGDFAEBDFBAGHAEEAEAAFAFBAFBEBBDDBDHEFHEHDEBDEFEBBAAEAEGBEDFHDHGBEGEFBHCHFBHEGGEFGEFGDFHFHGDBGDBFDBHDGA,False +751,10.0,15.0,9.0,6.0,11.0,12.0,12.0,15.0,GDEEDHHBBFGBHHBEHFHFBDCEGGEGCBCCAFCEFBECHEHEBHBAABFABFABFGFEGAEBDHCGHAGHAFCACGAHDHFDHGBBGF,False +752,16.0,16.0,21.0,19.0,22.0,24.0,24.0,17.0,HHEEFGDFCDFCDFGHFHABEGECBCGBCGBFGDFBCBAFFGCAGCAGBAGHGDHDDHGDHGEHAECADCEFFAFFDEGBAGBCEBAHFACCDCBGEHDEGAEFCEDBEHFHAEDBGAGFECFGGAGGEFHDHECHECFECFCBDCGABDBHDFEFFED,False +753,5.0,5.0,9.0,7.0,8.0,5.0,5.0,7.0,DHCDCBFEBACFGCHGCHGEDGDDEDHAGEACFACEAHEFCCFBDHBHBEE,False +754,1.0,1.0,2.0,5.0,0.0,0.0,2.0,1.0,GGBCDDCDDADH,True +755,3.0,4.0,2.0,11.0,7.0,7.0,7.0,3.0,DDGGDGFFEFFGGDECDEDFEDFBBHBGFBHDAGCADHDDEAEE,True +756,13.0,13.0,9.0,10.0,17.0,10.0,13.0,12.0,CGAEDBDFGGHCGBCFAEEAGFBFFBFFBEGEEBEEHEECDEGACGEHAFGADHABHAHHCGHFGHEHEAHGDDCAHFAEBAEDCBBCBBGBDEDDA,False +757,8.0,8.0,4.0,5.0,4.0,3.0,10.0,2.0,BDEBGHGGFDGFDAFCGGCEBBAACEDCADHABGGBGBAABGAE,True +758,26.0,19.0,23.0,17.0,12.0,22.0,20.0,22.0,DDGDEFCHCHHDHHCHGGHDBAFBFGBFEBCAFCAFHFFDCCDCEACACBFEGGHGGDFGDHCBGAFCAFEDBEAEEBDFGDAGBHBHHADGCDFCAHCHFCGFCGHCBHABDABAACHAFAAHCBHBFABFAGFDBFHBEECGAGAAGFAEDABACCEGH,False +759,4.0,1.0,4.0,4.0,4.0,6.0,8.0,4.0,GDFGAFGDGCFGCFCAHAHDFHEEHEEGDGAFGCB,False +760,2.0,2.0,0.0,1.0,4.0,1.0,5.0,1.0,ABEDBHAEGFGGEGGE,True +761,21.0,26.0,28.0,30.0,24.0,24.0,21.0,23.0,FDCHDHHDFHCCGFFAFAAGABBDGBCGBHGEHFHFBCEACEHEHBEABDBBABAGBFFBHDEEDBGFCGFCGFBBCBBDBGGGCDECDCFECFEABGCDAEHEHBEDDADFADGAEEAEFDCFHCFBCHBCHAEDDEBGEDGFHEDCBACDGFFCEGCDACABEGCDGHEECFCFHDFBDHADHADHACGDCDDHH,False +762,24.0,12.0,13.0,17.0,17.0,14.0,9.0,11.0,CEAAEBDEFDBCCBABBACBDBDDADGCGHAEHAEHBEFAEFAFCACHBHFEHADHFEFAGFGCDADDACDEDGEBGECAEBFEBEADGACFAHAACAAEADDFFGAFGCDHDHEFH,False +763,6.0,8.0,13.0,10.0,5.0,9.0,19.0,14.0,HGDFBDFGCHDCBGCEGCEGHGHHGACGFCAEEHBBGDHGCCGFAGHADHBCGDDBEAFDHFBHFDGCAGCGFFGHBGHCGHCD,False +764,27.0,23.0,30.0,22.0,19.0,28.0,33.0,17.0,AACCCCCCFBCDCCGCFBEFDGGDCGFCFFCAECBGBFCBGEHDEFGHFGHACHGFAGEAFFFCHFDGCHGDGCFGCFGCAGDBFFBECEGCGGBGHBDAEDABFABFDBDDBDAADGHHFBAECEBHAHHEFADFADFACAACGECEEAGEABADBDHEGEDGEDBFAHGAHGAGCDFBAGBGFFDCHBHEACGGBGB,False +765,18.0,15.0,16.0,11.0,14.0,19.0,16.0,15.0,CEFGFFADDDDCFAFGAFEEEAEHBEHCECAEBAECABHACHFCFGBGGBDABCFFFGFHGHGDEDABBABBAHFACGDFGDFGCBEEDFHACHGCHGBHFEGFAACECDGCHGBHCBHBAHAF,False +766,2.0,0.0,3.0,2.0,3.0,1.0,2.0,7.0,HHEHHCCHDGHDFCEHAEGA,True +767,17.0,7.0,6.0,11.0,18.0,9.0,7.0,8.0,HEEBEFBEBEEGHEFCEACFABFHBGEAEAACAADAADADDAFABDAGDEDAGDEDHCHFABEGDEFDEAEECEGHHHFGFAC,False +768,7.0,8.0,17.0,12.0,13.0,9.0,9.0,18.0,EBDDBCDHEEEGCEFDAFDABCBBHFGHGGHDCHFEHFAHAEHCFHCAHEHBEGECHEGDECCCCDCBHCGHCBFGECACHAFHDCDDHFDHG,False +769,20.0,21.0,9.0,15.0,21.0,8.0,21.0,20.0,HEDAEDGBFGHEDHEDHEBCGAEAAFAABHDHAEHGGGBEFDFFAAEAEHCHBCHACDBFGBGABHBBEBBAHBHHDABDAGDHEFEGBGGDCGEBGCHECHECHGBEDBEDBAAFGADBAGAHGBGDCGEEGEH,False +770,21.0,9.0,20.0,15.0,18.0,14.0,11.0,20.0,AGHAHEGHACBCDEHDEHEECGABBADBFCHFEABCBDEAGEAFEAFECFDCHDBDFADCAGCADCHDEADAAHFABFEDCEGCHFHHCEACGDDGHFGAFGAHHHECAEHDHHABCEFCHFCGCCEF,False +771,4.0,4.0,4.0,6.0,5.0,8.0,8.0,13.0,HGCHGCEBAEDFEDHAHHGEHDDBGDEGBHGFHGFCFFCHADFFBHGAHFHH,True +772,4.0,7.0,15.0,14.0,7.0,5.0,7.0,12.0,FCECCEHCHDDHEFHDDAEHECCGDDBDDBEDBFCGHHHBHHBCABCHBCDEDGCHFDACDFCDGCGGAGC,True +773,15.0,15.0,19.0,12.0,10.0,13.0,9.0,11.0,CDFCAAHAADAADBHCGEAHFBGCBCCEGCDCCDEAGHAGECHFHFFBFBHFBADCADEHBECBABBHFECAGCDDCFFFHDFHDFAEGAEGBCCBCEDGBBCB,False +774,17.0,15.0,18.0,13.0,14.0,14.0,9.0,11.0,BDADABGFCGHCGAGHAGFFDCCBAGFHDFHCFHCBACEACBAGBACBECFEBGABFBFFBHHBDEEDEAHEAGFDEFAFFBDHBECCCCDCEACEHCEAADDCBAEDDEH,False +775,12.0,10.0,12.0,10.0,14.0,18.0,9.0,17.0,FFDFGDFEBAEBHFHFFBFCBFCBACEGDDCHCHDGBEEAEHAEBACCCCCAHEAFFFFFHGBHDAADAHEFHGFHEDCAHHADHGFGCHGFEEHDEHBEGB,False +776,15.0,9.0,14.0,7.0,14.0,8.0,10.0,14.0,FGGCGFEGFEGEBBABCCDCHEHHCHGFDGAEHCEFCEGCAACEACADHABADBFDCEDAABEACDGCHHCHAFAGHEHBEFEAHBAHBEH,False +777,3.0,5.0,7.0,4.0,6.0,7.0,4.0,2.0,ACHDGDFECAEGAFGEBDFBCFCCFHCEECDBGFBEFB,False +778,13.0,16.0,17.0,23.0,18.0,12.0,11.0,15.0,HGEDGCCFHBDHDDECFEHAEBAEBHDCCDFCDCHGHFGHAABCAFCGHCGCEFFEBAEBABBEHBGHBFFDDGDAEDAEABBHBBHEDFEFCDCEDCEDHHCGDDDDDAGFEBBCDDADCAEEG,False +779,0.0,0.0,2.0,3.0,0.0,5.0,2.0,1.0,DCFGFFCDFHDFG,True +780,4.0,14.0,9.0,15.0,13.0,16.0,18.0,13.0,GFHBCDDGGEFBDFGDFEDHCBBGEFEAFEHBDHGFFECCDHGHCGBBGBEDHDDEDEEDBCFHGDHGFHGFHGFGGFGBFGAFHCDCAECAEBBEDBGFBH,False +781,14.0,11.0,9.0,17.0,16.0,19.0,16.0,13.0,AHAEEAEBDCFCAFEACDFGBGHHFBHDBFDCHDHHEHFDGFAFEABDGEEEFHFABFCGFGGBCHBEGBHACEADGACGCFGBFGAFDAGBAGFDHEDEEDEFDEFDGHDGDDF,False +782,17.0,30.0,15.0,20.0,20.0,24.0,22.0,25.0,GBEGHHGHFDDAEABGCBGDDCCHFEBFGBGDBGDBGCAAFGAFDEFGEFEFAEFACBGEBAEBHBBHBCHEHHEAHDDCBCFDADDHDGHFEHBHFBDBDHAFHFFHGGAFCFGCHEEHEDFAGBCHBFGBCGDCGBHBBCFBDBDEBFEFHHCBHGBEBAEBHEFAAFDAG,False +783,18.0,12.0,19.0,16.0,8.0,23.0,23.0,21.0,CAEAGEACHFBBCABCACFADGBFCCFGDFGFBGHEGHCCHABHGBHFBGEAGCCFDAFDCHBGHCGHDFEGEHGEHFDHBDFAHFAHCGGCGDBFAGFHHFHGFDDHGHFDAGBHFHEDDDDCCGCCGADFAFGAFAAF,False +784,26.0,24.0,29.0,15.0,21.0,16.0,22.0,14.0,GEEGAEGABFAFGEBBHCCCGGBHGBFDAADAAGAFGBEBBCCGCAAHAAHDBEEBGEDADDADDAECAECBEBHEFFADBCGECGCCDCGACBACFDCFHFDHGHBBHDBCECEGCBGEBCEFAECCCHFGECGCBACBFFBGFHCECAFBAHBHHAFDAGDECAG,False +785,1.0,0.0,2.0,2.0,2.0,6.0,1.0,1.0,FFFEFFEDFCDCGAH,True +786,20.0,28.0,18.0,25.0,30.0,17.0,20.0,19.0,ECEDCEBGECGBDDAGEBEEHHADHDECGEDEEFEADEAFEAGDBDFCEFBDHBHAGAAGCAGCHHCHDBDFFEECADBAGFCBBEBDEHHEBHFAHFBCEBFEGEHADBDHBDHCDBGDBHDCGBFEADEADHAEAGBBCBACEACFDCBDHBDGEGGEBGEFGBFCBGHFGFFAB,False +787,5.0,3.0,2.0,6.0,9.0,8.0,2.0,4.0,DAEDAECHGCHBEFFEFEDFEDADHEDAEFBFABFHFEG,True +788,5.0,9.0,7.0,1.0,4.0,3.0,1.0,5.0,EBABAACHBEHFACBBFBBEABCDECHGCHBCHFC,True +789,12.0,4.0,13.0,8.0,13.0,16.0,10.0,11.0,ADAAEBAEGDFGHFGEBGADFAFFAFFEFCECEEFEGFEDFCCECHHAFDCFGHEHBBFAGFGHACECGHCDCCHCCHDFHDGAAEH,False +790,6.0,10.0,8.0,9.0,9.0,8.0,9.0,13.0,CEAHHCFHCFHBEACFACDBGDBEHBGGCGGAFDHFCHFEHBABBHDHGDEAHGBEBEGBEDHEDGCDFHDF,False +791,8.0,14.0,12.0,15.0,11.0,8.0,8.0,8.0,EBHEBDCADCAGCABCGDEADEAEECBEDADFEHECHDBHGEGCFDCFBBBHBBDGHDFFDFFGBGHBACBFCHGCDCDDEBDA,False +792,10.0,22.0,18.0,14.0,21.0,20.0,16.0,23.0,DBGEHGFDGFECFHGFEGFBAECAHFHECBABHGFACEBDGBCGHCECAEGBBCDBEGEEGHEAAECGBFHBFHAFHCFBCDHCDHDBHEAEEBHHBCCBFHBCCBHCEDDEDDEFFHHFHFFHEFDAGBFEBHCBHDBFDGGG,False +793,23.0,21.0,27.0,21.0,31.0,27.0,29.0,18.0,AGFCEBGEFGHCGECBEFEGFCBFDBFHCCHCBEDDAGFBDCCDCCDEGHEGHAFHGGHDGDBADBAGEAEAGFFCDACFACFGCFGHFHEFHEDECBEBHFGDEGCEGDBAFCCFACEEBDDHCECDEADFGBBEABHACFAEFAEHAEHEGBFCAHGEFDEAAHACGDBEFBDBBCBCEHGEFGFGGFAGDAGEG,False +794,24.0,20.0,28.0,18.0,24.0,31.0,23.0,26.0,HHAHBAHDAHGAHECHECDEHEEGEFCECEFDEDDFCDFCHBBHBHFCGGEHCAHCDGAGADGCHGHFGEEGAEBABBAEFDGDHFFEGCBFBGHBGABDBCAGCEFEBFCFAAAGAGBABCAEAAFFBFFBEBDDFFCFFHFFECFHDFGCCACFAFHCFECECCFGHFGBAGBCDHHHCCHDCEDAEDGHFG,False +795,31.0,20.0,15.0,24.0,20.0,24.0,18.0,24.0,DDFDGFDGAGEBGEBGFHEDHBDBGHCFHBDCEACAGHADHGHFGBFHCDHDHEEHGGDGGEGDFGAEAEECGFCBFABFADAADAHGCFFHBFBAFDAFDBEBAAHAAHAAHAAFABCABEBEFDHDHEFHEDABHCDDDHBHCCGDHAECAEBEHAFBACEADFBFFEAFCAFC,False +796,6.0,5.0,4.0,8.0,8.0,11.0,14.0,10.0,AGGGDBHDBEDHHCHFAGFGEECFFAFFAEDAEFEGDBGHHFHDFGCGHAGHGGHGEBCEBDFGDF,False +797,13.0,13.0,14.0,16.0,20.0,20.0,14.0,14.0,FDCFDCDGCDGAFFFFHFBDGAEEFDHFGHGBFDAFHGFHGDEDDEADCHGBHGBACAHBECACHEEEEBBDFCEBBEBFEHAGCEBAEFCEFAGFAHFGHFGCFECADCGEADEHDEBDECHB,False +798,16.0,22.0,7.0,24.0,22.0,17.0,26.0,9.0,EFHFGCFGEDGFBGFBHACDACDAGBBGECEBBBDDADDADHGGGBGGBFEEDEFDEAGEAGEAFEDDBDGCDBBBGHGDHCDBDDEGEAFEADEABABBHFBFDBFDFEEFADGADECHBGEGFFGBBHEGGFDGAGAHGEE,False +799,20.0,13.0,23.0,31.0,20.0,22.0,27.0,27.0,ACCDDCDDCHDEGDBGEBHAHGDDDCDAHDGFAGHAEBFECFBCDECBAHEACGAEGFEFFGHADDGDDACEACECCFFFDFGHBHDBHDCFGCGACFCDHCBHEFDBDGCDCDEFDEFAGHAFHAHHCEGGDBGFEGHEHHAGFEBFGAHCBHCAHDADFGDEHDHHAGHFEHGEGGDGGBF,False +800,7.0,7.0,4.0,8.0,5.0,4.0,9.0,2.0,BFADCAGBDGDDGDDAEDEFBEABEBECGDGHAGHAGFGBABCGFC,True +801,27.0,24.0,11.0,26.0,22.0,20.0,24.0,21.0,FDEFHBBHDBDFECFEGGEGBBBFGBAGBGFBAEHFGHCAACHBBHBDHEABEFBAFGEDECDEGFGGHDGAGGAHCBHEEEFHEDHADFDHGEGFAAACDFDDFBDCEAHEBHEAAEFBDABAABHABDAGDADFAHFGHFGHCGDFGEBCDBDAGDBGHAHDADAGECDACDE,False +802,24.0,16.0,21.0,28.0,24.0,24.0,17.0,24.0,EHGDHECEADBDCGFCGDCFDEFDHFEEBHECAGBDHDDAAAAGEHGCCGBEGCEGEFDEBDAAGEFCAFABFBEAGEAFECCDDCDDHDHFDEFGAACEEEHGHHADHFHADHFCCAHGACGAHECBEBBDFBCFBHADDAGDCDFAHFAHFABFEBFECFHDBHDBHDGHFHFCDF,False +803,20.0,21.0,21.0,27.0,21.0,19.0,21.0,15.0,CHCDAADHHDHFEEFGGDBGABGCBCFAHFHFFGBDEBFEAFEHBEFDEFDAHCGGCDFCGCGECGEAGDBCEBGAADFADFCDAEDBDAHAEHAEGGEGAHGADFCHCCHBDBBGEADDADDBFDBCBBCBEGDDCEEAGDCGDFDEGBEBBFBAHCEHCFCFD,False +804,1.0,2.0,0.0,1.0,3.0,0.0,1.0,2.0,HBEHBEDEAG,True +805,17.0,17.0,12.0,11.0,12.0,11.0,11.0,14.0,CACCACHGBBBBABBDBGEGCAGFBEFAEBAECGBHHHHHHHFDEFGCGGBBBAFFAFFACAACGACDDEFEEDEADHAHCBHDGHABHEBGCFAHBEDDDFEDA,False +806,8.0,5.0,13.0,9.0,8.0,4.0,5.0,7.0,AABDACCACDACDBCBEEHEHCDHEDGEDADGFFCCBCGBEHCHHDGHECCFDCFAEGA,False +807,2.0,3.0,6.0,1.0,2.0,2.0,5.0,2.0,CCGFCGCAGEGGHBBHBDCFECA,True +808,8.0,11.0,13.0,11.0,20.0,5.0,10.0,7.0,EDGEBEBGEBGECCCADEEEBCEGEDBECBCCDAEDHECHAGHGCDDFDBFEBFEBEEGEFHAAGABGDFHDCHACBEDGECAHC,False +809,19.0,18.0,17.0,18.0,21.0,24.0,23.0,21.0,GGGGAGFDDEHDEHAEFAGHHHHCBECAGCEGEBGABGFBDCHDBHEHHGHFAHGCBGFDCFDCFBEFHHDAGFFGCEEDHGDCADAAHEEDEBHHFAFFABFACCBCABHGCGDBEDFEGFCGFBFBBCBBDFEGFECFAHDAEDAEAEEDCBGGFFFHA,False +810,20.0,16.0,11.0,12.0,13.0,19.0,22.0,18.0,AGFCHFDDFBEHGEHGBHGDCGFCHEGAGADFAGGAHAFBABBFBBGGAABAAEADEBDGCHHEBGCAEAHEGCAGFHDFHFEHAGDGFDBFBBFADCGDBGHFGHCCCGCDGBBAAFFAFHHFEHFEHEE,False +811,17.0,22.0,15.0,31.0,25.0,25.0,18.0,24.0,HAFEGGECCHDGGGHDGCDGDEAAEHGEFGBGGHGBEFEEBCHAEHCFHDFHDFGDGDBGDAFBFFBFHEECEDBEDHDBEDBFDBFABDEFCHAEFEDHCDAFDCBDABDABFCBCDHEHFCAFCDBEDACDEHFFHFFEEEBDEHEBHBHHAHGBHDHGDBCABDADDFDAFGAF,False +812,13.0,7.0,5.0,13.0,10.0,18.0,4.0,11.0,FGEADHABHAEHFCHFAAEEAFEAFDAFABEGGHFFBBDBHCAHADHBFADCCHEDFGDFDDBDFEDFEHFDAFDFFEHFC,True +813,30.0,25.0,17.0,27.0,18.0,16.0,23.0,20.0,DGAGBDGFDGFAAACAGCEFHDAHDBHCBACFACFGHFEFBHHBDHBAEDAHCEFDGCAADABGABDEGDGCAGCEGBABEABDFGDFADFABGBHGAFGDDGHDAHDCDDEDGECHEHGFBBFHBEBBCBDGGHHCEHBEGBCGADAADBHEFDEFHEAADCCHEDECAAABABB,False +814,24.0,14.0,14.0,18.0,16.0,18.0,16.0,21.0,ACBABDDGDGCCHAEHAEFDEFGHFGHFGDCGEBFDBGGBFACACFAGEHGBAFBAEAAEFHEGHCAEAADDHCABFHHEDHDHACHAGHACHGCHCHDDHABAAFADDBBABFHCFGCFEDDEDDHFEHFEGFBGEAFEB,False +815,13.0,9.0,13.0,16.0,13.0,6.0,10.0,11.0,EBHEDEGACDDCDGCDACHFCECCHGBHGBHCBEDAEDHFAFEAHEADAAEADDFFEGBDGEHHABGGHGCCADCDDCDHCABEFBEDBAG,False +816,3.0,7.0,5.0,5.0,0.0,0.0,5.0,2.0,DDCDBADBHGBGBBGCCCACBAGBDGH,True +817,5.0,5.0,2.0,2.0,3.0,8.0,12.0,6.0,HCHGCGFHGAEAFGHFGHFGFEADEHDFBGGGGGGFBFABABB,True +818,1.0,11.0,9.0,4.0,7.0,7.0,8.0,7.0,GABGHBHDBHCBECBFGHFGBCBBFEBECCEFCDFCGHCFCDHEFGEGBEBHDG,False +819,2.0,2.0,5.0,5.0,0.0,2.0,1.0,5.0,CDACFHHFAHDBHCCDCHDBGD,True +820,11.0,24.0,12.0,20.0,8.0,10.0,7.0,16.0,DDBDDECFEFFEBFBBABHAFHGGCCADEHHABDDDDCGHFABFABFHDCBDBGDBCDBFEHHCBHADHADBADCHDCBDHBEHBHABCGBEGBCDCGHBDAEFBBBH,False +821,9.0,5.0,8.0,7.0,7.0,2.0,8.0,6.0,DCDGGAGGCHGCHBBEEAGEGEFCEDADAADAAFCABCEHCBHBEHCAHDDG,False +822,4.0,6.0,4.0,6.0,8.0,10.0,6.0,8.0,DGEHGBHAFDDFEAHBFCBFCDFADFCDHGEHGBFCBHEHGEBEEHEFGFFA,False +823,11.0,21.0,15.0,29.0,14.0,28.0,25.0,13.0,GCBACBGFGGFADDGDDHCCBEGFEGBDBBDFFEFECFBCFBFFGFFGDDHHDFHEFDEDDAFAGFDEBEBBDDHDEHGCHFCGCAGCFGDGGHCFBBFBDCGGEGDEBAHFDEADEADFCDGABFDDFGDCGBFADABDGBHGHGFHFDHFEBCB,False +824,9.0,9.0,18.0,17.0,22.0,11.0,12.0,16.0,HDHHDBHCFHEEAEBDEDAEDBEDBHHAFFDDFCHGCHECDDCEEEFEDGADGCDCCHCAHCAHCEHGECGEGGHFDCCEECACBGCEGFGDEBAFFAGCGBEEEFDEFDBHBH,False +825,13.0,14.0,23.0,11.0,13.0,29.0,17.0,16.0,CFBCFDDFBDFBHFHGFAGEAFFBHFCCFCFACFACFDCAEBHFGGBAGDEEHBGFAGFHEDHGFEBFHHFGFDCFCBHEEGGCFGEFBCADHHDBFDBHDHACHCCGCEGAGGFFACCAECFHCGBCEFCEFCAB,False +826,5.0,8.0,5.0,6.0,10.0,4.0,3.0,7.0,DDEDAGAAGAHCDDBBHBGEEFHECEFHEBHEFHECEECBBCHBDFBA,False +827,20.0,17.0,26.0,28.0,18.0,27.0,26.0,26.0,ECFEGFEHFHHFABFABFEHABHAGDBHDBHDBGDGCDGHABHAFCEHDBHGCDCEFEEADECDAFBGFEGFBAAGDGDDEEDHDABDABFAGFDGDDADCBDAHGHHGHHFFFFFGCDEDGGCBCFEDGCCGCCDCEFFHHAHDBHAFCCFDGBCCHACHDEGGEGCCDCCHCBGFAAFEGFGCHHF,False +828,10.0,8.0,14.0,9.0,25.0,17.0,21.0,17.0,ECHGCHBCGEFDEFDECDEGBECBHBHHFFGGFGGHDGHACCAHHBDCFGAFGAGEEHEAHECEEHEEBEEGDECFEBFECFHFFGGGAEGHEGFCFBAGAHEEGDAAHFHCFGEEDFGDC,False +829,3.0,3.0,1.0,2.0,3.0,6.0,4.0,4.0,DHEHHDFHGGBAGAFEACEGFBFFBF,False +830,13.0,14.0,5.0,14.0,12.0,16.0,14.0,22.0,GDABFFCGFEHEGFFBHCBHEDHFGFBBFEDEHDHHGFHAEHAEHCEHABHADGEDGAFGHBCHAGHADHEFHFFGFGBAABAABDGBDCHDGBEAFHHDDBDHBFHDEG,False +831,30.0,21.0,25.0,25.0,16.0,20.0,17.0,32.0,ABDAGCAGBEEEEFEEFGBFGACGBHGBHCAACAACGCHGHADHACEECHDHACHFEGEAGDAHDAHDGBBHBFHGCHEHHAFGFFDDBGHHDHDEHABBACBHCADFDDHBDHBDCDCBDAHFFHDDBFHAGCDBFFEECCECCGHAHCAHBEHDACDAHDFCDAHDBBFFBAFCFFCAHAAGAC,False +832,25.0,27.0,23.0,20.0,26.0,20.0,20.0,27.0,AADBAGBCFACEEGDFBFFBFHCGDBHEFHCFBFBEEBHCCHCHBEBGABDAHDFHDHHFEHGECGFCBHDFHABBDDBDFHDGCGCCGCDGCHBHEEDEHDHBDEEHEGHBBHFBHFBGCEGEDAEGAECCEAAEACBAHDEBAEBFGACGAFAHDABAHDGCDEAHEAFECFGAACBACHAGBFGE,False +833,25.0,13.0,14.0,24.0,17.0,12.0,19.0,18.0,AEBDEBFCFGAEEHEAHBAHDCFDHFBFAGFAGAEGCCDCAAGAHEHHGAHEACFDEGDCFBAGGABGADGCDGFEBFEAAAGAAECBGDFCDBEDHEBCDDHDDHDGHDHHGCHGEBGHCAHDEEDCDDBADAAGABHDDF,False +834,15.0,10.0,18.0,19.0,15.0,14.0,14.0,17.0,GFDGHHGDHFHCFDBEBGADGACECCHHCHFAHCEHCHHDEHAEBADDGDBGDEEDECDFCAFEEFEDDHDCGAHBAGBDEADGHEFDFABCEBFGBCABCFGCFACGDHDEHACACCAFGF,False +835,20.0,10.0,18.0,14.0,16.0,28.0,23.0,12.0,CBFFGFCHEDBFHGFEGFEGFEDCEDAEHAGGGGFGGCCCDGCFGCFHAFBAFBDFCFFHAAGCEGAEGHEGDFAFFCDFADECHEAHGFGEHGEBDDBABFABABECHCFGCDDFFGFAACAAEDHGGHECDBAFCAFAF,False +836,30.0,20.0,19.0,16.0,19.0,13.0,25.0,21.0,GEHGEGBFGFCGFAGHHGFGGFDHAAHECBAGGAGHCGBCABFHBECAAHAFCEBCEACEADDADCGHBDHGFEDBCAEGAHGHCGHCGEBBHGDHEDHDFBEBBFADEAHEACBAEGFDCAABAABAABGAEACHBHDGADHAEBACHDGDAGCEDCEFCBF,False +837,11.0,6.0,11.0,21.0,12.0,11.0,14.0,20.0,CCGFFHDFDCHECHGCEGCGGDDGABGAEHDEHGGHGHDDHDABDHBHFFGEFHDAEDFEDFGFAHHHCFHAEDGEHCHFDADDGDBADAHDAHDCDCCBEHBEAE,False +838,2.0,11.0,5.0,5.0,5.0,11.0,2.0,7.0,HHAFDBFCBFHBFCBHCFEBHEBCFBFEBEHBDDDEDCABBFFGFFGH,True +839,10.0,18.0,12.0,15.0,22.0,22.0,14.0,20.0,GHGGHDGHEHCFHBHHGHGFDFFBHGBDFBCFBFEBAHAACAEBAFCEFHEABGAHCBCCADAEHFDHFEFFEHFEHCECGHFEBFGCFDBBDBDDCEDEEDEEFBFFGDBBEBGEAEHFDCEGEEDHGDHBF,False +840,6.0,5.0,3.0,4.0,8.0,4.0,5.0,6.0,HFAHFAGABEEHFEBBEABCGBGAFGAECDEDHEHHEDGDC,False +841,22.0,25.0,12.0,20.0,30.0,18.0,24.0,19.0,CFDABGGBGGDGGBGDBGDFEHGEHAEDEEDEEAEGABBABHABFEGAAAAFAAGHFEEEAHFBBFBDHEHAGHADHFDHEDHEDCFAHFEHGEHEEHCBBDBBGBGEBCEBFEHDCFAGFECABGDHEFFEBEACCHEGEGCAFDACECDGDBHEFCGFGGBBBDBDDA,False +842,26.0,32.0,18.0,28.0,33.0,16.0,26.0,21.0,BDFEACGAHGEHBEFBDDCDDEBGFBAHCGBBGCEDEHBAFGGFBDFDABCCBFCBHEBEAFGAEGFEGEDGAABBHBDCAAEAEEBEBGDGGDGHDHHCACBEGGDHADHGEFEBDEBDHBDHBEHBHDDCDFCDCGAGGEGGEGFECAEABEAHDAHCFFCDHAAHAACAABFEEEBDEBDGBDBCEEHDBGEBEAHF,False +843,17.0,15.0,21.0,18.0,10.0,19.0,19.0,11.0,GCGCCGCDBAAFCFFCGCCFCBGCBHBGADGFEEEBEDCFDCFBEFAEGDDDDDAGACDEFDBFGCFGEFDDHCGGGGGAFACHACHACGADGHHCHBFAAFDFFDABBEBFHBHEBHCAHBADGABFDC,False +844,28.0,20.0,25.0,32.0,29.0,10.0,34.0,16.0,GCBGCEAHBHHGHCGADBHDGAFGCFEEFDEAABAAFACGACHAGEEEEEBDBDDGEAEBGCFGAFGCGACGAGFEDAGDAGDBGDFEBECDGBDHBDBBDAEHADAAHGDCGDEBAHBEDCGBEGHEDHCCEDDEDCEGCDHDACAABADGEEFCEFGGAHGCCGCBECECBDHDCADAGDGGDGGDECHEBD,False +845,9.0,18.0,18.0,15.0,16.0,16.0,18.0,30.0,FHHFCHBCEBFEBFBHCGHEGFEDEHABHBHCEHCGGEGGCGGDGHDFHBFHAGACEDBBBBBFHEDHAHHBHEGHEHFDHEBHDDHCDCDHCACADBHDAAEGHFCCECCFHHBHGDHCDHFDGFBGFGGECAFBFCEG,False +846,25.0,21.0,20.0,25.0,14.0,20.0,19.0,27.0,DHHAHHGHBEBFFBHACHBCHFEAFHAGEAGEDFFDHACGDCGEBDDBGEAFAAGAAHAAFCFDCAEFBEGHGDCFAEDABDABHGBHGFHFDGDDGDDHFBABCADDACHBCHCGECACDBCGBCFHEHCCBBHHHFHFBHECEDHDAHDFDDFBBFDBEGACGACGADG,False +847,19.0,22.0,26.0,32.0,24.0,20.0,17.0,30.0,FFFFFBEBBCDDHBEHDHHFHCDHCDBCDAFBHDGHDECDEDGEDCBFEFEHAHHAEDBDGHDCHECDEFHHADHCHBCHCDDCHBBHBEECCDFEDFDBGDBDFBEBAEFAHAGFECCACDHCEHCGGCGGCAGABCAGAGCDBADGEDFEGAEGAEHACHCBHABDBEDEDDHADGGFBFFHEFHCAH,False +848,9.0,6.0,11.0,10.0,14.0,15.0,7.0,8.0,EBECBHGDFECFDGFDHFDCEAAGDEFDEFDFFHCAHGBDDHDHFEGEGBAFCEFCAFCACCACBAFHFEHEEFEGAEBC,False +849,4.0,12.0,3.0,4.0,4.0,6.0,9.0,4.0,BADBFBBDBCDAGGEGGAHFBHFECBBGGCGGBBGBDFFHFEHAEB,True +850,11.0,16.0,15.0,13.0,9.0,18.0,8.0,14.0,AHEFHEDHAHCBEFAEABEBBDHGAGCECCECCEDGADFFBFFBFFACACDFCDECHHFDFFHFFGFBAHBCDBGDBGHHGHFBDBHDBCCFHDACABDGBCBF,False +851,14.0,6.0,9.0,8.0,8.0,11.0,8.0,4.0,CADAAFAFGGBDGBECHEGAEGCEGHEAFCGCCAFCAFDBEHBAAAFAFFECEDADGACFBDFHDFBD,False +852,13.0,17.0,14.0,11.0,14.0,23.0,28.0,19.0,AHFBHFEDBHCBHGDHDDBEFGAFBEDCEDCGGCAGCHGCHGCDCEEGFBBFHCGHAGDCFEGABFCBECBAFBAFHHGHEBCFAEGGEGAFBFGGGDGBDBFAEEBGAGHAFHCFHFFAGFHGFHFFHGGBGGHDGFE,False +853,17.0,14.0,15.0,18.0,12.0,25.0,14.0,18.0,FEEDCEDAEDABFABGHCGEGBAFBAFADFDDFBDFGDGEEAEHDGHCFHCHGBHFHFACAEBGHHGHAGAAFFDCCDHCGGCFDCFHCGECADCFDBFEBFBDGHDCHCHDAFFFHFBBEAFADFHBFHFAB,False +854,4.0,8.0,7.0,9.0,7.0,13.0,4.0,5.0,HAHBAEBCEFDHFGBFDDFDDFCGFBBCBFCFFCAFEDFBCGCDGEHEEDFDHFEBA,False +855,8.0,9.0,7.0,8.0,14.0,11.0,8.0,11.0,FCGGHEGHCAHEGDGCDHEBHEGEEFAEFCEAAFAHDEHFEHBGFBFFBFEAHEADCBBCBBCEGDDHFDFBHEAD,False +856,15.0,19.0,19.0,21.0,20.0,23.0,9.0,21.0,EHCABCEDCEDCHDBADEFFEAHGADFHBFEBFEHFEGCHGBBFBDFDCFHCFCGHCDHEHADFFEFHCGHCBABEEBEFBCDBCEHDACDBBDCBACBAEBDDCADFAEFEEHDGHDEEFBFFDHGHFGAFAHFCGFHBHDADAHC,False +857,8.0,14.0,12.0,26.0,12.0,12.0,24.0,18.0,DDGDGFHGDEEDEHGEDDCHGCAGDGBBHHAHDBHDBGACHCCHFCHGGHDGHDBFABCHGHGFDCEAGEADEGDADEGHBCFBGFGDCGBFDFFDCBDCGDGBEGBFGEHHEFHDFGDAEDBDDB,False +858,3.0,12.0,7.0,10.0,7.0,11.0,5.0,6.0,EHBFDFFCEGCEBFAFCCFECFHDGCEHAEFDBFDBAHBGHBGEBCDFDDFBDBDGBHBBD,False +859,15.0,8.0,5.0,5.0,11.0,6.0,8.0,9.0,AFHEGGEGBEDBACAADADGGHGFEGCEHCDAFECBBABHHEHAECFHBAHGABDEBAEFAEFAHAA,False +860,24.0,23.0,16.0,29.0,25.0,13.0,28.0,31.0,ABDBGHHDBEAACAHBDDDDHHGAHBDHDAHCGHCAEGFECFECGHAGBBDBDDBDGBDBAEBACDAHDBGDBCEBGEDDEBDBBABGGGGGEHAEGGGDFHDAHAHFAFDCHDCHEFBEAGECHFCHGGEGGAGFDHADEGHAFHBGHEFBCAGCAEBHEDHEDEEDFEGFHCEHDHHFCHEAGECHA,False +861,19.0,16.0,16.0,18.0,22.0,19.0,15.0,18.0,HBDHADGAFFFCFDCFDHFAEEDEEABBABHHEAEDAHDEHCGFEECHECEFGHFDHFEEGCBDFDGHDGHDCBDCAECAHBACGEFBFFAFBAFBEDHDAHBBDGEGCEGBGDFGAFGAHCHGFECAEGABAHBACBECECD,False +862,23.0,28.0,34.0,23.0,21.0,19.0,19.0,23.0,AADEFDECBCFBFEGCHHCBCAHCAEDAEDFGBAHBGBBGEDGEFBAFBABEABFAHFAHADGBHAAHAAHCFCAECBEHBACDDCDCHDHHDAHDAHCFBCDHCBBGDEDEHFBCCCCCDGEDEEBCBHCDEBEHBCGCDECGCCGBCGBCFAGGACBHBFCAGCFBDHBFHFECFGHEGCEFDDFGDG,False +863,11.0,5.0,11.0,10.0,13.0,17.0,9.0,9.0,HGFAGHEGFFAEFGCHCCHCFACEAFEAFBFFBEEDDDGGDFEBHDFEDFEFCEHCDAAFBAFHCFECHEDDABDAGCCGAHGEF,False +864,8.0,4.0,8.0,5.0,6.0,11.0,2.0,13.0,CGDDADAFHFEHACHFFHAFHAGABEFBHHCHFCFBEHCEHDEFDCFEFHCAHCAHB,True +865,6.0,7.0,13.0,8.0,5.0,5.0,10.0,8.0,EBBEADDABHGBFBHDAHDFCCCCCGDCGACEFCEGCGGCDHHBGHCGCGBFDDFEAHCAHG,False +866,13.0,18.0,13.0,24.0,13.0,21.0,16.0,22.0,CECHEHGAHDBHAACGDDGDDGBGFBACBAFGCFGEBHHBHBBFBBFGDFEBHDBAEEAGEHFEDGEDFFHFADDADFHCHEADCFDBEDCDDFFBFFHFGEFGHCDFBHADHFDHFHCGCAGDACEBDHBDGDHGCHBH,False +867,3.0,4.0,1.0,1.0,0.0,0.0,2.0,1.0,BGHBGBAABACD,True +868,12.0,15.0,8.0,11.0,24.0,11.0,16.0,16.0,GBGAFGAHEABDAHEEHEGHFBEGHCHHCBDFECAADDGHFHFGEAGEBCDGEDBEFEEFGDGGAHGDHEEHBEHGEAGECGEAHECHBBEFBHBBDBBDCBFEFEEFECAAD,False +869,14.0,6.0,19.0,11.0,20.0,15.0,11.0,18.0,AFHAEHAEHGFHACHADFFGGFEGFEGDEDBAFBDECHHGHCCDBCFECHCHFBEDEECHACDGFDCHCEHFHCFACEACEACBCGBGEADECEEGFEHFACEDHEDHAGHFCA,False +870,7.0,10.0,10.0,16.0,6.0,4.0,11.0,16.0,HCBDCBHCBACDCCDHFHAGHCCDECGEDGDAFHGHGBDDFADHGDHBDHBGHFHEAABGBDHEDHEHHEGDDGADGCBB,False +871,6.0,1.0,1.0,3.0,2.0,4.0,9.0,6.0,AHCGEDGAHEAHAFGAGGBHGAHGFGDFGFHD,True +872,3.0,5.0,3.0,3.0,6.0,1.0,1.0,2.0,BBBDCBEGHEFHDBADAECAECEE,True +873,2.0,1.0,1.0,2.0,5.0,1.0,2.0,3.0,HEGAEHAEBCFDEHDEG,True +874,7.0,21.0,14.0,14.0,9.0,12.0,13.0,10.0,FDBFBBDBADBHBAGDHHCGEFDEBGEGGFGBCGEADAGGADHBDFCDECGBCEDFHFGHFEAFGHEDCEDCBFCBCCBHBBHBBDCBFGBCBHDBCAFC,False +875,6.0,6.0,10.0,12.0,5.0,8.0,13.0,6.0,GCGGCGGHBFDDADDBDFBDGCFGAEGAFBBCBHHFDHADHAGCDGEDEFGGCECCHDCEACGDFF,False +876,19.0,14.0,14.0,17.0,5.0,8.0,26.0,9.0,ADBACAGCHGCFGHDADABGEDABDABAFGCFDCADGGGGGGGGGBGGBACCHHAAGAADAGDAGDCGDBFFBCFBEBCEBGBBHEGDDCCCBHHAFGDGADGDDAFCGHHE,True +877,11.0,23.0,26.0,15.0,25.0,13.0,27.0,20.0,DHHEHGFGGCEHCGDGEDHCDHBFEDFEAFHBDGFCBHCEECEECBHCACGACACHGBHGBGGECGBDHCFEEEHCGHCGHCEBEFBGABCDDEGGEGGEGFEDBEBBGBCGBHABGEDCABCFECAHHBBCBDCAGBDGBAGCAHFHEBCEGCDFFDEF,False +878,10.0,21.0,12.0,20.0,16.0,27.0,18.0,16.0,EGCEHFAFAEBBGACGEEDEBDEFDBBDCBDEDFFAFGHBDFBHBGHBEBEGDDGDGBHGBHBFFGDFCFGCFAEGHEDEEDEAFFFFFFCHGGDGAFGAFHDBHEBCAGHBFDFFBHFCHFCHCCDCFDHBDGBDBHFA,False +879,13.0,7.0,15.0,3.0,11.0,11.0,9.0,9.0,CHBCFBFGEFEHCCAFAAFCEECBBHEEGEFBEABAADGAGGFGFCGACEHCHCFECADCACCACFAHFHDGHGAHEB,False +880,18.0,17.0,11.0,7.0,12.0,11.0,12.0,19.0,GACGHHGCCDAEAEBAFGHFGHEHABHBDHGCHGCHBABEEBECDDBABBHFHGCBGCBFAAGDAGHHHCAFCABAABAABHAFDAFBGDCHFEBEEHEFHEFBFHE,False +881,15.0,14.0,12.0,18.0,16.0,16.0,10.0,24.0,EFDEFDHBEHAEFFBHEBGEFABHGEHDFHAFEBCDGDAFDAHAACDACDGCEHDBBBBHDHEAEFAHGDFDABHABHAEHFEHFHHFHBFHAFHAEDCGBGGDDHDEHCBCCHCEFDGGHCDCC,False +882,1.0,3.0,4.0,5.0,7.0,5.0,2.0,5.0,HDHBCGDFACFECFEFBDFDGHEEHEBHEDCE,True +883,10.0,19.0,13.0,15.0,16.0,14.0,11.0,10.0,FDEBDAHCBEFHFHGGHGEBGCHCEECDACEFBAFHCBCEBAGBFGCEGBEHDDHBDHCDAFDEBDFBDEADBADBAECAGDABCGDCFBGFBDFBEFBFGBEHEECF,False +884,4.0,20.0,14.0,12.0,17.0,18.0,12.0,16.0,DHCFHCBHGFHFEDFEDBCDBFHHGCDFADCGHFBDCBDHAGEFBEHBEDCEGCABFHBHCCCCBHCGGFGFFBFBBEGFEBBBCGEGHHHFDAFDEFBEFHEGDEBEEBEEB,False +885,4.0,5.0,7.0,5.0,3.0,5.0,11.0,4.0,GBBEAFCABHGBGEFGDDCBDCFGCAGCDGCGHEGHFCHFGAGD,False +886,4.0,2.0,5.0,6.0,4.0,7.0,8.0,6.0,DEGFEGHBGCGHBGHDFAFFAFDADGCHECDECFFCHADHGG,False +887,7.0,10.0,2.0,12.0,7.0,8.0,10.0,7.0,HDGHAEDCDDBGDBAEBGCBDAEGFGFBGFBDDBFHBEHADFGDFHHFHEDGADGAFEAGEBB,False +888,22.0,21.0,26.0,15.0,24.0,25.0,19.0,23.0,HFHEFEAADAGDBCEBGEBEFHEGHAGEDGADFEBFCBFBBFCEHADFEHGHHFDFCHFCHDBGDHAAHFCFAEBAEGCEGCFFAHHGHHFHHCHCBABGDHHDFABGCFACFECDEAGEAGFBCFGCEGCBBBEBAGHGGCBAFACFDCDDCFCAHCACCBEEBEEBEADCCEF,False +889,14.0,18.0,14.0,7.0,16.0,10.0,10.0,16.0,FHAHHEDDECCCHBCBBFBFCBACDAGHAGHBFHBCHBEGEEGBBGBBGEAEAHHBEFFEAFEDHECEEGABGBDGCABEABAFCHCAACGBHHAHCDHFECFED,False +890,18.0,20.0,25.0,21.0,23.0,27.0,22.0,23.0,ECFEGEBFABFABCDBFHBHABHBDHGFGBFGECGCFHADHDEACCBHFEGFACHECHFBACCCBEBBDFDAEAABDAECCCFCFFCFFCEGCHBEGDEDFBDEGHFCHFCFDCFEGGEGDDGHDHHCGHFDFBDHGHHAAHAEHFGAFGAEADEFCEFBEGBGGHDAEDCEHCDGBDG,False +891,21.0,17.0,16.0,20.0,21.0,17.0,22.0,30.0,GEDGFABBHBBHFAGAEEAEAAECAEHHHBDDCABHGGHGCBAAFABFBFCGEBFEGEHHEHHDDHFGEEHDGHCAHFADBADCCGACHDGHAGHAFHAFBECBEDHGCHGAHGBDCEDCDBFDEGHGADGDHGFHCDGDFHBHHBHAECFECFEGFHFEDCED,False +892,2.0,4.0,1.0,8.0,1.0,2.0,5.0,5.0,HHHHBDABDGBDFFDCAHGGGBDGDDED,True +893,15.0,5.0,9.0,8.0,9.0,2.0,15.0,5.0,GGEGEEDAFGECACCAGFGEEDECDBAEGADGABAACCACCAHGAHADHGDGGHGBACBHBDEGAAGD,True +894,15.0,20.0,23.0,20.0,17.0,18.0,26.0,16.0,FGDFCFCCGBFEBEEDACGECGHCFFEDBBCHBFHBDAFHBGCFCCFAGHDGDGGBFEEGCEGAFGAEAFEDFEDBBDHBHGGGGCFDCEHBEHGCAAAAAGHCHHCHBGDDCDBGBBCABCABADBADBFDGGCCEDEEDGCGGDDGHCFHEFH,False +895,17.0,14.0,14.0,9.0,18.0,14.0,9.0,18.0,BGCDCCFADADBGDGCAEEAGEBEFBHHAEFFEHFEBEBCGCEBCEDAGGAHEABEABDAFDHBHHAAHBAHAHBAHCEHCAHFHBEHFCFFCEFCEHCHHCAEDFEDBGFGF,False +896,10.0,10.0,7.0,13.0,14.0,14.0,10.0,8.0,HCBCDHHGEAFHFCDGHEBDEAFBCFEDFADEADEADABBHCAEDGDDGFDAFHHFDGFGGFABFBCDBCEAGBBGEFGEFEEFEE,False +897,1.0,6.0,2.0,6.0,4.0,12.0,5.0,5.0,FBDGCGGDFEBFEFFEGFBGFHFFDFHBAHFEDFCHBBHDD,True +898,8.0,2.0,6.0,2.0,1.0,5.0,2.0,3.0,CFFCHDCFEHHAADAACCABAACGAFGBF,True +899,13.0,11.0,11.0,13.0,12.0,11.0,12.0,9.0,FCCGCABEBEEFCBGCDGCAECEEHAEGDCFFHDBCABDABEAFCBHABHADHGDFGDFBDFEDGHBGDGDAGAFECHEGDEGHFAHDABAF,False +900,11.0,8.0,16.0,15.0,15.0,12.0,12.0,10.0,HFDECDECFHCHGDEDEEBGHDAHDABCCDDFGDCGBCACCDGGFCGFEHEAGEAGEAFCCHCCAFEAFADEADHGDBFBBFBBFGCEAHFCDEEDHEG,False +901,6.0,5.0,13.0,12.0,14.0,4.0,0.0,2.0,DEEDEFCACAAEHEECDECAHCBDDECCBCFFDBFBCDECEECEDCADEDDEDACB,True +902,5.0,2.0,3.0,0.0,2.0,4.0,3.0,0.0,CFECFBAGAACAAGFFGBE,True +903,1.0,3.0,5.0,2.0,2.0,3.0,3.0,5.0,HEAGEFBCDBCBCFHCFHCDHGHG,False +904,8.0,10.0,8.0,10.0,10.0,10.0,8.0,8.0,HAEHAEDAEDGHFGFFAFFBFFGDABDECDEGGEGHBHBBCCFEDGECBCCBACHDCAFBDDEEDAHGBHBF,False +905,19.0,35.0,22.0,16.0,17.0,18.0,22.0,17.0,BEDEDGGBEBBDBGHBCBBCBHCAEAHBAGBCBHDBHDCHGCBGDAGDCCAGDGCDFCBFCBDBBDHAAEAGEGGEGBAFBHFGFGBFHEACECCGHCFFEFBCFBAFAABBBBBHDBEFBHFAGBEFCDGCFCDEEHBBFBDCGDEGFHGACAACAHHFGHEABE,False +906,6.0,6.0,11.0,1.0,5.0,2.0,8.0,3.0,GGECBACGCCGHCBFEGGAACAACDACBBCHCEFCEHBEGBG,True +907,10.0,11.0,15.0,22.0,12.0,15.0,10.0,11.0,CBDCFAHHHHCHDBDDBEDHCAECDFFDACDGBDABCFBCFBGDCFFCFEEHGGHGADGDFAFACGDCADFBCFGDFEDFDDADGAHEBHFCHDCDEEBEEDEGBE,False +908,4.0,0.0,2.0,5.0,3.0,0.0,2.0,3.0,GHACDADAEDAEDEGDHHC,True +909,1.0,4.0,0.0,5.0,2.0,3.0,1.0,1.0,FDHBDABFEBDDBDEGF,True +910,9.0,19.0,26.0,20.0,13.0,12.0,16.0,22.0,BHDCHGCHBCHDCBGCAEDFEBFBHDBHDGHEGECGCFDCHHGHHBHGFGCCBCCDCHAADFFDFFHEDCFBCEHCEHCDDFAGECGDBDBGFGEECBHCBACBACHCDEFDAHBCHCEGBGGCDDHDEHBAGBADB,False +911,5.0,1.0,2.0,3.0,2.0,3.0,0.0,2.0,HAHAADAFBAFEFCEDCD,True +912,26.0,20.0,25.0,15.0,11.0,21.0,19.0,28.0,BGFDDHABFAGCACFBCDBGDCCAAAHAAHFCHCEGGFFHHFBCABCGGGGBHEAHCAHBAHAHHACHFDHDAHABHCBFEBFADFGDCGFFHCGBCFBDFEDCHBBHBCGECGEHGFHAEHACHADAABHFDECEGBAGDHFDHCCFGAEGAECABFFBHCCHD,False +913,7.0,7.0,5.0,3.0,0.0,6.0,1.0,6.0,CDFCAFHACADCBBHBFHBFHFDGCABBABFHHAA,True +914,20.0,24.0,25.0,24.0,19.0,23.0,23.0,19.0,BDHFDGCHCAHFAHFGGCHBCHDFEDAEHCBFEBCGHCGFEACCAHDFGDFDBFBEFBEBGDBGDBCDECBFHEEEBCGBDDFDECHEHBFCAFADGADAHFCFFGFAGFEGEHGADDHDCHDBDDGEDBHABGGBEGBAHBHBDCFDCACCGEAACCACGAEGBEFBAFCCFGBAG,False +915,6.0,10.0,1.0,9.0,16.0,12.0,5.0,11.0,BFGFHGADDEEEEBEEHEHHEHFEBEGHFDHFBHFBDFDFFEBGDHCEBEEBEAGDADHAFAAFHBBEDF,True +916,19.0,25.0,17.0,15.0,26.0,25.0,27.0,16.0,EBBHBCGEEAEBCECGECHHCGDCECGECDBCDBAGCHGBFDBDBCEBFAAGAAHBGDFGAEGAEHEEHECGFFAFBEEAEEABEHBGHBFHDGCCFEFFCFFGFDHBAHAGFDGFDGHGGEDGEBGHGFFECBAFBHGEFBFGDFHDAADGGBAGBFCBFDEFAFBABE,False +917,1.0,1.0,0.0,2.0,5.0,1.0,1.0,0.0,DABDEEEEGFE,True +918,3.0,4.0,4.0,5.0,6.0,2.0,1.0,2.0,FCHDCBDCDEADEBDEBFBGACAEHEE,True +919,29.0,30.0,27.0,23.0,18.0,16.0,15.0,25.0,CECCDDBFGBEHCFACFCCAAAAABGDBDCBDABFBCEACABCGBHGDCGFBGHCDHCEHCBAFBFGHFHHDHFEHFEHCDBDDACBACGACGACFEDEBDHBDHAAEEGFBHHBHDAHBGBCGDAAHAFEBCCBDBEEAHEHFGHAHAABBABDHBDADDAECGBCEDCDCGEHAEHABBFF,False +920,6.0,8.0,6.0,2.0,10.0,1.0,2.0,2.0,ABABBFGBDGEECCEACECHEHBEABDBEEEACEACB,True +921,9.0,6.0,2.0,9.0,10.0,5.0,13.0,15.0,EBEDHGAHGFHGFBDEDDGCDGDHFAEABEGEGAHGAFEAGHAHHEHDEHDABDBGEGGBGHHACHFHH,True +922,0.0,4.0,4.0,4.0,5.0,3.0,8.0,5.0,BFCBHEBHDBCDFGGEGFEGEHGHCDHGDGGEC,False +923,9.0,18.0,18.0,28.0,20.0,33.0,20.0,19.0,FCFHEFDEBCBBCFACFDCDCAFCAHBDHBFGFHAFEAFEHGCHGDHCDHCFCGDCHBEGFFGDFGBHGDFGDFGFAHDBGGHHABEDFFDFFDFFEBFHDCEDFEFHEHHDGACFFGHBBHBADDDDCDEGDGGCEFCDBEBGEDEEBCEFGFFBEDGEDBFDE,False +924,2.0,5.0,0.0,7.0,6.0,1.0,0.0,3.0,EEDEEHEBAEBDDDADBHDFHBBD,True +925,12.0,20.0,17.0,18.0,18.0,15.0,13.0,21.0,GHHFHBACCFFHHFHHABHGDHFDEBABDDBCAEHABDEDCGDGDDGCDFFDHEBAEBAEBDCBGCEGBEHBFCEFDBGBFGBHBHHFFEEGECGECGECBHGBHDCHDAFDCFDEAHAHEAHACCEEFBBDCC,False 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+976,27.0,32.0,25.0,20.0,17.0,19.0,24.0,36.0,HCFABFDBGEFGFDCBDCAEBHEDADCADCGBCDACDBBHBBDAHAHHFFGEFHHBBHEFAEDHEHHBHHDAHCACCDDDAHCEECBBHBHHBGDBGBBGHCAHCFHFHGCHGAEGFFBBHCBHAAABACEGCGGCGACFACGHBDCBHCGGEHEBGAFFAEHHDFHDFEGFABDABGBBECBEBGAAFAACGHGHHGDH,False +977,21.0,23.0,33.0,29.0,26.0,21.0,26.0,19.0,BFCBCBEGFEGDEGFEBDACFGCDGADCDDCBBCGCDDCGCCGDDGBFBEEBAABAACFCCFHDDHDEBDEFCEBBGBEEDAEAHFCHFHHEBEEFFEFHEADEGEGGCGGADDFBCADDDCCGCCGCDGEDFADGDFGFFBCAAHAHEFHECAGFGDCEDCADBAHHHHEHHEFHBCCCCBBAABCAHHDGBEGCGG,False +978,7.0,8.0,10.0,5.0,10.0,5.0,5.0,1.0,DECDEBFCGFADFEBAECABABEGGECDFCGBEGCEHCBDCBCABCAEAFE,True +979,1.0,2.0,1.0,6.0,0.0,1.0,0.0,1.0,DCADFBDHDDBD,True +980,24.0,21.0,18.0,12.0,17.0,7.0,12.0,18.0,BBAHBHDDHBHFAHACBEBBCBAEEACHAHHEGBBGBCDCCAECAHCAGGAFFACFAHHEEAEHFGCACEACHFCHDDEDDEDDCBCCHEBHBAHEABBGBBADBGBBEAAGAADHEGEGGEGAFDACC,False +981,22.0,33.0,18.0,23.0,27.0,28.0,28.0,13.0,EAEDGBCFBAFBGFDAFAAGHAEBFHFFHFFGACDBDFCDFGDBEBBDHCFBEEGGDAGECGEFABFGBEDAEAHEGDDBEGCDABHBBGBDFBDHBGBBEBBHABAABDCEFGAFGAFBFCEFBGGHAGAFEDGEDCHFHBFGDHCFHCAGFDGCGECFECBECBECECABCAEFBEFEEGDBGDEGDBGD,False +982,22.0,20.0,15.0,16.0,27.0,17.0,27.0,21.0,GDFGHEGBEHCEBCHBEHBAHGCGGEGBBFDEADFFHADHEBHGDACDACDEBEEGEHBEGBEGHEBFAAFGFFGDFGDFABGHFHCEECHDGBDCBFFBGCBDDHDCGBCFAFHGGHEGACHECAEAAHCABAACAHEEDEADEFEGBGGEGAAGEBGFAHHAE,False +983,6.0,5.0,6.0,11.0,8.0,8.0,5.0,7.0,HBFHDFCEABBADECDEGDFCDFHBFEDECCFGHFAHGHHADEADFCDGDDGEBAE,False +984,9.0,13.0,13.0,13.0,32.0,25.0,15.0,18.0,EEAEEGEABEGHGFDADEEFAHHCBFGDCBBCHBCFDCFDCFDEFDEFCHFEFECFEHFHGFHGFHEBBCGECBDHHEEDEFCEGAADEFEHGEDFEHFEDFEGBHHFHGEEGEGAACFABFGFDGBEECEEFHBFHB,False +985,14.0,10.0,10.0,7.0,7.0,11.0,13.0,6.0,FAFAHGABAACAAGAFCDDCGCEFDBGBGACHECAECAEBAHDDFDBFDBFGBAGCHBEHBAGBECFFCEFGGGGGFH,False 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various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/src/main/scala/org/xcit/nback/markov/models/State.scala b/src/main/scala/org/xcit/nback/markov/models/State.scala deleted file mode 100644 index fbbd844..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/State.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * A Single state with a label in Markov chain - * @param label A simple string label, representing the state and node - */ -class State(val label: String) { - - /** - * Keep track of transitions from this state to other states. - */ - val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() -} diff --git a/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/src/main/scala/org/xcit/nback/markov/models/Transition.scala deleted file mode 100644 index bc20a9e..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/Transition.scala +++ /dev/null @@ -1,8 +0,0 @@ -package org.xcit.nback.markov.models - -/** - * A Single transition in Markov chain graph. It is stored in "from" node. - * @param to the ending node of the edge - * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). - */ -case class Transition(to: State, probability: Double = 0.0) diff --git a/src/test/scala/ThreeBackBenchmark.scala b/src/test/scala/ThreeBackBenchmark.scala deleted file mode 100644 index 0c7dad9..0000000 --- a/src/test/scala/ThreeBackBenchmark.scala +++ /dev/null @@ -1,7 +0,0 @@ - -/** - * TODO Benchmark 3-back simple sequence generator - */ -class ThreeBackBenchmark { - -} diff --git a/tests/benchmark_diagrams.py b/tests/benchmark_diagrams.py new file mode 100644 index 0000000..8fa448e --- /dev/null +++ b/tests/benchmark_diagrams.py @@ -0,0 +1,159 @@ +import pandas as pd +import numpy as np +from matplotlib import pyplot as plt + +import benchmarks.common as common + + +def tlratio(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2,ignore_index=True) + stats = [] + for trials in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == trials) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == trials) + targets2 = data[alg2].targets if alg2.shape[0] > 0 else np.nan + targets4 = data[alg4].targets if alg4.shape[0] > 0 else np.nan + lures2 = data[alg2].lures if alg2.shape[0] > 0 else np.nan + lures4 = data[alg4].lures if alg4.shape[0] > 0 else np.nan + stats.append([trials, (targets2/lures2).mean(), (targets4/lures4).mean()]) + stats = pd.DataFrame(stats, columns=['trials', 'tl2', 'tl4']) #.dropna(subset=['skewness']) + + plt.style.use('ggplot') + + plt.ylim(bottom=0, top=30) + plt.scatter(stats.trials, stats.tl2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl2[idx], 1)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.tl4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl4[idx], 2)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('T:L Ratio') + plt.ylabel('T:L Ratio') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_tlratio.png', bbox_inches='tight') + plt.show() + + +def time_per_trial(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for t in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == t) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == t) + time2 = data[alg2].time.mean() * 1000 if alg2.shape[0] > 0 else np.nan + time4 = data[alg4].time.mean() * 1000 if alg4.shape[0] > 0 else np.nan + stats.append([t, time2, time4]) + stats = pd.DataFrame(stats, columns=['trials', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.trials, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time2[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time4[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2v4_time_trials.png', bbox_inches='tight') + plt.show() + +def time_profiles(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 8): + alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + time2 = data[alg2].time.mean() * 1000 + time4 = data[alg4].time.mean() * 1000 + stats.append([ni, time2, time4]) + stats = pd.DataFrame(stats, columns=['n', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.n, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.time2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + plt.scatter(stats.n, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.time4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_time_n.png', bbox_inches='tight') + plt.show() + +def skewness(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 9): + all_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + skewed_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) & data.skewed + all_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + skewed_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) & data.skewed + num_of_sequences2 = data[all_alg2].shape[0] + skewed_sequences2 = data[skewed_alg2].shape[0] + num_of_sequences4 = data[all_alg4].shape[0] + skewed_sequences4 = data[skewed_alg4].shape[0] + skewness2 = skewed_sequences2 * 100.0 / num_of_sequences2 if (num_of_sequences2>0) else 0 + skewness4 = skewed_sequences4 * 100.0 / num_of_sequences4 if (num_of_sequences4>0) else 0 + stats.append([ni, skewness2, skewness4]) + stats = pd.DataFrame(stats, columns=['n', 'skewness2', 'skewness4']) #.dropna(subset=['skewness']) + + + plt.style.use('ggplot') + plt.scatter(stats.n, stats.skewness2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.skewness2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + + plt.scatter(stats.n, stats.skewness4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.skewness4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Skewness') + plt.ylabel('Skewed Blocks (%)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_skewness.png', bbox_inches='tight') + plt.show() + +if __name__ == "__main__": + tlratio() + skewness() + time_profiles() + time_per_trial() diff --git a/tests/benchmark_skewness.py b/tests/benchmark_skewness.py new file mode 100644 index 0000000..f468b4d --- /dev/null +++ b/tests/benchmark_skewness.py @@ -0,0 +1,97 @@ +import random +import heapq +import csv + +# Common parameters +alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'] +trials_range = (10, 40) +n = 3 +sample_size = 100 + + +def to_benchmark_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [str(ralph_skewed)] + +def benchmark_nb_gm_001(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_001') + + +def benchmark_nb_gm_002(filename): + import generators.nb_gm_002 as nb_gm_002 + + generator = nb_gm_002.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + # print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_002') + + +def benchmark_nb_gm_003(filename): + import generators.nb_gm_003 as nb_gm_003 + + generator = nb_gm_003.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + print(f"sequence {i}/{sample_size}: {trials} trials") + seq = generator.generate(trials) + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_003') + + +def show_skweness_diagram(filename, choices, title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + print(filename) + data = pd.read_csv(filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) #.dropna(subset=['skewness']) + #print(stats.trials) + #plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'{title}.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + benchmark_nb_gm_003('../benchmarks/nb_gm_003_2back.csv') diff --git a/tests/common.py b/tests/common.py new file mode 100644 index 0000000..e40c0df --- /dev/null +++ b/tests/common.py @@ -0,0 +1,27 @@ + + +# Common benchmark parameters +choices = alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F'] +trials_range = (10, 65) +n = 4 +sample_size = 100 + + +def count_targets_and_lures(seq, n): + mask = 'D'*n + for index in range(n, len(seq)): + if seq[index] == seq[index - n]: + mask += 'T' + elif seq[index] in seq[index - n - 1:index - n + 1]: + mask += 'L' + else: + mask += 'D' + return mask.count('T'), mask.count('L') + + +def skewness(seq, choices): + import heapq + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return ralph_skewed diff --git a/tests/nb_gm_001_bm.py b/tests/nb_gm_001_bm.py new file mode 100644 index 0000000..54f6cb3 --- /dev/null +++ b/tests/nb_gm_001_bm.py @@ -0,0 +1,75 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq) , str(ralph_skewed)] + + +def benchmark(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets / s.trials, axis=1) + plt.scatter(data.trials, data.targets_ratio, alpha=0.2) + plt.show() + +if __name__ == '__main__': + alg = 'nb_gm_001' + fn = f'results/{alg}_{n}back.csv' + benchmark(fn) + # skewness_diagram(fn, alg) + targets_ratio_diagram(fn, alg) diff --git a/tests/nb_gm_002_bm.py b/tests/nb_gm_002_bm.py new file mode 100644 index 0000000..c8af543 --- /dev/null +++ b/tests/nb_gm_002_bm.py @@ -0,0 +1,105 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq), str(ralph_skewed)] + + +def benchmark(filename): + from generators.nb_gm_002 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials, int(trials/3), 0, 0) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +import time +import numpy as np +import pandas as pd + +import benchmarks.common as common + +def profile(): + from generators.nb_gm_002 import SequenceGenerator + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, int(lures/2), int(lures/2)) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('benchmarks/results/nb_gm_002_profile.csv', sep=',', encoding='utf-8') + +if __name__ == '__main__': + alg = 'nb_gm_002' + fn = f'results/{alg}_{n}back.csv' + profile() diff --git a/tests/nb_gm_003_bm.py b/tests/nb_gm_003_bm.py new file mode 100644 index 0000000..fa6c19a --- /dev/null +++ b/tests/nb_gm_003_bm.py @@ -0,0 +1,114 @@ +import heapq +import csv +import random +import time + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq, time_per_block): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [time_per_block, ''.join(seq), str(ralph_skewed)] + + +def benchmark_skewness(filename): + from generators.nb_gm_003 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['time_per_block', 'seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + targets = trials / 3 + t = time.time() + seq = generator.generate(trials, targets) + t = time.time() - t + print(f"sequence {i}/{sample_size}: {trials} trials, took {t}s.") + writer.writerow(to_csv_row(i, seq, t)) + plot_skewness(fn, 'nb_gm_003') + + +def plot_skewness(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def plot_targets_ratio(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +def benchmark_targets_ratio(): + pass + +def benchmark_chunking(): + pass + + +def benchmark_n(): + pass + + +def plot_timing(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['time_per_trial'] = data.apply(lambda s: s.time_per_block / s.trials, axis=1) + plt.style.use('ggplot') + plt.title(f"{figure_title} - average time to generate a trial") + plt.ylabel('time (s)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.time_per_trial, alpha=0.5) + + # draw fitted curve + # import numpy as np + # p = np.poly1d(np.polyfit(data.trials, data.time_per_trial, 3)) + # plt.plot(data.trials, p(data.trials), color='red') + + plt.savefig(f'results/{figure_title}_timing.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + alg = 'nb_gm_003' + fn = f'results/{alg}_{n}back.csv' + benchmark_skewness(fn) diff --git a/tests/nb_gm_004_bm.py b/tests/nb_gm_004_bm.py new file mode 100644 index 0000000..b4ad4a8 --- /dev/null +++ b/tests/nb_gm_004_bm.py @@ -0,0 +1,26 @@ +import time +import numpy as np +import pandas as pd + +import tests.common as common +from generators.nb_gm_004 import SequenceGenerator + +def run(): + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, lures) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('tests/results/nb_gm_004_profile.csv', sep=',', encoding='utf-8') diff --git a/tests/results/2v4_time_trials.png b/tests/results/2v4_time_trials.png new file mode 100644 index 0000000..9be91b4 --- /dev/null +++ b/tests/results/2v4_time_trials.png Binary files differ diff --git a/tests/results/2vs4_skewness.png b/tests/results/2vs4_skewness.png new file mode 100644 index 0000000..a488e1f --- /dev/null +++ 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+210,87.0,0.0,0.0,88.0,1.0,0.0,0.0,0.0,EDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +211,0.0,0.0,12.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCC,True +212,0.0,0.0,0.0,66.0,0.0,65.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +213,1.0,0.0,0.0,0.0,0.0,21.0,22.0,0.0,AGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFG,True +214,74.0,73.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +215,0.0,5.0,0.0,0.0,6.0,0.0,0.0,1.0,HEBEBEBEBEBE,True +216,0.0,1.0,0.0,0.0,0.0,53.0,0.0,54.0,BHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +217,70.0,0.0,0.0,0.0,0.0,70.0,0.0,0.0,AFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +218,0.0,0.0,0.0,0.0,0.0,0.0,36.0,35.0,GGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +219,0.0,90.0,90.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +220,0.0,0.0,0.0,0.0,0.0,0.0,37.0,38.0,HHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +221,0.0,0.0,44.0,0.0,0.0,1.0,44.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +222,0.0,0.0,0.0,67.0,67.0,0.0,0.0,1.0,HDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True 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+409,0.0,0.0,72.0,1.0,0.0,0.0,72.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +410,55.0,0.0,1.0,0.0,0.0,0.0,55.0,0.0,CAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +411,0.0,59.0,0.0,0.0,0.0,60.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +412,61.0,0.0,0.0,61.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +413,0.0,1.0,0.0,75.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +414,0.0,53.0,0.0,0.0,0.0,0.0,52.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +415,0.0,0.0,16.0,0.0,1.0,0.0,0.0,15.0,ECHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +416,0.0,0.0,0.0,39.0,0.0,0.0,0.0,38.0,DHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +417,96.0,0.0,1.0,95.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +418,28.0,0.0,1.0,27.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +419,0.0,1.0,92.0,92.0,0.0,0.0,0.0,0.0,BCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +420,1.0,0.0,20.0,0.0,20.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECE,True +421,0.0,90.0,0.0,0.0,0.0,0.0,89.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +422,10.0,0.0,0.0,0.0,0.0,1.0,11.0,0.0,FGAGAGAGAGAGAGAGAGAGAG,True +423,0.0,0.0,0.0,74.0,73.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +424,0.0,0.0,127.0,0.0,0.0,0.0,1.0,0.0,GCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +425,1.0,9.0,0.0,0.0,0.0,9.0,0.0,0.0,AFBFBFBFBFBFBFBFBFB,True +426,0.0,0.0,84.0,0.0,0.0,0.0,0.0,84.0,HCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +427,33.0,0.0,0.0,34.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +428,1.0,30.0,0.0,30.0,0.0,0.0,0.0,0.0,ABDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +429,0.0,0.0,67.0,0.0,1.0,67.0,0.0,0.0,EFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +430,62.0,0.0,0.0,63.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +431,1.0,9.0,9.0,0.0,0.0,0.0,0.0,0.0,ABCBCBCBCBCBCBCBCBC,True +432,15.0,0.0,0.0,0.0,0.0,0.0,14.0,0.0,AAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +433,0.0,1.0,0.0,65.0,66.0,0.0,0.0,0.0,BEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +434,0.0,160.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +435,0.0,0.0,1.0,0.0,42.0,42.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +436,0.0,0.0,55.0,0.0,55.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +437,0.0,0.0,0.0,1.0,0.0,73.0,0.0,73.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +438,79.0,0.0,0.0,0.0,78.0,0.0,0.0,0.0,AAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +439,0.0,0.0,67.0,0.0,0.0,0.0,66.0,1.0,HCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +440,0.0,0.0,77.0,0.0,0.0,1.0,0.0,76.0,FCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +441,0.0,0.0,0.0,0.0,153.0,0.0,0.0,1.0,HEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +442,0.0,88.0,88.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +443,0.0,0.0,0.0,20.0,22.0,0.0,0.0,0.0,EEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +444,41.0,0.0,42.0,0.0,0.0,0.0,1.0,0.0,GCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +445,0.0,0.0,0.0,47.0,0.0,46.0,0.0,1.0,HDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +446,1.0,0.0,0.0,0.0,86.0,0.0,0.0,87.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +447,56.0,56.0,0.0,0.0,0.0,0.0,0.0,1.0,HABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +448,0.0,0.0,0.0,0.0,11.0,0.0,0.0,10.0,EEHEHEHEHEHEHEHEHEHEH,True +449,0.0,0.0,0.0,0.0,0.0,1.0,92.0,92.0,FGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +450,0.0,0.0,0.0,6.0,5.0,1.0,0.0,0.0,FDEDEDEDEDED,True +451,66.0,1.0,67.0,0.0,0.0,0.0,0.0,0.0,BCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +452,0.0,0.0,0.0,13.0,0.0,1.0,12.0,0.0,FDGDGDGDGDGDGDGDGDGDGDGDGD,True +453,1.0,0.0,0.0,0.0,56.0,0.0,56.0,0.0,AEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +454,15.0,0.0,0.0,0.0,0.0,0.0,0.0,16.0,HAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +455,0.0,21.0,1.0,0.0,21.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True +456,93.0,0.0,1.0,0.0,92.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +457,1.0,0.0,0.0,0.0,35.0,0.0,0.0,35.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +458,13.0,0.0,0.0,0.0,1.0,0.0,13.0,0.0,EAGAGAGAGAGAGAGAGAGAGAGAGAG,True +459,0.0,0.0,65.0,0.0,1.0,0.0,65.0,0.0,ECGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +460,0.0,0.0,95.0,1.0,0.0,95.0,0.0,0.0,DFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +461,15.0,0.0,0.0,0.0,1.0,0.0,0.0,15.0,EHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +462,0.0,0.0,198.0,0.0,1.0,0.0,0.0,0.0,ECCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +463,84.0,84.0,0.0,0.0,1.0,0.0,0.0,0.0,EABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +464,0.0,0.0,0.0,0.0,0.0,60.0,0.0,61.0,HFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +465,0.0,179.0,0.0,1.0,0.0,0.0,0.0,0.0,DBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +466,1.0,0.0,90.0,0.0,89.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +467,0.0,35.0,0.0,0.0,0.0,34.0,0.0,0.0,BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +468,0.0,0.0,0.0,1.0,7.0,0.0,0.0,7.0,DHEHEHEHEHEHEHE,True +469,0.0,0.0,0.0,0.0,92.0,0.0,91.0,0.0,EEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +470,0.0,0.0,46.0,0.0,0.0,1.0,46.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +471,0.0,0.0,0.0,0.0,0.0,1.0,158.0,0.0,FGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +472,1.0,0.0,0.0,0.0,0.0,58.0,0.0,59.0,AHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +473,0.0,0.0,6.0,1.0,0.0,0.0,6.0,0.0,DCGCGCGCGCGCG,True +474,0.0,0.0,0.0,0.0,0.0,98.0,0.0,97.0,FFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +475,0.0,87.0,0.0,0.0,0.0,0.0,0.0,85.0,BBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +476,0.0,0.0,33.0,0.0,0.0,0.0,1.0,33.0,GHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +477,45.0,0.0,0.0,0.0,46.0,0.0,0.0,0.0,EAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +478,0.0,0.0,0.0,77.0,0.0,0.0,75.0,0.0,DDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +479,73.0,1.0,73.0,0.0,0.0,0.0,0.0,0.0,BACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +480,0.0,1.0,0.0,0.0,37.0,37.0,0.0,0.0,BEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +481,0.0,92.0,93.0,0.0,0.0,1.0,0.0,0.0,FCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +482,0.0,0.0,0.0,1.0,0.0,0.0,0.0,24.0,DHHHHHHHHHHHHHHHHHHHHHHHH,True +483,25.0,0.0,0.0,1.0,0.0,25.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +484,0.0,0.0,0.0,0.0,0.0,37.0,0.0,36.0,FHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +485,21.0,0.0,0.0,1.0,0.0,20.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +486,0.0,35.0,0.0,36.0,0.0,0.0,0.0,1.0,HDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +487,0.0,0.0,1.0,0.0,97.0,98.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +488,0.0,93.0,0.0,0.0,0.0,1.0,0.0,94.0,FHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +489,0.0,1.0,0.0,93.0,0.0,0.0,93.0,0.0,BGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +490,0.0,0.0,0.0,70.0,0.0,0.0,72.0,0.0,GGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +491,86.0,0.0,0.0,0.0,1.0,86.0,0.0,0.0,EFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +492,0.0,65.0,1.0,0.0,0.0,65.0,0.0,0.0,CBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +493,0.0,0.0,0.0,69.0,0.0,0.0,0.0,1.0,HDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +494,0.0,0.0,144.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +495,0.0,45.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True 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+599,16.0,0.0,16.0,0.0,0.0,0.0,0.0,0.0,ACACACACACACACACACACACACACACACAC,True +600,0.0,21.0,0.0,22.0,0.0,0.0,0.0,0.0,DBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +601,70.0,71.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +602,0.0,0.0,0.0,1.0,0.0,0.0,53.0,0.0,DGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +603,45.0,0.0,0.0,0.0,0.0,45.0,0.0,0.0,FAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +604,0.0,1.0,56.0,0.0,0.0,0.0,56.0,0.0,BGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +605,0.0,1.0,0.0,0.0,0.0,0.0,0.0,195.0,BHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True 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+611,0.0,0.0,86.0,0.0,88.0,0.0,0.0,0.0,EECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +612,1.0,0.0,0.0,0.0,14.0,0.0,0.0,14.0,AEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +613,0.0,0.0,35.0,0.0,0.0,35.0,1.0,0.0,GCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCF,True +614,0.0,0.0,1.0,0.0,43.0,43.0,0.0,0.0,CEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +615,0.0,0.0,0.0,0.0,0.0,1.0,67.0,66.0,FGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +616,0.0,27.0,0.0,0.0,26.0,0.0,1.0,0.0,GBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +617,0.0,88.0,1.0,87.0,0.0,0.0,0.0,0.0,CBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +618,0.0,41.0,0.0,0.0,0.0,41.0,1.0,0.0,GFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +619,0.0,27.0,27.0,0.0,0.0,0.0,0.0,0.0,CBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +620,1.0,0.0,20.0,20.0,0.0,0.0,0.0,0.0,ADCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +621,0.0,0.0,1.0,24.0,24.0,0.0,0.0,0.0,CEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +622,1.0,0.0,0.0,0.0,55.0,55.0,0.0,0.0,AEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +623,1.0,0.0,0.0,0.0,26.0,0.0,26.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +624,0.0,0.0,15.0,0.0,0.0,0.0,0.0,13.0,CCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +625,0.0,0.0,1.0,67.0,67.0,0.0,0.0,0.0,CDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +626,0.0,0.0,65.0,0.0,0.0,1.0,0.0,64.0,FCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +627,0.0,0.0,0.0,0.0,89.0,1.0,90.0,0.0,FGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +628,0.0,0.0,0.0,0.0,1.0,0.0,51.0,0.0,EGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +629,0.0,0.0,41.0,0.0,0.0,40.0,0.0,0.0,CFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +630,0.0,0.0,93.0,0.0,0.0,0.0,1.0,0.0,GCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +631,0.0,53.0,1.0,0.0,0.0,53.0,0.0,0.0,CBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +632,0.0,0.0,0.0,14.0,0.0,0.0,0.0,15.0,HHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +633,0.0,29.0,0.0,0.0,0.0,0.0,28.0,0.0,BGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +634,0.0,66.0,0.0,0.0,0.0,1.0,66.0,0.0,FGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +635,0.0,0.0,62.0,62.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +636,0.0,31.0,32.0,0.0,1.0,0.0,0.0,0.0,ECBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +637,0.0,0.0,0.0,0.0,0.0,0.0,48.0,49.0,HGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +638,1.0,0.0,0.0,0.0,0.0,0.0,54.0,53.0,AGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +639,59.0,0.0,1.0,0.0,59.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +640,0.0,0.0,0.0,0.0,1.0,0.0,27.0,27.0,EGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +641,0.0,0.0,0.0,23.0,24.0,0.0,0.0,0.0,EDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +642,0.0,0.0,0.0,91.0,0.0,0.0,91.0,0.0,DGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +643,0.0,0.0,0.0,0.0,48.0,49.0,0.0,1.0,HFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +644,14.0,0.0,0.0,0.0,0.0,14.0,1.0,0.0,GAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +645,0.0,96.0,0.0,0.0,1.0,0.0,0.0,96.0,EHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +646,0.0,0.0,0.0,50.0,48.0,0.0,0.0,0.0,DDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +647,0.0,0.0,0.0,99.0,0.0,99.0,0.0,0.0,FDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +648,49.0,0.0,1.0,0.0,0.0,0.0,0.0,48.0,CAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +649,0.0,0.0,52.0,0.0,1.0,0.0,53.0,0.0,EGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True 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+667,1.0,147.0,0.0,0.0,0.0,0.0,0.0,0.0,ABBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +668,0.0,0.0,97.0,0.0,97.0,0.0,0.0,1.0,HCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +669,0.0,0.0,1.0,0.0,0.0,0.0,53.0,52.0,CGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +670,0.0,0.0,94.0,0.0,96.0,0.0,0.0,0.0,EECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +671,99.0,0.0,1.0,0.0,98.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +672,68.0,0.0,0.0,0.0,0.0,0.0,67.0,1.0,HAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGA,True +673,0.0,0.0,0.0,26.0,27.0,0.0,1.0,0.0,GEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +674,31.0,0.0,0.0,0.0,32.0,0.0,0.0,1.0,HEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +675,0.0,0.0,0.0,0.0,42.0,0.0,41.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +676,0.0,0.0,50.0,0.0,0.0,0.0,1.0,50.0,GCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +677,0.0,25.0,0.0,24.0,0.0,0.0,0.0,0.0,BBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +678,0.0,0.0,0.0,0.0,1.0,10.0,9.0,0.0,EFGFGFGFGFGFGFGFGFGF,True +679,65.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,DAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +680,0.0,23.0,0.0,0.0,0.0,0.0,23.0,1.0,HGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +681,0.0,1.0,58.0,0.0,0.0,0.0,57.0,0.0,BCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +682,0.0,0.0,0.0,0.0,0.0,68.0,1.0,68.0,GFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +683,0.0,0.0,0.0,0.0,96.0,0.0,96.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +684,1.0,0.0,0.0,0.0,66.0,0.0,66.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +685,0.0,0.0,0.0,0.0,0.0,1.0,0.0,21.0,FHHHHHHHHHHHHHHHHHHHHH,True +686,0.0,88.0,0.0,87.0,0.0,0.0,0.0,0.0,BDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +687,0.0,0.0,19.0,19.0,0.0,0.0,1.0,0.0,GDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +688,0.0,42.0,1.0,0.0,41.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +689,0.0,0.0,0.0,0.0,0.0,60.0,61.0,0.0,GGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +690,0.0,23.0,23.0,0.0,0.0,0.0,1.0,0.0,GBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +691,86.0,86.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +692,35.0,35.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +693,57.0,0.0,0.0,0.0,0.0,58.0,1.0,0.0,GFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +694,0.0,0.0,30.0,30.0,1.0,0.0,0.0,0.0,EDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +695,19.0,18.0,0.0,1.0,0.0,0.0,0.0,0.0,DABABABABABABABABABABABABABABABABABABA,True +696,0.0,0.0,0.0,1.0,0.0,56.0,0.0,57.0,DHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +697,10.0,0.0,1.0,0.0,0.0,0.0,0.0,11.0,CHAHAHAHAHAHAHAHAHAHAH,True +698,0.0,0.0,89.0,0.0,88.0,0.0,1.0,0.0,GCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +699,0.0,0.0,87.0,0.0,86.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +700,17.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAA,True +701,0.0,0.0,66.0,65.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +702,0.0,0.0,1.0,0.0,0.0,0.0,123.0,0.0,CGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +703,0.0,118.0,0.0,0.0,1.0,0.0,0.0,0.0,EBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +704,0.0,0.0,0.0,0.0,0.0,0.0,0.0,132.0,HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +705,0.0,0.0,0.0,0.0,0.0,23.0,1.0,23.0,GHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +706,0.0,0.0,0.0,0.0,6.0,5.0,0.0,0.0,EFEFEFEFEFE,True +707,18.0,0.0,0.0,16.0,0.0,0.0,0.0,0.0,AADADADADADADADADADADADADADADADADA,True +708,0.0,72.0,0.0,0.0,0.0,71.0,0.0,1.0,HBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +709,0.0,0.0,54.0,0.0,0.0,1.0,0.0,55.0,FHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +710,0.0,1.0,87.0,0.0,87.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +711,0.0,0.0,1.0,63.0,0.0,0.0,0.0,64.0,CHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +712,78.0,0.0,78.0,0.0,0.0,1.0,0.0,0.0,FCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +713,0.0,80.0,0.0,0.0,0.0,81.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +714,0.0,1.0,0.0,0.0,0.0,0.0,40.0,39.0,BGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +715,0.0,0.0,7.0,0.0,6.0,0.0,0.0,0.0,CCECECECECECE,True +716,35.0,0.0,0.0,0.0,0.0,0.0,0.0,33.0,AAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +717,0.0,0.0,0.0,1.0,73.0,0.0,0.0,72.0,DEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +718,0.0,0.0,90.0,0.0,0.0,1.0,89.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +719,1.0,0.0,0.0,67.0,0.0,0.0,0.0,66.0,ADHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +720,56.0,0.0,0.0,0.0,56.0,0.0,1.0,0.0,GAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +721,0.0,0.0,0.0,1.0,0.0,0.0,49.0,49.0,DHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +722,0.0,0.0,0.0,117.0,0.0,1.0,0.0,0.0,FDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +723,0.0,0.0,86.0,1.0,0.0,0.0,85.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +724,0.0,0.0,31.0,0.0,0.0,0.0,0.0,30.0,CCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +725,1.0,0.0,0.0,0.0,98.0,0.0,98.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +726,1.0,84.0,84.0,0.0,0.0,0.0,0.0,0.0,ACBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +727,0.0,56.0,56.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +728,0.0,1.0,0.0,24.0,24.0,0.0,0.0,0.0,BDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +729,37.0,0.0,0.0,0.0,0.0,37.0,0.0,0.0,FAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +730,0.0,0.0,91.0,0.0,0.0,0.0,91.0,0.0,GCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True 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+772,0.0,68.0,0.0,0.0,0.0,0.0,0.0,67.0,BBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +773,60.0,1.0,0.0,0.0,0.0,61.0,0.0,0.0,BFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +774,0.0,1.0,0.0,57.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +775,0.0,78.0,0.0,0.0,1.0,0.0,0.0,0.0,EBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +776,1.0,0.0,0.0,0.0,0.0,96.0,96.0,0.0,AGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +777,43.0,0.0,0.0,0.0,0.0,1.0,44.0,0.0,FGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True 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+989,93.0,0.0,92.0,0.0,0.0,0.0,0.0,1.0,HACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +990,0.0,1.0,0.0,0.0,60.0,0.0,0.0,61.0,BHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +991,0.0,1.0,0.0,0.0,0.0,0.0,32.0,32.0,BHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +992,0.0,0.0,34.0,35.0,0.0,0.0,1.0,0.0,GDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +993,0.0,0.0,0.0,0.0,54.0,0.0,54.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +994,0.0,0.0,0.0,1.0,0.0,39.0,0.0,38.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +995,0.0,0.0,0.0,0.0,99.0,98.0,0.0,1.0,HEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +996,86.0,1.0,0.0,0.0,0.0,86.0,0.0,0.0,BFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +997,0.0,76.0,77.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +998,0.0,0.0,19.0,0.0,0.0,0.0,0.0,1.0,HCCCCCCCCCCCCCCCCCCC,True +999,0.0,0.0,37.0,1.0,0.0,0.0,38.0,0.0,DGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True diff --git a/tests/results/nb_gm_001_3back.csv b/tests/results/nb_gm_001_3back.csv new file mode 100644 index 0000000..b2f89a4 --- /dev/null +++ b/tests/results/nb_gm_001_3back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,0.0,65.0,132.0,0.0,0.0,0.0,0.0,1.0,HCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCC,True +1,51.0,0.0,52.0,52.0,0.0,0.0,0.0,1.0,HCDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACD,True +2,0.0,61.0,0.0,62.0,0.0,0.0,61.0,1.0,HDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGD,True +3,40.0,0.0,0.0,1.0,0.0,0.0,0.0,80.0,DHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHA,True +4,4.0,0.0,1.0,0.0,0.0,6.0,0.0,0.0,CAFFAFFAFFA,True 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+401,0.0,55.0,55.0,0.0,0.0,1.0,54.0,0.0,FCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCB,True +402,47.0,0.0,0.0,0.0,1.0,47.0,0.0,47.0,EAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFH,True +403,56.0,0.0,0.0,0.0,58.0,0.0,0.0,56.0,EEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAE,True +404,0.0,39.0,0.0,0.0,39.0,1.0,40.0,0.0,FGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEG,True 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+3,12.0,15.0,11.0,20.0,13.0,17.0,17.0,22.0,AFAHGHGHGBEBCDDDDHHHABCEHEHEBBBAHADADCFHHHHHFEFCBDDFDGDEFCAGGFEFBDGEHECCBCFFFFFFHGEBBHHCBCACHHDDBFGGGGEGEAFDGDADGDGDGBEBAAHDDFH,False +4,4.0,4.0,8.0,8.0,5.0,7.0,4.0,2.0,FGDGECDCECGCDADAHFDFCFCGAFCDDDABEBHBEFEFBC,False +5,15.0,15.0,15.0,16.0,16.0,14.0,9.0,13.0,HGDGBFDHDADHBBBBBHBAAGBCEABCGFAFAFBGBCBFGDDDEAAAHDFACECECHFHFHFCFHEGEFEFDFDAAHDEECDABFCCCCGBEBDAHCECHCHEDEDEDAGEE,False +6,17.0,17.0,9.0,6.0,15.0,13.0,15.0,12.0,BEBEBHAGCFEHHABAHDEDGHFBFGFCAABAGFFFAFGECEBEAEAFBFCEBEGHGDBEFABABEGEHEHBGBGDADACAGHGHGBGBACGCAHFFBHAECDC,False +7,12.0,7.0,7.0,6.0,9.0,8.0,5.0,6.0,CEGBFEFEFEHCCDEBCCHBBBGAHACBGGDBDADACADHDHFEAEAEFGFAAEAHAFAF,False +8,9.0,13.0,10.0,11.0,12.0,15.0,11.0,12.0,CGCFDBDFHHEHFFGCDHEHCFCFAAEGDCEGHGCFCBBBCBGFGHGDFDBDADHBBEGAGABABHBEBEHGHADAFEFCFDBDEFEHEFEFA,False +9,13.0,26.0,23.0,14.0,20.0,18.0,19.0,27.0,HECEBEFFHFDCCFGBCBDBAHGHGCBBABHEFAFEBEBHBHGGCHBGGCCCCCFCBDDDEDHDEEEAAFAFGFDFCGBGHEHDHGHAFABCGGEHEHFBGBADEBEBEAAHBDCCFGGHHHBHBHGHBDBEEAEGCGCBCHCEFFFFCHDHCHDHABCB,False +10,14.0,18.0,15.0,13.0,15.0,19.0,18.0,11.0,AFACABDDFBBBEBECECGHFBFBECDCEEEDGDBHHGCBDDAFCBAAAGHCHCHEAFBFDHAHCFFAAAHBBBFBFBHGFBCBCFGGGHGDGDFEGEFCFEDGDGAGEGCGEGEFEFAFDGC,False +11,21.0,20.0,21.0,13.0,15.0,26.0,21.0,21.0,EECEFFHGCADHGEGEABCCFDEBABEBGGCACHFHFBFBFBAHGBGCGHDCDABHHAGABFHEBCFEGDFDFDFAFBCBCAHACFGFBFBFBFBDACCBCHFHEGEDFDFCAAAGGEBFAAACACHCHFGFBFGHGHAEAGCCEDDFHHHGHGHGDE,False +12,17.0,26.0,17.0,23.0,17.0,11.0,26.0,21.0,ABGCACGDDFHFHBCEHEAGBGBEBAHEBEBFAAHAFBCEGDGBAHGGGGFGDDDBABABHGGGCGDGHGHDACAEDEFECHGEGDABGCHCDDDDCBCBADAHCHGBGBGEHDCDBBFBABHBHBFBACHDEEHGHECDCDHDEFEDECFGHGBFBD,False +13,24.0,21.0,23.0,20.0,15.0,14.0,30.0,24.0,AHHHHAFEDHAFBFGFCFGADADCDGBBBBGDGEGBCBHGGGGCGFBFAGGGGHEEFEGHGHABCBFHGAGACBBDEDHDHDGBCACAHGCACEHECACHBHDCGCECADGDGDABADHFGCGAGAHHBGFDCHBHCAAABEEFDFDBDBEADAHGEGEHECCCBCFCAHD,False +14,1.0,0.0,2.0,1.0,1.0,1.0,2.0,2.0,DECGCGAHFH,True +15,7.0,7.0,10.0,5.0,8.0,4.0,8.0,9.0,HBABHHEEGAGAGEGHCDEECHCHGBCBCDDAEGCBCGEAEFDFBFBFAGCHCHCHAD,False +16,14.0,19.0,14.0,7.0,10.0,15.0,19.0,7.0,CEAFFGHGEGFDFDCACAGBDEAFCEDDFAHHFDFGBEACGCGBGAFECECFGHCEBAFGEGCBABEBHBHBACAGAGDGHBABCBCBGFGFGFGBBBBFBCBGA,False +17,17.0,15.0,14.0,12.0,10.0,9.0,17.0,6.0,EBACADACGBGBAFGHGHADCDGAAFFFADABAHGDGABBCBCACACECHFBFHDCACDGEBADDEGGGEDADFGFGCGFBBABCBEBDBCHGEGEGECE,False +18,14.0,22.0,17.0,9.0,14.0,10.0,25.0,20.0,EHCHAHEHAHCHCGBGCGCGAEBFBFGGCEFGBGHAHCBABABHHGHGCACHDEDBBABGGDGDEBBBHHGCAEGBFHGEGEGBCCGCDFBBGBFBDAEEHHHCFEFECEHGCGCBHDADFDAGAGAGFBB,False +19,13.0,27.0,12.0,18.0,19.0,17.0,20.0,18.0,BFGCGBHAHAHEFEDBABEBEDADGGGGBAFCGEBDFHBHGHGCBBEGEGBHDHDHBCBCACDBFHHCHBGAGAGEDADADCDCACGHEEEEBDFDFDHDCGGBGDEBBBABEHFHGEFFFBADHEFFCFDEBEBFFEBHBFBG,False +20,11.0,10.0,7.0,8.0,8.0,7.0,11.0,4.0,BGBABGHGCGFBFAEBGGEDEFAHEHACDCDADBGGAGAGADFBFBCBCEFBFDHDACCDAGAEEE,False +21,22.0,20.0,18.0,24.0,13.0,11.0,16.0,21.0,DADADHCACFCHEDAAAHGDDHAGCDEDEGBHAHBDBDBGHHHCHCECAAAEFEDECEDBHFABGBCAGDBEGEBABHFCBBABDFDGHGCBFBCCDHDHDGDHDHCHBGADAFACHEHBDCDAFAFAFAGGCGCFHGBDBEBEG,False +22,8.0,10.0,11.0,7.0,8.0,15.0,4.0,11.0,CBAEGDGEHEBGBFBFBDHCHFHBAEHFFGFCFBFCFEEHABECFFFFACAEHHDCDCDHDHAHCFCBCBAADF,False +23,32.0,19.0,21.0,23.0,13.0,27.0,21.0,27.0,GHCABDGDFFFAHHHEAEHGAGAGHEFEGBCFAFBFGCHCHFHBGCAFFDFDBACACHCHCHBFGFEACAFABEBEBHHGHFHAHGGAGAHAFCGDHDHAFGCBCHDAAAAAAFCFHGEFFBEBEDDDFDBCBDDDCGFAFADBDBEBCAGGHDFDFBCDEAGAHCCEHGHAHCDDDDABAFA,False +24,26.0,30.0,18.0,21.0,29.0,16.0,21.0,21.0,GDGDADAGAGDEHCDBDHAHEHFHAHAFBHBHGCEBHBDBHBHBEEABABABAEECEGEGAGADHDBEEGBCAADHGBFBCEAAHDEBEBFBFBFCCGCEFBABAEDBGFGBGCFCGEACDFEFBHDADFHCEAEBDHDCGBEFGCDCACDEBEGAGAEAEFDFBBEHEGEGHCACEFBHDH,False +25,17.0,15.0,10.0,21.0,16.0,11.0,16.0,22.0,BDBDBHHHAAGAEHEHCHCDADEBGHDAGEBHGAABADADEDECEHAHFBGCGBEHCGADFBHECGHHFFFHFBDDDDDFDFDFHFEDEDACAEAEBDCHHBFBABCBGDGEAECHHGHGEGHDAGGG,False +26,12.0,13.0,16.0,11.0,17.0,10.0,17.0,12.0,GEECBGFEEDHCEFGFEAEAHGEGEDDDHDCDCBHBCBCFCECEGAGAGAHECFCEAAFGFGCEHGHBBBGBGBCBDHEAEFHFHGBCDGGACHCGCDADAEBFBADH,False +27,14.0,11.0,17.0,13.0,14.0,21.0,16.0,19.0,AAECGGEGHCACACACHBHADCECBDHDHDFCFGHGDDEDHHHAHDFDACHBHAFBHHAEEECGGFGEGEBEFCFAEAEFFBFBFDGDGDGHFACCDFHFCGBBHBCGGFGEHEFFFFHFCBCAF,False +28,14.0,15.0,12.0,21.0,15.0,9.0,13.0,21.0,GGHGEDHFCFCACBCADAEEEEAHDGAGHGHEHEHBBECEDBBBDBEGDGBAEABCCABBECDDDFDFHGHGHDHGHGHDADHHCHBHCCBAFHFDDDEDHFHAABDFDFEGEAADBDCH,False +29,18.0,19.0,27.0,26.0,29.0,30.0,16.0,16.0,DEFFFAFAGDGEEBFBFGEBADACADFDCEEDEDFDCDEBBGDGHGHGFFFDFBEBEHCHFDCDCEGFGFHFEFCGBBDCHCGCDADEGEGCFAAEHEHFDACGCEABBDECBCBCEFEFBFCFCFEHEHDGACEBAGCEFEBACCCAEDHDHBCFCDEFFHDHDHDCFCAAAEBEBFDHA,False +30,5.0,11.0,5.0,8.0,3.0,2.0,5.0,1.0,BBFGGBABFGCCCDADAHBEDCDBABGEAECBDBDBDBDG,True +31,28.0,17.0,19.0,16.0,18.0,11.0,17.0,33.0,DHAFAHAEAHDHFHFAFADHCGGGDGDGHEBDHCHBHAEBCBCFEGHHHBHCAFDHEHEHCDAGBCBAAAGACCBCAFGBHEHBBEAHAHAFAEACGGEHAFABEDEDFDCGHEBGAGEEAEBBHDEDECHCGABHGHAHAHBHCHCHCHDGACACDFD,False +32,5.0,10.0,12.0,17.0,19.0,17.0,17.0,11.0,EEBHBFFFDDEDCCAGEFEGGDGDFFGEGEAEDEFCFCGCGCGFAEGECDHHCEFDDHDFDABFDECECEHEFDDGDGBBFBFHHGCECEFEHAHDHDGBBFBGHGBG,False +33,4.0,13.0,10.0,7.0,4.0,8.0,11.0,7.0,CGBHBCBCBHFHFECBADGBGBGBDBCFAGDBHGFGECEHBGBCCACFGFGFGDDDFCADHEHB,False +34,22.0,27.0,22.0,21.0,21.0,28.0,21.0,21.0,BABFBCCCCGCDCAGABAHFBAHCBDBDHDCDCDEFFHBHBCBCBEHDAGAEFBBEEEBEGAGHGDGCGEBFBDEAECCFCFGDGDGHBHAEFFFECCADHFFBGHDHEGAAEDEFEFCDCDCDEFCHADAEHFDFHBBEBEBFBFAFGFAAHGHGFFAFGGBABGHGBFBFDFHCHAHEGDA,False +35,24.0,23.0,21.0,17.0,28.0,15.0,20.0,21.0,EGHGAGEGCGDFFCEEEEEAHGEGFGFBCBGBDBACHCAGDDDDEDEHACGCECAFAFEFHCHCEFHDHEHBAEADBDBAFCHCEEEEHBHBECEAEAFGGGGCCHBHAAACABBEHFHBDFHHDHBGCAABEBGAGABBFADADEBBBBCDCACFGFHDCEHEBGADE,False +36,16.0,12.0,18.0,16.0,29.0,20.0,25.0,11.0,EEEBCFFDHDBBGHGHGEFDFACCCFCGAECECEAGFFFCFDAHAEEHGGGBGBGADDGDGEGCCBFEHEGEHACDGDGCCCFCEAFAEGEGBGFGBBBHFGDGFGAAHADADCEEEEDEAEFEAEBFFFHEGECEGEHECAFDDDB,False +37,1.0,6.0,2.0,11.0,2.0,11.0,4.0,7.0,DBFFFHHADFFEFBDBFBGDFFEBHBHFHGDGDGCCDDDDHDHF,True +38,11.0,12.0,15.0,5.0,3.0,15.0,15.0,13.0,HCCCCAEBGFCFBGAHHHHBAFGCGCGCGFGCAABFBABHBFBCAFHFAFGCDBGBGAGFCBBAADHDHDCGEGHGCGFFHFHDEFHFC,False +39,33.0,14.0,21.0,23.0,21.0,18.0,25.0,28.0,DHAHAHADGDAFAFGCHCHEHCHABACEDDDCGBHAEFFGCADADGBGCFFFGGHBAAFGGHFHFHECFCHCHBDEFGADDCGGGHEBEDEBEBEDFHCAAAACFGFBFBFADAEGBDCAGACACAFGEEECDDDDCGGGEEEEEGCADHHHHAHABAHGBBCACHEGGHDADADAHAHEHAH,False +40,9.0,21.0,8.0,6.0,13.0,11.0,9.0,15.0,HEBEGEGAGEBBBHFAFABCBCBEBCBEAFHGGGHEHCHBEDFFAFAHDBFBFBEBDFHHDHBHCHBHBDEFABGBCEDEBCACHHEAGBGF,False +41,13.0,18.0,18.0,16.0,8.0,20.0,16.0,13.0,AGDGBCDHFADAGFFFHHCFCFEBGBGFGFGCGCHHHHCGFBFGDHABCBCGDGECEFBFCACBDBDCFAFBDEDCFFBHGHBEBABDFDFDHDHACABDBAFAFDHEGACACBEECGCBDG,False +42,21.0,15.0,14.0,22.0,14.0,22.0,16.0,21.0,ACFDFDEDFDBAFDCDCDFFFFFACHCHGEDFCFEHADACEHEDEBAFAGGHGEDADFDHDHDHGADAGCCCFHBDBGBDEGEBHGFGHAHFBFBFEAABABACDDAHHGFGBGEGHFEABHBFEHHHGDFDCACABABGECHAH,False +43,17.0,19.0,23.0,19.0,19.0,21.0,20.0,22.0,GDGFGEDDDDDDFDFDFEHBHDGAECBHDEGHGEEDEBEDECGGAADAFAFADECFCDGDGFBHGCBHBACAGACFCGGGBGCHFHEHECECAHFHFGCGHBFCGCBCFEHEGEHBBAAABDHFBCCCCFFFHFCABFBHBHBEDAFEHBHACABECHCH,False +44,2.0,1.0,3.0,4.0,5.0,3.0,6.0,5.0,CHCHFGBGEHFDAGADEDEGGFGEDEHCH,True +45,17.0,20.0,26.0,20.0,18.0,24.0,15.0,12.0,BDEFBBBHHECFCFCBBFEDDADADGECEHEFCGCAFDCGCFFEDDGGHHHHHAFAFEFAFDFDFDEDFAACFCFCDCBBBCGCGDGDFCGCGBDCACBHDHEECBBEBECFCHGBGEGABCDCEFHFGACDFAFAECEBEBDACABAGFBA,False +46,5.0,7.0,11.0,5.0,5.0,3.0,8.0,10.0,CBDHFHCDCEGEHCHCHCHEGCGCGBBBBADAHGDGBACGEAHBHFGFCECAHD,False +47,5.0,4.0,4.0,5.0,0.0,1.0,5.0,3.0,ACABGBHBHBGDCACHCDAGFGAGDDD,True +48,21.0,22.0,13.0,24.0,16.0,18.0,24.0,19.0,DBDGAGBGFHFCABGFECEGBGHHEACDFDGCGBEBGDAFAHADADAHHBHBHAGABADEBFDGDBDGDGCFAFAFDDDDECGFEFEAHAHEHEHCBCDADGBFBFAEBCAHFHEDEGBBFDEHEBDHFGCGHGHGBGCDABCBDGHGBGDCEAFAF,False +49,5.0,12.0,11.0,8.0,8.0,7.0,11.0,9.0,FCFDGDHBEBECFBBHFCFCGDBCCCGCECECBDBGBEHDDBCAGAEHEDFDHGEGAHBHGAGAGFHBHBG,False +50,2.0,7.0,7.0,4.0,6.0,13.0,10.0,11.0,BBFEFEFHAHFDFGHEBABDFHBHEFGFGHEHGGGFDFEHCBGBFDFHFHCCGCGHGCCC,True +51,5.0,7.0,11.0,12.0,13.0,9.0,8.0,13.0,EFFBFDAAECCCHDHBHFEDBHBHDHDGGGGECDGHCFEFEDEDCDCDEDCCHFEFEGCGBHEHBHAHAGDFCEAEHB,False +52,15.0,6.0,11.0,6.0,11.0,16.0,3.0,8.0,BAEGCCEAHBFCCHFABEHEFDCHEBECACECEAFGFEFEFBFBFAFADADACACDFGFAFAFEFDAAHFDCAHHH,True +53,20.0,14.0,19.0,11.0,13.0,12.0,10.0,17.0,CHCECEHEGAHBFGHCHABCBCDCECEDAHACGCADDBBGFGFGFHAAACACFBEGGAGAEHCAAAFDFDCHBDBHGDFDHCBEFEBCBABHHHHDHCHDFEFABEBECAAAEACF,False +54,18.0,14.0,15.0,22.0,24.0,20.0,25.0,23.0,EGGCGCGDEDEBCBFDDDBFHDDGFBFEEEGDBDBEHFDFEACACADABEFDCECGGHBDCDBAGHGFBFECHCFEDEHEHAHEEAGCEEEEFGFHFAAGEEHHHHAHAHDEFGDGDBCGAGHFHFHAHAHDHDBFBFCEGGGGGGGHAADAGCDFFAHCB,False +55,3.0,4.0,2.0,5.0,2.0,5.0,3.0,1.0,EHAABABGBFDFGFGEDDFDCBCDF,True +56,9.0,9.0,8.0,11.0,11.0,13.0,8.0,11.0,ECFFFBCDEDAFEBEAFGFHFHFDEHEBEHEGBFEFHBABCCAGAGBGBDFHAHGHFCFDHDABADEDEDAHGGCDCHCD,False +57,10.0,13.0,10.0,15.0,7.0,9.0,16.0,11.0,HHCFEGEGEDFGABEHEADCHGHBDFDGDGHGCGBBDDCDCDBDBHCDEBAHACCFDGDFAFAFDDAGAGHGCGBGBHACBGBGAHEBFBF,False +58,15.0,15.0,14.0,21.0,27.0,24.0,20.0,28.0,FAFEFAADAGFBFACBCBHHCGFGFAFHCEGEGHHBDBFHFHBEGDGDAEEHEGCGDGHCDGDEHFHGCEEEGEGEDBDEEEEHHHHCHDAGFEBHFHAHFHFDDDCACHFBDDHDGDFDAGGEAEFBHEEEEBEHEFFCFCFDBHAFADCGCGFHDHEBABHB,False +59,11.0,16.0,18.0,17.0,22.0,31.0,15.0,17.0,FCECFCFCFBHCHBGBFHGEDADADEFEFHFDFDADEEADHGAEAECGDGCCFHFGFHFHFHFBFBFCEEEBEFFDEGGBHBEBHFCDDDDGHAFBFBFCACHCAFGCGHHEDCBFEFABCDCEGGGDAEBBBEDEFFFFECGHEHF,False +60,11.0,9.0,7.0,2.0,10.0,10.0,11.0,9.0,HGHCDCHCACBCEGEGEGEBBHCFGABEBFAEHHFBFAAGHGHFHABABCGEGFDEAAABFEFEFGFGA,False +61,23.0,23.0,21.0,24.0,24.0,17.0,27.0,24.0,EDGGCBCFCGCGCFCGCDCBAACHFHFHECACAGAHFHDBDEHAGADHGEGEBCAEAGDHAADDDDCEAEADBGFDBBBBDHDGDBBGCAAEHEGDGBGBFHCGCDBBBEFHFDAGHCDCHFHFGEHEGEGHGBEFACADAFCBGBGBFHDEDEDFBFEGHGHAHAEEEEGEDHAHACEFBHB,False +62,21.0,13.0,9.0,12.0,17.0,15.0,25.0,10.0,HFGFGBGEDEHGHAHFHGAAAFGHBFACGDBEBGAAFEGEFEFBGAHDEDECBCBFBEGAGAFCCBBDBAGABAGGGGGECDADAGAEFEDGACADDCDHDEAFHFHFGGGFGCABAEEEGE,False +63,6.0,6.0,3.0,12.0,7.0,8.0,6.0,13.0,FHEBEBHGHDAGHDCDEDEAFCFCHEEBAAFDDDFDHDAGBGFDHGHAHDHEHFHFHBDBG,False +64,6.0,15.0,15.0,8.0,14.0,13.0,8.0,8.0,CCEDEDBHHGDCBEFEFCCGCEAGFGEGECAHAHGBCFHACEBEBEGEFFFFBDBFBHBDDEDCBCBHBFGFHEAEBCBCFCBCAFD,False +65,6.0,4.0,3.0,4.0,6.0,8.0,5.0,5.0,CGCFEFAFAEEDEHCHBBDAAFAGHEHEBFDHDBAGFGFGF,False +66,17.0,8.0,15.0,6.0,16.0,16.0,11.0,12.0,AFGFGFGHGFECECECHAECCCFAHAFAEHGGCEBAFAEAEFGGHCBFAAEHFHFGBHEHGAFBFHCECEADFDBDBCACACAEAEBEDDACBDFHFHEGC,False +67,24.0,12.0,23.0,14.0,18.0,18.0,15.0,12.0,CCCFCFBHAEEDFDBAADAEAEABDBDGEHEGCCCACECHGEGEDECACFCFCHBFBAGAFFGHADBEBAAAAFAEECEDHDHECGGBHHCHDBGBABAGEFFGFAFADACADAGADCHFECGFGFHFCDCEGFCC,False +68,31.0,17.0,27.0,38.0,29.0,28.0,14.0,16.0,ACACBCFDGBHBDEGEAHDDEFEFEFEFDDHECEBDFDAEAEFECECGCHAHAHCBCDAHBDDDDEDEBEHGDDAFEFCFDDBCGAGACCECAADADABAFEDACGCAFAHDFDBDGCECBGBFFCHCGAEDFFFHADFDADGFAFADEDHABAGAGEHEFBFECEDEDCGEADADFDHBHDFDCBCFCDAFAECFCEHB,False +69,5.0,4.0,3.0,4.0,2.0,3.0,6.0,4.0,DAHAGAHAHAHFGCGEBDFDEDGGCFBBGBC,False +70,5.0,7.0,9.0,5.0,2.0,11.0,6.0,10.0,HAHDHDHBGBFCACDCHFBBHBHGDEACACEGFCDHBGFGFGFCCHBFFHFCFAF,True +71,11.0,10.0,6.0,19.0,14.0,23.0,11.0,9.0,FHFEADABECHFFDFDFHFEDECEFEFEFAFHDADAEADDCAGFGBBHGDGABDDFFFFDDDADEEGFGDABCDGGBHDHFGAGBHBHBEBEGFFFFFCCEDE,False +72,25.0,17.0,20.0,19.0,16.0,13.0,17.0,22.0,GDCDHGBEAEGDGEBDBDHDCDCBHDEAEHDCEFAAABCDCDABAGADADCFAFCGCACAFFBAHGCGCGEGEACHHECACECEHEGGFBDHFHAHAHGGDGFCECHFHFHCHFABABFDGABDEDABABHEACAFDHHGHAHBBBBEH,False +73,15.0,19.0,20.0,23.0,23.0,21.0,22.0,23.0,GFGFECGCEEGHFCBCFDDDHHGBGHGHDCDCFHAHCCCFHAADEBEHEDEDADCDCABEGEFDFHCHGGAHAHFCFCEADFFECGBDBDBDCCACADHGCGEGHFHGHGBFADEBEBEDGDBBACEEEHGBDBFFFFDGEGDGDGFBEHHHHAAEAEFBBBBEFH,False +74,3.0,11.0,6.0,11.0,10.0,12.0,5.0,7.0,ECHFHDHEFFHHDCFGEGFDBEBEFFFDBCBFEDCDCFEBBFADDBDBGBGBGBAHAHFDEDECE,True +75,21.0,13.0,22.0,19.0,30.0,19.0,18.0,19.0,HAHEEEFEDHDFDBHBGCCEEFEGGHGHCCCCCHGECEAHDBDBEFGHCACGBEFEHAFDFACAFEEEHABAGAFDGDADADAGBCBAEADAEFHCDCFGEHFHDEDCDFEFCCCEAEAEGGABFGEDBDBHBCCECEHEAEFGHGHDDAEAEHCFGFGFB,False +76,14.0,30.0,18.0,20.0,25.0,19.0,27.0,30.0,FCFBAEDEGEHEBGHGFEFCGDBDGGCGCGBEBHBHEAAAEECBCBCFHFCFDGAEHHFGGGGGHCHEHBABGBGHHDFAEBDBDBDBCCHAGGEGDGCCBCHFGFGHGHBHEFGHBFBCBHEHBBABCBHBCGEHEADDDBHFHAADEDBFHFEEGEDHDHDEDBDFEFEHCHAEGDHBFBA,False +77,25.0,17.0,30.0,29.0,22.0,22.0,23.0,24.0,CCHEAEHBBCBDADBDBDHGFEECBDFGFEAHDCGCDHHEHEHCGCFHGDGAGAGACACDDDFDFDGECCHDHCCEFAFEBAFGGHDCCGEDBDBDBCHCACDBAHCGCGAHAHAFFFHADCDCFCFHHCDCAEAGAGAGABFHGEGBGDFHEBEFCFAGBEEAABAGDGDFDFEABHCDEDEHEHEFCFCD,False +78,9.0,16.0,9.0,5.0,4.0,15.0,4.0,5.0,BCEADCBBBBABABCCEHFBDHFAAGAGHCFCBCBFDFAGAGBFBDBABFFFFFCEHEBDHFFFBFC,True +79,19.0,17.0,10.0,29.0,13.0,8.0,14.0,14.0,DEDEAEAEDDDDDDDHDGEBEFADAGBFFHDGFBBBBGBABFCHGDFDEACBBBAHADAHCGCAHDHEHABAGCGCGEDAGBDAACAHDBCBGBGBEDDDDDADGDFDHHFDAHAEEEHCDCHG,False +80,9.0,11.0,7.0,9.0,14.0,3.0,11.0,16.0,HEHEACBHBHAGEBEAEBHBHBDEDCFABCGAEABHEHDADABABGGGDGHECEHHDGDHHCHCDGFFHCBEDEGEGHGE,False +81,4.0,9.0,4.0,9.0,3.0,6.0,6.0,5.0,BGBACACHDGDFDFBFEAHFBDDEDEGHGHBBBFBADHDGCGDBFC,False +82,11.0,21.0,22.0,24.0,26.0,28.0,21.0,21.0,EDGDCDCFGEDEFFFFGEEEDEDEDADACHCEBAFAFCHEDBFEDHDCCAHGFDFDGAGEFECEDBHCECDGGGGGBGFGBHCGDGFFDCAGDBCEHEGBBBBHFHADFHCHCHCACHCBBEFAGBGBEBFFFHFBCEDFFEFHDHFHFCCECBHBDBDEDEHBHEHFBFEGAG,False +83,2.0,4.0,1.0,3.0,2.0,4.0,2.0,1.0,CBFHFBBDGDFDFEGEABA,True +84,18.0,13.0,21.0,13.0,16.0,19.0,15.0,8.0,CBCEEADAFGDCFHFHDHFACACEDGACFGGGCBABDCCCCCCBABABABDBDFACGCGCFCAGEFEFBDBCFEFEAGFDBEFEHEHBAEADAFAFGEGECAHFEDGDHHCAEDEFCFGGGBF,False +85,14.0,12.0,10.0,10.0,16.0,19.0,9.0,12.0,FGBGHDEEEGBFAEAEDHGHGFEDEFEGEDEFEFCBAHCHCFBFDGECFFFGAECBBBDGFAFACACBEDABEBFHFHFHAHAHFEDCDCFCAAHBHADAFB,False +86,14.0,13.0,10.0,16.0,18.0,7.0,14.0,15.0,GGGGHADGCGCEEEDEDBAAGBCDAEABAGAFFFDBEFEAHAHBDBDBDBGHAACDHHGHGHDHEFBCDCHCHDEEBEBDADABEFECCGHGHFHDGEEEADBEEHC,False +87,9.0,13.0,17.0,12.0,12.0,23.0,13.0,12.0,EHCHBDDCECFCFCFABABGBFDFDCDHBGDHDGBGCGCGCFCDHEHEFCHGEAFBFBFDFHCEBAFEDEDFFGHCFGBGFGCDCEBGFHFAFBEEEBGFFCFAACAHAHF,False +88,6.0,3.0,0.0,1.0,3.0,3.0,5.0,4.0,GBGAGBHAGAGFEBEFEHHAHAFAD,True +89,11.0,11.0,12.0,15.0,16.0,12.0,7.0,10.0,BHBHDDADCGCAEHHDCEAFAFBFCDEDECBGFCECHAHGCAEDDBDEAFAFHFDCHEBEGEGADBDBHEHDFGFGFDECECECAAEBEBDBFF,False +90,18.0,21.0,18.0,8.0,15.0,18.0,18.0,10.0,BCBDGCBCHGHAAFAFEFAFDFHGGGCCECEHBHFCADAFAFEGBAAAGAFBEBEBEGCBHBFADAECDGHGBGECCBCBABHFFDCEFEHGBGBGBEFGABCBFBDBEEAHACGCGEGFCFCFDA,False +91,21.0,22.0,23.0,29.0,25.0,21.0,20.0,16.0,EDECECBBDBGGGDHDFCFDFAFGBACHDHDADFDHBEAACACACEDECEDGDGEGEGEDEAFCFEGGBEBGFGEDECGFAFAFGHEDFHFCFBFBDEDFDGBHEADHDCCFBABABACGEHAHFHCEGEGHBHDACADFCCHBHDCDCFBHAGDBABEBFBGCDBEBCDDADAEEC,False +92,22.0,26.0,23.0,24.0,20.0,30.0,22.0,18.0,ADAFEGHDHFFFFDFECADDDFHBHDCBFAHCHCACHEGFBFBCDHEFEGABAFAEBGBFFFBFCFGBHBEBAACAHAEDEDEGCDCDCDCGHACFCFHFHGCFCEHEHCGCDCEFGDGBGBGEGBABGBGCCABBBDBAFGDABFBFEFEDADBFEFDBHGHDFEFECBAGGCGADDDGBHAEA,False +93,2.0,2.0,1.0,3.0,0.0,2.0,1.0,2.0,DBDCDGFFAHAHB,True +94,18.0,8.0,12.0,13.0,10.0,9.0,12.0,11.0,HHFAEHCHCHCDDAFACACACGGFEFGCHDEEGCGCGFDDADGDFDEBHCDABGBABDGAGEEBAFABGBDAHAFAFADADEHHCHCBGEAEA,False +95,4.0,5.0,6.0,3.0,5.0,4.0,4.0,3.0,AHBFEADADAGFHFGGCBCBCBCFCEHEBDCEEG,False +96,6.0,10.0,15.0,4.0,14.0,9.0,14.0,11.0,ECECEGHGHEHGDACGHHHFGFGCCCGFEEHEAAACCHCFCFEGEDHFHFDFGEABBBBEBHGCGBEBGCACBEBEGCCDBFG,False +97,3.0,4.0,3.0,4.0,3.0,2.0,2.0,6.0,BGHFHDHDCDBDECAHAHAEGBFBHCE,False +98,14.0,9.0,9.0,12.0,16.0,15.0,11.0,5.0,BGGACFEGEGEAFGFGFGFAADADACBCFDADGEBHBFDFGBBDCGAFAEEFECHCDCBFEAEAEADADCEBDDHDBGEFCHEHEFEAEFF,False +99,24.0,22.0,16.0,19.0,18.0,22.0,22.0,17.0,BABDFDEDEDEHAACABAEAFFGBHFGAHDBCAGADEDCHBBGEGAGAGAGAGFGABEDEDEFCBABDBECECEAGFGEGBGACBFEHEHAHAFBFBCHEFGDADAEEBCBHHHFHFBAGGGFFFFGHDCCHAHBCBCHFGDBCCAFBDGGFDHDFDFDC,False +100,10.0,7.0,6.0,7.0,6.0,11.0,8.0,15.0,GGHGHGFEFDCHAHFHEHEBACCBCHFHFBCBEBFFEFHAHGHDAGADAEGBGHHBAAADCFHFDADFDH,False +101,21.0,23.0,9.0,23.0,25.0,21.0,22.0,21.0,EEEEEACAHEHDDADHFBFBAHGHGBGDGFECGBBBBFBFEFHFGFGFAEHDHAHAHBHGHFBBHGGGGGEHDDDDHEAFBHHDEFEHEDDGBCDCHBGDDFFCAHADEDEGEGEAABBEBDFGEBABCDFEACFDADAGAGEGBAFABHBDGDCEEEAFAFBFC,False +102,1.0,8.0,5.0,3.0,5.0,5.0,6.0,8.0,HCGCHDEBGFEFECBBBFBFGHGHGDGBAHCFCHHHEDEBB,False +103,29.0,22.0,27.0,17.0,23.0,16.0,31.0,26.0,GGHCFGEBEDGCCDEBFFFEFHGCDCBCBCECFCHCHCHGHCEGAGCECABHEEEBEBEGAGBBBABABFBHBHDHGGDADCCFAFEDECEABGBFAFHDAGHGHADEFGBDCHHDEDCHGABABFGDEAAAEBGAAEGGGGFGHAHDBDCCHGHBDGEGHGEAEACCHCACAHGHGHAHDCACAFAGAFA,False +104,7.0,6.0,18.0,7.0,11.0,12.0,24.0,18.0,GDGEHCGGGEFECEBECGCGHGCFHFHFHCDFDFGACHHHGBGHACDCGAGADBCAHECACGHGHBBCFGHEDEFEHGHBHGGCGCGCHCEGGDGEAFFHFCF,True +105,16.0,23.0,21.0,18.0,22.0,17.0,10.0,18.0,ACEGEHEHAFACDCDCHFBFBGBHDFFFCAGHBBBHBHFABABABAHEGCAEEEFGBGBADGEBCDEHEBCFCHBHEFEBDDDDDDDGFEDEFEHAHBCACACBDBDHDCBCEDEHEGCCFEEEDHHAABCFCHAECBCBFFCFG,False +106,9.0,10.0,12.0,6.0,8.0,7.0,13.0,7.0,FABABHCEGEGBGBGCCCHCAAABGEGDGFGFAFCBCGCEHDCCAGHDHCAEHFBFAGBGBGHFDCDBEEDE,False +107,17.0,15.0,17.0,17.0,16.0,26.0,15.0,17.0,EFBHGEAFDGCGFGFGDEEAEGBDEFBGGFAHHCAFAFHBHBDGDGEGEGDFFFDFHHHAHBCDADBCBFGFCBCBGBFEHADAHCECFCECHBFFFFCDEDEDCDEFEFCHHHCACAEBCGAAAAHADAFHFBDBCFDF,False +108,20.0,24.0,27.0,23.0,19.0,28.0,19.0,18.0,AFAEGFGFGAHFCFEHEGDBBBEBEBEBCDDDHDFGFDCDCECFAFAHAGBBBEBFDEBCBAHGFGAGABDBEAGFCCCBEBHCDBDFDFBBHCHGGCDCDFHEHECGCFFFADAHHHDCDAEEBFGAEHCDDGACACACFCBEFFHAGCCCCEFEFCABDBFFFGHCHDHDFDGBGA,False +109,9.0,16.0,17.0,17.0,16.0,16.0,12.0,24.0,EGDDDAHBEAEABDCEBFFHFHFHCDGHAHCCFDFDFDFBBEBFBFEHGHGDCFCGHGHGCBCEDHBCDHFHFBFGDGACCCGAEBHBABCHHEHBDDEHEDEDEGEAHDHCECFCFCBHAHEGBHH,False +110,5.0,7.0,7.0,3.0,11.0,14.0,10.0,14.0,AHEHDHGFEFGCHFGFBBCAEFEFEFECEHFHBHAHFCBGFABHBEDEGCGFDFACGCGBFEFGHHHHEHG,True +111,20.0,16.0,22.0,22.0,11.0,17.0,13.0,10.0,ACAFFCDCDCACBFAFGDAACDCDEDEFFCBHDGDCDGDEABFEAADDCAHHDHEGACEFBCBCACACABBHDHDHEHCAAFAFCDDEDFDFBFCFBFDEDFFGGAGCCBEBCBHBAGGGGGEGACBHBDB,False +112,26.0,22.0,28.0,29.0,20.0,26.0,21.0,19.0,GCDCBAEHEHGGFABGFFFFBDBDBHCHCHAAADGFCBCDCFFFDCHCECEDEAFBFEFEGGCDCDAEAECFCEEACCBABGFDABADAFHBHFEFEAHAEADFCFHHBHAHAGGDHCCCDHBCADABHBDCGHGAGAGDDDFCAGBCBDBCFCFEHEDEBGGFGFDBCGAGDCDEDGDBDBEFEHAFADD,False +113,4.0,0.0,3.0,3.0,1.0,0.0,3.0,3.0,HAHADDGDHAGAECCCG,True +114,15.0,25.0,14.0,19.0,17.0,16.0,17.0,18.0,GDGCHHEBEBHBEFAFEFBFHFBGHEFEFEBAAAGFGDDFDFDFDBDBDBABABDHCBGDHCEBBGBCBEBAGHCHBEBGHEHEHEACACACACBBGGFGHCHDGBCDGEFDFDBEHECDGBCEHAHDHACFGADFDBAGD,False +115,4.0,7.0,3.0,5.0,3.0,0.0,6.0,6.0,HGHBHBDBABACEGDGEAHBHADGEGCHCBDGDB,True +116,18.0,19.0,11.0,27.0,26.0,22.0,18.0,28.0,FDFEHEBGBGBCFDFDFBEGFABHCHEEFAFAFAFBDHEHEABBDCHCDDGEHEADAFAFBHHCHBFBEDHGHGBFDFGECHHABDEGECEDADEHEDCAHAGEBABCDCDAHEDEDEDFFFFFBFHGAFEGEGDHDHGHGHGEDHDGEGDAHABBHHDHBCDADHEGE,False +117,9.0,10.0,11.0,5.0,12.0,11.0,5.0,12.0,HFBFCFBAAEABGHCHAFABBBBCCCHCECECHCGEHEHEHFHAHCEDDFDCEEBFFFFGEBEAFAHDGBGDEHA,False +118,1.0,8.0,6.0,3.0,6.0,11.0,9.0,8.0,BEBFGFGFBFBGBCDFEHBHAGEFHGDEFBFHHCGCDBGFGFGHCHFHCECE,True +119,16.0,21.0,23.0,14.0,8.0,20.0,24.0,21.0,EEGFBBADAFCBHFACCCFCFEFDGAFHFDABHBCGHHHBHGHCHEGCAABBGDHBHBGFGCGCGCGHFEFCFGABAGGCGAGACFCBCBHBFCFADHDHGHGFDEBEGCGCDBHBEAACHDDFDCDCFBFBGGGGCBHDHDHFABA,False +120,23.0,16.0,16.0,25.0,12.0,20.0,24.0,21.0,DFHFBBDGFFEDCHEEGGGEEADAGAGDBDAABFDFCGDGAABABABABACAGGHDHFACECBDDFDHGHGHBCBCAGFGBGCFFFDFDCGHGDEEHBCDCBHBCFGFDFDHAGCHHHHHGAFADDHEHEAGAGAGHCBAEAEDCDADCFGFDHDHF,False +121,19.0,17.0,15.0,20.0,28.0,24.0,23.0,17.0,DCDFFGAAFFFBGAGDGCACHEHDADADFEHEGGFFEFAABBHGGGFHEHACACBEEEHBAGAGFDFEBEGEBECECDCHBHGDGBEFEAEAEAECCGCEHBHCFFGBDBDCDAEEEAEFFFBHAHGEDEBGFGFGHGBGBDFDCDHEHDDDEBAFDFEGCFH,False +122,24.0,21.0,31.0,19.0,20.0,33.0,21.0,17.0,CBDGEGCBFGFHFHFEFBDAECCCBCBGHDCCCAFADHDHDEDACBDBGAHABFDGEGCHEECECDAFBGBGBFFFFHEAECHFHFHGEEBCFCFDGEGFFFFGCDCGBGBGFFBFBFAAAAAFGBAFABECAGEGBGFHFCADDCECHFAFADAHFHEDEHCFBACAEAEFDCCCCCBCHDADCG,False +123,23.0,22.0,33.0,26.0,18.0,14.0,26.0,19.0,DGDGCACABHFCADADGHGEEHGACAHAGACEDEDEDGDFCHDECFCBCGHGECHCHBEEDEDEDEDCBGBGBABCBCBHAGDGECAGDCCCFCDCFHFDABECGBGFHBBFBEBEBACEDBHHCCGCDAGGGFCCCGDDFCBCBGBGHGHGCBADHFFAHDGAAAAABAFDHDHCFCEAD,False +124,14.0,14.0,13.0,14.0,9.0,17.0,19.0,18.0,DCBFBFAFAHBHGFBABECACGGBGCGCFAFHHDGDGEBDADFFHHHHDAABHFFEGAGFDBGHGAGBGHFHFGCHCDGEGEFCGDGDCDCDCECBFAFCFHAHEBEGHBEBHHADAD,False +125,22.0,17.0,18.0,14.0,19.0,23.0,19.0,20.0,AFFEGCACEHAHBHFHECADBDEDHDHDACHCBCBHFDDAGHGHCECEAEAHBHGGCEAFAFBDGFFFFBAGAFAFHHCGDFFAEBBABADADBCGHHHGACACFCFDFBCGHGEGEGBGBCBEEAFHEBBGGECEFECEHGGEAFDFDFAF,False +126,2.0,2.0,5.0,1.0,2.0,0.0,0.0,0.0,CBABCCCECEAD,True +127,9.0,13.0,13.0,20.0,8.0,15.0,15.0,18.0,GGEFDFEHDHDHBAGABBBFFHFCFHGHGHGHGDADHDEDFCEDAGAGCBDFDHDHCBCDFDBHFHGHFBCGDDDDDABGHDHCHAAECFBDBEBCBCEGECCFFHCGAGF,False +128,26.0,16.0,20.0,13.0,15.0,14.0,8.0,14.0,AFAFGCBFDCCGCBCACACAFACECBAFAFDBBABABHECBGAHADEDCBADABABAHEHCHCHGECDHDHBHBAEDEAEAHBGFAHBBCACACAFEDCAHHEADGEGECEFFFCGHDFDEAEFFD,False +129,3.0,2.0,3.0,1.0,2.0,1.0,0.0,1.0,AHABFBEAECCDC,True +130,3.0,10.0,5.0,11.0,10.0,4.0,3.0,9.0,DBGBHBAEDEBCCEBAAFHHDHDCBEDHBHBHBDECECEDDDFDGDFBEGEHEHF,True +131,18.0,19.0,23.0,22.0,20.0,20.0,15.0,23.0,FGBCAABCBCDCDCBBAAADCEGHAFDFEBHBHAHGDAEAEAHGECHCDDFDBEBHHHDBCFCABFHHHABFHHEGEHBAFAFCDCHGEGEFBFEFEDEHCHCHDHDGFAFEBEBGBGFCDCAEDEGFFFHFBEAGACFDDDDHDCCCCDCDGEGBGCEH,False +132,27.0,13.0,16.0,13.0,20.0,12.0,27.0,15.0,HAACDHGHEBFFCDAGADAEABAGHFHDHCCAEHFHBGBECGGGGAGABACDEDCACACFGFGFHBBEBHGGGDABGGGEDECEAEAEAFCEGBBBAGAEAEABHEAEGGGCEHFHDGAGEDEDFDHDEAAGAHAFFGCCCCG,False +133,5.0,7.0,9.0,1.0,6.0,7.0,8.0,7.0,BGCFEBHHHHACABFBFHFCFGGGCCECGCGCHAEBBHFGCGDAEAEBEF,False +134,14.0,15.0,11.0,16.0,21.0,17.0,16.0,20.0,HBHDHFHDDEFEGEFEBGDFDFBBHBAGEGCFHBHDADHHFAFAHECEFADECEDDDBDBDACBEAFHFHGEGCGDECECBAGACHBHGHFHFHGEGFFHEHCHCEGEGEAEGDGEABDBABFFGECABA,False +135,8.0,3.0,1.0,2.0,4.0,6.0,9.0,3.0,GFGEGHGFEFGCGDBAHAFDEAEGBGBAAAFAGAHF,True +136,14.0,29.0,20.0,23.0,25.0,22.0,18.0,18.0,DGDCEBGFHDBFBECHFEFBDEDCACGCGHEFEFEFAFGGGDCFGFHFHAHADEBBCBCEEEFEBABCBEBACACBHHCFCEAEAGBGDCDBDEDGBACECBHEHBDGDFDGCGAFEFDBHBEBEAHGFCFBFBHEDFDGDBBBBACDBDHGBEAEGFCHBHEHDHDFD,False +137,3.0,5.0,1.0,6.0,8.0,6.0,3.0,5.0,FDFDBBBEDEHEHEFEACFFGDHDFGBHAEAEBEGDH,True +138,17.0,19.0,28.0,23.0,19.0,29.0,14.0,27.0,EEHFCDHDHBAADFECECFFFCDGBAHAHFHBCDDFDGDADBCAAHABAEGFHFHDHDEGCGHGHCFDFEFGBHAHBCBABEEECDCDEHFHFBABHCCCACHEACHDGDFHFHBHFGDGDGDFBCDCGABFFDFECHCFFFHFCDGEFCACHCHCHEGACFCFBFEEECEBBBBD,False +139,18.0,10.0,15.0,7.0,19.0,9.0,15.0,15.0,BCDGAGEBBAAFCBEFDFHCAAHABFEADAHGCCCACEDEDEDEDEHCBCFEHCHEACACHGGGGBGEGFGFEHECGFEAHGHEHEHEHACAFBGGABABHGHEAEAC,False +140,12.0,11.0,10.0,15.0,15.0,9.0,10.0,21.0,GGDEDEDHDABGBDCAFADADEEFHFEEBBAHECFCAHGHGHEBBCBABAFHHHHAFADHECEGGBGECECHBHECFCDDDEEHHHHHDHDHDHFACGDABFG,False +141,6.0,7.0,16.0,10.0,19.0,4.0,7.0,3.0,GAGEECEDBGBGFCFCHCFBDBDECEAEDBDCHBEEFAHAEAEGCBCEADDDDEGCCEEEECCCECDCGCEE,True +142,17.0,14.0,17.0,18.0,21.0,18.0,15.0,9.0,BADAGADHDGDGFHFAFDFGEEDDDADCCCGGECCCGEHAHAHEEEEAECFCDHDFABABFBGBCACEFFDADAEEHBHFDFCBEBGHGCFCDAGFDBEFFGFGEGCBAEDEBCBAACDCBEBEFEFEG,False +143,1.0,3.0,4.0,4.0,2.0,3.0,3.0,3.0,DHDCCGCGAGHBBFEFCFDHDEB,False +144,3.0,1.0,7.0,1.0,1.0,3.0,7.0,2.0,CDCFHGGFBCCCCGAGAGAEHFGCG,True +145,3.0,5.0,7.0,4.0,3.0,11.0,6.0,3.0,DHGEGBGBGCCFDFAFHCBEBEBDFCFCFGFCCAHFFFDGAF,True +146,4.0,13.0,6.0,8.0,6.0,15.0,9.0,3.0,FABGBGFGFDBBBCGEEEEBFGCBFBDBCFDFGFGFAFECCDDADAFBDGHGBFBFHFEFHCBD,True +147,16.0,16.0,22.0,23.0,21.0,20.0,35.0,29.0,FBFEECGAGFGFGHDHDFAGEGEHFHFHFEGHGCEEAHDGDEHEGEFHFCFHGHBECDBDBHHGGGGGGCBHAHACAHAGEBDCEAGGHGHGEGEBDAHHHCHADGCFBFHGBGCHDFDFDGHCBCHHAGBEBDACHCFFGGGDADEEAGCEDEDCCCGDFDBDGFBFBGBDEACACDCDCH,False +148,16.0,20.0,20.0,23.0,21.0,16.0,31.0,18.0,EBEHGGGHCACFDDDDDAFCHEGCACFCFDFAGADEGGGAGEECEGEGEGAFFDCBHBHDHEGCDCGBGBGCCCCCBDGEBCGFHCHGHAHBBCEGEGEBFBGAHABDBDAGAGFGBEEEFEDGDAFCHBABGBADADEGFFDHDCFGGDHBFBDEDEDGHHHBH,False +149,3.0,7.0,4.0,6.0,10.0,7.0,3.0,5.0,EBEHEBEDCFCBBADCHFHFGBGBDEEEECHBDADADEFFFGFHE,False +150,6.0,2.0,7.0,6.0,2.0,3.0,8.0,0.0,DDDCGCADFDFGGGACACAGBECGGDGABACFCE,True +151,5.0,2.0,2.0,0.0,5.0,4.0,2.0,3.0,GAGAFBFEFECEFHABAEHEACH,True +152,14.0,12.0,9.0,7.0,12.0,11.0,10.0,17.0,FDHDFEHDHCFCBCDGHGCFFFBFHACCHBGAGAHEHEBEAADAHBGBFBFBABABAHAHEEAFHEHBHEHABGGECDCECEAGDHAHEFGG,False +153,19.0,24.0,27.0,19.0,23.0,23.0,26.0,24.0,CDCGGGFAAGACHFHDHDHBBCCHCGFAHABGBEDHBGBGBABADECFFFFAGGCHDDGDGCGHGHGDCFHDHAFEFEFEHDCCGGBGEGAAFCEEDFDFGBEAFHFCGEBCBHBFBDCDGBCBEHADABCHCHEHEHBHDGFGAGEGBBEBHDEEHAHAEAECCFFFCCCECECEFBFBDECBA,False +154,13.0,10.0,11.0,9.0,11.0,8.0,12.0,4.0,GEAEAFAGADADAEFCGCGCGCAFBFBEECEGADADACBGBCHHBFEECACBEHEFBFBDADEDBCGGGBDFHCAGGD,False +155,23.0,15.0,20.0,21.0,22.0,13.0,16.0,23.0,FEBEBEBFDHDHCCDDBCBEGFDFGBHCHFDAEBCBFHAHGHDADCBGDHDHDFCAHHHDBCEHDFDAAECDCDCBCAFEEEEEAEAGACHCEGEAEGGGGAEABAFAFHHGEAAACHFHAHFGEAEDEDEDADHDBCGAGACBCHHBGGCHC,False +156,1.0,2.0,8.0,2.0,1.0,1.0,0.0,3.0,CCCCCHCHBACDCBHEDF,True +157,11.0,6.0,5.0,14.0,10.0,10.0,2.0,6.0,EFAHAHFBFGGABADFCBEDEDADAHAFAHBFEDEDCDEDEDEDFFCBEDFDFBACDDAEHCHA,True +158,15.0,22.0,16.0,16.0,9.0,21.0,17.0,9.0,CFCFCAEBDGDHBBFBHCAAGFFFAGGGGFGHCHDBDBECECECFHBBCBAFHFDFBCACHCAAAEFDBDBCFGAADADAGGBBBGCGBGCFBEEGHGFGFDFDFABABDFHFDBDCEFEBGDDB,False +159,3.0,6.0,10.0,6.0,2.0,3.0,4.0,5.0,GGGFDFDBCBHBHBCCHCBCEHHFCACDCBEDDDACGCA,True +160,7.0,12.0,7.0,6.0,6.0,8.0,8.0,5.0,AEFEFEBCBADCEFHHCHGBBECAABFBFBDBGBHECGDADADGBGAHFFCFCGDGBGB,False +161,25.0,18.0,13.0,27.0,15.0,21.0,17.0,28.0,HFHGDDBDFDGHGADHGFBHGCFDAECCHHEFEFEDDBEBAHAHFHFBFHAHDFDFAEDFBBCEHADGFGAHDGDGDGDFCBCEAEBCBHDHDHAHAEADHHFHFHEGBHEDABABACDCAEFDDGFGAGABAHDHDGDGDBHBFAABAGAECECHCACBFAFH,False +162,18.0,23.0,16.0,12.0,17.0,23.0,24.0,31.0,AEABABCBCHCHCFFFBHHEGBABDDDDDHHFHEECFCFCBEDDBHBHBCGHDFAFHCHFGCHHHHHHHCFGFGEHDBAAEGGHEBBHGDAHFHBHBECGFAFBGCAHEHGBBFBDCHHGEAEHGFFFADGEGBGBGCGFFCHGEGEGAGAFABABAEAEGFGF,False +163,24.0,23.0,17.0,16.0,25.0,31.0,34.0,30.0,FHFHFEFGFBAEHHHDHDHFGGDGDGFGDHACAFGDGDECECHCGAHAHBBBBBFFFCGBGEFFHFEAECGGBBAGABABAFHFHECGDECFCHDBACDEHBFBHBFEFDDGCHBHGHGHBEAGFGCEHFBAHACEHEACFCFEAEGEGAGACFEAEBGGFDBDBGEGECEAHHHAGBGHAFDFAFDFGBGHGFGAGHEE,False +164,16.0,17.0,19.0,27.0,19.0,29.0,35.0,19.0,GDGBCCGCAFBFGFDHGHBFAFGFGDDECECDGDCDFHFGFCFHFEABACFHFBFHEEECEDFDEDGGGDGCCBBDBFBABFBGDEDEGBHBDDDGGGGCFHFGFGFHFEABBDCDCHCGGGDGFGEDADHDECEAGAFAHEHADAFFGGGCABEGHCAEFGFGAGDDHDHBCEHGAEHFH,False +165,10.0,7.0,7.0,12.0,6.0,6.0,5.0,8.0,DGFFDCDCDAEGDBDCEBGACECHCECDBABDEAHDHGAAHHHFHFBFBGBHDADADAFAE,False +166,17.0,18.0,17.0,16.0,20.0,19.0,17.0,15.0,CACAHAFBDAAADADHBGFAFDGDGDGHHFHFGFGFHHCAAEBFBFCFAHEBABEEGEGEGEBAHGDCDGEBCHEGDGCFCEEFECBCFHBHBHBADDFBFBGDCBCFFEGCAEGEFBACDCECECFDDADEEEGHBHB,False +167,15.0,4.0,11.0,15.0,21.0,12.0,17.0,17.0,HHAHDEDGHFHEHCHGFGFCECEGEACFGDGDCDCHADCEHEGGAEEBEBFHHHCHCHCFDAHAGDGFGDDHEEGCAEDEABAEGEGHGDDFAAEFGAGAEAFAFDFEEBED,False +168,8.0,4.0,9.0,2.0,9.0,7.0,3.0,7.0,ECECBCHFHCGFGFEEEHEHECAAHAFFBAEAFHBGAEAHDBDACCCFC,True +169,16.0,14.0,9.0,11.0,11.0,11.0,12.0,11.0,DFDFDGAGAGAGFGHHACBHBHGFFDFGBCEAHBDAEADACCECAAEABBHEAEAEDEDCABABCBGGGGFFACHHBDBFFDFEEGBCDHEHBHB,False +170,4.0,2.0,1.0,1.0,6.0,4.0,5.0,2.0,GGDBEEEEBEAGFFCFGFHAHAEAG,True +171,28.0,14.0,20.0,10.0,8.0,25.0,20.0,36.0,HCHCDCGCDAGAGHGBABAFAFCFAFDFGFGEGHFEFHBHGFGCHEHABFGFHHHCFDACHEFBHHHCHAHGBAADCHBHBFAAAHHHFEGCGDAHAGFBFAADAEACFFGAEAGABFCHCBFDEAGAHBHBAAHHHFHFHCCACGHGHDHDHCHCFCBGF,True +172,3.0,11.0,4.0,4.0,5.0,7.0,5.0,5.0,BBBEBHHCCFEFGFGHGBBBGBDFAFACEHFGFHDBDBABCDEE,False +173,8.0,13.0,6.0,15.0,4.0,10.0,15.0,7.0,ACDCGBGFFFGEGBGFHBHDADHDFGBGBGHCDAGGGCHDHGADDDDDDEBBHBFBFGFAEADGCCBDBDGAAEFBFB,True +174,10.0,11.0,8.0,10.0,13.0,7.0,14.0,11.0,GCGCGCGFGEBCAAEEHEAEHDHDGAADADADFBEDECHCGGGHGEEHBHAHABFBEBHFADGDHEECHBBFBGEGBGDCFBFD,False +175,23.0,12.0,12.0,24.0,26.0,34.0,26.0,24.0,CDBFHAHBGAAFEGHAFGCAFGFGBGBEBEAFGDGDFDADCFGEGBFCHABFCGADHFFEFHFEFEFEDHFGCGEGEAABEGAGHGEAFAFAFCFAEDEDEDHDHDHFFFGFHACEFHHHDHDAGFDFGEGBGDHDBABAFEEEHEBGFGEEAEAHHFDDDGHGHDFCFCACHDDEDEFHC,False +176,18.0,8.0,20.0,16.0,15.0,17.0,11.0,11.0,FCFBECGAFAFABAEEEEDCDAECEDGAAADFHBDBECEHEABABCDCHBGEHAHAGAECHHHADCCCCFCDCDAGCFFEEAFAFGDDFHFHFHDBGGDGDADFGCECFCGCDCFF,False +177,13.0,12.0,13.0,12.0,6.0,11.0,5.0,9.0,DABFHGHCBDBDCFFGABAFEBACAHECGDFFHFHFDFEFCHCBCBAECGCGCHEAEADDDBDADAHHBACABACDCDBFB,False +178,7.0,14.0,10.0,12.0,19.0,22.0,10.0,9.0,FDECFBFDFDFHFGCEDEDEFHGBACCEGGAEBEGABFDFDFCHGHFFEDBFBFBFEGEHADAEFEFEFEABCFHDHDAECFCGBFBGBFBEECECDBEBHGH,False +179,2.0,2.0,2.0,1.0,5.0,4.0,1.0,6.0,HGFEHEHEFEDAFHFEABBCHCH,True +180,2.0,5.0,1.0,3.0,3.0,4.0,0.0,0.0,FAADBBBBEBEFEFDDCF,True +181,6.0,7.0,5.0,2.0,1.0,4.0,3.0,6.0,BHBDBAAGAHCHFHACAHEHBBBFCFCACGGDBF,True +182,2.0,3.0,10.0,6.0,8.0,6.0,4.0,4.0,BCBCECEAEDEDHCCCCHEHEGDGCFFFAHGBFFFECDDECGD,True +183,27.0,20.0,35.0,20.0,19.0,18.0,17.0,19.0,CHCHCFCBDEHBHEHCCCCBDBAADFFECCGCAEAFAHCFGDGAGACABFEAHCBDBDBDACGDEDEDEHEBGDGDCAGABEBEAECEGAGFGCABFGFCEAEAGACFCDCFFGFEHBDBDECACAFHBHCHBHBFAHDBCADHEHACAGDDDGCEBFBFCCCCGAHCFCACAHH,False +184,21.0,29.0,29.0,14.0,13.0,23.0,22.0,20.0,HBBEFAHAHDHCHCGCBCAFABDDHDFAAADBDBEBCBCBEACGCGFFBFAFHGHFCFEHCHDADFCFCEDBGBCCFCFGFHCHCACBEAFBECFCDAGGCGFGHGFGEGACCDCBHBACGFGFHFBFGEGBCHCBCDEBBCHGGBGBDDFAAAEBEBABHBABHGEGBHA,False +185,16.0,21.0,7.0,5.0,16.0,12.0,3.0,15.0,BBBHGHBACDBEAAAFDHEHAGAGAEEEHHCAEAFBBABFBCECAFAFBFHFEDABBBFBEBEBEBACHFHFHDHBFEAEBHAFCHEDECEHBHB,True +186,26.0,34.0,20.0,22.0,24.0,21.0,26.0,17.0,HFACACHCBBBBHBGBEHFHFEAHAEAEFDBHECAHAHDDBGEDCBEGGFGECAAADBEBGCGCFCFCFBFBFBAGCBBABEHGCGCGFGBBCHCEDAHBCEAEHDBAHGGDDDDHEADDDDDFFGBGAGBGBEBABDBDGDGBFBDBDBDHEFEFCFEAAFGEBCGEGBFFGCGAABAGCHEEEAFAEA,False +187,3.0,5.0,0.0,1.0,1.0,2.0,2.0,4.0,DEBGHGAFBFHHBHBABA,True +188,8.0,11.0,10.0,11.0,8.0,19.0,14.0,12.0,HGFBFHFBFGGAHDDEBAHFHFHFCEGFGFGFGBGEGBCEEAFDBBBHFHDBDBGACHCHFGCGFGCGFBCDCDFFAEAHAEFDFDHAECDCD,False +189,24.0,32.0,23.0,32.0,21.0,21.0,20.0,22.0,BBBABAEECDDDEDEHEBECEDEDHHHFHFDFHCDAHAHDBGBGEGFGFGFGFBAGCGDFBFHDHBBCHGHGFAEBEDCAAGFDDADADBDCFGHBABDHECBDBAAHADAGCDCBABABGBHDCGCBCGFEBDCHAHCCCFCFEBABHDDBGBHHCCCGBABDBCEEGHAFEFEDDBAFFFDFDCEAEAEGDBD,False +190,13.0,10.0,11.0,9.0,7.0,16.0,9.0,11.0,AGCHAGCBAHCBGBEBEACADADHDBFBDDAGEFCFCBHDEFEFHFHGHDFGFACAEFHAEAGGBGFCFCFHFDFCFCBBFDAHAH,False +191,14.0,3.0,6.0,9.0,14.0,7.0,4.0,6.0,EAEFDGEEFCCCFCFEAAAEADCDAEAEGGAFHHHHEAAADADEFEBDBAEGECEADFDHDHB,True +192,6.0,4.0,7.0,3.0,3.0,3.0,1.0,4.0,CFGEHCCFCBCEAEHCHDADADABBBACAFH,True +193,29.0,36.0,21.0,12.0,18.0,14.0,23.0,24.0,BBHFFFCEHEGEHDHBGBHBHDEBHBHBEAEBDBFHFHEHABADACGGGADBBHHFBBBAAAAABECDCACHCAGACFCFAEAFAFAGGDAEBDBHBEBGACBHFAFGFGBBCAGGBGHDCBBDGEHEGEACACACEBEBCACAEGDGHCBDGHGHBBABCCHCHCHGBAEAGBFBG,False +194,6.0,3.0,5.0,1.0,2.0,4.0,8.0,5.0,HBHGGFCFCACAEABGEACDCHBGGHGAGAFHFG,True +195,3.0,6.0,4.0,7.0,9.0,15.0,5.0,10.0,HAHEHFGFHHGHGFFCFCEDEFEDBGBDEDACBDFHEBFHFHFEFDFCFDFABEBGHFE,True +196,2.0,2.0,8.0,2.0,3.0,5.0,4.0,4.0,CCECHCDCDCEBHCGEHBHGAAFFFFGFGC,True +197,0.0,3.0,4.0,2.0,1.0,2.0,3.0,2.0,DBHBDFCCCGCGBGEFH,True +198,9.0,8.0,9.0,4.0,11.0,7.0,12.0,11.0,AAAFADHGGGFGCBCBCHEGEFEHDCABDHGEGEGDACBFHFBEBGBECEHAHAHGBECFCGEGAHEHCHF,False +199,9.0,8.0,10.0,11.0,7.0,10.0,5.0,6.0,ACADDFDHDABGCDEBEHAFFBECECDBBABAFAFAEAFHDDDHCCDCGCGHGDGHFCBCBFFEFE,False +200,15.0,9.0,5.0,13.0,12.0,23.0,15.0,22.0,CHGFEHBDGDHEHAHDFDFAEBDAHEFEFEGGGGAAAGEDAHGHGHECEGFGFGAGBFEFAFBFBGBDFAFHDHBHFHFHGDEDHFFCFEDBDHFFFAAHBHAHFCFDHHCHAA,False +201,8.0,4.0,6.0,6.0,2.0,3.0,2.0,2.0,AGCFBBCBCDAHABACEHDADADCDADAEFGFC,True +202,15.0,30.0,30.0,30.0,15.0,29.0,25.0,23.0,DFBBDGHBCEDBFBHBHBCBHEGGGEBEBHHEHCFFHFGBHEGBDFDFGBGDFDFHCEFHCGCFDHDFDEHADADEBCFEFDFEFECDAAHFGDDDCACACACACDBABGGEDAABBBGCACABFBGDCDAGGGGDCDFFFGFCBBBDBDHECGHGDGCGCHCHFBFHHHDHCEBFDFDFCFCGCBCBCFCDABHCG,False +203,14.0,19.0,19.0,3.0,12.0,14.0,16.0,22.0,CHAEADAHBHBHBHBGGDBHFHEAAABCBGEFCCHFEBHCHABABFHCCCHBHAGAFCFBFAAAHCFCGEGEHEHEHFHBHEGFGHBEGGGCCFGFGCDAECGCBBGBFBCHCHCGBFE,False +204,9.0,15.0,19.0,11.0,9.0,19.0,20.0,15.0,FAAACCHEGCGDGBHDCCCEBAHDGDFDBDBHCFGFCFCBCBFGFGHGBFBHHHFHEGBGBCAEBCCCFCFCHGAEFEAGCDHGHGFGFGCGBGBGFDACEBFDFDEHEDGHABFHF,False +205,20.0,16.0,16.0,34.0,30.0,20.0,29.0,29.0,CDCFGDGDEFHGHEHEGGBGBGBHBGEFECDCEBGDAHGCBDDGDHDHEBEDDDDHAFAFDEGCHEGFHFADBEEGAGDGDHFHBDEAEAHAHDDDECGBADEHEFEFDACAGEGFGBDEDECHHHEAEFFBADDDDAEAHHDHDCCFCAAAHCFCFEGHHHHGBGBDCHCHDFDGGEGBFBGHFAFEGEGEAE,False +206,20.0,18.0,16.0,14.0,21.0,4.0,6.0,11.0,ABABAFADEDBAECHGDDAAHEBBDBACECGAAAACHEFEBCDHGBCECECEBEFEAECBCEHEDGAHACADAHACECGDDEEECEHHHFECBCBEBHBDBDBDBAGDBA,True +207,1.0,3.0,2.0,6.0,1.0,4.0,1.0,1.0,FCADBDBGBFEFDFHCDDD,True +208,5.0,3.0,5.0,6.0,4.0,0.0,1.0,2.0,DCCBCDCDCAAAAHDHBGAEEDBDEE,True +209,9.0,6.0,7.0,6.0,5.0,8.0,3.0,2.0,FCFEAEGDADABCBCFGAGCFAFABABCBDHCFDFEFEACBDHEAD,False +210,21.0,21.0,15.0,16.0,11.0,15.0,20.0,12.0,CACFFACCCEHFDBGBGBFHFAGDGDADACGGDGBAACABBECECEGEDHDHCABDFDFDAGHGHGBGBFBGEGBFDFAGAEHFDAHEGABABFGAGEBCCGCHBDEDGBCACFBFAFHDBEBHBABADAH,False +211,10.0,24.0,13.0,13.0,14.0,11.0,16.0,23.0,EDEABACHGHAEGGBBBBECECEBBBAHGHGHCBCECDCBFBHBHFHFHFBBDAGFEBHAHDHGCFAGABCDDBEBEDHGHBCCACFDDBAHHHGBGBGEGEGHGFEFHHHDDBBCDEFGFHDH,False +212,19.0,7.0,17.0,13.0,17.0,11.0,21.0,24.0,FGCAHAHFGEHAAAAAHGDGHGFEEGDHHAEAEDCDFGBGDHDGFECECGGEEHGHGHCFBBHBFEEHGHGHDHFHDHDAAAHDECAAACBCECACAHFDFCCCCCCGGGGGEEEDHBHEFCGDHAHAB,False +213,10.0,20.0,7.0,7.0,13.0,11.0,10.0,5.0,HACBEBEBAGEEHEDAFABBFEEEBGBGBGBAAEBBDDFDFDFHCHDDAFECHBBAFAGGGFAFCGBEBEBEGGBFFCBCBCB,False +214,6.0,9.0,11.0,6.0,13.0,4.0,11.0,19.0,ECECBCFDGEGBHEDDHGEBHHGCGCBHHHHHEHEGACABADHFFGCGBGHDDCEEEEBEFHAECBCHGHGHBHAHAHC,True +215,3.0,0.0,0.0,3.0,3.0,2.0,6.0,5.0,HDFDHEHGGGGHAHAEGEAFDG,True +216,1.0,8.0,11.0,12.0,14.0,8.0,9.0,12.0,GEBDBDCCADDBGFGFEEGEGCDCEFEGEBEDCCFBHCEDDGEHEHDDFCHHHBHBHBCDFDEGEGCHCHEHFHF,False +217,10.0,10.0,22.0,13.0,14.0,8.0,15.0,10.0,DCHGECECEAGHEFGACFBGBECGCAEBEHHAGEGFDFDFHEDDCDBFBABACDDHDBDGCCCGHGACFCFDGCGCBCBGAGACECACBCECGDHEHEHECD,False +218,7.0,10.0,14.0,5.0,9.0,7.0,7.0,16.0,CFCECECDHHHHHHHHBBBHEFCCEBDBABAGDFDHCHGACCHCHEFEGHGDACFBGBCEEEFGHGFCBCHAAAB,False +219,15.0,20.0,16.0,12.0,13.0,12.0,14.0,14.0,AGAEAEAHGHFBFEHBHFGGEEHCFCDADACBDBFBCBFGFBBBCCAEGDGFAACAHBCBCDAFHFHECAFFEGEBCBGGCDCDCDEBBDBDBHHHHHDGAGDCHCAGEGABBEBE,False +220,0.0,1.0,1.0,0.0,3.0,3.0,1.0,3.0,HEHEHFFFGCBE,True +221,4.0,7.0,18.0,11.0,9.0,20.0,14.0,16.0,GGGBFCCCFBFDGCFCFDFHFHCDCDHHHGHFDCAGHCBAEEFEFEFHAEFCHCGEFCCCHCHEHCDCDAGBGBGCDDFDFGFHEHDHFGEGFHFGFBB,True +222,19.0,32.0,14.0,24.0,24.0,23.0,30.0,29.0,EAEAGFDFDCBHFAFADGBHBDAGCDEABDFGEEFFFEEAECHDHBHDGAHHGBGBGBGHCDFDBDBDEDADHFFAFEFGBHBGDCHEDABGBEBCDCHCBFAFBGBAHFHFGEDFHHHBBBBDBDBDBGEGBHEACCHEGEGEDEHECGHGFBHGHCBGAGHGHGEGEGEHAHAHFCCEFHFAGBGBGDADFBB,False +223,6.0,4.0,7.0,6.0,14.0,14.0,8.0,15.0,CEEFAGEBDFAHHDHFAFAHBFFHFCFEHHHHFDEGEGEDEDGAGHDFGBGBEFGFHHCHCHEHECFCACEEFE,True +224,11.0,10.0,13.0,13.0,21.0,14.0,25.0,19.0,CGBAEGEGEHHCGGHGCCBCAEBEGHCHDFDFDFEGBDFDFEFAGDGAGEGCGBHEEGCGBEEGEADACECABEDCDFFFDCAGAGHFHAHGEGEGEGBGBGHHHHHHDABCEDHHFFDHEHEGFF,False +225,6.0,19.0,5.0,11.0,12.0,6.0,9.0,5.0,GBHBDBABHBCBDEDBGBGBEBEBCCFDHDFEBBDDEAEAEAECFGFGEGABCFGBBDHDEFBGBGEEABHDD,True +226,11.0,18.0,23.0,14.0,12.0,26.0,20.0,26.0,EFEFEFGDCDFBHBHADECHHEHEFGFGHCBGACBGACFDFGFCFGFCCCHHHBHFHFHDADFFEBGFFFFFDBCCFCFHFCDGEHDFDBDCAGGHHHHHHBACGCGAGBGHAAAFFCHGBGCADGBBBCGDHEBEBEBEBHCHDHCCCG,False +227,23.0,20.0,28.0,18.0,25.0,23.0,23.0,21.0,FCCBCEFEDAGGBEHCHCHAFCCADFFHFEFAHCHDGCCHAEDEDFDGAGAGAGEFEBEBHHEFEFHFCGDFBGBDHAHBGAHFFFBFCDDADCDEEAGABHBHGHCHCABADABCHCHCDFGHGHBAFFEGECBGADCECGCGCBFEFDFCGCGDEECAGAEAGAGBBBBBCEEAEDECE,False +228,5.0,3.0,9.0,5.0,8.0,2.0,3.0,5.0,DDDACEHGFBCEAECCCCCFCEHEHEHEBCDAEBDHAGAG,True +229,15.0,19.0,18.0,23.0,23.0,15.0,10.0,23.0,HHFHGHEBFHHBCBDEEHCBGBAHAEDEDCGCGEBBDDDDEDBDHDFDEDACCEEDFCEEECBCBCBCDAFEHCFAHBEDACAGHHHHHHHAHGFACACAFBEBEFFFFFDEBEAEGCBEEDADACBHGCGBGDHDHDFDHDEABF,False +230,15.0,10.0,14.0,14.0,7.0,9.0,3.0,6.0,EDADBFADCDCDEBFBFAFEFEDCBADFBFBAHACCBCGEHEHBCCAGDCFFBAAABAGACHCHDDCCCEDHDADADA,True +231,21.0,19.0,19.0,16.0,21.0,13.0,13.0,23.0,EHBFBHBCDAEACABABEHCAAAAAEBDHDCECACAHGFCFBFBDCCBDBDECHCGCAAHHDDCDCDEEHHHADAFBFGFGDGFGHGAGEEFEHBBDBGHAHGHEBCCACACGEDEAABDBCEDEFEHBHEEEHGHFHEHFFGHB,False +232,10.0,11.0,13.0,7.0,8.0,12.0,12.0,9.0,EFGGGHCHBAEHFDFEADAHBBFBCGFGBCBCBCFHFAFAGCGCEBEDCCCHCHDGGGCGCADFEBEBDAFAFAHEFGBHDA,False +233,16.0,18.0,26.0,21.0,12.0,11.0,22.0,9.0,GBGCHBGDHEHDGAFCFCGCBBDDDHHGCEDEDCDBGBEBCCCCDBGBCACBGGEHEDGGAGACFCFCHCGGDGABDCCCGDBDEDEBBCHCDCDBDAGECECAFEFBFEAGAFAGBGAGDDDACAFAFAFCHBA,False +234,8.0,5.0,2.0,10.0,3.0,5.0,9.0,5.0,GAGBBEDFDFDBDGDAEADHGAGHBDGDFDFCGAGACABAGHHHFED,True +235,28.0,16.0,21.0,19.0,24.0,21.0,12.0,20.0,EDHFBEAFADABHFHFCFHFACCBBBHAHDHBADGDBCBDFEFDHHADACBHBEAEDDDGAGACAEHECFCECHHHEABFCFEEHGAFFFADADCDGEEEGEBECEBBCACAHAHADADFFAFAFHGDEEFEBCGCGCGCDCAHBGEEFGADECECAFAHA,False +236,13.0,6.0,14.0,8.0,9.0,13.0,7.0,14.0,FCFAFAFAHAHCDCDGFFEFECEDBCECDCFHEEFAFACHCHCEBGDHEHFHAHBHDHFCGGAGDHHACCBHDCGFGBAAEABA,False +237,4.0,7.0,4.0,12.0,6.0,4.0,7.0,10.0,DGGHBHDDDGDGCGCGADBHEDEDAGFCFEBDHDEBAHAFEHEHCHDBDBHFHB,False +238,25.0,27.0,17.0,20.0,11.0,20.0,27.0,24.0,BGGGHACECEFEAEDBDBHCGDGDHDHBHBHAHAHFBFGCGCAHFHABABEFFDDAAFHFHDAGADFDGBACCCHGHDAACHCHGBEBCCCBDAFAEGHAHGHGEDBDBCBHBGFEAGAGBGBABDHDGAGADFBFGFGCAEBGFFEHBBGDGBBBFFHFBFCDAGCGHDA,False +239,27.0,19.0,14.0,12.0,26.0,20.0,17.0,18.0,CACHFHBABHBABAHEGBDDEBFAFAEACABAFAHAHGHDFEGEFEBEBEAFCDCHABAGEGEDFBGBACAFDCDCAEHEHFHFEEEFABABCGEEEGHDHAHBHDFGEGBAAAFDHECEAGCGEBEDCDHFAFAGAGBGFFCGCEHGFEBEF,False +240,13.0,5.0,13.0,8.0,10.0,9.0,13.0,11.0,HCHAGAEFGBGAGFGCDCAGAECGCGEFEDHGFADADACHDFDGBCBCFEDEFEFBAHHHHHHAAFGCECACBCGEHEADCG,False +241,15.0,13.0,22.0,21.0,14.0,24.0,13.0,15.0,CECEBACABEFHFGBEFDCDBABGDAEADCDHGFGFDDDFDFDFGFEFGCGEAHGHGHCFCDABFEHHABCECBCHFHCACFBFBHBADFEFEFDFDHDHCHCDEDAGGECHAFDHCABFCFDFDGBGCFCACDCEA,False +242,10.0,3.0,9.0,4.0,10.0,22.0,6.0,6.0,CBAAFFFFGBDAFFFFFFFDGAGEHFGECEFEFHCHCEEEDCFAFAHAFBDEHGHCFEFCFCFEAAFAGC,True +243,16.0,18.0,13.0,25.0,8.0,14.0,16.0,17.0,CFHGHAFGFCFEDAGEBBFDGBGHDHAHBGBGBDCHHEBDBDBDCDHDHFAGGHGHABADDCDFBHAGDDDBCACECAGEGDDHDFDFHFHCGCGCDBAFAFDBDEFEACADADADBCFAHBHGEBB,False +244,14.0,10.0,26.0,18.0,17.0,28.0,19.0,21.0,HEHEHDFDFEGEGFGDCBBDAFHFHFDCEGBBDHFAGBHFHCECHCGAFCCDDADGHGCGAGBDCDHDHDACFCFGACEHEGDGFCFCFCAEFHHHFBFDFDCBCFEFCDGAGDEEFEFHFHFEECCCAAABECFHACECFAFGFCBCGHGHG,False +245,30.0,27.0,23.0,25.0,28.0,19.0,14.0,26.0,AAACACBCAEDEBEFCCHCAEGEDEFGAGCEAEADFEBBBEFAGBBBFDAEAEHHHHCFCHCHADFDEBHFACBFBGBFBCHHAHAEEGHHEAEGHGHGHGCAHADADAEAEAGDGBECHDDDDEFFDCDCACAFBFHCHEHEADFBFBGBDBCGABHBHDACCECDDBDBDFDBEEEEHCBAFHHDBBADF,False +246,9.0,17.0,16.0,9.0,17.0,6.0,11.0,16.0,HGEGACAHDHDCDEGFHBHDHECEDEDFDEEHCFCFHBEGGFABEHHHHGAABCCDBEBECHCHFBAHGCGABCBEBECCCCCEGEBBBBDBABEBHGEGA,False +247,10.0,6.0,15.0,20.0,23.0,16.0,16.0,6.0,AFDGEGEFEDCDFHEGEGFGBCACECEAEHEDDHEGEDEFGDDDCCCCGAGEDBABEFEFDGDHDGDCBHBGFFCFCEEEEFCHEFGDGFCDADCFCAEGFGBEFDADADAE,True +248,1.0,1.0,5.0,2.0,5.0,7.0,7.0,2.0,EFCFDAGFCFGFCHEHECEGGCGDGFGFBE,True +249,20.0,25.0,23.0,25.0,18.0,22.0,28.0,20.0,DGDBDAABACHGHEBDCCABFBAHGGBGEAAGDDFGFAHADADEDFHFHGGGFGFDHDEDBACDGDGBFACABBGBGEGEGECFFFEABDEDHFAFGBCBCACHHFHFBFBFHCHCHCECDGDCEHEGCGBBFBGEFEFHCGCBHGDGFHFEABCCEBDBHGDGDGBHCEDADCDCBAEAC,False +250,27.0,24.0,20.0,16.0,26.0,17.0,25.0,11.0,CHCBCACHBABAGHFEEBEGECEBEBEACDGDHHGAAFGEGABEGAGEGADADABAECFGBGAGAEBEADFGFECACGGFGEGDGFBFGCGBFBFEAEBEFAFAFEDEAAAAGBBBCDCDGECCCBCFADABHDEDEGEAHHBDEDFDFGCCCDBBHAHGBCBEHF,False +251,23.0,19.0,20.0,25.0,22.0,22.0,28.0,26.0,ACACGEBFHHCAGAGHGHGCGCGBEHFHFCAGFGCGHEHAHADDDDAEEEECCFBGHAHAHGBDECFADGCECEGEGDGAADBEAEFHFDGDGAEAFDECBGECCHDEEBGBABEHHAFFFFEFDADHBHBDDGGCGCBAGAHABDBDEFEBCBDHGHGFDFDFDFHBAFCBDBDFFGGCHHHDH,False +252,22.0,23.0,23.0,11.0,21.0,24.0,27.0,23.0,CGGAGEGECECECDBFFFHAHGEGCGAGACEDBBBFGFGHGHFCBGHFHBHGEAHAHABDHABABDBECHAHFCFEFAAGGGBGFCDCBEADADHFHDHCEABCGGGFGAHEEAECCCCGBBEHEHBHBHDCDFFAFBFCEBAGAGCCBCAGFDHHEHFFFCFEFBBEBFGEGA,False +253,21.0,15.0,11.0,10.0,10.0,18.0,15.0,19.0,CFCEEFHBGDEEFEFDAGAHAHGHFHFHGHAHAHGFFFGBDBGAAAABABGBFBFBEACGCEDHFACCFFFGECBAECDGGAFAHDHDHBCCGHAHAFAEDHDHGBBABDFCAGABHBH,False +254,16.0,7.0,14.0,11.0,13.0,17.0,11.0,13.0,CDFHFHECACEDEAECCHFHFHGHGCAHAGAGDEDFDCHCFDADFEGAAEAFFDEDCCEDBFCGCGEBEBHGAGFBABAGFHDHAHAEFFFFFBEBCGHACA,False +255,14.0,24.0,17.0,17.0,23.0,22.0,12.0,11.0,EDGFFFGBBBCACDDDBDCFCFCEEAFGFGFGFDBBBFBDCFEFADAHEDBDFHAAGHCHFGACABEDEDEAECEFEFDAABHHAHCECBFBCBFFDBDGHGHFBCDCECEDEAAGEGFBEBCBEEGEBEBEBHCEFBBH,False +256,15.0,18.0,13.0,27.0,17.0,28.0,20.0,24.0,FBDBCHCGDEDCGAGAGDDFBBBFFFFEDACGCHAGGGEGEBABFHFEDHFHFCBDGHGBGDHBCBGAEHFAFHHHDBDCHBFGFGFHFHEGEBDFFFHAHGHCHAHDHEBEFEDGDGAFABDBEHACFCFCEDADEFBDDEAEADFDFHFHFDGHEDDDDC,False +257,6.0,7.0,12.0,13.0,9.0,11.0,8.0,10.0,DDACHGHGHDHEFCCEGEGACCDCDCDADHBFEFEDEGCFBFDFBFEHCHDAGEDECBCBHFGFDFHAHCGABDBF,False +258,17.0,20.0,27.0,16.0,18.0,18.0,19.0,20.0,AGEHCDAGCGFGDCDCHCACDFEAGFGAAAADADCCHGHGHCCEEEGCADACAHECEGDGFBFBFCHCHCBBDBDBDEFCGCBBBEHFHACAGBCHFFBCBCGGGGHDBECEHEHGHBCAGEDEBFCEEBEBDFCFAFHBADDHFHFHFHECFBB,False +259,1.0,5.0,4.0,1.0,1.0,0.0,6.0,2.0,GGGGBGAHBHCGDBECCBCB,True +260,2.0,3.0,4.0,1.0,3.0,5.0,1.0,3.0,BFBCBFHEEGEHCACACHFFDF,True +261,2.0,4.0,3.0,2.0,3.0,2.0,6.0,2.0,CDCABEHHGFGFGEBABCBGDGEG,False +262,17.0,17.0,32.0,25.0,20.0,22.0,15.0,15.0,DHDCDCDGEHCBGBEBACGDFDCBCFCBCEAEAFCDEBAAEADHCEAEHECDDDBDCDBBFFEFGFBCBHAHFCCECGHDHFHAHACDEHECFCDEAAHABBCHGEGDGFHDDCDGDCCCGCACACFCFDADFGFBFBFEGEGEHDACGDFCFCFGBEBEFCF,False +263,7.0,4.0,7.0,4.0,5.0,5.0,7.0,12.0,GCACAHGHECGCHFGFEDHDHDHGHBAEAHBHFHGCCBCHEGEBHAFADAF,False +264,6.0,6.0,13.0,6.0,11.0,2.0,9.0,8.0,DCFBDBEEEEEEADAHGHGCGDHCHGEACBCGCAHEHGGAFAGCCCCCBEBHDCBCEGEHD,True +265,20.0,25.0,22.0,32.0,26.0,23.0,23.0,27.0,DCHBHBCEHHGHDCGCAHHGHDEEHEHBBECDCGBBACACADDDDDFCGEABGBABEBEBEACFHFBEGHFBABCGHGEGDDDEGAHAEFBFDGDHBFGFCDCDCDFGFHEBEHEHBDEAEACBDADHFBDDDDAFEFBGGGGHGHCHEHFCFGFGADDDDBDADHFEBEBECEADACBCFAFHFDFGFAEGHHCCFE,False +266,7.0,6.0,7.0,3.0,4.0,2.0,13.0,8.0,BGHCABHHCHGGBDBABAFCGEGDGAHCEEGEGBGCAHAHACGCGHGFGD,True +267,8.0,8.0,22.0,12.0,15.0,14.0,10.0,10.0,DCBAAGBEBEHECCCCFEDDDFGHGDEDCBCGEGEGEBFFAEHECFCHCHFHDCDCBHGGCCBCFCHHFAFGHGDFCEADCDCDCEBFAFACECAFEFE,False +268,20.0,11.0,17.0,15.0,11.0,11.0,19.0,11.0,FACAFGDHCEFHAECBCBEBEAEGBGBGFHCCBCAHDCFCDGDAEEEFBACADABACECHGGDBDGGGFHEHADAFGFGFGHGHGCFCDCDEGAAAABDDDGHBACACDGDHAGA,False +269,6.0,1.0,7.0,4.0,8.0,4.0,3.0,3.0,DBGECEAEAEAEAGDGFCHCECFAAHHFEFCCDEDC,True +270,18.0,16.0,20.0,26.0,19.0,21.0,22.0,23.0,BFBCDDGAGACDBDGDGDADHCAEACGCGDEBGDFDCDBDGHEHCFFFFFHFBFAFHDDGBHHHHFEFABGGDGDEFCDGHCHEFCFHBADHHCFCBGBFEEEEEFEDEDAFGHGDGCACDEAEACDEDHBHGHBHBHCDGAEACCEHGHAHACAGACBEBGFDF,False +271,0.0,3.0,1.0,4.0,2.0,4.0,2.0,3.0,HFHFEFDBEBHFDDBDGCG,True +272,16.0,16.0,17.0,14.0,11.0,14.0,8.0,16.0,FCHEHAFAFBFBDHGAFABBCDCDHBHEFABCHCHDAGABEBAHDHDFCEBGDFECECECEHECACDBDBDCGAGAGACAGBFBGDDACCDDBHEHBACFBFHHHFHFCFAE,False +273,13.0,11.0,14.0,14.0,11.0,17.0,18.0,16.0,CDFDGBHBFGFGFGEDABABCHHDDEDCHCGAGFBFDADHDCDCECAGEFEBEAFAEHEHGGEFBHCHFHFAFDFACGGFGHHDHGHAHCFAFGEBCBGBGCACDCDEHGFBAG,False +274,30.0,26.0,12.0,16.0,14.0,36.0,17.0,16.0,GGHCBABACFGFHFBBHAEAEACADADABABFFDABBFFEFBAGFHFBFCFBAHHHHGGDGFGBHBFEECEFDCHCHBHGEAHADDGAFAFDDBDGFGBEFFFFFGFACABGFFFAABAFACAGAGHDABABGDACFEAEADBBFBEDEAFFBFBFCFCDBHEHEDF,False +275,6.0,13.0,13.0,9.0,7.0,9.0,12.0,6.0,CEFBGCCCCHDBDBCAFDFDFGFHHCCGCGBGDGDBCBCBHFGAAEGBGBFBGBGECHCDAEGEFADAHEDEBBF,False +276,7.0,5.0,3.0,5.0,6.0,7.0,3.0,5.0,BCCDFEFEFEBADABCFDDHDHAAEAGFGFHFBAEAGHBHE,False +277,6.0,5.0,1.0,2.0,3.0,3.0,6.0,7.0,HBBFBFDHCGEGAHAHGHGFEBHBGGAEAHADA,True +278,4.0,8.0,15.0,16.0,12.0,11.0,10.0,10.0,DHCHAEEEHEHEFEHGFBHEDEGEGFCDCFCGCDCBFFFCEGDBHFDDADGGCGDEDEDGACDCFCFBGBHBDBCFCHCDDDHCAB,False +279,15.0,15.0,14.0,9.0,20.0,30.0,10.0,19.0,EAFFEFEFHBHBHBHCHCFAAACFCAHGBGBFEEBECEGEFDCEFEGCBFHFBEAFDBBGDDCGFDCBBHBHFEFEHCHFBFDGCHFHFHFGFGAAAAEECEFDBEFECEHDFCFHDHFFEAAAAAFGFHFH,False +280,20.0,27.0,17.0,23.0,26.0,20.0,26.0,25.0,AEDGCEBACABABGBGFDCEBHBCBCGHBAEACBHHHCDDEGFHAAFABCEHDBDBDFFGFCBGGGFGEEFEDEAEDEDHHHFHEEEGEGCBCBHBEBGBGECEAEHGHABBBFHEAFGBGDGFFEFDGDGDGHGDAFAGDHDECEHHHAHDDGHGCGEBEFABCBDBFCFCFHBADADFDAHH,False +281,10.0,6.0,6.0,8.0,8.0,11.0,10.0,7.0,GBFFDHAEAECDDBEGDGAEECGGGDHDAFADAEAHBHDEFFFFBCBCECAFABAHGFGFGFGHCH,False +282,21.0,33.0,19.0,20.0,21.0,12.0,19.0,26.0,CAADABABCEABHBABDCHEAEGHBBCCCCCHCBGGGGHHDHGHGDGDGDBDAAGCBHDFEEEEEEBEBAHHGHEHCCGHFBFBFBFGHBDBHAFAGACCHAHFBCCFDEDEHCHABDBEGADBBCBHEHEDDDDBDEDBBHAHBEEEDBBBBHGGGCEFBFAFBGAHAFA,False +283,12.0,9.0,6.0,10.0,12.0,16.0,15.0,10.0,CFCEDFGCGFHFBGCGFGABEGAGAGAGAFADBHGHDEFHHDGCADEGBBCHDAAAGEBEBABFDFEFEFHFHFHFHGBFEGEDDDEFEA,False +284,0.0,7.0,2.0,2.0,5.0,4.0,3.0,5.0,FBBHBHECBFDFGEHCHEHEBEBDGFGB,True +285,18.0,10.0,10.0,8.0,8.0,13.0,19.0,13.0,HHHFGFAHCCBCHCBFAGCGBABDBDGAFDCDAEAEHDADBHBAGFGFGHEFFGHGHBHAFFBFCFCAAABEEEAGGGAGCGFGAGADAGEHAHCDGEG,False +286,17.0,19.0,13.0,13.0,17.0,16.0,12.0,9.0,DBDADABCGDAFEFEFEDABCBEBGDGFEBEBEBEADBDGHCADABFDADADABGFGFCBCDCFBGGEEFCFAFEFBAGGEFHCGAFAHBHBFFEBACECACBCHAHEHEHCGBEH,False +287,11.0,13.0,8.0,14.0,5.0,10.0,1.0,11.0,ADDCHBHFDEACFDBDBABCBCDDDBAAADHFBFBABEHEHBHBCCHFDABAHCDDDCDAFHFEFEFHFHGAB,True +288,21.0,32.0,21.0,22.0,23.0,17.0,23.0,21.0,CFCBBDADEDEDBDHDADCCCEHEHBFBHADADBGBGDCBBHFAEBDHDFDFBEBHDEDBCECEGABCFGFHDHGHEHAAGHGEDEAEABGFCCBEBCFDFAEGGAGADECFFGFBBHCGEBEGAFABDBHFFAHAHAHBHBEBEBCBABDEGCGCHCHBHBGEGEGCAAGGBBFCCGDG,False +289,10.0,13.0,5.0,12.0,9.0,19.0,21.0,12.0,GBFAEDDDGGFEFDHHGHGFGFGDGFGHHHHEGDBHFGGHECBAGAEACFBBDBCADFGEGDBBBBCBHHFFBFBFDAAAEFGFAFAFDFDFHGGGGGECE,False +290,10.0,11.0,9.0,13.0,3.0,16.0,8.0,5.0,DBDBDCFFGFGABEBEDEFFGFGFAFABHCAFABCDHDADAHBGBDDDADFHCBCDCAAGHBFGFGFCCBFFCFD,False +291,22.0,19.0,25.0,28.0,18.0,24.0,23.0,17.0,FCFEFEFAGEGCGEAAAEGEHFHEGFGDGDEDBDEEECBBBEDFHFAGHCAGAFAHABFBFDDGECEBGFDFCFCDBEFABGEDACACDHDHDFFCDCACHCDBBGCDBHBHCFCDHHHBHBGFGFADDGDCDCHCDCACAGAGCDDABCEGHDHFGGDDEAFBFACACABGBGFD,False +292,22.0,21.0,17.0,19.0,16.0,16.0,15.0,29.0,EFHHAHDCDEBEHEHEHEHEHCFDBCBDHCAFEGGHDDBDFGFGHCFDDDDAFADCGCFDFBFBHGAFCCBBEEAAGAGDEDAHAHAHBHBHBHEHCABABHBCCCHCBBBDAHGFDEAEAFHGBGEHAFBGHAFAFAHABCDDECGCHHGHGAB,False +293,14.0,10.0,22.0,19.0,17.0,10.0,11.0,13.0,FDGGCACGCDCACBCDCDGHHDHBHFGGCCFBFBCBDFDAGEHAHEFECBHGDDDCEBBADCDFDADEEEEDEBHAHAGCGCBDGECEHEHAACADAHFHFEFCCECEDECCDAEA,False +294,21.0,23.0,11.0,16.0,19.0,13.0,19.0,13.0,ECDFDEAGAEAGHBFEFGHBBGBABABGDGCCAGHBHFEFGGCBDGDGDGHFHABAECEAGHFDFEFBFECECEFDHGFGABAEHEGEBBBBEBADFEHEHBDBDADADGBHADADHGAEBBBDCACECBCAAGA,False +295,16.0,21.0,15.0,23.0,14.0,18.0,17.0,12.0,DDBBHFDFGBGBHBFFFFFFFGEBCFCGHABBEHDDDDBBBBDGFHFAEDHDHCFCHCECBAHACDCDHAAADDECACAGABAGEFEBCAEACGDGFEFBGBDBCBGGDDAEFEDGCGEGEDEDGDBABADFHCHG,False +296,2.0,5.0,5.0,3.0,8.0,3.0,7.0,5.0,GHDHFBBGGCGBHEHBCACHCGCGEEEEFDADBEGEFE,False +297,8.0,7.0,6.0,6.0,3.0,4.0,7.0,7.0,GDGFBFEFAAEBDBDBAGAEHBDBHCHDGBGCGHGHAAACHCHAFCCD,False +298,10.0,8.0,9.0,8.0,12.0,10.0,12.0,8.0,AAAAAADGHGAEEEHFHEHEFFAGAFHCDCGEBCBCBFBFAFHFGGCGHEDGDFDBGEDEDCBEGEGHCBEBCCDGF,False +299,2.0,2.0,2.0,2.0,1.0,0.0,0.0,1.0,CHCEABDBDA,True +300,21.0,16.0,12.0,20.0,12.0,15.0,16.0,21.0,HFHGDDEFBFBFAGCFAGBGDHEHBHBHAEFBDGACHGHAHFFDFHFHEBBCBDBDBCFCDCACAEDEDHAHBHECABAGCEBHBGEDEGAAHAFAHADCDEGEGADFGAGAHCDAGADAHCHDDGDGDHFBF,False +301,18.0,17.0,21.0,18.0,14.0,17.0,20.0,23.0,BEBFFCAGAGAGHGHFHDHCFDFDEDEBEBEAGFBCCHCDCBCHHGHEACAEFGBGBEDEBCDADHFAADBHBHCHFDFDFHGBGBAEFGFAAEHEHEHCCGHDDDGHCCCCAABCGCGCADACABFEHDBCFHGHGDAHHDFGBGFG,False +302,17.0,9.0,16.0,15.0,18.0,20.0,16.0,20.0,CFEHGDGCGHFADAFGFBFHABACDEDEDGAEHEHCCCBCEFHGHAEAEAHAHEHEHCDFFAHDEAFDFGBGDHHFHFAGGFFBEHEAEAFFFDGBGCGEECAFFHEHEHDACBCFCDDDDCBCBHGAGCG,False +303,17.0,9.0,12.0,14.0,11.0,11.0,11.0,15.0,DFDFAGHHDEDEHEHECGFACAEADDHDEDCHCECFHBBBEGHBACGGGAGAHDHAAADEHEAFADGDBDFHFGBABABHBFCHAHACCFCGCEADFCFG,False +304,32.0,22.0,21.0,20.0,17.0,21.0,22.0,16.0,HABACGCBCGHGHADEGABAFHHGFCCGFFFHFHAHAGACFGEEAHAHABABFBAEAEDGDBDFFFFEGHGDDDCHFAFGECACECECEDFBEAAFBCGAGECECFCFCBGGADADGHACAEBHAHABGGDDADCDADBBBGHEFEDDDGEFBDBDBCBABCBAAAACFGB,False +305,22.0,14.0,10.0,9.0,20.0,15.0,19.0,12.0,GAGABHEFGHGABAEDECGAFABBEFEAECCAAHGHBEEEEEFHFGFGAEAGAGDGHGFAAAHAGAGFBECEFFBBGHGFCBCGCADEDBDBDBDFEECEBEDGAAEAFAHHBFCFCDHGH,False +306,7.0,13.0,6.0,7.0,4.0,5.0,5.0,12.0,BABAFAHDFDGBHHEHBDACHGHGDDBDHFFAFACEBEBEBHBCAHBHDHCGBHBCGCB,False +307,27.0,19.0,23.0,17.0,31.0,29.0,21.0,17.0,FADCDEGEBEGHDAEFEAEBHBCBAFAHAFGEGFBFCAHAHCCBDFHGCEFFCFEFEAEAFCBDADADHDFBFBEBADFCFEFBFBFDFCFGFEAHBBCCCCHHBHAAEGEBECEGDAEFDGECEFEHGAGEFEDGBABABHDHDCDCGHAEACAGFCECGGHEDCFAAAGAGCEHEGEGFGFE,False +308,16.0,23.0,23.0,25.0,22.0,21.0,28.0,27.0,BHGEFEDACAGADADGDGDBBFBCGGHGFCFCEHHDCDCEGFCFBEBEHDHCHCBEDDHBBEBGGFDECHCHCBFDFBGEHEGEDEGAHDBDAHGBGDGBCFCGCGBBAFAFABBBFGFHAHAEAGFFFGDDCABHECEDEBEHDGDEDEGCHCDCACHCAFGGGHFHFHGHGCAEHHHHDDBEF,False +309,11.0,10.0,14.0,4.0,9.0,15.0,8.0,17.0,CECHBGAHBHAHGCACBEFEFDCCCCCBCDCGAFFFFFBCBAFHFHFHDAEAHGHBHBHEHBHCGFBHAAGEFEFEGHAHDFFCAEHG,False +310,7.0,7.0,11.0,8.0,8.0,14.0,8.0,4.0,AFACGFEEDBGHDDADFCFCFCFDBGBHEHFAGDCACFCFEFBDBGBEBFCFCFCADGEGEAHCFGE,False +311,1.0,3.0,3.0,4.0,1.0,4.0,5.0,3.0,DHHBHDGDGCFAFGEBCBCGFGFD,False +312,9.0,6.0,12.0,3.0,7.0,3.0,4.0,5.0,AAEAECGCDFDHACECEAEBHBACCHCHEGCGCHCACBBAFAFCDGEBB,True +313,10.0,20.0,11.0,11.0,10.0,21.0,14.0,10.0,FHEBEBCAHAHBFGFGHGFAFCFDBDFDCHBECCCHEACABDGFBFEFAFAHGBFBDBDBFCCCEBFGGBGFAFABEEAEGBBFFDFBFBDBGBGCGDEDHFHDGGH,False +314,11.0,11.0,19.0,12.0,11.0,7.0,10.0,11.0,GBHBFGDABADADBDCDADHBGCECHCHCGCEAGCGCDCFEAGAEAEHECEFFBECDCGEHCBBBCGDHDBDADCFFEFCACAEBHHCHGHC,False +315,15.0,20.0,19.0,23.0,12.0,16.0,12.0,15.0,CCCCEFDBDHDCDFDCHFHFDEBACECHCGGFGAHDDDBACFFFDFBBABABDBACADAHCHDGCFFBHHDHDHGCCACEDBDECEHEBABHFDDDDGEFBFBGBEBFAGAGBGHEHDFEBABAEADBCGCG,False +316,6.0,8.0,6.0,3.0,8.0,2.0,0.0,9.0,CBCDFDHABAFEHBHBHECEBECHHBEEECEHAHCDAHABAB,True +317,5.0,12.0,12.0,7.0,8.0,8.0,7.0,11.0,CHGBGBFBFDABACAFFFCECHCEGDBBGHCCBGDGFGHEHDHCHBBCCECEBEAEAEHDCDHHBHBDFF,False +318,19.0,29.0,24.0,19.0,24.0,39.0,20.0,15.0,CFEFGHBHFHCEABFCCCFFEFEGBGBAHAHDBABCBGBGBGAGAGABHCCCFFFEHEDGBHEEDHDEDBHFDBCBGBFCFBEDFAFCFGACEFGFGAAFFFFDFEFECCGEGBDAAECECABEFDFCEAEAHFDBABDCHGBGBGBCACBCBEFGFGFCFHDDFAEHDFFEDDFDFBFBEBEBFHFCD,False +319,8.0,5.0,5.0,2.0,5.0,4.0,3.0,7.0,HAAEAHDHCBDEAHCGFGCEABAEAFAFHFHBHBCBCEG,False +320,4.0,0.0,2.0,0.0,3.0,0.0,0.0,1.0,CACAEAHAEE,True +321,19.0,25.0,20.0,14.0,21.0,25.0,19.0,10.0,ECEAHAGAGDCFHAHAHABEGAGBEBFFFFFGFDFDFGCDCBABEBGBFFFAGADFDGHGABAHAGCBABGDGEEACAEDBCBCEEFHGDDCBCEGEFEBEBFGCHBHBEDFHBCGEBCDCFCEBEFEBCBCBCBAGFFAFAFDCGEEFDCBF,False +322,4.0,3.0,7.0,8.0,3.0,3.0,6.0,6.0,AGDFDFDAGECEDDHCHGHCBFDEBCBCHCHCDDAHAGGG,True +323,20.0,23.0,10.0,13.0,14.0,23.0,24.0,21.0,AGAFFGHGEBBCDCEEEGBFAHAEGEGCGFGAAEBGHEBDGAGEBABEFCHAHADFBFDFBHBHBGBEBFBFHCACGCGBFBFAHAHFEFDBGGGBGFGBBEDHGHGHFHDHDGDHBFBFDFHFHFACADAGEFHCAADHBHCADFGA,False +324,6.0,10.0,13.0,15.0,5.0,10.0,12.0,7.0,ABBDDDDGDHDCBBHCHGDGBAEGEGHDBCFGFBEBADGCGCGHFFFFFCFCBDBDGDCAAAFDHCCCECDFDHCGEG,False +325,14.0,17.0,16.0,18.0,24.0,25.0,25.0,12.0,EAGDFBFEHEFGADABCCEGEAEGEGHGBFBDEAEDHDFEFDHCHGBGEECDCDCDCHCDEAEACCBEGAGEBFBFBFCCGFBEBCCDEDFDHHGAGAGEEFFFFFBGHGHBDECEBAFAFDFDGGGAHBEFGFGFHDGDEFGCABFBFGG,False +326,10.0,8.0,13.0,7.0,11.0,10.0,9.0,12.0,HGFCFAFCFAGADEDBHFCFCHHAHACEBECCCCEGEFEFGDBFBHBGBCEEABCECAADDEDHDHBGEGAHCHFHGAGH,False +327,13.0,9.0,7.0,7.0,11.0,9.0,9.0,4.0,EFEGEFABAFHDBFAFGGEBEFECCCEFFDADBDGEGAGABABABFBDDAEAHAHGHEAAGDECCCGCB,False +328,11.0,7.0,14.0,13.0,15.0,16.0,11.0,12.0,HHHHFDGEGFHFHGDGCCHFBFEDBAHGFCDCGGDDACACEDBGEDEHHGHEFEFCFGFAAACADHFAFCFCFCBDBAEEEEGDFBFAEAEDEDEBCCC,False +329,14.0,9.0,16.0,7.0,13.0,4.0,16.0,18.0,GCAEFCFCACAEDGGEGBGBGBHBHAHECAAAAHAHECECHGHADDCBCFCHHGAGEGDGEAECGBHDACECBHDCDGHCHGEBHBHEHCFGEGHHA,False +330,6.0,12.0,18.0,17.0,8.0,10.0,10.0,6.0,GGFCECDCDCAABEBEHEFDDADGDBDHGFBFBEDHDFBHGGCBCBCDCBCHDGCBCBEDCDGDBECADACCCFEFGFGFHDADFCC,False +331,11.0,25.0,21.0,16.0,17.0,27.0,21.0,23.0,FFFCHCBCGHHHGGCEBEDFCHAEFCFHDBDBABFBFEFBFHDHFBGCACHHFBFDFGFBHHDBEFAFAFHFEEEGEGEGEDBHCDCACHHGFGFHHBDBDBHCHGEDBDECECECFGBDBCEGGGGCCBCAAADAHBBBGBGFGHDAEFGFBBGHDCFCF,False +332,31.0,34.0,15.0,23.0,18.0,19.0,14.0,23.0,HBFBAAACBDEABCHDHAHDFEFHAAACDEBHBHBHBCBHBHBGCAFGBGBFFDFGAEAEBDFFADADACADDDHAHAEEBFDFGCCCFCAEGBCBAHCGEEEEEEBFDFEHBBBABAHADBDEDFGHHBHBDDABBHBHDHFCFCGEBAAAEGFDFDGDBBBAGAGABAGHBHCAD,False +333,20.0,17.0,9.0,14.0,13.0,13.0,13.0,14.0,ABGCECACBHDHGEEHEHBDAAAFDEDGDFAFABCCGHBABEBEGADADFDEHEHEGBGAHADDHHGHGCGFFABAFDBDHABEFDCDFFAFBEBHBAFAFABABGCECHGBG,False +334,7.0,5.0,2.0,4.0,6.0,6.0,4.0,9.0,GCGBFBHAHEBEAEDCGEAEHHFHAHABFGFHFHDEDADAFHB,False +335,17.0,13.0,10.0,10.0,9.0,12.0,9.0,20.0,AGHHAHAHCBABFGADADEFEFEDBBBBHHGHDHBCECEHFHFHBHAHDEAEAEBEHACAGADHCHBGGFFFHACBDFDAGHCDGDCFCACFHFBBHGAA,False +336,10.0,13.0,6.0,5.0,11.0,4.0,11.0,9.0,EGEBEBEGEBAHEFBCBEHGDFHFAFCBHBGDABHGGGBGCGBABADHDCEABABADAEEGAGCHCHEH,False +337,17.0,16.0,15.0,8.0,14.0,17.0,17.0,24.0,HBGBABHBHDFFAHAHAGAEAEAFACGCBCECFGDGCCEFEFHHHABGFCHDHGBCBHBDGDHEHGHCFCHGHDHFHFBFDABHBGBAFHEEGEGECBAGEHBHCHEFEADCBFGHCEFGCGFAAAAF,False +338,18.0,20.0,22.0,16.0,18.0,27.0,14.0,22.0,AEAEAEAFHDHAAEFBDHGFGFCAAAGADFFEFBADCHCHEGBBEBGFGFGEHEDCFHAEBHCDCBCGAECGCHCHBFBEBHHHGCBHFDDGHHHCHBDEDECBDFEFBFGFCFBFBCBFBFCDEAFDGABADADBFFFFECECADHHHCHCFCFCG,False +339,24.0,25.0,25.0,23.0,21.0,21.0,28.0,25.0,ABAFDFCFCGHGCDBDGEGEGCAAEBHBHGHGHDADCGCHFECEBDHDABHGCGHDHEEEBFBFBDDCDGEEEHBFFCFBFAFAFGCCCHGGFGCACHEDEHGDDBHEHDACAFHEABGCACABDBEBFDGHGHFHEAEAEADACGGBBBCGCGDGBGBFCHAHAHFBABFCEHBADGDEBACGCGFAFDHD,False +340,14.0,19.0,9.0,8.0,9.0,16.0,11.0,11.0,CAADABAEACBCBGAADHBFFFBDBDEGABHHHAEFHBCFHBEBGFDFBFBDBDBDAEGEGEFCGBFBAEGBGFGFHFHFGFCBCAAGAFEHHHCBC,False +341,2.0,6.0,2.0,4.0,1.0,4.0,1.0,1.0,ECBDBFAFDFDBGBHBCBAFD,True +342,10.0,9.0,6.0,7.0,9.0,12.0,7.0,13.0,AEAHAHFEGEGBGAEBBHFDBGBHHGHAFAFAFHFDDCDHECFCACFHFHCDCDHBEBFAFGFABEEEGBDHH,False +343,12.0,23.0,13.0,17.0,19.0,18.0,25.0,20.0,GCGCGCFABHCGAFCFDFBHBHEECDDBEHEAEABABAHHFFDFGEBEBGCABAGGEGEDEDHBCFDHDGBGDGHAEAGDHAEEECHHFBDGCFCDBDHFHBBBDHHCBEHFHGGGFGFBEBEFEFCFGFGHGDGDBHBGBABDGEG,False +344,8.0,19.0,17.0,14.0,18.0,17.0,16.0,26.0,BFBHCHCACDDFCHEHAFAFEEEDHGHBEEFADGGFGEEDEDEFEFBFBHHGHGHDEFCGCGHDHDBCHDBCFCGEBHBHEHFDEAEBEGCGBHBFBHBCBCBCBGACCHHHGHFDFCFHGDGHEHDCBAAFHBG,False +345,14.0,25.0,9.0,16.0,24.0,29.0,24.0,20.0,BDBDFDFEGEDADGGGGDFAABHGFGFEBHFECHCEDBABFBEDGGCFCEAAHGHFBBHHHHHHEBEBFAEEBEDGDCHEFBFBFBHEGEGEAEBGGCAFFGDGAGAGHFFFFFGCHAHBHDEDEFHBBBFDFHFBFBFBHDEFGBEDEGEGBAFFCACEG,False +346,20.0,21.0,26.0,20.0,28.0,15.0,21.0,20.0,EDEDFHFHEDCCECEHEHCGBBAEFDDHBGBEBGAEHECGCACECGCGCDEHCAFAECHBBDGDFCFBBHBEBEHDGDBDCAGACAHAHDHCEBEHEACDDDFFAGAFAFCGEACACGEEAHAGAGAGEFEFHFBGCHBDBHBCGDGCECHDHFBFDCGCBBEBDAEGEGE,False +347,9.0,10.0,7.0,7.0,9.0,11.0,7.0,1.0,DAFCBCBAFDEGEGEFAADGEGEAEAFGFBFEFCFGFCFHEDCBGBEBAFDDABCBABDBC,False +348,23.0,21.0,22.0,23.0,12.0,21.0,19.0,12.0,DBGBGFCCGCDHGFGFGFDCDEAEAFBFBHGHBCBABAFFFBBAFHFCDBFECCDCACAEADFDEDGCFCHBBBBDFDCGAHFGEADDGHFFDADEGEAEFEDECACACAFADCFCAGBBABEDGDHCGCACACHBDGGAGBGBHAHADDDHB,False +349,24.0,18.0,28.0,33.0,14.0,23.0,32.0,22.0,DBDACACDEGGCFCBGBHFGDGDEDHHADCFBFDFDAAFAGDGCFCECEGDGFBAGHDDCDCDGHCFFAFGDGDHDHFGGBGHDCDCAHFEDBFBFCDDEDGHAHADABHBEAAACADGBGAGAFHCCGFGCGDGAEAGDGHFHFEBAHCFCFGGGEGEGAGHBBBDCCHCHFHCHDFDBDCDEHECBCEAABC,False +350,8.0,4.0,6.0,7.0,7.0,4.0,16.0,7.0,EDGFGACAGBHBEBAGACAGEEEEEGGAGCGCDAFHGDCDHGHCHGBGAFDFDGGGDHH,False +351,14.0,22.0,13.0,15.0,4.0,11.0,14.0,13.0,ABCCHHFHCDBDBDBCCGCGFFDFBFGGBAHADDGDCDCBAHABEFHBBDBDBDBEBEBGDAEABDGFHBHGAGCBFHHHHHACGBGACFBBDGDBFAGAGACACF,False +352,23.0,10.0,18.0,19.0,18.0,25.0,14.0,15.0,GFADHDHFCGCBFFFHHEDFDHAEEFECAGBGEAHAHADAEGCBFBFEGEFHHEGGCFCHHAHAHEBAADAGBEBEDEDGFEFAFADADFGFAFCECECFFAFACACHCDFDADCDGGFDHCCCCDGDAFBFBEADBDAECF,False +353,28.0,26.0,15.0,29.0,24.0,17.0,31.0,29.0,EFGDADGCGBGBGBEAEHGHFDDEDEDEGHGEGEGHGHEHGDGBGFEAEGDCHCHDHFHEHAGDHDFEBEBEBEDCDCACAFGFCABFEGBGAGHHBDBABABHHAHAECEAGBGBHBFEDHCFCDGAFDHBEACFHHGDADHCFCBAAHFFGFDADBBEBHACABAHGDGBEAFABDBGGGGDDDAAHDDDHCHAABE,False +354,2.0,5.0,6.0,7.0,4.0,6.0,4.0,6.0,BHGHAECCCFADBDHDEDBFBHDCDCDFGCGFGFHHEFEB,False +355,6.0,5.0,6.0,6.0,6.0,7.0,2.0,4.0,HFHCGCGBFEAAAHAFBCBDEDEDEDCDFFABBCFCADFEHE,False +356,6.0,7.0,14.0,10.0,18.0,19.0,15.0,16.0,FBEHFGEHFDCDGGGEHCDCDFFFHBABDFDFHCCFEFECEHEFCAAGFGBCBFGFEBCACACDFFGHGBEHEHEHFHCCEGEGEGECAHEDEDGDGEHHHGHFF,False +357,14.0,24.0,11.0,19.0,13.0,13.0,20.0,12.0,CAHGEBBDBFBEGHAEDBDHDGDGECACACEFBDBFFGADBHBCCDCDHDEGEAFAFEGBFBABHFHAEDEDGHGBEBGBGBGFFBCGEGDAFAFAHAEBCGDDAGHHBCBDBDBFBDBDCGGGGH,False +358,14.0,23.0,16.0,16.0,14.0,16.0,6.0,16.0,HBCBHFHFHDBAGAEDCCCBFDFHFHDHDHGHABCFCFAGEGBBBFDADADBEBHFCFDFCBADDBCBCBCAEGEFCBABAFAHBFBEBEBCCEEHEDECBFAEHGADHDHEHBDEFBCDA,False +359,13.0,21.0,20.0,21.0,14.0,16.0,20.0,15.0,GFDBDCACAEBEBEBHBCBCECEGACHCHAHAGGBADADBDFCFHGDGDGEBHBDGGFGFGDBDAGABDGDGEHFDAEFFGFDHEBCCDCHCFCECHGDBCEHEFDFDABEBGDGHACFFBDCEAFGDBCGCBCFHBHBH,False +360,2.0,2.0,1.0,1.0,3.0,6.0,2.0,3.0,GFFFEFEBDBEHGCAHAHFF,True +361,14.0,17.0,14.0,17.0,23.0,22.0,11.0,18.0,DHACABDDDFEFBCAEAEAEFCFEFCFDFHFAFBCBCHGHFHEAEGBHBGCFCHAEBEFECECGFEDEFCCHAFAFAFADGHGBGDHDEDAHBHBHGEEBDHDBEEHGDEDEFBFBFHFGFBDAEBDGCHEEDCHB,False +362,7.0,7.0,14.0,4.0,6.0,6.0,6.0,3.0,CCBCGEGCAFAEADAGFGFCFCBCGHBBDBCGEAHAFCDCACBCHCEEFECBD,False +363,10.0,8.0,17.0,16.0,17.0,20.0,8.0,12.0,FEADABEGEHEBEBECFCDCHBHCAEEGHCFGFGFHHEFEFDFGFDECCACHFFFCDCGADAFGDCDCDCEFFFFAHAHBEECCDADAFFBEDEDEDHCFCDBHGHDB,False +364,8.0,4.0,4.0,12.0,13.0,9.0,10.0,11.0,FFHEHDFFAGEGEHEHFGDDDEDECEDABHFGFGDGAFADAEECGGABDBGHHCDCBGFDHDHAEAEHEHE,False +365,6.0,2.0,5.0,1.0,4.0,5.0,1.0,5.0,FEACAGFEFHCEABABAHFFEHAHCHCDC,True +366,11.0,5.0,9.0,15.0,4.0,9.0,12.0,5.0,CCFDEDFDFEFEHDBDCDHGGGGDFDAACADABFGCBCAGAFDFCGCGAHAGAHDBDHCGEBFDADADGG,True +367,22.0,11.0,14.0,10.0,20.0,19.0,35.0,19.0,DGGGBCECGDADABABHEHBHGAGHGFAFAGBGBGEEACACFEFGGGEFHCDEEBEBAHCEFFFFHAHAHGFECBHGGEGEHAHFGBDFHEEGCGFDAAAGEGAGFEFHFGAGAGDHAACAGHGCGAGDGBFHFGCGCECEHFHDGEGCD,False +368,2.0,3.0,4.0,0.0,3.0,2.0,2.0,2.0,BCECECHFHFAGEGBBCA,False +369,2.0,7.0,10.0,3.0,12.0,8.0,6.0,9.0,HHDHDCCEGEFFFHCBBHDEGEHEFEFEFEFBCBEBHBCCGCHEHBGGACECEFGAC,True +370,17.0,20.0,13.0,14.0,12.0,20.0,18.0,16.0,HEFEBECCHDECGCEBBGCDBDBDGFGFAFHGDDFDHBBBFAGDFAGACEFHGBFDFHFHFHCGBEDHFCFCFGAAEDECEFBFAHABACAGAGACAHABFBFGEGDBFBHBHDHDGBABAGCGEBAHGH,False +371,14.0,16.0,16.0,7.0,13.0,5.0,11.0,14.0,GBGBEHFHFBBBECAABDEABAGAEDEDBCEGECCACAGACACBCHCECEGABDBEBHBHFHCDAEADHCHCHFHCEABBCDHEGFGCHBGGHGHA,False +372,9.0,15.0,11.0,10.0,12.0,17.0,13.0,14.0,BEBEBGFFBFGFDFGCGCGFHDGGCFAFAFBFDHDEAEHEHAFBFEGHHEBGAGCHHHDDCECGCABFBFHFEDEDHBBCBGBCAGACAHBECEDDHBHFF,False +373,14.0,9.0,8.0,14.0,6.0,19.0,18.0,14.0,BHEFAHAHDDDDFBFDFGFEFHGBBFAAAGADHGBFCDGBEFGFCHHGFGHGHFHGEGAGEEAGDDABGGCCCBHBHCHDFAFAFAFGFDFDADADCGCGHF,False +374,13.0,6.0,13.0,5.0,8.0,10.0,12.0,6.0,CBGADAHAHAFAFGCGFGCDEAEADADCBHDFAACCCAFHBBCEGEGECFHAEBEHCGFGFGEGCGCFCGABF,False +375,8.0,5.0,6.0,3.0,11.0,9.0,8.0,4.0,EEEEHFFBFGGCGHGEBABEEFCFCBHGDBHFAFAFDFGAGDGAECECECAAAE,False +376,6.0,8.0,6.0,9.0,8.0,5.0,12.0,5.0,AEGEBACACHCGGHDBDBCEGEBEBHFDDGDCDBDBEGCAFBFGGGEHEAADFDFHGGG,False +377,2.0,3.0,2.0,5.0,6.0,4.0,2.0,2.0,EDEDECEBHBGFGAEADFHBDFEFDC,True +378,18.0,11.0,12.0,20.0,13.0,19.0,14.0,21.0,GAEHGHAADADADBFCECDCFCGDDFCGHAADFFFGHBHFDCDBFHFHGHFAGAGABADDHAEDECFFFAFAFDEDEBABFBGGHBCBAACBHHHFFEDEDADBEHFHGCGEEDHDCDGHGHEHEHCH,False +379,15.0,10.0,10.0,14.0,7.0,13.0,13.0,11.0,FHGHGHBBCDDDDABABGCEDADCHGAAHAFCFBDBDADFCFDDHCHFHAHCHCBCGGAACAHGGGGAGBEDFDFEAGDGFEBEFFAFAEBEF,False +380,20.0,20.0,27.0,28.0,18.0,28.0,19.0,15.0,FAEAEHHHHHHECBHFFFCFCDAGFGDEDCDCBGFFCGBGEGBAEAGFCADGGBEBEFHFDCBAEFDFDEDAHAHGEDAGBGFEBEGFDDDFDFAFCCCCCCBCBCGCGCACDDBFAFBCDADCDEDBCBCGHGFGBBAFDCDHBHDDBDCECACDFDGABFEDEAEFHHAAFFF,False +381,9.0,4.0,8.0,8.0,10.0,3.0,5.0,2.0,DEDECFCECEDAAACHEGDDFDFCACECGAABDGCHBEBGDGBAEAEAE,True +382,28.0,23.0,23.0,25.0,22.0,19.0,22.0,24.0,EBAHHEDEDBDHHGADFEFEHDHDGFFDFDADHDGEACBEHEFGDGAGAGEBCDCBBAFECHGGBHCHCGGGCGAFCHCHBBEBFBFHFCGCGEDEAAADABABADFEFDCDCECDCHCHCBAAAAAAHAFEGEADCCFHFEBEBFHDHFAAAGCBBBCDHDEDFBEGHCBDBGHGCGHDEAGABA,False +383,4.0,5.0,2.0,2.0,4.0,7.0,4.0,2.0,FAFBFGCGAGAGFBDEFEFHABFBDCHEBE,False +384,23.0,10.0,11.0,21.0,17.0,14.0,20.0,15.0,CBEFFDDBFAGHDAGAGAGDDBEGCCCDCBHHEAEFGFEEEHEACACAGAGBDAAHFHFAFADEHCACGDAEEFGGHEHBCDAGAEDEBFGHDHEHDHFHAGAGAGAFAFABBCDGGGDBDGDEDEDFDHD,False +385,16.0,15.0,15.0,12.0,17.0,20.0,20.0,23.0,FGBHBHAHAHBDFEFEBCAEEDEAHBHBHEFDCBAFCFAFAGHGHGACDHBCAEHGHBABFCFDGDFDFHFDBGFGHHACADACHCGBEBEHEACGEGFGFGDGEGEGECEADACBGFHHDFFHFHFGGBHCGCEEHC,False +386,22.0,28.0,19.0,25.0,19.0,24.0,12.0,27.0,BHDGBHDFDFDBABGDHAFAECECBCBCFCBEBHHHEEEBAFDFAFADECBDFDFAEHBHEHEGEADHHHFHFHDBFHAHADADFDFCAHBCGCDCBBBGBFAFCFHAGADDBFEFEAAHCDCECBDFFHFHBHBFEDCACAGEFDHGBEHGBCBHEEGAGHBDBDGHADADCBCB,False +387,16.0,23.0,23.0,12.0,27.0,6.0,20.0,14.0,EDEBGBEBCGGHCACBHBEGAGHGCGEGFCHBDCHGHBHGDADADBBCHCBEBACGEGEGEBABABDEEHECCCCBBBGAGAEAGFGHACCBBABAGFBEEEEEECGDDCDHEEEAEAECDCECGCFHFCBCEADDHEBFH,False +388,29.0,22.0,29.0,26.0,26.0,22.0,19.0,18.0,CECEGHFBFDDCDHGAFBGDFAAHACACAEEBEACFCAEECCGCGCFFFABGBGDCDGDEAEABHBHBFBHAHDCECECHFEFBACDDDEHAGABADFDFDBDBDECECEDHDAAAAEBEGAAADGFBFADACHEAACFGFGCGEHFHFCCCDGGBCEGFAFEBHCDAGBCBCDCEEGDBDBDHFHEBEHH,False +389,6.0,5.0,9.0,6.0,6.0,10.0,3.0,6.0,AFFFACCCEHHHHACDFDEGCBCDEDCFBFBDBFHFHADGCGCEFAFAEBE,False +390,5.0,5.0,8.0,6.0,3.0,4.0,2.0,9.0,CHCGBFDADACBFDFCHHDHDHCGCBFAEAEAECHCHBBDHH,False +391,17.0,18.0,29.0,20.0,13.0,16.0,17.0,22.0,GDCDGHHBEBFCFHGHAAAHBCDCDHFHEHBDDDDDCDCACHEBDBCBFDACBCBHACCDCGGGGCBCFCFBACADHHCFCADHHHGCBBGDGCGEEHEACAGGFGCABABDBEECECECFAFAGHHDHDFBFGFHECEFDFAHBHFGCACE,False +392,4.0,11.0,10.0,5.0,8.0,5.0,3.0,15.0,HHHHEEDDBGHGFABEBECCBHBCBEDECBCHCBEFEHDBDHAHBHFAGCHCHCBCAHFHF,True +393,5.0,6.0,6.0,2.0,4.0,4.0,5.0,6.0,HGFGHHHAGCGEFEBDFDAAHAFCBCBCECBGBEBHCA,False +394,21.0,28.0,17.0,22.0,17.0,15.0,15.0,14.0,DHAAAAFCDBDBDGGABBBCHCACGHFBBBBBBBAAAAFBBBBBEGEABCGFDHEHEDBAADEDEDEHCFEBEGDHFGGECDCHCHBDCEFEHDBDBDBDCECGCBFDGBADHGGFAFAFACEGEFDFBABFFEGDAACACHEHDHDCG,False +395,17.0,17.0,23.0,13.0,25.0,16.0,32.0,27.0,ACFCFGGGEEHEGGDEHBACACECEFEFHDEDFDGEGBGFHCCACEEFDACHGHGHBEEHBACCCCHCEFDAGAGEGCBHBHBGGGDGCFAHGHGHCAEFBBBHBGBHHEHEBGGEGEFHFHFHGHGCFCGHGDEDAAAGCBBBCHAEAHDHDFGGGEGBAHECDFDCAE,False +396,2.0,4.0,1.0,7.0,6.0,10.0,8.0,9.0,GCGFGFGHBFAEGFHFHGBDHEFEDHDEFEFDFEFBGHHAHGDBDHD,True +397,12.0,14.0,13.0,17.0,13.0,20.0,12.0,15.0,CEBHFCBGHGEGEACAHBHBDBGBADFDHDFDADHHEHFHBAAFACECECEDDGDGDCCCHCGBBDGFBECGDGACFFFFFFDHDHAEFEFBBGBFHFHECAFDBEHDFAFAEGFD,False +398,28.0,19.0,7.0,24.0,27.0,19.0,20.0,15.0,DHEAEADDHGAAHAGEHEBDBDHFCFEFEFEGAGHGBFHECAAGDCDADFCHDADADFDHGBGAEHDGFBFAFAFEFEFEHCAAAGGBBABDBCEADADFEGEFHADEGGGEGEGBGBDADEEBDBDHEEEDADEBBFHEEFCFEFAAAGABABDBHBG,False +399,0.0,3.0,1.0,3.0,3.0,3.0,0.0,4.0,DDHFBFEFDHBHCHEBE,True +400,14.0,15.0,8.0,10.0,12.0,16.0,15.0,13.0,BABABGHFHEHEAEBFGHDBCBGDCFFGAGDGFEFEFEFHDCAGAGHHAHACBCBGAGEGEDBDHDEBCACBHAHCFAFEBEDFFFBFGEGFABHGDADFBHG,False +401,11.0,5.0,16.0,15.0,7.0,18.0,6.0,17.0,EGDHHBGCGFFFFECHDAFAFBFDHGHAACFFFAEHBFDFHEHDFDFDABBEAFCCCCCCCFHAGADDDCCEHEHCHDHAHFHCCCFDHDHDADG,True +402,3.0,10.0,24.0,13.0,15.0,13.0,11.0,19.0,CBBEDHAHBDBDBGCECHHDHGHDCGCGEHCHCGCEEEEHFHFECEGBDDFBHEDBDADGFHCHCGCBCDCEAFGFGHGHCECFDECCCCCDHHEBFHFCFCEHFFCF,False +403,1.0,2.0,2.0,2.0,0.0,1.0,2.0,2.0,DGDABGBCHCHF,False +404,5.0,16.0,6.0,12.0,8.0,5.0,12.0,9.0,DGDHBCBCHGEEHEFGFBAGABADDCDBBBBBGAGEEDCDGHGHFHBHGGCEEDBDBDBCBDBGFAEBHFHGD,True +405,21.0,16.0,12.0,16.0,13.0,10.0,25.0,18.0,GFEFBFGGBGBGBHFHEBEBGBGFGFCEAGCDHAABHBEGCGHDHAHDCEGDGDBFGCAAAAEAGADFDGDAACACECEBFDHBAEACHGHAHDEDEFHHHBGEGACDBAGGBCBHHCDGAGDGHGHADAD,False +406,4.0,4.0,3.0,5.0,1.0,0.0,4.0,3.0,GBDDABCBCGDGDCHBHDHAGAEA,True +407,16.0,7.0,6.0,14.0,13.0,6.0,14.0,8.0,BFCAAAAAEFEBDFCFCADGDBDBDAGAHAEDEGHGHGFDBDGAEHEAEAGCEDHAEADGDAFADGGEGHGHDEBEHDGBGCCE,True +408,12.0,15.0,11.0,21.0,18.0,14.0,12.0,11.0,DBDBDBDBCBGGABCEFEFGGDBDAAAEHEFEBGBECCFCBGEEAEHCBFEFHFCEBFBHGADFDACABEBEAECDCGFDDDDDDHGEGFDHDHDHFCDDEDGAAFAFHHGHEE,False +409,20.0,21.0,28.0,22.0,20.0,26.0,20.0,22.0,FCFDFHADGDHDHBBCCHHDHDHDGAABAGCGCDCDFFFAEAFBHHGHCHEFEGBDCDAAHABBCFHFEEGEFFFCHCDBDEDEFEDAFAFABEHCCCEBHBDGDECCAAACDGFFEDHDFBHBAGAEAEFECGGGCHCDAHBGBDBCBEHGFCFCFCFCEGEGHFCBGFGCGCEABBB,False +410,3.0,1.0,3.0,3.0,0.0,0.0,1.0,2.0,DGACBHDHDCACA,True +411,10.0,24.0,18.0,15.0,16.0,10.0,24.0,18.0,HHFBFECHGHAHFGGDCBCBCEGHGBBAAGCCHCBDBGBDHHHBFBDBGGCGHGABABACEHEHCDGDECBAAEFGGDGEADDDHDHBEBEGEFEGEGCGDGDEDBCCCHCEBEDCGFGHGEGFBFBACHBBBBF,False +412,7.0,7.0,14.0,10.0,10.0,6.0,9.0,5.0,GEDFDFBAGCDABADDGAHEDEDFDCDCDFHCBCBCGCHBGCFCAEEEEEGEGCCCHHGCBEBCAGAF,False +413,1.0,1.0,2.0,0.0,2.0,2.0,3.0,2.0,FGCGCHEHEABGF,True +414,3.0,7.0,4.0,3.0,7.0,6.0,6.0,8.0,HCHGEEBABABFBEGFGAGBDFDEHEFCFBHHHFHCHCBEEGGD,False +415,17.0,22.0,23.0,22.0,24.0,17.0,20.0,16.0,BCBGBADDEHEBECCCCDGAGEGEAACEHEHGFABAEHECECFCGCECDBACAHADECGCBBFGFEHEFGDGEGCGFGDHDCBCAFGDGDAEFHFCFBEEHEBDDFHHHBAFAHDEDGDBDEDECFCFHFAGCFFAEGDGDADCBBBBCGHHABBBBBDED,False +416,23.0,23.0,29.0,23.0,28.0,15.0,36.0,18.0,HDFEEHAHFECBCGDFDFBAGABBGGADFDGEGECECGDHCECECEDEDACACGEGCGFBCBCACEEDEGGABHEDCHBGGGHGCGCBDBCCCEHEBGBCDDGGHGEFEGBBBDBAFAFAGBFFHHADEGEDBCCCACGCDCGEAHAEADGGGDGDBFBFCGCGBGBGACAHAHGEFDADEHEHAFGHBHDEAEA,False +417,6.0,3.0,6.0,6.0,13.0,9.0,7.0,12.0,HGCCECEAEHGHGCFAFHDDBDEGBGHHEEDAFGFHEHAAADBCHCGFEEEHEHEFEFDFHF,False +418,7.0,7.0,9.0,13.0,10.0,16.0,6.0,11.0,HEFFFEDECCHHBHFDFACACEDHDBDBDBDFCFDEDEBHGEFFAFADAFHGBGCGCFDEAHDFDHGHFHCGEFEFABC,False +419,6.0,2.0,4.0,3.0,3.0,0.0,2.0,0.0,EEBDBAAAACACEGGCCDAD,True +420,20.0,21.0,13.0,17.0,21.0,27.0,25.0,13.0,HAGAGAECCFDBEADDGAGFFDCBFFCABGBEBAGCGBFBGEGEFDCDEBFBEDCAHBHBDFDFBADGFFEGEGEFEFEFHFBBABAHHDGDGBGAGFGFGEEDEDAFAGDHEACACFFGFGFGEDECBFBFHHHGEAFAEAHFBEBGBCHCHGADC,False +421,9.0,14.0,14.0,8.0,6.0,14.0,12.0,12.0,FHFDFDBBBGBEBCBFDGDHFGABCGABBGEAFAHACACHDDFHCBBFHFHFGCHCHGBBHHGCGCACACHCEFEFADDFEFEGGCGCB,False +422,2.0,4.0,4.0,2.0,2.0,3.0,4.0,6.0,HFCFCECBGGGDGBEHFBAHAHBHDHC,False +423,19.0,10.0,8.0,8.0,6.0,9.0,8.0,8.0,DEABABCFEFDAAABFHFAFAFADACCGBABAGHBABABAGHEHCGDGDCDCGEHEGDAABAEHBAGACDFFCFHH,False +424,22.0,16.0,21.0,30.0,13.0,19.0,17.0,12.0,BCBEBDAEAEAHAHGHCBCAAEADGFGDGDCACFCDEGCDHBCADDDDDEABADADADAEGBGBHCGFAFDCDBDFACDBDBCFEHEHAHGFGFGFGECHFHCCGDGACDFDECFDADEBHFFDFDFBFBEHAGCGDFCBGDACBCFDAD,False +425,12.0,15.0,7.0,11.0,10.0,19.0,9.0,9.0,CADACAFHFDDCDBFBDBEBEDEHFABACFFHHGFDFDGDGHAHACCBEFDFGEGEADFFCEGBABAEHHBHBGBEBABGBEFFFFABGFFF,False +426,10.0,14.0,11.0,11.0,11.0,17.0,18.0,9.0,BFBAAEFEHCHGAFEBCFCGCGBGFHFCGGAFAFBFCFHBBFEFEFEBGCECBGBGCDFDBDBDGAGEFEGHGHAADEGCGHDBAEGDDDDCDFGFGABHH,False +427,37.0,20.0,35.0,16.0,24.0,26.0,23.0,17.0,AGAEEHGHGCCCGBGCHCHCHFGGAAAEAEAFHCHCGCACADEEECBABEFEHDFBFEEBBBCEFAFADACAFFCFDHDGBFFACDGDFDBBBCGCBAAAEAECGCDHFBDBCAAGACACAFAGGBEHECECEABFEGDFDHHAAAACHCHGHCHABEGCGFACCECFFBFBABAGFFDAECEDEFFACGCGAGCDFD,False +428,16.0,17.0,31.0,28.0,15.0,17.0,26.0,26.0,FGFCCACBEDEDBCGCGFDCAAECEAAFFGGGGHCHCAGDGDBHBHFHFHFHDHAGGDDADHDHBACGCGEDHBCDFDGDHDCCCBBBBGCCCCFBDDDBCCCHCFEHHGFBFCCAAGGDADGDHEHAGCGCBDBFBFEGAGEGHCFDHHHHEHEBEHDFDGDHAAECCCEDEDGH,False +429,8.0,4.0,6.0,7.0,12.0,5.0,7.0,6.0,AAHAGBFHFCEAEBECGFGFGEEECBCDCAEHEAEDEDHGHBCFDGEGDHDEDAA,False +430,5.0,7.0,8.0,4.0,4.0,3.0,11.0,4.0,HGDCHCBCBFGAGBGBEDHAEAEGFGCGEGAFCGCGDHDBBBCCGA,True +431,8.0,19.0,9.0,16.0,16.0,15.0,11.0,12.0,FABCEHHCGDGDFDFHFAEDGDFDFBBBBFEDEAGBEEEFEGEBEFDDGBBAAAFHFHEEDCDCGEDBDAEHEHBHBHBFGCDCHEDBFBGHGFBFBCBCGCBAHD,False +432,25.0,23.0,17.0,34.0,27.0,19.0,18.0,34.0,GBHHHFEGGFGFGHBABDBDBHGGEBBDEDHHHHAHFHEHFFFGBDDEAAAAADCDHACAFDBDCGCGDDDHAGBDHGHCHABAFEFEFEFDDBDBABGFAFEEDEDEAEBFDFDHAHABEBEDDDFHCEFEAAAECCBABHDADHCBFGDHEHAGBDHHEHEDEAECEDGCEEHDDGHCHCHEDDHBHCHCACBCG,False +433,11.0,10.0,8.0,8.0,5.0,5.0,7.0,5.0,GEEEBADHCHEBEACABDBDAHABABABCDCGCDABFDCACABGGAGHCHFFDDGFGFB,False +434,8.0,2.0,9.0,3.0,9.0,11.0,9.0,7.0,CECFFFHGHBHCFCFBFHDACEEFCGEDEDAAAGCGCEFFAAGGGHFHFHEGEGECAA,False +435,15.0,9.0,12.0,17.0,12.0,13.0,11.0,8.0,FEFHFAFEDEDBCGGFBHACGCFCHADADAFAEAEADHDBDFHEDEDBBGBDADAGAGEGECCHEAACBCDCEGFGFDADGHHFDFCCCBDGEFADB,False +436,9.0,4.0,4.0,2.0,2.0,7.0,7.0,7.0,HEFBABCEFAFABGGAAACFCFGHBHACGFGAGAGHHDHDHF,True +437,13.0,14.0,15.0,27.0,27.0,6.0,29.0,26.0,DDDEHABAHEHAHDCBGDHFCEGBBHBHADDEAGGEGDGDGCCDCDBDBHBHBAAHGGGGACECEGGGECCDGDGEGADADGFHEEDEGACAGHDDDFDFBEHCHGHFHEEEHEHEHEHEGEFDGDGHBCCEDHBCGDHEEBAGHGEGEGEDHBHCD,True +438,22.0,9.0,13.0,21.0,26.0,17.0,18.0,21.0,GAGEHFHCEGEDAFAHAHEDBDFDABAHEDGDBCAEGDDDGGGGAGEHHHGCCFHHBHBHBHAGECAGDGDGDGEHDFAGCEEFEHEAEAEFFCECFFFBDADFDADADAFEEEEAFAEEBABAHEFDGHEHFCDCDCECHCHFEAH,False +439,24.0,19.0,22.0,19.0,24.0,22.0,19.0,24.0,DCDCAAAAABAFGFDFDHGCGCGBDACCCCEHFACHEDAAEABAHABAEFHFCFCFBBHFHEHEGCGDHFECBBBGBEHEAEAHDGDGHCHFBFEFEBEDFAACDHDFBHADCCEHEHDBFGFHDHDGEGADADEDEBECHFGGAGEFCCBCGFBBAGEHFHGHEHEFECBGA,False +440,23.0,14.0,11.0,16.0,9.0,11.0,13.0,16.0,DCDGBGBAAHECEFGFGAGHHEDGBCFDFGHGEEFADAEGFBAAAABFBFDAACCCEDHHHDDAAEBHCHABCHAHAHABEDGFGBGDDDDDDGAAHACACACABFFHBHBHB,False +441,5.0,9.0,7.0,7.0,5.0,6.0,6.0,2.0,CFDBDGCADBDBDGAAEAEBFBCBFGHBEGDHDECECBCGFGFBFAC,False +442,21.0,17.0,17.0,31.0,26.0,21.0,12.0,20.0,AAAGDEAFCHCBEDDBDBDHCAAHBDBDADHFHFHFHFHFDFEADADHHCHDDCFBFACHDEEEDABADAFEFHCACFFFEFBBEHGDGEGFDDCDGEGECCCCCFCHDEEECGCFDEDGBBDBGGHBFAFEDADFDHEHDHAGDGDBAEEEBEDAHAEBEBEAE,False +443,22.0,20.0,27.0,22.0,26.0,31.0,22.0,17.0,EDEAHFDFEBGFEFHGAFAFEDEAHDFBEDACCCBCBAFADAHFCGHGHDCDCGGHBBGACADFEFEFBFBFBHBHAHAGGGEGAGACECECBAEFFDEECDFECECBCEHDFCABHBCGDHBFBFBFAEDCFFHFCFGFDEDEDGFGFGFBCHEGGCEDGCCHDGFGCCCACEDEAEABABADFDH,False +444,25.0,15.0,17.0,18.0,21.0,13.0,21.0,25.0,GCAFBBBBAFGHBACAFHCECHBEDEHHHEDAHABCGDEAAABDBHAHBEGGDGACDBGGGGHGHGCECEFHFCCGBEEEEEDFCGDGDADADCECBFFCAEAEADGDHAHAHEHDHAHEFEHDGFHFHBDDAHAGAGAGAGEFBHECFCACHDH,False +445,4.0,5.0,1.0,1.0,6.0,3.0,0.0,1.0,FEBBABEBEAFHFEAEAEBDC,True +446,3.0,5.0,3.0,4.0,0.0,2.0,5.0,1.0,DBDAGBGCGCGCBBBAGFDHDFA,True +447,27.0,17.0,19.0,29.0,21.0,26.0,19.0,16.0,AAEEEEFDFHEADAGFGFGAGHFABBBBDADAHFDGCHFDFAFGCCBFFHDHDADEBHGCAHAFCCGCHEEADCBFFDFAFACAEECDCDBHBDCCEDEAGABDBDGGGGHFHFHDEAFDCDAAABAGCGFDFEEEBGAGAHBGDGDFDFDHHACCDCEBEAECEFEFDFDBDB,False +448,12.0,3.0,7.0,7.0,6.0,6.0,10.0,15.0,GCACACAFHFHGHDHAHDDEDCFAHACAHGEFHBHBFGDEHEAAAGAGCDAEGEBHDGFGHHCHGH,False +449,27.0,20.0,31.0,20.0,16.0,31.0,25.0,16.0,CCFCACAHBDGCGCBCGCDCBBEBAGFFFCFCDCBHBEFDFDHGGDCFEDBDFDCDCFFDBAECHADBCHCHCAAAAFAFADDGFCECGCGDDEHGHFFEHGHGFGFGAEFBFEFDBHAFDGGCFAFHHHBHEAGAEAEABGHFAFACACBCACGBBAGACAFFGFGFDBCBCGEEEECFADGBGA,False +450,2.0,7.0,4.0,2.0,6.0,1.0,3.0,3.0,DGCGCBDBHCECHBEGEABFBHEAEBEB,True +451,8.0,7.0,6.0,1.0,2.0,4.0,4.0,3.0,FGFHEABCCCDBABAHCHEAGCGCBAAAABBBFGF,True +452,12.0,16.0,17.0,11.0,29.0,15.0,19.0,16.0,EGDGEGHCFCFDDBECFHFHGEBEBEBEBDBAHAHADCEEEEEEEBECCBBBGDCDCFGHHEACAGBGHFEGEAECFDEGFHCEDFDFDCBHEAEAEFBGCGBAHFHGGEEBFGFGEHAGAGAFCBHHHCCECEG,False +453,4.0,3.0,6.0,2.0,6.0,8.0,4.0,3.0,CCFCEEHCHBDEFAFAFHGDFEGEFBFBFCECGAGA,False +454,17.0,13.0,25.0,22.0,19.0,16.0,28.0,27.0,AGAHHCDEDGGGDHHFEEGEHHCGGHGABCDCDAAFCFCGAGCFFFHEEEHEBGBCFHDAEEBDCDCGCGCBHBFCFHDHGBGDHCHFHBHDHBEAFCCDEDAGCGCDCFFHGHGHGAGADACAEABFCECECEBEHAGAHHDGDGHGHGFDFDEBCHDDCDGBGEA,False +455,3.0,8.0,5.0,6.0,3.0,3.0,1.0,4.0,ADHHHDFFACBCBCHCBDDGDBDBEBEAEFCBB,True +456,17.0,25.0,25.0,21.0,21.0,26.0,24.0,21.0,GEGBFBFBFBGAHAFACDEDCCHFFGBGAACFCHGFCFGHDAEFEFGFGHEBEBDAFGFAFCCBABEHCGFEDEDGBGBFBEHEGGCDCDCBGHDCCCDFAGBHBDEDHCHCHEHCBCDDDDFBEEEEGGBFCFCHAHACGFBBHDHBABGBGDGDFAFAECECEFDFDBGCHBAAHHEH,False +457,12.0,10.0,8.0,8.0,4.0,11.0,8.0,8.0,DBDFDFCCCHBEGFBHEFACBDBGHGBFAFGHAHAHGDDDCCACGCEHGFGFBFBABABDHFAAAEAFA,False +458,20.0,11.0,18.0,22.0,26.0,28.0,20.0,28.0,BFGHCHEAEAFFFFGABCFGFECECECECHCHGHDHAHEEEFHAAFBCGHDHDHCABGHCFDGHGACFDDDBCGDDFGGGGEEABGFAFEHAFEHAFAEAEABAGFDFEEHEFECDADHDHBHEHDHCHFHDHFHGDDDDEDEFEFGDCHCECEFHFAGBFFEFCADGBGBHA,False +459,18.0,25.0,19.0,16.0,13.0,17.0,21.0,14.0,CACACDEDBCBHAAGHBHBCEDEDAGGHDFDEDCHFHECFBFACAHAGGGGGAGDFBABFFGFBHBHBGBHBACABHBGCGBGEFADCDCHAHDHDBACABBBGEGEFCFBGBEFDFABABFCEGECDCBCGDBEGFFCFDGE,False +460,21.0,19.0,19.0,30.0,29.0,19.0,23.0,32.0,FDEDECCDEEHFDFEFEFHAHDCGCGCFDDDCGAGAECDHBEBAHGCGEFEDHDHDGDBHBADCDCHHFECHBGBEHADBDHGHGHGHDHFBGAGHBFBAECGGFEFEFDGDCDAEGEBACHGGDDADFHAEABBGBABDFDFABEDAHBHAHAEDEAEHEHCFCHEHEHBHBHGGCACAHEEEEFDFCGDH,False +461,9.0,19.0,19.0,25.0,19.0,17.0,20.0,16.0,BEGCGDAEHEDBDCEHECACAEAEAFCEGHGHFHGHCEDDDHDEGGFEHEFDFGFDBDBDGDEDCFCFHECBDHACCBCBFGDGCHBHDDBGBGFCBCDDGDACFGGGGFGBEBEGHDBDFCFBFDFDBHHAHAEDFBCBEBEC,False +462,9.0,14.0,11.0,15.0,9.0,10.0,15.0,17.0,CHCHCGCBEBDHEHFBGDGDGDGDBDGEGCHHBDBDACFCHGFEAHFFDCGAGBFHEDEHHAHAEBHBHGAGBFBDBCFCBCBADAGEGHHEFDFDGDAH,False +463,15.0,16.0,16.0,16.0,13.0,12.0,15.0,14.0,EDEGEDHBHDHDACHCBCAHADGDGAEEHFGFGFAEGEDECGGAFAFDBCHCGCEBABABABDEACHCBABAFGEACFDBBCBEGEGCDCDADBDFHHHHHBDCDGBFFGFHCBCFG,False +464,20.0,13.0,10.0,7.0,14.0,12.0,14.0,15.0,HHHBDFFCHCGCGAGDFDGEBFBABAFAFHGHBAGEGEHBACFCEDBACCCABADAGBGAGEEAAFAFACGCFAHEHEDEBAGEHEHEGAGAEFHHHHABEBDBF,False +465,32.0,28.0,23.0,18.0,15.0,22.0,28.0,21.0,CAHHBFBGCACEGFGAAABABAGGCGCGEAAGCGEEDBDGDCDHDBBABAFABAEDBGCEDBDBAHABFHEDEDBFFGAGHHEGAGHEECDCFBHCGBDBDBFGFDFCFAAACACFGHGAGDCFGAGFFBHCHCEABHBFBFHFAFHFEFBABGBGBGHHHAHAGEFCCHBHCAGBCDCECADADAG,False +466,14.0,31.0,26.0,20.0,17.0,27.0,15.0,13.0,BBBBBCGFEFDFDFCCDCHHDAFADACCEAGGCGCACFFEGECEFECCACGEBAGDGHBABDBHBHFCBHFCFCAHDCDHBGFEEDEDFAFHHGBBFAFCCCFAFDFEBBABACHHBDBDBFBCCFFFFFFDBBBBBEBECEGEGDGDGEGCHEBCDFBBBDD,False +467,15.0,12.0,15.0,11.0,17.0,18.0,18.0,13.0,HAGECCBCFHEGGGGBGBDBGBAFACCFCFCBDFAAAAACEEEFECDFDCDCDHBGGGFGDABAGAFFEAEFHBEDEDEFBAHGCGCHFGFGFHHDHECEAEGFAFHHEHEBBGEHFDC,False +468,22.0,12.0,14.0,17.0,19.0,18.0,16.0,15.0,DADADADAHAGABAEHFGFGEGBHBGADHDGGACHEHCHGEFFBCGCAFGDGAEHEAAFCFGAHAHEDDFDCHFEFEDEBECABEFGBGAGCCECFCBBBBHAEBECCADEDHHHEDEDEDFFFFGDAAAFCF,False +469,18.0,26.0,29.0,20.0,29.0,19.0,16.0,15.0,CGCGCHCFCGHHCHCHCHCFAEAFFECEBFGDHDCECECHCFFDBDEDBGGEGAGEHBBCCACABEEEAEBEBACECGADBBHBDBEFEFEFCDDGCCBAHHFCBHBADAGFDBEFEFEAECBFFHABDBAEDECECEDBFBDBDBDACGEGEBADCDGBGDGACFEFBAEH,False +470,6.0,1.0,5.0,5.0,3.0,4.0,4.0,6.0,CBCAGGHDHDHDHFHFEECACADHCAFAFGEADG,False +471,8.0,12.0,3.0,4.0,7.0,8.0,8.0,2.0,GAAFBEGEFDAGEGEFEHGBCFFFFGBBBEBABABDBDBEBDHGCABACAGF,True +472,9.0,4.0,9.0,5.0,3.0,6.0,1.0,7.0,HACGCABHCEAFHBHDAAACFCBEDEDADAHFHFCFAFBCDCHC,True +473,2.0,1.0,5.0,2.0,7.0,3.0,2.0,10.0,CCHCDDGFHAEBEHHFACHHFHEHEHEHECEG,True +474,8.0,7.0,5.0,9.0,9.0,4.0,1.0,12.0,BCDHBCBADCDHHAHDHAHEDEDBHEEDHCHAFAHAHCEGDADEFEFEFABHBEB,True +475,11.0,5.0,2.0,1.0,3.0,2.0,5.0,4.0,AACDCFHAGAGAEBGBHBFEAGBGAAAHAHABE,True +476,25.0,30.0,25.0,21.0,26.0,22.0,25.0,24.0,HGHEDBDBCHEHEDEDEDEDCAHDCGCFDFGEGDGAGAGHGDGDCAAHABAFACBCBCEDEAEDEAGDFEBEBEHGHFHFCBBFGHGFEFBBBFHGBCFCEBABADHBCACGFHFACACDFABHEAEHHDGACHFBFBHBHBABGGDBABGFEFBHGHAHEBGBGCFBEBECGCACEFAGECACFDFEAECCBGHCDD,False +477,15.0,14.0,22.0,19.0,17.0,22.0,25.0,22.0,DFGGGFHHCHEHBGDEEBFBAAHGFGFGACCCGHFHBHCDEEFEFBFAFBFCGCEDEHEHEBFAFAFAFGCGCGDBCBFFCHCDDDEAEAGDEDECGDGABBHDHDFDFDGCGAHEHFHCHAACDDBHHACBGBGAGFFHCCGHHCCGDGDGCGEE,False +478,14.0,12.0,9.0,13.0,13.0,17.0,7.0,13.0,AFAFBFBDAAADFFBFBEHGFEFHAHFGDDFDHAHADABFBFHEHECCACGFBDBGAEHCDCHGHGEAECECEFECADFDBGBHBHEHDDFEFDBEAC,False +479,29.0,20.0,16.0,24.0,27.0,18.0,17.0,26.0,GEHHHAHEGBGCHCBCFGDGBFDHCCBCHFHAEFEGGDHDACEDDDCDFDFDHBAADHFHBEFEHCHCDFAFABAEGBHBABABAEHEAEAEDEAFHEDAGEBEFGCEDEFEDHBFFDFAHHDBDGDHEAEGCBDEDBAGAGAGAEAHACACAEAEBHAHGFGEBEADADBHBHFCC,False +480,11.0,14.0,7.0,9.0,18.0,15.0,6.0,9.0,FAFEGDGBBEFEDEFEFABAGEGEFFFBBCBEDABEGAAAFHFDEHHFBFDFAFCDCDEGHHCHBABCBEHEHEBEBEDEHABEFACDC,False +481,8.0,4.0,7.0,16.0,11.0,8.0,9.0,4.0,EEADADFDEAFBFGEGFGDGCHDDCDEBEGEGCFCHDAGCGDGAECFCEDDFDEABABADDDDEHFH,False +482,11.0,7.0,25.0,5.0,16.0,24.0,10.0,11.0,EAEAEACFCBCEFEGAGAGCCFFEFGBCFFHFCFAHACFCEEHCCFDFEEHBHFHAGFFEFEBDAGCGFAFEFEHECGCGCFCFHFHCCCBCDDBCCCCFDFHAECBHG,True +483,24.0,31.0,31.0,29.0,20.0,23.0,19.0,21.0,HAHEECBBBBGBECEFBFHHCHFHDBGBHEGEADAEAEBBFBCECFCACABHCHCEBFDFCFCFBFHHHEGCDCDCDHDCECGABADDDBAGAGAHEDEBBDGCBCFAFABAHCBCFHGHBDEDGBGEHCDCFCFCAHFBCDCDGDHABGFEBDBDBDGAFAGAFDDCEFABAFDDGAFEFDGCBABHCGDGDCDCAE,False +484,10.0,14.0,9.0,7.0,6.0,9.0,6.0,9.0,HCACBFBFCFCFHAHADACABDCHGHGCBFDHCBGBABFBDBFBEEHADADHBBEBADAGECEFHBGEGF,False +485,10.0,4.0,11.0,5.0,13.0,7.0,15.0,10.0,AEAEHCHCGCGCBEGEGFGBGAGFGEHAFGCHDECCAHADDFDFHFHEGEGACCBHDHAEGEGCGHBEEEGAFAC,False +486,10.0,4.0,4.0,3.0,10.0,7.0,9.0,8.0,HGHCFDHAFAECEFHFHEGECHDDACABAEEEGGAEAGAGAGAHFGFEHEFGBBB,True +487,5.0,6.0,9.0,7.0,10.0,8.0,5.0,12.0,FCFCFHFAFAFGEDCBEHHGGEHEHAGBHCHFEAEDEDBHADCBCDHDHDFBEBCCHCGEHE,False +488,11.0,11.0,11.0,8.0,15.0,8.0,13.0,12.0,CBABEBFHFGEGHCDCAGDGEABBCGGBBHEFBBABGBADEHCHCEAEAEGEFFFCGCEHDHDHECDCAFAGAGAGEHEGFDHCHEHED,False +489,22.0,25.0,26.0,26.0,18.0,25.0,28.0,23.0,BEBEBEBFFHDHDHCHDHCCGCFAGCHCHCDCGCABABAFCHEHBCBCDCGCEHAHAEGGABFDHEBECGCHCHFDADAHHEGFBHAHFDGDCCCHFFGGGGBFAFABGFEFAGGFGDBAHFEGEGEDBBEDDBHBDFDFGGCEFGFBFHGADADHCEGEGDGDFDBBCBCDGBADABAFCFAFADDDBCGAE,False +490,19.0,24.0,22.0,16.0,30.0,19.0,23.0,31.0,FGGAFEFECGHHEGEHEDEFEHAGFBFBFHAEAHAEAEACDEBBHCECACEGBBFBDBCHDHGCFEHHAHAHBEBECGGDGCHBHGFGBDFCGHGHDHBHBACACHBEAABDHEHDHFFBFHFHEBCDEDEDFDGEGAGADBCHFHABDBDCFAEAEBEBECGCGEHHCCBCHCEGEGHFCGEG,False +491,16.0,23.0,19.0,29.0,31.0,20.0,28.0,25.0,DHDBCECECAGFGBBEEEECEDEGHCDGGAFDFGFGCGCEHGHGEDFGCDFGFDDDCDEFEABDEDEBEBHBHBGGHBDBHAFABDGHCECGAEAEAGABHDHDHDHBBBGEHEFEDHBEEEGGCDEFGHGHAHAFCFGFEDCFEABHFHEBEBDHDHACBCFGAGFGHEHBGBCHFGDDADCDADFDECB,False +492,2.0,8.0,8.0,4.0,4.0,4.0,9.0,3.0,GEGFACBGAGECCHCHCBFDGHCCGCGBDBDBEBEFDFBGBG,True +493,21.0,13.0,20.0,26.0,11.0,13.0,10.0,15.0,AACGHHEEDBDBDCDCDBEBFBFEGDCEADDDFAFAEAHHHFAFADEDCHCBCAAGACDDDDDBCAGDCDBEHGHGFGABDHDHCCCCHADAEAEDHDAACAFAFBFEDGBHCCADHBGBDFCFCHCFG,False +494,4.0,3.0,5.0,3.0,3.0,7.0,4.0,3.0,AHFEBAHCHGFGFEFDADBFFCFCGCGCBEAD,False +495,0.0,4.0,1.0,1.0,4.0,0.0,2.0,1.0,BDEEBEGEGHBCB,True +496,6.0,16.0,13.0,12.0,12.0,13.0,12.0,10.0,DHFEEBAFCHCHCEFHABBCBCFGECECEGEBDCDCBBBBFAFEBEGGCGAGFHEDGBGEGCHEBDBHBHCGBHAGDFDFDFDFDHCADFDFGB,False +497,19.0,9.0,12.0,22.0,14.0,24.0,20.0,18.0,DEDAHEBAAGDBHHGABAGCHCDCACFCGCEEACBFAFAGEDDDHHHCHCGFGHBAGAFAHDDDDDGDFDFHFEEDEHFHEBFDFHBAGHGHFHFEDEDFDFDCGBFACAGAFHFEABGEGFGFGFECADAGGDGFFF,False +498,8.0,3.0,6.0,14.0,8.0,17.0,6.0,15.0,GFFDFEGGBEBHAEDGFAFEFDDDAFHCHCDCDGFHAHFHFGDHCEFHCHCFDHDHAFDFEFAFABAEHFHDHDEDH,True +499,0.0,6.0,1.0,2.0,2.0,3.0,3.0,4.0,EDECHDBGBGBHBHFGFBHBF,True +500,9.0,11.0,8.0,10.0,19.0,12.0,9.0,5.0,GCFDBACGFBFAAAAGBFAEGFGCGHEAGHDFFCEDEDEDEDECHBEGDDEAEFDFAFEBEHEHEDEBEBEBCBCBFFEGBCE,False +501,8.0,14.0,12.0,11.0,8.0,12.0,9.0,4.0,DBDBEBDBDFDAGCGFBCBCFFGCDCDEDBBBECECFBFECABDDAFAFAGEFBHAGAFCHCDCGHGHBFBEGEFCAG,False +502,5.0,5.0,5.0,5.0,9.0,6.0,4.0,8.0,FEFEBHHHAHABEBDDFDHDCAFFECEAHCBCEAEBHGHGCGFDEGE,False +503,12.0,12.0,13.0,25.0,16.0,10.0,18.0,21.0,GBGBDECCCFHHBACGDGDGDADCGCBBHDHDHDBDFDFDHEHGCEDEGEFAFHBEFFGCEHFFDDHDHGHGDAACAGBDHGHEDEDGAHCGDGDACEGAHAHDHEHEBEBCBFBEHEADDGDCAHE,False +504,10.0,15.0,9.0,13.0,14.0,7.0,8.0,9.0,CBEEFBBGBGBDBABADFBAAHEBEDEDGFCEBDBHAHBCBCBGGFDFCAGAFDGDHDHGEBEHFHECECEAHCDDEHEAEADCD,False +505,18.0,16.0,17.0,23.0,12.0,18.0,20.0,12.0,FGFABEFDHDHFHGDBDBGBGCACDDDHAHBHFFFBGCGEAEAGABHBGDGCECEDHFAGBDEAAHCEGHDEDEDFGHDDDDEFFAFGDGCFCFDFDACFCEAABGBABCBCFHGGBGEGAACCCCFCGBADADBD,False +506,22.0,16.0,25.0,22.0,25.0,11.0,27.0,18.0,AGCDCDHDBGCGAGDDCDGBGDCBCGFGHCECGHGAEFEDEAEGEFHGBCBCAAAAGGDGEHEAEDEDEBCBGFCFGDDEDECFDHDBEAEDEHGHCCCCABAFABCBAHCHGHCCDCEFAGEHAGAGHEBCHEGBHBHDHFEEEACACDEDEHGGGFBFBGDAAA,False +507,13.0,17.0,22.0,10.0,17.0,14.0,17.0,13.0,GGGCBBBEBHAEAGHDCGCDHFEAEABHCHGFGHGCCFFBCAAHEHEDCGCGCDADEHAHFDFAFCHCFCBDEEAEFHAHFCFABBDBDEGECEBGBGCGCDEEBEBFBEACBCGCGBGCFCF,False +508,17.0,21.0,24.0,12.0,17.0,20.0,19.0,17.0,ECHCHCHCGCFBGAGEBEBEBDCCFHFGCDFFHHBGBGDDDGFCFCGDGFAACACGFHDHGAAHAEBEGCCCFGFADADHBBBBABEBEBCGCHDHBGEHCACECEDDCFFAFEBACAEHEHBGBHEFAFBGHGFBCBEAEAGFFCF,False +509,4.0,0.0,5.0,5.0,1.0,0.0,3.0,4.0,GHDCDCDCDCAEHGCDHHAAAG,True +510,10.0,11.0,3.0,4.0,7.0,2.0,18.0,3.0,HAGGGGAFAGCGEGBGAEBGGEBEBDCEGDBDADEBEGAGAGBBBCGGBGAGHBHAFA,True +511,2.0,4.0,2.0,2.0,1.0,2.0,3.0,1.0,DEDFHGABBBBFAGCGC,False +512,2.0,4.0,2.0,1.0,1.0,1.0,0.0,1.0,HDBABCBCBFEA,True +513,4.0,5.0,8.0,7.0,6.0,8.0,11.0,4.0,GGHGHGDBCECECEGFHDABADEGGCGCECBFEGACFFFFBFCFHBAGGDDDD,False +514,20.0,26.0,19.0,15.0,24.0,22.0,24.0,21.0,FGFEFEFBHGHBEDHHHHEDCDEHEHCBFHGAFAFBFDCACAGGGGGGGHBBABFBFBCHGGBACGCGDFEEEEAEFFFFDECECFCBCBEAHCBADEDAGFDEDBBEBEHACAFAFABHEEDCFGHDAABEBEDGGHGHGDDFEFAHAHBGCGBGCCCABBHBAGCBHBE,False +515,22.0,23.0,26.0,33.0,16.0,30.0,25.0,23.0,GGGGCBEHCBCFEGGFADHDHCGDACCDBDGFCFHBHGAABFBAHAHDGDBDADACGCFDFGFDDHBGGGEBEBEFGFHBEFABEGCGCGHAHFHFHDBDBDCDCDCHFFFHFDFAGEGBABFEDBDCECBCDDHDBGECADEDEFFFFAFDFDECGHDFDFBCGFECHHAHAHGCBCDADAEAFCFCDHDABAHABC,False +516,17.0,13.0,13.0,12.0,15.0,20.0,10.0,20.0,FDFAGABHFHCEEAFCEGGBEBCBCBEBDHFACGHGCACACAHFHDBGFGDAEAEABFDEDHDFAFEBDHHHFHFHFHAHAHAEAFADCCFBBCEHFFFDGDGBEHHHHGCBEFEAEDFC,False +517,26.0,21.0,23.0,17.0,23.0,30.0,24.0,22.0,ABAEAEAEBGGGGGAECECEDFCEBAGHFHAEADCCGGGAGBEBEBEDCDFAFHFHGCCBHAFAFAFHFGBCDDFACGFGHDEEGEFEGBGFGADFCFCFCBAEABCDHHHCHFHFHBHAEFFFCFBECCCFFDFDBCHCADAFHBABDFDBBAHGGEAEHCGEGCDAGAHDGDFHFHFEBABEBH,False +518,7.0,13.0,9.0,12.0,7.0,6.0,7.0,5.0,CGCECBHDEBGBAFCDBDBDACEBDDGDGEGEFAFAFAHCFEHEDBCBDBDCDBBBDCHFBAGAGH,False +519,15.0,23.0,14.0,11.0,17.0,17.0,14.0,16.0,AFGEDCHBBBBBBGGECEFFBACACBCGCBHFAAABCCEEDDDHBBFBFBGEHEFDAEAFFFEHAGABAFHFBDBHHHBEBEACGCGCACDCHEEBEGGDGHGHGDDDCBGAEBEFEFAFHHHFHFB,False +520,18.0,12.0,17.0,12.0,18.0,12.0,16.0,36.0,EGEHCHDHDGDGCADAHAHFCEEBACEEEADAHHBCBEHEHEBAHCEEGCFEFAFABHBHGHDCGCGDHDHFHDHDHAHCHABCGCFBHHAHFHFHFCEHEAAHHBHGEAHHBFCCGBGFHAEAEGCHBHGDGDGAGFHHC,False +521,4.0,11.0,9.0,6.0,9.0,15.0,6.0,12.0,FFFCCHBHCFCBCBFDDGDGBFAGCFEFCHCGFBBBHCHDEDEAEBHBHGAEAFFBEGEHEHEHBHFFFFHD,False +522,17.0,10.0,12.0,14.0,22.0,13.0,17.0,18.0,EEEEDEABAGFEFEHGHBDAAABDBDAEHHAHGHGHDHAEABHHHHHBCGCFCFCDBAGACEEGCGAADGDHAFCFCEBEFDFEEACGHBEFEFEFEDCGFGHGEGDBAEGEDCHAHGDFDGC,False +523,0.0,4.0,3.0,2.0,1.0,0.0,4.0,2.0,DDEBCHCGBGCGBGBH,True +524,25.0,20.0,21.0,11.0,21.0,16.0,21.0,28.0,FGHGHEHEHBHFHFBFBDBEGDCHCGAEAFCDEAAACHEHEHBFFFFAAHCGGHGBGBHCHCDCGAGAGBHHHFDCDAEABBBCECBGGFACHCECEAFAGHFAEHGGEDEDEBHHACCCACBCHDGDGAAABAGFEBHAGBGCFEEDEAEAFBECHHAHBHB,False +525,5.0,5.0,3.0,6.0,5.0,16.0,3.0,8.0,DHFHFEFEADAGEGECBDFCBDDFHCHFAAAFEHHFBBBGDFFFFFFFHFH,True +526,1.0,0.0,1.0,1.0,2.0,0.0,4.0,6.0,HGHCHEHEGGHGDAH,True +527,14.0,26.0,15.0,11.0,16.0,18.0,25.0,17.0,BHFABADGFABCDGGECEBEFEDBDHGFCFDBDBCEFBFHAGBFEFGFHFHCHBHEHFHFHCHCEDBDBEGHGHGCBCBGDEEFCFBGBGBGBCBDBGAEAGBGAGECEAFGGGHGCCAFGGEAEDBHAGABAFAGHHCBBB,False +528,26.0,33.0,22.0,21.0,21.0,26.0,21.0,23.0,HDBFBDGDGHHEBFFCECFBABGGEBEGGAHEHABGBCCCABDFEFGFADACCGABDBFBADADBDAHAHBEGHFHBEGEBCBCBHAHABADCHBGCDEDEDHGGGGGCDBFFFFFAEECHCHCFEBEAADFBFBABDBGEEHEGEFCFCFEAEADCGFADHHFBDBAHAHACABABFBFCFHBHBHCDFGCD,False +529,19.0,28.0,16.0,26.0,16.0,17.0,19.0,17.0,ABADGCGBHDFFFGFGDGFBDGGFAFCGGFHHAAFFFEAAHAHCBCBABADDFFFABDBDBHGDACHCHGBBBBBGEDADAGCBEBHHEDBCBCBDEEGADABABADADCCBCBDFDFCBCHFEEEDEHHHGHBHDEECHGDGDBEEEDEDGDGCBBD,False +530,10.0,4.0,8.0,6.0,5.0,11.0,7.0,6.0,FFBFCDCGAGFEDCDBEGEGFCFCFCBAFDBHAHAHAGACAHAHEGDFCFADEGAFH,False +531,13.0,7.0,11.0,9.0,7.0,13.0,13.0,17.0,GCABEBFBAHHHGHGAAHCHBEBCDAFHFHBCDCDCDFGEGCHAHEHCHDFFFGFGCGAAAHGGGHFCECHHHGAAEADFBFDFDEDAGF,False +532,6.0,4.0,4.0,4.0,4.0,11.0,3.0,7.0,ABCDHFHFECEDADFGHAFCFCFBFBGADEHGBFHEHFHFAFA,False +533,14.0,30.0,24.0,27.0,22.0,23.0,21.0,29.0,CEBEDGCHDGAAABHEHGCGBFBEGDDDCDCHHDEGFHCEFBGBCCFBAEAGABEDFDCDCDHDHGFGHGCGDDFBBBBBDFDADCDGBFEFDBCFCFBDHDGFACAGFDFDEAECFBBHBHCACAHFDEHEHBDBGBHBFBEDCFEEHBHBCBCBHEFEFCHCHEAFHBHBHEHFGCAEGHGHGHGHED,False +534,7.0,14.0,11.0,10.0,12.0,6.0,11.0,7.0,ABADCBEGAGABDBHCECDBEHGCBCBCGCFCFHFHFBBCBGEGHGDGEGEDDDCDEDABAHCFEEAEFEBBGDEHBG,False +535,1.0,8.0,7.0,5.0,5.0,7.0,1.0,7.0,BHBGFHEDDFCBBBBHHHFEFHFCFCACBDBDEHEFECCCD,True +536,5.0,4.0,11.0,11.0,13.0,6.0,6.0,8.0,CDDDEBHHGHDFGCCACEDEDECEGEACACHEBFFEFEFGFGDGDHAEEEABCBHEDCDCHHDC,True +537,28.0,21.0,11.0,18.0,13.0,11.0,21.0,19.0,HGAGAGFDDHGEBDCGAAHGHEDBDFDEGAGHDECCAAAADDGBBCBHBHBHGCGCBBBFBFGABAGCHBGAFHFAACAGDFEFEGGBFHAADADFDADBBBDAEAFHGHEHEHAHAHAHAGEGDCDCHBABABECDGAEBE,False +538,3.0,5.0,4.0,4.0,5.0,2.0,1.0,6.0,HCHGHAFBEBEAEACDCHBEBFCEHBHDDD,False +539,6.0,6.0,7.0,4.0,9.0,4.0,6.0,1.0,CCAGDGDGEFBCACBCGDDBFEFCFEABABCEEEABAEGEGEH,False +540,4.0,1.0,2.0,4.0,0.0,6.0,5.0,0.0,FDDGAGFGCGAGAFFFBCDADF,True +541,9.0,14.0,13.0,6.0,8.0,6.0,10.0,5.0,CBCGEGEFEHAGEDBGEGAGHDCBCGAGAGHDFGAACBBDBDFFCFHFDACACBBEBECCCCHEACBBBBB,False +542,16.0,16.0,8.0,16.0,13.0,11.0,10.0,17.0,EAHAGFDCGCGDEHCHBAAADHDHEHEFBGBABFDAAADBDADADHDGEGCGHGBFAFEBBBBHFDFDEBEFAHEBDGFHCHCHGDFABABDHHHAEBEHEDEBCCF,False +543,21.0,26.0,17.0,27.0,29.0,23.0,26.0,18.0,GDEHHBFFAHDHDCBHBGEDBDGAGDHCEEEBFFACBBEDGFCFBEBECAFDDHBHDEFEFEFEGGCGBHFFCFEHBHEFBHBADAEAGAFBFGEGEGCGDEDEGCGCBDFDFDADABCFEBBBDBGGGFGCDCDCACFEDBGEGEGHABGEGEAAAACCHEBEDEHBABFGFHHEHADGDADADAD,False +544,22.0,22.0,21.0,19.0,23.0,23.0,21.0,20.0,CGDGDBCFDADCCGDBDHAHCHCEDFFGGGECECEAFAHCFDDEDAGCGCBDEDEAEHCHCEEECEFBFHDHGHGEGCHFEAEAEFFCFEDEABHHHGFBAGAGBDEGECECECHBHAHGBBFBGBDFDGAAFAFGBBCBGBFHEHCBDFFFHFBAAHBFBAAAFAGABDB,False +545,23.0,25.0,25.0,15.0,25.0,17.0,21.0,33.0,GAGAGEEHHHFHFHFHEHDCFHABBHBHBEBHFGBCCACACACGHBADHBECECEBABECCHCFEGHDCEBGGEBEBEFHHADCDCDFDHBHCAEEHEHFHGHGHFADCGFHCACACACBCEGDFHCABGDGEGFCDHGHAAAHBHBHBEBHBHAGABEEGEDEGFBFCGEDAGADDBBEAFCF,False +546,3.0,2.0,2.0,4.0,0.0,4.0,0.0,0.0,ADADAFCFDBBFCFD,True +547,13.0,21.0,3.0,11.0,13.0,5.0,12.0,11.0,GHBADHBHBGBEHDHEEFGHDHGFEDDDEGEAEDFAAGBBCBAGAGAEDEHBHBABABAGADBEBECEAEBBBBGBHBDFGCADBFBHG,False +548,25.0,24.0,22.0,17.0,28.0,18.0,39.0,21.0,CDCABDBHBGBGBGBCECBABGBGAHAHBFEEAEBGAGEHFACACDEGEGECHAEGEHFHFABEGHFHAHGHCDCEBEGDBFAFHGEGBGAGDBDBDBEFECHFHEBFGEGEGECAFABEBGBGHGFGEGCCCCHGFACGBHAHAECFGAEDHGHGDDDEAFADGDGDCAEGGACFBFAGEGACCEHDCDGGFG,False +549,3.0,2.0,4.0,4.0,5.0,8.0,5.0,2.0,HFEFGDGFBFDFEEEFEFGBGCCACDCAGAHFD,False +550,1.0,3.0,4.0,3.0,7.0,2.0,2.0,6.0,ECEBHBHGHBECEFDHAHECEDEDGCHF,True +551,16.0,22.0,21.0,26.0,28.0,20.0,19.0,21.0,EGEDEBEAEADDDCFCABGEFFHDBECHBBBBAHAFFCCDDDDDDHGHEFAAAAAGGBGFGBGCCHEHFBFHHDCDFFBFDGEGFCABBEBEBECDGFEECACDDBCFEDEHHDBDFHFHCHCEGGGEGEADCDCEGEFFHHGCCBCBDBEBEAEAEAGDFHCDGDHBHEHEH,False +552,4.0,5.0,6.0,11.0,3.0,11.0,11.0,5.0,GCCDFHFBDDEDECGCGDGHABDDGGGDHAHAFGFGEGFGFABDFHFCFDBDBFFC,True +553,5.0,13.0,12.0,7.0,6.0,1.0,8.0,8.0,BGDACECGDGCCCBCHCGCDBHHGBEAEAEFBCBEBDGCGDGCBABABEDCHHHHHBBDB,True +554,21.0,23.0,19.0,23.0,24.0,21.0,32.0,21.0,FAGAHAHFHGHBEEFGADABCBGBGFAHEDEFGFBHCECEHEHDGDEAAHGGGEGFFDFBCHGAGHCDGGGABDGDADHFEBHBHGGCACBCBCBGBCFADADGDEDACBGHEFDFHFHFBDDDDBHBGGGCDEFEGEGECHCBCBEBEBEFFAGBBFACECECDAEFECGAGEFDGGAADHDH,False +555,11.0,14.0,17.0,9.0,22.0,14.0,9.0,22.0,CGEEDCDADADBDBFFFHCAAEHHHEHEHAHEFFCFBGHHHFHCHDHEBGFGFBEECFCEEECGCGHEEEEADHBHAABCCACFCEDHCHCHBHBDBECGCEFFGFABBEBEGHAHBE,False +556,4.0,3.0,4.0,4.0,4.0,1.0,0.0,1.0,BABHECAAFBDCDEDEDECAC,True +557,11.0,15.0,15.0,16.0,14.0,18.0,14.0,14.0,BCBCBGDGCGEAHHEHGAFFCFHFCGAGACEBEBEBAFGCCDGBCEFDFDAEADDFDCEBFBFBEHDHEHEGEGBGHFHDDDDCCBGBCBHAHDEFFFGGCHBEAAAHFFDFDFDHC,False +558,5.0,2.0,3.0,3.0,1.0,2.0,3.0,2.0,DGDGACBFHFHAEACABACDG,False +559,29.0,26.0,17.0,17.0,20.0,26.0,24.0,23.0,DADCDFFHFAFACAFBDBACAGABFGFBHCHCFFEFEFGHGCBCAEGGGDBDBABFHFAEADDDEDEHAAGGDBHGFFFFCGAHBBGBGECEGEGEGEBEDCFFDFCCEAAFDHAEBFBFAHAGFHCCGBGBGBGAGABEDADHEBEHHAEFHAHABCBCHAEAFAEBHGHBBBAGDHHHHC,False +560,7.0,9.0,14.0,11.0,8.0,12.0,13.0,5.0,FCDCEFEFGHDAABACGCGCGDEBAHHBCCFCFGEGDBDBDBAFECDFDFEGGCAFABCFGFGEGHCDEDGDGFCBCBH,False +561,16.0,32.0,21.0,19.0,21.0,20.0,22.0,22.0,AFBGBGHGEDFAACDCDCEFEBCFCGHGHFDABABAHCCEAHBEDEDBDCCHGHEBEBEBCDEFGDGFBFEDHDHDBBBFFEGBGHEDGDFBGBACDGEBEBHBHCCGHGHGDGDGHGHBCAFHGHGFABAFAHAFCBCBFAHDHBBCBGFEBABCBCFCFEEBCFEDEAHBE,False +562,18.0,21.0,6.0,6.0,14.0,3.0,15.0,20.0,DGAAHCHBAFHBHBGCAEAEAHAEAHHHBCBGGEBDFAHAEAEBGAGAHDEGHAHBEAEGHGHBABHBHEDCGHGBEDGBGEGBGBABDBAEEHFHBCBCBHB,True +563,19.0,18.0,15.0,19.0,14.0,16.0,17.0,24.0,FAFAFABBHDCDCDFDCAABFCEDBBECDCDFFAGADBCHGGFHDHGHEECEGDADABEHHHHCHDHDFAHGFGFBDBCBFHAGABDBGBFDGGFCFCBHBHFHEHEHEGAGAHAGABAGABEECDCHHEBEDEHAGCGHDH,False +564,3.0,3.0,2.0,1.0,0.0,0.0,0.0,2.0,BABCBDAHCHA,True +565,8.0,12.0,12.0,9.0,13.0,13.0,12.0,17.0,BFBFEEHBFAFGGGCHDHDHGCDCGEHAHEEBBAEFGCGCHCFCFDBBBHCEBEHEHFGAGFFHFHABDGDFDFBHAHDHEAABCEGEGEDCHCHC,False +566,24.0,19.0,7.0,22.0,15.0,14.0,18.0,21.0,AEADAHECBGBFHGHDHAGDGHGBGBHFHBDDDHGHDHDADHDHAHDEDADGFEFGFBDBDFAAAAABEFDHHHEGBGAAEDEGEGAFAFHHBEEHCGBEADAEFFBFDFDBDBGBHAGBCBEFDHGCACBCBAAACAGE,False +567,18.0,34.0,25.0,23.0,26.0,29.0,16.0,24.0,CHFDFHBCBDBFBHEEAEABABCGAFDFDADADADBBBCBDBFCEEEFFAFDBDBGHDHBBBFFFDABFHGCABABABAHHHHDFBFEFHBCDCFCFBFEEGECFHEGEGBBDDHDEDHFHDHDFBAECCBHBEBHBCCCBDBEGHGCFCACEFAGEGEGCCFBFEHEHCGFECGFDAGFGHCCCEEEBEHAHDG,False +568,10.0,3.0,8.0,11.0,10.0,4.0,2.0,8.0,EGEDEHEHCDCEAEAEAFFEHCDDDCACHBHBDDDHAAACAEBFAGAHDCCFEDHD,True +569,16.0,11.0,9.0,12.0,15.0,17.0,17.0,12.0,EAEDEACHEAGBHHFFAGGDADADHBHAFFGDEDEHFBFCGBGFFDGHAEAFBCBEAECDADCGCGFGEGEGAGDEDBFFAFAFCBHAEAEGEGFGFDCHCGFBHBHBH,False +570,5.0,3.0,10.0,3.0,5.0,7.0,4.0,6.0,DADCHHGACACECHCFCFHDEGABAFFFFECECFGGHBCBCEH,False +571,19.0,19.0,10.0,25.0,20.0,11.0,12.0,21.0,EGEGEDDDADCBFBFCHCHGAGDHDHDADGHEDDDDHBHBHCADEEEDDHDBCEAABABFEEAEGHGHFEADDDCABHBHBHFHFEEEEFDCEEGCBCHGAEAGABFBHAHEHAFABHBFDDDBDBHAAFBBAGGCD,False +572,9.0,14.0,14.0,11.0,15.0,15.0,19.0,10.0,EFEAEGGGDGDADFHFGFBFBFGDGBBEBEADHGCBCBCGCECGFDCBCBFDFGEDBDHCAFEFEBGCHAFGFGEEHBGCGCEEEBHCHBADCCGGHAHADAGFHFE,False +573,4.0,10.0,13.0,15.0,11.0,8.0,6.0,4.0,AFCCGEEDEBEBAHAHADFBCBCBEFDGHBEGEFFBFDDBCECDCDCECEDDDDDGDCDCEBBGDHFCCGF,True +574,15.0,27.0,18.0,27.0,33.0,20.0,18.0,26.0,FACGCDEDBABABADHDBEFECGDFHHEBCBCGHHAEBHBHGDADGDGDEEEDEBCBDBEAFHFEDGDGDBCHEAADEDEAEDHCHAFDEDHDACHBHBHEHECFBABHDEEEFEGBGDDHGFBFBFCFCEBEBFFCECEGEFEDGDCBGEGHFCECEBGBHBHDHCEFFFBGBHHHEFAAHDG,False +575,16.0,17.0,13.0,14.0,16.0,19.0,22.0,14.0,HBCFCFDFEGAGAHHGEGBGDGFHEHAFBDBDCHCHGFDEDEFHFBEBHBHBEBHBDFDEDEHEGEFFACACGFHADGFADGBAEADAFBCHEFFBEBGBGBACGGFGFAABGGDGFCCACAEAECDGGGC,False +576,21.0,18.0,24.0,12.0,15.0,14.0,8.0,14.0,CDCDFBACHGHECECEDECECHHAHBGFAAHAGFEBCHAGBBBABCBADCFEGABABCGCFAFEBHAHDHECACHHFCBBBEBECFCFAFAHAFCGDFDFDBEBDCACACADBDEHEFEDGCACAC,False +577,11.0,6.0,10.0,4.0,4.0,6.0,15.0,11.0,HHGHAHGDGCEBABABGCHCGCECHCACHDFBABFHFCAHAHFFBFGGGGGGGACAGECDGAADEHG,True +578,13.0,11.0,13.0,13.0,10.0,10.0,11.0,13.0,HDHDFAHCHGEAAAACGBEEHHDEEEDADCDCACACDGDBDBCFEAGHCFCABFBFGCEFBHHHHGBGCGCGEEHAHFBFDDBDBCGDGAFAFB,False +579,16.0,20.0,17.0,10.0,16.0,13.0,17.0,18.0,HBHCDAHECCCCBHGEFCBCGFFAFACBDGDCHBHBCBEBEDGDFEHGHBHECCCEFAGAEHDGDGHBFAFAGAGBGBGBEECCAFAFDBBHFECBGHCHBHDHBHBAEEEAEHEAGAGFGFGDABA,False +580,19.0,23.0,27.0,23.0,24.0,28.0,24.0,26.0,FGFGCHDADGDHFFDCDABFFFFBCEAECEHADCDFDFABAHABDEDBAHCCCHBAAFAEGEGFGHDHGHBHGHDCFCFCADEFEHBAEEFGCDCGGGGGEHFGCGCFFHFHGHBCBDBDCCCGEBEHFBFCFEECFGHGHFHCAEBEBEGHGHFEFDCHCBCBGBDBEAAABCCEAFBHBHDHEEGABDDDED,False +581,14.0,16.0,19.0,20.0,20.0,20.0,13.0,20.0,ACAFBEAHDHEHBHCABBCHFHCEEGCHHFCDCBBEBHFABGDHFHFHBHBHBGDDDCFFHFBFGFECDCEAGAGACCCGCDCDEDEDADADFFFAFAGHCDAGHFEEGHCEEEHECECEGEFDFEEGDDDGDBBFBFBADH,False +582,13.0,15.0,13.0,20.0,21.0,19.0,19.0,16.0,EGGAGAHBFFEFEHECDCFCBGHFFGAGAGEGCGAGBFCFDDDEBEHEHCFBDDDDDDADAFAHHCFDEDBFFFFHAGCBDAFBHBEDGFGCBCBGEGEDCDCDCFHEHGHBDGEHABEGAGHFEDAHEEEEEBHB,False +583,6.0,13.0,10.0,9.0,17.0,8.0,10.0,9.0,FHFGBBBBABCCDHBEDHGFDEHCGCBEBEHCFCFBFBDBACFHGHGEEECECEDEDEHEDGCAEADFDGEAEGGGEBABEH,False +584,18.0,27.0,27.0,16.0,19.0,28.0,14.0,16.0,FHFCFAFHHBEBFBDCHBGEDBAFFCBHBCFGFGCGCEEEDEDBABGEFBGBAFAFHEGCGCDCDBHHCHAHAHGCECAHFHFDEGHBBCACABABFBFBFAFCDCDBABEBECFFGBECCCHCFAFDDDDFDBECEAEDBFCDCEFGFABABCCGEHCABGFEF,False +585,26.0,16.0,22.0,22.0,20.0,21.0,22.0,26.0,FHDHDHFCEBBDBAAAAGFGCBEDHDHGHAEAECDCBEBHCHAHGGFDAEFCFHHHEECCCDCDCDHAHABBECACADAHCDCDFBBEDAAGAFFHCEEEAFAFGFCECEFACAEAFFHEGFHCAGECFFGBGFGDBDBABAGGGGGHHHAHDDDHHHAHDGEGFGBGBFCEDGD,False +586,8.0,5.0,12.0,4.0,4.0,13.0,13.0,7.0,DFDCCCCCCFEBEBDFFAFGCGCBFDFBAAFHGHGCGAAHGFAFGFGCGAGBCHFHCGGHFHEAEG,True +587,4.0,3.0,2.0,3.0,2.0,5.0,3.0,1.0,BGGGDBDHDFCAEAFCFBFEFAA,False +588,7.0,14.0,10.0,16.0,16.0,9.0,9.0,13.0,BCDFHCGFGAEFFFDDBBHBFBHHGAEDDFDEHEGEGEHADFEEHEGEDEDEDEHHBHBDBHBDCDCDBBFBABACACEHECGHEBDGDCCCAG,False +589,41.0,28.0,27.0,20.0,22.0,14.0,25.0,23.0,EDEHHHEACAEAEGECBBHBHBEFAFEBAFHHGHAHACAGBDBEGCDEHAHADACACGEDCCCFBBBBBFAADACAGECDFHGDDBDCDCECDABAFCBEGEDFCGBGDHACABGHECBGGCDCGEFEAGCGDAAABABABDHGEAHBGAEHGBGBFCFCFEFBHGHBAAAAHABABADAGACACGCACHDHDHAFAGEG,False +590,25.0,17.0,16.0,9.0,20.0,24.0,14.0,17.0,HDFDEGEFBBECCBDBABFFAFDFCECBAGAEABGFHCACAFAFAFHEHEHECFCHEHEHECGBDBAFEBCFAFCFAGGCFCABHGABFFEGAHAGAGCHHEHFDFBEBCBEFAFAHAEFEAAHAHBHBGDGDGCEADAGEF,False +591,17.0,13.0,25.0,18.0,20.0,19.0,18.0,19.0,ADCFCHDBAEHEHEFEACAFAFDFEFECEGADHDHEBCCCCEHHGBDBDGCCFBGDDCGABAEAEDEAFAFCGCFHFEGAGDGFHCGCEHEAGCHCBDEDCFEDHCBEBFBAGEGAHCHCBCBAHACDBDCDCHFHEGFGFGDGHGFFH,False +592,4.0,14.0,3.0,5.0,17.0,15.0,9.0,5.0,HGFEEHBHFFEFHFEGBABFBGDFBBEFEDGDEDECEBEFEAEBBBBEBFAHAGFDFEFEBGCGFGBGFECE,True +593,13.0,8.0,10.0,11.0,8.0,10.0,5.0,8.0,EAEADADGFGCDDFBFHHGADABAFHHBAEABHHGBCFCFDFAFDHDCDCBFBCCCBCEEEAEAEFDAHACDG,False +594,16.0,13.0,15.0,7.0,3.0,9.0,20.0,22.0,BGBGCGHHHEHGAAFGCGBDFAFBHCHBDBCCCFDAHHBGBAAABHHHGHGBABABCCCCCDGHGHCHAHGEGDBFGFGCGAHAGFCHGGGAHAHCHFEDHDAAF,True +595,12.0,10.0,9.0,7.0,8.0,10.0,12.0,10.0,AEFDFGFGABHBHBACAHFFEECEFDFGBCAABBCDCGEBEBHHHHFBAEADGDGHGDGDCACGCACAEFHAHGGGBF,False +596,12.0,14.0,7.0,5.0,7.0,8.0,16.0,11.0,DBGBABFCGCGEGBGCHCABEEHGGGHGHFBEBABFBFBGGGGFDFCGABABAFAHHHHBEAAADDHCFEHAHBGACDGE,False +597,12.0,31.0,25.0,23.0,29.0,22.0,19.0,20.0,GBCAEDEGEDHCHGFBEGCCDCGAFBFAFEGBBDBDBDGGCEHEHFHDCDCDEDFHHBGBGCHABGCGCFHFDEBCDHDAABFBGBHDCDCEHEBFBFEFBFHEHEGEBBDBEBABCDGDBHBDFDFDACCEFBCBFHFGCEAEDFCCDCFGGEEEAEAFAFBHBEBCBCHEHCHGEEEBE,False +598,3.0,2.0,2.0,2.0,0.0,4.0,2.0,0.0,DADAGFCFCBGAFBF,True +599,18.0,18.0,17.0,19.0,19.0,25.0,24.0,26.0,EFEFADADEGEGBBHHABBHCCGAFDHDFEHHHHHHGAAADGHFHGGGGDEACHCHCFCGEGEFABEEGEHFCFDFEBGAHCHGFGFGFGFDDHEFCFEBDFEACAFHCHFBADGCGBADGDAFCHCHDDDFDFHCHBHEEEBEBGBABABABCBFFHFDGCGBGD,False +600,18.0,13.0,8.0,18.0,9.0,20.0,11.0,10.0,FAHEFAFAHDGGGGHCBEGABABFEFAAGAGAGAGAGBHBHCFFDHBHDEDEDABCFCEDEBEFADDBFFCFHFAAGDDDDDDFFFFHADFFFBBBCDADCCADHBE,False +601,28.0,16.0,18.0,22.0,25.0,31.0,31.0,28.0,DHDHCHCEGGGGGGHGHGABHGABAGDGEGBACHDHBGADFBHGAGFGDDADGEAEACHBBFFHFEGEFFAFAFGFEFAGADDFAFCFGHBFFEDBACABFHFCCCEEDFDCDAAHFHEHDDEDGHEFCAHFFBCGCGCACABAEAEHDHFHFHFCEDEDGAGAEEEEEFDAGGGHGHFHAGEBHBAEFCFBFCEHBHD,False +602,19.0,22.0,22.0,6.0,18.0,28.0,18.0,32.0,BEHEHCBFBFGAGFFFHEEGEFFGCHCHFABHHCCBFHFABBEBCACAEAFHFABHCHGBBAHEEEEAHAHBHECACAHEHEHCGBFFHFGAGCCBCBEFEGHDDGDHFHCDAHHHHDAFBFAFHFHGHGACCCACBHBGBGBCFGFHFHFGFGFAEBCGCBDEF,False +603,6.0,3.0,3.0,0.0,3.0,1.0,2.0,3.0,AAAAHHHEAEBFCEGAGCBCB,True +604,20.0,12.0,4.0,14.0,4.0,16.0,10.0,13.0,BHADGGGBAFFHAEDBAFGFCFHFHDHBHBGFFHADDEHFFBFGHAHAHABACADFFAAGADAGAGACADDEFEFDADAHBGBABDBDBDCHF,True +605,13.0,12.0,3.0,10.0,9.0,12.0,19.0,5.0,BFBFCDGDBDAGAFCHBBBDHGADCEAABAGFGFGEGEGDGFAFEGBGAGEFFGFGEDADBBGAGAGEFEBBHGHGEDDAFAH,True +606,25.0,22.0,15.0,23.0,20.0,14.0,29.0,17.0,ABABABGDEFEFEHBAAAFDDBDGDGAGEEBHFFCAHAGABACACHEGDGDFDHGGFFHFBEDECFGHCBAGDGCHBGBGCGFDADECEBEAEADAFEBEAEFCBCBCBHBABGBHAHAGAGDDEEEHBCEADGDGDHHFDGABDBDGGCGCADGGHHDHGGEGC,False +607,7.0,12.0,19.0,9.0,3.0,6.0,12.0,7.0,CHGGCADECECGBGCGCEHDAFACDBGGFABCBCBCBCBFBCGCBCBCBFHADACADHDCGGGDFCHGFCHDHDB,True +608,15.0,15.0,12.0,14.0,12.0,4.0,21.0,15.0,BGBEFEGDBCGCGHHEGCFAGEBFGHBCCEGAHACGBDBGBHAHGHGHEHEHACABADADAHACBGDAEHGHBDBDBEBAAAFCGCGDEDCDEDHDAGHGDGBGEGDC,False +609,11.0,19.0,6.0,5.0,9.0,14.0,11.0,10.0,BBBBGBFBFBABDHAHFBBAHEHFCAHGGDGDFCBCFCGAHBDBGBGFGHAHGBEEAFFFBFEFEACACEEGEAEDGFHAHBBBF,False +610,7.0,6.0,1.0,2.0,7.0,8.0,15.0,3.0,GGGGGDGFBAEAEBFHGHDFAGBEFEFGFGBHAGAGBCEAEGBGEGAFF,True +611,9.0,11.0,18.0,12.0,13.0,14.0,18.0,18.0,DABAEGBGEGEGEGFDHCGCHAHFHFCCCCHHGADFBGEHAHEHECFHEHEAGABDGEBCBFFFGDGBGACHHHDHCFCDCHHGDCHCBCDCGCBBDADGGGEDECBFFFFEF,False +612,1.0,6.0,5.0,8.0,3.0,4.0,3.0,4.0,BEBEBGBFBFDDCHBDFCHDGACHFHGDCDCDED,True +613,5.0,7.0,4.0,9.0,3.0,12.0,4.0,8.0,DEEHBFGFCHBHDHFAGDBDHDFCFEBHHHBFBABAGAGDFDCDFFFFCFDA,True +614,5.0,4.0,10.0,9.0,2.0,6.0,6.0,7.0,GCBCBCGGBFHHCFCHHDDDDCBGAEACACFDADCCAFHFHDHDEDGFG,False +615,20.0,20.0,21.0,19.0,32.0,21.0,14.0,26.0,FCCGGEHECEDEDBBECHCHCFGBEHECCCCCHCGCDCDEHAGCECEDDBEBABABEBEAAAAHAHEFAFHFEFBFBFAFGEEEAEHEBGHEHDBCBDAAEFFHCGFHHHGCEAGDBEHEFEGDFBFAHHDBCHFFBEGEGFHECEADADADBHFHAHDDFDFHEAEBDBDGH,False +616,4.0,1.0,4.0,5.0,3.0,3.0,4.0,3.0,AGAHCHBGDFDCHEDEDEFCFCDAGAG,False +617,14.0,17.0,16.0,17.0,18.0,16.0,11.0,15.0,EFEFHFABEBEGEAEBEAECBDHFEEGEGBGDHHHHHBHBHBHAFAHDBFHABDDFDHBGDECECEFEFGDABAFAFABDHFBFCGCGBEFCDCEADDDFACAHDCCGDDCBCGCFCABECGCD,False +618,29.0,30.0,26.0,14.0,18.0,25.0,13.0,17.0,HACCBHBFAFBFBFHFCBAAGAEBEFDDBDAAACACACEEDDAEFGBGFEFCABAGAGAGFGCHCAGFBBDFHAABFCFCFDHEHCFBFBHADBBBBHDDBCFABBEBFBADAEBCBHBHFHCBDDHCHGHCACAGAGDFCFEAEBECECECFCECECGHEBAFAEAGHBCF,False +619,31.0,22.0,24.0,19.0,30.0,25.0,19.0,29.0,CFHEHCGFFACEHBDEEGGACFCACAGAHAEAFDCGBACEFGAECCAGHBHBDBAEAGFBABAGACAHHHAHCHCDCDAGGGAHAEAEDGGCEHFHFHFDGBHBCEHEDEFEFEFEAADACHFBDBDBDBFBFAEHFHBHEHEGEDEDCCEBFBFCFCAHDBFEAEFEACAFADEBEHHDEGEAHBHCHDBGBCDHFGF,False +620,18.0,17.0,15.0,24.0,21.0,15.0,18.0,13.0,ECDGDBDGDGDEAEBEBCFGFGAGAGHCDEHEHBGGGFEAAFBBDFHCDCEEEEGAGAGEDFDHDHAFAFHEHDADADBDECACEDDBHFEGECADDCFHBCBCHCDDFDGBBBEAECEDEFABAHCHGDABFBFGFCBGA,False +621,0.0,2.0,1.0,1.0,4.0,1.0,0.0,1.0,FEEDEBEBHC,True +622,14.0,20.0,14.0,20.0,27.0,29.0,12.0,26.0,CDCACEHFHFHBHEFEDEBBFFFFBFECHHAHEHEDGDEEBFHFHAACEDECCCCEFEHAHBHDHFHFAFABEEEGEGEBDAHEEEEFHDDDGDEDABHBAFGFEHABFBABDBFFFHFCFHFBGCABBGBHFHFDDAHGFEFEDHCHDEBGGGBCDDDCGF,False +623,16.0,25.0,17.0,19.0,21.0,19.0,21.0,15.0,BFDFDFGBGDHBHEDCACFCEHEDEBCFDEDADBDACADDEGEGHAHBHFEBCCCAHEHEBEBAAAAGCFCFGFBEEEHBHEHGBDBDAGAEAGBDBGFEFGBCBCFGEGBGHDHGCCAADCDCBFBAGGFGEHDFBEBFBFDFCFHBGGGEB,False +624,23.0,27.0,21.0,27.0,12.0,19.0,33.0,26.0,DHAGAGFBFCCHHGGBCBFDFACGBGBGHCABACAHFHCDCDGFGFCFGFCAEGHGABABEDEDHFHFDFBGHGEGHAHBHCDAGAGAGBBAEAFGCACBFBDDHGHBHDGDGBGDAAAAEBBGBDBDCACFCHCBDBCCCBGFFHDHDHEGEDEHHDDDHBGBHDFFEBDDEEGGGGAGHCHDBAGD,False +625,17.0,22.0,27.0,7.0,24.0,19.0,26.0,18.0,GHECEGFGAGCBEEGBGHGBEBEAEFGFAFCFHGGGGEEECBFBDGGCGCEDGFBHBCBCBCAGABEGEAEABFFFBFBFHEGFGACAEFDBCBCAGAGAGFFCCBEHCCBCBDHCBEHCHCACEBFBCGDAHFCECEDACAEHHHHHDAFGHCHCEGEH,False +626,21.0,20.0,18.0,14.0,19.0,24.0,20.0,19.0,FGFGDBFGAAHHDABADDECCHFBGCEEHGHGHGAFHCHAHBCBFAFAFABBBABADDGEBBFCFCFCFCBCDCDHFAGGHGHGAGEHBFAFCHHEGEFBHDHAHAEDGAGAGEGCDEHECCCBBBAFFFEFDADBBEDEGCFBFCGAEEEEFEF,False +627,22.0,20.0,15.0,21.0,16.0,16.0,15.0,16.0,GBGEFDACFGFGHBHECCFAAAEEGBCHCBCFADHDHDBDBDFDADABAEDFBADACBCFCFEHGCEFEAEBHDHDFDEEBBHBGAGDGAEAEGGHAHDDDDFDGBBBAAAABDHGHFAFECCCECHBDBCBFEFGAGAHH,False +628,7.0,15.0,8.0,13.0,14.0,12.0,11.0,8.0,DEDBDHFHDCDCBBBCBDBFBFCGHGAGEFAFAEADBFBGBGHGDCFADBDFEFEDECEFHHCBEAGGGDEBECEABBGHGFDHEEFE,False +629,1.0,3.0,3.0,8.0,6.0,2.0,4.0,5.0,HEHDHDHDEFBGBGDDCDHBEDECGCEEFGAD,True +630,11.0,10.0,7.0,6.0,8.0,14.0,8.0,5.0,CAHAHABFCFCACFCAHAGDBCEGHFHEBDFAGAGABBBEBCFEFEFBFAFBDEDEGGDFDABFFEFGG,False +631,14.0,11.0,20.0,21.0,13.0,15.0,14.0,16.0,HCFAAHBFCFAFHFGDHFCFBBBEBEAEAEHEHGDDBHHHFHDCDEGECFHFDFDADACADHGEDADHDHDCDCGADDECEAGBBCECDGGCGCABAHFGCDCGFBHBDCDGAGCCCDCGEFEF,False +632,4.0,8.0,5.0,12.0,1.0,8.0,6.0,3.0,CAHAEDBCCFGDBDFFBFBHDDDDDADCGBGBCFAGDGFGFHDBDBF,True +633,3.0,4.0,7.0,2.0,2.0,6.0,5.0,5.0,CBCECACAFEFDAHBCGFGFBHCHDHCHGGFBFG,True +634,15.0,14.0,8.0,23.0,21.0,16.0,17.0,8.0,GDDDADADACBFGFGFAFACADAEEBEBFCGBFHFHGEDDDFCGABCBDHDHEEFHAHGEFDFEFBFAGAFEGDGDGBGDEDEBHBDCEEEEGEBCDDEAECDDDEGGGAFAEBFBGHEDAB,False +635,16.0,23.0,27.0,12.0,33.0,22.0,20.0,34.0,HEHACECAHFBGBEBHHHHFFCECEHEAEGDGDHAHBFFFFFFFGABCEFEBECECHABGCGFHEEEEEEGBCAHEHCHDFBGBCBCBHHGFBHDHCHEHEHCFCGCGEFHHHCDGDEDECBCAFEFAGHDCABHDAEACCHGHFBBHDEAGBGAFDDGCACEFEFEHEHEBEGCCEGBGBCAHBHB,False +636,18.0,21.0,19.0,22.0,14.0,15.0,21.0,26.0,GHABCDDDAGGFFEFDFHBACHDHDECGBFBFAAGECECDAFBHCDCEBGBAAAGHHEHEHEHEBAFDFCACECECEHHHCHDHAHAHCDBDGGGDHDBCCFCGHHHGDDDBEBFCFDGAFBFBDBDBGBGBABHHCHGHGDBEGAAHDCGAGBGF,False +637,7.0,11.0,15.0,9.0,7.0,9.0,10.0,13.0,DAFBFHGDGAGCDCDGHBCECFCGCDEDHDHBHBFBEGEHDADBBBBGFHHAECHGHGHBFCFAACCCFFHGACHCBCECE,False +638,23.0,18.0,27.0,21.0,18.0,14.0,17.0,30.0,DEDCHCBFEAEAEABAHGDGDADEBEHCFDGGCCCCDCBFGFCCHDHDHFBABDHEHAHFHCAFAEADHDHCHEDACCGCGCGCBAFHHHECDDDBGHHHCHBHAHECFBBGBDBFHAHGHCDGHGCGCBBBGBABFGCGAEEDFDAEHFHDHEEACAEFEACHCAAA,False +639,8.0,5.0,5.0,6.0,7.0,4.0,6.0,5.0,FGEBDBDBGHGDGCAHAHCDAGAFAFBEBEGEFDCHAEECEDACAH,False +640,25.0,30.0,19.0,18.0,18.0,25.0,21.0,28.0,DBGBFBFHFHCAFAFACGCHCHEHEGFGADHHFEAEGEGHGEAEBDADHBABDGGGGHBHDDGAEBDFCGCFFGACDHBHFHCHFAGHEDACAHBDDDAHHEBEBABACAGBDEDGHBHFHFCGCDFBFBFAHGCBDDCBAEAEFCABABACACEFHFBAEHEGBGBHBFFHBEBFBFBFHCBC,False +641,10.0,7.0,19.0,15.0,18.0,26.0,16.0,17.0,EBEBEADCFGFGAADCEFHCAEDEAEFBHEHDGDGDBHCGCFHFHCHFEFGFGCECFCGCEDAFEGDFCAEADCFEFHHHFDFGFGAGDGDFHHGACFBHDHCGFGFCHCHCHCDEECFFFFEBEBFD,False +642,17.0,19.0,31.0,20.0,20.0,27.0,31.0,22.0,EFGFHEBFAHAHFHGCFCFGFHFBFDHDAGAGBECCHCBGBFEABDEGEGFCBDDFEFADADBFEGEBBAEHEHAHAFGCGCGCBCBFGFCACHCECGCBCAGFHDBDCAFGCGCGCGCDDDCDGDGFBHGFFAHCFCFHECDGDBECCCDCEGEFBFEHHGAGCGDHAHGHEFDHAGBGBGHDECE,False +643,10.0,16.0,8.0,13.0,16.0,18.0,19.0,19.0,DBDFCEGABABHBFGAHEGFFDHCFCFBDHHACAFECHHHHGFGBEHEGEGEGFGBBDBFEFHFCEDECFAAGFGFEBAGHEHEHEGDBDFDFBEBDBDFDBGEHCAAGHGHGBGHGHD,False +644,23.0,23.0,24.0,17.0,10.0,17.0,18.0,14.0,BGGGGGEGBACCECHCHCACDBAEFEFHAHACFGGADDCDCDCDGHGCBHBAAFGFGFABBBBFBHGFAAADADCDEACDEACBHEEFCCHCHAFBCHGEGBFDFHEBBHBDBCHDBDBGFCFBDCGFGFACABBBAAAAAFDCDC,False +645,19.0,20.0,19.0,12.0,21.0,19.0,19.0,26.0,BCHEHEABABAHAHDHBEDEAEGECEBECAHDGCFEFCHHAHDHDHFBDACABGCEBHBCFHGCCCAEEDAACABBHGHGHFHBEBHDECEBDBCBFEFHHHGHGHGHFHFBDGEGACEFDFHFEFCGGGAEFDFGCGABFFCFCGBGAGFBAEA,False +646,24.0,19.0,25.0,16.0,26.0,22.0,27.0,28.0,DADGFHCDDBDHDHGGAEECHHHFCAGACFCFEDCCECEGFBFBCBGEHEACBCBGGHGAGFHCGCGEFEDAHAHFHEBBBHHAAEAECBGAAFBGBHBHAAFEEAECEGHGFCDCHHHHBDFGFGFGBEAFHFDAHAHCBCEHGHGFCDGDGCGEFABDBFBAAAHADEDEGCGHECEFEFECECG,False +647,19.0,19.0,11.0,23.0,12.0,13.0,15.0,22.0,FGFAADEGEAEADGDFHAHBHDGGGHDFBHBDDGDCDHBHBHEHECEDBDBEBHHDHEABCCGFAHGGEADAGFDAHEHDHDCDGDHHEHFFFGEGBDCACACDFDHBBBBDCGAAFAHABABACACFDFBBHB,False +648,14.0,18.0,21.0,17.0,4.0,13.0,14.0,14.0,HDCCBGAGBGFGFHCCACHCGCBCBEDEBCBDBHFCFCFGAGACBGFDFBHBADAGHCHBHFCACDFDBABAEGCHHDBDCFBECGCGBDAFFGHDBDBDADADACFDADCHHGH,False +649,18.0,10.0,20.0,21.0,15.0,23.0,20.0,19.0,CDCFFDAABAFGFDBHFHGADADAHGHGBDFCHHHCDCHAHADCDGDGDGCEFGFCECFCFCGCAAAAEAEDBDBFFHHHFECECGGEGAABHECFHDEDGHGAEADFFHGDGDGEEBDCFGEHFCGCECEDDFFFFBFBCBHHAG,False +650,2.0,8.0,12.0,4.0,7.0,2.0,3.0,2.0,BECADGCCCCCBCBCBDGGFECECDBDBHECEFABHBCEE,True +651,23.0,17.0,14.0,13.0,18.0,7.0,9.0,12.0,HGFCACACFCDEEAGBGBADADABCGDAEADGDBACFHBEDAABHBHGHCAAEBECECACEDECEGFGAAHABAEAHDHABABADEBCFCFBEEEHEBFBAEHEHDCDBGBHD,False +652,9.0,5.0,7.0,3.0,3.0,4.0,7.0,7.0,FHAHAGGGGHGCGCEHEAFAFCHDECHBABCFGBHBACDCDAABA,False +653,17.0,14.0,10.0,12.0,16.0,15.0,12.0,13.0,FFDCCCGHBHEFBAEAHDFFFHBBBBGAFABABAEADAEFCBDEEHFDACHCHDAFCFEDGBCBCBEBEGGGCHHDDAGAEAEDEDEBEHDHAHEFGFGFGHGAAEAFG,False +654,18.0,23.0,28.0,27.0,18.0,13.0,30.0,25.0,CGCBCACGBGHACACADFEBGBCAEHBDBCHAEDGDFDCCAEHDGDFDFAFBGBGEDCFBFBFDAHGCCCBGBHEHAHGGGCECEHEAGCGDGDHBBDGCECHAHDFDGEGAGDGEADHCACBGBCHAHAGBGHHCHCHGEBEAEDECHBGBGDGFGEGHCHBDDDCDHDFDHCFEHDBDBF,False +655,15.0,11.0,8.0,7.0,7.0,6.0,7.0,13.0,EFAFACBEEDCAHAHGEAEFFHBHBFBFHGAAHGHGAGDCBHHHABDBEBAGAGDDDADHBCBEACHCACACHB,False +656,23.0,17.0,14.0,15.0,23.0,23.0,21.0,14.0,DBBBEEGCGFABAGAHAHFDEEHECBHBFBEAEADGDACGFGFCFDFGFGFGBEBEDEHHCFEHAHAFAHEBABEDEFGFGBGAAECFCHCEAGDGDCBCAFHFDFDFCFEEEEECFDBGGGAAADBGBHDAGEEBHDAAAHFGCGFAFC,False +657,22.0,13.0,20.0,11.0,19.0,20.0,13.0,19.0,AAAEEECFGGCCCDBDAFHFAFCCBAAHBBBEBFBAGCGEGHCAEACDCEADBDEAFCDGECEGGAGABAHAEBHHHHHCFCFEHCHFHGHCHCFAFDFDFDHBEGEFFFFAEAECEDEDHFGABFEGCHCHAHABF,False +658,13.0,8.0,9.0,8.0,6.0,14.0,16.0,11.0,DFDAACADGHGFECCGBFFFHEAAFACAGFHCGCFAFDFBBHHFGAGABABAGEFEFGDEBFBDBGACHCHCHGDGHGHGEGDGH,False +659,24.0,22.0,11.0,20.0,12.0,19.0,20.0,10.0,ECECBBAAAFHDHDHCBGFGFACABAGGHADBEAFFDFDFDEGCGCBBBFAGABBEDGGAGFDAGHGDDAEABBGBHDGEBFBHDFGCBCBEBFDFDADADBBFEHEFEFDFHFEGDCDCDCGBGAAAAAGAFAHBGA,False +660,9.0,8.0,11.0,8.0,16.0,14.0,26.0,11.0,FEGEHCHBGBGEGHGHGEGHDEBHAFACGDGFGACHHGAFCGGFEHDFDEEGBGBGFGFGCCECFAFDFDHBGDAAHAGEGDGEGFGAGEBCCCCBEEGEFEF,False +661,21.0,16.0,26.0,12.0,16.0,24.0,13.0,16.0,AHBFGAHHBCBABABCCGBEFACECGHGFDAHHCCECFFFDFAHACACBCBGBDFEFEHEDACAEDEDEGEGDGBBBGCGAHACACEFAFDFAFBDACAFFHFCFCAGEGBFDFBFEGCFCBCFHACADDCHFHFCECEHHHCE,False +662,19.0,21.0,19.0,34.0,20.0,23.0,22.0,19.0,AFAFBGBGBABGDDADCFCECGGEAEACHDHDEFCFDFDECHHGDEDEGGFEBBBBBEFEDDFAHCBEDDBACDCDAHAHGHDCFCFDFEFEDHCHDDADBGCABDHEBBFBDCDHDEDEABDHEBFBCEAGGHFHEAGFGFGCGDGFGDGAGAGABFBFDDHDCDHHGHECDCFAF,False +663,30.0,32.0,21.0,26.0,25.0,15.0,23.0,18.0,GBDHGHGHGBGFGABAEEDBCBCAHAEEDFDADEGCCCGHDBBBEDHGGFCBBHEAACDBGAGBGFEAAAAAABADGGBGCDCFCFDFCBHAHBBBHBHGDBDEHBHBHBEAABABDDEAEDFDEBEBECEGEFAFCFCADEGCGBABABFBCEADAEGEGDCDGBFHAEAEFCDDHEHAHFDCDEDCAC,False +664,14.0,12.0,16.0,18.0,20.0,25.0,19.0,23.0,GFFDFGFDEAHBCEEHCFEEEABFGFGHGAGAGCGCFDBDBDEDEABABDBHFCFHDGAGEHEHEGDCDCFAAGAEEHFGFEDCHFHGGEHDDGBADDGHFHEHEHECFCFCDCAEFFFGFGCBHHCCFCFBFHFHEDADHHHHABB,False +665,1.0,1.0,5.0,0.0,2.0,0.0,2.0,0.0,CCCBGGAECEC,True +666,13.0,18.0,8.0,9.0,12.0,13.0,18.0,15.0,FADABCFAFAFGFGFBCBGGGFGDCDCABDHDAEHEDGDGEFFHCGEHHFHBGAGAHEGEGABFCGBGEEBEHFHBHBHBHBFBHCABBHGEEDCDBABABHGGAE,False +667,12.0,9.0,6.0,10.0,3.0,13.0,8.0,9.0,CBCHGHFADHGAGBCFDFAADDFCFHDAAAAAFCFEAAFADCDGDGHFHFHGBFBFBEBHGHGBBDFDEB,False +668,25.0,23.0,24.0,17.0,11.0,21.0,16.0,12.0,GDAFFFFHBBGCACGCECBHAEDBBFFFBCBCACACGBABEBEDDBFAHBHDAGAGBGBGAGBGAGEDBAFCCDCGAGHCDADACAEDFHACBEAACFDDBDBHBDBDFFFCFCFCFCAAAEDHFAFHCHCACHCGAGFFCEEBEBGDH,False +669,3.0,6.0,1.0,5.0,4.0,4.0,3.0,1.0,EABGBEBGBFBGDFDFDADEDBFHEAC,True +670,5.0,9.0,11.0,15.0,8.0,21.0,12.0,11.0,DFDCHCFFDHHAHACGGFBDBDCDCDAHEFFFHBDBDBEECFGDGHGBFCDADABHBHGGEGCCFFFFFDFHEBGCEFDFGFEFEHDGFGFC,False +671,9.0,14.0,11.0,13.0,12.0,14.0,11.0,23.0,HDHCHCFCFCHCFCDADADEHFHBAEGFGHCEDHFCCDEHAHFEBBBADCHHHHDHBHEDDDADHDBGBGBCBFHEBEFGBGHGFFHAHGHBAFAGBEFEBEHEGFG,False +672,3.0,4.0,0.0,0.0,2.0,6.0,4.0,2.0,HFHFAAGEGFGFABBFGFBEB,True +673,17.0,21.0,20.0,5.0,12.0,13.0,17.0,15.0,BCBDBECHCAAADCGGGGFBABABEBCBCACAGHBHDHBFEEEEAABCBCBAAHBGGCGBGHGFGAGFFCHGHGHBABFBFHCHADDFCCCECECHHEAFBFBCHHBCEGGCFAEAEGFF,False +674,14.0,34.0,17.0,24.0,19.0,23.0,30.0,24.0,BBGEGHHHEHEFABDCHCFBDAGBBBBDBFCFCFAHHEHAFGHGEGEDBDBDHCFCHCEDEDEDGCGCDDDGDGAGAGEGBHHCHADFDBBBCDDACGHGEGEHBGBGHFEFGFBBDBHBFBDGGCGCDFGCBBBDADGHFCFADGEHFCFAFGBHFHBGEAEBBBAFGGDGFEFBBHEHEBABF,False +675,22.0,22.0,20.0,24.0,22.0,17.0,36.0,34.0,CHGHGHAHAHCECDBGCADHEEGECDGBFCCHCHFGFGBBHFHFHEGFGAGCGCGDGDCBFBFEFEHEDECCHBGBDADHFHEBDBGFGBAHGHGEACGGAEAHGBDCDGDHFHBHCECBDHGGGGHBBDFDFHAAAAAHADADHGHEHAGFGDGAEDGDEEBHACFGHBHBHCGGGCAHEEAEHEFDDDGDBBBAE,False +676,5.0,3.0,7.0,7.0,6.0,1.0,5.0,6.0,EHCHEBAGEGDGDCCCCABHEGBAEDEDCDFDADAHHCHG,False +677,14.0,12.0,18.0,20.0,14.0,12.0,11.0,15.0,CCADHGFACAHGHDDDDDGFGHBADGBEBCCDDDADADABBHCFCFHBHGAGEEEEEEEGEFHCDFAFCCADBDCDCDCBBBBCHCBDAGAEHDHAHAEEHEHFFCGCDFGECFFH,False +678,20.0,18.0,16.0,16.0,18.0,22.0,18.0,25.0,DFFHFHFGFBADAGHCBCAGBCBFGFACBEFEGABBBEGHHFHFDFHEEGEBECFCEBEGGADEDEAEACHCHABEHAHAFAHAHAFBFAECECHCHGHAHBHCHFHGDCHGHEBDBDGCADEDGGFBFGDBDCFFEHDFDFDGDHCHBGAAA,False +679,13.0,13.0,11.0,11.0,12.0,13.0,13.0,10.0,DADAHACGEBDGEGEDEAACHFGEGEGFGFCFAFEBCBFEFHCCFCHCHEHAFFDBBBHGCEBGBGAAHFHGHBFDEGAGBBBBDDADADEDACFC,False +680,21.0,9.0,11.0,23.0,10.0,11.0,13.0,22.0,BHEFDAEAEGGAGBCHCBAAHAFDFGGGGBHADEDACFCFAEABHBHBAAADFFACDDDHDHCBCFHDHCHGDAHAHDDDCDADEHFFAFDEHHDHECDADAGAGBHHGHEHEHCDGDGD,False +681,29.0,26.0,19.0,24.0,29.0,20.0,27.0,23.0,AAHAECBCBAADACAFFGCEADCBGHGFEFEAEDEDBDHDEBHDHAACAHAEBCBDFFHFBFBFBFGFBEAHBCAEAGAGBEEEEEEEEDCABFGFBDHFAFAGBGHGCGEGDADHDFGBCBHBHACEBDADEDEDGGGGGGGBHBHDHCFGBBEHCCAHHFABDCGGECFBAHGDGDCEAEHECEGHDFDEDGAHA,False +682,12.0,18.0,15.0,23.0,25.0,24.0,20.0,8.0,DADHGFBFDADAEECECBFDHDBCBABAHFFFFEFEFBFBFBEDFDEAFCCHEBBGECCCCFAGBBDBGCEEDHGGEGEAEAEFDDDGDAFEGCGCGCFEDDGDFHEDGGGGGEBEDFDEDHBEBDCCEFFFEFEBABFGAGHGD,False +683,10.0,19.0,7.0,19.0,5.0,6.0,8.0,11.0,CHCGBDFEGADBBBBBEGHAFAHBGFACAGAHDBDBDADHDGDBDCCCEDDHDADADCDBBBHBFBDBDFDADEHHHBHGGEFBB,True +684,10.0,3.0,3.0,5.0,2.0,4.0,6.0,12.0,DBCHHBHEDEGAGAHFGGHFAAAGAGADBCHAHAFDFDACHHHHH,True +685,10.0,19.0,16.0,24.0,9.0,16.0,18.0,17.0,DGDFEBDHDADCDBDHFHFHAGCHCHAGEEBGBGBAFDHCBADCDHAHEEABDDFDFABBCDDADCDFDFBBGBGHECCGCGDECGDBFGGEGECHCGFFBFBDGFHBHBHBCGCGCGBDDDFHFHFHA,False +686,11.0,7.0,14.0,17.0,14.0,20.0,12.0,14.0,HDHABCEFFBEHCGCACACBHBGEGEFFFBGCECDCDEHEDEGFGFDDDDGDGAHDHDADADFFFAHAEDHFBADEDBCCGHAEEECFFEFCFHFGCGAHDFGFHFCFH,False +687,19.0,24.0,19.0,21.0,13.0,20.0,17.0,22.0,GBGCDCDHFCAHAHBFFDCAGBFBABCFFBFACBGHGHBFFGHDDADHFHFHBGGHGAFDFCGAGEDEGEADDFCBABFBABAHEDEGFGFCBCFDDADACECEBEBCHCACFEGCHBBBDDDGHHDHAHAFABDHEHEHEGEDBABCBDBHCHC,False +688,11.0,6.0,12.0,7.0,7.0,10.0,7.0,5.0,CCBGGGGFABECFADHEACFCFGFGEDFCFAFBHBCBHBDCCHCAAAAAEDDDDAFCFCEGEAEH,False +689,1.0,5.0,2.0,2.0,0.0,1.0,2.0,2.0,DHDGFGCBBBBBCHA,True +690,15.0,19.0,20.0,21.0,26.0,23.0,15.0,18.0,GBGBGEFEGECEDHDHDHDHDCGAEACGCFBFECCACGCDEDFDHDFBBBEBDHGHDCBAAAFBHADFBFHFHFHFEDDADEDEFCBBAEEGEACCHCEGACEDECECFFFFHAHEGEBABEDFBHEDEAEADFDCHFHFCGEBHCFFFGBBECGBG,False +691,16.0,20.0,16.0,13.0,21.0,17.0,19.0,17.0,EEBEDECEAEBBBBEHFBFBFDCDCBCBCAFGHGCECGGDHAHCDCFCEHDHDBBFHFGEECBGBFHDHGHEBEBEAEFBAAAAEAGGGFEFCFBABDFGFDFHAEEGHHHGDFHFGCGCGDAAACADEGBBCAHGEGH,False +692,15.0,18.0,25.0,15.0,20.0,16.0,23.0,15.0,DCAGACABGEGHGBBCAEGHHDAAAFGCBCBCGGDGCGCHCDCDAFCFGHGCGCEEEHBGGECACADEDFDFGFDBBFBCDCFCDCEEHEHFDBDBGEGFFBFBFEECHGHBAGABABEHEHGCEHBFDCCGDHEHEGBFAFAECEC,False +693,18.0,15.0,17.0,18.0,19.0,18.0,17.0,13.0,DAEAFACADHDHCFCBBBDFDEGEGEFDGBEFEBGHGHEHGGAFAFAGAEDEBHDADAEAEDEAHGHAHCECEHFHBGFAEAFBCGFDFGCACADFCGCBCBDAHFBCDEBCFCFGECDBDBGBGECECFDDHFG,False +694,7.0,11.0,9.0,10.0,9.0,4.0,5.0,10.0,CDDDBBCGFGDHDHEHBHEHEBEBEAEAFHDEGEDHBAAFHCBFEGCBCBCBAAHACCCGBHDDD,False +695,9.0,7.0,7.0,14.0,15.0,8.0,16.0,16.0,DFDCDCDEAHDDDBHHFHFCDCHCFBAEEDGAEAGGFGHAEECHGHGHEEGDGFEFEDEGBGEDDBHBHGEGFAHAEAHAHGBGHGHGDECB,False +696,24.0,23.0,24.0,22.0,20.0,19.0,26.0,26.0,ADGDAEBHCGCHCEADABGBGBFEEGFAFAFBFGDGDHHACDCHFACHCGGHGHDHCBGDHBACHBHGHGAAEBFAHGGDGHGFGDCDCGCDCAEGGGEEEEEHDFDAAAHADAFADEBBBHEHECACBEEEBABFCFCFCECFCHBHBAGABHHFHBHFCDEBCDGDFDFDCBFBCBEAGDGH,False +697,19.0,24.0,22.0,23.0,29.0,24.0,25.0,34.0,FCFEAEAHCGEDABFEFDHCHCGCGCFHABDGEGFGFGBHBCAEEHGBCBCBCGHDHFHABGHDHCCCAADDFDHDCDHFBEHEHEGFBBHHHADEEEBEBFACHHHHGHGABBBBEDCBBBEDEDFFFFFFHCHDAEFEGDGHFBDGEHHGFBDADECEDEDGFBFEGCGHHCHCHGHEFEAAGAGEGDGCAHAEAEBD,False +698,13.0,19.0,14.0,18.0,18.0,16.0,11.0,16.0,BDBFFDFDFGGHAHBHBHBHFGAGAHDHBEBDBHBFBFHCBEGEGEDCCCCBGHECDCACDBFCEDBDFDFDHDFEFHFHEHEFEBABDEHBCDDHAAADEBAGAEACGEAEFBCEGEDFCCAGE,False +699,20.0,17.0,18.0,13.0,20.0,22.0,16.0,23.0,ADHHHHFDFBFAGADBEFFFEFEGCFBDHCAEABAEAEBHFECCFDFHHHHHFHCHCHEHEAEBGHACABFCFGAGDFDFCBHGCFCBCHDEDHGHAFDFAGECECEFAGCDEGEHEAABCBGBGBGBABGEAHGEAFHFGCECADBDB,False +700,7.0,10.0,13.0,7.0,8.0,14.0,8.0,3.0,FAAEFBFCFBFBEDGHCCCCCEDEDFHECDBDGFGFADGBEFCFCGAAAHEDECACFBFBGGGFCFCBBB,False +701,16.0,27.0,21.0,29.0,23.0,22.0,14.0,18.0,ABAEADACBDBFAFDCGBDEDBBFBFADHHAABHDGABACDBDEAFCHCECHDDACAFDFDFEAEDHDFBFBFCEEBECDCDHABFBGEGFHFHGBDEDEDEDCDHDHFAGDGHGHGHBCBCBFHCEBEHCCDCBFBFBECFDGGGFCECEDHBGBCFEEDGBFBEHEDE,False +702,22.0,31.0,14.0,20.0,15.0,20.0,18.0,12.0,GHADBDAFCHAEBDBDBDFDEAAABADEDCAABBEGEGFGEGFDFBFBAEGBBCBCBEGDCDAHCHBADADGFBFBHBGBDCFGDGHCDCFCBEAGFGFHFEBECAFBFBHBHBFBEGEGEBEDAHABADABBGBCAAGDFBAGHCCFDFHF,False +703,21.0,26.0,13.0,16.0,14.0,14.0,14.0,17.0,CHABCBFGFAABAGAHAHAHACBDFHAHEHGCACDBEHDGBHCECEHFAACABHBABABECGBGAGEFCGDEFHBBFAFHFHAHEBEFEGBGBEBEDDDDDDDAHHCBCDDGEADABGBDBFGFBFBFBGEDCBB,False +704,1.0,0.0,1.0,1.0,3.0,1.0,3.0,0.0,DEECEGFGAG,True +705,7.0,6.0,9.0,6.0,4.0,3.0,8.0,5.0,AGABCBCEHFACGFHHCHEACADDDDGBGBGBCEFHBDEDACGCGCGA,False +706,6.0,5.0,9.0,7.0,4.0,10.0,8.0,4.0,BGHGEDCHCHCGCFFGDGDGCBCBAADFFAFEFGAGADFHBAFCBCEDEFCFD,False +707,10.0,10.0,4.0,9.0,12.0,8.0,9.0,7.0,EECFAEAHAHAEAEBEHFDFDAGCDHBHGGEGEGFDFDEBADDCHFDDBFGEGBGBEBEAHAGBFBABC,False +708,11.0,14.0,22.0,17.0,26.0,26.0,22.0,25.0,ADBFFHCHCHCDGFCFBHBHBAGACHDFEFHCBGECDDGEHEHDHEGEGEGECBHAECDHDCDEEFHFDFDABHGDEHEGDHDGFCCCHCHDHDHBAEEGEHEHGGGBBFEFEDEFHFCFAEHECGCAFFFCFBBCAFBCHEEGEGFFECGCGFGFGFAFAGB,False +709,20.0,25.0,16.0,17.0,13.0,14.0,18.0,22.0,CDEHBHBHAHBHBGDGEGBACAHAHGBGBGBAAAGFDEEBGBABABFGACACHGHDFDADHEFDHHECFDACABGHFHDDDAEAEDGDCDCFCBCFHBCBEBEBEBFCGCHFEGGDDBBBCEHGDACABGHGAFHHHBFAFCFHB,False +710,30.0,23.0,16.0,22.0,21.0,35.0,15.0,23.0,FAFAFAFEFEHAHAEBEFDFDBDHFCEAHHHHBEFDADHEHBCCCADEHFHFHFCGGDECGCBDBGAFAFBCDAHADBECEFHCBCBAAAFAGBFADDFDFHBGAAEABFDEDFHAGAHAGAGEGHFEFCABAFCBEBEBHFDDDFDADEEEFBFDACEGFBDBHBHBFGFBFCFGGHAHAFGFC,False +711,6.0,6.0,12.0,7.0,12.0,9.0,12.0,10.0,HGEDHDGCGCGBHBHGCFAGABCBGGEBCHCHFGDEEEHEHAHFHCGDFEFAFAFDECECDCFABCGEGFCEDE,False +712,23.0,31.0,32.0,27.0,25.0,14.0,31.0,14.0,CGABCFCEHDFDHEHBDBDECCFBDGHGAGBGCHCBAEHEHDFDBDCEFGCGCFBAGGGEFEABFBGEAAAAHAGACACECACBGDGDBHBCFGHGBCAAAFBDDDDDDFGFCECBBEEGDADCBEAEAFDGEGCCBCBCBDGCECGCGCGCECECBFBDBABDBDHDCEHEBECGAABDBGGGDEEGEBBAHGGDH,False +713,4.0,5.0,5.0,9.0,4.0,5.0,6.0,6.0,BEFEACAHDHDHGHBDCHCDEDFDGDBEFGDGDFAFBBGACHCG,False +714,18.0,19.0,22.0,14.0,25.0,27.0,18.0,19.0,GEHFCECFCAEFBFAHBCCEBFFEFECDADEDEAEFEBECECGHGAAADAGHBFGFAFHDEABBDGDEHEFEFDBCHEGCCEFBFEHHHHGHGCAFAFHFHFGEHEHCGDFEAEAGFFBADAFFCFABGBABFBCBGBGCDCDHFHCECECDHDBGBCBCGG,False +715,17.0,8.0,11.0,12.0,13.0,12.0,12.0,14.0,BAGDHBHDHABAEGHFDADFECDCGCGADHDHDHABCBHGAAFBFBEHEAFCFAGHEBCDFDFDCHCHCADAEHEGEAEGCGCFEHAGGFAFEFEAEAG,False +716,16.0,17.0,24.0,24.0,21.0,17.0,16.0,24.0,FCBCBHBCBCECDCDAFFHHHCHDBEFABAEDEDEDECFDGGGAEFEFEHCADAFACEEECFCGAEDEDGHGDGAGFBHDHFHCCGEGBDHGEBHHHEHACAEGFDFDHCECBADECHHHBBBFBFBDADCCFCDCBCDEDHHCGDDAAAHBHGHGDGF,False +717,30.0,23.0,30.0,24.0,12.0,21.0,21.0,16.0,ECEDACAHEHCACECDCGCBHAGDFACBCBAFGFGBACCCCACFGEGFHHAHABGBEFFBFDFCGABCDCBBBBBAADADGDFDFHFDCDCHFBFAAGAGAGAGFCCCHABGDGDBDCDEBHDCDCDBGFFHHGBEAAHAHDFDEDAHAGDCDBHAFGGGBABDFCACACBCFEEAE,False +718,8.0,9.0,11.0,13.0,10.0,18.0,7.0,15.0,BHBGDHDHDEAEFFAGAGABHFFFADHDHDGAFCDCAHBDECFAHDHCCBGHFCECEHEFDBDCDGEGDBHBECFCFCFHBEFFFFFHFHE,False +719,12.0,23.0,32.0,23.0,25.0,25.0,24.0,32.0,ACHDECHBHFHGHGHDADAGHCCEBEBCCGHFFGFCBEGCCDDDBGFDHDHDHGFGBCFCGCDCDCDCFGEDBDBEGGCFEFEHEBEHECBFDCDGBGEGBGEGCFEEECGFGADCFEAEADBBCECEHEBEDFHFCFCAABGHHHHHFAFABCCHCFCAHEHFBFBFHCGFBDGDEBHBHCECGDBAFHHHHHDH,False +720,9.0,6.0,1.0,2.0,6.0,3.0,3.0,2.0,AAABABDBGEHAGABCBGFHEAEDEAEFEFBA,True +721,4.0,4.0,5.0,4.0,1.0,4.0,3.0,0.0,BGBCACGCDDFDFABACECBFAFDG,True +722,16.0,8.0,13.0,19.0,18.0,17.0,9.0,17.0,DFEFCHCGADHDEDAHEDEBFHFEFEAEDEDHAHADCBAFACAHEHDCGCGCDCDHDFECEBEDEDEFGGABFBFGCACFDFAFBDGFHCADHEHEGDAEAHHHBHFHFADCFEBGA,False +723,20.0,21.0,15.0,7.0,15.0,20.0,22.0,15.0,AFCDCFCFGFGAGBCACBHAAFGFBBEEAEGHDEDBHBHEHBCGEGFACEGHGHGCGEGECAFFGEGEGEGBBFAFDCBCFCFADADBHEAEHGBGHGBAFAHCBADFBHBCBFAFHBABABAFABHFGFGEHCG,False +724,22.0,23.0,14.0,13.0,20.0,26.0,11.0,21.0,DEBABADADEGBGBEBHBCCAAEAFFDAAAAFEFAFGFCFCBHBCFFFCFBFDFEHHDHCHCFDEDHBHBGAACEFAHHFABAEEEEGBCHCECACGDHAFDFHFHFEFHAGGGFCHBBDBHBEBFBFHHEHBBBABEEFGFEDGDAHAE,False +725,21.0,25.0,25.0,29.0,21.0,32.0,25.0,20.0,FGGGCGEGDFAHHHCCCGAEABFBEBDBDHDCDEDAFGDGAEFCFCEAEADABCBGGGGGCDCDCFFFEHACBCBCGCFCFDBDFCFAHBDDFDFBEHEADCDFHEHFFEGGDGFHEGEBBBDHEAEAGAGAHBHAAGAHAHDDCBCFFFHFEDGDHDBFBEAHBFBEDFCHGFGDCFEGCHCFBFDEDFDABBFBCB,False +726,16.0,20.0,16.0,17.0,10.0,18.0,13.0,17.0,BBBBGCACACBFBABFBCDHGBCHCBADABFCFCFGAHEGBGEEEFDGDFAGAGCBCEFHFHGHFHAHFDFCHAHAGEBDBDGDCDCHFHBDDADCBFADEEEHHDGFGFHADEDHFHCBCBABADF,False +727,10.0,29.0,22.0,26.0,22.0,17.0,21.0,19.0,BCBCBCBDAFHFCECDCDCBHECFCGAGDGBHFDGDGBGBEDEDEDBCBAFAGHBHDHAADBDCGFGHDBDEGEFBBBCBEBEHECDHEGDADCDHDBBGCEHFGCAEAEBEBFBHADCECFCFEDGHGHBHFHGHBCFGBCEFDHGBGFGEBEHEFFDDBDECGD,False +728,11.0,13.0,13.0,11.0,13.0,20.0,15.0,18.0,EFFFEBCDCHCAAAADFHFHGAFDFHFCFBEBGCGAFBCACAHAHEDBBGEDEDCDGBGFGFGCHCFFDHEBBCGGGGGDFHAHDHBFFCHHDHEHEFBHBHECAGEGEFEFBH,False +729,26.0,25.0,13.0,24.0,26.0,16.0,21.0,19.0,DBDFABGGFGHEHAAAAABFBFBGBDBABAGEGCGFEEGEBEDHAEDCHABCDEFAFAGDHHAHADAFAFGBGAGHBDGCHHHBFFEAEDBDBEHDBBEDDHDHDCBCBEHCACDHFCGAGEGDDBEBEBEAGAEADABAFFFFEHGCGCEEEEBEGDHDGECEABHDCD,False +730,16.0,17.0,13.0,13.0,6.0,15.0,8.0,16.0,CCHDADACCDBABEBHDFBEAGBGFCECHBAAEAEDEGCHCHAFBHGHDBDADAFBDBGBHCHCAGAGHHCDCFFDFBFBADFBFBFHAAADBFCFGFBFHHHH,False +731,16.0,23.0,24.0,23.0,24.0,17.0,32.0,25.0,FFFFFFFDDEDGGHGHGHGFDHBCACGEGEBEBECFFBFBDECCDEHCFGEACHDHDHCFDHEGABHEGBGEAEHBAGCGHGHEEEDEDHFCGDGBAHAGAGDGBACCEAGAGAGAHFBCHCGCDCHCHBDBGBEBGCDFDBCBHEHEHGCGHBCBCGCAADDDGHGBDEDEGBBDFEAEGBCH,False +732,2.0,3.0,2.0,0.0,1.0,3.0,2.0,1.0,FCFGFHCBGBAEAB,True +733,6.0,2.0,3.0,2.0,1.0,4.0,1.0,4.0,BFFCHCHCHAAFADBGFDAHAEA,True +734,5.0,4.0,6.0,8.0,4.0,8.0,3.0,7.0,DGHGDEDEFAFBFBDDEAADFDHCHFAFBDGHHHHCCCCFCFBEA,False +735,11.0,7.0,8.0,6.0,4.0,4.0,8.0,5.0,CHCACAGAEDFDCBHDHFHBCDDHAFGGGCACAGAGBBBGBEBDFAAGAECEA,False +736,20.0,16.0,16.0,26.0,10.0,23.0,15.0,12.0,BDBHCCEBDBACHCDFGFCADHDFDHAECDAGAGCFEFCFEDDDDDDDCFHHADFDABEGGGAGAGADABAFCFAFDBEBEGACADDDHAHBECHDGBGBDDEGEGDBFCFHBADGHGHFFFBFAFAFCFCFBFCFBA,False +737,23.0,11.0,24.0,14.0,10.0,9.0,22.0,11.0,FHADCDEAAAABDBHAFADADFCGGGHGAEAHCGDDCDCDHAHCGGGGCACFCBCBCGCHAAFAHEBADAECGCGCGDGECEDGBFCDBAGACFHAEGCGEGBGCECHGGFHFABABABCCDCE,True +738,26.0,23.0,28.0,29.0,22.0,16.0,18.0,26.0,EHDFFHFHEAFFBBEHDBBBDBDCGEGEGCBCDGHAHDEDEDFAFGCCCACBDAGAEFHFHADAFHCDCDBDHAAAAAHCHCHFHFEFHCHFBAEDHCBCBCBEBDADGDAHAGACACBHEDDDEHCHBDECCGBGBHDCDHDBGCCBGDGCHHGFBAEGEAFACACBCEEEEHEGCGAADAEBGDDD,False +739,8.0,2.0,10.0,6.0,9.0,6.0,10.0,6.0,CGBDCDCHHEEAEACAEEGFHFDDDDFGFEAHCCCCCBFGAGAGEFAGAGHCEGEGH,False +740,11.0,8.0,17.0,13.0,9.0,9.0,18.0,8.0,BGAGBECGDGHFHBHBGDGDGCCCCCCFCFDFAFHBDADGDGBBCACAFEDGDHCECHAEEEBDCGGAGFGCGDAAEDEACHEHCCFGAGDGF,False +741,4.0,2.0,8.0,8.0,5.0,1.0,3.0,4.0,CECEAEHCCADDHDHGGEBHBECFCDDDDCDAGAC,True +742,2.0,9.0,1.0,2.0,5.0,5.0,1.0,4.0,CBHEDBAFFDBABEBEBHFHBHBFBGEFE,True +743,18.0,19.0,21.0,21.0,22.0,11.0,26.0,21.0,EAACDDDHDGEGBHHHHEBEBABHEHBFGCGDGEGCDCDGGCGHFFDFBBGACADADHHADCDGDGBCCCBEDECAGHGHBFCFEDEDEGGCBEFEBEBEHADBHBGGGADADFGFDAEAGBBHGDBHGHCHCACACAEFEGHCECEAFHCHBGEGECA,False +744,31.0,23.0,20.0,24.0,21.0,22.0,28.0,21.0,DADEBEBEDADABCBFGGGGGHGHAFFGBGBGCGDGFGHBCCFDEHEADABAGGBGFCFCAGAHHEDBHBHFFEHAGAGBCDFAEBHDDDDEHHACFBHDGDGACFFBDBAAADAHAHCHCEGAHAGEEEEEBHFFGADABABEBEBCDCBHFHFAADFCGCGBAADDDFCCCHFEFECEAGACAGDGFE,False +745,5.0,11.0,15.0,7.0,10.0,9.0,7.0,16.0,EFHFBCACFCEHBCBABABCECFHHHHFEFHCHCFCBHHGGEGEDDDHAFGEGCBDDDHEEAFBBCHCHEHGHBCBCDCG,False +746,1.0,0.0,6.0,5.0,2.0,2.0,2.0,0.0,GDCDCACECEDFDGCCFD,True +747,14.0,8.0,8.0,12.0,14.0,15.0,12.0,12.0,HCHDFEEGCBCDCAEEEBEFEFCABABFBFDEGFAHEHAHCHGGFCFDEDAHCHDFDGDGABHEAAFAFHFEEGAGDDFBHBHGDGEGAGAFAFD,False +748,23.0,22.0,15.0,27.0,27.0,24.0,31.0,19.0,CFEFAHGBGDEAEBEAEBHBDDGBFAHCGFHFHGEGFAFADBEFHBEBCCFCGEGADBBGGCGBGHHBEGEGABBEEEAHAGEGFGAGFCCBFAGBGFGFGFADDBDBGBFEFGFAAAABHCDDDDDDFDFHFHBGDEAEDDDEDEGEDEDECHDHCFAGAHAEAGADFGHEHDHCCGEGEDBDFCHC,False +749,18.0,23.0,17.0,19.0,17.0,23.0,21.0,21.0,EAADEDBDBFBEECFCDEGFDFHBDAFFBCCCGCHCHAFAFAGGHGECECEBEGAGDGDHEFEHCBAADAFBFBHBABGBGCFCDHFBDEDECFGFBCHHDBBCHDGDFFBFBGDGBHHAHABADADEEGHGHBHFFFFEFGCGCDEHHGHGAAAGBBH,False +750,26.0,15.0,24.0,31.0,22.0,18.0,27.0,36.0,HFCEEEDBCEHFDCDCDGDAHEDGBCCDCGHDEECFHFAFADHFCGEEAEHEHECGABAHFBFBFDACBDBDCDHDHGFBFACAHAHABAHHHCDGHGHGHAABFHFGGHADDDDDADCDEDGDEAGGGGAGBGACCHBHBFDDEEHEDDHCHCHCHGFGAHHHBHFGCGHEEDEDFBAGHGHCECGCAHAGFEADAGA,False +751,2.0,2.0,6.0,6.0,5.0,4.0,2.0,6.0,DCHAHGHCHCEBEGDFCHCDCFEFEDEFHADBD,True +752,12.0,16.0,4.0,9.0,13.0,13.0,11.0,4.0,EBEBDBDBFAHAHADAGBCBFHEEAFAEEBEFGFEFAAAGGGBAFCFCFDGEBBBBBBGAFEEDDDGAGFGCEFEGBDDFHB,False +753,20.0,22.0,13.0,25.0,23.0,25.0,27.0,11.0,DBDAFFDEDEDEFEFDBCFFHDDEEEBEFDFEFEGBGCHCEBEHEHAABAGGGDEAFDFBGGGDFAFAFACHEEBHACBFECCGGGGGGFDFAFCGEGEFHBDBACAHAEFDBDFGABFBEGCGCDHDHDGDBDBDGCFBGCAHGDGBBFAFABEGEGABADADGB,False +754,13.0,24.0,24.0,21.0,25.0,16.0,20.0,11.0,BHBDGCGFGFGFGHGHBFGCEEFEFBAHEHEHEBCDEDEDBBCBCEFECGCDBACAGDGDBBHCCGDAAEAHCEFECABABDGDGCBEDHGFEDEDBGGCACDDBEBCBDFGGGEEHECECEFDFDBBBDCHAFDCBCBCGCFFACAEAEDBFE,False +755,21.0,23.0,12.0,20.0,22.0,23.0,13.0,24.0,FBFBCBFBFECEBHBHDHBBBFBACGBGBDAGFDACHHGCGHFDBHEEEFEAEBEBFGAGAGEDDFDFEFBCAFDFEAEAEDFDBDHECDCFCEAHAFEEHAHGHGHCBDAEGHBDDDBDEHGBAHAFCHGBFHFHEHEADHFHFHFDEBCAAAAHAD,False +756,9.0,16.0,8.0,17.0,8.0,7.0,7.0,4.0,EFEFGFGCCBABHBDDDDGDABBGBFBFEACDBDEDHCGEGBCBCBFDDDEAFABADAHEBADHDCCEDGDBBBAD,False +757,15.0,20.0,18.0,27.0,18.0,16.0,16.0,19.0,GHFBGBCEEAHDBDAHAHEBFFDDDDBFBEEAGBDHDBEGHAHADDEDCFCFBHAHBHDDGDGDECECGHGFGDADEFCFCFDADBGEEBCDEDGABABHBHBHCDCECECEGACCEABFBFBCCHABGHFHFACDDDDDGHECGFGFH,False +758,24.0,10.0,20.0,10.0,13.0,18.0,25.0,18.0,HEHAHAFAHCGCGCHEBGCGHGHGFGCGEABGHGFGHCHEAACABAHACFEAGCECBGGGGGACDFHFAFDFDFDFBEEAEAECFCAADAGFCHHECFHGAGHGEAHFGCCDBDBGACAGADABBDBDCFAFHGEFCF,False +759,5.0,2.0,3.0,3.0,1.0,2.0,7.0,3.0,CFAGGHGHGHBDGDGACEDACAGABF,True +760,23.0,15.0,19.0,10.0,31.0,25.0,21.0,16.0,FGFGHGDGBHACAFAFEFEGEBFGFGFECEDBFEFEHHCFAEACFBBBAFEDCGCEAECFCBBHEGEDEAEFBFGFGADCCCBHAAEEBABAHAHACECFHFEDEABFEDEAEBECACECGFGFEAGAFEFACHGDGAEAEGHHHHGDCBEDEHFHGGCG,False +761,4.0,5.0,6.0,6.0,5.0,5.0,6.0,6.0,EFBFBFGDHCHFEFGGBDAGACHCHDHBAAECCBCDEDEDGHG,False +762,5.0,7.0,14.0,5.0,9.0,9.0,6.0,9.0,EGEFHBHFGFHCEDEBEFACAEAECHCHCHCHBGCFDFCCACBCDHDFGABHBCECDGGEFCFB,False +763,7.0,10.0,9.0,14.0,6.0,13.0,15.0,4.0,FHBHAHAFAEDCDEAEHFDDGFBFBFDGGFGBGBCBFDGDBCGEGECAGAGDGDFDCDCDFGCGEBDGFBACFBFDCG,False +764,18.0,17.0,21.0,10.0,17.0,19.0,30.0,14.0,GFCBGAFBBEFFCGHGEADAHFHEAEAHAHFGGGEGECCFAGAGFFCACBFAFAFGGGAEHGHFHBHCACHFAFDEDHGEGDFBCGCAHGCEBEHCBGBDDCAGBDAGECECACBCBCGGGBBBBBECFCFEFHGDGDGDGEGEGC,False +765,16.0,9.0,24.0,14.0,21.0,12.0,17.0,12.0,FCCCCEGDGDFBEGCBCDDDDCHFGACDHECCCEEAHGHGCCCFEAAADAHGEBEFDDDCDCEAGCGDHEAEAGADAGEFCFCFGFGEAFHEECECEGHGBFCECEBFBCAEBGBGHAHAHAHBE,False +766,2.0,5.0,3.0,5.0,5.0,3.0,5.0,14.0,GCCBCDHEEEFHHEBEHGHBHDHDHAHFGAHDGDGHHHHBFB,True +767,25.0,19.0,25.0,19.0,30.0,21.0,34.0,24.0,AABAGCCCGCDFDAEECGCHBHGHGHDAGCGDFDCEGEBAGFEEEHHAGAGAGFECEHGCECEHFHABEEEBEFEBEFEBCGGGDGABEDEDADGFGFCHHHHDDFBFBAEAEAHGFCFAAAAABAFHECGCDCGFADDBHBGCEHFBBGDHFAFHBHCHFHAGGGGGGAGCGEDEBEDECHFHGBDEDBFGCCCCE,False +768,25.0,18.0,18.0,14.0,17.0,14.0,28.0,21.0,DBBECABABAFFCHGBFEAEHGGEEEHGHGAGADAHGCCFDFDGAFCECECDBBBFBDHHGHEHBHAHGCGFGHHCCFAEAECGAGFHHCEGGGCDCEHEHEDGDHDAGABACCBCBGFFBBHBABADAGGGGHGAGAGAECFBAGAFADAEHDD,False +769,1.0,3.0,1.0,7.0,6.0,6.0,6.0,3.0,EFGFHFCEBGHFBDEDEHEAFDDGDGDGDGBEF,True +770,10.0,20.0,19.0,21.0,15.0,21.0,16.0,16.0,CDHDGGGCGEGECDCDCDABFBDBFBFDFHFHDDBEAEHBGBGCDBGBCHHDGFGCHDHCGCAAHABAFHHBDEFEFCFDFCFCFAHEFBFBGHGDDDCBEGGFEBEAEBDBHCHAEFCDCBFEFEBHCGCBFDFDEA,False +771,4.0,6.0,5.0,4.0,2.0,2.0,2.0,5.0,DBACDGDBBHBHCFDECECACAHAHGBFBH,False +772,20.0,21.0,27.0,26.0,23.0,24.0,13.0,18.0,HHGDAACADHDEDCABDHDFCFDBCFCABDCCCCFFFDFBCBHBGEGHGADACFDGAADDDDDECEHEHDFEBEFCFHFAFCFCFAFCHHHCEBEBEGECECFCHEFDCGBAFADAEAEDEDEFEHEGDAAEBCAEABBFBFBEADGCHDBGBDCDFGGBCBCBEHGHCHBF,False +773,23.0,11.0,12.0,12.0,15.0,10.0,15.0,14.0,HHBEBEDEBGBDFCECGCGEGCHDHGHGBCHAGAGAFAFAHAEEEAEAGBGEGCGAACABBHDABFDFAHADGHFBCDDHAAEAEAEAEACDFDEAAAHFDCCGCHHGDBFF,False +774,17.0,24.0,28.0,15.0,15.0,16.0,18.0,18.0,EFEFEBGCDADCEHBHBHBFBECECBFBFCGCEDEDCCFCGCGFGFACCDFHAHGHBHCHEHECCCGGFCHCADBBBGHHEGCCCGCBHGEGBBBAADCDCDCDADADABFHFAGBDBAHGBBABFEFGBEAHBGCCHFHGDABACAFDEA,False +775,3.0,0.0,2.0,1.0,0.0,2.0,2.0,3.0,AGHGHFDFCHCAA,True +776,17.0,9.0,11.0,6.0,12.0,12.0,17.0,14.0,GCGDABAFGFGCCECFABAEAEBGADHHEHAAAEDEAEABDFCGBADAEHGHFFFGAGFCFDBHBFGHHCGAGHGEGHBHCECEAEAGFCFCBHGHGH,False +777,4.0,6.0,1.0,5.0,7.0,2.0,6.0,4.0,HEFEAEAEDBBGDCDHDFEBAAHEHEDGBBBGGGG,True +778,6.0,7.0,4.0,4.0,5.0,13.0,4.0,5.0,HEHEAFGFAFAFBGBAFFFDEDECBCFGDBEHFAFBFDFHFHGBACCB,False +779,9.0,7.0,5.0,6.0,9.0,8.0,7.0,9.0,DGBEBEDHAFAFHFHFCFCEDEGEDEDGHAFBHBAGAFBCBHFAGADAECCBGEGHHEHA,False +780,19.0,21.0,16.0,16.0,23.0,19.0,26.0,22.0,FFCAGEGEGAHBBEBEGCDFEFCFGHHDHDHDBEFFAGEGAGAGAHEHFAEDBACCCEDGBEACFCFEDEABABABFHFBGBGAGEHHACBCGCHCHGHEABACDBDHEGFGEADHFBDCDCEBBAGHGHEHEHGHDHDGDGFHABECEBDGGFGBGBEFFF,False +781,15.0,24.0,23.0,18.0,23.0,14.0,17.0,21.0,FEAGCCBABABAFAHCDGHFCAEGBGBGHHBBCBFBABAEDEDADHFECGDGAHEBEBECCGCHCHEBCFEDDDCGCGDGDHEFGGCHCBEFECAHDEDFDEHEGEFBBHGGCECECFBDBDBAHAHEHDHECFBFDCECABABHBGBCHFHDHE,False +782,14.0,24.0,23.0,18.0,18.0,17.0,19.0,17.0,GAECGCBBAGAGAGFEEDDFBEEEBBGGEECCCCBEGEGFGDGCHCHCHEADBDBHBHFGADBFGDHHGAGADDDDDCBCDHFBFHDAGFHFHFHCBCFEHHHBFCFHFCGCBCAGFEBDFCECHCACBDBCEAGDBDBEBEBEBABAFC,False +783,17.0,21.0,14.0,26.0,20.0,11.0,14.0,15.0,CHAHEHDHGCCADABAEDBDBFAEABGDDCGADADBBAFCEGDBEBDHGEGFHEHEHEFCFDGHADADBDBDCDCGBABDECEDEDFDCDCDADEDBDHGBGBECDHEHFFBAEAEBEBGHGEBCGGBEFHBHCFAFA,False +784,9.0,13.0,21.0,19.0,11.0,19.0,13.0,15.0,ADHDFGEBBCCDCDCFHAGDBCBCECEAGAHCDEAHBHEFEAHHGDCHCHDHDHFBEADFCGCHDHAFBGBGBEFDFGFECACFEFGFDCDEBGBGCFBFCDGDGCFDFHFHFCFCDCDB,False +785,3.0,4.0,10.0,4.0,5.0,8.0,5.0,7.0,FCFCGCGEAAGFCECECHFFDHCACGCGEBHFEFHBHDFDBDBHHC,False +786,13.0,15.0,20.0,21.0,12.0,14.0,14.0,18.0,BFDGDGDADECHCHCEDGDBDGHCHDGCABEEFEFGGDDBDHDHDGCCEBDFDFBHBHBHFHFAECEBAAAFAEAHBHGHDFEFBHBABECCCCCDEGHGBFFGHCDCBGDCCCFHDCACAFGHADA,False +787,12.0,21.0,22.0,19.0,22.0,24.0,29.0,14.0,CGCGEECEGGBEAGCFFFCDCEEACFBFBGBGDGDHDHCBCGADEHGHBFGFGFDFDBGEGEBFCFCFCFABDBCAFFGDGBFHCHEECDFDFCBEBFHGCGEGAGAFDFCEGEGEAAHHHBGCGCGAGDGDBDFGEDBDFDBCHADEEGEHEHABBFEHBCB,False +788,17.0,13.0,19.0,20.0,16.0,16.0,19.0,15.0,BDCEGHGDAFFHFHDADAHEEEECFCGDHBHGGGAGAEFGBCADGCCCCCCGCDCBEFEFDFECADABAFEBGBGAADGEGHADABHFHFCEDHDGGCDCDFDADGHCFBBCBCEHBHFHDEDEDEGHGAAAFBF,False +789,28.0,17.0,13.0,32.0,28.0,13.0,27.0,17.0,AEADADBGBAFAEADGBAAGDDEGEBEFCFCFHFHAEGEHDHAADEDHDCFCBAEGEGDGCGAGBGBGBFDDDEDGBGBGBDDGGADCDBGAEAGDBCADEDHBABAECHCECAFEHAFACDCDGEHEHFBEHDDDDFEAABDHGHGHDAGECEGEGDHEAEGEGEAFHDHDFAE,False +790,20.0,14.0,14.0,14.0,17.0,15.0,16.0,18.0,FCFDDDHCHCEGHADCBGFEFCFEEEEBEADABHBDEFCABABAGAGEHHBHBDAECGDEAAAFAEADBHCGGBGBGBEFEFEFABAGFHHGACDBDHHGFDACEHDHGHFCFDHCHCHCEFAGAGAG,False +791,18.0,17.0,18.0,19.0,20.0,20.0,6.0,18.0,FHFHFDEAADAFBBACGHDCDFAGGFEFADEDBFBFECEAFAFACCCEFHBHFHBBACHFDGDCDHDHGBAHCDCBHBEEEEAECBABCBCEDHDFDEDEDEAEADACAHFHFHEDCCABEHEBEHCFBFGFBDHC,False +792,14.0,17.0,13.0,12.0,11.0,16.0,16.0,11.0,DDBDBDAFBDBFAFAGBDEGCCECHCHCGFABGBCFEFECHFBABAEECBDHDGDGHGHGFCFHEAEGDHBCBEFHBGAGACAHAFGFGFDEABFBABGFGFGBHCAEDC,False +793,9.0,19.0,17.0,11.0,13.0,16.0,16.0,13.0,DCGHBFFCGEEBEGGAGFDEEBFGHCHCDFDBCBCFCFCGCGBBBCBCBFHFGCAEABHBABGBDBDFDHAHFGFHBBBGHGHECFDECEGHGHDAAGDBCECDAEAEFEFCFH,False +794,18.0,14.0,23.0,18.0,18.0,15.0,28.0,20.0,GBGBGFGAEFECEBGBECECFGDEDGFCFGGHCHCFGDAHHCHCFCFCGCGCEAHAEABACDBDBAGGCGHAHBDFDHEHEGAGEGEHHDCDGFHBHGHFADECACAEABFCAHGHGBDCDFDFBAGACDGGCDBGGADHDBFHEHEAEGDCEC,False +795,2.0,6.0,5.0,6.0,3.0,1.0,4.0,1.0,GDGECBCHDEDECBBFBCBABDGDGACD,True +796,20.0,15.0,22.0,19.0,22.0,17.0,35.0,28.0,EHGHCDCDAEBCBFBACHCGEFEFEFDFHGHDCGAHDCGCDCACBGEEHEHGGGEHEFEGGAAAAHAFFECCAGHGHGHBACACDCFEAGGGGGGGCGAFCBEHHGDGHGADAHGHBDGAGBCDCABAHDDEEFGGEHHHBBBDBDHDHDHFHEHBCDCGFGECEFFGFGEGHFBEDA,False +797,22.0,14.0,14.0,13.0,13.0,14.0,15.0,9.0,HCHGGBDEFAFAGAHDCGCGCHCGFAADEDEABAGABFEFEFEBDFGABHFDAABCHCFCADBBAGDGDGDCDFEFGBDBDFFGCBCBEBGAAAAAAHEHEBEGCAAAFHECEC,False +798,15.0,14.0,14.0,26.0,14.0,22.0,16.0,23.0,DCGAADDDHDHFFDBGGFGEGBBDHAHFFFFAFCFBDDFEAEDHDHGHGDCHCFAGBDFCFEFGAGHECFCEDAHAGEBFBABDEDADCDHAFCFAFHBDFAFADEGEHEHBHGFGCGHGCDCDBBHHHHBCBCHDEDEDEDHH,False +799,27.0,20.0,19.0,24.0,17.0,17.0,26.0,21.0,GFGDGDCDFGBGBEBGBHHFDADAHEHEBBBHFFGGCADACAGHBHAAFACACHBECEFAHADGDAEHECFABCGCAHBHAHDGEEHFDFHFDFCAHDBDBFEGDGDGHBDBGAGEGBGCCECEBEHAGABADADADECGCGCAFHGHBFACACFDEDEBGACAGHGFDDD,False +800,14.0,22.0,27.0,22.0,29.0,27.0,20.0,20.0,BCBCBCACACAHDBFCHEHEFBGGCGCABBHBEEEBECECBDHDEBAACGCGFGFDFGBCDAHHHHFFEDDDDEFFHFDEGGGHEAEDEGBBDFEADFCGCGCHFHGHGEDCHFFFDFDCHFBCBCBCEEEGACAEHEFGFDFCFBAEHECGDEFGHGAFAEBBBBDCEHFCFEFDCDEDE,False +801,5.0,1.0,4.0,0.0,2.0,1.0,0.0,1.0,HCAEACAFBEACAC,True +802,15.0,14.0,17.0,11.0,11.0,11.0,14.0,5.0,DGAEAFAFCFDADEFEFCACGEHEFGCHABACABHBADDFDFCGEGEAAACHCGDGCGBEBFDCABBBBDBABFGGCCCEGFBBBEDAHCGCGCGCED,False +803,19.0,24.0,22.0,27.0,21.0,24.0,25.0,26.0,HFAFEFEFCCCHCHGDDHEHEDEACCFAFBHDEDEBGCGBFAHAHAHFGDBAGAHBHFEFBFEFABCDHDGACACBGDGHAFBDBCFHFHDHDGDADBCFGGBDACGHGCECEGGAGDGDGEGECADHDABGBDDCECEHFHBGGEGEHBFBDHFACAFBBBBHEEEGCDHGFDFDFEFHDHDCBBBC,False +804,14.0,12.0,12.0,16.0,9.0,14.0,9.0,8.0,ABCBAFDEDFDHDCDBAFCBGBDBEAEGEBCDGAACABDECECEHEAGHGDBHFFFCGDADFFFGFDBDFAHCHCHCHCBADADADABFFGGEF,False +805,10.0,5.0,7.0,4.0,17.0,8.0,9.0,3.0,AAGAGAGAGAHECEFEGEHEBEAEFDADFEEEECEDECHGFEFAFBEDFGBEACBCEFBCCGG,True +806,16.0,25.0,13.0,17.0,23.0,16.0,21.0,18.0,CBGEEFEGBBBCHGHBAAAAGAGEGCHCEDBBBBBHHHHDAFFEEDEDAAADFEBHGHDHEGEGHCECEBBDADGGGGGDGHEHEHEBBBFGFAFDFEFEBEBCFFEBHBECDBDFAFAGHDFDGBHDCFCAABCBHEGDGDEBGCCAF,False +807,3.0,8.0,5.0,8.0,9.0,8.0,9.0,9.0,HFFFBHCHEBEBEBGBDCGCECEFDFBFGAGHHDHFACHDHDEFBGDGEHEADGDBEGG,False +808,18.0,19.0,24.0,19.0,15.0,25.0,23.0,17.0,CDGFCFCAGHEAEADCGEGACBGFGDHEEECACECECFAHAFDCDHDFEBEHDFDFHFGBEBGGGBBBHBHFAEAFGFAHAGAFCGCHCHGHBCDDFDFDGDFBEBEBFAFCFGDCCHGHADCBFBGBGHFCGDGBCAHFDFCFCBCBDAEABADGFGHC,False +809,24.0,16.0,20.0,18.0,20.0,16.0,26.0,18.0,HBEFGCGHAHADGCACAFBFAFCEBGBFDGAGAEHHCDDHDFDHDHDEECGABCBFEAEHDGGGGBABGFEBCAEGBCFCHGHBHBABGBHFEFCCCCAHGEGEFHFDGAEBHDADCGHEAEAEAEAEGEDCDADGDGAGAGAEHDGCCFCFCADBGF,False +810,7.0,10.0,7.0,14.0,17.0,13.0,14.0,8.0,DEAEGEFECACABGEGEAHGHGHAEFEFECHDDFDBDBCBDBDFGCGEBECEDDDADBEFEBDFGBDFHGCFFDGGFEHEHFHBGAGEGF,False +811,11.0,12.0,11.0,18.0,16.0,11.0,15.0,16.0,EBEBABDHDHDHEHGHFAAGGCAFEDDGEFAFHDBDBDHEGGGGBCBCFDDDDDEDBHFEBHCHABEFEFGHECECBFGGGEDHCHCGEGACAEAECHABCHDADFDFHG,False +812,7.0,8.0,5.0,1.0,6.0,6.0,5.0,5.0,HHHHAEACACBEBCCAFAGEFCFDBHBFBFEGAGEGBGFABBE,False +813,7.0,6.0,14.0,17.0,20.0,8.0,11.0,16.0,BCHCAFAGAHCEFEDEHEDCHGHAEDGDFCFHGHGHAEGEGFHBBDFEHEDEDHDEDEBGDDFBEHGABCEDECCCADGHEHEHCHCDCDCDCEEGEFD,True +814,27.0,14.0,15.0,25.0,17.0,16.0,12.0,25.0,HFFCACAHFFCBCFFGDDECEFEHCBCBCDAAAGAHAHDECEFHAHAHDEABBEBCFGBGDEAEAEADGHAHACDHHHBCBEDFFAFHFEEGAAAAAHAHEHEDDDDGAGDHDBDFFAHDBACACAGHHDGBGBEDDBDHFHECGDDDHDH,False +815,9.0,8.0,11.0,6.0,5.0,16.0,9.0,7.0,DDGCCHAAADDFEFBHDFFFDFCFCFCFEBEGGGCFCGHGHEAAAFFHBCBGBEBCBFFFCFCAAGAHHGB,False +816,27.0,23.0,14.0,24.0,26.0,27.0,25.0,22.0,DABHHHEHAHAEFDBAGABDBGHDAAGAGFBAHAHEEDABFGGEEADAFBCACGCGCEFEBEBDFDCDGDEFEHEHFAGAGCBCGCBCBEDAGGBABHDFBFBDEHEHGBFEFEBDFHFHFDEECAFGFGFEADHDAGAGADCDCHFHCEADFDGEAFBFCFDBEEDGAGBEFEHDHGAGHGHFBFBF,False +817,1.0,1.0,2.0,2.0,3.0,7.0,3.0,4.0,FFFFADHDHEHEGCFBGECFHFG,True +818,10.0,14.0,17.0,5.0,12.0,5.0,16.0,9.0,CACBHAACABGDCAEAFGBEHEGCGCGEGEDBGAGFHBGCECEFEGEGBHBFGAGHEABDFDBCBCBHEHGHGBDCACBGBECCCCCH,True +819,20.0,12.0,13.0,11.0,16.0,13.0,21.0,6.0,ADCECACDCEGDFFAFBGBGBGBAAAEBEBGFDADEDAACACDCHHBGGGGGGGEGAAHFEFCGDGBCFABAFEGCDHFECEDEHABCDAHFGAGEGAGAEAGBFBCEFEFE,False +820,24.0,22.0,18.0,21.0,20.0,19.0,14.0,22.0,ECFBHAHAHAEAFBFGDGDCBCGAEAHABCBHFEDEDGBCDCDADABAEAEBHDGDHCBAHFDCDHHBHEGAAFAFCHCDDEHBFBFDGDGHBAFCEDEHFCEHEHEHGCGAHABCBEFHFGCDCDFBFBFAFGBDEDAGCHBEBCBADAGEBEAEAFFH,False +821,24.0,21.0,19.0,22.0,19.0,13.0,20.0,29.0,DAHAHAFEGCDEECECAAEHEFDDDGAGAGAGABHBGEHDHFHEHAHAHAFBHBHCAADCEBBGDECHGFGHGAGEDFDFDHHHCGAEABFDGBECECAHACFCHGFBDHGFDHBHDDDDGGHEHAHBGBGBHEABBFBDBFBDAEEBECCCCCACHCBCHAHDGDB,False +822,16.0,25.0,27.0,23.0,14.0,15.0,16.0,28.0,BHCHCDCAGFGAGBFHEHBABGDHBABFBGBDCHCHCHEHAHEHCHDBGBHACADADAFFHAADACBCBEGEFDFDFDFCHEHDDBDEGEDHHHCDEGHCFGFDEDBBGFGCGHAHBDCECHCABHFCCHCDEDCDCGBBEHDHBGBFEFCACHCBBABCBDGC,False +823,19.0,16.0,17.0,19.0,13.0,21.0,12.0,12.0,AAFGBDHDCDFDEHBBFHFCDCABBFDFGEGEBCHDDDBDGDACAGABEGECECECEFEHCHAGDDHCCDAEFFAFBFBGDAEHHBABAHADABGBFCFGDCDFHFHAGAFAFDFBACACFGFEFECBC,False +824,23.0,14.0,24.0,16.0,17.0,21.0,26.0,11.0,EEEECEBHDFDBDCFAABFDEEGGCGEGFHDGAGBCFCHCFAFAGAGFFBGAFAEABCGAEADADAHBBEHCHCBCBCDCECGHBHAFDEDEAAACACFFECEFFGACCDCFGGCGCGFDFHFGCGCGAEAGGHHFBFDADABBCGGGDGDG,False +825,16.0,23.0,19.0,19.0,25.0,21.0,19.0,16.0,BCECEGEHBGBGDACADFFBABGGEBEGCGAGDBCFCEADAEFEDDCHCDEDGBGCFHFGBEBEBEHCHCEBEDEBFBFEFHFHFGDEAEBGBEDDCBHDFGFCACAGAHBDBDBCCFCFAFDDDADHEEEFHAEAGBGCAHHHEHFGFBFGECHABF,False +826,8.0,5.0,4.0,4.0,6.0,3.0,1.0,4.0,CDGDCFEEEEABABADAHBFBHACAFHEAEAHCBD,False +827,24.0,26.0,18.0,19.0,16.0,34.0,27.0,29.0,CFAFCHHGFDHDBDBDCDCHEFBGBGBHBDADCGCGHGFDFBAHDDAFECBFFFHFAGECAHAEBEAAACGEGHGEABAFGCEAGFFHFGACBGHGAFHCHGHGBFAHGHBHBGBGAGCFBEDHBFBHEHEBFGECEADHFHFHFDABFEFHFEFBFBABDBDFDADGDGCAEAFCFCFCDAGGFGFBHHHHB,False +828,2.0,3.0,1.0,7.0,4.0,6.0,1.0,1.0,ADDDFDFEFEDEBFBEGFDADFHCB,True +829,18.0,8.0,19.0,22.0,14.0,21.0,12.0,12.0,EGEGCHAFEECHDBDBDCFAFEFDFEGEAFCFDADADCHFHEADAEHDHCCFCFDFHFDFDACACACEFDFDGBFBCGEGFGCGCAHADACEDDGCCACHBABDBHAHFFFDDHACBDEAEGGGFD,False +830,14.0,17.0,12.0,13.0,7.0,7.0,14.0,9.0,EGEBHBDCDGECBABADDGCABACFCEBDCCADADFGHGHGFGBGBGHGFDDCDAGABACHHDHDFDCBBGBAAFACEHAGAGBEBHBCBEBF,False +831,13.0,21.0,11.0,11.0,12.0,12.0,12.0,8.0,EAEDGBFBDBCHEBEBEBCHCHAFGGBCDDDCDCBADAFAFABADFCBCGEAEDBAFAEHEHADFHBBEHEFBFGEBHFGBCBCBFGGAGAGBGCGFBDB,False +832,14.0,20.0,21.0,16.0,26.0,24.0,30.0,17.0,BGGGEEEBFFFEFCDGGGGGCGABDFGHCAFFFDFEHDHAGAGAEBEBCBCAGBBDBFBFEEEDDFCCGCGEGBBDBHEDCFCHGFEEBGCFAEGEGECFCGCHEDDCBEDDDHHHCGBGEHEHGDDCGCGBGEGEBEHECGGAEABAFAHAFAFHFHCHCFFFHFBA,False +833,0.0,0.0,2.0,1.0,0.0,7.0,1.0,2.0,GFFCFHDHCFFFF,True +834,15.0,17.0,13.0,12.0,21.0,19.0,18.0,23.0,DEFBAGHEHEABHDFGFHFHCHDHECEHBHDGDGFFCGBFBEEHHCDEFECEDEBCBGEGEGACAGHGHAHDFCBHGFFFFDACEHEBFBHBHGAAEADGGADHHHHGHGFAFCFCGEDFFABABGECACABEBEBEB,False +835,9.0,17.0,15.0,12.0,13.0,15.0,12.0,18.0,AEAFDHGHGFDEDBFBABACCCFCHEHCFEDHFGFDHBHBHEFAACHEDECFCGCBCECEGHBHCABDBEGFDFDBDBEGEFFCCGHAHAHGHDFBBGBGDGHBHBCBFHE,False +836,24.0,27.0,17.0,31.0,24.0,22.0,21.0,23.0,DCGBEBCDEDADFBFEDADADBDCDCDEDFDGBGCGBHBHBHEHEDEDAGBGFDAHGHBCECADBDEDBFFAFAFAFEHHGCGFEFDDGDGFBFGEGEBAHAFDDHFABBBDADAHAGAFFFCGGEECHGAGAEECEBFBCBHHGEFDAAECFADHGHCHBBBBDEDHBBBEHHAHCHCAEFEHADGDC,False +837,8.0,2.0,11.0,12.0,11.0,8.0,3.0,11.0,BHCHEDEHFAFHDHCHFDCDFDFDAAHCFDDADHDECECACECAFEHEGDGEHEDEHFCBCGCAEA,True +838,12.0,19.0,12.0,11.0,20.0,17.0,13.0,16.0,DEFEFEHEFBFECEAEAGBGAFEBEDFGFGAHFHFCGBBBBBBHEFEBHBGBGHCHFBCDFHAACCHEHACDBFEGEDFBCBABHHCHEHACACEDDDDFDGHGHCAGFDFBEEEGEGBA,False +839,1.0,4.0,3.0,4.0,6.0,6.0,4.0,1.0,GBEECAGBFBFBEDCDFDFEEHEDGFGFC,True +840,5.0,4.0,4.0,1.0,6.0,4.0,2.0,2.0,GEBEFEHEAADACACFCFBBHCAGEBEF,True +841,15.0,12.0,13.0,8.0,18.0,15.0,11.0,15.0,FHFHFEAAHFEFCGEHEHCHCBCAEBBBCHAHAEGFGABHBEBEFCBCAHDHBEAFGBHAFEFBGCFEFCDADBDEDEDEGEFEFAACHDHAEACGEGHGCGAGFDC,False +842,17.0,27.0,15.0,15.0,25.0,21.0,18.0,18.0,DBEBDBEEGGGBGEHCACBCBABGEDEDGFAFCCBEDCGGFGBHAHDBBHBHECACEDBDHAAFAEBEDCDCHGBEDECHAFAFECECEFHGHGHBEBGBGBFFFFHFEFHFHEBEGEAEFFAFGBBBFHCHADFDFBABCGAEAGFHDADEBHBE,False +843,20.0,14.0,16.0,25.0,17.0,16.0,12.0,24.0,HBHEDGBFBCADADACHHDHDAEAHDDDDDHFFDHDGCGCBHEGABAHEDEABACDCEFGFHAGGBACGHAFFGDCAAGHDEGEGEDABACABHFDEEBEBDBDBDHDADAHCHBEFEDEDCFCFCHCHFHFHFHFCAEHHFCE,False +844,6.0,6.0,6.0,6.0,7.0,4.0,7.0,2.0,GCECFBDBDBEGHDEAEAFFECECACBGBDADGDGHFABGEGCA,False +845,14.0,10.0,13.0,17.0,13.0,16.0,16.0,22.0,DADFGHGHFHCBGAFEFCFCGDGDEDBABABECDCDBBGAFAGAHDDDDFDGDGDCEGGFHFHCHGAGDHHHFFCGCHHEFEAHHHFHGEGDAHECDCHHAHAEAEBCFHFBFCEHBBEEA,False +846,13.0,21.0,15.0,9.0,8.0,13.0,6.0,10.0,AGBCBCBDGCBFGHABCBCBEBABCGHEHBAFAFDFECDBBAAHBHBHCFCFDBABDCDFFCGHAHBHBEBEBCFCACDEHACEBFDFGFAFAED,False +847,8.0,14.0,10.0,15.0,9.0,10.0,9.0,7.0,DECFAHHBGBCEAACBCBADDEBHDHDEDFFFGEAEBGCGBGDGDFDADBDBDCFCGCBCHABFBDEDGDGBHBFFCFEAEH,False +848,10.0,5.0,6.0,10.0,12.0,17.0,10.0,11.0,DHDEDCDFDFAFAHCFGABAGFCFBGGGGAHCFDFAFEEEEBBABHFAFGFEEHDHECEHFHFEAHAHEDFDFHFDGGGEC,False +849,22.0,14.0,13.0,19.0,14.0,18.0,13.0,19.0,AACFCFBBHBGFDADADAHHCGFBCHHFHBHDGDCAHAHABDEDBDAHAGFGEBEBACHCDEGAFFDGBHFCFDDBABAEEDEGEFEAAGAGABADAHFGFCFAAGCFHEHFGFBFEEDEHEDCDCDCDHHH,False +850,12.0,11.0,24.0,25.0,18.0,37.0,27.0,36.0,GEGEAEAEDHDEDECECGGGEFEFEGCBFBFCFCDCHEHDDGEGFGDHFGEGAGCGFDHCHFHDGCCHEBBDACHCFCHGHCHCHGDFFFFDFHGHDFFFGFGHHHGCDFBFCHHFHDDBACHEEFDCAHDHBHFFFHHCHBHFHDGFGFGBEAHFHFHFCAGGDCBGDGDFFAACDCAFDFDFBHHAHE,False +851,8.0,20.0,9.0,10.0,16.0,10.0,11.0,18.0,GAGAGFFHFHCHGHEFEGADABHBHBFEEEBAHCHCEEHEDCAGGBBDBFGFHFHAHFHBABEHEBFBCHEBBBDDDCDBECEGDBCBEBEBHBGCHEDDHG,False +852,8.0,4.0,3.0,3.0,5.0,4.0,5.0,3.0,CEHEHBGFGBABDCGAGHFDCGAAAAEADAFEFEB,False +853,2.0,2.0,4.0,5.0,2.0,8.0,1.0,9.0,BHFHFHFADCCGFDFDBDEFAHHHHHFHECCFD,True +854,0.0,3.0,1.0,7.0,1.0,4.0,3.0,3.0,BGEDFDHDHGFBDBCGHDFDFD,True +855,13.0,9.0,23.0,8.0,13.0,14.0,12.0,14.0,CFCFCGHEACCCEEEGDHHAHBGBCFCDCDCFFGCAFDCABHCHCDFFCECGCGCAABFDEDACCHHAFAEBEBHGHBHFGEGCGCGAEBCBAGEFEFEFDHAHAH,False +856,10.0,14.0,21.0,25.0,13.0,22.0,18.0,15.0,HDAFAFDFBGDDCEEGEDFGBDBGCCCCDDDGDGHFDGHEFECHCHCFEDBDBACGFBFBFDCGEGCABABDEGCGCECEBAFGHHBDDDHHHGGDCDCACAFBEBECFCFAEHHFFFDGDGHGHDDFDFHFCFCBAF,False +857,5.0,7.0,6.0,6.0,3.0,6.0,3.0,6.0,HBHCDAHAFGBACABHBDBDEFGCHCHCBEFEFGFCFDDBDA,False +858,5.0,6.0,10.0,9.0,8.0,7.0,3.0,10.0,BGCHCHCBDDHDGDGABCBABFECECECDCDFHHCEDDFFFHHEHEAEAFHBEDHCAF,False +859,5.0,3.0,3.0,10.0,1.0,2.0,6.0,6.0,DADADBGHEADDDCDGHGHGCDCDBFAHHFHAGDGB,True +860,23.0,20.0,27.0,31.0,27.0,21.0,22.0,20.0,GBHCDCFCFDEDHCHGEFEFECCCCCADABAHFHFHFDGDAEEHACDDGBADFDEECFAFCFEGCGEEHFAFEFBABCDADEDEHBHGHBBAECECGBHAGFHHBGECCDEDBFHCACGCDAGAGADDDDDCDGFCFCEEEDEBHGHGHGCGCBDADHBGDDEDABABAEDEBFCDEBABGBDAFAFGEGH,False +861,7.0,7.0,14.0,4.0,11.0,5.0,11.0,5.0,GCGFGBGCCCGFAAEAECECECGBABHHCAEAHAEFEBEHDCDCGFGFBCGCGCDBEEHDGECB,True +862,12.0,3.0,10.0,5.0,8.0,8.0,5.0,6.0,GFCAHAHAGACCEHDBBAAAHADECEDECGCBCECFCFHFHAGGEDEFFCFAEAFAD,False +863,24.0,14.0,29.0,24.0,18.0,18.0,12.0,25.0,ACACHBEBEDABHBGCDCFCEDFCGCACGFADCCCCBCDEAEBDHEEGAGCDFDFDFGEHAHFEEAEHCCFHFEFCHCHDAAHGDCDAHFHEHDHDHAHADEBEBEGADAHEBFHFHACGFGCGCBCDCDCACFCFABCBADDBCBHHDHGAAHAHFFDHDEDA,False +864,12.0,14.0,8.0,8.0,15.0,8.0,10.0,15.0,EBEBGHCABAFAFDFDADGBHCEBGBGBCFCAEEDHCHGHBHDGDHEHEHEHCFGFBEEHAAAHGHGEGBFCABHFHEEBADCDABEBEA,False +865,3.0,2.0,2.0,3.0,0.0,3.0,0.0,4.0,BHDHBCFDFCAHAHAFD,True +866,5.0,8.0,8.0,6.0,13.0,7.0,15.0,8.0,FHCDEDADBEBGAGCCCEBGGFGEGEGAGAGHDHGBEHEDGAGEBECHCGFEEHEHGGFBFBFCFHEBCD,False +867,15.0,8.0,10.0,4.0,10.0,7.0,12.0,11.0,GCHHEHGBDBCGCBCFEAAHAHADFCFCFGAGAFBGAHAEGFBECEABHCHAEAEHGHGFBDCHGEGEGDACABAEA,False +868,13.0,19.0,24.0,20.0,14.0,16.0,12.0,20.0,HCHAHAGDDCDBGGHGHGCEEAEGFBFDEAEFCFHDHGFAFGEHDBDBDCECDFECHCDCFCHCHBBBBGAFDCACEDBFFAFAFBEHCACDHBCBCBHBCADDDBDHDHCHCBABHHEFGAECGCGCBDBDCFHFEE,False +869,11.0,10.0,12.0,15.0,14.0,12.0,10.0,5.0,CBGECDGDGDADCGAHDBDFFFFEAHFEFDBDGDGECECDDFDADBEACGFEBEBECCCGCBCBEAEAFGBAAAEDEGHHDHCFAFEFB,False +870,8.0,16.0,15.0,5.0,12.0,6.0,10.0,5.0,GEGAAFBCBCEGAAEBEBEFHHCBAAGACBBBBEBCGCGCECECBABCFCGCFEDEHCCDGBGFDFDEHCHBBGBDE,True +871,7.0,10.0,13.0,4.0,10.0,7.0,7.0,8.0,GAAHGCBADEDHDCCCACAFHEBBBBBCBEGEGFCHCBEGEGEHDHCFFABCFCFHGHABFECECE,False +872,5.0,6.0,11.0,4.0,5.0,6.0,7.0,6.0,FCCCACBDAFCCCFGBBHBGAGEGDGCGHGHDHDEBHCCFCBAEFEFEHA,False +873,6.0,3.0,2.0,8.0,3.0,5.0,4.0,1.0,AADDDCDCGGFFEBADADADEDGBGFFEFAHB,True +874,16.0,16.0,9.0,13.0,16.0,16.0,11.0,18.0,DGAGHBHCEFGDAAEAFAFBBDFHEDEDHBHGHGHDDEDFCFCAAADAHFBCBCGEHEBFDFAFCFAFAFBECCBEDHHEHEGBGCDFGFHHHBHBEBEBHAEADBEBAAGEGHF,False +875,10.0,10.0,11.0,9.0,10.0,8.0,13.0,16.0,AFADADEDEFHCHCFGBGEHDFGHCHEGBGHFABHEACHBHBHBHGDGBAAAHAHCHCGGGCGEDEBCDDGBGAECEFFFBCHCHDE,False +876,10.0,18.0,8.0,11.0,7.0,15.0,11.0,9.0,FCHDHBFBGCDHAGCCHDHAGFFHBHEFAFAFDBBBDBDEACGGGBGFECECACHDBABFBDBDGEADADFFFGEGEBBBFBFBGBFAH,False +877,4.0,5.0,14.0,13.0,6.0,8.0,11.0,11.0,ACACGHADGCECGGGDCCCFCFBFDFDHDHDADHDHFFBHGHCHCGCDCDHDEEBGFDEHBHGEEBDFCCGG,True +878,22.0,17.0,15.0,16.0,16.0,19.0,13.0,15.0,CCFCHHDBEGEGDCFHFBAGFEDDFDCECEGBCBABADADBGGDBACAFAEABHHHFHCHDBFBDBDBEHHCHCHEEGFGFHAEAEAEADFEAABCFCEAHFGAAADFDFBFBEGCGCDAFAFAEDGBHBGFA,False +879,11.0,12.0,5.0,10.0,10.0,9.0,11.0,9.0,BCBCEAFGFGHBHBHDDFEFGBGHGFBDCAAGEHDBDGHGHFADAEEFEDEDEAHABABACAGHEDFAGEDBGBCBF,False +880,22.0,23.0,20.0,22.0,17.0,22.0,27.0,22.0,AFEFEHDHDHDBFBGBGEGBGFGFGEHEABABGGGABAHDHEBCGCGCFCDBDFEEAAAFDCBFHGHBCGAEDFDFDBCECFBAGAGAFEHGGCGDBBCCGBDDCDBDCFCAHDBAFFHCHDHFHCEEDHDHBHCCBFBAEAEAFGDCDHAHFHEHADAGAGAFBGCGHGFBEGG,False +881,26.0,17.0,21.0,13.0,20.0,12.0,23.0,19.0,BAEAGCGHGAEADABEEEGAAHHDDBDFGAGACCHHEHEBFBHEEEDFGFEAGHCCACGEFEDCGCHCGFHHBHBGBCCCDCGBGBABABFDDHEAEFEGGGGEHAHACACDGBGBGBEAFACEHFAAAHGHGDCCECFCBCBHDAAAFAD,False +882,1.0,1.0,3.0,2.0,1.0,1.0,0.0,5.0,DHHFADEBCHCHCH,True +883,7.0,3.0,8.0,7.0,4.0,4.0,4.0,4.0,GDEDCFHFHDHDEGEACDCABBGFACACGCFCDADBCAEAH,False +884,21.0,12.0,14.0,11.0,9.0,9.0,15.0,13.0,EHEAEGDDAGGBGFFAGHDHDCDCDCFCGGGGGAAEGCHEDEAEFHFAFGCBHBCCCCADBBAGAGHBCACAHAHBFEDBGBCBEDDHHABAFAHAHFBCAAAA,False +885,16.0,26.0,24.0,20.0,25.0,24.0,19.0,20.0,DFDGGAEAEAEDHGHGCCABBEECFCFGBGBDCGFFDBDECEADADHGHFDBDCEEBCGCGAFBFBCHDFDFEFEFHFHFHBHFEFHCHCBAFDFBFCAGAECBBBBEAEBGCECFHEHDCCEGBGBGFGFHHEHCHBDACECABABDBHAEDDCGGBBEFDFDCBAEHEHECG,False +886,13.0,28.0,17.0,8.0,23.0,25.0,17.0,16.0,GFFBFBHCFBBBCGCGEEBCBABFDEBGBGCACEHFHFHBADDCGEGEBHAAACFCEHBHBDAEFFFFDFDFEFEFECEBBBHFGBBHBEGCBEAEDCHEEEFBGHGECEHFHBABFCFCFCGCEAGDGAGAFBGGAFHHHBEBEBF,False +887,12.0,16.0,10.0,18.0,15.0,11.0,14.0,8.0,EEHEFGDCAFDGDCBFBFGFBEAFBBBAGFGBGCHCHCAGADCFCDBDEHEAEDGDBHBFGEBEBDBDADCDHDEABDDEDFCAGDGAGAFDEAGCGBEBEHEH,False +888,18.0,13.0,17.0,15.0,11.0,10.0,18.0,15.0,DEGEDEFAHAHAHGHGHGCGCFDDDADFCBGDGDCBABCBEACAGAGCEDBABDHFGAGAGDEEHAFCDCBCACBEBHCGBFAHAHCDFHBGBGHFHGHFBACEGEGCHAECFCDAD,False +889,22.0,5.0,11.0,9.0,14.0,19.0,10.0,13.0,HEHFADEFGFCEHEFDFHFAFGGGGAGAFADGDFAEAHBCECEDFCFHFCFDFDAACACABBFGCHEAAABCDHEAEABFHFHEGEFHAAAAACAGDHCHEFE,False +890,27.0,36.0,17.0,27.0,26.0,14.0,25.0,25.0,FHDGFABEECADAEBECEABAGHECDCDADGDADADEHEHGHBFBCBGDEEEEEBABABHBHAGCEDEDEHAHAGGCDCDHBABHBCACAGFCFGHHFDFDGBGHGAGCGFFBHADFCECEHBDBGBABACAHEBBHGHEHBBEDEFEBGBDBCGEDBBBBBEBDHDBAHGFGAEBHAADGHGDABFCFDAGBGDHD,False +891,18.0,15.0,22.0,14.0,25.0,27.0,18.0,19.0,FHFHEHAHCFEDCDHFFFHCCCCCCFAFGEAHAFGGEGEGEGFGFAEHDCDFHGAGEBHFHCHBHBEDHDCFCACGBFCDDEHBCEGAFABEBFDEGAFDCACFEFEDEAAGAGAGCBCDFEHAHEHBCBCBFBEEFEHGGGCEFEFEBEAFFBDADB,False +892,15.0,15.0,17.0,14.0,25.0,21.0,15.0,21.0,EGAHHHDHDFEAEDEGGGGAGFHFAFEEEHHBCBGHGBGDFAAEAECEFEDDBFCFCAGFFHFHFHBCFCDHFHCHADBHFGFGBEBHHEEDDCDGBCEEEBGBHEHEDEAFCBCECEBGAAAEDCDCACABEHHCFEFCFBF,False +893,5.0,2.0,1.0,1.0,3.0,2.0,5.0,2.0,BHAHAEEEGFGFACGBDAGAG,True +894,1.0,2.0,2.0,3.0,4.0,6.0,4.0,3.0,FCFCHHEFEFGGGGHDBEBFAFDDE,True +895,12.0,25.0,10.0,17.0,18.0,19.0,18.0,17.0,CECBHFGFGEBBHFEFDBDBABDGAGAEABCBGAGAHCEEHEHEHDDCDBFHFHEDFCFBFBFAGGGGGFGEHBBBHDHBHDEBEFGDCBBBDBGCAHHEGBGBCDFDEEEDEACAFFGBBHFHFDFAFHGBADED,False +896,16.0,8.0,11.0,13.0,10.0,11.0,7.0,7.0,GEDEHEHBBDADFDADCDCAAAHFHFGFECACAEDCDGAEAEBBCBGEACAHDBDEGFHFBCDCFAADACBCHFAFAFEGGDF,False +897,11.0,6.0,9.0,7.0,10.0,14.0,15.0,10.0,HDBFBGCFCGCGBGDEDGHAHGHAAFHFCGBGCAHHGFCFAFEBGHGBDCHCHDEEFEFEAEAEFEFGDGFAFACGEFDAGA,False +898,17.0,13.0,21.0,30.0,28.0,20.0,12.0,19.0,EDDBGCECEDBCBCDHGFECBGBEHHHEHFHDGDHHAFAHCHDBEFDADCDHEEEHEGDGDGFEDCACEDEAEAEFDFDFDADCCACFEFCFEFCBBHCCFEEDHDFGEGAFCFCACABABCGDEDAHEDDDDGDGFHDHDABFCFDFAHEEBEBEHEAA,False +899,3.0,3.0,2.0,3.0,3.0,3.0,8.0,3.0,BCEFGHGHGAGBGBGDFDCHEGEFAADG,False +900,16.0,24.0,17.0,15.0,11.0,13.0,13.0,18.0,DDCDADAECDHHHCHADDHCHCBCADAECGHGEAHFHGBBHDADAEHHFHGACACFCFBEBEDCGCGBBBBGEFFHFBBGCGBABABAHFEFBBECCHGFDFBFAFAHBBEBEACDGDGCBHBGBDB,False +901,25.0,30.0,29.0,16.0,34.0,19.0,24.0,19.0,FFGCECEBBBCDCBFEEEECGCABAFEFGHBDAACECGHDFCHBFBGGGBGHCHCBCECBGBEFDHBHBHCHAHAGABABGEGFCFBEGEBBCBCDHHHCHCHDBDCFCAEDHGAGEBEGEBEDEFFDBDEFBCEFEAGGFGEGFBFHHACACAEAEAEBEHEBAGAEAECGABADDDAECECFAAEDDAGCECBG,False +902,24.0,23.0,19.0,24.0,26.0,27.0,19.0,14.0,FAAAEACAEEEGEDAHEBADAGGHEDCABGFFDFDFEBEBEDEDGAHFDGBCBFDFGECFBFGFBFEFCFEDADBEFEFACACACAHADBBBEHAHBGBFAGBEEGGFGCGCFAFDFEBHGCAAGDGFHFCFCHCDCBFBGBCBEHFHCHCBEDGDACAEBDBHFHEDDDDDEAED,False +903,29.0,29.0,25.0,18.0,19.0,26.0,26.0,24.0,GABBEDADAGFHBHFHGCBCBDADGBGDGHEDBGBGDAEBEAGFGACEBEDADFFFBBBCFCGAFAHEHEHGBAAAAAAGGCCHBGBABHEEFHFHAHFBGCHDHFEBEGEAEDFGCHBHACADBHGDGCEDFFHFEFBCBABAHAEAGGFFCFAHADGDGCBCBCGCGCBCBCFHEHDFFEFHFCFABCHCDCAC,False +904,6.0,3.0,10.0,6.0,5.0,4.0,4.0,1.0,ACGCFCACDCHCDDDEDCGGEFBCBCBFGFEEAEDCAAA,True +905,3.0,18.0,9.0,11.0,14.0,16.0,4.0,13.0,DCFBBCBEBDBFFEFDCGHBHGDCFBFDEHEFBHBFEFHFHFGCAEHFAFBEHEHEHCACHGFDCBEFEHEBDBDBHBDEDEDBCBFB,True +906,16.0,25.0,37.0,22.0,24.0,10.0,28.0,28.0,DFDCDCEAEHCHEACBHBGBHCCGCECADDDDDDCHHHAHCCCGDECECEBECHCFCFBHBACGCBABCBHGEBBBHGHGBCBCDEEAAGAGDHFCCEDEDGDGDGBGHHDFFGEEBFAGHGFCBBGEHHBCBDBABCEAGACACGBEHEHCFDHAHEGGGHGHGACEDECHCGCGCDHFHBEGEDBCGC,False +907,25.0,18.0,28.0,21.0,19.0,32.0,30.0,20.0,GCGCEBHGCGCEDDHHGCCCCGHGHDHEHACGGGBGFGBEACGHGCFDFDCCCHCFDFAFAEAGABACAGACEBHBFGFBFBDHCFAFGFACAGDEHCDBGHAHBBDFDFCFAEBDCGFAHGHGFGFGBADFEFHBDADABBEAFHDDFDFGBGDEDEFAFEFEFGFAFDFEFCACHFHBEEECGCGCAAEAC,False +908,28.0,27.0,16.0,15.0,23.0,29.0,25.0,24.0,FAFEFGFBABHFFBHDCCGAABEBCACAEFFCFAGAEEGEGFGFDFHFHBAGFGBGDHBHBHBCGEGFAAHAHAHAEGEBEAHABCBDFGFGEGBFBHBDBFBFGFGHGHBEBEBDGHGFAFCHADEEECECFBACCBCDDHGGEHEGCAAFAFBDHHHDHDFDADGFAAEAFABEECGHHDBEACB,False +909,22.0,23.0,20.0,21.0,31.0,23.0,29.0,28.0,EAGGGDCHHHHCDDEDBCHAEDGBGAGADBHAFFHGBGBDEGEGHGAGDBEGAGCCHFHFGEGHHEAEBDDDDADHCBBBCACFCGAGECEAEFEGEDDAAEFEHBHBGBFCFCHGBBDBFBFDEAEAEFCDDEGFGFCECAGHGFGFEHHDAFHFHGHGHFHFEEEHAFBBBEAECGCBCBCEEAHACBFDFEHEH,False +910,35.0,20.0,17.0,22.0,15.0,17.0,23.0,20.0,BABABADGDFFFFFADHEEAEHCBGBGDGEGCACHEFAAHAHAHBHGHBABCBCGCFDFAFCFCEAEHEDGFGBAAADBGADADBDBECGGFCBDBHCAADAHAGADCGFGFGCGCEDAAEAHDEDBAGFGBADDDCDHHHCHAHDEAHGFAEAFBDHAGAEHBBGCGA,False +911,20.0,22.0,16.0,16.0,19.0,34.0,24.0,21.0,HHBBFFAHAHEFAFCDBDBDGCEEBFBDCCBCHDFAFDBDBFCFAHGEDBGFFFDFHACEDGDBFBFCECHCHBFAFADAFFFFFFFGFBHGHGHGHAFABACHCFGGGAFHFHGGGGFAFEEGHGEEEGECDGECBCBHDGDGHEHDBAGEBEAEABABFEGACHEBGFAF,False +912,14.0,22.0,22.0,16.0,10.0,16.0,13.0,11.0,GABHDHAHACDCBFFFECHFHEBEGABCEHEBBFBACHCHCACABEFFDBACDHFADAFBFBGGCGCGCHFBFCGDFAFGBCBCBDHDGDCBCBCGDGCGAGABCBCACEDFDEEFBBDDDEDB,False +913,20.0,27.0,29.0,23.0,22.0,31.0,29.0,18.0,GFGEECFDFAGEFHFACDEGCGCGHGHDHDCGCFDBAGAGAGDGHFDFBFGFGAGHDAGAFABDCFFECECEFFDCDCBCGDBABFFHFDDDGACHHDBEBEBFCEEBEHAHECBABGGAGDHDCEEGFCFBDECACAFHFAFACBEAGGGBGBCBHFCFCFCFCHDFAEBBBHBEBECFCHEEGBGBFCDBDBDBHGC,False +914,12.0,9.0,6.0,2.0,6.0,6.0,2.0,13.0,BFBHEHEHBADCHBAGFHFEBHAAACABHBHAAACECBBACGCHFHAHAHEHEFFD,True +915,10.0,12.0,24.0,13.0,16.0,14.0,13.0,16.0,CEBDBDBDCDCDCDBDAHHBFBFCFGFGEDFHCBCFGECFCEBEBHBCCFCFDFEHAFBHAHAHFCACHCECEHACBCHCFEDEAGACDCHCGAHCDEGGHEEFHAGGGECEGEHDGG,False +916,4.0,4.0,9.0,4.0,6.0,12.0,3.0,4.0,CECDADFBACFCFDFBFGFCFGHCCGBEHEHEHEFFCACBEFFFAD,True +917,15.0,18.0,12.0,11.0,16.0,11.0,18.0,15.0,AEAEAEAEAHAHAGEEFHGHBHBEDABABADHGFGDHBCDDFHGBEFFFAFGGHBDFCBEHECECGFHBHEEGDBEGEBBGDCDHDCACGFGHGCABABHFACCCCBGBGBGDGBE,False +918,14.0,16.0,12.0,30.0,16.0,18.0,12.0,16.0,DHDAEBFADADADADADGDFAFHFHDEFGBGBGBGFHCGEHECEAACACGCDDDFEBEBHBFAFHCDDDDFCFDFGHCFDHEFEFDCHBBBHAEDEDBAAHCEFDCDBDFDBEEDBDHEBDHDGFHDHEGGGCB,False +919,5.0,11.0,3.0,9.0,10.0,8.0,8.0,5.0,BFBHEEEBCBHEHGAGAGDDBDEEEHABFCFBAGDCDGDBDGAFEFEFDBDGGFBFBHE,False +920,5.0,0.0,5.0,4.0,1.0,1.0,4.0,2.0,CGAAFADHDCACGCECGDGDHA,True +921,24.0,17.0,18.0,26.0,23.0,31.0,24.0,25.0,EDEDCDADFGBABAGGFCFDFEGCGBHHECEADGDEDFDFDBEGEFCAGFEFEFDHEADHCHAHFHFHEGEDDDDBGEGEFBCDCEAAHDBAGHDHFGGHEHAHAHAHFHFDFBGBHCGAGFEFEFADACAFEBGCCDBEBADAFBGCFAFCHCHAFEFGCGBGCAFABCDAFBFBHDHFHEGDGHFH,False +922,12.0,3.0,17.0,8.0,6.0,8.0,19.0,16.0,GDFCHCHAADGBHCHAFEHCHCBGBCHFACAFADGGGGGGCGCAADHEHECEAEDDCCEGFGFGAGAHHGHGCDADCCHHGCGFHFHGC,True +923,13.0,7.0,15.0,17.0,15.0,11.0,14.0,5.0,GDDDHCCBCDADAEABADADGHFDCCACAEAGGDEEEDFHFBDGCHBFBFDGGBCDDDFCFCFEEGCFEFADADACAGGGGEGCCAEBEHEGEFECE,False +924,19.0,22.0,14.0,20.0,28.0,12.0,19.0,18.0,CGCDHBFBHGEBEADBDGDGDCBCDCHCEBHGEGEHEGDFFCEAEDGCGEGFDEEEEEBABCBCBCBCBGFDFAEAFDHDHEHFDAAHHHHEAEADAFEFEDBABDHEFEAGCBBFHDHBHBGBADHEEDBDEGBAEAGGCGHBEGGAAAEA,False +925,20.0,23.0,18.0,19.0,19.0,27.0,21.0,22.0,FEHEHEGDGCBDBHBEBCAGACHFEFHAHADAFGBGFFEGECEHDGDAHAHEDCCEAGFDFEGCCBGBFBFHDADCBCBFBCCHBHAHBDCECDFHFGFADCFFFFBFADBGGHADFDBBCBGHHHEHEHBAEAEFGBHBHGAGEFEFGFGFDCDFBFACAGAEADGDB,False +926,8.0,4.0,5.0,5.0,6.0,5.0,4.0,8.0,FGFDECECEADFBFBHEHAHADAHAEACGDADHHHBHFACBEGCG,False +927,4.0,9.0,2.0,4.0,9.0,4.0,11.0,2.0,GHGBGDGBGBEAGFGBBBBDDEBGFGEGEDECEAEAGBFCEHFAE,True +928,19.0,13.0,20.0,26.0,25.0,21.0,11.0,20.0,DDDFAGCFCHADFCCECECFBEHDBEBEDEHEHCFAEAEAEFDFBFADAEAEAEADHDFDFGBGBADEDBHCGCFCBEEAEHECFHAGACCCDDEDHHHHAHDDDACGHBACFCFGDEFEBHFHFCDDDHDACECBDHGHEEFGBGFGFEDHFBA,False +929,31.0,26.0,25.0,22.0,30.0,19.0,16.0,16.0,GADBEEEAEAHACCCCFGFEHBGBGCFCFDDADGBAAAFEFAABEHADFDFACAHBHGEFBAAACFCGABEGFABGFGEGFBFBEBFDEDEHGFEECHAHADADADCHEHEBEDABHBEACADBDBDGDGDCDCACHEHGCEHDCEABCFAEDFDGCEBFBAAEHEDEBCBCBCBCBEEAEBCHC,False +930,5.0,6.0,16.0,9.0,2.0,8.0,6.0,8.0,FCFCBBGDGDBABHCHCGEBEDDGACFCFCFCHCGCABHCCCCHFHCAGFHHCAFDDDDD,True +931,13.0,10.0,13.0,5.0,17.0,8.0,8.0,11.0,AEAEAHAEECBHBHGHAEBFCEEAEBEGCHBFBGEGFACADAEGEDBFCCHHBHBHFHCGEGHDDCDCACAEAFBCGCFEFECEA,False +932,13.0,15.0,7.0,16.0,20.0,10.0,5.0,18.0,AEABBCHEBEHEFEDEAFBHBADFHHDBDEHBABABABACDCFEFHFEGGACEDEHEBBAFGHCEDEDBGCHHDBDBEHCHDADGDEDEDHFEEEAHAHFHFHD,False +933,4.0,6.0,3.0,4.0,2.0,6.0,4.0,5.0,AGAGAHBEEDCGBGBCBDFDFDHHAFBFHFCBHF,False +934,5.0,12.0,3.0,2.0,5.0,4.0,9.0,11.0,CEDBABACFFGFAEAGCGBGHGHBHGHEBBHBHGDFHHHHBEBEAGBBBGH,True +935,8.0,6.0,1.0,11.0,7.0,1.0,14.0,7.0,GEBHGHGDBAEEDAGGEGDGBGBHHHHDDAAAAGDGDGDADABCEGEHEDDFGGB,True +936,12.0,13.0,17.0,16.0,15.0,22.0,16.0,19.0,HHEDDDDGDGAFACACHCFEEECACADBGHGFFFFFFEHEHCAGBDFEFDFEFEHEFFBBABFCHEGFGDHBCBCBEEAHCCECDDBFBHCHFHFHDEDGGGDGBGHCBGAFDGDGCAHBCCHGHFHFAA,False +937,3.0,4.0,1.0,4.0,2.0,0.0,0.0,2.0,ADDEDEHBHBACADBB,True +938,5.0,10.0,7.0,7.0,2.0,7.0,13.0,13.0,FCGGGHHAFEFBFBGBABAEGGGGCFCFHBABHHDHDHFHACDBBGHGDGDHCBDHCHGBGDHC,True +939,0.0,2.0,2.0,0.0,2.0,1.0,2.0,1.0,CGEGEBFBHC,True +940,15.0,12.0,17.0,12.0,18.0,16.0,21.0,10.0,DADACBCEGEGCCAHFCDCDAEACDCFGDAEBEBEACABEGGGABACDFDCGGFDDHCGFGEGBCBDEDGHGFEFBFGGCBCEEFAFGFHFAFHGHGCEFEBHBHGEGEGEFAFAHACBHE,False +941,21.0,9.0,18.0,19.0,23.0,21.0,20.0,26.0,EGEDHBHBHGHGHCEAAGBHBDDDGGGDGFGFEFGFGADHEFEAEAFAHAEAHBFECDCAAGDFAFHEHCCDCEFHFHFAEAHACFCFCHCECEHDDGDHDHDADEBHFEGAAEAFBHCCEGGDEDBCHADAHFBFCFCGGEDECFHGAGHECEHFH,False +942,23.0,23.0,25.0,23.0,16.0,18.0,18.0,24.0,CAHDBDHDEGCADHGHGHGHFCDCHCDFGEDEDHDHBHFDFEEADAEABFFGFGACFBBCFCBBFAHCHCEEDCCFHACACABHBFFFDFECACHHEGDGDEDBHBCBHBHADABHBHBCGHACBCBEBABCGEEFEAEAGGCDDDDAGAGAHBHDGBCFGFDCAGACAB,False +943,9.0,5.0,6.0,3.0,2.0,3.0,4.0,6.0,DBDHCFFHCEAEGBGBGAHCHBBAGFCAHAHACADACA,True +944,1.0,5.0,5.0,2.0,2.0,3.0,5.0,5.0,EGGDGHCBBAEGHGCFCFBHBHBHCFCD,True +945,23.0,12.0,17.0,23.0,21.0,25.0,31.0,23.0,AHAHBHBHCHCEDDFCACDCDFGFBHBCCGFGHGAAHDEEGECFAHAHFHDHEADFGCGCGFGEADBEAEBEDDBCBHAAFAFAFDGDHABAEHDHGEEEHDADGFGHGFEFGFCFAFHFEFADGGEGEGECFDHCHDFGHGDGCAAGAGEGFDBGCEBGBGDEDHFFCFGAGDG,False +946,7.0,6.0,9.0,5.0,3.0,13.0,9.0,7.0,BEBECFHFHAHGCAABCCFGBGFFCFGFBFDFGGAGHGFFFFDBCGHHCHCDDADAEAC,False +947,12.0,14.0,22.0,9.0,8.0,15.0,19.0,16.0,GGGGGADFDBBBCHGACAHBFGHGHGFGCCFDACHGHEFFBCBGEGDGFHHHBHDGDCCCCGBFHACACECDCFGBHBHBCEFECHCBCBCHGFGDAAAADAEEFCFCACFFEHB,False +948,23.0,29.0,24.0,18.0,9.0,25.0,25.0,32.0,BBBHGFAEAEBEBCFCFAFAFCFDFBHBGCHFAEGDACAGBHCHFDBCBGGCCBBHHABDCFGHBDCDBDGFBCAFAHHGHFHEHACEGDABGBGHABABGHHHFBFCFHFABAEAGACBCFHHBABCBCBCACFCHGHCHBGBHDDFGAAFFFEDDDGDHDHGHGHGHDHGHGHDCDCGFGFEA,False +949,7.0,6.0,5.0,7.0,7.0,6.0,6.0,12.0,HHCHADDCGBGFFHDHBBCHCHBFADAEAGAFAEAHBHEEEEHHHBGDGEGCDFDF,False +950,24.0,23.0,22.0,11.0,20.0,30.0,30.0,14.0,EHFBFBFBCCFCAAACEGBFAEEBHCHFHEAEAGBGHGHGCGCFEFAFBEAGAEBGDGCGHGHBBGBGBFBFDFECAGGFEBEGCAEBEDGHAFBHBFBDGDGFGDACCGCECACAGFCECHDFBCGCGFFFGFGCBCGABADFBHGGFGDHDEFBHCAAAAAAFFFFFDEEAE,False +951,16.0,19.0,15.0,15.0,20.0,28.0,15.0,17.0,DGGFECEHGHFHCBCEHGDGCBCGCEEFAFAFAHEHFAABHEGDGAGBGEEBHDHBBCBCHFBDBDBHEDFCAEAFFFDFDFAGBCBDECFFFEFDFBFGFGEECECEFEFEDHGCDAHAEABBDGFBFHHBHDAFHFCFAFABA,False +952,9.0,0.0,6.0,3.0,8.0,5.0,2.0,3.0,EFACCCFAAAAHFFFDGAAEAEHGHECECEDECEAD,True +953,2.0,1.0,1.0,1.0,6.0,2.0,3.0,1.0,ECEHDAAGBGEEEEFGF,True +954,11.0,9.0,7.0,13.0,13.0,4.0,8.0,8.0,CADHDHDFDABBEACAFDBBHFHGAGECBGEGEGEBEHEDEAHBGDADADADFDEBEDDCAABHEHCGEGECC,False +955,17.0,19.0,17.0,18.0,12.0,19.0,16.0,32.0,GFGFAAGFGAHADGGHGEBABFEDBHBDFHHHHBGBHDHDEAACBFBFBEAEHCDDGDFHHEDGHGBGBGADHFHDHCCGAEACDCDCAHAHFHFHFHDBDADHCCCHBACACBHFHFEFECACGEBBFDHCHDHBHEFGCECHFFBHBH,False +956,21.0,23.0,17.0,24.0,20.0,16.0,15.0,22.0,DADEHFHDCBCBCAHGBGFDFDGBAFDFDHHFDBDBACACFEHEAEAHAEEBAGCHCFCFAHAGDGDADADHHGHGECCFCFGFCHAHGDGBCCHADBDEAHGCFBHBHBHEEEEEHEBEAEGDBBFBHHCDCEBBBDBDBAADGFABADFEEGEDDB,False +957,10.0,10.0,8.0,10.0,12.0,10.0,10.0,2.0,FGFBFDFCGGFGABBBDGAAAFHFDGDBDGDEDECECECECGBAEHECGDACEBGBDFCAEAFFEDEBABAE,False +958,23.0,37.0,29.0,27.0,20.0,20.0,23.0,19.0,ADBDBAFABHBADGGCCCHFHGBBDDCACACBBAGDHDHCHFECBHFEGEBEDCCFEDEFBFBCBCBHEHBGDCDGBGAGAFFGCGEGAADACADBGFEDGBGFDBHBCAHEEFFDCDADBDBACDCDCDBHBHFEFHFDBGBGEFHFHBACECEDEBCBCBCGCGBBACAGEFBFBABGDGDHEHEGBCDCBHEAAA,False +959,12.0,18.0,18.0,8.0,12.0,10.0,17.0,15.0,BEBEBGBGBHBCBCECGCGCDCFGGHGBCHEACCCEFGAAAEHBHEHBGBHAEABHGFCFCDCEABACAHEHCGCHFEAEGDBDHDCGFDCDAHBHGFDFGGGHFBBBAF,False +960,6.0,8.0,14.0,11.0,10.0,8.0,6.0,15.0,EADADHGFDEEHFHDHBHBHCECDFDBDECHFFAFGFBEDECBCECHHHHGCGDGDHCCCCCCEEDHHAHABCGFABB,False +961,20.0,29.0,25.0,20.0,25.0,26.0,26.0,18.0,BHBEFEABGFAEGDGDFFBDHDGBGBFFFHEEEEEDFAFADABGGCGCBCBAFCFABCCHEHGDDEDEGFFAAEEEEAGCGAGHGFDCCBCHGACACEDHGHGAFBFBFAHEBEBEDGBHCCEAEADDDHDCBCFHAHCHBHBFBFBGGGBHECGFGECBCBCDHDBBFDCACACBFGFGEGCDEBFBF,False +962,27.0,19.0,27.0,18.0,20.0,32.0,29.0,28.0,GEGECAFAHHHHEAEBDBDCHHGHFEFHDBFAFBFDGDBCBCGHGHFCFCFCFDEGADHHCCADADAGEHEHGACCHGHBHEHCHCHFECGCFAFBFAFGFBCAEFCDHAGFBFHGEGAAHGFGEDEACDCFHDDCDCFCHCGCEDGHBDAAFAGBFBFHEGAFACADEFEBEGGGCGCBBFBFGAGAGAFABAGFBEHF,False +963,18.0,20.0,27.0,19.0,14.0,17.0,15.0,25.0,FFACCGCGCDDHCHCDGGGEHFBCBHFCAAAAHAGFGDGAGDGHFBDEDHCBCACACGCGAFEBBCECEAEHEHBBCHHHHAACDCDBDFCFBFBHCHBHDGCEEEHEDGBBBFEFHFHDCDBDADAHFBCBABDCEAHHDACFCGHBHFHDCFE,False +964,12.0,10.0,8.0,9.0,12.0,10.0,10.0,9.0,FGFAEAEAGADFEECEHBBBAHAEBECECAGGHBAAGEHFHDHAEFDFECDCBFBFBABDDFDGGFGCCCEHAHBHGDGD,False +965,17.0,22.0,24.0,31.0,26.0,22.0,22.0,27.0,CGCEHFCFCEBDBDBEHEHGHGHFABABHEHFBEBGHDHDFCBDBEBGGCHCFDFHEHDHDGDFFBCAHAHGEEFHBHBEBADFFAFAHDHGAGAHEDDHDEBEFEBEFHFHACADDDFDEEEECCCDAGADBGAGFEHBGGHDCCCDEDGHCECDDABFBEBCGEGCGCFCDCAAEDCBGHGDFDGDCDF,False +966,27.0,18.0,26.0,14.0,26.0,27.0,37.0,24.0,AACDCHCFGHAHAGAGACFHEHABFHFAGHBCBDBFBFBABFHHHFHFCEDEFACHCECFGFEFECGDGHGCGFGEHECDCBCBGBECEDFAEECAGGFAFBHEFDGBGEGHFEEGEHCGEGDGDGDFCCCCHBAEACHGHGAGHGAGEHEGEGBCAGGGFABHDADADAGAFHBEDCFAEECFGFGFGCGABEFGABA,False +967,19.0,30.0,23.0,20.0,26.0,19.0,25.0,21.0,BBABCBGGAGFDFGHDHEGBGCGBBAFDCBCEFHDCDFBCBGEFBHBEEEEEBADAHAHBGGGEDBFBHCCCECBGHDHDFGBDCDFBEHECGBGBGFCFAHEHDGEGEFDFDECCCHCHEGEGHGBCEAGABEBABABABADADABAEADCCEFBABFECDFHFHCHFEFCGGEHEHGDADH,False +968,22.0,15.0,29.0,26.0,37.0,20.0,22.0,24.0,AEGBABEFGGEGDHDHAHEFECEFACEEACHBECFBABCDCACAHGHDEEFECECDAAAEHGHGHDHDFGFHCADFDBDEDEAEDEDEDEDGGECEABBGFADADEHGHFECBCAEAEGECECAGDBEGAACCCCCCBHEGECDCDFHFHFHFHFCGEGHBDFEBBBGECHDEFEHHGDADCGHGDDCEFHFCFC,False +969,16.0,6.0,14.0,15.0,9.0,8.0,13.0,13.0,HHHHFEFDDCAHGGEGDGDCBBHCCDADGGHAAADADFDFDGDGDGABEBAFABECDHAAFAFEFGDGCHEHCDCGCEEHHHAEACCCCBCGAA,False +970,21.0,25.0,9.0,17.0,8.0,13.0,18.0,16.0,GBGHGACACAFHFBCADGGGFGFGAGAGBBDBGCHHEHEBFDEABGDGDGBHBCDFFFFHFHAHBDACAHDHCCGAEADBHBDFABABABEBEAECGGBHBHDFBBBBAFDDAGBHHABDDADADBE,False +971,9.0,10.0,11.0,9.0,15.0,9.0,14.0,12.0,EAEDFCFBFBAGHGHGDGBHBGFHEHCFAFAGHECGCHCADAHCEGDGCGBBBBDBDEGFGCCFHEEEHEDEAEDBCGHGCADHEFEAE,False +972,18.0,16.0,12.0,13.0,15.0,19.0,12.0,21.0,BEHFBBABAHGEEAEAFAFCDEHFHAHCGCFBEAAFGCABHHFHFHCHBGADCDHDHCHCEEAGBFDFGADFFFFBFBGDGAGAEADHDHDAEEEBCBCBHBDEEHGFGFBFBDEHCHGHAHFCAD,False +973,27.0,25.0,26.0,28.0,24.0,17.0,20.0,27.0,HCHEFEACGCFDFGCBCHADFCFBADCGHBHCDDDCBAAHAEEDADGDGHGHGHGDAAEBEHAHGDADADEBEHHCEBADAHHHHCHCAAAHBFBDCGBFCHEEFBFBFHAEADDBFBFBDGDEHEHBHGCGAHACECAFBFBEEEBECEFDCCABDBDEDEGAGADEDEDCFBBACHGGFGBGCGDADCHCBC,False +974,2.0,9.0,5.0,14.0,10.0,16.0,13.0,8.0,HBEGFBDBDHEEFHFEGDBFBFBGHFAFDFGFCFDBDBDHDHBGGCFFEGEGECADGFECEHFGDCDHDEDGFGFGD,True +975,7.0,10.0,11.0,8.0,6.0,8.0,11.0,11.0,CECFCDCHGGGGHGAFCECEAECDCGHHBADHDHDBDBFBFDAHGBBBBBBGCFFFAAEHDFCHGAGHCHGE,False +976,22.0,16.0,20.0,24.0,18.0,27.0,21.0,14.0,GDBDHEGEBFHFHDDCFCDAAGEFBFEDBAHGBGBGDFEBBADGHGFABAFAFDCDCBCAHADDDCAHECCDAAFAFGHCCECFGECECEFDHCHAHGBGBGDECECECEAEAEBFBFGHGHAADDFDBDGAFCFBHACAEEFGFAFDFDFGFGDCDGGFFF,False +977,16.0,17.0,23.0,22.0,27.0,15.0,19.0,22.0,EEGGFDFHCHEEAEDEHEHGCEFGBEBEBHBDDCBAHAHDGDAEGEGDHFECBDDDHDCGCFAAAAAFCEHBBEECEFDFDBDBCCCCEFEGAFFCFCFCEBEAHAHAHAGGHGHCHCBGEDBDGEEHCDGHBCBDAHFHBHFGGDHDEDAGECECBCDCG,False +978,5.0,8.0,11.0,18.0,14.0,13.0,11.0,18.0,HFHDBAGHGEFEHCGGEGDAAFHFEFEFDHDGCECHHEHEDEDHGHDFBFCDHHHAHEHBCBCBCDCDGDECEDGDEBFGDCDEBGHFBFDCDFHFDA,False +979,22.0,10.0,19.0,14.0,19.0,26.0,19.0,18.0,HBGDGHGCGBGEFEAEFBDEHEAAHGGGGHDHDHFGEABAFAHEHCACFFDFDFAFECGCDCDCDCFCHCFCHAHFDCBGAGDEHBGEAFAHAHEFAGHEAGACEEEFFFFEFHFBFCFBACGCAFAFCBEFEGEFCGBDDDCAAAH,False +980,9.0,10.0,16.0,13.0,13.0,13.0,17.0,6.0,CDCEBDGFGFACEBDHFCEHACADBDBHBCBGACCECEFEFGFGACHCACDEEGGGEGEGDGCFFFGFDBDFGGAGAHACDDDDGEGFCFCEHBBEB,False +981,19.0,23.0,15.0,12.0,16.0,18.0,17.0,17.0,ECEDHFHFHFAGAHBHDAEFGFBEHGBGBCBHBCEDGDCBHEAGADEGHFHDBBABEBAGAGCCDADHDCGBBBEGAGAGEBBBGFGFCCBFBFEGHAEGHFCFCFCACEDHDAAAAAHDBFFHFEFCBCBEBEFHA,False +982,21.0,16.0,13.0,14.0,20.0,12.0,19.0,12.0,EBEBGBGDGEGECHCHFAAEHBCAEBHBECECACGCDCDCDBABAFABGHGHAAEAHABDEDEFHFGBCDAEAGFGECDHGFGDDDEHAGGGEGBCFDFAFBEGECEHAFDFGABADAGAEBHFAEB,False +983,22.0,16.0,20.0,28.0,16.0,18.0,28.0,14.0,CGCGBDCDCGHACGFDFDGDBDCFEFEFADAECBDDDEAEAEAHAHABGDFAAGFGFGCAAGEDEGFDFDCGBGAGBGHHHGABCBDBDFDFCFDFGCAHAGACABAFEFAGEEDEHBCCHEGBBBDBDHGEDCHCEFAHHGCDHGGFGDGDGDBEGACDCD,False +984,26.0,22.0,19.0,22.0,24.0,27.0,32.0,24.0,ADHHEFAFADABADAFABCGCGAGFGFEDADABEFHFHGHDFGEGADCCFHHHGHGEFCFCEBDGEFEFEGAFBFBFAHGBEBEAGDFAHABAEGHGCECEHBHBDCFFHBAAGAEAGBCCDCDHDHDBDBGBEDDDCBBFBGEDFDHGEGEGEAFAGGBGBHEGBGFGDECHFAFEHHFCGCGEGCCHCHAAFDG,False +985,7.0,9.0,7.0,9.0,13.0,11.0,7.0,5.0,FCBCHEDFAFHEGBGFAEAEAEAFGDGDBDBABAFGEGDCHCHEEBFCEEHEBEDEFFDFGBDBCCFD,False +986,8.0,13.0,17.0,13.0,13.0,11.0,14.0,10.0,HGEDFDFDFDHDHDHDBFEFAGAEBEDGDHHFBBEEABBBFBHGHCCBCEEGECFBACDCDAAGCFCGBGFFEAGDGHCCDGEGCGCGCHCECBCACEB,False +987,20.0,12.0,18.0,25.0,18.0,18.0,21.0,30.0,AAADFHFAADFECBCECEHEHADCDGDGDCFHFHGCGCGFGFCFHDCAHEEGDGCECHCHEBFBHGHGEFHBHFGDADEDHDAFADEHBBBEGEFHADFDBCGDHHGHGHGDGDHDGDFCFEGGFGCAAEAEBHAHADBHEAADHDCECHDADHCHBHFHAB,False +988,20.0,13.0,12.0,16.0,10.0,14.0,25.0,12.0,BBBCHGHGAGFGHGDCACHCHCAAAAAAEHBDBAFDGDGDFCGGEBAFDEDEHEDGDEDADABCBFDGAGAGHGAEDBGGGGDGBFBHAAGBGHDFEFGAEECCGFFBFGFGHCHAFFCACD,False +989,12.0,14.0,12.0,10.0,10.0,5.0,11.0,8.0,AEFEBABAHACGFBABGBGDEDGDEBBCBCHCECBCACDCGHGHGEACFCBBBEFGDDDCDBDADGEHAACHEGAGFBEHAH,False +990,22.0,22.0,18.0,21.0,13.0,23.0,11.0,18.0,AHAHEFFDDCDFGHDFDECHDHABEBCBCEAFBGGGGFCHCBCHHBEDFAFABCHCBCBCBABDDGHHDBFGEEDADFECGBAECEADADADAFFDFBFBFBFAHDFDBHBDEAEFHFGAHAHAHACCBBABGCGCFHFAFDFDEBCA,False +991,10.0,6.0,7.0,9.0,6.0,4.0,5.0,5.0,FDCBCGFHFHBBBABGDFDAGACACEEECAHDDGDEAAADADAECECHDBGH,False +992,9.0,13.0,4.0,15.0,7.0,15.0,17.0,13.0,DEAHFHGHBEGEBBGFFFAFDFDHDGDGHGHFHFDDDCEGBACGDBDGDEHEHGHGBGBGHFBABABFFFAGADHDGGGHFACBFEDDBCAFB,False +993,1.0,1.0,4.0,3.0,4.0,6.0,1.0,3.0,EFEFEFAFCEGDFHHHDFCBCDC,True +994,16.0,14.0,21.0,15.0,11.0,19.0,16.0,24.0,AHACCCDCAAFBFEFBDBAAGAHHCHDHEHAHEHEBGAGAFHFCGCEFEFEDACHCHCGGGFDFCHCDDDHDHAECHGBGBEHCFBDBGGFHFGBAFHFCDADCFCBCBCEHAHFHBCEGGGFAHBHDCDFHFGDB,False +995,7.0,6.0,13.0,6.0,12.0,13.0,4.0,9.0,CEAFHCHFHECCHEACFCFGGAGFCHCHFAFEDHHCECFBDBDGECHDFEEEEEEBABACFCFDFDFBAB,True +996,4.0,9.0,13.0,8.0,5.0,3.0,3.0,5.0,AGAEADDCACBCBCDCDEHECCFHEDBCBCDDDFEBHBHCCCBBFHGCGB,True +997,3.0,1.0,1.0,6.0,4.0,5.0,7.0,3.0,DDDFHEHCGFGFGFGEDAGAEHFDEDBGAG,True +998,18.0,17.0,15.0,15.0,11.0,15.0,12.0,20.0,EBCFCHHAACHCHCHGBCBCBCHDADAFAFEFDFDGHGHCBCFFHCACDFAFAHAEAEAEFEBCHAFBHBFGAEDBDHDHFBCDEAGABBHGADDBDBDHHHEBAGCEEHFHBGGDGFGAGDB,False +999,6.0,13.0,8.0,13.0,6.0,19.0,12.0,12.0,GDGCGCHCAFGFEFBFDEDHFBFBDBGFDADBFBACGBGDGEFBHHHHBDAFGFGBGHCFFECEFEFBAHFDFBFDAHCHDHCHDFDGB,False diff --git a/tests/results/nb_gm_002_2back_240trials.csv b/tests/results/nb_gm_002_2back_240trials.csv new file mode 100644 index 0000000..1c50201 --- /dev/null +++ b/tests/results/nb_gm_002_2back_240trials.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,ralph_skewed +0,30.0,39.0,31.0,30.0,32.0,24.0,27.0,27.0,False +1,33.0,23.0,27.0,32.0,37.0,34.0,25.0,29.0,False +2,31.0,20.0,37.0,28.0,31.0,32.0,26.0,35.0,False +3,27.0,32.0,39.0,24.0,25.0,34.0,35.0,24.0,False +4,34.0,24.0,38.0,28.0,31.0,29.0,28.0,28.0,False +5,29.0,24.0,36.0,31.0,32.0,32.0,31.0,25.0,False +6,25.0,38.0,28.0,30.0,33.0,30.0,26.0,30.0,False +7,27.0,30.0,30.0,29.0,32.0,26.0,33.0,33.0,False +8,24.0,36.0,32.0,23.0,30.0,29.0,35.0,31.0,False +9,35.0,34.0,30.0,29.0,35.0,26.0,23.0,28.0,False +10,30.0,25.0,33.0,31.0,27.0,37.0,30.0,27.0,False +11,28.0,28.0,29.0,26.0,28.0,27.0,34.0,40.0,False +12,35.0,27.0,30.0,29.0,26.0,30.0,36.0,27.0,False +13,38.0,27.0,31.0,27.0,34.0,23.0,27.0,33.0,False +14,29.0,30.0,28.0,35.0,19.0,30.0,37.0,32.0,False 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+9,11.0,23.0,19.0,24.0,13.0,20.0,28.0,13.0,DFDDFDGFDGCDFFDFEDCCDEGDAHEEDGGGGDAGHFBHFGEDAFGCHGFDBCDBDEBCHDEBGEAFBCHEFEAFBHFCCGEDGADGBCBCDACGCCGFAGBBDCGDBBBEBBECHACFAGFBGABCBBGFHHFHHFGHGGDGGBGBCDB,False +10,10.0,15.0,13.0,9.0,5.0,13.0,10.0,23.0,CAHCFDCFBGFGCFHBHAGHABAAHGFBAFDFBDBHDHCBGEFGDCBDHDEABHHHHGCFCEFCDHCFHBHHGHHGFHGBBABCABCABHEHEFHDCH,False +11,29.0,21.0,32.0,27.0,25.0,25.0,8.0,18.0,HEFAEFGCBEBDCBEADAADADCADABDHHFFEDFBCHACAAFBAFDAFDBCCCFDCEACAACEABFDCFDCFHHFBHDEFDAFCABGAEFDCDCCBCCDCDFAEFDCGCCECCBCBHDEGACBAHBEBEEFDBDHAFHAEAEECEGGHDBHDHCDEADEAHEHFEBFCBAHBHDEGAEFFCFCG,False +12,28.0,27.0,32.0,14.0,15.0,33.0,26.0,13.0,FFFAAFBAHCHHDHGCBBCEBFDGEGBFAACBACBACBAGBGBAGFFGFAHDGHEEFCAAHAHHECFBBFACFACAACDBCAEAHDFHFFCFFEFCAFBEFBFCBCABDBGGFECFGCBCDGGBGFDGDABBCCBEFBEFBAFDACGCCEHGAFCABDGEDFFDCFDGFGGCGGEEGCBGAAGCCCHC,False +13,29.0,16.0,17.0,15.0,16.0,11.0,15.0,11.0,CBECBEFBDDCDCAACAABFAGFEGACCECBEHBEGADFADFBBABCAHCABAABHEEEACEHHAGHABACGDHGDFGCHGCAGDAFAAFCCFEAEBAEDFDDGEABHAGAAGDGBAEDHHGABFEGDCD,False +14,17.0,24.0,25.0,11.0,18.0,20.0,15.0,30.0,DDCDHHAABGECDACBCCFHGEDGAHBABBHFBFFBCFHCHECHECACABHHBHEBHBHDCHCFBAHBFHBEBEDCEDEABCHCHFCHCAFBFBBHGEHGEHGHFCHACHCGGCGCDECFEGHEDFBAFGEFDAAHAHHGFHFABGEBGABGFFEFCEBC,False +15,8.0,6.0,1.0,3.0,4.0,2.0,2.0,6.0,EHBEDEHGEGFABBADBAHCAHAABDAHHABF,True +16,20.0,17.0,20.0,17.0,21.0,21.0,26.0,21.0,DEHCHAEHFEDFDHFCHGCGGCGAFBDDBDCFGEFGEFCEFHDHEFFAGDGDEGAHGFECFACFEEHBEHBGHBGHBGCECEDAHHBGFCCCADHAGHDEDBADGHEBDCHCCFAGEAFAABGABAHBAHBGHCACBEFEGAEFCECBGFDGFDGAGBAGBFG,False +17,12.0,3.0,7.0,9.0,7.0,12.0,9.0,8.0,ADGAGCADCFDFHEFDGHCEHAGGCDAHDCHDAHAFDAFEGFACFECFEBFGBAGAFFAEBDEHGHF,False +18,18.0,19.0,24.0,16.0,21.0,13.0,23.0,20.0,GGEGFBDFGDGEDAHGFBGHAGCDGCAAAHACECDECEBBEDEEDECDFDHBCCDHBHHACBACFHEAEEGHEGDEGAHBAFBEEHCBHCBGGFCGECGECBCAFCGHCBHFHHFHDGGAAEBFCBFDBCBECDCADCACGBHGEHGBFGADHA,False +19,10.0,14.0,15.0,8.0,25.0,14.0,11.0,20.0,EEEEBEEFHEHEEFEEGHEAFFAFHACGDCDDCFDCBDCBFFBCEAHEAHGCGGHGCHEEAEAHEAHEHHCCFGHABHGFGCHGCFDFHEHBBBDFBFBCEAEBHCDGCEEEHBBHB,False +20,16.0,9.0,19.0,17.0,10.0,22.0,10.0,24.0,HFGDDAFEAFEDCGHAADEHDBHAHDCGBAHBECEFFFFFEFEEDHEDCACEGHBGCFGAGGABDHFCHFCHCCDCFHHADFCFFCFFCBFCDHHHHDFFGHHDACDAFDACDCBHCHHAGHABHAB,False +21,6.0,10.0,3.0,4.0,7.0,3.0,3.0,4.0,EABBAEFHEFABAACHDCDDEFBEGHEGBDABHBBCBGEB,True +22,6.0,11.0,12.0,6.0,9.0,6.0,9.0,10.0,AEDBCDECBCHBCBBGFBGFHGEHACHAGAEFBDAECHCFHFDCCECGBCGECGAHGBHBHEBHDFGDE,False +23,11.0,8.0,12.0,13.0,7.0,5.0,13.0,9.0,EAAGACDACDHEEGGGGGBEGEABEAHGCHCCAFCFFGDHGDGCBGBDDEAFAADCDDCDDHBCGBCAFCBDDHHBHH,False +24,36.0,26.0,18.0,26.0,33.0,19.0,21.0,15.0,GBCHFHAAHAFFGBBEFBCFAEFDFGEGEEBECBEBBABBAEBEEAEEABGDBADBACFFBEFCECGACFADABCFDCDBCBBHDHHACGGEHDEGDEGAHAAFAAEDCCHHDDGDDBDGBDBDDCDAGAAFHEDHGDACDACDBGEEACGAEEBEHAFHBGAAAAAAAEEFBEDCDAEEEFGEGGHGFEAFED,False +25,11.0,17.0,16.0,9.0,15.0,15.0,6.0,9.0,CEEFABDBGDBFDFFDGADECBFCBCCACFABEABFABEGBEHBAHEAHEAECCFFCHDCBBBFGBAGCDFHHFBDFDCCHHEHAEBEGCCBFEECEF,False +26,8.0,5.0,15.0,9.0,10.0,7.0,11.0,5.0,ECAGCHDBBDCCDCGHBBEEFDHFEEEHBHGADADGFDEFGAFGAFCCCCCACCDCDGGECGECGEAGFA,False +27,9.0,11.0,8.0,5.0,8.0,4.0,2.0,4.0,FCAFDBEDBABAABAEEAEHDBHCEHCDBCFBABEEGECGBDABFCCAHCB,True +28,6.0,8.0,11.0,7.0,10.0,5.0,9.0,9.0,CFBCBCCBACBEHBEGCADHDGFEGFHGHDAFBAFBEDCDGCHGAACHCHBCEEEEDHEDGEGGH,False +29,24.0,16.0,18.0,25.0,13.0,19.0,26.0,18.0,HEFHCDEGDHFBACGGDEHDGHDGFDEAHFDHGBHEBGEGADFFGCCGDHFBFABDACDABAGFGDAGDAGCAFFAGHHCDHCHACEDDAFDCCDCAECAEDGEDGAFGFCGFAGBBGFBDBBAABAAGADGAFCHBEEGHBGCBFCGFAHHCHDBDDE,False +30,6.0,5.0,2.0,9.0,2.0,4.0,3.0,8.0,DADBAFBDFHDHHBAHEADGFBHFGHEAHDHBDGDCADC,True +31,19.0,18.0,16.0,13.0,19.0,13.0,14.0,15.0,FCHGCAEHAEBDEBABAABHAFEBDCBDCBHCGEAGEFBAFCCECCBCFHEHGEGAEDAECBECEAFEBDHBDEAGFGHDGCDGADFAHGCFCBFDEHEGCEABFADHAFHGBHABHBHDAEBGDFG,False +32,7.0,12.0,12.0,10.0,7.0,5.0,5.0,9.0,EBDGBGBBDCBACGHBDAAHEBGCBFHBFGAFEHFCCCHDCHDCHDAHDCDDEBDEAFECBAHBECC,False +33,1.0,4.0,8.0,1.0,4.0,4.0,5.0,3.0,GAECEGFBHFGHBGCBFCECCECCBCHDGF,True +34,5.0,4.0,6.0,9.0,13.0,13.0,5.0,7.0,CHHEFFDFFDFFDFDGGDFGDHCEAEAHEAFEBFCFEEFEECAECHCHFDEBDBGEGABDEH,True +35,3.0,2.0,3.0,3.0,5.0,4.0,0.0,6.0,CBDEEHHEAHCAEBDFADFHFCHFEH,True +36,13.0,2.0,13.0,8.0,7.0,6.0,16.0,9.0,DEGDECDHGAHGEDGEGACAFCADGACGACHFDACHCCHCEECGHDHBEGGGGCADCAFAGFGGBAGCAHFHFA,True +37,18.0,19.0,17.0,17.0,13.0,17.0,15.0,23.0,HBCABCGHCEEADEDCEDGAGFFFHDFADHHBHHGCHFHHAGHEHEBBBDEFECFEBHCDAADFGDFHDCDCCDCCFACAACHGGBGGBFBCFBFFCFGEDABDBBDAAGAABACBEGBAHAHHFGEDGHDHHEBHBHF,False +38,4.0,6.0,5.0,9.0,6.0,4.0,4.0,6.0,AGDAGHABHCEEFBEFDEHDBHDECDFCDBHDEGBBGCCADFDH,False +39,3.0,5.0,6.0,8.0,8.0,2.0,8.0,6.0,DCEDEEGEEGAAFEHFGHDGDBHDBGBBGECECDGHBGCDDCHCAH,False +40,0.0,0.0,1.0,3.0,1.0,3.0,5.0,1.0,GDGGDCEHFGFDGF,True +41,20.0,19.0,22.0,21.0,30.0,22.0,10.0,26.0,BADBABGCFGFDDDADEFHAAHAAHEAHBBHECFGFDEHDCDBBBHGEDEECCDCCDGCHHBGHCHACFDCFCFEDFEDAHHHBHAECABDABAAEHFEADCFEBFAGFGEABECFEFFECEEFEHFEHEEHDHDCHBBHBDHCEHCDHBDCFAEFAGHEGECBCFEEFE,False +42,3.0,7.0,4.0,4.0,5.0,2.0,5.0,3.0,EBBEAEEHDCHDCGDGGBACBEHBDGBAFBFCG,False +43,21.0,15.0,21.0,27.0,18.0,33.0,14.0,23.0,DDDDDDBCGFEFFABFDHDAGCEFHHACHGBHGBEFEHFEHFCFFCHDGHDFHDAGFECCCAAEAAGHGDFCHFCHBBBFABDEFDFFBBDBAAFDAFAGHACHACEFFEFDHABCAFGDFEDCGACFADFDDFBHFAFFBEHBEHFCHEADEGHEGCDGHDHDEECCFCCD,False +44,27.0,34.0,20.0,19.0,15.0,29.0,27.0,26.0,FGCFGADGADGDDBDBAFGAFDHHHAFBAEEAGGBDBFCEFAHFAHFAECDCBBCGBHAFHABHDCHAHHGBCGECFDCEHCFBCHBGHCABFBCFBEHBECBAHBGDECHFDFBDEAFBBGECGEBBHDBHDBEABEBFCDFHHFGHFAFFGCACFGDGGHGAABCDBHBGGBGGFHGHGGBEADABFABAAFAFF,False +45,15.0,12.0,15.0,7.0,7.0,15.0,11.0,5.0,CAFCDGCFACFCCFACGBBGCAEAEGAHFADBCHACHFCFBEFGEGBDGBDGBEGEHAEFGBFCDFBFBHACAFCAFGABDAFACDB,False +46,12.0,10.0,7.0,5.0,4.0,11.0,11.0,13.0,ECFFHGFGGFCGACGFGGAHFABBHDEDCHABFBHGAHGAHCAHDABDFHDFGCHGBEABAHEHBFHBFCBAA,False +47,15.0,6.0,13.0,11.0,17.0,21.0,13.0,9.0,EDCEFAEFAFFAGHCFCEEAFGFFHFDECECCEGCDGHDGHDGHACFFCFFCDFEHEEFEEGHEDAFBGEAAHAAGCABAEFAFDABGFCFHCDEDBABFGBGGD,False +48,11.0,17.0,17.0,9.0,17.0,17.0,13.0,15.0,GAFGHHGCHBCACCFBCFHHECHBHAFHEEGBAFCAGHGEFGEDGFCBBEBGABCFDCFDCFDBEEEGAAHDAEDFECBGCBHDBFEGHHBFGBFEBFCBCCHEFAEDAEDCEFHB,False +49,13.0,16.0,15.0,12.0,16.0,9.0,12.0,15.0,BGCBAEBCDBEDBECBDCBABDCDFCDBCEGDABDFFEHCEDGECHACHEBDECDGHFFHFHEAHAHHEFFBAGAGHCHCCHGCEEAAAAGEEGDEGBFGBAGBHHBH,False +50,13.0,6.0,16.0,14.0,12.0,13.0,9.0,12.0,DAEAAGAAGCHCCHDFHEFCCBEGFEGFHAHEAGBGCBFCBFCDACDAFDCHECEBFBAFCFFDEHAGHDEFDGCDECEHCHDGADEHHFADCDD,False +51,22.0,27.0,26.0,19.0,24.0,22.0,28.0,20.0,FDCGDAACFACHGCDGEBFCBDCBGBEGBEGAGGFGGCHGDHGDCAACHADHCFHAAEEBBCBCCBAEDAGBFGAFGEGGDGHCEEEDEHCBBCDECEBGEFCCHCFBCFBHFEABEBDEDHABHDBFFFCEFCEDHFFHBFABHAGGECAEADBGGEGAABHAGHAGEFGBFBFHHDHBEGBFCCDD,False +52,19.0,24.0,24.0,17.0,11.0,20.0,12.0,18.0,FBDFCFECGDCFBBFHBFHBAHECHAAHAFCAHCHCFBDFCDHCDBDDBAGAAGAGHFGBDABCFEEAHHGDHBDCCGCCDAEBAEFEBCHBHECHDABFFBHECFDCBDBFDGGDBFABGHBGFCFCBDCBACBFGHEACEACA,False +53,11.0,13.0,7.0,11.0,11.0,7.0,5.0,12.0,HABDABEADFFDABBHBEDAEDACBEHBEGBDDEAAHAHGBHBDEBAEDECCHFDHFGHFGHFDCCEBHEBHGCACF,False +54,11.0,20.0,14.0,17.0,12.0,15.0,15.0,22.0,DFABFDGCDCDDCBHCBECBDHHHBEFBGFEGHGFHEFEAFAHDBHDGDGEDFBAFBGFBGAGGHHCHHEDBDDBCFFCGFCHEEECDDADHBHHCDHCBHFAEGBCBBAHBAGEFGAHABHCBHG,False +55,17.0,24.0,24.0,12.0,23.0,20.0,17.0,26.0,GAECBGBFHAHHEFEGCGFBGBCHHADCACHBGGBHBAHBAEFAFGGFBCCAFCFHCGHCFHCBEFBEFBCHBGFECFGDHBEHCCACGFHEDAEBAEDDEDCEHBEBBEGEEHHACHECBDFFDFADFAEFHCFHCBECDEHDEHCBAGBAGADGBCBHHEH,False +56,17.0,25.0,29.0,22.0,21.0,19.0,27.0,22.0,FFFFFGGHDEHDFGAFGEEAFEGCEADDBBDHDCHECDGCDAAFCDHBGCBGBBECCDCCDAHGBHCBGCHCCEFEGFAABBEHFEHBCGFHGCHBDHCDHCFBDEBEABEDBCDGCHCCFGCFDAGGBGBBCBFABFEGGADGHEGHEDFBBCBCGACDAEEABDADGGEGHEGCCHHAHH,False +57,12.0,11.0,4.0,15.0,9.0,3.0,6.0,8.0,HABCEHAECBEDEDDHBDGAAFHAGCBGBEAAABADEADGHDFBAFBDEBEEBGDCDDGDDHDAHDBH,True +58,9.0,8.0,9.0,9.0,4.0,9.0,12.0,13.0,CAGCGGCBAHDEFDHHGHDFDBFBBFGAFEBFECHABGGDGDEGDHGBHADGFDCACAACHBFHFGHCHHCHA,False +59,15.0,19.0,20.0,23.0,14.0,16.0,21.0,18.0,GDGGBGGCFGABBABFGEFGCDDCFBCDBEBACHABGEBCDCCDFDDFDAACEBCEGGGFHHFDHGGHFGADHFHHGDHDFFGHGGHDEBDCAACGACFADDHDDCBDBBFEBHDDHFCEGBEHCABEAHEAHEFCCHBAEBCEDC,False +60,9.0,8.0,2.0,6.0,8.0,11.0,5.0,10.0,FEBDCDFHFEHFEHEGHBHFBHFEDCHBBBAGEAGEAGHADABFHFFDBFAEFADAAHG,False +61,26.0,25.0,20.0,16.0,13.0,13.0,17.0,12.0,CBACHGCFDHEBHBBEBBFAHCCEAEEABDDBDGEGADGHDAHEABBBEFCFFDEFDAGDADBBHGGCEGBAADABCHGCHGBDBBGCBGCHFAEFCHFBFDDCAACHACFACAACABFEBFAAEGGCGBCGBAGBDDACAA,False +62,9.0,9.0,5.0,7.0,5.0,5.0,11.0,6.0,FAADDAGBGGBGBCHBCAGEADACGAHGACFECDABBFEFDGGDFGHBGHDEHBEHB,False +63,7.0,8.0,8.0,6.0,13.0,12.0,11.0,4.0,GGBDGFEGCEGCECHDCFGFGABGFEHFCGGBHFBHEGEEAEEAFEDBCFBDFDEADACBABFACFEEF,False +64,20.0,11.0,23.0,13.0,16.0,11.0,12.0,18.0,AEDAHACHEFAEFAHCAEDAEDCBAGGCBGFBCHCHFCEACHCEHCFHCEAEAAEAHCAGBDCDHCEHEGBFCHHCGHFBHFAAGEADHBDCADCFDGFDCHDCBGCGAAHCGFGDEBDEBECB,False +65,19.0,12.0,22.0,18.0,18.0,14.0,20.0,17.0,CCDCCAFHAECADDGDGACGADGHDFHEBGEFEAFDHBDGBCGCFHBGHEGAEGBDHFDFDCGDHGDAGDCBHEBHEBGBAFHGCGCCFEEFCDCCDCHECHFCFAAAGECHBBEEBHDAGAAEAAEAHEGHCFCEFGAD,False +66,26.0,13.0,22.0,33.0,10.0,21.0,25.0,20.0,CDFGDFAHFEHDHBBCDECDAHDGGGFBCDBADHHDGADEBDEGDHFFCFFDHDGADHCFHDAGEGCEACGBGGEAGFAGBBDABCABGADGAHADDADCADHAFCFGDGEFBEAHDCGDHDCADFADFGHCCHGFHCFHGDHGHGECCCCCADBFDGAABAFDAFDAFC,False +67,3.0,0.0,0.0,5.0,2.0,3.0,2.0,1.0,FDFEDHDGAFGADEAD,True +68,21.0,30.0,10.0,18.0,20.0,13.0,15.0,10.0,ABBHBEEEHDEHDGFFGDBDBBCABFGDCCDHFHHAAAAABFAEEDBEDBGBBEABEABFBBFBBDDAEEAGCFHEBAFAGDGGBBEDBHDFEFEEBEEBABDHBFBGCBGCGGBGCCGCEGAADAABCDDADEAHF,False +69,23.0,30.0,20.0,17.0,29.0,22.0,24.0,20.0,BHBBFBBEEAEGAEHBCABCBGCGEFHEGHFFBFCBFCHEEDEGCCGBCHFHBAACDGBFBEAEAFEHFEHGHGGACBEDDDBDFBGBAGBAGEDGEHAEDDHGDFEDFEHFACCAEHFBCGBCECFGFFAEGAEAHHBGABGAEGDCGDCHDBBEFAECDHCDHABAFBACBAFBFGEDEEHGB,False +70,16.0,21.0,23.0,21.0,35.0,31.0,21.0,19.0,FEGHEGHEHFBHEBDEGDABDAGFAGCDGCEAEABGGEFEBAEBHDFEFACFEHFHHEBFGGDGBAGBAEEAFBACBCBDFFDGEECFEDFEAFEFFEDFBBFHFFCGFBFCECEHCHFFHGFDGFHECEGCDDBDDEECCBDHADHADEEEECDBCBFHGFHGBCGFCHCCBGDEEAEHAECDCCF,False +71,21.0,21.0,25.0,23.0,34.0,29.0,19.0,27.0,CGCABAFBECCEGAEFEEHEDHEFBAFBFFGFDCBDFHDFDDHCCAEGAEGEECFCDFGDHCDAFDFFHBAEGDECFHHFHHEAABFABAAHCCCCHHGBBCBHGGHEFDFFCGFDGHDAHAGHCEEBBEDBEGEHBEGCHAEHDEHFEBDECFHABHABAAFDDFDDFBEFGHGCEECFDCDCEECEEAHEGHEFBBG,False +72,26.0,9.0,19.0,24.0,24.0,27.0,21.0,27.0,DDGBDCADHEDABHHHAEHAHDCHDBFFEEFAEFAHGACFFEEDHACFCCFGCDACDCCDCEDBADHFEGDHDFHGCHFAEFHDFGFGEFGEGGEHEHHAHFEHCAAEAFCHDCFFFGABAFEAGGBGHCHDFHDAAGAFCADGADHAGHBGBBEEEGEEFAEFAEFCGDCFDHGDH,False +73,24.0,24.0,23.0,19.0,22.0,18.0,26.0,30.0,HGFHGHHBBHDBAGCEDEHDHCDAAGCBCCHCCDGGHAGHGHHFAEFGEGBEBFDFAEAHBBHBDCBDCBCCDECHHFHDDHCGAAAAEAEEDBGDBGCFACGAHGDFGCGHABBACBAHGHHBHGBEDDACFACFEBFGHCAEBGEBGEDGEDHEFFECEEAEFGGHHFBBFCHFBAFGAEHACD,False +74,26.0,17.0,19.0,17.0,28.0,19.0,13.0,23.0,EGCAHEHHEHABADBADECBECEEABEACFACACFFBFGBFBDFCFCCACAHEBHEGHDBHBBAFEADEHBCHEEHEGBFGBFDCGDEFDEADEDHEAAFFEFFHHFACDCCEAHDADDEEEFAFGADBHEBEAGAGDAHBCHCGHCAHGACGEEFAHGHHD,False +75,3.0,1.0,2.0,0.0,2.0,1.0,0.0,4.0,EAHBCHCAHEAHF,True +76,10.0,5.0,4.0,6.0,10.0,5.0,10.0,8.0,HGHHAEEAEDAECGDCAHGFBGAGEFGFBEFAFCGCEAEEBGEBGDDHDBHDAHGAHA,False +77,6.0,2.0,4.0,1.0,4.0,1.0,1.0,0.0,AACCDECAEBAEBAGFECA,True +78,26.0,21.0,24.0,22.0,21.0,23.0,16.0,22.0,AEAFDAFGAFHAHCGFCGFHDCBDCBABADBCDGGFGHEBBDFBFFDCDEAEEGGFHAHDCDDBGEHCEFCHFGEFDADGFHFBDFCCCBCGBCABDFHAEBCHBCHBCDECEGFFAHFAHFCHFDDCAEHAGHBGHBAEECDDDDAABAHECHEBHEAHABGEBAEACEACEAF,False +79,23.0,23.0,29.0,21.0,13.0,23.0,22.0,17.0,CDHBACEAHEFDEGHAGAAGFAHFADFCBBBEFBCDGFBCDBDHGGGGCGFBDBBCFBFDEGEEHEGGBGEHFCCFCBDCEDAEABFDHHBFBBCAGDDCHDCHDAHBACAGCAGCADDBDFHAFCAFCGHDEBGHBCHGCHFBEGBFACFCCACAADACFACFCCFGFDG,False +80,12.0,12.0,23.0,9.0,27.0,13.0,18.0,19.0,EGFECEECHEBEEHHFBDCGCAACFBCGEHEEGCEACEGDEADAGBAGBCDBFBHFHACHCDHCDHCECCEGFHGFBABCGDCBDCEACHBCGGAEEAECFEHHAFFEEFHFCEFCHGGGGDHBEHGGHEEHE,False +81,25.0,15.0,14.0,17.0,20.0,16.0,15.0,15.0,DGDFFBFFCAFHADGAEEAFDABDEGGEBGDGEDEBAHAAEGABAHCACEACAHBAGGECFCDDEDBEFHEBGAFCAFCAHDEHDAFAGFCDBCHCCHCEDBGFGHBADBHGBEAAHAAHAEFECFEDFEDHEBHGB,False +82,23.0,16.0,15.0,28.0,9.0,16.0,15.0,26.0,FAHGHHFHGDHGDHDHCCHFBHEDGDGADGBDFDHFBBEDBADEDDBDHFDACDBFGBFAHCDDDGDBGBBGAAADCHFCHCDGABFHDDHDAEDCEDCGDFEAAEACHHGHDGCFFCHABHAHHAFCFHAAHAACBABBHFEAGEAC,False +83,16.0,17.0,21.0,14.0,11.0,17.0,24.0,19.0,EGHCBBCBBHFAHAAGAFGHBCDFAGFBDABDADEEDBCDBCHBCBGEGFFGFGGCHGCGGHHADHDHCDHAFGACCEHDGHFFCDFEDAHDFFAFFHEGBDGCGCBECECHBGHGGHCGBCHBCEGFGGFCACAABAE,False +84,25.0,24.0,34.0,20.0,21.0,23.0,18.0,22.0,GCCGAFHHFBGFBCFBDFBGFCGDEGCAHEBCAFCBFHEFEDCGFCAFCHCHBCHEAHAFBAFDAHBHBDGAABAFBACACHHCFDAFDGBAHBEBBEDFCFECAEBGFHECCCCCCHHEEHAAFDGFDHBDGBEFBEDDHDDEBHECCECCEBAEBAGACGEDGADCBCCGGCDEAGCADCAFHHD,False +85,14.0,17.0,15.0,14.0,15.0,14.0,16.0,10.0,GGCGDDEBFFHGFBGFBHFHHEDAACAABGFFFCDBGBEHBEDBFDBCDCDGCDEFBCHBEGBEGBEFHGFBAEBCEFAAGGCHCCFCCBCHEHEAACADDEDDAGDAGEAEBAG,False +86,5.0,2.0,1.0,1.0,1.0,1.0,3.0,1.0,ADFAGGAHGBEABCA,True +87,28.0,33.0,23.0,19.0,20.0,25.0,30.0,22.0,FFGDBGHBGEGAADDHGEEDEHBBACDFCGFCGEHFBBFHBFBCCGCCFHDFCGHBECBAAFFDBBCBECGGFEGECCAGABBABHAEHBBHBHDEFDCHDBAFFDDFAAHAAHCDFCAHEAHGAHFAHAGHAGAAGEEDFGBEBECBGCBAFBGCCGAFAAFHAGGFGGBGGBDEEGEGBFGBFHBCHBDDBDDBECCA,False +88,27.0,30.0,28.0,20.0,23.0,12.0,23.0,29.0,EGBCBBCEBCHHGDBECBCDBEDGEHGAGACGEHGCDACFECFCBHBBFDAHCACBACBEFGGAGGADAAEBAHDFHDCDBAHCHHBHABGCBEEDHGHHGFHAHDAEDABDGCDECDBADBHHGHHGFGECBEABDHFDGAHEACFGCAGCABCHBFECHCBFCBFAEABDAGEHEEAECABDHBHHCEBG,False +89,14.0,15.0,7.0,17.0,10.0,11.0,15.0,9.0,CHBADFABGHBGFGGAGGADGDEBHADHGHGFDFDDCDBGAAGHAGFAEEBBEDBEBCEBFAFDAFDFGDEADEGDFACCCGBHBBHABHDEDCBDFE,False +90,5.0,3.0,3.0,1.0,8.0,0.0,6.0,3.0,CCACEGHEGDEGBBAHEHGBAGEAEEAEG,True +91,0.0,0.0,4.0,2.0,4.0,2.0,2.0,1.0,GDCFDCEECGEHFEC,True +92,14.0,4.0,7.0,10.0,8.0,6.0,12.0,5.0,DCDAEFAFCECEEAFEDFEGCCGACBDGHFAHBGEBGAGGAGGDGAEGHHGAADAFDADDCBAHDA,False +93,10.0,8.0,8.0,3.0,8.0,14.0,16.0,15.0,FAGFDGHDHHEHEEGGFFACFHEHACCACHFGHFGHCGCAGCGBCFFEGFGBHABHFDHGBGBHABHAFFAGFEHEEBBAGG,True +94,21.0,25.0,21.0,30.0,27.0,13.0,12.0,17.0,HHBEBCAACEABDGDGBDFBGFCAEHGDCADCHDCEDFEDCEDGDCEDAEGEHAADBBDAADHCDHDFHBEEBEEBCEGAECDEBBCGAHEBBFFHEBHEHDAHDAECFFDFEDFBDABDCCACEDEBDHDDAGFAEABECBHGFDDFEDCCBHCBHGBEGBACBA,False +95,4.0,6.0,6.0,8.0,7.0,6.0,6.0,9.0,EDGEBHEFHACBBCFEGHCHDAHDEHDBHDBDDEHFCGECGFGBFACFAHGD,False +96,8.0,5.0,5.0,6.0,5.0,8.0,12.0,12.0,AFACCAGAGGFBEHEGHECFDFFDGFHGAHGHHFDGAGCAGEFGHBBHEBHDDHDHHGCBA,False +97,20.0,25.0,21.0,20.0,27.0,26.0,25.0,26.0,BFCFGDFBECHDCEBGEFGBABHGDDGAFBEBCEFEEFGDAHFBHEHHCHDDHGEFDFFBGBBAEGCCFDDABEBBEBFHBHHBCCECEDCAFCGFGHFCBGHBEAFCBFDEEAEEAFECEBBGGAGHBDHFHHFHHFHHFHHEEHGCDABGABGACGAFGAGGDDEDDCADCFGAFGDCAHEAHEAEGC,False +98,4.0,3.0,1.0,1.0,6.0,1.0,5.0,3.0,BBAHAEDECGEAGBAGEEGHEGHF,True +99,21.0,17.0,15.0,21.0,17.0,23.0,10.0,21.0,AHDDHEDGFFGCFHDHAGHGHHDDFADFABHDBCCACAAHGDDFDDFGBHEBHBHEEHEFCFFBBDDBAABCEEHDACDHCEEAAEBHBFABFABCABFFFFDFFDFEEFCEHCEBDEBFCAGAGGDGCHBCHAAHEFFECAADH,False +100,21.0,17.0,13.0,22.0,21.0,22.0,21.0,31.0,GCAADDGBDEBDABDGDGGEADEDDFHHHEHDGHFGHFDHGAFAHEHDCHDHFEBGEACDACGABGABGFGGDGBHEEHEFFGHFABDHEDAECBFHAGHAHBAEAAEAFEHFEBGGBCFDFEEAHCHHCFDAFDCFDBFHBAHCHHFFGEHDECCGCBHFHHFBHBE,False +101,3.0,4.0,2.0,2.0,2.0,1.0,2.0,2.0,BCFBEABEABHADGCHGD,False +102,3.0,5.0,4.0,4.0,2.0,1.0,3.0,10.0,BGHBGHCCHCDHEHHABDFHDBHEGCDAHBAH,True +103,22.0,16.0,17.0,17.0,11.0,10.0,13.0,12.0,DECDFCDFEDCCBCCBCADGAGFAEAAHHCGECAAFHAHBAGEFDEFHHGGFBFCBACBABDACDAHDAGDGBDBADHFDBCEHGEHGDHABGBCEDEEHBAABADCGGCFCABDABA,False +104,12.0,15.0,10.0,16.0,25.0,15.0,20.0,17.0,GBFDCFDGDDBHDAADEBGBDEBEEFGHFGHFGHCGHEGDEADHBDHGGBGHEDCFHAAHACHGGEGGEFEBFGADCCEBHEGFEHDEHEEFAGDCHFEEAEEBCEGEDBEDBECBFFBHHCAFAEGAFB,False +105,7.0,10.0,8.0,8.0,6.0,8.0,6.0,10.0,HBEHAGHFGHBGDBAAGCDEHFEBEHBEBCABAACDFHBCHDFGDFGDFHCHCCACBFDBEDF,False +106,17.0,20.0,9.0,15.0,13.0,17.0,14.0,15.0,FBEAGDAGAABAHBGEFFBFFEDHEGHEGHEFHFDBBCBBDBCHCAHGAHCHBEGFDGFAEBAEGADCAHBDFBDFDFBABHEFGBCDAFDBCAGCFBHFBAFAEDHEDCEDHBDGGHGA,False +107,5.0,5.0,1.0,5.0,1.0,5.0,5.0,2.0,FABAAGDGFDFHBFEBAGBAGBFDDHGDC,True +108,17.0,16.0,20.0,15.0,16.0,19.0,21.0,30.0,CBHCHHDDDGADGAFCEHEBHEFEAAEBHFHCBGFAEDHEFEFFCFFAHEHHAHBGCDCHFGHBGFCGFBEABFBHHGHHGCHEAHEADABGHBHHBDHGDHGAGGBGGEFCFFCDBGDFDAECEECGCAGCGDCFDFHHAHHDHBBCCACGAC,False +109,19.0,26.0,19.0,10.0,27.0,23.0,8.0,14.0,EBCAAAGFADFADFEFBBBCBEABEABEAEEHEEHEECEBGACCAFCBHCDCCECFBCAGGAFEAFEFBHHBDFAHEHFEGFHCFBBHCCABCHFFBFFBDGCEGEBAEGCFFEEDHFFBFBADBDBBDBBEHEEFCHACBAHDEE,False +110,19.0,10.0,10.0,17.0,15.0,14.0,13.0,9.0,EACEADEDDGDAEBCFACEAEBFHFFGDFEDBBGBHGCADCFBBBHCAHEAHFAHAAHCDGCDGAEGAEGEDDFGEAEBAGFCGDGDDABDFCDFGFFAAEDFEHAH,False +111,6.0,10.0,13.0,9.0,4.0,7.0,3.0,10.0,CCCAFBAFBEHDFBCCBCHBCBCGHDAHDAGDCDFCHCEHDAFDFHDHHDEEBFBAGBCHBC,True +112,14.0,15.0,18.0,9.0,20.0,11.0,10.0,7.0,DEFDEFBEACFGEFCACCBGGBHAAEBEHCEGGEDEEFEEDBECBABGADFADFADGCHCCHCHACEDHEGAFAEFBFBAEACCAEBBGBBGEBEBHCCDCCFC,False +113,18.0,25.0,13.0,24.0,29.0,22.0,19.0,30.0,HCAHEABDACHBBDDHADBEHEEHCABCFBHFBABBABDHBEHFGAFGFHCHGCAEFHEFHGHCGCEHDDFEBFEFFDDHDEEDGEFCBGBDGAHHCHDCFDEEDGCFHHFEEFGBGGEEHBFAGFDHBEGFEDCEDEBDEFHEAHEAHABBEDBGFBGEHGAHFADBADHADHEDBGGB,False +114,13.0,9.0,15.0,32.0,17.0,18.0,11.0,14.0,HDHDDAGGFDDFHBFBCAEDGEDCEACDDEEDFHFAGFDECDCCDFADECFECHDCHDGAGAHGHDFEDCEDCEHBHDAHDCFDBFHHGDBDAFCGFAHFDCCDAEDGEDEEFADFAGFBBDEBDEBDF,False +115,21.0,18.0,26.0,25.0,21.0,27.0,25.0,34.0,AACCECDFFBBDABHAGHGFHGHAFHBFHFEHCBHFDAGHAGEDBEACHDCAGCDCCDBEDBDDEGGEHGAHFAHDBFGHFGCDCCFCBFCBHCHHFFDFGEEEDHFHHFHDFEDFDCBHAGAAGHBEEDCFFCHEDAEBAGDEGDEDBFBGCBECHCGHCDAGGAHGHCGHCFHBFHCFHDADAEGEGHCGAFFEH,False +116,25.0,15.0,25.0,18.0,19.0,11.0,22.0,30.0,BGGBGDHGBAECHEFABDHBHHBHDADBEEGFGGDGCCGFCHHHAHAFHBFEEGEAHCGEAGDCCHCGDAGBAGBAEADBADHADFCGHEDHCABCHHEHDFHFAHEAHCHCAHBDHBGHFGEFCAGCHGAAACAACHHDHCCGECEDDFCDACDACBCCEEGEE,False +117,28.0,24.0,15.0,28.0,23.0,30.0,14.0,19.0,CHACHAGEBEFDCFAGFADDEDDBDGBDBFEBEDHHDGDECDEBFABFAFFABAAHHAHHDFHFBHDBEDADCBGHEDFFDEDDEBEBAGADDFFFBDFBFFBFFBHACFDBFDFAEBACBACGEGGCFAFEHEAHECHBDGGFCAECFEFHEHHAGACBDCBAHAAEAAEDECDAFGGFB,False +118,0.0,3.0,1.0,0.0,4.0,1.0,0.0,2.0,FHBBEEBEECH,True +119,15.0,14.0,10.0,15.0,7.0,12.0,18.0,9.0,BGDBGBFEBDCFAFFADCGGAGDABAAHHAHHACEBCDDCBDAGDGBBGDGDDACEFCFFCGFHGBEFCGACHAGAGHAGDABBEEFHGFBFDBEDGHDG,False +120,18.0,23.0,21.0,12.0,21.0,14.0,26.0,15.0,GBBHAAEBAEHEEFEGFGCAECABAGCADBEFAAGDABCAGGFGGCHGCHGAHEAHFFCEHCEBBFBBEHBCGECGACGDCGDHGCGGHGGDDGHACBBGDBDECDCFABECFEBFECEBGBBEDDEGFCDFEGBHGBHAHFACEBCHBF,False +121,18.0,17.0,15.0,11.0,14.0,12.0,17.0,17.0,AGGAFDDFCDBBHECHBCHADHCBACFACDDGFACEBCBBGBHAAHEAEEHGFGCFGBHEBAFHAHHADHBEGBHHCEFEEFGHFGFGCBDCADGBDHHEBEBBAADAAFCAGCGGEGGEC,False +122,19.0,12.0,14.0,16.0,13.0,13.0,22.0,12.0,DFAEFDEBHGFEEDAEDFGGCGGFGGFGGAGGAFFDEAGEAGDBBABDHHCHHBDHBDGCGGDHDAGCACCBFCBABHEFHCCHECBCGDDAHDCEEFACFBCAGDAGAAGAEFAGDBEHA,False +123,3.0,8.0,5.0,11.0,9.0,10.0,4.0,11.0,EBFFHHFADFCHFGHEGHFGFACDEDDEGHFAEDHBDEBDECDCDDFHBFEBHHBCEBHDB,True +124,4.0,5.0,6.0,11.0,9.0,6.0,5.0,8.0,ACEACEADEDEHDCFFCDCCEHHEHEBHGBDGHDFDFEGFEDBHDHDBBGFAGD,False +125,11.0,14.0,19.0,12.0,21.0,14.0,17.0,9.0,CCDCBDBEDHEGHAFEECDGCFGCEGCBGEFAEDACCHCDHGFEFFBBEABEAHHAFCCFBFFCFCBEGDACDGCAEBAEGGEDGEDCAGGEDHEBHBBACBHGFEGEGDEGEFCBF,False +126,7.0,15.0,16.0,15.0,17.0,19.0,21.0,17.0,CHHHDBCCEFEEBEGBHFEDGEBFFBGFGHHGHHGEHDHCDHCDFAFFDCABAFBHGBCGBFHBDHCEGAGGHHGDEAFECHDBFGBDBCDECGEFEEBECBDFFDECGGCGADGEDGFGCFGCFAF,False +127,1.0,2.0,2.0,2.0,3.0,3.0,7.0,2.0,BEGGGGACFHCFHEFDGGDEGB,True +128,24.0,27.0,28.0,25.0,25.0,12.0,31.0,20.0,GGGBGGBDBCDHGACGEHDCHDCBDCHHEHBGHADDADDEBGGHGDDEADFAHFAGGEGEEABEHDEHCEBAEBECBACBACGACGADFADBBBBFCCAEGHFBEBCAAHBCHFCEFCDFCDCCBAEGEGCAGCGCCGEHFEHGCCACAACBDDBHGBEBDAFGEFGBBGHHEDGDABCGFHDEGGEDEADB,False +129,8.0,19.0,18.0,15.0,11.0,19.0,15.0,9.0,BEEBFHGAACFBCEBFHFADFCDHCDBCGBGGEGBDAADFDCHECHECEGCFGCFGFBCFGCAGDFGFFHHBDDFCDFBBEDBFDGDBBFBHABCEBCDAEGCBFHBFCGECGD,False +130,19.0,16.0,11.0,13.0,12.0,17.0,19.0,19.0,AGFEGFGGEGDAFDBFDBCGACBHEHHAHHDFADABHAGHBFHDFCDCADEEFEGBDGBEGADBAHFGBDGBAEFAGFBCAECHGBGFBGBBFBHAHHAHDEGEFAHADCACCHCEHGAHFHGFCF,False +131,4.0,4.0,2.0,0.0,2.0,2.0,3.0,2.0,FBECAGHAHCAGBAGBEFB,True +132,21.0,22.0,26.0,22.0,19.0,22.0,19.0,31.0,HHACHAGHDFHCACFECAECGDFFDFCAACEBEDHHAHDCGBCBBCAHCAFCDBGFGDCHBHECHCFACFGCHECBBCFBGHDGHEGHDGFBAADFGBGGFCGHCBHAGHFEEEDAEDAHHABFABHAHHGHBFDAFDGDDFEDGBDFEDHDDHCEHEAHECEECEADBGCBFFHCFBBBBH,False +133,16.0,18.0,20.0,18.0,16.0,13.0,27.0,16.0,DGGBCEDCEFHDGHFBDCHFHHBACBADAAHADEACBGHFGEDGCBCABGAGFCGDCGDGBEGBEGBECEEHGEHGHHDAAGGACBDGBGCBACDEBDBGCFHFEHCEGCEAEFCHFABFEGGCDHFDCDDCDBFGBFGAGHAG,False +134,19.0,21.0,15.0,10.0,12.0,12.0,10.0,11.0,DAGDAGAAHHFHABCBBCEBCFBCGDCGEEACACBACEAFGBDAAFEAFEHBBBFECDEADGFFACGECBBCBBGEBFEBDAACHADHFEFBCHBFGBHDBCGBHADHAH,False +135,13.0,9.0,13.0,6.0,13.0,9.0,17.0,10.0,ACEEHFBHFBGFCHABEADHHCGACGDHBCABEGBEDBGGCGHHAHCEDAEFAEGCEACEAGGFCGCDGBFGAFGAFBEGCEGAFGECHD,False +136,12.0,12.0,9.0,6.0,6.0,6.0,7.0,12.0,DGFDCFBCHHHHHHHBHBBABEAFGBEGCFDFGCCBDABAAEAAHACCAGHADEACGHGEBEFBCDBHAB,False +137,8.0,7.0,7.0,10.0,12.0,16.0,11.0,8.0,EEHEGHGAHFFEFEDBGDBEBBGGFGDCGFCFCGFDDFHDFHAFCFDGAAFFAEHAEDFEGFEDCEGAEFBHBCDBCHA,False +138,16.0,20.0,15.0,26.0,16.0,10.0,21.0,11.0,BCEFDBCDBAHBEFBCAHCAEBDCCDHGHHCHDDDEGBFDFGCACAEEDGADGEDBEGCEHCHBGHBEDDADDGBDGBCGBDHCFGCGGFGGAAEAADAEDGEDBEBADDADGCDGBAGBDGBHGFFBEDAEFBF,False +139,13.0,8.0,3.0,6.0,6.0,4.0,5.0,4.0,EDGABAADGAECAGAAGAACHFFHABGFBABBEDBEHBAHCABDFDEED,True +140,3.0,7.0,9.0,8.0,11.0,8.0,12.0,4.0,FGFCGCCEEDFEBFEBDACHADEBCEDFBDEHEFBEHCEDCGGBGFBEFCGGDGHDGCGGAG,False +141,7.0,6.0,3.0,11.0,10.0,4.0,8.0,7.0,EEAAECEEGHEHDFDCHCGHEAAEHBDFBDBGDBADBEHFEAFGGDHDDGBDGADG,False +142,25.0,23.0,17.0,19.0,29.0,25.0,18.0,29.0,EEBEEBHHHHBCHEFDGCDECDEDBEFHAFGBFBHFBHFCHFEDFBBFEAEGBCBAAAADAHEEFAEFDFACHHCHBEHBHHDGECFEFBEGHEGHAFHCDBCAGHEGHGDHGEGGFAAFAHEEHBFABDACHABDCDAFGFFGCFECFHBFEEDDGDBFCAHAEDDEACEAGDBGAAGAHCBHB,False +143,1.0,2.0,2.0,3.0,4.0,5.0,2.0,3.0,CFDCBDHGEEGAEDFEFFBHFH,True +144,9.0,4.0,7.0,5.0,3.0,7.0,3.0,7.0,EFAFABHACHECHGCBADBADAADGCFFAHGHDFHDCHFCBECAF,False +145,21.0,27.0,26.0,22.0,15.0,22.0,16.0,17.0,FCDFDDECEHCFGCEGDABBGHCGBBFABAEFEEFACHBGFEABEDBHCCFGAFEEFHAFECFHCEBCDBCBAHFAHFCFFCFFBFAGGAECDCCBBDDCDDCABBAGGAGBAGHCHECDACBAFHECGBGGBAGBHBACCADDDDCHHHFHHBDDBDDBDBADBF,False +146,23.0,23.0,27.0,18.0,23.0,27.0,25.0,28.0,DEGHEGFDBFGHDEACECDFDDFDBBBGCEAFHFFHFEBGEBDEBFBBFHFFEFCGFCGCHGAHBCFGAAECGEGDDGCHGAHAAHAADDADCAFBFFBHBHEGCAHCHHBEACCBBABBDBHCBDFAHAEBCEGEGCBHEHFAGCAFCACEFHEFADBCGGCGHAGHGEHEFHCAHCGHDGHCEHCEFCGFDF,False +147,19.0,22.0,21.0,22.0,15.0,18.0,18.0,18.0,ADDADEFBADAHFBBFBBCHGCGBCBHEDCCDHDDACGEGBEACEBCGCFABFHEAHFGDCDDCGFCGHEHHEHBFHDFBFFBAFAABAADACDFCEFHADGADCCECDBHDBCGBAEBAHDHHDHACFCGFGEFHEGGCGEFGBDGBGBBDE,False +148,23.0,18.0,18.0,17.0,20.0,20.0,23.0,19.0,GHBGCBDAFDAFHCBEFGACAECHHGEGFEGDEDDBCAAGFAGCGECAEFBEACEHGEHAEAFEAFBCGCCFCBBGHBAFBFCBFAEHBEHBEGAACFABGEDGHAGBCGCEBDGDDHEAHCADFFGHAHDGHDGHDGBDABHAEDDFHDFCFFHGFE,False +149,11.0,9.0,14.0,14.0,12.0,13.0,8.0,11.0,CCFCGFCDFHHHGGHEDDFHDFEEGCEAHAHCADFEBBBCBFCAHBAHEACDDCDACDADDBDDBEGBDFFCEHEFBEFEAGEGFCGFCAHA,False +150,20.0,17.0,22.0,21.0,18.0,23.0,27.0,26.0,FDDHHBGAEAABAAFAHBGFFHEHCEBEBBEDBGDCGHCGHCFFEGFEDFCDACDAEBFEDAEDHHHFGHGDHGAEFCFGBEDAADCCGFGGAAGCHCDDBDCGGFGGFGGFHGFBGBCGECHFHHACHABDFHDHCAEBBEBGCCFHEHGFHFEHFEHBCACCACGAGHDDDD,False +151,25.0,32.0,23.0,18.0,29.0,30.0,21.0,16.0,CHFAFBDBCEHGEHEEFEACEFCFHHFCAGAEGBCABCAECHDDFDFFEFFGHABFFEHBBDBGABGACGACEDCGDEBDEBCEBFDCHBADBFDAADEFBFHGAACAACHDEADHCBGCAFBFFBFFBEBBGBEEBHDBFDGDAGFEGCABEEBEHBGHBGFBGBAGFGCEGCACFDGAEBEEFCEFAFHBCE,False +152,2.0,5.0,8.0,6.0,3.0,7.0,7.0,3.0,ECBDCEGFFGHCGCGGFBDFDDADDHEBFCBCCBFCGFGAH,True +153,20.0,20.0,31.0,26.0,22.0,23.0,14.0,22.0,GBGFBFFBHCBHCBHGBEFCGFHHHHEHDCHCCDGCFFCDDHFDEDGEGCHHADHCEECFECHECDGCDGADCAGAAHEDHCFBEFEDCHFFAADEADHADCGBCFBCFEEEEBGBCCCCBCDBDHBAHDABCAGCBCFBEHDEBDCFDHFEFDAACAEDADAFGEFABFDCEDAFAB,False +154,14.0,22.0,13.0,6.0,19.0,16.0,15.0,9.0,EEBFEFCBFDAAGAHBCCBGCEEAEEAEEAEEAEGGFHBCHBCBCHBCFACFGDECBAGFFDBHBBHGGFAGBGCBEHGADBFBBGGAFCAFCEGBEGBEFBDFBHEHEFDAFB,False +155,13.0,9.0,8.0,9.0,16.0,11.0,16.0,26.0,HGHDBHECHGCDGAEGFEHDEGGHHFBHFGHBGBEFEAHEAHBFHFDHADHBCHEAHEAHDGHDHHEFFACDCEBFGGEGAEHEGHEGCCGFHGAAAHAFHAHDEBBC,False +156,21.0,23.0,28.0,17.0,32.0,20.0,26.0,33.0,AGBGFFGFGGCEFCBFGBECECGECBECAGHDHEDHCBHEEAEEBFGGHEEHAGFFGFHHCCHADABEGBHGCHGCFBHEHHEHHGFHFFHEFAEHADCEDCHAADBADHEDAFHEDDCCDCFEHBHGGHEFHEBHEBHGBCGCADAAHACBDFBGCBECBCCEHEADEGEEAFCDBHGBCGBCDFAGEAEHAHDCBBCG,False +157,3.0,5.0,10.0,12.0,6.0,7.0,9.0,8.0,CDDCFDCHDGGFGDBGDHFHHEGCCHDCADCAGBFHEGEEGCEDEFDBFDHAHGCBFCBD,False +158,27.0,19.0,22.0,22.0,21.0,22.0,30.0,32.0,AEAADDGDGHBHDGHBGHBHHBCHCAHCABEEBDBDHGFHGHHGBBAHAGFGBAGAGGAGHHCFFBHHGDHAACAGCAHDADGAFHCCHGHHCHGCFGEEDEDBECGAFEDFEDBEGBCACHFCDFGDCDCCBGCFGDFGHFAAEDHFBHFGFFEAEEHEDBECFEABGAFEEEAFDCFDAFDBCGHCGHAEHAG,False +159,6.0,10.0,10.0,5.0,6.0,6.0,5.0,10.0,HCEECDECAFABHBBFADFCGACGABHFEHCBBCBBHFHCDCEDCHGGHEGHFBHABD,False +160,18.0,20.0,20.0,17.0,21.0,19.0,20.0,20.0,FEDBECCGDCDBGDBGDGGDCDFCAHCEHAGAABACFCFFCAACHADAACEGEEGBFBHEHHBGHBACGFDFCHFCHEAEBBEDFFGCFGBEBBEHDDHABGEEEEFABHABHGEHGEHGEHBFDFDHGDHGBEGBECCFCAFHFGCCDAFAHDB,False +161,12.0,21.0,28.0,20.0,19.0,21.0,30.0,23.0,BEBCAAFGAFGBFGEEEFCCHCGHFGHGDDCCHBCGACGEHGHCEHCFCBHCBHDAHDHHDCHEABGHFGBGGCGHCGCEGFDGDDEFGEAHBGEADDCFDGBDGDCFECFCGFCHEGAFCDFCDGDFFEHFBHFCCBECHEBHCBFDBFBBGBDAEDGECGBHEBDABGGGAH,False +162,21.0,14.0,18.0,20.0,18.0,17.0,19.0,20.0,GHBEAFEGBGGHDEEDEABEBBEFECFCCABAAEAAEACBAFBHFHHAEDBCDECDAFBAFBAGEHEHGDAAHGAEDCCDHDDHGAHAFCCECAFCHHCHEGBCDCCBFFEFFGBFDDDDDGGCGDAFDGCGFHHDHHDHGFHGAGG,False +163,7.0,8.0,10.0,9.0,10.0,6.0,9.0,12.0,FBCCDDCAHADHEHHAGCGGHECHECHGBFABFADFGDHBDHDDCDHCEBFHGECEEAEFHECEBGBGGBA,False +164,2.0,1.0,4.0,3.0,2.0,6.0,3.0,7.0,CHCFEGFCGHHEABGAHDFHDFHCFHFD,True +165,27.0,21.0,24.0,26.0,31.0,11.0,22.0,21.0,CAADGACHHEAHDFHCAHCFBCFBEBHGCEFCHCGECDEABEACDDGHDAFCCDCADCAGBDGBEGBCDEHAHHAEFBEGDEFCEABBDBGAHAACAAEACBFBBFGEEHEBDEGDEGDCCDCABHEEEGCDGCDGHEGEEGEHDEGDHDAEFEGBDGADHFDGCDGBAAAAHHEEHDEBABB,False +166,7.0,16.0,7.0,13.0,4.0,10.0,9.0,15.0,BDDEDDGCAHEFHCFHCBHAGFDBDDBDDGFFBAHAHHFGBBDFBDHACHBCEBFEHHGHHBADBCFBHDGABGHBGFBGC,False +167,15.0,15.0,9.0,10.0,9.0,15.0,18.0,14.0,GGABCADCGHHGEHBDHCDHDEGGGFGGAGAABECBCFBEABEBEGAACBBFEAFBHFBHFBGFCAFGHFGHDGCBCEHFFGBFEDFBDAHHAHHGFDDAGDAFA,False +168,21.0,14.0,14.0,15.0,25.0,21.0,7.0,17.0,FDABDAHCHHFDACBGCBGCHFAACGEEBCBFABAEEAEEAFEADDHFAHFEHAHHCEHEFDGFEHFEGFDFHCCAEAAEADBHCFHEBBCFACFDEADFAECAEBBEDBEGFDAFEFDHFDHFEEBCEBGEHD,False +169,11.0,25.0,11.0,15.0,12.0,14.0,16.0,19.0,CDFBBCHGCEBDBACBDCGHFHHFHDFHBEGBEDBFDAFCAHBACFAGGAGEAGBAGBHBBDEBHGHHGHFEABDHFCBECBFDFEGHDFHBFHAEHECHBHBGDBGBCEBABDEGDGGDFDB,False +170,11.0,10.0,15.0,10.0,14.0,10.0,14.0,13.0,EEGCEHAGADCDEADGBDBHDFGDHCDFCDHBAEAHEHCGFCGFCEFDHGHHGHFGCAACHACHAEGEBDCFGCFBBFBBEEBGACGFHEECEBCGA,False +171,15.0,14.0,17.0,21.0,14.0,11.0,20.0,12.0,CBGBFHBCEACEAGAACBDBBDCDDCDDAGGAFGFGDHADEDDEFFAFFCBFCBFCFAHDDBGGGEADHHBHBBDEEGEEGCAGCDCCGCEBHHCGGCDBCHHEAHGAEGHEFADGDGEDGDDA,False +172,6.0,4.0,6.0,6.0,3.0,10.0,5.0,4.0,GBFGHFGDEDFCDAGDHCDACBECDECAHAFFAFBCBHAFFGFF,False +173,2.0,0.0,4.0,3.0,0.0,0.0,1.0,0.0,DDGDCCACCA,True +174,3.0,6.0,8.0,12.0,9.0,8.0,4.0,7.0,FGBDDHHDCFABFABCBCCHDEHEFAEFEBFEDDHDBCDECFHCFGEGGEDDCDDHE,False +175,4.0,4.0,3.0,0.0,0.0,0.0,2.0,1.0,GACGABHBBAABCC,True +176,4.0,2.0,4.0,1.0,2.0,1.0,1.0,1.0,HCDACAAEABCFBCEG,True +177,22.0,20.0,10.0,18.0,13.0,13.0,19.0,20.0,CBHCGHGEHEEADBHGAEGFEGFBAEBCFAFEGHCBABFADFDDCHBCHDHAGGADBAHFEEFHBBHBGDDDHDGHGFHAFAAEGBBDAADHGBEGBAGBADBAHCHHADHDGGDFGDFDCABCABCABEFHEGA,False +178,22.0,19.0,25.0,28.0,26.0,27.0,22.0,13.0,CCCCCCCDCAGHEHCGDGHCADEADBADHFDGGGBDACFHCFHDGBDGDAGDCDDBBCEBFBAABDCDDEDFEFEECDEBAFBDDBFEHEEAEFGEFGEAGBFFBFFBCFCFDGHEFCAFCAHEEGEEBEAHDGEFBFHDFEDCDHCDACGGBGCAGDAFAAFEAFHDFEGECBBGFAEFAG,False +179,3.0,7.0,11.0,8.0,19.0,13.0,15.0,4.0,BEEBAEFHEBGCBCEBFHFDECDCGHGFEGEEBECGFCGFDGDDGFAFFAEGCEFCEFDECEEGDEGCGGFGEBDHCEGF,True +180,23.0,18.0,16.0,19.0,17.0,9.0,16.0,16.0,DACDHCDECEHCBACDAFDAFABCEDHDGHBCFFABCDDFDDHCAHBAEDABHABDGDFCBECAEAAHGEFABFGBGBHABHCEAEGAEGEHGFHEAAEAHGCEGCHGAEGCBGCDGDEGHHADBAGBEDBDBB,False +181,7.0,4.0,3.0,4.0,1.0,4.0,0.0,2.0,CDDAFABHAECADFHCFABFABDAB,True +182,7.0,17.0,14.0,12.0,11.0,8.0,17.0,16.0,ECEECHEGDCFDCFDCEDBBGBGECGBHGFFGCBHEBHABAGBHFBHDGHBECBEHHGCGCCGCFGHABADDDHGDHEBHBCGGFFACHAEADBHDGHBGDB,False +183,18.0,19.0,14.0,22.0,20.0,25.0,20.0,18.0,FBAHCEHGHHGAEDEDDHDHGFACFDBFGCCBHGHHGBHGECBHFDEFBEBHECHFGDFHDEHAGGEGDBGAADFADAADGADGHFFEGCABDGFDBDECDFAFAEFCEFCADGFDFFBFFBHFCECGEBGEBHEADBBDFBCFDCFAAEGBEABE,False +184,9.0,17.0,14.0,14.0,12.0,19.0,15.0,10.0,DBDDHCBBBBGGFEBFEAFGCFDCADCDFEFGHFDHBDCECCFDCAEBEDHFDCBDGBACACGECFEHDBACBFFBFFGGDEGHHGCHFBHFBEFAEAABGFBGEGGFGH,False +185,5.0,15.0,12.0,28.0,11.0,16.0,11.0,13.0,FBEBDDHEDCEGFGGBGEBDBBHCDGDDHBDHECBDFBDEGHEFHEFEDCDHGDADDABHABDCBDBFDHGDFDCGHCGDCHHGDADDEDDAFDFFHFFECDCBBFFCFFC,False +186,3.0,2.0,0.0,4.0,2.0,3.0,6.0,2.0,EGADGADADBGHFGBDGHFGEF,True +187,7.0,12.0,9.0,16.0,4.0,16.0,12.0,10.0,BDFDFFBBBEBBFCHHCHHFFEGDADDFDFHAFDAFBBGDBGDBDDGCDFFDGDGCBCADGEHGDHCCHACABHAHGCFGFFGEFG,False +188,9.0,14.0,12.0,11.0,9.0,6.0,5.0,4.0,DFBEFDCDCBAFBADEFDEGCEBCGFCECHDBADBADBEEBABGHBACBACBECGACBBCADDHFGHECD,False +189,15.0,22.0,16.0,23.0,11.0,18.0,13.0,25.0,CHGBHDEHBEHDGCDFHFHHCHHGHEDDBGHACHECHBHGDHDCHDEAGEABFAEFACBBDDBDBADACDABFAHDABACBHHDHCAHFFBBDBGAFGFFBBABCGEEFEDCCDCBDBFDBFEFGGFHHFHDCADBDGFCGFH,False +190,23.0,11.0,18.0,25.0,19.0,12.0,19.0,38.0,DEHHAGHADHGCHACEDCAGEGFDADHADHDDGEEEEHFHGCAGEDDFHHEHHDHDGBDADHECEEGAFHDBHGBHGBDAHAEHABHBBFDDCDAHHGHHEHFGHCHDDECBFCADCGDCGHCGHGAHGABFHFHHFHHEHHBBAEDAEDFCCECAAGACCACAF,False +191,5.0,6.0,1.0,7.0,12.0,13.0,5.0,13.0,HEEFEHAEHFFHFGDFEDGEGAFGFHGEHDBHAFHFFEAHEBEBDFADBHHHEHBECFDBFD,True +192,14.0,9.0,19.0,16.0,17.0,13.0,14.0,12.0,FBCCBDDFFDHDDHGEFGEFGFHGFBDFCEEHACCAEEDBFDEDCHFCBAEFCGGAHFADGAHEHHAHBACBCEDEEDCCDCGACGCCGCEGDECAECAFGABGBHGDDEAEHA,False +193,13.0,11.0,10.0,13.0,18.0,18.0,16.0,24.0,BFHBGDBGHEFHEGEEGAAFHDFECFEAHEAHDFHCHHEHFAGEGCCHHEDHEDCCDAGGAGGBDCBDAFHFFAFDAFHGCHGCFGHGHHCHDBHBFFADFEDEBHGGFBADHAEEEHEEBFB,False +194,4.0,3.0,4.0,0.0,0.0,3.0,1.0,3.0,HCHBAHBAGFABCAFCFC,True +195,5.0,5.0,1.0,2.0,4.0,4.0,7.0,2.0,EFBGHBGABGADGABHAGDBECGAFGFFEE,True +196,16.0,12.0,12.0,7.0,4.0,7.0,9.0,12.0,ACGACAHFFCEACGGDEADCAGCFHBFBEFDHDBHAAAAGHBBHCBHGBAGBACBDCBHCBACDECHHAGHFHBGADFA,False +197,11.0,6.0,8.0,7.0,7.0,10.0,12.0,14.0,GHFFHACEECGEGGDBGBBFAGFGCHGHDGAEGCCBHCBHAFHAHDAFGAFADCADHAHHBCDFGEAHEHHFDEF,False +198,21.0,16.0,17.0,15.0,22.0,24.0,21.0,20.0,AEFABCDCDABGHHEHDFBBFCAGGAEFCGGCGABGACGHHGDGBDBBCFACBDFHHEHFCHFCECHFCHGEHGBFFECFBHFGHFEDFDCFCEAEEADDGDEGFEGFABFHBFAEHEDDADAAGAACEACBHEBFEDFAAAGGEGGBHEEHFEHF,False +199,3.0,4.0,1.0,2.0,7.0,5.0,9.0,5.0,HFFFEGEEGAHGBHGAHDADCBGGEEGEGBEGBFFH,True +200,27.0,17.0,26.0,18.0,16.0,17.0,15.0,13.0,BDEBEEBCBBCDFCHCCABDEGCGACGACACFGDDGAACBACEEDBDDCCCHCDFAHBGEBCHGGFCGHHHABHBGAEHCBGCDAEDFEFBEAHEAFFGDFHDHHDFDBFEBAAGAAGAGFCBCCEACEACECFAFAAFAADCFDAFDA,False +201,14.0,18.0,22.0,18.0,23.0,25.0,18.0,25.0,EHGEHCBHCHHAEHDEHDEAEBCEBCEGFAHFAHCEHBFHBHHBHEBCFADGHFGCFBAFBDHCHCEHADGBDFBFFBHBGGEFFFDFEBCDFDHCDHBECDEHECBECEFAGFCGCAGEHGEDEFHFCGCCDACAAFDAHDFFDBGDGAFGCBCDFEGFGGE,False +202,6.0,4.0,6.0,6.0,4.0,7.0,2.0,1.0,BADGAEAACFACGEFBACCEFCEFBDHDDFDBFDCF,True +203,4.0,8.0,7.0,5.0,6.0,6.0,6.0,7.0,EHAECAEHBEHBFHBCDBAEFEGGCFGDGHHACBBCGBDHCDFCDFGBF,False +204,6.0,15.0,10.0,9.0,18.0,10.0,16.0,17.0,EHHEDFBDFGDGEDGHFEEDDBGFADFCBHCBHFEEFAECGHHGBCEDCEHFACGHEGHEGCBGHBCHBEFFEHADBAGBGHCHEEBEAGEBGBHGBHCBG,False +205,6.0,8.0,4.0,6.0,11.0,10.0,4.0,7.0,BDFBFFCHFBADBGFCGCCEEAAHFAHFGFEEFBEAHEBDEBDFHDHEGEEBEHDA,False +206,7.0,11.0,7.0,14.0,12.0,11.0,11.0,15.0,DFFHFBABAHBEHBEHDHGCHFDFAGCGHEBADHGDHCEHCEFCEFGFFGHGCDAADGBBGDBGEBFEDHABHDBCDHHEFDEGDEDE,False +207,14.0,19.0,19.0,16.0,15.0,16.0,25.0,15.0,BHBBDBDDGDAHEGEGGECDCCBCDAEBGEDGHDCHFEHACACCEDCGFGFEGDGGAGGAGGHFBEGCEGCEBCAFGHEBHDAEGAFHHCADFBBFBFFDHFCHFBBGBBCBACGFDAFHBCGFCGEDGADEAHFCHBG,False +208,14.0,24.0,23.0,25.0,20.0,23.0,13.0,19.0,CGFHBECCCACGAFFHDFHDAHCCFBDFBCCBGFDAHDABGABGHBFHCDGDDHBHEBCEDEFFEFFEFFCDDGGECDEFDADDHEACEAHEAEEBFBFGBDBBFCBDCFDGFHBBDBCGCDAHDCCDHCEEFEGGECBBABDCBDEFEHHEHHBHBADFA,False +209,5.0,7.0,7.0,12.0,11.0,5.0,6.0,4.0,BEEGAGCAHCFDCAHCEFCAFGGDDEDCBDBEFBEDDADDHDDBBDBEEEGCEGHEF,False +210,21.0,21.0,29.0,26.0,25.0,22.0,25.0,25.0,HGGGCBGCBGFDHCEGCBADBADBDFHCBHDBEBBEHBEFBCABCACCFCEFHAFHGFGDDGDDHHDEDDHCBEDDEDCBGGFAADADGACHAFDBEBEECDECEFGGHECHEFHEBHEDGCDCABCEFGEGHFGHEECDBHDFDFGCAEAGEAHCHFAHDGHACFACGHHGDHGCAAEFAFBCBECGFCFFCA,False +211,25.0,20.0,15.0,18.0,16.0,31.0,22.0,17.0,GDHFDBEDFEFGAHDFFDBECFDAFDBFGBDAEGAEGFDCFDCEACBAFHGHHFBFFBHHEAFBAFDCFBGAGGACBACFCEACEACHHGDHGCGFHGHAGABGBGDFHHFCACEBHEDDAFDAGCADBEGBFGBFEFFEAFGCFBHFEHGABAABAEGAFDFB,False +212,11.0,12.0,15.0,21.0,14.0,13.0,13.0,22.0,FDHBAHAHFDBFDFCHHEFHDFAGBADBADCHDFFDABDHCDHCGAGFHDDHEEHBHHEHBCBGDGCDCDECDEGEBHEHHGHDFBCFDAGCAGCACCEFCDBGEBGEDEFGHCGHEDHEA,False +213,26.0,25.0,22.0,24.0,22.0,21.0,23.0,28.0,DGGABBFFGEFGHFBHBHFAGAHGECGEBAACCADCHDBGDHCDFEDCCCFBFAHDEGGBGECFEABGHDEADGBGGFDEFAABAAHAAHCAHGFHBFABFAEHHCHHCFBEEDEEFEGDEHDHHDHCBEABAGGAFGDFDCBCHBCHBHEBAAGCADCHFCFDBBDBCDECHACHDBEDHEFGADGHDBE,False +214,17.0,18.0,21.0,25.0,26.0,17.0,17.0,17.0,FEFAEAHHABBGBGGCDGDEEDAEBGFHHCADDHDDEDDEAFECGGAGGEBGBACEEDEEDHDDHGBHEBCBHADFEDEGGCDDBDCFCHFEFAHFHDBHDBHAGCFEFFEBEEBEEDGEACFABBCBFDBFHFECGHCGACDCCDCCECFHAACADC,False +215,3.0,8.0,12.0,3.0,11.0,1.0,8.0,8.0,ECHEGGEHEEBCEHGGHBAADGCHBCBBCHBCHBCEDFEGHEDCGCCECEBCGA,True +216,3.0,7.0,2.0,4.0,7.0,5.0,4.0,9.0,EEBACHABHEFDEHHEBHAFHFCHEDGEBBDFBHGBHGFDG,True +217,24.0,19.0,23.0,32.0,19.0,19.0,18.0,19.0,BDFHFFHEAGCGGEHGAHGADAEDAEGACABCBFDEDDEHDGDDEDDGCDGAFBBEBHFBDEADCDDCHBCEAHDBHCBHCACBGCGFCGFCGDHFABCACCABHEEHDGBFFDFFBHADDDCAAHDAEFEEFBDFADGADHADFGDCGCCBECADAHHCFDCGBEFEEDHBA,False +218,15.0,9.0,15.0,14.0,9.0,15.0,10.0,14.0,EDDHBDCEDAHHCDHCDEFECFDDBDEGDCAFCAGCHCFHBFBDFCABCEGEEHHGFHAFCABHABDAFAHBHHGFCGFHGBAAFDAFAAFEDFAGGCCGC,False +219,24.0,26.0,20.0,28.0,17.0,21.0,17.0,23.0,FBGGAGHAGHGGBGGFFDAFDHDCFBFFHFDHDDHFDHFHCFGDHBEFCEACHFEHCBADHDBADCEBCDDAGDAFDAEDEHCAFDAFDFBBAGBGHBCHAFECHDCEBBEABGFHEBHDGCEFCBACBACBCCBHBFGDADAAHAHBGDBDEBGECEDHDAEBAEBAEHADCDBC,False +220,10.0,6.0,12.0,8.0,3.0,8.0,5.0,9.0,DEDDFFBCFCCAGBFHBACAACAHFAHBEGGAGCDCCDFCDFCAHCACDHEHHABGDBHFH,False +221,18.0,20.0,25.0,20.0,16.0,11.0,30.0,25.0,BFFBEGBGFBGHBEFEDHBDCAAHAGHFGDADCBDBBDECAEBAHGHGABBHHBGCGECEECADDDGHDGBBGBCGHHGCHCCHCFHGGHAAHAHGAHGEHGDHBEGFHFAHGADFEGBDHFDGCDGCFGAGCCGACGHEGDCCCABCECGEHDEDDCCECADCB,False +222,19.0,19.0,21.0,28.0,17.0,28.0,23.0,16.0,FFFFGGBAGBFCDFCBFDGDDEDDFDEFCHDCHACAAFFDGFHCFBCDGEGEECCCBBAHHDEHDECFGGGDDGDDGDDCBACBABHCDCFDCEBEGBCHEFHGBHABAGFGFADHAGFAEFHEBBFBEFCGFHAFGADGAFHBCABDEDDCHFEHFEGAEDCGDFADBAG,False +223,23.0,19.0,28.0,13.0,18.0,28.0,23.0,33.0,GHBCHBGHEHEAHDHGDCFBHGCHGCFGCBGBGCDHEFAGHEGAABBHECFCFGDEHCEHAFCADAGDFGDHACBACHACHCHFBEFCFGCHHHHCHBCBEDBFHBEHBAGEACHACFAGGHGDHFFAFEADEAHFAHCCHEFGEFBFCBHDFGFFGAFDACDECECBEBFHBAGCHGCAFFAFF,False +224,3.0,2.0,2.0,3.0,1.0,3.0,0.0,0.0,DAADFBDFBCACFE,True +225,18.0,28.0,26.0,15.0,16.0,22.0,28.0,24.0,CCBGHAGAEGAFGBHGCHGBBBHBBHCBDDBFDFGECEECAGHEBBGBAGBFGCHCCDGCDHEAGCBBFBBFCBGGAGBDGHGGHGHHFHDCEDAFGHBGABHBEAACGCCHCCHBHHFFFFGCFHCFEDACFGEFCAAGDCDDHDBAABFACDABEGCEGFEHFEFCEDBFHBEHF,False +226,0.0,1.0,4.0,5.0,1.0,5.0,5.0,2.0,DBGCFGDHGFCGDHGEFCFDCFD,True +227,9.0,11.0,5.0,9.0,13.0,8.0,7.0,11.0,DGHBGEBGHACBAFHAFHFHDDHCGEAGEDEEBEAGFDFBDFBHFHCDHCEEAFBABBEEBEBDHADHGEEAC,False +228,3.0,5.0,4.0,5.0,8.0,4.0,5.0,8.0,DCEDEHGEHGFCEFGBDHBDCBDHFFHEAHEACGBGHAEHEB,False +229,5.0,2.0,1.0,1.0,0.0,2.0,0.0,0.0,ABABFACFADA,True +230,17.0,15.0,18.0,10.0,25.0,10.0,12.0,11.0,ECCHCABEAEAABAEBGEBCEBGAAGBBDFHDEHDEHCHHCHCEHEEHCGBAFCDEEFGEGGCFDEFBBADBEEFHEAHECGFCDAAAFBBCCCACBGGBAEDDEGDECCEFAEFAEG,False +231,31.0,18.0,29.0,27.0,23.0,14.0,25.0,29.0,DGBAGHGHDGCGACBADBDDEADFCHGDBFEBHEBHEFHFCDFCDACFGHDDDDDCGCEAEEADCBDBGGHCAACAEDACHEHHAHDDFDEHCEHCECEHHEAFEABCGEGABHEDHEFAGCGGCGACDAGDACAAHACBBCDACAACHCDHGAHGFBDAACEACECFEHGGHBGHBCFFGDBGHBEFEHHAHBAG,False +232,9.0,27.0,30.0,27.0,17.0,16.0,18.0,20.0,HDBHDCCCHHCHECBBCGCEDCHCADGDBBEBGEGGFDFDDGDBBFHCEEDFFFHFHHDGCEBCABABDEHDHCDHFDHFDHBDHGGEECBEHBDFDDBCDCCBCCGCAHDBBBBFBEHBEGBEDDGAAHCBECBCCBCFFEDFEDCCGBAGACGDCAFCGFGG,False +233,13.0,14.0,9.0,12.0,10.0,11.0,7.0,12.0,CACBADGHDGHDFHDFHDEEDGEBBEDHACHABBFCFAEHACFDCEAHEABFFBFEAAEBCHDGBDBBGCBFEAFGDCDHHABHABGF,False +234,27.0,12.0,19.0,20.0,14.0,11.0,16.0,19.0,DCEACEBHDGHAGFBGABGABGABCHFEADDADAHDHDGBFAECCBCHHFADFEFAHDAEDCHCHADBFDCGDCHECGAAAAGBAEEHGCCGEAGEFCDFDGGCGACHCEHCEHDEHBCADAADADDFHGAHBAHBAF,False +235,10.0,14.0,16.0,10.0,22.0,13.0,14.0,12.0,BCEFFEFBBGBBGEDGEABFACCDCCDHEGHCBDGHEEEFAGBHGBEEHEEHDEFDEFCECDECHGGAGFFEDGHBECBHCGFEAAEAHGBHGBHEBAFACCEDCACFDCF,False +236,7.0,11.0,9.0,8.0,13.0,11.0,4.0,12.0,AEBEHFHFFGFHBFHFAHBHHBHFEFABBEBAEFCEACHHDGDEGABCCBCEBDEDCEACFHCFDCHDEEDBGDE,False +237,23.0,30.0,14.0,18.0,17.0,26.0,17.0,30.0,DGDDFCEFCGCBBHACAFCEEEEAADADEHFABBADHADHFDBFHHFHDFDAFEADBADCAFAFBEBBEBBCBBCFBEFBGFBHBBFFHFAHABHEFHBFHEGHAAHBAGBGFHAFABEGEGGDCGBHBCHGHFGHGHHCDEFFHCBHBBHGEHGDHFDHCDBDAHGHBEAACFG,False +238,19.0,27.0,27.0,14.0,19.0,23.0,28.0,21.0,CCCACCFBHFGEBABBGFFGBCHBFAAFBAHCAHCBGABGADDABDAFDBCGECFEHBCHGHHGHEGDEBFBBCGBGHBGFBCCBDGDCHACHADFADEHDEHEGADGAFBFGBEGHFHEADFCCGCCGFCEFGHFEFBCDBGHHECGBCFAEBBCDGAGCAGFFEHGEGFEGBECHE,False +239,12.0,6.0,10.0,11.0,16.0,6.0,12.0,10.0,DBDGGDGCDECGHCHEAHGDEFEEFEBBHABCCDACGFEGHECAFAEDAHAGCBGAHGAGFABFDEEDGEHEECEDCEAHDAH,False +240,12.0,11.0,10.0,12.0,15.0,7.0,12.0,8.0,EHCEBGEBCADCDFCEGBEBCEBHDGAAGDGHDCFDEEGBEFEEFGEHGHBEABEAFCFHCGHCBADAADADGAEBBDDHDFGACGA,False +241,24.0,20.0,23.0,18.0,18.0,16.0,33.0,12.0,DCADHACHFFHADCCDEEDCEDCFAAFGBCGACGAGGACHBBDBCCBEFBGCDGHFECABCACGAEFAECBFFFHGCAECAGHEHBFHBAGEFGECGHBABCADDGGDGGDGGCGCFFHGGEAGEGEEBBEGAGFFGDGGBGDBGDCGHAAABGEBEBDDBDAA,False +242,2.0,5.0,2.0,2.0,7.0,2.0,2.0,4.0,EHCHBDECDEGFEAHHABBEBFEBGE,True +243,5.0,8.0,9.0,5.0,11.0,13.0,13.0,9.0,ECEEGBGFFHFBEFHFDBGDBGFHFFHGHCGHEACEABBFEEEEGCGGCFBCDCCEHCDHGAFGABGHFGAFD,False +244,8.0,13.0,8.0,11.0,10.0,14.0,17.0,10.0,EGDHGCEDHEAHFBCGBAABGEDAEDAEGGDDFDCFGCEGCGFADFCFEBBCBFDGFAGFEDFBGFGHBBHEDHGGHBAFBFHCFHGBHGB,False +245,10.0,16.0,19.0,10.0,13.0,11.0,21.0,15.0,BEEBGHAGHCCFEDFGFHBHHDFDDHCFAGFAHABFABGAFAACBECGGGHGCAGCHCEFGEHBEHBGFGEFCHDHHDEBCABDGBGGCGGCBGEBGDCCCCDCBDEBGEBECCH,False +246,9.0,13.0,8.0,9.0,4.0,11.0,15.0,3.0,BDDBDDBAGAEGABGEDFCBCCFCDABHCBGDGGEGCEFAGBAFBGGBGGBDFFAFBCGDHGHFFCFAGFAB,False +247,24.0,29.0,19.0,27.0,21.0,19.0,25.0,36.0,AGGDCEDBEDGADBCBEDBHDFHDBEFHEFEEGEGDEABEFHDBHBHHFFAFBGGHCFFEAFDABEAFCHDCABBBCBEEBFBGAGHBGHCABCAFHDGHCHHCDGADHADGFHGFCGDBHBCHBDAEGHHGHHAHCAHDDBGHBGCEAHGADDHDECGEHHEDEGFEDABHABHABCABDABDACHGCBGDHHFHFFGC,False +248,23.0,15.0,19.0,20.0,20.0,17.0,12.0,20.0,AEDAEDAEFADFAHFAHEEHBBCBBDBCAFAAGCCGACEHEADFHDFCDAHGBEFFEFDAFGACGECEHHGADGBCAFCGCHDDDGCFFDBCHECFEHEABEABDCBHFDHECAFDABDAGEBGHGEHDBADBADCHCHHCFHEEH,False +249,5.0,8.0,8.0,6.0,8.0,12.0,5.0,4.0,DDADDFEDFHACECHGGHCDBBFFBEEBGEBCECCGBEAAGAEBFCFFHFFBFFCF,False +250,9.0,9.0,5.0,9.0,9.0,5.0,9.0,6.0,EBGEGDECAEBBGBFDBACGCBBCBBFDADDACDGEDGHDHDAHEFHFGAEGHFGAAEHAE,False +251,3.0,4.0,6.0,7.0,2.0,6.0,5.0,5.0,FCHFEBDGHDHADFGGFGFFEDBCCBCCHGCHDBDDAA,False +252,23.0,16.0,22.0,22.0,17.0,24.0,15.0,22.0,GDGADAHGFBBFBCHBDHBDCCDHEGADCHBBDFHCGGCEFBECHECEACFDBADEACEDFFDFFDFCEFCGFCHFGAFADGAFHAEABFDEDHHBAAAAHGABGDBFEHFHHFCHDCEAEEAEDCFFAFHCHHADHACHAEDABDCCGGCGFCBFGEHBD,False +253,28.0,21.0,24.0,17.0,16.0,23.0,19.0,22.0,HBGAFCHGAFDHGAHGHGDDGADGECAACFACBDGFCBAHBHDBFDEFABFACAEGFHGBDGBFHDFHCGBAGCABEGHEFHECCEAEHADHFDCCDCCEAFBDDBFHHFGHFCHCDHCFFCBAEFAEFEEAAEBFCBAABAAHEABBAFBGCBGCBDFGAGCCDECAHH,False +254,22.0,21.0,35.0,22.0,18.0,16.0,18.0,17.0,CGFCBBCBBCFBDHEGBFDEHCCAECAHAFDEEDAEHAEBCHFHBFHCHBGEACCCCDCABFABCDBDHCGCCGDCDDADDGGEHFEGCCBCBAFDEFDAADFAGGHECHECHECHAHGCFBBBBAGGEDBFDAFDCEDCEDCADCBHEFCAGCAGCBGFDACAACGGH,False +255,16.0,23.0,16.0,16.0,20.0,17.0,25.0,22.0,FBDCDGFHBEHADAEBABHAGDEEDGEAABDDEEFEEDBCGGDHHDHGDABBCBBCDHCDBGDBGCHGHAGFECEEBEHFGDFACHGHHGBHCEHCECABHADHACFBBAEFCEHAGHGEHGFHGFGGFGBFBFCBGCFGEFGEHBBGFCAFGAB,False +256,4.0,5.0,1.0,1.0,3.0,4.0,5.0,7.0,BHFAGFAFHABDAEHHGHHGEGBEGBCBHF,True +257,15.0,16.0,15.0,21.0,14.0,16.0,23.0,29.0,BBAHCCDBGFHGFGFFCFGCGHCGHDGAGHDCHDEABEBGGFDDFHDHHGHBAHDGCAGBGEBHBCHGEFGEHGEBFECHEDGEHBAHBEHDACDHHHBCHBCHAFHDCHAHGAGGDDBDDEACBAEEAHDDFFHGFHFFDAEDACDFG,False +258,25.0,18.0,28.0,20.0,16.0,20.0,26.0,30.0,GBDGBHAEEAHBAHBCHCCHCEBCECDEAAFHHCGGCFFDFBAGBHGFHDAHBACCADCAECAFFAFFGGEGCEACECCFCBEAAGFCFFGGHCDECBGHBHACAAFDGHDCHDCFDHFEHFDGDGHDCHAEADGGEADCHDHBGBDGAGGFFHHFHAGHCHHCDBGHBEHDEHGABBADBCG,False +259,10.0,4.0,2.0,8.0,6.0,7.0,4.0,6.0,BFAHHADDBDEBDAHFACEADEFDEHDGAGFDGFAEFBGFEAACHAH,False +260,17.0,18.0,20.0,22.0,23.0,26.0,23.0,18.0,CGCHEEDEBDHDGEGFEFFCAHGBHBEHBACAAFAFFDBFDCFAEFADFAEGBBHADAGGHFGCCGCGFBDFEEEEADHGDCEDFGDEBDHBGHBFFCAFCECGEDADDBHGBECFEBFEDFDDEGDHCAHCFFGFFGAHCDHADCBECBHHBHCGFGGABGCEGFE,False +261,27.0,24.0,20.0,19.0,30.0,32.0,21.0,26.0,GEHGECEEBEDACCACGBFGFCDBHEFEEFGEFBFACFACFAFFAGDACBAGDEBABFAEDAGHAHBAECAFDFEEBBBFEBDEFCHFHBFHFEHDGHBGHCCFDDAADEAEECGGHGFECFEDFEAFACHACEFBEFHHBHHFEAFHBFBBFBHFCAGHHFHHGHDCHDCHFGAGDDGCAGDEEAGEBEDAGHADBBB,False +262,24.0,26.0,23.0,23.0,21.0,23.0,28.0,24.0,CFDHHBBHEEHEHHEFHBDAADAFDBCDHDDFGAFCACEADGBEGCGCHEAHGADGABGADCFFBFEDDAFDCFHBBCFBGDGCHECBEBBCABDAECAHAHHAHEBHDHHFAHGEBEHFAAGBAGBGGCAFAFBAFBDCDCCDGGDGBHBBCBGFGEEGECGEHECDFCBFGBDGCACEFGEGGFHGFDGF,False +263,0.0,1.0,9.0,1.0,3.0,4.0,6.0,1.0,CHCCEFCGGBGFDGEGCECCFCFGC,True +264,6.0,5.0,5.0,2.0,0.0,4.0,6.0,0.0,CCAGBBGDBGDBACACGAGGFFFAFBAC,True +265,4.0,10.0,10.0,7.0,1.0,8.0,4.0,4.0,BEFBDFGDFABCABCHFCDGBHBCAFCAFDBDBGGBDFCCBCFHCDHC,True +266,22.0,29.0,31.0,16.0,20.0,28.0,16.0,14.0,EHAHCBHCBECFGBBCHEEBAFBHHAFGBFDBFCBFCBFCBFCGFGECBBGFCEFBEFDEDDGFCFCAGCAFCEGAAGAACDCFGAFGAFHBGABDAGAHCAECABBBCFBCDEAAEBFBBFCCFCCFABFDDFBEHBFGEDBEDEHAECBGCFHCDECACCDEFDADEHCGDBHH,False +267,19.0,18.0,7.0,10.0,13.0,13.0,13.0,11.0,HAHCGEBDCBCBBEGHFGBCGAAGBGGFDGCAEADBAHBFEFFEAGEHCHHBAHAADEFGEAGFFEFAEFCBAABAABEAFGAEGDEDBBABBFBHHDDHDBFD,False +268,17.0,10.0,10.0,7.0,8.0,5.0,14.0,9.0,DCADHDGHAGBAEHECHCGADHCGAEGBEGAEGAEGACAHGHDCBGHBGFBCAAAACBBEEBGBCFCAFDAFDHFGABGA,False +269,1.0,3.0,0.0,1.0,3.0,4.0,3.0,1.0,GHGGEBEFBFABFEDF,True +270,23.0,19.0,18.0,18.0,15.0,13.0,11.0,15.0,AHDAFCAECAFBHBCEFDEFCEFEDAADBADCDDFDAFGEHGEAGHADBBEACFGBDHADGCCABHHGHFBEDGHFEACEFCBAGAAEABEABGABHBEABGABFCBACGDDHFCHBCHBHHCEDCDDCDBC,False +271,7.0,9.0,4.0,6.0,4.0,10.0,14.0,6.0,GDDGADGAHAAHABDGFFFECFBHBEGEGHEGDCABGGFFHFFHFBGABGDBGCBGFGCB,False +272,9.0,5.0,1.0,2.0,6.0,2.0,1.0,1.0,EDAEAFECFGHAABAEDEBBEBAABAA,True +273,6.0,7.0,5.0,6.0,3.0,4.0,5.0,6.0,DBGDAGHAGECGFBHFBGDDFEDFHCBBEHHCAHBACBACAD,False +274,13.0,30.0,20.0,14.0,22.0,14.0,15.0,16.0,HBGBBDCBAHEFEBDBCABCGFGEHGECGCDECDBFDECGHBFHACDCBBHEHGGHFGBBBBHBBHBBGBEABHDBGDEGEFDECCFHEBHEHGEFCFBCFCDABAAHEECEECEDCEDGEBFEBAABGABCBCAAFDAFDHFC,False +275,5.0,8.0,10.0,12.0,2.0,10.0,10.0,5.0,HGDDCDFCDBGFCGDBGEAFACFDBDDBHDBCDCCFGCHGDFGCFDABHGBAGCGFABFEHF,True +276,5.0,1.0,0.0,3.0,1.0,2.0,0.0,3.0,BDDHFAHAAHAFEAD,True +277,24.0,23.0,18.0,24.0,16.0,33.0,19.0,28.0,ADCABCHCAHCAHEADEAHBGBCGFGFFGAFBDFGFBGDEGDGHHGHHACDDGFFAFFBFFEFADHDDADDFFAFGBFBBFHFCHBDADEAHECEDFDGFDFFDCBBHDAHBBHCEGEBHHBFFCCHHHHCHBBHDHAGCAGEDEHDGHDAFAFBBFABFAEAAGABGFEHCCBCHECFEDFGFE,False +278,12.0,29.0,23.0,26.0,19.0,18.0,23.0,13.0,BEBBEHBCAFAHEDDCDBBDBBDAFFAFCADCGGBGGCGHCFECEBDECGEHGEADBFDHFDGCDGCBCCHDBEABDCBDEBEEBDCGECBDHBEHEAGAFGHFHEFBBDBGEBFHGGHFGFDGCDGDDCFFFDFECCGCGGFBDBAACHEDBDDBGCAGBBC,False +279,16.0,11.0,17.0,16.0,19.0,22.0,19.0,14.0,GFAAFDCCEGCHGBEGDABFBDFEFEEBEBGFCGHHHFHAFDADEAHACBFCDFHFGCDACDFCGFEDFEGADGAFCEHCAHBBHEGCDDHDCAFCAFGEEGEEFBEFEHAHFDEFDBGDBGAFCAGCGGCGHE,False +280,10.0,14.0,13.0,11.0,22.0,14.0,17.0,12.0,EHCECEHBFGCGGCAHCDGCGGEDBBBFHCFBFBBFGHGHFABEAEGACGACBFDBCEECDEBFEBDGHDEBEGGECGEHGEDEEHFEHFEGFAADGADEHDAFDHFEEFCBA,False +281,32.0,31.0,18.0,18.0,36.0,28.0,25.0,12.0,GAHFABEGCGAEFADGADFABCADAEBAEFEHFGBGCBHDAHAABBBECFEAEEFEEFEDAEBAECADCDDBBBCBBEDBFAAFHEEGFCGEEGEFGEFAFDABCABDAFGFBGFEGBEACGGHFGAFHBBDEEEGGBHGFFAFFGEFGEBGDCHCHGBBGABEABEFEDADCEEFDCDHCDBGABAACAHCEFCEFBEB,False +282,19.0,24.0,17.0,28.0,20.0,14.0,18.0,11.0,CEGDBCDFGFGCADCEEGFABEDBDBBDEFDEADBGBEGBACDDFDHFBHGGCGAEGHEGHECDDGDFGEFABAEEHDFBDFBEEBHCDCCEHHDCGDBHDFDDADDEEDBBBBABHAHDABAAGADBCFBCBECDAGECGACGACFABFA,False +283,26.0,21.0,30.0,21.0,22.0,23.0,22.0,14.0,ABEAFHABHEFEEFBHDAHFBHFBAFBCBGGHGDHFDHFBEBBACCAECAECACGBCFFEFCEGGACBCDFAAHABGDEGDEGDACFEGDEGAFAACCBEABGAFDCFDFFGACHCEGCFGABCHGAHCDHCDCCDCGABDFBDEDCGFFBFEACCDCHDGGCGEEAEBAGDCDDCEEB,False +284,14.0,18.0,15.0,12.0,15.0,14.0,12.0,12.0,DHBFHFFADGAHCABFABEEFDEAGEAGDDBACBCCBGCBEEBEAHEHCFFCEFCBCGDCGDEGHGGABADBEEBEHCHHDBEGGFFEFDADHAHBBDFBCCBGABCFHCFA,False +285,16.0,15.0,17.0,12.0,11.0,20.0,18.0,11.0,HGHCBHCECFEHFEGDAFFGFEGFEAFGFBGABDBBGBACBGFBECAAFDAHHFGGAGGAEGCBDBBDHEFGGDGEHAHADEADEFCCFCFADDBCCBCABHAFFCFGCFDCFACDBCGH,False +286,11.0,13.0,7.0,7.0,10.0,17.0,12.0,13.0,FDGFDGFHABDDHFAHBHFFGCFHBGAGFFGFHHAGHEGHCGBCECDECDBHBEHBEHCAFGABAFBGFBEFGEABFBFDEFAEAHEABC,False +287,8.0,6.0,3.0,14.0,2.0,6.0,4.0,6.0,BGDFDCCDGAFBADBDHHDHCDHAAFAADBADBFDEFABDGHEGDDFHD,True +288,13.0,9.0,15.0,13.0,19.0,11.0,16.0,13.0,GGEDADGABGCBHAGACCFCHECDDCBAFEEHEBBEABEACFACEDHEAFEGFGDAEAAECDEFEHHEHBFFDCFDCDAGDHEBHCGHGGHCEFCGFEGEDGDCGHBGH,False +289,21.0,24.0,27.0,24.0,13.0,22.0,21.0,28.0,EBFBBCGBDHCAHFAHBBHBDHBDHADECDCAHCGHGFHADHDCHFBBAHBDHECABFBFFCDFGDFECBECBCHEAHFHHEHGGFAGBDCEHCFHCGGBEGFHBFGAFCADDFDDBDFCAFCHFDDACGACGDCGAGGHDEDECDAGHBFABABBEFBCCDEAHGAHGCCGCFAHDGHC,False +290,11.0,5.0,20.0,12.0,8.0,15.0,4.0,7.0,CBCCHDDHADEADEFDAACCCFFDFCAFCADCGDFEDCECCECFFHFFAGFCEDEBFFHCHGCDBHGCFDAFBAEHACCACB,True +291,20.0,16.0,14.0,23.0,25.0,13.0,17.0,18.0,GBEGBEGFEGFBFDBFDBADHAFBDFGDEGDGGECCECAEAADAACHHHHBHEGDADDBHAAAEHEBDEBGEAEHDGHAAHFABCEGDFGFCECDGDABDHBDECCABFBEEDEGFEHFEHGAHBDCDAEHAECDCFDCEDHGHEC,False +292,22.0,21.0,19.0,22.0,30.0,26.0,23.0,31.0,AHGAHGABADGFGGEEAEFDCABCFBCGBCBHCBCFEDFEDHADEFDFBHCBHAHEAHEHHEHEBGEAGEDCEHGACGDCFCEFDEBDEBDFHACEEHBDDGGEBCEBCGHFGEABFAEEBHABGAHGAHDHHDHEABEGBFAEGHEHCADFFDFGAFCDDGFHFFGFFDEBCHFEGFCDFHHCHFBEGHHADH,False +293,16.0,24.0,24.0,18.0,24.0,17.0,14.0,18.0,BDDACEACHABHABHECHGHEGEEFCHFAFAGFBBBGBEECEEHEFDBDDBDDGCGBCEHCEDCBFABFBBCCECCGBEBAABHECEGCEDDECFECFHCFHCGBCFFDDFADFAHHCGBBBCAFEBHGDGADGAHCBEAAFGDBHHEDCEDFEH,False +294,32.0,23.0,12.0,12.0,9.0,21.0,14.0,23.0,BCGBDHDCGGGDAFDFFBCABCABCFGGFAAFBHEBHGBGGDAFAACABHBFFDAFAHHBHHDHGDEADBHGBHBBHBBFACCBECAAAHABHAEAEDFGCCEAFFHEBHFHHEHDABAAGAGHADAAHAACEAHAAFFBFFBFFH,True +295,25.0,28.0,34.0,29.0,21.0,15.0,21.0,21.0,GBBDDFEAEADECDAGBCFBADECDBBDCCGCAGCDBCBBCBDCBGCEHCGACACFBHFDDBCHFCGAGGECFFABDEGDEFDHFHHBBHDAEDBEDCDDCDDCDAADFACEDHHGACGBBGAGAEGFGGHCACCDHGEHGEHGHCEACBHFEAAEACEACHHCHBCBECHHFEBBDCBFCBDDBDABAEFAHG,False +296,10.0,5.0,3.0,10.0,3.0,6.0,4.0,2.0,FCDBCACHBFABDAGEAGDADEBDFDAFGABAADEADHGDFFD,True +297,18.0,24.0,24.0,26.0,29.0,26.0,24.0,26.0,HAEHBEAEEHCACDDCFDHFGCBHCBCDHFDEADBBGCBGABFAFGGHGEAGDBCCGCBDFDDFBEFBEGDEGAADHADHBHADHCDFEFFEGGEBAHBCFGCEGEBGBFGEAAEDHFDAAGHFGEEGEEDHECGEDFEBBDCCDBDECFCBBEFHFCGFEHHEHHAGHCEHCDFCDFCDHCHGGHFEFFBFHBADB,False +298,13.0,9.0,11.0,21.0,12.0,21.0,9.0,8.0,DDADBAGGAGEAGECGEFHFCCFBCABCABHAEFABFDFCHHDDEDDHADHCHABFFFEAEDCFDEGGFDDFCDFEFFEDFEBADFDDFBDFCHBGFCEDDAFG,False +299,9.0,10.0,7.0,5.0,4.0,5.0,9.0,5.0,AEBFBGFGGAGGADCADGDHGHEBHBBGEBGFCHBCHAAFAABCECCFDDBCAB,False +300,9.0,10.0,14.0,12.0,10.0,5.0,22.0,10.0,GBDGFGGEGEHGDGGEGCCGACBDBBDABDAEFABBCEAEHAGCFHDGHGGDGADGHGGBFCDHCDGCGBDAACEHCEGCEGDHCHECHCBF,False +301,23.0,15.0,14.0,8.0,21.0,17.0,19.0,20.0,FGCEGAEGEDHEDBGGECFFHEBBBFDAHHEBAEBHCHEGAAHABEEFEEFGBHGCHCAHDAFGGHGDHGFAGBABFAFHEEGEAAEDAGFAEFACFACBHFDCEHBAHCAHGAHCCGCCGEAGEACFADFHBBHBF,False +302,27.0,23.0,30.0,20.0,17.0,18.0,24.0,20.0,AACCCBGDBFHBAECFFHBHHGHAACGCHDDBFBGGCHGAFGAGGAGGAHGCHGCDGCHBHABFDBDDEEDEEDBCFCCFCHBHFBAFBDFHFBAAAFCCGHCDBADAFCABEACGBFBEEBAEHAEGAHGACBBDACDFCDGCDGHDEEDEBCFFCAACHECGCBGCEGCDAAEEHGD,False +303,30.0,27.0,22.0,22.0,20.0,20.0,25.0,21.0,FCHFDBBDBGCAADEBGFBGABGFEGHAHBADAEDACBECFFCFFGDBGAHHAEHFCAFAACEDCFFBEFAEABHDGAEHDDBGCBGEBGEAEEFBEBDHDAAACCHCCHGDAGDFCFABFHBFHBGBBDHBDHEEHECHDCADAEDGBCCBAGEHGEBGFBGCCACCAGAADAHGHHGFDABGGGD,False +304,29.0,17.0,17.0,22.0,14.0,23.0,28.0,17.0,DABGFCFHAEGAFGFBCCBEDDHFCADEHDEHGHDGADGHGGCCFFFFCCEGHEGBDDDDDFDFGDFGCEABADBCHADBGDCDAHFFBGFGGHAGHAGAEGEGCAAHAAGAAEBAGBGFBHBBHBGDCGFCDFBAEBHCFEAAEAAHGAHGAGFACFDCFEAFDAB,False +305,11.0,12.0,13.0,10.0,10.0,17.0,17.0,13.0,BFDDADEGGFGEFBEAGHAGBACAECAFFBBFHBCHGFHGHGFFGCFCBBAGCDGDDGCGHCBHDGGFHFFHGDECDFCDEAGFAFBAECAECHBHHEHCEBF,False +306,7.0,10.0,4.0,3.0,5.0,2.0,7.0,5.0,BHBHADABBABGABHDGHDBCEFEEFCEBCEHGGCGBAABGAG,True +307,17.0,17.0,13.0,19.0,19.0,19.0,22.0,12.0,FDEAAHFFBFBGFBDFGDFGDBGDBGFBFFHFFABEGGGHAAHEAFEDFCBFCEDCDAGBAFBGHDHCGHGDEGDGCBBDHGABCDHCFHEGGDBCHECEECEADEAEGAGBAEEDDEGCEGCHACBAFBDEDAFGAE,False +308,16.0,19.0,32.0,19.0,25.0,21.0,28.0,24.0,BCGCCBFCFGGDHGDADAACACGGBADDGDDGFBCHHCFECDGGAEBAEGHCDBCHEEHAEHFEFFEGFEHDCCCEGHFHHGBGDEGFHCFBFHBGEGFCGFCBHGBHEBEEBGBAGEEGHEAHEBFEBHCBGGDGDCHCCACCADBAHEDFGCACCHHCHHFBAFAEEDCECCDFCDFCDFEG,False +309,12.0,7.0,7.0,14.0,8.0,9.0,9.0,23.0,HFHHBHGACFAHHHHHDHBGHCEHEHCFHCBHDAHDAHFGDDHEBGFDDHADHBDGEEGDACDAHDAHCGHAADAECBEGEFFAFBDFG,False +310,7.0,9.0,2.0,2.0,5.0,3.0,5.0,9.0,BBABAGEAHBGHFEHBEHBHHAHBEGBGGBDACFCHFDHAAE,True +311,26.0,28.0,24.0,21.0,11.0,21.0,26.0,17.0,BFBEHBHGFHFHDDGADGADGFDCFBCHGFAEAAEAAEAABDDGHDBEDCCGFCFFCBBGGBFHCGGGDBGDBDEBCFBCABGDBGDFGEGCCAAHBGHGGFFBAHBAEGCFBCECHFADGGCECCFCBACBGBBGCCDAEHABFADDADDAFBHFCHAAFAABHHCHBCDBGA,False +312,23.0,13.0,12.0,13.0,21.0,13.0,8.0,13.0,FBAFBAECDHHEEEEAACADHEDAEAEFAEFAEGAEGAEAAEAGGBCDDFHAHHFFHFCCACAEFAHFAECHEAEDDHDGBBCBDFEHEAHBAHBAGCCDDDFGEGEFBBDBBCCB,False +313,3.0,1.0,2.0,0.0,2.0,1.0,1.0,1.0,HACAACEFGEB,True +314,19.0,17.0,14.0,10.0,16.0,21.0,10.0,13.0,AHDAHEEFAEAGCADFEHCEBCGCCGADDADFADFAHAAHFEHFEHFEFFCBFEBAAHEHBEBCCGHEBHCBFCFFGEAHEACBABBABFFGFFGBBBFBGDGCCBEDADAFBFFCHEDG,False +315,3.0,8.0,4.0,7.0,12.0,10.0,4.0,14.0,DHEDBEDBECHEFFFCHDAEBAHHFHFEGFECEEDEGHBGFBAHBHEBEDCFHHFHFDHGBH,True +316,19.0,13.0,26.0,20.0,13.0,13.0,16.0,14.0,AFCBGBFCAFCEECHBBAGCDGCFGHEBHEDCCAHCFEAEDDEDAGCAFCACCADCGDEBFAGDHGDCBACHAGHBFHCGECDCAGCADADFGDCGDGEDFADCADFFDAEDHCCHCBHGBHEBFGBCABHHDE,False +317,16.0,18.0,21.0,25.0,22.0,16.0,21.0,17.0,GDDGDDEDFEGFEDEEDHBDHBCHDHBBBBBBCCBCCHFCHBCHEHADGCDGCBGAFABCEDFFAEBCHBDDEADCGDEFAEGAGCCDCCGFDFBDHCGHGAAFEADAAHEBHEAHFCCDCEAHEAFGBGEBGDGEFGFHGEHFAFDGEDGECEDG,False +318,23.0,22.0,20.0,24.0,12.0,20.0,16.0,25.0,AABCHBFHCDHCGFGHDHHFGAGHBGHBGCEECAEHGBCGDDDHCFHGBHGBHEBHDCCAHCAHAHCAFCDFHHEBDDBGDGEABBAEBCDDFDDFEDFACFABFCHHCHHGBFAEFBCGBDHFDBFDFDAADAFDCEHCBBDFAAAAGECDABDAEFABFG,False +319,9.0,5.0,11.0,3.0,6.0,3.0,10.0,12.0,HABHDEGCCCDFCBHCHHGHAGHCGHCDHCEGCGCEGHEAHFABAECGBBAAFGAEHAG,True +320,31.0,18.0,28.0,29.0,18.0,25.0,23.0,22.0,ADEFDADBAGBEGHEGDCAHAAHCFGCHGFEGFHGCGBFDAFDCFCEBABHDBAFAFFDGDAAHABGGCAFCACCDEBDCCGCCDCCAFGGCHBDHGCHAHBBBBBCCGAADCBDEFDHCAHCHHFHAECDCHDGHDEADEDFADBADEEDGCBGCBGDGEFHAFEAFAAFGEEDCFDHFAHFAFFAEFHEDGD,False +321,11.0,11.0,8.0,16.0,26.0,18.0,18.0,26.0,HFGEAHHHHDBHGEHDFAGGDEFDEFDEFAEFBDFHDEEDEEBGEHEHHEHACGGEBHEGHEFHEHAEGFDGDDGBCEAEGAECDHCGHFEHGAGFCHHEHHFGDFEFFHBFABHDGFFBCEBAECGDABDHBC,False +322,6.0,3.0,4.0,2.0,1.0,1.0,3.0,2.0,CAAFAEHAGBDHCDBCGBAGCA,True +323,10.0,11.0,20.0,18.0,16.0,14.0,16.0,14.0,FCGBEHDGCCHABGBCGACFEFEEFEDCCCBGCFHCDAGDAGDEDFHGBAGEDFECGACGEFGEFEHCDHCDEFHGBHGEFDEFDEADBAEHFCBGCHDCHDCBDCFHBDABGAHDHCD,False +324,14.0,16.0,12.0,17.0,15.0,23.0,16.0,14.0,HDEBDGFAFHDDHDHECHEBHGHEGEGFADHGEFGDFBCEBGAFFAGFHBDHGDCGDCACFECFEHFAFBCEHCFBEFCEADHABCBBCFBAFAGFAEEAGBBECBDGBFGHGBFDDFDDFGAFDAF,False +325,15.0,13.0,7.0,9.0,15.0,10.0,11.0,11.0,BDABDCBEEECAECHCFHBBHDHEAHEAGEDEABEDHEGGFGGFEFBEHEEFBHAAAAAADAADFAEFGHHDFHGAGBBBBCDCGBFGFCG,False +326,18.0,22.0,21.0,20.0,18.0,16.0,22.0,11.0,FAHEBHABFAHGAEGHHBBBCBGCBECAAGDACFBCFEHGDHDDCDDFFCEGHEBHCFCDFCDGCHBAGCEBCBDGBDCBDHGEFADGEFABFGCFCDBCGACGABFACDEDEBDAFAFFABGEBGEGEEDEGDAGAGGEBGCBDCED,False +327,13.0,17.0,20.0,5.0,21.0,19.0,14.0,10.0,CACCAECGEGAFABCCDFAFFHFCEFCHAHBGEECEECGEFDECDECEEABFBEAEEBEDHCAHAADBABFGFFGFGGFBGBHEBHGFGEFBBGCBCCBCBECBCGFEHFHBGHACEFF,False +328,21.0,20.0,17.0,13.0,23.0,15.0,20.0,19.0,HECGCCHADAADGADBEGBEABEHFGFGGFGCBECFHBAAEAHDFHFFBGEBGCBFHAABAABDCBDCAFAAHCGDCGEEGHGDEGCHGHBFHDHCDBCFEAGCAHCEHEEFEFBDHHDEBEEDEBGGAHGAHBEFBECEFABGABEC,False +329,24.0,23.0,29.0,30.0,30.0,21.0,23.0,19.0,HADHFBHFEHCEHDHCDFCBABEEBDEHDACBGDBCDBGDBADCCDABAGCEGBDGBEGCDFAFFGEFGAGEAGEADCGHGBDEDAADEHBAHCAEGBGFBFHBGEBDBBAEEDEEFAEDGCABCEDGFFGECCDACHBDGBDFCHECHECEACEADDDEDFADFAFHCFGCADCEECFCCFCCAEBGGHHCHFDHFEG,False +330,7.0,6.0,9.0,9.0,7.0,8.0,16.0,10.0,HGGAAGEEFBEDHFDAFBAEDFGHFAHGDHEECGHCGCCACGFGHFAHEBHCGGCBGDHGDCGDCGBGDBDF,False +331,15.0,22.0,24.0,18.0,22.0,22.0,16.0,24.0,ABAFBECDEDAHCCGCAAHHCHHGBBGBAGBDGEDEHAECACBBFHHEHHEHHFHDCHDCBGFHFFHAEBFEFGDHAECEECBEFEGCCFBCGBCDEGHBGHFAHFGDBGEAGFADCBCCHCFFDEFEEFBEFHEHDCDDBHDBGFAFFBCCBCFBDADCGDE,False +332,9.0,18.0,16.0,12.0,7.0,14.0,10.0,14.0,AADCABGADACDAEDCHGCBFHBFHBEHGEFGHGECFBCDDGDAECHBCEBCFBCHHFDHDHHFFDFBGFGHBGECCFDFHDBHGBCFFABBACBCBBCB,False +333,24.0,10.0,12.0,14.0,8.0,11.0,24.0,18.0,AHAAHAADADGFHEEGBECBDCEACAHEGHEFHADAADFHGBHGBGBCGAGADGADGAHCAHFHFGEGGBACDCCDGFGBHCFGAFGBGEHACHAGGCDDHDAADGHDGFCGAHBAHBGFF,False +334,17.0,19.0,16.0,21.0,12.0,28.0,7.0,21.0,BCEAFGACAHCFEBBDBBDFFDBCDBFDFFDHFABDGBDFFGFDHFCGFGHCBHAFCEFHHBHHAHFADFBFCBFCBDCHEHDCADFDDEHDECDFCAFAAHABFBDFHFCDGHDHHCHECBEAEHAEFABDEFAFBGHEA,False +335,5.0,1.0,17.0,8.0,5.0,13.0,6.0,9.0,HFEEFACCHDCHDCHFBHDDCACCFCCGCFFDEFAFGCFHAEGFEGFDCCAFCHCGDCGDCHFH,True +336,7.0,5.0,7.0,10.0,4.0,6.0,4.0,9.0,CABCEBDDFADCAFCFGCEGEHDDBFGBFHCHHGHHDFDEHDAACAADHBDH,False +337,17.0,14.0,20.0,15.0,14.0,12.0,26.0,25.0,FEFFADAGDAGFCHHBHHBAFEECECAFCDFDDGGCHGCHFCGDGGBBGDAHDHECHGCBBBHDEHCCHFGHFCHBCHDAHCAGCAGEBHEBAAACEECEGGDHCEBFEHGHCGHCGDABAGHGGBBGFGGDGHHEHDDAAGA,False +338,17.0,17.0,8.0,23.0,13.0,10.0,15.0,13.0,DFFDBGEBEBCDBFDBAEEAFGAHDDDBBDEBGEBGBAGBGBCGEDEAHHADHDDHEDHGGHADDBDHHDCHDAGAECADCHDFBBFABDAFCAGDFFCAEGAEGEFGBDGCHAHA,False +339,18.0,24.0,23.0,25.0,16.0,22.0,30.0,24.0,DGBDGDDCDGCBGFEHEAAFCACGBFEBGCGCABCAFAGEAGEAHDCHBFEGHEBDDBDDBGABGFDGFBHCAEEAGDHEHFEFEHFGHFBFFGCAGCACCDHDDHBDFGDFGEEGBFDHHBCHDFFDCCABGBDGECBEGGGHDCHACHBHHGGHBGABDABHFCHFHHDBABGFCGFCDC,False +340,2.0,2.0,13.0,7.0,3.0,3.0,2.0,4.0,ECCCDCCACCBDCDFCDGAHHFEDFBDCDCCHGCHE,True +341,4.0,3.0,4.0,1.0,4.0,2.0,6.0,4.0,GAEGBCHBCFGAHGAHBACEECEGHGDF,False +342,10.0,14.0,13.0,18.0,10.0,15.0,4.0,7.0,BFBBADBAGACCABFAECCFCCEDEHDABBAFGGBDBCEBFDBFDEHDGHFAEECCDCCFHBFDEDDFDDCDDEHDEFFBDFBDFACHAFH,False +343,2.0,3.0,3.0,5.0,8.0,5.0,2.0,1.0,EAFDCDDCHEBFEFDEFEABECBFGEDGE,True +344,16.0,17.0,10.0,12.0,19.0,14.0,18.0,24.0,DGDFEBGECFCBBGFFEFHEHBEHGCBACBEGFGGHCBHGBHAEFBFFBHHBEHAGAADFAGFAHFAHGACGAEHABFGEGHEHHEHCABDAHEABCDHGEHGAHDDHDDBEFBGDBADGCHECHDHEEE,False +345,12.0,6.0,8.0,11.0,11.0,7.0,6.0,8.0,EEABBCDDGADCAECADHABGABECBECFEFFECDEGHAFHDGHFHAFAABDAHCEHAEHFDCDEGDGD,False +346,14.0,12.0,14.0,18.0,13.0,23.0,16.0,8.0,ECHBFBAFEFGCCDDGFDBFEGFEAFECFEHFEGBDDCHDHAAGAAGFBDBGDADDHGDCFFHEEHCEBGDGCFECFEBFDACDFGDAGDGGCGBABDCBCBAFFAFFAFEAFDHFCG,False +347,13.0,9.0,9.0,6.0,6.0,16.0,14.0,5.0,GEACFCDFGAFGAFCFFDDGGDBGDEGBAAHGAHFFBFFEEFBFFBFCEGBGGCECCAAHAGHAFAAHACGGFBCBBD,False +348,2.0,2.0,2.0,3.0,4.0,6.0,4.0,5.0,EFGDDADHEFBAFECFECFHBFGGHHGH,True +349,25.0,25.0,26.0,14.0,12.0,22.0,23.0,17.0,GCCGCCGEEDFADFDCCEHCBHCBGBBCBFGBAGFGHBGABFAGFBFFACCHHFHABAABCABGHEGBCGBFFAFGACCDDCBFGFAAAAAEACEFCEFCADCAGHAFABFDGADHHGBBCHGEBGCBHCBFDHGHHCEHBBBBEFAFHDDGFDCAGCAGDEDE,False +350,26.0,15.0,7.0,12.0,18.0,16.0,17.0,8.0,GFECAAAAAHFADABEGCECDGDAGEABEGBGBBGBBGCHEFFDFFAAAGEAFBAGDHHFGGAGEADFAEEBEFCGFDDFGDFDBFBEHHAHEAGEABEABEBBADAADAFFCEGCHAE,False +351,19.0,24.0,27.0,20.0,25.0,23.0,28.0,19.0,HHCHFCDGDBGDFGCBGDFGBFEDFBGABHABCABGBGAHGBHGBABCCEEBDFGDHGDBGHFGCFGCBHFBHECGCCBCGBFGACGDCHEEDFBGABFAFFGHDAEAAHDAFDEFDEDEECFEGHECAGCECCFCBABFADCAEGEDDFHFECFEGABGAHDHECBACDGHEEEEHECBECGFC,False +352,11.0,14.0,21.0,19.0,18.0,15.0,12.0,19.0,CGFBDFCAEDFEHEHCEACEAEEFGDAGBACBFCBFABDDGHDEHFGADGHDHCBHCEHCDHBBEFGFBADCGBHEADECDCBDCBACBACBDCHFHHCHFDGCDECGHCEEGHEHFFFFGEHDCHDED,False +353,14.0,12.0,11.0,22.0,22.0,10.0,7.0,14.0,BDEBEHDFDDCDEADEHCFHCAACAABBCDBHHEDHEFBAFDACABGEEDEADFADFBGFAGCGHCFEAEDGDDFDEEBEEBEHHEHHEDEEBHHCADCACHDDGGBFEDDE,False +354,25.0,23.0,25.0,17.0,15.0,24.0,9.0,25.0,FHABBAFCCFBCFBEDDHCHGBAEHCEBDAADFADFHFHHFHBFBCHBHHEHDACDFFAGBGDEGHHGDDCCCAHCEECAEDECFBBHDFCEFBAHAAHAFHAFHBFAAFAGGACEAEDAFDHEGFCFFCDFHGFHACHABBABECCCCACCBBCDBEBBHDB,False +355,17.0,20.0,28.0,20.0,27.0,26.0,18.0,20.0,FCDHEAHEGECAEDAEFCHFEFCCCCBECHEHEDHDHHEGHEDFEHAEDGEDGEFEECECHGCDGCBEDDEDDFDDBGGCGBHHAACABGGBCGBCGDCFHCFBCFBHFAHFEFFCFFBDACFCHBHEEFBGFBHFDGGCECAAFACFBBBABBDBEHCAFFEGCADEADFFBCGA,False +356,11.0,9.0,19.0,9.0,17.0,23.0,24.0,22.0,DCFDCHHGFEAECFFCFFGEFGFFGAHGBHAADAACEFFGGEHCAHCBDFFDGGHHBFHBHHAHFFGGFEGFCGFCHCGGGGEEEFCDHCDECHECEBCFGCHBCHAEHCEGFDGCHBEHBGHBGHFAEAEGGD,False +357,15.0,19.0,23.0,15.0,30.0,8.0,15.0,12.0,EDGEGBEGAEFADGHEFEEDEDDEGGFDAEEAGDAEEADEAEBBCFBCGECBEGGACEFBGDHECHEAHEHGGABCEDDFDDEDBHDBCBACACCGCABEGHCHCCBCCAFCHBEHEHHCCBCEBCEBCEBFBBECA,False +358,8.0,10.0,3.0,16.0,6.0,11.0,10.0,8.0,EADHDFFDBFEGFGCCAFCBHDGEDHDDFBBFEBHHDAHDHEDHGDAGDAEDGDGFBGABGFDGFABBADBF,False +359,20.0,14.0,12.0,8.0,11.0,4.0,10.0,13.0,BAHGAEDBEDCADCAHBABAAFAACGBHGBHABHEHCCHBCGAEACGDCADCHGAECADFAEBDEHFCHEAADHAGHFBEBCEAGEBGBGHB,False +360,26.0,15.0,17.0,18.0,13.0,10.0,21.0,9.0,HCBGGBGGBCCDDCDCCHCHHEGGEAFEDFAGEBDHBGAFGDGAABCADCEGCFGAEABEADHABGAEGFEAFAFCACGADDBEAGAABAHGDCDEADECDBCDBCBHCFDDFAGAEGAHGAGAAFBDB,False +361,15.0,32.0,16.0,34.0,25.0,18.0,29.0,23.0,HDFHFFDABBBBEEBGEBGEDEEGAHGBGBBHDAEGCDACHECHBGDBGDBGDGDDFBGGDEBFAHHHHEHHAHDADDEDBEBBHABHAFGDDBEDHEDHDDHGCHCEFDGGDGGBCFCCFEHFGGFHAEDFDFFCAEGABDFEDGBAGBGDBCFBCHEDADDCDCBBBDEBDEBGHCGBEABFCGGEFCEG,False +362,22.0,28.0,20.0,25.0,21.0,16.0,11.0,16.0,BHCHFBFFBDDBHHBAHBADBAHBAHGCCFCBBDBBECAEFEDHHBCCFDCBBBEBHEBFGBHGDHCFFCFAHHAGAGDBFDGFDBCGEADBFBBAAFEDGEDFDAAGBAGAABEDDACBECBEFDAHCCCCGCEEHAEADEDDEDCEACEAEDDEDDE,False +363,11.0,11.0,7.0,6.0,9.0,8.0,12.0,8.0,FBADHHEHFGGCGAFEAFEGFGGHGHCCHCCBCABAEBAHDDCGFABEABFABABDEBDBHAGGFBGEEGDE,False +364,5.0,2.0,8.0,2.0,1.0,2.0,9.0,6.0,AHGACBAGHCGHGBEFDAFGACHCCGCDGCHGHGC,True +365,33.0,17.0,16.0,24.0,25.0,19.0,21.0,11.0,GDDGDDGBDBAABAFECGEDGEDFAGCACCFHCGHCDAADBACFCHEDAEHABGGHCEEEBAEFEDFDCFDHFDAFAGFBCDAFGEDDEHBEDBDCBHCAGFHFDACAGDABEABGABGAHCAGDAFFGEFDEFGFGEEEAEAAEAAEAEFBBAHBABCEGEDGAA,False +366,24.0,28.0,22.0,9.0,23.0,15.0,15.0,17.0,HEGHECCBBCBBFAEDHBFCBFBBFABGEGCFDCHCCBAAHAADABBBBAECHECEEHEEBAECDDAGDFGDFCDCGBCEBCABEABAAEHGCHEFHEDHFGGAGEHGCBBAFBAHCFEEGAEGABAABAHFHBCCCEHAEBBEGCGFFBHFA,False +367,22.0,19.0,28.0,25.0,31.0,21.0,23.0,26.0,HGHDGHDGEBCDDCAEEADEDEEHAHBDCEEBEFGAHAADGDHBHFCEGEDBFDEFEEBEBCEFCEFCBACBADHADEGDAHCCEDDEDHFAHECDDCBEFBEGBDCHCHAABAACCHCCHCDHAGCAGEBEEAFECHBCHGCGGHFCFAGGEDAFDCBECBEHDEFFGFDGFHGFGGFGFFBFHBCCGAGHAHH,False +368,19.0,23.0,22.0,14.0,18.0,18.0,13.0,20.0,GAHHDGFBGDBFFBHGADABEHCCFDCBDAGDBFBBFBBFBFFEFFAHCAFGAHADHEBFBAFBECCEBCDDAEDGEHBBBBACBAEBDECHEGFCHACFDBGCHHCHGEHCCHCGHCGECEAGACHFCHFCHDEEEEEBDACAAHA,False +369,8.0,9.0,10.0,4.0,11.0,7.0,17.0,8.0,GEHGEBGFGGFCGEHAFBBFCBHCFDCGEHAEGCCGAEGBBCHBHFEAFGBCGADGADEADCGCHGEBAEGHEG,False +370,14.0,14.0,22.0,16.0,19.0,13.0,17.0,12.0,AEAAGFACECCFHBFDEGEAGADCEHCECCADHDEGFGGCCGBHGBHGBAFDGECGECGHBDHBABFACDDEBFECFEFFCAFGEGEEGHGCBACBCBDABCGBDFEDEDDHDFBDHCCHCCHEADE,False +371,24.0,19.0,21.0,13.0,20.0,18.0,17.0,23.0,GEGEADCDGEHBDCBDHAHCEFCEFEEFCDFBEGAGFHGFCCHCCFFCFFAADAFCABBBHGCHDHEAAGCAGDABHHCHHCHGBEFAAFHAFHGHHGDADEABEGBCGCDBADEHHEHACDABGECFEFEEABEBBHBBABCAGCFGEFABHAH,False +372,3.0,3.0,3.0,4.0,0.0,2.0,1.0,2.0,DDFDDBCABHABACFGCH,True +373,11.0,27.0,14.0,16.0,27.0,12.0,14.0,25.0,BGEGGBDBADECHGHHEHADHDGAEAHEFHBFHEEDGEDECBHFEHEBHDDCEABEAHEAHEBEEBEGAHCHHCBBBBBBBCCGDFGEBBEFHFDHFDHFDEFDEDEHGEAEEFBBHBBADBCBCCBGFDGHEFABBGHCCCGCHH,False +374,3.0,9.0,10.0,10.0,8.0,7.0,11.0,11.0,GCGGBBHHCCGFDGFDHDDHFDBFEGEEBECDDAECCBBCHGCHGFHADHACBEFHEBHDBHDGGFGEC,False +375,23.0,33.0,18.0,22.0,30.0,18.0,26.0,23.0,EBDEBDHHGCCGCFGADGBCGHCEHFEHDEHBEGDDGBHGAHDAHDBCBAABCFBCHEFDADCAEBBBBHBAFBAEBAHBHFBCAGCFHDADEAFECEECEFBBGGCCGEHHBBHEDCAFAHEEFFEAGABGCDGBBGBDFBDFGDBEDBHFBGDDGAEBAGAFGEEBEECEABEHGGADGDGFHGFEAEHHE,False +376,26.0,12.0,16.0,23.0,9.0,18.0,21.0,30.0,ADDFFDFFDFFHCFCBFAGFBGHEDHEAHECHCABFAEAAGAAGDDDDCFGCAHABDEGFHBCBCADGHDGADGHEGHDGHFBHGDHCDEABHGEHBDADAACHHHHFHAGHEGHDGHDHHCCCAHDHHGGFAAAAFABFHCFGBHGAACBGCDD,False +377,14.0,10.0,11.0,6.0,8.0,8.0,6.0,11.0,FCEFBBABDCHECFBCGBHGFHECGCFAFAEFDBACADCABCHHEAHGAEBAHAAHAAGFDCBDCBDGAEHHEH,False +378,10.0,13.0,11.0,8.0,10.0,9.0,5.0,12.0,ADCHBEECEEADBACBGBBAHBGHCCHGBHCCACCFHCDBDDFFDFFBFEAEHABHDBDAFHECBAHEGHEGHEFBAF,False +379,26.0,14.0,13.0,28.0,14.0,24.0,18.0,23.0,ACEAFGAGABGAGGEHAFHDCDDFFCGHCDHAAAEFFEGABGAHHADFGDFBCAGCAGBACDDDBDDEADCCHGEAGEABHHFHCCBDABHFEEDGHBGBBHFDFCDFBDADDEDDEDHFDHFDHEDHAAFAHDGDBGEFFABAECAHHFFHFFHDFHFG,False +380,21.0,15.0,24.0,10.0,21.0,16.0,24.0,20.0,GBFFDHFBFGEFHHHHHECHEDEEBCAFAABGACGBCAECBCCBEDFCDGCEEEAEGAGGACDAFDCGBBGBBCAFFDFHBAGGDGGCCHEAFEAFCAFCAHCGGAHCACCAEGHEHEEGEEGDCHDHHGCEGAFHHEHACBCFGHBGBAG,False +381,15.0,21.0,27.0,23.0,28.0,27.0,27.0,20.0,BCBHCAFBBGEBDEDHCDGCGGCGDCFECDECEBCEBFEBFGCGGBGABFAEHCFDCHEGEFFFBGFECCEHCGFFGFHGBECCFCFAEDAGAHDAGEFFFAFDACCHCHBBHFCDAGDHGDEGDBDEHDHHFHFBHDBFDEAGCADBDDBDDEEFEEAGEGGBCGEFEEFDGHHCHFEHCAGGABCE,False +382,0.0,4.0,3.0,2.0,1.0,1.0,2.0,3.0,BCDBHDBHFEHGGCBC,True +383,1.0,2.0,2.0,6.0,6.0,2.0,4.0,2.0,CHDAEDGEDCEGEBGEFDEDGHDFB,True +384,12.0,14.0,12.0,10.0,21.0,16.0,19.0,20.0,GDHEBFGHDHCEABECBDCAHGAEGCEBCEHDEAEBHEBHFHHBBFFAFDCGHAGDCBFHGHCADBAHBGHBGADHFCHFDHCHECEECEGFEGEAGEGGEBFEGAEBAFFFEGFGGDGHFEHF,False +385,9.0,9.0,5.0,9.0,10.0,4.0,7.0,7.0,BCCBABGHBGDEGDACDBEFBHDGADGAEHHCFCEFDEBDBBDAAEEAEHADAGEHGFHE,False +386,15.0,9.0,11.0,11.0,15.0,15.0,12.0,13.0,EGCFFCFGCFHFDHCHCCHACHECAGHFFABEAHEFHEDDEBDHBDHBECDEADGFGFBGFAGFAFAHEEEBDCDGEHGAGGABAAGDFDBEABEHECFAA,False +387,17.0,16.0,9.0,11.0,9.0,4.0,15.0,11.0,DADCFEBAEAGCBBHBEGBDABFBDFDHCAFEGGEAGEACHABHAGHDGHBHHBGDEGHCAAGDAHACEGBBGABAACGACGBDGBDHBDCE,False +388,10.0,3.0,8.0,5.0,5.0,8.0,6.0,3.0,BDDGGCAECAFGAFCACADCEGCAHCADCBFFAFFHHFADEGFEGBEA,False +389,17.0,13.0,28.0,32.0,15.0,31.0,24.0,29.0,HGHCCHGBFDBGAAAAEDAFHHDEGFECFHGFCFFEHFDHGDCCFCHFCFDCFDGEHBEHGHHAACAEDAHDACGEGFEBHDHCFHEFHGFAGFACDACBHCDHCDCCDEFDEFDHFECDHDDCGDGBBCCFDHBDFBDFCGBBHAEHCDGGFHGHAGFBDBDCGFCGFDGDDFDHGHAFFAGDCEDCF,False +390,23.0,24.0,19.0,26.0,25.0,15.0,25.0,27.0,FADECFEGAEGHCFDCBGCBDDHDDHDDAGAHHAEBAGDAHBHGBFGBGGFGDCADCBHBEHDEAEHGEHDBHGBHEBDGBHECAEDADDAEHFFHFHGGCCHHEFECCGDEACEHHAHGAFAADBBDCBGABDACCADABFABEHFEBEEBDDACDEEDGGGGBHGBHCFGCFHFBHCBEGEE,False +391,4.0,5.0,5.0,5.0,10.0,9.0,7.0,10.0,FGGFGCEGEEHHDHGDCEDAHBFHFGDFEBHBHHAHFCCFACFGBFEEHEEDEAB,False +392,2.0,1.0,3.0,2.0,5.0,3.0,4.0,3.0,FBGCCGDCAHEFHFDHAGEEGEE,False +393,32.0,34.0,23.0,23.0,23.0,22.0,17.0,26.0,AABCCBCADCAHAAEFAFBABBHCCFBFGDHDHCAHFGBBCCBHCBHBFCDFBHBEABEAGEDGECBEBHEBAEFHEBEBDHAHHBGCCFDDFDFBDHBGAAACEACDACHADFAGFAGFHGFDFADFAHEAEEBEAGDDHCDEFDBHCGGDGDAHABHEBHEBEEBEHFABAHBGEBHCFDGFGFEDADCACHACBGBB,False +394,10.0,5.0,5.0,10.0,12.0,9.0,5.0,11.0,DCDEADHACFADFADABDHGHHDAHGAGEEBEFFCFAEDAGBAEBCEHDBHFFCEFHEHHEGEEDHF,False +395,9.0,8.0,7.0,6.0,6.0,3.0,2.0,9.0,BAGBECDECDCHEAHAFGBFHBAHDHHAACAACHHFHBDDBEEAEDBCCB,False +396,28.0,25.0,16.0,17.0,19.0,17.0,23.0,14.0,FBGFAAAHBHHGFCGDGGBGGEGGEFCEHCDGBBHEACEGBEADCADGEGHDGAAAAABFABFADFCCBHCADEFGEDDBDACAABAAHHHFACFBDAADBAGBGEHDEDBBFBBFBBCEAGEBHEBHEBEFBCFECFEGDGBAGDACDHCFCFGAGAE,False +397,11.0,7.0,11.0,10.0,5.0,9.0,10.0,7.0,BCHBAHFDBFCHFCDDBHGAGCHGCGGCGGFGEAEECDDFADEBFCHDCHBGABGEFDCFDFAAADAACA,False +398,21.0,30.0,21.0,28.0,27.0,13.0,18.0,24.0,CBDCAGAAEHGBHBHHFHHAHHCGHDBDABFBEHDEBCEDFDCFDCFBCEDCBAEBEDBEBBABEDGFBGFEEAEBGHBGCBACBDCEECBDCDDCAAGDGEAGEAFEGEEBEHFDHDGCEBFEBDGDFHAFHFDHECHGCDGHEGDBDBHEBHGBDAAAAEADDDCABHDCHCEHCHGBBA,False +399,8.0,12.0,5.0,5.0,7.0,5.0,5.0,13.0,HHGHBAEGABBCBBCBBCFBCBHADAAFBAEBEBFHDECEEFHGAHGHHDFHDGHAHHED,False +400,7.0,6.0,11.0,5.0,6.0,14.0,10.0,3.0,AEFAEBCFDCFCFAEFCGGCGECHFGADCBDFGCHCCABCAGGEFHEFGAFBFBGFDGFDBF,True +401,5.0,2.0,3.0,1.0,8.0,3.0,7.0,1.0,BAGCFGEEAEBHEGFAGFDGEEGECAEGAC,True +402,7.0,14.0,22.0,10.0,18.0,10.0,12.0,15.0,GHECCAABBCBBEEBEGBDCEECFGGHCHACHAHFBGGCCCCHCEFCFDCHDCHDFHECHACDBCBAEBDEBDGGEGHDCEGHECEECEEHBEHDFBFBAFHDFGFCG,False +403,14.0,14.0,19.0,22.0,20.0,22.0,14.0,19.0,ECCEDFDGEDEEBCBHDAFBAFAAECCFDCEBBEBDAHCADCFDHEBFEDFEFEGFEAFHAFHGCHEEHDDFEDFDCFDCFCBAHFAHFHHFBDFDDEHCGGBGHBAHCAGCEGAHBHCGCEDEFDFGDHGFCGBBGCHGHDDA,False +404,9.0,11.0,17.0,12.0,11.0,7.0,12.0,10.0,BCBDCEGCECEGCDCCDGGAHGEBGBHCFCAFHAFHADEAHFDHEBCCDCCDCBDHEDHADBAHCHDDGBEGFGGBECFEFEGBAGCAB,False +405,5.0,5.0,3.0,4.0,12.0,4.0,3.0,6.0,DBGAEGEEDAEHAEBBEBEEHFDCBEFGEFCAFCEHHAHEDH,False +406,15.0,17.0,23.0,27.0,15.0,22.0,16.0,20.0,EFCEGEFDBFHCCACBDDHDCFBHFHGFCECAEABGBGDHCDBCABGADFDDFECCACFAEFHDGHDBHDAHDHHDHBFEFDEADFADBDCHDEHFCHFGGFHGHHEAACAFCFBDDCEBCGBDGDEGDBGDHFCCFDEHCBBCBGDFGAFEAGC,False +407,11.0,16.0,12.0,20.0,16.0,15.0,13.0,15.0,HBGBDGBDGFGEFCCHCDHCDHFFCDBCFBEEECEFCEABEHDEDBEFHFDAFDBHBBHDACAHFAFBAEBDDDADDAFDGGGEEGHEGDFHBFHGDBGCBGBACDAHHCEAEEDHGF,False +408,16.0,12.0,20.0,13.0,15.0,13.0,22.0,14.0,HACHAGEAGFHHDDCEDCBFEDFEACBBFHBFHBCGBCACCBDDGDDBEFEGGHDBDDGGFHGAHFEGAEACDACGABAAHEABECECCECGGCAHFAHFGGFEECEHAFDGGGGCFHCGGCGBC,False +409,4.0,7.0,9.0,5.0,9.0,7.0,4.0,6.0,EFCBHCFAFFACFDHHBHCBGBBGBCEHGECBAGDCEFCDFCDEEHEEAED,False +410,12.0,11.0,9.0,6.0,6.0,6.0,2.0,5.0,DDCDHBBABBACFACEBDEHDHBFBAFBAGCAEAEEFHCBCCFHCAAEAABDABGFC,False +411,10.0,13.0,4.0,12.0,8.0,3.0,7.0,11.0,BBHBBDDDDDEEAAHAAHBAHGEHGHHAEDEEDACDBBDGCDBBABHHCGCFGFEGBAGBFDDAEHBH,True +412,2.0,7.0,4.0,0.0,2.0,6.0,5.0,2.0,BGBFGBFGBCGCEACFBHFEABHCBGFF,True +413,28.0,23.0,16.0,19.0,25.0,12.0,17.0,19.0,BHADEAEEHEEAGEFBBCDDAGHHGHAEBDFBAFBAHAEHBECBDCGDGBFGEEAEEDBDDBHDEHGECAACGACABCABFABCADEAHEDBCGFEBFEADEBEGADAAFAFHADBACHABHCCDCDBFABGAEGCGFHACDEGHHGHGDHFBHEBEGC,False +414,4.0,13.0,10.0,10.0,10.0,2.0,11.0,8.0,EEGCECCGBBGBCGDEEAGEDBHCHHADHDBHEHCFBDBGDBDDBDEADEHBCAGCBGEGCBGCBGFH,False +415,13.0,21.0,20.0,13.0,22.0,19.0,15.0,24.0,HFDBGDBHHBCCFHHFBHFBHFBHACEFEHFCBGBBFBHFDGECGFCAABGCFGCHHBHHEGFEABCBECEECGDCHHFEDAHBAEEDECDHDGHFGHFAECAFBAGBDECDCHBHHDCEFCAFEHEEGEAGEAFEDEBACBDCBGG,False +416,21.0,17.0,11.0,9.0,12.0,14.0,19.0,7.0,CGHHGBDBAGBAGBDGACGAHFFBFAGCACDAGAAEAEFCCAEFBCFGCAACGEFFBDAEDABDCEGEFCEBBHFBHEBHEAGGBGFAHFEBFBBDABFAGGAGGDGADE,False +417,6.0,8.0,8.0,1.0,1.0,6.0,7.0,5.0,BADAECHCCHCCHAAFCGFBGBBHBBGFCFHCGGBGGBFFAA,True +418,11.0,22.0,19.0,15.0,20.0,16.0,14.0,28.0,CCEHHDBHECHCGAGDCCABHFHHEHDEGBEGBDDBDEBHBBGFFCFFHBDHBCHBEHBAHFFGFCDHHDCHBEABHDBHCBAAEFDCBCCDFHEFGBDABGFBCADEFDGFAGEHGBHCBCGFAAHEEHEFHEGEEHEEHCGHC,False +419,25.0,19.0,13.0,15.0,18.0,30.0,15.0,15.0,FHCDCFBEHCABEAFAFHEFDGFDCDEHAFGAFBDBBFBBGBAHFAGFBFFBDBDDEGFBDEBHCBFCEFCEFAECAEFECGADBABAEHFDGFGGBGFBGDAAAHAAHDFHGCHFCAFEAEEDECDHBFAGHAGFEEFAFFAFAHCAHG,False +420,5.0,4.0,3.0,9.0,10.0,5.0,4.0,4.0,DEBDADFEFCEHEABEAEEFEDHGDHEDCFGCFDDGBDGBEAAH,False +421,21.0,22.0,19.0,21.0,16.0,23.0,24.0,24.0,BGGDDGBHHHHGHHDAGFAGFBBFGGFGEHBAHECFACAGHEFCEADEAEBAHBGBBACDACDHCDHCHBCDBDDGCFHHFHHAHEEHCGCBGAADFBGEGFCCFCGFDHHDHCBFDAADABBCBFCFGDECBEFDEGDEDFABFADFGBFGFAGFADHHEGABCFBGEE,False +422,5.0,3.0,3.0,1.0,0.0,2.0,1.0,4.0,ABCABCBGAHHHFHAFCAD,True +423,8.0,5.0,10.0,3.0,2.0,6.0,4.0,7.0,CAHCAGAAEDGFCGDCFHCAHCAHBBDFAFFGBFBBCCCHCEHAH,True +424,4.0,2.0,3.0,3.0,3.0,5.0,4.0,1.0,GDFGCGACDACDEBFEGHEFFAAFB,False +425,20.0,29.0,28.0,22.0,37.0,21.0,18.0,23.0,DCDEFDAGCHCHFDAFEFFEHDEDBEABEHBEBFCBEDBCDCCEGCEBCEAHDHHDAHGAHBBBFABFABACBADHEEHEEAEAAEACDCHBCEDEEBEGGEBEFDGCBBBAFDAFCAFCHEDBEDGECHBHGFGECEDGDFECFDCFGHECEEHFEBCABCADEAFEGBBHBFGBEHCCHBCGBEFCHHCHGGGGDF,False +426,3.0,6.0,6.0,5.0,11.0,8.0,8.0,8.0,ECEBAECEDDEBDGBGHDGEBGECGFHGFHACHFGHFCFBEFHHBHEADEFGCFE,False +427,9.0,21.0,17.0,17.0,18.0,17.0,9.0,12.0,BHBBHBBAFBCCHEBDECFECDEFFGHCEFCAFAEHDGHDBHABEEBEEDAECBDCECABDAFDHDGEDBBDBFAFFCCBHCDHDBFDGFGBFCHACDBCGGDGGCBFFBFEEFHECEED,False +428,13.0,9.0,6.0,7.0,7.0,9.0,7.0,6.0,HDAAECHEGFFGFGCFHCBGAADAADAAFABFBEEAFFBBCBBEABECGHDGEDGDABDAFHCH,False +429,8.0,15.0,19.0,18.0,20.0,20.0,16.0,22.0,FGDFDDFHDGAFGFHEBABCDBHFGHFCHACACCECEACEBCFGDBHFEHFBHGHHEHEBGEAFFHCFDEFDADDBDGHFBDFBCFBGAHFBECHECBECHECECCEDCHGEEGEGFDFEDBEHBHCDGDHCHHGGDG,False +430,13.0,25.0,20.0,21.0,26.0,17.0,24.0,16.0,EFFGFCDFCEHCGHDGEECAEBBEGBECFEGHAADDAFCAFCBCEECFFCFCAGDACHBHHBGDCGDGGDEEDBHHGCHEDBEGEECEEBEBBDBAEEFDGBGGBDAEDHEFCGBCGFCGAHGFHDBGGBFBFFHEHBCDBADCEDEBBGAAGHBGHBDBDD,False +431,13.0,21.0,18.0,12.0,10.0,10.0,17.0,15.0,GAFBBBBFHGFAFBGCGGBBCABCAGDHGDHBCHBHBAHGGHEGHDCDBCFBCGECAEDDHBAEBDHBDHBDACECGEGGDHADBEFCDBGACEAHBCFBEHAEHAFGCCGCCFFC,False +432,14.0,11.0,9.0,15.0,14.0,12.0,12.0,18.0,DFAFFAHDHEDFEHHEDHCFHCECBABBDGEFGEDCDCGDHHFCHFCGGCEGABGDBEABAAHAEBDEBHEGHFGHDHEBADGADBAEHCEHDDHBFAGAAFFGH,False +433,16.0,16.0,12.0,20.0,13.0,18.0,9.0,14.0,FDCFDADDBDDAHDCBDCDDCDAEHAFAABADBECFAFBCFADAGCAGCDBAFCFFEHFHBFBEHGCGGDFGDABDEECGGDFEFBHCBHBEHBEABEHBAHGAEFBEHHHFEHFDFD,False +434,15.0,21.0,15.0,6.0,12.0,5.0,12.0,17.0,CBBDBGABGCDGCEADBCCADEFCCAHCHCDHCAHCHHABHBBHABEFCGCBGAFAAHEAFGAEGAHGEEGHEGBFBEECHEBBAHHCHDBHBBHBBABBGEG,False +435,0.0,0.0,3.0,2.0,2.0,2.0,2.0,3.0,CHDCEDEHCGHFGF,True +436,22.0,21.0,21.0,13.0,7.0,14.0,20.0,13.0,BHBGDAADEDFGCFGDHGAGGAFDCCACCHEADBCFBCGBFABEHDCHCEGBGDAGAADCAHGHHGHFFDEHAGAGGABCAFAFFACHACGBDGBDCBDHAGCFEBFACHBCABCGFCAFGBEBBCBBCBB,False +437,18.0,12.0,15.0,15.0,9.0,15.0,19.0,9.0,BEAEFBCFAADCBFGDGGHFCADAADGADHCBHDGDBGDBGDCGAHEFHGFAEBAHBADGCDGCGFCHFDEFEHFCAAAFBAHAEGDEGFEDCCBCGBFGBFGACGCCADFG,False +438,9.0,15.0,11.0,10.0,6.0,5.0,12.0,8.0,CBBCECABBAHBHBCHGGEGGDAEBEDCDFADBGDBGDBGBBCDGABHCFGBFGHFGHFEAAEAABHDDCGCCDCH,False +439,21.0,34.0,13.0,20.0,9.0,14.0,18.0,22.0,DBGDFCCFEAGHBHHCHHCBHBGHBDABCCBAFBAGBDCBDBBGBAFFDHEHGCBACBAEFGHBGAFGCFBAGHAHHAGHGCDEAHABHBDFEDBDDADDHFBHFBEABEABADBHFHDBABBHBAEBGCDCFHGGGBBGFDGDABDABDE,False +440,5.0,7.0,4.0,9.0,2.0,7.0,1.0,7.0,DEBHHHHHHDFAAFGADHABBFFDFFDBEDCCCCFBDDBDAB,True +441,9.0,3.0,11.0,9.0,5.0,3.0,13.0,6.0,GCHGCHBCDDAEAHEAGAGGCGEAEHACDFBDBDGCDGDGGHGCFGCAHCACDGCAEFD,True +442,26.0,15.0,9.0,16.0,20.0,21.0,20.0,20.0,EEHEFAFDDHDDBDEEFFEDFCHFAAGHAEHADBAGHAGBADAAEABCGBCBBFGCFGEFGEFGHDEAEEAFHFGHDGFAGACGCHBCHEAHGABGBGADGFFGEEBCFDHAEBAGBADAABBHFHHCEEFFEDFHAHHAHADDGFG,False +443,5.0,11.0,13.0,10.0,14.0,14.0,10.0,14.0,FCEHCEHCEDGDBBDGEDHEABEFGAFGAFCCFHFFHFBAEEGDFFAHECHGCHDCHBGFEHFHFFBBCBBEHCHHBECDEDBEDCGGGDC,False +444,9.0,3.0,12.0,6.0,9.0,11.0,10.0,6.0,GACGCGACGBHABFCEFCEFCAFGFEGDCFBCHHHHGAAAEADCDGAGEEEEECFFCDFGDFCDFH,False +445,9.0,10.0,13.0,13.0,17.0,11.0,15.0,15.0,DGCDBCDFEFHEHHEDDEGCCFCFFCGDEECEFHHFAHFAEDGGBBGHHGCHGBACAAHEEHEEDGGDGGDGEEFEBGHBCDCAACAHDHBFEFCEDBHBBAG,False +446,4.0,1.0,6.0,9.0,11.0,4.0,5.0,7.0,GACEFGGACGDFDECDEHDEHDEHEEDAHDCDFCDBEHAGFCHEEHE,True +447,26.0,19.0,18.0,11.0,16.0,16.0,12.0,21.0,EEHFFHCBABHABHAEHAEHEFFGFAGHBHAEEAEEAGAAGCCGABDACECFHGHHEDHCBHCBHCBAGDABDCHAHEFHFHHDDFBFFAFCACABEDFEDAGDBFCBDAGFACEACAGHABBFBBEBACCCGHCDBAG,False +448,6.0,5.0,7.0,6.0,1.0,1.0,3.0,5.0,HADHAHCACGDGBDGBAECACBABDCHDBHDCCF,True +449,11.0,2.0,6.0,6.0,9.0,16.0,8.0,5.0,AGAAHAAGFDFEEFBEDGEGEEFEAFCCDEDFFGFFGFFCFAEFAFHDFCBHADHFGHACCAG,True +450,11.0,4.0,8.0,12.0,7.0,9.0,7.0,8.0,FDEFCADCGCEBAHBGECHEFHCDACDABHGBFFDFAEFAEADGADFEDHCAHGDHDFCDAGDAGH,False +451,31.0,20.0,20.0,33.0,22.0,23.0,32.0,17.0,BCCAGAAGFAGCEGDBGDACDHDHGFBGBBDBFGBHBAHECEECDEDHHDFADFEDCEGHAFBCCBFADGCBADDFEFGEHGEFGDHECAEAGEDDEBDEADAADBCBGEDHDDFCEAAHBGBGFAGFDGFDEFEGHBAHFAGFDGDDFDFABCABCAFCAFCAGCAHEGHGDAADAGEFGHDGCDGBGHCFAGDEGA,False +452,6.0,6.0,6.0,10.0,8.0,9.0,9.0,6.0,AFEABEBDGBAFEDHGFHGEDGEHCHAGHECHCCFDADDFEDFEBAGCFGFFGCBGDBDD,False +453,13.0,18.0,14.0,23.0,17.0,19.0,19.0,12.0,DCGDCDDCADEBFFBFFCAACDACDCCABCDDFDFAAEGFHFADCBGCDGEDAFGGEHHEFBFFBFFBGFCDFCGAGDDHDDHFEHGEBGHDGHAEHBGBDEFCBDDEABHAGEBEEBHEDEGBHGBFGBGEEGB,False +454,18.0,22.0,18.0,14.0,25.0,31.0,12.0,21.0,FHADBACFDHAHHDGHBFFFCFGCBGDHFFFGFFGFGGFAHCHEEHFHDFHFFHFAHAHEACEGEEBDEDFAFFBFFBFBEFDCBBEAEHDFDEEEBBGCBFCFCBGBBFEHGCDEHDECDECBADEAEEACEACECCABBECBECBFAFAGHEHHABHAB,False +455,8.0,7.0,7.0,9.0,13.0,7.0,12.0,7.0,AGEBFEADAAGFABFHDEAFFCGFDEHGABGCBHCBGBDHBDFDEGCEGCEDCEHEDHGDAGEHEEGCEG,False +456,26.0,25.0,17.0,12.0,23.0,17.0,8.0,10.0,BCAFCEBDBGCAAFAAFGCBEAEDDBADBADCHEFFEADEAEEFEEGAEGEHBEGAFHAFHDFBBAEACCAECBBBBBFABEABDBBDABDCEDFECACHFHAFHGHDCCAGFEEACEABFABFBEFAEBBGHBCHCC,False +457,17.0,13.0,15.0,8.0,13.0,12.0,8.0,11.0,HFCEBGABGABDAECBBCBBEBEEBFEAADACFHFEHFBACAACDAFHHFAHGAHAAEAHGHCGFCDFDAEEBDECCHCCFFGBEGCDFCBCAEDHG,False +458,4.0,0.0,3.0,1.0,6.0,6.0,4.0,0.0,FEEFEFFGCFAEAGCAGEADEFGC,True +459,21.0,25.0,18.0,16.0,17.0,17.0,23.0,17.0,HDAGCGGBBGBCEDCBBBEGFEGFEGFAFFCGFCBECBFFBEBBGBFABCAFAHEHEDHGDCCEAAGAAGBCGHCBHCAEDHHDFFDABEFECCABHABEDBEGBEGDGDFGAFEAGCDGCBHHDHCAHGABFDEADBADBHGAGAHFHGCHDB,False +460,10.0,14.0,5.0,9.0,15.0,9.0,9.0,8.0,EDEEGEAGEGBEDBDFGDEABFAFDAGEBBABDAGDBGFFHAEHDEABGBHABEACEFBDFBCHGCEBCEBEHHHFHCF,False +461,5.0,3.0,5.0,6.0,2.0,12.0,7.0,4.0,CEAFFGFFGFFDFHDFBDADACCGGCABAHGFBFFDGHDGHEFC,True +462,6.0,6.0,14.0,9.0,5.0,9.0,18.0,19.0,FGCDHCHHGHDGADGECGHCGCGHCEDGEFFHHFHFGBAHEFGBCGHFDHFHHCGHCGHEGBCCBDAHDHGBHACGCGFCDABDAG,True +463,3.0,5.0,4.0,8.0,5.0,3.0,5.0,5.0,DGAFBBFAHGEGGEGBECECCAHHDDDEDDHFDHBDCB,False +464,8.0,5.0,4.0,6.0,7.0,4.0,8.0,3.0,DACBACHAGHBEHDEFEADGGCFEDGEBGEAGBAGFDGFDAAEBC,False +465,13.0,13.0,10.0,12.0,11.0,18.0,10.0,10.0,DFBGFDFFDGBBBEDGEDBECEEDFHAAACAAHHHHHBGGAAAFHACDACEFFHFFHAGCBEFBEBAFGAHGDEGFFBFDBFDECCECCGBCDBFDF,False +466,1.0,7.0,5.0,6.0,4.0,4.0,5.0,8.0,DHBECBCDBGDBHDBHFHECAECFFGHDGBBGHCGHDHFE,False +467,8.0,10.0,7.0,7.0,13.0,10.0,14.0,7.0,GGBEGHAGEGBEDBCAFFBHEEAEFBEGCFGCFHBFEGFEBFHFCHFDGDDGHDGDCHAEGCEGAEDCEBAABABG,False +468,7.0,9.0,14.0,4.0,4.0,10.0,8.0,4.0,FECAECBDFBGFCCFECFDCBGCBGBFDAHGAFGBBEBCHBCAAHGAGCCCFHCFGCDAF,True +469,11.0,8.0,10.0,17.0,9.0,15.0,9.0,16.0,FHDFDDEACFHCFCAHDEHAGHACHDGBAGBEGBAGEHHDGHFEHADHAEFAGGCFECFBCDGDHHDADBCDBEDFFDFFCCBEDHFHAFHDFDB,False +470,1.0,3.0,1.0,1.0,2.0,1.0,2.0,3.0,CHADBEEBGHBGHF,True +471,17.0,15.0,26.0,18.0,19.0,21.0,23.0,27.0,GFFCCCHCDHAGAEGFGCBGCBFCFFHDFBDCHDGHFEAFEAEEAEGDHGHCGABGDCGDGGFFFACHBEAEEDEAHFAHDHHGCHFHHGGHBBECGECEEDAHCACCBBCFBCHGCHACFDCEDAHCAHFFFDABEEBCBAHFCHBHBGDGECGEHDHGDHGDFD,False +472,2.0,5.0,3.0,5.0,4.0,6.0,6.0,2.0,EGHFGBFEBFEDFHGCCFEABDADDBDGBGCFG,False +473,20.0,30.0,26.0,33.0,27.0,26.0,18.0,15.0,CGAHFAGFAFDBCDEGDEHBEGBEBFDGFECFHBFHBEEFEECCEFEFFHCDGAHABDFBAGBADBADBDGFGCDCABGAEGDDDDACFACEAFEBEGDCGCEFDEBEEDFEFFDABDHBDEBCHBHHFDDBCDFGDAGHBDABFBDDDFFBBACBCCBCABCACCHGCBFBDDEEBCGDCGDCEDCHFEHEAHE,False +474,19.0,17.0,14.0,18.0,11.0,17.0,20.0,12.0,GAGCCFFCGFEDEBFFAFCGDHGEHGEHGHGFDFAAFDADDADCACCBFBDGBGGBFEBCABDAGHGBDBBHFGEAGCDGFDCFCHFAGCBBABBABAEBCFCDEDHGHAEHAEDAEDGFDGDAHHAB,False +475,29.0,21.0,29.0,16.0,8.0,11.0,32.0,19.0,GGHBGAGFAHFBGAHFBHGBHGCEACHGBAAAFHHFHHCBGCGAHBDCCDGAAGHHDBDCBDFBDBEACAFCEDCBGABGAFEACGACGCCGBCGHAGADEAHGDCGCBBAFBADCGBEGBEGBAGCGGAGABCCHCDACGHDGEAHAADFCCHACDGCDGCDFC,True +476,1.0,0.0,5.0,0.0,0.0,3.0,1.0,0.0,CCCGCCFFAF,True +477,12.0,12.0,12.0,10.0,3.0,21.0,15.0,7.0,FDFAGACBDCBGCEFEFDGAGGBBDBBAFCADCADCFCGFCFFHFFHBFCCDAGAAGBFDCFCAFHDBBGHDGHFGBFBEFGFFAHGAGGFH,False +478,17.0,16.0,18.0,22.0,16.0,25.0,17.0,21.0,ACEFGEHAECACCHBGAFFBCFECADCEFAEDEFAECBCGBCHFGHGEBAEAADHGDGAFGDDCEHCHAEHDEFGHHHBHABFABFHCFHCFHCFBDFBHBEFFEDFCDBGDAFDGBHFBHAEDCFHBDDGADGDFCDFGDGBDGDFHDFHG,False +479,10.0,7.0,13.0,9.0,7.0,6.0,9.0,3.0,HGCDGCAGAEGAGCCBCCFCEFEAFEACGGCHDABDECHFABFEBEBADBDDBAACGCFDCDDG,False +480,1.0,0.0,4.0,0.0,2.0,0.0,5.0,0.0,GCEGEGGCCGCA,True +481,21.0,16.0,14.0,17.0,11.0,10.0,25.0,16.0,FDGEEGBBDHAHGDHBHGBGCBCCFACEAEGAHHDHBGFDGADAAEAAFHCFHDFABGCBGAGGADCHDCECEDBDACDAHDAGDBHHBAGFAEFGBFGBGHAGAAEDCBCEBHEGHDDBGGGGCAGCFG,False +482,12.0,17.0,21.0,17.0,21.0,22.0,20.0,24.0,HCBHEEHCEHCBHADGBCGBEEHHFGHFDHFCHCGHGGHBGCBCHGDDACDFFFFFGBACFECGCFHFAEDHDDBDDHDEGDECAGCAGHAEHAHFEFDEACCDGGGFGCEBCEDHFCHBHBEHDDABHFFFAFFBFEBEBBGAEGCEGCEBFE,False +483,19.0,21.0,17.0,13.0,22.0,21.0,20.0,24.0,GDGGEGFHAHAEHADHCEHDAACCBEFBEAAFFAFGHHBHDBFDFFACBGDDGDHHBACBFDHFDBFEFFGABDACDFFHGFCCAEBBHGBHBBEBGCDGCHGCHEFHEAHEHHGACCACGAHHEBGECGACFEEEBEFBCFEEGEHGEAGBFHBEB,False +484,14.0,17.0,19.0,19.0,23.0,9.0,30.0,14.0,DBADEECEEGGGCGGCHGAEDCGDCDDHDGGDEBHBBCAHHADGGGEGCECCACHAGHAEDABCHGGHAGDADBEFHHFBCEAGAGGDGGHGGACFFBFGCFGBBDBECBEDBGFEHDEBDEFHEBCEBAEGEECEGBGFCDECD,False +485,23.0,20.0,17.0,18.0,15.0,7.0,16.0,20.0,ADAADBBFAFFAFAAGCDHCHABGABCAGHBGHCAHEECBECGDHHAHDEFBGDGDBGDBAAEABGHBDCECCBGGHCEHBFABFABCACAECBCDDCBEEADEADHHDHDDGEHGEHGEDCBDCHAAGGBHHBHE,False +486,19.0,15.0,16.0,14.0,11.0,13.0,25.0,19.0,GDCGHFGHCBDBAAAAAACAGHBGADDCCHEGBCBDAFDBGDBDEAAGAHBAHADCDDEHHFHEAGCGGCGGBGHCGCBGCBDCGGGFEGBEDFHCFEBFEAFGAEGCFGCFGDEGAHFEHABFFBHHHHHH,False +487,17.0,28.0,19.0,19.0,12.0,13.0,19.0,22.0,DBDEFAHAGFBGHEGHDDBBEBHEBHDCHFEHGEHGBBACBAGAAGEBBHBDFBDFBDCCHCCAEBGDGDCEBCACFAEGAHDFCCBHCEHDEGCBGABGBDFHCFDDFDBFGAGGFHBCHCABDABHAHCAGCHGBBBCBHFDHADHG,False +488,11.0,5.0,10.0,9.0,17.0,10.0,8.0,12.0,HFEBAGAEFADDEHDEHAEHDEHAEDEEDGBCHCFECFBCHGCHGEDBEABGAHFAHFHEEGFHACECCADEDCEFCAFGFG,False +489,15.0,27.0,19.0,19.0,24.0,16.0,18.0,23.0,GDHCDCEEBEBBHABHFBGFEGDDHDFACCAGGADEBDEHABHAFHGBHAFCAFCBFCFHCHDEHDBBFABDEGCECHDDDDGEAGHAFHFEBBEAHCAHFGHABEFEHDHHDCGBEHBEBCCBGDGEBGEBEECEGBECBEBDEBFGHABHFFDGCCGBC,False +490,3.0,2.0,6.0,3.0,7.0,0.0,1.0,4.0,CBCEHEADEACEADEDBCGHHECHEC,True +491,14.0,16.0,16.0,14.0,17.0,13.0,22.0,10.0,FADFCGFCEFCEBCGBCBBCBBAFBGGBGBEEEFDBBDHEEHGHAGHAGDDGBEAAGDFCHADHGDHGHFBDEDDEFECCEGGGGGADGCBEEHDCGCCGABHDBFAFEEECCAGAFGAFCA,False +492,26.0,18.0,20.0,24.0,26.0,19.0,29.0,28.0,DCADFADCEHGDGGFGEAHEHHAHFCCCGHBAHEAECBBGGBHGBHDBAAFECHEBHGFHCAHDAHDAHACHCGHCAAEGGGDBGDGGDEGHHDCGEEGEDAEDCGFCDFEFFADHGBCABHDBEGBGBHCHFGDFEFFEBBEDBEAAEFEBFGBAHAAHECDGDDFDACCAFAEHGEDGEDCEHFGHFA,False +493,1.0,0.0,2.0,1.0,4.0,2.0,0.0,0.0,ECEECEAFFD,True +494,11.0,16.0,14.0,24.0,25.0,15.0,20.0,16.0,HFCEDHDDCEGCFADBEDCEDAFBACGFFGHDDDGBDFEAFCAFHDFHEFBAFBDEBEHCEDBHDGHDFAEFCECCBGGBFDBCDHAHBGEBEEHGGHABDGDGGDHADGAEEBFECEECGEGGEBEEBHGCHGDHGDEDE,False +495,15.0,21.0,13.0,15.0,18.0,25.0,20.0,12.0,GFGGDGBFFFDCCDGCDECAEFFFHCECCEDEEAEEBEFHDHBGGBGGEGHAGEAGBGEAFAHFACFCHGBBGBBCCDEGDFFFFABBBEBDAGDAHFACFAFDABDBBEFDEFAFBBFBBFEHHGHDDHBFGAFHEGC,False +496,14.0,17.0,8.0,12.0,24.0,10.0,23.0,11.0,GBFGBDGAFGBGEBFEHDGAFEBCGGGBABDAEDGEFBAFHEFHBFHEEBGEBAEGGEFGEABAHBGHBCFGEGCAGCEHEGHDDEBAGCAGBECDECDEGDEGDBDHEEHAEHDCAAE,False +497,8.0,11.0,13.0,8.0,7.0,15.0,9.0,16.0,EHBHFAFCAGEGGCCGCAGBAGHDFFCFHBHHDDHFCAECHDBHCBHAFFDFEHCGDFGAFCAFCGFEBBCBBCFHDHEDHFBHEBH,False +498,3.0,6.0,8.0,3.0,3.0,7.0,4.0,5.0,CHECBEABACCGCBGFHFFBGDBFDAFDEFCGBCHFHHC,False +499,7.0,4.0,9.0,5.0,5.0,8.0,3.0,3.0,ECEEFHFFACFAHAABEABDCCGFDGFCCFCCFGDABDCDEBAH,False +500,7.0,8.0,5.0,8.0,4.0,3.0,2.0,4.0,CAEFHGBDDBDDBDDBCGBCFDFDHCAEAEHBEABAAHACB,True +501,22.0,26.0,22.0,26.0,16.0,25.0,21.0,27.0,EBHCGHBFHBFBAEEAHFAHEADFGDFBFHCHCCHGAAAAAHAGBBBDBCHCEHBHHGDDFBEFDECDBFFHFFDDDDDFDAACHBDABDHGCEGCGHFGAFDCFGCFGBBGFACDAGHFGHEEAEEAHHBDDAABBCBCDDCDCGHFGHEBHABGFCGCEGCBCHBCHDGFFBFGEFDEHDBAD,False +502,10.0,11.0,12.0,13.0,8.0,15.0,13.0,13.0,GFHHEHDCHDEFDADGCDGBDFADFHFACFACACBFCGFCAFEECBECBACAFDEHBGGAAFDGHCBDCBHGBHDFHDHGEFGFHGFHDBEBGGB,False +503,5.0,6.0,10.0,4.0,4.0,8.0,9.0,0.0,FEDCEDCGBGGBCFCFEDBEGAACABCGCCGFFGFFDAGGBCABCF,True +504,7.0,14.0,10.0,11.0,12.0,9.0,6.0,15.0,BDBBGBFCEDCHDCHEFFECHGDEEHEDHDBCDHGABFABFBBDBBCEECHEGFAHCGFBHFAHFAHDCEAHBDCBDHGEHAEH,False +505,21.0,9.0,16.0,11.0,15.0,16.0,15.0,15.0,DFAGEAGEAFCCECCECFEGFHGDHAFBCHEDHEHBEAGFCHDHGAHFFCAAGAAGAAGAFEDGCDFHGEHFEDFBDCAHGAHBABEABGABEDFFHGFCEACHADEBCCBGFDCCHA,False +506,17.0,15.0,12.0,11.0,15.0,5.0,18.0,14.0,BHGDHFBGBBABHAEGAEDAEAEDBEDGCGHADCFEHAGHAHHAFADCBBGEGGBDBBDEHHHGGBGADGACHCEGCEHAABFAEHAECAECEECFBCGDCGBCGDG,False +507,23.0,16.0,18.0,17.0,15.0,30.0,19.0,16.0,CAHCHFAHFDGFDGEHAABDAFCAFBAGBHGHCDBAAFGFFGADAHDGDGGFEDFEDCCCCDHGFFGFFCHFAFEAFEFHGBEFEEFEECDBGGHHGHCEHEGCADCEBAFBFDBGBCHBFFBFFBCDBDGAGFABEAEAAFFCBFCADCADHA,False +508,2.0,2.0,6.0,5.0,8.0,2.0,3.0,4.0,AECAHCEDEEGEDCFFCBECDDGGDHECHEBH,True +509,10.0,15.0,13.0,10.0,20.0,25.0,8.0,14.0,BFFFFGHDGHBEECGECGEHFEFAGBHGBEDEGAEAHHFFHCFCFFHEFADFBCEHCEGFAHFHEFECBDCBDABDCBFCBDHBEFCEFCHFEBEBFEAFACFHFBAFEADDDBE,False +510,9.0,6.0,15.0,8.0,8.0,15.0,8.0,4.0,CGFCHFDFCDFADGADECCCFCAFBFFCCFEGFDGFCGCCEBBEAEEAEFGHDGDFCHFEFAGDABBCBCAHA,False +511,1.0,1.0,2.0,5.0,3.0,1.0,4.0,3.0,GDDGCBGCHDEEDHEDFAGH,True +512,16.0,13.0,8.0,20.0,20.0,20.0,19.0,18.0,GEEGAEDHBDFBGBGGHGEEDHEHEGFEGBEGFHGEDBBAHGFDAFDAEDGFFHFFHEEHDEHDGDGADCADFADABFHDFCEFCHFDGAGABHAFHGHCBFCHEHBEAAEAAEBCEDFGABDCHFCBFDFDDG,False +513,2.0,0.0,0.0,0.0,3.0,1.0,1.0,4.0,HHEHHEAGAFE,True +514,16.0,32.0,27.0,32.0,20.0,18.0,31.0,18.0,FFCEHGEAGHCGDDGHDFEDFDDBDCHDAABHAGDEGDEGEFCBDAEABBAGBCGHEEDCCBCCAECAGBDFBCHGHHDHADGGGCCFFAGBGFDGACBHCBDAEDBEDAGDHCDGCEGFGCEGDADDCHBGHBAHBEGBEFBFGBHDHGEBBDBBFCCCDEBDFBDBBGFBGFBGFBGFHDBCCCEBCGDCED,False +515,26.0,15.0,26.0,29.0,17.0,18.0,23.0,22.0,GFHDAEAAEGAEGCEDCDDCAHCABBAEBECGEBHHGAADFECFBCFECEDGDDCDCGDBDFGCGHDAHFADDAHCADDGDFGDEAAGAFDHGCHDCBDCGCBGCBFABGAHHBHDFHDFDDGDCFFAHBEHECCFCBACHACEGCEHHBHFGHCGDAGDAGECBFHAAGFFDEAH,False +516,12.0,12.0,20.0,17.0,22.0,17.0,13.0,11.0,EEBEADDAFDADAHHEEBGEBFFBEBCCDFCEFCEFCEFCABEFHEFCEFGFCGCGHCHDCGFBECACAGDAHDGGDHFDHADEADBFHBFABDHECFDCHCEGGDCDDCGBEAFEBECGECGE,False +517,17.0,18.0,11.0,13.0,13.0,9.0,14.0,20.0,BEFHACHEDBAAHAHHAGBAGCGGHAADEHDEHBBHGEHAEHGEDGEBCEBCHAAHBCHADHCDBGFBGHAABBFFFCCFACBGDBGDBFDCFDCBEHFHHEGBADEDHEGGABD,False +518,20.0,13.0,17.0,15.0,17.0,19.0,27.0,13.0,CFECBCGACDECDHCHAGGAGGAGGAGEAGHBGFFGHHDEHDHDDGAAGDDGDHBEFDAGBABEECEAABAAFAGFGDFCDCEFGECBCGGEGHEGHBGEFHFFDCCAFGAFEAEEFCFACFGBDCBCAHGBEGFDFHBFB,False +519,4.0,10.0,8.0,8.0,7.0,6.0,3.0,5.0,EABADFAHCBFGDFCDCCBACBEFDGBHGBHFEHFECEDHBCCBEDBEDBD,False +520,21.0,21.0,12.0,9.0,4.0,4.0,12.0,8.0,FAACBBBAABGAFADBABBDBBABHACGACBABBHHCECAACAHGDHGABCBDABAGBDGDAEDGCDGCABFEHEAHFBHGADGCCGBCGB,True +521,7.0,6.0,5.0,6.0,9.0,6.0,4.0,9.0,HDFFDAFDAFBFEAGABCHCHHBFHBGEBHEHHEHEDAECEEGACDECDBGA,False +522,7.0,13.0,6.0,12.0,9.0,15.0,17.0,9.0,FEHCDBCDGGDGGDHFBHAEFDEFDFGEAABAFBHCBEFBACDGBDGHHBFGDFEDEEGGBGGBHGFGFEGHCFBFFBGFGHBADCAD,False +523,13.0,18.0,26.0,23.0,24.0,18.0,20.0,22.0,HDCHAFHBBHAEFFCCGDFGAFCFDBHGFGEFBEGCEHDHHEGCEGEDBDDBGAFHCFHCAECHBFHADHFDHECFBCBBEEDGBCGEEEDGHFGECCECDACDGFBCACCDDGDDEBDGBDGAACABCABCFBEFEDHEDHDGHEFHECDECGAHGEHGCCBH,False +524,23.0,26.0,27.0,25.0,18.0,14.0,25.0,20.0,AHEABADDECBHGBEGDCHHCEDCECAFCACEFEEGGDGGDGEDGCFBAEAHFGDFCACHEBDDBADBADBDDACFAFAGCBBHBGGFDBFDGAAGAHGDHFBEEDCCDCBACHHCHECFDDHABAACAAGHHGBGGBGFBGFHDCBDCBHBHHCDFCDEBGHBGACGCCGECBBBEE,False +525,9.0,5.0,7.0,9.0,10.0,14.0,16.0,12.0,GDEGFEHFGFFECEBCBHHAHAGHAGDFCDHBDAFFFGFGGHBDHFDCFDCDGFEGEGCEGAGAAHAGEGHEHFEHFGCDBA,False +526,21.0,20.0,28.0,24.0,24.0,22.0,22.0,28.0,FBFFHFFDFEBCDDDFBEABCGECGECFHFFCFDAACAAHAHCDHGHHFHCBHBDHGDGDHAHCDHGABAABGCGAAFBGFCDFCDFCABEHDEAGHABHEBAEFHCAEABHGHHACFEGEEFEEGDFGDCCDCEDHHGBHGEHGECGDHDDAFCEBDHBGGECBDCBGCAGCEBCECEBCEHCDHEDF,False +527,20.0,11.0,8.0,13.0,17.0,8.0,13.0,14.0,DDHGDHCDHDDHEGFEDECAEHFFHAABEGBEHBCAGADGACFACECDEAHGABBCEAAEAGFABAABAHGFHEEGGDCEBAFGFHGAEDHEDHEABEABDHBG,False +528,9.0,13.0,8.0,10.0,8.0,6.0,9.0,7.0,ECDBCHEGHFFBEDBGDBHDBHDFHFEBBCDFDACACCBEHBAGBAGFDGADGACHABDAEABGGEGCEB,False +529,2.0,5.0,6.0,3.0,4.0,6.0,5.0,4.0,FCBFCBFCDCHDEHBFGFFGAEAHEGBCGCHDEBG,False +530,5.0,3.0,3.0,2.0,4.0,2.0,5.0,5.0,AFBAEGACGFGHCEHEBGEHGHDAHDACB,False +531,14.0,18.0,15.0,23.0,16.0,17.0,15.0,32.0,HBAHEDHGDHCDHDEHDEHDEHDHFAGADFEEHBBDFHDAEDEEHHHBHDFHDFHCFCFECABGGBEGCEBFBBDBDCCHCAACFACFHEEHCHHDHGFHGFHDCDDBEBGHAFFCGBAEBAHBGHAGFBGAHCFFBDGDCBDHGHGDHA,False +532,8.0,6.0,17.0,12.0,9.0,14.0,14.0,11.0,DEGAFHFDCCDGCHHBHCFDCFDCEGGFHHCAGEGBFGBDGDAGHCGCCGDCHDGEDBEFFCFDCGHCEHEGHACCAFAFFDFFAEBAEBC,False +533,15.0,11.0,12.0,12.0,16.0,22.0,21.0,18.0,GAAFFACGGFHDCBDFBAFBAGEAFEBFGGFDDEGFEACHFFBDFGEGDFFAHFHHAHHEHHFHFABECBDHHDCHDGGDGGEFGEHACGACGECEECEEBDBHDHHFHEFGGCABCAFEFCGGGBA,False +534,6.0,6.0,12.0,13.0,5.0,12.0,12.0,8.0,HDGAGHFGHFCHABHFEHFACCCBCEGCGDCDEADCFDHGDGFDGFBGCDCHFFEGFAFDDFDDGADCBECBGB,False +535,22.0,16.0,25.0,15.0,17.0,33.0,16.0,16.0,FBFFEECEEDFEFEEBGGDGFEAAEFCGFDGHDGDEGAAAHACFECDACDCHFCHFAFFAFEGFBDFECHHBACBCCACDAGFGDFEDFCCFHCBCCFACAAGADGHEFFCBFHDFCDHBHGECAFFGBGBFGAAAFBHFHHFEBFCDFCBACBHCBHAB,False +536,20.0,17.0,26.0,15.0,22.0,17.0,17.0,16.0,BHHBAFEEFAEFAEDBBDFEEBCEHHAAHAGBDGBHBECECCBFFAFEACEGCEFEECDDDGBDABEEBEHAAHCFCCEACDAHAGHBGFACFHCGHCFCCBCFGHDHCDHCDGCEAHGAFBADGGFCBFCGDCGCCFADECDGGEGAEB,False +537,13.0,10.0,5.0,5.0,10.0,8.0,9.0,7.0,EADEDEAAGAEEBGGHHBFFBFEBFBBDEAHEABCAHCAEFAGDAEDBFFGFAGAHGCHGHABCGBC,False +538,10.0,10.0,16.0,12.0,12.0,14.0,12.0,13.0,DFCGBCDFCDGBDCFCFFCFDAHDCBECEEBEDBEHECFECGAHGDHEAHAHHGFHGDHFFCGGCEGFGGCGCAAHHAEHCBDFBDEBAFADFAEBCBH,False +539,2.0,2.0,4.0,2.0,0.0,2.0,1.0,0.0,ACCFCAFCBDDBG,True +540,3.0,8.0,6.0,4.0,2.0,10.0,5.0,6.0,FGBFBFDBFDBFHFFGCEAFHCCBFCBECFABGDGHDGHBHHAC,True +541,4.0,4.0,3.0,5.0,9.0,9.0,6.0,7.0,HHFDFBDFAFFAEFEHGEHGEBGEAHFDEBCGHGGFEAFDDHCEBCE,False +542,1.0,6.0,4.0,1.0,3.0,1.0,2.0,0.0,EGEEDACCFCCBBBBBGB,True +543,11.0,8.0,11.0,8.0,8.0,12.0,13.0,10.0,CGFCHFHAFHGCGCCHCGHGACBDDBCDFADFADFBBEDAEGACFAHHGBHGDAEFGEAGEABHBGFBAEEGEHDFCGFCF,False +544,1.0,2.0,1.0,1.0,0.0,0.0,2.0,3.0,GDAHBCHBGH,True +545,20.0,18.0,24.0,26.0,24.0,22.0,18.0,33.0,CBHDDADAHFAEFCEHCEHEBHCBGCHAAHAFHFFEAFDAFBEEGHAGDDDACDHCEECEGDEGDEGBADBEDBAACEECHFBFCHFHHEEDBHHAEFCCHHFDBFDHCHHAHHAHGCHCCGFCGBGGFGDFBHFDGGDCEDADDADCFBCHBCBFHEHBEGAFHCCBEFFHDHGAEGDBGDEHD,False +546,29.0,23.0,21.0,19.0,21.0,27.0,25.0,20.0,BHEADFCDFGBFAFFACEAGFABFACFACFHEBHBFHDFGEGCEHCGDCDFCACAGDEBDEFAEFGEGGHCEHEAFEGECAAGAAEFFFFDFGGGCDGBGEBGHBGEBADFGCAGEADDBDDBACCCBDBBHAAABAHBACGECDDHGHHGBFEACHBFHEDCFDAHEAGCBGBAHFAHFBHFBH,False +547,8.0,14.0,13.0,15.0,21.0,12.0,10.0,20.0,CHCHGGHDDADDEGDBGFHCBECDEFBGHEECEGCFAEHHEHHCHHCHFFAAEDAHDEGBEHAAGBEHDEDBCFFEFCEFCHHEHBEHBEHEDDEGDGABCEBDBBCBFFBDF,False +548,5.0,4.0,1.0,2.0,4.0,2.0,2.0,2.0,ACBADGEEGEEBAFBFHDAHBA,True +549,14.0,13.0,9.0,11.0,17.0,24.0,19.0,14.0,EHAEHGEDBEDCEGGEHFBFBBGBGGFHAFHBFEACBACEADGFEACGFEGFADHGDAGCBGHGCFEBAHBGHAHADDAFDHGGHGFFGFFCFFEAFEGEEFFHFDBBDCBEHFFDFAEFC,False +550,8.0,20.0,16.0,21.0,30.0,20.0,19.0,15.0,FHEAEECEEGBBBBBHBBDDCDDCDBCBFFEGFBCEHEEHEEBEEHFDCEECGBBGAGAHCAFCAFGDEGCEFEHCDBEDHGCGFFGEEGEECBEFEHFHCDHBDFDDGGDHEFHGDECDEHEGACFAFFGFBGBGAFGDDDDDBEFBH,False +551,8.0,3.0,13.0,5.0,6.0,13.0,5.0,7.0,BDFEDFGCFCHFCGCAFFAFFHFGCAGHAEHCBCCEHCHDCADCFFAEFCCDHGEFAEBA,True +552,10.0,10.0,17.0,16.0,16.0,11.0,4.0,13.0,CABEDBDDCCDFHBACBAEEDFGACHECHECEDHDDBDDHAHCBHEFHEFHEDDGACAECHEFBEFDEDDHCBHCHFGBFEBDCFACEGCAACFCEF,False +553,29.0,25.0,19.0,15.0,29.0,33.0,22.0,26.0,EABECBEDDEFBHACGBHHEHFFAFFEDBAGFCHDGEDEHDGDDCADHAFFABHCFEEBAECAECHHHACCAEABEABCCECFECEGCHGCFFBFFBEFDGGAGAECHEHHDHHABDEHAEFFEAFAFFAGFHGEAGFFGFAACAEFFEGBAABFGBEGDFHDFHEFBBHDHHGHBCABABBFBBGBGGEAGBFGCFH,False +554,19.0,13.0,14.0,11.0,11.0,13.0,12.0,8.0,ABGABGBBFEBEDGCDFCEAGEAGHAGFAGHACHCDHADCADFGDCDDAFEGFEDHHAGCGCFDEHBEFCFFCFEABGABFCHEBABBACADEAFBABACC,False +555,4.0,7.0,2.0,2.0,5.0,4.0,2.0,1.0,ABBABDFBHFBEFEGBAGEAEEFDCCB,True +556,33.0,24.0,13.0,22.0,28.0,22.0,18.0,30.0,EEFABBCDBADEGEHHHCAHGEHABDDBDAGAABDGBABBAGBEBHEFDEDCHDAEDBFHEAHFAHFABFCBEHBEHAEHCHHFEHBEHFEFFHAFHAGHEGDDHBCEDGAFGECHHDHFAEFAECAGAGCEGADDAEBABAAHHAHGAHFEEECAACGFCDFDDFAFEBBGHBGBAFBEHDFGDCGDFA,False +557,21.0,20.0,17.0,15.0,9.0,13.0,11.0,17.0,FFFCCBHDBHDBDDBDDHDCGFBAHBHCCDAADHAHHADGADCCHBCFECEACECCFDABDCEHEHHEBHDFFABAABAGBEGAHGACGCGGFBBHBAFBABAGHAFHFGCGDEFBBCABAAE,False +558,17.0,17.0,12.0,11.0,13.0,15.0,10.0,21.0,AACABFAEFAEGCEBAFBFHBDHEAHEBEEHDHHBHCBFGAFGFCACBFBDFADFCDBHHBHDACECHHDABGBBGFGHDACEBCEBCAFHDEBDCAAHHFHHFGHEGAEGHFGHD,False +559,14.0,31.0,29.0,20.0,24.0,28.0,19.0,25.0,CBHCBFCBGABHAFHAGDBEEHABFAEDGEDECFFCBFDFFDEAEHDDCECEHCBACBDFBCEECGGCGFCFHEABDABDGBDAHFHHGADGEFHDGHEFHEBBEBGCBFBBDCEGFFAHGBHAFFGFFHEFHCCHBBHFEHGBDDHCBCFBCFBCADCDBCGCCBBCBECGDCHDFHBGHFGFCEEHEE,False +560,11.0,11.0,9.0,9.0,7.0,8.0,12.0,11.0,FDCFDGECEACDHCFAFGAFAFECFCHECHABHGBHBBHBGEGGAGGAFDBHDCHDBEDGABEAGACHBHDBDABGHG,False +561,17.0,20.0,22.0,24.0,12.0,25.0,33.0,19.0,GFGGFCGFGDHGBCGHGHHGHCGHDGCGCDDCHGCFGFAHCHFDFCDEBDEBGFCEFCFFGAFCCGCHACBFDFGEEBBDDBECAFGAFGADGADGDDGADGFDEBDBBDBGCAGHGGDGGBBDFHCCDCEFABHHBHEEHBDHAFAGEAGDABFAHHAFBFGDCEBCBFFA,False +562,11.0,10.0,11.0,8.0,5.0,15.0,7.0,5.0,GBAGDDBFDHFDGFAACAACBBGFGEBGFFCFFCEFBEFBCBACFFCAHCAHEEDBAHFCFFCDDAGCAHDB,False +563,20.0,11.0,17.0,13.0,14.0,9.0,14.0,23.0,BAGDHGEHCAGCGEFAEFBCCHCCBDADHBDHADHCGHAGAFEAHHAHHACGCEACAHCDHBDGGDFEBFHHDHHCAHGAHFEEDGFDECDHHEHACFGHFECEGBBCAACAABDABEGBE,False +564,25.0,13.0,20.0,11.0,13.0,16.0,8.0,5.0,AAAAFFCFFBBFABDAGEAGAHGACCFEFGEGAEAACACEFCFFCDCHFBBCBCCADFBHFDCCBGABGCBABBDFACAAFGACACDEEDECDBDAEDAHDAECAECEEHF,False +565,28.0,15.0,20.0,25.0,16.0,15.0,18.0,16.0,AADAACACCACGGBEGAEGBEGFHCHCCEBCEBDBBDBCDAEDEBDABDFFHHEAADAHHGHGBDGCAGFADAADADFHEFHFGDEBDFCAFEHFBBFDHCDADDACDHFHAGCGDAGCABADCADEAGEGCHDDBDCAGFHGHCGAEFFECE,False +566,7.0,8.0,2.0,9.0,6.0,8.0,0.0,5.0,HEFHDFDDHDBEDBEFBDBBECBAFBFDAFHAFEDDBCEAAAFHA,True +567,12.0,8.0,8.0,9.0,5.0,12.0,6.0,5.0,DADDAGBGGBCHFGFDAFCACAEFADFGBFABCDDFEDFECHECDBAEAHCAHBACBFFAFFBGH,False +568,27.0,25.0,25.0,24.0,19.0,25.0,34.0,18.0,GGBDADGGGAGEFFECFEBGEADDADDAFHBBHBCFBCGGEGEDHDHBDFBACBGCFACBCGBEGHHGCAGHGBAFAHHBFHAFECHCABFGHCDHEFEFCEDCEGBGGDAGFFGFFGAFBEFEAFEGFDBFCAGCAGCABAHHHCEACBGEBDEAACCFGGFGDBGDCCDBEGBCDFADBAGBADDADHCDHCDGA,False +569,17.0,19.0,19.0,27.0,20.0,24.0,19.0,16.0,DCECCEHDBFDEDGEAGFGFBCHBCAGAHGFDAFDBHAGEADCHDCDGCBHCEFCHFCGFAADABFABFEECGFHHDHBDEBDBCFEEFEEAECGDBFCBDHBDEBDAFDAHCGDEBDEHDFADFDDFGAFEFCAFHDBEBBDGGACDBCHGFFGFGGEGH,False +570,14.0,23.0,26.0,22.0,21.0,32.0,13.0,35.0,DEACHFHFDHEHFCHFCEFBFHBECFECHDGEDFFDEFHFBCCACCHGDFCHFEHCAHCHHCEHEEHCHHCAHDDGFBHCBEAGGDBGFBEHBHFBADBFDAFGGGABHAGHABDFBFHCFDCFDHEHCEAAEGCBGDFCFFEFDBFBBFBCHBHDBEDHDDBAFFCFHAEHCEHCBHDBCDEGFH,False +571,12.0,18.0,32.0,29.0,10.0,22.0,15.0,20.0,DAHAAEGCCHHEBCEBHDDGDDFFCCCCCHCFHDDHDHADBEFBECBCDBCDFEDGHDHCECGACDAEGGDGDBFHCFDGDDGAEFDCFDAADAADHBCBBCGEDBBHCFHCABFDHFBFCBCCBCCHCFFDGCGGCHCBFDFFDFFCFHHBHGFCGD,False +572,19.0,12.0,16.0,19.0,24.0,11.0,17.0,21.0,AEAGEAEEBDEGDECBBDAHDAFECHEFHGFGGDEHDECGGCAEHEHHCBHDDHDEGCEGAHGFEGEEGEECFADFEDEGCCABAGBAHAHHAEHACACHAFHBCBBAEAFBHDDADDGDBFHGCHFCHCCGFDHDDBE,False +573,5.0,2.0,3.0,2.0,1.0,4.0,3.0,2.0,ACEFDDFABGAGGACFAHFCHB,True +574,17.0,18.0,22.0,17.0,4.0,9.0,12.0,14.0,CCBCGGAHDAEDBCFCCHCFACFAEDAHDAHGBGDFDDCACAAFBBDDBDBBFCBECADDACBFCBHCHHABCAHGBBGBADDACHAGHDGHDHBEHBGBGGCFDAGCCCFHC,False +575,13.0,19.0,23.0,32.0,16.0,20.0,25.0,19.0,GGDDGDDCHDBGDFDDHBBHGBHBFHCEAFEHFGFEGEGGDGDFCHFAEFBCFGHDGDEGDBHDAAGHDDADEBCEGCEFCEFEDBACHAHFDEFCGFGHBBBABDCBFCHDCFFCHDDGDDGECGEDAAHAADDAFDCGCHBCGBCEHDEGFFHBDCBDBGCCGCC,False +576,9.0,9.0,12.0,4.0,5.0,6.0,12.0,11.0,BHFCHFGHEGHBGEFHADCDCGGCFGCBDABAEBACGHEGFBGBAHCDHCGHAGEAHHCCFCBGABCA,False +577,6.0,7.0,11.0,9.0,9.0,12.0,13.0,8.0,EDDGBABEGCGACGECECCBCCHGEFDEFGGFGBCGDAGHGCHBFGBFDEFCFFAGFDHBDADFADFHHFHEEHC,False +578,0.0,1.0,2.0,1.0,0.0,2.0,4.0,0.0,GCGDCGFFGB,True +579,5.0,1.0,1.0,3.0,1.0,1.0,1.0,4.0,HGAHAACAAEHDFDDHB,True +580,23.0,6.0,7.0,14.0,17.0,10.0,20.0,6.0,EEAEEHDHGCBEABGFBGEACAADADGADHCGFGGEHGAGGDEAFEAGEDEAAAAAAEGCFGDFGDEGAEAFBAHBAGDFGDFECCECGDBAAGDEGHAFDDF,True +581,26.0,18.0,18.0,18.0,15.0,22.0,19.0,23.0,FFFAFECGECGHCGACGACAFFGHGEHADHFDHBDHCACGABGAFHHGAFGABDABAFBHEBAEAHFAGCAGCGFAEDGHFGAEBAEHDDHBDFAFBHDBFCHEHHGFDDBAEHAECAHGHECDFDDHHBFHBFCBADFFDCCDBCABGEBCEBDEGAC,False +582,21.0,17.0,16.0,25.0,18.0,9.0,13.0,8.0,GAHDCGBCBACDDBDGADCEDBFDAFDADEAEEBEHADFAHEGDBGFHGHCBAAHDEHEEACDACDECFEAHAGGAEGAEFADBGEBGCDDCFDABDCCAGBADBDFFDGDECDBCDCCEEBBEBBA,False +583,3.0,13.0,7.0,7.0,6.0,7.0,7.0,14.0,CGGBGGBGFBHBBHCAEBHEBHFFFDFADCDBFEBGCBCHHHDHHDBHEGDECBAHFDHBEHCH,False +584,19.0,16.0,23.0,16.0,22.0,21.0,12.0,29.0,CGHFFHFFHCFGDFDEECFDCDDABFAEAADFBEAECAEGAECHHCHAEHFECCHGCHGEGGEDHBABFAHEEBGEHHHBHHCDBCDBADCACABCBCCBHBGHDFHBFHCABGDCFCCADHAHHEHHEHFEABEGGAFDFEEFEAFCDDEHFBHCHF,False +585,5.0,14.0,11.0,11.0,4.0,5.0,12.0,10.0,DGDBCBFGBDAEHACCEHCDCCBHFBHFBHCAHGGGCGGBGCBEDBGBAGHFCHDCGDBHABEFBDDBDDHG,False +586,11.0,24.0,18.0,11.0,8.0,6.0,17.0,13.0,GBBGABCCDDEGDFGAHEAHCAEGBEGAEABEAHHCHBBHCBHCBGGGGGGBHCBCCBDDDCGGBEFFADFGBCABGBBDCBDBHABHBBHFBDFCHCBGDHACCCEC,False +587,14.0,18.0,17.0,13.0,15.0,17.0,25.0,21.0,ECCAFEAGBAGCGFCGHADHEBGCGGCBDCGABDHBEGBCGHHGFHGHHGHDGCACAEHBBBABGFHGFDGFDBDGBAHHGGBCEFCFHHFEHFEFFAFFAGFCHCHGABCHEFHCFEBDEBDACGAEGEEHBBDEDDGD,False +588,13.0,15.0,14.0,18.0,15.0,14.0,13.0,9.0,EFAHGBHGDHGDCADGDDEEEECFACDGDGHCCFCEDCBHFBGDBCDBCGFCGBCEDDEAFEAECAFCDFDDBHABHFEEBBHBACBADBGDEABFGFFADGAGFAEFEBH,False +589,12.0,8.0,10.0,3.0,6.0,15.0,8.0,10.0,FDAFCFFHFGHFGBFHAHAADACFCCBBCBBHADHACFAHBBCGGEBECHGAHEAEEAFFFCFFHGFCGAEG,False +590,17.0,15.0,7.0,14.0,11.0,14.0,9.0,6.0,HEAFCADCHBHAFEFFEDAAFBABCGDDFAAGDGDCBEBFEBDEBAEAEBAEBAFBGFBHFCGCHGHDGFAAFCADBDDBDDGFAGFABEDBE,False +591,10.0,3.0,10.0,5.0,10.0,14.0,7.0,11.0,CFGCFEAFHGFCGAHACGFEADCAECAEBEDGFDHFEHFEHBEHFECFAAFHAECDHGDBFHHFAHCCFG,False +592,19.0,16.0,12.0,22.0,13.0,29.0,15.0,13.0,GHBEBBFBGFCCFDDECDGGDFGAFABCHFAFFABBCHBAFGHFBEFDEFGEFGDDGDDACDBCEAFEACEDDFFAHEAEDDHHFFDFBGFHGDBFHECCCFBDEBAHFAEFAGFBGDHADAFDAFDAFHAFGAGCHDB,False +593,7.0,6.0,8.0,6.0,8.0,9.0,6.0,6.0,DCHBFDCFDGACEACBBCBGHAGHFEHFEHDEGAEAACGFBFCHFCAEDFEBEDGF,False +594,30.0,31.0,17.0,16.0,20.0,23.0,18.0,23.0,ECHGCHGBBGFBGABGCDGHFFBFABDADAFEAFEHGBAABEABHABHACFACBEFADDADFBCGHHABFEBEGBCGEHFEFEBGEHGDAFBHDAFBAHBAHFAFACGDCHDCHDGBEBHEFEAFEDHACEBCFBCHBFHBAACFCBAHGHDDEADHAECACGBBABAFBFEBGEHGD,False +595,9.0,14.0,16.0,12.0,7.0,14.0,15.0,6.0,FEGFGGFDBAGEFGEFCCHCBEFBCGACBACFCCBCAFCAGGFFCBHGBHDBADADHADGBDGBDEBCHFCFCCGBDGDHEDADDFEBGGCFB,False +596,26.0,34.0,20.0,24.0,21.0,26.0,22.0,25.0,FEEBEHGEHEFHEFEEACGABBDHDDHGCGFDACBGBHGFHDADCFGCGBDAHHCFHGFEEFEAHEBHGBAABDABFAHFHDDADDFDBGGBFHBAEBAEBAHBAFACFADADDAGGBBGBBCCACFFBDFHDFHDBCBCABAECDFGDGHHEECCAFDBDEFCEFGDBBHBBHGGHFBHEGGEBCABCFBCFCAHBA,False +597,16.0,18.0,17.0,23.0,22.0,17.0,16.0,28.0,EECBEAGEDFCFADAHFCHFCHECDBGDBHDCHAAHDDBDDCDHHFHBAHBEHDEHAFHAHHEEGEEGDEBDEDDHBEBGEHGEHCACFHBDBACHECEBCACCGCGGEHHDHBFGEABFDFFDGFAHCGHCFHBGHGDABDAFGBEGFDFBDEHFA,False +598,14.0,9.0,12.0,11.0,20.0,14.0,7.0,8.0,EEAFAGFHFFBEAGHBCFFFFDFFBAFCEGEEGDCGDCBAADAHFFHAGHACDECBEDBEAACDGCEACHDDADBECBECHEAHFDEEEEEEEBC,False +599,31.0,15.0,28.0,34.0,25.0,28.0,16.0,23.0,EADADBADCDDCGEGGEAFEFGBDDCFACDECFECFBCHAEHABGFCCAECDEDGCDGCDGEAHDBBDBACEAFBFEBEDBEBEEFGAAGADGDFFCEFAFAABDFHDFHDGCDGHDFCDFHEFAEGCFDAFDAFDEFHBCDAFEECHHDDHDCFFAHHHHCHADEADADBADBCGCCHFAFCEHHAFHAHHAEGACCCH,False +600,10.0,11.0,5.0,10.0,8.0,10.0,7.0,10.0,HBFHBHGFGEFGEFAAFAGFGEBBHBDGBHHAHCDHEHBEAFDDBBABDFDCFHEBCECCADGADFADAED,False +601,1.0,4.0,4.0,5.0,1.0,4.0,5.0,0.0,EGCDDCBDCFDFBGBDGCAGFBGF,True +602,4.0,2.0,2.0,6.0,6.0,0.0,2.0,3.0,EDEEBAEDHEAGEABCHDCDDADGH,True +603,22.0,28.0,15.0,26.0,22.0,27.0,16.0,24.0,EADBBCFGEFEAGAFEACAHCDBABGHBHAEDGGDCGFBBFHFCEFCEFEDAEGEHGABFHBFDBGDBABGGCGBCGBABHAFDDFBDFBGFHFCHFCHFHECHDFFDFABFDBHDFDCFDCABHABHEHADCDDCDHFEEDAEDFEBHHAFHGBHBBEEBDHDHEDABDABAEGEEHAF,False +604,21.0,11.0,14.0,19.0,11.0,12.0,18.0,29.0,GHHGHHAHADHAHCGBCGBDGBDHDFAABAEHFCDDAACAFHBHHDEBEGAGGEBGEHDEGFGGCHGDBDHHDAAAACFACFHBHEAAEHADHGCHGHDBCFHEFHEFECDDHFDCGDFGAFHAHHCHBCGDCAD,False +605,9.0,11.0,6.0,10.0,8.0,6.0,9.0,4.0,DCGDAGDABEBBEBGEBGDDGHAHHBCCECAHAFFAEDCEFFEDCBGBBGEGDFGDBAAFDAB,False +606,28.0,22.0,23.0,19.0,24.0,23.0,22.0,23.0,GHDEEDGFDEHCEBCEBAGAAGEGGEGABFHGFAGAHGDCCDHFBADBDDBCDBFHFDGEEGCEHFFHCCHAGHABEACCACDFEEFAFGEFBCGBCBFAFFBFFDGEEGBEHBHHDCACFHCACAABAABAECCDFHHFHBDAEFHEFEECGFBGCDGEHCBGDBAAAHCAHDEHDBHABAAG,False +607,13.0,16.0,14.0,14.0,17.0,12.0,10.0,10.0,BGHBGADGDDGCECBEDBECAECGECGECFACFBEEBEADEDHFAHAAHBFEBHDCFDGDBFFBEGCAFADDHCABDACDABDHGFFGEEBFEBABCEFEHCHHCB,False +608,9.0,17.0,16.0,8.0,12.0,15.0,18.0,16.0,BGGGDCHHBHGBEACEACEGCEHFHCBGBBGFBGFAHCDGCFFCFGCBGBBGBFGBFAHFBGFBABCEGCEADHHEHHCHFEGEDHDDCDABGHECCFCFFGBADEAEHFH,False +609,34.0,28.0,25.0,20.0,27.0,20.0,18.0,15.0,FHGFEGEBBEGBEGHFHDFDAAEAAEDCFDBFEFCDCDDGEAFEADBCCACCDFHHBCHFEDABBABBABHAFGACGEEEACCACDDCBFCDHBFGBAGCGFADEADGABFABAGEEEBHBFDBFEBGEBEBHCCDCAGCAECAECAFCHGEEBFEAGEDECAHHABABBABDFDAHCABCAGHAGA,False +610,27.0,20.0,29.0,19.0,16.0,20.0,23.0,16.0,EDGGDCDCCDCCFAHFACFEEAAGGAHFADGADAEDCEACDAGDAHDCHFAFFHCGHCGDEBAEBAFHADHCBFBBDAECAECACGGGGFFCDGBHGECFBABDABGECGEFBFCBHDBHAHGACBAHEACCACHBHEFCBDCGDBGCBGHGCBFCADEFBFFGABGCEF,False +611,22.0,21.0,24.0,24.0,11.0,17.0,21.0,18.0,CGCHDBGDBABGACGAEAACCDDCDGCDGFDEHBABFCHACHAFGDEBDEBDABHGBCFBCBAHBDFBHFCFECFECGAGEAEBDGCGGCHGDFGDFCFBHFAFGAGHHFBHDAADCAHCAGEABCCBDDEDDHCCAAHFHHDADDBGHCGBFFBEDG,False +612,15.0,15.0,16.0,7.0,8.0,15.0,11.0,10.0,BBGABCABCFCHFCBCAGHHFHFFBFAAFAGBAGDEFFCFECACDACAFCABEEGCEGCAGDBCHBDDFDDFAFHACBGBHGBHCEEEGHCGFBHBA,False +613,1.0,6.0,10.0,13.0,4.0,6.0,8.0,9.0,GCDDCDCAHCHEDFDCCDGGDBHDCHDBHCGGFGCFGHFGFFHHCBBEEBDEDDBDH,True +614,10.0,16.0,11.0,12.0,14.0,10.0,10.0,10.0,DECEGBDAEDAEGGGHGAAEBAEHDGHGEBCHBCHBFEBCBFCBAHEDFEDFGAFDCFBCFBDFBCHCCHDHBDBBABFDGEEEDCEGAHBAF,False +615,1.0,1.0,2.0,4.0,6.0,3.0,0.0,3.0,HDEHFEDCEABEHFEDDECF,True +616,10.0,6.0,9.0,12.0,6.0,14.0,6.0,4.0,DFHDFBBECCFCCFBCDGAFFABDAGEADBDDACECFECGAAGHFHFFHFFDGDAFDEFDEBDAAGC,True +617,6.0,1.0,4.0,3.0,5.0,2.0,0.0,4.0,BDEHDAAFACHECHECDEFHCAAEA,True +618,22.0,16.0,36.0,14.0,21.0,16.0,20.0,16.0,BBGEBEHHHHHACECCGBEDBCDHHAHDCHDCECAFHAFDAFCAECGCCACCGFFDEGACGCCGCEGCGGEGACGACBDGGDEAEBAEGFECAECFBGECAEFFHBCCBCHEFADFDECDBCBFDHDECDGAABHCFGCAGCFGABEABCABCECCFFAHH,False +619,26.0,17.0,24.0,18.0,27.0,15.0,23.0,23.0,ADFABEBGDCGDEAEHBHDBCGECBECEEGAHGCCECGFCAFCHECFACBAHBACBAEBDEHFEDDEHGHHGHHGAHGAHFADAAGEAEDAFAADADHEGHEGHGBHDBCEECGFCHEBHBBFAHDCGAEGEEGECGHCFCFGCDDFDCBCFEAAAFEAHGBGDCDBEFCHAG,False +620,7.0,2.0,1.0,9.0,6.0,2.0,5.0,5.0,GBEGBDDHGCFGDGHEEHDEFAADAAHAAEAHEDDDD,True +621,16.0,26.0,22.0,21.0,29.0,29.0,17.0,19.0,EAFBDDEEGGEGGEGDFBBFADADCGDCBCCHCDDEDFEDFADFEDFGBFHBECAHCDBCGFCFECEEHAFHAFCGFBEHGFHEEHFEBCGBGGHABFGDAGCABFDBFDFFDEFBBBDHBEECFEHEACBFBDFHAHHEHHEHCCHGBAEBDCCEEFBBFAFCBDCBFBAFEACEGHE,False +622,7.0,7.0,8.0,11.0,8.0,4.0,10.0,8.0,DAGDCGDHGDACDBCFHHEGDEDEFHCBHEBHFDHEHBCGGEGBCGDCFDGEDCAABAABEAG,False +623,28.0,16.0,21.0,17.0,19.0,16.0,21.0,15.0,DEHGEHCAACGFGGBEFBEGGGBGFADAEDADDCCHGGACAACEBDGFCBDAAFBCCCCCAEEEECHDCEDAEFAHFABFACFGHHBEGCEFBAHCDHDBCEBCEAHAAHAABEDGECGFAGFABFAHFAHEAHDHBFCBDDAFDAGBGGDGG,False +624,3.0,1.0,2.0,2.0,0.0,4.0,3.0,0.0,GAAFDAFGGFCDFCB,True +625,2.0,3.0,2.0,8.0,3.0,1.0,2.0,1.0,DHDDBDABEGDDGBFAEDCEDC,True +626,25.0,22.0,16.0,18.0,24.0,24.0,24.0,13.0,EBGFHAFDBGEBGEFGEDHADHADAAFCAFCHGEAGACBDGBFBDFEDGEHGEHGDHGCFCEFBEACEBHGFHEBHEGFEBAECFBABCACCABAEDEDGEGCABEEDGEAGAAGCFFDBCGHAGCAFFGFDAFHFFGEBBBHBDAGDABDBDGBAFEDFCAFCEF,False +627,29.0,21.0,28.0,24.0,31.0,21.0,20.0,20.0,FAHFBGFACEAEHGHHCFHGAGFFCCDDBDGBDGBDBHEBHECCEHCAFEGEHGEHGEGGBCABADDACDEEBCHCGAAEAFCABCEBDABEABCAECAEAHHFCFGDFHDFHBCECEDCDFCDACEFBEDBFDBEBEHHECCEDAFDGFDHEEHEGHCDDADAAEGAFADCGCGFEGFEABACFAEBACBGDA,False +628,12.0,14.0,20.0,9.0,14.0,5.0,7.0,10.0,BAHEECEFDEACFADDABAECEHFDHCCCACBAEDHEBHEBHFHCFCCGCDACAADGEGCCGCGBCBBCGBCEBEHBEDCADBEGBCABHH,False +629,5.0,5.0,7.0,3.0,4.0,2.0,2.0,2.0,EFAECAECHGHFCDABDBCDBCBCABCGEA,True +630,23.0,22.0,17.0,29.0,22.0,31.0,12.0,12.0,CCDECDBBHBBHBGFACDAEHBFBGFCCEHGEHEECEFDDFDDBEDBAFEHBDHBFFFFFFFAFFAFHDFAEFACFCCGAFAAFGADGADFFEBHEGEAAFBDGBDADDAGEACECCFBBEEGGEBDBBCAADFEDCADFFDFAEFBHDDDDBCCBFGDAEHEHDDAD,False +631,27.0,22.0,17.0,34.0,24.0,29.0,22.0,24.0,FFDCFDCHHBFADFAGECGECGBFBAFBGGACBFCBACHEFEEFBEFEEFCBAEECEHAEGAEFACFADFDBFBHHDHAFHADDGHHEHDDGEBEEGFFDDGEDGADGBDHFDHFBHFHAABAADHAEHBHGDFGEAADDFDCCDCDDFBAGCFDCGDHBDHEAFDGBEGBADEFGCDBADGADHEHGFHBDHADGACB,False +632,14.0,22.0,9.0,14.0,13.0,13.0,20.0,23.0,BCFBCFAHGDHGAHEDGEBBCBHEGHDDDBAGBAGCECBBGBDABAGHDGHEFFBHEEEEHDEBDEFAAFAHGDGCDAFHAHGADGAGCDDHHFHGFHEBHBGHBFBBFGBFHHFAHCHHBECBGBGG,False +633,24.0,22.0,20.0,25.0,23.0,16.0,19.0,23.0,DBBDHHDHHEFEEFGABGFEGADFACHGEHGEHAFFAHECCEACEBBHBEFADDDDGGHGGHAABCFDCFBGFAECDGBDABEAFECFEHBAHFDBFDBDEFCBCCGDEACAAGBBGBDEAEAAGAAHBGHACCAECGCCDCGDEHAHGBDDEDDHDBHDHHFCHDBHEBCE,False +634,17.0,21.0,22.0,24.0,23.0,23.0,16.0,18.0,CBHDBHCEHCHBGDBECHEHFBCFDFBDFCGFCACCACCGDEAFGADEADFCDFBAHAGHGEBDDBDEBDHBGBDAEDBEDCEFCEFHBHCGDAHAAEDEEGGECBEHDGDBGEHFEFGEFBFFAFFCCFECEDHEGCAGBACFDGFDHFBABHADFBEFHADC,False +635,16.0,6.0,8.0,5.0,5.0,8.0,8.0,4.0,FFABFACAAFAAHAFHCEACEABFCDGCFACABGGDGCABAEBGEAGBAGHACHFEDDDG,False +636,0.0,0.0,0.0,2.0,3.0,1.0,3.0,2.0,EHGEHDEDGFG,True +637,9.0,16.0,10.0,10.0,13.0,11.0,8.0,12.0,FEDBEDBEBBEFBEHBFBFCBEGBAGBHGHDBDDEGBECEFHDDHCFHGBHEBCGBEFAACBDEFCGFAAHAHHFFAADAHDCHGCECC,False +638,12.0,9.0,9.0,12.0,9.0,15.0,8.0,15.0,EFGFDCDAGDHFCBFEAFHACHBGADEEHEFGEDHFDGDDGAECCFHBFHBCACHACHACFAFBGDBGDBHBHHBHDEHDAAAEFFFHF,False +639,14.0,20.0,11.0,14.0,9.0,16.0,14.0,14.0,BFBHEBAEDADCGDAGDAFBHCBACBAEAHHCGBCGFCGAABFCBFGADBFFFDFCDFEAGGDHDDEFFHGHHGHHEFEBHBBGDBCHBEHBEFBCABDGGDCGAFHBFABD,False +640,8.0,6.0,17.0,2.0,13.0,12.0,17.0,7.0,HCFFGFCHCCACAADFGBFCFFCGFCABGBEABGCEGCEGCACCFGDGECGHCAEGBEGEEGHBGEAFEHFEHGHGEECCGF,True +641,14.0,17.0,15.0,14.0,30.0,13.0,21.0,15.0,BBGEDAHDBBEHBCBEHAEGAFGECGACGADAFGFFGFEGDBCCBFCHDHABHEBGEDADDHEGHBBHEGCGCHEEHEEHGEHACACCEGCGGEDGFGAFDBFCAFBAFEEEHGEGFEBEEBHEFDECEEDEBGEDCAD,False +642,26.0,25.0,28.0,26.0,13.0,16.0,19.0,13.0,EBDECDGCAACBAHFACDCCBCDDHDFBDBDAHGAHGBHGBCFDEADGADGHFGBAHBCCDHBDFDFHAEEFDCGGCFCAFGACGCCFADBAEBGBGGBFGDFBFCAACAACECBBHBBGABGFCAHCDFGDCCEBCDACHBCAAEDEEDFEHEDABDACDAGDBB,False +643,14.0,19.0,17.0,9.0,14.0,22.0,18.0,8.0,GCCFBFFBEABEHDEBDGBDFAHFBHCBDEBDGBDHHFFGAFGCGHCACFBGGAGGFEGFCAFCADGGCFECECGFAGFAGACHAFHDCBBCBFABFEBCCBGFEAECDBBFFBAEEEEFG,False +644,15.0,27.0,16.0,22.0,21.0,27.0,27.0,18.0,EDFEFFDFBDGBEGBHCFHCFHFAHFGFFEHGEBGEBGABGCGEBGFFHADEDGEBFABGAEFEGFGGAGFDHFBHCBADAEFBCFCCHDFBEADEDBBBGDBDCACCFCEFDDFBHHAGHGGBGBEGCFCBFEGDAGDEHCEHEBHEBADHDHHDGCDGBAFBDCGAFGDBB,False +645,14.0,11.0,10.0,13.0,16.0,12.0,10.0,15.0,EEHEEHGEFGEDEDBGCBHHFHBFDBEEBEBAHBDGACGADGHEHHECDFHDFDFAEFACFBEBHEHAGDCHDCDGCFAAFAAGCDGCAAAHHFBCDBAFE,False +646,3.0,5.0,2.0,4.0,7.0,6.0,2.0,5.0,EEDEFDFHDFHGFHCBHFBEEEABHABFDBGCEA,True +647,17.0,19.0,20.0,19.0,12.0,18.0,17.0,19.0,HCFBAFBDFDHBCACEAFHCGGCAHBHHBHFECADGBGCDACAECGDCFDFEHBABGADGACGBEFHGFBDBCCBCFBDFADFGGFEGFHGFEBDDBDDADBFGCFGHECHCHHGGBECECCEBDEDHADHADHAFHAHAB,False +648,10.0,10.0,6.0,7.0,5.0,10.0,7.0,10.0,CHGDHGHAECAEAGBCGCEDFBGFCGBCFBHAEAFHDFBEHBGFAFFDDABDABDFBHFHHABHA,False +649,23.0,19.0,18.0,23.0,11.0,22.0,22.0,16.0,DFGDAGAEGAEDABBFDGADBHHAEGECAFDAEDACGBCGDCGHCGBCHEGACCAFDBFHBGGGDBGBFCBEGFHAHHCEDAEDBBAFAFFAFGAHCHCCDCCGBDEFHFFDBFBCFDCDDAAAGDEBDBBHBFHGFHFFHFAHGDGGDACDAF,False +650,4.0,5.0,4.0,4.0,6.0,3.0,2.0,5.0,DDHGDFGEFAECAFCDBCHEEAEEHHBACBHBB,False +651,29.0,15.0,14.0,25.0,15.0,16.0,23.0,19.0,GAFBABHAGGACGAGGAGHABDGFCGDEGEFDFACFBDAHAAHCGECDHFEHCDDEDDECGFDDFEDADAFDBFDBEGHFBAGBADBCDGAFFCEDEHAAHAACGAGDFDDFDAADCAFHBEHGEHGCGEBBHHBCDBCDHEBAEGGHGHHAAHAA,False +652,17.0,19.0,21.0,19.0,20.0,33.0,24.0,19.0,EBHGBHEFHAFCFFEAFEADEBHCBFCEFDEFHBGHGFDGDAHEGFEABBBBFBBFBBFAFEBDHBCBCGFEHACDCFDBGHGEFGACCFFFFDADGFDCFGEGHHGEHFFHEFHCFAGFBGCCGDCDDCGECGHAHEAGEDBCDEHDGHFGFCCDAAFAAFGAFDCGECGD,False +653,4.0,2.0,1.0,5.0,5.0,3.0,4.0,8.0,GBFEDEDGEDEADHGHHGHHDBHAHEFHCFAA,True +654,20.0,23.0,22.0,29.0,18.0,18.0,13.0,18.0,EDEBAEGHHFAHFBDDBGFBGDDABDABDADCCBBCEHGFCGFCDEHDFDGHDCBDHFDCBHBFHECCADGHGGEGBCBACHAEGEEFDEHDCHBEHFDBFCEACFAEDAFBGDBDDBDDBFDCFDCHDAACAABACGFCACDHHAFBAFBHEDCEBEEAC,False +655,7.0,8.0,11.0,11.0,11.0,5.0,11.0,11.0,CHBCHDCHBAHBCGDEGDACDEBAAAFBEFHFBGFEDEEAEEGDGGDGHDAHDHBEEGDECCBHCGCCGHCFHDG,False +656,23.0,22.0,23.0,10.0,19.0,19.0,24.0,14.0,FCGFCGAAEBHECHECHCGABAAFFEHBAHBCBBDEBEFDFADFGDFACFAFAHFBCEACECCDGBFEBFCCCCEGAAHAGEBGABCFBAAGFDFCEABEABECDGCGAHGHCCHBAFBHEEHCGBFGBAHBGGEGGEDBEDBDFGGGGGGACH,False +657,17.0,18.0,13.0,17.0,9.0,17.0,17.0,24.0,BDHBDGBFEBCHBDFBDHBAHBHHAAGABHACFFHHBBDDHHDHGFCFFCGHHBAHADGFDCFHCHCCBDFFGAFGAEEAGEHHBGFFGFAGHADHDCBDEFDECGAGADCAGCHGEHBEHFDABDGBCGAE,False +658,8.0,8.0,5.0,2.0,2.0,4.0,5.0,8.0,CEGBBGBHCFHBHBBABGEBHHGCFAAHADHAHGACFACFAD,True +659,34.0,21.0,21.0,17.0,21.0,20.0,30.0,25.0,HAFHDCDEGEEGAAGBGCBEAGEBGEAHCAHEAHCAHAAHFBHECECABCAHGGFGHHGEHDADFACFACFCGFCGFBBFAAHAAHBFFDAFDGFCAEAGFAEDBGBCEEFFFDEAGGADGCDFHGGHBCABCABCABHDGDGGEGGEGHEAHBDGBHHBCHDFAECGDBHAGHADABBACEFHBDEGC,False +660,14.0,30.0,12.0,19.0,8.0,11.0,20.0,13.0,DEBHHDCGGHGCHBFBFGBFDDFDDGDGBDBBABHDBHACECCACEABBAEBDBBGGGCGDAHCADCABHEFHBFDCDCGGFBGDBDBBGGBCGBEBBEBBHHBHFFHFAADGBBGBGADDFEAAGA,False +661,11.0,26.0,15.0,26.0,16.0,14.0,18.0,26.0,FEBHBBCBDCEDFABGAGEABBHBGCDGFDEBBEBBDBEGBEDDHHDHFBHEBEEGAHHDHHCBHCAHDHCAACEGBEGBDGBHBHDFHDHDFHECHCHEAHBGCFCFHDDHDDFDDAGEGGCCGDFGFAGFGDBBBHBDHFDACDCHFGDE,False +662,5.0,2.0,4.0,1.0,4.0,3.0,0.0,4.0,HCDFCFHCACAEEAEFBHABHAE,True +663,14.0,22.0,18.0,13.0,14.0,22.0,18.0,29.0,DHBHHBGHGDDFFFCBHCBFCHGCGGHHHHABCCBAFAEGBBDBFCFECFADFHBCHADBADGHDGCDACFHBFGFFBFGCFAAEACHAFHEEEEHGEHAEBGBGGBFCBFBGGBGAHDHHBECEHCHBFECFHAFHDCHDEHDEHGFHB,False +664,22.0,13.0,19.0,20.0,21.0,19.0,24.0,26.0,AACFEGGECAHDGHDGDBEHBGDGGCBEAGEFEAGBGGBFFBGGGGDCEEAAFFAHEBFEFACFECEABEFHGFHDAHCBHCFGDFHDAHGEHEAHEAGCCCHDAHFCEFCDCAFCGCHFCHGCHGCBGFBGHHDAHEAHDHHDHEEADEFDHADADDHDBADB,False +665,19.0,16.0,20.0,18.0,23.0,17.0,22.0,24.0,DAACFCEFCEHBFHAEHDBHBHABHABHAHCCGGCGCEDBDHBACCCCCAEDHEACEHEDGECGEFGCGDEFHCAHADFDEEDBECEACDGEDGFHFAEFAGBHHAHHDHAGBBFCGFEGHBHFDEFDHFHHABGABGEDGEDGEGGBCEBGDFGFFGA,False +666,21.0,15.0,10.0,14.0,9.0,13.0,18.0,9.0,ACFGBACCACCADCDGADGADGHBABGDFEDEGAGFADADDBEABDABEABAFBAFBGFGGACGBFEBFEHFHGACGCFEDGBGABCEHFGBAGFEDADBAFHHGHHDH,False +667,8.0,7.0,10.0,12.0,11.0,15.0,18.0,9.0,FAGEGGDGEAGDFCFFHBFDBGDFGBAGHCGFCDBCGBDFHGFHEACECCECAEFGCFGHFEDGHGBHFCHAEDAEDGDFGFGEBEDHAD,False +668,10.0,9.0,8.0,13.0,5.0,7.0,10.0,7.0,GFDGECCECCFHAGBGDBDFADGEDAADAADAADCGBGHBHBDHFGHFAHFACDEHBEBDDCGGCDFBB,False +669,7.0,12.0,7.0,12.0,9.0,2.0,15.0,14.0,HBGHAGHEGBCADABEEHFCCGHGGEGGCDGCHGEDGDBADBHDBGEAGAACEDDFBHBBHBDHBDHGCHGHDEEBHD,True +670,0.0,5.0,2.0,3.0,7.0,4.0,3.0,4.0,FGCFHFEDBHBBHFBGEBEEDEEGEHCD,True +671,5.0,12.0,12.0,3.0,8.0,4.0,5.0,4.0,BBCBBAECHCGHCHFCFCCBDBECBEBFEBCGHCEFGGBAGEAEEACCBDABD,True +672,11.0,18.0,12.0,10.0,18.0,18.0,25.0,17.0,AGBBGFGCFCEFCBHCADEBHCHDEBGGGGGAGGCGFHFBHDBFFAFHAEHFEFFAGBEDHHHHBBCFHAFCGCCBEHBEHGDBFEAGEHGEAGEAGEGDBGDCGDGGDFHEFEBBCBAGBEDHEFGEF,False +673,9.0,13.0,14.0,18.0,14.0,11.0,8.0,15.0,CGDBHCCHGBFGAFEEHEHCEHCACCADCDDCGBCDBHDHCBHEHABHEEGDFHDGACBAGDFEDFEDECDBDHFEHBEFFEBCEBDABAAGFHFDDFDDHB,False +674,8.0,13.0,7.0,9.0,11.0,13.0,8.0,11.0,GHHFHFCGFBEFDEDDBFDBAHFHHFCHEDGEHGCBDBHHAEGAEAAEBAGBAEFCFGCFAHBGEFECBCBBDBBDEFDF,False +675,1.0,9.0,5.0,1.0,4.0,4.0,4.0,4.0,BECBCFDGHHBEBBFBBFBCFBHGAHGCEECG,True +676,7.0,7.0,1.0,4.0,6.0,8.0,6.0,3.0,ECHEDFEAHHDFABGEBEABEDGFAGBAFBAFGFGGFABFDB,False +677,14.0,18.0,19.0,11.0,14.0,16.0,16.0,25.0,EEHFECBGCECHDBHGHHGHHGABBDFBDFBAFHAGDABCABFHHABGAEGDBHHGHFFHDFEDFHFGACBCCGCAAFFAHACDGCDBCHBFGBHEFHAFCCEBBDHCHFAHEGHEGCEHCECCHGEGBECBD,False +678,9.0,12.0,6.0,10.0,11.0,11.0,13.0,11.0,CDEAGGDGGCGBCGBAGBGEBDCAFGHFGBFEHEEACFAGFDEFGBHHFHHEHFCGDADHHDHEDAADFBFBBFBEEHEABBD,False +679,27.0,20.0,25.0,20.0,31.0,18.0,23.0,23.0,EFHEDHDDBECBDAFEEFEEAADGGCGEBGADEECEEFEECAFCGEGGBFCBFABGACDAEHBHCFGCHGCHGCFDCBHHBEABAHBABAHEAHGADGCCFECDHDFAGECHAFBADBGDBCABHADDBHCEHCEHBFHGFEEDCDHCEECGCDBCAHGHBGEAGEAFFAFGAEEAFAHGEHGDACD,False +680,27.0,26.0,27.0,28.0,20.0,19.0,14.0,25.0,GDCFDCFHCBAEGAFACFAGFDBEABDBCAHCGFFFCFBBBADBGFCDACDGDDHCEHAEHBFGBHECDEGAACBHCHEAHEFCGACDBHDACGACHAHHAHDEHFCBBABBABCHBFDCGBCHBCHFDHEEBDEHEEHGEFABHAHCAEDBCDBCDEEDCBDBHAFAGEADDADFADFDDHGDEC,False +681,3.0,1.0,1.0,3.0,4.0,8.0,7.0,1.0,HGFEDDABGFGGFGFFGCGAFDAFEEFE,True +682,15.0,12.0,11.0,14.0,15.0,27.0,23.0,14.0,FHFFHFCHGEDCEDGABGDBGFFGFHGDDFFDGCHECAEGEBCEFCEAAAAGACFAGGGBEGBFBAFBAGGAEHAEHBDGGDFDAHGGEGGHAFHGCEFDBFEHDDBGFBCFAFFEHFCHFHDFCFFDEFB,False +683,3.0,2.0,5.0,6.0,4.0,4.0,5.0,2.0,GGFDFADFADECDCGBCGEDHEDHGCBCAEF,False +684,13.0,18.0,21.0,19.0,20.0,13.0,21.0,11.0,FEEGGCAGBEGFECBEGBDHBDCCGACGFBFEHHEHBCHCCFDCDDCEACEAFHHFCFDEBBGBDCBDBADEDEGCFDHABEDGEGFDCFECDEAHEDGEAGFAEAAGHADABDBGCGGBGFBDCBDGBCGECGHC,False +685,10.0,7.0,12.0,11.0,9.0,18.0,8.0,9.0,HDHAGFAFFAFFAEBDCBDBEAFEACEACDGDDGFCHFCBCCACHGCFFCGDEFDFHEFHDCBEHGEGFFDFAAFBEFCDGHBH,False +686,6.0,12.0,8.0,11.0,9.0,7.0,20.0,10.0,BCEBCDBHAGDAGDHGDEDAGDGHBEHDDFGDGEDAEGGGCEBCBGGGCHECBFHHGGFGGFGGHGAHFBBCBECBHABFDEF,False +687,12.0,20.0,16.0,25.0,15.0,20.0,20.0,33.0,DFDHAGHAEHBHBFCFFDHFDBGGCCBDABHGGHBBCBFCHCEEADDACDFCAFBHBHDBHFBADGHDGHDGFEEBHHGGHGHFGDFCDHEEHCECCHDBDAGDABDCBFHAGEAHEHHEHFDHFDHFDEFDCCGBCHEDHBDGEHGBBGFDHAHHFEFGG,False +688,3.0,9.0,2.0,3.0,7.0,7.0,3.0,4.0,CFEHFBFBBEDBCHAFABFEBEEBDEHFEDFHBGGBGA,True +689,15.0,26.0,20.0,34.0,29.0,23.0,27.0,17.0,GAAGDABHABEGDEBDFFDHFEHFBFCBGCBCCDGFDEHDCFDBHEBEFBEBCGCDGADBDGGGAAFCEDCEDBHGBDDBEDFFGFEHBEFFCAHCHHGFDDBCDBDFEHFGAFHFFDBEABEFBGFAGHGGEECCGABDDBEEBECBEAGCHGDHGDEDHFDHDAECAECDEDGEDEBCEDDGGDEGBCG,False +690,2.0,5.0,5.0,7.0,3.0,8.0,3.0,2.0,GFGFFGFDHHAEBCCBCDFCDEADFDBFDCEDBBF,True +691,11.0,14.0,14.0,3.0,13.0,5.0,13.0,10.0,ABGFGEEGEEGEHAHBCHBDDGHBBABACBCEEGECGECGHCABCABCHBEGAEFCCGBFGCAEFGECBFHACHACHDHBGBA,False +692,17.0,27.0,23.0,13.0,20.0,16.0,15.0,12.0,BCCBCGFCGFADAABEDHEHBEADCFFEFFCABCGBABBEGBADBABBFCACGEDBEBBGFBGHBGHDEHBEHBCHACHFGEECHGFHGCCGECGDBBDGAEADFCGECDEFEFCCFAHFEHEABAFCCECEBDDBADBABBC,False +693,27.0,22.0,19.0,22.0,14.0,28.0,28.0,25.0,FCDFEDBEDFECFBHAAHEACBFDEGDCGFFHHFADGABFAFAAGGBHFECAECAGCGBDGBDHBHCBHFEHBBAFAAFAFFCHFGGFHAADCCGCCGBHGDDGFDGBDGBABHAGFDBFGBHAEFFDGFDGCAACAGGHDGAGCDEHDHBGHEFCEFADHEHABHAFHEHHDBGGBFCBGCHAD,False +694,18.0,13.0,19.0,10.0,11.0,15.0,13.0,6.0,GDGHAABAGDGHFBFGBCGACGAEAFDAFDECHECACBFCBACBEBDGBFACEEBEDCEACEBBDDBGFAFFDCFECDHCACCGBFGHGCEGCAAHAAFCAFCFF,False +695,10.0,11.0,11.0,10.0,20.0,12.0,15.0,5.0,DBDBFDEGDBGEEGEGFAAEGDFCFECEEAEEBHGGHCGHCFACGHEGEEGAEFCEFBAFBAEEACCGFDBFCHACEDFADFGBGCBDEBEGBD,False +696,11.0,15.0,9.0,15.0,19.0,14.0,16.0,14.0,BBEABEBFEDFHBEDCFCEDEFDECCEFGFGBHGBCGHGFHEBDGBFGCFGDGDACDAFBFHBHGECGEHDEHBBFDEEDGEFCAAHEABEHHEAHEAHDAHDGGDBGFAGAD,False +697,4.0,10.0,3.0,4.0,4.0,9.0,13.0,9.0,EFFBHHHHHCADDEGDFGBBGHFGBBBBHBACEHCFBEGDGGFGGFGAFGAGHFGB,True +698,8.0,6.0,6.0,10.0,3.0,3.0,10.0,9.0,CHGBHGEHGAAGHDGDAGDBDHADHBDHDAFACBCFBGEHCEFCGABGAGDCDDH,True +699,23.0,20.0,26.0,25.0,24.0,29.0,20.0,24.0,CDBFFGEGEACCACDGBDCHACHACHBGDBCFBHFHHFHHAGHAGHCHAEEGCEHEEFFCDFDDFDFAAEEFEEFBEDAEDFGDFGDHHDBCBBCEBEABADDAEDGGGCEHAGBEFBCFDHFBEFADFDCEHFEHFHADCFDAFHAFBFCEDDBCAHAACGCBFCDHBFHDAGFEGFGGCCGCBBCAHGE,False +700,29.0,20.0,21.0,24.0,24.0,23.0,13.0,26.0,EBHEBHBADGAHAAEEACGAFAAFBBFCHDBHAGCDEBDCDDAHHBCEAAFHAFCABDDEDEEDFHDFCDFBEGCFGEFAFGCHGDHFFEFHEDDEADBACACEFCBHCEHCAAEAECAEBFDAFHAHGAHGBGCBDHBDABDHBDHADFGEBABHFCFFAHFDECHHCHHCFCGDEGEE,False +701,3.0,7.0,7.0,3.0,6.0,6.0,4.0,11.0,CEFCFHGFHBHEAHECHEBBAHAEECHCDHCFFCHBGFBDDBGHBGH,False +702,9.0,6.0,16.0,15.0,12.0,8.0,10.0,9.0,FDCFDCDAHDGHFAACBCHDEHEGDEDDFDDEGCGCDBCDEAFCBCCBCGACGACHHEEHADDAEDCECFECFAGGBBEHFGHEG,False +703,6.0,1.0,3.0,5.0,2.0,9.0,6.0,6.0,DABEAHCFGGFAGFHHFCFFHDFHDCGFFGDEGDHAAA,True +704,4.0,1.0,0.0,2.0,2.0,1.0,3.0,0.0,BGGAAGEADEFDA,True +705,18.0,19.0,12.0,21.0,25.0,19.0,18.0,24.0,FDAHBFHDCHACHAEAEEBDDDDDGFHHFEHDDBDAAAFHAGGAGDABCHGCEGCFDBGCBEFHFDHFHHEGCFABHEBHCAHBBHEAEEAEGAEDEBGFCDHEEHGEFGEFBDFEGFGHFDHFBHDBGDACBAFBDFEHEECBEGBDGAEGEHBC,False +706,17.0,12.0,10.0,18.0,25.0,13.0,22.0,21.0,AGEHCDCDAEDAEBAGGHGGHDCHEHEFCEABEGBEBHAGABHABFFGGFGAFGDBGAEDAGFAHEEBFFAEFBEHCEFDEFEHDCHDCHDGAEGAHHFHEBEEGABGDHGDHBDHDHGCEDCHFCEEDDEHDGAGGE,False +707,18.0,24.0,22.0,26.0,29.0,18.0,27.0,19.0,HFHHGDEGFHCDHCEGFEGBDCEDEEFFBFCAEBBGABHADAAGABFDCGCBHABAGHDEDEEHBAHDAGDBGCBDHHDBEEGCFGCHCFHBFDEGDHDFHAEDAGDFGEFCEGGEBGCCCCECGECGCHACEGCEFCDFBDFBGBEABECBEBBGAHGDHDDAABGGBEGAEBEDFDDFEDE,False +708,20.0,10.0,10.0,16.0,13.0,13.0,19.0,23.0,FFHDFHCCACGGGHEEHDGGAGEAGHAEBAHDGHGGHBGAGFCBDCDDADDCEHADDDHBAHBAHBGGAFAAGAGGBGFHAHHDHGEHEFHCFHCBACEDBDDFCEFAHFAHEAEFHFABEDHE,False +709,5.0,8.0,2.0,9.0,7.0,8.0,16.0,8.0,CGDAGDFHDGABHDEFFBFFBEDGGAGGCEGHHGADEFDEDHEDGFBGHGGHGGBGBBAHEFB,False +710,2.0,0.0,1.0,2.0,0.0,3.0,1.0,3.0,FGHDDHAFHAFC,True +711,11.0,11.0,7.0,14.0,11.0,15.0,19.0,23.0,DHDDADGHBGFBGHHGDGAHHHGHHGBCEDCHDHDECGGFDDAGBHGBGDAHBFFBFFCHFCFFHBFHEHHGAFGAHGHDCDDAGEHGEHBFHEGBAGFAEFCEABEAEEF,False +712,22.0,16.0,19.0,9.0,22.0,12.0,19.0,16.0,HDGBAGAAGFEEFADBADHGCGCDBCABEACGHGEABEAFGHFEHFGHFGHCGEFGEFHHACDAHFCGECEABEAEEBBABHEFEAGEDGBCEHDEADCBDABCHCCHBCGAGHACEACHFCEEBAEBAGBGFCC,False +713,10.0,16.0,20.0,25.0,19.0,11.0,23.0,14.0,FDCDDBFDGCEFFEBBEBBFDBHCFAAHGDHDBFFGFDACDAEDGEGGDCADCDDGEDGEGCEGDADCGDCBBHEBDECEHCEHGBHACEGGDCGHHGHDGCGGCGCDHHDECCEBEEDABBAGBGEAGEFDHFBHCC,False +714,7.0,8.0,11.0,9.0,14.0,8.0,8.0,14.0,AADAFBHGCCGCDHHFHBCHDCHDEHEEBFBAFHDGHDHHEAFEFCEGDHBEHCCFCHBBEDEEAFEAECGECGEGDBG,False +715,4.0,5.0,2.0,4.0,4.0,2.0,5.0,7.0,BEEHHBHHCDHCGEBGDBDHEFHFAAGAAGBDG,False +716,2.0,4.0,4.0,2.0,5.0,4.0,1.0,3.0,GBACBHFFEFFDHBDHEAEECECCB,True +717,15.0,12.0,19.0,9.0,14.0,21.0,18.0,23.0,DBHAHHEFBFAGHAGHAEHFEAAGCGHBFHBAHDCHCCDAGGHGFDAFEEEGECHCCEBGDAGCAGHGFACDHBDGBAFCFFCDFCFFCEGCBGFBCHBHAGHFHCBHAFHCFGCEGCEHFEBEEFFHDFH,False +718,21.0,29.0,17.0,17.0,19.0,12.0,14.0,21.0,BHBBDDFDBFDBDHADHBCABAHFADGBECCFDBADGEHHBBEGHEDHCHEBHBHHBEEBCABFBBFBFDAFABDGCEGCEGBEACEBBBBCDCHGEDEEGGHGAFGABGABAAHAHHAHGAHGEHCDCFDCFEEDEBHCCCACAAFABE,False +719,15.0,18.0,17.0,14.0,22.0,18.0,20.0,22.0,GGECFCHFHBEHBEDBEFBEHBDHBGAGFAHFAFECFDFHGFBGDEHECDGCAEFHEFBDGHDGDBGBBGBHGCCGCCGCHHEBBBBEEAHHBFEACADDACGCFEHFEHFAGAHGEHFAAFCHDCEGCEFDEGBHGDHEECAADA,False +720,4.0,4.0,3.0,2.0,1.0,3.0,4.0,4.0,BFBBFHBCHAHDAGEAFCADCGGGH,False +721,22.0,14.0,33.0,22.0,22.0,16.0,25.0,18.0,EGACBDEEDAADHAHBABBAEGAEGBHCBADGFBCFBAACFEEFEDHBDCGECHHHAGEAFECFEGFGAFGHCGAFGEFECFGCABEEGGDAGDCCHCCHGDEGBEDBACAHDACCCBHCAHCHDGHAECDDCDHCFCDAHHCECGECGDCGFGECCCFCCDDGDDGDFGBF,False +722,15.0,12.0,9.0,7.0,14.0,11.0,9.0,13.0,HFDHFEHEGDBCFBCAAHFAEFGGDBADEAFEAHEAHFBGFHEAGEDGBBABHGEHGECCABCEHDBADCFEEFAHFGHEAHACCABCBB,False +723,25.0,27.0,19.0,19.0,29.0,24.0,29.0,27.0,CHBDGEDBEGCHBAGECBACBGCEACAGCAGEFHHHGHAGAEDHGCGBBACHDGDAGDAGBFFBGFBDFEAFBABACDEFFEAHHAEHGHHBFABFACHHHEBGBBEABEAHEDGEDBFDCHDBGGEHHEGHFCHFHAFDAFEGGHGECDFGGBGCFEAGECBECBECFEAFEBFEHFEHBDDAEDADDFCBFEBFGHG,False +724,7.0,6.0,4.0,4.0,2.0,2.0,7.0,4.0,BACDABGAGDBGHFGHFCHAEGADGBEGBAADCBHC,False +725,13.0,14.0,14.0,9.0,9.0,11.0,7.0,5.0,ADEDDFDEGBCACCABCADGAFGFGAEGAGBAFCFFHBBHCBDBFEGAEDBDFHCEECEAFBAFHCFCCDBCABCABHBBEC,False +726,6.0,1.0,2.0,1.0,0.0,2.0,3.0,0.0,ADAAGACFACFBGGA,True +727,22.0,23.0,26.0,27.0,23.0,28.0,17.0,22.0,ECCBCCADCDDGGAHBAHFHCGHEGHCAHGHHGBEFCAFBAFHDFAFCCBACDGCBGHGEAGCDECFEBEEDFDFBHGBAGBADFEDAHDACDGEFEEHGEHFAHFAEBDBBEBFEDAEDHDDCFDGDABEGDFHBCBFDFFACFAFHEFHABDCCEABEFFHCFBFFBFCBDCBDCEDGDAHDCHCE,False +728,0.0,0.0,3.0,1.0,3.0,4.0,2.0,2.0,CEHCFCGFHDFEGFE,True +729,17.0,19.0,22.0,26.0,19.0,16.0,18.0,23.0,GFHGAGFACDAEAGFDCBCCBCBBGBDGEGCEHDDADHEDBADHDEFBEDBDGBCGAHHAEAAEBDGDGGDGABBECDEFDEFHCAHBDHBHGGDFFEFDCCDACBAHEABCHEEFCEFHGFHDEBGEBHHHHCFHEAHBAHCDDDDCGFCHFCHCCFCD,False +730,10.0,12.0,10.0,12.0,5.0,3.0,7.0,9.0,GGBHAHCBEBDABDCEDEGDCGDAFAHGAHDADDACHACGECADHABCCGCBBCBBHHBFDEHDBDFB,False +731,8.0,9.0,15.0,9.0,17.0,19.0,15.0,6.0,BHGBCGBCDBCFBCBACFAFEGFECFEGFGCEGCGADEFECHEDEEFFEFFGFFGDFCEGCACBAFADCGEEGDBADFAHHDGHGFEEDCEHFFBGEC,True +732,15.0,25.0,16.0,23.0,8.0,23.0,16.0,19.0,CCGCCHDFHDFABAHDHGDBFDHDDBBDHBGHGFDDFGGHEHABDFCHFAFCACBBDDBDFBDABHABGBEDBEDAFCFBCFGEBBHCBABGABGHBGHFGCFGCFGEBEFADCHFHFFCDDCHAEHBDGADAADGFCFFBFEBH,False +733,26.0,12.0,25.0,16.0,6.0,12.0,11.0,16.0,DDEFFEHBCBCAGCHGBHAAHCAHAHHBHHGGHCFDCADCADABFCCGAFDAGHCCCACFADFADAHBGBCFFDBCHAFAAEDEBAHBAEFAFBADBDDADCCCCCCCACCGCDGADGAEAHGH,True +734,24.0,26.0,16.0,18.0,21.0,14.0,24.0,22.0,HGDGADCHDBBAEBDEBDEBEEDECFBCAGCBCHGDBGEBDEBEEBDGBGHHFCDDHGDAGHADEBDAAHBGBAHAEEGEBGEBAACFHCFACFHFAHFAHFDHCBEAHEHBCHAHAEDGFBGDBGFBHBEGDGGACEACACBACFAGGEGBFBHAGHAGCFGHF,False +735,22.0,22.0,29.0,19.0,27.0,26.0,31.0,18.0,FACFCCFCAHCGBBDADAGDFEEFAEFAHADEGDACBFCBFBHGCGGCFFBGFGFBBHHBCAADGCDECGGCGGCAGCEGEGGDDGAGHAGHFCFCEGDGCFFBDEBDFBFEEEHEHBEAEEAEEAGEFDEGDBBEHGAGFDGEDHBCHGAAAAABCECCECCHCCDFHBFCEGEDGFBFCBFHBFHDHHCGEB,False +736,3.0,2.0,3.0,3.0,1.0,1.0,2.0,0.0,DCBDCBGCAGADEAF,True +737,25.0,20.0,13.0,20.0,9.0,15.0,15.0,17.0,BBCBGDDHBCECEDCBDHGDAGDAEAACDBCDAAHFAEFDCFAFBAGAGBABHABDABFAFFDDHHHHBFHDFGGHDCFGGHHGAAEAABCAGCBGCEGABCADEBBEFBDFHGFHDFHCFHAADEBDGADABH,False +738,15.0,21.0,15.0,20.0,23.0,14.0,16.0,14.0,HBDCBCCDFDDBDABDABDFDHHBEGEFGEFGECGECGECABBEGFEGFGFBABDGBHGBHCAEBBEBEDDDBHDAFCACCEBHGGDEDAEACFBFFBGFGEEHHEHEAHADFCDCAFCDEBDCDEGEHGAHAHEABE,False +739,6.0,4.0,7.0,3.0,11.0,9.0,13.0,4.0,CEEGFEGFDGBBEFGGDEDHCCEAFEAFBAFGACCAGAFEBFEGFGCHGEHGECGHG,True +740,18.0,18.0,17.0,21.0,22.0,23.0,24.0,19.0,CHFCHDGHDGBDCFEEFEDGHDAHDAECAFGFFHFCDEGAHBDBEDHEGAEGAEFBEHAEHABBAHFGECAHBFCDFDEEDEGDACBFHDFBGFGFEEFAEFCFBCHBDFAGGAGGAGBAGBEGEGDDGCDBBDBGEFGDDGHBBECHFCHCCFAGHCFCAH,False +741,9.0,8.0,14.0,9.0,12.0,8.0,10.0,8.0,HHAGBAGCACBHFBHFDEADGBFGCDABDCEDCEFABGECCEBCDGEEEEECECCFACHAEFGGFCGFDGDACDHHBH,False +742,12.0,15.0,13.0,8.0,14.0,16.0,4.0,12.0,AFFFBFFBCEAFAAEBHDAEAHBCHFCHBDHBFHBDEBAHGFHFBEGCFHCEAFEAHABDBEDEEFECHECGECFHCFCCDCCGBDABDBBEFA,False +743,10.0,6.0,7.0,8.0,13.0,10.0,9.0,5.0,AFAAEBGEBEECEEDFCGGHDGDFCFGHFBHEHDDAADEDDECBEFBECHCGAAFFAFEAGEAGFBGC,False +744,4.0,4.0,4.0,5.0,4.0,3.0,5.0,8.0,FHDHHGAHBHDDHGDAFEACEACEGGFHBCHBCGEDB,False +745,5.0,2.0,6.0,1.0,2.0,4.0,4.0,5.0,CHHCFFGFGAAGAHGCHABEACEHCBFCD,True +746,6.0,7.0,9.0,8.0,5.0,5.0,6.0,0.0,GDGGFGCEDBEDACDCCFACFCDABDACAACBEBBCFBFEEGBDGD,False +747,23.0,21.0,27.0,20.0,27.0,21.0,28.0,26.0,DEADBCCGHHGHDBADBADBEEBFEBEBGGCAEDAHDFDGHEAHEAGEDGEFGBAGHFHECBCAEEBEGFFFHHHDHHGACGEEDCADBAFBHGBAFBDFCDCBGHFHAFCCDCGACGAFGCEGCHBBDGCHFDAFGGGBHGBHAAHCAGEDCCGCCHBCHFFHEFCEFAAGACGCEECECHEBHEGEDFEDF,False +748,3.0,5.0,1.0,5.0,3.0,2.0,3.0,3.0,DBGHEAHDADDADECFEGBGHBFBB,False +749,11.0,7.0,13.0,10.0,10.0,9.0,18.0,6.0,AGEGGFDHECGGCGBCGECBCCEFCADCGHCGEGBEBDECGGCAFHDDHGDAGDAEAEFDGADGAFCCFBAFEFDGFAGBAHBH,False +750,19.0,21.0,8.0,26.0,26.0,23.0,18.0,20.0,FEHFHBCHBCHAAHDGEABEDCECBDDAFFAFDGDHCDEGDFADCHDEDEEGHAGDFGCFGDFAEBDFBAGHAEEAEAAFAFBAFBEBBDDBDHEFHEHDEBDEFEBBAAEAEGBEDFHDHGBEGEFBHCHFBHEGGEFGEFGDFHFHGDBGDBFDBHDGA,False +751,10.0,15.0,9.0,6.0,11.0,12.0,12.0,15.0,GDEEDHHBBFGBHHBEHFHFBDCEGGEGCBCCAFCEFBECHEHEBHBAABFABFABFGFEGAEBDHCGHAGHAFCACGAHDHFDHGBBGF,False +752,16.0,16.0,21.0,19.0,22.0,24.0,24.0,17.0,HHEEFGDFCDFCDFGHFHABEGECBCGBCGBFGDFBCBAFFGCAGCAGBAGHGDHDDHGDHGEHAECADCEFFAFFDEGBAGBCEBAHFACCDCBGEHDEGAEFCEDBEHFHAEDBGAGFECFGGAGGEFHDHECHECFECFCBDCGABDBHDFEFFED,False +753,5.0,5.0,9.0,7.0,8.0,5.0,5.0,7.0,DHCDCBFEBACFGCHGCHGEDGDDEDHAGEACFACEAHEFCCFBDHBHBEE,False +754,1.0,1.0,2.0,5.0,0.0,0.0,2.0,1.0,GGBCDDCDDADH,True +755,3.0,4.0,2.0,11.0,7.0,7.0,7.0,3.0,DDGGDGFFEFFGGDECDEDFEDFBBHBGFBHDAGCADHDDEAEE,True +756,13.0,13.0,9.0,10.0,17.0,10.0,13.0,12.0,CGAEDBDFGGHCGBCFAEEAGFBFFBFFBEGEEBEEHEECDEGACGEHAFGADHABHAHHCGHFGHEHEAHGDDCAHFAEBAEDCBBCBBGBDEDDA,False +757,8.0,8.0,4.0,5.0,4.0,3.0,10.0,2.0,BDEBGHGGFDGFDAFCGGCEBBAACEDCADHABGGBGBAABGAE,True +758,26.0,19.0,23.0,17.0,12.0,22.0,20.0,22.0,DDGDEFCHCHHDHHCHGGHDBAFBFGBFEBCAFCAFHFFDCCDCEACACBFEGGHGGDFGDHCBGAFCAFEDBEAEEBDFGDAGBHBHHADGCDFCAHCHFCGFCGHCBHABDABAACHAFAAHCBHBFABFAGFDBFHBEECGAGAAGFAEDABACCEGH,False +759,4.0,1.0,4.0,4.0,4.0,6.0,8.0,4.0,GDFGAFGDGCFGCFCAHAHDFHEEHEEGDGAFGCB,False +760,2.0,2.0,0.0,1.0,4.0,1.0,5.0,1.0,ABEDBHAEGFGGEGGE,True +761,21.0,26.0,28.0,30.0,24.0,24.0,21.0,23.0,FDCHDHHDFHCCGFFAFAAGABBDGBCGBHGEHFHFBCEACEHEHBEABDBBABAGBFFBHDEEDBGFCGFCGFBBCBBDBGGGCDECDCFECFEABGCDAEHEHBEDDADFADGAEEAEFDCFHCFBCHBCHAEDDEBGEDGFHEDCBACDGFFCEGCDACABEGCDGHEECFCFHDFBDHADHADHACGDCDDHH,False +762,24.0,12.0,13.0,17.0,17.0,14.0,9.0,11.0,CEAAEBDEFDBCCBABBACBDBDDADGCGHAEHAEHBEFAEFAFCACHBHFEHADHFEFAGFGCDADDACDEDGEBGECAEBFEBEADGACFAHAACAAEADDFFGAFGCDHDHEFH,False +763,6.0,8.0,13.0,10.0,5.0,9.0,19.0,14.0,HGDFBDFGCHDCBGCEGCEGHGHHGACGFCAEEHBBGDHGCCGFAGHADHBCGDDBEAFDHFBHFDGCAGCGFFGHBGHCGHCD,False +764,27.0,23.0,30.0,22.0,19.0,28.0,33.0,17.0,AACCCCCCFBCDCCGCFBEFDGGDCGFCFFCAECBGBFCBGEHDEFGHFGHACHGFAGEAFFFCHFDGCHGDGCFGCFGCAGDBFFBECEGCGGBGHBDAEDABFABFDBDDBDAADGHHFBAECEBHAHHEFADFADFACAACGECEEAGEABADBDHEGEDGEDBFAHGAHGAGCDFBAGBGFFDCHBHEACGGBGB,False +765,18.0,15.0,16.0,11.0,14.0,19.0,16.0,15.0,CEFGFFADDDDCFAFGAFEEEAEHBEHCECAEBAECABHACHFCFGBGGBDABCFFFGFHGHGDEDABBABBAHFACGDFGDFGCBEEDFHACHGCHGBHFEGFAACECDGCHGBHCBHBAHAF,False +766,2.0,0.0,3.0,2.0,3.0,1.0,2.0,7.0,HHEHHCCHDGHDFCEHAEGA,True +767,17.0,7.0,6.0,11.0,18.0,9.0,7.0,8.0,HEEBEFBEBEEGHEFCEACFABFHBGEAEAACAADAADADDAFABDAGDEDAGDEDHCHFABEGDEFDEAEECEGHHHFGFAC,False +768,7.0,8.0,17.0,12.0,13.0,9.0,9.0,18.0,EBDDBCDHEEEGCEFDAFDABCBBHFGHGGHDCHFEHFAHAEHCFHCAHEHBEGECHEGDECCCCDCBHCGHCBFGECACHAFHDCDDHFDHG,False +769,20.0,21.0,9.0,15.0,21.0,8.0,21.0,20.0,HEDAEDGBFGHEDHEDHEBCGAEAAFAABHDHAEHGGGBEFDFFAAEAEHCHBCHACDBFGBGABHBBEBBAHBHHDABDAGDHEFEGBGGDCGEBGCHECHECHGBEDBEDBAAFGADBAGAHGBGDCGEEGEH,False +770,21.0,9.0,20.0,15.0,18.0,14.0,11.0,20.0,AGHAHEGHACBCDEHDEHEECGABBADBFCHFEABCBDEAGEAFEAFECFDCHDBDFADCAGCADCHDEADAAHFABFEDCEGCHFHHCEACGDDGHFGAFGAHHHECAEHDHHABCEFCHFCGCCEF,False +771,4.0,4.0,4.0,6.0,5.0,8.0,8.0,13.0,HGCHGCEBAEDFEDHAHHGEHDDBGDEGBHGFHGFCFFCHADFFBHGAHFHH,True +772,4.0,7.0,15.0,14.0,7.0,5.0,7.0,12.0,FCECCEHCHDDHEFHDDAEHECCGDDBDDBEDBFCGHHHBHHBCABCHBCDEDGCHFDACDFCDGCGGAGC,True +773,15.0,15.0,19.0,12.0,10.0,13.0,9.0,11.0,CDFCAAHAADAADBHCGEAHFBGCBCCEGCDCCDEAGHAGECHFHFFBFBHFBADCADEHBECBABBHFECAGCDDCFFFHDFHDFAEGAEGBCCBCEDGBBCB,False +774,17.0,15.0,18.0,13.0,14.0,14.0,9.0,11.0,BDADABGFCGHCGAGHAGFFDCCBAGFHDFHCFHCBACEACBAGBACBECFEBGABFBFFBHHBDEEDEAHEAGFDEFAFFBDHBECCCCDCEACEHCEAADDCBAEDDEH,False +775,12.0,10.0,12.0,10.0,14.0,18.0,9.0,17.0,FFDFGDFEBAEBHFHFFBFCBFCBACEGDDCHCHDGBEEAEHAEBACCCCCAHEAFFFFFHGBHDAADAHEFHGFHEDCAHHADHGFGCHGFEEHDEHBEGB,False +776,15.0,9.0,14.0,7.0,14.0,8.0,10.0,14.0,FGGCGFEGFEGEBBABCCDCHEHHCHGFDGAEHCEFCEGCAACEACADHABADBFDCEDAABEACDGCHHCHAFAGHEHBEFEAHBAHBEH,False +777,3.0,5.0,7.0,4.0,6.0,7.0,4.0,2.0,ACHDGDFECAEGAFGEBDFBCFCCFHCEECDBGFBEFB,False +778,13.0,16.0,17.0,23.0,18.0,12.0,11.0,15.0,HGEDGCCFHBDHDDECFEHAEBAEBHDCCDFCDCHGHFGHAABCAFCGHCGCEFFEBAEBABBEHBGHBFFDDGDAEDAEABBHBBHEDFEFCDCEDCEDHHCGDDDDDAGFEBBCDDADCAEEG,False +779,0.0,0.0,2.0,3.0,0.0,5.0,2.0,1.0,DCFGFFCDFHDFG,True +780,4.0,14.0,9.0,15.0,13.0,16.0,18.0,13.0,GFHBCDDGGEFBDFGDFEDHCBBGEFEAFEHBDHGFFECCDHGHCGBBGBEDHDDEDEEDBCFHGDHGFHGFHGFGGFGBFGAFHCDCAECAEBBEDBGFBH,False +781,14.0,11.0,9.0,17.0,16.0,19.0,16.0,13.0,AHAEEAEBDCFCAFEACDFGBGHHFBHDBFDCHDHHEHFDGFAFEABDGEEEFHFABFCGFGGBCHBEGBHACEADGACGCFGBFGAFDAGBAGFDHEDEEDEFDEFDGHDGDDF,False +782,17.0,30.0,15.0,20.0,20.0,24.0,22.0,25.0,GBEGHHGHFDDAEABGCBGDDCCHFEBFGBGDBGDBGCAAFGAFDEFGEFEFAEFACBGEBAEBHBBHBCHEHHEAHDDCBCFDADDHDGHFEHBHFBDBDHAFHFFHGGAFCFGCHEEHEDFAGBCHBFGBCGDCGBHBBCFBDBDEBFEFHHCBHGBEBAEBHEFAAFDAG,False +783,18.0,12.0,19.0,16.0,8.0,23.0,23.0,21.0,CAEAGEACHFBBCABCACFADGBFCCFGDFGFBGHEGHCCHABHGBHFBGEAGCCFDAFDCHBGHCGHDFEGEHGEHFDHBDFAHFAHCGGCGDBFAGFHHFHGFDDHGHFDAGBHFHEDDDDCCGCCGADFAFGAFAAF,False +784,26.0,24.0,29.0,15.0,21.0,16.0,22.0,14.0,GEEGAEGABFAFGEBBHCCCGGBHGBFDAADAAGAFGBEBBCCGCAAHAAHDBEEBGEDADDADDAECAECBEBHEFFADBCGECGCCDCGACBACFDCFHFDHGHBBHDBCECEGCBGEBCEFAECCCHFGECGCBACBFFBGFHCECAFBAHBHHAFDAGDECAG,False +785,1.0,0.0,2.0,2.0,2.0,6.0,1.0,1.0,FFFEFFEDFCDCGAH,True +786,20.0,28.0,18.0,25.0,30.0,17.0,20.0,19.0,ECEDCEBGECGBDDAGEBEEHHADHDECGEDEEFEADEAFEAGDBDFCEFBDHBHAGAAGCAGCHHCHDBDFFEECADBAGFCBBEBDEHHEBHFAHFBCEBFEGEHADBDHBDHCDBGDBHDCGBFEADEADHAEAGBBCBACEACFDCBDHBDGEGGEBGEFGBFCBGHFGFFAB,False +787,5.0,3.0,2.0,6.0,9.0,8.0,2.0,4.0,DAEDAECHGCHBEFFEFEDFEDADHEDAEFBFABFHFEG,True +788,5.0,9.0,7.0,1.0,4.0,3.0,1.0,5.0,EBABAACHBEHFACBBFBBEABCDECHGCHBCHFC,True +789,12.0,4.0,13.0,8.0,13.0,16.0,10.0,11.0,ADAAEBAEGDFGHFGEBGADFAFFAFFEFCECEEFEGFEDFCCECHHAFDCFGHEHBBFAGFGHACECGHCDCCHCCHDFHDGAAEH,False +790,6.0,10.0,8.0,9.0,9.0,8.0,9.0,13.0,CEAHHCFHCFHBEACFACDBGDBEHBGGCGGAFDHFCHFEHBABBHDHGDEAHGBEBEGBEDHEDGCDFHDF,False +791,8.0,14.0,12.0,15.0,11.0,8.0,8.0,8.0,EBHEBDCADCAGCABCGDEADEAEECBEDADFEHECHDBHGEGCFDCFBBBHBBDGHDFFDFFGBGHBACBFCHGCDCDDEBDA,False +792,10.0,22.0,18.0,14.0,21.0,20.0,16.0,23.0,DBGEHGFDGFECFHGFEGFBAECAHFHECBABHGFACEBDGBCGHCECAEGBBCDBEGEEGHEAAECGBFHBFHAFHCFBCDHCDHDBHEAEEBHHBCCBFHBCCBHCEDDEDDEFFHHFHFFHEFDAGBFEBHCBHDBFDGGG,False +793,23.0,21.0,27.0,21.0,31.0,27.0,29.0,18.0,AGFCEBGEFGHCGECBEFEGFCBFDBFHCCHCBEDDAGFBDCCDCCDEGHEGHAFHGGHDGDBADBAGEAEAGFFCDACFACFGCFGHFHEFHEDECBEBHFGDEGCEGDBAFCCFACEEBDDHCECDEADFGBBEABHACFAEFAEHAEHEGBFCAHGEFDEAAHACGDBEFBDBBCBCEHGEFGFGGFAGDAGEG,False +794,24.0,20.0,28.0,18.0,24.0,31.0,23.0,26.0,HHAHBAHDAHGAHECHECDEHEEGEFCECEFDEDDFCDFCHBBHBHFCGGEHCAHCDGAGADGCHGHFGEEGAEBABBAEFDGDHFFEGCBFBGHBGABDBCAGCEFEBFCFAAAGAGBABCAEAAFFBFFBEBDDFFCFFHFFECFHDFGCCACFAFHCFECECCFGHFGBAGBCDHHHCCHDCEDAEDGHFG,False +795,31.0,20.0,15.0,24.0,20.0,24.0,18.0,24.0,DDFDGFDGAGEBGEBGFHEDHBDBGHCFHBDCEACAGHADHGHFGBFHCDHDHEEHGGDGGEGDFGAEAEECGFCBFABFADAADAHGCFFHBFBAFDAFDBEBAAHAAHAAHAAFABCABEBEFDHDHEFHEDABHCDDDHBHCCGDHAECAEBEHAFBACEADFBFFEAFCAFC,False +796,6.0,5.0,4.0,8.0,8.0,11.0,14.0,10.0,AGGGDBHDBEDHHCHFAGFGEECFFAFFAEDAEFEGDBGHHFHDFGCGHAGHGGHGEBCEBDFGDF,False +797,13.0,13.0,14.0,16.0,20.0,20.0,14.0,14.0,FDCFDCDGCDGAFFFFHFBDGAEEFDHFGHGBFDAFHGFHGDEDDEADCHGBHGBACAHBECACHEEEEBBDFCEBBEBFEHAGCEBAEFCEFAGFAHFGHFGCFECADCGEADEHDEBDECHB,False +798,16.0,22.0,7.0,24.0,22.0,17.0,26.0,9.0,EFHFGCFGEDGFBGFBHACDACDAGBBGECEBBBDDADDADHGGGBGGBFEEDEFDEAGEAGEAFEDDBDGCDBBBGHGDHCDBDDEGEAFEADEABABBHFBFDBFDFEEFADGADECHBGEGFFGBBHEGGFDGAGAHGEE,False +799,20.0,13.0,23.0,31.0,20.0,22.0,27.0,27.0,ACCDDCDDCHDEGDBGEBHAHGDDDCDAHDGFAGHAEBFECFBCDECBAHEACGAEGFEFFGHADDGDDACEACECCFFFDFGHBHDBHDCFGCGACFCDHCBHEFDBDGCDCDEFDEFAGHAFHAHHCEGGDBGFEGHEHHAGFEBFGAHCBHCAHDADFGDEHDHHAGHFEHGEGGDGGBF,False +800,7.0,7.0,4.0,8.0,5.0,4.0,9.0,2.0,BFADCAGBDGDDGDDAEDEFBEABEBECGDGHAGHAGFGBABCGFC,True +801,27.0,24.0,11.0,26.0,22.0,20.0,24.0,21.0,FDEFHBBHDBDFECFEGGEGBBBFGBAGBGFBAEHFGHCAACHBBHBDHEABEFBAFGEDECDEGFGGHDGAGGAHCBHEEEFHEDHADFDHGEGFAAACDFDDFBDCEAHEBHEAAEFBDABAABHABDAGDADFAHFGHFGHCGDFGEBCDBDAGDBGHAHDADAGECDACDE,False +802,24.0,16.0,21.0,28.0,24.0,24.0,17.0,24.0,EHGDHECEADBDCGFCGDCFDEFDHFEEBHECAGBDHDDAAAAGEHGCCGBEGCEGEFDEBDAAGEFCAFABFBEAGEAFECCDDCDDHDHFDEFGAACEEEHGHHADHFHADHFCCAHGACGAHECBEBBDFBCFBHADDAGDCDFAHFAHFABFEBFECFHDBHDBHDGHFHFCDF,False +803,20.0,21.0,21.0,27.0,21.0,19.0,21.0,15.0,CHCDAADHHDHFEEFGGDBGABGCBCFAHFHFFGBDEBFEAFEHBEFDEFDAHCGGCDFCGCGECGEAGDBCEBGAADFADFCDAEDBDAHAEHAEGGEGAHGADFCHCCHBDBBGEADDADDBFDBCBBCBEGDDCEEAGDCGDFDEGBEBBFBAHCEHCFCFD,False +804,1.0,2.0,0.0,1.0,3.0,0.0,1.0,2.0,HBEHBEDEAG,True +805,17.0,17.0,12.0,11.0,12.0,11.0,11.0,14.0,CACCACHGBBBBABBDBGEGCAGFBEFAEBAECGBHHHHHHHFDEFGCGGBBBAFFAFFACAACGACDDEFEEDEADHAHCBHDGHABHEBGCFAHBEDDDFEDA,False +806,8.0,5.0,13.0,9.0,8.0,4.0,5.0,7.0,AABDACCACDACDBCBEEHEHCDHEDGEDADGFFCCBCGBEHCHHDGHECCFDCFAEGA,False +807,2.0,3.0,6.0,1.0,2.0,2.0,5.0,2.0,CCGFCGCAGEGGHBBHBDCFECA,True +808,8.0,11.0,13.0,11.0,20.0,5.0,10.0,7.0,EDGEBEBGEBGECCCADEEEBCEGEDBECBCCDAEDHECHAGHGCDDFDBFEBFEBEEGEFHAAGABGDFHDCHACBEDGECAHC,False +809,19.0,18.0,17.0,18.0,21.0,24.0,23.0,21.0,GGGGAGFDDEHDEHAEFAGHHHHCBECAGCEGEBGABGFBDCHDBHEHHGHFAHGCBGFDCFDCFBEFHHDAGFFGCEEDHGDCADAAHEEDEBHHFAFFABFACCBCABHGCGDBEDFEGFCGFBFBBCBBDFEGFECFAHDAEDAEAEEDCBGGFFFHA,False +810,20.0,16.0,11.0,12.0,13.0,19.0,22.0,18.0,AGFCHFDDFBEHGEHGBHGDCGFCHEGAGADFAGGAHAFBABBFBBGGAABAAEADEBDGCHHEBGCAEAHEGCAGFHDFHFEHAGDGFDBFBBFADCGDBGHFGHCCCGCDGBBAAFFAFHHFEHFEHEE,False +811,17.0,22.0,15.0,31.0,25.0,25.0,18.0,24.0,HAFEGGECCHDGGGHDGCDGDEAAEHGEFGBGGHGBEFEEBCHAEHCFHDFHDFGDGDBGDAFBFFBFHEECEDBEDHDBEDBFDBFABDEFCHAEFEDHCDAFDCBDABDABFCBCDHEHFCAFCDBEDACDEHFFHFFEEEBDEHEBHBHHAHGBHDHGDBCABDADDFDAFGAF,False +812,13.0,7.0,5.0,13.0,10.0,18.0,4.0,11.0,FGEADHABHAEHFCHFAAEEAFEAFDAFABEGGHFFBBDBHCAHADHBFADCCHEDFGDFDDBDFEDFEHFDAFDFFEHFC,True +813,30.0,25.0,17.0,27.0,18.0,16.0,23.0,20.0,DGAGBDGFDGFAAACAGCEFHDAHDBHCBACFACFGHFEFBHHBDHBAEDAHCEFDGCAADABGABDEGDGCAGCEGBABEABDFGDFADFABGBHGAFGDDGHDAHDCDDEDGECHEHGFBBFHBEBBCBDGGHHCEHBEGBCGADAADBHEFDEFHEAADCCHEDECAAABABB,False +814,24.0,14.0,14.0,18.0,16.0,18.0,16.0,21.0,ACBABDDGDGCCHAEHAEFDEFGHFGHFGDCGEBFDBGGBFACACFAGEHGBAFBAEAAEFHEGHCAEAADDHCABFHHEDHDHACHAGHACHGCHCHDDHABAAFADDBBABFHCFGCFEDDEDDHFEHFEGFBGEAFEB,False +815,13.0,9.0,13.0,16.0,13.0,6.0,10.0,11.0,EBHEDEGACDDCDGCDACHFCECCHGBHGBHCBEDAEDHFAFEAHEADAAEADDFFEGBDGEHHABGGHGCCADCDDCDHCABEFBEDBAG,False +816,3.0,7.0,5.0,5.0,0.0,0.0,5.0,2.0,DDCDBADBHGBGBBGCCCACBAGBDGH,True +817,5.0,5.0,2.0,2.0,3.0,8.0,12.0,6.0,HCHGCGFHGAEAFGHFGHFGFEADEHDFBGGGGGGFBFABABB,True +818,1.0,11.0,9.0,4.0,7.0,7.0,8.0,7.0,GABGHBHDBHCBECBFGHFGBCBBFEBECCEFCDFCGHCFCDHEFGEGBEBHDG,False +819,2.0,2.0,5.0,5.0,0.0,2.0,1.0,5.0,CDACFHHFAHDBHCCDCHDBGD,True +820,11.0,24.0,12.0,20.0,8.0,10.0,7.0,16.0,DDBDDECFEFFEBFBBABHAFHGGCCADEHHABDDDDCGHFABFABFHDCBDBGDBCDBFEHHCBHADHADBADCHDCBDHBEHBHABCGBEGBCDCGHBDAEFBBBH,False +821,9.0,5.0,8.0,7.0,7.0,2.0,8.0,6.0,DCDGGAGGCHGCHBBEEAGEGEFCEDADAADAAFCABCEHCBHBEHCAHDDG,False +822,4.0,6.0,4.0,6.0,8.0,10.0,6.0,8.0,DGEHGBHAFDDFEAHBFCBFCDFADFCDHGEHGBFCBHEHGEBEEHEFGFFA,False +823,11.0,21.0,15.0,29.0,14.0,28.0,25.0,13.0,GCBACBGFGGFADDGDDHCCBEGFEGBDBBDFFEFECFBCFBFFGFFGDDHHDFHEFDEDDAFAGFDEBEBBDDHDEHGCHFCGCAGCFGDGGHCFBBFBDCGGEGDEBAHFDEADEADFCDGABFDDFGDCGBFADABDGBHGHGFHFDHFEBCB,False +824,9.0,9.0,18.0,17.0,22.0,11.0,12.0,16.0,HDHHDBHCFHEEAEBDEDAEDBEDBHHAFFDDFCHGCHECDDCEEEFEDGADGCDCCHCAHCAHCEHGECGEGGHFDCCEECACBGCEGFGDEBAFFAGCGBEEEFDEFDBHBH,False +825,13.0,14.0,23.0,11.0,13.0,29.0,17.0,16.0,CFBCFDDFBDFBHFHGFAGEAFFBHFCCFCFACFACFDCAEBHFGGBAGDEEHBGFAGFHEDHGFEBFHHFGFDCFCBHEEGGCFGEFBCADHHDBFDBHDHACHCCGCEGAGGFFACCAECFHCGBCEFCEFCAB,False +826,5.0,8.0,5.0,6.0,10.0,4.0,3.0,7.0,DDEDAGAAGAHCDDBBHBGEEFHECEFHEBHEFHECEECBBCHBDFBA,False +827,20.0,17.0,26.0,28.0,18.0,27.0,26.0,26.0,ECFEGFEHFHHFABFABFEHABHAGDBHDBHDBGDGCDGHABHAFCEHDBHGCDCEFEEADECDAFBGFEGFBAAGDGDDEEDHDABDABFAGFDGDDADCBDAHGHHGHHFFFFFGCDEDGGCBCFEDGCCGCCDCEFFHHAHDBHAFCCFDGBCCHACHDEGGEGCCDCCHCBGFAAFEGFGCHHF,False +828,10.0,8.0,14.0,9.0,25.0,17.0,21.0,17.0,ECHGCHBCGEFDEFDECDEGBECBHBHHFFGGFGGHDGHACCAHHBDCFGAFGAGEEHEAHECEEHEEBEEGDECFEBFECFHFFGGGAEGHEGFCFBAGAHEEGDAAHFHCFGEEDFGDC,False +829,3.0,3.0,1.0,2.0,3.0,6.0,4.0,4.0,DHEHHDFHGGBAGAFEACEGFBFFBF,False +830,13.0,14.0,5.0,14.0,12.0,16.0,14.0,22.0,GDABFFCGFEHEGFFBHCBHEDHFGFBBFEDEHDHHGFHAEHAEHCEHABHADGEDGAFGHBCHAGHADHEFHFFGFGBAABAABDGBDCHDGBEAFHHDDBDHBFHDEG,False +831,30.0,21.0,25.0,25.0,16.0,20.0,17.0,32.0,ABDAGCAGBEEEEFEEFGBFGACGBHGBHCAACAACGCHGHADHACEECHDHACHFEGEAGDAHDAHDGBBHBFHGCHEHHAFGFFDDBGHHDHDEHABBACBHCADFDDHBDHBDCDCBDAHFFHDDBFHAGCDBFFEECCECCGHAHCAHBEHDACDAHDFCDAHDBBFFBAFCFFCAHAAGAC,False +832,25.0,27.0,23.0,20.0,26.0,20.0,20.0,27.0,AADBAGBCFACEEGDFBFFBFHCGDBHEFHCFBFBEEBHCCHCHBEBGABDAHDFHDHHFEHGECGFCBHDFHABBDDBDFHDGCGCCGCDGCHBHEEDEHDHBDEEHEGHBBHFBHFBGCEGEDAEGAECCEAAEACBAHDEBAEBFGACGAFAHDABAHDGCDEAHEAFECFGAACBACHAGBFGE,False +833,25.0,13.0,14.0,24.0,17.0,12.0,19.0,18.0,AEBDEBFCFGAEEHEAHBAHDCFDHFBFAGFAGAEGCCDCAAGAHEHHGAHEACFDEGDCFBAGGABGADGCDGFEBFEAAAGAAECBGDFCDBEDHEBCDDHDDHDGHDHHGCHGEBGHCAHDEEDCDDBADAAGABHDDF,False +834,15.0,10.0,18.0,19.0,15.0,14.0,14.0,17.0,GFDGHHGDHFHCFDBEBGADGACECCHHCHFAHCEHCHHDEHAEBADDGDBGDEEDECDFCAFEEFEDDHDCGAHBAGBDEADGHEFDFABCEBFGBCABCFGCFACGDHDEHACACCAFGF,False +835,20.0,10.0,18.0,14.0,16.0,28.0,23.0,12.0,CBFFGFCHEDBFHGFEGFEGFEDCEDAEHAGGGGFGGCCCDGCFGCFHAFBAFBDFCFFHAAGCEGAEGHEGDFAFFCDFADECHEAHGFGEHGEBDDBABFABABECHCFGCDDFFGFAACAAEDHGGHECDBAFCAFAF,False +836,30.0,20.0,19.0,16.0,19.0,13.0,25.0,21.0,GEHGEGBFGFCGFAGHHGFGGFDHAAHECBAGGAGHCGBCABFHBECAAHAFCEBCEACEADDADCGHBDHGFEDBCAEGAHGHCGHCGEBBHGDHEDHDFBEBBFADEAHEACBAEGFDCAABAABAABGAEACHBHDGADHAEBACHDGDAGCEDCEFCBF,False +837,11.0,6.0,11.0,21.0,12.0,11.0,14.0,20.0,CCGFFHDFDCHECHGCEGCGGDDGABGAEHDEHGGHGHDDHDABDHBHFFGEFHDAEDFEDFGFAHHHCFHAEDGEHCHFDADDGDBADAHDAHDCDCCBEHBEAE,False +838,2.0,11.0,5.0,5.0,5.0,11.0,2.0,7.0,HHAFDBFCBFHBFCBHCFEBHEBCFBFEBEHBDDDEDCABBFFGFFGH,True +839,10.0,18.0,12.0,15.0,22.0,22.0,14.0,20.0,GHGGHDGHEHCFHBHHGHGFDFFBHGBDFBCFBFEBAHAACAEBAFCEFHEABGAHCBCCADAEHFDHFEFFEHFEHCECGHFEBFGCFDBBDBDDCEDEEDEEFBFFGDBBEBGEAEHFDCEGEEDHGDHBF,False +840,6.0,5.0,3.0,4.0,8.0,4.0,5.0,6.0,HFAHFAGABEEHFEBBEABCGBGAFGAECDEDHEHHEDGDC,False +841,22.0,25.0,12.0,20.0,30.0,18.0,24.0,19.0,CFDABGGBGGDGGBGDBGDFEHGEHAEDEEDEEAEGABBABHABFEGAAAAFAAGHFEEEAHFBBFBDHEHAGHADHFDHEDHEDCFAHFEHGEHEEHCBBDBBGBGEBCEBFEHDCFAGFECABGDHEFFEBEACCHEGEGCAFDACECDGDBHEFCGFGGBBBDBDDA,False +842,26.0,32.0,18.0,28.0,33.0,16.0,26.0,21.0,BDFEACGAHGEHBEFBDDCDDEBGFBAHCGBBGCEDEHBAFGGFBDFDABCCBFCBHEBEAFGAEGFEGEDGAABBHBDCAAEAEEBEBGDGGDGHDHHCACBEGGDHADHGEFEBDEBDHBDHBEHBHDDCDFCDCGAGGEGGEGFECAEABEAHDAHCFFCDHAAHAACAABFEEEBDEBDGBDBCEEHDBGEBEAHF,False +843,17.0,15.0,21.0,18.0,10.0,19.0,19.0,11.0,GCGCCGCDBAAFCFFCGCCFCBGCBHBGADGFEEEBEDCFDCFBEFAEGDDDDDAGACDEFDBFGCFGEFDDHCGGGGGAFACHACHACGADGHHCHBFAAFDFFDABBEBFHBHEBHCAHBADGABFDC,False +844,28.0,20.0,25.0,32.0,29.0,10.0,34.0,16.0,GCBGCEAHBHHGHCGADBHDGAFGCFEEFDEAABAAFACGACHAGEEEEEBDBDDGEAEBGCFGAFGCGACGAGFEDAGDAGDBGDFEBECDGBDHBDBBDAEHADAAHGDCGDEBAHBEDCGBEGHEDHCCEDDEDCEGCDHDACAABADGEEFCEFGGAHGCCGCBECECBDHDCADAGDGGDGGDECHEBD,False +845,9.0,18.0,18.0,15.0,16.0,16.0,18.0,30.0,FHHFCHBCEBFEBFBHCGHEGFEDEHABHBHCEHCGGEGGCGGDGHDFHBFHAGACEDBBBBBFHEDHAHHBHEGHEHFDHEBHDDHCDCDHCACADBHDAAEGHFCCECCFHHBHGDHCDHFDGFBGFGGECAFBFCEG,False +846,25.0,21.0,20.0,25.0,14.0,20.0,19.0,27.0,DHHAHHGHBEBFFBHACHBCHFEAFHAGEAGEDFFDHACGDCGEBDDBGEAFAAGAAHAAFCFDCAEFBEGHGDCFAEDABDABHGBHGFHFDGDDGDDHFBABCADDACHBCHCGECACDBCGBCFHEHCCBBHHHFHFBHECEDHDAHDFDDFBBFDBEGACGACGADG,False +847,19.0,22.0,26.0,32.0,24.0,20.0,17.0,30.0,FFFFFBEBBCDDHBEHDHHFHCDHCDBCDAFBHDGHDECDEDGEDCBFEFEHAHHAEDBDGHDCHECDEFHHADHCHBCHCDDCHBBHBEECCDFEDFDBGDBDFBEBAEFAHAGFECCACDHCEHCGGCGGCAGABCAGAGCDBADGEDFEGAEGAEHACHCBHABDBEDEDDHADGGFBFFHEFHCAH,False +848,9.0,6.0,11.0,10.0,14.0,15.0,7.0,8.0,EBECBHGDFECFDGFDHFDCEAAGDEFDEFDFFHCAHGBDDHDHFEGEGBAFCEFCAFCACCACBAFHFEHEEFEGAEBC,False +849,4.0,12.0,3.0,4.0,4.0,6.0,9.0,4.0,BADBFBBDBCDAGGEGGAHFBHFECBBGGCGGBBGBDFFHFEHAEB,True +850,11.0,16.0,15.0,13.0,9.0,18.0,8.0,14.0,AHEFHEDHAHCBEFAEABEBBDHGAGCECCECCEDGADFFBFFBFFACACDFCDECHHFDFFHFFGFBAHBCDBGDBGHHGHFBDBHDBCCFHDACABDGBCBF,False +851,14.0,6.0,9.0,8.0,8.0,11.0,8.0,4.0,CADAAFAFGGBDGBECHEGAEGCEGHEAFCGCCAFCAFDBEHBAAAFAFFECEDADGACFBDFHDFBD,False +852,13.0,17.0,14.0,11.0,14.0,23.0,28.0,19.0,AHFBHFEDBHCBHGDHDDBEFGAFBEDCEDCGGCAGCHGCHGCDCEEGFBBFHCGHAGDCFEGABFCBECBAFBAFHHGHEBCFAEGGEGAFBFGGGDGBDBFAEEBGAGHAFHCFHFFAGFHGFHFFHGGBGGHDGFE,False +853,17.0,14.0,15.0,18.0,12.0,25.0,14.0,18.0,FEEDCEDAEDABFABGHCGEGBAFBAFADFDDFBDFGDGEEAEHDGHCFHCHGBHFHFACAEBGHHGHAGAAFFDCCDHCGGCFDCFHCGECADCFDBFEBFBDGHDCHCHDAFFFHFBBEAFADFHBFHFAB,False +854,4.0,8.0,7.0,9.0,7.0,13.0,4.0,5.0,HAHBAEBCEFDHFGBFDDFDDFCGFBBCBFCFFCAFEDFBCGCDGEHEEDFDHFEBA,False +855,8.0,9.0,7.0,8.0,14.0,11.0,8.0,11.0,FCGGHEGHCAHEGDGCDHEBHEGEEFAEFCEAAFAHDEHFEHBGFBFFBFEAHEADCBBCBBCEGDDHFDFBHEAD,False +856,15.0,19.0,19.0,21.0,20.0,23.0,9.0,21.0,EHCABCEDCEDCHDBADEFFEAHGADFHBFEBFEHFEGCHGBBFBDFDCFHCFCGHCDHEHADFFEFHCGHCBABEEBEFBCDBCEHDACDBBDCBACBAEBDDCADFAEFEEHDGHDEEFBFFDHGHFGAFAHFCGFHBHDADAHC,False +857,8.0,14.0,12.0,26.0,12.0,12.0,24.0,18.0,DDGDGFHGDEEDEHGEDDCHGCAGDGBBHHAHDBHDBGACHCCHFCHGGHDGHDBFABCHGHGFDCEAGEADEGDADEGHBCFBGFGDCGBFDFFDCBDCGDGBEGBFGEHHEFHDFGDAEDBDDB,False +858,3.0,12.0,7.0,10.0,7.0,11.0,5.0,6.0,EHBFDFFCEGCEBFAFCCFECFHDGCEHAEFDBFDBAHBGHBGEBCDFDDFBDBDGBHBBD,False +859,15.0,8.0,5.0,5.0,11.0,6.0,8.0,9.0,AFHEGGEGBEDBACAADADGGHGFEGCEHCDAFECBBABHHEHAECFHBAHGABDEBAEFAEFAHAA,False +860,24.0,23.0,16.0,29.0,25.0,13.0,28.0,31.0,ABDBGHHDBEAACAHBDDDDHHGAHBDHDAHCGHCAEGFECFECGHAGBBDBDDBDGBDBAEBACDAHDBGDBCEBGEDDEBDBBABGGGGGEHAEGGGDFHDAHAHFAFDCHDCHEFBEAGECHFCHGGEGGAGFDHADEGHAFHBGHEFBCAGCAEBHEDHEDEEDFEGFHCEHDHHFCHEAGECHA,False +861,19.0,16.0,16.0,18.0,22.0,19.0,15.0,18.0,HBDHADGAFFFCFDCFDHFAEEDEEABBABHHEAEDAHDEHCGFEECHECEFGHFDHFEEGCBDFDGHDGHDCBDCAECAHBACGEFBFFAFBAFBEDHDAHBBDGEGCEGBGDFGAFGAHCHGFECAEGABAHBACBECECD,False +862,23.0,28.0,34.0,23.0,21.0,19.0,19.0,23.0,AADEFDECBCFBFEGCHHCBCAHCAEDAEDFGBAHBGBBGEDGEFBAFBABEABFAHFAHADGBHAAHAAHCFCAECBEHBACDDCDCHDHHDAHDAHCFBCDHCBBGDEDEHFBCCCCCDGEDEEBCBHCDEBEHBCGCDECGCCGBCGBCFAGGACBHBFCAGCFBDHBFHFECFGHEGCEFDDFGDG,False +863,11.0,5.0,11.0,10.0,13.0,17.0,9.0,9.0,HGFAGHEGFFAEFGCHCCHCFACEAFEAFBFFBEEDDDGGDFEBHDFEDFEFCEHCDAAFBAFHCFECHEDDABDAGCCGAHGEF,False +864,8.0,4.0,8.0,5.0,6.0,11.0,2.0,13.0,CGDDADAFHFEHACHFFHAFHAGABEFBHHCHFCFBEHCEHDEFDCFEFHCAHCAHB,True +865,6.0,7.0,13.0,8.0,5.0,5.0,10.0,8.0,EBBEADDABHGBFBHDAHDFCCCCCGDCGACEFCEGCGGCDHHBGHCGCGBFDDFEAHCAHG,False +866,13.0,18.0,13.0,24.0,13.0,21.0,16.0,22.0,CECHEHGAHDBHAACGDDGDDGBGFBACBAFGCFGEBHHBHBBFBBFGDFEBHDBAEEAGEHFEDGEDFFHFADDADFHCHEADCFDBEDCDDFFBFFHFGEFGHCDFBHADHFDHFHCGCAGDACEBDHBDGDHGCHBH,False +867,3.0,4.0,1.0,1.0,0.0,0.0,2.0,1.0,BGHBGBAABACD,True +868,12.0,15.0,8.0,11.0,24.0,11.0,16.0,16.0,GBGAFGAHEABDAHEEHEGHFBEGHCHHCBDFECAADDGHFHFGEAGEBCDGEDBEFEEFGDGGAHGDHEEHBEHGEAGECGEAHECHBBEFBHBBDBBDCBFEFEEFECAAD,False +869,14.0,6.0,19.0,11.0,20.0,15.0,11.0,18.0,AFHAEHAEHGFHACHADFFGGFEGFEGDEDBAFBDECHHGHCCDBCFECHCHFBEDEECHACDGFDCHCEHFHCFACEACEACBCGBGEADECEEGFEHFACEDHEDHAGHFCA,False +870,7.0,10.0,10.0,16.0,6.0,4.0,11.0,16.0,HCBDCBHCBACDCCDHFHAGHCCDECGEDGDAFHGHGBDDFADHGDHBDHBGHFHEAABGBDHEDHEHHEGDDGADGCBB,False +871,6.0,1.0,1.0,3.0,2.0,4.0,9.0,6.0,AHCGEDGAHEAHAFGAGGBHGAHGFGDFGFHD,True +872,3.0,5.0,3.0,3.0,6.0,1.0,1.0,2.0,BBBDCBEGHEFHDBADAECAECEE,True +873,2.0,1.0,1.0,2.0,5.0,1.0,2.0,3.0,HEGAEHAEBCFDEHDEG,True +874,7.0,21.0,14.0,14.0,9.0,12.0,13.0,10.0,FDBFBBDBADBHBAGDHHCGEFDEBGEGGFGBCGEADAGGADHBDFCDECGBCEDFHFGHFEAFGHEDCEDCBFCBCCBHBBHBBDCBFGBCBHDBCAFC,False +875,6.0,6.0,10.0,12.0,5.0,8.0,13.0,6.0,GCGGCGGHBFDDADDBDFBDGCFGAEGAFBBCBHHFDHADHAGCDGEDEFGGCECCHDCEACGDFF,False +876,19.0,14.0,14.0,17.0,5.0,8.0,26.0,9.0,ADBACAGCHGCFGHDADABGEDABDABAFGCFDCADGGGGGGGGGBGGBACCHHAAGAADAGDAGDCGDBFFBCFBEBCEBGBBHEGDDCCCBHHAFGDGADGDDAFCGHHE,True +877,11.0,23.0,26.0,15.0,25.0,13.0,27.0,20.0,DHHEHGFGGCEHCGDGEDHCDHBFEDFEAFHBDGFCBHCEECEECBHCACGACACHGBHGBGGECGBDHCFEEEHCGHCGHCEBEFBGABCDDEGGEGGEGFEDBEBBGBCGBHABGEDCABCFECAHHBBCBDCAGBDGBAGCAHFHEBCEGCDFFDEF,False +878,10.0,21.0,12.0,20.0,16.0,27.0,18.0,16.0,EGCEHFAFAEBBGACGEEDEBDEFDBBDCBDEDFFAFGHBDFBHBGHBEBEGDDGDGBHGBHBFFGDFCFGCFAEGHEDEEDEAFFFFFFCHGGDGAFGAFHDBHEBCAGHBFDFFBHFCHFCHCCDCFDHBDGBDBHFA,False +879,13.0,7.0,15.0,3.0,11.0,11.0,9.0,9.0,CHBCFBFGEFEHCCAFAAFCEECBBHEEGEFBEABAADGAGGFGFCGACEHCHCFECADCACCACFAHFHDGHGAHEB,False +880,18.0,17.0,11.0,7.0,12.0,11.0,12.0,19.0,GACGHHGCCDAEAEBAFGHFGHEHABHBDHGCHGCHBABEEBECDDBABBHFHGCBGCBFAAGDAGHHHCAFCABAABAABHAFDAFBGDCHFEBEEHEFHEFBFHE,False +881,15.0,14.0,12.0,18.0,16.0,16.0,10.0,24.0,EFDEFDHBEHAEFFBHEBGEFABHGEHDFHAFEBCDGDAFDAHAACDACDGCEHDBBBBHDHEAEFAHGDFDABHABHAEHFEHFHHFHBFHAFHAEDCGBGGDDHDEHCBCCHCEFDGGHCDCC,False +882,1.0,3.0,4.0,5.0,7.0,5.0,2.0,5.0,HDHBCGDFACFECFEFBDFDGHEEHEBHEDCE,True +883,10.0,19.0,13.0,15.0,16.0,14.0,11.0,10.0,FDEBDAHCBEFHFHGGHGEBGCHCEECDACEFBAFHCBCEBAGBFGCEGBEHDDHBDHCDAFDEBDFBDEADBADBAECAGDABCGDCFBGFBDFBEFBFGBEHEECF,False +884,4.0,20.0,14.0,12.0,17.0,18.0,12.0,16.0,DHCFHCBHGFHFEDFEDBCDBFHHGCDFADCGHFBDCBDHAGEFBEHBEDCEGCABFHBHCCCCBHCGGFGFFBFBBEGFEBBBCGEGHHHFDAFDEFBEFHEGDEBEEBEEB,False +885,4.0,5.0,7.0,5.0,3.0,5.0,11.0,4.0,GBBEAFCABHGBGEFGDDCBDCFGCAGCDGCGHEGHFCHFGAGD,False +886,4.0,2.0,5.0,6.0,4.0,7.0,8.0,6.0,DEGFEGHBGCGHBGHDFAFFAFDADGCHECDECFFCHADHGG,False +887,7.0,10.0,2.0,12.0,7.0,8.0,10.0,7.0,HDGHAEDCDDBGDBAEBGCBDAEGFGFBGFBDDBFHBEHADFGDFHHFHEDGADGAFEAGEBB,False +888,22.0,21.0,26.0,15.0,24.0,25.0,19.0,23.0,HFHEFEAADAGDBCEBGEBEFHEGHAGEDGADFEBFCBFBBFCEHADFEHGHHFDFCHFCHDBGDHAAHFCFAEBAEGCEGCFFAHHGHHFHHCHCBABGDHHDFABGCFACFECDEAGEAGFBCFGCEGCBBBEBAGHGGCBAFACFDCDDCFCAHCACCBEEBEEBEADCCEF,False +889,14.0,18.0,14.0,7.0,16.0,10.0,10.0,16.0,FHAHHEDDECCCHBCBBFBFCBACDAGHAGHBFHBCHBEGEEGBBGBBGEAEAHHBEFFEAFEDHECEEGABGBDGCABEABAFCHCAACGBHHAHCDHFECFED,False +890,18.0,20.0,25.0,21.0,23.0,27.0,22.0,23.0,ECFEGEBFABFABCDBFHBHABHBDHGFGBFGECGCFHADHDEACCBHFEGFACHECHFBACCCBEBBDFDAEAABDAECCCFCFFCFFCEGCHBEGDEDFBDEGHFCHFCFDCFEGGEGDDGHDHHCGHFDFBDHGHHAAHAEHFGAFGAEADEFCEFBEGBGGHDAEDCEHCDGBDG,False +891,21.0,17.0,16.0,20.0,21.0,17.0,22.0,30.0,GEDGFABBHBBHFAGAEEAEAAECAEHHHBDDCABHGGHGCBAAFABFBFCGEBFEGEHHEHHDDHFGEEHDGHCAHFADBADCCGACHDGHAGHAFHAFBECBEDHGCHGAHGBDCEDCDBFDEGHGADGDHGFHCDGDFHBHHBHAECFECFEGFHFEDCED,False +892,2.0,4.0,1.0,8.0,1.0,2.0,5.0,5.0,HHHHBDABDGBDFFDCAHGGGBDGDDED,True +893,15.0,5.0,9.0,8.0,9.0,2.0,15.0,5.0,GGEGEEDAFGECACCAGFGEEDECDBAEGADGABAACCACCAHGAHADHGDGGHGBACBHBDEGAAGD,True +894,15.0,20.0,23.0,20.0,17.0,18.0,26.0,16.0,FGDFCFCCGBFEBEEDACGECGHCFFEDBBCHBFHBDAFHBGCFCCFAGHDGDGGBFEEGCEGAFGAEAFEDFEDBBDHBHGGGGCFDCEHBEHGCAAAAAGHCHHCHBGDDCDBGBBCABCABADBADBFDGGCCEDEEDGCGGDDGHCFHEFH,False +895,17.0,14.0,14.0,9.0,18.0,14.0,9.0,18.0,BGCDCCFADADBGDGCAEEAGEBEFBHHAEFFEHFEBEBCGCEBCEDAGGAHEABEABDAFDHBHHAAHBAHAHBAHCEHCAHFHBEHFCFFCEFCEHCHHCAEDFEDBGFGF,False +896,10.0,10.0,7.0,13.0,14.0,14.0,10.0,8.0,HCBCDHHGEAFHFCDGHEBDEAFBCFEDFADEADEADABBHCAEDGDDGFDAFHHFDGFGGFABFBCDBCEAGBBGEFGEFEEFEE,False +897,1.0,6.0,2.0,6.0,4.0,12.0,5.0,5.0,FBDGCGGDFEBFEFFEGFBGFHFFDFHBAHFEDFCHBBHDD,True +898,8.0,2.0,6.0,2.0,1.0,5.0,2.0,3.0,CFFCHDCFEHHAADAACCABAACGAFGBF,True +899,13.0,11.0,11.0,13.0,12.0,11.0,12.0,9.0,FCCGCABEBEEFCBGCDGCAECEEHAEGDCFFHDBCABDABEAFCBHABHADHGDFGDFBDFEDGHBGDGDAGAFECHEGDEGHFAHDABAF,False +900,11.0,8.0,16.0,15.0,15.0,12.0,12.0,10.0,HFDECDECFHCHGDEDEEBGHDAHDABCCDDFGDCGBCACCDGGFCGFEHEAGEAGEAFCCHCCAFEAFADEADHGDBFBBFBBFGCEAHFCDEEDHEG,False +901,6.0,5.0,13.0,12.0,14.0,4.0,0.0,2.0,DEEDEFCACAAEHEECDECAHCBDDECCBCFFDBFBCDECEECEDCADEDDEDACB,True +902,5.0,2.0,3.0,0.0,2.0,4.0,3.0,0.0,CFECFBAGAACAAGFFGBE,True +903,1.0,3.0,5.0,2.0,2.0,3.0,3.0,5.0,HEAGEFBCDBCBCFHCFHCDHGHG,False +904,8.0,10.0,8.0,10.0,10.0,10.0,8.0,8.0,HAEHAEDAEDGHFGFFAFFBFFGDABDECDEGGEGHBHBBCCFEDGECBCCBACHDCAFBDDEEDAHGBHBF,False +905,19.0,35.0,22.0,16.0,17.0,18.0,22.0,17.0,BEDEDGGBEBBDBGHBCBBCBHCAEAHBAGBCBHDBHDCHGCBGDAGDCCAGDGCDFCBFCBDBBDHAAEAGEGGEGBAFBHFGFGBFHEACECCGHCFFEFBCFBAFAABBBBBHDBEFBHFAGBEFCDGCFCDEEHBBFBDCGDEGFHGACAACAHHFGHEABE,False +906,6.0,6.0,11.0,1.0,5.0,2.0,8.0,3.0,GGECBACGCCGHCBFEGGAACAACDACBBCHCEFCEHBEGBG,True +907,10.0,11.0,15.0,22.0,12.0,15.0,10.0,11.0,CBDCFAHHHHCHDBDDBEDHCAECDFFDACDGBDABCFBCFBGDCFFCFEEHGGHGADGDFAFACGDCADFBCFGDFEDFDDADGAHEBHFCHDCDEEBEEDEGBE,False +908,4.0,0.0,2.0,5.0,3.0,0.0,2.0,3.0,GHACDADAEDAEDEGDHHC,True +909,1.0,4.0,0.0,5.0,2.0,3.0,1.0,1.0,FDHBDABFEBDDBDEGF,True +910,9.0,19.0,26.0,20.0,13.0,12.0,16.0,22.0,BHDCHGCHBCHDCBGCAEDFEBFBHDBHDGHEGECGCFDCHHGHHBHGFGCCBCCDCHAADFFDFFHEDCFBCEHCEHCDDFAGECGDBDBGFGEECBHCBACBACHCDEFDAHBCHCEGBGGCDDHDEHBAGBADB,False +911,5.0,1.0,2.0,3.0,2.0,3.0,0.0,2.0,HAHAADAFBAFEFCEDCD,True +912,26.0,20.0,25.0,15.0,11.0,21.0,19.0,28.0,BGFDDHABFAGCACFBCDBGDCCAAAHAAHFCHCEGGFFHHFBCABCGGGGBHEAHCAHBAHAHHACHFDHDAHABHCBFEBFADFGDCGFFHCGBCFBDFEDCHBBHBCGECGEHGFHAEHACHADAABHFDECEGBAGDHFDHCCFGAEGAECABFFBHCCHD,False +913,7.0,7.0,5.0,3.0,0.0,6.0,1.0,6.0,CDFCAFHACADCBBHBFHBFHFDGCABBABFHHAA,True +914,20.0,24.0,25.0,24.0,19.0,23.0,23.0,19.0,BDHFDGCHCAHFAHFGGCHBCHDFEDAEHCBFEBCGHCGFEACCAHDFGDFDBFBEFBEBGDBGDBCDECBFHEEEBCGBDDFDECHEHBFCAFADGADAHFCFFGFAGFEGEHGADDHDCHDBDDGEDBHABGGBEGBAHBHBDCFDCACCGEAACCACGAEGBEFBAFCCFGBAG,False +915,6.0,10.0,1.0,9.0,16.0,12.0,5.0,11.0,BFGFHGADDEEEEBEEHEHHEHFEBEGHFDHFBHFBDFDFFEBGDHCEBEEBEAGDADHAFAAFHBBEDF,True +916,19.0,25.0,17.0,15.0,26.0,25.0,27.0,16.0,EBBHBCGEEAEBCECGECHHCGDCECGECDBCDBAGCHGBFDBDBCEBFAAGAAHBGDFGAEGAEHEEHECGFFAFBEEAEEABEHBGHBFHDGCCFEFFCFFGFDHBAHAGFDGFDGHGGEDGEBGHGFFECBAFBHGEFBFGDFHDAADGGBAGBFCBFDEFAFBABE,False +917,1.0,1.0,0.0,2.0,5.0,1.0,1.0,0.0,DABDEEEEGFE,True +918,3.0,4.0,4.0,5.0,6.0,2.0,1.0,2.0,FCHDCBDCDEADEBDEBFBGACAEHEE,True +919,29.0,30.0,27.0,23.0,18.0,16.0,15.0,25.0,CECCDDBFGBEHCFACFCCAAAAABGDBDCBDABFBCEACABCGBHGDCGFBGHCDHCEHCBAFBFGHFHHDHFEHFEHCDBDDACBACGACGACFEDEBDHBDHAAEEGFBHHBHDAHBGBCGDAAHAFEBCCBDBEEAHEHFGHAHAABBABDHBDADDAECGBCEDCDCGEHAEHABBFF,False +920,6.0,8.0,6.0,2.0,10.0,1.0,2.0,2.0,ABABBFGBDGEECCEACECHEHBEABDBEEEACEACB,True +921,9.0,6.0,2.0,9.0,10.0,5.0,13.0,15.0,EBEDHGAHGFHGFBDEDDGCDGDHFAEABEGEGAHGAFEAGHAHHEHDEHDABDBGEGGBGHHACHFHH,True +922,0.0,4.0,4.0,4.0,5.0,3.0,8.0,5.0,BFCBHEBHDBCDFGGEGFEGEHGHCDHGDGGEC,False +923,9.0,18.0,18.0,28.0,20.0,33.0,20.0,19.0,FCFHEFDEBCBBCFACFDCDCAFCAHBDHBFGFHAFEAFEHGCHGDHCDHCFCGDCHBEGFFGDFGBHGDFGDFGFAHDBGGHHABEDFFDFFDFFEBFHDCEDFEFHEHHDGACFFGHBBHBADDDDCDEGDGGCEFCDBEBGEDEEBCEFGFFBEDGEDBFDE,False +924,2.0,5.0,0.0,7.0,6.0,1.0,0.0,3.0,EEDEEHEBAEBDDDADBHDFHBBD,True +925,12.0,20.0,17.0,18.0,18.0,15.0,13.0,21.0,GHHFHBACCFFHHFHHABHGDHFDEBABDDBCAEHABDEDCGDGDDGCDFFDHEBAEBAEBDCBGCEGBEHBFCEFDBGBFGBHBHHFFEEGECGECGECBHGBHDCHDAFDCFDEAHAHEAHACCEEFBBDCC,False 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+976,27.0,32.0,25.0,20.0,17.0,19.0,24.0,36.0,HCFABFDBGEFGFDCBDCAEBHEDADCADCGBCDACDBBHBBDAHAHHFFGEFHHBBHEFAEDHEHHBHHDAHCACCDDDAHCEECBBHBHHBGDBGBBGHCAHCFHFHGCHGAEGFFBBHCBHAAABACEGCGGCGACFACGHBDCBHCGGEHEBGAFFAEHHDFHDFEGFABDABGBBECBEBGAAFAACGHGHHGDH,False +977,21.0,23.0,33.0,29.0,26.0,21.0,26.0,19.0,BFCBCBEGFEGDEGFEBDACFGCDGADCDDCBBCGCDDCGCCGDDGBFBEEBAABAACFCCFHDDHDEBDEFCEBBGBEEDAEAHFCHFHHEBEEFFEFHEADEGEGGCGGADDFBCADDDCCGCCGCDGEDFADGDFGFFBCAAHAHEFHECAGFGDCEDCADBAHHHHEHHEFHBCCCCBBAABCAHHDGBEGCGG,False +978,7.0,8.0,10.0,5.0,10.0,5.0,5.0,1.0,DECDEBFCGFADFEBAECABABEGGECDFCGBEGCEHCBDCBCABCAEAFE,True +979,1.0,2.0,1.0,6.0,0.0,1.0,0.0,1.0,DCADFBDHDDBD,True +980,24.0,21.0,18.0,12.0,17.0,7.0,12.0,18.0,BBAHBHDDHBHFAHACBEBBCBAEEACHAHHEGBBGBCDCCAECAHCAGGAFFACFAHHEEAEHFGCACEACHFCHDDEDDEDDCBCCHEBHBAHEABBGBBADBGBBEAAGAADHEGEGGEGAFDACC,False +981,22.0,33.0,18.0,23.0,27.0,28.0,28.0,13.0,EAEDGBCFBAFBGFDAFAAGHAEBFHFFHFFGACDBDFCDFGDBEBBDHCFBEEGGDAGECGEFABFGBEDAEAHEGDDBEGCDABHBBGBDFBDHBGBBEBBHABAABDCEFGAFGAFBFCEFBGGHAGAFEDGEDCHFHBFGDHCFHCAGFDGCGECFECBECBECECABCAEFBEFEEGDBGDEGDBGD,False +982,22.0,20.0,15.0,16.0,27.0,17.0,27.0,21.0,GDFGHEGBEHCEBCHBEHBAHGCGGEGBBFDEADFFHADHEBHGDACDACDEBEEGEHBEGBEGHEBFAAFGFFGDFGDFABGHFHCEECHDGBDCBFFBGCBDDHDCGBCFAFHGGHEGACHECAEAAHCABAACAHEEDEADEFEGBGGEGAAGEBGFAHHAE,False +983,6.0,5.0,6.0,11.0,8.0,8.0,5.0,7.0,HBFHDFCEABBADECDEGDFCDFHBFEDECCFGHFAHGHHADEADFCDGDDGEBAE,False +984,9.0,13.0,13.0,13.0,32.0,25.0,15.0,18.0,EEAEEGEABEGHGFDADEEFAHHCBFGDCBBCHBCFDCFDCFDEFDEFCHFEFECFEHFHGFHGFHEBBCGECBDHHEEDEFCEGAADEFEHGEDFEHFEDFEGBHHFHGEEGEGAACFABFGFDGBEECEEFHBFHB,False +985,14.0,10.0,10.0,7.0,7.0,11.0,13.0,6.0,FAFAHGABAACAAGAFCDDCGCEFDBGBGACHECAECAEBAHDDFDBFDBFGBAGCHBEHBAGBECFFCEFGGGGGFH,False 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it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/src/main/scala/org/xcit/nback/markov/models/State.scala b/src/main/scala/org/xcit/nback/markov/models/State.scala deleted file mode 100644 index fbbd844..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/State.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * A Single state with a label in Markov chain - * @param label A simple string label, representing the state and node - */ -class State(val label: String) { - - /** - * Keep track of transitions from this state to other states. - */ - val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() -} diff --git a/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/src/main/scala/org/xcit/nback/markov/models/Transition.scala deleted file mode 100644 index bc20a9e..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/Transition.scala +++ /dev/null @@ -1,8 +0,0 @@ -package org.xcit.nback.markov.models - -/** - * A Single transition in Markov chain graph. It is stored in "from" node. - * @param to the ending node of the edge - * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). - */ -case class Transition(to: State, probability: Double = 0.0) diff --git a/src/test/scala/ThreeBackBenchmark.scala b/src/test/scala/ThreeBackBenchmark.scala deleted file mode 100644 index 0c7dad9..0000000 --- a/src/test/scala/ThreeBackBenchmark.scala +++ /dev/null @@ -1,7 +0,0 @@ - -/** - * TODO Benchmark 3-back simple sequence generator - */ -class ThreeBackBenchmark { - -} diff --git a/tests/benchmark_diagrams.py b/tests/benchmark_diagrams.py new file mode 100644 index 0000000..8fa448e --- /dev/null +++ b/tests/benchmark_diagrams.py @@ -0,0 +1,159 @@ +import pandas as pd +import numpy as np +from matplotlib import pyplot as plt + +import benchmarks.common as common + + +def tlratio(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2,ignore_index=True) + stats = [] + for trials in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == trials) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == trials) + targets2 = data[alg2].targets if alg2.shape[0] > 0 else np.nan + targets4 = data[alg4].targets if alg4.shape[0] > 0 else np.nan + lures2 = data[alg2].lures if alg2.shape[0] > 0 else np.nan + lures4 = data[alg4].lures if alg4.shape[0] > 0 else np.nan + stats.append([trials, (targets2/lures2).mean(), (targets4/lures4).mean()]) + stats = pd.DataFrame(stats, columns=['trials', 'tl2', 'tl4']) #.dropna(subset=['skewness']) + + plt.style.use('ggplot') + + plt.ylim(bottom=0, top=30) + plt.scatter(stats.trials, stats.tl2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl2[idx], 1)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.tl4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl4[idx], 2)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('T:L Ratio') + plt.ylabel('T:L Ratio') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_tlratio.png', bbox_inches='tight') + plt.show() + + +def time_per_trial(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for t in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == t) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == t) + time2 = data[alg2].time.mean() * 1000 if alg2.shape[0] > 0 else np.nan + time4 = data[alg4].time.mean() * 1000 if alg4.shape[0] > 0 else np.nan + stats.append([t, time2, time4]) + stats = pd.DataFrame(stats, columns=['trials', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.trials, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time2[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time4[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2v4_time_trials.png', bbox_inches='tight') + plt.show() + +def time_profiles(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 8): + alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + time2 = data[alg2].time.mean() * 1000 + time4 = data[alg4].time.mean() * 1000 + stats.append([ni, time2, time4]) + stats = pd.DataFrame(stats, columns=['n', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.n, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.time2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + plt.scatter(stats.n, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.time4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_time_n.png', bbox_inches='tight') + plt.show() + +def skewness(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 9): + all_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + skewed_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) & data.skewed + all_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + skewed_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) & data.skewed + num_of_sequences2 = data[all_alg2].shape[0] + skewed_sequences2 = data[skewed_alg2].shape[0] + num_of_sequences4 = data[all_alg4].shape[0] + skewed_sequences4 = data[skewed_alg4].shape[0] + skewness2 = skewed_sequences2 * 100.0 / num_of_sequences2 if (num_of_sequences2>0) else 0 + skewness4 = skewed_sequences4 * 100.0 / num_of_sequences4 if (num_of_sequences4>0) else 0 + stats.append([ni, skewness2, skewness4]) + stats = pd.DataFrame(stats, columns=['n', 'skewness2', 'skewness4']) #.dropna(subset=['skewness']) + + + plt.style.use('ggplot') + plt.scatter(stats.n, stats.skewness2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.skewness2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + + plt.scatter(stats.n, stats.skewness4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.skewness4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Skewness') + plt.ylabel('Skewed Blocks (%)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_skewness.png', bbox_inches='tight') + plt.show() + +if __name__ == "__main__": + tlratio() + skewness() + time_profiles() + time_per_trial() diff --git a/tests/benchmark_skewness.py b/tests/benchmark_skewness.py new file mode 100644 index 0000000..f468b4d --- /dev/null +++ b/tests/benchmark_skewness.py @@ -0,0 +1,97 @@ +import random +import heapq +import csv + +# Common parameters +alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'] +trials_range = (10, 40) +n = 3 +sample_size = 100 + + +def to_benchmark_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [str(ralph_skewed)] + +def benchmark_nb_gm_001(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_001') + + +def benchmark_nb_gm_002(filename): + import generators.nb_gm_002 as nb_gm_002 + + generator = nb_gm_002.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + # print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_002') + + +def benchmark_nb_gm_003(filename): + import generators.nb_gm_003 as nb_gm_003 + + generator = nb_gm_003.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + print(f"sequence {i}/{sample_size}: {trials} trials") + seq = generator.generate(trials) + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_003') + + +def show_skweness_diagram(filename, choices, title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + print(filename) + data = pd.read_csv(filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) #.dropna(subset=['skewness']) + #print(stats.trials) + #plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'{title}.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + benchmark_nb_gm_003('../benchmarks/nb_gm_003_2back.csv') diff --git a/tests/common.py b/tests/common.py new file mode 100644 index 0000000..e40c0df --- /dev/null +++ b/tests/common.py @@ -0,0 +1,27 @@ + + +# Common benchmark parameters +choices = alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F'] +trials_range = (10, 65) +n = 4 +sample_size = 100 + + +def count_targets_and_lures(seq, n): + mask = 'D'*n + for index in range(n, len(seq)): + if seq[index] == seq[index - n]: + mask += 'T' + elif seq[index] in seq[index - n - 1:index - n + 1]: + mask += 'L' + else: + mask += 'D' + return mask.count('T'), mask.count('L') + + +def skewness(seq, choices): + import heapq + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return ralph_skewed diff --git a/tests/nb_gm_001_bm.py b/tests/nb_gm_001_bm.py new file mode 100644 index 0000000..54f6cb3 --- /dev/null +++ b/tests/nb_gm_001_bm.py @@ -0,0 +1,75 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq) , str(ralph_skewed)] + + +def benchmark(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets / s.trials, axis=1) + plt.scatter(data.trials, data.targets_ratio, alpha=0.2) + plt.show() + +if __name__ == '__main__': + alg = 'nb_gm_001' + fn = f'results/{alg}_{n}back.csv' + benchmark(fn) + # skewness_diagram(fn, alg) + targets_ratio_diagram(fn, alg) diff --git a/tests/nb_gm_002_bm.py b/tests/nb_gm_002_bm.py new file mode 100644 index 0000000..c8af543 --- /dev/null +++ b/tests/nb_gm_002_bm.py @@ -0,0 +1,105 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq), str(ralph_skewed)] + + +def benchmark(filename): + from generators.nb_gm_002 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials, int(trials/3), 0, 0) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +import time +import numpy as np +import pandas as pd + +import benchmarks.common as common + +def profile(): + from generators.nb_gm_002 import SequenceGenerator + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, int(lures/2), int(lures/2)) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('benchmarks/results/nb_gm_002_profile.csv', sep=',', encoding='utf-8') + +if __name__ == '__main__': + alg = 'nb_gm_002' + fn = f'results/{alg}_{n}back.csv' + profile() diff --git a/tests/nb_gm_003_bm.py b/tests/nb_gm_003_bm.py new file mode 100644 index 0000000..fa6c19a --- /dev/null +++ b/tests/nb_gm_003_bm.py @@ -0,0 +1,114 @@ +import heapq +import csv +import random +import time + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq, time_per_block): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [time_per_block, ''.join(seq), str(ralph_skewed)] + + +def benchmark_skewness(filename): + from generators.nb_gm_003 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['time_per_block', 'seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + targets = trials / 3 + t = time.time() + seq = generator.generate(trials, targets) + t = time.time() - t + print(f"sequence {i}/{sample_size}: {trials} trials, took {t}s.") + writer.writerow(to_csv_row(i, seq, t)) + plot_skewness(fn, 'nb_gm_003') + + +def plot_skewness(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def plot_targets_ratio(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +def benchmark_targets_ratio(): + pass + +def benchmark_chunking(): + pass + + +def benchmark_n(): + pass + + +def plot_timing(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['time_per_trial'] = data.apply(lambda s: s.time_per_block / s.trials, axis=1) + plt.style.use('ggplot') + plt.title(f"{figure_title} - average time to generate a trial") + plt.ylabel('time (s)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.time_per_trial, alpha=0.5) + + # draw fitted curve + # import numpy as np + # p = np.poly1d(np.polyfit(data.trials, data.time_per_trial, 3)) + # plt.plot(data.trials, p(data.trials), color='red') + + plt.savefig(f'results/{figure_title}_timing.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + alg = 'nb_gm_003' + fn = f'results/{alg}_{n}back.csv' + benchmark_skewness(fn) diff --git a/tests/nb_gm_004_bm.py b/tests/nb_gm_004_bm.py new file mode 100644 index 0000000..b4ad4a8 --- /dev/null +++ b/tests/nb_gm_004_bm.py @@ -0,0 +1,26 @@ +import time +import numpy as np +import pandas as pd + +import tests.common as common +from generators.nb_gm_004 import SequenceGenerator + +def run(): + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, lures) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('tests/results/nb_gm_004_profile.csv', sep=',', encoding='utf-8') diff --git a/tests/results/2v4_time_trials.png b/tests/results/2v4_time_trials.png new file mode 100644 index 0000000..9be91b4 --- /dev/null +++ b/tests/results/2v4_time_trials.png Binary files differ diff --git a/tests/results/2vs4_skewness.png b/tests/results/2vs4_skewness.png new file mode 100644 index 0000000..a488e1f --- /dev/null +++ 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+210,87.0,0.0,0.0,88.0,1.0,0.0,0.0,0.0,EDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +211,0.0,0.0,12.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCC,True +212,0.0,0.0,0.0,66.0,0.0,65.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +213,1.0,0.0,0.0,0.0,0.0,21.0,22.0,0.0,AGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFG,True +214,74.0,73.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +215,0.0,5.0,0.0,0.0,6.0,0.0,0.0,1.0,HEBEBEBEBEBE,True +216,0.0,1.0,0.0,0.0,0.0,53.0,0.0,54.0,BHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +217,70.0,0.0,0.0,0.0,0.0,70.0,0.0,0.0,AFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +218,0.0,0.0,0.0,0.0,0.0,0.0,36.0,35.0,GGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +219,0.0,90.0,90.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +220,0.0,0.0,0.0,0.0,0.0,0.0,37.0,38.0,HHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +221,0.0,0.0,44.0,0.0,0.0,1.0,44.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +222,0.0,0.0,0.0,67.0,67.0,0.0,0.0,1.0,HDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True 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+409,0.0,0.0,72.0,1.0,0.0,0.0,72.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +410,55.0,0.0,1.0,0.0,0.0,0.0,55.0,0.0,CAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +411,0.0,59.0,0.0,0.0,0.0,60.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +412,61.0,0.0,0.0,61.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +413,0.0,1.0,0.0,75.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +414,0.0,53.0,0.0,0.0,0.0,0.0,52.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +415,0.0,0.0,16.0,0.0,1.0,0.0,0.0,15.0,ECHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +416,0.0,0.0,0.0,39.0,0.0,0.0,0.0,38.0,DHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +417,96.0,0.0,1.0,95.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +418,28.0,0.0,1.0,27.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +419,0.0,1.0,92.0,92.0,0.0,0.0,0.0,0.0,BCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +420,1.0,0.0,20.0,0.0,20.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECE,True +421,0.0,90.0,0.0,0.0,0.0,0.0,89.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +422,10.0,0.0,0.0,0.0,0.0,1.0,11.0,0.0,FGAGAGAGAGAGAGAGAGAGAG,True +423,0.0,0.0,0.0,74.0,73.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +424,0.0,0.0,127.0,0.0,0.0,0.0,1.0,0.0,GCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +425,1.0,9.0,0.0,0.0,0.0,9.0,0.0,0.0,AFBFBFBFBFBFBFBFBFB,True +426,0.0,0.0,84.0,0.0,0.0,0.0,0.0,84.0,HCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +427,33.0,0.0,0.0,34.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +428,1.0,30.0,0.0,30.0,0.0,0.0,0.0,0.0,ABDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +429,0.0,0.0,67.0,0.0,1.0,67.0,0.0,0.0,EFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +430,62.0,0.0,0.0,63.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +431,1.0,9.0,9.0,0.0,0.0,0.0,0.0,0.0,ABCBCBCBCBCBCBCBCBC,True +432,15.0,0.0,0.0,0.0,0.0,0.0,14.0,0.0,AAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +433,0.0,1.0,0.0,65.0,66.0,0.0,0.0,0.0,BEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +434,0.0,160.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +435,0.0,0.0,1.0,0.0,42.0,42.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +436,0.0,0.0,55.0,0.0,55.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +437,0.0,0.0,0.0,1.0,0.0,73.0,0.0,73.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +438,79.0,0.0,0.0,0.0,78.0,0.0,0.0,0.0,AAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +439,0.0,0.0,67.0,0.0,0.0,0.0,66.0,1.0,HCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +440,0.0,0.0,77.0,0.0,0.0,1.0,0.0,76.0,FCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +441,0.0,0.0,0.0,0.0,153.0,0.0,0.0,1.0,HEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +442,0.0,88.0,88.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +443,0.0,0.0,0.0,20.0,22.0,0.0,0.0,0.0,EEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +444,41.0,0.0,42.0,0.0,0.0,0.0,1.0,0.0,GCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +445,0.0,0.0,0.0,47.0,0.0,46.0,0.0,1.0,HDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +446,1.0,0.0,0.0,0.0,86.0,0.0,0.0,87.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +447,56.0,56.0,0.0,0.0,0.0,0.0,0.0,1.0,HABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +448,0.0,0.0,0.0,0.0,11.0,0.0,0.0,10.0,EEHEHEHEHEHEHEHEHEHEH,True +449,0.0,0.0,0.0,0.0,0.0,1.0,92.0,92.0,FGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +450,0.0,0.0,0.0,6.0,5.0,1.0,0.0,0.0,FDEDEDEDEDED,True +451,66.0,1.0,67.0,0.0,0.0,0.0,0.0,0.0,BCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +452,0.0,0.0,0.0,13.0,0.0,1.0,12.0,0.0,FDGDGDGDGDGDGDGDGDGDGDGDGD,True +453,1.0,0.0,0.0,0.0,56.0,0.0,56.0,0.0,AEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +454,15.0,0.0,0.0,0.0,0.0,0.0,0.0,16.0,HAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +455,0.0,21.0,1.0,0.0,21.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True +456,93.0,0.0,1.0,0.0,92.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +457,1.0,0.0,0.0,0.0,35.0,0.0,0.0,35.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +458,13.0,0.0,0.0,0.0,1.0,0.0,13.0,0.0,EAGAGAGAGAGAGAGAGAGAGAGAGAG,True +459,0.0,0.0,65.0,0.0,1.0,0.0,65.0,0.0,ECGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +460,0.0,0.0,95.0,1.0,0.0,95.0,0.0,0.0,DFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +461,15.0,0.0,0.0,0.0,1.0,0.0,0.0,15.0,EHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +462,0.0,0.0,198.0,0.0,1.0,0.0,0.0,0.0,ECCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +463,84.0,84.0,0.0,0.0,1.0,0.0,0.0,0.0,EABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +464,0.0,0.0,0.0,0.0,0.0,60.0,0.0,61.0,HFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +465,0.0,179.0,0.0,1.0,0.0,0.0,0.0,0.0,DBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +466,1.0,0.0,90.0,0.0,89.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +467,0.0,35.0,0.0,0.0,0.0,34.0,0.0,0.0,BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +468,0.0,0.0,0.0,1.0,7.0,0.0,0.0,7.0,DHEHEHEHEHEHEHE,True +469,0.0,0.0,0.0,0.0,92.0,0.0,91.0,0.0,EEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +470,0.0,0.0,46.0,0.0,0.0,1.0,46.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +471,0.0,0.0,0.0,0.0,0.0,1.0,158.0,0.0,FGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +472,1.0,0.0,0.0,0.0,0.0,58.0,0.0,59.0,AHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +473,0.0,0.0,6.0,1.0,0.0,0.0,6.0,0.0,DCGCGCGCGCGCG,True +474,0.0,0.0,0.0,0.0,0.0,98.0,0.0,97.0,FFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +475,0.0,87.0,0.0,0.0,0.0,0.0,0.0,85.0,BBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +476,0.0,0.0,33.0,0.0,0.0,0.0,1.0,33.0,GHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +477,45.0,0.0,0.0,0.0,46.0,0.0,0.0,0.0,EAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +478,0.0,0.0,0.0,77.0,0.0,0.0,75.0,0.0,DDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +479,73.0,1.0,73.0,0.0,0.0,0.0,0.0,0.0,BACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +480,0.0,1.0,0.0,0.0,37.0,37.0,0.0,0.0,BEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +481,0.0,92.0,93.0,0.0,0.0,1.0,0.0,0.0,FCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +482,0.0,0.0,0.0,1.0,0.0,0.0,0.0,24.0,DHHHHHHHHHHHHHHHHHHHHHHHH,True +483,25.0,0.0,0.0,1.0,0.0,25.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +484,0.0,0.0,0.0,0.0,0.0,37.0,0.0,36.0,FHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +485,21.0,0.0,0.0,1.0,0.0,20.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +486,0.0,35.0,0.0,36.0,0.0,0.0,0.0,1.0,HDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +487,0.0,0.0,1.0,0.0,97.0,98.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +488,0.0,93.0,0.0,0.0,0.0,1.0,0.0,94.0,FHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +489,0.0,1.0,0.0,93.0,0.0,0.0,93.0,0.0,BGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +490,0.0,0.0,0.0,70.0,0.0,0.0,72.0,0.0,GGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +491,86.0,0.0,0.0,0.0,1.0,86.0,0.0,0.0,EFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +492,0.0,65.0,1.0,0.0,0.0,65.0,0.0,0.0,CBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +493,0.0,0.0,0.0,69.0,0.0,0.0,0.0,1.0,HDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +494,0.0,0.0,144.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +495,0.0,45.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True 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+599,16.0,0.0,16.0,0.0,0.0,0.0,0.0,0.0,ACACACACACACACACACACACACACACACAC,True +600,0.0,21.0,0.0,22.0,0.0,0.0,0.0,0.0,DBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +601,70.0,71.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +602,0.0,0.0,0.0,1.0,0.0,0.0,53.0,0.0,DGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +603,45.0,0.0,0.0,0.0,0.0,45.0,0.0,0.0,FAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +604,0.0,1.0,56.0,0.0,0.0,0.0,56.0,0.0,BGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +605,0.0,1.0,0.0,0.0,0.0,0.0,0.0,195.0,BHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True 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+611,0.0,0.0,86.0,0.0,88.0,0.0,0.0,0.0,EECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +612,1.0,0.0,0.0,0.0,14.0,0.0,0.0,14.0,AEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +613,0.0,0.0,35.0,0.0,0.0,35.0,1.0,0.0,GCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCF,True +614,0.0,0.0,1.0,0.0,43.0,43.0,0.0,0.0,CEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +615,0.0,0.0,0.0,0.0,0.0,1.0,67.0,66.0,FGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +616,0.0,27.0,0.0,0.0,26.0,0.0,1.0,0.0,GBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +617,0.0,88.0,1.0,87.0,0.0,0.0,0.0,0.0,CBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +618,0.0,41.0,0.0,0.0,0.0,41.0,1.0,0.0,GFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +619,0.0,27.0,27.0,0.0,0.0,0.0,0.0,0.0,CBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +620,1.0,0.0,20.0,20.0,0.0,0.0,0.0,0.0,ADCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +621,0.0,0.0,1.0,24.0,24.0,0.0,0.0,0.0,CEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +622,1.0,0.0,0.0,0.0,55.0,55.0,0.0,0.0,AEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +623,1.0,0.0,0.0,0.0,26.0,0.0,26.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +624,0.0,0.0,15.0,0.0,0.0,0.0,0.0,13.0,CCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +625,0.0,0.0,1.0,67.0,67.0,0.0,0.0,0.0,CDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +626,0.0,0.0,65.0,0.0,0.0,1.0,0.0,64.0,FCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +627,0.0,0.0,0.0,0.0,89.0,1.0,90.0,0.0,FGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +628,0.0,0.0,0.0,0.0,1.0,0.0,51.0,0.0,EGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +629,0.0,0.0,41.0,0.0,0.0,40.0,0.0,0.0,CFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +630,0.0,0.0,93.0,0.0,0.0,0.0,1.0,0.0,GCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +631,0.0,53.0,1.0,0.0,0.0,53.0,0.0,0.0,CBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +632,0.0,0.0,0.0,14.0,0.0,0.0,0.0,15.0,HHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +633,0.0,29.0,0.0,0.0,0.0,0.0,28.0,0.0,BGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +634,0.0,66.0,0.0,0.0,0.0,1.0,66.0,0.0,FGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +635,0.0,0.0,62.0,62.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +636,0.0,31.0,32.0,0.0,1.0,0.0,0.0,0.0,ECBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +637,0.0,0.0,0.0,0.0,0.0,0.0,48.0,49.0,HGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +638,1.0,0.0,0.0,0.0,0.0,0.0,54.0,53.0,AGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +639,59.0,0.0,1.0,0.0,59.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +640,0.0,0.0,0.0,0.0,1.0,0.0,27.0,27.0,EGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +641,0.0,0.0,0.0,23.0,24.0,0.0,0.0,0.0,EDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +642,0.0,0.0,0.0,91.0,0.0,0.0,91.0,0.0,DGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +643,0.0,0.0,0.0,0.0,48.0,49.0,0.0,1.0,HFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +644,14.0,0.0,0.0,0.0,0.0,14.0,1.0,0.0,GAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +645,0.0,96.0,0.0,0.0,1.0,0.0,0.0,96.0,EHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +646,0.0,0.0,0.0,50.0,48.0,0.0,0.0,0.0,DDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +647,0.0,0.0,0.0,99.0,0.0,99.0,0.0,0.0,FDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +648,49.0,0.0,1.0,0.0,0.0,0.0,0.0,48.0,CAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +649,0.0,0.0,52.0,0.0,1.0,0.0,53.0,0.0,EGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True 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+667,1.0,147.0,0.0,0.0,0.0,0.0,0.0,0.0,ABBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +668,0.0,0.0,97.0,0.0,97.0,0.0,0.0,1.0,HCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +669,0.0,0.0,1.0,0.0,0.0,0.0,53.0,52.0,CGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +670,0.0,0.0,94.0,0.0,96.0,0.0,0.0,0.0,EECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +671,99.0,0.0,1.0,0.0,98.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +672,68.0,0.0,0.0,0.0,0.0,0.0,67.0,1.0,HAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGA,True +673,0.0,0.0,0.0,26.0,27.0,0.0,1.0,0.0,GEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +674,31.0,0.0,0.0,0.0,32.0,0.0,0.0,1.0,HEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +675,0.0,0.0,0.0,0.0,42.0,0.0,41.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +676,0.0,0.0,50.0,0.0,0.0,0.0,1.0,50.0,GCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +677,0.0,25.0,0.0,24.0,0.0,0.0,0.0,0.0,BBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +678,0.0,0.0,0.0,0.0,1.0,10.0,9.0,0.0,EFGFGFGFGFGFGFGFGFGF,True +679,65.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,DAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +680,0.0,23.0,0.0,0.0,0.0,0.0,23.0,1.0,HGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +681,0.0,1.0,58.0,0.0,0.0,0.0,57.0,0.0,BCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +682,0.0,0.0,0.0,0.0,0.0,68.0,1.0,68.0,GFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +683,0.0,0.0,0.0,0.0,96.0,0.0,96.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +684,1.0,0.0,0.0,0.0,66.0,0.0,66.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +685,0.0,0.0,0.0,0.0,0.0,1.0,0.0,21.0,FHHHHHHHHHHHHHHHHHHHHH,True +686,0.0,88.0,0.0,87.0,0.0,0.0,0.0,0.0,BDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +687,0.0,0.0,19.0,19.0,0.0,0.0,1.0,0.0,GDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +688,0.0,42.0,1.0,0.0,41.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +689,0.0,0.0,0.0,0.0,0.0,60.0,61.0,0.0,GGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +690,0.0,23.0,23.0,0.0,0.0,0.0,1.0,0.0,GBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +691,86.0,86.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +692,35.0,35.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +693,57.0,0.0,0.0,0.0,0.0,58.0,1.0,0.0,GFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +694,0.0,0.0,30.0,30.0,1.0,0.0,0.0,0.0,EDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +695,19.0,18.0,0.0,1.0,0.0,0.0,0.0,0.0,DABABABABABABABABABABABABABABABABABABA,True +696,0.0,0.0,0.0,1.0,0.0,56.0,0.0,57.0,DHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +697,10.0,0.0,1.0,0.0,0.0,0.0,0.0,11.0,CHAHAHAHAHAHAHAHAHAHAH,True +698,0.0,0.0,89.0,0.0,88.0,0.0,1.0,0.0,GCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +699,0.0,0.0,87.0,0.0,86.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +700,17.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAA,True +701,0.0,0.0,66.0,65.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +702,0.0,0.0,1.0,0.0,0.0,0.0,123.0,0.0,CGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +703,0.0,118.0,0.0,0.0,1.0,0.0,0.0,0.0,EBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +704,0.0,0.0,0.0,0.0,0.0,0.0,0.0,132.0,HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +705,0.0,0.0,0.0,0.0,0.0,23.0,1.0,23.0,GHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +706,0.0,0.0,0.0,0.0,6.0,5.0,0.0,0.0,EFEFEFEFEFE,True +707,18.0,0.0,0.0,16.0,0.0,0.0,0.0,0.0,AADADADADADADADADADADADADADADADADA,True +708,0.0,72.0,0.0,0.0,0.0,71.0,0.0,1.0,HBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +709,0.0,0.0,54.0,0.0,0.0,1.0,0.0,55.0,FHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +710,0.0,1.0,87.0,0.0,87.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +711,0.0,0.0,1.0,63.0,0.0,0.0,0.0,64.0,CHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +712,78.0,0.0,78.0,0.0,0.0,1.0,0.0,0.0,FCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +713,0.0,80.0,0.0,0.0,0.0,81.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +714,0.0,1.0,0.0,0.0,0.0,0.0,40.0,39.0,BGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +715,0.0,0.0,7.0,0.0,6.0,0.0,0.0,0.0,CCECECECECECE,True +716,35.0,0.0,0.0,0.0,0.0,0.0,0.0,33.0,AAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +717,0.0,0.0,0.0,1.0,73.0,0.0,0.0,72.0,DEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +718,0.0,0.0,90.0,0.0,0.0,1.0,89.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +719,1.0,0.0,0.0,67.0,0.0,0.0,0.0,66.0,ADHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +720,56.0,0.0,0.0,0.0,56.0,0.0,1.0,0.0,GAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +721,0.0,0.0,0.0,1.0,0.0,0.0,49.0,49.0,DHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +722,0.0,0.0,0.0,117.0,0.0,1.0,0.0,0.0,FDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +723,0.0,0.0,86.0,1.0,0.0,0.0,85.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +724,0.0,0.0,31.0,0.0,0.0,0.0,0.0,30.0,CCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +725,1.0,0.0,0.0,0.0,98.0,0.0,98.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +726,1.0,84.0,84.0,0.0,0.0,0.0,0.0,0.0,ACBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +727,0.0,56.0,56.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +728,0.0,1.0,0.0,24.0,24.0,0.0,0.0,0.0,BDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +729,37.0,0.0,0.0,0.0,0.0,37.0,0.0,0.0,FAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +730,0.0,0.0,91.0,0.0,0.0,0.0,91.0,0.0,GCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True 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+772,0.0,68.0,0.0,0.0,0.0,0.0,0.0,67.0,BBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +773,60.0,1.0,0.0,0.0,0.0,61.0,0.0,0.0,BFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +774,0.0,1.0,0.0,57.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +775,0.0,78.0,0.0,0.0,1.0,0.0,0.0,0.0,EBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +776,1.0,0.0,0.0,0.0,0.0,96.0,96.0,0.0,AGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +777,43.0,0.0,0.0,0.0,0.0,1.0,44.0,0.0,FGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True 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+989,93.0,0.0,92.0,0.0,0.0,0.0,0.0,1.0,HACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +990,0.0,1.0,0.0,0.0,60.0,0.0,0.0,61.0,BHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +991,0.0,1.0,0.0,0.0,0.0,0.0,32.0,32.0,BHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +992,0.0,0.0,34.0,35.0,0.0,0.0,1.0,0.0,GDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +993,0.0,0.0,0.0,0.0,54.0,0.0,54.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +994,0.0,0.0,0.0,1.0,0.0,39.0,0.0,38.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +995,0.0,0.0,0.0,0.0,99.0,98.0,0.0,1.0,HEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +996,86.0,1.0,0.0,0.0,0.0,86.0,0.0,0.0,BFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +997,0.0,76.0,77.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +998,0.0,0.0,19.0,0.0,0.0,0.0,0.0,1.0,HCCCCCCCCCCCCCCCCCCC,True +999,0.0,0.0,37.0,1.0,0.0,0.0,38.0,0.0,DGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True diff --git a/tests/results/nb_gm_001_3back.csv b/tests/results/nb_gm_001_3back.csv new file mode 100644 index 0000000..b2f89a4 --- /dev/null +++ b/tests/results/nb_gm_001_3back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,0.0,65.0,132.0,0.0,0.0,0.0,0.0,1.0,HCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCC,True +1,51.0,0.0,52.0,52.0,0.0,0.0,0.0,1.0,HCDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACD,True +2,0.0,61.0,0.0,62.0,0.0,0.0,61.0,1.0,HDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGD,True +3,40.0,0.0,0.0,1.0,0.0,0.0,0.0,80.0,DHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHA,True +4,4.0,0.0,1.0,0.0,0.0,6.0,0.0,0.0,CAFFAFFAFFA,True 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+401,0.0,55.0,55.0,0.0,0.0,1.0,54.0,0.0,FCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCB,True +402,47.0,0.0,0.0,0.0,1.0,47.0,0.0,47.0,EAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFH,True +403,56.0,0.0,0.0,0.0,58.0,0.0,0.0,56.0,EEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAE,True +404,0.0,39.0,0.0,0.0,39.0,1.0,40.0,0.0,FGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEG,True 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+3,12.0,15.0,11.0,20.0,13.0,17.0,17.0,22.0,AFAHGHGHGBEBCDDDDHHHABCEHEHEBBBAHADADCFHHHHHFEFCBDDFDGDEFCAGGFEFBDGEHECCBCFFFFFFHGEBBHHCBCACHHDDBFGGGGEGEAFDGDADGDGDGBEBAAHDDFH,False +4,4.0,4.0,8.0,8.0,5.0,7.0,4.0,2.0,FGDGECDCECGCDADAHFDFCFCGAFCDDDABEBHBEFEFBC,False +5,15.0,15.0,15.0,16.0,16.0,14.0,9.0,13.0,HGDGBFDHDADHBBBBBHBAAGBCEABCGFAFAFBGBCBFGDDDEAAAHDFACECECHFHFHFCFHEGEFEFDFDAAHDEECDABFCCCCGBEBDAHCECHCHEDEDEDAGEE,False +6,17.0,17.0,9.0,6.0,15.0,13.0,15.0,12.0,BEBEBHAGCFEHHABAHDEDGHFBFGFCAABAGFFFAFGECEBEAEAFBFCEBEGHGDBEFABABEGEHEHBGBGDADACAGHGHGBGBACGCAHFFBHAECDC,False +7,12.0,7.0,7.0,6.0,9.0,8.0,5.0,6.0,CEGBFEFEFEHCCDEBCCHBBBGAHACBGGDBDADACADHDHFEAEAEFGFAAEAHAFAF,False +8,9.0,13.0,10.0,11.0,12.0,15.0,11.0,12.0,CGCFDBDFHHEHFFGCDHEHCFCFAAEGDCEGHGCFCBBBCBGFGHGDFDBDADHBBEGAGABABHBEBEHGHADAFEFCFDBDEFEHEFEFA,False +9,13.0,26.0,23.0,14.0,20.0,18.0,19.0,27.0,HECEBEFFHFDCCFGBCBDBAHGHGCBBABHEFAFEBEBHBHGGCHBGGCCCCCFCBDDDEDHDEEEAAFAFGFDFCGBGHEHDHGHAFABCGGEHEHFBGBADEBEBEAAHBDCCFGGHHHBHBHGHBDBEEAEGCGCBCHCEFFFFCHDHCHDHABCB,False +10,14.0,18.0,15.0,13.0,15.0,19.0,18.0,11.0,AFACABDDFBBBEBECECGHFBFBECDCEEEDGDBHHGCBDDAFCBAAAGHCHCHEAFBFDHAHCFFAAAHBBBFBFBHGFBCBCFGGGHGDGDFEGEFCFEDGDGAGEGCGEGEFEFAFDGC,False +11,21.0,20.0,21.0,13.0,15.0,26.0,21.0,21.0,EECEFFHGCADHGEGEABCCFDEBABEBGGCACHFHFBFBFBAHGBGCGHDCDABHHAGABFHEBCFEGDFDFDFAFBCBCAHACFGFBFBFBFBDACCBCHFHEGEDFDFCAAAGGEBFAAACACHCHFGFBFGHGHAEAGCCEDDFHHHGHGHGDE,False +12,17.0,26.0,17.0,23.0,17.0,11.0,26.0,21.0,ABGCACGDDFHFHBCEHEAGBGBEBAHEBEBFAAHAFBCEGDGBAHGGGGFGDDDBABABHGGGCGDGHGHDACAEDEFECHGEGDABGCHCDDDDCBCBADAHCHGBGBGEHDCDBBFBABHBHBFBACHDEEHGHECDCDHDEFEDECFGHGBFBD,False +13,24.0,21.0,23.0,20.0,15.0,14.0,30.0,24.0,AHHHHAFEDHAFBFGFCFGADADCDGBBBBGDGEGBCBHGGGGCGFBFAGGGGHEEFEGHGHABCBFHGAGACBBDEDHDHDGBCACAHGCACEHECACHBHDCGCECADGDGDABADHFGCGAGAHHBGFDCHBHCAAABEEFDFDBDBEADAHGEGEHECCCBCFCAHD,False +14,1.0,0.0,2.0,1.0,1.0,1.0,2.0,2.0,DECGCGAHFH,True +15,7.0,7.0,10.0,5.0,8.0,4.0,8.0,9.0,HBABHHEEGAGAGEGHCDEECHCHGBCBCDDAEGCBCGEAEFDFBFBFAGCHCHCHAD,False +16,14.0,19.0,14.0,7.0,10.0,15.0,19.0,7.0,CEAFFGHGEGFDFDCACAGBDEAFCEDDFAHHFDFGBEACGCGBGAFECECFGHCEBAFGEGCBABEBHBHBACAGAGDGHBABCBCBGFGFGFGBBBBFBCBGA,False +17,17.0,15.0,14.0,12.0,10.0,9.0,17.0,6.0,EBACADACGBGBAFGHGHADCDGAAFFFADABAHGDGABBCBCACACECHFBFHDCACDGEBADDEGGGEDADFGFGCGFBBABCBEBDBCHGEGEGECE,False +18,14.0,22.0,17.0,9.0,14.0,10.0,25.0,20.0,EHCHAHEHAHCHCGBGCGCGAEBFBFGGCEFGBGHAHCBABABHHGHGCACHDEDBBABGGDGDEBBBHHGCAEGBFHGEGEGBCCGCDFBBGBFBDAEEHHHCFEFECEHGCGCBHDADFDAGAGAGFBB,False +19,13.0,27.0,12.0,18.0,19.0,17.0,20.0,18.0,BFGCGBHAHAHEFEDBABEBEDADGGGGBAFCGEBDFHBHGHGCBBEGEGBHDHDHBCBCACDBFHHCHBGAGAGEDADADCDCACGHEEEEBDFDFDHDCGGBGDEBBBABEHFHGEFFFBADHEFFCFDEBEBFFEBHBFBG,False +20,11.0,10.0,7.0,8.0,8.0,7.0,11.0,4.0,BGBABGHGCGFBFAEBGGEDEFAHEHACDCDADBGGAGAGADFBFBCBCEFBFDHDACCDAGAEEE,False +21,22.0,20.0,18.0,24.0,13.0,11.0,16.0,21.0,DADADHCACFCHEDAAAHGDDHAGCDEDEGBHAHBDBDBGHHHCHCECAAAEFEDECEDBHFABGBCAGDBEGEBABHFCBBABDFDGHGCBFBCCDHDHDGDHDHCHBGADAFACHEHBDCDAFAFAFAGGCGCFHGBDBEBEG,False +22,8.0,10.0,11.0,7.0,8.0,15.0,4.0,11.0,CBAEGDGEHEBGBFBFBDHCHFHBAEHFFGFCFBFCFEEHABECFFFFACAEHHDCDCDHDHAHCFCBCBAADF,False +23,32.0,19.0,21.0,23.0,13.0,27.0,21.0,27.0,GHCABDGDFFFAHHHEAEHGAGAGHEFEGBCFAFBFGCHCHFHBGCAFFDFDBACACHCHCHBFGFEACAFABEBEBHHGHFHAHGGAGAHAFCGDHDHAFGCBCHDAAAAAAFCFHGEFFBEBEDDDFDBCBDDDCGFAFADBDBEBCAGGHDFDFBCDEAGAHCCEHGHAHCDDDDABAFA,False +24,26.0,30.0,18.0,21.0,29.0,16.0,21.0,21.0,GDGDADAGAGDEHCDBDHAHEHFHAHAFBHBHGCEBHBDBHBHBEEABABABAEECEGEGAGADHDBEEGBCAADHGBFBCEAAHDEBEBFBFBFCCGCEFBABAEDBGFGBGCFCGEACDFEFBHDADFHCEAEBDHDCGBEFGCDCACDEBEGAGAEAEFDFBBEHEGEGHCACEFBHDH,False +25,17.0,15.0,10.0,21.0,16.0,11.0,16.0,22.0,BDBDBHHHAAGAEHEHCHCDADEBGHDAGEBHGAABADADEDECEHAHFBGCGBEHCGADFBHECGHHFFFHFBDDDDDFDFDFHFEDEDACAEAEBDCHHBFBABCBGDGEAECHHGHGEGHDAGGG,False +26,12.0,13.0,16.0,11.0,17.0,10.0,17.0,12.0,GEECBGFEEDHCEFGFEAEAHGEGEDDDHDCDCBHBCBCFCECEGAGAGAHECFCEAAFGFGCEHGHBBBGBGBCBDHEAEFHFHGBCDGGACHCGCDADAEBFBADH,False +27,14.0,11.0,17.0,13.0,14.0,21.0,16.0,19.0,AAECGGEGHCACACACHBHADCECBDHDHDFCFGHGDDEDHHHAHDFDACHBHAFBHHAEEECGGFGEGEBEFCFAEAEFFBFBFDGDGDGHFACCDFHFCGBBHBCGGFGEHEFFFFHFCBCAF,False +28,14.0,15.0,12.0,21.0,15.0,9.0,13.0,21.0,GGHGEDHFCFCACBCADAEEEEAHDGAGHGHEHEHBBECEDBBBDBEGDGBAEABCCABBECDDDFDFHGHGHDHGHGHDADHHCHBHCCBAFHFDDDEDHFHAABDFDFEGEAADBDCH,False +29,18.0,19.0,27.0,26.0,29.0,30.0,16.0,16.0,DEFFFAFAGDGEEBFBFGEBADACADFDCEEDEDFDCDEBBGDGHGHGFFFDFBEBEHCHFDCDCEGFGFHFEFCGBBDCHCGCDADEGEGCFAAEHEHFDACGCEABBDECBCBCEFEFBFCFCFEHEHDGACEBAGCEFEBACCCAEDHDHBCFCDEFFHDHDHDCFCAAAEBEBFDHA,False +30,5.0,11.0,5.0,8.0,3.0,2.0,5.0,1.0,BBFGGBABFGCCCDADAHBEDCDBABGEAECBDBDBDBDG,True +31,28.0,17.0,19.0,16.0,18.0,11.0,17.0,33.0,DHAFAHAEAHDHFHFAFADHCGGGDGDGHEBDHCHBHAEBCBCFEGHHHBHCAFDHEHEHCDAGBCBAAAGACCBCAFGBHEHBBEAHAHAFAEACGGEHAFABEDEDFDCGHEBGAGEEAEBBHDEDECHCGABHGHAHAHBHCHCHCHDGACACDFD,False +32,5.0,10.0,12.0,17.0,19.0,17.0,17.0,11.0,EEBHBFFFDDEDCCAGEFEGGDGDFFGEGEAEDEFCFCGCGCGFAEGECDHHCEFDDHDFDABFDECECEHEFDDGDGBBFBFHHGCECEFEHAHDHDGBBFBGHGBG,False +33,4.0,13.0,10.0,7.0,4.0,8.0,11.0,7.0,CGBHBCBCBHFHFECBADGBGBGBDBCFAGDBHGFGECEHBGBCCACFGFGFGDDDFCADHEHB,False +34,22.0,27.0,22.0,21.0,21.0,28.0,21.0,21.0,BABFBCCCCGCDCAGABAHFBAHCBDBDHDCDCDEFFHBHBCBCBEHDAGAEFBBEEEBEGAGHGDGCGEBFBDEAECCFCFGDGDGHBHAEFFFECCADHFFBGHDHEGAAEDEFEFCDCDCDEFCHADAEHFDFHBBEBEBFBFAFGFAAHGHGFFAFGGBABGHGBFBFDFHCHAHEGDA,False +35,24.0,23.0,21.0,17.0,28.0,15.0,20.0,21.0,EGHGAGEGCGDFFCEEEEEAHGEGFGFBCBGBDBACHCAGDDDDEDEHACGCECAFAFEFHCHCEFHDHEHBAEADBDBAFCHCEEEEHBHBECEAEAFGGGGCCHBHAAACABBEHFHBDFHHDHBGCAABEBGAGABBFADADEBBBBCDCACFGFHDCEHEBGADE,False +36,16.0,12.0,18.0,16.0,29.0,20.0,25.0,11.0,EEEBCFFDHDBBGHGHGEFDFACCCFCGAECECEAGFFFCFDAHAEEHGGGBGBGADDGDGEGCCBFEHEGEHACDGDGCCCFCEAFAEGEGBGFGBBBHFGDGFGAAHADADCEEEEDEAEFEAEBFFFHEGECEGEHECAFDDDB,False +37,1.0,6.0,2.0,11.0,2.0,11.0,4.0,7.0,DBFFFHHADFFEFBDBFBGDFFEBHBHFHGDGDGCCDDDDHDHF,True +38,11.0,12.0,15.0,5.0,3.0,15.0,15.0,13.0,HCCCCAEBGFCFBGAHHHHBAFGCGCGCGFGCAABFBABHBFBCAFHFAFGCDBGBGAGFCBBAADHDHDCGEGHGCGFFHFHDEFHFC,False +39,33.0,14.0,21.0,23.0,21.0,18.0,25.0,28.0,DHAHAHADGDAFAFGCHCHEHCHABACEDDDCGBHAEFFGCADADGBGCFFFGGHBAAFGGHFHFHECFCHCHBDEFGADDCGGGHEBEDEBEBEDFHCAAAACFGFBFBFADAEGBDCAGACACAFGEEECDDDDCGGGEEEEEGCADHHHHAHABAHGBBCACHEGGHDADADAHAHEHAH,False +40,9.0,21.0,8.0,6.0,13.0,11.0,9.0,15.0,HEBEGEGAGEBBBHFAFABCBCBEBCBEAFHGGGHEHCHBEDFFAFAHDBFBFBEBDFHHDHBHCHBHBDEFABGBCEDEBCACHHEAGBGF,False +41,13.0,18.0,18.0,16.0,8.0,20.0,16.0,13.0,AGDGBCDHFADAGFFFHHCFCFEBGBGFGFGCGCHHHHCGFBFGDHABCBCGDGECEFBFCACBDBDCFAFBDEDCFFBHGHBEBABDFDFDHDHACABDBAFAFDHEGACACBEECGCBDG,False +42,21.0,15.0,14.0,22.0,14.0,22.0,16.0,21.0,ACFDFDEDFDBAFDCDCDFFFFFACHCHGEDFCFEHADACEHEDEBAFAGGHGEDADFDHDHDHGADAGCCCFHBDBGBDEGEBHGFGHAHFBFBFEAABABACDDAHHGFGBGEGHFEABHBFEHHHGDFDCACABABGECHAH,False +43,17.0,19.0,23.0,19.0,19.0,21.0,20.0,22.0,GDGFGEDDDDDDFDFDFEHBHDGAECBHDEGHGEEDEBEDECGGAADAFAFADECFCDGDGFBHGCBHBACAGACFCGGGBGCHFHEHECECAHFHFGCGHBFCGCBCFEHEGEHBBAAABDHFBCCCCFFFHFCABFBHBHBEDAFEHBHACABECHCH,False +44,2.0,1.0,3.0,4.0,5.0,3.0,6.0,5.0,CHCHFGBGEHFDAGADEDEGGFGEDEHCH,True +45,17.0,20.0,26.0,20.0,18.0,24.0,15.0,12.0,BDEFBBBHHECFCFCBBFEDDADADGECEHEFCGCAFDCGCFFEDDGGHHHHHAFAFEFAFDFDFDEDFAACFCFCDCBBBCGCGDGDFCGCGBDCACBHDHEECBBEBECFCHGBGEGABCDCEFHFGACDFAFAECEBEBDACABAGFBA,False +46,5.0,7.0,11.0,5.0,5.0,3.0,8.0,10.0,CBDHFHCDCEGEHCHCHCHEGCGCGBBBBADAHGDGBACGEAHBHFGFCECAHD,False +47,5.0,4.0,4.0,5.0,0.0,1.0,5.0,3.0,ACABGBHBHBGDCACHCDAGFGAGDDD,True +48,21.0,22.0,13.0,24.0,16.0,18.0,24.0,19.0,DBDGAGBGFHFCABGFECEGBGHHEACDFDGCGBEBGDAFAHADADAHHBHBHAGABADEBFDGDBDGDGCFAFAFDDDDECGFEFEAHAHEHEHCBCDADGBFBFAEBCAHFHEDEGBBFDEHEBDHFGCGHGHGBGCDABCBDGHGBGDCEAFAF,False +49,5.0,12.0,11.0,8.0,8.0,7.0,11.0,9.0,FCFDGDHBEBECFBBHFCFCGDBCCCGCECECBDBGBEHDDBCAGAEHEDFDHGEGAHBHGAGAGFHBHBG,False +50,2.0,7.0,7.0,4.0,6.0,13.0,10.0,11.0,BBFEFEFHAHFDFGHEBABDFHBHEFGFGHEHGGGFDFEHCBGBFDFHFHCCGCGHGCCC,True +51,5.0,7.0,11.0,12.0,13.0,9.0,8.0,13.0,EFFBFDAAECCCHDHBHFEDBHBHDHDGGGGECDGHCFEFEDEDCDCDEDCCHFEFEGCGBHEHBHAHAGDFCEAEHB,False +52,15.0,6.0,11.0,6.0,11.0,16.0,3.0,8.0,BAEGCCEAHBFCCHFABEHEFDCHEBECACECEAFGFEFEFBFBFAFADADACACDFGFAFAFEFDAAHFDCAHHH,True +53,20.0,14.0,19.0,11.0,13.0,12.0,10.0,17.0,CHCECEHEGAHBFGHCHABCBCDCECEDAHACGCADDBBGFGFGFHAAACACFBEGGAGAEHCAAAFDFDCHBDBHGDFDHCBEFEBCBABHHHHDHCHDFEFABEBECAAAEACF,False +54,18.0,14.0,15.0,22.0,24.0,20.0,25.0,23.0,EGGCGCGDEDEBCBFDDDBFHDDGFBFEEEGDBDBEHFDFEACACADABEFDCECGGHBDCDBAGHGFBFECHCFEDEHEHAHEEAGCEEEEFGFHFAAGEEHHHHAHAHDEFGDGDBCGAGHFHFHAHAHDHDBFBFCEGGGGGGGHAADAGCDFFAHCB,False +55,3.0,4.0,2.0,5.0,2.0,5.0,3.0,1.0,EHAABABGBFDFGFGEDDFDCBCDF,True +56,9.0,9.0,8.0,11.0,11.0,13.0,8.0,11.0,ECFFFBCDEDAFEBEAFGFHFHFDEHEBEHEGBFEFHBABCCAGAGBGBDFHAHGHFCFDHDABADEDEDAHGGCDCHCD,False +57,10.0,13.0,10.0,15.0,7.0,9.0,16.0,11.0,HHCFEGEGEDFGABEHEADCHGHBDFDGDGHGCGBBDDCDCDBDBHCDEBAHACCFDGDFAFAFDDAGAGHGCGBGBHACBGBGAHEBFBF,False +58,15.0,15.0,14.0,21.0,27.0,24.0,20.0,28.0,FAFEFAADAGFBFACBCBHHCGFGFAFHCEGEGHHBDBFHFHBEGDGDAEEHEGCGDGHCDGDEHFHGCEEEGEGEDBDEEEEHHHHCHDAGFEBHFHAHFHFDDDCACHFBDDHDGDFDAGGEAEFBHEEEEBEHEFFCFCFDBHAFADCGCGFHDHEBABHB,False +59,11.0,16.0,18.0,17.0,22.0,31.0,15.0,17.0,FCECFCFCFBHCHBGBFHGEDADADEFEFHFDFDADEEADHGAEAECGDGCCFHFGFHFHFHFBFBFCEEEBEFFDEGGBHBEBHFCDDDDGHAFBFBFCACHCAFGCGHHEDCBFEFABCDCEGGGDAEBBBEDEFFFFECGHEHF,False +60,11.0,9.0,7.0,2.0,10.0,10.0,11.0,9.0,HGHCDCHCACBCEGEGEGEBBHCFGABEBFAEHHFBFAAGHGHFHABABCGEGFDEAAABFEFEFGFGA,False +61,23.0,23.0,21.0,24.0,24.0,17.0,27.0,24.0,EDGGCBCFCGCGCFCGCDCBAACHFHFHECACAGAHFHDBDEHAGADHGEGEBCAEAGDHAADDDDCEAEADBGFDBBBBDHDGDBBGCAAEHEGDGBGBFHCGCDBBBEFHFDAGHCDCHFHFGEHEGEGHGBEFACADAFCBGBGBFHDEDEDFBFEGHGHAHAEEEEGEDHAHACEFBHB,False +62,21.0,13.0,9.0,12.0,17.0,15.0,25.0,10.0,HFGFGBGEDEHGHAHFHGAAAFGHBFACGDBEBGAAFEGEFEFBGAHDEDECBCBFBEGAGAFCCBBDBAGABAGGGGGECDADAGAEFEDGACADDCDHDEAFHFHFGGGFGCABAEEEGE,False +63,6.0,6.0,3.0,12.0,7.0,8.0,6.0,13.0,FHEBEBHGHDAGHDCDEDEAFCFCHEEBAAFDDDFDHDAGBGFDHGHAHDHEHFHFHBDBG,False +64,6.0,15.0,15.0,8.0,14.0,13.0,8.0,8.0,CCEDEDBHHGDCBEFEFCCGCEAGFGEGECAHAHGBCFHACEBEBEGEFFFFBDBFBHBDDEDCBCBHBFGFHEAEBCBCFCBCAFD,False +65,6.0,4.0,3.0,4.0,6.0,8.0,5.0,5.0,CGCFEFAFAEEDEHCHBBDAAFAGHEHEBFDHDBAGFGFGF,False +66,17.0,8.0,15.0,6.0,16.0,16.0,11.0,12.0,AFGFGFGHGFECECECHAECCCFAHAFAEHGGCEBAFAEAEFGGHCBFAAEHFHFGBHEHGAFBFHCECEADFDBDBCACACAEAEBEDDACBDFHFHEGC,False +67,24.0,12.0,23.0,14.0,18.0,18.0,15.0,12.0,CCCFCFBHAEEDFDBAADAEAEABDBDGEHEGCCCACECHGEGEDECACFCFCHBFBAGAFFGHADBEBAAAAFAEECEDHDHECGGBHHCHDBGBABAGEFFGFAFADACADAGADCHFECGFGFHFCDCEGFCC,False +68,31.0,17.0,27.0,38.0,29.0,28.0,14.0,16.0,ACACBCFDGBHBDEGEAHDDEFEFEFEFDDHECEBDFDAEAEFECECGCHAHAHCBCDAHBDDDDEDEBEHGDDAFEFCFDDBCGAGACCECAADADABAFEDACGCAFAHDFDBDGCECBGBFFCHCGAEDFFFHADFDADGFAFADEDHABAGAGEHEFBFECEDEDCGEADADFDHBHDFDCBCFCDAFAECFCEHB,False +69,5.0,4.0,3.0,4.0,2.0,3.0,6.0,4.0,DAHAGAHAHAHFGCGEBDFDEDGGCFBBGBC,False +70,5.0,7.0,9.0,5.0,2.0,11.0,6.0,10.0,HAHDHDHBGBFCACDCHFBBHBHGDEACACEGFCDHBGFGFGFCCHBFFHFCFAF,True +71,11.0,10.0,6.0,19.0,14.0,23.0,11.0,9.0,FHFEADABECHFFDFDFHFEDECEFEFEFAFHDADAEADDCAGFGBBHGDGABDDFFFFDDDADEEGFGDABCDGGBHDHFGAGBHBHBEBEGFFFFFCCEDE,False +72,25.0,17.0,20.0,19.0,16.0,13.0,17.0,22.0,GDCDHGBEAEGDGEBDBDHDCDCBHDEAEHDCEFAAABCDCDABAGADADCFAFCGCACAFFBAHGCGCGEGEACHHECACECEHEGGFBDHFHAHAHGGDGFCECHFHFHCHFABABFDGABDEDABABHEACAFDHHGHAHBBBBEH,False +73,15.0,19.0,20.0,23.0,23.0,21.0,22.0,23.0,GFGFECGCEEGHFCBCFDDDHHGBGHGHDCDCFHAHCCCFHAADEBEHEDEDADCDCABEGEFDFHCHGGAHAHFCFCEADFFECGBDBDBDCCACADHGCGEGHFHGHGBFADEBEBEDGDBBACEEEHGBDBFFFFDGEGDGDGFBEHHHHAAEAEFBBBBEFH,False +74,3.0,11.0,6.0,11.0,10.0,12.0,5.0,7.0,ECHFHDHEFFHHDCFGEGFDBEBEFFFDBCBFEDCDCFEBBFADDBDBGBGBGBAHAHFDEDECE,True +75,21.0,13.0,22.0,19.0,30.0,19.0,18.0,19.0,HAHEEEFEDHDFDBHBGCCEEFEGGHGHCCCCCHGECEAHDBDBEFGHCACGBEFEHAFDFACAFEEEHABAGAFDGDADADAGBCBAEADAEFHCDCFGEHFHDEDCDFEFCCCEAEAEGGABFGEDBDBHBCCECEHEAEFGHGHDDAEAEHCFGFGFB,False +76,14.0,30.0,18.0,20.0,25.0,19.0,27.0,30.0,FCFBAEDEGEHEBGHGFEFCGDBDGGCGCGBEBHBHEAAAEECBCBCFHFCFDGAEHHFGGGGGHCHEHBABGBGHHDFAEBDBDBDBCCHAGGEGDGCCBCHFGFGHGHBHEFGHBFBCBHEHBBABCBHBCGEHEADDDBHFHAADEDBFHFEEGEDHDHDEDBDFEFEHCHAEGDHBFBA,False +77,25.0,17.0,30.0,29.0,22.0,22.0,23.0,24.0,CCHEAEHBBCBDADBDBDHGFEECBDFGFEAHDCGCDHHEHEHCGCFHGDGAGAGACACDDDFDFDGECCHDHCCEFAFEBAFGGHDCCGEDBDBDBCHCACDBAHCGCGAHAHAFFFHADCDCFCFHHCDCAEAGAGAGABFHGEGBGDFHEBEFCFAGBEEAABAGDGDFDFEABHCDEDEHEHEFCFCD,False +78,9.0,16.0,9.0,5.0,4.0,15.0,4.0,5.0,BCEADCBBBBABABCCEHFBDHFAAGAGHCFCBCBFDFAGAGBFBDBABFFFFFCEHEBDHFFFBFC,True +79,19.0,17.0,10.0,29.0,13.0,8.0,14.0,14.0,DEDEAEAEDDDDDDDHDGEBEFADAGBFFHDGFBBBBGBABFCHGDFDEACBBBAHADAHCGCAHDHEHABAGCGCGEDAGBDAACAHDBCBGBGBEDDDDDADGDFDHHFDAHAEEEHCDCHG,False +80,9.0,11.0,7.0,9.0,14.0,3.0,11.0,16.0,HEHEACBHBHAGEBEAEBHBHBDEDCFABCGAEABHEHDADABABGGGDGHECEHHDGDHHCHCDGFFHCBEDEGEGHGE,False +81,4.0,9.0,4.0,9.0,3.0,6.0,6.0,5.0,BGBACACHDGDFDFBFEAHFBDDEDEGHGHBBBFBADHDGCGDBFC,False +82,11.0,21.0,22.0,24.0,26.0,28.0,21.0,21.0,EDGDCDCFGEDEFFFFGEEEDEDEDADACHCEBAFAFCHEDBFEDHDCCAHGFDFDGAGEFECEDBHCECDGGGGGBGFGBHCGDGFFDCAGDBCEHEGBBBBHFHADFHCHCHCACHCBBEFAGBGBEBFFFHFBCEDFFEFHDHFHFCCECBHBDBDEDEHBHEHFBFEGAG,False +83,2.0,4.0,1.0,3.0,2.0,4.0,2.0,1.0,CBFHFBBDGDFDFEGEABA,True +84,18.0,13.0,21.0,13.0,16.0,19.0,15.0,8.0,CBCEEADAFGDCFHFHDHFACACEDGACFGGGCBABDCCCCCCBABABABDBDFACGCGCFCAGEFEFBDBCFEFEAGFDBEFEHEHBAEADAFAFGEGECAHFEDGDHHCAEDEFCFGGGBF,False +85,14.0,12.0,10.0,10.0,16.0,19.0,9.0,12.0,FGBGHDEEEGBFAEAEDHGHGFEDEFEGEDEFEFCBAHCHCFBFDGECFFFGAECBBBDGFAFACACBEDABEBFHFHFHAHAHFEDCDCFCAAHBHADAFB,False +86,14.0,13.0,10.0,16.0,18.0,7.0,14.0,15.0,GGGGHADGCGCEEEDEDBAAGBCDAEABAGAFFFDBEFEAHAHBDBDBDBGHAACDHHGHGHDHEFBCDCHCHDEEBEBDADABEFECCGHGHFHDGEEEADBEEHC,False +87,9.0,13.0,17.0,12.0,12.0,23.0,13.0,12.0,EHCHBDDCECFCFCFABABGBFDFDCDHBGDHDGBGCGCGCFCDHEHEFCHGEAFBFBFDFHCEBAFEDEDFFGHCFGBGFGCDCEBGFHFAFBEEEBGFFCFAACAHAHF,False +88,6.0,3.0,0.0,1.0,3.0,3.0,5.0,4.0,GBGAGBHAGAGFEBEFEHHAHAFAD,True +89,11.0,11.0,12.0,15.0,16.0,12.0,7.0,10.0,BHBHDDADCGCAEHHDCEAFAFBFCDEDECBGFCECHAHGCAEDDBDEAFAFHFDCHEBEGEGADBDBHEHDFGFGFDECECECAAEBEBDBFF,False +90,18.0,21.0,18.0,8.0,15.0,18.0,18.0,10.0,BCBDGCBCHGHAAFAFEFAFDFHGGGCCECEHBHFCADAFAFEGBAAAGAFBEBEBEGCBHBFADAECDGHGBGECCBCBABHFFDCEFEHGBGBGBEFGABCBFBDBEEAHACGCGEGFCFCFDA,False +91,21.0,22.0,23.0,29.0,25.0,21.0,20.0,16.0,EDECECBBDBGGGDHDFCFDFAFGBACHDHDADFDHBEAACACACEDECEDGDGEGEGEDEAFCFEGGBEBGFGEDECGFAFAFGHEDFHFCFBFBDEDFDGBHEADHDCCFBABABACGEHAHFHCEGEGHBHDACADFCCHBHDCDCFBHAGDBABEBFBGCDBEBCDDADAEEC,False +92,22.0,26.0,23.0,24.0,20.0,30.0,22.0,18.0,ADAFEGHDHFFFFDFECADDDFHBHDCBFAHCHCACHEGFBFBCDHEFEGABAFAEBGBFFFBFCFGBHBEBAACAHAEDEDEGCDCDCDCGHACFCFHFHGCFCEHEHCGCDCEFGDGBGBGEGBABGBGCCABBBDBAFGDABFBFEFEDADBFEFDBHGHDFEFECBAGGCGADDDGBHAEA,False +93,2.0,2.0,1.0,3.0,0.0,2.0,1.0,2.0,DBDCDGFFAHAHB,True +94,18.0,8.0,12.0,13.0,10.0,9.0,12.0,11.0,HHFAEHCHCHCDDAFACACACGGFEFGCHDEEGCGCGFDDADGDFDEBHCDABGBABDGAGEEBAFABGBDAHAFAFADADEHHCHCBGEAEA,False +95,4.0,5.0,6.0,3.0,5.0,4.0,4.0,3.0,AHBFEADADAGFHFGGCBCBCBCFCEHEBDCEEG,False +96,6.0,10.0,15.0,4.0,14.0,9.0,14.0,11.0,ECECEGHGHEHGDACGHHHFGFGCCCGFEEHEAAACCHCFCFEGEDHFHFDFGEABBBBEBHGCGBEBGCACBEBEGCCDBFG,False +97,3.0,4.0,3.0,4.0,3.0,2.0,2.0,6.0,BGHFHDHDCDBDECAHAHAEGBFBHCE,False +98,14.0,9.0,9.0,12.0,16.0,15.0,11.0,5.0,BGGACFEGEGEAFGFGFGFAADADACBCFDADGEBHBFDFGBBDCGAFAEEFECHCDCBFEAEAEADADCEBDDHDBGEFCHEHEFEAEFF,False +99,24.0,22.0,16.0,19.0,18.0,22.0,22.0,17.0,BABDFDEDEDEHAACABAEAFFGBHFGAHDBCAGADEDCHBBGEGAGAGAGAGFGABEDEDEFCBABDBECECEAGFGEGBGACBFEHEHAHAFBFBCHEFGDADAEEBCBHHHFHFBAGGGFFFFGHDCCHAHBCBCHFGDBCCAFBDGGFDHDFDFDC,False +100,10.0,7.0,6.0,7.0,6.0,11.0,8.0,15.0,GGHGHGFEFDCHAHFHEHEBACCBCHFHFBCBEBFFEFHAHGHDAGADAEGBGHHBAAADCFHFDADFDH,False +101,21.0,23.0,9.0,23.0,25.0,21.0,22.0,21.0,EEEEEACAHEHDDADHFBFBAHGHGBGDGFECGBBBBFBFEFHFGFGFAEHDHAHAHBHGHFBBHGGGGGEHDDDDHEAFBHHDEFEHEDDGBCDCHBGDDFFCAHADEDEGEGEAABBEBDFGEBABCDFEACFDADAGAGEGBAFABHBDGDCEEEAFAFBFC,False +102,1.0,8.0,5.0,3.0,5.0,5.0,6.0,8.0,HCGCHDEBGFEFECBBBFBFGHGHGDGBAHCFCHHHEDEBB,False +103,29.0,22.0,27.0,17.0,23.0,16.0,31.0,26.0,GGHCFGEBEDGCCDEBFFFEFHGCDCBCBCECFCHCHCHGHCEGAGCECABHEEEBEBEGAGBBBABABFBHBHDHGGDADCCFAFEDECEABGBFAFHDAGHGHADEFGBDCHHDEDCHGABABFGDEAAAEBGAAEGGGGFGHAHDBDCCHGHBDGEGHGEAEACCHCACAHGHGHAHDCACAFAGAFA,False +104,7.0,6.0,18.0,7.0,11.0,12.0,24.0,18.0,GDGEHCGGGEFECEBECGCGHGCFHFHFHCDFDFGACHHHGBGHACDCGAGADBCAHECACGHGHBBCFGHEDEFEHGHBHGGCGCGCHCEGGDGEAFFHFCF,True +105,16.0,23.0,21.0,18.0,22.0,17.0,10.0,18.0,ACEGEHEHAFACDCDCHFBFBGBHDFFFCAGHBBBHBHFABABABAHEGCAEEEFGBGBADGEBCDEHEBCFCHBHEFEBDDDDDDDGFEDEFEHAHBCACACBDBDHDCBCEDEHEGCCFEEEDHHAABCFCHAECBCBFFCFG,False +106,9.0,10.0,12.0,6.0,8.0,7.0,13.0,7.0,FABABHCEGEGBGBGCCCHCAAABGEGDGFGFAFCBCGCEHDCCAGHDHCAEHFBFAGBGBGHFDCDBEEDE,False +107,17.0,15.0,17.0,17.0,16.0,26.0,15.0,17.0,EFBHGEAFDGCGFGFGDEEAEGBDEFBGGFAHHCAFAFHBHBDGDGEGEGDFFFDFHHHAHBCDADBCBFGFCBCBGBFEHADAHCECFCECHBFFFFCDEDEDCDEFEFCHHHCACAEBCGAAAAHADAFHFBDBCFDF,False +108,20.0,24.0,27.0,23.0,19.0,28.0,19.0,18.0,AFAEGFGFGAHFCFEHEGDBBBEBEBEBCDDDHDFGFDCDCECFAFAHAGBBBEBFDEBCBAHGFGAGABDBEAGFCCCBEBHCDBDFDFBBHCHGGCDCDFHEHECGCFFFADAHHHDCDAEEBFGAEHCDDGACACACFCBEFFHAGCCCCEFEFCABDBFFFGHCHDHDFDGBGA,False +109,9.0,16.0,17.0,17.0,16.0,16.0,12.0,24.0,EGDDDAHBEAEABDCEBFFHFHFHCDGHAHCCFDFDFDFBBEBFBFEHGHGDCFCGHGHGCBCEDHBCDHFHFBFGDGACCCGAEBHBABCHHEHBDDEHEDEDEGEAHDHCECFCFCBHAHEGBHH,False +110,5.0,7.0,7.0,3.0,11.0,14.0,10.0,14.0,AHEHDHGFEFGCHFGFBBCAEFEFEFECEHFHBHAHFCBGFABHBEDEGCGFDFACGCGBFEFGHHHHEHG,True +111,20.0,16.0,22.0,22.0,11.0,17.0,13.0,10.0,ACAFFCDCDCACBFAFGDAACDCDEDEFFCBHDGDCDGDEABFEAADDCAHHDHEGACEFBCBCACACABBHDHDHEHCAAFAFCDDEDFDFBFCFBFDEDFFGGAGCCBEBCBHBAGGGGGEGACBHBDB,False +112,26.0,22.0,28.0,29.0,20.0,26.0,21.0,19.0,GCDCBAEHEHGGFABGFFFFBDBDBHCHCHAAADGFCBCDCFFFDCHCECEDEAFBFEFEGGCDCDAEAECFCEEACCBABGFDABADAFHBHFEFEAHAEADFCFHHBHAHAGGDHCCCDHBCADABHBDCGHGAGAGDDDFCAGBCBDBCFCFEHEDEBGGFGFDBCGAGDCDEDGDBDBEFEHAFADD,False +113,4.0,0.0,3.0,3.0,1.0,0.0,3.0,3.0,HAHADDGDHAGAECCCG,True +114,15.0,25.0,14.0,19.0,17.0,16.0,17.0,18.0,GDGCHHEBEBHBEFAFEFBFHFBGHEFEFEBAAAGFGDDFDFDFDBDBDBABABDHCBGDHCEBBGBCBEBAGHCHBEBGHEHEHEACACACACBBGGFGHCHDGBCDGEFDFDBEHECDGBCEHAHDHACFGADFDBAGD,False +115,4.0,7.0,3.0,5.0,3.0,0.0,6.0,6.0,HGHBHBDBABACEGDGEAHBHADGEGCHCBDGDB,True +116,18.0,19.0,11.0,27.0,26.0,22.0,18.0,28.0,FDFEHEBGBGBCFDFDFBEGFABHCHEEFAFAFAFBDHEHEABBDCHCDDGEHEADAFAFBHHCHBFBEDHGHGBFDFGECHHABDEGECEDADEHEDCAHAGEBABCDCDAHEDEDEDFFFFFBFHGAFEGEGDHDHGHGHGEDHDGEGDAHABBHHDHBCDADHEGE,False +117,9.0,10.0,11.0,5.0,12.0,11.0,5.0,12.0,HFBFCFBAAEABGHCHAFABBBBCCCHCECECHCGEHEHEHFHAHCEDDFDCEEBFFFFGEBEAFAHDGBGDEHA,False +118,1.0,8.0,6.0,3.0,6.0,11.0,9.0,8.0,BEBFGFGFBFBGBCDFEHBHAGEFHGDEFBFHHCGCDBGFGFGHCHFHCECE,True +119,16.0,21.0,23.0,14.0,8.0,20.0,24.0,21.0,EEGFBBADAFCBHFACCCFCFEFDGAFHFDABHBCGHHHBHGHCHEGCAABBGDHBHBGFGCGCGCGHFEFCFGABAGGCGAGACFCBCBHBFCFADHDHGHGFDEBEGCGCDBHBEAACHDDFDCDCFBFBGGGGCBHDHDHFABA,False +120,23.0,16.0,16.0,25.0,12.0,20.0,24.0,21.0,DFHFBBDGFFEDCHEEGGGEEADAGAGDBDAABFDFCGDGAABABABABACAGGHDHFACECBDDFDHGHGHBCBCAGFGBGCFFFDFDCGHGDEEHBCDCBHBCFGFDFDHAGCHHHHHGAFADDHEHEAGAGAGHCBAEAEDCDADCFGFDHDHF,False +121,19.0,17.0,15.0,20.0,28.0,24.0,23.0,17.0,DCDFFGAAFFFBGAGDGCACHEHDADADFEHEGGFFEFAABBHGGGFHEHACACBEEEHBAGAGFDFEBEGEBECECDCHBHGDGBEFEAEAEAECCGCEHBHCFFGBDBDCDAEEEAEFFFBHAHGEDEBGFGFGHGBGBDFDCDHEHDDDEBAFDFEGCFH,False +122,24.0,21.0,31.0,19.0,20.0,33.0,21.0,17.0,CBDGEGCBFGFHFHFEFBDAECCCBCBGHDCCCAFADHDHDEDACBDBGAHABFDGEGCHEECECDAFBGBGBFFFFHEAECHFHFHGEEBCFCFDGEGFFFFGCDCGBGBGFFBFBFAAAAAFGBAFABECAGEGBGFHFCADDCECHFAFADAHFHEDEHCFBACAEAEFDCCCCCBCHDADCG,False +123,23.0,22.0,33.0,26.0,18.0,14.0,26.0,19.0,DGDGCACABHFCADADGHGEEHGACAHAGACEDEDEDGDFCHDECFCBCGHGECHCHBEEDEDEDEDCBGBGBABCBCBHAGDGECAGDCCCFCDCFHFDABECGBGFHBBFBEBEBACEDBHHCCGCDAGGGFCCCGDDFCBCBGBGHGHGCBADHFFAHDGAAAAABAFDHDHCFCEAD,False +124,14.0,14.0,13.0,14.0,9.0,17.0,19.0,18.0,DCBFBFAFAHBHGFBABECACGGBGCGCFAFHHDGDGEBDADFFHHHHDAABHFFEGAGFDBGHGAGBGHFHFGCHCDGEGEFCGDGDCDCDCECBFAFCFHAHEBEGHBEBHHADAD,False +125,22.0,17.0,18.0,14.0,19.0,23.0,19.0,20.0,AFFEGCACEHAHBHFHECADBDEDHDHDACHCBCBHFDDAGHGHCECEAEAHBHGGCEAFAFBDGFFFFBAGAFAFHHCGDFFAEBBABADADBCGHHHGACACFCFDFBCGHGEGEGBGBCBEEAFHEBBGGECEFECEHGGEAFDFDFAF,False +126,2.0,2.0,5.0,1.0,2.0,0.0,0.0,0.0,CBABCCCECEAD,True +127,9.0,13.0,13.0,20.0,8.0,15.0,15.0,18.0,GGEFDFEHDHDHBAGABBBFFHFCFHGHGHGHGDADHDEDFCEDAGAGCBDFDHDHCBCDFDBHFHGHFBCGDDDDDABGHDHCHAAECFBDBEBCBCEGECCFFHCGAGF,False +128,26.0,16.0,20.0,13.0,15.0,14.0,8.0,14.0,AFAFGCBFDCCGCBCACACAFACECBAFAFDBBABABHECBGAHADEDCBADABABAHEHCHCHGECDHDHBHBAEDEAEAHBGFAHBBCACACAFEDCAHHEADGEGECEFFFCGHDFDEAEFFD,False +129,3.0,2.0,3.0,1.0,2.0,1.0,0.0,1.0,AHABFBEAECCDC,True +130,3.0,10.0,5.0,11.0,10.0,4.0,3.0,9.0,DBGBHBAEDEBCCEBAAFHHDHDCBEDHBHBHBDECECEDDDFDGDFBEGEHEHF,True +131,18.0,19.0,23.0,22.0,20.0,20.0,15.0,23.0,FGBCAABCBCDCDCBBAAADCEGHAFDFEBHBHAHGDAEAEAHGECHCDDFDBEBHHHDBCFCABFHHHABFHHEGEHBAFAFCDCHGEGEFBFEFEDEHCHCHDHDGFAFEBEBGBGFCDCAEDEGFFFHFBEAGACFDDDDHDCCCCDCDGEGBGCEH,False +132,27.0,13.0,16.0,13.0,20.0,12.0,27.0,15.0,HAACDHGHEBFFCDAGADAEABAGHFHDHCCAEHFHBGBECGGGGAGABACDEDCACACFGFGFHBBEBHGGGDABGGGEDECEAEAEAFCEGBBBAGAEAEABHEAEGGGCEHFHDGAGEDEDFDHDEAAGAHAFFGCCCCG,False +133,5.0,7.0,9.0,1.0,6.0,7.0,8.0,7.0,BGCFEBHHHHACABFBFHFCFGGGCCECGCGCHAEBBHFGCGDAEAEBEF,False +134,14.0,15.0,11.0,16.0,21.0,17.0,16.0,20.0,HBHDHFHDDEFEGEFEBGDFDFBBHBAGEGCFHBHDADHHFAFAHECEFADECEDDDBDBDACBEAFHFHGEGCGDECECBAGACHBHGHFHFHGEGFFHEHCHCEGEGEAEGDGEABDBABFFGECABA,False +135,8.0,3.0,1.0,2.0,4.0,6.0,9.0,3.0,GFGEGHGFEFGCGDBAHAFDEAEGBGBAAAFAGAHF,True +136,14.0,29.0,20.0,23.0,25.0,22.0,18.0,18.0,DGDCEBGFHDBFBECHFEFBDEDCACGCGHEFEFEFAFGGGDCFGFHFHAHADEBBCBCEEEFEBABCBEBACACBHHCFCEAEAGBGDCDBDEDGBACECBHEHBDGDFDGCGAFEFDBHBEBEAHGFCFBFBHEDFDGDBBBBACDBDHGBEAEGFCHBHEHDHDFD,False +137,3.0,5.0,1.0,6.0,8.0,6.0,3.0,5.0,FDFDBBBEDEHEHEFEACFFGDHDFGBHAEAEBEGDH,True +138,17.0,19.0,28.0,23.0,19.0,29.0,14.0,27.0,EEHFCDHDHBAADFECECFFFCDGBAHAHFHBCDDFDGDADBCAAHABAEGFHFHDHDEGCGHGHCFDFEFGBHAHBCBABEEECDCDEHFHFBABHCCCACHEACHDGDFHFHBHFGDGDGDFBCDCGABFFDFECHCFFFHFCDGEFCACHCHCHEGACFCFBFEEECEBBBBD,False +139,18.0,10.0,15.0,7.0,19.0,9.0,15.0,15.0,BCDGAGEBBAAFCBEFDFHCAAHABFEADAHGCCCACEDEDEDEDEHCBCFEHCHEACACHGGGGBGEGFGFEHECGFEAHGHEHEHEHACAFBGGABABHGHEAEAC,False +140,12.0,11.0,10.0,15.0,15.0,9.0,10.0,21.0,GGDEDEDHDABGBDCAFADADEEFHFEEBBAHECFCAHGHGHEBBCBABAFHHHHAFADHECEGGBGECECHBHECFCDDDEEHHHHHDHDHDHFACGDABFG,False +141,6.0,7.0,16.0,10.0,19.0,4.0,7.0,3.0,GAGEECEDBGBGFCFCHCFBDBDECEAEDBDCHBEEFAHAEAEGCBCEADDDDEGCCEEEECCCECDCGCEE,True +142,17.0,14.0,17.0,18.0,21.0,18.0,15.0,9.0,BADAGADHDGDGFHFAFDFGEEDDDADCCCGGECCCGEHAHAHEEEEAECFCDHDFABABFBGBCACEFFDADAEEHBHFDFCBEBGHGCFCDAGFDBEFFGFGEGCBAEDEBCBAACDCBEBEFEFEG,False +143,1.0,3.0,4.0,4.0,2.0,3.0,3.0,3.0,DHDCCGCGAGHBBFEFCFDHDEB,False +144,3.0,1.0,7.0,1.0,1.0,3.0,7.0,2.0,CDCFHGGFBCCCCGAGAGAEHFGCG,True +145,3.0,5.0,7.0,4.0,3.0,11.0,6.0,3.0,DHGEGBGBGCCFDFAFHCBEBEBDFCFCFGFCCAHFFFDGAF,True +146,4.0,13.0,6.0,8.0,6.0,15.0,9.0,3.0,FABGBGFGFDBBBCGEEEEBFGCBFBDBCFDFGFGFAFECCDDADAFBDGHGBFBFHFEFHCBD,True +147,16.0,16.0,22.0,23.0,21.0,20.0,35.0,29.0,FBFEECGAGFGFGHDHDFAGEGEHFHFHFEGHGCEEAHDGDEHEGEFHFCFHGHBECDBDBHHGGGGGGCBHAHACAHAGEBDCEAGGHGHGEGEBDAHHHCHADGCFBFHGBGCHDFDFDGHCBCHHAGBEBDACHCFFGGGDADEEAGCEDEDCCCGDFDBDGFBFBGBDEACACDCDCH,False +148,16.0,20.0,20.0,23.0,21.0,16.0,31.0,18.0,EBEHGGGHCACFDDDDDAFCHEGCACFCFDFAGADEGGGAGEECEGEGEGAFFDCBHBHDHEGCDCGBGBGCCCCCBDGEBCGFHCHGHAHBBCEGEGEBFBGAHABDBDAGAGFGBEEEFEDGDAFCHBABGBADADEGFFDHDCFGGDHBFBDEDEDGHHHBH,False +149,3.0,7.0,4.0,6.0,10.0,7.0,3.0,5.0,EBEHEBEDCFCBBADCHFHFGBGBDEEEECHBDADADEFFFGFHE,False +150,6.0,2.0,7.0,6.0,2.0,3.0,8.0,0.0,DDDCGCADFDFGGGACACAGBECGGDGABACFCE,True +151,5.0,2.0,2.0,0.0,5.0,4.0,2.0,3.0,GAGAFBFEFECEFHABAEHEACH,True +152,14.0,12.0,9.0,7.0,12.0,11.0,10.0,17.0,FDHDFEHDHCFCBCDGHGCFFFBFHACCHBGAGAHEHEBEAADAHBGBFBFBABABAHAHEEAFHEHBHEHABGGECDCECEAGDHAHEFGG,False +153,19.0,24.0,27.0,19.0,23.0,23.0,26.0,24.0,CDCGGGFAAGACHFHDHDHBBCCHCGFAHABGBEDHBGBGBABADECFFFFAGGCHDDGDGCGHGHGDCFHDHAFEFEFEHDCCGGBGEGAAFCEEDFDFGBEAFHFCGEBCBHBFBDCDGBCBEHADABCHCHEHEHBHDGFGAGEGBBEBHDEEHAHAEAECCFFFCCCECECEFBFBDECBA,False +154,13.0,10.0,11.0,9.0,11.0,8.0,12.0,4.0,GEAEAFAGADADAEFCGCGCGCAFBFBEECEGADADACBGBCHHBFEECACBEHEFBFBDADEDBCGGGBDFHCAGGD,False +155,23.0,15.0,20.0,21.0,22.0,13.0,16.0,23.0,FEBEBEBFDHDHCCDDBCBEGFDFGBHCHFDAEBCBFHAHGHDADCBGDHDHDFCAHHHDBCEHDFDAAECDCDCBCAFEEEEEAEAGACHCEGEAEGGGGAEABAFAFHHGEAAACHFHAHFGEAEDEDEDADHDBCGAGACBCHHBGGCHC,False +156,1.0,2.0,8.0,2.0,1.0,1.0,0.0,3.0,CCCCCHCHBACDCBHEDF,True +157,11.0,6.0,5.0,14.0,10.0,10.0,2.0,6.0,EFAHAHFBFGGABADFCBEDEDADAHAFAHBFEDEDCDEDEDEDFFCBEDFDFBACDDAEHCHA,True +158,15.0,22.0,16.0,16.0,9.0,21.0,17.0,9.0,CFCFCAEBDGDHBBFBHCAAGFFFAGGGGFGHCHDBDBECECECFHBBCBAFHFDFBCACHCAAAEFDBDBCFGAADADAGGBBBGCGBGCFBEEGHGFGFDFDFABABDFHFDBDCEFEBGDDB,False +159,3.0,6.0,10.0,6.0,2.0,3.0,4.0,5.0,GGGFDFDBCBHBHBCCHCBCEHHFCACDCBEDDDACGCA,True +160,7.0,12.0,7.0,6.0,6.0,8.0,8.0,5.0,AEFEFEBCBADCEFHHCHGBBECAABFBFBDBGBHECGDADADGBGAHFFCFCGDGBGB,False +161,25.0,18.0,13.0,27.0,15.0,21.0,17.0,28.0,HFHGDDBDFDGHGADHGFBHGCFDAECCHHEFEFEDDBEBAHAHFHFBFHAHDFDFAEDFBBCEHADGFGAHDGDGDGDFCBCEAEBCBHDHDHAHAEADHHFHFHEGBHEDABABACDCAEFDDGFGAGABAHDHDGDGDBHBFAABAGAECECHCACBFAFH,False +162,18.0,23.0,16.0,12.0,17.0,23.0,24.0,31.0,AEABABCBCHCHCFFFBHHEGBABDDDDDHHFHEECFCFCBEDDBHBHBCGHDFAFHCHFGCHHHHHHHCFGFGEHDBAAEGGHEBBHGDAHFHBHBECGFAFBGCAHEHGBBFBDCHHGEAEHGFFFADGEGBGBGCGFFCHGEGEGAGAFABABAEAEGFGF,False +163,24.0,23.0,17.0,16.0,25.0,31.0,34.0,30.0,FHFHFEFGFBAEHHHDHDHFGGDGDGFGDHACAFGDGDECECHCGAHAHBBBBBFFFCGBGEFFHFEAECGGBBAGABABAFHFHECGDECFCHDBACDEHBFBHBFEFDDGCHBHGHGHBEAGFGCEHFBAHACEHEACFCFEAEGEGAGACFEAEBGGFDBDBGEGECEAHHHAGBGHAFDFAFDFGBGHGFGAGHEE,False +164,16.0,17.0,19.0,27.0,19.0,29.0,35.0,19.0,GDGBCCGCAFBFGFDHGHBFAFGFGDDECECDGDCDFHFGFCFHFEABACFHFBFHEEECEDFDEDGGGDGCCBBDBFBABFBGDEDEGBHBDDDGGGGCFHFGFGFHFEABBDCDCHCGGGDGFGEDADHDECEAGAFAHEHADAFFGGGCABEGHCAEFGFGAGDDHDHBCEHGAEHFH,False +165,10.0,7.0,7.0,12.0,6.0,6.0,5.0,8.0,DGFFDCDCDAEGDBDCEBGACECHCECDBABDEAHDHGAAHHHFHFBFBGBHDADADAFAE,False +166,17.0,18.0,17.0,16.0,20.0,19.0,17.0,15.0,CACAHAFBDAAADADHBGFAFDGDGDGHHFHFGFGFHHCAAEBFBFCFAHEBABEEGEGEGEBAHGDCDGEBCHEGDGCFCEEFECBCFHBHBHBADDFBFBGDCBCFFEGCAEGEFBACDCECECFDDADEEEGHBHB,False +167,15.0,4.0,11.0,15.0,21.0,12.0,17.0,17.0,HHAHDEDGHFHEHCHGFGFCECEGEACFGDGDCDCHADCEHEGGAEEBEBFHHHCHCHCFDAHAGDGFGDDHEEGCAEDEABAEGEGHGDDFAAEFGAGAEAFAFDFEEBED,False +168,8.0,4.0,9.0,2.0,9.0,7.0,3.0,7.0,ECECBCHFHCGFGFEEEHEHECAAHAFFBAEAFHBGAEAHDBDACCCFC,True +169,16.0,14.0,9.0,11.0,11.0,11.0,12.0,11.0,DFDFDGAGAGAGFGHHACBHBHGFFDFGBCEAHBDAEADACCECAAEABBHEAEAEDEDCABABCBGGGGFFACHHBDBFFDFEEGBCDHEHBHB,False +170,4.0,2.0,1.0,1.0,6.0,4.0,5.0,2.0,GGDBEEEEBEAGFFCFGFHAHAEAG,True +171,28.0,14.0,20.0,10.0,8.0,25.0,20.0,36.0,HCHCDCGCDAGAGHGBABAFAFCFAFDFGFGEGHFEFHBHGFGCHEHABFGFHHHCFDACHEFBHHHCHAHGBAADCHBHBFAAAHHHFEGCGDAHAGFBFAADAEACFFGAEAGABFCHCBFDEAGAHBHBAAHHHFHFHCCACGHGHDHDHCHCFCBGF,True +172,3.0,11.0,4.0,4.0,5.0,7.0,5.0,5.0,BBBEBHHCCFEFGFGHGBBBGBDFAFACEHFGFHDBDBABCDEE,False +173,8.0,13.0,6.0,15.0,4.0,10.0,15.0,7.0,ACDCGBGFFFGEGBGFHBHDADHDFGBGBGHCDAGGGCHDHGADDDDDDEBBHBFBFGFAEADGCCBDBDGAAEFBFB,True +174,10.0,11.0,8.0,10.0,13.0,7.0,14.0,11.0,GCGCGCGFGEBCAAEEHEAEHDHDGAADADADFBEDECHCGGGHGEEHBHAHABFBEBHFADGDHEECHBBFBGEGBGDCFBFD,False +175,23.0,12.0,12.0,24.0,26.0,34.0,26.0,24.0,CDBFHAHBGAAFEGHAFGCAFGFGBGBEBEAFGDGDFDADCFGEGBFCHABFCGADHFFEFHFEFEFEDHFGCGEGEAABEGAGHGEAFAFAFCFAEDEDEDHDHDHFFFGFHACEFHHHDHDAGFDFGEGBGDHDBABAFEEEHEBGFGEEAEAHHFDDDGHGHDFCFCACHDDEDEFHC,False +176,18.0,8.0,20.0,16.0,15.0,17.0,11.0,11.0,FCFBECGAFAFABAEEEEDCDAECEDGAAADFHBDBECEHEABABCDCHBGEHAHAGAECHHHADCCCCFCDCDAGCFFEEAFAFGDDFHFHFHDBGGDGDADFGCECFCGCDCFF,False +177,13.0,12.0,13.0,12.0,6.0,11.0,5.0,9.0,DABFHGHCBDBDCFFGABAFEBACAHECGDFFHFHFDFEFCHCBCBAECGCGCHEAEADDDBDADAHHBACABACDCDBFB,False +178,7.0,14.0,10.0,12.0,19.0,22.0,10.0,9.0,FDECFBFDFDFHFGCEDEDEFHGBACCEGGAEBEGABFDFDFCHGHFFEDBFBFBFEGEHADAEFEFEFEABCFHDHDAECFCGBFBGBFBEECECDBEBHGH,False +179,2.0,2.0,2.0,1.0,5.0,4.0,1.0,6.0,HGFEHEHEFEDAFHFEABBCHCH,True +180,2.0,5.0,1.0,3.0,3.0,4.0,0.0,0.0,FAADBBBBEBEFEFDDCF,True +181,6.0,7.0,5.0,2.0,1.0,4.0,3.0,6.0,BHBDBAAGAHCHFHACAHEHBBBFCFCACGGDBF,True +182,2.0,3.0,10.0,6.0,8.0,6.0,4.0,4.0,BCBCECEAEDEDHCCCCHEHEGDGCFFFAHGBFFFECDDECGD,True +183,27.0,20.0,35.0,20.0,19.0,18.0,17.0,19.0,CHCHCFCBDEHBHEHCCCCBDBAADFFECCGCAEAFAHCFGDGAGACABFEAHCBDBDBDACGDEDEDEHEBGDGDCAGABEBEAECEGAGFGCABFGFCEAEAGACFCDCFFGFEHBDBDECACAFHBHCHBHBFAHDBCADHEHACAGDDDGCEBFBFCCCCGAHCFCACAHH,False +184,21.0,29.0,29.0,14.0,13.0,23.0,22.0,20.0,HBBEFAHAHDHCHCGCBCAFABDDHDFAAADBDBEBCBCBEACGCGFFBFAFHGHFCFEHCHDADFCFCEDBGBCCFCFGFHCHCACBEAFBECFCDAGGCGFGHGFGEGACCDCBHBACGFGFHFBFGEGBCHCBCDEBBCHGGBGBDDFAAAEBEBABHBABHGEGBHA,False +185,16.0,21.0,7.0,5.0,16.0,12.0,3.0,15.0,BBBHGHBACDBEAAAFDHEHAGAGAEEEHHCAEAFBBABFBCECAFAFBFHFEDABBBFBEBEBEBACHFHFHDHBFEAEBHAFCHEDECEHBHB,True +186,26.0,34.0,20.0,22.0,24.0,21.0,26.0,17.0,HFACACHCBBBBHBGBEHFHFEAHAEAEFDBHECAHAHDDBGEDCBEGGFGECAAADBEBGCGCFCFCFBFBFBAGCBBABEHGCGCGFGBBCHCEDAHBCEAEHDBAHGGDDDDHEADDDDDFFGBGAGBGBEBABDBDGDGBFBDBDBDHEFEFCFEAAFGEBCGEGBFFGCGAABAGCHEEEAFAEA,False +187,3.0,5.0,0.0,1.0,1.0,2.0,2.0,4.0,DEBGHGAFBFHHBHBABA,True +188,8.0,11.0,10.0,11.0,8.0,19.0,14.0,12.0,HGFBFHFBFGGAHDDEBAHFHFHFCEGFGFGFGBGEGBCEEAFDBBBHFHDBDBGACHCHFGCGFGCGFBCDCDFFAEAHAEFDFDHAECDCD,False +189,24.0,32.0,23.0,32.0,21.0,21.0,20.0,22.0,BBBABAEECDDDEDEHEBECEDEDHHHFHFDFHCDAHAHDBGBGEGFGFGFGFBAGCGDFBFHDHBBCHGHGFAEBEDCAAGFDDADADBDCFGHBABDHECBDBAAHADAGCDCBABABGBHDCGCBCGFEBDCHAHCCCFCFEBABHDDBGBHHCCCGBABDBCEEGHAFEFEDDBAFFFDFDCEAEAEGDBD,False +190,13.0,10.0,11.0,9.0,7.0,16.0,9.0,11.0,AGCHAGCBAHCBGBEBEACADADHDBFBDDAGEFCFCBHDEFEFHFHGHDFGFACAEFHAEAGGBGFCFCFHFDFCFCBBFDAHAH,False +191,14.0,3.0,6.0,9.0,14.0,7.0,4.0,6.0,EAEFDGEEFCCCFCFEAAAEADCDAEAEGGAFHHHHEAAADADEFEBDBAEGECEADFDHDHB,True +192,6.0,4.0,7.0,3.0,3.0,3.0,1.0,4.0,CFGEHCCFCBCEAEHCHDADADABBBACAFH,True +193,29.0,36.0,21.0,12.0,18.0,14.0,23.0,24.0,BBHFFFCEHEGEHDHBGBHBHDEBHBHBEAEBDBFHFHEHABADACGGGADBBHHFBBBAAAAABECDCACHCAGACFCFAEAFAFAGGDAEBDBHBEBGACBHFAFGFGBBCAGGBGHDCBBDGEHEGEACACACEBEBCACAEGDGHCBDGHGHBBABCCHCHCHGBAEAGBFBG,False +194,6.0,3.0,5.0,1.0,2.0,4.0,8.0,5.0,HBHGGFCFCACAEABGEACDCHBGGHGAGAFHFG,True +195,3.0,6.0,4.0,7.0,9.0,15.0,5.0,10.0,HAHEHFGFHHGHGFFCFCEDEFEDBGBDEDACBDFHEBFHFHFEFDFCFDFABEBGHFE,True +196,2.0,2.0,8.0,2.0,3.0,5.0,4.0,4.0,CCECHCDCDCEBHCGEHBHGAAFFFFGFGC,True +197,0.0,3.0,4.0,2.0,1.0,2.0,3.0,2.0,DBHBDFCCCGCGBGEFH,True +198,9.0,8.0,9.0,4.0,11.0,7.0,12.0,11.0,AAAFADHGGGFGCBCBCHEGEFEHDCABDHGEGEGDACBFHFBEBGBECEHAHAHGBECFCGEGAHEHCHF,False +199,9.0,8.0,10.0,11.0,7.0,10.0,5.0,6.0,ACADDFDHDABGCDEBEHAFFBECECDBBABAFAFAEAFHDDDHCCDCGCGHGDGHFCBCBFFEFE,False +200,15.0,9.0,5.0,13.0,12.0,23.0,15.0,22.0,CHGFEHBDGDHEHAHDFDFAEBDAHEFEFEGGGGAAAGEDAHGHGHECEGFGFGAGBFEFAFBFBGBDFAFHDHBHFHFHGDEDHFFCFEDBDHFFFAAHBHAHFCFDHHCHAA,False +201,8.0,4.0,6.0,6.0,2.0,3.0,2.0,2.0,AGCFBBCBCDAHABACEHDADADCDADAEFGFC,True +202,15.0,30.0,30.0,30.0,15.0,29.0,25.0,23.0,DFBBDGHBCEDBFBHBHBCBHEGGGEBEBHHEHCFFHFGBHEGBDFDFGBGDFDFHCEFHCGCFDHDFDEHADADEBCFEFDFEFECDAAHFGDDDCACACACACDBABGGEDAABBBGCACABFBGDCDAGGGGDCDFFFGFCBBBDBDHECGHGDGCGCHCHFBFHHHDHCEBFDFDFCFCGCBCBCFCDABHCG,False +203,14.0,19.0,19.0,3.0,12.0,14.0,16.0,22.0,CHAEADAHBHBHBHBGGDBHFHEAAABCBGEFCCHFEBHCHABABFHCCCHBHAGAFCFBFAAAHCFCGEGEHEHEHFHBHEGFGHBEGGGCCFGFGCDAECGCBBGBFBCHCHCGBFE,False +204,9.0,15.0,19.0,11.0,9.0,19.0,20.0,15.0,FAAACCHEGCGDGBHDCCCEBAHDGDFDBDBHCFGFCFCBCBFGFGHGBFBHHHFHEGBGBCAEBCCCFCFCHGAEFEAGCDHGHGFGFGCGBGBGFDACEBFDFDEHEDGHABFHF,False +205,20.0,16.0,16.0,34.0,30.0,20.0,29.0,29.0,CDCFGDGDEFHGHEHEGGBGBGBHBGEFECDCEBGDAHGCBDDGDHDHEBEDDDDHAFAFDEGCHEGFHFADBEEGAGDGDHFHBDEAEAHAHDDDECGBADEHEFEFDACAGEGFGBDEDECHHHEAEFFBADDDDAEAHHDHDCCFCAAAHCFCFEGHHHHGBGBDCHCHDFDGGEGBFBGHFAFEGEGEAE,False +206,20.0,18.0,16.0,14.0,21.0,4.0,6.0,11.0,ABABAFADEDBAECHGDDAAHEBBDBACECGAAAACHEFEBCDHGBCECECEBEFEAECBCEHEDGAHACADAHACECGDDEEECEHHHFECBCBEBHBDBDBDBAGDBA,True +207,1.0,3.0,2.0,6.0,1.0,4.0,1.0,1.0,FCADBDBGBFEFDFHCDDD,True +208,5.0,3.0,5.0,6.0,4.0,0.0,1.0,2.0,DCCBCDCDCAAAAHDHBGAEEDBDEE,True +209,9.0,6.0,7.0,6.0,5.0,8.0,3.0,2.0,FCFEAEGDADABCBCFGAGCFAFABABCBDHCFDFEFEACBDHEAD,False +210,21.0,21.0,15.0,16.0,11.0,15.0,20.0,12.0,CACFFACCCEHFDBGBGBFHFAGDGDADACGGDGBAACABBECECEGEDHDHCABDFDFDAGHGHGBGBFBGEGBFDFAGAEHFDAHEGABABFGAGEBCCGCHBDEDGBCACFBFAFHDBEBHBABADAH,False +211,10.0,24.0,13.0,13.0,14.0,11.0,16.0,23.0,EDEABACHGHAEGGBBBBECECEBBBAHGHGHCBCECDCBFBHBHFHFHFBBDAGFEBHAHDHGCFAGABCDDBEBEDHGHBCCACFDDBAHHHGBGBGEGEGHGFEFHHHDDBBCDEFGFHDH,False +212,19.0,7.0,17.0,13.0,17.0,11.0,21.0,24.0,FGCAHAHFGEHAAAAAHGDGHGFEEGDHHAEAEDCDFGBGDHDGFECECGGEEHGHGHCFBBHBFEEHGHGHDHFHDHDAAAHDECAAACBCECACAHFDFCCCCCCGGGGGEEEDHBHEFCGDHAHAB,False +213,10.0,20.0,7.0,7.0,13.0,11.0,10.0,5.0,HACBEBEBAGEEHEDAFABBFEEEBGBGBGBAAEBBDDFDFDFHCHDDAFECHBBAFAGGGFAFCGBEBEBEGGBFFCBCBCB,False +214,6.0,9.0,11.0,6.0,13.0,4.0,11.0,19.0,ECECBCFDGEGBHEDDHGEBHHGCGCBHHHHHEHEGACABADHFFGCGBGHDDCEEEEBEFHAECBCHGHGHBHAHAHC,True +215,3.0,0.0,0.0,3.0,3.0,2.0,6.0,5.0,HDFDHEHGGGGHAHAEGEAFDG,True +216,1.0,8.0,11.0,12.0,14.0,8.0,9.0,12.0,GEBDBDCCADDBGFGFEEGEGCDCEFEGEBEDCCFBHCEDDGEHEHDDFCHHHBHBHBCDFDEGEGCHCHEHFHF,False +217,10.0,10.0,22.0,13.0,14.0,8.0,15.0,10.0,DCHGECECEAGHEFGACFBGBECGCAEBEHHAGEGFDFDFHEDDCDBFBABACDDHDBDGCCCGHGACFCFDGCGCBCBGAGACECACBCECGDHEHEHECD,False +218,7.0,10.0,14.0,5.0,9.0,7.0,7.0,16.0,CFCECECDHHHHHHHHBBBHEFCCEBDBABAGDFDHCHGACCHCHEFEGHGDACFBGBCEEEFGHGFCBCHAAAB,False +219,15.0,20.0,16.0,12.0,13.0,12.0,14.0,14.0,AGAEAEAHGHFBFEHBHFGGEEHCFCDADACBDBFBCBFGFBBBCCAEGDGFAACAHBCBCDAFHFHECAFFEGEBCBGGCDCDCDEBBDBDBHHHHHDGAGDCHCAGEGABBEBE,False +220,0.0,1.0,1.0,0.0,3.0,3.0,1.0,3.0,HEHEHFFFGCBE,True +221,4.0,7.0,18.0,11.0,9.0,20.0,14.0,16.0,GGGBFCCCFBFDGCFCFDFHFHCDCDHHHGHFDCAGHCBAEEFEFEFHAEFCHCGEFCCCHCHEHCDCDAGBGBGCDDFDFGFHEHDHFGEGFHFGFBB,True +222,19.0,32.0,14.0,24.0,24.0,23.0,30.0,29.0,EAEAGFDFDCBHFAFADGBHBDAGCDEABDFGEEFFFEEAECHDHBHDGAHHGBGBGBGHCDFDBDBDEDADHFFAFEFGBHBGDCHEDABGBEBCDCHCBFAFBGBAHFHFGEDFHHHBBBBDBDBDBGEGBHEACCHEGEGEDEHECGHGFBHGHCBGAGHGHGEGEGEHAHAHFCCEFHFAGBGBGDADFBB,False +223,6.0,4.0,7.0,6.0,14.0,14.0,8.0,15.0,CEEFAGEBDFAHHDHFAFAHBFFHFCFEHHHHFDEGEGEDEDGAGHDFGBGBEFGFHHCHCHEHECFCACEEFE,True +224,11.0,10.0,13.0,13.0,21.0,14.0,25.0,19.0,CGBAEGEGEHHCGGHGCCBCAEBEGHCHDFDFDFEGBDFDFEFAGDGAGEGCGBHEEGCGBEEGEADACECABEDCDFFFDCAGAGHFHAHGEGEGEGBGBGHHHHHHDABCEDHHFFDHEHEGFF,False +225,6.0,19.0,5.0,11.0,12.0,6.0,9.0,5.0,GBHBDBABHBCBDEDBGBGBEBEBCCFDHDFEBBDDEAEAEAECFGFGEGABCFGBBDHDEFBGBGEEABHDD,True +226,11.0,18.0,23.0,14.0,12.0,26.0,20.0,26.0,EFEFEFGDCDFBHBHADECHHEHEFGFGHCBGACBGACFDFGFCFGFCCCHHHBHFHFHDADFFEBGFFFFFDBCCFCFHFCDGEHDFDBDCAGGHHHHHHBACGCGAGBGHAAAFFCHGBGCADGBBBCGDHEBEBEBEBHCHDHCCCG,False +227,23.0,20.0,28.0,18.0,25.0,23.0,23.0,21.0,FCCBCEFEDAGGBEHCHCHAFCCADFFHFEFAHCHDGCCHAEDEDFDGAGAGAGEFEBEBHHEFEFHFCGDFBGBDHAHBGAHFFFBFCDDADCDEEAGABHBHGHCHCABADABCHCHCDFGHGHBAFFEGECBGADCECGCGCBFEFDFCGCGDEECAGAEAGAGBBBBBCEEAEDECE,False +228,5.0,3.0,9.0,5.0,8.0,2.0,3.0,5.0,DDDACEHGFBCEAECCCCCFCEHEHEHEBCDAEBDHAGAG,True +229,15.0,19.0,18.0,23.0,23.0,15.0,10.0,23.0,HHFHGHEBFHHBCBDEEHCBGBAHAEDEDCGCGEBBDDDDEDBDHDFDEDACCEEDFCEEECBCBCBCDAFEHCFAHBEDACAGHHHHHHHAHGFACACAFBEBEFFFFFDEBEAEGCBEEDADACBHGCGBGDHDHDFDHDEABF,False +230,15.0,10.0,14.0,14.0,7.0,9.0,3.0,6.0,EDADBFADCDCDEBFBFAFEFEDCBADFBFBAHACCBCGEHEHBCCAGDCFFBAAABAGACHCHDDCCCEDHDADADA,True +231,21.0,19.0,19.0,16.0,21.0,13.0,13.0,23.0,EHBFBHBCDAEACABABEHCAAAAAEBDHDCECACAHGFCFBFBDCCBDBDECHCGCAAHHDDCDCDEEHHHADAFBFGFGDGFGHGAGEEFEHBBDBGHAHGHEBCCACACGEDEAABDBCEDEFEHBHEEEHGHFHEHFFGHB,False +232,10.0,11.0,13.0,7.0,8.0,12.0,12.0,9.0,EFGGGHCHBAEHFDFEADAHBBFBCGFGBCBCBCFHFAFAGCGCEBEDCCCHCHDGGGCGCADFEBEBDAFAFAHEFGBHDA,False +233,16.0,18.0,26.0,21.0,12.0,11.0,22.0,9.0,GBGCHBGDHEHDGAFCFCGCBBDDDHHGCEDEDCDBGBEBCCCCDBGBCACBGGEHEDGGAGACFCFCHCGGDGABDCCCGDBDEDEBBCHCDCDBDAGECECAFEFBFEAGAFAGBGAGDDDACAFAFAFCHBA,False +234,8.0,5.0,2.0,10.0,3.0,5.0,9.0,5.0,GAGBBEDFDFDBDGDAEADHGAGHBDGDFDFCGAGACABAGHHHFED,True +235,28.0,16.0,21.0,19.0,24.0,21.0,12.0,20.0,EDHFBEAFADABHFHFCFHFACCBBBHAHDHBADGDBCBDFEFDHHADACBHBEAEDDDGAGACAEHECFCECHHHEABFCFEEHGAFFFADADCDGEEEGEBECEBBCACAHAHADADFFAFAFHGDEEFEBCGCGCGCDCAHBGEEFGADECECAFAHA,False +236,13.0,6.0,14.0,8.0,9.0,13.0,7.0,14.0,FCFAFAFAHAHCDCDGFFEFECEDBCECDCFHEEFAFACHCHCEBGDHEHFHAHBHDHFCGGAGDHHACCBHDCGFGBAAEABA,False +237,4.0,7.0,4.0,12.0,6.0,4.0,7.0,10.0,DGGHBHDDDGDGCGCGADBHEDEDAGFCFEBDHDEBAHAFEHEHCHDBDBHFHB,False +238,25.0,27.0,17.0,20.0,11.0,20.0,27.0,24.0,BGGGHACECEFEAEDBDBHCGDGDHDHBHBHAHAHFBFGCGCAHFHABABEFFDDAAFHFHDAGADFDGBACCCHGHDAACHCHGBEBCCCBDAFAEGHAHGHGEDBDBCBHBGFEAGAGBGBABDHDGAGADFBFGFGCAEBGFFEHBBGDGBBBFFHFBFCDAGCGHDA,False +239,27.0,19.0,14.0,12.0,26.0,20.0,17.0,18.0,CACHFHBABHBABAHEGBDDEBFAFAEACABAFAHAHGHDFEGEFEBEBEAFCDCHABAGEGEDFBGBACAFDCDCAEHEHFHFEEEFABABCGEEEGHDHAHBHDFGEGBAAAFDHECEAGCGEBEDCDHFAFAGAGBGFFCGCEHGFEBEF,False +240,13.0,5.0,13.0,8.0,10.0,9.0,13.0,11.0,HCHAGAEFGBGAGFGCDCAGAECGCGEFEDHGFADADACHDFDGBCBCFEDEFEFBAHHHHHHAAFGCECACBCGEHEADCG,False +241,15.0,13.0,22.0,21.0,14.0,24.0,13.0,15.0,CECEBACABEFHFGBEFDCDBABGDAEADCDHGFGFDDDFDFDFGFEFGCGEAHGHGHCFCDABFEHHABCECBCHFHCACFBFBHBADFEFEFDFDHDHCHCDEDAGGECHAFDHCABFCFDFDGBGCFCACDCEA,False +242,10.0,3.0,9.0,4.0,10.0,22.0,6.0,6.0,CBAAFFFFGBDAFFFFFFFDGAGEHFGECEFEFHCHCEEEDCFAFAHAFBDEHGHCFEFCFCFEAAFAGC,True +243,16.0,18.0,13.0,25.0,8.0,14.0,16.0,17.0,CFHGHAFGFCFEDAGEBBFDGBGHDHAHBGBGBDCHHEBDBDBDCDHDHFAGGHGHABADDCDFBHAGDDDBCACECAGEGDDHDFDFHFHCGCGCDBAFAFDBDEFEACADADADBCFAHBHGEBB,False +244,14.0,10.0,26.0,18.0,17.0,28.0,19.0,21.0,HEHEHDFDFEGEGFGDCBBDAFHFHFDCEGBBDHFAGBHFHCECHCGAFCCDDADGHGCGAGBDCDHDHDACFCFGACEHEGDGFCFCFCAEFHHHFBFDFDCBCFEFCDGAGDEEFEFHFHFEECCCAAABECFHACECFAFGFCBCGHGHG,False +245,30.0,27.0,23.0,25.0,28.0,19.0,14.0,26.0,AAACACBCAEDEBEFCCHCAEGEDEFGAGCEAEADFEBBBEFAGBBBFDAEAEHHHHCFCHCHADFDEBHFACBFBGBFBCHHAHAEEGHHEAEGHGHGHGCAHADADAEAEAGDGBECHDDDDEFFDCDCACAFBFHCHEHEADFBFBGBDBCGABHBHDACCECDDBDBDFDBEEEEHCBAFHHDBBADF,False +246,9.0,17.0,16.0,9.0,17.0,6.0,11.0,16.0,HGEGACAHDHDCDEGFHBHDHECEDEDFDEEHCFCFHBEGGFABEHHHHGAABCCDBEBECHCHFBAHGCGABCBEBECCCCCEGEBBBBDBABEBHGEGA,False +247,10.0,6.0,15.0,20.0,23.0,16.0,16.0,6.0,AFDGEGEFEDCDFHEGEGFGBCACECEAEHEDDHEGEDEFGDDDCCCCGAGEDBABEFEFDGDHDGDCBHBGFFCFCEEEEFCHEFGDGFCDADCFCAEGFGBEFDADADAE,True +248,1.0,1.0,5.0,2.0,5.0,7.0,7.0,2.0,EFCFDAGFCFGFCHEHECEGGCGDGFGFBE,True +249,20.0,25.0,23.0,25.0,18.0,22.0,28.0,20.0,DGDBDAABACHGHEBDCCABFBAHGGBGEAAGDDFGFAHADADEDFHFHGGGFGFDHDEDBACDGDGBFACABBGBGEGEGECFFFEABDEDHFAFGBCBCACHHFHFBFBFHCHCHCECDGDCEHEGCGBBFBGEFEFHCGCBHGDGFHFEABCCEBDBHGDGDGBHCEDADCDCBAEAC,False +250,27.0,24.0,20.0,16.0,26.0,17.0,25.0,11.0,CHCBCACHBABAGHFEEBEGECEBEBEACDGDHHGAAFGEGABEGAGEGADADABAECFGBGAGAEBEADFGFECACGGFGEGDGFBFGCGBFBFEAEBEFAFAFEDEAAAAGBBBCDCDGECCCBCFADABHDEDEGEAHHBDEDFDFGCCCDBBHAHGBCBEHF,False +251,23.0,19.0,20.0,25.0,22.0,22.0,28.0,26.0,ACACGEBFHHCAGAGHGHGCGCGBEHFHFCAGFGCGHEHAHADDDDAEEEECCFBGHAHAHGBDECFADGCECEGEGDGAADBEAEFHFDGDGAEAFDECBGECCHDEEBGBABEHHAFFFFEFDADHBHBDDGGCGCBAGAHABDBDEFEBCBDHGHGFDFDFDFHBAFCBDBDFFGGCHHHDH,False +252,22.0,23.0,23.0,11.0,21.0,24.0,27.0,23.0,CGGAGEGECECECDBFFFHAHGEGCGAGACEDBBBFGFGHGHFCBGHFHBHGEAHAHABDHABABDBECHAHFCFEFAAGGGBGFCDCBEADADHFHDHCEABCGGGFGAHEEAECCCCGBBEHEHBHBHDCDFFAFBFCEBAGAGCCBCAGFDHHEHFFFCFEFBBEBFGEGA,False +253,21.0,15.0,11.0,10.0,10.0,18.0,15.0,19.0,CFCEEFHBGDEEFEFDAGAHAHGHFHFHGHAHAHGFFFGBDBGAAAABABGBFBFBEACGCEDHFACCFFFGECBAECDGGAFAHDHDHBCCGHAHAFAEDHDHGBBABDFCAGABHBH,False +254,16.0,7.0,14.0,11.0,13.0,17.0,11.0,13.0,CDFHFHECACEDEAECCHFHFHGHGCAHAGAGDEDFDCHCFDADFEGAAEAFFDEDCCEDBFCGCGEBEBHGAGFBABAGFHDHAHAEFFFFFBEBCGHACA,False +255,14.0,24.0,17.0,17.0,23.0,22.0,12.0,11.0,EDGFFFGBBBCACDDDBDCFCFCEEAFGFGFGFDBBBFBDCFEFADAHEDBDFHAAGHCHFGACABEDEDEAECEFEFDAABHHAHCECBFBCBFFDBDGHGHFBCDCECEDEAAGEGFBEBCBEEGEBEBEBHCEFBBH,False +256,15.0,18.0,13.0,27.0,17.0,28.0,20.0,24.0,FBDBCHCGDEDCGAGAGDDFBBBFFFFEDACGCHAGGGEGEBABFHFEDHFHFCBDGHGBGDHBCBGAEHFAFHHHDBDCHBFGFGFHFHEGEBDFFFHAHGHCHAHDHEBEFEDGDGAFABDBEHACFCFCEDADEFBDDEAEADFDFHFHFDGHEDDDDC,False +257,6.0,7.0,12.0,13.0,9.0,11.0,8.0,10.0,DDACHGHGHDHEFCCEGEGACCDCDCDADHBFEFEDEGCFBFDFBFEHCHDAGEDECBCBHFGFDFHAHCGABDBF,False +258,17.0,20.0,27.0,16.0,18.0,18.0,19.0,20.0,AGEHCDAGCGFGDCDCHCACDFEAGFGAAAADADCCHGHGHCCEEEGCADACAHECEGDGFBFBFCHCHCBBDBDBDEFCGCBBBEHFHACAGBCHFFBCBCGGGGHDBECEHEHGHBCAGEDEBFCEEBEBDFCFAFHBADDHFHFHFHECFBB,False +259,1.0,5.0,4.0,1.0,1.0,0.0,6.0,2.0,GGGGBGAHBHCGDBECCBCB,True +260,2.0,3.0,4.0,1.0,3.0,5.0,1.0,3.0,BFBCBFHEEGEHCACACHFFDF,True +261,2.0,4.0,3.0,2.0,3.0,2.0,6.0,2.0,CDCABEHHGFGFGEBABCBGDGEG,False +262,17.0,17.0,32.0,25.0,20.0,22.0,15.0,15.0,DHDCDCDGEHCBGBEBACGDFDCBCFCBCEAEAFCDEBAAEADHCEAEHECDDDBDCDBBFFEFGFBCBHAHFCCECGHDHFHAHACDEHECFCDEAAHABBCHGEGDGFHDDCDGDCCCGCACACFCFDADFGFBFBFEGEGEHDACGDFCFCFGBEBEFCF,False +263,7.0,4.0,7.0,4.0,5.0,5.0,7.0,12.0,GCACAHGHECGCHFGFEDHDHDHGHBAEAHBHFHGCCBCHEGEBHAFADAF,False +264,6.0,6.0,13.0,6.0,11.0,2.0,9.0,8.0,DCFBDBEEEEEEADAHGHGCGDHCHGEACBCGCAHEHGGAFAGCCCCCBEBHDCBCEGEHD,True +265,20.0,25.0,22.0,32.0,26.0,23.0,23.0,27.0,DCHBHBCEHHGHDCGCAHHGHDEEHEHBBECDCGBBACACADDDDDFCGEABGBABEBEBEACFHFBEGHFBABCGHGEGDDDEGAHAEFBFDGDHBFGFCDCDCDFGFHEBEHEHBDEAEACBDADHFBDDDDAFEFBGGGGHGHCHEHFCFGFGADDDDBDADHFEBEBECEADACBCFAFHFDFGFAEGHHCCFE,False +266,7.0,6.0,7.0,3.0,4.0,2.0,13.0,8.0,BGHCABHHCHGGBDBABAFCGEGDGAHCEEGEGBGCAHAHACGCGHGFGD,True +267,8.0,8.0,22.0,12.0,15.0,14.0,10.0,10.0,DCBAAGBEBEHECCCCFEDDDFGHGDEDCBCGEGEGEBFFAEHECFCHCHFHDCDCBHGGCCBCFCHHFAFGHGDFCEADCDCDCEBFAFACECAFEFE,False +268,20.0,11.0,17.0,15.0,11.0,11.0,19.0,11.0,FACAFGDHCEFHAECBCBEBEAEGBGBGFHCCBCAHDCFCDGDAEEEFBACADABACECHGGDBDGGGFHEHADAFGFGFGHGHGCFCDCDEGAAAABDDDGHBACACDGDHAGA,False +269,6.0,1.0,7.0,4.0,8.0,4.0,3.0,3.0,DBGECEAEAEAEAGDGFCHCECFAAHHFEFCCDEDC,True +270,18.0,16.0,20.0,26.0,19.0,21.0,22.0,23.0,BFBCDDGAGACDBDGDGDADHCAEACGCGDEBGDFDCDBDGHEHCFFFFFHFBFAFHDDGBHHHHFEFABGGDGDEFCDGHCHEFCFHBADHHCFCBGBFEEEEEFEDEDAFGHGDGCACDEAEACDEDHBHGHBHBHCDGAEACCEHGHAHACAGACBEBGFDF,False +271,0.0,3.0,1.0,4.0,2.0,4.0,2.0,3.0,HFHFEFDBEBHFDDBDGCG,True +272,16.0,16.0,17.0,14.0,11.0,14.0,8.0,16.0,FCHEHAFAFBFBDHGAFABBCDCDHBHEFABCHCHDAGABEBAHDHDFCEBGDFECECECEHECACDBDBDCGAGAGACAGBFBGDDACCDDBHEHBACFBFHHHFHFCFAE,False +273,13.0,11.0,14.0,14.0,11.0,17.0,18.0,16.0,CDFDGBHBFGFGFGEDABABCHHDDEDCHCGAGFBFDADHDCDCECAGEFEBEAFAEHEHGGEFBHCHFHFAFDFACGGFGHHDHGHAHCFAFGEBCBGBGCACDCDEHGFBAG,False +274,30.0,26.0,12.0,16.0,14.0,36.0,17.0,16.0,GGHCBABACFGFHFBBHAEAEACADADABABFFDABBFFEFBAGFHFBFCFBAHHHHGGDGFGBHBFEECEFDCHCHBHGEAHADDGAFAFDDBDGFGBEFFFFFGFACABGFFFAABAFACAGAGHDABABGDACFEAEADBBFBEDEAFFBFBFCFCDBHEHEDF,False +275,6.0,13.0,13.0,9.0,7.0,9.0,12.0,6.0,CEFBGCCCCHDBDBCAFDFDFGFHHCCGCGBGDGDBCBCBHFGAAEGBGBFBGBGECHCDAEGEFADAHEDEBBF,False +276,7.0,5.0,3.0,5.0,6.0,7.0,3.0,5.0,BCCDFEFEFEBADABCFDDHDHAAEAGFGFHFBAEAGHBHE,False +277,6.0,5.0,1.0,2.0,3.0,3.0,6.0,7.0,HBBFBFDHCGEGAHAHGHGFEBHBGGAEAHADA,True +278,4.0,8.0,15.0,16.0,12.0,11.0,10.0,10.0,DHCHAEEEHEHEFEHGFBHEDEGEGFCDCFCGCDCBFFFCEGDBHFDDADGGCGDEDEDGACDCFCFBGBHBDBCFCHCDDDHCAB,False +279,15.0,15.0,14.0,9.0,20.0,30.0,10.0,19.0,EAFFEFEFHBHBHBHCHCFAAACFCAHGBGBFEEBECEGEFDCEFEGCBFHFBEAFDBBGDDCGFDCBBHBHFEFEHCHFBFDGCHFHFHFGFGAAAAEECEFDBEFECEHDFCFHDHFFEAAAAAFGFHFH,False +280,20.0,27.0,17.0,23.0,26.0,20.0,26.0,25.0,AEDGCEBACABABGBGFDCEBHBCBCGHBAEACBHHHCDDEGFHAAFABCEHDBDBDFFGFCBGGGFGEEFEDEAEDEDHHHFHEEEGEGCBCBHBEBGBGECEAEHGHABBBFHEAFGBGDGFFEFDGDGDGHGDAFAGDHDECEHHHAHDDGHGCGEBEFABCBDBFCFCFHBADADFDAHH,False +281,10.0,6.0,6.0,8.0,8.0,11.0,10.0,7.0,GBFFDHAEAECDDBEGDGAEECGGGDHDAFADAEAHBHDEFFFFBCBCECAFABAHGFGFGFGHCH,False +282,21.0,33.0,19.0,20.0,21.0,12.0,19.0,26.0,CAADABABCEABHBABDCHEAEGHBBCCCCCHCBGGGGHHDHGHGDGDGDBDAAGCBHDFEEEEEEBEBAHHGHEHCCGHFBFBFBFGHBDBHAFAGACCHAHFBCCFDEDEHCHABDBEGADBBCBHEHEDDDDBDEDBBHAHBEEEDBBBBHGGGCEFBFAFBGAHAFA,False +283,12.0,9.0,6.0,10.0,12.0,16.0,15.0,10.0,CFCEDFGCGFHFBGCGFGABEGAGAGAGAFADBHGHDEFHHDGCADEGBBCHDAAAGEBEBABFDFEFEFHFHFHFHGBFEGEDDDEFEA,False +284,0.0,7.0,2.0,2.0,5.0,4.0,3.0,5.0,FBBHBHECBFDFGEHCHEHEBEBDGFGB,True +285,18.0,10.0,10.0,8.0,8.0,13.0,19.0,13.0,HHHFGFAHCCBCHCBFAGCGBABDBDGAFDCDAEAEHDADBHBAGFGFGHEFFGHGHBHAFFBFCFCAAABEEEAGGGAGCGFGAGADAGEHAHCDGEG,False +286,17.0,19.0,13.0,13.0,17.0,16.0,12.0,9.0,DBDADABCGDAFEFEFEDABCBEBGDGFEBEBEBEADBDGHCADABFDADADABGFGFCBCDCFBGGEEFCFAFEFBAGGEFHCGAFAHBHBFFEBACECACBCHAHEHEHCGBEH,False +287,11.0,13.0,8.0,14.0,5.0,10.0,1.0,11.0,ADDCHBHFDEACFDBDBABCBCDDDBAAADHFBFBABEHEHBHBCCHFDABAHCDDDCDAFHFEFEFHFHGAB,True +288,21.0,32.0,21.0,22.0,23.0,17.0,23.0,21.0,CFCBBDADEDEDBDHDADCCCEHEHBFBHADADBGBGDCBBHFAEBDHDFDFBEBHDEDBCECEGABCFGFHDHGHEHAAGHGEDEAEABGFCCBEBCFDFAEGGAGADECFFGFBBHCGEBEGAFABDBHFFAHAHAHBHBEBEBCBABDEGCGCHCHBHBGEGEGCAAGGBBFCCGDG,False +289,10.0,13.0,5.0,12.0,9.0,19.0,21.0,12.0,GBFAEDDDGGFEFDHHGHGFGFGDGFGHHHHEGDBHFGGHECBAGAEACFBBDBCADFGEGDBBBBCBHHFFBFBFDAAAEFGFAFAFDFDFHGGGGGECE,False +290,10.0,11.0,9.0,13.0,3.0,16.0,8.0,5.0,DBDBDCFFGFGABEBEDEFFGFGFAFABHCAFABCDHDADAHBGBDDDADFHCBCDCAAGHBFGFGFCCBFFCFD,False +291,22.0,19.0,25.0,28.0,18.0,24.0,23.0,17.0,FCFEFEFAGEGCGEAAAEGEHFHEGFGDGDEDBDEEECBBBEDFHFAGHCAGAFAHABFBFDDGECEBGFDFCFCDBEFABGEDACACDHDHDFFCDCACHCDBBGCDBHBHCFCDHHHBHBGFGFADDGDCDCHCDCACAGAGCDDABCEGHDHFGGDDEAFBFACACABGBGFD,False +292,22.0,21.0,17.0,19.0,16.0,16.0,15.0,29.0,EFHHAHDCDEBEHEHEHEHEHCFDBCBDHCAFEGGHDDBDFGFGHCFDDDDAFADCGCFDFBFBHGAFCCBBEEAAGAGDEDAHAHAHBHBHBHEHCABABHBCCCHCBBBDAHGFDEAEAFHGBGEHAFBGHAFAFAHABCDDECGCHHGHGAB,False +293,14.0,10.0,22.0,19.0,17.0,10.0,11.0,13.0,FDGGCACGCDCACBCDCDGHHDHBHFGGCCFBFBCBDFDAGEHAHEFECBHGDDDCEBBADCDFDADEEEEDEBHAHAGCGCBDGECEHEHAACADAHFHFEFCCECEDECCDAEA,False +294,21.0,23.0,11.0,16.0,19.0,13.0,19.0,13.0,ECDFDEAGAEAGHBFEFGHBBGBABABGDGCCAGHBHFEFGGCBDGDGDGHFHABAECEAGHFDFEFBFECECEFDHGFGABAEHEGEBBBBEBADFEHEHBDBDADADGBHADADHGAEBBBDCACECBCAAGA,False +295,16.0,21.0,15.0,23.0,14.0,18.0,17.0,12.0,DDBBHFDFGBGBHBFFFFFFFGEBCFCGHABBEHDDDDBBBBDGFHFAEDHDHCFCHCECBAHACDCDHAAADDECACAGABAGEFEBCAEACGDGFEFBGBDBCBGGDDAEFEDGCGEGEDEDGDBABADFHCHG,False +296,2.0,5.0,5.0,3.0,8.0,3.0,7.0,5.0,GHDHFBBGGCGBHEHBCACHCGCGEEEEFDADBEGEFE,False +297,8.0,7.0,6.0,6.0,3.0,4.0,7.0,7.0,GDGFBFEFAAEBDBDBAGAEHBDBHCHDGBGCGHGHAAACHCHAFCCD,False +298,10.0,8.0,9.0,8.0,12.0,10.0,12.0,8.0,AAAAAADGHGAEEEHFHEHEFFAGAFHCDCGEBCBCBFBFAFHFGGCGHEDGDFDBGEDEDCBEGEGHCBEBCCDGF,False +299,2.0,2.0,2.0,2.0,1.0,0.0,0.0,1.0,CHCEABDBDA,True +300,21.0,16.0,12.0,20.0,12.0,15.0,16.0,21.0,HFHGDDEFBFBFAGCFAGBGDHEHBHBHAEFBDGACHGHAHFFDFHFHEBBCBDBDBCFCDCACAEDEDHAHBHECABAGCEBHBGEDEGAAHAFAHADCDEGEGADFGAGAHCDAGADAHCHDDGDGDHFBF,False +301,18.0,17.0,21.0,18.0,14.0,17.0,20.0,23.0,BEBFFCAGAGAGHGHFHDHCFDFDEDEBEBEAGFBCCHCDCBCHHGHEACAEFGBGBEDEBCDADHFAADBHBHCHFDFDFHGBGBAEFGFAAEHEHEHCCGHDDDGHCCCCAABCGCGCADACABFEHDBCFHGHGDAHHDFGBGFG,False +302,17.0,9.0,16.0,15.0,18.0,20.0,16.0,20.0,CFEHGDGCGHFADAFGFBFHABACDEDEDGAEHEHCCCBCEFHGHAEAEAHAHEHEHCDFFAHDEAFDFGBGDHHFHFAGGFFBEHEAEAFFFDGBGCGEECAFFHEHEHDACBCFCDDDDCBCBHGAGCG,False +303,17.0,9.0,12.0,14.0,11.0,11.0,11.0,15.0,DFDFAGHHDEDEHEHECGFACAEADDHDEDCHCECFHBBBEGHBACGGGAGAHDHAAADEHEAFADGDBDFHFGBABABHBFCHAHACCFCGCEADFCFG,False +304,32.0,22.0,21.0,20.0,17.0,21.0,22.0,16.0,HABACGCBCGHGHADEGABAFHHGFCCGFFFHFHAHAGACFGEEAHAHABABFBAEAEDGDBDFFFFEGHGDDDCHFAFGECACECECEDFBEAAFBCGAGECECFCFCBGGADADGHACAEBHAHABGGDDADCDADBBBGHEFEDDDGEFBDBDBCBABCBAAAACFGB,False +305,22.0,14.0,10.0,9.0,20.0,15.0,19.0,12.0,GAGABHEFGHGABAEDECGAFABBEFEAECCAAHGHBEEEEEFHFGFGAEAGAGDGHGFAAAHAGAGFBECEFFBBGHGFCBCGCADEDBDBDBDFEECEBEDGAAEAFAHHBFCFCDHGH,False +306,7.0,13.0,6.0,7.0,4.0,5.0,5.0,12.0,BABAFAHDFDGBHHEHBDACHGHGDDBDHFFAFACEBEBEBHBCAHBHDHCGBHBCGCB,False +307,27.0,19.0,23.0,17.0,31.0,29.0,21.0,17.0,FADCDEGEBEGHDAEFEAEBHBCBAFAHAFGEGFBFCAHAHCCBDFHGCEFFCFEFEAEAFCBDADADHDFBFBEBADFCFEFBFBFDFCFGFEAHBBCCCCHHBHAAEGEBECEGDAEFDGECEFEHGAGEFEDGBABABHDHDCDCGHAEACAGFCECGGHEDCFAAAGAGCEHEGEGFGFE,False +308,16.0,23.0,23.0,25.0,22.0,21.0,28.0,27.0,BHGEFEDACAGADADGDGDBBFBCGGHGFCFCEHHDCDCEGFCFBEBEHDHCHCBEDDHBBEBGGFDECHCHCBFDFBGEHEGEDEGAHDBDAHGBGDGBCFCGCGBBAFAFABBBFGFHAHAEAGFFFGDDCABHECEDEBEHDGDEDEGCHCDCACHCAFGGGHFHFHGHGCAEHHHHDDBEF,False +309,11.0,10.0,14.0,4.0,9.0,15.0,8.0,17.0,CECHBGAHBHAHGCACBEFEFDCCCCCBCDCGAFFFFFBCBAFHFHFHDAEAHGHBHBHEHBHCGFBHAAGEFEFEGHAHDFFCAEHG,False +310,7.0,7.0,11.0,8.0,8.0,14.0,8.0,4.0,AFACGFEEDBGHDDADFCFCFCFDBGBHEHFAGDCACFCFEFBDBGBEBFCFCFCADGEGEAHCFGE,False +311,1.0,3.0,3.0,4.0,1.0,4.0,5.0,3.0,DHHBHDGDGCFAFGEBCBCGFGFD,False +312,9.0,6.0,12.0,3.0,7.0,3.0,4.0,5.0,AAEAECGCDFDHACECEAEBHBACCHCHEGCGCHCACBBAFAFCDGEBB,True +313,10.0,20.0,11.0,11.0,10.0,21.0,14.0,10.0,FHEBEBCAHAHBFGFGHGFAFCFDBDFDCHBECCCHEACABDGFBFEFAFAHGBFBDBDBFCCCEBFGGBGFAFABEEAEGBBFFDFBFBDBGBGCGDEDHFHDGGH,False +314,11.0,11.0,19.0,12.0,11.0,7.0,10.0,11.0,GBHBFGDABADADBDCDADHBGCECHCHCGCEAGCGCDCFEAGAEAEHECEFFBECDCGEHCBBBCGDHDBDADCFFEFCACAEBHHCHGHC,False +315,15.0,20.0,19.0,23.0,12.0,16.0,12.0,15.0,CCCCEFDBDHDCDFDCHFHFDEBACECHCGGFGAHDDDBACFFFDFBBABABDBACADAHCHDGCFFBHHDHDHGCCACEDBDECEHEBABHFDDDDGEFBFBGBEBFAGAGBGHEHDFEBABAEADBCGCG,False +316,6.0,8.0,6.0,3.0,8.0,2.0,0.0,9.0,CBCDFDHABAFEHBHBHECEBECHHBEEECEHAHCDAHABAB,True +317,5.0,12.0,12.0,7.0,8.0,8.0,7.0,11.0,CHGBGBFBFDABACAFFFCECHCEGDBBGHCCBGDGFGHEHDHCHBBCCECEBEAEAEHDCDHHBHBDFF,False +318,19.0,29.0,24.0,19.0,24.0,39.0,20.0,15.0,CFEFGHBHFHCEABFCCCFFEFEGBGBAHAHDBABCBGBGBGAGAGABHCCCFFFEHEDGBHEEDHDEDBHFDBCBGBFCFBEDFAFCFGACEFGFGAAFFFFDFEFECCGEGBDAAECECABEFDFCEAEAHFDBABDCHGBGBGBCACBCBEFGFGFCFHDDFAEHDFFEDDFDFBFBEBEBFHFCD,False +319,8.0,5.0,5.0,2.0,5.0,4.0,3.0,7.0,HAAEAHDHCBDEAHCGFGCEABAEAFAFHFHBHBCBCEG,False +320,4.0,0.0,2.0,0.0,3.0,0.0,0.0,1.0,CACAEAHAEE,True +321,19.0,25.0,20.0,14.0,21.0,25.0,19.0,10.0,ECEAHAGAGDCFHAHAHABEGAGBEBFFFFFGFDFDFGCDCBABEBGBFFFAGADFDGHGABAHAGCBABGDGEEACAEDBCBCEEFHGDDCBCEGEFEBEBFGCHBHBEDFHBCGEBCDCFCEBEFEBCBCBCBAGFFAFAFDCGEEFDCBF,False +322,4.0,3.0,7.0,8.0,3.0,3.0,6.0,6.0,AGDFDFDAGECEDDHCHGHCBFDEBCBCHCHCDDAHAGGG,True +323,20.0,23.0,10.0,13.0,14.0,23.0,24.0,21.0,AGAFFGHGEBBCDCEEEGBFAHAEGEGCGFGAAEBGHEBDGAGEBABEFCHAHADFBFDFBHBHBGBEBFBFHCACGCGBFBFAHAHFEFDBGGGBGFGBBEDHGHGHFHDHDGDHBFBFDFHFHFACADAGEFHCAADHBHCADFGA,False +324,6.0,10.0,13.0,15.0,5.0,10.0,12.0,7.0,ABBDDDDGDHDCBBHCHGDGBAEGEGHDBCFGFBEBADGCGCGHFFFFFCFCBDBDGDCAAAFDHCCCECDFDHCGEG,False +325,14.0,17.0,16.0,18.0,24.0,25.0,25.0,12.0,EAGDFBFEHEFGADABCCEGEAEGEGHGBFBDEAEDHDFEFDHCHGBGEECDCDCDCHCDEAEACCBEGAGEBFBFBFCCGFBEBCCDEDFDHHGAGAGEEFFFFFBGHGHBDECEBAFAFDFDGGGAHBEFGFGFHDGDEFGCABFBFGG,False +326,10.0,8.0,13.0,7.0,11.0,10.0,9.0,12.0,HGFCFAFCFAGADEDBHFCFCHHAHACEBECCCCEGEFEFGDBFBHBGBCEEABCECAADDEDHDHBGEGAHCHFHGAGH,False +327,13.0,9.0,7.0,7.0,11.0,9.0,9.0,4.0,EFEGEFABAFHDBFAFGGEBEFECCCEFFDADBDGEGAGABABABFBDDAEAHAHGHEAAGDECCCGCB,False +328,11.0,7.0,14.0,13.0,15.0,16.0,11.0,12.0,HHHHFDGEGFHFHGDGCCHFBFEDBAHGFCDCGGDDACACEDBGEDEHHGHEFEFCFGFAAACADHFAFCFCFCBDBAEEEEGDFBFAEAEDEDEBCCC,False +329,14.0,9.0,16.0,7.0,13.0,4.0,16.0,18.0,GCAEFCFCACAEDGGEGBGBGBHBHAHECAAAAHAHECECHGHADDCBCFCHHGAGEGDGEAECGBHDACECBHDCDGHCHGEBHBHEHCFGEGHHA,False +330,6.0,12.0,18.0,17.0,8.0,10.0,10.0,6.0,GGFCECDCDCAABEBEHEFDDADGDBDHGFBFBEDHDFBHGGCBCBCDCBCHDGCBCBEDCDGDBECADACCCFEFGFGFHDADFCC,False +331,11.0,25.0,21.0,16.0,17.0,27.0,21.0,23.0,FFFCHCBCGHHHGGCEBEDFCHAEFCFHDBDBABFBFEFBFHDHFBGCACHHFBFDFGFBHHDBEFAFAFHFEEEGEGEGEDBHCDCACHHGFGFHHBDBDBHCHGEDBDECECECFGBDBCEGGGGCCBCAAADAHBBBGBGFGHDAEFGFBBGHDCFCF,False +332,31.0,34.0,15.0,23.0,18.0,19.0,14.0,23.0,HBFBAAACBDEABCHDHAHDFEFHAAACDEBHBHBHBCBHBHBGCAFGBGBFFDFGAEAEBDFFADADACADDDHAHAEEBFDFGCCCFCAEGBCBAHCGEEEEEEBFDFEHBBBABAHADBDEDFGHHBHBDDABBHBHDHFCFCGEBAAAEGFDFDGDBBBAGAGABAGHBHCAD,False +333,20.0,17.0,9.0,14.0,13.0,13.0,13.0,14.0,ABGCECACBHDHGEEHEHBDAAAFDEDGDFAFABCCGHBABEBEGADADFDEHEHEGBGAHADDHHGHGCGFFABAFDBDHABEFDCDFFAFBEBHBAFAFABABGCECHGBG,False +334,7.0,5.0,2.0,4.0,6.0,6.0,4.0,9.0,GCGBFBHAHEBEAEDCGEAEHHFHAHABFGFHFHDEDADAFHB,False +335,17.0,13.0,10.0,10.0,9.0,12.0,9.0,20.0,AGHHAHAHCBABFGADADEFEFEDBBBBHHGHDHBCECEHFHFHBHAHDEAEAEBEHACAGADHCHBGGFFFHACBDFDAGHCDGDCFCACFHFBBHGAA,False +336,10.0,13.0,6.0,5.0,11.0,4.0,11.0,9.0,EGEBEBEGEBAHEFBCBEHGDFHFAFCBHBGDABHGGGBGCGBABADHDCEABABADAEEGAGCHCHEH,False +337,17.0,16.0,15.0,8.0,14.0,17.0,17.0,24.0,HBGBABHBHDFFAHAHAGAEAEAFACGCBCECFGDGCCEFEFHHHABGFCHDHGBCBHBDGDHEHGHCFCHGHDHFHFBFDABHBGBAFHEEGEGECBAGEHBHCHEFEADCBFGHCEFGCGFAAAAF,False +338,18.0,20.0,22.0,16.0,18.0,27.0,14.0,22.0,AEAEAEAFHDHAAEFBDHGFGFCAAAGADFFEFBADCHCHEGBBEBGFGFGEHEDCFHAEBHCDCBCGAECGCHCHBFBEBHHHGCBHFDDGHHHCHBDEDECBDFEFBFGFCFBFBCBFBFCDEAFDGABADADBFFFFECECADHHHCHCFCFCG,False +339,24.0,25.0,25.0,23.0,21.0,21.0,28.0,25.0,ABAFDFCFCGHGCDBDGEGEGCAAEBHBHGHGHDADCGCHFECEBDHDABHGCGHDHEEEBFBFBDDCDGEEEHBFFCFBFAFAFGCCCHGGFGCACHEDEHGDDBHEHDACAFHEABGCACABDBEBFDGHGHFHEAEAEADACGGBBBCGCGDGBGBFCHAHAHFBABFCEHBADGDEBACGCGFAFDHD,False +340,14.0,19.0,9.0,8.0,9.0,16.0,11.0,11.0,CAADABAEACBCBGAADHBFFFBDBDEGABHHHAEFHBCFHBEBGFDFBFBDBDBDAEGEGEFCGBFBAEGBGFGFHFHFGFCBCAAGAFEHHHCBC,False +341,2.0,6.0,2.0,4.0,1.0,4.0,1.0,1.0,ECBDBFAFDFDBGBHBCBAFD,True +342,10.0,9.0,6.0,7.0,9.0,12.0,7.0,13.0,AEAHAHFEGEGBGAEBBHFDBGBHHGHAFAFAFHFDDCDHECFCACFHFHCDCDHBEBFAFGFABEEEGBDHH,False +343,12.0,23.0,13.0,17.0,19.0,18.0,25.0,20.0,GCGCGCFABHCGAFCFDFBHBHEECDDBEHEAEABABAHHFFDFGEBEBGCABAGGEGEDEDHBCFDHDGBGDGHAEAGDHAEEECHHFBDGCFCDBDHFHBBBDHHCBEHFHGGGFGFBEBEFEFCFGFGHGDGDBHBGBABDGEG,False +344,8.0,19.0,17.0,14.0,18.0,17.0,16.0,26.0,BFBHCHCACDDFCHEHAFAFEEEDHGHBEEFADGGFGEEDEDEFEFBFBHHGHGHDEFCGCGHDHDBCHDBCFCGEBHBHEHFDEAEBEGCGBHBFBHBCBCBCBGACCHHHGHFDFCFHGDGHEHDCBAAFHBG,False +345,14.0,25.0,9.0,16.0,24.0,29.0,24.0,20.0,BDBDFDFEGEDADGGGGDFAABHGFGFEBHFECHCEDBABFBEDGGCFCEAAHGHFBBHHHHHHEBEBFAEEBEDGDCHEFBFBFBHEGEGEAEBGGCAFFGDGAGAGHFFFFFGCHAHBHDEDEFHBBBFDFHFBFBFBHDEFGBEDEGEGBAFFCACEG,False +346,20.0,21.0,26.0,20.0,28.0,15.0,21.0,20.0,EDEDFHFHEDCCECEHEHCGBBAEFDDHBGBEBGAEHECGCACECGCGCDEHCAFAECHBBDGDFCFBBHBEBEHDGDBDCAGACAHAHDHCEBEHEACDDDFFAGAFAFCGEACACGEEAHAGAGAGEFEFHFBGCHBDBHBCGDGCECHDHFBFDCGCBBEBDAEGEGE,False +347,9.0,10.0,7.0,7.0,9.0,11.0,7.0,1.0,DAFCBCBAFDEGEGEFAADGEGEAEAFGFBFEFCFGFCFHEDCBGBEBAFDDABCBABDBC,False +348,23.0,21.0,22.0,23.0,12.0,21.0,19.0,12.0,DBGBGFCCGCDHGFGFGFDCDEAEAFBFBHGHBCBABAFFFBBAFHFCDBFECCDCACAEADFDEDGCFCHBBBBDFDCGAHFGEADDGHFFDADEGEAEFEDECACACAFADCFCAGBBABEDGDHCGCACACHBDGGAGBGBHAHADDDHB,False +349,24.0,18.0,28.0,33.0,14.0,23.0,32.0,22.0,DBDACACDEGGCFCBGBHFGDGDEDHHADCFBFDFDAAFAGDGCFCECEGDGFBAGHDDCDCDGHCFFAFGDGDHDHFGGBGHDCDCAHFEDBFBFCDDEDGHAHADABHBEAAACADGBGAGAFHCCGFGCGDGAEAGDGHFHFEBAHCFCFGGGEGEGAGHBBBDCCHCHFHCHDFDBDCDEHECBCEAABC,False +350,8.0,4.0,6.0,7.0,7.0,4.0,16.0,7.0,EDGFGACAGBHBEBAGACAGEEEEEGGAGCGCDAFHGDCDHGHCHGBGAFDFDGGGDHH,False +351,14.0,22.0,13.0,15.0,4.0,11.0,14.0,13.0,ABCCHHFHCDBDBDBCCGCGFFDFBFGGBAHADDGDCDCBAHABEFHBBDBDBDBEBEBGDAEABDGFHBHGAGCBFHHHHHACGBGACFBBDGDBFAGAGACACF,False +352,23.0,10.0,18.0,19.0,18.0,25.0,14.0,15.0,GFADHDHFCGCBFFFHHEDFDHAEEFECAGBGEAHAHADAEGCBFBFEGEFHHEGGCFCHHAHAHEBAADAGBEBEDEDGFEFAFADADFGFAFCECECFFAFACACHCDFDADCDGGFDHCCCCDGDAFBFBEADBDAECF,False +353,28.0,26.0,15.0,29.0,24.0,17.0,31.0,29.0,EFGDADGCGBGBGBEAEHGHFDDEDEDEGHGEGEGHGHEHGDGBGFEAEGDCHCHDHFHEHAGDHDFEBEBEBEDCDCACAFGFCABFEGBGAGHHBDBABABHHAHAECEAGBGBHBFEDHCFCDGAFDHBEACFHHGDADHCFCBAAHFFGFDADBBEBHACABAHGDGBEAFABDBGGGGDDDAAHDDDHCHAABE,False +354,2.0,5.0,6.0,7.0,4.0,6.0,4.0,6.0,BHGHAECCCFADBDHDEDBFBHDCDCDFGCGFGFHHEFEB,False +355,6.0,5.0,6.0,6.0,6.0,7.0,2.0,4.0,HFHCGCGBFEAAAHAFBCBDEDEDEDCDFFABBCFCADFEHE,False +356,6.0,7.0,14.0,10.0,18.0,19.0,15.0,16.0,FBEHFGEHFDCDGGGEHCDCDFFFHBABDFDFHCCFEFECEHEFCAAGFGBCBFGFEBCACACDFFGHGBEHEHEHFHCCEGEGEGECAHEDEDGDGEHHHGHFF,False +357,14.0,24.0,11.0,19.0,13.0,13.0,20.0,12.0,CAHGEBBDBFBEGHAEDBDHDGDGECACACEFBDBFFGADBHBCCDCDHDEGEAFAFEGBFBABHFHAEDEDGHGBEBGBGBGFFBCGEGDAFAFAHAEBCGDDAGHHBCBDBDBFBDBDCGGGGH,False +358,14.0,23.0,16.0,16.0,14.0,16.0,6.0,16.0,HBCBHFHFHDBAGAEDCCCBFDFHFHDHDHGHABCFCFAGEGBBBFDADADBEBHFCFDFCBADDBCBCBCAEGEFCBABAFAHBFBEBEBCCEEHEDECBFAEHGADHDHEHBDEFBCDA,False +359,13.0,21.0,20.0,21.0,14.0,16.0,20.0,15.0,GFDBDCACAEBEBEBHBCBCECEGACHCHAHAGGBADADBDFCFHGDGDGEBHBDGGFGFGDBDAGABDGDGEHFDAEFFGFDHEBCCDCHCFCECHGDBCEHEFDFDABEBGDGHACFFBDCEAFGDBCGCBCFHBHBH,False +360,2.0,2.0,1.0,1.0,3.0,6.0,2.0,3.0,GFFFEFEBDBEHGCAHAHFF,True +361,14.0,17.0,14.0,17.0,23.0,22.0,11.0,18.0,DHACABDDDFEFBCAEAEAEFCFEFCFDFHFAFBCBCHGHFHEAEGBHBGCFCHAEBEFECECGFEDEFCCHAFAFAFADGHGBGDHDEDAHBHBHGEEBDHDBEEHGDEDEFBFBFHFGFBDAEBDGCHEEDCHB,False +362,7.0,7.0,14.0,4.0,6.0,6.0,6.0,3.0,CCBCGEGCAFAEADAGFGFCFCBCGHBBDBCGEAHAFCDCACBCHCEEFECBD,False +363,10.0,8.0,17.0,16.0,17.0,20.0,8.0,12.0,FEADABEGEHEBEBECFCDCHBHCAEEGHCFGFGFHHEFEFDFGFDECCACHFFFCDCGADAFGDCDCDCEFFFFAHAHBEECCDADAFFBEDEDEDHCFCDBHGHDB,False +364,8.0,4.0,4.0,12.0,13.0,9.0,10.0,11.0,FFHEHDFFAGEGEHEHFGDDDEDECEDABHFGFGDGAFADAEECGGABDBGHHCDCBGFDHDHAEAEHEHE,False +365,6.0,2.0,5.0,1.0,4.0,5.0,1.0,5.0,FEACAGFEFHCEABABAHFFEHAHCHCDC,True +366,11.0,5.0,9.0,15.0,4.0,9.0,12.0,5.0,CCFDEDFDFEFEHDBDCDHGGGGDFDAACADABFGCBCAGAFDFCGCGAHAGAHDBDHCGEBFDADADGG,True +367,22.0,11.0,14.0,10.0,20.0,19.0,35.0,19.0,DGGGBCECGDADABABHEHBHGAGHGFAFAGBGBGEEACACFEFGGGEFHCDEEBEBAHCEFFFFHAHAHGFECBHGGEGEHAHFGBDFHEEGCGFDAAAGEGAGFEFHFGAGAGDHAACAGHGCGAGDGBFHFGCGCECEHFHDGEGCD,False +368,2.0,3.0,4.0,0.0,3.0,2.0,2.0,2.0,BCECECHFHFAGEGBBCA,False +369,2.0,7.0,10.0,3.0,12.0,8.0,6.0,9.0,HHDHDCCEGEFFFHCBBHDEGEHEFEFEFEFBCBEBHBCCGCHEHBGGACECEFGAC,True +370,17.0,20.0,13.0,14.0,12.0,20.0,18.0,16.0,HEFEBECCHDECGCEBBGCDBDBDGFGFAFHGDDFDHBBBFAGDFAGACEFHGBFDFHFHFHCGBEDHFCFCFGAAEDECEFBFAHABACAGAGACAHABFBFGEGDBFBHBHDHDGBABAGCGEBAHGH,False +371,14.0,16.0,16.0,7.0,13.0,5.0,11.0,14.0,GBGBEHFHFBBBECAABDEABAGAEDEDBCEGECCACAGACACBCHCECEGABDBEBHBHFHCDAEADHCHCHFHCEABBCDHEGFGCHBGGHGHA,False +372,9.0,15.0,11.0,10.0,12.0,17.0,13.0,14.0,BEBEBGFFBFGFDFGCGCGFHDGGCFAFAFBFDHDEAEHEHAFBFEGHHEBGAGCHHHDDCECGCABFBFHFEDEDHBBCBGBCAGACAHBECEDDHBHFF,False +373,14.0,9.0,8.0,14.0,6.0,19.0,18.0,14.0,BHEFAHAHDDDDFBFDFGFEFHGBBFAAAGADHGBFCDGBEFGFCHHGFGHGHFHGEGAGEEAGDDABGGCCCBHBHCHDFAFAFAFGFDFDADADCGCGHF,False +374,13.0,6.0,13.0,5.0,8.0,10.0,12.0,6.0,CBGADAHAHAFAFGCGFGCDEAEADADCBHDFAACCCAFHBBCEGEGECFHAEBEHCGFGFGEGCGCFCGABF,False +375,8.0,5.0,6.0,3.0,11.0,9.0,8.0,4.0,EEEEHFFBFGGCGHGEBABEEFCFCBHGDBHFAFAFDFGAGDGAECECECAAAE,False +376,6.0,8.0,6.0,9.0,8.0,5.0,12.0,5.0,AEGEBACACHCGGHDBDBCEGEBEBHFDDGDCDBDBEGCAFBFGGGEHEAADFDFHGGG,False +377,2.0,3.0,2.0,5.0,6.0,4.0,2.0,2.0,EDEDECEBHBGFGAEADFHBDFEFDC,True +378,18.0,11.0,12.0,20.0,13.0,19.0,14.0,21.0,GAEHGHAADADADBFCECDCFCGDDFCGHAADFFFGHBHFDCDBFHFHGHFAGAGABADDHAEDECFFFAFAFDEDEBABFBGGHBCBAACBHHHFFEDEDADBEHFHGCGEEDHDCDGHGHEHEHCH,False +379,15.0,10.0,10.0,14.0,7.0,13.0,13.0,11.0,FHGHGHBBCDDDDABABGCEDADCHGAAHAFCFBDBDADFCFDDHCHFHAHCHCBCGGAACAHGGGGAGBEDFDFEAGDGFEBEFFAFAEBEF,False +380,20.0,20.0,27.0,28.0,18.0,28.0,19.0,15.0,FAEAEHHHHHHECBHFFFCFCDAGFGDEDCDCBGFFCGBGEGBAEAGFCADGGBEBEFHFDCBAEFDFDEDAHAHGEDAGBGFEBEGFDDDFDFAFCCCCCCBCBCGCGCACDDBFAFBCDADCDEDBCBCGHGFGBBAFDCDHBHDDBDCECACDFDGABFEDEAEFHHAAFFF,False +381,9.0,4.0,8.0,8.0,10.0,3.0,5.0,2.0,DEDECFCECEDAAACHEGDDFDFCACECGAABDGCHBEBGDGBAEAEAE,True +382,28.0,23.0,23.0,25.0,22.0,19.0,22.0,24.0,EBAHHEDEDBDHHGADFEFEHDHDGFFDFDADHDGEACBEHEFGDGAGAGEBCDCBBAFECHGGBHCHCGGGCGAFCHCHBBEBFBFHFCGCGEDEAAADABABADFEFDCDCECDCHCHCBAAAAAAHAFEGEADCCFHFEBEBFHDHFAAAGCBBBCDHDEDFBEGHCBDBGHGCGHDEAGABA,False +383,4.0,5.0,2.0,2.0,4.0,7.0,4.0,2.0,FAFBFGCGAGAGFBDEFEFHABFBDCHEBE,False +384,23.0,10.0,11.0,21.0,17.0,14.0,20.0,15.0,CBEFFDDBFAGHDAGAGAGDDBEGCCCDCBHHEAEFGFEEEHEACACAGAGBDAAHFHFAFADEHCACGDAEEFGGHEHBCDAGAEDEBFGHDHEHDHFHAGAGAGAFAFABBCDGGGDBDGDEDEDFDHD,False +385,16.0,15.0,15.0,12.0,17.0,20.0,20.0,23.0,FGBHBHAHAHBDFEFEBCAEEDEAHBHBHEFDCBAFCFAFAGHGHGACDHBCAEHGHBABFCFDGDFDFHFDBGFGHHACADACHCGBEBEHEACGEGFGFGDGEGEGECEADACBGFHHDFFHFHFGGBHCGCEEHC,False +386,22.0,28.0,19.0,25.0,19.0,24.0,12.0,27.0,BHDGBHDFDFDBABGDHAFAECECBCBCFCBEBHHHEEEBAFDFAFADECBDFDFAEHBHEHEGEADHHHFHFHDBFHAHADADFDFCAHBCGCDCBBBGBFAFCFHAGADDBFEFEAAHCDCECBDFFHFHBHBFEDCACAGEFDHGBEHGBCBHEEGAGHBDBDGHADADCBCB,False +387,16.0,23.0,23.0,12.0,27.0,6.0,20.0,14.0,EDEBGBEBCGGHCACBHBEGAGHGCGEGFCHBDCHGHBHGDADADBBCHCBEBACGEGEGEBABABDEEHECCCCBBBGAGAEAGFGHACCBBABAGFBEEEEEECGDDCDHEEEAEAECDCECGCFHFCBCEADDHEBFH,False +388,29.0,22.0,29.0,26.0,26.0,22.0,19.0,18.0,CECEGHFBFDDCDHGAFBGDFAAHACACAEEBEACFCAEECCGCGCFFFABGBGDCDGDEAEABHBHBFBHAHDCECECHFEFBACDDDEHAGABADFDFDBDBDECECEDHDAAAAEBEGAAADGFBFADACHEAACFGFGCGEHFHFCCCDGGBCEGFAFEBHCDAGBCBCDCEEGDBDBDHFHEBEHH,False +389,6.0,5.0,9.0,6.0,6.0,10.0,3.0,6.0,AFFFACCCEHHHHACDFDEGCBCDEDCFBFBDBFHFHADGCGCEFAFAEBE,False +390,5.0,5.0,8.0,6.0,3.0,4.0,2.0,9.0,CHCGBFDADACBFDFCHHDHDHCGCBFAEAEAECHCHBBDHH,False +391,17.0,18.0,29.0,20.0,13.0,16.0,17.0,22.0,GDCDGHHBEBFCFHGHAAAHBCDCDHFHEHBDDDDDCDCACHEBDBCBFDACBCBHACCDCGGGGCBCFCFBACADHHCFCADHHHGCBBGDGCGEEHEACAGGFGCABABDBEECECECFAFAGHHDHDFBFGFHECEFDFAHBHFGCACE,False +392,4.0,11.0,10.0,5.0,8.0,5.0,3.0,15.0,HHHHEEDDBGHGFABEBECCBHBCBEDECBCHCBEFEHDBDHAHBHFAGCHCHCBCAHFHF,True +393,5.0,6.0,6.0,2.0,4.0,4.0,5.0,6.0,HGFGHHHAGCGEFEBDFDAAHAFCBCBCECBGBEBHCA,False +394,21.0,28.0,17.0,22.0,17.0,15.0,15.0,14.0,DHAAAAFCDBDBDGGABBBCHCACGHFBBBBBBBAAAAFBBBBBEGEABCGFDHEHEDBAADEDEDEHCFEBEGDHFGGECDCHCHBDCEFEHDBDBDBDCECGCBFDGBADHGGFAFAFACEGEFDFBABFFEGDAACACHEHDHDCG,False +395,17.0,17.0,23.0,13.0,25.0,16.0,32.0,27.0,ACFCFGGGEEHEGGDEHBACACECEFEFHDEDFDGEGBGFHCCACEEFDACHGHGHBEEHBACCCCHCEFDAGAGEGCBHBHBGGGDGCFAHGHGHCAEFBBBHBGBHHEHEBGGEGEFHFHFHGHGCFCGHGDEDAAAGCBBBCHAEAHDHDFGGGEGBAHECDFDCAE,False +396,2.0,4.0,1.0,7.0,6.0,10.0,8.0,9.0,GCGFGFGHBFAEGFHFHGBDHEFEDHDEFEFDFEFBGHHAHGDBDHD,True +397,12.0,14.0,13.0,17.0,13.0,20.0,12.0,15.0,CEBHFCBGHGEGEACAHBHBDBGBADFDHDFDADHHEHFHBAAFACECECEDDGDGDCCCHCGBBDGFBECGDGACFFFFFFDHDHAEFEFBBGBFHFHECAFDBEHDFAFAEGFD,False +398,28.0,19.0,7.0,24.0,27.0,19.0,20.0,15.0,DHEAEADDHGAAHAGEHEBDBDHFCFEFEFEGAGHGBFHECAAGDCDADFCHDADADFDHGBGAEHDGFBFAFAFEFEFEHCAAAGGBBABDBCEADADFEGEFHADEGGGEGEGBGBDADEEBDBDHEEEDADEBBFHEEFCFEFAAAGABABDBHBG,False +399,0.0,3.0,1.0,3.0,3.0,3.0,0.0,4.0,DDHFBFEFDHBHCHEBE,True +400,14.0,15.0,8.0,10.0,12.0,16.0,15.0,13.0,BABABGHFHEHEAEBFGHDBCBGDCFFGAGDGFEFEFEFHDCAGAGHHAHACBCBGAGEGEDBDHDEBCACBHAHCFAFEBEDFFFBFGEGFABHGDADFBHG,False +401,11.0,5.0,16.0,15.0,7.0,18.0,6.0,17.0,EGDHHBGCGFFFFECHDAFAFBFDHGHAACFFFAEHBFDFHEHDFDFDABBEAFCCCCCCCFHAGADDDCCEHEHCHDHAHFHCCCFDHDHDADG,True +402,3.0,10.0,24.0,13.0,15.0,13.0,11.0,19.0,CBBEDHAHBDBDBGCECHHDHGHDCGCGEHCHCGCEEEEHFHFECEGBDDFBHEDBDADGFHCHCGCBCDCEAFGFGHGHCECFDECCCCCDHHEBFHFCFCEHFFCF,False +403,1.0,2.0,2.0,2.0,0.0,1.0,2.0,2.0,DGDABGBCHCHF,False +404,5.0,16.0,6.0,12.0,8.0,5.0,12.0,9.0,DGDHBCBCHGEEHEFGFBAGABADDCDBBBBBGAGEEDCDGHGHFHBHGGCEEDBDBDBCBDBGFAEBHFHGD,True +405,21.0,16.0,12.0,16.0,13.0,10.0,25.0,18.0,GFEFBFGGBGBGBHFHEBEBGBGFGFCEAGCDHAABHBEGCGHDHAHDCEGDGDBFGCAAAAEAGADFDGDAACACECEBFDHBAEACHGHAHDEDEFHHHBGEGACDBAGGBCBHHCDGAGDGHGHADAD,False +406,4.0,4.0,3.0,5.0,1.0,0.0,4.0,3.0,GBDDABCBCGDGDCHBHDHAGAEA,True +407,16.0,7.0,6.0,14.0,13.0,6.0,14.0,8.0,BFCAAAAAEFEBDFCFCADGDBDBDAGAHAEDEGHGHGFDBDGAEHEAEAGCEDHAEADGDAFADGGEGHGHDEBEHDGBGCCE,True +408,12.0,15.0,11.0,21.0,18.0,14.0,12.0,11.0,DBDBDBDBCBGGABCEFEFGGDBDAAAEHEFEBGBECCFCBGEEAEHCBFEFHFCEBFBHGADFDACABEBEAECDCGFDDDDDDHGEGFDHDHDHFCDDEDGAAFAFHHGHEE,False +409,20.0,21.0,28.0,22.0,20.0,26.0,20.0,22.0,FCFDFHADGDHDHBBCCHHDHDHDGAABAGCGCDCDFFFAEAFBHHGHCHEFEGBDCDAAHABBCFHFEEGEFFFCHCDBDEDEFEDAFAFABEHCCCEBHBDGDECCAAACDGFFEDHDFBHBAGAEAEFECGGGCHCDAHBGBDBCBEHGFCFCFCFCEGEGHFCBGFGCGCEABBB,False +410,3.0,1.0,3.0,3.0,0.0,0.0,1.0,2.0,DGACBHDHDCACA,True +411,10.0,24.0,18.0,15.0,16.0,10.0,24.0,18.0,HHFBFECHGHAHFGGDCBCBCEGHGBBAAGCCHCBDBGBDHHHBFBDBGGCGHGABABACEHEHCDGDECBAAEFGGDGEADDDHDHBEBEGEFEGEGCGDGDEDBCCCHCEBEDCGFGHGEGFBFBACHBBBBF,False +412,7.0,7.0,14.0,10.0,10.0,6.0,9.0,5.0,GEDFDFBAGCDABADDGAHEDEDFDCDCDFHCBCBCGCHBGCFCAEEEEEGEGCCCHHGCBEBCAGAF,False +413,1.0,1.0,2.0,0.0,2.0,2.0,3.0,2.0,FGCGCHEHEABGF,True +414,3.0,7.0,4.0,3.0,7.0,6.0,6.0,8.0,HCHGEEBABABFBEGFGAGBDFDEHEFCFBHHHFHCHCBEEGGD,False +415,17.0,22.0,23.0,22.0,24.0,17.0,20.0,16.0,BCBGBADDEHEBECCCCDGAGEGEAACEHEHGFABAEHECECFCGCECDBACAHADECGCBBFGFEHEFGDGEGCGFGDHDCBCAFGDGDAEFHFCFBEEHEBDDFHHHBAFAHDEDGDBDEDECFCFHFAGCFFAEGDGDADCBBBBCGHHABBBBBDED,False +416,23.0,23.0,29.0,23.0,28.0,15.0,36.0,18.0,HDFEEHAHFECBCGDFDFBAGABBGGADFDGEGECECGDHCECECEDEDACACGEGCGFBCBCACEEDEGGABHEDCHBGGGHGCGCBDBCCCEHEBGBCDDGGHGEFEGBBBDBAFAFAGBFFHHADEGEDBCCCACGCDCGEAHAEADGGGDGDBFBFCGCGBGBGACAHAHGEFDADEHEHAFGHBHDEAEA,False +417,6.0,3.0,6.0,6.0,13.0,9.0,7.0,12.0,HGCCECEAEHGHGCFAFHDDBDEGBGHHEEDAFGFHEHAAADBCHCGFEEEHEHEFEFDFHF,False +418,7.0,7.0,9.0,13.0,10.0,16.0,6.0,11.0,HEFFFEDECCHHBHFDFACACEDHDBDBDBDFCFDEDEBHGEFFAFADAFHGBGCGCFDEAHDFDHGHFHCGEFEFABC,False +419,6.0,2.0,4.0,3.0,3.0,0.0,2.0,0.0,EEBDBAAAACACEGGCCDAD,True +420,20.0,21.0,13.0,17.0,21.0,27.0,25.0,13.0,HAGAGAECCFDBEADDGAGFFDCBFFCABGBEBAGCGBFBGEGEFDCDEBFBEDCAHBHBDFDFBADGFFEGEGEFEFEFHFBBABAHHDGDGBGAGFGFGEEDEDAFAGDHEACACFFGFGFGEDECBFBFHHHGEAFAEAHFBEBGBCHCHGADC,False +421,9.0,14.0,14.0,8.0,6.0,14.0,12.0,12.0,FHFDFDBBBGBEBCBFDGDHFGABCGABBGEAFAHACACHDDFHCBBFHFHFGCHCHGBBHHGCGCACACHCEFEFADDFEFEGGCGCB,False +422,2.0,4.0,4.0,2.0,2.0,3.0,4.0,6.0,HFCFCECBGGGDGBEHFBAHAHBHDHC,False +423,19.0,10.0,8.0,8.0,6.0,9.0,8.0,8.0,DEABABCFEFDAAABFHFAFAFADACCGBABAGHBABABAGHEHCGDGDCDCGEHEGDAABAEHBAGACDFFCFHH,False +424,22.0,16.0,21.0,30.0,13.0,19.0,17.0,12.0,BCBEBDAEAEAHAHGHCBCAAEADGFGDGDCACFCDEGCDHBCADDDDDEABADADADAEGBGBHCGFAFDCDBDFACDBDBCFEHEHAHGFGFGFGECHFHCCGDGACDFDECFDADEBHFFDFDFBFBEHAGCGDFCBGDACBCFDAD,False +425,12.0,15.0,7.0,11.0,10.0,19.0,9.0,9.0,CADACAFHFDDCDBFBDBEBEDEHFABACFFHHGFDFDGDGHAHACCBEFDFGEGEADFFCEGBABAEHHBHBGBEBABGBEFFFFABGFFF,False +426,10.0,14.0,11.0,11.0,11.0,17.0,18.0,9.0,BFBAAEFEHCHGAFEBCFCGCGBGFHFCGGAFAFBFCFHBBFEFEFEBGCECBGBGCDFDBDBDGAGEFEGHGHAADEGCGHDBAEGDDDDCDFGFGABHH,False +427,37.0,20.0,35.0,16.0,24.0,26.0,23.0,17.0,AGAEEHGHGCCCGBGCHCHCHFGGAAAEAEAFHCHCGCACADEEECBABEFEHDFBFEEBBBCEFAFADACAFFCFDHDGBFFACDGDFDBBBCGCBAAAEAECGCDHFBDBCAAGACACAFAGGBEHECECEABFEGDFDHHAAAACHCHGHCHABEGCGFACCECFFBFBABAGFFDAECEDEFFACGCGAGCDFD,False +428,16.0,17.0,31.0,28.0,15.0,17.0,26.0,26.0,FGFCCACBEDEDBCGCGFDCAAECEAAFFGGGGHCHCAGDGDBHBHFHFHFHDHAGGDDADHDHBACGCGEDHBCDFDGDHDCCCBBBBGCCCCFBDDDBCCCHCFEHHGFBFCCAAGGDADGDHEHAGCGCBDBFBFEGAGEGHCFDHHHHEHEBEHDFDGDHAAECCCEDEDGH,False +429,8.0,4.0,6.0,7.0,12.0,5.0,7.0,6.0,AAHAGBFHFCEAEBECGFGFGEEECBCDCAEHEAEDEDHGHBCFDGEGDHDEDAA,False +430,5.0,7.0,8.0,4.0,4.0,3.0,11.0,4.0,HGDCHCBCBFGAGBGBEDHAEAEGFGCGEGAFCGCGDHDBBBCCGA,True +431,8.0,19.0,9.0,16.0,16.0,15.0,11.0,12.0,FABCEHHCGDGDFDFHFAEDGDFDFBBBBFEDEAGBEEEFEGEBEFDDGBBAAAFHFHEEDCDCGEDBDAEHEHBHBHBFGCDCHEDBFBGHGFBFBCBCGCBAHD,False +432,25.0,23.0,17.0,34.0,27.0,19.0,18.0,34.0,GBHHHFEGGFGFGHBABDBDBHGGEBBDEDHHHHAHFHEHFFFGBDDEAAAAADCDHACAFDBDCGCGDDDHAGBDHGHCHABAFEFEFEFDDBDBABGFAFEEDEDEAEBFDFDHAHABEBEDDDFHCEFEAAAECCBABHDADHCBFGDHEHAGBDHHEHEDEAECEDGCEEHDDGHCHCHEDDHBHCHCACBCG,False +433,11.0,10.0,8.0,8.0,5.0,5.0,7.0,5.0,GEEEBADHCHEBEACABDBDAHABABABCDCGCDABFDCACABGGAGHCHFFDDGFGFB,False +434,8.0,2.0,9.0,3.0,9.0,11.0,9.0,7.0,CECFFFHGHBHCFCFBFHDACEEFCGEDEDAAAGCGCEFFAAGGGHFHFHEGEGECAA,False +435,15.0,9.0,12.0,17.0,12.0,13.0,11.0,8.0,FEFHFAFEDEDBCGGFBHACGCFCHADADAFAEAEADHDBDFHEDEDBBGBDADAGAGEGECCHEAACBCDCEGFGFDADGHHFDFCCCBDGEFADB,False +436,9.0,4.0,4.0,2.0,2.0,7.0,7.0,7.0,HEFBABCEFAFABGGAAACFCFGHBHACGFGAGAGHHDHDHF,True +437,13.0,14.0,15.0,27.0,27.0,6.0,29.0,26.0,DDDEHABAHEHAHDCBGDHFCEGBBHBHADDEAGGEGDGDGCCDCDBDBHBHBAAHGGGGACECEGGGECCDGDGEGADADGFHEEDEGACAGHDDDFDFBEHCHGHFHEEEHEHEHEHEGEFDGDGHBCCEDHBCGDHEEBAGHGEGEGEDHBHCD,True +438,22.0,9.0,13.0,21.0,26.0,17.0,18.0,21.0,GAGEHFHCEGEDAFAHAHEDBDFDABAHEDGDBCAEGDDDGGGGAGEHHHGCCFHHBHBHBHAGECAGDGDGDGEHDFAGCEEFEHEAEAEFFCECFFFBDADFDADADAFEEEEAFAEEBABAHEFDGHEHFCDCDCECHCHFEAH,False +439,24.0,19.0,22.0,19.0,24.0,22.0,19.0,24.0,DCDCAAAAABAFGFDFDHGCGCGBDACCCCEHFACHEDAAEABAHABAEFHFCFCFBBHFHEHEGCGDHFECBBBGBEHEAEAHDGDGHCHFBFEFEBEDFAACDHDFBHADCCEHEHDBFGFHDHDGEGADADEDEBECHFGGAGEFCCBCGFBBAGEHFHGHEHEFECBGA,False +440,23.0,14.0,11.0,16.0,9.0,11.0,13.0,16.0,DCDGBGBAAHECEFGFGAGHHEDGBCFDFGHGEEFADAEGFBAAAABFBFDAACCCEDHHHDDAAEBHCHABCHAHAHABEDGFGBGDDDDDDGAAHACACACABFFHBHBHB,False +441,5.0,9.0,7.0,7.0,5.0,6.0,6.0,2.0,CFDBDGCADBDBDGAAEAEBFBCBFGHBEGDHDECECBCGFGFBFAC,False +442,21.0,17.0,17.0,31.0,26.0,21.0,12.0,20.0,AAAGDEAFCHCBEDDBDBDHCAAHBDBDADHFHFHFHFHFDFEADADHHCHDDCFBFACHDEEEDABADAFEFHCACFFFEFBBEHGDGEGFDDCDGEGECCCCCFCHDEEECGCFDEDGBBDBGGHBFAFEDADFDHEHDHAGDGDBAEEEBEDAHAEBEBEAE,False +443,22.0,20.0,27.0,22.0,26.0,31.0,22.0,17.0,EDEAHFDFEBGFEFHGAFAFEDEAHDFBEDACCCBCBAFADAHFCGHGHDCDCGGHBBGACADFEFEFBFBFBHBHAHAGGGEGAGACECECBAEFFDEECDFECECBCEHDFCABHBCGDHBFBFBFAEDCFFHFCFGFDEDEDGFGFGFBCHEGGCEDGCCHDGFGCCCACEDEAEABABADFDH,False +444,25.0,15.0,17.0,18.0,21.0,13.0,21.0,25.0,GCAFBBBBAFGHBACAFHCECHBEDEHHHEDAHABCGDEAAABDBHAHBEGGDGACDBGGGGHGHGCECEFHFCCGBEEEEEDFCGDGDADADCECBFFCAEAEADGDHAHAHEHDHAHEFEHDGFHFHBDDAHAGAGAGAGEFBHECFCACHDH,False +445,4.0,5.0,1.0,1.0,6.0,3.0,0.0,1.0,FEBBABEBEAFHFEAEAEBDC,True +446,3.0,5.0,3.0,4.0,0.0,2.0,5.0,1.0,DBDAGBGCGCGCBBBAGFDHDFA,True +447,27.0,17.0,19.0,29.0,21.0,26.0,19.0,16.0,AAEEEEFDFHEADAGFGFGAGHFABBBBDADAHFDGCHFDFAFGCCBFFHDHDADEBHGCAHAFCCGCHEEADCBFFDFAFACAEECDCDBHBDCCEDEAGABDBDGGGGHFHFHDEAFDCDAAABAGCGFDFEEEBGAGAHBGDGDFDFDHHACCDCEBEAECEFEFDFDBDB,False +448,12.0,3.0,7.0,7.0,6.0,6.0,10.0,15.0,GCACACAFHFHGHDHAHDDEDCFAHACAHGEFHBHBFGDEHEAAAGAGCDAEGEBHDGFGHHCHGH,False +449,27.0,20.0,31.0,20.0,16.0,31.0,25.0,16.0,CCFCACAHBDGCGCBCGCDCBBEBAGFFFCFCDCBHBEFDFDHGGDCFEDBDFDCDCFFDBAECHADBCHCHCAAAAFAFADDGFCECGCGDDEHGHFFEHGHGFGFGAEFBFEFDBHAFDGGCFAFHHHBHEAGAEAEABGHFAFACACBCACGBBAGACAFFGFGFDBCBCGEEEECFADGBGA,False +450,2.0,7.0,4.0,2.0,6.0,1.0,3.0,3.0,DGCGCBDBHCECHBEGEABFBHEAEBEB,True +451,8.0,7.0,6.0,1.0,2.0,4.0,4.0,3.0,FGFHEABCCCDBABAHCHEAGCGCBAAAABBBFGF,True +452,12.0,16.0,17.0,11.0,29.0,15.0,19.0,16.0,EGDGEGHCFCFDDBECFHFHGEBEBEBEBDBAHAHADCEEEEEEEBECCBBBGDCDCFGHHEACAGBGHFEGEAECFDEGFHCEDFDFDCBHEAEAEFBGCGBAHFHGGEEBFGFGEHAGAGAFCBHHHCCECEG,False +453,4.0,3.0,6.0,2.0,6.0,8.0,4.0,3.0,CCFCEEHCHBDEFAFAFHGDFEGEFBFBFCECGAGA,False +454,17.0,13.0,25.0,22.0,19.0,16.0,28.0,27.0,AGAHHCDEDGGGDHHFEEGEHHCGGHGABCDCDAAFCFCGAGCFFFHEEEHEBGBCFHDAEEBDCDCGCGCBHBFCFHDHGBGDHCHFHBHDHBEAFCCDEDAGCGCDCFFHGHGHGAGADACAEABFCECECEBEHAGAHHDGDGHGHGFDFDEBCHDDCDGBGEA,False +455,3.0,8.0,5.0,6.0,3.0,3.0,1.0,4.0,ADHHHDFFACBCBCHCBDDGDBDBEBEAEFCBB,True +456,17.0,25.0,25.0,21.0,21.0,26.0,24.0,21.0,GEGBFBFBFBGAHAFACDEDCCHFFGBGAACFCHGFCFGHDAEFEFGFGHEBEBDAFGFAFCCBABEHCGFEDEDGBGBFBEHEGGCDCDCBGHDCCCDFAGBHBDEDHCHCHEHCBCDDDDFBEEEEGGBFCFCHAHACGFBBHDHBABGBGDGDFAFAECECEFDFDBGCHBAAHHEH,False +457,12.0,10.0,8.0,8.0,4.0,11.0,8.0,8.0,DBDFDFCCCHBEGFBHEFACBDBGHGBFAFGHAHAHGDDDCCACGCEHGFGFBFBABABDHFAAAEAFA,False +458,20.0,11.0,18.0,22.0,26.0,28.0,20.0,28.0,BFGHCHEAEAFFFFGABCFGFECECECECHCHGHDHAHEEEFHAAFBCGHDHDHCABGHCFDGHGACFDDDBCGDDFGGGGEEABGFAFEHAFEHAFAEAEABAGFDFEEHEFECDADHDHBHEHDHCHFHDHFHGDDDDEDEFEFGDCHCECEFHFAGBFFEFCADGBGBHA,False +459,18.0,25.0,19.0,16.0,13.0,17.0,21.0,14.0,CACACDEDBCBHAAGHBHBCEDEDAGGHDFDEDCHFHECFBFACAHAGGGGGAGDFBABFFGFBHBHBGBHBACABHBGCGBGEFADCDCHAHDHDBACABBBGEGEFCFBGBEFDFABABFCEGECDCBCGDBEGFFCFDGE,False +460,21.0,19.0,19.0,30.0,29.0,19.0,23.0,32.0,FDEDECCDEEHFDFEFEFHAHDCGCGCFDDDCGAGAECDHBEBAHGCGEFEDHDHDGDBHBADCDCHHFECHBGBEHADBDHGHGHGHDHFBGAGHBFBAECGGFEFEFDGDCDAEGEBACHGGDDADFHAEABBGBABDFDFABEDAHBHAHAEDEAEHEHCFCHEHEHBHBHGGCACAHEEEEFDFCGDH,False +461,9.0,19.0,19.0,25.0,19.0,17.0,20.0,16.0,BEGCGDAEHEDBDCEHECACAEAEAFCEGHGHFHGHCEDDDHDEGGFEHEFDFGFDBDBDGDEDCFCFHECBDHACCBCBFGDGCHBHDDBGBGFCBCDDGDACFGGGGFGBEBEGHDBDFCFBFDFDBHHAHAEDFBCBEBEC,False +462,9.0,14.0,11.0,15.0,9.0,10.0,15.0,17.0,CHCHCGCBEBDHEHFBGDGDGDGDBDGEGCHHBDBDACFCHGFEAHFFDCGAGBFHEDEHHAHAEBHBHGAGBFBDBCFCBCBADAGEGHHEFDFDGDAH,False +463,15.0,16.0,16.0,16.0,13.0,12.0,15.0,14.0,EDEGEDHBHDHDACHCBCAHADGDGAEEHFGFGFAEGEDECGGAFAFDBCHCGCEBABABABDEACHCBABAFGEACFDBBCBEGEGCDCDADBDFHHHHHBDCDGBFFGFHCBCFG,False +464,20.0,13.0,10.0,7.0,14.0,12.0,14.0,15.0,HHHBDFFCHCGCGAGDFDGEBFBABAFAFHGHBAGEGEHBACFCEDBACCCABADAGBGAGEEAAFAFACGCFAHEHEDEBAGEHEHEGAGAEFHHHHABEBDBF,False +465,32.0,28.0,23.0,18.0,15.0,22.0,28.0,21.0,CAHHBFBGCACEGFGAAABABAGGCGCGEAAGCGEEDBDGDCDHDBBABAFABAEDBGCEDBDBAHABFHEDEDBFFGAGHHEGAGHEECDCFBHCGBDBDBFGFDFCFAAACACFGHGAGDCFGAGFFBHCHCEABHBFBFHFAFHFEFBABGBGBGHHHAHAGEFCCHBHCAGBCDCECADADAG,False +466,14.0,31.0,26.0,20.0,17.0,27.0,15.0,13.0,BBBBBCGFEFDFDFCCDCHHDAFADACCEAGGCGCACFFEGECEFECCACGEBAGDGHBABDBHBHFCBHFCFCAHDCDHBGFEEDEDFAFHHGBBFAFCCCFAFDFEBBABACHHBDBDBFBCCFFFFFFDBBBBBEBECEGEGDGDGEGCHEBCDFBBBDD,False +467,15.0,12.0,15.0,11.0,17.0,18.0,18.0,13.0,HAGECCBCFHEGGGGBGBDBGBAFACCFCFCBDFAAAAACEEEFECDFDCDCDHBGGGFGDABAGAFFEAEFHBEDEDEFBAHGCGCHFGFGFHHDHECEAEGFAFHHEHEBBGEHFDC,False +468,22.0,12.0,14.0,17.0,19.0,18.0,16.0,15.0,DADADADAHAGABAEHFGFGEGBHBGADHDGGACHEHCHGEFFBCGCAFGDGAEHEAAFCFGAHAHEDDFDCHFEFEDEBECABEFGBGAGCCECFCBBBBHAEBECCADEDHHHEDEDEDFFFFGDAAAFCF,False +469,18.0,26.0,29.0,20.0,29.0,19.0,16.0,15.0,CGCGCHCFCGHHCHCHCHCFAEAFFECEBFGDHDCECECHCFFDBDEDBGGEGAGEHBBCCACABEEEAEBEBACECGADBBHBDBEFEFEFCDDGCCBAHHFCBHBADAGFDBEFEFEAECBFFHABDBAEDECECEDBFBDBDBDACGEGEBADCDGBGDGACFEFBAEH,False +470,6.0,1.0,5.0,5.0,3.0,4.0,4.0,6.0,CBCAGGHDHDHDHFHFEECACADHCAFAFGEADG,False +471,8.0,12.0,3.0,4.0,7.0,8.0,8.0,2.0,GAAFBEGEFDAGEGEFEHGBCFFFFGBBBEBABABDBDBEBDHGCABACAGF,True +472,9.0,4.0,9.0,5.0,3.0,6.0,1.0,7.0,HACGCABHCEAFHBHDAAACFCBEDEDADAHFHFCFAFBCDCHC,True +473,2.0,1.0,5.0,2.0,7.0,3.0,2.0,10.0,CCHCDDGFHAEBEHHFACHHFHEHEHEHECEG,True +474,8.0,7.0,5.0,9.0,9.0,4.0,1.0,12.0,BCDHBCBADCDHHAHDHAHEDEDBHEEDHCHAFAHAHCEGDADEFEFEFABHBEB,True +475,11.0,5.0,2.0,1.0,3.0,2.0,5.0,4.0,AACDCFHAGAGAEBGBHBFEAGBGAAAHAHABE,True +476,25.0,30.0,25.0,21.0,26.0,22.0,25.0,24.0,HGHEDBDBCHEHEDEDEDEDCAHDCGCFDFGEGDGAGAGHGDGDCAAHABAFACBCBCEDEAEDEAGDFEBEBEHGHFHFCBBFGHGFEFBBBFHGBCFCEBABADHBCACGFHFACACDFABHEAEHHDGACHFBFBHBHBABGGDBABGFEFBHGHAHEBGBGCFBEBECGCACEFAGECACFDFEAECCBGHCDD,False +477,15.0,14.0,22.0,19.0,17.0,22.0,25.0,22.0,DFGGGFHHCHEHBGDEEBFBAAHGFGFGACCCGHFHBHCDEEFEFBFAFBFCGCEDEHEHEBFAFAFAFGCGCGDBCBFFCHCDDDEAEAGDEDECGDGABBHDHDFDFDGCGAHEHFHCHAACDDBHHACBGBGAGFFHCCGHHCCGDGDGCGEE,False +478,14.0,12.0,9.0,13.0,13.0,17.0,7.0,13.0,AFAFBFBDAAADFFBFBEHGFEFHAHFGDDFDHAHADABFBFHEHECCACGFBDBGAEHCDCHGHGEAECECEFECADFDBGBHBHEHDDFEFDBEAC,False +479,29.0,20.0,16.0,24.0,27.0,18.0,17.0,26.0,GEHHHAHEGBGCHCBCFGDGBFDHCCBCHFHAEFEGGDHDACEDDDCDFDFDHBAADHFHBEFEHCHCDFAFABAEGBHBABABAEHEAEAEDEAFHEDAGEBEFGCEDEFEDHBFFDFAHHDBDGDHEAEGCBDEDBAGAGAGAEAHACACAEAEBHAHGFGEBEADADBHBHFCC,False +480,11.0,14.0,7.0,9.0,18.0,15.0,6.0,9.0,FAFEGDGBBEFEDEFEFABAGEGEFFFBBCBEDABEGAAAFHFDEHHFBFDFAFCDCDEGHHCHBABCBEHEHEBEBEDEHABEFACDC,False +481,8.0,4.0,7.0,16.0,11.0,8.0,9.0,4.0,EEADADFDEAFBFGEGFGDGCHDDCDEBEGEGCFCHDAGCGDGAECFCEDDFDEABABADDDDEHFH,False +482,11.0,7.0,25.0,5.0,16.0,24.0,10.0,11.0,EAEAEACFCBCEFEGAGAGCCFFEFGBCFFHFCFAHACFCEEHCCFDFEEHBHFHAGFFEFEBDAGCGFAFEFEHECGCGCFCFHFHCCCBCDDBCCCCFDFHAECBHG,True +483,24.0,31.0,31.0,29.0,20.0,23.0,19.0,21.0,HAHEECBBBBGBECEFBFHHCHFHDBGBHEGEADAEAEBBFBCECFCACABHCHCEBFDFCFCFBFHHHEGCDCDCDHDCECGABADDDBAGAGAHEDEBBDGCBCFAFABAHCBCFHGHBDEDGBGEHCDCFCFCAHFBCDCDGDHABGFEBDBDBDGAFAGAFDDCEFABAFDDGAFEFDGCBABHCGDGDCDCAE,False +484,10.0,14.0,9.0,7.0,6.0,9.0,6.0,9.0,HCACBFBFCFCFHAHADACABDCHGHGCBFDHCBGBABFBDBFBEEHADADHBBEBADAGECEFHBGEGF,False +485,10.0,4.0,11.0,5.0,13.0,7.0,15.0,10.0,AEAEHCHCGCGCBEGEGFGBGAGFGEHAFGCHDECCAHADDFDFHFHEGEGACCBHDHAEGEGCGHBEEEGAFAC,False +486,10.0,4.0,4.0,3.0,10.0,7.0,9.0,8.0,HGHCFDHAFAECEFHFHEGECHDDACABAEEEGGAEAGAGAGAHFGFEHEFGBBB,True +487,5.0,6.0,9.0,7.0,10.0,8.0,5.0,12.0,FCFCFHFAFAFGEDCBEHHGGEHEHAGBHCHFEAEDEDBHADCBCDHDHDFBEBCCHCGEHE,False +488,11.0,11.0,11.0,8.0,15.0,8.0,13.0,12.0,CBABEBFHFGEGHCDCAGDGEABBCGGBBHEFBBABGBADEHCHCEAEAEGEFFFCGCEHDHDHECDCAFAGAGAGEHEGFDHCHEHED,False +489,22.0,25.0,26.0,26.0,18.0,25.0,28.0,23.0,BEBEBEBFFHDHDHCHDHCCGCFAGCHCHCDCGCABABAFCHEHBCBCDCGCEHAHAEGGABFDHEBECGCHCHFDADAHHEGFBHAHFDGDCCCHFFGGGGBFAFABGFEFAGGFGDBAHFEGEGEDBBEDDBHBDFDFGGCEFGFBFHGADADHCEGEGDGDFDBBCBCDGBADABAFCFAFADDDBCGAE,False +490,19.0,24.0,22.0,16.0,30.0,19.0,23.0,31.0,FGGAFEFECGHHEGEHEDEFEHAGFBFBFHAEAHAEAEACDEBBHCECACEGBBFBDBCHDHGCFEHHAHAHBEBECGGDGCHBHGFGBDFCGHGHDHBHBACACHBEAABDHEHDHFFBFHFHEBCDEDEDFDGEGAGADBCHFHABDBDCFAEAEBEBECGCGEHHCCBCHCEGEGHFCGEG,False +491,16.0,23.0,19.0,29.0,31.0,20.0,28.0,25.0,DHDBCECECAGFGBBEEEECEDEGHCDGGAFDFGFGCGCEHGHGEDFGCDFGFDDDCDEFEABDEDEBEBHBHBGGHBDBHAFABDGHCECGAEAEAGABHDHDHDHBBBGEHEFEDHBEEEGGCDEFGHGHAHAFCFGFEDCFEABHFHEBEBDHDHACBCFGAGFGHEHBGBCHFGDDADCDADFDECB,False +492,2.0,8.0,8.0,4.0,4.0,4.0,9.0,3.0,GEGFACBGAGECCHCHCBFDGHCCGCGBDBDBEBEFDFBGBG,True +493,21.0,13.0,20.0,26.0,11.0,13.0,10.0,15.0,AACGHHEEDBDBDCDCDBEBFBFEGDCEADDDFAFAEAHHHFAFADEDCHCBCAAGACDDDDDBCAGDCDBEHGHGFGABDHDHCCCCHADAEAEDHDAACAFAFBFEDGBHCCADHBGBDFCFCHCFG,False +494,4.0,3.0,5.0,3.0,3.0,7.0,4.0,3.0,AHFEBAHCHGFGFEFDADBFFCFCGCGCBEAD,False +495,0.0,4.0,1.0,1.0,4.0,0.0,2.0,1.0,BDEEBEGEGHBCB,True +496,6.0,16.0,13.0,12.0,12.0,13.0,12.0,10.0,DHFEEBAFCHCHCEFHABBCBCFGECECEGEBDCDCBBBBFAFEBEGGCGAGFHEDGBGEGCHEBDBHBHCGBHAGDFDFDFDFDHCADFDFGB,False +497,19.0,9.0,12.0,22.0,14.0,24.0,20.0,18.0,DEDAHEBAAGDBHHGABAGCHCDCACFCGCEEACBFAFAGEDDDHHHCHCGFGHBAGAFAHDDDDDGDFDFHFEEDEHFHEBFDFHBAGHGHFHFEDEDFDFDCGBFACAGAFHFEABGEGFGFGFECADAGGDGFFF,False +498,8.0,3.0,6.0,14.0,8.0,17.0,6.0,15.0,GFFDFEGGBEBHAEDGFAFEFDDDAFHCHCDCDGFHAHFHFGDHCEFHCHCFDHDHAFDFEFAFABAEHFHDHDEDH,True +499,0.0,6.0,1.0,2.0,2.0,3.0,3.0,4.0,EDECHDBGBGBHBHFGFBHBF,True +500,9.0,11.0,8.0,10.0,19.0,12.0,9.0,5.0,GCFDBACGFBFAAAAGBFAEGFGCGHEAGHDFFCEDEDEDEDECHBEGDDEAEFDFAFEBEHEHEDEBEBEBCBCBFFEGBCE,False +501,8.0,14.0,12.0,11.0,8.0,12.0,9.0,4.0,DBDBEBDBDFDAGCGFBCBCFFGCDCDEDBBBECECFBFECABDDAFAFAGEFBHAGAFCHCDCGHGHBFBEGEFCAG,False +502,5.0,5.0,5.0,5.0,9.0,6.0,4.0,8.0,FEFEBHHHAHABEBDDFDHDCAFFECEAHCBCEAEBHGHGCGFDEGE,False +503,12.0,12.0,13.0,25.0,16.0,10.0,18.0,21.0,GBGBDECCCFHHBACGDGDGDADCGCBBHDHDHDBDFDFDHEHGCEDEGEFAFHBEFFGCEHFFDDHDHGHGDAACAGBDHGHEDEDGAHCGDGDACEGAHAHDHEHEBEBCBFBEHEADDGDCAHE,False +504,10.0,15.0,9.0,13.0,14.0,7.0,8.0,9.0,CBEEFBBGBGBDBABADFBAAHEBEDEDGFCEBDBHAHBCBCBGGFDFCAGAFDGDHDHGEBEHFHECECEAHCDDEHEAEADCD,False +505,18.0,16.0,17.0,23.0,12.0,18.0,20.0,12.0,FGFABEFDHDHFHGDBDBGBGCACDDDHAHBHFFFBGCGEAEAGABHBGDGCECEDHFAGBDEAAHCEGHDEDEDFGHDDDDEFFAFGDGCFCFDFDACFCEAABGBABCBCFHGGBGEGAACCCCFCGBADADBD,False +506,22.0,16.0,25.0,22.0,25.0,11.0,27.0,18.0,AGCDCDHDBGCGAGDDCDGBGDCBCGFGHCECGHGAEFEDEAEGEFHGBCBCAAAAGGDGEHEAEDEDEBCBGFCFGDDEDECFDHDBEAEDEHGHCCCCABAFABCBAHCHGHCCDCEFAGEHAGAGHEBCHEGBHBHDHFEEEACACDEDEHGGGFBFBGDAAA,False +507,13.0,17.0,22.0,10.0,17.0,14.0,17.0,13.0,GGGCBBBEBHAEAGHDCGCDHFEAEABHCHGFGHGCCFFBCAAHEHEDCGCGCDADEHAHFDFAFCHCFCBDEEAEFHAHFCFABBDBDEGECEBGBGCGCDEEBEBFBEACBCGCGBGCFCF,False +508,17.0,21.0,24.0,12.0,17.0,20.0,19.0,17.0,ECHCHCHCGCFBGAGEBEBEBDCCFHFGCDFFHHBGBGDDDGFCFCGDGFAACACGFHDHGAAHAEBEGCCCFGFADADHBBBBABEBEBCGCHDHBGEHCACECEDDCFFAFEBACAEHEHBGBHEFAFBGHGFBCBEAEAGFFCF,False +509,4.0,0.0,5.0,5.0,1.0,0.0,3.0,4.0,GHDCDCDCDCAEHGCDHHAAAG,True +510,10.0,11.0,3.0,4.0,7.0,2.0,18.0,3.0,HAGGGGAFAGCGEGBGAEBGGEBEBDCEGDBDADEBEGAGAGBBBCGGBGAGHBHAFA,True +511,2.0,4.0,2.0,2.0,1.0,2.0,3.0,1.0,DEDFHGABBBBFAGCGC,False +512,2.0,4.0,2.0,1.0,1.0,1.0,0.0,1.0,HDBABCBCBFEA,True +513,4.0,5.0,8.0,7.0,6.0,8.0,11.0,4.0,GGHGHGDBCECECEGFHDABADEGGCGCECBFEGACFFFFBFCFHBAGGDDDD,False +514,20.0,26.0,19.0,15.0,24.0,22.0,24.0,21.0,FGFEFEFBHGHBEDHHHHEDCDEHEHCBFHGAFAFBFDCACAGGGGGGGHBBABFBFBCHGGBACGCGDFEEEEAEFFFFDECECFCBCBEAHCBADEDAGFDEDBBEBEHACAFAFABHEEDCFGHDAABEBEDGGHGHGDDFEFAHAHBGCGBGCCCABBHBAGCBHBE,False +515,22.0,23.0,26.0,33.0,16.0,30.0,25.0,23.0,GGGGCBEHCBCFEGGFADHDHCGDACCDBDGFCFHBHGAABFBAHAHDGDBDADACGCFDFGFDDHBGGGEBEBEFGFHBEFABEGCGCGHAHFHFHDBDBDCDCDCHFFFHFDFAGEGBABFEDBDCECBCDDHDBGECADEDEFFFFAFDFDECGHDFDFBCGFECHHAHAHGCBCDADAEAFCFCDHDABAHABC,False +516,17.0,13.0,13.0,12.0,15.0,20.0,10.0,20.0,FDFAGABHFHCEEAFCEGGBEBCBCBEBDHFACGHGCACACAHFHDBGFGDAEAEABFDEDHDFAFEBDHHHFHFHFHAHAHAEAFADCCFBBCEHFFFDGDGBEHHHHGCBEFEAEDFC,False +517,26.0,21.0,23.0,17.0,23.0,30.0,24.0,22.0,ABAEAEAEBGGGGGAECECEDFCEBAGHFHAEADCCGGGAGBEBEBEDCDFAFHFHGCCBHAFAFAFHFGBCDDFACGFGHDEEGEFEGBGFGADFCFCFCBAEABCDHHHCHFHFHBHAEFFFCFBECCCFFDFDBCHCADAFHBABDFDBBAHGGEAEHCGEGCDAGAHDGDFHFHFEBABEBH,False +518,7.0,13.0,9.0,12.0,7.0,6.0,7.0,5.0,CGCECBHDEBGBAFCDBDBDACEBDDGDGEGEFAFAFAHCFEHEDBCBDBDCDBBBDCHFBAGAGH,False +519,15.0,23.0,14.0,11.0,17.0,17.0,14.0,16.0,AFGEDCHBBBBBBGGECEFFBACACBCGCBHFAAABCCEEDDDHBBFBFBGEHEFDAEAFFFEHAGABAFHFBDBHHHBEBEACGCGCACDCHEEBEGGDGHGHGDDDCBGAEBEFEFAFHHHFHFB,False +520,18.0,12.0,17.0,12.0,18.0,12.0,16.0,36.0,EGEHCHDHDGDGCADAHAHFCEEBACEEEADAHHBCBEHEHEBAHCEEGCFEFAFABHBHGHDCGCGDHDHFHDHDHAHCHABCGCFBHHAHFHFHFCEHEAAHHBHGEAHHBFCCGBGFHAEAEGCHBHGDGDGAGFHHC,False +521,4.0,11.0,9.0,6.0,9.0,15.0,6.0,12.0,FFFCCHBHCFCBCBFDDGDGBFAGCFEFCHCGFBBBHCHDEDEAEBHBHGAEAFFBEGEHEHEHBHFFFFHD,False +522,17.0,10.0,12.0,14.0,22.0,13.0,17.0,18.0,EEEEDEABAGFEFEHGHBDAAABDBDAEHHAHGHGHDHAEABHHHHHBCGCFCFCDBAGACEEGCGAADGDHAFCFCEBEFDFEEACGHBEFEFEFEDCGFGHGEGDBAEGEDCHAHGDFDGC,False +523,0.0,4.0,3.0,2.0,1.0,0.0,4.0,2.0,DDEBCHCGBGCGBGBH,True +524,25.0,20.0,21.0,11.0,21.0,16.0,21.0,28.0,FGHGHEHEHBHFHFBFBDBEGDCHCGAEAFCDEAAACHEHEHBFFFFAAHCGGHGBGBHCHCDCGAGAGBHHHFDCDAEABBBCECBGGFACHCECEAFAGHFAEHGGEDEDEBHHACCCACBCHDGDGAAABAGFEBHAGBGCFEEDEAEAFBECHHAHBHB,False +525,5.0,5.0,3.0,6.0,5.0,16.0,3.0,8.0,DHFHFEFEADAGEGECBDFCBDDFHCHFAAAFEHHFBBBGDFFFFFFFHFH,True +526,1.0,0.0,1.0,1.0,2.0,0.0,4.0,6.0,HGHCHEHEGGHGDAH,True +527,14.0,26.0,15.0,11.0,16.0,18.0,25.0,17.0,BHFABADGFABCDGGECEBEFEDBDHGFCFDBDBCEFBFHAGBFEFGFHFHCHBHEHFHFHCHCEDBDBEGHGHGCBCBGDEEFCFBGBGBGBCBDBGAEAGBGAGECEAFGGGHGCCAFGGEAEDBHAGABAFAGHHCBBB,False +528,26.0,33.0,22.0,21.0,21.0,26.0,21.0,23.0,HDBFBDGDGHHEBFFCECFBABGGEBEGGAHEHABGBCCCABDFEFGFADACCGABDBFBADADBDAHAHBEGHFHBEGEBCBCBHAHABADCHBGCDEDEDHGGGGGCDBFFFFFAEECHCHCFEBEAADFBFBABDBGEEHEGEFCFCFEAEADCGFADHHFBDBAHAHACABABFBFCFHBHBHCDFGCD,False +529,19.0,28.0,16.0,26.0,16.0,17.0,19.0,17.0,ABADGCGBHDFFFGFGDGFBDGGFAFCGGFHHAAFFFEAAHAHCBCBABADDFFFABDBDBHGDACHCHGBBBBBGEDADAGCBEBHHEDBCBCBDEEGADABABADADCCBCBDFDFCBCHFEEEDEHHHGHBHDEECHGDGDBEEEDEDGDGCBBD,False +530,10.0,4.0,8.0,6.0,5.0,11.0,7.0,6.0,FFBFCDCGAGFEDCDBEGEGFCFCFCBAFDBHAHAHAGACAHAHEGDFCFADEGAFH,False +531,13.0,7.0,11.0,9.0,7.0,13.0,13.0,17.0,GCABEBFBAHHHGHGAAHCHBEBCDAFHFHBCDCDCDFGEGCHAHEHCHDFFFGFGCGAAAHGGGHFCECHHHGAAEADFBFDFDEDAGF,False +532,6.0,4.0,4.0,4.0,4.0,11.0,3.0,7.0,ABCDHFHFECEDADFGHAFCFCFBFBGADEHGBFHEHFHFAFA,False +533,14.0,30.0,24.0,27.0,22.0,23.0,21.0,29.0,CEBEDGCHDGAAABHEHGCGBFBEGDDDCDCHHDEGFHCEFBGBCCFBAEAGABEDFDCDCDHDHGFGHGCGDDFBBBBBDFDADCDGBFEFDBCFCFBDHDGFACAGFDFDEAECFBBHBHCACAHFDEHEHBDBGBHBFBEDCFEEHBHBCBCBHEFEFCHCHEAFHBHBHEHFGCAEGHGHGHGHED,False +534,7.0,14.0,11.0,10.0,12.0,6.0,11.0,7.0,ABADCBEGAGABDBHCECDBEHGCBCBCGCFCFHFHFBBCBGEGHGDGEGEDDDCDEDABAHCFEEAEFEBBGDEHBG,False +535,1.0,8.0,7.0,5.0,5.0,7.0,1.0,7.0,BHBGFHEDDFCBBBBHHHFEFHFCFCACBDBDEHEFECCCD,True +536,5.0,4.0,11.0,11.0,13.0,6.0,6.0,8.0,CDDDEBHHGHDFGCCACEDEDECEGEACACHEBFFEFEFGFGDGDHAEEEABCBHEDCDCHHDC,True +537,28.0,21.0,11.0,18.0,13.0,11.0,21.0,19.0,HGAGAGFDDHGEBDCGAAHGHEDBDFDEGAGHDECCAAAADDGBBCBHBHBHGCGCBBBFBFGABAGCHBGAFHFAACAGDFEFEGGBFHAADADFDADBBBDAEAFHGHEHEHAHAHAHAGEGDCDCHBABABECDGAEBE,False +538,3.0,5.0,4.0,4.0,5.0,2.0,1.0,6.0,HCHGHAFBEBEAEACDCHBEBFCEHBHDDD,False +539,6.0,6.0,7.0,4.0,9.0,4.0,6.0,1.0,CCAGDGDGEFBCACBCGDDBFEFCFEABABCEEEABAEGEGEH,False +540,4.0,1.0,2.0,4.0,0.0,6.0,5.0,0.0,FDDGAGFGCGAGAFFFBCDADF,True +541,9.0,14.0,13.0,6.0,8.0,6.0,10.0,5.0,CBCGEGEFEHAGEDBGEGAGHDCBCGAGAGHDFGAACBBDBDFFCFHFDACACBBEBECCCCHEACBBBBB,False +542,16.0,16.0,8.0,16.0,13.0,11.0,10.0,17.0,EAHAGFDCGCGDEHCHBAAADHDHEHEFBGBABFDAAADBDADADHDGEGCGHGBFAFEBBBBHFDFDEBEFAHEBDGFHCHCHGDFABABDHHHAEBEHEDEBCCF,False +543,21.0,26.0,17.0,27.0,29.0,23.0,26.0,18.0,GDEHHBFFAHDHDCBHBGEDBDGAGDHCEEEBFFACBBEDGFCFBEBECAFDDHBHDEFEFEFEGGCGBHFFCFEHBHEFBHBADAEAGAFBFGEGEGCGDEDEGCGCBDFDFDADABCFEBBBDBGGGFGCDCDCACFEDBGEGEGHABGEGEAAAACCHEBEDEHBABFGFHHEHADGDADADAD,False +544,22.0,22.0,21.0,19.0,23.0,23.0,21.0,20.0,CGDGDBCFDADCCGDBDHAHCHCEDFFGGGECECEAFAHCFDDEDAGCGCBDEDEAEHCHCEEECEFBFHDHGHGEGCHFEAEAEFFCFEDEABHHHGFBAGAGBDEGECECECHBHAHGBBFBGBDFDGAAFAFGBBCBGBFHEHCBDFFFHFBAAHBFBAAAFAGABDB,False +545,23.0,25.0,25.0,15.0,25.0,17.0,21.0,33.0,GAGAGEEHHHFHFHFHEHDCFHABBHBHBEBHFGBCCACACACGHBADHBECECEBABECCHCFEGHDCEBGGEBEBEFHHADCDCDFDHBHCAEEHEHFHGHGHFADCGFHCACACACBCEGDFHCABGDGEGFCDHGHAAAHBHBHBEBHBHAGABEEGEDEGFBFCGEDAGADDBBEAFCF,False +546,3.0,2.0,2.0,4.0,0.0,4.0,0.0,0.0,ADADAFCFDBBFCFD,True +547,13.0,21.0,3.0,11.0,13.0,5.0,12.0,11.0,GHBADHBHBGBEHDHEEFGHDHGFEDDDEGEAEDFAAGBBCBAGAGAEDEHBHBABABAGADBEBECEAEBBBBGBHBDFGCADBFBHG,False +548,25.0,24.0,22.0,17.0,28.0,18.0,39.0,21.0,CDCABDBHBGBGBGBCECBABGBGAHAHBFEEAEBGAGEHFACACDEGEGECHAEGEHFHFABEGHFHAHGHCDCEBEGDBFAFHGEGBGAGDBDBDBEFECHFHEBFGEGEGECAFABEBGBGHGFGEGCCCCHGFACGBHAHAECFGAEDHGHGDDDEAFADGDGDCAEGGACFBFAGEGACCEHDCDGGFG,False +549,3.0,2.0,4.0,4.0,5.0,8.0,5.0,2.0,HFEFGDGFBFDFEEEFEFGBGCCACDCAGAHFD,False +550,1.0,3.0,4.0,3.0,7.0,2.0,2.0,6.0,ECEBHBHGHBECEFDHAHECEDEDGCHF,True +551,16.0,22.0,21.0,26.0,28.0,20.0,19.0,21.0,EGEDEBEAEADDDCFCABGEFFHDBECHBBBBAHAFFCCDDDDDDHGHEFAAAAAGGBGFGBGCCHEHFBFHHDCDFFBFDGEGFCABBEBEBECDGFEECACDDBCFEDEHHDBDFHFHCHCEGGGEGEADCDCEGEFFHHGCCBCBDBEBEAEAEAGDFHCDGDHBHEHEH,False +552,4.0,5.0,6.0,11.0,3.0,11.0,11.0,5.0,GCCDFHFBDDEDECGCGDGHABDDGGGDHAHAFGFGEGFGFABDFHFCFDBDBFFC,True +553,5.0,13.0,12.0,7.0,6.0,1.0,8.0,8.0,BGDACECGDGCCCBCHCGCDBHHGBEAEAEFBCBEBDGCGDGCBABABEDCHHHHHBBDB,True +554,21.0,23.0,19.0,23.0,24.0,21.0,32.0,21.0,FAGAHAHFHGHBEEFGADABCBGBGFAHEDEFGFBHCECEHEHDGDEAAHGGGEGFFDFBCHGAGHCDGGGABDGDADHFEBHBHGGCACBCBCBGBCFADADGDEDACBGHEFDFHFHFBDDDDBHBGGGCDEFEGEGECHCBCBEBEBEFFAGBBFACECECDAEFECGAGEFDGGAADHDH,False +555,11.0,14.0,17.0,9.0,22.0,14.0,9.0,22.0,CGEEDCDADADBDBFFFHCAAEHHHEHEHAHEFFCFBGHHHFHCHDHEBGFGFBEECFCEEECGCGHEEEEADHBHAABCCACFCEDHCHCHBHBDBECGCEFFGFABBEBEGHAHBE,False +556,4.0,3.0,4.0,4.0,4.0,1.0,0.0,1.0,BABHECAAFBDCDEDEDECAC,True +557,11.0,15.0,15.0,16.0,14.0,18.0,14.0,14.0,BCBCBGDGCGEAHHEHGAFFCFHFCGAGACEBEBEBAFGCCDGBCEFDFDAEADDFDCEBFBFBEHDHEHEGEGBGHFHDDDDCCBGBCBHAHDEFFFGGCHBEAAAHFFDFDFDHC,False +558,5.0,2.0,3.0,3.0,1.0,2.0,3.0,2.0,DGDGACBFHFHAEACABACDG,False +559,29.0,26.0,17.0,17.0,20.0,26.0,24.0,23.0,DADCDFFHFAFACAFBDBACAGABFGFBHCHCFFEFEFGHGCBCAEGGGDBDBABFHFAEADDDEDEHAAGGDBHGFFFFCGAHBBGBGECEGEGEGEBEDCFFDFCCEAAFDHAEBFBFAHAGFHCCGBGBGBGAGABEDADHEBEHHAEFHAHABCBCHAEAFAEBHGHBBBAGDHHHHC,False +560,7.0,9.0,14.0,11.0,8.0,12.0,13.0,5.0,FCDCEFEFGHDAABACGCGCGDEBAHHBCCFCFGEGDBDBDBAFECDFDFEGGCAFABCFGFGEGHCDEDGDGFCBCBH,False +561,16.0,32.0,21.0,19.0,21.0,20.0,22.0,22.0,AFBGBGHGEDFAACDCDCEFEBCFCGHGHFDABABAHCCEAHBEDEDBDCCHGHEBEBEBCDEFGDGFBFEDHDHDBBBFFEGBGHEDGDFBGBACDGEBEBHBHCCGHGHGDGDGHGHBCAFHGHGFABAFAHAFCBCBFAHDHBBCBGFEBABCBCFCFEEBCFEDEAHBE,False +562,18.0,21.0,6.0,6.0,14.0,3.0,15.0,20.0,DGAAHCHBAFHBHBGCAEAEAHAEAHHHBCBGGEBDFAHAEAEBGAGAHDEGHAHBEAEGHGHBABHBHEDCGHGBEDGBGEGBGBABDBAEEHFHBCBCBHB,True +563,19.0,18.0,15.0,19.0,14.0,16.0,17.0,24.0,FAFAFABBHDCDCDFDCAABFCEDBBECDCDFFAGADBCHGGFHDHGHEECEGDADABEHHHHCHDHDFAHGFGFBDBCBFHAGABDBGBFDGGFCFCBHBHFHEHEHEGAGAHAGABAGABEECDCHHEBEDEHAGCGHDH,False +564,3.0,3.0,2.0,1.0,0.0,0.0,0.0,2.0,BABCBDAHCHA,True +565,8.0,12.0,12.0,9.0,13.0,13.0,12.0,17.0,BFBFEEHBFAFGGGCHDHDHGCDCGEHAHEEBBAEFGCGCHCFCFDBBBHCEBEHEHFGAGFFHFHABDGDFDFBHAHDHEAABCEGEGEDCHCHC,False +566,24.0,19.0,7.0,22.0,15.0,14.0,18.0,21.0,AEADAHECBGBFHGHDHAGDGHGBGBHFHBDDDHGHDHDADHDHAHDEDADGFEFGFBDBDFAAAAABEFDHHHEGBGAAEDEGEGAFAFHHBEEHCGBEADAEFFBFDFDBDBGBHAGBCBEFDHGCACBCBAAACAGE,False +567,18.0,34.0,25.0,23.0,26.0,29.0,16.0,24.0,CHFDFHBCBDBFBHEEAEABABCGAFDFDADADADBBBCBDBFCEEEFFAFDBDBGHDHBBBFFFDABFHGCABABABAHHHHDFBFEFHBCDCFCFBFEEGECFHEGEGBBDDHDEDHFHDHDFBAECCBHBEBHBCCCBDBEGHGCFCACEFAGEGEGCCFBFEHEHCGFECGFDAGFGHCCCEEEBEHAHDG,False +568,10.0,3.0,8.0,11.0,10.0,4.0,2.0,8.0,EGEDEHEHCDCEAEAEAFFEHCDDDCACHBHBDDDHAAACAEBFAGAHDCCFEDHD,True +569,16.0,11.0,9.0,12.0,15.0,17.0,17.0,12.0,EAEDEACHEAGBHHFFAGGDADADHBHAFFGDEDEHFBFCGBGFFDGHAEAFBCBEAECDADCGCGFGEGEGAGDEDBFFAFAFCBHAEAEGEGFGFDCHCGFBHBHBH,False +570,5.0,3.0,10.0,3.0,5.0,7.0,4.0,6.0,DADCHHGACACECHCFCFHDEGABAFFFFECECFGGHBCBCEH,False +571,19.0,19.0,10.0,25.0,20.0,11.0,12.0,21.0,EGEGEDDDADCBFBFCHCHGAGDHDHDADGHEDDDDHBHBHCADEEEDDHDBCEAABABFEEAEGHGHFEADDDCABHBHBHFHFEEEEFDCEEGCBCHGAEAGABFBHAHEHAFABHBFDDDBDBHAAFBBAGGCD,False +572,9.0,14.0,14.0,11.0,15.0,15.0,19.0,10.0,EFEAEGGGDGDADFHFGFBFBFGDGBBEBEADHGCBCBCGCECGFDCBCBFDFGEDBDHCAFEFEBGCHAFGFGEEHBGCGCEEEBHCHBADCCGGHAHADAGFHFE,False +573,4.0,10.0,13.0,15.0,11.0,8.0,6.0,4.0,AFCCGEEDEBEBAHAHADFBCBCBEFDGHBEGEFFBFDDBCECDCDCECEDDDDDGDCDCEBBGDHFCCGF,True +574,15.0,27.0,18.0,27.0,33.0,20.0,18.0,26.0,FACGCDEDBABABADHDBEFECGDFHHEBCBCGHHAEBHBHGDADGDGDEEEDEBCBDBEAFHFEDGDGDBCHEAADEDEAEDHCHAFDEDHDACHBHBHEHECFBABHDEEEFEGBGDDHGFBFBFCFCEBEBFFCECEGEFEDGDCBGEGHFCECEBGBHBHDHCEFFFBGBHHHEFAAHDG,False +575,16.0,17.0,13.0,14.0,16.0,19.0,22.0,14.0,HBCFCFDFEGAGAHHGEGBGDGFHEHAFBDBDCHCHGFDEDEFHFBEBHBHBEBHBDFDEDEHEGEFFACACGFHADGFADGBAEADAFBCHEFFBEBGBGBACGGFGFAABGGDGFCCACAEAECDGGGC,False +576,21.0,18.0,24.0,12.0,15.0,14.0,8.0,14.0,CDCDFBACHGHECECEDECECHHAHBGFAAHAGFEBCHAGBBBABCBADCFEGABABCGCFAFEBHAHDHECACHHFCBBBEBECFCFAFAHAFCGDFDFDBEBDCACACADBDEHEFEDGCACAC,False +577,11.0,6.0,10.0,4.0,4.0,6.0,15.0,11.0,HHGHAHGDGCEBABABGCHCGCECHCACHDFBABFHFCAHAHFFBFGGGGGGGACAGECDGAADEHG,True +578,13.0,11.0,13.0,13.0,10.0,10.0,11.0,13.0,HDHDFAHCHGEAAAACGBEEHHDEEEDADCDCACACDGDBDBCFEAGHCFCABFBFGCEFBHHHHGBGCGCGEEHAHFBFDDBDBCGDGAFAFB,False +579,16.0,20.0,17.0,10.0,16.0,13.0,17.0,18.0,HBHCDAHECCCCBHGEFCBCGFFAFACBDGDCHBHBCBEBEDGDFEHGHBHECCCEFAGAEHDGDGHBFAFAGAGBGBGBEECCAFAFDBBHFECBGHCHBHDHBHBAEEEAEHEAGAGFGFGDABA,False +580,19.0,23.0,27.0,23.0,24.0,28.0,24.0,26.0,FGFGCHDADGDHFFDCDABFFFFBCEAECEHADCDFDFABAHABDEDBAHCCCHBAAFAEGEGFGHDHGHBHGHDCFCFCADEFEHBAEEFGCDCGGGGGEHFGCGCFFHFHGHBCBDBDCCCGEBEHFBFCFEECFGHGHFHCAEBEBEGHGHFEFDCHCBCBGBDBEAAABCCEAFBHBHDHEEGABDDDED,False +581,14.0,16.0,19.0,20.0,20.0,20.0,13.0,20.0,ACAFBEAHDHEHBHCABBCHFHCEEGCHHFCDCBBEBHFABGDHFHFHBHBHBGDDDCFFHFBFGFECDCEAGAGACCCGCDCDEDEDADADFFFAFAGHCDAGHFEEGHCEEEHECECEGEFDFEEGDDDGDBBFBFBADH,False +582,13.0,15.0,13.0,20.0,21.0,19.0,19.0,16.0,EGGAGAHBFFEFEHECDCFCBGHFFGAGAGEGCGAGBFCFDDDEBEHEHCFBDDDDDDADAFAHHCFDEDBFFFFHAGCBDAFBHBEDGFGCBCBGEGEDCDCDCFHEHGHBDGEHABEGAGHFEDAHEEEEEBHB,False +583,6.0,13.0,10.0,9.0,17.0,8.0,10.0,9.0,FHFGBBBBABCCDHBEDHGFDEHCGCBEBEHCFCFBFBDBACFHGHGEEECECEDEDEHEDGCAEADFDGEAEGGGEBABEH,False +584,18.0,27.0,27.0,16.0,19.0,28.0,14.0,16.0,FHFCFAFHHBEBFBDCHBGEDBAFFCBHBCFGFGCGCEEEDEDBABGEFBGBAFAFHEGCGCDCDBHHCHAHAHGCECAHFHFDEGHBBCACABABFBFBFAFCDCDBABEBECFFGBECCCHCFAFDDDDFDBECEAEDBFCDCEFGFABABCCGEHCABGFEF,False +585,26.0,16.0,22.0,22.0,20.0,21.0,22.0,26.0,FHDHDHFCEBBDBAAAAGFGCBEDHDHGHAEAECDCBEBHCHAHGGFDAEFCFHHHEECCCDCDCDHAHABBECACADAHCDCDFBBEDAAGAFFHCEEEAFAFGFCECEFACAEAFFHEGFHCAGECFFGBGFGDBDBABAGGGGGHHHAHDDDHHHAHDGEGFGBGBFCEDGD,False +586,8.0,5.0,12.0,4.0,4.0,13.0,13.0,7.0,DFDCCCCCCFEBEBDFFAFGCGCBFDFBAAFHGHGCGAAHGFAFGFGCGAGBCHFHCGGHFHEAEG,True +587,4.0,3.0,2.0,3.0,2.0,5.0,3.0,1.0,BGGGDBDHDFCAEAFCFBFEFAA,False +588,7.0,14.0,10.0,16.0,16.0,9.0,9.0,13.0,BCDFHCGFGAEFFFDDBBHBFBHHGAEDDFDEHEGEGEHADFEEHEGEDEDEDEHHBHBDBHBDCDCDBBFBABACACEHECGHEBDGDCCCAG,False +589,41.0,28.0,27.0,20.0,22.0,14.0,25.0,23.0,EDEHHHEACAEAEGECBBHBHBEFAFEBAFHHGHAHACAGBDBEGCDEHAHADACACGEDCCCFBBBBBFAADACAGECDFHGDDBDCDCECDABAFCBEGEDFCGBGDHACABGHECBGGCDCGEFEAGCGDAAABABABDHGEAHBGAEHGBGBFCFCFEFBHGHBAAAAHABABADAGACACGCACHDHDHAFAGEG,False +590,25.0,17.0,16.0,9.0,20.0,24.0,14.0,17.0,HDFDEGEFBBECCBDBABFFAFDFCECBAGAEABGFHCACAFAFAFHEHEHECFCHEHEHECGBDBAFEBCFAFCFAGGCFCABHGABFFEGAHAGAGCHHEHFDFBEBCBEFAFAHAEFEAAHAHBHBGDGDGCEADAGEF,False +591,17.0,13.0,25.0,18.0,20.0,19.0,18.0,19.0,ADCFCHDBAEHEHEFEACAFAFDFEFECEGADHDHEBCCCCEHHGBDBDGCCFBGDDCGABAEAEDEAFAFCGCFHFEGAGDGFHCGCEHEAGCHCBDEDCFEDHCBEBFBAGEGAHCHCBCBAHACDBDCDCHFHEGFGFGDGHGFFH,False +592,4.0,14.0,3.0,5.0,17.0,15.0,9.0,5.0,HGFEEHBHFFEFHFEGBABFBGDFBBEFEDGDEDECEBEFEAEBBBBEBFAHAGFDFEFEBGCGFGBGFECE,True +593,13.0,8.0,10.0,11.0,8.0,10.0,5.0,8.0,EAEADADGFGCDDFBFHHGADABAFHHBAEABHHGBCFCFDFAFDHDCDCBFBCCCBCEEEAEAEFDAHACDG,False +594,16.0,13.0,15.0,7.0,3.0,9.0,20.0,22.0,BGBGCGHHHEHGAAFGCGBDFAFBHCHBDBCCCFDAHHBGBAAABHHHGHGBABABCCCCCDGHGHCHAHGEGDBFGFGCGAHAGFCHGGGAHAHCHFEDHDAAF,True +595,12.0,10.0,9.0,7.0,8.0,10.0,12.0,10.0,AEFDFGFGABHBHBACAHFFEECEFDFGBCAABBCDCGEBEBHHHHFBAEADGDGHGDGDCACGCACAEFHAHGGGBF,False +596,12.0,14.0,7.0,5.0,7.0,8.0,16.0,11.0,DBGBABFCGCGEGBGCHCABEEHGGGHGHFBEBABFBFBGGGGFDFCGABABAFAHHHHBEAAADDHCFEHAHBGACDGE,False +597,12.0,31.0,25.0,23.0,29.0,22.0,19.0,20.0,GBCAEDEGEDHCHGFBEGCCDCGAFBFAFEGBBDBDBDGGCEHEHFHDCDCDEDFHHBGBGCHABGCGCFHFDEBCDHDAABFBGBHDCDCEHEBFBFEFBFHEHEGEBBDBEBABCDGDBHBDFDFDACCEFBCBFHFGCEAEDFCCDCFGGEEEAEAFAFBHBEBCBCHEHCHGEEEBE,False +598,3.0,2.0,2.0,2.0,0.0,4.0,2.0,0.0,DADAGFCFCBGAFBF,True +599,18.0,18.0,17.0,19.0,19.0,25.0,24.0,26.0,EFEFADADEGEGBBHHABBHCCGAFDHDFEHHHHHHGAAADGHFHGGGGDEACHCHCFCGEGEFABEEGEHFCFDFEBGAHCHGFGFGFGFDDHEFCFEBDFEACAFHCHFBADGCGBADGDAFCHCHDDDFDFHCHBHEEEBEBGBABABABCBFFHFDGCGBGD,False +600,18.0,13.0,8.0,18.0,9.0,20.0,11.0,10.0,FAHEFAFAHDGGGGHCBEGABABFEFAAGAGAGAGAGBHBHCFFDHBHDEDEDABCFCEDEBEFADDBFFCFHFAAGDDDDDDFFFFHADFFFBBBCDADCCADHBE,False +601,28.0,16.0,18.0,22.0,25.0,31.0,31.0,28.0,DHDHCHCEGGGGGGHGHGABHGABAGDGEGBACHDHBGADFBHGAGFGDDADGEAEACHBBFFHFEGEFFAFAFGFEFAGADDFAFCFGHBFFEDBACABFHFCCCEEDFDCDAAHFHEHDDEDGHEFCAHFFBCGCGCACABAEAEHDHFHFHFCEDEDGAGAEEEEEFDAGGGHGHFHAGEBHBAEFCFBFCEHBHD,False +602,19.0,22.0,22.0,6.0,18.0,28.0,18.0,32.0,BEHEHCBFBFGAGFFFHEEGEFFGCHCHFABHHCCBFHFABBEBCACAEAFHFABHCHGBBAHEEEEAHAHBHECACAHEHEHCGBFFHFGAGCCBCBEFEGHDDGDHFHCDAHHHHDAFBFAFHFHGHGACCCACBHBGBGBCFGFHFHFGFGFAEBCGCBDEF,False +603,6.0,3.0,3.0,0.0,3.0,1.0,2.0,3.0,AAAAHHHEAEBFCEGAGCBCB,True +604,20.0,12.0,4.0,14.0,4.0,16.0,10.0,13.0,BHADGGGBAFFHAEDBAFGFCFHFHDHBHBGFFHADDEHFFBFGHAHAHABACADFFAAGADAGAGACADDEFEFDADAHBGBABDBDBDCHF,True +605,13.0,12.0,3.0,10.0,9.0,12.0,19.0,5.0,BFBFCDGDBDAGAFCHBBBDHGADCEAABAGFGFGEGEGDGFAFEGBGAGEFFGFGEDADBBGAGAGEFEBBHGHGEDDAFAH,True +606,25.0,22.0,15.0,23.0,20.0,14.0,29.0,17.0,ABABABGDEFEFEHBAAAFDDBDGDGAGEEBHFFCAHAGABACACHEGDGDFDHGGFFHFBEDECFGHCBAGDGCHBGBGCGFDADECEBEAEADAFEBEAEFCBCBCBHBABGBHAHAGAGDDEEEHBCEADGDGDHHFDGABDBDGGCGCADGGHHDHGGEGC,False +607,7.0,12.0,19.0,9.0,3.0,6.0,12.0,7.0,CHGGCADECECGBGCGCEHDAFACDBGGFABCBCBCBCBFBCGCBCBCBFHADACADHDCGGGDFCHGFCHDHDB,True +608,15.0,15.0,12.0,14.0,12.0,4.0,21.0,15.0,BGBEFEGDBCGCGHHEGCFAGEBFGHBCCEGAHACGBDBGBHAHGHGHEHEHACABADADAHACBGDAEHGHBDBDBEBAAAFCGCGDEDCDEDHDAGHGDGBGEGDC,False +609,11.0,19.0,6.0,5.0,9.0,14.0,11.0,10.0,BBBBGBFBFBABDHAHFBBAHEHFCAHGGDGDFCBCFCGAHBDBGBGFGHAHGBEEAFFFBFEFEACACEEGEAEDGFHAHBBBF,False +610,7.0,6.0,1.0,2.0,7.0,8.0,15.0,3.0,GGGGGDGFBAEAEBFHGHDFAGBEFEFGFGBHAGAGBCEAEGBGEGAFF,True +611,9.0,11.0,18.0,12.0,13.0,14.0,18.0,18.0,DABAEGBGEGEGEGFDHCGCHAHFHFCCCCHHGADFBGEHAHEHECFHEHEAGABDGEBCBFFFGDGBGACHHHDHCFCDCHHGDCHCBCDCGCBBDADGGGEDECBFFFFEF,False +612,1.0,6.0,5.0,8.0,3.0,4.0,3.0,4.0,BEBEBGBFBFDDCHBDFCHDGACHFHGDCDCDED,True +613,5.0,7.0,4.0,9.0,3.0,12.0,4.0,8.0,DEEHBFGFCHBHDHFAGDBDHDFCFEBHHHBFBABAGAGDFDCDFFFFCFDA,True +614,5.0,4.0,10.0,9.0,2.0,6.0,6.0,7.0,GCBCBCGGBFHHCFCHHDDDDCBGAEACACFDADCCAFHFHDHDEDGFG,False +615,20.0,20.0,21.0,19.0,32.0,21.0,14.0,26.0,FCCGGEHECEDEDBBECHCHCFGBEHECCCCCHCGCDCDEHAGCECEDDBEBABABEBEAAAAHAHEFAFHFEFBFBFAFGEEEAEHEBGHEHDBCBDAAEFFHCGFHHHGCEAGDBEHEFEGDFBFAHHDBCHFFBEGEGFHECEADADADBHFHAHDDFDFHEAEBDBDGH,False +616,4.0,1.0,4.0,5.0,3.0,3.0,4.0,3.0,AGAHCHBGDFDCHEDEDEFCFCDAGAG,False +617,14.0,17.0,16.0,17.0,18.0,16.0,11.0,15.0,EFEFHFABEBEGEAEBEAECBDHFEEGEGBGDHHHHHBHBHBHAFAHDBFHABDDFDHBGDECECEFEFGDABAFAFABDHFBFCGCGBEFCDCEADDDFACAHDCCGDDCBCGCFCABECGCD,False +618,29.0,30.0,26.0,14.0,18.0,25.0,13.0,17.0,HACCBHBFAFBFBFHFCBAAGAEBEFDDBDAAACACACEEDDAEFGBGFEFCABAGAGAGFGCHCAGFBBDFHAABFCFCFDHEHCFBFBHADBBBBHDDBCFABBEBFBADAEBCBHBHFHCBDDHCHGHCACAGAGDFCFEAEBECECECFCECECGHEBAFAEAGHBCF,False +619,31.0,22.0,24.0,19.0,30.0,25.0,19.0,29.0,CFHEHCGFFACEHBDEEGGACFCACAGAHAEAFDCGBACEFGAECCAGHBHBDBAEAGFBABAGACAHHHAHCHCDCDAGGGAHAEAEDGGCEHFHFHFDGBHBCEHEDEFEFEFEAADACHFBDBDBDBFBFAEHFHBHEHEGEDEDCCEBFBFCFCAHDBFEAEFEACAFADEBEHHDEGEAHBHCHDBGBCDHFGF,False +620,18.0,17.0,15.0,24.0,21.0,15.0,18.0,13.0,ECDGDBDGDGDEAEBEBCFGFGAGAGHCDEHEHBGGGFEAAFBBDFHCDCEEEEGAGAGEDFDHDHAFAFHEHDADADBDECACEDDBHFEGECADDCFHBCBCHCDDFDGBBBEAECEDEFABAHCHGDABFBFGFCBGA,False +621,0.0,2.0,1.0,1.0,4.0,1.0,0.0,1.0,FEEDEBEBHC,True +622,14.0,20.0,14.0,20.0,27.0,29.0,12.0,26.0,CDCACEHFHFHBHEFEDEBBFFFFBFECHHAHEHEDGDEEBFHFHAACEDECCCCEFEHAHBHDHFHFAFABEEEGEGEBDAHEEEEFHDDDGDEDABHBAFGFEHABFBABDBFFFHFCFHFBGCABBGBHFHFDDAHGFEFEDHCHDEBGGGBCDDDCGF,False +623,16.0,25.0,17.0,19.0,21.0,19.0,21.0,15.0,BFDFDFGBGDHBHEDCACFCEHEDEBCFDEDADBDACADDEGEGHAHBHFEBCCCAHEHEBEBAAAAGCFCFGFBEEEHBHEHGBDBDAGAEAGBDBGFEFGBCBCFGEGBGHDHGCCAADCDCBFBAGGFGEHDFBEBFBFDFCFHBGGGEB,False +624,23.0,27.0,21.0,27.0,12.0,19.0,33.0,26.0,DHAGAGFBFCCHHGGBCBFDFACGBGBGHCABACAHFHCDCDGFGFCFGFCAEGHGABABEDEDHFHFDFBGHGEGHAHBHCDAGAGAGBBAEAFGCACBFBDDHGHBHDGDGBGDAAAAEBBGBDBDCACFCHCBDBCCCBGFFHDHDHEGEDEHHDDDHBGBHDFFEBDDEEGGGGAGHCHDBAGD,False +625,17.0,22.0,27.0,7.0,24.0,19.0,26.0,18.0,GHECEGFGAGCBEEGBGHGBEBEAEFGFAFCFHGGGGEEECBFBDGGCGCEDGFBHBCBCBCAGABEGEAEABFFFBFBFHEGFGACAEFDBCBCAGAGAGFFCCBEHCCBCBDHCBEHCHCACEBFBCGDAHFCECEDACAEHHHHHDAFGHCHCEGEH,False +626,21.0,20.0,18.0,14.0,19.0,24.0,20.0,19.0,FGFGDBFGAAHHDABADDECCHFBGCEEHGHGHGAFHCHAHBCBFAFAFABBBABADDGEBBFCFCFCFCBCDCDHFAGGHGHGAGEHBFAFCHHEGEFBHDHAHAEDGAGAGEGCDEHECCCBBBAFFFEFDADBBEDEGCFBFCGAEEEEFEF,False +627,22.0,20.0,15.0,21.0,16.0,16.0,15.0,16.0,GBGEFDACFGFGHBHECCFAAAEEGBCHCBCFADHDHDBDBDFDADABAEDFBADACBCFCFEHGCEFEAEBHDHDFDEEBBHBGAGDGAEAEGGHAHDDDDFDGBBBAAAABDHGHFAFECCCECHBDBCBFEFGAGAHH,False +628,7.0,15.0,8.0,13.0,14.0,12.0,11.0,8.0,DEDBDHFHDCDCBBBCBDBFBFCGHGAGEFAFAEADBFBGBGHGDCFADBDFEFEDECEFHHCBEAGGGDEBECEABBGHGFDHEEFE,False +629,1.0,3.0,3.0,8.0,6.0,2.0,4.0,5.0,HEHDHDHDEFBGBGDDCDHBEDECGCEEFGAD,True +630,11.0,10.0,7.0,6.0,8.0,14.0,8.0,5.0,CAHAHABFCFCACFCAHAGDBCEGHFHEBDFAGAGABBBEBCFEFEFBFAFBDEDEGGDFDABFFEFGG,False +631,14.0,11.0,20.0,21.0,13.0,15.0,14.0,16.0,HCFAAHBFCFAFHFGDHFCFBBBEBEAEAEHEHGDDBHHHFHDCDEGECFHFDFDADACADHGEDADHDHDCDCGADDECEAGBBCECDGGCGCABAHFGCDCGFBHBDCDGAGCCCDCGEFEF,False +632,4.0,8.0,5.0,12.0,1.0,8.0,6.0,3.0,CAHAEDBCCFGDBDFFBFBHDDDDDADCGBGBCFAGDGFGFHDBDBF,True +633,3.0,4.0,7.0,2.0,2.0,6.0,5.0,5.0,CBCECACAFEFDAHBCGFGFBHCHDHCHGGFBFG,True +634,15.0,14.0,8.0,23.0,21.0,16.0,17.0,8.0,GDDDADADACBFGFGFAFACADAEEBEBFCGBFHFHGEDDDFCGABCBDHDHEEFHAHGEFDFEFBFAGAFEGDGDGBGDEDEBHBDCEEEEGEBCDDEAECDDDEGGGAFAEBFBGHEDAB,False +635,16.0,23.0,27.0,12.0,33.0,22.0,20.0,34.0,HEHACECAHFBGBEBHHHHFFCECEHEAEGDGDHAHBFFFFFFFGABCEFEBECECHABGCGFHEEEEEEGBCAHEHCHDFBGBCBCBHHGFBHDHCHEHEHCFCGCGEFHHHCDGDEDECBCAFEFAGHDCABHDAEACCHGHFBBHDEAGBGAFDDGCACEFEFEHEHEBEGCCEGBGBCAHBHB,False +636,18.0,21.0,19.0,22.0,14.0,15.0,21.0,26.0,GHABCDDDAGGFFEFDFHBACHDHDECGBFBFAAGECECDAFBHCDCEBGBAAAGHHEHEHEHEBAFDFCACECECEHHHCHDHAHAHCDBDGGGDHDBCCFCGHHHGDDDBEBFCFDGAFBFBDBDBGBGBABHHCHGHGDBEGAAHDCGAGBGF,False +637,7.0,11.0,15.0,9.0,7.0,9.0,10.0,13.0,DAFBFHGDGAGCDCDGHBCECFCGCDEDHDHBHBFBEGEHDADBBBBGFHHAECHGHGHBFCFAACCCFFHGACHCBCECE,False +638,23.0,18.0,27.0,21.0,18.0,14.0,17.0,30.0,DEDCHCBFEAEAEABAHGDGDADEBEHCFDGGCCCCDCBFGFCCHDHDHFBABDHEHAHFHCAFAEADHDHCHEDACCGCGCGCBAFHHHECDDDBGHHHCHBHAHECFBBGBDBFHAHGHCDGHGCGCBBBGBABFGCGAEEDFDAEHFHDHEEACAEFEACHCAAA,False +639,8.0,5.0,5.0,6.0,7.0,4.0,6.0,5.0,FGEBDBDBGHGDGCAHAHCDAGAFAFBEBEGEFDCHAEECEDACAH,False +640,25.0,30.0,19.0,18.0,18.0,25.0,21.0,28.0,DBGBFBFHFHCAFAFACGCHCHEHEGFGADHHFEAEGEGHGEAEBDADHBABDGGGGHBHDDGAEBDFCGCFFGACDHBHFHCHFAGHEDACAHBDDDAHHEBEBABACAGBDEDGHBHFHFCGCDFBFBFAHGCBDDCBAEAEFCABABACACEFHFBAEHEGBGBHBFFHBEBFBFBFHCBC,False +641,10.0,7.0,19.0,15.0,18.0,26.0,16.0,17.0,EBEBEADCFGFGAADCEFHCAEDEAEFBHEHDGDGDBHCGCFHFHCHFEFGFGCECFCGCEDAFEGDFCAEADCFEFHHHFDFGFGAGDGDFHHGACFBHDHCGFGFCHCHCHCDEECFFFFEBEBFD,False +642,17.0,19.0,31.0,20.0,20.0,27.0,31.0,22.0,EFGFHEBFAHAHFHGCFCFGFHFBFDHDAGAGBECCHCBGBFEABDEGEGFCBDDFEFADADBFEGEBBAEHEHAHAFGCGCGCBCBFGFCACHCECGCBCAGFHDBDCAFGCGCGCGCDDDCDGDGFBHGFFAHCFCFHECDGDBECCCDCEGEFBFEHHGAGCGDHAHGHEFDHAGBGBGHDECE,False +643,10.0,16.0,8.0,13.0,16.0,18.0,19.0,19.0,DBDFCEGABABHBFGAHEGFFDHCFCFBDHHACAFECHHHHGFGBEHEGEGEGFGBBDBFEFHFCEDECFAAGFGFEBAGHEHEHEGDBDFDFBEBDBDFDBGEHCAAGHGHGBGHGHD,False +644,23.0,23.0,24.0,17.0,10.0,17.0,18.0,14.0,BGGGGGEGBACCECHCHCACDBAEFEFHAHACFGGADDCDCDCDGHGCBHBAAFGFGFABBBBFBHGFAAADADCDEACDEACBHEEFCCHCHAFBCHGEGBFDFHEBBHBDBCHDBDBGFCFBDCGFGFACABBBAAAAAFDCDC,False +645,19.0,20.0,19.0,12.0,21.0,19.0,19.0,26.0,BCHEHEABABAHAHDHBEDEAEGECEBECAHDGCFEFCHHAHDHDHFBDACABGCEBHBCFHGCCCAEEDAACABBHGHGHFHBEBHDECEBDBCBFEFHHHGHGHGHFHFBDGEGACEFDFHFEFCGGGAEFDFGCGABFFCFCGBGAGFBAEA,False +646,24.0,19.0,25.0,16.0,26.0,22.0,27.0,28.0,DADGFHCDDBDHDHGGAEECHHHFCAGACFCFEDCCECEGFBFBCBGEHEACBCBGGHGAGFHCGCGEFEDAHAHFHEBBBHHAAEAECBGAAFBGBHBHAAFEEAECEGHGFCDCHHHHBDFGFGFGBEAFHFDAHAHCBCEHGHGFCDGDGCGEFABDBFBAAAHADEDEGCGHECEFEFECECG,False +647,19.0,19.0,11.0,23.0,12.0,13.0,15.0,22.0,FGFAADEGEAEADGDFHAHBHDGGGHDFBHBDDGDCDHBHBHEHECEDBDBEBHHDHEABCCGFAHGGEADAGFDAHEHDHDCDGDHHEHFFFGEGBDCACACDFDHBBBBDCGAAFAHABABACACFDFBBHB,False +648,14.0,18.0,21.0,17.0,4.0,13.0,14.0,14.0,HDCCBGAGBGFGFHCCACHCGCBCBEDEBCBDBHFCFCFGAGACBGFDFBHBADAGHCHBHFCACDFDBABAEGCHHDBDCFBECGCGBDAFFGHDBDBDADADACFDADCHHGH,False +649,18.0,10.0,20.0,21.0,15.0,23.0,20.0,19.0,CDCFFDAABAFGFDBHFHGADADAHGHGBDFCHHHCDCHAHADCDGDGDGCEFGFCECFCFCGCAAAAEAEDBDBFFHHHFECECGGEGAABHECFHDEDGHGAEADFFHGDGDGEEBDCFGEHFCGCECEDDFFFFBFBCBHHAG,False +650,2.0,8.0,12.0,4.0,7.0,2.0,3.0,2.0,BECADGCCCCCBCBCBDGGFECECDBDBHECEFABHBCEE,True +651,23.0,17.0,14.0,13.0,18.0,7.0,9.0,12.0,HGFCACACFCDEEAGBGBADADABCGDAEADGDBACFHBEDAABHBHGHCAAEBECECACEDECEGFGAAHABAEAHDHABABADEBCFCFBEEEHEBFBAEHEHDCDBGBHD,False +652,9.0,5.0,7.0,3.0,3.0,4.0,7.0,7.0,FHAHAGGGGHGCGCEHEAFAFCHDECHBABCFGBHBACDCDAABA,False +653,17.0,14.0,10.0,12.0,16.0,15.0,12.0,13.0,FFDCCCGHBHEFBAEAHDFFFHBBBBGAFABABAEADAEFCBDEEHFDACHCHDAFCFEDGBCBCBEBEGGGCHHDDAGAEAEDEDEBEHDHAHEFGFGFGHGAAEAFG,False +654,18.0,23.0,28.0,27.0,18.0,13.0,30.0,25.0,CGCBCACGBGHACACADFEBGBCAEHBDBCHAEDGDFDCCAEHDGDFDFAFBGBGEDCFBFBFDAHGCCCBGBHEHAHGGGCECEHEAGCGDGDHBBDGCECHAHDFDGEGAGDGEADHCACBGBCHAHAGBGHHCHCHGEBEAEDECHBGBGDGFGEGHCHBDDDCDHDFDHCFEHDBDBF,False +655,15.0,11.0,8.0,7.0,7.0,6.0,7.0,13.0,EFAFACBEEDCAHAHGEAEFFHBHBFBFHGAAHGHGAGDCBHHHABDBEBAGAGDDDADHBCBEACHCACACHB,False +656,23.0,17.0,14.0,15.0,23.0,23.0,21.0,14.0,DBBBEEGCGFABAGAHAHFDEEHECBHBFBEAEADGDACGFGFCFDFGFGFGBEBEDEHHCFEHAHAFAHEBABEDEFGFGBGAAECFCHCEAGDGDCBCAFHFDFDFCFEEEEECFDBGGGAAADBGBHDAGEEBHDAAAHFGCGFAFC,False +657,22.0,13.0,20.0,11.0,19.0,20.0,13.0,19.0,AAAEEECFGGCCCDBDAFHFAFCCBAAHBBBEBFBAGCGEGHCAEACDCEADBDEAFCDGECEGGAGABAHAEBHHHHHCFCFEHCHFHGHCHCFAFDFDFDHBEGEFFFFAEAECEDEDHFGABFEGCHCHAHABF,False +658,13.0,8.0,9.0,8.0,6.0,14.0,16.0,11.0,DFDAACADGHGFECCGBFFFHEAAFACAGFHCGCFAFDFBBHHFGAGABABAGEFEFGDEBFBDBGACHCHCHGDGHGHGEGDGH,False +659,24.0,22.0,11.0,20.0,12.0,19.0,20.0,10.0,ECECBBAAAFHDHDHCBGFGFACABAGGHADBEAFFDFDFDEGCGCBBBFAGABBEDGGAGFDAGHGDDAEABBGBHDGEBFBHDFGCBCBEBFDFDADADBBFEHEFEFDFHFEGDCDCDCGBGAAAAAGAFAHBGA,False +660,9.0,8.0,11.0,8.0,16.0,14.0,26.0,11.0,FEGEHCHBGBGEGHGHGEGHDEBHAFACGDGFGACHHGAFCGGFEHDFDEEGBGBGFGFGCCECFAFDFDHBGDAAHAGEGDGEGFGAGEBCCCCBEEGEFEF,False +661,21.0,16.0,26.0,12.0,16.0,24.0,13.0,16.0,AHBFGAHHBCBABABCCGBEFACECGHGFDAHHCCECFFFDFAHACACBCBGBDFEFEHEDACAEDEDEGEGDGBBBGCGAHACACEFAFDFAFBDACAFFHFCFCAGEGBFDFBFEGCFCBCFHACADDCHFHFCECEHHHCE,False +662,19.0,21.0,19.0,34.0,20.0,23.0,22.0,19.0,AFAFBGBGBABGDDADCFCECGGEAEACHDHDEFCFDFDECHHGDEDEGGFEBBBBBEFEDDFAHCBEDDBACDCDAHAHGHDCFCFDFEFEDHCHDDADBGCABDHEBBFBDCDHDEDEABDHEBFBCEAGGHFHEAGFGFGCGDGFGDGAGAGABFBFDDHDCDHHGHECDCFAF,False +663,30.0,32.0,21.0,26.0,25.0,15.0,23.0,18.0,GBDHGHGHGBGFGABAEEDBCBCAHAEEDFDADEGCCCGHDBBBEDHGGFCBBHEAACDBGAGBGFEAAAAAABADGGBGCDCFCFDFCBHAHBBBHBHGDBDEHBHBHBEAABABDDEAEDFDEBEBECEGEFAFCFCADEGCGBABABFBCEADAEGEGDCDGBFHAEAEFCDDHEHAHFDCDEDCAC,False +664,14.0,12.0,16.0,18.0,20.0,25.0,19.0,23.0,GFFDFGFDEAHBCEEHCFEEEABFGFGHGAGAGCGCFDBDBDEDEABABDBHFCFHDGAGEHEHEGDCDCFAAGAEEHFGFEDCHFHGGEHDDGBADDGHFHEHEHECFCFCDCAEFFFGFGCBHHCCFCFBFHFHEDADHHHHABB,False +665,1.0,1.0,5.0,0.0,2.0,0.0,2.0,0.0,CCCBGGAECEC,True +666,13.0,18.0,8.0,9.0,12.0,13.0,18.0,15.0,FADABCFAFAFGFGFBCBGGGFGDCDCABDHDAEHEDGDGEFFHCGEHHFHBGAGAHEGEGABFCGBGEEBEHFHBHBHBHBFBHCABBHGEEDCDBABABHGGAE,False +667,12.0,9.0,6.0,10.0,3.0,13.0,8.0,9.0,CBCHGHFADHGAGBCFDFAADDFCFHDAAAAAFCFEAAFADCDGDGHFHFHGBFBFBEBHGHGBBDFDEB,False +668,25.0,23.0,24.0,17.0,11.0,21.0,16.0,12.0,GDAFFFFHBBGCACGCECBHAEDBBFFFBCBCACACGBABEBEDDBFAHBHDAGAGBGBGAGBGAGEDBAFCCDCGAGHCDADACAEDFHACBEAACFDDBDBHBDBDFFFCFCFCFCAAAEDHFAFHCHCACHCGAGFFCEEBEBGDH,False +669,3.0,6.0,1.0,5.0,4.0,4.0,3.0,1.0,EABGBEBGBFBGDFDFDADEDBFHEAC,True +670,5.0,9.0,11.0,15.0,8.0,21.0,12.0,11.0,DFDCHCFFDHHAHACGGFBDBDCDCDAHEFFFHBDBDBEECFGDGHGBFCDADABHBHGGEGCCFFFFFDFHEBGCEFDFGFEFEHDGFGFC,False +671,9.0,14.0,11.0,13.0,12.0,14.0,11.0,23.0,HDHCHCFCFCHCFCDADADEHFHBAEGFGHCEDHFCCDEHAHFEBBBADCHHHHDHBHEDDDADHDBGBGBCBFHEBEFGBGHGFFHAHGHBAFAGBEFEBEHEGFG,False +672,3.0,4.0,0.0,0.0,2.0,6.0,4.0,2.0,HFHFAAGEGFGFABBFGFBEB,True +673,17.0,21.0,20.0,5.0,12.0,13.0,17.0,15.0,BCBDBECHCAAADCGGGGFBABABEBCBCACAGHBHDHBFEEEEAABCBCBAAHBGGCGBGHGFGAGFFCHGHGHBABFBFHCHADDFCCCECECHHEAFBFBCHHBCEGGCFAEAEGFF,False +674,14.0,34.0,17.0,24.0,19.0,23.0,30.0,24.0,BBGEGHHHEHEFABDCHCFBDAGBBBBDBFCFCFAHHEHAFGHGEGEDBDBDHCFCHCEDEDEDGCGCDDDGDGAGAGEGBHHCHADFDBBBCDDACGHGEGEHBGBGHFEFGFBBDBHBFBDGGCGCDFGCBBBDADGHFCFADGEHFCFAFGBHFHBGEAEBBBAFGGDGFEFBBHEHEBABF,False +675,22.0,22.0,20.0,24.0,22.0,17.0,36.0,34.0,CHGHGHAHAHCECDBGCADHEEGECDGBFCCHCHFGFGBBHFHFHEGFGAGCGCGDGDCBFBFEFEHEDECCHBGBDADHFHEBDBGFGBAHGHGEACGGAEAHGBDCDGDHFHBHCECBDHGGGGHBBDFDFHAAAAAHADADHGHEHAGFGDGAEDGDEEBHACFGHBHBHCGGGCAHEEAEHEFDDDGDBBBAE,False +676,5.0,3.0,7.0,7.0,6.0,1.0,5.0,6.0,EHCHEBAGEGDGDCCCCABHEGBAEDEDCDFDADAHHCHG,False +677,14.0,12.0,18.0,20.0,14.0,12.0,11.0,15.0,CCADHGFACAHGHDDDDDGFGHBADGBEBCCDDDADADABBHCFCFHBHGAGEEEEEEEGEFHCDFAFCCADBDCDCDCBBBBCHCBDAGAEHDHAHAEEHEHFFCGCDFGECFFH,False +678,20.0,18.0,16.0,16.0,18.0,22.0,18.0,25.0,DFFHFHFGFBADAGHCBCAGBCBFGFACBEFEGABBBEGHHFHFDFHEEGEBECFCEBEGGADEDEAEACHCHABEHAHAFAHAHAFBFAECECHCHGHAHBHCHFHGDCHGHEBDBDGCADEDGGFBFGDBDCFFEHDFDFDGDHCHBGAAA,False +679,13.0,13.0,11.0,11.0,12.0,13.0,13.0,10.0,DADAHACGEBDGEGEDEAACHFGEGEGFGFCFAFEBCBFEFHCCFCHCHEHAFFDBBBHGCEBGBGAAHFHGHBFDEGAGBBBBDDADADEDACFC,False +680,21.0,9.0,11.0,23.0,10.0,11.0,13.0,22.0,BHEFDAEAEGGAGBCHCBAAHAFDFGGGGBHADEDACFCFAEABHBHBAAADFFACDDDHDHCBCFHDHCHGDAHAHDDDCDADEHFFAFDEHHDHECDADAGAGBHHGHEHEHCDGDGD,False +681,29.0,26.0,19.0,24.0,29.0,20.0,27.0,23.0,AAHAECBCBAADACAFFGCEADCBGHGFEFEAEDEDBDHDEBHDHAACAHAEBCBDFFHFBFBFBFGFBEAHBCAEAGAGBEEEEEEEEDCABFGFBDHFAFAGBGHGCGEGDADHDFGBCBHBHACEBDADEDEDGGGGGGGBHBHDHCFGBBEHCCAHHFABDCGGECFBAHGDGDCEAEHECEGHDFDEDGAHA,False +682,12.0,18.0,15.0,23.0,25.0,24.0,20.0,8.0,DADHGFBFDADAEECECBFDHDBCBABAHFFFFEFEFBFBFBEDFDEAFCCHEBBGECCCCFAGBBDBGCEEDHGGEGEAEAEFDDDGDAFEGCGCGCFEDDGDFHEDGGGGGEBEDFDEDHBEBDCCEFFFEFEBABFGAGHGD,False +683,10.0,19.0,7.0,19.0,5.0,6.0,8.0,11.0,CHCGBDFEGADBBBBBEGHAFAHBGFACAGAHDBDBDADHDGDBDCCCEDDHDADADCDBBBHBFBDBDFDADEHHHBHGGEFBB,True +684,10.0,3.0,3.0,5.0,2.0,4.0,6.0,12.0,DBCHHBHEDEGAGAHFGGHFAAAGAGADBCHAHAFDFDACHHHHH,True +685,10.0,19.0,16.0,24.0,9.0,16.0,18.0,17.0,DGDFEBDHDADCDBDHFHFHAGCHCHAGEEBGBGBAFDHCBADCDHAHEEABDDFDFABBCDDADCDFDFBBGBGHECCGCGDECGDBFGGEGECHCGFFBFBDGFHBHBHBCGCGCGBDDDFHFHFHA,False +686,11.0,7.0,14.0,17.0,14.0,20.0,12.0,14.0,HDHABCEFFBEHCGCACACBHBGEGEFFFBGCECDCDEHEDEGFGFDDDDGDGAHDHDADADFFFAHAEDHFBADEDBCCGHAEEECFFEFCFHFGCGAHDFGFHFCFH,False +687,19.0,24.0,19.0,21.0,13.0,20.0,17.0,22.0,GBGCDCDHFCAHAHBFFDCAGBFBABCFFBFACBGHGHBFFGHDDADHFHFHBGGHGAFDFCGAGEDEGEADDFCBABFBABAHEDEGFGFCBCFDDADACECEBEBCHCACFEGCHBBBDDDGHHDHAHAFABDHEHEHEGEDBABCBDBHCHC,False +688,11.0,6.0,12.0,7.0,7.0,10.0,7.0,5.0,CCBGGGGFABECFADHEACFCFGFGEDFCFAFBHBCBHBDCCHCAAAAAEDDDDAFCFCEGEAEH,False +689,1.0,5.0,2.0,2.0,0.0,1.0,2.0,2.0,DHDGFGCBBBBBCHA,True +690,15.0,19.0,20.0,21.0,26.0,23.0,15.0,18.0,GBGBGEFEGECEDHDHDHDHDCGAEACGCFBFECCACGCDEDFDHDFBBBEBDHGHDCBAAAFBHADFBFHFHFHFEDDADEDEFCBBAEEGEACCHCEGACEDECECFFFFHAHEGEBABEDFBHEDEAEADFDCHFHFCGEBHCFFFGBBECGBG,False +691,16.0,20.0,16.0,13.0,21.0,17.0,19.0,17.0,EEBEDECEAEBBBBEHFBFBFDCDCBCBCAFGHGCECGGDHAHCDCFCEHDHDBBFHFGEECBGBFHDHGHEBEBEAEFBAAAAEAGGGFEFCFBABDFGFDFHAEEGHHHGDFHFGCGCGDAAACADEGBBCAHGEGH,False +692,15.0,18.0,25.0,15.0,20.0,16.0,23.0,15.0,DCAGACABGEGHGBBCAEGHHDAAAFGCBCBCGGDGCGCHCDCDAFCFGHGCGCEEEHBGGECACADEDFDFGFDBBFBCDCFCDCEEHEHFDBDBGEGFFBFBFEECHGHBAGABABEHEHGCEHBFDCCGDHEHEGBFAFAECEC,False +693,18.0,15.0,17.0,18.0,19.0,18.0,17.0,13.0,DAEAFACADHDHCFCBBBDFDEGEGEFDGBEFEBGHGHEHGGAFAFAGAEDEBHDADAEAEDEAHGHAHCECEHFHBGFAEAFBCGFDFGCACADFCGCBCBDAHFBCDEBCFCFGECDBDBGBGECECFDDHFG,False +694,7.0,11.0,9.0,10.0,9.0,4.0,5.0,10.0,CDDDBBCGFGDHDHEHBHEHEBEBEAEAFHDEGEDHBAAFHCBFEGCBCBCBAAHACCCGBHDDD,False +695,9.0,7.0,7.0,14.0,15.0,8.0,16.0,16.0,DFDCDCDEAHDDDBHHFHFCDCHCFBAEEDGAEAGGFGHAEECHGHGHEEGDGFEFEDEGBGEDDBHBHGEGFAHAEAHAHGBGHGHGDECB,False +696,24.0,23.0,24.0,22.0,20.0,19.0,26.0,26.0,ADGDAEBHCGCHCEADABGBGBFEEGFAFAFBFGDGDHHACDCHFACHCGGHGHDHCBGDHBACHBHGHGAAEBFAHGGDGHGFGDCDCGCDCAEGGGEEEEEHDFDAAAHADAFADEBBBHEHECACBEEEBABFCFCFCECFCHBHBAGABHHFHBHFCDEBCDGDFDFDCBFBCBEAGDGH,False +697,19.0,24.0,22.0,23.0,29.0,24.0,25.0,34.0,FCFEAEAHCGEDABFEFDHCHCGCGCFHABDGEGFGFGBHBCAEEHGBCBCBCGHDHFHABGHDHCCCAADDFDHDCDHFBEHEHEGFBBHHHADEEEBEBFACHHHHGHGABBBBEDCBBBEDEDFFFFFFHCHDAEFEGDGHFBDGEHHGFBDADECEDEDGFBFEGCGHHCHCHGHEFEAAGAGEGDGCAHAEAEBD,False +698,13.0,19.0,14.0,18.0,18.0,16.0,11.0,16.0,BDBFFDFDFGGHAHBHBHBHFGAGAHDHBEBDBHBFBFHCBEGEGEDCCCCBGHECDCACDBFCEDBDFDFDHDFEFHFHEHEFEBABDEHBCDDHAAADEBAGAEACGEAEFBCEGEDFCCAGE,False +699,20.0,17.0,18.0,13.0,20.0,22.0,16.0,23.0,ADHHHHFDFBFAGADBEFFFEFEGCFBDHCAEABAEAEBHFECCFDFHHHHHFHCHCHEHEAEBGHACABFCFGAGDFDFCBHGCFCBCHDEDHGHAFDFAGECECEFAGCDEGEHEAABCBGBGBGBABGEAHGEAFHFGCECADBDB,False +700,7.0,10.0,13.0,7.0,8.0,14.0,8.0,3.0,FAAEFBFCFBFBEDGHCCCCCEDEDFHECDBDGFGFADGBEFCFCGAAAHEDECACFBFBGGGFCFCBBB,False +701,16.0,27.0,21.0,29.0,23.0,22.0,14.0,18.0,ABAEADACBDBFAFDCGBDEDBBFBFADHHAABHDGABACDBDEAFCHCECHDDACAFDFDFEAEDHDFBFBFCEEBECDCDHABFBGEGFHFHGBDEDEDEDCDHDHFAGDGHGHGHBCBCBFHCEBEHCCDCBFBFBECFDGGGFCECEDHBGBCFEEDGBFBEHEDE,False +702,22.0,31.0,14.0,20.0,15.0,20.0,18.0,12.0,GHADBDAFCHAEBDBDBDFDEAAABADEDCAABBEGEGFGEGFDFBFBAEGBBCBCBEGDCDAHCHBADADGFBFBHBGBDCFGDGHCDCFCBEAGFGFHFEBECAFBFBHBHBFBEGEGEBEDAHABADABBGBCAAGDFBAGHCCFDFHF,False +703,21.0,26.0,13.0,16.0,14.0,14.0,14.0,17.0,CHABCBFGFAABAGAHAHAHACBDFHAHEHGCACDBEHDGBHCECEHFAACABHBABABECGBGAGEFCGDEFHBBFAFHFHAHEBEFEGBGBEBEDDDDDDDAHHCBCDDGEADABGBDBFGFBFBFBGEDCBB,False +704,1.0,0.0,1.0,1.0,3.0,1.0,3.0,0.0,DEECEGFGAG,True +705,7.0,6.0,9.0,6.0,4.0,3.0,8.0,5.0,AGABCBCEHFACGFHHCHEACADDDDGBGBGBCEFHBDEDACGCGCGA,False +706,6.0,5.0,9.0,7.0,4.0,10.0,8.0,4.0,BGHGEDCHCHCGCFFGDGDGCBCBAADFFAFEFGAGADFHBAFCBCEDEFCFD,False +707,10.0,10.0,4.0,9.0,12.0,8.0,9.0,7.0,EECFAEAHAHAEAEBEHFDFDAGCDHBHGGEGEGFDFDEBADDCHFDDBFGEGBGBEBEAHAGBFBABC,False +708,11.0,14.0,22.0,17.0,26.0,26.0,22.0,25.0,ADBFFHCHCHCDGFCFBHBHBAGACHDFEFHCBGECDDGEHEHDHEGEGEGECBHAECDHDCDEEFHFDFDABHGDEHEGDHDGFCCCHCHDHDHBAEEGEHEHGGGBBFEFEDEFHFCFAEHECGCAFFFCFBBCAFBCHEEGEGFFECGCGFGFGFAFAGB,False +709,20.0,25.0,16.0,17.0,13.0,14.0,18.0,22.0,CDEHBHBHAHBHBGDGEGBACAHAHGBGBGBAAAGFDEEBGBABABFGACACHGHDFDADHEFDHHECFDACABGHFHDDDAEAEDGDCDCFCBCFHBCBEBEBEBFCGCHFEGGDDBBBCEHGDACABGHGAFHHHBFAFCFHB,False +710,30.0,23.0,16.0,22.0,21.0,35.0,15.0,23.0,FAFAFAFEFEHAHAEBEFDFDBDHFCEAHHHHBEFDADHEHBCCCADEHFHFHFCGGDECGCBDBGAFAFBCDAHADBECEFHCBCBAAAFAGBFADDFDFHBGAAEABFDEDFHAGAHAGAGEGHFEFCABAFCBEBEBHFDDDFDADEEEFBFDACEGFBDBHBHBFGFBFCFGGHAHAFGFC,False +711,6.0,6.0,12.0,7.0,12.0,9.0,12.0,10.0,HGEDHDGCGCGBHBHGCFAGABCBGGEBCHCHFGDEEEHEHAHFHCGDFEFAFAFDECECDCFABCGEGFCEDE,False +712,23.0,31.0,32.0,27.0,25.0,14.0,31.0,14.0,CGABCFCEHDFDHEHBDBDECCFBDGHGAGBGCHCBAEHEHDFDBDCEFGCGCFBAGGGEFEABFBGEAAAAHAGACACECACBGDGDBHBCFGHGBCAAAFBDDDDDDFGFCECBBEEGDADCBEAEAFDGEGCCBCBCBDGCECGCGCGCECECBFBDBABDBDHDCEHEBECGAABDBGGGDEEGEBBAHGGDH,False +713,4.0,5.0,5.0,9.0,4.0,5.0,6.0,6.0,BEFEACAHDHDHGHBDCHCDEDFDGDBEFGDGDFAFBBGACHCG,False +714,18.0,19.0,22.0,14.0,25.0,27.0,18.0,19.0,GEHFCECFCAEFBFAHBCCEBFFEFECDADEDEAEFEBECECGHGAAADAGHBFGFAFHDEABBDGDEHEFEFDBCHEGCCEFBFEHHHHGHGCAFAFHFHFGEHEHCGDFEAEAGFFBADAFFCFABGBABFBCBGBGCDCDHFHCECECDHDBGBCBCGG,False +715,17.0,8.0,11.0,12.0,13.0,12.0,12.0,14.0,BAGDHBHDHABAEGHFDADFECDCGCGADHDHDHABCBHGAAFBFBEHEAFCFAGHEBCDFDFDCHCHCADAEHEGEAEGCGCFEHAGGFAFEFEAEAG,False +716,16.0,17.0,24.0,24.0,21.0,17.0,16.0,24.0,FCBCBHBCBCECDCDAFFHHHCHDBEFABAEDEDEDECFDGGGAEFEFEHCADAFACEEECFCGAEDEDGHGDGAGFBHDHFHCCGEGBDHGEBHHHEHACAEGFDFDHCECBADECHHHBBBFBFBDADCCFCDCBCDEDHHCGDDAAAHBHGHGDGF,False +717,30.0,23.0,30.0,24.0,12.0,21.0,21.0,16.0,ECEDACAHEHCACECDCGCBHAGDFACBCBAFGFGBACCCCACFGEGFHHAHABGBEFFBFDFCGABCDCBBBBBAADADGDFDFHFDCDCHFBFAAGAGAGAGFCCCHABGDGDBDCDEBHDCDCDBGFFHHGBEAAHAHDFDEDAHAGDCDBHAFGGGBABDFCACACBCFEEAE,False +718,8.0,9.0,11.0,13.0,10.0,18.0,7.0,15.0,BHBGDHDHDEAEFFAGAGABHFFFADHDHDGAFCDCAHBDECFAHDHCCBGHFCECEHEFDBDCDGEGDBHBECFCFCFHBEFFFFFHFHE,False +719,12.0,23.0,32.0,23.0,25.0,25.0,24.0,32.0,ACHDECHBHFHGHGHDADAGHCCEBEBCCGHFFGFCBEGCCDDDBGFDHDHDHGFGBCFCGCDCDCDCFGEDBDBEGGCFEFEHEBEHECBFDCDGBGEGBGEGCFEEECGFGADCFEAEADBBCECEHEBEDFHFCFCAABGHHHHHFAFABCCHCFCAHEHFBFBFHCGFBDGDEBHBHCECGDBAFHHHHHDH,False +720,9.0,6.0,1.0,2.0,6.0,3.0,3.0,2.0,AAABABDBGEHAGABCBGFHEAEDEAEFEFBA,True +721,4.0,4.0,5.0,4.0,1.0,4.0,3.0,0.0,BGBCACGCDDFDFABACECBFAFDG,True +722,16.0,8.0,13.0,19.0,18.0,17.0,9.0,17.0,DFEFCHCGADHDEDAHEDEBFHFEFEAEDEDHAHADCBAFACAHEHDCGCGCDCDHDFECEBEDEDEFGGABFBFGCACFDFAFBDGFHCADHEHEGDAEAHHHBHFHFADCFEBGA,False +723,20.0,21.0,15.0,7.0,15.0,20.0,22.0,15.0,AFCDCFCFGFGAGBCACBHAAFGFBBEEAEGHDEDBHBHEHBCGEGFACEGHGHGCGEGECAFFGEGEGEGBBFAFDCBCFCFADADBHEAEHGBGHGBAFAHCBADFBHBCBFAFHBABABAFABHFGFGEHCG,False +724,22.0,23.0,14.0,13.0,20.0,26.0,11.0,21.0,DEBABADADEGBGBEBHBCCAAEAFFDAAAAFEFAFGFCFCBHBCFFFCFBFDFEHHDHCHCFDEDHBHBGAACEFAHHFABAEEEEGBCHCECACGDHAFDFHFHFEFHAGGGFCHBBDBHBEBFBFHHEHBBBABEEFGFEDGDAHAE,False +725,21.0,25.0,25.0,29.0,21.0,32.0,25.0,20.0,FGGGCGEGDFAHHHCCCGAEABFBEBDBDHDCDEDAFGDGAEFCFCEAEADABCBGGGGGCDCDCFFFEHACBCBCGCFCFDBDFCFAHBDDFDFBEHEADCDFHEHFFEGGDGFHEGEBBBDHEAEAGAGAHBHAAGAHAHDDCBCFFFHFEDGDHDBFBEAHBFBEDFCHGFGDCFEGCHCFBFDEDFDABBFBCB,False +726,16.0,20.0,16.0,17.0,10.0,18.0,13.0,17.0,BBBBGCACACBFBABFBCDHGBCHCBADABFCFCFGAHEGBGEEEFDGDFAGAGCBCEFHFHGHFHAHFDFCHAHAGEBDBDGDCDCHFHBDDADCBFADEEEHHDGFGFHADEDHFHCBCBABADF,False +727,10.0,29.0,22.0,26.0,22.0,17.0,21.0,19.0,BCBCBCBDAFHFCECDCDCBHECFCGAGDGBHFDGDGBGBEDEDEDBCBAFAGHBHDHAADBDCGFGHDBDEGEFBBBCBEBEHECDHEGDADCDHDBBGCEHFGCAEAEBEBFBHADCECFCFEDGHGHBHFHGHBCFGBCEFDHGBGFGEBEHEFFDDBDECGD,False +728,11.0,13.0,13.0,11.0,13.0,20.0,15.0,18.0,EFFFEBCDCHCAAAADFHFHGAFDFHFCFBEBGCGAFBCACAHAHEDBBGEDEDCDGBGFGFGCHCFFDHEBBCGGGGGDFHAHDHBFFCHHDHEHEFBHBHECAGEGEFEFBH,False +729,26.0,25.0,13.0,24.0,26.0,16.0,21.0,19.0,DBDFABGGFGHEHAAAAABFBFBGBDBABAGEGCGFEEGEBEDHAEDCHABCDEFAFAGDHHAHADAFAFGBGAGHBDGCHHHBFFEAEDBDBEHDBBEDDHDHDCBCBEHCACDHFCGAGEGDDBEBEBEAGAEADABAFFFFEHGCGCEEEEBEGDHDGECEABHDCD,False +730,16.0,17.0,13.0,13.0,6.0,15.0,8.0,16.0,CCHDADACCDBABEBHDFBEAGBGFCECHBAAEAEDEGCHCHAFBHGHDBDADAFBDBGBHCHCAGAGHHCDCFFDFBFBADFBFBFHAAADBFCFGFBFHHHH,False +731,16.0,23.0,24.0,23.0,24.0,17.0,32.0,25.0,FFFFFFFDDEDGGHGHGHGFDHBCACGEGEBEBECFFBFBDECCDEHCFGEACHDHDHCFDHEGABHEGBGEAEHBAGCGHGHEEEDEDHFCGDGBAHAGAGDGBACCEAGAGAGAHFBCHCGCDCHCHBDBGBEBGCDFDBCBHEHEHGCGHBCBCGCAADDDGHGBDEDEGBBDFEAEGBCH,False +732,2.0,3.0,2.0,0.0,1.0,3.0,2.0,1.0,FCFGFHCBGBAEAB,True +733,6.0,2.0,3.0,2.0,1.0,4.0,1.0,4.0,BFFCHCHCHAAFADBGFDAHAEA,True +734,5.0,4.0,6.0,8.0,4.0,8.0,3.0,7.0,DGHGDEDEFAFBFBDDEAADFDHCHFAFBDGHHHHCCCCFCFBEA,False +735,11.0,7.0,8.0,6.0,4.0,4.0,8.0,5.0,CHCACAGAEDFDCBHDHFHBCDDHAFGGGCACAGAGBBBGBEBDFAAGAECEA,False +736,20.0,16.0,16.0,26.0,10.0,23.0,15.0,12.0,BDBHCCEBDBACHCDFGFCADHDFDHAECDAGAGCFEFCFEDDDDDDDCFHHADFDABEGGGAGAGADABAFCFAFDBEBEGACADDDHAHBECHDGBGBDDEGEGDBFCFHBADGHGHFFFBFAFAFCFCFBFCFBA,False +737,23.0,11.0,24.0,14.0,10.0,9.0,22.0,11.0,FHADCDEAAAABDBHAFADADFCGGGHGAEAHCGDDCDCDHAHCGGGGCACFCBCBCGCHAAFAHEBADAECGCGCGDGECEDGBFCDBAGACFHAEGCGEGBGCECHGGFHFABABABCCDCE,True +738,26.0,23.0,28.0,29.0,22.0,16.0,18.0,26.0,EHDFFHFHEAFFBBEHDBBBDBDCGEGEGCBCDGHAHDEDEDFAFGCCCACBDAGAEFHFHADAFHCDCDBDHAAAAAHCHCHFHFEFHCHFBAEDHCBCBCBEBDADGDAHAGACACBHEDDDEHCHBDECCGBGBHDCDHDBGCCBGDGCHHGFBAEGEAFACACBCEEEEHEGCGAADAEBGDDD,False +739,8.0,2.0,10.0,6.0,9.0,6.0,10.0,6.0,CGBDCDCHHEEAEACAEEGFHFDDDDFGFEAHCCCCCBFGAGAGEFAGAGHCEGEGH,False +740,11.0,8.0,17.0,13.0,9.0,9.0,18.0,8.0,BGAGBECGDGHFHBHBGDGDGCCCCCCFCFDFAFHBDADGDGBBCACAFEDGDHCECHAEEEBDCGGAGFGCGDAAEDEACHEHCCFGAGDGF,False +741,4.0,2.0,8.0,8.0,5.0,1.0,3.0,4.0,CECEAEHCCADDHDHGGEBHBECFCDDDDCDAGAC,True +742,2.0,9.0,1.0,2.0,5.0,5.0,1.0,4.0,CBHEDBAFFDBABEBEBHFHBHBFBGEFE,True +743,18.0,19.0,21.0,21.0,22.0,11.0,26.0,21.0,EAACDDDHDGEGBHHHHEBEBABHEHBFGCGDGEGCDCDGGCGHFFDFBBGACADADHHADCDGDGBCCCBEDECAGHGHBFCFEDEDEGGCBEFEBEBEHADBHBGGGADADFGFDAEAGBBHGDBHGHCHCACACAEFEGHCECEAFHCHBGEGECA,False +744,31.0,23.0,20.0,24.0,21.0,22.0,28.0,21.0,DADEBEBEDADABCBFGGGGGHGHAFFGBGBGCGDGFGHBCCFDEHEADABAGGBGFCFCAGAHHEDBHBHFFEHAGAGBCDFAEBHDDDDEHHACFBHDGDGACFFBDBAAADAHAHCHCEGAHAGEEEEEBHFFGADABABEBEBCDCBHFHFAADFCGCGBAADDDFCCCHFEFECEAGACAGDGFE,False +745,5.0,11.0,15.0,7.0,10.0,9.0,7.0,16.0,EFHFBCACFCEHBCBABABCECFHHHHFEFHCHCFCBHHGGEGEDDDHAFGEGCBDDDHEEAFBBCHCHEHGHBCBCDCG,False +746,1.0,0.0,6.0,5.0,2.0,2.0,2.0,0.0,GDCDCACECEDFDGCCFD,True +747,14.0,8.0,8.0,12.0,14.0,15.0,12.0,12.0,HCHDFEEGCBCDCAEEEBEFEFCABABFBFDEGFAHEHAHCHGGFCFDEDAHCHDFDGDGABHEAAFAFHFEEGAGDDFBHBHGDGEGAGAFAFD,False +748,23.0,22.0,15.0,27.0,27.0,24.0,31.0,19.0,CFEFAHGBGDEAEBEAEBHBDDGBFAHCGFHFHGEGFAFADBEFHBEBCCFCGEGADBBGGCGBGHHBEGEGABBEEEAHAGEGFGAGFCCBFAGBGFGFGFADDBDBGBFEFGFAAAABHCDDDDDDFDFHFHBGDEAEDDDEDEGEDEDECHDHCFAGAHAEAGADFGHEHDHCCGEGEDBDFCHC,False +749,18.0,23.0,17.0,19.0,17.0,23.0,21.0,21.0,EAADEDBDBFBEECFCDEGFDFHBDAFFBCCCGCHCHAFAFAGGHGECECEBEGAGDGDHEFEHCBAADAFBFBHBABGBGCFCDHFBDEDECFGFBCHHDBBCHDGDFFBFBGDGBHHAHABADADEEGHGHBHFFFFEFGCGCDEHHGHGAAAGBBH,False +750,26.0,15.0,24.0,31.0,22.0,18.0,27.0,36.0,HFCEEEDBCEHFDCDCDGDAHEDGBCCDCGHDEECFHFAFADHFCGEEAEHEHECGABAHFBFBFDACBDBDCDHDHGFBFACAHAHABAHHHCDGHGHGHAABFHFGGHADDDDDADCDEDGDEAGGGGAGBGACCHBHBFDDEEHEDDHCHCHCHGFGAHHHBHFGCGHEEDEDFBAGHGHCECGCAHAGFEADAGA,False +751,2.0,2.0,6.0,6.0,5.0,4.0,2.0,6.0,DCHAHGHCHCEBEGDFCHCDCFEFEDEFHADBD,True +752,12.0,16.0,4.0,9.0,13.0,13.0,11.0,4.0,EBEBDBDBFAHAHADAGBCBFHEEAFAEEBEFGFEFAAAGGGBAFCFCFDGEBBBBBBGAFEEDDDGAGFGCEFEGBDDFHB,False +753,20.0,22.0,13.0,25.0,23.0,25.0,27.0,11.0,DBDAFFDEDEDEFEFDBCFFHDDEEEBEFDFEFEGBGCHCEBEHEHAABAGGGDEAFDFBGGGDFAFAFACHEEBHACBFECCGGGGGGFDFAFCGEGEFHBDBACAHAEFDBDFGABFBEGCGCDHDHDGDBDBDGCFBGCAHGDGBBFAFABEGEGABADADGB,False +754,13.0,24.0,24.0,21.0,25.0,16.0,20.0,11.0,BHBDGCGFGFGFGHGHBFGCEEFEFBAHEHEHEBCDEDEDBBCBCEFECGCDBACAGDGDBBHCCGDAAEAHCEFECABABDGDGCBEDHGFEDEDBGGCACDDBEBCBDFGGGEEHECECEFDFDBBBDCHAFDCBCBCGCFFACAEAEDBFE,False +755,21.0,23.0,12.0,20.0,22.0,23.0,13.0,24.0,FBFBCBFBFECEBHBHDHBBBFBACGBGBDAGFDACHHGCGHFDBHEEEFEAEBEBFGAGAGEDDFDFEFBCAFDFEAEAEDFDBDHECDCFCEAHAFEEHAHGHGHCBDAEGHBDDDBDEHGBAHAFCHGBFHFHEHEADHFHFHFDEBCAAAAHAD,False +756,9.0,16.0,8.0,17.0,8.0,7.0,7.0,4.0,EFEFGFGCCBABHBDDDDGDABBGBFBFEACDBDEDHCGEGBCBCBFDDDEAFABADAHEBADHDCCEDGDBBBAD,False +757,15.0,20.0,18.0,27.0,18.0,16.0,16.0,19.0,GHFBGBCEEAHDBDAHAHEBFFDDDDBFBEEAGBDHDBEGHAHADDEDCFCFBHAHBHDDGDGDECECGHGFGDADEFCFCFDADBGEEBCDEDGABABHBHBHCDCECECEGACCEABFBFBCCHABGHFHFACDDDDDGHECGFGFH,False +758,24.0,10.0,20.0,10.0,13.0,18.0,25.0,18.0,HEHAHAFAHCGCGCHEBGCGHGHGFGCGEABGHGFGHCHEAACABAHACFEAGCECBGGGGGACDFHFAFDFDFDFBEEAEAECFCAADAGFCHHECFHGAGHGEAHFGCCDBDBGACAGADABBDBDCFAFHGEFCF,False +759,5.0,2.0,3.0,3.0,1.0,2.0,7.0,3.0,CFAGGHGHGHBDGDGACEDACAGABF,True +760,23.0,15.0,19.0,10.0,31.0,25.0,21.0,16.0,FGFGHGDGBHACAFAFEFEGEBFGFGFECEDBFEFEHHCFAEACFBBBAFEDCGCEAECFCBBHEGEDEAEFBFGFGADCCCBHAAEEBABAHAHACECFHFEDEABFEDEAEBECACECGFGFEAGAFEFACHGDGAEAEGHHHHGDCBEDEHFHGGCG,False +761,4.0,5.0,6.0,6.0,5.0,5.0,6.0,6.0,EFBFBFGDHCHFEFGGBDAGACHCHDHBAAECCBCDEDEDGHG,False +762,5.0,7.0,14.0,5.0,9.0,9.0,6.0,9.0,EGEFHBHFGFHCEDEBEFACAEAECHCHCHCHBGCFDFCCACBCDHDFGABHBCECDGGEFCFB,False +763,7.0,10.0,9.0,14.0,6.0,13.0,15.0,4.0,FHBHAHAFAEDCDEAEHFDDGFBFBFDGGFGBGBCBFDGDBCGEGECAGAGDGDFDCDCDFGCGEBDGFBACFBFDCG,False +764,18.0,17.0,21.0,10.0,17.0,19.0,30.0,14.0,GFCBGAFBBEFFCGHGEADAHFHEAEAHAHFGGGEGECCFAGAGFFCACBFAFAFGGGAEHGHFHBHCACHFAFDEDHGEGDFBCGCAHGCEBEHCBGBDDCAGBDAGECECACBCBCGGGBBBBBECFCFEFHGDGDGDGEGEGC,False +765,16.0,9.0,24.0,14.0,21.0,12.0,17.0,12.0,FCCCCEGDGDFBEGCBCDDDDCHFGACDHECCCEEAHGHGCCCFEAAADAHGEBEFDDDCDCEAGCGDHEAEAGADAGEFCFCFGFGEAFHEECECEGHGBFCECEBFBCAEBGBGHAHAHAHBE,False +766,2.0,5.0,3.0,5.0,5.0,3.0,5.0,14.0,GCCBCDHEEEFHHEBEHGHBHDHDHAHFGAHDGDGHHHHBFB,True +767,25.0,19.0,25.0,19.0,30.0,21.0,34.0,24.0,AABAGCCCGCDFDAEECGCHBHGHGHDAGCGDFDCEGEBAGFEEEHHAGAGAGFECEHGCECEHFHABEEEBEFEBEFEBCGGGDGABEDEDADGFGFCHHHHDDFBFBAEAEAHGFCFAAAAABAFHECGCDCGFADDBHBGCEHFBBGDHFAFHBHCHFHAGGGGGGAGCGEDEBEDECHFHGBDEDBFGCCCCE,False +768,25.0,18.0,18.0,14.0,17.0,14.0,28.0,21.0,DBBECABABAFFCHGBFEAEHGGEEEHGHGAGADAHGCCFDFDGAFCECECDBBBFBDHHGHEHBHAHGCGFGHHCCFAEAECGAGFHHCEGGGCDCEHEHEDGDHDAGABACCBCBGFFBBHBABADAGGGGHGAGAGAECFBAGAFADAEHDD,False +769,1.0,3.0,1.0,7.0,6.0,6.0,6.0,3.0,EFGFHFCEBGHFBDEDEHEAFDDGDGDGDGBEF,True +770,10.0,20.0,19.0,21.0,15.0,21.0,16.0,16.0,CDHDGGGCGEGECDCDCDABFBDBFBFDFHFHDDBEAEHBGBGCDBGBCHHDGFGCHDHCGCAAHABAFHHBDEFEFCFDFCFCFAHEFBFBGHGDDDCBEGGFEBEAEBDBHCHAEFCDCBFEFEBHCGCBFDFDEA,False +771,4.0,6.0,5.0,4.0,2.0,2.0,2.0,5.0,DBACDGDBBHBHCFDECECACAHAHGBFBH,False +772,20.0,21.0,27.0,26.0,23.0,24.0,13.0,18.0,HHGDAACADHDEDCABDHDFCFDBCFCABDCCCCFFFDFBCBHBGEGHGADACFDGAADDDDDECEHEHDFEBEFCFHFAFCFCFAFCHHHCEBEBEGECECFCHEFDCGBAFADAEAEDEDEFEHEGDAAEBCAEABBFBFBEADGCHDBGBDCDFGGBCBCBEHGHCHBF,False +773,23.0,11.0,12.0,12.0,15.0,10.0,15.0,14.0,HHBEBEDEBGBDFCECGCGEGCHDHGHGBCHAGAGAFAFAHAEEEAEAGBGEGCGAACABBHDABFDFAHADGHFBCDDHAAEAEAEAEACDFDEAAAHFDCCGCHHGDBFF,False +774,17.0,24.0,28.0,15.0,15.0,16.0,18.0,18.0,EFEFEBGCDADCEHBHBHBFBECECBFBFCGCEDEDCCFCGCGFGFACCDFHAHGHBHCHEHECCCGGFCHCADBBBGHHEGCCCGCBHGEGBBBAADCDCDCDADADABFHFAGBDBAHGBBABFEFGBEAHBGCCHFHGDABACAFDEA,False +775,3.0,0.0,2.0,1.0,0.0,2.0,2.0,3.0,AGHGHFDFCHCAA,True +776,17.0,9.0,11.0,6.0,12.0,12.0,17.0,14.0,GCGDABAFGFGCCECFABAEAEBGADHHEHAAAEDEAEABDFCGBADAEHGHFFFGAGFCFDBHBFGHHCGAGHGEGHBHCECEAEAGFCFCBHGHGH,False +777,4.0,6.0,1.0,5.0,7.0,2.0,6.0,4.0,HEFEAEAEDBBGDCDHDFEBAAHEHEDGBBBGGGG,True +778,6.0,7.0,4.0,4.0,5.0,13.0,4.0,5.0,HEHEAFGFAFAFBGBAFFFDEDECBCFGDBEHFAFBFDFHFHGBACCB,False +779,9.0,7.0,5.0,6.0,9.0,8.0,7.0,9.0,DGBEBEDHAFAFHFHFCFCEDEGEDEDGHAFBHBAGAFBCBHFAGADAECCBGEGHHEHA,False +780,19.0,21.0,16.0,16.0,23.0,19.0,26.0,22.0,FFCAGEGEGAHBBEBEGCDFEFCFGHHDHDHDBEFFAGEGAGAGAHEHFAEDBACCCEDGBEACFCFEDEABABABFHFBGBGAGEHHACBCGCHCHGHEABACDBDHEGFGEADHFBDCDCEBBAGHGHEHEHGHDHDGDGFHABECEBDGGFGBGBEFFF,False +781,15.0,24.0,23.0,18.0,23.0,14.0,17.0,21.0,FEAGCCBABABAFAHCDGHFCAEGBGBGHHBBCBFBABAEDEDADHFECGDGAHEBEBECCGCHCHEBCFEDDDCGCGDGDHEFGGCHCBEFECAHDEDFDEHEGEFBBHGGCECECFBDBDBAHAHEHDHECFBFDCECABABHBGBCHFHDHE,False +782,14.0,24.0,23.0,18.0,18.0,17.0,19.0,17.0,GAECGCBBAGAGAGFEEDDFBEEEBBGGEECCCCBEGEGFGDGCHCHCHEADBDBHBHFGADBFGDHHGAGADDDDDCBCDHFBFHDAGFHFHFHCBCFEHHHBFCFHFCGCBCAGFEBDFCECHCACBDBCEAGDBDBEBEBEBABAFC,False +783,17.0,21.0,14.0,26.0,20.0,11.0,14.0,15.0,CHAHEHDHGCCADABAEDBDBFAEABGDDCGADADBBAFCEGDBEBDHGEGFHEHEHEFCFDGHADADBDBDCDCGBABDECEDEDFDCDCDADEDBDHGBGBECDHEHFFBAEAEBEBGHGEBCGGBEFHBHCFAFA,False +784,9.0,13.0,21.0,19.0,11.0,19.0,13.0,15.0,ADHDFGEBBCCDCDCFHAGDBCBCECEAGAHCDEAHBHEFEAHHGDCHCHDHDHFBEADFCGCHDHAFBGBGBEFDFGFECACFEFGFDCDEBGBGCFBFCDGDGCFDFHFHFCFCDCDB,False +785,3.0,4.0,10.0,4.0,5.0,8.0,5.0,7.0,FCFCGCGEAAGFCECECHFFDHCACGCGEBHFEFHBHDFDBDBHHC,False +786,13.0,15.0,20.0,21.0,12.0,14.0,14.0,18.0,BFDGDGDADECHCHCEDGDBDGHCHDGCABEEFEFGGDDBDHDHDGCCEBDFDFBHBHBHFHFAECEBAAAFAEAHBHGHDFEFBHBABECCCCCDEGHGBFFGHCDCBGDCCCFHDCACAFGHADA,False +787,12.0,21.0,22.0,19.0,22.0,24.0,29.0,14.0,CGCGEECEGGBEAGCFFFCDCEEACFBFBGBGDGDHDHCBCGADEHGHBFGFGFDFDBGEGEBFCFCFCFABDBCAFFGDGBFHCHEECDFDFCBEBFHGCGEGAGAFDFCEGEGEAAHHHBGCGCGAGDGDBDFGEDBDFDBCHADEEGEHEHABBFEHBCB,False +788,17.0,13.0,19.0,20.0,16.0,16.0,19.0,15.0,BDCEGHGDAFFHFHDADAHEEEECFCGDHBHGGGAGAEFGBCADGCCCCCCGCDCBEFEFDFECADABAFEBGBGAADGEGHADABHFHFCEDHDGGCDCDFDADGHCFBBCBCEHBHFHDEDEDEGHGAAAFBF,False +789,28.0,17.0,13.0,32.0,28.0,13.0,27.0,17.0,AEADADBGBAFAEADGBAAGDDEGEBEFCFCFHFHAEGEHDHAADEDHDCFCBAEGEGDGCGAGBGBGBFDDDEDGBGBGBDDGGADCDBGAEAGDBCADEDHBABAECHCECAFEHAFACDCDGEHEHFBEHDDDDFEAABDHGHGHDAGECEGEGDHEAEGEGEAFHDHDFAE,False +790,20.0,14.0,14.0,14.0,17.0,15.0,16.0,18.0,FCFDDDHCHCEGHADCBGFEFCFEEEEBEADABHBDEFCABABAGAGEHHBHBDAECGDEAAAFAEADBHCGGBGBGBEFEFEFABAGFHHGACDBDHHGFDACEHDHGHFCFDHCHCHCEFAGAGAG,False +791,18.0,17.0,18.0,19.0,20.0,20.0,6.0,18.0,FHFHFDEAADAFBBACGHDCDFAGGFEFADEDBFBFECEAFAFACCCEFHBHFHBBACHFDGDCDHDHGBAHCDCBHBEEEEAECBABCBCEDHDFDEDEDEAEADACAHFHFHEDCCABEHEBEHCFBFGFBDHC,False +792,14.0,17.0,13.0,12.0,11.0,16.0,16.0,11.0,DDBDBDAFBDBFAFAGBDEGCCECHCHCGFABGBCFEFECHFBABAEECBDHDGDGHGHGFCFHEAEGDHBCBEFHBGAGACAHAFGFGFDEABFBABGFGFGBHCAEDC,False +793,9.0,19.0,17.0,11.0,13.0,16.0,16.0,13.0,DCGHBFFCGEEBEGGAGFDEEBFGHCHCDFDBCBCFCFCGCGBBBCBCBFHFGCAEABHBABGBDBDFDHAHFGFHBBBGHGHECFDECEGHGHDAAGDBCECDAEAEFEFCFH,False +794,18.0,14.0,23.0,18.0,18.0,15.0,28.0,20.0,GBGBGFGAEFECEBGBECECFGDEDGFCFGGHCHCFGDAHHCHCFCFCGCGCEAHAEABACDBDBAGGCGHAHBDFDHEHEGAGEGEHHDCDGFHBHGHFADECACAEABFCAHGHGBDCDFDFBAGACDGGCDBGGADHDBFHEHEAEGDCEC,False +795,2.0,6.0,5.0,6.0,3.0,1.0,4.0,1.0,GDGECBCHDEDECBBFBCBABDGDGACD,True +796,20.0,15.0,22.0,19.0,22.0,17.0,35.0,28.0,EHGHCDCDAEBCBFBACHCGEFEFEFDFHGHDCGAHDCGCDCACBGEEHEHGGGEHEFEGGAAAAHAFFECCAGHGHGHBACACDCFEAGGGGGGGCGAFCBEHHGDGHGADAHGHBDGAGBCDCABAHDDEEFGGEHHHBBBDBDHDHDHFHEHBCDCGFGECEFFGFGEGHFBEDA,False +797,22.0,14.0,14.0,13.0,13.0,14.0,15.0,9.0,HCHGGBDEFAFAGAHDCGCGCHCGFAADEDEABAGABFEFEFEBDFGABHFDAABCHCFCADBBAGDGDGDCDFEFGBDBDFFGCBCBEBGAAAAAAHEHEBEGCAAAFHECEC,False +798,15.0,14.0,14.0,26.0,14.0,22.0,16.0,23.0,DCGAADDDHDHFFDBGGFGEGBBDHAHFFFFAFCFBDDFEAEDHDHGHGDCHCFAGBDFCFEFGAGHECFCEDAHAGEBFBABDEDADCDHAFCFAFHBDFAFADEGEHEHBHGFGCGHGCDCDBBHHHHBCBCHDEDEDEDHH,False +799,27.0,20.0,19.0,24.0,17.0,17.0,26.0,21.0,GFGDGDCDFGBGBEBGBHHFDADAHEHEBBBHFFGGCADACAGHBHAAFACACHBECEFAHADGDAEHECFABCGCAHBHAHDGEEHFDFHFDFCAHDBDBFEGDGDGHBDBGAGEGBGCCECEBEHAGABADADADECGCGCAFHGHBFACACFDEDEBGACAGHGFDDD,False +800,14.0,22.0,27.0,22.0,29.0,27.0,20.0,20.0,BCBCBCACACAHDBFCHEHEFBGGCGCABBHBEEEBECECBDHDEBAACGCGFGFDFGBCDAHHHHFFEDDDDEFFHFDEGGGHEAEDEGBBDFEADFCGCGCHFHGHGEDCHFFFDFDCHFBCBCBCEEEGACAEHEFGFDFCFBAEHECGDEFGHGAFAEBBBBDCEHFCFEFDCDEDE,False +801,5.0,1.0,4.0,0.0,2.0,1.0,0.0,1.0,HCAEACAFBEACAC,True +802,15.0,14.0,17.0,11.0,11.0,11.0,14.0,5.0,DGAEAFAFCFDADEFEFCACGEHEFGCHABACABHBADDFDFCGEGEAAACHCGDGCGBEBFDCABBBBDBABFGGCCCEGFBBBEDAHCGCGCGCED,False +803,19.0,24.0,22.0,27.0,21.0,24.0,25.0,26.0,HFAFEFEFCCCHCHGDDHEHEDEACCFAFBHDEDEBGCGBFAHAHAHFGDBAGAHBHFEFBFEFABCDHDGACACBGDGHAFBDBCFHFHDHDGDADBCFGGBDACGHGCECEGGAGDGDGEGECADHDABGBDDCECEHFHBGGEGEHBFBDHFACAFBBBBHEEEGCDHGFDFDFEFHDHDCBBBC,False +804,14.0,12.0,12.0,16.0,9.0,14.0,9.0,8.0,ABCBAFDEDFDHDCDBAFCBGBDBEAEGEBCDGAACABDECECEHEAGHGDBHFFFCGDADFFFGFDBDFAHCHCHCHCBADADADABFFGGEF,False +805,10.0,5.0,7.0,4.0,17.0,8.0,9.0,3.0,AAGAGAGAGAHECEFEGEHEBEAEFDADFEEEECEDECHGFEFAFBEDFGBEACBCEFBCCGG,True +806,16.0,25.0,13.0,17.0,23.0,16.0,21.0,18.0,CBGEEFEGBBBCHGHBAAAAGAGEGCHCEDBBBBBHHHHDAFFEEDEDAAADFEBHGHDHEGEGHCECEBBDADGGGGGDGHEHEHEBBBFGFAFDFEFEBEBCFFEBHBECDBDFAFAGHDFDGBHDCFCAABCBHEGDGDEBGCCAF,False +807,3.0,8.0,5.0,8.0,9.0,8.0,9.0,9.0,HFFFBHCHEBEBEBGBDCGCECEFDFBFGAGHHDHFACHDHDEFBGDGEHEADGDBEGG,False +808,18.0,19.0,24.0,19.0,15.0,25.0,23.0,17.0,CDGFCFCAGHEAEADCGEGACBGFGDHEEECACECECFAHAFDCDHDFEBEHDFDFHFGBEBGGGBBBHBHFAEAFGFAHAGAFCGCHCHGHBCDDFDFDGDFBEBEBFAFCFGDCCHGHADCBFBGBGHFCGDGBCAHFDFCFCBCBDAEABADGFGHC,False +809,24.0,16.0,20.0,18.0,20.0,16.0,26.0,18.0,HBEFGCGHAHADGCACAFBFAFCEBGBFDGAGAEHHCDDHDFDHDHDEECGABCBFEAEHDGGGGBABGFEBCAEGBCFCHGHBHBABGBHFEFCCCCAHGEGEFHFDGAEBHDADCGHEAEAEAEAEGEDCDADGDGAGAGAEHDGCCFCFCADBGF,False +810,7.0,10.0,7.0,14.0,17.0,13.0,14.0,8.0,DEAEGEFECACABGEGEAHGHGHAEFEFECHDDFDBDBCBDBDFGCGEBECEDDDADBEFEBDFGBDFHGCFFDGGFEHEHFHBGAGEGF,False +811,11.0,12.0,11.0,18.0,16.0,11.0,15.0,16.0,EBEBABDHDHDHEHGHFAAGGCAFEDDGEFAFHDBDBDHEGGGGBCBCFDDDDDEDBHFEBHCHABEFEFGHECECBFGGGEDHCHCGEGACAEAECHABCHDADFDFHG,False +812,7.0,8.0,5.0,1.0,6.0,6.0,5.0,5.0,HHHHAEACACBEBCCAFAGEFCFDBHBFBFEGAGEGBGFABBE,False +813,7.0,6.0,14.0,17.0,20.0,8.0,11.0,16.0,BCHCAFAGAHCEFEDEHEDCHGHAEDGDFCFHGHGHAEGEGFHBBDFEHEDEDHDEDEBGDDFBEHGABCEDECCCADGHEHEHCHCDCDCDCEEGEFD,True +814,27.0,14.0,15.0,25.0,17.0,16.0,12.0,25.0,HFFCACAHFFCBCFFGDDECEFEHCBCBCDAAAGAHAHDECEFHAHAHDEABBEBCFGBGDEAEAEADGHAHACDHHHBCBEDFFAFHFEEGAAAAAHAHEHEDDDDGAGDHDBDFFAHDBACACAGHHDGBGBEDDBDHFHECGDDDHDH,False +815,9.0,8.0,11.0,6.0,5.0,16.0,9.0,7.0,DDGCCHAAADDFEFBHDFFFDFCFCFCFEBEGGGCFCGHGHEAAAFFHBCBGBEBCBFFFCFCAAGAHHGB,False +816,27.0,23.0,14.0,24.0,26.0,27.0,25.0,22.0,DABHHHEHAHAEFDBAGABDBGHDAAGAGFBAHAHEEDABFGGEEADAFBCACGCGCEFEBEBDFDCDGDEFEHEHFAGAGCBCGCBCBEDAGGBABHDFBFBDEHEHGBFEFEBDFHFHFDEECAFGFGFEADHDAGAGADCDCHFHCEADFDGEAFBFCFDBEEDGAGBEFEHDHGAGHGHFBFBF,False +817,1.0,1.0,2.0,2.0,3.0,7.0,3.0,4.0,FFFFADHDHEHEGCFBGECFHFG,True +818,10.0,14.0,17.0,5.0,12.0,5.0,16.0,9.0,CACBHAACABGDCAEAFGBEHEGCGCGEGEDBGAGFHBGCECEFEGEGBHBFGAGHEABDFDBCBCBHEHGHGBDCACBGBECCCCCH,True +819,20.0,12.0,13.0,11.0,16.0,13.0,21.0,6.0,ADCECACDCEGDFFAFBGBGBGBAAAEBEBGFDADEDAACACDCHHBGGGGGGGEGAAHFEFCGDGBCFABAFEGCDHFECEDEHABCDAHFGAGEGAGAEAGBFBCEFEFE,False +820,24.0,22.0,18.0,21.0,20.0,19.0,14.0,22.0,ECFBHAHAHAEAFBFGDGDCBCGAEAHABCBHFEDEDGBCDCDADABAEAEBHDGDHCBAHFDCDHHBHEGAAFAFCHCDDEHBFBFDGDGHBAFCEDEHFCEHEHEHGCGAHABCBEFHFGCDCDFBFBFAFGBDEDAGCHBEBCBADAGEBEAEAFFH,False +821,24.0,21.0,19.0,22.0,19.0,13.0,20.0,29.0,DAHAHAFEGCDEECECAAEHEFDDDGAGAGAGABHBGEHDHFHEHAHAHAFBHBHCAADCEBBGDECHGFGHGAGEDFDFDHHHCGAEABFDGBECECAHACFCHGFBDHGFDHBHDDDDGGHEHAHBGBGBHEABBFBDBFBDAEEBECCCCCACHCBCHAHDGDB,False +822,16.0,25.0,27.0,23.0,14.0,15.0,16.0,28.0,BHCHCDCAGFGAGBFHEHBABGDHBABFBGBDCHCHCHEHAHEHCHDBGBHACADADAFFHAADACBCBEGEFDFDFDFCHEHDDBDEGEDHHHCDEGHCFGFDEDBBGFGCGHAHBDCECHCABHFCCHCDEDCDCGBBEHDHBGBFEFCACHCBBABCBDGC,False +823,19.0,16.0,17.0,19.0,13.0,21.0,12.0,12.0,AAFGBDHDCDFDEHBBFHFCDCABBFDFGEGEBCHDDDBDGDACAGABEGECECECEFEHCHAGDDHCCDAEFFAFBFBGDAEHHBABAHADABGBFCFGDCDFHFHAGAFAFDFBACACFGFEFECBC,False +824,23.0,14.0,24.0,16.0,17.0,21.0,26.0,11.0,EEEECEBHDFDBDCFAABFDEEGGCGEGFHDGAGBCFCHCFAFAGAGFFBGAFAEABCGAEADADAHBBEHCHCBCBCDCECGHBHAFDEDEAAACACFFECEFFGACCDCFGGCGCGFDFHFGCGCGAEAGGHHFBFDADABBCGGGDGDG,False +825,16.0,23.0,19.0,19.0,25.0,21.0,19.0,16.0,BCECEGEHBGBGDACADFFBABGGEBEGCGAGDBCFCEADAEFEDDCHCDEDGBGCFHFGBEBEBEHCHCEBEDEBFBFEFHFHFGDEAEBGBEDDCBHDFGFCACAGAHBDBDBCCFCFAFDDDADHEEEFHAEAGBGCAHHHEHFGFBFGECHABF,False +826,8.0,5.0,4.0,4.0,6.0,3.0,1.0,4.0,CDGDCFEEEEABABADAHBFBHACAFHEAEAHCBD,False +827,24.0,26.0,18.0,19.0,16.0,34.0,27.0,29.0,CFAFCHHGFDHDBDBDCDCHEFBGBGBHBDADCGCGHGFDFBAHDDAFECBFFFHFAGECAHAEBEAAACGEGHGEABAFGCEAGFFHFGACBGHGAFHCHGHGBFAHGHBHBGBGAGCFBEDHBFBHEHEBFGECEADHFHFHFDABFEFHFEFBFBABDBDFDADGDGCAEAFCFCFCDAGGFGFBHHHHB,False +828,2.0,3.0,1.0,7.0,4.0,6.0,1.0,1.0,ADDDFDFEFEDEBFBEGFDADFHCB,True +829,18.0,8.0,19.0,22.0,14.0,21.0,12.0,12.0,EGEGCHAFEECHDBDBDCFAFEFDFEGEAFCFDADADCHFHEADAEHDHCCFCFDFHFDFDACACACEFDFDGBFBCGEGFGCGCAHADACEDDGCCACHBABDBHAHFFFDDHACBDEAEGGGFD,False +830,14.0,17.0,12.0,13.0,7.0,7.0,14.0,9.0,EGEBHBDCDGECBABADDGCABACFCEBDCCADADFGHGHGFGBGBGHGFDDCDAGABACHHDHDFDCBBGBAAFACEHAGAGBEBHBCBEBF,False +831,13.0,21.0,11.0,11.0,12.0,12.0,12.0,8.0,EAEDGBFBDBCHEBEBEBCHCHAFGGBCDDDCDCBADAFAFABADFCBCGEAEDBAFAEHEHADFHBBEHEFBFGEBHFGBCBCBFGGAGAGBGCGFBDB,False +832,14.0,20.0,21.0,16.0,26.0,24.0,30.0,17.0,BGGGEEEBFFFEFCDGGGGGCGABDFGHCAFFFDFEHDHAGAGAEBEBCBCAGBBDBFBFEEEDDFCCGCGEGBBDBHEDCFCHGFEEBGCFAEGEGECFCGCHEDDCBEDDDHHHCGBGEHEHGDDCGCGBGEGEBEHECGGAEABAFAHAFAFHFHCHCFFFHFBA,False +833,0.0,0.0,2.0,1.0,0.0,7.0,1.0,2.0,GFFCFHDHCFFFF,True +834,15.0,17.0,13.0,12.0,21.0,19.0,18.0,23.0,DEFBAGHEHEABHDFGFHFHCHDHECEHBHDGDGFFCGBFBEEHHCDEFECEDEBCBGEGEGACAGHGHAHDFCBHGFFFFDACEHEBFBHBHGAAEADGGADHHHHGHGFAFCFCGEDFFABABGECACABEBEBEB,False +835,9.0,17.0,15.0,12.0,13.0,15.0,12.0,18.0,AEAFDHGHGFDEDBFBABACCCFCHEHCFEDHFGFDHBHBHEFAACHEDECFCGCBCECEGHBHCABDBEGFDFDBDBEGEFFCCGHAHAHGHDFBBGBGDGHBHBCBFHE,False +836,24.0,27.0,17.0,31.0,24.0,22.0,21.0,23.0,DCGBEBCDEDADFBFEDADADBDCDCDEDFDGBGCGBHBHBHEHEDEDAGBGFDAHGHBCECADBDEDBFFAFAFAFEHHGCGFEFDDGDGFBFGEGEBAHAFDDHFABBBDADAHAGAFFFCGGEECHGAGAEECEBFBCBHHGEFDAAECFADHGHCHBBBBDEDHBBBEHHAHCHCAEFEHADGDC,False +837,8.0,2.0,11.0,12.0,11.0,8.0,3.0,11.0,BHCHEDEHFAFHDHCHFDCDFDFDAAHCFDDADHDECECACECAFEHEGDGEHEDEHFCBCGCAEA,True +838,12.0,19.0,12.0,11.0,20.0,17.0,13.0,16.0,DEFEFEHEFBFECEAEAGBGAFEBEDFGFGAHFHFCGBBBBBBHEFEBHBGBGHCHFBCDFHAACCHEHACDBFEGEDFBCBABHHCHEHACACEDDDDFDGHGHCAGFDFBEEEGEGBA,False +839,1.0,4.0,3.0,4.0,6.0,6.0,4.0,1.0,GBEECAGBFBFBEDCDFDFEEHEDGFGFC,True +840,5.0,4.0,4.0,1.0,6.0,4.0,2.0,2.0,GEBEFEHEAADACACFCFBBHCAGEBEF,True +841,15.0,12.0,13.0,8.0,18.0,15.0,11.0,15.0,FHFHFEAAHFEFCGEHEHCHCBCAEBBBCHAHAEGFGABHBEBEFCBCAHDHBEAFGBHAFEFBGCFEFCDADBDEDEDEGEFEFAACHDHAEACGEGHGCGAGFDC,False +842,17.0,27.0,15.0,15.0,25.0,21.0,18.0,18.0,DBEBDBEEGGGBGEHCACBCBABGEDEDGFAFCCBEDCGGFGBHAHDBBHBHECACEDBDHAAFAEBEDCDCHGBEDECHAFAFECECEFHGHGHBEBGBGBFFFFHFEFHFHEBEGEAEFFAFGBBBFHCHADFDFBABCGAEAGFHDADEBHBE,False +843,20.0,14.0,16.0,25.0,17.0,16.0,12.0,24.0,HBHEDGBFBCADADACHHDHDAEAHDDDDDHFFDHDGCGCBHEGABAHEDEABACDCEFGFHAGGBACGHAFFGDCAAGHDEGEGEDABACABHFDEEBEBDBDBDHDADAHCHBEFEDEDCFCFCHCHFHFHFHFCAEHHFCE,False +844,6.0,6.0,6.0,6.0,7.0,4.0,7.0,2.0,GCECFBDBDBEGHDEAEAFFECECACBGBDADGDGHFABGEGCA,False +845,14.0,10.0,13.0,17.0,13.0,16.0,16.0,22.0,DADFGHGHFHCBGAFEFCFCGDGDEDBABABECDCDBBGAFAGAHDDDDFDGDGDCEGGFHFHCHGAGDHHHFFCGCHHEFEAHHHFHGEGDAHECDCHHAHAEAEBCFHFBFCEHBBEEA,False +846,13.0,21.0,15.0,9.0,8.0,13.0,6.0,10.0,AGBCBCBDGCBFGHABCBCBEBABCGHEHBAFAFDFECDBBAAHBHBHCFCFDBABDCDFFCGHAHBHBEBEBCFCACDEHACEBFDFGFAFAED,False +847,8.0,14.0,10.0,15.0,9.0,10.0,9.0,7.0,DECFAHHBGBCEAACBCBADDEBHDHDEDFFFGEAEBGCGBGDGDFDADBDBDCFCGCBCHABFBDEDGDGBHBFFCFEAEH,False +848,10.0,5.0,6.0,10.0,12.0,17.0,10.0,11.0,DHDEDCDFDFAFAHCFGABAGFCFBGGGGAHCFDFAFEEEEBBABHFAFGFEEHDHECEHFHFEAHAHEDFDFHFDGGGEC,False +849,22.0,14.0,13.0,19.0,14.0,18.0,13.0,19.0,AACFCFBBHBGFDADADAHHCGFBCHHFHBHDGDCAHAHABDEDBDAHAGFGEBEBACHCDEGAFFDGBHFCFDDBABAEEDEGEFEAAGAGABADAHFGFCFAAGCFHEHFGFBFEEDEHEDCDCDCDHHH,False +850,12.0,11.0,24.0,25.0,18.0,37.0,27.0,36.0,GEGEAEAEDHDEDECECGGGEFEFEGCBFBFCFCDCHEHDDGEGFGDHFGEGAGCGFDHCHFHDGCCHEBBDACHCFCHGHCHCHGDFFFFDFHGHDFFFGFGHHHGCDFBFCHHFHDDBACHEEFDCAHDHBHFFFHHCHBHFHDGFGFGBEAHFHFHFCAGGDCBGDGDFFAACDCAFDFDFBHHAHE,False +851,8.0,20.0,9.0,10.0,16.0,10.0,11.0,18.0,GAGAGFFHFHCHGHEFEGADABHBHBFEEEBAHCHCEEHEDCAGGBBDBFGFHFHAHFHBABEHEBFBCHEBBBDDDCDBECEGDBCBEBEBHBGCHEDDHG,False +852,8.0,4.0,3.0,3.0,5.0,4.0,5.0,3.0,CEHEHBGFGBABDCGAGHFDCGAAAAEADAFEFEB,False +853,2.0,2.0,4.0,5.0,2.0,8.0,1.0,9.0,BHFHFHFADCCGFDFDBDEFAHHHHHFHECCFD,True +854,0.0,3.0,1.0,7.0,1.0,4.0,3.0,3.0,BGEDFDHDHGFBDBCGHDFDFD,True +855,13.0,9.0,23.0,8.0,13.0,14.0,12.0,14.0,CFCFCGHEACCCEEEGDHHAHBGBCFCDCDCFFGCAFDCABHCHCDFFCECGCGCAABFDEDACCHHAFAEBEBHGHBHFGEGCGCGAEBCBAGEFEFEFDHAHAH,False +856,10.0,14.0,21.0,25.0,13.0,22.0,18.0,15.0,HDAFAFDFBGDDCEEGEDFGBDBGCCCCDDDGDGHFDGHEFECHCHCFEDBDBACGFBFBFDCGEGCABABDEGCGCECEBAFGHHBDDDHHHGGDCDCACAFBEBECFCFAEHHFFFDGDGHGHDDFDFHFCFCBAF,False +857,5.0,7.0,6.0,6.0,3.0,6.0,3.0,6.0,HBHCDAHAFGBACABHBDBDEFGCHCHCBEFEFGFCFDDBDA,False +858,5.0,6.0,10.0,9.0,8.0,7.0,3.0,10.0,BGCHCHCBDDHDGDGABCBABFECECECDCDFHHCEDDFFFHHEHEAEAFHBEDHCAF,False +859,5.0,3.0,3.0,10.0,1.0,2.0,6.0,6.0,DADADBGHEADDDCDGHGHGCDCDBFAHHFHAGDGB,True +860,23.0,20.0,27.0,31.0,27.0,21.0,22.0,20.0,GBHCDCFCFDEDHCHGEFEFECCCCCADABAHFHFHFDGDAEEHACDDGBADFDEECFAFCFEGCGEEHFAFEFBABCDADEDEHBHGHBBAECECGBHAGFHHBGECCDEDBFHCACGCDAGAGADDDDDCDGFCFCEEEDEBHGHGHGCGCBDADHBGDDEDABABAEDEBFCDEBABGBDAFAFGEGH,False +861,7.0,7.0,14.0,4.0,11.0,5.0,11.0,5.0,GCGFGBGCCCGFAAEAECECECGBABHHCAEAHAEFEBEHDCDCGFGFBCGCGCDBEEHDGECB,True +862,12.0,3.0,10.0,5.0,8.0,8.0,5.0,6.0,GFCAHAHAGACCEHDBBAAAHADECEDECGCBCECFCFHFHAGGEDEFFCFAEAFAD,False +863,24.0,14.0,29.0,24.0,18.0,18.0,12.0,25.0,ACACHBEBEDABHBGCDCFCEDFCGCACGFADCCCCBCDEAEBDHEEGAGCDFDFDFGEHAHFEEAEHCCFHFEFCHCHDAAHGDCDAHFHEHDHDHAHADEBEBEGADAHEBFHFHACGFGCGCBCDCDCACFCFABCBADDBCBHHDHGAAHAHFFDHDEDA,False +864,12.0,14.0,8.0,8.0,15.0,8.0,10.0,15.0,EBEBGHCABAFAFDFDADGBHCEBGBGBCFCAEEDHCHGHBHDGDHEHEHEHCFGFBEEHAAAHGHGEGBFCABHFHEEBADCDABEBEA,False +865,3.0,2.0,2.0,3.0,0.0,3.0,0.0,4.0,BHDHBCFDFCAHAHAFD,True +866,5.0,8.0,8.0,6.0,13.0,7.0,15.0,8.0,FHCDEDADBEBGAGCCCEBGGFGEGEGAGAGHDHGBEHEDGAGEBECHCGFEEHEHGGFBFBFCFHEBCD,False +867,15.0,8.0,10.0,4.0,10.0,7.0,12.0,11.0,GCHHEHGBDBCGCBCFEAAHAHADFCFCFGAGAFBGAHAEGFBECEABHCHAEAEHGHGFBDCHGEGEGDACABAEA,False +868,13.0,19.0,24.0,20.0,14.0,16.0,12.0,20.0,HCHAHAGDDCDBGGHGHGCEEAEGFBFDEAEFCFHDHGFAFGEHDBDBDCECDFECHCDCFCHCHBBBBGAFDCACEDBFFAFAFBEHCACDHBCBCBHBCADDDBDHDHCHCBABHHEFGAECGCGCBDBDCFHFEE,False +869,11.0,10.0,12.0,15.0,14.0,12.0,10.0,5.0,CBGECDGDGDADCGAHDBDFFFFEAHFEFDBDGDGECECDDFDADBEACGFEBEBECCCGCBCBEAEAFGBAAAEDEGHHDHCFAFEFB,False +870,8.0,16.0,15.0,5.0,12.0,6.0,10.0,5.0,GEGAAFBCBCEGAAEBEBEFHHCBAAGACBBBBEBCGCGCECECBABCFCGCFEDEHCCDGBGFDFDEHCHBBGBDE,True +871,7.0,10.0,13.0,4.0,10.0,7.0,7.0,8.0,GAAHGCBADEDHDCCCACAFHEBBBBBCBEGEGFCHCBEGEGEHDHCFFABCFCFHGHABFECECE,False +872,5.0,6.0,11.0,4.0,5.0,6.0,7.0,6.0,FCCCACBDAFCCCFGBBHBGAGEGDGCGHGHDHDEBHCCFCBAEFEFEHA,False +873,6.0,3.0,2.0,8.0,3.0,5.0,4.0,1.0,AADDDCDCGGFFEBADADADEDGBGFFEFAHB,True +874,16.0,16.0,9.0,13.0,16.0,16.0,11.0,18.0,DGAGHBHCEFGDAAEAFAFBBDFHEDEDHBHGHGHDDEDFCFCAAADAHFBCBCGEHEBFDFAFCFAFAFBECCBEDHHEHEGBGCDFGFHHHBHBEBEBHAEADBEBAAGEGHF,False +875,10.0,10.0,11.0,9.0,10.0,8.0,13.0,16.0,AFADADEDEFHCHCFGBGEHDFGHCHEGBGHFABHEACHBHBHBHGDGBAAAHAHCHCGGGCGEDEBCDDGBGAECEFFFBCHCHDE,False +876,10.0,18.0,8.0,11.0,7.0,15.0,11.0,9.0,FCHDHBFBGCDHAGCCHDHAGFFHBHEFAFAFDBBBDBDEACGGGBGFECECACHDBABFBDBDGEADADFFFGEGEBBBFBFBGBFAH,False +877,4.0,5.0,14.0,13.0,6.0,8.0,11.0,11.0,ACACGHADGCECGGGDCCCFCFBFDFDHDHDADHDHFFBHGHCHCGCDCDHDEEBGFDEHBHGEEBDFCCGG,True +878,22.0,17.0,15.0,16.0,16.0,19.0,13.0,15.0,CCFCHHDBEGEGDCFHFBAGFEDDFDCECEGBCBABADADBGGDBACAFAEABHHHFHCHDBFBDBDBEHHCHCHEEGFGFHAEAEAEADFEAABCFCEAHFGAAADFDFBFBEGCGCDAFAFAEDGBHBGFA,False +879,11.0,12.0,5.0,10.0,10.0,9.0,11.0,9.0,BCBCEAFGFGHBHBHDDFEFGBGHGFBDCAAGEHDBDGHGHFADAEEFEDEDEAHABABACAGHEDFAGEDBGBCBF,False +880,22.0,23.0,20.0,22.0,17.0,22.0,27.0,22.0,AFEFEHDHDHDBFBGBGEGBGFGFGEHEABABGGGABAHDHEBCGCGCFCDBDFEEAAAFDCBFHGHBCGAEDFDFDBCECFBAGAGAFEHGGCGDBBCCGBDDCDBDCFCAHDBAFFHCHDHFHCEEDHDHBHCCBFBAEAEAFGDCDHAHFHEHADAGAGAFBGCGHGFBEGG,False +881,26.0,17.0,21.0,13.0,20.0,12.0,23.0,19.0,BAEAGCGHGAEADABEEEGAAHHDDBDFGAGACCHHEHEBFBHEEEDFGFEAGHCCACGEFEDCGCHCGFHHBHBGBCCCDCGBGBABABFDDHEAEFEGGGGEHAHACACDGBGBGBEAFACEHFAAAHGHGDCCECFCBCBHDAAAFAD,False +882,1.0,1.0,3.0,2.0,1.0,1.0,0.0,5.0,DHHFADEBCHCHCH,True +883,7.0,3.0,8.0,7.0,4.0,4.0,4.0,4.0,GDEDCFHFHDHDEGEACDCABBGFACACGCFCDADBCAEAH,False +884,21.0,12.0,14.0,11.0,9.0,9.0,15.0,13.0,EHEAEGDDAGGBGFFAGHDHDCDCDCFCGGGGGAAEGCHEDEAEFHFAFGCBHBCCCCADBBAGAGHBCACAHAHBFEDBGBCBEDDHHABAFAHAHFBCAAAA,False +885,16.0,26.0,24.0,20.0,25.0,24.0,19.0,20.0,DFDGGAEAEAEDHGHGCCABBEECFCFGBGBDCGFFDBDECEADADHGHFDBDCEEBCGCGAFBFBCHDFDFEFEFHFHFHBHFEFHCHCBAFDFBFCAGAECBBBBEAEBGCECFHEHDCCEGBGBGFGFHHEHCHBDACECABABDBHAEDDCGGBBEFDFDCBAEHEHECG,False +886,13.0,28.0,17.0,8.0,23.0,25.0,17.0,16.0,GFFBFBHCFBBBCGCGEEBCBABFDEBGBGCACEHFHFHBADDCGEGEBHAAACFCEHBHBDAEFFFFDFDFEFEFECEBBBHFGBBHBEGCBEAEDCHEEEFBGHGECEHFHBABFCFCFCGCEAGDGAGAFBGGAFHHHBEBEBF,False +887,12.0,16.0,10.0,18.0,15.0,11.0,14.0,8.0,EEHEFGDCAFDGDCBFBFGFBEAFBBBAGFGBGCHCHCAGADCFCDBDEHEAEDGDBHBFGEBEBDBDADCDHDEABDDEDFCAGDGAGAFDEAGCGBEBEHEH,False +888,18.0,13.0,17.0,15.0,11.0,10.0,18.0,15.0,DEGEDEFAHAHAHGHGHGCGCFDDDADFCBGDGDCBABCBEACAGAGCEDBABDHFGAGAGDEEHAFCDCBCACBEBHCGBFAHAHCDFHBGBGHFHGHFBACEGEGCHAECFCDAD,False +889,22.0,5.0,11.0,9.0,14.0,19.0,10.0,13.0,HEHFADEFGFCEHEFDFHFAFGGGGAGAFADGDFAEAHBCECEDFCFHFCFDFDAACACABBFGCHEAAABCDHEAEABFHFHEGEFHAAAAACAGDHCHEFE,False +890,27.0,36.0,17.0,27.0,26.0,14.0,25.0,25.0,FHDGFABEECADAEBECEABAGHECDCDADGDADADEHEHGHBFBCBGDEEEEEBABABHBHAGCEDEDEHAHAGGCDCDHBABHBCACAGFCFGHHFDFDGBGHGAGCGFFBHADFCECEHBDBGBABACAHEBBHGHEHBBEDEFEBGBDBCGEDBBBBBEBDHDBAHGFGAEBHAADGHGDABFCFDAGBGDHD,False +891,18.0,15.0,22.0,14.0,25.0,27.0,18.0,19.0,FHFHEHAHCFEDCDHFFFHCCCCCCFAFGEAHAFGGEGEGEGFGFAEHDCDFHGAGEBHFHCHBHBEDHDCFCACGBFCDDEHBCEGAFABEBFDEGAFDCACFEFEDEAAGAGAGCBCDFEHAHEHBCBCBFBEEFEHGGGCEFEFEBEAFFBDADB,False +892,15.0,15.0,17.0,14.0,25.0,21.0,15.0,21.0,EGAHHHDHDFEAEDEGGGGAGFHFAFEEEHHBCBGHGBGDFAAEAECEFEDDBFCFCAGFFHFHFHBCFCDHFHCHADBHFGFGBEBHHEEDDCDGBCEEEBGBHEHEDEAFCBCECEBGAAAEDCDCACABEHHCFEFCFBF,False +893,5.0,2.0,1.0,1.0,3.0,2.0,5.0,2.0,BHAHAEEEGFGFACGBDAGAG,True +894,1.0,2.0,2.0,3.0,4.0,6.0,4.0,3.0,FCFCHHEFEFGGGGHDBEBFAFDDE,True +895,12.0,25.0,10.0,17.0,18.0,19.0,18.0,17.0,CECBHFGFGEBBHFEFDBDBABDGAGAEABCBGAGAHCEEHEHEHDDCDBFHFHEDFCFBFBFAGGGGGFGEHBBBHDHBHDEBEFGDCBBBDBGCAHHEGBGBCDFDEEEDEACAFFGBBHFHFDFAFHGBADED,False +896,16.0,8.0,11.0,13.0,10.0,11.0,7.0,7.0,GEDEHEHBBDADFDADCDCAAAHFHFGFECACAEDCDGAEAEBBCBGEACAHDBDEGFHFBCDCFAADACBCHFAFAFEGGDF,False +897,11.0,6.0,9.0,7.0,10.0,14.0,15.0,10.0,HDBFBGCFCGCGBGDEDGHAHGHAAFHFCGBGCAHHGFCFAFEBGHGBDCHCHDEEFEFEAEAEFEFGDGFAFACGEFDAGA,False +898,17.0,13.0,21.0,30.0,28.0,20.0,12.0,19.0,EDDBGCECEDBCBCDHGFECBGBEHHHEHFHDGDHHAFAHCHDBEFDADCDHEEEHEGDGDGFEDCACEDEAEAEFDFDFDADCCACFEFCFEFCBBHCCFEEDHDFGEGAFCFCACABABCGDEDAHEDDDDGDGFHDHDABFCFDFAHEEBEBEHEAA,False +899,3.0,3.0,2.0,3.0,3.0,3.0,8.0,3.0,BCEFGHGHGAGBGBGDFDCHEGEFAADG,False +900,16.0,24.0,17.0,15.0,11.0,13.0,13.0,18.0,DDCDADAECDHHHCHADDHCHCBCADAECGHGEAHFHGBBHDADAEHHFHGACACFCFBEBEDCGCGBBBBGEFFHFBBGCGBABABAHFEFBBECCHGFDFBFAFAHBBEBEACDGDGCBHBGBDB,False +901,25.0,30.0,29.0,16.0,34.0,19.0,24.0,19.0,FFGCECEBBBCDCBFEEEECGCABAFEFGHBDAACECGHDFCHBFBGGGBGHCHCBCECBGBEFDHBHBHCHAHAGABABGEGFCFBEGEBBCBCDHHHCHCHDBDCFCAEDHGAGEBEGEBEDEFFDBDEFBCEFEAGGFGEGFBFHHACACAEAEAEBEHEBAGAEAECGABADDDAECECFAAEDDAGCECBG,False +902,24.0,23.0,19.0,24.0,26.0,27.0,19.0,14.0,FAAAEACAEEEGEDAHEBADAGGHEDCABGFFDFDFEBEBEDEDGAHFDGBCBFDFGECFBFGFBFEFCFEDADBEFEFACACACAHADBBBEHAHBGBFAGBEEGGFGCGCFAFDFEBHGCAAGDGFHFCFCHCDCBFBGBCBEHFHCHCBEDGDACAEBDBHFHEDDDDDEAED,False +903,29.0,29.0,25.0,18.0,19.0,26.0,26.0,24.0,GABBEDADAGFHBHFHGCBCBDADGBGDGHEDBGBGDAEBEAGFGACEBEDADFFFBBBCFCGAFAHEHEHGBAAAAAAGGCCHBGBABHEEFHFHAHFBGCHDHFEBEGEAEDFGCHBHACADBHGDGCEDFFHFEFBCBABAHAEAGGFFCFAHADGDGCBCBCGCGCBCBCFHEHDFFEFHFCFABCHCDCAC,False +904,6.0,3.0,10.0,6.0,5.0,4.0,4.0,1.0,ACGCFCACDCHCDDDEDCGGEFBCBCBFGFEEAEDCAAA,True +905,3.0,18.0,9.0,11.0,14.0,16.0,4.0,13.0,DCFBBCBEBDBFFEFDCGHBHGDCFBFDEHEFBHBFEFHFHFGCAEHFAFBEHEHEHCACHGFDCBEFEHEBDBDBHBDEDEDBCBFB,True +906,16.0,25.0,37.0,22.0,24.0,10.0,28.0,28.0,DFDCDCEAEHCHEACBHBGBHCCGCECADDDDDDCHHHAHCCCGDECECEBECHCFCFBHBACGCBABCBHGEBBBHGHGBCBCDEEAAGAGDHFCCEDEDGDGDGBGHHDFFGEEBFAGHGFCBBGEHHBCBDBABCEAGACACGBEHEHCFDHAHEGGGHGHGACEDECHCGCGCDHFHBEGEDBCGC,False +907,25.0,18.0,28.0,21.0,19.0,32.0,30.0,20.0,GCGCEBHGCGCEDDHHGCCCCGHGHDHEHACGGGBGFGBEACGHGCFDFDCCCHCFDFAFAEAGABACAGACEBHBFGFBFBDHCFAFGFACAGDEHCDBGHAHBBDFDFCFAEBDCGFAHGHGFGFGBADFEFHBDADABBEAFHDDFDFGBGDEDEFAFEFEFGFAFDFEFCACHFHBEEECGCGCAAEAC,False +908,28.0,27.0,16.0,15.0,23.0,29.0,25.0,24.0,FAFEFGFBABHFFBHDCCGAABEBCACAEFFCFAGAEEGEGFGFDFHFHBAGFGBGDHBHBHBCGEGFAAHAHAHAEGEBEAHABCBDFGFGEGBFBHBDBFBFGFGHGHBEBEBDGHGFAFCHADEEECECFBACCBCDDHGGEHEGCAAFAFBDHHHDHDFDADGFAAEAFABEECGHHDBEACB,False +909,22.0,23.0,20.0,21.0,31.0,23.0,29.0,28.0,EAGGGDCHHHHCDDEDBCHAEDGBGAGADBHAFFHGBGBDEGEGHGAGDBEGAGCCHFHFGEGHHEAEBDDDDADHCBBBCACFCGAGECEAEFEGEDDAAEFEHBHBGBFCFCHGBBDBFBFDEAEAEFCDDEGFGFCECAGHGFGFEHHDAFHFHGHGHFHFEEEHAFBBBEAECGCBCBCEEAHACBFDFEHEH,False +910,35.0,20.0,17.0,22.0,15.0,17.0,23.0,20.0,BABABADGDFFFFFADHEEAEHCBGBGDGEGCACHEFAAHAHAHBHGHBABCBCGCFDFAFCFCEAEHEDGFGBAAADBGADADBDBECGGFCBDBHCAADAHAGADCGFGFGCGCEDAAEAHDEDBAGFGBADDDCDHHHCHAHDEAHGFAEAFBDHAGAEHBBGCGA,False +911,20.0,22.0,16.0,16.0,19.0,34.0,24.0,21.0,HHBBFFAHAHEFAFCDBDBDGCEEBFBDCCBCHDFAFDBDBFCFAHGEDBGFFFDFHACEDGDBFBFCECHCHBFAFADAFFFFFFFGFBHGHGHGHAFABACHCFGGGAFHFHGGGGFAFEEGHGEEEGECDGECBCBHDGDGHEHDBAGEBEAEABABFEGACHEBGFAF,False +912,14.0,22.0,22.0,16.0,10.0,16.0,13.0,11.0,GABHDHAHACDCBFFFECHFHEBEGABCEHEBBFBACHCHCACABEFFDBACDHFADAFBFBGGCGCGCHFBFCGDFAFGBCBCBDHDGDCBCBCGDGCGAGABCBCACEDFDEEFBBDDDEDB,False +913,20.0,27.0,29.0,23.0,22.0,31.0,29.0,18.0,GFGEECFDFAGEFHFACDEGCGCGHGHDHDCGCFDBAGAGAGDGHFDFBFGFGAGHDAGAFABDCFFECECEFFDCDCBCGDBABFFHFDDDGACHHDBEBEBFCEEBEHAHECBABGGAGDHDCEEGFCFBDECACAFHFAFACBEAGGGBGBCBHFCFCFCFCHDFAEBBBHBEBECFCHEEGBGBFCDBDBDBHGC,False +914,12.0,9.0,6.0,2.0,6.0,6.0,2.0,13.0,BFBHEHEHBADCHBAGFHFEBHAAACABHBHAAACECBBACGCHFHAHAHEHEFFD,True +915,10.0,12.0,24.0,13.0,16.0,14.0,13.0,16.0,CEBDBDBDCDCDCDBDAHHBFBFCFGFGEDFHCBCFGECFCEBEBHBCCFCFDFEHAFBHAHAHFCACHCECEHACBCHCFEDEAGACDCHCGAHCDEGGHEEFHAGGGECEGEHDGG,False +916,4.0,4.0,9.0,4.0,6.0,12.0,3.0,4.0,CECDADFBACFCFDFBFGFCFGHCCGBEHEHEHEFFCACBEFFFAD,True +917,15.0,18.0,12.0,11.0,16.0,11.0,18.0,15.0,AEAEAEAEAHAHAGEEFHGHBHBEDABABADHGFGDHBCDDFHGBEFFFAFGGHBDFCBEHECECGFHBHEEGDBEGEBBGDCDHDCACGFGHGCABABHFACCCCBGBGBGDGBE,False +918,14.0,16.0,12.0,30.0,16.0,18.0,12.0,16.0,DHDAEBFADADADADADGDFAFHFHDEFGBGBGBGFHCGEHECEAACACGCDDDFEBEBHBFAFHCDDDDFCFDFGHCFDHEFEFDCHBBBHAEDEDBAAHCEFDCDBDFDBEEDBDHEBDHDGFHDHEGGGCB,False +919,5.0,11.0,3.0,9.0,10.0,8.0,8.0,5.0,BFBHEEEBCBHEHGAGAGDDBDEEEHABFCFBAGDCDGDBDGAFEFEFDBDGGFBFBHE,False +920,5.0,0.0,5.0,4.0,1.0,1.0,4.0,2.0,CGAAFADHDCACGCECGDGDHA,True +921,24.0,17.0,18.0,26.0,23.0,31.0,24.0,25.0,EDEDCDADFGBABAGGFCFDFEGCGBHHECEADGDEDFDFDBEGEFCAGFEFEFDHEADHCHAHFHFHEGEDDDDBGEGEFBCDCEAAHDBAGHDHFGGHEHAHAHAHFHFDFBGBHCGAGFEFEFADACAFEBGCCDBEBADAFBGCFAFCHCHAFEFGCGBGCAFABCDAFBFBHDHFHEGDGHFH,False +922,12.0,3.0,17.0,8.0,6.0,8.0,19.0,16.0,GDFCHCHAADGBHCHAFEHCHCBGBCHFACAFADGGGGGGCGCAADHEHECEAEDDCCEGFGFGAGAHHGHGCDADCCHHGCGFHFHGC,True +923,13.0,7.0,15.0,17.0,15.0,11.0,14.0,5.0,GDDDHCCBCDADAEABADADGHFDCCACAEAGGDEEEDFHFBDGCHBFBFDGGBCDDDFCFCFEEGCFEFADADACAGGGGEGCCAEBEHEGEFECE,False +924,19.0,22.0,14.0,20.0,28.0,12.0,19.0,18.0,CGCDHBFBHGEBEADBDGDGDCBCDCHCEBHGEGEHEGDFFCEAEDGCGEGFDEEEEEBABCBCBCBCBGFDFAEAFDHDHEHFDAAHHHHEAEADAFEFEDBABDHEFEAGCBBFHDHBHBGBADHEEDBDEGBAEAGGCGHBEGGAAAEA,False +925,20.0,23.0,18.0,19.0,19.0,27.0,21.0,22.0,FEHEHEGDGCBDBHBEBCAGACHFEFHAHADAFGBGFFEGECEHDGDAHAHEDCCEAGFDFEGCCBGBFBFHDADCBCBFBCCHBHAHBDCECDFHFGFADCFFFFBFADBGGHADFDBBCBGHHHEHEHBAEAEFGBHBHGAGEFEFGFGFDCDFBFACAGAEADGDB,False +926,8.0,4.0,5.0,5.0,6.0,5.0,4.0,8.0,FGFDECECEADFBFBHEHAHADAHAEACGDADHHHBHFACBEGCG,False +927,4.0,9.0,2.0,4.0,9.0,4.0,11.0,2.0,GHGBGDGBGBEAGFGBBBBDDEBGFGEGEDECEAEAGBFCEHFAE,True +928,19.0,13.0,20.0,26.0,25.0,21.0,11.0,20.0,DDDFAGCFCHADFCCECECFBEHDBEBEDEHEHCFAEAEAEFDFBFADAEAEAEADHDFDFGBGBADEDBHCGCFCBEEAEHECFHAGACCCDDEDHHHHAHDDDACGHBACFCFGDEFEBHFHFCDDDHDACECBDHGHEEFGBGFGFEDHFBA,False +929,31.0,26.0,25.0,22.0,30.0,19.0,16.0,16.0,GADBEEEAEAHACCCCFGFEHBGBGCFCFDDADGBAAAFEFAABEHADFDFACAHBHGEFBAAACFCGABEGFABGFGEGFBFBEBFDEDEHGFEECHAHADADADCHEHEBEDABHBEACADBDBDGDGDCDCACHEHGCEHDCEABCFAEDFDGCEBFBAAEHEDEBCBCBCBCBEEAEBCHC,False +930,5.0,6.0,16.0,9.0,2.0,8.0,6.0,8.0,FCFCBBGDGDBABHCHCGEBEDDGACFCFCFCHCGCABHCCCCHFHCAGFHHCAFDDDDD,True +931,13.0,10.0,13.0,5.0,17.0,8.0,8.0,11.0,AEAEAHAEECBHBHGHAEBFCEEAEBEGCHBFBGEGFACADAEGEDBFCCHHBHBHFHCGEGHDDCDCACAEAFBCGCFEFECEA,False +932,13.0,15.0,7.0,16.0,20.0,10.0,5.0,18.0,AEABBCHEBEHEFEDEAFBHBADFHHDBDEHBABABABACDCFEFHFEGGACEDEHEBBAFGHCEDEDBGCHHDBDBEHCHDADGDEDEDHFEEEAHAHFHFHD,False +933,4.0,6.0,3.0,4.0,2.0,6.0,4.0,5.0,AGAGAHBEEDCGBGBCBDFDFDHHAFBFHFCBHF,False +934,5.0,12.0,3.0,2.0,5.0,4.0,9.0,11.0,CEDBABACFFGFAEAGCGBGHGHBHGHEBBHBHGDFHHHHBEBEAGBBBGH,True +935,8.0,6.0,1.0,11.0,7.0,1.0,14.0,7.0,GEBHGHGDBAEEDAGGEGDGBGBHHHHDDAAAAGDGDGDADABCEGEHEDDFGGB,True +936,12.0,13.0,17.0,16.0,15.0,22.0,16.0,19.0,HHEDDDDGDGAFACACHCFEEECACADBGHGFFFFFFEHEHCAGBDFEFDFEFEHEFFBBABFCHEGFGDHBCBCBEEAHCCECDDBFBHCHFHFHDEDGGGDGBGHCBGAFDGDGCAHBCCHGHFHFAA,False +937,3.0,4.0,1.0,4.0,2.0,0.0,0.0,2.0,ADDEDEHBHBACADBB,True +938,5.0,10.0,7.0,7.0,2.0,7.0,13.0,13.0,FCGGGHHAFEFBFBGBABAEGGGGCFCFHBABHHDHDHFHACDBBGHGDGDHCBDHCHGBGDHC,True +939,0.0,2.0,2.0,0.0,2.0,1.0,2.0,1.0,CGEGEBFBHC,True +940,15.0,12.0,17.0,12.0,18.0,16.0,21.0,10.0,DADACBCEGEGCCAHFCDCDAEACDCFGDAEBEBEACABEGGGABACDFDCGGFDDHCGFGEGBCBDEDGHGFEFBFGGCBCEEFAFGFHFAFHGHGCEFEBHBHGEGEGEFAFAHACBHE,False +941,21.0,9.0,18.0,19.0,23.0,21.0,20.0,26.0,EGEDHBHBHGHGHCEAAGBHBDDDGGGDGFGFEFGFGADHEFEAEAFAHAEAHBFECDCAAGDFAFHEHCCDCEFHFHFAEAHACFCFCHCECEHDDGDHDHDADEBHFEGAAEAFBHCCEGGDEDBCHADAHFBFCFCGGEDECFHGAGHECEHFH,False +942,23.0,23.0,25.0,23.0,16.0,18.0,18.0,24.0,CAHDBDHDEGCADHGHGHGHFCDCHCDFGEDEDHDHBHFDFEEADAEABFFGFGACFBBCFCBBFAHCHCEEDCCFHACACABHBFFFDFECACHHEGDGDEDBHBCBHBHADABHBHBCGHACBCBEBABCGEEFEAEAGGCDDDDAGAGAHBHDGBCFGFDCAGACAB,False +943,9.0,5.0,6.0,3.0,2.0,3.0,4.0,6.0,DBDHCFFHCEAEGBGBGAHCHBBAGFCAHAHACADACA,True +944,1.0,5.0,5.0,2.0,2.0,3.0,5.0,5.0,EGGDGHCBBAEGHGCFCFBHBHBHCFCD,True +945,23.0,12.0,17.0,23.0,21.0,25.0,31.0,23.0,AHAHBHBHCHCEDDFCACDCDFGFBHBCCGFGHGAAHDEEGECFAHAHFHDHEADFGCGCGFGEADBEAEBEDDBCBHAAFAFAFDGDHABAEHDHGEEEHDADGFGHGFEFGFCFAFHFEFADGGEGEGECFDHCHDFGHGDGCAAGAGEGFDBGCEBGBGDEDHFFCFGAGDG,False +946,7.0,6.0,9.0,5.0,3.0,13.0,9.0,7.0,BEBECFHFHAHGCAABCCFGBGFFCFGFBFDFGGAGHGFFFFDBCGHHCHCDDADAEAC,False +947,12.0,14.0,22.0,9.0,8.0,15.0,19.0,16.0,GGGGGADFDBBBCHGACAHBFGHGHGFGCCFDACHGHEFFBCBGEGDGFHHHBHDGDCCCCGBFHACACECDCFGBHBHBCEFECHCBCBCHGFGDAAAADAEEFCFCACFFEHB,False +948,23.0,29.0,24.0,18.0,9.0,25.0,25.0,32.0,BBBHGFAEAEBEBCFCFAFAFCFDFBHBGCHFAEGDACAGBHCHFDBCBGGCCBBHHABDCFGHBDCDBDGFBCAFAHHGHFHEHACEGDABGBGHABABGHHHFBFCFHFABAEAGACBCFHHBABCBCBCACFCHGHCHBGBHDDFGAAFFFEDDDGDHDHGHGHGHDHGHGHDCDCGFGFEA,False +949,7.0,6.0,5.0,7.0,7.0,6.0,6.0,12.0,HHCHADDCGBGFFHDHBBCHCHBFADAEAGAFAEAHBHEEEEHHHBGDGEGCDFDF,False +950,24.0,23.0,22.0,11.0,20.0,30.0,30.0,14.0,EHFBFBFBCCFCAAACEGBFAEEBHCHFHEAEAGBGHGHGCGCFEFAFBEAGAEBGDGCGHGHBBGBGBFBFDFECAGGFEBEGCAEBEDGHAFBHBFBDGDGFGDACCGCECACAGFCECHDFBCGCGFFFGFGCBCGABADFBHGGFGDHDEFBHCAAAAAAFFFFFDEEAE,False +951,16.0,19.0,15.0,15.0,20.0,28.0,15.0,17.0,DGGFECEHGHFHCBCEHGDGCBCGCEEFAFAFAHEHFAABHEGDGAGBGEEBHDHBBCBCHFBDBDBHEDFCAEAFFFDFDFAGBCBDECFFFEFDFBFGFGEECECEFEFEDHGCDAHAEABBDGFBFHHBHDAFHFCFAFABA,False +952,9.0,0.0,6.0,3.0,8.0,5.0,2.0,3.0,EFACCCFAAAAHFFFDGAAEAEHGHECECEDECEAD,True +953,2.0,1.0,1.0,1.0,6.0,2.0,3.0,1.0,ECEHDAAGBGEEEEFGF,True +954,11.0,9.0,7.0,13.0,13.0,4.0,8.0,8.0,CADHDHDFDABBEACAFDBBHFHGAGECBGEGEGEBEHEDEAHBGDADADADFDEBEDDCAABHEHCGEGECC,False +955,17.0,19.0,17.0,18.0,12.0,19.0,16.0,32.0,GFGFAAGFGAHADGGHGEBABFEDBHBDFHHHHBGBHDHDEAACBFBFBEAEHCDDGDFHHEDGHGBGBGADHFHDHCCGAEACDCDCAHAHFHFHFHDBDADHCCCHBACACBHFHFEFECACGEBBFDHCHDHBHEFGCECHFFBHBH,False +956,21.0,23.0,17.0,24.0,20.0,16.0,15.0,22.0,DADEHFHDCBCBCAHGBGFDFDGBAFDFDHHFDBDBACACFEHEAEAHAEEBAGCHCFCFAHAGDGDADADHHGHGECCFCFGFCHAHGDGBCCHADBDEAHGCFBHBHBHEEEEEHEBEAEGDBBFBHHCDCEBBBDBDBAADGFABADFEEGEDDB,False +957,10.0,10.0,8.0,10.0,12.0,10.0,10.0,2.0,FGFBFDFCGGFGABBBDGAAAFHFDGDBDGDEDECECECECGBAEHECGDACEBGBDFCAEAFFEDEBABAE,False +958,23.0,37.0,29.0,27.0,20.0,20.0,23.0,19.0,ADBDBAFABHBADGGCCCHFHGBBDDCACACBBAGDHDHCHFECBHFEGEBEDCCFEDEFBFBCBCBHEHBGDCDGBGAGAFFGCGEGAADACADBGFEDGBGFDBHBCAHEEFFDCDADBDBACDCDCDBHBHFEFHFDBGBGEFHFHBACECEDEBCBCBCGCGBBACAGEFBFBABGDGDHEHEGBCDCBHEAAA,False +959,12.0,18.0,18.0,8.0,12.0,10.0,17.0,15.0,BEBEBGBGBHBCBCECGCGCDCFGGHGBCHEACCCEFGAAAEHBHEHBGBHAEABHGFCFCDCEABACAHEHCGCHFEAEGDBDHDCGFDCDAHBHGFDFGGGHFBBBAF,False +960,6.0,8.0,14.0,11.0,10.0,8.0,6.0,15.0,EADADHGFDEEHFHDHBHBHCECDFDBDECHFFAFGFBEDECBCECHHHHGCGDGDHCCCCCCEEDHHAHABCGFABB,False +961,20.0,29.0,25.0,20.0,25.0,26.0,26.0,18.0,BHBEFEABGFAEGDGDFFBDHDGBGBFFFHEEEEEDFAFADABGGCGCBCBAFCFABCCHEHGDDEDEGFFAAEEEEAGCGAGHGFDCCBCHGACACEDHGHGAFBFBFAHEBEBEDGBHCCEAEADDDHDCBCFHAHCHBHBFBFBGGGBHECGFGECBCBCDHDBBFDCACACBFGFGEGCDEBFBF,False +962,27.0,19.0,27.0,18.0,20.0,32.0,29.0,28.0,GEGECAFAHHHHEAEBDBDCHHGHFEFHDBFAFBFDGDBCBCGHGHFCFCFCFDEGADHHCCADADAGEHEHGACCHGHBHEHCHCHFECGCFAFBFAFGFBCAEFCDHAGFBFHGEGAAHGFGEDEACDCFHDDCDCFCHCGCEDGHBDAAFAGBFBFHEGAFACADEFEBEGGGCGCBBFBFGAGAGAFABAGFBEHF,False +963,18.0,20.0,27.0,19.0,14.0,17.0,15.0,25.0,FFACCGCGCDDHCHCDGGGEHFBCBHFCAAAAHAGFGDGAGDGHFBDEDHCBCACACGCGAFEBBCECEAEHEHBBCHHHHAACDCDBDFCFBFBHCHBHDGCEEEHEDGBBBFEFHFHDCDBDADAHFBCBABDCEAHHDACFCGHBHFHDCFE,False +964,12.0,10.0,8.0,9.0,12.0,10.0,10.0,9.0,FGFAEAEAGADFEECEHBBBAHAEBECECAGGHBAAGEHFHDHAEFDFECDCBFBFBABDDFDGGFGCCCEHAHBHGDGD,False +965,17.0,22.0,24.0,31.0,26.0,22.0,22.0,27.0,CGCEHFCFCEBDBDBEHEHGHGHFABABHEHFBEBGHDHDFCBDBEBGGCHCFDFHEHDHDGDFFBCAHAHGEEFHBHBEBADFFAFAHDHGAGAHEDDHDEBEFEBEFHFHACADDDFDEEEECCCDAGADBGAGFEHBGGHDCCCDEDGHCECDDABFBEBCGEGCGCFCDCAAEDCBGHGDFDGDCDF,False +966,27.0,18.0,26.0,14.0,26.0,27.0,37.0,24.0,AACDCHCFGHAHAGAGACFHEHABFHFAGHBCBDBFBFBABFHHHFHFCEDEFACHCECFGFEFECGDGHGCGFGEHECDCBCBGBECEDFAEECAGGFAFBHEFDGBGEGHFEEGEHCGEGDGDGDFCCCCHBAEACHGHGAGHGAGEHEGEGBCAGGGFABHDADADAGAFHBEDCFAEECFGFGFGCGABEFGABA,False +967,19.0,30.0,23.0,20.0,26.0,19.0,25.0,21.0,BBABCBGGAGFDFGHDHEGBGCGBBAFDCBCEFHDCDFBCBGEFBHBEEEEEBADAHAHBGGGEDBFBHCCCECBGHDHDFGBDCDFBEHECGBGBGFCFAHEHDGEGEFDFDECCCHCHEGEGHGBCEAGABEBABABABADADABAEADCCEFBABFECDFHFHCHFEFCGGEHEHGDADH,False +968,22.0,15.0,29.0,26.0,37.0,20.0,22.0,24.0,AEGBABEFGGEGDHDHAHEFECEFACEEACHBECFBABCDCACAHGHDEEFECECDAAAEHGHGHDHDFGFHCADFDBDEDEAEDEDEDEDGGECEABBGFADADEHGHFECBCAEAEGECECAGDBEGAACCCCCCBHEGECDCDFHFHFHFHFCGEGHBDFEBBBGECHDEFEHHGDADCGHGDDCEFHFCFC,False +969,16.0,6.0,14.0,15.0,9.0,8.0,13.0,13.0,HHHHFEFDDCAHGGEGDGDCBBHCCDADGGHAAADADFDFDGDGDGABEBAFABECDHAAFAFEFGDGCHEHCDCGCEEHHHAEACCCCBCGAA,False +970,21.0,25.0,9.0,17.0,8.0,13.0,18.0,16.0,GBGHGACACAFHFBCADGGGFGFGAGAGBBDBGCHHEHEBFDEABGDGDGBHBCDFFFFHFHAHBDACAHDHCCGAEADBHBDFABABABEBEAECGGBHBHDFBBBBAFDDAGBHHABDDADADBE,False +971,9.0,10.0,11.0,9.0,15.0,9.0,14.0,12.0,EAEDFCFBFBAGHGHGDGBHBGFHEHCFAFAGHECGCHCADAHCEGDGCGBBBBDBDEGFGCCFHEEEHEDEAEDBCGHGCADHEFEAE,False +972,18.0,16.0,12.0,13.0,15.0,19.0,12.0,21.0,BEHFBBABAHGEEAEAFAFCDEHFHAHCGCFBEAAFGCABHHFHFHCHBGADCDHDHCHCEEAGBFDFGADFFFFBFBGDGAGAEADHDHDAEEEBCBCBHBDEEHGFGFBFBDEHCHGHAHFCAD,False +973,27.0,25.0,26.0,28.0,24.0,17.0,20.0,27.0,HCHEFEACGCFDFGCBCHADFCFBADCGHBHCDDDCBAAHAEEDADGDGHGHGHGDAAEBEHAHGDADADEBEHHCEBADAHHHHCHCAAAHBFBDCGBFCHEEFBFBFHAEADDBFBFBDGDEHEHBHGCGAHACECAFBFBEEEBECEFDCCABDBDEDEGAGADEDEDCFBBACHGGFGBGCGDADCHCBC,False +974,2.0,9.0,5.0,14.0,10.0,16.0,13.0,8.0,HBEGFBDBDHEEFHFEGDBFBFBGHFAFDFGFCFDBDBDHDHBGGCFFEGEGECADGFECEHFGDCDHDEDGFGFGD,True +975,7.0,10.0,11.0,8.0,6.0,8.0,11.0,11.0,CECFCDCHGGGGHGAFCECEAECDCGHHBADHDHDBDBFBFDAHGBBBBBBGCFFFAAEHDFCHGAGHCHGE,False +976,22.0,16.0,20.0,24.0,18.0,27.0,21.0,14.0,GDBDHEGEBFHFHDDCFCDAAGEFBFEDBAHGBGBGDFEBBADGHGFABAFAFDCDCBCAHADDDCAHECCDAAFAFGHCCECFGECECEFDHCHAHGBGBGDECECECEAEAEBFBFGHGHAADDFDBDGAFCFBHACAEEFGFAFDFDFGFGDCDGGFFF,False +977,16.0,17.0,23.0,22.0,27.0,15.0,19.0,22.0,EEGGFDFHCHEEAEDEHEHGCEFGBEBEBHBDDCBAHAHDGDAEGEGDHFECBDDDHDCGCFAAAAAFCEHBBEECEFDFDBDBCCCCEFEGAFFCFCFCEBEAHAHAHAGGHGHCHCBGEDBDGEEHCDGHBCBDAHFHBHFGGDHDEDAGECECBCDCG,False +978,5.0,8.0,11.0,18.0,14.0,13.0,11.0,18.0,HFHDBAGHGEFEHCGGEGDAAFHFEFEFDHDGCECHHEHEDEDHGHDFBFCDHHHAHEHBCBCBCDCDGDECEDGDEBFGDCDEBGHFBFDCDFHFDA,False +979,22.0,10.0,19.0,14.0,19.0,26.0,19.0,18.0,HBGDGHGCGBGEFEAEFBDEHEAAHGGGGHDHDHFGEABAFAHEHCACFFDFDFAFECGCDCDCDCFCHCFCHAHFDCBGAGDEHBGEAFAHAHEFAGHEAGACEEEFFFFEFHFBFCFBACGCAFAFCBEFEGEFCGBDDDCAAAH,False +980,9.0,10.0,16.0,13.0,13.0,13.0,17.0,6.0,CDCEBDGFGFACEBDHFCEHACADBDBHBCBGACCECEFEFGFGACHCACDEEGGGEGEGDGCFFFGFDBDFGGAGAHACDDDDGEGFCFCEHBBEB,False +981,19.0,23.0,15.0,12.0,16.0,18.0,17.0,17.0,ECEDHFHFHFAGAHBHDAEFGFBEHGBGBCBHBCEDGDCBHEAGADEGHFHDBBABEBAGAGCCDADHDCGBBBEGAGAGEBBBGFGFCCBFBFEGHAEGHFCFCFCACEDHDAAAAAHDBFFHFEFCBCBEBEFHA,False +982,21.0,16.0,13.0,14.0,20.0,12.0,19.0,12.0,EBEBGBGDGEGECHCHFAAEHBCAEBHBECECACGCDCDCDBABAFABGHGHAAEAHABDEDEFHFGBCDAEAGFGECDHGFGDDDEHAGGGEGBCFDFAFBEGECEHAFDFGABADAGAEBHFAEB,False +983,22.0,16.0,20.0,28.0,16.0,18.0,28.0,14.0,CGCGBDCDCGHACGFDFDGDBDCFEFEFADAECBDDDEAEAEAHAHABGDFAAGFGFGCAAGEDEGFDFDCGBGAGBGHHHGABCBDBDFDFCFDFGCAHAGACABAFEFAGEEDEHBCCHEGBBBDBDHGEDCHCEFAHHGCDHGGFGDGDGDBEGACDCD,False +984,26.0,22.0,19.0,22.0,24.0,27.0,32.0,24.0,ADHHEFAFADABADAFABCGCGAGFGFEDADABEFHFHGHDFGEGADCCFHHHGHGEFCFCEBDGEFEFEGAFBFBFAHGBEBEAGDFAHABAEGHGCECEHBHBDCFFHBAAGAEAGBCCDCDHDHDBDBGBEDDDCBBFBGEDFDHGEGEGEAFAGGBGBHEGBGFGDECHFAFEHHFCGCGEGCCHCHAAFDG,False +985,7.0,9.0,7.0,9.0,13.0,11.0,7.0,5.0,FCBCHEDFAFHEGBGFAEAEAEAFGDGDBDBABAFGEGDCHCHEEBFCEEHEBEDEFFDFGBDBCCFD,False +986,8.0,13.0,17.0,13.0,13.0,11.0,14.0,10.0,HGEDFDFDFDHDHDHDBFEFAGAEBEDGDHHFBBEEABBBFBHGHCCBCEEGECFBACDCDAAGCFCGBGFFEAGDGHCCDGEGCGCGCHCECBCACEB,False +987,20.0,12.0,18.0,25.0,18.0,18.0,21.0,30.0,AAADFHFAADFECBCECEHEHADCDGDGDCFHFHGCGCGFGFCFHDCAHEEGDGCECHCHEBFBHGHGEFHBHFGDADEDHDAFADEHBBBEGEFHADFDBCGDHHGHGHGDGDHDGDFCFEGGFGCAAEAEBHAHADBHEAADHDCECHDADHCHBHFHAB,False +988,20.0,13.0,12.0,16.0,10.0,14.0,25.0,12.0,BBBCHGHGAGFGHGDCACHCHCAAAAAAEHBDBAFDGDGDFCGGEBAFDEDEHEDGDEDADABCBFDGAGAGHGAEDBGGGGDGBFBHAAGBGHDFEFGAEECCGFFBFGFGHCHAFFCACD,False +989,12.0,14.0,12.0,10.0,10.0,5.0,11.0,8.0,AEFEBABAHACGFBABGBGDEDGDEBBCBCHCECBCACDCGHGHGEACFCBBBEFGDDDCDBDADGEHAACHEGAGFBEHAH,False +990,22.0,22.0,18.0,21.0,13.0,23.0,11.0,18.0,AHAHEFFDDCDFGHDFDECHDHABEBCBCEAFBGGGGFCHCBCHHBEDFAFABCHCBCBCBABDDGHHDBFGEEDADFECGBAECEADADADAFFDFBFBFBFAHDFDBHBDEAEFHFGAHAHAHACCBBABGCGCFHFAFDFDEBCA,False +991,10.0,6.0,7.0,9.0,6.0,4.0,5.0,5.0,FDCBCGFHFHBBBABGDFDAGACACEEECAHDDGDEAAADADAECECHDBGH,False +992,9.0,13.0,4.0,15.0,7.0,15.0,17.0,13.0,DEAHFHGHBEGEBBGFFFAFDFDHDGDGHGHFHFDDDCEGBACGDBDGDEHEHGHGBGBGHFBABABFFFAGADHDGGGHFACBFEDDBCAFB,False +993,1.0,1.0,4.0,3.0,4.0,6.0,1.0,3.0,EFEFEFAFCEGDFHHHDFCBCDC,True +994,16.0,14.0,21.0,15.0,11.0,19.0,16.0,24.0,AHACCCDCAAFBFEFBDBAAGAHHCHDHEHAHEHEBGAGAFHFCGCEFEFEDACHCHCGGGFDFCHCDDDHDHAECHGBGBEHCFBDBGGFHFGBAFHFCDADCFCBCBCEHAHFHBCEGGGFAHBHDCDFHFGDB,False +995,7.0,6.0,13.0,6.0,12.0,13.0,4.0,9.0,CEAFHCHFHECCHEACFCFGGAGFCHCHFAFEDHHCECFBDBDGECHDFEEEEEEBABACFCFDFDFBAB,True +996,4.0,9.0,13.0,8.0,5.0,3.0,3.0,5.0,AGAEADDCACBCBCDCDEHECCFHEDBCBCDDDFEBHBHCCCBBFHGCGB,True +997,3.0,1.0,1.0,6.0,4.0,5.0,7.0,3.0,DDDFHEHCGFGFGFGEDAGAEHFDEDBGAG,True +998,18.0,17.0,15.0,15.0,11.0,15.0,12.0,20.0,EBCFCHHAACHCHCHGBCBCBCHDADAFAFEFDFDGHGHCBCFFHCACDFAFAHAEAEAEFEBCHAFBHBFGAEDBDHDHFBCDEAGABBHGADDBDBDHHHEBAGCEEHFHBGGDGFGAGDB,False +999,6.0,13.0,8.0,13.0,6.0,19.0,12.0,12.0,GDGCGCHCAFGFEFBFDEDHFBFBDBGFDADBFBACGBGDGEFBHHHHBDAFGFGBGHCFFECEFEFBAHFDFBFDAHCHDHCHDFDGB,False diff --git a/tests/results/nb_gm_002_2back_240trials.csv b/tests/results/nb_gm_002_2back_240trials.csv new file mode 100644 index 0000000..1c50201 --- /dev/null +++ b/tests/results/nb_gm_002_2back_240trials.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,ralph_skewed +0,30.0,39.0,31.0,30.0,32.0,24.0,27.0,27.0,False +1,33.0,23.0,27.0,32.0,37.0,34.0,25.0,29.0,False +2,31.0,20.0,37.0,28.0,31.0,32.0,26.0,35.0,False +3,27.0,32.0,39.0,24.0,25.0,34.0,35.0,24.0,False +4,34.0,24.0,38.0,28.0,31.0,29.0,28.0,28.0,False +5,29.0,24.0,36.0,31.0,32.0,32.0,31.0,25.0,False +6,25.0,38.0,28.0,30.0,33.0,30.0,26.0,30.0,False +7,27.0,30.0,30.0,29.0,32.0,26.0,33.0,33.0,False +8,24.0,36.0,32.0,23.0,30.0,29.0,35.0,31.0,False +9,35.0,34.0,30.0,29.0,35.0,26.0,23.0,28.0,False +10,30.0,25.0,33.0,31.0,27.0,37.0,30.0,27.0,False +11,28.0,28.0,29.0,26.0,28.0,27.0,34.0,40.0,False +12,35.0,27.0,30.0,29.0,26.0,30.0,36.0,27.0,False +13,38.0,27.0,31.0,27.0,34.0,23.0,27.0,33.0,False +14,29.0,30.0,28.0,35.0,19.0,30.0,37.0,32.0,False 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+9,11.0,23.0,19.0,24.0,13.0,20.0,28.0,13.0,DFDDFDGFDGCDFFDFEDCCDEGDAHEEDGGGGDAGHFBHFGEDAFGCHGFDBCDBDEBCHDEBGEAFBCHEFEAFBHFCCGEDGADGBCBCDACGCCGFAGBBDCGDBBBEBBECHACFAGFBGABCBBGFHHFHHFGHGGDGGBGBCDB,False +10,10.0,15.0,13.0,9.0,5.0,13.0,10.0,23.0,CAHCFDCFBGFGCFHBHAGHABAAHGFBAFDFBDBHDHCBGEFGDCBDHDEABHHHHGCFCEFCDHCFHBHHGHHGFHGBBABCABCABHEHEFHDCH,False +11,29.0,21.0,32.0,27.0,25.0,25.0,8.0,18.0,HEFAEFGCBEBDCBEADAADADCADABDHHFFEDFBCHACAAFBAFDAFDBCCCFDCEACAACEABFDCFDCFHHFBHDEFDAFCABGAEFDCDCCBCCDCDFAEFDCGCCECCBCBHDEGACBAHBEBEEFDBDHAFHAEAEECEGGHDBHDHCDEADEAHEHFEBFCBAHBHDEGAEFFCFCG,False +12,28.0,27.0,32.0,14.0,15.0,33.0,26.0,13.0,FFFAAFBAHCHHDHGCBBCEBFDGEGBFAACBACBACBAGBGBAGFFGFAHDGHEEFCAAHAHHECFBBFACFACAACDBCAEAHDFHFFCFFEFCAFBEFBFCBCABDBGGFECFGCBCDGGBGFDGDABBCCBEFBEFBAFDACGCCEHGAFCABDGEDFFDCFDGFGGCGGEEGCBGAAGCCCHC,False +13,29.0,16.0,17.0,15.0,16.0,11.0,15.0,11.0,CBECBEFBDDCDCAACAABFAGFEGACCECBEHBEGADFADFBBABCAHCABAABHEEEACEHHAGHABACGDHGDFGCHGCAGDAFAAFCCFEAEBAEDFDDGEABHAGAAGDGBAEDHHGABFEGDCD,False +14,17.0,24.0,25.0,11.0,18.0,20.0,15.0,30.0,DDCDHHAABGECDACBCCFHGEDGAHBABBHFBFFBCFHCHECHECACABHHBHEBHBHDCHCFBAHBFHBEBEDCEDEABCHCHFCHCAFBFBBHGEHGEHGHFCHACHCGGCGCDECFEGHEDFBAFGEFDAAHAHHGFHFABGEBGABGFFEFCEBC,False +15,8.0,6.0,1.0,3.0,4.0,2.0,2.0,6.0,EHBEDEHGEGFABBADBAHCAHAABDAHHABF,True +16,20.0,17.0,20.0,17.0,21.0,21.0,26.0,21.0,DEHCHAEHFEDFDHFCHGCGGCGAFBDDBDCFGEFGEFCEFHDHEFFAGDGDEGAHGFECFACFEEHBEHBGHBGHBGCECEDAHHBGFCCCADHAGHDEDBADGHEBDCHCCFAGEAFAABGABAHBAHBGHCACBEFEGAEFCECBGFDGFDGAGBAGBFG,False +17,12.0,3.0,7.0,9.0,7.0,12.0,9.0,8.0,ADGAGCADCFDFHEFDGHCEHAGGCDAHDCHDAHAFDAFEGFACFECFEBFGBAGAFFAEBDEHGHF,False +18,18.0,19.0,24.0,16.0,21.0,13.0,23.0,20.0,GGEGFBDFGDGEDAHGFBGHAGCDGCAAAHACECDECEBBEDEEDECDFDHBCCDHBHHACBACFHEAEEGHEGDEGAHBAFBEEHCBHCBGGFCGECGECBCAFCGHCBHFHHFHDGGAAEBFCBFDBCBECDCADCACGBHGEHGBFGADHA,False +19,10.0,14.0,15.0,8.0,25.0,14.0,11.0,20.0,EEEEBEEFHEHEEFEEGHEAFFAFHACGDCDDCFDCBDCBFFBCEAHEAHGCGGHGCHEEAEAHEAHEHHCCFGHABHGFGCHGCFDFHEHBBBDFBFBCEAEBHCDGCEEEHBBHB,False +20,16.0,9.0,19.0,17.0,10.0,22.0,10.0,24.0,HFGDDAFEAFEDCGHAADEHDBHAHDCGBAHBECEFFFFFEFEEDHEDCACEGHBGCFGAGGABDHFCHFCHCCDCFHHADFCFFCFFCBFCDHHHHDFFGHHDACDAFDACDCBHCHHAGHABHAB,False +21,6.0,10.0,3.0,4.0,7.0,3.0,3.0,4.0,EABBAEFHEFABAACHDCDDEFBEGHEGBDABHBBCBGEB,True +22,6.0,11.0,12.0,6.0,9.0,6.0,9.0,10.0,AEDBCDECBCHBCBBGFBGFHGEHACHAGAEFBDAECHCFHFDCCECGBCGECGAHGBHBHEBHDFGDE,False +23,11.0,8.0,12.0,13.0,7.0,5.0,13.0,9.0,EAAGACDACDHEEGGGGGBEGEABEAHGCHCCAFCFFGDHGDGCBGBDDEAFAADCDDCDDHBCGBCAFCBDDHHBHH,False +24,36.0,26.0,18.0,26.0,33.0,19.0,21.0,15.0,GBCHFHAAHAFFGBBEFBCFAEFDFGEGEEBECBEBBABBAEBEEAEEABGDBADBACFFBEFCECGACFADABCFDCDBCBBHDHHACGGEHDEGDEGAHAAFAAEDCCHHDDGDDBDGBDBDDCDAGAAFHEDHGDACDACDBGEEACGAEEBEHAFHBGAAAAAAAEEFBEDCDAEEEFGEGGHGFEAFED,False +25,11.0,17.0,16.0,9.0,15.0,15.0,6.0,9.0,CEEFABDBGDBFDFFDGADECBFCBCCACFABEABFABEGBEHBAHEAHEAECCFFCHDCBBBFGBAGCDFHHFBDFDCCHHEHAEBEGCCBFEECEF,False +26,8.0,5.0,15.0,9.0,10.0,7.0,11.0,5.0,ECAGCHDBBDCCDCGHBBEEFDHFEEEHBHGADADGFDEFGAFGAFCCCCCACCDCDGGECGECGEAGFA,False +27,9.0,11.0,8.0,5.0,8.0,4.0,2.0,4.0,FCAFDBEDBABAABAEEAEHDBHCEHCDBCFBABEEGECGBDABFCCAHCB,True +28,6.0,8.0,11.0,7.0,10.0,5.0,9.0,9.0,CFBCBCCBACBEHBEGCADHDGFEGFHGHDAFBAFBEDCDGCHGAACHCHBCEEEEDHEDGEGGH,False +29,24.0,16.0,18.0,25.0,13.0,19.0,26.0,18.0,HEFHCDEGDHFBACGGDEHDGHDGFDEAHFDHGBHEBGEGADFFGCCGDHFBFABDACDABAGFGDAGDAGCAFFAGHHCDHCHACEDDAFDCCDCAECAEDGEDGAFGFCGFAGBBGFBDBBAABAAGADGAFCHBEEGHBGCBFCGFAHHCHDBDDE,False +30,6.0,5.0,2.0,9.0,2.0,4.0,3.0,8.0,DADBAFBDFHDHHBAHEADGFBHFGHEAHDHBDGDCADC,True +31,19.0,18.0,16.0,13.0,19.0,13.0,14.0,15.0,FCHGCAEHAEBDEBABAABHAFEBDCBDCBHCGEAGEFBAFCCECCBCFHEHGEGAEDAECBECEAFEBDHBDEAGFGHDGCDGADFAHGCFCBFDEHEGCEABFADHAFHGBHABHBHDAEBGDFG,False +32,7.0,12.0,12.0,10.0,7.0,5.0,5.0,9.0,EBDGBGBBDCBACGHBDAAHEBGCBFHBFGAFEHFCCCHDCHDCHDAHDCDDEBDEAFECBAHBECC,False +33,1.0,4.0,8.0,1.0,4.0,4.0,5.0,3.0,GAECEGFBHFGHBGCBFCECCECCBCHDGF,True +34,5.0,4.0,6.0,9.0,13.0,13.0,5.0,7.0,CHHEFFDFFDFFDFDGGDFGDHCEAEAHEAFEBFCFEEFEECAECHCHFDEBDBGEGABDEH,True +35,3.0,2.0,3.0,3.0,5.0,4.0,0.0,6.0,CBDEEHHEAHCAEBDFADFHFCHFEH,True +36,13.0,2.0,13.0,8.0,7.0,6.0,16.0,9.0,DEGDECDHGAHGEDGEGACAFCADGACGACHFDACHCCHCEECGHDHBEGGGGCADCAFAGFGGBAGCAHFHFA,True +37,18.0,19.0,17.0,17.0,13.0,17.0,15.0,23.0,HBCABCGHCEEADEDCEDGAGFFFHDFADHHBHHGCHFHHAGHEHEBBBDEFECFEBHCDAADFGDFHDCDCCDCCFACAACHGGBGGBFBCFBFFCFGEDABDBBDAAGAABACBEGBAHAHHFGEDGHDHHEBHBHF,False +38,4.0,6.0,5.0,9.0,6.0,4.0,4.0,6.0,AGDAGHABHCEEFBEFDEHDBHDECDFCDBHDEGBBGCCADFDH,False +39,3.0,5.0,6.0,8.0,8.0,2.0,8.0,6.0,DCEDEEGEEGAAFEHFGHDGDBHDBGBBGECECDGHBGCDDCHCAH,False +40,0.0,0.0,1.0,3.0,1.0,3.0,5.0,1.0,GDGGDCEHFGFDGF,True +41,20.0,19.0,22.0,21.0,30.0,22.0,10.0,26.0,BADBABGCFGFDDDADEFHAAHAAHEAHBBHECFGFDEHDCDBBBHGEDEECCDCCDGCHHBGHCHACFDCFCFEDFEDAHHHBHAECABDABAAEHFEADCFEBFAGFGEABECFEFFECEEFEHFEHEEHDHDCHBBHBDHCEHCDHBDCFAEFAGHEGECBCFEEFE,False +42,3.0,7.0,4.0,4.0,5.0,2.0,5.0,3.0,EBBEAEEHDCHDCGDGGBACBEHBDGBAFBFCG,False +43,21.0,15.0,21.0,27.0,18.0,33.0,14.0,23.0,DDDDDDBCGFEFFABFDHDAGCEFHHACHGBHGBEFEHFEHFCFFCHDGHDFHDAGFECCCAAEAAGHGDFCHFCHBBBFABDEFDFFBBDBAAFDAFAGHACHACEFFEFDHABCAFGDFEDCGACFADFDDFBHFAFFBEHBEHFCHEADEGHEGCDGHDHDEECCFCCD,False +44,27.0,34.0,20.0,19.0,15.0,29.0,27.0,26.0,FGCFGADGADGDDBDBAFGAFDHHHAFBAEEAGGBDBFCEFAHFAHFAECDCBBCGBHAFHABHDCHAHHGBCGECFDCEHCFBCHBGHCABFBCFBEHBECBAHBGDECHFDFBDEAFBBGECGEBBHDBHDBEABEBFCDFHHFGHFAFFGCACFGDGGHGAABCDBHBGGBGGFHGHGGBEADABFABAAFAFF,False +45,15.0,12.0,15.0,7.0,7.0,15.0,11.0,5.0,CAFCDGCFACFCCFACGBBGCAEAEGAHFADBCHACHFCFBEFGEGBDGBDGBEGEHAEFGBFCDFBFBHACAFCAFGABDAFACDB,False +46,12.0,10.0,7.0,5.0,4.0,11.0,11.0,13.0,ECFFHGFGGFCGACGFGGAHFABBHDEDCHABFBHGAHGAHCAHDABDFHDFGCHGBEABAHEHBFHBFCBAA,False +47,15.0,6.0,13.0,11.0,17.0,21.0,13.0,9.0,EDCEFAEFAFFAGHCFCEEAFGFFHFDECECCEGCDGHDGHDGHACFFCFFCDFEHEEFEEGHEDAFBGEAAHAAGCABAEFAFDABGFCFHCDEDBABFGBGGD,False +48,11.0,17.0,17.0,9.0,17.0,17.0,13.0,15.0,GAFGHHGCHBCACCFBCFHHECHBHAFHEEGBAFCAGHGEFGEDGFCBBEBGABCFDCFDCFDBEEEGAAHDAEDFECBGCBHDBFEGHHBFGBFEBFCBCCHEFAEDAEDCEFHB,False +49,13.0,16.0,15.0,12.0,16.0,9.0,12.0,15.0,BGCBAEBCDBEDBECBDCBABDCDFCDBCEGDABDFFEHCEDGECHACHEBDECDGHFFHFHEAHAHHEFFBAGAGHCHCCHGCEEAAAAGEEGDEGBFGBAGBHHBH,False +50,13.0,6.0,16.0,14.0,12.0,13.0,9.0,12.0,DAEAAGAAGCHCCHDFHEFCCBEGFEGFHAHEAGBGCBFCBFCDACDAFDCHECEBFBAFCFFDEHAGHDEFDGCDECEHCHDGADEHHFADCDD,False +51,22.0,27.0,26.0,19.0,24.0,22.0,28.0,20.0,FDCGDAACFACHGCDGEBFCBDCBGBEGBEGAGGFGGCHGDHGDCAACHADHCFHAAEEBBCBCCBAEDAGBFGAFGEGGDGHCEEEDEHCBBCDECEBGEFCCHCFBCFBHFEABEBDEDHABHDBFFFCEFCEDHFFHBFABHAGGECAEADBGGEGAABHAGHAGEFGBFBFHHDHBEGBFCCDD,False +52,19.0,24.0,24.0,17.0,11.0,20.0,12.0,18.0,FBDFCFECGDCFBBFHBFHBAHECHAAHAFCAHCHCFBDFCDHCDBDDBAGAAGAGHFGBDABCFEEAHHGDHBDCCGCCDAEBAEFEBCHBHECHDABFFBHECFDCBDBFDGGDBFABGHBGFCFCBDCBACBFGHEACEACA,False +53,11.0,13.0,7.0,11.0,11.0,7.0,5.0,12.0,HABDABEADFFDABBHBEDAEDACBEHBEGBDDEAAHAHGBHBDEBAEDECCHFDHFGHFGHFDCCEBHEBHGCACF,False +54,11.0,20.0,14.0,17.0,12.0,15.0,15.0,22.0,DFABFDGCDCDDCBHCBECBDHHHBEFBGFEGHGFHEFEAFAHDBHDGDGEDFBAFBGFBGAGGHHCHHEDBDDBCFFCGFCHEEECDDADHBHHCDHCBHFAEGBCBBAHBAGEFGAHABHCBHG,False +55,17.0,24.0,24.0,12.0,23.0,20.0,17.0,26.0,GAECBGBFHAHHEFEGCGFBGBCHHADCACHBGGBHBAHBAEFAFGGFBCCAFCFHCGHCFHCBEFBEFBCHBGFECFGDHBEHCCACGFHEDAEBAEDDEDCEHBEBBEGEEHHACHECBDFFDFADFAEFHCFHCBECDEHDEHCBAGBAGADGBCBHHEH,False +56,17.0,25.0,29.0,22.0,21.0,19.0,27.0,22.0,FFFFFGGHDEHDFGAFGEEAFEGCEADDBBDHDCHECDGCDAAFCDHBGCBGBBECCDCCDAHGBHCBGCHCCEFEGFAABBEHFEHBCGFHGCHBDHCDHCFBDEBEABEDBCDGCHCCFGCFDAGGBGBBCBFABFEGGADGHEGHEDFBBCBCGACDAEEABDADGGEGHEGCCHHAHH,False +57,12.0,11.0,4.0,15.0,9.0,3.0,6.0,8.0,HABCEHAECBEDEDDHBDGAAFHAGCBGBEAAABADEADGHDFBAFBDEBEEBGDCDDGDDHDAHDBH,True +58,9.0,8.0,9.0,9.0,4.0,9.0,12.0,13.0,CAGCGGCBAHDEFDHHGHDFDBFBBFGAFEBFECHABGGDGDEGDHGBHADGFDCACAACHBFHFGHCHHCHA,False +59,15.0,19.0,20.0,23.0,14.0,16.0,21.0,18.0,GDGGBGGCFGABBABFGEFGCDDCFBCDBEBACHABGEBCDCCDFDDFDAACEBCEGGGFHHFDHGGHFGADHFHHGDHDFFGHGGHDEBDCAACGACFADDHDDCBDBBFEBHDDHFCEGBEHCABEAHEAHEFCCHBAEBCEDC,False +60,9.0,8.0,2.0,6.0,8.0,11.0,5.0,10.0,FEBDCDFHFEHFEHEGHBHFBHFEDCHBBBAGEAGEAGHADABFHFFDBFAEFADAAHG,False +61,26.0,25.0,20.0,16.0,13.0,13.0,17.0,12.0,CBACHGCFDHEBHBBEBBFAHCCEAEEABDDBDGEGADGHDAHEABBBEFCFFDEFDAGDADBBHGGCEGBAADABCHGCHGBDBBGCBGCHFAEFCHFBFDDCAACHACFACAACABFEBFAAEGGCGBCGBAGBDDACAA,False +62,9.0,9.0,5.0,7.0,5.0,5.0,11.0,6.0,FAADDAGBGGBGBCHBCAGEADACGAHGACFECDABBFEFDGGDFGHBGHDEHBEHB,False +63,7.0,8.0,8.0,6.0,13.0,12.0,11.0,4.0,GGBDGFEGCEGCECHDCFGFGABGFEHFCGGBHFBHEGEEAEEAFEDBCFBDFDEADACBABFACFEEF,False +64,20.0,11.0,23.0,13.0,16.0,11.0,12.0,18.0,AEDAHACHEFAEFAHCAEDAEDCBAGGCBGFBCHCHFCEACHCEHCFHCEAEAAEAHCAGBDCDHCEHEGBFCHHCGHFBHFAAGEADHBDCADCFDGFDCHDCBGCGAAHCGFGDEBDEBECB,False +65,19.0,12.0,22.0,18.0,18.0,14.0,20.0,17.0,CCDCCAFHAECADDGDGACGADGHDFHEBGEFEAFDHBDGBCGCFHBGHEGAEGBDHFDFDCGDHGDAGDCBHEBHEBGBAFHGCGCCFEEFCDCCDCHECHFCFAAAGECHBBEEBHDAGAAEAAEAHEGHCFCEFGAD,False +66,26.0,13.0,22.0,33.0,10.0,21.0,25.0,20.0,CDFGDFAHFEHDHBBCDECDAHDGGGFBCDBADHHDGADEBDEGDHFFCFFDHDGADHCFHDAGEGCEACGBGGEAGFAGBBDABCABGADGAHADDADCADHAFCFGDGEFBEAHDCGDHDCADFADFGHCCHGFHCFHGDHGHGECCCCCADBFDGAABAFDAFDAFC,False +67,3.0,0.0,0.0,5.0,2.0,3.0,2.0,1.0,FDFEDHDGAFGADEAD,True +68,21.0,30.0,10.0,18.0,20.0,13.0,15.0,10.0,ABBHBEEEHDEHDGFFGDBDBBCABFGDCCDHFHHAAAAABFAEEDBEDBGBBEABEABFBBFBBDDAEEAGCFHEBAFAGDGGBBEDBHDFEFEEBEEBABDHBFBGCBGCGGBGCCGCEGAADAABCDDADEAHF,False +69,23.0,30.0,20.0,17.0,29.0,22.0,24.0,20.0,BHBBFBBEEAEGAEHBCABCBGCGEFHEGHFFBFCBFCHEEDEGCCGBCHFHBAACDGBFBEAEAFEHFEHGHGGACBEDDDBDFBGBAGBAGEDGEHAEDDHGDFEDFEHFACCAEHFBCGBCECFGFFAEGAEAHHBGABGAEGDCGDCHDBBEFAECDHCDHABAFBACBAFBFGEDEEHGB,False +70,16.0,21.0,23.0,21.0,35.0,31.0,21.0,19.0,FEGHEGHEHFBHEBDEGDABDAGFAGCDGCEAEABGGEFEBAEBHDFEFACFEHFHHEBFGGDGBAGBAEEAFBACBCBDFFDGEECFEDFEAFEFFEDFBBFHFFCGFBFCECEHCHFFHGFDGFHECEGCDDBDDEECCBDHADHADEEEECDBCBFHGFHGBCGFCHCCBGDEEAEHAECDCCF,False +71,21.0,21.0,25.0,23.0,34.0,29.0,19.0,27.0,CGCABAFBECCEGAEFEEHEDHEFBAFBFFGFDCBDFHDFDDHCCAEGAEGEECFCDFGDHCDAFDFFHBAEGDECFHHFHHEAABFABAAHCCCCHHGBBCBHGGHEFDFFCGFDGHDAHAGHCEEBBEDBEGEHBEGCHAEHDEHFEBDECFHABHABAAFDDFDDFBEFGHGCEECFDCDCEECEEAHEGHEFBBG,False +72,26.0,9.0,19.0,24.0,24.0,27.0,21.0,27.0,DDGBDCADHEDABHHHAEHAHDCHDBFFEEFAEFAHGACFFEEDHACFCCFGCDACDCCDCEDBADHFEGDHDFHGCHFAEFHDFGFGEFGEGGEHEHHAHFEHCAAEAFCHDCFFFGABAFEAGGBGHCHDFHDAAGAFCADGADHAGHBGBBEEEGEEFAEFAEFCGDCFDHGDH,False +73,24.0,24.0,23.0,19.0,22.0,18.0,26.0,30.0,HGFHGHHBBHDBAGCEDEHDHCDAAGCBCCHCCDGGHAGHGHHFAEFGEGBEBFDFAEAHBBHBDCBDCBCCDECHHFHDDHCGAAAAEAEEDBGDBGCFACGAHGDFGCGHABBACBAHGHHBHGBEDDACFACFEBFGHCAEBGEBGEDGEDHEFFECEEAEFGGHHFBBFCHFBAFGAEHACD,False +74,26.0,17.0,19.0,17.0,28.0,19.0,13.0,23.0,EGCAHEHHEHABADBADECBECEEABEACFACACFFBFGBFBDFCFCCACAHEBHEGHDBHBBAFEADEHBCHEEHEGBFGBFDCGDEFDEADEDHEAAFFEFFHHFACDCCEAHDADDEEEFAFGADBHEBEAGAGDAHBCHCGHCAHGACGEEFAHGHHD,False +75,3.0,1.0,2.0,0.0,2.0,1.0,0.0,4.0,EAHBCHCAHEAHF,True +76,10.0,5.0,4.0,6.0,10.0,5.0,10.0,8.0,HGHHAEEAEDAECGDCAHGFBGAGEFGFBEFAFCGCEAEEBGEBGDDHDBHDAHGAHA,False +77,6.0,2.0,4.0,1.0,4.0,1.0,1.0,0.0,AACCDECAEBAEBAGFECA,True +78,26.0,21.0,24.0,22.0,21.0,23.0,16.0,22.0,AEAFDAFGAFHAHCGFCGFHDCBDCBABADBCDGGFGHEBBDFBFFDCDEAEEGGFHAHDCDDBGEHCEFCHFGEFDADGFHFBDFCCCBCGBCABDFHAEBCHBCHBCDECEGFFAHFAHFCHFDDCAEHAGHBGHBAEECDDDDAABAHECHEBHEAHABGEBAEACEACEAF,False +79,23.0,23.0,29.0,21.0,13.0,23.0,22.0,17.0,CDHBACEAHEFDEGHAGAAGFAHFADFCBBBEFBCDGFBCDBDHGGGGCGFBDBBCFBFDEGEEHEGGBGEHFCCFCBDCEDAEABFDHHBFBBCAGDDCHDCHDAHBACAGCAGCADDBDFHAFCAFCGHDEBGHBCHGCHFBEGBFACFCCACAADACFACFCCFGFDG,False +80,12.0,12.0,23.0,9.0,27.0,13.0,18.0,19.0,EGFECEECHEBEEHHFBDCGCAACFBCGEHEEGCEACEGDEADAGBAGBCDBFBHFHACHCDHCDHCECCEGFHGFBABCGDCBDCEACHBCGGAEEAECFEHHAFFEEFHFCEFCHGGGGDHBEHGGHEEHE,False +81,25.0,15.0,14.0,17.0,20.0,16.0,15.0,15.0,DGDFFBFFCAFHADGAEEAFDABDEGGEBGDGEDEBAHAAEGABAHCACEACAHBAGGECFCDDEDBEFHEBGAFCAFCAHDEHDAFAGFCDBCHCCHCEDBGFGHBADBHGBEAAHAAHAEFECFEDFEDHEBHGB,False +82,23.0,16.0,15.0,28.0,9.0,16.0,15.0,26.0,FAHGHHFHGDHGDHDHCCHFBHEDGDGADGBDFDHFBBEDBADEDDBDHFDACDBFGBFAHCDDDGDBGBBGAAADCHFCHCDGABFHDDHDAEDCEDCGDFEAAEACHHGHDGCFFCHABHAHHAFCFHAAHAACBABBHFEAGEAC,False +83,16.0,17.0,21.0,14.0,11.0,17.0,24.0,19.0,EGHCBBCBBHFAHAAGAFGHBCDFAGFBDABDADEEDBCDBCHBCBGEGFFGFGGCHGCGGHHADHDHCDHAFGACCEHDGHFFCDFEDAHDFFAFFHEGBDGCGCBECECHBGHGGHCGBCHBCEGFGGFCACAABAE,False +84,25.0,24.0,34.0,20.0,21.0,23.0,18.0,22.0,GCCGAFHHFBGFBCFBDFBGFCGDEGCAHEBCAFCBFHEFEDCGFCAFCHCHBCHEAHAFBAFDAHBHBDGAABAFBACACHHCFDAFDGBAHBEBBEDFCFECAEBGFHECCCCCCHHEEHAAFDGFDHBDGBEFBEDDHDDEBHECCECCEBAEBAGACGEDGADCBCCGGCDEAGCADCAFHHD,False +85,14.0,17.0,15.0,14.0,15.0,14.0,16.0,10.0,GGCGDDEBFFHGFBGFBHFHHEDAACAABGFFFCDBGBEHBEDBFDBCDCDGCDEFBCHBEGBEGBEFHGFBAEBCEFAAGGCHCCFCCBCHEHEAACADDEDDAGDAGEAEBAG,False +86,5.0,2.0,1.0,1.0,1.0,1.0,3.0,1.0,ADFAGGAHGBEABCA,True +87,28.0,33.0,23.0,19.0,20.0,25.0,30.0,22.0,FFGDBGHBGEGAADDHGEEDEHBBACDFCGFCGEHFBBFHBFBCCGCCFHDFCGHBECBAAFFDBBCBECGGFEGECCAGABBABHAEHBBHBHDEFDCHDBAFFDDFAAHAAHCDFCAHEAHGAHFAHAGHAGAAGEEDFGBEBECBGCBAFBGCCGAFAAFHAGGFGGBGGBDEEGEGBFGBFHBCHBDDBDDBECCA,False +88,27.0,30.0,28.0,20.0,23.0,12.0,23.0,29.0,EGBCBBCEBCHHGDBECBCDBEDGEHGAGACGEHGCDACFECFCBHBBFDAHCACBACBEFGGAGGADAAEBAHDFHDCDBAHCHHBHABGCBEEDHGHHGFHAHDAEDABDGCDECDBADBHHGHHGFGECBEABDHFDGAHEACFGCAGCABCHBFECHCBFCBFAEABDAGEHEEAECABDHBHHCEBG,False +89,14.0,15.0,7.0,17.0,10.0,11.0,15.0,9.0,CHBADFABGHBGFGGAGGADGDEBHADHGHGFDFDDCDBGAAGHAGFAEEBBEDBEBCEBFAFDAFDFGDEADEGDFACCCGBHBBHABHDEDCBDFE,False +90,5.0,3.0,3.0,1.0,8.0,0.0,6.0,3.0,CCACEGHEGDEGBBAHEHGBAGEAEEAEG,True +91,0.0,0.0,4.0,2.0,4.0,2.0,2.0,1.0,GDCFDCEECGEHFEC,True +92,14.0,4.0,7.0,10.0,8.0,6.0,12.0,5.0,DCDAEFAFCECEEAFEDFEGCCGACBDGHFAHBGEBGAGGAGGDGAEGHHGAADAFDADDCBAHDA,False +93,10.0,8.0,8.0,3.0,8.0,14.0,16.0,15.0,FAGFDGHDHHEHEEGGFFACFHEHACCACHFGHFGHCGCAGCGBCFFEGFGBHABHFDHGBGBHABHAFFAGFEHEEBBAGG,True +94,21.0,25.0,21.0,30.0,27.0,13.0,12.0,17.0,HHBEBCAACEABDGDGBDFBGFCAEHGDCADCHDCEDFEDCEDGDCEDAEGEHAADBBDAADHCDHDFHBEEBEEBCEGAECDEBBCGAHEBBFFHEBHEHDAHDAECFFDFEDFBDABDCCACEDEBDHDDAGFAEABECBHGFDDFEDCCBHCBHGBEGBACBA,False +95,4.0,6.0,6.0,8.0,7.0,6.0,6.0,9.0,EDGEBHEFHACBBCFEGHCHDAHDEHDBHDBDDEHFCGECGFGBFACFAHGD,False +96,8.0,5.0,5.0,6.0,5.0,8.0,12.0,12.0,AFACCAGAGGFBEHEGHECFDFFDGFHGAHGHHFDGAGCAGEFGHBBHEBHDDHDHHGCBA,False +97,20.0,25.0,21.0,20.0,27.0,26.0,25.0,26.0,BFCFGDFBECHDCEBGEFGBABHGDDGAFBEBCEFEEFGDAHFBHEHHCHDDHGEFDFFBGBBAEGCCFDDABEBBEBFHBHHBCCECEDCAFCGFGHFCBGHBEAFCBFDEEAEEAFECEBBGGAGHBDHFHHFHHFHHFHHEEHGCDABGABGACGAFGAGGDDEDDCADCFGAFGDCAHEAHEAEGC,False +98,4.0,3.0,1.0,1.0,6.0,1.0,5.0,3.0,BBAHAEDECGEAGBAGEEGHEGHF,True +99,21.0,17.0,15.0,21.0,17.0,23.0,10.0,21.0,AHDDHEDGFFGCFHDHAGHGHHDDFADFABHDBCCACAAHGDDFDDFGBHEBHBHEEHEFCFFBBDDBAABCEEHDACDHCEEAAEBHBFABFABCABFFFFDFFDFEEFCEHCEBDEBFCAGAGGDGCHBCHAAHEFFECAADH,False +100,21.0,17.0,13.0,22.0,21.0,22.0,21.0,31.0,GCAADDGBDEBDABDGDGGEADEDDFHHHEHDGHFGHFDHGAFAHEHDCHDHFEBGEACDACGABGABGFGGDGBHEEHEFFGHFABDHEDAECBFHAGHAHBAEAAEAFEHFEBGGBCFDFEEAHCHHCFDAFDCFDBFHBAHCHHFFGEHDECCGCBHFHHFBHBE,False +101,3.0,4.0,2.0,2.0,2.0,1.0,2.0,2.0,BCFBEABEABHADGCHGD,False +102,3.0,5.0,4.0,4.0,2.0,1.0,3.0,10.0,BGHBGHCCHCDHEHHABDFHDBHEGCDAHBAH,True +103,22.0,16.0,17.0,17.0,11.0,10.0,13.0,12.0,DECDFCDFEDCCBCCBCADGAGFAEAAHHCGECAAFHAHBAGEFDEFHHGGFBFCBACBABDACDAHDAGDGBDBADHFDBCEHGEHGDHABGBCEDEEHBAABADCGGCFCABDABA,False +104,12.0,15.0,10.0,16.0,25.0,15.0,20.0,17.0,GBFDCFDGDDBHDAADEBGBDEBEEFGHFGHFGHCGHEGDEADHBDHGGBGHEDCFHAAHACHGGEGGEFEBFGADCCEBHEGFEHDEHEEFAGDCHFEEAEEBCEGEDBEDBECBFFBHHCAFAEGAFB,False +105,7.0,10.0,8.0,8.0,6.0,8.0,6.0,10.0,HBEHAGHFGHBGDBAAGCDEHFEBEHBEBCABAACDFHBCHDFGDFGDFHCHCCACBFDBEDF,False +106,17.0,20.0,9.0,15.0,13.0,17.0,14.0,15.0,FBEAGDAGAABAHBGEFFBFFEDHEGHEGHEFHFDBBCBBDBCHCAHGAHCHBEGFDGFAEBAEGADCAHBDFBDFDFBABHEFGBCDAFDBCAGCFBHFBAFAEDHEDCEDHBDGGHGA,False +107,5.0,5.0,1.0,5.0,1.0,5.0,5.0,2.0,FABAAGDGFDFHBFEBAGBAGBFDDHGDC,True +108,17.0,16.0,20.0,15.0,16.0,19.0,21.0,30.0,CBHCHHDDDGADGAFCEHEBHEFEAAEBHFHCBGFAEDHEFEFFCFFAHEHHAHBGCDCHFGHBGFCGFBEABFBHHGHHGCHEAHEADABGHBHHBDHGDHGAGGBGGEFCFFCDBGDFDAECEECGCAGCGDCFDFHHAHHDHBBCCACGAC,False +109,19.0,26.0,19.0,10.0,27.0,23.0,8.0,14.0,EBCAAAGFADFADFEFBBBCBEABEABEAEEHEEHEECEBGACCAFCBHCDCCECFBCAGGAFEAFEFBHHBDFAHEHFEGFHCFBBHCCABCHFFBFFBDGCEGEBAEGCFFEEDHFFBFBADBDBBDBBEHEEFCHACBAHDEE,False +110,19.0,10.0,10.0,17.0,15.0,14.0,13.0,9.0,EACEADEDDGDAEBCFACEAEBFHFFGDFEDBBGBHGCADCFBBBHCAHEAHFAHAAHCDGCDGAEGAEGEDDFGEAEBAGFCGDGDDABDFCDFGFFAAEDFEHAH,False +111,6.0,10.0,13.0,9.0,4.0,7.0,3.0,10.0,CCCAFBAFBEHDFBCCBCHBCBCGHDAHDAGDCDFCHCEHDAFDFHDHHDEEBFBAGBCHBC,True +112,14.0,15.0,18.0,9.0,20.0,11.0,10.0,7.0,DEFDEFBEACFGEFCACCBGGBHAAEBEHCEGGEDEEFEEDBECBABGADFADFADGCHCCHCHACEDHEGAFAEFBFBAEACCAEBBGBBGEBEBHCCDCCFC,False +113,18.0,25.0,13.0,24.0,29.0,22.0,19.0,30.0,HCAHEABDACHBBDDHADBEHEEHCABCFBHFBABBABDHBEHFGAFGFHCHGCAEFHEFHGHCGCEHDDFEBFEFFDDHDEEDGEFCBGBDGAHHCHDCFDEEDGCFHHFEEFGBGGEEHBFAGFDHBEGFEDCEDEBDEFHEAHEAHABBEDBGFBGEHGAHFADBADHADHEDBGGB,False +114,13.0,9.0,15.0,32.0,17.0,18.0,11.0,14.0,HDHDDAGGFDDFHBFBCAEDGEDCEACDDEEDFHFAGFDECDCCDFADECFECHDCHDGAGAHGHDFEDCEDCEHBHDAHDCFDBFHHGDBDAFCGFAHFDCCDAEDGEDEEFADFAGFBBDEBDEBDF,False +115,21.0,18.0,26.0,25.0,21.0,27.0,25.0,34.0,AACCECDFFBBDABHAGHGFHGHAFHBFHFEHCBHFDAGHAGEDBEACHDCAGCDCCDBEDBDDEGGEHGAHFAHDBFGHFGCDCCFCBFCBHCHHFFDFGEEEDHFHHFHDFEDFDCBHAGAAGHBEEDCFFCHEDAEBAGDEGDEDBFBGCBECHCGHCDAGGAHGHCGHCFHBFHCFHDADAEGEGHCGAFFEH,False +116,25.0,15.0,25.0,18.0,19.0,11.0,22.0,30.0,BGGBGDHGBAECHEFABDHBHHBHDADBEEGFGGDGCCGFCHHHAHAFHBFEEGEAHCGEAGDCCHCGDAGBAGBAEADBADHADFCGHEDHCABCHHEHDFHFAHEAHCHCAHBDHBGHFGEFCAGCHGAAACAACHHDHCCGECEDDFCDACDACBCCEEGEE,False +117,28.0,24.0,15.0,28.0,23.0,30.0,14.0,19.0,CHACHAGEBEFDCFAGFADDEDDBDGBDBFEBEDHHDGDECDEBFABFAFFABAAHHAHHDFHFBHDBEDADCBGHEDFFDEDDEBEBAGADDFFFBDFBFFBFFBHACFDBFDFAEBACBACGEGGCFAFEHEAHECHBDGGFCAECFEFHEHHAGACBDCBAHAAEAAEDECDAFGGFB,False +118,0.0,3.0,1.0,0.0,4.0,1.0,0.0,2.0,FHBBEEBEECH,True +119,15.0,14.0,10.0,15.0,7.0,12.0,18.0,9.0,BGDBGBFEBDCFAFFADCGGAGDABAAHHAHHACEBCDDCBDAGDGBBGDGDDACEFCFFCGFHGBEFCGACHAGAGHAGDABBEEFHGFBFDBEDGHDG,False +120,18.0,23.0,21.0,12.0,21.0,14.0,26.0,15.0,GBBHAAEBAEHEEFEGFGCAECABAGCADBEFAAGDABCAGGFGGCHGCHGAHEAHFFCEHCEBBFBBEHBCGECGACGDCGDHGCGGHGGDDGHACBBGDBDECDCFABECFEBFECEBGBBEDDEGFCDFEGBHGBHAHFACEBCHBF,False +121,18.0,17.0,15.0,11.0,14.0,12.0,17.0,17.0,AGGAFDDFCDBBHECHBCHADHCBACFACDDGFACEBCBBGBHAAHEAEEHGFGCFGBHEBAFHAHHADHBEGBHHCEFEEFGHFGFGCBDCADGBDHHEBEBBAADAAFCAGCGGEGGEC,False +122,19.0,12.0,14.0,16.0,13.0,13.0,22.0,12.0,DFAEFDEBHGFEEDAEDFGGCGGFGGFGGAGGAFFDEAGEAGDBBABDHHCHHBDHBDGCGGDHDAGCACCBFCBABHEFHCCHECBCGDDAHDCEEFACFBCAGDAGAAGAEFAGDBEHA,False +123,3.0,8.0,5.0,11.0,9.0,10.0,4.0,11.0,EBFFHHFADFCHFGHEGHFGFACDEDDEGHFAEDHBDEBDECDCDDFHBFEBHHBCEBHDB,True +124,4.0,5.0,6.0,11.0,9.0,6.0,5.0,8.0,ACEACEADEDEHDCFFCDCCEHHEHEBHGBDGHDFDFEGFEDBHDHDBBGFAGD,False +125,11.0,14.0,19.0,12.0,21.0,14.0,17.0,9.0,CCDCBDBEDHEGHAFEECDGCFGCEGCBGEFAEDACCHCDHGFEFFBBEABEAHHAFCCFBFFCFCBEGDACDGCAEBAEGGEDGEDCAGGEDHEBHBBACBHGFEGEGDEGEFCBF,False +126,7.0,15.0,16.0,15.0,17.0,19.0,21.0,17.0,CHHHDBCCEFEEBEGBHFEDGEBFFBGFGHHGHHGEHDHCDHCDFAFFDCABAFBHGBCGBFHBDHCEGAGGHHGDEAFECHDBFGBDBCDECGEFEEBECBDFFDECGGCGADGEDGFGCFGCFAF,False +127,1.0,2.0,2.0,2.0,3.0,3.0,7.0,2.0,BEGGGGACFHCFHEFDGGDEGB,True +128,24.0,27.0,28.0,25.0,25.0,12.0,31.0,20.0,GGGBGGBDBCDHGACGEHDCHDCBDCHHEHBGHADDADDEBGGHGDDEADFAHFAGGEGEEABEHDEHCEBAEBECBACBACGACGADFADBBBBFCCAEGHFBEBCAAHBCHFCEFCDFCDCCBAEGEGCAGCGCCGEHFEHGCCACAACBDDBHGBEBDAFGEFGBBGHHEDGDABCGFHDEGGEDEADB,False +129,8.0,19.0,18.0,15.0,11.0,19.0,15.0,9.0,BEEBFHGAACFBCEBFHFADFCDHCDBCGBGGEGBDAADFDCHECHECEGCFGCFGFBCFGCAGDFGFFHHBDDFCDFBBEDBFDGDBBFBHABCEBCDAEGCBFHBFCGECGD,False +130,19.0,16.0,11.0,13.0,12.0,17.0,19.0,19.0,AGFEGFGGEGDAFDBFDBCGACBHEHHAHHDFADABHAGHBFHDFCDCADEEFEGBDGBEGADBAHFGBDGBAEFAGFBCAECHGBGFBGBBFBHAHHAHDEGEFAHADCACCHCEHGAHFHGFCF,False +131,4.0,4.0,2.0,0.0,2.0,2.0,3.0,2.0,FBECAGHAHCAGBAGBEFB,True +132,21.0,22.0,26.0,22.0,19.0,22.0,19.0,31.0,HHACHAGHDFHCACFECAECGDFFDFCAACEBEDHHAHDCGBCBBCAHCAFCDBGFGDCHBHECHCFACFGCHECBBCFBGHDGHEGHDGFBAADFGBGGFCGHCBHAGHFEEEDAEDAHHABFABHAHHGHBFDAFDGDDFEDGBDFEDHDDHCEHEAHECEECEADBGCBFFHCFBBBBH,False +133,16.0,18.0,20.0,18.0,16.0,13.0,27.0,16.0,DGGBCEDCEFHDGHFBDCHFHHBACBADAAHADEACBGHFGEDGCBCABGAGFCGDCGDGBEGBEGBECEEHGEHGHHDAAGGACBDGBGCBACDEBDBGCFHFEHCEGCEAEFCHFABFEGGCDHFDCDDCDBFGBFGAGHAG,False +134,19.0,21.0,15.0,10.0,12.0,12.0,10.0,11.0,DAGDAGAAHHFHABCBBCEBCFBCGDCGEEACACBACEAFGBDAAFEAFEHBBBFECDEADGFFACGECBBCBBGEBFEBDAACHADHFEFBCHBFGBHDBCGBHADHAH,False +135,13.0,9.0,13.0,6.0,13.0,9.0,17.0,10.0,ACEEHFBHFBGFCHABEADHHCGACGDHBCABEGBEDBGGCGHHAHCEDAEFAEGCEACEAGGFCGCDGBFGAFGAFBEGCEGAFGECHD,False +136,12.0,12.0,9.0,6.0,6.0,6.0,7.0,12.0,DGFDCFBCHHHHHHHBHBBABEAFGBEGCFDFGCCBDABAAEAAHACCAGHADEACGHGEBEFBCDBHAB,False +137,8.0,7.0,7.0,10.0,12.0,16.0,11.0,8.0,EEHEGHGAHFFEFEDBGDBEBBGGFGDCGFCFCGFDDFHDFHAFCFDGAAFFAEHAEDFEGFEDCEGAEFBHBCDBCHA,False +138,16.0,20.0,15.0,26.0,16.0,10.0,21.0,11.0,BCEFDBCDBAHBEFBCAHCAEBDCCDHGHHCHDDDEGBFDFGCACAEEDGADGEDBEGCEHCHBGHBEDDADDGBDGBCGBDHCFGCGGFGGAAEAADAEDGEDBEBADDADGCDGBAGBDGBHGFFBEDAEFBF,False +139,13.0,8.0,3.0,6.0,6.0,4.0,5.0,4.0,EDGABAADGAECAGAAGAACHFFHABGFBABBEDBEHBAHCABDFDEED,True +140,3.0,7.0,9.0,8.0,11.0,8.0,12.0,4.0,FGFCGCCEEDFEBFEBDACHADEBCEDFBDEHEFBEHCEDCGGBGFBEFCGGDGHDGCGGAG,False +141,7.0,6.0,3.0,11.0,10.0,4.0,8.0,7.0,EEAAECEEGHEHDFDCHCGHEAAEHBDFBDBGDBADBEHFEAFGGDHDDGBDGADG,False +142,25.0,23.0,17.0,19.0,29.0,25.0,18.0,29.0,EEBEEBHHHHBCHEFDGCDECDEDBEFHAFGBFBHFBHFCHFEDFBBFEAEGBCBAAAADAHEEFAEFDFACHHCHBEHBHHDGECFEFBEGHEGHAFHCDBCAGHEGHGDHGEGGFAAFAHEEHBFABDACHABDCDAFGFFGCFECFHBFEEDDGDBFCAHAEDDEACEAGDBGAAGAHCBHB,False +143,1.0,2.0,2.0,3.0,4.0,5.0,2.0,3.0,CFDCBDHGEEGAEDFEFFBHFH,True +144,9.0,4.0,7.0,5.0,3.0,7.0,3.0,7.0,EFAFABHACHECHGCBADBADAADGCFFAHGHDFHDCHFCBECAF,False +145,21.0,27.0,26.0,22.0,15.0,22.0,16.0,17.0,FCDFDDECEHCFGCEGDABBGHCGBBFABAEFEEFACHBGFEABEDBHCCFGAFEEFHAFECFHCEBCDBCBAHFAHFCFFCFFBFAGGAECDCCBBDDCDDCABBAGGAGBAGHCHECDACBAFHECGBGGBAGBHBACCADDDDCHHHFHHBDDBDDBDBADBF,False +146,23.0,23.0,27.0,18.0,23.0,27.0,25.0,28.0,DEGHEGFDBFGHDEACECDFDDFDBBBGCEAFHFFHFEBGEBDEBFBBFHFFEFCGFCGCHGAHBCFGAAECGEGDDGCHGAHAAHAADDADCAFBFFBHBHEGCAHCHHBEACCBBABBDBHCBDFAHAEBCEGEGCBHEHFAGCAFCACEFHEFADBCGGCGHAGHGEHEFHCAHCGHDGHCEHCEFCGFDF,False +147,19.0,22.0,21.0,22.0,15.0,18.0,18.0,18.0,ADDADEFBADAHFBBFBBCHGCGBCBHEDCCDHDDACGEGBEACEBCGCFABFHEAHFGDCDDCGFCGHEHHEHBFHDFBFFBAFAABAADACDFCEFHADGADCCECDBHDBCGBAEBAHDHHDHACFCGFGEFHEGGCGEFGBDGBGBBDE,False +148,23.0,18.0,18.0,17.0,20.0,20.0,23.0,19.0,GHBGCBDAFDAFHCBEFGACAECHHGEGFEGDEDDBCAAGFAGCGECAEFBEACEHGEHAEAFEAFBCGCCFCBBGHBAFBFCBFAEHBEHBEGAACFABGEDGHAGBCGCEBDGDDHEAHCADFFGHAHDGHDGHDGBDABHAEDDFHDFCFFHGFE,False +149,11.0,9.0,14.0,14.0,12.0,13.0,8.0,11.0,CCFCGFCDFHHHGGHEDDFHDFEEGCEAHAHCADFEBBBCBFCAHBAHEACDDCDACDADDBDDBEGBDFFCEHEFBEFEAGEGFCGFCAHA,False +150,20.0,17.0,22.0,21.0,18.0,23.0,27.0,26.0,FDDHHBGAEAABAAFAHBGFFHEHCEBEBBEDBGDCGHCGHCFFEGFEDFCDACDAEBFEDAEDHHHFGHGDHGAEFCFGBEDAADCCGFGGAAGCHCDDBDCGGFGGFGGFHGFBGBCGECHFHHACHABDFHDHCAEBBEBGCCFHEHGFHFEHFEHBCACCACGAGHDDDD,False +151,25.0,32.0,23.0,18.0,29.0,30.0,21.0,16.0,CHFAFBDBCEHGEHEEFEACEFCFHHFCAGAEGBCABCAECHDDFDFFEFFGHABFFEHBBDBGABGACGACEDCGDEBDEBCEBFDCHBADBFDAADEFBFHGAACAACHDEADHCBGCAFBFFBFFBEBBGBEEBHDBFDGDAGFEGCABEEBEHBGHBGFBGBAGFGCEGCACFDGAEBEEFCEFAFHBCE,False +152,2.0,5.0,8.0,6.0,3.0,7.0,7.0,3.0,ECBDCEGFFGHCGCGGFBDFDDADDHEBFCBCCBFCGFGAH,True +153,20.0,20.0,31.0,26.0,22.0,23.0,14.0,22.0,GBGFBFFBHCBHCBHGBEFCGFHHHHEHDCHCCDGCFFCDDHFDEDGEGCHHADHCEECFECHECDGCDGADCAGAAHEDHCFBEFEDCHFFAADEADHADCGBCFBCFEEEEBGBCCCCBCDBDHBAHDABCAGCBCFBEHDEBDCFDHFEFDAACAEDADAFGEFABFDCEDAFAB,False +154,14.0,22.0,13.0,6.0,19.0,16.0,15.0,9.0,EEBFEFCBFDAAGAHBCCBGCEEAEEAEEAEEAEGGFHBCHBCBCHBCFACFGDECBAGFFDBHBBHGGFAGBGCBEHGADBFBBGGAFCAFCEGBEGBEFBDFBHEHEFDAFB,False +155,13.0,9.0,8.0,9.0,16.0,11.0,16.0,26.0,HGHDBHECHGCDGAEGFEHDEGGHHFBHFGHBGBEFEAHEAHBFHFDHADHBCHEAHEAHDGHDHHEFFACDCEBFGGEGAEHEGHEGCCGFHGAAAHAFHAHDEBBC,False +156,21.0,23.0,28.0,17.0,32.0,20.0,26.0,33.0,AGBGFFGFGGCEFCBFGBECECGECBECAGHDHEDHCBHEEAEEBFGGHEEHAGFFGFHHCCHADABEGBHGCHGCFBHEHHEHHGFHFFHEFAEHADCEDCHAADBADHEDAFHEDDCCDCFEHBHGGHEFHEBHEBHGBCGCADAAHACBDFBGCBECBCCEHEADEGEEAFCDBHGBCGBCDFAGEAEHAHDCBBCG,False +157,3.0,5.0,10.0,12.0,6.0,7.0,9.0,8.0,CDDCFDCHDGGFGDBGDHFHHEGCCHDCADCAGBFHEGEEGCEDEFDBFDHAHGCBFCBD,False +158,27.0,19.0,22.0,22.0,21.0,22.0,30.0,32.0,AEAADDGDGHBHDGHBGHBHHBCHCAHCABEEBDBDHGFHGHHGBBAHAGFGBAGAGGAGHHCFFBHHGDHAACAGCAHDADGAFHCCHGHHCHGCFGEEDEDBECGAFEDFEDBEGBCACHFCDFGDCDCCBGCFGDFGHFAAEDHFBHFGFFEAEEHEDBECFEABGAFEEEAFDCFDAFDBCGHCGHAEHAG,False +159,6.0,10.0,10.0,5.0,6.0,6.0,5.0,10.0,HCEECDECAFABHBBFADFCGACGABHFEHCBBCBBHFHCDCEDCHGGHEGHFBHABD,False +160,18.0,20.0,20.0,17.0,21.0,19.0,20.0,20.0,FEDBECCGDCDBGDBGDGGDCDFCAHCEHAGAABACFCFFCAACHADAACEGEEGBFBHEHHBGHBACGFDFCHFCHEAEBBEDFFGCFGBEBBEHDDHABGEEEEFABHABHGEHGEHGEHBFDFDHGDHGBEGBECCFCAFHFGCCDAFAHDB,False +161,12.0,21.0,28.0,20.0,19.0,21.0,30.0,23.0,BEBCAAFGAFGBFGEEEFCCHCGHFGHGDDCCHBCGACGEHGHCEHCFCBHCBHDAHDHHDCHEABGHFGBGGCGHCGCEGFDGDDEFGEAHBGEADDCFDGBDGDCFECFCGFCHEGAFCDFCDGDFFEHFBHFCCBECHEBHCBFDBFBBGBDAEDGECGBHEBDABGGGAH,False +162,21.0,14.0,18.0,20.0,18.0,17.0,19.0,20.0,GHBEAFEGBGGHDEEDEABEBBEFECFCCABAAEAAEACBAFBHFHHAEDBCDECDAFBAFBAGEHEHGDAAHGAEDCCDHDDHGAHAFCCECAFCHHCHEGBCDCCBFFEFFGBFDDDDDGGCGDAFDGCGFHHDHHDHGFHGAGG,False +163,7.0,8.0,10.0,9.0,10.0,6.0,9.0,12.0,FBCCDDCAHADHEHHAGCGGHECHECHGBFABFADFGDHBDHDDCDHCEBFHGECEEAEFHECEBGBGGBA,False +164,2.0,1.0,4.0,3.0,2.0,6.0,3.0,7.0,CHCFEGFCGHHEABGAHDFHDFHCFHFD,True +165,27.0,21.0,24.0,26.0,31.0,11.0,22.0,21.0,CAADGACHHEAHDFHCAHCFBCFBEBHGCEFCHCGECDEABEACDDGHDAFCCDCADCAGBDGBEGBCDEHAHHAEFBEGDEFCEABBDBGAHAACAAEACBFBBFGEEHEBDEGDEGDCCDCABHEEEGCDGCDGHEGEEGEHDEGDHDAEFEGBDGADHFDGCDGBAAAAHHEEHDEBABB,False +166,7.0,16.0,7.0,13.0,4.0,10.0,9.0,15.0,BDDEDDGCAHEFHCFHCBHAGFDBDDBDDGFFBAHAHHFGBBDFBDHACHBCEBFEHHGHHBADBCFBHDGABGHBGFBGC,False +167,15.0,15.0,9.0,10.0,9.0,15.0,18.0,14.0,GGABCADCGHHGEHBDHCDHDEGGGFGGAGAABECBCFBEABEBEGAACBBFEAFBHFBHFBGFCAFGHFGHDGCBCEHFFGBFEDFBDAHHAHHGFDDAGDAFA,False +168,21.0,14.0,14.0,15.0,25.0,21.0,7.0,17.0,FDABDAHCHHFDACBGCBGCHFAACGEEBCBFABAEEAEEAFEADDHFAHFEHAHHCEHEFDGFEHFEGFDFHCCAEAAEADBHCFHEBBCFACFDEADFAECAEBBEDBEGFDAFEFDHFDHFEEBCEBGEHD,False +169,11.0,25.0,11.0,15.0,12.0,14.0,16.0,19.0,CDFBBCHGCEBDBACBDCGHFHHFHDFHBEGBEDBFDAFCAHBACFAGGAGEAGBAGBHBBDEBHGHHGHFEABDHFCBECBFDFEGHDFHBFHAEHECHBHBGDBGBCEBABDEGDGGDFDB,False +170,11.0,10.0,15.0,10.0,14.0,10.0,14.0,13.0,EEGCEHAGADCDEADGBDBHDFGDHCDFCDHBAEAHEHCGFCGFCEFDHGHHGHFGCAACHACHAEGEBDCFGCFBBFBBEEBGACGFHEECEBCGA,False +171,15.0,14.0,17.0,21.0,14.0,11.0,20.0,12.0,CBGBFHBCEACEAGAACBDBBDCDDCDDAGGAFGFGDHADEDDEFFAFFCBFCBFCFAHDDBGGGEADHHBHBBDEEGEEGCAGCDCCGCEBHHCGGCDBCHHEAHGAEGHEFADGDGEDGDDA,False +172,6.0,4.0,6.0,6.0,3.0,10.0,5.0,4.0,GBFGHFGDEDFCDAGDHCDACBECDECAHAFFAFBCBHAFFGFF,False +173,2.0,0.0,4.0,3.0,0.0,0.0,1.0,0.0,DDGDCCACCA,True +174,3.0,6.0,8.0,12.0,9.0,8.0,4.0,7.0,FGBDDHHDCFABFABCBCCHDEHEFAEFEBFEDDHDBCDECFHCFGEGGEDDCDDHE,False +175,4.0,4.0,3.0,0.0,0.0,0.0,2.0,1.0,GACGABHBBAABCC,True +176,4.0,2.0,4.0,1.0,2.0,1.0,1.0,1.0,HCDACAAEABCFBCEG,True +177,22.0,20.0,10.0,18.0,13.0,13.0,19.0,20.0,CBHCGHGEHEEADBHGAEGFEGFBAEBCFAFEGHCBABFADFDDCHBCHDHAGGADBAHFEEFHBBHBGDDDHDGHGFHAFAAEGBBDAADHGBEGBAGBADBAHCHHADHDGGDFGDFDCABCABCABEFHEGA,False +178,22.0,19.0,25.0,28.0,26.0,27.0,22.0,13.0,CCCCCCCDCAGHEHCGDGHCADEADBADHFDGGGBDACFHCFHDGBDGDAGDCDDBBCEBFBAABDCDDEDFEFEECDEBAFBDDBFEHEEAEFGEFGEAGBFFBFFBCFCFDGHEFCAFCAHEEGEEBEAHDGEFBFHDFEDCDHCDACGGBGCAGDAFAAFEAFHDFEGECBBGFAEFAG,False +179,3.0,7.0,11.0,8.0,19.0,13.0,15.0,4.0,BEEBAEFHEBGCBCEBFHFDECDCGHGFEGEEBECGFCGFDGDDGFAFFAEGCEFCEFDECEEGDEGCGGFGEBDHCEGF,True +180,23.0,18.0,16.0,19.0,17.0,9.0,16.0,16.0,DACDHCDECEHCBACDAFDAFABCEDHDGHBCFFABCDDFDDHCAHBAEDABHABDGDFCBECAEAAHGEFABFGBGBHABHCEAEGAEGEHGFHEAAEAHGCEGCHGAEGCBGCDGDEGHHADBAGBEDBDBB,False +181,7.0,4.0,3.0,4.0,1.0,4.0,0.0,2.0,CDDAFABHAECADFHCFABFABDAB,True +182,7.0,17.0,14.0,12.0,11.0,8.0,17.0,16.0,ECEECHEGDCFDCFDCEDBBGBGECGBHGFFGCBHEBHABAGBHFBHDGHBECBEHHGCGCCGCFGHABADDDHGDHEBHBCGGFFACHAEADBHDGHBGDB,False +183,18.0,19.0,14.0,22.0,20.0,25.0,20.0,18.0,FBAHCEHGHHGAEDEDDHDHGFACFDBFGCCBHGHHGBHGECBHFDEFBEBHECHFGDFHDEHAGGEGDBGAADFADAADGADGHFFEGCABDGFDBDECDFAFAEFCEFCADGFDFFBFFBHFCECGEBGEBHEADBBDFBCFDCFAAEGBEABE,False +184,9.0,17.0,14.0,14.0,12.0,19.0,15.0,10.0,DBDDHCBBBBGGFEBFEAFGCFDCADCDFEFGHFDHBDCECCFDCAEBEDHFDCBDGBACACGECFEHDBACBFFBFFGGDEGHHGCHFBHFBEFAEAABGFBGEGGFGH,False +185,5.0,15.0,12.0,28.0,11.0,16.0,11.0,13.0,FBEBDDHEDCEGFGGBGEBDBBHCDGDDHBDHECBDFBDEGHEFHEFEDCDHGDADDABHABDCBDBFDHGDFDCGHCGDCHHGDADDEDDAFDFFHFFECDCBBFFCFFC,False +186,3.0,2.0,0.0,4.0,2.0,3.0,6.0,2.0,EGADGADADBGHFGBDGHFGEF,True +187,7.0,12.0,9.0,16.0,4.0,16.0,12.0,10.0,BDFDFFBBBEBBFCHHCHHFFEGDADDFDFHAFDAFBBGDBGDBDDGCDFFDGDGCBCADGEHGDHCCHACABHAHGCFGFFGEFG,False +188,9.0,14.0,12.0,11.0,9.0,6.0,5.0,4.0,DFBEFDCDCBAFBADEFDEGCEBCGFCECHDBADBADBEEBABGHBACBACBECGACBBCADDHFGHECD,False +189,15.0,22.0,16.0,23.0,11.0,18.0,13.0,25.0,CHGBHDEHBEHDGCDFHFHHCHHGHEDDBGHACHECHBHGDHDCHDEAGEABFAEFACBBDDBDBADACDABFAHDABACBHHDHCAHFFBBDBGAFGFFBBABCGEEFEDCCDCBDBFDBFEFGGFHHFHDCADBDGFCGFH,False +190,23.0,11.0,18.0,25.0,19.0,12.0,19.0,38.0,DEHHAGHADHGCHACEDCAGEGFDADHADHDDGEEEEHFHGCAGEDDFHHEHHDHDGBDADHECEEGAFHDBHGBHGBDAHAEHABHBBFDDCDAHHGHHEHFGHCHDDECBFCADCGDCGHCGHGAHGABFHFHHFHHEHHBBAEDAEDFCCECAAGACCACAF,False +191,5.0,6.0,1.0,7.0,12.0,13.0,5.0,13.0,HEEFEHAEHFFHFGDFEDGEGAFGFHGEHDBHAFHFFEAHEBEBDFADBHHHEHBECFDBFD,True +192,14.0,9.0,19.0,16.0,17.0,13.0,14.0,12.0,FBCCBDDFFDHDDHGEFGEFGFHGFBDFCEEHACCAEEDBFDEDCHFCBAEFCGGAHFADGAHEHHAHBACBCEDEEDCCDCGACGCCGCEGDECAECAFGABGBHGDDEAEHA,False +193,13.0,11.0,10.0,13.0,18.0,18.0,16.0,24.0,BFHBGDBGHEFHEGEEGAAFHDFECFEAHEAHDFHCHHEHFAGEGCCHHEDHEDCCDAGGAGGBDCBDAFHFFAFDAFHGCHGCFGHGHHCHDBHBFFADFEDEBHGGFBADHAEEEHEEBFB,False +194,4.0,3.0,4.0,0.0,0.0,3.0,1.0,3.0,HCHBAHBAGFABCAFCFC,True +195,5.0,5.0,1.0,2.0,4.0,4.0,7.0,2.0,EFBGHBGABGADGABHAGDBECGAFGFFEE,True +196,16.0,12.0,12.0,7.0,4.0,7.0,9.0,12.0,ACGACAHFFCEACGGDEADCAGCFHBFBEFDHDBHAAAAGHBBHCBHGBAGBACBDCBHCBACDECHHAGHFHBGADFA,False +197,11.0,6.0,8.0,7.0,7.0,10.0,12.0,14.0,GHFFHACEECGEGGDBGBBFAGFGCHGHDGAEGCCBHCBHAFHAHDAFGAFADCADHAHHBCDFGEAHEHHFDEF,False +198,21.0,16.0,17.0,15.0,22.0,24.0,21.0,20.0,AEFABCDCDABGHHEHDFBBFCAGGAEFCGGCGABGACGHHGDGBDBBCFACBDFHHEHFCHFCECHFCHGEHGBFFECFBHFGHFEDFDCFCEAEEADDGDEGFEGFABFHBFAEHEDDADAAGAACEACBHEBFEDFAAAGGEGGBHEEHFEHF,False +199,3.0,4.0,1.0,2.0,7.0,5.0,9.0,5.0,HFFFEGEEGAHGBHGAHDADCBGGEEGEGBEGBFFH,True +200,27.0,17.0,26.0,18.0,16.0,17.0,15.0,13.0,BDEBEEBCBBCDFCHCCABDEGCGACGACACFGDDGAACBACEEDBDDCCCHCDFAHBGEBCHGGFCGHHHABHBGAEHCBGCDAEDFEFBEAHEAFFGDFHDHHDFDBFEBAAGAAGAGFCBCCEACEACECFAFAAFAADCFDAFDA,False +201,14.0,18.0,22.0,18.0,23.0,25.0,18.0,25.0,EHGEHCBHCHHAEHDEHDEAEBCEBCEGFAHFAHCEHBFHBHHBHEBCFADGHFGCFBAFBDHCHCEHADGBDFBFFBHBGGEFFFDFEBCDFDHCDHBECDEHECBECEFAGFCGCAGEHGEDEFHFCGCCDACAAFDAHDFFDBGDGAFGCBCDFEGFGGE,False +202,6.0,4.0,6.0,6.0,4.0,7.0,2.0,1.0,BADGAEAACFACGEFBACCEFCEFBDHDDFDBFDCF,True +203,4.0,8.0,7.0,5.0,6.0,6.0,6.0,7.0,EHAECAEHBEHBFHBCDBAEFEGGCFGDGHHACBBCGBDHCDFCDFGBF,False +204,6.0,15.0,10.0,9.0,18.0,10.0,16.0,17.0,EHHEDFBDFGDGEDGHFEEDDBGFADFCBHCBHFEEFAECGHHGBCEDCEHFACGHEGHEGCBGHBCHBEFFEHADBAGBGHCHEEBEAGEBGBHGBHCBG,False +205,6.0,8.0,4.0,6.0,11.0,10.0,4.0,7.0,BDFBFFCHFBADBGFCGCCEEAAHFAHFGFEEFBEAHEBDEBDFHDHEGEEBEHDA,False +206,7.0,11.0,7.0,14.0,12.0,11.0,11.0,15.0,DFFHFBABAHBEHBEHDHGCHFDFAGCGHEBADHGDHCEHCEFCEFGFFGHGCDAADGBBGDBGEBFEDHABHDBCDHHEFDEGDEDE,False +207,14.0,19.0,19.0,16.0,15.0,16.0,25.0,15.0,BHBBDBDDGDAHEGEGGECDCCBCDAEBGEDGHDCHFEHACACCEDCGFGFEGDGGAGGAGGHFBEGCEGCEBCAFGHEBHDAEGAFHHCADFBBFBFFDHFCHFBBGBBCBACGFDAFHBCGFCGEDGADEAHFCHBG,False +208,14.0,24.0,23.0,25.0,20.0,23.0,13.0,19.0,CGFHBECCCACGAFFHDFHDAHCCFBDFBCCBGFDAHDABGABGHBFHCDGDDHBHEBCEDEFFEFFEFFCDDGGECDEFDADDHEACEAHEAEEBFBFGBDBBFCBDCFDGFHBBDBCGCDAHDCCDHCEEFEGGECBBABDCBDEFEHHEHHBHBADFA,False +209,5.0,7.0,7.0,12.0,11.0,5.0,6.0,4.0,BEEGAGCAHCFDCAHCEFCAFGGDDEDCBDBEFBEDDADDHDDBBDBEEEGCEGHEF,False +210,21.0,21.0,29.0,26.0,25.0,22.0,25.0,25.0,HGGGCBGCBGFDHCEGCBADBADBDFHCBHDBEBBEHBEFBCABCACCFCEFHAFHGFGDDGDDHHDEDDHCBEDDEDCBGGFAADADGACHAFDBEBEECDECEFGGHECHEFHEBHEDGCDCABCEFGEGHFGHEECDBHDFDFGCAEAGEAHCHFAHDGHACFACGHHGDHGCAAEFAFBCBECGFCFFCA,False +211,25.0,20.0,15.0,18.0,16.0,31.0,22.0,17.0,GDHFDBEDFEFGAHDFFDBECFDAFDBFGBDAEGAEGFDCFDCEACBAFHGHHFBFFBHHEAFBAFDCFBGAGGACBACFCEACEACHHGDHGCGFHGHAGABGBGDFHHFCACEBHEDDAFDAGCADBEGBFGBFEFFEAFGCFBHFEHGABAABAEGAFDFB,False +212,11.0,12.0,15.0,21.0,14.0,13.0,13.0,22.0,FDHBAHAHFDBFDFCHHEFHDFAGBADBADCHDFFDABDHCDHCGAGFHDDHEEHBHHEHBCBGDGCDCDECDEGEBHEHHGHDFBCFDAGCAGCACCEFCDBGEBGEDEFGHCGHEDHEA,False +213,26.0,25.0,22.0,24.0,22.0,21.0,23.0,28.0,DGGABBFFGEFGHFBHBHFAGAHGECGEBAACCADCHDBGDHCDFEDCCCFBFAHDEGGBGECFEABGHDEADGBGGFDEFAABAAHAAHCAHGFHBFABFAEHHCHHCFBEEDEEFEGDEHDHHDHCBEABAGGAFGDFDCBCHBCHBHEBAAGCADCHFCFDBBDBCDECHACHDBEDHEFGADGHDBE,False +214,17.0,18.0,21.0,25.0,26.0,17.0,17.0,17.0,FEFAEAHHABBGBGGCDGDEEDAEBGFHHCADDHDDEDDEAFECGGAGGEBGBACEEDEEDHDDHGBHEBCBHADFEDEGGCDDBDCFCHFEFAHFHDBHDBHAGCFEFFEBEEBEEDGEACFABBCBFDBFHFECGHCGACDCCDCCECFHAACADC,False +215,3.0,8.0,12.0,3.0,11.0,1.0,8.0,8.0,ECHEGGEHEEBCEHGGHBAADGCHBCBBCHBCHBCEDFEGHEDCGCCECEBCGA,True +216,3.0,7.0,2.0,4.0,7.0,5.0,4.0,9.0,EEBACHABHEFDEHHEBHAFHFCHEDGEBBDFBHGBHGFDG,True +217,24.0,19.0,23.0,32.0,19.0,19.0,18.0,19.0,BDFHFFHEAGCGGEHGAHGADAEDAEGACABCBFDEDDEHDGDDEDDGCDGAFBBEBHFBDEADCDDCHBCEAHDBHCBHCACBGCGFCGFCGDHFABCACCABHEEHDGBFFDFFBHADDDCAAHDAEFEEFBDFADGADHADFGDCGCCBECADAHHCFDCGBEFEEDHBA,False +218,15.0,9.0,15.0,14.0,9.0,15.0,10.0,14.0,EDDHBDCEDAHHCDHCDEFECFDDBDEGDCAFCAGCHCFHBFBDFCABCEGEEHHGFHAFCABHABDAFAHBHHGFCGFHGBAAFDAFAAFEDFAGGCCGC,False +219,24.0,26.0,20.0,28.0,17.0,21.0,17.0,23.0,FBGGAGHAGHGGBGGFFDAFDHDCFBFFHFDHDDHFDHFHCFGDHBEFCEACHFEHCBADHDBADCEBCDDAGDAFDAEDEHCAFDAFDFBBAGBGHBCHAFECHDCEBBEABGFHEBHDGCEFCBACBACBCCBHBFGDADAAHAHBGDBDEBGECEDHDAEBAEBAEHADCDBC,False +220,10.0,6.0,12.0,8.0,3.0,8.0,5.0,9.0,DEDDFFBCFCCAGBFHBACAACAHFAHBEGGAGCDCCDFCDFCAHCACDHEHHABGDBHFH,False +221,18.0,20.0,25.0,20.0,16.0,11.0,30.0,25.0,BFFBEGBGFBGHBEFEDHBDCAAHAGHFGDADCBDBBDECAEBAHGHGABBHHBGCGECEECADDDGHDGBBGBCGHHGCHCCHCFHGGHAAHAHGAHGEHGDHBEGFHFAHGADFEGBDHFDGCDGCFGAGCCGACGHEGDCCCABCECGEHDEDDCCECADCB,False +222,19.0,19.0,21.0,28.0,17.0,28.0,23.0,16.0,FFFFGGBAGBFCDFCBFDGDDEDDFDEFCHDCHACAAFFDGFHCFBCDGEGEECCCBBAHHDEHDECFGGGDDGDDGDDCBACBABHCDCFDCEBEGBCHEFHGBHABAGFGFADHAGFAEFHEBBFBEFCGFHAFGADGAFHBCABDEDDCHFEHFEGAEDCGDFADBAG,False +223,23.0,19.0,28.0,13.0,18.0,28.0,23.0,33.0,GHBCHBGHEHEAHDHGDCFBHGCHGCFGCBGBGCDHEFAGHEGAABBHECFCFGDEHCEHAFCADAGDFGDHACBACHACHCHFBEFCFGCHHHHCHBCBEDBFHBEHBAGEACHACFAGGHGDHFFAFEADEAHFAHCCHEFGEFBFCBHDFGFFGAFDACDECECBEBFHBAGCHGCAFFAFF,False +224,3.0,2.0,2.0,3.0,1.0,3.0,0.0,0.0,DAADFBDFBCACFE,True +225,18.0,28.0,26.0,15.0,16.0,22.0,28.0,24.0,CCBGHAGAEGAFGBHGCHGBBBHBBHCBDDBFDFGECEECAGHEBBGBAGBFGCHCCDGCDHEAGCBBFBBFCBGGAGBDGHGGHGHHFHDCEDAFGHBGABHBEAACGCCHCCHBHHFFFFGCFHCFEDACFGEFCAAGDCDDHDBAABFACDABEGCEGFEHFEFCEDBFHBEHF,False +226,0.0,1.0,4.0,5.0,1.0,5.0,5.0,2.0,DBGCFGDHGFCGDHGEFCFDCFD,True +227,9.0,11.0,5.0,9.0,13.0,8.0,7.0,11.0,DGHBGEBGHACBAFHAFHFHDDHCGEAGEDEEBEAGFDFBDFBHFHCDHCEEAFBABBEEBEBDHADHGEEAC,False +228,3.0,5.0,4.0,5.0,8.0,4.0,5.0,8.0,DCEDEHGEHGFCEFGBDHBDCBDHFFHEAHEACGBGHAEHEB,False +229,5.0,2.0,1.0,1.0,0.0,2.0,0.0,0.0,ABABFACFADA,True +230,17.0,15.0,18.0,10.0,25.0,10.0,12.0,11.0,ECCHCABEAEAABAEBGEBCEBGAAGBBDFHDEHDEHCHHCHCEHEEHCGBAFCDEEFGEGGCFDEFBBADBEEFHEAHECGFCDAAAFBBCCCACBGGBAEDDEGDECCEFAEFAEG,False +231,31.0,18.0,29.0,27.0,23.0,14.0,25.0,29.0,DGBAGHGHDGCGACBADBDDEADFCHGDBFEBHEBHEFHFCDFCDACFGHDDDDDCGCEAEEADCBDBGGHCAACAEDACHEHHAHDDFDEHCEHCECEHHEAFEABCGEGABHEDHEFAGCGGCGACDAGDACAAHACBBCDACAACHCDHGAHGFBDAACEACECFEHGGHBGHBCFFGDBGHBEFEHHAHBAG,False +232,9.0,27.0,30.0,27.0,17.0,16.0,18.0,20.0,HDBHDCCCHHCHECBBCGCEDCHCADGDBBEBGEGGFDFDDGDBBFHCEEDFFFHFHHDGCEBCABABDEHDHCDHFDHFDHBDHGGEECBEHBDFDDBCDCCBCCGCAHDBBBBFBEHBEGBEDDGAAHCBECBCCBCFFEDFEDCCGBAGACGDCAFCGFGG,False +233,13.0,14.0,9.0,12.0,10.0,11.0,7.0,12.0,CACBADGHDGHDFHDFHDEEDGEBBEDHACHABBFCFAEHACFDCEAHEABFFBFEAAEBCHDGBDBBGCBFEAFGDCDHHABHABGF,False +234,27.0,12.0,19.0,20.0,14.0,11.0,16.0,19.0,DCEACEBHDGHAGFBGABGABGABCHFEADDADAHDHDGBFAECCBCHHFADFEFAHDAEDCHCHADBFDCGDCHECGAAAAGBAEEHGCCGEAGEFCDFDGGCGACHCEHCEHDEHBCADAADADDFHGAHBAHBAF,False +235,10.0,14.0,16.0,10.0,22.0,13.0,14.0,12.0,BCEFFEFBBGBBGEDGEABFACCDCCDHEGHCBDGHEEEFAGBHGBEEHEEHDEFDEFCECDECHGGAGFFEDGHBECBHCGFEAAEAHGBHGBHEBAFACCEDCACFDCF,False +236,7.0,11.0,9.0,8.0,13.0,11.0,4.0,12.0,AEBEHFHFFGFHBFHFAHBHHBHFEFABBEBAEFCEACHHDGDEGABCCBCEBDEDCEACFHCFDCHDEEDBGDE,False +237,23.0,30.0,14.0,18.0,17.0,26.0,17.0,30.0,DGDDFCEFCGCBBHACAFCEEEEAADADEHFABBADHADHFDBFHHFHDFDAFEADBADCAFAFBEBBEBBCBBCFBEFBGFBHBBFFHFAHABHEFHBFHEGHAAHBAGBGFHAFABEGEGGDCGBHBCHGHFGHGHHCDEFFHCBHBBHGEHGDHFDHCDBDAHGHBEAACFG,False +238,19.0,27.0,27.0,14.0,19.0,23.0,28.0,21.0,CCCACCFBHFGEBABBGFFGBCHBFAAFBAHCAHCBGABGADDABDAFDBCGECFEHBCHGHHGHEGDEBFBBCGBGHBGFBCCBDGDCHACHADFADEHDEHEGADGAFBFGBEGHFHEADFCCGCCGFCEFGHFEFBCDBGHHECGBCFAEBBCDGAGCAGFFEHGEGFEGBECHE,False +239,12.0,6.0,10.0,11.0,16.0,6.0,12.0,10.0,DBDGGDGCDECGHCHEAHGDEFEEFEBBHABCCDACGFEGHECAFAEDAHAGCBGAHGAGFABFDEEDGEHEECEDCEAHDAH,False +240,12.0,11.0,10.0,12.0,15.0,7.0,12.0,8.0,EHCEBGEBCADCDFCEGBEBCEBHDGAAGDGHDCFDEEGBEFEEFGEHGHBEABEAFCFHCGHCBADAADADGAEBBDDHDFGACGA,False +241,24.0,20.0,23.0,18.0,18.0,16.0,33.0,12.0,DCADHACHFFHADCCDEEDCEDCFAAFGBCGACGAGGACHBBDBCCBEFBGCDGHFECABCACGAEFAECBFFFHGCAECAGHEHBFHBAGEFGECGHBABCADDGGDGGDGGCGCFFHGGEAGEGEEBBEGAGFFGDGGBGDBGDCGHAAABGEBEBDDBDAA,False +242,2.0,5.0,2.0,2.0,7.0,2.0,2.0,4.0,EHCHBDECDEGFEAHHABBEBFEBGE,True +243,5.0,8.0,9.0,5.0,11.0,13.0,13.0,9.0,ECEEGBGFFHFBEFHFDBGDBGFHFFHGHCGHEACEABBFEEEEGCGGCFBCDCCEHCDHGAFGABGHFGAFD,False +244,8.0,13.0,8.0,11.0,10.0,14.0,17.0,10.0,EGDHGCEDHEAHFBCGBAABGEDAEDAEGGDDFDCFGCEGCGFADFCFEBBCBFDGFAGFEDFBGFGHBBHEDHGGHBAFBFHCFHGBHGB,False +245,10.0,16.0,19.0,10.0,13.0,11.0,21.0,15.0,BEEBGHAGHCCFEDFGFHBHHDFDDHCFAGFAHABFABGAFAACBECGGGHGCAGCHCEFGEHBEHBGFGEFCHDHHDEBCABDGBGGCGGCBGEBGDCCCCDCBDEBGEBECCH,False +246,9.0,13.0,8.0,9.0,4.0,11.0,15.0,3.0,BDDBDDBAGAEGABGEDFCBCCFCDABHCBGDGGEGCEFAGBAFBGGBGGBDFFAFBCGDHGHFFCFAGFAB,False +247,24.0,29.0,19.0,27.0,21.0,19.0,25.0,36.0,AGGDCEDBEDGADBCBEDBHDFHDBEFHEFEEGEGDEABEFHDBHBHHFFAFBGGHCFFEAFDABEAFCHDCABBBCBEEBFBGAGHBGHCABCAFHDGHCHHCDGADHADGFHGFCGDBHBCHBDAEGHHGHHAHCAHDDBGHBGCEAHGADDHDECGEHHEDEGFEDABHABHABCABDABDACHGCBGDHHFHFFGC,False +248,23.0,15.0,19.0,20.0,20.0,17.0,12.0,20.0,AEDAEDAEFADFAHFAHEEHBBCBBDBCAFAAGCCGACEHEADFHDFCDAHGBEFFEFDAFGACGECEHHGADGBCAFCGCHDDDGCFFDBCHECFEHEABEABDCBHFDHECAFDABDAGEBGHGEHDBADBADCHCHHCFHEEH,False +249,5.0,8.0,8.0,6.0,8.0,12.0,5.0,4.0,DDADDFEDFHACECHGGHCDBBFFBEEBGEBCECCGBEAAGAEBFCFFHFFBFFCF,False +250,9.0,9.0,5.0,9.0,9.0,5.0,9.0,6.0,EBGEGDECAEBBGBFDBACGCBBCBBFDADDACDGEDGHDHDAHEFHFGAEGHFGAAEHAE,False +251,3.0,4.0,6.0,7.0,2.0,6.0,5.0,5.0,FCHFEBDGHDHADFGGFGFFEDBCCBCCHGCHDBDDAA,False +252,23.0,16.0,22.0,22.0,17.0,24.0,15.0,22.0,GDGADAHGFBBFBCHBDHBDCCDHEGADCHBBDFHCGGCEFBECHECEACFDBADEACEDFFDFFDFCEFCGFCHFGAFADGAFHAEABFDEDHHBAAAAHGABGDBFEHFHHFCHDCEAEEAEDCFFAFHCHHADHACHAEDABDCCGGCGFCBFGEHBD,False +253,28.0,21.0,24.0,17.0,16.0,23.0,19.0,22.0,HBGAFCHGAFDHGAHGHGDDGADGECAACFACBDGFCBAHBHDBFDEFABFACAEGFHGBDGBFHDFHCGBAGCABEGHEFHECCEAEHADHFDCCDCCEAFBDDBFHHFGHFCHCDHCFFCBAEFAEFEEAAEBFCBAABAAHEABBAFBGCBGCBDFGAGCCDECAHH,False +254,22.0,21.0,35.0,22.0,18.0,16.0,18.0,17.0,CGFCBBCBBCFBDHEGBFDEHCCAECAHAFDEEDAEHAEBCHFHBFHCHBGEACCCCDCABFABCDBDHCGCCGDCDDADDGGEHFEGCCBCBAFDEFDAADFAGGHECHECHECHAHGCFBBBBAGGEDBFDAFDCEDCEDCADCBHEFCAGCAGCBGFDACAACGGH,False +255,16.0,23.0,16.0,16.0,20.0,17.0,25.0,22.0,FBDCDGFHBEHADAEBABHAGDEEDGEAABDDEEFEEDBCGGDHHDHGDABBCBBCDHCDBGDBGCHGHAGFECEEBEHFGDFACHGHHGBHCEHCECABHADHACFBBAEFCEHAGHGEHGFHGFGGFGBFBFCBGCFGEFGEHBBGFCAFGAB,False +256,4.0,5.0,1.0,1.0,3.0,4.0,5.0,7.0,BHFAGFAFHABDAEHHGHHGEGBEGBCBHF,True +257,15.0,16.0,15.0,21.0,14.0,16.0,23.0,29.0,BBAHCCDBGFHGFGFFCFGCGHCGHDGAGHDCHDEABEBGGFDDFHDHHGHBAHDGCAGBGEBHBCHGEFGEHGEBFECHEDGEHBAHBEHDACDHHHBCHBCHAFHDCHAHGAGGDDBDDEACBAEEAHDDFFHGFHFFDAEDACDFG,False +258,25.0,18.0,28.0,20.0,16.0,20.0,26.0,30.0,GBDGBHAEEAHBAHBCHCCHCEBCECDEAAFHHCGGCFFDFBAGBHGFHDAHBACCADCAECAFFAFFGGEGCEACECCFCBEAAGFCFFGGHCDECBGHBHACAAFDGHDCHDCFDHFEHFDGDGHDCHAEADGGEADCHDHBGBDGAGGFFHHFHAGHCHHCDBGHBEHDEHGABBADBCG,False +259,10.0,4.0,2.0,8.0,6.0,7.0,4.0,6.0,BFAHHADDBDEBDAHFACEADEFDEHDGAGFDGFAEFBGFEAACHAH,False +260,17.0,18.0,20.0,22.0,23.0,26.0,23.0,18.0,CGCHEEDEBDHDGEGFEFFCAHGBHBEHBACAAFAFFDBFDCFAEFADFAEGBBHADAGGHFGCCGCGFBDFEEEEADHGDCEDFGDEBDHBGHBFFCAFCECGEDADDBHGBECFEBFEDFDDEGDHCAHCFFGFFGAHCDHADCBECBHHBHCGFGGABGCEGFE,False +261,27.0,24.0,20.0,19.0,30.0,32.0,21.0,26.0,GEHGECEEBEDACCACGBFGFCDBHEFEEFGEFBFACFACFAFFAGDACBAGDEBABFAEDAGHAHBAECAFDFEEBBBFEBDEFCHFHBFHFEHDGHBGHCCFDDAADEAEECGGHGFECFEDFEAFACHACEFBEFHHBHHFEAFHBFBBFBHFCAGHHFHHGHDCHDCHFGAGDDGCAGDEEAGEBEDAGHADBBB,False +262,24.0,26.0,23.0,23.0,21.0,23.0,28.0,24.0,CFDHHBBHEEHEHHEFHBDAADAFDBCDHDDFGAFCACEADGBEGCGCHEAHGADGABGADCFFBFEDDAFDCFHBBCFBGDGCHECBEBBCABDAECAHAHHAHEBHDHHFAHGEBEHFAAGBAGBGGCAFAFBAFBDCDCCDGGDGBHBBCBGFGEEGECGEHECDFCBFGBDGCACEFGEGGFHGFDGF,False +263,0.0,1.0,9.0,1.0,3.0,4.0,6.0,1.0,CHCCEFCGGBGFDGEGCECCFCFGC,True +264,6.0,5.0,5.0,2.0,0.0,4.0,6.0,0.0,CCAGBBGDBGDBACACGAGGFFFAFBAC,True +265,4.0,10.0,10.0,7.0,1.0,8.0,4.0,4.0,BEFBDFGDFABCABCHFCDGBHBCAFCAFDBDBGGBDFCCBCFHCDHC,True +266,22.0,29.0,31.0,16.0,20.0,28.0,16.0,14.0,EHAHCBHCBECFGBBCHEEBAFBHHAFGBFDBFCBFCBFCBFCGFGECBBGFCEFBEFDEDDGFCFCAGCAFCEGAAGAACDCFGAFGAFHBGABDAGAHCAECABBBCFBCDEAAEBFBBFCCFCCFABFDDFBEHBFGEDBEDEHAECBGCFHCDECACCDEFDADEHCGDBHH,False +267,19.0,18.0,7.0,10.0,13.0,13.0,13.0,11.0,HAHCGEBDCBCBBEGHFGBCGAAGBGGFDGCAEADBAHBFEFFEAGEHCHHBAHAADEFGEAGFFEFAEFCBAABAABEAFGAEGDEDBBABBFBHHDDHDBFD,False +268,17.0,10.0,10.0,7.0,8.0,5.0,14.0,9.0,DCADHDGHAGBAEHECHCGADHCGAEGBEGAEGAEGACAHGHDCBGHBGFBCAAAACBBEEBGBCFCAFDAFDHFGABGA,False +269,1.0,3.0,0.0,1.0,3.0,4.0,3.0,1.0,GHGGEBEFBFABFEDF,True +270,23.0,19.0,18.0,18.0,15.0,13.0,11.0,15.0,AHDAFCAECAFBHBCEFDEFCEFEDAADBADCDDFDAFGEHGEAGHADBBEACFGBDHADGCCABHHGHFBEDGHFEACEFCBAGAAEABEABGABHBEABGABFCBACGDDHFCHBCHBHHCEDCDDCDBC,False +271,7.0,9.0,4.0,6.0,4.0,10.0,14.0,6.0,GDDGADGAHAAHABDGFFFECFBHBEGEGHEGDCABGGFFHFFHFBGABGDBGCBGFGCB,False +272,9.0,5.0,1.0,2.0,6.0,2.0,1.0,1.0,EDAEAFECFGHAABAEDEBBEBAABAA,True +273,6.0,7.0,5.0,6.0,3.0,4.0,5.0,6.0,DBGDAGHAGECGFBHFBGDDFEDFHCBBEHHCAHBACBACAD,False +274,13.0,30.0,20.0,14.0,22.0,14.0,15.0,16.0,HBGBBDCBAHEFEBDBCABCGFGEHGECGCDECDBFDECGHBFHACDCBBHEHGGHFGBBBBHBBHBBGBEABHDBGDEGEFDECCFHEBHEHGEFCFBCFCDABAAHEECEECEDCEDGEBFEBAABGABCBCAAFDAFDHFC,False +275,5.0,8.0,10.0,12.0,2.0,10.0,10.0,5.0,HGDDCDFCDBGFCGDBGEAFACFDBDDBHDBCDCCFGCHGDFGCFDABHGBAGCGFABFEHF,True +276,5.0,1.0,0.0,3.0,1.0,2.0,0.0,3.0,BDDHFAHAAHAFEAD,True +277,24.0,23.0,18.0,24.0,16.0,33.0,19.0,28.0,ADCABCHCAHCAHEADEAHBGBCGFGFFGAFBDFGFBGDEGDGHHGHHACDDGFFAFFBFFEFADHDDADDFFAFGBFBBFHFCHBDADEAHECEDFDGFDFFDCBBHDAHBBHCEGEBHHBFFCCHHHHCHBBHDHAGCAGEDEHDGHDAFAFBBFABFAEAAGABGFEHCCBCHECFEDFGFE,False +278,12.0,29.0,23.0,26.0,19.0,18.0,23.0,13.0,BEBBEHBCAFAHEDDCDBBDBBDAFFAFCADCGGBGGCGHCFECEBDECGEHGEADBFDHFDGCDGCBCCHDBEABDCBDEBEEBDCGECBDHBEHEAGAFGHFHEFBBDBGEBFHGGHFGFDGCDGDDCFFFDFECCGCGGFBDBAACHEDBDDBGCAGBBC,False +279,16.0,11.0,17.0,16.0,19.0,22.0,19.0,14.0,GFAAFDCCEGCHGBEGDABFBDFEFEEBEBGFCGHHHFHAFDADEAHACBFCDFHFGCDACDFCGFEDFEGADGAFCEHCAHBBHEGCDDHDCAFCAFGEEGEEFBEFEHAHFDEFDBGDBGAFCAGCGGCGHE,False +280,10.0,14.0,13.0,11.0,22.0,14.0,17.0,12.0,EHCECEHBFGCGGCAHCDGCGGEDBBBFHCFBFBBFGHGHFABEAEGACGACBFDBCEECDEBFEBDGHDEBEGGECGEHGEDEEHFEHFEGFAADGADEHDAFDHFEEFCBA,False +281,32.0,31.0,18.0,18.0,36.0,28.0,25.0,12.0,GAHFABEGCGAEFADGADFABCADAEBAEFEHFGBGCBHDAHAABBBECFEAEEFEEFEDAEBAECADCDDBBBCBBEDBFAAFHEEGFCGEEGEFGEFAFDABCABDAFGFBGFEGBEACGGHFGAFHBBDEEEGGBHGFFAFFGEFGEBGDCHCHGBBGABEABEFEDADCEEFDCDHCDBGABAACAHCEFCEFBEB,False +282,19.0,24.0,17.0,28.0,20.0,14.0,18.0,11.0,CEGDBCDFGFGCADCEEGFABEDBDBBDEFDEADBGBEGBACDDFDHFBHGGCGAEGHEGHECDDGDFGEFABAEEHDFBDFBEEBHCDCCEHHDCGDBHDFDDADDEEDBBBBABHAHDABAAGADBCFBCBECDAGECGACGACFABFA,False +283,26.0,21.0,30.0,21.0,22.0,23.0,22.0,14.0,ABEAFHABHEFEEFBHDAHFBHFBAFBCBGGHGDHFDHFBEBBACCAECAECACGBCFFEFCEGGACBCDFAAHABGDEGDEGDACFEGDEGAFAACCBEABGAFDCFDFFGACHCEGCFGABCHGAHCDHCDCCDCGABDFBDEDCGFFBFEACCDCHDGGCGEEAEBAGDCDDCEEB,False +284,14.0,18.0,15.0,12.0,15.0,14.0,12.0,12.0,DHBFHFFADGAHCABFABEEFDEAGEAGDDBACBCCBGCBEEBEAHEHCFFCEFCBCGDCGDEGHGGABADBEEBEHCHHDBEGGFFEFDADHAHBBDFBCCBGABCFHCFA,False +285,16.0,15.0,17.0,12.0,11.0,20.0,18.0,11.0,HGHCBHCECFEHFEGDAFFGFEGFEAFGFBGABDBBGBACBGFBECAAFDAHHFGGAGGAEGCBDBBDHEFGGDGEHAHADEADEFCCFCFADDBCCBCABHAFFCFGCFDCFACDBCGH,False +286,11.0,13.0,7.0,7.0,10.0,17.0,12.0,13.0,FDGFDGFHABDDHFAHBHFFGCFHBGAGFFGFHHAGHEGHCGBCECDECDBHBEHBEHCAFGABAFBGFBEFGEABFBFDEFAEAHEABC,False +287,8.0,6.0,3.0,14.0,2.0,6.0,4.0,6.0,BGDFDCCDGAFBADBDHHDHCDHAAFAADBADBFDEFABDGHEGDDFHD,True +288,13.0,9.0,15.0,13.0,19.0,11.0,16.0,13.0,GGEDADGABGCBHAGACCFCHECDDCBAFEEHEBBEABEACFACEDHEAFEGFGDAEAAECDEFEHHEHBFFDCFDCDAGDHEBHCGHGGHCEFCGFEGEDGDCGHBGH,False +289,21.0,24.0,27.0,24.0,13.0,22.0,21.0,28.0,EBFBBCGBDHCAHFAHBBHBDHBDHADECDCAHCGHGFHADHDCHFBBAHBDHECABFBFFCDFGDFECBECBCHEAHFHHEHGGFAGBDCEHCFHCGGBEGFHBFGAFCADDFDDBDFCAFCHFDDACGACGDCGAGGHDEDECDAGHBFABABBEFBCCDEAHGAHGCCGCFAHDGHC,False +290,11.0,5.0,20.0,12.0,8.0,15.0,4.0,7.0,CBCCHDDHADEADEFDAACCCFFDFCAFCADCGDFEDCECCECFFHFFAGFCEDEBFFHCHGCDBHGCFDAFBAEHACCACB,True +291,20.0,16.0,14.0,23.0,25.0,13.0,17.0,18.0,GBEGBEGFEGFBFDBFDBADHAFBDFGDEGDGGECCECAEAADAACHHHHBHEGDADDBHAAAEHEBDEBGEAEHDGHAAHFABCEGDFGFCECDGDABDHBDECCABFBEEDEGFEHFEHGAHBDCDAEHAECDCFDCEDHGHEC,False +292,22.0,21.0,19.0,22.0,30.0,26.0,23.0,31.0,AHGAHGABADGFGGEEAEFDCABCFBCGBCBHCBCFEDFEDHADEFDFBHCBHAHEAHEHHEHEBGEAGEDCEHGACGDCFCEFDEBDEBDFHACEEHBDDGGEBCEBCGHFGEABFAEEBHABGAHGAHDHHDHEABEGBFAEGHEHCADFFDFGAFCDDGFHFFGFFDEBCHFEGFCDFHHCHFBEGHHADH,False +293,16.0,24.0,24.0,18.0,24.0,17.0,14.0,18.0,BDDACEACHABHABHECHGHEGEEFCHFAFAGFBBBGBEECEEHEFDBDDBDDGCGBCEHCEDCBFABFBBCCECCGBEBAABHECEGCEDDECFECFHCFHCGBCFFDDFADFAHHCGBBBCAFEBHGDGADGAHCBEAAFGDBHHEDCEDFEH,False +294,32.0,23.0,12.0,12.0,9.0,21.0,14.0,23.0,BCGBDHDCGGGDAFDFFBCABCABCFGGFAAFBHEBHGBGGDAFAACABHBFFDAFAHHBHHDHGDEADBHGBHBBHBBFACCBECAAAHABHAEAEDFGCCEAFFHEBHFHHEHDABAAGAGHADAAHAACEAHAAFFBFFBFFH,True +295,25.0,28.0,34.0,29.0,21.0,15.0,21.0,21.0,GBBDDFEAEADECDAGBCFBADECDBBDCCGCAGCDBCBBCBDCBGCEHCGACACFBHFDDBCHFCGAGGECFFABDEGDEFDHFHHBBHDAEDBEDCDDCDDCDAADFACEDHHGACGBBGAGAEGFGGHCACCDHGEHGEHGHCEACBHFEAAEACEACHHCHBCBECHHFEBBDCBFCBDDBDABAEFAHG,False +296,10.0,5.0,3.0,10.0,3.0,6.0,4.0,2.0,FCDBCACHBFABDAGEAGDADEBDFDAFGABAADEADHGDFFD,True +297,18.0,24.0,24.0,26.0,29.0,26.0,24.0,26.0,HAEHBEAEEHCACDDCFDHFGCBHCBCDHFDEADBBGCBGABFAFGGHGEAGDBCCGCBDFDDFBEFBEGDEGAADHADHBHADHCDFEFFEGGEBAHBCFGCEGEBGBFGEAAEDHFDAAGHFGEEGEEDHECGEDFEBBDCCDBDECFCBBEFHFCGFEHHEHHAGHCEHCDFCDFCDHCHGGHFEFFBFHBADB,False +298,13.0,9.0,11.0,21.0,12.0,21.0,9.0,8.0,DDADBAGGAGEAGECGEFHFCCFBCABCABHAEFABFDFCHHDDEDDHADHCHABFFFEAEDCFDEGGFDDFCDFEFFEDFEBADFDDFBDFCHBGFCEDDAFG,False +299,9.0,10.0,7.0,5.0,4.0,5.0,9.0,5.0,AEBFBGFGGAGGADCADGDHGHEBHBBGEBGFCHBCHAAFAABCECCFDDBCAB,False +300,9.0,10.0,14.0,12.0,10.0,5.0,22.0,10.0,GBDGFGGEGEHGDGGEGCCGACBDBBDABDAEFABBCEAEHAGCFHDGHGGDGADGHGGBFCDHCDGCGBDAACEHCEGCEGDHCHECHCBF,False +301,23.0,15.0,14.0,8.0,21.0,17.0,19.0,20.0,FGCEGAEGEDHEDBGGECFFHEBBBFDAHHEBAEBHCHEGAAHABEEFEEFGBHGCHCAHDAFGGHGDHGFAGBABFAFHEEGEAAEDAGFAEFACFACBHFDCEHBAHCAHGAHCCGCCGEAGEACFADFHBBHBF,False +302,27.0,23.0,30.0,20.0,17.0,18.0,24.0,20.0,AACCCBGDBFHBAECFFHBHHGHAACGCHDDBFBGGCHGAFGAGGAGGAHGCHGCDGCHBHABFDBDDEEDEEDBCFCCFCHBHFBAFBDFHFBAAAFCCGHCDBADAFCABEACGBFBEEBAEHAEGAHGACBBDACDFCDGCDGHDEEDEBCFFCAACHECGCBGCEGCDAAEEHGD,False +303,30.0,27.0,22.0,22.0,20.0,20.0,25.0,21.0,FCHFDBBDBGCAADEBGFBGABGFEGHAHBADAEDACBECFFCFFGDBGAHHAEHFCAFAACEDCFFBEFAEABHDGAEHDDBGCBGEBGEAEEFBEBDHDAAACCHCCHGDAGDFCFABFHBFHBGBBDHBDHEEHECHDCADAEDGBCCBAGEHGEBGFBGCCACCAGAADAHGHHGFDABGGGD,False +304,29.0,17.0,17.0,22.0,14.0,23.0,28.0,17.0,DABGFCFHAEGAFGFBCCBEDDHFCADEHDEHGHDGADGHGGCCFFFFCCEGHEGBDDDDDFDFGDFGCEABADBCHADBGDCDAHFFBGFGGHAGHAGAEGEGCAAHAAGAAEBAGBGFBHBBHBGDCGFCDFBAEBHCFEAAEAAHGAHGAGFACFDCFEAFDAB,False +305,11.0,12.0,13.0,10.0,10.0,17.0,17.0,13.0,BFDDADEGGFGEFBEAGHAGBACAECAFFBBFHBCHGFHGHGFFGCFCBBAGCDGDDGCGHCBHDGGFHFFHGDECDFCDEAGFAFBAECAECHBHHEHCEBF,False +306,7.0,10.0,4.0,3.0,5.0,2.0,7.0,5.0,BHBHADABBABGABHDGHDBCEFEEFCEBCEHGGCGBAABGAG,True +307,17.0,17.0,13.0,19.0,19.0,19.0,22.0,12.0,FDEAAHFFBFBGFBDFGDFGDBGDBGFBFFHFFABEGGGHAAHEAFEDFCBFCEDCDAGBAFBGHDHCGHGDEGDGCBBDHGABCDHCFHEGGDBCHECEECEADEAEGAGBAEEDDEGCEGCHACBAFBDEDAFGAE,False +308,16.0,19.0,32.0,19.0,25.0,21.0,28.0,24.0,BCGCCBFCFGGDHGDADAACACGGBADDGDDGFBCHHCFECDGGAEBAEGHCDBCHEEHAEHFEFFEGFEHDCCCEGHFHHGBGDEGFHCFBFHBGEGFCGFCBHGBHEBEEBGBAGEEGHEAHEBFEBHCBGGDGDCHCCACCADBAHEDFGCACCHHCHHFBAFAEEDCECCDFCDFCDFEG,False +309,12.0,7.0,7.0,14.0,8.0,9.0,9.0,23.0,HFHHBHGACFAHHHHHDHBGHCEHEHCFHCBHDAHDAHFGDDHEBGFDDHADHBDGEEGDACDAHDAHCGHAADAECBEGEFFAFBDFG,False +310,7.0,9.0,2.0,2.0,5.0,3.0,5.0,9.0,BBABAGEAHBGHFEHBEHBHHAHBEGBGGBDACFCHFDHAAE,True +311,26.0,28.0,24.0,21.0,11.0,21.0,26.0,17.0,BFBEHBHGFHFHDDGADGADGFDCFBCHGFAEAAEAAEAABDDGHDBEDCCGFCFFCBBGGBFHCGGGDBGDBDEBCFBCABGDBGDFGEGCCAAHBGHGGFFBAHBAEGCFBCECHFADGGCECCFCBACBGBBGCCDAEHABFADDADDAFBHFCHAAFAABHHCHBCDBGA,False +312,23.0,13.0,12.0,13.0,21.0,13.0,8.0,13.0,FBAFBAECDHHEEEEAACADHEDAEAEFAEFAEGAEGAEAAEAGGBCDDFHAHHFFHFCCACAEFAHFAECHEAEDDHDGBBCBDFEHEAHBAHBAGCCDDDFGEGEFBBDBBCCB,False +313,3.0,1.0,2.0,0.0,2.0,1.0,1.0,1.0,HACAACEFGEB,True +314,19.0,17.0,14.0,10.0,16.0,21.0,10.0,13.0,AHDAHEEFAEAGCADFEHCEBCGCCGADDADFADFAHAAHFEHFEHFEFFCBFEBAAHEHBEBCCGHEBHCBFCFFGEAHEACBABBABFFGFFGBBBFBGDGCCBEDADAFBFFCHEDG,False +315,3.0,8.0,4.0,7.0,12.0,10.0,4.0,14.0,DHEDBEDBECHEFFFCHDAEBAHHFHFEGFECEEDEGHBGFBAHBHEBEDCFHHFHFDHGBH,True +316,19.0,13.0,26.0,20.0,13.0,13.0,16.0,14.0,AFCBGBFCAFCEECHBBAGCDGCFGHEBHEDCCAHCFEAEDDEDAGCAFCACCADCGDEBFAGDHGDCBACHAGHBFHCGECDCAGCADADFGDCGDGEDFADCADFFDAEDHCCHCBHGBHEBFGBCABHHDE,False +317,16.0,18.0,21.0,25.0,22.0,16.0,21.0,17.0,GDDGDDEDFEGFEDEEDHBDHBCHDHBBBBBBCCBCCHFCHBCHEHADGCDGCBGAFABCEDFFAEBCHBDDEADCGDEFAEGAGCCDCCGFDFBDHCGHGAAFEADAAHEBHEAHFCCDCEAHEAFGBGEBGDGEFGFHGEHFAFDGEDGECEDG,False +318,23.0,22.0,20.0,24.0,12.0,20.0,16.0,25.0,AABCHBFHCDHCGFGHDHHFGAGHBGHBGCEECAEHGBCGDDDHCFHGBHGBHEBHDCCAHCAHAHCAFCDFHHEBDDBGDGEABBAEBCDDFDDFEDFACFABFCHHCHHGBFAEFBCGBDHFDBFDFDAADAFDCEHCBBDFAAAAGECDABDAEFABFG,False +319,9.0,5.0,11.0,3.0,6.0,3.0,10.0,12.0,HABHDEGCCCDFCBHCHHGHAGHCGHCDHCEGCGCEGHEAHFABAECGBBAAFGAEHAG,True +320,31.0,18.0,28.0,29.0,18.0,25.0,23.0,22.0,ADEFDADBAGBEGHEGDCAHAAHCFGCHGFEGFHGCGBFDAFDCFCEBABHDBAFAFFDGDAAHABGGCAFCACCDEBDCCGCCDCCAFGGCHBDHGCHAHBBBBBCCGAADCBDEFDHCAHCHHFHAECDCHDGHDEADEDFADBADEEDGCBGCBGDGEFHAFEAFAAFGEEDCFDHFAHFAFFAEFHEDGD,False +321,11.0,11.0,8.0,16.0,26.0,18.0,18.0,26.0,HFGEAHHHHDBHGEHDFAGGDEFDEFDEFAEFBDFHDEEDEEBGEHEHHEHACGGEBHEGHEFHEHAEGFDGDDGBCEAEGAECDHCGHFEHGAGFCHHEHHFGDFEFFHBFABHDGFFBCEBAECGDABDHBC,False +322,6.0,3.0,4.0,2.0,1.0,1.0,3.0,2.0,CAAFAEHAGBDHCDBCGBAGCA,True +323,10.0,11.0,20.0,18.0,16.0,14.0,16.0,14.0,FCGBEHDGCCHABGBCGACFEFEEFEDCCCBGCFHCDAGDAGDEDFHGBAGEDFECGACGEFGEFEHCDHCDEFHGBHGEFDEFDEADBAEHFCBGCHDCHDCBDCFHBDABGAHDHCD,False +324,14.0,16.0,12.0,17.0,15.0,23.0,16.0,14.0,HDEBDGFAFHDDHDHECHEBHGHEGEGFADHGEFGDFBCEBGAFFAGFHBDHGDCGDCACFECFEHFAFBCEHCFBEFCEADHABCBBCFBAFAGFAEEAGBBECBDGBFGHGBFDDFDDFGAFDAF,False +325,15.0,13.0,7.0,9.0,15.0,10.0,11.0,11.0,BDABDCBEEECAECHCFHBBHDHEAHEAGEDEABEDHEGGFGGFEFBEHEEFBHAAAAAADAADFAEFGHHDFHGAGBBBBCDCGBFGFCG,False +326,18.0,22.0,21.0,20.0,18.0,16.0,22.0,11.0,FAHEBHABFAHGAEGHHBBBCBGCBECAAGDACFBCFEHGDHDDCDDFFCEGHEBHCFCDFCDGCHBAGCEBCBDGBDCBDHGEFADGEFABFGCFCDBCGACGABFACDEDEBDAFAFFABGEBGEGEEDEGDAGAGGEBGCBDCED,False +327,13.0,17.0,20.0,5.0,21.0,19.0,14.0,10.0,CACCAECGEGAFABCCDFAFFHFCEFCHAHBGEECEECGEFDECDECEEABFBEAEEBEDHCAHAADBABFGFFGFGGFBGBHEBHGFGEFBBGCBCCBCBECBCGFEHFHBGHACEFF,False +328,21.0,20.0,17.0,13.0,23.0,15.0,20.0,19.0,HECGCCHADAADGADBEGBEABEHFGFGGFGCBECFHBAAEAHDFHFFBGEBGCBFHAABAABDCBDCAFAAHCGDCGEEGHGDEGCHGHBFHDHCDBCFEAGCAHCEHEEFEFBDHHDEBEEDEBGGAHGAHBEFBECEFABGABEC,False +329,24.0,23.0,29.0,30.0,30.0,21.0,23.0,19.0,HADHFBHFEHCEHDHCDFCBABEEBDEHDACBGDBCDBGDBADCCDABAGCEGBDGBEGCDFAFFGEFGAGEAGEADCGHGBDEDAADEHBAHCAEGBGFBFHBGEBDBBAEEDEEFAEDGCABCEDGFFGECCDACHBDGBDFCHECHECEACEADDDEDFADFAFHCFGCADCEECFCCFCCAEBGGHHCHFDHFEG,False +330,7.0,6.0,9.0,9.0,7.0,8.0,16.0,10.0,HGGAAGEEFBEDHFDAFBAEDFGHFAHGDHEECGHCGCCACGFGHFAHEBHCGGCBGDHGDCGDCGBGDBDF,False +331,15.0,22.0,24.0,18.0,22.0,22.0,16.0,24.0,ABAFBECDEDAHCCGCAAHHCHHGBBGBAGBDGEDEHAECACBBFHHEHHEHHFHDCHDCBGFHFFHAEBFEFGDHAECEECBEFEGCCFBCGBCDEGHBGHFAHFGDBGEAGFADCBCCHCFFDEFEEFBEFHEHDCDDBHDBGFAFFBCCBCFBDADCGDE,False +332,9.0,18.0,16.0,12.0,7.0,14.0,10.0,14.0,AADCABGADACDAEDCHGCBFHBFHBEHGEFGHGECFBCDDGDAECHBCEBCFBCHHFDHDHHFFDFBGFGHBGECCFDFHDBHGBCFFABBACBCBBCB,False +333,24.0,10.0,12.0,14.0,8.0,11.0,24.0,18.0,AHAAHAADADGFHEEGBECBDCEACAHEGHEFHADAADFHGBHGBGBCGAGADGADGAHCAHFHFGEGGBACDCCDGFGBHCFGAFGBGEHACHAGGCDDHDAADGHDGFCGAHBAHBGFF,False +334,17.0,19.0,16.0,21.0,12.0,28.0,7.0,21.0,BCEAFGACAHCFEBBDBBDFFDBCDBFDFFDHFABDGBDFFGFDHFCGFGHCBHAFCEFHHBHHAHFADFBFCBFCBDCHEHDCADFDDEHDECDFCAFAAHABFBDFHFCDGHDHHCHECBEAEHAEFABDEFAFBGHEA,False +335,5.0,1.0,17.0,8.0,5.0,13.0,6.0,9.0,HFEEFACCHDCHDCHFBHDDCACCFCCGCFFDEFAFGCFHAEGFEGFDCCAFCHCGDCGDCHFH,True +336,7.0,5.0,7.0,10.0,4.0,6.0,4.0,9.0,CABCEBDDFADCAFCFGCEGEHDDBFGBFHCHHGHHDFDEHDAACAADHBDH,False +337,17.0,14.0,20.0,15.0,14.0,12.0,26.0,25.0,FEFFADAGDAGFCHHBHHBAFEECECAFCDFDDGGCHGCHFCGDGGBBGDAHDHECHGCBBBHDEHCCHFGHFCHBCHDAHCAGCAGEBHEBAAACEECEGGDHCEBFEHGHCGHCGDABAGHGGBBGFGGDGHHEHDDAAGA,False +338,17.0,17.0,8.0,23.0,13.0,10.0,15.0,13.0,DFFDBGEBEBCDBFDBAEEAFGAHDDDBBDEBGEBGBAGBGBCGEDEAHHADHDDHEDHGGHADDBDHHDCHDAGAECADCHDFBBFABDAFCAGDFFCAEGAEGEFGBDGCHAHA,False +339,18.0,24.0,23.0,25.0,16.0,22.0,30.0,24.0,DGBDGDDCDGCBGFEHEAAFCACGBFEBGCGCABCAFAGEAGEAHDCHBFEGHEBDDBDDBGABGFDGFBHCAEEAGDHEHFEFEHFGHFBFFGCAGCACCDHDDHBDFGDFGEEGBFDHHBCHDFFDCCABGBDGECBEGGGHDCHACHBHHGGHBGABDABHFCHFHHDBABGFCGFCDC,False +340,2.0,2.0,13.0,7.0,3.0,3.0,2.0,4.0,ECCCDCCACCBDCDFCDGAHHFEDFBDCDCCHGCHE,True +341,4.0,3.0,4.0,1.0,4.0,2.0,6.0,4.0,GAEGBCHBCFGAHGAHBACEECEGHGDF,False +342,10.0,14.0,13.0,18.0,10.0,15.0,4.0,7.0,BFBBADBAGACCABFAECCFCCEDEHDABBAFGGBDBCEBFDBFDEHDGHFAEECCDCCFHBFDEDDFDDCDDEHDEFFBDFBDFACHAFH,False +343,2.0,3.0,3.0,5.0,8.0,5.0,2.0,1.0,EAFDCDDCHEBFEFDEFEABECBFGEDGE,True +344,16.0,17.0,10.0,12.0,19.0,14.0,18.0,24.0,DGDFEBGECFCBBGFFEFHEHBEHGCBACBEGFGGHCBHGBHAEFBFFBHHBEHAGAADFAGFAHFAHGACGAEHABFGEGHEHHEHCABDAHEABCDHGEHGAHDDHDDBEFBGDBADGCHECHDHEEE,False +345,12.0,6.0,8.0,11.0,11.0,7.0,6.0,8.0,EEABBCDDGADCAECADHABGABECBECFEFFECDEGHAFHDGHFHAFAABDAHCEHAEHFDCDEGDGD,False +346,14.0,12.0,14.0,18.0,13.0,23.0,16.0,8.0,ECHBFBAFEFGCCDDGFDBFEGFEAFECFEHFEGBDDCHDHAAGAAGFBDBGDADDHGDCFFHEEHCEBGDGCFECFEBFDACDFGDAGDGGCGBABDCBCBAFFAFFAFEAFDHFCG,False +347,13.0,9.0,9.0,6.0,6.0,16.0,14.0,5.0,GEACFCDFGAFGAFCFFDDGGDBGDEGBAAHGAHFFBFFEEFBFFBFCEGBGGCECCAAHAGHAFAAHACGGFBCBBD,False +348,2.0,2.0,2.0,3.0,4.0,6.0,4.0,5.0,EFGDDADHEFBAFECFECFHBFGGHHGH,True +349,25.0,25.0,26.0,14.0,12.0,22.0,23.0,17.0,GCCGCCGEEDFADFDCCEHCBHCBGBBCBFGBAGFGHBGABFAGFBFFACCHHFHABAABCABGHEGBCGBFFAFGACCDDCBFGFAAAAAEACEFCEFCADCAGHAFABFDGADHHGBBCHGEBGCBHCBFDHGHHCEHBBBBEFAFHDDGFDCAGCAGDEDE,False +350,26.0,15.0,7.0,12.0,18.0,16.0,17.0,8.0,GFECAAAAAHFADABEGCECDGDAGEABEGBGBBGBBGCHEFFDFFAAAGEAFBAGDHHFGGAGEADFAEEBEFCGFDDFGDFDBFBEHHAHEAGEABEABEBBADAADAFFCEGCHAE,False +351,19.0,24.0,27.0,20.0,25.0,23.0,28.0,19.0,HHCHFCDGDBGDFGCBGDFGBFEDFBGABHABCABGBGAHGBHGBABCCEEBDFGDHGDBGHFGCFGCBHFBHECGCCBCGBFGACGDCHEEDFBGABFAFFGHDAEAAHDAFDEFDEDEECFEGHECAGCECCFCBABFADCAEGEDDFHFECFEGABGAHDHECBACDGHEEEEHECBECGFC,False +352,11.0,14.0,21.0,19.0,18.0,15.0,12.0,19.0,CGFBDFCAEDFEHEHCEACEAEEFGDAGBACBFCBFABDDGHDEHFGADGHDHCBHCEHCDHBBEFGFBADCGBHEADECDCBDCBACBACBDCHFHHCHFDGCDECGHCEEGHEHFFFFGEHDCHDED,False +353,14.0,12.0,11.0,22.0,22.0,10.0,7.0,14.0,BDEBEHDFDDCDEADEHCFHCAACAABBCDBHHEDHEFBAFDACABGEEDEADFADFBGFAGCGHCFEAEDGDDFDEEBEEBEHHEHHEDEEBHHCADCACHDDGGBFEDDE,False +354,25.0,23.0,25.0,17.0,15.0,24.0,9.0,25.0,FHABBAFCCFBCFBEDDHCHGBAEHCEBDAADFADFHFHHFHBFBCHBHHEHDACDFFAGBGDEGHHGDDCCCAHCEECAEDECFBBHDFCEFBAHAAHAFHAFHBFAAFAGGACEAEDAFDHEGFCFFCDFHGFHACHABBABECCCCACCBBCDBEBBHDB,False +355,17.0,20.0,28.0,20.0,27.0,26.0,18.0,20.0,FCDHEAHEGECAEDAEFCHFEFCCCCBECHEHEDHDHHEGHEDFEHAEDGEDGEFEECECHGCDGCBEDDEDDFDDBGGCGBHHAACABGGBCGBCGDCFHCFBCFBHFAHFEFFCFFBDACFCHBHEEFBGFBHFDGGCECAAFACFBBBABBDBEHCAFFEGCADEADFFBCGA,False +356,11.0,9.0,19.0,9.0,17.0,23.0,24.0,22.0,DCFDCHHGFEAECFFCFFGEFGFFGAHGBHAADAACEFFGGEHCAHCBDFFDGGHHBFHBHHAHFFGGFEGFCGFCHCGGGGEEEFCDHCDECHECEBCFGCHBCHAEHCEGFDGCHBEHBGHBGHFAEAEGGD,False +357,15.0,19.0,23.0,15.0,30.0,8.0,15.0,12.0,EDGEGBEGAEFADGHEFEEDEDDEGGFDAEEAGDAEEADEAEBBCFBCGECBEGGACEFBGDHECHEAHEHGGABCEDDFDDEDBHDBCBACACCGCABEGHCHCCBCCAFCHBEHEHHCCBCEBCEBCEBFBBECA,False +358,8.0,10.0,3.0,16.0,6.0,11.0,10.0,8.0,EADHDFFDBFEGFGCCAFCBHDGEDHDDFBBFEBHHDAHDHEDHGDAGDAEDGDGFBGABGFDGFABBADBF,False +359,20.0,14.0,12.0,8.0,11.0,4.0,10.0,13.0,BAHGAEDBEDCADCAHBABAAFAACGBHGBHABHEHCCHBCGAEACGDCADCHGAECADFAEBDEHFCHEAADHAGHFBEBCEAGEBGBGHB,False +360,26.0,15.0,17.0,18.0,13.0,10.0,21.0,9.0,HCBGGBGGBCCDDCDCCHCHHEGGEAFEDFAGEBDHBGAFGDGAABCADCEGCFGAEABEADHABGAEGFEAFAFCACGADDBEAGAABAHGDCDEADECDBCDBCBHCFDDFAGAEGAHGAGAAFBDB,False +361,15.0,32.0,16.0,34.0,25.0,18.0,29.0,23.0,HDFHFFDABBBBEEBGEBGEDEEGAHGBGBBHDAEGCDACHECHBGDBGDBGDGDDFBGGDEBFAHHHHEHHAHDADDEDBEBBHABHAFGDDBEDHEDHDDHGCHCEFDGGDGGBCFCCFEHFGGFHAEDFDFFCAEGABDFEDGBAGBGDBCFBCHEDADDCDCBBBDEBDEBGHCGBEABFCGGEFCEG,False +362,22.0,28.0,20.0,25.0,21.0,16.0,11.0,16.0,BHCHFBFFBDDBHHBAHBADBAHBAHGCCFCBBDBBECAEFEDHHBCCFDCBBBEBHEBFGBHGDHCFFCFAHHAGAGDBFDGFDBCGEADBFBBAAFEDGEDFDAAGBAGAABEDDACBECBEFDAHCCCCGCEEHAEADEDDEDCEACEAEDDEDDE,False +363,11.0,11.0,7.0,6.0,9.0,8.0,12.0,8.0,FBADHHEHFGGCGAFEAFEGFGGHGHCCHCCBCABAEBAHDDCGFABEABFABABDEBDBHAGGFBGEEGDE,False +364,5.0,2.0,8.0,2.0,1.0,2.0,9.0,6.0,AHGACBAGHCGHGBEFDAFGACHCCGCDGCHGHGC,True +365,33.0,17.0,16.0,24.0,25.0,19.0,21.0,11.0,GDDGDDGBDBAABAFECGEDGEDFAGCACCFHCGHCDAADBACFCHEDAEHABGGHCEEEBAEFEDFDCFDHFDAFAGFBCDAFGEDDEHBEDBDCBHCAGFHFDACAGDABEABGABGAHCAGDAFFGEFDEFGFGEEEAEAAEAAEAEFBBAHBABCEGEDGAA,False +366,24.0,28.0,22.0,9.0,23.0,15.0,15.0,17.0,HEGHECCBBCBBFAEDHBFCBFBBFABGEGCFDCHCCBAAHAADABBBBAECHECEEHEEBAECDDAGDFGDFCDCGBCEBCABEABAAEHGCHEFHEDHFGGAGEHGCBBAFBAHCFEEGAEGABAABAHFHBCCCEHAEBBEGCGFFBHFA,False +367,22.0,19.0,28.0,25.0,31.0,21.0,23.0,26.0,HGHDGHDGEBCDDCAEEADEDEEHAHBDCEEBEFGAHAADGDHBHFCEGEDBFDEFEEBEBCEFCEFCBACBADHADEGDAHCCEDDEDHFAHECDDCBEFBEGBDCHCHAABAACCHCCHCDHAGCAGEBEEAFECHBCHGCGGHFCFAGGEDAFDCBECBEHDEFFGFDGFHGFGGFGFFBFHBCCGAGHAHH,False +368,19.0,23.0,22.0,14.0,18.0,18.0,13.0,20.0,GAHHDGFBGDBFFBHGADABEHCCFDCBDAGDBFBBFBBFBFFEFFAHCAFGAHADHEBFBAFBECCEBCDDAEDGEHBBBBACBAEBDECHEGFCHACFDBGCHHCHGEHCCHCGHCGECEAGACHFCHFCHDEEEEEBDACAAHA,False +369,8.0,9.0,10.0,4.0,11.0,7.0,17.0,8.0,GEHGEBGFGGFCGEHAFBBFCBHCFDCGEHAEGCCGAEGBBCHBHFEAFGBCGADGADEADCGCHGEBAEGHEG,False +370,14.0,14.0,22.0,16.0,19.0,13.0,17.0,12.0,AEAAGFACECCFHBFDEGEAGADCEHCECCADHDEGFGGCCGBHGBHGBAFDGECGECGHBDHBABFACDDEBFECFEFFCAFGEGEEGHGCBACBCBDABCGBDFEDEDDHDFBDHCCHCCHEADE,False +371,24.0,19.0,21.0,13.0,20.0,18.0,17.0,23.0,GEGEADCDGEHBDCBDHAHCEFCEFEEFCDFBEGAGFHGFCCHCCFFCFFAADAFCABBBHGCHDHEAAGCAGDABHHCHHCHGBEFAAFHAFHGHHGDADEABEGBCGCDBADEHHEHACDABGECFEFEEABEBBHBBABCAGCFGEFABHAH,False +372,3.0,3.0,3.0,4.0,0.0,2.0,1.0,2.0,DDFDDBCABHABACFGCH,True +373,11.0,27.0,14.0,16.0,27.0,12.0,14.0,25.0,BGEGGBDBADECHGHHEHADHDGAEAHEFHBFHEEDGEDECBHFEHEBHDDCEABEAHEAHEBEEBEGAHCHHCBBBBBBBCCGDFGEBBEFHFDHFDHFDEFDEDEHGEAEEFBBHBBADBCBCCBGFDGHEFABBGHCCCGCHH,False +374,3.0,9.0,10.0,10.0,8.0,7.0,11.0,11.0,GCGGBBHHCCGFDGFDHDDHFDBFEGEEBECDDAECCBBCHGCHGFHADHACBEFHEBHDBHDGGFGEC,False +375,23.0,33.0,18.0,22.0,30.0,18.0,26.0,23.0,EBDEBDHHGCCGCFGADGBCGHCEHFEHDEHBEGDDGBHGAHDAHDBCBAABCFBCHEFDADCAEBBBBHBAFBAEBAHBHFBCAGCFHDADEAFECEECEFBBGGCCGEHHBBHEDCAFAHEEFFEAGABGCDGBBGBDFBDFGDBEDBHFBGDDGAEBAGAFGEEBEECEABEHGGADGDGFHGFEAEHHE,False +376,26.0,12.0,16.0,23.0,9.0,18.0,21.0,30.0,ADDFFDFFDFFHCFCBFAGFBGHEDHEAHECHCABFAEAAGAAGDDDDCFGCAHABDEGFHBCBCADGHDGADGHEGHDGHFBHGDHCDEABHGEHBDADAACHHHHFHAGHEGHDGHDHHCCCAHDHHGGFAAAAFABFHCFGBHGAACBGCDD,False +377,14.0,10.0,11.0,6.0,8.0,8.0,6.0,11.0,FCEFBBABDCHECFBCGBHGFHECGCFAFAEFDBACADCABCHHEAHGAEBAHAAHAAGFDCBDCBDGAEHHEH,False +378,10.0,13.0,11.0,8.0,10.0,9.0,5.0,12.0,ADCHBEECEEADBACBGBBAHBGHCCHGBHCCACCFHCDBDDFFDFFBFEAEHABHDBDAFHECBAHEGHEGHEFBAF,False +379,26.0,14.0,13.0,28.0,14.0,24.0,18.0,23.0,ACEAFGAGABGAGGEHAFHDCDDFFCGHCDHAAAEFFEGABGAHHADFGDFBCAGCAGBACDDDBDDEADCCHGEAGEABHHFHCCBDABHFEEDGHBGBBHFDFCDFBDADDEDDEDHFDHFDHEDHAAFAHDGDBGEFFABAECAHHFFHFFHDFHFG,False +380,21.0,15.0,24.0,10.0,21.0,16.0,24.0,20.0,GBFFDHFBFGEFHHHHHECHEDEEBCAFAABGACGBCAECBCCBEDFCDGCEEEAEGAGGACDAFDCGBBGBBCAFFDFHBAGGDGGCCHEAFEAFCAFCAHCGGAHCACCAEGHEHEEGEEGDCHDHHGCEGAFHHEHACBCFGHBGBAG,False +381,15.0,21.0,27.0,23.0,28.0,27.0,27.0,20.0,BCBHCAFBBGEBDEDHCDGCGGCGDCFECDECEBCEBFEBFGCGGBGABFAEHCFDCHEGEFFFBGFECCEHCGFFGFHGBECCFCFAEDAGAHDAGEFFFAFDACCHCHBBHFCDAGDHGDEGDBDEHDHHFHFBHDBFDEAGCADBDDBDDEEFEEAGEGGBCGEFEEFDGHHCHFEHCAGGABCE,False +382,0.0,4.0,3.0,2.0,1.0,1.0,2.0,3.0,BCDBHDBHFEHGGCBC,True +383,1.0,2.0,2.0,6.0,6.0,2.0,4.0,2.0,CHDAEDGEDCEGEBGEFDEDGHDFB,True +384,12.0,14.0,12.0,10.0,21.0,16.0,19.0,20.0,GDHEBFGHDHCEABECBDCAHGAEGCEBCEHDEAEBHEBHFHHBBFFAFDCGHAGDCBFHGHCADBAHBGHBGADHFCHFDHCHECEECEGFEGEAGEGGEBFEGAEBAFFFEGFGGDGHFEHF,False +385,9.0,9.0,5.0,9.0,10.0,4.0,7.0,7.0,BCCBABGHBGDEGDACDBEFBHDGADGAEHHCFCEFDEBDBBDAAEEAEHADAGEHGFHE,False +386,15.0,9.0,11.0,11.0,15.0,15.0,12.0,13.0,EGCFFCFGCFHFDHCHCCHACHECAGHFFABEAHEFHEDDEBDHBDHBECDEADGFGFBGFAGFAFAHEEEBDCDGEHGAGGABAAGDFDBEABEHECFAA,False +387,17.0,16.0,9.0,11.0,9.0,4.0,15.0,11.0,DADCFEBAEAGCBBHBEGBDABFBDFDHCAFEGGEAGEACHABHAGHDGHBHHBGDEGHCAAGDAHACEGBBGABAACGACGBDGBDHBDCE,False +388,10.0,3.0,8.0,5.0,5.0,8.0,6.0,3.0,BDDGGCAECAFGAFCACADCEGCAHCADCBFFAFFHHFADEGFEGBEA,False +389,17.0,13.0,28.0,32.0,15.0,31.0,24.0,29.0,HGHCCHGBFDBGAAAAEDAFHHDEGFECFHGFCFFEHFDHGDCCFCHFCFDCFDGEHBEHGHHAACAEDAHDACGEGFEBHDHCFHEFHGFAGFACDACBHCDHCDCCDEFDEFDHFECDHDDCGDGBBCCFDHBDFBDFCGBBHAEHCDGGFHGHAGFBDBDCGFCGFDGDDFDHGHAFFAGDCEDCF,False +390,23.0,24.0,19.0,26.0,25.0,15.0,25.0,27.0,FADECFEGAEGHCFDCBGCBDDHDDHDDAGAHHAEBAGDAHBHGBFGBGGFGDCADCBHBEHDEAEHGEHDBHGBHEBDGBHECAEDADDAEHFFHFHGGCCHHEFECCGDEACEHHAHGAFAADBBDCBGABDACCADABFABEHFEBEEBDDACDEEDGGGGBHGBHCFGCFHFBHCBEGEE,False +391,4.0,5.0,5.0,5.0,10.0,9.0,7.0,10.0,FGGFGCEGEEHHDHGDCEDAHBFHFGDFEBHBHHAHFCCFACFGBFEEHEEDEAB,False +392,2.0,1.0,3.0,2.0,5.0,3.0,4.0,3.0,FBGCCGDCAHEFHFDHAGEEGEE,False +393,32.0,34.0,23.0,23.0,23.0,22.0,17.0,26.0,AABCCBCADCAHAAEFAFBABBHCCFBFGDHDHCAHFGBBCCBHCBHBFCDFBHBEABEAGEDGECBEBHEBAEFHEBEBDHAHHBGCCFDDFDFBDHBGAAACEACDACHADFAGFAGFHGFDFADFAHEAEEBEAGDDHCDEFDBHCGGDGDAHABHEBHEBEEBEHFABAHBGEBHCFDGFGFEDADCACHACBGBB,False +394,10.0,5.0,5.0,10.0,12.0,9.0,5.0,11.0,DCDEADHACFADFADABDHGHHDAHGAGEEBEFFCFAEDAGBAEBCEHDBHFFCEFHEHHEGEEDHF,False +395,9.0,8.0,7.0,6.0,6.0,3.0,2.0,9.0,BAGBECDECDCHEAHAFGBFHBAHDHHAACAACHHFHBDDBEEAEDBCCB,False +396,28.0,25.0,16.0,17.0,19.0,17.0,23.0,14.0,FBGFAAAHBHHGFCGDGGBGGEGGEFCEHCDGBBHEACEGBEADCADGEGHDGAAAAABFABFADFCCBHCADEFGEDDBDACAABAAHHHFACFBDAADBAGBGEHDEDBBFBBFBBCEAGEBHEBHEBEFBCFECFEGDGBAGDACDHCFCFGAGAE,False +397,11.0,7.0,11.0,10.0,5.0,9.0,10.0,7.0,BCHBAHFDBFCHFCDDBHGAGCHGCGGCGGFGEAEECDDFADEBFCHDCHBGABGEFDCFDFAAADAACA,False +398,21.0,30.0,21.0,28.0,27.0,13.0,18.0,24.0,CBDCAGAAEHGBHBHHFHHAHHCGHDBDABFBEHDEBCEDFDCFDCFBCEDCBAEBEDBEBBABEDGFBGFEEAEBGHBGCBACBDCEECBDCDDCAAGDGEAGEAFEGEEBEHFDHDGCEBFEBDGDFHAFHFDHECHGCDGHEGDBDBHEBHGBDAAAAEADDDCABHDCHCEHCHGBBA,False +399,8.0,12.0,5.0,5.0,7.0,5.0,5.0,13.0,HHGHBAEGABBCBBCBBCFBCBHADAAFBAEBEBFHDECEEFHGAHGHHDFHDGHAHHED,False +400,7.0,6.0,11.0,5.0,6.0,14.0,10.0,3.0,AEFAEBCFDCFCFAEFCGGCGECHFGADCBDFGCHCCABCAGGEFHEFGAFBFBGFDGFDBF,True +401,5.0,2.0,3.0,1.0,8.0,3.0,7.0,1.0,BAGCFGEEAEBHEGFAGFDGEEGECAEGAC,True +402,7.0,14.0,22.0,10.0,18.0,10.0,12.0,15.0,GHECCAABBCBBEEBEGBDCEECFGGHCHACHAHFBGGCCCCHCEFCFDCHDCHDFHECHACDBCBAEBDEBDGGEGHDCEGHECEECEEHBEHDFBFBAFHDFGFCG,False +403,14.0,14.0,19.0,22.0,20.0,22.0,14.0,19.0,ECCEDFDGEDEEBCBHDAFBAFAAECCFDCEBBEBDAHCADCFDHEBFEDFEFEGFEAFHAFHGCHEEHDDFEDFDCFDCFCBAHFAHFHHFBDFDDEHCGGBGHBAHCAGCEGAHBHCGCEDEFDFGDHGFCGBBGCHGHDDA,False +404,9.0,11.0,17.0,12.0,11.0,7.0,12.0,10.0,BCBDCEGCECEGCDCCDGGAHGEBGBHCFCAFHAFHADEAHFDHEBCCDCCDCBDHEDHADBAHCHDDGBEGFGGBECFEFEGBAGCAB,False +405,5.0,5.0,3.0,4.0,12.0,4.0,3.0,6.0,DBGAEGEEDAEHAEBBEBEEHFDCBEFGEFCAFCEHHAHEDH,False +406,15.0,17.0,23.0,27.0,15.0,22.0,16.0,20.0,EFCEGEFDBFHCCACBDDHDCFBHFHGFCECAEABGBGDHCDBCABGADFDDFECCACFAEFHDGHDBHDAHDHHDHBFEFDEADFADBDCHDEHFCHFGGFHGHHEAACAFCFBDDCEBCGBDGDEGDBGDHFCCFDEHCBBCBGDFGAFEAGC,False +407,11.0,16.0,12.0,20.0,16.0,15.0,13.0,15.0,HBGBDGBDGFGEFCCHCDHCDHFFCDBCFBEEECEFCEABEHDEDBEFHFDAFDBHBBHDACAHFAFBAEBDDDADDAFDGGGEEGHEGDFHBFHGDBGCBGBACDAHHCEAEEDHGF,False +408,16.0,12.0,20.0,13.0,15.0,13.0,22.0,14.0,HACHAGEAGFHHDDCEDCBFEDFEACBBFHBFHBCGBCACCBDDGDDBEFEGGHDBDDGGFHGAHFEGAEACDACGABAAHEABECECCECGGCAHFAHFGGFEECEHAFDGGGGCFHCGGCGBC,False +409,4.0,7.0,9.0,5.0,9.0,7.0,4.0,6.0,EFCBHCFAFFACFDHHBHCBGBBGBCEHGECBAGDCEFCDFCDEEHEEAED,False +410,12.0,11.0,9.0,6.0,6.0,6.0,2.0,5.0,DDCDHBBABBACFACEBDEHDHBFBAFBAGCAEAEEFHCBCCFHCAAEAABDABGFC,False +411,10.0,13.0,4.0,12.0,8.0,3.0,7.0,11.0,BBHBBDDDDDEEAAHAAHBAHGEHGHHAEDEEDACDBBDGCDBBABHHCGCFGFEGBAGBFDDAEHBH,True +412,2.0,7.0,4.0,0.0,2.0,6.0,5.0,2.0,BGBFGBFGBCGCEACFBHFEABHCBGFF,True +413,28.0,23.0,16.0,19.0,25.0,12.0,17.0,19.0,BHADEAEEHEEAGEFBBCDDAGHHGHAEBDFBAFBAHAEHBECBDCGDGBFGEEAEEDBDDBHDEHGECAACGACABCABFABCADEAHEDBCGFEBFEADEBEGADAAFAFHADBACHABHCCDCDBFABGAEGCGFHACDEGHHGHGDHFBHEBEGC,False +414,4.0,13.0,10.0,10.0,10.0,2.0,11.0,8.0,EEGCECCGBBGBCGDEEAGEDBHCHHADHDBHEHCFBDBGDBDDBDEADEHBCAGCBGEGCBGCBGFH,False +415,13.0,21.0,20.0,13.0,22.0,19.0,15.0,24.0,HFDBGDBHHBCCFHHFBHFBHFBHACEFEHFCBGBBFBHFDGECGFCAABGCFGCHHBHHEGFEABCBECEECGDCHHFEDAHBAEEDECDHDGHFGHFAECAFBAGBDECDCHBHHDCEFCAFEHEEGEAGEAFEDEBACBDCBGG,False +416,21.0,17.0,11.0,9.0,12.0,14.0,19.0,7.0,CGHHGBDBAGBAGBDGACGAHFFBFAGCACDAGAAEAEFCCAEFBCFGCAACGEFFBDAEDABDCEGEFCEBBHFBHEBHEAGGBGFAHFEBFBBDABFAGGAGGDGADE,False +417,6.0,8.0,8.0,1.0,1.0,6.0,7.0,5.0,BADAECHCCHCCHAAFCGFBGBBHBBGFCFHCGGBGGBFFAA,True +418,11.0,22.0,19.0,15.0,20.0,16.0,14.0,28.0,CCEHHDBHECHCGAGDCCABHFHHEHDEGBEGBDDBDEBHBBGFFCFFHBDHBCHBEHBAHFFGFCDHHDCHBEABHDBHCBAAEFDCBCCDFHEFGBDABGFBCADEFDGFAGEHGBHCBCGFAAHEEHEFHEGEEHEEHCGHC,False +419,25.0,19.0,13.0,15.0,18.0,30.0,15.0,15.0,FHCDCFBEHCABEAFAFHEFDGFDCDEHAFGAFBDBBFBBGBAHFAGFBFFBDBDDEGFBDEBHCBFCEFCEFAECAEFECGADBABAEHFDGFGGBGFBGDAAAHAAHDFHGCHFCAFEAEEDECDHBFAGHAGFEEFAFFAFAHCAHG,False +420,5.0,4.0,3.0,9.0,10.0,5.0,4.0,4.0,DEBDADFEFCEHEABEAEEFEDHGDHEDCFGCFDDGBDGBEAAH,False +421,21.0,22.0,19.0,21.0,16.0,23.0,24.0,24.0,BGGDDGBHHHHGHHDAGFAGFBBFGGFGEHBAHECFACAGHEFCEADEAEBAHBGBBACDACDHCDHCHBCDBDDGCFHHFHHAHEEHCGCBGAADFBGEGFCCFCGFDHHDHCBFDAADABBCBFCFGDECBEFDEGDEDFABFADFGBFGFAGFADHHEGABCFBGEE,False +422,5.0,3.0,3.0,1.0,0.0,2.0,1.0,4.0,ABCABCBGAHHHFHAFCAD,True +423,8.0,5.0,10.0,3.0,2.0,6.0,4.0,7.0,CAHCAGAAEDGFCGDCFHCAHCAHBBDFAFFGBFBBCCCHCEHAH,True +424,4.0,2.0,3.0,3.0,3.0,5.0,4.0,1.0,GDFGCGACDACDEBFEGHEFFAAFB,False +425,20.0,29.0,28.0,22.0,37.0,21.0,18.0,23.0,DCDEFDAGCHCHFDAFEFFEHDEDBEABEHBEBFCBEDBCDCCEGCEBCEAHDHHDAHGAHBBBFABFABACBADHEEHEEAEAAEACDCHBCEDEEBEGGEBEFDGCBBBAFDAFCAFCHEDBEDGECHBHGFGECEDGDFECFDCFGHECEEHFEBCABCADEAFEGBBHBFGBEHCCHBCGBEFCHHCHGGGGDF,False +426,3.0,6.0,6.0,5.0,11.0,8.0,8.0,8.0,ECEBAECEDDEBDGBGHDGEBGECGFHGFHACHFGHFCFBEFHHBHEADEFGCFE,False +427,9.0,21.0,17.0,17.0,18.0,17.0,9.0,12.0,BHBBHBBAFBCCHEBDECFECDEFFGHCEFCAFAEHDGHDBHABEEBEEDAECBDCECABDAFDHDGEDBBDBFAFFCCBHCDHDBFDGFGBFCHACDBCGGDGGCBFFBFEEFHECEED,False +428,13.0,9.0,6.0,7.0,7.0,9.0,7.0,6.0,HDAAECHEGFFGFGCFHCBGAADAADAAFABFBEEAFFBBCBBEABECGHDGEDGDABDAFHCH,False +429,8.0,15.0,19.0,18.0,20.0,20.0,16.0,22.0,FGDFDDFHDGAFGFHEBABCDBHFGHFCHACACCECEACEBCFGDBHFEHFBHGHHEHEBGEAFFHCFDEFDADDBDGHFBDFBCFBGAHFBECHECBECHECECCEDCHGEEGEGFDFEDBEHBHCDGDHCHHGGDG,False +430,13.0,25.0,20.0,21.0,26.0,17.0,24.0,16.0,EFFGFCDFCEHCGHDGEECAEBBEGBECFEGHAADDAFCAFCBCEECFFCFCAGDACHBHHBGDCGDGGDEEDBHHGCHEDBEGEECEEBEBBDBAEEFDGBGGBDAEDHEFCGBCGFCGAHGFHDBGGBFBFFHEHBCDBADCEDEBBGAAGHBGHBDBDD,False +431,13.0,21.0,18.0,12.0,10.0,10.0,17.0,15.0,GAFBBBBFHGFAFBGCGGBBCABCAGDHGDHBCHBHBAHGGHEGHDCDBCFBCGECAEDDHBAEBDHBDHBDACECGEGGDHADBEFCDBGACEAHBCFBEHAEHAFGCCGCCFFC,False +432,14.0,11.0,9.0,15.0,14.0,12.0,12.0,18.0,DFAFFAHDHEDFEHHEDHCFHCECBABBDGEFGEDCDCGDHHFCHFCGGCEGABGDBEABAAHAEBDEBHEGHFGHDHEBADGADBAEHCEHDDHBFAGAAFFGH,False +433,16.0,16.0,12.0,20.0,13.0,18.0,9.0,14.0,FDCFDADDBDDAHDCBDCDDCDAEHAFAABADBECFAFBCFADAGCAGCDBAFCFFEHFHBFBEHGCGGDFGDABDEECGGDFEFBHCBHBEHBEABEHBAHGAEFBEHHHFEHFDFD,False +434,15.0,21.0,15.0,6.0,12.0,5.0,12.0,17.0,CBBDBGABGCDGCEADBCCADEFCCAHCHCDHCAHCHHABHBBHABEFCGCBGAFAAHEAFGAEGAHGEEGHEGBFBEECHEBBAHHCHDBHBBHBBABBGEG,False +435,0.0,0.0,3.0,2.0,2.0,2.0,2.0,3.0,CHDCEDEHCGHFGF,True +436,22.0,21.0,21.0,13.0,7.0,14.0,20.0,13.0,BHBGDAADEDFGCFGDHGAGGAFDCCACCHEADBCFBCGBFABEHDCHCEGBGDAGAADCAHGHHGHFFDEHAGAGGABCAFAFFACHACGBDGBDCBDHAGCFEBFACHBCABCGFCAFGBEBBCBBCBB,False +437,18.0,12.0,15.0,15.0,9.0,15.0,19.0,9.0,BEAEFBCFAADCBFGDGGHFCADAADGADHCBHDGDBGDBGDCGAHEFHGFAEBAHBADGCDGCGFCHFDEFEHFCAAAFBAHAEGDEGFEDCCBCGBFGBFGACGCCADFG,False +438,9.0,15.0,11.0,10.0,6.0,5.0,12.0,8.0,CBBCECABBAHBHBCHGGEGGDAEBEDCDFADBGDBGDBGBBCDGABHCFGBFGHFGHFEAAEAABHDDCGCCDCH,False +439,21.0,34.0,13.0,20.0,9.0,14.0,18.0,22.0,DBGDFCCFEAGHBHHCHHCBHBGHBDABCCBAFBAGBDCBDBBGBAFFDHEHGCBACBAEFGHBGAFGCFBAGHAHHAGHGCDEAHABHBDFEDBDDADDHFBHFBEABEABADBHFHDBABBHBAEBGCDCFHGGGBBGFDGDABDABDE,False +440,5.0,7.0,4.0,9.0,2.0,7.0,1.0,7.0,DEBHHHHHHDFAAFGADHABBFFDFFDBEDCCCCFBDDBDAB,True +441,9.0,3.0,11.0,9.0,5.0,3.0,13.0,6.0,GCHGCHBCDDAEAHEAGAGGCGEAEHACDFBDBDGCDGDGGHGCFGCAHCACDGCAEFD,True +442,26.0,15.0,9.0,16.0,20.0,21.0,20.0,20.0,EEHEFAFDDHDDBDEEFFEDFCHFAAGHAEHADBAGHAGBADAAEABCGBCBBFGCFGEFGEFGHDEAEEAFHFGHDGFAGACGCHBCHEAHGABGBGADGFFGEEBCFDHAEBAGBADAABBHFHHCEEFFEDFHAHHAHADDGFG,False +443,5.0,11.0,13.0,10.0,14.0,14.0,10.0,14.0,FCEHCEHCEDGDBBDGEDHEABEFGAFGAFCCFHFFHFBAEEGDFFAHECHGCHDCHBGFEHFHFFBBCBBEHCHHBECDEDBEDCGGGDC,False +444,9.0,3.0,12.0,6.0,9.0,11.0,10.0,6.0,GACGCGACGBHABFCEFCEFCAFGFEGDCFBCHHHHGAAAEADCDGAGEEEEECFFCDFGDFCDFH,False +445,9.0,10.0,13.0,13.0,17.0,11.0,15.0,15.0,DGCDBCDFEFHEHHEDDEGCCFCFFCGDEECEFHHFAHFAEDGGBBGHHGCHGBACAAHEEHEEDGGDGGDGEEFEBGHBCDCAACAHDHBFEFCEDBHBBAG,False +446,4.0,1.0,6.0,9.0,11.0,4.0,5.0,7.0,GACEFGGACGDFDECDEHDEHDEHEEDAHDCDFCDBEHAGFCHEEHE,True +447,26.0,19.0,18.0,11.0,16.0,16.0,12.0,21.0,EEHFFHCBABHABHAEHAEHEFFGFAGHBHAEEAEEAGAAGCCGABDACECFHGHHEDHCBHCBHCBAGDABDCHAHEFHFHHDDFBFFAFCACABEDFEDAGDBFCBDAGFACEACAGHABBFBBEBACCCGHCDBAG,False +448,6.0,5.0,7.0,6.0,1.0,1.0,3.0,5.0,HADHAHCACGDGBDGBAECACBABDCHDBHDCCF,True +449,11.0,2.0,6.0,6.0,9.0,16.0,8.0,5.0,AGAAHAAGFDFEEFBEDGEGEEFEAFCCDEDFFGFFGFFCFAEFAFHDFCBHADHFGHACCAG,True +450,11.0,4.0,8.0,12.0,7.0,9.0,7.0,8.0,FDEFCADCGCEBAHBGECHEFHCDACDABHGBFFDFAEFAEADGADFEDHCAHGDHDFCDAGDAGH,False +451,31.0,20.0,20.0,33.0,22.0,23.0,32.0,17.0,BCCAGAAGFAGCEGDBGDACDHDHGFBGBBDBFGBHBAHECEECDEDHHDFADFEDCEGHAFBCCBFADGCBADDFEFGEHGEFGDHECAEAGEDDEBDEADAADBCBGEDHDDFCEAAHBGBGFAGFDGFDEFEGHBAHFAGFDGDDFDFABCABCAFCAFCAGCAHEGHGDAADAGEFGHDGCDGBGHCFAGDEGA,False +452,6.0,6.0,6.0,10.0,8.0,9.0,9.0,6.0,AFEABEBDGBAFEDHGFHGEDGEHCHAGHECHCCFDADDFEDFEBAGCFGFFGCBGDBDD,False +453,13.0,18.0,14.0,23.0,17.0,19.0,19.0,12.0,DCGDCDDCADEBFFBFFCAACDACDCCABCDDFDFAAEGFHFADCBGCDGEDAFGGEHHEFBFFBFFBGFCDFCGAGDDHDDHFEHGEBGHDGHAEHBGBDEFCBDDEABHAGEBEEBHEDEGBHGBFGBGEEGB,False +454,18.0,22.0,18.0,14.0,25.0,31.0,12.0,21.0,FHADBACFDHAHHDGHBFFFCFGCBGDHFFFGFFGFGGFAHCHEEHFHDFHFFHFAHAHEACEGEEBDEDFAFFBFFBFBEFDCBBEAEHDFDEEEBBGCBFCFCBGBBFEHGCDEHDECDECBADEAEEACEACECCABBECBECBFAFAGHEHHABHAB,False +455,8.0,7.0,7.0,9.0,13.0,7.0,12.0,7.0,AGEBFEADAAGFABFHDEAFFCGFDEHGABGCBHCBGBDHBDFDEGCEGCEDCEHEDHGDAGEHEEGCEG,False +456,26.0,25.0,17.0,12.0,23.0,17.0,8.0,10.0,BCAFCEBDBGCAAFAAFGCBEAEDDBADBADCHEFFEADEAEEFEEGAEGEHBEGAFHAFHDFBBAEACCAECBBBBBFABEABDBBDABDCEDFECACHFHAFHGHDCCAGFEEACEABFABFBEFAEBBGHBCHCC,False +457,17.0,13.0,15.0,8.0,13.0,12.0,8.0,11.0,HFCEBGABGABDAECBBCBBEBEEBFEAADACFHFEHFBACAACDAFHHFAHGAHAAEAHGHCGFCDFDAEEBDECCHCCFFGBEGCDFCBCAEDHG,False +458,4.0,0.0,3.0,1.0,6.0,6.0,4.0,0.0,FEEFEFFGCFAEAGCAGEADEFGC,True +459,21.0,25.0,18.0,16.0,17.0,17.0,23.0,17.0,HDAGCGGBBGBCEDCBBBEGFEGFEGFAFFCGFCBECBFFBEBBGBFABCAFAHEHEDHGDCCEAAGAAGBCGHCBHCAEDHHDFFDABEFECCABHABEDBEGBEGDGDFGAFEAGCDGCBHHDHCAHGABFDEADBADBHGAGAHFHGCHDB,False +460,10.0,14.0,5.0,9.0,15.0,9.0,9.0,8.0,EDEEGEAGEGBEDBDFGDEABFAFDAGEBBABDAGDBGFFHAEHDEABGBHABEACEFBDFBCHGCEBCEBEHHHFHCF,False +461,5.0,3.0,5.0,6.0,2.0,12.0,7.0,4.0,CEAFFGFFGFFDFHDFBDADACCGGCABAHGFBFFDGHDGHEFC,True +462,6.0,6.0,14.0,9.0,5.0,9.0,18.0,19.0,FGCDHCHHGHDGADGECGHCGCGHCEDGEFFHHFHFGBAHEFGBCGHFDHFHHCGHCGHEGBCCBDAHDHGBHACGCGFCDABDAG,True +463,3.0,5.0,4.0,8.0,5.0,3.0,5.0,5.0,DGAFBBFAHGEGGEGBECECCAHHDDDEDDHFDHBDCB,False +464,8.0,5.0,4.0,6.0,7.0,4.0,8.0,3.0,DACBACHAGHBEHDEFEADGGCFEDGEBGEAGBAGFDGFDAAEBC,False +465,13.0,13.0,10.0,12.0,11.0,18.0,10.0,10.0,DFBGFDFFDGBBBEDGEDBECEEDFHAAACAAHHHHHBGGAAAFHACDACEFFHFFHAGCBEFBEBAFGAHGDEGFFBFDBFDECCECCGBCDBFDF,False +466,1.0,7.0,5.0,6.0,4.0,4.0,5.0,8.0,DHBECBCDBGDBHDBHFHECAECFFGHDGBBGHCGHDHFE,False +467,8.0,10.0,7.0,7.0,13.0,10.0,14.0,7.0,GGBEGHAGEGBEDBCAFFBHEEAEFBEGCFGCFHBFEGFEBFHFCHFDGDDGHDGDCHAEGCEGAEDCEBAABABG,False +468,7.0,9.0,14.0,4.0,4.0,10.0,8.0,4.0,FECAECBDFBGFCCFECFDCBGCBGBFDAHGAFGBBEBCHBCAAHGAGCCCFHCFGCDAF,True +469,11.0,8.0,10.0,17.0,9.0,15.0,9.0,16.0,FHDFDDEACFHCFCAHDEHAGHACHDGBAGBEGBAGEHHDGHFEHADHAEFAGGCFECFBCDGDHHDADBCDBEDFFDFFCCBEDHFHAFHDFDB,False +470,1.0,3.0,1.0,1.0,2.0,1.0,2.0,3.0,CHADBEEBGHBGHF,True +471,17.0,15.0,26.0,18.0,19.0,21.0,23.0,27.0,GFFCCCHCDHAGAEGFGCBGCBFCFFHDFBDCHDGHFEAFEAEEAEGDHGHCGABGDCGDGGFFFACHBEAEEDEAHFAHDHHGCHFHHGGHBBECGECEEDAHCACCBBCFBCHGCHACFDCEDAHCAHFFFDABEEBCBAHFCHBHBGDGECGEHDHGDHGDFD,False +472,2.0,5.0,3.0,5.0,4.0,6.0,6.0,2.0,EGHFGBFEBFEDFHGCCFEABDADDBDGBGCFG,False +473,20.0,30.0,26.0,33.0,27.0,26.0,18.0,15.0,CGAHFAGFAFDBCDEGDEHBEGBEBFDGFECFHBFHBEEFEECCEFEFFHCDGAHABDFBAGBADBADBDGFGCDCABGAEGDDDDACFACEAFEBEGDCGCEFDEBEEDFEFFDABDHBDEBCHBHHFDDBCDFGDAGHBDABFBDDDFFBBACBCCBCABCACCHGCBFBDDEEBCGDCGDCEDCHFEHEAHE,False +474,19.0,17.0,14.0,18.0,11.0,17.0,20.0,12.0,GAGCCFFCGFEDEBFFAFCGDHGEHGEHGHGFDFAAFDADDADCACCBFBDGBGGBFEBCABDAGHGBDBBHFGEAGCDGFDCFCHFAGCBBABBABAEBCFCDEDHGHAEHAEDAEDGFDGDAHHAB,False +475,29.0,21.0,29.0,16.0,8.0,11.0,32.0,19.0,GGHBGAGFAHFBGAHFBHGBHGCEACHGBAAAFHHFHHCBGCGAHBDCCDGAAGHHDBDCBDFBDBEACAFCEDCBGABGAFEACGACGCCGBCGHAGADEAHGDCGCBBAFBADCGBEGBEGBAGCGGAGABCCHCDACGHDGEAHAADFCCHACDGCDGCDFC,True +476,1.0,0.0,5.0,0.0,0.0,3.0,1.0,0.0,CCCGCCFFAF,True +477,12.0,12.0,12.0,10.0,3.0,21.0,15.0,7.0,FDFAGACBDCBGCEFEFDGAGGBBDBBAFCADCADCFCGFCFFHFFHBFCCDAGAAGBFDCFCAFHDBBGHDGHFGBFBEFGFFAHGAGGFH,False +478,17.0,16.0,18.0,22.0,16.0,25.0,17.0,21.0,ACEFGEHAECACCHBGAFFBCFECADCEFAEDEFAECBCGBCHFGHGEBAEAADHGDGAFGDDCEHCHAEHDEFGHHHBHABFABFHCFHCFHCFBDFBHBEFFEDFCDBGDAFDGBHFBHAEDCFHBDDGADGDFCDFGDGBDGDFHDFHG,False +479,10.0,7.0,13.0,9.0,7.0,6.0,9.0,3.0,HGCDGCAGAEGAGCCBCCFCEFEAFEACGGCHDABDECHFABFEBEBADBDDBAACGCFDCDDG,False +480,1.0,0.0,4.0,0.0,2.0,0.0,5.0,0.0,GCEGEGGCCGCA,True +481,21.0,16.0,14.0,17.0,11.0,10.0,25.0,16.0,FDGEEGBBDHAHGDHBHGBGCBCCFACEAEGAHHDHBGFDGADAAEAAFHCFHDFABGCBGAGGADCHDCECEDBDACDAHDAGDBHHBAGFAEFGBFGBGHAGAAEDCBCEBHEGHDDBGGGGCAGCFG,False +482,12.0,17.0,21.0,17.0,21.0,22.0,20.0,24.0,HCBHEEHCEHCBHADGBCGBEEHHFGHFDHFCHCGHGGHBGCBCHGDDACDFFFFFGBACFECGCFHFAEDHDDBDDHDEGDECAGCAGHAEHAHFEFDEACCDGGGFGCEBCEDHFCHBHBEHDDABHFFFAFFBFEBEBBGAEGCEGCEBFE,False +483,19.0,21.0,17.0,13.0,22.0,21.0,20.0,24.0,GDGGEGFHAHAEHADHCEHDAACCBEFBEAAFFAFGHHBHDBFDFFACBGDDGDHHBACBFDHFDBFEFFGABDACDFFHGFCCAEBBHGBHBBEBGCDGCHGCHEFHEAHEHHGACCACGAHHEBGECGACFEEEBEFBCFEEGEHGEAGBFHBEB,False +484,14.0,17.0,19.0,19.0,23.0,9.0,30.0,14.0,DBADEECEEGGGCGGCHGAEDCGDCDDHDGGDEBHBBCAHHADGGGEGCECCACHAGHAEDABCHGGHAGDADBEFHHFBCEAGAGGDGGHGGACFFBFGCFGBBDBECBEDBGFEHDEBDEFHEBCEBAEGEECEGBGFCDECD,False +485,23.0,20.0,17.0,18.0,15.0,7.0,16.0,20.0,ADAADBBFAFFAFAAGCDHCHABGABCAGHBGHCAHEECBECGDHHAHDEFBGDGDBGDBAAEABGHBDCECCBGGHCEHBFABFABCACAECBCDDCBEEADEADHHDHDDGEHGEHGEDCBDCHAAGGBHHBHE,False +486,19.0,15.0,16.0,14.0,11.0,13.0,25.0,19.0,GDCGHFGHCBDBAAAAAACAGHBGADDCCHEGBCBDAFDBGDBDEAAGAHBAHADCDDEHHFHEAGCGGCGGBGHCGCBGCBDCGGGFEGBEDFHCFEBFEAFGAEGCFGCFGDEGAHFEHABFFBHHHHHH,False +487,17.0,28.0,19.0,19.0,12.0,13.0,19.0,22.0,DBDEFAHAGFBGHEGHDDBBEBHEBHDCHFEHGEHGBBACBAGAAGEBBHBDFBDFBDCCHCCAEBGDGDCEBCACFAEGAHDFCCBHCEHDEGCBGABGBDFHCFDDFDBFGAGGFHBCHCABDABHAHCAGCHGBBBCBHFDHADHG,False +488,11.0,5.0,10.0,9.0,17.0,10.0,8.0,12.0,HFEBAGAEFADDEHDEHAEHDEHAEDEEDGBCHCFECFBCHGCHGEDBEABGAHFAHFHEEGFHACECCADEDCEFCAFGFG,False +489,15.0,27.0,19.0,19.0,24.0,16.0,18.0,23.0,GDHCDCEEBEBBHABHFBGFEGDDHDFACCAGGADEBDEHABHAFHGBHAFCAFCBFCFHCHDEHDBBFABDEGCECHDDDDGEAGHAFHFEBBEAHCAHFGHABEFEHDHHDCGBEHBEBCCBGDGEBGEBEECEGBECBEBDEBFGHABHFFDGCCGBC,False +490,3.0,2.0,6.0,3.0,7.0,0.0,1.0,4.0,CBCEHEADEACEADEDBCGHHECHEC,True +491,14.0,16.0,16.0,14.0,17.0,13.0,22.0,10.0,FADFCGFCEFCEBCGBCBBCBBAFBGGBGBEEEFDBBDHEEHGHAGHAGDDGBEAAGDFCHADHGDHGHFBDEDDEFECCEGGGGGADGCBEEHDCGCCGABHDBFAFEEECCAGAFGAFCA,False +492,26.0,18.0,20.0,24.0,26.0,19.0,29.0,28.0,DCADFADCEHGDGGFGEAHEHHAHFCCCGHBAHEAECBBGGBHGBHDBAAFECHEBHGFHCAHDAHDAHACHCGHCAAEGGGDBGDGGDEGHHDCGEEGEDAEDCGFCDFEFFADHGBCABHDBEGBGBHCHFGDFEFFEBBEDBEAAEFEBFGBAHAAHECDGDDFDACCAFAEHGEDGEDCEHFGHFA,False +493,1.0,0.0,2.0,1.0,4.0,2.0,0.0,0.0,ECEECEAFFD,True +494,11.0,16.0,14.0,24.0,25.0,15.0,20.0,16.0,HFCEDHDDCEGCFADBEDCEDAFBACGFFGHDDDGBDFEAFCAFHDFHEFBAFBDEBEHCEDBHDGHDFAEFCECCBGGBFDBCDHAHBGEBEEHGGHABDGDGGDHADGAEEBFECEECGEGGEBEEBHGCHGDHGDEDE,False +495,15.0,21.0,13.0,15.0,18.0,25.0,20.0,12.0,GFGGDGBFFFDCCDGCDECAEFFFHCECCEDEEAEEBEFHDHBGGBGGEGHAGEAGBGEAFAHFACFCHGBBGBBCCDEGDFFFFABBBEBDAGDAHFACFAFDABDBBEFDEFAFBBFBBFEHHGHDDHBFGAFHEGC,False +496,14.0,17.0,8.0,12.0,24.0,10.0,23.0,11.0,GBFGBDGAFGBGEBFEHDGAFEBCGGGBABDAEDGEFBAFHEFHBFHEEBGEBAEGGEFGEABAHBGHBCFGEGCAGCEHEGHDDEBAGCAGBECDECDEGDEGDBDHEEHAEHDCAAE,False +497,8.0,11.0,13.0,8.0,7.0,15.0,9.0,16.0,EHBHFAFCAGEGGCCGCAGBAGHDFFCFHBHHDDHFCAECHDBHCBHAFFDFEHCGDFGAFCAFCGFEBBCBBCFHDHEDHFBHEBH,False +498,3.0,6.0,8.0,3.0,3.0,7.0,4.0,5.0,CHECBEABACCGCBGFHFFBGDBFDAFDEFCGBCHFHHC,False +499,7.0,4.0,9.0,5.0,5.0,8.0,3.0,3.0,ECEEFHFFACFAHAABEABDCCGFDGFCCFCCFGDABDCDEBAH,False +500,7.0,8.0,5.0,8.0,4.0,3.0,2.0,4.0,CAEFHGBDDBDDBDDBCGBCFDFDHCAEAEHBEABAAHACB,True +501,22.0,26.0,22.0,26.0,16.0,25.0,21.0,27.0,EBHCGHBFHBFBAEEAHFAHEADFGDFBFHCHCCHGAAAAAHAGBBBDBCHCEHBHHGDDFBEFDECDBFFHFFDDDDDFDAACHBDABDHGCEGCGHFGAFDCFGCFGBBGFACDAGHFGHEEAEEAHHBDDAABBCBCDDCDCGHFGHEBHABGFCGCEGCBCHBCHDGFFBFGEFDEHDBAD,False +502,10.0,11.0,12.0,13.0,8.0,15.0,13.0,13.0,GFHHEHDCHDEFDADGCDGBDFADFHFACFACACBFCGFCAFEECBECBACAFDEHBGGAAFDGHCBDCBHGBHDFHDHGEFGFHGFHDBEBGGB,False +503,5.0,6.0,10.0,4.0,4.0,8.0,9.0,0.0,FEDCEDCGBGGBCFCFEDBEGAACABCGCCGFFGFFDAGGBCABCF,True +504,7.0,14.0,10.0,11.0,12.0,9.0,6.0,15.0,BDBBGBFCEDCHDCHEFFECHGDEEHEDHDBCDHGABFABFBBDBBCEECHEGFAHCGFBHFAHFAHDCEAHBDCBDHGEHAEH,False +505,21.0,9.0,16.0,11.0,15.0,16.0,15.0,15.0,DFAGEAGEAFCCECCECFEGFHGDHAFBCHEDHEHBEAGFCHDHGAHFFCAAGAAGAAGAFEDGCDFHGEHFEDFBDCAHGAHBABEABGABEDFFHGFCEACHADEBCCBGFDCCHA,False +506,17.0,15.0,12.0,11.0,15.0,5.0,18.0,14.0,BHGDHFBGBBABHAEGAEDAEAEDBEDGCGHADCFEHAGHAHHAFADCBBGEGGBDBBDEHHHGGBGADGACHCEGCEHAABFAEHAECAECEECFBCGDCGBCGDG,False +507,23.0,16.0,18.0,17.0,15.0,30.0,19.0,16.0,CAHCHFAHFDGFDGEHAABDAFCAFBAGBHGHCDBAAFGFFGADAHDGDGGFEDFEDCCCCDHGFFGFFCHFAFEAFEFHGBEFEEFEECDBGGHHGHCEHEGCADCEBAFBFDBGBCHBFFBFFBCDBDGAGFABEAEAAFFCBFCADCADHA,False +508,2.0,2.0,6.0,5.0,8.0,2.0,3.0,4.0,AECAHCEDEEGEDCFFCBECDDGGDHECHEBH,True +509,10.0,15.0,13.0,10.0,20.0,25.0,8.0,14.0,BFFFFGHDGHBEECGECGEHFEFAGBHGBEDEGAEAHHFFHCFCFFHEFADFBCEHCEGFAHFHEFECBDCBDABDCBFCBDHBEFCEFCHFEBEBFEAFACFHFBAFEADDDBE,False +510,9.0,6.0,15.0,8.0,8.0,15.0,8.0,4.0,CGFCHFDFCDFADGADECCCFCAFBFFCCFEGFDGFCGCCEBBEAEEAEFGHDGDFCHFEFAGDABBCBCAHA,False +511,1.0,1.0,2.0,5.0,3.0,1.0,4.0,3.0,GDDGCBGCHDEEDHEDFAGH,True +512,16.0,13.0,8.0,20.0,20.0,20.0,19.0,18.0,GEEGAEDHBDFBGBGGHGEEDHEHEGFEGBEGFHGEDBBAHGFDAFDAEDGFFHFFHEEHDEHDGDGADCADFADABFHDFCEFCHFDGAGABHAFHGHCBFCHEHBEAAEAAEBCEDFGABDCHFCBFDFDDG,False +513,2.0,0.0,0.0,0.0,3.0,1.0,1.0,4.0,HHEHHEAGAFE,True +514,16.0,32.0,27.0,32.0,20.0,18.0,31.0,18.0,FFCEHGEAGHCGDDGHDFEDFDDBDCHDAABHAGDEGDEGEFCBDAEABBAGBCGHEEDCCBCCAECAGBDFBCHGHHDHADGGGCCFFAGBGFDGACBHCBDAEDBEDAGDHCDGCEGFGCEGDADDCHBGHBAHBEGBEFBFGBHDHGEBBDBBFCCCDEBDFBDBBGFBGFBGFBGFHDBCCCEBCGDCED,False +515,26.0,15.0,26.0,29.0,17.0,18.0,23.0,22.0,GFHDAEAAEGAEGCEDCDDCAHCABBAEBECGEBHHGAADFECFBCFECEDGDDCDCGDBDFGCGHDAHFADDAHCADDGDFGDEAAGAFDHGCHDCBDCGCBGCBFABGAHHBHDFHDFDDGDCFFAHBEHECCFCBACHACEGCEHHBHFGHCGDAGDAGECBFHAAGFFDEAH,False +516,12.0,12.0,20.0,17.0,22.0,17.0,13.0,11.0,EEBEADDAFDADAHHEEBGEBFFBEBCCDFCEFCEFCEFCABEFHEFCEFGFCGCGHCHDCGFBECACAGDAHDGGDHFDHADEADBFHBFABDHECFDCHCEGGDCDDCGBEAFEBECGECGE,False +517,17.0,18.0,11.0,13.0,13.0,9.0,14.0,20.0,BEFHACHEDBAAHAHHAGBAGCGGHAADEHDEHBBHGEHAEHGEDGEBCEBCHAAHBCHADHCDBGFBGHAABBFFFCCFACBGDBGDBFDCFDCBEHFHHEGBADEDHEGGABD,False +518,20.0,13.0,17.0,15.0,17.0,19.0,27.0,13.0,CFECBCGACDECDHCHAGGAGGAGGAGEAGHBGFFGHHDEHDHDDGAAGDDGDHBEFDAGBABEECEAABAAFAGFGDFCDCEFGECBCGGEGHEGHBGEFHFFDCCAFGAFEAEEFCFACFGBDCBCAHGBEGFDFHBFB,False +519,4.0,10.0,8.0,8.0,7.0,6.0,3.0,5.0,EABADFAHCBFGDFCDCCBACBEFDGBHGBHFEHFECEDHBCCBEDBEDBD,False +520,21.0,21.0,12.0,9.0,4.0,4.0,12.0,8.0,FAACBBBAABGAFADBABBDBBABHACGACBABBHHCECAACAHGDHGABCBDABAGBDGDAEDGCDGCABFEHEAHFBHGADGCCGBCGB,True +521,7.0,6.0,5.0,6.0,9.0,6.0,4.0,9.0,HDFFDAFDAFBFEAGABCHCHHBFHBGEBHEHHEHEDAECEEGACDECDBGA,False +522,7.0,13.0,6.0,12.0,9.0,15.0,17.0,9.0,FEHCDBCDGGDGGDHFBHAEFDEFDFGEAABAFBHCBEFBACDGBDGHHBFGDFEDEEGGBGGBHGFGFEGHCFBFFBGFGHBADCAD,False +523,13.0,18.0,26.0,23.0,24.0,18.0,20.0,22.0,HDCHAFHBBHAEFFCCGDFGAFCFDBHGFGEFBEGCEHDHHEGCEGEDBDDBGAFHCFHCAECHBFHADHFDHECFBCBBEEDGBCGEEEDGHFGECCECDACDGFBCACCDDGDDEBDGBDGAACABCABCFBEFEDHEDHDGHEFHECDECGAHGEHGCCBH,False +524,23.0,26.0,27.0,25.0,18.0,14.0,25.0,20.0,AHEABADDECBHGBEGDCHHCEDCECAFCACEFEEGGDGGDGEDGCFBAEAHFGDFCACHEBDDBADBADBDDACFAFAGCBBHBGGFDBFDGAAGAHGDHFBEEDCCDCBACHHCHECFDDHABAACAAGHHGBGGBGFBGFHDCBDCBHBHHCDFCDEBGHBGACGCCGECBBBEE,False +525,9.0,5.0,7.0,9.0,10.0,14.0,16.0,12.0,GDEGFEHFGFFECEBCBHHAHAGHAGDFCDHBDAFFFGFGGHBDHFDCFDCDGFEGEGCEGAGAAHAGEGHEHFEHFGCDBA,False +526,21.0,20.0,28.0,24.0,24.0,22.0,22.0,28.0,FBFFHFFDFEBCDDDFBEABCGECGECFHFFCFDAACAAHAHCDHGHHFHCBHBDHGDGDHAHCDHGABAABGCGAAFBGFCDFCDFCABEHDEAGHABHEBAEFHCAEABHGHHACFEGEEFEEGDFGDCCDCEDHHGBHGEHGECGDHDDAFCEBDHBGGECBDCBGCAGCEBCECEBCEHCDHEDF,False +527,20.0,11.0,8.0,13.0,17.0,8.0,13.0,14.0,DDHGDHCDHDDHEGFEDECAEHFFHAABEGBEHBCAGADGACFACECDEAHGABBCEAAEAGFABAABAHGFHEEGGDCEBAFGFHGAEDHEDHEABEABDHBG,False +528,9.0,13.0,8.0,10.0,8.0,6.0,9.0,7.0,ECDBCHEGHFFBEDBGDBHDBHDFHFEBBCDFDACACCBEHBAGBAGFDGADGACHABDAEABGGEGCEB,False +529,2.0,5.0,6.0,3.0,4.0,6.0,5.0,4.0,FCBFCBFCDCHDEHBFGFFGAEAHEGBCGCHDEBG,False +530,5.0,3.0,3.0,2.0,4.0,2.0,5.0,5.0,AFBAEGACGFGHCEHEBGEHGHDAHDACB,False +531,14.0,18.0,15.0,23.0,16.0,17.0,15.0,32.0,HBAHEDHGDHCDHDEHDEHDEHDHFAGADFEEHBBDFHDAEDEEHHHBHDFHDFHCFCFECABGGBEGCEBFBBDBDCCHCAACFACFHEEHCHHDHGFHGFHDCDDBEBGHAFFCGBAEBAHBGHAGFBGAHCFFBDGDCBDHGHGDHA,False +532,8.0,6.0,17.0,12.0,9.0,14.0,14.0,11.0,DEGAFHFDCCDGCHHBHCFDCFDCEGGFHHCAGEGBFGBDGDAGHCGCCGDCHDGEDBEFFCFDCGHCEHEGHACCAFAFFDFFAEBAEBC,False +533,15.0,11.0,12.0,12.0,16.0,22.0,21.0,18.0,GAAFFACGGFHDCBDFBAFBAGEAFEBFGGFDDEGFEACHFFBDFGEGDFFAHFHHAHHEHHFHFABECBDHHDCHDGGDGGEFGEHACGACGECEECEEBDBHDHHFHEFGGCABCAFEFCGGGBA,False +534,6.0,6.0,12.0,13.0,5.0,12.0,12.0,8.0,HDGAGHFGHFCHABHFEHFACCCBCEGCGDCDEADCFDHGDGFDGFBGCDCHFFEGFAFDDFDDGADCBECBGB,False +535,22.0,16.0,25.0,15.0,17.0,33.0,16.0,16.0,FBFFEECEEDFEFEEBGGDGFEAAEFCGFDGHDGDEGAAAHACFECDACDCHFCHFAFFAFEGFBDFECHHBACBCCACDAGFGDFEDFCCFHCBCCFACAAGADGHEFFCBFHDFCDHBHGECAFFGBGBFGAAAFBHFHHFEBFCDFCBACBHCBHAB,False +536,20.0,17.0,26.0,15.0,22.0,17.0,17.0,16.0,BHHBAFEEFAEFAEDBBDFEEBCEHHAAHAGBDGBHBECECCBFFAFEACEGCEFEECDDDGBDABEEBEHAAHCFCCEACDAHAGHBGFACFHCGHCFCCBCFGHDHCDHCDGCEAHGAFBADGGFCBFCGDCGCCFADECDGGEGAEB,False +537,13.0,10.0,5.0,5.0,10.0,8.0,9.0,7.0,EADEDEAAGAEEBGGHHBFFBFEBFBBDEAHEABCAHCAEFAGDAEDBFFGFAGAHGCHGHABCGBC,False +538,10.0,10.0,16.0,12.0,12.0,14.0,12.0,13.0,DFCGBCDFCDGBDCFCFFCFDAHDCBECEEBEDBEHECFECGAHGDHEAHAHHGFHGDHFFCGGCEGFGGCGCAAHHAEHCBDFBDEBAFADFAEBCBH,False +539,2.0,2.0,4.0,2.0,0.0,2.0,1.0,0.0,ACCFCAFCBDDBG,True +540,3.0,8.0,6.0,4.0,2.0,10.0,5.0,6.0,FGBFBFDBFDBFHFFGCEAFHCCBFCBECFABGDGHDGHBHHAC,True +541,4.0,4.0,3.0,5.0,9.0,9.0,6.0,7.0,HHFDFBDFAFFAEFEHGEHGEBGEAHFDEBCGHGGFEAFDDHCEBCE,False +542,1.0,6.0,4.0,1.0,3.0,1.0,2.0,0.0,EGEEDACCFCCBBBBBGB,True +543,11.0,8.0,11.0,8.0,8.0,12.0,13.0,10.0,CGFCHFHAFHGCGCCHCGHGACBDDBCDFADFADFBBEDAEGACFAHHGBHGDAEFGEAGEABHBGFBAEEGEHDFCGFCF,False +544,1.0,2.0,1.0,1.0,0.0,0.0,2.0,3.0,GDAHBCHBGH,True +545,20.0,18.0,24.0,26.0,24.0,22.0,18.0,33.0,CBHDDADAHFAEFCEHCEHEBHCBGCHAAHAFHFFEAFDAFBEEGHAGDDDACDHCEECEGDEGDEGBADBEDBAACEECHFBFCHFHHEEDBHHAEFCCHHFDBFDHCHHAHHAHGCHCCGFCGBGGFGDFBHFDGGDCEDADDADCFBCHBCBFHEHBEGAFHCCBEFFHDHGAEGDBGDEHD,False +546,29.0,23.0,21.0,19.0,21.0,27.0,25.0,20.0,BHEADFCDFGBFAFFACEAGFABFACFACFHEBHBFHDFGEGCEHCGDCDFCACAGDEBDEFAEFGEGGHCEHEAFEGECAAGAAEFFFFDFGGGCDGBGEBGHBGEBADFGCAGEADDBDDBACCCBDBBHAAABAHBACGECDDHGHHGBFEACHBFHEDCFDAHEAGCBGBAHFAHFBHFBH,False +547,8.0,14.0,13.0,15.0,21.0,12.0,10.0,20.0,CHCHGGHDDADDEGDBGFHCBECDEFBGHEECEGCFAEHHEHHCHHCHFFAAEDAHDEGBEHAAGBEHDEDBCFFEFCEFCHHEHBEHBEHEDDEGDGABCEBDBBCBFFBDF,False +548,5.0,4.0,1.0,2.0,4.0,2.0,2.0,2.0,ACBADGEEGEEBAFBFHDAHBA,True +549,14.0,13.0,9.0,11.0,17.0,24.0,19.0,14.0,EHAEHGEDBEDCEGGEHFBFBBGBGGFHAFHBFEACBACEADGFEACGFEGFADHGDAGCBGHGCFEBAHBGHAHADDAFDHGGHGFFGFFCFFEAFEGEEFFHFDBBDCBEHFFDFAEFC,False +550,8.0,20.0,16.0,21.0,30.0,20.0,19.0,15.0,FHEAEECEEGBBBBBHBBDDCDDCDBCBFFEGFBCEHEEHEEBEEHFDCEECGBBGAGAHCAFCAFGDEGCEFEHCDBEDHGCGFFGEEGEECBEFEHFHCDHBDFDDGGDHEFHGDECDEHEGACFAFFGFBGBGAFGDDDDDBEFBH,False +551,8.0,3.0,13.0,5.0,6.0,13.0,5.0,7.0,BDFEDFGCFCHFCGCAFFAFFHFGCAGHAEHCBCCEHCHDCADCFFAEFCCDHGEFAEBA,True +552,10.0,10.0,17.0,16.0,16.0,11.0,4.0,13.0,CABEDBDDCCDFHBACBAEEDFGACHECHECEDHDDBDDHAHCBHEFHEFHEDDGACAECHEFBEFDEDDHCBHCHFGBFEBDCFACEGCAACFCEF,False +553,29.0,25.0,19.0,15.0,29.0,33.0,22.0,26.0,EABECBEDDEFBHACGBHHEHFFAFFEDBAGFCHDGEDEHDGDDCADHAFFABHCFEEBAECAECHHHACCAEABEABCCECFECEGCHGCFFBFFBEFDGGAGAECHEHHDHHABDEHAEFFEAFAFFAGFHGEAGFFGFAACAEFFEGBAABFGBEGDFHDFHEFBBHDHHGHBCABABBFBBGBGGEAGBFGCFH,False +554,19.0,13.0,14.0,11.0,11.0,13.0,12.0,8.0,ABGABGBBFEBEDGCDFCEAGEAGHAGFAGHACHCDHADCADFGDCDDAFEGFEDHHAGCGCFDEHBEFCFFCFEABGABFCHEBABBACADEAFBABACC,False +555,4.0,7.0,2.0,2.0,5.0,4.0,2.0,1.0,ABBABDFBHFBEFEGBAGEAEEFDCCB,True +556,33.0,24.0,13.0,22.0,28.0,22.0,18.0,30.0,EEFABBCDBADEGEHHHCAHGEHABDDBDAGAABDGBABBAGBEBHEFDEDCHDAEDBFHEAHFAHFABFCBEHBEHAEHCHHFEHBEHFEFFHAFHAGHEGDDHBCEDGAFGECHHDHFAEFAECAGAGCEGADDAEBABAAHHAHGAHFEEECAACGFCDFDDFAFEBBGHBGBAFBEHDFGDCGDFA,False +557,21.0,20.0,17.0,15.0,9.0,13.0,11.0,17.0,FFFCCBHDBHDBDDBDDHDCGFBAHBHCCDAADHAHHADGADCCHBCFECEACECCFDABDCEHEHHEBHDFFABAABAGBEGAHGACGCGGFBBHBAFBABAGHAFHFGCGDEFBBCABAAE,False +558,17.0,17.0,12.0,11.0,13.0,15.0,10.0,21.0,AACABFAEFAEGCEBAFBFHBDHEAHEBEEHDHHBHCBFGAFGFCACBFBDFADFCDBHHBHDACECHHDABGBBGFGHDACEBCEBCAFHDEBDCAAHHFHHFGHEGAEGHFGHD,False +559,14.0,31.0,29.0,20.0,24.0,28.0,19.0,25.0,CBHCBFCBGABHAFHAGDBEEHABFAEDGEDECFFCBFDFFDEAEHDDCECEHCBACBDFBCEECGGCGFCFHEABDABDGBDAHFHHGADGEFHDGHEFHEBBEBGCBFBBDCEGFFAHGBHAFFGFFHEFHCCHBBHFEHGBDDHCBCFBCFBCADCDBCGCCBBCBECGDCHDFHBGHFGFCEEHEE,False +560,11.0,11.0,9.0,9.0,7.0,8.0,12.0,11.0,FDCFDGECEACDHCFAFGAFAFECFCHECHABHGBHBBHBGEGGAGGAFDBHDCHDBEDGABEAGACHBHDBDABGHG,False +561,17.0,20.0,22.0,24.0,12.0,25.0,33.0,19.0,GFGGFCGFGDHGBCGHGHHGHCGHDGCGCDDCHGCFGFAHCHFDFCDEBDEBGFCEFCFFGAFCCGCHACBFDFGEEBBDDBECAFGAFGADGADGDDGADGFDEBDBBDBGCAGHGGDGGBBDFHCCDCEFABHHBHEEHBDHAFAGEAGDABFAHHAFBFGDCEBCBFFA,False +562,11.0,10.0,11.0,8.0,5.0,15.0,7.0,5.0,GBAGDDBFDHFDGFAACAACBBGFGEBGFFCFFCEFBEFBCBACFFCAHCAHEEDBAHFCFFCDDAGCAHDB,False +563,20.0,11.0,17.0,13.0,14.0,9.0,14.0,23.0,BAGDHGEHCAGCGEFAEFBCCHCCBDADHBDHADHCGHAGAFEAHHAHHACGCEACAHCDHBDGGDFEBFHHDHHCAHGAHFEEDGFDECDHHEHACFGHFECEGBBCAACAABDABEGBE,False +564,25.0,13.0,20.0,11.0,13.0,16.0,8.0,5.0,AAAAFFCFFBBFABDAGEAGAHGACCFEFGEGAEAACACEFCFFCDCHFBBCBCCADFBHFDCCBGABGCBABBDFACAAFGACACDEEDECDBDAEDAHDAECAECEEHF,False +565,28.0,15.0,20.0,25.0,16.0,15.0,18.0,16.0,AADAACACCACGGBEGAEGBEGFHCHCCEBCEBDBBDBCDAEDEBDABDFFHHEAADAHHGHGBDGCAGFADAADADFHEFHFGDEBDFCAFEHFBBFDHCDADDACDHFHAGCGDAGCABADCADEAGEGCHDDBDCAGFHGHCGAEFFECE,False +566,7.0,8.0,2.0,9.0,6.0,8.0,0.0,5.0,HEFHDFDDHDBEDBEFBDBBECBAFBFDAFHAFEDDBCEAAAFHA,True +567,12.0,8.0,8.0,9.0,5.0,12.0,6.0,5.0,DADDAGBGGBCHFGFDAFCACAEFADFGBFABCDDFEDFECHECDBAEAHCAHBACBFFAFFBGH,False +568,27.0,25.0,25.0,24.0,19.0,25.0,34.0,18.0,GGBDADGGGAGEFFECFEBGEADDADDAFHBBHBCFBCGGEGEDHDHBDFBACBGCFACBCGBEGHHGCAGHGBAFAHHBFHAFECHCABFGHCDHEFEFCEDCEGBGGDAGFFGFFGAFBEFEAFEGFDBFCAGCAGCABAHHHCEACBGEBDEAACCFGGFGDBGDCCDBEGBCDFADBAGBADDADHCDHCDGA,False +569,17.0,19.0,19.0,27.0,20.0,24.0,19.0,16.0,DCECCEHDBFDEDGEAGFGFBCHBCAGAHGFDAFDBHAGEADCHDCDGCBHCEFCHFCGFAADABFABFEECGFHHDHBDEBDBCFEEFEEAECGDBFCBDHBDEBDAFDAHCGDEBDEHDFADFDDFGAFEFCAFHDBEBBDGGACDBCHGFFGFGGEGH,False +570,14.0,23.0,26.0,22.0,21.0,32.0,13.0,35.0,DEACHFHFDHEHFCHFCEFBFHBECFECHDGEDFFDEFHFBCCACCHGDFCHFEHCAHCHHCEHEEHCHHCAHDDGFBHCBEAGGDBGFBEHBHFBADBFDAFGGGABHAGHABDFBFHCFDCFDHEHCEAAEGCBGDFCFFEFDBFBBFBCHBHDBEDHDDBAFFCFHAEHCEHCBHDBCDEGFH,False +571,12.0,18.0,32.0,29.0,10.0,22.0,15.0,20.0,DAHAAEGCCHHEBCEBHDDGDDFFCCCCCHCFHDDHDHADBEFBECBCDBCDFEDGHDHCECGACDAEGGDGDBFHCFDGDDGAEFDCFDAADAADHBCBBCGEDBBHCFHCABFDHFBFCBCCBCCHCFFDGCGGCHCBFDFFDFFCFHHBHGFCGD,False +572,19.0,12.0,16.0,19.0,24.0,11.0,17.0,21.0,AEAGEAEEBDEGDECBBDAHDAFECHEFHGFGGDEHDECGGCAEHEHHCBHDDHDEGCEGAHGFEGEEGEECFADFEDEGCCABAGBAHAHHAEHACACHAFHBCBBAEAFBHDDADDGDBFHGCHFCHCCGFDHDDBE,False +573,5.0,2.0,3.0,2.0,1.0,4.0,3.0,2.0,ACEFDDFABGAGGACFAHFCHB,True +574,17.0,18.0,22.0,17.0,4.0,9.0,12.0,14.0,CCBCGGAHDAEDBCFCCHCFACFAEDAHDAHGBGDFDDCACAAFBBDDBDBBFCBECADDACBFCBHCHHABCAHGBBGBADDACHAGHDGHDHBEHBGBGGCFDAGCCCFHC,False +575,13.0,19.0,23.0,32.0,16.0,20.0,25.0,19.0,GGDDGDDCHDBGDFDDHBBHGBHBFHCEAFEHFGFEGEGGDGDFCHFAEFBCFGHDGDEGDBHDAAGHDDADEBCEGCEFCEFEDBACHAHFDEFCGFGHBBBABDCBFCHDCFFCHDDGDDGECGEDAAHAADDAFDCGCHBCGBCEHDEGFFHBDCBDBGCCGCC,False +576,9.0,9.0,12.0,4.0,5.0,6.0,12.0,11.0,BHFCHFGHEGHBGEFHADCDCGGCFGCBDABAEBACGHEGFBGBAHCDHCGHAGEAHHCCFCBGABCA,False +577,6.0,7.0,11.0,9.0,9.0,12.0,13.0,8.0,EDDGBABEGCGACGECECCBCCHGEFDEFGGFGBCGDAGHGCHBFGBFDEFCFFAGFDHBDADFADFHHFHEEHC,False +578,0.0,1.0,2.0,1.0,0.0,2.0,4.0,0.0,GCGDCGFFGB,True +579,5.0,1.0,1.0,3.0,1.0,1.0,1.0,4.0,HGAHAACAAEHDFDDHB,True +580,23.0,6.0,7.0,14.0,17.0,10.0,20.0,6.0,EEAEEHDHGCBEABGFBGEACAADADGADHCGFGGEHGAGGDEAFEAGEDEAAAAAAEGCFGDFGDEGAEAFBAHBAGDFGDFECCECGDBAAGDEGHAFDDF,True +581,26.0,18.0,18.0,18.0,15.0,22.0,19.0,23.0,FFFAFECGECGHCGACGACAFFGHGEHADHFDHBDHCACGABGAFHHGAFGABDABAFBHEBAEAHFAGCAGCGFAEDGHFGAEBAEHDDHBDFAFBHDBFCHEHHGFDDBAEHAECAHGHECDFDDHHBFHBFCBADFFDCCDBCABGEBCEBDEGAC,False +582,21.0,17.0,16.0,25.0,18.0,9.0,13.0,8.0,GAHDCGBCBACDDBDGADCEDBFDAFDADEAEEBEHADFAHEGDBGFHGHCBAAHDEHEEACDACDECFEAHAGGAEGAEFADBGEBGCDDCFDABDCCAGBADBDFFDGDECDBCDCCEEBBEBBA,False +583,3.0,13.0,7.0,7.0,6.0,7.0,7.0,14.0,CGGBGGBGFBHBBHCAEBHEBHFFFDFADCDBFEBGCBCHHHDHHDBHEGDECBAHFDHBEHCH,False +584,19.0,16.0,23.0,16.0,22.0,21.0,12.0,29.0,CGHFFHFFHCFGDFDEECFDCDDABFAEAADFBEAECAEGAECHHCHAEHFECCHGCHGEGGEDHBABFAHEEBGEHHHBHHCDBCDBADCACABCBCCBHBGHDFHBFHCABGDCFCCADHAHHEHHEHFEABEGGAFDFEEFEAFCDDEHFBHCHF,False +585,5.0,14.0,11.0,11.0,4.0,5.0,12.0,10.0,DGDBCBFGBDAEHACCEHCDCCBHFBHFBHCAHGGGCGGBGCBEDBGBAGHFCHDCGDBHABEFBDDBDDHG,False +586,11.0,24.0,18.0,11.0,8.0,6.0,17.0,13.0,GBBGABCCDDEGDFGAHEAHCAEGBEGAEABEAHHCHBBHCBHCBGGGGGGBHCBCCBDDDCGGBEFFADFGBCABGBBDCBDBHABHBBHFBDFCHCBGDHACCCEC,False +587,14.0,18.0,17.0,13.0,15.0,17.0,25.0,21.0,ECCAFEAGBAGCGFCGHADHEBGCGGCBDCGABDHBEGBCGHHGFHGHHGHDGCACAEHBBBABGFHGFDGFDBDGBAHHGGBCEFCFHHFEHFEFFAFFAGFCHCHGABCHEFHCFEBDEBDACGAEGEEHBBDEDDGD,False +588,13.0,15.0,14.0,18.0,15.0,14.0,13.0,9.0,EFAHGBHGDHGDCADGDDEEEECFACDGDGHCCFCEDCBHFBGDBCDBCGFCGBCEDDEAFEAECAFCDFDDBHABHFEEBBHBACBADBGDEABFGFFADGAGFAEFEBH,False +589,12.0,8.0,10.0,3.0,6.0,15.0,8.0,10.0,FDAFCFFHFGHFGBFHAHAADACFCCBBCBBHADHACFAHBBCGGEBECHGAHEAEEAFFFCFFHGFCGAEG,False +590,17.0,15.0,7.0,14.0,11.0,14.0,9.0,6.0,HEAFCADCHBHAFEFFEDAAFBABCGDDFAAGDGDCBEBFEBDEBAEAEBAEBAFBGFBHFCGCHGHDGFAAFCADBDDBDDGFAGFABEDBE,False +591,10.0,3.0,10.0,5.0,10.0,14.0,7.0,11.0,CFGCFEAFHGFCGAHACGFEADCAECAEBEDGFDHFEHFEHBEHFECFAAFHAECDHGDBFHHFAHCCFG,False +592,19.0,16.0,12.0,22.0,13.0,29.0,15.0,13.0,GHBEBBFBGFCCFDDECDGGDFGAFABCHFAFFABBCHBAFGHFBEFDEFGEFGDDGDDACDBCEAFEACEDDFFAHEAEDDHHFFDFBGFHGDBFHECCCFBDEBAHFAEFAGFBGDHADAFDAFDAFHAFGAGCHDB,False +593,7.0,6.0,8.0,6.0,8.0,9.0,6.0,6.0,DCHBFDCFDGACEACBBCBGHAGHFEHFEHDEGAEAACGFBFCHFCAEDFEBEDGF,False +594,30.0,31.0,17.0,16.0,20.0,23.0,18.0,23.0,ECHGCHGBBGFBGABGCDGHFFBFABDADAFEAFEHGBAABEABHABHACFACBEFADDADFBCGHHABFEBEGBCGEHFEFEBGEHGDAFBHDAFBAHBAHFAFACGDCHDCHDGBEBHEFEAFEDHACEBCFBCHBFHBAACFCBAHGHDDEADHAECACGBBABAFBFEBGEHGD,False +595,9.0,14.0,16.0,12.0,7.0,14.0,15.0,6.0,FEGFGGFDBAGEFGEFCCHCBEFBCGACBACFCCBCAFCAGGFFCBHGBHDBADADHADGBDGBDEBCHFCFCCGBDGDHEDADDFEBGGCFB,False +596,26.0,34.0,20.0,24.0,21.0,26.0,22.0,25.0,FEEBEHGEHEFHEFEEACGABBDHDDHGCGFDACBGBHGFHDADCFGCGBDAHHCFHGFEEFEAHEBHGBAABDABFAHFHDDADDFDBGGBFHBAEBAEBAHBAFACFADADDAGGBBGBBCCACFFBDFHDFHDBCBCABAECDFGDGHHEECCAFDBDEFCEFGDBBHBBHGGHFBHEGGEBCABCFBCFCAHBA,False +597,16.0,18.0,17.0,23.0,22.0,17.0,16.0,28.0,EECBEAGEDFCFADAHFCHFCHECDBGDBHDCHAAHDDBDDCDHHFHBAHBEHDEHAFHAHHEEGEEGDEBDEDDHBEBGEHGEHCACFHBDBACHECEBCACCGCGGEHHDHBFGEABFDFFDGFAHCGHCFHBGHGDABDAFGBEGFDFBDEHFA,False +598,14.0,9.0,12.0,11.0,20.0,14.0,7.0,8.0,EEAFAGFHFFBEAGHBCFFFFDFFBAFCEGEEGDCGDCBAADAHFFHAGHACDECBEDBEAACDGCEACHDDADBECBECHEAHFDEEEEEEEBC,False +599,31.0,15.0,28.0,34.0,25.0,28.0,16.0,23.0,EADADBADCDDCGEGGEAFEFGBDDCFACDECFECFBCHAEHABGFCCAECDEDGCDGCDGEAHDBBDBACEAFBFEBEDBEBEEFGAAGADGDFFCEFAFAABDFHDFHDGCDGHDFCDFHEFAEGCFDAFDAFDEFHBCDAFEECHHDDHDCFFAHHHHCHADEADADBADBCGCCHFAFCEHHAFHAHHAEGACCCH,False +600,10.0,11.0,5.0,10.0,8.0,10.0,7.0,10.0,HBFHBHGFGEFGEFAAFAGFGEBBHBDGBHHAHCDHEHBEAFDDBBABDFDCFHEBCECCADGADFADAED,False +601,1.0,4.0,4.0,5.0,1.0,4.0,5.0,0.0,EGCDDCBDCFDFBGBDGCAGFBGF,True +602,4.0,2.0,2.0,6.0,6.0,0.0,2.0,3.0,EDEEBAEDHEAGEABCHDCDDADGH,True +603,22.0,28.0,15.0,26.0,22.0,27.0,16.0,24.0,EADBBCFGEFEAGAFEACAHCDBABGHBHAEDGGDCGFBBFHFCEFCEFEDAEGEHGABFHBFDBGDBABGGCGBCGBABHAFDDFBDFBGFHFCHFCHFHECHDFFDFABFDBHDFDCFDCABHABHEHADCDDCDHFEEDAEDFEBHHAFHGBHBBEEBDHDHEDABDABAEGEEHAF,False +604,21.0,11.0,14.0,19.0,11.0,12.0,18.0,29.0,GHHGHHAHADHAHCGBCGBDGBDHDFAABAEHFCDDAACAFHBHHDEBEGAGGEBGEHDEGFGGCHGDBDHHDAAAACFACFHBHEAAEHADHGCHGHDBCFHEFHEFECDDHFDCGDFGAFHAHHCHBCGDCAD,False +605,9.0,11.0,6.0,10.0,8.0,6.0,9.0,4.0,DCGDAGDABEBBEBGEBGDDGHAHHBCCECAHAFFAEDCEFFEDCBGBBGEGDFGDBAAFDAB,False +606,28.0,22.0,23.0,19.0,24.0,23.0,22.0,23.0,GHDEEDGFDEHCEBCEBAGAAGEGGEGABFHGFAGAHGDCCDHFBADBDDBCDBFHFDGEEGCEHFFHCCHAGHABEACCACDFEEFAFGEFBCGBCBFAFFBFFDGEEGBEHBHHDCACFHCACAABAABAECCDFHHFHBDAEFHEFEECGFBGCDGEHCBGDBAAAHCAHDEHDBHABAAG,False +607,13.0,16.0,14.0,14.0,17.0,12.0,10.0,10.0,BGHBGADGDDGCECBEDBECAECGECGECFACFBEEBEADEDHFAHAAHBFEBHDCFDGDBFFBEGCAFADDHCABDACDABDHGFFGEEBFEBABCEFEHCHHCB,False +608,9.0,17.0,16.0,8.0,12.0,15.0,18.0,16.0,BGGGDCHHBHGBEACEACEGCEHFHCBGBBGFBGFAHCDGCFFCFGCBGBBGBFGBFAHFBGFBABCEGCEADHHEHHCHFEGEDHDDCDABGHECCFCFFGBADEAEHFH,False +609,34.0,28.0,25.0,20.0,27.0,20.0,18.0,15.0,FHGFEGEBBEGBEGHFHDFDAAEAAEDCFDBFEFCDCDDGEAFEADBCCACCDFHHBCHFEDABBABBABHAFGACGEEEACCACDDCBFCDHBFGBAGCGFADEADGABFABAGEEEBHBFDBFEBGEBEBHCCDCAGCAECAECAFCHGEEBFEAGEDECAHHABABBABDFDAHCABCAGHAGA,False +610,27.0,20.0,29.0,19.0,16.0,20.0,23.0,16.0,EDGGDCDCCDCCFAHFACFEEAAGGAHFADGADAEDCEACDAGDAHDCHFAFFHCGHCGDEBAEBAFHADHCBFBBDAECAECACGGGGFFCDGBHGECFBABDABGECGEFBFCBHDBHAHGACBAHEACCACHBHEFCBDCGDBGCBGHGCBFCADEFBFFGABGCEF,False +611,22.0,21.0,24.0,24.0,11.0,17.0,21.0,18.0,CGCHDBGDBABGACGAEAACCDDCDGCDGFDEHBABFCHACHAFGDEBDEBDABHGBCFBCBAHBDFBHFCFECFECGAGEAEBDGCGGCHGDFGDFCFBHFAFGAGHHFBHDAADCAHCAGEABCCBDDEDDHCCAAHFHHDADDBGHCGBFFBEDG,False +612,15.0,15.0,16.0,7.0,8.0,15.0,11.0,10.0,BBGABCABCFCHFCBCAGHHFHFFBFAAFAGBAGDEFFCFECACDACAFCABEEGCEGCAGDBCHBDDFDDFAFHACBGBHGBHCEEEGHCGFBHBA,False +613,1.0,6.0,10.0,13.0,4.0,6.0,8.0,9.0,GCDDCDCAHCHEDFDCCDGGDBHDCHDBHCGGFGCFGHFGFFHHCBBEEBDEDDBDH,True +614,10.0,16.0,11.0,12.0,14.0,10.0,10.0,10.0,DECEGBDAEDAEGGGHGAAEBAEHDGHGEBCHBCHBFEBCBFCBAHEDFEDFGAFDCFBCFBDFBCHCCHDHBDBBABFDGEEEDCEGAHBAF,False +615,1.0,1.0,2.0,4.0,6.0,3.0,0.0,3.0,HDEHFEDCEABEHFEDDECF,True +616,10.0,6.0,9.0,12.0,6.0,14.0,6.0,4.0,DFHDFBBECCFCCFBCDGAFFABDAGEADBDDACECFECGAAGHFHFFHFFDGDAFDEFDEBDAAGC,True +617,6.0,1.0,4.0,3.0,5.0,2.0,0.0,4.0,BDEHDAAFACHECHECDEFHCAAEA,True +618,22.0,16.0,36.0,14.0,21.0,16.0,20.0,16.0,BBGEBEHHHHHACECCGBEDBCDHHAHDCHDCECAFHAFDAFCAECGCCACCGFFDEGACGCCGCEGCGGEGACGACBDGGDEAEBAEGFECAECFBGECAEFFHBCCBCHEFADFDECDBCBFDHDECDGAABHCFGCAGCFGABEABCABCECCFFAHH,False +619,26.0,17.0,24.0,18.0,27.0,15.0,23.0,23.0,ADFABEBGDCGDEAEHBHDBCGECBECEEGAHGCCECGFCAFCHECFACBAHBACBAEBDEHFEDDEHGHHGHHGAHGAHFADAAGEAEDAFAADADHEGHEGHGBHDBCEECGFCHEBHBBFAHDCGAEGEEGECGHCFCFGCDDFDCBCFEAAAFEAHGBGDCDBEFCHAG,False +620,7.0,2.0,1.0,9.0,6.0,2.0,5.0,5.0,GBEGBDDHGCFGDGHEEHDEFAADAAHAAEAHEDDDD,True +621,16.0,26.0,22.0,21.0,29.0,29.0,17.0,19.0,EAFBDDEEGGEGGEGDFBBFADADCGDCBCCHCDDEDFEDFADFEDFGBFHBECAHCDBCGFCFECEEHAFHAFCGFBEHGFHEEHFEBCGBGGHABFGDAGCABFDBFDFFDEFBBBDHBEECFEHEACBFBDFHAHHEHHEHCCHGBAEBDCCEEFBBFAFCBDCBFBAFEACEGHE,False +622,7.0,7.0,8.0,11.0,8.0,4.0,10.0,8.0,DAGDCGDHGDACDBCFHHEGDEDEFHCBHEBHFDHEHBCGGEGBCGDCFDGEDCAABAABEAG,False +623,28.0,16.0,21.0,17.0,19.0,16.0,21.0,15.0,DEHGEHCAACGFGGBEFBEGGGBGFADAEDADDCCHGGACAACEBDGFCBDAAFBCCCCCAEEEECHDCEDAEFAHFABFACFGHHBEGCEFBAHCDHDBCEBCEAHAAHAABEDGECGFAGFABFAHFAHEAHDHBFCBDDAFDAGBGGDGG,False +624,3.0,1.0,2.0,2.0,0.0,4.0,3.0,0.0,GAAFDAFGGFCDFCB,True +625,2.0,3.0,2.0,8.0,3.0,1.0,2.0,1.0,DHDDBDABEGDDGBFAEDCEDC,True +626,25.0,22.0,16.0,18.0,24.0,24.0,24.0,13.0,EBGFHAFDBGEBGEFGEDHADHADAAFCAFCHGEAGACBDGBFBDFEDGEHGEHGDHGCFCEFBEACEBHGFHEBHEGFEBAECFBABCACCABAEDEDGEGCABEEDGEAGAAGCFFDBCGHAGCAFFGFDAFHFFGEBBBHBDAGDABDBDGBAFEDFCAFCEF,False +627,29.0,21.0,28.0,24.0,31.0,21.0,20.0,20.0,FAHFBGFACEAEHGHHCFHGAGFFCCDDBDGBDGBDBHEBHECCEHCAFEGEHGEHGEGGBCABADDACDEEBCHCGAAEAFCABCEBDABEABCAECAEAHHFCFGDFHDFHBCECEDCDFCDACEFBEDBFDBEBEHHECCEDAFDGFDHEEHEGHCDDADAAEGAFADCGCGFEGFEABACFAEBACBGDA,False +628,12.0,14.0,20.0,9.0,14.0,5.0,7.0,10.0,BAHEECEFDEACFADDABAECEHFDHCCCACBAEDHEBHEBHFHCFCCGCDACAADGEGCCGCGBCBBCGBCEBEHBEDCADBEGBCABHH,False +629,5.0,5.0,7.0,3.0,4.0,2.0,2.0,2.0,EFAECAECHGHFCDABDBCDBCBCABCGEA,True +630,23.0,22.0,17.0,29.0,22.0,31.0,12.0,12.0,CCDECDBBHBBHBGFACDAEHBFBGFCCEHGEHEECEFDDFDDBEDBAFEHBDHBFFFFFFFAFFAFHDFAEFACFCCGAFAAFGADGADFFEBHEGEAAFBDGBDADDAGEACECCFBBEEGGEBDBBCAADFEDCADFFDFAEFBHDDDDBCCBFGDAEHEHDDAD,False +631,27.0,22.0,17.0,34.0,24.0,29.0,22.0,24.0,FFDCFDCHHBFADFAGECGECGBFBAFBGGACBFCBACHEFEEFBEFEEFCBAEECEHAEGAEFACFADFDBFBHHDHAFHADDGHHEHDDGEBEEGFFDDGEDGADGBDHFDHFBHFHAABAADHAEHBHGDFGEAADDFDCCDCDDFBAGCFDCGDHBDHEAFDGBEGBADEFGCDBADGADHEHGFHBDHADGACB,False +632,14.0,22.0,9.0,14.0,13.0,13.0,20.0,23.0,BCFBCFAHGDHGAHEDGEBBCBHEGHDDDBAGBAGCECBBGBDABAGHDGHEFFBHEEEEHDEBDEFAAFAHGDGCDAFHAHGADGAGCDDHHFHGFHEBHBGHBFBBFGBFHHFAHCHHBECBGBGG,False +633,24.0,22.0,20.0,25.0,23.0,16.0,19.0,23.0,DBBDHHDHHEFEEFGABGFEGADFACHGEHGEHAFFAHECCEACEBBHBEFADDDDGGHGGHAABCFDCFBGFAECDGBDABEAFECFEHBAHFDBFDBDEFCBCCGDEACAAGBBGBDEAEAAGAAHBGHACCAECGCCDCGDEHAHGBDDEDDHDBHDHHFCHDBHEBCE,False +634,17.0,21.0,22.0,24.0,23.0,23.0,16.0,18.0,CBHDBHCEHCHBGDBECHEHFBCFDFBDFCGFCACCACCGDEAFGADEADFCDFBAHAGHGEBDDBDEBDHBGBDAEDBEDCEFCEFHBHCGDAHAAEDEEGGECBEHDGDBGEHFEFGEFBFFAFFCCFECEDHEGCAGBACFDGFDHFBABHADFBEFHADC,False +635,16.0,6.0,8.0,5.0,5.0,8.0,8.0,4.0,FFABFACAAFAAHAFHCEACEABFCDGCFACABGGDGCABAEBGEAGBAGHACHFEDDDG,False +636,0.0,0.0,0.0,2.0,3.0,1.0,3.0,2.0,EHGEHDEDGFG,True +637,9.0,16.0,10.0,10.0,13.0,11.0,8.0,12.0,FEDBEDBEBBEFBEHBFBFCBEGBAGBHGHDBDDEGBECEFHDDHCFHGBHEBCGBEFAACBDEFCGFAAHAHHFFAADAHDCHGCECC,False +638,12.0,9.0,9.0,12.0,9.0,15.0,8.0,15.0,EFGFDCDAGDHFCBFEAFHACHBGADEEHEFGEDHFDGDDGAECCFHBFHBCACHACHACFAFBGDBGDBHBHHBHDEHDAAAEFFFHF,False +639,14.0,20.0,11.0,14.0,9.0,16.0,14.0,14.0,BFBHEBAEDADCGDAGDAFBHCBACBAEAHHCGBCGFCGAABFCBFGADBFFFDFCDFEAGGDHDDEFFHGHHGHHEFEBHBBGDBCHBEHBEFBCABDGGDCGAFHBFABD,False +640,8.0,6.0,17.0,2.0,13.0,12.0,17.0,7.0,HCFFGFCHCCACAADFGBFCFFCGFCABGBEABGCEGCEGCACCFGDGECGHCAEGBEGEEGHBGEAFEHFEHGHGEECCGF,True +641,14.0,17.0,15.0,14.0,30.0,13.0,21.0,15.0,BBGEDAHDBBEHBCBEHAEGAFGECGACGADAFGFFGFEGDBCCBFCHDHABHEBGEDADDHEGHBBHEGCGCHEEHEEHGEHACACCEGCGGEDGFGAFDBFCAFBAFEEEHGEGFEBEEBHEFDECEEDEBGEDCAD,False +642,26.0,25.0,28.0,26.0,13.0,16.0,19.0,13.0,EBDECDGCAACBAHFACDCCBCDDHDFBDBDAHGAHGBHGBCFDEADGADGHFGBAHBCCDHBDFDFHAEEFDCGGCFCAFGACGCCFADBAEBGBGGBFGDFBFCAACAACECBBHBBGABGFCAHCDFGDCCEBCDACHBCAAEDEEDFEHEDABDACDAGDBB,False +643,14.0,19.0,17.0,9.0,14.0,22.0,18.0,8.0,GCCFBFFBEABEHDEBDGBDFAHFBHCBDEBDGBDHHFFGAFGCGHCACFBGGAGGFEGFCAFCADGGCFECECGFAGFAGACHAFHDCBBCBFABFEBCCBGFEAECDBBFFBAEEEEFG,False +644,15.0,27.0,16.0,22.0,21.0,27.0,27.0,18.0,EDFEFFDFBDGBEGBHCFHCFHFAHFGFFEHGEBGEBGABGCGEBGFFHADEDGEBFABGAEFEGFGGAGFDHFBHCBADAEFBCFCCHDFBEADEDBBBGDBDCACCFCEFDDFBHHAGHGGBGBEGCFCBFEGDAGDEHCEHEBHEBADHDHHDGCDGBAFBDCGAFGDBB,False +645,14.0,11.0,10.0,13.0,16.0,12.0,10.0,15.0,EEHEEHGEFGEDEDBGCBHHFHBFDBEEBEBAHBDGACGADGHEHHECDFHDFDFAEFACFBEBHEHAGDCHDCDGCFAAFAAGCDGCAAAHHFBCDBAFE,False +646,3.0,5.0,2.0,4.0,7.0,6.0,2.0,5.0,EEDEFDFHDFHGFHCBHFBEEEABHABFDBGCEA,True +647,17.0,19.0,20.0,19.0,12.0,18.0,17.0,19.0,HCFBAFBDFDHBCACEAFHCGGCAHBHHBHFECADGBGCDACAECGDCFDFEHBABGADGACGBEFHGFBDBCCBCFBDFADFGGFEGFHGFEBDDBDDADBFGCFGHECHCHHGGBECECCEBDEDHADHADHAFHAHAB,False +648,10.0,10.0,6.0,7.0,5.0,10.0,7.0,10.0,CHGDHGHAECAEAGBCGCEDFBGFCGBCFBHAEAFHDFBEHBGFAFFDDABDABDFBHFHHABHA,False +649,23.0,19.0,18.0,23.0,11.0,22.0,22.0,16.0,DFGDAGAEGAEDABBFDGADBHHAEGECAFDAEDACGBCGDCGHCGBCHEGACCAFDBFHBGGGDBGBFCBEGFHAHHCEDAEDBBAFAFFAFGAHCHCCDCCGBDEFHFFDBFBCFDCDDAAAGDEBDBBHBFHGFHFFHFAHGDGGDACDAF,False +650,4.0,5.0,4.0,4.0,6.0,3.0,2.0,5.0,DDHGDFGEFAECAFCDBCHEEAEEHHBACBHBB,False +651,29.0,15.0,14.0,25.0,15.0,16.0,23.0,19.0,GAFBABHAGGACGAGGAGHABDGFCGDEGEFDFACFBDAHAAHCGECDHFEHCDDEDDECGFDDFEDADAFDBFDBEGHFBAGBADBCDGAFFCEDEHAAHAACGAGDFDDFDAADCAFHBEHGEHGCGEBBHHBCDBCDHEBAEGGHGHHAAHAA,False +652,17.0,19.0,21.0,19.0,20.0,33.0,24.0,19.0,EBHGBHEFHAFCFFEAFEADEBHCBFCEFDEFHBGHGFDGDAHEGFEABBBBFBBFBBFAFEBDHBCBCGFEHACDCFDBGHGEFGACCFFFFDADGFDCFGEGHHGEHFFHEFHCFAGFBGCCGDCDDCGECGHAHEAGEDBCDEHDGHFGFCCDAAFAAFGAFDCGECGD,False +653,4.0,2.0,1.0,5.0,5.0,3.0,4.0,8.0,GBFEDEDGEDEADHGHHGHHDBHAHEFHCFAA,True +654,20.0,23.0,22.0,29.0,18.0,18.0,13.0,18.0,EDEBAEGHHFAHFBDDBGFBGDDABDABDADCCBBCEHGFCGFCDEHDFDGHDCBDHFDCBHBFHECCADGHGGEGBCBACHAEGEEFDEHDCHBEHFDBFCEACFAEDAFBGDBDDBDDBFDCFDCHDAACAABACGFCACDHHAFBAFBHEDCEBEEAC,False +655,7.0,8.0,11.0,11.0,11.0,5.0,11.0,11.0,CHBCHDCHBAHBCGDEGDACDEBAAAFBEFHFBGFEDEEAEEGDGGDGHDAHDHBEEGDECCBHCGCCGHCFHDG,False +656,23.0,22.0,23.0,10.0,19.0,19.0,24.0,14.0,FCGFCGAAEBHECHECHCGABAAFFEHBAHBCBBDEBEFDFADFGDFACFAFAHFBCEACECCDGBFEBFCCCCEGAAHAGEBGABCFBAAGFDFCEABEABECDGCGAHGHCCHBAFBHEEHCGBFGBAHBGGEGGEDBEDBDFGGGGGGACH,False +657,17.0,18.0,13.0,17.0,9.0,17.0,17.0,24.0,BDHBDGBFEBCHBDFBDHBAHBHHAAGABHACFFHHBBDDHHDHGFCFFCGHHBAHADGFDCFHCHCCBDFFGAFGAEEAGEHHBGFFGFAGHADHDCBDEFDECGAGADCAGCHGEHBEHFDABDGBCGAE,False +658,8.0,8.0,5.0,2.0,2.0,4.0,5.0,8.0,CEGBBGBHCFHBHBBABGEBHHGCFAAHADHAHGACFACFAD,True +659,34.0,21.0,21.0,17.0,21.0,20.0,30.0,25.0,HAFHDCDEGEEGAAGBGCBEAGEBGEAHCAHEAHCAHAAHFBHECECABCAHGGFGHHGEHDADFACFACFCGFCGFBBFAAHAAHBFFDAFDGFCAEAGFAEDBGBCEEFFFDEAGGADGCDFHGGHBCABCABCABHDGDGGEGGEGHEAHBDGBHHBCHDFAECGDBHAGHADABBACEFHBDEGC,False +660,14.0,30.0,12.0,19.0,8.0,11.0,20.0,13.0,DEBHHDCGGHGCHBFBFGBFDDFDDGDGBDBBABHDBHACECCACEABBAEBDBBGGGCGDAHCADCABHEFHBFDCDCGGFBGDBDBBGGBCGBEBBEBBHHBHFFHFAADGBBGBGADDFEAAGA,False +661,11.0,26.0,15.0,26.0,16.0,14.0,18.0,26.0,FEBHBBCBDCEDFABGAGEABBHBGCDGFDEBBEBBDBEGBEDDHHDHFBHEBEEGAHHDHHCBHCAHDHCAACEGBEGBDGBHBHDFHDHDFHECHCHEAHBGCFCFHDDHDDFDDAGEGGCCGDFGFAGFGDBBBHBDHFDACDCHFGDE,False +662,5.0,2.0,4.0,1.0,4.0,3.0,0.0,4.0,HCDFCFHCACAEEAEFBHABHAE,True +663,14.0,22.0,18.0,13.0,14.0,22.0,18.0,29.0,DHBHHBGHGDDFFFCBHCBFCHGCGGHHHHABCCBAFAEGBBDBFCFECFADFHBCHADBADGHDGCDACFHBFGFFBFGCFAAEACHAFHEEEEHGEHAEBGBGGBFCBFBGGBGAHDHHBECEHCHBFECFHAFHDCHDEHDEHGFHB,False +664,22.0,13.0,19.0,20.0,21.0,19.0,24.0,26.0,AACFEGGECAHDGHDGDBEHBGDGGCBEAGEFEAGBGGBFFBGGGGDCEEAAFFAHEBFEFACFECEABEFHGFHDAHCBHCFGDFHDAHGEHEAHEAGCCCHDAHFCEFCDCAFCGCHFCHGCHGCBGFBGHHDAHEAHDHHDHEEADEFDHADADDHDBADB,False +665,19.0,16.0,20.0,18.0,23.0,17.0,22.0,24.0,DAACFCEFCEHBFHAEHDBHBHABHABHAHCCGGCGCEDBDHBACCCCCAEDHEACEHEDGECGEFGCGDEFHCAHADFDEEDBECEACDGEDGFHFAEFAGBHHAHHDHAGBBFCGFEGHBHFDEFDHFHHABGABGEDGEDGEGGBCEBGDFGFFGA,False +666,21.0,15.0,10.0,14.0,9.0,13.0,18.0,9.0,ACFGBACCACCADCDGADGADGHBABGDFEDEGAGFADADDBEABDABEABAFBAFBGFGGACGBFEBFEHFHGACGCFEDGBGABCEHFGBAGFEDADBAFHHGHHDH,False +667,8.0,7.0,10.0,12.0,11.0,15.0,18.0,9.0,FAGEGGDGEAGDFCFFHBFDBGDFGBAGHCGFCDBCGBDFHGFHEACECCECAEFGCFGHFEDGHGBHFCHAEDAEDGDFGFGEBEDHAD,False +668,10.0,9.0,8.0,13.0,5.0,7.0,10.0,7.0,GFDGECCECCFHAGBGDBDFADGEDAADAADAADCGBGHBHBDHFGHFAHFACDEHBEBDDCGGCDFBB,False +669,7.0,12.0,7.0,12.0,9.0,2.0,15.0,14.0,HBGHAGHEGBCADABEEHFCCGHGGEGGCDGCHGEDGDBADBHDBGEAGAACEDDFBHBBHBDHBDHGCHGHDEEBHD,True +670,0.0,5.0,2.0,3.0,7.0,4.0,3.0,4.0,FGCFHFEDBHBBHFBGEBEEDEEGEHCD,True +671,5.0,12.0,12.0,3.0,8.0,4.0,5.0,4.0,BBCBBAECHCGHCHFCFCCBDBECBEBFEBCGHCEFGGBAGEAEEACCBDABD,True +672,11.0,18.0,12.0,10.0,18.0,18.0,25.0,17.0,AGBBGFGCFCEFCBHCADEBHCHDEBGGGGGAGGCGFHFBHDBFFAFHAEHFEFFAGBEDHHHHBBCFHAFCGCCBEHBEHGDBFEAGEHGEAGEAGEGDBGDCGDGGDFHEFEBBCBAGBEDHEFGEF,False +673,9.0,13.0,14.0,18.0,14.0,11.0,8.0,15.0,CGDBHCCHGBFGAFEEHEHCEHCACCADCDDCGBCDBHDHCBHEHABHEEGDFHDGACBAGDFEDFEDECDBDHFEHBEFFEBCEBDABAAGFHFDDFDDHB,False +674,8.0,13.0,7.0,9.0,11.0,13.0,8.0,11.0,GHHFHFCGFBEFDEDDBFDBAHFHHFCHEDGEHGCBDBHHAEGAEAAEBAGBAEFCFGCFAHBGEFECBCBBDBBDEFDF,False +675,1.0,9.0,5.0,1.0,4.0,4.0,4.0,4.0,BECBCFDGHHBEBBFBBFBCFBHGAHGCEECG,True +676,7.0,7.0,1.0,4.0,6.0,8.0,6.0,3.0,ECHEDFEAHHDFABGEBEABEDGFAGBAFBAFGFGGFABFDB,False +677,14.0,18.0,19.0,11.0,14.0,16.0,16.0,25.0,EEHFECBGCECHDBHGHHGHHGABBDFBDFBAFHAGDABCABFHHABGAEGDBHHGHFFHDFEDFHFGACBCCGCAAFFAHACDGCDBCHBFGBHEFHAFCCEBBDHCHFAHEGHEGCEHCECCHGEGBECBD,False +678,9.0,12.0,6.0,10.0,11.0,11.0,13.0,11.0,CDEAGGDGGCGBCGBAGBGEBDCAFGHFGBFEHEEACFAGFDEFGBHHFHHEHFCGDADHHDHEDAADFBFBBFBEEHEABBD,False +679,27.0,20.0,25.0,20.0,31.0,18.0,23.0,23.0,EFHEDHDDBECBDAFEEFEEAADGGCGEBGADEECEEFEECAFCGEGGBFCBFABGACDAEHBHCFGCHGCHGCFDCBHHBEABAHBABAHEAHGADGCCFECDHDFAGECHAFBADBGDBCABHADDBHCEHCEHBFHGFEEDCDHCEECGCDBCAHGHBGEAGEAFFAFGAEEAFAHGEHGDACD,False +680,27.0,26.0,27.0,28.0,20.0,19.0,14.0,25.0,GDCFDCFHCBAEGAFACFAGFDBEABDBCAHCGFFFCFBBBADBGFCDACDGDDHCEHAEHBFGBHECDEGAACBHCHEAHEFCGACDBHDACGACHAHHAHDEHFCBBABBABCHBFDCGBCHBCHFDHEEBDEHEEHGEFABHAHCAEDBCDBCDEEDCBDBHAFAGEADDADFADFDDHGDEC,False +681,3.0,1.0,1.0,3.0,4.0,8.0,7.0,1.0,HGFEDDABGFGGFGFFGCGAFDAFEEFE,True +682,15.0,12.0,11.0,14.0,15.0,27.0,23.0,14.0,FHFFHFCHGEDCEDGABGDBGFFGFHGDDFFDGCHECAEGEBCEFCEAAAAGACFAGGGBEGBFBAFBAGGAEHAEHBDGGDFDAHGGEGGHAFHGCEFDBFEHDDBGFBCFAFFEHFCHFHDFCFFDEFB,False +683,3.0,2.0,5.0,6.0,4.0,4.0,5.0,2.0,GGFDFADFADECDCGBCGEDHEDHGCBCAEF,False +684,13.0,18.0,21.0,19.0,20.0,13.0,21.0,11.0,FEEGGCAGBEGFECBEGBDHBDCCGACGFBFEHHEHBCHCCFDCDDCEACEAFHHFCFDEBBGBDCBDBADEDEGCFDHABEDGEGFDCFECDEAHEDGEAGFAEAAGHADABDBGCGGBGFBDCBDGBCGECGHC,False +685,10.0,7.0,12.0,11.0,9.0,18.0,8.0,9.0,HDHAGFAFFAFFAEBDCBDBEAFEACEACDGDDGFCHFCBCCACHGCFFCGDEFDFHEFHDCBEHGEGFFDFAAFBEFCDGHBH,False +686,6.0,12.0,8.0,11.0,9.0,7.0,20.0,10.0,BCEBCDBHAGDAGDHGDEDAGDGHBEHDDFGDGEDAEGGGCEBCBGGGCHECBFHHGGFGGFGGHGAHFBBCBECBHABFDEF,False +687,12.0,20.0,16.0,25.0,15.0,20.0,20.0,33.0,DFDHAGHAEHBHBFCFFDHFDBGGCCBDABHGGHBBCBFCHCEEADDACDFCAFBHBHDBHFBADGHDGHDGFEEBHHGGHGHFGDFCDHEEHCECCHDBDAGDABDCBFHAGEAHEHHEHFDHFDHFDEFDCCGBCHEDHBDGEHGBBGFDHAHHFEFGG,False +688,3.0,9.0,2.0,3.0,7.0,7.0,3.0,4.0,CFEHFBFBBEDBCHAFABFEBEEBDEHFEDFHBGGBGA,True +689,15.0,26.0,20.0,34.0,29.0,23.0,27.0,17.0,GAAGDABHABEGDEBDFFDHFEHFBFCBGCBCCDGFDEHDCFDBHEBEFBEBCGCDGADBDGGGAAFCEDCEDBHGBDDBEDFFGFEHBEFFCAHCHHGFDDBCDBDFEHFGAFHFFDBEABEFBGFAGHGGEECCGABDDBEEBECBEAGCHGDHGDEDHFDHDAECAECDEDGEDEBCEDDGGDEGBCG,False +690,2.0,5.0,5.0,7.0,3.0,8.0,3.0,2.0,GFGFFGFDHHAEBCCBCDFCDEADFDBFDCEDBBF,True +691,11.0,14.0,14.0,3.0,13.0,5.0,13.0,10.0,ABGFGEEGEEGEHAHBCHBDDGHBBABACBCEEGECGECGHCABCABCHBEGAEFCCGBFGCAEFGECBFHACHACHDHBGBA,False +692,17.0,27.0,23.0,13.0,20.0,16.0,15.0,12.0,BCCBCGFCGFADAABEDHEHBEADCFFEFFCABCGBABBEGBADBABBFCACGEDBEBBGFBGHBGHDEHBEHBCHACHFGEECHGFHGCCGECGDBBDGAEADFCGECDEFEFCCFAHFEHEABAFCCECEBDDBADBABBC,False +693,27.0,22.0,19.0,22.0,14.0,28.0,28.0,25.0,FCDFEDBEDFECFBHAAHEACBFDEGDCGFFHHFADGABFAFAAGGBHFECAECAGCGBDGBDHBHCBHFEHBBAFAAFAFFCHFGGFHAADCCGCCGBHGDDGFDGBDGBABHAGFDBFGBHAEFFDGFDGCAACAGGHDGAGCDEHDHBGHEFCEFADHEHABHAFHEHHDBGGBFCBGCHAD,False +694,18.0,13.0,19.0,10.0,11.0,15.0,13.0,6.0,GDGHAABAGDGHFBFGBCGACGAEAFDAFDECHECACBFCBACBEBDGBFACEEBEDCEACEBBDDBGFAFFDCFECDHCACCGBFGHGCEGCAAHAAFCAFCFF,False +695,10.0,11.0,11.0,10.0,20.0,12.0,15.0,5.0,DBDBFDEGDBGEEGEGFAAEGDFCFECEEAEEBHGGHCGHCFACGHEGEEGAEFCEFBAFBAEEACCGFDBFCHACEDFADFGBGCBDEBEGBD,False +696,11.0,15.0,9.0,15.0,19.0,14.0,16.0,14.0,BBEABEBFEDFHBEDCFCEDEFDECCEFGFGBHGBCGHGFHEBDGBFGCFGDGDACDAFBFHBHGECGEHDEHBBFDEEDGEFCAAHEABEHHEAHEAHDAHDGGDBGFAGAD,False +697,4.0,10.0,3.0,4.0,4.0,9.0,13.0,9.0,EFFBHHHHHCADDEGDFGBBGHFGBBBBHBACEHCFBEGDGGFGGFGAFGAGHFGB,True +698,8.0,6.0,6.0,10.0,3.0,3.0,10.0,9.0,CHGBHGEHGAAGHDGDAGDBDHADHBDHDAFACBCFBGEHCEFCGABGAGDCDDH,True +699,23.0,20.0,26.0,25.0,24.0,29.0,20.0,24.0,CDBFFGEGEACCACDGBDCHACHACHBGDBCFBHFHHFHHAGHAGHCHAEEGCEHEEFFCDFDDFDFAAEEFEEFBEDAEDFGDFGDHHDBCBBCEBEABADDAEDGGGCEHAGBEFBCFDHFBEFADFDCEHFEHFHADCFDAFHAFBFCEDDBCAHAACGCBFCDHBFHDAGFEGFGGCCGCBBCAHGE,False +700,29.0,20.0,21.0,24.0,24.0,23.0,13.0,26.0,EBHEBHBADGAHAAEEACGAFAAFBBFCHDBHAGCDEBDCDDAHHBCEAAFHAFCABDDEDEEDFHDFCDFBEGCFGEFAFGCHGDHFFEFHEDDEADBACACEFCBHCEHCAAEAECAEBFDAFHAHGAHGBGCBDHBDABDHBDHADFGEBABHFCFFAHFDECHHCHHCFCGDEGEE,False +701,3.0,7.0,7.0,3.0,6.0,6.0,4.0,11.0,CEFCFHGFHBHEAHECHEBBAHAEECHCDHCFFCHBGFBDDBGHBGH,False +702,9.0,6.0,16.0,15.0,12.0,8.0,10.0,9.0,FDCFDCDAHDGHFAACBCHDEHEGDEDDFDDEGCGCDBCDEAFCBCCBCGACGACHHEEHADDAEDCECFECFAGGBBEHFGHEG,False +703,6.0,1.0,3.0,5.0,2.0,9.0,6.0,6.0,DABEAHCFGGFAGFHHFCFFHDFHDCGFFGDEGDHAAA,True +704,4.0,1.0,0.0,2.0,2.0,1.0,3.0,0.0,BGGAAGEADEFDA,True +705,18.0,19.0,12.0,21.0,25.0,19.0,18.0,24.0,FDAHBFHDCHACHAEAEEBDDDDDGFHHFEHDDBDAAAFHAGGAGDABCHGCEGCFDBGCBEFHFDHFHHEGCFABHEBHCAHBBHEAEEAEGAEDEBGFCDHEEHGEFGEFBDFEGFGHFDHFBHDBGDACBAFBDFEHEECBEGBDGAEGEHBC,False +706,17.0,12.0,10.0,18.0,25.0,13.0,22.0,21.0,AGEHCDCDAEDAEBAGGHGGHDCHEHEFCEABEGBEBHAGABHABFFGGFGAFGDBGAEDAGFAHEEBFFAEFBEHCEFDEFEHDCHDCHDGAEGAHHFHEBEEGABGDHGDHBDHDHGCEDCHFCEEDDEHDGAGGE,False +707,18.0,24.0,22.0,26.0,29.0,18.0,27.0,19.0,HFHHGDEGFHCDHCEGFEGBDCEDEEFFBFCAEBBGABHADAAGABFDCGCBHABAGHDEDEEHBAHDAGDBGCBDHHDBEEGCFGCHCFHBFDEGDHDFHAEDAGDFGEFCEGGEBGCCCCECGECGCHACEGCEFCDFBDFBGBEABECBEBBGAHGDHDDAABGGBEGAEBEDFDDFEDE,False +708,20.0,10.0,10.0,16.0,13.0,13.0,19.0,23.0,FFHDFHCCACGGGHEEHDGGAGEAGHAEBAHDGHGGHBGAGFCBDCDDADDCEHADDDHBAHBAHBGGAFAAGAGGBGFHAHHDHGEHEFHCFHCBACEDBDDFCEFAHFAHEAEFHFABEDHE,False +709,5.0,8.0,2.0,9.0,7.0,8.0,16.0,8.0,CGDAGDFHDGABHDEFFBFFBEDGGAGGCEGHHGADEFDEDHEDGFBGHGGHGGBGBBAHEFB,False +710,2.0,0.0,1.0,2.0,0.0,3.0,1.0,3.0,FGHDDHAFHAFC,True +711,11.0,11.0,7.0,14.0,11.0,15.0,19.0,23.0,DHDDADGHBGFBGHHGDGAHHHGHHGBCEDCHDHDECGGFDDAGBHGBGDAHBFFBFFCHFCFFHBFHEHHGAFGAHGHDCDDAGEHGEHBFHEGBAGFAEFCEABEAEEF,False +712,22.0,16.0,19.0,9.0,22.0,12.0,19.0,16.0,HDGBAGAAGFEEFADBADHGCGCDBCABEACGHGEABEAFGHFEHFGHFGHCGEFGEFHHACDAHFCGECEABEAEEBBABHEFEAGEDGBCEHDEADCBDABCHCCHBCGAGHACEACHFCEEBAEBAGBGFCC,False +713,10.0,16.0,20.0,25.0,19.0,11.0,23.0,14.0,FDCDDBFDGCEFFEBBEBBFDBHCFAAHGDHDBFFGFDACDAEDGEGGDCADCDDGEDGEGCEGDADCGDCBBHEBDECEHCEHGBHACEGGDCGHHGHDGCGGCGCDHHDECCEBEEDABBAGBGEAGEFDHFBHCC,False +714,7.0,8.0,11.0,9.0,14.0,8.0,8.0,14.0,AADAFBHGCCGCDHHFHBCHDCHDEHEEBFBAFHDGHDHHEAFEFCEGDHBEHCCFCHBBEDEEAFEAECGECGEGDBG,False +715,4.0,5.0,2.0,4.0,4.0,2.0,5.0,7.0,BEEHHBHHCDHCGEBGDBDHEFHFAAGAAGBDG,False +716,2.0,4.0,4.0,2.0,5.0,4.0,1.0,3.0,GBACBHFFEFFDHBDHEAEECECCB,True +717,15.0,12.0,19.0,9.0,14.0,21.0,18.0,23.0,DBHAHHEFBFAGHAGHAEHFEAAGCGHBFHBAHDCHCCDAGGHGFDAFEEEGECHCCEBGDAGCAGHGFACDHBDGBAFCFFCDFCFFCEGCBGFBCHBHAGHFHCBHAFHCFGCEGCEHFEBEEFFHDFH,False +718,21.0,29.0,17.0,17.0,19.0,12.0,14.0,21.0,BHBBDDFDBFDBDHADHBCABAHFADGBECCFDBADGEHHBBEGHEDHCHEBHBHHBEEBCABFBBFBFDAFABDGCEGCEGBEACEBBBBCDCHGEDEEGGHGAFGABGABAAHAHHAHGAHGEHCDCFDCFEEDEBHCCCACAAFABE,False +719,15.0,18.0,17.0,14.0,22.0,18.0,20.0,22.0,GGECFCHFHBEHBEDBEFBEHBDHBGAGFAHFAFECFDFHGFBGDEHECDGCAEFHEFBDGHDGDBGBBGBHGCCGCCGCHHEBBBBEEAHHBFEACADDACGCFEHFEHFAGAHGEHFAAFCHDCEGCEFDEGBHGDHEECAADA,False +720,4.0,4.0,3.0,2.0,1.0,3.0,4.0,4.0,BFBBFHBCHAHDAGEAFCADCGGGH,False +721,22.0,14.0,33.0,22.0,22.0,16.0,25.0,18.0,EGACBDEEDAADHAHBABBAEGAEGBHCBADGFBCFBAACFEEFEDHBDCGECHHHAGEAFECFEGFGAFGHCGAFGEFECFGCABEEGGDAGDCCHCCHGDEGBEDBACAHDACCCBHCAHCHDGHAECDDCDHCFCDAHHCECGECGDCGFGECCCFCCDDGDDGDFGBF,False +722,15.0,12.0,9.0,7.0,14.0,11.0,9.0,13.0,HFDHFEHEGDBCFBCAAHFAEFGGDBADEAFEAHEAHFBGFHEAGEDGBBABHGEHGECCABCEHDBADCFEEFAHFGHEAHACCABCBB,False +723,25.0,27.0,19.0,19.0,29.0,24.0,29.0,27.0,CHBDGEDBEGCHBAGECBACBGCEACAGCAGEFHHHGHAGAEDHGCGBBACHDGDAGDAGBFFBGFBDFEAFBABACDEFFEAHHAEHGHHBFABFACHHHEBGBBEABEAHEDGEDBFDCHDBGGEHHEGHFCHFHAFDAFEGGHGECDFGGBGCFEAGECBECBECFEAFEBFEHFEHBDDAEDADDFCBFEBFGHG,False +724,7.0,6.0,4.0,4.0,2.0,2.0,7.0,4.0,BACDABGAGDBGHFGHFCHAEGADGBEGBAADCBHC,False +725,13.0,14.0,14.0,9.0,9.0,11.0,7.0,5.0,ADEDDFDEGBCACCABCADGAFGFGAEGAGBAFCFFHBBHCBDBFEGAEDBDFHCEECEAFBAFHCFCCDBCABCABHBBEC,False +726,6.0,1.0,2.0,1.0,0.0,2.0,3.0,0.0,ADAAGACFACFBGGA,True +727,22.0,23.0,26.0,27.0,23.0,28.0,17.0,22.0,ECCBCCADCDDGGAHBAHFHCGHEGHCAHGHHGBEFCAFBAFHDFAFCCBACDGCBGHGEAGCDECFEBEEDFDFBHGBAGBADFEDAHDACDGEFEEHGEHFAHFAEBDBBEBFEDAEDHDDCFDGDABEGDFHBCBFDFFACFAFHEFHABDCCEABEFFHCFBFFBFCBDCBDCEDGDAHDCHCE,False +728,0.0,0.0,3.0,1.0,3.0,4.0,2.0,2.0,CEHCFCGFHDFEGFE,True +729,17.0,19.0,22.0,26.0,19.0,16.0,18.0,23.0,GFHGAGFACDAEAGFDCBCCBCBBGBDGEGCEHDDADHEDBADHDEFBEDBDGBCGAHHAEAAEBDGDGGDGABBECDEFDEFHCAHBDHBHGGDFFEFDCCDACBAHEABCHEEFCEFHGFHDEBGEBHHHHCFHEAHBAHCDDDDCGFCHFCHCCFCD,False +730,10.0,12.0,10.0,12.0,5.0,3.0,7.0,9.0,GGBHAHCBEBDABDCEDEGDCGDAFAHGAHDADDACHACGECADHABCCGCBBCBBHHBFDEHDBDFB,False +731,8.0,9.0,15.0,9.0,17.0,19.0,15.0,6.0,BHGBCGBCDBCFBCBACFAFEGFECFEGFGCEGCGADEFECHEDEEFFEFFGFFGDFCEGCACBAFADCGEEGDBADFAHHDGHGFEEDCEHFFBGEC,True +732,15.0,25.0,16.0,23.0,8.0,23.0,16.0,19.0,CCGCCHDFHDFABAHDHGDBFDHDDBBDHBGHGFDDFGGHEHABDFCHFAFCACBBDDBDFBDABHABGBEDBEDAFCFBCFGEBBHCBABGABGHBGHFGCFGCFGEBEFADCHFHFFCDDCHAEHBDGADAADGFCFFBFEBH,False +733,26.0,12.0,25.0,16.0,6.0,12.0,11.0,16.0,DDEFFEHBCBCAGCHGBHAAHCAHAHHBHHGGHCFDCADCADABFCCGAFDAGHCCCACFADFADAHBGBCFFDBCHAFAAEDEBAHBAEFAFBADBDDADCCCCCCCACCGCDGADGAEAHGH,True +734,24.0,26.0,16.0,18.0,21.0,14.0,24.0,22.0,HGDGADCHDBBAEBDEBDEBEEDECFBCAGCBCHGDBGEBDEBEEBDGBGHHFCDDHGDAGHADEBDAAHBGBAHAEEGEBGEBAACFHCFACFHFAHFAHFDHCBEAHEHBCHAHAEDGFBGDBGFBHBEGDGGACEACACBACFAGGEGBFBHAGHAGCFGHF,False +735,22.0,22.0,29.0,19.0,27.0,26.0,31.0,18.0,FACFCCFCAHCGBBDADAGDFEEFAEFAHADEGDACBFCBFBHGCGGCFFBGFGFBBHHBCAADGCDECGGCGGCAGCEGEGGDDGAGHAGHFCFCEGDGCFFBDEBDFBFEEEHEHBEAEEAEEAGEFDEGDBBEHGAGFDGEDHBCHGAAAAABCECCECCHCCDFHBFCEGEDGFBFCBFHBFHDHHCGEB,False +736,3.0,2.0,3.0,3.0,1.0,1.0,2.0,0.0,DCBDCBGCAGADEAF,True +737,25.0,20.0,13.0,20.0,9.0,15.0,15.0,17.0,BBCBGDDHBCECEDCBDHGDAGDAEAACDBCDAAHFAEFDCFAFBAGAGBABHABDABFAFFDDHHHHBFHDFGGHDCFGGHHGAAEAABCAGCBGCEGABCADEBBEFBDFHGFHDFHCFHAADEBDGADABH,False +738,15.0,21.0,15.0,20.0,23.0,14.0,16.0,14.0,HBDCBCCDFDDBDABDABDFDHHBEGEFGEFGECGECGECABBEGFEGFGFBABDGBHGBHCAEBBEBEDDDBHDAFCACCEBHGGDEDAEACFBFFBGFGEEHHEHEAHADFCDCAFCDEBDCDEGEHGAHAHEABE,False +739,6.0,4.0,7.0,3.0,11.0,9.0,13.0,4.0,CEEGFEGFDGBBEFGGDEDHCCEAFEAFBAFGACCAGAFEBFEGFGCHGEHGECGHG,True +740,18.0,18.0,17.0,21.0,22.0,23.0,24.0,19.0,CHFCHDGHDGBDCFEEFEDGHDAHDAECAFGFFHFCDEGAHBDBEDHEGAEGAEFBEHAEHABBAHFGECAHBFCDFDEEDEGDACBFHDFBGFGFEEFAEFCFBCHBDFAGGAGGAGBAGBEGEGDDGCDBBDBGEFGDDGHBBECHFCHCCFAGHCFCAH,False +741,9.0,8.0,14.0,9.0,12.0,8.0,10.0,8.0,HHAGBAGCACBHFBHFDEADGBFGCDABDCEDCEFABGECCEBCDGEEEEECECCFACHAEFGGFCGFDGDACDHHBH,False +742,12.0,15.0,13.0,8.0,14.0,16.0,4.0,12.0,AFFFBFFBCEAFAAEBHDAEAHBCHFCHBDHBFHBDEBAHGFHFBEGCFHCEAFEAHABDBEDEEFECHECGECFHCFCCDCCGBDABDBBEFA,False +743,10.0,6.0,7.0,8.0,13.0,10.0,9.0,5.0,AFAAEBGEBEECEEDFCGGHDGDFCFGHFBHEHDDAADEDDECBEFBECHCGAAFFAFEAGEAGFBGC,False +744,4.0,4.0,4.0,5.0,4.0,3.0,5.0,8.0,FHDHHGAHBHDDHGDAFEACEACEGGFHBCHBCGEDB,False +745,5.0,2.0,6.0,1.0,2.0,4.0,4.0,5.0,CHHCFFGFGAAGAHGCHABEACEHCBFCD,True +746,6.0,7.0,9.0,8.0,5.0,5.0,6.0,0.0,GDGGFGCEDBEDACDCCFACFCDABDACAACBEBBCFBFEEGBDGD,False +747,23.0,21.0,27.0,20.0,27.0,21.0,28.0,26.0,DEADBCCGHHGHDBADBADBEEBFEBEBGGCAEDAHDFDGHEAHEAGEDGEFGBAGHFHECBCAEEBEGFFFHHHDHHGACGEEDCADBAFBHGBAFBDFCDCBGHFHAFCCDCGACGAFGCEGCHBBDGCHFDAFGGGBHGBHAAHCAGEDCCGCCHBCHFFHEFCEFAAGACGCEECECHEBHEGEDFEDF,False +748,3.0,5.0,1.0,5.0,3.0,2.0,3.0,3.0,DBGHEAHDADDADECFEGBGHBFBB,False +749,11.0,7.0,13.0,10.0,10.0,9.0,18.0,6.0,AGEGGFDHECGGCGBCGECBCCEFCADCGHCGEGBEBDECGGCAFHDDHGDAGDAEAEFDGADGAFCCFBAFEFDGFAGBAHBH,False +750,19.0,21.0,8.0,26.0,26.0,23.0,18.0,20.0,FEHFHBCHBCHAAHDGEABEDCECBDDAFFAFDGDHCDEGDFADCHDEDEEGHAGDFGCFGDFAEBDFBAGHAEEAEAAFAFBAFBEBBDDBDHEFHEHDEBDEFEBBAAEAEGBEDFHDHGBEGEFBHCHFBHEGGEFGEFGDFHFHGDBGDBFDBHDGA,False +751,10.0,15.0,9.0,6.0,11.0,12.0,12.0,15.0,GDEEDHHBBFGBHHBEHFHFBDCEGGEGCBCCAFCEFBECHEHEBHBAABFABFABFGFEGAEBDHCGHAGHAFCACGAHDHFDHGBBGF,False +752,16.0,16.0,21.0,19.0,22.0,24.0,24.0,17.0,HHEEFGDFCDFCDFGHFHABEGECBCGBCGBFGDFBCBAFFGCAGCAGBAGHGDHDDHGDHGEHAECADCEFFAFFDEGBAGBCEBAHFACCDCBGEHDEGAEFCEDBEHFHAEDBGAGFECFGGAGGEFHDHECHECFECFCBDCGABDBHDFEFFED,False +753,5.0,5.0,9.0,7.0,8.0,5.0,5.0,7.0,DHCDCBFEBACFGCHGCHGEDGDDEDHAGEACFACEAHEFCCFBDHBHBEE,False +754,1.0,1.0,2.0,5.0,0.0,0.0,2.0,1.0,GGBCDDCDDADH,True +755,3.0,4.0,2.0,11.0,7.0,7.0,7.0,3.0,DDGGDGFFEFFGGDECDEDFEDFBBHBGFBHDAGCADHDDEAEE,True +756,13.0,13.0,9.0,10.0,17.0,10.0,13.0,12.0,CGAEDBDFGGHCGBCFAEEAGFBFFBFFBEGEEBEEHEECDEGACGEHAFGADHABHAHHCGHFGHEHEAHGDDCAHFAEBAEDCBBCBBGBDEDDA,False +757,8.0,8.0,4.0,5.0,4.0,3.0,10.0,2.0,BDEBGHGGFDGFDAFCGGCEBBAACEDCADHABGGBGBAABGAE,True +758,26.0,19.0,23.0,17.0,12.0,22.0,20.0,22.0,DDGDEFCHCHHDHHCHGGHDBAFBFGBFEBCAFCAFHFFDCCDCEACACBFEGGHGGDFGDHCBGAFCAFEDBEAEEBDFGDAGBHBHHADGCDFCAHCHFCGFCGHCBHABDABAACHAFAAHCBHBFABFAGFDBFHBEECGAGAAGFAEDABACCEGH,False +759,4.0,1.0,4.0,4.0,4.0,6.0,8.0,4.0,GDFGAFGDGCFGCFCAHAHDFHEEHEEGDGAFGCB,False +760,2.0,2.0,0.0,1.0,4.0,1.0,5.0,1.0,ABEDBHAEGFGGEGGE,True +761,21.0,26.0,28.0,30.0,24.0,24.0,21.0,23.0,FDCHDHHDFHCCGFFAFAAGABBDGBCGBHGEHFHFBCEACEHEHBEABDBBABAGBFFBHDEEDBGFCGFCGFBBCBBDBGGGCDECDCFECFEABGCDAEHEHBEDDADFADGAEEAEFDCFHCFBCHBCHAEDDEBGEDGFHEDCBACDGFFCEGCDACABEGCDGHEECFCFHDFBDHADHADHACGDCDDHH,False +762,24.0,12.0,13.0,17.0,17.0,14.0,9.0,11.0,CEAAEBDEFDBCCBABBACBDBDDADGCGHAEHAEHBEFAEFAFCACHBHFEHADHFEFAGFGCDADDACDEDGEBGECAEBFEBEADGACFAHAACAAEADDFFGAFGCDHDHEFH,False +763,6.0,8.0,13.0,10.0,5.0,9.0,19.0,14.0,HGDFBDFGCHDCBGCEGCEGHGHHGACGFCAEEHBBGDHGCCGFAGHADHBCGDDBEAFDHFBHFDGCAGCGFFGHBGHCGHCD,False +764,27.0,23.0,30.0,22.0,19.0,28.0,33.0,17.0,AACCCCCCFBCDCCGCFBEFDGGDCGFCFFCAECBGBFCBGEHDEFGHFGHACHGFAGEAFFFCHFDGCHGDGCFGCFGCAGDBFFBECEGCGGBGHBDAEDABFABFDBDDBDAADGHHFBAECEBHAHHEFADFADFACAACGECEEAGEABADBDHEGEDGEDBFAHGAHGAGCDFBAGBGFFDCHBHEACGGBGB,False +765,18.0,15.0,16.0,11.0,14.0,19.0,16.0,15.0,CEFGFFADDDDCFAFGAFEEEAEHBEHCECAEBAECABHACHFCFGBGGBDABCFFFGFHGHGDEDABBABBAHFACGDFGDFGCBEEDFHACHGCHGBHFEGFAACECDGCHGBHCBHBAHAF,False +766,2.0,0.0,3.0,2.0,3.0,1.0,2.0,7.0,HHEHHCCHDGHDFCEHAEGA,True +767,17.0,7.0,6.0,11.0,18.0,9.0,7.0,8.0,HEEBEFBEBEEGHEFCEACFABFHBGEAEAACAADAADADDAFABDAGDEDAGDEDHCHFABEGDEFDEAEECEGHHHFGFAC,False +768,7.0,8.0,17.0,12.0,13.0,9.0,9.0,18.0,EBDDBCDHEEEGCEFDAFDABCBBHFGHGGHDCHFEHFAHAEHCFHCAHEHBEGECHEGDECCCCDCBHCGHCBFGECACHAFHDCDDHFDHG,False +769,20.0,21.0,9.0,15.0,21.0,8.0,21.0,20.0,HEDAEDGBFGHEDHEDHEBCGAEAAFAABHDHAEHGGGBEFDFFAAEAEHCHBCHACDBFGBGABHBBEBBAHBHHDABDAGDHEFEGBGGDCGEBGCHECHECHGBEDBEDBAAFGADBAGAHGBGDCGEEGEH,False +770,21.0,9.0,20.0,15.0,18.0,14.0,11.0,20.0,AGHAHEGHACBCDEHDEHEECGABBADBFCHFEABCBDEAGEAFEAFECFDCHDBDFADCAGCADCHDEADAAHFABFEDCEGCHFHHCEACGDDGHFGAFGAHHHECAEHDHHABCEFCHFCGCCEF,False +771,4.0,4.0,4.0,6.0,5.0,8.0,8.0,13.0,HGCHGCEBAEDFEDHAHHGEHDDBGDEGBHGFHGFCFFCHADFFBHGAHFHH,True +772,4.0,7.0,15.0,14.0,7.0,5.0,7.0,12.0,FCECCEHCHDDHEFHDDAEHECCGDDBDDBEDBFCGHHHBHHBCABCHBCDEDGCHFDACDFCDGCGGAGC,True +773,15.0,15.0,19.0,12.0,10.0,13.0,9.0,11.0,CDFCAAHAADAADBHCGEAHFBGCBCCEGCDCCDEAGHAGECHFHFFBFBHFBADCADEHBECBABBHFECAGCDDCFFFHDFHDFAEGAEGBCCBCEDGBBCB,False +774,17.0,15.0,18.0,13.0,14.0,14.0,9.0,11.0,BDADABGFCGHCGAGHAGFFDCCBAGFHDFHCFHCBACEACBAGBACBECFEBGABFBFFBHHBDEEDEAHEAGFDEFAFFBDHBECCCCDCEACEHCEAADDCBAEDDEH,False +775,12.0,10.0,12.0,10.0,14.0,18.0,9.0,17.0,FFDFGDFEBAEBHFHFFBFCBFCBACEGDDCHCHDGBEEAEHAEBACCCCCAHEAFFFFFHGBHDAADAHEFHGFHEDCAHHADHGFGCHGFEEHDEHBEGB,False +776,15.0,9.0,14.0,7.0,14.0,8.0,10.0,14.0,FGGCGFEGFEGEBBABCCDCHEHHCHGFDGAEHCEFCEGCAACEACADHABADBFDCEDAABEACDGCHHCHAFAGHEHBEFEAHBAHBEH,False +777,3.0,5.0,7.0,4.0,6.0,7.0,4.0,2.0,ACHDGDFECAEGAFGEBDFBCFCCFHCEECDBGFBEFB,False +778,13.0,16.0,17.0,23.0,18.0,12.0,11.0,15.0,HGEDGCCFHBDHDDECFEHAEBAEBHDCCDFCDCHGHFGHAABCAFCGHCGCEFFEBAEBABBEHBGHBFFDDGDAEDAEABBHBBHEDFEFCDCEDCEDHHCGDDDDDAGFEBBCDDADCAEEG,False +779,0.0,0.0,2.0,3.0,0.0,5.0,2.0,1.0,DCFGFFCDFHDFG,True +780,4.0,14.0,9.0,15.0,13.0,16.0,18.0,13.0,GFHBCDDGGEFBDFGDFEDHCBBGEFEAFEHBDHGFFECCDHGHCGBBGBEDHDDEDEEDBCFHGDHGFHGFHGFGGFGBFGAFHCDCAECAEBBEDBGFBH,False +781,14.0,11.0,9.0,17.0,16.0,19.0,16.0,13.0,AHAEEAEBDCFCAFEACDFGBGHHFBHDBFDCHDHHEHFDGFAFEABDGEEEFHFABFCGFGGBCHBEGBHACEADGACGCFGBFGAFDAGBAGFDHEDEEDEFDEFDGHDGDDF,False +782,17.0,30.0,15.0,20.0,20.0,24.0,22.0,25.0,GBEGHHGHFDDAEABGCBGDDCCHFEBFGBGDBGDBGCAAFGAFDEFGEFEFAEFACBGEBAEBHBBHBCHEHHEAHDDCBCFDADDHDGHFEHBHFBDBDHAFHFFHGGAFCFGCHEEHEDFAGBCHBFGBCGDCGBHBBCFBDBDEBFEFHHCBHGBEBAEBHEFAAFDAG,False +783,18.0,12.0,19.0,16.0,8.0,23.0,23.0,21.0,CAEAGEACHFBBCABCACFADGBFCCFGDFGFBGHEGHCCHABHGBHFBGEAGCCFDAFDCHBGHCGHDFEGEHGEHFDHBDFAHFAHCGGCGDBFAGFHHFHGFDDHGHFDAGBHFHEDDDDCCGCCGADFAFGAFAAF,False +784,26.0,24.0,29.0,15.0,21.0,16.0,22.0,14.0,GEEGAEGABFAFGEBBHCCCGGBHGBFDAADAAGAFGBEBBCCGCAAHAAHDBEEBGEDADDADDAECAECBEBHEFFADBCGECGCCDCGACBACFDCFHFDHGHBBHDBCECEGCBGEBCEFAECCCHFGECGCBACBFFBGFHCECAFBAHBHHAFDAGDECAG,False +785,1.0,0.0,2.0,2.0,2.0,6.0,1.0,1.0,FFFEFFEDFCDCGAH,True +786,20.0,28.0,18.0,25.0,30.0,17.0,20.0,19.0,ECEDCEBGECGBDDAGEBEEHHADHDECGEDEEFEADEAFEAGDBDFCEFBDHBHAGAAGCAGCHHCHDBDFFEECADBAGFCBBEBDEHHEBHFAHFBCEBFEGEHADBDHBDHCDBGDBHDCGBFEADEADHAEAGBBCBACEACFDCBDHBDGEGGEBGEFGBFCBGHFGFFAB,False +787,5.0,3.0,2.0,6.0,9.0,8.0,2.0,4.0,DAEDAECHGCHBEFFEFEDFEDADHEDAEFBFABFHFEG,True +788,5.0,9.0,7.0,1.0,4.0,3.0,1.0,5.0,EBABAACHBEHFACBBFBBEABCDECHGCHBCHFC,True +789,12.0,4.0,13.0,8.0,13.0,16.0,10.0,11.0,ADAAEBAEGDFGHFGEBGADFAFFAFFEFCECEEFEGFEDFCCECHHAFDCFGHEHBBFAGFGHACECGHCDCCHCCHDFHDGAAEH,False +790,6.0,10.0,8.0,9.0,9.0,8.0,9.0,13.0,CEAHHCFHCFHBEACFACDBGDBEHBGGCGGAFDHFCHFEHBABBHDHGDEAHGBEBEGBEDHEDGCDFHDF,False +791,8.0,14.0,12.0,15.0,11.0,8.0,8.0,8.0,EBHEBDCADCAGCABCGDEADEAEECBEDADFEHECHDBHGEGCFDCFBBBHBBDGHDFFDFFGBGHBACBFCHGCDCDDEBDA,False +792,10.0,22.0,18.0,14.0,21.0,20.0,16.0,23.0,DBGEHGFDGFECFHGFEGFBAECAHFHECBABHGFACEBDGBCGHCECAEGBBCDBEGEEGHEAAECGBFHBFHAFHCFBCDHCDHDBHEAEEBHHBCCBFHBCCBHCEDDEDDEFFHHFHFFHEFDAGBFEBHCBHDBFDGGG,False +793,23.0,21.0,27.0,21.0,31.0,27.0,29.0,18.0,AGFCEBGEFGHCGECBEFEGFCBFDBFHCCHCBEDDAGFBDCCDCCDEGHEGHAFHGGHDGDBADBAGEAEAGFFCDACFACFGCFGHFHEFHEDECBEBHFGDEGCEGDBAFCCFACEEBDDHCECDEADFGBBEABHACFAEFAEHAEHEGBFCAHGEFDEAAHACGDBEFBDBBCBCEHGEFGFGGFAGDAGEG,False +794,24.0,20.0,28.0,18.0,24.0,31.0,23.0,26.0,HHAHBAHDAHGAHECHECDEHEEGEFCECEFDEDDFCDFCHBBHBHFCGGEHCAHCDGAGADGCHGHFGEEGAEBABBAEFDGDHFFEGCBFBGHBGABDBCAGCEFEBFCFAAAGAGBABCAEAAFFBFFBEBDDFFCFFHFFECFHDFGCCACFAFHCFECECCFGHFGBAGBCDHHHCCHDCEDAEDGHFG,False +795,31.0,20.0,15.0,24.0,20.0,24.0,18.0,24.0,DDFDGFDGAGEBGEBGFHEDHBDBGHCFHBDCEACAGHADHGHFGBFHCDHDHEEHGGDGGEGDFGAEAEECGFCBFABFADAADAHGCFFHBFBAFDAFDBEBAAHAAHAAHAAFABCABEBEFDHDHEFHEDABHCDDDHBHCCGDHAECAEBEHAFBACEADFBFFEAFCAFC,False +796,6.0,5.0,4.0,8.0,8.0,11.0,14.0,10.0,AGGGDBHDBEDHHCHFAGFGEECFFAFFAEDAEFEGDBGHHFHDFGCGHAGHGGHGEBCEBDFGDF,False +797,13.0,13.0,14.0,16.0,20.0,20.0,14.0,14.0,FDCFDCDGCDGAFFFFHFBDGAEEFDHFGHGBFDAFHGFHGDEDDEADCHGBHGBACAHBECACHEEEEBBDFCEBBEBFEHAGCEBAEFCEFAGFAHFGHFGCFECADCGEADEHDEBDECHB,False +798,16.0,22.0,7.0,24.0,22.0,17.0,26.0,9.0,EFHFGCFGEDGFBGFBHACDACDAGBBGECEBBBDDADDADHGGGBGGBFEEDEFDEAGEAGEAFEDDBDGCDBBBGHGDHCDBDDEGEAFEADEABABBHFBFDBFDFEEFADGADECHBGEGFFGBBHEGGFDGAGAHGEE,False +799,20.0,13.0,23.0,31.0,20.0,22.0,27.0,27.0,ACCDDCDDCHDEGDBGEBHAHGDDDCDAHDGFAGHAEBFECFBCDECBAHEACGAEGFEFFGHADDGDDACEACECCFFFDFGHBHDBHDCFGCGACFCDHCBHEFDBDGCDCDEFDEFAGHAFHAHHCEGGDBGFEGHEHHAGFEBFGAHCBHCAHDADFGDEHDHHAGHFEHGEGGDGGBF,False +800,7.0,7.0,4.0,8.0,5.0,4.0,9.0,2.0,BFADCAGBDGDDGDDAEDEFBEABEBECGDGHAGHAGFGBABCGFC,True +801,27.0,24.0,11.0,26.0,22.0,20.0,24.0,21.0,FDEFHBBHDBDFECFEGGEGBBBFGBAGBGFBAEHFGHCAACHBBHBDHEABEFBAFGEDECDEGFGGHDGAGGAHCBHEEEFHEDHADFDHGEGFAAACDFDDFBDCEAHEBHEAAEFBDABAABHABDAGDADFAHFGHFGHCGDFGEBCDBDAGDBGHAHDADAGECDACDE,False +802,24.0,16.0,21.0,28.0,24.0,24.0,17.0,24.0,EHGDHECEADBDCGFCGDCFDEFDHFEEBHECAGBDHDDAAAAGEHGCCGBEGCEGEFDEBDAAGEFCAFABFBEAGEAFECCDDCDDHDHFDEFGAACEEEHGHHADHFHADHFCCAHGACGAHECBEBBDFBCFBHADDAGDCDFAHFAHFABFEBFECFHDBHDBHDGHFHFCDF,False +803,20.0,21.0,21.0,27.0,21.0,19.0,21.0,15.0,CHCDAADHHDHFEEFGGDBGABGCBCFAHFHFFGBDEBFEAFEHBEFDEFDAHCGGCDFCGCGECGEAGDBCEBGAADFADFCDAEDBDAHAEHAEGGEGAHGADFCHCCHBDBBGEADDADDBFDBCBBCBEGDDCEEAGDCGDFDEGBEBBFBAHCEHCFCFD,False +804,1.0,2.0,0.0,1.0,3.0,0.0,1.0,2.0,HBEHBEDEAG,True +805,17.0,17.0,12.0,11.0,12.0,11.0,11.0,14.0,CACCACHGBBBBABBDBGEGCAGFBEFAEBAECGBHHHHHHHFDEFGCGGBBBAFFAFFACAACGACDDEFEEDEADHAHCBHDGHABHEBGCFAHBEDDDFEDA,False +806,8.0,5.0,13.0,9.0,8.0,4.0,5.0,7.0,AABDACCACDACDBCBEEHEHCDHEDGEDADGFFCCBCGBEHCHHDGHECCFDCFAEGA,False +807,2.0,3.0,6.0,1.0,2.0,2.0,5.0,2.0,CCGFCGCAGEGGHBBHBDCFECA,True +808,8.0,11.0,13.0,11.0,20.0,5.0,10.0,7.0,EDGEBEBGEBGECCCADEEEBCEGEDBECBCCDAEDHECHAGHGCDDFDBFEBFEBEEGEFHAAGABGDFHDCHACBEDGECAHC,False +809,19.0,18.0,17.0,18.0,21.0,24.0,23.0,21.0,GGGGAGFDDEHDEHAEFAGHHHHCBECAGCEGEBGABGFBDCHDBHEHHGHFAHGCBGFDCFDCFBEFHHDAGFFGCEEDHGDCADAAHEEDEBHHFAFFABFACCBCABHGCGDBEDFEGFCGFBFBBCBBDFEGFECFAHDAEDAEAEEDCBGGFFFHA,False +810,20.0,16.0,11.0,12.0,13.0,19.0,22.0,18.0,AGFCHFDDFBEHGEHGBHGDCGFCHEGAGADFAGGAHAFBABBFBBGGAABAAEADEBDGCHHEBGCAEAHEGCAGFHDFHFEHAGDGFDBFBBFADCGDBGHFGHCCCGCDGBBAAFFAFHHFEHFEHEE,False +811,17.0,22.0,15.0,31.0,25.0,25.0,18.0,24.0,HAFEGGECCHDGGGHDGCDGDEAAEHGEFGBGGHGBEFEEBCHAEHCFHDFHDFGDGDBGDAFBFFBFHEECEDBEDHDBEDBFDBFABDEFCHAEFEDHCDAFDCBDABDABFCBCDHEHFCAFCDBEDACDEHFFHFFEEEBDEHEBHBHHAHGBHDHGDBCABDADDFDAFGAF,False +812,13.0,7.0,5.0,13.0,10.0,18.0,4.0,11.0,FGEADHABHAEHFCHFAAEEAFEAFDAFABEGGHFFBBDBHCAHADHBFADCCHEDFGDFDDBDFEDFEHFDAFDFFEHFC,True +813,30.0,25.0,17.0,27.0,18.0,16.0,23.0,20.0,DGAGBDGFDGFAAACAGCEFHDAHDBHCBACFACFGHFEFBHHBDHBAEDAHCEFDGCAADABGABDEGDGCAGCEGBABEABDFGDFADFABGBHGAFGDDGHDAHDCDDEDGECHEHGFBBFHBEBBCBDGGHHCEHBEGBCGADAADBHEFDEFHEAADCCHEDECAAABABB,False +814,24.0,14.0,14.0,18.0,16.0,18.0,16.0,21.0,ACBABDDGDGCCHAEHAEFDEFGHFGHFGDCGEBFDBGGBFACACFAGEHGBAFBAEAAEFHEGHCAEAADDHCABFHHEDHDHACHAGHACHGCHCHDDHABAAFADDBBABFHCFGCFEDDEDDHFEHFEGFBGEAFEB,False +815,13.0,9.0,13.0,16.0,13.0,6.0,10.0,11.0,EBHEDEGACDDCDGCDACHFCECCHGBHGBHCBEDAEDHFAFEAHEADAAEADDFFEGBDGEHHABGGHGCCADCDDCDHCABEFBEDBAG,False +816,3.0,7.0,5.0,5.0,0.0,0.0,5.0,2.0,DDCDBADBHGBGBBGCCCACBAGBDGH,True +817,5.0,5.0,2.0,2.0,3.0,8.0,12.0,6.0,HCHGCGFHGAEAFGHFGHFGFEADEHDFBGGGGGGFBFABABB,True +818,1.0,11.0,9.0,4.0,7.0,7.0,8.0,7.0,GABGHBHDBHCBECBFGHFGBCBBFEBECCEFCDFCGHCFCDHEFGEGBEBHDG,False +819,2.0,2.0,5.0,5.0,0.0,2.0,1.0,5.0,CDACFHHFAHDBHCCDCHDBGD,True +820,11.0,24.0,12.0,20.0,8.0,10.0,7.0,16.0,DDBDDECFEFFEBFBBABHAFHGGCCADEHHABDDDDCGHFABFABFHDCBDBGDBCDBFEHHCBHADHADBADCHDCBDHBEHBHABCGBEGBCDCGHBDAEFBBBH,False +821,9.0,5.0,8.0,7.0,7.0,2.0,8.0,6.0,DCDGGAGGCHGCHBBEEAGEGEFCEDADAADAAFCABCEHCBHBEHCAHDDG,False +822,4.0,6.0,4.0,6.0,8.0,10.0,6.0,8.0,DGEHGBHAFDDFEAHBFCBFCDFADFCDHGEHGBFCBHEHGEBEEHEFGFFA,False +823,11.0,21.0,15.0,29.0,14.0,28.0,25.0,13.0,GCBACBGFGGFADDGDDHCCBEGFEGBDBBDFFEFECFBCFBFFGFFGDDHHDFHEFDEDDAFAGFDEBEBBDDHDEHGCHFCGCAGCFGDGGHCFBBFBDCGGEGDEBAHFDEADEADFCDGABFDDFGDCGBFADABDGBHGHGFHFDHFEBCB,False +824,9.0,9.0,18.0,17.0,22.0,11.0,12.0,16.0,HDHHDBHCFHEEAEBDEDAEDBEDBHHAFFDDFCHGCHECDDCEEEFEDGADGCDCCHCAHCAHCEHGECGEGGHFDCCEECACBGCEGFGDEBAFFAGCGBEEEFDEFDBHBH,False +825,13.0,14.0,23.0,11.0,13.0,29.0,17.0,16.0,CFBCFDDFBDFBHFHGFAGEAFFBHFCCFCFACFACFDCAEBHFGGBAGDEEHBGFAGFHEDHGFEBFHHFGFDCFCBHEEGGCFGEFBCADHHDBFDBHDHACHCCGCEGAGGFFACCAECFHCGBCEFCEFCAB,False +826,5.0,8.0,5.0,6.0,10.0,4.0,3.0,7.0,DDEDAGAAGAHCDDBBHBGEEFHECEFHEBHEFHECEECBBCHBDFBA,False +827,20.0,17.0,26.0,28.0,18.0,27.0,26.0,26.0,ECFEGFEHFHHFABFABFEHABHAGDBHDBHDBGDGCDGHABHAFCEHDBHGCDCEFEEADECDAFBGFEGFBAAGDGDDEEDHDABDABFAGFDGDDADCBDAHGHHGHHFFFFFGCDEDGGCBCFEDGCCGCCDCEFFHHAHDBHAFCCFDGBCCHACHDEGGEGCCDCCHCBGFAAFEGFGCHHF,False +828,10.0,8.0,14.0,9.0,25.0,17.0,21.0,17.0,ECHGCHBCGEFDEFDECDEGBECBHBHHFFGGFGGHDGHACCAHHBDCFGAFGAGEEHEAHECEEHEEBEEGDECFEBFECFHFFGGGAEGHEGFCFBAGAHEEGDAAHFHCFGEEDFGDC,False +829,3.0,3.0,1.0,2.0,3.0,6.0,4.0,4.0,DHEHHDFHGGBAGAFEACEGFBFFBF,False +830,13.0,14.0,5.0,14.0,12.0,16.0,14.0,22.0,GDABFFCGFEHEGFFBHCBHEDHFGFBBFEDEHDHHGFHAEHAEHCEHABHADGEDGAFGHBCHAGHADHEFHFFGFGBAABAABDGBDCHDGBEAFHHDDBDHBFHDEG,False +831,30.0,21.0,25.0,25.0,16.0,20.0,17.0,32.0,ABDAGCAGBEEEEFEEFGBFGACGBHGBHCAACAACGCHGHADHACEECHDHACHFEGEAGDAHDAHDGBBHBFHGCHEHHAFGFFDDBGHHDHDEHABBACBHCADFDDHBDHBDCDCBDAHFFHDDBFHAGCDBFFEECCECCGHAHCAHBEHDACDAHDFCDAHDBBFFBAFCFFCAHAAGAC,False +832,25.0,27.0,23.0,20.0,26.0,20.0,20.0,27.0,AADBAGBCFACEEGDFBFFBFHCGDBHEFHCFBFBEEBHCCHCHBEBGABDAHDFHDHHFEHGECGFCBHDFHABBDDBDFHDGCGCCGCDGCHBHEEDEHDHBDEEHEGHBBHFBHFBGCEGEDAEGAECCEAAEACBAHDEBAEBFGACGAFAHDABAHDGCDEAHEAFECFGAACBACHAGBFGE,False +833,25.0,13.0,14.0,24.0,17.0,12.0,19.0,18.0,AEBDEBFCFGAEEHEAHBAHDCFDHFBFAGFAGAEGCCDCAAGAHEHHGAHEACFDEGDCFBAGGABGADGCDGFEBFEAAAGAAECBGDFCDBEDHEBCDDHDDHDGHDHHGCHGEBGHCAHDEEDCDDBADAAGABHDDF,False +834,15.0,10.0,18.0,19.0,15.0,14.0,14.0,17.0,GFDGHHGDHFHCFDBEBGADGACECCHHCHFAHCEHCHHDEHAEBADDGDBGDEEDECDFCAFEEFEDDHDCGAHBAGBDEADGHEFDFABCEBFGBCABCFGCFACGDHDEHACACCAFGF,False +835,20.0,10.0,18.0,14.0,16.0,28.0,23.0,12.0,CBFFGFCHEDBFHGFEGFEGFEDCEDAEHAGGGGFGGCCCDGCFGCFHAFBAFBDFCFFHAAGCEGAEGHEGDFAFFCDFADECHEAHGFGEHGEBDDBABFABABECHCFGCDDFFGFAACAAEDHGGHECDBAFCAFAF,False +836,30.0,20.0,19.0,16.0,19.0,13.0,25.0,21.0,GEHGEGBFGFCGFAGHHGFGGFDHAAHECBAGGAGHCGBCABFHBECAAHAFCEBCEACEADDADCGHBDHGFEDBCAEGAHGHCGHCGEBBHGDHEDHDFBEBBFADEAHEACBAEGFDCAABAABAABGAEACHBHDGADHAEBACHDGDAGCEDCEFCBF,False +837,11.0,6.0,11.0,21.0,12.0,11.0,14.0,20.0,CCGFFHDFDCHECHGCEGCGGDDGABGAEHDEHGGHGHDDHDABDHBHFFGEFHDAEDFEDFGFAHHHCFHAEDGEHCHFDADDGDBADAHDAHDCDCCBEHBEAE,False +838,2.0,11.0,5.0,5.0,5.0,11.0,2.0,7.0,HHAFDBFCBFHBFCBHCFEBHEBCFBFEBEHBDDDEDCABBFFGFFGH,True +839,10.0,18.0,12.0,15.0,22.0,22.0,14.0,20.0,GHGGHDGHEHCFHBHHGHGFDFFBHGBDFBCFBFEBAHAACAEBAFCEFHEABGAHCBCCADAEHFDHFEFFEHFEHCECGHFEBFGCFDBBDBDDCEDEEDEEFBFFGDBBEBGEAEHFDCEGEEDHGDHBF,False +840,6.0,5.0,3.0,4.0,8.0,4.0,5.0,6.0,HFAHFAGABEEHFEBBEABCGBGAFGAECDEDHEHHEDGDC,False +841,22.0,25.0,12.0,20.0,30.0,18.0,24.0,19.0,CFDABGGBGGDGGBGDBGDFEHGEHAEDEEDEEAEGABBABHABFEGAAAAFAAGHFEEEAHFBBFBDHEHAGHADHFDHEDHEDCFAHFEHGEHEEHCBBDBBGBGEBCEBFEHDCFAGFECABGDHEFFEBEACCHEGEGCAFDACECDGDBHEFCGFGGBBBDBDDA,False +842,26.0,32.0,18.0,28.0,33.0,16.0,26.0,21.0,BDFEACGAHGEHBEFBDDCDDEBGFBAHCGBBGCEDEHBAFGGFBDFDABCCBFCBHEBEAFGAEGFEGEDGAABBHBDCAAEAEEBEBGDGGDGHDHHCACBEGGDHADHGEFEBDEBDHBDHBEHBHDDCDFCDCGAGGEGGEGFECAEABEAHDAHCFFCDHAAHAACAABFEEEBDEBDGBDBCEEHDBGEBEAHF,False +843,17.0,15.0,21.0,18.0,10.0,19.0,19.0,11.0,GCGCCGCDBAAFCFFCGCCFCBGCBHBGADGFEEEBEDCFDCFBEFAEGDDDDDAGACDEFDBFGCFGEFDDHCGGGGGAFACHACHACGADGHHCHBFAAFDFFDABBEBFHBHEBHCAHBADGABFDC,False +844,28.0,20.0,25.0,32.0,29.0,10.0,34.0,16.0,GCBGCEAHBHHGHCGADBHDGAFGCFEEFDEAABAAFACGACHAGEEEEEBDBDDGEAEBGCFGAFGCGACGAGFEDAGDAGDBGDFEBECDGBDHBDBBDAEHADAAHGDCGDEBAHBEDCGBEGHEDHCCEDDEDCEGCDHDACAABADGEEFCEFGGAHGCCGCBECECBDHDCADAGDGGDGGDECHEBD,False +845,9.0,18.0,18.0,15.0,16.0,16.0,18.0,30.0,FHHFCHBCEBFEBFBHCGHEGFEDEHABHBHCEHCGGEGGCGGDGHDFHBFHAGACEDBBBBBFHEDHAHHBHEGHEHFDHEBHDDHCDCDHCACADBHDAAEGHFCCECCFHHBHGDHCDHFDGFBGFGGECAFBFCEG,False +846,25.0,21.0,20.0,25.0,14.0,20.0,19.0,27.0,DHHAHHGHBEBFFBHACHBCHFEAFHAGEAGEDFFDHACGDCGEBDDBGEAFAAGAAHAAFCFDCAEFBEGHGDCFAEDABDABHGBHGFHFDGDDGDDHFBABCADDACHBCHCGECACDBCGBCFHEHCCBBHHHFHFBHECEDHDAHDFDDFBBFDBEGACGACGADG,False +847,19.0,22.0,26.0,32.0,24.0,20.0,17.0,30.0,FFFFFBEBBCDDHBEHDHHFHCDHCDBCDAFBHDGHDECDEDGEDCBFEFEHAHHAEDBDGHDCHECDEFHHADHCHBCHCDDCHBBHBEECCDFEDFDBGDBDFBEBAEFAHAGFECCACDHCEHCGGCGGCAGABCAGAGCDBADGEDFEGAEGAEHACHCBHABDBEDEDDHADGGFBFFHEFHCAH,False +848,9.0,6.0,11.0,10.0,14.0,15.0,7.0,8.0,EBECBHGDFECFDGFDHFDCEAAGDEFDEFDFFHCAHGBDDHDHFEGEGBAFCEFCAFCACCACBAFHFEHEEFEGAEBC,False +849,4.0,12.0,3.0,4.0,4.0,6.0,9.0,4.0,BADBFBBDBCDAGGEGGAHFBHFECBBGGCGGBBGBDFFHFEHAEB,True +850,11.0,16.0,15.0,13.0,9.0,18.0,8.0,14.0,AHEFHEDHAHCBEFAEABEBBDHGAGCECCECCEDGADFFBFFBFFACACDFCDECHHFDFFHFFGFBAHBCDBGDBGHHGHFBDBHDBCCFHDACABDGBCBF,False +851,14.0,6.0,9.0,8.0,8.0,11.0,8.0,4.0,CADAAFAFGGBDGBECHEGAEGCEGHEAFCGCCAFCAFDBEHBAAAFAFFECEDADGACFBDFHDFBD,False +852,13.0,17.0,14.0,11.0,14.0,23.0,28.0,19.0,AHFBHFEDBHCBHGDHDDBEFGAFBEDCEDCGGCAGCHGCHGCDCEEGFBBFHCGHAGDCFEGABFCBECBAFBAFHHGHEBCFAEGGEGAFBFGGGDGBDBFAEEBGAGHAFHCFHFFAGFHGFHFFHGGBGGHDGFE,False +853,17.0,14.0,15.0,18.0,12.0,25.0,14.0,18.0,FEEDCEDAEDABFABGHCGEGBAFBAFADFDDFBDFGDGEEAEHDGHCFHCHGBHFHFACAEBGHHGHAGAAFFDCCDHCGGCFDCFHCGECADCFDBFEBFBDGHDCHCHDAFFFHFBBEAFADFHBFHFAB,False +854,4.0,8.0,7.0,9.0,7.0,13.0,4.0,5.0,HAHBAEBCEFDHFGBFDDFDDFCGFBBCBFCFFCAFEDFBCGCDGEHEEDFDHFEBA,False +855,8.0,9.0,7.0,8.0,14.0,11.0,8.0,11.0,FCGGHEGHCAHEGDGCDHEBHEGEEFAEFCEAAFAHDEHFEHBGFBFFBFEAHEADCBBCBBCEGDDHFDFBHEAD,False +856,15.0,19.0,19.0,21.0,20.0,23.0,9.0,21.0,EHCABCEDCEDCHDBADEFFEAHGADFHBFEBFEHFEGCHGBBFBDFDCFHCFCGHCDHEHADFFEFHCGHCBABEEBEFBCDBCEHDACDBBDCBACBAEBDDCADFAEFEEHDGHDEEFBFFDHGHFGAFAHFCGFHBHDADAHC,False +857,8.0,14.0,12.0,26.0,12.0,12.0,24.0,18.0,DDGDGFHGDEEDEHGEDDCHGCAGDGBBHHAHDBHDBGACHCCHFCHGGHDGHDBFABCHGHGFDCEAGEADEGDADEGHBCFBGFGDCGBFDFFDCBDCGDGBEGBFGEHHEFHDFGDAEDBDDB,False +858,3.0,12.0,7.0,10.0,7.0,11.0,5.0,6.0,EHBFDFFCEGCEBFAFCCFECFHDGCEHAEFDBFDBAHBGHBGEBCDFDDFBDBDGBHBBD,False +859,15.0,8.0,5.0,5.0,11.0,6.0,8.0,9.0,AFHEGGEGBEDBACAADADGGHGFEGCEHCDAFECBBABHHEHAECFHBAHGABDEBAEFAEFAHAA,False +860,24.0,23.0,16.0,29.0,25.0,13.0,28.0,31.0,ABDBGHHDBEAACAHBDDDDHHGAHBDHDAHCGHCAEGFECFECGHAGBBDBDDBDGBDBAEBACDAHDBGDBCEBGEDDEBDBBABGGGGGEHAEGGGDFHDAHAHFAFDCHDCHEFBEAGECHFCHGGEGGAGFDHADEGHAFHBGHEFBCAGCAEBHEDHEDEEDFEGFHCEHDHHFCHEAGECHA,False +861,19.0,16.0,16.0,18.0,22.0,19.0,15.0,18.0,HBDHADGAFFFCFDCFDHFAEEDEEABBABHHEAEDAHDEHCGFEECHECEFGHFDHFEEGCBDFDGHDGHDCBDCAECAHBACGEFBFFAFBAFBEDHDAHBBDGEGCEGBGDFGAFGAHCHGFECAEGABAHBACBECECD,False +862,23.0,28.0,34.0,23.0,21.0,19.0,19.0,23.0,AADEFDECBCFBFEGCHHCBCAHCAEDAEDFGBAHBGBBGEDGEFBAFBABEABFAHFAHADGBHAAHAAHCFCAECBEHBACDDCDCHDHHDAHDAHCFBCDHCBBGDEDEHFBCCCCCDGEDEEBCBHCDEBEHBCGCDECGCCGBCGBCFAGGACBHBFCAGCFBDHBFHFECFGHEGCEFDDFGDG,False +863,11.0,5.0,11.0,10.0,13.0,17.0,9.0,9.0,HGFAGHEGFFAEFGCHCCHCFACEAFEAFBFFBEEDDDGGDFEBHDFEDFEFCEHCDAAFBAFHCFECHEDDABDAGCCGAHGEF,False +864,8.0,4.0,8.0,5.0,6.0,11.0,2.0,13.0,CGDDADAFHFEHACHFFHAFHAGABEFBHHCHFCFBEHCEHDEFDCFEFHCAHCAHB,True +865,6.0,7.0,13.0,8.0,5.0,5.0,10.0,8.0,EBBEADDABHGBFBHDAHDFCCCCCGDCGACEFCEGCGGCDHHBGHCGCGBFDDFEAHCAHG,False +866,13.0,18.0,13.0,24.0,13.0,21.0,16.0,22.0,CECHEHGAHDBHAACGDDGDDGBGFBACBAFGCFGEBHHBHBBFBBFGDFEBHDBAEEAGEHFEDGEDFFHFADDADFHCHEADCFDBEDCDDFFBFFHFGEFGHCDFBHADHFDHFHCGCAGDACEBDHBDGDHGCHBH,False +867,3.0,4.0,1.0,1.0,0.0,0.0,2.0,1.0,BGHBGBAABACD,True +868,12.0,15.0,8.0,11.0,24.0,11.0,16.0,16.0,GBGAFGAHEABDAHEEHEGHFBEGHCHHCBDFECAADDGHFHFGEAGEBCDGEDBEFEEFGDGGAHGDHEEHBEHGEAGECGEAHECHBBEFBHBBDBBDCBFEFEEFECAAD,False +869,14.0,6.0,19.0,11.0,20.0,15.0,11.0,18.0,AFHAEHAEHGFHACHADFFGGFEGFEGDEDBAFBDECHHGHCCDBCFECHCHFBEDEECHACDGFDCHCEHFHCFACEACEACBCGBGEADECEEGFEHFACEDHEDHAGHFCA,False +870,7.0,10.0,10.0,16.0,6.0,4.0,11.0,16.0,HCBDCBHCBACDCCDHFHAGHCCDECGEDGDAFHGHGBDDFADHGDHBDHBGHFHEAABGBDHEDHEHHEGDDGADGCBB,False +871,6.0,1.0,1.0,3.0,2.0,4.0,9.0,6.0,AHCGEDGAHEAHAFGAGGBHGAHGFGDFGFHD,True +872,3.0,5.0,3.0,3.0,6.0,1.0,1.0,2.0,BBBDCBEGHEFHDBADAECAECEE,True +873,2.0,1.0,1.0,2.0,5.0,1.0,2.0,3.0,HEGAEHAEBCFDEHDEG,True +874,7.0,21.0,14.0,14.0,9.0,12.0,13.0,10.0,FDBFBBDBADBHBAGDHHCGEFDEBGEGGFGBCGEADAGGADHBDFCDECGBCEDFHFGHFEAFGHEDCEDCBFCBCCBHBBHBBDCBFGBCBHDBCAFC,False +875,6.0,6.0,10.0,12.0,5.0,8.0,13.0,6.0,GCGGCGGHBFDDADDBDFBDGCFGAEGAFBBCBHHFDHADHAGCDGEDEFGGCECCHDCEACGDFF,False +876,19.0,14.0,14.0,17.0,5.0,8.0,26.0,9.0,ADBACAGCHGCFGHDADABGEDABDABAFGCFDCADGGGGGGGGGBGGBACCHHAAGAADAGDAGDCGDBFFBCFBEBCEBGBBHEGDDCCCBHHAFGDGADGDDAFCGHHE,True +877,11.0,23.0,26.0,15.0,25.0,13.0,27.0,20.0,DHHEHGFGGCEHCGDGEDHCDHBFEDFEAFHBDGFCBHCEECEECBHCACGACACHGBHGBGGECGBDHCFEEEHCGHCGHCEBEFBGABCDDEGGEGGEGFEDBEBBGBCGBHABGEDCABCFECAHHBBCBDCAGBDGBAGCAHFHEBCEGCDFFDEF,False +878,10.0,21.0,12.0,20.0,16.0,27.0,18.0,16.0,EGCEHFAFAEBBGACGEEDEBDEFDBBDCBDEDFFAFGHBDFBHBGHBEBEGDDGDGBHGBHBFFGDFCFGCFAEGHEDEEDEAFFFFFFCHGGDGAFGAFHDBHEBCAGHBFDFFBHFCHFCHCCDCFDHBDGBDBHFA,False +879,13.0,7.0,15.0,3.0,11.0,11.0,9.0,9.0,CHBCFBFGEFEHCCAFAAFCEECBBHEEGEFBEABAADGAGGFGFCGACEHCHCFECADCACCACFAHFHDGHGAHEB,False +880,18.0,17.0,11.0,7.0,12.0,11.0,12.0,19.0,GACGHHGCCDAEAEBAFGHFGHEHABHBDHGCHGCHBABEEBECDDBABBHFHGCBGCBFAAGDAGHHHCAFCABAABAABHAFDAFBGDCHFEBEEHEFHEFBFHE,False +881,15.0,14.0,12.0,18.0,16.0,16.0,10.0,24.0,EFDEFDHBEHAEFFBHEBGEFABHGEHDFHAFEBCDGDAFDAHAACDACDGCEHDBBBBHDHEAEFAHGDFDABHABHAEHFEHFHHFHBFHAFHAEDCGBGGDDHDEHCBCCHCEFDGGHCDCC,False +882,1.0,3.0,4.0,5.0,7.0,5.0,2.0,5.0,HDHBCGDFACFECFEFBDFDGHEEHEBHEDCE,True +883,10.0,19.0,13.0,15.0,16.0,14.0,11.0,10.0,FDEBDAHCBEFHFHGGHGEBGCHCEECDACEFBAFHCBCEBAGBFGCEGBEHDDHBDHCDAFDEBDFBDEADBADBAECAGDABCGDCFBGFBDFBEFBFGBEHEECF,False +884,4.0,20.0,14.0,12.0,17.0,18.0,12.0,16.0,DHCFHCBHGFHFEDFEDBCDBFHHGCDFADCGHFBDCBDHAGEFBEHBEDCEGCABFHBHCCCCBHCGGFGFFBFBBEGFEBBBCGEGHHHFDAFDEFBEFHEGDEBEEBEEB,False +885,4.0,5.0,7.0,5.0,3.0,5.0,11.0,4.0,GBBEAFCABHGBGEFGDDCBDCFGCAGCDGCGHEGHFCHFGAGD,False +886,4.0,2.0,5.0,6.0,4.0,7.0,8.0,6.0,DEGFEGHBGCGHBGHDFAFFAFDADGCHECDECFFCHADHGG,False +887,7.0,10.0,2.0,12.0,7.0,8.0,10.0,7.0,HDGHAEDCDDBGDBAEBGCBDAEGFGFBGFBDDBFHBEHADFGDFHHFHEDGADGAFEAGEBB,False +888,22.0,21.0,26.0,15.0,24.0,25.0,19.0,23.0,HFHEFEAADAGDBCEBGEBEFHEGHAGEDGADFEBFCBFBBFCEHADFEHGHHFDFCHFCHDBGDHAAHFCFAEBAEGCEGCFFAHHGHHFHHCHCBABGDHHDFABGCFACFECDEAGEAGFBCFGCEGCBBBEBAGHGGCBAFACFDCDDCFCAHCACCBEEBEEBEADCCEF,False +889,14.0,18.0,14.0,7.0,16.0,10.0,10.0,16.0,FHAHHEDDECCCHBCBBFBFCBACDAGHAGHBFHBCHBEGEEGBBGBBGEAEAHHBEFFEAFEDHECEEGABGBDGCABEABAFCHCAACGBHHAHCDHFECFED,False +890,18.0,20.0,25.0,21.0,23.0,27.0,22.0,23.0,ECFEGEBFABFABCDBFHBHABHBDHGFGBFGECGCFHADHDEACCBHFEGFACHECHFBACCCBEBBDFDAEAABDAECCCFCFFCFFCEGCHBEGDEDFBDEGHFCHFCFDCFEGGEGDDGHDHHCGHFDFBDHGHHAAHAEHFGAFGAEADEFCEFBEGBGGHDAEDCEHCDGBDG,False +891,21.0,17.0,16.0,20.0,21.0,17.0,22.0,30.0,GEDGFABBHBBHFAGAEEAEAAECAEHHHBDDCABHGGHGCBAAFABFBFCGEBFEGEHHEHHDDHFGEEHDGHCAHFADBADCCGACHDGHAGHAFHAFBECBEDHGCHGAHGBDCEDCDBFDEGHGADGDHGFHCDGDFHBHHBHAECFECFEGFHFEDCED,False +892,2.0,4.0,1.0,8.0,1.0,2.0,5.0,5.0,HHHHBDABDGBDFFDCAHGGGBDGDDED,True +893,15.0,5.0,9.0,8.0,9.0,2.0,15.0,5.0,GGEGEEDAFGECACCAGFGEEDECDBAEGADGABAACCACCAHGAHADHGDGGHGBACBHBDEGAAGD,True +894,15.0,20.0,23.0,20.0,17.0,18.0,26.0,16.0,FGDFCFCCGBFEBEEDACGECGHCFFEDBBCHBFHBDAFHBGCFCCFAGHDGDGGBFEEGCEGAFGAEAFEDFEDBBDHBHGGGGCFDCEHBEHGCAAAAAGHCHHCHBGDDCDBGBBCABCABADBADBFDGGCCEDEEDGCGGDDGHCFHEFH,False +895,17.0,14.0,14.0,9.0,18.0,14.0,9.0,18.0,BGCDCCFADADBGDGCAEEAGEBEFBHHAEFFEHFEBEBCGCEBCEDAGGAHEABEABDAFDHBHHAAHBAHAHBAHCEHCAHFHBEHFCFFCEFCEHCHHCAEDFEDBGFGF,False +896,10.0,10.0,7.0,13.0,14.0,14.0,10.0,8.0,HCBCDHHGEAFHFCDGHEBDEAFBCFEDFADEADEADABBHCAEDGDDGFDAFHHFDGFGGFABFBCDBCEAGBBGEFGEFEEFEE,False +897,1.0,6.0,2.0,6.0,4.0,12.0,5.0,5.0,FBDGCGGDFEBFEFFEGFBGFHFFDFHBAHFEDFCHBBHDD,True +898,8.0,2.0,6.0,2.0,1.0,5.0,2.0,3.0,CFFCHDCFEHHAADAACCABAACGAFGBF,True +899,13.0,11.0,11.0,13.0,12.0,11.0,12.0,9.0,FCCGCABEBEEFCBGCDGCAECEEHAEGDCFFHDBCABDABEAFCBHABHADHGDFGDFBDFEDGHBGDGDAGAFECHEGDEGHFAHDABAF,False +900,11.0,8.0,16.0,15.0,15.0,12.0,12.0,10.0,HFDECDECFHCHGDEDEEBGHDAHDABCCDDFGDCGBCACCDGGFCGFEHEAGEAGEAFCCHCCAFEAFADEADHGDBFBBFBBFGCEAHFCDEEDHEG,False +901,6.0,5.0,13.0,12.0,14.0,4.0,0.0,2.0,DEEDEFCACAAEHEECDECAHCBDDECCBCFFDBFBCDECEECEDCADEDDEDACB,True +902,5.0,2.0,3.0,0.0,2.0,4.0,3.0,0.0,CFECFBAGAACAAGFFGBE,True +903,1.0,3.0,5.0,2.0,2.0,3.0,3.0,5.0,HEAGEFBCDBCBCFHCFHCDHGHG,False +904,8.0,10.0,8.0,10.0,10.0,10.0,8.0,8.0,HAEHAEDAEDGHFGFFAFFBFFGDABDECDEGGEGHBHBBCCFEDGECBCCBACHDCAFBDDEEDAHGBHBF,False +905,19.0,35.0,22.0,16.0,17.0,18.0,22.0,17.0,BEDEDGGBEBBDBGHBCBBCBHCAEAHBAGBCBHDBHDCHGCBGDAGDCCAGDGCDFCBFCBDBBDHAAEAGEGGEGBAFBHFGFGBFHEACECCGHCFFEFBCFBAFAABBBBBHDBEFBHFAGBEFCDGCFCDEEHBBFBDCGDEGFHGACAACAHHFGHEABE,False +906,6.0,6.0,11.0,1.0,5.0,2.0,8.0,3.0,GGECBACGCCGHCBFEGGAACAACDACBBCHCEFCEHBEGBG,True +907,10.0,11.0,15.0,22.0,12.0,15.0,10.0,11.0,CBDCFAHHHHCHDBDDBEDHCAECDFFDACDGBDABCFBCFBGDCFFCFEEHGGHGADGDFAFACGDCADFBCFGDFEDFDDADGAHEBHFCHDCDEEBEEDEGBE,False +908,4.0,0.0,2.0,5.0,3.0,0.0,2.0,3.0,GHACDADAEDAEDEGDHHC,True +909,1.0,4.0,0.0,5.0,2.0,3.0,1.0,1.0,FDHBDABFEBDDBDEGF,True +910,9.0,19.0,26.0,20.0,13.0,12.0,16.0,22.0,BHDCHGCHBCHDCBGCAEDFEBFBHDBHDGHEGECGCFDCHHGHHBHGFGCCBCCDCHAADFFDFFHEDCFBCEHCEHCDDFAGECGDBDBGFGEECBHCBACBACHCDEFDAHBCHCEGBGGCDDHDEHBAGBADB,False +911,5.0,1.0,2.0,3.0,2.0,3.0,0.0,2.0,HAHAADAFBAFEFCEDCD,True +912,26.0,20.0,25.0,15.0,11.0,21.0,19.0,28.0,BGFDDHABFAGCACFBCDBGDCCAAAHAAHFCHCEGGFFHHFBCABCGGGGBHEAHCAHBAHAHHACHFDHDAHABHCBFEBFADFGDCGFFHCGBCFBDFEDCHBBHBCGECGEHGFHAEHACHADAABHFDECEGBAGDHFDHCCFGAEGAECABFFBHCCHD,False +913,7.0,7.0,5.0,3.0,0.0,6.0,1.0,6.0,CDFCAFHACADCBBHBFHBFHFDGCABBABFHHAA,True +914,20.0,24.0,25.0,24.0,19.0,23.0,23.0,19.0,BDHFDGCHCAHFAHFGGCHBCHDFEDAEHCBFEBCGHCGFEACCAHDFGDFDBFBEFBEBGDBGDBCDECBFHEEEBCGBDDFDECHEHBFCAFADGADAHFCFFGFAGFEGEHGADDHDCHDBDDGEDBHABGGBEGBAHBHBDCFDCACCGEAACCACGAEGBEFBAFCCFGBAG,False +915,6.0,10.0,1.0,9.0,16.0,12.0,5.0,11.0,BFGFHGADDEEEEBEEHEHHEHFEBEGHFDHFBHFBDFDFFEBGDHCEBEEBEAGDADHAFAAFHBBEDF,True +916,19.0,25.0,17.0,15.0,26.0,25.0,27.0,16.0,EBBHBCGEEAEBCECGECHHCGDCECGECDBCDBAGCHGBFDBDBCEBFAAGAAHBGDFGAEGAEHEEHECGFFAFBEEAEEABEHBGHBFHDGCCFEFFCFFGFDHBAHAGFDGFDGHGGEDGEBGHGFFECBAFBHGEFBFGDFHDAADGGBAGBFCBFDEFAFBABE,False +917,1.0,1.0,0.0,2.0,5.0,1.0,1.0,0.0,DABDEEEEGFE,True +918,3.0,4.0,4.0,5.0,6.0,2.0,1.0,2.0,FCHDCBDCDEADEBDEBFBGACAEHEE,True +919,29.0,30.0,27.0,23.0,18.0,16.0,15.0,25.0,CECCDDBFGBEHCFACFCCAAAAABGDBDCBDABFBCEACABCGBHGDCGFBGHCDHCEHCBAFBFGHFHHDHFEHFEHCDBDDACBACGACGACFEDEBDHBDHAAEEGFBHHBHDAHBGBCGDAAHAFEBCCBDBEEAHEHFGHAHAABBABDHBDADDAECGBCEDCDCGEHAEHABBFF,False +920,6.0,8.0,6.0,2.0,10.0,1.0,2.0,2.0,ABABBFGBDGEECCEACECHEHBEABDBEEEACEACB,True +921,9.0,6.0,2.0,9.0,10.0,5.0,13.0,15.0,EBEDHGAHGFHGFBDEDDGCDGDHFAEABEGEGAHGAFEAGHAHHEHDEHDABDBGEGGBGHHACHFHH,True +922,0.0,4.0,4.0,4.0,5.0,3.0,8.0,5.0,BFCBHEBHDBCDFGGEGFEGEHGHCDHGDGGEC,False +923,9.0,18.0,18.0,28.0,20.0,33.0,20.0,19.0,FCFHEFDEBCBBCFACFDCDCAFCAHBDHBFGFHAFEAFEHGCHGDHCDHCFCGDCHBEGFFGDFGBHGDFGDFGFAHDBGGHHABEDFFDFFDFFEBFHDCEDFEFHEHHDGACFFGHBBHBADDDDCDEGDGGCEFCDBEBGEDEEBCEFGFFBEDGEDBFDE,False +924,2.0,5.0,0.0,7.0,6.0,1.0,0.0,3.0,EEDEEHEBAEBDDDADBHDFHBBD,True +925,12.0,20.0,17.0,18.0,18.0,15.0,13.0,21.0,GHHFHBACCFFHHFHHABHGDHFDEBABDDBCAEHABDEDCGDGDDGCDFFDHEBAEBAEBDCBGCEGBEHBFCEFDBGBFGBHBHHFFEEGECGECGECBHGBHDCHDAFDCFDEAHAHEAHACCEEFBBDCC,False 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+976,27.0,32.0,25.0,20.0,17.0,19.0,24.0,36.0,HCFABFDBGEFGFDCBDCAEBHEDADCADCGBCDACDBBHBBDAHAHHFFGEFHHBBHEFAEDHEHHBHHDAHCACCDDDAHCEECBBHBHHBGDBGBBGHCAHCFHFHGCHGAEGFFBBHCBHAAABACEGCGGCGACFACGHBDCBHCGGEHEBGAFFAEHHDFHDFEGFABDABGBBECBEBGAAFAACGHGHHGDH,False +977,21.0,23.0,33.0,29.0,26.0,21.0,26.0,19.0,BFCBCBEGFEGDEGFEBDACFGCDGADCDDCBBCGCDDCGCCGDDGBFBEEBAABAACFCCFHDDHDEBDEFCEBBGBEEDAEAHFCHFHHEBEEFFEFHEADEGEGGCGGADDFBCADDDCCGCCGCDGEDFADGDFGFFBCAAHAHEFHECAGFGDCEDCADBAHHHHEHHEFHBCCCCBBAABCAHHDGBEGCGG,False +978,7.0,8.0,10.0,5.0,10.0,5.0,5.0,1.0,DECDEBFCGFADFEBAECABABEGGECDFCGBEGCEHCBDCBCABCAEAFE,True +979,1.0,2.0,1.0,6.0,0.0,1.0,0.0,1.0,DCADFBDHDDBD,True +980,24.0,21.0,18.0,12.0,17.0,7.0,12.0,18.0,BBAHBHDDHBHFAHACBEBBCBAEEACHAHHEGBBGBCDCCAECAHCAGGAFFACFAHHEEAEHFGCACEACHFCHDDEDDEDDCBCCHEBHBAHEABBGBBADBGBBEAAGAADHEGEGGEGAFDACC,False +981,22.0,33.0,18.0,23.0,27.0,28.0,28.0,13.0,EAEDGBCFBAFBGFDAFAAGHAEBFHFFHFFGACDBDFCDFGDBEBBDHCFBEEGGDAGECGEFABFGBEDAEAHEGDDBEGCDABHBBGBDFBDHBGBBEBBHABAABDCEFGAFGAFBFCEFBGGHAGAFEDGEDCHFHBFGDHCFHCAGFDGCGECFECBECBECECABCAEFBEFEEGDBGDEGDBGD,False +982,22.0,20.0,15.0,16.0,27.0,17.0,27.0,21.0,GDFGHEGBEHCEBCHBEHBAHGCGGEGBBFDEADFFHADHEBHGDACDACDEBEEGEHBEGBEGHEBFAAFGFFGDFGDFABGHFHCEECHDGBDCBFFBGCBDDHDCGBCFAFHGGHEGACHECAEAAHCABAACAHEEDEADEFEGBGGEGAAGEBGFAHHAE,False +983,6.0,5.0,6.0,11.0,8.0,8.0,5.0,7.0,HBFHDFCEABBADECDEGDFCDFHBFEDECCFGHFAHGHHADEADFCDGDDGEBAE,False +984,9.0,13.0,13.0,13.0,32.0,25.0,15.0,18.0,EEAEEGEABEGHGFDADEEFAHHCBFGDCBBCHBCFDCFDCFDEFDEFCHFEFECFEHFHGFHGFHEBBCGECBDHHEEDEFCEGAADEFEHGEDFEHFEDFEGBHHFHGEEGEGAACFABFGFDGBEECEEFHBFHB,False +985,14.0,10.0,10.0,7.0,7.0,11.0,13.0,6.0,FAFAHGABAACAAGAFCDDCGCEFDBGBGACHECAECAEBAHDDFDBFDBFGBAGCHBEHBAGBECFFCEFGGGGGFH,False 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100644 --- a/README.md +++ b/README.md @@ -1,36 +1,10 @@ -# N-Back Sequence Generator with [Hidden] Markov Chain +# N-Back Sequence Generators -**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/src/main/scala/org/xcit/nback/markov/models/State.scala b/src/main/scala/org/xcit/nback/markov/models/State.scala deleted file mode 100644 index fbbd844..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/State.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * A Single state with a label in Markov chain - * @param label A simple string label, representing the state and node - */ -class State(val label: String) { - - /** - * Keep track of transitions from this state to other states. - */ - val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() -} diff --git a/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/src/main/scala/org/xcit/nback/markov/models/Transition.scala deleted file mode 100644 index bc20a9e..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/Transition.scala +++ /dev/null @@ -1,8 +0,0 @@ -package org.xcit.nback.markov.models - -/** - * A Single transition in Markov chain graph. It is stored in "from" node. - * @param to the ending node of the edge - * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). - */ -case class Transition(to: State, probability: Double = 0.0) diff --git a/src/test/scala/ThreeBackBenchmark.scala b/src/test/scala/ThreeBackBenchmark.scala deleted file mode 100644 index 0c7dad9..0000000 --- a/src/test/scala/ThreeBackBenchmark.scala +++ /dev/null @@ -1,7 +0,0 @@ - -/** - * TODO Benchmark 3-back simple sequence generator - */ -class ThreeBackBenchmark { - -} diff --git a/tests/benchmark_diagrams.py b/tests/benchmark_diagrams.py new file mode 100644 index 0000000..8fa448e --- /dev/null +++ b/tests/benchmark_diagrams.py @@ -0,0 +1,159 @@ +import pandas as pd +import numpy as np +from matplotlib import pyplot as plt + +import benchmarks.common as common + + +def tlratio(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2,ignore_index=True) + stats = [] + for trials in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == trials) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == trials) + targets2 = data[alg2].targets if alg2.shape[0] > 0 else np.nan + targets4 = data[alg4].targets if alg4.shape[0] > 0 else np.nan + lures2 = data[alg2].lures if alg2.shape[0] > 0 else np.nan + lures4 = data[alg4].lures if alg4.shape[0] > 0 else np.nan + stats.append([trials, (targets2/lures2).mean(), (targets4/lures4).mean()]) + stats = pd.DataFrame(stats, columns=['trials', 'tl2', 'tl4']) #.dropna(subset=['skewness']) + + plt.style.use('ggplot') + + plt.ylim(bottom=0, top=30) + plt.scatter(stats.trials, stats.tl2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl2[idx], 1)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.tl4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl4[idx], 2)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('T:L Ratio') + plt.ylabel('T:L Ratio') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_tlratio.png', bbox_inches='tight') + plt.show() + + +def time_per_trial(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for t in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == t) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == t) + time2 = data[alg2].time.mean() * 1000 if alg2.shape[0] > 0 else np.nan + time4 = data[alg4].time.mean() * 1000 if alg4.shape[0] > 0 else np.nan + stats.append([t, time2, time4]) + stats = pd.DataFrame(stats, columns=['trials', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.trials, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time2[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time4[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2v4_time_trials.png', bbox_inches='tight') + plt.show() + +def time_profiles(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 8): + alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + time2 = data[alg2].time.mean() * 1000 + time4 = data[alg4].time.mean() * 1000 + stats.append([ni, time2, time4]) + stats = pd.DataFrame(stats, columns=['n', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.n, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.time2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + plt.scatter(stats.n, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.time4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_time_n.png', bbox_inches='tight') + plt.show() + +def skewness(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 9): + all_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + skewed_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) & data.skewed + all_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + skewed_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) & data.skewed + num_of_sequences2 = data[all_alg2].shape[0] + skewed_sequences2 = data[skewed_alg2].shape[0] + num_of_sequences4 = data[all_alg4].shape[0] + skewed_sequences4 = data[skewed_alg4].shape[0] + skewness2 = skewed_sequences2 * 100.0 / num_of_sequences2 if (num_of_sequences2>0) else 0 + skewness4 = skewed_sequences4 * 100.0 / num_of_sequences4 if (num_of_sequences4>0) else 0 + stats.append([ni, skewness2, skewness4]) + stats = pd.DataFrame(stats, columns=['n', 'skewness2', 'skewness4']) #.dropna(subset=['skewness']) + + + plt.style.use('ggplot') + plt.scatter(stats.n, stats.skewness2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.skewness2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + + plt.scatter(stats.n, stats.skewness4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.skewness4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Skewness') + plt.ylabel('Skewed Blocks (%)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_skewness.png', bbox_inches='tight') + plt.show() + +if __name__ == "__main__": + tlratio() + skewness() + time_profiles() + time_per_trial() diff --git a/tests/benchmark_skewness.py b/tests/benchmark_skewness.py new file mode 100644 index 0000000..f468b4d --- /dev/null +++ b/tests/benchmark_skewness.py @@ -0,0 +1,97 @@ +import random +import heapq +import csv + +# Common parameters +alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'] +trials_range = (10, 40) +n = 3 +sample_size = 100 + + +def to_benchmark_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [str(ralph_skewed)] + +def benchmark_nb_gm_001(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_001') + + +def benchmark_nb_gm_002(filename): + import generators.nb_gm_002 as nb_gm_002 + + generator = nb_gm_002.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + # print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_002') + + +def benchmark_nb_gm_003(filename): + import generators.nb_gm_003 as nb_gm_003 + + generator = nb_gm_003.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + print(f"sequence {i}/{sample_size}: {trials} trials") + seq = generator.generate(trials) + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_003') + + +def show_skweness_diagram(filename, choices, title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + print(filename) + data = pd.read_csv(filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) #.dropna(subset=['skewness']) + #print(stats.trials) + #plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'{title}.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + benchmark_nb_gm_003('../benchmarks/nb_gm_003_2back.csv') diff --git a/tests/common.py b/tests/common.py new file mode 100644 index 0000000..e40c0df --- /dev/null +++ b/tests/common.py @@ -0,0 +1,27 @@ + + +# Common benchmark parameters +choices = alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F'] +trials_range = (10, 65) +n = 4 +sample_size = 100 + + +def count_targets_and_lures(seq, n): + mask = 'D'*n + for index in range(n, len(seq)): + if seq[index] == seq[index - n]: + mask += 'T' + elif seq[index] in seq[index - n - 1:index - n + 1]: + mask += 'L' + else: + mask += 'D' + return mask.count('T'), mask.count('L') + + +def skewness(seq, choices): + import heapq + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return ralph_skewed diff --git a/tests/nb_gm_001_bm.py b/tests/nb_gm_001_bm.py new file mode 100644 index 0000000..54f6cb3 --- /dev/null +++ b/tests/nb_gm_001_bm.py @@ -0,0 +1,75 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq) , str(ralph_skewed)] + + +def benchmark(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets / s.trials, axis=1) + plt.scatter(data.trials, data.targets_ratio, alpha=0.2) + plt.show() + +if __name__ == '__main__': + alg = 'nb_gm_001' + fn = f'results/{alg}_{n}back.csv' + benchmark(fn) + # skewness_diagram(fn, alg) + targets_ratio_diagram(fn, alg) diff --git a/tests/nb_gm_002_bm.py b/tests/nb_gm_002_bm.py new file mode 100644 index 0000000..c8af543 --- /dev/null +++ b/tests/nb_gm_002_bm.py @@ -0,0 +1,105 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq), str(ralph_skewed)] + + +def benchmark(filename): + from generators.nb_gm_002 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials, int(trials/3), 0, 0) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +import time +import numpy as np +import pandas as pd + +import benchmarks.common as common + +def profile(): + from generators.nb_gm_002 import SequenceGenerator + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, int(lures/2), int(lures/2)) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('benchmarks/results/nb_gm_002_profile.csv', sep=',', encoding='utf-8') + +if __name__ == '__main__': + alg = 'nb_gm_002' + fn = f'results/{alg}_{n}back.csv' + profile() diff --git a/tests/nb_gm_003_bm.py b/tests/nb_gm_003_bm.py new file mode 100644 index 0000000..fa6c19a --- /dev/null +++ b/tests/nb_gm_003_bm.py @@ -0,0 +1,114 @@ +import heapq +import csv +import random +import time + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq, time_per_block): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [time_per_block, ''.join(seq), str(ralph_skewed)] + + +def benchmark_skewness(filename): + from generators.nb_gm_003 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['time_per_block', 'seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + targets = trials / 3 + t = time.time() + seq = generator.generate(trials, targets) + t = time.time() - t + print(f"sequence {i}/{sample_size}: {trials} trials, took {t}s.") + writer.writerow(to_csv_row(i, seq, t)) + plot_skewness(fn, 'nb_gm_003') + + +def plot_skewness(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def plot_targets_ratio(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +def benchmark_targets_ratio(): + pass + +def benchmark_chunking(): + pass + + +def benchmark_n(): + pass + + +def plot_timing(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['time_per_trial'] = data.apply(lambda s: s.time_per_block / s.trials, axis=1) + plt.style.use('ggplot') + plt.title(f"{figure_title} - average time to generate a trial") + plt.ylabel('time (s)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.time_per_trial, alpha=0.5) + + # draw fitted curve + # import numpy as np + # p = np.poly1d(np.polyfit(data.trials, data.time_per_trial, 3)) + # plt.plot(data.trials, p(data.trials), color='red') + + plt.savefig(f'results/{figure_title}_timing.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + alg = 'nb_gm_003' + fn = f'results/{alg}_{n}back.csv' + benchmark_skewness(fn) diff --git a/tests/nb_gm_004_bm.py b/tests/nb_gm_004_bm.py new file mode 100644 index 0000000..b4ad4a8 --- /dev/null +++ b/tests/nb_gm_004_bm.py @@ -0,0 +1,26 @@ +import time +import numpy as np +import pandas as pd + +import tests.common as common +from generators.nb_gm_004 import SequenceGenerator + +def run(): + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, lures) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('tests/results/nb_gm_004_profile.csv', sep=',', encoding='utf-8') diff --git a/tests/results/2v4_time_trials.png b/tests/results/2v4_time_trials.png new file mode 100644 index 0000000..9be91b4 --- /dev/null +++ b/tests/results/2v4_time_trials.png Binary files differ diff --git a/tests/results/2vs4_skewness.png b/tests/results/2vs4_skewness.png new file mode 100644 index 0000000..a488e1f --- /dev/null +++ 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+210,87.0,0.0,0.0,88.0,1.0,0.0,0.0,0.0,EDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +211,0.0,0.0,12.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCC,True +212,0.0,0.0,0.0,66.0,0.0,65.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +213,1.0,0.0,0.0,0.0,0.0,21.0,22.0,0.0,AGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFG,True +214,74.0,73.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +215,0.0,5.0,0.0,0.0,6.0,0.0,0.0,1.0,HEBEBEBEBEBE,True +216,0.0,1.0,0.0,0.0,0.0,53.0,0.0,54.0,BHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +217,70.0,0.0,0.0,0.0,0.0,70.0,0.0,0.0,AFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +218,0.0,0.0,0.0,0.0,0.0,0.0,36.0,35.0,GGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +219,0.0,90.0,90.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +220,0.0,0.0,0.0,0.0,0.0,0.0,37.0,38.0,HHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +221,0.0,0.0,44.0,0.0,0.0,1.0,44.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +222,0.0,0.0,0.0,67.0,67.0,0.0,0.0,1.0,HDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True 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+409,0.0,0.0,72.0,1.0,0.0,0.0,72.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +410,55.0,0.0,1.0,0.0,0.0,0.0,55.0,0.0,CAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +411,0.0,59.0,0.0,0.0,0.0,60.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +412,61.0,0.0,0.0,61.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +413,0.0,1.0,0.0,75.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +414,0.0,53.0,0.0,0.0,0.0,0.0,52.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +415,0.0,0.0,16.0,0.0,1.0,0.0,0.0,15.0,ECHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +416,0.0,0.0,0.0,39.0,0.0,0.0,0.0,38.0,DHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +417,96.0,0.0,1.0,95.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +418,28.0,0.0,1.0,27.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +419,0.0,1.0,92.0,92.0,0.0,0.0,0.0,0.0,BCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +420,1.0,0.0,20.0,0.0,20.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECE,True +421,0.0,90.0,0.0,0.0,0.0,0.0,89.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +422,10.0,0.0,0.0,0.0,0.0,1.0,11.0,0.0,FGAGAGAGAGAGAGAGAGAGAG,True +423,0.0,0.0,0.0,74.0,73.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +424,0.0,0.0,127.0,0.0,0.0,0.0,1.0,0.0,GCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +425,1.0,9.0,0.0,0.0,0.0,9.0,0.0,0.0,AFBFBFBFBFBFBFBFBFB,True +426,0.0,0.0,84.0,0.0,0.0,0.0,0.0,84.0,HCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +427,33.0,0.0,0.0,34.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +428,1.0,30.0,0.0,30.0,0.0,0.0,0.0,0.0,ABDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +429,0.0,0.0,67.0,0.0,1.0,67.0,0.0,0.0,EFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +430,62.0,0.0,0.0,63.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +431,1.0,9.0,9.0,0.0,0.0,0.0,0.0,0.0,ABCBCBCBCBCBCBCBCBC,True +432,15.0,0.0,0.0,0.0,0.0,0.0,14.0,0.0,AAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +433,0.0,1.0,0.0,65.0,66.0,0.0,0.0,0.0,BEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +434,0.0,160.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +435,0.0,0.0,1.0,0.0,42.0,42.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +436,0.0,0.0,55.0,0.0,55.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +437,0.0,0.0,0.0,1.0,0.0,73.0,0.0,73.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +438,79.0,0.0,0.0,0.0,78.0,0.0,0.0,0.0,AAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +439,0.0,0.0,67.0,0.0,0.0,0.0,66.0,1.0,HCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +440,0.0,0.0,77.0,0.0,0.0,1.0,0.0,76.0,FCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +441,0.0,0.0,0.0,0.0,153.0,0.0,0.0,1.0,HEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +442,0.0,88.0,88.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +443,0.0,0.0,0.0,20.0,22.0,0.0,0.0,0.0,EEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +444,41.0,0.0,42.0,0.0,0.0,0.0,1.0,0.0,GCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +445,0.0,0.0,0.0,47.0,0.0,46.0,0.0,1.0,HDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +446,1.0,0.0,0.0,0.0,86.0,0.0,0.0,87.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +447,56.0,56.0,0.0,0.0,0.0,0.0,0.0,1.0,HABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +448,0.0,0.0,0.0,0.0,11.0,0.0,0.0,10.0,EEHEHEHEHEHEHEHEHEHEH,True +449,0.0,0.0,0.0,0.0,0.0,1.0,92.0,92.0,FGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +450,0.0,0.0,0.0,6.0,5.0,1.0,0.0,0.0,FDEDEDEDEDED,True +451,66.0,1.0,67.0,0.0,0.0,0.0,0.0,0.0,BCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +452,0.0,0.0,0.0,13.0,0.0,1.0,12.0,0.0,FDGDGDGDGDGDGDGDGDGDGDGDGD,True +453,1.0,0.0,0.0,0.0,56.0,0.0,56.0,0.0,AEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +454,15.0,0.0,0.0,0.0,0.0,0.0,0.0,16.0,HAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +455,0.0,21.0,1.0,0.0,21.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True +456,93.0,0.0,1.0,0.0,92.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +457,1.0,0.0,0.0,0.0,35.0,0.0,0.0,35.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +458,13.0,0.0,0.0,0.0,1.0,0.0,13.0,0.0,EAGAGAGAGAGAGAGAGAGAGAGAGAG,True +459,0.0,0.0,65.0,0.0,1.0,0.0,65.0,0.0,ECGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +460,0.0,0.0,95.0,1.0,0.0,95.0,0.0,0.0,DFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +461,15.0,0.0,0.0,0.0,1.0,0.0,0.0,15.0,EHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +462,0.0,0.0,198.0,0.0,1.0,0.0,0.0,0.0,ECCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +463,84.0,84.0,0.0,0.0,1.0,0.0,0.0,0.0,EABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +464,0.0,0.0,0.0,0.0,0.0,60.0,0.0,61.0,HFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +465,0.0,179.0,0.0,1.0,0.0,0.0,0.0,0.0,DBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +466,1.0,0.0,90.0,0.0,89.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +467,0.0,35.0,0.0,0.0,0.0,34.0,0.0,0.0,BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +468,0.0,0.0,0.0,1.0,7.0,0.0,0.0,7.0,DHEHEHEHEHEHEHE,True +469,0.0,0.0,0.0,0.0,92.0,0.0,91.0,0.0,EEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +470,0.0,0.0,46.0,0.0,0.0,1.0,46.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +471,0.0,0.0,0.0,0.0,0.0,1.0,158.0,0.0,FGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +472,1.0,0.0,0.0,0.0,0.0,58.0,0.0,59.0,AHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +473,0.0,0.0,6.0,1.0,0.0,0.0,6.0,0.0,DCGCGCGCGCGCG,True +474,0.0,0.0,0.0,0.0,0.0,98.0,0.0,97.0,FFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +475,0.0,87.0,0.0,0.0,0.0,0.0,0.0,85.0,BBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +476,0.0,0.0,33.0,0.0,0.0,0.0,1.0,33.0,GHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +477,45.0,0.0,0.0,0.0,46.0,0.0,0.0,0.0,EAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +478,0.0,0.0,0.0,77.0,0.0,0.0,75.0,0.0,DDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +479,73.0,1.0,73.0,0.0,0.0,0.0,0.0,0.0,BACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +480,0.0,1.0,0.0,0.0,37.0,37.0,0.0,0.0,BEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +481,0.0,92.0,93.0,0.0,0.0,1.0,0.0,0.0,FCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +482,0.0,0.0,0.0,1.0,0.0,0.0,0.0,24.0,DHHHHHHHHHHHHHHHHHHHHHHHH,True +483,25.0,0.0,0.0,1.0,0.0,25.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +484,0.0,0.0,0.0,0.0,0.0,37.0,0.0,36.0,FHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +485,21.0,0.0,0.0,1.0,0.0,20.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +486,0.0,35.0,0.0,36.0,0.0,0.0,0.0,1.0,HDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +487,0.0,0.0,1.0,0.0,97.0,98.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +488,0.0,93.0,0.0,0.0,0.0,1.0,0.0,94.0,FHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +489,0.0,1.0,0.0,93.0,0.0,0.0,93.0,0.0,BGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +490,0.0,0.0,0.0,70.0,0.0,0.0,72.0,0.0,GGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +491,86.0,0.0,0.0,0.0,1.0,86.0,0.0,0.0,EFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +492,0.0,65.0,1.0,0.0,0.0,65.0,0.0,0.0,CBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +493,0.0,0.0,0.0,69.0,0.0,0.0,0.0,1.0,HDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +494,0.0,0.0,144.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +495,0.0,45.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True 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+599,16.0,0.0,16.0,0.0,0.0,0.0,0.0,0.0,ACACACACACACACACACACACACACACACAC,True +600,0.0,21.0,0.0,22.0,0.0,0.0,0.0,0.0,DBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +601,70.0,71.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +602,0.0,0.0,0.0,1.0,0.0,0.0,53.0,0.0,DGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +603,45.0,0.0,0.0,0.0,0.0,45.0,0.0,0.0,FAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +604,0.0,1.0,56.0,0.0,0.0,0.0,56.0,0.0,BGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +605,0.0,1.0,0.0,0.0,0.0,0.0,0.0,195.0,BHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True 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+611,0.0,0.0,86.0,0.0,88.0,0.0,0.0,0.0,EECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +612,1.0,0.0,0.0,0.0,14.0,0.0,0.0,14.0,AEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +613,0.0,0.0,35.0,0.0,0.0,35.0,1.0,0.0,GCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCF,True +614,0.0,0.0,1.0,0.0,43.0,43.0,0.0,0.0,CEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +615,0.0,0.0,0.0,0.0,0.0,1.0,67.0,66.0,FGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +616,0.0,27.0,0.0,0.0,26.0,0.0,1.0,0.0,GBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +617,0.0,88.0,1.0,87.0,0.0,0.0,0.0,0.0,CBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +618,0.0,41.0,0.0,0.0,0.0,41.0,1.0,0.0,GFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +619,0.0,27.0,27.0,0.0,0.0,0.0,0.0,0.0,CBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +620,1.0,0.0,20.0,20.0,0.0,0.0,0.0,0.0,ADCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +621,0.0,0.0,1.0,24.0,24.0,0.0,0.0,0.0,CEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +622,1.0,0.0,0.0,0.0,55.0,55.0,0.0,0.0,AEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +623,1.0,0.0,0.0,0.0,26.0,0.0,26.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +624,0.0,0.0,15.0,0.0,0.0,0.0,0.0,13.0,CCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +625,0.0,0.0,1.0,67.0,67.0,0.0,0.0,0.0,CDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +626,0.0,0.0,65.0,0.0,0.0,1.0,0.0,64.0,FCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +627,0.0,0.0,0.0,0.0,89.0,1.0,90.0,0.0,FGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +628,0.0,0.0,0.0,0.0,1.0,0.0,51.0,0.0,EGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +629,0.0,0.0,41.0,0.0,0.0,40.0,0.0,0.0,CFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +630,0.0,0.0,93.0,0.0,0.0,0.0,1.0,0.0,GCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +631,0.0,53.0,1.0,0.0,0.0,53.0,0.0,0.0,CBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +632,0.0,0.0,0.0,14.0,0.0,0.0,0.0,15.0,HHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +633,0.0,29.0,0.0,0.0,0.0,0.0,28.0,0.0,BGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +634,0.0,66.0,0.0,0.0,0.0,1.0,66.0,0.0,FGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +635,0.0,0.0,62.0,62.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +636,0.0,31.0,32.0,0.0,1.0,0.0,0.0,0.0,ECBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +637,0.0,0.0,0.0,0.0,0.0,0.0,48.0,49.0,HGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +638,1.0,0.0,0.0,0.0,0.0,0.0,54.0,53.0,AGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +639,59.0,0.0,1.0,0.0,59.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +640,0.0,0.0,0.0,0.0,1.0,0.0,27.0,27.0,EGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +641,0.0,0.0,0.0,23.0,24.0,0.0,0.0,0.0,EDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +642,0.0,0.0,0.0,91.0,0.0,0.0,91.0,0.0,DGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +643,0.0,0.0,0.0,0.0,48.0,49.0,0.0,1.0,HFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +644,14.0,0.0,0.0,0.0,0.0,14.0,1.0,0.0,GAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +645,0.0,96.0,0.0,0.0,1.0,0.0,0.0,96.0,EHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +646,0.0,0.0,0.0,50.0,48.0,0.0,0.0,0.0,DDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +647,0.0,0.0,0.0,99.0,0.0,99.0,0.0,0.0,FDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +648,49.0,0.0,1.0,0.0,0.0,0.0,0.0,48.0,CAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +649,0.0,0.0,52.0,0.0,1.0,0.0,53.0,0.0,EGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True 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+667,1.0,147.0,0.0,0.0,0.0,0.0,0.0,0.0,ABBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +668,0.0,0.0,97.0,0.0,97.0,0.0,0.0,1.0,HCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +669,0.0,0.0,1.0,0.0,0.0,0.0,53.0,52.0,CGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +670,0.0,0.0,94.0,0.0,96.0,0.0,0.0,0.0,EECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +671,99.0,0.0,1.0,0.0,98.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +672,68.0,0.0,0.0,0.0,0.0,0.0,67.0,1.0,HAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGA,True +673,0.0,0.0,0.0,26.0,27.0,0.0,1.0,0.0,GEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +674,31.0,0.0,0.0,0.0,32.0,0.0,0.0,1.0,HEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +675,0.0,0.0,0.0,0.0,42.0,0.0,41.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +676,0.0,0.0,50.0,0.0,0.0,0.0,1.0,50.0,GCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +677,0.0,25.0,0.0,24.0,0.0,0.0,0.0,0.0,BBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +678,0.0,0.0,0.0,0.0,1.0,10.0,9.0,0.0,EFGFGFGFGFGFGFGFGFGF,True +679,65.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,DAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +680,0.0,23.0,0.0,0.0,0.0,0.0,23.0,1.0,HGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +681,0.0,1.0,58.0,0.0,0.0,0.0,57.0,0.0,BCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +682,0.0,0.0,0.0,0.0,0.0,68.0,1.0,68.0,GFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +683,0.0,0.0,0.0,0.0,96.0,0.0,96.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +684,1.0,0.0,0.0,0.0,66.0,0.0,66.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +685,0.0,0.0,0.0,0.0,0.0,1.0,0.0,21.0,FHHHHHHHHHHHHHHHHHHHHH,True +686,0.0,88.0,0.0,87.0,0.0,0.0,0.0,0.0,BDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +687,0.0,0.0,19.0,19.0,0.0,0.0,1.0,0.0,GDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +688,0.0,42.0,1.0,0.0,41.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +689,0.0,0.0,0.0,0.0,0.0,60.0,61.0,0.0,GGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +690,0.0,23.0,23.0,0.0,0.0,0.0,1.0,0.0,GBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +691,86.0,86.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +692,35.0,35.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +693,57.0,0.0,0.0,0.0,0.0,58.0,1.0,0.0,GFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +694,0.0,0.0,30.0,30.0,1.0,0.0,0.0,0.0,EDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +695,19.0,18.0,0.0,1.0,0.0,0.0,0.0,0.0,DABABABABABABABABABABABABABABABABABABA,True +696,0.0,0.0,0.0,1.0,0.0,56.0,0.0,57.0,DHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +697,10.0,0.0,1.0,0.0,0.0,0.0,0.0,11.0,CHAHAHAHAHAHAHAHAHAHAH,True +698,0.0,0.0,89.0,0.0,88.0,0.0,1.0,0.0,GCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +699,0.0,0.0,87.0,0.0,86.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +700,17.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAA,True +701,0.0,0.0,66.0,65.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +702,0.0,0.0,1.0,0.0,0.0,0.0,123.0,0.0,CGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +703,0.0,118.0,0.0,0.0,1.0,0.0,0.0,0.0,EBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +704,0.0,0.0,0.0,0.0,0.0,0.0,0.0,132.0,HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +705,0.0,0.0,0.0,0.0,0.0,23.0,1.0,23.0,GHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +706,0.0,0.0,0.0,0.0,6.0,5.0,0.0,0.0,EFEFEFEFEFE,True +707,18.0,0.0,0.0,16.0,0.0,0.0,0.0,0.0,AADADADADADADADADADADADADADADADADA,True +708,0.0,72.0,0.0,0.0,0.0,71.0,0.0,1.0,HBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +709,0.0,0.0,54.0,0.0,0.0,1.0,0.0,55.0,FHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +710,0.0,1.0,87.0,0.0,87.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +711,0.0,0.0,1.0,63.0,0.0,0.0,0.0,64.0,CHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +712,78.0,0.0,78.0,0.0,0.0,1.0,0.0,0.0,FCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +713,0.0,80.0,0.0,0.0,0.0,81.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +714,0.0,1.0,0.0,0.0,0.0,0.0,40.0,39.0,BGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +715,0.0,0.0,7.0,0.0,6.0,0.0,0.0,0.0,CCECECECECECE,True +716,35.0,0.0,0.0,0.0,0.0,0.0,0.0,33.0,AAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +717,0.0,0.0,0.0,1.0,73.0,0.0,0.0,72.0,DEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +718,0.0,0.0,90.0,0.0,0.0,1.0,89.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +719,1.0,0.0,0.0,67.0,0.0,0.0,0.0,66.0,ADHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +720,56.0,0.0,0.0,0.0,56.0,0.0,1.0,0.0,GAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +721,0.0,0.0,0.0,1.0,0.0,0.0,49.0,49.0,DHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +722,0.0,0.0,0.0,117.0,0.0,1.0,0.0,0.0,FDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +723,0.0,0.0,86.0,1.0,0.0,0.0,85.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +724,0.0,0.0,31.0,0.0,0.0,0.0,0.0,30.0,CCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +725,1.0,0.0,0.0,0.0,98.0,0.0,98.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +726,1.0,84.0,84.0,0.0,0.0,0.0,0.0,0.0,ACBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +727,0.0,56.0,56.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +728,0.0,1.0,0.0,24.0,24.0,0.0,0.0,0.0,BDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +729,37.0,0.0,0.0,0.0,0.0,37.0,0.0,0.0,FAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +730,0.0,0.0,91.0,0.0,0.0,0.0,91.0,0.0,GCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True 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+772,0.0,68.0,0.0,0.0,0.0,0.0,0.0,67.0,BBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +773,60.0,1.0,0.0,0.0,0.0,61.0,0.0,0.0,BFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +774,0.0,1.0,0.0,57.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +775,0.0,78.0,0.0,0.0,1.0,0.0,0.0,0.0,EBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +776,1.0,0.0,0.0,0.0,0.0,96.0,96.0,0.0,AGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +777,43.0,0.0,0.0,0.0,0.0,1.0,44.0,0.0,FGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True 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+989,93.0,0.0,92.0,0.0,0.0,0.0,0.0,1.0,HACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +990,0.0,1.0,0.0,0.0,60.0,0.0,0.0,61.0,BHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +991,0.0,1.0,0.0,0.0,0.0,0.0,32.0,32.0,BHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +992,0.0,0.0,34.0,35.0,0.0,0.0,1.0,0.0,GDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +993,0.0,0.0,0.0,0.0,54.0,0.0,54.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +994,0.0,0.0,0.0,1.0,0.0,39.0,0.0,38.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +995,0.0,0.0,0.0,0.0,99.0,98.0,0.0,1.0,HEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +996,86.0,1.0,0.0,0.0,0.0,86.0,0.0,0.0,BFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +997,0.0,76.0,77.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +998,0.0,0.0,19.0,0.0,0.0,0.0,0.0,1.0,HCCCCCCCCCCCCCCCCCCC,True +999,0.0,0.0,37.0,1.0,0.0,0.0,38.0,0.0,DGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True diff --git a/tests/results/nb_gm_001_3back.csv b/tests/results/nb_gm_001_3back.csv new file mode 100644 index 0000000..b2f89a4 --- /dev/null +++ b/tests/results/nb_gm_001_3back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,0.0,65.0,132.0,0.0,0.0,0.0,0.0,1.0,HCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCC,True +1,51.0,0.0,52.0,52.0,0.0,0.0,0.0,1.0,HCDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACD,True +2,0.0,61.0,0.0,62.0,0.0,0.0,61.0,1.0,HDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGD,True +3,40.0,0.0,0.0,1.0,0.0,0.0,0.0,80.0,DHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHA,True +4,4.0,0.0,1.0,0.0,0.0,6.0,0.0,0.0,CAFFAFFAFFA,True 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+401,0.0,55.0,55.0,0.0,0.0,1.0,54.0,0.0,FCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCB,True +402,47.0,0.0,0.0,0.0,1.0,47.0,0.0,47.0,EAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFH,True +403,56.0,0.0,0.0,0.0,58.0,0.0,0.0,56.0,EEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAE,True +404,0.0,39.0,0.0,0.0,39.0,1.0,40.0,0.0,FGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEG,True 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+3,12.0,15.0,11.0,20.0,13.0,17.0,17.0,22.0,AFAHGHGHGBEBCDDDDHHHABCEHEHEBBBAHADADCFHHHHHFEFCBDDFDGDEFCAGGFEFBDGEHECCBCFFFFFFHGEBBHHCBCACHHDDBFGGGGEGEAFDGDADGDGDGBEBAAHDDFH,False +4,4.0,4.0,8.0,8.0,5.0,7.0,4.0,2.0,FGDGECDCECGCDADAHFDFCFCGAFCDDDABEBHBEFEFBC,False +5,15.0,15.0,15.0,16.0,16.0,14.0,9.0,13.0,HGDGBFDHDADHBBBBBHBAAGBCEABCGFAFAFBGBCBFGDDDEAAAHDFACECECHFHFHFCFHEGEFEFDFDAAHDEECDABFCCCCGBEBDAHCECHCHEDEDEDAGEE,False +6,17.0,17.0,9.0,6.0,15.0,13.0,15.0,12.0,BEBEBHAGCFEHHABAHDEDGHFBFGFCAABAGFFFAFGECEBEAEAFBFCEBEGHGDBEFABABEGEHEHBGBGDADACAGHGHGBGBACGCAHFFBHAECDC,False +7,12.0,7.0,7.0,6.0,9.0,8.0,5.0,6.0,CEGBFEFEFEHCCDEBCCHBBBGAHACBGGDBDADACADHDHFEAEAEFGFAAEAHAFAF,False +8,9.0,13.0,10.0,11.0,12.0,15.0,11.0,12.0,CGCFDBDFHHEHFFGCDHEHCFCFAAEGDCEGHGCFCBBBCBGFGHGDFDBDADHBBEGAGABABHBEBEHGHADAFEFCFDBDEFEHEFEFA,False +9,13.0,26.0,23.0,14.0,20.0,18.0,19.0,27.0,HECEBEFFHFDCCFGBCBDBAHGHGCBBABHEFAFEBEBHBHGGCHBGGCCCCCFCBDDDEDHDEEEAAFAFGFDFCGBGHEHDHGHAFABCGGEHEHFBGBADEBEBEAAHBDCCFGGHHHBHBHGHBDBEEAEGCGCBCHCEFFFFCHDHCHDHABCB,False +10,14.0,18.0,15.0,13.0,15.0,19.0,18.0,11.0,AFACABDDFBBBEBECECGHFBFBECDCEEEDGDBHHGCBDDAFCBAAAGHCHCHEAFBFDHAHCFFAAAHBBBFBFBHGFBCBCFGGGHGDGDFEGEFCFEDGDGAGEGCGEGEFEFAFDGC,False +11,21.0,20.0,21.0,13.0,15.0,26.0,21.0,21.0,EECEFFHGCADHGEGEABCCFDEBABEBGGCACHFHFBFBFBAHGBGCGHDCDABHHAGABFHEBCFEGDFDFDFAFBCBCAHACFGFBFBFBFBDACCBCHFHEGEDFDFCAAAGGEBFAAACACHCHFGFBFGHGHAEAGCCEDDFHHHGHGHGDE,False +12,17.0,26.0,17.0,23.0,17.0,11.0,26.0,21.0,ABGCACGDDFHFHBCEHEAGBGBEBAHEBEBFAAHAFBCEGDGBAHGGGGFGDDDBABABHGGGCGDGHGHDACAEDEFECHGEGDABGCHCDDDDCBCBADAHCHGBGBGEHDCDBBFBABHBHBFBACHDEEHGHECDCDHDEFEDECFGHGBFBD,False +13,24.0,21.0,23.0,20.0,15.0,14.0,30.0,24.0,AHHHHAFEDHAFBFGFCFGADADCDGBBBBGDGEGBCBHGGGGCGFBFAGGGGHEEFEGHGHABCBFHGAGACBBDEDHDHDGBCACAHGCACEHECACHBHDCGCECADGDGDABADHFGCGAGAHHBGFDCHBHCAAABEEFDFDBDBEADAHGEGEHECCCBCFCAHD,False +14,1.0,0.0,2.0,1.0,1.0,1.0,2.0,2.0,DECGCGAHFH,True +15,7.0,7.0,10.0,5.0,8.0,4.0,8.0,9.0,HBABHHEEGAGAGEGHCDEECHCHGBCBCDDAEGCBCGEAEFDFBFBFAGCHCHCHAD,False +16,14.0,19.0,14.0,7.0,10.0,15.0,19.0,7.0,CEAFFGHGEGFDFDCACAGBDEAFCEDDFAHHFDFGBEACGCGBGAFECECFGHCEBAFGEGCBABEBHBHBACAGAGDGHBABCBCBGFGFGFGBBBBFBCBGA,False +17,17.0,15.0,14.0,12.0,10.0,9.0,17.0,6.0,EBACADACGBGBAFGHGHADCDGAAFFFADABAHGDGABBCBCACACECHFBFHDCACDGEBADDEGGGEDADFGFGCGFBBABCBEBDBCHGEGEGECE,False +18,14.0,22.0,17.0,9.0,14.0,10.0,25.0,20.0,EHCHAHEHAHCHCGBGCGCGAEBFBFGGCEFGBGHAHCBABABHHGHGCACHDEDBBABGGDGDEBBBHHGCAEGBFHGEGEGBCCGCDFBBGBFBDAEEHHHCFEFECEHGCGCBHDADFDAGAGAGFBB,False +19,13.0,27.0,12.0,18.0,19.0,17.0,20.0,18.0,BFGCGBHAHAHEFEDBABEBEDADGGGGBAFCGEBDFHBHGHGCBBEGEGBHDHDHBCBCACDBFHHCHBGAGAGEDADADCDCACGHEEEEBDFDFDHDCGGBGDEBBBABEHFHGEFFFBADHEFFCFDEBEBFFEBHBFBG,False +20,11.0,10.0,7.0,8.0,8.0,7.0,11.0,4.0,BGBABGHGCGFBFAEBGGEDEFAHEHACDCDADBGGAGAGADFBFBCBCEFBFDHDACCDAGAEEE,False +21,22.0,20.0,18.0,24.0,13.0,11.0,16.0,21.0,DADADHCACFCHEDAAAHGDDHAGCDEDEGBHAHBDBDBGHHHCHCECAAAEFEDECEDBHFABGBCAGDBEGEBABHFCBBABDFDGHGCBFBCCDHDHDGDHDHCHBGADAFACHEHBDCDAFAFAFAGGCGCFHGBDBEBEG,False +22,8.0,10.0,11.0,7.0,8.0,15.0,4.0,11.0,CBAEGDGEHEBGBFBFBDHCHFHBAEHFFGFCFBFCFEEHABECFFFFACAEHHDCDCDHDHAHCFCBCBAADF,False +23,32.0,19.0,21.0,23.0,13.0,27.0,21.0,27.0,GHCABDGDFFFAHHHEAEHGAGAGHEFEGBCFAFBFGCHCHFHBGCAFFDFDBACACHCHCHBFGFEACAFABEBEBHHGHFHAHGGAGAHAFCGDHDHAFGCBCHDAAAAAAFCFHGEFFBEBEDDDFDBCBDDDCGFAFADBDBEBCAGGHDFDFBCDEAGAHCCEHGHAHCDDDDABAFA,False +24,26.0,30.0,18.0,21.0,29.0,16.0,21.0,21.0,GDGDADAGAGDEHCDBDHAHEHFHAHAFBHBHGCEBHBDBHBHBEEABABABAEECEGEGAGADHDBEEGBCAADHGBFBCEAAHDEBEBFBFBFCCGCEFBABAEDBGFGBGCFCGEACDFEFBHDADFHCEAEBDHDCGBEFGCDCACDEBEGAGAEAEFDFBBEHEGEGHCACEFBHDH,False +25,17.0,15.0,10.0,21.0,16.0,11.0,16.0,22.0,BDBDBHHHAAGAEHEHCHCDADEBGHDAGEBHGAABADADEDECEHAHFBGCGBEHCGADFBHECGHHFFFHFBDDDDDFDFDFHFEDEDACAEAEBDCHHBFBABCBGDGEAECHHGHGEGHDAGGG,False +26,12.0,13.0,16.0,11.0,17.0,10.0,17.0,12.0,GEECBGFEEDHCEFGFEAEAHGEGEDDDHDCDCBHBCBCFCECEGAGAGAHECFCEAAFGFGCEHGHBBBGBGBCBDHEAEFHFHGBCDGGACHCGCDADAEBFBADH,False +27,14.0,11.0,17.0,13.0,14.0,21.0,16.0,19.0,AAECGGEGHCACACACHBHADCECBDHDHDFCFGHGDDEDHHHAHDFDACHBHAFBHHAEEECGGFGEGEBEFCFAEAEFFBFBFDGDGDGHFACCDFHFCGBBHBCGGFGEHEFFFFHFCBCAF,False +28,14.0,15.0,12.0,21.0,15.0,9.0,13.0,21.0,GGHGEDHFCFCACBCADAEEEEAHDGAGHGHEHEHBBECEDBBBDBEGDGBAEABCCABBECDDDFDFHGHGHDHGHGHDADHHCHBHCCBAFHFDDDEDHFHAABDFDFEGEAADBDCH,False +29,18.0,19.0,27.0,26.0,29.0,30.0,16.0,16.0,DEFFFAFAGDGEEBFBFGEBADACADFDCEEDEDFDCDEBBGDGHGHGFFFDFBEBEHCHFDCDCEGFGFHFEFCGBBDCHCGCDADEGEGCFAAEHEHFDACGCEABBDECBCBCEFEFBFCFCFEHEHDGACEBAGCEFEBACCCAEDHDHBCFCDEFFHDHDHDCFCAAAEBEBFDHA,False +30,5.0,11.0,5.0,8.0,3.0,2.0,5.0,1.0,BBFGGBABFGCCCDADAHBEDCDBABGEAECBDBDBDBDG,True +31,28.0,17.0,19.0,16.0,18.0,11.0,17.0,33.0,DHAFAHAEAHDHFHFAFADHCGGGDGDGHEBDHCHBHAEBCBCFEGHHHBHCAFDHEHEHCDAGBCBAAAGACCBCAFGBHEHBBEAHAHAFAEACGGEHAFABEDEDFDCGHEBGAGEEAEBBHDEDECHCGABHGHAHAHBHCHCHCHDGACACDFD,False +32,5.0,10.0,12.0,17.0,19.0,17.0,17.0,11.0,EEBHBFFFDDEDCCAGEFEGGDGDFFGEGEAEDEFCFCGCGCGFAEGECDHHCEFDDHDFDABFDECECEHEFDDGDGBBFBFHHGCECEFEHAHDHDGBBFBGHGBG,False +33,4.0,13.0,10.0,7.0,4.0,8.0,11.0,7.0,CGBHBCBCBHFHFECBADGBGBGBDBCFAGDBHGFGECEHBGBCCACFGFGFGDDDFCADHEHB,False +34,22.0,27.0,22.0,21.0,21.0,28.0,21.0,21.0,BABFBCCCCGCDCAGABAHFBAHCBDBDHDCDCDEFFHBHBCBCBEHDAGAEFBBEEEBEGAGHGDGCGEBFBDEAECCFCFGDGDGHBHAEFFFECCADHFFBGHDHEGAAEDEFEFCDCDCDEFCHADAEHFDFHBBEBEBFBFAFGFAAHGHGFFAFGGBABGHGBFBFDFHCHAHEGDA,False +35,24.0,23.0,21.0,17.0,28.0,15.0,20.0,21.0,EGHGAGEGCGDFFCEEEEEAHGEGFGFBCBGBDBACHCAGDDDDEDEHACGCECAFAFEFHCHCEFHDHEHBAEADBDBAFCHCEEEEHBHBECEAEAFGGGGCCHBHAAACABBEHFHBDFHHDHBGCAABEBGAGABBFADADEBBBBCDCACFGFHDCEHEBGADE,False +36,16.0,12.0,18.0,16.0,29.0,20.0,25.0,11.0,EEEBCFFDHDBBGHGHGEFDFACCCFCGAECECEAGFFFCFDAHAEEHGGGBGBGADDGDGEGCCBFEHEGEHACDGDGCCCFCEAFAEGEGBGFGBBBHFGDGFGAAHADADCEEEEDEAEFEAEBFFFHEGECEGEHECAFDDDB,False +37,1.0,6.0,2.0,11.0,2.0,11.0,4.0,7.0,DBFFFHHADFFEFBDBFBGDFFEBHBHFHGDGDGCCDDDDHDHF,True +38,11.0,12.0,15.0,5.0,3.0,15.0,15.0,13.0,HCCCCAEBGFCFBGAHHHHBAFGCGCGCGFGCAABFBABHBFBCAFHFAFGCDBGBGAGFCBBAADHDHDCGEGHGCGFFHFHDEFHFC,False +39,33.0,14.0,21.0,23.0,21.0,18.0,25.0,28.0,DHAHAHADGDAFAFGCHCHEHCHABACEDDDCGBHAEFFGCADADGBGCFFFGGHBAAFGGHFHFHECFCHCHBDEFGADDCGGGHEBEDEBEBEDFHCAAAACFGFBFBFADAEGBDCAGACACAFGEEECDDDDCGGGEEEEEGCADHHHHAHABAHGBBCACHEGGHDADADAHAHEHAH,False +40,9.0,21.0,8.0,6.0,13.0,11.0,9.0,15.0,HEBEGEGAGEBBBHFAFABCBCBEBCBEAFHGGGHEHCHBEDFFAFAHDBFBFBEBDFHHDHBHCHBHBDEFABGBCEDEBCACHHEAGBGF,False +41,13.0,18.0,18.0,16.0,8.0,20.0,16.0,13.0,AGDGBCDHFADAGFFFHHCFCFEBGBGFGFGCGCHHHHCGFBFGDHABCBCGDGECEFBFCACBDBDCFAFBDEDCFFBHGHBEBABDFDFDHDHACABDBAFAFDHEGACACBEECGCBDG,False +42,21.0,15.0,14.0,22.0,14.0,22.0,16.0,21.0,ACFDFDEDFDBAFDCDCDFFFFFACHCHGEDFCFEHADACEHEDEBAFAGGHGEDADFDHDHDHGADAGCCCFHBDBGBDEGEBHGFGHAHFBFBFEAABABACDDAHHGFGBGEGHFEABHBFEHHHGDFDCACABABGECHAH,False +43,17.0,19.0,23.0,19.0,19.0,21.0,20.0,22.0,GDGFGEDDDDDDFDFDFEHBHDGAECBHDEGHGEEDEBEDECGGAADAFAFADECFCDGDGFBHGCBHBACAGACFCGGGBGCHFHEHECECAHFHFGCGHBFCGCBCFEHEGEHBBAAABDHFBCCCCFFFHFCABFBHBHBEDAFEHBHACABECHCH,False +44,2.0,1.0,3.0,4.0,5.0,3.0,6.0,5.0,CHCHFGBGEHFDAGADEDEGGFGEDEHCH,True +45,17.0,20.0,26.0,20.0,18.0,24.0,15.0,12.0,BDEFBBBHHECFCFCBBFEDDADADGECEHEFCGCAFDCGCFFEDDGGHHHHHAFAFEFAFDFDFDEDFAACFCFCDCBBBCGCGDGDFCGCGBDCACBHDHEECBBEBECFCHGBGEGABCDCEFHFGACDFAFAECEBEBDACABAGFBA,False +46,5.0,7.0,11.0,5.0,5.0,3.0,8.0,10.0,CBDHFHCDCEGEHCHCHCHEGCGCGBBBBADAHGDGBACGEAHBHFGFCECAHD,False +47,5.0,4.0,4.0,5.0,0.0,1.0,5.0,3.0,ACABGBHBHBGDCACHCDAGFGAGDDD,True +48,21.0,22.0,13.0,24.0,16.0,18.0,24.0,19.0,DBDGAGBGFHFCABGFECEGBGHHEACDFDGCGBEBGDAFAHADADAHHBHBHAGABADEBFDGDBDGDGCFAFAFDDDDECGFEFEAHAHEHEHCBCDADGBFBFAEBCAHFHEDEGBBFDEHEBDHFGCGHGHGBGCDABCBDGHGBGDCEAFAF,False +49,5.0,12.0,11.0,8.0,8.0,7.0,11.0,9.0,FCFDGDHBEBECFBBHFCFCGDBCCCGCECECBDBGBEHDDBCAGAEHEDFDHGEGAHBHGAGAGFHBHBG,False +50,2.0,7.0,7.0,4.0,6.0,13.0,10.0,11.0,BBFEFEFHAHFDFGHEBABDFHBHEFGFGHEHGGGFDFEHCBGBFDFHFHCCGCGHGCCC,True +51,5.0,7.0,11.0,12.0,13.0,9.0,8.0,13.0,EFFBFDAAECCCHDHBHFEDBHBHDHDGGGGECDGHCFEFEDEDCDCDEDCCHFEFEGCGBHEHBHAHAGDFCEAEHB,False +52,15.0,6.0,11.0,6.0,11.0,16.0,3.0,8.0,BAEGCCEAHBFCCHFABEHEFDCHEBECACECEAFGFEFEFBFBFAFADADACACDFGFAFAFEFDAAHFDCAHHH,True +53,20.0,14.0,19.0,11.0,13.0,12.0,10.0,17.0,CHCECEHEGAHBFGHCHABCBCDCECEDAHACGCADDBBGFGFGFHAAACACFBEGGAGAEHCAAAFDFDCHBDBHGDFDHCBEFEBCBABHHHHDHCHDFEFABEBECAAAEACF,False +54,18.0,14.0,15.0,22.0,24.0,20.0,25.0,23.0,EGGCGCGDEDEBCBFDDDBFHDDGFBFEEEGDBDBEHFDFEACACADABEFDCECGGHBDCDBAGHGFBFECHCFEDEHEHAHEEAGCEEEEFGFHFAAGEEHHHHAHAHDEFGDGDBCGAGHFHFHAHAHDHDBFBFCEGGGGGGGHAADAGCDFFAHCB,False +55,3.0,4.0,2.0,5.0,2.0,5.0,3.0,1.0,EHAABABGBFDFGFGEDDFDCBCDF,True +56,9.0,9.0,8.0,11.0,11.0,13.0,8.0,11.0,ECFFFBCDEDAFEBEAFGFHFHFDEHEBEHEGBFEFHBABCCAGAGBGBDFHAHGHFCFDHDABADEDEDAHGGCDCHCD,False +57,10.0,13.0,10.0,15.0,7.0,9.0,16.0,11.0,HHCFEGEGEDFGABEHEADCHGHBDFDGDGHGCGBBDDCDCDBDBHCDEBAHACCFDGDFAFAFDDAGAGHGCGBGBHACBGBGAHEBFBF,False +58,15.0,15.0,14.0,21.0,27.0,24.0,20.0,28.0,FAFEFAADAGFBFACBCBHHCGFGFAFHCEGEGHHBDBFHFHBEGDGDAEEHEGCGDGHCDGDEHFHGCEEEGEGEDBDEEEEHHHHCHDAGFEBHFHAHFHFDDDCACHFBDDHDGDFDAGGEAEFBHEEEEBEHEFFCFCFDBHAFADCGCGFHDHEBABHB,False +59,11.0,16.0,18.0,17.0,22.0,31.0,15.0,17.0,FCECFCFCFBHCHBGBFHGEDADADEFEFHFDFDADEEADHGAEAECGDGCCFHFGFHFHFHFBFBFCEEEBEFFDEGGBHBEBHFCDDDDGHAFBFBFCACHCAFGCGHHEDCBFEFABCDCEGGGDAEBBBEDEFFFFECGHEHF,False +60,11.0,9.0,7.0,2.0,10.0,10.0,11.0,9.0,HGHCDCHCACBCEGEGEGEBBHCFGABEBFAEHHFBFAAGHGHFHABABCGEGFDEAAABFEFEFGFGA,False +61,23.0,23.0,21.0,24.0,24.0,17.0,27.0,24.0,EDGGCBCFCGCGCFCGCDCBAACHFHFHECACAGAHFHDBDEHAGADHGEGEBCAEAGDHAADDDDCEAEADBGFDBBBBDHDGDBBGCAAEHEGDGBGBFHCGCDBBBEFHFDAGHCDCHFHFGEHEGEGHGBEFACADAFCBGBGBFHDEDEDFBFEGHGHAHAEEEEGEDHAHACEFBHB,False +62,21.0,13.0,9.0,12.0,17.0,15.0,25.0,10.0,HFGFGBGEDEHGHAHFHGAAAFGHBFACGDBEBGAAFEGEFEFBGAHDEDECBCBFBEGAGAFCCBBDBAGABAGGGGGECDADAGAEFEDGACADDCDHDEAFHFHFGGGFGCABAEEEGE,False +63,6.0,6.0,3.0,12.0,7.0,8.0,6.0,13.0,FHEBEBHGHDAGHDCDEDEAFCFCHEEBAAFDDDFDHDAGBGFDHGHAHDHEHFHFHBDBG,False +64,6.0,15.0,15.0,8.0,14.0,13.0,8.0,8.0,CCEDEDBHHGDCBEFEFCCGCEAGFGEGECAHAHGBCFHACEBEBEGEFFFFBDBFBHBDDEDCBCBHBFGFHEAEBCBCFCBCAFD,False +65,6.0,4.0,3.0,4.0,6.0,8.0,5.0,5.0,CGCFEFAFAEEDEHCHBBDAAFAGHEHEBFDHDBAGFGFGF,False +66,17.0,8.0,15.0,6.0,16.0,16.0,11.0,12.0,AFGFGFGHGFECECECHAECCCFAHAFAEHGGCEBAFAEAEFGGHCBFAAEHFHFGBHEHGAFBFHCECEADFDBDBCACACAEAEBEDDACBDFHFHEGC,False +67,24.0,12.0,23.0,14.0,18.0,18.0,15.0,12.0,CCCFCFBHAEEDFDBAADAEAEABDBDGEHEGCCCACECHGEGEDECACFCFCHBFBAGAFFGHADBEBAAAAFAEECEDHDHECGGBHHCHDBGBABAGEFFGFAFADACADAGADCHFECGFGFHFCDCEGFCC,False +68,31.0,17.0,27.0,38.0,29.0,28.0,14.0,16.0,ACACBCFDGBHBDEGEAHDDEFEFEFEFDDHECEBDFDAEAEFECECGCHAHAHCBCDAHBDDDDEDEBEHGDDAFEFCFDDBCGAGACCECAADADABAFEDACGCAFAHDFDBDGCECBGBFFCHCGAEDFFFHADFDADGFAFADEDHABAGAGEHEFBFECEDEDCGEADADFDHBHDFDCBCFCDAFAECFCEHB,False +69,5.0,4.0,3.0,4.0,2.0,3.0,6.0,4.0,DAHAGAHAHAHFGCGEBDFDEDGGCFBBGBC,False +70,5.0,7.0,9.0,5.0,2.0,11.0,6.0,10.0,HAHDHDHBGBFCACDCHFBBHBHGDEACACEGFCDHBGFGFGFCCHBFFHFCFAF,True +71,11.0,10.0,6.0,19.0,14.0,23.0,11.0,9.0,FHFEADABECHFFDFDFHFEDECEFEFEFAFHDADAEADDCAGFGBBHGDGABDDFFFFDDDADEEGFGDABCDGGBHDHFGAGBHBHBEBEGFFFFFCCEDE,False +72,25.0,17.0,20.0,19.0,16.0,13.0,17.0,22.0,GDCDHGBEAEGDGEBDBDHDCDCBHDEAEHDCEFAAABCDCDABAGADADCFAFCGCACAFFBAHGCGCGEGEACHHECACECEHEGGFBDHFHAHAHGGDGFCECHFHFHCHFABABFDGABDEDABABHEACAFDHHGHAHBBBBEH,False +73,15.0,19.0,20.0,23.0,23.0,21.0,22.0,23.0,GFGFECGCEEGHFCBCFDDDHHGBGHGHDCDCFHAHCCCFHAADEBEHEDEDADCDCABEGEFDFHCHGGAHAHFCFCEADFFECGBDBDBDCCACADHGCGEGHFHGHGBFADEBEBEDGDBBACEEEHGBDBFFFFDGEGDGDGFBEHHHHAAEAEFBBBBEFH,False +74,3.0,11.0,6.0,11.0,10.0,12.0,5.0,7.0,ECHFHDHEFFHHDCFGEGFDBEBEFFFDBCBFEDCDCFEBBFADDBDBGBGBGBAHAHFDEDECE,True +75,21.0,13.0,22.0,19.0,30.0,19.0,18.0,19.0,HAHEEEFEDHDFDBHBGCCEEFEGGHGHCCCCCHGECEAHDBDBEFGHCACGBEFEHAFDFACAFEEEHABAGAFDGDADADAGBCBAEADAEFHCDCFGEHFHDEDCDFEFCCCEAEAEGGABFGEDBDBHBCCECEHEAEFGHGHDDAEAEHCFGFGFB,False +76,14.0,30.0,18.0,20.0,25.0,19.0,27.0,30.0,FCFBAEDEGEHEBGHGFEFCGDBDGGCGCGBEBHBHEAAAEECBCBCFHFCFDGAEHHFGGGGGHCHEHBABGBGHHDFAEBDBDBDBCCHAGGEGDGCCBCHFGFGHGHBHEFGHBFBCBHEHBBABCBHBCGEHEADDDBHFHAADEDBFHFEEGEDHDHDEDBDFEFEHCHAEGDHBFBA,False +77,25.0,17.0,30.0,29.0,22.0,22.0,23.0,24.0,CCHEAEHBBCBDADBDBDHGFEECBDFGFEAHDCGCDHHEHEHCGCFHGDGAGAGACACDDDFDFDGECCHDHCCEFAFEBAFGGHDCCGEDBDBDBCHCACDBAHCGCGAHAHAFFFHADCDCFCFHHCDCAEAGAGAGABFHGEGBGDFHEBEFCFAGBEEAABAGDGDFDFEABHCDEDEHEHEFCFCD,False +78,9.0,16.0,9.0,5.0,4.0,15.0,4.0,5.0,BCEADCBBBBABABCCEHFBDHFAAGAGHCFCBCBFDFAGAGBFBDBABFFFFFCEHEBDHFFFBFC,True +79,19.0,17.0,10.0,29.0,13.0,8.0,14.0,14.0,DEDEAEAEDDDDDDDHDGEBEFADAGBFFHDGFBBBBGBABFCHGDFDEACBBBAHADAHCGCAHDHEHABAGCGCGEDAGBDAACAHDBCBGBGBEDDDDDADGDFDHHFDAHAEEEHCDCHG,False +80,9.0,11.0,7.0,9.0,14.0,3.0,11.0,16.0,HEHEACBHBHAGEBEAEBHBHBDEDCFABCGAEABHEHDADABABGGGDGHECEHHDGDHHCHCDGFFHCBEDEGEGHGE,False +81,4.0,9.0,4.0,9.0,3.0,6.0,6.0,5.0,BGBACACHDGDFDFBFEAHFBDDEDEGHGHBBBFBADHDGCGDBFC,False +82,11.0,21.0,22.0,24.0,26.0,28.0,21.0,21.0,EDGDCDCFGEDEFFFFGEEEDEDEDADACHCEBAFAFCHEDBFEDHDCCAHGFDFDGAGEFECEDBHCECDGGGGGBGFGBHCGDGFFDCAGDBCEHEGBBBBHFHADFHCHCHCACHCBBEFAGBGBEBFFFHFBCEDFFEFHDHFHFCCECBHBDBDEDEHBHEHFBFEGAG,False +83,2.0,4.0,1.0,3.0,2.0,4.0,2.0,1.0,CBFHFBBDGDFDFEGEABA,True +84,18.0,13.0,21.0,13.0,16.0,19.0,15.0,8.0,CBCEEADAFGDCFHFHDHFACACEDGACFGGGCBABDCCCCCCBABABABDBDFACGCGCFCAGEFEFBDBCFEFEAGFDBEFEHEHBAEADAFAFGEGECAHFEDGDHHCAEDEFCFGGGBF,False +85,14.0,12.0,10.0,10.0,16.0,19.0,9.0,12.0,FGBGHDEEEGBFAEAEDHGHGFEDEFEGEDEFEFCBAHCHCFBFDGECFFFGAECBBBDGFAFACACBEDABEBFHFHFHAHAHFEDCDCFCAAHBHADAFB,False +86,14.0,13.0,10.0,16.0,18.0,7.0,14.0,15.0,GGGGHADGCGCEEEDEDBAAGBCDAEABAGAFFFDBEFEAHAHBDBDBDBGHAACDHHGHGHDHEFBCDCHCHDEEBEBDADABEFECCGHGHFHDGEEEADBEEHC,False +87,9.0,13.0,17.0,12.0,12.0,23.0,13.0,12.0,EHCHBDDCECFCFCFABABGBFDFDCDHBGDHDGBGCGCGCFCDHEHEFCHGEAFBFBFDFHCEBAFEDEDFFGHCFGBGFGCDCEBGFHFAFBEEEBGFFCFAACAHAHF,False +88,6.0,3.0,0.0,1.0,3.0,3.0,5.0,4.0,GBGAGBHAGAGFEBEFEHHAHAFAD,True +89,11.0,11.0,12.0,15.0,16.0,12.0,7.0,10.0,BHBHDDADCGCAEHHDCEAFAFBFCDEDECBGFCECHAHGCAEDDBDEAFAFHFDCHEBEGEGADBDBHEHDFGFGFDECECECAAEBEBDBFF,False +90,18.0,21.0,18.0,8.0,15.0,18.0,18.0,10.0,BCBDGCBCHGHAAFAFEFAFDFHGGGCCECEHBHFCADAFAFEGBAAAGAFBEBEBEGCBHBFADAECDGHGBGECCBCBABHFFDCEFEHGBGBGBEFGABCBFBDBEEAHACGCGEGFCFCFDA,False +91,21.0,22.0,23.0,29.0,25.0,21.0,20.0,16.0,EDECECBBDBGGGDHDFCFDFAFGBACHDHDADFDHBEAACACACEDECEDGDGEGEGEDEAFCFEGGBEBGFGEDECGFAFAFGHEDFHFCFBFBDEDFDGBHEADHDCCFBABABACGEHAHFHCEGEGHBHDACADFCCHBHDCDCFBHAGDBABEBFBGCDBEBCDDADAEEC,False +92,22.0,26.0,23.0,24.0,20.0,30.0,22.0,18.0,ADAFEGHDHFFFFDFECADDDFHBHDCBFAHCHCACHEGFBFBCDHEFEGABAFAEBGBFFFBFCFGBHBEBAACAHAEDEDEGCDCDCDCGHACFCFHFHGCFCEHEHCGCDCEFGDGBGBGEGBABGBGCCABBBDBAFGDABFBFEFEDADBFEFDBHGHDFEFECBAGGCGADDDGBHAEA,False +93,2.0,2.0,1.0,3.0,0.0,2.0,1.0,2.0,DBDCDGFFAHAHB,True +94,18.0,8.0,12.0,13.0,10.0,9.0,12.0,11.0,HHFAEHCHCHCDDAFACACACGGFEFGCHDEEGCGCGFDDADGDFDEBHCDABGBABDGAGEEBAFABGBDAHAFAFADADEHHCHCBGEAEA,False +95,4.0,5.0,6.0,3.0,5.0,4.0,4.0,3.0,AHBFEADADAGFHFGGCBCBCBCFCEHEBDCEEG,False +96,6.0,10.0,15.0,4.0,14.0,9.0,14.0,11.0,ECECEGHGHEHGDACGHHHFGFGCCCGFEEHEAAACCHCFCFEGEDHFHFDFGEABBBBEBHGCGBEBGCACBEBEGCCDBFG,False +97,3.0,4.0,3.0,4.0,3.0,2.0,2.0,6.0,BGHFHDHDCDBDECAHAHAEGBFBHCE,False +98,14.0,9.0,9.0,12.0,16.0,15.0,11.0,5.0,BGGACFEGEGEAFGFGFGFAADADACBCFDADGEBHBFDFGBBDCGAFAEEFECHCDCBFEAEAEADADCEBDDHDBGEFCHEHEFEAEFF,False +99,24.0,22.0,16.0,19.0,18.0,22.0,22.0,17.0,BABDFDEDEDEHAACABAEAFFGBHFGAHDBCAGADEDCHBBGEGAGAGAGAGFGABEDEDEFCBABDBECECEAGFGEGBGACBFEHEHAHAFBFBCHEFGDADAEEBCBHHHFHFBAGGGFFFFGHDCCHAHBCBCHFGDBCCAFBDGGFDHDFDFDC,False +100,10.0,7.0,6.0,7.0,6.0,11.0,8.0,15.0,GGHGHGFEFDCHAHFHEHEBACCBCHFHFBCBEBFFEFHAHGHDAGADAEGBGHHBAAADCFHFDADFDH,False +101,21.0,23.0,9.0,23.0,25.0,21.0,22.0,21.0,EEEEEACAHEHDDADHFBFBAHGHGBGDGFECGBBBBFBFEFHFGFGFAEHDHAHAHBHGHFBBHGGGGGEHDDDDHEAFBHHDEFEHEDDGBCDCHBGDDFFCAHADEDEGEGEAABBEBDFGEBABCDFEACFDADAGAGEGBAFABHBDGDCEEEAFAFBFC,False +102,1.0,8.0,5.0,3.0,5.0,5.0,6.0,8.0,HCGCHDEBGFEFECBBBFBFGHGHGDGBAHCFCHHHEDEBB,False +103,29.0,22.0,27.0,17.0,23.0,16.0,31.0,26.0,GGHCFGEBEDGCCDEBFFFEFHGCDCBCBCECFCHCHCHGHCEGAGCECABHEEEBEBEGAGBBBABABFBHBHDHGGDADCCFAFEDECEABGBFAFHDAGHGHADEFGBDCHHDEDCHGABABFGDEAAAEBGAAEGGGGFGHAHDBDCCHGHBDGEGHGEAEACCHCACAHGHGHAHDCACAFAGAFA,False +104,7.0,6.0,18.0,7.0,11.0,12.0,24.0,18.0,GDGEHCGGGEFECEBECGCGHGCFHFHFHCDFDFGACHHHGBGHACDCGAGADBCAHECACGHGHBBCFGHEDEFEHGHBHGGCGCGCHCEGGDGEAFFHFCF,True +105,16.0,23.0,21.0,18.0,22.0,17.0,10.0,18.0,ACEGEHEHAFACDCDCHFBFBGBHDFFFCAGHBBBHBHFABABABAHEGCAEEEFGBGBADGEBCDEHEBCFCHBHEFEBDDDDDDDGFEDEFEHAHBCACACBDBDHDCBCEDEHEGCCFEEEDHHAABCFCHAECBCBFFCFG,False +106,9.0,10.0,12.0,6.0,8.0,7.0,13.0,7.0,FABABHCEGEGBGBGCCCHCAAABGEGDGFGFAFCBCGCEHDCCAGHDHCAEHFBFAGBGBGHFDCDBEEDE,False +107,17.0,15.0,17.0,17.0,16.0,26.0,15.0,17.0,EFBHGEAFDGCGFGFGDEEAEGBDEFBGGFAHHCAFAFHBHBDGDGEGEGDFFFDFHHHAHBCDADBCBFGFCBCBGBFEHADAHCECFCECHBFFFFCDEDEDCDEFEFCHHHCACAEBCGAAAAHADAFHFBDBCFDF,False +108,20.0,24.0,27.0,23.0,19.0,28.0,19.0,18.0,AFAEGFGFGAHFCFEHEGDBBBEBEBEBCDDDHDFGFDCDCECFAFAHAGBBBEBFDEBCBAHGFGAGABDBEAGFCCCBEBHCDBDFDFBBHCHGGCDCDFHEHECGCFFFADAHHHDCDAEEBFGAEHCDDGACACACFCBEFFHAGCCCCEFEFCABDBFFFGHCHDHDFDGBGA,False +109,9.0,16.0,17.0,17.0,16.0,16.0,12.0,24.0,EGDDDAHBEAEABDCEBFFHFHFHCDGHAHCCFDFDFDFBBEBFBFEHGHGDCFCGHGHGCBCEDHBCDHFHFBFGDGACCCGAEBHBABCHHEHBDDEHEDEDEGEAHDHCECFCFCBHAHEGBHH,False +110,5.0,7.0,7.0,3.0,11.0,14.0,10.0,14.0,AHEHDHGFEFGCHFGFBBCAEFEFEFECEHFHBHAHFCBGFABHBEDEGCGFDFACGCGBFEFGHHHHEHG,True +111,20.0,16.0,22.0,22.0,11.0,17.0,13.0,10.0,ACAFFCDCDCACBFAFGDAACDCDEDEFFCBHDGDCDGDEABFEAADDCAHHDHEGACEFBCBCACACABBHDHDHEHCAAFAFCDDEDFDFBFCFBFDEDFFGGAGCCBEBCBHBAGGGGGEGACBHBDB,False +112,26.0,22.0,28.0,29.0,20.0,26.0,21.0,19.0,GCDCBAEHEHGGFABGFFFFBDBDBHCHCHAAADGFCBCDCFFFDCHCECEDEAFBFEFEGGCDCDAEAECFCEEACCBABGFDABADAFHBHFEFEAHAEADFCFHHBHAHAGGDHCCCDHBCADABHBDCGHGAGAGDDDFCAGBCBDBCFCFEHEDEBGGFGFDBCGAGDCDEDGDBDBEFEHAFADD,False +113,4.0,0.0,3.0,3.0,1.0,0.0,3.0,3.0,HAHADDGDHAGAECCCG,True +114,15.0,25.0,14.0,19.0,17.0,16.0,17.0,18.0,GDGCHHEBEBHBEFAFEFBFHFBGHEFEFEBAAAGFGDDFDFDFDBDBDBABABDHCBGDHCEBBGBCBEBAGHCHBEBGHEHEHEACACACACBBGGFGHCHDGBCDGEFDFDBEHECDGBCEHAHDHACFGADFDBAGD,False +115,4.0,7.0,3.0,5.0,3.0,0.0,6.0,6.0,HGHBHBDBABACEGDGEAHBHADGEGCHCBDGDB,True +116,18.0,19.0,11.0,27.0,26.0,22.0,18.0,28.0,FDFEHEBGBGBCFDFDFBEGFABHCHEEFAFAFAFBDHEHEABBDCHCDDGEHEADAFAFBHHCHBFBEDHGHGBFDFGECHHABDEGECEDADEHEDCAHAGEBABCDCDAHEDEDEDFFFFFBFHGAFEGEGDHDHGHGHGEDHDGEGDAHABBHHDHBCDADHEGE,False +117,9.0,10.0,11.0,5.0,12.0,11.0,5.0,12.0,HFBFCFBAAEABGHCHAFABBBBCCCHCECECHCGEHEHEHFHAHCEDDFDCEEBFFFFGEBEAFAHDGBGDEHA,False +118,1.0,8.0,6.0,3.0,6.0,11.0,9.0,8.0,BEBFGFGFBFBGBCDFEHBHAGEFHGDEFBFHHCGCDBGFGFGHCHFHCECE,True +119,16.0,21.0,23.0,14.0,8.0,20.0,24.0,21.0,EEGFBBADAFCBHFACCCFCFEFDGAFHFDABHBCGHHHBHGHCHEGCAABBGDHBHBGFGCGCGCGHFEFCFGABAGGCGAGACFCBCBHBFCFADHDHGHGFDEBEGCGCDBHBEAACHDDFDCDCFBFBGGGGCBHDHDHFABA,False +120,23.0,16.0,16.0,25.0,12.0,20.0,24.0,21.0,DFHFBBDGFFEDCHEEGGGEEADAGAGDBDAABFDFCGDGAABABABABACAGGHDHFACECBDDFDHGHGHBCBCAGFGBGCFFFDFDCGHGDEEHBCDCBHBCFGFDFDHAGCHHHHHGAFADDHEHEAGAGAGHCBAEAEDCDADCFGFDHDHF,False +121,19.0,17.0,15.0,20.0,28.0,24.0,23.0,17.0,DCDFFGAAFFFBGAGDGCACHEHDADADFEHEGGFFEFAABBHGGGFHEHACACBEEEHBAGAGFDFEBEGEBECECDCHBHGDGBEFEAEAEAECCGCEHBHCFFGBDBDCDAEEEAEFFFBHAHGEDEBGFGFGHGBGBDFDCDHEHDDDEBAFDFEGCFH,False +122,24.0,21.0,31.0,19.0,20.0,33.0,21.0,17.0,CBDGEGCBFGFHFHFEFBDAECCCBCBGHDCCCAFADHDHDEDACBDBGAHABFDGEGCHEECECDAFBGBGBFFFFHEAECHFHFHGEEBCFCFDGEGFFFFGCDCGBGBGFFBFBFAAAAAFGBAFABECAGEGBGFHFCADDCECHFAFADAHFHEDEHCFBACAEAEFDCCCCCBCHDADCG,False +123,23.0,22.0,33.0,26.0,18.0,14.0,26.0,19.0,DGDGCACABHFCADADGHGEEHGACAHAGACEDEDEDGDFCHDECFCBCGHGECHCHBEEDEDEDEDCBGBGBABCBCBHAGDGECAGDCCCFCDCFHFDABECGBGFHBBFBEBEBACEDBHHCCGCDAGGGFCCCGDDFCBCBGBGHGHGCBADHFFAHDGAAAAABAFDHDHCFCEAD,False +124,14.0,14.0,13.0,14.0,9.0,17.0,19.0,18.0,DCBFBFAFAHBHGFBABECACGGBGCGCFAFHHDGDGEBDADFFHHHHDAABHFFEGAGFDBGHGAGBGHFHFGCHCDGEGEFCGDGDCDCDCECBFAFCFHAHEBEGHBEBHHADAD,False +125,22.0,17.0,18.0,14.0,19.0,23.0,19.0,20.0,AFFEGCACEHAHBHFHECADBDEDHDHDACHCBCBHFDDAGHGHCECEAEAHBHGGCEAFAFBDGFFFFBAGAFAFHHCGDFFAEBBABADADBCGHHHGACACFCFDFBCGHGEGEGBGBCBEEAFHEBBGGECEFECEHGGEAFDFDFAF,False +126,2.0,2.0,5.0,1.0,2.0,0.0,0.0,0.0,CBABCCCECEAD,True +127,9.0,13.0,13.0,20.0,8.0,15.0,15.0,18.0,GGEFDFEHDHDHBAGABBBFFHFCFHGHGHGHGDADHDEDFCEDAGAGCBDFDHDHCBCDFDBHFHGHFBCGDDDDDABGHDHCHAAECFBDBEBCBCEGECCFFHCGAGF,False +128,26.0,16.0,20.0,13.0,15.0,14.0,8.0,14.0,AFAFGCBFDCCGCBCACACAFACECBAFAFDBBABABHECBGAHADEDCBADABABAHEHCHCHGECDHDHBHBAEDEAEAHBGFAHBBCACACAFEDCAHHEADGEGECEFFFCGHDFDEAEFFD,False +129,3.0,2.0,3.0,1.0,2.0,1.0,0.0,1.0,AHABFBEAECCDC,True +130,3.0,10.0,5.0,11.0,10.0,4.0,3.0,9.0,DBGBHBAEDEBCCEBAAFHHDHDCBEDHBHBHBDECECEDDDFDGDFBEGEHEHF,True +131,18.0,19.0,23.0,22.0,20.0,20.0,15.0,23.0,FGBCAABCBCDCDCBBAAADCEGHAFDFEBHBHAHGDAEAEAHGECHCDDFDBEBHHHDBCFCABFHHHABFHHEGEHBAFAFCDCHGEGEFBFEFEDEHCHCHDHDGFAFEBEBGBGFCDCAEDEGFFFHFBEAGACFDDDDHDCCCCDCDGEGBGCEH,False +132,27.0,13.0,16.0,13.0,20.0,12.0,27.0,15.0,HAACDHGHEBFFCDAGADAEABAGHFHDHCCAEHFHBGBECGGGGAGABACDEDCACACFGFGFHBBEBHGGGDABGGGEDECEAEAEAFCEGBBBAGAEAEABHEAEGGGCEHFHDGAGEDEDFDHDEAAGAHAFFGCCCCG,False +133,5.0,7.0,9.0,1.0,6.0,7.0,8.0,7.0,BGCFEBHHHHACABFBFHFCFGGGCCECGCGCHAEBBHFGCGDAEAEBEF,False +134,14.0,15.0,11.0,16.0,21.0,17.0,16.0,20.0,HBHDHFHDDEFEGEFEBGDFDFBBHBAGEGCFHBHDADHHFAFAHECEFADECEDDDBDBDACBEAFHFHGEGCGDECECBAGACHBHGHFHFHGEGFFHEHCHCEGEGEAEGDGEABDBABFFGECABA,False +135,8.0,3.0,1.0,2.0,4.0,6.0,9.0,3.0,GFGEGHGFEFGCGDBAHAFDEAEGBGBAAAFAGAHF,True +136,14.0,29.0,20.0,23.0,25.0,22.0,18.0,18.0,DGDCEBGFHDBFBECHFEFBDEDCACGCGHEFEFEFAFGGGDCFGFHFHAHADEBBCBCEEEFEBABCBEBACACBHHCFCEAEAGBGDCDBDEDGBACECBHEHBDGDFDGCGAFEFDBHBEBEAHGFCFBFBHEDFDGDBBBBACDBDHGBEAEGFCHBHEHDHDFD,False +137,3.0,5.0,1.0,6.0,8.0,6.0,3.0,5.0,FDFDBBBEDEHEHEFEACFFGDHDFGBHAEAEBEGDH,True +138,17.0,19.0,28.0,23.0,19.0,29.0,14.0,27.0,EEHFCDHDHBAADFECECFFFCDGBAHAHFHBCDDFDGDADBCAAHABAEGFHFHDHDEGCGHGHCFDFEFGBHAHBCBABEEECDCDEHFHFBABHCCCACHEACHDGDFHFHBHFGDGDGDFBCDCGABFFDFECHCFFFHFCDGEFCACHCHCHEGACFCFBFEEECEBBBBD,False +139,18.0,10.0,15.0,7.0,19.0,9.0,15.0,15.0,BCDGAGEBBAAFCBEFDFHCAAHABFEADAHGCCCACEDEDEDEDEHCBCFEHCHEACACHGGGGBGEGFGFEHECGFEAHGHEHEHEHACAFBGGABABHGHEAEAC,False +140,12.0,11.0,10.0,15.0,15.0,9.0,10.0,21.0,GGDEDEDHDABGBDCAFADADEEFHFEEBBAHECFCAHGHGHEBBCBABAFHHHHAFADHECEGGBGECECHBHECFCDDDEEHHHHHDHDHDHFACGDABFG,False +141,6.0,7.0,16.0,10.0,19.0,4.0,7.0,3.0,GAGEECEDBGBGFCFCHCFBDBDECEAEDBDCHBEEFAHAEAEGCBCEADDDDEGCCEEEECCCECDCGCEE,True +142,17.0,14.0,17.0,18.0,21.0,18.0,15.0,9.0,BADAGADHDGDGFHFAFDFGEEDDDADCCCGGECCCGEHAHAHEEEEAECFCDHDFABABFBGBCACEFFDADAEEHBHFDFCBEBGHGCFCDAGFDBEFFGFGEGCBAEDEBCBAACDCBEBEFEFEG,False +143,1.0,3.0,4.0,4.0,2.0,3.0,3.0,3.0,DHDCCGCGAGHBBFEFCFDHDEB,False +144,3.0,1.0,7.0,1.0,1.0,3.0,7.0,2.0,CDCFHGGFBCCCCGAGAGAEHFGCG,True +145,3.0,5.0,7.0,4.0,3.0,11.0,6.0,3.0,DHGEGBGBGCCFDFAFHCBEBEBDFCFCFGFCCAHFFFDGAF,True +146,4.0,13.0,6.0,8.0,6.0,15.0,9.0,3.0,FABGBGFGFDBBBCGEEEEBFGCBFBDBCFDFGFGFAFECCDDADAFBDGHGBFBFHFEFHCBD,True +147,16.0,16.0,22.0,23.0,21.0,20.0,35.0,29.0,FBFEECGAGFGFGHDHDFAGEGEHFHFHFEGHGCEEAHDGDEHEGEFHFCFHGHBECDBDBHHGGGGGGCBHAHACAHAGEBDCEAGGHGHGEGEBDAHHHCHADGCFBFHGBGCHDFDFDGHCBCHHAGBEBDACHCFFGGGDADEEAGCEDEDCCCGDFDBDGFBFBGBDEACACDCDCH,False +148,16.0,20.0,20.0,23.0,21.0,16.0,31.0,18.0,EBEHGGGHCACFDDDDDAFCHEGCACFCFDFAGADEGGGAGEECEGEGEGAFFDCBHBHDHEGCDCGBGBGCCCCCBDGEBCGFHCHGHAHBBCEGEGEBFBGAHABDBDAGAGFGBEEEFEDGDAFCHBABGBADADEGFFDHDCFGGDHBFBDEDEDGHHHBH,False +149,3.0,7.0,4.0,6.0,10.0,7.0,3.0,5.0,EBEHEBEDCFCBBADCHFHFGBGBDEEEECHBDADADEFFFGFHE,False +150,6.0,2.0,7.0,6.0,2.0,3.0,8.0,0.0,DDDCGCADFDFGGGACACAGBECGGDGABACFCE,True +151,5.0,2.0,2.0,0.0,5.0,4.0,2.0,3.0,GAGAFBFEFECEFHABAEHEACH,True +152,14.0,12.0,9.0,7.0,12.0,11.0,10.0,17.0,FDHDFEHDHCFCBCDGHGCFFFBFHACCHBGAGAHEHEBEAADAHBGBFBFBABABAHAHEEAFHEHBHEHABGGECDCECEAGDHAHEFGG,False +153,19.0,24.0,27.0,19.0,23.0,23.0,26.0,24.0,CDCGGGFAAGACHFHDHDHBBCCHCGFAHABGBEDHBGBGBABADECFFFFAGGCHDDGDGCGHGHGDCFHDHAFEFEFEHDCCGGBGEGAAFCEEDFDFGBEAFHFCGEBCBHBFBDCDGBCBEHADABCHCHEHEHBHDGFGAGEGBBEBHDEEHAHAEAECCFFFCCCECECEFBFBDECBA,False +154,13.0,10.0,11.0,9.0,11.0,8.0,12.0,4.0,GEAEAFAGADADAEFCGCGCGCAFBFBEECEGADADACBGBCHHBFEECACBEHEFBFBDADEDBCGGGBDFHCAGGD,False +155,23.0,15.0,20.0,21.0,22.0,13.0,16.0,23.0,FEBEBEBFDHDHCCDDBCBEGFDFGBHCHFDAEBCBFHAHGHDADCBGDHDHDFCAHHHDBCEHDFDAAECDCDCBCAFEEEEEAEAGACHCEGEAEGGGGAEABAFAFHHGEAAACHFHAHFGEAEDEDEDADHDBCGAGACBCHHBGGCHC,False +156,1.0,2.0,8.0,2.0,1.0,1.0,0.0,3.0,CCCCCHCHBACDCBHEDF,True +157,11.0,6.0,5.0,14.0,10.0,10.0,2.0,6.0,EFAHAHFBFGGABADFCBEDEDADAHAFAHBFEDEDCDEDEDEDFFCBEDFDFBACDDAEHCHA,True +158,15.0,22.0,16.0,16.0,9.0,21.0,17.0,9.0,CFCFCAEBDGDHBBFBHCAAGFFFAGGGGFGHCHDBDBECECECFHBBCBAFHFDFBCACHCAAAEFDBDBCFGAADADAGGBBBGCGBGCFBEEGHGFGFDFDFABABDFHFDBDCEFEBGDDB,False +159,3.0,6.0,10.0,6.0,2.0,3.0,4.0,5.0,GGGFDFDBCBHBHBCCHCBCEHHFCACDCBEDDDACGCA,True +160,7.0,12.0,7.0,6.0,6.0,8.0,8.0,5.0,AEFEFEBCBADCEFHHCHGBBECAABFBFBDBGBHECGDADADGBGAHFFCFCGDGBGB,False +161,25.0,18.0,13.0,27.0,15.0,21.0,17.0,28.0,HFHGDDBDFDGHGADHGFBHGCFDAECCHHEFEFEDDBEBAHAHFHFBFHAHDFDFAEDFBBCEHADGFGAHDGDGDGDFCBCEAEBCBHDHDHAHAEADHHFHFHEGBHEDABABACDCAEFDDGFGAGABAHDHDGDGDBHBFAABAGAECECHCACBFAFH,False +162,18.0,23.0,16.0,12.0,17.0,23.0,24.0,31.0,AEABABCBCHCHCFFFBHHEGBABDDDDDHHFHEECFCFCBEDDBHBHBCGHDFAFHCHFGCHHHHHHHCFGFGEHDBAAEGGHEBBHGDAHFHBHBECGFAFBGCAHEHGBBFBDCHHGEAEHGFFFADGEGBGBGCGFFCHGEGEGAGAFABABAEAEGFGF,False +163,24.0,23.0,17.0,16.0,25.0,31.0,34.0,30.0,FHFHFEFGFBAEHHHDHDHFGGDGDGFGDHACAFGDGDECECHCGAHAHBBBBBFFFCGBGEFFHFEAECGGBBAGABABAFHFHECGDECFCHDBACDEHBFBHBFEFDDGCHBHGHGHBEAGFGCEHFBAHACEHEACFCFEAEGEGAGACFEAEBGGFDBDBGEGECEAHHHAGBGHAFDFAFDFGBGHGFGAGHEE,False +164,16.0,17.0,19.0,27.0,19.0,29.0,35.0,19.0,GDGBCCGCAFBFGFDHGHBFAFGFGDDECECDGDCDFHFGFCFHFEABACFHFBFHEEECEDFDEDGGGDGCCBBDBFBABFBGDEDEGBHBDDDGGGGCFHFGFGFHFEABBDCDCHCGGGDGFGEDADHDECEAGAFAHEHADAFFGGGCABEGHCAEFGFGAGDDHDHBCEHGAEHFH,False +165,10.0,7.0,7.0,12.0,6.0,6.0,5.0,8.0,DGFFDCDCDAEGDBDCEBGACECHCECDBABDEAHDHGAAHHHFHFBFBGBHDADADAFAE,False +166,17.0,18.0,17.0,16.0,20.0,19.0,17.0,15.0,CACAHAFBDAAADADHBGFAFDGDGDGHHFHFGFGFHHCAAEBFBFCFAHEBABEEGEGEGEBAHGDCDGEBCHEGDGCFCEEFECBCFHBHBHBADDFBFBGDCBCFFEGCAEGEFBACDCECECFDDADEEEGHBHB,False +167,15.0,4.0,11.0,15.0,21.0,12.0,17.0,17.0,HHAHDEDGHFHEHCHGFGFCECEGEACFGDGDCDCHADCEHEGGAEEBEBFHHHCHCHCFDAHAGDGFGDDHEEGCAEDEABAEGEGHGDDFAAEFGAGAEAFAFDFEEBED,False +168,8.0,4.0,9.0,2.0,9.0,7.0,3.0,7.0,ECECBCHFHCGFGFEEEHEHECAAHAFFBAEAFHBGAEAHDBDACCCFC,True +169,16.0,14.0,9.0,11.0,11.0,11.0,12.0,11.0,DFDFDGAGAGAGFGHHACBHBHGFFDFGBCEAHBDAEADACCECAAEABBHEAEAEDEDCABABCBGGGGFFACHHBDBFFDFEEGBCDHEHBHB,False +170,4.0,2.0,1.0,1.0,6.0,4.0,5.0,2.0,GGDBEEEEBEAGFFCFGFHAHAEAG,True +171,28.0,14.0,20.0,10.0,8.0,25.0,20.0,36.0,HCHCDCGCDAGAGHGBABAFAFCFAFDFGFGEGHFEFHBHGFGCHEHABFGFHHHCFDACHEFBHHHCHAHGBAADCHBHBFAAAHHHFEGCGDAHAGFBFAADAEACFFGAEAGABFCHCBFDEAGAHBHBAAHHHFHFHCCACGHGHDHDHCHCFCBGF,True +172,3.0,11.0,4.0,4.0,5.0,7.0,5.0,5.0,BBBEBHHCCFEFGFGHGBBBGBDFAFACEHFGFHDBDBABCDEE,False +173,8.0,13.0,6.0,15.0,4.0,10.0,15.0,7.0,ACDCGBGFFFGEGBGFHBHDADHDFGBGBGHCDAGGGCHDHGADDDDDDEBBHBFBFGFAEADGCCBDBDGAAEFBFB,True +174,10.0,11.0,8.0,10.0,13.0,7.0,14.0,11.0,GCGCGCGFGEBCAAEEHEAEHDHDGAADADADFBEDECHCGGGHGEEHBHAHABFBEBHFADGDHEECHBBFBGEGBGDCFBFD,False +175,23.0,12.0,12.0,24.0,26.0,34.0,26.0,24.0,CDBFHAHBGAAFEGHAFGCAFGFGBGBEBEAFGDGDFDADCFGEGBFCHABFCGADHFFEFHFEFEFEDHFGCGEGEAABEGAGHGEAFAFAFCFAEDEDEDHDHDHFFFGFHACEFHHHDHDAGFDFGEGBGDHDBABAFEEEHEBGFGEEAEAHHFDDDGHGHDFCFCACHDDEDEFHC,False +176,18.0,8.0,20.0,16.0,15.0,17.0,11.0,11.0,FCFBECGAFAFABAEEEEDCDAECEDGAAADFHBDBECEHEABABCDCHBGEHAHAGAECHHHADCCCCFCDCDAGCFFEEAFAFGDDFHFHFHDBGGDGDADFGCECFCGCDCFF,False +177,13.0,12.0,13.0,12.0,6.0,11.0,5.0,9.0,DABFHGHCBDBDCFFGABAFEBACAHECGDFFHFHFDFEFCHCBCBAECGCGCHEAEADDDBDADAHHBACABACDCDBFB,False +178,7.0,14.0,10.0,12.0,19.0,22.0,10.0,9.0,FDECFBFDFDFHFGCEDEDEFHGBACCEGGAEBEGABFDFDFCHGHFFEDBFBFBFEGEHADAEFEFEFEABCFHDHDAECFCGBFBGBFBEECECDBEBHGH,False +179,2.0,2.0,2.0,1.0,5.0,4.0,1.0,6.0,HGFEHEHEFEDAFHFEABBCHCH,True +180,2.0,5.0,1.0,3.0,3.0,4.0,0.0,0.0,FAADBBBBEBEFEFDDCF,True +181,6.0,7.0,5.0,2.0,1.0,4.0,3.0,6.0,BHBDBAAGAHCHFHACAHEHBBBFCFCACGGDBF,True +182,2.0,3.0,10.0,6.0,8.0,6.0,4.0,4.0,BCBCECEAEDEDHCCCCHEHEGDGCFFFAHGBFFFECDDECGD,True +183,27.0,20.0,35.0,20.0,19.0,18.0,17.0,19.0,CHCHCFCBDEHBHEHCCCCBDBAADFFECCGCAEAFAHCFGDGAGACABFEAHCBDBDBDACGDEDEDEHEBGDGDCAGABEBEAECEGAGFGCABFGFCEAEAGACFCDCFFGFEHBDBDECACAFHBHCHBHBFAHDBCADHEHACAGDDDGCEBFBFCCCCGAHCFCACAHH,False +184,21.0,29.0,29.0,14.0,13.0,23.0,22.0,20.0,HBBEFAHAHDHCHCGCBCAFABDDHDFAAADBDBEBCBCBEACGCGFFBFAFHGHFCFEHCHDADFCFCEDBGBCCFCFGFHCHCACBEAFBECFCDAGGCGFGHGFGEGACCDCBHBACGFGFHFBFGEGBCHCBCDEBBCHGGBGBDDFAAAEBEBABHBABHGEGBHA,False +185,16.0,21.0,7.0,5.0,16.0,12.0,3.0,15.0,BBBHGHBACDBEAAAFDHEHAGAGAEEEHHCAEAFBBABFBCECAFAFBFHFEDABBBFBEBEBEBACHFHFHDHBFEAEBHAFCHEDECEHBHB,True +186,26.0,34.0,20.0,22.0,24.0,21.0,26.0,17.0,HFACACHCBBBBHBGBEHFHFEAHAEAEFDBHECAHAHDDBGEDCBEGGFGECAAADBEBGCGCFCFCFBFBFBAGCBBABEHGCGCGFGBBCHCEDAHBCEAEHDBAHGGDDDDHEADDDDDFFGBGAGBGBEBABDBDGDGBFBDBDBDHEFEFCFEAAFGEBCGEGBFFGCGAABAGCHEEEAFAEA,False +187,3.0,5.0,0.0,1.0,1.0,2.0,2.0,4.0,DEBGHGAFBFHHBHBABA,True +188,8.0,11.0,10.0,11.0,8.0,19.0,14.0,12.0,HGFBFHFBFGGAHDDEBAHFHFHFCEGFGFGFGBGEGBCEEAFDBBBHFHDBDBGACHCHFGCGFGCGFBCDCDFFAEAHAEFDFDHAECDCD,False +189,24.0,32.0,23.0,32.0,21.0,21.0,20.0,22.0,BBBABAEECDDDEDEHEBECEDEDHHHFHFDFHCDAHAHDBGBGEGFGFGFGFBAGCGDFBFHDHBBCHGHGFAEBEDCAAGFDDADADBDCFGHBABDHECBDBAAHADAGCDCBABABGBHDCGCBCGFEBDCHAHCCCFCFEBABHDDBGBHHCCCGBABDBCEEGHAFEFEDDBAFFFDFDCEAEAEGDBD,False +190,13.0,10.0,11.0,9.0,7.0,16.0,9.0,11.0,AGCHAGCBAHCBGBEBEACADADHDBFBDDAGEFCFCBHDEFEFHFHGHDFGFACAEFHAEAGGBGFCFCFHFDFCFCBBFDAHAH,False +191,14.0,3.0,6.0,9.0,14.0,7.0,4.0,6.0,EAEFDGEEFCCCFCFEAAAEADCDAEAEGGAFHHHHEAAADADEFEBDBAEGECEADFDHDHB,True +192,6.0,4.0,7.0,3.0,3.0,3.0,1.0,4.0,CFGEHCCFCBCEAEHCHDADADABBBACAFH,True +193,29.0,36.0,21.0,12.0,18.0,14.0,23.0,24.0,BBHFFFCEHEGEHDHBGBHBHDEBHBHBEAEBDBFHFHEHABADACGGGADBBHHFBBBAAAAABECDCACHCAGACFCFAEAFAFAGGDAEBDBHBEBGACBHFAFGFGBBCAGGBGHDCBBDGEHEGEACACACEBEBCACAEGDGHCBDGHGHBBABCCHCHCHGBAEAGBFBG,False +194,6.0,3.0,5.0,1.0,2.0,4.0,8.0,5.0,HBHGGFCFCACAEABGEACDCHBGGHGAGAFHFG,True +195,3.0,6.0,4.0,7.0,9.0,15.0,5.0,10.0,HAHEHFGFHHGHGFFCFCEDEFEDBGBDEDACBDFHEBFHFHFEFDFCFDFABEBGHFE,True +196,2.0,2.0,8.0,2.0,3.0,5.0,4.0,4.0,CCECHCDCDCEBHCGEHBHGAAFFFFGFGC,True +197,0.0,3.0,4.0,2.0,1.0,2.0,3.0,2.0,DBHBDFCCCGCGBGEFH,True +198,9.0,8.0,9.0,4.0,11.0,7.0,12.0,11.0,AAAFADHGGGFGCBCBCHEGEFEHDCABDHGEGEGDACBFHFBEBGBECEHAHAHGBECFCGEGAHEHCHF,False +199,9.0,8.0,10.0,11.0,7.0,10.0,5.0,6.0,ACADDFDHDABGCDEBEHAFFBECECDBBABAFAFAEAFHDDDHCCDCGCGHGDGHFCBCBFFEFE,False +200,15.0,9.0,5.0,13.0,12.0,23.0,15.0,22.0,CHGFEHBDGDHEHAHDFDFAEBDAHEFEFEGGGGAAAGEDAHGHGHECEGFGFGAGBFEFAFBFBGBDFAFHDHBHFHFHGDEDHFFCFEDBDHFFFAAHBHAHFCFDHHCHAA,False +201,8.0,4.0,6.0,6.0,2.0,3.0,2.0,2.0,AGCFBBCBCDAHABACEHDADADCDADAEFGFC,True +202,15.0,30.0,30.0,30.0,15.0,29.0,25.0,23.0,DFBBDGHBCEDBFBHBHBCBHEGGGEBEBHHEHCFFHFGBHEGBDFDFGBGDFDFHCEFHCGCFDHDFDEHADADEBCFEFDFEFECDAAHFGDDDCACACACACDBABGGEDAABBBGCACABFBGDCDAGGGGDCDFFFGFCBBBDBDHECGHGDGCGCHCHFBFHHHDHCEBFDFDFCFCGCBCBCFCDABHCG,False +203,14.0,19.0,19.0,3.0,12.0,14.0,16.0,22.0,CHAEADAHBHBHBHBGGDBHFHEAAABCBGEFCCHFEBHCHABABFHCCCHBHAGAFCFBFAAAHCFCGEGEHEHEHFHBHEGFGHBEGGGCCFGFGCDAECGCBBGBFBCHCHCGBFE,False +204,9.0,15.0,19.0,11.0,9.0,19.0,20.0,15.0,FAAACCHEGCGDGBHDCCCEBAHDGDFDBDBHCFGFCFCBCBFGFGHGBFBHHHFHEGBGBCAEBCCCFCFCHGAEFEAGCDHGHGFGFGCGBGBGFDACEBFDFDEHEDGHABFHF,False +205,20.0,16.0,16.0,34.0,30.0,20.0,29.0,29.0,CDCFGDGDEFHGHEHEGGBGBGBHBGEFECDCEBGDAHGCBDDGDHDHEBEDDDDHAFAFDEGCHEGFHFADBEEGAGDGDHFHBDEAEAHAHDDDECGBADEHEFEFDACAGEGFGBDEDECHHHEAEFFBADDDDAEAHHDHDCCFCAAAHCFCFEGHHHHGBGBDCHCHDFDGGEGBFBGHFAFEGEGEAE,False +206,20.0,18.0,16.0,14.0,21.0,4.0,6.0,11.0,ABABAFADEDBAECHGDDAAHEBBDBACECGAAAACHEFEBCDHGBCECECEBEFEAECBCEHEDGAHACADAHACECGDDEEECEHHHFECBCBEBHBDBDBDBAGDBA,True +207,1.0,3.0,2.0,6.0,1.0,4.0,1.0,1.0,FCADBDBGBFEFDFHCDDD,True +208,5.0,3.0,5.0,6.0,4.0,0.0,1.0,2.0,DCCBCDCDCAAAAHDHBGAEEDBDEE,True +209,9.0,6.0,7.0,6.0,5.0,8.0,3.0,2.0,FCFEAEGDADABCBCFGAGCFAFABABCBDHCFDFEFEACBDHEAD,False +210,21.0,21.0,15.0,16.0,11.0,15.0,20.0,12.0,CACFFACCCEHFDBGBGBFHFAGDGDADACGGDGBAACABBECECEGEDHDHCABDFDFDAGHGHGBGBFBGEGBFDFAGAEHFDAHEGABABFGAGEBCCGCHBDEDGBCACFBFAFHDBEBHBABADAH,False +211,10.0,24.0,13.0,13.0,14.0,11.0,16.0,23.0,EDEABACHGHAEGGBBBBECECEBBBAHGHGHCBCECDCBFBHBHFHFHFBBDAGFEBHAHDHGCFAGABCDDBEBEDHGHBCCACFDDBAHHHGBGBGEGEGHGFEFHHHDDBBCDEFGFHDH,False +212,19.0,7.0,17.0,13.0,17.0,11.0,21.0,24.0,FGCAHAHFGEHAAAAAHGDGHGFEEGDHHAEAEDCDFGBGDHDGFECECGGEEHGHGHCFBBHBFEEHGHGHDHFHDHDAAAHDECAAACBCECACAHFDFCCCCCCGGGGGEEEDHBHEFCGDHAHAB,False +213,10.0,20.0,7.0,7.0,13.0,11.0,10.0,5.0,HACBEBEBAGEEHEDAFABBFEEEBGBGBGBAAEBBDDFDFDFHCHDDAFECHBBAFAGGGFAFCGBEBEBEGGBFFCBCBCB,False +214,6.0,9.0,11.0,6.0,13.0,4.0,11.0,19.0,ECECBCFDGEGBHEDDHGEBHHGCGCBHHHHHEHEGACABADHFFGCGBGHDDCEEEEBEFHAECBCHGHGHBHAHAHC,True +215,3.0,0.0,0.0,3.0,3.0,2.0,6.0,5.0,HDFDHEHGGGGHAHAEGEAFDG,True +216,1.0,8.0,11.0,12.0,14.0,8.0,9.0,12.0,GEBDBDCCADDBGFGFEEGEGCDCEFEGEBEDCCFBHCEDDGEHEHDDFCHHHBHBHBCDFDEGEGCHCHEHFHF,False +217,10.0,10.0,22.0,13.0,14.0,8.0,15.0,10.0,DCHGECECEAGHEFGACFBGBECGCAEBEHHAGEGFDFDFHEDDCDBFBABACDDHDBDGCCCGHGACFCFDGCGCBCBGAGACECACBCECGDHEHEHECD,False +218,7.0,10.0,14.0,5.0,9.0,7.0,7.0,16.0,CFCECECDHHHHHHHHBBBHEFCCEBDBABAGDFDHCHGACCHCHEFEGHGDACFBGBCEEEFGHGFCBCHAAAB,False +219,15.0,20.0,16.0,12.0,13.0,12.0,14.0,14.0,AGAEAEAHGHFBFEHBHFGGEEHCFCDADACBDBFBCBFGFBBBCCAEGDGFAACAHBCBCDAFHFHECAFFEGEBCBGGCDCDCDEBBDBDBHHHHHDGAGDCHCAGEGABBEBE,False +220,0.0,1.0,1.0,0.0,3.0,3.0,1.0,3.0,HEHEHFFFGCBE,True +221,4.0,7.0,18.0,11.0,9.0,20.0,14.0,16.0,GGGBFCCCFBFDGCFCFDFHFHCDCDHHHGHFDCAGHCBAEEFEFEFHAEFCHCGEFCCCHCHEHCDCDAGBGBGCDDFDFGFHEHDHFGEGFHFGFBB,True +222,19.0,32.0,14.0,24.0,24.0,23.0,30.0,29.0,EAEAGFDFDCBHFAFADGBHBDAGCDEABDFGEEFFFEEAECHDHBHDGAHHGBGBGBGHCDFDBDBDEDADHFFAFEFGBHBGDCHEDABGBEBCDCHCBFAFBGBAHFHFGEDFHHHBBBBDBDBDBGEGBHEACCHEGEGEDEHECGHGFBHGHCBGAGHGHGEGEGEHAHAHFCCEFHFAGBGBGDADFBB,False +223,6.0,4.0,7.0,6.0,14.0,14.0,8.0,15.0,CEEFAGEBDFAHHDHFAFAHBFFHFCFEHHHHFDEGEGEDEDGAGHDFGBGBEFGFHHCHCHEHECFCACEEFE,True +224,11.0,10.0,13.0,13.0,21.0,14.0,25.0,19.0,CGBAEGEGEHHCGGHGCCBCAEBEGHCHDFDFDFEGBDFDFEFAGDGAGEGCGBHEEGCGBEEGEADACECABEDCDFFFDCAGAGHFHAHGEGEGEGBGBGHHHHHHDABCEDHHFFDHEHEGFF,False +225,6.0,19.0,5.0,11.0,12.0,6.0,9.0,5.0,GBHBDBABHBCBDEDBGBGBEBEBCCFDHDFEBBDDEAEAEAECFGFGEGABCFGBBDHDEFBGBGEEABHDD,True +226,11.0,18.0,23.0,14.0,12.0,26.0,20.0,26.0,EFEFEFGDCDFBHBHADECHHEHEFGFGHCBGACBGACFDFGFCFGFCCCHHHBHFHFHDADFFEBGFFFFFDBCCFCFHFCDGEHDFDBDCAGGHHHHHHBACGCGAGBGHAAAFFCHGBGCADGBBBCGDHEBEBEBEBHCHDHCCCG,False +227,23.0,20.0,28.0,18.0,25.0,23.0,23.0,21.0,FCCBCEFEDAGGBEHCHCHAFCCADFFHFEFAHCHDGCCHAEDEDFDGAGAGAGEFEBEBHHEFEFHFCGDFBGBDHAHBGAHFFFBFCDDADCDEEAGABHBHGHCHCABADABCHCHCDFGHGHBAFFEGECBGADCECGCGCBFEFDFCGCGDEECAGAEAGAGBBBBBCEEAEDECE,False +228,5.0,3.0,9.0,5.0,8.0,2.0,3.0,5.0,DDDACEHGFBCEAECCCCCFCEHEHEHEBCDAEBDHAGAG,True +229,15.0,19.0,18.0,23.0,23.0,15.0,10.0,23.0,HHFHGHEBFHHBCBDEEHCBGBAHAEDEDCGCGEBBDDDDEDBDHDFDEDACCEEDFCEEECBCBCBCDAFEHCFAHBEDACAGHHHHHHHAHGFACACAFBEBEFFFFFDEBEAEGCBEEDADACBHGCGBGDHDHDFDHDEABF,False +230,15.0,10.0,14.0,14.0,7.0,9.0,3.0,6.0,EDADBFADCDCDEBFBFAFEFEDCBADFBFBAHACCBCGEHEHBCCAGDCFFBAAABAGACHCHDDCCCEDHDADADA,True +231,21.0,19.0,19.0,16.0,21.0,13.0,13.0,23.0,EHBFBHBCDAEACABABEHCAAAAAEBDHDCECACAHGFCFBFBDCCBDBDECHCGCAAHHDDCDCDEEHHHADAFBFGFGDGFGHGAGEEFEHBBDBGHAHGHEBCCACACGEDEAABDBCEDEFEHBHEEEHGHFHEHFFGHB,False +232,10.0,11.0,13.0,7.0,8.0,12.0,12.0,9.0,EFGGGHCHBAEHFDFEADAHBBFBCGFGBCBCBCFHFAFAGCGCEBEDCCCHCHDGGGCGCADFEBEBDAFAFAHEFGBHDA,False +233,16.0,18.0,26.0,21.0,12.0,11.0,22.0,9.0,GBGCHBGDHEHDGAFCFCGCBBDDDHHGCEDEDCDBGBEBCCCCDBGBCACBGGEHEDGGAGACFCFCHCGGDGABDCCCGDBDEDEBBCHCDCDBDAGECECAFEFBFEAGAFAGBGAGDDDACAFAFAFCHBA,False +234,8.0,5.0,2.0,10.0,3.0,5.0,9.0,5.0,GAGBBEDFDFDBDGDAEADHGAGHBDGDFDFCGAGACABAGHHHFED,True +235,28.0,16.0,21.0,19.0,24.0,21.0,12.0,20.0,EDHFBEAFADABHFHFCFHFACCBBBHAHDHBADGDBCBDFEFDHHADACBHBEAEDDDGAGACAEHECFCECHHHEABFCFEEHGAFFFADADCDGEEEGEBECEBBCACAHAHADADFFAFAFHGDEEFEBCGCGCGCDCAHBGEEFGADECECAFAHA,False +236,13.0,6.0,14.0,8.0,9.0,13.0,7.0,14.0,FCFAFAFAHAHCDCDGFFEFECEDBCECDCFHEEFAFACHCHCEBGDHEHFHAHBHDHFCGGAGDHHACCBHDCGFGBAAEABA,False +237,4.0,7.0,4.0,12.0,6.0,4.0,7.0,10.0,DGGHBHDDDGDGCGCGADBHEDEDAGFCFEBDHDEBAHAFEHEHCHDBDBHFHB,False +238,25.0,27.0,17.0,20.0,11.0,20.0,27.0,24.0,BGGGHACECEFEAEDBDBHCGDGDHDHBHBHAHAHFBFGCGCAHFHABABEFFDDAAFHFHDAGADFDGBACCCHGHDAACHCHGBEBCCCBDAFAEGHAHGHGEDBDBCBHBGFEAGAGBGBABDHDGAGADFBFGFGCAEBGFFEHBBGDGBBBFFHFBFCDAGCGHDA,False +239,27.0,19.0,14.0,12.0,26.0,20.0,17.0,18.0,CACHFHBABHBABAHEGBDDEBFAFAEACABAFAHAHGHDFEGEFEBEBEAFCDCHABAGEGEDFBGBACAFDCDCAEHEHFHFEEEFABABCGEEEGHDHAHBHDFGEGBAAAFDHECEAGCGEBEDCDHFAFAGAGBGFFCGCEHGFEBEF,False +240,13.0,5.0,13.0,8.0,10.0,9.0,13.0,11.0,HCHAGAEFGBGAGFGCDCAGAECGCGEFEDHGFADADACHDFDGBCBCFEDEFEFBAHHHHHHAAFGCECACBCGEHEADCG,False +241,15.0,13.0,22.0,21.0,14.0,24.0,13.0,15.0,CECEBACABEFHFGBEFDCDBABGDAEADCDHGFGFDDDFDFDFGFEFGCGEAHGHGHCFCDABFEHHABCECBCHFHCACFBFBHBADFEFEFDFDHDHCHCDEDAGGECHAFDHCABFCFDFDGBGCFCACDCEA,False +242,10.0,3.0,9.0,4.0,10.0,22.0,6.0,6.0,CBAAFFFFGBDAFFFFFFFDGAGEHFGECEFEFHCHCEEEDCFAFAHAFBDEHGHCFEFCFCFEAAFAGC,True +243,16.0,18.0,13.0,25.0,8.0,14.0,16.0,17.0,CFHGHAFGFCFEDAGEBBFDGBGHDHAHBGBGBDCHHEBDBDBDCDHDHFAGGHGHABADDCDFBHAGDDDBCACECAGEGDDHDFDFHFHCGCGCDBAFAFDBDEFEACADADADBCFAHBHGEBB,False +244,14.0,10.0,26.0,18.0,17.0,28.0,19.0,21.0,HEHEHDFDFEGEGFGDCBBDAFHFHFDCEGBBDHFAGBHFHCECHCGAFCCDDADGHGCGAGBDCDHDHDACFCFGACEHEGDGFCFCFCAEFHHHFBFDFDCBCFEFCDGAGDEEFEFHFHFEECCCAAABECFHACECFAFGFCBCGHGHG,False +245,30.0,27.0,23.0,25.0,28.0,19.0,14.0,26.0,AAACACBCAEDEBEFCCHCAEGEDEFGAGCEAEADFEBBBEFAGBBBFDAEAEHHHHCFCHCHADFDEBHFACBFBGBFBCHHAHAEEGHHEAEGHGHGHGCAHADADAEAEAGDGBECHDDDDEFFDCDCACAFBFHCHEHEADFBFBGBDBCGABHBHDACCECDDBDBDFDBEEEEHCBAFHHDBBADF,False +246,9.0,17.0,16.0,9.0,17.0,6.0,11.0,16.0,HGEGACAHDHDCDEGFHBHDHECEDEDFDEEHCFCFHBEGGFABEHHHHGAABCCDBEBECHCHFBAHGCGABCBEBECCCCCEGEBBBBDBABEBHGEGA,False +247,10.0,6.0,15.0,20.0,23.0,16.0,16.0,6.0,AFDGEGEFEDCDFHEGEGFGBCACECEAEHEDDHEGEDEFGDDDCCCCGAGEDBABEFEFDGDHDGDCBHBGFFCFCEEEEFCHEFGDGFCDADCFCAEGFGBEFDADADAE,True +248,1.0,1.0,5.0,2.0,5.0,7.0,7.0,2.0,EFCFDAGFCFGFCHEHECEGGCGDGFGFBE,True +249,20.0,25.0,23.0,25.0,18.0,22.0,28.0,20.0,DGDBDAABACHGHEBDCCABFBAHGGBGEAAGDDFGFAHADADEDFHFHGGGFGFDHDEDBACDGDGBFACABBGBGEGEGECFFFEABDEDHFAFGBCBCACHHFHFBFBFHCHCHCECDGDCEHEGCGBBFBGEFEFHCGCBHGDGFHFEABCCEBDBHGDGDGBHCEDADCDCBAEAC,False +250,27.0,24.0,20.0,16.0,26.0,17.0,25.0,11.0,CHCBCACHBABAGHFEEBEGECEBEBEACDGDHHGAAFGEGABEGAGEGADADABAECFGBGAGAEBEADFGFECACGGFGEGDGFBFGCGBFBFEAEBEFAFAFEDEAAAAGBBBCDCDGECCCBCFADABHDEDEGEAHHBDEDFDFGCCCDBBHAHGBCBEHF,False +251,23.0,19.0,20.0,25.0,22.0,22.0,28.0,26.0,ACACGEBFHHCAGAGHGHGCGCGBEHFHFCAGFGCGHEHAHADDDDAEEEECCFBGHAHAHGBDECFADGCECEGEGDGAADBEAEFHFDGDGAEAFDECBGECCHDEEBGBABEHHAFFFFEFDADHBHBDDGGCGCBAGAHABDBDEFEBCBDHGHGFDFDFDFHBAFCBDBDFFGGCHHHDH,False +252,22.0,23.0,23.0,11.0,21.0,24.0,27.0,23.0,CGGAGEGECECECDBFFFHAHGEGCGAGACEDBBBFGFGHGHFCBGHFHBHGEAHAHABDHABABDBECHAHFCFEFAAGGGBGFCDCBEADADHFHDHCEABCGGGFGAHEEAECCCCGBBEHEHBHBHDCDFFAFBFCEBAGAGCCBCAGFDHHEHFFFCFEFBBEBFGEGA,False +253,21.0,15.0,11.0,10.0,10.0,18.0,15.0,19.0,CFCEEFHBGDEEFEFDAGAHAHGHFHFHGHAHAHGFFFGBDBGAAAABABGBFBFBEACGCEDHFACCFFFGECBAECDGGAFAHDHDHBCCGHAHAFAEDHDHGBBABDFCAGABHBH,False +254,16.0,7.0,14.0,11.0,13.0,17.0,11.0,13.0,CDFHFHECACEDEAECCHFHFHGHGCAHAGAGDEDFDCHCFDADFEGAAEAFFDEDCCEDBFCGCGEBEBHGAGFBABAGFHDHAHAEFFFFFBEBCGHACA,False +255,14.0,24.0,17.0,17.0,23.0,22.0,12.0,11.0,EDGFFFGBBBCACDDDBDCFCFCEEAFGFGFGFDBBBFBDCFEFADAHEDBDFHAAGHCHFGACABEDEDEAECEFEFDAABHHAHCECBFBCBFFDBDGHGHFBCDCECEDEAAGEGFBEBCBEEGEBEBEBHCEFBBH,False +256,15.0,18.0,13.0,27.0,17.0,28.0,20.0,24.0,FBDBCHCGDEDCGAGAGDDFBBBFFFFEDACGCHAGGGEGEBABFHFEDHFHFCBDGHGBGDHBCBGAEHFAFHHHDBDCHBFGFGFHFHEGEBDFFFHAHGHCHAHDHEBEFEDGDGAFABDBEHACFCFCEDADEFBDDEAEADFDFHFHFDGHEDDDDC,False +257,6.0,7.0,12.0,13.0,9.0,11.0,8.0,10.0,DDACHGHGHDHEFCCEGEGACCDCDCDADHBFEFEDEGCFBFDFBFEHCHDAGEDECBCBHFGFDFHAHCGABDBF,False +258,17.0,20.0,27.0,16.0,18.0,18.0,19.0,20.0,AGEHCDAGCGFGDCDCHCACDFEAGFGAAAADADCCHGHGHCCEEEGCADACAHECEGDGFBFBFCHCHCBBDBDBDEFCGCBBBEHFHACAGBCHFFBCBCGGGGHDBECEHEHGHBCAGEDEBFCEEBEBDFCFAFHBADDHFHFHFHECFBB,False +259,1.0,5.0,4.0,1.0,1.0,0.0,6.0,2.0,GGGGBGAHBHCGDBECCBCB,True +260,2.0,3.0,4.0,1.0,3.0,5.0,1.0,3.0,BFBCBFHEEGEHCACACHFFDF,True +261,2.0,4.0,3.0,2.0,3.0,2.0,6.0,2.0,CDCABEHHGFGFGEBABCBGDGEG,False +262,17.0,17.0,32.0,25.0,20.0,22.0,15.0,15.0,DHDCDCDGEHCBGBEBACGDFDCBCFCBCEAEAFCDEBAAEADHCEAEHECDDDBDCDBBFFEFGFBCBHAHFCCECGHDHFHAHACDEHECFCDEAAHABBCHGEGDGFHDDCDGDCCCGCACACFCFDADFGFBFBFEGEGEHDACGDFCFCFGBEBEFCF,False +263,7.0,4.0,7.0,4.0,5.0,5.0,7.0,12.0,GCACAHGHECGCHFGFEDHDHDHGHBAEAHBHFHGCCBCHEGEBHAFADAF,False +264,6.0,6.0,13.0,6.0,11.0,2.0,9.0,8.0,DCFBDBEEEEEEADAHGHGCGDHCHGEACBCGCAHEHGGAFAGCCCCCBEBHDCBCEGEHD,True +265,20.0,25.0,22.0,32.0,26.0,23.0,23.0,27.0,DCHBHBCEHHGHDCGCAHHGHDEEHEHBBECDCGBBACACADDDDDFCGEABGBABEBEBEACFHFBEGHFBABCGHGEGDDDEGAHAEFBFDGDHBFGFCDCDCDFGFHEBEHEHBDEAEACBDADHFBDDDDAFEFBGGGGHGHCHEHFCFGFGADDDDBDADHFEBEBECEADACBCFAFHFDFGFAEGHHCCFE,False +266,7.0,6.0,7.0,3.0,4.0,2.0,13.0,8.0,BGHCABHHCHGGBDBABAFCGEGDGAHCEEGEGBGCAHAHACGCGHGFGD,True +267,8.0,8.0,22.0,12.0,15.0,14.0,10.0,10.0,DCBAAGBEBEHECCCCFEDDDFGHGDEDCBCGEGEGEBFFAEHECFCHCHFHDCDCBHGGCCBCFCHHFAFGHGDFCEADCDCDCEBFAFACECAFEFE,False +268,20.0,11.0,17.0,15.0,11.0,11.0,19.0,11.0,FACAFGDHCEFHAECBCBEBEAEGBGBGFHCCBCAHDCFCDGDAEEEFBACADABACECHGGDBDGGGFHEHADAFGFGFGHGHGCFCDCDEGAAAABDDDGHBACACDGDHAGA,False +269,6.0,1.0,7.0,4.0,8.0,4.0,3.0,3.0,DBGECEAEAEAEAGDGFCHCECFAAHHFEFCCDEDC,True +270,18.0,16.0,20.0,26.0,19.0,21.0,22.0,23.0,BFBCDDGAGACDBDGDGDADHCAEACGCGDEBGDFDCDBDGHEHCFFFFFHFBFAFHDDGBHHHHFEFABGGDGDEFCDGHCHEFCFHBADHHCFCBGBFEEEEEFEDEDAFGHGDGCACDEAEACDEDHBHGHBHBHCDGAEACCEHGHAHACAGACBEBGFDF,False +271,0.0,3.0,1.0,4.0,2.0,4.0,2.0,3.0,HFHFEFDBEBHFDDBDGCG,True +272,16.0,16.0,17.0,14.0,11.0,14.0,8.0,16.0,FCHEHAFAFBFBDHGAFABBCDCDHBHEFABCHCHDAGABEBAHDHDFCEBGDFECECECEHECACDBDBDCGAGAGACAGBFBGDDACCDDBHEHBACFBFHHHFHFCFAE,False +273,13.0,11.0,14.0,14.0,11.0,17.0,18.0,16.0,CDFDGBHBFGFGFGEDABABCHHDDEDCHCGAGFBFDADHDCDCECAGEFEBEAFAEHEHGGEFBHCHFHFAFDFACGGFGHHDHGHAHCFAFGEBCBGBGCACDCDEHGFBAG,False +274,30.0,26.0,12.0,16.0,14.0,36.0,17.0,16.0,GGHCBABACFGFHFBBHAEAEACADADABABFFDABBFFEFBAGFHFBFCFBAHHHHGGDGFGBHBFEECEFDCHCHBHGEAHADDGAFAFDDBDGFGBEFFFFFGFACABGFFFAABAFACAGAGHDABABGDACFEAEADBBFBEDEAFFBFBFCFCDBHEHEDF,False +275,6.0,13.0,13.0,9.0,7.0,9.0,12.0,6.0,CEFBGCCCCHDBDBCAFDFDFGFHHCCGCGBGDGDBCBCBHFGAAEGBGBFBGBGECHCDAEGEFADAHEDEBBF,False +276,7.0,5.0,3.0,5.0,6.0,7.0,3.0,5.0,BCCDFEFEFEBADABCFDDHDHAAEAGFGFHFBAEAGHBHE,False +277,6.0,5.0,1.0,2.0,3.0,3.0,6.0,7.0,HBBFBFDHCGEGAHAHGHGFEBHBGGAEAHADA,True +278,4.0,8.0,15.0,16.0,12.0,11.0,10.0,10.0,DHCHAEEEHEHEFEHGFBHEDEGEGFCDCFCGCDCBFFFCEGDBHFDDADGGCGDEDEDGACDCFCFBGBHBDBCFCHCDDDHCAB,False +279,15.0,15.0,14.0,9.0,20.0,30.0,10.0,19.0,EAFFEFEFHBHBHBHCHCFAAACFCAHGBGBFEEBECEGEFDCEFEGCBFHFBEAFDBBGDDCGFDCBBHBHFEFEHCHFBFDGCHFHFHFGFGAAAAEECEFDBEFECEHDFCFHDHFFEAAAAAFGFHFH,False +280,20.0,27.0,17.0,23.0,26.0,20.0,26.0,25.0,AEDGCEBACABABGBGFDCEBHBCBCGHBAEACBHHHCDDEGFHAAFABCEHDBDBDFFGFCBGGGFGEEFEDEAEDEDHHHFHEEEGEGCBCBHBEBGBGECEAEHGHABBBFHEAFGBGDGFFEFDGDGDGHGDAFAGDHDECEHHHAHDDGHGCGEBEFABCBDBFCFCFHBADADFDAHH,False +281,10.0,6.0,6.0,8.0,8.0,11.0,10.0,7.0,GBFFDHAEAECDDBEGDGAEECGGGDHDAFADAEAHBHDEFFFFBCBCECAFABAHGFGFGFGHCH,False +282,21.0,33.0,19.0,20.0,21.0,12.0,19.0,26.0,CAADABABCEABHBABDCHEAEGHBBCCCCCHCBGGGGHHDHGHGDGDGDBDAAGCBHDFEEEEEEBEBAHHGHEHCCGHFBFBFBFGHBDBHAFAGACCHAHFBCCFDEDEHCHABDBEGADBBCBHEHEDDDDBDEDBBHAHBEEEDBBBBHGGGCEFBFAFBGAHAFA,False +283,12.0,9.0,6.0,10.0,12.0,16.0,15.0,10.0,CFCEDFGCGFHFBGCGFGABEGAGAGAGAFADBHGHDEFHHDGCADEGBBCHDAAAGEBEBABFDFEFEFHFHFHFHGBFEGEDDDEFEA,False +284,0.0,7.0,2.0,2.0,5.0,4.0,3.0,5.0,FBBHBHECBFDFGEHCHEHEBEBDGFGB,True +285,18.0,10.0,10.0,8.0,8.0,13.0,19.0,13.0,HHHFGFAHCCBCHCBFAGCGBABDBDGAFDCDAEAEHDADBHBAGFGFGHEFFGHGHBHAFFBFCFCAAABEEEAGGGAGCGFGAGADAGEHAHCDGEG,False +286,17.0,19.0,13.0,13.0,17.0,16.0,12.0,9.0,DBDADABCGDAFEFEFEDABCBEBGDGFEBEBEBEADBDGHCADABFDADADABGFGFCBCDCFBGGEEFCFAFEFBAGGEFHCGAFAHBHBFFEBACECACBCHAHEHEHCGBEH,False +287,11.0,13.0,8.0,14.0,5.0,10.0,1.0,11.0,ADDCHBHFDEACFDBDBABCBCDDDBAAADHFBFBABEHEHBHBCCHFDABAHCDDDCDAFHFEFEFHFHGAB,True +288,21.0,32.0,21.0,22.0,23.0,17.0,23.0,21.0,CFCBBDADEDEDBDHDADCCCEHEHBFBHADADBGBGDCBBHFAEBDHDFDFBEBHDEDBCECEGABCFGFHDHGHEHAAGHGEDEAEABGFCCBEBCFDFAEGGAGADECFFGFBBHCGEBEGAFABDBHFFAHAHAHBHBEBEBCBABDEGCGCHCHBHBGEGEGCAAGGBBFCCGDG,False +289,10.0,13.0,5.0,12.0,9.0,19.0,21.0,12.0,GBFAEDDDGGFEFDHHGHGFGFGDGFGHHHHEGDBHFGGHECBAGAEACFBBDBCADFGEGDBBBBCBHHFFBFBFDAAAEFGFAFAFDFDFHGGGGGECE,False +290,10.0,11.0,9.0,13.0,3.0,16.0,8.0,5.0,DBDBDCFFGFGABEBEDEFFGFGFAFABHCAFABCDHDADAHBGBDDDADFHCBCDCAAGHBFGFGFCCBFFCFD,False +291,22.0,19.0,25.0,28.0,18.0,24.0,23.0,17.0,FCFEFEFAGEGCGEAAAEGEHFHEGFGDGDEDBDEEECBBBEDFHFAGHCAGAFAHABFBFDDGECEBGFDFCFCDBEFABGEDACACDHDHDFFCDCACHCDBBGCDBHBHCFCDHHHBHBGFGFADDGDCDCHCDCACAGAGCDDABCEGHDHFGGDDEAFBFACACABGBGFD,False +292,22.0,21.0,17.0,19.0,16.0,16.0,15.0,29.0,EFHHAHDCDEBEHEHEHEHEHCFDBCBDHCAFEGGHDDBDFGFGHCFDDDDAFADCGCFDFBFBHGAFCCBBEEAAGAGDEDAHAHAHBHBHBHEHCABABHBCCCHCBBBDAHGFDEAEAFHGBGEHAFBGHAFAFAHABCDDECGCHHGHGAB,False +293,14.0,10.0,22.0,19.0,17.0,10.0,11.0,13.0,FDGGCACGCDCACBCDCDGHHDHBHFGGCCFBFBCBDFDAGEHAHEFECBHGDDDCEBBADCDFDADEEEEDEBHAHAGCGCBDGECEHEHAACADAHFHFEFCCECEDECCDAEA,False +294,21.0,23.0,11.0,16.0,19.0,13.0,19.0,13.0,ECDFDEAGAEAGHBFEFGHBBGBABABGDGCCAGHBHFEFGGCBDGDGDGHFHABAECEAGHFDFEFBFECECEFDHGFGABAEHEGEBBBBEBADFEHEHBDBDADADGBHADADHGAEBBBDCACECBCAAGA,False +295,16.0,21.0,15.0,23.0,14.0,18.0,17.0,12.0,DDBBHFDFGBGBHBFFFFFFFGEBCFCGHABBEHDDDDBBBBDGFHFAEDHDHCFCHCECBAHACDCDHAAADDECACAGABAGEFEBCAEACGDGFEFBGBDBCBGGDDAEFEDGCGEGEDEDGDBABADFHCHG,False +296,2.0,5.0,5.0,3.0,8.0,3.0,7.0,5.0,GHDHFBBGGCGBHEHBCACHCGCGEEEEFDADBEGEFE,False +297,8.0,7.0,6.0,6.0,3.0,4.0,7.0,7.0,GDGFBFEFAAEBDBDBAGAEHBDBHCHDGBGCGHGHAAACHCHAFCCD,False +298,10.0,8.0,9.0,8.0,12.0,10.0,12.0,8.0,AAAAAADGHGAEEEHFHEHEFFAGAFHCDCGEBCBCBFBFAFHFGGCGHEDGDFDBGEDEDCBEGEGHCBEBCCDGF,False +299,2.0,2.0,2.0,2.0,1.0,0.0,0.0,1.0,CHCEABDBDA,True +300,21.0,16.0,12.0,20.0,12.0,15.0,16.0,21.0,HFHGDDEFBFBFAGCFAGBGDHEHBHBHAEFBDGACHGHAHFFDFHFHEBBCBDBDBCFCDCACAEDEDHAHBHECABAGCEBHBGEDEGAAHAFAHADCDEGEGADFGAGAHCDAGADAHCHDDGDGDHFBF,False +301,18.0,17.0,21.0,18.0,14.0,17.0,20.0,23.0,BEBFFCAGAGAGHGHFHDHCFDFDEDEBEBEAGFBCCHCDCBCHHGHEACAEFGBGBEDEBCDADHFAADBHBHCHFDFDFHGBGBAEFGFAAEHEHEHCCGHDDDGHCCCCAABCGCGCADACABFEHDBCFHGHGDAHHDFGBGFG,False +302,17.0,9.0,16.0,15.0,18.0,20.0,16.0,20.0,CFEHGDGCGHFADAFGFBFHABACDEDEDGAEHEHCCCBCEFHGHAEAEAHAHEHEHCDFFAHDEAFDFGBGDHHFHFAGGFFBEHEAEAFFFDGBGCGEECAFFHEHEHDACBCFCDDDDCBCBHGAGCG,False +303,17.0,9.0,12.0,14.0,11.0,11.0,11.0,15.0,DFDFAGHHDEDEHEHECGFACAEADDHDEDCHCECFHBBBEGHBACGGGAGAHDHAAADEHEAFADGDBDFHFGBABABHBFCHAHACCFCGCEADFCFG,False +304,32.0,22.0,21.0,20.0,17.0,21.0,22.0,16.0,HABACGCBCGHGHADEGABAFHHGFCCGFFFHFHAHAGACFGEEAHAHABABFBAEAEDGDBDFFFFEGHGDDDCHFAFGECACECECEDFBEAAFBCGAGECECFCFCBGGADADGHACAEBHAHABGGDDADCDADBBBGHEFEDDDGEFBDBDBCBABCBAAAACFGB,False +305,22.0,14.0,10.0,9.0,20.0,15.0,19.0,12.0,GAGABHEFGHGABAEDECGAFABBEFEAECCAAHGHBEEEEEFHFGFGAEAGAGDGHGFAAAHAGAGFBECEFFBBGHGFCBCGCADEDBDBDBDFEECEBEDGAAEAFAHHBFCFCDHGH,False +306,7.0,13.0,6.0,7.0,4.0,5.0,5.0,12.0,BABAFAHDFDGBHHEHBDACHGHGDDBDHFFAFACEBEBEBHBCAHBHDHCGBHBCGCB,False +307,27.0,19.0,23.0,17.0,31.0,29.0,21.0,17.0,FADCDEGEBEGHDAEFEAEBHBCBAFAHAFGEGFBFCAHAHCCBDFHGCEFFCFEFEAEAFCBDADADHDFBFBEBADFCFEFBFBFDFCFGFEAHBBCCCCHHBHAAEGEBECEGDAEFDGECEFEHGAGEFEDGBABABHDHDCDCGHAEACAGFCECGGHEDCFAAAGAGCEHEGEGFGFE,False +308,16.0,23.0,23.0,25.0,22.0,21.0,28.0,27.0,BHGEFEDACAGADADGDGDBBFBCGGHGFCFCEHHDCDCEGFCFBEBEHDHCHCBEDDHBBEBGGFDECHCHCBFDFBGEHEGEDEGAHDBDAHGBGDGBCFCGCGBBAFAFABBBFGFHAHAEAGFFFGDDCABHECEDEBEHDGDEDEGCHCDCACHCAFGGGHFHFHGHGCAEHHHHDDBEF,False +309,11.0,10.0,14.0,4.0,9.0,15.0,8.0,17.0,CECHBGAHBHAHGCACBEFEFDCCCCCBCDCGAFFFFFBCBAFHFHFHDAEAHGHBHBHEHBHCGFBHAAGEFEFEGHAHDFFCAEHG,False +310,7.0,7.0,11.0,8.0,8.0,14.0,8.0,4.0,AFACGFEEDBGHDDADFCFCFCFDBGBHEHFAGDCACFCFEFBDBGBEBFCFCFCADGEGEAHCFGE,False +311,1.0,3.0,3.0,4.0,1.0,4.0,5.0,3.0,DHHBHDGDGCFAFGEBCBCGFGFD,False +312,9.0,6.0,12.0,3.0,7.0,3.0,4.0,5.0,AAEAECGCDFDHACECEAEBHBACCHCHEGCGCHCACBBAFAFCDGEBB,True +313,10.0,20.0,11.0,11.0,10.0,21.0,14.0,10.0,FHEBEBCAHAHBFGFGHGFAFCFDBDFDCHBECCCHEACABDGFBFEFAFAHGBFBDBDBFCCCEBFGGBGFAFABEEAEGBBFFDFBFBDBGBGCGDEDHFHDGGH,False +314,11.0,11.0,19.0,12.0,11.0,7.0,10.0,11.0,GBHBFGDABADADBDCDADHBGCECHCHCGCEAGCGCDCFEAGAEAEHECEFFBECDCGEHCBBBCGDHDBDADCFFEFCACAEBHHCHGHC,False +315,15.0,20.0,19.0,23.0,12.0,16.0,12.0,15.0,CCCCEFDBDHDCDFDCHFHFDEBACECHCGGFGAHDDDBACFFFDFBBABABDBACADAHCHDGCFFBHHDHDHGCCACEDBDECEHEBABHFDDDDGEFBFBGBEBFAGAGBGHEHDFEBABAEADBCGCG,False +316,6.0,8.0,6.0,3.0,8.0,2.0,0.0,9.0,CBCDFDHABAFEHBHBHECEBECHHBEEECEHAHCDAHABAB,True +317,5.0,12.0,12.0,7.0,8.0,8.0,7.0,11.0,CHGBGBFBFDABACAFFFCECHCEGDBBGHCCBGDGFGHEHDHCHBBCCECEBEAEAEHDCDHHBHBDFF,False +318,19.0,29.0,24.0,19.0,24.0,39.0,20.0,15.0,CFEFGHBHFHCEABFCCCFFEFEGBGBAHAHDBABCBGBGBGAGAGABHCCCFFFEHEDGBHEEDHDEDBHFDBCBGBFCFBEDFAFCFGACEFGFGAAFFFFDFEFECCGEGBDAAECECABEFDFCEAEAHFDBABDCHGBGBGBCACBCBEFGFGFCFHDDFAEHDFFEDDFDFBFBEBEBFHFCD,False +319,8.0,5.0,5.0,2.0,5.0,4.0,3.0,7.0,HAAEAHDHCBDEAHCGFGCEABAEAFAFHFHBHBCBCEG,False +320,4.0,0.0,2.0,0.0,3.0,0.0,0.0,1.0,CACAEAHAEE,True +321,19.0,25.0,20.0,14.0,21.0,25.0,19.0,10.0,ECEAHAGAGDCFHAHAHABEGAGBEBFFFFFGFDFDFGCDCBABEBGBFFFAGADFDGHGABAHAGCBABGDGEEACAEDBCBCEEFHGDDCBCEGEFEBEBFGCHBHBEDFHBCGEBCDCFCEBEFEBCBCBCBAGFFAFAFDCGEEFDCBF,False +322,4.0,3.0,7.0,8.0,3.0,3.0,6.0,6.0,AGDFDFDAGECEDDHCHGHCBFDEBCBCHCHCDDAHAGGG,True +323,20.0,23.0,10.0,13.0,14.0,23.0,24.0,21.0,AGAFFGHGEBBCDCEEEGBFAHAEGEGCGFGAAEBGHEBDGAGEBABEFCHAHADFBFDFBHBHBGBEBFBFHCACGCGBFBFAHAHFEFDBGGGBGFGBBEDHGHGHFHDHDGDHBFBFDFHFHFACADAGEFHCAADHBHCADFGA,False +324,6.0,10.0,13.0,15.0,5.0,10.0,12.0,7.0,ABBDDDDGDHDCBBHCHGDGBAEGEGHDBCFGFBEBADGCGCGHFFFFFCFCBDBDGDCAAAFDHCCCECDFDHCGEG,False +325,14.0,17.0,16.0,18.0,24.0,25.0,25.0,12.0,EAGDFBFEHEFGADABCCEGEAEGEGHGBFBDEAEDHDFEFDHCHGBGEECDCDCDCHCDEAEACCBEGAGEBFBFBFCCGFBEBCCDEDFDHHGAGAGEEFFFFFBGHGHBDECEBAFAFDFDGGGAHBEFGFGFHDGDEFGCABFBFGG,False +326,10.0,8.0,13.0,7.0,11.0,10.0,9.0,12.0,HGFCFAFCFAGADEDBHFCFCHHAHACEBECCCCEGEFEFGDBFBHBGBCEEABCECAADDEDHDHBGEGAHCHFHGAGH,False +327,13.0,9.0,7.0,7.0,11.0,9.0,9.0,4.0,EFEGEFABAFHDBFAFGGEBEFECCCEFFDADBDGEGAGABABABFBDDAEAHAHGHEAAGDECCCGCB,False +328,11.0,7.0,14.0,13.0,15.0,16.0,11.0,12.0,HHHHFDGEGFHFHGDGCCHFBFEDBAHGFCDCGGDDACACEDBGEDEHHGHEFEFCFGFAAACADHFAFCFCFCBDBAEEEEGDFBFAEAEDEDEBCCC,False +329,14.0,9.0,16.0,7.0,13.0,4.0,16.0,18.0,GCAEFCFCACAEDGGEGBGBGBHBHAHECAAAAHAHECECHGHADDCBCFCHHGAGEGDGEAECGBHDACECBHDCDGHCHGEBHBHEHCFGEGHHA,False +330,6.0,12.0,18.0,17.0,8.0,10.0,10.0,6.0,GGFCECDCDCAABEBEHEFDDADGDBDHGFBFBEDHDFBHGGCBCBCDCBCHDGCBCBEDCDGDBECADACCCFEFGFGFHDADFCC,False +331,11.0,25.0,21.0,16.0,17.0,27.0,21.0,23.0,FFFCHCBCGHHHGGCEBEDFCHAEFCFHDBDBABFBFEFBFHDHFBGCACHHFBFDFGFBHHDBEFAFAFHFEEEGEGEGEDBHCDCACHHGFGFHHBDBDBHCHGEDBDECECECFGBDBCEGGGGCCBCAAADAHBBBGBGFGHDAEFGFBBGHDCFCF,False +332,31.0,34.0,15.0,23.0,18.0,19.0,14.0,23.0,HBFBAAACBDEABCHDHAHDFEFHAAACDEBHBHBHBCBHBHBGCAFGBGBFFDFGAEAEBDFFADADACADDDHAHAEEBFDFGCCCFCAEGBCBAHCGEEEEEEBFDFEHBBBABAHADBDEDFGHHBHBDDABBHBHDHFCFCGEBAAAEGFDFDGDBBBAGAGABAGHBHCAD,False +333,20.0,17.0,9.0,14.0,13.0,13.0,13.0,14.0,ABGCECACBHDHGEEHEHBDAAAFDEDGDFAFABCCGHBABEBEGADADFDEHEHEGBGAHADDHHGHGCGFFABAFDBDHABEFDCDFFAFBEBHBAFAFABABGCECHGBG,False +334,7.0,5.0,2.0,4.0,6.0,6.0,4.0,9.0,GCGBFBHAHEBEAEDCGEAEHHFHAHABFGFHFHDEDADAFHB,False +335,17.0,13.0,10.0,10.0,9.0,12.0,9.0,20.0,AGHHAHAHCBABFGADADEFEFEDBBBBHHGHDHBCECEHFHFHBHAHDEAEAEBEHACAGADHCHBGGFFFHACBDFDAGHCDGDCFCACFHFBBHGAA,False +336,10.0,13.0,6.0,5.0,11.0,4.0,11.0,9.0,EGEBEBEGEBAHEFBCBEHGDFHFAFCBHBGDABHGGGBGCGBABADHDCEABABADAEEGAGCHCHEH,False +337,17.0,16.0,15.0,8.0,14.0,17.0,17.0,24.0,HBGBABHBHDFFAHAHAGAEAEAFACGCBCECFGDGCCEFEFHHHABGFCHDHGBCBHBDGDHEHGHCFCHGHDHFHFBFDABHBGBAFHEEGEGECBAGEHBHCHEFEADCBFGHCEFGCGFAAAAF,False +338,18.0,20.0,22.0,16.0,18.0,27.0,14.0,22.0,AEAEAEAFHDHAAEFBDHGFGFCAAAGADFFEFBADCHCHEGBBEBGFGFGEHEDCFHAEBHCDCBCGAECGCHCHBFBEBHHHGCBHFDDGHHHCHBDEDECBDFEFBFGFCFBFBCBFBFCDEAFDGABADADBFFFFECECADHHHCHCFCFCG,False +339,24.0,25.0,25.0,23.0,21.0,21.0,28.0,25.0,ABAFDFCFCGHGCDBDGEGEGCAAEBHBHGHGHDADCGCHFECEBDHDABHGCGHDHEEEBFBFBDDCDGEEEHBFFCFBFAFAFGCCCHGGFGCACHEDEHGDDBHEHDACAFHEABGCACABDBEBFDGHGHFHEAEAEADACGGBBBCGCGDGBGBFCHAHAHFBABFCEHBADGDEBACGCGFAFDHD,False +340,14.0,19.0,9.0,8.0,9.0,16.0,11.0,11.0,CAADABAEACBCBGAADHBFFFBDBDEGABHHHAEFHBCFHBEBGFDFBFBDBDBDAEGEGEFCGBFBAEGBGFGFHFHFGFCBCAAGAFEHHHCBC,False +341,2.0,6.0,2.0,4.0,1.0,4.0,1.0,1.0,ECBDBFAFDFDBGBHBCBAFD,True +342,10.0,9.0,6.0,7.0,9.0,12.0,7.0,13.0,AEAHAHFEGEGBGAEBBHFDBGBHHGHAFAFAFHFDDCDHECFCACFHFHCDCDHBEBFAFGFABEEEGBDHH,False +343,12.0,23.0,13.0,17.0,19.0,18.0,25.0,20.0,GCGCGCFABHCGAFCFDFBHBHEECDDBEHEAEABABAHHFFDFGEBEBGCABAGGEGEDEDHBCFDHDGBGDGHAEAGDHAEEECHHFBDGCFCDBDHFHBBBDHHCBEHFHGGGFGFBEBEFEFCFGFGHGDGDBHBGBABDGEG,False +344,8.0,19.0,17.0,14.0,18.0,17.0,16.0,26.0,BFBHCHCACDDFCHEHAFAFEEEDHGHBEEFADGGFGEEDEDEFEFBFBHHGHGHDEFCGCGHDHDBCHDBCFCGEBHBHEHFDEAEBEGCGBHBFBHBCBCBCBGACCHHHGHFDFCFHGDGHEHDCBAAFHBG,False +345,14.0,25.0,9.0,16.0,24.0,29.0,24.0,20.0,BDBDFDFEGEDADGGGGDFAABHGFGFEBHFECHCEDBABFBEDGGCFCEAAHGHFBBHHHHHHEBEBFAEEBEDGDCHEFBFBFBHEGEGEAEBGGCAFFGDGAGAGHFFFFFGCHAHBHDEDEFHBBBFDFHFBFBFBHDEFGBEDEGEGBAFFCACEG,False +346,20.0,21.0,26.0,20.0,28.0,15.0,21.0,20.0,EDEDFHFHEDCCECEHEHCGBBAEFDDHBGBEBGAEHECGCACECGCGCDEHCAFAECHBBDGDFCFBBHBEBEHDGDBDCAGACAHAHDHCEBEHEACDDDFFAGAFAFCGEACACGEEAHAGAGAGEFEFHFBGCHBDBHBCGDGCECHDHFBFDCGCBBEBDAEGEGE,False +347,9.0,10.0,7.0,7.0,9.0,11.0,7.0,1.0,DAFCBCBAFDEGEGEFAADGEGEAEAFGFBFEFCFGFCFHEDCBGBEBAFDDABCBABDBC,False +348,23.0,21.0,22.0,23.0,12.0,21.0,19.0,12.0,DBGBGFCCGCDHGFGFGFDCDEAEAFBFBHGHBCBABAFFFBBAFHFCDBFECCDCACAEADFDEDGCFCHBBBBDFDCGAHFGEADDGHFFDADEGEAEFEDECACACAFADCFCAGBBABEDGDHCGCACACHBDGGAGBGBHAHADDDHB,False +349,24.0,18.0,28.0,33.0,14.0,23.0,32.0,22.0,DBDACACDEGGCFCBGBHFGDGDEDHHADCFBFDFDAAFAGDGCFCECEGDGFBAGHDDCDCDGHCFFAFGDGDHDHFGGBGHDCDCAHFEDBFBFCDDEDGHAHADABHBEAAACADGBGAGAFHCCGFGCGDGAEAGDGHFHFEBAHCFCFGGGEGEGAGHBBBDCCHCHFHCHDFDBDCDEHECBCEAABC,False +350,8.0,4.0,6.0,7.0,7.0,4.0,16.0,7.0,EDGFGACAGBHBEBAGACAGEEEEEGGAGCGCDAFHGDCDHGHCHGBGAFDFDGGGDHH,False +351,14.0,22.0,13.0,15.0,4.0,11.0,14.0,13.0,ABCCHHFHCDBDBDBCCGCGFFDFBFGGBAHADDGDCDCBAHABEFHBBDBDBDBEBEBGDAEABDGFHBHGAGCBFHHHHHACGBGACFBBDGDBFAGAGACACF,False +352,23.0,10.0,18.0,19.0,18.0,25.0,14.0,15.0,GFADHDHFCGCBFFFHHEDFDHAEEFECAGBGEAHAHADAEGCBFBFEGEFHHEGGCFCHHAHAHEBAADAGBEBEDEDGFEFAFADADFGFAFCECECFFAFACACHCDFDADCDGGFDHCCCCDGDAFBFBEADBDAECF,False +353,28.0,26.0,15.0,29.0,24.0,17.0,31.0,29.0,EFGDADGCGBGBGBEAEHGHFDDEDEDEGHGEGEGHGHEHGDGBGFEAEGDCHCHDHFHEHAGDHDFEBEBEBEDCDCACAFGFCABFEGBGAGHHBDBABABHHAHAECEAGBGBHBFEDHCFCDGAFDHBEACFHHGDADHCFCBAAHFFGFDADBBEBHACABAHGDGBEAFABDBGGGGDDDAAHDDDHCHAABE,False +354,2.0,5.0,6.0,7.0,4.0,6.0,4.0,6.0,BHGHAECCCFADBDHDEDBFBHDCDCDFGCGFGFHHEFEB,False +355,6.0,5.0,6.0,6.0,6.0,7.0,2.0,4.0,HFHCGCGBFEAAAHAFBCBDEDEDEDCDFFABBCFCADFEHE,False +356,6.0,7.0,14.0,10.0,18.0,19.0,15.0,16.0,FBEHFGEHFDCDGGGEHCDCDFFFHBABDFDFHCCFEFECEHEFCAAGFGBCBFGFEBCACACDFFGHGBEHEHEHFHCCEGEGEGECAHEDEDGDGEHHHGHFF,False +357,14.0,24.0,11.0,19.0,13.0,13.0,20.0,12.0,CAHGEBBDBFBEGHAEDBDHDGDGECACACEFBDBFFGADBHBCCDCDHDEGEAFAFEGBFBABHFHAEDEDGHGBEBGBGBGFFBCGEGDAFAFAHAEBCGDDAGHHBCBDBDBFBDBDCGGGGH,False +358,14.0,23.0,16.0,16.0,14.0,16.0,6.0,16.0,HBCBHFHFHDBAGAEDCCCBFDFHFHDHDHGHABCFCFAGEGBBBFDADADBEBHFCFDFCBADDBCBCBCAEGEFCBABAFAHBFBEBEBCCEEHEDECBFAEHGADHDHEHBDEFBCDA,False +359,13.0,21.0,20.0,21.0,14.0,16.0,20.0,15.0,GFDBDCACAEBEBEBHBCBCECEGACHCHAHAGGBADADBDFCFHGDGDGEBHBDGGFGFGDBDAGABDGDGEHFDAEFFGFDHEBCCDCHCFCECHGDBCEHEFDFDABEBGDGHACFFBDCEAFGDBCGCBCFHBHBH,False +360,2.0,2.0,1.0,1.0,3.0,6.0,2.0,3.0,GFFFEFEBDBEHGCAHAHFF,True +361,14.0,17.0,14.0,17.0,23.0,22.0,11.0,18.0,DHACABDDDFEFBCAEAEAEFCFEFCFDFHFAFBCBCHGHFHEAEGBHBGCFCHAEBEFECECGFEDEFCCHAFAFAFADGHGBGDHDEDAHBHBHGEEBDHDBEEHGDEDEFBFBFHFGFBDAEBDGCHEEDCHB,False +362,7.0,7.0,14.0,4.0,6.0,6.0,6.0,3.0,CCBCGEGCAFAEADAGFGFCFCBCGHBBDBCGEAHAFCDCACBCHCEEFECBD,False +363,10.0,8.0,17.0,16.0,17.0,20.0,8.0,12.0,FEADABEGEHEBEBECFCDCHBHCAEEGHCFGFGFHHEFEFDFGFDECCACHFFFCDCGADAFGDCDCDCEFFFFAHAHBEECCDADAFFBEDEDEDHCFCDBHGHDB,False +364,8.0,4.0,4.0,12.0,13.0,9.0,10.0,11.0,FFHEHDFFAGEGEHEHFGDDDEDECEDABHFGFGDGAFADAEECGGABDBGHHCDCBGFDHDHAEAEHEHE,False +365,6.0,2.0,5.0,1.0,4.0,5.0,1.0,5.0,FEACAGFEFHCEABABAHFFEHAHCHCDC,True +366,11.0,5.0,9.0,15.0,4.0,9.0,12.0,5.0,CCFDEDFDFEFEHDBDCDHGGGGDFDAACADABFGCBCAGAFDFCGCGAHAGAHDBDHCGEBFDADADGG,True +367,22.0,11.0,14.0,10.0,20.0,19.0,35.0,19.0,DGGGBCECGDADABABHEHBHGAGHGFAFAGBGBGEEACACFEFGGGEFHCDEEBEBAHCEFFFFHAHAHGFECBHGGEGEHAHFGBDFHEEGCGFDAAAGEGAGFEFHFGAGAGDHAACAGHGCGAGDGBFHFGCGCECEHFHDGEGCD,False +368,2.0,3.0,4.0,0.0,3.0,2.0,2.0,2.0,BCECECHFHFAGEGBBCA,False +369,2.0,7.0,10.0,3.0,12.0,8.0,6.0,9.0,HHDHDCCEGEFFFHCBBHDEGEHEFEFEFEFBCBEBHBCCGCHEHBGGACECEFGAC,True +370,17.0,20.0,13.0,14.0,12.0,20.0,18.0,16.0,HEFEBECCHDECGCEBBGCDBDBDGFGFAFHGDDFDHBBBFAGDFAGACEFHGBFDFHFHFHCGBEDHFCFCFGAAEDECEFBFAHABACAGAGACAHABFBFGEGDBFBHBHDHDGBABAGCGEBAHGH,False +371,14.0,16.0,16.0,7.0,13.0,5.0,11.0,14.0,GBGBEHFHFBBBECAABDEABAGAEDEDBCEGECCACAGACACBCHCECEGABDBEBHBHFHCDAEADHCHCHFHCEABBCDHEGFGCHBGGHGHA,False +372,9.0,15.0,11.0,10.0,12.0,17.0,13.0,14.0,BEBEBGFFBFGFDFGCGCGFHDGGCFAFAFBFDHDEAEHEHAFBFEGHHEBGAGCHHHDDCECGCABFBFHFEDEDHBBCBGBCAGACAHBECEDDHBHFF,False +373,14.0,9.0,8.0,14.0,6.0,19.0,18.0,14.0,BHEFAHAHDDDDFBFDFGFEFHGBBFAAAGADHGBFCDGBEFGFCHHGFGHGHFHGEGAGEEAGDDABGGCCCBHBHCHDFAFAFAFGFDFDADADCGCGHF,False +374,13.0,6.0,13.0,5.0,8.0,10.0,12.0,6.0,CBGADAHAHAFAFGCGFGCDEAEADADCBHDFAACCCAFHBBCEGEGECFHAEBEHCGFGFGEGCGCFCGABF,False +375,8.0,5.0,6.0,3.0,11.0,9.0,8.0,4.0,EEEEHFFBFGGCGHGEBABEEFCFCBHGDBHFAFAFDFGAGDGAECECECAAAE,False +376,6.0,8.0,6.0,9.0,8.0,5.0,12.0,5.0,AEGEBACACHCGGHDBDBCEGEBEBHFDDGDCDBDBEGCAFBFGGGEHEAADFDFHGGG,False +377,2.0,3.0,2.0,5.0,6.0,4.0,2.0,2.0,EDEDECEBHBGFGAEADFHBDFEFDC,True +378,18.0,11.0,12.0,20.0,13.0,19.0,14.0,21.0,GAEHGHAADADADBFCECDCFCGDDFCGHAADFFFGHBHFDCDBFHFHGHFAGAGABADDHAEDECFFFAFAFDEDEBABFBGGHBCBAACBHHHFFEDEDADBEHFHGCGEEDHDCDGHGHEHEHCH,False +379,15.0,10.0,10.0,14.0,7.0,13.0,13.0,11.0,FHGHGHBBCDDDDABABGCEDADCHGAAHAFCFBDBDADFCFDDHCHFHAHCHCBCGGAACAHGGGGAGBEDFDFEAGDGFEBEFFAFAEBEF,False +380,20.0,20.0,27.0,28.0,18.0,28.0,19.0,15.0,FAEAEHHHHHHECBHFFFCFCDAGFGDEDCDCBGFFCGBGEGBAEAGFCADGGBEBEFHFDCBAEFDFDEDAHAHGEDAGBGFEBEGFDDDFDFAFCCCCCCBCBCGCGCACDDBFAFBCDADCDEDBCBCGHGFGBBAFDCDHBHDDBDCECACDFDGABFEDEAEFHHAAFFF,False +381,9.0,4.0,8.0,8.0,10.0,3.0,5.0,2.0,DEDECFCECEDAAACHEGDDFDFCACECGAABDGCHBEBGDGBAEAEAE,True +382,28.0,23.0,23.0,25.0,22.0,19.0,22.0,24.0,EBAHHEDEDBDHHGADFEFEHDHDGFFDFDADHDGEACBEHEFGDGAGAGEBCDCBBAFECHGGBHCHCGGGCGAFCHCHBBEBFBFHFCGCGEDEAAADABABADFEFDCDCECDCHCHCBAAAAAAHAFEGEADCCFHFEBEBFHDHFAAAGCBBBCDHDEDFBEGHCBDBGHGCGHDEAGABA,False +383,4.0,5.0,2.0,2.0,4.0,7.0,4.0,2.0,FAFBFGCGAGAGFBDEFEFHABFBDCHEBE,False +384,23.0,10.0,11.0,21.0,17.0,14.0,20.0,15.0,CBEFFDDBFAGHDAGAGAGDDBEGCCCDCBHHEAEFGFEEEHEACACAGAGBDAAHFHFAFADEHCACGDAEEFGGHEHBCDAGAEDEBFGHDHEHDHFHAGAGAGAFAFABBCDGGGDBDGDEDEDFDHD,False +385,16.0,15.0,15.0,12.0,17.0,20.0,20.0,23.0,FGBHBHAHAHBDFEFEBCAEEDEAHBHBHEFDCBAFCFAFAGHGHGACDHBCAEHGHBABFCFDGDFDFHFDBGFGHHACADACHCGBEBEHEACGEGFGFGDGEGEGECEADACBGFHHDFFHFHFGGBHCGCEEHC,False +386,22.0,28.0,19.0,25.0,19.0,24.0,12.0,27.0,BHDGBHDFDFDBABGDHAFAECECBCBCFCBEBHHHEEEBAFDFAFADECBDFDFAEHBHEHEGEADHHHFHFHDBFHAHADADFDFCAHBCGCDCBBBGBFAFCFHAGADDBFEFEAAHCDCECBDFFHFHBHBFEDCACAGEFDHGBEHGBCBHEEGAGHBDBDGHADADCBCB,False +387,16.0,23.0,23.0,12.0,27.0,6.0,20.0,14.0,EDEBGBEBCGGHCACBHBEGAGHGCGEGFCHBDCHGHBHGDADADBBCHCBEBACGEGEGEBABABDEEHECCCCBBBGAGAEAGFGHACCBBABAGFBEEEEEECGDDCDHEEEAEAECDCECGCFHFCBCEADDHEBFH,False +388,29.0,22.0,29.0,26.0,26.0,22.0,19.0,18.0,CECEGHFBFDDCDHGAFBGDFAAHACACAEEBEACFCAEECCGCGCFFFABGBGDCDGDEAEABHBHBFBHAHDCECECHFEFBACDDDEHAGABADFDFDBDBDECECEDHDAAAAEBEGAAADGFBFADACHEAACFGFGCGEHFHFCCCDGGBCEGFAFEBHCDAGBCBCDCEEGDBDBDHFHEBEHH,False +389,6.0,5.0,9.0,6.0,6.0,10.0,3.0,6.0,AFFFACCCEHHHHACDFDEGCBCDEDCFBFBDBFHFHADGCGCEFAFAEBE,False +390,5.0,5.0,8.0,6.0,3.0,4.0,2.0,9.0,CHCGBFDADACBFDFCHHDHDHCGCBFAEAEAECHCHBBDHH,False +391,17.0,18.0,29.0,20.0,13.0,16.0,17.0,22.0,GDCDGHHBEBFCFHGHAAAHBCDCDHFHEHBDDDDDCDCACHEBDBCBFDACBCBHACCDCGGGGCBCFCFBACADHHCFCADHHHGCBBGDGCGEEHEACAGGFGCABABDBEECECECFAFAGHHDHDFBFGFHECEFDFAHBHFGCACE,False +392,4.0,11.0,10.0,5.0,8.0,5.0,3.0,15.0,HHHHEEDDBGHGFABEBECCBHBCBEDECBCHCBEFEHDBDHAHBHFAGCHCHCBCAHFHF,True +393,5.0,6.0,6.0,2.0,4.0,4.0,5.0,6.0,HGFGHHHAGCGEFEBDFDAAHAFCBCBCECBGBEBHCA,False +394,21.0,28.0,17.0,22.0,17.0,15.0,15.0,14.0,DHAAAAFCDBDBDGGABBBCHCACGHFBBBBBBBAAAAFBBBBBEGEABCGFDHEHEDBAADEDEDEHCFEBEGDHFGGECDCHCHBDCEFEHDBDBDBDCECGCBFDGBADHGGFAFAFACEGEFDFBABFFEGDAACACHEHDHDCG,False +395,17.0,17.0,23.0,13.0,25.0,16.0,32.0,27.0,ACFCFGGGEEHEGGDEHBACACECEFEFHDEDFDGEGBGFHCCACEEFDACHGHGHBEEHBACCCCHCEFDAGAGEGCBHBHBGGGDGCFAHGHGHCAEFBBBHBGBHHEHEBGGEGEFHFHFHGHGCFCGHGDEDAAAGCBBBCHAEAHDHDFGGGEGBAHECDFDCAE,False +396,2.0,4.0,1.0,7.0,6.0,10.0,8.0,9.0,GCGFGFGHBFAEGFHFHGBDHEFEDHDEFEFDFEFBGHHAHGDBDHD,True +397,12.0,14.0,13.0,17.0,13.0,20.0,12.0,15.0,CEBHFCBGHGEGEACAHBHBDBGBADFDHDFDADHHEHFHBAAFACECECEDDGDGDCCCHCGBBDGFBECGDGACFFFFFFDHDHAEFEFBBGBFHFHECAFDBEHDFAFAEGFD,False +398,28.0,19.0,7.0,24.0,27.0,19.0,20.0,15.0,DHEAEADDHGAAHAGEHEBDBDHFCFEFEFEGAGHGBFHECAAGDCDADFCHDADADFDHGBGAEHDGFBFAFAFEFEFEHCAAAGGBBABDBCEADADFEGEFHADEGGGEGEGBGBDADEEBDBDHEEEDADEBBFHEEFCFEFAAAGABABDBHBG,False +399,0.0,3.0,1.0,3.0,3.0,3.0,0.0,4.0,DDHFBFEFDHBHCHEBE,True +400,14.0,15.0,8.0,10.0,12.0,16.0,15.0,13.0,BABABGHFHEHEAEBFGHDBCBGDCFFGAGDGFEFEFEFHDCAGAGHHAHACBCBGAGEGEDBDHDEBCACBHAHCFAFEBEDFFFBFGEGFABHGDADFBHG,False +401,11.0,5.0,16.0,15.0,7.0,18.0,6.0,17.0,EGDHHBGCGFFFFECHDAFAFBFDHGHAACFFFAEHBFDFHEHDFDFDABBEAFCCCCCCCFHAGADDDCCEHEHCHDHAHFHCCCFDHDHDADG,True +402,3.0,10.0,24.0,13.0,15.0,13.0,11.0,19.0,CBBEDHAHBDBDBGCECHHDHGHDCGCGEHCHCGCEEEEHFHFECEGBDDFBHEDBDADGFHCHCGCBCDCEAFGFGHGHCECFDECCCCCDHHEBFHFCFCEHFFCF,False +403,1.0,2.0,2.0,2.0,0.0,1.0,2.0,2.0,DGDABGBCHCHF,False +404,5.0,16.0,6.0,12.0,8.0,5.0,12.0,9.0,DGDHBCBCHGEEHEFGFBAGABADDCDBBBBBGAGEEDCDGHGHFHBHGGCEEDBDBDBCBDBGFAEBHFHGD,True +405,21.0,16.0,12.0,16.0,13.0,10.0,25.0,18.0,GFEFBFGGBGBGBHFHEBEBGBGFGFCEAGCDHAABHBEGCGHDHAHDCEGDGDBFGCAAAAEAGADFDGDAACACECEBFDHBAEACHGHAHDEDEFHHHBGEGACDBAGGBCBHHCDGAGDGHGHADAD,False +406,4.0,4.0,3.0,5.0,1.0,0.0,4.0,3.0,GBDDABCBCGDGDCHBHDHAGAEA,True +407,16.0,7.0,6.0,14.0,13.0,6.0,14.0,8.0,BFCAAAAAEFEBDFCFCADGDBDBDAGAHAEDEGHGHGFDBDGAEHEAEAGCEDHAEADGDAFADGGEGHGHDEBEHDGBGCCE,True +408,12.0,15.0,11.0,21.0,18.0,14.0,12.0,11.0,DBDBDBDBCBGGABCEFEFGGDBDAAAEHEFEBGBECCFCBGEEAEHCBFEFHFCEBFBHGADFDACABEBEAECDCGFDDDDDDHGEGFDHDHDHFCDDEDGAAFAFHHGHEE,False +409,20.0,21.0,28.0,22.0,20.0,26.0,20.0,22.0,FCFDFHADGDHDHBBCCHHDHDHDGAABAGCGCDCDFFFAEAFBHHGHCHEFEGBDCDAAHABBCFHFEEGEFFFCHCDBDEDEFEDAFAFABEHCCCEBHBDGDECCAAACDGFFEDHDFBHBAGAEAEFECGGGCHCDAHBGBDBCBEHGFCFCFCFCEGEGHFCBGFGCGCEABBB,False +410,3.0,1.0,3.0,3.0,0.0,0.0,1.0,2.0,DGACBHDHDCACA,True +411,10.0,24.0,18.0,15.0,16.0,10.0,24.0,18.0,HHFBFECHGHAHFGGDCBCBCEGHGBBAAGCCHCBDBGBDHHHBFBDBGGCGHGABABACEHEHCDGDECBAAEFGGDGEADDDHDHBEBEGEFEGEGCGDGDEDBCCCHCEBEDCGFGHGEGFBFBACHBBBBF,False +412,7.0,7.0,14.0,10.0,10.0,6.0,9.0,5.0,GEDFDFBAGCDABADDGAHEDEDFDCDCDFHCBCBCGCHBGCFCAEEEEEGEGCCCHHGCBEBCAGAF,False +413,1.0,1.0,2.0,0.0,2.0,2.0,3.0,2.0,FGCGCHEHEABGF,True +414,3.0,7.0,4.0,3.0,7.0,6.0,6.0,8.0,HCHGEEBABABFBEGFGAGBDFDEHEFCFBHHHFHCHCBEEGGD,False +415,17.0,22.0,23.0,22.0,24.0,17.0,20.0,16.0,BCBGBADDEHEBECCCCDGAGEGEAACEHEHGFABAEHECECFCGCECDBACAHADECGCBBFGFEHEFGDGEGCGFGDHDCBCAFGDGDAEFHFCFBEEHEBDDFHHHBAFAHDEDGDBDEDECFCFHFAGCFFAEGDGDADCBBBBCGHHABBBBBDED,False +416,23.0,23.0,29.0,23.0,28.0,15.0,36.0,18.0,HDFEEHAHFECBCGDFDFBAGABBGGADFDGEGECECGDHCECECEDEDACACGEGCGFBCBCACEEDEGGABHEDCHBGGGHGCGCBDBCCCEHEBGBCDDGGHGEFEGBBBDBAFAFAGBFFHHADEGEDBCCCACGCDCGEAHAEADGGGDGDBFBFCGCGBGBGACAHAHGEFDADEHEHAFGHBHDEAEA,False +417,6.0,3.0,6.0,6.0,13.0,9.0,7.0,12.0,HGCCECEAEHGHGCFAFHDDBDEGBGHHEEDAFGFHEHAAADBCHCGFEEEHEHEFEFDFHF,False +418,7.0,7.0,9.0,13.0,10.0,16.0,6.0,11.0,HEFFFEDECCHHBHFDFACACEDHDBDBDBDFCFDEDEBHGEFFAFADAFHGBGCGCFDEAHDFDHGHFHCGEFEFABC,False +419,6.0,2.0,4.0,3.0,3.0,0.0,2.0,0.0,EEBDBAAAACACEGGCCDAD,True +420,20.0,21.0,13.0,17.0,21.0,27.0,25.0,13.0,HAGAGAECCFDBEADDGAGFFDCBFFCABGBEBAGCGBFBGEGEFDCDEBFBEDCAHBHBDFDFBADGFFEGEGEFEFEFHFBBABAHHDGDGBGAGFGFGEEDEDAFAGDHEACACFFGFGFGEDECBFBFHHHGEAFAEAHFBEBGBCHCHGADC,False +421,9.0,14.0,14.0,8.0,6.0,14.0,12.0,12.0,FHFDFDBBBGBEBCBFDGDHFGABCGABBGEAFAHACACHDDFHCBBFHFHFGCHCHGBBHHGCGCACACHCEFEFADDFEFEGGCGCB,False +422,2.0,4.0,4.0,2.0,2.0,3.0,4.0,6.0,HFCFCECBGGGDGBEHFBAHAHBHDHC,False +423,19.0,10.0,8.0,8.0,6.0,9.0,8.0,8.0,DEABABCFEFDAAABFHFAFAFADACCGBABAGHBABABAGHEHCGDGDCDCGEHEGDAABAEHBAGACDFFCFHH,False +424,22.0,16.0,21.0,30.0,13.0,19.0,17.0,12.0,BCBEBDAEAEAHAHGHCBCAAEADGFGDGDCACFCDEGCDHBCADDDDDEABADADADAEGBGBHCGFAFDCDBDFACDBDBCFEHEHAHGFGFGFGECHFHCCGDGACDFDECFDADEBHFFDFDFBFBEHAGCGDFCBGDACBCFDAD,False +425,12.0,15.0,7.0,11.0,10.0,19.0,9.0,9.0,CADACAFHFDDCDBFBDBEBEDEHFABACFFHHGFDFDGDGHAHACCBEFDFGEGEADFFCEGBABAEHHBHBGBEBABGBEFFFFABGFFF,False +426,10.0,14.0,11.0,11.0,11.0,17.0,18.0,9.0,BFBAAEFEHCHGAFEBCFCGCGBGFHFCGGAFAFBFCFHBBFEFEFEBGCECBGBGCDFDBDBDGAGEFEGHGHAADEGCGHDBAEGDDDDCDFGFGABHH,False +427,37.0,20.0,35.0,16.0,24.0,26.0,23.0,17.0,AGAEEHGHGCCCGBGCHCHCHFGGAAAEAEAFHCHCGCACADEEECBABEFEHDFBFEEBBBCEFAFADACAFFCFDHDGBFFACDGDFDBBBCGCBAAAEAECGCDHFBDBCAAGACACAFAGGBEHECECEABFEGDFDHHAAAACHCHGHCHABEGCGFACCECFFBFBABAGFFDAECEDEFFACGCGAGCDFD,False +428,16.0,17.0,31.0,28.0,15.0,17.0,26.0,26.0,FGFCCACBEDEDBCGCGFDCAAECEAAFFGGGGHCHCAGDGDBHBHFHFHFHDHAGGDDADHDHBACGCGEDHBCDFDGDHDCCCBBBBGCCCCFBDDDBCCCHCFEHHGFBFCCAAGGDADGDHEHAGCGCBDBFBFEGAGEGHCFDHHHHEHEBEHDFDGDHAAECCCEDEDGH,False +429,8.0,4.0,6.0,7.0,12.0,5.0,7.0,6.0,AAHAGBFHFCEAEBECGFGFGEEECBCDCAEHEAEDEDHGHBCFDGEGDHDEDAA,False +430,5.0,7.0,8.0,4.0,4.0,3.0,11.0,4.0,HGDCHCBCBFGAGBGBEDHAEAEGFGCGEGAFCGCGDHDBBBCCGA,True +431,8.0,19.0,9.0,16.0,16.0,15.0,11.0,12.0,FABCEHHCGDGDFDFHFAEDGDFDFBBBBFEDEAGBEEEFEGEBEFDDGBBAAAFHFHEEDCDCGEDBDAEHEHBHBHBFGCDCHEDBFBGHGFBFBCBCGCBAHD,False +432,25.0,23.0,17.0,34.0,27.0,19.0,18.0,34.0,GBHHHFEGGFGFGHBABDBDBHGGEBBDEDHHHHAHFHEHFFFGBDDEAAAAADCDHACAFDBDCGCGDDDHAGBDHGHCHABAFEFEFEFDDBDBABGFAFEEDEDEAEBFDFDHAHABEBEDDDFHCEFEAAAECCBABHDADHCBFGDHEHAGBDHHEHEDEAECEDGCEEHDDGHCHCHEDDHBHCHCACBCG,False +433,11.0,10.0,8.0,8.0,5.0,5.0,7.0,5.0,GEEEBADHCHEBEACABDBDAHABABABCDCGCDABFDCACABGGAGHCHFFDDGFGFB,False +434,8.0,2.0,9.0,3.0,9.0,11.0,9.0,7.0,CECFFFHGHBHCFCFBFHDACEEFCGEDEDAAAGCGCEFFAAGGGHFHFHEGEGECAA,False +435,15.0,9.0,12.0,17.0,12.0,13.0,11.0,8.0,FEFHFAFEDEDBCGGFBHACGCFCHADADAFAEAEADHDBDFHEDEDBBGBDADAGAGEGECCHEAACBCDCEGFGFDADGHHFDFCCCBDGEFADB,False +436,9.0,4.0,4.0,2.0,2.0,7.0,7.0,7.0,HEFBABCEFAFABGGAAACFCFGHBHACGFGAGAGHHDHDHF,True +437,13.0,14.0,15.0,27.0,27.0,6.0,29.0,26.0,DDDEHABAHEHAHDCBGDHFCEGBBHBHADDEAGGEGDGDGCCDCDBDBHBHBAAHGGGGACECEGGGECCDGDGEGADADGFHEEDEGACAGHDDDFDFBEHCHGHFHEEEHEHEHEHEGEFDGDGHBCCEDHBCGDHEEBAGHGEGEGEDHBHCD,True +438,22.0,9.0,13.0,21.0,26.0,17.0,18.0,21.0,GAGEHFHCEGEDAFAHAHEDBDFDABAHEDGDBCAEGDDDGGGGAGEHHHGCCFHHBHBHBHAGECAGDGDGDGEHDFAGCEEFEHEAEAEFFCECFFFBDADFDADADAFEEEEAFAEEBABAHEFDGHEHFCDCDCECHCHFEAH,False +439,24.0,19.0,22.0,19.0,24.0,22.0,19.0,24.0,DCDCAAAAABAFGFDFDHGCGCGBDACCCCEHFACHEDAAEABAHABAEFHFCFCFBBHFHEHEGCGDHFECBBBGBEHEAEAHDGDGHCHFBFEFEBEDFAACDHDFBHADCCEHEHDBFGFHDHDGEGADADEDEBECHFGGAGEFCCBCGFBBAGEHFHGHEHEFECBGA,False +440,23.0,14.0,11.0,16.0,9.0,11.0,13.0,16.0,DCDGBGBAAHECEFGFGAGHHEDGBCFDFGHGEEFADAEGFBAAAABFBFDAACCCEDHHHDDAAEBHCHABCHAHAHABEDGFGBGDDDDDDGAAHACACACABFFHBHBHB,False +441,5.0,9.0,7.0,7.0,5.0,6.0,6.0,2.0,CFDBDGCADBDBDGAAEAEBFBCBFGHBEGDHDECECBCGFGFBFAC,False +442,21.0,17.0,17.0,31.0,26.0,21.0,12.0,20.0,AAAGDEAFCHCBEDDBDBDHCAAHBDBDADHFHFHFHFHFDFEADADHHCHDDCFBFACHDEEEDABADAFEFHCACFFFEFBBEHGDGEGFDDCDGEGECCCCCFCHDEEECGCFDEDGBBDBGGHBFAFEDADFDHEHDHAGDGDBAEEEBEDAHAEBEBEAE,False +443,22.0,20.0,27.0,22.0,26.0,31.0,22.0,17.0,EDEAHFDFEBGFEFHGAFAFEDEAHDFBEDACCCBCBAFADAHFCGHGHDCDCGGHBBGACADFEFEFBFBFBHBHAHAGGGEGAGACECECBAEFFDEECDFECECBCEHDFCABHBCGDHBFBFBFAEDCFFHFCFGFDEDEDGFGFGFBCHEGGCEDGCCHDGFGCCCACEDEAEABABADFDH,False +444,25.0,15.0,17.0,18.0,21.0,13.0,21.0,25.0,GCAFBBBBAFGHBACAFHCECHBEDEHHHEDAHABCGDEAAABDBHAHBEGGDGACDBGGGGHGHGCECEFHFCCGBEEEEEDFCGDGDADADCECBFFCAEAEADGDHAHAHEHDHAHEFEHDGFHFHBDDAHAGAGAGAGEFBHECFCACHDH,False +445,4.0,5.0,1.0,1.0,6.0,3.0,0.0,1.0,FEBBABEBEAFHFEAEAEBDC,True +446,3.0,5.0,3.0,4.0,0.0,2.0,5.0,1.0,DBDAGBGCGCGCBBBAGFDHDFA,True +447,27.0,17.0,19.0,29.0,21.0,26.0,19.0,16.0,AAEEEEFDFHEADAGFGFGAGHFABBBBDADAHFDGCHFDFAFGCCBFFHDHDADEBHGCAHAFCCGCHEEADCBFFDFAFACAEECDCDBHBDCCEDEAGABDBDGGGGHFHFHDEAFDCDAAABAGCGFDFEEEBGAGAHBGDGDFDFDHHACCDCEBEAECEFEFDFDBDB,False +448,12.0,3.0,7.0,7.0,6.0,6.0,10.0,15.0,GCACACAFHFHGHDHAHDDEDCFAHACAHGEFHBHBFGDEHEAAAGAGCDAEGEBHDGFGHHCHGH,False +449,27.0,20.0,31.0,20.0,16.0,31.0,25.0,16.0,CCFCACAHBDGCGCBCGCDCBBEBAGFFFCFCDCBHBEFDFDHGGDCFEDBDFDCDCFFDBAECHADBCHCHCAAAAFAFADDGFCECGCGDDEHGHFFEHGHGFGFGAEFBFEFDBHAFDGGCFAFHHHBHEAGAEAEABGHFAFACACBCACGBBAGACAFFGFGFDBCBCGEEEECFADGBGA,False +450,2.0,7.0,4.0,2.0,6.0,1.0,3.0,3.0,DGCGCBDBHCECHBEGEABFBHEAEBEB,True +451,8.0,7.0,6.0,1.0,2.0,4.0,4.0,3.0,FGFHEABCCCDBABAHCHEAGCGCBAAAABBBFGF,True +452,12.0,16.0,17.0,11.0,29.0,15.0,19.0,16.0,EGDGEGHCFCFDDBECFHFHGEBEBEBEBDBAHAHADCEEEEEEEBECCBBBGDCDCFGHHEACAGBGHFEGEAECFDEGFHCEDFDFDCBHEAEAEFBGCGBAHFHGGEEBFGFGEHAGAGAFCBHHHCCECEG,False +453,4.0,3.0,6.0,2.0,6.0,8.0,4.0,3.0,CCFCEEHCHBDEFAFAFHGDFEGEFBFBFCECGAGA,False +454,17.0,13.0,25.0,22.0,19.0,16.0,28.0,27.0,AGAHHCDEDGGGDHHFEEGEHHCGGHGABCDCDAAFCFCGAGCFFFHEEEHEBGBCFHDAEEBDCDCGCGCBHBFCFHDHGBGDHCHFHBHDHBEAFCCDEDAGCGCDCFFHGHGHGAGADACAEABFCECECEBEHAGAHHDGDGHGHGFDFDEBCHDDCDGBGEA,False +455,3.0,8.0,5.0,6.0,3.0,3.0,1.0,4.0,ADHHHDFFACBCBCHCBDDGDBDBEBEAEFCBB,True +456,17.0,25.0,25.0,21.0,21.0,26.0,24.0,21.0,GEGBFBFBFBGAHAFACDEDCCHFFGBGAACFCHGFCFGHDAEFEFGFGHEBEBDAFGFAFCCBABEHCGFEDEDGBGBFBEHEGGCDCDCBGHDCCCDFAGBHBDEDHCHCHEHCBCDDDDFBEEEEGGBFCFCHAHACGFBBHDHBABGBGDGDFAFAECECEFDFDBGCHBAAHHEH,False +457,12.0,10.0,8.0,8.0,4.0,11.0,8.0,8.0,DBDFDFCCCHBEGFBHEFACBDBGHGBFAFGHAHAHGDDDCCACGCEHGFGFBFBABABDHFAAAEAFA,False +458,20.0,11.0,18.0,22.0,26.0,28.0,20.0,28.0,BFGHCHEAEAFFFFGABCFGFECECECECHCHGHDHAHEEEFHAAFBCGHDHDHCABGHCFDGHGACFDDDBCGDDFGGGGEEABGFAFEHAFEHAFAEAEABAGFDFEEHEFECDADHDHBHEHDHCHFHDHFHGDDDDEDEFEFGDCHCECEFHFAGBFFEFCADGBGBHA,False +459,18.0,25.0,19.0,16.0,13.0,17.0,21.0,14.0,CACACDEDBCBHAAGHBHBCEDEDAGGHDFDEDCHFHECFBFACAHAGGGGGAGDFBABFFGFBHBHBGBHBACABHBGCGBGEFADCDCHAHDHDBACABBBGEGEFCFBGBEFDFABABFCEGECDCBCGDBEGFFCFDGE,False +460,21.0,19.0,19.0,30.0,29.0,19.0,23.0,32.0,FDEDECCDEEHFDFEFEFHAHDCGCGCFDDDCGAGAECDHBEBAHGCGEFEDHDHDGDBHBADCDCHHFECHBGBEHADBDHGHGHGHDHFBGAGHBFBAECGGFEFEFDGDCDAEGEBACHGGDDADFHAEABBGBABDFDFABEDAHBHAHAEDEAEHEHCFCHEHEHBHBHGGCACAHEEEEFDFCGDH,False +461,9.0,19.0,19.0,25.0,19.0,17.0,20.0,16.0,BEGCGDAEHEDBDCEHECACAEAEAFCEGHGHFHGHCEDDDHDEGGFEHEFDFGFDBDBDGDEDCFCFHECBDHACCBCBFGDGCHBHDDBGBGFCBCDDGDACFGGGGFGBEBEGHDBDFCFBFDFDBHHAHAEDFBCBEBEC,False +462,9.0,14.0,11.0,15.0,9.0,10.0,15.0,17.0,CHCHCGCBEBDHEHFBGDGDGDGDBDGEGCHHBDBDACFCHGFEAHFFDCGAGBFHEDEHHAHAEBHBHGAGBFBDBCFCBCBADAGEGHHEFDFDGDAH,False +463,15.0,16.0,16.0,16.0,13.0,12.0,15.0,14.0,EDEGEDHBHDHDACHCBCAHADGDGAEEHFGFGFAEGEDECGGAFAFDBCHCGCEBABABABDEACHCBABAFGEACFDBBCBEGEGCDCDADBDFHHHHHBDCDGBFFGFHCBCFG,False +464,20.0,13.0,10.0,7.0,14.0,12.0,14.0,15.0,HHHBDFFCHCGCGAGDFDGEBFBABAFAFHGHBAGEGEHBACFCEDBACCCABADAGBGAGEEAAFAFACGCFAHEHEDEBAGEHEHEGAGAEFHHHHABEBDBF,False +465,32.0,28.0,23.0,18.0,15.0,22.0,28.0,21.0,CAHHBFBGCACEGFGAAABABAGGCGCGEAAGCGEEDBDGDCDHDBBABAFABAEDBGCEDBDBAHABFHEDEDBFFGAGHHEGAGHEECDCFBHCGBDBDBFGFDFCFAAACACFGHGAGDCFGAGFFBHCHCEABHBFBFHFAFHFEFBABGBGBGHHHAHAGEFCCHBHCAGBCDCECADADAG,False +466,14.0,31.0,26.0,20.0,17.0,27.0,15.0,13.0,BBBBBCGFEFDFDFCCDCHHDAFADACCEAGGCGCACFFEGECEFECCACGEBAGDGHBABDBHBHFCBHFCFCAHDCDHBGFEEDEDFAFHHGBBFAFCCCFAFDFEBBABACHHBDBDBFBCCFFFFFFDBBBBBEBECEGEGDGDGEGCHEBCDFBBBDD,False +467,15.0,12.0,15.0,11.0,17.0,18.0,18.0,13.0,HAGECCBCFHEGGGGBGBDBGBAFACCFCFCBDFAAAAACEEEFECDFDCDCDHBGGGFGDABAGAFFEAEFHBEDEDEFBAHGCGCHFGFGFHHDHECEAEGFAFHHEHEBBGEHFDC,False +468,22.0,12.0,14.0,17.0,19.0,18.0,16.0,15.0,DADADADAHAGABAEHFGFGEGBHBGADHDGGACHEHCHGEFFBCGCAFGDGAEHEAAFCFGAHAHEDDFDCHFEFEDEBECABEFGBGAGCCECFCBBBBHAEBECCADEDHHHEDEDEDFFFFGDAAAFCF,False +469,18.0,26.0,29.0,20.0,29.0,19.0,16.0,15.0,CGCGCHCFCGHHCHCHCHCFAEAFFECEBFGDHDCECECHCFFDBDEDBGGEGAGEHBBCCACABEEEAEBEBACECGADBBHBDBEFEFEFCDDGCCBAHHFCBHBADAGFDBEFEFEAECBFFHABDBAEDECECEDBFBDBDBDACGEGEBADCDGBGDGACFEFBAEH,False +470,6.0,1.0,5.0,5.0,3.0,4.0,4.0,6.0,CBCAGGHDHDHDHFHFEECACADHCAFAFGEADG,False +471,8.0,12.0,3.0,4.0,7.0,8.0,8.0,2.0,GAAFBEGEFDAGEGEFEHGBCFFFFGBBBEBABABDBDBEBDHGCABACAGF,True +472,9.0,4.0,9.0,5.0,3.0,6.0,1.0,7.0,HACGCABHCEAFHBHDAAACFCBEDEDADAHFHFCFAFBCDCHC,True +473,2.0,1.0,5.0,2.0,7.0,3.0,2.0,10.0,CCHCDDGFHAEBEHHFACHHFHEHEHEHECEG,True +474,8.0,7.0,5.0,9.0,9.0,4.0,1.0,12.0,BCDHBCBADCDHHAHDHAHEDEDBHEEDHCHAFAHAHCEGDADEFEFEFABHBEB,True +475,11.0,5.0,2.0,1.0,3.0,2.0,5.0,4.0,AACDCFHAGAGAEBGBHBFEAGBGAAAHAHABE,True +476,25.0,30.0,25.0,21.0,26.0,22.0,25.0,24.0,HGHEDBDBCHEHEDEDEDEDCAHDCGCFDFGEGDGAGAGHGDGDCAAHABAFACBCBCEDEAEDEAGDFEBEBEHGHFHFCBBFGHGFEFBBBFHGBCFCEBABADHBCACGFHFACACDFABHEAEHHDGACHFBFBHBHBABGGDBABGFEFBHGHAHEBGBGCFBEBECGCACEFAGECACFDFEAECCBGHCDD,False +477,15.0,14.0,22.0,19.0,17.0,22.0,25.0,22.0,DFGGGFHHCHEHBGDEEBFBAAHGFGFGACCCGHFHBHCDEEFEFBFAFBFCGCEDEHEHEBFAFAFAFGCGCGDBCBFFCHCDDDEAEAGDEDECGDGABBHDHDFDFDGCGAHEHFHCHAACDDBHHACBGBGAGFFHCCGHHCCGDGDGCGEE,False +478,14.0,12.0,9.0,13.0,13.0,17.0,7.0,13.0,AFAFBFBDAAADFFBFBEHGFEFHAHFGDDFDHAHADABFBFHEHECCACGFBDBGAEHCDCHGHGEAECECEFECADFDBGBHBHEHDDFEFDBEAC,False +479,29.0,20.0,16.0,24.0,27.0,18.0,17.0,26.0,GEHHHAHEGBGCHCBCFGDGBFDHCCBCHFHAEFEGGDHDACEDDDCDFDFDHBAADHFHBEFEHCHCDFAFABAEGBHBABABAEHEAEAEDEAFHEDAGEBEFGCEDEFEDHBFFDFAHHDBDGDHEAEGCBDEDBAGAGAGAEAHACACAEAEBHAHGFGEBEADADBHBHFCC,False +480,11.0,14.0,7.0,9.0,18.0,15.0,6.0,9.0,FAFEGDGBBEFEDEFEFABAGEGEFFFBBCBEDABEGAAAFHFDEHHFBFDFAFCDCDEGHHCHBABCBEHEHEBEBEDEHABEFACDC,False +481,8.0,4.0,7.0,16.0,11.0,8.0,9.0,4.0,EEADADFDEAFBFGEGFGDGCHDDCDEBEGEGCFCHDAGCGDGAECFCEDDFDEABABADDDDEHFH,False +482,11.0,7.0,25.0,5.0,16.0,24.0,10.0,11.0,EAEAEACFCBCEFEGAGAGCCFFEFGBCFFHFCFAHACFCEEHCCFDFEEHBHFHAGFFEFEBDAGCGFAFEFEHECGCGCFCFHFHCCCBCDDBCCCCFDFHAECBHG,True +483,24.0,31.0,31.0,29.0,20.0,23.0,19.0,21.0,HAHEECBBBBGBECEFBFHHCHFHDBGBHEGEADAEAEBBFBCECFCACABHCHCEBFDFCFCFBFHHHEGCDCDCDHDCECGABADDDBAGAGAHEDEBBDGCBCFAFABAHCBCFHGHBDEDGBGEHCDCFCFCAHFBCDCDGDHABGFEBDBDBDGAFAGAFDDCEFABAFDDGAFEFDGCBABHCGDGDCDCAE,False +484,10.0,14.0,9.0,7.0,6.0,9.0,6.0,9.0,HCACBFBFCFCFHAHADACABDCHGHGCBFDHCBGBABFBDBFBEEHADADHBBEBADAGECEFHBGEGF,False +485,10.0,4.0,11.0,5.0,13.0,7.0,15.0,10.0,AEAEHCHCGCGCBEGEGFGBGAGFGEHAFGCHDECCAHADDFDFHFHEGEGACCBHDHAEGEGCGHBEEEGAFAC,False +486,10.0,4.0,4.0,3.0,10.0,7.0,9.0,8.0,HGHCFDHAFAECEFHFHEGECHDDACABAEEEGGAEAGAGAGAHFGFEHEFGBBB,True +487,5.0,6.0,9.0,7.0,10.0,8.0,5.0,12.0,FCFCFHFAFAFGEDCBEHHGGEHEHAGBHCHFEAEDEDBHADCBCDHDHDFBEBCCHCGEHE,False +488,11.0,11.0,11.0,8.0,15.0,8.0,13.0,12.0,CBABEBFHFGEGHCDCAGDGEABBCGGBBHEFBBABGBADEHCHCEAEAEGEFFFCGCEHDHDHECDCAFAGAGAGEHEGFDHCHEHED,False +489,22.0,25.0,26.0,26.0,18.0,25.0,28.0,23.0,BEBEBEBFFHDHDHCHDHCCGCFAGCHCHCDCGCABABAFCHEHBCBCDCGCEHAHAEGGABFDHEBECGCHCHFDADAHHEGFBHAHFDGDCCCHFFGGGGBFAFABGFEFAGGFGDBAHFEGEGEDBBEDDBHBDFDFGGCEFGFBFHGADADHCEGEGDGDFDBBCBCDGBADABAFCFAFADDDBCGAE,False +490,19.0,24.0,22.0,16.0,30.0,19.0,23.0,31.0,FGGAFEFECGHHEGEHEDEFEHAGFBFBFHAEAHAEAEACDEBBHCECACEGBBFBDBCHDHGCFEHHAHAHBEBECGGDGCHBHGFGBDFCGHGHDHBHBACACHBEAABDHEHDHFFBFHFHEBCDEDEDFDGEGAGADBCHFHABDBDCFAEAEBEBECGCGEHHCCBCHCEGEGHFCGEG,False +491,16.0,23.0,19.0,29.0,31.0,20.0,28.0,25.0,DHDBCECECAGFGBBEEEECEDEGHCDGGAFDFGFGCGCEHGHGEDFGCDFGFDDDCDEFEABDEDEBEBHBHBGGHBDBHAFABDGHCECGAEAEAGABHDHDHDHBBBGEHEFEDHBEEEGGCDEFGHGHAHAFCFGFEDCFEABHFHEBEBDHDHACBCFGAGFGHEHBGBCHFGDDADCDADFDECB,False +492,2.0,8.0,8.0,4.0,4.0,4.0,9.0,3.0,GEGFACBGAGECCHCHCBFDGHCCGCGBDBDBEBEFDFBGBG,True +493,21.0,13.0,20.0,26.0,11.0,13.0,10.0,15.0,AACGHHEEDBDBDCDCDBEBFBFEGDCEADDDFAFAEAHHHFAFADEDCHCBCAAGACDDDDDBCAGDCDBEHGHGFGABDHDHCCCCHADAEAEDHDAACAFAFBFEDGBHCCADHBGBDFCFCHCFG,False +494,4.0,3.0,5.0,3.0,3.0,7.0,4.0,3.0,AHFEBAHCHGFGFEFDADBFFCFCGCGCBEAD,False +495,0.0,4.0,1.0,1.0,4.0,0.0,2.0,1.0,BDEEBEGEGHBCB,True +496,6.0,16.0,13.0,12.0,12.0,13.0,12.0,10.0,DHFEEBAFCHCHCEFHABBCBCFGECECEGEBDCDCBBBBFAFEBEGGCGAGFHEDGBGEGCHEBDBHBHCGBHAGDFDFDFDFDHCADFDFGB,False +497,19.0,9.0,12.0,22.0,14.0,24.0,20.0,18.0,DEDAHEBAAGDBHHGABAGCHCDCACFCGCEEACBFAFAGEDDDHHHCHCGFGHBAGAFAHDDDDDGDFDFHFEEDEHFHEBFDFHBAGHGHFHFEDEDFDFDCGBFACAGAFHFEABGEGFGFGFECADAGGDGFFF,False +498,8.0,3.0,6.0,14.0,8.0,17.0,6.0,15.0,GFFDFEGGBEBHAEDGFAFEFDDDAFHCHCDCDGFHAHFHFGDHCEFHCHCFDHDHAFDFEFAFABAEHFHDHDEDH,True +499,0.0,6.0,1.0,2.0,2.0,3.0,3.0,4.0,EDECHDBGBGBHBHFGFBHBF,True +500,9.0,11.0,8.0,10.0,19.0,12.0,9.0,5.0,GCFDBACGFBFAAAAGBFAEGFGCGHEAGHDFFCEDEDEDEDECHBEGDDEAEFDFAFEBEHEHEDEBEBEBCBCBFFEGBCE,False +501,8.0,14.0,12.0,11.0,8.0,12.0,9.0,4.0,DBDBEBDBDFDAGCGFBCBCFFGCDCDEDBBBECECFBFECABDDAFAFAGEFBHAGAFCHCDCGHGHBFBEGEFCAG,False +502,5.0,5.0,5.0,5.0,9.0,6.0,4.0,8.0,FEFEBHHHAHABEBDDFDHDCAFFECEAHCBCEAEBHGHGCGFDEGE,False +503,12.0,12.0,13.0,25.0,16.0,10.0,18.0,21.0,GBGBDECCCFHHBACGDGDGDADCGCBBHDHDHDBDFDFDHEHGCEDEGEFAFHBEFFGCEHFFDDHDHGHGDAACAGBDHGHEDEDGAHCGDGDACEGAHAHDHEHEBEBCBFBEHEADDGDCAHE,False +504,10.0,15.0,9.0,13.0,14.0,7.0,8.0,9.0,CBEEFBBGBGBDBABADFBAAHEBEDEDGFCEBDBHAHBCBCBGGFDFCAGAFDGDHDHGEBEHFHECECEAHCDDEHEAEADCD,False +505,18.0,16.0,17.0,23.0,12.0,18.0,20.0,12.0,FGFABEFDHDHFHGDBDBGBGCACDDDHAHBHFFFBGCGEAEAGABHBGDGCECEDHFAGBDEAAHCEGHDEDEDFGHDDDDEFFAFGDGCFCFDFDACFCEAABGBABCBCFHGGBGEGAACCCCFCGBADADBD,False +506,22.0,16.0,25.0,22.0,25.0,11.0,27.0,18.0,AGCDCDHDBGCGAGDDCDGBGDCBCGFGHCECGHGAEFEDEAEGEFHGBCBCAAAAGGDGEHEAEDEDEBCBGFCFGDDEDECFDHDBEAEDEHGHCCCCABAFABCBAHCHGHCCDCEFAGEHAGAGHEBCHEGBHBHDHFEEEACACDEDEHGGGFBFBGDAAA,False +507,13.0,17.0,22.0,10.0,17.0,14.0,17.0,13.0,GGGCBBBEBHAEAGHDCGCDHFEAEABHCHGFGHGCCFFBCAAHEHEDCGCGCDADEHAHFDFAFCHCFCBDEEAEFHAHFCFABBDBDEGECEBGBGCGCDEEBEBFBEACBCGCGBGCFCF,False +508,17.0,21.0,24.0,12.0,17.0,20.0,19.0,17.0,ECHCHCHCGCFBGAGEBEBEBDCCFHFGCDFFHHBGBGDDDGFCFCGDGFAACACGFHDHGAAHAEBEGCCCFGFADADHBBBBABEBEBCGCHDHBGEHCACECEDDCFFAFEBACAEHEHBGBHEFAFBGHGFBCBEAEAGFFCF,False +509,4.0,0.0,5.0,5.0,1.0,0.0,3.0,4.0,GHDCDCDCDCAEHGCDHHAAAG,True +510,10.0,11.0,3.0,4.0,7.0,2.0,18.0,3.0,HAGGGGAFAGCGEGBGAEBGGEBEBDCEGDBDADEBEGAGAGBBBCGGBGAGHBHAFA,True +511,2.0,4.0,2.0,2.0,1.0,2.0,3.0,1.0,DEDFHGABBBBFAGCGC,False +512,2.0,4.0,2.0,1.0,1.0,1.0,0.0,1.0,HDBABCBCBFEA,True +513,4.0,5.0,8.0,7.0,6.0,8.0,11.0,4.0,GGHGHGDBCECECEGFHDABADEGGCGCECBFEGACFFFFBFCFHBAGGDDDD,False +514,20.0,26.0,19.0,15.0,24.0,22.0,24.0,21.0,FGFEFEFBHGHBEDHHHHEDCDEHEHCBFHGAFAFBFDCACAGGGGGGGHBBABFBFBCHGGBACGCGDFEEEEAEFFFFDECECFCBCBEAHCBADEDAGFDEDBBEBEHACAFAFABHEEDCFGHDAABEBEDGGHGHGDDFEFAHAHBGCGBGCCCABBHBAGCBHBE,False +515,22.0,23.0,26.0,33.0,16.0,30.0,25.0,23.0,GGGGCBEHCBCFEGGFADHDHCGDACCDBDGFCFHBHGAABFBAHAHDGDBDADACGCFDFGFDDHBGGGEBEBEFGFHBEFABEGCGCGHAHFHFHDBDBDCDCDCHFFFHFDFAGEGBABFEDBDCECBCDDHDBGECADEDEFFFFAFDFDECGHDFDFBCGFECHHAHAHGCBCDADAEAFCFCDHDABAHABC,False +516,17.0,13.0,13.0,12.0,15.0,20.0,10.0,20.0,FDFAGABHFHCEEAFCEGGBEBCBCBEBDHFACGHGCACACAHFHDBGFGDAEAEABFDEDHDFAFEBDHHHFHFHFHAHAHAEAFADCCFBBCEHFFFDGDGBEHHHHGCBEFEAEDFC,False +517,26.0,21.0,23.0,17.0,23.0,30.0,24.0,22.0,ABAEAEAEBGGGGGAECECEDFCEBAGHFHAEADCCGGGAGBEBEBEDCDFAFHFHGCCBHAFAFAFHFGBCDDFACGFGHDEEGEFEGBGFGADFCFCFCBAEABCDHHHCHFHFHBHAEFFFCFBECCCFFDFDBCHCADAFHBABDFDBBAHGGEAEHCGEGCDAGAHDGDFHFHFEBABEBH,False +518,7.0,13.0,9.0,12.0,7.0,6.0,7.0,5.0,CGCECBHDEBGBAFCDBDBDACEBDDGDGEGEFAFAFAHCFEHEDBCBDBDCDBBBDCHFBAGAGH,False +519,15.0,23.0,14.0,11.0,17.0,17.0,14.0,16.0,AFGEDCHBBBBBBGGECEFFBACACBCGCBHFAAABCCEEDDDHBBFBFBGEHEFDAEAFFFEHAGABAFHFBDBHHHBEBEACGCGCACDCHEEBEGGDGHGHGDDDCBGAEBEFEFAFHHHFHFB,False +520,18.0,12.0,17.0,12.0,18.0,12.0,16.0,36.0,EGEHCHDHDGDGCADAHAHFCEEBACEEEADAHHBCBEHEHEBAHCEEGCFEFAFABHBHGHDCGCGDHDHFHDHDHAHCHABCGCFBHHAHFHFHFCEHEAAHHBHGEAHHBFCCGBGFHAEAEGCHBHGDGDGAGFHHC,False +521,4.0,11.0,9.0,6.0,9.0,15.0,6.0,12.0,FFFCCHBHCFCBCBFDDGDGBFAGCFEFCHCGFBBBHCHDEDEAEBHBHGAEAFFBEGEHEHEHBHFFFFHD,False +522,17.0,10.0,12.0,14.0,22.0,13.0,17.0,18.0,EEEEDEABAGFEFEHGHBDAAABDBDAEHHAHGHGHDHAEABHHHHHBCGCFCFCDBAGACEEGCGAADGDHAFCFCEBEFDFEEACGHBEFEFEFEDCGFGHGEGDBAEGEDCHAHGDFDGC,False +523,0.0,4.0,3.0,2.0,1.0,0.0,4.0,2.0,DDEBCHCGBGCGBGBH,True +524,25.0,20.0,21.0,11.0,21.0,16.0,21.0,28.0,FGHGHEHEHBHFHFBFBDBEGDCHCGAEAFCDEAAACHEHEHBFFFFAAHCGGHGBGBHCHCDCGAGAGBHHHFDCDAEABBBCECBGGFACHCECEAFAGHFAEHGGEDEDEBHHACCCACBCHDGDGAAABAGFEBHAGBGCFEEDEAEAFBECHHAHBHB,False +525,5.0,5.0,3.0,6.0,5.0,16.0,3.0,8.0,DHFHFEFEADAGEGECBDFCBDDFHCHFAAAFEHHFBBBGDFFFFFFFHFH,True +526,1.0,0.0,1.0,1.0,2.0,0.0,4.0,6.0,HGHCHEHEGGHGDAH,True +527,14.0,26.0,15.0,11.0,16.0,18.0,25.0,17.0,BHFABADGFABCDGGECEBEFEDBDHGFCFDBDBCEFBFHAGBFEFGFHFHCHBHEHFHFHCHCEDBDBEGHGHGCBCBGDEEFCFBGBGBGBCBDBGAEAGBGAGECEAFGGGHGCCAFGGEAEDBHAGABAFAGHHCBBB,False +528,26.0,33.0,22.0,21.0,21.0,26.0,21.0,23.0,HDBFBDGDGHHEBFFCECFBABGGEBEGGAHEHABGBCCCABDFEFGFADACCGABDBFBADADBDAHAHBEGHFHBEGEBCBCBHAHABADCHBGCDEDEDHGGGGGCDBFFFFFAEECHCHCFEBEAADFBFBABDBGEEHEGEFCFCFEAEADCGFADHHFBDBAHAHACABABFBFCFHBHBHCDFGCD,False +529,19.0,28.0,16.0,26.0,16.0,17.0,19.0,17.0,ABADGCGBHDFFFGFGDGFBDGGFAFCGGFHHAAFFFEAAHAHCBCBABADDFFFABDBDBHGDACHCHGBBBBBGEDADAGCBEBHHEDBCBCBDEEGADABABADADCCBCBDFDFCBCHFEEEDEHHHGHBHDEECHGDGDBEEEDEDGDGCBBD,False +530,10.0,4.0,8.0,6.0,5.0,11.0,7.0,6.0,FFBFCDCGAGFEDCDBEGEGFCFCFCBAFDBHAHAHAGACAHAHEGDFCFADEGAFH,False +531,13.0,7.0,11.0,9.0,7.0,13.0,13.0,17.0,GCABEBFBAHHHGHGAAHCHBEBCDAFHFHBCDCDCDFGEGCHAHEHCHDFFFGFGCGAAAHGGGHFCECHHHGAAEADFBFDFDEDAGF,False +532,6.0,4.0,4.0,4.0,4.0,11.0,3.0,7.0,ABCDHFHFECEDADFGHAFCFCFBFBGADEHGBFHEHFHFAFA,False +533,14.0,30.0,24.0,27.0,22.0,23.0,21.0,29.0,CEBEDGCHDGAAABHEHGCGBFBEGDDDCDCHHDEGFHCEFBGBCCFBAEAGABEDFDCDCDHDHGFGHGCGDDFBBBBBDFDADCDGBFEFDBCFCFBDHDGFACAGFDFDEAECFBBHBHCACAHFDEHEHBDBGBHBFBEDCFEEHBHBCBCBHEFEFCHCHEAFHBHBHEHFGCAEGHGHGHGHED,False +534,7.0,14.0,11.0,10.0,12.0,6.0,11.0,7.0,ABADCBEGAGABDBHCECDBEHGCBCBCGCFCFHFHFBBCBGEGHGDGEGEDDDCDEDABAHCFEEAEFEBBGDEHBG,False +535,1.0,8.0,7.0,5.0,5.0,7.0,1.0,7.0,BHBGFHEDDFCBBBBHHHFEFHFCFCACBDBDEHEFECCCD,True +536,5.0,4.0,11.0,11.0,13.0,6.0,6.0,8.0,CDDDEBHHGHDFGCCACEDEDECEGEACACHEBFFEFEFGFGDGDHAEEEABCBHEDCDCHHDC,True +537,28.0,21.0,11.0,18.0,13.0,11.0,21.0,19.0,HGAGAGFDDHGEBDCGAAHGHEDBDFDEGAGHDECCAAAADDGBBCBHBHBHGCGCBBBFBFGABAGCHBGAFHFAACAGDFEFEGGBFHAADADFDADBBBDAEAFHGHEHEHAHAHAHAGEGDCDCHBABABECDGAEBE,False +538,3.0,5.0,4.0,4.0,5.0,2.0,1.0,6.0,HCHGHAFBEBEAEACDCHBEBFCEHBHDDD,False +539,6.0,6.0,7.0,4.0,9.0,4.0,6.0,1.0,CCAGDGDGEFBCACBCGDDBFEFCFEABABCEEEABAEGEGEH,False +540,4.0,1.0,2.0,4.0,0.0,6.0,5.0,0.0,FDDGAGFGCGAGAFFFBCDADF,True +541,9.0,14.0,13.0,6.0,8.0,6.0,10.0,5.0,CBCGEGEFEHAGEDBGEGAGHDCBCGAGAGHDFGAACBBDBDFFCFHFDACACBBEBECCCCHEACBBBBB,False +542,16.0,16.0,8.0,16.0,13.0,11.0,10.0,17.0,EAHAGFDCGCGDEHCHBAAADHDHEHEFBGBABFDAAADBDADADHDGEGCGHGBFAFEBBBBHFDFDEBEFAHEBDGFHCHCHGDFABABDHHHAEBEHEDEBCCF,False +543,21.0,26.0,17.0,27.0,29.0,23.0,26.0,18.0,GDEHHBFFAHDHDCBHBGEDBDGAGDHCEEEBFFACBBEDGFCFBEBECAFDDHBHDEFEFEFEGGCGBHFFCFEHBHEFBHBADAEAGAFBFGEGEGCGDEDEGCGCBDFDFDADABCFEBBBDBGGGFGCDCDCACFEDBGEGEGHABGEGEAAAACCHEBEDEHBABFGFHHEHADGDADADAD,False +544,22.0,22.0,21.0,19.0,23.0,23.0,21.0,20.0,CGDGDBCFDADCCGDBDHAHCHCEDFFGGGECECEAFAHCFDDEDAGCGCBDEDEAEHCHCEEECEFBFHDHGHGEGCHFEAEAEFFCFEDEABHHHGFBAGAGBDEGECECECHBHAHGBBFBGBDFDGAAFAFGBBCBGBFHEHCBDFFFHFBAAHBFBAAAFAGABDB,False +545,23.0,25.0,25.0,15.0,25.0,17.0,21.0,33.0,GAGAGEEHHHFHFHFHEHDCFHABBHBHBEBHFGBCCACACACGHBADHBECECEBABECCHCFEGHDCEBGGEBEBEFHHADCDCDFDHBHCAEEHEHFHGHGHFADCGFHCACACACBCEGDFHCABGDGEGFCDHGHAAAHBHBHBEBHBHAGABEEGEDEGFBFCGEDAGADDBBEAFCF,False +546,3.0,2.0,2.0,4.0,0.0,4.0,0.0,0.0,ADADAFCFDBBFCFD,True +547,13.0,21.0,3.0,11.0,13.0,5.0,12.0,11.0,GHBADHBHBGBEHDHEEFGHDHGFEDDDEGEAEDFAAGBBCBAGAGAEDEHBHBABABAGADBEBECEAEBBBBGBHBDFGCADBFBHG,False +548,25.0,24.0,22.0,17.0,28.0,18.0,39.0,21.0,CDCABDBHBGBGBGBCECBABGBGAHAHBFEEAEBGAGEHFACACDEGEGECHAEGEHFHFABEGHFHAHGHCDCEBEGDBFAFHGEGBGAGDBDBDBEFECHFHEBFGEGEGECAFABEBGBGHGFGEGCCCCHGFACGBHAHAECFGAEDHGHGDDDEAFADGDGDCAEGGACFBFAGEGACCEHDCDGGFG,False +549,3.0,2.0,4.0,4.0,5.0,8.0,5.0,2.0,HFEFGDGFBFDFEEEFEFGBGCCACDCAGAHFD,False +550,1.0,3.0,4.0,3.0,7.0,2.0,2.0,6.0,ECEBHBHGHBECEFDHAHECEDEDGCHF,True +551,16.0,22.0,21.0,26.0,28.0,20.0,19.0,21.0,EGEDEBEAEADDDCFCABGEFFHDBECHBBBBAHAFFCCDDDDDDHGHEFAAAAAGGBGFGBGCCHEHFBFHHDCDFFBFDGEGFCABBEBEBECDGFEECACDDBCFEDEHHDBDFHFHCHCEGGGEGEADCDCEGEFFHHGCCBCBDBEBEAEAEAGDFHCDGDHBHEHEH,False +552,4.0,5.0,6.0,11.0,3.0,11.0,11.0,5.0,GCCDFHFBDDEDECGCGDGHABDDGGGDHAHAFGFGEGFGFABDFHFCFDBDBFFC,True +553,5.0,13.0,12.0,7.0,6.0,1.0,8.0,8.0,BGDACECGDGCCCBCHCGCDBHHGBEAEAEFBCBEBDGCGDGCBABABEDCHHHHHBBDB,True +554,21.0,23.0,19.0,23.0,24.0,21.0,32.0,21.0,FAGAHAHFHGHBEEFGADABCBGBGFAHEDEFGFBHCECEHEHDGDEAAHGGGEGFFDFBCHGAGHCDGGGABDGDADHFEBHBHGGCACBCBCBGBCFADADGDEDACBGHEFDFHFHFBDDDDBHBGGGCDEFEGEGECHCBCBEBEBEFFAGBBFACECECDAEFECGAGEFDGGAADHDH,False +555,11.0,14.0,17.0,9.0,22.0,14.0,9.0,22.0,CGEEDCDADADBDBFFFHCAAEHHHEHEHAHEFFCFBGHHHFHCHDHEBGFGFBEECFCEEECGCGHEEEEADHBHAABCCACFCEDHCHCHBHBDBECGCEFFGFABBEBEGHAHBE,False +556,4.0,3.0,4.0,4.0,4.0,1.0,0.0,1.0,BABHECAAFBDCDEDEDECAC,True +557,11.0,15.0,15.0,16.0,14.0,18.0,14.0,14.0,BCBCBGDGCGEAHHEHGAFFCFHFCGAGACEBEBEBAFGCCDGBCEFDFDAEADDFDCEBFBFBEHDHEHEGEGBGHFHDDDDCCBGBCBHAHDEFFFGGCHBEAAAHFFDFDFDHC,False +558,5.0,2.0,3.0,3.0,1.0,2.0,3.0,2.0,DGDGACBFHFHAEACABACDG,False +559,29.0,26.0,17.0,17.0,20.0,26.0,24.0,23.0,DADCDFFHFAFACAFBDBACAGABFGFBHCHCFFEFEFGHGCBCAEGGGDBDBABFHFAEADDDEDEHAAGGDBHGFFFFCGAHBBGBGECEGEGEGEBEDCFFDFCCEAAFDHAEBFBFAHAGFHCCGBGBGBGAGABEDADHEBEHHAEFHAHABCBCHAEAFAEBHGHBBBAGDHHHHC,False +560,7.0,9.0,14.0,11.0,8.0,12.0,13.0,5.0,FCDCEFEFGHDAABACGCGCGDEBAHHBCCFCFGEGDBDBDBAFECDFDFEGGCAFABCFGFGEGHCDEDGDGFCBCBH,False +561,16.0,32.0,21.0,19.0,21.0,20.0,22.0,22.0,AFBGBGHGEDFAACDCDCEFEBCFCGHGHFDABABAHCCEAHBEDEDBDCCHGHEBEBEBCDEFGDGFBFEDHDHDBBBFFEGBGHEDGDFBGBACDGEBEBHBHCCGHGHGDGDGHGHBCAFHGHGFABAFAHAFCBCBFAHDHBBCBGFEBABCBCFCFEEBCFEDEAHBE,False +562,18.0,21.0,6.0,6.0,14.0,3.0,15.0,20.0,DGAAHCHBAFHBHBGCAEAEAHAEAHHHBCBGGEBDFAHAEAEBGAGAHDEGHAHBEAEGHGHBABHBHEDCGHGBEDGBGEGBGBABDBAEEHFHBCBCBHB,True +563,19.0,18.0,15.0,19.0,14.0,16.0,17.0,24.0,FAFAFABBHDCDCDFDCAABFCEDBBECDCDFFAGADBCHGGFHDHGHEECEGDADABEHHHHCHDHDFAHGFGFBDBCBFHAGABDBGBFDGGFCFCBHBHFHEHEHEGAGAHAGABAGABEECDCHHEBEDEHAGCGHDH,False +564,3.0,3.0,2.0,1.0,0.0,0.0,0.0,2.0,BABCBDAHCHA,True +565,8.0,12.0,12.0,9.0,13.0,13.0,12.0,17.0,BFBFEEHBFAFGGGCHDHDHGCDCGEHAHEEBBAEFGCGCHCFCFDBBBHCEBEHEHFGAGFFHFHABDGDFDFBHAHDHEAABCEGEGEDCHCHC,False +566,24.0,19.0,7.0,22.0,15.0,14.0,18.0,21.0,AEADAHECBGBFHGHDHAGDGHGBGBHFHBDDDHGHDHDADHDHAHDEDADGFEFGFBDBDFAAAAABEFDHHHEGBGAAEDEGEGAFAFHHBEEHCGBEADAEFFBFDFDBDBGBHAGBCBEFDHGCACBCBAAACAGE,False +567,18.0,34.0,25.0,23.0,26.0,29.0,16.0,24.0,CHFDFHBCBDBFBHEEAEABABCGAFDFDADADADBBBCBDBFCEEEFFAFDBDBGHDHBBBFFFDABFHGCABABABAHHHHDFBFEFHBCDCFCFBFEEGECFHEGEGBBDDHDEDHFHDHDFBAECCBHBEBHBCCCBDBEGHGCFCACEFAGEGEGCCFBFEHEHCGFECGFDAGFGHCCCEEEBEHAHDG,False +568,10.0,3.0,8.0,11.0,10.0,4.0,2.0,8.0,EGEDEHEHCDCEAEAEAFFEHCDDDCACHBHBDDDHAAACAEBFAGAHDCCFEDHD,True +569,16.0,11.0,9.0,12.0,15.0,17.0,17.0,12.0,EAEDEACHEAGBHHFFAGGDADADHBHAFFGDEDEHFBFCGBGFFDGHAEAFBCBEAECDADCGCGFGEGEGAGDEDBFFAFAFCBHAEAEGEGFGFDCHCGFBHBHBH,False +570,5.0,3.0,10.0,3.0,5.0,7.0,4.0,6.0,DADCHHGACACECHCFCFHDEGABAFFFFECECFGGHBCBCEH,False +571,19.0,19.0,10.0,25.0,20.0,11.0,12.0,21.0,EGEGEDDDADCBFBFCHCHGAGDHDHDADGHEDDDDHBHBHCADEEEDDHDBCEAABABFEEAEGHGHFEADDDCABHBHBHFHFEEEEFDCEEGCBCHGAEAGABFBHAHEHAFABHBFDDDBDBHAAFBBAGGCD,False +572,9.0,14.0,14.0,11.0,15.0,15.0,19.0,10.0,EFEAEGGGDGDADFHFGFBFBFGDGBBEBEADHGCBCBCGCECGFDCBCBFDFGEDBDHCAFEFEBGCHAFGFGEEHBGCGCEEEBHCHBADCCGGHAHADAGFHFE,False +573,4.0,10.0,13.0,15.0,11.0,8.0,6.0,4.0,AFCCGEEDEBEBAHAHADFBCBCBEFDGHBEGEFFBFDDBCECDCDCECEDDDDDGDCDCEBBGDHFCCGF,True +574,15.0,27.0,18.0,27.0,33.0,20.0,18.0,26.0,FACGCDEDBABABADHDBEFECGDFHHEBCBCGHHAEBHBHGDADGDGDEEEDEBCBDBEAFHFEDGDGDBCHEAADEDEAEDHCHAFDEDHDACHBHBHEHECFBABHDEEEFEGBGDDHGFBFBFCFCEBEBFFCECEGEFEDGDCBGEGHFCECEBGBHBHDHCEFFFBGBHHHEFAAHDG,False +575,16.0,17.0,13.0,14.0,16.0,19.0,22.0,14.0,HBCFCFDFEGAGAHHGEGBGDGFHEHAFBDBDCHCHGFDEDEFHFBEBHBHBEBHBDFDEDEHEGEFFACACGFHADGFADGBAEADAFBCHEFFBEBGBGBACGGFGFAABGGDGFCCACAEAECDGGGC,False +576,21.0,18.0,24.0,12.0,15.0,14.0,8.0,14.0,CDCDFBACHGHECECEDECECHHAHBGFAAHAGFEBCHAGBBBABCBADCFEGABABCGCFAFEBHAHDHECACHHFCBBBEBECFCFAFAHAFCGDFDFDBEBDCACACADBDEHEFEDGCACAC,False +577,11.0,6.0,10.0,4.0,4.0,6.0,15.0,11.0,HHGHAHGDGCEBABABGCHCGCECHCACHDFBABFHFCAHAHFFBFGGGGGGGACAGECDGAADEHG,True +578,13.0,11.0,13.0,13.0,10.0,10.0,11.0,13.0,HDHDFAHCHGEAAAACGBEEHHDEEEDADCDCACACDGDBDBCFEAGHCFCABFBFGCEFBHHHHGBGCGCGEEHAHFBFDDBDBCGDGAFAFB,False +579,16.0,20.0,17.0,10.0,16.0,13.0,17.0,18.0,HBHCDAHECCCCBHGEFCBCGFFAFACBDGDCHBHBCBEBEDGDFEHGHBHECCCEFAGAEHDGDGHBFAFAGAGBGBGBEECCAFAFDBBHFECBGHCHBHDHBHBAEEEAEHEAGAGFGFGDABA,False +580,19.0,23.0,27.0,23.0,24.0,28.0,24.0,26.0,FGFGCHDADGDHFFDCDABFFFFBCEAECEHADCDFDFABAHABDEDBAHCCCHBAAFAEGEGFGHDHGHBHGHDCFCFCADEFEHBAEEFGCDCGGGGGEHFGCGCFFHFHGHBCBDBDCCCGEBEHFBFCFEECFGHGHFHCAEBEBEGHGHFEFDCHCBCBGBDBEAAABCCEAFBHBHDHEEGABDDDED,False +581,14.0,16.0,19.0,20.0,20.0,20.0,13.0,20.0,ACAFBEAHDHEHBHCABBCHFHCEEGCHHFCDCBBEBHFABGDHFHFHBHBHBGDDDCFFHFBFGFECDCEAGAGACCCGCDCDEDEDADADFFFAFAGHCDAGHFEEGHCEEEHECECEGEFDFEEGDDDGDBBFBFBADH,False +582,13.0,15.0,13.0,20.0,21.0,19.0,19.0,16.0,EGGAGAHBFFEFEHECDCFCBGHFFGAGAGEGCGAGBFCFDDDEBEHEHCFBDDDDDDADAFAHHCFDEDBFFFFHAGCBDAFBHBEDGFGCBCBGEGEDCDCDCFHEHGHBDGEHABEGAGHFEDAHEEEEEBHB,False +583,6.0,13.0,10.0,9.0,17.0,8.0,10.0,9.0,FHFGBBBBABCCDHBEDHGFDEHCGCBEBEHCFCFBFBDBACFHGHGEEECECEDEDEHEDGCAEADFDGEAEGGGEBABEH,False +584,18.0,27.0,27.0,16.0,19.0,28.0,14.0,16.0,FHFCFAFHHBEBFBDCHBGEDBAFFCBHBCFGFGCGCEEEDEDBABGEFBGBAFAFHEGCGCDCDBHHCHAHAHGCECAHFHFDEGHBBCACABABFBFBFAFCDCDBABEBECFFGBECCCHCFAFDDDDFDBECEAEDBFCDCEFGFABABCCGEHCABGFEF,False +585,26.0,16.0,22.0,22.0,20.0,21.0,22.0,26.0,FHDHDHFCEBBDBAAAAGFGCBEDHDHGHAEAECDCBEBHCHAHGGFDAEFCFHHHEECCCDCDCDHAHABBECACADAHCDCDFBBEDAAGAFFHCEEEAFAFGFCECEFACAEAFFHEGFHCAGECFFGBGFGDBDBABAGGGGGHHHAHDDDHHHAHDGEGFGBGBFCEDGD,False +586,8.0,5.0,12.0,4.0,4.0,13.0,13.0,7.0,DFDCCCCCCFEBEBDFFAFGCGCBFDFBAAFHGHGCGAAHGFAFGFGCGAGBCHFHCGGHFHEAEG,True +587,4.0,3.0,2.0,3.0,2.0,5.0,3.0,1.0,BGGGDBDHDFCAEAFCFBFEFAA,False +588,7.0,14.0,10.0,16.0,16.0,9.0,9.0,13.0,BCDFHCGFGAEFFFDDBBHBFBHHGAEDDFDEHEGEGEHADFEEHEGEDEDEDEHHBHBDBHBDCDCDBBFBABACACEHECGHEBDGDCCCAG,False +589,41.0,28.0,27.0,20.0,22.0,14.0,25.0,23.0,EDEHHHEACAEAEGECBBHBHBEFAFEBAFHHGHAHACAGBDBEGCDEHAHADACACGEDCCCFBBBBBFAADACAGECDFHGDDBDCDCECDABAFCBEGEDFCGBGDHACABGHECBGGCDCGEFEAGCGDAAABABABDHGEAHBGAEHGBGBFCFCFEFBHGHBAAAAHABABADAGACACGCACHDHDHAFAGEG,False +590,25.0,17.0,16.0,9.0,20.0,24.0,14.0,17.0,HDFDEGEFBBECCBDBABFFAFDFCECBAGAEABGFHCACAFAFAFHEHEHECFCHEHEHECGBDBAFEBCFAFCFAGGCFCABHGABFFEGAHAGAGCHHEHFDFBEBCBEFAFAHAEFEAAHAHBHBGDGDGCEADAGEF,False +591,17.0,13.0,25.0,18.0,20.0,19.0,18.0,19.0,ADCFCHDBAEHEHEFEACAFAFDFEFECEGADHDHEBCCCCEHHGBDBDGCCFBGDDCGABAEAEDEAFAFCGCFHFEGAGDGFHCGCEHEAGCHCBDEDCFEDHCBEBFBAGEGAHCHCBCBAHACDBDCDCHFHEGFGFGDGHGFFH,False +592,4.0,14.0,3.0,5.0,17.0,15.0,9.0,5.0,HGFEEHBHFFEFHFEGBABFBGDFBBEFEDGDEDECEBEFEAEBBBBEBFAHAGFDFEFEBGCGFGBGFECE,True +593,13.0,8.0,10.0,11.0,8.0,10.0,5.0,8.0,EAEADADGFGCDDFBFHHGADABAFHHBAEABHHGBCFCFDFAFDHDCDCBFBCCCBCEEEAEAEFDAHACDG,False +594,16.0,13.0,15.0,7.0,3.0,9.0,20.0,22.0,BGBGCGHHHEHGAAFGCGBDFAFBHCHBDBCCCFDAHHBGBAAABHHHGHGBABABCCCCCDGHGHCHAHGEGDBFGFGCGAHAGFCHGGGAHAHCHFEDHDAAF,True +595,12.0,10.0,9.0,7.0,8.0,10.0,12.0,10.0,AEFDFGFGABHBHBACAHFFEECEFDFGBCAABBCDCGEBEBHHHHFBAEADGDGHGDGDCACGCACAEFHAHGGGBF,False +596,12.0,14.0,7.0,5.0,7.0,8.0,16.0,11.0,DBGBABFCGCGEGBGCHCABEEHGGGHGHFBEBABFBFBGGGGFDFCGABABAFAHHHHBEAAADDHCFEHAHBGACDGE,False +597,12.0,31.0,25.0,23.0,29.0,22.0,19.0,20.0,GBCAEDEGEDHCHGFBEGCCDCGAFBFAFEGBBDBDBDGGCEHEHFHDCDCDEDFHHBGBGCHABGCGCFHFDEBCDHDAABFBGBHDCDCEHEBFBFEFBFHEHEGEBBDBEBABCDGDBHBDFDFDACCEFBCBFHFGCEAEDFCCDCFGGEEEAEAFAFBHBEBCBCHEHCHGEEEBE,False +598,3.0,2.0,2.0,2.0,0.0,4.0,2.0,0.0,DADAGFCFCBGAFBF,True +599,18.0,18.0,17.0,19.0,19.0,25.0,24.0,26.0,EFEFADADEGEGBBHHABBHCCGAFDHDFEHHHHHHGAAADGHFHGGGGDEACHCHCFCGEGEFABEEGEHFCFDFEBGAHCHGFGFGFGFDDHEFCFEBDFEACAFHCHFBADGCGBADGDAFCHCHDDDFDFHCHBHEEEBEBGBABABABCBFFHFDGCGBGD,False +600,18.0,13.0,8.0,18.0,9.0,20.0,11.0,10.0,FAHEFAFAHDGGGGHCBEGABABFEFAAGAGAGAGAGBHBHCFFDHBHDEDEDABCFCEDEBEFADDBFFCFHFAAGDDDDDDFFFFHADFFFBBBCDADCCADHBE,False +601,28.0,16.0,18.0,22.0,25.0,31.0,31.0,28.0,DHDHCHCEGGGGGGHGHGABHGABAGDGEGBACHDHBGADFBHGAGFGDDADGEAEACHBBFFHFEGEFFAFAFGFEFAGADDFAFCFGHBFFEDBACABFHFCCCEEDFDCDAAHFHEHDDEDGHEFCAHFFBCGCGCACABAEAEHDHFHFHFCEDEDGAGAEEEEEFDAGGGHGHFHAGEBHBAEFCFBFCEHBHD,False +602,19.0,22.0,22.0,6.0,18.0,28.0,18.0,32.0,BEHEHCBFBFGAGFFFHEEGEFFGCHCHFABHHCCBFHFABBEBCACAEAFHFABHCHGBBAHEEEEAHAHBHECACAHEHEHCGBFFHFGAGCCBCBEFEGHDDGDHFHCDAHHHHDAFBFAFHFHGHGACCCACBHBGBGBCFGFHFHFGFGFAEBCGCBDEF,False +603,6.0,3.0,3.0,0.0,3.0,1.0,2.0,3.0,AAAAHHHEAEBFCEGAGCBCB,True +604,20.0,12.0,4.0,14.0,4.0,16.0,10.0,13.0,BHADGGGBAFFHAEDBAFGFCFHFHDHBHBGFFHADDEHFFBFGHAHAHABACADFFAAGADAGAGACADDEFEFDADAHBGBABDBDBDCHF,True +605,13.0,12.0,3.0,10.0,9.0,12.0,19.0,5.0,BFBFCDGDBDAGAFCHBBBDHGADCEAABAGFGFGEGEGDGFAFEGBGAGEFFGFGEDADBBGAGAGEFEBBHGHGEDDAFAH,True +606,25.0,22.0,15.0,23.0,20.0,14.0,29.0,17.0,ABABABGDEFEFEHBAAAFDDBDGDGAGEEBHFFCAHAGABACACHEGDGDFDHGGFFHFBEDECFGHCBAGDGCHBGBGCGFDADECEBEAEADAFEBEAEFCBCBCBHBABGBHAHAGAGDDEEEHBCEADGDGDHHFDGABDBDGGCGCADGGHHDHGGEGC,False +607,7.0,12.0,19.0,9.0,3.0,6.0,12.0,7.0,CHGGCADECECGBGCGCEHDAFACDBGGFABCBCBCBCBFBCGCBCBCBFHADACADHDCGGGDFCHGFCHDHDB,True +608,15.0,15.0,12.0,14.0,12.0,4.0,21.0,15.0,BGBEFEGDBCGCGHHEGCFAGEBFGHBCCEGAHACGBDBGBHAHGHGHEHEHACABADADAHACBGDAEHGHBDBDBEBAAAFCGCGDEDCDEDHDAGHGDGBGEGDC,False +609,11.0,19.0,6.0,5.0,9.0,14.0,11.0,10.0,BBBBGBFBFBABDHAHFBBAHEHFCAHGGDGDFCBCFCGAHBDBGBGFGHAHGBEEAFFFBFEFEACACEEGEAEDGFHAHBBBF,False +610,7.0,6.0,1.0,2.0,7.0,8.0,15.0,3.0,GGGGGDGFBAEAEBFHGHDFAGBEFEFGFGBHAGAGBCEAEGBGEGAFF,True +611,9.0,11.0,18.0,12.0,13.0,14.0,18.0,18.0,DABAEGBGEGEGEGFDHCGCHAHFHFCCCCHHGADFBGEHAHEHECFHEHEAGABDGEBCBFFFGDGBGACHHHDHCFCDCHHGDCHCBCDCGCBBDADGGGEDECBFFFFEF,False +612,1.0,6.0,5.0,8.0,3.0,4.0,3.0,4.0,BEBEBGBFBFDDCHBDFCHDGACHFHGDCDCDED,True +613,5.0,7.0,4.0,9.0,3.0,12.0,4.0,8.0,DEEHBFGFCHBHDHFAGDBDHDFCFEBHHHBFBABAGAGDFDCDFFFFCFDA,True +614,5.0,4.0,10.0,9.0,2.0,6.0,6.0,7.0,GCBCBCGGBFHHCFCHHDDDDCBGAEACACFDADCCAFHFHDHDEDGFG,False +615,20.0,20.0,21.0,19.0,32.0,21.0,14.0,26.0,FCCGGEHECEDEDBBECHCHCFGBEHECCCCCHCGCDCDEHAGCECEDDBEBABABEBEAAAAHAHEFAFHFEFBFBFAFGEEEAEHEBGHEHDBCBDAAEFFHCGFHHHGCEAGDBEHEFEGDFBFAHHDBCHFFBEGEGFHECEADADADBHFHAHDDFDFHEAEBDBDGH,False +616,4.0,1.0,4.0,5.0,3.0,3.0,4.0,3.0,AGAHCHBGDFDCHEDEDEFCFCDAGAG,False +617,14.0,17.0,16.0,17.0,18.0,16.0,11.0,15.0,EFEFHFABEBEGEAEBEAECBDHFEEGEGBGDHHHHHBHBHBHAFAHDBFHABDDFDHBGDECECEFEFGDABAFAFABDHFBFCGCGBEFCDCEADDDFACAHDCCGDDCBCGCFCABECGCD,False +618,29.0,30.0,26.0,14.0,18.0,25.0,13.0,17.0,HACCBHBFAFBFBFHFCBAAGAEBEFDDBDAAACACACEEDDAEFGBGFEFCABAGAGAGFGCHCAGFBBDFHAABFCFCFDHEHCFBFBHADBBBBHDDBCFABBEBFBADAEBCBHBHFHCBDDHCHGHCACAGAGDFCFEAEBECECECFCECECGHEBAFAEAGHBCF,False +619,31.0,22.0,24.0,19.0,30.0,25.0,19.0,29.0,CFHEHCGFFACEHBDEEGGACFCACAGAHAEAFDCGBACEFGAECCAGHBHBDBAEAGFBABAGACAHHHAHCHCDCDAGGGAHAEAEDGGCEHFHFHFDGBHBCEHEDEFEFEFEAADACHFBDBDBDBFBFAEHFHBHEHEGEDEDCCEBFBFCFCAHDBFEAEFEACAFADEBEHHDEGEAHBHCHDBGBCDHFGF,False +620,18.0,17.0,15.0,24.0,21.0,15.0,18.0,13.0,ECDGDBDGDGDEAEBEBCFGFGAGAGHCDEHEHBGGGFEAAFBBDFHCDCEEEEGAGAGEDFDHDHAFAFHEHDADADBDECACEDDBHFEGECADDCFHBCBCHCDDFDGBBBEAECEDEFABAHCHGDABFBFGFCBGA,False +621,0.0,2.0,1.0,1.0,4.0,1.0,0.0,1.0,FEEDEBEBHC,True +622,14.0,20.0,14.0,20.0,27.0,29.0,12.0,26.0,CDCACEHFHFHBHEFEDEBBFFFFBFECHHAHEHEDGDEEBFHFHAACEDECCCCEFEHAHBHDHFHFAFABEEEGEGEBDAHEEEEFHDDDGDEDABHBAFGFEHABFBABDBFFFHFCFHFBGCABBGBHFHFDDAHGFEFEDHCHDEBGGGBCDDDCGF,False +623,16.0,25.0,17.0,19.0,21.0,19.0,21.0,15.0,BFDFDFGBGDHBHEDCACFCEHEDEBCFDEDADBDACADDEGEGHAHBHFEBCCCAHEHEBEBAAAAGCFCFGFBEEEHBHEHGBDBDAGAEAGBDBGFEFGBCBCFGEGBGHDHGCCAADCDCBFBAGGFGEHDFBEBFBFDFCFHBGGGEB,False +624,23.0,27.0,21.0,27.0,12.0,19.0,33.0,26.0,DHAGAGFBFCCHHGGBCBFDFACGBGBGHCABACAHFHCDCDGFGFCFGFCAEGHGABABEDEDHFHFDFBGHGEGHAHBHCDAGAGAGBBAEAFGCACBFBDDHGHBHDGDGBGDAAAAEBBGBDBDCACFCHCBDBCCCBGFFHDHDHEGEDEHHDDDHBGBHDFFEBDDEEGGGGAGHCHDBAGD,False +625,17.0,22.0,27.0,7.0,24.0,19.0,26.0,18.0,GHECEGFGAGCBEEGBGHGBEBEAEFGFAFCFHGGGGEEECBFBDGGCGCEDGFBHBCBCBCAGABEGEAEABFFFBFBFHEGFGACAEFDBCBCAGAGAGFFCCBEHCCBCBDHCBEHCHCACEBFBCGDAHFCECEDACAEHHHHHDAFGHCHCEGEH,False +626,21.0,20.0,18.0,14.0,19.0,24.0,20.0,19.0,FGFGDBFGAAHHDABADDECCHFBGCEEHGHGHGAFHCHAHBCBFAFAFABBBABADDGEBBFCFCFCFCBCDCDHFAGGHGHGAGEHBFAFCHHEGEFBHDHAHAEDGAGAGEGCDEHECCCBBBAFFFEFDADBBEDEGCFBFCGAEEEEFEF,False +627,22.0,20.0,15.0,21.0,16.0,16.0,15.0,16.0,GBGEFDACFGFGHBHECCFAAAEEGBCHCBCFADHDHDBDBDFDADABAEDFBADACBCFCFEHGCEFEAEBHDHDFDEEBBHBGAGDGAEAEGGHAHDDDDFDGBBBAAAABDHGHFAFECCCECHBDBCBFEFGAGAHH,False +628,7.0,15.0,8.0,13.0,14.0,12.0,11.0,8.0,DEDBDHFHDCDCBBBCBDBFBFCGHGAGEFAFAEADBFBGBGHGDCFADBDFEFEDECEFHHCBEAGGGDEBECEABBGHGFDHEEFE,False +629,1.0,3.0,3.0,8.0,6.0,2.0,4.0,5.0,HEHDHDHDEFBGBGDDCDHBEDECGCEEFGAD,True +630,11.0,10.0,7.0,6.0,8.0,14.0,8.0,5.0,CAHAHABFCFCACFCAHAGDBCEGHFHEBDFAGAGABBBEBCFEFEFBFAFBDEDEGGDFDABFFEFGG,False +631,14.0,11.0,20.0,21.0,13.0,15.0,14.0,16.0,HCFAAHBFCFAFHFGDHFCFBBBEBEAEAEHEHGDDBHHHFHDCDEGECFHFDFDADACADHGEDADHDHDCDCGADDECEAGBBCECDGGCGCABAHFGCDCGFBHBDCDGAGCCCDCGEFEF,False +632,4.0,8.0,5.0,12.0,1.0,8.0,6.0,3.0,CAHAEDBCCFGDBDFFBFBHDDDDDADCGBGBCFAGDGFGFHDBDBF,True +633,3.0,4.0,7.0,2.0,2.0,6.0,5.0,5.0,CBCECACAFEFDAHBCGFGFBHCHDHCHGGFBFG,True +634,15.0,14.0,8.0,23.0,21.0,16.0,17.0,8.0,GDDDADADACBFGFGFAFACADAEEBEBFCGBFHFHGEDDDFCGABCBDHDHEEFHAHGEFDFEFBFAGAFEGDGDGBGDEDEBHBDCEEEEGEBCDDEAECDDDEGGGAFAEBFBGHEDAB,False +635,16.0,23.0,27.0,12.0,33.0,22.0,20.0,34.0,HEHACECAHFBGBEBHHHHFFCECEHEAEGDGDHAHBFFFFFFFGABCEFEBECECHABGCGFHEEEEEEGBCAHEHCHDFBGBCBCBHHGFBHDHCHEHEHCFCGCGEFHHHCDGDEDECBCAFEFAGHDCABHDAEACCHGHFBBHDEAGBGAFDDGCACEFEFEHEHEBEGCCEGBGBCAHBHB,False +636,18.0,21.0,19.0,22.0,14.0,15.0,21.0,26.0,GHABCDDDAGGFFEFDFHBACHDHDECGBFBFAAGECECDAFBHCDCEBGBAAAGHHEHEHEHEBAFDFCACECECEHHHCHDHAHAHCDBDGGGDHDBCCFCGHHHGDDDBEBFCFDGAFBFBDBDBGBGBABHHCHGHGDBEGAAHDCGAGBGF,False +637,7.0,11.0,15.0,9.0,7.0,9.0,10.0,13.0,DAFBFHGDGAGCDCDGHBCECFCGCDEDHDHBHBFBEGEHDADBBBBGFHHAECHGHGHBFCFAACCCFFHGACHCBCECE,False +638,23.0,18.0,27.0,21.0,18.0,14.0,17.0,30.0,DEDCHCBFEAEAEABAHGDGDADEBEHCFDGGCCCCDCBFGFCCHDHDHFBABDHEHAHFHCAFAEADHDHCHEDACCGCGCGCBAFHHHECDDDBGHHHCHBHAHECFBBGBDBFHAHGHCDGHGCGCBBBGBABFGCGAEEDFDAEHFHDHEEACAEFEACHCAAA,False +639,8.0,5.0,5.0,6.0,7.0,4.0,6.0,5.0,FGEBDBDBGHGDGCAHAHCDAGAFAFBEBEGEFDCHAEECEDACAH,False +640,25.0,30.0,19.0,18.0,18.0,25.0,21.0,28.0,DBGBFBFHFHCAFAFACGCHCHEHEGFGADHHFEAEGEGHGEAEBDADHBABDGGGGHBHDDGAEBDFCGCFFGACDHBHFHCHFAGHEDACAHBDDDAHHEBEBABACAGBDEDGHBHFHFCGCDFBFBFAHGCBDDCBAEAEFCABABACACEFHFBAEHEGBGBHBFFHBEBFBFBFHCBC,False +641,10.0,7.0,19.0,15.0,18.0,26.0,16.0,17.0,EBEBEADCFGFGAADCEFHCAEDEAEFBHEHDGDGDBHCGCFHFHCHFEFGFGCECFCGCEDAFEGDFCAEADCFEFHHHFDFGFGAGDGDFHHGACFBHDHCGFGFCHCHCHCDEECFFFFEBEBFD,False +642,17.0,19.0,31.0,20.0,20.0,27.0,31.0,22.0,EFGFHEBFAHAHFHGCFCFGFHFBFDHDAGAGBECCHCBGBFEABDEGEGFCBDDFEFADADBFEGEBBAEHEHAHAFGCGCGCBCBFGFCACHCECGCBCAGFHDBDCAFGCGCGCGCDDDCDGDGFBHGFFAHCFCFHECDGDBECCCDCEGEFBFEHHGAGCGDHAHGHEFDHAGBGBGHDECE,False +643,10.0,16.0,8.0,13.0,16.0,18.0,19.0,19.0,DBDFCEGABABHBFGAHEGFFDHCFCFBDHHACAFECHHHHGFGBEHEGEGEGFGBBDBFEFHFCEDECFAAGFGFEBAGHEHEHEGDBDFDFBEBDBDFDBGEHCAAGHGHGBGHGHD,False +644,23.0,23.0,24.0,17.0,10.0,17.0,18.0,14.0,BGGGGGEGBACCECHCHCACDBAEFEFHAHACFGGADDCDCDCDGHGCBHBAAFGFGFABBBBFBHGFAAADADCDEACDEACBHEEFCCHCHAFBCHGEGBFDFHEBBHBDBCHDBDBGFCFBDCGFGFACABBBAAAAAFDCDC,False +645,19.0,20.0,19.0,12.0,21.0,19.0,19.0,26.0,BCHEHEABABAHAHDHBEDEAEGECEBECAHDGCFEFCHHAHDHDHFBDACABGCEBHBCFHGCCCAEEDAACABBHGHGHFHBEBHDECEBDBCBFEFHHHGHGHGHFHFBDGEGACEFDFHFEFCGGGAEFDFGCGABFFCFCGBGAGFBAEA,False +646,24.0,19.0,25.0,16.0,26.0,22.0,27.0,28.0,DADGFHCDDBDHDHGGAEECHHHFCAGACFCFEDCCECEGFBFBCBGEHEACBCBGGHGAGFHCGCGEFEDAHAHFHEBBBHHAAEAECBGAAFBGBHBHAAFEEAECEGHGFCDCHHHHBDFGFGFGBEAFHFDAHAHCBCEHGHGFCDGDGCGEFABDBFBAAAHADEDEGCGHECEFEFECECG,False +647,19.0,19.0,11.0,23.0,12.0,13.0,15.0,22.0,FGFAADEGEAEADGDFHAHBHDGGGHDFBHBDDGDCDHBHBHEHECEDBDBEBHHDHEABCCGFAHGGEADAGFDAHEHDHDCDGDHHEHFFFGEGBDCACACDFDHBBBBDCGAAFAHABABACACFDFBBHB,False +648,14.0,18.0,21.0,17.0,4.0,13.0,14.0,14.0,HDCCBGAGBGFGFHCCACHCGCBCBEDEBCBDBHFCFCFGAGACBGFDFBHBADAGHCHBHFCACDFDBABAEGCHHDBDCFBECGCGBDAFFGHDBDBDADADACFDADCHHGH,False +649,18.0,10.0,20.0,21.0,15.0,23.0,20.0,19.0,CDCFFDAABAFGFDBHFHGADADAHGHGBDFCHHHCDCHAHADCDGDGDGCEFGFCECFCFCGCAAAAEAEDBDBFFHHHFECECGGEGAABHECFHDEDGHGAEADFFHGDGDGEEBDCFGEHFCGCECEDDFFFFBFBCBHHAG,False +650,2.0,8.0,12.0,4.0,7.0,2.0,3.0,2.0,BECADGCCCCCBCBCBDGGFECECDBDBHECEFABHBCEE,True +651,23.0,17.0,14.0,13.0,18.0,7.0,9.0,12.0,HGFCACACFCDEEAGBGBADADABCGDAEADGDBACFHBEDAABHBHGHCAAEBECECACEDECEGFGAAHABAEAHDHABABADEBCFCFBEEEHEBFBAEHEHDCDBGBHD,False +652,9.0,5.0,7.0,3.0,3.0,4.0,7.0,7.0,FHAHAGGGGHGCGCEHEAFAFCHDECHBABCFGBHBACDCDAABA,False +653,17.0,14.0,10.0,12.0,16.0,15.0,12.0,13.0,FFDCCCGHBHEFBAEAHDFFFHBBBBGAFABABAEADAEFCBDEEHFDACHCHDAFCFEDGBCBCBEBEGGGCHHDDAGAEAEDEDEBEHDHAHEFGFGFGHGAAEAFG,False +654,18.0,23.0,28.0,27.0,18.0,13.0,30.0,25.0,CGCBCACGBGHACACADFEBGBCAEHBDBCHAEDGDFDCCAEHDGDFDFAFBGBGEDCFBFBFDAHGCCCBGBHEHAHGGGCECEHEAGCGDGDHBBDGCECHAHDFDGEGAGDGEADHCACBGBCHAHAGBGHHCHCHGEBEAEDECHBGBGDGFGEGHCHBDDDCDHDFDHCFEHDBDBF,False +655,15.0,11.0,8.0,7.0,7.0,6.0,7.0,13.0,EFAFACBEEDCAHAHGEAEFFHBHBFBFHGAAHGHGAGDCBHHHABDBEBAGAGDDDADHBCBEACHCACACHB,False +656,23.0,17.0,14.0,15.0,23.0,23.0,21.0,14.0,DBBBEEGCGFABAGAHAHFDEEHECBHBFBEAEADGDACGFGFCFDFGFGFGBEBEDEHHCFEHAHAFAHEBABEDEFGFGBGAAECFCHCEAGDGDCBCAFHFDFDFCFEEEEECFDBGGGAAADBGBHDAGEEBHDAAAHFGCGFAFC,False +657,22.0,13.0,20.0,11.0,19.0,20.0,13.0,19.0,AAAEEECFGGCCCDBDAFHFAFCCBAAHBBBEBFBAGCGEGHCAEACDCEADBDEAFCDGECEGGAGABAHAEBHHHHHCFCFEHCHFHGHCHCFAFDFDFDHBEGEFFFFAEAECEDEDHFGABFEGCHCHAHABF,False +658,13.0,8.0,9.0,8.0,6.0,14.0,16.0,11.0,DFDAACADGHGFECCGBFFFHEAAFACAGFHCGCFAFDFBBHHFGAGABABAGEFEFGDEBFBDBGACHCHCHGDGHGHGEGDGH,False +659,24.0,22.0,11.0,20.0,12.0,19.0,20.0,10.0,ECECBBAAAFHDHDHCBGFGFACABAGGHADBEAFFDFDFDEGCGCBBBFAGABBEDGGAGFDAGHGDDAEABBGBHDGEBFBHDFGCBCBEBFDFDADADBBFEHEFEFDFHFEGDCDCDCGBGAAAAAGAFAHBGA,False +660,9.0,8.0,11.0,8.0,16.0,14.0,26.0,11.0,FEGEHCHBGBGEGHGHGEGHDEBHAFACGDGFGACHHGAFCGGFEHDFDEEGBGBGFGFGCCECFAFDFDHBGDAAHAGEGDGEGFGAGEBCCCCBEEGEFEF,False +661,21.0,16.0,26.0,12.0,16.0,24.0,13.0,16.0,AHBFGAHHBCBABABCCGBEFACECGHGFDAHHCCECFFFDFAHACACBCBGBDFEFEHEDACAEDEDEGEGDGBBBGCGAHACACEFAFDFAFBDACAFFHFCFCAGEGBFDFBFEGCFCBCFHACADDCHFHFCECEHHHCE,False +662,19.0,21.0,19.0,34.0,20.0,23.0,22.0,19.0,AFAFBGBGBABGDDADCFCECGGEAEACHDHDEFCFDFDECHHGDEDEGGFEBBBBBEFEDDFAHCBEDDBACDCDAHAHGHDCFCFDFEFEDHCHDDADBGCABDHEBBFBDCDHDEDEABDHEBFBCEAGGHFHEAGFGFGCGDGFGDGAGAGABFBFDDHDCDHHGHECDCFAF,False +663,30.0,32.0,21.0,26.0,25.0,15.0,23.0,18.0,GBDHGHGHGBGFGABAEEDBCBCAHAEEDFDADEGCCCGHDBBBEDHGGFCBBHEAACDBGAGBGFEAAAAAABADGGBGCDCFCFDFCBHAHBBBHBHGDBDEHBHBHBEAABABDDEAEDFDEBEBECEGEFAFCFCADEGCGBABABFBCEADAEGEGDCDGBFHAEAEFCDDHEHAHFDCDEDCAC,False +664,14.0,12.0,16.0,18.0,20.0,25.0,19.0,23.0,GFFDFGFDEAHBCEEHCFEEEABFGFGHGAGAGCGCFDBDBDEDEABABDBHFCFHDGAGEHEHEGDCDCFAAGAEEHFGFEDCHFHGGEHDDGBADDGHFHEHEHECFCFCDCAEFFFGFGCBHHCCFCFBFHFHEDADHHHHABB,False +665,1.0,1.0,5.0,0.0,2.0,0.0,2.0,0.0,CCCBGGAECEC,True +666,13.0,18.0,8.0,9.0,12.0,13.0,18.0,15.0,FADABCFAFAFGFGFBCBGGGFGDCDCABDHDAEHEDGDGEFFHCGEHHFHBGAGAHEGEGABFCGBGEEBEHFHBHBHBHBFBHCABBHGEEDCDBABABHGGAE,False +667,12.0,9.0,6.0,10.0,3.0,13.0,8.0,9.0,CBCHGHFADHGAGBCFDFAADDFCFHDAAAAAFCFEAAFADCDGDGHFHFHGBFBFBEBHGHGBBDFDEB,False +668,25.0,23.0,24.0,17.0,11.0,21.0,16.0,12.0,GDAFFFFHBBGCACGCECBHAEDBBFFFBCBCACACGBABEBEDDBFAHBHDAGAGBGBGAGBGAGEDBAFCCDCGAGHCDADACAEDFHACBEAACFDDBDBHBDBDFFFCFCFCFCAAAEDHFAFHCHCACHCGAGFFCEEBEBGDH,False +669,3.0,6.0,1.0,5.0,4.0,4.0,3.0,1.0,EABGBEBGBFBGDFDFDADEDBFHEAC,True +670,5.0,9.0,11.0,15.0,8.0,21.0,12.0,11.0,DFDCHCFFDHHAHACGGFBDBDCDCDAHEFFFHBDBDBEECFGDGHGBFCDADABHBHGGEGCCFFFFFDFHEBGCEFDFGFEFEHDGFGFC,False +671,9.0,14.0,11.0,13.0,12.0,14.0,11.0,23.0,HDHCHCFCFCHCFCDADADEHFHBAEGFGHCEDHFCCDEHAHFEBBBADCHHHHDHBHEDDDADHDBGBGBCBFHEBEFGBGHGFFHAHGHBAFAGBEFEBEHEGFG,False +672,3.0,4.0,0.0,0.0,2.0,6.0,4.0,2.0,HFHFAAGEGFGFABBFGFBEB,True +673,17.0,21.0,20.0,5.0,12.0,13.0,17.0,15.0,BCBDBECHCAAADCGGGGFBABABEBCBCACAGHBHDHBFEEEEAABCBCBAAHBGGCGBGHGFGAGFFCHGHGHBABFBFHCHADDFCCCECECHHEAFBFBCHHBCEGGCFAEAEGFF,False +674,14.0,34.0,17.0,24.0,19.0,23.0,30.0,24.0,BBGEGHHHEHEFABDCHCFBDAGBBBBDBFCFCFAHHEHAFGHGEGEDBDBDHCFCHCEDEDEDGCGCDDDGDGAGAGEGBHHCHADFDBBBCDDACGHGEGEHBGBGHFEFGFBBDBHBFBDGGCGCDFGCBBBDADGHFCFADGEHFCFAFGBHFHBGEAEBBBAFGGDGFEFBBHEHEBABF,False +675,22.0,22.0,20.0,24.0,22.0,17.0,36.0,34.0,CHGHGHAHAHCECDBGCADHEEGECDGBFCCHCHFGFGBBHFHFHEGFGAGCGCGDGDCBFBFEFEHEDECCHBGBDADHFHEBDBGFGBAHGHGEACGGAEAHGBDCDGDHFHBHCECBDHGGGGHBBDFDFHAAAAAHADADHGHEHAGFGDGAEDGDEEBHACFGHBHBHCGGGCAHEEAEHEFDDDGDBBBAE,False +676,5.0,3.0,7.0,7.0,6.0,1.0,5.0,6.0,EHCHEBAGEGDGDCCCCABHEGBAEDEDCDFDADAHHCHG,False +677,14.0,12.0,18.0,20.0,14.0,12.0,11.0,15.0,CCADHGFACAHGHDDDDDGFGHBADGBEBCCDDDADADABBHCFCFHBHGAGEEEEEEEGEFHCDFAFCCADBDCDCDCBBBBCHCBDAGAEHDHAHAEEHEHFFCGCDFGECFFH,False +678,20.0,18.0,16.0,16.0,18.0,22.0,18.0,25.0,DFFHFHFGFBADAGHCBCAGBCBFGFACBEFEGABBBEGHHFHFDFHEEGEBECFCEBEGGADEDEAEACHCHABEHAHAFAHAHAFBFAECECHCHGHAHBHCHFHGDCHGHEBDBDGCADEDGGFBFGDBDCFFEHDFDFDGDHCHBGAAA,False +679,13.0,13.0,11.0,11.0,12.0,13.0,13.0,10.0,DADAHACGEBDGEGEDEAACHFGEGEGFGFCFAFEBCBFEFHCCFCHCHEHAFFDBBBHGCEBGBGAAHFHGHBFDEGAGBBBBDDADADEDACFC,False +680,21.0,9.0,11.0,23.0,10.0,11.0,13.0,22.0,BHEFDAEAEGGAGBCHCBAAHAFDFGGGGBHADEDACFCFAEABHBHBAAADFFACDDDHDHCBCFHDHCHGDAHAHDDDCDADEHFFAFDEHHDHECDADAGAGBHHGHEHEHCDGDGD,False +681,29.0,26.0,19.0,24.0,29.0,20.0,27.0,23.0,AAHAECBCBAADACAFFGCEADCBGHGFEFEAEDEDBDHDEBHDHAACAHAEBCBDFFHFBFBFBFGFBEAHBCAEAGAGBEEEEEEEEDCABFGFBDHFAFAGBGHGCGEGDADHDFGBCBHBHACEBDADEDEDGGGGGGGBHBHDHCFGBBEHCCAHHFABDCGGECFBAHGDGDCEAEHECEGHDFDEDGAHA,False +682,12.0,18.0,15.0,23.0,25.0,24.0,20.0,8.0,DADHGFBFDADAEECECBFDHDBCBABAHFFFFEFEFBFBFBEDFDEAFCCHEBBGECCCCFAGBBDBGCEEDHGGEGEAEAEFDDDGDAFEGCGCGCFEDDGDFHEDGGGGGEBEDFDEDHBEBDCCEFFFEFEBABFGAGHGD,False +683,10.0,19.0,7.0,19.0,5.0,6.0,8.0,11.0,CHCGBDFEGADBBBBBEGHAFAHBGFACAGAHDBDBDADHDGDBDCCCEDDHDADADCDBBBHBFBDBDFDADEHHHBHGGEFBB,True +684,10.0,3.0,3.0,5.0,2.0,4.0,6.0,12.0,DBCHHBHEDEGAGAHFGGHFAAAGAGADBCHAHAFDFDACHHHHH,True +685,10.0,19.0,16.0,24.0,9.0,16.0,18.0,17.0,DGDFEBDHDADCDBDHFHFHAGCHCHAGEEBGBGBAFDHCBADCDHAHEEABDDFDFABBCDDADCDFDFBBGBGHECCGCGDECGDBFGGEGECHCGFFBFBDGFHBHBHBCGCGCGBDDDFHFHFHA,False +686,11.0,7.0,14.0,17.0,14.0,20.0,12.0,14.0,HDHABCEFFBEHCGCACACBHBGEGEFFFBGCECDCDEHEDEGFGFDDDDGDGAHDHDADADFFFAHAEDHFBADEDBCCGHAEEECFFEFCFHFGCGAHDFGFHFCFH,False +687,19.0,24.0,19.0,21.0,13.0,20.0,17.0,22.0,GBGCDCDHFCAHAHBFFDCAGBFBABCFFBFACBGHGHBFFGHDDADHFHFHBGGHGAFDFCGAGEDEGEADDFCBABFBABAHEDEGFGFCBCFDDADACECEBEBCHCACFEGCHBBBDDDGHHDHAHAFABDHEHEHEGEDBABCBDBHCHC,False +688,11.0,6.0,12.0,7.0,7.0,10.0,7.0,5.0,CCBGGGGFABECFADHEACFCFGFGEDFCFAFBHBCBHBDCCHCAAAAAEDDDDAFCFCEGEAEH,False +689,1.0,5.0,2.0,2.0,0.0,1.0,2.0,2.0,DHDGFGCBBBBBCHA,True +690,15.0,19.0,20.0,21.0,26.0,23.0,15.0,18.0,GBGBGEFEGECEDHDHDHDHDCGAEACGCFBFECCACGCDEDFDHDFBBBEBDHGHDCBAAAFBHADFBFHFHFHFEDDADEDEFCBBAEEGEACCHCEGACEDECECFFFFHAHEGEBABEDFBHEDEAEADFDCHFHFCGEBHCFFFGBBECGBG,False +691,16.0,20.0,16.0,13.0,21.0,17.0,19.0,17.0,EEBEDECEAEBBBBEHFBFBFDCDCBCBCAFGHGCECGGDHAHCDCFCEHDHDBBFHFGEECBGBFHDHGHEBEBEAEFBAAAAEAGGGFEFCFBABDFGFDFHAEEGHHHGDFHFGCGCGDAAACADEGBBCAHGEGH,False +692,15.0,18.0,25.0,15.0,20.0,16.0,23.0,15.0,DCAGACABGEGHGBBCAEGHHDAAAFGCBCBCGGDGCGCHCDCDAFCFGHGCGCEEEHBGGECACADEDFDFGFDBBFBCDCFCDCEEHEHFDBDBGEGFFBFBFEECHGHBAGABABEHEHGCEHBFDCCGDHEHEGBFAFAECEC,False +693,18.0,15.0,17.0,18.0,19.0,18.0,17.0,13.0,DAEAFACADHDHCFCBBBDFDEGEGEFDGBEFEBGHGHEHGGAFAFAGAEDEBHDADAEAEDEAHGHAHCECEHFHBGFAEAFBCGFDFGCACADFCGCBCBDAHFBCDEBCFCFGECDBDBGBGECECFDDHFG,False +694,7.0,11.0,9.0,10.0,9.0,4.0,5.0,10.0,CDDDBBCGFGDHDHEHBHEHEBEBEAEAFHDEGEDHBAAFHCBFEGCBCBCBAAHACCCGBHDDD,False +695,9.0,7.0,7.0,14.0,15.0,8.0,16.0,16.0,DFDCDCDEAHDDDBHHFHFCDCHCFBAEEDGAEAGGFGHAEECHGHGHEEGDGFEFEDEGBGEDDBHBHGEGFAHAEAHAHGBGHGHGDECB,False +696,24.0,23.0,24.0,22.0,20.0,19.0,26.0,26.0,ADGDAEBHCGCHCEADABGBGBFEEGFAFAFBFGDGDHHACDCHFACHCGGHGHDHCBGDHBACHBHGHGAAEBFAHGGDGHGFGDCDCGCDCAEGGGEEEEEHDFDAAAHADAFADEBBBHEHECACBEEEBABFCFCFCECFCHBHBAGABHHFHBHFCDEBCDGDFDFDCBFBCBEAGDGH,False +697,19.0,24.0,22.0,23.0,29.0,24.0,25.0,34.0,FCFEAEAHCGEDABFEFDHCHCGCGCFHABDGEGFGFGBHBCAEEHGBCBCBCGHDHFHABGHDHCCCAADDFDHDCDHFBEHEHEGFBBHHHADEEEBEBFACHHHHGHGABBBBEDCBBBEDEDFFFFFFHCHDAEFEGDGHFBDGEHHGFBDADECEDEDGFBFEGCGHHCHCHGHEFEAAGAGEGDGCAHAEAEBD,False +698,13.0,19.0,14.0,18.0,18.0,16.0,11.0,16.0,BDBFFDFDFGGHAHBHBHBHFGAGAHDHBEBDBHBFBFHCBEGEGEDCCCCBGHECDCACDBFCEDBDFDFDHDFEFHFHEHEFEBABDEHBCDDHAAADEBAGAEACGEAEFBCEGEDFCCAGE,False +699,20.0,17.0,18.0,13.0,20.0,22.0,16.0,23.0,ADHHHHFDFBFAGADBEFFFEFEGCFBDHCAEABAEAEBHFECCFDFHHHHHFHCHCHEHEAEBGHACABFCFGAGDFDFCBHGCFCBCHDEDHGHAFDFAGECECEFAGCDEGEHEAABCBGBGBGBABGEAHGEAFHFGCECADBDB,False +700,7.0,10.0,13.0,7.0,8.0,14.0,8.0,3.0,FAAEFBFCFBFBEDGHCCCCCEDEDFHECDBDGFGFADGBEFCFCGAAAHEDECACFBFBGGGFCFCBBB,False +701,16.0,27.0,21.0,29.0,23.0,22.0,14.0,18.0,ABAEADACBDBFAFDCGBDEDBBFBFADHHAABHDGABACDBDEAFCHCECHDDACAFDFDFEAEDHDFBFBFCEEBECDCDHABFBGEGFHFHGBDEDEDEDCDHDHFAGDGHGHGHBCBCBFHCEBEHCCDCBFBFBECFDGGGFCECEDHBGBCFEEDGBFBEHEDE,False +702,22.0,31.0,14.0,20.0,15.0,20.0,18.0,12.0,GHADBDAFCHAEBDBDBDFDEAAABADEDCAABBEGEGFGEGFDFBFBAEGBBCBCBEGDCDAHCHBADADGFBFBHBGBDCFGDGHCDCFCBEAGFGFHFEBECAFBFBHBHBFBEGEGEBEDAHABADABBGBCAAGDFBAGHCCFDFHF,False +703,21.0,26.0,13.0,16.0,14.0,14.0,14.0,17.0,CHABCBFGFAABAGAHAHAHACBDFHAHEHGCACDBEHDGBHCECEHFAACABHBABABECGBGAGEFCGDEFHBBFAFHFHAHEBEFEGBGBEBEDDDDDDDAHHCBCDDGEADABGBDBFGFBFBFBGEDCBB,False +704,1.0,0.0,1.0,1.0,3.0,1.0,3.0,0.0,DEECEGFGAG,True +705,7.0,6.0,9.0,6.0,4.0,3.0,8.0,5.0,AGABCBCEHFACGFHHCHEACADDDDGBGBGBCEFHBDEDACGCGCGA,False +706,6.0,5.0,9.0,7.0,4.0,10.0,8.0,4.0,BGHGEDCHCHCGCFFGDGDGCBCBAADFFAFEFGAGADFHBAFCBCEDEFCFD,False +707,10.0,10.0,4.0,9.0,12.0,8.0,9.0,7.0,EECFAEAHAHAEAEBEHFDFDAGCDHBHGGEGEGFDFDEBADDCHFDDBFGEGBGBEBEAHAGBFBABC,False +708,11.0,14.0,22.0,17.0,26.0,26.0,22.0,25.0,ADBFFHCHCHCDGFCFBHBHBAGACHDFEFHCBGECDDGEHEHDHEGEGEGECBHAECDHDCDEEFHFDFDABHGDEHEGDHDGFCCCHCHDHDHBAEEGEHEHGGGBBFEFEDEFHFCFAEHECGCAFFFCFBBCAFBCHEEGEGFFECGCGFGFGFAFAGB,False +709,20.0,25.0,16.0,17.0,13.0,14.0,18.0,22.0,CDEHBHBHAHBHBGDGEGBACAHAHGBGBGBAAAGFDEEBGBABABFGACACHGHDFDADHEFDHHECFDACABGHFHDDDAEAEDGDCDCFCBCFHBCBEBEBEBFCGCHFEGGDDBBBCEHGDACABGHGAFHHHBFAFCFHB,False +710,30.0,23.0,16.0,22.0,21.0,35.0,15.0,23.0,FAFAFAFEFEHAHAEBEFDFDBDHFCEAHHHHBEFDADHEHBCCCADEHFHFHFCGGDECGCBDBGAFAFBCDAHADBECEFHCBCBAAAFAGBFADDFDFHBGAAEABFDEDFHAGAHAGAGEGHFEFCABAFCBEBEBHFDDDFDADEEEFBFDACEGFBDBHBHBFGFBFCFGGHAHAFGFC,False +711,6.0,6.0,12.0,7.0,12.0,9.0,12.0,10.0,HGEDHDGCGCGBHBHGCFAGABCBGGEBCHCHFGDEEEHEHAHFHCGDFEFAFAFDECECDCFABCGEGFCEDE,False +712,23.0,31.0,32.0,27.0,25.0,14.0,31.0,14.0,CGABCFCEHDFDHEHBDBDECCFBDGHGAGBGCHCBAEHEHDFDBDCEFGCGCFBAGGGEFEABFBGEAAAAHAGACACECACBGDGDBHBCFGHGBCAAAFBDDDDDDFGFCECBBEEGDADCBEAEAFDGEGCCBCBCBDGCECGCGCGCECECBFBDBABDBDHDCEHEBECGAABDBGGGDEEGEBBAHGGDH,False +713,4.0,5.0,5.0,9.0,4.0,5.0,6.0,6.0,BEFEACAHDHDHGHBDCHCDEDFDGDBEFGDGDFAFBBGACHCG,False +714,18.0,19.0,22.0,14.0,25.0,27.0,18.0,19.0,GEHFCECFCAEFBFAHBCCEBFFEFECDADEDEAEFEBECECGHGAAADAGHBFGFAFHDEABBDGDEHEFEFDBCHEGCCEFBFEHHHHGHGCAFAFHFHFGEHEHCGDFEAEAGFFBADAFFCFABGBABFBCBGBGCDCDHFHCECECDHDBGBCBCGG,False +715,17.0,8.0,11.0,12.0,13.0,12.0,12.0,14.0,BAGDHBHDHABAEGHFDADFECDCGCGADHDHDHABCBHGAAFBFBEHEAFCFAGHEBCDFDFDCHCHCADAEHEGEAEGCGCFEHAGGFAFEFEAEAG,False +716,16.0,17.0,24.0,24.0,21.0,17.0,16.0,24.0,FCBCBHBCBCECDCDAFFHHHCHDBEFABAEDEDEDECFDGGGAEFEFEHCADAFACEEECFCGAEDEDGHGDGAGFBHDHFHCCGEGBDHGEBHHHEHACAEGFDFDHCECBADECHHHBBBFBFBDADCCFCDCBCDEDHHCGDDAAAHBHGHGDGF,False +717,30.0,23.0,30.0,24.0,12.0,21.0,21.0,16.0,ECEDACAHEHCACECDCGCBHAGDFACBCBAFGFGBACCCCACFGEGFHHAHABGBEFFBFDFCGABCDCBBBBBAADADGDFDFHFDCDCHFBFAAGAGAGAGFCCCHABGDGDBDCDEBHDCDCDBGFFHHGBEAAHAHDFDEDAHAGDCDBHAFGGGBABDFCACACBCFEEAE,False +718,8.0,9.0,11.0,13.0,10.0,18.0,7.0,15.0,BHBGDHDHDEAEFFAGAGABHFFFADHDHDGAFCDCAHBDECFAHDHCCBGHFCECEHEFDBDCDGEGDBHBECFCFCFHBEFFFFFHFHE,False +719,12.0,23.0,32.0,23.0,25.0,25.0,24.0,32.0,ACHDECHBHFHGHGHDADAGHCCEBEBCCGHFFGFCBEGCCDDDBGFDHDHDHGFGBCFCGCDCDCDCFGEDBDBEGGCFEFEHEBEHECBFDCDGBGEGBGEGCFEEECGFGADCFEAEADBBCECEHEBEDFHFCFCAABGHHHHHFAFABCCHCFCAHEHFBFBFHCGFBDGDEBHBHCECGDBAFHHHHHDH,False +720,9.0,6.0,1.0,2.0,6.0,3.0,3.0,2.0,AAABABDBGEHAGABCBGFHEAEDEAEFEFBA,True +721,4.0,4.0,5.0,4.0,1.0,4.0,3.0,0.0,BGBCACGCDDFDFABACECBFAFDG,True +722,16.0,8.0,13.0,19.0,18.0,17.0,9.0,17.0,DFEFCHCGADHDEDAHEDEBFHFEFEAEDEDHAHADCBAFACAHEHDCGCGCDCDHDFECEBEDEDEFGGABFBFGCACFDFAFBDGFHCADHEHEGDAEAHHHBHFHFADCFEBGA,False +723,20.0,21.0,15.0,7.0,15.0,20.0,22.0,15.0,AFCDCFCFGFGAGBCACBHAAFGFBBEEAEGHDEDBHBHEHBCGEGFACEGHGHGCGEGECAFFGEGEGEGBBFAFDCBCFCFADADBHEAEHGBGHGBAFAHCBADFBHBCBFAFHBABABAFABHFGFGEHCG,False +724,22.0,23.0,14.0,13.0,20.0,26.0,11.0,21.0,DEBABADADEGBGBEBHBCCAAEAFFDAAAAFEFAFGFCFCBHBCFFFCFBFDFEHHDHCHCFDEDHBHBGAACEFAHHFABAEEEEGBCHCECACGDHAFDFHFHFEFHAGGGFCHBBDBHBEBFBFHHEHBBBABEEFGFEDGDAHAE,False +725,21.0,25.0,25.0,29.0,21.0,32.0,25.0,20.0,FGGGCGEGDFAHHHCCCGAEABFBEBDBDHDCDEDAFGDGAEFCFCEAEADABCBGGGGGCDCDCFFFEHACBCBCGCFCFDBDFCFAHBDDFDFBEHEADCDFHEHFFEGGDGFHEGEBBBDHEAEAGAGAHBHAAGAHAHDDCBCFFFHFEDGDHDBFBEAHBFBEDFCHGFGDCFEGCHCFBFDEDFDABBFBCB,False +726,16.0,20.0,16.0,17.0,10.0,18.0,13.0,17.0,BBBBGCACACBFBABFBCDHGBCHCBADABFCFCFGAHEGBGEEEFDGDFAGAGCBCEFHFHGHFHAHFDFCHAHAGEBDBDGDCDCHFHBDDADCBFADEEEHHDGFGFHADEDHFHCBCBABADF,False +727,10.0,29.0,22.0,26.0,22.0,17.0,21.0,19.0,BCBCBCBDAFHFCECDCDCBHECFCGAGDGBHFDGDGBGBEDEDEDBCBAFAGHBHDHAADBDCGFGHDBDEGEFBBBCBEBEHECDHEGDADCDHDBBGCEHFGCAEAEBEBFBHADCECFCFEDGHGHBHFHGHBCFGBCEFDHGBGFGEBEHEFFDDBDECGD,False +728,11.0,13.0,13.0,11.0,13.0,20.0,15.0,18.0,EFFFEBCDCHCAAAADFHFHGAFDFHFCFBEBGCGAFBCACAHAHEDBBGEDEDCDGBGFGFGCHCFFDHEBBCGGGGGDFHAHDHBFFCHHDHEHEFBHBHECAGEGEFEFBH,False +729,26.0,25.0,13.0,24.0,26.0,16.0,21.0,19.0,DBDFABGGFGHEHAAAAABFBFBGBDBABAGEGCGFEEGEBEDHAEDCHABCDEFAFAGDHHAHADAFAFGBGAGHBDGCHHHBFFEAEDBDBEHDBBEDDHDHDCBCBEHCACDHFCGAGEGDDBEBEBEAGAEADABAFFFFEHGCGCEEEEBEGDHDGECEABHDCD,False +730,16.0,17.0,13.0,13.0,6.0,15.0,8.0,16.0,CCHDADACCDBABEBHDFBEAGBGFCECHBAAEAEDEGCHCHAFBHGHDBDADAFBDBGBHCHCAGAGHHCDCFFDFBFBADFBFBFHAAADBFCFGFBFHHHH,False +731,16.0,23.0,24.0,23.0,24.0,17.0,32.0,25.0,FFFFFFFDDEDGGHGHGHGFDHBCACGEGEBEBECFFBFBDECCDEHCFGEACHDHDHCFDHEGABHEGBGEAEHBAGCGHGHEEEDEDHFCGDGBAHAGAGDGBACCEAGAGAGAHFBCHCGCDCHCHBDBGBEBGCDFDBCBHEHEHGCGHBCBCGCAADDDGHGBDEDEGBBDFEAEGBCH,False +732,2.0,3.0,2.0,0.0,1.0,3.0,2.0,1.0,FCFGFHCBGBAEAB,True +733,6.0,2.0,3.0,2.0,1.0,4.0,1.0,4.0,BFFCHCHCHAAFADBGFDAHAEA,True +734,5.0,4.0,6.0,8.0,4.0,8.0,3.0,7.0,DGHGDEDEFAFBFBDDEAADFDHCHFAFBDGHHHHCCCCFCFBEA,False +735,11.0,7.0,8.0,6.0,4.0,4.0,8.0,5.0,CHCACAGAEDFDCBHDHFHBCDDHAFGGGCACAGAGBBBGBEBDFAAGAECEA,False +736,20.0,16.0,16.0,26.0,10.0,23.0,15.0,12.0,BDBHCCEBDBACHCDFGFCADHDFDHAECDAGAGCFEFCFEDDDDDDDCFHHADFDABEGGGAGAGADABAFCFAFDBEBEGACADDDHAHBECHDGBGBDDEGEGDBFCFHBADGHGHFFFBFAFAFCFCFBFCFBA,False +737,23.0,11.0,24.0,14.0,10.0,9.0,22.0,11.0,FHADCDEAAAABDBHAFADADFCGGGHGAEAHCGDDCDCDHAHCGGGGCACFCBCBCGCHAAFAHEBADAECGCGCGDGECEDGBFCDBAGACFHAEGCGEGBGCECHGGFHFABABABCCDCE,True +738,26.0,23.0,28.0,29.0,22.0,16.0,18.0,26.0,EHDFFHFHEAFFBBEHDBBBDBDCGEGEGCBCDGHAHDEDEDFAFGCCCACBDAGAEFHFHADAFHCDCDBDHAAAAAHCHCHFHFEFHCHFBAEDHCBCBCBEBDADGDAHAGACACBHEDDDEHCHBDECCGBGBHDCDHDBGCCBGDGCHHGFBAEGEAFACACBCEEEEHEGCGAADAEBGDDD,False +739,8.0,2.0,10.0,6.0,9.0,6.0,10.0,6.0,CGBDCDCHHEEAEACAEEGFHFDDDDFGFEAHCCCCCBFGAGAGEFAGAGHCEGEGH,False +740,11.0,8.0,17.0,13.0,9.0,9.0,18.0,8.0,BGAGBECGDGHFHBHBGDGDGCCCCCCFCFDFAFHBDADGDGBBCACAFEDGDHCECHAEEEBDCGGAGFGCGDAAEDEACHEHCCFGAGDGF,False +741,4.0,2.0,8.0,8.0,5.0,1.0,3.0,4.0,CECEAEHCCADDHDHGGEBHBECFCDDDDCDAGAC,True +742,2.0,9.0,1.0,2.0,5.0,5.0,1.0,4.0,CBHEDBAFFDBABEBEBHFHBHBFBGEFE,True +743,18.0,19.0,21.0,21.0,22.0,11.0,26.0,21.0,EAACDDDHDGEGBHHHHEBEBABHEHBFGCGDGEGCDCDGGCGHFFDFBBGACADADHHADCDGDGBCCCBEDECAGHGHBFCFEDEDEGGCBEFEBEBEHADBHBGGGADADFGFDAEAGBBHGDBHGHCHCACACAEFEGHCECEAFHCHBGEGECA,False +744,31.0,23.0,20.0,24.0,21.0,22.0,28.0,21.0,DADEBEBEDADABCBFGGGGGHGHAFFGBGBGCGDGFGHBCCFDEHEADABAGGBGFCFCAGAHHEDBHBHFFEHAGAGBCDFAEBHDDDDEHHACFBHDGDGACFFBDBAAADAHAHCHCEGAHAGEEEEEBHFFGADABABEBEBCDCBHFHFAADFCGCGBAADDDFCCCHFEFECEAGACAGDGFE,False +745,5.0,11.0,15.0,7.0,10.0,9.0,7.0,16.0,EFHFBCACFCEHBCBABABCECFHHHHFEFHCHCFCBHHGGEGEDDDHAFGEGCBDDDHEEAFBBCHCHEHGHBCBCDCG,False +746,1.0,0.0,6.0,5.0,2.0,2.0,2.0,0.0,GDCDCACECEDFDGCCFD,True +747,14.0,8.0,8.0,12.0,14.0,15.0,12.0,12.0,HCHDFEEGCBCDCAEEEBEFEFCABABFBFDEGFAHEHAHCHGGFCFDEDAHCHDFDGDGABHEAAFAFHFEEGAGDDFBHBHGDGEGAGAFAFD,False +748,23.0,22.0,15.0,27.0,27.0,24.0,31.0,19.0,CFEFAHGBGDEAEBEAEBHBDDGBFAHCGFHFHGEGFAFADBEFHBEBCCFCGEGADBBGGCGBGHHBEGEGABBEEEAHAGEGFGAGFCCBFAGBGFGFGFADDBDBGBFEFGFAAAABHCDDDDDDFDFHFHBGDEAEDDDEDEGEDEDECHDHCFAGAHAEAGADFGHEHDHCCGEGEDBDFCHC,False +749,18.0,23.0,17.0,19.0,17.0,23.0,21.0,21.0,EAADEDBDBFBEECFCDEGFDFHBDAFFBCCCGCHCHAFAFAGGHGECECEBEGAGDGDHEFEHCBAADAFBFBHBABGBGCFCDHFBDEDECFGFBCHHDBBCHDGDFFBFBGDGBHHAHABADADEEGHGHBHFFFFEFGCGCDEHHGHGAAAGBBH,False +750,26.0,15.0,24.0,31.0,22.0,18.0,27.0,36.0,HFCEEEDBCEHFDCDCDGDAHEDGBCCDCGHDEECFHFAFADHFCGEEAEHEHECGABAHFBFBFDACBDBDCDHDHGFBFACAHAHABAHHHCDGHGHGHAABFHFGGHADDDDDADCDEDGDEAGGGGAGBGACCHBHBFDDEEHEDDHCHCHCHGFGAHHHBHFGCGHEEDEDFBAGHGHCECGCAHAGFEADAGA,False +751,2.0,2.0,6.0,6.0,5.0,4.0,2.0,6.0,DCHAHGHCHCEBEGDFCHCDCFEFEDEFHADBD,True +752,12.0,16.0,4.0,9.0,13.0,13.0,11.0,4.0,EBEBDBDBFAHAHADAGBCBFHEEAFAEEBEFGFEFAAAGGGBAFCFCFDGEBBBBBBGAFEEDDDGAGFGCEFEGBDDFHB,False +753,20.0,22.0,13.0,25.0,23.0,25.0,27.0,11.0,DBDAFFDEDEDEFEFDBCFFHDDEEEBEFDFEFEGBGCHCEBEHEHAABAGGGDEAFDFBGGGDFAFAFACHEEBHACBFECCGGGGGGFDFAFCGEGEFHBDBACAHAEFDBDFGABFBEGCGCDHDHDGDBDBDGCFBGCAHGDGBBFAFABEGEGABADADGB,False +754,13.0,24.0,24.0,21.0,25.0,16.0,20.0,11.0,BHBDGCGFGFGFGHGHBFGCEEFEFBAHEHEHEBCDEDEDBBCBCEFECGCDBACAGDGDBBHCCGDAAEAHCEFECABABDGDGCBEDHGFEDEDBGGCACDDBEBCBDFGGGEEHECECEFDFDBBBDCHAFDCBCBCGCFFACAEAEDBFE,False +755,21.0,23.0,12.0,20.0,22.0,23.0,13.0,24.0,FBFBCBFBFECEBHBHDHBBBFBACGBGBDAGFDACHHGCGHFDBHEEEFEAEBEBFGAGAGEDDFDFEFBCAFDFEAEAEDFDBDHECDCFCEAHAFEEHAHGHGHCBDAEGHBDDDBDEHGBAHAFCHGBFHFHEHEADHFHFHFDEBCAAAAHAD,False +756,9.0,16.0,8.0,17.0,8.0,7.0,7.0,4.0,EFEFGFGCCBABHBDDDDGDABBGBFBFEACDBDEDHCGEGBCBCBFDDDEAFABADAHEBADHDCCEDGDBBBAD,False +757,15.0,20.0,18.0,27.0,18.0,16.0,16.0,19.0,GHFBGBCEEAHDBDAHAHEBFFDDDDBFBEEAGBDHDBEGHAHADDEDCFCFBHAHBHDDGDGDECECGHGFGDADEFCFCFDADBGEEBCDEDGABABHBHBHCDCECECEGACCEABFBFBCCHABGHFHFACDDDDDGHECGFGFH,False +758,24.0,10.0,20.0,10.0,13.0,18.0,25.0,18.0,HEHAHAFAHCGCGCHEBGCGHGHGFGCGEABGHGFGHCHEAACABAHACFEAGCECBGGGGGACDFHFAFDFDFDFBEEAEAECFCAADAGFCHHECFHGAGHGEAHFGCCDBDBGACAGADABBDBDCFAFHGEFCF,False +759,5.0,2.0,3.0,3.0,1.0,2.0,7.0,3.0,CFAGGHGHGHBDGDGACEDACAGABF,True +760,23.0,15.0,19.0,10.0,31.0,25.0,21.0,16.0,FGFGHGDGBHACAFAFEFEGEBFGFGFECEDBFEFEHHCFAEACFBBBAFEDCGCEAECFCBBHEGEDEAEFBFGFGADCCCBHAAEEBABAHAHACECFHFEDEABFEDEAEBECACECGFGFEAGAFEFACHGDGAEAEGHHHHGDCBEDEHFHGGCG,False +761,4.0,5.0,6.0,6.0,5.0,5.0,6.0,6.0,EFBFBFGDHCHFEFGGBDAGACHCHDHBAAECCBCDEDEDGHG,False +762,5.0,7.0,14.0,5.0,9.0,9.0,6.0,9.0,EGEFHBHFGFHCEDEBEFACAEAECHCHCHCHBGCFDFCCACBCDHDFGABHBCECDGGEFCFB,False +763,7.0,10.0,9.0,14.0,6.0,13.0,15.0,4.0,FHBHAHAFAEDCDEAEHFDDGFBFBFDGGFGBGBCBFDGDBCGEGECAGAGDGDFDCDCDFGCGEBDGFBACFBFDCG,False +764,18.0,17.0,21.0,10.0,17.0,19.0,30.0,14.0,GFCBGAFBBEFFCGHGEADAHFHEAEAHAHFGGGEGECCFAGAGFFCACBFAFAFGGGAEHGHFHBHCACHFAFDEDHGEGDFBCGCAHGCEBEHCBGBDDCAGBDAGECECACBCBCGGGBBBBBECFCFEFHGDGDGDGEGEGC,False +765,16.0,9.0,24.0,14.0,21.0,12.0,17.0,12.0,FCCCCEGDGDFBEGCBCDDDDCHFGACDHECCCEEAHGHGCCCFEAAADAHGEBEFDDDCDCEAGCGDHEAEAGADAGEFCFCFGFGEAFHEECECEGHGBFCECEBFBCAEBGBGHAHAHAHBE,False +766,2.0,5.0,3.0,5.0,5.0,3.0,5.0,14.0,GCCBCDHEEEFHHEBEHGHBHDHDHAHFGAHDGDGHHHHBFB,True +767,25.0,19.0,25.0,19.0,30.0,21.0,34.0,24.0,AABAGCCCGCDFDAEECGCHBHGHGHDAGCGDFDCEGEBAGFEEEHHAGAGAGFECEHGCECEHFHABEEEBEFEBEFEBCGGGDGABEDEDADGFGFCHHHHDDFBFBAEAEAHGFCFAAAAABAFHECGCDCGFADDBHBGCEHFBBGDHFAFHBHCHFHAGGGGGGAGCGEDEBEDECHFHGBDEDBFGCCCCE,False +768,25.0,18.0,18.0,14.0,17.0,14.0,28.0,21.0,DBBECABABAFFCHGBFEAEHGGEEEHGHGAGADAHGCCFDFDGAFCECECDBBBFBDHHGHEHBHAHGCGFGHHCCFAEAECGAGFHHCEGGGCDCEHEHEDGDHDAGABACCBCBGFFBBHBABADAGGGGHGAGAGAECFBAGAFADAEHDD,False +769,1.0,3.0,1.0,7.0,6.0,6.0,6.0,3.0,EFGFHFCEBGHFBDEDEHEAFDDGDGDGDGBEF,True +770,10.0,20.0,19.0,21.0,15.0,21.0,16.0,16.0,CDHDGGGCGEGECDCDCDABFBDBFBFDFHFHDDBEAEHBGBGCDBGBCHHDGFGCHDHCGCAAHABAFHHBDEFEFCFDFCFCFAHEFBFBGHGDDDCBEGGFEBEAEBDBHCHAEFCDCBFEFEBHCGCBFDFDEA,False +771,4.0,6.0,5.0,4.0,2.0,2.0,2.0,5.0,DBACDGDBBHBHCFDECECACAHAHGBFBH,False +772,20.0,21.0,27.0,26.0,23.0,24.0,13.0,18.0,HHGDAACADHDEDCABDHDFCFDBCFCABDCCCCFFFDFBCBHBGEGHGADACFDGAADDDDDECEHEHDFEBEFCFHFAFCFCFAFCHHHCEBEBEGECECFCHEFDCGBAFADAEAEDEDEFEHEGDAAEBCAEABBFBFBEADGCHDBGBDCDFGGBCBCBEHGHCHBF,False +773,23.0,11.0,12.0,12.0,15.0,10.0,15.0,14.0,HHBEBEDEBGBDFCECGCGEGCHDHGHGBCHAGAGAFAFAHAEEEAEAGBGEGCGAACABBHDABFDFAHADGHFBCDDHAAEAEAEAEACDFDEAAAHFDCCGCHHGDBFF,False +774,17.0,24.0,28.0,15.0,15.0,16.0,18.0,18.0,EFEFEBGCDADCEHBHBHBFBECECBFBFCGCEDEDCCFCGCGFGFACCDFHAHGHBHCHEHECCCGGFCHCADBBBGHHEGCCCGCBHGEGBBBAADCDCDCDADADABFHFAGBDBAHGBBABFEFGBEAHBGCCHFHGDABACAFDEA,False +775,3.0,0.0,2.0,1.0,0.0,2.0,2.0,3.0,AGHGHFDFCHCAA,True +776,17.0,9.0,11.0,6.0,12.0,12.0,17.0,14.0,GCGDABAFGFGCCECFABAEAEBGADHHEHAAAEDEAEABDFCGBADAEHGHFFFGAGFCFDBHBFGHHCGAGHGEGHBHCECEAEAGFCFCBHGHGH,False +777,4.0,6.0,1.0,5.0,7.0,2.0,6.0,4.0,HEFEAEAEDBBGDCDHDFEBAAHEHEDGBBBGGGG,True +778,6.0,7.0,4.0,4.0,5.0,13.0,4.0,5.0,HEHEAFGFAFAFBGBAFFFDEDECBCFGDBEHFAFBFDFHFHGBACCB,False +779,9.0,7.0,5.0,6.0,9.0,8.0,7.0,9.0,DGBEBEDHAFAFHFHFCFCEDEGEDEDGHAFBHBAGAFBCBHFAGADAECCBGEGHHEHA,False +780,19.0,21.0,16.0,16.0,23.0,19.0,26.0,22.0,FFCAGEGEGAHBBEBEGCDFEFCFGHHDHDHDBEFFAGEGAGAGAHEHFAEDBACCCEDGBEACFCFEDEABABABFHFBGBGAGEHHACBCGCHCHGHEABACDBDHEGFGEADHFBDCDCEBBAGHGHEHEHGHDHDGDGFHABECEBDGGFGBGBEFFF,False +781,15.0,24.0,23.0,18.0,23.0,14.0,17.0,21.0,FEAGCCBABABAFAHCDGHFCAEGBGBGHHBBCBFBABAEDEDADHFECGDGAHEBEBECCGCHCHEBCFEDDDCGCGDGDHEFGGCHCBEFECAHDEDFDEHEGEFBBHGGCECECFBDBDBAHAHEHDHECFBFDCECABABHBGBCHFHDHE,False +782,14.0,24.0,23.0,18.0,18.0,17.0,19.0,17.0,GAECGCBBAGAGAGFEEDDFBEEEBBGGEECCCCBEGEGFGDGCHCHCHEADBDBHBHFGADBFGDHHGAGADDDDDCBCDHFBFHDAGFHFHFHCBCFEHHHBFCFHFCGCBCAGFEBDFCECHCACBDBCEAGDBDBEBEBEBABAFC,False +783,17.0,21.0,14.0,26.0,20.0,11.0,14.0,15.0,CHAHEHDHGCCADABAEDBDBFAEABGDDCGADADBBAFCEGDBEBDHGEGFHEHEHEFCFDGHADADBDBDCDCGBABDECEDEDFDCDCDADEDBDHGBGBECDHEHFFBAEAEBEBGHGEBCGGBEFHBHCFAFA,False +784,9.0,13.0,21.0,19.0,11.0,19.0,13.0,15.0,ADHDFGEBBCCDCDCFHAGDBCBCECEAGAHCDEAHBHEFEAHHGDCHCHDHDHFBEADFCGCHDHAFBGBGBEFDFGFECACFEFGFDCDEBGBGCFBFCDGDGCFDFHFHFCFCDCDB,False +785,3.0,4.0,10.0,4.0,5.0,8.0,5.0,7.0,FCFCGCGEAAGFCECECHFFDHCACGCGEBHFEFHBHDFDBDBHHC,False +786,13.0,15.0,20.0,21.0,12.0,14.0,14.0,18.0,BFDGDGDADECHCHCEDGDBDGHCHDGCABEEFEFGGDDBDHDHDGCCEBDFDFBHBHBHFHFAECEBAAAFAEAHBHGHDFEFBHBABECCCCCDEGHGBFFGHCDCBGDCCCFHDCACAFGHADA,False +787,12.0,21.0,22.0,19.0,22.0,24.0,29.0,14.0,CGCGEECEGGBEAGCFFFCDCEEACFBFBGBGDGDHDHCBCGADEHGHBFGFGFDFDBGEGEBFCFCFCFABDBCAFFGDGBFHCHEECDFDFCBEBFHGCGEGAGAFDFCEGEGEAAHHHBGCGCGAGDGDBDFGEDBDFDBCHADEEGEHEHABBFEHBCB,False +788,17.0,13.0,19.0,20.0,16.0,16.0,19.0,15.0,BDCEGHGDAFFHFHDADAHEEEECFCGDHBHGGGAGAEFGBCADGCCCCCCGCDCBEFEFDFECADABAFEBGBGAADGEGHADABHFHFCEDHDGGCDCDFDADGHCFBBCBCEHBHFHDEDEDEGHGAAAFBF,False +789,28.0,17.0,13.0,32.0,28.0,13.0,27.0,17.0,AEADADBGBAFAEADGBAAGDDEGEBEFCFCFHFHAEGEHDHAADEDHDCFCBAEGEGDGCGAGBGBGBFDDDEDGBGBGBDDGGADCDBGAEAGDBCADEDHBABAECHCECAFEHAFACDCDGEHEHFBEHDDDDFEAABDHGHGHDAGECEGEGDHEAEGEGEAFHDHDFAE,False +790,20.0,14.0,14.0,14.0,17.0,15.0,16.0,18.0,FCFDDDHCHCEGHADCBGFEFCFEEEEBEADABHBDEFCABABAGAGEHHBHBDAECGDEAAAFAEADBHCGGBGBGBEFEFEFABAGFHHGACDBDHHGFDACEHDHGHFCFDHCHCHCEFAGAGAG,False +791,18.0,17.0,18.0,19.0,20.0,20.0,6.0,18.0,FHFHFDEAADAFBBACGHDCDFAGGFEFADEDBFBFECEAFAFACCCEFHBHFHBBACHFDGDCDHDHGBAHCDCBHBEEEEAECBABCBCEDHDFDEDEDEAEADACAHFHFHEDCCABEHEBEHCFBFGFBDHC,False +792,14.0,17.0,13.0,12.0,11.0,16.0,16.0,11.0,DDBDBDAFBDBFAFAGBDEGCCECHCHCGFABGBCFEFECHFBABAEECBDHDGDGHGHGFCFHEAEGDHBCBEFHBGAGACAHAFGFGFDEABFBABGFGFGBHCAEDC,False +793,9.0,19.0,17.0,11.0,13.0,16.0,16.0,13.0,DCGHBFFCGEEBEGGAGFDEEBFGHCHCDFDBCBCFCFCGCGBBBCBCBFHFGCAEABHBABGBDBDFDHAHFGFHBBBGHGHECFDECEGHGHDAAGDBCECDAEAEFEFCFH,False +794,18.0,14.0,23.0,18.0,18.0,15.0,28.0,20.0,GBGBGFGAEFECEBGBECECFGDEDGFCFGGHCHCFGDAHHCHCFCFCGCGCEAHAEABACDBDBAGGCGHAHBDFDHEHEGAGEGEHHDCDGFHBHGHFADECACAEABFCAHGHGBDCDFDFBAGACDGGCDBGGADHDBFHEHEAEGDCEC,False +795,2.0,6.0,5.0,6.0,3.0,1.0,4.0,1.0,GDGECBCHDEDECBBFBCBABDGDGACD,True +796,20.0,15.0,22.0,19.0,22.0,17.0,35.0,28.0,EHGHCDCDAEBCBFBACHCGEFEFEFDFHGHDCGAHDCGCDCACBGEEHEHGGGEHEFEGGAAAAHAFFECCAGHGHGHBACACDCFEAGGGGGGGCGAFCBEHHGDGHGADAHGHBDGAGBCDCABAHDDEEFGGEHHHBBBDBDHDHDHFHEHBCDCGFGECEFFGFGEGHFBEDA,False +797,22.0,14.0,14.0,13.0,13.0,14.0,15.0,9.0,HCHGGBDEFAFAGAHDCGCGCHCGFAADEDEABAGABFEFEFEBDFGABHFDAABCHCFCADBBAGDGDGDCDFEFGBDBDFFGCBCBEBGAAAAAAHEHEBEGCAAAFHECEC,False +798,15.0,14.0,14.0,26.0,14.0,22.0,16.0,23.0,DCGAADDDHDHFFDBGGFGEGBBDHAHFFFFAFCFBDDFEAEDHDHGHGDCHCFAGBDFCFEFGAGHECFCEDAHAGEBFBABDEDADCDHAFCFAFHBDFAFADEGEHEHBHGFGCGHGCDCDBBHHHHBCBCHDEDEDEDHH,False +799,27.0,20.0,19.0,24.0,17.0,17.0,26.0,21.0,GFGDGDCDFGBGBEBGBHHFDADAHEHEBBBHFFGGCADACAGHBHAAFACACHBECEFAHADGDAEHECFABCGCAHBHAHDGEEHFDFHFDFCAHDBDBFEGDGDGHBDBGAGEGBGCCECEBEHAGABADADADECGCGCAFHGHBFACACFDEDEBGACAGHGFDDD,False +800,14.0,22.0,27.0,22.0,29.0,27.0,20.0,20.0,BCBCBCACACAHDBFCHEHEFBGGCGCABBHBEEEBECECBDHDEBAACGCGFGFDFGBCDAHHHHFFEDDDDEFFHFDEGGGHEAEDEGBBDFEADFCGCGCHFHGHGEDCHFFFDFDCHFBCBCBCEEEGACAEHEFGFDFCFBAEHECGDEFGHGAFAEBBBBDCEHFCFEFDCDEDE,False +801,5.0,1.0,4.0,0.0,2.0,1.0,0.0,1.0,HCAEACAFBEACAC,True +802,15.0,14.0,17.0,11.0,11.0,11.0,14.0,5.0,DGAEAFAFCFDADEFEFCACGEHEFGCHABACABHBADDFDFCGEGEAAACHCGDGCGBEBFDCABBBBDBABFGGCCCEGFBBBEDAHCGCGCGCED,False +803,19.0,24.0,22.0,27.0,21.0,24.0,25.0,26.0,HFAFEFEFCCCHCHGDDHEHEDEACCFAFBHDEDEBGCGBFAHAHAHFGDBAGAHBHFEFBFEFABCDHDGACACBGDGHAFBDBCFHFHDHDGDADBCFGGBDACGHGCECEGGAGDGDGEGECADHDABGBDDCECEHFHBGGEGEHBFBDHFACAFBBBBHEEEGCDHGFDFDFEFHDHDCBBBC,False +804,14.0,12.0,12.0,16.0,9.0,14.0,9.0,8.0,ABCBAFDEDFDHDCDBAFCBGBDBEAEGEBCDGAACABDECECEHEAGHGDBHFFFCGDADFFFGFDBDFAHCHCHCHCBADADADABFFGGEF,False +805,10.0,5.0,7.0,4.0,17.0,8.0,9.0,3.0,AAGAGAGAGAHECEFEGEHEBEAEFDADFEEEECEDECHGFEFAFBEDFGBEACBCEFBCCGG,True +806,16.0,25.0,13.0,17.0,23.0,16.0,21.0,18.0,CBGEEFEGBBBCHGHBAAAAGAGEGCHCEDBBBBBHHHHDAFFEEDEDAAADFEBHGHDHEGEGHCECEBBDADGGGGGDGHEHEHEBBBFGFAFDFEFEBEBCFFEBHBECDBDFAFAGHDFDGBHDCFCAABCBHEGDGDEBGCCAF,False +807,3.0,8.0,5.0,8.0,9.0,8.0,9.0,9.0,HFFFBHCHEBEBEBGBDCGCECEFDFBFGAGHHDHFACHDHDEFBGDGEHEADGDBEGG,False +808,18.0,19.0,24.0,19.0,15.0,25.0,23.0,17.0,CDGFCFCAGHEAEADCGEGACBGFGDHEEECACECECFAHAFDCDHDFEBEHDFDFHFGBEBGGGBBBHBHFAEAFGFAHAGAFCGCHCHGHBCDDFDFDGDFBEBEBFAFCFGDCCHGHADCBFBGBGHFCGDGBCAHFDFCFCBCBDAEABADGFGHC,False +809,24.0,16.0,20.0,18.0,20.0,16.0,26.0,18.0,HBEFGCGHAHADGCACAFBFAFCEBGBFDGAGAEHHCDDHDFDHDHDEECGABCBFEAEHDGGGGBABGFEBCAEGBCFCHGHBHBABGBHFEFCCCCAHGEGEFHFDGAEBHDADCGHEAEAEAEAEGEDCDADGDGAGAGAEHDGCCFCFCADBGF,False +810,7.0,10.0,7.0,14.0,17.0,13.0,14.0,8.0,DEAEGEFECACABGEGEAHGHGHAEFEFECHDDFDBDBCBDBDFGCGEBECEDDDADBEFEBDFGBDFHGCFFDGGFEHEHFHBGAGEGF,False +811,11.0,12.0,11.0,18.0,16.0,11.0,15.0,16.0,EBEBABDHDHDHEHGHFAAGGCAFEDDGEFAFHDBDBDHEGGGGBCBCFDDDDDEDBHFEBHCHABEFEFGHECECBFGGGEDHCHCGEGACAEAECHABCHDADFDFHG,False +812,7.0,8.0,5.0,1.0,6.0,6.0,5.0,5.0,HHHHAEACACBEBCCAFAGEFCFDBHBFBFEGAGEGBGFABBE,False +813,7.0,6.0,14.0,17.0,20.0,8.0,11.0,16.0,BCHCAFAGAHCEFEDEHEDCHGHAEDGDFCFHGHGHAEGEGFHBBDFEHEDEDHDEDEBGDDFBEHGABCEDECCCADGHEHEHCHCDCDCDCEEGEFD,True +814,27.0,14.0,15.0,25.0,17.0,16.0,12.0,25.0,HFFCACAHFFCBCFFGDDECEFEHCBCBCDAAAGAHAHDECEFHAHAHDEABBEBCFGBGDEAEAEADGHAHACDHHHBCBEDFFAFHFEEGAAAAAHAHEHEDDDDGAGDHDBDFFAHDBACACAGHHDGBGBEDDBDHFHECGDDDHDH,False +815,9.0,8.0,11.0,6.0,5.0,16.0,9.0,7.0,DDGCCHAAADDFEFBHDFFFDFCFCFCFEBEGGGCFCGHGHEAAAFFHBCBGBEBCBFFFCFCAAGAHHGB,False +816,27.0,23.0,14.0,24.0,26.0,27.0,25.0,22.0,DABHHHEHAHAEFDBAGABDBGHDAAGAGFBAHAHEEDABFGGEEADAFBCACGCGCEFEBEBDFDCDGDEFEHEHFAGAGCBCGCBCBEDAGGBABHDFBFBDEHEHGBFEFEBDFHFHFDEECAFGFGFEADHDAGAGADCDCHFHCEADFDGEAFBFCFDBEEDGAGBEFEHDHGAGHGHFBFBF,False +817,1.0,1.0,2.0,2.0,3.0,7.0,3.0,4.0,FFFFADHDHEHEGCFBGECFHFG,True +818,10.0,14.0,17.0,5.0,12.0,5.0,16.0,9.0,CACBHAACABGDCAEAFGBEHEGCGCGEGEDBGAGFHBGCECEFEGEGBHBFGAGHEABDFDBCBCBHEHGHGBDCACBGBECCCCCH,True +819,20.0,12.0,13.0,11.0,16.0,13.0,21.0,6.0,ADCECACDCEGDFFAFBGBGBGBAAAEBEBGFDADEDAACACDCHHBGGGGGGGEGAAHFEFCGDGBCFABAFEGCDHFECEDEHABCDAHFGAGEGAGAEAGBFBCEFEFE,False +820,24.0,22.0,18.0,21.0,20.0,19.0,14.0,22.0,ECFBHAHAHAEAFBFGDGDCBCGAEAHABCBHFEDEDGBCDCDADABAEAEBHDGDHCBAHFDCDHHBHEGAAFAFCHCDDEHBFBFDGDGHBAFCEDEHFCEHEHEHGCGAHABCBEFHFGCDCDFBFBFAFGBDEDAGCHBEBCBADAGEBEAEAFFH,False +821,24.0,21.0,19.0,22.0,19.0,13.0,20.0,29.0,DAHAHAFEGCDEECECAAEHEFDDDGAGAGAGABHBGEHDHFHEHAHAHAFBHBHCAADCEBBGDECHGFGHGAGEDFDFDHHHCGAEABFDGBECECAHACFCHGFBDHGFDHBHDDDDGGHEHAHBGBGBHEABBFBDBFBDAEEBECCCCCACHCBCHAHDGDB,False +822,16.0,25.0,27.0,23.0,14.0,15.0,16.0,28.0,BHCHCDCAGFGAGBFHEHBABGDHBABFBGBDCHCHCHEHAHEHCHDBGBHACADADAFFHAADACBCBEGEFDFDFDFCHEHDDBDEGEDHHHCDEGHCFGFDEDBBGFGCGHAHBDCECHCABHFCCHCDEDCDCGBBEHDHBGBFEFCACHCBBABCBDGC,False +823,19.0,16.0,17.0,19.0,13.0,21.0,12.0,12.0,AAFGBDHDCDFDEHBBFHFCDCABBFDFGEGEBCHDDDBDGDACAGABEGECECECEFEHCHAGDDHCCDAEFFAFBFBGDAEHHBABAHADABGBFCFGDCDFHFHAGAFAFDFBACACFGFEFECBC,False +824,23.0,14.0,24.0,16.0,17.0,21.0,26.0,11.0,EEEECEBHDFDBDCFAABFDEEGGCGEGFHDGAGBCFCHCFAFAGAGFFBGAFAEABCGAEADADAHBBEHCHCBCBCDCECGHBHAFDEDEAAACACFFECEFFGACCDCFGGCGCGFDFHFGCGCGAEAGGHHFBFDADABBCGGGDGDG,False +825,16.0,23.0,19.0,19.0,25.0,21.0,19.0,16.0,BCECEGEHBGBGDACADFFBABGGEBEGCGAGDBCFCEADAEFEDDCHCDEDGBGCFHFGBEBEBEHCHCEBEDEBFBFEFHFHFGDEAEBGBEDDCBHDFGFCACAGAHBDBDBCCFCFAFDDDADHEEEFHAEAGBGCAHHHEHFGFBFGECHABF,False +826,8.0,5.0,4.0,4.0,6.0,3.0,1.0,4.0,CDGDCFEEEEABABADAHBFBHACAFHEAEAHCBD,False +827,24.0,26.0,18.0,19.0,16.0,34.0,27.0,29.0,CFAFCHHGFDHDBDBDCDCHEFBGBGBHBDADCGCGHGFDFBAHDDAFECBFFFHFAGECAHAEBEAAACGEGHGEABAFGCEAGFFHFGACBGHGAFHCHGHGBFAHGHBHBGBGAGCFBEDHBFBHEHEBFGECEADHFHFHFDABFEFHFEFBFBABDBDFDADGDGCAEAFCFCFCDAGGFGFBHHHHB,False +828,2.0,3.0,1.0,7.0,4.0,6.0,1.0,1.0,ADDDFDFEFEDEBFBEGFDADFHCB,True +829,18.0,8.0,19.0,22.0,14.0,21.0,12.0,12.0,EGEGCHAFEECHDBDBDCFAFEFDFEGEAFCFDADADCHFHEADAEHDHCCFCFDFHFDFDACACACEFDFDGBFBCGEGFGCGCAHADACEDDGCCACHBABDBHAHFFFDDHACBDEAEGGGFD,False +830,14.0,17.0,12.0,13.0,7.0,7.0,14.0,9.0,EGEBHBDCDGECBABADDGCABACFCEBDCCADADFGHGHGFGBGBGHGFDDCDAGABACHHDHDFDCBBGBAAFACEHAGAGBEBHBCBEBF,False +831,13.0,21.0,11.0,11.0,12.0,12.0,12.0,8.0,EAEDGBFBDBCHEBEBEBCHCHAFGGBCDDDCDCBADAFAFABADFCBCGEAEDBAFAEHEHADFHBBEHEFBFGEBHFGBCBCBFGGAGAGBGCGFBDB,False +832,14.0,20.0,21.0,16.0,26.0,24.0,30.0,17.0,BGGGEEEBFFFEFCDGGGGGCGABDFGHCAFFFDFEHDHAGAGAEBEBCBCAGBBDBFBFEEEDDFCCGCGEGBBDBHEDCFCHGFEEBGCFAEGEGECFCGCHEDDCBEDDDHHHCGBGEHEHGDDCGCGBGEGEBEHECGGAEABAFAHAFAFHFHCHCFFFHFBA,False +833,0.0,0.0,2.0,1.0,0.0,7.0,1.0,2.0,GFFCFHDHCFFFF,True +834,15.0,17.0,13.0,12.0,21.0,19.0,18.0,23.0,DEFBAGHEHEABHDFGFHFHCHDHECEHBHDGDGFFCGBFBEEHHCDEFECEDEBCBGEGEGACAGHGHAHDFCBHGFFFFDACEHEBFBHBHGAAEADGGADHHHHGHGFAFCFCGEDFFABABGECACABEBEBEB,False +835,9.0,17.0,15.0,12.0,13.0,15.0,12.0,18.0,AEAFDHGHGFDEDBFBABACCCFCHEHCFEDHFGFDHBHBHEFAACHEDECFCGCBCECEGHBHCABDBEGFDFDBDBEGEFFCCGHAHAHGHDFBBGBGDGHBHBCBFHE,False +836,24.0,27.0,17.0,31.0,24.0,22.0,21.0,23.0,DCGBEBCDEDADFBFEDADADBDCDCDEDFDGBGCGBHBHBHEHEDEDAGBGFDAHGHBCECADBDEDBFFAFAFAFEHHGCGFEFDDGDGFBFGEGEBAHAFDDHFABBBDADAHAGAFFFCGGEECHGAGAEECEBFBCBHHGEFDAAECFADHGHCHBBBBDEDHBBBEHHAHCHCAEFEHADGDC,False +837,8.0,2.0,11.0,12.0,11.0,8.0,3.0,11.0,BHCHEDEHFAFHDHCHFDCDFDFDAAHCFDDADHDECECACECAFEHEGDGEHEDEHFCBCGCAEA,True +838,12.0,19.0,12.0,11.0,20.0,17.0,13.0,16.0,DEFEFEHEFBFECEAEAGBGAFEBEDFGFGAHFHFCGBBBBBBHEFEBHBGBGHCHFBCDFHAACCHEHACDBFEGEDFBCBABHHCHEHACACEDDDDFDGHGHCAGFDFBEEEGEGBA,False +839,1.0,4.0,3.0,4.0,6.0,6.0,4.0,1.0,GBEECAGBFBFBEDCDFDFEEHEDGFGFC,True +840,5.0,4.0,4.0,1.0,6.0,4.0,2.0,2.0,GEBEFEHEAADACACFCFBBHCAGEBEF,True +841,15.0,12.0,13.0,8.0,18.0,15.0,11.0,15.0,FHFHFEAAHFEFCGEHEHCHCBCAEBBBCHAHAEGFGABHBEBEFCBCAHDHBEAFGBHAFEFBGCFEFCDADBDEDEDEGEFEFAACHDHAEACGEGHGCGAGFDC,False +842,17.0,27.0,15.0,15.0,25.0,21.0,18.0,18.0,DBEBDBEEGGGBGEHCACBCBABGEDEDGFAFCCBEDCGGFGBHAHDBBHBHECACEDBDHAAFAEBEDCDCHGBEDECHAFAFECECEFHGHGHBEBGBGBFFFFHFEFHFHEBEGEAEFFAFGBBBFHCHADFDFBABCGAEAGFHDADEBHBE,False +843,20.0,14.0,16.0,25.0,17.0,16.0,12.0,24.0,HBHEDGBFBCADADACHHDHDAEAHDDDDDHFFDHDGCGCBHEGABAHEDEABACDCEFGFHAGGBACGHAFFGDCAAGHDEGEGEDABACABHFDEEBEBDBDBDHDADAHCHBEFEDEDCFCFCHCHFHFHFHFCAEHHFCE,False +844,6.0,6.0,6.0,6.0,7.0,4.0,7.0,2.0,GCECFBDBDBEGHDEAEAFFECECACBGBDADGDGHFABGEGCA,False +845,14.0,10.0,13.0,17.0,13.0,16.0,16.0,22.0,DADFGHGHFHCBGAFEFCFCGDGDEDBABABECDCDBBGAFAGAHDDDDFDGDGDCEGGFHFHCHGAGDHHHFFCGCHHEFEAHHHFHGEGDAHECDCHHAHAEAEBCFHFBFCEHBBEEA,False +846,13.0,21.0,15.0,9.0,8.0,13.0,6.0,10.0,AGBCBCBDGCBFGHABCBCBEBABCGHEHBAFAFDFECDBBAAHBHBHCFCFDBABDCDFFCGHAHBHBEBEBCFCACDEHACEBFDFGFAFAED,False +847,8.0,14.0,10.0,15.0,9.0,10.0,9.0,7.0,DECFAHHBGBCEAACBCBADDEBHDHDEDFFFGEAEBGCGBGDGDFDADBDBDCFCGCBCHABFBDEDGDGBHBFFCFEAEH,False +848,10.0,5.0,6.0,10.0,12.0,17.0,10.0,11.0,DHDEDCDFDFAFAHCFGABAGFCFBGGGGAHCFDFAFEEEEBBABHFAFGFEEHDHECEHFHFEAHAHEDFDFHFDGGGEC,False +849,22.0,14.0,13.0,19.0,14.0,18.0,13.0,19.0,AACFCFBBHBGFDADADAHHCGFBCHHFHBHDGDCAHAHABDEDBDAHAGFGEBEBACHCDEGAFFDGBHFCFDDBABAEEDEGEFEAAGAGABADAHFGFCFAAGCFHEHFGFBFEEDEHEDCDCDCDHHH,False +850,12.0,11.0,24.0,25.0,18.0,37.0,27.0,36.0,GEGEAEAEDHDEDECECGGGEFEFEGCBFBFCFCDCHEHDDGEGFGDHFGEGAGCGFDHCHFHDGCCHEBBDACHCFCHGHCHCHGDFFFFDFHGHDFFFGFGHHHGCDFBFCHHFHDDBACHEEFDCAHDHBHFFFHHCHBHFHDGFGFGBEAHFHFHFCAGGDCBGDGDFFAACDCAFDFDFBHHAHE,False +851,8.0,20.0,9.0,10.0,16.0,10.0,11.0,18.0,GAGAGFFHFHCHGHEFEGADABHBHBFEEEBAHCHCEEHEDCAGGBBDBFGFHFHAHFHBABEHEBFBCHEBBBDDDCDBECEGDBCBEBEBHBGCHEDDHG,False +852,8.0,4.0,3.0,3.0,5.0,4.0,5.0,3.0,CEHEHBGFGBABDCGAGHFDCGAAAAEADAFEFEB,False +853,2.0,2.0,4.0,5.0,2.0,8.0,1.0,9.0,BHFHFHFADCCGFDFDBDEFAHHHHHFHECCFD,True +854,0.0,3.0,1.0,7.0,1.0,4.0,3.0,3.0,BGEDFDHDHGFBDBCGHDFDFD,True +855,13.0,9.0,23.0,8.0,13.0,14.0,12.0,14.0,CFCFCGHEACCCEEEGDHHAHBGBCFCDCDCFFGCAFDCABHCHCDFFCECGCGCAABFDEDACCHHAFAEBEBHGHBHFGEGCGCGAEBCBAGEFEFEFDHAHAH,False +856,10.0,14.0,21.0,25.0,13.0,22.0,18.0,15.0,HDAFAFDFBGDDCEEGEDFGBDBGCCCCDDDGDGHFDGHEFECHCHCFEDBDBACGFBFBFDCGEGCABABDEGCGCECEBAFGHHBDDDHHHGGDCDCACAFBEBECFCFAEHHFFFDGDGHGHDDFDFHFCFCBAF,False +857,5.0,7.0,6.0,6.0,3.0,6.0,3.0,6.0,HBHCDAHAFGBACABHBDBDEFGCHCHCBEFEFGFCFDDBDA,False +858,5.0,6.0,10.0,9.0,8.0,7.0,3.0,10.0,BGCHCHCBDDHDGDGABCBABFECECECDCDFHHCEDDFFFHHEHEAEAFHBEDHCAF,False +859,5.0,3.0,3.0,10.0,1.0,2.0,6.0,6.0,DADADBGHEADDDCDGHGHGCDCDBFAHHFHAGDGB,True +860,23.0,20.0,27.0,31.0,27.0,21.0,22.0,20.0,GBHCDCFCFDEDHCHGEFEFECCCCCADABAHFHFHFDGDAEEHACDDGBADFDEECFAFCFEGCGEEHFAFEFBABCDADEDEHBHGHBBAECECGBHAGFHHBGECCDEDBFHCACGCDAGAGADDDDDCDGFCFCEEEDEBHGHGHGCGCBDADHBGDDEDABABAEDEBFCDEBABGBDAFAFGEGH,False +861,7.0,7.0,14.0,4.0,11.0,5.0,11.0,5.0,GCGFGBGCCCGFAAEAECECECGBABHHCAEAHAEFEBEHDCDCGFGFBCGCGCDBEEHDGECB,True +862,12.0,3.0,10.0,5.0,8.0,8.0,5.0,6.0,GFCAHAHAGACCEHDBBAAAHADECEDECGCBCECFCFHFHAGGEDEFFCFAEAFAD,False +863,24.0,14.0,29.0,24.0,18.0,18.0,12.0,25.0,ACACHBEBEDABHBGCDCFCEDFCGCACGFADCCCCBCDEAEBDHEEGAGCDFDFDFGEHAHFEEAEHCCFHFEFCHCHDAAHGDCDAHFHEHDHDHAHADEBEBEGADAHEBFHFHACGFGCGCBCDCDCACFCFABCBADDBCBHHDHGAAHAHFFDHDEDA,False +864,12.0,14.0,8.0,8.0,15.0,8.0,10.0,15.0,EBEBGHCABAFAFDFDADGBHCEBGBGBCFCAEEDHCHGHBHDGDHEHEHEHCFGFBEEHAAAHGHGEGBFCABHFHEEBADCDABEBEA,False +865,3.0,2.0,2.0,3.0,0.0,3.0,0.0,4.0,BHDHBCFDFCAHAHAFD,True +866,5.0,8.0,8.0,6.0,13.0,7.0,15.0,8.0,FHCDEDADBEBGAGCCCEBGGFGEGEGAGAGHDHGBEHEDGAGEBECHCGFEEHEHGGFBFBFCFHEBCD,False +867,15.0,8.0,10.0,4.0,10.0,7.0,12.0,11.0,GCHHEHGBDBCGCBCFEAAHAHADFCFCFGAGAFBGAHAEGFBECEABHCHAEAEHGHGFBDCHGEGEGDACABAEA,False +868,13.0,19.0,24.0,20.0,14.0,16.0,12.0,20.0,HCHAHAGDDCDBGGHGHGCEEAEGFBFDEAEFCFHDHGFAFGEHDBDBDCECDFECHCDCFCHCHBBBBGAFDCACEDBFFAFAFBEHCACDHBCBCBHBCADDDBDHDHCHCBABHHEFGAECGCGCBDBDCFHFEE,False +869,11.0,10.0,12.0,15.0,14.0,12.0,10.0,5.0,CBGECDGDGDADCGAHDBDFFFFEAHFEFDBDGDGECECDDFDADBEACGFEBEBECCCGCBCBEAEAFGBAAAEDEGHHDHCFAFEFB,False +870,8.0,16.0,15.0,5.0,12.0,6.0,10.0,5.0,GEGAAFBCBCEGAAEBEBEFHHCBAAGACBBBBEBCGCGCECECBABCFCGCFEDEHCCDGBGFDFDEHCHBBGBDE,True +871,7.0,10.0,13.0,4.0,10.0,7.0,7.0,8.0,GAAHGCBADEDHDCCCACAFHEBBBBBCBEGEGFCHCBEGEGEHDHCFFABCFCFHGHABFECECE,False +872,5.0,6.0,11.0,4.0,5.0,6.0,7.0,6.0,FCCCACBDAFCCCFGBBHBGAGEGDGCGHGHDHDEBHCCFCBAEFEFEHA,False +873,6.0,3.0,2.0,8.0,3.0,5.0,4.0,1.0,AADDDCDCGGFFEBADADADEDGBGFFEFAHB,True +874,16.0,16.0,9.0,13.0,16.0,16.0,11.0,18.0,DGAGHBHCEFGDAAEAFAFBBDFHEDEDHBHGHGHDDEDFCFCAAADAHFBCBCGEHEBFDFAFCFAFAFBECCBEDHHEHEGBGCDFGFHHHBHBEBEBHAEADBEBAAGEGHF,False +875,10.0,10.0,11.0,9.0,10.0,8.0,13.0,16.0,AFADADEDEFHCHCFGBGEHDFGHCHEGBGHFABHEACHBHBHBHGDGBAAAHAHCHCGGGCGEDEBCDDGBGAECEFFFBCHCHDE,False +876,10.0,18.0,8.0,11.0,7.0,15.0,11.0,9.0,FCHDHBFBGCDHAGCCHDHAGFFHBHEFAFAFDBBBDBDEACGGGBGFECECACHDBABFBDBDGEADADFFFGEGEBBBFBFBGBFAH,False +877,4.0,5.0,14.0,13.0,6.0,8.0,11.0,11.0,ACACGHADGCECGGGDCCCFCFBFDFDHDHDADHDHFFBHGHCHCGCDCDHDEEBGFDEHBHGEEBDFCCGG,True +878,22.0,17.0,15.0,16.0,16.0,19.0,13.0,15.0,CCFCHHDBEGEGDCFHFBAGFEDDFDCECEGBCBABADADBGGDBACAFAEABHHHFHCHDBFBDBDBEHHCHCHEEGFGFHAEAEAEADFEAABCFCEAHFGAAADFDFBFBEGCGCDAFAFAEDGBHBGFA,False +879,11.0,12.0,5.0,10.0,10.0,9.0,11.0,9.0,BCBCEAFGFGHBHBHDDFEFGBGHGFBDCAAGEHDBDGHGHFADAEEFEDEDEAHABABACAGHEDFAGEDBGBCBF,False +880,22.0,23.0,20.0,22.0,17.0,22.0,27.0,22.0,AFEFEHDHDHDBFBGBGEGBGFGFGEHEABABGGGABAHDHEBCGCGCFCDBDFEEAAAFDCBFHGHBCGAEDFDFDBCECFBAGAGAFEHGGCGDBBCCGBDDCDBDCFCAHDBAFFHCHDHFHCEEDHDHBHCCBFBAEAEAFGDCDHAHFHEHADAGAGAFBGCGHGFBEGG,False +881,26.0,17.0,21.0,13.0,20.0,12.0,23.0,19.0,BAEAGCGHGAEADABEEEGAAHHDDBDFGAGACCHHEHEBFBHEEEDFGFEAGHCCACGEFEDCGCHCGFHHBHBGBCCCDCGBGBABABFDDHEAEFEGGGGEHAHACACDGBGBGBEAFACEHFAAAHGHGDCCECFCBCBHDAAAFAD,False +882,1.0,1.0,3.0,2.0,1.0,1.0,0.0,5.0,DHHFADEBCHCHCH,True +883,7.0,3.0,8.0,7.0,4.0,4.0,4.0,4.0,GDEDCFHFHDHDEGEACDCABBGFACACGCFCDADBCAEAH,False +884,21.0,12.0,14.0,11.0,9.0,9.0,15.0,13.0,EHEAEGDDAGGBGFFAGHDHDCDCDCFCGGGGGAAEGCHEDEAEFHFAFGCBHBCCCCADBBAGAGHBCACAHAHBFEDBGBCBEDDHHABAFAHAHFBCAAAA,False +885,16.0,26.0,24.0,20.0,25.0,24.0,19.0,20.0,DFDGGAEAEAEDHGHGCCABBEECFCFGBGBDCGFFDBDECEADADHGHFDBDCEEBCGCGAFBFBCHDFDFEFEFHFHFHBHFEFHCHCBAFDFBFCAGAECBBBBEAEBGCECFHEHDCCEGBGBGFGFHHEHCHBDACECABABDBHAEDDCGGBBEFDFDCBAEHEHECG,False +886,13.0,28.0,17.0,8.0,23.0,25.0,17.0,16.0,GFFBFBHCFBBBCGCGEEBCBABFDEBGBGCACEHFHFHBADDCGEGEBHAAACFCEHBHBDAEFFFFDFDFEFEFECEBBBHFGBBHBEGCBEAEDCHEEEFBGHGECEHFHBABFCFCFCGCEAGDGAGAFBGGAFHHHBEBEBF,False +887,12.0,16.0,10.0,18.0,15.0,11.0,14.0,8.0,EEHEFGDCAFDGDCBFBFGFBEAFBBBAGFGBGCHCHCAGADCFCDBDEHEAEDGDBHBFGEBEBDBDADCDHDEABDDEDFCAGDGAGAFDEAGCGBEBEHEH,False +888,18.0,13.0,17.0,15.0,11.0,10.0,18.0,15.0,DEGEDEFAHAHAHGHGHGCGCFDDDADFCBGDGDCBABCBEACAGAGCEDBABDHFGAGAGDEEHAFCDCBCACBEBHCGBFAHAHCDFHBGBGHFHGHFBACEGEGCHAECFCDAD,False +889,22.0,5.0,11.0,9.0,14.0,19.0,10.0,13.0,HEHFADEFGFCEHEFDFHFAFGGGGAGAFADGDFAEAHBCECEDFCFHFCFDFDAACACABBFGCHEAAABCDHEAEABFHFHEGEFHAAAAACAGDHCHEFE,False +890,27.0,36.0,17.0,27.0,26.0,14.0,25.0,25.0,FHDGFABEECADAEBECEABAGHECDCDADGDADADEHEHGHBFBCBGDEEEEEBABABHBHAGCEDEDEHAHAGGCDCDHBABHBCACAGFCFGHHFDFDGBGHGAGCGFFBHADFCECEHBDBGBABACAHEBBHGHEHBBEDEFEBGBDBCGEDBBBBBEBDHDBAHGFGAEBHAADGHGDABFCFDAGBGDHD,False +891,18.0,15.0,22.0,14.0,25.0,27.0,18.0,19.0,FHFHEHAHCFEDCDHFFFHCCCCCCFAFGEAHAFGGEGEGEGFGFAEHDCDFHGAGEBHFHCHBHBEDHDCFCACGBFCDDEHBCEGAFABEBFDEGAFDCACFEFEDEAAGAGAGCBCDFEHAHEHBCBCBFBEEFEHGGGCEFEFEBEAFFBDADB,False +892,15.0,15.0,17.0,14.0,25.0,21.0,15.0,21.0,EGAHHHDHDFEAEDEGGGGAGFHFAFEEEHHBCBGHGBGDFAAEAECEFEDDBFCFCAGFFHFHFHBCFCDHFHCHADBHFGFGBEBHHEEDDCDGBCEEEBGBHEHEDEAFCBCECEBGAAAEDCDCACABEHHCFEFCFBF,False +893,5.0,2.0,1.0,1.0,3.0,2.0,5.0,2.0,BHAHAEEEGFGFACGBDAGAG,True +894,1.0,2.0,2.0,3.0,4.0,6.0,4.0,3.0,FCFCHHEFEFGGGGHDBEBFAFDDE,True +895,12.0,25.0,10.0,17.0,18.0,19.0,18.0,17.0,CECBHFGFGEBBHFEFDBDBABDGAGAEABCBGAGAHCEEHEHEHDDCDBFHFHEDFCFBFBFAGGGGGFGEHBBBHDHBHDEBEFGDCBBBDBGCAHHEGBGBCDFDEEEDEACAFFGBBHFHFDFAFHGBADED,False +896,16.0,8.0,11.0,13.0,10.0,11.0,7.0,7.0,GEDEHEHBBDADFDADCDCAAAHFHFGFECACAEDCDGAEAEBBCBGEACAHDBDEGFHFBCDCFAADACBCHFAFAFEGGDF,False +897,11.0,6.0,9.0,7.0,10.0,14.0,15.0,10.0,HDBFBGCFCGCGBGDEDGHAHGHAAFHFCGBGCAHHGFCFAFEBGHGBDCHCHDEEFEFEAEAEFEFGDGFAFACGEFDAGA,False +898,17.0,13.0,21.0,30.0,28.0,20.0,12.0,19.0,EDDBGCECEDBCBCDHGFECBGBEHHHEHFHDGDHHAFAHCHDBEFDADCDHEEEHEGDGDGFEDCACEDEAEAEFDFDFDADCCACFEFCFEFCBBHCCFEEDHDFGEGAFCFCACABABCGDEDAHEDDDDGDGFHDHDABFCFDFAHEEBEBEHEAA,False +899,3.0,3.0,2.0,3.0,3.0,3.0,8.0,3.0,BCEFGHGHGAGBGBGDFDCHEGEFAADG,False +900,16.0,24.0,17.0,15.0,11.0,13.0,13.0,18.0,DDCDADAECDHHHCHADDHCHCBCADAECGHGEAHFHGBBHDADAEHHFHGACACFCFBEBEDCGCGBBBBGEFFHFBBGCGBABABAHFEFBBECCHGFDFBFAFAHBBEBEACDGDGCBHBGBDB,False +901,25.0,30.0,29.0,16.0,34.0,19.0,24.0,19.0,FFGCECEBBBCDCBFEEEECGCABAFEFGHBDAACECGHDFCHBFBGGGBGHCHCBCECBGBEFDHBHBHCHAHAGABABGEGFCFBEGEBBCBCDHHHCHCHDBDCFCAEDHGAGEBEGEBEDEFFDBDEFBCEFEAGGFGEGFBFHHACACAEAEAEBEHEBAGAEAECGABADDDAECECFAAEDDAGCECBG,False +902,24.0,23.0,19.0,24.0,26.0,27.0,19.0,14.0,FAAAEACAEEEGEDAHEBADAGGHEDCABGFFDFDFEBEBEDEDGAHFDGBCBFDFGECFBFGFBFEFCFEDADBEFEFACACACAHADBBBEHAHBGBFAGBEEGGFGCGCFAFDFEBHGCAAGDGFHFCFCHCDCBFBGBCBEHFHCHCBEDGDACAEBDBHFHEDDDDDEAED,False +903,29.0,29.0,25.0,18.0,19.0,26.0,26.0,24.0,GABBEDADAGFHBHFHGCBCBDADGBGDGHEDBGBGDAEBEAGFGACEBEDADFFFBBBCFCGAFAHEHEHGBAAAAAAGGCCHBGBABHEEFHFHAHFBGCHDHFEBEGEAEDFGCHBHACADBHGDGCEDFFHFEFBCBABAHAEAGGFFCFAHADGDGCBCBCGCGCBCBCFHEHDFFEFHFCFABCHCDCAC,False +904,6.0,3.0,10.0,6.0,5.0,4.0,4.0,1.0,ACGCFCACDCHCDDDEDCGGEFBCBCBFGFEEAEDCAAA,True +905,3.0,18.0,9.0,11.0,14.0,16.0,4.0,13.0,DCFBBCBEBDBFFEFDCGHBHGDCFBFDEHEFBHBFEFHFHFGCAEHFAFBEHEHEHCACHGFDCBEFEHEBDBDBHBDEDEDBCBFB,True +906,16.0,25.0,37.0,22.0,24.0,10.0,28.0,28.0,DFDCDCEAEHCHEACBHBGBHCCGCECADDDDDDCHHHAHCCCGDECECEBECHCFCFBHBACGCBABCBHGEBBBHGHGBCBCDEEAAGAGDHFCCEDEDGDGDGBGHHDFFGEEBFAGHGFCBBGEHHBCBDBABCEAGACACGBEHEHCFDHAHEGGGHGHGACEDECHCGCGCDHFHBEGEDBCGC,False +907,25.0,18.0,28.0,21.0,19.0,32.0,30.0,20.0,GCGCEBHGCGCEDDHHGCCCCGHGHDHEHACGGGBGFGBEACGHGCFDFDCCCHCFDFAFAEAGABACAGACEBHBFGFBFBDHCFAFGFACAGDEHCDBGHAHBBDFDFCFAEBDCGFAHGHGFGFGBADFEFHBDADABBEAFHDDFDFGBGDEDEFAFEFEFGFAFDFEFCACHFHBEEECGCGCAAEAC,False +908,28.0,27.0,16.0,15.0,23.0,29.0,25.0,24.0,FAFEFGFBABHFFBHDCCGAABEBCACAEFFCFAGAEEGEGFGFDFHFHBAGFGBGDHBHBHBCGEGFAAHAHAHAEGEBEAHABCBDFGFGEGBFBHBDBFBFGFGHGHBEBEBDGHGFAFCHADEEECECFBACCBCDDHGGEHEGCAAFAFBDHHHDHDFDADGFAAEAFABEECGHHDBEACB,False +909,22.0,23.0,20.0,21.0,31.0,23.0,29.0,28.0,EAGGGDCHHHHCDDEDBCHAEDGBGAGADBHAFFHGBGBDEGEGHGAGDBEGAGCCHFHFGEGHHEAEBDDDDADHCBBBCACFCGAGECEAEFEGEDDAAEFEHBHBGBFCFCHGBBDBFBFDEAEAEFCDDEGFGFCECAGHGFGFEHHDAFHFHGHGHFHFEEEHAFBBBEAECGCBCBCEEAHACBFDFEHEH,False +910,35.0,20.0,17.0,22.0,15.0,17.0,23.0,20.0,BABABADGDFFFFFADHEEAEHCBGBGDGEGCACHEFAAHAHAHBHGHBABCBCGCFDFAFCFCEAEHEDGFGBAAADBGADADBDBECGGFCBDBHCAADAHAGADCGFGFGCGCEDAAEAHDEDBAGFGBADDDCDHHHCHAHDEAHGFAEAFBDHAGAEHBBGCGA,False +911,20.0,22.0,16.0,16.0,19.0,34.0,24.0,21.0,HHBBFFAHAHEFAFCDBDBDGCEEBFBDCCBCHDFAFDBDBFCFAHGEDBGFFFDFHACEDGDBFBFCECHCHBFAFADAFFFFFFFGFBHGHGHGHAFABACHCFGGGAFHFHGGGGFAFEEGHGEEEGECDGECBCBHDGDGHEHDBAGEBEAEABABFEGACHEBGFAF,False +912,14.0,22.0,22.0,16.0,10.0,16.0,13.0,11.0,GABHDHAHACDCBFFFECHFHEBEGABCEHEBBFBACHCHCACABEFFDBACDHFADAFBFBGGCGCGCHFBFCGDFAFGBCBCBDHDGDCBCBCGDGCGAGABCBCACEDFDEEFBBDDDEDB,False +913,20.0,27.0,29.0,23.0,22.0,31.0,29.0,18.0,GFGEECFDFAGEFHFACDEGCGCGHGHDHDCGCFDBAGAGAGDGHFDFBFGFGAGHDAGAFABDCFFECECEFFDCDCBCGDBABFFHFDDDGACHHDBEBEBFCEEBEHAHECBABGGAGDHDCEEGFCFBDECACAFHFAFACBEAGGGBGBCBHFCFCFCFCHDFAEBBBHBEBECFCHEEGBGBFCDBDBDBHGC,False +914,12.0,9.0,6.0,2.0,6.0,6.0,2.0,13.0,BFBHEHEHBADCHBAGFHFEBHAAACABHBHAAACECBBACGCHFHAHAHEHEFFD,True +915,10.0,12.0,24.0,13.0,16.0,14.0,13.0,16.0,CEBDBDBDCDCDCDBDAHHBFBFCFGFGEDFHCBCFGECFCEBEBHBCCFCFDFEHAFBHAHAHFCACHCECEHACBCHCFEDEAGACDCHCGAHCDEGGHEEFHAGGGECEGEHDGG,False +916,4.0,4.0,9.0,4.0,6.0,12.0,3.0,4.0,CECDADFBACFCFDFBFGFCFGHCCGBEHEHEHEFFCACBEFFFAD,True +917,15.0,18.0,12.0,11.0,16.0,11.0,18.0,15.0,AEAEAEAEAHAHAGEEFHGHBHBEDABABADHGFGDHBCDDFHGBEFFFAFGGHBDFCBEHECECGFHBHEEGDBEGEBBGDCDHDCACGFGHGCABABHFACCCCBGBGBGDGBE,False +918,14.0,16.0,12.0,30.0,16.0,18.0,12.0,16.0,DHDAEBFADADADADADGDFAFHFHDEFGBGBGBGFHCGEHECEAACACGCDDDFEBEBHBFAFHCDDDDFCFDFGHCFDHEFEFDCHBBBHAEDEDBAAHCEFDCDBDFDBEEDBDHEBDHDGFHDHEGGGCB,False +919,5.0,11.0,3.0,9.0,10.0,8.0,8.0,5.0,BFBHEEEBCBHEHGAGAGDDBDEEEHABFCFBAGDCDGDBDGAFEFEFDBDGGFBFBHE,False +920,5.0,0.0,5.0,4.0,1.0,1.0,4.0,2.0,CGAAFADHDCACGCECGDGDHA,True +921,24.0,17.0,18.0,26.0,23.0,31.0,24.0,25.0,EDEDCDADFGBABAGGFCFDFEGCGBHHECEADGDEDFDFDBEGEFCAGFEFEFDHEADHCHAHFHFHEGEDDDDBGEGEFBCDCEAAHDBAGHDHFGGHEHAHAHAHFHFDFBGBHCGAGFEFEFADACAFEBGCCDBEBADAFBGCFAFCHCHAFEFGCGBGCAFABCDAFBFBHDHFHEGDGHFH,False +922,12.0,3.0,17.0,8.0,6.0,8.0,19.0,16.0,GDFCHCHAADGBHCHAFEHCHCBGBCHFACAFADGGGGGGCGCAADHEHECEAEDDCCEGFGFGAGAHHGHGCDADCCHHGCGFHFHGC,True +923,13.0,7.0,15.0,17.0,15.0,11.0,14.0,5.0,GDDDHCCBCDADAEABADADGHFDCCACAEAGGDEEEDFHFBDGCHBFBFDGGBCDDDFCFCFEEGCFEFADADACAGGGGEGCCAEBEHEGEFECE,False +924,19.0,22.0,14.0,20.0,28.0,12.0,19.0,18.0,CGCDHBFBHGEBEADBDGDGDCBCDCHCEBHGEGEHEGDFFCEAEDGCGEGFDEEEEEBABCBCBCBCBGFDFAEAFDHDHEHFDAAHHHHEAEADAFEFEDBABDHEFEAGCBBFHDHBHBGBADHEEDBDEGBAEAGGCGHBEGGAAAEA,False +925,20.0,23.0,18.0,19.0,19.0,27.0,21.0,22.0,FEHEHEGDGCBDBHBEBCAGACHFEFHAHADAFGBGFFEGECEHDGDAHAHEDCCEAGFDFEGCCBGBFBFHDADCBCBFBCCHBHAHBDCECDFHFGFADCFFFFBFADBGGHADFDBBCBGHHHEHEHBAEAEFGBHBHGAGEFEFGFGFDCDFBFACAGAEADGDB,False +926,8.0,4.0,5.0,5.0,6.0,5.0,4.0,8.0,FGFDECECEADFBFBHEHAHADAHAEACGDADHHHBHFACBEGCG,False +927,4.0,9.0,2.0,4.0,9.0,4.0,11.0,2.0,GHGBGDGBGBEAGFGBBBBDDEBGFGEGEDECEAEAGBFCEHFAE,True +928,19.0,13.0,20.0,26.0,25.0,21.0,11.0,20.0,DDDFAGCFCHADFCCECECFBEHDBEBEDEHEHCFAEAEAEFDFBFADAEAEAEADHDFDFGBGBADEDBHCGCFCBEEAEHECFHAGACCCDDEDHHHHAHDDDACGHBACFCFGDEFEBHFHFCDDDHDACECBDHGHEEFGBGFGFEDHFBA,False +929,31.0,26.0,25.0,22.0,30.0,19.0,16.0,16.0,GADBEEEAEAHACCCCFGFEHBGBGCFCFDDADGBAAAFEFAABEHADFDFACAHBHGEFBAAACFCGABEGFABGFGEGFBFBEBFDEDEHGFEECHAHADADADCHEHEBEDABHBEACADBDBDGDGDCDCACHEHGCEHDCEABCFAEDFDGCEBFBAAEHEDEBCBCBCBCBEEAEBCHC,False +930,5.0,6.0,16.0,9.0,2.0,8.0,6.0,8.0,FCFCBBGDGDBABHCHCGEBEDDGACFCFCFCHCGCABHCCCCHFHCAGFHHCAFDDDDD,True +931,13.0,10.0,13.0,5.0,17.0,8.0,8.0,11.0,AEAEAHAEECBHBHGHAEBFCEEAEBEGCHBFBGEGFACADAEGEDBFCCHHBHBHFHCGEGHDDCDCACAEAFBCGCFEFECEA,False +932,13.0,15.0,7.0,16.0,20.0,10.0,5.0,18.0,AEABBCHEBEHEFEDEAFBHBADFHHDBDEHBABABABACDCFEFHFEGGACEDEHEBBAFGHCEDEDBGCHHDBDBEHCHDADGDEDEDHFEEEAHAHFHFHD,False +933,4.0,6.0,3.0,4.0,2.0,6.0,4.0,5.0,AGAGAHBEEDCGBGBCBDFDFDHHAFBFHFCBHF,False +934,5.0,12.0,3.0,2.0,5.0,4.0,9.0,11.0,CEDBABACFFGFAEAGCGBGHGHBHGHEBBHBHGDFHHHHBEBEAGBBBGH,True +935,8.0,6.0,1.0,11.0,7.0,1.0,14.0,7.0,GEBHGHGDBAEEDAGGEGDGBGBHHHHDDAAAAGDGDGDADABCEGEHEDDFGGB,True +936,12.0,13.0,17.0,16.0,15.0,22.0,16.0,19.0,HHEDDDDGDGAFACACHCFEEECACADBGHGFFFFFFEHEHCAGBDFEFDFEFEHEFFBBABFCHEGFGDHBCBCBEEAHCCECDDBFBHCHFHFHDEDGGGDGBGHCBGAFDGDGCAHBCCHGHFHFAA,False +937,3.0,4.0,1.0,4.0,2.0,0.0,0.0,2.0,ADDEDEHBHBACADBB,True +938,5.0,10.0,7.0,7.0,2.0,7.0,13.0,13.0,FCGGGHHAFEFBFBGBABAEGGGGCFCFHBABHHDHDHFHACDBBGHGDGDHCBDHCHGBGDHC,True +939,0.0,2.0,2.0,0.0,2.0,1.0,2.0,1.0,CGEGEBFBHC,True +940,15.0,12.0,17.0,12.0,18.0,16.0,21.0,10.0,DADACBCEGEGCCAHFCDCDAEACDCFGDAEBEBEACABEGGGABACDFDCGGFDDHCGFGEGBCBDEDGHGFEFBFGGCBCEEFAFGFHFAFHGHGCEFEBHBHGEGEGEFAFAHACBHE,False +941,21.0,9.0,18.0,19.0,23.0,21.0,20.0,26.0,EGEDHBHBHGHGHCEAAGBHBDDDGGGDGFGFEFGFGADHEFEAEAFAHAEAHBFECDCAAGDFAFHEHCCDCEFHFHFAEAHACFCFCHCECEHDDGDHDHDADEBHFEGAAEAFBHCCEGGDEDBCHADAHFBFCFCGGEDECFHGAGHECEHFH,False +942,23.0,23.0,25.0,23.0,16.0,18.0,18.0,24.0,CAHDBDHDEGCADHGHGHGHFCDCHCDFGEDEDHDHBHFDFEEADAEABFFGFGACFBBCFCBBFAHCHCEEDCCFHACACABHBFFFDFECACHHEGDGDEDBHBCBHBHADABHBHBCGHACBCBEBABCGEEFEAEAGGCDDDDAGAGAHBHDGBCFGFDCAGACAB,False +943,9.0,5.0,6.0,3.0,2.0,3.0,4.0,6.0,DBDHCFFHCEAEGBGBGAHCHBBAGFCAHAHACADACA,True +944,1.0,5.0,5.0,2.0,2.0,3.0,5.0,5.0,EGGDGHCBBAEGHGCFCFBHBHBHCFCD,True +945,23.0,12.0,17.0,23.0,21.0,25.0,31.0,23.0,AHAHBHBHCHCEDDFCACDCDFGFBHBCCGFGHGAAHDEEGECFAHAHFHDHEADFGCGCGFGEADBEAEBEDDBCBHAAFAFAFDGDHABAEHDHGEEEHDADGFGHGFEFGFCFAFHFEFADGGEGEGECFDHCHDFGHGDGCAAGAGEGFDBGCEBGBGDEDHFFCFGAGDG,False +946,7.0,6.0,9.0,5.0,3.0,13.0,9.0,7.0,BEBECFHFHAHGCAABCCFGBGFFCFGFBFDFGGAGHGFFFFDBCGHHCHCDDADAEAC,False +947,12.0,14.0,22.0,9.0,8.0,15.0,19.0,16.0,GGGGGADFDBBBCHGACAHBFGHGHGFGCCFDACHGHEFFBCBGEGDGFHHHBHDGDCCCCGBFHACACECDCFGBHBHBCEFECHCBCBCHGFGDAAAADAEEFCFCACFFEHB,False +948,23.0,29.0,24.0,18.0,9.0,25.0,25.0,32.0,BBBHGFAEAEBEBCFCFAFAFCFDFBHBGCHFAEGDACAGBHCHFDBCBGGCCBBHHABDCFGHBDCDBDGFBCAFAHHGHFHEHACEGDABGBGHABABGHHHFBFCFHFABAEAGACBCFHHBABCBCBCACFCHGHCHBGBHDDFGAAFFFEDDDGDHDHGHGHGHDHGHGHDCDCGFGFEA,False +949,7.0,6.0,5.0,7.0,7.0,6.0,6.0,12.0,HHCHADDCGBGFFHDHBBCHCHBFADAEAGAFAEAHBHEEEEHHHBGDGEGCDFDF,False +950,24.0,23.0,22.0,11.0,20.0,30.0,30.0,14.0,EHFBFBFBCCFCAAACEGBFAEEBHCHFHEAEAGBGHGHGCGCFEFAFBEAGAEBGDGCGHGHBBGBGBFBFDFECAGGFEBEGCAEBEDGHAFBHBFBDGDGFGDACCGCECACAGFCECHDFBCGCGFFFGFGCBCGABADFBHGGFGDHDEFBHCAAAAAAFFFFFDEEAE,False +951,16.0,19.0,15.0,15.0,20.0,28.0,15.0,17.0,DGGFECEHGHFHCBCEHGDGCBCGCEEFAFAFAHEHFAABHEGDGAGBGEEBHDHBBCBCHFBDBDBHEDFCAEAFFFDFDFAGBCBDECFFFEFDFBFGFGEECECEFEFEDHGCDAHAEABBDGFBFHHBHDAFHFCFAFABA,False +952,9.0,0.0,6.0,3.0,8.0,5.0,2.0,3.0,EFACCCFAAAAHFFFDGAAEAEHGHECECEDECEAD,True +953,2.0,1.0,1.0,1.0,6.0,2.0,3.0,1.0,ECEHDAAGBGEEEEFGF,True +954,11.0,9.0,7.0,13.0,13.0,4.0,8.0,8.0,CADHDHDFDABBEACAFDBBHFHGAGECBGEGEGEBEHEDEAHBGDADADADFDEBEDDCAABHEHCGEGECC,False +955,17.0,19.0,17.0,18.0,12.0,19.0,16.0,32.0,GFGFAAGFGAHADGGHGEBABFEDBHBDFHHHHBGBHDHDEAACBFBFBEAEHCDDGDFHHEDGHGBGBGADHFHDHCCGAEACDCDCAHAHFHFHFHDBDADHCCCHBACACBHFHFEFECACGEBBFDHCHDHBHEFGCECHFFBHBH,False +956,21.0,23.0,17.0,24.0,20.0,16.0,15.0,22.0,DADEHFHDCBCBCAHGBGFDFDGBAFDFDHHFDBDBACACFEHEAEAHAEEBAGCHCFCFAHAGDGDADADHHGHGECCFCFGFCHAHGDGBCCHADBDEAHGCFBHBHBHEEEEEHEBEAEGDBBFBHHCDCEBBBDBDBAADGFABADFEEGEDDB,False +957,10.0,10.0,8.0,10.0,12.0,10.0,10.0,2.0,FGFBFDFCGGFGABBBDGAAAFHFDGDBDGDEDECECECECGBAEHECGDACEBGBDFCAEAFFEDEBABAE,False +958,23.0,37.0,29.0,27.0,20.0,20.0,23.0,19.0,ADBDBAFABHBADGGCCCHFHGBBDDCACACBBAGDHDHCHFECBHFEGEBEDCCFEDEFBFBCBCBHEHBGDCDGBGAGAFFGCGEGAADACADBGFEDGBGFDBHBCAHEEFFDCDADBDBACDCDCDBHBHFEFHFDBGBGEFHFHBACECEDEBCBCBCGCGBBACAGEFBFBABGDGDHEHEGBCDCBHEAAA,False +959,12.0,18.0,18.0,8.0,12.0,10.0,17.0,15.0,BEBEBGBGBHBCBCECGCGCDCFGGHGBCHEACCCEFGAAAEHBHEHBGBHAEABHGFCFCDCEABACAHEHCGCHFEAEGDBDHDCGFDCDAHBHGFDFGGGHFBBBAF,False +960,6.0,8.0,14.0,11.0,10.0,8.0,6.0,15.0,EADADHGFDEEHFHDHBHBHCECDFDBDECHFFAFGFBEDECBCECHHHHGCGDGDHCCCCCCEEDHHAHABCGFABB,False +961,20.0,29.0,25.0,20.0,25.0,26.0,26.0,18.0,BHBEFEABGFAEGDGDFFBDHDGBGBFFFHEEEEEDFAFADABGGCGCBCBAFCFABCCHEHGDDEDEGFFAAEEEEAGCGAGHGFDCCBCHGACACEDHGHGAFBFBFAHEBEBEDGBHCCEAEADDDHDCBCFHAHCHBHBFBFBGGGBHECGFGECBCBCDHDBBFDCACACBFGFGEGCDEBFBF,False +962,27.0,19.0,27.0,18.0,20.0,32.0,29.0,28.0,GEGECAFAHHHHEAEBDBDCHHGHFEFHDBFAFBFDGDBCBCGHGHFCFCFCFDEGADHHCCADADAGEHEHGACCHGHBHEHCHCHFECGCFAFBFAFGFBCAEFCDHAGFBFHGEGAAHGFGEDEACDCFHDDCDCFCHCGCEDGHBDAAFAGBFBFHEGAFACADEFEBEGGGCGCBBFBFGAGAGAFABAGFBEHF,False +963,18.0,20.0,27.0,19.0,14.0,17.0,15.0,25.0,FFACCGCGCDDHCHCDGGGEHFBCBHFCAAAAHAGFGDGAGDGHFBDEDHCBCACACGCGAFEBBCECEAEHEHBBCHHHHAACDCDBDFCFBFBHCHBHDGCEEEHEDGBBBFEFHFHDCDBDADAHFBCBABDCEAHHDACFCGHBHFHDCFE,False +964,12.0,10.0,8.0,9.0,12.0,10.0,10.0,9.0,FGFAEAEAGADFEECEHBBBAHAEBECECAGGHBAAGEHFHDHAEFDFECDCBFBFBABDDFDGGFGCCCEHAHBHGDGD,False +965,17.0,22.0,24.0,31.0,26.0,22.0,22.0,27.0,CGCEHFCFCEBDBDBEHEHGHGHFABABHEHFBEBGHDHDFCBDBEBGGCHCFDFHEHDHDGDFFBCAHAHGEEFHBHBEBADFFAFAHDHGAGAHEDDHDEBEFEBEFHFHACADDDFDEEEECCCDAGADBGAGFEHBGGHDCCCDEDGHCECDDABFBEBCGEGCGCFCDCAAEDCBGHGDFDGDCDF,False +966,27.0,18.0,26.0,14.0,26.0,27.0,37.0,24.0,AACDCHCFGHAHAGAGACFHEHABFHFAGHBCBDBFBFBABFHHHFHFCEDEFACHCECFGFEFECGDGHGCGFGEHECDCBCBGBECEDFAEECAGGFAFBHEFDGBGEGHFEEGEHCGEGDGDGDFCCCCHBAEACHGHGAGHGAGEHEGEGBCAGGGFABHDADADAGAFHBEDCFAEECFGFGFGCGABEFGABA,False +967,19.0,30.0,23.0,20.0,26.0,19.0,25.0,21.0,BBABCBGGAGFDFGHDHEGBGCGBBAFDCBCEFHDCDFBCBGEFBHBEEEEEBADAHAHBGGGEDBFBHCCCECBGHDHDFGBDCDFBEHECGBGBGFCFAHEHDGEGEFDFDECCCHCHEGEGHGBCEAGABEBABABABADADABAEADCCEFBABFECDFHFHCHFEFCGGEHEHGDADH,False +968,22.0,15.0,29.0,26.0,37.0,20.0,22.0,24.0,AEGBABEFGGEGDHDHAHEFECEFACEEACHBECFBABCDCACAHGHDEEFECECDAAAEHGHGHDHDFGFHCADFDBDEDEAEDEDEDEDGGECEABBGFADADEHGHFECBCAEAEGECECAGDBEGAACCCCCCBHEGECDCDFHFHFHFHFCGEGHBDFEBBBGECHDEFEHHGDADCGHGDDCEFHFCFC,False +969,16.0,6.0,14.0,15.0,9.0,8.0,13.0,13.0,HHHHFEFDDCAHGGEGDGDCBBHCCDADGGHAAADADFDFDGDGDGABEBAFABECDHAAFAFEFGDGCHEHCDCGCEEHHHAEACCCCBCGAA,False +970,21.0,25.0,9.0,17.0,8.0,13.0,18.0,16.0,GBGHGACACAFHFBCADGGGFGFGAGAGBBDBGCHHEHEBFDEABGDGDGBHBCDFFFFHFHAHBDACAHDHCCGAEADBHBDFABABABEBEAECGGBHBHDFBBBBAFDDAGBHHABDDADADBE,False +971,9.0,10.0,11.0,9.0,15.0,9.0,14.0,12.0,EAEDFCFBFBAGHGHGDGBHBGFHEHCFAFAGHECGCHCADAHCEGDGCGBBBBDBDEGFGCCFHEEEHEDEAEDBCGHGCADHEFEAE,False +972,18.0,16.0,12.0,13.0,15.0,19.0,12.0,21.0,BEHFBBABAHGEEAEAFAFCDEHFHAHCGCFBEAAFGCABHHFHFHCHBGADCDHDHCHCEEAGBFDFGADFFFFBFBGDGAGAEADHDHDAEEEBCBCBHBDEEHGFGFBFBDEHCHGHAHFCAD,False +973,27.0,25.0,26.0,28.0,24.0,17.0,20.0,27.0,HCHEFEACGCFDFGCBCHADFCFBADCGHBHCDDDCBAAHAEEDADGDGHGHGHGDAAEBEHAHGDADADEBEHHCEBADAHHHHCHCAAAHBFBDCGBFCHEEFBFBFHAEADDBFBFBDGDEHEHBHGCGAHACECAFBFBEEEBECEFDCCABDBDEDEGAGADEDEDCFBBACHGGFGBGCGDADCHCBC,False +974,2.0,9.0,5.0,14.0,10.0,16.0,13.0,8.0,HBEGFBDBDHEEFHFEGDBFBFBGHFAFDFGFCFDBDBDHDHBGGCFFEGEGECADGFECEHFGDCDHDEDGFGFGD,True +975,7.0,10.0,11.0,8.0,6.0,8.0,11.0,11.0,CECFCDCHGGGGHGAFCECEAECDCGHHBADHDHDBDBFBFDAHGBBBBBBGCFFFAAEHDFCHGAGHCHGE,False +976,22.0,16.0,20.0,24.0,18.0,27.0,21.0,14.0,GDBDHEGEBFHFHDDCFCDAAGEFBFEDBAHGBGBGDFEBBADGHGFABAFAFDCDCBCAHADDDCAHECCDAAFAFGHCCECFGECECEFDHCHAHGBGBGDECECECEAEAEBFBFGHGHAADDFDBDGAFCFBHACAEEFGFAFDFDFGFGDCDGGFFF,False +977,16.0,17.0,23.0,22.0,27.0,15.0,19.0,22.0,EEGGFDFHCHEEAEDEHEHGCEFGBEBEBHBDDCBAHAHDGDAEGEGDHFECBDDDHDCGCFAAAAAFCEHBBEECEFDFDBDBCCCCEFEGAFFCFCFCEBEAHAHAHAGGHGHCHCBGEDBDGEEHCDGHBCBDAHFHBHFGGDHDEDAGECECBCDCG,False +978,5.0,8.0,11.0,18.0,14.0,13.0,11.0,18.0,HFHDBAGHGEFEHCGGEGDAAFHFEFEFDHDGCECHHEHEDEDHGHDFBFCDHHHAHEHBCBCBCDCDGDECEDGDEBFGDCDEBGHFBFDCDFHFDA,False +979,22.0,10.0,19.0,14.0,19.0,26.0,19.0,18.0,HBGDGHGCGBGEFEAEFBDEHEAAHGGGGHDHDHFGEABAFAHEHCACFFDFDFAFECGCDCDCDCFCHCFCHAHFDCBGAGDEHBGEAFAHAHEFAGHEAGACEEEFFFFEFHFBFCFBACGCAFAFCBEFEGEFCGBDDDCAAAH,False +980,9.0,10.0,16.0,13.0,13.0,13.0,17.0,6.0,CDCEBDGFGFACEBDHFCEHACADBDBHBCBGACCECEFEFGFGACHCACDEEGGGEGEGDGCFFFGFDBDFGGAGAHACDDDDGEGFCFCEHBBEB,False +981,19.0,23.0,15.0,12.0,16.0,18.0,17.0,17.0,ECEDHFHFHFAGAHBHDAEFGFBEHGBGBCBHBCEDGDCBHEAGADEGHFHDBBABEBAGAGCCDADHDCGBBBEGAGAGEBBBGFGFCCBFBFEGHAEGHFCFCFCACEDHDAAAAAHDBFFHFEFCBCBEBEFHA,False +982,21.0,16.0,13.0,14.0,20.0,12.0,19.0,12.0,EBEBGBGDGEGECHCHFAAEHBCAEBHBECECACGCDCDCDBABAFABGHGHAAEAHABDEDEFHFGBCDAEAGFGECDHGFGDDDEHAGGGEGBCFDFAFBEGECEHAFDFGABADAGAEBHFAEB,False +983,22.0,16.0,20.0,28.0,16.0,18.0,28.0,14.0,CGCGBDCDCGHACGFDFDGDBDCFEFEFADAECBDDDEAEAEAHAHABGDFAAGFGFGCAAGEDEGFDFDCGBGAGBGHHHGABCBDBDFDFCFDFGCAHAGACABAFEFAGEEDEHBCCHEGBBBDBDHGEDCHCEFAHHGCDHGGFGDGDGDBEGACDCD,False +984,26.0,22.0,19.0,22.0,24.0,27.0,32.0,24.0,ADHHEFAFADABADAFABCGCGAGFGFEDADABEFHFHGHDFGEGADCCFHHHGHGEFCFCEBDGEFEFEGAFBFBFAHGBEBEAGDFAHABAEGHGCECEHBHBDCFFHBAAGAEAGBCCDCDHDHDBDBGBEDDDCBBFBGEDFDHGEGEGEAFAGGBGBHEGBGFGDECHFAFEHHFCGCGEGCCHCHAAFDG,False +985,7.0,9.0,7.0,9.0,13.0,11.0,7.0,5.0,FCBCHEDFAFHEGBGFAEAEAEAFGDGDBDBABAFGEGDCHCHEEBFCEEHEBEDEFFDFGBDBCCFD,False +986,8.0,13.0,17.0,13.0,13.0,11.0,14.0,10.0,HGEDFDFDFDHDHDHDBFEFAGAEBEDGDHHFBBEEABBBFBHGHCCBCEEGECFBACDCDAAGCFCGBGFFEAGDGHCCDGEGCGCGCHCECBCACEB,False +987,20.0,12.0,18.0,25.0,18.0,18.0,21.0,30.0,AAADFHFAADFECBCECEHEHADCDGDGDCFHFHGCGCGFGFCFHDCAHEEGDGCECHCHEBFBHGHGEFHBHFGDADEDHDAFADEHBBBEGEFHADFDBCGDHHGHGHGDGDHDGDFCFEGGFGCAAEAEBHAHADBHEAADHDCECHDADHCHBHFHAB,False +988,20.0,13.0,12.0,16.0,10.0,14.0,25.0,12.0,BBBCHGHGAGFGHGDCACHCHCAAAAAAEHBDBAFDGDGDFCGGEBAFDEDEHEDGDEDADABCBFDGAGAGHGAEDBGGGGDGBFBHAAGBGHDFEFGAEECCGFFBFGFGHCHAFFCACD,False +989,12.0,14.0,12.0,10.0,10.0,5.0,11.0,8.0,AEFEBABAHACGFBABGBGDEDGDEBBCBCHCECBCACDCGHGHGEACFCBBBEFGDDDCDBDADGEHAACHEGAGFBEHAH,False +990,22.0,22.0,18.0,21.0,13.0,23.0,11.0,18.0,AHAHEFFDDCDFGHDFDECHDHABEBCBCEAFBGGGGFCHCBCHHBEDFAFABCHCBCBCBABDDGHHDBFGEEDADFECGBAECEADADADAFFDFBFBFBFAHDFDBHBDEAEFHFGAHAHAHACCBBABGCGCFHFAFDFDEBCA,False +991,10.0,6.0,7.0,9.0,6.0,4.0,5.0,5.0,FDCBCGFHFHBBBABGDFDAGACACEEECAHDDGDEAAADADAECECHDBGH,False +992,9.0,13.0,4.0,15.0,7.0,15.0,17.0,13.0,DEAHFHGHBEGEBBGFFFAFDFDHDGDGHGHFHFDDDCEGBACGDBDGDEHEHGHGBGBGHFBABABFFFAGADHDGGGHFACBFEDDBCAFB,False +993,1.0,1.0,4.0,3.0,4.0,6.0,1.0,3.0,EFEFEFAFCEGDFHHHDFCBCDC,True +994,16.0,14.0,21.0,15.0,11.0,19.0,16.0,24.0,AHACCCDCAAFBFEFBDBAAGAHHCHDHEHAHEHEBGAGAFHFCGCEFEFEDACHCHCGGGFDFCHCDDDHDHAECHGBGBEHCFBDBGGFHFGBAFHFCDADCFCBCBCEHAHFHBCEGGGFAHBHDCDFHFGDB,False +995,7.0,6.0,13.0,6.0,12.0,13.0,4.0,9.0,CEAFHCHFHECCHEACFCFGGAGFCHCHFAFEDHHCECFBDBDGECHDFEEEEEEBABACFCFDFDFBAB,True +996,4.0,9.0,13.0,8.0,5.0,3.0,3.0,5.0,AGAEADDCACBCBCDCDEHECCFHEDBCBCDDDFEBHBHCCCBBFHGCGB,True +997,3.0,1.0,1.0,6.0,4.0,5.0,7.0,3.0,DDDFHEHCGFGFGFGEDAGAEHFDEDBGAG,True +998,18.0,17.0,15.0,15.0,11.0,15.0,12.0,20.0,EBCFCHHAACHCHCHGBCBCBCHDADAFAFEFDFDGHGHCBCFFHCACDFAFAHAEAEAEFEBCHAFBHBFGAEDBDHDHFBCDEAGABBHGADDBDBDHHHEBAGCEEHFHBGGDGFGAGDB,False +999,6.0,13.0,8.0,13.0,6.0,19.0,12.0,12.0,GDGCGCHCAFGFEFBFDEDHFBFBDBGFDADBFBACGBGDGEFBHHHHBDAFGFGBGHCFFECEFEFBAHFDFBFDAHCHDHCHDFDGB,False diff --git a/tests/results/nb_gm_002_2back_240trials.csv b/tests/results/nb_gm_002_2back_240trials.csv new file mode 100644 index 0000000..1c50201 --- /dev/null +++ b/tests/results/nb_gm_002_2back_240trials.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,ralph_skewed +0,30.0,39.0,31.0,30.0,32.0,24.0,27.0,27.0,False +1,33.0,23.0,27.0,32.0,37.0,34.0,25.0,29.0,False +2,31.0,20.0,37.0,28.0,31.0,32.0,26.0,35.0,False +3,27.0,32.0,39.0,24.0,25.0,34.0,35.0,24.0,False +4,34.0,24.0,38.0,28.0,31.0,29.0,28.0,28.0,False +5,29.0,24.0,36.0,31.0,32.0,32.0,31.0,25.0,False +6,25.0,38.0,28.0,30.0,33.0,30.0,26.0,30.0,False +7,27.0,30.0,30.0,29.0,32.0,26.0,33.0,33.0,False +8,24.0,36.0,32.0,23.0,30.0,29.0,35.0,31.0,False +9,35.0,34.0,30.0,29.0,35.0,26.0,23.0,28.0,False +10,30.0,25.0,33.0,31.0,27.0,37.0,30.0,27.0,False +11,28.0,28.0,29.0,26.0,28.0,27.0,34.0,40.0,False +12,35.0,27.0,30.0,29.0,26.0,30.0,36.0,27.0,False +13,38.0,27.0,31.0,27.0,34.0,23.0,27.0,33.0,False +14,29.0,30.0,28.0,35.0,19.0,30.0,37.0,32.0,False 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+9,11.0,23.0,19.0,24.0,13.0,20.0,28.0,13.0,DFDDFDGFDGCDFFDFEDCCDEGDAHEEDGGGGDAGHFBHFGEDAFGCHGFDBCDBDEBCHDEBGEAFBCHEFEAFBHFCCGEDGADGBCBCDACGCCGFAGBBDCGDBBBEBBECHACFAGFBGABCBBGFHHFHHFGHGGDGGBGBCDB,False +10,10.0,15.0,13.0,9.0,5.0,13.0,10.0,23.0,CAHCFDCFBGFGCFHBHAGHABAAHGFBAFDFBDBHDHCBGEFGDCBDHDEABHHHHGCFCEFCDHCFHBHHGHHGFHGBBABCABCABHEHEFHDCH,False +11,29.0,21.0,32.0,27.0,25.0,25.0,8.0,18.0,HEFAEFGCBEBDCBEADAADADCADABDHHFFEDFBCHACAAFBAFDAFDBCCCFDCEACAACEABFDCFDCFHHFBHDEFDAFCABGAEFDCDCCBCCDCDFAEFDCGCCECCBCBHDEGACBAHBEBEEFDBDHAFHAEAEECEGGHDBHDHCDEADEAHEHFEBFCBAHBHDEGAEFFCFCG,False +12,28.0,27.0,32.0,14.0,15.0,33.0,26.0,13.0,FFFAAFBAHCHHDHGCBBCEBFDGEGBFAACBACBACBAGBGBAGFFGFAHDGHEEFCAAHAHHECFBBFACFACAACDBCAEAHDFHFFCFFEFCAFBEFBFCBCABDBGGFECFGCBCDGGBGFDGDABBCCBEFBEFBAFDACGCCEHGAFCABDGEDFFDCFDGFGGCGGEEGCBGAAGCCCHC,False +13,29.0,16.0,17.0,15.0,16.0,11.0,15.0,11.0,CBECBEFBDDCDCAACAABFAGFEGACCECBEHBEGADFADFBBABCAHCABAABHEEEACEHHAGHABACGDHGDFGCHGCAGDAFAAFCCFEAEBAEDFDDGEABHAGAAGDGBAEDHHGABFEGDCD,False +14,17.0,24.0,25.0,11.0,18.0,20.0,15.0,30.0,DDCDHHAABGECDACBCCFHGEDGAHBABBHFBFFBCFHCHECHECACABHHBHEBHBHDCHCFBAHBFHBEBEDCEDEABCHCHFCHCAFBFBBHGEHGEHGHFCHACHCGGCGCDECFEGHEDFBAFGEFDAAHAHHGFHFABGEBGABGFFEFCEBC,False +15,8.0,6.0,1.0,3.0,4.0,2.0,2.0,6.0,EHBEDEHGEGFABBADBAHCAHAABDAHHABF,True +16,20.0,17.0,20.0,17.0,21.0,21.0,26.0,21.0,DEHCHAEHFEDFDHFCHGCGGCGAFBDDBDCFGEFGEFCEFHDHEFFAGDGDEGAHGFECFACFEEHBEHBGHBGHBGCECEDAHHBGFCCCADHAGHDEDBADGHEBDCHCCFAGEAFAABGABAHBAHBGHCACBEFEGAEFCECBGFDGFDGAGBAGBFG,False +17,12.0,3.0,7.0,9.0,7.0,12.0,9.0,8.0,ADGAGCADCFDFHEFDGHCEHAGGCDAHDCHDAHAFDAFEGFACFECFEBFGBAGAFFAEBDEHGHF,False +18,18.0,19.0,24.0,16.0,21.0,13.0,23.0,20.0,GGEGFBDFGDGEDAHGFBGHAGCDGCAAAHACECDECEBBEDEEDECDFDHBCCDHBHHACBACFHEAEEGHEGDEGAHBAFBEEHCBHCBGGFCGECGECBCAFCGHCBHFHHFHDGGAAEBFCBFDBCBECDCADCACGBHGEHGBFGADHA,False +19,10.0,14.0,15.0,8.0,25.0,14.0,11.0,20.0,EEEEBEEFHEHEEFEEGHEAFFAFHACGDCDDCFDCBDCBFFBCEAHEAHGCGGHGCHEEAEAHEAHEHHCCFGHABHGFGCHGCFDFHEHBBBDFBFBCEAEBHCDGCEEEHBBHB,False +20,16.0,9.0,19.0,17.0,10.0,22.0,10.0,24.0,HFGDDAFEAFEDCGHAADEHDBHAHDCGBAHBECEFFFFFEFEEDHEDCACEGHBGCFGAGGABDHFCHFCHCCDCFHHADFCFFCFFCBFCDHHHHDFFGHHDACDAFDACDCBHCHHAGHABHAB,False +21,6.0,10.0,3.0,4.0,7.0,3.0,3.0,4.0,EABBAEFHEFABAACHDCDDEFBEGHEGBDABHBBCBGEB,True +22,6.0,11.0,12.0,6.0,9.0,6.0,9.0,10.0,AEDBCDECBCHBCBBGFBGFHGEHACHAGAEFBDAECHCFHFDCCECGBCGECGAHGBHBHEBHDFGDE,False +23,11.0,8.0,12.0,13.0,7.0,5.0,13.0,9.0,EAAGACDACDHEEGGGGGBEGEABEAHGCHCCAFCFFGDHGDGCBGBDDEAFAADCDDCDDHBCGBCAFCBDDHHBHH,False +24,36.0,26.0,18.0,26.0,33.0,19.0,21.0,15.0,GBCHFHAAHAFFGBBEFBCFAEFDFGEGEEBECBEBBABBAEBEEAEEABGDBADBACFFBEFCECGACFADABCFDCDBCBBHDHHACGGEHDEGDEGAHAAFAAEDCCHHDDGDDBDGBDBDDCDAGAAFHEDHGDACDACDBGEEACGAEEBEHAFHBGAAAAAAAEEFBEDCDAEEEFGEGGHGFEAFED,False +25,11.0,17.0,16.0,9.0,15.0,15.0,6.0,9.0,CEEFABDBGDBFDFFDGADECBFCBCCACFABEABFABEGBEHBAHEAHEAECCFFCHDCBBBFGBAGCDFHHFBDFDCCHHEHAEBEGCCBFEECEF,False +26,8.0,5.0,15.0,9.0,10.0,7.0,11.0,5.0,ECAGCHDBBDCCDCGHBBEEFDHFEEEHBHGADADGFDEFGAFGAFCCCCCACCDCDGGECGECGEAGFA,False +27,9.0,11.0,8.0,5.0,8.0,4.0,2.0,4.0,FCAFDBEDBABAABAEEAEHDBHCEHCDBCFBABEEGECGBDABFCCAHCB,True +28,6.0,8.0,11.0,7.0,10.0,5.0,9.0,9.0,CFBCBCCBACBEHBEGCADHDGFEGFHGHDAFBAFBEDCDGCHGAACHCHBCEEEEDHEDGEGGH,False +29,24.0,16.0,18.0,25.0,13.0,19.0,26.0,18.0,HEFHCDEGDHFBACGGDEHDGHDGFDEAHFDHGBHEBGEGADFFGCCGDHFBFABDACDABAGFGDAGDAGCAFFAGHHCDHCHACEDDAFDCCDCAECAEDGEDGAFGFCGFAGBBGFBDBBAABAAGADGAFCHBEEGHBGCBFCGFAHHCHDBDDE,False +30,6.0,5.0,2.0,9.0,2.0,4.0,3.0,8.0,DADBAFBDFHDHHBAHEADGFBHFGHEAHDHBDGDCADC,True +31,19.0,18.0,16.0,13.0,19.0,13.0,14.0,15.0,FCHGCAEHAEBDEBABAABHAFEBDCBDCBHCGEAGEFBAFCCECCBCFHEHGEGAEDAECBECEAFEBDHBDEAGFGHDGCDGADFAHGCFCBFDEHEGCEABFADHAFHGBHABHBHDAEBGDFG,False +32,7.0,12.0,12.0,10.0,7.0,5.0,5.0,9.0,EBDGBGBBDCBACGHBDAAHEBGCBFHBFGAFEHFCCCHDCHDCHDAHDCDDEBDEAFECBAHBECC,False +33,1.0,4.0,8.0,1.0,4.0,4.0,5.0,3.0,GAECEGFBHFGHBGCBFCECCECCBCHDGF,True +34,5.0,4.0,6.0,9.0,13.0,13.0,5.0,7.0,CHHEFFDFFDFFDFDGGDFGDHCEAEAHEAFEBFCFEEFEECAECHCHFDEBDBGEGABDEH,True +35,3.0,2.0,3.0,3.0,5.0,4.0,0.0,6.0,CBDEEHHEAHCAEBDFADFHFCHFEH,True +36,13.0,2.0,13.0,8.0,7.0,6.0,16.0,9.0,DEGDECDHGAHGEDGEGACAFCADGACGACHFDACHCCHCEECGHDHBEGGGGCADCAFAGFGGBAGCAHFHFA,True +37,18.0,19.0,17.0,17.0,13.0,17.0,15.0,23.0,HBCABCGHCEEADEDCEDGAGFFFHDFADHHBHHGCHFHHAGHEHEBBBDEFECFEBHCDAADFGDFHDCDCCDCCFACAACHGGBGGBFBCFBFFCFGEDABDBBDAAGAABACBEGBAHAHHFGEDGHDHHEBHBHF,False +38,4.0,6.0,5.0,9.0,6.0,4.0,4.0,6.0,AGDAGHABHCEEFBEFDEHDBHDECDFCDBHDEGBBGCCADFDH,False +39,3.0,5.0,6.0,8.0,8.0,2.0,8.0,6.0,DCEDEEGEEGAAFEHFGHDGDBHDBGBBGECECDGHBGCDDCHCAH,False +40,0.0,0.0,1.0,3.0,1.0,3.0,5.0,1.0,GDGGDCEHFGFDGF,True +41,20.0,19.0,22.0,21.0,30.0,22.0,10.0,26.0,BADBABGCFGFDDDADEFHAAHAAHEAHBBHECFGFDEHDCDBBBHGEDEECCDCCDGCHHBGHCHACFDCFCFEDFEDAHHHBHAECABDABAAEHFEADCFEBFAGFGEABECFEFFECEEFEHFEHEEHDHDCHBBHBDHCEHCDHBDCFAEFAGHEGECBCFEEFE,False +42,3.0,7.0,4.0,4.0,5.0,2.0,5.0,3.0,EBBEAEEHDCHDCGDGGBACBEHBDGBAFBFCG,False +43,21.0,15.0,21.0,27.0,18.0,33.0,14.0,23.0,DDDDDDBCGFEFFABFDHDAGCEFHHACHGBHGBEFEHFEHFCFFCHDGHDFHDAGFECCCAAEAAGHGDFCHFCHBBBFABDEFDFFBBDBAAFDAFAGHACHACEFFEFDHABCAFGDFEDCGACFADFDDFBHFAFFBEHBEHFCHEADEGHEGCDGHDHDEECCFCCD,False +44,27.0,34.0,20.0,19.0,15.0,29.0,27.0,26.0,FGCFGADGADGDDBDBAFGAFDHHHAFBAEEAGGBDBFCEFAHFAHFAECDCBBCGBHAFHABHDCHAHHGBCGECFDCEHCFBCHBGHCABFBCFBEHBECBAHBGDECHFDFBDEAFBBGECGEBBHDBHDBEABEBFCDFHHFGHFAFFGCACFGDGGHGAABCDBHBGGBGGFHGHGGBEADABFABAAFAFF,False +45,15.0,12.0,15.0,7.0,7.0,15.0,11.0,5.0,CAFCDGCFACFCCFACGBBGCAEAEGAHFADBCHACHFCFBEFGEGBDGBDGBEGEHAEFGBFCDFBFBHACAFCAFGABDAFACDB,False +46,12.0,10.0,7.0,5.0,4.0,11.0,11.0,13.0,ECFFHGFGGFCGACGFGGAHFABBHDEDCHABFBHGAHGAHCAHDABDFHDFGCHGBEABAHEHBFHBFCBAA,False +47,15.0,6.0,13.0,11.0,17.0,21.0,13.0,9.0,EDCEFAEFAFFAGHCFCEEAFGFFHFDECECCEGCDGHDGHDGHACFFCFFCDFEHEEFEEGHEDAFBGEAAHAAGCABAEFAFDABGFCFHCDEDBABFGBGGD,False +48,11.0,17.0,17.0,9.0,17.0,17.0,13.0,15.0,GAFGHHGCHBCACCFBCFHHECHBHAFHEEGBAFCAGHGEFGEDGFCBBEBGABCFDCFDCFDBEEEGAAHDAEDFECBGCBHDBFEGHHBFGBFEBFCBCCHEFAEDAEDCEFHB,False +49,13.0,16.0,15.0,12.0,16.0,9.0,12.0,15.0,BGCBAEBCDBEDBECBDCBABDCDFCDBCEGDABDFFEHCEDGECHACHEBDECDGHFFHFHEAHAHHEFFBAGAGHCHCCHGCEEAAAAGEEGDEGBFGBAGBHHBH,False +50,13.0,6.0,16.0,14.0,12.0,13.0,9.0,12.0,DAEAAGAAGCHCCHDFHEFCCBEGFEGFHAHEAGBGCBFCBFCDACDAFDCHECEBFBAFCFFDEHAGHDEFDGCDECEHCHDGADEHHFADCDD,False +51,22.0,27.0,26.0,19.0,24.0,22.0,28.0,20.0,FDCGDAACFACHGCDGEBFCBDCBGBEGBEGAGGFGGCHGDHGDCAACHADHCFHAAEEBBCBCCBAEDAGBFGAFGEGGDGHCEEEDEHCBBCDECEBGEFCCHCFBCFBHFEABEBDEDHABHDBFFFCEFCEDHFFHBFABHAGGECAEADBGGEGAABHAGHAGEFGBFBFHHDHBEGBFCCDD,False +52,19.0,24.0,24.0,17.0,11.0,20.0,12.0,18.0,FBDFCFECGDCFBBFHBFHBAHECHAAHAFCAHCHCFBDFCDHCDBDDBAGAAGAGHFGBDABCFEEAHHGDHBDCCGCCDAEBAEFEBCHBHECHDABFFBHECFDCBDBFDGGDBFABGHBGFCFCBDCBACBFGHEACEACA,False +53,11.0,13.0,7.0,11.0,11.0,7.0,5.0,12.0,HABDABEADFFDABBHBEDAEDACBEHBEGBDDEAAHAHGBHBDEBAEDECCHFDHFGHFGHFDCCEBHEBHGCACF,False +54,11.0,20.0,14.0,17.0,12.0,15.0,15.0,22.0,DFABFDGCDCDDCBHCBECBDHHHBEFBGFEGHGFHEFEAFAHDBHDGDGEDFBAFBGFBGAGGHHCHHEDBDDBCFFCGFCHEEECDDADHBHHCDHCBHFAEGBCBBAHBAGEFGAHABHCBHG,False +55,17.0,24.0,24.0,12.0,23.0,20.0,17.0,26.0,GAECBGBFHAHHEFEGCGFBGBCHHADCACHBGGBHBAHBAEFAFGGFBCCAFCFHCGHCFHCBEFBEFBCHBGFECFGDHBEHCCACGFHEDAEBAEDDEDCEHBEBBEGEEHHACHECBDFFDFADFAEFHCFHCBECDEHDEHCBAGBAGADGBCBHHEH,False +56,17.0,25.0,29.0,22.0,21.0,19.0,27.0,22.0,FFFFFGGHDEHDFGAFGEEAFEGCEADDBBDHDCHECDGCDAAFCDHBGCBGBBECCDCCDAHGBHCBGCHCCEFEGFAABBEHFEHBCGFHGCHBDHCDHCFBDEBEABEDBCDGCHCCFGCFDAGGBGBBCBFABFEGGADGHEGHEDFBBCBCGACDAEEABDADGGEGHEGCCHHAHH,False +57,12.0,11.0,4.0,15.0,9.0,3.0,6.0,8.0,HABCEHAECBEDEDDHBDGAAFHAGCBGBEAAABADEADGHDFBAFBDEBEEBGDCDDGDDHDAHDBH,True +58,9.0,8.0,9.0,9.0,4.0,9.0,12.0,13.0,CAGCGGCBAHDEFDHHGHDFDBFBBFGAFEBFECHABGGDGDEGDHGBHADGFDCACAACHBFHFGHCHHCHA,False +59,15.0,19.0,20.0,23.0,14.0,16.0,21.0,18.0,GDGGBGGCFGABBABFGEFGCDDCFBCDBEBACHABGEBCDCCDFDDFDAACEBCEGGGFHHFDHGGHFGADHFHHGDHDFFGHGGHDEBDCAACGACFADDHDDCBDBBFEBHDDHFCEGBEHCABEAHEAHEFCCHBAEBCEDC,False +60,9.0,8.0,2.0,6.0,8.0,11.0,5.0,10.0,FEBDCDFHFEHFEHEGHBHFBHFEDCHBBBAGEAGEAGHADABFHFFDBFAEFADAAHG,False +61,26.0,25.0,20.0,16.0,13.0,13.0,17.0,12.0,CBACHGCFDHEBHBBEBBFAHCCEAEEABDDBDGEGADGHDAHEABBBEFCFFDEFDAGDADBBHGGCEGBAADABCHGCHGBDBBGCBGCHFAEFCHFBFDDCAACHACFACAACABFEBFAAEGGCGBCGBAGBDDACAA,False +62,9.0,9.0,5.0,7.0,5.0,5.0,11.0,6.0,FAADDAGBGGBGBCHBCAGEADACGAHGACFECDABBFEFDGGDFGHBGHDEHBEHB,False +63,7.0,8.0,8.0,6.0,13.0,12.0,11.0,4.0,GGBDGFEGCEGCECHDCFGFGABGFEHFCGGBHFBHEGEEAEEAFEDBCFBDFDEADACBABFACFEEF,False +64,20.0,11.0,23.0,13.0,16.0,11.0,12.0,18.0,AEDAHACHEFAEFAHCAEDAEDCBAGGCBGFBCHCHFCEACHCEHCFHCEAEAAEAHCAGBDCDHCEHEGBFCHHCGHFBHFAAGEADHBDCADCFDGFDCHDCBGCGAAHCGFGDEBDEBECB,False +65,19.0,12.0,22.0,18.0,18.0,14.0,20.0,17.0,CCDCCAFHAECADDGDGACGADGHDFHEBGEFEAFDHBDGBCGCFHBGHEGAEGBDHFDFDCGDHGDAGDCBHEBHEBGBAFHGCGCCFEEFCDCCDCHECHFCFAAAGECHBBEEBHDAGAAEAAEAHEGHCFCEFGAD,False +66,26.0,13.0,22.0,33.0,10.0,21.0,25.0,20.0,CDFGDFAHFEHDHBBCDECDAHDGGGFBCDBADHHDGADEBDEGDHFFCFFDHDGADHCFHDAGEGCEACGBGGEAGFAGBBDABCABGADGAHADDADCADHAFCFGDGEFBEAHDCGDHDCADFADFGHCCHGFHCFHGDHGHGECCCCCADBFDGAABAFDAFDAFC,False +67,3.0,0.0,0.0,5.0,2.0,3.0,2.0,1.0,FDFEDHDGAFGADEAD,True +68,21.0,30.0,10.0,18.0,20.0,13.0,15.0,10.0,ABBHBEEEHDEHDGFFGDBDBBCABFGDCCDHFHHAAAAABFAEEDBEDBGBBEABEABFBBFBBDDAEEAGCFHEBAFAGDGGBBEDBHDFEFEEBEEBABDHBFBGCBGCGGBGCCGCEGAADAABCDDADEAHF,False +69,23.0,30.0,20.0,17.0,29.0,22.0,24.0,20.0,BHBBFBBEEAEGAEHBCABCBGCGEFHEGHFFBFCBFCHEEDEGCCGBCHFHBAACDGBFBEAEAFEHFEHGHGGACBEDDDBDFBGBAGBAGEDGEHAEDDHGDFEDFEHFACCAEHFBCGBCECFGFFAEGAEAHHBGABGAEGDCGDCHDBBEFAECDHCDHABAFBACBAFBFGEDEEHGB,False +70,16.0,21.0,23.0,21.0,35.0,31.0,21.0,19.0,FEGHEGHEHFBHEBDEGDABDAGFAGCDGCEAEABGGEFEBAEBHDFEFACFEHFHHEBFGGDGBAGBAEEAFBACBCBDFFDGEECFEDFEAFEFFEDFBBFHFFCGFBFCECEHCHFFHGFDGFHECEGCDDBDDEECCBDHADHADEEEECDBCBFHGFHGBCGFCHCCBGDEEAEHAECDCCF,False +71,21.0,21.0,25.0,23.0,34.0,29.0,19.0,27.0,CGCABAFBECCEGAEFEEHEDHEFBAFBFFGFDCBDFHDFDDHCCAEGAEGEECFCDFGDHCDAFDFFHBAEGDECFHHFHHEAABFABAAHCCCCHHGBBCBHGGHEFDFFCGFDGHDAHAGHCEEBBEDBEGEHBEGCHAEHDEHFEBDECFHABHABAAFDDFDDFBEFGHGCEECFDCDCEECEEAHEGHEFBBG,False +72,26.0,9.0,19.0,24.0,24.0,27.0,21.0,27.0,DDGBDCADHEDABHHHAEHAHDCHDBFFEEFAEFAHGACFFEEDHACFCCFGCDACDCCDCEDBADHFEGDHDFHGCHFAEFHDFGFGEFGEGGEHEHHAHFEHCAAEAFCHDCFFFGABAFEAGGBGHCHDFHDAAGAFCADGADHAGHBGBBEEEGEEFAEFAEFCGDCFDHGDH,False +73,24.0,24.0,23.0,19.0,22.0,18.0,26.0,30.0,HGFHGHHBBHDBAGCEDEHDHCDAAGCBCCHCCDGGHAGHGHHFAEFGEGBEBFDFAEAHBBHBDCBDCBCCDECHHFHDDHCGAAAAEAEEDBGDBGCFACGAHGDFGCGHABBACBAHGHHBHGBEDDACFACFEBFGHCAEBGEBGEDGEDHEFFECEEAEFGGHHFBBFCHFBAFGAEHACD,False +74,26.0,17.0,19.0,17.0,28.0,19.0,13.0,23.0,EGCAHEHHEHABADBADECBECEEABEACFACACFFBFGBFBDFCFCCACAHEBHEGHDBHBBAFEADEHBCHEEHEGBFGBFDCGDEFDEADEDHEAAFFEFFHHFACDCCEAHDADDEEEFAFGADBHEBEAGAGDAHBCHCGHCAHGACGEEFAHGHHD,False +75,3.0,1.0,2.0,0.0,2.0,1.0,0.0,4.0,EAHBCHCAHEAHF,True +76,10.0,5.0,4.0,6.0,10.0,5.0,10.0,8.0,HGHHAEEAEDAECGDCAHGFBGAGEFGFBEFAFCGCEAEEBGEBGDDHDBHDAHGAHA,False +77,6.0,2.0,4.0,1.0,4.0,1.0,1.0,0.0,AACCDECAEBAEBAGFECA,True +78,26.0,21.0,24.0,22.0,21.0,23.0,16.0,22.0,AEAFDAFGAFHAHCGFCGFHDCBDCBABADBCDGGFGHEBBDFBFFDCDEAEEGGFHAHDCDDBGEHCEFCHFGEFDADGFHFBDFCCCBCGBCABDFHAEBCHBCHBCDECEGFFAHFAHFCHFDDCAEHAGHBGHBAEECDDDDAABAHECHEBHEAHABGEBAEACEACEAF,False +79,23.0,23.0,29.0,21.0,13.0,23.0,22.0,17.0,CDHBACEAHEFDEGHAGAAGFAHFADFCBBBEFBCDGFBCDBDHGGGGCGFBDBBCFBFDEGEEHEGGBGEHFCCFCBDCEDAEABFDHHBFBBCAGDDCHDCHDAHBACAGCAGCADDBDFHAFCAFCGHDEBGHBCHGCHFBEGBFACFCCACAADACFACFCCFGFDG,False +80,12.0,12.0,23.0,9.0,27.0,13.0,18.0,19.0,EGFECEECHEBEEHHFBDCGCAACFBCGEHEEGCEACEGDEADAGBAGBCDBFBHFHACHCDHCDHCECCEGFHGFBABCGDCBDCEACHBCGGAEEAECFEHHAFFEEFHFCEFCHGGGGDHBEHGGHEEHE,False +81,25.0,15.0,14.0,17.0,20.0,16.0,15.0,15.0,DGDFFBFFCAFHADGAEEAFDABDEGGEBGDGEDEBAHAAEGABAHCACEACAHBAGGECFCDDEDBEFHEBGAFCAFCAHDEHDAFAGFCDBCHCCHCEDBGFGHBADBHGBEAAHAAHAEFECFEDFEDHEBHGB,False +82,23.0,16.0,15.0,28.0,9.0,16.0,15.0,26.0,FAHGHHFHGDHGDHDHCCHFBHEDGDGADGBDFDHFBBEDBADEDDBDHFDACDBFGBFAHCDDDGDBGBBGAAADCHFCHCDGABFHDDHDAEDCEDCGDFEAAEACHHGHDGCFFCHABHAHHAFCFHAAHAACBABBHFEAGEAC,False +83,16.0,17.0,21.0,14.0,11.0,17.0,24.0,19.0,EGHCBBCBBHFAHAAGAFGHBCDFAGFBDABDADEEDBCDBCHBCBGEGFFGFGGCHGCGGHHADHDHCDHAFGACCEHDGHFFCDFEDAHDFFAFFHEGBDGCGCBECECHBGHGGHCGBCHBCEGFGGFCACAABAE,False +84,25.0,24.0,34.0,20.0,21.0,23.0,18.0,22.0,GCCGAFHHFBGFBCFBDFBGFCGDEGCAHEBCAFCBFHEFEDCGFCAFCHCHBCHEAHAFBAFDAHBHBDGAABAFBACACHHCFDAFDGBAHBEBBEDFCFECAEBGFHECCCCCCHHEEHAAFDGFDHBDGBEFBEDDHDDEBHECCECCEBAEBAGACGEDGADCBCCGGCDEAGCADCAFHHD,False +85,14.0,17.0,15.0,14.0,15.0,14.0,16.0,10.0,GGCGDDEBFFHGFBGFBHFHHEDAACAABGFFFCDBGBEHBEDBFDBCDCDGCDEFBCHBEGBEGBEFHGFBAEBCEFAAGGCHCCFCCBCHEHEAACADDEDDAGDAGEAEBAG,False +86,5.0,2.0,1.0,1.0,1.0,1.0,3.0,1.0,ADFAGGAHGBEABCA,True +87,28.0,33.0,23.0,19.0,20.0,25.0,30.0,22.0,FFGDBGHBGEGAADDHGEEDEHBBACDFCGFCGEHFBBFHBFBCCGCCFHDFCGHBECBAAFFDBBCBECGGFEGECCAGABBABHAEHBBHBHDEFDCHDBAFFDDFAAHAAHCDFCAHEAHGAHFAHAGHAGAAGEEDFGBEBECBGCBAFBGCCGAFAAFHAGGFGGBGGBDEEGEGBFGBFHBCHBDDBDDBECCA,False +88,27.0,30.0,28.0,20.0,23.0,12.0,23.0,29.0,EGBCBBCEBCHHGDBECBCDBEDGEHGAGACGEHGCDACFECFCBHBBFDAHCACBACBEFGGAGGADAAEBAHDFHDCDBAHCHHBHABGCBEEDHGHHGFHAHDAEDABDGCDECDBADBHHGHHGFGECBEABDHFDGAHEACFGCAGCABCHBFECHCBFCBFAEABDAGEHEEAECABDHBHHCEBG,False +89,14.0,15.0,7.0,17.0,10.0,11.0,15.0,9.0,CHBADFABGHBGFGGAGGADGDEBHADHGHGFDFDDCDBGAAGHAGFAEEBBEDBEBCEBFAFDAFDFGDEADEGDFACCCGBHBBHABHDEDCBDFE,False +90,5.0,3.0,3.0,1.0,8.0,0.0,6.0,3.0,CCACEGHEGDEGBBAHEHGBAGEAEEAEG,True +91,0.0,0.0,4.0,2.0,4.0,2.0,2.0,1.0,GDCFDCEECGEHFEC,True +92,14.0,4.0,7.0,10.0,8.0,6.0,12.0,5.0,DCDAEFAFCECEEAFEDFEGCCGACBDGHFAHBGEBGAGGAGGDGAEGHHGAADAFDADDCBAHDA,False +93,10.0,8.0,8.0,3.0,8.0,14.0,16.0,15.0,FAGFDGHDHHEHEEGGFFACFHEHACCACHFGHFGHCGCAGCGBCFFEGFGBHABHFDHGBGBHABHAFFAGFEHEEBBAGG,True +94,21.0,25.0,21.0,30.0,27.0,13.0,12.0,17.0,HHBEBCAACEABDGDGBDFBGFCAEHGDCADCHDCEDFEDCEDGDCEDAEGEHAADBBDAADHCDHDFHBEEBEEBCEGAECDEBBCGAHEBBFFHEBHEHDAHDAECFFDFEDFBDABDCCACEDEBDHDDAGFAEABECBHGFDDFEDCCBHCBHGBEGBACBA,False +95,4.0,6.0,6.0,8.0,7.0,6.0,6.0,9.0,EDGEBHEFHACBBCFEGHCHDAHDEHDBHDBDDEHFCGECGFGBFACFAHGD,False +96,8.0,5.0,5.0,6.0,5.0,8.0,12.0,12.0,AFACCAGAGGFBEHEGHECFDFFDGFHGAHGHHFDGAGCAGEFGHBBHEBHDDHDHHGCBA,False +97,20.0,25.0,21.0,20.0,27.0,26.0,25.0,26.0,BFCFGDFBECHDCEBGEFGBABHGDDGAFBEBCEFEEFGDAHFBHEHHCHDDHGEFDFFBGBBAEGCCFDDABEBBEBFHBHHBCCECEDCAFCGFGHFCBGHBEAFCBFDEEAEEAFECEBBGGAGHBDHFHHFHHFHHFHHEEHGCDABGABGACGAFGAGGDDEDDCADCFGAFGDCAHEAHEAEGC,False +98,4.0,3.0,1.0,1.0,6.0,1.0,5.0,3.0,BBAHAEDECGEAGBAGEEGHEGHF,True +99,21.0,17.0,15.0,21.0,17.0,23.0,10.0,21.0,AHDDHEDGFFGCFHDHAGHGHHDDFADFABHDBCCACAAHGDDFDDFGBHEBHBHEEHEFCFFBBDDBAABCEEHDACDHCEEAAEBHBFABFABCABFFFFDFFDFEEFCEHCEBDEBFCAGAGGDGCHBCHAAHEFFECAADH,False +100,21.0,17.0,13.0,22.0,21.0,22.0,21.0,31.0,GCAADDGBDEBDABDGDGGEADEDDFHHHEHDGHFGHFDHGAFAHEHDCHDHFEBGEACDACGABGABGFGGDGBHEEHEFFGHFABDHEDAECBFHAGHAHBAEAAEAFEHFEBGGBCFDFEEAHCHHCFDAFDCFDBFHBAHCHHFFGEHDECCGCBHFHHFBHBE,False +101,3.0,4.0,2.0,2.0,2.0,1.0,2.0,2.0,BCFBEABEABHADGCHGD,False +102,3.0,5.0,4.0,4.0,2.0,1.0,3.0,10.0,BGHBGHCCHCDHEHHABDFHDBHEGCDAHBAH,True +103,22.0,16.0,17.0,17.0,11.0,10.0,13.0,12.0,DECDFCDFEDCCBCCBCADGAGFAEAAHHCGECAAFHAHBAGEFDEFHHGGFBFCBACBABDACDAHDAGDGBDBADHFDBCEHGEHGDHABGBCEDEEHBAABADCGGCFCABDABA,False +104,12.0,15.0,10.0,16.0,25.0,15.0,20.0,17.0,GBFDCFDGDDBHDAADEBGBDEBEEFGHFGHFGHCGHEGDEADHBDHGGBGHEDCFHAAHACHGGEGGEFEBFGADCCEBHEGFEHDEHEEFAGDCHFEEAEEBCEGEDBEDBECBFFBHHCAFAEGAFB,False +105,7.0,10.0,8.0,8.0,6.0,8.0,6.0,10.0,HBEHAGHFGHBGDBAAGCDEHFEBEHBEBCABAACDFHBCHDFGDFGDFHCHCCACBFDBEDF,False +106,17.0,20.0,9.0,15.0,13.0,17.0,14.0,15.0,FBEAGDAGAABAHBGEFFBFFEDHEGHEGHEFHFDBBCBBDBCHCAHGAHCHBEGFDGFAEBAEGADCAHBDFBDFDFBABHEFGBCDAFDBCAGCFBHFBAFAEDHEDCEDHBDGGHGA,False +107,5.0,5.0,1.0,5.0,1.0,5.0,5.0,2.0,FABAAGDGFDFHBFEBAGBAGBFDDHGDC,True +108,17.0,16.0,20.0,15.0,16.0,19.0,21.0,30.0,CBHCHHDDDGADGAFCEHEBHEFEAAEBHFHCBGFAEDHEFEFFCFFAHEHHAHBGCDCHFGHBGFCGFBEABFBHHGHHGCHEAHEADABGHBHHBDHGDHGAGGBGGEFCFFCDBGDFDAECEECGCAGCGDCFDFHHAHHDHBBCCACGAC,False +109,19.0,26.0,19.0,10.0,27.0,23.0,8.0,14.0,EBCAAAGFADFADFEFBBBCBEABEABEAEEHEEHEECEBGACCAFCBHCDCCECFBCAGGAFEAFEFBHHBDFAHEHFEGFHCFBBHCCABCHFFBFFBDGCEGEBAEGCFFEEDHFFBFBADBDBBDBBEHEEFCHACBAHDEE,False +110,19.0,10.0,10.0,17.0,15.0,14.0,13.0,9.0,EACEADEDDGDAEBCFACEAEBFHFFGDFEDBBGBHGCADCFBBBHCAHEAHFAHAAHCDGCDGAEGAEGEDDFGEAEBAGFCGDGDDABDFCDFGFFAAEDFEHAH,False +111,6.0,10.0,13.0,9.0,4.0,7.0,3.0,10.0,CCCAFBAFBEHDFBCCBCHBCBCGHDAHDAGDCDFCHCEHDAFDFHDHHDEEBFBAGBCHBC,True +112,14.0,15.0,18.0,9.0,20.0,11.0,10.0,7.0,DEFDEFBEACFGEFCACCBGGBHAAEBEHCEGGEDEEFEEDBECBABGADFADFADGCHCCHCHACEDHEGAFAEFBFBAEACCAEBBGBBGEBEBHCCDCCFC,False +113,18.0,25.0,13.0,24.0,29.0,22.0,19.0,30.0,HCAHEABDACHBBDDHADBEHEEHCABCFBHFBABBABDHBEHFGAFGFHCHGCAEFHEFHGHCGCEHDDFEBFEFFDDHDEEDGEFCBGBDGAHHCHDCFDEEDGCFHHFEEFGBGGEEHBFAGFDHBEGFEDCEDEBDEFHEAHEAHABBEDBGFBGEHGAHFADBADHADHEDBGGB,False +114,13.0,9.0,15.0,32.0,17.0,18.0,11.0,14.0,HDHDDAGGFDDFHBFBCAEDGEDCEACDDEEDFHFAGFDECDCCDFADECFECHDCHDGAGAHGHDFEDCEDCEHBHDAHDCFDBFHHGDBDAFCGFAHFDCCDAEDGEDEEFADFAGFBBDEBDEBDF,False +115,21.0,18.0,26.0,25.0,21.0,27.0,25.0,34.0,AACCECDFFBBDABHAGHGFHGHAFHBFHFEHCBHFDAGHAGEDBEACHDCAGCDCCDBEDBDDEGGEHGAHFAHDBFGHFGCDCCFCBFCBHCHHFFDFGEEEDHFHHFHDFEDFDCBHAGAAGHBEEDCFFCHEDAEBAGDEGDEDBFBGCBECHCGHCDAGGAHGHCGHCFHBFHCFHDADAEGEGHCGAFFEH,False +116,25.0,15.0,25.0,18.0,19.0,11.0,22.0,30.0,BGGBGDHGBAECHEFABDHBHHBHDADBEEGFGGDGCCGFCHHHAHAFHBFEEGEAHCGEAGDCCHCGDAGBAGBAEADBADHADFCGHEDHCABCHHEHDFHFAHEAHCHCAHBDHBGHFGEFCAGCHGAAACAACHHDHCCGECEDDFCDACDACBCCEEGEE,False +117,28.0,24.0,15.0,28.0,23.0,30.0,14.0,19.0,CHACHAGEBEFDCFAGFADDEDDBDGBDBFEBEDHHDGDECDEBFABFAFFABAAHHAHHDFHFBHDBEDADCBGHEDFFDEDDEBEBAGADDFFFBDFBFFBFFBHACFDBFDFAEBACBACGEGGCFAFEHEAHECHBDGGFCAECFEFHEHHAGACBDCBAHAAEAAEDECDAFGGFB,False +118,0.0,3.0,1.0,0.0,4.0,1.0,0.0,2.0,FHBBEEBEECH,True +119,15.0,14.0,10.0,15.0,7.0,12.0,18.0,9.0,BGDBGBFEBDCFAFFADCGGAGDABAAHHAHHACEBCDDCBDAGDGBBGDGDDACEFCFFCGFHGBEFCGACHAGAGHAGDABBEEFHGFBFDBEDGHDG,False +120,18.0,23.0,21.0,12.0,21.0,14.0,26.0,15.0,GBBHAAEBAEHEEFEGFGCAECABAGCADBEFAAGDABCAGGFGGCHGCHGAHEAHFFCEHCEBBFBBEHBCGECGACGDCGDHGCGGHGGDDGHACBBGDBDECDCFABECFEBFECEBGBBEDDEGFCDFEGBHGBHAHFACEBCHBF,False +121,18.0,17.0,15.0,11.0,14.0,12.0,17.0,17.0,AGGAFDDFCDBBHECHBCHADHCBACFACDDGFACEBCBBGBHAAHEAEEHGFGCFGBHEBAFHAHHADHBEGBHHCEFEEFGHFGFGCBDCADGBDHHEBEBBAADAAFCAGCGGEGGEC,False +122,19.0,12.0,14.0,16.0,13.0,13.0,22.0,12.0,DFAEFDEBHGFEEDAEDFGGCGGFGGFGGAGGAFFDEAGEAGDBBABDHHCHHBDHBDGCGGDHDAGCACCBFCBABHEFHCCHECBCGDDAHDCEEFACFBCAGDAGAAGAEFAGDBEHA,False +123,3.0,8.0,5.0,11.0,9.0,10.0,4.0,11.0,EBFFHHFADFCHFGHEGHFGFACDEDDEGHFAEDHBDEBDECDCDDFHBFEBHHBCEBHDB,True +124,4.0,5.0,6.0,11.0,9.0,6.0,5.0,8.0,ACEACEADEDEHDCFFCDCCEHHEHEBHGBDGHDFDFEGFEDBHDHDBBGFAGD,False +125,11.0,14.0,19.0,12.0,21.0,14.0,17.0,9.0,CCDCBDBEDHEGHAFEECDGCFGCEGCBGEFAEDACCHCDHGFEFFBBEABEAHHAFCCFBFFCFCBEGDACDGCAEBAEGGEDGEDCAGGEDHEBHBBACBHGFEGEGDEGEFCBF,False +126,7.0,15.0,16.0,15.0,17.0,19.0,21.0,17.0,CHHHDBCCEFEEBEGBHFEDGEBFFBGFGHHGHHGEHDHCDHCDFAFFDCABAFBHGBCGBFHBDHCEGAGGHHGDEAFECHDBFGBDBCDECGEFEEBECBDFFDECGGCGADGEDGFGCFGCFAF,False +127,1.0,2.0,2.0,2.0,3.0,3.0,7.0,2.0,BEGGGGACFHCFHEFDGGDEGB,True +128,24.0,27.0,28.0,25.0,25.0,12.0,31.0,20.0,GGGBGGBDBCDHGACGEHDCHDCBDCHHEHBGHADDADDEBGGHGDDEADFAHFAGGEGEEABEHDEHCEBAEBECBACBACGACGADFADBBBBFCCAEGHFBEBCAAHBCHFCEFCDFCDCCBAEGEGCAGCGCCGEHFEHGCCACAACBDDBHGBEBDAFGEFGBBGHHEDGDABCGFHDEGGEDEADB,False +129,8.0,19.0,18.0,15.0,11.0,19.0,15.0,9.0,BEEBFHGAACFBCEBFHFADFCDHCDBCGBGGEGBDAADFDCHECHECEGCFGCFGFBCFGCAGDFGFFHHBDDFCDFBBEDBFDGDBBFBHABCEBCDAEGCBFHBFCGECGD,False +130,19.0,16.0,11.0,13.0,12.0,17.0,19.0,19.0,AGFEGFGGEGDAFDBFDBCGACBHEHHAHHDFADABHAGHBFHDFCDCADEEFEGBDGBEGADBAHFGBDGBAEFAGFBCAECHGBGFBGBBFBHAHHAHDEGEFAHADCACCHCEHGAHFHGFCF,False +131,4.0,4.0,2.0,0.0,2.0,2.0,3.0,2.0,FBECAGHAHCAGBAGBEFB,True +132,21.0,22.0,26.0,22.0,19.0,22.0,19.0,31.0,HHACHAGHDFHCACFECAECGDFFDFCAACEBEDHHAHDCGBCBBCAHCAFCDBGFGDCHBHECHCFACFGCHECBBCFBGHDGHEGHDGFBAADFGBGGFCGHCBHAGHFEEEDAEDAHHABFABHAHHGHBFDAFDGDDFEDGBDFEDHDDHCEHEAHECEECEADBGCBFFHCFBBBBH,False +133,16.0,18.0,20.0,18.0,16.0,13.0,27.0,16.0,DGGBCEDCEFHDGHFBDCHFHHBACBADAAHADEACBGHFGEDGCBCABGAGFCGDCGDGBEGBEGBECEEHGEHGHHDAAGGACBDGBGCBACDEBDBGCFHFEHCEGCEAEFCHFABFEGGCDHFDCDDCDBFGBFGAGHAG,False +134,19.0,21.0,15.0,10.0,12.0,12.0,10.0,11.0,DAGDAGAAHHFHABCBBCEBCFBCGDCGEEACACBACEAFGBDAAFEAFEHBBBFECDEADGFFACGECBBCBBGEBFEBDAACHADHFEFBCHBFGBHDBCGBHADHAH,False +135,13.0,9.0,13.0,6.0,13.0,9.0,17.0,10.0,ACEEHFBHFBGFCHABEADHHCGACGDHBCABEGBEDBGGCGHHAHCEDAEFAEGCEACEAGGFCGCDGBFGAFGAFBEGCEGAFGECHD,False +136,12.0,12.0,9.0,6.0,6.0,6.0,7.0,12.0,DGFDCFBCHHHHHHHBHBBABEAFGBEGCFDFGCCBDABAAEAAHACCAGHADEACGHGEBEFBCDBHAB,False +137,8.0,7.0,7.0,10.0,12.0,16.0,11.0,8.0,EEHEGHGAHFFEFEDBGDBEBBGGFGDCGFCFCGFDDFHDFHAFCFDGAAFFAEHAEDFEGFEDCEGAEFBHBCDBCHA,False +138,16.0,20.0,15.0,26.0,16.0,10.0,21.0,11.0,BCEFDBCDBAHBEFBCAHCAEBDCCDHGHHCHDDDEGBFDFGCACAEEDGADGEDBEGCEHCHBGHBEDDADDGBDGBCGBDHCFGCGGFGGAAEAADAEDGEDBEBADDADGCDGBAGBDGBHGFFBEDAEFBF,False +139,13.0,8.0,3.0,6.0,6.0,4.0,5.0,4.0,EDGABAADGAECAGAAGAACHFFHABGFBABBEDBEHBAHCABDFDEED,True +140,3.0,7.0,9.0,8.0,11.0,8.0,12.0,4.0,FGFCGCCEEDFEBFEBDACHADEBCEDFBDEHEFBEHCEDCGGBGFBEFCGGDGHDGCGGAG,False +141,7.0,6.0,3.0,11.0,10.0,4.0,8.0,7.0,EEAAECEEGHEHDFDCHCGHEAAEHBDFBDBGDBADBEHFEAFGGDHDDGBDGADG,False +142,25.0,23.0,17.0,19.0,29.0,25.0,18.0,29.0,EEBEEBHHHHBCHEFDGCDECDEDBEFHAFGBFBHFBHFCHFEDFBBFEAEGBCBAAAADAHEEFAEFDFACHHCHBEHBHHDGECFEFBEGHEGHAFHCDBCAGHEGHGDHGEGGFAAFAHEEHBFABDACHABDCDAFGFFGCFECFHBFEEDDGDBFCAHAEDDEACEAGDBGAAGAHCBHB,False +143,1.0,2.0,2.0,3.0,4.0,5.0,2.0,3.0,CFDCBDHGEEGAEDFEFFBHFH,True +144,9.0,4.0,7.0,5.0,3.0,7.0,3.0,7.0,EFAFABHACHECHGCBADBADAADGCFFAHGHDFHDCHFCBECAF,False +145,21.0,27.0,26.0,22.0,15.0,22.0,16.0,17.0,FCDFDDECEHCFGCEGDABBGHCGBBFABAEFEEFACHBGFEABEDBHCCFGAFEEFHAFECFHCEBCDBCBAHFAHFCFFCFFBFAGGAECDCCBBDDCDDCABBAGGAGBAGHCHECDACBAFHECGBGGBAGBHBACCADDDDCHHHFHHBDDBDDBDBADBF,False +146,23.0,23.0,27.0,18.0,23.0,27.0,25.0,28.0,DEGHEGFDBFGHDEACECDFDDFDBBBGCEAFHFFHFEBGEBDEBFBBFHFFEFCGFCGCHGAHBCFGAAECGEGDDGCHGAHAAHAADDADCAFBFFBHBHEGCAHCHHBEACCBBABBDBHCBDFAHAEBCEGEGCBHEHFAGCAFCACEFHEFADBCGGCGHAGHGEHEFHCAHCGHDGHCEHCEFCGFDF,False +147,19.0,22.0,21.0,22.0,15.0,18.0,18.0,18.0,ADDADEFBADAHFBBFBBCHGCGBCBHEDCCDHDDACGEGBEACEBCGCFABFHEAHFGDCDDCGFCGHEHHEHBFHDFBFFBAFAABAADACDFCEFHADGADCCECDBHDBCGBAEBAHDHHDHACFCGFGEFHEGGCGEFGBDGBGBBDE,False +148,23.0,18.0,18.0,17.0,20.0,20.0,23.0,19.0,GHBGCBDAFDAFHCBEFGACAECHHGEGFEGDEDDBCAAGFAGCGECAEFBEACEHGEHAEAFEAFBCGCCFCBBGHBAFBFCBFAEHBEHBEGAACFABGEDGHAGBCGCEBDGDDHEAHCADFFGHAHDGHDGHDGBDABHAEDDFHDFCFFHGFE,False +149,11.0,9.0,14.0,14.0,12.0,13.0,8.0,11.0,CCFCGFCDFHHHGGHEDDFHDFEEGCEAHAHCADFEBBBCBFCAHBAHEACDDCDACDADDBDDBEGBDFFCEHEFBEFEAGEGFCGFCAHA,False +150,20.0,17.0,22.0,21.0,18.0,23.0,27.0,26.0,FDDHHBGAEAABAAFAHBGFFHEHCEBEBBEDBGDCGHCGHCFFEGFEDFCDACDAEBFEDAEDHHHFGHGDHGAEFCFGBEDAADCCGFGGAAGCHCDDBDCGGFGGFGGFHGFBGBCGECHFHHACHABDFHDHCAEBBEBGCCFHEHGFHFEHFEHBCACCACGAGHDDDD,False +151,25.0,32.0,23.0,18.0,29.0,30.0,21.0,16.0,CHFAFBDBCEHGEHEEFEACEFCFHHFCAGAEGBCABCAECHDDFDFFEFFGHABFFEHBBDBGABGACGACEDCGDEBDEBCEBFDCHBADBFDAADEFBFHGAACAACHDEADHCBGCAFBFFBFFBEBBGBEEBHDBFDGDAGFEGCABEEBEHBGHBGFBGBAGFGCEGCACFDGAEBEEFCEFAFHBCE,False +152,2.0,5.0,8.0,6.0,3.0,7.0,7.0,3.0,ECBDCEGFFGHCGCGGFBDFDDADDHEBFCBCCBFCGFGAH,True +153,20.0,20.0,31.0,26.0,22.0,23.0,14.0,22.0,GBGFBFFBHCBHCBHGBEFCGFHHHHEHDCHCCDGCFFCDDHFDEDGEGCHHADHCEECFECHECDGCDGADCAGAAHEDHCFBEFEDCHFFAADEADHADCGBCFBCFEEEEBGBCCCCBCDBDHBAHDABCAGCBCFBEHDEBDCFDHFEFDAACAEDADAFGEFABFDCEDAFAB,False +154,14.0,22.0,13.0,6.0,19.0,16.0,15.0,9.0,EEBFEFCBFDAAGAHBCCBGCEEAEEAEEAEEAEGGFHBCHBCBCHBCFACFGDECBAGFFDBHBBHGGFAGBGCBEHGADBFBBGGAFCAFCEGBEGBEFBDFBHEHEFDAFB,False +155,13.0,9.0,8.0,9.0,16.0,11.0,16.0,26.0,HGHDBHECHGCDGAEGFEHDEGGHHFBHFGHBGBEFEAHEAHBFHFDHADHBCHEAHEAHDGHDHHEFFACDCEBFGGEGAEHEGHEGCCGFHGAAAHAFHAHDEBBC,False +156,21.0,23.0,28.0,17.0,32.0,20.0,26.0,33.0,AGBGFFGFGGCEFCBFGBECECGECBECAGHDHEDHCBHEEAEEBFGGHEEHAGFFGFHHCCHADABEGBHGCHGCFBHEHHEHHGFHFFHEFAEHADCEDCHAADBADHEDAFHEDDCCDCFEHBHGGHEFHEBHEBHGBCGCADAAHACBDFBGCBECBCCEHEADEGEEAFCDBHGBCGBCDFAGEAEHAHDCBBCG,False +157,3.0,5.0,10.0,12.0,6.0,7.0,9.0,8.0,CDDCFDCHDGGFGDBGDHFHHEGCCHDCADCAGBFHEGEEGCEDEFDBFDHAHGCBFCBD,False +158,27.0,19.0,22.0,22.0,21.0,22.0,30.0,32.0,AEAADDGDGHBHDGHBGHBHHBCHCAHCABEEBDBDHGFHGHHGBBAHAGFGBAGAGGAGHHCFFBHHGDHAACAGCAHDADGAFHCCHGHHCHGCFGEEDEDBECGAFEDFEDBEGBCACHFCDFGDCDCCBGCFGDFGHFAAEDHFBHFGFFEAEEHEDBECFEABGAFEEEAFDCFDAFDBCGHCGHAEHAG,False +159,6.0,10.0,10.0,5.0,6.0,6.0,5.0,10.0,HCEECDECAFABHBBFADFCGACGABHFEHCBBCBBHFHCDCEDCHGGHEGHFBHABD,False +160,18.0,20.0,20.0,17.0,21.0,19.0,20.0,20.0,FEDBECCGDCDBGDBGDGGDCDFCAHCEHAGAABACFCFFCAACHADAACEGEEGBFBHEHHBGHBACGFDFCHFCHEAEBBEDFFGCFGBEBBEHDDHABGEEEEFABHABHGEHGEHGEHBFDFDHGDHGBEGBECCFCAFHFGCCDAFAHDB,False +161,12.0,21.0,28.0,20.0,19.0,21.0,30.0,23.0,BEBCAAFGAFGBFGEEEFCCHCGHFGHGDDCCHBCGACGEHGHCEHCFCBHCBHDAHDHHDCHEABGHFGBGGCGHCGCEGFDGDDEFGEAHBGEADDCFDGBDGDCFECFCGFCHEGAFCDFCDGDFFEHFBHFCCBECHEBHCBFDBFBBGBDAEDGECGBHEBDABGGGAH,False +162,21.0,14.0,18.0,20.0,18.0,17.0,19.0,20.0,GHBEAFEGBGGHDEEDEABEBBEFECFCCABAAEAAEACBAFBHFHHAEDBCDECDAFBAFBAGEHEHGDAAHGAEDCCDHDDHGAHAFCCECAFCHHCHEGBCDCCBFFEFFGBFDDDDDGGCGDAFDGCGFHHDHHDHGFHGAGG,False +163,7.0,8.0,10.0,9.0,10.0,6.0,9.0,12.0,FBCCDDCAHADHEHHAGCGGHECHECHGBFABFADFGDHBDHDDCDHCEBFHGECEEAEFHECEBGBGGBA,False +164,2.0,1.0,4.0,3.0,2.0,6.0,3.0,7.0,CHCFEGFCGHHEABGAHDFHDFHCFHFD,True +165,27.0,21.0,24.0,26.0,31.0,11.0,22.0,21.0,CAADGACHHEAHDFHCAHCFBCFBEBHGCEFCHCGECDEABEACDDGHDAFCCDCADCAGBDGBEGBCDEHAHHAEFBEGDEFCEABBDBGAHAACAAEACBFBBFGEEHEBDEGDEGDCCDCABHEEEGCDGCDGHEGEEGEHDEGDHDAEFEGBDGADHFDGCDGBAAAAHHEEHDEBABB,False +166,7.0,16.0,7.0,13.0,4.0,10.0,9.0,15.0,BDDEDDGCAHEFHCFHCBHAGFDBDDBDDGFFBAHAHHFGBBDFBDHACHBCEBFEHHGHHBADBCFBHDGABGHBGFBGC,False +167,15.0,15.0,9.0,10.0,9.0,15.0,18.0,14.0,GGABCADCGHHGEHBDHCDHDEGGGFGGAGAABECBCFBEABEBEGAACBBFEAFBHFBHFBGFCAFGHFGHDGCBCEHFFGBFEDFBDAHHAHHGFDDAGDAFA,False +168,21.0,14.0,14.0,15.0,25.0,21.0,7.0,17.0,FDABDAHCHHFDACBGCBGCHFAACGEEBCBFABAEEAEEAFEADDHFAHFEHAHHCEHEFDGFEHFEGFDFHCCAEAAEADBHCFHEBBCFACFDEADFAECAEBBEDBEGFDAFEFDHFDHFEEBCEBGEHD,False +169,11.0,25.0,11.0,15.0,12.0,14.0,16.0,19.0,CDFBBCHGCEBDBACBDCGHFHHFHDFHBEGBEDBFDAFCAHBACFAGGAGEAGBAGBHBBDEBHGHHGHFEABDHFCBECBFDFEGHDFHBFHAEHECHBHBGDBGBCEBABDEGDGGDFDB,False +170,11.0,10.0,15.0,10.0,14.0,10.0,14.0,13.0,EEGCEHAGADCDEADGBDBHDFGDHCDFCDHBAEAHEHCGFCGFCEFDHGHHGHFGCAACHACHAEGEBDCFGCFBBFBBEEBGACGFHEECEBCGA,False +171,15.0,14.0,17.0,21.0,14.0,11.0,20.0,12.0,CBGBFHBCEACEAGAACBDBBDCDDCDDAGGAFGFGDHADEDDEFFAFFCBFCBFCFAHDDBGGGEADHHBHBBDEEGEEGCAGCDCCGCEBHHCGGCDBCHHEAHGAEGHEFADGDGEDGDDA,False +172,6.0,4.0,6.0,6.0,3.0,10.0,5.0,4.0,GBFGHFGDEDFCDAGDHCDACBECDECAHAFFAFBCBHAFFGFF,False +173,2.0,0.0,4.0,3.0,0.0,0.0,1.0,0.0,DDGDCCACCA,True +174,3.0,6.0,8.0,12.0,9.0,8.0,4.0,7.0,FGBDDHHDCFABFABCBCCHDEHEFAEFEBFEDDHDBCDECFHCFGEGGEDDCDDHE,False +175,4.0,4.0,3.0,0.0,0.0,0.0,2.0,1.0,GACGABHBBAABCC,True +176,4.0,2.0,4.0,1.0,2.0,1.0,1.0,1.0,HCDACAAEABCFBCEG,True +177,22.0,20.0,10.0,18.0,13.0,13.0,19.0,20.0,CBHCGHGEHEEADBHGAEGFEGFBAEBCFAFEGHCBABFADFDDCHBCHDHAGGADBAHFEEFHBBHBGDDDHDGHGFHAFAAEGBBDAADHGBEGBAGBADBAHCHHADHDGGDFGDFDCABCABCABEFHEGA,False +178,22.0,19.0,25.0,28.0,26.0,27.0,22.0,13.0,CCCCCCCDCAGHEHCGDGHCADEADBADHFDGGGBDACFHCFHDGBDGDAGDCDDBBCEBFBAABDCDDEDFEFEECDEBAFBDDBFEHEEAEFGEFGEAGBFFBFFBCFCFDGHEFCAFCAHEEGEEBEAHDGEFBFHDFEDCDHCDACGGBGCAGDAFAAFEAFHDFEGECBBGFAEFAG,False +179,3.0,7.0,11.0,8.0,19.0,13.0,15.0,4.0,BEEBAEFHEBGCBCEBFHFDECDCGHGFEGEEBECGFCGFDGDDGFAFFAEGCEFCEFDECEEGDEGCGGFGEBDHCEGF,True +180,23.0,18.0,16.0,19.0,17.0,9.0,16.0,16.0,DACDHCDECEHCBACDAFDAFABCEDHDGHBCFFABCDDFDDHCAHBAEDABHABDGDFCBECAEAAHGEFABFGBGBHABHCEAEGAEGEHGFHEAAEAHGCEGCHGAEGCBGCDGDEGHHADBAGBEDBDBB,False +181,7.0,4.0,3.0,4.0,1.0,4.0,0.0,2.0,CDDAFABHAECADFHCFABFABDAB,True +182,7.0,17.0,14.0,12.0,11.0,8.0,17.0,16.0,ECEECHEGDCFDCFDCEDBBGBGECGBHGFFGCBHEBHABAGBHFBHDGHBECBEHHGCGCCGCFGHABADDDHGDHEBHBCGGFFACHAEADBHDGHBGDB,False +183,18.0,19.0,14.0,22.0,20.0,25.0,20.0,18.0,FBAHCEHGHHGAEDEDDHDHGFACFDBFGCCBHGHHGBHGECBHFDEFBEBHECHFGDFHDEHAGGEGDBGAADFADAADGADGHFFEGCABDGFDBDECDFAFAEFCEFCADGFDFFBFFBHFCECGEBGEBHEADBBDFBCFDCFAAEGBEABE,False +184,9.0,17.0,14.0,14.0,12.0,19.0,15.0,10.0,DBDDHCBBBBGGFEBFEAFGCFDCADCDFEFGHFDHBDCECCFDCAEBEDHFDCBDGBACACGECFEHDBACBFFBFFGGDEGHHGCHFBHFBEFAEAABGFBGEGGFGH,False +185,5.0,15.0,12.0,28.0,11.0,16.0,11.0,13.0,FBEBDDHEDCEGFGGBGEBDBBHCDGDDHBDHECBDFBDEGHEFHEFEDCDHGDADDABHABDCBDBFDHGDFDCGHCGDCHHGDADDEDDAFDFFHFFECDCBBFFCFFC,False +186,3.0,2.0,0.0,4.0,2.0,3.0,6.0,2.0,EGADGADADBGHFGBDGHFGEF,True +187,7.0,12.0,9.0,16.0,4.0,16.0,12.0,10.0,BDFDFFBBBEBBFCHHCHHFFEGDADDFDFHAFDAFBBGDBGDBDDGCDFFDGDGCBCADGEHGDHCCHACABHAHGCFGFFGEFG,False +188,9.0,14.0,12.0,11.0,9.0,6.0,5.0,4.0,DFBEFDCDCBAFBADEFDEGCEBCGFCECHDBADBADBEEBABGHBACBACBECGACBBCADDHFGHECD,False +189,15.0,22.0,16.0,23.0,11.0,18.0,13.0,25.0,CHGBHDEHBEHDGCDFHFHHCHHGHEDDBGHACHECHBHGDHDCHDEAGEABFAEFACBBDDBDBADACDABFAHDABACBHHDHCAHFFBBDBGAFGFFBBABCGEEFEDCCDCBDBFDBFEFGGFHHFHDCADBDGFCGFH,False +190,23.0,11.0,18.0,25.0,19.0,12.0,19.0,38.0,DEHHAGHADHGCHACEDCAGEGFDADHADHDDGEEEEHFHGCAGEDDFHHEHHDHDGBDADHECEEGAFHDBHGBHGBDAHAEHABHBBFDDCDAHHGHHEHFGHCHDDECBFCADCGDCGHCGHGAHGABFHFHHFHHEHHBBAEDAEDFCCECAAGACCACAF,False +191,5.0,6.0,1.0,7.0,12.0,13.0,5.0,13.0,HEEFEHAEHFFHFGDFEDGEGAFGFHGEHDBHAFHFFEAHEBEBDFADBHHHEHBECFDBFD,True +192,14.0,9.0,19.0,16.0,17.0,13.0,14.0,12.0,FBCCBDDFFDHDDHGEFGEFGFHGFBDFCEEHACCAEEDBFDEDCHFCBAEFCGGAHFADGAHEHHAHBACBCEDEEDCCDCGACGCCGCEGDECAECAFGABGBHGDDEAEHA,False +193,13.0,11.0,10.0,13.0,18.0,18.0,16.0,24.0,BFHBGDBGHEFHEGEEGAAFHDFECFEAHEAHDFHCHHEHFAGEGCCHHEDHEDCCDAGGAGGBDCBDAFHFFAFDAFHGCHGCFGHGHHCHDBHBFFADFEDEBHGGFBADHAEEEHEEBFB,False +194,4.0,3.0,4.0,0.0,0.0,3.0,1.0,3.0,HCHBAHBAGFABCAFCFC,True +195,5.0,5.0,1.0,2.0,4.0,4.0,7.0,2.0,EFBGHBGABGADGABHAGDBECGAFGFFEE,True +196,16.0,12.0,12.0,7.0,4.0,7.0,9.0,12.0,ACGACAHFFCEACGGDEADCAGCFHBFBEFDHDBHAAAAGHBBHCBHGBAGBACBDCBHCBACDECHHAGHFHBGADFA,False +197,11.0,6.0,8.0,7.0,7.0,10.0,12.0,14.0,GHFFHACEECGEGGDBGBBFAGFGCHGHDGAEGCCBHCBHAFHAHDAFGAFADCADHAHHBCDFGEAHEHHFDEF,False +198,21.0,16.0,17.0,15.0,22.0,24.0,21.0,20.0,AEFABCDCDABGHHEHDFBBFCAGGAEFCGGCGABGACGHHGDGBDBBCFACBDFHHEHFCHFCECHFCHGEHGBFFECFBHFGHFEDFDCFCEAEEADDGDEGFEGFABFHBFAEHEDDADAAGAACEACBHEBFEDFAAAGGEGGBHEEHFEHF,False +199,3.0,4.0,1.0,2.0,7.0,5.0,9.0,5.0,HFFFEGEEGAHGBHGAHDADCBGGEEGEGBEGBFFH,True +200,27.0,17.0,26.0,18.0,16.0,17.0,15.0,13.0,BDEBEEBCBBCDFCHCCABDEGCGACGACACFGDDGAACBACEEDBDDCCCHCDFAHBGEBCHGGFCGHHHABHBGAEHCBGCDAEDFEFBEAHEAFFGDFHDHHDFDBFEBAAGAAGAGFCBCCEACEACECFAFAAFAADCFDAFDA,False +201,14.0,18.0,22.0,18.0,23.0,25.0,18.0,25.0,EHGEHCBHCHHAEHDEHDEAEBCEBCEGFAHFAHCEHBFHBHHBHEBCFADGHFGCFBAFBDHCHCEHADGBDFBFFBHBGGEFFFDFEBCDFDHCDHBECDEHECBECEFAGFCGCAGEHGEDEFHFCGCCDACAAFDAHDFFDBGDGAFGCBCDFEGFGGE,False +202,6.0,4.0,6.0,6.0,4.0,7.0,2.0,1.0,BADGAEAACFACGEFBACCEFCEFBDHDDFDBFDCF,True +203,4.0,8.0,7.0,5.0,6.0,6.0,6.0,7.0,EHAECAEHBEHBFHBCDBAEFEGGCFGDGHHACBBCGBDHCDFCDFGBF,False +204,6.0,15.0,10.0,9.0,18.0,10.0,16.0,17.0,EHHEDFBDFGDGEDGHFEEDDBGFADFCBHCBHFEEFAECGHHGBCEDCEHFACGHEGHEGCBGHBCHBEFFEHADBAGBGHCHEEBEAGEBGBHGBHCBG,False +205,6.0,8.0,4.0,6.0,11.0,10.0,4.0,7.0,BDFBFFCHFBADBGFCGCCEEAAHFAHFGFEEFBEAHEBDEBDFHDHEGEEBEHDA,False +206,7.0,11.0,7.0,14.0,12.0,11.0,11.0,15.0,DFFHFBABAHBEHBEHDHGCHFDFAGCGHEBADHGDHCEHCEFCEFGFFGHGCDAADGBBGDBGEBFEDHABHDBCDHHEFDEGDEDE,False +207,14.0,19.0,19.0,16.0,15.0,16.0,25.0,15.0,BHBBDBDDGDAHEGEGGECDCCBCDAEBGEDGHDCHFEHACACCEDCGFGFEGDGGAGGAGGHFBEGCEGCEBCAFGHEBHDAEGAFHHCADFBBFBFFDHFCHFBBGBBCBACGFDAFHBCGFCGEDGADEAHFCHBG,False +208,14.0,24.0,23.0,25.0,20.0,23.0,13.0,19.0,CGFHBECCCACGAFFHDFHDAHCCFBDFBCCBGFDAHDABGABGHBFHCDGDDHBHEBCEDEFFEFFEFFCDDGGECDEFDADDHEACEAHEAEEBFBFGBDBBFCBDCFDGFHBBDBCGCDAHDCCDHCEEFEGGECBBABDCBDEFEHHEHHBHBADFA,False +209,5.0,7.0,7.0,12.0,11.0,5.0,6.0,4.0,BEEGAGCAHCFDCAHCEFCAFGGDDEDCBDBEFBEDDADDHDDBBDBEEEGCEGHEF,False +210,21.0,21.0,29.0,26.0,25.0,22.0,25.0,25.0,HGGGCBGCBGFDHCEGCBADBADBDFHCBHDBEBBEHBEFBCABCACCFCEFHAFHGFGDDGDDHHDEDDHCBEDDEDCBGGFAADADGACHAFDBEBEECDECEFGGHECHEFHEBHEDGCDCABCEFGEGHFGHEECDBHDFDFGCAEAGEAHCHFAHDGHACFACGHHGDHGCAAEFAFBCBECGFCFFCA,False +211,25.0,20.0,15.0,18.0,16.0,31.0,22.0,17.0,GDHFDBEDFEFGAHDFFDBECFDAFDBFGBDAEGAEGFDCFDCEACBAFHGHHFBFFBHHEAFBAFDCFBGAGGACBACFCEACEACHHGDHGCGFHGHAGABGBGDFHHFCACEBHEDDAFDAGCADBEGBFGBFEFFEAFGCFBHFEHGABAABAEGAFDFB,False +212,11.0,12.0,15.0,21.0,14.0,13.0,13.0,22.0,FDHBAHAHFDBFDFCHHEFHDFAGBADBADCHDFFDABDHCDHCGAGFHDDHEEHBHHEHBCBGDGCDCDECDEGEBHEHHGHDFBCFDAGCAGCACCEFCDBGEBGEDEFGHCGHEDHEA,False +213,26.0,25.0,22.0,24.0,22.0,21.0,23.0,28.0,DGGABBFFGEFGHFBHBHFAGAHGECGEBAACCADCHDBGDHCDFEDCCCFBFAHDEGGBGECFEABGHDEADGBGGFDEFAABAAHAAHCAHGFHBFABFAEHHCHHCFBEEDEEFEGDEHDHHDHCBEABAGGAFGDFDCBCHBCHBHEBAAGCADCHFCFDBBDBCDECHACHDBEDHEFGADGHDBE,False +214,17.0,18.0,21.0,25.0,26.0,17.0,17.0,17.0,FEFAEAHHABBGBGGCDGDEEDAEBGFHHCADDHDDEDDEAFECGGAGGEBGBACEEDEEDHDDHGBHEBCBHADFEDEGGCDDBDCFCHFEFAHFHDBHDBHAGCFEFFEBEEBEEDGEACFABBCBFDBFHFECGHCGACDCCDCCECFHAACADC,False +215,3.0,8.0,12.0,3.0,11.0,1.0,8.0,8.0,ECHEGGEHEEBCEHGGHBAADGCHBCBBCHBCHBCEDFEGHEDCGCCECEBCGA,True +216,3.0,7.0,2.0,4.0,7.0,5.0,4.0,9.0,EEBACHABHEFDEHHEBHAFHFCHEDGEBBDFBHGBHGFDG,True +217,24.0,19.0,23.0,32.0,19.0,19.0,18.0,19.0,BDFHFFHEAGCGGEHGAHGADAEDAEGACABCBFDEDDEHDGDDEDDGCDGAFBBEBHFBDEADCDDCHBCEAHDBHCBHCACBGCGFCGFCGDHFABCACCABHEEHDGBFFDFFBHADDDCAAHDAEFEEFBDFADGADHADFGDCGCCBECADAHHCFDCGBEFEEDHBA,False +218,15.0,9.0,15.0,14.0,9.0,15.0,10.0,14.0,EDDHBDCEDAHHCDHCDEFECFDDBDEGDCAFCAGCHCFHBFBDFCABCEGEEHHGFHAFCABHABDAFAHBHHGFCGFHGBAAFDAFAAFEDFAGGCCGC,False +219,24.0,26.0,20.0,28.0,17.0,21.0,17.0,23.0,FBGGAGHAGHGGBGGFFDAFDHDCFBFFHFDHDDHFDHFHCFGDHBEFCEACHFEHCBADHDBADCEBCDDAGDAFDAEDEHCAFDAFDFBBAGBGHBCHAFECHDCEBBEABGFHEBHDGCEFCBACBACBCCBHBFGDADAAHAHBGDBDEBGECEDHDAEBAEBAEHADCDBC,False +220,10.0,6.0,12.0,8.0,3.0,8.0,5.0,9.0,DEDDFFBCFCCAGBFHBACAACAHFAHBEGGAGCDCCDFCDFCAHCACDHEHHABGDBHFH,False +221,18.0,20.0,25.0,20.0,16.0,11.0,30.0,25.0,BFFBEGBGFBGHBEFEDHBDCAAHAGHFGDADCBDBBDECAEBAHGHGABBHHBGCGECEECADDDGHDGBBGBCGHHGCHCCHCFHGGHAAHAHGAHGEHGDHBEGFHFAHGADFEGBDHFDGCDGCFGAGCCGACGHEGDCCCABCECGEHDEDDCCECADCB,False +222,19.0,19.0,21.0,28.0,17.0,28.0,23.0,16.0,FFFFGGBAGBFCDFCBFDGDDEDDFDEFCHDCHACAAFFDGFHCFBCDGEGEECCCBBAHHDEHDECFGGGDDGDDGDDCBACBABHCDCFDCEBEGBCHEFHGBHABAGFGFADHAGFAEFHEBBFBEFCGFHAFGADGAFHBCABDEDDCHFEHFEGAEDCGDFADBAG,False +223,23.0,19.0,28.0,13.0,18.0,28.0,23.0,33.0,GHBCHBGHEHEAHDHGDCFBHGCHGCFGCBGBGCDHEFAGHEGAABBHECFCFGDEHCEHAFCADAGDFGDHACBACHACHCHFBEFCFGCHHHHCHBCBEDBFHBEHBAGEACHACFAGGHGDHFFAFEADEAHFAHCCHEFGEFBFCBHDFGFFGAFDACDECECBEBFHBAGCHGCAFFAFF,False +224,3.0,2.0,2.0,3.0,1.0,3.0,0.0,0.0,DAADFBDFBCACFE,True +225,18.0,28.0,26.0,15.0,16.0,22.0,28.0,24.0,CCBGHAGAEGAFGBHGCHGBBBHBBHCBDDBFDFGECEECAGHEBBGBAGBFGCHCCDGCDHEAGCBBFBBFCBGGAGBDGHGGHGHHFHDCEDAFGHBGABHBEAACGCCHCCHBHHFFFFGCFHCFEDACFGEFCAAGDCDDHDBAABFACDABEGCEGFEHFEFCEDBFHBEHF,False +226,0.0,1.0,4.0,5.0,1.0,5.0,5.0,2.0,DBGCFGDHGFCGDHGEFCFDCFD,True +227,9.0,11.0,5.0,9.0,13.0,8.0,7.0,11.0,DGHBGEBGHACBAFHAFHFHDDHCGEAGEDEEBEAGFDFBDFBHFHCDHCEEAFBABBEEBEBDHADHGEEAC,False +228,3.0,5.0,4.0,5.0,8.0,4.0,5.0,8.0,DCEDEHGEHGFCEFGBDHBDCBDHFFHEAHEACGBGHAEHEB,False +229,5.0,2.0,1.0,1.0,0.0,2.0,0.0,0.0,ABABFACFADA,True +230,17.0,15.0,18.0,10.0,25.0,10.0,12.0,11.0,ECCHCABEAEAABAEBGEBCEBGAAGBBDFHDEHDEHCHHCHCEHEEHCGBAFCDEEFGEGGCFDEFBBADBEEFHEAHECGFCDAAAFBBCCCACBGGBAEDDEGDECCEFAEFAEG,False +231,31.0,18.0,29.0,27.0,23.0,14.0,25.0,29.0,DGBAGHGHDGCGACBADBDDEADFCHGDBFEBHEBHEFHFCDFCDACFGHDDDDDCGCEAEEADCBDBGGHCAACAEDACHEHHAHDDFDEHCEHCECEHHEAFEABCGEGABHEDHEFAGCGGCGACDAGDACAAHACBBCDACAACHCDHGAHGFBDAACEACECFEHGGHBGHBCFFGDBGHBEFEHHAHBAG,False +232,9.0,27.0,30.0,27.0,17.0,16.0,18.0,20.0,HDBHDCCCHHCHECBBCGCEDCHCADGDBBEBGEGGFDFDDGDBBFHCEEDFFFHFHHDGCEBCABABDEHDHCDHFDHFDHBDHGGEECBEHBDFDDBCDCCBCCGCAHDBBBBFBEHBEGBEDDGAAHCBECBCCBCFFEDFEDCCGBAGACGDCAFCGFGG,False +233,13.0,14.0,9.0,12.0,10.0,11.0,7.0,12.0,CACBADGHDGHDFHDFHDEEDGEBBEDHACHABBFCFAEHACFDCEAHEABFFBFEAAEBCHDGBDBBGCBFEAFGDCDHHABHABGF,False +234,27.0,12.0,19.0,20.0,14.0,11.0,16.0,19.0,DCEACEBHDGHAGFBGABGABGABCHFEADDADAHDHDGBFAECCBCHHFADFEFAHDAEDCHCHADBFDCGDCHECGAAAAGBAEEHGCCGEAGEFCDFDGGCGACHCEHCEHDEHBCADAADADDFHGAHBAHBAF,False +235,10.0,14.0,16.0,10.0,22.0,13.0,14.0,12.0,BCEFFEFBBGBBGEDGEABFACCDCCDHEGHCBDGHEEEFAGBHGBEEHEEHDEFDEFCECDECHGGAGFFEDGHBECBHCGFEAAEAHGBHGBHEBAFACCEDCACFDCF,False +236,7.0,11.0,9.0,8.0,13.0,11.0,4.0,12.0,AEBEHFHFFGFHBFHFAHBHHBHFEFABBEBAEFCEACHHDGDEGABCCBCEBDEDCEACFHCFDCHDEEDBGDE,False +237,23.0,30.0,14.0,18.0,17.0,26.0,17.0,30.0,DGDDFCEFCGCBBHACAFCEEEEAADADEHFABBADHADHFDBFHHFHDFDAFEADBADCAFAFBEBBEBBCBBCFBEFBGFBHBBFFHFAHABHEFHBFHEGHAAHBAGBGFHAFABEGEGGDCGBHBCHGHFGHGHHCDEFFHCBHBBHGEHGDHFDHCDBDAHGHBEAACFG,False +238,19.0,27.0,27.0,14.0,19.0,23.0,28.0,21.0,CCCACCFBHFGEBABBGFFGBCHBFAAFBAHCAHCBGABGADDABDAFDBCGECFEHBCHGHHGHEGDEBFBBCGBGHBGFBCCBDGDCHACHADFADEHDEHEGADGAFBFGBEGHFHEADFCCGCCGFCEFGHFEFBCDBGHHECGBCFAEBBCDGAGCAGFFEHGEGFEGBECHE,False +239,12.0,6.0,10.0,11.0,16.0,6.0,12.0,10.0,DBDGGDGCDECGHCHEAHGDEFEEFEBBHABCCDACGFEGHECAFAEDAHAGCBGAHGAGFABFDEEDGEHEECEDCEAHDAH,False +240,12.0,11.0,10.0,12.0,15.0,7.0,12.0,8.0,EHCEBGEBCADCDFCEGBEBCEBHDGAAGDGHDCFDEEGBEFEEFGEHGHBEABEAFCFHCGHCBADAADADGAEBBDDHDFGACGA,False +241,24.0,20.0,23.0,18.0,18.0,16.0,33.0,12.0,DCADHACHFFHADCCDEEDCEDCFAAFGBCGACGAGGACHBBDBCCBEFBGCDGHFECABCACGAEFAECBFFFHGCAECAGHEHBFHBAGEFGECGHBABCADDGGDGGDGGCGCFFHGGEAGEGEEBBEGAGFFGDGGBGDBGDCGHAAABGEBEBDDBDAA,False +242,2.0,5.0,2.0,2.0,7.0,2.0,2.0,4.0,EHCHBDECDEGFEAHHABBEBFEBGE,True +243,5.0,8.0,9.0,5.0,11.0,13.0,13.0,9.0,ECEEGBGFFHFBEFHFDBGDBGFHFFHGHCGHEACEABBFEEEEGCGGCFBCDCCEHCDHGAFGABGHFGAFD,False +244,8.0,13.0,8.0,11.0,10.0,14.0,17.0,10.0,EGDHGCEDHEAHFBCGBAABGEDAEDAEGGDDFDCFGCEGCGFADFCFEBBCBFDGFAGFEDFBGFGHBBHEDHGGHBAFBFHCFHGBHGB,False +245,10.0,16.0,19.0,10.0,13.0,11.0,21.0,15.0,BEEBGHAGHCCFEDFGFHBHHDFDDHCFAGFAHABFABGAFAACBECGGGHGCAGCHCEFGEHBEHBGFGEFCHDHHDEBCABDGBGGCGGCBGEBGDCCCCDCBDEBGEBECCH,False +246,9.0,13.0,8.0,9.0,4.0,11.0,15.0,3.0,BDDBDDBAGAEGABGEDFCBCCFCDABHCBGDGGEGCEFAGBAFBGGBGGBDFFAFBCGDHGHFFCFAGFAB,False +247,24.0,29.0,19.0,27.0,21.0,19.0,25.0,36.0,AGGDCEDBEDGADBCBEDBHDFHDBEFHEFEEGEGDEABEFHDBHBHHFFAFBGGHCFFEAFDABEAFCHDCABBBCBEEBFBGAGHBGHCABCAFHDGHCHHCDGADHADGFHGFCGDBHBCHBDAEGHHGHHAHCAHDDBGHBGCEAHGADDHDECGEHHEDEGFEDABHABHABCABDABDACHGCBGDHHFHFFGC,False +248,23.0,15.0,19.0,20.0,20.0,17.0,12.0,20.0,AEDAEDAEFADFAHFAHEEHBBCBBDBCAFAAGCCGACEHEADFHDFCDAHGBEFFEFDAFGACGECEHHGADGBCAFCGCHDDDGCFFDBCHECFEHEABEABDCBHFDHECAFDABDAGEBGHGEHDBADBADCHCHHCFHEEH,False +249,5.0,8.0,8.0,6.0,8.0,12.0,5.0,4.0,DDADDFEDFHACECHGGHCDBBFFBEEBGEBCECCGBEAAGAEBFCFFHFFBFFCF,False +250,9.0,9.0,5.0,9.0,9.0,5.0,9.0,6.0,EBGEGDECAEBBGBFDBACGCBBCBBFDADDACDGEDGHDHDAHEFHFGAEGHFGAAEHAE,False +251,3.0,4.0,6.0,7.0,2.0,6.0,5.0,5.0,FCHFEBDGHDHADFGGFGFFEDBCCBCCHGCHDBDDAA,False +252,23.0,16.0,22.0,22.0,17.0,24.0,15.0,22.0,GDGADAHGFBBFBCHBDHBDCCDHEGADCHBBDFHCGGCEFBECHECEACFDBADEACEDFFDFFDFCEFCGFCHFGAFADGAFHAEABFDEDHHBAAAAHGABGDBFEHFHHFCHDCEAEEAEDCFFAFHCHHADHACHAEDABDCCGGCGFCBFGEHBD,False +253,28.0,21.0,24.0,17.0,16.0,23.0,19.0,22.0,HBGAFCHGAFDHGAHGHGDDGADGECAACFACBDGFCBAHBHDBFDEFABFACAEGFHGBDGBFHDFHCGBAGCABEGHEFHECCEAEHADHFDCCDCCEAFBDDBFHHFGHFCHCDHCFFCBAEFAEFEEAAEBFCBAABAAHEABBAFBGCBGCBDFGAGCCDECAHH,False +254,22.0,21.0,35.0,22.0,18.0,16.0,18.0,17.0,CGFCBBCBBCFBDHEGBFDEHCCAECAHAFDEEDAEHAEBCHFHBFHCHBGEACCCCDCABFABCDBDHCGCCGDCDDADDGGEHFEGCCBCBAFDEFDAADFAGGHECHECHECHAHGCFBBBBAGGEDBFDAFDCEDCEDCADCBHEFCAGCAGCBGFDACAACGGH,False +255,16.0,23.0,16.0,16.0,20.0,17.0,25.0,22.0,FBDCDGFHBEHADAEBABHAGDEEDGEAABDDEEFEEDBCGGDHHDHGDABBCBBCDHCDBGDBGCHGHAGFECEEBEHFGDFACHGHHGBHCEHCECABHADHACFBBAEFCEHAGHGEHGFHGFGGFGBFBFCBGCFGEFGEHBBGFCAFGAB,False +256,4.0,5.0,1.0,1.0,3.0,4.0,5.0,7.0,BHFAGFAFHABDAEHHGHHGEGBEGBCBHF,True +257,15.0,16.0,15.0,21.0,14.0,16.0,23.0,29.0,BBAHCCDBGFHGFGFFCFGCGHCGHDGAGHDCHDEABEBGGFDDFHDHHGHBAHDGCAGBGEBHBCHGEFGEHGEBFECHEDGEHBAHBEHDACDHHHBCHBCHAFHDCHAHGAGGDDBDDEACBAEEAHDDFFHGFHFFDAEDACDFG,False +258,25.0,18.0,28.0,20.0,16.0,20.0,26.0,30.0,GBDGBHAEEAHBAHBCHCCHCEBCECDEAAFHHCGGCFFDFBAGBHGFHDAHBACCADCAECAFFAFFGGEGCEACECCFCBEAAGFCFFGGHCDECBGHBHACAAFDGHDCHDCFDHFEHFDGDGHDCHAEADGGEADCHDHBGBDGAGGFFHHFHAGHCHHCDBGHBEHDEHGABBADBCG,False +259,10.0,4.0,2.0,8.0,6.0,7.0,4.0,6.0,BFAHHADDBDEBDAHFACEADEFDEHDGAGFDGFAEFBGFEAACHAH,False +260,17.0,18.0,20.0,22.0,23.0,26.0,23.0,18.0,CGCHEEDEBDHDGEGFEFFCAHGBHBEHBACAAFAFFDBFDCFAEFADFAEGBBHADAGGHFGCCGCGFBDFEEEEADHGDCEDFGDEBDHBGHBFFCAFCECGEDADDBHGBECFEBFEDFDDEGDHCAHCFFGFFGAHCDHADCBECBHHBHCGFGGABGCEGFE,False +261,27.0,24.0,20.0,19.0,30.0,32.0,21.0,26.0,GEHGECEEBEDACCACGBFGFCDBHEFEEFGEFBFACFACFAFFAGDACBAGDEBABFAEDAGHAHBAECAFDFEEBBBFEBDEFCHFHBFHFEHDGHBGHCCFDDAADEAEECGGHGFECFEDFEAFACHACEFBEFHHBHHFEAFHBFBBFBHFCAGHHFHHGHDCHDCHFGAGDDGCAGDEEAGEBEDAGHADBBB,False +262,24.0,26.0,23.0,23.0,21.0,23.0,28.0,24.0,CFDHHBBHEEHEHHEFHBDAADAFDBCDHDDFGAFCACEADGBEGCGCHEAHGADGABGADCFFBFEDDAFDCFHBBCFBGDGCHECBEBBCABDAECAHAHHAHEBHDHHFAHGEBEHFAAGBAGBGGCAFAFBAFBDCDCCDGGDGBHBBCBGFGEEGECGEHECDFCBFGBDGCACEFGEGGFHGFDGF,False +263,0.0,1.0,9.0,1.0,3.0,4.0,6.0,1.0,CHCCEFCGGBGFDGEGCECCFCFGC,True +264,6.0,5.0,5.0,2.0,0.0,4.0,6.0,0.0,CCAGBBGDBGDBACACGAGGFFFAFBAC,True +265,4.0,10.0,10.0,7.0,1.0,8.0,4.0,4.0,BEFBDFGDFABCABCHFCDGBHBCAFCAFDBDBGGBDFCCBCFHCDHC,True +266,22.0,29.0,31.0,16.0,20.0,28.0,16.0,14.0,EHAHCBHCBECFGBBCHEEBAFBHHAFGBFDBFCBFCBFCBFCGFGECBBGFCEFBEFDEDDGFCFCAGCAFCEGAAGAACDCFGAFGAFHBGABDAGAHCAECABBBCFBCDEAAEBFBBFCCFCCFABFDDFBEHBFGEDBEDEHAECBGCFHCDECACCDEFDADEHCGDBHH,False +267,19.0,18.0,7.0,10.0,13.0,13.0,13.0,11.0,HAHCGEBDCBCBBEGHFGBCGAAGBGGFDGCAEADBAHBFEFFEAGEHCHHBAHAADEFGEAGFFEFAEFCBAABAABEAFGAEGDEDBBABBFBHHDDHDBFD,False +268,17.0,10.0,10.0,7.0,8.0,5.0,14.0,9.0,DCADHDGHAGBAEHECHCGADHCGAEGBEGAEGAEGACAHGHDCBGHBGFBCAAAACBBEEBGBCFCAFDAFDHFGABGA,False +269,1.0,3.0,0.0,1.0,3.0,4.0,3.0,1.0,GHGGEBEFBFABFEDF,True +270,23.0,19.0,18.0,18.0,15.0,13.0,11.0,15.0,AHDAFCAECAFBHBCEFDEFCEFEDAADBADCDDFDAFGEHGEAGHADBBEACFGBDHADGCCABHHGHFBEDGHFEACEFCBAGAAEABEABGABHBEABGABFCBACGDDHFCHBCHBHHCEDCDDCDBC,False +271,7.0,9.0,4.0,6.0,4.0,10.0,14.0,6.0,GDDGADGAHAAHABDGFFFECFBHBEGEGHEGDCABGGFFHFFHFBGABGDBGCBGFGCB,False +272,9.0,5.0,1.0,2.0,6.0,2.0,1.0,1.0,EDAEAFECFGHAABAEDEBBEBAABAA,True +273,6.0,7.0,5.0,6.0,3.0,4.0,5.0,6.0,DBGDAGHAGECGFBHFBGDDFEDFHCBBEHHCAHBACBACAD,False +274,13.0,30.0,20.0,14.0,22.0,14.0,15.0,16.0,HBGBBDCBAHEFEBDBCABCGFGEHGECGCDECDBFDECGHBFHACDCBBHEHGGHFGBBBBHBBHBBGBEABHDBGDEGEFDECCFHEBHEHGEFCFBCFCDABAAHEECEECEDCEDGEBFEBAABGABCBCAAFDAFDHFC,False +275,5.0,8.0,10.0,12.0,2.0,10.0,10.0,5.0,HGDDCDFCDBGFCGDBGEAFACFDBDDBHDBCDCCFGCHGDFGCFDABHGBAGCGFABFEHF,True +276,5.0,1.0,0.0,3.0,1.0,2.0,0.0,3.0,BDDHFAHAAHAFEAD,True +277,24.0,23.0,18.0,24.0,16.0,33.0,19.0,28.0,ADCABCHCAHCAHEADEAHBGBCGFGFFGAFBDFGFBGDEGDGHHGHHACDDGFFAFFBFFEFADHDDADDFFAFGBFBBFHFCHBDADEAHECEDFDGFDFFDCBBHDAHBBHCEGEBHHBFFCCHHHHCHBBHDHAGCAGEDEHDGHDAFAFBBFABFAEAAGABGFEHCCBCHECFEDFGFE,False +278,12.0,29.0,23.0,26.0,19.0,18.0,23.0,13.0,BEBBEHBCAFAHEDDCDBBDBBDAFFAFCADCGGBGGCGHCFECEBDECGEHGEADBFDHFDGCDGCBCCHDBEABDCBDEBEEBDCGECBDHBEHEAGAFGHFHEFBBDBGEBFHGGHFGFDGCDGDDCFFFDFECCGCGGFBDBAACHEDBDDBGCAGBBC,False +279,16.0,11.0,17.0,16.0,19.0,22.0,19.0,14.0,GFAAFDCCEGCHGBEGDABFBDFEFEEBEBGFCGHHHFHAFDADEAHACBFCDFHFGCDACDFCGFEDFEGADGAFCEHCAHBBHEGCDDHDCAFCAFGEEGEEFBEFEHAHFDEFDBGDBGAFCAGCGGCGHE,False +280,10.0,14.0,13.0,11.0,22.0,14.0,17.0,12.0,EHCECEHBFGCGGCAHCDGCGGEDBBBFHCFBFBBFGHGHFABEAEGACGACBFDBCEECDEBFEBDGHDEBEGGECGEHGEDEEHFEHFEGFAADGADEHDAFDHFEEFCBA,False +281,32.0,31.0,18.0,18.0,36.0,28.0,25.0,12.0,GAHFABEGCGAEFADGADFABCADAEBAEFEHFGBGCBHDAHAABBBECFEAEEFEEFEDAEBAECADCDDBBBCBBEDBFAAFHEEGFCGEEGEFGEFAFDABCABDAFGFBGFEGBEACGGHFGAFHBBDEEEGGBHGFFAFFGEFGEBGDCHCHGBBGABEABEFEDADCEEFDCDHCDBGABAACAHCEFCEFBEB,False +282,19.0,24.0,17.0,28.0,20.0,14.0,18.0,11.0,CEGDBCDFGFGCADCEEGFABEDBDBBDEFDEADBGBEGBACDDFDHFBHGGCGAEGHEGHECDDGDFGEFABAEEHDFBDFBEEBHCDCCEHHDCGDBHDFDDADDEEDBBBBABHAHDABAAGADBCFBCBECDAGECGACGACFABFA,False +283,26.0,21.0,30.0,21.0,22.0,23.0,22.0,14.0,ABEAFHABHEFEEFBHDAHFBHFBAFBCBGGHGDHFDHFBEBBACCAECAECACGBCFFEFCEGGACBCDFAAHABGDEGDEGDACFEGDEGAFAACCBEABGAFDCFDFFGACHCEGCFGABCHGAHCDHCDCCDCGABDFBDEDCGFFBFEACCDCHDGGCGEEAEBAGDCDDCEEB,False +284,14.0,18.0,15.0,12.0,15.0,14.0,12.0,12.0,DHBFHFFADGAHCABFABEEFDEAGEAGDDBACBCCBGCBEEBEAHEHCFFCEFCBCGDCGDEGHGGABADBEEBEHCHHDBEGGFFEFDADHAHBBDFBCCBGABCFHCFA,False +285,16.0,15.0,17.0,12.0,11.0,20.0,18.0,11.0,HGHCBHCECFEHFEGDAFFGFEGFEAFGFBGABDBBGBACBGFBECAAFDAHHFGGAGGAEGCBDBBDHEFGGDGEHAHADEADEFCCFCFADDBCCBCABHAFFCFGCFDCFACDBCGH,False +286,11.0,13.0,7.0,7.0,10.0,17.0,12.0,13.0,FDGFDGFHABDDHFAHBHFFGCFHBGAGFFGFHHAGHEGHCGBCECDECDBHBEHBEHCAFGABAFBGFBEFGEABFBFDEFAEAHEABC,False +287,8.0,6.0,3.0,14.0,2.0,6.0,4.0,6.0,BGDFDCCDGAFBADBDHHDHCDHAAFAADBADBFDEFABDGHEGDDFHD,True +288,13.0,9.0,15.0,13.0,19.0,11.0,16.0,13.0,GGEDADGABGCBHAGACCFCHECDDCBAFEEHEBBEABEACFACEDHEAFEGFGDAEAAECDEFEHHEHBFFDCFDCDAGDHEBHCGHGGHCEFCGFEGEDGDCGHBGH,False +289,21.0,24.0,27.0,24.0,13.0,22.0,21.0,28.0,EBFBBCGBDHCAHFAHBBHBDHBDHADECDCAHCGHGFHADHDCHFBBAHBDHECABFBFFCDFGDFECBECBCHEAHFHHEHGGFAGBDCEHCFHCGGBEGFHBFGAFCADDFDDBDFCAFCHFDDACGACGDCGAGGHDEDECDAGHBFABABBEFBCCDEAHGAHGCCGCFAHDGHC,False +290,11.0,5.0,20.0,12.0,8.0,15.0,4.0,7.0,CBCCHDDHADEADEFDAACCCFFDFCAFCADCGDFEDCECCECFFHFFAGFCEDEBFFHCHGCDBHGCFDAFBAEHACCACB,True +291,20.0,16.0,14.0,23.0,25.0,13.0,17.0,18.0,GBEGBEGFEGFBFDBFDBADHAFBDFGDEGDGGECCECAEAADAACHHHHBHEGDADDBHAAAEHEBDEBGEAEHDGHAAHFABCEGDFGFCECDGDABDHBDECCABFBEEDEGFEHFEHGAHBDCDAEHAECDCFDCEDHGHEC,False +292,22.0,21.0,19.0,22.0,30.0,26.0,23.0,31.0,AHGAHGABADGFGGEEAEFDCABCFBCGBCBHCBCFEDFEDHADEFDFBHCBHAHEAHEHHEHEBGEAGEDCEHGACGDCFCEFDEBDEBDFHACEEHBDDGGEBCEBCGHFGEABFAEEBHABGAHGAHDHHDHEABEGBFAEGHEHCADFFDFGAFCDDGFHFFGFFDEBCHFEGFCDFHHCHFBEGHHADH,False +293,16.0,24.0,24.0,18.0,24.0,17.0,14.0,18.0,BDDACEACHABHABHECHGHEGEEFCHFAFAGFBBBGBEECEEHEFDBDDBDDGCGBCEHCEDCBFABFBBCCECCGBEBAABHECEGCEDDECFECFHCFHCGBCFFDDFADFAHHCGBBBCAFEBHGDGADGAHCBEAAFGDBHHEDCEDFEH,False +294,32.0,23.0,12.0,12.0,9.0,21.0,14.0,23.0,BCGBDHDCGGGDAFDFFBCABCABCFGGFAAFBHEBHGBGGDAFAACABHBFFDAFAHHBHHDHGDEADBHGBHBBHBBFACCBECAAAHABHAEAEDFGCCEAFFHEBHFHHEHDABAAGAGHADAAHAACEAHAAFFBFFBFFH,True +295,25.0,28.0,34.0,29.0,21.0,15.0,21.0,21.0,GBBDDFEAEADECDAGBCFBADECDBBDCCGCAGCDBCBBCBDCBGCEHCGACACFBHFDDBCHFCGAGGECFFABDEGDEFDHFHHBBHDAEDBEDCDDCDDCDAADFACEDHHGACGBBGAGAEGFGGHCACCDHGEHGEHGHCEACBHFEAAEACEACHHCHBCBECHHFEBBDCBFCBDDBDABAEFAHG,False +296,10.0,5.0,3.0,10.0,3.0,6.0,4.0,2.0,FCDBCACHBFABDAGEAGDADEBDFDAFGABAADEADHGDFFD,True +297,18.0,24.0,24.0,26.0,29.0,26.0,24.0,26.0,HAEHBEAEEHCACDDCFDHFGCBHCBCDHFDEADBBGCBGABFAFGGHGEAGDBCCGCBDFDDFBEFBEGDEGAADHADHBHADHCDFEFFEGGEBAHBCFGCEGEBGBFGEAAEDHFDAAGHFGEEGEEDHECGEDFEBBDCCDBDECFCBBEFHFCGFEHHEHHAGHCEHCDFCDFCDHCHGGHFEFFBFHBADB,False +298,13.0,9.0,11.0,21.0,12.0,21.0,9.0,8.0,DDADBAGGAGEAGECGEFHFCCFBCABCABHAEFABFDFCHHDDEDDHADHCHABFFFEAEDCFDEGGFDDFCDFEFFEDFEBADFDDFBDFCHBGFCEDDAFG,False +299,9.0,10.0,7.0,5.0,4.0,5.0,9.0,5.0,AEBFBGFGGAGGADCADGDHGHEBHBBGEBGFCHBCHAAFAABCECCFDDBCAB,False +300,9.0,10.0,14.0,12.0,10.0,5.0,22.0,10.0,GBDGFGGEGEHGDGGEGCCGACBDBBDABDAEFABBCEAEHAGCFHDGHGGDGADGHGGBFCDHCDGCGBDAACEHCEGCEGDHCHECHCBF,False +301,23.0,15.0,14.0,8.0,21.0,17.0,19.0,20.0,FGCEGAEGEDHEDBGGECFFHEBBBFDAHHEBAEBHCHEGAAHABEEFEEFGBHGCHCAHDAFGGHGDHGFAGBABFAFHEEGEAAEDAGFAEFACFACBHFDCEHBAHCAHGAHCCGCCGEAGEACFADFHBBHBF,False +302,27.0,23.0,30.0,20.0,17.0,18.0,24.0,20.0,AACCCBGDBFHBAECFFHBHHGHAACGCHDDBFBGGCHGAFGAGGAGGAHGCHGCDGCHBHABFDBDDEEDEEDBCFCCFCHBHFBAFBDFHFBAAAFCCGHCDBADAFCABEACGBFBEEBAEHAEGAHGACBBDACDFCDGCDGHDEEDEBCFFCAACHECGCBGCEGCDAAEEHGD,False +303,30.0,27.0,22.0,22.0,20.0,20.0,25.0,21.0,FCHFDBBDBGCAADEBGFBGABGFEGHAHBADAEDACBECFFCFFGDBGAHHAEHFCAFAACEDCFFBEFAEABHDGAEHDDBGCBGEBGEAEEFBEBDHDAAACCHCCHGDAGDFCFABFHBFHBGBBDHBDHEEHECHDCADAEDGBCCBAGEHGEBGFBGCCACCAGAADAHGHHGFDABGGGD,False +304,29.0,17.0,17.0,22.0,14.0,23.0,28.0,17.0,DABGFCFHAEGAFGFBCCBEDDHFCADEHDEHGHDGADGHGGCCFFFFCCEGHEGBDDDDDFDFGDFGCEABADBCHADBGDCDAHFFBGFGGHAGHAGAEGEGCAAHAAGAAEBAGBGFBHBBHBGDCGFCDFBAEBHCFEAAEAAHGAHGAGFACFDCFEAFDAB,False +305,11.0,12.0,13.0,10.0,10.0,17.0,17.0,13.0,BFDDADEGGFGEFBEAGHAGBACAECAFFBBFHBCHGFHGHGFFGCFCBBAGCDGDDGCGHCBHDGGFHFFHGDECDFCDEAGFAFBAECAECHBHHEHCEBF,False +306,7.0,10.0,4.0,3.0,5.0,2.0,7.0,5.0,BHBHADABBABGABHDGHDBCEFEEFCEBCEHGGCGBAABGAG,True +307,17.0,17.0,13.0,19.0,19.0,19.0,22.0,12.0,FDEAAHFFBFBGFBDFGDFGDBGDBGFBFFHFFABEGGGHAAHEAFEDFCBFCEDCDAGBAFBGHDHCGHGDEGDGCBBDHGABCDHCFHEGGDBCHECEECEADEAEGAGBAEEDDEGCEGCHACBAFBDEDAFGAE,False +308,16.0,19.0,32.0,19.0,25.0,21.0,28.0,24.0,BCGCCBFCFGGDHGDADAACACGGBADDGDDGFBCHHCFECDGGAEBAEGHCDBCHEEHAEHFEFFEGFEHDCCCEGHFHHGBGDEGFHCFBFHBGEGFCGFCBHGBHEBEEBGBAGEEGHEAHEBFEBHCBGGDGDCHCCACCADBAHEDFGCACCHHCHHFBAFAEEDCECCDFCDFCDFEG,False +309,12.0,7.0,7.0,14.0,8.0,9.0,9.0,23.0,HFHHBHGACFAHHHHHDHBGHCEHEHCFHCBHDAHDAHFGDDHEBGFDDHADHBDGEEGDACDAHDAHCGHAADAECBEGEFFAFBDFG,False +310,7.0,9.0,2.0,2.0,5.0,3.0,5.0,9.0,BBABAGEAHBGHFEHBEHBHHAHBEGBGGBDACFCHFDHAAE,True +311,26.0,28.0,24.0,21.0,11.0,21.0,26.0,17.0,BFBEHBHGFHFHDDGADGADGFDCFBCHGFAEAAEAAEAABDDGHDBEDCCGFCFFCBBGGBFHCGGGDBGDBDEBCFBCABGDBGDFGEGCCAAHBGHGGFFBAHBAEGCFBCECHFADGGCECCFCBACBGBBGCCDAEHABFADDADDAFBHFCHAAFAABHHCHBCDBGA,False +312,23.0,13.0,12.0,13.0,21.0,13.0,8.0,13.0,FBAFBAECDHHEEEEAACADHEDAEAEFAEFAEGAEGAEAAEAGGBCDDFHAHHFFHFCCACAEFAHFAECHEAEDDHDGBBCBDFEHEAHBAHBAGCCDDDFGEGEFBBDBBCCB,False +313,3.0,1.0,2.0,0.0,2.0,1.0,1.0,1.0,HACAACEFGEB,True +314,19.0,17.0,14.0,10.0,16.0,21.0,10.0,13.0,AHDAHEEFAEAGCADFEHCEBCGCCGADDADFADFAHAAHFEHFEHFEFFCBFEBAAHEHBEBCCGHEBHCBFCFFGEAHEACBABBABFFGFFGBBBFBGDGCCBEDADAFBFFCHEDG,False +315,3.0,8.0,4.0,7.0,12.0,10.0,4.0,14.0,DHEDBEDBECHEFFFCHDAEBAHHFHFEGFECEEDEGHBGFBAHBHEBEDCFHHFHFDHGBH,True +316,19.0,13.0,26.0,20.0,13.0,13.0,16.0,14.0,AFCBGBFCAFCEECHBBAGCDGCFGHEBHEDCCAHCFEAEDDEDAGCAFCACCADCGDEBFAGDHGDCBACHAGHBFHCGECDCAGCADADFGDCGDGEDFADCADFFDAEDHCCHCBHGBHEBFGBCABHHDE,False +317,16.0,18.0,21.0,25.0,22.0,16.0,21.0,17.0,GDDGDDEDFEGFEDEEDHBDHBCHDHBBBBBBCCBCCHFCHBCHEHADGCDGCBGAFABCEDFFAEBCHBDDEADCGDEFAEGAGCCDCCGFDFBDHCGHGAAFEADAAHEBHEAHFCCDCEAHEAFGBGEBGDGEFGFHGEHFAFDGEDGECEDG,False +318,23.0,22.0,20.0,24.0,12.0,20.0,16.0,25.0,AABCHBFHCDHCGFGHDHHFGAGHBGHBGCEECAEHGBCGDDDHCFHGBHGBHEBHDCCAHCAHAHCAFCDFHHEBDDBGDGEABBAEBCDDFDDFEDFACFABFCHHCHHGBFAEFBCGBDHFDBFDFDAADAFDCEHCBBDFAAAAGECDABDAEFABFG,False +319,9.0,5.0,11.0,3.0,6.0,3.0,10.0,12.0,HABHDEGCCCDFCBHCHHGHAGHCGHCDHCEGCGCEGHEAHFABAECGBBAAFGAEHAG,True +320,31.0,18.0,28.0,29.0,18.0,25.0,23.0,22.0,ADEFDADBAGBEGHEGDCAHAAHCFGCHGFEGFHGCGBFDAFDCFCEBABHDBAFAFFDGDAAHABGGCAFCACCDEBDCCGCCDCCAFGGCHBDHGCHAHBBBBBCCGAADCBDEFDHCAHCHHFHAECDCHDGHDEADEDFADBADEEDGCBGCBGDGEFHAFEAFAAFGEEDCFDHFAHFAFFAEFHEDGD,False +321,11.0,11.0,8.0,16.0,26.0,18.0,18.0,26.0,HFGEAHHHHDBHGEHDFAGGDEFDEFDEFAEFBDFHDEEDEEBGEHEHHEHACGGEBHEGHEFHEHAEGFDGDDGBCEAEGAECDHCGHFEHGAGFCHHEHHFGDFEFFHBFABHDGFFBCEBAECGDABDHBC,False +322,6.0,3.0,4.0,2.0,1.0,1.0,3.0,2.0,CAAFAEHAGBDHCDBCGBAGCA,True +323,10.0,11.0,20.0,18.0,16.0,14.0,16.0,14.0,FCGBEHDGCCHABGBCGACFEFEEFEDCCCBGCFHCDAGDAGDEDFHGBAGEDFECGACGEFGEFEHCDHCDEFHGBHGEFDEFDEADBAEHFCBGCHDCHDCBDCFHBDABGAHDHCD,False +324,14.0,16.0,12.0,17.0,15.0,23.0,16.0,14.0,HDEBDGFAFHDDHDHECHEBHGHEGEGFADHGEFGDFBCEBGAFFAGFHBDHGDCGDCACFECFEHFAFBCEHCFBEFCEADHABCBBCFBAFAGFAEEAGBBECBDGBFGHGBFDDFDDFGAFDAF,False +325,15.0,13.0,7.0,9.0,15.0,10.0,11.0,11.0,BDABDCBEEECAECHCFHBBHDHEAHEAGEDEABEDHEGGFGGFEFBEHEEFBHAAAAAADAADFAEFGHHDFHGAGBBBBCDCGBFGFCG,False +326,18.0,22.0,21.0,20.0,18.0,16.0,22.0,11.0,FAHEBHABFAHGAEGHHBBBCBGCBECAAGDACFBCFEHGDHDDCDDFFCEGHEBHCFCDFCDGCHBAGCEBCBDGBDCBDHGEFADGEFABFGCFCDBCGACGABFACDEDEBDAFAFFABGEBGEGEEDEGDAGAGGEBGCBDCED,False +327,13.0,17.0,20.0,5.0,21.0,19.0,14.0,10.0,CACCAECGEGAFABCCDFAFFHFCEFCHAHBGEECEECGEFDECDECEEABFBEAEEBEDHCAHAADBABFGFFGFGGFBGBHEBHGFGEFBBGCBCCBCBECBCGFEHFHBGHACEFF,False +328,21.0,20.0,17.0,13.0,23.0,15.0,20.0,19.0,HECGCCHADAADGADBEGBEABEHFGFGGFGCBECFHBAAEAHDFHFFBGEBGCBFHAABAABDCBDCAFAAHCGDCGEEGHGDEGCHGHBFHDHCDBCFEAGCAHCEHEEFEFBDHHDEBEEDEBGGAHGAHBEFBECEFABGABEC,False +329,24.0,23.0,29.0,30.0,30.0,21.0,23.0,19.0,HADHFBHFEHCEHDHCDFCBABEEBDEHDACBGDBCDBGDBADCCDABAGCEGBDGBEGCDFAFFGEFGAGEAGEADCGHGBDEDAADEHBAHCAEGBGFBFHBGEBDBBAEEDEEFAEDGCABCEDGFFGECCDACHBDGBDFCHECHECEACEADDDEDFADFAFHCFGCADCEECFCCFCCAEBGGHHCHFDHFEG,False +330,7.0,6.0,9.0,9.0,7.0,8.0,16.0,10.0,HGGAAGEEFBEDHFDAFBAEDFGHFAHGDHEECGHCGCCACGFGHFAHEBHCGGCBGDHGDCGDCGBGDBDF,False +331,15.0,22.0,24.0,18.0,22.0,22.0,16.0,24.0,ABAFBECDEDAHCCGCAAHHCHHGBBGBAGBDGEDEHAECACBBFHHEHHEHHFHDCHDCBGFHFFHAEBFEFGDHAECEECBEFEGCCFBCGBCDEGHBGHFAHFGDBGEAGFADCBCCHCFFDEFEEFBEFHEHDCDDBHDBGFAFFBCCBCFBDADCGDE,False +332,9.0,18.0,16.0,12.0,7.0,14.0,10.0,14.0,AADCABGADACDAEDCHGCBFHBFHBEHGEFGHGECFBCDDGDAECHBCEBCFBCHHFDHDHHFFDFBGFGHBGECCFDFHDBHGBCFFABBACBCBBCB,False +333,24.0,10.0,12.0,14.0,8.0,11.0,24.0,18.0,AHAAHAADADGFHEEGBECBDCEACAHEGHEFHADAADFHGBHGBGBCGAGADGADGAHCAHFHFGEGGBACDCCDGFGBHCFGAFGBGEHACHAGGCDDHDAADGHDGFCGAHBAHBGFF,False +334,17.0,19.0,16.0,21.0,12.0,28.0,7.0,21.0,BCEAFGACAHCFEBBDBBDFFDBCDBFDFFDHFABDGBDFFGFDHFCGFGHCBHAFCEFHHBHHAHFADFBFCBFCBDCHEHDCADFDDEHDECDFCAFAAHABFBDFHFCDGHDHHCHECBEAEHAEFABDEFAFBGHEA,False +335,5.0,1.0,17.0,8.0,5.0,13.0,6.0,9.0,HFEEFACCHDCHDCHFBHDDCACCFCCGCFFDEFAFGCFHAEGFEGFDCCAFCHCGDCGDCHFH,True +336,7.0,5.0,7.0,10.0,4.0,6.0,4.0,9.0,CABCEBDDFADCAFCFGCEGEHDDBFGBFHCHHGHHDFDEHDAACAADHBDH,False +337,17.0,14.0,20.0,15.0,14.0,12.0,26.0,25.0,FEFFADAGDAGFCHHBHHBAFEECECAFCDFDDGGCHGCHFCGDGGBBGDAHDHECHGCBBBHDEHCCHFGHFCHBCHDAHCAGCAGEBHEBAAACEECEGGDHCEBFEHGHCGHCGDABAGHGGBBGFGGDGHHEHDDAAGA,False +338,17.0,17.0,8.0,23.0,13.0,10.0,15.0,13.0,DFFDBGEBEBCDBFDBAEEAFGAHDDDBBDEBGEBGBAGBGBCGEDEAHHADHDDHEDHGGHADDBDHHDCHDAGAECADCHDFBBFABDAFCAGDFFCAEGAEGEFGBDGCHAHA,False +339,18.0,24.0,23.0,25.0,16.0,22.0,30.0,24.0,DGBDGDDCDGCBGFEHEAAFCACGBFEBGCGCABCAFAGEAGEAHDCHBFEGHEBDDBDDBGABGFDGFBHCAEEAGDHEHFEFEHFGHFBFFGCAGCACCDHDDHBDFGDFGEEGBFDHHBCHDFFDCCABGBDGECBEGGGHDCHACHBHHGGHBGABDABHFCHFHHDBABGFCGFCDC,False +340,2.0,2.0,13.0,7.0,3.0,3.0,2.0,4.0,ECCCDCCACCBDCDFCDGAHHFEDFBDCDCCHGCHE,True +341,4.0,3.0,4.0,1.0,4.0,2.0,6.0,4.0,GAEGBCHBCFGAHGAHBACEECEGHGDF,False +342,10.0,14.0,13.0,18.0,10.0,15.0,4.0,7.0,BFBBADBAGACCABFAECCFCCEDEHDABBAFGGBDBCEBFDBFDEHDGHFAEECCDCCFHBFDEDDFDDCDDEHDEFFBDFBDFACHAFH,False +343,2.0,3.0,3.0,5.0,8.0,5.0,2.0,1.0,EAFDCDDCHEBFEFDEFEABECBFGEDGE,True +344,16.0,17.0,10.0,12.0,19.0,14.0,18.0,24.0,DGDFEBGECFCBBGFFEFHEHBEHGCBACBEGFGGHCBHGBHAEFBFFBHHBEHAGAADFAGFAHFAHGACGAEHABFGEGHEHHEHCABDAHEABCDHGEHGAHDDHDDBEFBGDBADGCHECHDHEEE,False +345,12.0,6.0,8.0,11.0,11.0,7.0,6.0,8.0,EEABBCDDGADCAECADHABGABECBECFEFFECDEGHAFHDGHFHAFAABDAHCEHAEHFDCDEGDGD,False +346,14.0,12.0,14.0,18.0,13.0,23.0,16.0,8.0,ECHBFBAFEFGCCDDGFDBFEGFEAFECFEHFEGBDDCHDHAAGAAGFBDBGDADDHGDCFFHEEHCEBGDGCFECFEBFDACDFGDAGDGGCGBABDCBCBAFFAFFAFEAFDHFCG,False +347,13.0,9.0,9.0,6.0,6.0,16.0,14.0,5.0,GEACFCDFGAFGAFCFFDDGGDBGDEGBAAHGAHFFBFFEEFBFFBFCEGBGGCECCAAHAGHAFAAHACGGFBCBBD,False +348,2.0,2.0,2.0,3.0,4.0,6.0,4.0,5.0,EFGDDADHEFBAFECFECFHBFGGHHGH,True +349,25.0,25.0,26.0,14.0,12.0,22.0,23.0,17.0,GCCGCCGEEDFADFDCCEHCBHCBGBBCBFGBAGFGHBGABFAGFBFFACCHHFHABAABCABGHEGBCGBFFAFGACCDDCBFGFAAAAAEACEFCEFCADCAGHAFABFDGADHHGBBCHGEBGCBHCBFDHGHHCEHBBBBEFAFHDDGFDCAGCAGDEDE,False +350,26.0,15.0,7.0,12.0,18.0,16.0,17.0,8.0,GFECAAAAAHFADABEGCECDGDAGEABEGBGBBGBBGCHEFFDFFAAAGEAFBAGDHHFGGAGEADFAEEBEFCGFDDFGDFDBFBEHHAHEAGEABEABEBBADAADAFFCEGCHAE,False +351,19.0,24.0,27.0,20.0,25.0,23.0,28.0,19.0,HHCHFCDGDBGDFGCBGDFGBFEDFBGABHABCABGBGAHGBHGBABCCEEBDFGDHGDBGHFGCFGCBHFBHECGCCBCGBFGACGDCHEEDFBGABFAFFGHDAEAAHDAFDEFDEDEECFEGHECAGCECCFCBABFADCAEGEDDFHFECFEGABGAHDHECBACDGHEEEEHECBECGFC,False +352,11.0,14.0,21.0,19.0,18.0,15.0,12.0,19.0,CGFBDFCAEDFEHEHCEACEAEEFGDAGBACBFCBFABDDGHDEHFGADGHDHCBHCEHCDHBBEFGFBADCGBHEADECDCBDCBACBACBDCHFHHCHFDGCDECGHCEEGHEHFFFFGEHDCHDED,False +353,14.0,12.0,11.0,22.0,22.0,10.0,7.0,14.0,BDEBEHDFDDCDEADEHCFHCAACAABBCDBHHEDHEFBAFDACABGEEDEADFADFBGFAGCGHCFEAEDGDDFDEEBEEBEHHEHHEDEEBHHCADCACHDDGGBFEDDE,False +354,25.0,23.0,25.0,17.0,15.0,24.0,9.0,25.0,FHABBAFCCFBCFBEDDHCHGBAEHCEBDAADFADFHFHHFHBFBCHBHHEHDACDFFAGBGDEGHHGDDCCCAHCEECAEDECFBBHDFCEFBAHAAHAFHAFHBFAAFAGGACEAEDAFDHEGFCFFCDFHGFHACHABBABECCCCACCBBCDBEBBHDB,False +355,17.0,20.0,28.0,20.0,27.0,26.0,18.0,20.0,FCDHEAHEGECAEDAEFCHFEFCCCCBECHEHEDHDHHEGHEDFEHAEDGEDGEFEECECHGCDGCBEDDEDDFDDBGGCGBHHAACABGGBCGBCGDCFHCFBCFBHFAHFEFFCFFBDACFCHBHEEFBGFBHFDGGCECAAFACFBBBABBDBEHCAFFEGCADEADFFBCGA,False +356,11.0,9.0,19.0,9.0,17.0,23.0,24.0,22.0,DCFDCHHGFEAECFFCFFGEFGFFGAHGBHAADAACEFFGGEHCAHCBDFFDGGHHBFHBHHAHFFGGFEGFCGFCHCGGGGEEEFCDHCDECHECEBCFGCHBCHAEHCEGFDGCHBEHBGHBGHFAEAEGGD,False +357,15.0,19.0,23.0,15.0,30.0,8.0,15.0,12.0,EDGEGBEGAEFADGHEFEEDEDDEGGFDAEEAGDAEEADEAEBBCFBCGECBEGGACEFBGDHECHEAHEHGGABCEDDFDDEDBHDBCBACACCGCABEGHCHCCBCCAFCHBEHEHHCCBCEBCEBCEBFBBECA,False +358,8.0,10.0,3.0,16.0,6.0,11.0,10.0,8.0,EADHDFFDBFEGFGCCAFCBHDGEDHDDFBBFEBHHDAHDHEDHGDAGDAEDGDGFBGABGFDGFABBADBF,False +359,20.0,14.0,12.0,8.0,11.0,4.0,10.0,13.0,BAHGAEDBEDCADCAHBABAAFAACGBHGBHABHEHCCHBCGAEACGDCADCHGAECADFAEBDEHFCHEAADHAGHFBEBCEAGEBGBGHB,False +360,26.0,15.0,17.0,18.0,13.0,10.0,21.0,9.0,HCBGGBGGBCCDDCDCCHCHHEGGEAFEDFAGEBDHBGAFGDGAABCADCEGCFGAEABEADHABGAEGFEAFAFCACGADDBEAGAABAHGDCDEADECDBCDBCBHCFDDFAGAEGAHGAGAAFBDB,False +361,15.0,32.0,16.0,34.0,25.0,18.0,29.0,23.0,HDFHFFDABBBBEEBGEBGEDEEGAHGBGBBHDAEGCDACHECHBGDBGDBGDGDDFBGGDEBFAHHHHEHHAHDADDEDBEBBHABHAFGDDBEDHEDHDDHGCHCEFDGGDGGBCFCCFEHFGGFHAEDFDFFCAEGABDFEDGBAGBGDBCFBCHEDADDCDCBBBDEBDEBGHCGBEABFCGGEFCEG,False +362,22.0,28.0,20.0,25.0,21.0,16.0,11.0,16.0,BHCHFBFFBDDBHHBAHBADBAHBAHGCCFCBBDBBECAEFEDHHBCCFDCBBBEBHEBFGBHGDHCFFCFAHHAGAGDBFDGFDBCGEADBFBBAAFEDGEDFDAAGBAGAABEDDACBECBEFDAHCCCCGCEEHAEADEDDEDCEACEAEDDEDDE,False +363,11.0,11.0,7.0,6.0,9.0,8.0,12.0,8.0,FBADHHEHFGGCGAFEAFEGFGGHGHCCHCCBCABAEBAHDDCGFABEABFABABDEBDBHAGGFBGEEGDE,False +364,5.0,2.0,8.0,2.0,1.0,2.0,9.0,6.0,AHGACBAGHCGHGBEFDAFGACHCCGCDGCHGHGC,True +365,33.0,17.0,16.0,24.0,25.0,19.0,21.0,11.0,GDDGDDGBDBAABAFECGEDGEDFAGCACCFHCGHCDAADBACFCHEDAEHABGGHCEEEBAEFEDFDCFDHFDAFAGFBCDAFGEDDEHBEDBDCBHCAGFHFDACAGDABEABGABGAHCAGDAFFGEFDEFGFGEEEAEAAEAAEAEFBBAHBABCEGEDGAA,False +366,24.0,28.0,22.0,9.0,23.0,15.0,15.0,17.0,HEGHECCBBCBBFAEDHBFCBFBBFABGEGCFDCHCCBAAHAADABBBBAECHECEEHEEBAECDDAGDFGDFCDCGBCEBCABEABAAEHGCHEFHEDHFGGAGEHGCBBAFBAHCFEEGAEGABAABAHFHBCCCEHAEBBEGCGFFBHFA,False +367,22.0,19.0,28.0,25.0,31.0,21.0,23.0,26.0,HGHDGHDGEBCDDCAEEADEDEEHAHBDCEEBEFGAHAADGDHBHFCEGEDBFDEFEEBEBCEFCEFCBACBADHADEGDAHCCEDDEDHFAHECDDCBEFBEGBDCHCHAABAACCHCCHCDHAGCAGEBEEAFECHBCHGCGGHFCFAGGEDAFDCBECBEHDEFFGFDGFHGFGGFGFFBFHBCCGAGHAHH,False +368,19.0,23.0,22.0,14.0,18.0,18.0,13.0,20.0,GAHHDGFBGDBFFBHGADABEHCCFDCBDAGDBFBBFBBFBFFEFFAHCAFGAHADHEBFBAFBECCEBCDDAEDGEHBBBBACBAEBDECHEGFCHACFDBGCHHCHGEHCCHCGHCGECEAGACHFCHFCHDEEEEEBDACAAHA,False +369,8.0,9.0,10.0,4.0,11.0,7.0,17.0,8.0,GEHGEBGFGGFCGEHAFBBFCBHCFDCGEHAEGCCGAEGBBCHBHFEAFGBCGADGADEADCGCHGEBAEGHEG,False +370,14.0,14.0,22.0,16.0,19.0,13.0,17.0,12.0,AEAAGFACECCFHBFDEGEAGADCEHCECCADHDEGFGGCCGBHGBHGBAFDGECGECGHBDHBABFACDDEBFECFEFFCAFGEGEEGHGCBACBCBDABCGBDFEDEDDHDFBDHCCHCCHEADE,False +371,24.0,19.0,21.0,13.0,20.0,18.0,17.0,23.0,GEGEADCDGEHBDCBDHAHCEFCEFEEFCDFBEGAGFHGFCCHCCFFCFFAADAFCABBBHGCHDHEAAGCAGDABHHCHHCHGBEFAAFHAFHGHHGDADEABEGBCGCDBADEHHEHACDABGECFEFEEABEBBHBBABCAGCFGEFABHAH,False +372,3.0,3.0,3.0,4.0,0.0,2.0,1.0,2.0,DDFDDBCABHABACFGCH,True +373,11.0,27.0,14.0,16.0,27.0,12.0,14.0,25.0,BGEGGBDBADECHGHHEHADHDGAEAHEFHBFHEEDGEDECBHFEHEBHDDCEABEAHEAHEBEEBEGAHCHHCBBBBBBBCCGDFGEBBEFHFDHFDHFDEFDEDEHGEAEEFBBHBBADBCBCCBGFDGHEFABBGHCCCGCHH,False +374,3.0,9.0,10.0,10.0,8.0,7.0,11.0,11.0,GCGGBBHHCCGFDGFDHDDHFDBFEGEEBECDDAECCBBCHGCHGFHADHACBEFHEBHDBHDGGFGEC,False +375,23.0,33.0,18.0,22.0,30.0,18.0,26.0,23.0,EBDEBDHHGCCGCFGADGBCGHCEHFEHDEHBEGDDGBHGAHDAHDBCBAABCFBCHEFDADCAEBBBBHBAFBAEBAHBHFBCAGCFHDADEAFECEECEFBBGGCCGEHHBBHEDCAFAHEEFFEAGABGCDGBBGBDFBDFGDBEDBHFBGDDGAEBAGAFGEEBEECEABEHGGADGDGFHGFEAEHHE,False +376,26.0,12.0,16.0,23.0,9.0,18.0,21.0,30.0,ADDFFDFFDFFHCFCBFAGFBGHEDHEAHECHCABFAEAAGAAGDDDDCFGCAHABDEGFHBCBCADGHDGADGHEGHDGHFBHGDHCDEABHGEHBDADAACHHHHFHAGHEGHDGHDHHCCCAHDHHGGFAAAAFABFHCFGBHGAACBGCDD,False +377,14.0,10.0,11.0,6.0,8.0,8.0,6.0,11.0,FCEFBBABDCHECFBCGBHGFHECGCFAFAEFDBACADCABCHHEAHGAEBAHAAHAAGFDCBDCBDGAEHHEH,False +378,10.0,13.0,11.0,8.0,10.0,9.0,5.0,12.0,ADCHBEECEEADBACBGBBAHBGHCCHGBHCCACCFHCDBDDFFDFFBFEAEHABHDBDAFHECBAHEGHEGHEFBAF,False +379,26.0,14.0,13.0,28.0,14.0,24.0,18.0,23.0,ACEAFGAGABGAGGEHAFHDCDDFFCGHCDHAAAEFFEGABGAHHADFGDFBCAGCAGBACDDDBDDEADCCHGEAGEABHHFHCCBDABHFEEDGHBGBBHFDFCDFBDADDEDDEDHFDHFDHEDHAAFAHDGDBGEFFABAECAHHFFHFFHDFHFG,False +380,21.0,15.0,24.0,10.0,21.0,16.0,24.0,20.0,GBFFDHFBFGEFHHHHHECHEDEEBCAFAABGACGBCAECBCCBEDFCDGCEEEAEGAGGACDAFDCGBBGBBCAFFDFHBAGGDGGCCHEAFEAFCAFCAHCGGAHCACCAEGHEHEEGEEGDCHDHHGCEGAFHHEHACBCFGHBGBAG,False +381,15.0,21.0,27.0,23.0,28.0,27.0,27.0,20.0,BCBHCAFBBGEBDEDHCDGCGGCGDCFECDECEBCEBFEBFGCGGBGABFAEHCFDCHEGEFFFBGFECCEHCGFFGFHGBECCFCFAEDAGAHDAGEFFFAFDACCHCHBBHFCDAGDHGDEGDBDEHDHHFHFBHDBFDEAGCADBDDBDDEEFEEAGEGGBCGEFEEFDGHHCHFEHCAGGABCE,False +382,0.0,4.0,3.0,2.0,1.0,1.0,2.0,3.0,BCDBHDBHFEHGGCBC,True +383,1.0,2.0,2.0,6.0,6.0,2.0,4.0,2.0,CHDAEDGEDCEGEBGEFDEDGHDFB,True +384,12.0,14.0,12.0,10.0,21.0,16.0,19.0,20.0,GDHEBFGHDHCEABECBDCAHGAEGCEBCEHDEAEBHEBHFHHBBFFAFDCGHAGDCBFHGHCADBAHBGHBGADHFCHFDHCHECEECEGFEGEAGEGGEBFEGAEBAFFFEGFGGDGHFEHF,False +385,9.0,9.0,5.0,9.0,10.0,4.0,7.0,7.0,BCCBABGHBGDEGDACDBEFBHDGADGAEHHCFCEFDEBDBBDAAEEAEHADAGEHGFHE,False +386,15.0,9.0,11.0,11.0,15.0,15.0,12.0,13.0,EGCFFCFGCFHFDHCHCCHACHECAGHFFABEAHEFHEDDEBDHBDHBECDEADGFGFBGFAGFAFAHEEEBDCDGEHGAGGABAAGDFDBEABEHECFAA,False +387,17.0,16.0,9.0,11.0,9.0,4.0,15.0,11.0,DADCFEBAEAGCBBHBEGBDABFBDFDHCAFEGGEAGEACHABHAGHDGHBHHBGDEGHCAAGDAHACEGBBGABAACGACGBDGBDHBDCE,False +388,10.0,3.0,8.0,5.0,5.0,8.0,6.0,3.0,BDDGGCAECAFGAFCACADCEGCAHCADCBFFAFFHHFADEGFEGBEA,False +389,17.0,13.0,28.0,32.0,15.0,31.0,24.0,29.0,HGHCCHGBFDBGAAAAEDAFHHDEGFECFHGFCFFEHFDHGDCCFCHFCFDCFDGEHBEHGHHAACAEDAHDACGEGFEBHDHCFHEFHGFAGFACDACBHCDHCDCCDEFDEFDHFECDHDDCGDGBBCCFDHBDFBDFCGBBHAEHCDGGFHGHAGFBDBDCGFCGFDGDDFDHGHAFFAGDCEDCF,False +390,23.0,24.0,19.0,26.0,25.0,15.0,25.0,27.0,FADECFEGAEGHCFDCBGCBDDHDDHDDAGAHHAEBAGDAHBHGBFGBGGFGDCADCBHBEHDEAEHGEHDBHGBHEBDGBHECAEDADDAEHFFHFHGGCCHHEFECCGDEACEHHAHGAFAADBBDCBGABDACCADABFABEHFEBEEBDDACDEEDGGGGBHGBHCFGCFHFBHCBEGEE,False +391,4.0,5.0,5.0,5.0,10.0,9.0,7.0,10.0,FGGFGCEGEEHHDHGDCEDAHBFHFGDFEBHBHHAHFCCFACFGBFEEHEEDEAB,False +392,2.0,1.0,3.0,2.0,5.0,3.0,4.0,3.0,FBGCCGDCAHEFHFDHAGEEGEE,False +393,32.0,34.0,23.0,23.0,23.0,22.0,17.0,26.0,AABCCBCADCAHAAEFAFBABBHCCFBFGDHDHCAHFGBBCCBHCBHBFCDFBHBEABEAGEDGECBEBHEBAEFHEBEBDHAHHBGCCFDDFDFBDHBGAAACEACDACHADFAGFAGFHGFDFADFAHEAEEBEAGDDHCDEFDBHCGGDGDAHABHEBHEBEEBEHFABAHBGEBHCFDGFGFEDADCACHACBGBB,False +394,10.0,5.0,5.0,10.0,12.0,9.0,5.0,11.0,DCDEADHACFADFADABDHGHHDAHGAGEEBEFFCFAEDAGBAEBCEHDBHFFCEFHEHHEGEEDHF,False +395,9.0,8.0,7.0,6.0,6.0,3.0,2.0,9.0,BAGBECDECDCHEAHAFGBFHBAHDHHAACAACHHFHBDDBEEAEDBCCB,False +396,28.0,25.0,16.0,17.0,19.0,17.0,23.0,14.0,FBGFAAAHBHHGFCGDGGBGGEGGEFCEHCDGBBHEACEGBEADCADGEGHDGAAAAABFABFADFCCBHCADEFGEDDBDACAABAAHHHFACFBDAADBAGBGEHDEDBBFBBFBBCEAGEBHEBHEBEFBCFECFEGDGBAGDACDHCFCFGAGAE,False +397,11.0,7.0,11.0,10.0,5.0,9.0,10.0,7.0,BCHBAHFDBFCHFCDDBHGAGCHGCGGCGGFGEAEECDDFADEBFCHDCHBGABGEFDCFDFAAADAACA,False +398,21.0,30.0,21.0,28.0,27.0,13.0,18.0,24.0,CBDCAGAAEHGBHBHHFHHAHHCGHDBDABFBEHDEBCEDFDCFDCFBCEDCBAEBEDBEBBABEDGFBGFEEAEBGHBGCBACBDCEECBDCDDCAAGDGEAGEAFEGEEBEHFDHDGCEBFEBDGDFHAFHFDHECHGCDGHEGDBDBHEBHGBDAAAAEADDDCABHDCHCEHCHGBBA,False +399,8.0,12.0,5.0,5.0,7.0,5.0,5.0,13.0,HHGHBAEGABBCBBCBBCFBCBHADAAFBAEBEBFHDECEEFHGAHGHHDFHDGHAHHED,False +400,7.0,6.0,11.0,5.0,6.0,14.0,10.0,3.0,AEFAEBCFDCFCFAEFCGGCGECHFGADCBDFGCHCCABCAGGEFHEFGAFBFBGFDGFDBF,True +401,5.0,2.0,3.0,1.0,8.0,3.0,7.0,1.0,BAGCFGEEAEBHEGFAGFDGEEGECAEGAC,True +402,7.0,14.0,22.0,10.0,18.0,10.0,12.0,15.0,GHECCAABBCBBEEBEGBDCEECFGGHCHACHAHFBGGCCCCHCEFCFDCHDCHDFHECHACDBCBAEBDEBDGGEGHDCEGHECEECEEHBEHDFBFBAFHDFGFCG,False +403,14.0,14.0,19.0,22.0,20.0,22.0,14.0,19.0,ECCEDFDGEDEEBCBHDAFBAFAAECCFDCEBBEBDAHCADCFDHEBFEDFEFEGFEAFHAFHGCHEEHDDFEDFDCFDCFCBAHFAHFHHFBDFDDEHCGGBGHBAHCAGCEGAHBHCGCEDEFDFGDHGFCGBBGCHGHDDA,False +404,9.0,11.0,17.0,12.0,11.0,7.0,12.0,10.0,BCBDCEGCECEGCDCCDGGAHGEBGBHCFCAFHAFHADEAHFDHEBCCDCCDCBDHEDHADBAHCHDDGBEGFGGBECFEFEGBAGCAB,False +405,5.0,5.0,3.0,4.0,12.0,4.0,3.0,6.0,DBGAEGEEDAEHAEBBEBEEHFDCBEFGEFCAFCEHHAHEDH,False +406,15.0,17.0,23.0,27.0,15.0,22.0,16.0,20.0,EFCEGEFDBFHCCACBDDHDCFBHFHGFCECAEABGBGDHCDBCABGADFDDFECCACFAEFHDGHDBHDAHDHHDHBFEFDEADFADBDCHDEHFCHFGGFHGHHEAACAFCFBDDCEBCGBDGDEGDBGDHFCCFDEHCBBCBGDFGAFEAGC,False +407,11.0,16.0,12.0,20.0,16.0,15.0,13.0,15.0,HBGBDGBDGFGEFCCHCDHCDHFFCDBCFBEEECEFCEABEHDEDBEFHFDAFDBHBBHDACAHFAFBAEBDDDADDAFDGGGEEGHEGDFHBFHGDBGCBGBACDAHHCEAEEDHGF,False +408,16.0,12.0,20.0,13.0,15.0,13.0,22.0,14.0,HACHAGEAGFHHDDCEDCBFEDFEACBBFHBFHBCGBCACCBDDGDDBEFEGGHDBDDGGFHGAHFEGAEACDACGABAAHEABECECCECGGCAHFAHFGGFEECEHAFDGGGGCFHCGGCGBC,False +409,4.0,7.0,9.0,5.0,9.0,7.0,4.0,6.0,EFCBHCFAFFACFDHHBHCBGBBGBCEHGECBAGDCEFCDFCDEEHEEAED,False +410,12.0,11.0,9.0,6.0,6.0,6.0,2.0,5.0,DDCDHBBABBACFACEBDEHDHBFBAFBAGCAEAEEFHCBCCFHCAAEAABDABGFC,False +411,10.0,13.0,4.0,12.0,8.0,3.0,7.0,11.0,BBHBBDDDDDEEAAHAAHBAHGEHGHHAEDEEDACDBBDGCDBBABHHCGCFGFEGBAGBFDDAEHBH,True +412,2.0,7.0,4.0,0.0,2.0,6.0,5.0,2.0,BGBFGBFGBCGCEACFBHFEABHCBGFF,True +413,28.0,23.0,16.0,19.0,25.0,12.0,17.0,19.0,BHADEAEEHEEAGEFBBCDDAGHHGHAEBDFBAFBAHAEHBECBDCGDGBFGEEAEEDBDDBHDEHGECAACGACABCABFABCADEAHEDBCGFEBFEADEBEGADAAFAFHADBACHABHCCDCDBFABGAEGCGFHACDEGHHGHGDHFBHEBEGC,False +414,4.0,13.0,10.0,10.0,10.0,2.0,11.0,8.0,EEGCECCGBBGBCGDEEAGEDBHCHHADHDBHEHCFBDBGDBDDBDEADEHBCAGCBGEGCBGCBGFH,False +415,13.0,21.0,20.0,13.0,22.0,19.0,15.0,24.0,HFDBGDBHHBCCFHHFBHFBHFBHACEFEHFCBGBBFBHFDGECGFCAABGCFGCHHBHHEGFEABCBECEECGDCHHFEDAHBAEEDECDHDGHFGHFAECAFBAGBDECDCHBHHDCEFCAFEHEEGEAGEAFEDEBACBDCBGG,False +416,21.0,17.0,11.0,9.0,12.0,14.0,19.0,7.0,CGHHGBDBAGBAGBDGACGAHFFBFAGCACDAGAAEAEFCCAEFBCFGCAACGEFFBDAEDABDCEGEFCEBBHFBHEBHEAGGBGFAHFEBFBBDABFAGGAGGDGADE,False +417,6.0,8.0,8.0,1.0,1.0,6.0,7.0,5.0,BADAECHCCHCCHAAFCGFBGBBHBBGFCFHCGGBGGBFFAA,True +418,11.0,22.0,19.0,15.0,20.0,16.0,14.0,28.0,CCEHHDBHECHCGAGDCCABHFHHEHDEGBEGBDDBDEBHBBGFFCFFHBDHBCHBEHBAHFFGFCDHHDCHBEABHDBHCBAAEFDCBCCDFHEFGBDABGFBCADEFDGFAGEHGBHCBCGFAAHEEHEFHEGEEHEEHCGHC,False +419,25.0,19.0,13.0,15.0,18.0,30.0,15.0,15.0,FHCDCFBEHCABEAFAFHEFDGFDCDEHAFGAFBDBBFBBGBAHFAGFBFFBDBDDEGFBDEBHCBFCEFCEFAECAEFECGADBABAEHFDGFGGBGFBGDAAAHAAHDFHGCHFCAFEAEEDECDHBFAGHAGFEEFAFFAFAHCAHG,False +420,5.0,4.0,3.0,9.0,10.0,5.0,4.0,4.0,DEBDADFEFCEHEABEAEEFEDHGDHEDCFGCFDDGBDGBEAAH,False +421,21.0,22.0,19.0,21.0,16.0,23.0,24.0,24.0,BGGDDGBHHHHGHHDAGFAGFBBFGGFGEHBAHECFACAGHEFCEADEAEBAHBGBBACDACDHCDHCHBCDBDDGCFHHFHHAHEEHCGCBGAADFBGEGFCCFCGFDHHDHCBFDAADABBCBFCFGDECBEFDEGDEDFABFADFGBFGFAGFADHHEGABCFBGEE,False +422,5.0,3.0,3.0,1.0,0.0,2.0,1.0,4.0,ABCABCBGAHHHFHAFCAD,True +423,8.0,5.0,10.0,3.0,2.0,6.0,4.0,7.0,CAHCAGAAEDGFCGDCFHCAHCAHBBDFAFFGBFBBCCCHCEHAH,True +424,4.0,2.0,3.0,3.0,3.0,5.0,4.0,1.0,GDFGCGACDACDEBFEGHEFFAAFB,False +425,20.0,29.0,28.0,22.0,37.0,21.0,18.0,23.0,DCDEFDAGCHCHFDAFEFFEHDEDBEABEHBEBFCBEDBCDCCEGCEBCEAHDHHDAHGAHBBBFABFABACBADHEEHEEAEAAEACDCHBCEDEEBEGGEBEFDGCBBBAFDAFCAFCHEDBEDGECHBHGFGECEDGDFECFDCFGHECEEHFEBCABCADEAFEGBBHBFGBEHCCHBCGBEFCHHCHGGGGDF,False +426,3.0,6.0,6.0,5.0,11.0,8.0,8.0,8.0,ECEBAECEDDEBDGBGHDGEBGECGFHGFHACHFGHFCFBEFHHBHEADEFGCFE,False +427,9.0,21.0,17.0,17.0,18.0,17.0,9.0,12.0,BHBBHBBAFBCCHEBDECFECDEFFGHCEFCAFAEHDGHDBHABEEBEEDAECBDCECABDAFDHDGEDBBDBFAFFCCBHCDHDBFDGFGBFCHACDBCGGDGGCBFFBFEEFHECEED,False +428,13.0,9.0,6.0,7.0,7.0,9.0,7.0,6.0,HDAAECHEGFFGFGCFHCBGAADAADAAFABFBEEAFFBBCBBEABECGHDGEDGDABDAFHCH,False +429,8.0,15.0,19.0,18.0,20.0,20.0,16.0,22.0,FGDFDDFHDGAFGFHEBABCDBHFGHFCHACACCECEACEBCFGDBHFEHFBHGHHEHEBGEAFFHCFDEFDADDBDGHFBDFBCFBGAHFBECHECBECHECECCEDCHGEEGEGFDFEDBEHBHCDGDHCHHGGDG,False +430,13.0,25.0,20.0,21.0,26.0,17.0,24.0,16.0,EFFGFCDFCEHCGHDGEECAEBBEGBECFEGHAADDAFCAFCBCEECFFCFCAGDACHBHHBGDCGDGGDEEDBHHGCHEDBEGEECEEBEBBDBAEEFDGBGGBDAEDHEFCGBCGFCGAHGFHDBGGBFBFFHEHBCDBADCEDEBBGAAGHBGHBDBDD,False +431,13.0,21.0,18.0,12.0,10.0,10.0,17.0,15.0,GAFBBBBFHGFAFBGCGGBBCABCAGDHGDHBCHBHBAHGGHEGHDCDBCFBCGECAEDDHBAEBDHBDHBDACECGEGGDHADBEFCDBGACEAHBCFBEHAEHAFGCCGCCFFC,False +432,14.0,11.0,9.0,15.0,14.0,12.0,12.0,18.0,DFAFFAHDHEDFEHHEDHCFHCECBABBDGEFGEDCDCGDHHFCHFCGGCEGABGDBEABAAHAEBDEBHEGHFGHDHEBADGADBAEHCEHDDHBFAGAAFFGH,False +433,16.0,16.0,12.0,20.0,13.0,18.0,9.0,14.0,FDCFDADDBDDAHDCBDCDDCDAEHAFAABADBECFAFBCFADAGCAGCDBAFCFFEHFHBFBEHGCGGDFGDABDEECGGDFEFBHCBHBEHBEABEHBAHGAEFBEHHHFEHFDFD,False +434,15.0,21.0,15.0,6.0,12.0,5.0,12.0,17.0,CBBDBGABGCDGCEADBCCADEFCCAHCHCDHCAHCHHABHBBHABEFCGCBGAFAAHEAFGAEGAHGEEGHEGBFBEECHEBBAHHCHDBHBBHBBABBGEG,False +435,0.0,0.0,3.0,2.0,2.0,2.0,2.0,3.0,CHDCEDEHCGHFGF,True +436,22.0,21.0,21.0,13.0,7.0,14.0,20.0,13.0,BHBGDAADEDFGCFGDHGAGGAFDCCACCHEADBCFBCGBFABEHDCHCEGBGDAGAADCAHGHHGHFFDEHAGAGGABCAFAFFACHACGBDGBDCBDHAGCFEBFACHBCABCGFCAFGBEBBCBBCBB,False +437,18.0,12.0,15.0,15.0,9.0,15.0,19.0,9.0,BEAEFBCFAADCBFGDGGHFCADAADGADHCBHDGDBGDBGDCGAHEFHGFAEBAHBADGCDGCGFCHFDEFEHFCAAAFBAHAEGDEGFEDCCBCGBFGBFGACGCCADFG,False +438,9.0,15.0,11.0,10.0,6.0,5.0,12.0,8.0,CBBCECABBAHBHBCHGGEGGDAEBEDCDFADBGDBGDBGBBCDGABHCFGBFGHFGHFEAAEAABHDDCGCCDCH,False +439,21.0,34.0,13.0,20.0,9.0,14.0,18.0,22.0,DBGDFCCFEAGHBHHCHHCBHBGHBDABCCBAFBAGBDCBDBBGBAFFDHEHGCBACBAEFGHBGAFGCFBAGHAHHAGHGCDEAHABHBDFEDBDDADDHFBHFBEABEABADBHFHDBABBHBAEBGCDCFHGGGBBGFDGDABDABDE,False +440,5.0,7.0,4.0,9.0,2.0,7.0,1.0,7.0,DEBHHHHHHDFAAFGADHABBFFDFFDBEDCCCCFBDDBDAB,True +441,9.0,3.0,11.0,9.0,5.0,3.0,13.0,6.0,GCHGCHBCDDAEAHEAGAGGCGEAEHACDFBDBDGCDGDGGHGCFGCAHCACDGCAEFD,True +442,26.0,15.0,9.0,16.0,20.0,21.0,20.0,20.0,EEHEFAFDDHDDBDEEFFEDFCHFAAGHAEHADBAGHAGBADAAEABCGBCBBFGCFGEFGEFGHDEAEEAFHFGHDGFAGACGCHBCHEAHGABGBGADGFFGEEBCFDHAEBAGBADAABBHFHHCEEFFEDFHAHHAHADDGFG,False +443,5.0,11.0,13.0,10.0,14.0,14.0,10.0,14.0,FCEHCEHCEDGDBBDGEDHEABEFGAFGAFCCFHFFHFBAEEGDFFAHECHGCHDCHBGFEHFHFFBBCBBEHCHHBECDEDBEDCGGGDC,False +444,9.0,3.0,12.0,6.0,9.0,11.0,10.0,6.0,GACGCGACGBHABFCEFCEFCAFGFEGDCFBCHHHHGAAAEADCDGAGEEEEECFFCDFGDFCDFH,False +445,9.0,10.0,13.0,13.0,17.0,11.0,15.0,15.0,DGCDBCDFEFHEHHEDDEGCCFCFFCGDEECEFHHFAHFAEDGGBBGHHGCHGBACAAHEEHEEDGGDGGDGEEFEBGHBCDCAACAHDHBFEFCEDBHBBAG,False +446,4.0,1.0,6.0,9.0,11.0,4.0,5.0,7.0,GACEFGGACGDFDECDEHDEHDEHEEDAHDCDFCDBEHAGFCHEEHE,True +447,26.0,19.0,18.0,11.0,16.0,16.0,12.0,21.0,EEHFFHCBABHABHAEHAEHEFFGFAGHBHAEEAEEAGAAGCCGABDACECFHGHHEDHCBHCBHCBAGDABDCHAHEFHFHHDDFBFFAFCACABEDFEDAGDBFCBDAGFACEACAGHABBFBBEBACCCGHCDBAG,False +448,6.0,5.0,7.0,6.0,1.0,1.0,3.0,5.0,HADHAHCACGDGBDGBAECACBABDCHDBHDCCF,True +449,11.0,2.0,6.0,6.0,9.0,16.0,8.0,5.0,AGAAHAAGFDFEEFBEDGEGEEFEAFCCDEDFFGFFGFFCFAEFAFHDFCBHADHFGHACCAG,True +450,11.0,4.0,8.0,12.0,7.0,9.0,7.0,8.0,FDEFCADCGCEBAHBGECHEFHCDACDABHGBFFDFAEFAEADGADFEDHCAHGDHDFCDAGDAGH,False +451,31.0,20.0,20.0,33.0,22.0,23.0,32.0,17.0,BCCAGAAGFAGCEGDBGDACDHDHGFBGBBDBFGBHBAHECEECDEDHHDFADFEDCEGHAFBCCBFADGCBADDFEFGEHGEFGDHECAEAGEDDEBDEADAADBCBGEDHDDFCEAAHBGBGFAGFDGFDEFEGHBAHFAGFDGDDFDFABCABCAFCAFCAGCAHEGHGDAADAGEFGHDGCDGBGHCFAGDEGA,False +452,6.0,6.0,6.0,10.0,8.0,9.0,9.0,6.0,AFEABEBDGBAFEDHGFHGEDGEHCHAGHECHCCFDADDFEDFEBAGCFGFFGCBGDBDD,False +453,13.0,18.0,14.0,23.0,17.0,19.0,19.0,12.0,DCGDCDDCADEBFFBFFCAACDACDCCABCDDFDFAAEGFHFADCBGCDGEDAFGGEHHEFBFFBFFBGFCDFCGAGDDHDDHFEHGEBGHDGHAEHBGBDEFCBDDEABHAGEBEEBHEDEGBHGBFGBGEEGB,False +454,18.0,22.0,18.0,14.0,25.0,31.0,12.0,21.0,FHADBACFDHAHHDGHBFFFCFGCBGDHFFFGFFGFGGFAHCHEEHFHDFHFFHFAHAHEACEGEEBDEDFAFFBFFBFBEFDCBBEAEHDFDEEEBBGCBFCFCBGBBFEHGCDEHDECDECBADEAEEACEACECCABBECBECBFAFAGHEHHABHAB,False +455,8.0,7.0,7.0,9.0,13.0,7.0,12.0,7.0,AGEBFEADAAGFABFHDEAFFCGFDEHGABGCBHCBGBDHBDFDEGCEGCEDCEHEDHGDAGEHEEGCEG,False +456,26.0,25.0,17.0,12.0,23.0,17.0,8.0,10.0,BCAFCEBDBGCAAFAAFGCBEAEDDBADBADCHEFFEADEAEEFEEGAEGEHBEGAFHAFHDFBBAEACCAECBBBBBFABEABDBBDABDCEDFECACHFHAFHGHDCCAGFEEACEABFABFBEFAEBBGHBCHCC,False +457,17.0,13.0,15.0,8.0,13.0,12.0,8.0,11.0,HFCEBGABGABDAECBBCBBEBEEBFEAADACFHFEHFBACAACDAFHHFAHGAHAAEAHGHCGFCDFDAEEBDECCHCCFFGBEGCDFCBCAEDHG,False +458,4.0,0.0,3.0,1.0,6.0,6.0,4.0,0.0,FEEFEFFGCFAEAGCAGEADEFGC,True +459,21.0,25.0,18.0,16.0,17.0,17.0,23.0,17.0,HDAGCGGBBGBCEDCBBBEGFEGFEGFAFFCGFCBECBFFBEBBGBFABCAFAHEHEDHGDCCEAAGAAGBCGHCBHCAEDHHDFFDABEFECCABHABEDBEGBEGDGDFGAFEAGCDGCBHHDHCAHGABFDEADBADBHGAGAHFHGCHDB,False +460,10.0,14.0,5.0,9.0,15.0,9.0,9.0,8.0,EDEEGEAGEGBEDBDFGDEABFAFDAGEBBABDAGDBGFFHAEHDEABGBHABEACEFBDFBCHGCEBCEBEHHHFHCF,False +461,5.0,3.0,5.0,6.0,2.0,12.0,7.0,4.0,CEAFFGFFGFFDFHDFBDADACCGGCABAHGFBFFDGHDGHEFC,True +462,6.0,6.0,14.0,9.0,5.0,9.0,18.0,19.0,FGCDHCHHGHDGADGECGHCGCGHCEDGEFFHHFHFGBAHEFGBCGHFDHFHHCGHCGHEGBCCBDAHDHGBHACGCGFCDABDAG,True +463,3.0,5.0,4.0,8.0,5.0,3.0,5.0,5.0,DGAFBBFAHGEGGEGBECECCAHHDDDEDDHFDHBDCB,False +464,8.0,5.0,4.0,6.0,7.0,4.0,8.0,3.0,DACBACHAGHBEHDEFEADGGCFEDGEBGEAGBAGFDGFDAAEBC,False +465,13.0,13.0,10.0,12.0,11.0,18.0,10.0,10.0,DFBGFDFFDGBBBEDGEDBECEEDFHAAACAAHHHHHBGGAAAFHACDACEFFHFFHAGCBEFBEBAFGAHGDEGFFBFDBFDECCECCGBCDBFDF,False +466,1.0,7.0,5.0,6.0,4.0,4.0,5.0,8.0,DHBECBCDBGDBHDBHFHECAECFFGHDGBBGHCGHDHFE,False +467,8.0,10.0,7.0,7.0,13.0,10.0,14.0,7.0,GGBEGHAGEGBEDBCAFFBHEEAEFBEGCFGCFHBFEGFEBFHFCHFDGDDGHDGDCHAEGCEGAEDCEBAABABG,False +468,7.0,9.0,14.0,4.0,4.0,10.0,8.0,4.0,FECAECBDFBGFCCFECFDCBGCBGBFDAHGAFGBBEBCHBCAAHGAGCCCFHCFGCDAF,True +469,11.0,8.0,10.0,17.0,9.0,15.0,9.0,16.0,FHDFDDEACFHCFCAHDEHAGHACHDGBAGBEGBAGEHHDGHFEHADHAEFAGGCFECFBCDGDHHDADBCDBEDFFDFFCCBEDHFHAFHDFDB,False +470,1.0,3.0,1.0,1.0,2.0,1.0,2.0,3.0,CHADBEEBGHBGHF,True +471,17.0,15.0,26.0,18.0,19.0,21.0,23.0,27.0,GFFCCCHCDHAGAEGFGCBGCBFCFFHDFBDCHDGHFEAFEAEEAEGDHGHCGABGDCGDGGFFFACHBEAEEDEAHFAHDHHGCHFHHGGHBBECGECEEDAHCACCBBCFBCHGCHACFDCEDAHCAHFFFDABEEBCBAHFCHBHBGDGECGEHDHGDHGDFD,False +472,2.0,5.0,3.0,5.0,4.0,6.0,6.0,2.0,EGHFGBFEBFEDFHGCCFEABDADDBDGBGCFG,False +473,20.0,30.0,26.0,33.0,27.0,26.0,18.0,15.0,CGAHFAGFAFDBCDEGDEHBEGBEBFDGFECFHBFHBEEFEECCEFEFFHCDGAHABDFBAGBADBADBDGFGCDCABGAEGDDDDACFACEAFEBEGDCGCEFDEBEEDFEFFDABDHBDEBCHBHHFDDBCDFGDAGHBDABFBDDDFFBBACBCCBCABCACCHGCBFBDDEEBCGDCGDCEDCHFEHEAHE,False +474,19.0,17.0,14.0,18.0,11.0,17.0,20.0,12.0,GAGCCFFCGFEDEBFFAFCGDHGEHGEHGHGFDFAAFDADDADCACCBFBDGBGGBFEBCABDAGHGBDBBHFGEAGCDGFDCFCHFAGCBBABBABAEBCFCDEDHGHAEHAEDAEDGFDGDAHHAB,False +475,29.0,21.0,29.0,16.0,8.0,11.0,32.0,19.0,GGHBGAGFAHFBGAHFBHGBHGCEACHGBAAAFHHFHHCBGCGAHBDCCDGAAGHHDBDCBDFBDBEACAFCEDCBGABGAFEACGACGCCGBCGHAGADEAHGDCGCBBAFBADCGBEGBEGBAGCGGAGABCCHCDACGHDGEAHAADFCCHACDGCDGCDFC,True +476,1.0,0.0,5.0,0.0,0.0,3.0,1.0,0.0,CCCGCCFFAF,True +477,12.0,12.0,12.0,10.0,3.0,21.0,15.0,7.0,FDFAGACBDCBGCEFEFDGAGGBBDBBAFCADCADCFCGFCFFHFFHBFCCDAGAAGBFDCFCAFHDBBGHDGHFGBFBEFGFFAHGAGGFH,False +478,17.0,16.0,18.0,22.0,16.0,25.0,17.0,21.0,ACEFGEHAECACCHBGAFFBCFECADCEFAEDEFAECBCGBCHFGHGEBAEAADHGDGAFGDDCEHCHAEHDEFGHHHBHABFABFHCFHCFHCFBDFBHBEFFEDFCDBGDAFDGBHFBHAEDCFHBDDGADGDFCDFGDGBDGDFHDFHG,False +479,10.0,7.0,13.0,9.0,7.0,6.0,9.0,3.0,HGCDGCAGAEGAGCCBCCFCEFEAFEACGGCHDABDECHFABFEBEBADBDDBAACGCFDCDDG,False +480,1.0,0.0,4.0,0.0,2.0,0.0,5.0,0.0,GCEGEGGCCGCA,True +481,21.0,16.0,14.0,17.0,11.0,10.0,25.0,16.0,FDGEEGBBDHAHGDHBHGBGCBCCFACEAEGAHHDHBGFDGADAAEAAFHCFHDFABGCBGAGGADCHDCECEDBDACDAHDAGDBHHBAGFAEFGBFGBGHAGAAEDCBCEBHEGHDDBGGGGCAGCFG,False +482,12.0,17.0,21.0,17.0,21.0,22.0,20.0,24.0,HCBHEEHCEHCBHADGBCGBEEHHFGHFDHFCHCGHGGHBGCBCHGDDACDFFFFFGBACFECGCFHFAEDHDDBDDHDEGDECAGCAGHAEHAHFEFDEACCDGGGFGCEBCEDHFCHBHBEHDDABHFFFAFFBFEBEBBGAEGCEGCEBFE,False +483,19.0,21.0,17.0,13.0,22.0,21.0,20.0,24.0,GDGGEGFHAHAEHADHCEHDAACCBEFBEAAFFAFGHHBHDBFDFFACBGDDGDHHBACBFDHFDBFEFFGABDACDFFHGFCCAEBBHGBHBBEBGCDGCHGCHEFHEAHEHHGACCACGAHHEBGECGACFEEEBEFBCFEEGEHGEAGBFHBEB,False +484,14.0,17.0,19.0,19.0,23.0,9.0,30.0,14.0,DBADEECEEGGGCGGCHGAEDCGDCDDHDGGDEBHBBCAHHADGGGEGCECCACHAGHAEDABCHGGHAGDADBEFHHFBCEAGAGGDGGHGGACFFBFGCFGBBDBECBEDBGFEHDEBDEFHEBCEBAEGEECEGBGFCDECD,False +485,23.0,20.0,17.0,18.0,15.0,7.0,16.0,20.0,ADAADBBFAFFAFAAGCDHCHABGABCAGHBGHCAHEECBECGDHHAHDEFBGDGDBGDBAAEABGHBDCECCBGGHCEHBFABFABCACAECBCDDCBEEADEADHHDHDDGEHGEHGEDCBDCHAAGGBHHBHE,False +486,19.0,15.0,16.0,14.0,11.0,13.0,25.0,19.0,GDCGHFGHCBDBAAAAAACAGHBGADDCCHEGBCBDAFDBGDBDEAAGAHBAHADCDDEHHFHEAGCGGCGGBGHCGCBGCBDCGGGFEGBEDFHCFEBFEAFGAEGCFGCFGDEGAHFEHABFFBHHHHHH,False +487,17.0,28.0,19.0,19.0,12.0,13.0,19.0,22.0,DBDEFAHAGFBGHEGHDDBBEBHEBHDCHFEHGEHGBBACBAGAAGEBBHBDFBDFBDCCHCCAEBGDGDCEBCACFAEGAHDFCCBHCEHDEGCBGABGBDFHCFDDFDBFGAGGFHBCHCABDABHAHCAGCHGBBBCBHFDHADHG,False +488,11.0,5.0,10.0,9.0,17.0,10.0,8.0,12.0,HFEBAGAEFADDEHDEHAEHDEHAEDEEDGBCHCFECFBCHGCHGEDBEABGAHFAHFHEEGFHACECCADEDCEFCAFGFG,False +489,15.0,27.0,19.0,19.0,24.0,16.0,18.0,23.0,GDHCDCEEBEBBHABHFBGFEGDDHDFACCAGGADEBDEHABHAFHGBHAFCAFCBFCFHCHDEHDBBFABDEGCECHDDDDGEAGHAFHFEBBEAHCAHFGHABEFEHDHHDCGBEHBEBCCBGDGEBGEBEECEGBECBEBDEBFGHABHFFDGCCGBC,False +490,3.0,2.0,6.0,3.0,7.0,0.0,1.0,4.0,CBCEHEADEACEADEDBCGHHECHEC,True +491,14.0,16.0,16.0,14.0,17.0,13.0,22.0,10.0,FADFCGFCEFCEBCGBCBBCBBAFBGGBGBEEEFDBBDHEEHGHAGHAGDDGBEAAGDFCHADHGDHGHFBDEDDEFECCEGGGGGADGCBEEHDCGCCGABHDBFAFEEECCAGAFGAFCA,False +492,26.0,18.0,20.0,24.0,26.0,19.0,29.0,28.0,DCADFADCEHGDGGFGEAHEHHAHFCCCGHBAHEAECBBGGBHGBHDBAAFECHEBHGFHCAHDAHDAHACHCGHCAAEGGGDBGDGGDEGHHDCGEEGEDAEDCGFCDFEFFADHGBCABHDBEGBGBHCHFGDFEFFEBBEDBEAAEFEBFGBAHAAHECDGDDFDACCAFAEHGEDGEDCEHFGHFA,False +493,1.0,0.0,2.0,1.0,4.0,2.0,0.0,0.0,ECEECEAFFD,True +494,11.0,16.0,14.0,24.0,25.0,15.0,20.0,16.0,HFCEDHDDCEGCFADBEDCEDAFBACGFFGHDDDGBDFEAFCAFHDFHEFBAFBDEBEHCEDBHDGHDFAEFCECCBGGBFDBCDHAHBGEBEEHGGHABDGDGGDHADGAEEBFECEECGEGGEBEEBHGCHGDHGDEDE,False +495,15.0,21.0,13.0,15.0,18.0,25.0,20.0,12.0,GFGGDGBFFFDCCDGCDECAEFFFHCECCEDEEAEEBEFHDHBGGBGGEGHAGEAGBGEAFAHFACFCHGBBGBBCCDEGDFFFFABBBEBDAGDAHFACFAFDABDBBEFDEFAFBBFBBFEHHGHDDHBFGAFHEGC,False +496,14.0,17.0,8.0,12.0,24.0,10.0,23.0,11.0,GBFGBDGAFGBGEBFEHDGAFEBCGGGBABDAEDGEFBAFHEFHBFHEEBGEBAEGGEFGEABAHBGHBCFGEGCAGCEHEGHDDEBAGCAGBECDECDEGDEGDBDHEEHAEHDCAAE,False +497,8.0,11.0,13.0,8.0,7.0,15.0,9.0,16.0,EHBHFAFCAGEGGCCGCAGBAGHDFFCFHBHHDDHFCAECHDBHCBHAFFDFEHCGDFGAFCAFCGFEBBCBBCFHDHEDHFBHEBH,False +498,3.0,6.0,8.0,3.0,3.0,7.0,4.0,5.0,CHECBEABACCGCBGFHFFBGDBFDAFDEFCGBCHFHHC,False +499,7.0,4.0,9.0,5.0,5.0,8.0,3.0,3.0,ECEEFHFFACFAHAABEABDCCGFDGFCCFCCFGDABDCDEBAH,False +500,7.0,8.0,5.0,8.0,4.0,3.0,2.0,4.0,CAEFHGBDDBDDBDDBCGBCFDFDHCAEAEHBEABAAHACB,True +501,22.0,26.0,22.0,26.0,16.0,25.0,21.0,27.0,EBHCGHBFHBFBAEEAHFAHEADFGDFBFHCHCCHGAAAAAHAGBBBDBCHCEHBHHGDDFBEFDECDBFFHFFDDDDDFDAACHBDABDHGCEGCGHFGAFDCFGCFGBBGFACDAGHFGHEEAEEAHHBDDAABBCBCDDCDCGHFGHEBHABGFCGCEGCBCHBCHDGFFBFGEFDEHDBAD,False +502,10.0,11.0,12.0,13.0,8.0,15.0,13.0,13.0,GFHHEHDCHDEFDADGCDGBDFADFHFACFACACBFCGFCAFEECBECBACAFDEHBGGAAFDGHCBDCBHGBHDFHDHGEFGFHGFHDBEBGGB,False +503,5.0,6.0,10.0,4.0,4.0,8.0,9.0,0.0,FEDCEDCGBGGBCFCFEDBEGAACABCGCCGFFGFFDAGGBCABCF,True +504,7.0,14.0,10.0,11.0,12.0,9.0,6.0,15.0,BDBBGBFCEDCHDCHEFFECHGDEEHEDHDBCDHGABFABFBBDBBCEECHEGFAHCGFBHFAHFAHDCEAHBDCBDHGEHAEH,False +505,21.0,9.0,16.0,11.0,15.0,16.0,15.0,15.0,DFAGEAGEAFCCECCECFEGFHGDHAFBCHEDHEHBEAGFCHDHGAHFFCAAGAAGAAGAFEDGCDFHGEHFEDFBDCAHGAHBABEABGABEDFFHGFCEACHADEBCCBGFDCCHA,False +506,17.0,15.0,12.0,11.0,15.0,5.0,18.0,14.0,BHGDHFBGBBABHAEGAEDAEAEDBEDGCGHADCFEHAGHAHHAFADCBBGEGGBDBBDEHHHGGBGADGACHCEGCEHAABFAEHAECAECEECFBCGDCGBCGDG,False +507,23.0,16.0,18.0,17.0,15.0,30.0,19.0,16.0,CAHCHFAHFDGFDGEHAABDAFCAFBAGBHGHCDBAAFGFFGADAHDGDGGFEDFEDCCCCDHGFFGFFCHFAFEAFEFHGBEFEEFEECDBGGHHGHCEHEGCADCEBAFBFDBGBCHBFFBFFBCDBDGAGFABEAEAAFFCBFCADCADHA,False +508,2.0,2.0,6.0,5.0,8.0,2.0,3.0,4.0,AECAHCEDEEGEDCFFCBECDDGGDHECHEBH,True +509,10.0,15.0,13.0,10.0,20.0,25.0,8.0,14.0,BFFFFGHDGHBEECGECGEHFEFAGBHGBEDEGAEAHHFFHCFCFFHEFADFBCEHCEGFAHFHEFECBDCBDABDCBFCBDHBEFCEFCHFEBEBFEAFACFHFBAFEADDDBE,False +510,9.0,6.0,15.0,8.0,8.0,15.0,8.0,4.0,CGFCHFDFCDFADGADECCCFCAFBFFCCFEGFDGFCGCCEBBEAEEAEFGHDGDFCHFEFAGDABBCBCAHA,False +511,1.0,1.0,2.0,5.0,3.0,1.0,4.0,3.0,GDDGCBGCHDEEDHEDFAGH,True +512,16.0,13.0,8.0,20.0,20.0,20.0,19.0,18.0,GEEGAEDHBDFBGBGGHGEEDHEHEGFEGBEGFHGEDBBAHGFDAFDAEDGFFHFFHEEHDEHDGDGADCADFADABFHDFCEFCHFDGAGABHAFHGHCBFCHEHBEAAEAAEBCEDFGABDCHFCBFDFDDG,False +513,2.0,0.0,0.0,0.0,3.0,1.0,1.0,4.0,HHEHHEAGAFE,True +514,16.0,32.0,27.0,32.0,20.0,18.0,31.0,18.0,FFCEHGEAGHCGDDGHDFEDFDDBDCHDAABHAGDEGDEGEFCBDAEABBAGBCGHEEDCCBCCAECAGBDFBCHGHHDHADGGGCCFFAGBGFDGACBHCBDAEDBEDAGDHCDGCEGFGCEGDADDCHBGHBAHBEGBEFBFGBHDHGEBBDBBFCCCDEBDFBDBBGFBGFBGFBGFHDBCCCEBCGDCED,False +515,26.0,15.0,26.0,29.0,17.0,18.0,23.0,22.0,GFHDAEAAEGAEGCEDCDDCAHCABBAEBECGEBHHGAADFECFBCFECEDGDDCDCGDBDFGCGHDAHFADDAHCADDGDFGDEAAGAFDHGCHDCBDCGCBGCBFABGAHHBHDFHDFDDGDCFFAHBEHECCFCBACHACEGCEHHBHFGHCGDAGDAGECBFHAAGFFDEAH,False +516,12.0,12.0,20.0,17.0,22.0,17.0,13.0,11.0,EEBEADDAFDADAHHEEBGEBFFBEBCCDFCEFCEFCEFCABEFHEFCEFGFCGCGHCHDCGFBECACAGDAHDGGDHFDHADEADBFHBFABDHECFDCHCEGGDCDDCGBEAFEBECGECGE,False +517,17.0,18.0,11.0,13.0,13.0,9.0,14.0,20.0,BEFHACHEDBAAHAHHAGBAGCGGHAADEHDEHBBHGEHAEHGEDGEBCEBCHAAHBCHADHCDBGFBGHAABBFFFCCFACBGDBGDBFDCFDCBEHFHHEGBADEDHEGGABD,False +518,20.0,13.0,17.0,15.0,17.0,19.0,27.0,13.0,CFECBCGACDECDHCHAGGAGGAGGAGEAGHBGFFGHHDEHDHDDGAAGDDGDHBEFDAGBABEECEAABAAFAGFGDFCDCEFGECBCGGEGHEGHBGEFHFFDCCAFGAFEAEEFCFACFGBDCBCAHGBEGFDFHBFB,False +519,4.0,10.0,8.0,8.0,7.0,6.0,3.0,5.0,EABADFAHCBFGDFCDCCBACBEFDGBHGBHFEHFECEDHBCCBEDBEDBD,False +520,21.0,21.0,12.0,9.0,4.0,4.0,12.0,8.0,FAACBBBAABGAFADBABBDBBABHACGACBABBHHCECAACAHGDHGABCBDABAGBDGDAEDGCDGCABFEHEAHFBHGADGCCGBCGB,True +521,7.0,6.0,5.0,6.0,9.0,6.0,4.0,9.0,HDFFDAFDAFBFEAGABCHCHHBFHBGEBHEHHEHEDAECEEGACDECDBGA,False +522,7.0,13.0,6.0,12.0,9.0,15.0,17.0,9.0,FEHCDBCDGGDGGDHFBHAEFDEFDFGEAABAFBHCBEFBACDGBDGHHBFGDFEDEEGGBGGBHGFGFEGHCFBFFBGFGHBADCAD,False +523,13.0,18.0,26.0,23.0,24.0,18.0,20.0,22.0,HDCHAFHBBHAEFFCCGDFGAFCFDBHGFGEFBEGCEHDHHEGCEGEDBDDBGAFHCFHCAECHBFHADHFDHECFBCBBEEDGBCGEEEDGHFGECCECDACDGFBCACCDDGDDEBDGBDGAACABCABCFBEFEDHEDHDGHEFHECDECGAHGEHGCCBH,False +524,23.0,26.0,27.0,25.0,18.0,14.0,25.0,20.0,AHEABADDECBHGBEGDCHHCEDCECAFCACEFEEGGDGGDGEDGCFBAEAHFGDFCACHEBDDBADBADBDDACFAFAGCBBHBGGFDBFDGAAGAHGDHFBEEDCCDCBACHHCHECFDDHABAACAAGHHGBGGBGFBGFHDCBDCBHBHHCDFCDEBGHBGACGCCGECBBBEE,False +525,9.0,5.0,7.0,9.0,10.0,14.0,16.0,12.0,GDEGFEHFGFFECEBCBHHAHAGHAGDFCDHBDAFFFGFGGHBDHFDCFDCDGFEGEGCEGAGAAHAGEGHEHFEHFGCDBA,False +526,21.0,20.0,28.0,24.0,24.0,22.0,22.0,28.0,FBFFHFFDFEBCDDDFBEABCGECGECFHFFCFDAACAAHAHCDHGHHFHCBHBDHGDGDHAHCDHGABAABGCGAAFBGFCDFCDFCABEHDEAGHABHEBAEFHCAEABHGHHACFEGEEFEEGDFGDCCDCEDHHGBHGEHGECGDHDDAFCEBDHBGGECBDCBGCAGCEBCECEBCEHCDHEDF,False +527,20.0,11.0,8.0,13.0,17.0,8.0,13.0,14.0,DDHGDHCDHDDHEGFEDECAEHFFHAABEGBEHBCAGADGACFACECDEAHGABBCEAAEAGFABAABAHGFHEEGGDCEBAFGFHGAEDHEDHEABEABDHBG,False +528,9.0,13.0,8.0,10.0,8.0,6.0,9.0,7.0,ECDBCHEGHFFBEDBGDBHDBHDFHFEBBCDFDACACCBEHBAGBAGFDGADGACHABDAEABGGEGCEB,False +529,2.0,5.0,6.0,3.0,4.0,6.0,5.0,4.0,FCBFCBFCDCHDEHBFGFFGAEAHEGBCGCHDEBG,False +530,5.0,3.0,3.0,2.0,4.0,2.0,5.0,5.0,AFBAEGACGFGHCEHEBGEHGHDAHDACB,False +531,14.0,18.0,15.0,23.0,16.0,17.0,15.0,32.0,HBAHEDHGDHCDHDEHDEHDEHDHFAGADFEEHBBDFHDAEDEEHHHBHDFHDFHCFCFECABGGBEGCEBFBBDBDCCHCAACFACFHEEHCHHDHGFHGFHDCDDBEBGHAFFCGBAEBAHBGHAGFBGAHCFFBDGDCBDHGHGDHA,False +532,8.0,6.0,17.0,12.0,9.0,14.0,14.0,11.0,DEGAFHFDCCDGCHHBHCFDCFDCEGGFHHCAGEGBFGBDGDAGHCGCCGDCHDGEDBEFFCFDCGHCEHEGHACCAFAFFDFFAEBAEBC,False +533,15.0,11.0,12.0,12.0,16.0,22.0,21.0,18.0,GAAFFACGGFHDCBDFBAFBAGEAFEBFGGFDDEGFEACHFFBDFGEGDFFAHFHHAHHEHHFHFABECBDHHDCHDGGDGGEFGEHACGACGECEECEEBDBHDHHFHEFGGCABCAFEFCGGGBA,False +534,6.0,6.0,12.0,13.0,5.0,12.0,12.0,8.0,HDGAGHFGHFCHABHFEHFACCCBCEGCGDCDEADCFDHGDGFDGFBGCDCHFFEGFAFDDFDDGADCBECBGB,False +535,22.0,16.0,25.0,15.0,17.0,33.0,16.0,16.0,FBFFEECEEDFEFEEBGGDGFEAAEFCGFDGHDGDEGAAAHACFECDACDCHFCHFAFFAFEGFBDFECHHBACBCCACDAGFGDFEDFCCFHCBCCFACAAGADGHEFFCBFHDFCDHBHGECAFFGBGBFGAAAFBHFHHFEBFCDFCBACBHCBHAB,False +536,20.0,17.0,26.0,15.0,22.0,17.0,17.0,16.0,BHHBAFEEFAEFAEDBBDFEEBCEHHAAHAGBDGBHBECECCBFFAFEACEGCEFEECDDDGBDABEEBEHAAHCFCCEACDAHAGHBGFACFHCGHCFCCBCFGHDHCDHCDGCEAHGAFBADGGFCBFCGDCGCCFADECDGGEGAEB,False +537,13.0,10.0,5.0,5.0,10.0,8.0,9.0,7.0,EADEDEAAGAEEBGGHHBFFBFEBFBBDEAHEABCAHCAEFAGDAEDBFFGFAGAHGCHGHABCGBC,False +538,10.0,10.0,16.0,12.0,12.0,14.0,12.0,13.0,DFCGBCDFCDGBDCFCFFCFDAHDCBECEEBEDBEHECFECGAHGDHEAHAHHGFHGDHFFCGGCEGFGGCGCAAHHAEHCBDFBDEBAFADFAEBCBH,False +539,2.0,2.0,4.0,2.0,0.0,2.0,1.0,0.0,ACCFCAFCBDDBG,True +540,3.0,8.0,6.0,4.0,2.0,10.0,5.0,6.0,FGBFBFDBFDBFHFFGCEAFHCCBFCBECFABGDGHDGHBHHAC,True +541,4.0,4.0,3.0,5.0,9.0,9.0,6.0,7.0,HHFDFBDFAFFAEFEHGEHGEBGEAHFDEBCGHGGFEAFDDHCEBCE,False +542,1.0,6.0,4.0,1.0,3.0,1.0,2.0,0.0,EGEEDACCFCCBBBBBGB,True +543,11.0,8.0,11.0,8.0,8.0,12.0,13.0,10.0,CGFCHFHAFHGCGCCHCGHGACBDDBCDFADFADFBBEDAEGACFAHHGBHGDAEFGEAGEABHBGFBAEEGEHDFCGFCF,False +544,1.0,2.0,1.0,1.0,0.0,0.0,2.0,3.0,GDAHBCHBGH,True +545,20.0,18.0,24.0,26.0,24.0,22.0,18.0,33.0,CBHDDADAHFAEFCEHCEHEBHCBGCHAAHAFHFFEAFDAFBEEGHAGDDDACDHCEECEGDEGDEGBADBEDBAACEECHFBFCHFHHEEDBHHAEFCCHHFDBFDHCHHAHHAHGCHCCGFCGBGGFGDFBHFDGGDCEDADDADCFBCHBCBFHEHBEGAFHCCBEFFHDHGAEGDBGDEHD,False +546,29.0,23.0,21.0,19.0,21.0,27.0,25.0,20.0,BHEADFCDFGBFAFFACEAGFABFACFACFHEBHBFHDFGEGCEHCGDCDFCACAGDEBDEFAEFGEGGHCEHEAFEGECAAGAAEFFFFDFGGGCDGBGEBGHBGEBADFGCAGEADDBDDBACCCBDBBHAAABAHBACGECDDHGHHGBFEACHBFHEDCFDAHEAGCBGBAHFAHFBHFBH,False +547,8.0,14.0,13.0,15.0,21.0,12.0,10.0,20.0,CHCHGGHDDADDEGDBGFHCBECDEFBGHEECEGCFAEHHEHHCHHCHFFAAEDAHDEGBEHAAGBEHDEDBCFFEFCEFCHHEHBEHBEHEDDEGDGABCEBDBBCBFFBDF,False +548,5.0,4.0,1.0,2.0,4.0,2.0,2.0,2.0,ACBADGEEGEEBAFBFHDAHBA,True +549,14.0,13.0,9.0,11.0,17.0,24.0,19.0,14.0,EHAEHGEDBEDCEGGEHFBFBBGBGGFHAFHBFEACBACEADGFEACGFEGFADHGDAGCBGHGCFEBAHBGHAHADDAFDHGGHGFFGFFCFFEAFEGEEFFHFDBBDCBEHFFDFAEFC,False +550,8.0,20.0,16.0,21.0,30.0,20.0,19.0,15.0,FHEAEECEEGBBBBBHBBDDCDDCDBCBFFEGFBCEHEEHEEBEEHFDCEECGBBGAGAHCAFCAFGDEGCEFEHCDBEDHGCGFFGEEGEECBEFEHFHCDHBDFDDGGDHEFHGDECDEHEGACFAFFGFBGBGAFGDDDDDBEFBH,False +551,8.0,3.0,13.0,5.0,6.0,13.0,5.0,7.0,BDFEDFGCFCHFCGCAFFAFFHFGCAGHAEHCBCCEHCHDCADCFFAEFCCDHGEFAEBA,True +552,10.0,10.0,17.0,16.0,16.0,11.0,4.0,13.0,CABEDBDDCCDFHBACBAEEDFGACHECHECEDHDDBDDHAHCBHEFHEFHEDDGACAECHEFBEFDEDDHCBHCHFGBFEBDCFACEGCAACFCEF,False +553,29.0,25.0,19.0,15.0,29.0,33.0,22.0,26.0,EABECBEDDEFBHACGBHHEHFFAFFEDBAGFCHDGEDEHDGDDCADHAFFABHCFEEBAECAECHHHACCAEABEABCCECFECEGCHGCFFBFFBEFDGGAGAECHEHHDHHABDEHAEFFEAFAFFAGFHGEAGFFGFAACAEFFEGBAABFGBEGDFHDFHEFBBHDHHGHBCABABBFBBGBGGEAGBFGCFH,False +554,19.0,13.0,14.0,11.0,11.0,13.0,12.0,8.0,ABGABGBBFEBEDGCDFCEAGEAGHAGFAGHACHCDHADCADFGDCDDAFEGFEDHHAGCGCFDEHBEFCFFCFEABGABFCHEBABBACADEAFBABACC,False +555,4.0,7.0,2.0,2.0,5.0,4.0,2.0,1.0,ABBABDFBHFBEFEGBAGEAEEFDCCB,True +556,33.0,24.0,13.0,22.0,28.0,22.0,18.0,30.0,EEFABBCDBADEGEHHHCAHGEHABDDBDAGAABDGBABBAGBEBHEFDEDCHDAEDBFHEAHFAHFABFCBEHBEHAEHCHHFEHBEHFEFFHAFHAGHEGDDHBCEDGAFGECHHDHFAEFAECAGAGCEGADDAEBABAAHHAHGAHFEEECAACGFCDFDDFAFEBBGHBGBAFBEHDFGDCGDFA,False +557,21.0,20.0,17.0,15.0,9.0,13.0,11.0,17.0,FFFCCBHDBHDBDDBDDHDCGFBAHBHCCDAADHAHHADGADCCHBCFECEACECCFDABDCEHEHHEBHDFFABAABAGBEGAHGACGCGGFBBHBAFBABAGHAFHFGCGDEFBBCABAAE,False +558,17.0,17.0,12.0,11.0,13.0,15.0,10.0,21.0,AACABFAEFAEGCEBAFBFHBDHEAHEBEEHDHHBHCBFGAFGFCACBFBDFADFCDBHHBHDACECHHDABGBBGFGHDACEBCEBCAFHDEBDCAAHHFHHFGHEGAEGHFGHD,False +559,14.0,31.0,29.0,20.0,24.0,28.0,19.0,25.0,CBHCBFCBGABHAFHAGDBEEHABFAEDGEDECFFCBFDFFDEAEHDDCECEHCBACBDFBCEECGGCGFCFHEABDABDGBDAHFHHGADGEFHDGHEFHEBBEBGCBFBBDCEGFFAHGBHAFFGFFHEFHCCHBBHFEHGBDDHCBCFBCFBCADCDBCGCCBBCBECGDCHDFHBGHFGFCEEHEE,False +560,11.0,11.0,9.0,9.0,7.0,8.0,12.0,11.0,FDCFDGECEACDHCFAFGAFAFECFCHECHABHGBHBBHBGEGGAGGAFDBHDCHDBEDGABEAGACHBHDBDABGHG,False +561,17.0,20.0,22.0,24.0,12.0,25.0,33.0,19.0,GFGGFCGFGDHGBCGHGHHGHCGHDGCGCDDCHGCFGFAHCHFDFCDEBDEBGFCEFCFFGAFCCGCHACBFDFGEEBBDDBECAFGAFGADGADGDDGADGFDEBDBBDBGCAGHGGDGGBBDFHCCDCEFABHHBHEEHBDHAFAGEAGDABFAHHAFBFGDCEBCBFFA,False +562,11.0,10.0,11.0,8.0,5.0,15.0,7.0,5.0,GBAGDDBFDHFDGFAACAACBBGFGEBGFFCFFCEFBEFBCBACFFCAHCAHEEDBAHFCFFCDDAGCAHDB,False +563,20.0,11.0,17.0,13.0,14.0,9.0,14.0,23.0,BAGDHGEHCAGCGEFAEFBCCHCCBDADHBDHADHCGHAGAFEAHHAHHACGCEACAHCDHBDGGDFEBFHHDHHCAHGAHFEEDGFDECDHHEHACFGHFECEGBBCAACAABDABEGBE,False +564,25.0,13.0,20.0,11.0,13.0,16.0,8.0,5.0,AAAAFFCFFBBFABDAGEAGAHGACCFEFGEGAEAACACEFCFFCDCHFBBCBCCADFBHFDCCBGABGCBABBDFACAAFGACACDEEDECDBDAEDAHDAECAECEEHF,False +565,28.0,15.0,20.0,25.0,16.0,15.0,18.0,16.0,AADAACACCACGGBEGAEGBEGFHCHCCEBCEBDBBDBCDAEDEBDABDFFHHEAADAHHGHGBDGCAGFADAADADFHEFHFGDEBDFCAFEHFBBFDHCDADDACDHFHAGCGDAGCABADCADEAGEGCHDDBDCAGFHGHCGAEFFECE,False +566,7.0,8.0,2.0,9.0,6.0,8.0,0.0,5.0,HEFHDFDDHDBEDBEFBDBBECBAFBFDAFHAFEDDBCEAAAFHA,True +567,12.0,8.0,8.0,9.0,5.0,12.0,6.0,5.0,DADDAGBGGBCHFGFDAFCACAEFADFGBFABCDDFEDFECHECDBAEAHCAHBACBFFAFFBGH,False +568,27.0,25.0,25.0,24.0,19.0,25.0,34.0,18.0,GGBDADGGGAGEFFECFEBGEADDADDAFHBBHBCFBCGGEGEDHDHBDFBACBGCFACBCGBEGHHGCAGHGBAFAHHBFHAFECHCABFGHCDHEFEFCEDCEGBGGDAGFFGFFGAFBEFEAFEGFDBFCAGCAGCABAHHHCEACBGEBDEAACCFGGFGDBGDCCDBEGBCDFADBAGBADDADHCDHCDGA,False +569,17.0,19.0,19.0,27.0,20.0,24.0,19.0,16.0,DCECCEHDBFDEDGEAGFGFBCHBCAGAHGFDAFDBHAGEADCHDCDGCBHCEFCHFCGFAADABFABFEECGFHHDHBDEBDBCFEEFEEAECGDBFCBDHBDEBDAFDAHCGDEBDEHDFADFDDFGAFEFCAFHDBEBBDGGACDBCHGFFGFGGEGH,False +570,14.0,23.0,26.0,22.0,21.0,32.0,13.0,35.0,DEACHFHFDHEHFCHFCEFBFHBECFECHDGEDFFDEFHFBCCACCHGDFCHFEHCAHCHHCEHEEHCHHCAHDDGFBHCBEAGGDBGFBEHBHFBADBFDAFGGGABHAGHABDFBFHCFDCFDHEHCEAAEGCBGDFCFFEFDBFBBFBCHBHDBEDHDDBAFFCFHAEHCEHCBHDBCDEGFH,False +571,12.0,18.0,32.0,29.0,10.0,22.0,15.0,20.0,DAHAAEGCCHHEBCEBHDDGDDFFCCCCCHCFHDDHDHADBEFBECBCDBCDFEDGHDHCECGACDAEGGDGDBFHCFDGDDGAEFDCFDAADAADHBCBBCGEDBBHCFHCABFDHFBFCBCCBCCHCFFDGCGGCHCBFDFFDFFCFHHBHGFCGD,False +572,19.0,12.0,16.0,19.0,24.0,11.0,17.0,21.0,AEAGEAEEBDEGDECBBDAHDAFECHEFHGFGGDEHDECGGCAEHEHHCBHDDHDEGCEGAHGFEGEEGEECFADFEDEGCCABAGBAHAHHAEHACACHAFHBCBBAEAFBHDDADDGDBFHGCHFCHCCGFDHDDBE,False +573,5.0,2.0,3.0,2.0,1.0,4.0,3.0,2.0,ACEFDDFABGAGGACFAHFCHB,True +574,17.0,18.0,22.0,17.0,4.0,9.0,12.0,14.0,CCBCGGAHDAEDBCFCCHCFACFAEDAHDAHGBGDFDDCACAAFBBDDBDBBFCBECADDACBFCBHCHHABCAHGBBGBADDACHAGHDGHDHBEHBGBGGCFDAGCCCFHC,False +575,13.0,19.0,23.0,32.0,16.0,20.0,25.0,19.0,GGDDGDDCHDBGDFDDHBBHGBHBFHCEAFEHFGFEGEGGDGDFCHFAEFBCFGHDGDEGDBHDAAGHDDADEBCEGCEFCEFEDBACHAHFDEFCGFGHBBBABDCBFCHDCFFCHDDGDDGECGEDAAHAADDAFDCGCHBCGBCEHDEGFFHBDCBDBGCCGCC,False +576,9.0,9.0,12.0,4.0,5.0,6.0,12.0,11.0,BHFCHFGHEGHBGEFHADCDCGGCFGCBDABAEBACGHEGFBGBAHCDHCGHAGEAHHCCFCBGABCA,False +577,6.0,7.0,11.0,9.0,9.0,12.0,13.0,8.0,EDDGBABEGCGACGECECCBCCHGEFDEFGGFGBCGDAGHGCHBFGBFDEFCFFAGFDHBDADFADFHHFHEEHC,False +578,0.0,1.0,2.0,1.0,0.0,2.0,4.0,0.0,GCGDCGFFGB,True +579,5.0,1.0,1.0,3.0,1.0,1.0,1.0,4.0,HGAHAACAAEHDFDDHB,True +580,23.0,6.0,7.0,14.0,17.0,10.0,20.0,6.0,EEAEEHDHGCBEABGFBGEACAADADGADHCGFGGEHGAGGDEAFEAGEDEAAAAAAEGCFGDFGDEGAEAFBAHBAGDFGDFECCECGDBAAGDEGHAFDDF,True +581,26.0,18.0,18.0,18.0,15.0,22.0,19.0,23.0,FFFAFECGECGHCGACGACAFFGHGEHADHFDHBDHCACGABGAFHHGAFGABDABAFBHEBAEAHFAGCAGCGFAEDGHFGAEBAEHDDHBDFAFBHDBFCHEHHGFDDBAEHAECAHGHECDFDDHHBFHBFCBADFFDCCDBCABGEBCEBDEGAC,False +582,21.0,17.0,16.0,25.0,18.0,9.0,13.0,8.0,GAHDCGBCBACDDBDGADCEDBFDAFDADEAEEBEHADFAHEGDBGFHGHCBAAHDEHEEACDACDECFEAHAGGAEGAEFADBGEBGCDDCFDABDCCAGBADBDFFDGDECDBCDCCEEBBEBBA,False +583,3.0,13.0,7.0,7.0,6.0,7.0,7.0,14.0,CGGBGGBGFBHBBHCAEBHEBHFFFDFADCDBFEBGCBCHHHDHHDBHEGDECBAHFDHBEHCH,False +584,19.0,16.0,23.0,16.0,22.0,21.0,12.0,29.0,CGHFFHFFHCFGDFDEECFDCDDABFAEAADFBEAECAEGAECHHCHAEHFECCHGCHGEGGEDHBABFAHEEBGEHHHBHHCDBCDBADCACABCBCCBHBGHDFHBFHCABGDCFCCADHAHHEHHEHFEABEGGAFDFEEFEAFCDDEHFBHCHF,False +585,5.0,14.0,11.0,11.0,4.0,5.0,12.0,10.0,DGDBCBFGBDAEHACCEHCDCCBHFBHFBHCAHGGGCGGBGCBEDBGBAGHFCHDCGDBHABEFBDDBDDHG,False +586,11.0,24.0,18.0,11.0,8.0,6.0,17.0,13.0,GBBGABCCDDEGDFGAHEAHCAEGBEGAEABEAHHCHBBHCBHCBGGGGGGBHCBCCBDDDCGGBEFFADFGBCABGBBDCBDBHABHBBHFBDFCHCBGDHACCCEC,False +587,14.0,18.0,17.0,13.0,15.0,17.0,25.0,21.0,ECCAFEAGBAGCGFCGHADHEBGCGGCBDCGABDHBEGBCGHHGFHGHHGHDGCACAEHBBBABGFHGFDGFDBDGBAHHGGBCEFCFHHFEHFEFFAFFAGFCHCHGABCHEFHCFEBDEBDACGAEGEEHBBDEDDGD,False +588,13.0,15.0,14.0,18.0,15.0,14.0,13.0,9.0,EFAHGBHGDHGDCADGDDEEEECFACDGDGHCCFCEDCBHFBGDBCDBCGFCGBCEDDEAFEAECAFCDFDDBHABHFEEBBHBACBADBGDEABFGFFADGAGFAEFEBH,False +589,12.0,8.0,10.0,3.0,6.0,15.0,8.0,10.0,FDAFCFFHFGHFGBFHAHAADACFCCBBCBBHADHACFAHBBCGGEBECHGAHEAEEAFFFCFFHGFCGAEG,False +590,17.0,15.0,7.0,14.0,11.0,14.0,9.0,6.0,HEAFCADCHBHAFEFFEDAAFBABCGDDFAAGDGDCBEBFEBDEBAEAEBAEBAFBGFBHFCGCHGHDGFAAFCADBDDBDDGFAGFABEDBE,False +591,10.0,3.0,10.0,5.0,10.0,14.0,7.0,11.0,CFGCFEAFHGFCGAHACGFEADCAECAEBEDGFDHFEHFEHBEHFECFAAFHAECDHGDBFHHFAHCCFG,False +592,19.0,16.0,12.0,22.0,13.0,29.0,15.0,13.0,GHBEBBFBGFCCFDDECDGGDFGAFABCHFAFFABBCHBAFGHFBEFDEFGEFGDDGDDACDBCEAFEACEDDFFAHEAEDDHHFFDFBGFHGDBFHECCCFBDEBAHFAEFAGFBGDHADAFDAFDAFHAFGAGCHDB,False +593,7.0,6.0,8.0,6.0,8.0,9.0,6.0,6.0,DCHBFDCFDGACEACBBCBGHAGHFEHFEHDEGAEAACGFBFCHFCAEDFEBEDGF,False +594,30.0,31.0,17.0,16.0,20.0,23.0,18.0,23.0,ECHGCHGBBGFBGABGCDGHFFBFABDADAFEAFEHGBAABEABHABHACFACBEFADDADFBCGHHABFEBEGBCGEHFEFEBGEHGDAFBHDAFBAHBAHFAFACGDCHDCHDGBEBHEFEAFEDHACEBCFBCHBFHBAACFCBAHGHDDEADHAECACGBBABAFBFEBGEHGD,False +595,9.0,14.0,16.0,12.0,7.0,14.0,15.0,6.0,FEGFGGFDBAGEFGEFCCHCBEFBCGACBACFCCBCAFCAGGFFCBHGBHDBADADHADGBDGBDEBCHFCFCCGBDGDHEDADDFEBGGCFB,False +596,26.0,34.0,20.0,24.0,21.0,26.0,22.0,25.0,FEEBEHGEHEFHEFEEACGABBDHDDHGCGFDACBGBHGFHDADCFGCGBDAHHCFHGFEEFEAHEBHGBAABDABFAHFHDDADDFDBGGBFHBAEBAEBAHBAFACFADADDAGGBBGBBCCACFFBDFHDFHDBCBCABAECDFGDGHHEECCAFDBDEFCEFGDBBHBBHGGHFBHEGGEBCABCFBCFCAHBA,False +597,16.0,18.0,17.0,23.0,22.0,17.0,16.0,28.0,EECBEAGEDFCFADAHFCHFCHECDBGDBHDCHAAHDDBDDCDHHFHBAHBEHDEHAFHAHHEEGEEGDEBDEDDHBEBGEHGEHCACFHBDBACHECEBCACCGCGGEHHDHBFGEABFDFFDGFAHCGHCFHBGHGDABDAFGBEGFDFBDEHFA,False +598,14.0,9.0,12.0,11.0,20.0,14.0,7.0,8.0,EEAFAGFHFFBEAGHBCFFFFDFFBAFCEGEEGDCGDCBAADAHFFHAGHACDECBEDBEAACDGCEACHDDADBECBECHEAHFDEEEEEEEBC,False +599,31.0,15.0,28.0,34.0,25.0,28.0,16.0,23.0,EADADBADCDDCGEGGEAFEFGBDDCFACDECFECFBCHAEHABGFCCAECDEDGCDGCDGEAHDBBDBACEAFBFEBEDBEBEEFGAAGADGDFFCEFAFAABDFHDFHDGCDGHDFCDFHEFAEGCFDAFDAFDEFHBCDAFEECHHDDHDCFFAHHHHCHADEADADBADBCGCCHFAFCEHHAFHAHHAEGACCCH,False +600,10.0,11.0,5.0,10.0,8.0,10.0,7.0,10.0,HBFHBHGFGEFGEFAAFAGFGEBBHBDGBHHAHCDHEHBEAFDDBBABDFDCFHEBCECCADGADFADAED,False +601,1.0,4.0,4.0,5.0,1.0,4.0,5.0,0.0,EGCDDCBDCFDFBGBDGCAGFBGF,True +602,4.0,2.0,2.0,6.0,6.0,0.0,2.0,3.0,EDEEBAEDHEAGEABCHDCDDADGH,True +603,22.0,28.0,15.0,26.0,22.0,27.0,16.0,24.0,EADBBCFGEFEAGAFEACAHCDBABGHBHAEDGGDCGFBBFHFCEFCEFEDAEGEHGABFHBFDBGDBABGGCGBCGBABHAFDDFBDFBGFHFCHFCHFHECHDFFDFABFDBHDFDCFDCABHABHEHADCDDCDHFEEDAEDFEBHHAFHGBHBBEEBDHDHEDABDABAEGEEHAF,False +604,21.0,11.0,14.0,19.0,11.0,12.0,18.0,29.0,GHHGHHAHADHAHCGBCGBDGBDHDFAABAEHFCDDAACAFHBHHDEBEGAGGEBGEHDEGFGGCHGDBDHHDAAAACFACFHBHEAAEHADHGCHGHDBCFHEFHEFECDDHFDCGDFGAFHAHHCHBCGDCAD,False +605,9.0,11.0,6.0,10.0,8.0,6.0,9.0,4.0,DCGDAGDABEBBEBGEBGDDGHAHHBCCECAHAFFAEDCEFFEDCBGBBGEGDFGDBAAFDAB,False +606,28.0,22.0,23.0,19.0,24.0,23.0,22.0,23.0,GHDEEDGFDEHCEBCEBAGAAGEGGEGABFHGFAGAHGDCCDHFBADBDDBCDBFHFDGEEGCEHFFHCCHAGHABEACCACDFEEFAFGEFBCGBCBFAFFBFFDGEEGBEHBHHDCACFHCACAABAABAECCDFHHFHBDAEFHEFEECGFBGCDGEHCBGDBAAAHCAHDEHDBHABAAG,False +607,13.0,16.0,14.0,14.0,17.0,12.0,10.0,10.0,BGHBGADGDDGCECBEDBECAECGECGECFACFBEEBEADEDHFAHAAHBFEBHDCFDGDBFFBEGCAFADDHCABDACDABDHGFFGEEBFEBABCEFEHCHHCB,False +608,9.0,17.0,16.0,8.0,12.0,15.0,18.0,16.0,BGGGDCHHBHGBEACEACEGCEHFHCBGBBGFBGFAHCDGCFFCFGCBGBBGBFGBFAHFBGFBABCEGCEADHHEHHCHFEGEDHDDCDABGHECCFCFFGBADEAEHFH,False +609,34.0,28.0,25.0,20.0,27.0,20.0,18.0,15.0,FHGFEGEBBEGBEGHFHDFDAAEAAEDCFDBFEFCDCDDGEAFEADBCCACCDFHHBCHFEDABBABBABHAFGACGEEEACCACDDCBFCDHBFGBAGCGFADEADGABFABAGEEEBHBFDBFEBGEBEBHCCDCAGCAECAECAFCHGEEBFEAGEDECAHHABABBABDFDAHCABCAGHAGA,False +610,27.0,20.0,29.0,19.0,16.0,20.0,23.0,16.0,EDGGDCDCCDCCFAHFACFEEAAGGAHFADGADAEDCEACDAGDAHDCHFAFFHCGHCGDEBAEBAFHADHCBFBBDAECAECACGGGGFFCDGBHGECFBABDABGECGEFBFCBHDBHAHGACBAHEACCACHBHEFCBDCGDBGCBGHGCBFCADEFBFFGABGCEF,False +611,22.0,21.0,24.0,24.0,11.0,17.0,21.0,18.0,CGCHDBGDBABGACGAEAACCDDCDGCDGFDEHBABFCHACHAFGDEBDEBDABHGBCFBCBAHBDFBHFCFECFECGAGEAEBDGCGGCHGDFGDFCFBHFAFGAGHHFBHDAADCAHCAGEABCCBDDEDDHCCAAHFHHDADDBGHCGBFFBEDG,False +612,15.0,15.0,16.0,7.0,8.0,15.0,11.0,10.0,BBGABCABCFCHFCBCAGHHFHFFBFAAFAGBAGDEFFCFECACDACAFCABEEGCEGCAGDBCHBDDFDDFAFHACBGBHGBHCEEEGHCGFBHBA,False +613,1.0,6.0,10.0,13.0,4.0,6.0,8.0,9.0,GCDDCDCAHCHEDFDCCDGGDBHDCHDBHCGGFGCFGHFGFFHHCBBEEBDEDDBDH,True +614,10.0,16.0,11.0,12.0,14.0,10.0,10.0,10.0,DECEGBDAEDAEGGGHGAAEBAEHDGHGEBCHBCHBFEBCBFCBAHEDFEDFGAFDCFBCFBDFBCHCCHDHBDBBABFDGEEEDCEGAHBAF,False +615,1.0,1.0,2.0,4.0,6.0,3.0,0.0,3.0,HDEHFEDCEABEHFEDDECF,True +616,10.0,6.0,9.0,12.0,6.0,14.0,6.0,4.0,DFHDFBBECCFCCFBCDGAFFABDAGEADBDDACECFECGAAGHFHFFHFFDGDAFDEFDEBDAAGC,True +617,6.0,1.0,4.0,3.0,5.0,2.0,0.0,4.0,BDEHDAAFACHECHECDEFHCAAEA,True +618,22.0,16.0,36.0,14.0,21.0,16.0,20.0,16.0,BBGEBEHHHHHACECCGBEDBCDHHAHDCHDCECAFHAFDAFCAECGCCACCGFFDEGACGCCGCEGCGGEGACGACBDGGDEAEBAEGFECAECFBGECAEFFHBCCBCHEFADFDECDBCBFDHDECDGAABHCFGCAGCFGABEABCABCECCFFAHH,False +619,26.0,17.0,24.0,18.0,27.0,15.0,23.0,23.0,ADFABEBGDCGDEAEHBHDBCGECBECEEGAHGCCECGFCAFCHECFACBAHBACBAEBDEHFEDDEHGHHGHHGAHGAHFADAAGEAEDAFAADADHEGHEGHGBHDBCEECGFCHEBHBBFAHDCGAEGEEGECGHCFCFGCDDFDCBCFEAAAFEAHGBGDCDBEFCHAG,False +620,7.0,2.0,1.0,9.0,6.0,2.0,5.0,5.0,GBEGBDDHGCFGDGHEEHDEFAADAAHAAEAHEDDDD,True +621,16.0,26.0,22.0,21.0,29.0,29.0,17.0,19.0,EAFBDDEEGGEGGEGDFBBFADADCGDCBCCHCDDEDFEDFADFEDFGBFHBECAHCDBCGFCFECEEHAFHAFCGFBEHGFHEEHFEBCGBGGHABFGDAGCABFDBFDFFDEFBBBDHBEECFEHEACBFBDFHAHHEHHEHCCHGBAEBDCCEEFBBFAFCBDCBFBAFEACEGHE,False +622,7.0,7.0,8.0,11.0,8.0,4.0,10.0,8.0,DAGDCGDHGDACDBCFHHEGDEDEFHCBHEBHFDHEHBCGGEGBCGDCFDGEDCAABAABEAG,False +623,28.0,16.0,21.0,17.0,19.0,16.0,21.0,15.0,DEHGEHCAACGFGGBEFBEGGGBGFADAEDADDCCHGGACAACEBDGFCBDAAFBCCCCCAEEEECHDCEDAEFAHFABFACFGHHBEGCEFBAHCDHDBCEBCEAHAAHAABEDGECGFAGFABFAHFAHEAHDHBFCBDDAFDAGBGGDGG,False +624,3.0,1.0,2.0,2.0,0.0,4.0,3.0,0.0,GAAFDAFGGFCDFCB,True +625,2.0,3.0,2.0,8.0,3.0,1.0,2.0,1.0,DHDDBDABEGDDGBFAEDCEDC,True +626,25.0,22.0,16.0,18.0,24.0,24.0,24.0,13.0,EBGFHAFDBGEBGEFGEDHADHADAAFCAFCHGEAGACBDGBFBDFEDGEHGEHGDHGCFCEFBEACEBHGFHEBHEGFEBAECFBABCACCABAEDEDGEGCABEEDGEAGAAGCFFDBCGHAGCAFFGFDAFHFFGEBBBHBDAGDABDBDGBAFEDFCAFCEF,False +627,29.0,21.0,28.0,24.0,31.0,21.0,20.0,20.0,FAHFBGFACEAEHGHHCFHGAGFFCCDDBDGBDGBDBHEBHECCEHCAFEGEHGEHGEGGBCABADDACDEEBCHCGAAEAFCABCEBDABEABCAECAEAHHFCFGDFHDFHBCECEDCDFCDACEFBEDBFDBEBEHHECCEDAFDGFDHEEHEGHCDDADAAEGAFADCGCGFEGFEABACFAEBACBGDA,False +628,12.0,14.0,20.0,9.0,14.0,5.0,7.0,10.0,BAHEECEFDEACFADDABAECEHFDHCCCACBAEDHEBHEBHFHCFCCGCDACAADGEGCCGCGBCBBCGBCEBEHBEDCADBEGBCABHH,False +629,5.0,5.0,7.0,3.0,4.0,2.0,2.0,2.0,EFAECAECHGHFCDABDBCDBCBCABCGEA,True +630,23.0,22.0,17.0,29.0,22.0,31.0,12.0,12.0,CCDECDBBHBBHBGFACDAEHBFBGFCCEHGEHEECEFDDFDDBEDBAFEHBDHBFFFFFFFAFFAFHDFAEFACFCCGAFAAFGADGADFFEBHEGEAAFBDGBDADDAGEACECCFBBEEGGEBDBBCAADFEDCADFFDFAEFBHDDDDBCCBFGDAEHEHDDAD,False +631,27.0,22.0,17.0,34.0,24.0,29.0,22.0,24.0,FFDCFDCHHBFADFAGECGECGBFBAFBGGACBFCBACHEFEEFBEFEEFCBAEECEHAEGAEFACFADFDBFBHHDHAFHADDGHHEHDDGEBEEGFFDDGEDGADGBDHFDHFBHFHAABAADHAEHBHGDFGEAADDFDCCDCDDFBAGCFDCGDHBDHEAFDGBEGBADEFGCDBADGADHEHGFHBDHADGACB,False +632,14.0,22.0,9.0,14.0,13.0,13.0,20.0,23.0,BCFBCFAHGDHGAHEDGEBBCBHEGHDDDBAGBAGCECBBGBDABAGHDGHEFFBHEEEEHDEBDEFAAFAHGDGCDAFHAHGADGAGCDDHHFHGFHEBHBGHBFBBFGBFHHFAHCHHBECBGBGG,False +633,24.0,22.0,20.0,25.0,23.0,16.0,19.0,23.0,DBBDHHDHHEFEEFGABGFEGADFACHGEHGEHAFFAHECCEACEBBHBEFADDDDGGHGGHAABCFDCFBGFAECDGBDABEAFECFEHBAHFDBFDBDEFCBCCGDEACAAGBBGBDEAEAAGAAHBGHACCAECGCCDCGDEHAHGBDDEDDHDBHDHHFCHDBHEBCE,False +634,17.0,21.0,22.0,24.0,23.0,23.0,16.0,18.0,CBHDBHCEHCHBGDBECHEHFBCFDFBDFCGFCACCACCGDEAFGADEADFCDFBAHAGHGEBDDBDEBDHBGBDAEDBEDCEFCEFHBHCGDAHAAEDEEGGECBEHDGDBGEHFEFGEFBFFAFFCCFECEDHEGCAGBACFDGFDHFBABHADFBEFHADC,False +635,16.0,6.0,8.0,5.0,5.0,8.0,8.0,4.0,FFABFACAAFAAHAFHCEACEABFCDGCFACABGGDGCABAEBGEAGBAGHACHFEDDDG,False +636,0.0,0.0,0.0,2.0,3.0,1.0,3.0,2.0,EHGEHDEDGFG,True +637,9.0,16.0,10.0,10.0,13.0,11.0,8.0,12.0,FEDBEDBEBBEFBEHBFBFCBEGBAGBHGHDBDDEGBECEFHDDHCFHGBHEBCGBEFAACBDEFCGFAAHAHHFFAADAHDCHGCECC,False +638,12.0,9.0,9.0,12.0,9.0,15.0,8.0,15.0,EFGFDCDAGDHFCBFEAFHACHBGADEEHEFGEDHFDGDDGAECCFHBFHBCACHACHACFAFBGDBGDBHBHHBHDEHDAAAEFFFHF,False +639,14.0,20.0,11.0,14.0,9.0,16.0,14.0,14.0,BFBHEBAEDADCGDAGDAFBHCBACBAEAHHCGBCGFCGAABFCBFGADBFFFDFCDFEAGGDHDDEFFHGHHGHHEFEBHBBGDBCHBEHBEFBCABDGGDCGAFHBFABD,False +640,8.0,6.0,17.0,2.0,13.0,12.0,17.0,7.0,HCFFGFCHCCACAADFGBFCFFCGFCABGBEABGCEGCEGCACCFGDGECGHCAEGBEGEEGHBGEAFEHFEHGHGEECCGF,True +641,14.0,17.0,15.0,14.0,30.0,13.0,21.0,15.0,BBGEDAHDBBEHBCBEHAEGAFGECGACGADAFGFFGFEGDBCCBFCHDHABHEBGEDADDHEGHBBHEGCGCHEEHEEHGEHACACCEGCGGEDGFGAFDBFCAFBAFEEEHGEGFEBEEBHEFDECEEDEBGEDCAD,False +642,26.0,25.0,28.0,26.0,13.0,16.0,19.0,13.0,EBDECDGCAACBAHFACDCCBCDDHDFBDBDAHGAHGBHGBCFDEADGADGHFGBAHBCCDHBDFDFHAEEFDCGGCFCAFGACGCCFADBAEBGBGGBFGDFBFCAACAACECBBHBBGABGFCAHCDFGDCCEBCDACHBCAAEDEEDFEHEDABDACDAGDBB,False +643,14.0,19.0,17.0,9.0,14.0,22.0,18.0,8.0,GCCFBFFBEABEHDEBDGBDFAHFBHCBDEBDGBDHHFFGAFGCGHCACFBGGAGGFEGFCAFCADGGCFECECGFAGFAGACHAFHDCBBCBFABFEBCCBGFEAECDBBFFBAEEEEFG,False +644,15.0,27.0,16.0,22.0,21.0,27.0,27.0,18.0,EDFEFFDFBDGBEGBHCFHCFHFAHFGFFEHGEBGEBGABGCGEBGFFHADEDGEBFABGAEFEGFGGAGFDHFBHCBADAEFBCFCCHDFBEADEDBBBGDBDCACCFCEFDDFBHHAGHGGBGBEGCFCBFEGDAGDEHCEHEBHEBADHDHHDGCDGBAFBDCGAFGDBB,False +645,14.0,11.0,10.0,13.0,16.0,12.0,10.0,15.0,EEHEEHGEFGEDEDBGCBHHFHBFDBEEBEBAHBDGACGADGHEHHECDFHDFDFAEFACFBEBHEHAGDCHDCDGCFAAFAAGCDGCAAAHHFBCDBAFE,False +646,3.0,5.0,2.0,4.0,7.0,6.0,2.0,5.0,EEDEFDFHDFHGFHCBHFBEEEABHABFDBGCEA,True +647,17.0,19.0,20.0,19.0,12.0,18.0,17.0,19.0,HCFBAFBDFDHBCACEAFHCGGCAHBHHBHFECADGBGCDACAECGDCFDFEHBABGADGACGBEFHGFBDBCCBCFBDFADFGGFEGFHGFEBDDBDDADBFGCFGHECHCHHGGBECECCEBDEDHADHADHAFHAHAB,False +648,10.0,10.0,6.0,7.0,5.0,10.0,7.0,10.0,CHGDHGHAECAEAGBCGCEDFBGFCGBCFBHAEAFHDFBEHBGFAFFDDABDABDFBHFHHABHA,False +649,23.0,19.0,18.0,23.0,11.0,22.0,22.0,16.0,DFGDAGAEGAEDABBFDGADBHHAEGECAFDAEDACGBCGDCGHCGBCHEGACCAFDBFHBGGGDBGBFCBEGFHAHHCEDAEDBBAFAFFAFGAHCHCCDCCGBDEFHFFDBFBCFDCDDAAAGDEBDBBHBFHGFHFFHFAHGDGGDACDAF,False +650,4.0,5.0,4.0,4.0,6.0,3.0,2.0,5.0,DDHGDFGEFAECAFCDBCHEEAEEHHBACBHBB,False +651,29.0,15.0,14.0,25.0,15.0,16.0,23.0,19.0,GAFBABHAGGACGAGGAGHABDGFCGDEGEFDFACFBDAHAAHCGECDHFEHCDDEDDECGFDDFEDADAFDBFDBEGHFBAGBADBCDGAFFCEDEHAAHAACGAGDFDDFDAADCAFHBEHGEHGCGEBBHHBCDBCDHEBAEGGHGHHAAHAA,False +652,17.0,19.0,21.0,19.0,20.0,33.0,24.0,19.0,EBHGBHEFHAFCFFEAFEADEBHCBFCEFDEFHBGHGFDGDAHEGFEABBBBFBBFBBFAFEBDHBCBCGFEHACDCFDBGHGEFGACCFFFFDADGFDCFGEGHHGEHFFHEFHCFAGFBGCCGDCDDCGECGHAHEAGEDBCDEHDGHFGFCCDAAFAAFGAFDCGECGD,False +653,4.0,2.0,1.0,5.0,5.0,3.0,4.0,8.0,GBFEDEDGEDEADHGHHGHHDBHAHEFHCFAA,True +654,20.0,23.0,22.0,29.0,18.0,18.0,13.0,18.0,EDEBAEGHHFAHFBDDBGFBGDDABDABDADCCBBCEHGFCGFCDEHDFDGHDCBDHFDCBHBFHECCADGHGGEGBCBACHAEGEEFDEHDCHBEHFDBFCEACFAEDAFBGDBDDBDDBFDCFDCHDAACAABACGFCACDHHAFBAFBHEDCEBEEAC,False +655,7.0,8.0,11.0,11.0,11.0,5.0,11.0,11.0,CHBCHDCHBAHBCGDEGDACDEBAAAFBEFHFBGFEDEEAEEGDGGDGHDAHDHBEEGDECCBHCGCCGHCFHDG,False +656,23.0,22.0,23.0,10.0,19.0,19.0,24.0,14.0,FCGFCGAAEBHECHECHCGABAAFFEHBAHBCBBDEBEFDFADFGDFACFAFAHFBCEACECCDGBFEBFCCCCEGAAHAGEBGABCFBAAGFDFCEABEABECDGCGAHGHCCHBAFBHEEHCGBFGBAHBGGEGGEDBEDBDFGGGGGGACH,False +657,17.0,18.0,13.0,17.0,9.0,17.0,17.0,24.0,BDHBDGBFEBCHBDFBDHBAHBHHAAGABHACFFHHBBDDHHDHGFCFFCGHHBAHADGFDCFHCHCCBDFFGAFGAEEAGEHHBGFFGFAGHADHDCBDEFDECGAGADCAGCHGEHBEHFDABDGBCGAE,False +658,8.0,8.0,5.0,2.0,2.0,4.0,5.0,8.0,CEGBBGBHCFHBHBBABGEBHHGCFAAHADHAHGACFACFAD,True +659,34.0,21.0,21.0,17.0,21.0,20.0,30.0,25.0,HAFHDCDEGEEGAAGBGCBEAGEBGEAHCAHEAHCAHAAHFBHECECABCAHGGFGHHGEHDADFACFACFCGFCGFBBFAAHAAHBFFDAFDGFCAEAGFAEDBGBCEEFFFDEAGGADGCDFHGGHBCABCABCABHDGDGGEGGEGHEAHBDGBHHBCHDFAECGDBHAGHADABBACEFHBDEGC,False +660,14.0,30.0,12.0,19.0,8.0,11.0,20.0,13.0,DEBHHDCGGHGCHBFBFGBFDDFDDGDGBDBBABHDBHACECCACEABBAEBDBBGGGCGDAHCADCABHEFHBFDCDCGGFBGDBDBBGGBCGBEBBEBBHHBHFFHFAADGBBGBGADDFEAAGA,False +661,11.0,26.0,15.0,26.0,16.0,14.0,18.0,26.0,FEBHBBCBDCEDFABGAGEABBHBGCDGFDEBBEBBDBEGBEDDHHDHFBHEBEEGAHHDHHCBHCAHDHCAACEGBEGBDGBHBHDFHDHDFHECHCHEAHBGCFCFHDDHDDFDDAGEGGCCGDFGFAGFGDBBBHBDHFDACDCHFGDE,False +662,5.0,2.0,4.0,1.0,4.0,3.0,0.0,4.0,HCDFCFHCACAEEAEFBHABHAE,True +663,14.0,22.0,18.0,13.0,14.0,22.0,18.0,29.0,DHBHHBGHGDDFFFCBHCBFCHGCGGHHHHABCCBAFAEGBBDBFCFECFADFHBCHADBADGHDGCDACFHBFGFFBFGCFAAEACHAFHEEEEHGEHAEBGBGGBFCBFBGGBGAHDHHBECEHCHBFECFHAFHDCHDEHDEHGFHB,False +664,22.0,13.0,19.0,20.0,21.0,19.0,24.0,26.0,AACFEGGECAHDGHDGDBEHBGDGGCBEAGEFEAGBGGBFFBGGGGDCEEAAFFAHEBFEFACFECEABEFHGFHDAHCBHCFGDFHDAHGEHEAHEAGCCCHDAHFCEFCDCAFCGCHFCHGCHGCBGFBGHHDAHEAHDHHDHEEADEFDHADADDHDBADB,False +665,19.0,16.0,20.0,18.0,23.0,17.0,22.0,24.0,DAACFCEFCEHBFHAEHDBHBHABHABHAHCCGGCGCEDBDHBACCCCCAEDHEACEHEDGECGEFGCGDEFHCAHADFDEEDBECEACDGEDGFHFAEFAGBHHAHHDHAGBBFCGFEGHBHFDEFDHFHHABGABGEDGEDGEGGBCEBGDFGFFGA,False +666,21.0,15.0,10.0,14.0,9.0,13.0,18.0,9.0,ACFGBACCACCADCDGADGADGHBABGDFEDEGAGFADADDBEABDABEABAFBAFBGFGGACGBFEBFEHFHGACGCFEDGBGABCEHFGBAGFEDADBAFHHGHHDH,False +667,8.0,7.0,10.0,12.0,11.0,15.0,18.0,9.0,FAGEGGDGEAGDFCFFHBFDBGDFGBAGHCGFCDBCGBDFHGFHEACECCECAEFGCFGHFEDGHGBHFCHAEDAEDGDFGFGEBEDHAD,False +668,10.0,9.0,8.0,13.0,5.0,7.0,10.0,7.0,GFDGECCECCFHAGBGDBDFADGEDAADAADAADCGBGHBHBDHFGHFAHFACDEHBEBDDCGGCDFBB,False +669,7.0,12.0,7.0,12.0,9.0,2.0,15.0,14.0,HBGHAGHEGBCADABEEHFCCGHGGEGGCDGCHGEDGDBADBHDBGEAGAACEDDFBHBBHBDHBDHGCHGHDEEBHD,True +670,0.0,5.0,2.0,3.0,7.0,4.0,3.0,4.0,FGCFHFEDBHBBHFBGEBEEDEEGEHCD,True +671,5.0,12.0,12.0,3.0,8.0,4.0,5.0,4.0,BBCBBAECHCGHCHFCFCCBDBECBEBFEBCGHCEFGGBAGEAEEACCBDABD,True +672,11.0,18.0,12.0,10.0,18.0,18.0,25.0,17.0,AGBBGFGCFCEFCBHCADEBHCHDEBGGGGGAGGCGFHFBHDBFFAFHAEHFEFFAGBEDHHHHBBCFHAFCGCCBEHBEHGDBFEAGEHGEAGEAGEGDBGDCGDGGDFHEFEBBCBAGBEDHEFGEF,False +673,9.0,13.0,14.0,18.0,14.0,11.0,8.0,15.0,CGDBHCCHGBFGAFEEHEHCEHCACCADCDDCGBCDBHDHCBHEHABHEEGDFHDGACBAGDFEDFEDECDBDHFEHBEFFEBCEBDABAAGFHFDDFDDHB,False +674,8.0,13.0,7.0,9.0,11.0,13.0,8.0,11.0,GHHFHFCGFBEFDEDDBFDBAHFHHFCHEDGEHGCBDBHHAEGAEAAEBAGBAEFCFGCFAHBGEFECBCBBDBBDEFDF,False +675,1.0,9.0,5.0,1.0,4.0,4.0,4.0,4.0,BECBCFDGHHBEBBFBBFBCFBHGAHGCEECG,True +676,7.0,7.0,1.0,4.0,6.0,8.0,6.0,3.0,ECHEDFEAHHDFABGEBEABEDGFAGBAFBAFGFGGFABFDB,False +677,14.0,18.0,19.0,11.0,14.0,16.0,16.0,25.0,EEHFECBGCECHDBHGHHGHHGABBDFBDFBAFHAGDABCABFHHABGAEGDBHHGHFFHDFEDFHFGACBCCGCAAFFAHACDGCDBCHBFGBHEFHAFCCEBBDHCHFAHEGHEGCEHCECCHGEGBECBD,False +678,9.0,12.0,6.0,10.0,11.0,11.0,13.0,11.0,CDEAGGDGGCGBCGBAGBGEBDCAFGHFGBFEHEEACFAGFDEFGBHHFHHEHFCGDADHHDHEDAADFBFBBFBEEHEABBD,False +679,27.0,20.0,25.0,20.0,31.0,18.0,23.0,23.0,EFHEDHDDBECBDAFEEFEEAADGGCGEBGADEECEEFEECAFCGEGGBFCBFABGACDAEHBHCFGCHGCHGCFDCBHHBEABAHBABAHEAHGADGCCFECDHDFAGECHAFBADBGDBCABHADDBHCEHCEHBFHGFEEDCDHCEECGCDBCAHGHBGEAGEAFFAFGAEEAFAHGEHGDACD,False +680,27.0,26.0,27.0,28.0,20.0,19.0,14.0,25.0,GDCFDCFHCBAEGAFACFAGFDBEABDBCAHCGFFFCFBBBADBGFCDACDGDDHCEHAEHBFGBHECDEGAACBHCHEAHEFCGACDBHDACGACHAHHAHDEHFCBBABBABCHBFDCGBCHBCHFDHEEBDEHEEHGEFABHAHCAEDBCDBCDEEDCBDBHAFAGEADDADFADFDDHGDEC,False +681,3.0,1.0,1.0,3.0,4.0,8.0,7.0,1.0,HGFEDDABGFGGFGFFGCGAFDAFEEFE,True +682,15.0,12.0,11.0,14.0,15.0,27.0,23.0,14.0,FHFFHFCHGEDCEDGABGDBGFFGFHGDDFFDGCHECAEGEBCEFCEAAAAGACFAGGGBEGBFBAFBAGGAEHAEHBDGGDFDAHGGEGGHAFHGCEFDBFEHDDBGFBCFAFFEHFCHFHDFCFFDEFB,False +683,3.0,2.0,5.0,6.0,4.0,4.0,5.0,2.0,GGFDFADFADECDCGBCGEDHEDHGCBCAEF,False +684,13.0,18.0,21.0,19.0,20.0,13.0,21.0,11.0,FEEGGCAGBEGFECBEGBDHBDCCGACGFBFEHHEHBCHCCFDCDDCEACEAFHHFCFDEBBGBDCBDBADEDEGCFDHABEDGEGFDCFECDEAHEDGEAGFAEAAGHADABDBGCGGBGFBDCBDGBCGECGHC,False +685,10.0,7.0,12.0,11.0,9.0,18.0,8.0,9.0,HDHAGFAFFAFFAEBDCBDBEAFEACEACDGDDGFCHFCBCCACHGCFFCGDEFDFHEFHDCBEHGEGFFDFAAFBEFCDGHBH,False +686,6.0,12.0,8.0,11.0,9.0,7.0,20.0,10.0,BCEBCDBHAGDAGDHGDEDAGDGHBEHDDFGDGEDAEGGGCEBCBGGGCHECBFHHGGFGGFGGHGAHFBBCBECBHABFDEF,False +687,12.0,20.0,16.0,25.0,15.0,20.0,20.0,33.0,DFDHAGHAEHBHBFCFFDHFDBGGCCBDABHGGHBBCBFCHCEEADDACDFCAFBHBHDBHFBADGHDGHDGFEEBHHGGHGHFGDFCDHEEHCECCHDBDAGDABDCBFHAGEAHEHHEHFDHFDHFDEFDCCGBCHEDHBDGEHGBBGFDHAHHFEFGG,False +688,3.0,9.0,2.0,3.0,7.0,7.0,3.0,4.0,CFEHFBFBBEDBCHAFABFEBEEBDEHFEDFHBGGBGA,True +689,15.0,26.0,20.0,34.0,29.0,23.0,27.0,17.0,GAAGDABHABEGDEBDFFDHFEHFBFCBGCBCCDGFDEHDCFDBHEBEFBEBCGCDGADBDGGGAAFCEDCEDBHGBDDBEDFFGFEHBEFFCAHCHHGFDDBCDBDFEHFGAFHFFDBEABEFBGFAGHGGEECCGABDDBEEBECBEAGCHGDHGDEDHFDHDAECAECDEDGEDEBCEDDGGDEGBCG,False +690,2.0,5.0,5.0,7.0,3.0,8.0,3.0,2.0,GFGFFGFDHHAEBCCBCDFCDEADFDBFDCEDBBF,True +691,11.0,14.0,14.0,3.0,13.0,5.0,13.0,10.0,ABGFGEEGEEGEHAHBCHBDDGHBBABACBCEEGECGECGHCABCABCHBEGAEFCCGBFGCAEFGECBFHACHACHDHBGBA,False +692,17.0,27.0,23.0,13.0,20.0,16.0,15.0,12.0,BCCBCGFCGFADAABEDHEHBEADCFFEFFCABCGBABBEGBADBABBFCACGEDBEBBGFBGHBGHDEHBEHBCHACHFGEECHGFHGCCGECGDBBDGAEADFCGECDEFEFCCFAHFEHEABAFCCECEBDDBADBABBC,False +693,27.0,22.0,19.0,22.0,14.0,28.0,28.0,25.0,FCDFEDBEDFECFBHAAHEACBFDEGDCGFFHHFADGABFAFAAGGBHFECAECAGCGBDGBDHBHCBHFEHBBAFAAFAFFCHFGGFHAADCCGCCGBHGDDGFDGBDGBABHAGFDBFGBHAEFFDGFDGCAACAGGHDGAGCDEHDHBGHEFCEFADHEHABHAFHEHHDBGGBFCBGCHAD,False +694,18.0,13.0,19.0,10.0,11.0,15.0,13.0,6.0,GDGHAABAGDGHFBFGBCGACGAEAFDAFDECHECACBFCBACBEBDGBFACEEBEDCEACEBBDDBGFAFFDCFECDHCACCGBFGHGCEGCAAHAAFCAFCFF,False +695,10.0,11.0,11.0,10.0,20.0,12.0,15.0,5.0,DBDBFDEGDBGEEGEGFAAEGDFCFECEEAEEBHGGHCGHCFACGHEGEEGAEFCEFBAFBAEEACCGFDBFCHACEDFADFGBGCBDEBEGBD,False +696,11.0,15.0,9.0,15.0,19.0,14.0,16.0,14.0,BBEABEBFEDFHBEDCFCEDEFDECCEFGFGBHGBCGHGFHEBDGBFGCFGDGDACDAFBFHBHGECGEHDEHBBFDEEDGEFCAAHEABEHHEAHEAHDAHDGGDBGFAGAD,False +697,4.0,10.0,3.0,4.0,4.0,9.0,13.0,9.0,EFFBHHHHHCADDEGDFGBBGHFGBBBBHBACEHCFBEGDGGFGGFGAFGAGHFGB,True +698,8.0,6.0,6.0,10.0,3.0,3.0,10.0,9.0,CHGBHGEHGAAGHDGDAGDBDHADHBDHDAFACBCFBGEHCEFCGABGAGDCDDH,True +699,23.0,20.0,26.0,25.0,24.0,29.0,20.0,24.0,CDBFFGEGEACCACDGBDCHACHACHBGDBCFBHFHHFHHAGHAGHCHAEEGCEHEEFFCDFDDFDFAAEEFEEFBEDAEDFGDFGDHHDBCBBCEBEABADDAEDGGGCEHAGBEFBCFDHFBEFADFDCEHFEHFHADCFDAFHAFBFCEDDBCAHAACGCBFCDHBFHDAGFEGFGGCCGCBBCAHGE,False +700,29.0,20.0,21.0,24.0,24.0,23.0,13.0,26.0,EBHEBHBADGAHAAEEACGAFAAFBBFCHDBHAGCDEBDCDDAHHBCEAAFHAFCABDDEDEEDFHDFCDFBEGCFGEFAFGCHGDHFFEFHEDDEADBACACEFCBHCEHCAAEAECAEBFDAFHAHGAHGBGCBDHBDABDHBDHADFGEBABHFCFFAHFDECHHCHHCFCGDEGEE,False +701,3.0,7.0,7.0,3.0,6.0,6.0,4.0,11.0,CEFCFHGFHBHEAHECHEBBAHAEECHCDHCFFCHBGFBDDBGHBGH,False +702,9.0,6.0,16.0,15.0,12.0,8.0,10.0,9.0,FDCFDCDAHDGHFAACBCHDEHEGDEDDFDDEGCGCDBCDEAFCBCCBCGACGACHHEEHADDAEDCECFECFAGGBBEHFGHEG,False +703,6.0,1.0,3.0,5.0,2.0,9.0,6.0,6.0,DABEAHCFGGFAGFHHFCFFHDFHDCGFFGDEGDHAAA,True +704,4.0,1.0,0.0,2.0,2.0,1.0,3.0,0.0,BGGAAGEADEFDA,True +705,18.0,19.0,12.0,21.0,25.0,19.0,18.0,24.0,FDAHBFHDCHACHAEAEEBDDDDDGFHHFEHDDBDAAAFHAGGAGDABCHGCEGCFDBGCBEFHFDHFHHEGCFABHEBHCAHBBHEAEEAEGAEDEBGFCDHEEHGEFGEFBDFEGFGHFDHFBHDBGDACBAFBDFEHEECBEGBDGAEGEHBC,False +706,17.0,12.0,10.0,18.0,25.0,13.0,22.0,21.0,AGEHCDCDAEDAEBAGGHGGHDCHEHEFCEABEGBEBHAGABHABFFGGFGAFGDBGAEDAGFAHEEBFFAEFBEHCEFDEFEHDCHDCHDGAEGAHHFHEBEEGABGDHGDHBDHDHGCEDCHFCEEDDEHDGAGGE,False +707,18.0,24.0,22.0,26.0,29.0,18.0,27.0,19.0,HFHHGDEGFHCDHCEGFEGBDCEDEEFFBFCAEBBGABHADAAGABFDCGCBHABAGHDEDEEHBAHDAGDBGCBDHHDBEEGCFGCHCFHBFDEGDHDFHAEDAGDFGEFCEGGEBGCCCCECGECGCHACEGCEFCDFBDFBGBEABECBEBBGAHGDHDDAABGGBEGAEBEDFDDFEDE,False +708,20.0,10.0,10.0,16.0,13.0,13.0,19.0,23.0,FFHDFHCCACGGGHEEHDGGAGEAGHAEBAHDGHGGHBGAGFCBDCDDADDCEHADDDHBAHBAHBGGAFAAGAGGBGFHAHHDHGEHEFHCFHCBACEDBDDFCEFAHFAHEAEFHFABEDHE,False +709,5.0,8.0,2.0,9.0,7.0,8.0,16.0,8.0,CGDAGDFHDGABHDEFFBFFBEDGGAGGCEGHHGADEFDEDHEDGFBGHGGHGGBGBBAHEFB,False +710,2.0,0.0,1.0,2.0,0.0,3.0,1.0,3.0,FGHDDHAFHAFC,True +711,11.0,11.0,7.0,14.0,11.0,15.0,19.0,23.0,DHDDADGHBGFBGHHGDGAHHHGHHGBCEDCHDHDECGGFDDAGBHGBGDAHBFFBFFCHFCFFHBFHEHHGAFGAHGHDCDDAGEHGEHBFHEGBAGFAEFCEABEAEEF,False +712,22.0,16.0,19.0,9.0,22.0,12.0,19.0,16.0,HDGBAGAAGFEEFADBADHGCGCDBCABEACGHGEABEAFGHFEHFGHFGHCGEFGEFHHACDAHFCGECEABEAEEBBABHEFEAGEDGBCEHDEADCBDABCHCCHBCGAGHACEACHFCEEBAEBAGBGFCC,False +713,10.0,16.0,20.0,25.0,19.0,11.0,23.0,14.0,FDCDDBFDGCEFFEBBEBBFDBHCFAAHGDHDBFFGFDACDAEDGEGGDCADCDDGEDGEGCEGDADCGDCBBHEBDECEHCEHGBHACEGGDCGHHGHDGCGGCGCDHHDECCEBEEDABBAGBGEAGEFDHFBHCC,False +714,7.0,8.0,11.0,9.0,14.0,8.0,8.0,14.0,AADAFBHGCCGCDHHFHBCHDCHDEHEEBFBAFHDGHDHHEAFEFCEGDHBEHCCFCHBBEDEEAFEAECGECGEGDBG,False +715,4.0,5.0,2.0,4.0,4.0,2.0,5.0,7.0,BEEHHBHHCDHCGEBGDBDHEFHFAAGAAGBDG,False +716,2.0,4.0,4.0,2.0,5.0,4.0,1.0,3.0,GBACBHFFEFFDHBDHEAEECECCB,True +717,15.0,12.0,19.0,9.0,14.0,21.0,18.0,23.0,DBHAHHEFBFAGHAGHAEHFEAAGCGHBFHBAHDCHCCDAGGHGFDAFEEEGECHCCEBGDAGCAGHGFACDHBDGBAFCFFCDFCFFCEGCBGFBCHBHAGHFHCBHAFHCFGCEGCEHFEBEEFFHDFH,False +718,21.0,29.0,17.0,17.0,19.0,12.0,14.0,21.0,BHBBDDFDBFDBDHADHBCABAHFADGBECCFDBADGEHHBBEGHEDHCHEBHBHHBEEBCABFBBFBFDAFABDGCEGCEGBEACEBBBBCDCHGEDEEGGHGAFGABGABAAHAHHAHGAHGEHCDCFDCFEEDEBHCCCACAAFABE,False +719,15.0,18.0,17.0,14.0,22.0,18.0,20.0,22.0,GGECFCHFHBEHBEDBEFBEHBDHBGAGFAHFAFECFDFHGFBGDEHECDGCAEFHEFBDGHDGDBGBBGBHGCCGCCGCHHEBBBBEEAHHBFEACADDACGCFEHFEHFAGAHGEHFAAFCHDCEGCEFDEGBHGDHEECAADA,False +720,4.0,4.0,3.0,2.0,1.0,3.0,4.0,4.0,BFBBFHBCHAHDAGEAFCADCGGGH,False +721,22.0,14.0,33.0,22.0,22.0,16.0,25.0,18.0,EGACBDEEDAADHAHBABBAEGAEGBHCBADGFBCFBAACFEEFEDHBDCGECHHHAGEAFECFEGFGAFGHCGAFGEFECFGCABEEGGDAGDCCHCCHGDEGBEDBACAHDACCCBHCAHCHDGHAECDDCDHCFCDAHHCECGECGDCGFGECCCFCCDDGDDGDFGBF,False +722,15.0,12.0,9.0,7.0,14.0,11.0,9.0,13.0,HFDHFEHEGDBCFBCAAHFAEFGGDBADEAFEAHEAHFBGFHEAGEDGBBABHGEHGECCABCEHDBADCFEEFAHFGHEAHACCABCBB,False +723,25.0,27.0,19.0,19.0,29.0,24.0,29.0,27.0,CHBDGEDBEGCHBAGECBACBGCEACAGCAGEFHHHGHAGAEDHGCGBBACHDGDAGDAGBFFBGFBDFEAFBABACDEFFEAHHAEHGHHBFABFACHHHEBGBBEABEAHEDGEDBFDCHDBGGEHHEGHFCHFHAFDAFEGGHGECDFGGBGCFEAGECBECBECFEAFEBFEHFEHBDDAEDADDFCBFEBFGHG,False +724,7.0,6.0,4.0,4.0,2.0,2.0,7.0,4.0,BACDABGAGDBGHFGHFCHAEGADGBEGBAADCBHC,False +725,13.0,14.0,14.0,9.0,9.0,11.0,7.0,5.0,ADEDDFDEGBCACCABCADGAFGFGAEGAGBAFCFFHBBHCBDBFEGAEDBDFHCEECEAFBAFHCFCCDBCABCABHBBEC,False +726,6.0,1.0,2.0,1.0,0.0,2.0,3.0,0.0,ADAAGACFACFBGGA,True +727,22.0,23.0,26.0,27.0,23.0,28.0,17.0,22.0,ECCBCCADCDDGGAHBAHFHCGHEGHCAHGHHGBEFCAFBAFHDFAFCCBACDGCBGHGEAGCDECFEBEEDFDFBHGBAGBADFEDAHDACDGEFEEHGEHFAHFAEBDBBEBFEDAEDHDDCFDGDABEGDFHBCBFDFFACFAFHEFHABDCCEABEFFHCFBFFBFCBDCBDCEDGDAHDCHCE,False +728,0.0,0.0,3.0,1.0,3.0,4.0,2.0,2.0,CEHCFCGFHDFEGFE,True +729,17.0,19.0,22.0,26.0,19.0,16.0,18.0,23.0,GFHGAGFACDAEAGFDCBCCBCBBGBDGEGCEHDDADHEDBADHDEFBEDBDGBCGAHHAEAAEBDGDGGDGABBECDEFDEFHCAHBDHBHGGDFFEFDCCDACBAHEABCHEEFCEFHGFHDEBGEBHHHHCFHEAHBAHCDDDDCGFCHFCHCCFCD,False +730,10.0,12.0,10.0,12.0,5.0,3.0,7.0,9.0,GGBHAHCBEBDABDCEDEGDCGDAFAHGAHDADDACHACGECADHABCCGCBBCBBHHBFDEHDBDFB,False +731,8.0,9.0,15.0,9.0,17.0,19.0,15.0,6.0,BHGBCGBCDBCFBCBACFAFEGFECFEGFGCEGCGADEFECHEDEEFFEFFGFFGDFCEGCACBAFADCGEEGDBADFAHHDGHGFEEDCEHFFBGEC,True +732,15.0,25.0,16.0,23.0,8.0,23.0,16.0,19.0,CCGCCHDFHDFABAHDHGDBFDHDDBBDHBGHGFDDFGGHEHABDFCHFAFCACBBDDBDFBDABHABGBEDBEDAFCFBCFGEBBHCBABGABGHBGHFGCFGCFGEBEFADCHFHFFCDDCHAEHBDGADAADGFCFFBFEBH,False +733,26.0,12.0,25.0,16.0,6.0,12.0,11.0,16.0,DDEFFEHBCBCAGCHGBHAAHCAHAHHBHHGGHCFDCADCADABFCCGAFDAGHCCCACFADFADAHBGBCFFDBCHAFAAEDEBAHBAEFAFBADBDDADCCCCCCCACCGCDGADGAEAHGH,True +734,24.0,26.0,16.0,18.0,21.0,14.0,24.0,22.0,HGDGADCHDBBAEBDEBDEBEEDECFBCAGCBCHGDBGEBDEBEEBDGBGHHFCDDHGDAGHADEBDAAHBGBAHAEEGEBGEBAACFHCFACFHFAHFAHFDHCBEAHEHBCHAHAEDGFBGDBGFBHBEGDGGACEACACBACFAGGEGBFBHAGHAGCFGHF,False +735,22.0,22.0,29.0,19.0,27.0,26.0,31.0,18.0,FACFCCFCAHCGBBDADAGDFEEFAEFAHADEGDACBFCBFBHGCGGCFFBGFGFBBHHBCAADGCDECGGCGGCAGCEGEGGDDGAGHAGHFCFCEGDGCFFBDEBDFBFEEEHEHBEAEEAEEAGEFDEGDBBEHGAGFDGEDHBCHGAAAAABCECCECCHCCDFHBFCEGEDGFBFCBFHBFHDHHCGEB,False +736,3.0,2.0,3.0,3.0,1.0,1.0,2.0,0.0,DCBDCBGCAGADEAF,True +737,25.0,20.0,13.0,20.0,9.0,15.0,15.0,17.0,BBCBGDDHBCECEDCBDHGDAGDAEAACDBCDAAHFAEFDCFAFBAGAGBABHABDABFAFFDDHHHHBFHDFGGHDCFGGHHGAAEAABCAGCBGCEGABCADEBBEFBDFHGFHDFHCFHAADEBDGADABH,False +738,15.0,21.0,15.0,20.0,23.0,14.0,16.0,14.0,HBDCBCCDFDDBDABDABDFDHHBEGEFGEFGECGECGECABBEGFEGFGFBABDGBHGBHCAEBBEBEDDDBHDAFCACCEBHGGDEDAEACFBFFBGFGEEHHEHEAHADFCDCAFCDEBDCDEGEHGAHAHEABE,False +739,6.0,4.0,7.0,3.0,11.0,9.0,13.0,4.0,CEEGFEGFDGBBEFGGDEDHCCEAFEAFBAFGACCAGAFEBFEGFGCHGEHGECGHG,True +740,18.0,18.0,17.0,21.0,22.0,23.0,24.0,19.0,CHFCHDGHDGBDCFEEFEDGHDAHDAECAFGFFHFCDEGAHBDBEDHEGAEGAEFBEHAEHABBAHFGECAHBFCDFDEEDEGDACBFHDFBGFGFEEFAEFCFBCHBDFAGGAGGAGBAGBEGEGDDGCDBBDBGEFGDDGHBBECHFCHCCFAGHCFCAH,False +741,9.0,8.0,14.0,9.0,12.0,8.0,10.0,8.0,HHAGBAGCACBHFBHFDEADGBFGCDABDCEDCEFABGECCEBCDGEEEEECECCFACHAEFGGFCGFDGDACDHHBH,False +742,12.0,15.0,13.0,8.0,14.0,16.0,4.0,12.0,AFFFBFFBCEAFAAEBHDAEAHBCHFCHBDHBFHBDEBAHGFHFBEGCFHCEAFEAHABDBEDEEFECHECGECFHCFCCDCCGBDABDBBEFA,False +743,10.0,6.0,7.0,8.0,13.0,10.0,9.0,5.0,AFAAEBGEBEECEEDFCGGHDGDFCFGHFBHEHDDAADEDDECBEFBECHCGAAFFAFEAGEAGFBGC,False +744,4.0,4.0,4.0,5.0,4.0,3.0,5.0,8.0,FHDHHGAHBHDDHGDAFEACEACEGGFHBCHBCGEDB,False +745,5.0,2.0,6.0,1.0,2.0,4.0,4.0,5.0,CHHCFFGFGAAGAHGCHABEACEHCBFCD,True +746,6.0,7.0,9.0,8.0,5.0,5.0,6.0,0.0,GDGGFGCEDBEDACDCCFACFCDABDACAACBEBBCFBFEEGBDGD,False +747,23.0,21.0,27.0,20.0,27.0,21.0,28.0,26.0,DEADBCCGHHGHDBADBADBEEBFEBEBGGCAEDAHDFDGHEAHEAGEDGEFGBAGHFHECBCAEEBEGFFFHHHDHHGACGEEDCADBAFBHGBAFBDFCDCBGHFHAFCCDCGACGAFGCEGCHBBDGCHFDAFGGGBHGBHAAHCAGEDCCGCCHBCHFFHEFCEFAAGACGCEECECHEBHEGEDFEDF,False +748,3.0,5.0,1.0,5.0,3.0,2.0,3.0,3.0,DBGHEAHDADDADECFEGBGHBFBB,False +749,11.0,7.0,13.0,10.0,10.0,9.0,18.0,6.0,AGEGGFDHECGGCGBCGECBCCEFCADCGHCGEGBEBDECGGCAFHDDHGDAGDAEAEFDGADGAFCCFBAFEFDGFAGBAHBH,False +750,19.0,21.0,8.0,26.0,26.0,23.0,18.0,20.0,FEHFHBCHBCHAAHDGEABEDCECBDDAFFAFDGDHCDEGDFADCHDEDEEGHAGDFGCFGDFAEBDFBAGHAEEAEAAFAFBAFBEBBDDBDHEFHEHDEBDEFEBBAAEAEGBEDFHDHGBEGEFBHCHFBHEGGEFGEFGDFHFHGDBGDBFDBHDGA,False +751,10.0,15.0,9.0,6.0,11.0,12.0,12.0,15.0,GDEEDHHBBFGBHHBEHFHFBDCEGGEGCBCCAFCEFBECHEHEBHBAABFABFABFGFEGAEBDHCGHAGHAFCACGAHDHFDHGBBGF,False +752,16.0,16.0,21.0,19.0,22.0,24.0,24.0,17.0,HHEEFGDFCDFCDFGHFHABEGECBCGBCGBFGDFBCBAFFGCAGCAGBAGHGDHDDHGDHGEHAECADCEFFAFFDEGBAGBCEBAHFACCDCBGEHDEGAEFCEDBEHFHAEDBGAGFECFGGAGGEFHDHECHECFECFCBDCGABDBHDFEFFED,False +753,5.0,5.0,9.0,7.0,8.0,5.0,5.0,7.0,DHCDCBFEBACFGCHGCHGEDGDDEDHAGEACFACEAHEFCCFBDHBHBEE,False +754,1.0,1.0,2.0,5.0,0.0,0.0,2.0,1.0,GGBCDDCDDADH,True +755,3.0,4.0,2.0,11.0,7.0,7.0,7.0,3.0,DDGGDGFFEFFGGDECDEDFEDFBBHBGFBHDAGCADHDDEAEE,True +756,13.0,13.0,9.0,10.0,17.0,10.0,13.0,12.0,CGAEDBDFGGHCGBCFAEEAGFBFFBFFBEGEEBEEHEECDEGACGEHAFGADHABHAHHCGHFGHEHEAHGDDCAHFAEBAEDCBBCBBGBDEDDA,False +757,8.0,8.0,4.0,5.0,4.0,3.0,10.0,2.0,BDEBGHGGFDGFDAFCGGCEBBAACEDCADHABGGBGBAABGAE,True +758,26.0,19.0,23.0,17.0,12.0,22.0,20.0,22.0,DDGDEFCHCHHDHHCHGGHDBAFBFGBFEBCAFCAFHFFDCCDCEACACBFEGGHGGDFGDHCBGAFCAFEDBEAEEBDFGDAGBHBHHADGCDFCAHCHFCGFCGHCBHABDABAACHAFAAHCBHBFABFAGFDBFHBEECGAGAAGFAEDABACCEGH,False +759,4.0,1.0,4.0,4.0,4.0,6.0,8.0,4.0,GDFGAFGDGCFGCFCAHAHDFHEEHEEGDGAFGCB,False +760,2.0,2.0,0.0,1.0,4.0,1.0,5.0,1.0,ABEDBHAEGFGGEGGE,True +761,21.0,26.0,28.0,30.0,24.0,24.0,21.0,23.0,FDCHDHHDFHCCGFFAFAAGABBDGBCGBHGEHFHFBCEACEHEHBEABDBBABAGBFFBHDEEDBGFCGFCGFBBCBBDBGGGCDECDCFECFEABGCDAEHEHBEDDADFADGAEEAEFDCFHCFBCHBCHAEDDEBGEDGFHEDCBACDGFFCEGCDACABEGCDGHEECFCFHDFBDHADHADHACGDCDDHH,False +762,24.0,12.0,13.0,17.0,17.0,14.0,9.0,11.0,CEAAEBDEFDBCCBABBACBDBDDADGCGHAEHAEHBEFAEFAFCACHBHFEHADHFEFAGFGCDADDACDEDGEBGECAEBFEBEADGACFAHAACAAEADDFFGAFGCDHDHEFH,False +763,6.0,8.0,13.0,10.0,5.0,9.0,19.0,14.0,HGDFBDFGCHDCBGCEGCEGHGHHGACGFCAEEHBBGDHGCCGFAGHADHBCGDDBEAFDHFBHFDGCAGCGFFGHBGHCGHCD,False +764,27.0,23.0,30.0,22.0,19.0,28.0,33.0,17.0,AACCCCCCFBCDCCGCFBEFDGGDCGFCFFCAECBGBFCBGEHDEFGHFGHACHGFAGEAFFFCHFDGCHGDGCFGCFGCAGDBFFBECEGCGGBGHBDAEDABFABFDBDDBDAADGHHFBAECEBHAHHEFADFADFACAACGECEEAGEABADBDHEGEDGEDBFAHGAHGAGCDFBAGBGFFDCHBHEACGGBGB,False +765,18.0,15.0,16.0,11.0,14.0,19.0,16.0,15.0,CEFGFFADDDDCFAFGAFEEEAEHBEHCECAEBAECABHACHFCFGBGGBDABCFFFGFHGHGDEDABBABBAHFACGDFGDFGCBEEDFHACHGCHGBHFEGFAACECDGCHGBHCBHBAHAF,False +766,2.0,0.0,3.0,2.0,3.0,1.0,2.0,7.0,HHEHHCCHDGHDFCEHAEGA,True +767,17.0,7.0,6.0,11.0,18.0,9.0,7.0,8.0,HEEBEFBEBEEGHEFCEACFABFHBGEAEAACAADAADADDAFABDAGDEDAGDEDHCHFABEGDEFDEAEECEGHHHFGFAC,False +768,7.0,8.0,17.0,12.0,13.0,9.0,9.0,18.0,EBDDBCDHEEEGCEFDAFDABCBBHFGHGGHDCHFEHFAHAEHCFHCAHEHBEGECHEGDECCCCDCBHCGHCBFGECACHAFHDCDDHFDHG,False +769,20.0,21.0,9.0,15.0,21.0,8.0,21.0,20.0,HEDAEDGBFGHEDHEDHEBCGAEAAFAABHDHAEHGGGBEFDFFAAEAEHCHBCHACDBFGBGABHBBEBBAHBHHDABDAGDHEFEGBGGDCGEBGCHECHECHGBEDBEDBAAFGADBAGAHGBGDCGEEGEH,False +770,21.0,9.0,20.0,15.0,18.0,14.0,11.0,20.0,AGHAHEGHACBCDEHDEHEECGABBADBFCHFEABCBDEAGEAFEAFECFDCHDBDFADCAGCADCHDEADAAHFABFEDCEGCHFHHCEACGDDGHFGAFGAHHHECAEHDHHABCEFCHFCGCCEF,False +771,4.0,4.0,4.0,6.0,5.0,8.0,8.0,13.0,HGCHGCEBAEDFEDHAHHGEHDDBGDEGBHGFHGFCFFCHADFFBHGAHFHH,True +772,4.0,7.0,15.0,14.0,7.0,5.0,7.0,12.0,FCECCEHCHDDHEFHDDAEHECCGDDBDDBEDBFCGHHHBHHBCABCHBCDEDGCHFDACDFCDGCGGAGC,True +773,15.0,15.0,19.0,12.0,10.0,13.0,9.0,11.0,CDFCAAHAADAADBHCGEAHFBGCBCCEGCDCCDEAGHAGECHFHFFBFBHFBADCADEHBECBABBHFECAGCDDCFFFHDFHDFAEGAEGBCCBCEDGBBCB,False +774,17.0,15.0,18.0,13.0,14.0,14.0,9.0,11.0,BDADABGFCGHCGAGHAGFFDCCBAGFHDFHCFHCBACEACBAGBACBECFEBGABFBFFBHHBDEEDEAHEAGFDEFAFFBDHBECCCCDCEACEHCEAADDCBAEDDEH,False +775,12.0,10.0,12.0,10.0,14.0,18.0,9.0,17.0,FFDFGDFEBAEBHFHFFBFCBFCBACEGDDCHCHDGBEEAEHAEBACCCCCAHEAFFFFFHGBHDAADAHEFHGFHEDCAHHADHGFGCHGFEEHDEHBEGB,False +776,15.0,9.0,14.0,7.0,14.0,8.0,10.0,14.0,FGGCGFEGFEGEBBABCCDCHEHHCHGFDGAEHCEFCEGCAACEACADHABADBFDCEDAABEACDGCHHCHAFAGHEHBEFEAHBAHBEH,False +777,3.0,5.0,7.0,4.0,6.0,7.0,4.0,2.0,ACHDGDFECAEGAFGEBDFBCFCCFHCEECDBGFBEFB,False +778,13.0,16.0,17.0,23.0,18.0,12.0,11.0,15.0,HGEDGCCFHBDHDDECFEHAEBAEBHDCCDFCDCHGHFGHAABCAFCGHCGCEFFEBAEBABBEHBGHBFFDDGDAEDAEABBHBBHEDFEFCDCEDCEDHHCGDDDDDAGFEBBCDDADCAEEG,False +779,0.0,0.0,2.0,3.0,0.0,5.0,2.0,1.0,DCFGFFCDFHDFG,True +780,4.0,14.0,9.0,15.0,13.0,16.0,18.0,13.0,GFHBCDDGGEFBDFGDFEDHCBBGEFEAFEHBDHGFFECCDHGHCGBBGBEDHDDEDEEDBCFHGDHGFHGFHGFGGFGBFGAFHCDCAECAEBBEDBGFBH,False +781,14.0,11.0,9.0,17.0,16.0,19.0,16.0,13.0,AHAEEAEBDCFCAFEACDFGBGHHFBHDBFDCHDHHEHFDGFAFEABDGEEEFHFABFCGFGGBCHBEGBHACEADGACGCFGBFGAFDAGBAGFDHEDEEDEFDEFDGHDGDDF,False +782,17.0,30.0,15.0,20.0,20.0,24.0,22.0,25.0,GBEGHHGHFDDAEABGCBGDDCCHFEBFGBGDBGDBGCAAFGAFDEFGEFEFAEFACBGEBAEBHBBHBCHEHHEAHDDCBCFDADDHDGHFEHBHFBDBDHAFHFFHGGAFCFGCHEEHEDFAGBCHBFGBCGDCGBHBBCFBDBDEBFEFHHCBHGBEBAEBHEFAAFDAG,False +783,18.0,12.0,19.0,16.0,8.0,23.0,23.0,21.0,CAEAGEACHFBBCABCACFADGBFCCFGDFGFBGHEGHCCHABHGBHFBGEAGCCFDAFDCHBGHCGHDFEGEHGEHFDHBDFAHFAHCGGCGDBFAGFHHFHGFDDHGHFDAGBHFHEDDDDCCGCCGADFAFGAFAAF,False +784,26.0,24.0,29.0,15.0,21.0,16.0,22.0,14.0,GEEGAEGABFAFGEBBHCCCGGBHGBFDAADAAGAFGBEBBCCGCAAHAAHDBEEBGEDADDADDAECAECBEBHEFFADBCGECGCCDCGACBACFDCFHFDHGHBBHDBCECEGCBGEBCEFAECCCHFGECGCBACBFFBGFHCECAFBAHBHHAFDAGDECAG,False +785,1.0,0.0,2.0,2.0,2.0,6.0,1.0,1.0,FFFEFFEDFCDCGAH,True +786,20.0,28.0,18.0,25.0,30.0,17.0,20.0,19.0,ECEDCEBGECGBDDAGEBEEHHADHDECGEDEEFEADEAFEAGDBDFCEFBDHBHAGAAGCAGCHHCHDBDFFEECADBAGFCBBEBDEHHEBHFAHFBCEBFEGEHADBDHBDHCDBGDBHDCGBFEADEADHAEAGBBCBACEACFDCBDHBDGEGGEBGEFGBFCBGHFGFFAB,False +787,5.0,3.0,2.0,6.0,9.0,8.0,2.0,4.0,DAEDAECHGCHBEFFEFEDFEDADHEDAEFBFABFHFEG,True +788,5.0,9.0,7.0,1.0,4.0,3.0,1.0,5.0,EBABAACHBEHFACBBFBBEABCDECHGCHBCHFC,True +789,12.0,4.0,13.0,8.0,13.0,16.0,10.0,11.0,ADAAEBAEGDFGHFGEBGADFAFFAFFEFCECEEFEGFEDFCCECHHAFDCFGHEHBBFAGFGHACECGHCDCCHCCHDFHDGAAEH,False +790,6.0,10.0,8.0,9.0,9.0,8.0,9.0,13.0,CEAHHCFHCFHBEACFACDBGDBEHBGGCGGAFDHFCHFEHBABBHDHGDEAHGBEBEGBEDHEDGCDFHDF,False +791,8.0,14.0,12.0,15.0,11.0,8.0,8.0,8.0,EBHEBDCADCAGCABCGDEADEAEECBEDADFEHECHDBHGEGCFDCFBBBHBBDGHDFFDFFGBGHBACBFCHGCDCDDEBDA,False +792,10.0,22.0,18.0,14.0,21.0,20.0,16.0,23.0,DBGEHGFDGFECFHGFEGFBAECAHFHECBABHGFACEBDGBCGHCECAEGBBCDBEGEEGHEAAECGBFHBFHAFHCFBCDHCDHDBHEAEEBHHBCCBFHBCCBHCEDDEDDEFFHHFHFFHEFDAGBFEBHCBHDBFDGGG,False +793,23.0,21.0,27.0,21.0,31.0,27.0,29.0,18.0,AGFCEBGEFGHCGECBEFEGFCBFDBFHCCHCBEDDAGFBDCCDCCDEGHEGHAFHGGHDGDBADBAGEAEAGFFCDACFACFGCFGHFHEFHEDECBEBHFGDEGCEGDBAFCCFACEEBDDHCECDEADFGBBEABHACFAEFAEHAEHEGBFCAHGEFDEAAHACGDBEFBDBBCBCEHGEFGFGGFAGDAGEG,False +794,24.0,20.0,28.0,18.0,24.0,31.0,23.0,26.0,HHAHBAHDAHGAHECHECDEHEEGEFCECEFDEDDFCDFCHBBHBHFCGGEHCAHCDGAGADGCHGHFGEEGAEBABBAEFDGDHFFEGCBFBGHBGABDBCAGCEFEBFCFAAAGAGBABCAEAAFFBFFBEBDDFFCFFHFFECFHDFGCCACFAFHCFECECCFGHFGBAGBCDHHHCCHDCEDAEDGHFG,False +795,31.0,20.0,15.0,24.0,20.0,24.0,18.0,24.0,DDFDGFDGAGEBGEBGFHEDHBDBGHCFHBDCEACAGHADHGHFGBFHCDHDHEEHGGDGGEGDFGAEAEECGFCBFABFADAADAHGCFFHBFBAFDAFDBEBAAHAAHAAHAAFABCABEBEFDHDHEFHEDABHCDDDHBHCCGDHAECAEBEHAFBACEADFBFFEAFCAFC,False +796,6.0,5.0,4.0,8.0,8.0,11.0,14.0,10.0,AGGGDBHDBEDHHCHFAGFGEECFFAFFAEDAEFEGDBGHHFHDFGCGHAGHGGHGEBCEBDFGDF,False +797,13.0,13.0,14.0,16.0,20.0,20.0,14.0,14.0,FDCFDCDGCDGAFFFFHFBDGAEEFDHFGHGBFDAFHGFHGDEDDEADCHGBHGBACAHBECACHEEEEBBDFCEBBEBFEHAGCEBAEFCEFAGFAHFGHFGCFECADCGEADEHDEBDECHB,False +798,16.0,22.0,7.0,24.0,22.0,17.0,26.0,9.0,EFHFGCFGEDGFBGFBHACDACDAGBBGECEBBBDDADDADHGGGBGGBFEEDEFDEAGEAGEAFEDDBDGCDBBBGHGDHCDBDDEGEAFEADEABABBHFBFDBFDFEEFADGADECHBGEGFFGBBHEGGFDGAGAHGEE,False +799,20.0,13.0,23.0,31.0,20.0,22.0,27.0,27.0,ACCDDCDDCHDEGDBGEBHAHGDDDCDAHDGFAGHAEBFECFBCDECBAHEACGAEGFEFFGHADDGDDACEACECCFFFDFGHBHDBHDCFGCGACFCDHCBHEFDBDGCDCDEFDEFAGHAFHAHHCEGGDBGFEGHEHHAGFEBFGAHCBHCAHDADFGDEHDHHAGHFEHGEGGDGGBF,False +800,7.0,7.0,4.0,8.0,5.0,4.0,9.0,2.0,BFADCAGBDGDDGDDAEDEFBEABEBECGDGHAGHAGFGBABCGFC,True +801,27.0,24.0,11.0,26.0,22.0,20.0,24.0,21.0,FDEFHBBHDBDFECFEGGEGBBBFGBAGBGFBAEHFGHCAACHBBHBDHEABEFBAFGEDECDEGFGGHDGAGGAHCBHEEEFHEDHADFDHGEGFAAACDFDDFBDCEAHEBHEAAEFBDABAABHABDAGDADFAHFGHFGHCGDFGEBCDBDAGDBGHAHDADAGECDACDE,False +802,24.0,16.0,21.0,28.0,24.0,24.0,17.0,24.0,EHGDHECEADBDCGFCGDCFDEFDHFEEBHECAGBDHDDAAAAGEHGCCGBEGCEGEFDEBDAAGEFCAFABFBEAGEAFECCDDCDDHDHFDEFGAACEEEHGHHADHFHADHFCCAHGACGAHECBEBBDFBCFBHADDAGDCDFAHFAHFABFEBFECFHDBHDBHDGHFHFCDF,False +803,20.0,21.0,21.0,27.0,21.0,19.0,21.0,15.0,CHCDAADHHDHFEEFGGDBGABGCBCFAHFHFFGBDEBFEAFEHBEFDEFDAHCGGCDFCGCGECGEAGDBCEBGAADFADFCDAEDBDAHAEHAEGGEGAHGADFCHCCHBDBBGEADDADDBFDBCBBCBEGDDCEEAGDCGDFDEGBEBBFBAHCEHCFCFD,False +804,1.0,2.0,0.0,1.0,3.0,0.0,1.0,2.0,HBEHBEDEAG,True +805,17.0,17.0,12.0,11.0,12.0,11.0,11.0,14.0,CACCACHGBBBBABBDBGEGCAGFBEFAEBAECGBHHHHHHHFDEFGCGGBBBAFFAFFACAACGACDDEFEEDEADHAHCBHDGHABHEBGCFAHBEDDDFEDA,False +806,8.0,5.0,13.0,9.0,8.0,4.0,5.0,7.0,AABDACCACDACDBCBEEHEHCDHEDGEDADGFFCCBCGBEHCHHDGHECCFDCFAEGA,False +807,2.0,3.0,6.0,1.0,2.0,2.0,5.0,2.0,CCGFCGCAGEGGHBBHBDCFECA,True +808,8.0,11.0,13.0,11.0,20.0,5.0,10.0,7.0,EDGEBEBGEBGECCCADEEEBCEGEDBECBCCDAEDHECHAGHGCDDFDBFEBFEBEEGEFHAAGABGDFHDCHACBEDGECAHC,False +809,19.0,18.0,17.0,18.0,21.0,24.0,23.0,21.0,GGGGAGFDDEHDEHAEFAGHHHHCBECAGCEGEBGABGFBDCHDBHEHHGHFAHGCBGFDCFDCFBEFHHDAGFFGCEEDHGDCADAAHEEDEBHHFAFFABFACCBCABHGCGDBEDFEGFCGFBFBBCBBDFEGFECFAHDAEDAEAEEDCBGGFFFHA,False +810,20.0,16.0,11.0,12.0,13.0,19.0,22.0,18.0,AGFCHFDDFBEHGEHGBHGDCGFCHEGAGADFAGGAHAFBABBFBBGGAABAAEADEBDGCHHEBGCAEAHEGCAGFHDFHFEHAGDGFDBFBBFADCGDBGHFGHCCCGCDGBBAAFFAFHHFEHFEHEE,False +811,17.0,22.0,15.0,31.0,25.0,25.0,18.0,24.0,HAFEGGECCHDGGGHDGCDGDEAAEHGEFGBGGHGBEFEEBCHAEHCFHDFHDFGDGDBGDAFBFFBFHEECEDBEDHDBEDBFDBFABDEFCHAEFEDHCDAFDCBDABDABFCBCDHEHFCAFCDBEDACDEHFFHFFEEEBDEHEBHBHHAHGBHDHGDBCABDADDFDAFGAF,False +812,13.0,7.0,5.0,13.0,10.0,18.0,4.0,11.0,FGEADHABHAEHFCHFAAEEAFEAFDAFABEGGHFFBBDBHCAHADHBFADCCHEDFGDFDDBDFEDFEHFDAFDFFEHFC,True +813,30.0,25.0,17.0,27.0,18.0,16.0,23.0,20.0,DGAGBDGFDGFAAACAGCEFHDAHDBHCBACFACFGHFEFBHHBDHBAEDAHCEFDGCAADABGABDEGDGCAGCEGBABEABDFGDFADFABGBHGAFGDDGHDAHDCDDEDGECHEHGFBBFHBEBBCBDGGHHCEHBEGBCGADAADBHEFDEFHEAADCCHEDECAAABABB,False +814,24.0,14.0,14.0,18.0,16.0,18.0,16.0,21.0,ACBABDDGDGCCHAEHAEFDEFGHFGHFGDCGEBFDBGGBFACACFAGEHGBAFBAEAAEFHEGHCAEAADDHCABFHHEDHDHACHAGHACHGCHCHDDHABAAFADDBBABFHCFGCFEDDEDDHFEHFEGFBGEAFEB,False +815,13.0,9.0,13.0,16.0,13.0,6.0,10.0,11.0,EBHEDEGACDDCDGCDACHFCECCHGBHGBHCBEDAEDHFAFEAHEADAAEADDFFEGBDGEHHABGGHGCCADCDDCDHCABEFBEDBAG,False +816,3.0,7.0,5.0,5.0,0.0,0.0,5.0,2.0,DDCDBADBHGBGBBGCCCACBAGBDGH,True +817,5.0,5.0,2.0,2.0,3.0,8.0,12.0,6.0,HCHGCGFHGAEAFGHFGHFGFEADEHDFBGGGGGGFBFABABB,True +818,1.0,11.0,9.0,4.0,7.0,7.0,8.0,7.0,GABGHBHDBHCBECBFGHFGBCBBFEBECCEFCDFCGHCFCDHEFGEGBEBHDG,False +819,2.0,2.0,5.0,5.0,0.0,2.0,1.0,5.0,CDACFHHFAHDBHCCDCHDBGD,True +820,11.0,24.0,12.0,20.0,8.0,10.0,7.0,16.0,DDBDDECFEFFEBFBBABHAFHGGCCADEHHABDDDDCGHFABFABFHDCBDBGDBCDBFEHHCBHADHADBADCHDCBDHBEHBHABCGBEGBCDCGHBDAEFBBBH,False +821,9.0,5.0,8.0,7.0,7.0,2.0,8.0,6.0,DCDGGAGGCHGCHBBEEAGEGEFCEDADAADAAFCABCEHCBHBEHCAHDDG,False +822,4.0,6.0,4.0,6.0,8.0,10.0,6.0,8.0,DGEHGBHAFDDFEAHBFCBFCDFADFCDHGEHGBFCBHEHGEBEEHEFGFFA,False +823,11.0,21.0,15.0,29.0,14.0,28.0,25.0,13.0,GCBACBGFGGFADDGDDHCCBEGFEGBDBBDFFEFECFBCFBFFGFFGDDHHDFHEFDEDDAFAGFDEBEBBDDHDEHGCHFCGCAGCFGDGGHCFBBFBDCGGEGDEBAHFDEADEADFCDGABFDDFGDCGBFADABDGBHGHGFHFDHFEBCB,False +824,9.0,9.0,18.0,17.0,22.0,11.0,12.0,16.0,HDHHDBHCFHEEAEBDEDAEDBEDBHHAFFDDFCHGCHECDDCEEEFEDGADGCDCCHCAHCAHCEHGECGEGGHFDCCEECACBGCEGFGDEBAFFAGCGBEEEFDEFDBHBH,False +825,13.0,14.0,23.0,11.0,13.0,29.0,17.0,16.0,CFBCFDDFBDFBHFHGFAGEAFFBHFCCFCFACFACFDCAEBHFGGBAGDEEHBGFAGFHEDHGFEBFHHFGFDCFCBHEEGGCFGEFBCADHHDBFDBHDHACHCCGCEGAGGFFACCAECFHCGBCEFCEFCAB,False +826,5.0,8.0,5.0,6.0,10.0,4.0,3.0,7.0,DDEDAGAAGAHCDDBBHBGEEFHECEFHEBHEFHECEECBBCHBDFBA,False +827,20.0,17.0,26.0,28.0,18.0,27.0,26.0,26.0,ECFEGFEHFHHFABFABFEHABHAGDBHDBHDBGDGCDGHABHAFCEHDBHGCDCEFEEADECDAFBGFEGFBAAGDGDDEEDHDABDABFAGFDGDDADCBDAHGHHGHHFFFFFGCDEDGGCBCFEDGCCGCCDCEFFHHAHDBHAFCCFDGBCCHACHDEGGEGCCDCCHCBGFAAFEGFGCHHF,False +828,10.0,8.0,14.0,9.0,25.0,17.0,21.0,17.0,ECHGCHBCGEFDEFDECDEGBECBHBHHFFGGFGGHDGHACCAHHBDCFGAFGAGEEHEAHECEEHEEBEEGDECFEBFECFHFFGGGAEGHEGFCFBAGAHEEGDAAHFHCFGEEDFGDC,False +829,3.0,3.0,1.0,2.0,3.0,6.0,4.0,4.0,DHEHHDFHGGBAGAFEACEGFBFFBF,False +830,13.0,14.0,5.0,14.0,12.0,16.0,14.0,22.0,GDABFFCGFEHEGFFBHCBHEDHFGFBBFEDEHDHHGFHAEHAEHCEHABHADGEDGAFGHBCHAGHADHEFHFFGFGBAABAABDGBDCHDGBEAFHHDDBDHBFHDEG,False +831,30.0,21.0,25.0,25.0,16.0,20.0,17.0,32.0,ABDAGCAGBEEEEFEEFGBFGACGBHGBHCAACAACGCHGHADHACEECHDHACHFEGEAGDAHDAHDGBBHBFHGCHEHHAFGFFDDBGHHDHDEHABBACBHCADFDDHBDHBDCDCBDAHFFHDDBFHAGCDBFFEECCECCGHAHCAHBEHDACDAHDFCDAHDBBFFBAFCFFCAHAAGAC,False +832,25.0,27.0,23.0,20.0,26.0,20.0,20.0,27.0,AADBAGBCFACEEGDFBFFBFHCGDBHEFHCFBFBEEBHCCHCHBEBGABDAHDFHDHHFEHGECGFCBHDFHABBDDBDFHDGCGCCGCDGCHBHEEDEHDHBDEEHEGHBBHFBHFBGCEGEDAEGAECCEAAEACBAHDEBAEBFGACGAFAHDABAHDGCDEAHEAFECFGAACBACHAGBFGE,False +833,25.0,13.0,14.0,24.0,17.0,12.0,19.0,18.0,AEBDEBFCFGAEEHEAHBAHDCFDHFBFAGFAGAEGCCDCAAGAHEHHGAHEACFDEGDCFBAGGABGADGCDGFEBFEAAAGAAECBGDFCDBEDHEBCDDHDDHDGHDHHGCHGEBGHCAHDEEDCDDBADAAGABHDDF,False +834,15.0,10.0,18.0,19.0,15.0,14.0,14.0,17.0,GFDGHHGDHFHCFDBEBGADGACECCHHCHFAHCEHCHHDEHAEBADDGDBGDEEDECDFCAFEEFEDDHDCGAHBAGBDEADGHEFDFABCEBFGBCABCFGCFACGDHDEHACACCAFGF,False +835,20.0,10.0,18.0,14.0,16.0,28.0,23.0,12.0,CBFFGFCHEDBFHGFEGFEGFEDCEDAEHAGGGGFGGCCCDGCFGCFHAFBAFBDFCFFHAAGCEGAEGHEGDFAFFCDFADECHEAHGFGEHGEBDDBABFABABECHCFGCDDFFGFAACAAEDHGGHECDBAFCAFAF,False +836,30.0,20.0,19.0,16.0,19.0,13.0,25.0,21.0,GEHGEGBFGFCGFAGHHGFGGFDHAAHECBAGGAGHCGBCABFHBECAAHAFCEBCEACEADDADCGHBDHGFEDBCAEGAHGHCGHCGEBBHGDHEDHDFBEBBFADEAHEACBAEGFDCAABAABAABGAEACHBHDGADHAEBACHDGDAGCEDCEFCBF,False +837,11.0,6.0,11.0,21.0,12.0,11.0,14.0,20.0,CCGFFHDFDCHECHGCEGCGGDDGABGAEHDEHGGHGHDDHDABDHBHFFGEFHDAEDFEDFGFAHHHCFHAEDGEHCHFDADDGDBADAHDAHDCDCCBEHBEAE,False +838,2.0,11.0,5.0,5.0,5.0,11.0,2.0,7.0,HHAFDBFCBFHBFCBHCFEBHEBCFBFEBEHBDDDEDCABBFFGFFGH,True +839,10.0,18.0,12.0,15.0,22.0,22.0,14.0,20.0,GHGGHDGHEHCFHBHHGHGFDFFBHGBDFBCFBFEBAHAACAEBAFCEFHEABGAHCBCCADAEHFDHFEFFEHFEHCECGHFEBFGCFDBBDBDDCEDEEDEEFBFFGDBBEBGEAEHFDCEGEEDHGDHBF,False +840,6.0,5.0,3.0,4.0,8.0,4.0,5.0,6.0,HFAHFAGABEEHFEBBEABCGBGAFGAECDEDHEHHEDGDC,False +841,22.0,25.0,12.0,20.0,30.0,18.0,24.0,19.0,CFDABGGBGGDGGBGDBGDFEHGEHAEDEEDEEAEGABBABHABFEGAAAAFAAGHFEEEAHFBBFBDHEHAGHADHFDHEDHEDCFAHFEHGEHEEHCBBDBBGBGEBCEBFEHDCFAGFECABGDHEFFEBEACCHEGEGCAFDACECDGDBHEFCGFGGBBBDBDDA,False +842,26.0,32.0,18.0,28.0,33.0,16.0,26.0,21.0,BDFEACGAHGEHBEFBDDCDDEBGFBAHCGBBGCEDEHBAFGGFBDFDABCCBFCBHEBEAFGAEGFEGEDGAABBHBDCAAEAEEBEBGDGGDGHDHHCACBEGGDHADHGEFEBDEBDHBDHBEHBHDDCDFCDCGAGGEGGEGFECAEABEAHDAHCFFCDHAAHAACAABFEEEBDEBDGBDBCEEHDBGEBEAHF,False +843,17.0,15.0,21.0,18.0,10.0,19.0,19.0,11.0,GCGCCGCDBAAFCFFCGCCFCBGCBHBGADGFEEEBEDCFDCFBEFAEGDDDDDAGACDEFDBFGCFGEFDDHCGGGGGAFACHACHACGADGHHCHBFAAFDFFDABBEBFHBHEBHCAHBADGABFDC,False +844,28.0,20.0,25.0,32.0,29.0,10.0,34.0,16.0,GCBGCEAHBHHGHCGADBHDGAFGCFEEFDEAABAAFACGACHAGEEEEEBDBDDGEAEBGCFGAFGCGACGAGFEDAGDAGDBGDFEBECDGBDHBDBBDAEHADAAHGDCGDEBAHBEDCGBEGHEDHCCEDDEDCEGCDHDACAABADGEEFCEFGGAHGCCGCBECECBDHDCADAGDGGDGGDECHEBD,False +845,9.0,18.0,18.0,15.0,16.0,16.0,18.0,30.0,FHHFCHBCEBFEBFBHCGHEGFEDEHABHBHCEHCGGEGGCGGDGHDFHBFHAGACEDBBBBBFHEDHAHHBHEGHEHFDHEBHDDHCDCDHCACADBHDAAEGHFCCECCFHHBHGDHCDHFDGFBGFGGECAFBFCEG,False +846,25.0,21.0,20.0,25.0,14.0,20.0,19.0,27.0,DHHAHHGHBEBFFBHACHBCHFEAFHAGEAGEDFFDHACGDCGEBDDBGEAFAAGAAHAAFCFDCAEFBEGHGDCFAEDABDABHGBHGFHFDGDDGDDHFBABCADDACHBCHCGECACDBCGBCFHEHCCBBHHHFHFBHECEDHDAHDFDDFBBFDBEGACGACGADG,False +847,19.0,22.0,26.0,32.0,24.0,20.0,17.0,30.0,FFFFFBEBBCDDHBEHDHHFHCDHCDBCDAFBHDGHDECDEDGEDCBFEFEHAHHAEDBDGHDCHECDEFHHADHCHBCHCDDCHBBHBEECCDFEDFDBGDBDFBEBAEFAHAGFECCACDHCEHCGGCGGCAGABCAGAGCDBADGEDFEGAEGAEHACHCBHABDBEDEDDHADGGFBFFHEFHCAH,False +848,9.0,6.0,11.0,10.0,14.0,15.0,7.0,8.0,EBECBHGDFECFDGFDHFDCEAAGDEFDEFDFFHCAHGBDDHDHFEGEGBAFCEFCAFCACCACBAFHFEHEEFEGAEBC,False +849,4.0,12.0,3.0,4.0,4.0,6.0,9.0,4.0,BADBFBBDBCDAGGEGGAHFBHFECBBGGCGGBBGBDFFHFEHAEB,True +850,11.0,16.0,15.0,13.0,9.0,18.0,8.0,14.0,AHEFHEDHAHCBEFAEABEBBDHGAGCECCECCEDGADFFBFFBFFACACDFCDECHHFDFFHFFGFBAHBCDBGDBGHHGHFBDBHDBCCFHDACABDGBCBF,False +851,14.0,6.0,9.0,8.0,8.0,11.0,8.0,4.0,CADAAFAFGGBDGBECHEGAEGCEGHEAFCGCCAFCAFDBEHBAAAFAFFECEDADGACFBDFHDFBD,False +852,13.0,17.0,14.0,11.0,14.0,23.0,28.0,19.0,AHFBHFEDBHCBHGDHDDBEFGAFBEDCEDCGGCAGCHGCHGCDCEEGFBBFHCGHAGDCFEGABFCBECBAFBAFHHGHEBCFAEGGEGAFBFGGGDGBDBFAEEBGAGHAFHCFHFFAGFHGFHFFHGGBGGHDGFE,False +853,17.0,14.0,15.0,18.0,12.0,25.0,14.0,18.0,FEEDCEDAEDABFABGHCGEGBAFBAFADFDDFBDFGDGEEAEHDGHCFHCHGBHFHFACAEBGHHGHAGAAFFDCCDHCGGCFDCFHCGECADCFDBFEBFBDGHDCHCHDAFFFHFBBEAFADFHBFHFAB,False +854,4.0,8.0,7.0,9.0,7.0,13.0,4.0,5.0,HAHBAEBCEFDHFGBFDDFDDFCGFBBCBFCFFCAFEDFBCGCDGEHEEDFDHFEBA,False +855,8.0,9.0,7.0,8.0,14.0,11.0,8.0,11.0,FCGGHEGHCAHEGDGCDHEBHEGEEFAEFCEAAFAHDEHFEHBGFBFFBFEAHEADCBBCBBCEGDDHFDFBHEAD,False +856,15.0,19.0,19.0,21.0,20.0,23.0,9.0,21.0,EHCABCEDCEDCHDBADEFFEAHGADFHBFEBFEHFEGCHGBBFBDFDCFHCFCGHCDHEHADFFEFHCGHCBABEEBEFBCDBCEHDACDBBDCBACBAEBDDCADFAEFEEHDGHDEEFBFFDHGHFGAFAHFCGFHBHDADAHC,False +857,8.0,14.0,12.0,26.0,12.0,12.0,24.0,18.0,DDGDGFHGDEEDEHGEDDCHGCAGDGBBHHAHDBHDBGACHCCHFCHGGHDGHDBFABCHGHGFDCEAGEADEGDADEGHBCFBGFGDCGBFDFFDCBDCGDGBEGBFGEHHEFHDFGDAEDBDDB,False +858,3.0,12.0,7.0,10.0,7.0,11.0,5.0,6.0,EHBFDFFCEGCEBFAFCCFECFHDGCEHAEFDBFDBAHBGHBGEBCDFDDFBDBDGBHBBD,False +859,15.0,8.0,5.0,5.0,11.0,6.0,8.0,9.0,AFHEGGEGBEDBACAADADGGHGFEGCEHCDAFECBBABHHEHAECFHBAHGABDEBAEFAEFAHAA,False +860,24.0,23.0,16.0,29.0,25.0,13.0,28.0,31.0,ABDBGHHDBEAACAHBDDDDHHGAHBDHDAHCGHCAEGFECFECGHAGBBDBDDBDGBDBAEBACDAHDBGDBCEBGEDDEBDBBABGGGGGEHAEGGGDFHDAHAHFAFDCHDCHEFBEAGECHFCHGGEGGAGFDHADEGHAFHBGHEFBCAGCAEBHEDHEDEEDFEGFHCEHDHHFCHEAGECHA,False +861,19.0,16.0,16.0,18.0,22.0,19.0,15.0,18.0,HBDHADGAFFFCFDCFDHFAEEDEEABBABHHEAEDAHDEHCGFEECHECEFGHFDHFEEGCBDFDGHDGHDCBDCAECAHBACGEFBFFAFBAFBEDHDAHBBDGEGCEGBGDFGAFGAHCHGFECAEGABAHBACBECECD,False +862,23.0,28.0,34.0,23.0,21.0,19.0,19.0,23.0,AADEFDECBCFBFEGCHHCBCAHCAEDAEDFGBAHBGBBGEDGEFBAFBABEABFAHFAHADGBHAAHAAHCFCAECBEHBACDDCDCHDHHDAHDAHCFBCDHCBBGDEDEHFBCCCCCDGEDEEBCBHCDEBEHBCGCDECGCCGBCGBCFAGGACBHBFCAGCFBDHBFHFECFGHEGCEFDDFGDG,False +863,11.0,5.0,11.0,10.0,13.0,17.0,9.0,9.0,HGFAGHEGFFAEFGCHCCHCFACEAFEAFBFFBEEDDDGGDFEBHDFEDFEFCEHCDAAFBAFHCFECHEDDABDAGCCGAHGEF,False +864,8.0,4.0,8.0,5.0,6.0,11.0,2.0,13.0,CGDDADAFHFEHACHFFHAFHAGABEFBHHCHFCFBEHCEHDEFDCFEFHCAHCAHB,True +865,6.0,7.0,13.0,8.0,5.0,5.0,10.0,8.0,EBBEADDABHGBFBHDAHDFCCCCCGDCGACEFCEGCGGCDHHBGHCGCGBFDDFEAHCAHG,False +866,13.0,18.0,13.0,24.0,13.0,21.0,16.0,22.0,CECHEHGAHDBHAACGDDGDDGBGFBACBAFGCFGEBHHBHBBFBBFGDFEBHDBAEEAGEHFEDGEDFFHFADDADFHCHEADCFDBEDCDDFFBFFHFGEFGHCDFBHADHFDHFHCGCAGDACEBDHBDGDHGCHBH,False +867,3.0,4.0,1.0,1.0,0.0,0.0,2.0,1.0,BGHBGBAABACD,True +868,12.0,15.0,8.0,11.0,24.0,11.0,16.0,16.0,GBGAFGAHEABDAHEEHEGHFBEGHCHHCBDFECAADDGHFHFGEAGEBCDGEDBEFEEFGDGGAHGDHEEHBEHGEAGECGEAHECHBBEFBHBBDBBDCBFEFEEFECAAD,False +869,14.0,6.0,19.0,11.0,20.0,15.0,11.0,18.0,AFHAEHAEHGFHACHADFFGGFEGFEGDEDBAFBDECHHGHCCDBCFECHCHFBEDEECHACDGFDCHCEHFHCFACEACEACBCGBGEADECEEGFEHFACEDHEDHAGHFCA,False +870,7.0,10.0,10.0,16.0,6.0,4.0,11.0,16.0,HCBDCBHCBACDCCDHFHAGHCCDECGEDGDAFHGHGBDDFADHGDHBDHBGHFHEAABGBDHEDHEHHEGDDGADGCBB,False +871,6.0,1.0,1.0,3.0,2.0,4.0,9.0,6.0,AHCGEDGAHEAHAFGAGGBHGAHGFGDFGFHD,True +872,3.0,5.0,3.0,3.0,6.0,1.0,1.0,2.0,BBBDCBEGHEFHDBADAECAECEE,True +873,2.0,1.0,1.0,2.0,5.0,1.0,2.0,3.0,HEGAEHAEBCFDEHDEG,True +874,7.0,21.0,14.0,14.0,9.0,12.0,13.0,10.0,FDBFBBDBADBHBAGDHHCGEFDEBGEGGFGBCGEADAGGADHBDFCDECGBCEDFHFGHFEAFGHEDCEDCBFCBCCBHBBHBBDCBFGBCBHDBCAFC,False +875,6.0,6.0,10.0,12.0,5.0,8.0,13.0,6.0,GCGGCGGHBFDDADDBDFBDGCFGAEGAFBBCBHHFDHADHAGCDGEDEFGGCECCHDCEACGDFF,False +876,19.0,14.0,14.0,17.0,5.0,8.0,26.0,9.0,ADBACAGCHGCFGHDADABGEDABDABAFGCFDCADGGGGGGGGGBGGBACCHHAAGAADAGDAGDCGDBFFBCFBEBCEBGBBHEGDDCCCBHHAFGDGADGDDAFCGHHE,True +877,11.0,23.0,26.0,15.0,25.0,13.0,27.0,20.0,DHHEHGFGGCEHCGDGEDHCDHBFEDFEAFHBDGFCBHCEECEECBHCACGACACHGBHGBGGECGBDHCFEEEHCGHCGHCEBEFBGABCDDEGGEGGEGFEDBEBBGBCGBHABGEDCABCFECAHHBBCBDCAGBDGBAGCAHFHEBCEGCDFFDEF,False +878,10.0,21.0,12.0,20.0,16.0,27.0,18.0,16.0,EGCEHFAFAEBBGACGEEDEBDEFDBBDCBDEDFFAFGHBDFBHBGHBEBEGDDGDGBHGBHBFFGDFCFGCFAEGHEDEEDEAFFFFFFCHGGDGAFGAFHDBHEBCAGHBFDFFBHFCHFCHCCDCFDHBDGBDBHFA,False +879,13.0,7.0,15.0,3.0,11.0,11.0,9.0,9.0,CHBCFBFGEFEHCCAFAAFCEECBBHEEGEFBEABAADGAGGFGFCGACEHCHCFECADCACCACFAHFHDGHGAHEB,False +880,18.0,17.0,11.0,7.0,12.0,11.0,12.0,19.0,GACGHHGCCDAEAEBAFGHFGHEHABHBDHGCHGCHBABEEBECDDBABBHFHGCBGCBFAAGDAGHHHCAFCABAABAABHAFDAFBGDCHFEBEEHEFHEFBFHE,False +881,15.0,14.0,12.0,18.0,16.0,16.0,10.0,24.0,EFDEFDHBEHAEFFBHEBGEFABHGEHDFHAFEBCDGDAFDAHAACDACDGCEHDBBBBHDHEAEFAHGDFDABHABHAEHFEHFHHFHBFHAFHAEDCGBGGDDHDEHCBCCHCEFDGGHCDCC,False +882,1.0,3.0,4.0,5.0,7.0,5.0,2.0,5.0,HDHBCGDFACFECFEFBDFDGHEEHEBHEDCE,True +883,10.0,19.0,13.0,15.0,16.0,14.0,11.0,10.0,FDEBDAHCBEFHFHGGHGEBGCHCEECDACEFBAFHCBCEBAGBFGCEGBEHDDHBDHCDAFDEBDFBDEADBADBAECAGDABCGDCFBGFBDFBEFBFGBEHEECF,False +884,4.0,20.0,14.0,12.0,17.0,18.0,12.0,16.0,DHCFHCBHGFHFEDFEDBCDBFHHGCDFADCGHFBDCBDHAGEFBEHBEDCEGCABFHBHCCCCBHCGGFGFFBFBBEGFEBBBCGEGHHHFDAFDEFBEFHEGDEBEEBEEB,False +885,4.0,5.0,7.0,5.0,3.0,5.0,11.0,4.0,GBBEAFCABHGBGEFGDDCBDCFGCAGCDGCGHEGHFCHFGAGD,False +886,4.0,2.0,5.0,6.0,4.0,7.0,8.0,6.0,DEGFEGHBGCGHBGHDFAFFAFDADGCHECDECFFCHADHGG,False +887,7.0,10.0,2.0,12.0,7.0,8.0,10.0,7.0,HDGHAEDCDDBGDBAEBGCBDAEGFGFBGFBDDBFHBEHADFGDFHHFHEDGADGAFEAGEBB,False +888,22.0,21.0,26.0,15.0,24.0,25.0,19.0,23.0,HFHEFEAADAGDBCEBGEBEFHEGHAGEDGADFEBFCBFBBFCEHADFEHGHHFDFCHFCHDBGDHAAHFCFAEBAEGCEGCFFAHHGHHFHHCHCBABGDHHDFABGCFACFECDEAGEAGFBCFGCEGCBBBEBAGHGGCBAFACFDCDDCFCAHCACCBEEBEEBEADCCEF,False +889,14.0,18.0,14.0,7.0,16.0,10.0,10.0,16.0,FHAHHEDDECCCHBCBBFBFCBACDAGHAGHBFHBCHBEGEEGBBGBBGEAEAHHBEFFEAFEDHECEEGABGBDGCABEABAFCHCAACGBHHAHCDHFECFED,False +890,18.0,20.0,25.0,21.0,23.0,27.0,22.0,23.0,ECFEGEBFABFABCDBFHBHABHBDHGFGBFGECGCFHADHDEACCBHFEGFACHECHFBACCCBEBBDFDAEAABDAECCCFCFFCFFCEGCHBEGDEDFBDEGHFCHFCFDCFEGGEGDDGHDHHCGHFDFBDHGHHAAHAEHFGAFGAEADEFCEFBEGBGGHDAEDCEHCDGBDG,False +891,21.0,17.0,16.0,20.0,21.0,17.0,22.0,30.0,GEDGFABBHBBHFAGAEEAEAAECAEHHHBDDCABHGGHGCBAAFABFBFCGEBFEGEHHEHHDDHFGEEHDGHCAHFADBADCCGACHDGHAGHAFHAFBECBEDHGCHGAHGBDCEDCDBFDEGHGADGDHGFHCDGDFHBHHBHAECFECFEGFHFEDCED,False +892,2.0,4.0,1.0,8.0,1.0,2.0,5.0,5.0,HHHHBDABDGBDFFDCAHGGGBDGDDED,True +893,15.0,5.0,9.0,8.0,9.0,2.0,15.0,5.0,GGEGEEDAFGECACCAGFGEEDECDBAEGADGABAACCACCAHGAHADHGDGGHGBACBHBDEGAAGD,True +894,15.0,20.0,23.0,20.0,17.0,18.0,26.0,16.0,FGDFCFCCGBFEBEEDACGECGHCFFEDBBCHBFHBDAFHBGCFCCFAGHDGDGGBFEEGCEGAFGAEAFEDFEDBBDHBHGGGGCFDCEHBEHGCAAAAAGHCHHCHBGDDCDBGBBCABCABADBADBFDGGCCEDEEDGCGGDDGHCFHEFH,False +895,17.0,14.0,14.0,9.0,18.0,14.0,9.0,18.0,BGCDCCFADADBGDGCAEEAGEBEFBHHAEFFEHFEBEBCGCEBCEDAGGAHEABEABDAFDHBHHAAHBAHAHBAHCEHCAHFHBEHFCFFCEFCEHCHHCAEDFEDBGFGF,False +896,10.0,10.0,7.0,13.0,14.0,14.0,10.0,8.0,HCBCDHHGEAFHFCDGHEBDEAFBCFEDFADEADEADABBHCAEDGDDGFDAFHHFDGFGGFABFBCDBCEAGBBGEFGEFEEFEE,False +897,1.0,6.0,2.0,6.0,4.0,12.0,5.0,5.0,FBDGCGGDFEBFEFFEGFBGFHFFDFHBAHFEDFCHBBHDD,True +898,8.0,2.0,6.0,2.0,1.0,5.0,2.0,3.0,CFFCHDCFEHHAADAACCABAACGAFGBF,True +899,13.0,11.0,11.0,13.0,12.0,11.0,12.0,9.0,FCCGCABEBEEFCBGCDGCAECEEHAEGDCFFHDBCABDABEAFCBHABHADHGDFGDFBDFEDGHBGDGDAGAFECHEGDEGHFAHDABAF,False +900,11.0,8.0,16.0,15.0,15.0,12.0,12.0,10.0,HFDECDECFHCHGDEDEEBGHDAHDABCCDDFGDCGBCACCDGGFCGFEHEAGEAGEAFCCHCCAFEAFADEADHGDBFBBFBBFGCEAHFCDEEDHEG,False +901,6.0,5.0,13.0,12.0,14.0,4.0,0.0,2.0,DEEDEFCACAAEHEECDECAHCBDDECCBCFFDBFBCDECEECEDCADEDDEDACB,True +902,5.0,2.0,3.0,0.0,2.0,4.0,3.0,0.0,CFECFBAGAACAAGFFGBE,True +903,1.0,3.0,5.0,2.0,2.0,3.0,3.0,5.0,HEAGEFBCDBCBCFHCFHCDHGHG,False +904,8.0,10.0,8.0,10.0,10.0,10.0,8.0,8.0,HAEHAEDAEDGHFGFFAFFBFFGDABDECDEGGEGHBHBBCCFEDGECBCCBACHDCAFBDDEEDAHGBHBF,False +905,19.0,35.0,22.0,16.0,17.0,18.0,22.0,17.0,BEDEDGGBEBBDBGHBCBBCBHCAEAHBAGBCBHDBHDCHGCBGDAGDCCAGDGCDFCBFCBDBBDHAAEAGEGGEGBAFBHFGFGBFHEACECCGHCFFEFBCFBAFAABBBBBHDBEFBHFAGBEFCDGCFCDEEHBBFBDCGDEGFHGACAACAHHFGHEABE,False +906,6.0,6.0,11.0,1.0,5.0,2.0,8.0,3.0,GGECBACGCCGHCBFEGGAACAACDACBBCHCEFCEHBEGBG,True +907,10.0,11.0,15.0,22.0,12.0,15.0,10.0,11.0,CBDCFAHHHHCHDBDDBEDHCAECDFFDACDGBDABCFBCFBGDCFFCFEEHGGHGADGDFAFACGDCADFBCFGDFEDFDDADGAHEBHFCHDCDEEBEEDEGBE,False +908,4.0,0.0,2.0,5.0,3.0,0.0,2.0,3.0,GHACDADAEDAEDEGDHHC,True +909,1.0,4.0,0.0,5.0,2.0,3.0,1.0,1.0,FDHBDABFEBDDBDEGF,True +910,9.0,19.0,26.0,20.0,13.0,12.0,16.0,22.0,BHDCHGCHBCHDCBGCAEDFEBFBHDBHDGHEGECGCFDCHHGHHBHGFGCCBCCDCHAADFFDFFHEDCFBCEHCEHCDDFAGECGDBDBGFGEECBHCBACBACHCDEFDAHBCHCEGBGGCDDHDEHBAGBADB,False +911,5.0,1.0,2.0,3.0,2.0,3.0,0.0,2.0,HAHAADAFBAFEFCEDCD,True +912,26.0,20.0,25.0,15.0,11.0,21.0,19.0,28.0,BGFDDHABFAGCACFBCDBGDCCAAAHAAHFCHCEGGFFHHFBCABCGGGGBHEAHCAHBAHAHHACHFDHDAHABHCBFEBFADFGDCGFFHCGBCFBDFEDCHBBHBCGECGEHGFHAEHACHADAABHFDECEGBAGDHFDHCCFGAEGAECABFFBHCCHD,False +913,7.0,7.0,5.0,3.0,0.0,6.0,1.0,6.0,CDFCAFHACADCBBHBFHBFHFDGCABBABFHHAA,True +914,20.0,24.0,25.0,24.0,19.0,23.0,23.0,19.0,BDHFDGCHCAHFAHFGGCHBCHDFEDAEHCBFEBCGHCGFEACCAHDFGDFDBFBEFBEBGDBGDBCDECBFHEEEBCGBDDFDECHEHBFCAFADGADAHFCFFGFAGFEGEHGADDHDCHDBDDGEDBHABGGBEGBAHBHBDCFDCACCGEAACCACGAEGBEFBAFCCFGBAG,False +915,6.0,10.0,1.0,9.0,16.0,12.0,5.0,11.0,BFGFHGADDEEEEBEEHEHHEHFEBEGHFDHFBHFBDFDFFEBGDHCEBEEBEAGDADHAFAAFHBBEDF,True +916,19.0,25.0,17.0,15.0,26.0,25.0,27.0,16.0,EBBHBCGEEAEBCECGECHHCGDCECGECDBCDBAGCHGBFDBDBCEBFAAGAAHBGDFGAEGAEHEEHECGFFAFBEEAEEABEHBGHBFHDGCCFEFFCFFGFDHBAHAGFDGFDGHGGEDGEBGHGFFECBAFBHGEFBFGDFHDAADGGBAGBFCBFDEFAFBABE,False +917,1.0,1.0,0.0,2.0,5.0,1.0,1.0,0.0,DABDEEEEGFE,True +918,3.0,4.0,4.0,5.0,6.0,2.0,1.0,2.0,FCHDCBDCDEADEBDEBFBGACAEHEE,True +919,29.0,30.0,27.0,23.0,18.0,16.0,15.0,25.0,CECCDDBFGBEHCFACFCCAAAAABGDBDCBDABFBCEACABCGBHGDCGFBGHCDHCEHCBAFBFGHFHHDHFEHFEHCDBDDACBACGACGACFEDEBDHBDHAAEEGFBHHBHDAHBGBCGDAAHAFEBCCBDBEEAHEHFGHAHAABBABDHBDADDAECGBCEDCDCGEHAEHABBFF,False +920,6.0,8.0,6.0,2.0,10.0,1.0,2.0,2.0,ABABBFGBDGEECCEACECHEHBEABDBEEEACEACB,True +921,9.0,6.0,2.0,9.0,10.0,5.0,13.0,15.0,EBEDHGAHGFHGFBDEDDGCDGDHFAEABEGEGAHGAFEAGHAHHEHDEHDABDBGEGGBGHHACHFHH,True +922,0.0,4.0,4.0,4.0,5.0,3.0,8.0,5.0,BFCBHEBHDBCDFGGEGFEGEHGHCDHGDGGEC,False +923,9.0,18.0,18.0,28.0,20.0,33.0,20.0,19.0,FCFHEFDEBCBBCFACFDCDCAFCAHBDHBFGFHAFEAFEHGCHGDHCDHCFCGDCHBEGFFGDFGBHGDFGDFGFAHDBGGHHABEDFFDFFDFFEBFHDCEDFEFHEHHDGACFFGHBBHBADDDDCDEGDGGCEFCDBEBGEDEEBCEFGFFBEDGEDBFDE,False +924,2.0,5.0,0.0,7.0,6.0,1.0,0.0,3.0,EEDEEHEBAEBDDDADBHDFHBBD,True +925,12.0,20.0,17.0,18.0,18.0,15.0,13.0,21.0,GHHFHBACCFFHHFHHABHGDHFDEBABDDBCAEHABDEDCGDGDDGCDFFDHEBAEBAEBDCBGCEGBEHBFCEFDBGBFGBHBHHFFEEGECGECGECBHGBHDCHDAFDCFDEAHAHEAHACCEEFBBDCC,False 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+976,27.0,32.0,25.0,20.0,17.0,19.0,24.0,36.0,HCFABFDBGEFGFDCBDCAEBHEDADCADCGBCDACDBBHBBDAHAHHFFGEFHHBBHEFAEDHEHHBHHDAHCACCDDDAHCEECBBHBHHBGDBGBBGHCAHCFHFHGCHGAEGFFBBHCBHAAABACEGCGGCGACFACGHBDCBHCGGEHEBGAFFAEHHDFHDFEGFABDABGBBECBEBGAAFAACGHGHHGDH,False +977,21.0,23.0,33.0,29.0,26.0,21.0,26.0,19.0,BFCBCBEGFEGDEGFEBDACFGCDGADCDDCBBCGCDDCGCCGDDGBFBEEBAABAACFCCFHDDHDEBDEFCEBBGBEEDAEAHFCHFHHEBEEFFEFHEADEGEGGCGGADDFBCADDDCCGCCGCDGEDFADGDFGFFBCAAHAHEFHECAGFGDCEDCADBAHHHHEHHEFHBCCCCBBAABCAHHDGBEGCGG,False +978,7.0,8.0,10.0,5.0,10.0,5.0,5.0,1.0,DECDEBFCGFADFEBAECABABEGGECDFCGBEGCEHCBDCBCABCAEAFE,True +979,1.0,2.0,1.0,6.0,0.0,1.0,0.0,1.0,DCADFBDHDDBD,True +980,24.0,21.0,18.0,12.0,17.0,7.0,12.0,18.0,BBAHBHDDHBHFAHACBEBBCBAEEACHAHHEGBBGBCDCCAECAHCAGGAFFACFAHHEEAEHFGCACEACHFCHDDEDDEDDCBCCHEBHBAHEABBGBBADBGBBEAAGAADHEGEGGEGAFDACC,False +981,22.0,33.0,18.0,23.0,27.0,28.0,28.0,13.0,EAEDGBCFBAFBGFDAFAAGHAEBFHFFHFFGACDBDFCDFGDBEBBDHCFBEEGGDAGECGEFABFGBEDAEAHEGDDBEGCDABHBBGBDFBDHBGBBEBBHABAABDCEFGAFGAFBFCEFBGGHAGAFEDGEDCHFHBFGDHCFHCAGFDGCGECFECBECBECECABCAEFBEFEEGDBGDEGDBGD,False +982,22.0,20.0,15.0,16.0,27.0,17.0,27.0,21.0,GDFGHEGBEHCEBCHBEHBAHGCGGEGBBFDEADFFHADHEBHGDACDACDEBEEGEHBEGBEGHEBFAAFGFFGDFGDFABGHFHCEECHDGBDCBFFBGCBDDHDCGBCFAFHGGHEGACHECAEAAHCABAACAHEEDEADEFEGBGGEGAAGEBGFAHHAE,False +983,6.0,5.0,6.0,11.0,8.0,8.0,5.0,7.0,HBFHDFCEABBADECDEGDFCDFHBFEDECCFGHFAHGHHADEADFCDGDDGEBAE,False +984,9.0,13.0,13.0,13.0,32.0,25.0,15.0,18.0,EEAEEGEABEGHGFDADEEFAHHCBFGDCBBCHBCFDCFDCFDEFDEFCHFEFECFEHFHGFHGFHEBBCGECBDHHEEDEFCEGAADEFEHGEDFEHFEDFEGBHHFHGEEGEGAACFABFGFDGBEECEEFHBFHB,False +985,14.0,10.0,10.0,7.0,7.0,11.0,13.0,6.0,FAFAHGABAACAAGAFCDDCGCEFDBGBGACHECAECAEBAHDDFDBFDBFGBAGCHBEHBAGBECFFCEFGGGGGFH,False 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various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/src/main/scala/org/xcit/nback/markov/models/State.scala b/src/main/scala/org/xcit/nback/markov/models/State.scala deleted file mode 100644 index fbbd844..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/State.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * A Single state with a label in Markov chain - * @param label A simple string label, representing the state and node - */ -class State(val label: String) { - - /** - * Keep track of transitions from this state to other states. - */ - val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() -} diff --git a/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/src/main/scala/org/xcit/nback/markov/models/Transition.scala deleted file mode 100644 index bc20a9e..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/Transition.scala +++ /dev/null @@ -1,8 +0,0 @@ -package org.xcit.nback.markov.models - -/** - * A Single transition in Markov chain graph. It is stored in "from" node. - * @param to the ending node of the edge - * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). - */ -case class Transition(to: State, probability: Double = 0.0) diff --git a/src/test/scala/ThreeBackBenchmark.scala b/src/test/scala/ThreeBackBenchmark.scala deleted file mode 100644 index 0c7dad9..0000000 --- a/src/test/scala/ThreeBackBenchmark.scala +++ /dev/null @@ -1,7 +0,0 @@ - -/** - * TODO Benchmark 3-back simple sequence generator - */ -class ThreeBackBenchmark { - -} diff --git a/tests/benchmark_diagrams.py b/tests/benchmark_diagrams.py new file mode 100644 index 0000000..8fa448e --- /dev/null +++ b/tests/benchmark_diagrams.py @@ -0,0 +1,159 @@ +import pandas as pd +import numpy as np +from matplotlib import pyplot as plt + +import benchmarks.common as common + + +def tlratio(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2,ignore_index=True) + stats = [] + for trials in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == trials) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == trials) + targets2 = data[alg2].targets if alg2.shape[0] > 0 else np.nan + targets4 = data[alg4].targets if alg4.shape[0] > 0 else np.nan + lures2 = data[alg2].lures if alg2.shape[0] > 0 else np.nan + lures4 = data[alg4].lures if alg4.shape[0] > 0 else np.nan + stats.append([trials, (targets2/lures2).mean(), (targets4/lures4).mean()]) + stats = pd.DataFrame(stats, columns=['trials', 'tl2', 'tl4']) #.dropna(subset=['skewness']) + + plt.style.use('ggplot') + + plt.ylim(bottom=0, top=30) + plt.scatter(stats.trials, stats.tl2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl2[idx], 1)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.tl4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl4[idx], 2)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('T:L Ratio') + plt.ylabel('T:L Ratio') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_tlratio.png', bbox_inches='tight') + plt.show() + + +def time_per_trial(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for t in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == t) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == t) + time2 = data[alg2].time.mean() * 1000 if alg2.shape[0] > 0 else np.nan + time4 = data[alg4].time.mean() * 1000 if alg4.shape[0] > 0 else np.nan + stats.append([t, time2, time4]) + stats = pd.DataFrame(stats, columns=['trials', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.trials, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time2[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time4[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2v4_time_trials.png', bbox_inches='tight') + plt.show() + +def time_profiles(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 8): + alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + time2 = data[alg2].time.mean() * 1000 + time4 = data[alg4].time.mean() * 1000 + stats.append([ni, time2, time4]) + stats = pd.DataFrame(stats, columns=['n', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.n, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.time2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + plt.scatter(stats.n, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.time4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_time_n.png', bbox_inches='tight') + plt.show() + +def skewness(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 9): + all_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + skewed_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) & data.skewed + all_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + skewed_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) & data.skewed + num_of_sequences2 = data[all_alg2].shape[0] + skewed_sequences2 = data[skewed_alg2].shape[0] + num_of_sequences4 = data[all_alg4].shape[0] + skewed_sequences4 = data[skewed_alg4].shape[0] + skewness2 = skewed_sequences2 * 100.0 / num_of_sequences2 if (num_of_sequences2>0) else 0 + skewness4 = skewed_sequences4 * 100.0 / num_of_sequences4 if (num_of_sequences4>0) else 0 + stats.append([ni, skewness2, skewness4]) + stats = pd.DataFrame(stats, columns=['n', 'skewness2', 'skewness4']) #.dropna(subset=['skewness']) + + + plt.style.use('ggplot') + plt.scatter(stats.n, stats.skewness2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.skewness2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + + plt.scatter(stats.n, stats.skewness4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.skewness4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Skewness') + plt.ylabel('Skewed Blocks (%)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_skewness.png', bbox_inches='tight') + plt.show() + +if __name__ == "__main__": + tlratio() + skewness() + time_profiles() + time_per_trial() diff --git a/tests/benchmark_skewness.py b/tests/benchmark_skewness.py new file mode 100644 index 0000000..f468b4d --- /dev/null +++ b/tests/benchmark_skewness.py @@ -0,0 +1,97 @@ +import random +import heapq +import csv + +# Common parameters +alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'] +trials_range = (10, 40) +n = 3 +sample_size = 100 + + +def to_benchmark_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [str(ralph_skewed)] + +def benchmark_nb_gm_001(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_001') + + +def benchmark_nb_gm_002(filename): + import generators.nb_gm_002 as nb_gm_002 + + generator = nb_gm_002.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + # print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_002') + + +def benchmark_nb_gm_003(filename): + import generators.nb_gm_003 as nb_gm_003 + + generator = nb_gm_003.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + print(f"sequence {i}/{sample_size}: {trials} trials") + seq = generator.generate(trials) + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_003') + + +def show_skweness_diagram(filename, choices, title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + print(filename) + data = pd.read_csv(filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) #.dropna(subset=['skewness']) + #print(stats.trials) + #plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'{title}.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + benchmark_nb_gm_003('../benchmarks/nb_gm_003_2back.csv') diff --git a/tests/common.py b/tests/common.py new file mode 100644 index 0000000..e40c0df --- /dev/null +++ b/tests/common.py @@ -0,0 +1,27 @@ + + +# Common benchmark parameters +choices = alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F'] +trials_range = (10, 65) +n = 4 +sample_size = 100 + + +def count_targets_and_lures(seq, n): + mask = 'D'*n + for index in range(n, len(seq)): + if seq[index] == seq[index - n]: + mask += 'T' + elif seq[index] in seq[index - n - 1:index - n + 1]: + mask += 'L' + else: + mask += 'D' + return mask.count('T'), mask.count('L') + + +def skewness(seq, choices): + import heapq + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return ralph_skewed diff --git a/tests/nb_gm_001_bm.py b/tests/nb_gm_001_bm.py new file mode 100644 index 0000000..54f6cb3 --- /dev/null +++ b/tests/nb_gm_001_bm.py @@ -0,0 +1,75 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq) , str(ralph_skewed)] + + +def benchmark(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets / s.trials, axis=1) + plt.scatter(data.trials, data.targets_ratio, alpha=0.2) + plt.show() + +if __name__ == '__main__': + alg = 'nb_gm_001' + fn = f'results/{alg}_{n}back.csv' + benchmark(fn) + # skewness_diagram(fn, alg) + targets_ratio_diagram(fn, alg) diff --git a/tests/nb_gm_002_bm.py b/tests/nb_gm_002_bm.py new file mode 100644 index 0000000..c8af543 --- /dev/null +++ b/tests/nb_gm_002_bm.py @@ -0,0 +1,105 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq), str(ralph_skewed)] + + +def benchmark(filename): + from generators.nb_gm_002 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials, int(trials/3), 0, 0) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +import time +import numpy as np +import pandas as pd + +import benchmarks.common as common + +def profile(): + from generators.nb_gm_002 import SequenceGenerator + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, int(lures/2), int(lures/2)) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('benchmarks/results/nb_gm_002_profile.csv', sep=',', encoding='utf-8') + +if __name__ == '__main__': + alg = 'nb_gm_002' + fn = f'results/{alg}_{n}back.csv' + profile() diff --git a/tests/nb_gm_003_bm.py b/tests/nb_gm_003_bm.py new file mode 100644 index 0000000..fa6c19a --- /dev/null +++ b/tests/nb_gm_003_bm.py @@ -0,0 +1,114 @@ +import heapq +import csv +import random +import time + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq, time_per_block): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [time_per_block, ''.join(seq), str(ralph_skewed)] + + +def benchmark_skewness(filename): + from generators.nb_gm_003 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['time_per_block', 'seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + targets = trials / 3 + t = time.time() + seq = generator.generate(trials, targets) + t = time.time() - t + print(f"sequence {i}/{sample_size}: {trials} trials, took {t}s.") + writer.writerow(to_csv_row(i, seq, t)) + plot_skewness(fn, 'nb_gm_003') + + +def plot_skewness(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def plot_targets_ratio(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +def benchmark_targets_ratio(): + pass + +def benchmark_chunking(): + pass + + +def benchmark_n(): + pass + + +def plot_timing(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['time_per_trial'] = data.apply(lambda s: s.time_per_block / s.trials, axis=1) + plt.style.use('ggplot') + plt.title(f"{figure_title} - average time to generate a trial") + plt.ylabel('time (s)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.time_per_trial, alpha=0.5) + + # draw fitted curve + # import numpy as np + # p = np.poly1d(np.polyfit(data.trials, data.time_per_trial, 3)) + # plt.plot(data.trials, p(data.trials), color='red') + + plt.savefig(f'results/{figure_title}_timing.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + alg = 'nb_gm_003' + fn = f'results/{alg}_{n}back.csv' + benchmark_skewness(fn) diff --git a/tests/nb_gm_004_bm.py b/tests/nb_gm_004_bm.py new file mode 100644 index 0000000..b4ad4a8 --- /dev/null +++ b/tests/nb_gm_004_bm.py @@ -0,0 +1,26 @@ +import time +import numpy as np +import pandas as pd + +import tests.common as common +from generators.nb_gm_004 import SequenceGenerator + +def run(): + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, lures) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('tests/results/nb_gm_004_profile.csv', sep=',', encoding='utf-8') diff --git a/tests/results/2v4_time_trials.png b/tests/results/2v4_time_trials.png new file mode 100644 index 0000000..9be91b4 --- /dev/null +++ b/tests/results/2v4_time_trials.png Binary files differ diff --git a/tests/results/2vs4_skewness.png b/tests/results/2vs4_skewness.png new file mode 100644 index 0000000..a488e1f --- /dev/null +++ b/tests/results/2vs4_skewness.png Binary files differ diff --git a/tests/results/2vs4_time_n.png b/tests/results/2vs4_time_n.png new file mode 100644 index 0000000..d022ed0 --- /dev/null +++ b/tests/results/2vs4_time_n.png Binary files differ diff --git a/tests/results/2vs4_tlratio.png b/tests/results/2vs4_tlratio.png new file mode 100644 index 0000000..b76f296 --- /dev/null +++ b/tests/results/2vs4_tlratio.png Binary files differ diff --git a/tests/results/nb_gm_001_2back.csv b/tests/results/nb_gm_001_2back.csv new file mode 100644 index 0000000..f6ad25e --- /dev/null +++ b/tests/results/nb_gm_001_2back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,0.0,1.0,0.0,55.0,56.0,0.0,0.0,0.0,BEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True 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+364,0.0,0.0,0.0,1.0,0.0,31.0,0.0,31.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +365,0.0,0.0,0.0,24.0,0.0,23.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +366,0.0,15.0,0.0,0.0,16.0,0.0,0.0,0.0,EEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +367,22.0,0.0,0.0,0.0,0.0,0.0,1.0,22.0,GHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +368,0.0,25.0,0.0,0.0,0.0,0.0,25.0,0.0,BGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +369,0.0,0.0,0.0,100.0,1.0,0.0,0.0,0.0,EDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +370,0.0,17.0,0.0,17.0,1.0,0.0,0.0,0.0,EBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +371,0.0,1.0,49.0,0.0,49.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True 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+377,27.0,0.0,0.0,29.0,0.0,0.0,0.0,0.0,DDADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +378,81.0,0.0,0.0,81.0,0.0,0.0,0.0,1.0,HADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +379,1.0,0.0,9.0,0.0,8.0,0.0,0.0,0.0,ACECECECECECECECEC,True +380,1.0,0.0,0.0,32.0,33.0,0.0,0.0,0.0,AEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +381,5.0,0.0,5.0,0.0,1.0,0.0,0.0,0.0,ECACACACACA,True +382,0.0,0.0,0.0,96.0,0.0,0.0,98.0,0.0,GGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +383,0.0,86.0,0.0,0.0,0.0,85.0,0.0,0.0,BBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +384,0.0,0.0,28.0,0.0,1.0,0.0,0.0,28.0,ECHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +385,0.0,1.0,119.0,0.0,0.0,0.0,0.0,0.0,BCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +386,0.0,0.0,93.0,0.0,0.0,93.0,1.0,0.0,GCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCF,True +387,92.0,0.0,1.0,0.0,92.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +388,0.0,186.0,0.0,0.0,0.0,0.0,0.0,0.0,BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +389,1.0,74.0,0.0,0.0,0.0,0.0,0.0,0.0,ABBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +390,0.0,0.0,0.0,0.0,1.0,86.0,0.0,87.0,EHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +391,61.0,0.0,0.0,61.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +392,0.0,0.0,0.0,1.0,16.0,0.0,0.0,15.0,DEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +393,118.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +394,0.0,0.0,0.0,0.0,0.0,75.0,0.0,1.0,HFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +395,30.0,0.0,0.0,0.0,0.0,0.0,0.0,30.0,AHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +396,65.0,0.0,0.0,0.0,0.0,1.0,0.0,65.0,FAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +397,0.0,0.0,0.0,55.0,56.0,0.0,0.0,0.0,EEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +398,26.0,0.0,0.0,25.0,1.0,0.0,0.0,0.0,EADADADADADADADADADADADADADADADADADADADADADADADADADA,True +399,0.0,0.0,60.0,0.0,0.0,0.0,1.0,59.0,GCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +400,1.0,0.0,0.0,0.0,160.0,0.0,0.0,0.0,AEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +401,1.0,0.0,31.0,0.0,0.0,31.0,0.0,0.0,AFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +402,0.0,0.0,0.0,15.0,1.0,0.0,0.0,0.0,EDDDDDDDDDDDDDDD,True +403,0.0,0.0,0.0,54.0,55.0,0.0,0.0,1.0,HEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +404,0.0,0.0,0.0,27.0,0.0,27.0,0.0,1.0,HFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +405,0.0,0.0,0.0,1.0,0.0,15.0,0.0,15.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +406,0.0,95.0,0.0,94.0,0.0,1.0,0.0,0.0,FBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +407,0.0,0.0,15.0,14.0,0.0,0.0,0.0,0.0,CCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +408,78.0,78.0,0.0,0.0,0.0,0.0,1.0,0.0,GBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +409,0.0,0.0,72.0,1.0,0.0,0.0,72.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +410,55.0,0.0,1.0,0.0,0.0,0.0,55.0,0.0,CAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +411,0.0,59.0,0.0,0.0,0.0,60.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +412,61.0,0.0,0.0,61.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +413,0.0,1.0,0.0,75.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +414,0.0,53.0,0.0,0.0,0.0,0.0,52.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +415,0.0,0.0,16.0,0.0,1.0,0.0,0.0,15.0,ECHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +416,0.0,0.0,0.0,39.0,0.0,0.0,0.0,38.0,DHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +417,96.0,0.0,1.0,95.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +418,28.0,0.0,1.0,27.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +419,0.0,1.0,92.0,92.0,0.0,0.0,0.0,0.0,BCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +420,1.0,0.0,20.0,0.0,20.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECE,True +421,0.0,90.0,0.0,0.0,0.0,0.0,89.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +422,10.0,0.0,0.0,0.0,0.0,1.0,11.0,0.0,FGAGAGAGAGAGAGAGAGAGAG,True +423,0.0,0.0,0.0,74.0,73.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +424,0.0,0.0,127.0,0.0,0.0,0.0,1.0,0.0,GCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +425,1.0,9.0,0.0,0.0,0.0,9.0,0.0,0.0,AFBFBFBFBFBFBFBFBFB,True +426,0.0,0.0,84.0,0.0,0.0,0.0,0.0,84.0,HCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +427,33.0,0.0,0.0,34.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +428,1.0,30.0,0.0,30.0,0.0,0.0,0.0,0.0,ABDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +429,0.0,0.0,67.0,0.0,1.0,67.0,0.0,0.0,EFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +430,62.0,0.0,0.0,63.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +431,1.0,9.0,9.0,0.0,0.0,0.0,0.0,0.0,ABCBCBCBCBCBCBCBCBC,True +432,15.0,0.0,0.0,0.0,0.0,0.0,14.0,0.0,AAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +433,0.0,1.0,0.0,65.0,66.0,0.0,0.0,0.0,BEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +434,0.0,160.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +435,0.0,0.0,1.0,0.0,42.0,42.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +436,0.0,0.0,55.0,0.0,55.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +437,0.0,0.0,0.0,1.0,0.0,73.0,0.0,73.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +438,79.0,0.0,0.0,0.0,78.0,0.0,0.0,0.0,AAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +439,0.0,0.0,67.0,0.0,0.0,0.0,66.0,1.0,HCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +440,0.0,0.0,77.0,0.0,0.0,1.0,0.0,76.0,FCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +441,0.0,0.0,0.0,0.0,153.0,0.0,0.0,1.0,HEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +442,0.0,88.0,88.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +443,0.0,0.0,0.0,20.0,22.0,0.0,0.0,0.0,EEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +444,41.0,0.0,42.0,0.0,0.0,0.0,1.0,0.0,GCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +445,0.0,0.0,0.0,47.0,0.0,46.0,0.0,1.0,HDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +446,1.0,0.0,0.0,0.0,86.0,0.0,0.0,87.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +447,56.0,56.0,0.0,0.0,0.0,0.0,0.0,1.0,HABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +448,0.0,0.0,0.0,0.0,11.0,0.0,0.0,10.0,EEHEHEHEHEHEHEHEHEHEH,True +449,0.0,0.0,0.0,0.0,0.0,1.0,92.0,92.0,FGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +450,0.0,0.0,0.0,6.0,5.0,1.0,0.0,0.0,FDEDEDEDEDED,True +451,66.0,1.0,67.0,0.0,0.0,0.0,0.0,0.0,BCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +452,0.0,0.0,0.0,13.0,0.0,1.0,12.0,0.0,FDGDGDGDGDGDGDGDGDGDGDGDGD,True +453,1.0,0.0,0.0,0.0,56.0,0.0,56.0,0.0,AEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +454,15.0,0.0,0.0,0.0,0.0,0.0,0.0,16.0,HAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +455,0.0,21.0,1.0,0.0,21.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True +456,93.0,0.0,1.0,0.0,92.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +457,1.0,0.0,0.0,0.0,35.0,0.0,0.0,35.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +458,13.0,0.0,0.0,0.0,1.0,0.0,13.0,0.0,EAGAGAGAGAGAGAGAGAGAGAGAGAG,True +459,0.0,0.0,65.0,0.0,1.0,0.0,65.0,0.0,ECGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +460,0.0,0.0,95.0,1.0,0.0,95.0,0.0,0.0,DFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +461,15.0,0.0,0.0,0.0,1.0,0.0,0.0,15.0,EHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +462,0.0,0.0,198.0,0.0,1.0,0.0,0.0,0.0,ECCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +463,84.0,84.0,0.0,0.0,1.0,0.0,0.0,0.0,EABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +464,0.0,0.0,0.0,0.0,0.0,60.0,0.0,61.0,HFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +465,0.0,179.0,0.0,1.0,0.0,0.0,0.0,0.0,DBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +466,1.0,0.0,90.0,0.0,89.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +467,0.0,35.0,0.0,0.0,0.0,34.0,0.0,0.0,BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +468,0.0,0.0,0.0,1.0,7.0,0.0,0.0,7.0,DHEHEHEHEHEHEHE,True +469,0.0,0.0,0.0,0.0,92.0,0.0,91.0,0.0,EEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +470,0.0,0.0,46.0,0.0,0.0,1.0,46.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +471,0.0,0.0,0.0,0.0,0.0,1.0,158.0,0.0,FGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +472,1.0,0.0,0.0,0.0,0.0,58.0,0.0,59.0,AHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +473,0.0,0.0,6.0,1.0,0.0,0.0,6.0,0.0,DCGCGCGCGCGCG,True +474,0.0,0.0,0.0,0.0,0.0,98.0,0.0,97.0,FFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +475,0.0,87.0,0.0,0.0,0.0,0.0,0.0,85.0,BBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +476,0.0,0.0,33.0,0.0,0.0,0.0,1.0,33.0,GHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +477,45.0,0.0,0.0,0.0,46.0,0.0,0.0,0.0,EAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +478,0.0,0.0,0.0,77.0,0.0,0.0,75.0,0.0,DDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +479,73.0,1.0,73.0,0.0,0.0,0.0,0.0,0.0,BACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +480,0.0,1.0,0.0,0.0,37.0,37.0,0.0,0.0,BEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +481,0.0,92.0,93.0,0.0,0.0,1.0,0.0,0.0,FCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +482,0.0,0.0,0.0,1.0,0.0,0.0,0.0,24.0,DHHHHHHHHHHHHHHHHHHHHHHHH,True +483,25.0,0.0,0.0,1.0,0.0,25.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +484,0.0,0.0,0.0,0.0,0.0,37.0,0.0,36.0,FHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +485,21.0,0.0,0.0,1.0,0.0,20.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +486,0.0,35.0,0.0,36.0,0.0,0.0,0.0,1.0,HDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +487,0.0,0.0,1.0,0.0,97.0,98.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +488,0.0,93.0,0.0,0.0,0.0,1.0,0.0,94.0,FHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +489,0.0,1.0,0.0,93.0,0.0,0.0,93.0,0.0,BGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +490,0.0,0.0,0.0,70.0,0.0,0.0,72.0,0.0,GGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +491,86.0,0.0,0.0,0.0,1.0,86.0,0.0,0.0,EFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +492,0.0,65.0,1.0,0.0,0.0,65.0,0.0,0.0,CBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +493,0.0,0.0,0.0,69.0,0.0,0.0,0.0,1.0,HDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +494,0.0,0.0,144.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +495,0.0,45.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +496,0.0,0.0,0.0,28.0,0.0,27.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +497,0.0,72.0,0.0,0.0,0.0,1.0,73.0,0.0,FGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +498,0.0,0.0,41.0,0.0,1.0,0.0,40.0,0.0,ECGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +499,0.0,1.0,0.0,0.0,0.0,131.0,0.0,0.0,BFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +500,17.0,0.0,0.0,1.0,0.0,17.0,0.0,0.0,DFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +501,19.0,0.0,0.0,19.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADA,True +502,1.0,0.0,0.0,0.0,51.0,0.0,52.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +503,1.0,0.0,0.0,0.0,0.0,0.0,29.0,29.0,AGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +504,36.0,0.0,0.0,1.0,0.0,35.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +505,0.0,0.0,0.0,20.0,0.0,0.0,1.0,20.0,GDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +506,0.0,0.0,0.0,163.0,0.0,0.0,0.0,1.0,HDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +507,22.0,23.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABAB,True +508,0.0,1.0,0.0,0.0,0.0,0.0,41.0,42.0,BHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +509,0.0,0.0,0.0,45.0,1.0,0.0,0.0,44.0,EDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True 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+671,99.0,0.0,1.0,0.0,98.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +672,68.0,0.0,0.0,0.0,0.0,0.0,67.0,1.0,HAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGA,True +673,0.0,0.0,0.0,26.0,27.0,0.0,1.0,0.0,GEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +674,31.0,0.0,0.0,0.0,32.0,0.0,0.0,1.0,HEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +675,0.0,0.0,0.0,0.0,42.0,0.0,41.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +676,0.0,0.0,50.0,0.0,0.0,0.0,1.0,50.0,GCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +677,0.0,25.0,0.0,24.0,0.0,0.0,0.0,0.0,BBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +678,0.0,0.0,0.0,0.0,1.0,10.0,9.0,0.0,EFGFGFGFGFGFGFGFGFGF,True +679,65.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,DAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +680,0.0,23.0,0.0,0.0,0.0,0.0,23.0,1.0,HGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +681,0.0,1.0,58.0,0.0,0.0,0.0,57.0,0.0,BCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +682,0.0,0.0,0.0,0.0,0.0,68.0,1.0,68.0,GFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +683,0.0,0.0,0.0,0.0,96.0,0.0,96.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +684,1.0,0.0,0.0,0.0,66.0,0.0,66.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +685,0.0,0.0,0.0,0.0,0.0,1.0,0.0,21.0,FHHHHHHHHHHHHHHHHHHHHH,True +686,0.0,88.0,0.0,87.0,0.0,0.0,0.0,0.0,BDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +687,0.0,0.0,19.0,19.0,0.0,0.0,1.0,0.0,GDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +688,0.0,42.0,1.0,0.0,41.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +689,0.0,0.0,0.0,0.0,0.0,60.0,61.0,0.0,GGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +690,0.0,23.0,23.0,0.0,0.0,0.0,1.0,0.0,GBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +691,86.0,86.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +692,35.0,35.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +693,57.0,0.0,0.0,0.0,0.0,58.0,1.0,0.0,GFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +694,0.0,0.0,30.0,30.0,1.0,0.0,0.0,0.0,EDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +695,19.0,18.0,0.0,1.0,0.0,0.0,0.0,0.0,DABABABABABABABABABABABABABABABABABABA,True +696,0.0,0.0,0.0,1.0,0.0,56.0,0.0,57.0,DHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +697,10.0,0.0,1.0,0.0,0.0,0.0,0.0,11.0,CHAHAHAHAHAHAHAHAHAHAH,True +698,0.0,0.0,89.0,0.0,88.0,0.0,1.0,0.0,GCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +699,0.0,0.0,87.0,0.0,86.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +700,17.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAA,True +701,0.0,0.0,66.0,65.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +702,0.0,0.0,1.0,0.0,0.0,0.0,123.0,0.0,CGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +703,0.0,118.0,0.0,0.0,1.0,0.0,0.0,0.0,EBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +704,0.0,0.0,0.0,0.0,0.0,0.0,0.0,132.0,HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +705,0.0,0.0,0.0,0.0,0.0,23.0,1.0,23.0,GHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +706,0.0,0.0,0.0,0.0,6.0,5.0,0.0,0.0,EFEFEFEFEFE,True +707,18.0,0.0,0.0,16.0,0.0,0.0,0.0,0.0,AADADADADADADADADADADADADADADADADA,True +708,0.0,72.0,0.0,0.0,0.0,71.0,0.0,1.0,HBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +709,0.0,0.0,54.0,0.0,0.0,1.0,0.0,55.0,FHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +710,0.0,1.0,87.0,0.0,87.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +711,0.0,0.0,1.0,63.0,0.0,0.0,0.0,64.0,CHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +712,78.0,0.0,78.0,0.0,0.0,1.0,0.0,0.0,FCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +713,0.0,80.0,0.0,0.0,0.0,81.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +714,0.0,1.0,0.0,0.0,0.0,0.0,40.0,39.0,BGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +715,0.0,0.0,7.0,0.0,6.0,0.0,0.0,0.0,CCECECECECECE,True +716,35.0,0.0,0.0,0.0,0.0,0.0,0.0,33.0,AAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +717,0.0,0.0,0.0,1.0,73.0,0.0,0.0,72.0,DEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +718,0.0,0.0,90.0,0.0,0.0,1.0,89.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +719,1.0,0.0,0.0,67.0,0.0,0.0,0.0,66.0,ADHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +720,56.0,0.0,0.0,0.0,56.0,0.0,1.0,0.0,GAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +721,0.0,0.0,0.0,1.0,0.0,0.0,49.0,49.0,DHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +722,0.0,0.0,0.0,117.0,0.0,1.0,0.0,0.0,FDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +723,0.0,0.0,86.0,1.0,0.0,0.0,85.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +724,0.0,0.0,31.0,0.0,0.0,0.0,0.0,30.0,CCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +725,1.0,0.0,0.0,0.0,98.0,0.0,98.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +726,1.0,84.0,84.0,0.0,0.0,0.0,0.0,0.0,ACBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +727,0.0,56.0,56.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +728,0.0,1.0,0.0,24.0,24.0,0.0,0.0,0.0,BDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +729,37.0,0.0,0.0,0.0,0.0,37.0,0.0,0.0,FAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +730,0.0,0.0,91.0,0.0,0.0,0.0,91.0,0.0,GCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +731,98.0,0.0,99.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +732,0.0,0.0,0.0,0.0,99.0,1.0,98.0,0.0,FEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +733,0.0,0.0,30.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +734,12.0,1.0,13.0,0.0,0.0,0.0,0.0,0.0,BCACACACACACACACACACACACAC,True +735,0.0,93.0,1.0,0.0,93.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True 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+852,0.0,1.0,0.0,0.0,136.0,0.0,0.0,0.0,BEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +853,0.0,0.0,0.0,0.0,1.0,0.0,0.0,163.0,EHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +854,74.0,0.0,75.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +855,0.0,0.0,0.0,19.0,0.0,0.0,17.0,0.0,DDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +856,0.0,73.0,0.0,1.0,0.0,0.0,74.0,0.0,DGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True 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+863,0.0,0.0,0.0,32.0,1.0,0.0,32.0,0.0,EGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +864,0.0,0.0,15.0,0.0,1.0,14.0,0.0,0.0,ECFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +865,0.0,1.0,98.0,0.0,0.0,0.0,98.0,0.0,BGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +866,1.0,0.0,0.0,0.0,19.0,0.0,0.0,0.0,AEEEEEEEEEEEEEEEEEEE,True +867,24.0,0.0,0.0,0.0,24.0,0.0,0.0,0.0,AEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +868,0.0,0.0,0.0,74.0,0.0,0.0,0.0,73.0,DHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +869,0.0,78.0,1.0,0.0,0.0,0.0,77.0,0.0,CBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +870,0.0,0.0,1.0,0.0,50.0,0.0,51.0,0.0,CGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +871,0.0,0.0,16.0,0.0,0.0,16.0,0.0,1.0,HFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +872,0.0,0.0,0.0,1.0,28.0,28.0,0.0,0.0,DFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +873,0.0,0.0,65.0,65.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +874,0.0,34.0,0.0,0.0,0.0,35.0,0.0,0.0,FBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +875,0.0,0.0,9.0,0.0,8.0,0.0,0.0,1.0,HCECECECECECECECEC,True +876,0.0,0.0,0.0,0.0,94.0,0.0,94.0,1.0,HEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +877,0.0,18.0,0.0,16.0,0.0,0.0,0.0,0.0,BBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True 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+885,0.0,0.0,0.0,93.0,0.0,93.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDF,True +886,0.0,1.0,0.0,89.0,0.0,89.0,0.0,0.0,BFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +887,0.0,1.0,0.0,0.0,42.0,0.0,0.0,42.0,BHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +888,68.0,0.0,0.0,0.0,1.0,0.0,0.0,67.0,EAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +889,55.0,0.0,0.0,0.0,0.0,57.0,0.0,0.0,FFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +890,25.0,1.0,0.0,0.0,0.0,0.0,26.0,0.0,BGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +891,81.0,0.0,0.0,0.0,80.0,0.0,0.0,0.0,AAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +892,0.0,0.0,1.0,0.0,10.0,0.0,10.0,0.0,CGEGEGEGEGEGEGEGEGEGE,True +893,1.0,0.0,43.0,42.0,0.0,0.0,0.0,0.0,ACDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +894,55.0,54.0,0.0,0.0,0.0,0.0,0.0,0.0,AABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +895,43.0,0.0,0.0,0.0,0.0,1.0,0.0,43.0,FAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +896,1.0,0.0,0.0,0.0,97.0,97.0,0.0,0.0,AEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +897,0.0,25.0,0.0,1.0,0.0,25.0,0.0,0.0,DFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +898,0.0,0.0,0.0,0.0,26.0,26.0,1.0,0.0,GEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +899,0.0,0.0,36.0,0.0,36.0,0.0,0.0,0.0,ECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +900,0.0,0.0,0.0,0.0,1.0,0.0,89.0,88.0,EGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +901,0.0,1.0,142.0,0.0,0.0,0.0,0.0,0.0,BCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +902,1.0,83.0,0.0,83.0,0.0,0.0,0.0,0.0,ABDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +903,0.0,0.0,17.0,0.0,17.0,0.0,0.0,1.0,HECECECECECECECECECECECECECECECECEC,True +904,77.0,77.0,0.0,0.0,0.0,0.0,0.0,0.0,BABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +905,0.0,0.0,0.0,0.0,0.0,0.0,164.0,0.0,GGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +906,0.0,0.0,0.0,89.0,0.0,1.0,0.0,90.0,FHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +907,0.0,0.0,41.0,0.0,0.0,0.0,42.0,0.0,GCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +908,28.0,0.0,0.0,0.0,0.0,28.0,1.0,0.0,GAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +909,0.0,0.0,94.0,0.0,1.0,0.0,95.0,0.0,EGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +910,0.0,0.0,27.0,1.0,27.0,0.0,0.0,0.0,DECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +911,0.0,0.0,0.0,100.0,0.0,1.0,0.0,0.0,FDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +912,0.0,1.0,66.0,0.0,0.0,0.0,66.0,0.0,BGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +913,0.0,23.0,23.0,0.0,0.0,1.0,0.0,0.0,FCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +914,0.0,0.0,0.0,0.0,0.0,0.0,150.0,0.0,GGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +915,0.0,0.0,0.0,0.0,0.0,0.0,1.0,42.0,GHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +916,0.0,147.0,0.0,0.0,0.0,0.0,1.0,0.0,GBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +917,0.0,56.0,0.0,1.0,0.0,0.0,0.0,56.0,DHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +918,0.0,0.0,0.0,0.0,0.0,76.0,76.0,1.0,HFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFG,True +919,0.0,53.0,0.0,0.0,0.0,0.0,0.0,52.0,BHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +920,0.0,0.0,147.0,0.0,0.0,1.0,0.0,0.0,FCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +921,0.0,0.0,0.0,40.0,40.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +922,0.0,82.0,0.0,84.0,0.0,0.0,0.0,0.0,DDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +923,1.0,0.0,0.0,0.0,0.0,0.0,0.0,97.0,AHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +924,0.0,29.0,0.0,0.0,0.0,0.0,0.0,30.0,HHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +925,25.0,0.0,0.0,1.0,0.0,0.0,0.0,25.0,DHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +926,0.0,164.0,0.0,0.0,0.0,0.0,1.0,0.0,GBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +927,89.0,0.0,0.0,0.0,1.0,0.0,90.0,0.0,EGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +928,0.0,0.0,1.0,0.0,41.0,41.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +929,0.0,0.0,1.0,19.0,18.0,0.0,0.0,0.0,CDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +930,0.0,0.0,0.0,0.0,1.0,75.0,75.0,0.0,EGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +931,0.0,0.0,21.0,0.0,0.0,22.0,0.0,0.0,FCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCF,True +932,0.0,0.0,81.0,0.0,80.0,1.0,0.0,0.0,FCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +933,20.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAAAAA,True +934,0.0,40.0,0.0,0.0,0.0,40.0,0.0,0.0,BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +935,0.0,72.0,0.0,0.0,72.0,0.0,1.0,0.0,GBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True +936,56.0,1.0,0.0,56.0,0.0,0.0,0.0,0.0,BADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +937,0.0,0.0,0.0,0.0,0.0,96.0,1.0,0.0,GFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +938,0.0,1.0,0.0,88.0,0.0,0.0,0.0,88.0,BHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +939,1.0,0.0,0.0,0.0,0.0,0.0,0.0,175.0,AHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +940,0.0,0.0,84.0,1.0,83.0,0.0,0.0,0.0,DCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +941,0.0,0.0,83.0,0.0,0.0,0.0,0.0,85.0,HHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +942,1.0,5.0,5.0,0.0,0.0,0.0,0.0,0.0,ABCBCBCBCBC,True +943,0.0,0.0,0.0,68.0,0.0,0.0,0.0,69.0,HHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +944,29.0,0.0,0.0,0.0,0.0,29.0,1.0,0.0,GAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +945,0.0,0.0,1.0,0.0,0.0,0.0,81.0,82.0,CHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +946,89.0,0.0,89.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +947,0.0,0.0,0.0,78.0,1.0,0.0,0.0,0.0,EDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +948,90.0,1.0,0.0,0.0,0.0,0.0,91.0,0.0,BGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +949,0.0,0.0,0.0,86.0,1.0,0.0,0.0,86.0,EHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +950,0.0,0.0,0.0,42.0,1.0,0.0,42.0,0.0,EDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +951,85.0,0.0,0.0,84.0,1.0,0.0,0.0,0.0,EADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +952,90.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +953,0.0,0.0,1.0,0.0,0.0,90.0,0.0,0.0,CFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +954,62.0,0.0,0.0,1.0,0.0,62.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +955,0.0,20.0,20.0,0.0,1.0,0.0,0.0,0.0,EBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +956,0.0,0.0,37.0,0.0,0.0,1.0,0.0,38.0,FHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +957,98.0,1.0,0.0,0.0,0.0,98.0,0.0,0.0,BFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +958,0.0,1.0,0.0,0.0,189.0,0.0,0.0,0.0,BEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +959,0.0,0.0,0.0,9.0,0.0,1.0,8.0,0.0,FDGDGDGDGDGDGDGDGD,True +960,0.0,68.0,0.0,0.0,0.0,0.0,0.0,69.0,HHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +961,0.0,0.0,0.0,138.0,0.0,0.0,0.0,0.0,DDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +962,0.0,0.0,0.0,0.0,1.0,30.0,0.0,30.0,EHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +963,0.0,0.0,0.0,80.0,80.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +964,77.0,0.0,0.0,1.0,0.0,0.0,0.0,78.0,DHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +965,0.0,0.0,0.0,58.0,58.0,0.0,1.0,0.0,GEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +966,0.0,0.0,0.0,1.0,35.0,34.0,0.0,0.0,DEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +967,0.0,60.0,0.0,60.0,0.0,1.0,0.0,0.0,FDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +968,0.0,1.0,80.0,0.0,81.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +969,0.0,1.0,0.0,0.0,0.0,0.0,81.0,81.0,BGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +970,16.0,0.0,0.0,16.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADA,True +971,0.0,0.0,0.0,0.0,78.0,77.0,0.0,0.0,EFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +972,0.0,0.0,10.0,1.0,0.0,10.0,0.0,0.0,DFCFCFCFCFCFCFCFCFCFC,True +973,0.0,0.0,0.0,0.0,0.0,44.0,1.0,44.0,GHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +974,0.0,36.0,0.0,0.0,0.0,36.0,1.0,0.0,GFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +975,0.0,87.0,0.0,0.0,0.0,0.0,87.0,0.0,BGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +976,42.0,0.0,42.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True 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b/tests/results/nb_gm_001_3back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,0.0,65.0,132.0,0.0,0.0,0.0,0.0,1.0,HCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCC,True +1,51.0,0.0,52.0,52.0,0.0,0.0,0.0,1.0,HCDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACD,True +2,0.0,61.0,0.0,62.0,0.0,0.0,61.0,1.0,HDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGD,True +3,40.0,0.0,0.0,1.0,0.0,0.0,0.0,80.0,DHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHA,True +4,4.0,0.0,1.0,0.0,0.0,6.0,0.0,0.0,CAFFAFFAFFA,True 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+62,0.0,1.0,0.0,0.0,59.0,0.0,60.0,59.0,BGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEG,True +63,0.0,0.0,0.0,0.0,0.0,0.0,1.0,167.0,GHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +64,48.0,0.0,0.0,0.0,1.0,0.0,0.0,95.0,EHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHA,True +65,0.0,0.0,0.0,65.0,66.0,0.0,67.0,0.0,GGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGE,True +66,35.0,71.0,0.0,0.0,0.0,0.0,0.0,0.0,BBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBAB,True +67,50.0,0.0,0.0,50.0,50.0,0.0,0.0,1.0,HAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAED,True +68,0.0,0.0,4.0,0.0,0.0,0.0,5.0,3.0,GCGHCGHCGHCG,True +69,0.0,0.0,5.0,0.0,0.0,0.0,1.0,10.0,GCHHCHHCHHCHHCHH,True +70,0.0,0.0,19.0,0.0,19.0,20.0,0.0,0.0,FECFECFECFECFECFECFECFECFECFECFECFECFECFECFECFECFECFECFECF,True +71,0.0,0.0,1.0,0.0,0.0,0.0,43.0,84.0,CGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHG,True +72,6.0,0.0,0.0,0.0,6.0,6.0,0.0,0.0,FAEFAEFAEFAEFAEFAE,True +73,0.0,0.0,35.0,35.0,35.0,0.0,0.0,1.0,HECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECD,True +74,25.0,0.0,26.0,0.0,1.0,0.0,0.0,25.0,ECAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHC,True +75,61.0,0.0,0.0,60.0,0.0,60.0,0.0,1.0,HAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDA,True +76,0.0,0.0,0.0,41.0,0.0,0.0,0.0,20.0,DHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDD,True +77,0.0,0.0,1.0,0.0,0.0,15.0,15.0,14.0,CGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGF,True +78,6.0,0.0,1.0,6.0,0.0,0.0,0.0,6.0,CHDAHDAHDAHDAHDAHDA,True +79,0.0,124.0,0.0,62.0,0.0,0.0,0.0,0.0,BBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBD,True +80,0.0,0.0,32.0,0.0,0.0,31.0,31.0,0.0,CGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCF,True 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+317,61.0,0.0,0.0,0.0,0.0,61.0,1.0,61.0,GFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHA,True +318,0.0,0.0,0.0,7.0,7.0,8.0,1.0,0.0,GFEDFEDFEDFEDFEDFEDFEDF,True +319,7.0,0.0,0.0,0.0,1.0,3.0,0.0,0.0,EAAFAAFAAFA,True +320,0.0,48.0,0.0,48.0,0.0,0.0,0.0,48.0,BHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHD,True +321,0.0,23.0,23.0,0.0,0.0,0.0,0.0,24.0,HBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCH,True +322,0.0,0.0,1.0,0.0,0.0,30.0,30.0,30.0,CGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFH,True +323,48.0,0.0,0.0,47.0,47.0,0.0,1.0,0.0,GADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEA,True 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+401,0.0,55.0,55.0,0.0,0.0,1.0,54.0,0.0,FCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCB,True +402,47.0,0.0,0.0,0.0,1.0,47.0,0.0,47.0,EAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFH,True +403,56.0,0.0,0.0,0.0,58.0,0.0,0.0,56.0,EEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAE,True +404,0.0,39.0,0.0,0.0,39.0,1.0,40.0,0.0,FGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEG,True 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+951,0.0,0.0,0.0,0.0,35.0,1.0,35.0,35.0,FHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEG,True +952,0.0,0.0,1.0,0.0,0.0,0.0,36.0,71.0,CHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHG,True +953,0.0,42.0,0.0,0.0,21.0,0.0,0.0,1.0,HEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBB,True +954,0.0,49.0,0.0,50.0,0.0,0.0,49.0,0.0,DDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBG,True +955,11.0,0.0,0.0,0.0,22.0,0.0,1.0,0.0,GEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAE,True +956,0.0,0.0,0.0,1.0,0.0,18.0,0.0,38.0,DHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHH,True +957,58.0,58.0,60.0,0.0,0.0,0.0,0.0,0.0,CCBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBAC,True +958,19.0,19.0,0.0,0.0,19.0,0.0,0.0,0.0,BEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEA,True +959,0.0,0.0,39.0,0.0,0.0,38.0,0.0,38.0,CFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHC,True +960,0.0,0.0,0.0,80.0,41.0,0.0,0.0,1.0,HEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDE,True +961,0.0,21.0,0.0,22.0,0.0,23.0,0.0,0.0,FDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDF,True +962,0.0,0.0,0.0,0.0,6.0,10.0,0.0,0.0,EFEFFEFFEFFEFFEF,True +963,65.0,65.0,1.0,0.0,65.0,0.0,0.0,0.0,CBEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEA,True +964,0.0,46.0,1.0,0.0,45.0,46.0,0.0,0.0,CFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFB,True +965,64.0,64.0,0.0,0.0,63.0,0.0,1.0,0.0,GABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEAB,True +966,1.0,0.0,47.0,0.0,0.0,48.0,47.0,0.0,AFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGF,True +967,54.0,0.0,54.0,53.0,0.0,0.0,0.0,0.0,ACADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADC,True +968,10.0,0.0,10.0,0.0,12.0,0.0,0.0,0.0,EEACEACEACEACEACEACEACEACEACEACE,True +969,0.0,0.0,0.0,0.0,0.0,0.0,125.0,62.0,GGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGH,True +970,0.0,8.0,1.0,9.0,0.0,0.0,8.0,0.0,CDBGDBGDBGDBGDBGDBGDBGDBGD,True +971,0.0,0.0,0.0,66.0,66.0,67.0,1.0,0.0,GFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEF,True +972,63.0,0.0,0.0,0.0,127.0,0.0,1.0,0.0,GEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAE,True +973,0.0,0.0,11.0,0.0,0.0,0.0,21.0,1.0,HCGGCGGCGGCGGCGGCGGCGGCGGCGGCGGCG,True +974,0.0,0.0,39.0,0.0,0.0,40.0,40.0,0.0,FGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFG,True +975,0.0,0.0,1.0,31.0,0.0,0.0,62.0,0.0,CDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGG,True +976,0.0,54.0,0.0,0.0,0.0,1.0,54.0,55.0,FHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBH,True +977,0.0,0.0,18.0,19.0,0.0,18.0,0.0,0.0,DFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCD,True +978,126.0,63.0,0.0,0.0,1.0,0.0,0.0,0.0,EAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAAB,True +979,19.0,0.0,0.0,0.0,0.0,1.0,0.0,9.0,FAHAAHAAHAAHAAHAAHAAHAAHAAHAA,True +980,0.0,0.0,32.0,32.0,0.0,33.0,0.0,0.0,FDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFC,True +981,15.0,0.0,15.0,0.0,16.0,0.0,0.0,0.0,ECEACEACEACEACEACEACEACEACEACEACEACEACEACEACEA,True +982,0.0,0.0,55.0,0.0,0.0,56.0,57.0,0.0,GFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFG,True +983,0.0,0.0,32.0,0.0,1.0,32.0,31.0,0.0,EFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFC,True +984,0.0,0.0,0.0,41.0,1.0,40.0,40.0,0.0,EDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGD,True +985,0.0,0.0,0.0,0.0,5.0,6.0,5.0,1.0,HFGEFGEFGEFGEFGEF,True +986,0.0,19.0,17.0,0.0,0.0,0.0,0.0,18.0,BBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBH,True +987,0.0,0.0,0.0,0.0,0.0,0.0,6.0,10.0,GHGHHGHHGHHGHHGH,True +988,0.0,0.0,69.0,0.0,36.0,0.0,0.0,0.0,ECECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCE,True +989,1.0,0.0,0.0,0.0,0.0,19.0,0.0,37.0,AHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHF,True +990,67.0,0.0,0.0,0.0,0.0,0.0,0.0,33.0,AHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAA,True +991,0.0,0.0,16.0,18.0,0.0,17.0,0.0,0.0,DFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFD,True +992,1.0,0.0,50.0,50.0,0.0,0.0,49.0,0.0,ACDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCD,True +993,0.0,40.0,39.0,0.0,39.0,0.0,0.0,1.0,HBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEB,True +994,0.0,30.0,1.0,0.0,0.0,0.0,30.0,30.0,CBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGH,True +995,126.0,0.0,1.0,0.0,0.0,0.0,0.0,63.0,CHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAA,True +996,45.0,0.0,45.0,1.0,0.0,0.0,0.0,45.0,DHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHAC,True +997,15.0,0.0,0.0,0.0,29.0,0.0,0.0,0.0,AEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEE,True +998,0.0,4.0,1.0,0.0,0.0,4.0,0.0,4.0,CHBFHBFHBFHBF,True +999,0.0,100.0,0.0,0.0,0.0,0.0,0.0,51.0,HBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBH,True diff --git a/tests/results/nb_gm_002_2back.csv b/tests/results/nb_gm_002_2back.csv new file mode 100644 index 0000000..33538c3 --- /dev/null +++ b/tests/results/nb_gm_002_2back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,4.0,2.0,2.0,2.0,2.0,1.0,0.0,5.0,BHCHDHDAEBEHAFAHAC,True +1,0.0,4.0,1.0,2.0,4.0,0.0,0.0,0.0,DBEBDBCEEBE,True +2,5.0,10.0,14.0,6.0,16.0,18.0,12.0,12.0,CFFGHCFCGHEDCCACECBGEGFGAEBGHFDCEEDCCEGEGCBBBHCCECHBHEHBHDEDAFAFAFHFGFGFGHGHEFFFEFEDHFEFEFBBB,False +3,12.0,15.0,11.0,20.0,13.0,17.0,17.0,22.0,AFAHGHGHGBEBCDDDDHHHABCEHEHEBBBAHADADCFHHHHHFEFCBDDFDGDEFCAGGFEFBDGEHECCBCFFFFFFHGEBBHHCBCACHHDDBFGGGGEGEAFDGDADGDGDGBEBAAHDDFH,False +4,4.0,4.0,8.0,8.0,5.0,7.0,4.0,2.0,FGDGECDCECGCDADAHFDFCFCGAFCDDDABEBHBEFEFBC,False +5,15.0,15.0,15.0,16.0,16.0,14.0,9.0,13.0,HGDGBFDHDADHBBBBBHBAAGBCEABCGFAFAFBGBCBFGDDDEAAAHDFACECECHFHFHFCFHEGEFEFDFDAAHDEECDABFCCCCGBEBDAHCECHCHEDEDEDAGEE,False +6,17.0,17.0,9.0,6.0,15.0,13.0,15.0,12.0,BEBEBHAGCFEHHABAHDEDGHFBFGFCAABAGFFFAFGECEBEAEAFBFCEBEGHGDBEFABABEGEHEHBGBGDADACAGHGHGBGBACGCAHFFBHAECDC,False +7,12.0,7.0,7.0,6.0,9.0,8.0,5.0,6.0,CEGBFEFEFEHCCDEBCCHBBBGAHACBGGDBDADACADHDHFEAEAEFGFAAEAHAFAF,False +8,9.0,13.0,10.0,11.0,12.0,15.0,11.0,12.0,CGCFDBDFHHEHFFGCDHEHCFCFAAEGDCEGHGCFCBBBCBGFGHGDFDBDADHBBEGAGABABHBEBEHGHADAFEFCFDBDEFEHEFEFA,False +9,13.0,26.0,23.0,14.0,20.0,18.0,19.0,27.0,HECEBEFFHFDCCFGBCBDBAHGHGCBBABHEFAFEBEBHBHGGCHBGGCCCCCFCBDDDEDHDEEEAAFAFGFDFCGBGHEHDHGHAFABCGGEHEHFBGBADEBEBEAAHBDCCFGGHHHBHBHGHBDBEEAEGCGCBCHCEFFFFCHDHCHDHABCB,False +10,14.0,18.0,15.0,13.0,15.0,19.0,18.0,11.0,AFACABDDFBBBEBECECGHFBFBECDCEEEDGDBHHGCBDDAFCBAAAGHCHCHEAFBFDHAHCFFAAAHBBBFBFBHGFBCBCFGGGHGDGDFEGEFCFEDGDGAGEGCGEGEFEFAFDGC,False +11,21.0,20.0,21.0,13.0,15.0,26.0,21.0,21.0,EECEFFHGCADHGEGEABCCFDEBABEBGGCACHFHFBFBFBAHGBGCGHDCDABHHAGABFHEBCFEGDFDFDFAFBCBCAHACFGFBFBFBFBDACCBCHFHEGEDFDFCAAAGGEBFAAACACHCHFGFBFGHGHAEAGCCEDDFHHHGHGHGDE,False +12,17.0,26.0,17.0,23.0,17.0,11.0,26.0,21.0,ABGCACGDDFHFHBCEHEAGBGBEBAHEBEBFAAHAFBCEGDGBAHGGGGFGDDDBABABHGGGCGDGHGHDACAEDEFECHGEGDABGCHCDDDDCBCBADAHCHGBGBGEHDCDBBFBABHBHBFBACHDEEHGHECDCDHDEFEDECFGHGBFBD,False +13,24.0,21.0,23.0,20.0,15.0,14.0,30.0,24.0,AHHHHAFEDHAFBFGFCFGADADCDGBBBBGDGEGBCBHGGGGCGFBFAGGGGHEEFEGHGHABCBFHGAGACBBDEDHDHDGBCACAHGCACEHECACHBHDCGCECADGDGDABADHFGCGAGAHHBGFDCHBHCAAABEEFDFDBDBEADAHGEGEHECCCBCFCAHD,False +14,1.0,0.0,2.0,1.0,1.0,1.0,2.0,2.0,DECGCGAHFH,True +15,7.0,7.0,10.0,5.0,8.0,4.0,8.0,9.0,HBABHHEEGAGAGEGHCDEECHCHGBCBCDDAEGCBCGEAEFDFBFBFAGCHCHCHAD,False +16,14.0,19.0,14.0,7.0,10.0,15.0,19.0,7.0,CEAFFGHGEGFDFDCACAGBDEAFCEDDFAHHFDFGBEACGCGBGAFECECFGHCEBAFGEGCBABEBHBHBACAGAGDGHBABCBCBGFGFGFGBBBBFBCBGA,False +17,17.0,15.0,14.0,12.0,10.0,9.0,17.0,6.0,EBACADACGBGBAFGHGHADCDGAAFFFADABAHGDGABBCBCACACECHFBFHDCACDGEBADDEGGGEDADFGFGCGFBBABCBEBDBCHGEGEGECE,False +18,14.0,22.0,17.0,9.0,14.0,10.0,25.0,20.0,EHCHAHEHAHCHCGBGCGCGAEBFBFGGCEFGBGHAHCBABABHHGHGCACHDEDBBABGGDGDEBBBHHGCAEGBFHGEGEGBCCGCDFBBGBFBDAEEHHHCFEFECEHGCGCBHDADFDAGAGAGFBB,False +19,13.0,27.0,12.0,18.0,19.0,17.0,20.0,18.0,BFGCGBHAHAHEFEDBABEBEDADGGGGBAFCGEBDFHBHGHGCBBEGEGBHDHDHBCBCACDBFHHCHBGAGAGEDADADCDCACGHEEEEBDFDFDHDCGGBGDEBBBABEHFHGEFFFBADHEFFCFDEBEBFFEBHBFBG,False +20,11.0,10.0,7.0,8.0,8.0,7.0,11.0,4.0,BGBABGHGCGFBFAEBGGEDEFAHEHACDCDADBGGAGAGADFBFBCBCEFBFDHDACCDAGAEEE,False +21,22.0,20.0,18.0,24.0,13.0,11.0,16.0,21.0,DADADHCACFCHEDAAAHGDDHAGCDEDEGBHAHBDBDBGHHHCHCECAAAEFEDECEDBHFABGBCAGDBEGEBABHFCBBABDFDGHGCBFBCCDHDHDGDHDHCHBGADAFACHEHBDCDAFAFAFAGGCGCFHGBDBEBEG,False +22,8.0,10.0,11.0,7.0,8.0,15.0,4.0,11.0,CBAEGDGEHEBGBFBFBDHCHFHBAEHFFGFCFBFCFEEHABECFFFFACAEHHDCDCDHDHAHCFCBCBAADF,False +23,32.0,19.0,21.0,23.0,13.0,27.0,21.0,27.0,GHCABDGDFFFAHHHEAEHGAGAGHEFEGBCFAFBFGCHCHFHBGCAFFDFDBACACHCHCHBFGFEACAFABEBEBHHGHFHAHGGAGAHAFCGDHDHAFGCBCHDAAAAAAFCFHGEFFBEBEDDDFDBCBDDDCGFAFADBDBEBCAGGHDFDFBCDEAGAHCCEHGHAHCDDDDABAFA,False +24,26.0,30.0,18.0,21.0,29.0,16.0,21.0,21.0,GDGDADAGAGDEHCDBDHAHEHFHAHAFBHBHGCEBHBDBHBHBEEABABABAEECEGEGAGADHDBEEGBCAADHGBFBCEAAHDEBEBFBFBFCCGCEFBABAEDBGFGBGCFCGEACDFEFBHDADFHCEAEBDHDCGBEFGCDCACDEBEGAGAEAEFDFBBEHEGEGHCACEFBHDH,False +25,17.0,15.0,10.0,21.0,16.0,11.0,16.0,22.0,BDBDBHHHAAGAEHEHCHCDADEBGHDAGEBHGAABADADEDECEHAHFBGCGBEHCGADFBHECGHHFFFHFBDDDDDFDFDFHFEDEDACAEAEBDCHHBFBABCBGDGEAECHHGHGEGHDAGGG,False +26,12.0,13.0,16.0,11.0,17.0,10.0,17.0,12.0,GEECBGFEEDHCEFGFEAEAHGEGEDDDHDCDCBHBCBCFCECEGAGAGAHECFCEAAFGFGCEHGHBBBGBGBCBDHEAEFHFHGBCDGGACHCGCDADAEBFBADH,False +27,14.0,11.0,17.0,13.0,14.0,21.0,16.0,19.0,AAECGGEGHCACACACHBHADCECBDHDHDFCFGHGDDEDHHHAHDFDACHBHAFBHHAEEECGGFGEGEBEFCFAEAEFFBFBFDGDGDGHFACCDFHFCGBBHBCGGFGEHEFFFFHFCBCAF,False +28,14.0,15.0,12.0,21.0,15.0,9.0,13.0,21.0,GGHGEDHFCFCACBCADAEEEEAHDGAGHGHEHEHBBECEDBBBDBEGDGBAEABCCABBECDDDFDFHGHGHDHGHGHDADHHCHBHCCBAFHFDDDEDHFHAABDFDFEGEAADBDCH,False +29,18.0,19.0,27.0,26.0,29.0,30.0,16.0,16.0,DEFFFAFAGDGEEBFBFGEBADACADFDCEEDEDFDCDEBBGDGHGHGFFFDFBEBEHCHFDCDCEGFGFHFEFCGBBDCHCGCDADEGEGCFAAEHEHFDACGCEABBDECBCBCEFEFBFCFCFEHEHDGACEBAGCEFEBACCCAEDHDHBCFCDEFFHDHDHDCFCAAAEBEBFDHA,False +30,5.0,11.0,5.0,8.0,3.0,2.0,5.0,1.0,BBFGGBABFGCCCDADAHBEDCDBABGEAECBDBDBDBDG,True +31,28.0,17.0,19.0,16.0,18.0,11.0,17.0,33.0,DHAFAHAEAHDHFHFAFADHCGGGDGDGHEBDHCHBHAEBCBCFEGHHHBHCAFDHEHEHCDAGBCBAAAGACCBCAFGBHEHBBEAHAHAFAEACGGEHAFABEDEDFDCGHEBGAGEEAEBBHDEDECHCGABHGHAHAHBHCHCHCHDGACACDFD,False +32,5.0,10.0,12.0,17.0,19.0,17.0,17.0,11.0,EEBHBFFFDDEDCCAGEFEGGDGDFFGEGEAEDEFCFCGCGCGFAEGECDHHCEFDDHDFDABFDECECEHEFDDGDGBBFBFHHGCECEFEHAHDHDGBBFBGHGBG,False +33,4.0,13.0,10.0,7.0,4.0,8.0,11.0,7.0,CGBHBCBCBHFHFECBADGBGBGBDBCFAGDBHGFGECEHBGBCCACFGFGFGDDDFCADHEHB,False +34,22.0,27.0,22.0,21.0,21.0,28.0,21.0,21.0,BABFBCCCCGCDCAGABAHFBAHCBDBDHDCDCDEFFHBHBCBCBEHDAGAEFBBEEEBEGAGHGDGCGEBFBDEAECCFCFGDGDGHBHAEFFFECCADHFFBGHDHEGAAEDEFEFCDCDCDEFCHADAEHFDFHBBEBEBFBFAFGFAAHGHGFFAFGGBABGHGBFBFDFHCHAHEGDA,False +35,24.0,23.0,21.0,17.0,28.0,15.0,20.0,21.0,EGHGAGEGCGDFFCEEEEEAHGEGFGFBCBGBDBACHCAGDDDDEDEHACGCECAFAFEFHCHCEFHDHEHBAEADBDBAFCHCEEEEHBHBECEAEAFGGGGCCHBHAAACABBEHFHBDFHHDHBGCAABEBGAGABBFADADEBBBBCDCACFGFHDCEHEBGADE,False +36,16.0,12.0,18.0,16.0,29.0,20.0,25.0,11.0,EEEBCFFDHDBBGHGHGEFDFACCCFCGAECECEAGFFFCFDAHAEEHGGGBGBGADDGDGEGCCBFEHEGEHACDGDGCCCFCEAFAEGEGBGFGBBBHFGDGFGAAHADADCEEEEDEAEFEAEBFFFHEGECEGEHECAFDDDB,False +37,1.0,6.0,2.0,11.0,2.0,11.0,4.0,7.0,DBFFFHHADFFEFBDBFBGDFFEBHBHFHGDGDGCCDDDDHDHF,True +38,11.0,12.0,15.0,5.0,3.0,15.0,15.0,13.0,HCCCCAEBGFCFBGAHHHHBAFGCGCGCGFGCAABFBABHBFBCAFHFAFGCDBGBGAGFCBBAADHDHDCGEGHGCGFFHFHDEFHFC,False +39,33.0,14.0,21.0,23.0,21.0,18.0,25.0,28.0,DHAHAHADGDAFAFGCHCHEHCHABACEDDDCGBHAEFFGCADADGBGCFFFGGHBAAFGGHFHFHECFCHCHBDEFGADDCGGGHEBEDEBEBEDFHCAAAACFGFBFBFADAEGBDCAGACACAFGEEECDDDDCGGGEEEEEGCADHHHHAHABAHGBBCACHEGGHDADADAHAHEHAH,False +40,9.0,21.0,8.0,6.0,13.0,11.0,9.0,15.0,HEBEGEGAGEBBBHFAFABCBCBEBCBEAFHGGGHEHCHBEDFFAFAHDBFBFBEBDFHHDHBHCHBHBDEFABGBCEDEBCACHHEAGBGF,False +41,13.0,18.0,18.0,16.0,8.0,20.0,16.0,13.0,AGDGBCDHFADAGFFFHHCFCFEBGBGFGFGCGCHHHHCGFBFGDHABCBCGDGECEFBFCACBDBDCFAFBDEDCFFBHGHBEBABDFDFDHDHACABDBAFAFDHEGACACBEECGCBDG,False +42,21.0,15.0,14.0,22.0,14.0,22.0,16.0,21.0,ACFDFDEDFDBAFDCDCDFFFFFACHCHGEDFCFEHADACEHEDEBAFAGGHGEDADFDHDHDHGADAGCCCFHBDBGBDEGEBHGFGHAHFBFBFEAABABACDDAHHGFGBGEGHFEABHBFEHHHGDFDCACABABGECHAH,False +43,17.0,19.0,23.0,19.0,19.0,21.0,20.0,22.0,GDGFGEDDDDDDFDFDFEHBHDGAECBHDEGHGEEDEBEDECGGAADAFAFADECFCDGDGFBHGCBHBACAGACFCGGGBGCHFHEHECECAHFHFGCGHBFCGCBCFEHEGEHBBAAABDHFBCCCCFFFHFCABFBHBHBEDAFEHBHACABECHCH,False +44,2.0,1.0,3.0,4.0,5.0,3.0,6.0,5.0,CHCHFGBGEHFDAGADEDEGGFGEDEHCH,True +45,17.0,20.0,26.0,20.0,18.0,24.0,15.0,12.0,BDEFBBBHHECFCFCBBFEDDADADGECEHEFCGCAFDCGCFFEDDGGHHHHHAFAFEFAFDFDFDEDFAACFCFCDCBBBCGCGDGDFCGCGBDCACBHDHEECBBEBECFCHGBGEGABCDCEFHFGACDFAFAECEBEBDACABAGFBA,False +46,5.0,7.0,11.0,5.0,5.0,3.0,8.0,10.0,CBDHFHCDCEGEHCHCHCHEGCGCGBBBBADAHGDGBACGEAHBHFGFCECAHD,False +47,5.0,4.0,4.0,5.0,0.0,1.0,5.0,3.0,ACABGBHBHBGDCACHCDAGFGAGDDD,True +48,21.0,22.0,13.0,24.0,16.0,18.0,24.0,19.0,DBDGAGBGFHFCABGFECEGBGHHEACDFDGCGBEBGDAFAHADADAHHBHBHAGABADEBFDGDBDGDGCFAFAFDDDDECGFEFEAHAHEHEHCBCDADGBFBFAEBCAHFHEDEGBBFDEHEBDHFGCGHGHGBGCDABCBDGHGBGDCEAFAF,False +49,5.0,12.0,11.0,8.0,8.0,7.0,11.0,9.0,FCFDGDHBEBECFBBHFCFCGDBCCCGCECECBDBGBEHDDBCAGAEHEDFDHGEGAHBHGAGAGFHBHBG,False +50,2.0,7.0,7.0,4.0,6.0,13.0,10.0,11.0,BBFEFEFHAHFDFGHEBABDFHBHEFGFGHEHGGGFDFEHCBGBFDFHFHCCGCGHGCCC,True +51,5.0,7.0,11.0,12.0,13.0,9.0,8.0,13.0,EFFBFDAAECCCHDHBHFEDBHBHDHDGGGGECDGHCFEFEDEDCDCDEDCCHFEFEGCGBHEHBHAHAGDFCEAEHB,False +52,15.0,6.0,11.0,6.0,11.0,16.0,3.0,8.0,BAEGCCEAHBFCCHFABEHEFDCHEBECACECEAFGFEFEFBFBFAFADADACACDFGFAFAFEFDAAHFDCAHHH,True +53,20.0,14.0,19.0,11.0,13.0,12.0,10.0,17.0,CHCECEHEGAHBFGHCHABCBCDCECEDAHACGCADDBBGFGFGFHAAACACFBEGGAGAEHCAAAFDFDCHBDBHGDFDHCBEFEBCBABHHHHDHCHDFEFABEBECAAAEACF,False +54,18.0,14.0,15.0,22.0,24.0,20.0,25.0,23.0,EGGCGCGDEDEBCBFDDDBFHDDGFBFEEEGDBDBEHFDFEACACADABEFDCECGGHBDCDBAGHGFBFECHCFEDEHEHAHEEAGCEEEEFGFHFAAGEEHHHHAHAHDEFGDGDBCGAGHFHFHAHAHDHDBFBFCEGGGGGGGHAADAGCDFFAHCB,False +55,3.0,4.0,2.0,5.0,2.0,5.0,3.0,1.0,EHAABABGBFDFGFGEDDFDCBCDF,True +56,9.0,9.0,8.0,11.0,11.0,13.0,8.0,11.0,ECFFFBCDEDAFEBEAFGFHFHFDEHEBEHEGBFEFHBABCCAGAGBGBDFHAHGHFCFDHDABADEDEDAHGGCDCHCD,False +57,10.0,13.0,10.0,15.0,7.0,9.0,16.0,11.0,HHCFEGEGEDFGABEHEADCHGHBDFDGDGHGCGBBDDCDCDBDBHCDEBAHACCFDGDFAFAFDDAGAGHGCGBGBHACBGBGAHEBFBF,False +58,15.0,15.0,14.0,21.0,27.0,24.0,20.0,28.0,FAFEFAADAGFBFACBCBHHCGFGFAFHCEGEGHHBDBFHFHBEGDGDAEEHEGCGDGHCDGDEHFHGCEEEGEGEDBDEEEEHHHHCHDAGFEBHFHAHFHFDDDCACHFBDDHDGDFDAGGEAEFBHEEEEBEHEFFCFCFDBHAFADCGCGFHDHEBABHB,False +59,11.0,16.0,18.0,17.0,22.0,31.0,15.0,17.0,FCECFCFCFBHCHBGBFHGEDADADEFEFHFDFDADEEADHGAEAECGDGCCFHFGFHFHFHFBFBFCEEEBEFFDEGGBHBEBHFCDDDDGHAFBFBFCACHCAFGCGHHEDCBFEFABCDCEGGGDAEBBBEDEFFFFECGHEHF,False +60,11.0,9.0,7.0,2.0,10.0,10.0,11.0,9.0,HGHCDCHCACBCEGEGEGEBBHCFGABEBFAEHHFBFAAGHGHFHABABCGEGFDEAAABFEFEFGFGA,False +61,23.0,23.0,21.0,24.0,24.0,17.0,27.0,24.0,EDGGCBCFCGCGCFCGCDCBAACHFHFHECACAGAHFHDBDEHAGADHGEGEBCAEAGDHAADDDDCEAEADBGFDBBBBDHDGDBBGCAAEHEGDGBGBFHCGCDBBBEFHFDAGHCDCHFHFGEHEGEGHGBEFACADAFCBGBGBFHDEDEDFBFEGHGHAHAEEEEGEDHAHACEFBHB,False +62,21.0,13.0,9.0,12.0,17.0,15.0,25.0,10.0,HFGFGBGEDEHGHAHFHGAAAFGHBFACGDBEBGAAFEGEFEFBGAHDEDECBCBFBEGAGAFCCBBDBAGABAGGGGGECDADAGAEFEDGACADDCDHDEAFHFHFGGGFGCABAEEEGE,False +63,6.0,6.0,3.0,12.0,7.0,8.0,6.0,13.0,FHEBEBHGHDAGHDCDEDEAFCFCHEEBAAFDDDFDHDAGBGFDHGHAHDHEHFHFHBDBG,False +64,6.0,15.0,15.0,8.0,14.0,13.0,8.0,8.0,CCEDEDBHHGDCBEFEFCCGCEAGFGEGECAHAHGBCFHACEBEBEGEFFFFBDBFBHBDDEDCBCBHBFGFHEAEBCBCFCBCAFD,False +65,6.0,4.0,3.0,4.0,6.0,8.0,5.0,5.0,CGCFEFAFAEEDEHCHBBDAAFAGHEHEBFDHDBAGFGFGF,False +66,17.0,8.0,15.0,6.0,16.0,16.0,11.0,12.0,AFGFGFGHGFECECECHAECCCFAHAFAEHGGCEBAFAEAEFGGHCBFAAEHFHFGBHEHGAFBFHCECEADFDBDBCACACAEAEBEDDACBDFHFHEGC,False +67,24.0,12.0,23.0,14.0,18.0,18.0,15.0,12.0,CCCFCFBHAEEDFDBAADAEAEABDBDGEHEGCCCACECHGEGEDECACFCFCHBFBAGAFFGHADBEBAAAAFAEECEDHDHECGGBHHCHDBGBABAGEFFGFAFADACADAGADCHFECGFGFHFCDCEGFCC,False +68,31.0,17.0,27.0,38.0,29.0,28.0,14.0,16.0,ACACBCFDGBHBDEGEAHDDEFEFEFEFDDHECEBDFDAEAEFECECGCHAHAHCBCDAHBDDDDEDEBEHGDDAFEFCFDDBCGAGACCECAADADABAFEDACGCAFAHDFDBDGCECBGBFFCHCGAEDFFFHADFDADGFAFADEDHABAGAGEHEFBFECEDEDCGEADADFDHBHDFDCBCFCDAFAECFCEHB,False +69,5.0,4.0,3.0,4.0,2.0,3.0,6.0,4.0,DAHAGAHAHAHFGCGEBDFDEDGGCFBBGBC,False +70,5.0,7.0,9.0,5.0,2.0,11.0,6.0,10.0,HAHDHDHBGBFCACDCHFBBHBHGDEACACEGFCDHBGFGFGFCCHBFFHFCFAF,True +71,11.0,10.0,6.0,19.0,14.0,23.0,11.0,9.0,FHFEADABECHFFDFDFHFEDECEFEFEFAFHDADAEADDCAGFGBBHGDGABDDFFFFDDDADEEGFGDABCDGGBHDHFGAGBHBHBEBEGFFFFFCCEDE,False +72,25.0,17.0,20.0,19.0,16.0,13.0,17.0,22.0,GDCDHGBEAEGDGEBDBDHDCDCBHDEAEHDCEFAAABCDCDABAGADADCFAFCGCACAFFBAHGCGCGEGEACHHECACECEHEGGFBDHFHAHAHGGDGFCECHFHFHCHFABABFDGABDEDABABHEACAFDHHGHAHBBBBEH,False +73,15.0,19.0,20.0,23.0,23.0,21.0,22.0,23.0,GFGFECGCEEGHFCBCFDDDHHGBGHGHDCDCFHAHCCCFHAADEBEHEDEDADCDCABEGEFDFHCHGGAHAHFCFCEADFFECGBDBDBDCCACADHGCGEGHFHGHGBFADEBEBEDGDBBACEEEHGBDBFFFFDGEGDGDGFBEHHHHAAEAEFBBBBEFH,False +74,3.0,11.0,6.0,11.0,10.0,12.0,5.0,7.0,ECHFHDHEFFHHDCFGEGFDBEBEFFFDBCBFEDCDCFEBBFADDBDBGBGBGBAHAHFDEDECE,True +75,21.0,13.0,22.0,19.0,30.0,19.0,18.0,19.0,HAHEEEFEDHDFDBHBGCCEEFEGGHGHCCCCCHGECEAHDBDBEFGHCACGBEFEHAFDFACAFEEEHABAGAFDGDADADAGBCBAEADAEFHCDCFGEHFHDEDCDFEFCCCEAEAEGGABFGEDBDBHBCCECEHEAEFGHGHDDAEAEHCFGFGFB,False +76,14.0,30.0,18.0,20.0,25.0,19.0,27.0,30.0,FCFBAEDEGEHEBGHGFEFCGDBDGGCGCGBEBHBHEAAAEECBCBCFHFCFDGAEHHFGGGGGHCHEHBABGBGHHDFAEBDBDBDBCCHAGGEGDGCCBCHFGFGHGHBHEFGHBFBCBHEHBBABCBHBCGEHEADDDBHFHAADEDBFHFEEGEDHDHDEDBDFEFEHCHAEGDHBFBA,False +77,25.0,17.0,30.0,29.0,22.0,22.0,23.0,24.0,CCHEAEHBBCBDADBDBDHGFEECBDFGFEAHDCGCDHHEHEHCGCFHGDGAGAGACACDDDFDFDGECCHDHCCEFAFEBAFGGHDCCGEDBDBDBCHCACDBAHCGCGAHAHAFFFHADCDCFCFHHCDCAEAGAGAGABFHGEGBGDFHEBEFCFAGBEEAABAGDGDFDFEABHCDEDEHEHEFCFCD,False +78,9.0,16.0,9.0,5.0,4.0,15.0,4.0,5.0,BCEADCBBBBABABCCEHFBDHFAAGAGHCFCBCBFDFAGAGBFBDBABFFFFFCEHEBDHFFFBFC,True +79,19.0,17.0,10.0,29.0,13.0,8.0,14.0,14.0,DEDEAEAEDDDDDDDHDGEBEFADAGBFFHDGFBBBBGBABFCHGDFDEACBBBAHADAHCGCAHDHEHABAGCGCGEDAGBDAACAHDBCBGBGBEDDDDDADGDFDHHFDAHAEEEHCDCHG,False +80,9.0,11.0,7.0,9.0,14.0,3.0,11.0,16.0,HEHEACBHBHAGEBEAEBHBHBDEDCFABCGAEABHEHDADABABGGGDGHECEHHDGDHHCHCDGFFHCBEDEGEGHGE,False +81,4.0,9.0,4.0,9.0,3.0,6.0,6.0,5.0,BGBACACHDGDFDFBFEAHFBDDEDEGHGHBBBFBADHDGCGDBFC,False +82,11.0,21.0,22.0,24.0,26.0,28.0,21.0,21.0,EDGDCDCFGEDEFFFFGEEEDEDEDADACHCEBAFAFCHEDBFEDHDCCAHGFDFDGAGEFECEDBHCECDGGGGGBGFGBHCGDGFFDCAGDBCEHEGBBBBHFHADFHCHCHCACHCBBEFAGBGBEBFFFHFBCEDFFEFHDHFHFCCECBHBDBDEDEHBHEHFBFEGAG,False +83,2.0,4.0,1.0,3.0,2.0,4.0,2.0,1.0,CBFHFBBDGDFDFEGEABA,True +84,18.0,13.0,21.0,13.0,16.0,19.0,15.0,8.0,CBCEEADAFGDCFHFHDHFACACEDGACFGGGCBABDCCCCCCBABABABDBDFACGCGCFCAGEFEFBDBCFEFEAGFDBEFEHEHBAEADAFAFGEGECAHFEDGDHHCAEDEFCFGGGBF,False +85,14.0,12.0,10.0,10.0,16.0,19.0,9.0,12.0,FGBGHDEEEGBFAEAEDHGHGFEDEFEGEDEFEFCBAHCHCFBFDGECFFFGAECBBBDGFAFACACBEDABEBFHFHFHAHAHFEDCDCFCAAHBHADAFB,False +86,14.0,13.0,10.0,16.0,18.0,7.0,14.0,15.0,GGGGHADGCGCEEEDEDBAAGBCDAEABAGAFFFDBEFEAHAHBDBDBDBGHAACDHHGHGHDHEFBCDCHCHDEEBEBDADABEFECCGHGHFHDGEEEADBEEHC,False +87,9.0,13.0,17.0,12.0,12.0,23.0,13.0,12.0,EHCHBDDCECFCFCFABABGBFDFDCDHBGDHDGBGCGCGCFCDHEHEFCHGEAFBFBFDFHCEBAFEDEDFFGHCFGBGFGCDCEBGFHFAFBEEEBGFFCFAACAHAHF,False +88,6.0,3.0,0.0,1.0,3.0,3.0,5.0,4.0,GBGAGBHAGAGFEBEFEHHAHAFAD,True +89,11.0,11.0,12.0,15.0,16.0,12.0,7.0,10.0,BHBHDDADCGCAEHHDCEAFAFBFCDEDECBGFCECHAHGCAEDDBDEAFAFHFDCHEBEGEGADBDBHEHDFGFGFDECECECAAEBEBDBFF,False +90,18.0,21.0,18.0,8.0,15.0,18.0,18.0,10.0,BCBDGCBCHGHAAFAFEFAFDFHGGGCCECEHBHFCADAFAFEGBAAAGAFBEBEBEGCBHBFADAECDGHGBGECCBCBABHFFDCEFEHGBGBGBEFGABCBFBDBEEAHACGCGEGFCFCFDA,False +91,21.0,22.0,23.0,29.0,25.0,21.0,20.0,16.0,EDECECBBDBGGGDHDFCFDFAFGBACHDHDADFDHBEAACACACEDECEDGDGEGEGEDEAFCFEGGBEBGFGEDECGFAFAFGHEDFHFCFBFBDEDFDGBHEADHDCCFBABABACGEHAHFHCEGEGHBHDACADFCCHBHDCDCFBHAGDBABEBFBGCDBEBCDDADAEEC,False +92,22.0,26.0,23.0,24.0,20.0,30.0,22.0,18.0,ADAFEGHDHFFFFDFECADDDFHBHDCBFAHCHCACHEGFBFBCDHEFEGABAFAEBGBFFFBFCFGBHBEBAACAHAEDEDEGCDCDCDCGHACFCFHFHGCFCEHEHCGCDCEFGDGBGBGEGBABGBGCCABBBDBAFGDABFBFEFEDADBFEFDBHGHDFEFECBAGGCGADDDGBHAEA,False +93,2.0,2.0,1.0,3.0,0.0,2.0,1.0,2.0,DBDCDGFFAHAHB,True +94,18.0,8.0,12.0,13.0,10.0,9.0,12.0,11.0,HHFAEHCHCHCDDAFACACACGGFEFGCHDEEGCGCGFDDADGDFDEBHCDABGBABDGAGEEBAFABGBDAHAFAFADADEHHCHCBGEAEA,False +95,4.0,5.0,6.0,3.0,5.0,4.0,4.0,3.0,AHBFEADADAGFHFGGCBCBCBCFCEHEBDCEEG,False +96,6.0,10.0,15.0,4.0,14.0,9.0,14.0,11.0,ECECEGHGHEHGDACGHHHFGFGCCCGFEEHEAAACCHCFCFEGEDHFHFDFGEABBBBEBHGCGBEBGCACBEBEGCCDBFG,False +97,3.0,4.0,3.0,4.0,3.0,2.0,2.0,6.0,BGHFHDHDCDBDECAHAHAEGBFBHCE,False +98,14.0,9.0,9.0,12.0,16.0,15.0,11.0,5.0,BGGACFEGEGEAFGFGFGFAADADACBCFDADGEBHBFDFGBBDCGAFAEEFECHCDCBFEAEAEADADCEBDDHDBGEFCHEHEFEAEFF,False +99,24.0,22.0,16.0,19.0,18.0,22.0,22.0,17.0,BABDFDEDEDEHAACABAEAFFGBHFGAHDBCAGADEDCHBBGEGAGAGAGAGFGABEDEDEFCBABDBECECEAGFGEGBGACBFEHEHAHAFBFBCHEFGDADAEEBCBHHHFHFBAGGGFFFFGHDCCHAHBCBCHFGDBCCAFBDGGFDHDFDFDC,False +100,10.0,7.0,6.0,7.0,6.0,11.0,8.0,15.0,GGHGHGFEFDCHAHFHEHEBACCBCHFHFBCBEBFFEFHAHGHDAGADAEGBGHHBAAADCFHFDADFDH,False +101,21.0,23.0,9.0,23.0,25.0,21.0,22.0,21.0,EEEEEACAHEHDDADHFBFBAHGHGBGDGFECGBBBBFBFEFHFGFGFAEHDHAHAHBHGHFBBHGGGGGEHDDDDHEAFBHHDEFEHEDDGBCDCHBGDDFFCAHADEDEGEGEAABBEBDFGEBABCDFEACFDADAGAGEGBAFABHBDGDCEEEAFAFBFC,False +102,1.0,8.0,5.0,3.0,5.0,5.0,6.0,8.0,HCGCHDEBGFEFECBBBFBFGHGHGDGBAHCFCHHHEDEBB,False +103,29.0,22.0,27.0,17.0,23.0,16.0,31.0,26.0,GGHCFGEBEDGCCDEBFFFEFHGCDCBCBCECFCHCHCHGHCEGAGCECABHEEEBEBEGAGBBBABABFBHBHDHGGDADCCFAFEDECEABGBFAFHDAGHGHADEFGBDCHHDEDCHGABABFGDEAAAEBGAAEGGGGFGHAHDBDCCHGHBDGEGHGEAEACCHCACAHGHGHAHDCACAFAGAFA,False +104,7.0,6.0,18.0,7.0,11.0,12.0,24.0,18.0,GDGEHCGGGEFECEBECGCGHGCFHFHFHCDFDFGACHHHGBGHACDCGAGADBCAHECACGHGHBBCFGHEDEFEHGHBHGGCGCGCHCEGGDGEAFFHFCF,True +105,16.0,23.0,21.0,18.0,22.0,17.0,10.0,18.0,ACEGEHEHAFACDCDCHFBFBGBHDFFFCAGHBBBHBHFABABABAHEGCAEEEFGBGBADGEBCDEHEBCFCHBHEFEBDDDDDDDGFEDEFEHAHBCACACBDBDHDCBCEDEHEGCCFEEEDHHAABCFCHAECBCBFFCFG,False +106,9.0,10.0,12.0,6.0,8.0,7.0,13.0,7.0,FABABHCEGEGBGBGCCCHCAAABGEGDGFGFAFCBCGCEHDCCAGHDHCAEHFBFAGBGBGHFDCDBEEDE,False +107,17.0,15.0,17.0,17.0,16.0,26.0,15.0,17.0,EFBHGEAFDGCGFGFGDEEAEGBDEFBGGFAHHCAFAFHBHBDGDGEGEGDFFFDFHHHAHBCDADBCBFGFCBCBGBFEHADAHCECFCECHBFFFFCDEDEDCDEFEFCHHHCACAEBCGAAAAHADAFHFBDBCFDF,False +108,20.0,24.0,27.0,23.0,19.0,28.0,19.0,18.0,AFAEGFGFGAHFCFEHEGDBBBEBEBEBCDDDHDFGFDCDCECFAFAHAGBBBEBFDEBCBAHGFGAGABDBEAGFCCCBEBHCDBDFDFBBHCHGGCDCDFHEHECGCFFFADAHHHDCDAEEBFGAEHCDDGACACACFCBEFFHAGCCCCEFEFCABDBFFFGHCHDHDFDGBGA,False +109,9.0,16.0,17.0,17.0,16.0,16.0,12.0,24.0,EGDDDAHBEAEABDCEBFFHFHFHCDGHAHCCFDFDFDFBBEBFBFEHGHGDCFCGHGHGCBCEDHBCDHFHFBFGDGACCCGAEBHBABCHHEHBDDEHEDEDEGEAHDHCECFCFCBHAHEGBHH,False +110,5.0,7.0,7.0,3.0,11.0,14.0,10.0,14.0,AHEHDHGFEFGCHFGFBBCAEFEFEFECEHFHBHAHFCBGFABHBEDEGCGFDFACGCGBFEFGHHHHEHG,True +111,20.0,16.0,22.0,22.0,11.0,17.0,13.0,10.0,ACAFFCDCDCACBFAFGDAACDCDEDEFFCBHDGDCDGDEABFEAADDCAHHDHEGACEFBCBCACACABBHDHDHEHCAAFAFCDDEDFDFBFCFBFDEDFFGGAGCCBEBCBHBAGGGGGEGACBHBDB,False +112,26.0,22.0,28.0,29.0,20.0,26.0,21.0,19.0,GCDCBAEHEHGGFABGFFFFBDBDBHCHCHAAADGFCBCDCFFFDCHCECEDEAFBFEFEGGCDCDAEAECFCEEACCBABGFDABADAFHBHFEFEAHAEADFCFHHBHAHAGGDHCCCDHBCADABHBDCGHGAGAGDDDFCAGBCBDBCFCFEHEDEBGGFGFDBCGAGDCDEDGDBDBEFEHAFADD,False +113,4.0,0.0,3.0,3.0,1.0,0.0,3.0,3.0,HAHADDGDHAGAECCCG,True +114,15.0,25.0,14.0,19.0,17.0,16.0,17.0,18.0,GDGCHHEBEBHBEFAFEFBFHFBGHEFEFEBAAAGFGDDFDFDFDBDBDBABABDHCBGDHCEBBGBCBEBAGHCHBEBGHEHEHEACACACACBBGGFGHCHDGBCDGEFDFDBEHECDGBCEHAHDHACFGADFDBAGD,False +115,4.0,7.0,3.0,5.0,3.0,0.0,6.0,6.0,HGHBHBDBABACEGDGEAHBHADGEGCHCBDGDB,True +116,18.0,19.0,11.0,27.0,26.0,22.0,18.0,28.0,FDFEHEBGBGBCFDFDFBEGFABHCHEEFAFAFAFBDHEHEABBDCHCDDGEHEADAFAFBHHCHBFBEDHGHGBFDFGECHHABDEGECEDADEHEDCAHAGEBABCDCDAHEDEDEDFFFFFBFHGAFEGEGDHDHGHGHGEDHDGEGDAHABBHHDHBCDADHEGE,False +117,9.0,10.0,11.0,5.0,12.0,11.0,5.0,12.0,HFBFCFBAAEABGHCHAFABBBBCCCHCECECHCGEHEHEHFHAHCEDDFDCEEBFFFFGEBEAFAHDGBGDEHA,False +118,1.0,8.0,6.0,3.0,6.0,11.0,9.0,8.0,BEBFGFGFBFBGBCDFEHBHAGEFHGDEFBFHHCGCDBGFGFGHCHFHCECE,True +119,16.0,21.0,23.0,14.0,8.0,20.0,24.0,21.0,EEGFBBADAFCBHFACCCFCFEFDGAFHFDABHBCGHHHBHGHCHEGCAABBGDHBHBGFGCGCGCGHFEFCFGABAGGCGAGACFCBCBHBFCFADHDHGHGFDEBEGCGCDBHBEAACHDDFDCDCFBFBGGGGCBHDHDHFABA,False +120,23.0,16.0,16.0,25.0,12.0,20.0,24.0,21.0,DFHFBBDGFFEDCHEEGGGEEADAGAGDBDAABFDFCGDGAABABABABACAGGHDHFACECBDDFDHGHGHBCBCAGFGBGCFFFDFDCGHGDEEHBCDCBHBCFGFDFDHAGCHHHHHGAFADDHEHEAGAGAGHCBAEAEDCDADCFGFDHDHF,False +121,19.0,17.0,15.0,20.0,28.0,24.0,23.0,17.0,DCDFFGAAFFFBGAGDGCACHEHDADADFEHEGGFFEFAABBHGGGFHEHACACBEEEHBAGAGFDFEBEGEBECECDCHBHGDGBEFEAEAEAECCGCEHBHCFFGBDBDCDAEEEAEFFFBHAHGEDEBGFGFGHGBGBDFDCDHEHDDDEBAFDFEGCFH,False +122,24.0,21.0,31.0,19.0,20.0,33.0,21.0,17.0,CBDGEGCBFGFHFHFEFBDAECCCBCBGHDCCCAFADHDHDEDACBDBGAHABFDGEGCHEECECDAFBGBGBFFFFHEAECHFHFHGEEBCFCFDGEGFFFFGCDCGBGBGFFBFBFAAAAAFGBAFABECAGEGBGFHFCADDCECHFAFADAHFHEDEHCFBACAEAEFDCCCCCBCHDADCG,False +123,23.0,22.0,33.0,26.0,18.0,14.0,26.0,19.0,DGDGCACABHFCADADGHGEEHGACAHAGACEDEDEDGDFCHDECFCBCGHGECHCHBEEDEDEDEDCBGBGBABCBCBHAGDGECAGDCCCFCDCFHFDABECGBGFHBBFBEBEBACEDBHHCCGCDAGGGFCCCGDDFCBCBGBGHGHGCBADHFFAHDGAAAAABAFDHDHCFCEAD,False +124,14.0,14.0,13.0,14.0,9.0,17.0,19.0,18.0,DCBFBFAFAHBHGFBABECACGGBGCGCFAFHHDGDGEBDADFFHHHHDAABHFFEGAGFDBGHGAGBGHFHFGCHCDGEGEFCGDGDCDCDCECBFAFCFHAHEBEGHBEBHHADAD,False +125,22.0,17.0,18.0,14.0,19.0,23.0,19.0,20.0,AFFEGCACEHAHBHFHECADBDEDHDHDACHCBCBHFDDAGHGHCECEAEAHBHGGCEAFAFBDGFFFFBAGAFAFHHCGDFFAEBBABADADBCGHHHGACACFCFDFBCGHGEGEGBGBCBEEAFHEBBGGECEFECEHGGEAFDFDFAF,False +126,2.0,2.0,5.0,1.0,2.0,0.0,0.0,0.0,CBABCCCECEAD,True +127,9.0,13.0,13.0,20.0,8.0,15.0,15.0,18.0,GGEFDFEHDHDHBAGABBBFFHFCFHGHGHGHGDADHDEDFCEDAGAGCBDFDHDHCBCDFDBHFHGHFBCGDDDDDABGHDHCHAAECFBDBEBCBCEGECCFFHCGAGF,False +128,26.0,16.0,20.0,13.0,15.0,14.0,8.0,14.0,AFAFGCBFDCCGCBCACACAFACECBAFAFDBBABABHECBGAHADEDCBADABABAHEHCHCHGECDHDHBHBAEDEAEAHBGFAHBBCACACAFEDCAHHEADGEGECEFFFCGHDFDEAEFFD,False +129,3.0,2.0,3.0,1.0,2.0,1.0,0.0,1.0,AHABFBEAECCDC,True +130,3.0,10.0,5.0,11.0,10.0,4.0,3.0,9.0,DBGBHBAEDEBCCEBAAFHHDHDCBEDHBHBHBDECECEDDDFDGDFBEGEHEHF,True +131,18.0,19.0,23.0,22.0,20.0,20.0,15.0,23.0,FGBCAABCBCDCDCBBAAADCEGHAFDFEBHBHAHGDAEAEAHGECHCDDFDBEBHHHDBCFCABFHHHABFHHEGEHBAFAFCDCHGEGEFBFEFEDEHCHCHDHDGFAFEBEBGBGFCDCAEDEGFFFHFBEAGACFDDDDHDCCCCDCDGEGBGCEH,False +132,27.0,13.0,16.0,13.0,20.0,12.0,27.0,15.0,HAACDHGHEBFFCDAGADAEABAGHFHDHCCAEHFHBGBECGGGGAGABACDEDCACACFGFGFHBBEBHGGGDABGGGEDECEAEAEAFCEGBBBAGAEAEABHEAEGGGCEHFHDGAGEDEDFDHDEAAGAHAFFGCCCCG,False +133,5.0,7.0,9.0,1.0,6.0,7.0,8.0,7.0,BGCFEBHHHHACABFBFHFCFGGGCCECGCGCHAEBBHFGCGDAEAEBEF,False +134,14.0,15.0,11.0,16.0,21.0,17.0,16.0,20.0,HBHDHFHDDEFEGEFEBGDFDFBBHBAGEGCFHBHDADHHFAFAHECEFADECEDDDBDBDACBEAFHFHGEGCGDECECBAGACHBHGHFHFHGEGFFHEHCHCEGEGEAEGDGEABDBABFFGECABA,False +135,8.0,3.0,1.0,2.0,4.0,6.0,9.0,3.0,GFGEGHGFEFGCGDBAHAFDEAEGBGBAAAFAGAHF,True +136,14.0,29.0,20.0,23.0,25.0,22.0,18.0,18.0,DGDCEBGFHDBFBECHFEFBDEDCACGCGHEFEFEFAFGGGDCFGFHFHAHADEBBCBCEEEFEBABCBEBACACBHHCFCEAEAGBGDCDBDEDGBACECBHEHBDGDFDGCGAFEFDBHBEBEAHGFCFBFBHEDFDGDBBBBACDBDHGBEAEGFCHBHEHDHDFD,False +137,3.0,5.0,1.0,6.0,8.0,6.0,3.0,5.0,FDFDBBBEDEHEHEFEACFFGDHDFGBHAEAEBEGDH,True +138,17.0,19.0,28.0,23.0,19.0,29.0,14.0,27.0,EEHFCDHDHBAADFECECFFFCDGBAHAHFHBCDDFDGDADBCAAHABAEGFHFHDHDEGCGHGHCFDFEFGBHAHBCBABEEECDCDEHFHFBABHCCCACHEACHDGDFHFHBHFGDGDGDFBCDCGABFFDFECHCFFFHFCDGEFCACHCHCHEGACFCFBFEEECEBBBBD,False +139,18.0,10.0,15.0,7.0,19.0,9.0,15.0,15.0,BCDGAGEBBAAFCBEFDFHCAAHABFEADAHGCCCACEDEDEDEDEHCBCFEHCHEACACHGGGGBGEGFGFEHECGFEAHGHEHEHEHACAFBGGABABHGHEAEAC,False +140,12.0,11.0,10.0,15.0,15.0,9.0,10.0,21.0,GGDEDEDHDABGBDCAFADADEEFHFEEBBAHECFCAHGHGHEBBCBABAFHHHHAFADHECEGGBGECECHBHECFCDDDEEHHHHHDHDHDHFACGDABFG,False +141,6.0,7.0,16.0,10.0,19.0,4.0,7.0,3.0,GAGEECEDBGBGFCFCHCFBDBDECEAEDBDCHBEEFAHAEAEGCBCEADDDDEGCCEEEECCCECDCGCEE,True +142,17.0,14.0,17.0,18.0,21.0,18.0,15.0,9.0,BADAGADHDGDGFHFAFDFGEEDDDADCCCGGECCCGEHAHAHEEEEAECFCDHDFABABFBGBCACEFFDADAEEHBHFDFCBEBGHGCFCDAGFDBEFFGFGEGCBAEDEBCBAACDCBEBEFEFEG,False +143,1.0,3.0,4.0,4.0,2.0,3.0,3.0,3.0,DHDCCGCGAGHBBFEFCFDHDEB,False +144,3.0,1.0,7.0,1.0,1.0,3.0,7.0,2.0,CDCFHGGFBCCCCGAGAGAEHFGCG,True +145,3.0,5.0,7.0,4.0,3.0,11.0,6.0,3.0,DHGEGBGBGCCFDFAFHCBEBEBDFCFCFGFCCAHFFFDGAF,True +146,4.0,13.0,6.0,8.0,6.0,15.0,9.0,3.0,FABGBGFGFDBBBCGEEEEBFGCBFBDBCFDFGFGFAFECCDDADAFBDGHGBFBFHFEFHCBD,True +147,16.0,16.0,22.0,23.0,21.0,20.0,35.0,29.0,FBFEECGAGFGFGHDHDFAGEGEHFHFHFEGHGCEEAHDGDEHEGEFHFCFHGHBECDBDBHHGGGGGGCBHAHACAHAGEBDCEAGGHGHGEGEBDAHHHCHADGCFBFHGBGCHDFDFDGHCBCHHAGBEBDACHCFFGGGDADEEAGCEDEDCCCGDFDBDGFBFBGBDEACACDCDCH,False +148,16.0,20.0,20.0,23.0,21.0,16.0,31.0,18.0,EBEHGGGHCACFDDDDDAFCHEGCACFCFDFAGADEGGGAGEECEGEGEGAFFDCBHBHDHEGCDCGBGBGCCCCCBDGEBCGFHCHGHAHBBCEGEGEBFBGAHABDBDAGAGFGBEEEFEDGDAFCHBABGBADADEGFFDHDCFGGDHBFBDEDEDGHHHBH,False +149,3.0,7.0,4.0,6.0,10.0,7.0,3.0,5.0,EBEHEBEDCFCBBADCHFHFGBGBDEEEECHBDADADEFFFGFHE,False +150,6.0,2.0,7.0,6.0,2.0,3.0,8.0,0.0,DDDCGCADFDFGGGACACAGBECGGDGABACFCE,True +151,5.0,2.0,2.0,0.0,5.0,4.0,2.0,3.0,GAGAFBFEFECEFHABAEHEACH,True +152,14.0,12.0,9.0,7.0,12.0,11.0,10.0,17.0,FDHDFEHDHCFCBCDGHGCFFFBFHACCHBGAGAHEHEBEAADAHBGBFBFBABABAHAHEEAFHEHBHEHABGGECDCECEAGDHAHEFGG,False +153,19.0,24.0,27.0,19.0,23.0,23.0,26.0,24.0,CDCGGGFAAGACHFHDHDHBBCCHCGFAHABGBEDHBGBGBABADECFFFFAGGCHDDGDGCGHGHGDCFHDHAFEFEFEHDCCGGBGEGAAFCEEDFDFGBEAFHFCGEBCBHBFBDCDGBCBEHADABCHCHEHEHBHDGFGAGEGBBEBHDEEHAHAEAECCFFFCCCECECEFBFBDECBA,False +154,13.0,10.0,11.0,9.0,11.0,8.0,12.0,4.0,GEAEAFAGADADAEFCGCGCGCAFBFBEECEGADADACBGBCHHBFEECACBEHEFBFBDADEDBCGGGBDFHCAGGD,False +155,23.0,15.0,20.0,21.0,22.0,13.0,16.0,23.0,FEBEBEBFDHDHCCDDBCBEGFDFGBHCHFDAEBCBFHAHGHDADCBGDHDHDFCAHHHDBCEHDFDAAECDCDCBCAFEEEEEAEAGACHCEGEAEGGGGAEABAFAFHHGEAAACHFHAHFGEAEDEDEDADHDBCGAGACBCHHBGGCHC,False +156,1.0,2.0,8.0,2.0,1.0,1.0,0.0,3.0,CCCCCHCHBACDCBHEDF,True +157,11.0,6.0,5.0,14.0,10.0,10.0,2.0,6.0,EFAHAHFBFGGABADFCBEDEDADAHAFAHBFEDEDCDEDEDEDFFCBEDFDFBACDDAEHCHA,True +158,15.0,22.0,16.0,16.0,9.0,21.0,17.0,9.0,CFCFCAEBDGDHBBFBHCAAGFFFAGGGGFGHCHDBDBECECECFHBBCBAFHFDFBCACHCAAAEFDBDBCFGAADADAGGBBBGCGBGCFBEEGHGFGFDFDFABABDFHFDBDCEFEBGDDB,False +159,3.0,6.0,10.0,6.0,2.0,3.0,4.0,5.0,GGGFDFDBCBHBHBCCHCBCEHHFCACDCBEDDDACGCA,True +160,7.0,12.0,7.0,6.0,6.0,8.0,8.0,5.0,AEFEFEBCBADCEFHHCHGBBECAABFBFBDBGBHECGDADADGBGAHFFCFCGDGBGB,False +161,25.0,18.0,13.0,27.0,15.0,21.0,17.0,28.0,HFHGDDBDFDGHGADHGFBHGCFDAECCHHEFEFEDDBEBAHAHFHFBFHAHDFDFAEDFBBCEHADGFGAHDGDGDGDFCBCEAEBCBHDHDHAHAEADHHFHFHEGBHEDABABACDCAEFDDGFGAGABAHDHDGDGDBHBFAABAGAECECHCACBFAFH,False +162,18.0,23.0,16.0,12.0,17.0,23.0,24.0,31.0,AEABABCBCHCHCFFFBHHEGBABDDDDDHHFHEECFCFCBEDDBHBHBCGHDFAFHCHFGCHHHHHHHCFGFGEHDBAAEGGHEBBHGDAHFHBHBECGFAFBGCAHEHGBBFBDCHHGEAEHGFFFADGEGBGBGCGFFCHGEGEGAGAFABABAEAEGFGF,False +163,24.0,23.0,17.0,16.0,25.0,31.0,34.0,30.0,FHFHFEFGFBAEHHHDHDHFGGDGDGFGDHACAFGDGDECECHCGAHAHBBBBBFFFCGBGEFFHFEAECGGBBAGABABAFHFHECGDECFCHDBACDEHBFBHBFEFDDGCHBHGHGHBEAGFGCEHFBAHACEHEACFCFEAEGEGAGACFEAEBGGFDBDBGEGECEAHHHAGBGHAFDFAFDFGBGHGFGAGHEE,False +164,16.0,17.0,19.0,27.0,19.0,29.0,35.0,19.0,GDGBCCGCAFBFGFDHGHBFAFGFGDDECECDGDCDFHFGFCFHFEABACFHFBFHEEECEDFDEDGGGDGCCBBDBFBABFBGDEDEGBHBDDDGGGGCFHFGFGFHFEABBDCDCHCGGGDGFGEDADHDECEAGAFAHEHADAFFGGGCABEGHCAEFGFGAGDDHDHBCEHGAEHFH,False +165,10.0,7.0,7.0,12.0,6.0,6.0,5.0,8.0,DGFFDCDCDAEGDBDCEBGACECHCECDBABDEAHDHGAAHHHFHFBFBGBHDADADAFAE,False +166,17.0,18.0,17.0,16.0,20.0,19.0,17.0,15.0,CACAHAFBDAAADADHBGFAFDGDGDGHHFHFGFGFHHCAAEBFBFCFAHEBABEEGEGEGEBAHGDCDGEBCHEGDGCFCEEFECBCFHBHBHBADDFBFBGDCBCFFEGCAEGEFBACDCECECFDDADEEEGHBHB,False +167,15.0,4.0,11.0,15.0,21.0,12.0,17.0,17.0,HHAHDEDGHFHEHCHGFGFCECEGEACFGDGDCDCHADCEHEGGAEEBEBFHHHCHCHCFDAHAGDGFGDDHEEGCAEDEABAEGEGHGDDFAAEFGAGAEAFAFDFEEBED,False +168,8.0,4.0,9.0,2.0,9.0,7.0,3.0,7.0,ECECBCHFHCGFGFEEEHEHECAAHAFFBAEAFHBGAEAHDBDACCCFC,True +169,16.0,14.0,9.0,11.0,11.0,11.0,12.0,11.0,DFDFDGAGAGAGFGHHACBHBHGFFDFGBCEAHBDAEADACCECAAEABBHEAEAEDEDCABABCBGGGGFFACHHBDBFFDFEEGBCDHEHBHB,False +170,4.0,2.0,1.0,1.0,6.0,4.0,5.0,2.0,GGDBEEEEBEAGFFCFGFHAHAEAG,True +171,28.0,14.0,20.0,10.0,8.0,25.0,20.0,36.0,HCHCDCGCDAGAGHGBABAFAFCFAFDFGFGEGHFEFHBHGFGCHEHABFGFHHHCFDACHEFBHHHCHAHGBAADCHBHBFAAAHHHFEGCGDAHAGFBFAADAEACFFGAEAGABFCHCBFDEAGAHBHBAAHHHFHFHCCACGHGHDHDHCHCFCBGF,True +172,3.0,11.0,4.0,4.0,5.0,7.0,5.0,5.0,BBBEBHHCCFEFGFGHGBBBGBDFAFACEHFGFHDBDBABCDEE,False +173,8.0,13.0,6.0,15.0,4.0,10.0,15.0,7.0,ACDCGBGFFFGEGBGFHBHDADHDFGBGBGHCDAGGGCHDHGADDDDDDEBBHBFBFGFAEADGCCBDBDGAAEFBFB,True +174,10.0,11.0,8.0,10.0,13.0,7.0,14.0,11.0,GCGCGCGFGEBCAAEEHEAEHDHDGAADADADFBEDECHCGGGHGEEHBHAHABFBEBHFADGDHEECHBBFBGEGBGDCFBFD,False +175,23.0,12.0,12.0,24.0,26.0,34.0,26.0,24.0,CDBFHAHBGAAFEGHAFGCAFGFGBGBEBEAFGDGDFDADCFGEGBFCHABFCGADHFFEFHFEFEFEDHFGCGEGEAABEGAGHGEAFAFAFCFAEDEDEDHDHDHFFFGFHACEFHHHDHDAGFDFGEGBGDHDBABAFEEEHEBGFGEEAEAHHFDDDGHGHDFCFCACHDDEDEFHC,False +176,18.0,8.0,20.0,16.0,15.0,17.0,11.0,11.0,FCFBECGAFAFABAEEEEDCDAECEDGAAADFHBDBECEHEABABCDCHBGEHAHAGAECHHHADCCCCFCDCDAGCFFEEAFAFGDDFHFHFHDBGGDGDADFGCECFCGCDCFF,False +177,13.0,12.0,13.0,12.0,6.0,11.0,5.0,9.0,DABFHGHCBDBDCFFGABAFEBACAHECGDFFHFHFDFEFCHCBCBAECGCGCHEAEADDDBDADAHHBACABACDCDBFB,False +178,7.0,14.0,10.0,12.0,19.0,22.0,10.0,9.0,FDECFBFDFDFHFGCEDEDEFHGBACCEGGAEBEGABFDFDFCHGHFFEDBFBFBFEGEHADAEFEFEFEABCFHDHDAECFCGBFBGBFBEECECDBEBHGH,False +179,2.0,2.0,2.0,1.0,5.0,4.0,1.0,6.0,HGFEHEHEFEDAFHFEABBCHCH,True +180,2.0,5.0,1.0,3.0,3.0,4.0,0.0,0.0,FAADBBBBEBEFEFDDCF,True +181,6.0,7.0,5.0,2.0,1.0,4.0,3.0,6.0,BHBDBAAGAHCHFHACAHEHBBBFCFCACGGDBF,True +182,2.0,3.0,10.0,6.0,8.0,6.0,4.0,4.0,BCBCECEAEDEDHCCCCHEHEGDGCFFFAHGBFFFECDDECGD,True +183,27.0,20.0,35.0,20.0,19.0,18.0,17.0,19.0,CHCHCFCBDEHBHEHCCCCBDBAADFFECCGCAEAFAHCFGDGAGACABFEAHCBDBDBDACGDEDEDEHEBGDGDCAGABEBEAECEGAGFGCABFGFCEAEAGACFCDCFFGFEHBDBDECACAFHBHCHBHBFAHDBCADHEHACAGDDDGCEBFBFCCCCGAHCFCACAHH,False +184,21.0,29.0,29.0,14.0,13.0,23.0,22.0,20.0,HBBEFAHAHDHCHCGCBCAFABDDHDFAAADBDBEBCBCBEACGCGFFBFAFHGHFCFEHCHDADFCFCEDBGBCCFCFGFHCHCACBEAFBECFCDAGGCGFGHGFGEGACCDCBHBACGFGFHFBFGEGBCHCBCDEBBCHGGBGBDDFAAAEBEBABHBABHGEGBHA,False +185,16.0,21.0,7.0,5.0,16.0,12.0,3.0,15.0,BBBHGHBACDBEAAAFDHEHAGAGAEEEHHCAEAFBBABFBCECAFAFBFHFEDABBBFBEBEBEBACHFHFHDHBFEAEBHAFCHEDECEHBHB,True +186,26.0,34.0,20.0,22.0,24.0,21.0,26.0,17.0,HFACACHCBBBBHBGBEHFHFEAHAEAEFDBHECAHAHDDBGEDCBEGGFGECAAADBEBGCGCFCFCFBFBFBAGCBBABEHGCGCGFGBBCHCEDAHBCEAEHDBAHGGDDDDHEADDDDDFFGBGAGBGBEBABDBDGDGBFBDBDBDHEFEFCFEAAFGEBCGEGBFFGCGAABAGCHEEEAFAEA,False +187,3.0,5.0,0.0,1.0,1.0,2.0,2.0,4.0,DEBGHGAFBFHHBHBABA,True +188,8.0,11.0,10.0,11.0,8.0,19.0,14.0,12.0,HGFBFHFBFGGAHDDEBAHFHFHFCEGFGFGFGBGEGBCEEAFDBBBHFHDBDBGACHCHFGCGFGCGFBCDCDFFAEAHAEFDFDHAECDCD,False +189,24.0,32.0,23.0,32.0,21.0,21.0,20.0,22.0,BBBABAEECDDDEDEHEBECEDEDHHHFHFDFHCDAHAHDBGBGEGFGFGFGFBAGCGDFBFHDHBBCHGHGFAEBEDCAAGFDDADADBDCFGHBABDHECBDBAAHADAGCDCBABABGBHDCGCBCGFEBDCHAHCCCFCFEBABHDDBGBHHCCCGBABDBCEEGHAFEFEDDBAFFFDFDCEAEAEGDBD,False +190,13.0,10.0,11.0,9.0,7.0,16.0,9.0,11.0,AGCHAGCBAHCBGBEBEACADADHDBFBDDAGEFCFCBHDEFEFHFHGHDFGFACAEFHAEAGGBGFCFCFHFDFCFCBBFDAHAH,False +191,14.0,3.0,6.0,9.0,14.0,7.0,4.0,6.0,EAEFDGEEFCCCFCFEAAAEADCDAEAEGGAFHHHHEAAADADEFEBDBAEGECEADFDHDHB,True +192,6.0,4.0,7.0,3.0,3.0,3.0,1.0,4.0,CFGEHCCFCBCEAEHCHDADADABBBACAFH,True +193,29.0,36.0,21.0,12.0,18.0,14.0,23.0,24.0,BBHFFFCEHEGEHDHBGBHBHDEBHBHBEAEBDBFHFHEHABADACGGGADBBHHFBBBAAAAABECDCACHCAGACFCFAEAFAFAGGDAEBDBHBEBGACBHFAFGFGBBCAGGBGHDCBBDGEHEGEACACACEBEBCACAEGDGHCBDGHGHBBABCCHCHCHGBAEAGBFBG,False +194,6.0,3.0,5.0,1.0,2.0,4.0,8.0,5.0,HBHGGFCFCACAEABGEACDCHBGGHGAGAFHFG,True +195,3.0,6.0,4.0,7.0,9.0,15.0,5.0,10.0,HAHEHFGFHHGHGFFCFCEDEFEDBGBDEDACBDFHEBFHFHFEFDFCFDFABEBGHFE,True +196,2.0,2.0,8.0,2.0,3.0,5.0,4.0,4.0,CCECHCDCDCEBHCGEHBHGAAFFFFGFGC,True +197,0.0,3.0,4.0,2.0,1.0,2.0,3.0,2.0,DBHBDFCCCGCGBGEFH,True +198,9.0,8.0,9.0,4.0,11.0,7.0,12.0,11.0,AAAFADHGGGFGCBCBCHEGEFEHDCABDHGEGEGDACBFHFBEBGBECEHAHAHGBECFCGEGAHEHCHF,False +199,9.0,8.0,10.0,11.0,7.0,10.0,5.0,6.0,ACADDFDHDABGCDEBEHAFFBECECDBBABAFAFAEAFHDDDHCCDCGCGHGDGHFCBCBFFEFE,False +200,15.0,9.0,5.0,13.0,12.0,23.0,15.0,22.0,CHGFEHBDGDHEHAHDFDFAEBDAHEFEFEGGGGAAAGEDAHGHGHECEGFGFGAGBFEFAFBFBGBDFAFHDHBHFHFHGDEDHFFCFEDBDHFFFAAHBHAHFCFDHHCHAA,False +201,8.0,4.0,6.0,6.0,2.0,3.0,2.0,2.0,AGCFBBCBCDAHABACEHDADADCDADAEFGFC,True +202,15.0,30.0,30.0,30.0,15.0,29.0,25.0,23.0,DFBBDGHBCEDBFBHBHBCBHEGGGEBEBHHEHCFFHFGBHEGBDFDFGBGDFDFHCEFHCGCFDHDFDEHADADEBCFEFDFEFECDAAHFGDDDCACACACACDBABGGEDAABBBGCACABFBGDCDAGGGGDCDFFFGFCBBBDBDHECGHGDGCGCHCHFBFHHHDHCEBFDFDFCFCGCBCBCFCDABHCG,False +203,14.0,19.0,19.0,3.0,12.0,14.0,16.0,22.0,CHAEADAHBHBHBHBGGDBHFHEAAABCBGEFCCHFEBHCHABABFHCCCHBHAGAFCFBFAAAHCFCGEGEHEHEHFHBHEGFGHBEGGGCCFGFGCDAECGCBBGBFBCHCHCGBFE,False +204,9.0,15.0,19.0,11.0,9.0,19.0,20.0,15.0,FAAACCHEGCGDGBHDCCCEBAHDGDFDBDBHCFGFCFCBCBFGFGHGBFBHHHFHEGBGBCAEBCCCFCFCHGAEFEAGCDHGHGFGFGCGBGBGFDACEBFDFDEHEDGHABFHF,False +205,20.0,16.0,16.0,34.0,30.0,20.0,29.0,29.0,CDCFGDGDEFHGHEHEGGBGBGBHBGEFECDCEBGDAHGCBDDGDHDHEBEDDDDHAFAFDEGCHEGFHFADBEEGAGDGDHFHBDEAEAHAHDDDECGBADEHEFEFDACAGEGFGBDEDECHHHEAEFFBADDDDAEAHHDHDCCFCAAAHCFCFEGHHHHGBGBDCHCHDFDGGEGBFBGHFAFEGEGEAE,False +206,20.0,18.0,16.0,14.0,21.0,4.0,6.0,11.0,ABABAFADEDBAECHGDDAAHEBBDBACECGAAAACHEFEBCDHGBCECECEBEFEAECBCEHEDGAHACADAHACECGDDEEECEHHHFECBCBEBHBDBDBDBAGDBA,True +207,1.0,3.0,2.0,6.0,1.0,4.0,1.0,1.0,FCADBDBGBFEFDFHCDDD,True +208,5.0,3.0,5.0,6.0,4.0,0.0,1.0,2.0,DCCBCDCDCAAAAHDHBGAEEDBDEE,True +209,9.0,6.0,7.0,6.0,5.0,8.0,3.0,2.0,FCFEAEGDADABCBCFGAGCFAFABABCBDHCFDFEFEACBDHEAD,False +210,21.0,21.0,15.0,16.0,11.0,15.0,20.0,12.0,CACFFACCCEHFDBGBGBFHFAGDGDADACGGDGBAACABBECECEGEDHDHCABDFDFDAGHGHGBGBFBGEGBFDFAGAEHFDAHEGABABFGAGEBCCGCHBDEDGBCACFBFAFHDBEBHBABADAH,False +211,10.0,24.0,13.0,13.0,14.0,11.0,16.0,23.0,EDEABACHGHAEGGBBBBECECEBBBAHGHGHCBCECDCBFBHBHFHFHFBBDAGFEBHAHDHGCFAGABCDDBEBEDHGHBCCACFDDBAHHHGBGBGEGEGHGFEFHHHDDBBCDEFGFHDH,False +212,19.0,7.0,17.0,13.0,17.0,11.0,21.0,24.0,FGCAHAHFGEHAAAAAHGDGHGFEEGDHHAEAEDCDFGBGDHDGFECECGGEEHGHGHCFBBHBFEEHGHGHDHFHDHDAAAHDECAAACBCECACAHFDFCCCCCCGGGGGEEEDHBHEFCGDHAHAB,False +213,10.0,20.0,7.0,7.0,13.0,11.0,10.0,5.0,HACBEBEBAGEEHEDAFABBFEEEBGBGBGBAAEBBDDFDFDFHCHDDAFECHBBAFAGGGFAFCGBEBEBEGGBFFCBCBCB,False +214,6.0,9.0,11.0,6.0,13.0,4.0,11.0,19.0,ECECBCFDGEGBHEDDHGEBHHGCGCBHHHHHEHEGACABADHFFGCGBGHDDCEEEEBEFHAECBCHGHGHBHAHAHC,True +215,3.0,0.0,0.0,3.0,3.0,2.0,6.0,5.0,HDFDHEHGGGGHAHAEGEAFDG,True +216,1.0,8.0,11.0,12.0,14.0,8.0,9.0,12.0,GEBDBDCCADDBGFGFEEGEGCDCEFEGEBEDCCFBHCEDDGEHEHDDFCHHHBHBHBCDFDEGEGCHCHEHFHF,False +217,10.0,10.0,22.0,13.0,14.0,8.0,15.0,10.0,DCHGECECEAGHEFGACFBGBECGCAEBEHHAGEGFDFDFHEDDCDBFBABACDDHDBDGCCCGHGACFCFDGCGCBCBGAGACECACBCECGDHEHEHECD,False +218,7.0,10.0,14.0,5.0,9.0,7.0,7.0,16.0,CFCECECDHHHHHHHHBBBHEFCCEBDBABAGDFDHCHGACCHCHEFEGHGDACFBGBCEEEFGHGFCBCHAAAB,False +219,15.0,20.0,16.0,12.0,13.0,12.0,14.0,14.0,AGAEAEAHGHFBFEHBHFGGEEHCFCDADACBDBFBCBFGFBBBCCAEGDGFAACAHBCBCDAFHFHECAFFEGEBCBGGCDCDCDEBBDBDBHHHHHDGAGDCHCAGEGABBEBE,False +220,0.0,1.0,1.0,0.0,3.0,3.0,1.0,3.0,HEHEHFFFGCBE,True +221,4.0,7.0,18.0,11.0,9.0,20.0,14.0,16.0,GGGBFCCCFBFDGCFCFDFHFHCDCDHHHGHFDCAGHCBAEEFEFEFHAEFCHCGEFCCCHCHEHCDCDAGBGBGCDDFDFGFHEHDHFGEGFHFGFBB,True +222,19.0,32.0,14.0,24.0,24.0,23.0,30.0,29.0,EAEAGFDFDCBHFAFADGBHBDAGCDEABDFGEEFFFEEAECHDHBHDGAHHGBGBGBGHCDFDBDBDEDADHFFAFEFGBHBGDCHEDABGBEBCDCHCBFAFBGBAHFHFGEDFHHHBBBBDBDBDBGEGBHEACCHEGEGEDEHECGHGFBHGHCBGAGHGHGEGEGEHAHAHFCCEFHFAGBGBGDADFBB,False +223,6.0,4.0,7.0,6.0,14.0,14.0,8.0,15.0,CEEFAGEBDFAHHDHFAFAHBFFHFCFEHHHHFDEGEGEDEDGAGHDFGBGBEFGFHHCHCHEHECFCACEEFE,True +224,11.0,10.0,13.0,13.0,21.0,14.0,25.0,19.0,CGBAEGEGEHHCGGHGCCBCAEBEGHCHDFDFDFEGBDFDFEFAGDGAGEGCGBHEEGCGBEEGEADACECABEDCDFFFDCAGAGHFHAHGEGEGEGBGBGHHHHHHDABCEDHHFFDHEHEGFF,False +225,6.0,19.0,5.0,11.0,12.0,6.0,9.0,5.0,GBHBDBABHBCBDEDBGBGBEBEBCCFDHDFEBBDDEAEAEAECFGFGEGABCFGBBDHDEFBGBGEEABHDD,True +226,11.0,18.0,23.0,14.0,12.0,26.0,20.0,26.0,EFEFEFGDCDFBHBHADECHHEHEFGFGHCBGACBGACFDFGFCFGFCCCHHHBHFHFHDADFFEBGFFFFFDBCCFCFHFCDGEHDFDBDCAGGHHHHHHBACGCGAGBGHAAAFFCHGBGCADGBBBCGDHEBEBEBEBHCHDHCCCG,False +227,23.0,20.0,28.0,18.0,25.0,23.0,23.0,21.0,FCCBCEFEDAGGBEHCHCHAFCCADFFHFEFAHCHDGCCHAEDEDFDGAGAGAGEFEBEBHHEFEFHFCGDFBGBDHAHBGAHFFFBFCDDADCDEEAGABHBHGHCHCABADABCHCHCDFGHGHBAFFEGECBGADCECGCGCBFEFDFCGCGDEECAGAEAGAGBBBBBCEEAEDECE,False +228,5.0,3.0,9.0,5.0,8.0,2.0,3.0,5.0,DDDACEHGFBCEAECCCCCFCEHEHEHEBCDAEBDHAGAG,True +229,15.0,19.0,18.0,23.0,23.0,15.0,10.0,23.0,HHFHGHEBFHHBCBDEEHCBGBAHAEDEDCGCGEBBDDDDEDBDHDFDEDACCEEDFCEEECBCBCBCDAFEHCFAHBEDACAGHHHHHHHAHGFACACAFBEBEFFFFFDEBEAEGCBEEDADACBHGCGBGDHDHDFDHDEABF,False +230,15.0,10.0,14.0,14.0,7.0,9.0,3.0,6.0,EDADBFADCDCDEBFBFAFEFEDCBADFBFBAHACCBCGEHEHBCCAGDCFFBAAABAGACHCHDDCCCEDHDADADA,True +231,21.0,19.0,19.0,16.0,21.0,13.0,13.0,23.0,EHBFBHBCDAEACABABEHCAAAAAEBDHDCECACAHGFCFBFBDCCBDBDECHCGCAAHHDDCDCDEEHHHADAFBFGFGDGFGHGAGEEFEHBBDBGHAHGHEBCCACACGEDEAABDBCEDEFEHBHEEEHGHFHEHFFGHB,False +232,10.0,11.0,13.0,7.0,8.0,12.0,12.0,9.0,EFGGGHCHBAEHFDFEADAHBBFBCGFGBCBCBCFHFAFAGCGCEBEDCCCHCHDGGGCGCADFEBEBDAFAFAHEFGBHDA,False +233,16.0,18.0,26.0,21.0,12.0,11.0,22.0,9.0,GBGCHBGDHEHDGAFCFCGCBBDDDHHGCEDEDCDBGBEBCCCCDBGBCACBGGEHEDGGAGACFCFCHCGGDGABDCCCGDBDEDEBBCHCDCDBDAGECECAFEFBFEAGAFAGBGAGDDDACAFAFAFCHBA,False +234,8.0,5.0,2.0,10.0,3.0,5.0,9.0,5.0,GAGBBEDFDFDBDGDAEADHGAGHBDGDFDFCGAGACABAGHHHFED,True +235,28.0,16.0,21.0,19.0,24.0,21.0,12.0,20.0,EDHFBEAFADABHFHFCFHFACCBBBHAHDHBADGDBCBDFEFDHHADACBHBEAEDDDGAGACAEHECFCECHHHEABFCFEEHGAFFFADADCDGEEEGEBECEBBCACAHAHADADFFAFAFHGDEEFEBCGCGCGCDCAHBGEEFGADECECAFAHA,False +236,13.0,6.0,14.0,8.0,9.0,13.0,7.0,14.0,FCFAFAFAHAHCDCDGFFEFECEDBCECDCFHEEFAFACHCHCEBGDHEHFHAHBHDHFCGGAGDHHACCBHDCGFGBAAEABA,False +237,4.0,7.0,4.0,12.0,6.0,4.0,7.0,10.0,DGGHBHDDDGDGCGCGADBHEDEDAGFCFEBDHDEBAHAFEHEHCHDBDBHFHB,False +238,25.0,27.0,17.0,20.0,11.0,20.0,27.0,24.0,BGGGHACECEFEAEDBDBHCGDGDHDHBHBHAHAHFBFGCGCAHFHABABEFFDDAAFHFHDAGADFDGBACCCHGHDAACHCHGBEBCCCBDAFAEGHAHGHGEDBDBCBHBGFEAGAGBGBABDHDGAGADFBFGFGCAEBGFFEHBBGDGBBBFFHFBFCDAGCGHDA,False +239,27.0,19.0,14.0,12.0,26.0,20.0,17.0,18.0,CACHFHBABHBABAHEGBDDEBFAFAEACABAFAHAHGHDFEGEFEBEBEAFCDCHABAGEGEDFBGBACAFDCDCAEHEHFHFEEEFABABCGEEEGHDHAHBHDFGEGBAAAFDHECEAGCGEBEDCDHFAFAGAGBGFFCGCEHGFEBEF,False +240,13.0,5.0,13.0,8.0,10.0,9.0,13.0,11.0,HCHAGAEFGBGAGFGCDCAGAECGCGEFEDHGFADADACHDFDGBCBCFEDEFEFBAHHHHHHAAFGCECACBCGEHEADCG,False +241,15.0,13.0,22.0,21.0,14.0,24.0,13.0,15.0,CECEBACABEFHFGBEFDCDBABGDAEADCDHGFGFDDDFDFDFGFEFGCGEAHGHGHCFCDABFEHHABCECBCHFHCACFBFBHBADFEFEFDFDHDHCHCDEDAGGECHAFDHCABFCFDFDGBGCFCACDCEA,False +242,10.0,3.0,9.0,4.0,10.0,22.0,6.0,6.0,CBAAFFFFGBDAFFFFFFFDGAGEHFGECEFEFHCHCEEEDCFAFAHAFBDEHGHCFEFCFCFEAAFAGC,True +243,16.0,18.0,13.0,25.0,8.0,14.0,16.0,17.0,CFHGHAFGFCFEDAGEBBFDGBGHDHAHBGBGBDCHHEBDBDBDCDHDHFAGGHGHABADDCDFBHAGDDDBCACECAGEGDDHDFDFHFHCGCGCDBAFAFDBDEFEACADADADBCFAHBHGEBB,False +244,14.0,10.0,26.0,18.0,17.0,28.0,19.0,21.0,HEHEHDFDFEGEGFGDCBBDAFHFHFDCEGBBDHFAGBHFHCECHCGAFCCDDADGHGCGAGBDCDHDHDACFCFGACEHEGDGFCFCFCAEFHHHFBFDFDCBCFEFCDGAGDEEFEFHFHFEECCCAAABECFHACECFAFGFCBCGHGHG,False +245,30.0,27.0,23.0,25.0,28.0,19.0,14.0,26.0,AAACACBCAEDEBEFCCHCAEGEDEFGAGCEAEADFEBBBEFAGBBBFDAEAEHHHHCFCHCHADFDEBHFACBFBGBFBCHHAHAEEGHHEAEGHGHGHGCAHADADAEAEAGDGBECHDDDDEFFDCDCACAFBFHCHEHEADFBFBGBDBCGABHBHDACCECDDBDBDFDBEEEEHCBAFHHDBBADF,False +246,9.0,17.0,16.0,9.0,17.0,6.0,11.0,16.0,HGEGACAHDHDCDEGFHBHDHECEDEDFDEEHCFCFHBEGGFABEHHHHGAABCCDBEBECHCHFBAHGCGABCBEBECCCCCEGEBBBBDBABEBHGEGA,False +247,10.0,6.0,15.0,20.0,23.0,16.0,16.0,6.0,AFDGEGEFEDCDFHEGEGFGBCACECEAEHEDDHEGEDEFGDDDCCCCGAGEDBABEFEFDGDHDGDCBHBGFFCFCEEEEFCHEFGDGFCDADCFCAEGFGBEFDADADAE,True +248,1.0,1.0,5.0,2.0,5.0,7.0,7.0,2.0,EFCFDAGFCFGFCHEHECEGGCGDGFGFBE,True +249,20.0,25.0,23.0,25.0,18.0,22.0,28.0,20.0,DGDBDAABACHGHEBDCCABFBAHGGBGEAAGDDFGFAHADADEDFHFHGGGFGFDHDEDBACDGDGBFACABBGBGEGEGECFFFEABDEDHFAFGBCBCACHHFHFBFBFHCHCHCECDGDCEHEGCGBBFBGEFEFHCGCBHGDGFHFEABCCEBDBHGDGDGBHCEDADCDCBAEAC,False +250,27.0,24.0,20.0,16.0,26.0,17.0,25.0,11.0,CHCBCACHBABAGHFEEBEGECEBEBEACDGDHHGAAFGEGABEGAGEGADADABAECFGBGAGAEBEADFGFECACGGFGEGDGFBFGCGBFBFEAEBEFAFAFEDEAAAAGBBBCDCDGECCCBCFADABHDEDEGEAHHBDEDFDFGCCCDBBHAHGBCBEHF,False +251,23.0,19.0,20.0,25.0,22.0,22.0,28.0,26.0,ACACGEBFHHCAGAGHGHGCGCGBEHFHFCAGFGCGHEHAHADDDDAEEEECCFBGHAHAHGBDECFADGCECEGEGDGAADBEAEFHFDGDGAEAFDECBGECCHDEEBGBABEHHAFFFFEFDADHBHBDDGGCGCBAGAHABDBDEFEBCBDHGHGFDFDFDFHBAFCBDBDFFGGCHHHDH,False +252,22.0,23.0,23.0,11.0,21.0,24.0,27.0,23.0,CGGAGEGECECECDBFFFHAHGEGCGAGACEDBBBFGFGHGHFCBGHFHBHGEAHAHABDHABABDBECHAHFCFEFAAGGGBGFCDCBEADADHFHDHCEABCGGGFGAHEEAECCCCGBBEHEHBHBHDCDFFAFBFCEBAGAGCCBCAGFDHHEHFFFCFEFBBEBFGEGA,False +253,21.0,15.0,11.0,10.0,10.0,18.0,15.0,19.0,CFCEEFHBGDEEFEFDAGAHAHGHFHFHGHAHAHGFFFGBDBGAAAABABGBFBFBEACGCEDHFACCFFFGECBAECDGGAFAHDHDHBCCGHAHAFAEDHDHGBBABDFCAGABHBH,False +254,16.0,7.0,14.0,11.0,13.0,17.0,11.0,13.0,CDFHFHECACEDEAECCHFHFHGHGCAHAGAGDEDFDCHCFDADFEGAAEAFFDEDCCEDBFCGCGEBEBHGAGFBABAGFHDHAHAEFFFFFBEBCGHACA,False +255,14.0,24.0,17.0,17.0,23.0,22.0,12.0,11.0,EDGFFFGBBBCACDDDBDCFCFCEEAFGFGFGFDBBBFBDCFEFADAHEDBDFHAAGHCHFGACABEDEDEAECEFEFDAABHHAHCECBFBCBFFDBDGHGHFBCDCECEDEAAGEGFBEBCBEEGEBEBEBHCEFBBH,False +256,15.0,18.0,13.0,27.0,17.0,28.0,20.0,24.0,FBDBCHCGDEDCGAGAGDDFBBBFFFFEDACGCHAGGGEGEBABFHFEDHFHFCBDGHGBGDHBCBGAEHFAFHHHDBDCHBFGFGFHFHEGEBDFFFHAHGHCHAHDHEBEFEDGDGAFABDBEHACFCFCEDADEFBDDEAEADFDFHFHFDGHEDDDDC,False +257,6.0,7.0,12.0,13.0,9.0,11.0,8.0,10.0,DDACHGHGHDHEFCCEGEGACCDCDCDADHBFEFEDEGCFBFDFBFEHCHDAGEDECBCBHFGFDFHAHCGABDBF,False +258,17.0,20.0,27.0,16.0,18.0,18.0,19.0,20.0,AGEHCDAGCGFGDCDCHCACDFEAGFGAAAADADCCHGHGHCCEEEGCADACAHECEGDGFBFBFCHCHCBBDBDBDEFCGCBBBEHFHACAGBCHFFBCBCGGGGHDBECEHEHGHBCAGEDEBFCEEBEBDFCFAFHBADDHFHFHFHECFBB,False +259,1.0,5.0,4.0,1.0,1.0,0.0,6.0,2.0,GGGGBGAHBHCGDBECCBCB,True +260,2.0,3.0,4.0,1.0,3.0,5.0,1.0,3.0,BFBCBFHEEGEHCACACHFFDF,True +261,2.0,4.0,3.0,2.0,3.0,2.0,6.0,2.0,CDCABEHHGFGFGEBABCBGDGEG,False +262,17.0,17.0,32.0,25.0,20.0,22.0,15.0,15.0,DHDCDCDGEHCBGBEBACGDFDCBCFCBCEAEAFCDEBAAEADHCEAEHECDDDBDCDBBFFEFGFBCBHAHFCCECGHDHFHAHACDEHECFCDEAAHABBCHGEGDGFHDDCDGDCCCGCACACFCFDADFGFBFBFEGEGEHDACGDFCFCFGBEBEFCF,False +263,7.0,4.0,7.0,4.0,5.0,5.0,7.0,12.0,GCACAHGHECGCHFGFEDHDHDHGHBAEAHBHFHGCCBCHEGEBHAFADAF,False +264,6.0,6.0,13.0,6.0,11.0,2.0,9.0,8.0,DCFBDBEEEEEEADAHGHGCGDHCHGEACBCGCAHEHGGAFAGCCCCCBEBHDCBCEGEHD,True +265,20.0,25.0,22.0,32.0,26.0,23.0,23.0,27.0,DCHBHBCEHHGHDCGCAHHGHDEEHEHBBECDCGBBACACADDDDDFCGEABGBABEBEBEACFHFBEGHFBABCGHGEGDDDEGAHAEFBFDGDHBFGFCDCDCDFGFHEBEHEHBDEAEACBDADHFBDDDDAFEFBGGGGHGHCHEHFCFGFGADDDDBDADHFEBEBECEADACBCFAFHFDFGFAEGHHCCFE,False +266,7.0,6.0,7.0,3.0,4.0,2.0,13.0,8.0,BGHCABHHCHGGBDBABAFCGEGDGAHCEEGEGBGCAHAHACGCGHGFGD,True +267,8.0,8.0,22.0,12.0,15.0,14.0,10.0,10.0,DCBAAGBEBEHECCCCFEDDDFGHGDEDCBCGEGEGEBFFAEHECFCHCHFHDCDCBHGGCCBCFCHHFAFGHGDFCEADCDCDCEBFAFACECAFEFE,False +268,20.0,11.0,17.0,15.0,11.0,11.0,19.0,11.0,FACAFGDHCEFHAECBCBEBEAEGBGBGFHCCBCAHDCFCDGDAEEEFBACADABACECHGGDBDGGGFHEHADAFGFGFGHGHGCFCDCDEGAAAABDDDGHBACACDGDHAGA,False +269,6.0,1.0,7.0,4.0,8.0,4.0,3.0,3.0,DBGECEAEAEAEAGDGFCHCECFAAHHFEFCCDEDC,True +270,18.0,16.0,20.0,26.0,19.0,21.0,22.0,23.0,BFBCDDGAGACDBDGDGDADHCAEACGCGDEBGDFDCDBDGHEHCFFFFFHFBFAFHDDGBHHHHFEFABGGDGDEFCDGHCHEFCFHBADHHCFCBGBFEEEEEFEDEDAFGHGDGCACDEAEACDEDHBHGHBHBHCDGAEACCEHGHAHACAGACBEBGFDF,False +271,0.0,3.0,1.0,4.0,2.0,4.0,2.0,3.0,HFHFEFDBEBHFDDBDGCG,True +272,16.0,16.0,17.0,14.0,11.0,14.0,8.0,16.0,FCHEHAFAFBFBDHGAFABBCDCDHBHEFABCHCHDAGABEBAHDHDFCEBGDFECECECEHECACDBDBDCGAGAGACAGBFBGDDACCDDBHEHBACFBFHHHFHFCFAE,False +273,13.0,11.0,14.0,14.0,11.0,17.0,18.0,16.0,CDFDGBHBFGFGFGEDABABCHHDDEDCHCGAGFBFDADHDCDCECAGEFEBEAFAEHEHGGEFBHCHFHFAFDFACGGFGHHDHGHAHCFAFGEBCBGBGCACDCDEHGFBAG,False +274,30.0,26.0,12.0,16.0,14.0,36.0,17.0,16.0,GGHCBABACFGFHFBBHAEAEACADADABABFFDABBFFEFBAGFHFBFCFBAHHHHGGDGFGBHBFEECEFDCHCHBHGEAHADDGAFAFDDBDGFGBEFFFFFGFACABGFFFAABAFACAGAGHDABABGDACFEAEADBBFBEDEAFFBFBFCFCDBHEHEDF,False +275,6.0,13.0,13.0,9.0,7.0,9.0,12.0,6.0,CEFBGCCCCHDBDBCAFDFDFGFHHCCGCGBGDGDBCBCBHFGAAEGBGBFBGBGECHCDAEGEFADAHEDEBBF,False +276,7.0,5.0,3.0,5.0,6.0,7.0,3.0,5.0,BCCDFEFEFEBADABCFDDHDHAAEAGFGFHFBAEAGHBHE,False +277,6.0,5.0,1.0,2.0,3.0,3.0,6.0,7.0,HBBFBFDHCGEGAHAHGHGFEBHBGGAEAHADA,True +278,4.0,8.0,15.0,16.0,12.0,11.0,10.0,10.0,DHCHAEEEHEHEFEHGFBHEDEGEGFCDCFCGCDCBFFFCEGDBHFDDADGGCGDEDEDGACDCFCFBGBHBDBCFCHCDDDHCAB,False +279,15.0,15.0,14.0,9.0,20.0,30.0,10.0,19.0,EAFFEFEFHBHBHBHCHCFAAACFCAHGBGBFEEBECEGEFDCEFEGCBFHFBEAFDBBGDDCGFDCBBHBHFEFEHCHFBFDGCHFHFHFGFGAAAAEECEFDBEFECEHDFCFHDHFFEAAAAAFGFHFH,False +280,20.0,27.0,17.0,23.0,26.0,20.0,26.0,25.0,AEDGCEBACABABGBGFDCEBHBCBCGHBAEACBHHHCDDEGFHAAFABCEHDBDBDFFGFCBGGGFGEEFEDEAEDEDHHHFHEEEGEGCBCBHBEBGBGECEAEHGHABBBFHEAFGBGDGFFEFDGDGDGHGDAFAGDHDECEHHHAHDDGHGCGEBEFABCBDBFCFCFHBADADFDAHH,False +281,10.0,6.0,6.0,8.0,8.0,11.0,10.0,7.0,GBFFDHAEAECDDBEGDGAEECGGGDHDAFADAEAHBHDEFFFFBCBCECAFABAHGFGFGFGHCH,False +282,21.0,33.0,19.0,20.0,21.0,12.0,19.0,26.0,CAADABABCEABHBABDCHEAEGHBBCCCCCHCBGGGGHHDHGHGDGDGDBDAAGCBHDFEEEEEEBEBAHHGHEHCCGHFBFBFBFGHBDBHAFAGACCHAHFBCCFDEDEHCHABDBEGADBBCBHEHEDDDDBDEDBBHAHBEEEDBBBBHGGGCEFBFAFBGAHAFA,False +283,12.0,9.0,6.0,10.0,12.0,16.0,15.0,10.0,CFCEDFGCGFHFBGCGFGABEGAGAGAGAFADBHGHDEFHHDGCADEGBBCHDAAAGEBEBABFDFEFEFHFHFHFHGBFEGEDDDEFEA,False +284,0.0,7.0,2.0,2.0,5.0,4.0,3.0,5.0,FBBHBHECBFDFGEHCHEHEBEBDGFGB,True +285,18.0,10.0,10.0,8.0,8.0,13.0,19.0,13.0,HHHFGFAHCCBCHCBFAGCGBABDBDGAFDCDAEAEHDADBHBAGFGFGHEFFGHGHBHAFFBFCFCAAABEEEAGGGAGCGFGAGADAGEHAHCDGEG,False +286,17.0,19.0,13.0,13.0,17.0,16.0,12.0,9.0,DBDADABCGDAFEFEFEDABCBEBGDGFEBEBEBEADBDGHCADABFDADADABGFGFCBCDCFBGGEEFCFAFEFBAGGEFHCGAFAHBHBFFEBACECACBCHAHEHEHCGBEH,False +287,11.0,13.0,8.0,14.0,5.0,10.0,1.0,11.0,ADDCHBHFDEACFDBDBABCBCDDDBAAADHFBFBABEHEHBHBCCHFDABAHCDDDCDAFHFEFEFHFHGAB,True +288,21.0,32.0,21.0,22.0,23.0,17.0,23.0,21.0,CFCBBDADEDEDBDHDADCCCEHEHBFBHADADBGBGDCBBHFAEBDHDFDFBEBHDEDBCECEGABCFGFHDHGHEHAAGHGEDEAEABGFCCBEBCFDFAEGGAGADECFFGFBBHCGEBEGAFABDBHFFAHAHAHBHBEBEBCBABDEGCGCHCHBHBGEGEGCAAGGBBFCCGDG,False +289,10.0,13.0,5.0,12.0,9.0,19.0,21.0,12.0,GBFAEDDDGGFEFDHHGHGFGFGDGFGHHHHEGDBHFGGHECBAGAEACFBBDBCADFGEGDBBBBCBHHFFBFBFDAAAEFGFAFAFDFDFHGGGGGECE,False +290,10.0,11.0,9.0,13.0,3.0,16.0,8.0,5.0,DBDBDCFFGFGABEBEDEFFGFGFAFABHCAFABCDHDADAHBGBDDDADFHCBCDCAAGHBFGFGFCCBFFCFD,False +291,22.0,19.0,25.0,28.0,18.0,24.0,23.0,17.0,FCFEFEFAGEGCGEAAAEGEHFHEGFGDGDEDBDEEECBBBEDFHFAGHCAGAFAHABFBFDDGECEBGFDFCFCDBEFABGEDACACDHDHDFFCDCACHCDBBGCDBHBHCFCDHHHBHBGFGFADDGDCDCHCDCACAGAGCDDABCEGHDHFGGDDEAFBFACACABGBGFD,False +292,22.0,21.0,17.0,19.0,16.0,16.0,15.0,29.0,EFHHAHDCDEBEHEHEHEHEHCFDBCBDHCAFEGGHDDBDFGFGHCFDDDDAFADCGCFDFBFBHGAFCCBBEEAAGAGDEDAHAHAHBHBHBHEHCABABHBCCCHCBBBDAHGFDEAEAFHGBGEHAFBGHAFAFAHABCDDECGCHHGHGAB,False +293,14.0,10.0,22.0,19.0,17.0,10.0,11.0,13.0,FDGGCACGCDCACBCDCDGHHDHBHFGGCCFBFBCBDFDAGEHAHEFECBHGDDDCEBBADCDFDADEEEEDEBHAHAGCGCBDGECEHEHAACADAHFHFEFCCECEDECCDAEA,False +294,21.0,23.0,11.0,16.0,19.0,13.0,19.0,13.0,ECDFDEAGAEAGHBFEFGHBBGBABABGDGCCAGHBHFEFGGCBDGDGDGHFHABAECEAGHFDFEFBFECECEFDHGFGABAEHEGEBBBBEBADFEHEHBDBDADADGBHADADHGAEBBBDCACECBCAAGA,False +295,16.0,21.0,15.0,23.0,14.0,18.0,17.0,12.0,DDBBHFDFGBGBHBFFFFFFFGEBCFCGHABBEHDDDDBBBBDGFHFAEDHDHCFCHCECBAHACDCDHAAADDECACAGABAGEFEBCAEACGDGFEFBGBDBCBGGDDAEFEDGCGEGEDEDGDBABADFHCHG,False +296,2.0,5.0,5.0,3.0,8.0,3.0,7.0,5.0,GHDHFBBGGCGBHEHBCACHCGCGEEEEFDADBEGEFE,False +297,8.0,7.0,6.0,6.0,3.0,4.0,7.0,7.0,GDGFBFEFAAEBDBDBAGAEHBDBHCHDGBGCGHGHAAACHCHAFCCD,False +298,10.0,8.0,9.0,8.0,12.0,10.0,12.0,8.0,AAAAAADGHGAEEEHFHEHEFFAGAFHCDCGEBCBCBFBFAFHFGGCGHEDGDFDBGEDEDCBEGEGHCBEBCCDGF,False +299,2.0,2.0,2.0,2.0,1.0,0.0,0.0,1.0,CHCEABDBDA,True +300,21.0,16.0,12.0,20.0,12.0,15.0,16.0,21.0,HFHGDDEFBFBFAGCFAGBGDHEHBHBHAEFBDGACHGHAHFFDFHFHEBBCBDBDBCFCDCACAEDEDHAHBHECABAGCEBHBGEDEGAAHAFAHADCDEGEGADFGAGAHCDAGADAHCHDDGDGDHFBF,False +301,18.0,17.0,21.0,18.0,14.0,17.0,20.0,23.0,BEBFFCAGAGAGHGHFHDHCFDFDEDEBEBEAGFBCCHCDCBCHHGHEACAEFGBGBEDEBCDADHFAADBHBHCHFDFDFHGBGBAEFGFAAEHEHEHCCGHDDDGHCCCCAABCGCGCADACABFEHDBCFHGHGDAHHDFGBGFG,False +302,17.0,9.0,16.0,15.0,18.0,20.0,16.0,20.0,CFEHGDGCGHFADAFGFBFHABACDEDEDGAEHEHCCCBCEFHGHAEAEAHAHEHEHCDFFAHDEAFDFGBGDHHFHFAGGFFBEHEAEAFFFDGBGCGEECAFFHEHEHDACBCFCDDDDCBCBHGAGCG,False +303,17.0,9.0,12.0,14.0,11.0,11.0,11.0,15.0,DFDFAGHHDEDEHEHECGFACAEADDHDEDCHCECFHBBBEGHBACGGGAGAHDHAAADEHEAFADGDBDFHFGBABABHBFCHAHACCFCGCEADFCFG,False +304,32.0,22.0,21.0,20.0,17.0,21.0,22.0,16.0,HABACGCBCGHGHADEGABAFHHGFCCGFFFHFHAHAGACFGEEAHAHABABFBAEAEDGDBDFFFFEGHGDDDCHFAFGECACECECEDFBEAAFBCGAGECECFCFCBGGADADGHACAEBHAHABGGDDADCDADBBBGHEFEDDDGEFBDBDBCBABCBAAAACFGB,False +305,22.0,14.0,10.0,9.0,20.0,15.0,19.0,12.0,GAGABHEFGHGABAEDECGAFABBEFEAECCAAHGHBEEEEEFHFGFGAEAGAGDGHGFAAAHAGAGFBECEFFBBGHGFCBCGCADEDBDBDBDFEECEBEDGAAEAFAHHBFCFCDHGH,False +306,7.0,13.0,6.0,7.0,4.0,5.0,5.0,12.0,BABAFAHDFDGBHHEHBDACHGHGDDBDHFFAFACEBEBEBHBCAHBHDHCGBHBCGCB,False +307,27.0,19.0,23.0,17.0,31.0,29.0,21.0,17.0,FADCDEGEBEGHDAEFEAEBHBCBAFAHAFGEGFBFCAHAHCCBDFHGCEFFCFEFEAEAFCBDADADHDFBFBEBADFCFEFBFBFDFCFGFEAHBBCCCCHHBHAAEGEBECEGDAEFDGECEFEHGAGEFEDGBABABHDHDCDCGHAEACAGFCECGGHEDCFAAAGAGCEHEGEGFGFE,False +308,16.0,23.0,23.0,25.0,22.0,21.0,28.0,27.0,BHGEFEDACAGADADGDGDBBFBCGGHGFCFCEHHDCDCEGFCFBEBEHDHCHCBEDDHBBEBGGFDECHCHCBFDFBGEHEGEDEGAHDBDAHGBGDGBCFCGCGBBAFAFABBBFGFHAHAEAGFFFGDDCABHECEDEBEHDGDEDEGCHCDCACHCAFGGGHFHFHGHGCAEHHHHDDBEF,False +309,11.0,10.0,14.0,4.0,9.0,15.0,8.0,17.0,CECHBGAHBHAHGCACBEFEFDCCCCCBCDCGAFFFFFBCBAFHFHFHDAEAHGHBHBHEHBHCGFBHAAGEFEFEGHAHDFFCAEHG,False +310,7.0,7.0,11.0,8.0,8.0,14.0,8.0,4.0,AFACGFEEDBGHDDADFCFCFCFDBGBHEHFAGDCACFCFEFBDBGBEBFCFCFCADGEGEAHCFGE,False +311,1.0,3.0,3.0,4.0,1.0,4.0,5.0,3.0,DHHBHDGDGCFAFGEBCBCGFGFD,False +312,9.0,6.0,12.0,3.0,7.0,3.0,4.0,5.0,AAEAECGCDFDHACECEAEBHBACCHCHEGCGCHCACBBAFAFCDGEBB,True +313,10.0,20.0,11.0,11.0,10.0,21.0,14.0,10.0,FHEBEBCAHAHBFGFGHGFAFCFDBDFDCHBECCCHEACABDGFBFEFAFAHGBFBDBDBFCCCEBFGGBGFAFABEEAEGBBFFDFBFBDBGBGCGDEDHFHDGGH,False +314,11.0,11.0,19.0,12.0,11.0,7.0,10.0,11.0,GBHBFGDABADADBDCDADHBGCECHCHCGCEAGCGCDCFEAGAEAEHECEFFBECDCGEHCBBBCGDHDBDADCFFEFCACAEBHHCHGHC,False +315,15.0,20.0,19.0,23.0,12.0,16.0,12.0,15.0,CCCCEFDBDHDCDFDCHFHFDEBACECHCGGFGAHDDDBACFFFDFBBABABDBACADAHCHDGCFFBHHDHDHGCCACEDBDECEHEBABHFDDDDGEFBFBGBEBFAGAGBGHEHDFEBABAEADBCGCG,False +316,6.0,8.0,6.0,3.0,8.0,2.0,0.0,9.0,CBCDFDHABAFEHBHBHECEBECHHBEEECEHAHCDAHABAB,True +317,5.0,12.0,12.0,7.0,8.0,8.0,7.0,11.0,CHGBGBFBFDABACAFFFCECHCEGDBBGHCCBGDGFGHEHDHCHBBCCECEBEAEAEHDCDHHBHBDFF,False +318,19.0,29.0,24.0,19.0,24.0,39.0,20.0,15.0,CFEFGHBHFHCEABFCCCFFEFEGBGBAHAHDBABCBGBGBGAGAGABHCCCFFFEHEDGBHEEDHDEDBHFDBCBGBFCFBEDFAFCFGACEFGFGAAFFFFDFEFECCGEGBDAAECECABEFDFCEAEAHFDBABDCHGBGBGBCACBCBEFGFGFCFHDDFAEHDFFEDDFDFBFBEBEBFHFCD,False +319,8.0,5.0,5.0,2.0,5.0,4.0,3.0,7.0,HAAEAHDHCBDEAHCGFGCEABAEAFAFHFHBHBCBCEG,False +320,4.0,0.0,2.0,0.0,3.0,0.0,0.0,1.0,CACAEAHAEE,True +321,19.0,25.0,20.0,14.0,21.0,25.0,19.0,10.0,ECEAHAGAGDCFHAHAHABEGAGBEBFFFFFGFDFDFGCDCBABEBGBFFFAGADFDGHGABAHAGCBABGDGEEACAEDBCBCEEFHGDDCBCEGEFEBEBFGCHBHBEDFHBCGEBCDCFCEBEFEBCBCBCBAGFFAFAFDCGEEFDCBF,False +322,4.0,3.0,7.0,8.0,3.0,3.0,6.0,6.0,AGDFDFDAGECEDDHCHGHCBFDEBCBCHCHCDDAHAGGG,True +323,20.0,23.0,10.0,13.0,14.0,23.0,24.0,21.0,AGAFFGHGEBBCDCEEEGBFAHAEGEGCGFGAAEBGHEBDGAGEBABEFCHAHADFBFDFBHBHBGBEBFBFHCACGCGBFBFAHAHFEFDBGGGBGFGBBEDHGHGHFHDHDGDHBFBFDFHFHFACADAGEFHCAADHBHCADFGA,False +324,6.0,10.0,13.0,15.0,5.0,10.0,12.0,7.0,ABBDDDDGDHDCBBHCHGDGBAEGEGHDBCFGFBEBADGCGCGHFFFFFCFCBDBDGDCAAAFDHCCCECDFDHCGEG,False +325,14.0,17.0,16.0,18.0,24.0,25.0,25.0,12.0,EAGDFBFEHEFGADABCCEGEAEGEGHGBFBDEAEDHDFEFDHCHGBGEECDCDCDCHCDEAEACCBEGAGEBFBFBFCCGFBEBCCDEDFDHHGAGAGEEFFFFFBGHGHBDECEBAFAFDFDGGGAHBEFGFGFHDGDEFGCABFBFGG,False +326,10.0,8.0,13.0,7.0,11.0,10.0,9.0,12.0,HGFCFAFCFAGADEDBHFCFCHHAHACEBECCCCEGEFEFGDBFBHBGBCEEABCECAADDEDHDHBGEGAHCHFHGAGH,False +327,13.0,9.0,7.0,7.0,11.0,9.0,9.0,4.0,EFEGEFABAFHDBFAFGGEBEFECCCEFFDADBDGEGAGABABABFBDDAEAHAHGHEAAGDECCCGCB,False +328,11.0,7.0,14.0,13.0,15.0,16.0,11.0,12.0,HHHHFDGEGFHFHGDGCCHFBFEDBAHGFCDCGGDDACACEDBGEDEHHGHEFEFCFGFAAACADHFAFCFCFCBDBAEEEEGDFBFAEAEDEDEBCCC,False +329,14.0,9.0,16.0,7.0,13.0,4.0,16.0,18.0,GCAEFCFCACAEDGGEGBGBGBHBHAHECAAAAHAHECECHGHADDCBCFCHHGAGEGDGEAECGBHDACECBHDCDGHCHGEBHBHEHCFGEGHHA,False +330,6.0,12.0,18.0,17.0,8.0,10.0,10.0,6.0,GGFCECDCDCAABEBEHEFDDADGDBDHGFBFBEDHDFBHGGCBCBCDCBCHDGCBCBEDCDGDBECADACCCFEFGFGFHDADFCC,False +331,11.0,25.0,21.0,16.0,17.0,27.0,21.0,23.0,FFFCHCBCGHHHGGCEBEDFCHAEFCFHDBDBABFBFEFBFHDHFBGCACHHFBFDFGFBHHDBEFAFAFHFEEEGEGEGEDBHCDCACHHGFGFHHBDBDBHCHGEDBDECECECFGBDBCEGGGGCCBCAAADAHBBBGBGFGHDAEFGFBBGHDCFCF,False +332,31.0,34.0,15.0,23.0,18.0,19.0,14.0,23.0,HBFBAAACBDEABCHDHAHDFEFHAAACDEBHBHBHBCBHBHBGCAFGBGBFFDFGAEAEBDFFADADACADDDHAHAEEBFDFGCCCFCAEGBCBAHCGEEEEEEBFDFEHBBBABAHADBDEDFGHHBHBDDABBHBHDHFCFCGEBAAAEGFDFDGDBBBAGAGABAGHBHCAD,False +333,20.0,17.0,9.0,14.0,13.0,13.0,13.0,14.0,ABGCECACBHDHGEEHEHBDAAAFDEDGDFAFABCCGHBABEBEGADADFDEHEHEGBGAHADDHHGHGCGFFABAFDBDHABEFDCDFFAFBEBHBAFAFABABGCECHGBG,False +334,7.0,5.0,2.0,4.0,6.0,6.0,4.0,9.0,GCGBFBHAHEBEAEDCGEAEHHFHAHABFGFHFHDEDADAFHB,False +335,17.0,13.0,10.0,10.0,9.0,12.0,9.0,20.0,AGHHAHAHCBABFGADADEFEFEDBBBBHHGHDHBCECEHFHFHBHAHDEAEAEBEHACAGADHCHBGGFFFHACBDFDAGHCDGDCFCACFHFBBHGAA,False +336,10.0,13.0,6.0,5.0,11.0,4.0,11.0,9.0,EGEBEBEGEBAHEFBCBEHGDFHFAFCBHBGDABHGGGBGCGBABADHDCEABABADAEEGAGCHCHEH,False +337,17.0,16.0,15.0,8.0,14.0,17.0,17.0,24.0,HBGBABHBHDFFAHAHAGAEAEAFACGCBCECFGDGCCEFEFHHHABGFCHDHGBCBHBDGDHEHGHCFCHGHDHFHFBFDABHBGBAFHEEGEGECBAGEHBHCHEFEADCBFGHCEFGCGFAAAAF,False +338,18.0,20.0,22.0,16.0,18.0,27.0,14.0,22.0,AEAEAEAFHDHAAEFBDHGFGFCAAAGADFFEFBADCHCHEGBBEBGFGFGEHEDCFHAEBHCDCBCGAECGCHCHBFBEBHHHGCBHFDDGHHHCHBDEDECBDFEFBFGFCFBFBCBFBFCDEAFDGABADADBFFFFECECADHHHCHCFCFCG,False +339,24.0,25.0,25.0,23.0,21.0,21.0,28.0,25.0,ABAFDFCFCGHGCDBDGEGEGCAAEBHBHGHGHDADCGCHFECEBDHDABHGCGHDHEEEBFBFBDDCDGEEEHBFFCFBFAFAFGCCCHGGFGCACHEDEHGDDBHEHDACAFHEABGCACABDBEBFDGHGHFHEAEAEADACGGBBBCGCGDGBGBFCHAHAHFBABFCEHBADGDEBACGCGFAFDHD,False +340,14.0,19.0,9.0,8.0,9.0,16.0,11.0,11.0,CAADABAEACBCBGAADHBFFFBDBDEGABHHHAEFHBCFHBEBGFDFBFBDBDBDAEGEGEFCGBFBAEGBGFGFHFHFGFCBCAAGAFEHHHCBC,False +341,2.0,6.0,2.0,4.0,1.0,4.0,1.0,1.0,ECBDBFAFDFDBGBHBCBAFD,True +342,10.0,9.0,6.0,7.0,9.0,12.0,7.0,13.0,AEAHAHFEGEGBGAEBBHFDBGBHHGHAFAFAFHFDDCDHECFCACFHFHCDCDHBEBFAFGFABEEEGBDHH,False +343,12.0,23.0,13.0,17.0,19.0,18.0,25.0,20.0,GCGCGCFABHCGAFCFDFBHBHEECDDBEHEAEABABAHHFFDFGEBEBGCABAGGEGEDEDHBCFDHDGBGDGHAEAGDHAEEECHHFBDGCFCDBDHFHBBBDHHCBEHFHGGGFGFBEBEFEFCFGFGHGDGDBHBGBABDGEG,False +344,8.0,19.0,17.0,14.0,18.0,17.0,16.0,26.0,BFBHCHCACDDFCHEHAFAFEEEDHGHBEEFADGGFGEEDEDEFEFBFBHHGHGHDEFCGCGHDHDBCHDBCFCGEBHBHEHFDEAEBEGCGBHBFBHBCBCBCBGACCHHHGHFDFCFHGDGHEHDCBAAFHBG,False +345,14.0,25.0,9.0,16.0,24.0,29.0,24.0,20.0,BDBDFDFEGEDADGGGGDFAABHGFGFEBHFECHCEDBABFBEDGGCFCEAAHGHFBBHHHHHHEBEBFAEEBEDGDCHEFBFBFBHEGEGEAEBGGCAFFGDGAGAGHFFFFFGCHAHBHDEDEFHBBBFDFHFBFBFBHDEFGBEDEGEGBAFFCACEG,False +346,20.0,21.0,26.0,20.0,28.0,15.0,21.0,20.0,EDEDFHFHEDCCECEHEHCGBBAEFDDHBGBEBGAEHECGCACECGCGCDEHCAFAECHBBDGDFCFBBHBEBEHDGDBDCAGACAHAHDHCEBEHEACDDDFFAGAFAFCGEACACGEEAHAGAGAGEFEFHFBGCHBDBHBCGDGCECHDHFBFDCGCBBEBDAEGEGE,False +347,9.0,10.0,7.0,7.0,9.0,11.0,7.0,1.0,DAFCBCBAFDEGEGEFAADGEGEAEAFGFBFEFCFGFCFHEDCBGBEBAFDDABCBABDBC,False +348,23.0,21.0,22.0,23.0,12.0,21.0,19.0,12.0,DBGBGFCCGCDHGFGFGFDCDEAEAFBFBHGHBCBABAFFFBBAFHFCDBFECCDCACAEADFDEDGCFCHBBBBDFDCGAHFGEADDGHFFDADEGEAEFEDECACACAFADCFCAGBBABEDGDHCGCACACHBDGGAGBGBHAHADDDHB,False +349,24.0,18.0,28.0,33.0,14.0,23.0,32.0,22.0,DBDACACDEGGCFCBGBHFGDGDEDHHADCFBFDFDAAFAGDGCFCECEGDGFBAGHDDCDCDGHCFFAFGDGDHDHFGGBGHDCDCAHFEDBFBFCDDEDGHAHADABHBEAAACADGBGAGAFHCCGFGCGDGAEAGDGHFHFEBAHCFCFGGGEGEGAGHBBBDCCHCHFHCHDFDBDCDEHECBCEAABC,False +350,8.0,4.0,6.0,7.0,7.0,4.0,16.0,7.0,EDGFGACAGBHBEBAGACAGEEEEEGGAGCGCDAFHGDCDHGHCHGBGAFDFDGGGDHH,False +351,14.0,22.0,13.0,15.0,4.0,11.0,14.0,13.0,ABCCHHFHCDBDBDBCCGCGFFDFBFGGBAHADDGDCDCBAHABEFHBBDBDBDBEBEBGDAEABDGFHBHGAGCBFHHHHHACGBGACFBBDGDBFAGAGACACF,False +352,23.0,10.0,18.0,19.0,18.0,25.0,14.0,15.0,GFADHDHFCGCBFFFHHEDFDHAEEFECAGBGEAHAHADAEGCBFBFEGEFHHEGGCFCHHAHAHEBAADAGBEBEDEDGFEFAFADADFGFAFCECECFFAFACACHCDFDADCDGGFDHCCCCDGDAFBFBEADBDAECF,False +353,28.0,26.0,15.0,29.0,24.0,17.0,31.0,29.0,EFGDADGCGBGBGBEAEHGHFDDEDEDEGHGEGEGHGHEHGDGBGFEAEGDCHCHDHFHEHAGDHDFEBEBEBEDCDCACAFGFCABFEGBGAGHHBDBABABHHAHAECEAGBGBHBFEDHCFCDGAFDHBEACFHHGDADHCFCBAAHFFGFDADBBEBHACABAHGDGBEAFABDBGGGGDDDAAHDDDHCHAABE,False +354,2.0,5.0,6.0,7.0,4.0,6.0,4.0,6.0,BHGHAECCCFADBDHDEDBFBHDCDCDFGCGFGFHHEFEB,False +355,6.0,5.0,6.0,6.0,6.0,7.0,2.0,4.0,HFHCGCGBFEAAAHAFBCBDEDEDEDCDFFABBCFCADFEHE,False +356,6.0,7.0,14.0,10.0,18.0,19.0,15.0,16.0,FBEHFGEHFDCDGGGEHCDCDFFFHBABDFDFHCCFEFECEHEFCAAGFGBCBFGFEBCACACDFFGHGBEHEHEHFHCCEGEGEGECAHEDEDGDGEHHHGHFF,False +357,14.0,24.0,11.0,19.0,13.0,13.0,20.0,12.0,CAHGEBBDBFBEGHAEDBDHDGDGECACACEFBDBFFGADBHBCCDCDHDEGEAFAFEGBFBABHFHAEDEDGHGBEBGBGBGFFBCGEGDAFAFAHAEBCGDDAGHHBCBDBDBFBDBDCGGGGH,False +358,14.0,23.0,16.0,16.0,14.0,16.0,6.0,16.0,HBCBHFHFHDBAGAEDCCCBFDFHFHDHDHGHABCFCFAGEGBBBFDADADBEBHFCFDFCBADDBCBCBCAEGEFCBABAFAHBFBEBEBCCEEHEDECBFAEHGADHDHEHBDEFBCDA,False +359,13.0,21.0,20.0,21.0,14.0,16.0,20.0,15.0,GFDBDCACAEBEBEBHBCBCECEGACHCHAHAGGBADADBDFCFHGDGDGEBHBDGGFGFGDBDAGABDGDGEHFDAEFFGFDHEBCCDCHCFCECHGDBCEHEFDFDABEBGDGHACFFBDCEAFGDBCGCBCFHBHBH,False +360,2.0,2.0,1.0,1.0,3.0,6.0,2.0,3.0,GFFFEFEBDBEHGCAHAHFF,True +361,14.0,17.0,14.0,17.0,23.0,22.0,11.0,18.0,DHACABDDDFEFBCAEAEAEFCFEFCFDFHFAFBCBCHGHFHEAEGBHBGCFCHAEBEFECECGFEDEFCCHAFAFAFADGHGBGDHDEDAHBHBHGEEBDHDBEEHGDEDEFBFBFHFGFBDAEBDGCHEEDCHB,False +362,7.0,7.0,14.0,4.0,6.0,6.0,6.0,3.0,CCBCGEGCAFAEADAGFGFCFCBCGHBBDBCGEAHAFCDCACBCHCEEFECBD,False +363,10.0,8.0,17.0,16.0,17.0,20.0,8.0,12.0,FEADABEGEHEBEBECFCDCHBHCAEEGHCFGFGFHHEFEFDFGFDECCACHFFFCDCGADAFGDCDCDCEFFFFAHAHBEECCDADAFFBEDEDEDHCFCDBHGHDB,False +364,8.0,4.0,4.0,12.0,13.0,9.0,10.0,11.0,FFHEHDFFAGEGEHEHFGDDDEDECEDABHFGFGDGAFADAEECGGABDBGHHCDCBGFDHDHAEAEHEHE,False +365,6.0,2.0,5.0,1.0,4.0,5.0,1.0,5.0,FEACAGFEFHCEABABAHFFEHAHCHCDC,True +366,11.0,5.0,9.0,15.0,4.0,9.0,12.0,5.0,CCFDEDFDFEFEHDBDCDHGGGGDFDAACADABFGCBCAGAFDFCGCGAHAGAHDBDHCGEBFDADADGG,True +367,22.0,11.0,14.0,10.0,20.0,19.0,35.0,19.0,DGGGBCECGDADABABHEHBHGAGHGFAFAGBGBGEEACACFEFGGGEFHCDEEBEBAHCEFFFFHAHAHGFECBHGGEGEHAHFGBDFHEEGCGFDAAAGEGAGFEFHFGAGAGDHAACAGHGCGAGDGBFHFGCGCECEHFHDGEGCD,False +368,2.0,3.0,4.0,0.0,3.0,2.0,2.0,2.0,BCECECHFHFAGEGBBCA,False +369,2.0,7.0,10.0,3.0,12.0,8.0,6.0,9.0,HHDHDCCEGEFFFHCBBHDEGEHEFEFEFEFBCBEBHBCCGCHEHBGGACECEFGAC,True +370,17.0,20.0,13.0,14.0,12.0,20.0,18.0,16.0,HEFEBECCHDECGCEBBGCDBDBDGFGFAFHGDDFDHBBBFAGDFAGACEFHGBFDFHFHFHCGBEDHFCFCFGAAEDECEFBFAHABACAGAGACAHABFBFGEGDBFBHBHDHDGBABAGCGEBAHGH,False +371,14.0,16.0,16.0,7.0,13.0,5.0,11.0,14.0,GBGBEHFHFBBBECAABDEABAGAEDEDBCEGECCACAGACACBCHCECEGABDBEBHBHFHCDAEADHCHCHFHCEABBCDHEGFGCHBGGHGHA,False +372,9.0,15.0,11.0,10.0,12.0,17.0,13.0,14.0,BEBEBGFFBFGFDFGCGCGFHDGGCFAFAFBFDHDEAEHEHAFBFEGHHEBGAGCHHHDDCECGCABFBFHFEDEDHBBCBGBCAGACAHBECEDDHBHFF,False +373,14.0,9.0,8.0,14.0,6.0,19.0,18.0,14.0,BHEFAHAHDDDDFBFDFGFEFHGBBFAAAGADHGBFCDGBEFGFCHHGFGHGHFHGEGAGEEAGDDABGGCCCBHBHCHDFAFAFAFGFDFDADADCGCGHF,False +374,13.0,6.0,13.0,5.0,8.0,10.0,12.0,6.0,CBGADAHAHAFAFGCGFGCDEAEADADCBHDFAACCCAFHBBCEGEGECFHAEBEHCGFGFGEGCGCFCGABF,False +375,8.0,5.0,6.0,3.0,11.0,9.0,8.0,4.0,EEEEHFFBFGGCGHGEBABEEFCFCBHGDBHFAFAFDFGAGDGAECECECAAAE,False +376,6.0,8.0,6.0,9.0,8.0,5.0,12.0,5.0,AEGEBACACHCGGHDBDBCEGEBEBHFDDGDCDBDBEGCAFBFGGGEHEAADFDFHGGG,False +377,2.0,3.0,2.0,5.0,6.0,4.0,2.0,2.0,EDEDECEBHBGFGAEADFHBDFEFDC,True +378,18.0,11.0,12.0,20.0,13.0,19.0,14.0,21.0,GAEHGHAADADADBFCECDCFCGDDFCGHAADFFFGHBHFDCDBFHFHGHFAGAGABADDHAEDECFFFAFAFDEDEBABFBGGHBCBAACBHHHFFEDEDADBEHFHGCGEEDHDCDGHGHEHEHCH,False +379,15.0,10.0,10.0,14.0,7.0,13.0,13.0,11.0,FHGHGHBBCDDDDABABGCEDADCHGAAHAFCFBDBDADFCFDDHCHFHAHCHCBCGGAACAHGGGGAGBEDFDFEAGDGFEBEFFAFAEBEF,False +380,20.0,20.0,27.0,28.0,18.0,28.0,19.0,15.0,FAEAEHHHHHHECBHFFFCFCDAGFGDEDCDCBGFFCGBGEGBAEAGFCADGGBEBEFHFDCBAEFDFDEDAHAHGEDAGBGFEBEGFDDDFDFAFCCCCCCBCBCGCGCACDDBFAFBCDADCDEDBCBCGHGFGBBAFDCDHBHDDBDCECACDFDGABFEDEAEFHHAAFFF,False +381,9.0,4.0,8.0,8.0,10.0,3.0,5.0,2.0,DEDECFCECEDAAACHEGDDFDFCACECGAABDGCHBEBGDGBAEAEAE,True +382,28.0,23.0,23.0,25.0,22.0,19.0,22.0,24.0,EBAHHEDEDBDHHGADFEFEHDHDGFFDFDADHDGEACBEHEFGDGAGAGEBCDCBBAFECHGGBHCHCGGGCGAFCHCHBBEBFBFHFCGCGEDEAAADABABADFEFDCDCECDCHCHCBAAAAAAHAFEGEADCCFHFEBEBFHDHFAAAGCBBBCDHDEDFBEGHCBDBGHGCGHDEAGABA,False +383,4.0,5.0,2.0,2.0,4.0,7.0,4.0,2.0,FAFBFGCGAGAGFBDEFEFHABFBDCHEBE,False +384,23.0,10.0,11.0,21.0,17.0,14.0,20.0,15.0,CBEFFDDBFAGHDAGAGAGDDBEGCCCDCBHHEAEFGFEEEHEACACAGAGBDAAHFHFAFADEHCACGDAEEFGGHEHBCDAGAEDEBFGHDHEHDHFHAGAGAGAFAFABBCDGGGDBDGDEDEDFDHD,False +385,16.0,15.0,15.0,12.0,17.0,20.0,20.0,23.0,FGBHBHAHAHBDFEFEBCAEEDEAHBHBHEFDCBAFCFAFAGHGHGACDHBCAEHGHBABFCFDGDFDFHFDBGFGHHACADACHCGBEBEHEACGEGFGFGDGEGEGECEADACBGFHHDFFHFHFGGBHCGCEEHC,False +386,22.0,28.0,19.0,25.0,19.0,24.0,12.0,27.0,BHDGBHDFDFDBABGDHAFAECECBCBCFCBEBHHHEEEBAFDFAFADECBDFDFAEHBHEHEGEADHHHFHFHDBFHAHADADFDFCAHBCGCDCBBBGBFAFCFHAGADDBFEFEAAHCDCECBDFFHFHBHBFEDCACAGEFDHGBEHGBCBHEEGAGHBDBDGHADADCBCB,False +387,16.0,23.0,23.0,12.0,27.0,6.0,20.0,14.0,EDEBGBEBCGGHCACBHBEGAGHGCGEGFCHBDCHGHBHGDADADBBCHCBEBACGEGEGEBABABDEEHECCCCBBBGAGAEAGFGHACCBBABAGFBEEEEEECGDDCDHEEEAEAECDCECGCFHFCBCEADDHEBFH,False +388,29.0,22.0,29.0,26.0,26.0,22.0,19.0,18.0,CECEGHFBFDDCDHGAFBGDFAAHACACAEEBEACFCAEECCGCGCFFFABGBGDCDGDEAEABHBHBFBHAHDCECECHFEFBACDDDEHAGABADFDFDBDBDECECEDHDAAAAEBEGAAADGFBFADACHEAACFGFGCGEHFHFCCCDGGBCEGFAFEBHCDAGBCBCDCEEGDBDBDHFHEBEHH,False +389,6.0,5.0,9.0,6.0,6.0,10.0,3.0,6.0,AFFFACCCEHHHHACDFDEGCBCDEDCFBFBDBFHFHADGCGCEFAFAEBE,False +390,5.0,5.0,8.0,6.0,3.0,4.0,2.0,9.0,CHCGBFDADACBFDFCHHDHDHCGCBFAEAEAECHCHBBDHH,False +391,17.0,18.0,29.0,20.0,13.0,16.0,17.0,22.0,GDCDGHHBEBFCFHGHAAAHBCDCDHFHEHBDDDDDCDCACHEBDBCBFDACBCBHACCDCGGGGCBCFCFBACADHHCFCADHHHGCBBGDGCGEEHEACAGGFGCABABDBEECECECFAFAGHHDHDFBFGFHECEFDFAHBHFGCACE,False +392,4.0,11.0,10.0,5.0,8.0,5.0,3.0,15.0,HHHHEEDDBGHGFABEBECCBHBCBEDECBCHCBEFEHDBDHAHBHFAGCHCHCBCAHFHF,True +393,5.0,6.0,6.0,2.0,4.0,4.0,5.0,6.0,HGFGHHHAGCGEFEBDFDAAHAFCBCBCECBGBEBHCA,False +394,21.0,28.0,17.0,22.0,17.0,15.0,15.0,14.0,DHAAAAFCDBDBDGGABBBCHCACGHFBBBBBBBAAAAFBBBBBEGEABCGFDHEHEDBAADEDEDEHCFEBEGDHFGGECDCHCHBDCEFEHDBDBDBDCECGCBFDGBADHGGFAFAFACEGEFDFBABFFEGDAACACHEHDHDCG,False +395,17.0,17.0,23.0,13.0,25.0,16.0,32.0,27.0,ACFCFGGGEEHEGGDEHBACACECEFEFHDEDFDGEGBGFHCCACEEFDACHGHGHBEEHBACCCCHCEFDAGAGEGCBHBHBGGGDGCFAHGHGHCAEFBBBHBGBHHEHEBGGEGEFHFHFHGHGCFCGHGDEDAAAGCBBBCHAEAHDHDFGGGEGBAHECDFDCAE,False +396,2.0,4.0,1.0,7.0,6.0,10.0,8.0,9.0,GCGFGFGHBFAEGFHFHGBDHEFEDHDEFEFDFEFBGHHAHGDBDHD,True +397,12.0,14.0,13.0,17.0,13.0,20.0,12.0,15.0,CEBHFCBGHGEGEACAHBHBDBGBADFDHDFDADHHEHFHBAAFACECECEDDGDGDCCCHCGBBDGFBECGDGACFFFFFFDHDHAEFEFBBGBFHFHECAFDBEHDFAFAEGFD,False +398,28.0,19.0,7.0,24.0,27.0,19.0,20.0,15.0,DHEAEADDHGAAHAGEHEBDBDHFCFEFEFEGAGHGBFHECAAGDCDADFCHDADADFDHGBGAEHDGFBFAFAFEFEFEHCAAAGGBBABDBCEADADFEGEFHADEGGGEGEGBGBDADEEBDBDHEEEDADEBBFHEEFCFEFAAAGABABDBHBG,False +399,0.0,3.0,1.0,3.0,3.0,3.0,0.0,4.0,DDHFBFEFDHBHCHEBE,True +400,14.0,15.0,8.0,10.0,12.0,16.0,15.0,13.0,BABABGHFHEHEAEBFGHDBCBGDCFFGAGDGFEFEFEFHDCAGAGHHAHACBCBGAGEGEDBDHDEBCACBHAHCFAFEBEDFFFBFGEGFABHGDADFBHG,False +401,11.0,5.0,16.0,15.0,7.0,18.0,6.0,17.0,EGDHHBGCGFFFFECHDAFAFBFDHGHAACFFFAEHBFDFHEHDFDFDABBEAFCCCCCCCFHAGADDDCCEHEHCHDHAHFHCCCFDHDHDADG,True +402,3.0,10.0,24.0,13.0,15.0,13.0,11.0,19.0,CBBEDHAHBDBDBGCECHHDHGHDCGCGEHCHCGCEEEEHFHFECEGBDDFBHEDBDADGFHCHCGCBCDCEAFGFGHGHCECFDECCCCCDHHEBFHFCFCEHFFCF,False +403,1.0,2.0,2.0,2.0,0.0,1.0,2.0,2.0,DGDABGBCHCHF,False +404,5.0,16.0,6.0,12.0,8.0,5.0,12.0,9.0,DGDHBCBCHGEEHEFGFBAGABADDCDBBBBBGAGEEDCDGHGHFHBHGGCEEDBDBDBCBDBGFAEBHFHGD,True +405,21.0,16.0,12.0,16.0,13.0,10.0,25.0,18.0,GFEFBFGGBGBGBHFHEBEBGBGFGFCEAGCDHAABHBEGCGHDHAHDCEGDGDBFGCAAAAEAGADFDGDAACACECEBFDHBAEACHGHAHDEDEFHHHBGEGACDBAGGBCBHHCDGAGDGHGHADAD,False +406,4.0,4.0,3.0,5.0,1.0,0.0,4.0,3.0,GBDDABCBCGDGDCHBHDHAGAEA,True +407,16.0,7.0,6.0,14.0,13.0,6.0,14.0,8.0,BFCAAAAAEFEBDFCFCADGDBDBDAGAHAEDEGHGHGFDBDGAEHEAEAGCEDHAEADGDAFADGGEGHGHDEBEHDGBGCCE,True +408,12.0,15.0,11.0,21.0,18.0,14.0,12.0,11.0,DBDBDBDBCBGGABCEFEFGGDBDAAAEHEFEBGBECCFCBGEEAEHCBFEFHFCEBFBHGADFDACABEBEAECDCGFDDDDDDHGEGFDHDHDHFCDDEDGAAFAFHHGHEE,False +409,20.0,21.0,28.0,22.0,20.0,26.0,20.0,22.0,FCFDFHADGDHDHBBCCHHDHDHDGAABAGCGCDCDFFFAEAFBHHGHCHEFEGBDCDAAHABBCFHFEEGEFFFCHCDBDEDEFEDAFAFABEHCCCEBHBDGDECCAAACDGFFEDHDFBHBAGAEAEFECGGGCHCDAHBGBDBCBEHGFCFCFCFCEGEGHFCBGFGCGCEABBB,False +410,3.0,1.0,3.0,3.0,0.0,0.0,1.0,2.0,DGACBHDHDCACA,True +411,10.0,24.0,18.0,15.0,16.0,10.0,24.0,18.0,HHFBFECHGHAHFGGDCBCBCEGHGBBAAGCCHCBDBGBDHHHBFBDBGGCGHGABABACEHEHCDGDECBAAEFGGDGEADDDHDHBEBEGEFEGEGCGDGDEDBCCCHCEBEDCGFGHGEGFBFBACHBBBBF,False +412,7.0,7.0,14.0,10.0,10.0,6.0,9.0,5.0,GEDFDFBAGCDABADDGAHEDEDFDCDCDFHCBCBCGCHBGCFCAEEEEEGEGCCCHHGCBEBCAGAF,False +413,1.0,1.0,2.0,0.0,2.0,2.0,3.0,2.0,FGCGCHEHEABGF,True +414,3.0,7.0,4.0,3.0,7.0,6.0,6.0,8.0,HCHGEEBABABFBEGFGAGBDFDEHEFCFBHHHFHCHCBEEGGD,False +415,17.0,22.0,23.0,22.0,24.0,17.0,20.0,16.0,BCBGBADDEHEBECCCCDGAGEGEAACEHEHGFABAEHECECFCGCECDBACAHADECGCBBFGFEHEFGDGEGCGFGDHDCBCAFGDGDAEFHFCFBEEHEBDDFHHHBAFAHDEDGDBDEDECFCFHFAGCFFAEGDGDADCBBBBCGHHABBBBBDED,False +416,23.0,23.0,29.0,23.0,28.0,15.0,36.0,18.0,HDFEEHAHFECBCGDFDFBAGABBGGADFDGEGECECGDHCECECEDEDACACGEGCGFBCBCACEEDEGGABHEDCHBGGGHGCGCBDBCCCEHEBGBCDDGGHGEFEGBBBDBAFAFAGBFFHHADEGEDBCCCACGCDCGEAHAEADGGGDGDBFBFCGCGBGBGACAHAHGEFDADEHEHAFGHBHDEAEA,False +417,6.0,3.0,6.0,6.0,13.0,9.0,7.0,12.0,HGCCECEAEHGHGCFAFHDDBDEGBGHHEEDAFGFHEHAAADBCHCGFEEEHEHEFEFDFHF,False +418,7.0,7.0,9.0,13.0,10.0,16.0,6.0,11.0,HEFFFEDECCHHBHFDFACACEDHDBDBDBDFCFDEDEBHGEFFAFADAFHGBGCGCFDEAHDFDHGHFHCGEFEFABC,False +419,6.0,2.0,4.0,3.0,3.0,0.0,2.0,0.0,EEBDBAAAACACEGGCCDAD,True +420,20.0,21.0,13.0,17.0,21.0,27.0,25.0,13.0,HAGAGAECCFDBEADDGAGFFDCBFFCABGBEBAGCGBFBGEGEFDCDEBFBEDCAHBHBDFDFBADGFFEGEGEFEFEFHFBBABAHHDGDGBGAGFGFGEEDEDAFAGDHEACACFFGFGFGEDECBFBFHHHGEAFAEAHFBEBGBCHCHGADC,False +421,9.0,14.0,14.0,8.0,6.0,14.0,12.0,12.0,FHFDFDBBBGBEBCBFDGDHFGABCGABBGEAFAHACACHDDFHCBBFHFHFGCHCHGBBHHGCGCACACHCEFEFADDFEFEGGCGCB,False +422,2.0,4.0,4.0,2.0,2.0,3.0,4.0,6.0,HFCFCECBGGGDGBEHFBAHAHBHDHC,False +423,19.0,10.0,8.0,8.0,6.0,9.0,8.0,8.0,DEABABCFEFDAAABFHFAFAFADACCGBABAGHBABABAGHEHCGDGDCDCGEHEGDAABAEHBAGACDFFCFHH,False +424,22.0,16.0,21.0,30.0,13.0,19.0,17.0,12.0,BCBEBDAEAEAHAHGHCBCAAEADGFGDGDCACFCDEGCDHBCADDDDDEABADADADAEGBGBHCGFAFDCDBDFACDBDBCFEHEHAHGFGFGFGECHFHCCGDGACDFDECFDADEBHFFDFDFBFBEHAGCGDFCBGDACBCFDAD,False +425,12.0,15.0,7.0,11.0,10.0,19.0,9.0,9.0,CADACAFHFDDCDBFBDBEBEDEHFABACFFHHGFDFDGDGHAHACCBEFDFGEGEADFFCEGBABAEHHBHBGBEBABGBEFFFFABGFFF,False +426,10.0,14.0,11.0,11.0,11.0,17.0,18.0,9.0,BFBAAEFEHCHGAFEBCFCGCGBGFHFCGGAFAFBFCFHBBFEFEFEBGCECBGBGCDFDBDBDGAGEFEGHGHAADEGCGHDBAEGDDDDCDFGFGABHH,False +427,37.0,20.0,35.0,16.0,24.0,26.0,23.0,17.0,AGAEEHGHGCCCGBGCHCHCHFGGAAAEAEAFHCHCGCACADEEECBABEFEHDFBFEEBBBCEFAFADACAFFCFDHDGBFFACDGDFDBBBCGCBAAAEAECGCDHFBDBCAAGACACAFAGGBEHECECEABFEGDFDHHAAAACHCHGHCHABEGCGFACCECFFBFBABAGFFDAECEDEFFACGCGAGCDFD,False +428,16.0,17.0,31.0,28.0,15.0,17.0,26.0,26.0,FGFCCACBEDEDBCGCGFDCAAECEAAFFGGGGHCHCAGDGDBHBHFHFHFHDHAGGDDADHDHBACGCGEDHBCDFDGDHDCCCBBBBGCCCCFBDDDBCCCHCFEHHGFBFCCAAGGDADGDHEHAGCGCBDBFBFEGAGEGHCFDHHHHEHEBEHDFDGDHAAECCCEDEDGH,False +429,8.0,4.0,6.0,7.0,12.0,5.0,7.0,6.0,AAHAGBFHFCEAEBECGFGFGEEECBCDCAEHEAEDEDHGHBCFDGEGDHDEDAA,False +430,5.0,7.0,8.0,4.0,4.0,3.0,11.0,4.0,HGDCHCBCBFGAGBGBEDHAEAEGFGCGEGAFCGCGDHDBBBCCGA,True +431,8.0,19.0,9.0,16.0,16.0,15.0,11.0,12.0,FABCEHHCGDGDFDFHFAEDGDFDFBBBBFEDEAGBEEEFEGEBEFDDGBBAAAFHFHEEDCDCGEDBDAEHEHBHBHBFGCDCHEDBFBGHGFBFBCBCGCBAHD,False +432,25.0,23.0,17.0,34.0,27.0,19.0,18.0,34.0,GBHHHFEGGFGFGHBABDBDBHGGEBBDEDHHHHAHFHEHFFFGBDDEAAAAADCDHACAFDBDCGCGDDDHAGBDHGHCHABAFEFEFEFDDBDBABGFAFEEDEDEAEBFDFDHAHABEBEDDDFHCEFEAAAECCBABHDADHCBFGDHEHAGBDHHEHEDEAECEDGCEEHDDGHCHCHEDDHBHCHCACBCG,False +433,11.0,10.0,8.0,8.0,5.0,5.0,7.0,5.0,GEEEBADHCHEBEACABDBDAHABABABCDCGCDABFDCACABGGAGHCHFFDDGFGFB,False +434,8.0,2.0,9.0,3.0,9.0,11.0,9.0,7.0,CECFFFHGHBHCFCFBFHDACEEFCGEDEDAAAGCGCEFFAAGGGHFHFHEGEGECAA,False +435,15.0,9.0,12.0,17.0,12.0,13.0,11.0,8.0,FEFHFAFEDEDBCGGFBHACGCFCHADADAFAEAEADHDBDFHEDEDBBGBDADAGAGEGECCHEAACBCDCEGFGFDADGHHFDFCCCBDGEFADB,False +436,9.0,4.0,4.0,2.0,2.0,7.0,7.0,7.0,HEFBABCEFAFABGGAAACFCFGHBHACGFGAGAGHHDHDHF,True +437,13.0,14.0,15.0,27.0,27.0,6.0,29.0,26.0,DDDEHABAHEHAHDCBGDHFCEGBBHBHADDEAGGEGDGDGCCDCDBDBHBHBAAHGGGGACECEGGGECCDGDGEGADADGFHEEDEGACAGHDDDFDFBEHCHGHFHEEEHEHEHEHEGEFDGDGHBCCEDHBCGDHEEBAGHGEGEGEDHBHCD,True +438,22.0,9.0,13.0,21.0,26.0,17.0,18.0,21.0,GAGEHFHCEGEDAFAHAHEDBDFDABAHEDGDBCAEGDDDGGGGAGEHHHGCCFHHBHBHBHAGECAGDGDGDGEHDFAGCEEFEHEAEAEFFCECFFFBDADFDADADAFEEEEAFAEEBABAHEFDGHEHFCDCDCECHCHFEAH,False +439,24.0,19.0,22.0,19.0,24.0,22.0,19.0,24.0,DCDCAAAAABAFGFDFDHGCGCGBDACCCCEHFACHEDAAEABAHABAEFHFCFCFBBHFHEHEGCGDHFECBBBGBEHEAEAHDGDGHCHFBFEFEBEDFAACDHDFBHADCCEHEHDBFGFHDHDGEGADADEDEBECHFGGAGEFCCBCGFBBAGEHFHGHEHEFECBGA,False +440,23.0,14.0,11.0,16.0,9.0,11.0,13.0,16.0,DCDGBGBAAHECEFGFGAGHHEDGBCFDFGHGEEFADAEGFBAAAABFBFDAACCCEDHHHDDAAEBHCHABCHAHAHABEDGFGBGDDDDDDGAAHACACACABFFHBHBHB,False +441,5.0,9.0,7.0,7.0,5.0,6.0,6.0,2.0,CFDBDGCADBDBDGAAEAEBFBCBFGHBEGDHDECECBCGFGFBFAC,False +442,21.0,17.0,17.0,31.0,26.0,21.0,12.0,20.0,AAAGDEAFCHCBEDDBDBDHCAAHBDBDADHFHFHFHFHFDFEADADHHCHDDCFBFACHDEEEDABADAFEFHCACFFFEFBBEHGDGEGFDDCDGEGECCCCCFCHDEEECGCFDEDGBBDBGGHBFAFEDADFDHEHDHAGDGDBAEEEBEDAHAEBEBEAE,False +443,22.0,20.0,27.0,22.0,26.0,31.0,22.0,17.0,EDEAHFDFEBGFEFHGAFAFEDEAHDFBEDACCCBCBAFADAHFCGHGHDCDCGGHBBGACADFEFEFBFBFBHBHAHAGGGEGAGACECECBAEFFDEECDFECECBCEHDFCABHBCGDHBFBFBFAEDCFFHFCFGFDEDEDGFGFGFBCHEGGCEDGCCHDGFGCCCACEDEAEABABADFDH,False +444,25.0,15.0,17.0,18.0,21.0,13.0,21.0,25.0,GCAFBBBBAFGHBACAFHCECHBEDEHHHEDAHABCGDEAAABDBHAHBEGGDGACDBGGGGHGHGCECEFHFCCGBEEEEEDFCGDGDADADCECBFFCAEAEADGDHAHAHEHDHAHEFEHDGFHFHBDDAHAGAGAGAGEFBHECFCACHDH,False +445,4.0,5.0,1.0,1.0,6.0,3.0,0.0,1.0,FEBBABEBEAFHFEAEAEBDC,True +446,3.0,5.0,3.0,4.0,0.0,2.0,5.0,1.0,DBDAGBGCGCGCBBBAGFDHDFA,True +447,27.0,17.0,19.0,29.0,21.0,26.0,19.0,16.0,AAEEEEFDFHEADAGFGFGAGHFABBBBDADAHFDGCHFDFAFGCCBFFHDHDADEBHGCAHAFCCGCHEEADCBFFDFAFACAEECDCDBHBDCCEDEAGABDBDGGGGHFHFHDEAFDCDAAABAGCGFDFEEEBGAGAHBGDGDFDFDHHACCDCEBEAECEFEFDFDBDB,False +448,12.0,3.0,7.0,7.0,6.0,6.0,10.0,15.0,GCACACAFHFHGHDHAHDDEDCFAHACAHGEFHBHBFGDEHEAAAGAGCDAEGEBHDGFGHHCHGH,False +449,27.0,20.0,31.0,20.0,16.0,31.0,25.0,16.0,CCFCACAHBDGCGCBCGCDCBBEBAGFFFCFCDCBHBEFDFDHGGDCFEDBDFDCDCFFDBAECHADBCHCHCAAAAFAFADDGFCECGCGDDEHGHFFEHGHGFGFGAEFBFEFDBHAFDGGCFAFHHHBHEAGAEAEABGHFAFACACBCACGBBAGACAFFGFGFDBCBCGEEEECFADGBGA,False +450,2.0,7.0,4.0,2.0,6.0,1.0,3.0,3.0,DGCGCBDBHCECHBEGEABFBHEAEBEB,True +451,8.0,7.0,6.0,1.0,2.0,4.0,4.0,3.0,FGFHEABCCCDBABAHCHEAGCGCBAAAABBBFGF,True +452,12.0,16.0,17.0,11.0,29.0,15.0,19.0,16.0,EGDGEGHCFCFDDBECFHFHGEBEBEBEBDBAHAHADCEEEEEEEBECCBBBGDCDCFGHHEACAGBGHFEGEAECFDEGFHCEDFDFDCBHEAEAEFBGCGBAHFHGGEEBFGFGEHAGAGAFCBHHHCCECEG,False +453,4.0,3.0,6.0,2.0,6.0,8.0,4.0,3.0,CCFCEEHCHBDEFAFAFHGDFEGEFBFBFCECGAGA,False +454,17.0,13.0,25.0,22.0,19.0,16.0,28.0,27.0,AGAHHCDEDGGGDHHFEEGEHHCGGHGABCDCDAAFCFCGAGCFFFHEEEHEBGBCFHDAEEBDCDCGCGCBHBFCFHDHGBGDHCHFHBHDHBEAFCCDEDAGCGCDCFFHGHGHGAGADACAEABFCECECEBEHAGAHHDGDGHGHGFDFDEBCHDDCDGBGEA,False +455,3.0,8.0,5.0,6.0,3.0,3.0,1.0,4.0,ADHHHDFFACBCBCHCBDDGDBDBEBEAEFCBB,True +456,17.0,25.0,25.0,21.0,21.0,26.0,24.0,21.0,GEGBFBFBFBGAHAFACDEDCCHFFGBGAACFCHGFCFGHDAEFEFGFGHEBEBDAFGFAFCCBABEHCGFEDEDGBGBFBEHEGGCDCDCBGHDCCCDFAGBHBDEDHCHCHEHCBCDDDDFBEEEEGGBFCFCHAHACGFBBHDHBABGBGDGDFAFAECECEFDFDBGCHBAAHHEH,False +457,12.0,10.0,8.0,8.0,4.0,11.0,8.0,8.0,DBDFDFCCCHBEGFBHEFACBDBGHGBFAFGHAHAHGDDDCCACGCEHGFGFBFBABABDHFAAAEAFA,False +458,20.0,11.0,18.0,22.0,26.0,28.0,20.0,28.0,BFGHCHEAEAFFFFGABCFGFECECECECHCHGHDHAHEEEFHAAFBCGHDHDHCABGHCFDGHGACFDDDBCGDDFGGGGEEABGFAFEHAFEHAFAEAEABAGFDFEEHEFECDADHDHBHEHDHCHFHDHFHGDDDDEDEFEFGDCHCECEFHFAGBFFEFCADGBGBHA,False +459,18.0,25.0,19.0,16.0,13.0,17.0,21.0,14.0,CACACDEDBCBHAAGHBHBCEDEDAGGHDFDEDCHFHECFBFACAHAGGGGGAGDFBABFFGFBHBHBGBHBACABHBGCGBGEFADCDCHAHDHDBACABBBGEGEFCFBGBEFDFABABFCEGECDCBCGDBEGFFCFDGE,False +460,21.0,19.0,19.0,30.0,29.0,19.0,23.0,32.0,FDEDECCDEEHFDFEFEFHAHDCGCGCFDDDCGAGAECDHBEBAHGCGEFEDHDHDGDBHBADCDCHHFECHBGBEHADBDHGHGHGHDHFBGAGHBFBAECGGFEFEFDGDCDAEGEBACHGGDDADFHAEABBGBABDFDFABEDAHBHAHAEDEAEHEHCFCHEHEHBHBHGGCACAHEEEEFDFCGDH,False +461,9.0,19.0,19.0,25.0,19.0,17.0,20.0,16.0,BEGCGDAEHEDBDCEHECACAEAEAFCEGHGHFHGHCEDDDHDEGGFEHEFDFGFDBDBDGDEDCFCFHECBDHACCBCBFGDGCHBHDDBGBGFCBCDDGDACFGGGGFGBEBEGHDBDFCFBFDFDBHHAHAEDFBCBEBEC,False +462,9.0,14.0,11.0,15.0,9.0,10.0,15.0,17.0,CHCHCGCBEBDHEHFBGDGDGDGDBDGEGCHHBDBDACFCHGFEAHFFDCGAGBFHEDEHHAHAEBHBHGAGBFBDBCFCBCBADAGEGHHEFDFDGDAH,False +463,15.0,16.0,16.0,16.0,13.0,12.0,15.0,14.0,EDEGEDHBHDHDACHCBCAHADGDGAEEHFGFGFAEGEDECGGAFAFDBCHCGCEBABABABDEACHCBABAFGEACFDBBCBEGEGCDCDADBDFHHHHHBDCDGBFFGFHCBCFG,False +464,20.0,13.0,10.0,7.0,14.0,12.0,14.0,15.0,HHHBDFFCHCGCGAGDFDGEBFBABAFAFHGHBAGEGEHBACFCEDBACCCABADAGBGAGEEAAFAFACGCFAHEHEDEBAGEHEHEGAGAEFHHHHABEBDBF,False +465,32.0,28.0,23.0,18.0,15.0,22.0,28.0,21.0,CAHHBFBGCACEGFGAAABABAGGCGCGEAAGCGEEDBDGDCDHDBBABAFABAEDBGCEDBDBAHABFHEDEDBFFGAGHHEGAGHEECDCFBHCGBDBDBFGFDFCFAAACACFGHGAGDCFGAGFFBHCHCEABHBFBFHFAFHFEFBABGBGBGHHHAHAGEFCCHBHCAGBCDCECADADAG,False +466,14.0,31.0,26.0,20.0,17.0,27.0,15.0,13.0,BBBBBCGFEFDFDFCCDCHHDAFADACCEAGGCGCACFFEGECEFECCACGEBAGDGHBABDBHBHFCBHFCFCAHDCDHBGFEEDEDFAFHHGBBFAFCCCFAFDFEBBABACHHBDBDBFBCCFFFFFFDBBBBBEBECEGEGDGDGEGCHEBCDFBBBDD,False +467,15.0,12.0,15.0,11.0,17.0,18.0,18.0,13.0,HAGECCBCFHEGGGGBGBDBGBAFACCFCFCBDFAAAAACEEEFECDFDCDCDHBGGGFGDABAGAFFEAEFHBEDEDEFBAHGCGCHFGFGFHHDHECEAEGFAFHHEHEBBGEHFDC,False +468,22.0,12.0,14.0,17.0,19.0,18.0,16.0,15.0,DADADADAHAGABAEHFGFGEGBHBGADHDGGACHEHCHGEFFBCGCAFGDGAEHEAAFCFGAHAHEDDFDCHFEFEDEBECABEFGBGAGCCECFCBBBBHAEBECCADEDHHHEDEDEDFFFFGDAAAFCF,False +469,18.0,26.0,29.0,20.0,29.0,19.0,16.0,15.0,CGCGCHCFCGHHCHCHCHCFAEAFFECEBFGDHDCECECHCFFDBDEDBGGEGAGEHBBCCACABEEEAEBEBACECGADBBHBDBEFEFEFCDDGCCBAHHFCBHBADAGFDBEFEFEAECBFFHABDBAEDECECEDBFBDBDBDACGEGEBADCDGBGDGACFEFBAEH,False +470,6.0,1.0,5.0,5.0,3.0,4.0,4.0,6.0,CBCAGGHDHDHDHFHFEECACADHCAFAFGEADG,False +471,8.0,12.0,3.0,4.0,7.0,8.0,8.0,2.0,GAAFBEGEFDAGEGEFEHGBCFFFFGBBBEBABABDBDBEBDHGCABACAGF,True +472,9.0,4.0,9.0,5.0,3.0,6.0,1.0,7.0,HACGCABHCEAFHBHDAAACFCBEDEDADAHFHFCFAFBCDCHC,True +473,2.0,1.0,5.0,2.0,7.0,3.0,2.0,10.0,CCHCDDGFHAEBEHHFACHHFHEHEHEHECEG,True +474,8.0,7.0,5.0,9.0,9.0,4.0,1.0,12.0,BCDHBCBADCDHHAHDHAHEDEDBHEEDHCHAFAHAHCEGDADEFEFEFABHBEB,True +475,11.0,5.0,2.0,1.0,3.0,2.0,5.0,4.0,AACDCFHAGAGAEBGBHBFEAGBGAAAHAHABE,True +476,25.0,30.0,25.0,21.0,26.0,22.0,25.0,24.0,HGHEDBDBCHEHEDEDEDEDCAHDCGCFDFGEGDGAGAGHGDGDCAAHABAFACBCBCEDEAEDEAGDFEBEBEHGHFHFCBBFGHGFEFBBBFHGBCFCEBABADHBCACGFHFACACDFABHEAEHHDGACHFBFBHBHBABGGDBABGFEFBHGHAHEBGBGCFBEBECGCACEFAGECACFDFEAECCBGHCDD,False +477,15.0,14.0,22.0,19.0,17.0,22.0,25.0,22.0,DFGGGFHHCHEHBGDEEBFBAAHGFGFGACCCGHFHBHCDEEFEFBFAFBFCGCEDEHEHEBFAFAFAFGCGCGDBCBFFCHCDDDEAEAGDEDECGDGABBHDHDFDFDGCGAHEHFHCHAACDDBHHACBGBGAGFFHCCGHHCCGDGDGCGEE,False +478,14.0,12.0,9.0,13.0,13.0,17.0,7.0,13.0,AFAFBFBDAAADFFBFBEHGFEFHAHFGDDFDHAHADABFBFHEHECCACGFBDBGAEHCDCHGHGEAECECEFECADFDBGBHBHEHDDFEFDBEAC,False +479,29.0,20.0,16.0,24.0,27.0,18.0,17.0,26.0,GEHHHAHEGBGCHCBCFGDGBFDHCCBCHFHAEFEGGDHDACEDDDCDFDFDHBAADHFHBEFEHCHCDFAFABAEGBHBABABAEHEAEAEDEAFHEDAGEBEFGCEDEFEDHBFFDFAHHDBDGDHEAEGCBDEDBAGAGAGAEAHACACAEAEBHAHGFGEBEADADBHBHFCC,False +480,11.0,14.0,7.0,9.0,18.0,15.0,6.0,9.0,FAFEGDGBBEFEDEFEFABAGEGEFFFBBCBEDABEGAAAFHFDEHHFBFDFAFCDCDEGHHCHBABCBEHEHEBEBEDEHABEFACDC,False +481,8.0,4.0,7.0,16.0,11.0,8.0,9.0,4.0,EEADADFDEAFBFGEGFGDGCHDDCDEBEGEGCFCHDAGCGDGAECFCEDDFDEABABADDDDEHFH,False +482,11.0,7.0,25.0,5.0,16.0,24.0,10.0,11.0,EAEAEACFCBCEFEGAGAGCCFFEFGBCFFHFCFAHACFCEEHCCFDFEEHBHFHAGFFEFEBDAGCGFAFEFEHECGCGCFCFHFHCCCBCDDBCCCCFDFHAECBHG,True +483,24.0,31.0,31.0,29.0,20.0,23.0,19.0,21.0,HAHEECBBBBGBECEFBFHHCHFHDBGBHEGEADAEAEBBFBCECFCACABHCHCEBFDFCFCFBFHHHEGCDCDCDHDCECGABADDDBAGAGAHEDEBBDGCBCFAFABAHCBCFHGHBDEDGBGEHCDCFCFCAHFBCDCDGDHABGFEBDBDBDGAFAGAFDDCEFABAFDDGAFEFDGCBABHCGDGDCDCAE,False +484,10.0,14.0,9.0,7.0,6.0,9.0,6.0,9.0,HCACBFBFCFCFHAHADACABDCHGHGCBFDHCBGBABFBDBFBEEHADADHBBEBADAGECEFHBGEGF,False +485,10.0,4.0,11.0,5.0,13.0,7.0,15.0,10.0,AEAEHCHCGCGCBEGEGFGBGAGFGEHAFGCHDECCAHADDFDFHFHEGEGACCBHDHAEGEGCGHBEEEGAFAC,False +486,10.0,4.0,4.0,3.0,10.0,7.0,9.0,8.0,HGHCFDHAFAECEFHFHEGECHDDACABAEEEGGAEAGAGAGAHFGFEHEFGBBB,True +487,5.0,6.0,9.0,7.0,10.0,8.0,5.0,12.0,FCFCFHFAFAFGEDCBEHHGGEHEHAGBHCHFEAEDEDBHADCBCDHDHDFBEBCCHCGEHE,False +488,11.0,11.0,11.0,8.0,15.0,8.0,13.0,12.0,CBABEBFHFGEGHCDCAGDGEABBCGGBBHEFBBABGBADEHCHCEAEAEGEFFFCGCEHDHDHECDCAFAGAGAGEHEGFDHCHEHED,False +489,22.0,25.0,26.0,26.0,18.0,25.0,28.0,23.0,BEBEBEBFFHDHDHCHDHCCGCFAGCHCHCDCGCABABAFCHEHBCBCDCGCEHAHAEGGABFDHEBECGCHCHFDADAHHEGFBHAHFDGDCCCHFFGGGGBFAFABGFEFAGGFGDBAHFEGEGEDBBEDDBHBDFDFGGCEFGFBFHGADADHCEGEGDGDFDBBCBCDGBADABAFCFAFADDDBCGAE,False +490,19.0,24.0,22.0,16.0,30.0,19.0,23.0,31.0,FGGAFEFECGHHEGEHEDEFEHAGFBFBFHAEAHAEAEACDEBBHCECACEGBBFBDBCHDHGCFEHHAHAHBEBECGGDGCHBHGFGBDFCGHGHDHBHBACACHBEAABDHEHDHFFBFHFHEBCDEDEDFDGEGAGADBCHFHABDBDCFAEAEBEBECGCGEHHCCBCHCEGEGHFCGEG,False +491,16.0,23.0,19.0,29.0,31.0,20.0,28.0,25.0,DHDBCECECAGFGBBEEEECEDEGHCDGGAFDFGFGCGCEHGHGEDFGCDFGFDDDCDEFEABDEDEBEBHBHBGGHBDBHAFABDGHCECGAEAEAGABHDHDHDHBBBGEHEFEDHBEEEGGCDEFGHGHAHAFCFGFEDCFEABHFHEBEBDHDHACBCFGAGFGHEHBGBCHFGDDADCDADFDECB,False +492,2.0,8.0,8.0,4.0,4.0,4.0,9.0,3.0,GEGFACBGAGECCHCHCBFDGHCCGCGBDBDBEBEFDFBGBG,True +493,21.0,13.0,20.0,26.0,11.0,13.0,10.0,15.0,AACGHHEEDBDBDCDCDBEBFBFEGDCEADDDFAFAEAHHHFAFADEDCHCBCAAGACDDDDDBCAGDCDBEHGHGFGABDHDHCCCCHADAEAEDHDAACAFAFBFEDGBHCCADHBGBDFCFCHCFG,False +494,4.0,3.0,5.0,3.0,3.0,7.0,4.0,3.0,AHFEBAHCHGFGFEFDADBFFCFCGCGCBEAD,False +495,0.0,4.0,1.0,1.0,4.0,0.0,2.0,1.0,BDEEBEGEGHBCB,True +496,6.0,16.0,13.0,12.0,12.0,13.0,12.0,10.0,DHFEEBAFCHCHCEFHABBCBCFGECECEGEBDCDCBBBBFAFEBEGGCGAGFHEDGBGEGCHEBDBHBHCGBHAGDFDFDFDFDHCADFDFGB,False +497,19.0,9.0,12.0,22.0,14.0,24.0,20.0,18.0,DEDAHEBAAGDBHHGABAGCHCDCACFCGCEEACBFAFAGEDDDHHHCHCGFGHBAGAFAHDDDDDGDFDFHFEEDEHFHEBFDFHBAGHGHFHFEDEDFDFDCGBFACAGAFHFEABGEGFGFGFECADAGGDGFFF,False +498,8.0,3.0,6.0,14.0,8.0,17.0,6.0,15.0,GFFDFEGGBEBHAEDGFAFEFDDDAFHCHCDCDGFHAHFHFGDHCEFHCHCFDHDHAFDFEFAFABAEHFHDHDEDH,True +499,0.0,6.0,1.0,2.0,2.0,3.0,3.0,4.0,EDECHDBGBGBHBHFGFBHBF,True +500,9.0,11.0,8.0,10.0,19.0,12.0,9.0,5.0,GCFDBACGFBFAAAAGBFAEGFGCGHEAGHDFFCEDEDEDEDECHBEGDDEAEFDFAFEBEHEHEDEBEBEBCBCBFFEGBCE,False +501,8.0,14.0,12.0,11.0,8.0,12.0,9.0,4.0,DBDBEBDBDFDAGCGFBCBCFFGCDCDEDBBBECECFBFECABDDAFAFAGEFBHAGAFCHCDCGHGHBFBEGEFCAG,False +502,5.0,5.0,5.0,5.0,9.0,6.0,4.0,8.0,FEFEBHHHAHABEBDDFDHDCAFFECEAHCBCEAEBHGHGCGFDEGE,False +503,12.0,12.0,13.0,25.0,16.0,10.0,18.0,21.0,GBGBDECCCFHHBACGDGDGDADCGCBBHDHDHDBDFDFDHEHGCEDEGEFAFHBEFFGCEHFFDDHDHGHGDAACAGBDHGHEDEDGAHCGDGDACEGAHAHDHEHEBEBCBFBEHEADDGDCAHE,False +504,10.0,15.0,9.0,13.0,14.0,7.0,8.0,9.0,CBEEFBBGBGBDBABADFBAAHEBEDEDGFCEBDBHAHBCBCBGGFDFCAGAFDGDHDHGEBEHFHECECEAHCDDEHEAEADCD,False +505,18.0,16.0,17.0,23.0,12.0,18.0,20.0,12.0,FGFABEFDHDHFHGDBDBGBGCACDDDHAHBHFFFBGCGEAEAGABHBGDGCECEDHFAGBDEAAHCEGHDEDEDFGHDDDDEFFAFGDGCFCFDFDACFCEAABGBABCBCFHGGBGEGAACCCCFCGBADADBD,False +506,22.0,16.0,25.0,22.0,25.0,11.0,27.0,18.0,AGCDCDHDBGCGAGDDCDGBGDCBCGFGHCECGHGAEFEDEAEGEFHGBCBCAAAAGGDGEHEAEDEDEBCBGFCFGDDEDECFDHDBEAEDEHGHCCCCABAFABCBAHCHGHCCDCEFAGEHAGAGHEBCHEGBHBHDHFEEEACACDEDEHGGGFBFBGDAAA,False +507,13.0,17.0,22.0,10.0,17.0,14.0,17.0,13.0,GGGCBBBEBHAEAGHDCGCDHFEAEABHCHGFGHGCCFFBCAAHEHEDCGCGCDADEHAHFDFAFCHCFCBDEEAEFHAHFCFABBDBDEGECEBGBGCGCDEEBEBFBEACBCGCGBGCFCF,False +508,17.0,21.0,24.0,12.0,17.0,20.0,19.0,17.0,ECHCHCHCGCFBGAGEBEBEBDCCFHFGCDFFHHBGBGDDDGFCFCGDGFAACACGFHDHGAAHAEBEGCCCFGFADADHBBBBABEBEBCGCHDHBGEHCACECEDDCFFAFEBACAEHEHBGBHEFAFBGHGFBCBEAEAGFFCF,False +509,4.0,0.0,5.0,5.0,1.0,0.0,3.0,4.0,GHDCDCDCDCAEHGCDHHAAAG,True +510,10.0,11.0,3.0,4.0,7.0,2.0,18.0,3.0,HAGGGGAFAGCGEGBGAEBGGEBEBDCEGDBDADEBEGAGAGBBBCGGBGAGHBHAFA,True +511,2.0,4.0,2.0,2.0,1.0,2.0,3.0,1.0,DEDFHGABBBBFAGCGC,False +512,2.0,4.0,2.0,1.0,1.0,1.0,0.0,1.0,HDBABCBCBFEA,True +513,4.0,5.0,8.0,7.0,6.0,8.0,11.0,4.0,GGHGHGDBCECECEGFHDABADEGGCGCECBFEGACFFFFBFCFHBAGGDDDD,False +514,20.0,26.0,19.0,15.0,24.0,22.0,24.0,21.0,FGFEFEFBHGHBEDHHHHEDCDEHEHCBFHGAFAFBFDCACAGGGGGGGHBBABFBFBCHGGBACGCGDFEEEEAEFFFFDECECFCBCBEAHCBADEDAGFDEDBBEBEHACAFAFABHEEDCFGHDAABEBEDGGHGHGDDFEFAHAHBGCGBGCCCABBHBAGCBHBE,False +515,22.0,23.0,26.0,33.0,16.0,30.0,25.0,23.0,GGGGCBEHCBCFEGGFADHDHCGDACCDBDGFCFHBHGAABFBAHAHDGDBDADACGCFDFGFDDHBGGGEBEBEFGFHBEFABEGCGCGHAHFHFHDBDBDCDCDCHFFFHFDFAGEGBABFEDBDCECBCDDHDBGECADEDEFFFFAFDFDECGHDFDFBCGFECHHAHAHGCBCDADAEAFCFCDHDABAHABC,False +516,17.0,13.0,13.0,12.0,15.0,20.0,10.0,20.0,FDFAGABHFHCEEAFCEGGBEBCBCBEBDHFACGHGCACACAHFHDBGFGDAEAEABFDEDHDFAFEBDHHHFHFHFHAHAHAEAFADCCFBBCEHFFFDGDGBEHHHHGCBEFEAEDFC,False +517,26.0,21.0,23.0,17.0,23.0,30.0,24.0,22.0,ABAEAEAEBGGGGGAECECEDFCEBAGHFHAEADCCGGGAGBEBEBEDCDFAFHFHGCCBHAFAFAFHFGBCDDFACGFGHDEEGEFEGBGFGADFCFCFCBAEABCDHHHCHFHFHBHAEFFFCFBECCCFFDFDBCHCADAFHBABDFDBBAHGGEAEHCGEGCDAGAHDGDFHFHFEBABEBH,False +518,7.0,13.0,9.0,12.0,7.0,6.0,7.0,5.0,CGCECBHDEBGBAFCDBDBDACEBDDGDGEGEFAFAFAHCFEHEDBCBDBDCDBBBDCHFBAGAGH,False +519,15.0,23.0,14.0,11.0,17.0,17.0,14.0,16.0,AFGEDCHBBBBBBGGECEFFBACACBCGCBHFAAABCCEEDDDHBBFBFBGEHEFDAEAFFFEHAGABAFHFBDBHHHBEBEACGCGCACDCHEEBEGGDGHGHGDDDCBGAEBEFEFAFHHHFHFB,False +520,18.0,12.0,17.0,12.0,18.0,12.0,16.0,36.0,EGEHCHDHDGDGCADAHAHFCEEBACEEEADAHHBCBEHEHEBAHCEEGCFEFAFABHBHGHDCGCGDHDHFHDHDHAHCHABCGCFBHHAHFHFHFCEHEAAHHBHGEAHHBFCCGBGFHAEAEGCHBHGDGDGAGFHHC,False +521,4.0,11.0,9.0,6.0,9.0,15.0,6.0,12.0,FFFCCHBHCFCBCBFDDGDGBFAGCFEFCHCGFBBBHCHDEDEAEBHBHGAEAFFBEGEHEHEHBHFFFFHD,False +522,17.0,10.0,12.0,14.0,22.0,13.0,17.0,18.0,EEEEDEABAGFEFEHGHBDAAABDBDAEHHAHGHGHDHAEABHHHHHBCGCFCFCDBAGACEEGCGAADGDHAFCFCEBEFDFEEACGHBEFEFEFEDCGFGHGEGDBAEGEDCHAHGDFDGC,False +523,0.0,4.0,3.0,2.0,1.0,0.0,4.0,2.0,DDEBCHCGBGCGBGBH,True +524,25.0,20.0,21.0,11.0,21.0,16.0,21.0,28.0,FGHGHEHEHBHFHFBFBDBEGDCHCGAEAFCDEAAACHEHEHBFFFFAAHCGGHGBGBHCHCDCGAGAGBHHHFDCDAEABBBCECBGGFACHCECEAFAGHFAEHGGEDEDEBHHACCCACBCHDGDGAAABAGFEBHAGBGCFEEDEAEAFBECHHAHBHB,False +525,5.0,5.0,3.0,6.0,5.0,16.0,3.0,8.0,DHFHFEFEADAGEGECBDFCBDDFHCHFAAAFEHHFBBBGDFFFFFFFHFH,True +526,1.0,0.0,1.0,1.0,2.0,0.0,4.0,6.0,HGHCHEHEGGHGDAH,True +527,14.0,26.0,15.0,11.0,16.0,18.0,25.0,17.0,BHFABADGFABCDGGECEBEFEDBDHGFCFDBDBCEFBFHAGBFEFGFHFHCHBHEHFHFHCHCEDBDBEGHGHGCBCBGDEEFCFBGBGBGBCBDBGAEAGBGAGECEAFGGGHGCCAFGGEAEDBHAGABAFAGHHCBBB,False +528,26.0,33.0,22.0,21.0,21.0,26.0,21.0,23.0,HDBFBDGDGHHEBFFCECFBABGGEBEGGAHEHABGBCCCABDFEFGFADACCGABDBFBADADBDAHAHBEGHFHBEGEBCBCBHAHABADCHBGCDEDEDHGGGGGCDBFFFFFAEECHCHCFEBEAADFBFBABDBGEEHEGEFCFCFEAEADCGFADHHFBDBAHAHACABABFBFCFHBHBHCDFGCD,False +529,19.0,28.0,16.0,26.0,16.0,17.0,19.0,17.0,ABADGCGBHDFFFGFGDGFBDGGFAFCGGFHHAAFFFEAAHAHCBCBABADDFFFABDBDBHGDACHCHGBBBBBGEDADAGCBEBHHEDBCBCBDEEGADABABADADCCBCBDFDFCBCHFEEEDEHHHGHBHDEECHGDGDBEEEDEDGDGCBBD,False +530,10.0,4.0,8.0,6.0,5.0,11.0,7.0,6.0,FFBFCDCGAGFEDCDBEGEGFCFCFCBAFDBHAHAHAGACAHAHEGDFCFADEGAFH,False +531,13.0,7.0,11.0,9.0,7.0,13.0,13.0,17.0,GCABEBFBAHHHGHGAAHCHBEBCDAFHFHBCDCDCDFGEGCHAHEHCHDFFFGFGCGAAAHGGGHFCECHHHGAAEADFBFDFDEDAGF,False +532,6.0,4.0,4.0,4.0,4.0,11.0,3.0,7.0,ABCDHFHFECEDADFGHAFCFCFBFBGADEHGBFHEHFHFAFA,False +533,14.0,30.0,24.0,27.0,22.0,23.0,21.0,29.0,CEBEDGCHDGAAABHEHGCGBFBEGDDDCDCHHDEGFHCEFBGBCCFBAEAGABEDFDCDCDHDHGFGHGCGDDFBBBBBDFDADCDGBFEFDBCFCFBDHDGFACAGFDFDEAECFBBHBHCACAHFDEHEHBDBGBHBFBEDCFEEHBHBCBCBHEFEFCHCHEAFHBHBHEHFGCAEGHGHGHGHED,False +534,7.0,14.0,11.0,10.0,12.0,6.0,11.0,7.0,ABADCBEGAGABDBHCECDBEHGCBCBCGCFCFHFHFBBCBGEGHGDGEGEDDDCDEDABAHCFEEAEFEBBGDEHBG,False +535,1.0,8.0,7.0,5.0,5.0,7.0,1.0,7.0,BHBGFHEDDFCBBBBHHHFEFHFCFCACBDBDEHEFECCCD,True +536,5.0,4.0,11.0,11.0,13.0,6.0,6.0,8.0,CDDDEBHHGHDFGCCACEDEDECEGEACACHEBFFEFEFGFGDGDHAEEEABCBHEDCDCHHDC,True +537,28.0,21.0,11.0,18.0,13.0,11.0,21.0,19.0,HGAGAGFDDHGEBDCGAAHGHEDBDFDEGAGHDECCAAAADDGBBCBHBHBHGCGCBBBFBFGABAGCHBGAFHFAACAGDFEFEGGBFHAADADFDADBBBDAEAFHGHEHEHAHAHAHAGEGDCDCHBABABECDGAEBE,False +538,3.0,5.0,4.0,4.0,5.0,2.0,1.0,6.0,HCHGHAFBEBEAEACDCHBEBFCEHBHDDD,False +539,6.0,6.0,7.0,4.0,9.0,4.0,6.0,1.0,CCAGDGDGEFBCACBCGDDBFEFCFEABABCEEEABAEGEGEH,False +540,4.0,1.0,2.0,4.0,0.0,6.0,5.0,0.0,FDDGAGFGCGAGAFFFBCDADF,True +541,9.0,14.0,13.0,6.0,8.0,6.0,10.0,5.0,CBCGEGEFEHAGEDBGEGAGHDCBCGAGAGHDFGAACBBDBDFFCFHFDACACBBEBECCCCHEACBBBBB,False +542,16.0,16.0,8.0,16.0,13.0,11.0,10.0,17.0,EAHAGFDCGCGDEHCHBAAADHDHEHEFBGBABFDAAADBDADADHDGEGCGHGBFAFEBBBBHFDFDEBEFAHEBDGFHCHCHGDFABABDHHHAEBEHEDEBCCF,False +543,21.0,26.0,17.0,27.0,29.0,23.0,26.0,18.0,GDEHHBFFAHDHDCBHBGEDBDGAGDHCEEEBFFACBBEDGFCFBEBECAFDDHBHDEFEFEFEGGCGBHFFCFEHBHEFBHBADAEAGAFBFGEGEGCGDEDEGCGCBDFDFDADABCFEBBBDBGGGFGCDCDCACFEDBGEGEGHABGEGEAAAACCHEBEDEHBABFGFHHEHADGDADADAD,False +544,22.0,22.0,21.0,19.0,23.0,23.0,21.0,20.0,CGDGDBCFDADCCGDBDHAHCHCEDFFGGGECECEAFAHCFDDEDAGCGCBDEDEAEHCHCEEECEFBFHDHGHGEGCHFEAEAEFFCFEDEABHHHGFBAGAGBDEGECECECHBHAHGBBFBGBDFDGAAFAFGBBCBGBFHEHCBDFFFHFBAAHBFBAAAFAGABDB,False +545,23.0,25.0,25.0,15.0,25.0,17.0,21.0,33.0,GAGAGEEHHHFHFHFHEHDCFHABBHBHBEBHFGBCCACACACGHBADHBECECEBABECCHCFEGHDCEBGGEBEBEFHHADCDCDFDHBHCAEEHEHFHGHGHFADCGFHCACACACBCEGDFHCABGDGEGFCDHGHAAAHBHBHBEBHBHAGABEEGEDEGFBFCGEDAGADDBBEAFCF,False +546,3.0,2.0,2.0,4.0,0.0,4.0,0.0,0.0,ADADAFCFDBBFCFD,True +547,13.0,21.0,3.0,11.0,13.0,5.0,12.0,11.0,GHBADHBHBGBEHDHEEFGHDHGFEDDDEGEAEDFAAGBBCBAGAGAEDEHBHBABABAGADBEBECEAEBBBBGBHBDFGCADBFBHG,False +548,25.0,24.0,22.0,17.0,28.0,18.0,39.0,21.0,CDCABDBHBGBGBGBCECBABGBGAHAHBFEEAEBGAGEHFACACDEGEGECHAEGEHFHFABEGHFHAHGHCDCEBEGDBFAFHGEGBGAGDBDBDBEFECHFHEBFGEGEGECAFABEBGBGHGFGEGCCCCHGFACGBHAHAECFGAEDHGHGDDDEAFADGDGDCAEGGACFBFAGEGACCEHDCDGGFG,False +549,3.0,2.0,4.0,4.0,5.0,8.0,5.0,2.0,HFEFGDGFBFDFEEEFEFGBGCCACDCAGAHFD,False +550,1.0,3.0,4.0,3.0,7.0,2.0,2.0,6.0,ECEBHBHGHBECEFDHAHECEDEDGCHF,True +551,16.0,22.0,21.0,26.0,28.0,20.0,19.0,21.0,EGEDEBEAEADDDCFCABGEFFHDBECHBBBBAHAFFCCDDDDDDHGHEFAAAAAGGBGFGBGCCHEHFBFHHDCDFFBFDGEGFCABBEBEBECDGFEECACDDBCFEDEHHDBDFHFHCHCEGGGEGEADCDCEGEFFHHGCCBCBDBEBEAEAEAGDFHCDGDHBHEHEH,False +552,4.0,5.0,6.0,11.0,3.0,11.0,11.0,5.0,GCCDFHFBDDEDECGCGDGHABDDGGGDHAHAFGFGEGFGFABDFHFCFDBDBFFC,True +553,5.0,13.0,12.0,7.0,6.0,1.0,8.0,8.0,BGDACECGDGCCCBCHCGCDBHHGBEAEAEFBCBEBDGCGDGCBABABEDCHHHHHBBDB,True +554,21.0,23.0,19.0,23.0,24.0,21.0,32.0,21.0,FAGAHAHFHGHBEEFGADABCBGBGFAHEDEFGFBHCECEHEHDGDEAAHGGGEGFFDFBCHGAGHCDGGGABDGDADHFEBHBHGGCACBCBCBGBCFADADGDEDACBGHEFDFHFHFBDDDDBHBGGGCDEFEGEGECHCBCBEBEBEFFAGBBFACECECDAEFECGAGEFDGGAADHDH,False +555,11.0,14.0,17.0,9.0,22.0,14.0,9.0,22.0,CGEEDCDADADBDBFFFHCAAEHHHEHEHAHEFFCFBGHHHFHCHDHEBGFGFBEECFCEEECGCGHEEEEADHBHAABCCACFCEDHCHCHBHBDBECGCEFFGFABBEBEGHAHBE,False +556,4.0,3.0,4.0,4.0,4.0,1.0,0.0,1.0,BABHECAAFBDCDEDEDECAC,True +557,11.0,15.0,15.0,16.0,14.0,18.0,14.0,14.0,BCBCBGDGCGEAHHEHGAFFCFHFCGAGACEBEBEBAFGCCDGBCEFDFDAEADDFDCEBFBFBEHDHEHEGEGBGHFHDDDDCCBGBCBHAHDEFFFGGCHBEAAAHFFDFDFDHC,False +558,5.0,2.0,3.0,3.0,1.0,2.0,3.0,2.0,DGDGACBFHFHAEACABACDG,False +559,29.0,26.0,17.0,17.0,20.0,26.0,24.0,23.0,DADCDFFHFAFACAFBDBACAGABFGFBHCHCFFEFEFGHGCBCAEGGGDBDBABFHFAEADDDEDEHAAGGDBHGFFFFCGAHBBGBGECEGEGEGEBEDCFFDFCCEAAFDHAEBFBFAHAGFHCCGBGBGBGAGABEDADHEBEHHAEFHAHABCBCHAEAFAEBHGHBBBAGDHHHHC,False +560,7.0,9.0,14.0,11.0,8.0,12.0,13.0,5.0,FCDCEFEFGHDAABACGCGCGDEBAHHBCCFCFGEGDBDBDBAFECDFDFEGGCAFABCFGFGEGHCDEDGDGFCBCBH,False +561,16.0,32.0,21.0,19.0,21.0,20.0,22.0,22.0,AFBGBGHGEDFAACDCDCEFEBCFCGHGHFDABABAHCCEAHBEDEDBDCCHGHEBEBEBCDEFGDGFBFEDHDHDBBBFFEGBGHEDGDFBGBACDGEBEBHBHCCGHGHGDGDGHGHBCAFHGHGFABAFAHAFCBCBFAHDHBBCBGFEBABCBCFCFEEBCFEDEAHBE,False +562,18.0,21.0,6.0,6.0,14.0,3.0,15.0,20.0,DGAAHCHBAFHBHBGCAEAEAHAEAHHHBCBGGEBDFAHAEAEBGAGAHDEGHAHBEAEGHGHBABHBHEDCGHGBEDGBGEGBGBABDBAEEHFHBCBCBHB,True +563,19.0,18.0,15.0,19.0,14.0,16.0,17.0,24.0,FAFAFABBHDCDCDFDCAABFCEDBBECDCDFFAGADBCHGGFHDHGHEECEGDADABEHHHHCHDHDFAHGFGFBDBCBFHAGABDBGBFDGGFCFCBHBHFHEHEHEGAGAHAGABAGABEECDCHHEBEDEHAGCGHDH,False +564,3.0,3.0,2.0,1.0,0.0,0.0,0.0,2.0,BABCBDAHCHA,True +565,8.0,12.0,12.0,9.0,13.0,13.0,12.0,17.0,BFBFEEHBFAFGGGCHDHDHGCDCGEHAHEEBBAEFGCGCHCFCFDBBBHCEBEHEHFGAGFFHFHABDGDFDFBHAHDHEAABCEGEGEDCHCHC,False +566,24.0,19.0,7.0,22.0,15.0,14.0,18.0,21.0,AEADAHECBGBFHGHDHAGDGHGBGBHFHBDDDHGHDHDADHDHAHDEDADGFEFGFBDBDFAAAAABEFDHHHEGBGAAEDEGEGAFAFHHBEEHCGBEADAEFFBFDFDBDBGBHAGBCBEFDHGCACBCBAAACAGE,False +567,18.0,34.0,25.0,23.0,26.0,29.0,16.0,24.0,CHFDFHBCBDBFBHEEAEABABCGAFDFDADADADBBBCBDBFCEEEFFAFDBDBGHDHBBBFFFDABFHGCABABABAHHHHDFBFEFHBCDCFCFBFEEGECFHEGEGBBDDHDEDHFHDHDFBAECCBHBEBHBCCCBDBEGHGCFCACEFAGEGEGCCFBFEHEHCGFECGFDAGFGHCCCEEEBEHAHDG,False +568,10.0,3.0,8.0,11.0,10.0,4.0,2.0,8.0,EGEDEHEHCDCEAEAEAFFEHCDDDCACHBHBDDDHAAACAEBFAGAHDCCFEDHD,True +569,16.0,11.0,9.0,12.0,15.0,17.0,17.0,12.0,EAEDEACHEAGBHHFFAGGDADADHBHAFFGDEDEHFBFCGBGFFDGHAEAFBCBEAECDADCGCGFGEGEGAGDEDBFFAFAFCBHAEAEGEGFGFDCHCGFBHBHBH,False +570,5.0,3.0,10.0,3.0,5.0,7.0,4.0,6.0,DADCHHGACACECHCFCFHDEGABAFFFFECECFGGHBCBCEH,False +571,19.0,19.0,10.0,25.0,20.0,11.0,12.0,21.0,EGEGEDDDADCBFBFCHCHGAGDHDHDADGHEDDDDHBHBHCADEEEDDHDBCEAABABFEEAEGHGHFEADDDCABHBHBHFHFEEEEFDCEEGCBCHGAEAGABFBHAHEHAFABHBFDDDBDBHAAFBBAGGCD,False +572,9.0,14.0,14.0,11.0,15.0,15.0,19.0,10.0,EFEAEGGGDGDADFHFGFBFBFGDGBBEBEADHGCBCBCGCECGFDCBCBFDFGEDBDHCAFEFEBGCHAFGFGEEHBGCGCEEEBHCHBADCCGGHAHADAGFHFE,False +573,4.0,10.0,13.0,15.0,11.0,8.0,6.0,4.0,AFCCGEEDEBEBAHAHADFBCBCBEFDGHBEGEFFBFDDBCECDCDCECEDDDDDGDCDCEBBGDHFCCGF,True +574,15.0,27.0,18.0,27.0,33.0,20.0,18.0,26.0,FACGCDEDBABABADHDBEFECGDFHHEBCBCGHHAEBHBHGDADGDGDEEEDEBCBDBEAFHFEDGDGDBCHEAADEDEAEDHCHAFDEDHDACHBHBHEHECFBABHDEEEFEGBGDDHGFBFBFCFCEBEBFFCECEGEFEDGDCBGEGHFCECEBGBHBHDHCEFFFBGBHHHEFAAHDG,False +575,16.0,17.0,13.0,14.0,16.0,19.0,22.0,14.0,HBCFCFDFEGAGAHHGEGBGDGFHEHAFBDBDCHCHGFDEDEFHFBEBHBHBEBHBDFDEDEHEGEFFACACGFHADGFADGBAEADAFBCHEFFBEBGBGBACGGFGFAABGGDGFCCACAEAECDGGGC,False +576,21.0,18.0,24.0,12.0,15.0,14.0,8.0,14.0,CDCDFBACHGHECECEDECECHHAHBGFAAHAGFEBCHAGBBBABCBADCFEGABABCGCFAFEBHAHDHECACHHFCBBBEBECFCFAFAHAFCGDFDFDBEBDCACACADBDEHEFEDGCACAC,False +577,11.0,6.0,10.0,4.0,4.0,6.0,15.0,11.0,HHGHAHGDGCEBABABGCHCGCECHCACHDFBABFHFCAHAHFFBFGGGGGGGACAGECDGAADEHG,True +578,13.0,11.0,13.0,13.0,10.0,10.0,11.0,13.0,HDHDFAHCHGEAAAACGBEEHHDEEEDADCDCACACDGDBDBCFEAGHCFCABFBFGCEFBHHHHGBGCGCGEEHAHFBFDDBDBCGDGAFAFB,False +579,16.0,20.0,17.0,10.0,16.0,13.0,17.0,18.0,HBHCDAHECCCCBHGEFCBCGFFAFACBDGDCHBHBCBEBEDGDFEHGHBHECCCEFAGAEHDGDGHBFAFAGAGBGBGBEECCAFAFDBBHFECBGHCHBHDHBHBAEEEAEHEAGAGFGFGDABA,False +580,19.0,23.0,27.0,23.0,24.0,28.0,24.0,26.0,FGFGCHDADGDHFFDCDABFFFFBCEAECEHADCDFDFABAHABDEDBAHCCCHBAAFAEGEGFGHDHGHBHGHDCFCFCADEFEHBAEEFGCDCGGGGGEHFGCGCFFHFHGHBCBDBDCCCGEBEHFBFCFEECFGHGHFHCAEBEBEGHGHFEFDCHCBCBGBDBEAAABCCEAFBHBHDHEEGABDDDED,False +581,14.0,16.0,19.0,20.0,20.0,20.0,13.0,20.0,ACAFBEAHDHEHBHCABBCHFHCEEGCHHFCDCBBEBHFABGDHFHFHBHBHBGDDDCFFHFBFGFECDCEAGAGACCCGCDCDEDEDADADFFFAFAGHCDAGHFEEGHCEEEHECECEGEFDFEEGDDDGDBBFBFBADH,False +582,13.0,15.0,13.0,20.0,21.0,19.0,19.0,16.0,EGGAGAHBFFEFEHECDCFCBGHFFGAGAGEGCGAGBFCFDDDEBEHEHCFBDDDDDDADAFAHHCFDEDBFFFFHAGCBDAFBHBEDGFGCBCBGEGEDCDCDCFHEHGHBDGEHABEGAGHFEDAHEEEEEBHB,False +583,6.0,13.0,10.0,9.0,17.0,8.0,10.0,9.0,FHFGBBBBABCCDHBEDHGFDEHCGCBEBEHCFCFBFBDBACFHGHGEEECECEDEDEHEDGCAEADFDGEAEGGGEBABEH,False +584,18.0,27.0,27.0,16.0,19.0,28.0,14.0,16.0,FHFCFAFHHBEBFBDCHBGEDBAFFCBHBCFGFGCGCEEEDEDBABGEFBGBAFAFHEGCGCDCDBHHCHAHAHGCECAHFHFDEGHBBCACABABFBFBFAFCDCDBABEBECFFGBECCCHCFAFDDDDFDBECEAEDBFCDCEFGFABABCCGEHCABGFEF,False +585,26.0,16.0,22.0,22.0,20.0,21.0,22.0,26.0,FHDHDHFCEBBDBAAAAGFGCBEDHDHGHAEAECDCBEBHCHAHGGFDAEFCFHHHEECCCDCDCDHAHABBECACADAHCDCDFBBEDAAGAFFHCEEEAFAFGFCECEFACAEAFFHEGFHCAGECFFGBGFGDBDBABAGGGGGHHHAHDDDHHHAHDGEGFGBGBFCEDGD,False +586,8.0,5.0,12.0,4.0,4.0,13.0,13.0,7.0,DFDCCCCCCFEBEBDFFAFGCGCBFDFBAAFHGHGCGAAHGFAFGFGCGAGBCHFHCGGHFHEAEG,True +587,4.0,3.0,2.0,3.0,2.0,5.0,3.0,1.0,BGGGDBDHDFCAEAFCFBFEFAA,False +588,7.0,14.0,10.0,16.0,16.0,9.0,9.0,13.0,BCDFHCGFGAEFFFDDBBHBFBHHGAEDDFDEHEGEGEHADFEEHEGEDEDEDEHHBHBDBHBDCDCDBBFBABACACEHECGHEBDGDCCCAG,False +589,41.0,28.0,27.0,20.0,22.0,14.0,25.0,23.0,EDEHHHEACAEAEGECBBHBHBEFAFEBAFHHGHAHACAGBDBEGCDEHAHADACACGEDCCCFBBBBBFAADACAGECDFHGDDBDCDCECDABAFCBEGEDFCGBGDHACABGHECBGGCDCGEFEAGCGDAAABABABDHGEAHBGAEHGBGBFCFCFEFBHGHBAAAAHABABADAGACACGCACHDHDHAFAGEG,False +590,25.0,17.0,16.0,9.0,20.0,24.0,14.0,17.0,HDFDEGEFBBECCBDBABFFAFDFCECBAGAEABGFHCACAFAFAFHEHEHECFCHEHEHECGBDBAFEBCFAFCFAGGCFCABHGABFFEGAHAGAGCHHEHFDFBEBCBEFAFAHAEFEAAHAHBHBGDGDGCEADAGEF,False +591,17.0,13.0,25.0,18.0,20.0,19.0,18.0,19.0,ADCFCHDBAEHEHEFEACAFAFDFEFECEGADHDHEBCCCCEHHGBDBDGCCFBGDDCGABAEAEDEAFAFCGCFHFEGAGDGFHCGCEHEAGCHCBDEDCFEDHCBEBFBAGEGAHCHCBCBAHACDBDCDCHFHEGFGFGDGHGFFH,False +592,4.0,14.0,3.0,5.0,17.0,15.0,9.0,5.0,HGFEEHBHFFEFHFEGBABFBGDFBBEFEDGDEDECEBEFEAEBBBBEBFAHAGFDFEFEBGCGFGBGFECE,True +593,13.0,8.0,10.0,11.0,8.0,10.0,5.0,8.0,EAEADADGFGCDDFBFHHGADABAFHHBAEABHHGBCFCFDFAFDHDCDCBFBCCCBCEEEAEAEFDAHACDG,False +594,16.0,13.0,15.0,7.0,3.0,9.0,20.0,22.0,BGBGCGHHHEHGAAFGCGBDFAFBHCHBDBCCCFDAHHBGBAAABHHHGHGBABABCCCCCDGHGHCHAHGEGDBFGFGCGAHAGFCHGGGAHAHCHFEDHDAAF,True +595,12.0,10.0,9.0,7.0,8.0,10.0,12.0,10.0,AEFDFGFGABHBHBACAHFFEECEFDFGBCAABBCDCGEBEBHHHHFBAEADGDGHGDGDCACGCACAEFHAHGGGBF,False +596,12.0,14.0,7.0,5.0,7.0,8.0,16.0,11.0,DBGBABFCGCGEGBGCHCABEEHGGGHGHFBEBABFBFBGGGGFDFCGABABAFAHHHHBEAAADDHCFEHAHBGACDGE,False +597,12.0,31.0,25.0,23.0,29.0,22.0,19.0,20.0,GBCAEDEGEDHCHGFBEGCCDCGAFBFAFEGBBDBDBDGGCEHEHFHDCDCDEDFHHBGBGCHABGCGCFHFDEBCDHDAABFBGBHDCDCEHEBFBFEFBFHEHEGEBBDBEBABCDGDBHBDFDFDACCEFBCBFHFGCEAEDFCCDCFGGEEEAEAFAFBHBEBCBCHEHCHGEEEBE,False +598,3.0,2.0,2.0,2.0,0.0,4.0,2.0,0.0,DADAGFCFCBGAFBF,True +599,18.0,18.0,17.0,19.0,19.0,25.0,24.0,26.0,EFEFADADEGEGBBHHABBHCCGAFDHDFEHHHHHHGAAADGHFHGGGGDEACHCHCFCGEGEFABEEGEHFCFDFEBGAHCHGFGFGFGFDDHEFCFEBDFEACAFHCHFBADGCGBADGDAFCHCHDDDFDFHCHBHEEEBEBGBABABABCBFFHFDGCGBGD,False +600,18.0,13.0,8.0,18.0,9.0,20.0,11.0,10.0,FAHEFAFAHDGGGGHCBEGABABFEFAAGAGAGAGAGBHBHCFFDHBHDEDEDABCFCEDEBEFADDBFFCFHFAAGDDDDDDFFFFHADFFFBBBCDADCCADHBE,False +601,28.0,16.0,18.0,22.0,25.0,31.0,31.0,28.0,DHDHCHCEGGGGGGHGHGABHGABAGDGEGBACHDHBGADFBHGAGFGDDADGEAEACHBBFFHFEGEFFAFAFGFEFAGADDFAFCFGHBFFEDBACABFHFCCCEEDFDCDAAHFHEHDDEDGHEFCAHFFBCGCGCACABAEAEHDHFHFHFCEDEDGAGAEEEEEFDAGGGHGHFHAGEBHBAEFCFBFCEHBHD,False +602,19.0,22.0,22.0,6.0,18.0,28.0,18.0,32.0,BEHEHCBFBFGAGFFFHEEGEFFGCHCHFABHHCCBFHFABBEBCACAEAFHFABHCHGBBAHEEEEAHAHBHECACAHEHEHCGBFFHFGAGCCBCBEFEGHDDGDHFHCDAHHHHDAFBFAFHFHGHGACCCACBHBGBGBCFGFHFHFGFGFAEBCGCBDEF,False +603,6.0,3.0,3.0,0.0,3.0,1.0,2.0,3.0,AAAAHHHEAEBFCEGAGCBCB,True +604,20.0,12.0,4.0,14.0,4.0,16.0,10.0,13.0,BHADGGGBAFFHAEDBAFGFCFHFHDHBHBGFFHADDEHFFBFGHAHAHABACADFFAAGADAGAGACADDEFEFDADAHBGBABDBDBDCHF,True +605,13.0,12.0,3.0,10.0,9.0,12.0,19.0,5.0,BFBFCDGDBDAGAFCHBBBDHGADCEAABAGFGFGEGEGDGFAFEGBGAGEFFGFGEDADBBGAGAGEFEBBHGHGEDDAFAH,True +606,25.0,22.0,15.0,23.0,20.0,14.0,29.0,17.0,ABABABGDEFEFEHBAAAFDDBDGDGAGEEBHFFCAHAGABACACHEGDGDFDHGGFFHFBEDECFGHCBAGDGCHBGBGCGFDADECEBEAEADAFEBEAEFCBCBCBHBABGBHAHAGAGDDEEEHBCEADGDGDHHFDGABDBDGGCGCADGGHHDHGGEGC,False +607,7.0,12.0,19.0,9.0,3.0,6.0,12.0,7.0,CHGGCADECECGBGCGCEHDAFACDBGGFABCBCBCBCBFBCGCBCBCBFHADACADHDCGGGDFCHGFCHDHDB,True +608,15.0,15.0,12.0,14.0,12.0,4.0,21.0,15.0,BGBEFEGDBCGCGHHEGCFAGEBFGHBCCEGAHACGBDBGBHAHGHGHEHEHACABADADAHACBGDAEHGHBDBDBEBAAAFCGCGDEDCDEDHDAGHGDGBGEGDC,False +609,11.0,19.0,6.0,5.0,9.0,14.0,11.0,10.0,BBBBGBFBFBABDHAHFBBAHEHFCAHGGDGDFCBCFCGAHBDBGBGFGHAHGBEEAFFFBFEFEACACEEGEAEDGFHAHBBBF,False +610,7.0,6.0,1.0,2.0,7.0,8.0,15.0,3.0,GGGGGDGFBAEAEBFHGHDFAGBEFEFGFGBHAGAGBCEAEGBGEGAFF,True +611,9.0,11.0,18.0,12.0,13.0,14.0,18.0,18.0,DABAEGBGEGEGEGFDHCGCHAHFHFCCCCHHGADFBGEHAHEHECFHEHEAGABDGEBCBFFFGDGBGACHHHDHCFCDCHHGDCHCBCDCGCBBDADGGGEDECBFFFFEF,False +612,1.0,6.0,5.0,8.0,3.0,4.0,3.0,4.0,BEBEBGBFBFDDCHBDFCHDGACHFHGDCDCDED,True +613,5.0,7.0,4.0,9.0,3.0,12.0,4.0,8.0,DEEHBFGFCHBHDHFAGDBDHDFCFEBHHHBFBABAGAGDFDCDFFFFCFDA,True +614,5.0,4.0,10.0,9.0,2.0,6.0,6.0,7.0,GCBCBCGGBFHHCFCHHDDDDCBGAEACACFDADCCAFHFHDHDEDGFG,False +615,20.0,20.0,21.0,19.0,32.0,21.0,14.0,26.0,FCCGGEHECEDEDBBECHCHCFGBEHECCCCCHCGCDCDEHAGCECEDDBEBABABEBEAAAAHAHEFAFHFEFBFBFAFGEEEAEHEBGHEHDBCBDAAEFFHCGFHHHGCEAGDBEHEFEGDFBFAHHDBCHFFBEGEGFHECEADADADBHFHAHDDFDFHEAEBDBDGH,False +616,4.0,1.0,4.0,5.0,3.0,3.0,4.0,3.0,AGAHCHBGDFDCHEDEDEFCFCDAGAG,False +617,14.0,17.0,16.0,17.0,18.0,16.0,11.0,15.0,EFEFHFABEBEGEAEBEAECBDHFEEGEGBGDHHHHHBHBHBHAFAHDBFHABDDFDHBGDECECEFEFGDABAFAFABDHFBFCGCGBEFCDCEADDDFACAHDCCGDDCBCGCFCABECGCD,False +618,29.0,30.0,26.0,14.0,18.0,25.0,13.0,17.0,HACCBHBFAFBFBFHFCBAAGAEBEFDDBDAAACACACEEDDAEFGBGFEFCABAGAGAGFGCHCAGFBBDFHAABFCFCFDHEHCFBFBHADBBBBHDDBCFABBEBFBADAEBCBHBHFHCBDDHCHGHCACAGAGDFCFEAEBECECECFCECECGHEBAFAEAGHBCF,False +619,31.0,22.0,24.0,19.0,30.0,25.0,19.0,29.0,CFHEHCGFFACEHBDEEGGACFCACAGAHAEAFDCGBACEFGAECCAGHBHBDBAEAGFBABAGACAHHHAHCHCDCDAGGGAHAEAEDGGCEHFHFHFDGBHBCEHEDEFEFEFEAADACHFBDBDBDBFBFAEHFHBHEHEGEDEDCCEBFBFCFCAHDBFEAEFEACAFADEBEHHDEGEAHBHCHDBGBCDHFGF,False +620,18.0,17.0,15.0,24.0,21.0,15.0,18.0,13.0,ECDGDBDGDGDEAEBEBCFGFGAGAGHCDEHEHBGGGFEAAFBBDFHCDCEEEEGAGAGEDFDHDHAFAFHEHDADADBDECACEDDBHFEGECADDCFHBCBCHCDDFDGBBBEAECEDEFABAHCHGDABFBFGFCBGA,False +621,0.0,2.0,1.0,1.0,4.0,1.0,0.0,1.0,FEEDEBEBHC,True +622,14.0,20.0,14.0,20.0,27.0,29.0,12.0,26.0,CDCACEHFHFHBHEFEDEBBFFFFBFECHHAHEHEDGDEEBFHFHAACEDECCCCEFEHAHBHDHFHFAFABEEEGEGEBDAHEEEEFHDDDGDEDABHBAFGFEHABFBABDBFFFHFCFHFBGCABBGBHFHFDDAHGFEFEDHCHDEBGGGBCDDDCGF,False +623,16.0,25.0,17.0,19.0,21.0,19.0,21.0,15.0,BFDFDFGBGDHBHEDCACFCEHEDEBCFDEDADBDACADDEGEGHAHBHFEBCCCAHEHEBEBAAAAGCFCFGFBEEEHBHEHGBDBDAGAEAGBDBGFEFGBCBCFGEGBGHDHGCCAADCDCBFBAGGFGEHDFBEBFBFDFCFHBGGGEB,False +624,23.0,27.0,21.0,27.0,12.0,19.0,33.0,26.0,DHAGAGFBFCCHHGGBCBFDFACGBGBGHCABACAHFHCDCDGFGFCFGFCAEGHGABABEDEDHFHFDFBGHGEGHAHBHCDAGAGAGBBAEAFGCACBFBDDHGHBHDGDGBGDAAAAEBBGBDBDCACFCHCBDBCCCBGFFHDHDHEGEDEHHDDDHBGBHDFFEBDDEEGGGGAGHCHDBAGD,False +625,17.0,22.0,27.0,7.0,24.0,19.0,26.0,18.0,GHECEGFGAGCBEEGBGHGBEBEAEFGFAFCFHGGGGEEECBFBDGGCGCEDGFBHBCBCBCAGABEGEAEABFFFBFBFHEGFGACAEFDBCBCAGAGAGFFCCBEHCCBCBDHCBEHCHCACEBFBCGDAHFCECEDACAEHHHHHDAFGHCHCEGEH,False +626,21.0,20.0,18.0,14.0,19.0,24.0,20.0,19.0,FGFGDBFGAAHHDABADDECCHFBGCEEHGHGHGAFHCHAHBCBFAFAFABBBABADDGEBBFCFCFCFCBCDCDHFAGGHGHGAGEHBFAFCHHEGEFBHDHAHAEDGAGAGEGCDEHECCCBBBAFFFEFDADBBEDEGCFBFCGAEEEEFEF,False +627,22.0,20.0,15.0,21.0,16.0,16.0,15.0,16.0,GBGEFDACFGFGHBHECCFAAAEEGBCHCBCFADHDHDBDBDFDADABAEDFBADACBCFCFEHGCEFEAEBHDHDFDEEBBHBGAGDGAEAEGGHAHDDDDFDGBBBAAAABDHGHFAFECCCECHBDBCBFEFGAGAHH,False +628,7.0,15.0,8.0,13.0,14.0,12.0,11.0,8.0,DEDBDHFHDCDCBBBCBDBFBFCGHGAGEFAFAEADBFBGBGHGDCFADBDFEFEDECEFHHCBEAGGGDEBECEABBGHGFDHEEFE,False +629,1.0,3.0,3.0,8.0,6.0,2.0,4.0,5.0,HEHDHDHDEFBGBGDDCDHBEDECGCEEFGAD,True +630,11.0,10.0,7.0,6.0,8.0,14.0,8.0,5.0,CAHAHABFCFCACFCAHAGDBCEGHFHEBDFAGAGABBBEBCFEFEFBFAFBDEDEGGDFDABFFEFGG,False +631,14.0,11.0,20.0,21.0,13.0,15.0,14.0,16.0,HCFAAHBFCFAFHFGDHFCFBBBEBEAEAEHEHGDDBHHHFHDCDEGECFHFDFDADACADHGEDADHDHDCDCGADDECEAGBBCECDGGCGCABAHFGCDCGFBHBDCDGAGCCCDCGEFEF,False +632,4.0,8.0,5.0,12.0,1.0,8.0,6.0,3.0,CAHAEDBCCFGDBDFFBFBHDDDDDADCGBGBCFAGDGFGFHDBDBF,True +633,3.0,4.0,7.0,2.0,2.0,6.0,5.0,5.0,CBCECACAFEFDAHBCGFGFBHCHDHCHGGFBFG,True +634,15.0,14.0,8.0,23.0,21.0,16.0,17.0,8.0,GDDDADADACBFGFGFAFACADAEEBEBFCGBFHFHGEDDDFCGABCBDHDHEEFHAHGEFDFEFBFAGAFEGDGDGBGDEDEBHBDCEEEEGEBCDDEAECDDDEGGGAFAEBFBGHEDAB,False +635,16.0,23.0,27.0,12.0,33.0,22.0,20.0,34.0,HEHACECAHFBGBEBHHHHFFCECEHEAEGDGDHAHBFFFFFFFGABCEFEBECECHABGCGFHEEEEEEGBCAHEHCHDFBGBCBCBHHGFBHDHCHEHEHCFCGCGEFHHHCDGDEDECBCAFEFAGHDCABHDAEACCHGHFBBHDEAGBGAFDDGCACEFEFEHEHEBEGCCEGBGBCAHBHB,False +636,18.0,21.0,19.0,22.0,14.0,15.0,21.0,26.0,GHABCDDDAGGFFEFDFHBACHDHDECGBFBFAAGECECDAFBHCDCEBGBAAAGHHEHEHEHEBAFDFCACECECEHHHCHDHAHAHCDBDGGGDHDBCCFCGHHHGDDDBEBFCFDGAFBFBDBDBGBGBABHHCHGHGDBEGAAHDCGAGBGF,False +637,7.0,11.0,15.0,9.0,7.0,9.0,10.0,13.0,DAFBFHGDGAGCDCDGHBCECFCGCDEDHDHBHBFBEGEHDADBBBBGFHHAECHGHGHBFCFAACCCFFHGACHCBCECE,False +638,23.0,18.0,27.0,21.0,18.0,14.0,17.0,30.0,DEDCHCBFEAEAEABAHGDGDADEBEHCFDGGCCCCDCBFGFCCHDHDHFBABDHEHAHFHCAFAEADHDHCHEDACCGCGCGCBAFHHHECDDDBGHHHCHBHAHECFBBGBDBFHAHGHCDGHGCGCBBBGBABFGCGAEEDFDAEHFHDHEEACAEFEACHCAAA,False +639,8.0,5.0,5.0,6.0,7.0,4.0,6.0,5.0,FGEBDBDBGHGDGCAHAHCDAGAFAFBEBEGEFDCHAEECEDACAH,False +640,25.0,30.0,19.0,18.0,18.0,25.0,21.0,28.0,DBGBFBFHFHCAFAFACGCHCHEHEGFGADHHFEAEGEGHGEAEBDADHBABDGGGGHBHDDGAEBDFCGCFFGACDHBHFHCHFAGHEDACAHBDDDAHHEBEBABACAGBDEDGHBHFHFCGCDFBFBFAHGCBDDCBAEAEFCABABACACEFHFBAEHEGBGBHBFFHBEBFBFBFHCBC,False +641,10.0,7.0,19.0,15.0,18.0,26.0,16.0,17.0,EBEBEADCFGFGAADCEFHCAEDEAEFBHEHDGDGDBHCGCFHFHCHFEFGFGCECFCGCEDAFEGDFCAEADCFEFHHHFDFGFGAGDGDFHHGACFBHDHCGFGFCHCHCHCDEECFFFFEBEBFD,False +642,17.0,19.0,31.0,20.0,20.0,27.0,31.0,22.0,EFGFHEBFAHAHFHGCFCFGFHFBFDHDAGAGBECCHCBGBFEABDEGEGFCBDDFEFADADBFEGEBBAEHEHAHAFGCGCGCBCBFGFCACHCECGCBCAGFHDBDCAFGCGCGCGCDDDCDGDGFBHGFFAHCFCFHECDGDBECCCDCEGEFBFEHHGAGCGDHAHGHEFDHAGBGBGHDECE,False +643,10.0,16.0,8.0,13.0,16.0,18.0,19.0,19.0,DBDFCEGABABHBFGAHEGFFDHCFCFBDHHACAFECHHHHGFGBEHEGEGEGFGBBDBFEFHFCEDECFAAGFGFEBAGHEHEHEGDBDFDFBEBDBDFDBGEHCAAGHGHGBGHGHD,False +644,23.0,23.0,24.0,17.0,10.0,17.0,18.0,14.0,BGGGGGEGBACCECHCHCACDBAEFEFHAHACFGGADDCDCDCDGHGCBHBAAFGFGFABBBBFBHGFAAADADCDEACDEACBHEEFCCHCHAFBCHGEGBFDFHEBBHBDBCHDBDBGFCFBDCGFGFACABBBAAAAAFDCDC,False +645,19.0,20.0,19.0,12.0,21.0,19.0,19.0,26.0,BCHEHEABABAHAHDHBEDEAEGECEBECAHDGCFEFCHHAHDHDHFBDACABGCEBHBCFHGCCCAEEDAACABBHGHGHFHBEBHDECEBDBCBFEFHHHGHGHGHFHFBDGEGACEFDFHFEFCGGGAEFDFGCGABFFCFCGBGAGFBAEA,False +646,24.0,19.0,25.0,16.0,26.0,22.0,27.0,28.0,DADGFHCDDBDHDHGGAEECHHHFCAGACFCFEDCCECEGFBFBCBGEHEACBCBGGHGAGFHCGCGEFEDAHAHFHEBBBHHAAEAECBGAAFBGBHBHAAFEEAECEGHGFCDCHHHHBDFGFGFGBEAFHFDAHAHCBCEHGHGFCDGDGCGEFABDBFBAAAHADEDEGCGHECEFEFECECG,False +647,19.0,19.0,11.0,23.0,12.0,13.0,15.0,22.0,FGFAADEGEAEADGDFHAHBHDGGGHDFBHBDDGDCDHBHBHEHECEDBDBEBHHDHEABCCGFAHGGEADAGFDAHEHDHDCDGDHHEHFFFGEGBDCACACDFDHBBBBDCGAAFAHABABACACFDFBBHB,False +648,14.0,18.0,21.0,17.0,4.0,13.0,14.0,14.0,HDCCBGAGBGFGFHCCACHCGCBCBEDEBCBDBHFCFCFGAGACBGFDFBHBADAGHCHBHFCACDFDBABAEGCHHDBDCFBECGCGBDAFFGHDBDBDADADACFDADCHHGH,False +649,18.0,10.0,20.0,21.0,15.0,23.0,20.0,19.0,CDCFFDAABAFGFDBHFHGADADAHGHGBDFCHHHCDCHAHADCDGDGDGCEFGFCECFCFCGCAAAAEAEDBDBFFHHHFECECGGEGAABHECFHDEDGHGAEADFFHGDGDGEEBDCFGEHFCGCECEDDFFFFBFBCBHHAG,False +650,2.0,8.0,12.0,4.0,7.0,2.0,3.0,2.0,BECADGCCCCCBCBCBDGGFECECDBDBHECEFABHBCEE,True +651,23.0,17.0,14.0,13.0,18.0,7.0,9.0,12.0,HGFCACACFCDEEAGBGBADADABCGDAEADGDBACFHBEDAABHBHGHCAAEBECECACEDECEGFGAAHABAEAHDHABABADEBCFCFBEEEHEBFBAEHEHDCDBGBHD,False +652,9.0,5.0,7.0,3.0,3.0,4.0,7.0,7.0,FHAHAGGGGHGCGCEHEAFAFCHDECHBABCFGBHBACDCDAABA,False +653,17.0,14.0,10.0,12.0,16.0,15.0,12.0,13.0,FFDCCCGHBHEFBAEAHDFFFHBBBBGAFABABAEADAEFCBDEEHFDACHCHDAFCFEDGBCBCBEBEGGGCHHDDAGAEAEDEDEBEHDHAHEFGFGFGHGAAEAFG,False +654,18.0,23.0,28.0,27.0,18.0,13.0,30.0,25.0,CGCBCACGBGHACACADFEBGBCAEHBDBCHAEDGDFDCCAEHDGDFDFAFBGBGEDCFBFBFDAHGCCCBGBHEHAHGGGCECEHEAGCGDGDHBBDGCECHAHDFDGEGAGDGEADHCACBGBCHAHAGBGHHCHCHGEBEAEDECHBGBGDGFGEGHCHBDDDCDHDFDHCFEHDBDBF,False +655,15.0,11.0,8.0,7.0,7.0,6.0,7.0,13.0,EFAFACBEEDCAHAHGEAEFFHBHBFBFHGAAHGHGAGDCBHHHABDBEBAGAGDDDADHBCBEACHCACACHB,False +656,23.0,17.0,14.0,15.0,23.0,23.0,21.0,14.0,DBBBEEGCGFABAGAHAHFDEEHECBHBFBEAEADGDACGFGFCFDFGFGFGBEBEDEHHCFEHAHAFAHEBABEDEFGFGBGAAECFCHCEAGDGDCBCAFHFDFDFCFEEEEECFDBGGGAAADBGBHDAGEEBHDAAAHFGCGFAFC,False +657,22.0,13.0,20.0,11.0,19.0,20.0,13.0,19.0,AAAEEECFGGCCCDBDAFHFAFCCBAAHBBBEBFBAGCGEGHCAEACDCEADBDEAFCDGECEGGAGABAHAEBHHHHHCFCFEHCHFHGHCHCFAFDFDFDHBEGEFFFFAEAECEDEDHFGABFEGCHCHAHABF,False +658,13.0,8.0,9.0,8.0,6.0,14.0,16.0,11.0,DFDAACADGHGFECCGBFFFHEAAFACAGFHCGCFAFDFBBHHFGAGABABAGEFEFGDEBFBDBGACHCHCHGDGHGHGEGDGH,False +659,24.0,22.0,11.0,20.0,12.0,19.0,20.0,10.0,ECECBBAAAFHDHDHCBGFGFACABAGGHADBEAFFDFDFDEGCGCBBBFAGABBEDGGAGFDAGHGDDAEABBGBHDGEBFBHDFGCBCBEBFDFDADADBBFEHEFEFDFHFEGDCDCDCGBGAAAAAGAFAHBGA,False +660,9.0,8.0,11.0,8.0,16.0,14.0,26.0,11.0,FEGEHCHBGBGEGHGHGEGHDEBHAFACGDGFGACHHGAFCGGFEHDFDEEGBGBGFGFGCCECFAFDFDHBGDAAHAGEGDGEGFGAGEBCCCCBEEGEFEF,False +661,21.0,16.0,26.0,12.0,16.0,24.0,13.0,16.0,AHBFGAHHBCBABABCCGBEFACECGHGFDAHHCCECFFFDFAHACACBCBGBDFEFEHEDACAEDEDEGEGDGBBBGCGAHACACEFAFDFAFBDACAFFHFCFCAGEGBFDFBFEGCFCBCFHACADDCHFHFCECEHHHCE,False +662,19.0,21.0,19.0,34.0,20.0,23.0,22.0,19.0,AFAFBGBGBABGDDADCFCECGGEAEACHDHDEFCFDFDECHHGDEDEGGFEBBBBBEFEDDFAHCBEDDBACDCDAHAHGHDCFCFDFEFEDHCHDDADBGCABDHEBBFBDCDHDEDEABDHEBFBCEAGGHFHEAGFGFGCGDGFGDGAGAGABFBFDDHDCDHHGHECDCFAF,False +663,30.0,32.0,21.0,26.0,25.0,15.0,23.0,18.0,GBDHGHGHGBGFGABAEEDBCBCAHAEEDFDADEGCCCGHDBBBEDHGGFCBBHEAACDBGAGBGFEAAAAAABADGGBGCDCFCFDFCBHAHBBBHBHGDBDEHBHBHBEAABABDDEAEDFDEBEBECEGEFAFCFCADEGCGBABABFBCEADAEGEGDCDGBFHAEAEFCDDHEHAHFDCDEDCAC,False +664,14.0,12.0,16.0,18.0,20.0,25.0,19.0,23.0,GFFDFGFDEAHBCEEHCFEEEABFGFGHGAGAGCGCFDBDBDEDEABABDBHFCFHDGAGEHEHEGDCDCFAAGAEEHFGFEDCHFHGGEHDDGBADDGHFHEHEHECFCFCDCAEFFFGFGCBHHCCFCFBFHFHEDADHHHHABB,False +665,1.0,1.0,5.0,0.0,2.0,0.0,2.0,0.0,CCCBGGAECEC,True +666,13.0,18.0,8.0,9.0,12.0,13.0,18.0,15.0,FADABCFAFAFGFGFBCBGGGFGDCDCABDHDAEHEDGDGEFFHCGEHHFHBGAGAHEGEGABFCGBGEEBEHFHBHBHBHBFBHCABBHGEEDCDBABABHGGAE,False +667,12.0,9.0,6.0,10.0,3.0,13.0,8.0,9.0,CBCHGHFADHGAGBCFDFAADDFCFHDAAAAAFCFEAAFADCDGDGHFHFHGBFBFBEBHGHGBBDFDEB,False +668,25.0,23.0,24.0,17.0,11.0,21.0,16.0,12.0,GDAFFFFHBBGCACGCECBHAEDBBFFFBCBCACACGBABEBEDDBFAHBHDAGAGBGBGAGBGAGEDBAFCCDCGAGHCDADACAEDFHACBEAACFDDBDBHBDBDFFFCFCFCFCAAAEDHFAFHCHCACHCGAGFFCEEBEBGDH,False +669,3.0,6.0,1.0,5.0,4.0,4.0,3.0,1.0,EABGBEBGBFBGDFDFDADEDBFHEAC,True +670,5.0,9.0,11.0,15.0,8.0,21.0,12.0,11.0,DFDCHCFFDHHAHACGGFBDBDCDCDAHEFFFHBDBDBEECFGDGHGBFCDADABHBHGGEGCCFFFFFDFHEBGCEFDFGFEFEHDGFGFC,False +671,9.0,14.0,11.0,13.0,12.0,14.0,11.0,23.0,HDHCHCFCFCHCFCDADADEHFHBAEGFGHCEDHFCCDEHAHFEBBBADCHHHHDHBHEDDDADHDBGBGBCBFHEBEFGBGHGFFHAHGHBAFAGBEFEBEHEGFG,False +672,3.0,4.0,0.0,0.0,2.0,6.0,4.0,2.0,HFHFAAGEGFGFABBFGFBEB,True +673,17.0,21.0,20.0,5.0,12.0,13.0,17.0,15.0,BCBDBECHCAAADCGGGGFBABABEBCBCACAGHBHDHBFEEEEAABCBCBAAHBGGCGBGHGFGAGFFCHGHGHBABFBFHCHADDFCCCECECHHEAFBFBCHHBCEGGCFAEAEGFF,False +674,14.0,34.0,17.0,24.0,19.0,23.0,30.0,24.0,BBGEGHHHEHEFABDCHCFBDAGBBBBDBFCFCFAHHEHAFGHGEGEDBDBDHCFCHCEDEDEDGCGCDDDGDGAGAGEGBHHCHADFDBBBCDDACGHGEGEHBGBGHFEFGFBBDBHBFBDGGCGCDFGCBBBDADGHFCFADGEHFCFAFGBHFHBGEAEBBBAFGGDGFEFBBHEHEBABF,False +675,22.0,22.0,20.0,24.0,22.0,17.0,36.0,34.0,CHGHGHAHAHCECDBGCADHEEGECDGBFCCHCHFGFGBBHFHFHEGFGAGCGCGDGDCBFBFEFEHEDECCHBGBDADHFHEBDBGFGBAHGHGEACGGAEAHGBDCDGDHFHBHCECBDHGGGGHBBDFDFHAAAAAHADADHGHEHAGFGDGAEDGDEEBHACFGHBHBHCGGGCAHEEAEHEFDDDGDBBBAE,False +676,5.0,3.0,7.0,7.0,6.0,1.0,5.0,6.0,EHCHEBAGEGDGDCCCCABHEGBAEDEDCDFDADAHHCHG,False +677,14.0,12.0,18.0,20.0,14.0,12.0,11.0,15.0,CCADHGFACAHGHDDDDDGFGHBADGBEBCCDDDADADABBHCFCFHBHGAGEEEEEEEGEFHCDFAFCCADBDCDCDCBBBBCHCBDAGAEHDHAHAEEHEHFFCGCDFGECFFH,False +678,20.0,18.0,16.0,16.0,18.0,22.0,18.0,25.0,DFFHFHFGFBADAGHCBCAGBCBFGFACBEFEGABBBEGHHFHFDFHEEGEBECFCEBEGGADEDEAEACHCHABEHAHAFAHAHAFBFAECECHCHGHAHBHCHFHGDCHGHEBDBDGCADEDGGFBFGDBDCFFEHDFDFDGDHCHBGAAA,False +679,13.0,13.0,11.0,11.0,12.0,13.0,13.0,10.0,DADAHACGEBDGEGEDEAACHFGEGEGFGFCFAFEBCBFEFHCCFCHCHEHAFFDBBBHGCEBGBGAAHFHGHBFDEGAGBBBBDDADADEDACFC,False +680,21.0,9.0,11.0,23.0,10.0,11.0,13.0,22.0,BHEFDAEAEGGAGBCHCBAAHAFDFGGGGBHADEDACFCFAEABHBHBAAADFFACDDDHDHCBCFHDHCHGDAHAHDDDCDADEHFFAFDEHHDHECDADAGAGBHHGHEHEHCDGDGD,False +681,29.0,26.0,19.0,24.0,29.0,20.0,27.0,23.0,AAHAECBCBAADACAFFGCEADCBGHGFEFEAEDEDBDHDEBHDHAACAHAEBCBDFFHFBFBFBFGFBEAHBCAEAGAGBEEEEEEEEDCABFGFBDHFAFAGBGHGCGEGDADHDFGBCBHBHACEBDADEDEDGGGGGGGBHBHDHCFGBBEHCCAHHFABDCGGECFBAHGDGDCEAEHECEGHDFDEDGAHA,False +682,12.0,18.0,15.0,23.0,25.0,24.0,20.0,8.0,DADHGFBFDADAEECECBFDHDBCBABAHFFFFEFEFBFBFBEDFDEAFCCHEBBGECCCCFAGBBDBGCEEDHGGEGEAEAEFDDDGDAFEGCGCGCFEDDGDFHEDGGGGGEBEDFDEDHBEBDCCEFFFEFEBABFGAGHGD,False +683,10.0,19.0,7.0,19.0,5.0,6.0,8.0,11.0,CHCGBDFEGADBBBBBEGHAFAHBGFACAGAHDBDBDADHDGDBDCCCEDDHDADADCDBBBHBFBDBDFDADEHHHBHGGEFBB,True +684,10.0,3.0,3.0,5.0,2.0,4.0,6.0,12.0,DBCHHBHEDEGAGAHFGGHFAAAGAGADBCHAHAFDFDACHHHHH,True +685,10.0,19.0,16.0,24.0,9.0,16.0,18.0,17.0,DGDFEBDHDADCDBDHFHFHAGCHCHAGEEBGBGBAFDHCBADCDHAHEEABDDFDFABBCDDADCDFDFBBGBGHECCGCGDECGDBFGGEGECHCGFFBFBDGFHBHBHBCGCGCGBDDDFHFHFHA,False +686,11.0,7.0,14.0,17.0,14.0,20.0,12.0,14.0,HDHABCEFFBEHCGCACACBHBGEGEFFFBGCECDCDEHEDEGFGFDDDDGDGAHDHDADADFFFAHAEDHFBADEDBCCGHAEEECFFEFCFHFGCGAHDFGFHFCFH,False +687,19.0,24.0,19.0,21.0,13.0,20.0,17.0,22.0,GBGCDCDHFCAHAHBFFDCAGBFBABCFFBFACBGHGHBFFGHDDADHFHFHBGGHGAFDFCGAGEDEGEADDFCBABFBABAHEDEGFGFCBCFDDADACECEBEBCHCACFEGCHBBBDDDGHHDHAHAFABDHEHEHEGEDBABCBDBHCHC,False +688,11.0,6.0,12.0,7.0,7.0,10.0,7.0,5.0,CCBGGGGFABECFADHEACFCFGFGEDFCFAFBHBCBHBDCCHCAAAAAEDDDDAFCFCEGEAEH,False +689,1.0,5.0,2.0,2.0,0.0,1.0,2.0,2.0,DHDGFGCBBBBBCHA,True +690,15.0,19.0,20.0,21.0,26.0,23.0,15.0,18.0,GBGBGEFEGECEDHDHDHDHDCGAEACGCFBFECCACGCDEDFDHDFBBBEBDHGHDCBAAAFBHADFBFHFHFHFEDDADEDEFCBBAEEGEACCHCEGACEDECECFFFFHAHEGEBABEDFBHEDEAEADFDCHFHFCGEBHCFFFGBBECGBG,False +691,16.0,20.0,16.0,13.0,21.0,17.0,19.0,17.0,EEBEDECEAEBBBBEHFBFBFDCDCBCBCAFGHGCECGGDHAHCDCFCEHDHDBBFHFGEECBGBFHDHGHEBEBEAEFBAAAAEAGGGFEFCFBABDFGFDFHAEEGHHHGDFHFGCGCGDAAACADEGBBCAHGEGH,False +692,15.0,18.0,25.0,15.0,20.0,16.0,23.0,15.0,DCAGACABGEGHGBBCAEGHHDAAAFGCBCBCGGDGCGCHCDCDAFCFGHGCGCEEEHBGGECACADEDFDFGFDBBFBCDCFCDCEEHEHFDBDBGEGFFBFBFEECHGHBAGABABEHEHGCEHBFDCCGDHEHEGBFAFAECEC,False +693,18.0,15.0,17.0,18.0,19.0,18.0,17.0,13.0,DAEAFACADHDHCFCBBBDFDEGEGEFDGBEFEBGHGHEHGGAFAFAGAEDEBHDADAEAEDEAHGHAHCECEHFHBGFAEAFBCGFDFGCACADFCGCBCBDAHFBCDEBCFCFGECDBDBGBGECECFDDHFG,False +694,7.0,11.0,9.0,10.0,9.0,4.0,5.0,10.0,CDDDBBCGFGDHDHEHBHEHEBEBEAEAFHDEGEDHBAAFHCBFEGCBCBCBAAHACCCGBHDDD,False +695,9.0,7.0,7.0,14.0,15.0,8.0,16.0,16.0,DFDCDCDEAHDDDBHHFHFCDCHCFBAEEDGAEAGGFGHAEECHGHGHEEGDGFEFEDEGBGEDDBHBHGEGFAHAEAHAHGBGHGHGDECB,False +696,24.0,23.0,24.0,22.0,20.0,19.0,26.0,26.0,ADGDAEBHCGCHCEADABGBGBFEEGFAFAFBFGDGDHHACDCHFACHCGGHGHDHCBGDHBACHBHGHGAAEBFAHGGDGHGFGDCDCGCDCAEGGGEEEEEHDFDAAAHADAFADEBBBHEHECACBEEEBABFCFCFCECFCHBHBAGABHHFHBHFCDEBCDGDFDFDCBFBCBEAGDGH,False +697,19.0,24.0,22.0,23.0,29.0,24.0,25.0,34.0,FCFEAEAHCGEDABFEFDHCHCGCGCFHABDGEGFGFGBHBCAEEHGBCBCBCGHDHFHABGHDHCCCAADDFDHDCDHFBEHEHEGFBBHHHADEEEBEBFACHHHHGHGABBBBEDCBBBEDEDFFFFFFHCHDAEFEGDGHFBDGEHHGFBDADECEDEDGFBFEGCGHHCHCHGHEFEAAGAGEGDGCAHAEAEBD,False +698,13.0,19.0,14.0,18.0,18.0,16.0,11.0,16.0,BDBFFDFDFGGHAHBHBHBHFGAGAHDHBEBDBHBFBFHCBEGEGEDCCCCBGHECDCACDBFCEDBDFDFDHDFEFHFHEHEFEBABDEHBCDDHAAADEBAGAEACGEAEFBCEGEDFCCAGE,False +699,20.0,17.0,18.0,13.0,20.0,22.0,16.0,23.0,ADHHHHFDFBFAGADBEFFFEFEGCFBDHCAEABAEAEBHFECCFDFHHHHHFHCHCHEHEAEBGHACABFCFGAGDFDFCBHGCFCBCHDEDHGHAFDFAGECECEFAGCDEGEHEAABCBGBGBGBABGEAHGEAFHFGCECADBDB,False +700,7.0,10.0,13.0,7.0,8.0,14.0,8.0,3.0,FAAEFBFCFBFBEDGHCCCCCEDEDFHECDBDGFGFADGBEFCFCGAAAHEDECACFBFBGGGFCFCBBB,False +701,16.0,27.0,21.0,29.0,23.0,22.0,14.0,18.0,ABAEADACBDBFAFDCGBDEDBBFBFADHHAABHDGABACDBDEAFCHCECHDDACAFDFDFEAEDHDFBFBFCEEBECDCDHABFBGEGFHFHGBDEDEDEDCDHDHFAGDGHGHGHBCBCBFHCEBEHCCDCBFBFBECFDGGGFCECEDHBGBCFEEDGBFBEHEDE,False +702,22.0,31.0,14.0,20.0,15.0,20.0,18.0,12.0,GHADBDAFCHAEBDBDBDFDEAAABADEDCAABBEGEGFGEGFDFBFBAEGBBCBCBEGDCDAHCHBADADGFBFBHBGBDCFGDGHCDCFCBEAGFGFHFEBECAFBFBHBHBFBEGEGEBEDAHABADABBGBCAAGDFBAGHCCFDFHF,False +703,21.0,26.0,13.0,16.0,14.0,14.0,14.0,17.0,CHABCBFGFAABAGAHAHAHACBDFHAHEHGCACDBEHDGBHCECEHFAACABHBABABECGBGAGEFCGDEFHBBFAFHFHAHEBEFEGBGBEBEDDDDDDDAHHCBCDDGEADABGBDBFGFBFBFBGEDCBB,False +704,1.0,0.0,1.0,1.0,3.0,1.0,3.0,0.0,DEECEGFGAG,True +705,7.0,6.0,9.0,6.0,4.0,3.0,8.0,5.0,AGABCBCEHFACGFHHCHEACADDDDGBGBGBCEFHBDEDACGCGCGA,False +706,6.0,5.0,9.0,7.0,4.0,10.0,8.0,4.0,BGHGEDCHCHCGCFFGDGDGCBCBAADFFAFEFGAGADFHBAFCBCEDEFCFD,False +707,10.0,10.0,4.0,9.0,12.0,8.0,9.0,7.0,EECFAEAHAHAEAEBEHFDFDAGCDHBHGGEGEGFDFDEBADDCHFDDBFGEGBGBEBEAHAGBFBABC,False +708,11.0,14.0,22.0,17.0,26.0,26.0,22.0,25.0,ADBFFHCHCHCDGFCFBHBHBAGACHDFEFHCBGECDDGEHEHDHEGEGEGECBHAECDHDCDEEFHFDFDABHGDEHEGDHDGFCCCHCHDHDHBAEEGEHEHGGGBBFEFEDEFHFCFAEHECGCAFFFCFBBCAFBCHEEGEGFFECGCGFGFGFAFAGB,False +709,20.0,25.0,16.0,17.0,13.0,14.0,18.0,22.0,CDEHBHBHAHBHBGDGEGBACAHAHGBGBGBAAAGFDEEBGBABABFGACACHGHDFDADHEFDHHECFDACABGHFHDDDAEAEDGDCDCFCBCFHBCBEBEBEBFCGCHFEGGDDBBBCEHGDACABGHGAFHHHBFAFCFHB,False +710,30.0,23.0,16.0,22.0,21.0,35.0,15.0,23.0,FAFAFAFEFEHAHAEBEFDFDBDHFCEAHHHHBEFDADHEHBCCCADEHFHFHFCGGDECGCBDBGAFAFBCDAHADBECEFHCBCBAAAFAGBFADDFDFHBGAAEABFDEDFHAGAHAGAGEGHFEFCABAFCBEBEBHFDDDFDADEEEFBFDACEGFBDBHBHBFGFBFCFGGHAHAFGFC,False +711,6.0,6.0,12.0,7.0,12.0,9.0,12.0,10.0,HGEDHDGCGCGBHBHGCFAGABCBGGEBCHCHFGDEEEHEHAHFHCGDFEFAFAFDECECDCFABCGEGFCEDE,False +712,23.0,31.0,32.0,27.0,25.0,14.0,31.0,14.0,CGABCFCEHDFDHEHBDBDECCFBDGHGAGBGCHCBAEHEHDFDBDCEFGCGCFBAGGGEFEABFBGEAAAAHAGACACECACBGDGDBHBCFGHGBCAAAFBDDDDDDFGFCECBBEEGDADCBEAEAFDGEGCCBCBCBDGCECGCGCGCECECBFBDBABDBDHDCEHEBECGAABDBGGGDEEGEBBAHGGDH,False +713,4.0,5.0,5.0,9.0,4.0,5.0,6.0,6.0,BEFEACAHDHDHGHBDCHCDEDFDGDBEFGDGDFAFBBGACHCG,False +714,18.0,19.0,22.0,14.0,25.0,27.0,18.0,19.0,GEHFCECFCAEFBFAHBCCEBFFEFECDADEDEAEFEBECECGHGAAADAGHBFGFAFHDEABBDGDEHEFEFDBCHEGCCEFBFEHHHHGHGCAFAFHFHFGEHEHCGDFEAEAGFFBADAFFCFABGBABFBCBGBGCDCDHFHCECECDHDBGBCBCGG,False +715,17.0,8.0,11.0,12.0,13.0,12.0,12.0,14.0,BAGDHBHDHABAEGHFDADFECDCGCGADHDHDHABCBHGAAFBFBEHEAFCFAGHEBCDFDFDCHCHCADAEHEGEAEGCGCFEHAGGFAFEFEAEAG,False +716,16.0,17.0,24.0,24.0,21.0,17.0,16.0,24.0,FCBCBHBCBCECDCDAFFHHHCHDBEFABAEDEDEDECFDGGGAEFEFEHCADAFACEEECFCGAEDEDGHGDGAGFBHDHFHCCGEGBDHGEBHHHEHACAEGFDFDHCECBADECHHHBBBFBFBDADCCFCDCBCDEDHHCGDDAAAHBHGHGDGF,False +717,30.0,23.0,30.0,24.0,12.0,21.0,21.0,16.0,ECEDACAHEHCACECDCGCBHAGDFACBCBAFGFGBACCCCACFGEGFHHAHABGBEFFBFDFCGABCDCBBBBBAADADGDFDFHFDCDCHFBFAAGAGAGAGFCCCHABGDGDBDCDEBHDCDCDBGFFHHGBEAAHAHDFDEDAHAGDCDBHAFGGGBABDFCACACBCFEEAE,False +718,8.0,9.0,11.0,13.0,10.0,18.0,7.0,15.0,BHBGDHDHDEAEFFAGAGABHFFFADHDHDGAFCDCAHBDECFAHDHCCBGHFCECEHEFDBDCDGEGDBHBECFCFCFHBEFFFFFHFHE,False +719,12.0,23.0,32.0,23.0,25.0,25.0,24.0,32.0,ACHDECHBHFHGHGHDADAGHCCEBEBCCGHFFGFCBEGCCDDDBGFDHDHDHGFGBCFCGCDCDCDCFGEDBDBEGGCFEFEHEBEHECBFDCDGBGEGBGEGCFEEECGFGADCFEAEADBBCECEHEBEDFHFCFCAABGHHHHHFAFABCCHCFCAHEHFBFBFHCGFBDGDEBHBHCECGDBAFHHHHHDH,False +720,9.0,6.0,1.0,2.0,6.0,3.0,3.0,2.0,AAABABDBGEHAGABCBGFHEAEDEAEFEFBA,True +721,4.0,4.0,5.0,4.0,1.0,4.0,3.0,0.0,BGBCACGCDDFDFABACECBFAFDG,True +722,16.0,8.0,13.0,19.0,18.0,17.0,9.0,17.0,DFEFCHCGADHDEDAHEDEBFHFEFEAEDEDHAHADCBAFACAHEHDCGCGCDCDHDFECEBEDEDEFGGABFBFGCACFDFAFBDGFHCADHEHEGDAEAHHHBHFHFADCFEBGA,False +723,20.0,21.0,15.0,7.0,15.0,20.0,22.0,15.0,AFCDCFCFGFGAGBCACBHAAFGFBBEEAEGHDEDBHBHEHBCGEGFACEGHGHGCGEGECAFFGEGEGEGBBFAFDCBCFCFADADBHEAEHGBGHGBAFAHCBADFBHBCBFAFHBABABAFABHFGFGEHCG,False +724,22.0,23.0,14.0,13.0,20.0,26.0,11.0,21.0,DEBABADADEGBGBEBHBCCAAEAFFDAAAAFEFAFGFCFCBHBCFFFCFBFDFEHHDHCHCFDEDHBHBGAACEFAHHFABAEEEEGBCHCECACGDHAFDFHFHFEFHAGGGFCHBBDBHBEBFBFHHEHBBBABEEFGFEDGDAHAE,False +725,21.0,25.0,25.0,29.0,21.0,32.0,25.0,20.0,FGGGCGEGDFAHHHCCCGAEABFBEBDBDHDCDEDAFGDGAEFCFCEAEADABCBGGGGGCDCDCFFFEHACBCBCGCFCFDBDFCFAHBDDFDFBEHEADCDFHEHFFEGGDGFHEGEBBBDHEAEAGAGAHBHAAGAHAHDDCBCFFFHFEDGDHDBFBEAHBFBEDFCHGFGDCFEGCHCFBFDEDFDABBFBCB,False +726,16.0,20.0,16.0,17.0,10.0,18.0,13.0,17.0,BBBBGCACACBFBABFBCDHGBCHCBADABFCFCFGAHEGBGEEEFDGDFAGAGCBCEFHFHGHFHAHFDFCHAHAGEBDBDGDCDCHFHBDDADCBFADEEEHHDGFGFHADEDHFHCBCBABADF,False +727,10.0,29.0,22.0,26.0,22.0,17.0,21.0,19.0,BCBCBCBDAFHFCECDCDCBHECFCGAGDGBHFDGDGBGBEDEDEDBCBAFAGHBHDHAADBDCGFGHDBDEGEFBBBCBEBEHECDHEGDADCDHDBBGCEHFGCAEAEBEBFBHADCECFCFEDGHGHBHFHGHBCFGBCEFDHGBGFGEBEHEFFDDBDECGD,False +728,11.0,13.0,13.0,11.0,13.0,20.0,15.0,18.0,EFFFEBCDCHCAAAADFHFHGAFDFHFCFBEBGCGAFBCACAHAHEDBBGEDEDCDGBGFGFGCHCFFDHEBBCGGGGGDFHAHDHBFFCHHDHEHEFBHBHECAGEGEFEFBH,False +729,26.0,25.0,13.0,24.0,26.0,16.0,21.0,19.0,DBDFABGGFGHEHAAAAABFBFBGBDBABAGEGCGFEEGEBEDHAEDCHABCDEFAFAGDHHAHADAFAFGBGAGHBDGCHHHBFFEAEDBDBEHDBBEDDHDHDCBCBEHCACDHFCGAGEGDDBEBEBEAGAEADABAFFFFEHGCGCEEEEBEGDHDGECEABHDCD,False +730,16.0,17.0,13.0,13.0,6.0,15.0,8.0,16.0,CCHDADACCDBABEBHDFBEAGBGFCECHBAAEAEDEGCHCHAFBHGHDBDADAFBDBGBHCHCAGAGHHCDCFFDFBFBADFBFBFHAAADBFCFGFBFHHHH,False +731,16.0,23.0,24.0,23.0,24.0,17.0,32.0,25.0,FFFFFFFDDEDGGHGHGHGFDHBCACGEGEBEBECFFBFBDECCDEHCFGEACHDHDHCFDHEGABHEGBGEAEHBAGCGHGHEEEDEDHFCGDGBAHAGAGDGBACCEAGAGAGAHFBCHCGCDCHCHBDBGBEBGCDFDBCBHEHEHGCGHBCBCGCAADDDGHGBDEDEGBBDFEAEGBCH,False +732,2.0,3.0,2.0,0.0,1.0,3.0,2.0,1.0,FCFGFHCBGBAEAB,True +733,6.0,2.0,3.0,2.0,1.0,4.0,1.0,4.0,BFFCHCHCHAAFADBGFDAHAEA,True +734,5.0,4.0,6.0,8.0,4.0,8.0,3.0,7.0,DGHGDEDEFAFBFBDDEAADFDHCHFAFBDGHHHHCCCCFCFBEA,False +735,11.0,7.0,8.0,6.0,4.0,4.0,8.0,5.0,CHCACAGAEDFDCBHDHFHBCDDHAFGGGCACAGAGBBBGBEBDFAAGAECEA,False +736,20.0,16.0,16.0,26.0,10.0,23.0,15.0,12.0,BDBHCCEBDBACHCDFGFCADHDFDHAECDAGAGCFEFCFEDDDDDDDCFHHADFDABEGGGAGAGADABAFCFAFDBEBEGACADDDHAHBECHDGBGBDDEGEGDBFCFHBADGHGHFFFBFAFAFCFCFBFCFBA,False +737,23.0,11.0,24.0,14.0,10.0,9.0,22.0,11.0,FHADCDEAAAABDBHAFADADFCGGGHGAEAHCGDDCDCDHAHCGGGGCACFCBCBCGCHAAFAHEBADAECGCGCGDGECEDGBFCDBAGACFHAEGCGEGBGCECHGGFHFABABABCCDCE,True +738,26.0,23.0,28.0,29.0,22.0,16.0,18.0,26.0,EHDFFHFHEAFFBBEHDBBBDBDCGEGEGCBCDGHAHDEDEDFAFGCCCACBDAGAEFHFHADAFHCDCDBDHAAAAAHCHCHFHFEFHCHFBAEDHCBCBCBEBDADGDAHAGACACBHEDDDEHCHBDECCGBGBHDCDHDBGCCBGDGCHHGFBAEGEAFACACBCEEEEHEGCGAADAEBGDDD,False +739,8.0,2.0,10.0,6.0,9.0,6.0,10.0,6.0,CGBDCDCHHEEAEACAEEGFHFDDDDFGFEAHCCCCCBFGAGAGEFAGAGHCEGEGH,False +740,11.0,8.0,17.0,13.0,9.0,9.0,18.0,8.0,BGAGBECGDGHFHBHBGDGDGCCCCCCFCFDFAFHBDADGDGBBCACAFEDGDHCECHAEEEBDCGGAGFGCGDAAEDEACHEHCCFGAGDGF,False +741,4.0,2.0,8.0,8.0,5.0,1.0,3.0,4.0,CECEAEHCCADDHDHGGEBHBECFCDDDDCDAGAC,True +742,2.0,9.0,1.0,2.0,5.0,5.0,1.0,4.0,CBHEDBAFFDBABEBEBHFHBHBFBGEFE,True +743,18.0,19.0,21.0,21.0,22.0,11.0,26.0,21.0,EAACDDDHDGEGBHHHHEBEBABHEHBFGCGDGEGCDCDGGCGHFFDFBBGACADADHHADCDGDGBCCCBEDECAGHGHBFCFEDEDEGGCBEFEBEBEHADBHBGGGADADFGFDAEAGBBHGDBHGHCHCACACAEFEGHCECEAFHCHBGEGECA,False +744,31.0,23.0,20.0,24.0,21.0,22.0,28.0,21.0,DADEBEBEDADABCBFGGGGGHGHAFFGBGBGCGDGFGHBCCFDEHEADABAGGBGFCFCAGAHHEDBHBHFFEHAGAGBCDFAEBHDDDDEHHACFBHDGDGACFFBDBAAADAHAHCHCEGAHAGEEEEEBHFFGADABABEBEBCDCBHFHFAADFCGCGBAADDDFCCCHFEFECEAGACAGDGFE,False +745,5.0,11.0,15.0,7.0,10.0,9.0,7.0,16.0,EFHFBCACFCEHBCBABABCECFHHHHFEFHCHCFCBHHGGEGEDDDHAFGEGCBDDDHEEAFBBCHCHEHGHBCBCDCG,False +746,1.0,0.0,6.0,5.0,2.0,2.0,2.0,0.0,GDCDCACECEDFDGCCFD,True +747,14.0,8.0,8.0,12.0,14.0,15.0,12.0,12.0,HCHDFEEGCBCDCAEEEBEFEFCABABFBFDEGFAHEHAHCHGGFCFDEDAHCHDFDGDGABHEAAFAFHFEEGAGDDFBHBHGDGEGAGAFAFD,False +748,23.0,22.0,15.0,27.0,27.0,24.0,31.0,19.0,CFEFAHGBGDEAEBEAEBHBDDGBFAHCGFHFHGEGFAFADBEFHBEBCCFCGEGADBBGGCGBGHHBEGEGABBEEEAHAGEGFGAGFCCBFAGBGFGFGFADDBDBGBFEFGFAAAABHCDDDDDDFDFHFHBGDEAEDDDEDEGEDEDECHDHCFAGAHAEAGADFGHEHDHCCGEGEDBDFCHC,False +749,18.0,23.0,17.0,19.0,17.0,23.0,21.0,21.0,EAADEDBDBFBEECFCDEGFDFHBDAFFBCCCGCHCHAFAFAGGHGECECEBEGAGDGDHEFEHCBAADAFBFBHBABGBGCFCDHFBDEDECFGFBCHHDBBCHDGDFFBFBGDGBHHAHABADADEEGHGHBHFFFFEFGCGCDEHHGHGAAAGBBH,False +750,26.0,15.0,24.0,31.0,22.0,18.0,27.0,36.0,HFCEEEDBCEHFDCDCDGDAHEDGBCCDCGHDEECFHFAFADHFCGEEAEHEHECGABAHFBFBFDACBDBDCDHDHGFBFACAHAHABAHHHCDGHGHGHAABFHFGGHADDDDDADCDEDGDEAGGGGAGBGACCHBHBFDDEEHEDDHCHCHCHGFGAHHHBHFGCGHEEDEDFBAGHGHCECGCAHAGFEADAGA,False +751,2.0,2.0,6.0,6.0,5.0,4.0,2.0,6.0,DCHAHGHCHCEBEGDFCHCDCFEFEDEFHADBD,True +752,12.0,16.0,4.0,9.0,13.0,13.0,11.0,4.0,EBEBDBDBFAHAHADAGBCBFHEEAFAEEBEFGFEFAAAGGGBAFCFCFDGEBBBBBBGAFEEDDDGAGFGCEFEGBDDFHB,False +753,20.0,22.0,13.0,25.0,23.0,25.0,27.0,11.0,DBDAFFDEDEDEFEFDBCFFHDDEEEBEFDFEFEGBGCHCEBEHEHAABAGGGDEAFDFBGGGDFAFAFACHEEBHACBFECCGGGGGGFDFAFCGEGEFHBDBACAHAEFDBDFGABFBEGCGCDHDHDGDBDBDGCFBGCAHGDGBBFAFABEGEGABADADGB,False +754,13.0,24.0,24.0,21.0,25.0,16.0,20.0,11.0,BHBDGCGFGFGFGHGHBFGCEEFEFBAHEHEHEBCDEDEDBBCBCEFECGCDBACAGDGDBBHCCGDAAEAHCEFECABABDGDGCBEDHGFEDEDBGGCACDDBEBCBDFGGGEEHECECEFDFDBBBDCHAFDCBCBCGCFFACAEAEDBFE,False +755,21.0,23.0,12.0,20.0,22.0,23.0,13.0,24.0,FBFBCBFBFECEBHBHDHBBBFBACGBGBDAGFDACHHGCGHFDBHEEEFEAEBEBFGAGAGEDDFDFEFBCAFDFEAEAEDFDBDHECDCFCEAHAFEEHAHGHGHCBDAEGHBDDDBDEHGBAHAFCHGBFHFHEHEADHFHFHFDEBCAAAAHAD,False +756,9.0,16.0,8.0,17.0,8.0,7.0,7.0,4.0,EFEFGFGCCBABHBDDDDGDABBGBFBFEACDBDEDHCGEGBCBCBFDDDEAFABADAHEBADHDCCEDGDBBBAD,False +757,15.0,20.0,18.0,27.0,18.0,16.0,16.0,19.0,GHFBGBCEEAHDBDAHAHEBFFDDDDBFBEEAGBDHDBEGHAHADDEDCFCFBHAHBHDDGDGDECECGHGFGDADEFCFCFDADBGEEBCDEDGABABHBHBHCDCECECEGACCEABFBFBCCHABGHFHFACDDDDDGHECGFGFH,False +758,24.0,10.0,20.0,10.0,13.0,18.0,25.0,18.0,HEHAHAFAHCGCGCHEBGCGHGHGFGCGEABGHGFGHCHEAACABAHACFEAGCECBGGGGGACDFHFAFDFDFDFBEEAEAECFCAADAGFCHHECFHGAGHGEAHFGCCDBDBGACAGADABBDBDCFAFHGEFCF,False +759,5.0,2.0,3.0,3.0,1.0,2.0,7.0,3.0,CFAGGHGHGHBDGDGACEDACAGABF,True +760,23.0,15.0,19.0,10.0,31.0,25.0,21.0,16.0,FGFGHGDGBHACAFAFEFEGEBFGFGFECEDBFEFEHHCFAEACFBBBAFEDCGCEAECFCBBHEGEDEAEFBFGFGADCCCBHAAEEBABAHAHACECFHFEDEABFEDEAEBECACECGFGFEAGAFEFACHGDGAEAEGHHHHGDCBEDEHFHGGCG,False +761,4.0,5.0,6.0,6.0,5.0,5.0,6.0,6.0,EFBFBFGDHCHFEFGGBDAGACHCHDHBAAECCBCDEDEDGHG,False +762,5.0,7.0,14.0,5.0,9.0,9.0,6.0,9.0,EGEFHBHFGFHCEDEBEFACAEAECHCHCHCHBGCFDFCCACBCDHDFGABHBCECDGGEFCFB,False +763,7.0,10.0,9.0,14.0,6.0,13.0,15.0,4.0,FHBHAHAFAEDCDEAEHFDDGFBFBFDGGFGBGBCBFDGDBCGEGECAGAGDGDFDCDCDFGCGEBDGFBACFBFDCG,False +764,18.0,17.0,21.0,10.0,17.0,19.0,30.0,14.0,GFCBGAFBBEFFCGHGEADAHFHEAEAHAHFGGGEGECCFAGAGFFCACBFAFAFGGGAEHGHFHBHCACHFAFDEDHGEGDFBCGCAHGCEBEHCBGBDDCAGBDAGECECACBCBCGGGBBBBBECFCFEFHGDGDGDGEGEGC,False +765,16.0,9.0,24.0,14.0,21.0,12.0,17.0,12.0,FCCCCEGDGDFBEGCBCDDDDCHFGACDHECCCEEAHGHGCCCFEAAADAHGEBEFDDDCDCEAGCGDHEAEAGADAGEFCFCFGFGEAFHEECECEGHGBFCECEBFBCAEBGBGHAHAHAHBE,False +766,2.0,5.0,3.0,5.0,5.0,3.0,5.0,14.0,GCCBCDHEEEFHHEBEHGHBHDHDHAHFGAHDGDGHHHHBFB,True +767,25.0,19.0,25.0,19.0,30.0,21.0,34.0,24.0,AABAGCCCGCDFDAEECGCHBHGHGHDAGCGDFDCEGEBAGFEEEHHAGAGAGFECEHGCECEHFHABEEEBEFEBEFEBCGGGDGABEDEDADGFGFCHHHHDDFBFBAEAEAHGFCFAAAAABAFHECGCDCGFADDBHBGCEHFBBGDHFAFHBHCHFHAGGGGGGAGCGEDEBEDECHFHGBDEDBFGCCCCE,False +768,25.0,18.0,18.0,14.0,17.0,14.0,28.0,21.0,DBBECABABAFFCHGBFEAEHGGEEEHGHGAGADAHGCCFDFDGAFCECECDBBBFBDHHGHEHBHAHGCGFGHHCCFAEAECGAGFHHCEGGGCDCEHEHEDGDHDAGABACCBCBGFFBBHBABADAGGGGHGAGAGAECFBAGAFADAEHDD,False +769,1.0,3.0,1.0,7.0,6.0,6.0,6.0,3.0,EFGFHFCEBGHFBDEDEHEAFDDGDGDGDGBEF,True +770,10.0,20.0,19.0,21.0,15.0,21.0,16.0,16.0,CDHDGGGCGEGECDCDCDABFBDBFBFDFHFHDDBEAEHBGBGCDBGBCHHDGFGCHDHCGCAAHABAFHHBDEFEFCFDFCFCFAHEFBFBGHGDDDCBEGGFEBEAEBDBHCHAEFCDCBFEFEBHCGCBFDFDEA,False +771,4.0,6.0,5.0,4.0,2.0,2.0,2.0,5.0,DBACDGDBBHBHCFDECECACAHAHGBFBH,False +772,20.0,21.0,27.0,26.0,23.0,24.0,13.0,18.0,HHGDAACADHDEDCABDHDFCFDBCFCABDCCCCFFFDFBCBHBGEGHGADACFDGAADDDDDECEHEHDFEBEFCFHFAFCFCFAFCHHHCEBEBEGECECFCHEFDCGBAFADAEAEDEDEFEHEGDAAEBCAEABBFBFBEADGCHDBGBDCDFGGBCBCBEHGHCHBF,False +773,23.0,11.0,12.0,12.0,15.0,10.0,15.0,14.0,HHBEBEDEBGBDFCECGCGEGCHDHGHGBCHAGAGAFAFAHAEEEAEAGBGEGCGAACABBHDABFDFAHADGHFBCDDHAAEAEAEAEACDFDEAAAHFDCCGCHHGDBFF,False +774,17.0,24.0,28.0,15.0,15.0,16.0,18.0,18.0,EFEFEBGCDADCEHBHBHBFBECECBFBFCGCEDEDCCFCGCGFGFACCDFHAHGHBHCHEHECCCGGFCHCADBBBGHHEGCCCGCBHGEGBBBAADCDCDCDADADABFHFAGBDBAHGBBABFEFGBEAHBGCCHFHGDABACAFDEA,False +775,3.0,0.0,2.0,1.0,0.0,2.0,2.0,3.0,AGHGHFDFCHCAA,True +776,17.0,9.0,11.0,6.0,12.0,12.0,17.0,14.0,GCGDABAFGFGCCECFABAEAEBGADHHEHAAAEDEAEABDFCGBADAEHGHFFFGAGFCFDBHBFGHHCGAGHGEGHBHCECEAEAGFCFCBHGHGH,False +777,4.0,6.0,1.0,5.0,7.0,2.0,6.0,4.0,HEFEAEAEDBBGDCDHDFEBAAHEHEDGBBBGGGG,True +778,6.0,7.0,4.0,4.0,5.0,13.0,4.0,5.0,HEHEAFGFAFAFBGBAFFFDEDECBCFGDBEHFAFBFDFHFHGBACCB,False +779,9.0,7.0,5.0,6.0,9.0,8.0,7.0,9.0,DGBEBEDHAFAFHFHFCFCEDEGEDEDGHAFBHBAGAFBCBHFAGADAECCBGEGHHEHA,False +780,19.0,21.0,16.0,16.0,23.0,19.0,26.0,22.0,FFCAGEGEGAHBBEBEGCDFEFCFGHHDHDHDBEFFAGEGAGAGAHEHFAEDBACCCEDGBEACFCFEDEABABABFHFBGBGAGEHHACBCGCHCHGHEABACDBDHEGFGEADHFBDCDCEBBAGHGHEHEHGHDHDGDGFHABECEBDGGFGBGBEFFF,False +781,15.0,24.0,23.0,18.0,23.0,14.0,17.0,21.0,FEAGCCBABABAFAHCDGHFCAEGBGBGHHBBCBFBABAEDEDADHFECGDGAHEBEBECCGCHCHEBCFEDDDCGCGDGDHEFGGCHCBEFECAHDEDFDEHEGEFBBHGGCECECFBDBDBAHAHEHDHECFBFDCECABABHBGBCHFHDHE,False +782,14.0,24.0,23.0,18.0,18.0,17.0,19.0,17.0,GAECGCBBAGAGAGFEEDDFBEEEBBGGEECCCCBEGEGFGDGCHCHCHEADBDBHBHFGADBFGDHHGAGADDDDDCBCDHFBFHDAGFHFHFHCBCFEHHHBFCFHFCGCBCAGFEBDFCECHCACBDBCEAGDBDBEBEBEBABAFC,False +783,17.0,21.0,14.0,26.0,20.0,11.0,14.0,15.0,CHAHEHDHGCCADABAEDBDBFAEABGDDCGADADBBAFCEGDBEBDHGEGFHEHEHEFCFDGHADADBDBDCDCGBABDECEDEDFDCDCDADEDBDHGBGBECDHEHFFBAEAEBEBGHGEBCGGBEFHBHCFAFA,False +784,9.0,13.0,21.0,19.0,11.0,19.0,13.0,15.0,ADHDFGEBBCCDCDCFHAGDBCBCECEAGAHCDEAHBHEFEAHHGDCHCHDHDHFBEADFCGCHDHAFBGBGBEFDFGFECACFEFGFDCDEBGBGCFBFCDGDGCFDFHFHFCFCDCDB,False +785,3.0,4.0,10.0,4.0,5.0,8.0,5.0,7.0,FCFCGCGEAAGFCECECHFFDHCACGCGEBHFEFHBHDFDBDBHHC,False +786,13.0,15.0,20.0,21.0,12.0,14.0,14.0,18.0,BFDGDGDADECHCHCEDGDBDGHCHDGCABEEFEFGGDDBDHDHDGCCEBDFDFBHBHBHFHFAECEBAAAFAEAHBHGHDFEFBHBABECCCCCDEGHGBFFGHCDCBGDCCCFHDCACAFGHADA,False +787,12.0,21.0,22.0,19.0,22.0,24.0,29.0,14.0,CGCGEECEGGBEAGCFFFCDCEEACFBFBGBGDGDHDHCBCGADEHGHBFGFGFDFDBGEGEBFCFCFCFABDBCAFFGDGBFHCHEECDFDFCBEBFHGCGEGAGAFDFCEGEGEAAHHHBGCGCGAGDGDBDFGEDBDFDBCHADEEGEHEHABBFEHBCB,False +788,17.0,13.0,19.0,20.0,16.0,16.0,19.0,15.0,BDCEGHGDAFFHFHDADAHEEEECFCGDHBHGGGAGAEFGBCADGCCCCCCGCDCBEFEFDFECADABAFEBGBGAADGEGHADABHFHFCEDHDGGCDCDFDADGHCFBBCBCEHBHFHDEDEDEGHGAAAFBF,False +789,28.0,17.0,13.0,32.0,28.0,13.0,27.0,17.0,AEADADBGBAFAEADGBAAGDDEGEBEFCFCFHFHAEGEHDHAADEDHDCFCBAEGEGDGCGAGBGBGBFDDDEDGBGBGBDDGGADCDBGAEAGDBCADEDHBABAECHCECAFEHAFACDCDGEHEHFBEHDDDDFEAABDHGHGHDAGECEGEGDHEAEGEGEAFHDHDFAE,False +790,20.0,14.0,14.0,14.0,17.0,15.0,16.0,18.0,FCFDDDHCHCEGHADCBGFEFCFEEEEBEADABHBDEFCABABAGAGEHHBHBDAECGDEAAAFAEADBHCGGBGBGBEFEFEFABAGFHHGACDBDHHGFDACEHDHGHFCFDHCHCHCEFAGAGAG,False +791,18.0,17.0,18.0,19.0,20.0,20.0,6.0,18.0,FHFHFDEAADAFBBACGHDCDFAGGFEFADEDBFBFECEAFAFACCCEFHBHFHBBACHFDGDCDHDHGBAHCDCBHBEEEEAECBABCBCEDHDFDEDEDEAEADACAHFHFHEDCCABEHEBEHCFBFGFBDHC,False +792,14.0,17.0,13.0,12.0,11.0,16.0,16.0,11.0,DDBDBDAFBDBFAFAGBDEGCCECHCHCGFABGBCFEFECHFBABAEECBDHDGDGHGHGFCFHEAEGDHBCBEFHBGAGACAHAFGFGFDEABFBABGFGFGBHCAEDC,False +793,9.0,19.0,17.0,11.0,13.0,16.0,16.0,13.0,DCGHBFFCGEEBEGGAGFDEEBFGHCHCDFDBCBCFCFCGCGBBBCBCBFHFGCAEABHBABGBDBDFDHAHFGFHBBBGHGHECFDECEGHGHDAAGDBCECDAEAEFEFCFH,False +794,18.0,14.0,23.0,18.0,18.0,15.0,28.0,20.0,GBGBGFGAEFECEBGBECECFGDEDGFCFGGHCHCFGDAHHCHCFCFCGCGCEAHAEABACDBDBAGGCGHAHBDFDHEHEGAGEGEHHDCDGFHBHGHFADECACAEABFCAHGHGBDCDFDFBAGACDGGCDBGGADHDBFHEHEAEGDCEC,False +795,2.0,6.0,5.0,6.0,3.0,1.0,4.0,1.0,GDGECBCHDEDECBBFBCBABDGDGACD,True +796,20.0,15.0,22.0,19.0,22.0,17.0,35.0,28.0,EHGHCDCDAEBCBFBACHCGEFEFEFDFHGHDCGAHDCGCDCACBGEEHEHGGGEHEFEGGAAAAHAFFECCAGHGHGHBACACDCFEAGGGGGGGCGAFCBEHHGDGHGADAHGHBDGAGBCDCABAHDDEEFGGEHHHBBBDBDHDHDHFHEHBCDCGFGECEFFGFGEGHFBEDA,False +797,22.0,14.0,14.0,13.0,13.0,14.0,15.0,9.0,HCHGGBDEFAFAGAHDCGCGCHCGFAADEDEABAGABFEFEFEBDFGABHFDAABCHCFCADBBAGDGDGDCDFEFGBDBDFFGCBCBEBGAAAAAAHEHEBEGCAAAFHECEC,False +798,15.0,14.0,14.0,26.0,14.0,22.0,16.0,23.0,DCGAADDDHDHFFDBGGFGEGBBDHAHFFFFAFCFBDDFEAEDHDHGHGDCHCFAGBDFCFEFGAGHECFCEDAHAGEBFBABDEDADCDHAFCFAFHBDFAFADEGEHEHBHGFGCGHGCDCDBBHHHHBCBCHDEDEDEDHH,False +799,27.0,20.0,19.0,24.0,17.0,17.0,26.0,21.0,GFGDGDCDFGBGBEBGBHHFDADAHEHEBBBHFFGGCADACAGHBHAAFACACHBECEFAHADGDAEHECFABCGCAHBHAHDGEEHFDFHFDFCAHDBDBFEGDGDGHBDBGAGEGBGCCECEBEHAGABADADADECGCGCAFHGHBFACACFDEDEBGACAGHGFDDD,False +800,14.0,22.0,27.0,22.0,29.0,27.0,20.0,20.0,BCBCBCACACAHDBFCHEHEFBGGCGCABBHBEEEBECECBDHDEBAACGCGFGFDFGBCDAHHHHFFEDDDDEFFHFDEGGGHEAEDEGBBDFEADFCGCGCHFHGHGEDCHFFFDFDCHFBCBCBCEEEGACAEHEFGFDFCFBAEHECGDEFGHGAFAEBBBBDCEHFCFEFDCDEDE,False +801,5.0,1.0,4.0,0.0,2.0,1.0,0.0,1.0,HCAEACAFBEACAC,True +802,15.0,14.0,17.0,11.0,11.0,11.0,14.0,5.0,DGAEAFAFCFDADEFEFCACGEHEFGCHABACABHBADDFDFCGEGEAAACHCGDGCGBEBFDCABBBBDBABFGGCCCEGFBBBEDAHCGCGCGCED,False +803,19.0,24.0,22.0,27.0,21.0,24.0,25.0,26.0,HFAFEFEFCCCHCHGDDHEHEDEACCFAFBHDEDEBGCGBFAHAHAHFGDBAGAHBHFEFBFEFABCDHDGACACBGDGHAFBDBCFHFHDHDGDADBCFGGBDACGHGCECEGGAGDGDGEGECADHDABGBDDCECEHFHBGGEGEHBFBDHFACAFBBBBHEEEGCDHGFDFDFEFHDHDCBBBC,False +804,14.0,12.0,12.0,16.0,9.0,14.0,9.0,8.0,ABCBAFDEDFDHDCDBAFCBGBDBEAEGEBCDGAACABDECECEHEAGHGDBHFFFCGDADFFFGFDBDFAHCHCHCHCBADADADABFFGGEF,False +805,10.0,5.0,7.0,4.0,17.0,8.0,9.0,3.0,AAGAGAGAGAHECEFEGEHEBEAEFDADFEEEECEDECHGFEFAFBEDFGBEACBCEFBCCGG,True +806,16.0,25.0,13.0,17.0,23.0,16.0,21.0,18.0,CBGEEFEGBBBCHGHBAAAAGAGEGCHCEDBBBBBHHHHDAFFEEDEDAAADFEBHGHDHEGEGHCECEBBDADGGGGGDGHEHEHEBBBFGFAFDFEFEBEBCFFEBHBECDBDFAFAGHDFDGBHDCFCAABCBHEGDGDEBGCCAF,False +807,3.0,8.0,5.0,8.0,9.0,8.0,9.0,9.0,HFFFBHCHEBEBEBGBDCGCECEFDFBFGAGHHDHFACHDHDEFBGDGEHEADGDBEGG,False +808,18.0,19.0,24.0,19.0,15.0,25.0,23.0,17.0,CDGFCFCAGHEAEADCGEGACBGFGDHEEECACECECFAHAFDCDHDFEBEHDFDFHFGBEBGGGBBBHBHFAEAFGFAHAGAFCGCHCHGHBCDDFDFDGDFBEBEBFAFCFGDCCHGHADCBFBGBGHFCGDGBCAHFDFCFCBCBDAEABADGFGHC,False +809,24.0,16.0,20.0,18.0,20.0,16.0,26.0,18.0,HBEFGCGHAHADGCACAFBFAFCEBGBFDGAGAEHHCDDHDFDHDHDEECGABCBFEAEHDGGGGBABGFEBCAEGBCFCHGHBHBABGBHFEFCCCCAHGEGEFHFDGAEBHDADCGHEAEAEAEAEGEDCDADGDGAGAGAEHDGCCFCFCADBGF,False +810,7.0,10.0,7.0,14.0,17.0,13.0,14.0,8.0,DEAEGEFECACABGEGEAHGHGHAEFEFECHDDFDBDBCBDBDFGCGEBECEDDDADBEFEBDFGBDFHGCFFDGGFEHEHFHBGAGEGF,False +811,11.0,12.0,11.0,18.0,16.0,11.0,15.0,16.0,EBEBABDHDHDHEHGHFAAGGCAFEDDGEFAFHDBDBDHEGGGGBCBCFDDDDDEDBHFEBHCHABEFEFGHECECBFGGGEDHCHCGEGACAEAECHABCHDADFDFHG,False +812,7.0,8.0,5.0,1.0,6.0,6.0,5.0,5.0,HHHHAEACACBEBCCAFAGEFCFDBHBFBFEGAGEGBGFABBE,False +813,7.0,6.0,14.0,17.0,20.0,8.0,11.0,16.0,BCHCAFAGAHCEFEDEHEDCHGHAEDGDFCFHGHGHAEGEGFHBBDFEHEDEDHDEDEBGDDFBEHGABCEDECCCADGHEHEHCHCDCDCDCEEGEFD,True +814,27.0,14.0,15.0,25.0,17.0,16.0,12.0,25.0,HFFCACAHFFCBCFFGDDECEFEHCBCBCDAAAGAHAHDECEFHAHAHDEABBEBCFGBGDEAEAEADGHAHACDHHHBCBEDFFAFHFEEGAAAAAHAHEHEDDDDGAGDHDBDFFAHDBACACAGHHDGBGBEDDBDHFHECGDDDHDH,False +815,9.0,8.0,11.0,6.0,5.0,16.0,9.0,7.0,DDGCCHAAADDFEFBHDFFFDFCFCFCFEBEGGGCFCGHGHEAAAFFHBCBGBEBCBFFFCFCAAGAHHGB,False +816,27.0,23.0,14.0,24.0,26.0,27.0,25.0,22.0,DABHHHEHAHAEFDBAGABDBGHDAAGAGFBAHAHEEDABFGGEEADAFBCACGCGCEFEBEBDFDCDGDEFEHEHFAGAGCBCGCBCBEDAGGBABHDFBFBDEHEHGBFEFEBDFHFHFDEECAFGFGFEADHDAGAGADCDCHFHCEADFDGEAFBFCFDBEEDGAGBEFEHDHGAGHGHFBFBF,False +817,1.0,1.0,2.0,2.0,3.0,7.0,3.0,4.0,FFFFADHDHEHEGCFBGECFHFG,True +818,10.0,14.0,17.0,5.0,12.0,5.0,16.0,9.0,CACBHAACABGDCAEAFGBEHEGCGCGEGEDBGAGFHBGCECEFEGEGBHBFGAGHEABDFDBCBCBHEHGHGBDCACBGBECCCCCH,True +819,20.0,12.0,13.0,11.0,16.0,13.0,21.0,6.0,ADCECACDCEGDFFAFBGBGBGBAAAEBEBGFDADEDAACACDCHHBGGGGGGGEGAAHFEFCGDGBCFABAFEGCDHFECEDEHABCDAHFGAGEGAGAEAGBFBCEFEFE,False +820,24.0,22.0,18.0,21.0,20.0,19.0,14.0,22.0,ECFBHAHAHAEAFBFGDGDCBCGAEAHABCBHFEDEDGBCDCDADABAEAEBHDGDHCBAHFDCDHHBHEGAAFAFCHCDDEHBFBFDGDGHBAFCEDEHFCEHEHEHGCGAHABCBEFHFGCDCDFBFBFAFGBDEDAGCHBEBCBADAGEBEAEAFFH,False +821,24.0,21.0,19.0,22.0,19.0,13.0,20.0,29.0,DAHAHAFEGCDEECECAAEHEFDDDGAGAGAGABHBGEHDHFHEHAHAHAFBHBHCAADCEBBGDECHGFGHGAGEDFDFDHHHCGAEABFDGBECECAHACFCHGFBDHGFDHBHDDDDGGHEHAHBGBGBHEABBFBDBFBDAEEBECCCCCACHCBCHAHDGDB,False +822,16.0,25.0,27.0,23.0,14.0,15.0,16.0,28.0,BHCHCDCAGFGAGBFHEHBABGDHBABFBGBDCHCHCHEHAHEHCHDBGBHACADADAFFHAADACBCBEGEFDFDFDFCHEHDDBDEGEDHHHCDEGHCFGFDEDBBGFGCGHAHBDCECHCABHFCCHCDEDCDCGBBEHDHBGBFEFCACHCBBABCBDGC,False +823,19.0,16.0,17.0,19.0,13.0,21.0,12.0,12.0,AAFGBDHDCDFDEHBBFHFCDCABBFDFGEGEBCHDDDBDGDACAGABEGECECECEFEHCHAGDDHCCDAEFFAFBFBGDAEHHBABAHADABGBFCFGDCDFHFHAGAFAFDFBACACFGFEFECBC,False +824,23.0,14.0,24.0,16.0,17.0,21.0,26.0,11.0,EEEECEBHDFDBDCFAABFDEEGGCGEGFHDGAGBCFCHCFAFAGAGFFBGAFAEABCGAEADADAHBBEHCHCBCBCDCECGHBHAFDEDEAAACACFFECEFFGACCDCFGGCGCGFDFHFGCGCGAEAGGHHFBFDADABBCGGGDGDG,False +825,16.0,23.0,19.0,19.0,25.0,21.0,19.0,16.0,BCECEGEHBGBGDACADFFBABGGEBEGCGAGDBCFCEADAEFEDDCHCDEDGBGCFHFGBEBEBEHCHCEBEDEBFBFEFHFHFGDEAEBGBEDDCBHDFGFCACAGAHBDBDBCCFCFAFDDDADHEEEFHAEAGBGCAHHHEHFGFBFGECHABF,False +826,8.0,5.0,4.0,4.0,6.0,3.0,1.0,4.0,CDGDCFEEEEABABADAHBFBHACAFHEAEAHCBD,False +827,24.0,26.0,18.0,19.0,16.0,34.0,27.0,29.0,CFAFCHHGFDHDBDBDCDCHEFBGBGBHBDADCGCGHGFDFBAHDDAFECBFFFHFAGECAHAEBEAAACGEGHGEABAFGCEAGFFHFGACBGHGAFHCHGHGBFAHGHBHBGBGAGCFBEDHBFBHEHEBFGECEADHFHFHFDABFEFHFEFBFBABDBDFDADGDGCAEAFCFCFCDAGGFGFBHHHHB,False +828,2.0,3.0,1.0,7.0,4.0,6.0,1.0,1.0,ADDDFDFEFEDEBFBEGFDADFHCB,True +829,18.0,8.0,19.0,22.0,14.0,21.0,12.0,12.0,EGEGCHAFEECHDBDBDCFAFEFDFEGEAFCFDADADCHFHEADAEHDHCCFCFDFHFDFDACACACEFDFDGBFBCGEGFGCGCAHADACEDDGCCACHBABDBHAHFFFDDHACBDEAEGGGFD,False +830,14.0,17.0,12.0,13.0,7.0,7.0,14.0,9.0,EGEBHBDCDGECBABADDGCABACFCEBDCCADADFGHGHGFGBGBGHGFDDCDAGABACHHDHDFDCBBGBAAFACEHAGAGBEBHBCBEBF,False +831,13.0,21.0,11.0,11.0,12.0,12.0,12.0,8.0,EAEDGBFBDBCHEBEBEBCHCHAFGGBCDDDCDCBADAFAFABADFCBCGEAEDBAFAEHEHADFHBBEHEFBFGEBHFGBCBCBFGGAGAGBGCGFBDB,False +832,14.0,20.0,21.0,16.0,26.0,24.0,30.0,17.0,BGGGEEEBFFFEFCDGGGGGCGABDFGHCAFFFDFEHDHAGAGAEBEBCBCAGBBDBFBFEEEDDFCCGCGEGBBDBHEDCFCHGFEEBGCFAEGEGECFCGCHEDDCBEDDDHHHCGBGEHEHGDDCGCGBGEGEBEHECGGAEABAFAHAFAFHFHCHCFFFHFBA,False +833,0.0,0.0,2.0,1.0,0.0,7.0,1.0,2.0,GFFCFHDHCFFFF,True +834,15.0,17.0,13.0,12.0,21.0,19.0,18.0,23.0,DEFBAGHEHEABHDFGFHFHCHDHECEHBHDGDGFFCGBFBEEHHCDEFECEDEBCBGEGEGACAGHGHAHDFCBHGFFFFDACEHEBFBHBHGAAEADGGADHHHHGHGFAFCFCGEDFFABABGECACABEBEBEB,False +835,9.0,17.0,15.0,12.0,13.0,15.0,12.0,18.0,AEAFDHGHGFDEDBFBABACCCFCHEHCFEDHFGFDHBHBHEFAACHEDECFCGCBCECEGHBHCABDBEGFDFDBDBEGEFFCCGHAHAHGHDFBBGBGDGHBHBCBFHE,False +836,24.0,27.0,17.0,31.0,24.0,22.0,21.0,23.0,DCGBEBCDEDADFBFEDADADBDCDCDEDFDGBGCGBHBHBHEHEDEDAGBGFDAHGHBCECADBDEDBFFAFAFAFEHHGCGFEFDDGDGFBFGEGEBAHAFDDHFABBBDADAHAGAFFFCGGEECHGAGAEECEBFBCBHHGEFDAAECFADHGHCHBBBBDEDHBBBEHHAHCHCAEFEHADGDC,False +837,8.0,2.0,11.0,12.0,11.0,8.0,3.0,11.0,BHCHEDEHFAFHDHCHFDCDFDFDAAHCFDDADHDECECACECAFEHEGDGEHEDEHFCBCGCAEA,True +838,12.0,19.0,12.0,11.0,20.0,17.0,13.0,16.0,DEFEFEHEFBFECEAEAGBGAFEBEDFGFGAHFHFCGBBBBBBHEFEBHBGBGHCHFBCDFHAACCHEHACDBFEGEDFBCBABHHCHEHACACEDDDDFDGHGHCAGFDFBEEEGEGBA,False +839,1.0,4.0,3.0,4.0,6.0,6.0,4.0,1.0,GBEECAGBFBFBEDCDFDFEEHEDGFGFC,True +840,5.0,4.0,4.0,1.0,6.0,4.0,2.0,2.0,GEBEFEHEAADACACFCFBBHCAGEBEF,True +841,15.0,12.0,13.0,8.0,18.0,15.0,11.0,15.0,FHFHFEAAHFEFCGEHEHCHCBCAEBBBCHAHAEGFGABHBEBEFCBCAHDHBEAFGBHAFEFBGCFEFCDADBDEDEDEGEFEFAACHDHAEACGEGHGCGAGFDC,False +842,17.0,27.0,15.0,15.0,25.0,21.0,18.0,18.0,DBEBDBEEGGGBGEHCACBCBABGEDEDGFAFCCBEDCGGFGBHAHDBBHBHECACEDBDHAAFAEBEDCDCHGBEDECHAFAFECECEFHGHGHBEBGBGBFFFFHFEFHFHEBEGEAEFFAFGBBBFHCHADFDFBABCGAEAGFHDADEBHBE,False +843,20.0,14.0,16.0,25.0,17.0,16.0,12.0,24.0,HBHEDGBFBCADADACHHDHDAEAHDDDDDHFFDHDGCGCBHEGABAHEDEABACDCEFGFHAGGBACGHAFFGDCAAGHDEGEGEDABACABHFDEEBEBDBDBDHDADAHCHBEFEDEDCFCFCHCHFHFHFHFCAEHHFCE,False +844,6.0,6.0,6.0,6.0,7.0,4.0,7.0,2.0,GCECFBDBDBEGHDEAEAFFECECACBGBDADGDGHFABGEGCA,False +845,14.0,10.0,13.0,17.0,13.0,16.0,16.0,22.0,DADFGHGHFHCBGAFEFCFCGDGDEDBABABECDCDBBGAFAGAHDDDDFDGDGDCEGGFHFHCHGAGDHHHFFCGCHHEFEAHHHFHGEGDAHECDCHHAHAEAEBCFHFBFCEHBBEEA,False +846,13.0,21.0,15.0,9.0,8.0,13.0,6.0,10.0,AGBCBCBDGCBFGHABCBCBEBABCGHEHBAFAFDFECDBBAAHBHBHCFCFDBABDCDFFCGHAHBHBEBEBCFCACDEHACEBFDFGFAFAED,False +847,8.0,14.0,10.0,15.0,9.0,10.0,9.0,7.0,DECFAHHBGBCEAACBCBADDEBHDHDEDFFFGEAEBGCGBGDGDFDADBDBDCFCGCBCHABFBDEDGDGBHBFFCFEAEH,False +848,10.0,5.0,6.0,10.0,12.0,17.0,10.0,11.0,DHDEDCDFDFAFAHCFGABAGFCFBGGGGAHCFDFAFEEEEBBABHFAFGFEEHDHECEHFHFEAHAHEDFDFHFDGGGEC,False +849,22.0,14.0,13.0,19.0,14.0,18.0,13.0,19.0,AACFCFBBHBGFDADADAHHCGFBCHHFHBHDGDCAHAHABDEDBDAHAGFGEBEBACHCDEGAFFDGBHFCFDDBABAEEDEGEFEAAGAGABADAHFGFCFAAGCFHEHFGFBFEEDEHEDCDCDCDHHH,False +850,12.0,11.0,24.0,25.0,18.0,37.0,27.0,36.0,GEGEAEAEDHDEDECECGGGEFEFEGCBFBFCFCDCHEHDDGEGFGDHFGEGAGCGFDHCHFHDGCCHEBBDACHCFCHGHCHCHGDFFFFDFHGHDFFFGFGHHHGCDFBFCHHFHDDBACHEEFDCAHDHBHFFFHHCHBHFHDGFGFGBEAHFHFHFCAGGDCBGDGDFFAACDCAFDFDFBHHAHE,False +851,8.0,20.0,9.0,10.0,16.0,10.0,11.0,18.0,GAGAGFFHFHCHGHEFEGADABHBHBFEEEBAHCHCEEHEDCAGGBBDBFGFHFHAHFHBABEHEBFBCHEBBBDDDCDBECEGDBCBEBEBHBGCHEDDHG,False +852,8.0,4.0,3.0,3.0,5.0,4.0,5.0,3.0,CEHEHBGFGBABDCGAGHFDCGAAAAEADAFEFEB,False +853,2.0,2.0,4.0,5.0,2.0,8.0,1.0,9.0,BHFHFHFADCCGFDFDBDEFAHHHHHFHECCFD,True +854,0.0,3.0,1.0,7.0,1.0,4.0,3.0,3.0,BGEDFDHDHGFBDBCGHDFDFD,True +855,13.0,9.0,23.0,8.0,13.0,14.0,12.0,14.0,CFCFCGHEACCCEEEGDHHAHBGBCFCDCDCFFGCAFDCABHCHCDFFCECGCGCAABFDEDACCHHAFAEBEBHGHBHFGEGCGCGAEBCBAGEFEFEFDHAHAH,False +856,10.0,14.0,21.0,25.0,13.0,22.0,18.0,15.0,HDAFAFDFBGDDCEEGEDFGBDBGCCCCDDDGDGHFDGHEFECHCHCFEDBDBACGFBFBFDCGEGCABABDEGCGCECEBAFGHHBDDDHHHGGDCDCACAFBEBECFCFAEHHFFFDGDGHGHDDFDFHFCFCBAF,False +857,5.0,7.0,6.0,6.0,3.0,6.0,3.0,6.0,HBHCDAHAFGBACABHBDBDEFGCHCHCBEFEFGFCFDDBDA,False +858,5.0,6.0,10.0,9.0,8.0,7.0,3.0,10.0,BGCHCHCBDDHDGDGABCBABFECECECDCDFHHCEDDFFFHHEHEAEAFHBEDHCAF,False +859,5.0,3.0,3.0,10.0,1.0,2.0,6.0,6.0,DADADBGHEADDDCDGHGHGCDCDBFAHHFHAGDGB,True +860,23.0,20.0,27.0,31.0,27.0,21.0,22.0,20.0,GBHCDCFCFDEDHCHGEFEFECCCCCADABAHFHFHFDGDAEEHACDDGBADFDEECFAFCFEGCGEEHFAFEFBABCDADEDEHBHGHBBAECECGBHAGFHHBGECCDEDBFHCACGCDAGAGADDDDDCDGFCFCEEEDEBHGHGHGCGCBDADHBGDDEDABABAEDEBFCDEBABGBDAFAFGEGH,False +861,7.0,7.0,14.0,4.0,11.0,5.0,11.0,5.0,GCGFGBGCCCGFAAEAECECECGBABHHCAEAHAEFEBEHDCDCGFGFBCGCGCDBEEHDGECB,True +862,12.0,3.0,10.0,5.0,8.0,8.0,5.0,6.0,GFCAHAHAGACCEHDBBAAAHADECEDECGCBCECFCFHFHAGGEDEFFCFAEAFAD,False +863,24.0,14.0,29.0,24.0,18.0,18.0,12.0,25.0,ACACHBEBEDABHBGCDCFCEDFCGCACGFADCCCCBCDEAEBDHEEGAGCDFDFDFGEHAHFEEAEHCCFHFEFCHCHDAAHGDCDAHFHEHDHDHAHADEBEBEGADAHEBFHFHACGFGCGCBCDCDCACFCFABCBADDBCBHHDHGAAHAHFFDHDEDA,False +864,12.0,14.0,8.0,8.0,15.0,8.0,10.0,15.0,EBEBGHCABAFAFDFDADGBHCEBGBGBCFCAEEDHCHGHBHDGDHEHEHEHCFGFBEEHAAAHGHGEGBFCABHFHEEBADCDABEBEA,False +865,3.0,2.0,2.0,3.0,0.0,3.0,0.0,4.0,BHDHBCFDFCAHAHAFD,True +866,5.0,8.0,8.0,6.0,13.0,7.0,15.0,8.0,FHCDEDADBEBGAGCCCEBGGFGEGEGAGAGHDHGBEHEDGAGEBECHCGFEEHEHGGFBFBFCFHEBCD,False +867,15.0,8.0,10.0,4.0,10.0,7.0,12.0,11.0,GCHHEHGBDBCGCBCFEAAHAHADFCFCFGAGAFBGAHAEGFBECEABHCHAEAEHGHGFBDCHGEGEGDACABAEA,False +868,13.0,19.0,24.0,20.0,14.0,16.0,12.0,20.0,HCHAHAGDDCDBGGHGHGCEEAEGFBFDEAEFCFHDHGFAFGEHDBDBDCECDFECHCDCFCHCHBBBBGAFDCACEDBFFAFAFBEHCACDHBCBCBHBCADDDBDHDHCHCBABHHEFGAECGCGCBDBDCFHFEE,False +869,11.0,10.0,12.0,15.0,14.0,12.0,10.0,5.0,CBGECDGDGDADCGAHDBDFFFFEAHFEFDBDGDGECECDDFDADBEACGFEBEBECCCGCBCBEAEAFGBAAAEDEGHHDHCFAFEFB,False +870,8.0,16.0,15.0,5.0,12.0,6.0,10.0,5.0,GEGAAFBCBCEGAAEBEBEFHHCBAAGACBBBBEBCGCGCECECBABCFCGCFEDEHCCDGBGFDFDEHCHBBGBDE,True +871,7.0,10.0,13.0,4.0,10.0,7.0,7.0,8.0,GAAHGCBADEDHDCCCACAFHEBBBBBCBEGEGFCHCBEGEGEHDHCFFABCFCFHGHABFECECE,False +872,5.0,6.0,11.0,4.0,5.0,6.0,7.0,6.0,FCCCACBDAFCCCFGBBHBGAGEGDGCGHGHDHDEBHCCFCBAEFEFEHA,False +873,6.0,3.0,2.0,8.0,3.0,5.0,4.0,1.0,AADDDCDCGGFFEBADADADEDGBGFFEFAHB,True +874,16.0,16.0,9.0,13.0,16.0,16.0,11.0,18.0,DGAGHBHCEFGDAAEAFAFBBDFHEDEDHBHGHGHDDEDFCFCAAADAHFBCBCGEHEBFDFAFCFAFAFBECCBEDHHEHEGBGCDFGFHHHBHBEBEBHAEADBEBAAGEGHF,False +875,10.0,10.0,11.0,9.0,10.0,8.0,13.0,16.0,AFADADEDEFHCHCFGBGEHDFGHCHEGBGHFABHEACHBHBHBHGDGBAAAHAHCHCGGGCGEDEBCDDGBGAECEFFFBCHCHDE,False +876,10.0,18.0,8.0,11.0,7.0,15.0,11.0,9.0,FCHDHBFBGCDHAGCCHDHAGFFHBHEFAFAFDBBBDBDEACGGGBGFECECACHDBABFBDBDGEADADFFFGEGEBBBFBFBGBFAH,False +877,4.0,5.0,14.0,13.0,6.0,8.0,11.0,11.0,ACACGHADGCECGGGDCCCFCFBFDFDHDHDADHDHFFBHGHCHCGCDCDHDEEBGFDEHBHGEEBDFCCGG,True +878,22.0,17.0,15.0,16.0,16.0,19.0,13.0,15.0,CCFCHHDBEGEGDCFHFBAGFEDDFDCECEGBCBABADADBGGDBACAFAEABHHHFHCHDBFBDBDBEHHCHCHEEGFGFHAEAEAEADFEAABCFCEAHFGAAADFDFBFBEGCGCDAFAFAEDGBHBGFA,False +879,11.0,12.0,5.0,10.0,10.0,9.0,11.0,9.0,BCBCEAFGFGHBHBHDDFEFGBGHGFBDCAAGEHDBDGHGHFADAEEFEDEDEAHABABACAGHEDFAGEDBGBCBF,False +880,22.0,23.0,20.0,22.0,17.0,22.0,27.0,22.0,AFEFEHDHDHDBFBGBGEGBGFGFGEHEABABGGGABAHDHEBCGCGCFCDBDFEEAAAFDCBFHGHBCGAEDFDFDBCECFBAGAGAFEHGGCGDBBCCGBDDCDBDCFCAHDBAFFHCHDHFHCEEDHDHBHCCBFBAEAEAFGDCDHAHFHEHADAGAGAFBGCGHGFBEGG,False +881,26.0,17.0,21.0,13.0,20.0,12.0,23.0,19.0,BAEAGCGHGAEADABEEEGAAHHDDBDFGAGACCHHEHEBFBHEEEDFGFEAGHCCACGEFEDCGCHCGFHHBHBGBCCCDCGBGBABABFDDHEAEFEGGGGEHAHACACDGBGBGBEAFACEHFAAAHGHGDCCECFCBCBHDAAAFAD,False +882,1.0,1.0,3.0,2.0,1.0,1.0,0.0,5.0,DHHFADEBCHCHCH,True +883,7.0,3.0,8.0,7.0,4.0,4.0,4.0,4.0,GDEDCFHFHDHDEGEACDCABBGFACACGCFCDADBCAEAH,False +884,21.0,12.0,14.0,11.0,9.0,9.0,15.0,13.0,EHEAEGDDAGGBGFFAGHDHDCDCDCFCGGGGGAAEGCHEDEAEFHFAFGCBHBCCCCADBBAGAGHBCACAHAHBFEDBGBCBEDDHHABAFAHAHFBCAAAA,False +885,16.0,26.0,24.0,20.0,25.0,24.0,19.0,20.0,DFDGGAEAEAEDHGHGCCABBEECFCFGBGBDCGFFDBDECEADADHGHFDBDCEEBCGCGAFBFBCHDFDFEFEFHFHFHBHFEFHCHCBAFDFBFCAGAECBBBBEAEBGCECFHEHDCCEGBGBGFGFHHEHCHBDACECABABDBHAEDDCGGBBEFDFDCBAEHEHECG,False +886,13.0,28.0,17.0,8.0,23.0,25.0,17.0,16.0,GFFBFBHCFBBBCGCGEEBCBABFDEBGBGCACEHFHFHBADDCGEGEBHAAACFCEHBHBDAEFFFFDFDFEFEFECEBBBHFGBBHBEGCBEAEDCHEEEFBGHGECEHFHBABFCFCFCGCEAGDGAGAFBGGAFHHHBEBEBF,False +887,12.0,16.0,10.0,18.0,15.0,11.0,14.0,8.0,EEHEFGDCAFDGDCBFBFGFBEAFBBBAGFGBGCHCHCAGADCFCDBDEHEAEDGDBHBFGEBEBDBDADCDHDEABDDEDFCAGDGAGAFDEAGCGBEBEHEH,False +888,18.0,13.0,17.0,15.0,11.0,10.0,18.0,15.0,DEGEDEFAHAHAHGHGHGCGCFDDDADFCBGDGDCBABCBEACAGAGCEDBABDHFGAGAGDEEHAFCDCBCACBEBHCGBFAHAHCDFHBGBGHFHGHFBACEGEGCHAECFCDAD,False +889,22.0,5.0,11.0,9.0,14.0,19.0,10.0,13.0,HEHFADEFGFCEHEFDFHFAFGGGGAGAFADGDFAEAHBCECEDFCFHFCFDFDAACACABBFGCHEAAABCDHEAEABFHFHEGEFHAAAAACAGDHCHEFE,False +890,27.0,36.0,17.0,27.0,26.0,14.0,25.0,25.0,FHDGFABEECADAEBECEABAGHECDCDADGDADADEHEHGHBFBCBGDEEEEEBABABHBHAGCEDEDEHAHAGGCDCDHBABHBCACAGFCFGHHFDFDGBGHGAGCGFFBHADFCECEHBDBGBABACAHEBBHGHEHBBEDEFEBGBDBCGEDBBBBBEBDHDBAHGFGAEBHAADGHGDABFCFDAGBGDHD,False +891,18.0,15.0,22.0,14.0,25.0,27.0,18.0,19.0,FHFHEHAHCFEDCDHFFFHCCCCCCFAFGEAHAFGGEGEGEGFGFAEHDCDFHGAGEBHFHCHBHBEDHDCFCACGBFCDDEHBCEGAFABEBFDEGAFDCACFEFEDEAAGAGAGCBCDFEHAHEHBCBCBFBEEFEHGGGCEFEFEBEAFFBDADB,False +892,15.0,15.0,17.0,14.0,25.0,21.0,15.0,21.0,EGAHHHDHDFEAEDEGGGGAGFHFAFEEEHHBCBGHGBGDFAAEAECEFEDDBFCFCAGFFHFHFHBCFCDHFHCHADBHFGFGBEBHHEEDDCDGBCEEEBGBHEHEDEAFCBCECEBGAAAEDCDCACABEHHCFEFCFBF,False +893,5.0,2.0,1.0,1.0,3.0,2.0,5.0,2.0,BHAHAEEEGFGFACGBDAGAG,True +894,1.0,2.0,2.0,3.0,4.0,6.0,4.0,3.0,FCFCHHEFEFGGGGHDBEBFAFDDE,True +895,12.0,25.0,10.0,17.0,18.0,19.0,18.0,17.0,CECBHFGFGEBBHFEFDBDBABDGAGAEABCBGAGAHCEEHEHEHDDCDBFHFHEDFCFBFBFAGGGGGFGEHBBBHDHBHDEBEFGDCBBBDBGCAHHEGBGBCDFDEEEDEACAFFGBBHFHFDFAFHGBADED,False +896,16.0,8.0,11.0,13.0,10.0,11.0,7.0,7.0,GEDEHEHBBDADFDADCDCAAAHFHFGFECACAEDCDGAEAEBBCBGEACAHDBDEGFHFBCDCFAADACBCHFAFAFEGGDF,False +897,11.0,6.0,9.0,7.0,10.0,14.0,15.0,10.0,HDBFBGCFCGCGBGDEDGHAHGHAAFHFCGBGCAHHGFCFAFEBGHGBDCHCHDEEFEFEAEAEFEFGDGFAFACGEFDAGA,False +898,17.0,13.0,21.0,30.0,28.0,20.0,12.0,19.0,EDDBGCECEDBCBCDHGFECBGBEHHHEHFHDGDHHAFAHCHDBEFDADCDHEEEHEGDGDGFEDCACEDEAEAEFDFDFDADCCACFEFCFEFCBBHCCFEEDHDFGEGAFCFCACABABCGDEDAHEDDDDGDGFHDHDABFCFDFAHEEBEBEHEAA,False +899,3.0,3.0,2.0,3.0,3.0,3.0,8.0,3.0,BCEFGHGHGAGBGBGDFDCHEGEFAADG,False +900,16.0,24.0,17.0,15.0,11.0,13.0,13.0,18.0,DDCDADAECDHHHCHADDHCHCBCADAECGHGEAHFHGBBHDADAEHHFHGACACFCFBEBEDCGCGBBBBGEFFHFBBGCGBABABAHFEFBBECCHGFDFBFAFAHBBEBEACDGDGCBHBGBDB,False +901,25.0,30.0,29.0,16.0,34.0,19.0,24.0,19.0,FFGCECEBBBCDCBFEEEECGCABAFEFGHBDAACECGHDFCHBFBGGGBGHCHCBCECBGBEFDHBHBHCHAHAGABABGEGFCFBEGEBBCBCDHHHCHCHDBDCFCAEDHGAGEBEGEBEDEFFDBDEFBCEFEAGGFGEGFBFHHACACAEAEAEBEHEBAGAEAECGABADDDAECECFAAEDDAGCECBG,False +902,24.0,23.0,19.0,24.0,26.0,27.0,19.0,14.0,FAAAEACAEEEGEDAHEBADAGGHEDCABGFFDFDFEBEBEDEDGAHFDGBCBFDFGECFBFGFBFEFCFEDADBEFEFACACACAHADBBBEHAHBGBFAGBEEGGFGCGCFAFDFEBHGCAAGDGFHFCFCHCDCBFBGBCBEHFHCHCBEDGDACAEBDBHFHEDDDDDEAED,False +903,29.0,29.0,25.0,18.0,19.0,26.0,26.0,24.0,GABBEDADAGFHBHFHGCBCBDADGBGDGHEDBGBGDAEBEAGFGACEBEDADFFFBBBCFCGAFAHEHEHGBAAAAAAGGCCHBGBABHEEFHFHAHFBGCHDHFEBEGEAEDFGCHBHACADBHGDGCEDFFHFEFBCBABAHAEAGGFFCFAHADGDGCBCBCGCGCBCBCFHEHDFFEFHFCFABCHCDCAC,False +904,6.0,3.0,10.0,6.0,5.0,4.0,4.0,1.0,ACGCFCACDCHCDDDEDCGGEFBCBCBFGFEEAEDCAAA,True +905,3.0,18.0,9.0,11.0,14.0,16.0,4.0,13.0,DCFBBCBEBDBFFEFDCGHBHGDCFBFDEHEFBHBFEFHFHFGCAEHFAFBEHEHEHCACHGFDCBEFEHEBDBDBHBDEDEDBCBFB,True +906,16.0,25.0,37.0,22.0,24.0,10.0,28.0,28.0,DFDCDCEAEHCHEACBHBGBHCCGCECADDDDDDCHHHAHCCCGDECECEBECHCFCFBHBACGCBABCBHGEBBBHGHGBCBCDEEAAGAGDHFCCEDEDGDGDGBGHHDFFGEEBFAGHGFCBBGEHHBCBDBABCEAGACACGBEHEHCFDHAHEGGGHGHGACEDECHCGCGCDHFHBEGEDBCGC,False +907,25.0,18.0,28.0,21.0,19.0,32.0,30.0,20.0,GCGCEBHGCGCEDDHHGCCCCGHGHDHEHACGGGBGFGBEACGHGCFDFDCCCHCFDFAFAEAGABACAGACEBHBFGFBFBDHCFAFGFACAGDEHCDBGHAHBBDFDFCFAEBDCGFAHGHGFGFGBADFEFHBDADABBEAFHDDFDFGBGDEDEFAFEFEFGFAFDFEFCACHFHBEEECGCGCAAEAC,False +908,28.0,27.0,16.0,15.0,23.0,29.0,25.0,24.0,FAFEFGFBABHFFBHDCCGAABEBCACAEFFCFAGAEEGEGFGFDFHFHBAGFGBGDHBHBHBCGEGFAAHAHAHAEGEBEAHABCBDFGFGEGBFBHBDBFBFGFGHGHBEBEBDGHGFAFCHADEEECECFBACCBCDDHGGEHEGCAAFAFBDHHHDHDFDADGFAAEAFABEECGHHDBEACB,False +909,22.0,23.0,20.0,21.0,31.0,23.0,29.0,28.0,EAGGGDCHHHHCDDEDBCHAEDGBGAGADBHAFFHGBGBDEGEGHGAGDBEGAGCCHFHFGEGHHEAEBDDDDADHCBBBCACFCGAGECEAEFEGEDDAAEFEHBHBGBFCFCHGBBDBFBFDEAEAEFCDDEGFGFCECAGHGFGFEHHDAFHFHGHGHFHFEEEHAFBBBEAECGCBCBCEEAHACBFDFEHEH,False +910,35.0,20.0,17.0,22.0,15.0,17.0,23.0,20.0,BABABADGDFFFFFADHEEAEHCBGBGDGEGCACHEFAAHAHAHBHGHBABCBCGCFDFAFCFCEAEHEDGFGBAAADBGADADBDBECGGFCBDBHCAADAHAGADCGFGFGCGCEDAAEAHDEDBAGFGBADDDCDHHHCHAHDEAHGFAEAFBDHAGAEHBBGCGA,False +911,20.0,22.0,16.0,16.0,19.0,34.0,24.0,21.0,HHBBFFAHAHEFAFCDBDBDGCEEBFBDCCBCHDFAFDBDBFCFAHGEDBGFFFDFHACEDGDBFBFCECHCHBFAFADAFFFFFFFGFBHGHGHGHAFABACHCFGGGAFHFHGGGGFAFEEGHGEEEGECDGECBCBHDGDGHEHDBAGEBEAEABABFEGACHEBGFAF,False +912,14.0,22.0,22.0,16.0,10.0,16.0,13.0,11.0,GABHDHAHACDCBFFFECHFHEBEGABCEHEBBFBACHCHCACABEFFDBACDHFADAFBFBGGCGCGCHFBFCGDFAFGBCBCBDHDGDCBCBCGDGCGAGABCBCACEDFDEEFBBDDDEDB,False +913,20.0,27.0,29.0,23.0,22.0,31.0,29.0,18.0,GFGEECFDFAGEFHFACDEGCGCGHGHDHDCGCFDBAGAGAGDGHFDFBFGFGAGHDAGAFABDCFFECECEFFDCDCBCGDBABFFHFDDDGACHHDBEBEBFCEEBEHAHECBABGGAGDHDCEEGFCFBDECACAFHFAFACBEAGGGBGBCBHFCFCFCFCHDFAEBBBHBEBECFCHEEGBGBFCDBDBDBHGC,False +914,12.0,9.0,6.0,2.0,6.0,6.0,2.0,13.0,BFBHEHEHBADCHBAGFHFEBHAAACABHBHAAACECBBACGCHFHAHAHEHEFFD,True +915,10.0,12.0,24.0,13.0,16.0,14.0,13.0,16.0,CEBDBDBDCDCDCDBDAHHBFBFCFGFGEDFHCBCFGECFCEBEBHBCCFCFDFEHAFBHAHAHFCACHCECEHACBCHCFEDEAGACDCHCGAHCDEGGHEEFHAGGGECEGEHDGG,False +916,4.0,4.0,9.0,4.0,6.0,12.0,3.0,4.0,CECDADFBACFCFDFBFGFCFGHCCGBEHEHEHEFFCACBEFFFAD,True +917,15.0,18.0,12.0,11.0,16.0,11.0,18.0,15.0,AEAEAEAEAHAHAGEEFHGHBHBEDABABADHGFGDHBCDDFHGBEFFFAFGGHBDFCBEHECECGFHBHEEGDBEGEBBGDCDHDCACGFGHGCABABHFACCCCBGBGBGDGBE,False +918,14.0,16.0,12.0,30.0,16.0,18.0,12.0,16.0,DHDAEBFADADADADADGDFAFHFHDEFGBGBGBGFHCGEHECEAACACGCDDDFEBEBHBFAFHCDDDDFCFDFGHCFDHEFEFDCHBBBHAEDEDBAAHCEFDCDBDFDBEEDBDHEBDHDGFHDHEGGGCB,False +919,5.0,11.0,3.0,9.0,10.0,8.0,8.0,5.0,BFBHEEEBCBHEHGAGAGDDBDEEEHABFCFBAGDCDGDBDGAFEFEFDBDGGFBFBHE,False +920,5.0,0.0,5.0,4.0,1.0,1.0,4.0,2.0,CGAAFADHDCACGCECGDGDHA,True +921,24.0,17.0,18.0,26.0,23.0,31.0,24.0,25.0,EDEDCDADFGBABAGGFCFDFEGCGBHHECEADGDEDFDFDBEGEFCAGFEFEFDHEADHCHAHFHFHEGEDDDDBGEGEFBCDCEAAHDBAGHDHFGGHEHAHAHAHFHFDFBGBHCGAGFEFEFADACAFEBGCCDBEBADAFBGCFAFCHCHAFEFGCGBGCAFABCDAFBFBHDHFHEGDGHFH,False +922,12.0,3.0,17.0,8.0,6.0,8.0,19.0,16.0,GDFCHCHAADGBHCHAFEHCHCBGBCHFACAFADGGGGGGCGCAADHEHECEAEDDCCEGFGFGAGAHHGHGCDADCCHHGCGFHFHGC,True +923,13.0,7.0,15.0,17.0,15.0,11.0,14.0,5.0,GDDDHCCBCDADAEABADADGHFDCCACAEAGGDEEEDFHFBDGCHBFBFDGGBCDDDFCFCFEEGCFEFADADACAGGGGEGCCAEBEHEGEFECE,False +924,19.0,22.0,14.0,20.0,28.0,12.0,19.0,18.0,CGCDHBFBHGEBEADBDGDGDCBCDCHCEBHGEGEHEGDFFCEAEDGCGEGFDEEEEEBABCBCBCBCBGFDFAEAFDHDHEHFDAAHHHHEAEADAFEFEDBABDHEFEAGCBBFHDHBHBGBADHEEDBDEGBAEAGGCGHBEGGAAAEA,False +925,20.0,23.0,18.0,19.0,19.0,27.0,21.0,22.0,FEHEHEGDGCBDBHBEBCAGACHFEFHAHADAFGBGFFEGECEHDGDAHAHEDCCEAGFDFEGCCBGBFBFHDADCBCBFBCCHBHAHBDCECDFHFGFADCFFFFBFADBGGHADFDBBCBGHHHEHEHBAEAEFGBHBHGAGEFEFGFGFDCDFBFACAGAEADGDB,False +926,8.0,4.0,5.0,5.0,6.0,5.0,4.0,8.0,FGFDECECEADFBFBHEHAHADAHAEACGDADHHHBHFACBEGCG,False +927,4.0,9.0,2.0,4.0,9.0,4.0,11.0,2.0,GHGBGDGBGBEAGFGBBBBDDEBGFGEGEDECEAEAGBFCEHFAE,True +928,19.0,13.0,20.0,26.0,25.0,21.0,11.0,20.0,DDDFAGCFCHADFCCECECFBEHDBEBEDEHEHCFAEAEAEFDFBFADAEAEAEADHDFDFGBGBADEDBHCGCFCBEEAEHECFHAGACCCDDEDHHHHAHDDDACGHBACFCFGDEFEBHFHFCDDDHDACECBDHGHEEFGBGFGFEDHFBA,False +929,31.0,26.0,25.0,22.0,30.0,19.0,16.0,16.0,GADBEEEAEAHACCCCFGFEHBGBGCFCFDDADGBAAAFEFAABEHADFDFACAHBHGEFBAAACFCGABEGFABGFGEGFBFBEBFDEDEHGFEECHAHADADADCHEHEBEDABHBEACADBDBDGDGDCDCACHEHGCEHDCEABCFAEDFDGCEBFBAAEHEDEBCBCBCBCBEEAEBCHC,False +930,5.0,6.0,16.0,9.0,2.0,8.0,6.0,8.0,FCFCBBGDGDBABHCHCGEBEDDGACFCFCFCHCGCABHCCCCHFHCAGFHHCAFDDDDD,True +931,13.0,10.0,13.0,5.0,17.0,8.0,8.0,11.0,AEAEAHAEECBHBHGHAEBFCEEAEBEGCHBFBGEGFACADAEGEDBFCCHHBHBHFHCGEGHDDCDCACAEAFBCGCFEFECEA,False +932,13.0,15.0,7.0,16.0,20.0,10.0,5.0,18.0,AEABBCHEBEHEFEDEAFBHBADFHHDBDEHBABABABACDCFEFHFEGGACEDEHEBBAFGHCEDEDBGCHHDBDBEHCHDADGDEDEDHFEEEAHAHFHFHD,False +933,4.0,6.0,3.0,4.0,2.0,6.0,4.0,5.0,AGAGAHBEEDCGBGBCBDFDFDHHAFBFHFCBHF,False +934,5.0,12.0,3.0,2.0,5.0,4.0,9.0,11.0,CEDBABACFFGFAEAGCGBGHGHBHGHEBBHBHGDFHHHHBEBEAGBBBGH,True +935,8.0,6.0,1.0,11.0,7.0,1.0,14.0,7.0,GEBHGHGDBAEEDAGGEGDGBGBHHHHDDAAAAGDGDGDADABCEGEHEDDFGGB,True +936,12.0,13.0,17.0,16.0,15.0,22.0,16.0,19.0,HHEDDDDGDGAFACACHCFEEECACADBGHGFFFFFFEHEHCAGBDFEFDFEFEHEFFBBABFCHEGFGDHBCBCBEEAHCCECDDBFBHCHFHFHDEDGGGDGBGHCBGAFDGDGCAHBCCHGHFHFAA,False +937,3.0,4.0,1.0,4.0,2.0,0.0,0.0,2.0,ADDEDEHBHBACADBB,True +938,5.0,10.0,7.0,7.0,2.0,7.0,13.0,13.0,FCGGGHHAFEFBFBGBABAEGGGGCFCFHBABHHDHDHFHACDBBGHGDGDHCBDHCHGBGDHC,True +939,0.0,2.0,2.0,0.0,2.0,1.0,2.0,1.0,CGEGEBFBHC,True +940,15.0,12.0,17.0,12.0,18.0,16.0,21.0,10.0,DADACBCEGEGCCAHFCDCDAEACDCFGDAEBEBEACABEGGGABACDFDCGGFDDHCGFGEGBCBDEDGHGFEFBFGGCBCEEFAFGFHFAFHGHGCEFEBHBHGEGEGEFAFAHACBHE,False +941,21.0,9.0,18.0,19.0,23.0,21.0,20.0,26.0,EGEDHBHBHGHGHCEAAGBHBDDDGGGDGFGFEFGFGADHEFEAEAFAHAEAHBFECDCAAGDFAFHEHCCDCEFHFHFAEAHACFCFCHCECEHDDGDHDHDADEBHFEGAAEAFBHCCEGGDEDBCHADAHFBFCFCGGEDECFHGAGHECEHFH,False +942,23.0,23.0,25.0,23.0,16.0,18.0,18.0,24.0,CAHDBDHDEGCADHGHGHGHFCDCHCDFGEDEDHDHBHFDFEEADAEABFFGFGACFBBCFCBBFAHCHCEEDCCFHACACABHBFFFDFECACHHEGDGDEDBHBCBHBHADABHBHBCGHACBCBEBABCGEEFEAEAGGCDDDDAGAGAHBHDGBCFGFDCAGACAB,False +943,9.0,5.0,6.0,3.0,2.0,3.0,4.0,6.0,DBDHCFFHCEAEGBGBGAHCHBBAGFCAHAHACADACA,True +944,1.0,5.0,5.0,2.0,2.0,3.0,5.0,5.0,EGGDGHCBBAEGHGCFCFBHBHBHCFCD,True +945,23.0,12.0,17.0,23.0,21.0,25.0,31.0,23.0,AHAHBHBHCHCEDDFCACDCDFGFBHBCCGFGHGAAHDEEGECFAHAHFHDHEADFGCGCGFGEADBEAEBEDDBCBHAAFAFAFDGDHABAEHDHGEEEHDADGFGHGFEFGFCFAFHFEFADGGEGEGECFDHCHDFGHGDGCAAGAGEGFDBGCEBGBGDEDHFFCFGAGDG,False +946,7.0,6.0,9.0,5.0,3.0,13.0,9.0,7.0,BEBECFHFHAHGCAABCCFGBGFFCFGFBFDFGGAGHGFFFFDBCGHHCHCDDADAEAC,False +947,12.0,14.0,22.0,9.0,8.0,15.0,19.0,16.0,GGGGGADFDBBBCHGACAHBFGHGHGFGCCFDACHGHEFFBCBGEGDGFHHHBHDGDCCCCGBFHACACECDCFGBHBHBCEFECHCBCBCHGFGDAAAADAEEFCFCACFFEHB,False +948,23.0,29.0,24.0,18.0,9.0,25.0,25.0,32.0,BBBHGFAEAEBEBCFCFAFAFCFDFBHBGCHFAEGDACAGBHCHFDBCBGGCCBBHHABDCFGHBDCDBDGFBCAFAHHGHFHEHACEGDABGBGHABABGHHHFBFCFHFABAEAGACBCFHHBABCBCBCACFCHGHCHBGBHDDFGAAFFFEDDDGDHDHGHGHGHDHGHGHDCDCGFGFEA,False +949,7.0,6.0,5.0,7.0,7.0,6.0,6.0,12.0,HHCHADDCGBGFFHDHBBCHCHBFADAEAGAFAEAHBHEEEEHHHBGDGEGCDFDF,False +950,24.0,23.0,22.0,11.0,20.0,30.0,30.0,14.0,EHFBFBFBCCFCAAACEGBFAEEBHCHFHEAEAGBGHGHGCGCFEFAFBEAGAEBGDGCGHGHBBGBGBFBFDFECAGGFEBEGCAEBEDGHAFBHBFBDGDGFGDACCGCECACAGFCECHDFBCGCGFFFGFGCBCGABADFBHGGFGDHDEFBHCAAAAAAFFFFFDEEAE,False +951,16.0,19.0,15.0,15.0,20.0,28.0,15.0,17.0,DGGFECEHGHFHCBCEHGDGCBCGCEEFAFAFAHEHFAABHEGDGAGBGEEBHDHBBCBCHFBDBDBHEDFCAEAFFFDFDFAGBCBDECFFFEFDFBFGFGEECECEFEFEDHGCDAHAEABBDGFBFHHBHDAFHFCFAFABA,False +952,9.0,0.0,6.0,3.0,8.0,5.0,2.0,3.0,EFACCCFAAAAHFFFDGAAEAEHGHECECEDECEAD,True +953,2.0,1.0,1.0,1.0,6.0,2.0,3.0,1.0,ECEHDAAGBGEEEEFGF,True +954,11.0,9.0,7.0,13.0,13.0,4.0,8.0,8.0,CADHDHDFDABBEACAFDBBHFHGAGECBGEGEGEBEHEDEAHBGDADADADFDEBEDDCAABHEHCGEGECC,False +955,17.0,19.0,17.0,18.0,12.0,19.0,16.0,32.0,GFGFAAGFGAHADGGHGEBABFEDBHBDFHHHHBGBHDHDEAACBFBFBEAEHCDDGDFHHEDGHGBGBGADHFHDHCCGAEACDCDCAHAHFHFHFHDBDADHCCCHBACACBHFHFEFECACGEBBFDHCHDHBHEFGCECHFFBHBH,False +956,21.0,23.0,17.0,24.0,20.0,16.0,15.0,22.0,DADEHFHDCBCBCAHGBGFDFDGBAFDFDHHFDBDBACACFEHEAEAHAEEBAGCHCFCFAHAGDGDADADHHGHGECCFCFGFCHAHGDGBCCHADBDEAHGCFBHBHBHEEEEEHEBEAEGDBBFBHHCDCEBBBDBDBAADGFABADFEEGEDDB,False +957,10.0,10.0,8.0,10.0,12.0,10.0,10.0,2.0,FGFBFDFCGGFGABBBDGAAAFHFDGDBDGDEDECECECECGBAEHECGDACEBGBDFCAEAFFEDEBABAE,False +958,23.0,37.0,29.0,27.0,20.0,20.0,23.0,19.0,ADBDBAFABHBADGGCCCHFHGBBDDCACACBBAGDHDHCHFECBHFEGEBEDCCFEDEFBFBCBCBHEHBGDCDGBGAGAFFGCGEGAADACADBGFEDGBGFDBHBCAHEEFFDCDADBDBACDCDCDBHBHFEFHFDBGBGEFHFHBACECEDEBCBCBCGCGBBACAGEFBFBABGDGDHEHEGBCDCBHEAAA,False +959,12.0,18.0,18.0,8.0,12.0,10.0,17.0,15.0,BEBEBGBGBHBCBCECGCGCDCFGGHGBCHEACCCEFGAAAEHBHEHBGBHAEABHGFCFCDCEABACAHEHCGCHFEAEGDBDHDCGFDCDAHBHGFDFGGGHFBBBAF,False +960,6.0,8.0,14.0,11.0,10.0,8.0,6.0,15.0,EADADHGFDEEHFHDHBHBHCECDFDBDECHFFAFGFBEDECBCECHHHHGCGDGDHCCCCCCEEDHHAHABCGFABB,False +961,20.0,29.0,25.0,20.0,25.0,26.0,26.0,18.0,BHBEFEABGFAEGDGDFFBDHDGBGBFFFHEEEEEDFAFADABGGCGCBCBAFCFABCCHEHGDDEDEGFFAAEEEEAGCGAGHGFDCCBCHGACACEDHGHGAFBFBFAHEBEBEDGBHCCEAEADDDHDCBCFHAHCHBHBFBFBGGGBHECGFGECBCBCDHDBBFDCACACBFGFGEGCDEBFBF,False +962,27.0,19.0,27.0,18.0,20.0,32.0,29.0,28.0,GEGECAFAHHHHEAEBDBDCHHGHFEFHDBFAFBFDGDBCBCGHGHFCFCFCFDEGADHHCCADADAGEHEHGACCHGHBHEHCHCHFECGCFAFBFAFGFBCAEFCDHAGFBFHGEGAAHGFGEDEACDCFHDDCDCFCHCGCEDGHBDAAFAGBFBFHEGAFACADEFEBEGGGCGCBBFBFGAGAGAFABAGFBEHF,False +963,18.0,20.0,27.0,19.0,14.0,17.0,15.0,25.0,FFACCGCGCDDHCHCDGGGEHFBCBHFCAAAAHAGFGDGAGDGHFBDEDHCBCACACGCGAFEBBCECEAEHEHBBCHHHHAACDCDBDFCFBFBHCHBHDGCEEEHEDGBBBFEFHFHDCDBDADAHFBCBABDCEAHHDACFCGHBHFHDCFE,False +964,12.0,10.0,8.0,9.0,12.0,10.0,10.0,9.0,FGFAEAEAGADFEECEHBBBAHAEBECECAGGHBAAGEHFHDHAEFDFECDCBFBFBABDDFDGGFGCCCEHAHBHGDGD,False +965,17.0,22.0,24.0,31.0,26.0,22.0,22.0,27.0,CGCEHFCFCEBDBDBEHEHGHGHFABABHEHFBEBGHDHDFCBDBEBGGCHCFDFHEHDHDGDFFBCAHAHGEEFHBHBEBADFFAFAHDHGAGAHEDDHDEBEFEBEFHFHACADDDFDEEEECCCDAGADBGAGFEHBGGHDCCCDEDGHCECDDABFBEBCGEGCGCFCDCAAEDCBGHGDFDGDCDF,False +966,27.0,18.0,26.0,14.0,26.0,27.0,37.0,24.0,AACDCHCFGHAHAGAGACFHEHABFHFAGHBCBDBFBFBABFHHHFHFCEDEFACHCECFGFEFECGDGHGCGFGEHECDCBCBGBECEDFAEECAGGFAFBHEFDGBGEGHFEEGEHCGEGDGDGDFCCCCHBAEACHGHGAGHGAGEHEGEGBCAGGGFABHDADADAGAFHBEDCFAEECFGFGFGCGABEFGABA,False +967,19.0,30.0,23.0,20.0,26.0,19.0,25.0,21.0,BBABCBGGAGFDFGHDHEGBGCGBBAFDCBCEFHDCDFBCBGEFBHBEEEEEBADAHAHBGGGEDBFBHCCCECBGHDHDFGBDCDFBEHECGBGBGFCFAHEHDGEGEFDFDECCCHCHEGEGHGBCEAGABEBABABABADADABAEADCCEFBABFECDFHFHCHFEFCGGEHEHGDADH,False +968,22.0,15.0,29.0,26.0,37.0,20.0,22.0,24.0,AEGBABEFGGEGDHDHAHEFECEFACEEACHBECFBABCDCACAHGHDEEFECECDAAAEHGHGHDHDFGFHCADFDBDEDEAEDEDEDEDGGECEABBGFADADEHGHFECBCAEAEGECECAGDBEGAACCCCCCBHEGECDCDFHFHFHFHFCGEGHBDFEBBBGECHDEFEHHGDADCGHGDDCEFHFCFC,False +969,16.0,6.0,14.0,15.0,9.0,8.0,13.0,13.0,HHHHFEFDDCAHGGEGDGDCBBHCCDADGGHAAADADFDFDGDGDGABEBAFABECDHAAFAFEFGDGCHEHCDCGCEEHHHAEACCCCBCGAA,False +970,21.0,25.0,9.0,17.0,8.0,13.0,18.0,16.0,GBGHGACACAFHFBCADGGGFGFGAGAGBBDBGCHHEHEBFDEABGDGDGBHBCDFFFFHFHAHBDACAHDHCCGAEADBHBDFABABABEBEAECGGBHBHDFBBBBAFDDAGBHHABDDADADBE,False +971,9.0,10.0,11.0,9.0,15.0,9.0,14.0,12.0,EAEDFCFBFBAGHGHGDGBHBGFHEHCFAFAGHECGCHCADAHCEGDGCGBBBBDBDEGFGCCFHEEEHEDEAEDBCGHGCADHEFEAE,False +972,18.0,16.0,12.0,13.0,15.0,19.0,12.0,21.0,BEHFBBABAHGEEAEAFAFCDEHFHAHCGCFBEAAFGCABHHFHFHCHBGADCDHDHCHCEEAGBFDFGADFFFFBFBGDGAGAEADHDHDAEEEBCBCBHBDEEHGFGFBFBDEHCHGHAHFCAD,False +973,27.0,25.0,26.0,28.0,24.0,17.0,20.0,27.0,HCHEFEACGCFDFGCBCHADFCFBADCGHBHCDDDCBAAHAEEDADGDGHGHGHGDAAEBEHAHGDADADEBEHHCEBADAHHHHCHCAAAHBFBDCGBFCHEEFBFBFHAEADDBFBFBDGDEHEHBHGCGAHACECAFBFBEEEBECEFDCCABDBDEDEGAGADEDEDCFBBACHGGFGBGCGDADCHCBC,False +974,2.0,9.0,5.0,14.0,10.0,16.0,13.0,8.0,HBEGFBDBDHEEFHFEGDBFBFBGHFAFDFGFCFDBDBDHDHBGGCFFEGEGECADGFECEHFGDCDHDEDGFGFGD,True +975,7.0,10.0,11.0,8.0,6.0,8.0,11.0,11.0,CECFCDCHGGGGHGAFCECEAECDCGHHBADHDHDBDBFBFDAHGBBBBBBGCFFFAAEHDFCHGAGHCHGE,False +976,22.0,16.0,20.0,24.0,18.0,27.0,21.0,14.0,GDBDHEGEBFHFHDDCFCDAAGEFBFEDBAHGBGBGDFEBBADGHGFABAFAFDCDCBCAHADDDCAHECCDAAFAFGHCCECFGECECEFDHCHAHGBGBGDECECECEAEAEBFBFGHGHAADDFDBDGAFCFBHACAEEFGFAFDFDFGFGDCDGGFFF,False +977,16.0,17.0,23.0,22.0,27.0,15.0,19.0,22.0,EEGGFDFHCHEEAEDEHEHGCEFGBEBEBHBDDCBAHAHDGDAEGEGDHFECBDDDHDCGCFAAAAAFCEHBBEECEFDFDBDBCCCCEFEGAFFCFCFCEBEAHAHAHAGGHGHCHCBGEDBDGEEHCDGHBCBDAHFHBHFGGDHDEDAGECECBCDCG,False +978,5.0,8.0,11.0,18.0,14.0,13.0,11.0,18.0,HFHDBAGHGEFEHCGGEGDAAFHFEFEFDHDGCECHHEHEDEDHGHDFBFCDHHHAHEHBCBCBCDCDGDECEDGDEBFGDCDEBGHFBFDCDFHFDA,False +979,22.0,10.0,19.0,14.0,19.0,26.0,19.0,18.0,HBGDGHGCGBGEFEAEFBDEHEAAHGGGGHDHDHFGEABAFAHEHCACFFDFDFAFECGCDCDCDCFCHCFCHAHFDCBGAGDEHBGEAFAHAHEFAGHEAGACEEEFFFFEFHFBFCFBACGCAFAFCBEFEGEFCGBDDDCAAAH,False +980,9.0,10.0,16.0,13.0,13.0,13.0,17.0,6.0,CDCEBDGFGFACEBDHFCEHACADBDBHBCBGACCECEFEFGFGACHCACDEEGGGEGEGDGCFFFGFDBDFGGAGAHACDDDDGEGFCFCEHBBEB,False +981,19.0,23.0,15.0,12.0,16.0,18.0,17.0,17.0,ECEDHFHFHFAGAHBHDAEFGFBEHGBGBCBHBCEDGDCBHEAGADEGHFHDBBABEBAGAGCCDADHDCGBBBEGAGAGEBBBGFGFCCBFBFEGHAEGHFCFCFCACEDHDAAAAAHDBFFHFEFCBCBEBEFHA,False +982,21.0,16.0,13.0,14.0,20.0,12.0,19.0,12.0,EBEBGBGDGEGECHCHFAAEHBCAEBHBECECACGCDCDCDBABAFABGHGHAAEAHABDEDEFHFGBCDAEAGFGECDHGFGDDDEHAGGGEGBCFDFAFBEGECEHAFDFGABADAGAEBHFAEB,False +983,22.0,16.0,20.0,28.0,16.0,18.0,28.0,14.0,CGCGBDCDCGHACGFDFDGDBDCFEFEFADAECBDDDEAEAEAHAHABGDFAAGFGFGCAAGEDEGFDFDCGBGAGBGHHHGABCBDBDFDFCFDFGCAHAGACABAFEFAGEEDEHBCCHEGBBBDBDHGEDCHCEFAHHGCDHGGFGDGDGDBEGACDCD,False +984,26.0,22.0,19.0,22.0,24.0,27.0,32.0,24.0,ADHHEFAFADABADAFABCGCGAGFGFEDADABEFHFHGHDFGEGADCCFHHHGHGEFCFCEBDGEFEFEGAFBFBFAHGBEBEAGDFAHABAEGHGCECEHBHBDCFFHBAAGAEAGBCCDCDHDHDBDBGBEDDDCBBFBGEDFDHGEGEGEAFAGGBGBHEGBGFGDECHFAFEHHFCGCGEGCCHCHAAFDG,False +985,7.0,9.0,7.0,9.0,13.0,11.0,7.0,5.0,FCBCHEDFAFHEGBGFAEAEAEAFGDGDBDBABAFGEGDCHCHEEBFCEEHEBEDEFFDFGBDBCCFD,False +986,8.0,13.0,17.0,13.0,13.0,11.0,14.0,10.0,HGEDFDFDFDHDHDHDBFEFAGAEBEDGDHHFBBEEABBBFBHGHCCBCEEGECFBACDCDAAGCFCGBGFFEAGDGHCCDGEGCGCGCHCECBCACEB,False +987,20.0,12.0,18.0,25.0,18.0,18.0,21.0,30.0,AAADFHFAADFECBCECEHEHADCDGDGDCFHFHGCGCGFGFCFHDCAHEEGDGCECHCHEBFBHGHGEFHBHFGDADEDHDAFADEHBBBEGEFHADFDBCGDHHGHGHGDGDHDGDFCFEGGFGCAAEAEBHAHADBHEAADHDCECHDADHCHBHFHAB,False +988,20.0,13.0,12.0,16.0,10.0,14.0,25.0,12.0,BBBCHGHGAGFGHGDCACHCHCAAAAAAEHBDBAFDGDGDFCGGEBAFDEDEHEDGDEDADABCBFDGAGAGHGAEDBGGGGDGBFBHAAGBGHDFEFGAEECCGFFBFGFGHCHAFFCACD,False +989,12.0,14.0,12.0,10.0,10.0,5.0,11.0,8.0,AEFEBABAHACGFBABGBGDEDGDEBBCBCHCECBCACDCGHGHGEACFCBBBEFGDDDCDBDADGEHAACHEGAGFBEHAH,False +990,22.0,22.0,18.0,21.0,13.0,23.0,11.0,18.0,AHAHEFFDDCDFGHDFDECHDHABEBCBCEAFBGGGGFCHCBCHHBEDFAFABCHCBCBCBABDDGHHDBFGEEDADFECGBAECEADADADAFFDFBFBFBFAHDFDBHBDEAEFHFGAHAHAHACCBBABGCGCFHFAFDFDEBCA,False +991,10.0,6.0,7.0,9.0,6.0,4.0,5.0,5.0,FDCBCGFHFHBBBABGDFDAGACACEEECAHDDGDEAAADADAECECHDBGH,False +992,9.0,13.0,4.0,15.0,7.0,15.0,17.0,13.0,DEAHFHGHBEGEBBGFFFAFDFDHDGDGHGHFHFDDDCEGBACGDBDGDEHEHGHGBGBGHFBABABFFFAGADHDGGGHFACBFEDDBCAFB,False +993,1.0,1.0,4.0,3.0,4.0,6.0,1.0,3.0,EFEFEFAFCEGDFHHHDFCBCDC,True +994,16.0,14.0,21.0,15.0,11.0,19.0,16.0,24.0,AHACCCDCAAFBFEFBDBAAGAHHCHDHEHAHEHEBGAGAFHFCGCEFEFEDACHCHCGGGFDFCHCDDDHDHAECHGBGBEHCFBDBGGFHFGBAFHFCDADCFCBCBCEHAHFHBCEGGGFAHBHDCDFHFGDB,False +995,7.0,6.0,13.0,6.0,12.0,13.0,4.0,9.0,CEAFHCHFHECCHEACFCFGGAGFCHCHFAFEDHHCECFBDBDGECHDFEEEEEEBABACFCFDFDFBAB,True +996,4.0,9.0,13.0,8.0,5.0,3.0,3.0,5.0,AGAEADDCACBCBCDCDEHECCFHEDBCBCDDDFEBHBHCCCBBFHGCGB,True +997,3.0,1.0,1.0,6.0,4.0,5.0,7.0,3.0,DDDFHEHCGFGFGFGEDAGAEHFDEDBGAG,True +998,18.0,17.0,15.0,15.0,11.0,15.0,12.0,20.0,EBCFCHHAACHCHCHGBCBCBCHDADAFAFEFDFDGHGHCBCFFHCACDFAFAHAEAEAEFEBCHAFBHBFGAEDBDHDHFBCDEAGABBHGADDBDBDHHHEBAGCEEHFHBGGDGFGAGDB,False +999,6.0,13.0,8.0,13.0,6.0,19.0,12.0,12.0,GDGCGCHCAFGFEFBFDEDHFBFBDBGFDADBFBACGBGDGEFBHHHHBDAFGFGBGHCFFECEFEFBAHFDFBFDAHCHDHCHDFDGB,False diff --git a/tests/results/nb_gm_002_2back_240trials.csv b/tests/results/nb_gm_002_2back_240trials.csv new file mode 100644 index 0000000..1c50201 --- /dev/null +++ b/tests/results/nb_gm_002_2back_240trials.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,ralph_skewed +0,30.0,39.0,31.0,30.0,32.0,24.0,27.0,27.0,False +1,33.0,23.0,27.0,32.0,37.0,34.0,25.0,29.0,False +2,31.0,20.0,37.0,28.0,31.0,32.0,26.0,35.0,False +3,27.0,32.0,39.0,24.0,25.0,34.0,35.0,24.0,False +4,34.0,24.0,38.0,28.0,31.0,29.0,28.0,28.0,False +5,29.0,24.0,36.0,31.0,32.0,32.0,31.0,25.0,False +6,25.0,38.0,28.0,30.0,33.0,30.0,26.0,30.0,False +7,27.0,30.0,30.0,29.0,32.0,26.0,33.0,33.0,False +8,24.0,36.0,32.0,23.0,30.0,29.0,35.0,31.0,False +9,35.0,34.0,30.0,29.0,35.0,26.0,23.0,28.0,False +10,30.0,25.0,33.0,31.0,27.0,37.0,30.0,27.0,False +11,28.0,28.0,29.0,26.0,28.0,27.0,34.0,40.0,False +12,35.0,27.0,30.0,29.0,26.0,30.0,36.0,27.0,False +13,38.0,27.0,31.0,27.0,34.0,23.0,27.0,33.0,False +14,29.0,30.0,28.0,35.0,19.0,30.0,37.0,32.0,False 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+19,10.0,14.0,15.0,8.0,25.0,14.0,11.0,20.0,EEEEBEEFHEHEEFEEGHEAFFAFHACGDCDDCFDCBDCBFFBCEAHEAHGCGGHGCHEEAEAHEAHEHHCCFGHABHGFGCHGCFDFHEHBBBDFBFBCEAEBHCDGCEEEHBBHB,False +20,16.0,9.0,19.0,17.0,10.0,22.0,10.0,24.0,HFGDDAFEAFEDCGHAADEHDBHAHDCGBAHBECEFFFFFEFEEDHEDCACEGHBGCFGAGGABDHFCHFCHCCDCFHHADFCFFCFFCBFCDHHHHDFFGHHDACDAFDACDCBHCHHAGHABHAB,False +21,6.0,10.0,3.0,4.0,7.0,3.0,3.0,4.0,EABBAEFHEFABAACHDCDDEFBEGHEGBDABHBBCBGEB,True +22,6.0,11.0,12.0,6.0,9.0,6.0,9.0,10.0,AEDBCDECBCHBCBBGFBGFHGEHACHAGAEFBDAECHCFHFDCCECGBCGECGAHGBHBHEBHDFGDE,False +23,11.0,8.0,12.0,13.0,7.0,5.0,13.0,9.0,EAAGACDACDHEEGGGGGBEGEABEAHGCHCCAFCFFGDHGDGCBGBDDEAFAADCDDCDDHBCGBCAFCBDDHHBHH,False +24,36.0,26.0,18.0,26.0,33.0,19.0,21.0,15.0,GBCHFHAAHAFFGBBEFBCFAEFDFGEGEEBECBEBBABBAEBEEAEEABGDBADBACFFBEFCECGACFADABCFDCDBCBBHDHHACGGEHDEGDEGAHAAFAAEDCCHHDDGDDBDGBDBDDCDAGAAFHEDHGDACDACDBGEEACGAEEBEHAFHBGAAAAAAAEEFBEDCDAEEEFGEGGHGFEAFED,False +25,11.0,17.0,16.0,9.0,15.0,15.0,6.0,9.0,CEEFABDBGDBFDFFDGADECBFCBCCACFABEABFABEGBEHBAHEAHEAECCFFCHDCBBBFGBAGCDFHHFBDFDCCHHEHAEBEGCCBFEECEF,False +26,8.0,5.0,15.0,9.0,10.0,7.0,11.0,5.0,ECAGCHDBBDCCDCGHBBEEFDHFEEEHBHGADADGFDEFGAFGAFCCCCCACCDCDGGECGECGEAGFA,False +27,9.0,11.0,8.0,5.0,8.0,4.0,2.0,4.0,FCAFDBEDBABAABAEEAEHDBHCEHCDBCFBABEEGECGBDABFCCAHCB,True +28,6.0,8.0,11.0,7.0,10.0,5.0,9.0,9.0,CFBCBCCBACBEHBEGCADHDGFEGFHGHDAFBAFBEDCDGCHGAACHCHBCEEEEDHEDGEGGH,False +29,24.0,16.0,18.0,25.0,13.0,19.0,26.0,18.0,HEFHCDEGDHFBACGGDEHDGHDGFDEAHFDHGBHEBGEGADFFGCCGDHFBFABDACDABAGFGDAGDAGCAFFAGHHCDHCHACEDDAFDCCDCAECAEDGEDGAFGFCGFAGBBGFBDBBAABAAGADGAFCHBEEGHBGCBFCGFAHHCHDBDDE,False +30,6.0,5.0,2.0,9.0,2.0,4.0,3.0,8.0,DADBAFBDFHDHHBAHEADGFBHFGHEAHDHBDGDCADC,True +31,19.0,18.0,16.0,13.0,19.0,13.0,14.0,15.0,FCHGCAEHAEBDEBABAABHAFEBDCBDCBHCGEAGEFBAFCCECCBCFHEHGEGAEDAECBECEAFEBDHBDEAGFGHDGCDGADFAHGCFCBFDEHEGCEABFADHAFHGBHABHBHDAEBGDFG,False +32,7.0,12.0,12.0,10.0,7.0,5.0,5.0,9.0,EBDGBGBBDCBACGHBDAAHEBGCBFHBFGAFEHFCCCHDCHDCHDAHDCDDEBDEAFECBAHBECC,False +33,1.0,4.0,8.0,1.0,4.0,4.0,5.0,3.0,GAECEGFBHFGHBGCBFCECCECCBCHDGF,True +34,5.0,4.0,6.0,9.0,13.0,13.0,5.0,7.0,CHHEFFDFFDFFDFDGGDFGDHCEAEAHEAFEBFCFEEFEECAECHCHFDEBDBGEGABDEH,True +35,3.0,2.0,3.0,3.0,5.0,4.0,0.0,6.0,CBDEEHHEAHCAEBDFADFHFCHFEH,True +36,13.0,2.0,13.0,8.0,7.0,6.0,16.0,9.0,DEGDECDHGAHGEDGEGACAFCADGACGACHFDACHCCHCEECGHDHBEGGGGCADCAFAGFGGBAGCAHFHFA,True +37,18.0,19.0,17.0,17.0,13.0,17.0,15.0,23.0,HBCABCGHCEEADEDCEDGAGFFFHDFADHHBHHGCHFHHAGHEHEBBBDEFECFEBHCDAADFGDFHDCDCCDCCFACAACHGGBGGBFBCFBFFCFGEDABDBBDAAGAABACBEGBAHAHHFGEDGHDHHEBHBHF,False +38,4.0,6.0,5.0,9.0,6.0,4.0,4.0,6.0,AGDAGHABHCEEFBEFDEHDBHDECDFCDBHDEGBBGCCADFDH,False +39,3.0,5.0,6.0,8.0,8.0,2.0,8.0,6.0,DCEDEEGEEGAAFEHFGHDGDBHDBGBBGECECDGHBGCDDCHCAH,False +40,0.0,0.0,1.0,3.0,1.0,3.0,5.0,1.0,GDGGDCEHFGFDGF,True +41,20.0,19.0,22.0,21.0,30.0,22.0,10.0,26.0,BADBABGCFGFDDDADEFHAAHAAHEAHBBHECFGFDEHDCDBBBHGEDEECCDCCDGCHHBGHCHACFDCFCFEDFEDAHHHBHAECABDABAAEHFEADCFEBFAGFGEABECFEFFECEEFEHFEHEEHDHDCHBBHBDHCEHCDHBDCFAEFAGHEGECBCFEEFE,False +42,3.0,7.0,4.0,4.0,5.0,2.0,5.0,3.0,EBBEAEEHDCHDCGDGGBACBEHBDGBAFBFCG,False +43,21.0,15.0,21.0,27.0,18.0,33.0,14.0,23.0,DDDDDDBCGFEFFABFDHDAGCEFHHACHGBHGBEFEHFEHFCFFCHDGHDFHDAGFECCCAAEAAGHGDFCHFCHBBBFABDEFDFFBBDBAAFDAFAGHACHACEFFEFDHABCAFGDFEDCGACFADFDDFBHFAFFBEHBEHFCHEADEGHEGCDGHDHDEECCFCCD,False +44,27.0,34.0,20.0,19.0,15.0,29.0,27.0,26.0,FGCFGADGADGDDBDBAFGAFDHHHAFBAEEAGGBDBFCEFAHFAHFAECDCBBCGBHAFHABHDCHAHHGBCGECFDCEHCFBCHBGHCABFBCFBEHBECBAHBGDECHFDFBDEAFBBGECGEBBHDBHDBEABEBFCDFHHFGHFAFFGCACFGDGGHGAABCDBHBGGBGGFHGHGGBEADABFABAAFAFF,False +45,15.0,12.0,15.0,7.0,7.0,15.0,11.0,5.0,CAFCDGCFACFCCFACGBBGCAEAEGAHFADBCHACHFCFBEFGEGBDGBDGBEGEHAEFGBFCDFBFBHACAFCAFGABDAFACDB,False +46,12.0,10.0,7.0,5.0,4.0,11.0,11.0,13.0,ECFFHGFGGFCGACGFGGAHFABBHDEDCHABFBHGAHGAHCAHDABDFHDFGCHGBEABAHEHBFHBFCBAA,False +47,15.0,6.0,13.0,11.0,17.0,21.0,13.0,9.0,EDCEFAEFAFFAGHCFCEEAFGFFHFDECECCEGCDGHDGHDGHACFFCFFCDFEHEEFEEGHEDAFBGEAAHAAGCABAEFAFDABGFCFHCDEDBABFGBGGD,False +48,11.0,17.0,17.0,9.0,17.0,17.0,13.0,15.0,GAFGHHGCHBCACCFBCFHHECHBHAFHEEGBAFCAGHGEFGEDGFCBBEBGABCFDCFDCFDBEEEGAAHDAEDFECBGCBHDBFEGHHBFGBFEBFCBCCHEFAEDAEDCEFHB,False +49,13.0,16.0,15.0,12.0,16.0,9.0,12.0,15.0,BGCBAEBCDBEDBECBDCBABDCDFCDBCEGDABDFFEHCEDGECHACHEBDECDGHFFHFHEAHAHHEFFBAGAGHCHCCHGCEEAAAAGEEGDEGBFGBAGBHHBH,False +50,13.0,6.0,16.0,14.0,12.0,13.0,9.0,12.0,DAEAAGAAGCHCCHDFHEFCCBEGFEGFHAHEAGBGCBFCBFCDACDAFDCHECEBFBAFCFFDEHAGHDEFDGCDECEHCHDGADEHHFADCDD,False +51,22.0,27.0,26.0,19.0,24.0,22.0,28.0,20.0,FDCGDAACFACHGCDGEBFCBDCBGBEGBEGAGGFGGCHGDHGDCAACHADHCFHAAEEBBCBCCBAEDAGBFGAFGEGGDGHCEEEDEHCBBCDECEBGEFCCHCFBCFBHFEABEBDEDHABHDBFFFCEFCEDHFFHBFABHAGGECAEADBGGEGAABHAGHAGEFGBFBFHHDHBEGBFCCDD,False 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+79,23.0,23.0,29.0,21.0,13.0,23.0,22.0,17.0,CDHBACEAHEFDEGHAGAAGFAHFADFCBBBEFBCDGFBCDBDHGGGGCGFBDBBCFBFDEGEEHEGGBGEHFCCFCBDCEDAEABFDHHBFBBCAGDDCHDCHDAHBACAGCAGCADDBDFHAFCAFCGHDEBGHBCHGCHFBEGBFACFCCACAADACFACFCCFGFDG,False +80,12.0,12.0,23.0,9.0,27.0,13.0,18.0,19.0,EGFECEECHEBEEHHFBDCGCAACFBCGEHEEGCEACEGDEADAGBAGBCDBFBHFHACHCDHCDHCECCEGFHGFBABCGDCBDCEACHBCGGAEEAECFEHHAFFEEFHFCEFCHGGGGDHBEHGGHEEHE,False +81,25.0,15.0,14.0,17.0,20.0,16.0,15.0,15.0,DGDFFBFFCAFHADGAEEAFDABDEGGEBGDGEDEBAHAAEGABAHCACEACAHBAGGECFCDDEDBEFHEBGAFCAFCAHDEHDAFAGFCDBCHCCHCEDBGFGHBADBHGBEAAHAAHAEFECFEDFEDHEBHGB,False +82,23.0,16.0,15.0,28.0,9.0,16.0,15.0,26.0,FAHGHHFHGDHGDHDHCCHFBHEDGDGADGBDFDHFBBEDBADEDDBDHFDACDBFGBFAHCDDDGDBGBBGAAADCHFCHCDGABFHDDHDAEDCEDCGDFEAAEACHHGHDGCFFCHABHAHHAFCFHAAHAACBABBHFEAGEAC,False +83,16.0,17.0,21.0,14.0,11.0,17.0,24.0,19.0,EGHCBBCBBHFAHAAGAFGHBCDFAGFBDABDADEEDBCDBCHBCBGEGFFGFGGCHGCGGHHADHDHCDHAFGACCEHDGHFFCDFEDAHDFFAFFHEGBDGCGCBECECHBGHGGHCGBCHBCEGFGGFCACAABAE,False +84,25.0,24.0,34.0,20.0,21.0,23.0,18.0,22.0,GCCGAFHHFBGFBCFBDFBGFCGDEGCAHEBCAFCBFHEFEDCGFCAFCHCHBCHEAHAFBAFDAHBHBDGAABAFBACACHHCFDAFDGBAHBEBBEDFCFECAEBGFHECCCCCCHHEEHAAFDGFDHBDGBEFBEDDHDDEBHECCECCEBAEBAGACGEDGADCBCCGGCDEAGCADCAFHHD,False +85,14.0,17.0,15.0,14.0,15.0,14.0,16.0,10.0,GGCGDDEBFFHGFBGFBHFHHEDAACAABGFFFCDBGBEHBEDBFDBCDCDGCDEFBCHBEGBEGBEFHGFBAEBCEFAAGGCHCCFCCBCHEHEAACADDEDDAGDAGEAEBAG,False +86,5.0,2.0,1.0,1.0,1.0,1.0,3.0,1.0,ADFAGGAHGBEABCA,True +87,28.0,33.0,23.0,19.0,20.0,25.0,30.0,22.0,FFGDBGHBGEGAADDHGEEDEHBBACDFCGFCGEHFBBFHBFBCCGCCFHDFCGHBECBAAFFDBBCBECGGFEGECCAGABBABHAEHBBHBHDEFDCHDBAFFDDFAAHAAHCDFCAHEAHGAHFAHAGHAGAAGEEDFGBEBECBGCBAFBGCCGAFAAFHAGGFGGBGGBDEEGEGBFGBFHBCHBDDBDDBECCA,False +88,27.0,30.0,28.0,20.0,23.0,12.0,23.0,29.0,EGBCBBCEBCHHGDBECBCDBEDGEHGAGACGEHGCDACFECFCBHBBFDAHCACBACBEFGGAGGADAAEBAHDFHDCDBAHCHHBHABGCBEEDHGHHGFHAHDAEDABDGCDECDBADBHHGHHGFGECBEABDHFDGAHEACFGCAGCABCHBFECHCBFCBFAEABDAGEHEEAECABDHBHHCEBG,False +89,14.0,15.0,7.0,17.0,10.0,11.0,15.0,9.0,CHBADFABGHBGFGGAGGADGDEBHADHGHGFDFDDCDBGAAGHAGFAEEBBEDBEBCEBFAFDAFDFGDEADEGDFACCCGBHBBHABHDEDCBDFE,False +90,5.0,3.0,3.0,1.0,8.0,0.0,6.0,3.0,CCACEGHEGDEGBBAHEHGBAGEAEEAEG,True +91,0.0,0.0,4.0,2.0,4.0,2.0,2.0,1.0,GDCFDCEECGEHFEC,True +92,14.0,4.0,7.0,10.0,8.0,6.0,12.0,5.0,DCDAEFAFCECEEAFEDFEGCCGACBDGHFAHBGEBGAGGAGGDGAEGHHGAADAFDADDCBAHDA,False +93,10.0,8.0,8.0,3.0,8.0,14.0,16.0,15.0,FAGFDGHDHHEHEEGGFFACFHEHACCACHFGHFGHCGCAGCGBCFFEGFGBHABHFDHGBGBHABHAFFAGFEHEEBBAGG,True +94,21.0,25.0,21.0,30.0,27.0,13.0,12.0,17.0,HHBEBCAACEABDGDGBDFBGFCAEHGDCADCHDCEDFEDCEDGDCEDAEGEHAADBBDAADHCDHDFHBEEBEEBCEGAECDEBBCGAHEBBFFHEBHEHDAHDAECFFDFEDFBDABDCCACEDEBDHDDAGFAEABECBHGFDDFEDCCBHCBHGBEGBACBA,False +95,4.0,6.0,6.0,8.0,7.0,6.0,6.0,9.0,EDGEBHEFHACBBCFEGHCHDAHDEHDBHDBDDEHFCGECGFGBFACFAHGD,False +96,8.0,5.0,5.0,6.0,5.0,8.0,12.0,12.0,AFACCAGAGGFBEHEGHECFDFFDGFHGAHGHHFDGAGCAGEFGHBBHEBHDDHDHHGCBA,False +97,20.0,25.0,21.0,20.0,27.0,26.0,25.0,26.0,BFCFGDFBECHDCEBGEFGBABHGDDGAFBEBCEFEEFGDAHFBHEHHCHDDHGEFDFFBGBBAEGCCFDDABEBBEBFHBHHBCCECEDCAFCGFGHFCBGHBEAFCBFDEEAEEAFECEBBGGAGHBDHFHHFHHFHHFHHEEHGCDABGABGACGAFGAGGDDEDDCADCFGAFGDCAHEAHEAEGC,False +98,4.0,3.0,1.0,1.0,6.0,1.0,5.0,3.0,BBAHAEDECGEAGBAGEEGHEGHF,True +99,21.0,17.0,15.0,21.0,17.0,23.0,10.0,21.0,AHDDHEDGFFGCFHDHAGHGHHDDFADFABHDBCCACAAHGDDFDDFGBHEBHBHEEHEFCFFBBDDBAABCEEHDACDHCEEAAEBHBFABFABCABFFFFDFFDFEEFCEHCEBDEBFCAGAGGDGCHBCHAAHEFFECAADH,False +100,21.0,17.0,13.0,22.0,21.0,22.0,21.0,31.0,GCAADDGBDEBDABDGDGGEADEDDFHHHEHDGHFGHFDHGAFAHEHDCHDHFEBGEACDACGABGABGFGGDGBHEEHEFFGHFABDHEDAECBFHAGHAHBAEAAEAFEHFEBGGBCFDFEEAHCHHCFDAFDCFDBFHBAHCHHFFGEHDECCGCBHFHHFBHBE,False +101,3.0,4.0,2.0,2.0,2.0,1.0,2.0,2.0,BCFBEABEABHADGCHGD,False +102,3.0,5.0,4.0,4.0,2.0,1.0,3.0,10.0,BGHBGHCCHCDHEHHABDFHDBHEGCDAHBAH,True +103,22.0,16.0,17.0,17.0,11.0,10.0,13.0,12.0,DECDFCDFEDCCBCCBCADGAGFAEAAHHCGECAAFHAHBAGEFDEFHHGGFBFCBACBABDACDAHDAGDGBDBADHFDBCEHGEHGDHABGBCEDEEHBAABADCGGCFCABDABA,False +104,12.0,15.0,10.0,16.0,25.0,15.0,20.0,17.0,GBFDCFDGDDBHDAADEBGBDEBEEFGHFGHFGHCGHEGDEADHBDHGGBGHEDCFHAAHACHGGEGGEFEBFGADCCEBHEGFEHDEHEEFAGDCHFEEAEEBCEGEDBEDBECBFFBHHCAFAEGAFB,False +105,7.0,10.0,8.0,8.0,6.0,8.0,6.0,10.0,HBEHAGHFGHBGDBAAGCDEHFEBEHBEBCABAACDFHBCHDFGDFGDFHCHCCACBFDBEDF,False +106,17.0,20.0,9.0,15.0,13.0,17.0,14.0,15.0,FBEAGDAGAABAHBGEFFBFFEDHEGHEGHEFHFDBBCBBDBCHCAHGAHCHBEGFDGFAEBAEGADCAHBDFBDFDFBABHEFGBCDAFDBCAGCFBHFBAFAEDHEDCEDHBDGGHGA,False +107,5.0,5.0,1.0,5.0,1.0,5.0,5.0,2.0,FABAAGDGFDFHBFEBAGBAGBFDDHGDC,True +108,17.0,16.0,20.0,15.0,16.0,19.0,21.0,30.0,CBHCHHDDDGADGAFCEHEBHEFEAAEBHFHCBGFAEDHEFEFFCFFAHEHHAHBGCDCHFGHBGFCGFBEABFBHHGHHGCHEAHEADABGHBHHBDHGDHGAGGBGGEFCFFCDBGDFDAECEECGCAGCGDCFDFHHAHHDHBBCCACGAC,False +109,19.0,26.0,19.0,10.0,27.0,23.0,8.0,14.0,EBCAAAGFADFADFEFBBBCBEABEABEAEEHEEHEECEBGACCAFCBHCDCCECFBCAGGAFEAFEFBHHBDFAHEHFEGFHCFBBHCCABCHFFBFFBDGCEGEBAEGCFFEEDHFFBFBADBDBBDBBEHEEFCHACBAHDEE,False +110,19.0,10.0,10.0,17.0,15.0,14.0,13.0,9.0,EACEADEDDGDAEBCFACEAEBFHFFGDFEDBBGBHGCADCFBBBHCAHEAHFAHAAHCDGCDGAEGAEGEDDFGEAEBAGFCGDGDDABDFCDFGFFAAEDFEHAH,False +111,6.0,10.0,13.0,9.0,4.0,7.0,3.0,10.0,CCCAFBAFBEHDFBCCBCHBCBCGHDAHDAGDCDFCHCEHDAFDFHDHHDEEBFBAGBCHBC,True +112,14.0,15.0,18.0,9.0,20.0,11.0,10.0,7.0,DEFDEFBEACFGEFCACCBGGBHAAEBEHCEGGEDEEFEEDBECBABGADFADFADGCHCCHCHACEDHEGAFAEFBFBAEACCAEBBGBBGEBEBHCCDCCFC,False +113,18.0,25.0,13.0,24.0,29.0,22.0,19.0,30.0,HCAHEABDACHBBDDHADBEHEEHCABCFBHFBABBABDHBEHFGAFGFHCHGCAEFHEFHGHCGCEHDDFEBFEFFDDHDEEDGEFCBGBDGAHHCHDCFDEEDGCFHHFEEFGBGGEEHBFAGFDHBEGFEDCEDEBDEFHEAHEAHABBEDBGFBGEHGAHFADBADHADHEDBGGB,False +114,13.0,9.0,15.0,32.0,17.0,18.0,11.0,14.0,HDHDDAGGFDDFHBFBCAEDGEDCEACDDEEDFHFAGFDECDCCDFADECFECHDCHDGAGAHGHDFEDCEDCEHBHDAHDCFDBFHHGDBDAFCGFAHFDCCDAEDGEDEEFADFAGFBBDEBDEBDF,False +115,21.0,18.0,26.0,25.0,21.0,27.0,25.0,34.0,AACCECDFFBBDABHAGHGFHGHAFHBFHFEHCBHFDAGHAGEDBEACHDCAGCDCCDBEDBDDEGGEHGAHFAHDBFGHFGCDCCFCBFCBHCHHFFDFGEEEDHFHHFHDFEDFDCBHAGAAGHBEEDCFFCHEDAEBAGDEGDEDBFBGCBECHCGHCDAGGAHGHCGHCFHBFHCFHDADAEGEGHCGAFFEH,False +116,25.0,15.0,25.0,18.0,19.0,11.0,22.0,30.0,BGGBGDHGBAECHEFABDHBHHBHDADBEEGFGGDGCCGFCHHHAHAFHBFEEGEAHCGEAGDCCHCGDAGBAGBAEADBADHADFCGHEDHCABCHHEHDFHFAHEAHCHCAHBDHBGHFGEFCAGCHGAAACAACHHDHCCGECEDDFCDACDACBCCEEGEE,False +117,28.0,24.0,15.0,28.0,23.0,30.0,14.0,19.0,CHACHAGEBEFDCFAGFADDEDDBDGBDBFEBEDHHDGDECDEBFABFAFFABAAHHAHHDFHFBHDBEDADCBGHEDFFDEDDEBEBAGADDFFFBDFBFFBFFBHACFDBFDFAEBACBACGEGGCFAFEHEAHECHBDGGFCAECFEFHEHHAGACBDCBAHAAEAAEDECDAFGGFB,False +118,0.0,3.0,1.0,0.0,4.0,1.0,0.0,2.0,FHBBEEBEECH,True +119,15.0,14.0,10.0,15.0,7.0,12.0,18.0,9.0,BGDBGBFEBDCFAFFADCGGAGDABAAHHAHHACEBCDDCBDAGDGBBGDGDDACEFCFFCGFHGBEFCGACHAGAGHAGDABBEEFHGFBFDBEDGHDG,False +120,18.0,23.0,21.0,12.0,21.0,14.0,26.0,15.0,GBBHAAEBAEHEEFEGFGCAECABAGCADBEFAAGDABCAGGFGGCHGCHGAHEAHFFCEHCEBBFBBEHBCGECGACGDCGDHGCGGHGGDDGHACBBGDBDECDCFABECFEBFECEBGBBEDDEGFCDFEGBHGBHAHFACEBCHBF,False +121,18.0,17.0,15.0,11.0,14.0,12.0,17.0,17.0,AGGAFDDFCDBBHECHBCHADHCBACFACDDGFACEBCBBGBHAAHEAEEHGFGCFGBHEBAFHAHHADHBEGBHHCEFEEFGHFGFGCBDCADGBDHHEBEBBAADAAFCAGCGGEGGEC,False +122,19.0,12.0,14.0,16.0,13.0,13.0,22.0,12.0,DFAEFDEBHGFEEDAEDFGGCGGFGGFGGAGGAFFDEAGEAGDBBABDHHCHHBDHBDGCGGDHDAGCACCBFCBABHEFHCCHECBCGDDAHDCEEFACFBCAGDAGAAGAEFAGDBEHA,False +123,3.0,8.0,5.0,11.0,9.0,10.0,4.0,11.0,EBFFHHFADFCHFGHEGHFGFACDEDDEGHFAEDHBDEBDECDCDDFHBFEBHHBCEBHDB,True +124,4.0,5.0,6.0,11.0,9.0,6.0,5.0,8.0,ACEACEADEDEHDCFFCDCCEHHEHEBHGBDGHDFDFEGFEDBHDHDBBGFAGD,False +125,11.0,14.0,19.0,12.0,21.0,14.0,17.0,9.0,CCDCBDBEDHEGHAFEECDGCFGCEGCBGEFAEDACCHCDHGFEFFBBEABEAHHAFCCFBFFCFCBEGDACDGCAEBAEGGEDGEDCAGGEDHEBHBBACBHGFEGEGDEGEFCBF,False +126,7.0,15.0,16.0,15.0,17.0,19.0,21.0,17.0,CHHHDBCCEFEEBEGBHFEDGEBFFBGFGHHGHHGEHDHCDHCDFAFFDCABAFBHGBCGBFHBDHCEGAGGHHGDEAFECHDBFGBDBCDECGEFEEBECBDFFDECGGCGADGEDGFGCFGCFAF,False +127,1.0,2.0,2.0,2.0,3.0,3.0,7.0,2.0,BEGGGGACFHCFHEFDGGDEGB,True +128,24.0,27.0,28.0,25.0,25.0,12.0,31.0,20.0,GGGBGGBDBCDHGACGEHDCHDCBDCHHEHBGHADDADDEBGGHGDDEADFAHFAGGEGEEABEHDEHCEBAEBECBACBACGACGADFADBBBBFCCAEGHFBEBCAAHBCHFCEFCDFCDCCBAEGEGCAGCGCCGEHFEHGCCACAACBDDBHGBEBDAFGEFGBBGHHEDGDABCGFHDEGGEDEADB,False +129,8.0,19.0,18.0,15.0,11.0,19.0,15.0,9.0,BEEBFHGAACFBCEBFHFADFCDHCDBCGBGGEGBDAADFDCHECHECEGCFGCFGFBCFGCAGDFGFFHHBDDFCDFBBEDBFDGDBBFBHABCEBCDAEGCBFHBFCGECGD,False +130,19.0,16.0,11.0,13.0,12.0,17.0,19.0,19.0,AGFEGFGGEGDAFDBFDBCGACBHEHHAHHDFADABHAGHBFHDFCDCADEEFEGBDGBEGADBAHFGBDGBAEFAGFBCAECHGBGFBGBBFBHAHHAHDEGEFAHADCACCHCEHGAHFHGFCF,False +131,4.0,4.0,2.0,0.0,2.0,2.0,3.0,2.0,FBECAGHAHCAGBAGBEFB,True +132,21.0,22.0,26.0,22.0,19.0,22.0,19.0,31.0,HHACHAGHDFHCACFECAECGDFFDFCAACEBEDHHAHDCGBCBBCAHCAFCDBGFGDCHBHECHCFACFGCHECBBCFBGHDGHEGHDGFBAADFGBGGFCGHCBHAGHFEEEDAEDAHHABFABHAHHGHBFDAFDGDDFEDGBDFEDHDDHCEHEAHECEECEADBGCBFFHCFBBBBH,False +133,16.0,18.0,20.0,18.0,16.0,13.0,27.0,16.0,DGGBCEDCEFHDGHFBDCHFHHBACBADAAHADEACBGHFGEDGCBCABGAGFCGDCGDGBEGBEGBECEEHGEHGHHDAAGGACBDGBGCBACDEBDBGCFHFEHCEGCEAEFCHFABFEGGCDHFDCDDCDBFGBFGAGHAG,False +134,19.0,21.0,15.0,10.0,12.0,12.0,10.0,11.0,DAGDAGAAHHFHABCBBCEBCFBCGDCGEEACACBACEAFGBDAAFEAFEHBBBFECDEADGFFACGECBBCBBGEBFEBDAACHADHFEFBCHBFGBHDBCGBHADHAH,False +135,13.0,9.0,13.0,6.0,13.0,9.0,17.0,10.0,ACEEHFBHFBGFCHABEADHHCGACGDHBCABEGBEDBGGCGHHAHCEDAEFAEGCEACEAGGFCGCDGBFGAFGAFBEGCEGAFGECHD,False +136,12.0,12.0,9.0,6.0,6.0,6.0,7.0,12.0,DGFDCFBCHHHHHHHBHBBABEAFGBEGCFDFGCCBDABAAEAAHACCAGHADEACGHGEBEFBCDBHAB,False +137,8.0,7.0,7.0,10.0,12.0,16.0,11.0,8.0,EEHEGHGAHFFEFEDBGDBEBBGGFGDCGFCFCGFDDFHDFHAFCFDGAAFFAEHAEDFEGFEDCEGAEFBHBCDBCHA,False +138,16.0,20.0,15.0,26.0,16.0,10.0,21.0,11.0,BCEFDBCDBAHBEFBCAHCAEBDCCDHGHHCHDDDEGBFDFGCACAEEDGADGEDBEGCEHCHBGHBEDDADDGBDGBCGBDHCFGCGGFGGAAEAADAEDGEDBEBADDADGCDGBAGBDGBHGFFBEDAEFBF,False +139,13.0,8.0,3.0,6.0,6.0,4.0,5.0,4.0,EDGABAADGAECAGAAGAACHFFHABGFBABBEDBEHBAHCABDFDEED,True +140,3.0,7.0,9.0,8.0,11.0,8.0,12.0,4.0,FGFCGCCEEDFEBFEBDACHADEBCEDFBDEHEFBEHCEDCGGBGFBEFCGGDGHDGCGGAG,False +141,7.0,6.0,3.0,11.0,10.0,4.0,8.0,7.0,EEAAECEEGHEHDFDCHCGHEAAEHBDFBDBGDBADBEHFEAFGGDHDDGBDGADG,False +142,25.0,23.0,17.0,19.0,29.0,25.0,18.0,29.0,EEBEEBHHHHBCHEFDGCDECDEDBEFHAFGBFBHFBHFCHFEDFBBFEAEGBCBAAAADAHEEFAEFDFACHHCHBEHBHHDGECFEFBEGHEGHAFHCDBCAGHEGHGDHGEGGFAAFAHEEHBFABDACHABDCDAFGFFGCFECFHBFEEDDGDBFCAHAEDDEACEAGDBGAAGAHCBHB,False +143,1.0,2.0,2.0,3.0,4.0,5.0,2.0,3.0,CFDCBDHGEEGAEDFEFFBHFH,True +144,9.0,4.0,7.0,5.0,3.0,7.0,3.0,7.0,EFAFABHACHECHGCBADBADAADGCFFAHGHDFHDCHFCBECAF,False +145,21.0,27.0,26.0,22.0,15.0,22.0,16.0,17.0,FCDFDDECEHCFGCEGDABBGHCGBBFABAEFEEFACHBGFEABEDBHCCFGAFEEFHAFECFHCEBCDBCBAHFAHFCFFCFFBFAGGAECDCCBBDDCDDCABBAGGAGBAGHCHECDACBAFHECGBGGBAGBHBACCADDDDCHHHFHHBDDBDDBDBADBF,False +146,23.0,23.0,27.0,18.0,23.0,27.0,25.0,28.0,DEGHEGFDBFGHDEACECDFDDFDBBBGCEAFHFFHFEBGEBDEBFBBFHFFEFCGFCGCHGAHBCFGAAECGEGDDGCHGAHAAHAADDADCAFBFFBHBHEGCAHCHHBEACCBBABBDBHCBDFAHAEBCEGEGCBHEHFAGCAFCACEFHEFADBCGGCGHAGHGEHEFHCAHCGHDGHCEHCEFCGFDF,False +147,19.0,22.0,21.0,22.0,15.0,18.0,18.0,18.0,ADDADEFBADAHFBBFBBCHGCGBCBHEDCCDHDDACGEGBEACEBCGCFABFHEAHFGDCDDCGFCGHEHHEHBFHDFBFFBAFAABAADACDFCEFHADGADCCECDBHDBCGBAEBAHDHHDHACFCGFGEFHEGGCGEFGBDGBGBBDE,False +148,23.0,18.0,18.0,17.0,20.0,20.0,23.0,19.0,GHBGCBDAFDAFHCBEFGACAECHHGEGFEGDEDDBCAAGFAGCGECAEFBEACEHGEHAEAFEAFBCGCCFCBBGHBAFBFCBFAEHBEHBEGAACFABGEDGHAGBCGCEBDGDDHEAHCADFFGHAHDGHDGHDGBDABHAEDDFHDFCFFHGFE,False +149,11.0,9.0,14.0,14.0,12.0,13.0,8.0,11.0,CCFCGFCDFHHHGGHEDDFHDFEEGCEAHAHCADFEBBBCBFCAHBAHEACDDCDACDADDBDDBEGBDFFCEHEFBEFEAGEGFCGFCAHA,False +150,20.0,17.0,22.0,21.0,18.0,23.0,27.0,26.0,FDDHHBGAEAABAAFAHBGFFHEHCEBEBBEDBGDCGHCGHCFFEGFEDFCDACDAEBFEDAEDHHHFGHGDHGAEFCFGBEDAADCCGFGGAAGCHCDDBDCGGFGGFGGFHGFBGBCGECHFHHACHABDFHDHCAEBBEBGCCFHEHGFHFEHFEHBCACCACGAGHDDDD,False +151,25.0,32.0,23.0,18.0,29.0,30.0,21.0,16.0,CHFAFBDBCEHGEHEEFEACEFCFHHFCAGAEGBCABCAECHDDFDFFEFFGHABFFEHBBDBGABGACGACEDCGDEBDEBCEBFDCHBADBFDAADEFBFHGAACAACHDEADHCBGCAFBFFBFFBEBBGBEEBHDBFDGDAGFEGCABEEBEHBGHBGFBGBAGFGCEGCACFDGAEBEEFCEFAFHBCE,False +152,2.0,5.0,8.0,6.0,3.0,7.0,7.0,3.0,ECBDCEGFFGHCGCGGFBDFDDADDHEBFCBCCBFCGFGAH,True +153,20.0,20.0,31.0,26.0,22.0,23.0,14.0,22.0,GBGFBFFBHCBHCBHGBEFCGFHHHHEHDCHCCDGCFFCDDHFDEDGEGCHHADHCEECFECHECDGCDGADCAGAAHEDHCFBEFEDCHFFAADEADHADCGBCFBCFEEEEBGBCCCCBCDBDHBAHDABCAGCBCFBEHDEBDCFDHFEFDAACAEDADAFGEFABFDCEDAFAB,False +154,14.0,22.0,13.0,6.0,19.0,16.0,15.0,9.0,EEBFEFCBFDAAGAHBCCBGCEEAEEAEEAEEAEGGFHBCHBCBCHBCFACFGDECBAGFFDBHBBHGGFAGBGCBEHGADBFBBGGAFCAFCEGBEGBEFBDFBHEHEFDAFB,False +155,13.0,9.0,8.0,9.0,16.0,11.0,16.0,26.0,HGHDBHECHGCDGAEGFEHDEGGHHFBHFGHBGBEFEAHEAHBFHFDHADHBCHEAHEAHDGHDHHEFFACDCEBFGGEGAEHEGHEGCCGFHGAAAHAFHAHDEBBC,False +156,21.0,23.0,28.0,17.0,32.0,20.0,26.0,33.0,AGBGFFGFGGCEFCBFGBECECGECBECAGHDHEDHCBHEEAEEBFGGHEEHAGFFGFHHCCHADABEGBHGCHGCFBHEHHEHHGFHFFHEFAEHADCEDCHAADBADHEDAFHEDDCCDCFEHBHGGHEFHEBHEBHGBCGCADAAHACBDFBGCBECBCCEHEADEGEEAFCDBHGBCGBCDFAGEAEHAHDCBBCG,False +157,3.0,5.0,10.0,12.0,6.0,7.0,9.0,8.0,CDDCFDCHDGGFGDBGDHFHHEGCCHDCADCAGBFHEGEEGCEDEFDBFDHAHGCBFCBD,False +158,27.0,19.0,22.0,22.0,21.0,22.0,30.0,32.0,AEAADDGDGHBHDGHBGHBHHBCHCAHCABEEBDBDHGFHGHHGBBAHAGFGBAGAGGAGHHCFFBHHGDHAACAGCAHDADGAFHCCHGHHCHGCFGEEDEDBECGAFEDFEDBEGBCACHFCDFGDCDCCBGCFGDFGHFAAEDHFBHFGFFEAEEHEDBECFEABGAFEEEAFDCFDAFDBCGHCGHAEHAG,False +159,6.0,10.0,10.0,5.0,6.0,6.0,5.0,10.0,HCEECDECAFABHBBFADFCGACGABHFEHCBBCBBHFHCDCEDCHGGHEGHFBHABD,False +160,18.0,20.0,20.0,17.0,21.0,19.0,20.0,20.0,FEDBECCGDCDBGDBGDGGDCDFCAHCEHAGAABACFCFFCAACHADAACEGEEGBFBHEHHBGHBACGFDFCHFCHEAEBBEDFFGCFGBEBBEHDDHABGEEEEFABHABHGEHGEHGEHBFDFDHGDHGBEGBECCFCAFHFGCCDAFAHDB,False +161,12.0,21.0,28.0,20.0,19.0,21.0,30.0,23.0,BEBCAAFGAFGBFGEEEFCCHCGHFGHGDDCCHBCGACGEHGHCEHCFCBHCBHDAHDHHDCHEABGHFGBGGCGHCGCEGFDGDDEFGEAHBGEADDCFDGBDGDCFECFCGFCHEGAFCDFCDGDFFEHFBHFCCBECHEBHCBFDBFBBGBDAEDGECGBHEBDABGGGAH,False +162,21.0,14.0,18.0,20.0,18.0,17.0,19.0,20.0,GHBEAFEGBGGHDEEDEABEBBEFECFCCABAAEAAEACBAFBHFHHAEDBCDECDAFBAFBAGEHEHGDAAHGAEDCCDHDDHGAHAFCCECAFCHHCHEGBCDCCBFFEFFGBFDDDDDGGCGDAFDGCGFHHDHHDHGFHGAGG,False +163,7.0,8.0,10.0,9.0,10.0,6.0,9.0,12.0,FBCCDDCAHADHEHHAGCGGHECHECHGBFABFADFGDHBDHDDCDHCEBFHGECEEAEFHECEBGBGGBA,False +164,2.0,1.0,4.0,3.0,2.0,6.0,3.0,7.0,CHCFEGFCGHHEABGAHDFHDFHCFHFD,True +165,27.0,21.0,24.0,26.0,31.0,11.0,22.0,21.0,CAADGACHHEAHDFHCAHCFBCFBEBHGCEFCHCGECDEABEACDDGHDAFCCDCADCAGBDGBEGBCDEHAHHAEFBEGDEFCEABBDBGAHAACAAEACBFBBFGEEHEBDEGDEGDCCDCABHEEEGCDGCDGHEGEEGEHDEGDHDAEFEGBDGADHFDGCDGBAAAAHHEEHDEBABB,False +166,7.0,16.0,7.0,13.0,4.0,10.0,9.0,15.0,BDDEDDGCAHEFHCFHCBHAGFDBDDBDDGFFBAHAHHFGBBDFBDHACHBCEBFEHHGHHBADBCFBHDGABGHBGFBGC,False +167,15.0,15.0,9.0,10.0,9.0,15.0,18.0,14.0,GGABCADCGHHGEHBDHCDHDEGGGFGGAGAABECBCFBEABEBEGAACBBFEAFBHFBHFBGFCAFGHFGHDGCBCEHFFGBFEDFBDAHHAHHGFDDAGDAFA,False +168,21.0,14.0,14.0,15.0,25.0,21.0,7.0,17.0,FDABDAHCHHFDACBGCBGCHFAACGEEBCBFABAEEAEEAFEADDHFAHFEHAHHCEHEFDGFEHFEGFDFHCCAEAAEADBHCFHEBBCFACFDEADFAECAEBBEDBEGFDAFEFDHFDHFEEBCEBGEHD,False +169,11.0,25.0,11.0,15.0,12.0,14.0,16.0,19.0,CDFBBCHGCEBDBACBDCGHFHHFHDFHBEGBEDBFDAFCAHBACFAGGAGEAGBAGBHBBDEBHGHHGHFEABDHFCBECBFDFEGHDFHBFHAEHECHBHBGDBGBCEBABDEGDGGDFDB,False +170,11.0,10.0,15.0,10.0,14.0,10.0,14.0,13.0,EEGCEHAGADCDEADGBDBHDFGDHCDFCDHBAEAHEHCGFCGFCEFDHGHHGHFGCAACHACHAEGEBDCFGCFBBFBBEEBGACGFHEECEBCGA,False +171,15.0,14.0,17.0,21.0,14.0,11.0,20.0,12.0,CBGBFHBCEACEAGAACBDBBDCDDCDDAGGAFGFGDHADEDDEFFAFFCBFCBFCFAHDDBGGGEADHHBHBBDEEGEEGCAGCDCCGCEBHHCGGCDBCHHEAHGAEGHEFADGDGEDGDDA,False +172,6.0,4.0,6.0,6.0,3.0,10.0,5.0,4.0,GBFGHFGDEDFCDAGDHCDACBECDECAHAFFAFBCBHAFFGFF,False +173,2.0,0.0,4.0,3.0,0.0,0.0,1.0,0.0,DDGDCCACCA,True +174,3.0,6.0,8.0,12.0,9.0,8.0,4.0,7.0,FGBDDHHDCFABFABCBCCHDEHEFAEFEBFEDDHDBCDECFHCFGEGGEDDCDDHE,False +175,4.0,4.0,3.0,0.0,0.0,0.0,2.0,1.0,GACGABHBBAABCC,True +176,4.0,2.0,4.0,1.0,2.0,1.0,1.0,1.0,HCDACAAEABCFBCEG,True +177,22.0,20.0,10.0,18.0,13.0,13.0,19.0,20.0,CBHCGHGEHEEADBHGAEGFEGFBAEBCFAFEGHCBABFADFDDCHBCHDHAGGADBAHFEEFHBBHBGDDDHDGHGFHAFAAEGBBDAADHGBEGBAGBADBAHCHHADHDGGDFGDFDCABCABCABEFHEGA,False +178,22.0,19.0,25.0,28.0,26.0,27.0,22.0,13.0,CCCCCCCDCAGHEHCGDGHCADEADBADHFDGGGBDACFHCFHDGBDGDAGDCDDBBCEBFBAABDCDDEDFEFEECDEBAFBDDBFEHEEAEFGEFGEAGBFFBFFBCFCFDGHEFCAFCAHEEGEEBEAHDGEFBFHDFEDCDHCDACGGBGCAGDAFAAFEAFHDFEGECBBGFAEFAG,False +179,3.0,7.0,11.0,8.0,19.0,13.0,15.0,4.0,BEEBAEFHEBGCBCEBFHFDECDCGHGFEGEEBECGFCGFDGDDGFAFFAEGCEFCEFDECEEGDEGCGGFGEBDHCEGF,True +180,23.0,18.0,16.0,19.0,17.0,9.0,16.0,16.0,DACDHCDECEHCBACDAFDAFABCEDHDGHBCFFABCDDFDDHCAHBAEDABHABDGDFCBECAEAAHGEFABFGBGBHABHCEAEGAEGEHGFHEAAEAHGCEGCHGAEGCBGCDGDEGHHADBAGBEDBDBB,False +181,7.0,4.0,3.0,4.0,1.0,4.0,0.0,2.0,CDDAFABHAECADFHCFABFABDAB,True +182,7.0,17.0,14.0,12.0,11.0,8.0,17.0,16.0,ECEECHEGDCFDCFDCEDBBGBGECGBHGFFGCBHEBHABAGBHFBHDGHBECBEHHGCGCCGCFGHABADDDHGDHEBHBCGGFFACHAEADBHDGHBGDB,False +183,18.0,19.0,14.0,22.0,20.0,25.0,20.0,18.0,FBAHCEHGHHGAEDEDDHDHGFACFDBFGCCBHGHHGBHGECBHFDEFBEBHECHFGDFHDEHAGGEGDBGAADFADAADGADGHFFEGCABDGFDBDECDFAFAEFCEFCADGFDFFBFFBHFCECGEBGEBHEADBBDFBCFDCFAAEGBEABE,False +184,9.0,17.0,14.0,14.0,12.0,19.0,15.0,10.0,DBDDHCBBBBGGFEBFEAFGCFDCADCDFEFGHFDHBDCECCFDCAEBEDHFDCBDGBACACGECFEHDBACBFFBFFGGDEGHHGCHFBHFBEFAEAABGFBGEGGFGH,False +185,5.0,15.0,12.0,28.0,11.0,16.0,11.0,13.0,FBEBDDHEDCEGFGGBGEBDBBHCDGDDHBDHECBDFBDEGHEFHEFEDCDHGDADDABHABDCBDBFDHGDFDCGHCGDCHHGDADDEDDAFDFFHFFECDCBBFFCFFC,False +186,3.0,2.0,0.0,4.0,2.0,3.0,6.0,2.0,EGADGADADBGHFGBDGHFGEF,True +187,7.0,12.0,9.0,16.0,4.0,16.0,12.0,10.0,BDFDFFBBBEBBFCHHCHHFFEGDADDFDFHAFDAFBBGDBGDBDDGCDFFDGDGCBCADGEHGDHCCHACABHAHGCFGFFGEFG,False +188,9.0,14.0,12.0,11.0,9.0,6.0,5.0,4.0,DFBEFDCDCBAFBADEFDEGCEBCGFCECHDBADBADBEEBABGHBACBACBECGACBBCADDHFGHECD,False +189,15.0,22.0,16.0,23.0,11.0,18.0,13.0,25.0,CHGBHDEHBEHDGCDFHFHHCHHGHEDDBGHACHECHBHGDHDCHDEAGEABFAEFACBBDDBDBADACDABFAHDABACBHHDHCAHFFBBDBGAFGFFBBABCGEEFEDCCDCBDBFDBFEFGGFHHFHDCADBDGFCGFH,False +190,23.0,11.0,18.0,25.0,19.0,12.0,19.0,38.0,DEHHAGHADHGCHACEDCAGEGFDADHADHDDGEEEEHFHGCAGEDDFHHEHHDHDGBDADHECEEGAFHDBHGBHGBDAHAEHABHBBFDDCDAHHGHHEHFGHCHDDECBFCADCGDCGHCGHGAHGABFHFHHFHHEHHBBAEDAEDFCCECAAGACCACAF,False +191,5.0,6.0,1.0,7.0,12.0,13.0,5.0,13.0,HEEFEHAEHFFHFGDFEDGEGAFGFHGEHDBHAFHFFEAHEBEBDFADBHHHEHBECFDBFD,True +192,14.0,9.0,19.0,16.0,17.0,13.0,14.0,12.0,FBCCBDDFFDHDDHGEFGEFGFHGFBDFCEEHACCAEEDBFDEDCHFCBAEFCGGAHFADGAHEHHAHBACBCEDEEDCCDCGACGCCGCEGDECAECAFGABGBHGDDEAEHA,False +193,13.0,11.0,10.0,13.0,18.0,18.0,16.0,24.0,BFHBGDBGHEFHEGEEGAAFHDFECFEAHEAHDFHCHHEHFAGEGCCHHEDHEDCCDAGGAGGBDCBDAFHFFAFDAFHGCHGCFGHGHHCHDBHBFFADFEDEBHGGFBADHAEEEHEEBFB,False +194,4.0,3.0,4.0,0.0,0.0,3.0,1.0,3.0,HCHBAHBAGFABCAFCFC,True +195,5.0,5.0,1.0,2.0,4.0,4.0,7.0,2.0,EFBGHBGABGADGABHAGDBECGAFGFFEE,True +196,16.0,12.0,12.0,7.0,4.0,7.0,9.0,12.0,ACGACAHFFCEACGGDEADCAGCFHBFBEFDHDBHAAAAGHBBHCBHGBAGBACBDCBHCBACDECHHAGHFHBGADFA,False +197,11.0,6.0,8.0,7.0,7.0,10.0,12.0,14.0,GHFFHACEECGEGGDBGBBFAGFGCHGHDGAEGCCBHCBHAFHAHDAFGAFADCADHAHHBCDFGEAHEHHFDEF,False +198,21.0,16.0,17.0,15.0,22.0,24.0,21.0,20.0,AEFABCDCDABGHHEHDFBBFCAGGAEFCGGCGABGACGHHGDGBDBBCFACBDFHHEHFCHFCECHFCHGEHGBFFECFBHFGHFEDFDCFCEAEEADDGDEGFEGFABFHBFAEHEDDADAAGAACEACBHEBFEDFAAAGGEGGBHEEHFEHF,False +199,3.0,4.0,1.0,2.0,7.0,5.0,9.0,5.0,HFFFEGEEGAHGBHGAHDADCBGGEEGEGBEGBFFH,True +200,27.0,17.0,26.0,18.0,16.0,17.0,15.0,13.0,BDEBEEBCBBCDFCHCCABDEGCGACGACACFGDDGAACBACEEDBDDCCCHCDFAHBGEBCHGGFCGHHHABHBGAEHCBGCDAEDFEFBEAHEAFFGDFHDHHDFDBFEBAAGAAGAGFCBCCEACEACECFAFAAFAADCFDAFDA,False +201,14.0,18.0,22.0,18.0,23.0,25.0,18.0,25.0,EHGEHCBHCHHAEHDEHDEAEBCEBCEGFAHFAHCEHBFHBHHBHEBCFADGHFGCFBAFBDHCHCEHADGBDFBFFBHBGGEFFFDFEBCDFDHCDHBECDEHECBECEFAGFCGCAGEHGEDEFHFCGCCDACAAFDAHDFFDBGDGAFGCBCDFEGFGGE,False +202,6.0,4.0,6.0,6.0,4.0,7.0,2.0,1.0,BADGAEAACFACGEFBACCEFCEFBDHDDFDBFDCF,True +203,4.0,8.0,7.0,5.0,6.0,6.0,6.0,7.0,EHAECAEHBEHBFHBCDBAEFEGGCFGDGHHACBBCGBDHCDFCDFGBF,False +204,6.0,15.0,10.0,9.0,18.0,10.0,16.0,17.0,EHHEDFBDFGDGEDGHFEEDDBGFADFCBHCBHFEEFAECGHHGBCEDCEHFACGHEGHEGCBGHBCHBEFFEHADBAGBGHCHEEBEAGEBGBHGBHCBG,False +205,6.0,8.0,4.0,6.0,11.0,10.0,4.0,7.0,BDFBFFCHFBADBGFCGCCEEAAHFAHFGFEEFBEAHEBDEBDFHDHEGEEBEHDA,False +206,7.0,11.0,7.0,14.0,12.0,11.0,11.0,15.0,DFFHFBABAHBEHBEHDHGCHFDFAGCGHEBADHGDHCEHCEFCEFGFFGHGCDAADGBBGDBGEBFEDHABHDBCDHHEFDEGDEDE,False +207,14.0,19.0,19.0,16.0,15.0,16.0,25.0,15.0,BHBBDBDDGDAHEGEGGECDCCBCDAEBGEDGHDCHFEHACACCEDCGFGFEGDGGAGGAGGHFBEGCEGCEBCAFGHEBHDAEGAFHHCADFBBFBFFDHFCHFBBGBBCBACGFDAFHBCGFCGEDGADEAHFCHBG,False +208,14.0,24.0,23.0,25.0,20.0,23.0,13.0,19.0,CGFHBECCCACGAFFHDFHDAHCCFBDFBCCBGFDAHDABGABGHBFHCDGDDHBHEBCEDEFFEFFEFFCDDGGECDEFDADDHEACEAHEAEEBFBFGBDBBFCBDCFDGFHBBDBCGCDAHDCCDHCEEFEGGECBBABDCBDEFEHHEHHBHBADFA,False +209,5.0,7.0,7.0,12.0,11.0,5.0,6.0,4.0,BEEGAGCAHCFDCAHCEFCAFGGDDEDCBDBEFBEDDADDHDDBBDBEEEGCEGHEF,False +210,21.0,21.0,29.0,26.0,25.0,22.0,25.0,25.0,HGGGCBGCBGFDHCEGCBADBADBDFHCBHDBEBBEHBEFBCABCACCFCEFHAFHGFGDDGDDHHDEDDHCBEDDEDCBGGFAADADGACHAFDBEBEECDECEFGGHECHEFHEBHEDGCDCABCEFGEGHFGHEECDBHDFDFGCAEAGEAHCHFAHDGHACFACGHHGDHGCAAEFAFBCBECGFCFFCA,False +211,25.0,20.0,15.0,18.0,16.0,31.0,22.0,17.0,GDHFDBEDFEFGAHDFFDBECFDAFDBFGBDAEGAEGFDCFDCEACBAFHGHHFBFFBHHEAFBAFDCFBGAGGACBACFCEACEACHHGDHGCGFHGHAGABGBGDFHHFCACEBHEDDAFDAGCADBEGBFGBFEFFEAFGCFBHFEHGABAABAEGAFDFB,False +212,11.0,12.0,15.0,21.0,14.0,13.0,13.0,22.0,FDHBAHAHFDBFDFCHHEFHDFAGBADBADCHDFFDABDHCDHCGAGFHDDHEEHBHHEHBCBGDGCDCDECDEGEBHEHHGHDFBCFDAGCAGCACCEFCDBGEBGEDEFGHCGHEDHEA,False +213,26.0,25.0,22.0,24.0,22.0,21.0,23.0,28.0,DGGABBFFGEFGHFBHBHFAGAHGECGEBAACCADCHDBGDHCDFEDCCCFBFAHDEGGBGECFEABGHDEADGBGGFDEFAABAAHAAHCAHGFHBFABFAEHHCHHCFBEEDEEFEGDEHDHHDHCBEABAGGAFGDFDCBCHBCHBHEBAAGCADCHFCFDBBDBCDECHACHDBEDHEFGADGHDBE,False +214,17.0,18.0,21.0,25.0,26.0,17.0,17.0,17.0,FEFAEAHHABBGBGGCDGDEEDAEBGFHHCADDHDDEDDEAFECGGAGGEBGBACEEDEEDHDDHGBHEBCBHADFEDEGGCDDBDCFCHFEFAHFHDBHDBHAGCFEFFEBEEBEEDGEACFABBCBFDBFHFECGHCGACDCCDCCECFHAACADC,False +215,3.0,8.0,12.0,3.0,11.0,1.0,8.0,8.0,ECHEGGEHEEBCEHGGHBAADGCHBCBBCHBCHBCEDFEGHEDCGCCECEBCGA,True +216,3.0,7.0,2.0,4.0,7.0,5.0,4.0,9.0,EEBACHABHEFDEHHEBHAFHFCHEDGEBBDFBHGBHGFDG,True +217,24.0,19.0,23.0,32.0,19.0,19.0,18.0,19.0,BDFHFFHEAGCGGEHGAHGADAEDAEGACABCBFDEDDEHDGDDEDDGCDGAFBBEBHFBDEADCDDCHBCEAHDBHCBHCACBGCGFCGFCGDHFABCACCABHEEHDGBFFDFFBHADDDCAAHDAEFEEFBDFADGADHADFGDCGCCBECADAHHCFDCGBEFEEDHBA,False +218,15.0,9.0,15.0,14.0,9.0,15.0,10.0,14.0,EDDHBDCEDAHHCDHCDEFECFDDBDEGDCAFCAGCHCFHBFBDFCABCEGEEHHGFHAFCABHABDAFAHBHHGFCGFHGBAAFDAFAAFEDFAGGCCGC,False +219,24.0,26.0,20.0,28.0,17.0,21.0,17.0,23.0,FBGGAGHAGHGGBGGFFDAFDHDCFBFFHFDHDDHFDHFHCFGDHBEFCEACHFEHCBADHDBADCEBCDDAGDAFDAEDEHCAFDAFDFBBAGBGHBCHAFECHDCEBBEABGFHEBHDGCEFCBACBACBCCBHBFGDADAAHAHBGDBDEBGECEDHDAEBAEBAEHADCDBC,False +220,10.0,6.0,12.0,8.0,3.0,8.0,5.0,9.0,DEDDFFBCFCCAGBFHBACAACAHFAHBEGGAGCDCCDFCDFCAHCACDHEHHABGDBHFH,False +221,18.0,20.0,25.0,20.0,16.0,11.0,30.0,25.0,BFFBEGBGFBGHBEFEDHBDCAAHAGHFGDADCBDBBDECAEBAHGHGABBHHBGCGECEECADDDGHDGBBGBCGHHGCHCCHCFHGGHAAHAHGAHGEHGDHBEGFHFAHGADFEGBDHFDGCDGCFGAGCCGACGHEGDCCCABCECGEHDEDDCCECADCB,False +222,19.0,19.0,21.0,28.0,17.0,28.0,23.0,16.0,FFFFGGBAGBFCDFCBFDGDDEDDFDEFCHDCHACAAFFDGFHCFBCDGEGEECCCBBAHHDEHDECFGGGDDGDDGDDCBACBABHCDCFDCEBEGBCHEFHGBHABAGFGFADHAGFAEFHEBBFBEFCGFHAFGADGAFHBCABDEDDCHFEHFEGAEDCGDFADBAG,False +223,23.0,19.0,28.0,13.0,18.0,28.0,23.0,33.0,GHBCHBGHEHEAHDHGDCFBHGCHGCFGCBGBGCDHEFAGHEGAABBHECFCFGDEHCEHAFCADAGDFGDHACBACHACHCHFBEFCFGCHHHHCHBCBEDBFHBEHBAGEACHACFAGGHGDHFFAFEADEAHFAHCCHEFGEFBFCBHDFGFFGAFDACDECECBEBFHBAGCHGCAFFAFF,False +224,3.0,2.0,2.0,3.0,1.0,3.0,0.0,0.0,DAADFBDFBCACFE,True +225,18.0,28.0,26.0,15.0,16.0,22.0,28.0,24.0,CCBGHAGAEGAFGBHGCHGBBBHBBHCBDDBFDFGECEECAGHEBBGBAGBFGCHCCDGCDHEAGCBBFBBFCBGGAGBDGHGGHGHHFHDCEDAFGHBGABHBEAACGCCHCCHBHHFFFFGCFHCFEDACFGEFCAAGDCDDHDBAABFACDABEGCEGFEHFEFCEDBFHBEHF,False +226,0.0,1.0,4.0,5.0,1.0,5.0,5.0,2.0,DBGCFGDHGFCGDHGEFCFDCFD,True +227,9.0,11.0,5.0,9.0,13.0,8.0,7.0,11.0,DGHBGEBGHACBAFHAFHFHDDHCGEAGEDEEBEAGFDFBDFBHFHCDHCEEAFBABBEEBEBDHADHGEEAC,False +228,3.0,5.0,4.0,5.0,8.0,4.0,5.0,8.0,DCEDEHGEHGFCEFGBDHBDCBDHFFHEAHEACGBGHAEHEB,False +229,5.0,2.0,1.0,1.0,0.0,2.0,0.0,0.0,ABABFACFADA,True +230,17.0,15.0,18.0,10.0,25.0,10.0,12.0,11.0,ECCHCABEAEAABAEBGEBCEBGAAGBBDFHDEHDEHCHHCHCEHEEHCGBAFCDEEFGEGGCFDEFBBADBEEFHEAHECGFCDAAAFBBCCCACBGGBAEDDEGDECCEFAEFAEG,False +231,31.0,18.0,29.0,27.0,23.0,14.0,25.0,29.0,DGBAGHGHDGCGACBADBDDEADFCHGDBFEBHEBHEFHFCDFCDACFGHDDDDDCGCEAEEADCBDBGGHCAACAEDACHEHHAHDDFDEHCEHCECEHHEAFEABCGEGABHEDHEFAGCGGCGACDAGDACAAHACBBCDACAACHCDHGAHGFBDAACEACECFEHGGHBGHBCFFGDBGHBEFEHHAHBAG,False +232,9.0,27.0,30.0,27.0,17.0,16.0,18.0,20.0,HDBHDCCCHHCHECBBCGCEDCHCADGDBBEBGEGGFDFDDGDBBFHCEEDFFFHFHHDGCEBCABABDEHDHCDHFDHFDHBDHGGEECBEHBDFDDBCDCCBCCGCAHDBBBBFBEHBEGBEDDGAAHCBECBCCBCFFEDFEDCCGBAGACGDCAFCGFGG,False +233,13.0,14.0,9.0,12.0,10.0,11.0,7.0,12.0,CACBADGHDGHDFHDFHDEEDGEBBEDHACHABBFCFAEHACFDCEAHEABFFBFEAAEBCHDGBDBBGCBFEAFGDCDHHABHABGF,False +234,27.0,12.0,19.0,20.0,14.0,11.0,16.0,19.0,DCEACEBHDGHAGFBGABGABGABCHFEADDADAHDHDGBFAECCBCHHFADFEFAHDAEDCHCHADBFDCGDCHECGAAAAGBAEEHGCCGEAGEFCDFDGGCGACHCEHCEHDEHBCADAADADDFHGAHBAHBAF,False +235,10.0,14.0,16.0,10.0,22.0,13.0,14.0,12.0,BCEFFEFBBGBBGEDGEABFACCDCCDHEGHCBDGHEEEFAGBHGBEEHEEHDEFDEFCECDECHGGAGFFEDGHBECBHCGFEAAEAHGBHGBHEBAFACCEDCACFDCF,False +236,7.0,11.0,9.0,8.0,13.0,11.0,4.0,12.0,AEBEHFHFFGFHBFHFAHBHHBHFEFABBEBAEFCEACHHDGDEGABCCBCEBDEDCEACFHCFDCHDEEDBGDE,False +237,23.0,30.0,14.0,18.0,17.0,26.0,17.0,30.0,DGDDFCEFCGCBBHACAFCEEEEAADADEHFABBADHADHFDBFHHFHDFDAFEADBADCAFAFBEBBEBBCBBCFBEFBGFBHBBFFHFAHABHEFHBFHEGHAAHBAGBGFHAFABEGEGGDCGBHBCHGHFGHGHHCDEFFHCBHBBHGEHGDHFDHCDBDAHGHBEAACFG,False +238,19.0,27.0,27.0,14.0,19.0,23.0,28.0,21.0,CCCACCFBHFGEBABBGFFGBCHBFAAFBAHCAHCBGABGADDABDAFDBCGECFEHBCHGHHGHEGDEBFBBCGBGHBGFBCCBDGDCHACHADFADEHDEHEGADGAFBFGBEGHFHEADFCCGCCGFCEFGHFEFBCDBGHHECGBCFAEBBCDGAGCAGFFEHGEGFEGBECHE,False +239,12.0,6.0,10.0,11.0,16.0,6.0,12.0,10.0,DBDGGDGCDECGHCHEAHGDEFEEFEBBHABCCDACGFEGHECAFAEDAHAGCBGAHGAGFABFDEEDGEHEECEDCEAHDAH,False +240,12.0,11.0,10.0,12.0,15.0,7.0,12.0,8.0,EHCEBGEBCADCDFCEGBEBCEBHDGAAGDGHDCFDEEGBEFEEFGEHGHBEABEAFCFHCGHCBADAADADGAEBBDDHDFGACGA,False +241,24.0,20.0,23.0,18.0,18.0,16.0,33.0,12.0,DCADHACHFFHADCCDEEDCEDCFAAFGBCGACGAGGACHBBDBCCBEFBGCDGHFECABCACGAEFAECBFFFHGCAECAGHEHBFHBAGEFGECGHBABCADDGGDGGDGGCGCFFHGGEAGEGEEBBEGAGFFGDGGBGDBGDCGHAAABGEBEBDDBDAA,False +242,2.0,5.0,2.0,2.0,7.0,2.0,2.0,4.0,EHCHBDECDEGFEAHHABBEBFEBGE,True +243,5.0,8.0,9.0,5.0,11.0,13.0,13.0,9.0,ECEEGBGFFHFBEFHFDBGDBGFHFFHGHCGHEACEABBFEEEEGCGGCFBCDCCEHCDHGAFGABGHFGAFD,False +244,8.0,13.0,8.0,11.0,10.0,14.0,17.0,10.0,EGDHGCEDHEAHFBCGBAABGEDAEDAEGGDDFDCFGCEGCGFADFCFEBBCBFDGFAGFEDFBGFGHBBHEDHGGHBAFBFHCFHGBHGB,False +245,10.0,16.0,19.0,10.0,13.0,11.0,21.0,15.0,BEEBGHAGHCCFEDFGFHBHHDFDDHCFAGFAHABFABGAFAACBECGGGHGCAGCHCEFGEHBEHBGFGEFCHDHHDEBCABDGBGGCGGCBGEBGDCCCCDCBDEBGEBECCH,False +246,9.0,13.0,8.0,9.0,4.0,11.0,15.0,3.0,BDDBDDBAGAEGABGEDFCBCCFCDABHCBGDGGEGCEFAGBAFBGGBGGBDFFAFBCGDHGHFFCFAGFAB,False +247,24.0,29.0,19.0,27.0,21.0,19.0,25.0,36.0,AGGDCEDBEDGADBCBEDBHDFHDBEFHEFEEGEGDEABEFHDBHBHHFFAFBGGHCFFEAFDABEAFCHDCABBBCBEEBFBGAGHBGHCABCAFHDGHCHHCDGADHADGFHGFCGDBHBCHBDAEGHHGHHAHCAHDDBGHBGCEAHGADDHDECGEHHEDEGFEDABHABHABCABDABDACHGCBGDHHFHFFGC,False +248,23.0,15.0,19.0,20.0,20.0,17.0,12.0,20.0,AEDAEDAEFADFAHFAHEEHBBCBBDBCAFAAGCCGACEHEADFHDFCDAHGBEFFEFDAFGACGECEHHGADGBCAFCGCHDDDGCFFDBCHECFEHEABEABDCBHFDHECAFDABDAGEBGHGEHDBADBADCHCHHCFHEEH,False +249,5.0,8.0,8.0,6.0,8.0,12.0,5.0,4.0,DDADDFEDFHACECHGGHCDBBFFBEEBGEBCECCGBEAAGAEBFCFFHFFBFFCF,False +250,9.0,9.0,5.0,9.0,9.0,5.0,9.0,6.0,EBGEGDECAEBBGBFDBACGCBBCBBFDADDACDGEDGHDHDAHEFHFGAEGHFGAAEHAE,False +251,3.0,4.0,6.0,7.0,2.0,6.0,5.0,5.0,FCHFEBDGHDHADFGGFGFFEDBCCBCCHGCHDBDDAA,False +252,23.0,16.0,22.0,22.0,17.0,24.0,15.0,22.0,GDGADAHGFBBFBCHBDHBDCCDHEGADCHBBDFHCGGCEFBECHECEACFDBADEACEDFFDFFDFCEFCGFCHFGAFADGAFHAEABFDEDHHBAAAAHGABGDBFEHFHHFCHDCEAEEAEDCFFAFHCHHADHACHAEDABDCCGGCGFCBFGEHBD,False +253,28.0,21.0,24.0,17.0,16.0,23.0,19.0,22.0,HBGAFCHGAFDHGAHGHGDDGADGECAACFACBDGFCBAHBHDBFDEFABFACAEGFHGBDGBFHDFHCGBAGCABEGHEFHECCEAEHADHFDCCDCCEAFBDDBFHHFGHFCHCDHCFFCBAEFAEFEEAAEBFCBAABAAHEABBAFBGCBGCBDFGAGCCDECAHH,False +254,22.0,21.0,35.0,22.0,18.0,16.0,18.0,17.0,CGFCBBCBBCFBDHEGBFDEHCCAECAHAFDEEDAEHAEBCHFHBFHCHBGEACCCCDCABFABCDBDHCGCCGDCDDADDGGEHFEGCCBCBAFDEFDAADFAGGHECHECHECHAHGCFBBBBAGGEDBFDAFDCEDCEDCADCBHEFCAGCAGCBGFDACAACGGH,False +255,16.0,23.0,16.0,16.0,20.0,17.0,25.0,22.0,FBDCDGFHBEHADAEBABHAGDEEDGEAABDDEEFEEDBCGGDHHDHGDABBCBBCDHCDBGDBGCHGHAGFECEEBEHFGDFACHGHHGBHCEHCECABHADHACFBBAEFCEHAGHGEHGFHGFGGFGBFBFCBGCFGEFGEHBBGFCAFGAB,False +256,4.0,5.0,1.0,1.0,3.0,4.0,5.0,7.0,BHFAGFAFHABDAEHHGHHGEGBEGBCBHF,True +257,15.0,16.0,15.0,21.0,14.0,16.0,23.0,29.0,BBAHCCDBGFHGFGFFCFGCGHCGHDGAGHDCHDEABEBGGFDDFHDHHGHBAHDGCAGBGEBHBCHGEFGEHGEBFECHEDGEHBAHBEHDACDHHHBCHBCHAFHDCHAHGAGGDDBDDEACBAEEAHDDFFHGFHFFDAEDACDFG,False +258,25.0,18.0,28.0,20.0,16.0,20.0,26.0,30.0,GBDGBHAEEAHBAHBCHCCHCEBCECDEAAFHHCGGCFFDFBAGBHGFHDAHBACCADCAECAFFAFFGGEGCEACECCFCBEAAGFCFFGGHCDECBGHBHACAAFDGHDCHDCFDHFEHFDGDGHDCHAEADGGEADCHDHBGBDGAGGFFHHFHAGHCHHCDBGHBEHDEHGABBADBCG,False +259,10.0,4.0,2.0,8.0,6.0,7.0,4.0,6.0,BFAHHADDBDEBDAHFACEADEFDEHDGAGFDGFAEFBGFEAACHAH,False +260,17.0,18.0,20.0,22.0,23.0,26.0,23.0,18.0,CGCHEEDEBDHDGEGFEFFCAHGBHBEHBACAAFAFFDBFDCFAEFADFAEGBBHADAGGHFGCCGCGFBDFEEEEADHGDCEDFGDEBDHBGHBFFCAFCECGEDADDBHGBECFEBFEDFDDEGDHCAHCFFGFFGAHCDHADCBECBHHBHCGFGGABGCEGFE,False +261,27.0,24.0,20.0,19.0,30.0,32.0,21.0,26.0,GEHGECEEBEDACCACGBFGFCDBHEFEEFGEFBFACFACFAFFAGDACBAGDEBABFAEDAGHAHBAECAFDFEEBBBFEBDEFCHFHBFHFEHDGHBGHCCFDDAADEAEECGGHGFECFEDFEAFACHACEFBEFHHBHHFEAFHBFBBFBHFCAGHHFHHGHDCHDCHFGAGDDGCAGDEEAGEBEDAGHADBBB,False +262,24.0,26.0,23.0,23.0,21.0,23.0,28.0,24.0,CFDHHBBHEEHEHHEFHBDAADAFDBCDHDDFGAFCACEADGBEGCGCHEAHGADGABGADCFFBFEDDAFDCFHBBCFBGDGCHECBEBBCABDAECAHAHHAHEBHDHHFAHGEBEHFAAGBAGBGGCAFAFBAFBDCDCCDGGDGBHBBCBGFGEEGECGEHECDFCBFGBDGCACEFGEGGFHGFDGF,False +263,0.0,1.0,9.0,1.0,3.0,4.0,6.0,1.0,CHCCEFCGGBGFDGEGCECCFCFGC,True +264,6.0,5.0,5.0,2.0,0.0,4.0,6.0,0.0,CCAGBBGDBGDBACACGAGGFFFAFBAC,True +265,4.0,10.0,10.0,7.0,1.0,8.0,4.0,4.0,BEFBDFGDFABCABCHFCDGBHBCAFCAFDBDBGGBDFCCBCFHCDHC,True +266,22.0,29.0,31.0,16.0,20.0,28.0,16.0,14.0,EHAHCBHCBECFGBBCHEEBAFBHHAFGBFDBFCBFCBFCBFCGFGECBBGFCEFBEFDEDDGFCFCAGCAFCEGAAGAACDCFGAFGAFHBGABDAGAHCAECABBBCFBCDEAAEBFBBFCCFCCFABFDDFBEHBFGEDBEDEHAECBGCFHCDECACCDEFDADEHCGDBHH,False +267,19.0,18.0,7.0,10.0,13.0,13.0,13.0,11.0,HAHCGEBDCBCBBEGHFGBCGAAGBGGFDGCAEADBAHBFEFFEAGEHCHHBAHAADEFGEAGFFEFAEFCBAABAABEAFGAEGDEDBBABBFBHHDDHDBFD,False +268,17.0,10.0,10.0,7.0,8.0,5.0,14.0,9.0,DCADHDGHAGBAEHECHCGADHCGAEGBEGAEGAEGACAHGHDCBGHBGFBCAAAACBBEEBGBCFCAFDAFDHFGABGA,False +269,1.0,3.0,0.0,1.0,3.0,4.0,3.0,1.0,GHGGEBEFBFABFEDF,True +270,23.0,19.0,18.0,18.0,15.0,13.0,11.0,15.0,AHDAFCAECAFBHBCEFDEFCEFEDAADBADCDDFDAFGEHGEAGHADBBEACFGBDHADGCCABHHGHFBEDGHFEACEFCBAGAAEABEABGABHBEABGABFCBACGDDHFCHBCHBHHCEDCDDCDBC,False +271,7.0,9.0,4.0,6.0,4.0,10.0,14.0,6.0,GDDGADGAHAAHABDGFFFECFBHBEGEGHEGDCABGGFFHFFHFBGABGDBGCBGFGCB,False +272,9.0,5.0,1.0,2.0,6.0,2.0,1.0,1.0,EDAEAFECFGHAABAEDEBBEBAABAA,True +273,6.0,7.0,5.0,6.0,3.0,4.0,5.0,6.0,DBGDAGHAGECGFBHFBGDDFEDFHCBBEHHCAHBACBACAD,False +274,13.0,30.0,20.0,14.0,22.0,14.0,15.0,16.0,HBGBBDCBAHEFEBDBCABCGFGEHGECGCDECDBFDECGHBFHACDCBBHEHGGHFGBBBBHBBHBBGBEABHDBGDEGEFDECCFHEBHEHGEFCFBCFCDABAAHEECEECEDCEDGEBFEBAABGABCBCAAFDAFDHFC,False +275,5.0,8.0,10.0,12.0,2.0,10.0,10.0,5.0,HGDDCDFCDBGFCGDBGEAFACFDBDDBHDBCDCCFGCHGDFGCFDABHGBAGCGFABFEHF,True +276,5.0,1.0,0.0,3.0,1.0,2.0,0.0,3.0,BDDHFAHAAHAFEAD,True +277,24.0,23.0,18.0,24.0,16.0,33.0,19.0,28.0,ADCABCHCAHCAHEADEAHBGBCGFGFFGAFBDFGFBGDEGDGHHGHHACDDGFFAFFBFFEFADHDDADDFFAFGBFBBFHFCHBDADEAHECEDFDGFDFFDCBBHDAHBBHCEGEBHHBFFCCHHHHCHBBHDHAGCAGEDEHDGHDAFAFBBFABFAEAAGABGFEHCCBCHECFEDFGFE,False +278,12.0,29.0,23.0,26.0,19.0,18.0,23.0,13.0,BEBBEHBCAFAHEDDCDBBDBBDAFFAFCADCGGBGGCGHCFECEBDECGEHGEADBFDHFDGCDGCBCCHDBEABDCBDEBEEBDCGECBDHBEHEAGAFGHFHEFBBDBGEBFHGGHFGFDGCDGDDCFFFDFECCGCGGFBDBAACHEDBDDBGCAGBBC,False +279,16.0,11.0,17.0,16.0,19.0,22.0,19.0,14.0,GFAAFDCCEGCHGBEGDABFBDFEFEEBEBGFCGHHHFHAFDADEAHACBFCDFHFGCDACDFCGFEDFEGADGAFCEHCAHBBHEGCDDHDCAFCAFGEEGEEFBEFEHAHFDEFDBGDBGAFCAGCGGCGHE,False +280,10.0,14.0,13.0,11.0,22.0,14.0,17.0,12.0,EHCECEHBFGCGGCAHCDGCGGEDBBBFHCFBFBBFGHGHFABEAEGACGACBFDBCEECDEBFEBDGHDEBEGGECGEHGEDEEHFEHFEGFAADGADEHDAFDHFEEFCBA,False +281,32.0,31.0,18.0,18.0,36.0,28.0,25.0,12.0,GAHFABEGCGAEFADGADFABCADAEBAEFEHFGBGCBHDAHAABBBECFEAEEFEEFEDAEBAECADCDDBBBCBBEDBFAAFHEEGFCGEEGEFGEFAFDABCABDAFGFBGFEGBEACGGHFGAFHBBDEEEGGBHGFFAFFGEFGEBGDCHCHGBBGABEABEFEDADCEEFDCDHCDBGABAACAHCEFCEFBEB,False +282,19.0,24.0,17.0,28.0,20.0,14.0,18.0,11.0,CEGDBCDFGFGCADCEEGFABEDBDBBDEFDEADBGBEGBACDDFDHFBHGGCGAEGHEGHECDDGDFGEFABAEEHDFBDFBEEBHCDCCEHHDCGDBHDFDDADDEEDBBBBABHAHDABAAGADBCFBCBECDAGECGACGACFABFA,False +283,26.0,21.0,30.0,21.0,22.0,23.0,22.0,14.0,ABEAFHABHEFEEFBHDAHFBHFBAFBCBGGHGDHFDHFBEBBACCAECAECACGBCFFEFCEGGACBCDFAAHABGDEGDEGDACFEGDEGAFAACCBEABGAFDCFDFFGACHCEGCFGABCHGAHCDHCDCCDCGABDFBDEDCGFFBFEACCDCHDGGCGEEAEBAGDCDDCEEB,False +284,14.0,18.0,15.0,12.0,15.0,14.0,12.0,12.0,DHBFHFFADGAHCABFABEEFDEAGEAGDDBACBCCBGCBEEBEAHEHCFFCEFCBCGDCGDEGHGGABADBEEBEHCHHDBEGGFFEFDADHAHBBDFBCCBGABCFHCFA,False +285,16.0,15.0,17.0,12.0,11.0,20.0,18.0,11.0,HGHCBHCECFEHFEGDAFFGFEGFEAFGFBGABDBBGBACBGFBECAAFDAHHFGGAGGAEGCBDBBDHEFGGDGEHAHADEADEFCCFCFADDBCCBCABHAFFCFGCFDCFACDBCGH,False +286,11.0,13.0,7.0,7.0,10.0,17.0,12.0,13.0,FDGFDGFHABDDHFAHBHFFGCFHBGAGFFGFHHAGHEGHCGBCECDECDBHBEHBEHCAFGABAFBGFBEFGEABFBFDEFAEAHEABC,False +287,8.0,6.0,3.0,14.0,2.0,6.0,4.0,6.0,BGDFDCCDGAFBADBDHHDHCDHAAFAADBADBFDEFABDGHEGDDFHD,True +288,13.0,9.0,15.0,13.0,19.0,11.0,16.0,13.0,GGEDADGABGCBHAGACCFCHECDDCBAFEEHEBBEABEACFACEDHEAFEGFGDAEAAECDEFEHHEHBFFDCFDCDAGDHEBHCGHGGHCEFCGFEGEDGDCGHBGH,False +289,21.0,24.0,27.0,24.0,13.0,22.0,21.0,28.0,EBFBBCGBDHCAHFAHBBHBDHBDHADECDCAHCGHGFHADHDCHFBBAHBDHECABFBFFCDFGDFECBECBCHEAHFHHEHGGFAGBDCEHCFHCGGBEGFHBFGAFCADDFDDBDFCAFCHFDDACGACGDCGAGGHDEDECDAGHBFABABBEFBCCDEAHGAHGCCGCFAHDGHC,False +290,11.0,5.0,20.0,12.0,8.0,15.0,4.0,7.0,CBCCHDDHADEADEFDAACCCFFDFCAFCADCGDFEDCECCECFFHFFAGFCEDEBFFHCHGCDBHGCFDAFBAEHACCACB,True +291,20.0,16.0,14.0,23.0,25.0,13.0,17.0,18.0,GBEGBEGFEGFBFDBFDBADHAFBDFGDEGDGGECCECAEAADAACHHHHBHEGDADDBHAAAEHEBDEBGEAEHDGHAAHFABCEGDFGFCECDGDABDHBDECCABFBEEDEGFEHFEHGAHBDCDAEHAECDCFDCEDHGHEC,False +292,22.0,21.0,19.0,22.0,30.0,26.0,23.0,31.0,AHGAHGABADGFGGEEAEFDCABCFBCGBCBHCBCFEDFEDHADEFDFBHCBHAHEAHEHHEHEBGEAGEDCEHGACGDCFCEFDEBDEBDFHACEEHBDDGGEBCEBCGHFGEABFAEEBHABGAHGAHDHHDHEABEGBFAEGHEHCADFFDFGAFCDDGFHFFGFFDEBCHFEGFCDFHHCHFBEGHHADH,False +293,16.0,24.0,24.0,18.0,24.0,17.0,14.0,18.0,BDDACEACHABHABHECHGHEGEEFCHFAFAGFBBBGBEECEEHEFDBDDBDDGCGBCEHCEDCBFABFBBCCECCGBEBAABHECEGCEDDECFECFHCFHCGBCFFDDFADFAHHCGBBBCAFEBHGDGADGAHCBEAAFGDBHHEDCEDFEH,False +294,32.0,23.0,12.0,12.0,9.0,21.0,14.0,23.0,BCGBDHDCGGGDAFDFFBCABCABCFGGFAAFBHEBHGBGGDAFAACABHBFFDAFAHHBHHDHGDEADBHGBHBBHBBFACCBECAAAHABHAEAEDFGCCEAFFHEBHFHHEHDABAAGAGHADAAHAACEAHAAFFBFFBFFH,True +295,25.0,28.0,34.0,29.0,21.0,15.0,21.0,21.0,GBBDDFEAEADECDAGBCFBADECDBBDCCGCAGCDBCBBCBDCBGCEHCGACACFBHFDDBCHFCGAGGECFFABDEGDEFDHFHHBBHDAEDBEDCDDCDDCDAADFACEDHHGACGBBGAGAEGFGGHCACCDHGEHGEHGHCEACBHFEAAEACEACHHCHBCBECHHFEBBDCBFCBDDBDABAEFAHG,False +296,10.0,5.0,3.0,10.0,3.0,6.0,4.0,2.0,FCDBCACHBFABDAGEAGDADEBDFDAFGABAADEADHGDFFD,True +297,18.0,24.0,24.0,26.0,29.0,26.0,24.0,26.0,HAEHBEAEEHCACDDCFDHFGCBHCBCDHFDEADBBGCBGABFAFGGHGEAGDBCCGCBDFDDFBEFBEGDEGAADHADHBHADHCDFEFFEGGEBAHBCFGCEGEBGBFGEAAEDHFDAAGHFGEEGEEDHECGEDFEBBDCCDBDECFCBBEFHFCGFEHHEHHAGHCEHCDFCDFCDHCHGGHFEFFBFHBADB,False +298,13.0,9.0,11.0,21.0,12.0,21.0,9.0,8.0,DDADBAGGAGEAGECGEFHFCCFBCABCABHAEFABFDFCHHDDEDDHADHCHABFFFEAEDCFDEGGFDDFCDFEFFEDFEBADFDDFBDFCHBGFCEDDAFG,False +299,9.0,10.0,7.0,5.0,4.0,5.0,9.0,5.0,AEBFBGFGGAGGADCADGDHGHEBHBBGEBGFCHBCHAAFAABCECCFDDBCAB,False +300,9.0,10.0,14.0,12.0,10.0,5.0,22.0,10.0,GBDGFGGEGEHGDGGEGCCGACBDBBDABDAEFABBCEAEHAGCFHDGHGGDGADGHGGBFCDHCDGCGBDAACEHCEGCEGDHCHECHCBF,False +301,23.0,15.0,14.0,8.0,21.0,17.0,19.0,20.0,FGCEGAEGEDHEDBGGECFFHEBBBFDAHHEBAEBHCHEGAAHABEEFEEFGBHGCHCAHDAFGGHGDHGFAGBABFAFHEEGEAAEDAGFAEFACFACBHFDCEHBAHCAHGAHCCGCCGEAGEACFADFHBBHBF,False +302,27.0,23.0,30.0,20.0,17.0,18.0,24.0,20.0,AACCCBGDBFHBAECFFHBHHGHAACGCHDDBFBGGCHGAFGAGGAGGAHGCHGCDGCHBHABFDBDDEEDEEDBCFCCFCHBHFBAFBDFHFBAAAFCCGHCDBADAFCABEACGBFBEEBAEHAEGAHGACBBDACDFCDGCDGHDEEDEBCFFCAACHECGCBGCEGCDAAEEHGD,False +303,30.0,27.0,22.0,22.0,20.0,20.0,25.0,21.0,FCHFDBBDBGCAADEBGFBGABGFEGHAHBADAEDACBECFFCFFGDBGAHHAEHFCAFAACEDCFFBEFAEABHDGAEHDDBGCBGEBGEAEEFBEBDHDAAACCHCCHGDAGDFCFABFHBFHBGBBDHBDHEEHECHDCADAEDGBCCBAGEHGEBGFBGCCACCAGAADAHGHHGFDABGGGD,False +304,29.0,17.0,17.0,22.0,14.0,23.0,28.0,17.0,DABGFCFHAEGAFGFBCCBEDDHFCADEHDEHGHDGADGHGGCCFFFFCCEGHEGBDDDDDFDFGDFGCEABADBCHADBGDCDAHFFBGFGGHAGHAGAEGEGCAAHAAGAAEBAGBGFBHBBHBGDCGFCDFBAEBHCFEAAEAAHGAHGAGFACFDCFEAFDAB,False +305,11.0,12.0,13.0,10.0,10.0,17.0,17.0,13.0,BFDDADEGGFGEFBEAGHAGBACAECAFFBBFHBCHGFHGHGFFGCFCBBAGCDGDDGCGHCBHDGGFHFFHGDECDFCDEAGFAFBAECAECHBHHEHCEBF,False +306,7.0,10.0,4.0,3.0,5.0,2.0,7.0,5.0,BHBHADABBABGABHDGHDBCEFEEFCEBCEHGGCGBAABGAG,True +307,17.0,17.0,13.0,19.0,19.0,19.0,22.0,12.0,FDEAAHFFBFBGFBDFGDFGDBGDBGFBFFHFFABEGGGHAAHEAFEDFCBFCEDCDAGBAFBGHDHCGHGDEGDGCBBDHGABCDHCFHEGGDBCHECEECEADEAEGAGBAEEDDEGCEGCHACBAFBDEDAFGAE,False +308,16.0,19.0,32.0,19.0,25.0,21.0,28.0,24.0,BCGCCBFCFGGDHGDADAACACGGBADDGDDGFBCHHCFECDGGAEBAEGHCDBCHEEHAEHFEFFEGFEHDCCCEGHFHHGBGDEGFHCFBFHBGEGFCGFCBHGBHEBEEBGBAGEEGHEAHEBFEBHCBGGDGDCHCCACCADBAHEDFGCACCHHCHHFBAFAEEDCECCDFCDFCDFEG,False +309,12.0,7.0,7.0,14.0,8.0,9.0,9.0,23.0,HFHHBHGACFAHHHHHDHBGHCEHEHCFHCBHDAHDAHFGDDHEBGFDDHADHBDGEEGDACDAHDAHCGHAADAECBEGEFFAFBDFG,False +310,7.0,9.0,2.0,2.0,5.0,3.0,5.0,9.0,BBABAGEAHBGHFEHBEHBHHAHBEGBGGBDACFCHFDHAAE,True +311,26.0,28.0,24.0,21.0,11.0,21.0,26.0,17.0,BFBEHBHGFHFHDDGADGADGFDCFBCHGFAEAAEAAEAABDDGHDBEDCCGFCFFCBBGGBFHCGGGDBGDBDEBCFBCABGDBGDFGEGCCAAHBGHGGFFBAHBAEGCFBCECHFADGGCECCFCBACBGBBGCCDAEHABFADDADDAFBHFCHAAFAABHHCHBCDBGA,False +312,23.0,13.0,12.0,13.0,21.0,13.0,8.0,13.0,FBAFBAECDHHEEEEAACADHEDAEAEFAEFAEGAEGAEAAEAGGBCDDFHAHHFFHFCCACAEFAHFAECHEAEDDHDGBBCBDFEHEAHBAHBAGCCDDDFGEGEFBBDBBCCB,False +313,3.0,1.0,2.0,0.0,2.0,1.0,1.0,1.0,HACAACEFGEB,True +314,19.0,17.0,14.0,10.0,16.0,21.0,10.0,13.0,AHDAHEEFAEAGCADFEHCEBCGCCGADDADFADFAHAAHFEHFEHFEFFCBFEBAAHEHBEBCCGHEBHCBFCFFGEAHEACBABBABFFGFFGBBBFBGDGCCBEDADAFBFFCHEDG,False +315,3.0,8.0,4.0,7.0,12.0,10.0,4.0,14.0,DHEDBEDBECHEFFFCHDAEBAHHFHFEGFECEEDEGHBGFBAHBHEBEDCFHHFHFDHGBH,True +316,19.0,13.0,26.0,20.0,13.0,13.0,16.0,14.0,AFCBGBFCAFCEECHBBAGCDGCFGHEBHEDCCAHCFEAEDDEDAGCAFCACCADCGDEBFAGDHGDCBACHAGHBFHCGECDCAGCADADFGDCGDGEDFADCADFFDAEDHCCHCBHGBHEBFGBCABHHDE,False +317,16.0,18.0,21.0,25.0,22.0,16.0,21.0,17.0,GDDGDDEDFEGFEDEEDHBDHBCHDHBBBBBBCCBCCHFCHBCHEHADGCDGCBGAFABCEDFFAEBCHBDDEADCGDEFAEGAGCCDCCGFDFBDHCGHGAAFEADAAHEBHEAHFCCDCEAHEAFGBGEBGDGEFGFHGEHFAFDGEDGECEDG,False +318,23.0,22.0,20.0,24.0,12.0,20.0,16.0,25.0,AABCHBFHCDHCGFGHDHHFGAGHBGHBGCEECAEHGBCGDDDHCFHGBHGBHEBHDCCAHCAHAHCAFCDFHHEBDDBGDGEABBAEBCDDFDDFEDFACFABFCHHCHHGBFAEFBCGBDHFDBFDFDAADAFDCEHCBBDFAAAAGECDABDAEFABFG,False +319,9.0,5.0,11.0,3.0,6.0,3.0,10.0,12.0,HABHDEGCCCDFCBHCHHGHAGHCGHCDHCEGCGCEGHEAHFABAECGBBAAFGAEHAG,True +320,31.0,18.0,28.0,29.0,18.0,25.0,23.0,22.0,ADEFDADBAGBEGHEGDCAHAAHCFGCHGFEGFHGCGBFDAFDCFCEBABHDBAFAFFDGDAAHABGGCAFCACCDEBDCCGCCDCCAFGGCHBDHGCHAHBBBBBCCGAADCBDEFDHCAHCHHFHAECDCHDGHDEADEDFADBADEEDGCBGCBGDGEFHAFEAFAAFGEEDCFDHFAHFAFFAEFHEDGD,False +321,11.0,11.0,8.0,16.0,26.0,18.0,18.0,26.0,HFGEAHHHHDBHGEHDFAGGDEFDEFDEFAEFBDFHDEEDEEBGEHEHHEHACGGEBHEGHEFHEHAEGFDGDDGBCEAEGAECDHCGHFEHGAGFCHHEHHFGDFEFFHBFABHDGFFBCEBAECGDABDHBC,False +322,6.0,3.0,4.0,2.0,1.0,1.0,3.0,2.0,CAAFAEHAGBDHCDBCGBAGCA,True +323,10.0,11.0,20.0,18.0,16.0,14.0,16.0,14.0,FCGBEHDGCCHABGBCGACFEFEEFEDCCCBGCFHCDAGDAGDEDFHGBAGEDFECGACGEFGEFEHCDHCDEFHGBHGEFDEFDEADBAEHFCBGCHDCHDCBDCFHBDABGAHDHCD,False +324,14.0,16.0,12.0,17.0,15.0,23.0,16.0,14.0,HDEBDGFAFHDDHDHECHEBHGHEGEGFADHGEFGDFBCEBGAFFAGFHBDHGDCGDCACFECFEHFAFBCEHCFBEFCEADHABCBBCFBAFAGFAEEAGBBECBDGBFGHGBFDDFDDFGAFDAF,False +325,15.0,13.0,7.0,9.0,15.0,10.0,11.0,11.0,BDABDCBEEECAECHCFHBBHDHEAHEAGEDEABEDHEGGFGGFEFBEHEEFBHAAAAAADAADFAEFGHHDFHGAGBBBBCDCGBFGFCG,False +326,18.0,22.0,21.0,20.0,18.0,16.0,22.0,11.0,FAHEBHABFAHGAEGHHBBBCBGCBECAAGDACFBCFEHGDHDDCDDFFCEGHEBHCFCDFCDGCHBAGCEBCBDGBDCBDHGEFADGEFABFGCFCDBCGACGABFACDEDEBDAFAFFABGEBGEGEEDEGDAGAGGEBGCBDCED,False +327,13.0,17.0,20.0,5.0,21.0,19.0,14.0,10.0,CACCAECGEGAFABCCDFAFFHFCEFCHAHBGEECEECGEFDECDECEEABFBEAEEBEDHCAHAADBABFGFFGFGGFBGBHEBHGFGEFBBGCBCCBCBECBCGFEHFHBGHACEFF,False +328,21.0,20.0,17.0,13.0,23.0,15.0,20.0,19.0,HECGCCHADAADGADBEGBEABEHFGFGGFGCBECFHBAAEAHDFHFFBGEBGCBFHAABAABDCBDCAFAAHCGDCGEEGHGDEGCHGHBFHDHCDBCFEAGCAHCEHEEFEFBDHHDEBEEDEBGGAHGAHBEFBECEFABGABEC,False +329,24.0,23.0,29.0,30.0,30.0,21.0,23.0,19.0,HADHFBHFEHCEHDHCDFCBABEEBDEHDACBGDBCDBGDBADCCDABAGCEGBDGBEGCDFAFFGEFGAGEAGEADCGHGBDEDAADEHBAHCAEGBGFBFHBGEBDBBAEEDEEFAEDGCABCEDGFFGECCDACHBDGBDFCHECHECEACEADDDEDFADFAFHCFGCADCEECFCCFCCAEBGGHHCHFDHFEG,False +330,7.0,6.0,9.0,9.0,7.0,8.0,16.0,10.0,HGGAAGEEFBEDHFDAFBAEDFGHFAHGDHEECGHCGCCACGFGHFAHEBHCGGCBGDHGDCGDCGBGDBDF,False +331,15.0,22.0,24.0,18.0,22.0,22.0,16.0,24.0,ABAFBECDEDAHCCGCAAHHCHHGBBGBAGBDGEDEHAECACBBFHHEHHEHHFHDCHDCBGFHFFHAEBFEFGDHAECEECBEFEGCCFBCGBCDEGHBGHFAHFGDBGEAGFADCBCCHCFFDEFEEFBEFHEHDCDDBHDBGFAFFBCCBCFBDADCGDE,False +332,9.0,18.0,16.0,12.0,7.0,14.0,10.0,14.0,AADCABGADACDAEDCHGCBFHBFHBEHGEFGHGECFBCDDGDAECHBCEBCFBCHHFDHDHHFFDFBGFGHBGECCFDFHDBHGBCFFABBACBCBBCB,False +333,24.0,10.0,12.0,14.0,8.0,11.0,24.0,18.0,AHAAHAADADGFHEEGBECBDCEACAHEGHEFHADAADFHGBHGBGBCGAGADGADGAHCAHFHFGEGGBACDCCDGFGBHCFGAFGBGEHACHAGGCDDHDAADGHDGFCGAHBAHBGFF,False +334,17.0,19.0,16.0,21.0,12.0,28.0,7.0,21.0,BCEAFGACAHCFEBBDBBDFFDBCDBFDFFDHFABDGBDFFGFDHFCGFGHCBHAFCEFHHBHHAHFADFBFCBFCBDCHEHDCADFDDEHDECDFCAFAAHABFBDFHFCDGHDHHCHECBEAEHAEFABDEFAFBGHEA,False +335,5.0,1.0,17.0,8.0,5.0,13.0,6.0,9.0,HFEEFACCHDCHDCHFBHDDCACCFCCGCFFDEFAFGCFHAEGFEGFDCCAFCHCGDCGDCHFH,True +336,7.0,5.0,7.0,10.0,4.0,6.0,4.0,9.0,CABCEBDDFADCAFCFGCEGEHDDBFGBFHCHHGHHDFDEHDAACAADHBDH,False +337,17.0,14.0,20.0,15.0,14.0,12.0,26.0,25.0,FEFFADAGDAGFCHHBHHBAFEECECAFCDFDDGGCHGCHFCGDGGBBGDAHDHECHGCBBBHDEHCCHFGHFCHBCHDAHCAGCAGEBHEBAAACEECEGGDHCEBFEHGHCGHCGDABAGHGGBBGFGGDGHHEHDDAAGA,False +338,17.0,17.0,8.0,23.0,13.0,10.0,15.0,13.0,DFFDBGEBEBCDBFDBAEEAFGAHDDDBBDEBGEBGBAGBGBCGEDEAHHADHDDHEDHGGHADDBDHHDCHDAGAECADCHDFBBFABDAFCAGDFFCAEGAEGEFGBDGCHAHA,False +339,18.0,24.0,23.0,25.0,16.0,22.0,30.0,24.0,DGBDGDDCDGCBGFEHEAAFCACGBFEBGCGCABCAFAGEAGEAHDCHBFEGHEBDDBDDBGABGFDGFBHCAEEAGDHEHFEFEHFGHFBFFGCAGCACCDHDDHBDFGDFGEEGBFDHHBCHDFFDCCABGBDGECBEGGGHDCHACHBHHGGHBGABDABHFCHFHHDBABGFCGFCDC,False +340,2.0,2.0,13.0,7.0,3.0,3.0,2.0,4.0,ECCCDCCACCBDCDFCDGAHHFEDFBDCDCCHGCHE,True +341,4.0,3.0,4.0,1.0,4.0,2.0,6.0,4.0,GAEGBCHBCFGAHGAHBACEECEGHGDF,False +342,10.0,14.0,13.0,18.0,10.0,15.0,4.0,7.0,BFBBADBAGACCABFAECCFCCEDEHDABBAFGGBDBCEBFDBFDEHDGHFAEECCDCCFHBFDEDDFDDCDDEHDEFFBDFBDFACHAFH,False +343,2.0,3.0,3.0,5.0,8.0,5.0,2.0,1.0,EAFDCDDCHEBFEFDEFEABECBFGEDGE,True +344,16.0,17.0,10.0,12.0,19.0,14.0,18.0,24.0,DGDFEBGECFCBBGFFEFHEHBEHGCBACBEGFGGHCBHGBHAEFBFFBHHBEHAGAADFAGFAHFAHGACGAEHABFGEGHEHHEHCABDAHEABCDHGEHGAHDDHDDBEFBGDBADGCHECHDHEEE,False +345,12.0,6.0,8.0,11.0,11.0,7.0,6.0,8.0,EEABBCDDGADCAECADHABGABECBECFEFFECDEGHAFHDGHFHAFAABDAHCEHAEHFDCDEGDGD,False +346,14.0,12.0,14.0,18.0,13.0,23.0,16.0,8.0,ECHBFBAFEFGCCDDGFDBFEGFEAFECFEHFEGBDDCHDHAAGAAGFBDBGDADDHGDCFFHEEHCEBGDGCFECFEBFDACDFGDAGDGGCGBABDCBCBAFFAFFAFEAFDHFCG,False +347,13.0,9.0,9.0,6.0,6.0,16.0,14.0,5.0,GEACFCDFGAFGAFCFFDDGGDBGDEGBAAHGAHFFBFFEEFBFFBFCEGBGGCECCAAHAGHAFAAHACGGFBCBBD,False +348,2.0,2.0,2.0,3.0,4.0,6.0,4.0,5.0,EFGDDADHEFBAFECFECFHBFGGHHGH,True +349,25.0,25.0,26.0,14.0,12.0,22.0,23.0,17.0,GCCGCCGEEDFADFDCCEHCBHCBGBBCBFGBAGFGHBGABFAGFBFFACCHHFHABAABCABGHEGBCGBFFAFGACCDDCBFGFAAAAAEACEFCEFCADCAGHAFABFDGADHHGBBCHGEBGCBHCBFDHGHHCEHBBBBEFAFHDDGFDCAGCAGDEDE,False +350,26.0,15.0,7.0,12.0,18.0,16.0,17.0,8.0,GFECAAAAAHFADABEGCECDGDAGEABEGBGBBGBBGCHEFFDFFAAAGEAFBAGDHHFGGAGEADFAEEBEFCGFDDFGDFDBFBEHHAHEAGEABEABEBBADAADAFFCEGCHAE,False +351,19.0,24.0,27.0,20.0,25.0,23.0,28.0,19.0,HHCHFCDGDBGDFGCBGDFGBFEDFBGABHABCABGBGAHGBHGBABCCEEBDFGDHGDBGHFGCFGCBHFBHECGCCBCGBFGACGDCHEEDFBGABFAFFGHDAEAAHDAFDEFDEDEECFEGHECAGCECCFCBABFADCAEGEDDFHFECFEGABGAHDHECBACDGHEEEEHECBECGFC,False +352,11.0,14.0,21.0,19.0,18.0,15.0,12.0,19.0,CGFBDFCAEDFEHEHCEACEAEEFGDAGBACBFCBFABDDGHDEHFGADGHDHCBHCEHCDHBBEFGFBADCGBHEADECDCBDCBACBACBDCHFHHCHFDGCDECGHCEEGHEHFFFFGEHDCHDED,False +353,14.0,12.0,11.0,22.0,22.0,10.0,7.0,14.0,BDEBEHDFDDCDEADEHCFHCAACAABBCDBHHEDHEFBAFDACABGEEDEADFADFBGFAGCGHCFEAEDGDDFDEEBEEBEHHEHHEDEEBHHCADCACHDDGGBFEDDE,False +354,25.0,23.0,25.0,17.0,15.0,24.0,9.0,25.0,FHABBAFCCFBCFBEDDHCHGBAEHCEBDAADFADFHFHHFHBFBCHBHHEHDACDFFAGBGDEGHHGDDCCCAHCEECAEDECFBBHDFCEFBAHAAHAFHAFHBFAAFAGGACEAEDAFDHEGFCFFCDFHGFHACHABBABECCCCACCBBCDBEBBHDB,False +355,17.0,20.0,28.0,20.0,27.0,26.0,18.0,20.0,FCDHEAHEGECAEDAEFCHFEFCCCCBECHEHEDHDHHEGHEDFEHAEDGEDGEFEECECHGCDGCBEDDEDDFDDBGGCGBHHAACABGGBCGBCGDCFHCFBCFBHFAHFEFFCFFBDACFCHBHEEFBGFBHFDGGCECAAFACFBBBABBDBEHCAFFEGCADEADFFBCGA,False +356,11.0,9.0,19.0,9.0,17.0,23.0,24.0,22.0,DCFDCHHGFEAECFFCFFGEFGFFGAHGBHAADAACEFFGGEHCAHCBDFFDGGHHBFHBHHAHFFGGFEGFCGFCHCGGGGEEEFCDHCDECHECEBCFGCHBCHAEHCEGFDGCHBEHBGHBGHFAEAEGGD,False +357,15.0,19.0,23.0,15.0,30.0,8.0,15.0,12.0,EDGEGBEGAEFADGHEFEEDEDDEGGFDAEEAGDAEEADEAEBBCFBCGECBEGGACEFBGDHECHEAHEHGGABCEDDFDDEDBHDBCBACACCGCABEGHCHCCBCCAFCHBEHEHHCCBCEBCEBCEBFBBECA,False +358,8.0,10.0,3.0,16.0,6.0,11.0,10.0,8.0,EADHDFFDBFEGFGCCAFCBHDGEDHDDFBBFEBHHDAHDHEDHGDAGDAEDGDGFBGABGFDGFABBADBF,False +359,20.0,14.0,12.0,8.0,11.0,4.0,10.0,13.0,BAHGAEDBEDCADCAHBABAAFAACGBHGBHABHEHCCHBCGAEACGDCADCHGAECADFAEBDEHFCHEAADHAGHFBEBCEAGEBGBGHB,False +360,26.0,15.0,17.0,18.0,13.0,10.0,21.0,9.0,HCBGGBGGBCCDDCDCCHCHHEGGEAFEDFAGEBDHBGAFGDGAABCADCEGCFGAEABEADHABGAEGFEAFAFCACGADDBEAGAABAHGDCDEADECDBCDBCBHCFDDFAGAEGAHGAGAAFBDB,False +361,15.0,32.0,16.0,34.0,25.0,18.0,29.0,23.0,HDFHFFDABBBBEEBGEBGEDEEGAHGBGBBHDAEGCDACHECHBGDBGDBGDGDDFBGGDEBFAHHHHEHHAHDADDEDBEBBHABHAFGDDBEDHEDHDDHGCHCEFDGGDGGBCFCCFEHFGGFHAEDFDFFCAEGABDFEDGBAGBGDBCFBCHEDADDCDCBBBDEBDEBGHCGBEABFCGGEFCEG,False +362,22.0,28.0,20.0,25.0,21.0,16.0,11.0,16.0,BHCHFBFFBDDBHHBAHBADBAHBAHGCCFCBBDBBECAEFEDHHBCCFDCBBBEBHEBFGBHGDHCFFCFAHHAGAGDBFDGFDBCGEADBFBBAAFEDGEDFDAAGBAGAABEDDACBECBEFDAHCCCCGCEEHAEADEDDEDCEACEAEDDEDDE,False +363,11.0,11.0,7.0,6.0,9.0,8.0,12.0,8.0,FBADHHEHFGGCGAFEAFEGFGGHGHCCHCCBCABAEBAHDDCGFABEABFABABDEBDBHAGGFBGEEGDE,False +364,5.0,2.0,8.0,2.0,1.0,2.0,9.0,6.0,AHGACBAGHCGHGBEFDAFGACHCCGCDGCHGHGC,True +365,33.0,17.0,16.0,24.0,25.0,19.0,21.0,11.0,GDDGDDGBDBAABAFECGEDGEDFAGCACCFHCGHCDAADBACFCHEDAEHABGGHCEEEBAEFEDFDCFDHFDAFAGFBCDAFGEDDEHBEDBDCBHCAGFHFDACAGDABEABGABGAHCAGDAFFGEFDEFGFGEEEAEAAEAAEAEFBBAHBABCEGEDGAA,False +366,24.0,28.0,22.0,9.0,23.0,15.0,15.0,17.0,HEGHECCBBCBBFAEDHBFCBFBBFABGEGCFDCHCCBAAHAADABBBBAECHECEEHEEBAECDDAGDFGDFCDCGBCEBCABEABAAEHGCHEFHEDHFGGAGEHGCBBAFBAHCFEEGAEGABAABAHFHBCCCEHAEBBEGCGFFBHFA,False +367,22.0,19.0,28.0,25.0,31.0,21.0,23.0,26.0,HGHDGHDGEBCDDCAEEADEDEEHAHBDCEEBEFGAHAADGDHBHFCEGEDBFDEFEEBEBCEFCEFCBACBADHADEGDAHCCEDDEDHFAHECDDCBEFBEGBDCHCHAABAACCHCCHCDHAGCAGEBEEAFECHBCHGCGGHFCFAGGEDAFDCBECBEHDEFFGFDGFHGFGGFGFFBFHBCCGAGHAHH,False +368,19.0,23.0,22.0,14.0,18.0,18.0,13.0,20.0,GAHHDGFBGDBFFBHGADABEHCCFDCBDAGDBFBBFBBFBFFEFFAHCAFGAHADHEBFBAFBECCEBCDDAEDGEHBBBBACBAEBDECHEGFCHACFDBGCHHCHGEHCCHCGHCGECEAGACHFCHFCHDEEEEEBDACAAHA,False +369,8.0,9.0,10.0,4.0,11.0,7.0,17.0,8.0,GEHGEBGFGGFCGEHAFBBFCBHCFDCGEHAEGCCGAEGBBCHBHFEAFGBCGADGADEADCGCHGEBAEGHEG,False +370,14.0,14.0,22.0,16.0,19.0,13.0,17.0,12.0,AEAAGFACECCFHBFDEGEAGADCEHCECCADHDEGFGGCCGBHGBHGBAFDGECGECGHBDHBABFACDDEBFECFEFFCAFGEGEEGHGCBACBCBDABCGBDFEDEDDHDFBDHCCHCCHEADE,False +371,24.0,19.0,21.0,13.0,20.0,18.0,17.0,23.0,GEGEADCDGEHBDCBDHAHCEFCEFEEFCDFBEGAGFHGFCCHCCFFCFFAADAFCABBBHGCHDHEAAGCAGDABHHCHHCHGBEFAAFHAFHGHHGDADEABEGBCGCDBADEHHEHACDABGECFEFEEABEBBHBBABCAGCFGEFABHAH,False +372,3.0,3.0,3.0,4.0,0.0,2.0,1.0,2.0,DDFDDBCABHABACFGCH,True +373,11.0,27.0,14.0,16.0,27.0,12.0,14.0,25.0,BGEGGBDBADECHGHHEHADHDGAEAHEFHBFHEEDGEDECBHFEHEBHDDCEABEAHEAHEBEEBEGAHCHHCBBBBBBBCCGDFGEBBEFHFDHFDHFDEFDEDEHGEAEEFBBHBBADBCBCCBGFDGHEFABBGHCCCGCHH,False +374,3.0,9.0,10.0,10.0,8.0,7.0,11.0,11.0,GCGGBBHHCCGFDGFDHDDHFDBFEGEEBECDDAECCBBCHGCHGFHADHACBEFHEBHDBHDGGFGEC,False +375,23.0,33.0,18.0,22.0,30.0,18.0,26.0,23.0,EBDEBDHHGCCGCFGADGBCGHCEHFEHDEHBEGDDGBHGAHDAHDBCBAABCFBCHEFDADCAEBBBBHBAFBAEBAHBHFBCAGCFHDADEAFECEECEFBBGGCCGEHHBBHEDCAFAHEEFFEAGABGCDGBBGBDFBDFGDBEDBHFBGDDGAEBAGAFGEEBEECEABEHGGADGDGFHGFEAEHHE,False +376,26.0,12.0,16.0,23.0,9.0,18.0,21.0,30.0,ADDFFDFFDFFHCFCBFAGFBGHEDHEAHECHCABFAEAAGAAGDDDDCFGCAHABDEGFHBCBCADGHDGADGHEGHDGHFBHGDHCDEABHGEHBDADAACHHHHFHAGHEGHDGHDHHCCCAHDHHGGFAAAAFABFHCFGBHGAACBGCDD,False +377,14.0,10.0,11.0,6.0,8.0,8.0,6.0,11.0,FCEFBBABDCHECFBCGBHGFHECGCFAFAEFDBACADCABCHHEAHGAEBAHAAHAAGFDCBDCBDGAEHHEH,False +378,10.0,13.0,11.0,8.0,10.0,9.0,5.0,12.0,ADCHBEECEEADBACBGBBAHBGHCCHGBHCCACCFHCDBDDFFDFFBFEAEHABHDBDAFHECBAHEGHEGHEFBAF,False +379,26.0,14.0,13.0,28.0,14.0,24.0,18.0,23.0,ACEAFGAGABGAGGEHAFHDCDDFFCGHCDHAAAEFFEGABGAHHADFGDFBCAGCAGBACDDDBDDEADCCHGEAGEABHHFHCCBDABHFEEDGHBGBBHFDFCDFBDADDEDDEDHFDHFDHEDHAAFAHDGDBGEFFABAECAHHFFHFFHDFHFG,False +380,21.0,15.0,24.0,10.0,21.0,16.0,24.0,20.0,GBFFDHFBFGEFHHHHHECHEDEEBCAFAABGACGBCAECBCCBEDFCDGCEEEAEGAGGACDAFDCGBBGBBCAFFDFHBAGGDGGCCHEAFEAFCAFCAHCGGAHCACCAEGHEHEEGEEGDCHDHHGCEGAFHHEHACBCFGHBGBAG,False +381,15.0,21.0,27.0,23.0,28.0,27.0,27.0,20.0,BCBHCAFBBGEBDEDHCDGCGGCGDCFECDECEBCEBFEBFGCGGBGABFAEHCFDCHEGEFFFBGFECCEHCGFFGFHGBECCFCFAEDAGAHDAGEFFFAFDACCHCHBBHFCDAGDHGDEGDBDEHDHHFHFBHDBFDEAGCADBDDBDDEEFEEAGEGGBCGEFEEFDGHHCHFEHCAGGABCE,False +382,0.0,4.0,3.0,2.0,1.0,1.0,2.0,3.0,BCDBHDBHFEHGGCBC,True +383,1.0,2.0,2.0,6.0,6.0,2.0,4.0,2.0,CHDAEDGEDCEGEBGEFDEDGHDFB,True +384,12.0,14.0,12.0,10.0,21.0,16.0,19.0,20.0,GDHEBFGHDHCEABECBDCAHGAEGCEBCEHDEAEBHEBHFHHBBFFAFDCGHAGDCBFHGHCADBAHBGHBGADHFCHFDHCHECEECEGFEGEAGEGGEBFEGAEBAFFFEGFGGDGHFEHF,False +385,9.0,9.0,5.0,9.0,10.0,4.0,7.0,7.0,BCCBABGHBGDEGDACDBEFBHDGADGAEHHCFCEFDEBDBBDAAEEAEHADAGEHGFHE,False +386,15.0,9.0,11.0,11.0,15.0,15.0,12.0,13.0,EGCFFCFGCFHFDHCHCCHACHECAGHFFABEAHEFHEDDEBDHBDHBECDEADGFGFBGFAGFAFAHEEEBDCDGEHGAGGABAAGDFDBEABEHECFAA,False +387,17.0,16.0,9.0,11.0,9.0,4.0,15.0,11.0,DADCFEBAEAGCBBHBEGBDABFBDFDHCAFEGGEAGEACHABHAGHDGHBHHBGDEGHCAAGDAHACEGBBGABAACGACGBDGBDHBDCE,False +388,10.0,3.0,8.0,5.0,5.0,8.0,6.0,3.0,BDDGGCAECAFGAFCACADCEGCAHCADCBFFAFFHHFADEGFEGBEA,False +389,17.0,13.0,28.0,32.0,15.0,31.0,24.0,29.0,HGHCCHGBFDBGAAAAEDAFHHDEGFECFHGFCFFEHFDHGDCCFCHFCFDCFDGEHBEHGHHAACAEDAHDACGEGFEBHDHCFHEFHGFAGFACDACBHCDHCDCCDEFDEFDHFECDHDDCGDGBBCCFDHBDFBDFCGBBHAEHCDGGFHGHAGFBDBDCGFCGFDGDDFDHGHAFFAGDCEDCF,False +390,23.0,24.0,19.0,26.0,25.0,15.0,25.0,27.0,FADECFEGAEGHCFDCBGCBDDHDDHDDAGAHHAEBAGDAHBHGBFGBGGFGDCADCBHBEHDEAEHGEHDBHGBHEBDGBHECAEDADDAEHFFHFHGGCCHHEFECCGDEACEHHAHGAFAADBBDCBGABDACCADABFABEHFEBEEBDDACDEEDGGGGBHGBHCFGCFHFBHCBEGEE,False +391,4.0,5.0,5.0,5.0,10.0,9.0,7.0,10.0,FGGFGCEGEEHHDHGDCEDAHBFHFGDFEBHBHHAHFCCFACFGBFEEHEEDEAB,False +392,2.0,1.0,3.0,2.0,5.0,3.0,4.0,3.0,FBGCCGDCAHEFHFDHAGEEGEE,False +393,32.0,34.0,23.0,23.0,23.0,22.0,17.0,26.0,AABCCBCADCAHAAEFAFBABBHCCFBFGDHDHCAHFGBBCCBHCBHBFCDFBHBEABEAGEDGECBEBHEBAEFHEBEBDHAHHBGCCFDDFDFBDHBGAAACEACDACHADFAGFAGFHGFDFADFAHEAEEBEAGDDHCDEFDBHCGGDGDAHABHEBHEBEEBEHFABAHBGEBHCFDGFGFEDADCACHACBGBB,False +394,10.0,5.0,5.0,10.0,12.0,9.0,5.0,11.0,DCDEADHACFADFADABDHGHHDAHGAGEEBEFFCFAEDAGBAEBCEHDBHFFCEFHEHHEGEEDHF,False +395,9.0,8.0,7.0,6.0,6.0,3.0,2.0,9.0,BAGBECDECDCHEAHAFGBFHBAHDHHAACAACHHFHBDDBEEAEDBCCB,False +396,28.0,25.0,16.0,17.0,19.0,17.0,23.0,14.0,FBGFAAAHBHHGFCGDGGBGGEGGEFCEHCDGBBHEACEGBEADCADGEGHDGAAAAABFABFADFCCBHCADEFGEDDBDACAABAAHHHFACFBDAADBAGBGEHDEDBBFBBFBBCEAGEBHEBHEBEFBCFECFEGDGBAGDACDHCFCFGAGAE,False +397,11.0,7.0,11.0,10.0,5.0,9.0,10.0,7.0,BCHBAHFDBFCHFCDDBHGAGCHGCGGCGGFGEAEECDDFADEBFCHDCHBGABGEFDCFDFAAADAACA,False +398,21.0,30.0,21.0,28.0,27.0,13.0,18.0,24.0,CBDCAGAAEHGBHBHHFHHAHHCGHDBDABFBEHDEBCEDFDCFDCFBCEDCBAEBEDBEBBABEDGFBGFEEAEBGHBGCBACBDCEECBDCDDCAAGDGEAGEAFEGEEBEHFDHDGCEBFEBDGDFHAFHFDHECHGCDGHEGDBDBHEBHGBDAAAAEADDDCABHDCHCEHCHGBBA,False +399,8.0,12.0,5.0,5.0,7.0,5.0,5.0,13.0,HHGHBAEGABBCBBCBBCFBCBHADAAFBAEBEBFHDECEEFHGAHGHHDFHDGHAHHED,False +400,7.0,6.0,11.0,5.0,6.0,14.0,10.0,3.0,AEFAEBCFDCFCFAEFCGGCGECHFGADCBDFGCHCCABCAGGEFHEFGAFBFBGFDGFDBF,True +401,5.0,2.0,3.0,1.0,8.0,3.0,7.0,1.0,BAGCFGEEAEBHEGFAGFDGEEGECAEGAC,True +402,7.0,14.0,22.0,10.0,18.0,10.0,12.0,15.0,GHECCAABBCBBEEBEGBDCEECFGGHCHACHAHFBGGCCCCHCEFCFDCHDCHDFHECHACDBCBAEBDEBDGGEGHDCEGHECEECEEHBEHDFBFBAFHDFGFCG,False +403,14.0,14.0,19.0,22.0,20.0,22.0,14.0,19.0,ECCEDFDGEDEEBCBHDAFBAFAAECCFDCEBBEBDAHCADCFDHEBFEDFEFEGFEAFHAFHGCHEEHDDFEDFDCFDCFCBAHFAHFHHFBDFDDEHCGGBGHBAHCAGCEGAHBHCGCEDEFDFGDHGFCGBBGCHGHDDA,False +404,9.0,11.0,17.0,12.0,11.0,7.0,12.0,10.0,BCBDCEGCECEGCDCCDGGAHGEBGBHCFCAFHAFHADEAHFDHEBCCDCCDCBDHEDHADBAHCHDDGBEGFGGBECFEFEGBAGCAB,False +405,5.0,5.0,3.0,4.0,12.0,4.0,3.0,6.0,DBGAEGEEDAEHAEBBEBEEHFDCBEFGEFCAFCEHHAHEDH,False +406,15.0,17.0,23.0,27.0,15.0,22.0,16.0,20.0,EFCEGEFDBFHCCACBDDHDCFBHFHGFCECAEABGBGDHCDBCABGADFDDFECCACFAEFHDGHDBHDAHDHHDHBFEFDEADFADBDCHDEHFCHFGGFHGHHEAACAFCFBDDCEBCGBDGDEGDBGDHFCCFDEHCBBCBGDFGAFEAGC,False +407,11.0,16.0,12.0,20.0,16.0,15.0,13.0,15.0,HBGBDGBDGFGEFCCHCDHCDHFFCDBCFBEEECEFCEABEHDEDBEFHFDAFDBHBBHDACAHFAFBAEBDDDADDAFDGGGEEGHEGDFHBFHGDBGCBGBACDAHHCEAEEDHGF,False +408,16.0,12.0,20.0,13.0,15.0,13.0,22.0,14.0,HACHAGEAGFHHDDCEDCBFEDFEACBBFHBFHBCGBCACCBDDGDDBEFEGGHDBDDGGFHGAHFEGAEACDACGABAAHEABECECCECGGCAHFAHFGGFEECEHAFDGGGGCFHCGGCGBC,False +409,4.0,7.0,9.0,5.0,9.0,7.0,4.0,6.0,EFCBHCFAFFACFDHHBHCBGBBGBCEHGECBAGDCEFCDFCDEEHEEAED,False +410,12.0,11.0,9.0,6.0,6.0,6.0,2.0,5.0,DDCDHBBABBACFACEBDEHDHBFBAFBAGCAEAEEFHCBCCFHCAAEAABDABGFC,False +411,10.0,13.0,4.0,12.0,8.0,3.0,7.0,11.0,BBHBBDDDDDEEAAHAAHBAHGEHGHHAEDEEDACDBBDGCDBBABHHCGCFGFEGBAGBFDDAEHBH,True +412,2.0,7.0,4.0,0.0,2.0,6.0,5.0,2.0,BGBFGBFGBCGCEACFBHFEABHCBGFF,True +413,28.0,23.0,16.0,19.0,25.0,12.0,17.0,19.0,BHADEAEEHEEAGEFBBCDDAGHHGHAEBDFBAFBAHAEHBECBDCGDGBFGEEAEEDBDDBHDEHGECAACGACABCABFABCADEAHEDBCGFEBFEADEBEGADAAFAFHADBACHABHCCDCDBFABGAEGCGFHACDEGHHGHGDHFBHEBEGC,False +414,4.0,13.0,10.0,10.0,10.0,2.0,11.0,8.0,EEGCECCGBBGBCGDEEAGEDBHCHHADHDBHEHCFBDBGDBDDBDEADEHBCAGCBGEGCBGCBGFH,False +415,13.0,21.0,20.0,13.0,22.0,19.0,15.0,24.0,HFDBGDBHHBCCFHHFBHFBHFBHACEFEHFCBGBBFBHFDGECGFCAABGCFGCHHBHHEGFEABCBECEECGDCHHFEDAHBAEEDECDHDGHFGHFAECAFBAGBDECDCHBHHDCEFCAFEHEEGEAGEAFEDEBACBDCBGG,False +416,21.0,17.0,11.0,9.0,12.0,14.0,19.0,7.0,CGHHGBDBAGBAGBDGACGAHFFBFAGCACDAGAAEAEFCCAEFBCFGCAACGEFFBDAEDABDCEGEFCEBBHFBHEBHEAGGBGFAHFEBFBBDABFAGGAGGDGADE,False +417,6.0,8.0,8.0,1.0,1.0,6.0,7.0,5.0,BADAECHCCHCCHAAFCGFBGBBHBBGFCFHCGGBGGBFFAA,True +418,11.0,22.0,19.0,15.0,20.0,16.0,14.0,28.0,CCEHHDBHECHCGAGDCCABHFHHEHDEGBEGBDDBDEBHBBGFFCFFHBDHBCHBEHBAHFFGFCDHHDCHBEABHDBHCBAAEFDCBCCDFHEFGBDABGFBCADEFDGFAGEHGBHCBCGFAAHEEHEFHEGEEHEEHCGHC,False +419,25.0,19.0,13.0,15.0,18.0,30.0,15.0,15.0,FHCDCFBEHCABEAFAFHEFDGFDCDEHAFGAFBDBBFBBGBAHFAGFBFFBDBDDEGFBDEBHCBFCEFCEFAECAEFECGADBABAEHFDGFGGBGFBGDAAAHAAHDFHGCHFCAFEAEEDECDHBFAGHAGFEEFAFFAFAHCAHG,False +420,5.0,4.0,3.0,9.0,10.0,5.0,4.0,4.0,DEBDADFEFCEHEABEAEEFEDHGDHEDCFGCFDDGBDGBEAAH,False +421,21.0,22.0,19.0,21.0,16.0,23.0,24.0,24.0,BGGDDGBHHHHGHHDAGFAGFBBFGGFGEHBAHECFACAGHEFCEADEAEBAHBGBBACDACDHCDHCHBCDBDDGCFHHFHHAHEEHCGCBGAADFBGEGFCCFCGFDHHDHCBFDAADABBCBFCFGDECBEFDEGDEDFABFADFGBFGFAGFADHHEGABCFBGEE,False +422,5.0,3.0,3.0,1.0,0.0,2.0,1.0,4.0,ABCABCBGAHHHFHAFCAD,True +423,8.0,5.0,10.0,3.0,2.0,6.0,4.0,7.0,CAHCAGAAEDGFCGDCFHCAHCAHBBDFAFFGBFBBCCCHCEHAH,True +424,4.0,2.0,3.0,3.0,3.0,5.0,4.0,1.0,GDFGCGACDACDEBFEGHEFFAAFB,False +425,20.0,29.0,28.0,22.0,37.0,21.0,18.0,23.0,DCDEFDAGCHCHFDAFEFFEHDEDBEABEHBEBFCBEDBCDCCEGCEBCEAHDHHDAHGAHBBBFABFABACBADHEEHEEAEAAEACDCHBCEDEEBEGGEBEFDGCBBBAFDAFCAFCHEDBEDGECHBHGFGECEDGDFECFDCFGHECEEHFEBCABCADEAFEGBBHBFGBEHCCHBCGBEFCHHCHGGGGDF,False +426,3.0,6.0,6.0,5.0,11.0,8.0,8.0,8.0,ECEBAECEDDEBDGBGHDGEBGECGFHGFHACHFGHFCFBEFHHBHEADEFGCFE,False +427,9.0,21.0,17.0,17.0,18.0,17.0,9.0,12.0,BHBBHBBAFBCCHEBDECFECDEFFGHCEFCAFAEHDGHDBHABEEBEEDAECBDCECABDAFDHDGEDBBDBFAFFCCBHCDHDBFDGFGBFCHACDBCGGDGGCBFFBFEEFHECEED,False +428,13.0,9.0,6.0,7.0,7.0,9.0,7.0,6.0,HDAAECHEGFFGFGCFHCBGAADAADAAFABFBEEAFFBBCBBEABECGHDGEDGDABDAFHCH,False +429,8.0,15.0,19.0,18.0,20.0,20.0,16.0,22.0,FGDFDDFHDGAFGFHEBABCDBHFGHFCHACACCECEACEBCFGDBHFEHFBHGHHEHEBGEAFFHCFDEFDADDBDGHFBDFBCFBGAHFBECHECBECHECECCEDCHGEEGEGFDFEDBEHBHCDGDHCHHGGDG,False +430,13.0,25.0,20.0,21.0,26.0,17.0,24.0,16.0,EFFGFCDFCEHCGHDGEECAEBBEGBECFEGHAADDAFCAFCBCEECFFCFCAGDACHBHHBGDCGDGGDEEDBHHGCHEDBEGEECEEBEBBDBAEEFDGBGGBDAEDHEFCGBCGFCGAHGFHDBGGBFBFFHEHBCDBADCEDEBBGAAGHBGHBDBDD,False +431,13.0,21.0,18.0,12.0,10.0,10.0,17.0,15.0,GAFBBBBFHGFAFBGCGGBBCABCAGDHGDHBCHBHBAHGGHEGHDCDBCFBCGECAEDDHBAEBDHBDHBDACECGEGGDHADBEFCDBGACEAHBCFBEHAEHAFGCCGCCFFC,False +432,14.0,11.0,9.0,15.0,14.0,12.0,12.0,18.0,DFAFFAHDHEDFEHHEDHCFHCECBABBDGEFGEDCDCGDHHFCHFCGGCEGABGDBEABAAHAEBDEBHEGHFGHDHEBADGADBAEHCEHDDHBFAGAAFFGH,False +433,16.0,16.0,12.0,20.0,13.0,18.0,9.0,14.0,FDCFDADDBDDAHDCBDCDDCDAEHAFAABADBECFAFBCFADAGCAGCDBAFCFFEHFHBFBEHGCGGDFGDABDEECGGDFEFBHCBHBEHBEABEHBAHGAEFBEHHHFEHFDFD,False +434,15.0,21.0,15.0,6.0,12.0,5.0,12.0,17.0,CBBDBGABGCDGCEADBCCADEFCCAHCHCDHCAHCHHABHBBHABEFCGCBGAFAAHEAFGAEGAHGEEGHEGBFBEECHEBBAHHCHDBHBBHBBABBGEG,False +435,0.0,0.0,3.0,2.0,2.0,2.0,2.0,3.0,CHDCEDEHCGHFGF,True +436,22.0,21.0,21.0,13.0,7.0,14.0,20.0,13.0,BHBGDAADEDFGCFGDHGAGGAFDCCACCHEADBCFBCGBFABEHDCHCEGBGDAGAADCAHGHHGHFFDEHAGAGGABCAFAFFACHACGBDGBDCBDHAGCFEBFACHBCABCGFCAFGBEBBCBBCBB,False +437,18.0,12.0,15.0,15.0,9.0,15.0,19.0,9.0,BEAEFBCFAADCBFGDGGHFCADAADGADHCBHDGDBGDBGDCGAHEFHGFAEBAHBADGCDGCGFCHFDEFEHFCAAAFBAHAEGDEGFEDCCBCGBFGBFGACGCCADFG,False +438,9.0,15.0,11.0,10.0,6.0,5.0,12.0,8.0,CBBCECABBAHBHBCHGGEGGDAEBEDCDFADBGDBGDBGBBCDGABHCFGBFGHFGHFEAAEAABHDDCGCCDCH,False +439,21.0,34.0,13.0,20.0,9.0,14.0,18.0,22.0,DBGDFCCFEAGHBHHCHHCBHBGHBDABCCBAFBAGBDCBDBBGBAFFDHEHGCBACBAEFGHBGAFGCFBAGHAHHAGHGCDEAHABHBDFEDBDDADDHFBHFBEABEABADBHFHDBABBHBAEBGCDCFHGGGBBGFDGDABDABDE,False +440,5.0,7.0,4.0,9.0,2.0,7.0,1.0,7.0,DEBHHHHHHDFAAFGADHABBFFDFFDBEDCCCCFBDDBDAB,True +441,9.0,3.0,11.0,9.0,5.0,3.0,13.0,6.0,GCHGCHBCDDAEAHEAGAGGCGEAEHACDFBDBDGCDGDGGHGCFGCAHCACDGCAEFD,True +442,26.0,15.0,9.0,16.0,20.0,21.0,20.0,20.0,EEHEFAFDDHDDBDEEFFEDFCHFAAGHAEHADBAGHAGBADAAEABCGBCBBFGCFGEFGEFGHDEAEEAFHFGHDGFAGACGCHBCHEAHGABGBGADGFFGEEBCFDHAEBAGBADAABBHFHHCEEFFEDFHAHHAHADDGFG,False +443,5.0,11.0,13.0,10.0,14.0,14.0,10.0,14.0,FCEHCEHCEDGDBBDGEDHEABEFGAFGAFCCFHFFHFBAEEGDFFAHECHGCHDCHBGFEHFHFFBBCBBEHCHHBECDEDBEDCGGGDC,False +444,9.0,3.0,12.0,6.0,9.0,11.0,10.0,6.0,GACGCGACGBHABFCEFCEFCAFGFEGDCFBCHHHHGAAAEADCDGAGEEEEECFFCDFGDFCDFH,False +445,9.0,10.0,13.0,13.0,17.0,11.0,15.0,15.0,DGCDBCDFEFHEHHEDDEGCCFCFFCGDEECEFHHFAHFAEDGGBBGHHGCHGBACAAHEEHEEDGGDGGDGEEFEBGHBCDCAACAHDHBFEFCEDBHBBAG,False +446,4.0,1.0,6.0,9.0,11.0,4.0,5.0,7.0,GACEFGGACGDFDECDEHDEHDEHEEDAHDCDFCDBEHAGFCHEEHE,True +447,26.0,19.0,18.0,11.0,16.0,16.0,12.0,21.0,EEHFFHCBABHABHAEHAEHEFFGFAGHBHAEEAEEAGAAGCCGABDACECFHGHHEDHCBHCBHCBAGDABDCHAHEFHFHHDDFBFFAFCACABEDFEDAGDBFCBDAGFACEACAGHABBFBBEBACCCGHCDBAG,False +448,6.0,5.0,7.0,6.0,1.0,1.0,3.0,5.0,HADHAHCACGDGBDGBAECACBABDCHDBHDCCF,True +449,11.0,2.0,6.0,6.0,9.0,16.0,8.0,5.0,AGAAHAAGFDFEEFBEDGEGEEFEAFCCDEDFFGFFGFFCFAEFAFHDFCBHADHFGHACCAG,True +450,11.0,4.0,8.0,12.0,7.0,9.0,7.0,8.0,FDEFCADCGCEBAHBGECHEFHCDACDABHGBFFDFAEFAEADGADFEDHCAHGDHDFCDAGDAGH,False +451,31.0,20.0,20.0,33.0,22.0,23.0,32.0,17.0,BCCAGAAGFAGCEGDBGDACDHDHGFBGBBDBFGBHBAHECEECDEDHHDFADFEDCEGHAFBCCBFADGCBADDFEFGEHGEFGDHECAEAGEDDEBDEADAADBCBGEDHDDFCEAAHBGBGFAGFDGFDEFEGHBAHFAGFDGDDFDFABCABCAFCAFCAGCAHEGHGDAADAGEFGHDGCDGBGHCFAGDEGA,False +452,6.0,6.0,6.0,10.0,8.0,9.0,9.0,6.0,AFEABEBDGBAFEDHGFHGEDGEHCHAGHECHCCFDADDFEDFEBAGCFGFFGCBGDBDD,False +453,13.0,18.0,14.0,23.0,17.0,19.0,19.0,12.0,DCGDCDDCADEBFFBFFCAACDACDCCABCDDFDFAAEGFHFADCBGCDGEDAFGGEHHEFBFFBFFBGFCDFCGAGDDHDDHFEHGEBGHDGHAEHBGBDEFCBDDEABHAGEBEEBHEDEGBHGBFGBGEEGB,False +454,18.0,22.0,18.0,14.0,25.0,31.0,12.0,21.0,FHADBACFDHAHHDGHBFFFCFGCBGDHFFFGFFGFGGFAHCHEEHFHDFHFFHFAHAHEACEGEEBDEDFAFFBFFBFBEFDCBBEAEHDFDEEEBBGCBFCFCBGBBFEHGCDEHDECDECBADEAEEACEACECCABBECBECBFAFAGHEHHABHAB,False +455,8.0,7.0,7.0,9.0,13.0,7.0,12.0,7.0,AGEBFEADAAGFABFHDEAFFCGFDEHGABGCBHCBGBDHBDFDEGCEGCEDCEHEDHGDAGEHEEGCEG,False +456,26.0,25.0,17.0,12.0,23.0,17.0,8.0,10.0,BCAFCEBDBGCAAFAAFGCBEAEDDBADBADCHEFFEADEAEEFEEGAEGEHBEGAFHAFHDFBBAEACCAECBBBBBFABEABDBBDABDCEDFECACHFHAFHGHDCCAGFEEACEABFABFBEFAEBBGHBCHCC,False +457,17.0,13.0,15.0,8.0,13.0,12.0,8.0,11.0,HFCEBGABGABDAECBBCBBEBEEBFEAADACFHFEHFBACAACDAFHHFAHGAHAAEAHGHCGFCDFDAEEBDECCHCCFFGBEGCDFCBCAEDHG,False +458,4.0,0.0,3.0,1.0,6.0,6.0,4.0,0.0,FEEFEFFGCFAEAGCAGEADEFGC,True +459,21.0,25.0,18.0,16.0,17.0,17.0,23.0,17.0,HDAGCGGBBGBCEDCBBBEGFEGFEGFAFFCGFCBECBFFBEBBGBFABCAFAHEHEDHGDCCEAAGAAGBCGHCBHCAEDHHDFFDABEFECCABHABEDBEGBEGDGDFGAFEAGCDGCBHHDHCAHGABFDEADBADBHGAGAHFHGCHDB,False +460,10.0,14.0,5.0,9.0,15.0,9.0,9.0,8.0,EDEEGEAGEGBEDBDFGDEABFAFDAGEBBABDAGDBGFFHAEHDEABGBHABEACEFBDFBCHGCEBCEBEHHHFHCF,False +461,5.0,3.0,5.0,6.0,2.0,12.0,7.0,4.0,CEAFFGFFGFFDFHDFBDADACCGGCABAHGFBFFDGHDGHEFC,True +462,6.0,6.0,14.0,9.0,5.0,9.0,18.0,19.0,FGCDHCHHGHDGADGECGHCGCGHCEDGEFFHHFHFGBAHEFGBCGHFDHFHHCGHCGHEGBCCBDAHDHGBHACGCGFCDABDAG,True +463,3.0,5.0,4.0,8.0,5.0,3.0,5.0,5.0,DGAFBBFAHGEGGEGBECECCAHHDDDEDDHFDHBDCB,False +464,8.0,5.0,4.0,6.0,7.0,4.0,8.0,3.0,DACBACHAGHBEHDEFEADGGCFEDGEBGEAGBAGFDGFDAAEBC,False +465,13.0,13.0,10.0,12.0,11.0,18.0,10.0,10.0,DFBGFDFFDGBBBEDGEDBECEEDFHAAACAAHHHHHBGGAAAFHACDACEFFHFFHAGCBEFBEBAFGAHGDEGFFBFDBFDECCECCGBCDBFDF,False +466,1.0,7.0,5.0,6.0,4.0,4.0,5.0,8.0,DHBECBCDBGDBHDBHFHECAECFFGHDGBBGHCGHDHFE,False +467,8.0,10.0,7.0,7.0,13.0,10.0,14.0,7.0,GGBEGHAGEGBEDBCAFFBHEEAEFBEGCFGCFHBFEGFEBFHFCHFDGDDGHDGDCHAEGCEGAEDCEBAABABG,False +468,7.0,9.0,14.0,4.0,4.0,10.0,8.0,4.0,FECAECBDFBGFCCFECFDCBGCBGBFDAHGAFGBBEBCHBCAAHGAGCCCFHCFGCDAF,True +469,11.0,8.0,10.0,17.0,9.0,15.0,9.0,16.0,FHDFDDEACFHCFCAHDEHAGHACHDGBAGBEGBAGEHHDGHFEHADHAEFAGGCFECFBCDGDHHDADBCDBEDFFDFFCCBEDHFHAFHDFDB,False +470,1.0,3.0,1.0,1.0,2.0,1.0,2.0,3.0,CHADBEEBGHBGHF,True +471,17.0,15.0,26.0,18.0,19.0,21.0,23.0,27.0,GFFCCCHCDHAGAEGFGCBGCBFCFFHDFBDCHDGHFEAFEAEEAEGDHGHCGABGDCGDGGFFFACHBEAEEDEAHFAHDHHGCHFHHGGHBBECGECEEDAHCACCBBCFBCHGCHACFDCEDAHCAHFFFDABEEBCBAHFCHBHBGDGECGEHDHGDHGDFD,False +472,2.0,5.0,3.0,5.0,4.0,6.0,6.0,2.0,EGHFGBFEBFEDFHGCCFEABDADDBDGBGCFG,False +473,20.0,30.0,26.0,33.0,27.0,26.0,18.0,15.0,CGAHFAGFAFDBCDEGDEHBEGBEBFDGFECFHBFHBEEFEECCEFEFFHCDGAHABDFBAGBADBADBDGFGCDCABGAEGDDDDACFACEAFEBEGDCGCEFDEBEEDFEFFDABDHBDEBCHBHHFDDBCDFGDAGHBDABFBDDDFFBBACBCCBCABCACCHGCBFBDDEEBCGDCGDCEDCHFEHEAHE,False +474,19.0,17.0,14.0,18.0,11.0,17.0,20.0,12.0,GAGCCFFCGFEDEBFFAFCGDHGEHGEHGHGFDFAAFDADDADCACCBFBDGBGGBFEBCABDAGHGBDBBHFGEAGCDGFDCFCHFAGCBBABBABAEBCFCDEDHGHAEHAEDAEDGFDGDAHHAB,False +475,29.0,21.0,29.0,16.0,8.0,11.0,32.0,19.0,GGHBGAGFAHFBGAHFBHGBHGCEACHGBAAAFHHFHHCBGCGAHBDCCDGAAGHHDBDCBDFBDBEACAFCEDCBGABGAFEACGACGCCGBCGHAGADEAHGDCGCBBAFBADCGBEGBEGBAGCGGAGABCCHCDACGHDGEAHAADFCCHACDGCDGCDFC,True +476,1.0,0.0,5.0,0.0,0.0,3.0,1.0,0.0,CCCGCCFFAF,True +477,12.0,12.0,12.0,10.0,3.0,21.0,15.0,7.0,FDFAGACBDCBGCEFEFDGAGGBBDBBAFCADCADCFCGFCFFHFFHBFCCDAGAAGBFDCFCAFHDBBGHDGHFGBFBEFGFFAHGAGGFH,False +478,17.0,16.0,18.0,22.0,16.0,25.0,17.0,21.0,ACEFGEHAECACCHBGAFFBCFECADCEFAEDEFAECBCGBCHFGHGEBAEAADHGDGAFGDDCEHCHAEHDEFGHHHBHABFABFHCFHCFHCFBDFBHBEFFEDFCDBGDAFDGBHFBHAEDCFHBDDGADGDFCDFGDGBDGDFHDFHG,False +479,10.0,7.0,13.0,9.0,7.0,6.0,9.0,3.0,HGCDGCAGAEGAGCCBCCFCEFEAFEACGGCHDABDECHFABFEBEBADBDDBAACGCFDCDDG,False +480,1.0,0.0,4.0,0.0,2.0,0.0,5.0,0.0,GCEGEGGCCGCA,True +481,21.0,16.0,14.0,17.0,11.0,10.0,25.0,16.0,FDGEEGBBDHAHGDHBHGBGCBCCFACEAEGAHHDHBGFDGADAAEAAFHCFHDFABGCBGAGGADCHDCECEDBDACDAHDAGDBHHBAGFAEFGBFGBGHAGAAEDCBCEBHEGHDDBGGGGCAGCFG,False +482,12.0,17.0,21.0,17.0,21.0,22.0,20.0,24.0,HCBHEEHCEHCBHADGBCGBEEHHFGHFDHFCHCGHGGHBGCBCHGDDACDFFFFFGBACFECGCFHFAEDHDDBDDHDEGDECAGCAGHAEHAHFEFDEACCDGGGFGCEBCEDHFCHBHBEHDDABHFFFAFFBFEBEBBGAEGCEGCEBFE,False +483,19.0,21.0,17.0,13.0,22.0,21.0,20.0,24.0,GDGGEGFHAHAEHADHCEHDAACCBEFBEAAFFAFGHHBHDBFDFFACBGDDGDHHBACBFDHFDBFEFFGABDACDFFHGFCCAEBBHGBHBBEBGCDGCHGCHEFHEAHEHHGACCACGAHHEBGECGACFEEEBEFBCFEEGEHGEAGBFHBEB,False +484,14.0,17.0,19.0,19.0,23.0,9.0,30.0,14.0,DBADEECEEGGGCGGCHGAEDCGDCDDHDGGDEBHBBCAHHADGGGEGCECCACHAGHAEDABCHGGHAGDADBEFHHFBCEAGAGGDGGHGGACFFBFGCFGBBDBECBEDBGFEHDEBDEFHEBCEBAEGEECEGBGFCDECD,False +485,23.0,20.0,17.0,18.0,15.0,7.0,16.0,20.0,ADAADBBFAFFAFAAGCDHCHABGABCAGHBGHCAHEECBECGDHHAHDEFBGDGDBGDBAAEABGHBDCECCBGGHCEHBFABFABCACAECBCDDCBEEADEADHHDHDDGEHGEHGEDCBDCHAAGGBHHBHE,False +486,19.0,15.0,16.0,14.0,11.0,13.0,25.0,19.0,GDCGHFGHCBDBAAAAAACAGHBGADDCCHEGBCBDAFDBGDBDEAAGAHBAHADCDDEHHFHEAGCGGCGGBGHCGCBGCBDCGGGFEGBEDFHCFEBFEAFGAEGCFGCFGDEGAHFEHABFFBHHHHHH,False +487,17.0,28.0,19.0,19.0,12.0,13.0,19.0,22.0,DBDEFAHAGFBGHEGHDDBBEBHEBHDCHFEHGEHGBBACBAGAAGEBBHBDFBDFBDCCHCCAEBGDGDCEBCACFAEGAHDFCCBHCEHDEGCBGABGBDFHCFDDFDBFGAGGFHBCHCABDABHAHCAGCHGBBBCBHFDHADHG,False +488,11.0,5.0,10.0,9.0,17.0,10.0,8.0,12.0,HFEBAGAEFADDEHDEHAEHDEHAEDEEDGBCHCFECFBCHGCHGEDBEABGAHFAHFHEEGFHACECCADEDCEFCAFGFG,False +489,15.0,27.0,19.0,19.0,24.0,16.0,18.0,23.0,GDHCDCEEBEBBHABHFBGFEGDDHDFACCAGGADEBDEHABHAFHGBHAFCAFCBFCFHCHDEHDBBFABDEGCECHDDDDGEAGHAFHFEBBEAHCAHFGHABEFEHDHHDCGBEHBEBCCBGDGEBGEBEECEGBECBEBDEBFGHABHFFDGCCGBC,False +490,3.0,2.0,6.0,3.0,7.0,0.0,1.0,4.0,CBCEHEADEACEADEDBCGHHECHEC,True +491,14.0,16.0,16.0,14.0,17.0,13.0,22.0,10.0,FADFCGFCEFCEBCGBCBBCBBAFBGGBGBEEEFDBBDHEEHGHAGHAGDDGBEAAGDFCHADHGDHGHFBDEDDEFECCEGGGGGADGCBEEHDCGCCGABHDBFAFEEECCAGAFGAFCA,False +492,26.0,18.0,20.0,24.0,26.0,19.0,29.0,28.0,DCADFADCEHGDGGFGEAHEHHAHFCCCGHBAHEAECBBGGBHGBHDBAAFECHEBHGFHCAHDAHDAHACHCGHCAAEGGGDBGDGGDEGHHDCGEEGEDAEDCGFCDFEFFADHGBCABHDBEGBGBHCHFGDFEFFEBBEDBEAAEFEBFGBAHAAHECDGDDFDACCAFAEHGEDGEDCEHFGHFA,False +493,1.0,0.0,2.0,1.0,4.0,2.0,0.0,0.0,ECEECEAFFD,True +494,11.0,16.0,14.0,24.0,25.0,15.0,20.0,16.0,HFCEDHDDCEGCFADBEDCEDAFBACGFFGHDDDGBDFEAFCAFHDFHEFBAFBDEBEHCEDBHDGHDFAEFCECCBGGBFDBCDHAHBGEBEEHGGHABDGDGGDHADGAEEBFECEECGEGGEBEEBHGCHGDHGDEDE,False +495,15.0,21.0,13.0,15.0,18.0,25.0,20.0,12.0,GFGGDGBFFFDCCDGCDECAEFFFHCECCEDEEAEEBEFHDHBGGBGGEGHAGEAGBGEAFAHFACFCHGBBGBBCCDEGDFFFFABBBEBDAGDAHFACFAFDABDBBEFDEFAFBBFBBFEHHGHDDHBFGAFHEGC,False +496,14.0,17.0,8.0,12.0,24.0,10.0,23.0,11.0,GBFGBDGAFGBGEBFEHDGAFEBCGGGBABDAEDGEFBAFHEFHBFHEEBGEBAEGGEFGEABAHBGHBCFGEGCAGCEHEGHDDEBAGCAGBECDECDEGDEGDBDHEEHAEHDCAAE,False +497,8.0,11.0,13.0,8.0,7.0,15.0,9.0,16.0,EHBHFAFCAGEGGCCGCAGBAGHDFFCFHBHHDDHFCAECHDBHCBHAFFDFEHCGDFGAFCAFCGFEBBCBBCFHDHEDHFBHEBH,False +498,3.0,6.0,8.0,3.0,3.0,7.0,4.0,5.0,CHECBEABACCGCBGFHFFBGDBFDAFDEFCGBCHFHHC,False +499,7.0,4.0,9.0,5.0,5.0,8.0,3.0,3.0,ECEEFHFFACFAHAABEABDCCGFDGFCCFCCFGDABDCDEBAH,False +500,7.0,8.0,5.0,8.0,4.0,3.0,2.0,4.0,CAEFHGBDDBDDBDDBCGBCFDFDHCAEAEHBEABAAHACB,True +501,22.0,26.0,22.0,26.0,16.0,25.0,21.0,27.0,EBHCGHBFHBFBAEEAHFAHEADFGDFBFHCHCCHGAAAAAHAGBBBDBCHCEHBHHGDDFBEFDECDBFFHFFDDDDDFDAACHBDABDHGCEGCGHFGAFDCFGCFGBBGFACDAGHFGHEEAEEAHHBDDAABBCBCDDCDCGHFGHEBHABGFCGCEGCBCHBCHDGFFBFGEFDEHDBAD,False +502,10.0,11.0,12.0,13.0,8.0,15.0,13.0,13.0,GFHHEHDCHDEFDADGCDGBDFADFHFACFACACBFCGFCAFEECBECBACAFDEHBGGAAFDGHCBDCBHGBHDFHDHGEFGFHGFHDBEBGGB,False +503,5.0,6.0,10.0,4.0,4.0,8.0,9.0,0.0,FEDCEDCGBGGBCFCFEDBEGAACABCGCCGFFGFFDAGGBCABCF,True +504,7.0,14.0,10.0,11.0,12.0,9.0,6.0,15.0,BDBBGBFCEDCHDCHEFFECHGDEEHEDHDBCDHGABFABFBBDBBCEECHEGFAHCGFBHFAHFAHDCEAHBDCBDHGEHAEH,False +505,21.0,9.0,16.0,11.0,15.0,16.0,15.0,15.0,DFAGEAGEAFCCECCECFEGFHGDHAFBCHEDHEHBEAGFCHDHGAHFFCAAGAAGAAGAFEDGCDFHGEHFEDFBDCAHGAHBABEABGABEDFFHGFCEACHADEBCCBGFDCCHA,False +506,17.0,15.0,12.0,11.0,15.0,5.0,18.0,14.0,BHGDHFBGBBABHAEGAEDAEAEDBEDGCGHADCFEHAGHAHHAFADCBBGEGGBDBBDEHHHGGBGADGACHCEGCEHAABFAEHAECAECEECFBCGDCGBCGDG,False +507,23.0,16.0,18.0,17.0,15.0,30.0,19.0,16.0,CAHCHFAHFDGFDGEHAABDAFCAFBAGBHGHCDBAAFGFFGADAHDGDGGFEDFEDCCCCDHGFFGFFCHFAFEAFEFHGBEFEEFEECDBGGHHGHCEHEGCADCEBAFBFDBGBCHBFFBFFBCDBDGAGFABEAEAAFFCBFCADCADHA,False +508,2.0,2.0,6.0,5.0,8.0,2.0,3.0,4.0,AECAHCEDEEGEDCFFCBECDDGGDHECHEBH,True +509,10.0,15.0,13.0,10.0,20.0,25.0,8.0,14.0,BFFFFGHDGHBEECGECGEHFEFAGBHGBEDEGAEAHHFFHCFCFFHEFADFBCEHCEGFAHFHEFECBDCBDABDCBFCBDHBEFCEFCHFEBEBFEAFACFHFBAFEADDDBE,False +510,9.0,6.0,15.0,8.0,8.0,15.0,8.0,4.0,CGFCHFDFCDFADGADECCCFCAFBFFCCFEGFDGFCGCCEBBEAEEAEFGHDGDFCHFEFAGDABBCBCAHA,False +511,1.0,1.0,2.0,5.0,3.0,1.0,4.0,3.0,GDDGCBGCHDEEDHEDFAGH,True +512,16.0,13.0,8.0,20.0,20.0,20.0,19.0,18.0,GEEGAEDHBDFBGBGGHGEEDHEHEGFEGBEGFHGEDBBAHGFDAFDAEDGFFHFFHEEHDEHDGDGADCADFADABFHDFCEFCHFDGAGABHAFHGHCBFCHEHBEAAEAAEBCEDFGABDCHFCBFDFDDG,False +513,2.0,0.0,0.0,0.0,3.0,1.0,1.0,4.0,HHEHHEAGAFE,True +514,16.0,32.0,27.0,32.0,20.0,18.0,31.0,18.0,FFCEHGEAGHCGDDGHDFEDFDDBDCHDAABHAGDEGDEGEFCBDAEABBAGBCGHEEDCCBCCAECAGBDFBCHGHHDHADGGGCCFFAGBGFDGACBHCBDAEDBEDAGDHCDGCEGFGCEGDADDCHBGHBAHBEGBEFBFGBHDHGEBBDBBFCCCDEBDFBDBBGFBGFBGFBGFHDBCCCEBCGDCED,False +515,26.0,15.0,26.0,29.0,17.0,18.0,23.0,22.0,GFHDAEAAEGAEGCEDCDDCAHCABBAEBECGEBHHGAADFECFBCFECEDGDDCDCGDBDFGCGHDAHFADDAHCADDGDFGDEAAGAFDHGCHDCBDCGCBGCBFABGAHHBHDFHDFDDGDCFFAHBEHECCFCBACHACEGCEHHBHFGHCGDAGDAGECBFHAAGFFDEAH,False +516,12.0,12.0,20.0,17.0,22.0,17.0,13.0,11.0,EEBEADDAFDADAHHEEBGEBFFBEBCCDFCEFCEFCEFCABEFHEFCEFGFCGCGHCHDCGFBECACAGDAHDGGDHFDHADEADBFHBFABDHECFDCHCEGGDCDDCGBEAFEBECGECGE,False +517,17.0,18.0,11.0,13.0,13.0,9.0,14.0,20.0,BEFHACHEDBAAHAHHAGBAGCGGHAADEHDEHBBHGEHAEHGEDGEBCEBCHAAHBCHADHCDBGFBGHAABBFFFCCFACBGDBGDBFDCFDCBEHFHHEGBADEDHEGGABD,False +518,20.0,13.0,17.0,15.0,17.0,19.0,27.0,13.0,CFECBCGACDECDHCHAGGAGGAGGAGEAGHBGFFGHHDEHDHDDGAAGDDGDHBEFDAGBABEECEAABAAFAGFGDFCDCEFGECBCGGEGHEGHBGEFHFFDCCAFGAFEAEEFCFACFGBDCBCAHGBEGFDFHBFB,False +519,4.0,10.0,8.0,8.0,7.0,6.0,3.0,5.0,EABADFAHCBFGDFCDCCBACBEFDGBHGBHFEHFECEDHBCCBEDBEDBD,False +520,21.0,21.0,12.0,9.0,4.0,4.0,12.0,8.0,FAACBBBAABGAFADBABBDBBABHACGACBABBHHCECAACAHGDHGABCBDABAGBDGDAEDGCDGCABFEHEAHFBHGADGCCGBCGB,True +521,7.0,6.0,5.0,6.0,9.0,6.0,4.0,9.0,HDFFDAFDAFBFEAGABCHCHHBFHBGEBHEHHEHEDAECEEGACDECDBGA,False +522,7.0,13.0,6.0,12.0,9.0,15.0,17.0,9.0,FEHCDBCDGGDGGDHFBHAEFDEFDFGEAABAFBHCBEFBACDGBDGHHBFGDFEDEEGGBGGBHGFGFEGHCFBFFBGFGHBADCAD,False +523,13.0,18.0,26.0,23.0,24.0,18.0,20.0,22.0,HDCHAFHBBHAEFFCCGDFGAFCFDBHGFGEFBEGCEHDHHEGCEGEDBDDBGAFHCFHCAECHBFHADHFDHECFBCBBEEDGBCGEEEDGHFGECCECDACDGFBCACCDDGDDEBDGBDGAACABCABCFBEFEDHEDHDGHEFHECDECGAHGEHGCCBH,False +524,23.0,26.0,27.0,25.0,18.0,14.0,25.0,20.0,AHEABADDECBHGBEGDCHHCEDCECAFCACEFEEGGDGGDGEDGCFBAEAHFGDFCACHEBDDBADBADBDDACFAFAGCBBHBGGFDBFDGAAGAHGDHFBEEDCCDCBACHHCHECFDDHABAACAAGHHGBGGBGFBGFHDCBDCBHBHHCDFCDEBGHBGACGCCGECBBBEE,False +525,9.0,5.0,7.0,9.0,10.0,14.0,16.0,12.0,GDEGFEHFGFFECEBCBHHAHAGHAGDFCDHBDAFFFGFGGHBDHFDCFDCDGFEGEGCEGAGAAHAGEGHEHFEHFGCDBA,False +526,21.0,20.0,28.0,24.0,24.0,22.0,22.0,28.0,FBFFHFFDFEBCDDDFBEABCGECGECFHFFCFDAACAAHAHCDHGHHFHCBHBDHGDGDHAHCDHGABAABGCGAAFBGFCDFCDFCABEHDEAGHABHEBAEFHCAEABHGHHACFEGEEFEEGDFGDCCDCEDHHGBHGEHGECGDHDDAFCEBDHBGGECBDCBGCAGCEBCECEBCEHCDHEDF,False +527,20.0,11.0,8.0,13.0,17.0,8.0,13.0,14.0,DDHGDHCDHDDHEGFEDECAEHFFHAABEGBEHBCAGADGACFACECDEAHGABBCEAAEAGFABAABAHGFHEEGGDCEBAFGFHGAEDHEDHEABEABDHBG,False +528,9.0,13.0,8.0,10.0,8.0,6.0,9.0,7.0,ECDBCHEGHFFBEDBGDBHDBHDFHFEBBCDFDACACCBEHBAGBAGFDGADGACHABDAEABGGEGCEB,False +529,2.0,5.0,6.0,3.0,4.0,6.0,5.0,4.0,FCBFCBFCDCHDEHBFGFFGAEAHEGBCGCHDEBG,False +530,5.0,3.0,3.0,2.0,4.0,2.0,5.0,5.0,AFBAEGACGFGHCEHEBGEHGHDAHDACB,False +531,14.0,18.0,15.0,23.0,16.0,17.0,15.0,32.0,HBAHEDHGDHCDHDEHDEHDEHDHFAGADFEEHBBDFHDAEDEEHHHBHDFHDFHCFCFECABGGBEGCEBFBBDBDCCHCAACFACFHEEHCHHDHGFHGFHDCDDBEBGHAFFCGBAEBAHBGHAGFBGAHCFFBDGDCBDHGHGDHA,False +532,8.0,6.0,17.0,12.0,9.0,14.0,14.0,11.0,DEGAFHFDCCDGCHHBHCFDCFDCEGGFHHCAGEGBFGBDGDAGHCGCCGDCHDGEDBEFFCFDCGHCEHEGHACCAFAFFDFFAEBAEBC,False +533,15.0,11.0,12.0,12.0,16.0,22.0,21.0,18.0,GAAFFACGGFHDCBDFBAFBAGEAFEBFGGFDDEGFEACHFFBDFGEGDFFAHFHHAHHEHHFHFABECBDHHDCHDGGDGGEFGEHACGACGECEECEEBDBHDHHFHEFGGCABCAFEFCGGGBA,False +534,6.0,6.0,12.0,13.0,5.0,12.0,12.0,8.0,HDGAGHFGHFCHABHFEHFACCCBCEGCGDCDEADCFDHGDGFDGFBGCDCHFFEGFAFDDFDDGADCBECBGB,False +535,22.0,16.0,25.0,15.0,17.0,33.0,16.0,16.0,FBFFEECEEDFEFEEBGGDGFEAAEFCGFDGHDGDEGAAAHACFECDACDCHFCHFAFFAFEGFBDFECHHBACBCCACDAGFGDFEDFCCFHCBCCFACAAGADGHEFFCBFHDFCDHBHGECAFFGBGBFGAAAFBHFHHFEBFCDFCBACBHCBHAB,False +536,20.0,17.0,26.0,15.0,22.0,17.0,17.0,16.0,BHHBAFEEFAEFAEDBBDFEEBCEHHAAHAGBDGBHBECECCBFFAFEACEGCEFEECDDDGBDABEEBEHAAHCFCCEACDAHAGHBGFACFHCGHCFCCBCFGHDHCDHCDGCEAHGAFBADGGFCBFCGDCGCCFADECDGGEGAEB,False +537,13.0,10.0,5.0,5.0,10.0,8.0,9.0,7.0,EADEDEAAGAEEBGGHHBFFBFEBFBBDEAHEABCAHCAEFAGDAEDBFFGFAGAHGCHGHABCGBC,False +538,10.0,10.0,16.0,12.0,12.0,14.0,12.0,13.0,DFCGBCDFCDGBDCFCFFCFDAHDCBECEEBEDBEHECFECGAHGDHEAHAHHGFHGDHFFCGGCEGFGGCGCAAHHAEHCBDFBDEBAFADFAEBCBH,False +539,2.0,2.0,4.0,2.0,0.0,2.0,1.0,0.0,ACCFCAFCBDDBG,True +540,3.0,8.0,6.0,4.0,2.0,10.0,5.0,6.0,FGBFBFDBFDBFHFFGCEAFHCCBFCBECFABGDGHDGHBHHAC,True +541,4.0,4.0,3.0,5.0,9.0,9.0,6.0,7.0,HHFDFBDFAFFAEFEHGEHGEBGEAHFDEBCGHGGFEAFDDHCEBCE,False +542,1.0,6.0,4.0,1.0,3.0,1.0,2.0,0.0,EGEEDACCFCCBBBBBGB,True +543,11.0,8.0,11.0,8.0,8.0,12.0,13.0,10.0,CGFCHFHAFHGCGCCHCGHGACBDDBCDFADFADFBBEDAEGACFAHHGBHGDAEFGEAGEABHBGFBAEEGEHDFCGFCF,False +544,1.0,2.0,1.0,1.0,0.0,0.0,2.0,3.0,GDAHBCHBGH,True +545,20.0,18.0,24.0,26.0,24.0,22.0,18.0,33.0,CBHDDADAHFAEFCEHCEHEBHCBGCHAAHAFHFFEAFDAFBEEGHAGDDDACDHCEECEGDEGDEGBADBEDBAACEECHFBFCHFHHEEDBHHAEFCCHHFDBFDHCHHAHHAHGCHCCGFCGBGGFGDFBHFDGGDCEDADDADCFBCHBCBFHEHBEGAFHCCBEFFHDHGAEGDBGDEHD,False +546,29.0,23.0,21.0,19.0,21.0,27.0,25.0,20.0,BHEADFCDFGBFAFFACEAGFABFACFACFHEBHBFHDFGEGCEHCGDCDFCACAGDEBDEFAEFGEGGHCEHEAFEGECAAGAAEFFFFDFGGGCDGBGEBGHBGEBADFGCAGEADDBDDBACCCBDBBHAAABAHBACGECDDHGHHGBFEACHBFHEDCFDAHEAGCBGBAHFAHFBHFBH,False +547,8.0,14.0,13.0,15.0,21.0,12.0,10.0,20.0,CHCHGGHDDADDEGDBGFHCBECDEFBGHEECEGCFAEHHEHHCHHCHFFAAEDAHDEGBEHAAGBEHDEDBCFFEFCEFCHHEHBEHBEHEDDEGDGABCEBDBBCBFFBDF,False +548,5.0,4.0,1.0,2.0,4.0,2.0,2.0,2.0,ACBADGEEGEEBAFBFHDAHBA,True +549,14.0,13.0,9.0,11.0,17.0,24.0,19.0,14.0,EHAEHGEDBEDCEGGEHFBFBBGBGGFHAFHBFEACBACEADGFEACGFEGFADHGDAGCBGHGCFEBAHBGHAHADDAFDHGGHGFFGFFCFFEAFEGEEFFHFDBBDCBEHFFDFAEFC,False +550,8.0,20.0,16.0,21.0,30.0,20.0,19.0,15.0,FHEAEECEEGBBBBBHBBDDCDDCDBCBFFEGFBCEHEEHEEBEEHFDCEECGBBGAGAHCAFCAFGDEGCEFEHCDBEDHGCGFFGEEGEECBEFEHFHCDHBDFDDGGDHEFHGDECDEHEGACFAFFGFBGBGAFGDDDDDBEFBH,False +551,8.0,3.0,13.0,5.0,6.0,13.0,5.0,7.0,BDFEDFGCFCHFCGCAFFAFFHFGCAGHAEHCBCCEHCHDCADCFFAEFCCDHGEFAEBA,True +552,10.0,10.0,17.0,16.0,16.0,11.0,4.0,13.0,CABEDBDDCCDFHBACBAEEDFGACHECHECEDHDDBDDHAHCBHEFHEFHEDDGACAECHEFBEFDEDDHCBHCHFGBFEBDCFACEGCAACFCEF,False +553,29.0,25.0,19.0,15.0,29.0,33.0,22.0,26.0,EABECBEDDEFBHACGBHHEHFFAFFEDBAGFCHDGEDEHDGDDCADHAFFABHCFEEBAECAECHHHACCAEABEABCCECFECEGCHGCFFBFFBEFDGGAGAECHEHHDHHABDEHAEFFEAFAFFAGFHGEAGFFGFAACAEFFEGBAABFGBEGDFHDFHEFBBHDHHGHBCABABBFBBGBGGEAGBFGCFH,False +554,19.0,13.0,14.0,11.0,11.0,13.0,12.0,8.0,ABGABGBBFEBEDGCDFCEAGEAGHAGFAGHACHCDHADCADFGDCDDAFEGFEDHHAGCGCFDEHBEFCFFCFEABGABFCHEBABBACADEAFBABACC,False +555,4.0,7.0,2.0,2.0,5.0,4.0,2.0,1.0,ABBABDFBHFBEFEGBAGEAEEFDCCB,True +556,33.0,24.0,13.0,22.0,28.0,22.0,18.0,30.0,EEFABBCDBADEGEHHHCAHGEHABDDBDAGAABDGBABBAGBEBHEFDEDCHDAEDBFHEAHFAHFABFCBEHBEHAEHCHHFEHBEHFEFFHAFHAGHEGDDHBCEDGAFGECHHDHFAEFAECAGAGCEGADDAEBABAAHHAHGAHFEEECAACGFCDFDDFAFEBBGHBGBAFBEHDFGDCGDFA,False +557,21.0,20.0,17.0,15.0,9.0,13.0,11.0,17.0,FFFCCBHDBHDBDDBDDHDCGFBAHBHCCDAADHAHHADGADCCHBCFECEACECCFDABDCEHEHHEBHDFFABAABAGBEGAHGACGCGGFBBHBAFBABAGHAFHFGCGDEFBBCABAAE,False +558,17.0,17.0,12.0,11.0,13.0,15.0,10.0,21.0,AACABFAEFAEGCEBAFBFHBDHEAHEBEEHDHHBHCBFGAFGFCACBFBDFADFCDBHHBHDACECHHDABGBBGFGHDACEBCEBCAFHDEBDCAAHHFHHFGHEGAEGHFGHD,False +559,14.0,31.0,29.0,20.0,24.0,28.0,19.0,25.0,CBHCBFCBGABHAFHAGDBEEHABFAEDGEDECFFCBFDFFDEAEHDDCECEHCBACBDFBCEECGGCGFCFHEABDABDGBDAHFHHGADGEFHDGHEFHEBBEBGCBFBBDCEGFFAHGBHAFFGFFHEFHCCHBBHFEHGBDDHCBCFBCFBCADCDBCGCCBBCBECGDCHDFHBGHFGFCEEHEE,False +560,11.0,11.0,9.0,9.0,7.0,8.0,12.0,11.0,FDCFDGECEACDHCFAFGAFAFECFCHECHABHGBHBBHBGEGGAGGAFDBHDCHDBEDGABEAGACHBHDBDABGHG,False +561,17.0,20.0,22.0,24.0,12.0,25.0,33.0,19.0,GFGGFCGFGDHGBCGHGHHGHCGHDGCGCDDCHGCFGFAHCHFDFCDEBDEBGFCEFCFFGAFCCGCHACBFDFGEEBBDDBECAFGAFGADGADGDDGADGFDEBDBBDBGCAGHGGDGGBBDFHCCDCEFABHHBHEEHBDHAFAGEAGDABFAHHAFBFGDCEBCBFFA,False +562,11.0,10.0,11.0,8.0,5.0,15.0,7.0,5.0,GBAGDDBFDHFDGFAACAACBBGFGEBGFFCFFCEFBEFBCBACFFCAHCAHEEDBAHFCFFCDDAGCAHDB,False +563,20.0,11.0,17.0,13.0,14.0,9.0,14.0,23.0,BAGDHGEHCAGCGEFAEFBCCHCCBDADHBDHADHCGHAGAFEAHHAHHACGCEACAHCDHBDGGDFEBFHHDHHCAHGAHFEEDGFDECDHHEHACFGHFECEGBBCAACAABDABEGBE,False +564,25.0,13.0,20.0,11.0,13.0,16.0,8.0,5.0,AAAAFFCFFBBFABDAGEAGAHGACCFEFGEGAEAACACEFCFFCDCHFBBCBCCADFBHFDCCBGABGCBABBDFACAAFGACACDEEDECDBDAEDAHDAECAECEEHF,False +565,28.0,15.0,20.0,25.0,16.0,15.0,18.0,16.0,AADAACACCACGGBEGAEGBEGFHCHCCEBCEBDBBDBCDAEDEBDABDFFHHEAADAHHGHGBDGCAGFADAADADFHEFHFGDEBDFCAFEHFBBFDHCDADDACDHFHAGCGDAGCABADCADEAGEGCHDDBDCAGFHGHCGAEFFECE,False +566,7.0,8.0,2.0,9.0,6.0,8.0,0.0,5.0,HEFHDFDDHDBEDBEFBDBBECBAFBFDAFHAFEDDBCEAAAFHA,True +567,12.0,8.0,8.0,9.0,5.0,12.0,6.0,5.0,DADDAGBGGBCHFGFDAFCACAEFADFGBFABCDDFEDFECHECDBAEAHCAHBACBFFAFFBGH,False +568,27.0,25.0,25.0,24.0,19.0,25.0,34.0,18.0,GGBDADGGGAGEFFECFEBGEADDADDAFHBBHBCFBCGGEGEDHDHBDFBACBGCFACBCGBEGHHGCAGHGBAFAHHBFHAFECHCABFGHCDHEFEFCEDCEGBGGDAGFFGFFGAFBEFEAFEGFDBFCAGCAGCABAHHHCEACBGEBDEAACCFGGFGDBGDCCDBEGBCDFADBAGBADDADHCDHCDGA,False +569,17.0,19.0,19.0,27.0,20.0,24.0,19.0,16.0,DCECCEHDBFDEDGEAGFGFBCHBCAGAHGFDAFDBHAGEADCHDCDGCBHCEFCHFCGFAADABFABFEECGFHHDHBDEBDBCFEEFEEAECGDBFCBDHBDEBDAFDAHCGDEBDEHDFADFDDFGAFEFCAFHDBEBBDGGACDBCHGFFGFGGEGH,False +570,14.0,23.0,26.0,22.0,21.0,32.0,13.0,35.0,DEACHFHFDHEHFCHFCEFBFHBECFECHDGEDFFDEFHFBCCACCHGDFCHFEHCAHCHHCEHEEHCHHCAHDDGFBHCBEAGGDBGFBEHBHFBADBFDAFGGGABHAGHABDFBFHCFDCFDHEHCEAAEGCBGDFCFFEFDBFBBFBCHBHDBEDHDDBAFFCFHAEHCEHCBHDBCDEGFH,False +571,12.0,18.0,32.0,29.0,10.0,22.0,15.0,20.0,DAHAAEGCCHHEBCEBHDDGDDFFCCCCCHCFHDDHDHADBEFBECBCDBCDFEDGHDHCECGACDAEGGDGDBFHCFDGDDGAEFDCFDAADAADHBCBBCGEDBBHCFHCABFDHFBFCBCCBCCHCFFDGCGGCHCBFDFFDFFCFHHBHGFCGD,False +572,19.0,12.0,16.0,19.0,24.0,11.0,17.0,21.0,AEAGEAEEBDEGDECBBDAHDAFECHEFHGFGGDEHDECGGCAEHEHHCBHDDHDEGCEGAHGFEGEEGEECFADFEDEGCCABAGBAHAHHAEHACACHAFHBCBBAEAFBHDDADDGDBFHGCHFCHCCGFDHDDBE,False +573,5.0,2.0,3.0,2.0,1.0,4.0,3.0,2.0,ACEFDDFABGAGGACFAHFCHB,True +574,17.0,18.0,22.0,17.0,4.0,9.0,12.0,14.0,CCBCGGAHDAEDBCFCCHCFACFAEDAHDAHGBGDFDDCACAAFBBDDBDBBFCBECADDACBFCBHCHHABCAHGBBGBADDACHAGHDGHDHBEHBGBGGCFDAGCCCFHC,False +575,13.0,19.0,23.0,32.0,16.0,20.0,25.0,19.0,GGDDGDDCHDBGDFDDHBBHGBHBFHCEAFEHFGFEGEGGDGDFCHFAEFBCFGHDGDEGDBHDAAGHDDADEBCEGCEFCEFEDBACHAHFDEFCGFGHBBBABDCBFCHDCFFCHDDGDDGECGEDAAHAADDAFDCGCHBCGBCEHDEGFFHBDCBDBGCCGCC,False +576,9.0,9.0,12.0,4.0,5.0,6.0,12.0,11.0,BHFCHFGHEGHBGEFHADCDCGGCFGCBDABAEBACGHEGFBGBAHCDHCGHAGEAHHCCFCBGABCA,False +577,6.0,7.0,11.0,9.0,9.0,12.0,13.0,8.0,EDDGBABEGCGACGECECCBCCHGEFDEFGGFGBCGDAGHGCHBFGBFDEFCFFAGFDHBDADFADFHHFHEEHC,False +578,0.0,1.0,2.0,1.0,0.0,2.0,4.0,0.0,GCGDCGFFGB,True +579,5.0,1.0,1.0,3.0,1.0,1.0,1.0,4.0,HGAHAACAAEHDFDDHB,True +580,23.0,6.0,7.0,14.0,17.0,10.0,20.0,6.0,EEAEEHDHGCBEABGFBGEACAADADGADHCGFGGEHGAGGDEAFEAGEDEAAAAAAEGCFGDFGDEGAEAFBAHBAGDFGDFECCECGDBAAGDEGHAFDDF,True +581,26.0,18.0,18.0,18.0,15.0,22.0,19.0,23.0,FFFAFECGECGHCGACGACAFFGHGEHADHFDHBDHCACGABGAFHHGAFGABDABAFBHEBAEAHFAGCAGCGFAEDGHFGAEBAEHDDHBDFAFBHDBFCHEHHGFDDBAEHAECAHGHECDFDDHHBFHBFCBADFFDCCDBCABGEBCEBDEGAC,False +582,21.0,17.0,16.0,25.0,18.0,9.0,13.0,8.0,GAHDCGBCBACDDBDGADCEDBFDAFDADEAEEBEHADFAHEGDBGFHGHCBAAHDEHEEACDACDECFEAHAGGAEGAEFADBGEBGCDDCFDABDCCAGBADBDFFDGDECDBCDCCEEBBEBBA,False +583,3.0,13.0,7.0,7.0,6.0,7.0,7.0,14.0,CGGBGGBGFBHBBHCAEBHEBHFFFDFADCDBFEBGCBCHHHDHHDBHEGDECBAHFDHBEHCH,False +584,19.0,16.0,23.0,16.0,22.0,21.0,12.0,29.0,CGHFFHFFHCFGDFDEECFDCDDABFAEAADFBEAECAEGAECHHCHAEHFECCHGCHGEGGEDHBABFAHEEBGEHHHBHHCDBCDBADCACABCBCCBHBGHDFHBFHCABGDCFCCADHAHHEHHEHFEABEGGAFDFEEFEAFCDDEHFBHCHF,False +585,5.0,14.0,11.0,11.0,4.0,5.0,12.0,10.0,DGDBCBFGBDAEHACCEHCDCCBHFBHFBHCAHGGGCGGBGCBEDBGBAGHFCHDCGDBHABEFBDDBDDHG,False +586,11.0,24.0,18.0,11.0,8.0,6.0,17.0,13.0,GBBGABCCDDEGDFGAHEAHCAEGBEGAEABEAHHCHBBHCBHCBGGGGGGBHCBCCBDDDCGGBEFFADFGBCABGBBDCBDBHABHBBHFBDFCHCBGDHACCCEC,False +587,14.0,18.0,17.0,13.0,15.0,17.0,25.0,21.0,ECCAFEAGBAGCGFCGHADHEBGCGGCBDCGABDHBEGBCGHHGFHGHHGHDGCACAEHBBBABGFHGFDGFDBDGBAHHGGBCEFCFHHFEHFEFFAFFAGFCHCHGABCHEFHCFEBDEBDACGAEGEEHBBDEDDGD,False +588,13.0,15.0,14.0,18.0,15.0,14.0,13.0,9.0,EFAHGBHGDHGDCADGDDEEEECFACDGDGHCCFCEDCBHFBGDBCDBCGFCGBCEDDEAFEAECAFCDFDDBHABHFEEBBHBACBADBGDEABFGFFADGAGFAEFEBH,False +589,12.0,8.0,10.0,3.0,6.0,15.0,8.0,10.0,FDAFCFFHFGHFGBFHAHAADACFCCBBCBBHADHACFAHBBCGGEBECHGAHEAEEAFFFCFFHGFCGAEG,False +590,17.0,15.0,7.0,14.0,11.0,14.0,9.0,6.0,HEAFCADCHBHAFEFFEDAAFBABCGDDFAAGDGDCBEBFEBDEBAEAEBAEBAFBGFBHFCGCHGHDGFAAFCADBDDBDDGFAGFABEDBE,False +591,10.0,3.0,10.0,5.0,10.0,14.0,7.0,11.0,CFGCFEAFHGFCGAHACGFEADCAECAEBEDGFDHFEHFEHBEHFECFAAFHAECDHGDBFHHFAHCCFG,False +592,19.0,16.0,12.0,22.0,13.0,29.0,15.0,13.0,GHBEBBFBGFCCFDDECDGGDFGAFABCHFAFFABBCHBAFGHFBEFDEFGEFGDDGDDACDBCEAFEACEDDFFAHEAEDDHHFFDFBGFHGDBFHECCCFBDEBAHFAEFAGFBGDHADAFDAFDAFHAFGAGCHDB,False +593,7.0,6.0,8.0,6.0,8.0,9.0,6.0,6.0,DCHBFDCFDGACEACBBCBGHAGHFEHFEHDEGAEAACGFBFCHFCAEDFEBEDGF,False +594,30.0,31.0,17.0,16.0,20.0,23.0,18.0,23.0,ECHGCHGBBGFBGABGCDGHFFBFABDADAFEAFEHGBAABEABHABHACFACBEFADDADFBCGHHABFEBEGBCGEHFEFEBGEHGDAFBHDAFBAHBAHFAFACGDCHDCHDGBEBHEFEAFEDHACEBCFBCHBFHBAACFCBAHGHDDEADHAECACGBBABAFBFEBGEHGD,False +595,9.0,14.0,16.0,12.0,7.0,14.0,15.0,6.0,FEGFGGFDBAGEFGEFCCHCBEFBCGACBACFCCBCAFCAGGFFCBHGBHDBADADHADGBDGBDEBCHFCFCCGBDGDHEDADDFEBGGCFB,False +596,26.0,34.0,20.0,24.0,21.0,26.0,22.0,25.0,FEEBEHGEHEFHEFEEACGABBDHDDHGCGFDACBGBHGFHDADCFGCGBDAHHCFHGFEEFEAHEBHGBAABDABFAHFHDDADDFDBGGBFHBAEBAEBAHBAFACFADADDAGGBBGBBCCACFFBDFHDFHDBCBCABAECDFGDGHHEECCAFDBDEFCEFGDBBHBBHGGHFBHEGGEBCABCFBCFCAHBA,False +597,16.0,18.0,17.0,23.0,22.0,17.0,16.0,28.0,EECBEAGEDFCFADAHFCHFCHECDBGDBHDCHAAHDDBDDCDHHFHBAHBEHDEHAFHAHHEEGEEGDEBDEDDHBEBGEHGEHCACFHBDBACHECEBCACCGCGGEHHDHBFGEABFDFFDGFAHCGHCFHBGHGDABDAFGBEGFDFBDEHFA,False +598,14.0,9.0,12.0,11.0,20.0,14.0,7.0,8.0,EEAFAGFHFFBEAGHBCFFFFDFFBAFCEGEEGDCGDCBAADAHFFHAGHACDECBEDBEAACDGCEACHDDADBECBECHEAHFDEEEEEEEBC,False +599,31.0,15.0,28.0,34.0,25.0,28.0,16.0,23.0,EADADBADCDDCGEGGEAFEFGBDDCFACDECFECFBCHAEHABGFCCAECDEDGCDGCDGEAHDBBDBACEAFBFEBEDBEBEEFGAAGADGDFFCEFAFAABDFHDFHDGCDGHDFCDFHEFAEGCFDAFDAFDEFHBCDAFEECHHDDHDCFFAHHHHCHADEADADBADBCGCCHFAFCEHHAFHAHHAEGACCCH,False +600,10.0,11.0,5.0,10.0,8.0,10.0,7.0,10.0,HBFHBHGFGEFGEFAAFAGFGEBBHBDGBHHAHCDHEHBEAFDDBBABDFDCFHEBCECCADGADFADAED,False +601,1.0,4.0,4.0,5.0,1.0,4.0,5.0,0.0,EGCDDCBDCFDFBGBDGCAGFBGF,True +602,4.0,2.0,2.0,6.0,6.0,0.0,2.0,3.0,EDEEBAEDHEAGEABCHDCDDADGH,True +603,22.0,28.0,15.0,26.0,22.0,27.0,16.0,24.0,EADBBCFGEFEAGAFEACAHCDBABGHBHAEDGGDCGFBBFHFCEFCEFEDAEGEHGABFHBFDBGDBABGGCGBCGBABHAFDDFBDFBGFHFCHFCHFHECHDFFDFABFDBHDFDCFDCABHABHEHADCDDCDHFEEDAEDFEBHHAFHGBHBBEEBDHDHEDABDABAEGEEHAF,False +604,21.0,11.0,14.0,19.0,11.0,12.0,18.0,29.0,GHHGHHAHADHAHCGBCGBDGBDHDFAABAEHFCDDAACAFHBHHDEBEGAGGEBGEHDEGFGGCHGDBDHHDAAAACFACFHBHEAAEHADHGCHGHDBCFHEFHEFECDDHFDCGDFGAFHAHHCHBCGDCAD,False +605,9.0,11.0,6.0,10.0,8.0,6.0,9.0,4.0,DCGDAGDABEBBEBGEBGDDGHAHHBCCECAHAFFAEDCEFFEDCBGBBGEGDFGDBAAFDAB,False +606,28.0,22.0,23.0,19.0,24.0,23.0,22.0,23.0,GHDEEDGFDEHCEBCEBAGAAGEGGEGABFHGFAGAHGDCCDHFBADBDDBCDBFHFDGEEGCEHFFHCCHAGHABEACCACDFEEFAFGEFBCGBCBFAFFBFFDGEEGBEHBHHDCACFHCACAABAABAECCDFHHFHBDAEFHEFEECGFBGCDGEHCBGDBAAAHCAHDEHDBHABAAG,False +607,13.0,16.0,14.0,14.0,17.0,12.0,10.0,10.0,BGHBGADGDDGCECBEDBECAECGECGECFACFBEEBEADEDHFAHAAHBFEBHDCFDGDBFFBEGCAFADDHCABDACDABDHGFFGEEBFEBABCEFEHCHHCB,False +608,9.0,17.0,16.0,8.0,12.0,15.0,18.0,16.0,BGGGDCHHBHGBEACEACEGCEHFHCBGBBGFBGFAHCDGCFFCFGCBGBBGBFGBFAHFBGFBABCEGCEADHHEHHCHFEGEDHDDCDABGHECCFCFFGBADEAEHFH,False +609,34.0,28.0,25.0,20.0,27.0,20.0,18.0,15.0,FHGFEGEBBEGBEGHFHDFDAAEAAEDCFDBFEFCDCDDGEAFEADBCCACCDFHHBCHFEDABBABBABHAFGACGEEEACCACDDCBFCDHBFGBAGCGFADEADGABFABAGEEEBHBFDBFEBGEBEBHCCDCAGCAECAECAFCHGEEBFEAGEDECAHHABABBABDFDAHCABCAGHAGA,False +610,27.0,20.0,29.0,19.0,16.0,20.0,23.0,16.0,EDGGDCDCCDCCFAHFACFEEAAGGAHFADGADAEDCEACDAGDAHDCHFAFFHCGHCGDEBAEBAFHADHCBFBBDAECAECACGGGGFFCDGBHGECFBABDABGECGEFBFCBHDBHAHGACBAHEACCACHBHEFCBDCGDBGCBGHGCBFCADEFBFFGABGCEF,False +611,22.0,21.0,24.0,24.0,11.0,17.0,21.0,18.0,CGCHDBGDBABGACGAEAACCDDCDGCDGFDEHBABFCHACHAFGDEBDEBDABHGBCFBCBAHBDFBHFCFECFECGAGEAEBDGCGGCHGDFGDFCFBHFAFGAGHHFBHDAADCAHCAGEABCCBDDEDDHCCAAHFHHDADDBGHCGBFFBEDG,False +612,15.0,15.0,16.0,7.0,8.0,15.0,11.0,10.0,BBGABCABCFCHFCBCAGHHFHFFBFAAFAGBAGDEFFCFECACDACAFCABEEGCEGCAGDBCHBDDFDDFAFHACBGBHGBHCEEEGHCGFBHBA,False +613,1.0,6.0,10.0,13.0,4.0,6.0,8.0,9.0,GCDDCDCAHCHEDFDCCDGGDBHDCHDBHCGGFGCFGHFGFFHHCBBEEBDEDDBDH,True +614,10.0,16.0,11.0,12.0,14.0,10.0,10.0,10.0,DECEGBDAEDAEGGGHGAAEBAEHDGHGEBCHBCHBFEBCBFCBAHEDFEDFGAFDCFBCFBDFBCHCCHDHBDBBABFDGEEEDCEGAHBAF,False +615,1.0,1.0,2.0,4.0,6.0,3.0,0.0,3.0,HDEHFEDCEABEHFEDDECF,True +616,10.0,6.0,9.0,12.0,6.0,14.0,6.0,4.0,DFHDFBBECCFCCFBCDGAFFABDAGEADBDDACECFECGAAGHFHFFHFFDGDAFDEFDEBDAAGC,True +617,6.0,1.0,4.0,3.0,5.0,2.0,0.0,4.0,BDEHDAAFACHECHECDEFHCAAEA,True +618,22.0,16.0,36.0,14.0,21.0,16.0,20.0,16.0,BBGEBEHHHHHACECCGBEDBCDHHAHDCHDCECAFHAFDAFCAECGCCACCGFFDEGACGCCGCEGCGGEGACGACBDGGDEAEBAEGFECAECFBGECAEFFHBCCBCHEFADFDECDBCBFDHDECDGAABHCFGCAGCFGABEABCABCECCFFAHH,False +619,26.0,17.0,24.0,18.0,27.0,15.0,23.0,23.0,ADFABEBGDCGDEAEHBHDBCGECBECEEGAHGCCECGFCAFCHECFACBAHBACBAEBDEHFEDDEHGHHGHHGAHGAHFADAAGEAEDAFAADADHEGHEGHGBHDBCEECGFCHEBHBBFAHDCGAEGEEGECGHCFCFGCDDFDCBCFEAAAFEAHGBGDCDBEFCHAG,False +620,7.0,2.0,1.0,9.0,6.0,2.0,5.0,5.0,GBEGBDDHGCFGDGHEEHDEFAADAAHAAEAHEDDDD,True +621,16.0,26.0,22.0,21.0,29.0,29.0,17.0,19.0,EAFBDDEEGGEGGEGDFBBFADADCGDCBCCHCDDEDFEDFADFEDFGBFHBECAHCDBCGFCFECEEHAFHAFCGFBEHGFHEEHFEBCGBGGHABFGDAGCABFDBFDFFDEFBBBDHBEECFEHEACBFBDFHAHHEHHEHCCHGBAEBDCCEEFBBFAFCBDCBFBAFEACEGHE,False +622,7.0,7.0,8.0,11.0,8.0,4.0,10.0,8.0,DAGDCGDHGDACDBCFHHEGDEDEFHCBHEBHFDHEHBCGGEGBCGDCFDGEDCAABAABEAG,False +623,28.0,16.0,21.0,17.0,19.0,16.0,21.0,15.0,DEHGEHCAACGFGGBEFBEGGGBGFADAEDADDCCHGGACAACEBDGFCBDAAFBCCCCCAEEEECHDCEDAEFAHFABFACFGHHBEGCEFBAHCDHDBCEBCEAHAAHAABEDGECGFAGFABFAHFAHEAHDHBFCBDDAFDAGBGGDGG,False +624,3.0,1.0,2.0,2.0,0.0,4.0,3.0,0.0,GAAFDAFGGFCDFCB,True +625,2.0,3.0,2.0,8.0,3.0,1.0,2.0,1.0,DHDDBDABEGDDGBFAEDCEDC,True +626,25.0,22.0,16.0,18.0,24.0,24.0,24.0,13.0,EBGFHAFDBGEBGEFGEDHADHADAAFCAFCHGEAGACBDGBFBDFEDGEHGEHGDHGCFCEFBEACEBHGFHEBHEGFEBAECFBABCACCABAEDEDGEGCABEEDGEAGAAGCFFDBCGHAGCAFFGFDAFHFFGEBBBHBDAGDABDBDGBAFEDFCAFCEF,False +627,29.0,21.0,28.0,24.0,31.0,21.0,20.0,20.0,FAHFBGFACEAEHGHHCFHGAGFFCCDDBDGBDGBDBHEBHECCEHCAFEGEHGEHGEGGBCABADDACDEEBCHCGAAEAFCABCEBDABEABCAECAEAHHFCFGDFHDFHBCECEDCDFCDACEFBEDBFDBEBEHHECCEDAFDGFDHEEHEGHCDDADAAEGAFADCGCGFEGFEABACFAEBACBGDA,False +628,12.0,14.0,20.0,9.0,14.0,5.0,7.0,10.0,BAHEECEFDEACFADDABAECEHFDHCCCACBAEDHEBHEBHFHCFCCGCDACAADGEGCCGCGBCBBCGBCEBEHBEDCADBEGBCABHH,False +629,5.0,5.0,7.0,3.0,4.0,2.0,2.0,2.0,EFAECAECHGHFCDABDBCDBCBCABCGEA,True +630,23.0,22.0,17.0,29.0,22.0,31.0,12.0,12.0,CCDECDBBHBBHBGFACDAEHBFBGFCCEHGEHEECEFDDFDDBEDBAFEHBDHBFFFFFFFAFFAFHDFAEFACFCCGAFAAFGADGADFFEBHEGEAAFBDGBDADDAGEACECCFBBEEGGEBDBBCAADFEDCADFFDFAEFBHDDDDBCCBFGDAEHEHDDAD,False +631,27.0,22.0,17.0,34.0,24.0,29.0,22.0,24.0,FFDCFDCHHBFADFAGECGECGBFBAFBGGACBFCBACHEFEEFBEFEEFCBAEECEHAEGAEFACFADFDBFBHHDHAFHADDGHHEHDDGEBEEGFFDDGEDGADGBDHFDHFBHFHAABAADHAEHBHGDFGEAADDFDCCDCDDFBAGCFDCGDHBDHEAFDGBEGBADEFGCDBADGADHEHGFHBDHADGACB,False +632,14.0,22.0,9.0,14.0,13.0,13.0,20.0,23.0,BCFBCFAHGDHGAHEDGEBBCBHEGHDDDBAGBAGCECBBGBDABAGHDGHEFFBHEEEEHDEBDEFAAFAHGDGCDAFHAHGADGAGCDDHHFHGFHEBHBGHBFBBFGBFHHFAHCHHBECBGBGG,False +633,24.0,22.0,20.0,25.0,23.0,16.0,19.0,23.0,DBBDHHDHHEFEEFGABGFEGADFACHGEHGEHAFFAHECCEACEBBHBEFADDDDGGHGGHAABCFDCFBGFAECDGBDABEAFECFEHBAHFDBFDBDEFCBCCGDEACAAGBBGBDEAEAAGAAHBGHACCAECGCCDCGDEHAHGBDDEDDHDBHDHHFCHDBHEBCE,False +634,17.0,21.0,22.0,24.0,23.0,23.0,16.0,18.0,CBHDBHCEHCHBGDBECHEHFBCFDFBDFCGFCACCACCGDEAFGADEADFCDFBAHAGHGEBDDBDEBDHBGBDAEDBEDCEFCEFHBHCGDAHAAEDEEGGECBEHDGDBGEHFEFGEFBFFAFFCCFECEDHEGCAGBACFDGFDHFBABHADFBEFHADC,False +635,16.0,6.0,8.0,5.0,5.0,8.0,8.0,4.0,FFABFACAAFAAHAFHCEACEABFCDGCFACABGGDGCABAEBGEAGBAGHACHFEDDDG,False +636,0.0,0.0,0.0,2.0,3.0,1.0,3.0,2.0,EHGEHDEDGFG,True +637,9.0,16.0,10.0,10.0,13.0,11.0,8.0,12.0,FEDBEDBEBBEFBEHBFBFCBEGBAGBHGHDBDDEGBECEFHDDHCFHGBHEBCGBEFAACBDEFCGFAAHAHHFFAADAHDCHGCECC,False +638,12.0,9.0,9.0,12.0,9.0,15.0,8.0,15.0,EFGFDCDAGDHFCBFEAFHACHBGADEEHEFGEDHFDGDDGAECCFHBFHBCACHACHACFAFBGDBGDBHBHHBHDEHDAAAEFFFHF,False +639,14.0,20.0,11.0,14.0,9.0,16.0,14.0,14.0,BFBHEBAEDADCGDAGDAFBHCBACBAEAHHCGBCGFCGAABFCBFGADBFFFDFCDFEAGGDHDDEFFHGHHGHHEFEBHBBGDBCHBEHBEFBCABDGGDCGAFHBFABD,False +640,8.0,6.0,17.0,2.0,13.0,12.0,17.0,7.0,HCFFGFCHCCACAADFGBFCFFCGFCABGBEABGCEGCEGCACCFGDGECGHCAEGBEGEEGHBGEAFEHFEHGHGEECCGF,True +641,14.0,17.0,15.0,14.0,30.0,13.0,21.0,15.0,BBGEDAHDBBEHBCBEHAEGAFGECGACGADAFGFFGFEGDBCCBFCHDHABHEBGEDADDHEGHBBHEGCGCHEEHEEHGEHACACCEGCGGEDGFGAFDBFCAFBAFEEEHGEGFEBEEBHEFDECEEDEBGEDCAD,False +642,26.0,25.0,28.0,26.0,13.0,16.0,19.0,13.0,EBDECDGCAACBAHFACDCCBCDDHDFBDBDAHGAHGBHGBCFDEADGADGHFGBAHBCCDHBDFDFHAEEFDCGGCFCAFGACGCCFADBAEBGBGGBFGDFBFCAACAACECBBHBBGABGFCAHCDFGDCCEBCDACHBCAAEDEEDFEHEDABDACDAGDBB,False +643,14.0,19.0,17.0,9.0,14.0,22.0,18.0,8.0,GCCFBFFBEABEHDEBDGBDFAHFBHCBDEBDGBDHHFFGAFGCGHCACFBGGAGGFEGFCAFCADGGCFECECGFAGFAGACHAFHDCBBCBFABFEBCCBGFEAECDBBFFBAEEEEFG,False +644,15.0,27.0,16.0,22.0,21.0,27.0,27.0,18.0,EDFEFFDFBDGBEGBHCFHCFHFAHFGFFEHGEBGEBGABGCGEBGFFHADEDGEBFABGAEFEGFGGAGFDHFBHCBADAEFBCFCCHDFBEADEDBBBGDBDCACCFCEFDDFBHHAGHGGBGBEGCFCBFEGDAGDEHCEHEBHEBADHDHHDGCDGBAFBDCGAFGDBB,False +645,14.0,11.0,10.0,13.0,16.0,12.0,10.0,15.0,EEHEEHGEFGEDEDBGCBHHFHBFDBEEBEBAHBDGACGADGHEHHECDFHDFDFAEFACFBEBHEHAGDCHDCDGCFAAFAAGCDGCAAAHHFBCDBAFE,False +646,3.0,5.0,2.0,4.0,7.0,6.0,2.0,5.0,EEDEFDFHDFHGFHCBHFBEEEABHABFDBGCEA,True +647,17.0,19.0,20.0,19.0,12.0,18.0,17.0,19.0,HCFBAFBDFDHBCACEAFHCGGCAHBHHBHFECADGBGCDACAECGDCFDFEHBABGADGACGBEFHGFBDBCCBCFBDFADFGGFEGFHGFEBDDBDDADBFGCFGHECHCHHGGBECECCEBDEDHADHADHAFHAHAB,False +648,10.0,10.0,6.0,7.0,5.0,10.0,7.0,10.0,CHGDHGHAECAEAGBCGCEDFBGFCGBCFBHAEAFHDFBEHBGFAFFDDABDABDFBHFHHABHA,False +649,23.0,19.0,18.0,23.0,11.0,22.0,22.0,16.0,DFGDAGAEGAEDABBFDGADBHHAEGECAFDAEDACGBCGDCGHCGBCHEGACCAFDBFHBGGGDBGBFCBEGFHAHHCEDAEDBBAFAFFAFGAHCHCCDCCGBDEFHFFDBFBCFDCDDAAAGDEBDBBHBFHGFHFFHFAHGDGGDACDAF,False +650,4.0,5.0,4.0,4.0,6.0,3.0,2.0,5.0,DDHGDFGEFAECAFCDBCHEEAEEHHBACBHBB,False +651,29.0,15.0,14.0,25.0,15.0,16.0,23.0,19.0,GAFBABHAGGACGAGGAGHABDGFCGDEGEFDFACFBDAHAAHCGECDHFEHCDDEDDECGFDDFEDADAFDBFDBEGHFBAGBADBCDGAFFCEDEHAAHAACGAGDFDDFDAADCAFHBEHGEHGCGEBBHHBCDBCDHEBAEGGHGHHAAHAA,False +652,17.0,19.0,21.0,19.0,20.0,33.0,24.0,19.0,EBHGBHEFHAFCFFEAFEADEBHCBFCEFDEFHBGHGFDGDAHEGFEABBBBFBBFBBFAFEBDHBCBCGFEHACDCFDBGHGEFGACCFFFFDADGFDCFGEGHHGEHFFHEFHCFAGFBGCCGDCDDCGECGHAHEAGEDBCDEHDGHFGFCCDAAFAAFGAFDCGECGD,False +653,4.0,2.0,1.0,5.0,5.0,3.0,4.0,8.0,GBFEDEDGEDEADHGHHGHHDBHAHEFHCFAA,True +654,20.0,23.0,22.0,29.0,18.0,18.0,13.0,18.0,EDEBAEGHHFAHFBDDBGFBGDDABDABDADCCBBCEHGFCGFCDEHDFDGHDCBDHFDCBHBFHECCADGHGGEGBCBACHAEGEEFDEHDCHBEHFDBFCEACFAEDAFBGDBDDBDDBFDCFDCHDAACAABACGFCACDHHAFBAFBHEDCEBEEAC,False +655,7.0,8.0,11.0,11.0,11.0,5.0,11.0,11.0,CHBCHDCHBAHBCGDEGDACDEBAAAFBEFHFBGFEDEEAEEGDGGDGHDAHDHBEEGDECCBHCGCCGHCFHDG,False +656,23.0,22.0,23.0,10.0,19.0,19.0,24.0,14.0,FCGFCGAAEBHECHECHCGABAAFFEHBAHBCBBDEBEFDFADFGDFACFAFAHFBCEACECCDGBFEBFCCCCEGAAHAGEBGABCFBAAGFDFCEABEABECDGCGAHGHCCHBAFBHEEHCGBFGBAHBGGEGGEDBEDBDFGGGGGGACH,False +657,17.0,18.0,13.0,17.0,9.0,17.0,17.0,24.0,BDHBDGBFEBCHBDFBDHBAHBHHAAGABHACFFHHBBDDHHDHGFCFFCGHHBAHADGFDCFHCHCCBDFFGAFGAEEAGEHHBGFFGFAGHADHDCBDEFDECGAGADCAGCHGEHBEHFDABDGBCGAE,False +658,8.0,8.0,5.0,2.0,2.0,4.0,5.0,8.0,CEGBBGBHCFHBHBBABGEBHHGCFAAHADHAHGACFACFAD,True +659,34.0,21.0,21.0,17.0,21.0,20.0,30.0,25.0,HAFHDCDEGEEGAAGBGCBEAGEBGEAHCAHEAHCAHAAHFBHECECABCAHGGFGHHGEHDADFACFACFCGFCGFBBFAAHAAHBFFDAFDGFCAEAGFAEDBGBCEEFFFDEAGGADGCDFHGGHBCABCABCABHDGDGGEGGEGHEAHBDGBHHBCHDFAECGDBHAGHADABBACEFHBDEGC,False +660,14.0,30.0,12.0,19.0,8.0,11.0,20.0,13.0,DEBHHDCGGHGCHBFBFGBFDDFDDGDGBDBBABHDBHACECCACEABBAEBDBBGGGCGDAHCADCABHEFHBFDCDCGGFBGDBDBBGGBCGBEBBEBBHHBHFFHFAADGBBGBGADDFEAAGA,False +661,11.0,26.0,15.0,26.0,16.0,14.0,18.0,26.0,FEBHBBCBDCEDFABGAGEABBHBGCDGFDEBBEBBDBEGBEDDHHDHFBHEBEEGAHHDHHCBHCAHDHCAACEGBEGBDGBHBHDFHDHDFHECHCHEAHBGCFCFHDDHDDFDDAGEGGCCGDFGFAGFGDBBBHBDHFDACDCHFGDE,False +662,5.0,2.0,4.0,1.0,4.0,3.0,0.0,4.0,HCDFCFHCACAEEAEFBHABHAE,True +663,14.0,22.0,18.0,13.0,14.0,22.0,18.0,29.0,DHBHHBGHGDDFFFCBHCBFCHGCGGHHHHABCCBAFAEGBBDBFCFECFADFHBCHADBADGHDGCDACFHBFGFFBFGCFAAEACHAFHEEEEHGEHAEBGBGGBFCBFBGGBGAHDHHBECEHCHBFECFHAFHDCHDEHDEHGFHB,False +664,22.0,13.0,19.0,20.0,21.0,19.0,24.0,26.0,AACFEGGECAHDGHDGDBEHBGDGGCBEAGEFEAGBGGBFFBGGGGDCEEAAFFAHEBFEFACFECEABEFHGFHDAHCBHCFGDFHDAHGEHEAHEAGCCCHDAHFCEFCDCAFCGCHFCHGCHGCBGFBGHHDAHEAHDHHDHEEADEFDHADADDHDBADB,False +665,19.0,16.0,20.0,18.0,23.0,17.0,22.0,24.0,DAACFCEFCEHBFHAEHDBHBHABHABHAHCCGGCGCEDBDHBACCCCCAEDHEACEHEDGECGEFGCGDEFHCAHADFDEEDBECEACDGEDGFHFAEFAGBHHAHHDHAGBBFCGFEGHBHFDEFDHFHHABGABGEDGEDGEGGBCEBGDFGFFGA,False +666,21.0,15.0,10.0,14.0,9.0,13.0,18.0,9.0,ACFGBACCACCADCDGADGADGHBABGDFEDEGAGFADADDBEABDABEABAFBAFBGFGGACGBFEBFEHFHGACGCFEDGBGABCEHFGBAGFEDADBAFHHGHHDH,False +667,8.0,7.0,10.0,12.0,11.0,15.0,18.0,9.0,FAGEGGDGEAGDFCFFHBFDBGDFGBAGHCGFCDBCGBDFHGFHEACECCECAEFGCFGHFEDGHGBHFCHAEDAEDGDFGFGEBEDHAD,False +668,10.0,9.0,8.0,13.0,5.0,7.0,10.0,7.0,GFDGECCECCFHAGBGDBDFADGEDAADAADAADCGBGHBHBDHFGHFAHFACDEHBEBDDCGGCDFBB,False +669,7.0,12.0,7.0,12.0,9.0,2.0,15.0,14.0,HBGHAGHEGBCADABEEHFCCGHGGEGGCDGCHGEDGDBADBHDBGEAGAACEDDFBHBBHBDHBDHGCHGHDEEBHD,True +670,0.0,5.0,2.0,3.0,7.0,4.0,3.0,4.0,FGCFHFEDBHBBHFBGEBEEDEEGEHCD,True +671,5.0,12.0,12.0,3.0,8.0,4.0,5.0,4.0,BBCBBAECHCGHCHFCFCCBDBECBEBFEBCGHCEFGGBAGEAEEACCBDABD,True +672,11.0,18.0,12.0,10.0,18.0,18.0,25.0,17.0,AGBBGFGCFCEFCBHCADEBHCHDEBGGGGGAGGCGFHFBHDBFFAFHAEHFEFFAGBEDHHHHBBCFHAFCGCCBEHBEHGDBFEAGEHGEAGEAGEGDBGDCGDGGDFHEFEBBCBAGBEDHEFGEF,False +673,9.0,13.0,14.0,18.0,14.0,11.0,8.0,15.0,CGDBHCCHGBFGAFEEHEHCEHCACCADCDDCGBCDBHDHCBHEHABHEEGDFHDGACBAGDFEDFEDECDBDHFEHBEFFEBCEBDABAAGFHFDDFDDHB,False +674,8.0,13.0,7.0,9.0,11.0,13.0,8.0,11.0,GHHFHFCGFBEFDEDDBFDBAHFHHFCHEDGEHGCBDBHHAEGAEAAEBAGBAEFCFGCFAHBGEFECBCBBDBBDEFDF,False +675,1.0,9.0,5.0,1.0,4.0,4.0,4.0,4.0,BECBCFDGHHBEBBFBBFBCFBHGAHGCEECG,True +676,7.0,7.0,1.0,4.0,6.0,8.0,6.0,3.0,ECHEDFEAHHDFABGEBEABEDGFAGBAFBAFGFGGFABFDB,False +677,14.0,18.0,19.0,11.0,14.0,16.0,16.0,25.0,EEHFECBGCECHDBHGHHGHHGABBDFBDFBAFHAGDABCABFHHABGAEGDBHHGHFFHDFEDFHFGACBCCGCAAFFAHACDGCDBCHBFGBHEFHAFCCEBBDHCHFAHEGHEGCEHCECCHGEGBECBD,False +678,9.0,12.0,6.0,10.0,11.0,11.0,13.0,11.0,CDEAGGDGGCGBCGBAGBGEBDCAFGHFGBFEHEEACFAGFDEFGBHHFHHEHFCGDADHHDHEDAADFBFBBFBEEHEABBD,False +679,27.0,20.0,25.0,20.0,31.0,18.0,23.0,23.0,EFHEDHDDBECBDAFEEFEEAADGGCGEBGADEECEEFEECAFCGEGGBFCBFABGACDAEHBHCFGCHGCHGCFDCBHHBEABAHBABAHEAHGADGCCFECDHDFAGECHAFBADBGDBCABHADDBHCEHCEHBFHGFEEDCDHCEECGCDBCAHGHBGEAGEAFFAFGAEEAFAHGEHGDACD,False +680,27.0,26.0,27.0,28.0,20.0,19.0,14.0,25.0,GDCFDCFHCBAEGAFACFAGFDBEABDBCAHCGFFFCFBBBADBGFCDACDGDDHCEHAEHBFGBHECDEGAACBHCHEAHEFCGACDBHDACGACHAHHAHDEHFCBBABBABCHBFDCGBCHBCHFDHEEBDEHEEHGEFABHAHCAEDBCDBCDEEDCBDBHAFAGEADDADFADFDDHGDEC,False +681,3.0,1.0,1.0,3.0,4.0,8.0,7.0,1.0,HGFEDDABGFGGFGFFGCGAFDAFEEFE,True +682,15.0,12.0,11.0,14.0,15.0,27.0,23.0,14.0,FHFFHFCHGEDCEDGABGDBGFFGFHGDDFFDGCHECAEGEBCEFCEAAAAGACFAGGGBEGBFBAFBAGGAEHAEHBDGGDFDAHGGEGGHAFHGCEFDBFEHDDBGFBCFAFFEHFCHFHDFCFFDEFB,False +683,3.0,2.0,5.0,6.0,4.0,4.0,5.0,2.0,GGFDFADFADECDCGBCGEDHEDHGCBCAEF,False +684,13.0,18.0,21.0,19.0,20.0,13.0,21.0,11.0,FEEGGCAGBEGFECBEGBDHBDCCGACGFBFEHHEHBCHCCFDCDDCEACEAFHHFCFDEBBGBDCBDBADEDEGCFDHABEDGEGFDCFECDEAHEDGEAGFAEAAGHADABDBGCGGBGFBDCBDGBCGECGHC,False +685,10.0,7.0,12.0,11.0,9.0,18.0,8.0,9.0,HDHAGFAFFAFFAEBDCBDBEAFEACEACDGDDGFCHFCBCCACHGCFFCGDEFDFHEFHDCBEHGEGFFDFAAFBEFCDGHBH,False +686,6.0,12.0,8.0,11.0,9.0,7.0,20.0,10.0,BCEBCDBHAGDAGDHGDEDAGDGHBEHDDFGDGEDAEGGGCEBCBGGGCHECBFHHGGFGGFGGHGAHFBBCBECBHABFDEF,False +687,12.0,20.0,16.0,25.0,15.0,20.0,20.0,33.0,DFDHAGHAEHBHBFCFFDHFDBGGCCBDABHGGHBBCBFCHCEEADDACDFCAFBHBHDBHFBADGHDGHDGFEEBHHGGHGHFGDFCDHEEHCECCHDBDAGDABDCBFHAGEAHEHHEHFDHFDHFDEFDCCGBCHEDHBDGEHGBBGFDHAHHFEFGG,False +688,3.0,9.0,2.0,3.0,7.0,7.0,3.0,4.0,CFEHFBFBBEDBCHAFABFEBEEBDEHFEDFHBGGBGA,True +689,15.0,26.0,20.0,34.0,29.0,23.0,27.0,17.0,GAAGDABHABEGDEBDFFDHFEHFBFCBGCBCCDGFDEHDCFDBHEBEFBEBCGCDGADBDGGGAAFCEDCEDBHGBDDBEDFFGFEHBEFFCAHCHHGFDDBCDBDFEHFGAFHFFDBEABEFBGFAGHGGEECCGABDDBEEBECBEAGCHGDHGDEDHFDHDAECAECDEDGEDEBCEDDGGDEGBCG,False +690,2.0,5.0,5.0,7.0,3.0,8.0,3.0,2.0,GFGFFGFDHHAEBCCBCDFCDEADFDBFDCEDBBF,True +691,11.0,14.0,14.0,3.0,13.0,5.0,13.0,10.0,ABGFGEEGEEGEHAHBCHBDDGHBBABACBCEEGECGECGHCABCABCHBEGAEFCCGBFGCAEFGECBFHACHACHDHBGBA,False +692,17.0,27.0,23.0,13.0,20.0,16.0,15.0,12.0,BCCBCGFCGFADAABEDHEHBEADCFFEFFCABCGBABBEGBADBABBFCACGEDBEBBGFBGHBGHDEHBEHBCHACHFGEECHGFHGCCGECGDBBDGAEADFCGECDEFEFCCFAHFEHEABAFCCECEBDDBADBABBC,False +693,27.0,22.0,19.0,22.0,14.0,28.0,28.0,25.0,FCDFEDBEDFECFBHAAHEACBFDEGDCGFFHHFADGABFAFAAGGBHFECAECAGCGBDGBDHBHCBHFEHBBAFAAFAFFCHFGGFHAADCCGCCGBHGDDGFDGBDGBABHAGFDBFGBHAEFFDGFDGCAACAGGHDGAGCDEHDHBGHEFCEFADHEHABHAFHEHHDBGGBFCBGCHAD,False +694,18.0,13.0,19.0,10.0,11.0,15.0,13.0,6.0,GDGHAABAGDGHFBFGBCGACGAEAFDAFDECHECACBFCBACBEBDGBFACEEBEDCEACEBBDDBGFAFFDCFECDHCACCGBFGHGCEGCAAHAAFCAFCFF,False +695,10.0,11.0,11.0,10.0,20.0,12.0,15.0,5.0,DBDBFDEGDBGEEGEGFAAEGDFCFECEEAEEBHGGHCGHCFACGHEGEEGAEFCEFBAFBAEEACCGFDBFCHACEDFADFGBGCBDEBEGBD,False +696,11.0,15.0,9.0,15.0,19.0,14.0,16.0,14.0,BBEABEBFEDFHBEDCFCEDEFDECCEFGFGBHGBCGHGFHEBDGBFGCFGDGDACDAFBFHBHGECGEHDEHBBFDEEDGEFCAAHEABEHHEAHEAHDAHDGGDBGFAGAD,False +697,4.0,10.0,3.0,4.0,4.0,9.0,13.0,9.0,EFFBHHHHHCADDEGDFGBBGHFGBBBBHBACEHCFBEGDGGFGGFGAFGAGHFGB,True +698,8.0,6.0,6.0,10.0,3.0,3.0,10.0,9.0,CHGBHGEHGAAGHDGDAGDBDHADHBDHDAFACBCFBGEHCEFCGABGAGDCDDH,True +699,23.0,20.0,26.0,25.0,24.0,29.0,20.0,24.0,CDBFFGEGEACCACDGBDCHACHACHBGDBCFBHFHHFHHAGHAGHCHAEEGCEHEEFFCDFDDFDFAAEEFEEFBEDAEDFGDFGDHHDBCBBCEBEABADDAEDGGGCEHAGBEFBCFDHFBEFADFDCEHFEHFHADCFDAFHAFBFCEDDBCAHAACGCBFCDHBFHDAGFEGFGGCCGCBBCAHGE,False +700,29.0,20.0,21.0,24.0,24.0,23.0,13.0,26.0,EBHEBHBADGAHAAEEACGAFAAFBBFCHDBHAGCDEBDCDDAHHBCEAAFHAFCABDDEDEEDFHDFCDFBEGCFGEFAFGCHGDHFFEFHEDDEADBACACEFCBHCEHCAAEAECAEBFDAFHAHGAHGBGCBDHBDABDHBDHADFGEBABHFCFFAHFDECHHCHHCFCGDEGEE,False +701,3.0,7.0,7.0,3.0,6.0,6.0,4.0,11.0,CEFCFHGFHBHEAHECHEBBAHAEECHCDHCFFCHBGFBDDBGHBGH,False +702,9.0,6.0,16.0,15.0,12.0,8.0,10.0,9.0,FDCFDCDAHDGHFAACBCHDEHEGDEDDFDDEGCGCDBCDEAFCBCCBCGACGACHHEEHADDAEDCECFECFAGGBBEHFGHEG,False +703,6.0,1.0,3.0,5.0,2.0,9.0,6.0,6.0,DABEAHCFGGFAGFHHFCFFHDFHDCGFFGDEGDHAAA,True +704,4.0,1.0,0.0,2.0,2.0,1.0,3.0,0.0,BGGAAGEADEFDA,True +705,18.0,19.0,12.0,21.0,25.0,19.0,18.0,24.0,FDAHBFHDCHACHAEAEEBDDDDDGFHHFEHDDBDAAAFHAGGAGDABCHGCEGCFDBGCBEFHFDHFHHEGCFABHEBHCAHBBHEAEEAEGAEDEBGFCDHEEHGEFGEFBDFEGFGHFDHFBHDBGDACBAFBDFEHEECBEGBDGAEGEHBC,False +706,17.0,12.0,10.0,18.0,25.0,13.0,22.0,21.0,AGEHCDCDAEDAEBAGGHGGHDCHEHEFCEABEGBEBHAGABHABFFGGFGAFGDBGAEDAGFAHEEBFFAEFBEHCEFDEFEHDCHDCHDGAEGAHHFHEBEEGABGDHGDHBDHDHGCEDCHFCEEDDEHDGAGGE,False +707,18.0,24.0,22.0,26.0,29.0,18.0,27.0,19.0,HFHHGDEGFHCDHCEGFEGBDCEDEEFFBFCAEBBGABHADAAGABFDCGCBHABAGHDEDEEHBAHDAGDBGCBDHHDBEEGCFGCHCFHBFDEGDHDFHAEDAGDFGEFCEGGEBGCCCCECGECGCHACEGCEFCDFBDFBGBEABECBEBBGAHGDHDDAABGGBEGAEBEDFDDFEDE,False +708,20.0,10.0,10.0,16.0,13.0,13.0,19.0,23.0,FFHDFHCCACGGGHEEHDGGAGEAGHAEBAHDGHGGHBGAGFCBDCDDADDCEHADDDHBAHBAHBGGAFAAGAGGBGFHAHHDHGEHEFHCFHCBACEDBDDFCEFAHFAHEAEFHFABEDHE,False +709,5.0,8.0,2.0,9.0,7.0,8.0,16.0,8.0,CGDAGDFHDGABHDEFFBFFBEDGGAGGCEGHHGADEFDEDHEDGFBGHGGHGGBGBBAHEFB,False +710,2.0,0.0,1.0,2.0,0.0,3.0,1.0,3.0,FGHDDHAFHAFC,True +711,11.0,11.0,7.0,14.0,11.0,15.0,19.0,23.0,DHDDADGHBGFBGHHGDGAHHHGHHGBCEDCHDHDECGGFDDAGBHGBGDAHBFFBFFCHFCFFHBFHEHHGAFGAHGHDCDDAGEHGEHBFHEGBAGFAEFCEABEAEEF,False +712,22.0,16.0,19.0,9.0,22.0,12.0,19.0,16.0,HDGBAGAAGFEEFADBADHGCGCDBCABEACGHGEABEAFGHFEHFGHFGHCGEFGEFHHACDAHFCGECEABEAEEBBABHEFEAGEDGBCEHDEADCBDABCHCCHBCGAGHACEACHFCEEBAEBAGBGFCC,False +713,10.0,16.0,20.0,25.0,19.0,11.0,23.0,14.0,FDCDDBFDGCEFFEBBEBBFDBHCFAAHGDHDBFFGFDACDAEDGEGGDCADCDDGEDGEGCEGDADCGDCBBHEBDECEHCEHGBHACEGGDCGHHGHDGCGGCGCDHHDECCEBEEDABBAGBGEAGEFDHFBHCC,False +714,7.0,8.0,11.0,9.0,14.0,8.0,8.0,14.0,AADAFBHGCCGCDHHFHBCHDCHDEHEEBFBAFHDGHDHHEAFEFCEGDHBEHCCFCHBBEDEEAFEAECGECGEGDBG,False +715,4.0,5.0,2.0,4.0,4.0,2.0,5.0,7.0,BEEHHBHHCDHCGEBGDBDHEFHFAAGAAGBDG,False +716,2.0,4.0,4.0,2.0,5.0,4.0,1.0,3.0,GBACBHFFEFFDHBDHEAEECECCB,True +717,15.0,12.0,19.0,9.0,14.0,21.0,18.0,23.0,DBHAHHEFBFAGHAGHAEHFEAAGCGHBFHBAHDCHCCDAGGHGFDAFEEEGECHCCEBGDAGCAGHGFACDHBDGBAFCFFCDFCFFCEGCBGFBCHBHAGHFHCBHAFHCFGCEGCEHFEBEEFFHDFH,False +718,21.0,29.0,17.0,17.0,19.0,12.0,14.0,21.0,BHBBDDFDBFDBDHADHBCABAHFADGBECCFDBADGEHHBBEGHEDHCHEBHBHHBEEBCABFBBFBFDAFABDGCEGCEGBEACEBBBBCDCHGEDEEGGHGAFGABGABAAHAHHAHGAHGEHCDCFDCFEEDEBHCCCACAAFABE,False +719,15.0,18.0,17.0,14.0,22.0,18.0,20.0,22.0,GGECFCHFHBEHBEDBEFBEHBDHBGAGFAHFAFECFDFHGFBGDEHECDGCAEFHEFBDGHDGDBGBBGBHGCCGCCGCHHEBBBBEEAHHBFEACADDACGCFEHFEHFAGAHGEHFAAFCHDCEGCEFDEGBHGDHEECAADA,False +720,4.0,4.0,3.0,2.0,1.0,3.0,4.0,4.0,BFBBFHBCHAHDAGEAFCADCGGGH,False +721,22.0,14.0,33.0,22.0,22.0,16.0,25.0,18.0,EGACBDEEDAADHAHBABBAEGAEGBHCBADGFBCFBAACFEEFEDHBDCGECHHHAGEAFECFEGFGAFGHCGAFGEFECFGCABEEGGDAGDCCHCCHGDEGBEDBACAHDACCCBHCAHCHDGHAECDDCDHCFCDAHHCECGECGDCGFGECCCFCCDDGDDGDFGBF,False +722,15.0,12.0,9.0,7.0,14.0,11.0,9.0,13.0,HFDHFEHEGDBCFBCAAHFAEFGGDBADEAFEAHEAHFBGFHEAGEDGBBABHGEHGECCABCEHDBADCFEEFAHFGHEAHACCABCBB,False +723,25.0,27.0,19.0,19.0,29.0,24.0,29.0,27.0,CHBDGEDBEGCHBAGECBACBGCEACAGCAGEFHHHGHAGAEDHGCGBBACHDGDAGDAGBFFBGFBDFEAFBABACDEFFEAHHAEHGHHBFABFACHHHEBGBBEABEAHEDGEDBFDCHDBGGEHHEGHFCHFHAFDAFEGGHGECDFGGBGCFEAGECBECBECFEAFEBFEHFEHBDDAEDADDFCBFEBFGHG,False +724,7.0,6.0,4.0,4.0,2.0,2.0,7.0,4.0,BACDABGAGDBGHFGHFCHAEGADGBEGBAADCBHC,False +725,13.0,14.0,14.0,9.0,9.0,11.0,7.0,5.0,ADEDDFDEGBCACCABCADGAFGFGAEGAGBAFCFFHBBHCBDBFEGAEDBDFHCEECEAFBAFHCFCCDBCABCABHBBEC,False +726,6.0,1.0,2.0,1.0,0.0,2.0,3.0,0.0,ADAAGACFACFBGGA,True +727,22.0,23.0,26.0,27.0,23.0,28.0,17.0,22.0,ECCBCCADCDDGGAHBAHFHCGHEGHCAHGHHGBEFCAFBAFHDFAFCCBACDGCBGHGEAGCDECFEBEEDFDFBHGBAGBADFEDAHDACDGEFEEHGEHFAHFAEBDBBEBFEDAEDHDDCFDGDABEGDFHBCBFDFFACFAFHEFHABDCCEABEFFHCFBFFBFCBDCBDCEDGDAHDCHCE,False +728,0.0,0.0,3.0,1.0,3.0,4.0,2.0,2.0,CEHCFCGFHDFEGFE,True +729,17.0,19.0,22.0,26.0,19.0,16.0,18.0,23.0,GFHGAGFACDAEAGFDCBCCBCBBGBDGEGCEHDDADHEDBADHDEFBEDBDGBCGAHHAEAAEBDGDGGDGABBECDEFDEFHCAHBDHBHGGDFFEFDCCDACBAHEABCHEEFCEFHGFHDEBGEBHHHHCFHEAHBAHCDDDDCGFCHFCHCCFCD,False +730,10.0,12.0,10.0,12.0,5.0,3.0,7.0,9.0,GGBHAHCBEBDABDCEDEGDCGDAFAHGAHDADDACHACGECADHABCCGCBBCBBHHBFDEHDBDFB,False +731,8.0,9.0,15.0,9.0,17.0,19.0,15.0,6.0,BHGBCGBCDBCFBCBACFAFEGFECFEGFGCEGCGADEFECHEDEEFFEFFGFFGDFCEGCACBAFADCGEEGDBADFAHHDGHGFEEDCEHFFBGEC,True +732,15.0,25.0,16.0,23.0,8.0,23.0,16.0,19.0,CCGCCHDFHDFABAHDHGDBFDHDDBBDHBGHGFDDFGGHEHABDFCHFAFCACBBDDBDFBDABHABGBEDBEDAFCFBCFGEBBHCBABGABGHBGHFGCFGCFGEBEFADCHFHFFCDDCHAEHBDGADAADGFCFFBFEBH,False +733,26.0,12.0,25.0,16.0,6.0,12.0,11.0,16.0,DDEFFEHBCBCAGCHGBHAAHCAHAHHBHHGGHCFDCADCADABFCCGAFDAGHCCCACFADFADAHBGBCFFDBCHAFAAEDEBAHBAEFAFBADBDDADCCCCCCCACCGCDGADGAEAHGH,True +734,24.0,26.0,16.0,18.0,21.0,14.0,24.0,22.0,HGDGADCHDBBAEBDEBDEBEEDECFBCAGCBCHGDBGEBDEBEEBDGBGHHFCDDHGDAGHADEBDAAHBGBAHAEEGEBGEBAACFHCFACFHFAHFAHFDHCBEAHEHBCHAHAEDGFBGDBGFBHBEGDGGACEACACBACFAGGEGBFBHAGHAGCFGHF,False +735,22.0,22.0,29.0,19.0,27.0,26.0,31.0,18.0,FACFCCFCAHCGBBDADAGDFEEFAEFAHADEGDACBFCBFBHGCGGCFFBGFGFBBHHBCAADGCDECGGCGGCAGCEGEGGDDGAGHAGHFCFCEGDGCFFBDEBDFBFEEEHEHBEAEEAEEAGEFDEGDBBEHGAGFDGEDHBCHGAAAAABCECCECCHCCDFHBFCEGEDGFBFCBFHBFHDHHCGEB,False +736,3.0,2.0,3.0,3.0,1.0,1.0,2.0,0.0,DCBDCBGCAGADEAF,True +737,25.0,20.0,13.0,20.0,9.0,15.0,15.0,17.0,BBCBGDDHBCECEDCBDHGDAGDAEAACDBCDAAHFAEFDCFAFBAGAGBABHABDABFAFFDDHHHHBFHDFGGHDCFGGHHGAAEAABCAGCBGCEGABCADEBBEFBDFHGFHDFHCFHAADEBDGADABH,False +738,15.0,21.0,15.0,20.0,23.0,14.0,16.0,14.0,HBDCBCCDFDDBDABDABDFDHHBEGEFGEFGECGECGECABBEGFEGFGFBABDGBHGBHCAEBBEBEDDDBHDAFCACCEBHGGDEDAEACFBFFBGFGEEHHEHEAHADFCDCAFCDEBDCDEGEHGAHAHEABE,False +739,6.0,4.0,7.0,3.0,11.0,9.0,13.0,4.0,CEEGFEGFDGBBEFGGDEDHCCEAFEAFBAFGACCAGAFEBFEGFGCHGEHGECGHG,True +740,18.0,18.0,17.0,21.0,22.0,23.0,24.0,19.0,CHFCHDGHDGBDCFEEFEDGHDAHDAECAFGFFHFCDEGAHBDBEDHEGAEGAEFBEHAEHABBAHFGECAHBFCDFDEEDEGDACBFHDFBGFGFEEFAEFCFBCHBDFAGGAGGAGBAGBEGEGDDGCDBBDBGEFGDDGHBBECHFCHCCFAGHCFCAH,False +741,9.0,8.0,14.0,9.0,12.0,8.0,10.0,8.0,HHAGBAGCACBHFBHFDEADGBFGCDABDCEDCEFABGECCEBCDGEEEEECECCFACHAEFGGFCGFDGDACDHHBH,False +742,12.0,15.0,13.0,8.0,14.0,16.0,4.0,12.0,AFFFBFFBCEAFAAEBHDAEAHBCHFCHBDHBFHBDEBAHGFHFBEGCFHCEAFEAHABDBEDEEFECHECGECFHCFCCDCCGBDABDBBEFA,False +743,10.0,6.0,7.0,8.0,13.0,10.0,9.0,5.0,AFAAEBGEBEECEEDFCGGHDGDFCFGHFBHEHDDAADEDDECBEFBECHCGAAFFAFEAGEAGFBGC,False +744,4.0,4.0,4.0,5.0,4.0,3.0,5.0,8.0,FHDHHGAHBHDDHGDAFEACEACEGGFHBCHBCGEDB,False +745,5.0,2.0,6.0,1.0,2.0,4.0,4.0,5.0,CHHCFFGFGAAGAHGCHABEACEHCBFCD,True +746,6.0,7.0,9.0,8.0,5.0,5.0,6.0,0.0,GDGGFGCEDBEDACDCCFACFCDABDACAACBEBBCFBFEEGBDGD,False +747,23.0,21.0,27.0,20.0,27.0,21.0,28.0,26.0,DEADBCCGHHGHDBADBADBEEBFEBEBGGCAEDAHDFDGHEAHEAGEDGEFGBAGHFHECBCAEEBEGFFFHHHDHHGACGEEDCADBAFBHGBAFBDFCDCBGHFHAFCCDCGACGAFGCEGCHBBDGCHFDAFGGGBHGBHAAHCAGEDCCGCCHBCHFFHEFCEFAAGACGCEECECHEBHEGEDFEDF,False +748,3.0,5.0,1.0,5.0,3.0,2.0,3.0,3.0,DBGHEAHDADDADECFEGBGHBFBB,False +749,11.0,7.0,13.0,10.0,10.0,9.0,18.0,6.0,AGEGGFDHECGGCGBCGECBCCEFCADCGHCGEGBEBDECGGCAFHDDHGDAGDAEAEFDGADGAFCCFBAFEFDGFAGBAHBH,False +750,19.0,21.0,8.0,26.0,26.0,23.0,18.0,20.0,FEHFHBCHBCHAAHDGEABEDCECBDDAFFAFDGDHCDEGDFADCHDEDEEGHAGDFGCFGDFAEBDFBAGHAEEAEAAFAFBAFBEBBDDBDHEFHEHDEBDEFEBBAAEAEGBEDFHDHGBEGEFBHCHFBHEGGEFGEFGDFHFHGDBGDBFDBHDGA,False +751,10.0,15.0,9.0,6.0,11.0,12.0,12.0,15.0,GDEEDHHBBFGBHHBEHFHFBDCEGGEGCBCCAFCEFBECHEHEBHBAABFABFABFGFEGAEBDHCGHAGHAFCACGAHDHFDHGBBGF,False +752,16.0,16.0,21.0,19.0,22.0,24.0,24.0,17.0,HHEEFGDFCDFCDFGHFHABEGECBCGBCGBFGDFBCBAFFGCAGCAGBAGHGDHDDHGDHGEHAECADCEFFAFFDEGBAGBCEBAHFACCDCBGEHDEGAEFCEDBEHFHAEDBGAGFECFGGAGGEFHDHECHECFECFCBDCGABDBHDFEFFED,False +753,5.0,5.0,9.0,7.0,8.0,5.0,5.0,7.0,DHCDCBFEBACFGCHGCHGEDGDDEDHAGEACFACEAHEFCCFBDHBHBEE,False +754,1.0,1.0,2.0,5.0,0.0,0.0,2.0,1.0,GGBCDDCDDADH,True +755,3.0,4.0,2.0,11.0,7.0,7.0,7.0,3.0,DDGGDGFFEFFGGDECDEDFEDFBBHBGFBHDAGCADHDDEAEE,True +756,13.0,13.0,9.0,10.0,17.0,10.0,13.0,12.0,CGAEDBDFGGHCGBCFAEEAGFBFFBFFBEGEEBEEHEECDEGACGEHAFGADHABHAHHCGHFGHEHEAHGDDCAHFAEBAEDCBBCBBGBDEDDA,False +757,8.0,8.0,4.0,5.0,4.0,3.0,10.0,2.0,BDEBGHGGFDGFDAFCGGCEBBAACEDCADHABGGBGBAABGAE,True +758,26.0,19.0,23.0,17.0,12.0,22.0,20.0,22.0,DDGDEFCHCHHDHHCHGGHDBAFBFGBFEBCAFCAFHFFDCCDCEACACBFEGGHGGDFGDHCBGAFCAFEDBEAEEBDFGDAGBHBHHADGCDFCAHCHFCGFCGHCBHABDABAACHAFAAHCBHBFABFAGFDBFHBEECGAGAAGFAEDABACCEGH,False +759,4.0,1.0,4.0,4.0,4.0,6.0,8.0,4.0,GDFGAFGDGCFGCFCAHAHDFHEEHEEGDGAFGCB,False +760,2.0,2.0,0.0,1.0,4.0,1.0,5.0,1.0,ABEDBHAEGFGGEGGE,True +761,21.0,26.0,28.0,30.0,24.0,24.0,21.0,23.0,FDCHDHHDFHCCGFFAFAAGABBDGBCGBHGEHFHFBCEACEHEHBEABDBBABAGBFFBHDEEDBGFCGFCGFBBCBBDBGGGCDECDCFECFEABGCDAEHEHBEDDADFADGAEEAEFDCFHCFBCHBCHAEDDEBGEDGFHEDCBACDGFFCEGCDACABEGCDGHEECFCFHDFBDHADHADHACGDCDDHH,False +762,24.0,12.0,13.0,17.0,17.0,14.0,9.0,11.0,CEAAEBDEFDBCCBABBACBDBDDADGCGHAEHAEHBEFAEFAFCACHBHFEHADHFEFAGFGCDADDACDEDGEBGECAEBFEBEADGACFAHAACAAEADDFFGAFGCDHDHEFH,False +763,6.0,8.0,13.0,10.0,5.0,9.0,19.0,14.0,HGDFBDFGCHDCBGCEGCEGHGHHGACGFCAEEHBBGDHGCCGFAGHADHBCGDDBEAFDHFBHFDGCAGCGFFGHBGHCGHCD,False +764,27.0,23.0,30.0,22.0,19.0,28.0,33.0,17.0,AACCCCCCFBCDCCGCFBEFDGGDCGFCFFCAECBGBFCBGEHDEFGHFGHACHGFAGEAFFFCHFDGCHGDGCFGCFGCAGDBFFBECEGCGGBGHBDAEDABFABFDBDDBDAADGHHFBAECEBHAHHEFADFADFACAACGECEEAGEABADBDHEGEDGEDBFAHGAHGAGCDFBAGBGFFDCHBHEACGGBGB,False +765,18.0,15.0,16.0,11.0,14.0,19.0,16.0,15.0,CEFGFFADDDDCFAFGAFEEEAEHBEHCECAEBAECABHACHFCFGBGGBDABCFFFGFHGHGDEDABBABBAHFACGDFGDFGCBEEDFHACHGCHGBHFEGFAACECDGCHGBHCBHBAHAF,False +766,2.0,0.0,3.0,2.0,3.0,1.0,2.0,7.0,HHEHHCCHDGHDFCEHAEGA,True +767,17.0,7.0,6.0,11.0,18.0,9.0,7.0,8.0,HEEBEFBEBEEGHEFCEACFABFHBGEAEAACAADAADADDAFABDAGDEDAGDEDHCHFABEGDEFDEAEECEGHHHFGFAC,False +768,7.0,8.0,17.0,12.0,13.0,9.0,9.0,18.0,EBDDBCDHEEEGCEFDAFDABCBBHFGHGGHDCHFEHFAHAEHCFHCAHEHBEGECHEGDECCCCDCBHCGHCBFGECACHAFHDCDDHFDHG,False +769,20.0,21.0,9.0,15.0,21.0,8.0,21.0,20.0,HEDAEDGBFGHEDHEDHEBCGAEAAFAABHDHAEHGGGBEFDFFAAEAEHCHBCHACDBFGBGABHBBEBBAHBHHDABDAGDHEFEGBGGDCGEBGCHECHECHGBEDBEDBAAFGADBAGAHGBGDCGEEGEH,False +770,21.0,9.0,20.0,15.0,18.0,14.0,11.0,20.0,AGHAHEGHACBCDEHDEHEECGABBADBFCHFEABCBDEAGEAFEAFECFDCHDBDFADCAGCADCHDEADAAHFABFEDCEGCHFHHCEACGDDGHFGAFGAHHHECAEHDHHABCEFCHFCGCCEF,False +771,4.0,4.0,4.0,6.0,5.0,8.0,8.0,13.0,HGCHGCEBAEDFEDHAHHGEHDDBGDEGBHGFHGFCFFCHADFFBHGAHFHH,True +772,4.0,7.0,15.0,14.0,7.0,5.0,7.0,12.0,FCECCEHCHDDHEFHDDAEHECCGDDBDDBEDBFCGHHHBHHBCABCHBCDEDGCHFDACDFCDGCGGAGC,True +773,15.0,15.0,19.0,12.0,10.0,13.0,9.0,11.0,CDFCAAHAADAADBHCGEAHFBGCBCCEGCDCCDEAGHAGECHFHFFBFBHFBADCADEHBECBABBHFECAGCDDCFFFHDFHDFAEGAEGBCCBCEDGBBCB,False +774,17.0,15.0,18.0,13.0,14.0,14.0,9.0,11.0,BDADABGFCGHCGAGHAGFFDCCBAGFHDFHCFHCBACEACBAGBACBECFEBGABFBFFBHHBDEEDEAHEAGFDEFAFFBDHBECCCCDCEACEHCEAADDCBAEDDEH,False +775,12.0,10.0,12.0,10.0,14.0,18.0,9.0,17.0,FFDFGDFEBAEBHFHFFBFCBFCBACEGDDCHCHDGBEEAEHAEBACCCCCAHEAFFFFFHGBHDAADAHEFHGFHEDCAHHADHGFGCHGFEEHDEHBEGB,False +776,15.0,9.0,14.0,7.0,14.0,8.0,10.0,14.0,FGGCGFEGFEGEBBABCCDCHEHHCHGFDGAEHCEFCEGCAACEACADHABADBFDCEDAABEACDGCHHCHAFAGHEHBEFEAHBAHBEH,False +777,3.0,5.0,7.0,4.0,6.0,7.0,4.0,2.0,ACHDGDFECAEGAFGEBDFBCFCCFHCEECDBGFBEFB,False +778,13.0,16.0,17.0,23.0,18.0,12.0,11.0,15.0,HGEDGCCFHBDHDDECFEHAEBAEBHDCCDFCDCHGHFGHAABCAFCGHCGCEFFEBAEBABBEHBGHBFFDDGDAEDAEABBHBBHEDFEFCDCEDCEDHHCGDDDDDAGFEBBCDDADCAEEG,False +779,0.0,0.0,2.0,3.0,0.0,5.0,2.0,1.0,DCFGFFCDFHDFG,True +780,4.0,14.0,9.0,15.0,13.0,16.0,18.0,13.0,GFHBCDDGGEFBDFGDFEDHCBBGEFEAFEHBDHGFFECCDHGHCGBBGBEDHDDEDEEDBCFHGDHGFHGFHGFGGFGBFGAFHCDCAECAEBBEDBGFBH,False +781,14.0,11.0,9.0,17.0,16.0,19.0,16.0,13.0,AHAEEAEBDCFCAFEACDFGBGHHFBHDBFDCHDHHEHFDGFAFEABDGEEEFHFABFCGFGGBCHBEGBHACEADGACGCFGBFGAFDAGBAGFDHEDEEDEFDEFDGHDGDDF,False +782,17.0,30.0,15.0,20.0,20.0,24.0,22.0,25.0,GBEGHHGHFDDAEABGCBGDDCCHFEBFGBGDBGDBGCAAFGAFDEFGEFEFAEFACBGEBAEBHBBHBCHEHHEAHDDCBCFDADDHDGHFEHBHFBDBDHAFHFFHGGAFCFGCHEEHEDFAGBCHBFGBCGDCGBHBBCFBDBDEBFEFHHCBHGBEBAEBHEFAAFDAG,False +783,18.0,12.0,19.0,16.0,8.0,23.0,23.0,21.0,CAEAGEACHFBBCABCACFADGBFCCFGDFGFBGHEGHCCHABHGBHFBGEAGCCFDAFDCHBGHCGHDFEGEHGEHFDHBDFAHFAHCGGCGDBFAGFHHFHGFDDHGHFDAGBHFHEDDDDCCGCCGADFAFGAFAAF,False +784,26.0,24.0,29.0,15.0,21.0,16.0,22.0,14.0,GEEGAEGABFAFGEBBHCCCGGBHGBFDAADAAGAFGBEBBCCGCAAHAAHDBEEBGEDADDADDAECAECBEBHEFFADBCGECGCCDCGACBACFDCFHFDHGHBBHDBCECEGCBGEBCEFAECCCHFGECGCBACBFFBGFHCECAFBAHBHHAFDAGDECAG,False +785,1.0,0.0,2.0,2.0,2.0,6.0,1.0,1.0,FFFEFFEDFCDCGAH,True +786,20.0,28.0,18.0,25.0,30.0,17.0,20.0,19.0,ECEDCEBGECGBDDAGEBEEHHADHDECGEDEEFEADEAFEAGDBDFCEFBDHBHAGAAGCAGCHHCHDBDFFEECADBAGFCBBEBDEHHEBHFAHFBCEBFEGEHADBDHBDHCDBGDBHDCGBFEADEADHAEAGBBCBACEACFDCBDHBDGEGGEBGEFGBFCBGHFGFFAB,False +787,5.0,3.0,2.0,6.0,9.0,8.0,2.0,4.0,DAEDAECHGCHBEFFEFEDFEDADHEDAEFBFABFHFEG,True +788,5.0,9.0,7.0,1.0,4.0,3.0,1.0,5.0,EBABAACHBEHFACBBFBBEABCDECHGCHBCHFC,True +789,12.0,4.0,13.0,8.0,13.0,16.0,10.0,11.0,ADAAEBAEGDFGHFGEBGADFAFFAFFEFCECEEFEGFEDFCCECHHAFDCFGHEHBBFAGFGHACECGHCDCCHCCHDFHDGAAEH,False +790,6.0,10.0,8.0,9.0,9.0,8.0,9.0,13.0,CEAHHCFHCFHBEACFACDBGDBEHBGGCGGAFDHFCHFEHBABBHDHGDEAHGBEBEGBEDHEDGCDFHDF,False +791,8.0,14.0,12.0,15.0,11.0,8.0,8.0,8.0,EBHEBDCADCAGCABCGDEADEAEECBEDADFEHECHDBHGEGCFDCFBBBHBBDGHDFFDFFGBGHBACBFCHGCDCDDEBDA,False +792,10.0,22.0,18.0,14.0,21.0,20.0,16.0,23.0,DBGEHGFDGFECFHGFEGFBAECAHFHECBABHGFACEBDGBCGHCECAEGBBCDBEGEEGHEAAECGBFHBFHAFHCFBCDHCDHDBHEAEEBHHBCCBFHBCCBHCEDDEDDEFFHHFHFFHEFDAGBFEBHCBHDBFDGGG,False +793,23.0,21.0,27.0,21.0,31.0,27.0,29.0,18.0,AGFCEBGEFGHCGECBEFEGFCBFDBFHCCHCBEDDAGFBDCCDCCDEGHEGHAFHGGHDGDBADBAGEAEAGFFCDACFACFGCFGHFHEFHEDECBEBHFGDEGCEGDBAFCCFACEEBDDHCECDEADFGBBEABHACFAEFAEHAEHEGBFCAHGEFDEAAHACGDBEFBDBBCBCEHGEFGFGGFAGDAGEG,False +794,24.0,20.0,28.0,18.0,24.0,31.0,23.0,26.0,HHAHBAHDAHGAHECHECDEHEEGEFCECEFDEDDFCDFCHBBHBHFCGGEHCAHCDGAGADGCHGHFGEEGAEBABBAEFDGDHFFEGCBFBGHBGABDBCAGCEFEBFCFAAAGAGBABCAEAAFFBFFBEBDDFFCFFHFFECFHDFGCCACFAFHCFECECCFGHFGBAGBCDHHHCCHDCEDAEDGHFG,False +795,31.0,20.0,15.0,24.0,20.0,24.0,18.0,24.0,DDFDGFDGAGEBGEBGFHEDHBDBGHCFHBDCEACAGHADHGHFGBFHCDHDHEEHGGDGGEGDFGAEAEECGFCBFABFADAADAHGCFFHBFBAFDAFDBEBAAHAAHAAHAAFABCABEBEFDHDHEFHEDABHCDDDHBHCCGDHAECAEBEHAFBACEADFBFFEAFCAFC,False +796,6.0,5.0,4.0,8.0,8.0,11.0,14.0,10.0,AGGGDBHDBEDHHCHFAGFGEECFFAFFAEDAEFEGDBGHHFHDFGCGHAGHGGHGEBCEBDFGDF,False +797,13.0,13.0,14.0,16.0,20.0,20.0,14.0,14.0,FDCFDCDGCDGAFFFFHFBDGAEEFDHFGHGBFDAFHGFHGDEDDEADCHGBHGBACAHBECACHEEEEBBDFCEBBEBFEHAGCEBAEFCEFAGFAHFGHFGCFECADCGEADEHDEBDECHB,False +798,16.0,22.0,7.0,24.0,22.0,17.0,26.0,9.0,EFHFGCFGEDGFBGFBHACDACDAGBBGECEBBBDDADDADHGGGBGGBFEEDEFDEAGEAGEAFEDDBDGCDBBBGHGDHCDBDDEGEAFEADEABABBHFBFDBFDFEEFADGADECHBGEGFFGBBHEGGFDGAGAHGEE,False +799,20.0,13.0,23.0,31.0,20.0,22.0,27.0,27.0,ACCDDCDDCHDEGDBGEBHAHGDDDCDAHDGFAGHAEBFECFBCDECBAHEACGAEGFEFFGHADDGDDACEACECCFFFDFGHBHDBHDCFGCGACFCDHCBHEFDBDGCDCDEFDEFAGHAFHAHHCEGGDBGFEGHEHHAGFEBFGAHCBHCAHDADFGDEHDHHAGHFEHGEGGDGGBF,False +800,7.0,7.0,4.0,8.0,5.0,4.0,9.0,2.0,BFADCAGBDGDDGDDAEDEFBEABEBECGDGHAGHAGFGBABCGFC,True +801,27.0,24.0,11.0,26.0,22.0,20.0,24.0,21.0,FDEFHBBHDBDFECFEGGEGBBBFGBAGBGFBAEHFGHCAACHBBHBDHEABEFBAFGEDECDEGFGGHDGAGGAHCBHEEEFHEDHADFDHGEGFAAACDFDDFBDCEAHEBHEAAEFBDABAABHABDAGDADFAHFGHFGHCGDFGEBCDBDAGDBGHAHDADAGECDACDE,False +802,24.0,16.0,21.0,28.0,24.0,24.0,17.0,24.0,EHGDHECEADBDCGFCGDCFDEFDHFEEBHECAGBDHDDAAAAGEHGCCGBEGCEGEFDEBDAAGEFCAFABFBEAGEAFECCDDCDDHDHFDEFGAACEEEHGHHADHFHADHFCCAHGACGAHECBEBBDFBCFBHADDAGDCDFAHFAHFABFEBFECFHDBHDBHDGHFHFCDF,False +803,20.0,21.0,21.0,27.0,21.0,19.0,21.0,15.0,CHCDAADHHDHFEEFGGDBGABGCBCFAHFHFFGBDEBFEAFEHBEFDEFDAHCGGCDFCGCGECGEAGDBCEBGAADFADFCDAEDBDAHAEHAEGGEGAHGADFCHCCHBDBBGEADDADDBFDBCBBCBEGDDCEEAGDCGDFDEGBEBBFBAHCEHCFCFD,False +804,1.0,2.0,0.0,1.0,3.0,0.0,1.0,2.0,HBEHBEDEAG,True +805,17.0,17.0,12.0,11.0,12.0,11.0,11.0,14.0,CACCACHGBBBBABBDBGEGCAGFBEFAEBAECGBHHHHHHHFDEFGCGGBBBAFFAFFACAACGACDDEFEEDEADHAHCBHDGHABHEBGCFAHBEDDDFEDA,False +806,8.0,5.0,13.0,9.0,8.0,4.0,5.0,7.0,AABDACCACDACDBCBEEHEHCDHEDGEDADGFFCCBCGBEHCHHDGHECCFDCFAEGA,False +807,2.0,3.0,6.0,1.0,2.0,2.0,5.0,2.0,CCGFCGCAGEGGHBBHBDCFECA,True +808,8.0,11.0,13.0,11.0,20.0,5.0,10.0,7.0,EDGEBEBGEBGECCCADEEEBCEGEDBECBCCDAEDHECHAGHGCDDFDBFEBFEBEEGEFHAAGABGDFHDCHACBEDGECAHC,False +809,19.0,18.0,17.0,18.0,21.0,24.0,23.0,21.0,GGGGAGFDDEHDEHAEFAGHHHHCBECAGCEGEBGABGFBDCHDBHEHHGHFAHGCBGFDCFDCFBEFHHDAGFFGCEEDHGDCADAAHEEDEBHHFAFFABFACCBCABHGCGDBEDFEGFCGFBFBBCBBDFEGFECFAHDAEDAEAEEDCBGGFFFHA,False +810,20.0,16.0,11.0,12.0,13.0,19.0,22.0,18.0,AGFCHFDDFBEHGEHGBHGDCGFCHEGAGADFAGGAHAFBABBFBBGGAABAAEADEBDGCHHEBGCAEAHEGCAGFHDFHFEHAGDGFDBFBBFADCGDBGHFGHCCCGCDGBBAAFFAFHHFEHFEHEE,False +811,17.0,22.0,15.0,31.0,25.0,25.0,18.0,24.0,HAFEGGECCHDGGGHDGCDGDEAAEHGEFGBGGHGBEFEEBCHAEHCFHDFHDFGDGDBGDAFBFFBFHEECEDBEDHDBEDBFDBFABDEFCHAEFEDHCDAFDCBDABDABFCBCDHEHFCAFCDBEDACDEHFFHFFEEEBDEHEBHBHHAHGBHDHGDBCABDADDFDAFGAF,False +812,13.0,7.0,5.0,13.0,10.0,18.0,4.0,11.0,FGEADHABHAEHFCHFAAEEAFEAFDAFABEGGHFFBBDBHCAHADHBFADCCHEDFGDFDDBDFEDFEHFDAFDFFEHFC,True +813,30.0,25.0,17.0,27.0,18.0,16.0,23.0,20.0,DGAGBDGFDGFAAACAGCEFHDAHDBHCBACFACFGHFEFBHHBDHBAEDAHCEFDGCAADABGABDEGDGCAGCEGBABEABDFGDFADFABGBHGAFGDDGHDAHDCDDEDGECHEHGFBBFHBEBBCBDGGHHCEHBEGBCGADAADBHEFDEFHEAADCCHEDECAAABABB,False +814,24.0,14.0,14.0,18.0,16.0,18.0,16.0,21.0,ACBABDDGDGCCHAEHAEFDEFGHFGHFGDCGEBFDBGGBFACACFAGEHGBAFBAEAAEFHEGHCAEAADDHCABFHHEDHDHACHAGHACHGCHCHDDHABAAFADDBBABFHCFGCFEDDEDDHFEHFEGFBGEAFEB,False +815,13.0,9.0,13.0,16.0,13.0,6.0,10.0,11.0,EBHEDEGACDDCDGCDACHFCECCHGBHGBHCBEDAEDHFAFEAHEADAAEADDFFEGBDGEHHABGGHGCCADCDDCDHCABEFBEDBAG,False +816,3.0,7.0,5.0,5.0,0.0,0.0,5.0,2.0,DDCDBADBHGBGBBGCCCACBAGBDGH,True +817,5.0,5.0,2.0,2.0,3.0,8.0,12.0,6.0,HCHGCGFHGAEAFGHFGHFGFEADEHDFBGGGGGGFBFABABB,True +818,1.0,11.0,9.0,4.0,7.0,7.0,8.0,7.0,GABGHBHDBHCBECBFGHFGBCBBFEBECCEFCDFCGHCFCDHEFGEGBEBHDG,False +819,2.0,2.0,5.0,5.0,0.0,2.0,1.0,5.0,CDACFHHFAHDBHCCDCHDBGD,True +820,11.0,24.0,12.0,20.0,8.0,10.0,7.0,16.0,DDBDDECFEFFEBFBBABHAFHGGCCADEHHABDDDDCGHFABFABFHDCBDBGDBCDBFEHHCBHADHADBADCHDCBDHBEHBHABCGBEGBCDCGHBDAEFBBBH,False +821,9.0,5.0,8.0,7.0,7.0,2.0,8.0,6.0,DCDGGAGGCHGCHBBEEAGEGEFCEDADAADAAFCABCEHCBHBEHCAHDDG,False +822,4.0,6.0,4.0,6.0,8.0,10.0,6.0,8.0,DGEHGBHAFDDFEAHBFCBFCDFADFCDHGEHGBFCBHEHGEBEEHEFGFFA,False +823,11.0,21.0,15.0,29.0,14.0,28.0,25.0,13.0,GCBACBGFGGFADDGDDHCCBEGFEGBDBBDFFEFECFBCFBFFGFFGDDHHDFHEFDEDDAFAGFDEBEBBDDHDEHGCHFCGCAGCFGDGGHCFBBFBDCGGEGDEBAHFDEADEADFCDGABFDDFGDCGBFADABDGBHGHGFHFDHFEBCB,False +824,9.0,9.0,18.0,17.0,22.0,11.0,12.0,16.0,HDHHDBHCFHEEAEBDEDAEDBEDBHHAFFDDFCHGCHECDDCEEEFEDGADGCDCCHCAHCAHCEHGECGEGGHFDCCEECACBGCEGFGDEBAFFAGCGBEEEFDEFDBHBH,False +825,13.0,14.0,23.0,11.0,13.0,29.0,17.0,16.0,CFBCFDDFBDFBHFHGFAGEAFFBHFCCFCFACFACFDCAEBHFGGBAGDEEHBGFAGFHEDHGFEBFHHFGFDCFCBHEEGGCFGEFBCADHHDBFDBHDHACHCCGCEGAGGFFACCAECFHCGBCEFCEFCAB,False +826,5.0,8.0,5.0,6.0,10.0,4.0,3.0,7.0,DDEDAGAAGAHCDDBBHBGEEFHECEFHEBHEFHECEECBBCHBDFBA,False +827,20.0,17.0,26.0,28.0,18.0,27.0,26.0,26.0,ECFEGFEHFHHFABFABFEHABHAGDBHDBHDBGDGCDGHABHAFCEHDBHGCDCEFEEADECDAFBGFEGFBAAGDGDDEEDHDABDABFAGFDGDDADCBDAHGHHGHHFFFFFGCDEDGGCBCFEDGCCGCCDCEFFHHAHDBHAFCCFDGBCCHACHDEGGEGCCDCCHCBGFAAFEGFGCHHF,False +828,10.0,8.0,14.0,9.0,25.0,17.0,21.0,17.0,ECHGCHBCGEFDEFDECDEGBECBHBHHFFGGFGGHDGHACCAHHBDCFGAFGAGEEHEAHECEEHEEBEEGDECFEBFECFHFFGGGAEGHEGFCFBAGAHEEGDAAHFHCFGEEDFGDC,False +829,3.0,3.0,1.0,2.0,3.0,6.0,4.0,4.0,DHEHHDFHGGBAGAFEACEGFBFFBF,False +830,13.0,14.0,5.0,14.0,12.0,16.0,14.0,22.0,GDABFFCGFEHEGFFBHCBHEDHFGFBBFEDEHDHHGFHAEHAEHCEHABHADGEDGAFGHBCHAGHADHEFHFFGFGBAABAABDGBDCHDGBEAFHHDDBDHBFHDEG,False +831,30.0,21.0,25.0,25.0,16.0,20.0,17.0,32.0,ABDAGCAGBEEEEFEEFGBFGACGBHGBHCAACAACGCHGHADHACEECHDHACHFEGEAGDAHDAHDGBBHBFHGCHEHHAFGFFDDBGHHDHDEHABBACBHCADFDDHBDHBDCDCBDAHFFHDDBFHAGCDBFFEECCECCGHAHCAHBEHDACDAHDFCDAHDBBFFBAFCFFCAHAAGAC,False +832,25.0,27.0,23.0,20.0,26.0,20.0,20.0,27.0,AADBAGBCFACEEGDFBFFBFHCGDBHEFHCFBFBEEBHCCHCHBEBGABDAHDFHDHHFEHGECGFCBHDFHABBDDBDFHDGCGCCGCDGCHBHEEDEHDHBDEEHEGHBBHFBHFBGCEGEDAEGAECCEAAEACBAHDEBAEBFGACGAFAHDABAHDGCDEAHEAFECFGAACBACHAGBFGE,False +833,25.0,13.0,14.0,24.0,17.0,12.0,19.0,18.0,AEBDEBFCFGAEEHEAHBAHDCFDHFBFAGFAGAEGCCDCAAGAHEHHGAHEACFDEGDCFBAGGABGADGCDGFEBFEAAAGAAECBGDFCDBEDHEBCDDHDDHDGHDHHGCHGEBGHCAHDEEDCDDBADAAGABHDDF,False +834,15.0,10.0,18.0,19.0,15.0,14.0,14.0,17.0,GFDGHHGDHFHCFDBEBGADGACECCHHCHFAHCEHCHHDEHAEBADDGDBGDEEDECDFCAFEEFEDDHDCGAHBAGBDEADGHEFDFABCEBFGBCABCFGCFACGDHDEHACACCAFGF,False +835,20.0,10.0,18.0,14.0,16.0,28.0,23.0,12.0,CBFFGFCHEDBFHGFEGFEGFEDCEDAEHAGGGGFGGCCCDGCFGCFHAFBAFBDFCFFHAAGCEGAEGHEGDFAFFCDFADECHEAHGFGEHGEBDDBABFABABECHCFGCDDFFGFAACAAEDHGGHECDBAFCAFAF,False +836,30.0,20.0,19.0,16.0,19.0,13.0,25.0,21.0,GEHGEGBFGFCGFAGHHGFGGFDHAAHECBAGGAGHCGBCABFHBECAAHAFCEBCEACEADDADCGHBDHGFEDBCAEGAHGHCGHCGEBBHGDHEDHDFBEBBFADEAHEACBAEGFDCAABAABAABGAEACHBHDGADHAEBACHDGDAGCEDCEFCBF,False +837,11.0,6.0,11.0,21.0,12.0,11.0,14.0,20.0,CCGFFHDFDCHECHGCEGCGGDDGABGAEHDEHGGHGHDDHDABDHBHFFGEFHDAEDFEDFGFAHHHCFHAEDGEHCHFDADDGDBADAHDAHDCDCCBEHBEAE,False +838,2.0,11.0,5.0,5.0,5.0,11.0,2.0,7.0,HHAFDBFCBFHBFCBHCFEBHEBCFBFEBEHBDDDEDCABBFFGFFGH,True +839,10.0,18.0,12.0,15.0,22.0,22.0,14.0,20.0,GHGGHDGHEHCFHBHHGHGFDFFBHGBDFBCFBFEBAHAACAEBAFCEFHEABGAHCBCCADAEHFDHFEFFEHFEHCECGHFEBFGCFDBBDBDDCEDEEDEEFBFFGDBBEBGEAEHFDCEGEEDHGDHBF,False +840,6.0,5.0,3.0,4.0,8.0,4.0,5.0,6.0,HFAHFAGABEEHFEBBEABCGBGAFGAECDEDHEHHEDGDC,False +841,22.0,25.0,12.0,20.0,30.0,18.0,24.0,19.0,CFDABGGBGGDGGBGDBGDFEHGEHAEDEEDEEAEGABBABHABFEGAAAAFAAGHFEEEAHFBBFBDHEHAGHADHFDHEDHEDCFAHFEHGEHEEHCBBDBBGBGEBCEBFEHDCFAGFECABGDHEFFEBEACCHEGEGCAFDACECDGDBHEFCGFGGBBBDBDDA,False +842,26.0,32.0,18.0,28.0,33.0,16.0,26.0,21.0,BDFEACGAHGEHBEFBDDCDDEBGFBAHCGBBGCEDEHBAFGGFBDFDABCCBFCBHEBEAFGAEGFEGEDGAABBHBDCAAEAEEBEBGDGGDGHDHHCACBEGGDHADHGEFEBDEBDHBDHBEHBHDDCDFCDCGAGGEGGEGFECAEABEAHDAHCFFCDHAAHAACAABFEEEBDEBDGBDBCEEHDBGEBEAHF,False +843,17.0,15.0,21.0,18.0,10.0,19.0,19.0,11.0,GCGCCGCDBAAFCFFCGCCFCBGCBHBGADGFEEEBEDCFDCFBEFAEGDDDDDAGACDEFDBFGCFGEFDDHCGGGGGAFACHACHACGADGHHCHBFAAFDFFDABBEBFHBHEBHCAHBADGABFDC,False +844,28.0,20.0,25.0,32.0,29.0,10.0,34.0,16.0,GCBGCEAHBHHGHCGADBHDGAFGCFEEFDEAABAAFACGACHAGEEEEEBDBDDGEAEBGCFGAFGCGACGAGFEDAGDAGDBGDFEBECDGBDHBDBBDAEHADAAHGDCGDEBAHBEDCGBEGHEDHCCEDDEDCEGCDHDACAABADGEEFCEFGGAHGCCGCBECECBDHDCADAGDGGDGGDECHEBD,False +845,9.0,18.0,18.0,15.0,16.0,16.0,18.0,30.0,FHHFCHBCEBFEBFBHCGHEGFEDEHABHBHCEHCGGEGGCGGDGHDFHBFHAGACEDBBBBBFHEDHAHHBHEGHEHFDHEBHDDHCDCDHCACADBHDAAEGHFCCECCFHHBHGDHCDHFDGFBGFGGECAFBFCEG,False +846,25.0,21.0,20.0,25.0,14.0,20.0,19.0,27.0,DHHAHHGHBEBFFBHACHBCHFEAFHAGEAGEDFFDHACGDCGEBDDBGEAFAAGAAHAAFCFDCAEFBEGHGDCFAEDABDABHGBHGFHFDGDDGDDHFBABCADDACHBCHCGECACDBCGBCFHEHCCBBHHHFHFBHECEDHDAHDFDDFBBFDBEGACGACGADG,False +847,19.0,22.0,26.0,32.0,24.0,20.0,17.0,30.0,FFFFFBEBBCDDHBEHDHHFHCDHCDBCDAFBHDGHDECDEDGEDCBFEFEHAHHAEDBDGHDCHECDEFHHADHCHBCHCDDCHBBHBEECCDFEDFDBGDBDFBEBAEFAHAGFECCACDHCEHCGGCGGCAGABCAGAGCDBADGEDFEGAEGAEHACHCBHABDBEDEDDHADGGFBFFHEFHCAH,False +848,9.0,6.0,11.0,10.0,14.0,15.0,7.0,8.0,EBECBHGDFECFDGFDHFDCEAAGDEFDEFDFFHCAHGBDDHDHFEGEGBAFCEFCAFCACCACBAFHFEHEEFEGAEBC,False +849,4.0,12.0,3.0,4.0,4.0,6.0,9.0,4.0,BADBFBBDBCDAGGEGGAHFBHFECBBGGCGGBBGBDFFHFEHAEB,True +850,11.0,16.0,15.0,13.0,9.0,18.0,8.0,14.0,AHEFHEDHAHCBEFAEABEBBDHGAGCECCECCEDGADFFBFFBFFACACDFCDECHHFDFFHFFGFBAHBCDBGDBGHHGHFBDBHDBCCFHDACABDGBCBF,False +851,14.0,6.0,9.0,8.0,8.0,11.0,8.0,4.0,CADAAFAFGGBDGBECHEGAEGCEGHEAFCGCCAFCAFDBEHBAAAFAFFECEDADGACFBDFHDFBD,False +852,13.0,17.0,14.0,11.0,14.0,23.0,28.0,19.0,AHFBHFEDBHCBHGDHDDBEFGAFBEDCEDCGGCAGCHGCHGCDCEEGFBBFHCGHAGDCFEGABFCBECBAFBAFHHGHEBCFAEGGEGAFBFGGGDGBDBFAEEBGAGHAFHCFHFFAGFHGFHFFHGGBGGHDGFE,False +853,17.0,14.0,15.0,18.0,12.0,25.0,14.0,18.0,FEEDCEDAEDABFABGHCGEGBAFBAFADFDDFBDFGDGEEAEHDGHCFHCHGBHFHFACAEBGHHGHAGAAFFDCCDHCGGCFDCFHCGECADCFDBFEBFBDGHDCHCHDAFFFHFBBEAFADFHBFHFAB,False +854,4.0,8.0,7.0,9.0,7.0,13.0,4.0,5.0,HAHBAEBCEFDHFGBFDDFDDFCGFBBCBFCFFCAFEDFBCGCDGEHEEDFDHFEBA,False +855,8.0,9.0,7.0,8.0,14.0,11.0,8.0,11.0,FCGGHEGHCAHEGDGCDHEBHEGEEFAEFCEAAFAHDEHFEHBGFBFFBFEAHEADCBBCBBCEGDDHFDFBHEAD,False +856,15.0,19.0,19.0,21.0,20.0,23.0,9.0,21.0,EHCABCEDCEDCHDBADEFFEAHGADFHBFEBFEHFEGCHGBBFBDFDCFHCFCGHCDHEHADFFEFHCGHCBABEEBEFBCDBCEHDACDBBDCBACBAEBDDCADFAEFEEHDGHDEEFBFFDHGHFGAFAHFCGFHBHDADAHC,False +857,8.0,14.0,12.0,26.0,12.0,12.0,24.0,18.0,DDGDGFHGDEEDEHGEDDCHGCAGDGBBHHAHDBHDBGACHCCHFCHGGHDGHDBFABCHGHGFDCEAGEADEGDADEGHBCFBGFGDCGBFDFFDCBDCGDGBEGBFGEHHEFHDFGDAEDBDDB,False +858,3.0,12.0,7.0,10.0,7.0,11.0,5.0,6.0,EHBFDFFCEGCEBFAFCCFECFHDGCEHAEFDBFDBAHBGHBGEBCDFDDFBDBDGBHBBD,False +859,15.0,8.0,5.0,5.0,11.0,6.0,8.0,9.0,AFHEGGEGBEDBACAADADGGHGFEGCEHCDAFECBBABHHEHAECFHBAHGABDEBAEFAEFAHAA,False +860,24.0,23.0,16.0,29.0,25.0,13.0,28.0,31.0,ABDBGHHDBEAACAHBDDDDHHGAHBDHDAHCGHCAEGFECFECGHAGBBDBDDBDGBDBAEBACDAHDBGDBCEBGEDDEBDBBABGGGGGEHAEGGGDFHDAHAHFAFDCHDCHEFBEAGECHFCHGGEGGAGFDHADEGHAFHBGHEFBCAGCAEBHEDHEDEEDFEGFHCEHDHHFCHEAGECHA,False +861,19.0,16.0,16.0,18.0,22.0,19.0,15.0,18.0,HBDHADGAFFFCFDCFDHFAEEDEEABBABHHEAEDAHDEHCGFEECHECEFGHFDHFEEGCBDFDGHDGHDCBDCAECAHBACGEFBFFAFBAFBEDHDAHBBDGEGCEGBGDFGAFGAHCHGFECAEGABAHBACBECECD,False +862,23.0,28.0,34.0,23.0,21.0,19.0,19.0,23.0,AADEFDECBCFBFEGCHHCBCAHCAEDAEDFGBAHBGBBGEDGEFBAFBABEABFAHFAHADGBHAAHAAHCFCAECBEHBACDDCDCHDHHDAHDAHCFBCDHCBBGDEDEHFBCCCCCDGEDEEBCBHCDEBEHBCGCDECGCCGBCGBCFAGGACBHBFCAGCFBDHBFHFECFGHEGCEFDDFGDG,False +863,11.0,5.0,11.0,10.0,13.0,17.0,9.0,9.0,HGFAGHEGFFAEFGCHCCHCFACEAFEAFBFFBEEDDDGGDFEBHDFEDFEFCEHCDAAFBAFHCFECHEDDABDAGCCGAHGEF,False +864,8.0,4.0,8.0,5.0,6.0,11.0,2.0,13.0,CGDDADAFHFEHACHFFHAFHAGABEFBHHCHFCFBEHCEHDEFDCFEFHCAHCAHB,True +865,6.0,7.0,13.0,8.0,5.0,5.0,10.0,8.0,EBBEADDABHGBFBHDAHDFCCCCCGDCGACEFCEGCGGCDHHBGHCGCGBFDDFEAHCAHG,False +866,13.0,18.0,13.0,24.0,13.0,21.0,16.0,22.0,CECHEHGAHDBHAACGDDGDDGBGFBACBAFGCFGEBHHBHBBFBBFGDFEBHDBAEEAGEHFEDGEDFFHFADDADFHCHEADCFDBEDCDDFFBFFHFGEFGHCDFBHADHFDHFHCGCAGDACEBDHBDGDHGCHBH,False +867,3.0,4.0,1.0,1.0,0.0,0.0,2.0,1.0,BGHBGBAABACD,True +868,12.0,15.0,8.0,11.0,24.0,11.0,16.0,16.0,GBGAFGAHEABDAHEEHEGHFBEGHCHHCBDFECAADDGHFHFGEAGEBCDGEDBEFEEFGDGGAHGDHEEHBEHGEAGECGEAHECHBBEFBHBBDBBDCBFEFEEFECAAD,False +869,14.0,6.0,19.0,11.0,20.0,15.0,11.0,18.0,AFHAEHAEHGFHACHADFFGGFEGFEGDEDBAFBDECHHGHCCDBCFECHCHFBEDEECHACDGFDCHCEHFHCFACEACEACBCGBGEADECEEGFEHFACEDHEDHAGHFCA,False +870,7.0,10.0,10.0,16.0,6.0,4.0,11.0,16.0,HCBDCBHCBACDCCDHFHAGHCCDECGEDGDAFHGHGBDDFADHGDHBDHBGHFHEAABGBDHEDHEHHEGDDGADGCBB,False +871,6.0,1.0,1.0,3.0,2.0,4.0,9.0,6.0,AHCGEDGAHEAHAFGAGGBHGAHGFGDFGFHD,True +872,3.0,5.0,3.0,3.0,6.0,1.0,1.0,2.0,BBBDCBEGHEFHDBADAECAECEE,True +873,2.0,1.0,1.0,2.0,5.0,1.0,2.0,3.0,HEGAEHAEBCFDEHDEG,True +874,7.0,21.0,14.0,14.0,9.0,12.0,13.0,10.0,FDBFBBDBADBHBAGDHHCGEFDEBGEGGFGBCGEADAGGADHBDFCDECGBCEDFHFGHFEAFGHEDCEDCBFCBCCBHBBHBBDCBFGBCBHDBCAFC,False +875,6.0,6.0,10.0,12.0,5.0,8.0,13.0,6.0,GCGGCGGHBFDDADDBDFBDGCFGAEGAFBBCBHHFDHADHAGCDGEDEFGGCECCHDCEACGDFF,False +876,19.0,14.0,14.0,17.0,5.0,8.0,26.0,9.0,ADBACAGCHGCFGHDADABGEDABDABAFGCFDCADGGGGGGGGGBGGBACCHHAAGAADAGDAGDCGDBFFBCFBEBCEBGBBHEGDDCCCBHHAFGDGADGDDAFCGHHE,True +877,11.0,23.0,26.0,15.0,25.0,13.0,27.0,20.0,DHHEHGFGGCEHCGDGEDHCDHBFEDFEAFHBDGFCBHCEECEECBHCACGACACHGBHGBGGECGBDHCFEEEHCGHCGHCEBEFBGABCDDEGGEGGEGFEDBEBBGBCGBHABGEDCABCFECAHHBBCBDCAGBDGBAGCAHFHEBCEGCDFFDEF,False +878,10.0,21.0,12.0,20.0,16.0,27.0,18.0,16.0,EGCEHFAFAEBBGACGEEDEBDEFDBBDCBDEDFFAFGHBDFBHBGHBEBEGDDGDGBHGBHBFFGDFCFGCFAEGHEDEEDEAFFFFFFCHGGDGAFGAFHDBHEBCAGHBFDFFBHFCHFCHCCDCFDHBDGBDBHFA,False +879,13.0,7.0,15.0,3.0,11.0,11.0,9.0,9.0,CHBCFBFGEFEHCCAFAAFCEECBBHEEGEFBEABAADGAGGFGFCGACEHCHCFECADCACCACFAHFHDGHGAHEB,False +880,18.0,17.0,11.0,7.0,12.0,11.0,12.0,19.0,GACGHHGCCDAEAEBAFGHFGHEHABHBDHGCHGCHBABEEBECDDBABBHFHGCBGCBFAAGDAGHHHCAFCABAABAABHAFDAFBGDCHFEBEEHEFHEFBFHE,False +881,15.0,14.0,12.0,18.0,16.0,16.0,10.0,24.0,EFDEFDHBEHAEFFBHEBGEFABHGEHDFHAFEBCDGDAFDAHAACDACDGCEHDBBBBHDHEAEFAHGDFDABHABHAEHFEHFHHFHBFHAFHAEDCGBGGDDHDEHCBCCHCEFDGGHCDCC,False +882,1.0,3.0,4.0,5.0,7.0,5.0,2.0,5.0,HDHBCGDFACFECFEFBDFDGHEEHEBHEDCE,True +883,10.0,19.0,13.0,15.0,16.0,14.0,11.0,10.0,FDEBDAHCBEFHFHGGHGEBGCHCEECDACEFBAFHCBCEBAGBFGCEGBEHDDHBDHCDAFDEBDFBDEADBADBAECAGDABCGDCFBGFBDFBEFBFGBEHEECF,False +884,4.0,20.0,14.0,12.0,17.0,18.0,12.0,16.0,DHCFHCBHGFHFEDFEDBCDBFHHGCDFADCGHFBDCBDHAGEFBEHBEDCEGCABFHBHCCCCBHCGGFGFFBFBBEGFEBBBCGEGHHHFDAFDEFBEFHEGDEBEEBEEB,False +885,4.0,5.0,7.0,5.0,3.0,5.0,11.0,4.0,GBBEAFCABHGBGEFGDDCBDCFGCAGCDGCGHEGHFCHFGAGD,False +886,4.0,2.0,5.0,6.0,4.0,7.0,8.0,6.0,DEGFEGHBGCGHBGHDFAFFAFDADGCHECDECFFCHADHGG,False +887,7.0,10.0,2.0,12.0,7.0,8.0,10.0,7.0,HDGHAEDCDDBGDBAEBGCBDAEGFGFBGFBDDBFHBEHADFGDFHHFHEDGADGAFEAGEBB,False +888,22.0,21.0,26.0,15.0,24.0,25.0,19.0,23.0,HFHEFEAADAGDBCEBGEBEFHEGHAGEDGADFEBFCBFBBFCEHADFEHGHHFDFCHFCHDBGDHAAHFCFAEBAEGCEGCFFAHHGHHFHHCHCBABGDHHDFABGCFACFECDEAGEAGFBCFGCEGCBBBEBAGHGGCBAFACFDCDDCFCAHCACCBEEBEEBEADCCEF,False +889,14.0,18.0,14.0,7.0,16.0,10.0,10.0,16.0,FHAHHEDDECCCHBCBBFBFCBACDAGHAGHBFHBCHBEGEEGBBGBBGEAEAHHBEFFEAFEDHECEEGABGBDGCABEABAFCHCAACGBHHAHCDHFECFED,False +890,18.0,20.0,25.0,21.0,23.0,27.0,22.0,23.0,ECFEGEBFABFABCDBFHBHABHBDHGFGBFGECGCFHADHDEACCBHFEGFACHECHFBACCCBEBBDFDAEAABDAECCCFCFFCFFCEGCHBEGDEDFBDEGHFCHFCFDCFEGGEGDDGHDHHCGHFDFBDHGHHAAHAEHFGAFGAEADEFCEFBEGBGGHDAEDCEHCDGBDG,False +891,21.0,17.0,16.0,20.0,21.0,17.0,22.0,30.0,GEDGFABBHBBHFAGAEEAEAAECAEHHHBDDCABHGGHGCBAAFABFBFCGEBFEGEHHEHHDDHFGEEHDGHCAHFADBADCCGACHDGHAGHAFHAFBECBEDHGCHGAHGBDCEDCDBFDEGHGADGDHGFHCDGDFHBHHBHAECFECFEGFHFEDCED,False +892,2.0,4.0,1.0,8.0,1.0,2.0,5.0,5.0,HHHHBDABDGBDFFDCAHGGGBDGDDED,True +893,15.0,5.0,9.0,8.0,9.0,2.0,15.0,5.0,GGEGEEDAFGECACCAGFGEEDECDBAEGADGABAACCACCAHGAHADHGDGGHGBACBHBDEGAAGD,True +894,15.0,20.0,23.0,20.0,17.0,18.0,26.0,16.0,FGDFCFCCGBFEBEEDACGECGHCFFEDBBCHBFHBDAFHBGCFCCFAGHDGDGGBFEEGCEGAFGAEAFEDFEDBBDHBHGGGGCFDCEHBEHGCAAAAAGHCHHCHBGDDCDBGBBCABCABADBADBFDGGCCEDEEDGCGGDDGHCFHEFH,False +895,17.0,14.0,14.0,9.0,18.0,14.0,9.0,18.0,BGCDCCFADADBGDGCAEEAGEBEFBHHAEFFEHFEBEBCGCEBCEDAGGAHEABEABDAFDHBHHAAHBAHAHBAHCEHCAHFHBEHFCFFCEFCEHCHHCAEDFEDBGFGF,False +896,10.0,10.0,7.0,13.0,14.0,14.0,10.0,8.0,HCBCDHHGEAFHFCDGHEBDEAFBCFEDFADEADEADABBHCAEDGDDGFDAFHHFDGFGGFABFBCDBCEAGBBGEFGEFEEFEE,False +897,1.0,6.0,2.0,6.0,4.0,12.0,5.0,5.0,FBDGCGGDFEBFEFFEGFBGFHFFDFHBAHFEDFCHBBHDD,True +898,8.0,2.0,6.0,2.0,1.0,5.0,2.0,3.0,CFFCHDCFEHHAADAACCABAACGAFGBF,True +899,13.0,11.0,11.0,13.0,12.0,11.0,12.0,9.0,FCCGCABEBEEFCBGCDGCAECEEHAEGDCFFHDBCABDABEAFCBHABHADHGDFGDFBDFEDGHBGDGDAGAFECHEGDEGHFAHDABAF,False +900,11.0,8.0,16.0,15.0,15.0,12.0,12.0,10.0,HFDECDECFHCHGDEDEEBGHDAHDABCCDDFGDCGBCACCDGGFCGFEHEAGEAGEAFCCHCCAFEAFADEADHGDBFBBFBBFGCEAHFCDEEDHEG,False +901,6.0,5.0,13.0,12.0,14.0,4.0,0.0,2.0,DEEDEFCACAAEHEECDECAHCBDDECCBCFFDBFBCDECEECEDCADEDDEDACB,True +902,5.0,2.0,3.0,0.0,2.0,4.0,3.0,0.0,CFECFBAGAACAAGFFGBE,True +903,1.0,3.0,5.0,2.0,2.0,3.0,3.0,5.0,HEAGEFBCDBCBCFHCFHCDHGHG,False +904,8.0,10.0,8.0,10.0,10.0,10.0,8.0,8.0,HAEHAEDAEDGHFGFFAFFBFFGDABDECDEGGEGHBHBBCCFEDGECBCCBACHDCAFBDDEEDAHGBHBF,False +905,19.0,35.0,22.0,16.0,17.0,18.0,22.0,17.0,BEDEDGGBEBBDBGHBCBBCBHCAEAHBAGBCBHDBHDCHGCBGDAGDCCAGDGCDFCBFCBDBBDHAAEAGEGGEGBAFBHFGFGBFHEACECCGHCFFEFBCFBAFAABBBBBHDBEFBHFAGBEFCDGCFCDEEHBBFBDCGDEGFHGACAACAHHFGHEABE,False +906,6.0,6.0,11.0,1.0,5.0,2.0,8.0,3.0,GGECBACGCCGHCBFEGGAACAACDACBBCHCEFCEHBEGBG,True +907,10.0,11.0,15.0,22.0,12.0,15.0,10.0,11.0,CBDCFAHHHHCHDBDDBEDHCAECDFFDACDGBDABCFBCFBGDCFFCFEEHGGHGADGDFAFACGDCADFBCFGDFEDFDDADGAHEBHFCHDCDEEBEEDEGBE,False +908,4.0,0.0,2.0,5.0,3.0,0.0,2.0,3.0,GHACDADAEDAEDEGDHHC,True +909,1.0,4.0,0.0,5.0,2.0,3.0,1.0,1.0,FDHBDABFEBDDBDEGF,True +910,9.0,19.0,26.0,20.0,13.0,12.0,16.0,22.0,BHDCHGCHBCHDCBGCAEDFEBFBHDBHDGHEGECGCFDCHHGHHBHGFGCCBCCDCHAADFFDFFHEDCFBCEHCEHCDDFAGECGDBDBGFGEECBHCBACBACHCDEFDAHBCHCEGBGGCDDHDEHBAGBADB,False +911,5.0,1.0,2.0,3.0,2.0,3.0,0.0,2.0,HAHAADAFBAFEFCEDCD,True +912,26.0,20.0,25.0,15.0,11.0,21.0,19.0,28.0,BGFDDHABFAGCACFBCDBGDCCAAAHAAHFCHCEGGFFHHFBCABCGGGGBHEAHCAHBAHAHHACHFDHDAHABHCBFEBFADFGDCGFFHCGBCFBDFEDCHBBHBCGECGEHGFHAEHACHADAABHFDECEGBAGDHFDHCCFGAEGAECABFFBHCCHD,False +913,7.0,7.0,5.0,3.0,0.0,6.0,1.0,6.0,CDFCAFHACADCBBHBFHBFHFDGCABBABFHHAA,True +914,20.0,24.0,25.0,24.0,19.0,23.0,23.0,19.0,BDHFDGCHCAHFAHFGGCHBCHDFEDAEHCBFEBCGHCGFEACCAHDFGDFDBFBEFBEBGDBGDBCDECBFHEEEBCGBDDFDECHEHBFCAFADGADAHFCFFGFAGFEGEHGADDHDCHDBDDGEDBHABGGBEGBAHBHBDCFDCACCGEAACCACGAEGBEFBAFCCFGBAG,False +915,6.0,10.0,1.0,9.0,16.0,12.0,5.0,11.0,BFGFHGADDEEEEBEEHEHHEHFEBEGHFDHFBHFBDFDFFEBGDHCEBEEBEAGDADHAFAAFHBBEDF,True +916,19.0,25.0,17.0,15.0,26.0,25.0,27.0,16.0,EBBHBCGEEAEBCECGECHHCGDCECGECDBCDBAGCHGBFDBDBCEBFAAGAAHBGDFGAEGAEHEEHECGFFAFBEEAEEABEHBGHBFHDGCCFEFFCFFGFDHBAHAGFDGFDGHGGEDGEBGHGFFECBAFBHGEFBFGDFHDAADGGBAGBFCBFDEFAFBABE,False +917,1.0,1.0,0.0,2.0,5.0,1.0,1.0,0.0,DABDEEEEGFE,True +918,3.0,4.0,4.0,5.0,6.0,2.0,1.0,2.0,FCHDCBDCDEADEBDEBFBGACAEHEE,True +919,29.0,30.0,27.0,23.0,18.0,16.0,15.0,25.0,CECCDDBFGBEHCFACFCCAAAAABGDBDCBDABFBCEACABCGBHGDCGFBGHCDHCEHCBAFBFGHFHHDHFEHFEHCDBDDACBACGACGACFEDEBDHBDHAAEEGFBHHBHDAHBGBCGDAAHAFEBCCBDBEEAHEHFGHAHAABBABDHBDADDAECGBCEDCDCGEHAEHABBFF,False +920,6.0,8.0,6.0,2.0,10.0,1.0,2.0,2.0,ABABBFGBDGEECCEACECHEHBEABDBEEEACEACB,True +921,9.0,6.0,2.0,9.0,10.0,5.0,13.0,15.0,EBEDHGAHGFHGFBDEDDGCDGDHFAEABEGEGAHGAFEAGHAHHEHDEHDABDBGEGGBGHHACHFHH,True +922,0.0,4.0,4.0,4.0,5.0,3.0,8.0,5.0,BFCBHEBHDBCDFGGEGFEGEHGHCDHGDGGEC,False +923,9.0,18.0,18.0,28.0,20.0,33.0,20.0,19.0,FCFHEFDEBCBBCFACFDCDCAFCAHBDHBFGFHAFEAFEHGCHGDHCDHCFCGDCHBEGFFGDFGBHGDFGDFGFAHDBGGHHABEDFFDFFDFFEBFHDCEDFEFHEHHDGACFFGHBBHBADDDDCDEGDGGCEFCDBEBGEDEEBCEFGFFBEDGEDBFDE,False +924,2.0,5.0,0.0,7.0,6.0,1.0,0.0,3.0,EEDEEHEBAEBDDDADBHDFHBBD,True +925,12.0,20.0,17.0,18.0,18.0,15.0,13.0,21.0,GHHFHBACCFFHHFHHABHGDHFDEBABDDBCAEHABDEDCGDGDDGCDFFDHEBAEBAEBDCBGCEGBEHBFCEFDBGBFGBHBHHFFEEGECGECGECBHGBHDCHDAFDCFDEAHAHEAHACCEEFBBDCC,False +926,4.0,3.0,0.0,1.0,0.0,3.0,0.0,2.0,FHBFBBAAHAFDA,True +927,18.0,22.0,21.0,28.0,13.0,24.0,11.0,19.0,CBHHDCBAGFEDFBGBCGDCEFHFGHFGBFDDDDCDDCFHGFBDEBAFBEDACDAFEGFEDFCHEDADFBEFBABDGCCACBACHDCFDFAACCACBHFBHFBHADDADHACBBCDHCFFBFAEAACDBCHHFHGFHGHBGHBDEDDEDFEAHDBE,False +928,1.0,4.0,0.0,2.0,0.0,5.0,1.0,1.0,HBBFFDFFGFBADB,True +929,3.0,12.0,7.0,6.0,3.0,6.0,4.0,12.0,DHGHFACCACBAFHGDEGDCCBBFEBDEBHHCHHBHBBHBFHFCBFHGDBBDH,True +930,4.0,2.0,2.0,0.0,0.0,4.0,2.0,2.0,HCAACAFFGBFGBHAF,True +931,5.0,1.0,3.0,1.0,0.0,1.0,1.0,3.0,FGAADCACHACHAHB,True +932,6.0,4.0,3.0,4.0,3.0,1.0,3.0,2.0,DGCABBECFGCBGAADHAEHAEDABD,False +933,9.0,5.0,1.0,9.0,8.0,8.0,7.0,8.0,EFBCBAHBDFADADEAFFGGDEHDEHDHAAEABBFEDHEDHGFHGFEGFGGADHA,False +934,4.0,7.0,1.0,3.0,1.0,1.0,4.0,5.0,AEBGGBGBHABDFGDBADBHHCHHBA,True +935,14.0,14.0,13.0,12.0,23.0,12.0,15.0,6.0,EDAGFAGECGAGGACEACGGEHGEHCEBCFBEGECGEDEECFCBFBAFADBBDFBGCEEBEEDCDDFHFHEFDBCEGABGAFDAFDABDAEEEHBEDBEFCEAAGBGHC,False +936,16.0,21.0,7.0,13.0,13.0,15.0,22.0,19.0,GFBGHEGBBAABABEAHHADCEHFAHFACEGBHHBEFGAGEAHADDGDFGDFDAGHCGFFGBFAFEGFHGAHADGBDHCDHEHEGDEGDCGBHGBCGBFEAHCGHEBDBBEBBFBHFBHFBDAGGB,False +937,24.0,12.0,20.0,15.0,16.0,11.0,15.0,24.0,HAECEECEEBBAGGADHAHCGHDDAGBFGAHEHCAABGAHGAFGADHEDGFDHADBBCABGABDDCCDBHBEEBEEHAHHAGHAHHDHCFCAHAACCDCGHCHFCHFCHFADGAHFAFFCCFEDEEBGECCACEHDG,False +938,3.0,5.0,0.0,6.0,7.0,6.0,5.0,5.0,DGBFHAFEFDHBDHBDGGGEEHBEHBFDEGAEFAEFD,False +939,22.0,26.0,26.0,14.0,18.0,22.0,25.0,26.0,ACFACFGFBAFBGBHHBDHBGGEAHFAHFAFEHGECCECCFAEGABGABEAHGBEGFHCHBBDBCHFDEFHEABEFCEBHEBHDBADACDEFBCHDGBBCCBCHBEHFCGFCGCEGCHHCHGAFCADDBHDGFFHBAGCACABCGDGGBFHDCBFGBFEEFHEHAGHGGHCCDAGDAGA,False +940,8.0,10.0,2.0,5.0,4.0,6.0,1.0,9.0,BGDEHABAADAFBAFHHFHHFHBAHDCEABDBBHEDHEBBFBAFC,True +941,29.0,18.0,34.0,25.0,27.0,21.0,24.0,19.0,DEDAEGFBGFBGCBFCHECFEFAGBABDCBEHHEHGADEHDFHFFCEAAEAFEAFCGGDGFEHEECGCCDCCECCDHFAHCACDGDBGFBCFADEABHABDABDHBGHGDADDADFCDAGFAGBBBECFCCECCEDGGDCDEGGAHHFEEAEACBDCDHCHEEAEACFAGDHFEGCAGHABDACHCCBCFGCAGEAC,False +942,22.0,23.0,26.0,28.0,25.0,25.0,28.0,22.0,HHDBFEGFEGCHBDEBHGCHGBDFHDBHFBHBGHCCECADHADGAGGCGCFDCFAFGDFAHGEDEEAEFDBCHBDHGHECFAFFAEFBGFHAFBGFAHFCCGHDBABEGBDBHFACAADAGDGECGEGGHCGFCFFEDFCCACEDDHDDEADECDGBBGBCHAEHEEFCBCCACGFBDFCDEADBGBEGBEGDEADEAD,False +943,10.0,5.0,3.0,10.0,7.0,4.0,2.0,3.0,DEBBHAGEABHDCADAADEEBCEFEDFADAADAGDABDCHDFFE,True +944,12.0,16.0,22.0,10.0,9.0,17.0,15.0,10.0,CBFHFFBDFBAGECGCCHCAHCFECDDFFDECBBCBBCBFCAFCFFEFABFGBEAHAGBGGCCGBADCADHDGBFGCEGCEGCGHFGCFEFBDHADACGABBHHDAHCGCE,False +945,14.0,9.0,10.0,9.0,9.0,9.0,8.0,11.0,GBHGAHFAHFBGGDDGCHFAAFACDEFDACDHCEEAHEAFCBHCBGFBAEBAEBAFCAHDAEGCHDEBAEFGDDCHBCH,False +946,25.0,17.0,25.0,19.0,25.0,14.0,14.0,31.0,ECDHCBBCFADECDCDBGDBECEEGEEGFAGHACFDHBEEBAFCCBAHBAGBEGBGFHHDHHAHHAHCFHFHAFHEFBGBAHBEDCEDCEHHAHEABAGGAEGACAFCADEEECDACHADECFCDDEHAEFAEFBBADEHHHHCDHCDHCEHGFHGHHBCCAADHAGCCD,False +947,9.0,11.0,9.0,14.0,8.0,14.0,11.0,13.0,AFGAFHBFDGCGGDFFBBDCBDHFDHCECGHDFHDCHGGHAEHCEAAEFDEFAAFBBDBFDBFDBHDBECBFCEGGHGAEDHGHHACDF,False +948,13.0,8.0,5.0,13.0,9.0,10.0,22.0,12.0,AGDCGDCEDGFHFEAAEAAHADGGGBGHFGHDGHDHCBHFGEGGHAEBEDFADEGGEGGAGFHCDABDHBGGAGGDDBDFBCFEFAHFABGH,False +949,21.0,23.0,21.0,26.0,19.0,22.0,10.0,18.0,AAAEAHBDFFHFCGEGBDFDFADHEDBEABCAGDDBHEHFBHFBHBAEGABDDFDFECEECBCABADBEDFEBECCHBBABBEBBHBEDDHGHCGHCGDEGDGDDEDDHDCHDFDBFHHHCFACEAFAACHACFECFDCFCFFAAFDABCCBCDFCAFGE,False +950,20.0,25.0,18.0,22.0,18.0,18.0,14.0,12.0,GEDGBHAHGAHGCCDAADBDEADBDDBFFHFBHFBACBFCAFADDCHCGEFBEABFFGGDBGBBEFCEFBDHBDHDEEFEADEDDFDDFDCBDHEDEEBEBAECCEBGBHCBHCEGFBBCBACAGCAEFGCFGCFBAAAAGCBHAAD,False 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+970,16.0,13.0,19.0,11.0,15.0,16.0,18.0,14.0,FGHFHAFEAGGHFBHEBABAFBGFDFHEEGEDAEBBEBDECAFAACCBCDACFHCAHCFHGHHGCBCFGHGHHADGDDCDBCECDBGDGEDGEFCCGHAGECGECGAGAAEAFFCFFCEBCB,False +971,4.0,3.0,0.0,5.0,2.0,3.0,5.0,1.0,DAGAHGDGBDEFAEFABFGDGBD,True +972,7.0,2.0,1.0,3.0,2.0,2.0,4.0,4.0,HCFDAHGAHABGADEHDEABGAFGA,True +973,2.0,6.0,7.0,4.0,4.0,5.0,7.0,4.0,FBGDEGHCGHAGBDGCEGCGCCFDCAHFBCFBHEBDFBE,False +974,17.0,19.0,14.0,32.0,17.0,26.0,26.0,16.0,EBDHBAEGEFDDBGDAGDHGFFBFDGGDAGAAEFAEFCEHCBCCAGCBDFBDFADHGDHEDAEBHFDHBDHBDGBGEBDCCDGCDFCEFBEGEFHAGHAGFAGFAHDDDDGDFGAEDEBDCHGGEEGDBCCHDGAFGHBGABDFFFCBFAEDDHCFFFFDFDHGGBF,False +975,8.0,18.0,16.0,11.0,10.0,10.0,17.0,15.0,EBFCBFCBCBBGFAFFCHFHHBDHBDBCEGDHGBGEBGDBDDHCDEBACCGHDGEFGAGCCGCCGAEHDCHECHGCDFFGGBGGBAHBFHADGAEHBBAEHCEHB,False +976,27.0,32.0,25.0,20.0,17.0,19.0,24.0,36.0,HCFABFDBGEFGFDCBDCAEBHEDADCADCGBCDACDBBHBBDAHAHHFFGEFHHBBHEFAEDHEHHBHHDAHCACCDDDAHCEECBBHBHHBGDBGBBGHCAHCFHFHGCHGAEGFFBBHCBHAAABACEGCGGCGACFACGHBDCBHCGGEHEBGAFFAEHHDFHDFEGFABDABGBBECBEBGAAFAACGHGHHGDH,False +977,21.0,23.0,33.0,29.0,26.0,21.0,26.0,19.0,BFCBCBEGFEGDEGFEBDACFGCDGADCDDCBBCGCDDCGCCGDDGBFBEEBAABAACFCCFHDDHDEBDEFCEBBGBEEDAEAHFCHFHHEBEEFFEFHEADEGEGGCGGADDFBCADDDCCGCCGCDGEDFADGDFGFFBCAAHAHEFHECAGFGDCEDCADBAHHHHEHHEFHBCCCCBBAABCAHHDGBEGCGG,False +978,7.0,8.0,10.0,5.0,10.0,5.0,5.0,1.0,DECDEBFCGFADFEBAECABABEGGECDFCGBEGCEHCBDCBCABCAEAFE,True +979,1.0,2.0,1.0,6.0,0.0,1.0,0.0,1.0,DCADFBDHDDBD,True +980,24.0,21.0,18.0,12.0,17.0,7.0,12.0,18.0,BBAHBHDDHBHFAHACBEBBCBAEEACHAHHEGBBGBCDCCAECAHCAGGAFFACFAHHEEAEHFGCACEACHFCHDDEDDEDDCBCCHEBHBAHEABBGBBADBGBBEAAGAADHEGEGGEGAFDACC,False +981,22.0,33.0,18.0,23.0,27.0,28.0,28.0,13.0,EAEDGBCFBAFBGFDAFAAGHAEBFHFFHFFGACDBDFCDFGDBEBBDHCFBEEGGDAGECGEFABFGBEDAEAHEGDDBEGCDABHBBGBDFBDHBGBBEBBHABAABDCEFGAFGAFBFCEFBGGHAGAFEDGEDCHFHBFGDHCFHCAGFDGCGECFECBECBECECABCAEFBEFEEGDBGDEGDBGD,False +982,22.0,20.0,15.0,16.0,27.0,17.0,27.0,21.0,GDFGHEGBEHCEBCHBEHBAHGCGGEGBBFDEADFFHADHEBHGDACDACDEBEEGEHBEGBEGHEBFAAFGFFGDFGDFABGHFHCEECHDGBDCBFFBGCBDDHDCGBCFAFHGGHEGACHECAEAAHCABAACAHEEDEADEFEGBGGEGAAGEBGFAHHAE,False +983,6.0,5.0,6.0,11.0,8.0,8.0,5.0,7.0,HBFHDFCEABBADECDEGDFCDFHBFEDECCFGHFAHGHHADEADFCDGDDGEBAE,False +984,9.0,13.0,13.0,13.0,32.0,25.0,15.0,18.0,EEAEEGEABEGHGFDADEEFAHHCBFGDCBBCHBCFDCFDCFDEFDEFCHFEFECFEHFHGFHGFHEBBCGECBDHHEEDEFCEGAADEFEHGEDFEHFEDFEGBHHFHGEEGEGAACFABFGFDGBEECEEFHBFHB,False +985,14.0,10.0,10.0,7.0,7.0,11.0,13.0,6.0,FAFAHGABAACAAGAFCDDCGCEFDBGBGACHECAECAEBAHDDFDBFDBFGBAGCHBEHBAGBECFFCEFGGGGGFH,False 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+991,18.0,26.0,30.0,28.0,39.0,25.0,17.0,17.0,ACBACBFFBACEFCFACFBDEBDEHCFHCDHEDAFCAFEAGEDGEGBEDEDGEFADCEDGECCCDFEDGEBEHBCFBCBDCBEFHDFAEECEFCEFBBFEBDEADEGEEAEEHEDFADGDHGBBACBGHFGHABBACCDCCECGECDHHHAEBBHBHGBCFFAEDDGFDEBHEBFEHCCFDGEDCDCHEBDEGDEGFFCA,False +992,19.0,14.0,13.0,21.0,20.0,19.0,18.0,15.0,GGFGDFGACGCFHCEHFECCAGBDFBDGADCDEBHFBHDAHEHCBHBEDBEDFADBHDFDEBDEGAAHAAEFAEFGEFGDFGEHAEDCDDHGDHDFADFEEAEBADBCHCHGCAGEGGFDEFEFGAAACACFHBGBBEF,False +993,25.0,22.0,19.0,27.0,20.0,17.0,20.0,31.0,GHDGEDGEGAEGFEHDBHDEFDEACEAGEHFDFFDFFHGEADEBHGHDDBDGBAEFCHCBHGBADBDFCHCABGDCDDHEDHDCBBAHACHGHHEAHBAHBCHAHBGHEDDEAHEDCGCCDAHAFHFBBABBHBFHBAGBCGBFFHFEGEEACCAGCABFAGGADHCDHCDHAHADDACEF,False +994,11.0,8.0,14.0,13.0,20.0,15.0,19.0,10.0,DHBGHCGCCAFEBGCDAEGAEGADDAGEEBEGBEGDFGHECFACFHEEBEECCEBDAGFBFEGHEGDABCEEGEAGDDHCAHCGHFGDDEFHEFHFFCFGCFGFAGFDCD,False +995,4.0,5.0,0.0,4.0,3.0,4.0,11.0,4.0,HGFEAHEADDGFGGFHGFBGBGGBGBBHAGGDDAE,True 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Generator with [Hidden] Markov Chain +# N-Back Sequence Generators -**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/src/main/scala/org/xcit/nback/markov/models/State.scala b/src/main/scala/org/xcit/nback/markov/models/State.scala deleted file mode 100644 index fbbd844..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/State.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * A Single state with a label in Markov chain - * @param label A simple string label, representing the state and node - */ -class State(val label: String) { - - /** - * Keep track of transitions from this state to other states. - */ - val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() -} diff --git a/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/src/main/scala/org/xcit/nback/markov/models/Transition.scala deleted file mode 100644 index bc20a9e..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/Transition.scala +++ /dev/null @@ -1,8 +0,0 @@ -package org.xcit.nback.markov.models - -/** - * A Single transition in Markov chain graph. It is stored in "from" node. - * @param to the ending node of the edge - * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). - */ -case class Transition(to: State, probability: Double = 0.0) diff --git a/src/test/scala/ThreeBackBenchmark.scala b/src/test/scala/ThreeBackBenchmark.scala deleted file mode 100644 index 0c7dad9..0000000 --- a/src/test/scala/ThreeBackBenchmark.scala +++ /dev/null @@ -1,7 +0,0 @@ - -/** - * TODO Benchmark 3-back simple sequence generator - */ -class ThreeBackBenchmark { - -} diff --git a/tests/benchmark_diagrams.py b/tests/benchmark_diagrams.py new file mode 100644 index 0000000..8fa448e --- /dev/null +++ b/tests/benchmark_diagrams.py @@ -0,0 +1,159 @@ +import pandas as pd +import numpy as np +from matplotlib import pyplot as plt + +import benchmarks.common as common + + +def tlratio(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2,ignore_index=True) + stats = [] + for trials in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == trials) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == trials) + targets2 = data[alg2].targets if alg2.shape[0] > 0 else np.nan + targets4 = data[alg4].targets if alg4.shape[0] > 0 else np.nan + lures2 = data[alg2].lures if alg2.shape[0] > 0 else np.nan + lures4 = data[alg4].lures if alg4.shape[0] > 0 else np.nan + stats.append([trials, (targets2/lures2).mean(), (targets4/lures4).mean()]) + stats = pd.DataFrame(stats, columns=['trials', 'tl2', 'tl4']) #.dropna(subset=['skewness']) + + plt.style.use('ggplot') + + plt.ylim(bottom=0, top=30) + plt.scatter(stats.trials, stats.tl2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl2[idx], 1)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.tl4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl4[idx], 2)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('T:L Ratio') + plt.ylabel('T:L Ratio') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_tlratio.png', bbox_inches='tight') + plt.show() + + +def time_per_trial(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for t in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == t) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == t) + time2 = data[alg2].time.mean() * 1000 if alg2.shape[0] > 0 else np.nan + time4 = data[alg4].time.mean() * 1000 if alg4.shape[0] > 0 else np.nan + stats.append([t, time2, time4]) + stats = pd.DataFrame(stats, columns=['trials', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.trials, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time2[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time4[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2v4_time_trials.png', bbox_inches='tight') + plt.show() + +def time_profiles(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 8): + alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + time2 = data[alg2].time.mean() * 1000 + time4 = data[alg4].time.mean() * 1000 + stats.append([ni, time2, time4]) + stats = pd.DataFrame(stats, columns=['n', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.n, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.time2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + plt.scatter(stats.n, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.time4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_time_n.png', bbox_inches='tight') + plt.show() + +def skewness(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 9): + all_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + skewed_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) & data.skewed + all_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + skewed_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) & data.skewed + num_of_sequences2 = data[all_alg2].shape[0] + skewed_sequences2 = data[skewed_alg2].shape[0] + num_of_sequences4 = data[all_alg4].shape[0] + skewed_sequences4 = data[skewed_alg4].shape[0] + skewness2 = skewed_sequences2 * 100.0 / num_of_sequences2 if (num_of_sequences2>0) else 0 + skewness4 = skewed_sequences4 * 100.0 / num_of_sequences4 if (num_of_sequences4>0) else 0 + stats.append([ni, skewness2, skewness4]) + stats = pd.DataFrame(stats, columns=['n', 'skewness2', 'skewness4']) #.dropna(subset=['skewness']) + + + plt.style.use('ggplot') + plt.scatter(stats.n, stats.skewness2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.skewness2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + + plt.scatter(stats.n, stats.skewness4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.skewness4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Skewness') + plt.ylabel('Skewed Blocks (%)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_skewness.png', bbox_inches='tight') + plt.show() + +if __name__ == "__main__": + tlratio() + skewness() + time_profiles() + time_per_trial() diff --git a/tests/benchmark_skewness.py b/tests/benchmark_skewness.py new file mode 100644 index 0000000..f468b4d --- /dev/null +++ b/tests/benchmark_skewness.py @@ -0,0 +1,97 @@ +import random +import heapq +import csv + +# Common parameters +alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'] +trials_range = (10, 40) +n = 3 +sample_size = 100 + + +def to_benchmark_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [str(ralph_skewed)] + +def benchmark_nb_gm_001(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_001') + + +def benchmark_nb_gm_002(filename): + import generators.nb_gm_002 as nb_gm_002 + + generator = nb_gm_002.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + # print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_002') + + +def benchmark_nb_gm_003(filename): + import generators.nb_gm_003 as nb_gm_003 + + generator = nb_gm_003.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + print(f"sequence {i}/{sample_size}: {trials} trials") + seq = generator.generate(trials) + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_003') + + +def show_skweness_diagram(filename, choices, title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + print(filename) + data = pd.read_csv(filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) #.dropna(subset=['skewness']) + #print(stats.trials) + #plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'{title}.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + benchmark_nb_gm_003('../benchmarks/nb_gm_003_2back.csv') diff --git a/tests/common.py b/tests/common.py new file mode 100644 index 0000000..e40c0df --- /dev/null +++ b/tests/common.py @@ -0,0 +1,27 @@ + + +# Common benchmark parameters +choices = alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F'] +trials_range = (10, 65) +n = 4 +sample_size = 100 + + +def count_targets_and_lures(seq, n): + mask = 'D'*n + for index in range(n, len(seq)): + if seq[index] == seq[index - n]: + mask += 'T' + elif seq[index] in seq[index - n - 1:index - n + 1]: + mask += 'L' + else: + mask += 'D' + return mask.count('T'), mask.count('L') + + +def skewness(seq, choices): + import heapq + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return ralph_skewed diff --git a/tests/nb_gm_001_bm.py b/tests/nb_gm_001_bm.py new file mode 100644 index 0000000..54f6cb3 --- /dev/null +++ b/tests/nb_gm_001_bm.py @@ -0,0 +1,75 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq) , str(ralph_skewed)] + + +def benchmark(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets / s.trials, axis=1) + plt.scatter(data.trials, data.targets_ratio, alpha=0.2) + plt.show() + +if __name__ == '__main__': + alg = 'nb_gm_001' + fn = f'results/{alg}_{n}back.csv' + benchmark(fn) + # skewness_diagram(fn, alg) + targets_ratio_diagram(fn, alg) diff --git a/tests/nb_gm_002_bm.py b/tests/nb_gm_002_bm.py new file mode 100644 index 0000000..c8af543 --- /dev/null +++ b/tests/nb_gm_002_bm.py @@ -0,0 +1,105 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq), str(ralph_skewed)] + + +def benchmark(filename): + from generators.nb_gm_002 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials, int(trials/3), 0, 0) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +import time +import numpy as np +import pandas as pd + +import benchmarks.common as common + +def profile(): + from generators.nb_gm_002 import SequenceGenerator + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, int(lures/2), int(lures/2)) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('benchmarks/results/nb_gm_002_profile.csv', sep=',', encoding='utf-8') + +if __name__ == '__main__': + alg = 'nb_gm_002' + fn = f'results/{alg}_{n}back.csv' + profile() diff --git a/tests/nb_gm_003_bm.py b/tests/nb_gm_003_bm.py new file mode 100644 index 0000000..fa6c19a --- /dev/null +++ b/tests/nb_gm_003_bm.py @@ -0,0 +1,114 @@ +import heapq +import csv +import random +import time + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq, time_per_block): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [time_per_block, ''.join(seq), str(ralph_skewed)] + + +def benchmark_skewness(filename): + from generators.nb_gm_003 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['time_per_block', 'seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + targets = trials / 3 + t = time.time() + seq = generator.generate(trials, targets) + t = time.time() - t + print(f"sequence {i}/{sample_size}: {trials} trials, took {t}s.") + writer.writerow(to_csv_row(i, seq, t)) + plot_skewness(fn, 'nb_gm_003') + + +def plot_skewness(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def plot_targets_ratio(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +def benchmark_targets_ratio(): + pass + +def benchmark_chunking(): + pass + + +def benchmark_n(): + pass + + +def plot_timing(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['time_per_trial'] = data.apply(lambda s: s.time_per_block / s.trials, axis=1) + plt.style.use('ggplot') + plt.title(f"{figure_title} - average time to generate a trial") + plt.ylabel('time (s)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.time_per_trial, alpha=0.5) + + # draw fitted curve + # import numpy as np + # p = np.poly1d(np.polyfit(data.trials, data.time_per_trial, 3)) + # plt.plot(data.trials, p(data.trials), color='red') + + plt.savefig(f'results/{figure_title}_timing.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + alg = 'nb_gm_003' + fn = f'results/{alg}_{n}back.csv' + benchmark_skewness(fn) diff --git a/tests/nb_gm_004_bm.py b/tests/nb_gm_004_bm.py new file mode 100644 index 0000000..b4ad4a8 --- /dev/null +++ b/tests/nb_gm_004_bm.py @@ -0,0 +1,26 @@ +import time +import numpy as np +import pandas as pd + +import tests.common as common +from generators.nb_gm_004 import SequenceGenerator + +def run(): + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, lures) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('tests/results/nb_gm_004_profile.csv', sep=',', encoding='utf-8') diff --git a/tests/results/2v4_time_trials.png b/tests/results/2v4_time_trials.png new file mode 100644 index 0000000..9be91b4 --- /dev/null +++ b/tests/results/2v4_time_trials.png Binary files differ diff --git a/tests/results/2vs4_skewness.png b/tests/results/2vs4_skewness.png new file mode 100644 index 0000000..a488e1f --- /dev/null +++ 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+210,87.0,0.0,0.0,88.0,1.0,0.0,0.0,0.0,EDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +211,0.0,0.0,12.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCC,True +212,0.0,0.0,0.0,66.0,0.0,65.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +213,1.0,0.0,0.0,0.0,0.0,21.0,22.0,0.0,AGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFG,True +214,74.0,73.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +215,0.0,5.0,0.0,0.0,6.0,0.0,0.0,1.0,HEBEBEBEBEBE,True +216,0.0,1.0,0.0,0.0,0.0,53.0,0.0,54.0,BHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +217,70.0,0.0,0.0,0.0,0.0,70.0,0.0,0.0,AFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +218,0.0,0.0,0.0,0.0,0.0,0.0,36.0,35.0,GGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +219,0.0,90.0,90.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +220,0.0,0.0,0.0,0.0,0.0,0.0,37.0,38.0,HHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +221,0.0,0.0,44.0,0.0,0.0,1.0,44.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +222,0.0,0.0,0.0,67.0,67.0,0.0,0.0,1.0,HDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True 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+409,0.0,0.0,72.0,1.0,0.0,0.0,72.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +410,55.0,0.0,1.0,0.0,0.0,0.0,55.0,0.0,CAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +411,0.0,59.0,0.0,0.0,0.0,60.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +412,61.0,0.0,0.0,61.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +413,0.0,1.0,0.0,75.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +414,0.0,53.0,0.0,0.0,0.0,0.0,52.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +415,0.0,0.0,16.0,0.0,1.0,0.0,0.0,15.0,ECHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +416,0.0,0.0,0.0,39.0,0.0,0.0,0.0,38.0,DHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +417,96.0,0.0,1.0,95.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +418,28.0,0.0,1.0,27.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +419,0.0,1.0,92.0,92.0,0.0,0.0,0.0,0.0,BCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +420,1.0,0.0,20.0,0.0,20.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECE,True +421,0.0,90.0,0.0,0.0,0.0,0.0,89.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +422,10.0,0.0,0.0,0.0,0.0,1.0,11.0,0.0,FGAGAGAGAGAGAGAGAGAGAG,True +423,0.0,0.0,0.0,74.0,73.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +424,0.0,0.0,127.0,0.0,0.0,0.0,1.0,0.0,GCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +425,1.0,9.0,0.0,0.0,0.0,9.0,0.0,0.0,AFBFBFBFBFBFBFBFBFB,True +426,0.0,0.0,84.0,0.0,0.0,0.0,0.0,84.0,HCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +427,33.0,0.0,0.0,34.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +428,1.0,30.0,0.0,30.0,0.0,0.0,0.0,0.0,ABDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +429,0.0,0.0,67.0,0.0,1.0,67.0,0.0,0.0,EFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +430,62.0,0.0,0.0,63.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +431,1.0,9.0,9.0,0.0,0.0,0.0,0.0,0.0,ABCBCBCBCBCBCBCBCBC,True +432,15.0,0.0,0.0,0.0,0.0,0.0,14.0,0.0,AAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +433,0.0,1.0,0.0,65.0,66.0,0.0,0.0,0.0,BEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +434,0.0,160.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +435,0.0,0.0,1.0,0.0,42.0,42.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +436,0.0,0.0,55.0,0.0,55.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +437,0.0,0.0,0.0,1.0,0.0,73.0,0.0,73.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +438,79.0,0.0,0.0,0.0,78.0,0.0,0.0,0.0,AAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +439,0.0,0.0,67.0,0.0,0.0,0.0,66.0,1.0,HCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +440,0.0,0.0,77.0,0.0,0.0,1.0,0.0,76.0,FCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +441,0.0,0.0,0.0,0.0,153.0,0.0,0.0,1.0,HEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +442,0.0,88.0,88.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +443,0.0,0.0,0.0,20.0,22.0,0.0,0.0,0.0,EEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +444,41.0,0.0,42.0,0.0,0.0,0.0,1.0,0.0,GCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +445,0.0,0.0,0.0,47.0,0.0,46.0,0.0,1.0,HDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +446,1.0,0.0,0.0,0.0,86.0,0.0,0.0,87.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +447,56.0,56.0,0.0,0.0,0.0,0.0,0.0,1.0,HABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +448,0.0,0.0,0.0,0.0,11.0,0.0,0.0,10.0,EEHEHEHEHEHEHEHEHEHEH,True +449,0.0,0.0,0.0,0.0,0.0,1.0,92.0,92.0,FGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +450,0.0,0.0,0.0,6.0,5.0,1.0,0.0,0.0,FDEDEDEDEDED,True +451,66.0,1.0,67.0,0.0,0.0,0.0,0.0,0.0,BCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +452,0.0,0.0,0.0,13.0,0.0,1.0,12.0,0.0,FDGDGDGDGDGDGDGDGDGDGDGDGD,True +453,1.0,0.0,0.0,0.0,56.0,0.0,56.0,0.0,AEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +454,15.0,0.0,0.0,0.0,0.0,0.0,0.0,16.0,HAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +455,0.0,21.0,1.0,0.0,21.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True +456,93.0,0.0,1.0,0.0,92.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +457,1.0,0.0,0.0,0.0,35.0,0.0,0.0,35.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +458,13.0,0.0,0.0,0.0,1.0,0.0,13.0,0.0,EAGAGAGAGAGAGAGAGAGAGAGAGAG,True +459,0.0,0.0,65.0,0.0,1.0,0.0,65.0,0.0,ECGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +460,0.0,0.0,95.0,1.0,0.0,95.0,0.0,0.0,DFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +461,15.0,0.0,0.0,0.0,1.0,0.0,0.0,15.0,EHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +462,0.0,0.0,198.0,0.0,1.0,0.0,0.0,0.0,ECCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +463,84.0,84.0,0.0,0.0,1.0,0.0,0.0,0.0,EABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +464,0.0,0.0,0.0,0.0,0.0,60.0,0.0,61.0,HFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +465,0.0,179.0,0.0,1.0,0.0,0.0,0.0,0.0,DBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +466,1.0,0.0,90.0,0.0,89.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +467,0.0,35.0,0.0,0.0,0.0,34.0,0.0,0.0,BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +468,0.0,0.0,0.0,1.0,7.0,0.0,0.0,7.0,DHEHEHEHEHEHEHE,True +469,0.0,0.0,0.0,0.0,92.0,0.0,91.0,0.0,EEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +470,0.0,0.0,46.0,0.0,0.0,1.0,46.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +471,0.0,0.0,0.0,0.0,0.0,1.0,158.0,0.0,FGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +472,1.0,0.0,0.0,0.0,0.0,58.0,0.0,59.0,AHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +473,0.0,0.0,6.0,1.0,0.0,0.0,6.0,0.0,DCGCGCGCGCGCG,True +474,0.0,0.0,0.0,0.0,0.0,98.0,0.0,97.0,FFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +475,0.0,87.0,0.0,0.0,0.0,0.0,0.0,85.0,BBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +476,0.0,0.0,33.0,0.0,0.0,0.0,1.0,33.0,GHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +477,45.0,0.0,0.0,0.0,46.0,0.0,0.0,0.0,EAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +478,0.0,0.0,0.0,77.0,0.0,0.0,75.0,0.0,DDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +479,73.0,1.0,73.0,0.0,0.0,0.0,0.0,0.0,BACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +480,0.0,1.0,0.0,0.0,37.0,37.0,0.0,0.0,BEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +481,0.0,92.0,93.0,0.0,0.0,1.0,0.0,0.0,FCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +482,0.0,0.0,0.0,1.0,0.0,0.0,0.0,24.0,DHHHHHHHHHHHHHHHHHHHHHHHH,True +483,25.0,0.0,0.0,1.0,0.0,25.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +484,0.0,0.0,0.0,0.0,0.0,37.0,0.0,36.0,FHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +485,21.0,0.0,0.0,1.0,0.0,20.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +486,0.0,35.0,0.0,36.0,0.0,0.0,0.0,1.0,HDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +487,0.0,0.0,1.0,0.0,97.0,98.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +488,0.0,93.0,0.0,0.0,0.0,1.0,0.0,94.0,FHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +489,0.0,1.0,0.0,93.0,0.0,0.0,93.0,0.0,BGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +490,0.0,0.0,0.0,70.0,0.0,0.0,72.0,0.0,GGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +491,86.0,0.0,0.0,0.0,1.0,86.0,0.0,0.0,EFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +492,0.0,65.0,1.0,0.0,0.0,65.0,0.0,0.0,CBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +493,0.0,0.0,0.0,69.0,0.0,0.0,0.0,1.0,HDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +494,0.0,0.0,144.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +495,0.0,45.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True 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+599,16.0,0.0,16.0,0.0,0.0,0.0,0.0,0.0,ACACACACACACACACACACACACACACACAC,True +600,0.0,21.0,0.0,22.0,0.0,0.0,0.0,0.0,DBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +601,70.0,71.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +602,0.0,0.0,0.0,1.0,0.0,0.0,53.0,0.0,DGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +603,45.0,0.0,0.0,0.0,0.0,45.0,0.0,0.0,FAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +604,0.0,1.0,56.0,0.0,0.0,0.0,56.0,0.0,BGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +605,0.0,1.0,0.0,0.0,0.0,0.0,0.0,195.0,BHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True 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+611,0.0,0.0,86.0,0.0,88.0,0.0,0.0,0.0,EECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +612,1.0,0.0,0.0,0.0,14.0,0.0,0.0,14.0,AEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +613,0.0,0.0,35.0,0.0,0.0,35.0,1.0,0.0,GCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCF,True +614,0.0,0.0,1.0,0.0,43.0,43.0,0.0,0.0,CEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +615,0.0,0.0,0.0,0.0,0.0,1.0,67.0,66.0,FGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +616,0.0,27.0,0.0,0.0,26.0,0.0,1.0,0.0,GBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +617,0.0,88.0,1.0,87.0,0.0,0.0,0.0,0.0,CBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +618,0.0,41.0,0.0,0.0,0.0,41.0,1.0,0.0,GFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +619,0.0,27.0,27.0,0.0,0.0,0.0,0.0,0.0,CBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +620,1.0,0.0,20.0,20.0,0.0,0.0,0.0,0.0,ADCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +621,0.0,0.0,1.0,24.0,24.0,0.0,0.0,0.0,CEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +622,1.0,0.0,0.0,0.0,55.0,55.0,0.0,0.0,AEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +623,1.0,0.0,0.0,0.0,26.0,0.0,26.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +624,0.0,0.0,15.0,0.0,0.0,0.0,0.0,13.0,CCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +625,0.0,0.0,1.0,67.0,67.0,0.0,0.0,0.0,CDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +626,0.0,0.0,65.0,0.0,0.0,1.0,0.0,64.0,FCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +627,0.0,0.0,0.0,0.0,89.0,1.0,90.0,0.0,FGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +628,0.0,0.0,0.0,0.0,1.0,0.0,51.0,0.0,EGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +629,0.0,0.0,41.0,0.0,0.0,40.0,0.0,0.0,CFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +630,0.0,0.0,93.0,0.0,0.0,0.0,1.0,0.0,GCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +631,0.0,53.0,1.0,0.0,0.0,53.0,0.0,0.0,CBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +632,0.0,0.0,0.0,14.0,0.0,0.0,0.0,15.0,HHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +633,0.0,29.0,0.0,0.0,0.0,0.0,28.0,0.0,BGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +634,0.0,66.0,0.0,0.0,0.0,1.0,66.0,0.0,FGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +635,0.0,0.0,62.0,62.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +636,0.0,31.0,32.0,0.0,1.0,0.0,0.0,0.0,ECBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +637,0.0,0.0,0.0,0.0,0.0,0.0,48.0,49.0,HGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +638,1.0,0.0,0.0,0.0,0.0,0.0,54.0,53.0,AGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +639,59.0,0.0,1.0,0.0,59.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +640,0.0,0.0,0.0,0.0,1.0,0.0,27.0,27.0,EGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +641,0.0,0.0,0.0,23.0,24.0,0.0,0.0,0.0,EDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +642,0.0,0.0,0.0,91.0,0.0,0.0,91.0,0.0,DGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +643,0.0,0.0,0.0,0.0,48.0,49.0,0.0,1.0,HFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +644,14.0,0.0,0.0,0.0,0.0,14.0,1.0,0.0,GAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +645,0.0,96.0,0.0,0.0,1.0,0.0,0.0,96.0,EHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +646,0.0,0.0,0.0,50.0,48.0,0.0,0.0,0.0,DDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +647,0.0,0.0,0.0,99.0,0.0,99.0,0.0,0.0,FDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +648,49.0,0.0,1.0,0.0,0.0,0.0,0.0,48.0,CAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +649,0.0,0.0,52.0,0.0,1.0,0.0,53.0,0.0,EGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True 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+667,1.0,147.0,0.0,0.0,0.0,0.0,0.0,0.0,ABBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +668,0.0,0.0,97.0,0.0,97.0,0.0,0.0,1.0,HCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +669,0.0,0.0,1.0,0.0,0.0,0.0,53.0,52.0,CGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +670,0.0,0.0,94.0,0.0,96.0,0.0,0.0,0.0,EECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +671,99.0,0.0,1.0,0.0,98.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +672,68.0,0.0,0.0,0.0,0.0,0.0,67.0,1.0,HAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGA,True +673,0.0,0.0,0.0,26.0,27.0,0.0,1.0,0.0,GEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +674,31.0,0.0,0.0,0.0,32.0,0.0,0.0,1.0,HEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +675,0.0,0.0,0.0,0.0,42.0,0.0,41.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +676,0.0,0.0,50.0,0.0,0.0,0.0,1.0,50.0,GCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +677,0.0,25.0,0.0,24.0,0.0,0.0,0.0,0.0,BBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +678,0.0,0.0,0.0,0.0,1.0,10.0,9.0,0.0,EFGFGFGFGFGFGFGFGFGF,True +679,65.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,DAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +680,0.0,23.0,0.0,0.0,0.0,0.0,23.0,1.0,HGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +681,0.0,1.0,58.0,0.0,0.0,0.0,57.0,0.0,BCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +682,0.0,0.0,0.0,0.0,0.0,68.0,1.0,68.0,GFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +683,0.0,0.0,0.0,0.0,96.0,0.0,96.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +684,1.0,0.0,0.0,0.0,66.0,0.0,66.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +685,0.0,0.0,0.0,0.0,0.0,1.0,0.0,21.0,FHHHHHHHHHHHHHHHHHHHHH,True +686,0.0,88.0,0.0,87.0,0.0,0.0,0.0,0.0,BDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +687,0.0,0.0,19.0,19.0,0.0,0.0,1.0,0.0,GDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +688,0.0,42.0,1.0,0.0,41.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +689,0.0,0.0,0.0,0.0,0.0,60.0,61.0,0.0,GGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +690,0.0,23.0,23.0,0.0,0.0,0.0,1.0,0.0,GBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +691,86.0,86.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +692,35.0,35.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +693,57.0,0.0,0.0,0.0,0.0,58.0,1.0,0.0,GFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +694,0.0,0.0,30.0,30.0,1.0,0.0,0.0,0.0,EDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +695,19.0,18.0,0.0,1.0,0.0,0.0,0.0,0.0,DABABABABABABABABABABABABABABABABABABA,True +696,0.0,0.0,0.0,1.0,0.0,56.0,0.0,57.0,DHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +697,10.0,0.0,1.0,0.0,0.0,0.0,0.0,11.0,CHAHAHAHAHAHAHAHAHAHAH,True +698,0.0,0.0,89.0,0.0,88.0,0.0,1.0,0.0,GCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +699,0.0,0.0,87.0,0.0,86.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +700,17.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAA,True +701,0.0,0.0,66.0,65.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +702,0.0,0.0,1.0,0.0,0.0,0.0,123.0,0.0,CGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +703,0.0,118.0,0.0,0.0,1.0,0.0,0.0,0.0,EBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +704,0.0,0.0,0.0,0.0,0.0,0.0,0.0,132.0,HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +705,0.0,0.0,0.0,0.0,0.0,23.0,1.0,23.0,GHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +706,0.0,0.0,0.0,0.0,6.0,5.0,0.0,0.0,EFEFEFEFEFE,True +707,18.0,0.0,0.0,16.0,0.0,0.0,0.0,0.0,AADADADADADADADADADADADADADADADADA,True +708,0.0,72.0,0.0,0.0,0.0,71.0,0.0,1.0,HBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +709,0.0,0.0,54.0,0.0,0.0,1.0,0.0,55.0,FHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +710,0.0,1.0,87.0,0.0,87.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +711,0.0,0.0,1.0,63.0,0.0,0.0,0.0,64.0,CHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +712,78.0,0.0,78.0,0.0,0.0,1.0,0.0,0.0,FCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +713,0.0,80.0,0.0,0.0,0.0,81.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +714,0.0,1.0,0.0,0.0,0.0,0.0,40.0,39.0,BGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +715,0.0,0.0,7.0,0.0,6.0,0.0,0.0,0.0,CCECECECECECE,True +716,35.0,0.0,0.0,0.0,0.0,0.0,0.0,33.0,AAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +717,0.0,0.0,0.0,1.0,73.0,0.0,0.0,72.0,DEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +718,0.0,0.0,90.0,0.0,0.0,1.0,89.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +719,1.0,0.0,0.0,67.0,0.0,0.0,0.0,66.0,ADHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +720,56.0,0.0,0.0,0.0,56.0,0.0,1.0,0.0,GAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +721,0.0,0.0,0.0,1.0,0.0,0.0,49.0,49.0,DHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +722,0.0,0.0,0.0,117.0,0.0,1.0,0.0,0.0,FDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +723,0.0,0.0,86.0,1.0,0.0,0.0,85.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +724,0.0,0.0,31.0,0.0,0.0,0.0,0.0,30.0,CCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +725,1.0,0.0,0.0,0.0,98.0,0.0,98.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +726,1.0,84.0,84.0,0.0,0.0,0.0,0.0,0.0,ACBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +727,0.0,56.0,56.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +728,0.0,1.0,0.0,24.0,24.0,0.0,0.0,0.0,BDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +729,37.0,0.0,0.0,0.0,0.0,37.0,0.0,0.0,FAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +730,0.0,0.0,91.0,0.0,0.0,0.0,91.0,0.0,GCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True 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+772,0.0,68.0,0.0,0.0,0.0,0.0,0.0,67.0,BBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +773,60.0,1.0,0.0,0.0,0.0,61.0,0.0,0.0,BFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +774,0.0,1.0,0.0,57.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +775,0.0,78.0,0.0,0.0,1.0,0.0,0.0,0.0,EBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +776,1.0,0.0,0.0,0.0,0.0,96.0,96.0,0.0,AGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +777,43.0,0.0,0.0,0.0,0.0,1.0,44.0,0.0,FGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True 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+989,93.0,0.0,92.0,0.0,0.0,0.0,0.0,1.0,HACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +990,0.0,1.0,0.0,0.0,60.0,0.0,0.0,61.0,BHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +991,0.0,1.0,0.0,0.0,0.0,0.0,32.0,32.0,BHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +992,0.0,0.0,34.0,35.0,0.0,0.0,1.0,0.0,GDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +993,0.0,0.0,0.0,0.0,54.0,0.0,54.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +994,0.0,0.0,0.0,1.0,0.0,39.0,0.0,38.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +995,0.0,0.0,0.0,0.0,99.0,98.0,0.0,1.0,HEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +996,86.0,1.0,0.0,0.0,0.0,86.0,0.0,0.0,BFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +997,0.0,76.0,77.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +998,0.0,0.0,19.0,0.0,0.0,0.0,0.0,1.0,HCCCCCCCCCCCCCCCCCCC,True +999,0.0,0.0,37.0,1.0,0.0,0.0,38.0,0.0,DGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True diff --git a/tests/results/nb_gm_001_3back.csv b/tests/results/nb_gm_001_3back.csv new file mode 100644 index 0000000..b2f89a4 --- /dev/null +++ b/tests/results/nb_gm_001_3back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,0.0,65.0,132.0,0.0,0.0,0.0,0.0,1.0,HCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCC,True +1,51.0,0.0,52.0,52.0,0.0,0.0,0.0,1.0,HCDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACD,True +2,0.0,61.0,0.0,62.0,0.0,0.0,61.0,1.0,HDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGD,True +3,40.0,0.0,0.0,1.0,0.0,0.0,0.0,80.0,DHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHA,True +4,4.0,0.0,1.0,0.0,0.0,6.0,0.0,0.0,CAFFAFFAFFA,True 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+401,0.0,55.0,55.0,0.0,0.0,1.0,54.0,0.0,FCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCB,True +402,47.0,0.0,0.0,0.0,1.0,47.0,0.0,47.0,EAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFH,True +403,56.0,0.0,0.0,0.0,58.0,0.0,0.0,56.0,EEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAE,True +404,0.0,39.0,0.0,0.0,39.0,1.0,40.0,0.0,FGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEG,True 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+3,12.0,15.0,11.0,20.0,13.0,17.0,17.0,22.0,AFAHGHGHGBEBCDDDDHHHABCEHEHEBBBAHADADCFHHHHHFEFCBDDFDGDEFCAGGFEFBDGEHECCBCFFFFFFHGEBBHHCBCACHHDDBFGGGGEGEAFDGDADGDGDGBEBAAHDDFH,False +4,4.0,4.0,8.0,8.0,5.0,7.0,4.0,2.0,FGDGECDCECGCDADAHFDFCFCGAFCDDDABEBHBEFEFBC,False +5,15.0,15.0,15.0,16.0,16.0,14.0,9.0,13.0,HGDGBFDHDADHBBBBBHBAAGBCEABCGFAFAFBGBCBFGDDDEAAAHDFACECECHFHFHFCFHEGEFEFDFDAAHDEECDABFCCCCGBEBDAHCECHCHEDEDEDAGEE,False +6,17.0,17.0,9.0,6.0,15.0,13.0,15.0,12.0,BEBEBHAGCFEHHABAHDEDGHFBFGFCAABAGFFFAFGECEBEAEAFBFCEBEGHGDBEFABABEGEHEHBGBGDADACAGHGHGBGBACGCAHFFBHAECDC,False +7,12.0,7.0,7.0,6.0,9.0,8.0,5.0,6.0,CEGBFEFEFEHCCDEBCCHBBBGAHACBGGDBDADACADHDHFEAEAEFGFAAEAHAFAF,False +8,9.0,13.0,10.0,11.0,12.0,15.0,11.0,12.0,CGCFDBDFHHEHFFGCDHEHCFCFAAEGDCEGHGCFCBBBCBGFGHGDFDBDADHBBEGAGABABHBEBEHGHADAFEFCFDBDEFEHEFEFA,False +9,13.0,26.0,23.0,14.0,20.0,18.0,19.0,27.0,HECEBEFFHFDCCFGBCBDBAHGHGCBBABHEFAFEBEBHBHGGCHBGGCCCCCFCBDDDEDHDEEEAAFAFGFDFCGBGHEHDHGHAFABCGGEHEHFBGBADEBEBEAAHBDCCFGGHHHBHBHGHBDBEEAEGCGCBCHCEFFFFCHDHCHDHABCB,False +10,14.0,18.0,15.0,13.0,15.0,19.0,18.0,11.0,AFACABDDFBBBEBECECGHFBFBECDCEEEDGDBHHGCBDDAFCBAAAGHCHCHEAFBFDHAHCFFAAAHBBBFBFBHGFBCBCFGGGHGDGDFEGEFCFEDGDGAGEGCGEGEFEFAFDGC,False +11,21.0,20.0,21.0,13.0,15.0,26.0,21.0,21.0,EECEFFHGCADHGEGEABCCFDEBABEBGGCACHFHFBFBFBAHGBGCGHDCDABHHAGABFHEBCFEGDFDFDFAFBCBCAHACFGFBFBFBFBDACCBCHFHEGEDFDFCAAAGGEBFAAACACHCHFGFBFGHGHAEAGCCEDDFHHHGHGHGDE,False +12,17.0,26.0,17.0,23.0,17.0,11.0,26.0,21.0,ABGCACGDDFHFHBCEHEAGBGBEBAHEBEBFAAHAFBCEGDGBAHGGGGFGDDDBABABHGGGCGDGHGHDACAEDEFECHGEGDABGCHCDDDDCBCBADAHCHGBGBGEHDCDBBFBABHBHBFBACHDEEHGHECDCDHDEFEDECFGHGBFBD,False +13,24.0,21.0,23.0,20.0,15.0,14.0,30.0,24.0,AHHHHAFEDHAFBFGFCFGADADCDGBBBBGDGEGBCBHGGGGCGFBFAGGGGHEEFEGHGHABCBFHGAGACBBDEDHDHDGBCACAHGCACEHECACHBHDCGCECADGDGDABADHFGCGAGAHHBGFDCHBHCAAABEEFDFDBDBEADAHGEGEHECCCBCFCAHD,False +14,1.0,0.0,2.0,1.0,1.0,1.0,2.0,2.0,DECGCGAHFH,True +15,7.0,7.0,10.0,5.0,8.0,4.0,8.0,9.0,HBABHHEEGAGAGEGHCDEECHCHGBCBCDDAEGCBCGEAEFDFBFBFAGCHCHCHAD,False +16,14.0,19.0,14.0,7.0,10.0,15.0,19.0,7.0,CEAFFGHGEGFDFDCACAGBDEAFCEDDFAHHFDFGBEACGCGBGAFECECFGHCEBAFGEGCBABEBHBHBACAGAGDGHBABCBCBGFGFGFGBBBBFBCBGA,False +17,17.0,15.0,14.0,12.0,10.0,9.0,17.0,6.0,EBACADACGBGBAFGHGHADCDGAAFFFADABAHGDGABBCBCACACECHFBFHDCACDGEBADDEGGGEDADFGFGCGFBBABCBEBDBCHGEGEGECE,False +18,14.0,22.0,17.0,9.0,14.0,10.0,25.0,20.0,EHCHAHEHAHCHCGBGCGCGAEBFBFGGCEFGBGHAHCBABABHHGHGCACHDEDBBABGGDGDEBBBHHGCAEGBFHGEGEGBCCGCDFBBGBFBDAEEHHHCFEFECEHGCGCBHDADFDAGAGAGFBB,False +19,13.0,27.0,12.0,18.0,19.0,17.0,20.0,18.0,BFGCGBHAHAHEFEDBABEBEDADGGGGBAFCGEBDFHBHGHGCBBEGEGBHDHDHBCBCACDBFHHCHBGAGAGEDADADCDCACGHEEEEBDFDFDHDCGGBGDEBBBABEHFHGEFFFBADHEFFCFDEBEBFFEBHBFBG,False +20,11.0,10.0,7.0,8.0,8.0,7.0,11.0,4.0,BGBABGHGCGFBFAEBGGEDEFAHEHACDCDADBGGAGAGADFBFBCBCEFBFDHDACCDAGAEEE,False +21,22.0,20.0,18.0,24.0,13.0,11.0,16.0,21.0,DADADHCACFCHEDAAAHGDDHAGCDEDEGBHAHBDBDBGHHHCHCECAAAEFEDECEDBHFABGBCAGDBEGEBABHFCBBABDFDGHGCBFBCCDHDHDGDHDHCHBGADAFACHEHBDCDAFAFAFAGGCGCFHGBDBEBEG,False +22,8.0,10.0,11.0,7.0,8.0,15.0,4.0,11.0,CBAEGDGEHEBGBFBFBDHCHFHBAEHFFGFCFBFCFEEHABECFFFFACAEHHDCDCDHDHAHCFCBCBAADF,False +23,32.0,19.0,21.0,23.0,13.0,27.0,21.0,27.0,GHCABDGDFFFAHHHEAEHGAGAGHEFEGBCFAFBFGCHCHFHBGCAFFDFDBACACHCHCHBFGFEACAFABEBEBHHGHFHAHGGAGAHAFCGDHDHAFGCBCHDAAAAAAFCFHGEFFBEBEDDDFDBCBDDDCGFAFADBDBEBCAGGHDFDFBCDEAGAHCCEHGHAHCDDDDABAFA,False +24,26.0,30.0,18.0,21.0,29.0,16.0,21.0,21.0,GDGDADAGAGDEHCDBDHAHEHFHAHAFBHBHGCEBHBDBHBHBEEABABABAEECEGEGAGADHDBEEGBCAADHGBFBCEAAHDEBEBFBFBFCCGCEFBABAEDBGFGBGCFCGEACDFEFBHDADFHCEAEBDHDCGBEFGCDCACDEBEGAGAEAEFDFBBEHEGEGHCACEFBHDH,False +25,17.0,15.0,10.0,21.0,16.0,11.0,16.0,22.0,BDBDBHHHAAGAEHEHCHCDADEBGHDAGEBHGAABADADEDECEHAHFBGCGBEHCGADFBHECGHHFFFHFBDDDDDFDFDFHFEDEDACAEAEBDCHHBFBABCBGDGEAECHHGHGEGHDAGGG,False +26,12.0,13.0,16.0,11.0,17.0,10.0,17.0,12.0,GEECBGFEEDHCEFGFEAEAHGEGEDDDHDCDCBHBCBCFCECEGAGAGAHECFCEAAFGFGCEHGHBBBGBGBCBDHEAEFHFHGBCDGGACHCGCDADAEBFBADH,False +27,14.0,11.0,17.0,13.0,14.0,21.0,16.0,19.0,AAECGGEGHCACACACHBHADCECBDHDHDFCFGHGDDEDHHHAHDFDACHBHAFBHHAEEECGGFGEGEBEFCFAEAEFFBFBFDGDGDGHFACCDFHFCGBBHBCGGFGEHEFFFFHFCBCAF,False +28,14.0,15.0,12.0,21.0,15.0,9.0,13.0,21.0,GGHGEDHFCFCACBCADAEEEEAHDGAGHGHEHEHBBECEDBBBDBEGDGBAEABCCABBECDDDFDFHGHGHDHGHGHDADHHCHBHCCBAFHFDDDEDHFHAABDFDFEGEAADBDCH,False +29,18.0,19.0,27.0,26.0,29.0,30.0,16.0,16.0,DEFFFAFAGDGEEBFBFGEBADACADFDCEEDEDFDCDEBBGDGHGHGFFFDFBEBEHCHFDCDCEGFGFHFEFCGBBDCHCGCDADEGEGCFAAEHEHFDACGCEABBDECBCBCEFEFBFCFCFEHEHDGACEBAGCEFEBACCCAEDHDHBCFCDEFFHDHDHDCFCAAAEBEBFDHA,False +30,5.0,11.0,5.0,8.0,3.0,2.0,5.0,1.0,BBFGGBABFGCCCDADAHBEDCDBABGEAECBDBDBDBDG,True +31,28.0,17.0,19.0,16.0,18.0,11.0,17.0,33.0,DHAFAHAEAHDHFHFAFADHCGGGDGDGHEBDHCHBHAEBCBCFEGHHHBHCAFDHEHEHCDAGBCBAAAGACCBCAFGBHEHBBEAHAHAFAEACGGEHAFABEDEDFDCGHEBGAGEEAEBBHDEDECHCGABHGHAHAHBHCHCHCHDGACACDFD,False +32,5.0,10.0,12.0,17.0,19.0,17.0,17.0,11.0,EEBHBFFFDDEDCCAGEFEGGDGDFFGEGEAEDEFCFCGCGCGFAEGECDHHCEFDDHDFDABFDECECEHEFDDGDGBBFBFHHGCECEFEHAHDHDGBBFBGHGBG,False +33,4.0,13.0,10.0,7.0,4.0,8.0,11.0,7.0,CGBHBCBCBHFHFECBADGBGBGBDBCFAGDBHGFGECEHBGBCCACFGFGFGDDDFCADHEHB,False +34,22.0,27.0,22.0,21.0,21.0,28.0,21.0,21.0,BABFBCCCCGCDCAGABAHFBAHCBDBDHDCDCDEFFHBHBCBCBEHDAGAEFBBEEEBEGAGHGDGCGEBFBDEAECCFCFGDGDGHBHAEFFFECCADHFFBGHDHEGAAEDEFEFCDCDCDEFCHADAEHFDFHBBEBEBFBFAFGFAAHGHGFFAFGGBABGHGBFBFDFHCHAHEGDA,False +35,24.0,23.0,21.0,17.0,28.0,15.0,20.0,21.0,EGHGAGEGCGDFFCEEEEEAHGEGFGFBCBGBDBACHCAGDDDDEDEHACGCECAFAFEFHCHCEFHDHEHBAEADBDBAFCHCEEEEHBHBECEAEAFGGGGCCHBHAAACABBEHFHBDFHHDHBGCAABEBGAGABBFADADEBBBBCDCACFGFHDCEHEBGADE,False +36,16.0,12.0,18.0,16.0,29.0,20.0,25.0,11.0,EEEBCFFDHDBBGHGHGEFDFACCCFCGAECECEAGFFFCFDAHAEEHGGGBGBGADDGDGEGCCBFEHEGEHACDGDGCCCFCEAFAEGEGBGFGBBBHFGDGFGAAHADADCEEEEDEAEFEAEBFFFHEGECEGEHECAFDDDB,False +37,1.0,6.0,2.0,11.0,2.0,11.0,4.0,7.0,DBFFFHHADFFEFBDBFBGDFFEBHBHFHGDGDGCCDDDDHDHF,True +38,11.0,12.0,15.0,5.0,3.0,15.0,15.0,13.0,HCCCCAEBGFCFBGAHHHHBAFGCGCGCGFGCAABFBABHBFBCAFHFAFGCDBGBGAGFCBBAADHDHDCGEGHGCGFFHFHDEFHFC,False +39,33.0,14.0,21.0,23.0,21.0,18.0,25.0,28.0,DHAHAHADGDAFAFGCHCHEHCHABACEDDDCGBHAEFFGCADADGBGCFFFGGHBAAFGGHFHFHECFCHCHBDEFGADDCGGGHEBEDEBEBEDFHCAAAACFGFBFBFADAEGBDCAGACACAFGEEECDDDDCGGGEEEEEGCADHHHHAHABAHGBBCACHEGGHDADADAHAHEHAH,False +40,9.0,21.0,8.0,6.0,13.0,11.0,9.0,15.0,HEBEGEGAGEBBBHFAFABCBCBEBCBEAFHGGGHEHCHBEDFFAFAHDBFBFBEBDFHHDHBHCHBHBDEFABGBCEDEBCACHHEAGBGF,False +41,13.0,18.0,18.0,16.0,8.0,20.0,16.0,13.0,AGDGBCDHFADAGFFFHHCFCFEBGBGFGFGCGCHHHHCGFBFGDHABCBCGDGECEFBFCACBDBDCFAFBDEDCFFBHGHBEBABDFDFDHDHACABDBAFAFDHEGACACBEECGCBDG,False +42,21.0,15.0,14.0,22.0,14.0,22.0,16.0,21.0,ACFDFDEDFDBAFDCDCDFFFFFACHCHGEDFCFEHADACEHEDEBAFAGGHGEDADFDHDHDHGADAGCCCFHBDBGBDEGEBHGFGHAHFBFBFEAABABACDDAHHGFGBGEGHFEABHBFEHHHGDFDCACABABGECHAH,False +43,17.0,19.0,23.0,19.0,19.0,21.0,20.0,22.0,GDGFGEDDDDDDFDFDFEHBHDGAECBHDEGHGEEDEBEDECGGAADAFAFADECFCDGDGFBHGCBHBACAGACFCGGGBGCHFHEHECECAHFHFGCGHBFCGCBCFEHEGEHBBAAABDHFBCCCCFFFHFCABFBHBHBEDAFEHBHACABECHCH,False +44,2.0,1.0,3.0,4.0,5.0,3.0,6.0,5.0,CHCHFGBGEHFDAGADEDEGGFGEDEHCH,True +45,17.0,20.0,26.0,20.0,18.0,24.0,15.0,12.0,BDEFBBBHHECFCFCBBFEDDADADGECEHEFCGCAFDCGCFFEDDGGHHHHHAFAFEFAFDFDFDEDFAACFCFCDCBBBCGCGDGDFCGCGBDCACBHDHEECBBEBECFCHGBGEGABCDCEFHFGACDFAFAECEBEBDACABAGFBA,False +46,5.0,7.0,11.0,5.0,5.0,3.0,8.0,10.0,CBDHFHCDCEGEHCHCHCHEGCGCGBBBBADAHGDGBACGEAHBHFGFCECAHD,False +47,5.0,4.0,4.0,5.0,0.0,1.0,5.0,3.0,ACABGBHBHBGDCACHCDAGFGAGDDD,True +48,21.0,22.0,13.0,24.0,16.0,18.0,24.0,19.0,DBDGAGBGFHFCABGFECEGBGHHEACDFDGCGBEBGDAFAHADADAHHBHBHAGABADEBFDGDBDGDGCFAFAFDDDDECGFEFEAHAHEHEHCBCDADGBFBFAEBCAHFHEDEGBBFDEHEBDHFGCGHGHGBGCDABCBDGHGBGDCEAFAF,False +49,5.0,12.0,11.0,8.0,8.0,7.0,11.0,9.0,FCFDGDHBEBECFBBHFCFCGDBCCCGCECECBDBGBEHDDBCAGAEHEDFDHGEGAHBHGAGAGFHBHBG,False +50,2.0,7.0,7.0,4.0,6.0,13.0,10.0,11.0,BBFEFEFHAHFDFGHEBABDFHBHEFGFGHEHGGGFDFEHCBGBFDFHFHCCGCGHGCCC,True +51,5.0,7.0,11.0,12.0,13.0,9.0,8.0,13.0,EFFBFDAAECCCHDHBHFEDBHBHDHDGGGGECDGHCFEFEDEDCDCDEDCCHFEFEGCGBHEHBHAHAGDFCEAEHB,False +52,15.0,6.0,11.0,6.0,11.0,16.0,3.0,8.0,BAEGCCEAHBFCCHFABEHEFDCHEBECACECEAFGFEFEFBFBFAFADADACACDFGFAFAFEFDAAHFDCAHHH,True +53,20.0,14.0,19.0,11.0,13.0,12.0,10.0,17.0,CHCECEHEGAHBFGHCHABCBCDCECEDAHACGCADDBBGFGFGFHAAACACFBEGGAGAEHCAAAFDFDCHBDBHGDFDHCBEFEBCBABHHHHDHCHDFEFABEBECAAAEACF,False +54,18.0,14.0,15.0,22.0,24.0,20.0,25.0,23.0,EGGCGCGDEDEBCBFDDDBFHDDGFBFEEEGDBDBEHFDFEACACADABEFDCECGGHBDCDBAGHGFBFECHCFEDEHEHAHEEAGCEEEEFGFHFAAGEEHHHHAHAHDEFGDGDBCGAGHFHFHAHAHDHDBFBFCEGGGGGGGHAADAGCDFFAHCB,False +55,3.0,4.0,2.0,5.0,2.0,5.0,3.0,1.0,EHAABABGBFDFGFGEDDFDCBCDF,True +56,9.0,9.0,8.0,11.0,11.0,13.0,8.0,11.0,ECFFFBCDEDAFEBEAFGFHFHFDEHEBEHEGBFEFHBABCCAGAGBGBDFHAHGHFCFDHDABADEDEDAHGGCDCHCD,False +57,10.0,13.0,10.0,15.0,7.0,9.0,16.0,11.0,HHCFEGEGEDFGABEHEADCHGHBDFDGDGHGCGBBDDCDCDBDBHCDEBAHACCFDGDFAFAFDDAGAGHGCGBGBHACBGBGAHEBFBF,False +58,15.0,15.0,14.0,21.0,27.0,24.0,20.0,28.0,FAFEFAADAGFBFACBCBHHCGFGFAFHCEGEGHHBDBFHFHBEGDGDAEEHEGCGDGHCDGDEHFHGCEEEGEGEDBDEEEEHHHHCHDAGFEBHFHAHFHFDDDCACHFBDDHDGDFDAGGEAEFBHEEEEBEHEFFCFCFDBHAFADCGCGFHDHEBABHB,False +59,11.0,16.0,18.0,17.0,22.0,31.0,15.0,17.0,FCECFCFCFBHCHBGBFHGEDADADEFEFHFDFDADEEADHGAEAECGDGCCFHFGFHFHFHFBFBFCEEEBEFFDEGGBHBEBHFCDDDDGHAFBFBFCACHCAFGCGHHEDCBFEFABCDCEGGGDAEBBBEDEFFFFECGHEHF,False +60,11.0,9.0,7.0,2.0,10.0,10.0,11.0,9.0,HGHCDCHCACBCEGEGEGEBBHCFGABEBFAEHHFBFAAGHGHFHABABCGEGFDEAAABFEFEFGFGA,False +61,23.0,23.0,21.0,24.0,24.0,17.0,27.0,24.0,EDGGCBCFCGCGCFCGCDCBAACHFHFHECACAGAHFHDBDEHAGADHGEGEBCAEAGDHAADDDDCEAEADBGFDBBBBDHDGDBBGCAAEHEGDGBGBFHCGCDBBBEFHFDAGHCDCHFHFGEHEGEGHGBEFACADAFCBGBGBFHDEDEDFBFEGHGHAHAEEEEGEDHAHACEFBHB,False +62,21.0,13.0,9.0,12.0,17.0,15.0,25.0,10.0,HFGFGBGEDEHGHAHFHGAAAFGHBFACGDBEBGAAFEGEFEFBGAHDEDECBCBFBEGAGAFCCBBDBAGABAGGGGGECDADAGAEFEDGACADDCDHDEAFHFHFGGGFGCABAEEEGE,False +63,6.0,6.0,3.0,12.0,7.0,8.0,6.0,13.0,FHEBEBHGHDAGHDCDEDEAFCFCHEEBAAFDDDFDHDAGBGFDHGHAHDHEHFHFHBDBG,False +64,6.0,15.0,15.0,8.0,14.0,13.0,8.0,8.0,CCEDEDBHHGDCBEFEFCCGCEAGFGEGECAHAHGBCFHACEBEBEGEFFFFBDBFBHBDDEDCBCBHBFGFHEAEBCBCFCBCAFD,False +65,6.0,4.0,3.0,4.0,6.0,8.0,5.0,5.0,CGCFEFAFAEEDEHCHBBDAAFAGHEHEBFDHDBAGFGFGF,False +66,17.0,8.0,15.0,6.0,16.0,16.0,11.0,12.0,AFGFGFGHGFECECECHAECCCFAHAFAEHGGCEBAFAEAEFGGHCBFAAEHFHFGBHEHGAFBFHCECEADFDBDBCACACAEAEBEDDACBDFHFHEGC,False +67,24.0,12.0,23.0,14.0,18.0,18.0,15.0,12.0,CCCFCFBHAEEDFDBAADAEAEABDBDGEHEGCCCACECHGEGEDECACFCFCHBFBAGAFFGHADBEBAAAAFAEECEDHDHECGGBHHCHDBGBABAGEFFGFAFADACADAGADCHFECGFGFHFCDCEGFCC,False +68,31.0,17.0,27.0,38.0,29.0,28.0,14.0,16.0,ACACBCFDGBHBDEGEAHDDEFEFEFEFDDHECEBDFDAEAEFECECGCHAHAHCBCDAHBDDDDEDEBEHGDDAFEFCFDDBCGAGACCECAADADABAFEDACGCAFAHDFDBDGCECBGBFFCHCGAEDFFFHADFDADGFAFADEDHABAGAGEHEFBFECEDEDCGEADADFDHBHDFDCBCFCDAFAECFCEHB,False +69,5.0,4.0,3.0,4.0,2.0,3.0,6.0,4.0,DAHAGAHAHAHFGCGEBDFDEDGGCFBBGBC,False +70,5.0,7.0,9.0,5.0,2.0,11.0,6.0,10.0,HAHDHDHBGBFCACDCHFBBHBHGDEACACEGFCDHBGFGFGFCCHBFFHFCFAF,True +71,11.0,10.0,6.0,19.0,14.0,23.0,11.0,9.0,FHFEADABECHFFDFDFHFEDECEFEFEFAFHDADAEADDCAGFGBBHGDGABDDFFFFDDDADEEGFGDABCDGGBHDHFGAGBHBHBEBEGFFFFFCCEDE,False +72,25.0,17.0,20.0,19.0,16.0,13.0,17.0,22.0,GDCDHGBEAEGDGEBDBDHDCDCBHDEAEHDCEFAAABCDCDABAGADADCFAFCGCACAFFBAHGCGCGEGEACHHECACECEHEGGFBDHFHAHAHGGDGFCECHFHFHCHFABABFDGABDEDABABHEACAFDHHGHAHBBBBEH,False +73,15.0,19.0,20.0,23.0,23.0,21.0,22.0,23.0,GFGFECGCEEGHFCBCFDDDHHGBGHGHDCDCFHAHCCCFHAADEBEHEDEDADCDCABEGEFDFHCHGGAHAHFCFCEADFFECGBDBDBDCCACADHGCGEGHFHGHGBFADEBEBEDGDBBACEEEHGBDBFFFFDGEGDGDGFBEHHHHAAEAEFBBBBEFH,False +74,3.0,11.0,6.0,11.0,10.0,12.0,5.0,7.0,ECHFHDHEFFHHDCFGEGFDBEBEFFFDBCBFEDCDCFEBBFADDBDBGBGBGBAHAHFDEDECE,True +75,21.0,13.0,22.0,19.0,30.0,19.0,18.0,19.0,HAHEEEFEDHDFDBHBGCCEEFEGGHGHCCCCCHGECEAHDBDBEFGHCACGBEFEHAFDFACAFEEEHABAGAFDGDADADAGBCBAEADAEFHCDCFGEHFHDEDCDFEFCCCEAEAEGGABFGEDBDBHBCCECEHEAEFGHGHDDAEAEHCFGFGFB,False +76,14.0,30.0,18.0,20.0,25.0,19.0,27.0,30.0,FCFBAEDEGEHEBGHGFEFCGDBDGGCGCGBEBHBHEAAAEECBCBCFHFCFDGAEHHFGGGGGHCHEHBABGBGHHDFAEBDBDBDBCCHAGGEGDGCCBCHFGFGHGHBHEFGHBFBCBHEHBBABCBHBCGEHEADDDBHFHAADEDBFHFEEGEDHDHDEDBDFEFEHCHAEGDHBFBA,False +77,25.0,17.0,30.0,29.0,22.0,22.0,23.0,24.0,CCHEAEHBBCBDADBDBDHGFEECBDFGFEAHDCGCDHHEHEHCGCFHGDGAGAGACACDDDFDFDGECCHDHCCEFAFEBAFGGHDCCGEDBDBDBCHCACDBAHCGCGAHAHAFFFHADCDCFCFHHCDCAEAGAGAGABFHGEGBGDFHEBEFCFAGBEEAABAGDGDFDFEABHCDEDEHEHEFCFCD,False +78,9.0,16.0,9.0,5.0,4.0,15.0,4.0,5.0,BCEADCBBBBABABCCEHFBDHFAAGAGHCFCBCBFDFAGAGBFBDBABFFFFFCEHEBDHFFFBFC,True +79,19.0,17.0,10.0,29.0,13.0,8.0,14.0,14.0,DEDEAEAEDDDDDDDHDGEBEFADAGBFFHDGFBBBBGBABFCHGDFDEACBBBAHADAHCGCAHDHEHABAGCGCGEDAGBDAACAHDBCBGBGBEDDDDDADGDFDHHFDAHAEEEHCDCHG,False +80,9.0,11.0,7.0,9.0,14.0,3.0,11.0,16.0,HEHEACBHBHAGEBEAEBHBHBDEDCFABCGAEABHEHDADABABGGGDGHECEHHDGDHHCHCDGFFHCBEDEGEGHGE,False +81,4.0,9.0,4.0,9.0,3.0,6.0,6.0,5.0,BGBACACHDGDFDFBFEAHFBDDEDEGHGHBBBFBADHDGCGDBFC,False +82,11.0,21.0,22.0,24.0,26.0,28.0,21.0,21.0,EDGDCDCFGEDEFFFFGEEEDEDEDADACHCEBAFAFCHEDBFEDHDCCAHGFDFDGAGEFECEDBHCECDGGGGGBGFGBHCGDGFFDCAGDBCEHEGBBBBHFHADFHCHCHCACHCBBEFAGBGBEBFFFHFBCEDFFEFHDHFHFCCECBHBDBDEDEHBHEHFBFEGAG,False +83,2.0,4.0,1.0,3.0,2.0,4.0,2.0,1.0,CBFHFBBDGDFDFEGEABA,True +84,18.0,13.0,21.0,13.0,16.0,19.0,15.0,8.0,CBCEEADAFGDCFHFHDHFACACEDGACFGGGCBABDCCCCCCBABABABDBDFACGCGCFCAGEFEFBDBCFEFEAGFDBEFEHEHBAEADAFAFGEGECAHFEDGDHHCAEDEFCFGGGBF,False +85,14.0,12.0,10.0,10.0,16.0,19.0,9.0,12.0,FGBGHDEEEGBFAEAEDHGHGFEDEFEGEDEFEFCBAHCHCFBFDGECFFFGAECBBBDGFAFACACBEDABEBFHFHFHAHAHFEDCDCFCAAHBHADAFB,False +86,14.0,13.0,10.0,16.0,18.0,7.0,14.0,15.0,GGGGHADGCGCEEEDEDBAAGBCDAEABAGAFFFDBEFEAHAHBDBDBDBGHAACDHHGHGHDHEFBCDCHCHDEEBEBDADABEFECCGHGHFHDGEEEADBEEHC,False +87,9.0,13.0,17.0,12.0,12.0,23.0,13.0,12.0,EHCHBDDCECFCFCFABABGBFDFDCDHBGDHDGBGCGCGCFCDHEHEFCHGEAFBFBFDFHCEBAFEDEDFFGHCFGBGFGCDCEBGFHFAFBEEEBGFFCFAACAHAHF,False +88,6.0,3.0,0.0,1.0,3.0,3.0,5.0,4.0,GBGAGBHAGAGFEBEFEHHAHAFAD,True +89,11.0,11.0,12.0,15.0,16.0,12.0,7.0,10.0,BHBHDDADCGCAEHHDCEAFAFBFCDEDECBGFCECHAHGCAEDDBDEAFAFHFDCHEBEGEGADBDBHEHDFGFGFDECECECAAEBEBDBFF,False +90,18.0,21.0,18.0,8.0,15.0,18.0,18.0,10.0,BCBDGCBCHGHAAFAFEFAFDFHGGGCCECEHBHFCADAFAFEGBAAAGAFBEBEBEGCBHBFADAECDGHGBGECCBCBABHFFDCEFEHGBGBGBEFGABCBFBDBEEAHACGCGEGFCFCFDA,False +91,21.0,22.0,23.0,29.0,25.0,21.0,20.0,16.0,EDECECBBDBGGGDHDFCFDFAFGBACHDHDADFDHBEAACACACEDECEDGDGEGEGEDEAFCFEGGBEBGFGEDECGFAFAFGHEDFHFCFBFBDEDFDGBHEADHDCCFBABABACGEHAHFHCEGEGHBHDACADFCCHBHDCDCFBHAGDBABEBFBGCDBEBCDDADAEEC,False +92,22.0,26.0,23.0,24.0,20.0,30.0,22.0,18.0,ADAFEGHDHFFFFDFECADDDFHBHDCBFAHCHCACHEGFBFBCDHEFEGABAFAEBGBFFFBFCFGBHBEBAACAHAEDEDEGCDCDCDCGHACFCFHFHGCFCEHEHCGCDCEFGDGBGBGEGBABGBGCCABBBDBAFGDABFBFEFEDADBFEFDBHGHDFEFECBAGGCGADDDGBHAEA,False +93,2.0,2.0,1.0,3.0,0.0,2.0,1.0,2.0,DBDCDGFFAHAHB,True +94,18.0,8.0,12.0,13.0,10.0,9.0,12.0,11.0,HHFAEHCHCHCDDAFACACACGGFEFGCHDEEGCGCGFDDADGDFDEBHCDABGBABDGAGEEBAFABGBDAHAFAFADADEHHCHCBGEAEA,False +95,4.0,5.0,6.0,3.0,5.0,4.0,4.0,3.0,AHBFEADADAGFHFGGCBCBCBCFCEHEBDCEEG,False +96,6.0,10.0,15.0,4.0,14.0,9.0,14.0,11.0,ECECEGHGHEHGDACGHHHFGFGCCCGFEEHEAAACCHCFCFEGEDHFHFDFGEABBBBEBHGCGBEBGCACBEBEGCCDBFG,False +97,3.0,4.0,3.0,4.0,3.0,2.0,2.0,6.0,BGHFHDHDCDBDECAHAHAEGBFBHCE,False +98,14.0,9.0,9.0,12.0,16.0,15.0,11.0,5.0,BGGACFEGEGEAFGFGFGFAADADACBCFDADGEBHBFDFGBBDCGAFAEEFECHCDCBFEAEAEADADCEBDDHDBGEFCHEHEFEAEFF,False +99,24.0,22.0,16.0,19.0,18.0,22.0,22.0,17.0,BABDFDEDEDEHAACABAEAFFGBHFGAHDBCAGADEDCHBBGEGAGAGAGAGFGABEDEDEFCBABDBECECEAGFGEGBGACBFEHEHAHAFBFBCHEFGDADAEEBCBHHHFHFBAGGGFFFFGHDCCHAHBCBCHFGDBCCAFBDGGFDHDFDFDC,False +100,10.0,7.0,6.0,7.0,6.0,11.0,8.0,15.0,GGHGHGFEFDCHAHFHEHEBACCBCHFHFBCBEBFFEFHAHGHDAGADAEGBGHHBAAADCFHFDADFDH,False +101,21.0,23.0,9.0,23.0,25.0,21.0,22.0,21.0,EEEEEACAHEHDDADHFBFBAHGHGBGDGFECGBBBBFBFEFHFGFGFAEHDHAHAHBHGHFBBHGGGGGEHDDDDHEAFBHHDEFEHEDDGBCDCHBGDDFFCAHADEDEGEGEAABBEBDFGEBABCDFEACFDADAGAGEGBAFABHBDGDCEEEAFAFBFC,False +102,1.0,8.0,5.0,3.0,5.0,5.0,6.0,8.0,HCGCHDEBGFEFECBBBFBFGHGHGDGBAHCFCHHHEDEBB,False +103,29.0,22.0,27.0,17.0,23.0,16.0,31.0,26.0,GGHCFGEBEDGCCDEBFFFEFHGCDCBCBCECFCHCHCHGHCEGAGCECABHEEEBEBEGAGBBBABABFBHBHDHGGDADCCFAFEDECEABGBFAFHDAGHGHADEFGBDCHHDEDCHGABABFGDEAAAEBGAAEGGGGFGHAHDBDCCHGHBDGEGHGEAEACCHCACAHGHGHAHDCACAFAGAFA,False +104,7.0,6.0,18.0,7.0,11.0,12.0,24.0,18.0,GDGEHCGGGEFECEBECGCGHGCFHFHFHCDFDFGACHHHGBGHACDCGAGADBCAHECACGHGHBBCFGHEDEFEHGHBHGGCGCGCHCEGGDGEAFFHFCF,True +105,16.0,23.0,21.0,18.0,22.0,17.0,10.0,18.0,ACEGEHEHAFACDCDCHFBFBGBHDFFFCAGHBBBHBHFABABABAHEGCAEEEFGBGBADGEBCDEHEBCFCHBHEFEBDDDDDDDGFEDEFEHAHBCACACBDBDHDCBCEDEHEGCCFEEEDHHAABCFCHAECBCBFFCFG,False +106,9.0,10.0,12.0,6.0,8.0,7.0,13.0,7.0,FABABHCEGEGBGBGCCCHCAAABGEGDGFGFAFCBCGCEHDCCAGHDHCAEHFBFAGBGBGHFDCDBEEDE,False +107,17.0,15.0,17.0,17.0,16.0,26.0,15.0,17.0,EFBHGEAFDGCGFGFGDEEAEGBDEFBGGFAHHCAFAFHBHBDGDGEGEGDFFFDFHHHAHBCDADBCBFGFCBCBGBFEHADAHCECFCECHBFFFFCDEDEDCDEFEFCHHHCACAEBCGAAAAHADAFHFBDBCFDF,False +108,20.0,24.0,27.0,23.0,19.0,28.0,19.0,18.0,AFAEGFGFGAHFCFEHEGDBBBEBEBEBCDDDHDFGFDCDCECFAFAHAGBBBEBFDEBCBAHGFGAGABDBEAGFCCCBEBHCDBDFDFBBHCHGGCDCDFHEHECGCFFFADAHHHDCDAEEBFGAEHCDDGACACACFCBEFFHAGCCCCEFEFCABDBFFFGHCHDHDFDGBGA,False +109,9.0,16.0,17.0,17.0,16.0,16.0,12.0,24.0,EGDDDAHBEAEABDCEBFFHFHFHCDGHAHCCFDFDFDFBBEBFBFEHGHGDCFCGHGHGCBCEDHBCDHFHFBFGDGACCCGAEBHBABCHHEHBDDEHEDEDEGEAHDHCECFCFCBHAHEGBHH,False +110,5.0,7.0,7.0,3.0,11.0,14.0,10.0,14.0,AHEHDHGFEFGCHFGFBBCAEFEFEFECEHFHBHAHFCBGFABHBEDEGCGFDFACGCGBFEFGHHHHEHG,True +111,20.0,16.0,22.0,22.0,11.0,17.0,13.0,10.0,ACAFFCDCDCACBFAFGDAACDCDEDEFFCBHDGDCDGDEABFEAADDCAHHDHEGACEFBCBCACACABBHDHDHEHCAAFAFCDDEDFDFBFCFBFDEDFFGGAGCCBEBCBHBAGGGGGEGACBHBDB,False +112,26.0,22.0,28.0,29.0,20.0,26.0,21.0,19.0,GCDCBAEHEHGGFABGFFFFBDBDBHCHCHAAADGFCBCDCFFFDCHCECEDEAFBFEFEGGCDCDAEAECFCEEACCBABGFDABADAFHBHFEFEAHAEADFCFHHBHAHAGGDHCCCDHBCADABHBDCGHGAGAGDDDFCAGBCBDBCFCFEHEDEBGGFGFDBCGAGDCDEDGDBDBEFEHAFADD,False +113,4.0,0.0,3.0,3.0,1.0,0.0,3.0,3.0,HAHADDGDHAGAECCCG,True +114,15.0,25.0,14.0,19.0,17.0,16.0,17.0,18.0,GDGCHHEBEBHBEFAFEFBFHFBGHEFEFEBAAAGFGDDFDFDFDBDBDBABABDHCBGDHCEBBGBCBEBAGHCHBEBGHEHEHEACACACACBBGGFGHCHDGBCDGEFDFDBEHECDGBCEHAHDHACFGADFDBAGD,False +115,4.0,7.0,3.0,5.0,3.0,0.0,6.0,6.0,HGHBHBDBABACEGDGEAHBHADGEGCHCBDGDB,True +116,18.0,19.0,11.0,27.0,26.0,22.0,18.0,28.0,FDFEHEBGBGBCFDFDFBEGFABHCHEEFAFAFAFBDHEHEABBDCHCDDGEHEADAFAFBHHCHBFBEDHGHGBFDFGECHHABDEGECEDADEHEDCAHAGEBABCDCDAHEDEDEDFFFFFBFHGAFEGEGDHDHGHGHGEDHDGEGDAHABBHHDHBCDADHEGE,False +117,9.0,10.0,11.0,5.0,12.0,11.0,5.0,12.0,HFBFCFBAAEABGHCHAFABBBBCCCHCECECHCGEHEHEHFHAHCEDDFDCEEBFFFFGEBEAFAHDGBGDEHA,False +118,1.0,8.0,6.0,3.0,6.0,11.0,9.0,8.0,BEBFGFGFBFBGBCDFEHBHAGEFHGDEFBFHHCGCDBGFGFGHCHFHCECE,True +119,16.0,21.0,23.0,14.0,8.0,20.0,24.0,21.0,EEGFBBADAFCBHFACCCFCFEFDGAFHFDABHBCGHHHBHGHCHEGCAABBGDHBHBGFGCGCGCGHFEFCFGABAGGCGAGACFCBCBHBFCFADHDHGHGFDEBEGCGCDBHBEAACHDDFDCDCFBFBGGGGCBHDHDHFABA,False +120,23.0,16.0,16.0,25.0,12.0,20.0,24.0,21.0,DFHFBBDGFFEDCHEEGGGEEADAGAGDBDAABFDFCGDGAABABABABACAGGHDHFACECBDDFDHGHGHBCBCAGFGBGCFFFDFDCGHGDEEHBCDCBHBCFGFDFDHAGCHHHHHGAFADDHEHEAGAGAGHCBAEAEDCDADCFGFDHDHF,False +121,19.0,17.0,15.0,20.0,28.0,24.0,23.0,17.0,DCDFFGAAFFFBGAGDGCACHEHDADADFEHEGGFFEFAABBHGGGFHEHACACBEEEHBAGAGFDFEBEGEBECECDCHBHGDGBEFEAEAEAECCGCEHBHCFFGBDBDCDAEEEAEFFFBHAHGEDEBGFGFGHGBGBDFDCDHEHDDDEBAFDFEGCFH,False +122,24.0,21.0,31.0,19.0,20.0,33.0,21.0,17.0,CBDGEGCBFGFHFHFEFBDAECCCBCBGHDCCCAFADHDHDEDACBDBGAHABFDGEGCHEECECDAFBGBGBFFFFHEAECHFHFHGEEBCFCFDGEGFFFFGCDCGBGBGFFBFBFAAAAAFGBAFABECAGEGBGFHFCADDCECHFAFADAHFHEDEHCFBACAEAEFDCCCCCBCHDADCG,False +123,23.0,22.0,33.0,26.0,18.0,14.0,26.0,19.0,DGDGCACABHFCADADGHGEEHGACAHAGACEDEDEDGDFCHDECFCBCGHGECHCHBEEDEDEDEDCBGBGBABCBCBHAGDGECAGDCCCFCDCFHFDABECGBGFHBBFBEBEBACEDBHHCCGCDAGGGFCCCGDDFCBCBGBGHGHGCBADHFFAHDGAAAAABAFDHDHCFCEAD,False +124,14.0,14.0,13.0,14.0,9.0,17.0,19.0,18.0,DCBFBFAFAHBHGFBABECACGGBGCGCFAFHHDGDGEBDADFFHHHHDAABHFFEGAGFDBGHGAGBGHFHFGCHCDGEGEFCGDGDCDCDCECBFAFCFHAHEBEGHBEBHHADAD,False +125,22.0,17.0,18.0,14.0,19.0,23.0,19.0,20.0,AFFEGCACEHAHBHFHECADBDEDHDHDACHCBCBHFDDAGHGHCECEAEAHBHGGCEAFAFBDGFFFFBAGAFAFHHCGDFFAEBBABADADBCGHHHGACACFCFDFBCGHGEGEGBGBCBEEAFHEBBGGECEFECEHGGEAFDFDFAF,False +126,2.0,2.0,5.0,1.0,2.0,0.0,0.0,0.0,CBABCCCECEAD,True +127,9.0,13.0,13.0,20.0,8.0,15.0,15.0,18.0,GGEFDFEHDHDHBAGABBBFFHFCFHGHGHGHGDADHDEDFCEDAGAGCBDFDHDHCBCDFDBHFHGHFBCGDDDDDABGHDHCHAAECFBDBEBCBCEGECCFFHCGAGF,False +128,26.0,16.0,20.0,13.0,15.0,14.0,8.0,14.0,AFAFGCBFDCCGCBCACACAFACECBAFAFDBBABABHECBGAHADEDCBADABABAHEHCHCHGECDHDHBHBAEDEAEAHBGFAHBBCACACAFEDCAHHEADGEGECEFFFCGHDFDEAEFFD,False +129,3.0,2.0,3.0,1.0,2.0,1.0,0.0,1.0,AHABFBEAECCDC,True +130,3.0,10.0,5.0,11.0,10.0,4.0,3.0,9.0,DBGBHBAEDEBCCEBAAFHHDHDCBEDHBHBHBDECECEDDDFDGDFBEGEHEHF,True +131,18.0,19.0,23.0,22.0,20.0,20.0,15.0,23.0,FGBCAABCBCDCDCBBAAADCEGHAFDFEBHBHAHGDAEAEAHGECHCDDFDBEBHHHDBCFCABFHHHABFHHEGEHBAFAFCDCHGEGEFBFEFEDEHCHCHDHDGFAFEBEBGBGFCDCAEDEGFFFHFBEAGACFDDDDHDCCCCDCDGEGBGCEH,False +132,27.0,13.0,16.0,13.0,20.0,12.0,27.0,15.0,HAACDHGHEBFFCDAGADAEABAGHFHDHCCAEHFHBGBECGGGGAGABACDEDCACACFGFGFHBBEBHGGGDABGGGEDECEAEAEAFCEGBBBAGAEAEABHEAEGGGCEHFHDGAGEDEDFDHDEAAGAHAFFGCCCCG,False +133,5.0,7.0,9.0,1.0,6.0,7.0,8.0,7.0,BGCFEBHHHHACABFBFHFCFGGGCCECGCGCHAEBBHFGCGDAEAEBEF,False +134,14.0,15.0,11.0,16.0,21.0,17.0,16.0,20.0,HBHDHFHDDEFEGEFEBGDFDFBBHBAGEGCFHBHDADHHFAFAHECEFADECEDDDBDBDACBEAFHFHGEGCGDECECBAGACHBHGHFHFHGEGFFHEHCHCEGEGEAEGDGEABDBABFFGECABA,False +135,8.0,3.0,1.0,2.0,4.0,6.0,9.0,3.0,GFGEGHGFEFGCGDBAHAFDEAEGBGBAAAFAGAHF,True +136,14.0,29.0,20.0,23.0,25.0,22.0,18.0,18.0,DGDCEBGFHDBFBECHFEFBDEDCACGCGHEFEFEFAFGGGDCFGFHFHAHADEBBCBCEEEFEBABCBEBACACBHHCFCEAEAGBGDCDBDEDGBACECBHEHBDGDFDGCGAFEFDBHBEBEAHGFCFBFBHEDFDGDBBBBACDBDHGBEAEGFCHBHEHDHDFD,False +137,3.0,5.0,1.0,6.0,8.0,6.0,3.0,5.0,FDFDBBBEDEHEHEFEACFFGDHDFGBHAEAEBEGDH,True +138,17.0,19.0,28.0,23.0,19.0,29.0,14.0,27.0,EEHFCDHDHBAADFECECFFFCDGBAHAHFHBCDDFDGDADBCAAHABAEGFHFHDHDEGCGHGHCFDFEFGBHAHBCBABEEECDCDEHFHFBABHCCCACHEACHDGDFHFHBHFGDGDGDFBCDCGABFFDFECHCFFFHFCDGEFCACHCHCHEGACFCFBFEEECEBBBBD,False +139,18.0,10.0,15.0,7.0,19.0,9.0,15.0,15.0,BCDGAGEBBAAFCBEFDFHCAAHABFEADAHGCCCACEDEDEDEDEHCBCFEHCHEACACHGGGGBGEGFGFEHECGFEAHGHEHEHEHACAFBGGABABHGHEAEAC,False +140,12.0,11.0,10.0,15.0,15.0,9.0,10.0,21.0,GGDEDEDHDABGBDCAFADADEEFHFEEBBAHECFCAHGHGHEBBCBABAFHHHHAFADHECEGGBGECECHBHECFCDDDEEHHHHHDHDHDHFACGDABFG,False +141,6.0,7.0,16.0,10.0,19.0,4.0,7.0,3.0,GAGEECEDBGBGFCFCHCFBDBDECEAEDBDCHBEEFAHAEAEGCBCEADDDDEGCCEEEECCCECDCGCEE,True +142,17.0,14.0,17.0,18.0,21.0,18.0,15.0,9.0,BADAGADHDGDGFHFAFDFGEEDDDADCCCGGECCCGEHAHAHEEEEAECFCDHDFABABFBGBCACEFFDADAEEHBHFDFCBEBGHGCFCDAGFDBEFFGFGEGCBAEDEBCBAACDCBEBEFEFEG,False +143,1.0,3.0,4.0,4.0,2.0,3.0,3.0,3.0,DHDCCGCGAGHBBFEFCFDHDEB,False +144,3.0,1.0,7.0,1.0,1.0,3.0,7.0,2.0,CDCFHGGFBCCCCGAGAGAEHFGCG,True +145,3.0,5.0,7.0,4.0,3.0,11.0,6.0,3.0,DHGEGBGBGCCFDFAFHCBEBEBDFCFCFGFCCAHFFFDGAF,True +146,4.0,13.0,6.0,8.0,6.0,15.0,9.0,3.0,FABGBGFGFDBBBCGEEEEBFGCBFBDBCFDFGFGFAFECCDDADAFBDGHGBFBFHFEFHCBD,True +147,16.0,16.0,22.0,23.0,21.0,20.0,35.0,29.0,FBFEECGAGFGFGHDHDFAGEGEHFHFHFEGHGCEEAHDGDEHEGEFHFCFHGHBECDBDBHHGGGGGGCBHAHACAHAGEBDCEAGGHGHGEGEBDAHHHCHADGCFBFHGBGCHDFDFDGHCBCHHAGBEBDACHCFFGGGDADEEAGCEDEDCCCGDFDBDGFBFBGBDEACACDCDCH,False +148,16.0,20.0,20.0,23.0,21.0,16.0,31.0,18.0,EBEHGGGHCACFDDDDDAFCHEGCACFCFDFAGADEGGGAGEECEGEGEGAFFDCBHBHDHEGCDCGBGBGCCCCCBDGEBCGFHCHGHAHBBCEGEGEBFBGAHABDBDAGAGFGBEEEFEDGDAFCHBABGBADADEGFFDHDCFGGDHBFBDEDEDGHHHBH,False +149,3.0,7.0,4.0,6.0,10.0,7.0,3.0,5.0,EBEHEBEDCFCBBADCHFHFGBGBDEEEECHBDADADEFFFGFHE,False +150,6.0,2.0,7.0,6.0,2.0,3.0,8.0,0.0,DDDCGCADFDFGGGACACAGBECGGDGABACFCE,True +151,5.0,2.0,2.0,0.0,5.0,4.0,2.0,3.0,GAGAFBFEFECEFHABAEHEACH,True +152,14.0,12.0,9.0,7.0,12.0,11.0,10.0,17.0,FDHDFEHDHCFCBCDGHGCFFFBFHACCHBGAGAHEHEBEAADAHBGBFBFBABABAHAHEEAFHEHBHEHABGGECDCECEAGDHAHEFGG,False +153,19.0,24.0,27.0,19.0,23.0,23.0,26.0,24.0,CDCGGGFAAGACHFHDHDHBBCCHCGFAHABGBEDHBGBGBABADECFFFFAGGCHDDGDGCGHGHGDCFHDHAFEFEFEHDCCGGBGEGAAFCEEDFDFGBEAFHFCGEBCBHBFBDCDGBCBEHADABCHCHEHEHBHDGFGAGEGBBEBHDEEHAHAEAECCFFFCCCECECEFBFBDECBA,False +154,13.0,10.0,11.0,9.0,11.0,8.0,12.0,4.0,GEAEAFAGADADAEFCGCGCGCAFBFBEECEGADADACBGBCHHBFEECACBEHEFBFBDADEDBCGGGBDFHCAGGD,False +155,23.0,15.0,20.0,21.0,22.0,13.0,16.0,23.0,FEBEBEBFDHDHCCDDBCBEGFDFGBHCHFDAEBCBFHAHGHDADCBGDHDHDFCAHHHDBCEHDFDAAECDCDCBCAFEEEEEAEAGACHCEGEAEGGGGAEABAFAFHHGEAAACHFHAHFGEAEDEDEDADHDBCGAGACBCHHBGGCHC,False +156,1.0,2.0,8.0,2.0,1.0,1.0,0.0,3.0,CCCCCHCHBACDCBHEDF,True +157,11.0,6.0,5.0,14.0,10.0,10.0,2.0,6.0,EFAHAHFBFGGABADFCBEDEDADAHAFAHBFEDEDCDEDEDEDFFCBEDFDFBACDDAEHCHA,True +158,15.0,22.0,16.0,16.0,9.0,21.0,17.0,9.0,CFCFCAEBDGDHBBFBHCAAGFFFAGGGGFGHCHDBDBECECECFHBBCBAFHFDFBCACHCAAAEFDBDBCFGAADADAGGBBBGCGBGCFBEEGHGFGFDFDFABABDFHFDBDCEFEBGDDB,False +159,3.0,6.0,10.0,6.0,2.0,3.0,4.0,5.0,GGGFDFDBCBHBHBCCHCBCEHHFCACDCBEDDDACGCA,True +160,7.0,12.0,7.0,6.0,6.0,8.0,8.0,5.0,AEFEFEBCBADCEFHHCHGBBECAABFBFBDBGBHECGDADADGBGAHFFCFCGDGBGB,False +161,25.0,18.0,13.0,27.0,15.0,21.0,17.0,28.0,HFHGDDBDFDGHGADHGFBHGCFDAECCHHEFEFEDDBEBAHAHFHFBFHAHDFDFAEDFBBCEHADGFGAHDGDGDGDFCBCEAEBCBHDHDHAHAEADHHFHFHEGBHEDABABACDCAEFDDGFGAGABAHDHDGDGDBHBFAABAGAECECHCACBFAFH,False +162,18.0,23.0,16.0,12.0,17.0,23.0,24.0,31.0,AEABABCBCHCHCFFFBHHEGBABDDDDDHHFHEECFCFCBEDDBHBHBCGHDFAFHCHFGCHHHHHHHCFGFGEHDBAAEGGHEBBHGDAHFHBHBECGFAFBGCAHEHGBBFBDCHHGEAEHGFFFADGEGBGBGCGFFCHGEGEGAGAFABABAEAEGFGF,False +163,24.0,23.0,17.0,16.0,25.0,31.0,34.0,30.0,FHFHFEFGFBAEHHHDHDHFGGDGDGFGDHACAFGDGDECECHCGAHAHBBBBBFFFCGBGEFFHFEAECGGBBAGABABAFHFHECGDECFCHDBACDEHBFBHBFEFDDGCHBHGHGHBEAGFGCEHFBAHACEHEACFCFEAEGEGAGACFEAEBGGFDBDBGEGECEAHHHAGBGHAFDFAFDFGBGHGFGAGHEE,False +164,16.0,17.0,19.0,27.0,19.0,29.0,35.0,19.0,GDGBCCGCAFBFGFDHGHBFAFGFGDDECECDGDCDFHFGFCFHFEABACFHFBFHEEECEDFDEDGGGDGCCBBDBFBABFBGDEDEGBHBDDDGGGGCFHFGFGFHFEABBDCDCHCGGGDGFGEDADHDECEAGAFAHEHADAFFGGGCABEGHCAEFGFGAGDDHDHBCEHGAEHFH,False +165,10.0,7.0,7.0,12.0,6.0,6.0,5.0,8.0,DGFFDCDCDAEGDBDCEBGACECHCECDBABDEAHDHGAAHHHFHFBFBGBHDADADAFAE,False +166,17.0,18.0,17.0,16.0,20.0,19.0,17.0,15.0,CACAHAFBDAAADADHBGFAFDGDGDGHHFHFGFGFHHCAAEBFBFCFAHEBABEEGEGEGEBAHGDCDGEBCHEGDGCFCEEFECBCFHBHBHBADDFBFBGDCBCFFEGCAEGEFBACDCECECFDDADEEEGHBHB,False +167,15.0,4.0,11.0,15.0,21.0,12.0,17.0,17.0,HHAHDEDGHFHEHCHGFGFCECEGEACFGDGDCDCHADCEHEGGAEEBEBFHHHCHCHCFDAHAGDGFGDDHEEGCAEDEABAEGEGHGDDFAAEFGAGAEAFAFDFEEBED,False +168,8.0,4.0,9.0,2.0,9.0,7.0,3.0,7.0,ECECBCHFHCGFGFEEEHEHECAAHAFFBAEAFHBGAEAHDBDACCCFC,True +169,16.0,14.0,9.0,11.0,11.0,11.0,12.0,11.0,DFDFDGAGAGAGFGHHACBHBHGFFDFGBCEAHBDAEADACCECAAEABBHEAEAEDEDCABABCBGGGGFFACHHBDBFFDFEEGBCDHEHBHB,False +170,4.0,2.0,1.0,1.0,6.0,4.0,5.0,2.0,GGDBEEEEBEAGFFCFGFHAHAEAG,True +171,28.0,14.0,20.0,10.0,8.0,25.0,20.0,36.0,HCHCDCGCDAGAGHGBABAFAFCFAFDFGFGEGHFEFHBHGFGCHEHABFGFHHHCFDACHEFBHHHCHAHGBAADCHBHBFAAAHHHFEGCGDAHAGFBFAADAEACFFGAEAGABFCHCBFDEAGAHBHBAAHHHFHFHCCACGHGHDHDHCHCFCBGF,True +172,3.0,11.0,4.0,4.0,5.0,7.0,5.0,5.0,BBBEBHHCCFEFGFGHGBBBGBDFAFACEHFGFHDBDBABCDEE,False +173,8.0,13.0,6.0,15.0,4.0,10.0,15.0,7.0,ACDCGBGFFFGEGBGFHBHDADHDFGBGBGHCDAGGGCHDHGADDDDDDEBBHBFBFGFAEADGCCBDBDGAAEFBFB,True +174,10.0,11.0,8.0,10.0,13.0,7.0,14.0,11.0,GCGCGCGFGEBCAAEEHEAEHDHDGAADADADFBEDECHCGGGHGEEHBHAHABFBEBHFADGDHEECHBBFBGEGBGDCFBFD,False +175,23.0,12.0,12.0,24.0,26.0,34.0,26.0,24.0,CDBFHAHBGAAFEGHAFGCAFGFGBGBEBEAFGDGDFDADCFGEGBFCHABFCGADHFFEFHFEFEFEDHFGCGEGEAABEGAGHGEAFAFAFCFAEDEDEDHDHDHFFFGFHACEFHHHDHDAGFDFGEGBGDHDBABAFEEEHEBGFGEEAEAHHFDDDGHGHDFCFCACHDDEDEFHC,False +176,18.0,8.0,20.0,16.0,15.0,17.0,11.0,11.0,FCFBECGAFAFABAEEEEDCDAECEDGAAADFHBDBECEHEABABCDCHBGEHAHAGAECHHHADCCCCFCDCDAGCFFEEAFAFGDDFHFHFHDBGGDGDADFGCECFCGCDCFF,False +177,13.0,12.0,13.0,12.0,6.0,11.0,5.0,9.0,DABFHGHCBDBDCFFGABAFEBACAHECGDFFHFHFDFEFCHCBCBAECGCGCHEAEADDDBDADAHHBACABACDCDBFB,False +178,7.0,14.0,10.0,12.0,19.0,22.0,10.0,9.0,FDECFBFDFDFHFGCEDEDEFHGBACCEGGAEBEGABFDFDFCHGHFFEDBFBFBFEGEHADAEFEFEFEABCFHDHDAECFCGBFBGBFBEECECDBEBHGH,False +179,2.0,2.0,2.0,1.0,5.0,4.0,1.0,6.0,HGFEHEHEFEDAFHFEABBCHCH,True +180,2.0,5.0,1.0,3.0,3.0,4.0,0.0,0.0,FAADBBBBEBEFEFDDCF,True +181,6.0,7.0,5.0,2.0,1.0,4.0,3.0,6.0,BHBDBAAGAHCHFHACAHEHBBBFCFCACGGDBF,True +182,2.0,3.0,10.0,6.0,8.0,6.0,4.0,4.0,BCBCECEAEDEDHCCCCHEHEGDGCFFFAHGBFFFECDDECGD,True +183,27.0,20.0,35.0,20.0,19.0,18.0,17.0,19.0,CHCHCFCBDEHBHEHCCCCBDBAADFFECCGCAEAFAHCFGDGAGACABFEAHCBDBDBDACGDEDEDEHEBGDGDCAGABEBEAECEGAGFGCABFGFCEAEAGACFCDCFFGFEHBDBDECACAFHBHCHBHBFAHDBCADHEHACAGDDDGCEBFBFCCCCGAHCFCACAHH,False +184,21.0,29.0,29.0,14.0,13.0,23.0,22.0,20.0,HBBEFAHAHDHCHCGCBCAFABDDHDFAAADBDBEBCBCBEACGCGFFBFAFHGHFCFEHCHDADFCFCEDBGBCCFCFGFHCHCACBEAFBECFCDAGGCGFGHGFGEGACCDCBHBACGFGFHFBFGEGBCHCBCDEBBCHGGBGBDDFAAAEBEBABHBABHGEGBHA,False +185,16.0,21.0,7.0,5.0,16.0,12.0,3.0,15.0,BBBHGHBACDBEAAAFDHEHAGAGAEEEHHCAEAFBBABFBCECAFAFBFHFEDABBBFBEBEBEBACHFHFHDHBFEAEBHAFCHEDECEHBHB,True +186,26.0,34.0,20.0,22.0,24.0,21.0,26.0,17.0,HFACACHCBBBBHBGBEHFHFEAHAEAEFDBHECAHAHDDBGEDCBEGGFGECAAADBEBGCGCFCFCFBFBFBAGCBBABEHGCGCGFGBBCHCEDAHBCEAEHDBAHGGDDDDHEADDDDDFFGBGAGBGBEBABDBDGDGBFBDBDBDHEFEFCFEAAFGEBCGEGBFFGCGAABAGCHEEEAFAEA,False +187,3.0,5.0,0.0,1.0,1.0,2.0,2.0,4.0,DEBGHGAFBFHHBHBABA,True +188,8.0,11.0,10.0,11.0,8.0,19.0,14.0,12.0,HGFBFHFBFGGAHDDEBAHFHFHFCEGFGFGFGBGEGBCEEAFDBBBHFHDBDBGACHCHFGCGFGCGFBCDCDFFAEAHAEFDFDHAECDCD,False +189,24.0,32.0,23.0,32.0,21.0,21.0,20.0,22.0,BBBABAEECDDDEDEHEBECEDEDHHHFHFDFHCDAHAHDBGBGEGFGFGFGFBAGCGDFBFHDHBBCHGHGFAEBEDCAAGFDDADADBDCFGHBABDHECBDBAAHADAGCDCBABABGBHDCGCBCGFEBDCHAHCCCFCFEBABHDDBGBHHCCCGBABDBCEEGHAFEFEDDBAFFFDFDCEAEAEGDBD,False +190,13.0,10.0,11.0,9.0,7.0,16.0,9.0,11.0,AGCHAGCBAHCBGBEBEACADADHDBFBDDAGEFCFCBHDEFEFHFHGHDFGFACAEFHAEAGGBGFCFCFHFDFCFCBBFDAHAH,False +191,14.0,3.0,6.0,9.0,14.0,7.0,4.0,6.0,EAEFDGEEFCCCFCFEAAAEADCDAEAEGGAFHHHHEAAADADEFEBDBAEGECEADFDHDHB,True +192,6.0,4.0,7.0,3.0,3.0,3.0,1.0,4.0,CFGEHCCFCBCEAEHCHDADADABBBACAFH,True +193,29.0,36.0,21.0,12.0,18.0,14.0,23.0,24.0,BBHFFFCEHEGEHDHBGBHBHDEBHBHBEAEBDBFHFHEHABADACGGGADBBHHFBBBAAAAABECDCACHCAGACFCFAEAFAFAGGDAEBDBHBEBGACBHFAFGFGBBCAGGBGHDCBBDGEHEGEACACACEBEBCACAEGDGHCBDGHGHBBABCCHCHCHGBAEAGBFBG,False +194,6.0,3.0,5.0,1.0,2.0,4.0,8.0,5.0,HBHGGFCFCACAEABGEACDCHBGGHGAGAFHFG,True +195,3.0,6.0,4.0,7.0,9.0,15.0,5.0,10.0,HAHEHFGFHHGHGFFCFCEDEFEDBGBDEDACBDFHEBFHFHFEFDFCFDFABEBGHFE,True +196,2.0,2.0,8.0,2.0,3.0,5.0,4.0,4.0,CCECHCDCDCEBHCGEHBHGAAFFFFGFGC,True +197,0.0,3.0,4.0,2.0,1.0,2.0,3.0,2.0,DBHBDFCCCGCGBGEFH,True +198,9.0,8.0,9.0,4.0,11.0,7.0,12.0,11.0,AAAFADHGGGFGCBCBCHEGEFEHDCABDHGEGEGDACBFHFBEBGBECEHAHAHGBECFCGEGAHEHCHF,False +199,9.0,8.0,10.0,11.0,7.0,10.0,5.0,6.0,ACADDFDHDABGCDEBEHAFFBECECDBBABAFAFAEAFHDDDHCCDCGCGHGDGHFCBCBFFEFE,False +200,15.0,9.0,5.0,13.0,12.0,23.0,15.0,22.0,CHGFEHBDGDHEHAHDFDFAEBDAHEFEFEGGGGAAAGEDAHGHGHECEGFGFGAGBFEFAFBFBGBDFAFHDHBHFHFHGDEDHFFCFEDBDHFFFAAHBHAHFCFDHHCHAA,False +201,8.0,4.0,6.0,6.0,2.0,3.0,2.0,2.0,AGCFBBCBCDAHABACEHDADADCDADAEFGFC,True +202,15.0,30.0,30.0,30.0,15.0,29.0,25.0,23.0,DFBBDGHBCEDBFBHBHBCBHEGGGEBEBHHEHCFFHFGBHEGBDFDFGBGDFDFHCEFHCGCFDHDFDEHADADEBCFEFDFEFECDAAHFGDDDCACACACACDBABGGEDAABBBGCACABFBGDCDAGGGGDCDFFFGFCBBBDBDHECGHGDGCGCHCHFBFHHHDHCEBFDFDFCFCGCBCBCFCDABHCG,False +203,14.0,19.0,19.0,3.0,12.0,14.0,16.0,22.0,CHAEADAHBHBHBHBGGDBHFHEAAABCBGEFCCHFEBHCHABABFHCCCHBHAGAFCFBFAAAHCFCGEGEHEHEHFHBHEGFGHBEGGGCCFGFGCDAECGCBBGBFBCHCHCGBFE,False +204,9.0,15.0,19.0,11.0,9.0,19.0,20.0,15.0,FAAACCHEGCGDGBHDCCCEBAHDGDFDBDBHCFGFCFCBCBFGFGHGBFBHHHFHEGBGBCAEBCCCFCFCHGAEFEAGCDHGHGFGFGCGBGBGFDACEBFDFDEHEDGHABFHF,False +205,20.0,16.0,16.0,34.0,30.0,20.0,29.0,29.0,CDCFGDGDEFHGHEHEGGBGBGBHBGEFECDCEBGDAHGCBDDGDHDHEBEDDDDHAFAFDEGCHEGFHFADBEEGAGDGDHFHBDEAEAHAHDDDECGBADEHEFEFDACAGEGFGBDEDECHHHEAEFFBADDDDAEAHHDHDCCFCAAAHCFCFEGHHHHGBGBDCHCHDFDGGEGBFBGHFAFEGEGEAE,False +206,20.0,18.0,16.0,14.0,21.0,4.0,6.0,11.0,ABABAFADEDBAECHGDDAAHEBBDBACECGAAAACHEFEBCDHGBCECECEBEFEAECBCEHEDGAHACADAHACECGDDEEECEHHHFECBCBEBHBDBDBDBAGDBA,True +207,1.0,3.0,2.0,6.0,1.0,4.0,1.0,1.0,FCADBDBGBFEFDFHCDDD,True +208,5.0,3.0,5.0,6.0,4.0,0.0,1.0,2.0,DCCBCDCDCAAAAHDHBGAEEDBDEE,True +209,9.0,6.0,7.0,6.0,5.0,8.0,3.0,2.0,FCFEAEGDADABCBCFGAGCFAFABABCBDHCFDFEFEACBDHEAD,False +210,21.0,21.0,15.0,16.0,11.0,15.0,20.0,12.0,CACFFACCCEHFDBGBGBFHFAGDGDADACGGDGBAACABBECECEGEDHDHCABDFDFDAGHGHGBGBFBGEGBFDFAGAEHFDAHEGABABFGAGEBCCGCHBDEDGBCACFBFAFHDBEBHBABADAH,False +211,10.0,24.0,13.0,13.0,14.0,11.0,16.0,23.0,EDEABACHGHAEGGBBBBECECEBBBAHGHGHCBCECDCBFBHBHFHFHFBBDAGFEBHAHDHGCFAGABCDDBEBEDHGHBCCACFDDBAHHHGBGBGEGEGHGFEFHHHDDBBCDEFGFHDH,False +212,19.0,7.0,17.0,13.0,17.0,11.0,21.0,24.0,FGCAHAHFGEHAAAAAHGDGHGFEEGDHHAEAEDCDFGBGDHDGFECECGGEEHGHGHCFBBHBFEEHGHGHDHFHDHDAAAHDECAAACBCECACAHFDFCCCCCCGGGGGEEEDHBHEFCGDHAHAB,False +213,10.0,20.0,7.0,7.0,13.0,11.0,10.0,5.0,HACBEBEBAGEEHEDAFABBFEEEBGBGBGBAAEBBDDFDFDFHCHDDAFECHBBAFAGGGFAFCGBEBEBEGGBFFCBCBCB,False +214,6.0,9.0,11.0,6.0,13.0,4.0,11.0,19.0,ECECBCFDGEGBHEDDHGEBHHGCGCBHHHHHEHEGACABADHFFGCGBGHDDCEEEEBEFHAECBCHGHGHBHAHAHC,True +215,3.0,0.0,0.0,3.0,3.0,2.0,6.0,5.0,HDFDHEHGGGGHAHAEGEAFDG,True +216,1.0,8.0,11.0,12.0,14.0,8.0,9.0,12.0,GEBDBDCCADDBGFGFEEGEGCDCEFEGEBEDCCFBHCEDDGEHEHDDFCHHHBHBHBCDFDEGEGCHCHEHFHF,False +217,10.0,10.0,22.0,13.0,14.0,8.0,15.0,10.0,DCHGECECEAGHEFGACFBGBECGCAEBEHHAGEGFDFDFHEDDCDBFBABACDDHDBDGCCCGHGACFCFDGCGCBCBGAGACECACBCECGDHEHEHECD,False +218,7.0,10.0,14.0,5.0,9.0,7.0,7.0,16.0,CFCECECDHHHHHHHHBBBHEFCCEBDBABAGDFDHCHGACCHCHEFEGHGDACFBGBCEEEFGHGFCBCHAAAB,False +219,15.0,20.0,16.0,12.0,13.0,12.0,14.0,14.0,AGAEAEAHGHFBFEHBHFGGEEHCFCDADACBDBFBCBFGFBBBCCAEGDGFAACAHBCBCDAFHFHECAFFEGEBCBGGCDCDCDEBBDBDBHHHHHDGAGDCHCAGEGABBEBE,False +220,0.0,1.0,1.0,0.0,3.0,3.0,1.0,3.0,HEHEHFFFGCBE,True +221,4.0,7.0,18.0,11.0,9.0,20.0,14.0,16.0,GGGBFCCCFBFDGCFCFDFHFHCDCDHHHGHFDCAGHCBAEEFEFEFHAEFCHCGEFCCCHCHEHCDCDAGBGBGCDDFDFGFHEHDHFGEGFHFGFBB,True +222,19.0,32.0,14.0,24.0,24.0,23.0,30.0,29.0,EAEAGFDFDCBHFAFADGBHBDAGCDEABDFGEEFFFEEAECHDHBHDGAHHGBGBGBGHCDFDBDBDEDADHFFAFEFGBHBGDCHEDABGBEBCDCHCBFAFBGBAHFHFGEDFHHHBBBBDBDBDBGEGBHEACCHEGEGEDEHECGHGFBHGHCBGAGHGHGEGEGEHAHAHFCCEFHFAGBGBGDADFBB,False +223,6.0,4.0,7.0,6.0,14.0,14.0,8.0,15.0,CEEFAGEBDFAHHDHFAFAHBFFHFCFEHHHHFDEGEGEDEDGAGHDFGBGBEFGFHHCHCHEHECFCACEEFE,True +224,11.0,10.0,13.0,13.0,21.0,14.0,25.0,19.0,CGBAEGEGEHHCGGHGCCBCAEBEGHCHDFDFDFEGBDFDFEFAGDGAGEGCGBHEEGCGBEEGEADACECABEDCDFFFDCAGAGHFHAHGEGEGEGBGBGHHHHHHDABCEDHHFFDHEHEGFF,False +225,6.0,19.0,5.0,11.0,12.0,6.0,9.0,5.0,GBHBDBABHBCBDEDBGBGBEBEBCCFDHDFEBBDDEAEAEAECFGFGEGABCFGBBDHDEFBGBGEEABHDD,True +226,11.0,18.0,23.0,14.0,12.0,26.0,20.0,26.0,EFEFEFGDCDFBHBHADECHHEHEFGFGHCBGACBGACFDFGFCFGFCCCHHHBHFHFHDADFFEBGFFFFFDBCCFCFHFCDGEHDFDBDCAGGHHHHHHBACGCGAGBGHAAAFFCHGBGCADGBBBCGDHEBEBEBEBHCHDHCCCG,False +227,23.0,20.0,28.0,18.0,25.0,23.0,23.0,21.0,FCCBCEFEDAGGBEHCHCHAFCCADFFHFEFAHCHDGCCHAEDEDFDGAGAGAGEFEBEBHHEFEFHFCGDFBGBDHAHBGAHFFFBFCDDADCDEEAGABHBHGHCHCABADABCHCHCDFGHGHBAFFEGECBGADCECGCGCBFEFDFCGCGDEECAGAEAGAGBBBBBCEEAEDECE,False +228,5.0,3.0,9.0,5.0,8.0,2.0,3.0,5.0,DDDACEHGFBCEAECCCCCFCEHEHEHEBCDAEBDHAGAG,True +229,15.0,19.0,18.0,23.0,23.0,15.0,10.0,23.0,HHFHGHEBFHHBCBDEEHCBGBAHAEDEDCGCGEBBDDDDEDBDHDFDEDACCEEDFCEEECBCBCBCDAFEHCFAHBEDACAGHHHHHHHAHGFACACAFBEBEFFFFFDEBEAEGCBEEDADACBHGCGBGDHDHDFDHDEABF,False +230,15.0,10.0,14.0,14.0,7.0,9.0,3.0,6.0,EDADBFADCDCDEBFBFAFEFEDCBADFBFBAHACCBCGEHEHBCCAGDCFFBAAABAGACHCHDDCCCEDHDADADA,True +231,21.0,19.0,19.0,16.0,21.0,13.0,13.0,23.0,EHBFBHBCDAEACABABEHCAAAAAEBDHDCECACAHGFCFBFBDCCBDBDECHCGCAAHHDDCDCDEEHHHADAFBFGFGDGFGHGAGEEFEHBBDBGHAHGHEBCCACACGEDEAABDBCEDEFEHBHEEEHGHFHEHFFGHB,False +232,10.0,11.0,13.0,7.0,8.0,12.0,12.0,9.0,EFGGGHCHBAEHFDFEADAHBBFBCGFGBCBCBCFHFAFAGCGCEBEDCCCHCHDGGGCGCADFEBEBDAFAFAHEFGBHDA,False +233,16.0,18.0,26.0,21.0,12.0,11.0,22.0,9.0,GBGCHBGDHEHDGAFCFCGCBBDDDHHGCEDEDCDBGBEBCCCCDBGBCACBGGEHEDGGAGACFCFCHCGGDGABDCCCGDBDEDEBBCHCDCDBDAGECECAFEFBFEAGAFAGBGAGDDDACAFAFAFCHBA,False +234,8.0,5.0,2.0,10.0,3.0,5.0,9.0,5.0,GAGBBEDFDFDBDGDAEADHGAGHBDGDFDFCGAGACABAGHHHFED,True +235,28.0,16.0,21.0,19.0,24.0,21.0,12.0,20.0,EDHFBEAFADABHFHFCFHFACCBBBHAHDHBADGDBCBDFEFDHHADACBHBEAEDDDGAGACAEHECFCECHHHEABFCFEEHGAFFFADADCDGEEEGEBECEBBCACAHAHADADFFAFAFHGDEEFEBCGCGCGCDCAHBGEEFGADECECAFAHA,False +236,13.0,6.0,14.0,8.0,9.0,13.0,7.0,14.0,FCFAFAFAHAHCDCDGFFEFECEDBCECDCFHEEFAFACHCHCEBGDHEHFHAHBHDHFCGGAGDHHACCBHDCGFGBAAEABA,False +237,4.0,7.0,4.0,12.0,6.0,4.0,7.0,10.0,DGGHBHDDDGDGCGCGADBHEDEDAGFCFEBDHDEBAHAFEHEHCHDBDBHFHB,False +238,25.0,27.0,17.0,20.0,11.0,20.0,27.0,24.0,BGGGHACECEFEAEDBDBHCGDGDHDHBHBHAHAHFBFGCGCAHFHABABEFFDDAAFHFHDAGADFDGBACCCHGHDAACHCHGBEBCCCBDAFAEGHAHGHGEDBDBCBHBGFEAGAGBGBABDHDGAGADFBFGFGCAEBGFFEHBBGDGBBBFFHFBFCDAGCGHDA,False +239,27.0,19.0,14.0,12.0,26.0,20.0,17.0,18.0,CACHFHBABHBABAHEGBDDEBFAFAEACABAFAHAHGHDFEGEFEBEBEAFCDCHABAGEGEDFBGBACAFDCDCAEHEHFHFEEEFABABCGEEEGHDHAHBHDFGEGBAAAFDHECEAGCGEBEDCDHFAFAGAGBGFFCGCEHGFEBEF,False +240,13.0,5.0,13.0,8.0,10.0,9.0,13.0,11.0,HCHAGAEFGBGAGFGCDCAGAECGCGEFEDHGFADADACHDFDGBCBCFEDEFEFBAHHHHHHAAFGCECACBCGEHEADCG,False +241,15.0,13.0,22.0,21.0,14.0,24.0,13.0,15.0,CECEBACABEFHFGBEFDCDBABGDAEADCDHGFGFDDDFDFDFGFEFGCGEAHGHGHCFCDABFEHHABCECBCHFHCACFBFBHBADFEFEFDFDHDHCHCDEDAGGECHAFDHCABFCFDFDGBGCFCACDCEA,False +242,10.0,3.0,9.0,4.0,10.0,22.0,6.0,6.0,CBAAFFFFGBDAFFFFFFFDGAGEHFGECEFEFHCHCEEEDCFAFAHAFBDEHGHCFEFCFCFEAAFAGC,True +243,16.0,18.0,13.0,25.0,8.0,14.0,16.0,17.0,CFHGHAFGFCFEDAGEBBFDGBGHDHAHBGBGBDCHHEBDBDBDCDHDHFAGGHGHABADDCDFBHAGDDDBCACECAGEGDDHDFDFHFHCGCGCDBAFAFDBDEFEACADADADBCFAHBHGEBB,False +244,14.0,10.0,26.0,18.0,17.0,28.0,19.0,21.0,HEHEHDFDFEGEGFGDCBBDAFHFHFDCEGBBDHFAGBHFHCECHCGAFCCDDADGHGCGAGBDCDHDHDACFCFGACEHEGDGFCFCFCAEFHHHFBFDFDCBCFEFCDGAGDEEFEFHFHFEECCCAAABECFHACECFAFGFCBCGHGHG,False +245,30.0,27.0,23.0,25.0,28.0,19.0,14.0,26.0,AAACACBCAEDEBEFCCHCAEGEDEFGAGCEAEADFEBBBEFAGBBBFDAEAEHHHHCFCHCHADFDEBHFACBFBGBFBCHHAHAEEGHHEAEGHGHGHGCAHADADAEAEAGDGBECHDDDDEFFDCDCACAFBFHCHEHEADFBFBGBDBCGABHBHDACCECDDBDBDFDBEEEEHCBAFHHDBBADF,False +246,9.0,17.0,16.0,9.0,17.0,6.0,11.0,16.0,HGEGACAHDHDCDEGFHBHDHECEDEDFDEEHCFCFHBEGGFABEHHHHGAABCCDBEBECHCHFBAHGCGABCBEBECCCCCEGEBBBBDBABEBHGEGA,False +247,10.0,6.0,15.0,20.0,23.0,16.0,16.0,6.0,AFDGEGEFEDCDFHEGEGFGBCACECEAEHEDDHEGEDEFGDDDCCCCGAGEDBABEFEFDGDHDGDCBHBGFFCFCEEEEFCHEFGDGFCDADCFCAEGFGBEFDADADAE,True +248,1.0,1.0,5.0,2.0,5.0,7.0,7.0,2.0,EFCFDAGFCFGFCHEHECEGGCGDGFGFBE,True +249,20.0,25.0,23.0,25.0,18.0,22.0,28.0,20.0,DGDBDAABACHGHEBDCCABFBAHGGBGEAAGDDFGFAHADADEDFHFHGGGFGFDHDEDBACDGDGBFACABBGBGEGEGECFFFEABDEDHFAFGBCBCACHHFHFBFBFHCHCHCECDGDCEHEGCGBBFBGEFEFHCGCBHGDGFHFEABCCEBDBHGDGDGBHCEDADCDCBAEAC,False +250,27.0,24.0,20.0,16.0,26.0,17.0,25.0,11.0,CHCBCACHBABAGHFEEBEGECEBEBEACDGDHHGAAFGEGABEGAGEGADADABAECFGBGAGAEBEADFGFECACGGFGEGDGFBFGCGBFBFEAEBEFAFAFEDEAAAAGBBBCDCDGECCCBCFADABHDEDEGEAHHBDEDFDFGCCCDBBHAHGBCBEHF,False +251,23.0,19.0,20.0,25.0,22.0,22.0,28.0,26.0,ACACGEBFHHCAGAGHGHGCGCGBEHFHFCAGFGCGHEHAHADDDDAEEEECCFBGHAHAHGBDECFADGCECEGEGDGAADBEAEFHFDGDGAEAFDECBGECCHDEEBGBABEHHAFFFFEFDADHBHBDDGGCGCBAGAHABDBDEFEBCBDHGHGFDFDFDFHBAFCBDBDFFGGCHHHDH,False +252,22.0,23.0,23.0,11.0,21.0,24.0,27.0,23.0,CGGAGEGECECECDBFFFHAHGEGCGAGACEDBBBFGFGHGHFCBGHFHBHGEAHAHABDHABABDBECHAHFCFEFAAGGGBGFCDCBEADADHFHDHCEABCGGGFGAHEEAECCCCGBBEHEHBHBHDCDFFAFBFCEBAGAGCCBCAGFDHHEHFFFCFEFBBEBFGEGA,False +253,21.0,15.0,11.0,10.0,10.0,18.0,15.0,19.0,CFCEEFHBGDEEFEFDAGAHAHGHFHFHGHAHAHGFFFGBDBGAAAABABGBFBFBEACGCEDHFACCFFFGECBAECDGGAFAHDHDHBCCGHAHAFAEDHDHGBBABDFCAGABHBH,False +254,16.0,7.0,14.0,11.0,13.0,17.0,11.0,13.0,CDFHFHECACEDEAECCHFHFHGHGCAHAGAGDEDFDCHCFDADFEGAAEAFFDEDCCEDBFCGCGEBEBHGAGFBABAGFHDHAHAEFFFFFBEBCGHACA,False +255,14.0,24.0,17.0,17.0,23.0,22.0,12.0,11.0,EDGFFFGBBBCACDDDBDCFCFCEEAFGFGFGFDBBBFBDCFEFADAHEDBDFHAAGHCHFGACABEDEDEAECEFEFDAABHHAHCECBFBCBFFDBDGHGHFBCDCECEDEAAGEGFBEBCBEEGEBEBEBHCEFBBH,False +256,15.0,18.0,13.0,27.0,17.0,28.0,20.0,24.0,FBDBCHCGDEDCGAGAGDDFBBBFFFFEDACGCHAGGGEGEBABFHFEDHFHFCBDGHGBGDHBCBGAEHFAFHHHDBDCHBFGFGFHFHEGEBDFFFHAHGHCHAHDHEBEFEDGDGAFABDBEHACFCFCEDADEFBDDEAEADFDFHFHFDGHEDDDDC,False +257,6.0,7.0,12.0,13.0,9.0,11.0,8.0,10.0,DDACHGHGHDHEFCCEGEGACCDCDCDADHBFEFEDEGCFBFDFBFEHCHDAGEDECBCBHFGFDFHAHCGABDBF,False +258,17.0,20.0,27.0,16.0,18.0,18.0,19.0,20.0,AGEHCDAGCGFGDCDCHCACDFEAGFGAAAADADCCHGHGHCCEEEGCADACAHECEGDGFBFBFCHCHCBBDBDBDEFCGCBBBEHFHACAGBCHFFBCBCGGGGHDBECEHEHGHBCAGEDEBFCEEBEBDFCFAFHBADDHFHFHFHECFBB,False +259,1.0,5.0,4.0,1.0,1.0,0.0,6.0,2.0,GGGGBGAHBHCGDBECCBCB,True +260,2.0,3.0,4.0,1.0,3.0,5.0,1.0,3.0,BFBCBFHEEGEHCACACHFFDF,True +261,2.0,4.0,3.0,2.0,3.0,2.0,6.0,2.0,CDCABEHHGFGFGEBABCBGDGEG,False +262,17.0,17.0,32.0,25.0,20.0,22.0,15.0,15.0,DHDCDCDGEHCBGBEBACGDFDCBCFCBCEAEAFCDEBAAEADHCEAEHECDDDBDCDBBFFEFGFBCBHAHFCCECGHDHFHAHACDEHECFCDEAAHABBCHGEGDGFHDDCDGDCCCGCACACFCFDADFGFBFBFEGEGEHDACGDFCFCFGBEBEFCF,False +263,7.0,4.0,7.0,4.0,5.0,5.0,7.0,12.0,GCACAHGHECGCHFGFEDHDHDHGHBAEAHBHFHGCCBCHEGEBHAFADAF,False +264,6.0,6.0,13.0,6.0,11.0,2.0,9.0,8.0,DCFBDBEEEEEEADAHGHGCGDHCHGEACBCGCAHEHGGAFAGCCCCCBEBHDCBCEGEHD,True +265,20.0,25.0,22.0,32.0,26.0,23.0,23.0,27.0,DCHBHBCEHHGHDCGCAHHGHDEEHEHBBECDCGBBACACADDDDDFCGEABGBABEBEBEACFHFBEGHFBABCGHGEGDDDEGAHAEFBFDGDHBFGFCDCDCDFGFHEBEHEHBDEAEACBDADHFBDDDDAFEFBGGGGHGHCHEHFCFGFGADDDDBDADHFEBEBECEADACBCFAFHFDFGFAEGHHCCFE,False +266,7.0,6.0,7.0,3.0,4.0,2.0,13.0,8.0,BGHCABHHCHGGBDBABAFCGEGDGAHCEEGEGBGCAHAHACGCGHGFGD,True +267,8.0,8.0,22.0,12.0,15.0,14.0,10.0,10.0,DCBAAGBEBEHECCCCFEDDDFGHGDEDCBCGEGEGEBFFAEHECFCHCHFHDCDCBHGGCCBCFCHHFAFGHGDFCEADCDCDCEBFAFACECAFEFE,False +268,20.0,11.0,17.0,15.0,11.0,11.0,19.0,11.0,FACAFGDHCEFHAECBCBEBEAEGBGBGFHCCBCAHDCFCDGDAEEEFBACADABACECHGGDBDGGGFHEHADAFGFGFGHGHGCFCDCDEGAAAABDDDGHBACACDGDHAGA,False +269,6.0,1.0,7.0,4.0,8.0,4.0,3.0,3.0,DBGECEAEAEAEAGDGFCHCECFAAHHFEFCCDEDC,True +270,18.0,16.0,20.0,26.0,19.0,21.0,22.0,23.0,BFBCDDGAGACDBDGDGDADHCAEACGCGDEBGDFDCDBDGHEHCFFFFFHFBFAFHDDGBHHHHFEFABGGDGDEFCDGHCHEFCFHBADHHCFCBGBFEEEEEFEDEDAFGHGDGCACDEAEACDEDHBHGHBHBHCDGAEACCEHGHAHACAGACBEBGFDF,False +271,0.0,3.0,1.0,4.0,2.0,4.0,2.0,3.0,HFHFEFDBEBHFDDBDGCG,True +272,16.0,16.0,17.0,14.0,11.0,14.0,8.0,16.0,FCHEHAFAFBFBDHGAFABBCDCDHBHEFABCHCHDAGABEBAHDHDFCEBGDFECECECEHECACDBDBDCGAGAGACAGBFBGDDACCDDBHEHBACFBFHHHFHFCFAE,False +273,13.0,11.0,14.0,14.0,11.0,17.0,18.0,16.0,CDFDGBHBFGFGFGEDABABCHHDDEDCHCGAGFBFDADHDCDCECAGEFEBEAFAEHEHGGEFBHCHFHFAFDFACGGFGHHDHGHAHCFAFGEBCBGBGCACDCDEHGFBAG,False +274,30.0,26.0,12.0,16.0,14.0,36.0,17.0,16.0,GGHCBABACFGFHFBBHAEAEACADADABABFFDABBFFEFBAGFHFBFCFBAHHHHGGDGFGBHBFEECEFDCHCHBHGEAHADDGAFAFDDBDGFGBEFFFFFGFACABGFFFAABAFACAGAGHDABABGDACFEAEADBBFBEDEAFFBFBFCFCDBHEHEDF,False +275,6.0,13.0,13.0,9.0,7.0,9.0,12.0,6.0,CEFBGCCCCHDBDBCAFDFDFGFHHCCGCGBGDGDBCBCBHFGAAEGBGBFBGBGECHCDAEGEFADAHEDEBBF,False +276,7.0,5.0,3.0,5.0,6.0,7.0,3.0,5.0,BCCDFEFEFEBADABCFDDHDHAAEAGFGFHFBAEAGHBHE,False +277,6.0,5.0,1.0,2.0,3.0,3.0,6.0,7.0,HBBFBFDHCGEGAHAHGHGFEBHBGGAEAHADA,True +278,4.0,8.0,15.0,16.0,12.0,11.0,10.0,10.0,DHCHAEEEHEHEFEHGFBHEDEGEGFCDCFCGCDCBFFFCEGDBHFDDADGGCGDEDEDGACDCFCFBGBHBDBCFCHCDDDHCAB,False +279,15.0,15.0,14.0,9.0,20.0,30.0,10.0,19.0,EAFFEFEFHBHBHBHCHCFAAACFCAHGBGBFEEBECEGEFDCEFEGCBFHFBEAFDBBGDDCGFDCBBHBHFEFEHCHFBFDGCHFHFHFGFGAAAAEECEFDBEFECEHDFCFHDHFFEAAAAAFGFHFH,False +280,20.0,27.0,17.0,23.0,26.0,20.0,26.0,25.0,AEDGCEBACABABGBGFDCEBHBCBCGHBAEACBHHHCDDEGFHAAFABCEHDBDBDFFGFCBGGGFGEEFEDEAEDEDHHHFHEEEGEGCBCBHBEBGBGECEAEHGHABBBFHEAFGBGDGFFEFDGDGDGHGDAFAGDHDECEHHHAHDDGHGCGEBEFABCBDBFCFCFHBADADFDAHH,False +281,10.0,6.0,6.0,8.0,8.0,11.0,10.0,7.0,GBFFDHAEAECDDBEGDGAEECGGGDHDAFADAEAHBHDEFFFFBCBCECAFABAHGFGFGFGHCH,False +282,21.0,33.0,19.0,20.0,21.0,12.0,19.0,26.0,CAADABABCEABHBABDCHEAEGHBBCCCCCHCBGGGGHHDHGHGDGDGDBDAAGCBHDFEEEEEEBEBAHHGHEHCCGHFBFBFBFGHBDBHAFAGACCHAHFBCCFDEDEHCHABDBEGADBBCBHEHEDDDDBDEDBBHAHBEEEDBBBBHGGGCEFBFAFBGAHAFA,False +283,12.0,9.0,6.0,10.0,12.0,16.0,15.0,10.0,CFCEDFGCGFHFBGCGFGABEGAGAGAGAFADBHGHDEFHHDGCADEGBBCHDAAAGEBEBABFDFEFEFHFHFHFHGBFEGEDDDEFEA,False +284,0.0,7.0,2.0,2.0,5.0,4.0,3.0,5.0,FBBHBHECBFDFGEHCHEHEBEBDGFGB,True +285,18.0,10.0,10.0,8.0,8.0,13.0,19.0,13.0,HHHFGFAHCCBCHCBFAGCGBABDBDGAFDCDAEAEHDADBHBAGFGFGHEFFGHGHBHAFFBFCFCAAABEEEAGGGAGCGFGAGADAGEHAHCDGEG,False +286,17.0,19.0,13.0,13.0,17.0,16.0,12.0,9.0,DBDADABCGDAFEFEFEDABCBEBGDGFEBEBEBEADBDGHCADABFDADADABGFGFCBCDCFBGGEEFCFAFEFBAGGEFHCGAFAHBHBFFEBACECACBCHAHEHEHCGBEH,False +287,11.0,13.0,8.0,14.0,5.0,10.0,1.0,11.0,ADDCHBHFDEACFDBDBABCBCDDDBAAADHFBFBABEHEHBHBCCHFDABAHCDDDCDAFHFEFEFHFHGAB,True +288,21.0,32.0,21.0,22.0,23.0,17.0,23.0,21.0,CFCBBDADEDEDBDHDADCCCEHEHBFBHADADBGBGDCBBHFAEBDHDFDFBEBHDEDBCECEGABCFGFHDHGHEHAAGHGEDEAEABGFCCBEBCFDFAEGGAGADECFFGFBBHCGEBEGAFABDBHFFAHAHAHBHBEBEBCBABDEGCGCHCHBHBGEGEGCAAGGBBFCCGDG,False +289,10.0,13.0,5.0,12.0,9.0,19.0,21.0,12.0,GBFAEDDDGGFEFDHHGHGFGFGDGFGHHHHEGDBHFGGHECBAGAEACFBBDBCADFGEGDBBBBCBHHFFBFBFDAAAEFGFAFAFDFDFHGGGGGECE,False +290,10.0,11.0,9.0,13.0,3.0,16.0,8.0,5.0,DBDBDCFFGFGABEBEDEFFGFGFAFABHCAFABCDHDADAHBGBDDDADFHCBCDCAAGHBFGFGFCCBFFCFD,False +291,22.0,19.0,25.0,28.0,18.0,24.0,23.0,17.0,FCFEFEFAGEGCGEAAAEGEHFHEGFGDGDEDBDEEECBBBEDFHFAGHCAGAFAHABFBFDDGECEBGFDFCFCDBEFABGEDACACDHDHDFFCDCACHCDBBGCDBHBHCFCDHHHBHBGFGFADDGDCDCHCDCACAGAGCDDABCEGHDHFGGDDEAFBFACACABGBGFD,False +292,22.0,21.0,17.0,19.0,16.0,16.0,15.0,29.0,EFHHAHDCDEBEHEHEHEHEHCFDBCBDHCAFEGGHDDBDFGFGHCFDDDDAFADCGCFDFBFBHGAFCCBBEEAAGAGDEDAHAHAHBHBHBHEHCABABHBCCCHCBBBDAHGFDEAEAFHGBGEHAFBGHAFAFAHABCDDECGCHHGHGAB,False +293,14.0,10.0,22.0,19.0,17.0,10.0,11.0,13.0,FDGGCACGCDCACBCDCDGHHDHBHFGGCCFBFBCBDFDAGEHAHEFECBHGDDDCEBBADCDFDADEEEEDEBHAHAGCGCBDGECEHEHAACADAHFHFEFCCECEDECCDAEA,False +294,21.0,23.0,11.0,16.0,19.0,13.0,19.0,13.0,ECDFDEAGAEAGHBFEFGHBBGBABABGDGCCAGHBHFEFGGCBDGDGDGHFHABAECEAGHFDFEFBFECECEFDHGFGABAEHEGEBBBBEBADFEHEHBDBDADADGBHADADHGAEBBBDCACECBCAAGA,False +295,16.0,21.0,15.0,23.0,14.0,18.0,17.0,12.0,DDBBHFDFGBGBHBFFFFFFFGEBCFCGHABBEHDDDDBBBBDGFHFAEDHDHCFCHCECBAHACDCDHAAADDECACAGABAGEFEBCAEACGDGFEFBGBDBCBGGDDAEFEDGCGEGEDEDGDBABADFHCHG,False +296,2.0,5.0,5.0,3.0,8.0,3.0,7.0,5.0,GHDHFBBGGCGBHEHBCACHCGCGEEEEFDADBEGEFE,False +297,8.0,7.0,6.0,6.0,3.0,4.0,7.0,7.0,GDGFBFEFAAEBDBDBAGAEHBDBHCHDGBGCGHGHAAACHCHAFCCD,False +298,10.0,8.0,9.0,8.0,12.0,10.0,12.0,8.0,AAAAAADGHGAEEEHFHEHEFFAGAFHCDCGEBCBCBFBFAFHFGGCGHEDGDFDBGEDEDCBEGEGHCBEBCCDGF,False +299,2.0,2.0,2.0,2.0,1.0,0.0,0.0,1.0,CHCEABDBDA,True +300,21.0,16.0,12.0,20.0,12.0,15.0,16.0,21.0,HFHGDDEFBFBFAGCFAGBGDHEHBHBHAEFBDGACHGHAHFFDFHFHEBBCBDBDBCFCDCACAEDEDHAHBHECABAGCEBHBGEDEGAAHAFAHADCDEGEGADFGAGAHCDAGADAHCHDDGDGDHFBF,False +301,18.0,17.0,21.0,18.0,14.0,17.0,20.0,23.0,BEBFFCAGAGAGHGHFHDHCFDFDEDEBEBEAGFBCCHCDCBCHHGHEACAEFGBGBEDEBCDADHFAADBHBHCHFDFDFHGBGBAEFGFAAEHEHEHCCGHDDDGHCCCCAABCGCGCADACABFEHDBCFHGHGDAHHDFGBGFG,False +302,17.0,9.0,16.0,15.0,18.0,20.0,16.0,20.0,CFEHGDGCGHFADAFGFBFHABACDEDEDGAEHEHCCCBCEFHGHAEAEAHAHEHEHCDFFAHDEAFDFGBGDHHFHFAGGFFBEHEAEAFFFDGBGCGEECAFFHEHEHDACBCFCDDDDCBCBHGAGCG,False +303,17.0,9.0,12.0,14.0,11.0,11.0,11.0,15.0,DFDFAGHHDEDEHEHECGFACAEADDHDEDCHCECFHBBBEGHBACGGGAGAHDHAAADEHEAFADGDBDFHFGBABABHBFCHAHACCFCGCEADFCFG,False +304,32.0,22.0,21.0,20.0,17.0,21.0,22.0,16.0,HABACGCBCGHGHADEGABAFHHGFCCGFFFHFHAHAGACFGEEAHAHABABFBAEAEDGDBDFFFFEGHGDDDCHFAFGECACECECEDFBEAAFBCGAGECECFCFCBGGADADGHACAEBHAHABGGDDADCDADBBBGHEFEDDDGEFBDBDBCBABCBAAAACFGB,False +305,22.0,14.0,10.0,9.0,20.0,15.0,19.0,12.0,GAGABHEFGHGABAEDECGAFABBEFEAECCAAHGHBEEEEEFHFGFGAEAGAGDGHGFAAAHAGAGFBECEFFBBGHGFCBCGCADEDBDBDBDFEECEBEDGAAEAFAHHBFCFCDHGH,False +306,7.0,13.0,6.0,7.0,4.0,5.0,5.0,12.0,BABAFAHDFDGBHHEHBDACHGHGDDBDHFFAFACEBEBEBHBCAHBHDHCGBHBCGCB,False +307,27.0,19.0,23.0,17.0,31.0,29.0,21.0,17.0,FADCDEGEBEGHDAEFEAEBHBCBAFAHAFGEGFBFCAHAHCCBDFHGCEFFCFEFEAEAFCBDADADHDFBFBEBADFCFEFBFBFDFCFGFEAHBBCCCCHHBHAAEGEBECEGDAEFDGECEFEHGAGEFEDGBABABHDHDCDCGHAEACAGFCECGGHEDCFAAAGAGCEHEGEGFGFE,False +308,16.0,23.0,23.0,25.0,22.0,21.0,28.0,27.0,BHGEFEDACAGADADGDGDBBFBCGGHGFCFCEHHDCDCEGFCFBEBEHDHCHCBEDDHBBEBGGFDECHCHCBFDFBGEHEGEDEGAHDBDAHGBGDGBCFCGCGBBAFAFABBBFGFHAHAEAGFFFGDDCABHECEDEBEHDGDEDEGCHCDCACHCAFGGGHFHFHGHGCAEHHHHDDBEF,False +309,11.0,10.0,14.0,4.0,9.0,15.0,8.0,17.0,CECHBGAHBHAHGCACBEFEFDCCCCCBCDCGAFFFFFBCBAFHFHFHDAEAHGHBHBHEHBHCGFBHAAGEFEFEGHAHDFFCAEHG,False +310,7.0,7.0,11.0,8.0,8.0,14.0,8.0,4.0,AFACGFEEDBGHDDADFCFCFCFDBGBHEHFAGDCACFCFEFBDBGBEBFCFCFCADGEGEAHCFGE,False +311,1.0,3.0,3.0,4.0,1.0,4.0,5.0,3.0,DHHBHDGDGCFAFGEBCBCGFGFD,False +312,9.0,6.0,12.0,3.0,7.0,3.0,4.0,5.0,AAEAECGCDFDHACECEAEBHBACCHCHEGCGCHCACBBAFAFCDGEBB,True +313,10.0,20.0,11.0,11.0,10.0,21.0,14.0,10.0,FHEBEBCAHAHBFGFGHGFAFCFDBDFDCHBECCCHEACABDGFBFEFAFAHGBFBDBDBFCCCEBFGGBGFAFABEEAEGBBFFDFBFBDBGBGCGDEDHFHDGGH,False +314,11.0,11.0,19.0,12.0,11.0,7.0,10.0,11.0,GBHBFGDABADADBDCDADHBGCECHCHCGCEAGCGCDCFEAGAEAEHECEFFBECDCGEHCBBBCGDHDBDADCFFEFCACAEBHHCHGHC,False +315,15.0,20.0,19.0,23.0,12.0,16.0,12.0,15.0,CCCCEFDBDHDCDFDCHFHFDEBACECHCGGFGAHDDDBACFFFDFBBABABDBACADAHCHDGCFFBHHDHDHGCCACEDBDECEHEBABHFDDDDGEFBFBGBEBFAGAGBGHEHDFEBABAEADBCGCG,False +316,6.0,8.0,6.0,3.0,8.0,2.0,0.0,9.0,CBCDFDHABAFEHBHBHECEBECHHBEEECEHAHCDAHABAB,True +317,5.0,12.0,12.0,7.0,8.0,8.0,7.0,11.0,CHGBGBFBFDABACAFFFCECHCEGDBBGHCCBGDGFGHEHDHCHBBCCECEBEAEAEHDCDHHBHBDFF,False +318,19.0,29.0,24.0,19.0,24.0,39.0,20.0,15.0,CFEFGHBHFHCEABFCCCFFEFEGBGBAHAHDBABCBGBGBGAGAGABHCCCFFFEHEDGBHEEDHDEDBHFDBCBGBFCFBEDFAFCFGACEFGFGAAFFFFDFEFECCGEGBDAAECECABEFDFCEAEAHFDBABDCHGBGBGBCACBCBEFGFGFCFHDDFAEHDFFEDDFDFBFBEBEBFHFCD,False +319,8.0,5.0,5.0,2.0,5.0,4.0,3.0,7.0,HAAEAHDHCBDEAHCGFGCEABAEAFAFHFHBHBCBCEG,False +320,4.0,0.0,2.0,0.0,3.0,0.0,0.0,1.0,CACAEAHAEE,True +321,19.0,25.0,20.0,14.0,21.0,25.0,19.0,10.0,ECEAHAGAGDCFHAHAHABEGAGBEBFFFFFGFDFDFGCDCBABEBGBFFFAGADFDGHGABAHAGCBABGDGEEACAEDBCBCEEFHGDDCBCEGEFEBEBFGCHBHBEDFHBCGEBCDCFCEBEFEBCBCBCBAGFFAFAFDCGEEFDCBF,False +322,4.0,3.0,7.0,8.0,3.0,3.0,6.0,6.0,AGDFDFDAGECEDDHCHGHCBFDEBCBCHCHCDDAHAGGG,True +323,20.0,23.0,10.0,13.0,14.0,23.0,24.0,21.0,AGAFFGHGEBBCDCEEEGBFAHAEGEGCGFGAAEBGHEBDGAGEBABEFCHAHADFBFDFBHBHBGBEBFBFHCACGCGBFBFAHAHFEFDBGGGBGFGBBEDHGHGHFHDHDGDHBFBFDFHFHFACADAGEFHCAADHBHCADFGA,False +324,6.0,10.0,13.0,15.0,5.0,10.0,12.0,7.0,ABBDDDDGDHDCBBHCHGDGBAEGEGHDBCFGFBEBADGCGCGHFFFFFCFCBDBDGDCAAAFDHCCCECDFDHCGEG,False +325,14.0,17.0,16.0,18.0,24.0,25.0,25.0,12.0,EAGDFBFEHEFGADABCCEGEAEGEGHGBFBDEAEDHDFEFDHCHGBGEECDCDCDCHCDEAEACCBEGAGEBFBFBFCCGFBEBCCDEDFDHHGAGAGEEFFFFFBGHGHBDECEBAFAFDFDGGGAHBEFGFGFHDGDEFGCABFBFGG,False +326,10.0,8.0,13.0,7.0,11.0,10.0,9.0,12.0,HGFCFAFCFAGADEDBHFCFCHHAHACEBECCCCEGEFEFGDBFBHBGBCEEABCECAADDEDHDHBGEGAHCHFHGAGH,False +327,13.0,9.0,7.0,7.0,11.0,9.0,9.0,4.0,EFEGEFABAFHDBFAFGGEBEFECCCEFFDADBDGEGAGABABABFBDDAEAHAHGHEAAGDECCCGCB,False +328,11.0,7.0,14.0,13.0,15.0,16.0,11.0,12.0,HHHHFDGEGFHFHGDGCCHFBFEDBAHGFCDCGGDDACACEDBGEDEHHGHEFEFCFGFAAACADHFAFCFCFCBDBAEEEEGDFBFAEAEDEDEBCCC,False +329,14.0,9.0,16.0,7.0,13.0,4.0,16.0,18.0,GCAEFCFCACAEDGGEGBGBGBHBHAHECAAAAHAHECECHGHADDCBCFCHHGAGEGDGEAECGBHDACECBHDCDGHCHGEBHBHEHCFGEGHHA,False +330,6.0,12.0,18.0,17.0,8.0,10.0,10.0,6.0,GGFCECDCDCAABEBEHEFDDADGDBDHGFBFBEDHDFBHGGCBCBCDCBCHDGCBCBEDCDGDBECADACCCFEFGFGFHDADFCC,False +331,11.0,25.0,21.0,16.0,17.0,27.0,21.0,23.0,FFFCHCBCGHHHGGCEBEDFCHAEFCFHDBDBABFBFEFBFHDHFBGCACHHFBFDFGFBHHDBEFAFAFHFEEEGEGEGEDBHCDCACHHGFGFHHBDBDBHCHGEDBDECECECFGBDBCEGGGGCCBCAAADAHBBBGBGFGHDAEFGFBBGHDCFCF,False +332,31.0,34.0,15.0,23.0,18.0,19.0,14.0,23.0,HBFBAAACBDEABCHDHAHDFEFHAAACDEBHBHBHBCBHBHBGCAFGBGBFFDFGAEAEBDFFADADACADDDHAHAEEBFDFGCCCFCAEGBCBAHCGEEEEEEBFDFEHBBBABAHADBDEDFGHHBHBDDABBHBHDHFCFCGEBAAAEGFDFDGDBBBAGAGABAGHBHCAD,False +333,20.0,17.0,9.0,14.0,13.0,13.0,13.0,14.0,ABGCECACBHDHGEEHEHBDAAAFDEDGDFAFABCCGHBABEBEGADADFDEHEHEGBGAHADDHHGHGCGFFABAFDBDHABEFDCDFFAFBEBHBAFAFABABGCECHGBG,False +334,7.0,5.0,2.0,4.0,6.0,6.0,4.0,9.0,GCGBFBHAHEBEAEDCGEAEHHFHAHABFGFHFHDEDADAFHB,False +335,17.0,13.0,10.0,10.0,9.0,12.0,9.0,20.0,AGHHAHAHCBABFGADADEFEFEDBBBBHHGHDHBCECEHFHFHBHAHDEAEAEBEHACAGADHCHBGGFFFHACBDFDAGHCDGDCFCACFHFBBHGAA,False +336,10.0,13.0,6.0,5.0,11.0,4.0,11.0,9.0,EGEBEBEGEBAHEFBCBEHGDFHFAFCBHBGDABHGGGBGCGBABADHDCEABABADAEEGAGCHCHEH,False +337,17.0,16.0,15.0,8.0,14.0,17.0,17.0,24.0,HBGBABHBHDFFAHAHAGAEAEAFACGCBCECFGDGCCEFEFHHHABGFCHDHGBCBHBDGDHEHGHCFCHGHDHFHFBFDABHBGBAFHEEGEGECBAGEHBHCHEFEADCBFGHCEFGCGFAAAAF,False +338,18.0,20.0,22.0,16.0,18.0,27.0,14.0,22.0,AEAEAEAFHDHAAEFBDHGFGFCAAAGADFFEFBADCHCHEGBBEBGFGFGEHEDCFHAEBHCDCBCGAECGCHCHBFBEBHHHGCBHFDDGHHHCHBDEDECBDFEFBFGFCFBFBCBFBFCDEAFDGABADADBFFFFECECADHHHCHCFCFCG,False +339,24.0,25.0,25.0,23.0,21.0,21.0,28.0,25.0,ABAFDFCFCGHGCDBDGEGEGCAAEBHBHGHGHDADCGCHFECEBDHDABHGCGHDHEEEBFBFBDDCDGEEEHBFFCFBFAFAFGCCCHGGFGCACHEDEHGDDBHEHDACAFHEABGCACABDBEBFDGHGHFHEAEAEADACGGBBBCGCGDGBGBFCHAHAHFBABFCEHBADGDEBACGCGFAFDHD,False +340,14.0,19.0,9.0,8.0,9.0,16.0,11.0,11.0,CAADABAEACBCBGAADHBFFFBDBDEGABHHHAEFHBCFHBEBGFDFBFBDBDBDAEGEGEFCGBFBAEGBGFGFHFHFGFCBCAAGAFEHHHCBC,False +341,2.0,6.0,2.0,4.0,1.0,4.0,1.0,1.0,ECBDBFAFDFDBGBHBCBAFD,True +342,10.0,9.0,6.0,7.0,9.0,12.0,7.0,13.0,AEAHAHFEGEGBGAEBBHFDBGBHHGHAFAFAFHFDDCDHECFCACFHFHCDCDHBEBFAFGFABEEEGBDHH,False +343,12.0,23.0,13.0,17.0,19.0,18.0,25.0,20.0,GCGCGCFABHCGAFCFDFBHBHEECDDBEHEAEABABAHHFFDFGEBEBGCABAGGEGEDEDHBCFDHDGBGDGHAEAGDHAEEECHHFBDGCFCDBDHFHBBBDHHCBEHFHGGGFGFBEBEFEFCFGFGHGDGDBHBGBABDGEG,False +344,8.0,19.0,17.0,14.0,18.0,17.0,16.0,26.0,BFBHCHCACDDFCHEHAFAFEEEDHGHBEEFADGGFGEEDEDEFEFBFBHHGHGHDEFCGCGHDHDBCHDBCFCGEBHBHEHFDEAEBEGCGBHBFBHBCBCBCBGACCHHHGHFDFCFHGDGHEHDCBAAFHBG,False +345,14.0,25.0,9.0,16.0,24.0,29.0,24.0,20.0,BDBDFDFEGEDADGGGGDFAABHGFGFEBHFECHCEDBABFBEDGGCFCEAAHGHFBBHHHHHHEBEBFAEEBEDGDCHEFBFBFBHEGEGEAEBGGCAFFGDGAGAGHFFFFFGCHAHBHDEDEFHBBBFDFHFBFBFBHDEFGBEDEGEGBAFFCACEG,False +346,20.0,21.0,26.0,20.0,28.0,15.0,21.0,20.0,EDEDFHFHEDCCECEHEHCGBBAEFDDHBGBEBGAEHECGCACECGCGCDEHCAFAECHBBDGDFCFBBHBEBEHDGDBDCAGACAHAHDHCEBEHEACDDDFFAGAFAFCGEACACGEEAHAGAGAGEFEFHFBGCHBDBHBCGDGCECHDHFBFDCGCBBEBDAEGEGE,False +347,9.0,10.0,7.0,7.0,9.0,11.0,7.0,1.0,DAFCBCBAFDEGEGEFAADGEGEAEAFGFBFEFCFGFCFHEDCBGBEBAFDDABCBABDBC,False +348,23.0,21.0,22.0,23.0,12.0,21.0,19.0,12.0,DBGBGFCCGCDHGFGFGFDCDEAEAFBFBHGHBCBABAFFFBBAFHFCDBFECCDCACAEADFDEDGCFCHBBBBDFDCGAHFGEADDGHFFDADEGEAEFEDECACACAFADCFCAGBBABEDGDHCGCACACHBDGGAGBGBHAHADDDHB,False +349,24.0,18.0,28.0,33.0,14.0,23.0,32.0,22.0,DBDACACDEGGCFCBGBHFGDGDEDHHADCFBFDFDAAFAGDGCFCECEGDGFBAGHDDCDCDGHCFFAFGDGDHDHFGGBGHDCDCAHFEDBFBFCDDEDGHAHADABHBEAAACADGBGAGAFHCCGFGCGDGAEAGDGHFHFEBAHCFCFGGGEGEGAGHBBBDCCHCHFHCHDFDBDCDEHECBCEAABC,False +350,8.0,4.0,6.0,7.0,7.0,4.0,16.0,7.0,EDGFGACAGBHBEBAGACAGEEEEEGGAGCGCDAFHGDCDHGHCHGBGAFDFDGGGDHH,False +351,14.0,22.0,13.0,15.0,4.0,11.0,14.0,13.0,ABCCHHFHCDBDBDBCCGCGFFDFBFGGBAHADDGDCDCBAHABEFHBBDBDBDBEBEBGDAEABDGFHBHGAGCBFHHHHHACGBGACFBBDGDBFAGAGACACF,False +352,23.0,10.0,18.0,19.0,18.0,25.0,14.0,15.0,GFADHDHFCGCBFFFHHEDFDHAEEFECAGBGEAHAHADAEGCBFBFEGEFHHEGGCFCHHAHAHEBAADAGBEBEDEDGFEFAFADADFGFAFCECECFFAFACACHCDFDADCDGGFDHCCCCDGDAFBFBEADBDAECF,False +353,28.0,26.0,15.0,29.0,24.0,17.0,31.0,29.0,EFGDADGCGBGBGBEAEHGHFDDEDEDEGHGEGEGHGHEHGDGBGFEAEGDCHCHDHFHEHAGDHDFEBEBEBEDCDCACAFGFCABFEGBGAGHHBDBABABHHAHAECEAGBGBHBFEDHCFCDGAFDHBEACFHHGDADHCFCBAAHFFGFDADBBEBHACABAHGDGBEAFABDBGGGGDDDAAHDDDHCHAABE,False +354,2.0,5.0,6.0,7.0,4.0,6.0,4.0,6.0,BHGHAECCCFADBDHDEDBFBHDCDCDFGCGFGFHHEFEB,False +355,6.0,5.0,6.0,6.0,6.0,7.0,2.0,4.0,HFHCGCGBFEAAAHAFBCBDEDEDEDCDFFABBCFCADFEHE,False +356,6.0,7.0,14.0,10.0,18.0,19.0,15.0,16.0,FBEHFGEHFDCDGGGEHCDCDFFFHBABDFDFHCCFEFECEHEFCAAGFGBCBFGFEBCACACDFFGHGBEHEHEHFHCCEGEGEGECAHEDEDGDGEHHHGHFF,False +357,14.0,24.0,11.0,19.0,13.0,13.0,20.0,12.0,CAHGEBBDBFBEGHAEDBDHDGDGECACACEFBDBFFGADBHBCCDCDHDEGEAFAFEGBFBABHFHAEDEDGHGBEBGBGBGFFBCGEGDAFAFAHAEBCGDDAGHHBCBDBDBFBDBDCGGGGH,False +358,14.0,23.0,16.0,16.0,14.0,16.0,6.0,16.0,HBCBHFHFHDBAGAEDCCCBFDFHFHDHDHGHABCFCFAGEGBBBFDADADBEBHFCFDFCBADDBCBCBCAEGEFCBABAFAHBFBEBEBCCEEHEDECBFAEHGADHDHEHBDEFBCDA,False +359,13.0,21.0,20.0,21.0,14.0,16.0,20.0,15.0,GFDBDCACAEBEBEBHBCBCECEGACHCHAHAGGBADADBDFCFHGDGDGEBHBDGGFGFGDBDAGABDGDGEHFDAEFFGFDHEBCCDCHCFCECHGDBCEHEFDFDABEBGDGHACFFBDCEAFGDBCGCBCFHBHBH,False +360,2.0,2.0,1.0,1.0,3.0,6.0,2.0,3.0,GFFFEFEBDBEHGCAHAHFF,True +361,14.0,17.0,14.0,17.0,23.0,22.0,11.0,18.0,DHACABDDDFEFBCAEAEAEFCFEFCFDFHFAFBCBCHGHFHEAEGBHBGCFCHAEBEFECECGFEDEFCCHAFAFAFADGHGBGDHDEDAHBHBHGEEBDHDBEEHGDEDEFBFBFHFGFBDAEBDGCHEEDCHB,False +362,7.0,7.0,14.0,4.0,6.0,6.0,6.0,3.0,CCBCGEGCAFAEADAGFGFCFCBCGHBBDBCGEAHAFCDCACBCHCEEFECBD,False +363,10.0,8.0,17.0,16.0,17.0,20.0,8.0,12.0,FEADABEGEHEBEBECFCDCHBHCAEEGHCFGFGFHHEFEFDFGFDECCACHFFFCDCGADAFGDCDCDCEFFFFAHAHBEECCDADAFFBEDEDEDHCFCDBHGHDB,False +364,8.0,4.0,4.0,12.0,13.0,9.0,10.0,11.0,FFHEHDFFAGEGEHEHFGDDDEDECEDABHFGFGDGAFADAEECGGABDBGHHCDCBGFDHDHAEAEHEHE,False +365,6.0,2.0,5.0,1.0,4.0,5.0,1.0,5.0,FEACAGFEFHCEABABAHFFEHAHCHCDC,True +366,11.0,5.0,9.0,15.0,4.0,9.0,12.0,5.0,CCFDEDFDFEFEHDBDCDHGGGGDFDAACADABFGCBCAGAFDFCGCGAHAGAHDBDHCGEBFDADADGG,True +367,22.0,11.0,14.0,10.0,20.0,19.0,35.0,19.0,DGGGBCECGDADABABHEHBHGAGHGFAFAGBGBGEEACACFEFGGGEFHCDEEBEBAHCEFFFFHAHAHGFECBHGGEGEHAHFGBDFHEEGCGFDAAAGEGAGFEFHFGAGAGDHAACAGHGCGAGDGBFHFGCGCECEHFHDGEGCD,False +368,2.0,3.0,4.0,0.0,3.0,2.0,2.0,2.0,BCECECHFHFAGEGBBCA,False +369,2.0,7.0,10.0,3.0,12.0,8.0,6.0,9.0,HHDHDCCEGEFFFHCBBHDEGEHEFEFEFEFBCBEBHBCCGCHEHBGGACECEFGAC,True +370,17.0,20.0,13.0,14.0,12.0,20.0,18.0,16.0,HEFEBECCHDECGCEBBGCDBDBDGFGFAFHGDDFDHBBBFAGDFAGACEFHGBFDFHFHFHCGBEDHFCFCFGAAEDECEFBFAHABACAGAGACAHABFBFGEGDBFBHBHDHDGBABAGCGEBAHGH,False +371,14.0,16.0,16.0,7.0,13.0,5.0,11.0,14.0,GBGBEHFHFBBBECAABDEABAGAEDEDBCEGECCACAGACACBCHCECEGABDBEBHBHFHCDAEADHCHCHFHCEABBCDHEGFGCHBGGHGHA,False +372,9.0,15.0,11.0,10.0,12.0,17.0,13.0,14.0,BEBEBGFFBFGFDFGCGCGFHDGGCFAFAFBFDHDEAEHEHAFBFEGHHEBGAGCHHHDDCECGCABFBFHFEDEDHBBCBGBCAGACAHBECEDDHBHFF,False +373,14.0,9.0,8.0,14.0,6.0,19.0,18.0,14.0,BHEFAHAHDDDDFBFDFGFEFHGBBFAAAGADHGBFCDGBEFGFCHHGFGHGHFHGEGAGEEAGDDABGGCCCBHBHCHDFAFAFAFGFDFDADADCGCGHF,False +374,13.0,6.0,13.0,5.0,8.0,10.0,12.0,6.0,CBGADAHAHAFAFGCGFGCDEAEADADCBHDFAACCCAFHBBCEGEGECFHAEBEHCGFGFGEGCGCFCGABF,False +375,8.0,5.0,6.0,3.0,11.0,9.0,8.0,4.0,EEEEHFFBFGGCGHGEBABEEFCFCBHGDBHFAFAFDFGAGDGAECECECAAAE,False +376,6.0,8.0,6.0,9.0,8.0,5.0,12.0,5.0,AEGEBACACHCGGHDBDBCEGEBEBHFDDGDCDBDBEGCAFBFGGGEHEAADFDFHGGG,False +377,2.0,3.0,2.0,5.0,6.0,4.0,2.0,2.0,EDEDECEBHBGFGAEADFHBDFEFDC,True +378,18.0,11.0,12.0,20.0,13.0,19.0,14.0,21.0,GAEHGHAADADADBFCECDCFCGDDFCGHAADFFFGHBHFDCDBFHFHGHFAGAGABADDHAEDECFFFAFAFDEDEBABFBGGHBCBAACBHHHFFEDEDADBEHFHGCGEEDHDCDGHGHEHEHCH,False +379,15.0,10.0,10.0,14.0,7.0,13.0,13.0,11.0,FHGHGHBBCDDDDABABGCEDADCHGAAHAFCFBDBDADFCFDDHCHFHAHCHCBCGGAACAHGGGGAGBEDFDFEAGDGFEBEFFAFAEBEF,False +380,20.0,20.0,27.0,28.0,18.0,28.0,19.0,15.0,FAEAEHHHHHHECBHFFFCFCDAGFGDEDCDCBGFFCGBGEGBAEAGFCADGGBEBEFHFDCBAEFDFDEDAHAHGEDAGBGFEBEGFDDDFDFAFCCCCCCBCBCGCGCACDDBFAFBCDADCDEDBCBCGHGFGBBAFDCDHBHDDBDCECACDFDGABFEDEAEFHHAAFFF,False +381,9.0,4.0,8.0,8.0,10.0,3.0,5.0,2.0,DEDECFCECEDAAACHEGDDFDFCACECGAABDGCHBEBGDGBAEAEAE,True +382,28.0,23.0,23.0,25.0,22.0,19.0,22.0,24.0,EBAHHEDEDBDHHGADFEFEHDHDGFFDFDADHDGEACBEHEFGDGAGAGEBCDCBBAFECHGGBHCHCGGGCGAFCHCHBBEBFBFHFCGCGEDEAAADABABADFEFDCDCECDCHCHCBAAAAAAHAFEGEADCCFHFEBEBFHDHFAAAGCBBBCDHDEDFBEGHCBDBGHGCGHDEAGABA,False +383,4.0,5.0,2.0,2.0,4.0,7.0,4.0,2.0,FAFBFGCGAGAGFBDEFEFHABFBDCHEBE,False +384,23.0,10.0,11.0,21.0,17.0,14.0,20.0,15.0,CBEFFDDBFAGHDAGAGAGDDBEGCCCDCBHHEAEFGFEEEHEACACAGAGBDAAHFHFAFADEHCACGDAEEFGGHEHBCDAGAEDEBFGHDHEHDHFHAGAGAGAFAFABBCDGGGDBDGDEDEDFDHD,False +385,16.0,15.0,15.0,12.0,17.0,20.0,20.0,23.0,FGBHBHAHAHBDFEFEBCAEEDEAHBHBHEFDCBAFCFAFAGHGHGACDHBCAEHGHBABFCFDGDFDFHFDBGFGHHACADACHCGBEBEHEACGEGFGFGDGEGEGECEADACBGFHHDFFHFHFGGBHCGCEEHC,False +386,22.0,28.0,19.0,25.0,19.0,24.0,12.0,27.0,BHDGBHDFDFDBABGDHAFAECECBCBCFCBEBHHHEEEBAFDFAFADECBDFDFAEHBHEHEGEADHHHFHFHDBFHAHADADFDFCAHBCGCDCBBBGBFAFCFHAGADDBFEFEAAHCDCECBDFFHFHBHBFEDCACAGEFDHGBEHGBCBHEEGAGHBDBDGHADADCBCB,False +387,16.0,23.0,23.0,12.0,27.0,6.0,20.0,14.0,EDEBGBEBCGGHCACBHBEGAGHGCGEGFCHBDCHGHBHGDADADBBCHCBEBACGEGEGEBABABDEEHECCCCBBBGAGAEAGFGHACCBBABAGFBEEEEEECGDDCDHEEEAEAECDCECGCFHFCBCEADDHEBFH,False +388,29.0,22.0,29.0,26.0,26.0,22.0,19.0,18.0,CECEGHFBFDDCDHGAFBGDFAAHACACAEEBEACFCAEECCGCGCFFFABGBGDCDGDEAEABHBHBFBHAHDCECECHFEFBACDDDEHAGABADFDFDBDBDECECEDHDAAAAEBEGAAADGFBFADACHEAACFGFGCGEHFHFCCCDGGBCEGFAFEBHCDAGBCBCDCEEGDBDBDHFHEBEHH,False +389,6.0,5.0,9.0,6.0,6.0,10.0,3.0,6.0,AFFFACCCEHHHHACDFDEGCBCDEDCFBFBDBFHFHADGCGCEFAFAEBE,False +390,5.0,5.0,8.0,6.0,3.0,4.0,2.0,9.0,CHCGBFDADACBFDFCHHDHDHCGCBFAEAEAECHCHBBDHH,False +391,17.0,18.0,29.0,20.0,13.0,16.0,17.0,22.0,GDCDGHHBEBFCFHGHAAAHBCDCDHFHEHBDDDDDCDCACHEBDBCBFDACBCBHACCDCGGGGCBCFCFBACADHHCFCADHHHGCBBGDGCGEEHEACAGGFGCABABDBEECECECFAFAGHHDHDFBFGFHECEFDFAHBHFGCACE,False +392,4.0,11.0,10.0,5.0,8.0,5.0,3.0,15.0,HHHHEEDDBGHGFABEBECCBHBCBEDECBCHCBEFEHDBDHAHBHFAGCHCHCBCAHFHF,True +393,5.0,6.0,6.0,2.0,4.0,4.0,5.0,6.0,HGFGHHHAGCGEFEBDFDAAHAFCBCBCECBGBEBHCA,False +394,21.0,28.0,17.0,22.0,17.0,15.0,15.0,14.0,DHAAAAFCDBDBDGGABBBCHCACGHFBBBBBBBAAAAFBBBBBEGEABCGFDHEHEDBAADEDEDEHCFEBEGDHFGGECDCHCHBDCEFEHDBDBDBDCECGCBFDGBADHGGFAFAFACEGEFDFBABFFEGDAACACHEHDHDCG,False +395,17.0,17.0,23.0,13.0,25.0,16.0,32.0,27.0,ACFCFGGGEEHEGGDEHBACACECEFEFHDEDFDGEGBGFHCCACEEFDACHGHGHBEEHBACCCCHCEFDAGAGEGCBHBHBGGGDGCFAHGHGHCAEFBBBHBGBHHEHEBGGEGEFHFHFHGHGCFCGHGDEDAAAGCBBBCHAEAHDHDFGGGEGBAHECDFDCAE,False +396,2.0,4.0,1.0,7.0,6.0,10.0,8.0,9.0,GCGFGFGHBFAEGFHFHGBDHEFEDHDEFEFDFEFBGHHAHGDBDHD,True +397,12.0,14.0,13.0,17.0,13.0,20.0,12.0,15.0,CEBHFCBGHGEGEACAHBHBDBGBADFDHDFDADHHEHFHBAAFACECECEDDGDGDCCCHCGBBDGFBECGDGACFFFFFFDHDHAEFEFBBGBFHFHECAFDBEHDFAFAEGFD,False +398,28.0,19.0,7.0,24.0,27.0,19.0,20.0,15.0,DHEAEADDHGAAHAGEHEBDBDHFCFEFEFEGAGHGBFHECAAGDCDADFCHDADADFDHGBGAEHDGFBFAFAFEFEFEHCAAAGGBBABDBCEADADFEGEFHADEGGGEGEGBGBDADEEBDBDHEEEDADEBBFHEEFCFEFAAAGABABDBHBG,False +399,0.0,3.0,1.0,3.0,3.0,3.0,0.0,4.0,DDHFBFEFDHBHCHEBE,True +400,14.0,15.0,8.0,10.0,12.0,16.0,15.0,13.0,BABABGHFHEHEAEBFGHDBCBGDCFFGAGDGFEFEFEFHDCAGAGHHAHACBCBGAGEGEDBDHDEBCACBHAHCFAFEBEDFFFBFGEGFABHGDADFBHG,False +401,11.0,5.0,16.0,15.0,7.0,18.0,6.0,17.0,EGDHHBGCGFFFFECHDAFAFBFDHGHAACFFFAEHBFDFHEHDFDFDABBEAFCCCCCCCFHAGADDDCCEHEHCHDHAHFHCCCFDHDHDADG,True +402,3.0,10.0,24.0,13.0,15.0,13.0,11.0,19.0,CBBEDHAHBDBDBGCECHHDHGHDCGCGEHCHCGCEEEEHFHFECEGBDDFBHEDBDADGFHCHCGCBCDCEAFGFGHGHCECFDECCCCCDHHEBFHFCFCEHFFCF,False +403,1.0,2.0,2.0,2.0,0.0,1.0,2.0,2.0,DGDABGBCHCHF,False +404,5.0,16.0,6.0,12.0,8.0,5.0,12.0,9.0,DGDHBCBCHGEEHEFGFBAGABADDCDBBBBBGAGEEDCDGHGHFHBHGGCEEDBDBDBCBDBGFAEBHFHGD,True +405,21.0,16.0,12.0,16.0,13.0,10.0,25.0,18.0,GFEFBFGGBGBGBHFHEBEBGBGFGFCEAGCDHAABHBEGCGHDHAHDCEGDGDBFGCAAAAEAGADFDGDAACACECEBFDHBAEACHGHAHDEDEFHHHBGEGACDBAGGBCBHHCDGAGDGHGHADAD,False +406,4.0,4.0,3.0,5.0,1.0,0.0,4.0,3.0,GBDDABCBCGDGDCHBHDHAGAEA,True +407,16.0,7.0,6.0,14.0,13.0,6.0,14.0,8.0,BFCAAAAAEFEBDFCFCADGDBDBDAGAHAEDEGHGHGFDBDGAEHEAEAGCEDHAEADGDAFADGGEGHGHDEBEHDGBGCCE,True +408,12.0,15.0,11.0,21.0,18.0,14.0,12.0,11.0,DBDBDBDBCBGGABCEFEFGGDBDAAAEHEFEBGBECCFCBGEEAEHCBFEFHFCEBFBHGADFDACABEBEAECDCGFDDDDDDHGEGFDHDHDHFCDDEDGAAFAFHHGHEE,False +409,20.0,21.0,28.0,22.0,20.0,26.0,20.0,22.0,FCFDFHADGDHDHBBCCHHDHDHDGAABAGCGCDCDFFFAEAFBHHGHCHEFEGBDCDAAHABBCFHFEEGEFFFCHCDBDEDEFEDAFAFABEHCCCEBHBDGDECCAAACDGFFEDHDFBHBAGAEAEFECGGGCHCDAHBGBDBCBEHGFCFCFCFCEGEGHFCBGFGCGCEABBB,False +410,3.0,1.0,3.0,3.0,0.0,0.0,1.0,2.0,DGACBHDHDCACA,True +411,10.0,24.0,18.0,15.0,16.0,10.0,24.0,18.0,HHFBFECHGHAHFGGDCBCBCEGHGBBAAGCCHCBDBGBDHHHBFBDBGGCGHGABABACEHEHCDGDECBAAEFGGDGEADDDHDHBEBEGEFEGEGCGDGDEDBCCCHCEBEDCGFGHGEGFBFBACHBBBBF,False +412,7.0,7.0,14.0,10.0,10.0,6.0,9.0,5.0,GEDFDFBAGCDABADDGAHEDEDFDCDCDFHCBCBCGCHBGCFCAEEEEEGEGCCCHHGCBEBCAGAF,False +413,1.0,1.0,2.0,0.0,2.0,2.0,3.0,2.0,FGCGCHEHEABGF,True +414,3.0,7.0,4.0,3.0,7.0,6.0,6.0,8.0,HCHGEEBABABFBEGFGAGBDFDEHEFCFBHHHFHCHCBEEGGD,False +415,17.0,22.0,23.0,22.0,24.0,17.0,20.0,16.0,BCBGBADDEHEBECCCCDGAGEGEAACEHEHGFABAEHECECFCGCECDBACAHADECGCBBFGFEHEFGDGEGCGFGDHDCBCAFGDGDAEFHFCFBEEHEBDDFHHHBAFAHDEDGDBDEDECFCFHFAGCFFAEGDGDADCBBBBCGHHABBBBBDED,False +416,23.0,23.0,29.0,23.0,28.0,15.0,36.0,18.0,HDFEEHAHFECBCGDFDFBAGABBGGADFDGEGECECGDHCECECEDEDACACGEGCGFBCBCACEEDEGGABHEDCHBGGGHGCGCBDBCCCEHEBGBCDDGGHGEFEGBBBDBAFAFAGBFFHHADEGEDBCCCACGCDCGEAHAEADGGGDGDBFBFCGCGBGBGACAHAHGEFDADEHEHAFGHBHDEAEA,False +417,6.0,3.0,6.0,6.0,13.0,9.0,7.0,12.0,HGCCECEAEHGHGCFAFHDDBDEGBGHHEEDAFGFHEHAAADBCHCGFEEEHEHEFEFDFHF,False +418,7.0,7.0,9.0,13.0,10.0,16.0,6.0,11.0,HEFFFEDECCHHBHFDFACACEDHDBDBDBDFCFDEDEBHGEFFAFADAFHGBGCGCFDEAHDFDHGHFHCGEFEFABC,False +419,6.0,2.0,4.0,3.0,3.0,0.0,2.0,0.0,EEBDBAAAACACEGGCCDAD,True +420,20.0,21.0,13.0,17.0,21.0,27.0,25.0,13.0,HAGAGAECCFDBEADDGAGFFDCBFFCABGBEBAGCGBFBGEGEFDCDEBFBEDCAHBHBDFDFBADGFFEGEGEFEFEFHFBBABAHHDGDGBGAGFGFGEEDEDAFAGDHEACACFFGFGFGEDECBFBFHHHGEAFAEAHFBEBGBCHCHGADC,False +421,9.0,14.0,14.0,8.0,6.0,14.0,12.0,12.0,FHFDFDBBBGBEBCBFDGDHFGABCGABBGEAFAHACACHDDFHCBBFHFHFGCHCHGBBHHGCGCACACHCEFEFADDFEFEGGCGCB,False +422,2.0,4.0,4.0,2.0,2.0,3.0,4.0,6.0,HFCFCECBGGGDGBEHFBAHAHBHDHC,False +423,19.0,10.0,8.0,8.0,6.0,9.0,8.0,8.0,DEABABCFEFDAAABFHFAFAFADACCGBABAGHBABABAGHEHCGDGDCDCGEHEGDAABAEHBAGACDFFCFHH,False +424,22.0,16.0,21.0,30.0,13.0,19.0,17.0,12.0,BCBEBDAEAEAHAHGHCBCAAEADGFGDGDCACFCDEGCDHBCADDDDDEABADADADAEGBGBHCGFAFDCDBDFACDBDBCFEHEHAHGFGFGFGECHFHCCGDGACDFDECFDADEBHFFDFDFBFBEHAGCGDFCBGDACBCFDAD,False +425,12.0,15.0,7.0,11.0,10.0,19.0,9.0,9.0,CADACAFHFDDCDBFBDBEBEDEHFABACFFHHGFDFDGDGHAHACCBEFDFGEGEADFFCEGBABAEHHBHBGBEBABGBEFFFFABGFFF,False +426,10.0,14.0,11.0,11.0,11.0,17.0,18.0,9.0,BFBAAEFEHCHGAFEBCFCGCGBGFHFCGGAFAFBFCFHBBFEFEFEBGCECBGBGCDFDBDBDGAGEFEGHGHAADEGCGHDBAEGDDDDCDFGFGABHH,False +427,37.0,20.0,35.0,16.0,24.0,26.0,23.0,17.0,AGAEEHGHGCCCGBGCHCHCHFGGAAAEAEAFHCHCGCACADEEECBABEFEHDFBFEEBBBCEFAFADACAFFCFDHDGBFFACDGDFDBBBCGCBAAAEAECGCDHFBDBCAAGACACAFAGGBEHECECEABFEGDFDHHAAAACHCHGHCHABEGCGFACCECFFBFBABAGFFDAECEDEFFACGCGAGCDFD,False +428,16.0,17.0,31.0,28.0,15.0,17.0,26.0,26.0,FGFCCACBEDEDBCGCGFDCAAECEAAFFGGGGHCHCAGDGDBHBHFHFHFHDHAGGDDADHDHBACGCGEDHBCDFDGDHDCCCBBBBGCCCCFBDDDBCCCHCFEHHGFBFCCAAGGDADGDHEHAGCGCBDBFBFEGAGEGHCFDHHHHEHEBEHDFDGDHAAECCCEDEDGH,False +429,8.0,4.0,6.0,7.0,12.0,5.0,7.0,6.0,AAHAGBFHFCEAEBECGFGFGEEECBCDCAEHEAEDEDHGHBCFDGEGDHDEDAA,False +430,5.0,7.0,8.0,4.0,4.0,3.0,11.0,4.0,HGDCHCBCBFGAGBGBEDHAEAEGFGCGEGAFCGCGDHDBBBCCGA,True +431,8.0,19.0,9.0,16.0,16.0,15.0,11.0,12.0,FABCEHHCGDGDFDFHFAEDGDFDFBBBBFEDEAGBEEEFEGEBEFDDGBBAAAFHFHEEDCDCGEDBDAEHEHBHBHBFGCDCHEDBFBGHGFBFBCBCGCBAHD,False +432,25.0,23.0,17.0,34.0,27.0,19.0,18.0,34.0,GBHHHFEGGFGFGHBABDBDBHGGEBBDEDHHHHAHFHEHFFFGBDDEAAAAADCDHACAFDBDCGCGDDDHAGBDHGHCHABAFEFEFEFDDBDBABGFAFEEDEDEAEBFDFDHAHABEBEDDDFHCEFEAAAECCBABHDADHCBFGDHEHAGBDHHEHEDEAECEDGCEEHDDGHCHCHEDDHBHCHCACBCG,False +433,11.0,10.0,8.0,8.0,5.0,5.0,7.0,5.0,GEEEBADHCHEBEACABDBDAHABABABCDCGCDABFDCACABGGAGHCHFFDDGFGFB,False +434,8.0,2.0,9.0,3.0,9.0,11.0,9.0,7.0,CECFFFHGHBHCFCFBFHDACEEFCGEDEDAAAGCGCEFFAAGGGHFHFHEGEGECAA,False +435,15.0,9.0,12.0,17.0,12.0,13.0,11.0,8.0,FEFHFAFEDEDBCGGFBHACGCFCHADADAFAEAEADHDBDFHEDEDBBGBDADAGAGEGECCHEAACBCDCEGFGFDADGHHFDFCCCBDGEFADB,False +436,9.0,4.0,4.0,2.0,2.0,7.0,7.0,7.0,HEFBABCEFAFABGGAAACFCFGHBHACGFGAGAGHHDHDHF,True +437,13.0,14.0,15.0,27.0,27.0,6.0,29.0,26.0,DDDEHABAHEHAHDCBGDHFCEGBBHBHADDEAGGEGDGDGCCDCDBDBHBHBAAHGGGGACECEGGGECCDGDGEGADADGFHEEDEGACAGHDDDFDFBEHCHGHFHEEEHEHEHEHEGEFDGDGHBCCEDHBCGDHEEBAGHGEGEGEDHBHCD,True +438,22.0,9.0,13.0,21.0,26.0,17.0,18.0,21.0,GAGEHFHCEGEDAFAHAHEDBDFDABAHEDGDBCAEGDDDGGGGAGEHHHGCCFHHBHBHBHAGECAGDGDGDGEHDFAGCEEFEHEAEAEFFCECFFFBDADFDADADAFEEEEAFAEEBABAHEFDGHEHFCDCDCECHCHFEAH,False +439,24.0,19.0,22.0,19.0,24.0,22.0,19.0,24.0,DCDCAAAAABAFGFDFDHGCGCGBDACCCCEHFACHEDAAEABAHABAEFHFCFCFBBHFHEHEGCGDHFECBBBGBEHEAEAHDGDGHCHFBFEFEBEDFAACDHDFBHADCCEHEHDBFGFHDHDGEGADADEDEBECHFGGAGEFCCBCGFBBAGEHFHGHEHEFECBGA,False +440,23.0,14.0,11.0,16.0,9.0,11.0,13.0,16.0,DCDGBGBAAHECEFGFGAGHHEDGBCFDFGHGEEFADAEGFBAAAABFBFDAACCCEDHHHDDAAEBHCHABCHAHAHABEDGFGBGDDDDDDGAAHACACACABFFHBHBHB,False +441,5.0,9.0,7.0,7.0,5.0,6.0,6.0,2.0,CFDBDGCADBDBDGAAEAEBFBCBFGHBEGDHDECECBCGFGFBFAC,False +442,21.0,17.0,17.0,31.0,26.0,21.0,12.0,20.0,AAAGDEAFCHCBEDDBDBDHCAAHBDBDADHFHFHFHFHFDFEADADHHCHDDCFBFACHDEEEDABADAFEFHCACFFFEFBBEHGDGEGFDDCDGEGECCCCCFCHDEEECGCFDEDGBBDBGGHBFAFEDADFDHEHDHAGDGDBAEEEBEDAHAEBEBEAE,False +443,22.0,20.0,27.0,22.0,26.0,31.0,22.0,17.0,EDEAHFDFEBGFEFHGAFAFEDEAHDFBEDACCCBCBAFADAHFCGHGHDCDCGGHBBGACADFEFEFBFBFBHBHAHAGGGEGAGACECECBAEFFDEECDFECECBCEHDFCABHBCGDHBFBFBFAEDCFFHFCFGFDEDEDGFGFGFBCHEGGCEDGCCHDGFGCCCACEDEAEABABADFDH,False +444,25.0,15.0,17.0,18.0,21.0,13.0,21.0,25.0,GCAFBBBBAFGHBACAFHCECHBEDEHHHEDAHABCGDEAAABDBHAHBEGGDGACDBGGGGHGHGCECEFHFCCGBEEEEEDFCGDGDADADCECBFFCAEAEADGDHAHAHEHDHAHEFEHDGFHFHBDDAHAGAGAGAGEFBHECFCACHDH,False +445,4.0,5.0,1.0,1.0,6.0,3.0,0.0,1.0,FEBBABEBEAFHFEAEAEBDC,True +446,3.0,5.0,3.0,4.0,0.0,2.0,5.0,1.0,DBDAGBGCGCGCBBBAGFDHDFA,True +447,27.0,17.0,19.0,29.0,21.0,26.0,19.0,16.0,AAEEEEFDFHEADAGFGFGAGHFABBBBDADAHFDGCHFDFAFGCCBFFHDHDADEBHGCAHAFCCGCHEEADCBFFDFAFACAEECDCDBHBDCCEDEAGABDBDGGGGHFHFHDEAFDCDAAABAGCGFDFEEEBGAGAHBGDGDFDFDHHACCDCEBEAECEFEFDFDBDB,False +448,12.0,3.0,7.0,7.0,6.0,6.0,10.0,15.0,GCACACAFHFHGHDHAHDDEDCFAHACAHGEFHBHBFGDEHEAAAGAGCDAEGEBHDGFGHHCHGH,False +449,27.0,20.0,31.0,20.0,16.0,31.0,25.0,16.0,CCFCACAHBDGCGCBCGCDCBBEBAGFFFCFCDCBHBEFDFDHGGDCFEDBDFDCDCFFDBAECHADBCHCHCAAAAFAFADDGFCECGCGDDEHGHFFEHGHGFGFGAEFBFEFDBHAFDGGCFAFHHHBHEAGAEAEABGHFAFACACBCACGBBAGACAFFGFGFDBCBCGEEEECFADGBGA,False +450,2.0,7.0,4.0,2.0,6.0,1.0,3.0,3.0,DGCGCBDBHCECHBEGEABFBHEAEBEB,True +451,8.0,7.0,6.0,1.0,2.0,4.0,4.0,3.0,FGFHEABCCCDBABAHCHEAGCGCBAAAABBBFGF,True +452,12.0,16.0,17.0,11.0,29.0,15.0,19.0,16.0,EGDGEGHCFCFDDBECFHFHGEBEBEBEBDBAHAHADCEEEEEEEBECCBBBGDCDCFGHHEACAGBGHFEGEAECFDEGFHCEDFDFDCBHEAEAEFBGCGBAHFHGGEEBFGFGEHAGAGAFCBHHHCCECEG,False +453,4.0,3.0,6.0,2.0,6.0,8.0,4.0,3.0,CCFCEEHCHBDEFAFAFHGDFEGEFBFBFCECGAGA,False +454,17.0,13.0,25.0,22.0,19.0,16.0,28.0,27.0,AGAHHCDEDGGGDHHFEEGEHHCGGHGABCDCDAAFCFCGAGCFFFHEEEHEBGBCFHDAEEBDCDCGCGCBHBFCFHDHGBGDHCHFHBHDHBEAFCCDEDAGCGCDCFFHGHGHGAGADACAEABFCECECEBEHAGAHHDGDGHGHGFDFDEBCHDDCDGBGEA,False +455,3.0,8.0,5.0,6.0,3.0,3.0,1.0,4.0,ADHHHDFFACBCBCHCBDDGDBDBEBEAEFCBB,True +456,17.0,25.0,25.0,21.0,21.0,26.0,24.0,21.0,GEGBFBFBFBGAHAFACDEDCCHFFGBGAACFCHGFCFGHDAEFEFGFGHEBEBDAFGFAFCCBABEHCGFEDEDGBGBFBEHEGGCDCDCBGHDCCCDFAGBHBDEDHCHCHEHCBCDDDDFBEEEEGGBFCFCHAHACGFBBHDHBABGBGDGDFAFAECECEFDFDBGCHBAAHHEH,False +457,12.0,10.0,8.0,8.0,4.0,11.0,8.0,8.0,DBDFDFCCCHBEGFBHEFACBDBGHGBFAFGHAHAHGDDDCCACGCEHGFGFBFBABABDHFAAAEAFA,False +458,20.0,11.0,18.0,22.0,26.0,28.0,20.0,28.0,BFGHCHEAEAFFFFGABCFGFECECECECHCHGHDHAHEEEFHAAFBCGHDHDHCABGHCFDGHGACFDDDBCGDDFGGGGEEABGFAFEHAFEHAFAEAEABAGFDFEEHEFECDADHDHBHEHDHCHFHDHFHGDDDDEDEFEFGDCHCECEFHFAGBFFEFCADGBGBHA,False +459,18.0,25.0,19.0,16.0,13.0,17.0,21.0,14.0,CACACDEDBCBHAAGHBHBCEDEDAGGHDFDEDCHFHECFBFACAHAGGGGGAGDFBABFFGFBHBHBGBHBACABHBGCGBGEFADCDCHAHDHDBACABBBGEGEFCFBGBEFDFABABFCEGECDCBCGDBEGFFCFDGE,False +460,21.0,19.0,19.0,30.0,29.0,19.0,23.0,32.0,FDEDECCDEEHFDFEFEFHAHDCGCGCFDDDCGAGAECDHBEBAHGCGEFEDHDHDGDBHBADCDCHHFECHBGBEHADBDHGHGHGHDHFBGAGHBFBAECGGFEFEFDGDCDAEGEBACHGGDDADFHAEABBGBABDFDFABEDAHBHAHAEDEAEHEHCFCHEHEHBHBHGGCACAHEEEEFDFCGDH,False +461,9.0,19.0,19.0,25.0,19.0,17.0,20.0,16.0,BEGCGDAEHEDBDCEHECACAEAEAFCEGHGHFHGHCEDDDHDEGGFEHEFDFGFDBDBDGDEDCFCFHECBDHACCBCBFGDGCHBHDDBGBGFCBCDDGDACFGGGGFGBEBEGHDBDFCFBFDFDBHHAHAEDFBCBEBEC,False +462,9.0,14.0,11.0,15.0,9.0,10.0,15.0,17.0,CHCHCGCBEBDHEHFBGDGDGDGDBDGEGCHHBDBDACFCHGFEAHFFDCGAGBFHEDEHHAHAEBHBHGAGBFBDBCFCBCBADAGEGHHEFDFDGDAH,False +463,15.0,16.0,16.0,16.0,13.0,12.0,15.0,14.0,EDEGEDHBHDHDACHCBCAHADGDGAEEHFGFGFAEGEDECGGAFAFDBCHCGCEBABABABDEACHCBABAFGEACFDBBCBEGEGCDCDADBDFHHHHHBDCDGBFFGFHCBCFG,False +464,20.0,13.0,10.0,7.0,14.0,12.0,14.0,15.0,HHHBDFFCHCGCGAGDFDGEBFBABAFAFHGHBAGEGEHBACFCEDBACCCABADAGBGAGEEAAFAFACGCFAHEHEDEBAGEHEHEGAGAEFHHHHABEBDBF,False +465,32.0,28.0,23.0,18.0,15.0,22.0,28.0,21.0,CAHHBFBGCACEGFGAAABABAGGCGCGEAAGCGEEDBDGDCDHDBBABAFABAEDBGCEDBDBAHABFHEDEDBFFGAGHHEGAGHEECDCFBHCGBDBDBFGFDFCFAAACACFGHGAGDCFGAGFFBHCHCEABHBFBFHFAFHFEFBABGBGBGHHHAHAGEFCCHBHCAGBCDCECADADAG,False +466,14.0,31.0,26.0,20.0,17.0,27.0,15.0,13.0,BBBBBCGFEFDFDFCCDCHHDAFADACCEAGGCGCACFFEGECEFECCACGEBAGDGHBABDBHBHFCBHFCFCAHDCDHBGFEEDEDFAFHHGBBFAFCCCFAFDFEBBABACHHBDBDBFBCCFFFFFFDBBBBBEBECEGEGDGDGEGCHEBCDFBBBDD,False +467,15.0,12.0,15.0,11.0,17.0,18.0,18.0,13.0,HAGECCBCFHEGGGGBGBDBGBAFACCFCFCBDFAAAAACEEEFECDFDCDCDHBGGGFGDABAGAFFEAEFHBEDEDEFBAHGCGCHFGFGFHHDHECEAEGFAFHHEHEBBGEHFDC,False +468,22.0,12.0,14.0,17.0,19.0,18.0,16.0,15.0,DADADADAHAGABAEHFGFGEGBHBGADHDGGACHEHCHGEFFBCGCAFGDGAEHEAAFCFGAHAHEDDFDCHFEFEDEBECABEFGBGAGCCECFCBBBBHAEBECCADEDHHHEDEDEDFFFFGDAAAFCF,False +469,18.0,26.0,29.0,20.0,29.0,19.0,16.0,15.0,CGCGCHCFCGHHCHCHCHCFAEAFFECEBFGDHDCECECHCFFDBDEDBGGEGAGEHBBCCACABEEEAEBEBACECGADBBHBDBEFEFEFCDDGCCBAHHFCBHBADAGFDBEFEFEAECBFFHABDBAEDECECEDBFBDBDBDACGEGEBADCDGBGDGACFEFBAEH,False +470,6.0,1.0,5.0,5.0,3.0,4.0,4.0,6.0,CBCAGGHDHDHDHFHFEECACADHCAFAFGEADG,False +471,8.0,12.0,3.0,4.0,7.0,8.0,8.0,2.0,GAAFBEGEFDAGEGEFEHGBCFFFFGBBBEBABABDBDBEBDHGCABACAGF,True +472,9.0,4.0,9.0,5.0,3.0,6.0,1.0,7.0,HACGCABHCEAFHBHDAAACFCBEDEDADAHFHFCFAFBCDCHC,True +473,2.0,1.0,5.0,2.0,7.0,3.0,2.0,10.0,CCHCDDGFHAEBEHHFACHHFHEHEHEHECEG,True +474,8.0,7.0,5.0,9.0,9.0,4.0,1.0,12.0,BCDHBCBADCDHHAHDHAHEDEDBHEEDHCHAFAHAHCEGDADEFEFEFABHBEB,True +475,11.0,5.0,2.0,1.0,3.0,2.0,5.0,4.0,AACDCFHAGAGAEBGBHBFEAGBGAAAHAHABE,True +476,25.0,30.0,25.0,21.0,26.0,22.0,25.0,24.0,HGHEDBDBCHEHEDEDEDEDCAHDCGCFDFGEGDGAGAGHGDGDCAAHABAFACBCBCEDEAEDEAGDFEBEBEHGHFHFCBBFGHGFEFBBBFHGBCFCEBABADHBCACGFHFACACDFABHEAEHHDGACHFBFBHBHBABGGDBABGFEFBHGHAHEBGBGCFBEBECGCACEFAGECACFDFEAECCBGHCDD,False +477,15.0,14.0,22.0,19.0,17.0,22.0,25.0,22.0,DFGGGFHHCHEHBGDEEBFBAAHGFGFGACCCGHFHBHCDEEFEFBFAFBFCGCEDEHEHEBFAFAFAFGCGCGDBCBFFCHCDDDEAEAGDEDECGDGABBHDHDFDFDGCGAHEHFHCHAACDDBHHACBGBGAGFFHCCGHHCCGDGDGCGEE,False +478,14.0,12.0,9.0,13.0,13.0,17.0,7.0,13.0,AFAFBFBDAAADFFBFBEHGFEFHAHFGDDFDHAHADABFBFHEHECCACGFBDBGAEHCDCHGHGEAECECEFECADFDBGBHBHEHDDFEFDBEAC,False +479,29.0,20.0,16.0,24.0,27.0,18.0,17.0,26.0,GEHHHAHEGBGCHCBCFGDGBFDHCCBCHFHAEFEGGDHDACEDDDCDFDFDHBAADHFHBEFEHCHCDFAFABAEGBHBABABAEHEAEAEDEAFHEDAGEBEFGCEDEFEDHBFFDFAHHDBDGDHEAEGCBDEDBAGAGAGAEAHACACAEAEBHAHGFGEBEADADBHBHFCC,False +480,11.0,14.0,7.0,9.0,18.0,15.0,6.0,9.0,FAFEGDGBBEFEDEFEFABAGEGEFFFBBCBEDABEGAAAFHFDEHHFBFDFAFCDCDEGHHCHBABCBEHEHEBEBEDEHABEFACDC,False +481,8.0,4.0,7.0,16.0,11.0,8.0,9.0,4.0,EEADADFDEAFBFGEGFGDGCHDDCDEBEGEGCFCHDAGCGDGAECFCEDDFDEABABADDDDEHFH,False +482,11.0,7.0,25.0,5.0,16.0,24.0,10.0,11.0,EAEAEACFCBCEFEGAGAGCCFFEFGBCFFHFCFAHACFCEEHCCFDFEEHBHFHAGFFEFEBDAGCGFAFEFEHECGCGCFCFHFHCCCBCDDBCCCCFDFHAECBHG,True +483,24.0,31.0,31.0,29.0,20.0,23.0,19.0,21.0,HAHEECBBBBGBECEFBFHHCHFHDBGBHEGEADAEAEBBFBCECFCACABHCHCEBFDFCFCFBFHHHEGCDCDCDHDCECGABADDDBAGAGAHEDEBBDGCBCFAFABAHCBCFHGHBDEDGBGEHCDCFCFCAHFBCDCDGDHABGFEBDBDBDGAFAGAFDDCEFABAFDDGAFEFDGCBABHCGDGDCDCAE,False +484,10.0,14.0,9.0,7.0,6.0,9.0,6.0,9.0,HCACBFBFCFCFHAHADACABDCHGHGCBFDHCBGBABFBDBFBEEHADADHBBEBADAGECEFHBGEGF,False +485,10.0,4.0,11.0,5.0,13.0,7.0,15.0,10.0,AEAEHCHCGCGCBEGEGFGBGAGFGEHAFGCHDECCAHADDFDFHFHEGEGACCBHDHAEGEGCGHBEEEGAFAC,False +486,10.0,4.0,4.0,3.0,10.0,7.0,9.0,8.0,HGHCFDHAFAECEFHFHEGECHDDACABAEEEGGAEAGAGAGAHFGFEHEFGBBB,True +487,5.0,6.0,9.0,7.0,10.0,8.0,5.0,12.0,FCFCFHFAFAFGEDCBEHHGGEHEHAGBHCHFEAEDEDBHADCBCDHDHDFBEBCCHCGEHE,False +488,11.0,11.0,11.0,8.0,15.0,8.0,13.0,12.0,CBABEBFHFGEGHCDCAGDGEABBCGGBBHEFBBABGBADEHCHCEAEAEGEFFFCGCEHDHDHECDCAFAGAGAGEHEGFDHCHEHED,False +489,22.0,25.0,26.0,26.0,18.0,25.0,28.0,23.0,BEBEBEBFFHDHDHCHDHCCGCFAGCHCHCDCGCABABAFCHEHBCBCDCGCEHAHAEGGABFDHEBECGCHCHFDADAHHEGFBHAHFDGDCCCHFFGGGGBFAFABGFEFAGGFGDBAHFEGEGEDBBEDDBHBDFDFGGCEFGFBFHGADADHCEGEGDGDFDBBCBCDGBADABAFCFAFADDDBCGAE,False +490,19.0,24.0,22.0,16.0,30.0,19.0,23.0,31.0,FGGAFEFECGHHEGEHEDEFEHAGFBFBFHAEAHAEAEACDEBBHCECACEGBBFBDBCHDHGCFEHHAHAHBEBECGGDGCHBHGFGBDFCGHGHDHBHBACACHBEAABDHEHDHFFBFHFHEBCDEDEDFDGEGAGADBCHFHABDBDCFAEAEBEBECGCGEHHCCBCHCEGEGHFCGEG,False +491,16.0,23.0,19.0,29.0,31.0,20.0,28.0,25.0,DHDBCECECAGFGBBEEEECEDEGHCDGGAFDFGFGCGCEHGHGEDFGCDFGFDDDCDEFEABDEDEBEBHBHBGGHBDBHAFABDGHCECGAEAEAGABHDHDHDHBBBGEHEFEDHBEEEGGCDEFGHGHAHAFCFGFEDCFEABHFHEBEBDHDHACBCFGAGFGHEHBGBCHFGDDADCDADFDECB,False +492,2.0,8.0,8.0,4.0,4.0,4.0,9.0,3.0,GEGFACBGAGECCHCHCBFDGHCCGCGBDBDBEBEFDFBGBG,True +493,21.0,13.0,20.0,26.0,11.0,13.0,10.0,15.0,AACGHHEEDBDBDCDCDBEBFBFEGDCEADDDFAFAEAHHHFAFADEDCHCBCAAGACDDDDDBCAGDCDBEHGHGFGABDHDHCCCCHADAEAEDHDAACAFAFBFEDGBHCCADHBGBDFCFCHCFG,False +494,4.0,3.0,5.0,3.0,3.0,7.0,4.0,3.0,AHFEBAHCHGFGFEFDADBFFCFCGCGCBEAD,False +495,0.0,4.0,1.0,1.0,4.0,0.0,2.0,1.0,BDEEBEGEGHBCB,True +496,6.0,16.0,13.0,12.0,12.0,13.0,12.0,10.0,DHFEEBAFCHCHCEFHABBCBCFGECECEGEBDCDCBBBBFAFEBEGGCGAGFHEDGBGEGCHEBDBHBHCGBHAGDFDFDFDFDHCADFDFGB,False +497,19.0,9.0,12.0,22.0,14.0,24.0,20.0,18.0,DEDAHEBAAGDBHHGABAGCHCDCACFCGCEEACBFAFAGEDDDHHHCHCGFGHBAGAFAHDDDDDGDFDFHFEEDEHFHEBFDFHBAGHGHFHFEDEDFDFDCGBFACAGAFHFEABGEGFGFGFECADAGGDGFFF,False +498,8.0,3.0,6.0,14.0,8.0,17.0,6.0,15.0,GFFDFEGGBEBHAEDGFAFEFDDDAFHCHCDCDGFHAHFHFGDHCEFHCHCFDHDHAFDFEFAFABAEHFHDHDEDH,True +499,0.0,6.0,1.0,2.0,2.0,3.0,3.0,4.0,EDECHDBGBGBHBHFGFBHBF,True +500,9.0,11.0,8.0,10.0,19.0,12.0,9.0,5.0,GCFDBACGFBFAAAAGBFAEGFGCGHEAGHDFFCEDEDEDEDECHBEGDDEAEFDFAFEBEHEHEDEBEBEBCBCBFFEGBCE,False +501,8.0,14.0,12.0,11.0,8.0,12.0,9.0,4.0,DBDBEBDBDFDAGCGFBCBCFFGCDCDEDBBBECECFBFECABDDAFAFAGEFBHAGAFCHCDCGHGHBFBEGEFCAG,False +502,5.0,5.0,5.0,5.0,9.0,6.0,4.0,8.0,FEFEBHHHAHABEBDDFDHDCAFFECEAHCBCEAEBHGHGCGFDEGE,False +503,12.0,12.0,13.0,25.0,16.0,10.0,18.0,21.0,GBGBDECCCFHHBACGDGDGDADCGCBBHDHDHDBDFDFDHEHGCEDEGEFAFHBEFFGCEHFFDDHDHGHGDAACAGBDHGHEDEDGAHCGDGDACEGAHAHDHEHEBEBCBFBEHEADDGDCAHE,False +504,10.0,15.0,9.0,13.0,14.0,7.0,8.0,9.0,CBEEFBBGBGBDBABADFBAAHEBEDEDGFCEBDBHAHBCBCBGGFDFCAGAFDGDHDHGEBEHFHECECEAHCDDEHEAEADCD,False +505,18.0,16.0,17.0,23.0,12.0,18.0,20.0,12.0,FGFABEFDHDHFHGDBDBGBGCACDDDHAHBHFFFBGCGEAEAGABHBGDGCECEDHFAGBDEAAHCEGHDEDEDFGHDDDDEFFAFGDGCFCFDFDACFCEAABGBABCBCFHGGBGEGAACCCCFCGBADADBD,False +506,22.0,16.0,25.0,22.0,25.0,11.0,27.0,18.0,AGCDCDHDBGCGAGDDCDGBGDCBCGFGHCECGHGAEFEDEAEGEFHGBCBCAAAAGGDGEHEAEDEDEBCBGFCFGDDEDECFDHDBEAEDEHGHCCCCABAFABCBAHCHGHCCDCEFAGEHAGAGHEBCHEGBHBHDHFEEEACACDEDEHGGGFBFBGDAAA,False +507,13.0,17.0,22.0,10.0,17.0,14.0,17.0,13.0,GGGCBBBEBHAEAGHDCGCDHFEAEABHCHGFGHGCCFFBCAAHEHEDCGCGCDADEHAHFDFAFCHCFCBDEEAEFHAHFCFABBDBDEGECEBGBGCGCDEEBEBFBEACBCGCGBGCFCF,False +508,17.0,21.0,24.0,12.0,17.0,20.0,19.0,17.0,ECHCHCHCGCFBGAGEBEBEBDCCFHFGCDFFHHBGBGDDDGFCFCGDGFAACACGFHDHGAAHAEBEGCCCFGFADADHBBBBABEBEBCGCHDHBGEHCACECEDDCFFAFEBACAEHEHBGBHEFAFBGHGFBCBEAEAGFFCF,False +509,4.0,0.0,5.0,5.0,1.0,0.0,3.0,4.0,GHDCDCDCDCAEHGCDHHAAAG,True +510,10.0,11.0,3.0,4.0,7.0,2.0,18.0,3.0,HAGGGGAFAGCGEGBGAEBGGEBEBDCEGDBDADEBEGAGAGBBBCGGBGAGHBHAFA,True +511,2.0,4.0,2.0,2.0,1.0,2.0,3.0,1.0,DEDFHGABBBBFAGCGC,False +512,2.0,4.0,2.0,1.0,1.0,1.0,0.0,1.0,HDBABCBCBFEA,True +513,4.0,5.0,8.0,7.0,6.0,8.0,11.0,4.0,GGHGHGDBCECECEGFHDABADEGGCGCECBFEGACFFFFBFCFHBAGGDDDD,False +514,20.0,26.0,19.0,15.0,24.0,22.0,24.0,21.0,FGFEFEFBHGHBEDHHHHEDCDEHEHCBFHGAFAFBFDCACAGGGGGGGHBBABFBFBCHGGBACGCGDFEEEEAEFFFFDECECFCBCBEAHCBADEDAGFDEDBBEBEHACAFAFABHEEDCFGHDAABEBEDGGHGHGDDFEFAHAHBGCGBGCCCABBHBAGCBHBE,False +515,22.0,23.0,26.0,33.0,16.0,30.0,25.0,23.0,GGGGCBEHCBCFEGGFADHDHCGDACCDBDGFCFHBHGAABFBAHAHDGDBDADACGCFDFGFDDHBGGGEBEBEFGFHBEFABEGCGCGHAHFHFHDBDBDCDCDCHFFFHFDFAGEGBABFEDBDCECBCDDHDBGECADEDEFFFFAFDFDECGHDFDFBCGFECHHAHAHGCBCDADAEAFCFCDHDABAHABC,False +516,17.0,13.0,13.0,12.0,15.0,20.0,10.0,20.0,FDFAGABHFHCEEAFCEGGBEBCBCBEBDHFACGHGCACACAHFHDBGFGDAEAEABFDEDHDFAFEBDHHHFHFHFHAHAHAEAFADCCFBBCEHFFFDGDGBEHHHHGCBEFEAEDFC,False +517,26.0,21.0,23.0,17.0,23.0,30.0,24.0,22.0,ABAEAEAEBGGGGGAECECEDFCEBAGHFHAEADCCGGGAGBEBEBEDCDFAFHFHGCCBHAFAFAFHFGBCDDFACGFGHDEEGEFEGBGFGADFCFCFCBAEABCDHHHCHFHFHBHAEFFFCFBECCCFFDFDBCHCADAFHBABDFDBBAHGGEAEHCGEGCDAGAHDGDFHFHFEBABEBH,False +518,7.0,13.0,9.0,12.0,7.0,6.0,7.0,5.0,CGCECBHDEBGBAFCDBDBDACEBDDGDGEGEFAFAFAHCFEHEDBCBDBDCDBBBDCHFBAGAGH,False +519,15.0,23.0,14.0,11.0,17.0,17.0,14.0,16.0,AFGEDCHBBBBBBGGECEFFBACACBCGCBHFAAABCCEEDDDHBBFBFBGEHEFDAEAFFFEHAGABAFHFBDBHHHBEBEACGCGCACDCHEEBEGGDGHGHGDDDCBGAEBEFEFAFHHHFHFB,False +520,18.0,12.0,17.0,12.0,18.0,12.0,16.0,36.0,EGEHCHDHDGDGCADAHAHFCEEBACEEEADAHHBCBEHEHEBAHCEEGCFEFAFABHBHGHDCGCGDHDHFHDHDHAHCHABCGCFBHHAHFHFHFCEHEAAHHBHGEAHHBFCCGBGFHAEAEGCHBHGDGDGAGFHHC,False +521,4.0,11.0,9.0,6.0,9.0,15.0,6.0,12.0,FFFCCHBHCFCBCBFDDGDGBFAGCFEFCHCGFBBBHCHDEDEAEBHBHGAEAFFBEGEHEHEHBHFFFFHD,False +522,17.0,10.0,12.0,14.0,22.0,13.0,17.0,18.0,EEEEDEABAGFEFEHGHBDAAABDBDAEHHAHGHGHDHAEABHHHHHBCGCFCFCDBAGACEEGCGAADGDHAFCFCEBEFDFEEACGHBEFEFEFEDCGFGHGEGDBAEGEDCHAHGDFDGC,False +523,0.0,4.0,3.0,2.0,1.0,0.0,4.0,2.0,DDEBCHCGBGCGBGBH,True +524,25.0,20.0,21.0,11.0,21.0,16.0,21.0,28.0,FGHGHEHEHBHFHFBFBDBEGDCHCGAEAFCDEAAACHEHEHBFFFFAAHCGGHGBGBHCHCDCGAGAGBHHHFDCDAEABBBCECBGGFACHCECEAFAGHFAEHGGEDEDEBHHACCCACBCHDGDGAAABAGFEBHAGBGCFEEDEAEAFBECHHAHBHB,False +525,5.0,5.0,3.0,6.0,5.0,16.0,3.0,8.0,DHFHFEFEADAGEGECBDFCBDDFHCHFAAAFEHHFBBBGDFFFFFFFHFH,True +526,1.0,0.0,1.0,1.0,2.0,0.0,4.0,6.0,HGHCHEHEGGHGDAH,True +527,14.0,26.0,15.0,11.0,16.0,18.0,25.0,17.0,BHFABADGFABCDGGECEBEFEDBDHGFCFDBDBCEFBFHAGBFEFGFHFHCHBHEHFHFHCHCEDBDBEGHGHGCBCBGDEEFCFBGBGBGBCBDBGAEAGBGAGECEAFGGGHGCCAFGGEAEDBHAGABAFAGHHCBBB,False +528,26.0,33.0,22.0,21.0,21.0,26.0,21.0,23.0,HDBFBDGDGHHEBFFCECFBABGGEBEGGAHEHABGBCCCABDFEFGFADACCGABDBFBADADBDAHAHBEGHFHBEGEBCBCBHAHABADCHBGCDEDEDHGGGGGCDBFFFFFAEECHCHCFEBEAADFBFBABDBGEEHEGEFCFCFEAEADCGFADHHFBDBAHAHACABABFBFCFHBHBHCDFGCD,False +529,19.0,28.0,16.0,26.0,16.0,17.0,19.0,17.0,ABADGCGBHDFFFGFGDGFBDGGFAFCGGFHHAAFFFEAAHAHCBCBABADDFFFABDBDBHGDACHCHGBBBBBGEDADAGCBEBHHEDBCBCBDEEGADABABADADCCBCBDFDFCBCHFEEEDEHHHGHBHDEECHGDGDBEEEDEDGDGCBBD,False +530,10.0,4.0,8.0,6.0,5.0,11.0,7.0,6.0,FFBFCDCGAGFEDCDBEGEGFCFCFCBAFDBHAHAHAGACAHAHEGDFCFADEGAFH,False +531,13.0,7.0,11.0,9.0,7.0,13.0,13.0,17.0,GCABEBFBAHHHGHGAAHCHBEBCDAFHFHBCDCDCDFGEGCHAHEHCHDFFFGFGCGAAAHGGGHFCECHHHGAAEADFBFDFDEDAGF,False +532,6.0,4.0,4.0,4.0,4.0,11.0,3.0,7.0,ABCDHFHFECEDADFGHAFCFCFBFBGADEHGBFHEHFHFAFA,False +533,14.0,30.0,24.0,27.0,22.0,23.0,21.0,29.0,CEBEDGCHDGAAABHEHGCGBFBEGDDDCDCHHDEGFHCEFBGBCCFBAEAGABEDFDCDCDHDHGFGHGCGDDFBBBBBDFDADCDGBFEFDBCFCFBDHDGFACAGFDFDEAECFBBHBHCACAHFDEHEHBDBGBHBFBEDCFEEHBHBCBCBHEFEFCHCHEAFHBHBHEHFGCAEGHGHGHGHED,False +534,7.0,14.0,11.0,10.0,12.0,6.0,11.0,7.0,ABADCBEGAGABDBHCECDBEHGCBCBCGCFCFHFHFBBCBGEGHGDGEGEDDDCDEDABAHCFEEAEFEBBGDEHBG,False +535,1.0,8.0,7.0,5.0,5.0,7.0,1.0,7.0,BHBGFHEDDFCBBBBHHHFEFHFCFCACBDBDEHEFECCCD,True +536,5.0,4.0,11.0,11.0,13.0,6.0,6.0,8.0,CDDDEBHHGHDFGCCACEDEDECEGEACACHEBFFEFEFGFGDGDHAEEEABCBHEDCDCHHDC,True +537,28.0,21.0,11.0,18.0,13.0,11.0,21.0,19.0,HGAGAGFDDHGEBDCGAAHGHEDBDFDEGAGHDECCAAAADDGBBCBHBHBHGCGCBBBFBFGABAGCHBGAFHFAACAGDFEFEGGBFHAADADFDADBBBDAEAFHGHEHEHAHAHAHAGEGDCDCHBABABECDGAEBE,False +538,3.0,5.0,4.0,4.0,5.0,2.0,1.0,6.0,HCHGHAFBEBEAEACDCHBEBFCEHBHDDD,False +539,6.0,6.0,7.0,4.0,9.0,4.0,6.0,1.0,CCAGDGDGEFBCACBCGDDBFEFCFEABABCEEEABAEGEGEH,False +540,4.0,1.0,2.0,4.0,0.0,6.0,5.0,0.0,FDDGAGFGCGAGAFFFBCDADF,True +541,9.0,14.0,13.0,6.0,8.0,6.0,10.0,5.0,CBCGEGEFEHAGEDBGEGAGHDCBCGAGAGHDFGAACBBDBDFFCFHFDACACBBEBECCCCHEACBBBBB,False +542,16.0,16.0,8.0,16.0,13.0,11.0,10.0,17.0,EAHAGFDCGCGDEHCHBAAADHDHEHEFBGBABFDAAADBDADADHDGEGCGHGBFAFEBBBBHFDFDEBEFAHEBDGFHCHCHGDFABABDHHHAEBEHEDEBCCF,False +543,21.0,26.0,17.0,27.0,29.0,23.0,26.0,18.0,GDEHHBFFAHDHDCBHBGEDBDGAGDHCEEEBFFACBBEDGFCFBEBECAFDDHBHDEFEFEFEGGCGBHFFCFEHBHEFBHBADAEAGAFBFGEGEGCGDEDEGCGCBDFDFDADABCFEBBBDBGGGFGCDCDCACFEDBGEGEGHABGEGEAAAACCHEBEDEHBABFGFHHEHADGDADADAD,False +544,22.0,22.0,21.0,19.0,23.0,23.0,21.0,20.0,CGDGDBCFDADCCGDBDHAHCHCEDFFGGGECECEAFAHCFDDEDAGCGCBDEDEAEHCHCEEECEFBFHDHGHGEGCHFEAEAEFFCFEDEABHHHGFBAGAGBDEGECECECHBHAHGBBFBGBDFDGAAFAFGBBCBGBFHEHCBDFFFHFBAAHBFBAAAFAGABDB,False +545,23.0,25.0,25.0,15.0,25.0,17.0,21.0,33.0,GAGAGEEHHHFHFHFHEHDCFHABBHBHBEBHFGBCCACACACGHBADHBECECEBABECCHCFEGHDCEBGGEBEBEFHHADCDCDFDHBHCAEEHEHFHGHGHFADCGFHCACACACBCEGDFHCABGDGEGFCDHGHAAAHBHBHBEBHBHAGABEEGEDEGFBFCGEDAGADDBBEAFCF,False +546,3.0,2.0,2.0,4.0,0.0,4.0,0.0,0.0,ADADAFCFDBBFCFD,True +547,13.0,21.0,3.0,11.0,13.0,5.0,12.0,11.0,GHBADHBHBGBEHDHEEFGHDHGFEDDDEGEAEDFAAGBBCBAGAGAEDEHBHBABABAGADBEBECEAEBBBBGBHBDFGCADBFBHG,False +548,25.0,24.0,22.0,17.0,28.0,18.0,39.0,21.0,CDCABDBHBGBGBGBCECBABGBGAHAHBFEEAEBGAGEHFACACDEGEGECHAEGEHFHFABEGHFHAHGHCDCEBEGDBFAFHGEGBGAGDBDBDBEFECHFHEBFGEGEGECAFABEBGBGHGFGEGCCCCHGFACGBHAHAECFGAEDHGHGDDDEAFADGDGDCAEGGACFBFAGEGACCEHDCDGGFG,False +549,3.0,2.0,4.0,4.0,5.0,8.0,5.0,2.0,HFEFGDGFBFDFEEEFEFGBGCCACDCAGAHFD,False +550,1.0,3.0,4.0,3.0,7.0,2.0,2.0,6.0,ECEBHBHGHBECEFDHAHECEDEDGCHF,True +551,16.0,22.0,21.0,26.0,28.0,20.0,19.0,21.0,EGEDEBEAEADDDCFCABGEFFHDBECHBBBBAHAFFCCDDDDDDHGHEFAAAAAGGBGFGBGCCHEHFBFHHDCDFFBFDGEGFCABBEBEBECDGFEECACDDBCFEDEHHDBDFHFHCHCEGGGEGEADCDCEGEFFHHGCCBCBDBEBEAEAEAGDFHCDGDHBHEHEH,False +552,4.0,5.0,6.0,11.0,3.0,11.0,11.0,5.0,GCCDFHFBDDEDECGCGDGHABDDGGGDHAHAFGFGEGFGFABDFHFCFDBDBFFC,True +553,5.0,13.0,12.0,7.0,6.0,1.0,8.0,8.0,BGDACECGDGCCCBCHCGCDBHHGBEAEAEFBCBEBDGCGDGCBABABEDCHHHHHBBDB,True +554,21.0,23.0,19.0,23.0,24.0,21.0,32.0,21.0,FAGAHAHFHGHBEEFGADABCBGBGFAHEDEFGFBHCECEHEHDGDEAAHGGGEGFFDFBCHGAGHCDGGGABDGDADHFEBHBHGGCACBCBCBGBCFADADGDEDACBGHEFDFHFHFBDDDDBHBGGGCDEFEGEGECHCBCBEBEBEFFAGBBFACECECDAEFECGAGEFDGGAADHDH,False +555,11.0,14.0,17.0,9.0,22.0,14.0,9.0,22.0,CGEEDCDADADBDBFFFHCAAEHHHEHEHAHEFFCFBGHHHFHCHDHEBGFGFBEECFCEEECGCGHEEEEADHBHAABCCACFCEDHCHCHBHBDBECGCEFFGFABBEBEGHAHBE,False +556,4.0,3.0,4.0,4.0,4.0,1.0,0.0,1.0,BABHECAAFBDCDEDEDECAC,True +557,11.0,15.0,15.0,16.0,14.0,18.0,14.0,14.0,BCBCBGDGCGEAHHEHGAFFCFHFCGAGACEBEBEBAFGCCDGBCEFDFDAEADDFDCEBFBFBEHDHEHEGEGBGHFHDDDDCCBGBCBHAHDEFFFGGCHBEAAAHFFDFDFDHC,False +558,5.0,2.0,3.0,3.0,1.0,2.0,3.0,2.0,DGDGACBFHFHAEACABACDG,False +559,29.0,26.0,17.0,17.0,20.0,26.0,24.0,23.0,DADCDFFHFAFACAFBDBACAGABFGFBHCHCFFEFEFGHGCBCAEGGGDBDBABFHFAEADDDEDEHAAGGDBHGFFFFCGAHBBGBGECEGEGEGEBEDCFFDFCCEAAFDHAEBFBFAHAGFHCCGBGBGBGAGABEDADHEBEHHAEFHAHABCBCHAEAFAEBHGHBBBAGDHHHHC,False +560,7.0,9.0,14.0,11.0,8.0,12.0,13.0,5.0,FCDCEFEFGHDAABACGCGCGDEBAHHBCCFCFGEGDBDBDBAFECDFDFEGGCAFABCFGFGEGHCDEDGDGFCBCBH,False +561,16.0,32.0,21.0,19.0,21.0,20.0,22.0,22.0,AFBGBGHGEDFAACDCDCEFEBCFCGHGHFDABABAHCCEAHBEDEDBDCCHGHEBEBEBCDEFGDGFBFEDHDHDBBBFFEGBGHEDGDFBGBACDGEBEBHBHCCGHGHGDGDGHGHBCAFHGHGFABAFAHAFCBCBFAHDHBBCBGFEBABCBCFCFEEBCFEDEAHBE,False +562,18.0,21.0,6.0,6.0,14.0,3.0,15.0,20.0,DGAAHCHBAFHBHBGCAEAEAHAEAHHHBCBGGEBDFAHAEAEBGAGAHDEGHAHBEAEGHGHBABHBHEDCGHGBEDGBGEGBGBABDBAEEHFHBCBCBHB,True +563,19.0,18.0,15.0,19.0,14.0,16.0,17.0,24.0,FAFAFABBHDCDCDFDCAABFCEDBBECDCDFFAGADBCHGGFHDHGHEECEGDADABEHHHHCHDHDFAHGFGFBDBCBFHAGABDBGBFDGGFCFCBHBHFHEHEHEGAGAHAGABAGABEECDCHHEBEDEHAGCGHDH,False +564,3.0,3.0,2.0,1.0,0.0,0.0,0.0,2.0,BABCBDAHCHA,True +565,8.0,12.0,12.0,9.0,13.0,13.0,12.0,17.0,BFBFEEHBFAFGGGCHDHDHGCDCGEHAHEEBBAEFGCGCHCFCFDBBBHCEBEHEHFGAGFFHFHABDGDFDFBHAHDHEAABCEGEGEDCHCHC,False +566,24.0,19.0,7.0,22.0,15.0,14.0,18.0,21.0,AEADAHECBGBFHGHDHAGDGHGBGBHFHBDDDHGHDHDADHDHAHDEDADGFEFGFBDBDFAAAAABEFDHHHEGBGAAEDEGEGAFAFHHBEEHCGBEADAEFFBFDFDBDBGBHAGBCBEFDHGCACBCBAAACAGE,False +567,18.0,34.0,25.0,23.0,26.0,29.0,16.0,24.0,CHFDFHBCBDBFBHEEAEABABCGAFDFDADADADBBBCBDBFCEEEFFAFDBDBGHDHBBBFFFDABFHGCABABABAHHHHDFBFEFHBCDCFCFBFEEGECFHEGEGBBDDHDEDHFHDHDFBAECCBHBEBHBCCCBDBEGHGCFCACEFAGEGEGCCFBFEHEHCGFECGFDAGFGHCCCEEEBEHAHDG,False +568,10.0,3.0,8.0,11.0,10.0,4.0,2.0,8.0,EGEDEHEHCDCEAEAEAFFEHCDDDCACHBHBDDDHAAACAEBFAGAHDCCFEDHD,True +569,16.0,11.0,9.0,12.0,15.0,17.0,17.0,12.0,EAEDEACHEAGBHHFFAGGDADADHBHAFFGDEDEHFBFCGBGFFDGHAEAFBCBEAECDADCGCGFGEGEGAGDEDBFFAFAFCBHAEAEGEGFGFDCHCGFBHBHBH,False +570,5.0,3.0,10.0,3.0,5.0,7.0,4.0,6.0,DADCHHGACACECHCFCFHDEGABAFFFFECECFGGHBCBCEH,False +571,19.0,19.0,10.0,25.0,20.0,11.0,12.0,21.0,EGEGEDDDADCBFBFCHCHGAGDHDHDADGHEDDDDHBHBHCADEEEDDHDBCEAABABFEEAEGHGHFEADDDCABHBHBHFHFEEEEFDCEEGCBCHGAEAGABFBHAHEHAFABHBFDDDBDBHAAFBBAGGCD,False +572,9.0,14.0,14.0,11.0,15.0,15.0,19.0,10.0,EFEAEGGGDGDADFHFGFBFBFGDGBBEBEADHGCBCBCGCECGFDCBCBFDFGEDBDHCAFEFEBGCHAFGFGEEHBGCGCEEEBHCHBADCCGGHAHADAGFHFE,False +573,4.0,10.0,13.0,15.0,11.0,8.0,6.0,4.0,AFCCGEEDEBEBAHAHADFBCBCBEFDGHBEGEFFBFDDBCECDCDCECEDDDDDGDCDCEBBGDHFCCGF,True +574,15.0,27.0,18.0,27.0,33.0,20.0,18.0,26.0,FACGCDEDBABABADHDBEFECGDFHHEBCBCGHHAEBHBHGDADGDGDEEEDEBCBDBEAFHFEDGDGDBCHEAADEDEAEDHCHAFDEDHDACHBHBHEHECFBABHDEEEFEGBGDDHGFBFBFCFCEBEBFFCECEGEFEDGDCBGEGHFCECEBGBHBHDHCEFFFBGBHHHEFAAHDG,False +575,16.0,17.0,13.0,14.0,16.0,19.0,22.0,14.0,HBCFCFDFEGAGAHHGEGBGDGFHEHAFBDBDCHCHGFDEDEFHFBEBHBHBEBHBDFDEDEHEGEFFACACGFHADGFADGBAEADAFBCHEFFBEBGBGBACGGFGFAABGGDGFCCACAEAECDGGGC,False +576,21.0,18.0,24.0,12.0,15.0,14.0,8.0,14.0,CDCDFBACHGHECECEDECECHHAHBGFAAHAGFEBCHAGBBBABCBADCFEGABABCGCFAFEBHAHDHECACHHFCBBBEBECFCFAFAHAFCGDFDFDBEBDCACACADBDEHEFEDGCACAC,False +577,11.0,6.0,10.0,4.0,4.0,6.0,15.0,11.0,HHGHAHGDGCEBABABGCHCGCECHCACHDFBABFHFCAHAHFFBFGGGGGGGACAGECDGAADEHG,True +578,13.0,11.0,13.0,13.0,10.0,10.0,11.0,13.0,HDHDFAHCHGEAAAACGBEEHHDEEEDADCDCACACDGDBDBCFEAGHCFCABFBFGCEFBHHHHGBGCGCGEEHAHFBFDDBDBCGDGAFAFB,False +579,16.0,20.0,17.0,10.0,16.0,13.0,17.0,18.0,HBHCDAHECCCCBHGEFCBCGFFAFACBDGDCHBHBCBEBEDGDFEHGHBHECCCEFAGAEHDGDGHBFAFAGAGBGBGBEECCAFAFDBBHFECBGHCHBHDHBHBAEEEAEHEAGAGFGFGDABA,False +580,19.0,23.0,27.0,23.0,24.0,28.0,24.0,26.0,FGFGCHDADGDHFFDCDABFFFFBCEAECEHADCDFDFABAHABDEDBAHCCCHBAAFAEGEGFGHDHGHBHGHDCFCFCADEFEHBAEEFGCDCGGGGGEHFGCGCFFHFHGHBCBDBDCCCGEBEHFBFCFEECFGHGHFHCAEBEBEGHGHFEFDCHCBCBGBDBEAAABCCEAFBHBHDHEEGABDDDED,False +581,14.0,16.0,19.0,20.0,20.0,20.0,13.0,20.0,ACAFBEAHDHEHBHCABBCHFHCEEGCHHFCDCBBEBHFABGDHFHFHBHBHBGDDDCFFHFBFGFECDCEAGAGACCCGCDCDEDEDADADFFFAFAGHCDAGHFEEGHCEEEHECECEGEFDFEEGDDDGDBBFBFBADH,False +582,13.0,15.0,13.0,20.0,21.0,19.0,19.0,16.0,EGGAGAHBFFEFEHECDCFCBGHFFGAGAGEGCGAGBFCFDDDEBEHEHCFBDDDDDDADAFAHHCFDEDBFFFFHAGCBDAFBHBEDGFGCBCBGEGEDCDCDCFHEHGHBDGEHABEGAGHFEDAHEEEEEBHB,False +583,6.0,13.0,10.0,9.0,17.0,8.0,10.0,9.0,FHFGBBBBABCCDHBEDHGFDEHCGCBEBEHCFCFBFBDBACFHGHGEEECECEDEDEHEDGCAEADFDGEAEGGGEBABEH,False +584,18.0,27.0,27.0,16.0,19.0,28.0,14.0,16.0,FHFCFAFHHBEBFBDCHBGEDBAFFCBHBCFGFGCGCEEEDEDBABGEFBGBAFAFHEGCGCDCDBHHCHAHAHGCECAHFHFDEGHBBCACABABFBFBFAFCDCDBABEBECFFGBECCCHCFAFDDDDFDBECEAEDBFCDCEFGFABABCCGEHCABGFEF,False +585,26.0,16.0,22.0,22.0,20.0,21.0,22.0,26.0,FHDHDHFCEBBDBAAAAGFGCBEDHDHGHAEAECDCBEBHCHAHGGFDAEFCFHHHEECCCDCDCDHAHABBECACADAHCDCDFBBEDAAGAFFHCEEEAFAFGFCECEFACAEAFFHEGFHCAGECFFGBGFGDBDBABAGGGGGHHHAHDDDHHHAHDGEGFGBGBFCEDGD,False +586,8.0,5.0,12.0,4.0,4.0,13.0,13.0,7.0,DFDCCCCCCFEBEBDFFAFGCGCBFDFBAAFHGHGCGAAHGFAFGFGCGAGBCHFHCGGHFHEAEG,True +587,4.0,3.0,2.0,3.0,2.0,5.0,3.0,1.0,BGGGDBDHDFCAEAFCFBFEFAA,False +588,7.0,14.0,10.0,16.0,16.0,9.0,9.0,13.0,BCDFHCGFGAEFFFDDBBHBFBHHGAEDDFDEHEGEGEHADFEEHEGEDEDEDEHHBHBDBHBDCDCDBBFBABACACEHECGHEBDGDCCCAG,False +589,41.0,28.0,27.0,20.0,22.0,14.0,25.0,23.0,EDEHHHEACAEAEGECBBHBHBEFAFEBAFHHGHAHACAGBDBEGCDEHAHADACACGEDCCCFBBBBBFAADACAGECDFHGDDBDCDCECDABAFCBEGEDFCGBGDHACABGHECBGGCDCGEFEAGCGDAAABABABDHGEAHBGAEHGBGBFCFCFEFBHGHBAAAAHABABADAGACACGCACHDHDHAFAGEG,False +590,25.0,17.0,16.0,9.0,20.0,24.0,14.0,17.0,HDFDEGEFBBECCBDBABFFAFDFCECBAGAEABGFHCACAFAFAFHEHEHECFCHEHEHECGBDBAFEBCFAFCFAGGCFCABHGABFFEGAHAGAGCHHEHFDFBEBCBEFAFAHAEFEAAHAHBHBGDGDGCEADAGEF,False +591,17.0,13.0,25.0,18.0,20.0,19.0,18.0,19.0,ADCFCHDBAEHEHEFEACAFAFDFEFECEGADHDHEBCCCCEHHGBDBDGCCFBGDDCGABAEAEDEAFAFCGCFHFEGAGDGFHCGCEHEAGCHCBDEDCFEDHCBEBFBAGEGAHCHCBCBAHACDBDCDCHFHEGFGFGDGHGFFH,False +592,4.0,14.0,3.0,5.0,17.0,15.0,9.0,5.0,HGFEEHBHFFEFHFEGBABFBGDFBBEFEDGDEDECEBEFEAEBBBBEBFAHAGFDFEFEBGCGFGBGFECE,True +593,13.0,8.0,10.0,11.0,8.0,10.0,5.0,8.0,EAEADADGFGCDDFBFHHGADABAFHHBAEABHHGBCFCFDFAFDHDCDCBFBCCCBCEEEAEAEFDAHACDG,False +594,16.0,13.0,15.0,7.0,3.0,9.0,20.0,22.0,BGBGCGHHHEHGAAFGCGBDFAFBHCHBDBCCCFDAHHBGBAAABHHHGHGBABABCCCCCDGHGHCHAHGEGDBFGFGCGAHAGFCHGGGAHAHCHFEDHDAAF,True +595,12.0,10.0,9.0,7.0,8.0,10.0,12.0,10.0,AEFDFGFGABHBHBACAHFFEECEFDFGBCAABBCDCGEBEBHHHHFBAEADGDGHGDGDCACGCACAEFHAHGGGBF,False +596,12.0,14.0,7.0,5.0,7.0,8.0,16.0,11.0,DBGBABFCGCGEGBGCHCABEEHGGGHGHFBEBABFBFBGGGGFDFCGABABAFAHHHHBEAAADDHCFEHAHBGACDGE,False +597,12.0,31.0,25.0,23.0,29.0,22.0,19.0,20.0,GBCAEDEGEDHCHGFBEGCCDCGAFBFAFEGBBDBDBDGGCEHEHFHDCDCDEDFHHBGBGCHABGCGCFHFDEBCDHDAABFBGBHDCDCEHEBFBFEFBFHEHEGEBBDBEBABCDGDBHBDFDFDACCEFBCBFHFGCEAEDFCCDCFGGEEEAEAFAFBHBEBCBCHEHCHGEEEBE,False +598,3.0,2.0,2.0,2.0,0.0,4.0,2.0,0.0,DADAGFCFCBGAFBF,True +599,18.0,18.0,17.0,19.0,19.0,25.0,24.0,26.0,EFEFADADEGEGBBHHABBHCCGAFDHDFEHHHHHHGAAADGHFHGGGGDEACHCHCFCGEGEFABEEGEHFCFDFEBGAHCHGFGFGFGFDDHEFCFEBDFEACAFHCHFBADGCGBADGDAFCHCHDDDFDFHCHBHEEEBEBGBABABABCBFFHFDGCGBGD,False +600,18.0,13.0,8.0,18.0,9.0,20.0,11.0,10.0,FAHEFAFAHDGGGGHCBEGABABFEFAAGAGAGAGAGBHBHCFFDHBHDEDEDABCFCEDEBEFADDBFFCFHFAAGDDDDDDFFFFHADFFFBBBCDADCCADHBE,False +601,28.0,16.0,18.0,22.0,25.0,31.0,31.0,28.0,DHDHCHCEGGGGGGHGHGABHGABAGDGEGBACHDHBGADFBHGAGFGDDADGEAEACHBBFFHFEGEFFAFAFGFEFAGADDFAFCFGHBFFEDBACABFHFCCCEEDFDCDAAHFHEHDDEDGHEFCAHFFBCGCGCACABAEAEHDHFHFHFCEDEDGAGAEEEEEFDAGGGHGHFHAGEBHBAEFCFBFCEHBHD,False +602,19.0,22.0,22.0,6.0,18.0,28.0,18.0,32.0,BEHEHCBFBFGAGFFFHEEGEFFGCHCHFABHHCCBFHFABBEBCACAEAFHFABHCHGBBAHEEEEAHAHBHECACAHEHEHCGBFFHFGAGCCBCBEFEGHDDGDHFHCDAHHHHDAFBFAFHFHGHGACCCACBHBGBGBCFGFHFHFGFGFAEBCGCBDEF,False +603,6.0,3.0,3.0,0.0,3.0,1.0,2.0,3.0,AAAAHHHEAEBFCEGAGCBCB,True +604,20.0,12.0,4.0,14.0,4.0,16.0,10.0,13.0,BHADGGGBAFFHAEDBAFGFCFHFHDHBHBGFFHADDEHFFBFGHAHAHABACADFFAAGADAGAGACADDEFEFDADAHBGBABDBDBDCHF,True +605,13.0,12.0,3.0,10.0,9.0,12.0,19.0,5.0,BFBFCDGDBDAGAFCHBBBDHGADCEAABAGFGFGEGEGDGFAFEGBGAGEFFGFGEDADBBGAGAGEFEBBHGHGEDDAFAH,True +606,25.0,22.0,15.0,23.0,20.0,14.0,29.0,17.0,ABABABGDEFEFEHBAAAFDDBDGDGAGEEBHFFCAHAGABACACHEGDGDFDHGGFFHFBEDECFGHCBAGDGCHBGBGCGFDADECEBEAEADAFEBEAEFCBCBCBHBABGBHAHAGAGDDEEEHBCEADGDGDHHFDGABDBDGGCGCADGGHHDHGGEGC,False +607,7.0,12.0,19.0,9.0,3.0,6.0,12.0,7.0,CHGGCADECECGBGCGCEHDAFACDBGGFABCBCBCBCBFBCGCBCBCBFHADACADHDCGGGDFCHGFCHDHDB,True +608,15.0,15.0,12.0,14.0,12.0,4.0,21.0,15.0,BGBEFEGDBCGCGHHEGCFAGEBFGHBCCEGAHACGBDBGBHAHGHGHEHEHACABADADAHACBGDAEHGHBDBDBEBAAAFCGCGDEDCDEDHDAGHGDGBGEGDC,False +609,11.0,19.0,6.0,5.0,9.0,14.0,11.0,10.0,BBBBGBFBFBABDHAHFBBAHEHFCAHGGDGDFCBCFCGAHBDBGBGFGHAHGBEEAFFFBFEFEACACEEGEAEDGFHAHBBBF,False +610,7.0,6.0,1.0,2.0,7.0,8.0,15.0,3.0,GGGGGDGFBAEAEBFHGHDFAGBEFEFGFGBHAGAGBCEAEGBGEGAFF,True +611,9.0,11.0,18.0,12.0,13.0,14.0,18.0,18.0,DABAEGBGEGEGEGFDHCGCHAHFHFCCCCHHGADFBGEHAHEHECFHEHEAGABDGEBCBFFFGDGBGACHHHDHCFCDCHHGDCHCBCDCGCBBDADGGGEDECBFFFFEF,False +612,1.0,6.0,5.0,8.0,3.0,4.0,3.0,4.0,BEBEBGBFBFDDCHBDFCHDGACHFHGDCDCDED,True +613,5.0,7.0,4.0,9.0,3.0,12.0,4.0,8.0,DEEHBFGFCHBHDHFAGDBDHDFCFEBHHHBFBABAGAGDFDCDFFFFCFDA,True +614,5.0,4.0,10.0,9.0,2.0,6.0,6.0,7.0,GCBCBCGGBFHHCFCHHDDDDCBGAEACACFDADCCAFHFHDHDEDGFG,False +615,20.0,20.0,21.0,19.0,32.0,21.0,14.0,26.0,FCCGGEHECEDEDBBECHCHCFGBEHECCCCCHCGCDCDEHAGCECEDDBEBABABEBEAAAAHAHEFAFHFEFBFBFAFGEEEAEHEBGHEHDBCBDAAEFFHCGFHHHGCEAGDBEHEFEGDFBFAHHDBCHFFBEGEGFHECEADADADBHFHAHDDFDFHEAEBDBDGH,False +616,4.0,1.0,4.0,5.0,3.0,3.0,4.0,3.0,AGAHCHBGDFDCHEDEDEFCFCDAGAG,False +617,14.0,17.0,16.0,17.0,18.0,16.0,11.0,15.0,EFEFHFABEBEGEAEBEAECBDHFEEGEGBGDHHHHHBHBHBHAFAHDBFHABDDFDHBGDECECEFEFGDABAFAFABDHFBFCGCGBEFCDCEADDDFACAHDCCGDDCBCGCFCABECGCD,False +618,29.0,30.0,26.0,14.0,18.0,25.0,13.0,17.0,HACCBHBFAFBFBFHFCBAAGAEBEFDDBDAAACACACEEDDAEFGBGFEFCABAGAGAGFGCHCAGFBBDFHAABFCFCFDHEHCFBFBHADBBBBHDDBCFABBEBFBADAEBCBHBHFHCBDDHCHGHCACAGAGDFCFEAEBECECECFCECECGHEBAFAEAGHBCF,False +619,31.0,22.0,24.0,19.0,30.0,25.0,19.0,29.0,CFHEHCGFFACEHBDEEGGACFCACAGAHAEAFDCGBACEFGAECCAGHBHBDBAEAGFBABAGACAHHHAHCHCDCDAGGGAHAEAEDGGCEHFHFHFDGBHBCEHEDEFEFEFEAADACHFBDBDBDBFBFAEHFHBHEHEGEDEDCCEBFBFCFCAHDBFEAEFEACAFADEBEHHDEGEAHBHCHDBGBCDHFGF,False +620,18.0,17.0,15.0,24.0,21.0,15.0,18.0,13.0,ECDGDBDGDGDEAEBEBCFGFGAGAGHCDEHEHBGGGFEAAFBBDFHCDCEEEEGAGAGEDFDHDHAFAFHEHDADADBDECACEDDBHFEGECADDCFHBCBCHCDDFDGBBBEAECEDEFABAHCHGDABFBFGFCBGA,False +621,0.0,2.0,1.0,1.0,4.0,1.0,0.0,1.0,FEEDEBEBHC,True +622,14.0,20.0,14.0,20.0,27.0,29.0,12.0,26.0,CDCACEHFHFHBHEFEDEBBFFFFBFECHHAHEHEDGDEEBFHFHAACEDECCCCEFEHAHBHDHFHFAFABEEEGEGEBDAHEEEEFHDDDGDEDABHBAFGFEHABFBABDBFFFHFCFHFBGCABBGBHFHFDDAHGFEFEDHCHDEBGGGBCDDDCGF,False +623,16.0,25.0,17.0,19.0,21.0,19.0,21.0,15.0,BFDFDFGBGDHBHEDCACFCEHEDEBCFDEDADBDACADDEGEGHAHBHFEBCCCAHEHEBEBAAAAGCFCFGFBEEEHBHEHGBDBDAGAEAGBDBGFEFGBCBCFGEGBGHDHGCCAADCDCBFBAGGFGEHDFBEBFBFDFCFHBGGGEB,False +624,23.0,27.0,21.0,27.0,12.0,19.0,33.0,26.0,DHAGAGFBFCCHHGGBCBFDFACGBGBGHCABACAHFHCDCDGFGFCFGFCAEGHGABABEDEDHFHFDFBGHGEGHAHBHCDAGAGAGBBAEAFGCACBFBDDHGHBHDGDGBGDAAAAEBBGBDBDCACFCHCBDBCCCBGFFHDHDHEGEDEHHDDDHBGBHDFFEBDDEEGGGGAGHCHDBAGD,False +625,17.0,22.0,27.0,7.0,24.0,19.0,26.0,18.0,GHECEGFGAGCBEEGBGHGBEBEAEFGFAFCFHGGGGEEECBFBDGGCGCEDGFBHBCBCBCAGABEGEAEABFFFBFBFHEGFGACAEFDBCBCAGAGAGFFCCBEHCCBCBDHCBEHCHCACEBFBCGDAHFCECEDACAEHHHHHDAFGHCHCEGEH,False +626,21.0,20.0,18.0,14.0,19.0,24.0,20.0,19.0,FGFGDBFGAAHHDABADDECCHFBGCEEHGHGHGAFHCHAHBCBFAFAFABBBABADDGEBBFCFCFCFCBCDCDHFAGGHGHGAGEHBFAFCHHEGEFBHDHAHAEDGAGAGEGCDEHECCCBBBAFFFEFDADBBEDEGCFBFCGAEEEEFEF,False +627,22.0,20.0,15.0,21.0,16.0,16.0,15.0,16.0,GBGEFDACFGFGHBHECCFAAAEEGBCHCBCFADHDHDBDBDFDADABAEDFBADACBCFCFEHGCEFEAEBHDHDFDEEBBHBGAGDGAEAEGGHAHDDDDFDGBBBAAAABDHGHFAFECCCECHBDBCBFEFGAGAHH,False +628,7.0,15.0,8.0,13.0,14.0,12.0,11.0,8.0,DEDBDHFHDCDCBBBCBDBFBFCGHGAGEFAFAEADBFBGBGHGDCFADBDFEFEDECEFHHCBEAGGGDEBECEABBGHGFDHEEFE,False +629,1.0,3.0,3.0,8.0,6.0,2.0,4.0,5.0,HEHDHDHDEFBGBGDDCDHBEDECGCEEFGAD,True +630,11.0,10.0,7.0,6.0,8.0,14.0,8.0,5.0,CAHAHABFCFCACFCAHAGDBCEGHFHEBDFAGAGABBBEBCFEFEFBFAFBDEDEGGDFDABFFEFGG,False +631,14.0,11.0,20.0,21.0,13.0,15.0,14.0,16.0,HCFAAHBFCFAFHFGDHFCFBBBEBEAEAEHEHGDDBHHHFHDCDEGECFHFDFDADACADHGEDADHDHDCDCGADDECEAGBBCECDGGCGCABAHFGCDCGFBHBDCDGAGCCCDCGEFEF,False +632,4.0,8.0,5.0,12.0,1.0,8.0,6.0,3.0,CAHAEDBCCFGDBDFFBFBHDDDDDADCGBGBCFAGDGFGFHDBDBF,True +633,3.0,4.0,7.0,2.0,2.0,6.0,5.0,5.0,CBCECACAFEFDAHBCGFGFBHCHDHCHGGFBFG,True +634,15.0,14.0,8.0,23.0,21.0,16.0,17.0,8.0,GDDDADADACBFGFGFAFACADAEEBEBFCGBFHFHGEDDDFCGABCBDHDHEEFHAHGEFDFEFBFAGAFEGDGDGBGDEDEBHBDCEEEEGEBCDDEAECDDDEGGGAFAEBFBGHEDAB,False +635,16.0,23.0,27.0,12.0,33.0,22.0,20.0,34.0,HEHACECAHFBGBEBHHHHFFCECEHEAEGDGDHAHBFFFFFFFGABCEFEBECECHABGCGFHEEEEEEGBCAHEHCHDFBGBCBCBHHGFBHDHCHEHEHCFCGCGEFHHHCDGDEDECBCAFEFAGHDCABHDAEACCHGHFBBHDEAGBGAFDDGCACEFEFEHEHEBEGCCEGBGBCAHBHB,False +636,18.0,21.0,19.0,22.0,14.0,15.0,21.0,26.0,GHABCDDDAGGFFEFDFHBACHDHDECGBFBFAAGECECDAFBHCDCEBGBAAAGHHEHEHEHEBAFDFCACECECEHHHCHDHAHAHCDBDGGGDHDBCCFCGHHHGDDDBEBFCFDGAFBFBDBDBGBGBABHHCHGHGDBEGAAHDCGAGBGF,False +637,7.0,11.0,15.0,9.0,7.0,9.0,10.0,13.0,DAFBFHGDGAGCDCDGHBCECFCGCDEDHDHBHBFBEGEHDADBBBBGFHHAECHGHGHBFCFAACCCFFHGACHCBCECE,False +638,23.0,18.0,27.0,21.0,18.0,14.0,17.0,30.0,DEDCHCBFEAEAEABAHGDGDADEBEHCFDGGCCCCDCBFGFCCHDHDHFBABDHEHAHFHCAFAEADHDHCHEDACCGCGCGCBAFHHHECDDDBGHHHCHBHAHECFBBGBDBFHAHGHCDGHGCGCBBBGBABFGCGAEEDFDAEHFHDHEEACAEFEACHCAAA,False +639,8.0,5.0,5.0,6.0,7.0,4.0,6.0,5.0,FGEBDBDBGHGDGCAHAHCDAGAFAFBEBEGEFDCHAEECEDACAH,False +640,25.0,30.0,19.0,18.0,18.0,25.0,21.0,28.0,DBGBFBFHFHCAFAFACGCHCHEHEGFGADHHFEAEGEGHGEAEBDADHBABDGGGGHBHDDGAEBDFCGCFFGACDHBHFHCHFAGHEDACAHBDDDAHHEBEBABACAGBDEDGHBHFHFCGCDFBFBFAHGCBDDCBAEAEFCABABACACEFHFBAEHEGBGBHBFFHBEBFBFBFHCBC,False +641,10.0,7.0,19.0,15.0,18.0,26.0,16.0,17.0,EBEBEADCFGFGAADCEFHCAEDEAEFBHEHDGDGDBHCGCFHFHCHFEFGFGCECFCGCEDAFEGDFCAEADCFEFHHHFDFGFGAGDGDFHHGACFBHDHCGFGFCHCHCHCDEECFFFFEBEBFD,False +642,17.0,19.0,31.0,20.0,20.0,27.0,31.0,22.0,EFGFHEBFAHAHFHGCFCFGFHFBFDHDAGAGBECCHCBGBFEABDEGEGFCBDDFEFADADBFEGEBBAEHEHAHAFGCGCGCBCBFGFCACHCECGCBCAGFHDBDCAFGCGCGCGCDDDCDGDGFBHGFFAHCFCFHECDGDBECCCDCEGEFBFEHHGAGCGDHAHGHEFDHAGBGBGHDECE,False +643,10.0,16.0,8.0,13.0,16.0,18.0,19.0,19.0,DBDFCEGABABHBFGAHEGFFDHCFCFBDHHACAFECHHHHGFGBEHEGEGEGFGBBDBFEFHFCEDECFAAGFGFEBAGHEHEHEGDBDFDFBEBDBDFDBGEHCAAGHGHGBGHGHD,False +644,23.0,23.0,24.0,17.0,10.0,17.0,18.0,14.0,BGGGGGEGBACCECHCHCACDBAEFEFHAHACFGGADDCDCDCDGHGCBHBAAFGFGFABBBBFBHGFAAADADCDEACDEACBHEEFCCHCHAFBCHGEGBFDFHEBBHBDBCHDBDBGFCFBDCGFGFACABBBAAAAAFDCDC,False +645,19.0,20.0,19.0,12.0,21.0,19.0,19.0,26.0,BCHEHEABABAHAHDHBEDEAEGECEBECAHDGCFEFCHHAHDHDHFBDACABGCEBHBCFHGCCCAEEDAACABBHGHGHFHBEBHDECEBDBCBFEFHHHGHGHGHFHFBDGEGACEFDFHFEFCGGGAEFDFGCGABFFCFCGBGAGFBAEA,False +646,24.0,19.0,25.0,16.0,26.0,22.0,27.0,28.0,DADGFHCDDBDHDHGGAEECHHHFCAGACFCFEDCCECEGFBFBCBGEHEACBCBGGHGAGFHCGCGEFEDAHAHFHEBBBHHAAEAECBGAAFBGBHBHAAFEEAECEGHGFCDCHHHHBDFGFGFGBEAFHFDAHAHCBCEHGHGFCDGDGCGEFABDBFBAAAHADEDEGCGHECEFEFECECG,False +647,19.0,19.0,11.0,23.0,12.0,13.0,15.0,22.0,FGFAADEGEAEADGDFHAHBHDGGGHDFBHBDDGDCDHBHBHEHECEDBDBEBHHDHEABCCGFAHGGEADAGFDAHEHDHDCDGDHHEHFFFGEGBDCACACDFDHBBBBDCGAAFAHABABACACFDFBBHB,False +648,14.0,18.0,21.0,17.0,4.0,13.0,14.0,14.0,HDCCBGAGBGFGFHCCACHCGCBCBEDEBCBDBHFCFCFGAGACBGFDFBHBADAGHCHBHFCACDFDBABAEGCHHDBDCFBECGCGBDAFFGHDBDBDADADACFDADCHHGH,False +649,18.0,10.0,20.0,21.0,15.0,23.0,20.0,19.0,CDCFFDAABAFGFDBHFHGADADAHGHGBDFCHHHCDCHAHADCDGDGDGCEFGFCECFCFCGCAAAAEAEDBDBFFHHHFECECGGEGAABHECFHDEDGHGAEADFFHGDGDGEEBDCFGEHFCGCECEDDFFFFBFBCBHHAG,False +650,2.0,8.0,12.0,4.0,7.0,2.0,3.0,2.0,BECADGCCCCCBCBCBDGGFECECDBDBHECEFABHBCEE,True +651,23.0,17.0,14.0,13.0,18.0,7.0,9.0,12.0,HGFCACACFCDEEAGBGBADADABCGDAEADGDBACFHBEDAABHBHGHCAAEBECECACEDECEGFGAAHABAEAHDHABABADEBCFCFBEEEHEBFBAEHEHDCDBGBHD,False +652,9.0,5.0,7.0,3.0,3.0,4.0,7.0,7.0,FHAHAGGGGHGCGCEHEAFAFCHDECHBABCFGBHBACDCDAABA,False +653,17.0,14.0,10.0,12.0,16.0,15.0,12.0,13.0,FFDCCCGHBHEFBAEAHDFFFHBBBBGAFABABAEADAEFCBDEEHFDACHCHDAFCFEDGBCBCBEBEGGGCHHDDAGAEAEDEDEBEHDHAHEFGFGFGHGAAEAFG,False +654,18.0,23.0,28.0,27.0,18.0,13.0,30.0,25.0,CGCBCACGBGHACACADFEBGBCAEHBDBCHAEDGDFDCCAEHDGDFDFAFBGBGEDCFBFBFDAHGCCCBGBHEHAHGGGCECEHEAGCGDGDHBBDGCECHAHDFDGEGAGDGEADHCACBGBCHAHAGBGHHCHCHGEBEAEDECHBGBGDGFGEGHCHBDDDCDHDFDHCFEHDBDBF,False +655,15.0,11.0,8.0,7.0,7.0,6.0,7.0,13.0,EFAFACBEEDCAHAHGEAEFFHBHBFBFHGAAHGHGAGDCBHHHABDBEBAGAGDDDADHBCBEACHCACACHB,False +656,23.0,17.0,14.0,15.0,23.0,23.0,21.0,14.0,DBBBEEGCGFABAGAHAHFDEEHECBHBFBEAEADGDACGFGFCFDFGFGFGBEBEDEHHCFEHAHAFAHEBABEDEFGFGBGAAECFCHCEAGDGDCBCAFHFDFDFCFEEEEECFDBGGGAAADBGBHDAGEEBHDAAAHFGCGFAFC,False +657,22.0,13.0,20.0,11.0,19.0,20.0,13.0,19.0,AAAEEECFGGCCCDBDAFHFAFCCBAAHBBBEBFBAGCGEGHCAEACDCEADBDEAFCDGECEGGAGABAHAEBHHHHHCFCFEHCHFHGHCHCFAFDFDFDHBEGEFFFFAEAECEDEDHFGABFEGCHCHAHABF,False +658,13.0,8.0,9.0,8.0,6.0,14.0,16.0,11.0,DFDAACADGHGFECCGBFFFHEAAFACAGFHCGCFAFDFBBHHFGAGABABAGEFEFGDEBFBDBGACHCHCHGDGHGHGEGDGH,False +659,24.0,22.0,11.0,20.0,12.0,19.0,20.0,10.0,ECECBBAAAFHDHDHCBGFGFACABAGGHADBEAFFDFDFDEGCGCBBBFAGABBEDGGAGFDAGHGDDAEABBGBHDGEBFBHDFGCBCBEBFDFDADADBBFEHEFEFDFHFEGDCDCDCGBGAAAAAGAFAHBGA,False +660,9.0,8.0,11.0,8.0,16.0,14.0,26.0,11.0,FEGEHCHBGBGEGHGHGEGHDEBHAFACGDGFGACHHGAFCGGFEHDFDEEGBGBGFGFGCCECFAFDFDHBGDAAHAGEGDGEGFGAGEBCCCCBEEGEFEF,False +661,21.0,16.0,26.0,12.0,16.0,24.0,13.0,16.0,AHBFGAHHBCBABABCCGBEFACECGHGFDAHHCCECFFFDFAHACACBCBGBDFEFEHEDACAEDEDEGEGDGBBBGCGAHACACEFAFDFAFBDACAFFHFCFCAGEGBFDFBFEGCFCBCFHACADDCHFHFCECEHHHCE,False +662,19.0,21.0,19.0,34.0,20.0,23.0,22.0,19.0,AFAFBGBGBABGDDADCFCECGGEAEACHDHDEFCFDFDECHHGDEDEGGFEBBBBBEFEDDFAHCBEDDBACDCDAHAHGHDCFCFDFEFEDHCHDDADBGCABDHEBBFBDCDHDEDEABDHEBFBCEAGGHFHEAGFGFGCGDGFGDGAGAGABFBFDDHDCDHHGHECDCFAF,False +663,30.0,32.0,21.0,26.0,25.0,15.0,23.0,18.0,GBDHGHGHGBGFGABAEEDBCBCAHAEEDFDADEGCCCGHDBBBEDHGGFCBBHEAACDBGAGBGFEAAAAAABADGGBGCDCFCFDFCBHAHBBBHBHGDBDEHBHBHBEAABABDDEAEDFDEBEBECEGEFAFCFCADEGCGBABABFBCEADAEGEGDCDGBFHAEAEFCDDHEHAHFDCDEDCAC,False +664,14.0,12.0,16.0,18.0,20.0,25.0,19.0,23.0,GFFDFGFDEAHBCEEHCFEEEABFGFGHGAGAGCGCFDBDBDEDEABABDBHFCFHDGAGEHEHEGDCDCFAAGAEEHFGFEDCHFHGGEHDDGBADDGHFHEHEHECFCFCDCAEFFFGFGCBHHCCFCFBFHFHEDADHHHHABB,False +665,1.0,1.0,5.0,0.0,2.0,0.0,2.0,0.0,CCCBGGAECEC,True +666,13.0,18.0,8.0,9.0,12.0,13.0,18.0,15.0,FADABCFAFAFGFGFBCBGGGFGDCDCABDHDAEHEDGDGEFFHCGEHHFHBGAGAHEGEGABFCGBGEEBEHFHBHBHBHBFBHCABBHGEEDCDBABABHGGAE,False +667,12.0,9.0,6.0,10.0,3.0,13.0,8.0,9.0,CBCHGHFADHGAGBCFDFAADDFCFHDAAAAAFCFEAAFADCDGDGHFHFHGBFBFBEBHGHGBBDFDEB,False +668,25.0,23.0,24.0,17.0,11.0,21.0,16.0,12.0,GDAFFFFHBBGCACGCECBHAEDBBFFFBCBCACACGBABEBEDDBFAHBHDAGAGBGBGAGBGAGEDBAFCCDCGAGHCDADACAEDFHACBEAACFDDBDBHBDBDFFFCFCFCFCAAAEDHFAFHCHCACHCGAGFFCEEBEBGDH,False +669,3.0,6.0,1.0,5.0,4.0,4.0,3.0,1.0,EABGBEBGBFBGDFDFDADEDBFHEAC,True +670,5.0,9.0,11.0,15.0,8.0,21.0,12.0,11.0,DFDCHCFFDHHAHACGGFBDBDCDCDAHEFFFHBDBDBEECFGDGHGBFCDADABHBHGGEGCCFFFFFDFHEBGCEFDFGFEFEHDGFGFC,False +671,9.0,14.0,11.0,13.0,12.0,14.0,11.0,23.0,HDHCHCFCFCHCFCDADADEHFHBAEGFGHCEDHFCCDEHAHFEBBBADCHHHHDHBHEDDDADHDBGBGBCBFHEBEFGBGHGFFHAHGHBAFAGBEFEBEHEGFG,False +672,3.0,4.0,0.0,0.0,2.0,6.0,4.0,2.0,HFHFAAGEGFGFABBFGFBEB,True +673,17.0,21.0,20.0,5.0,12.0,13.0,17.0,15.0,BCBDBECHCAAADCGGGGFBABABEBCBCACAGHBHDHBFEEEEAABCBCBAAHBGGCGBGHGFGAGFFCHGHGHBABFBFHCHADDFCCCECECHHEAFBFBCHHBCEGGCFAEAEGFF,False +674,14.0,34.0,17.0,24.0,19.0,23.0,30.0,24.0,BBGEGHHHEHEFABDCHCFBDAGBBBBDBFCFCFAHHEHAFGHGEGEDBDBDHCFCHCEDEDEDGCGCDDDGDGAGAGEGBHHCHADFDBBBCDDACGHGEGEHBGBGHFEFGFBBDBHBFBDGGCGCDFGCBBBDADGHFCFADGEHFCFAFGBHFHBGEAEBBBAFGGDGFEFBBHEHEBABF,False +675,22.0,22.0,20.0,24.0,22.0,17.0,36.0,34.0,CHGHGHAHAHCECDBGCADHEEGECDGBFCCHCHFGFGBBHFHFHEGFGAGCGCGDGDCBFBFEFEHEDECCHBGBDADHFHEBDBGFGBAHGHGEACGGAEAHGBDCDGDHFHBHCECBDHGGGGHBBDFDFHAAAAAHADADHGHEHAGFGDGAEDGDEEBHACFGHBHBHCGGGCAHEEAEHEFDDDGDBBBAE,False +676,5.0,3.0,7.0,7.0,6.0,1.0,5.0,6.0,EHCHEBAGEGDGDCCCCABHEGBAEDEDCDFDADAHHCHG,False +677,14.0,12.0,18.0,20.0,14.0,12.0,11.0,15.0,CCADHGFACAHGHDDDDDGFGHBADGBEBCCDDDADADABBHCFCFHBHGAGEEEEEEEGEFHCDFAFCCADBDCDCDCBBBBCHCBDAGAEHDHAHAEEHEHFFCGCDFGECFFH,False +678,20.0,18.0,16.0,16.0,18.0,22.0,18.0,25.0,DFFHFHFGFBADAGHCBCAGBCBFGFACBEFEGABBBEGHHFHFDFHEEGEBECFCEBEGGADEDEAEACHCHABEHAHAFAHAHAFBFAECECHCHGHAHBHCHFHGDCHGHEBDBDGCADEDGGFBFGDBDCFFEHDFDFDGDHCHBGAAA,False +679,13.0,13.0,11.0,11.0,12.0,13.0,13.0,10.0,DADAHACGEBDGEGEDEAACHFGEGEGFGFCFAFEBCBFEFHCCFCHCHEHAFFDBBBHGCEBGBGAAHFHGHBFDEGAGBBBBDDADADEDACFC,False +680,21.0,9.0,11.0,23.0,10.0,11.0,13.0,22.0,BHEFDAEAEGGAGBCHCBAAHAFDFGGGGBHADEDACFCFAEABHBHBAAADFFACDDDHDHCBCFHDHCHGDAHAHDDDCDADEHFFAFDEHHDHECDADAGAGBHHGHEHEHCDGDGD,False +681,29.0,26.0,19.0,24.0,29.0,20.0,27.0,23.0,AAHAECBCBAADACAFFGCEADCBGHGFEFEAEDEDBDHDEBHDHAACAHAEBCBDFFHFBFBFBFGFBEAHBCAEAGAGBEEEEEEEEDCABFGFBDHFAFAGBGHGCGEGDADHDFGBCBHBHACEBDADEDEDGGGGGGGBHBHDHCFGBBEHCCAHHFABDCGGECFBAHGDGDCEAEHECEGHDFDEDGAHA,False +682,12.0,18.0,15.0,23.0,25.0,24.0,20.0,8.0,DADHGFBFDADAEECECBFDHDBCBABAHFFFFEFEFBFBFBEDFDEAFCCHEBBGECCCCFAGBBDBGCEEDHGGEGEAEAEFDDDGDAFEGCGCGCFEDDGDFHEDGGGGGEBEDFDEDHBEBDCCEFFFEFEBABFGAGHGD,False +683,10.0,19.0,7.0,19.0,5.0,6.0,8.0,11.0,CHCGBDFEGADBBBBBEGHAFAHBGFACAGAHDBDBDADHDGDBDCCCEDDHDADADCDBBBHBFBDBDFDADEHHHBHGGEFBB,True +684,10.0,3.0,3.0,5.0,2.0,4.0,6.0,12.0,DBCHHBHEDEGAGAHFGGHFAAAGAGADBCHAHAFDFDACHHHHH,True +685,10.0,19.0,16.0,24.0,9.0,16.0,18.0,17.0,DGDFEBDHDADCDBDHFHFHAGCHCHAGEEBGBGBAFDHCBADCDHAHEEABDDFDFABBCDDADCDFDFBBGBGHECCGCGDECGDBFGGEGECHCGFFBFBDGFHBHBHBCGCGCGBDDDFHFHFHA,False +686,11.0,7.0,14.0,17.0,14.0,20.0,12.0,14.0,HDHABCEFFBEHCGCACACBHBGEGEFFFBGCECDCDEHEDEGFGFDDDDGDGAHDHDADADFFFAHAEDHFBADEDBCCGHAEEECFFEFCFHFGCGAHDFGFHFCFH,False +687,19.0,24.0,19.0,21.0,13.0,20.0,17.0,22.0,GBGCDCDHFCAHAHBFFDCAGBFBABCFFBFACBGHGHBFFGHDDADHFHFHBGGHGAFDFCGAGEDEGEADDFCBABFBABAHEDEGFGFCBCFDDADACECEBEBCHCACFEGCHBBBDDDGHHDHAHAFABDHEHEHEGEDBABCBDBHCHC,False +688,11.0,6.0,12.0,7.0,7.0,10.0,7.0,5.0,CCBGGGGFABECFADHEACFCFGFGEDFCFAFBHBCBHBDCCHCAAAAAEDDDDAFCFCEGEAEH,False +689,1.0,5.0,2.0,2.0,0.0,1.0,2.0,2.0,DHDGFGCBBBBBCHA,True +690,15.0,19.0,20.0,21.0,26.0,23.0,15.0,18.0,GBGBGEFEGECEDHDHDHDHDCGAEACGCFBFECCACGCDEDFDHDFBBBEBDHGHDCBAAAFBHADFBFHFHFHFEDDADEDEFCBBAEEGEACCHCEGACEDECECFFFFHAHEGEBABEDFBHEDEAEADFDCHFHFCGEBHCFFFGBBECGBG,False +691,16.0,20.0,16.0,13.0,21.0,17.0,19.0,17.0,EEBEDECEAEBBBBEHFBFBFDCDCBCBCAFGHGCECGGDHAHCDCFCEHDHDBBFHFGEECBGBFHDHGHEBEBEAEFBAAAAEAGGGFEFCFBABDFGFDFHAEEGHHHGDFHFGCGCGDAAACADEGBBCAHGEGH,False +692,15.0,18.0,25.0,15.0,20.0,16.0,23.0,15.0,DCAGACABGEGHGBBCAEGHHDAAAFGCBCBCGGDGCGCHCDCDAFCFGHGCGCEEEHBGGECACADEDFDFGFDBBFBCDCFCDCEEHEHFDBDBGEGFFBFBFEECHGHBAGABABEHEHGCEHBFDCCGDHEHEGBFAFAECEC,False +693,18.0,15.0,17.0,18.0,19.0,18.0,17.0,13.0,DAEAFACADHDHCFCBBBDFDEGEGEFDGBEFEBGHGHEHGGAFAFAGAEDEBHDADAEAEDEAHGHAHCECEHFHBGFAEAFBCGFDFGCACADFCGCBCBDAHFBCDEBCFCFGECDBDBGBGECECFDDHFG,False +694,7.0,11.0,9.0,10.0,9.0,4.0,5.0,10.0,CDDDBBCGFGDHDHEHBHEHEBEBEAEAFHDEGEDHBAAFHCBFEGCBCBCBAAHACCCGBHDDD,False +695,9.0,7.0,7.0,14.0,15.0,8.0,16.0,16.0,DFDCDCDEAHDDDBHHFHFCDCHCFBAEEDGAEAGGFGHAEECHGHGHEEGDGFEFEDEGBGEDDBHBHGEGFAHAEAHAHGBGHGHGDECB,False +696,24.0,23.0,24.0,22.0,20.0,19.0,26.0,26.0,ADGDAEBHCGCHCEADABGBGBFEEGFAFAFBFGDGDHHACDCHFACHCGGHGHDHCBGDHBACHBHGHGAAEBFAHGGDGHGFGDCDCGCDCAEGGGEEEEEHDFDAAAHADAFADEBBBHEHECACBEEEBABFCFCFCECFCHBHBAGABHHFHBHFCDEBCDGDFDFDCBFBCBEAGDGH,False +697,19.0,24.0,22.0,23.0,29.0,24.0,25.0,34.0,FCFEAEAHCGEDABFEFDHCHCGCGCFHABDGEGFGFGBHBCAEEHGBCBCBCGHDHFHABGHDHCCCAADDFDHDCDHFBEHEHEGFBBHHHADEEEBEBFACHHHHGHGABBBBEDCBBBEDEDFFFFFFHCHDAEFEGDGHFBDGEHHGFBDADECEDEDGFBFEGCGHHCHCHGHEFEAAGAGEGDGCAHAEAEBD,False +698,13.0,19.0,14.0,18.0,18.0,16.0,11.0,16.0,BDBFFDFDFGGHAHBHBHBHFGAGAHDHBEBDBHBFBFHCBEGEGEDCCCCBGHECDCACDBFCEDBDFDFDHDFEFHFHEHEFEBABDEHBCDDHAAADEBAGAEACGEAEFBCEGEDFCCAGE,False +699,20.0,17.0,18.0,13.0,20.0,22.0,16.0,23.0,ADHHHHFDFBFAGADBEFFFEFEGCFBDHCAEABAEAEBHFECCFDFHHHHHFHCHCHEHEAEBGHACABFCFGAGDFDFCBHGCFCBCHDEDHGHAFDFAGECECEFAGCDEGEHEAABCBGBGBGBABGEAHGEAFHFGCECADBDB,False +700,7.0,10.0,13.0,7.0,8.0,14.0,8.0,3.0,FAAEFBFCFBFBEDGHCCCCCEDEDFHECDBDGFGFADGBEFCFCGAAAHEDECACFBFBGGGFCFCBBB,False +701,16.0,27.0,21.0,29.0,23.0,22.0,14.0,18.0,ABAEADACBDBFAFDCGBDEDBBFBFADHHAABHDGABACDBDEAFCHCECHDDACAFDFDFEAEDHDFBFBFCEEBECDCDHABFBGEGFHFHGBDEDEDEDCDHDHFAGDGHGHGHBCBCBFHCEBEHCCDCBFBFBECFDGGGFCECEDHBGBCFEEDGBFBEHEDE,False +702,22.0,31.0,14.0,20.0,15.0,20.0,18.0,12.0,GHADBDAFCHAEBDBDBDFDEAAABADEDCAABBEGEGFGEGFDFBFBAEGBBCBCBEGDCDAHCHBADADGFBFBHBGBDCFGDGHCDCFCBEAGFGFHFEBECAFBFBHBHBFBEGEGEBEDAHABADABBGBCAAGDFBAGHCCFDFHF,False +703,21.0,26.0,13.0,16.0,14.0,14.0,14.0,17.0,CHABCBFGFAABAGAHAHAHACBDFHAHEHGCACDBEHDGBHCECEHFAACABHBABABECGBGAGEFCGDEFHBBFAFHFHAHEBEFEGBGBEBEDDDDDDDAHHCBCDDGEADABGBDBFGFBFBFBGEDCBB,False +704,1.0,0.0,1.0,1.0,3.0,1.0,3.0,0.0,DEECEGFGAG,True +705,7.0,6.0,9.0,6.0,4.0,3.0,8.0,5.0,AGABCBCEHFACGFHHCHEACADDDDGBGBGBCEFHBDEDACGCGCGA,False +706,6.0,5.0,9.0,7.0,4.0,10.0,8.0,4.0,BGHGEDCHCHCGCFFGDGDGCBCBAADFFAFEFGAGADFHBAFCBCEDEFCFD,False +707,10.0,10.0,4.0,9.0,12.0,8.0,9.0,7.0,EECFAEAHAHAEAEBEHFDFDAGCDHBHGGEGEGFDFDEBADDCHFDDBFGEGBGBEBEAHAGBFBABC,False +708,11.0,14.0,22.0,17.0,26.0,26.0,22.0,25.0,ADBFFHCHCHCDGFCFBHBHBAGACHDFEFHCBGECDDGEHEHDHEGEGEGECBHAECDHDCDEEFHFDFDABHGDEHEGDHDGFCCCHCHDHDHBAEEGEHEHGGGBBFEFEDEFHFCFAEHECGCAFFFCFBBCAFBCHEEGEGFFECGCGFGFGFAFAGB,False +709,20.0,25.0,16.0,17.0,13.0,14.0,18.0,22.0,CDEHBHBHAHBHBGDGEGBACAHAHGBGBGBAAAGFDEEBGBABABFGACACHGHDFDADHEFDHHECFDACABGHFHDDDAEAEDGDCDCFCBCFHBCBEBEBEBFCGCHFEGGDDBBBCEHGDACABGHGAFHHHBFAFCFHB,False +710,30.0,23.0,16.0,22.0,21.0,35.0,15.0,23.0,FAFAFAFEFEHAHAEBEFDFDBDHFCEAHHHHBEFDADHEHBCCCADEHFHFHFCGGDECGCBDBGAFAFBCDAHADBECEFHCBCBAAAFAGBFADDFDFHBGAAEABFDEDFHAGAHAGAGEGHFEFCABAFCBEBEBHFDDDFDADEEEFBFDACEGFBDBHBHBFGFBFCFGGHAHAFGFC,False +711,6.0,6.0,12.0,7.0,12.0,9.0,12.0,10.0,HGEDHDGCGCGBHBHGCFAGABCBGGEBCHCHFGDEEEHEHAHFHCGDFEFAFAFDECECDCFABCGEGFCEDE,False +712,23.0,31.0,32.0,27.0,25.0,14.0,31.0,14.0,CGABCFCEHDFDHEHBDBDECCFBDGHGAGBGCHCBAEHEHDFDBDCEFGCGCFBAGGGEFEABFBGEAAAAHAGACACECACBGDGDBHBCFGHGBCAAAFBDDDDDDFGFCECBBEEGDADCBEAEAFDGEGCCBCBCBDGCECGCGCGCECECBFBDBABDBDHDCEHEBECGAABDBGGGDEEGEBBAHGGDH,False +713,4.0,5.0,5.0,9.0,4.0,5.0,6.0,6.0,BEFEACAHDHDHGHBDCHCDEDFDGDBEFGDGDFAFBBGACHCG,False +714,18.0,19.0,22.0,14.0,25.0,27.0,18.0,19.0,GEHFCECFCAEFBFAHBCCEBFFEFECDADEDEAEFEBECECGHGAAADAGHBFGFAFHDEABBDGDEHEFEFDBCHEGCCEFBFEHHHHGHGCAFAFHFHFGEHEHCGDFEAEAGFFBADAFFCFABGBABFBCBGBGCDCDHFHCECECDHDBGBCBCGG,False +715,17.0,8.0,11.0,12.0,13.0,12.0,12.0,14.0,BAGDHBHDHABAEGHFDADFECDCGCGADHDHDHABCBHGAAFBFBEHEAFCFAGHEBCDFDFDCHCHCADAEHEGEAEGCGCFEHAGGFAFEFEAEAG,False +716,16.0,17.0,24.0,24.0,21.0,17.0,16.0,24.0,FCBCBHBCBCECDCDAFFHHHCHDBEFABAEDEDEDECFDGGGAEFEFEHCADAFACEEECFCGAEDEDGHGDGAGFBHDHFHCCGEGBDHGEBHHHEHACAEGFDFDHCECBADECHHHBBBFBFBDADCCFCDCBCDEDHHCGDDAAAHBHGHGDGF,False +717,30.0,23.0,30.0,24.0,12.0,21.0,21.0,16.0,ECEDACAHEHCACECDCGCBHAGDFACBCBAFGFGBACCCCACFGEGFHHAHABGBEFFBFDFCGABCDCBBBBBAADADGDFDFHFDCDCHFBFAAGAGAGAGFCCCHABGDGDBDCDEBHDCDCDBGFFHHGBEAAHAHDFDEDAHAGDCDBHAFGGGBABDFCACACBCFEEAE,False +718,8.0,9.0,11.0,13.0,10.0,18.0,7.0,15.0,BHBGDHDHDEAEFFAGAGABHFFFADHDHDGAFCDCAHBDECFAHDHCCBGHFCECEHEFDBDCDGEGDBHBECFCFCFHBEFFFFFHFHE,False +719,12.0,23.0,32.0,23.0,25.0,25.0,24.0,32.0,ACHDECHBHFHGHGHDADAGHCCEBEBCCGHFFGFCBEGCCDDDBGFDHDHDHGFGBCFCGCDCDCDCFGEDBDBEGGCFEFEHEBEHECBFDCDGBGEGBGEGCFEEECGFGADCFEAEADBBCECEHEBEDFHFCFCAABGHHHHHFAFABCCHCFCAHEHFBFBFHCGFBDGDEBHBHCECGDBAFHHHHHDH,False +720,9.0,6.0,1.0,2.0,6.0,3.0,3.0,2.0,AAABABDBGEHAGABCBGFHEAEDEAEFEFBA,True +721,4.0,4.0,5.0,4.0,1.0,4.0,3.0,0.0,BGBCACGCDDFDFABACECBFAFDG,True +722,16.0,8.0,13.0,19.0,18.0,17.0,9.0,17.0,DFEFCHCGADHDEDAHEDEBFHFEFEAEDEDHAHADCBAFACAHEHDCGCGCDCDHDFECEBEDEDEFGGABFBFGCACFDFAFBDGFHCADHEHEGDAEAHHHBHFHFADCFEBGA,False +723,20.0,21.0,15.0,7.0,15.0,20.0,22.0,15.0,AFCDCFCFGFGAGBCACBHAAFGFBBEEAEGHDEDBHBHEHBCGEGFACEGHGHGCGEGECAFFGEGEGEGBBFAFDCBCFCFADADBHEAEHGBGHGBAFAHCBADFBHBCBFAFHBABABAFABHFGFGEHCG,False +724,22.0,23.0,14.0,13.0,20.0,26.0,11.0,21.0,DEBABADADEGBGBEBHBCCAAEAFFDAAAAFEFAFGFCFCBHBCFFFCFBFDFEHHDHCHCFDEDHBHBGAACEFAHHFABAEEEEGBCHCECACGDHAFDFHFHFEFHAGGGFCHBBDBHBEBFBFHHEHBBBABEEFGFEDGDAHAE,False +725,21.0,25.0,25.0,29.0,21.0,32.0,25.0,20.0,FGGGCGEGDFAHHHCCCGAEABFBEBDBDHDCDEDAFGDGAEFCFCEAEADABCBGGGGGCDCDCFFFEHACBCBCGCFCFDBDFCFAHBDDFDFBEHEADCDFHEHFFEGGDGFHEGEBBBDHEAEAGAGAHBHAAGAHAHDDCBCFFFHFEDGDHDBFBEAHBFBEDFCHGFGDCFEGCHCFBFDEDFDABBFBCB,False +726,16.0,20.0,16.0,17.0,10.0,18.0,13.0,17.0,BBBBGCACACBFBABFBCDHGBCHCBADABFCFCFGAHEGBGEEEFDGDFAGAGCBCEFHFHGHFHAHFDFCHAHAGEBDBDGDCDCHFHBDDADCBFADEEEHHDGFGFHADEDHFHCBCBABADF,False +727,10.0,29.0,22.0,26.0,22.0,17.0,21.0,19.0,BCBCBCBDAFHFCECDCDCBHECFCGAGDGBHFDGDGBGBEDEDEDBCBAFAGHBHDHAADBDCGFGHDBDEGEFBBBCBEBEHECDHEGDADCDHDBBGCEHFGCAEAEBEBFBHADCECFCFEDGHGHBHFHGHBCFGBCEFDHGBGFGEBEHEFFDDBDECGD,False +728,11.0,13.0,13.0,11.0,13.0,20.0,15.0,18.0,EFFFEBCDCHCAAAADFHFHGAFDFHFCFBEBGCGAFBCACAHAHEDBBGEDEDCDGBGFGFGCHCFFDHEBBCGGGGGDFHAHDHBFFCHHDHEHEFBHBHECAGEGEFEFBH,False +729,26.0,25.0,13.0,24.0,26.0,16.0,21.0,19.0,DBDFABGGFGHEHAAAAABFBFBGBDBABAGEGCGFEEGEBEDHAEDCHABCDEFAFAGDHHAHADAFAFGBGAGHBDGCHHHBFFEAEDBDBEHDBBEDDHDHDCBCBEHCACDHFCGAGEGDDBEBEBEAGAEADABAFFFFEHGCGCEEEEBEGDHDGECEABHDCD,False +730,16.0,17.0,13.0,13.0,6.0,15.0,8.0,16.0,CCHDADACCDBABEBHDFBEAGBGFCECHBAAEAEDEGCHCHAFBHGHDBDADAFBDBGBHCHCAGAGHHCDCFFDFBFBADFBFBFHAAADBFCFGFBFHHHH,False +731,16.0,23.0,24.0,23.0,24.0,17.0,32.0,25.0,FFFFFFFDDEDGGHGHGHGFDHBCACGEGEBEBECFFBFBDECCDEHCFGEACHDHDHCFDHEGABHEGBGEAEHBAGCGHGHEEEDEDHFCGDGBAHAGAGDGBACCEAGAGAGAHFBCHCGCDCHCHBDBGBEBGCDFDBCBHEHEHGCGHBCBCGCAADDDGHGBDEDEGBBDFEAEGBCH,False +732,2.0,3.0,2.0,0.0,1.0,3.0,2.0,1.0,FCFGFHCBGBAEAB,True +733,6.0,2.0,3.0,2.0,1.0,4.0,1.0,4.0,BFFCHCHCHAAFADBGFDAHAEA,True +734,5.0,4.0,6.0,8.0,4.0,8.0,3.0,7.0,DGHGDEDEFAFBFBDDEAADFDHCHFAFBDGHHHHCCCCFCFBEA,False +735,11.0,7.0,8.0,6.0,4.0,4.0,8.0,5.0,CHCACAGAEDFDCBHDHFHBCDDHAFGGGCACAGAGBBBGBEBDFAAGAECEA,False +736,20.0,16.0,16.0,26.0,10.0,23.0,15.0,12.0,BDBHCCEBDBACHCDFGFCADHDFDHAECDAGAGCFEFCFEDDDDDDDCFHHADFDABEGGGAGAGADABAFCFAFDBEBEGACADDDHAHBECHDGBGBDDEGEGDBFCFHBADGHGHFFFBFAFAFCFCFBFCFBA,False +737,23.0,11.0,24.0,14.0,10.0,9.0,22.0,11.0,FHADCDEAAAABDBHAFADADFCGGGHGAEAHCGDDCDCDHAHCGGGGCACFCBCBCGCHAAFAHEBADAECGCGCGDGECEDGBFCDBAGACFHAEGCGEGBGCECHGGFHFABABABCCDCE,True +738,26.0,23.0,28.0,29.0,22.0,16.0,18.0,26.0,EHDFFHFHEAFFBBEHDBBBDBDCGEGEGCBCDGHAHDEDEDFAFGCCCACBDAGAEFHFHADAFHCDCDBDHAAAAAHCHCHFHFEFHCHFBAEDHCBCBCBEBDADGDAHAGACACBHEDDDEHCHBDECCGBGBHDCDHDBGCCBGDGCHHGFBAEGEAFACACBCEEEEHEGCGAADAEBGDDD,False +739,8.0,2.0,10.0,6.0,9.0,6.0,10.0,6.0,CGBDCDCHHEEAEACAEEGFHFDDDDFGFEAHCCCCCBFGAGAGEFAGAGHCEGEGH,False +740,11.0,8.0,17.0,13.0,9.0,9.0,18.0,8.0,BGAGBECGDGHFHBHBGDGDGCCCCCCFCFDFAFHBDADGDGBBCACAFEDGDHCECHAEEEBDCGGAGFGCGDAAEDEACHEHCCFGAGDGF,False +741,4.0,2.0,8.0,8.0,5.0,1.0,3.0,4.0,CECEAEHCCADDHDHGGEBHBECFCDDDDCDAGAC,True +742,2.0,9.0,1.0,2.0,5.0,5.0,1.0,4.0,CBHEDBAFFDBABEBEBHFHBHBFBGEFE,True +743,18.0,19.0,21.0,21.0,22.0,11.0,26.0,21.0,EAACDDDHDGEGBHHHHEBEBABHEHBFGCGDGEGCDCDGGCGHFFDFBBGACADADHHADCDGDGBCCCBEDECAGHGHBFCFEDEDEGGCBEFEBEBEHADBHBGGGADADFGFDAEAGBBHGDBHGHCHCACACAEFEGHCECEAFHCHBGEGECA,False +744,31.0,23.0,20.0,24.0,21.0,22.0,28.0,21.0,DADEBEBEDADABCBFGGGGGHGHAFFGBGBGCGDGFGHBCCFDEHEADABAGGBGFCFCAGAHHEDBHBHFFEHAGAGBCDFAEBHDDDDEHHACFBHDGDGACFFBDBAAADAHAHCHCEGAHAGEEEEEBHFFGADABABEBEBCDCBHFHFAADFCGCGBAADDDFCCCHFEFECEAGACAGDGFE,False +745,5.0,11.0,15.0,7.0,10.0,9.0,7.0,16.0,EFHFBCACFCEHBCBABABCECFHHHHFEFHCHCFCBHHGGEGEDDDHAFGEGCBDDDHEEAFBBCHCHEHGHBCBCDCG,False +746,1.0,0.0,6.0,5.0,2.0,2.0,2.0,0.0,GDCDCACECEDFDGCCFD,True +747,14.0,8.0,8.0,12.0,14.0,15.0,12.0,12.0,HCHDFEEGCBCDCAEEEBEFEFCABABFBFDEGFAHEHAHCHGGFCFDEDAHCHDFDGDGABHEAAFAFHFEEGAGDDFBHBHGDGEGAGAFAFD,False +748,23.0,22.0,15.0,27.0,27.0,24.0,31.0,19.0,CFEFAHGBGDEAEBEAEBHBDDGBFAHCGFHFHGEGFAFADBEFHBEBCCFCGEGADBBGGCGBGHHBEGEGABBEEEAHAGEGFGAGFCCBFAGBGFGFGFADDBDBGBFEFGFAAAABHCDDDDDDFDFHFHBGDEAEDDDEDEGEDEDECHDHCFAGAHAEAGADFGHEHDHCCGEGEDBDFCHC,False +749,18.0,23.0,17.0,19.0,17.0,23.0,21.0,21.0,EAADEDBDBFBEECFCDEGFDFHBDAFFBCCCGCHCHAFAFAGGHGECECEBEGAGDGDHEFEHCBAADAFBFBHBABGBGCFCDHFBDEDECFGFBCHHDBBCHDGDFFBFBGDGBHHAHABADADEEGHGHBHFFFFEFGCGCDEHHGHGAAAGBBH,False +750,26.0,15.0,24.0,31.0,22.0,18.0,27.0,36.0,HFCEEEDBCEHFDCDCDGDAHEDGBCCDCGHDEECFHFAFADHFCGEEAEHEHECGABAHFBFBFDACBDBDCDHDHGFBFACAHAHABAHHHCDGHGHGHAABFHFGGHADDDDDADCDEDGDEAGGGGAGBGACCHBHBFDDEEHEDDHCHCHCHGFGAHHHBHFGCGHEEDEDFBAGHGHCECGCAHAGFEADAGA,False +751,2.0,2.0,6.0,6.0,5.0,4.0,2.0,6.0,DCHAHGHCHCEBEGDFCHCDCFEFEDEFHADBD,True +752,12.0,16.0,4.0,9.0,13.0,13.0,11.0,4.0,EBEBDBDBFAHAHADAGBCBFHEEAFAEEBEFGFEFAAAGGGBAFCFCFDGEBBBBBBGAFEEDDDGAGFGCEFEGBDDFHB,False +753,20.0,22.0,13.0,25.0,23.0,25.0,27.0,11.0,DBDAFFDEDEDEFEFDBCFFHDDEEEBEFDFEFEGBGCHCEBEHEHAABAGGGDEAFDFBGGGDFAFAFACHEEBHACBFECCGGGGGGFDFAFCGEGEFHBDBACAHAEFDBDFGABFBEGCGCDHDHDGDBDBDGCFBGCAHGDGBBFAFABEGEGABADADGB,False +754,13.0,24.0,24.0,21.0,25.0,16.0,20.0,11.0,BHBDGCGFGFGFGHGHBFGCEEFEFBAHEHEHEBCDEDEDBBCBCEFECGCDBACAGDGDBBHCCGDAAEAHCEFECABABDGDGCBEDHGFEDEDBGGCACDDBEBCBDFGGGEEHECECEFDFDBBBDCHAFDCBCBCGCFFACAEAEDBFE,False +755,21.0,23.0,12.0,20.0,22.0,23.0,13.0,24.0,FBFBCBFBFECEBHBHDHBBBFBACGBGBDAGFDACHHGCGHFDBHEEEFEAEBEBFGAGAGEDDFDFEFBCAFDFEAEAEDFDBDHECDCFCEAHAFEEHAHGHGHCBDAEGHBDDDBDEHGBAHAFCHGBFHFHEHEADHFHFHFDEBCAAAAHAD,False +756,9.0,16.0,8.0,17.0,8.0,7.0,7.0,4.0,EFEFGFGCCBABHBDDDDGDABBGBFBFEACDBDEDHCGEGBCBCBFDDDEAFABADAHEBADHDCCEDGDBBBAD,False +757,15.0,20.0,18.0,27.0,18.0,16.0,16.0,19.0,GHFBGBCEEAHDBDAHAHEBFFDDDDBFBEEAGBDHDBEGHAHADDEDCFCFBHAHBHDDGDGDECECGHGFGDADEFCFCFDADBGEEBCDEDGABABHBHBHCDCECECEGACCEABFBFBCCHABGHFHFACDDDDDGHECGFGFH,False +758,24.0,10.0,20.0,10.0,13.0,18.0,25.0,18.0,HEHAHAFAHCGCGCHEBGCGHGHGFGCGEABGHGFGHCHEAACABAHACFEAGCECBGGGGGACDFHFAFDFDFDFBEEAEAECFCAADAGFCHHECFHGAGHGEAHFGCCDBDBGACAGADABBDBDCFAFHGEFCF,False +759,5.0,2.0,3.0,3.0,1.0,2.0,7.0,3.0,CFAGGHGHGHBDGDGACEDACAGABF,True +760,23.0,15.0,19.0,10.0,31.0,25.0,21.0,16.0,FGFGHGDGBHACAFAFEFEGEBFGFGFECEDBFEFEHHCFAEACFBBBAFEDCGCEAECFCBBHEGEDEAEFBFGFGADCCCBHAAEEBABAHAHACECFHFEDEABFEDEAEBECACECGFGFEAGAFEFACHGDGAEAEGHHHHGDCBEDEHFHGGCG,False +761,4.0,5.0,6.0,6.0,5.0,5.0,6.0,6.0,EFBFBFGDHCHFEFGGBDAGACHCHDHBAAECCBCDEDEDGHG,False +762,5.0,7.0,14.0,5.0,9.0,9.0,6.0,9.0,EGEFHBHFGFHCEDEBEFACAEAECHCHCHCHBGCFDFCCACBCDHDFGABHBCECDGGEFCFB,False +763,7.0,10.0,9.0,14.0,6.0,13.0,15.0,4.0,FHBHAHAFAEDCDEAEHFDDGFBFBFDGGFGBGBCBFDGDBCGEGECAGAGDGDFDCDCDFGCGEBDGFBACFBFDCG,False +764,18.0,17.0,21.0,10.0,17.0,19.0,30.0,14.0,GFCBGAFBBEFFCGHGEADAHFHEAEAHAHFGGGEGECCFAGAGFFCACBFAFAFGGGAEHGHFHBHCACHFAFDEDHGEGDFBCGCAHGCEBEHCBGBDDCAGBDAGECECACBCBCGGGBBBBBECFCFEFHGDGDGDGEGEGC,False +765,16.0,9.0,24.0,14.0,21.0,12.0,17.0,12.0,FCCCCEGDGDFBEGCBCDDDDCHFGACDHECCCEEAHGHGCCCFEAAADAHGEBEFDDDCDCEAGCGDHEAEAGADAGEFCFCFGFGEAFHEECECEGHGBFCECEBFBCAEBGBGHAHAHAHBE,False +766,2.0,5.0,3.0,5.0,5.0,3.0,5.0,14.0,GCCBCDHEEEFHHEBEHGHBHDHDHAHFGAHDGDGHHHHBFB,True +767,25.0,19.0,25.0,19.0,30.0,21.0,34.0,24.0,AABAGCCCGCDFDAEECGCHBHGHGHDAGCGDFDCEGEBAGFEEEHHAGAGAGFECEHGCECEHFHABEEEBEFEBEFEBCGGGDGABEDEDADGFGFCHHHHDDFBFBAEAEAHGFCFAAAAABAFHECGCDCGFADDBHBGCEHFBBGDHFAFHBHCHFHAGGGGGGAGCGEDEBEDECHFHGBDEDBFGCCCCE,False +768,25.0,18.0,18.0,14.0,17.0,14.0,28.0,21.0,DBBECABABAFFCHGBFEAEHGGEEEHGHGAGADAHGCCFDFDGAFCECECDBBBFBDHHGHEHBHAHGCGFGHHCCFAEAECGAGFHHCEGGGCDCEHEHEDGDHDAGABACCBCBGFFBBHBABADAGGGGHGAGAGAECFBAGAFADAEHDD,False +769,1.0,3.0,1.0,7.0,6.0,6.0,6.0,3.0,EFGFHFCEBGHFBDEDEHEAFDDGDGDGDGBEF,True +770,10.0,20.0,19.0,21.0,15.0,21.0,16.0,16.0,CDHDGGGCGEGECDCDCDABFBDBFBFDFHFHDDBEAEHBGBGCDBGBCHHDGFGCHDHCGCAAHABAFHHBDEFEFCFDFCFCFAHEFBFBGHGDDDCBEGGFEBEAEBDBHCHAEFCDCBFEFEBHCGCBFDFDEA,False +771,4.0,6.0,5.0,4.0,2.0,2.0,2.0,5.0,DBACDGDBBHBHCFDECECACAHAHGBFBH,False +772,20.0,21.0,27.0,26.0,23.0,24.0,13.0,18.0,HHGDAACADHDEDCABDHDFCFDBCFCABDCCCCFFFDFBCBHBGEGHGADACFDGAADDDDDECEHEHDFEBEFCFHFAFCFCFAFCHHHCEBEBEGECECFCHEFDCGBAFADAEAEDEDEFEHEGDAAEBCAEABBFBFBEADGCHDBGBDCDFGGBCBCBEHGHCHBF,False +773,23.0,11.0,12.0,12.0,15.0,10.0,15.0,14.0,HHBEBEDEBGBDFCECGCGEGCHDHGHGBCHAGAGAFAFAHAEEEAEAGBGEGCGAACABBHDABFDFAHADGHFBCDDHAAEAEAEAEACDFDEAAAHFDCCGCHHGDBFF,False +774,17.0,24.0,28.0,15.0,15.0,16.0,18.0,18.0,EFEFEBGCDADCEHBHBHBFBECECBFBFCGCEDEDCCFCGCGFGFACCDFHAHGHBHCHEHECCCGGFCHCADBBBGHHEGCCCGCBHGEGBBBAADCDCDCDADADABFHFAGBDBAHGBBABFEFGBEAHBGCCHFHGDABACAFDEA,False +775,3.0,0.0,2.0,1.0,0.0,2.0,2.0,3.0,AGHGHFDFCHCAA,True +776,17.0,9.0,11.0,6.0,12.0,12.0,17.0,14.0,GCGDABAFGFGCCECFABAEAEBGADHHEHAAAEDEAEABDFCGBADAEHGHFFFGAGFCFDBHBFGHHCGAGHGEGHBHCECEAEAGFCFCBHGHGH,False +777,4.0,6.0,1.0,5.0,7.0,2.0,6.0,4.0,HEFEAEAEDBBGDCDHDFEBAAHEHEDGBBBGGGG,True +778,6.0,7.0,4.0,4.0,5.0,13.0,4.0,5.0,HEHEAFGFAFAFBGBAFFFDEDECBCFGDBEHFAFBFDFHFHGBACCB,False +779,9.0,7.0,5.0,6.0,9.0,8.0,7.0,9.0,DGBEBEDHAFAFHFHFCFCEDEGEDEDGHAFBHBAGAFBCBHFAGADAECCBGEGHHEHA,False +780,19.0,21.0,16.0,16.0,23.0,19.0,26.0,22.0,FFCAGEGEGAHBBEBEGCDFEFCFGHHDHDHDBEFFAGEGAGAGAHEHFAEDBACCCEDGBEACFCFEDEABABABFHFBGBGAGEHHACBCGCHCHGHEABACDBDHEGFGEADHFBDCDCEBBAGHGHEHEHGHDHDGDGFHABECEBDGGFGBGBEFFF,False +781,15.0,24.0,23.0,18.0,23.0,14.0,17.0,21.0,FEAGCCBABABAFAHCDGHFCAEGBGBGHHBBCBFBABAEDEDADHFECGDGAHEBEBECCGCHCHEBCFEDDDCGCGDGDHEFGGCHCBEFECAHDEDFDEHEGEFBBHGGCECECFBDBDBAHAHEHDHECFBFDCECABABHBGBCHFHDHE,False +782,14.0,24.0,23.0,18.0,18.0,17.0,19.0,17.0,GAECGCBBAGAGAGFEEDDFBEEEBBGGEECCCCBEGEGFGDGCHCHCHEADBDBHBHFGADBFGDHHGAGADDDDDCBCDHFBFHDAGFHFHFHCBCFEHHHBFCFHFCGCBCAGFEBDFCECHCACBDBCEAGDBDBEBEBEBABAFC,False +783,17.0,21.0,14.0,26.0,20.0,11.0,14.0,15.0,CHAHEHDHGCCADABAEDBDBFAEABGDDCGADADBBAFCEGDBEBDHGEGFHEHEHEFCFDGHADADBDBDCDCGBABDECEDEDFDCDCDADEDBDHGBGBECDHEHFFBAEAEBEBGHGEBCGGBEFHBHCFAFA,False +784,9.0,13.0,21.0,19.0,11.0,19.0,13.0,15.0,ADHDFGEBBCCDCDCFHAGDBCBCECEAGAHCDEAHBHEFEAHHGDCHCHDHDHFBEADFCGCHDHAFBGBGBEFDFGFECACFEFGFDCDEBGBGCFBFCDGDGCFDFHFHFCFCDCDB,False +785,3.0,4.0,10.0,4.0,5.0,8.0,5.0,7.0,FCFCGCGEAAGFCECECHFFDHCACGCGEBHFEFHBHDFDBDBHHC,False +786,13.0,15.0,20.0,21.0,12.0,14.0,14.0,18.0,BFDGDGDADECHCHCEDGDBDGHCHDGCABEEFEFGGDDBDHDHDGCCEBDFDFBHBHBHFHFAECEBAAAFAEAHBHGHDFEFBHBABECCCCCDEGHGBFFGHCDCBGDCCCFHDCACAFGHADA,False +787,12.0,21.0,22.0,19.0,22.0,24.0,29.0,14.0,CGCGEECEGGBEAGCFFFCDCEEACFBFBGBGDGDHDHCBCGADEHGHBFGFGFDFDBGEGEBFCFCFCFABDBCAFFGDGBFHCHEECDFDFCBEBFHGCGEGAGAFDFCEGEGEAAHHHBGCGCGAGDGDBDFGEDBDFDBCHADEEGEHEHABBFEHBCB,False +788,17.0,13.0,19.0,20.0,16.0,16.0,19.0,15.0,BDCEGHGDAFFHFHDADAHEEEECFCGDHBHGGGAGAEFGBCADGCCCCCCGCDCBEFEFDFECADABAFEBGBGAADGEGHADABHFHFCEDHDGGCDCDFDADGHCFBBCBCEHBHFHDEDEDEGHGAAAFBF,False +789,28.0,17.0,13.0,32.0,28.0,13.0,27.0,17.0,AEADADBGBAFAEADGBAAGDDEGEBEFCFCFHFHAEGEHDHAADEDHDCFCBAEGEGDGCGAGBGBGBFDDDEDGBGBGBDDGGADCDBGAEAGDBCADEDHBABAECHCECAFEHAFACDCDGEHEHFBEHDDDDFEAABDHGHGHDAGECEGEGDHEAEGEGEAFHDHDFAE,False +790,20.0,14.0,14.0,14.0,17.0,15.0,16.0,18.0,FCFDDDHCHCEGHADCBGFEFCFEEEEBEADABHBDEFCABABAGAGEHHBHBDAECGDEAAAFAEADBHCGGBGBGBEFEFEFABAGFHHGACDBDHHGFDACEHDHGHFCFDHCHCHCEFAGAGAG,False +791,18.0,17.0,18.0,19.0,20.0,20.0,6.0,18.0,FHFHFDEAADAFBBACGHDCDFAGGFEFADEDBFBFECEAFAFACCCEFHBHFHBBACHFDGDCDHDHGBAHCDCBHBEEEEAECBABCBCEDHDFDEDEDEAEADACAHFHFHEDCCABEHEBEHCFBFGFBDHC,False +792,14.0,17.0,13.0,12.0,11.0,16.0,16.0,11.0,DDBDBDAFBDBFAFAGBDEGCCECHCHCGFABGBCFEFECHFBABAEECBDHDGDGHGHGFCFHEAEGDHBCBEFHBGAGACAHAFGFGFDEABFBABGFGFGBHCAEDC,False +793,9.0,19.0,17.0,11.0,13.0,16.0,16.0,13.0,DCGHBFFCGEEBEGGAGFDEEBFGHCHCDFDBCBCFCFCGCGBBBCBCBFHFGCAEABHBABGBDBDFDHAHFGFHBBBGHGHECFDECEGHGHDAAGDBCECDAEAEFEFCFH,False +794,18.0,14.0,23.0,18.0,18.0,15.0,28.0,20.0,GBGBGFGAEFECEBGBECECFGDEDGFCFGGHCHCFGDAHHCHCFCFCGCGCEAHAEABACDBDBAGGCGHAHBDFDHEHEGAGEGEHHDCDGFHBHGHFADECACAEABFCAHGHGBDCDFDFBAGACDGGCDBGGADHDBFHEHEAEGDCEC,False +795,2.0,6.0,5.0,6.0,3.0,1.0,4.0,1.0,GDGECBCHDEDECBBFBCBABDGDGACD,True +796,20.0,15.0,22.0,19.0,22.0,17.0,35.0,28.0,EHGHCDCDAEBCBFBACHCGEFEFEFDFHGHDCGAHDCGCDCACBGEEHEHGGGEHEFEGGAAAAHAFFECCAGHGHGHBACACDCFEAGGGGGGGCGAFCBEHHGDGHGADAHGHBDGAGBCDCABAHDDEEFGGEHHHBBBDBDHDHDHFHEHBCDCGFGECEFFGFGEGHFBEDA,False +797,22.0,14.0,14.0,13.0,13.0,14.0,15.0,9.0,HCHGGBDEFAFAGAHDCGCGCHCGFAADEDEABAGABFEFEFEBDFGABHFDAABCHCFCADBBAGDGDGDCDFEFGBDBDFFGCBCBEBGAAAAAAHEHEBEGCAAAFHECEC,False +798,15.0,14.0,14.0,26.0,14.0,22.0,16.0,23.0,DCGAADDDHDHFFDBGGFGEGBBDHAHFFFFAFCFBDDFEAEDHDHGHGDCHCFAGBDFCFEFGAGHECFCEDAHAGEBFBABDEDADCDHAFCFAFHBDFAFADEGEHEHBHGFGCGHGCDCDBBHHHHBCBCHDEDEDEDHH,False +799,27.0,20.0,19.0,24.0,17.0,17.0,26.0,21.0,GFGDGDCDFGBGBEBGBHHFDADAHEHEBBBHFFGGCADACAGHBHAAFACACHBECEFAHADGDAEHECFABCGCAHBHAHDGEEHFDFHFDFCAHDBDBFEGDGDGHBDBGAGEGBGCCECEBEHAGABADADADECGCGCAFHGHBFACACFDEDEBGACAGHGFDDD,False +800,14.0,22.0,27.0,22.0,29.0,27.0,20.0,20.0,BCBCBCACACAHDBFCHEHEFBGGCGCABBHBEEEBECECBDHDEBAACGCGFGFDFGBCDAHHHHFFEDDDDEFFHFDEGGGHEAEDEGBBDFEADFCGCGCHFHGHGEDCHFFFDFDCHFBCBCBCEEEGACAEHEFGFDFCFBAEHECGDEFGHGAFAEBBBBDCEHFCFEFDCDEDE,False +801,5.0,1.0,4.0,0.0,2.0,1.0,0.0,1.0,HCAEACAFBEACAC,True +802,15.0,14.0,17.0,11.0,11.0,11.0,14.0,5.0,DGAEAFAFCFDADEFEFCACGEHEFGCHABACABHBADDFDFCGEGEAAACHCGDGCGBEBFDCABBBBDBABFGGCCCEGFBBBEDAHCGCGCGCED,False +803,19.0,24.0,22.0,27.0,21.0,24.0,25.0,26.0,HFAFEFEFCCCHCHGDDHEHEDEACCFAFBHDEDEBGCGBFAHAHAHFGDBAGAHBHFEFBFEFABCDHDGACACBGDGHAFBDBCFHFHDHDGDADBCFGGBDACGHGCECEGGAGDGDGEGECADHDABGBDDCECEHFHBGGEGEHBFBDHFACAFBBBBHEEEGCDHGFDFDFEFHDHDCBBBC,False +804,14.0,12.0,12.0,16.0,9.0,14.0,9.0,8.0,ABCBAFDEDFDHDCDBAFCBGBDBEAEGEBCDGAACABDECECEHEAGHGDBHFFFCGDADFFFGFDBDFAHCHCHCHCBADADADABFFGGEF,False +805,10.0,5.0,7.0,4.0,17.0,8.0,9.0,3.0,AAGAGAGAGAHECEFEGEHEBEAEFDADFEEEECEDECHGFEFAFBEDFGBEACBCEFBCCGG,True +806,16.0,25.0,13.0,17.0,23.0,16.0,21.0,18.0,CBGEEFEGBBBCHGHBAAAAGAGEGCHCEDBBBBBHHHHDAFFEEDEDAAADFEBHGHDHEGEGHCECEBBDADGGGGGDGHEHEHEBBBFGFAFDFEFEBEBCFFEBHBECDBDFAFAGHDFDGBHDCFCAABCBHEGDGDEBGCCAF,False +807,3.0,8.0,5.0,8.0,9.0,8.0,9.0,9.0,HFFFBHCHEBEBEBGBDCGCECEFDFBFGAGHHDHFACHDHDEFBGDGEHEADGDBEGG,False +808,18.0,19.0,24.0,19.0,15.0,25.0,23.0,17.0,CDGFCFCAGHEAEADCGEGACBGFGDHEEECACECECFAHAFDCDHDFEBEHDFDFHFGBEBGGGBBBHBHFAEAFGFAHAGAFCGCHCHGHBCDDFDFDGDFBEBEBFAFCFGDCCHGHADCBFBGBGHFCGDGBCAHFDFCFCBCBDAEABADGFGHC,False +809,24.0,16.0,20.0,18.0,20.0,16.0,26.0,18.0,HBEFGCGHAHADGCACAFBFAFCEBGBFDGAGAEHHCDDHDFDHDHDEECGABCBFEAEHDGGGGBABGFEBCAEGBCFCHGHBHBABGBHFEFCCCCAHGEGEFHFDGAEBHDADCGHEAEAEAEAEGEDCDADGDGAGAGAEHDGCCFCFCADBGF,False +810,7.0,10.0,7.0,14.0,17.0,13.0,14.0,8.0,DEAEGEFECACABGEGEAHGHGHAEFEFECHDDFDBDBCBDBDFGCGEBECEDDDADBEFEBDFGBDFHGCFFDGGFEHEHFHBGAGEGF,False +811,11.0,12.0,11.0,18.0,16.0,11.0,15.0,16.0,EBEBABDHDHDHEHGHFAAGGCAFEDDGEFAFHDBDBDHEGGGGBCBCFDDDDDEDBHFEBHCHABEFEFGHECECBFGGGEDHCHCGEGACAEAECHABCHDADFDFHG,False +812,7.0,8.0,5.0,1.0,6.0,6.0,5.0,5.0,HHHHAEACACBEBCCAFAGEFCFDBHBFBFEGAGEGBGFABBE,False +813,7.0,6.0,14.0,17.0,20.0,8.0,11.0,16.0,BCHCAFAGAHCEFEDEHEDCHGHAEDGDFCFHGHGHAEGEGFHBBDFEHEDEDHDEDEBGDDFBEHGABCEDECCCADGHEHEHCHCDCDCDCEEGEFD,True +814,27.0,14.0,15.0,25.0,17.0,16.0,12.0,25.0,HFFCACAHFFCBCFFGDDECEFEHCBCBCDAAAGAHAHDECEFHAHAHDEABBEBCFGBGDEAEAEADGHAHACDHHHBCBEDFFAFHFEEGAAAAAHAHEHEDDDDGAGDHDBDFFAHDBACACAGHHDGBGBEDDBDHFHECGDDDHDH,False +815,9.0,8.0,11.0,6.0,5.0,16.0,9.0,7.0,DDGCCHAAADDFEFBHDFFFDFCFCFCFEBEGGGCFCGHGHEAAAFFHBCBGBEBCBFFFCFCAAGAHHGB,False +816,27.0,23.0,14.0,24.0,26.0,27.0,25.0,22.0,DABHHHEHAHAEFDBAGABDBGHDAAGAGFBAHAHEEDABFGGEEADAFBCACGCGCEFEBEBDFDCDGDEFEHEHFAGAGCBCGCBCBEDAGGBABHDFBFBDEHEHGBFEFEBDFHFHFDEECAFGFGFEADHDAGAGADCDCHFHCEADFDGEAFBFCFDBEEDGAGBEFEHDHGAGHGHFBFBF,False +817,1.0,1.0,2.0,2.0,3.0,7.0,3.0,4.0,FFFFADHDHEHEGCFBGECFHFG,True +818,10.0,14.0,17.0,5.0,12.0,5.0,16.0,9.0,CACBHAACABGDCAEAFGBEHEGCGCGEGEDBGAGFHBGCECEFEGEGBHBFGAGHEABDFDBCBCBHEHGHGBDCACBGBECCCCCH,True +819,20.0,12.0,13.0,11.0,16.0,13.0,21.0,6.0,ADCECACDCEGDFFAFBGBGBGBAAAEBEBGFDADEDAACACDCHHBGGGGGGGEGAAHFEFCGDGBCFABAFEGCDHFECEDEHABCDAHFGAGEGAGAEAGBFBCEFEFE,False +820,24.0,22.0,18.0,21.0,20.0,19.0,14.0,22.0,ECFBHAHAHAEAFBFGDGDCBCGAEAHABCBHFEDEDGBCDCDADABAEAEBHDGDHCBAHFDCDHHBHEGAAFAFCHCDDEHBFBFDGDGHBAFCEDEHFCEHEHEHGCGAHABCBEFHFGCDCDFBFBFAFGBDEDAGCHBEBCBADAGEBEAEAFFH,False +821,24.0,21.0,19.0,22.0,19.0,13.0,20.0,29.0,DAHAHAFEGCDEECECAAEHEFDDDGAGAGAGABHBGEHDHFHEHAHAHAFBHBHCAADCEBBGDECHGFGHGAGEDFDFDHHHCGAEABFDGBECECAHACFCHGFBDHGFDHBHDDDDGGHEHAHBGBGBHEABBFBDBFBDAEEBECCCCCACHCBCHAHDGDB,False +822,16.0,25.0,27.0,23.0,14.0,15.0,16.0,28.0,BHCHCDCAGFGAGBFHEHBABGDHBABFBGBDCHCHCHEHAHEHCHDBGBHACADADAFFHAADACBCBEGEFDFDFDFCHEHDDBDEGEDHHHCDEGHCFGFDEDBBGFGCGHAHBDCECHCABHFCCHCDEDCDCGBBEHDHBGBFEFCACHCBBABCBDGC,False +823,19.0,16.0,17.0,19.0,13.0,21.0,12.0,12.0,AAFGBDHDCDFDEHBBFHFCDCABBFDFGEGEBCHDDDBDGDACAGABEGECECECEFEHCHAGDDHCCDAEFFAFBFBGDAEHHBABAHADABGBFCFGDCDFHFHAGAFAFDFBACACFGFEFECBC,False +824,23.0,14.0,24.0,16.0,17.0,21.0,26.0,11.0,EEEECEBHDFDBDCFAABFDEEGGCGEGFHDGAGBCFCHCFAFAGAGFFBGAFAEABCGAEADADAHBBEHCHCBCBCDCECGHBHAFDEDEAAACACFFECEFFGACCDCFGGCGCGFDFHFGCGCGAEAGGHHFBFDADABBCGGGDGDG,False +825,16.0,23.0,19.0,19.0,25.0,21.0,19.0,16.0,BCECEGEHBGBGDACADFFBABGGEBEGCGAGDBCFCEADAEFEDDCHCDEDGBGCFHFGBEBEBEHCHCEBEDEBFBFEFHFHFGDEAEBGBEDDCBHDFGFCACAGAHBDBDBCCFCFAFDDDADHEEEFHAEAGBGCAHHHEHFGFBFGECHABF,False +826,8.0,5.0,4.0,4.0,6.0,3.0,1.0,4.0,CDGDCFEEEEABABADAHBFBHACAFHEAEAHCBD,False +827,24.0,26.0,18.0,19.0,16.0,34.0,27.0,29.0,CFAFCHHGFDHDBDBDCDCHEFBGBGBHBDADCGCGHGFDFBAHDDAFECBFFFHFAGECAHAEBEAAACGEGHGEABAFGCEAGFFHFGACBGHGAFHCHGHGBFAHGHBHBGBGAGCFBEDHBFBHEHEBFGECEADHFHFHFDABFEFHFEFBFBABDBDFDADGDGCAEAFCFCFCDAGGFGFBHHHHB,False +828,2.0,3.0,1.0,7.0,4.0,6.0,1.0,1.0,ADDDFDFEFEDEBFBEGFDADFHCB,True +829,18.0,8.0,19.0,22.0,14.0,21.0,12.0,12.0,EGEGCHAFEECHDBDBDCFAFEFDFEGEAFCFDADADCHFHEADAEHDHCCFCFDFHFDFDACACACEFDFDGBFBCGEGFGCGCAHADACEDDGCCACHBABDBHAHFFFDDHACBDEAEGGGFD,False +830,14.0,17.0,12.0,13.0,7.0,7.0,14.0,9.0,EGEBHBDCDGECBABADDGCABACFCEBDCCADADFGHGHGFGBGBGHGFDDCDAGABACHHDHDFDCBBGBAAFACEHAGAGBEBHBCBEBF,False +831,13.0,21.0,11.0,11.0,12.0,12.0,12.0,8.0,EAEDGBFBDBCHEBEBEBCHCHAFGGBCDDDCDCBADAFAFABADFCBCGEAEDBAFAEHEHADFHBBEHEFBFGEBHFGBCBCBFGGAGAGBGCGFBDB,False +832,14.0,20.0,21.0,16.0,26.0,24.0,30.0,17.0,BGGGEEEBFFFEFCDGGGGGCGABDFGHCAFFFDFEHDHAGAGAEBEBCBCAGBBDBFBFEEEDDFCCGCGEGBBDBHEDCFCHGFEEBGCFAEGEGECFCGCHEDDCBEDDDHHHCGBGEHEHGDDCGCGBGEGEBEHECGGAEABAFAHAFAFHFHCHCFFFHFBA,False +833,0.0,0.0,2.0,1.0,0.0,7.0,1.0,2.0,GFFCFHDHCFFFF,True +834,15.0,17.0,13.0,12.0,21.0,19.0,18.0,23.0,DEFBAGHEHEABHDFGFHFHCHDHECEHBHDGDGFFCGBFBEEHHCDEFECEDEBCBGEGEGACAGHGHAHDFCBHGFFFFDACEHEBFBHBHGAAEADGGADHHHHGHGFAFCFCGEDFFABABGECACABEBEBEB,False +835,9.0,17.0,15.0,12.0,13.0,15.0,12.0,18.0,AEAFDHGHGFDEDBFBABACCCFCHEHCFEDHFGFDHBHBHEFAACHEDECFCGCBCECEGHBHCABDBEGFDFDBDBEGEFFCCGHAHAHGHDFBBGBGDGHBHBCBFHE,False +836,24.0,27.0,17.0,31.0,24.0,22.0,21.0,23.0,DCGBEBCDEDADFBFEDADADBDCDCDEDFDGBGCGBHBHBHEHEDEDAGBGFDAHGHBCECADBDEDBFFAFAFAFEHHGCGFEFDDGDGFBFGEGEBAHAFDDHFABBBDADAHAGAFFFCGGEECHGAGAEECEBFBCBHHGEFDAAECFADHGHCHBBBBDEDHBBBEHHAHCHCAEFEHADGDC,False +837,8.0,2.0,11.0,12.0,11.0,8.0,3.0,11.0,BHCHEDEHFAFHDHCHFDCDFDFDAAHCFDDADHDECECACECAFEHEGDGEHEDEHFCBCGCAEA,True +838,12.0,19.0,12.0,11.0,20.0,17.0,13.0,16.0,DEFEFEHEFBFECEAEAGBGAFEBEDFGFGAHFHFCGBBBBBBHEFEBHBGBGHCHFBCDFHAACCHEHACDBFEGEDFBCBABHHCHEHACACEDDDDFDGHGHCAGFDFBEEEGEGBA,False +839,1.0,4.0,3.0,4.0,6.0,6.0,4.0,1.0,GBEECAGBFBFBEDCDFDFEEHEDGFGFC,True +840,5.0,4.0,4.0,1.0,6.0,4.0,2.0,2.0,GEBEFEHEAADACACFCFBBHCAGEBEF,True +841,15.0,12.0,13.0,8.0,18.0,15.0,11.0,15.0,FHFHFEAAHFEFCGEHEHCHCBCAEBBBCHAHAEGFGABHBEBEFCBCAHDHBEAFGBHAFEFBGCFEFCDADBDEDEDEGEFEFAACHDHAEACGEGHGCGAGFDC,False +842,17.0,27.0,15.0,15.0,25.0,21.0,18.0,18.0,DBEBDBEEGGGBGEHCACBCBABGEDEDGFAFCCBEDCGGFGBHAHDBBHBHECACEDBDHAAFAEBEDCDCHGBEDECHAFAFECECEFHGHGHBEBGBGBFFFFHFEFHFHEBEGEAEFFAFGBBBFHCHADFDFBABCGAEAGFHDADEBHBE,False +843,20.0,14.0,16.0,25.0,17.0,16.0,12.0,24.0,HBHEDGBFBCADADACHHDHDAEAHDDDDDHFFDHDGCGCBHEGABAHEDEABACDCEFGFHAGGBACGHAFFGDCAAGHDEGEGEDABACABHFDEEBEBDBDBDHDADAHCHBEFEDEDCFCFCHCHFHFHFHFCAEHHFCE,False +844,6.0,6.0,6.0,6.0,7.0,4.0,7.0,2.0,GCECFBDBDBEGHDEAEAFFECECACBGBDADGDGHFABGEGCA,False +845,14.0,10.0,13.0,17.0,13.0,16.0,16.0,22.0,DADFGHGHFHCBGAFEFCFCGDGDEDBABABECDCDBBGAFAGAHDDDDFDGDGDCEGGFHFHCHGAGDHHHFFCGCHHEFEAHHHFHGEGDAHECDCHHAHAEAEBCFHFBFCEHBBEEA,False +846,13.0,21.0,15.0,9.0,8.0,13.0,6.0,10.0,AGBCBCBDGCBFGHABCBCBEBABCGHEHBAFAFDFECDBBAAHBHBHCFCFDBABDCDFFCGHAHBHBEBEBCFCACDEHACEBFDFGFAFAED,False +847,8.0,14.0,10.0,15.0,9.0,10.0,9.0,7.0,DECFAHHBGBCEAACBCBADDEBHDHDEDFFFGEAEBGCGBGDGDFDADBDBDCFCGCBCHABFBDEDGDGBHBFFCFEAEH,False +848,10.0,5.0,6.0,10.0,12.0,17.0,10.0,11.0,DHDEDCDFDFAFAHCFGABAGFCFBGGGGAHCFDFAFEEEEBBABHFAFGFEEHDHECEHFHFEAHAHEDFDFHFDGGGEC,False +849,22.0,14.0,13.0,19.0,14.0,18.0,13.0,19.0,AACFCFBBHBGFDADADAHHCGFBCHHFHBHDGDCAHAHABDEDBDAHAGFGEBEBACHCDEGAFFDGBHFCFDDBABAEEDEGEFEAAGAGABADAHFGFCFAAGCFHEHFGFBFEEDEHEDCDCDCDHHH,False +850,12.0,11.0,24.0,25.0,18.0,37.0,27.0,36.0,GEGEAEAEDHDEDECECGGGEFEFEGCBFBFCFCDCHEHDDGEGFGDHFGEGAGCGFDHCHFHDGCCHEBBDACHCFCHGHCHCHGDFFFFDFHGHDFFFGFGHHHGCDFBFCHHFHDDBACHEEFDCAHDHBHFFFHHCHBHFHDGFGFGBEAHFHFHFCAGGDCBGDGDFFAACDCAFDFDFBHHAHE,False +851,8.0,20.0,9.0,10.0,16.0,10.0,11.0,18.0,GAGAGFFHFHCHGHEFEGADABHBHBFEEEBAHCHCEEHEDCAGGBBDBFGFHFHAHFHBABEHEBFBCHEBBBDDDCDBECEGDBCBEBEBHBGCHEDDHG,False +852,8.0,4.0,3.0,3.0,5.0,4.0,5.0,3.0,CEHEHBGFGBABDCGAGHFDCGAAAAEADAFEFEB,False +853,2.0,2.0,4.0,5.0,2.0,8.0,1.0,9.0,BHFHFHFADCCGFDFDBDEFAHHHHHFHECCFD,True +854,0.0,3.0,1.0,7.0,1.0,4.0,3.0,3.0,BGEDFDHDHGFBDBCGHDFDFD,True +855,13.0,9.0,23.0,8.0,13.0,14.0,12.0,14.0,CFCFCGHEACCCEEEGDHHAHBGBCFCDCDCFFGCAFDCABHCHCDFFCECGCGCAABFDEDACCHHAFAEBEBHGHBHFGEGCGCGAEBCBAGEFEFEFDHAHAH,False +856,10.0,14.0,21.0,25.0,13.0,22.0,18.0,15.0,HDAFAFDFBGDDCEEGEDFGBDBGCCCCDDDGDGHFDGHEFECHCHCFEDBDBACGFBFBFDCGEGCABABDEGCGCECEBAFGHHBDDDHHHGGDCDCACAFBEBECFCFAEHHFFFDGDGHGHDDFDFHFCFCBAF,False +857,5.0,7.0,6.0,6.0,3.0,6.0,3.0,6.0,HBHCDAHAFGBACABHBDBDEFGCHCHCBEFEFGFCFDDBDA,False +858,5.0,6.0,10.0,9.0,8.0,7.0,3.0,10.0,BGCHCHCBDDHDGDGABCBABFECECECDCDFHHCEDDFFFHHEHEAEAFHBEDHCAF,False +859,5.0,3.0,3.0,10.0,1.0,2.0,6.0,6.0,DADADBGHEADDDCDGHGHGCDCDBFAHHFHAGDGB,True +860,23.0,20.0,27.0,31.0,27.0,21.0,22.0,20.0,GBHCDCFCFDEDHCHGEFEFECCCCCADABAHFHFHFDGDAEEHACDDGBADFDEECFAFCFEGCGEEHFAFEFBABCDADEDEHBHGHBBAECECGBHAGFHHBGECCDEDBFHCACGCDAGAGADDDDDCDGFCFCEEEDEBHGHGHGCGCBDADHBGDDEDABABAEDEBFCDEBABGBDAFAFGEGH,False +861,7.0,7.0,14.0,4.0,11.0,5.0,11.0,5.0,GCGFGBGCCCGFAAEAECECECGBABHHCAEAHAEFEBEHDCDCGFGFBCGCGCDBEEHDGECB,True +862,12.0,3.0,10.0,5.0,8.0,8.0,5.0,6.0,GFCAHAHAGACCEHDBBAAAHADECEDECGCBCECFCFHFHAGGEDEFFCFAEAFAD,False +863,24.0,14.0,29.0,24.0,18.0,18.0,12.0,25.0,ACACHBEBEDABHBGCDCFCEDFCGCACGFADCCCCBCDEAEBDHEEGAGCDFDFDFGEHAHFEEAEHCCFHFEFCHCHDAAHGDCDAHFHEHDHDHAHADEBEBEGADAHEBFHFHACGFGCGCBCDCDCACFCFABCBADDBCBHHDHGAAHAHFFDHDEDA,False +864,12.0,14.0,8.0,8.0,15.0,8.0,10.0,15.0,EBEBGHCABAFAFDFDADGBHCEBGBGBCFCAEEDHCHGHBHDGDHEHEHEHCFGFBEEHAAAHGHGEGBFCABHFHEEBADCDABEBEA,False +865,3.0,2.0,2.0,3.0,0.0,3.0,0.0,4.0,BHDHBCFDFCAHAHAFD,True +866,5.0,8.0,8.0,6.0,13.0,7.0,15.0,8.0,FHCDEDADBEBGAGCCCEBGGFGEGEGAGAGHDHGBEHEDGAGEBECHCGFEEHEHGGFBFBFCFHEBCD,False +867,15.0,8.0,10.0,4.0,10.0,7.0,12.0,11.0,GCHHEHGBDBCGCBCFEAAHAHADFCFCFGAGAFBGAHAEGFBECEABHCHAEAEHGHGFBDCHGEGEGDACABAEA,False +868,13.0,19.0,24.0,20.0,14.0,16.0,12.0,20.0,HCHAHAGDDCDBGGHGHGCEEAEGFBFDEAEFCFHDHGFAFGEHDBDBDCECDFECHCDCFCHCHBBBBGAFDCACEDBFFAFAFBEHCACDHBCBCBHBCADDDBDHDHCHCBABHHEFGAECGCGCBDBDCFHFEE,False +869,11.0,10.0,12.0,15.0,14.0,12.0,10.0,5.0,CBGECDGDGDADCGAHDBDFFFFEAHFEFDBDGDGECECDDFDADBEACGFEBEBECCCGCBCBEAEAFGBAAAEDEGHHDHCFAFEFB,False +870,8.0,16.0,15.0,5.0,12.0,6.0,10.0,5.0,GEGAAFBCBCEGAAEBEBEFHHCBAAGACBBBBEBCGCGCECECBABCFCGCFEDEHCCDGBGFDFDEHCHBBGBDE,True +871,7.0,10.0,13.0,4.0,10.0,7.0,7.0,8.0,GAAHGCBADEDHDCCCACAFHEBBBBBCBEGEGFCHCBEGEGEHDHCFFABCFCFHGHABFECECE,False +872,5.0,6.0,11.0,4.0,5.0,6.0,7.0,6.0,FCCCACBDAFCCCFGBBHBGAGEGDGCGHGHDHDEBHCCFCBAEFEFEHA,False +873,6.0,3.0,2.0,8.0,3.0,5.0,4.0,1.0,AADDDCDCGGFFEBADADADEDGBGFFEFAHB,True +874,16.0,16.0,9.0,13.0,16.0,16.0,11.0,18.0,DGAGHBHCEFGDAAEAFAFBBDFHEDEDHBHGHGHDDEDFCFCAAADAHFBCBCGEHEBFDFAFCFAFAFBECCBEDHHEHEGBGCDFGFHHHBHBEBEBHAEADBEBAAGEGHF,False +875,10.0,10.0,11.0,9.0,10.0,8.0,13.0,16.0,AFADADEDEFHCHCFGBGEHDFGHCHEGBGHFABHEACHBHBHBHGDGBAAAHAHCHCGGGCGEDEBCDDGBGAECEFFFBCHCHDE,False +876,10.0,18.0,8.0,11.0,7.0,15.0,11.0,9.0,FCHDHBFBGCDHAGCCHDHAGFFHBHEFAFAFDBBBDBDEACGGGBGFECECACHDBABFBDBDGEADADFFFGEGEBBBFBFBGBFAH,False +877,4.0,5.0,14.0,13.0,6.0,8.0,11.0,11.0,ACACGHADGCECGGGDCCCFCFBFDFDHDHDADHDHFFBHGHCHCGCDCDHDEEBGFDEHBHGEEBDFCCGG,True +878,22.0,17.0,15.0,16.0,16.0,19.0,13.0,15.0,CCFCHHDBEGEGDCFHFBAGFEDDFDCECEGBCBABADADBGGDBACAFAEABHHHFHCHDBFBDBDBEHHCHCHEEGFGFHAEAEAEADFEAABCFCEAHFGAAADFDFBFBEGCGCDAFAFAEDGBHBGFA,False +879,11.0,12.0,5.0,10.0,10.0,9.0,11.0,9.0,BCBCEAFGFGHBHBHDDFEFGBGHGFBDCAAGEHDBDGHGHFADAEEFEDEDEAHABABACAGHEDFAGEDBGBCBF,False +880,22.0,23.0,20.0,22.0,17.0,22.0,27.0,22.0,AFEFEHDHDHDBFBGBGEGBGFGFGEHEABABGGGABAHDHEBCGCGCFCDBDFEEAAAFDCBFHGHBCGAEDFDFDBCECFBAGAGAFEHGGCGDBBCCGBDDCDBDCFCAHDBAFFHCHDHFHCEEDHDHBHCCBFBAEAEAFGDCDHAHFHEHADAGAGAFBGCGHGFBEGG,False +881,26.0,17.0,21.0,13.0,20.0,12.0,23.0,19.0,BAEAGCGHGAEADABEEEGAAHHDDBDFGAGACCHHEHEBFBHEEEDFGFEAGHCCACGEFEDCGCHCGFHHBHBGBCCCDCGBGBABABFDDHEAEFEGGGGEHAHACACDGBGBGBEAFACEHFAAAHGHGDCCECFCBCBHDAAAFAD,False +882,1.0,1.0,3.0,2.0,1.0,1.0,0.0,5.0,DHHFADEBCHCHCH,True +883,7.0,3.0,8.0,7.0,4.0,4.0,4.0,4.0,GDEDCFHFHDHDEGEACDCABBGFACACGCFCDADBCAEAH,False +884,21.0,12.0,14.0,11.0,9.0,9.0,15.0,13.0,EHEAEGDDAGGBGFFAGHDHDCDCDCFCGGGGGAAEGCHEDEAEFHFAFGCBHBCCCCADBBAGAGHBCACAHAHBFEDBGBCBEDDHHABAFAHAHFBCAAAA,False +885,16.0,26.0,24.0,20.0,25.0,24.0,19.0,20.0,DFDGGAEAEAEDHGHGCCABBEECFCFGBGBDCGFFDBDECEADADHGHFDBDCEEBCGCGAFBFBCHDFDFEFEFHFHFHBHFEFHCHCBAFDFBFCAGAECBBBBEAEBGCECFHEHDCCEGBGBGFGFHHEHCHBDACECABABDBHAEDDCGGBBEFDFDCBAEHEHECG,False +886,13.0,28.0,17.0,8.0,23.0,25.0,17.0,16.0,GFFBFBHCFBBBCGCGEEBCBABFDEBGBGCACEHFHFHBADDCGEGEBHAAACFCEHBHBDAEFFFFDFDFEFEFECEBBBHFGBBHBEGCBEAEDCHEEEFBGHGECEHFHBABFCFCFCGCEAGDGAGAFBGGAFHHHBEBEBF,False +887,12.0,16.0,10.0,18.0,15.0,11.0,14.0,8.0,EEHEFGDCAFDGDCBFBFGFBEAFBBBAGFGBGCHCHCAGADCFCDBDEHEAEDGDBHBFGEBEBDBDADCDHDEABDDEDFCAGDGAGAFDEAGCGBEBEHEH,False +888,18.0,13.0,17.0,15.0,11.0,10.0,18.0,15.0,DEGEDEFAHAHAHGHGHGCGCFDDDADFCBGDGDCBABCBEACAGAGCEDBABDHFGAGAGDEEHAFCDCBCACBEBHCGBFAHAHCDFHBGBGHFHGHFBACEGEGCHAECFCDAD,False +889,22.0,5.0,11.0,9.0,14.0,19.0,10.0,13.0,HEHFADEFGFCEHEFDFHFAFGGGGAGAFADGDFAEAHBCECEDFCFHFCFDFDAACACABBFGCHEAAABCDHEAEABFHFHEGEFHAAAAACAGDHCHEFE,False +890,27.0,36.0,17.0,27.0,26.0,14.0,25.0,25.0,FHDGFABEECADAEBECEABAGHECDCDADGDADADEHEHGHBFBCBGDEEEEEBABABHBHAGCEDEDEHAHAGGCDCDHBABHBCACAGFCFGHHFDFDGBGHGAGCGFFBHADFCECEHBDBGBABACAHEBBHGHEHBBEDEFEBGBDBCGEDBBBBBEBDHDBAHGFGAEBHAADGHGDABFCFDAGBGDHD,False +891,18.0,15.0,22.0,14.0,25.0,27.0,18.0,19.0,FHFHEHAHCFEDCDHFFFHCCCCCCFAFGEAHAFGGEGEGEGFGFAEHDCDFHGAGEBHFHCHBHBEDHDCFCACGBFCDDEHBCEGAFABEBFDEGAFDCACFEFEDEAAGAGAGCBCDFEHAHEHBCBCBFBEEFEHGGGCEFEFEBEAFFBDADB,False +892,15.0,15.0,17.0,14.0,25.0,21.0,15.0,21.0,EGAHHHDHDFEAEDEGGGGAGFHFAFEEEHHBCBGHGBGDFAAEAECEFEDDBFCFCAGFFHFHFHBCFCDHFHCHADBHFGFGBEBHHEEDDCDGBCEEEBGBHEHEDEAFCBCECEBGAAAEDCDCACABEHHCFEFCFBF,False +893,5.0,2.0,1.0,1.0,3.0,2.0,5.0,2.0,BHAHAEEEGFGFACGBDAGAG,True +894,1.0,2.0,2.0,3.0,4.0,6.0,4.0,3.0,FCFCHHEFEFGGGGHDBEBFAFDDE,True +895,12.0,25.0,10.0,17.0,18.0,19.0,18.0,17.0,CECBHFGFGEBBHFEFDBDBABDGAGAEABCBGAGAHCEEHEHEHDDCDBFHFHEDFCFBFBFAGGGGGFGEHBBBHDHBHDEBEFGDCBBBDBGCAHHEGBGBCDFDEEEDEACAFFGBBHFHFDFAFHGBADED,False +896,16.0,8.0,11.0,13.0,10.0,11.0,7.0,7.0,GEDEHEHBBDADFDADCDCAAAHFHFGFECACAEDCDGAEAEBBCBGEACAHDBDEGFHFBCDCFAADACBCHFAFAFEGGDF,False +897,11.0,6.0,9.0,7.0,10.0,14.0,15.0,10.0,HDBFBGCFCGCGBGDEDGHAHGHAAFHFCGBGCAHHGFCFAFEBGHGBDCHCHDEEFEFEAEAEFEFGDGFAFACGEFDAGA,False +898,17.0,13.0,21.0,30.0,28.0,20.0,12.0,19.0,EDDBGCECEDBCBCDHGFECBGBEHHHEHFHDGDHHAFAHCHDBEFDADCDHEEEHEGDGDGFEDCACEDEAEAEFDFDFDADCCACFEFCFEFCBBHCCFEEDHDFGEGAFCFCACABABCGDEDAHEDDDDGDGFHDHDABFCFDFAHEEBEBEHEAA,False +899,3.0,3.0,2.0,3.0,3.0,3.0,8.0,3.0,BCEFGHGHGAGBGBGDFDCHEGEFAADG,False +900,16.0,24.0,17.0,15.0,11.0,13.0,13.0,18.0,DDCDADAECDHHHCHADDHCHCBCADAECGHGEAHFHGBBHDADAEHHFHGACACFCFBEBEDCGCGBBBBGEFFHFBBGCGBABABAHFEFBBECCHGFDFBFAFAHBBEBEACDGDGCBHBGBDB,False +901,25.0,30.0,29.0,16.0,34.0,19.0,24.0,19.0,FFGCECEBBBCDCBFEEEECGCABAFEFGHBDAACECGHDFCHBFBGGGBGHCHCBCECBGBEFDHBHBHCHAHAGABABGEGFCFBEGEBBCBCDHHHCHCHDBDCFCAEDHGAGEBEGEBEDEFFDBDEFBCEFEAGGFGEGFBFHHACACAEAEAEBEHEBAGAEAECGABADDDAECECFAAEDDAGCECBG,False +902,24.0,23.0,19.0,24.0,26.0,27.0,19.0,14.0,FAAAEACAEEEGEDAHEBADAGGHEDCABGFFDFDFEBEBEDEDGAHFDGBCBFDFGECFBFGFBFEFCFEDADBEFEFACACACAHADBBBEHAHBGBFAGBEEGGFGCGCFAFDFEBHGCAAGDGFHFCFCHCDCBFBGBCBEHFHCHCBEDGDACAEBDBHFHEDDDDDEAED,False +903,29.0,29.0,25.0,18.0,19.0,26.0,26.0,24.0,GABBEDADAGFHBHFHGCBCBDADGBGDGHEDBGBGDAEBEAGFGACEBEDADFFFBBBCFCGAFAHEHEHGBAAAAAAGGCCHBGBABHEEFHFHAHFBGCHDHFEBEGEAEDFGCHBHACADBHGDGCEDFFHFEFBCBABAHAEAGGFFCFAHADGDGCBCBCGCGCBCBCFHEHDFFEFHFCFABCHCDCAC,False +904,6.0,3.0,10.0,6.0,5.0,4.0,4.0,1.0,ACGCFCACDCHCDDDEDCGGEFBCBCBFGFEEAEDCAAA,True +905,3.0,18.0,9.0,11.0,14.0,16.0,4.0,13.0,DCFBBCBEBDBFFEFDCGHBHGDCFBFDEHEFBHBFEFHFHFGCAEHFAFBEHEHEHCACHGFDCBEFEHEBDBDBHBDEDEDBCBFB,True +906,16.0,25.0,37.0,22.0,24.0,10.0,28.0,28.0,DFDCDCEAEHCHEACBHBGBHCCGCECADDDDDDCHHHAHCCCGDECECEBECHCFCFBHBACGCBABCBHGEBBBHGHGBCBCDEEAAGAGDHFCCEDEDGDGDGBGHHDFFGEEBFAGHGFCBBGEHHBCBDBABCEAGACACGBEHEHCFDHAHEGGGHGHGACEDECHCGCGCDHFHBEGEDBCGC,False +907,25.0,18.0,28.0,21.0,19.0,32.0,30.0,20.0,GCGCEBHGCGCEDDHHGCCCCGHGHDHEHACGGGBGFGBEACGHGCFDFDCCCHCFDFAFAEAGABACAGACEBHBFGFBFBDHCFAFGFACAGDEHCDBGHAHBBDFDFCFAEBDCGFAHGHGFGFGBADFEFHBDADABBEAFHDDFDFGBGDEDEFAFEFEFGFAFDFEFCACHFHBEEECGCGCAAEAC,False +908,28.0,27.0,16.0,15.0,23.0,29.0,25.0,24.0,FAFEFGFBABHFFBHDCCGAABEBCACAEFFCFAGAEEGEGFGFDFHFHBAGFGBGDHBHBHBCGEGFAAHAHAHAEGEBEAHABCBDFGFGEGBFBHBDBFBFGFGHGHBEBEBDGHGFAFCHADEEECECFBACCBCDDHGGEHEGCAAFAFBDHHHDHDFDADGFAAEAFABEECGHHDBEACB,False +909,22.0,23.0,20.0,21.0,31.0,23.0,29.0,28.0,EAGGGDCHHHHCDDEDBCHAEDGBGAGADBHAFFHGBGBDEGEGHGAGDBEGAGCCHFHFGEGHHEAEBDDDDADHCBBBCACFCGAGECEAEFEGEDDAAEFEHBHBGBFCFCHGBBDBFBFDEAEAEFCDDEGFGFCECAGHGFGFEHHDAFHFHGHGHFHFEEEHAFBBBEAECGCBCBCEEAHACBFDFEHEH,False +910,35.0,20.0,17.0,22.0,15.0,17.0,23.0,20.0,BABABADGDFFFFFADHEEAEHCBGBGDGEGCACHEFAAHAHAHBHGHBABCBCGCFDFAFCFCEAEHEDGFGBAAADBGADADBDBECGGFCBDBHCAADAHAGADCGFGFGCGCEDAAEAHDEDBAGFGBADDDCDHHHCHAHDEAHGFAEAFBDHAGAEHBBGCGA,False +911,20.0,22.0,16.0,16.0,19.0,34.0,24.0,21.0,HHBBFFAHAHEFAFCDBDBDGCEEBFBDCCBCHDFAFDBDBFCFAHGEDBGFFFDFHACEDGDBFBFCECHCHBFAFADAFFFFFFFGFBHGHGHGHAFABACHCFGGGAFHFHGGGGFAFEEGHGEEEGECDGECBCBHDGDGHEHDBAGEBEAEABABFEGACHEBGFAF,False +912,14.0,22.0,22.0,16.0,10.0,16.0,13.0,11.0,GABHDHAHACDCBFFFECHFHEBEGABCEHEBBFBACHCHCACABEFFDBACDHFADAFBFBGGCGCGCHFBFCGDFAFGBCBCBDHDGDCBCBCGDGCGAGABCBCACEDFDEEFBBDDDEDB,False +913,20.0,27.0,29.0,23.0,22.0,31.0,29.0,18.0,GFGEECFDFAGEFHFACDEGCGCGHGHDHDCGCFDBAGAGAGDGHFDFBFGFGAGHDAGAFABDCFFECECEFFDCDCBCGDBABFFHFDDDGACHHDBEBEBFCEEBEHAHECBABGGAGDHDCEEGFCFBDECACAFHFAFACBEAGGGBGBCBHFCFCFCFCHDFAEBBBHBEBECFCHEEGBGBFCDBDBDBHGC,False +914,12.0,9.0,6.0,2.0,6.0,6.0,2.0,13.0,BFBHEHEHBADCHBAGFHFEBHAAACABHBHAAACECBBACGCHFHAHAHEHEFFD,True +915,10.0,12.0,24.0,13.0,16.0,14.0,13.0,16.0,CEBDBDBDCDCDCDBDAHHBFBFCFGFGEDFHCBCFGECFCEBEBHBCCFCFDFEHAFBHAHAHFCACHCECEHACBCHCFEDEAGACDCHCGAHCDEGGHEEFHAGGGECEGEHDGG,False +916,4.0,4.0,9.0,4.0,6.0,12.0,3.0,4.0,CECDADFBACFCFDFBFGFCFGHCCGBEHEHEHEFFCACBEFFFAD,True +917,15.0,18.0,12.0,11.0,16.0,11.0,18.0,15.0,AEAEAEAEAHAHAGEEFHGHBHBEDABABADHGFGDHBCDDFHGBEFFFAFGGHBDFCBEHECECGFHBHEEGDBEGEBBGDCDHDCACGFGHGCABABHFACCCCBGBGBGDGBE,False +918,14.0,16.0,12.0,30.0,16.0,18.0,12.0,16.0,DHDAEBFADADADADADGDFAFHFHDEFGBGBGBGFHCGEHECEAACACGCDDDFEBEBHBFAFHCDDDDFCFDFGHCFDHEFEFDCHBBBHAEDEDBAAHCEFDCDBDFDBEEDBDHEBDHDGFHDHEGGGCB,False +919,5.0,11.0,3.0,9.0,10.0,8.0,8.0,5.0,BFBHEEEBCBHEHGAGAGDDBDEEEHABFCFBAGDCDGDBDGAFEFEFDBDGGFBFBHE,False +920,5.0,0.0,5.0,4.0,1.0,1.0,4.0,2.0,CGAAFADHDCACGCECGDGDHA,True +921,24.0,17.0,18.0,26.0,23.0,31.0,24.0,25.0,EDEDCDADFGBABAGGFCFDFEGCGBHHECEADGDEDFDFDBEGEFCAGFEFEFDHEADHCHAHFHFHEGEDDDDBGEGEFBCDCEAAHDBAGHDHFGGHEHAHAHAHFHFDFBGBHCGAGFEFEFADACAFEBGCCDBEBADAFBGCFAFCHCHAFEFGCGBGCAFABCDAFBFBHDHFHEGDGHFH,False +922,12.0,3.0,17.0,8.0,6.0,8.0,19.0,16.0,GDFCHCHAADGBHCHAFEHCHCBGBCHFACAFADGGGGGGCGCAADHEHECEAEDDCCEGFGFGAGAHHGHGCDADCCHHGCGFHFHGC,True +923,13.0,7.0,15.0,17.0,15.0,11.0,14.0,5.0,GDDDHCCBCDADAEABADADGHFDCCACAEAGGDEEEDFHFBDGCHBFBFDGGBCDDDFCFCFEEGCFEFADADACAGGGGEGCCAEBEHEGEFECE,False +924,19.0,22.0,14.0,20.0,28.0,12.0,19.0,18.0,CGCDHBFBHGEBEADBDGDGDCBCDCHCEBHGEGEHEGDFFCEAEDGCGEGFDEEEEEBABCBCBCBCBGFDFAEAFDHDHEHFDAAHHHHEAEADAFEFEDBABDHEFEAGCBBFHDHBHBGBADHEEDBDEGBAEAGGCGHBEGGAAAEA,False +925,20.0,23.0,18.0,19.0,19.0,27.0,21.0,22.0,FEHEHEGDGCBDBHBEBCAGACHFEFHAHADAFGBGFFEGECEHDGDAHAHEDCCEAGFDFEGCCBGBFBFHDADCBCBFBCCHBHAHBDCECDFHFGFADCFFFFBFADBGGHADFDBBCBGHHHEHEHBAEAEFGBHBHGAGEFEFGFGFDCDFBFACAGAEADGDB,False +926,8.0,4.0,5.0,5.0,6.0,5.0,4.0,8.0,FGFDECECEADFBFBHEHAHADAHAEACGDADHHHBHFACBEGCG,False +927,4.0,9.0,2.0,4.0,9.0,4.0,11.0,2.0,GHGBGDGBGBEAGFGBBBBDDEBGFGEGEDECEAEAGBFCEHFAE,True +928,19.0,13.0,20.0,26.0,25.0,21.0,11.0,20.0,DDDFAGCFCHADFCCECECFBEHDBEBEDEHEHCFAEAEAEFDFBFADAEAEAEADHDFDFGBGBADEDBHCGCFCBEEAEHECFHAGACCCDDEDHHHHAHDDDACGHBACFCFGDEFEBHFHFCDDDHDACECBDHGHEEFGBGFGFEDHFBA,False +929,31.0,26.0,25.0,22.0,30.0,19.0,16.0,16.0,GADBEEEAEAHACCCCFGFEHBGBGCFCFDDADGBAAAFEFAABEHADFDFACAHBHGEFBAAACFCGABEGFABGFGEGFBFBEBFDEDEHGFEECHAHADADADCHEHEBEDABHBEACADBDBDGDGDCDCACHEHGCEHDCEABCFAEDFDGCEBFBAAEHEDEBCBCBCBCBEEAEBCHC,False +930,5.0,6.0,16.0,9.0,2.0,8.0,6.0,8.0,FCFCBBGDGDBABHCHCGEBEDDGACFCFCFCHCGCABHCCCCHFHCAGFHHCAFDDDDD,True +931,13.0,10.0,13.0,5.0,17.0,8.0,8.0,11.0,AEAEAHAEECBHBHGHAEBFCEEAEBEGCHBFBGEGFACADAEGEDBFCCHHBHBHFHCGEGHDDCDCACAEAFBCGCFEFECEA,False +932,13.0,15.0,7.0,16.0,20.0,10.0,5.0,18.0,AEABBCHEBEHEFEDEAFBHBADFHHDBDEHBABABABACDCFEFHFEGGACEDEHEBBAFGHCEDEDBGCHHDBDBEHCHDADGDEDEDHFEEEAHAHFHFHD,False +933,4.0,6.0,3.0,4.0,2.0,6.0,4.0,5.0,AGAGAHBEEDCGBGBCBDFDFDHHAFBFHFCBHF,False +934,5.0,12.0,3.0,2.0,5.0,4.0,9.0,11.0,CEDBABACFFGFAEAGCGBGHGHBHGHEBBHBHGDFHHHHBEBEAGBBBGH,True +935,8.0,6.0,1.0,11.0,7.0,1.0,14.0,7.0,GEBHGHGDBAEEDAGGEGDGBGBHHHHDDAAAAGDGDGDADABCEGEHEDDFGGB,True +936,12.0,13.0,17.0,16.0,15.0,22.0,16.0,19.0,HHEDDDDGDGAFACACHCFEEECACADBGHGFFFFFFEHEHCAGBDFEFDFEFEHEFFBBABFCHEGFGDHBCBCBEEAHCCECDDBFBHCHFHFHDEDGGGDGBGHCBGAFDGDGCAHBCCHGHFHFAA,False +937,3.0,4.0,1.0,4.0,2.0,0.0,0.0,2.0,ADDEDEHBHBACADBB,True +938,5.0,10.0,7.0,7.0,2.0,7.0,13.0,13.0,FCGGGHHAFEFBFBGBABAEGGGGCFCFHBABHHDHDHFHACDBBGHGDGDHCBDHCHGBGDHC,True +939,0.0,2.0,2.0,0.0,2.0,1.0,2.0,1.0,CGEGEBFBHC,True +940,15.0,12.0,17.0,12.0,18.0,16.0,21.0,10.0,DADACBCEGEGCCAHFCDCDAEACDCFGDAEBEBEACABEGGGABACDFDCGGFDDHCGFGEGBCBDEDGHGFEFBFGGCBCEEFAFGFHFAFHGHGCEFEBHBHGEGEGEFAFAHACBHE,False +941,21.0,9.0,18.0,19.0,23.0,21.0,20.0,26.0,EGEDHBHBHGHGHCEAAGBHBDDDGGGDGFGFEFGFGADHEFEAEAFAHAEAHBFECDCAAGDFAFHEHCCDCEFHFHFAEAHACFCFCHCECEHDDGDHDHDADEBHFEGAAEAFBHCCEGGDEDBCHADAHFBFCFCGGEDECFHGAGHECEHFH,False +942,23.0,23.0,25.0,23.0,16.0,18.0,18.0,24.0,CAHDBDHDEGCADHGHGHGHFCDCHCDFGEDEDHDHBHFDFEEADAEABFFGFGACFBBCFCBBFAHCHCEEDCCFHACACABHBFFFDFECACHHEGDGDEDBHBCBHBHADABHBHBCGHACBCBEBABCGEEFEAEAGGCDDDDAGAGAHBHDGBCFGFDCAGACAB,False +943,9.0,5.0,6.0,3.0,2.0,3.0,4.0,6.0,DBDHCFFHCEAEGBGBGAHCHBBAGFCAHAHACADACA,True +944,1.0,5.0,5.0,2.0,2.0,3.0,5.0,5.0,EGGDGHCBBAEGHGCFCFBHBHBHCFCD,True +945,23.0,12.0,17.0,23.0,21.0,25.0,31.0,23.0,AHAHBHBHCHCEDDFCACDCDFGFBHBCCGFGHGAAHDEEGECFAHAHFHDHEADFGCGCGFGEADBEAEBEDDBCBHAAFAFAFDGDHABAEHDHGEEEHDADGFGHGFEFGFCFAFHFEFADGGEGEGECFDHCHDFGHGDGCAAGAGEGFDBGCEBGBGDEDHFFCFGAGDG,False +946,7.0,6.0,9.0,5.0,3.0,13.0,9.0,7.0,BEBECFHFHAHGCAABCCFGBGFFCFGFBFDFGGAGHGFFFFDBCGHHCHCDDADAEAC,False +947,12.0,14.0,22.0,9.0,8.0,15.0,19.0,16.0,GGGGGADFDBBBCHGACAHBFGHGHGFGCCFDACHGHEFFBCBGEGDGFHHHBHDGDCCCCGBFHACACECDCFGBHBHBCEFECHCBCBCHGFGDAAAADAEEFCFCACFFEHB,False +948,23.0,29.0,24.0,18.0,9.0,25.0,25.0,32.0,BBBHGFAEAEBEBCFCFAFAFCFDFBHBGCHFAEGDACAGBHCHFDBCBGGCCBBHHABDCFGHBDCDBDGFBCAFAHHGHFHEHACEGDABGBGHABABGHHHFBFCFHFABAEAGACBCFHHBABCBCBCACFCHGHCHBGBHDDFGAAFFFEDDDGDHDHGHGHGHDHGHGHDCDCGFGFEA,False +949,7.0,6.0,5.0,7.0,7.0,6.0,6.0,12.0,HHCHADDCGBGFFHDHBBCHCHBFADAEAGAFAEAHBHEEEEHHHBGDGEGCDFDF,False +950,24.0,23.0,22.0,11.0,20.0,30.0,30.0,14.0,EHFBFBFBCCFCAAACEGBFAEEBHCHFHEAEAGBGHGHGCGCFEFAFBEAGAEBGDGCGHGHBBGBGBFBFDFECAGGFEBEGCAEBEDGHAFBHBFBDGDGFGDACCGCECACAGFCECHDFBCGCGFFFGFGCBCGABADFBHGGFGDHDEFBHCAAAAAAFFFFFDEEAE,False +951,16.0,19.0,15.0,15.0,20.0,28.0,15.0,17.0,DGGFECEHGHFHCBCEHGDGCBCGCEEFAFAFAHEHFAABHEGDGAGBGEEBHDHBBCBCHFBDBDBHEDFCAEAFFFDFDFAGBCBDECFFFEFDFBFGFGEECECEFEFEDHGCDAHAEABBDGFBFHHBHDAFHFCFAFABA,False +952,9.0,0.0,6.0,3.0,8.0,5.0,2.0,3.0,EFACCCFAAAAHFFFDGAAEAEHGHECECEDECEAD,True +953,2.0,1.0,1.0,1.0,6.0,2.0,3.0,1.0,ECEHDAAGBGEEEEFGF,True +954,11.0,9.0,7.0,13.0,13.0,4.0,8.0,8.0,CADHDHDFDABBEACAFDBBHFHGAGECBGEGEGEBEHEDEAHBGDADADADFDEBEDDCAABHEHCGEGECC,False +955,17.0,19.0,17.0,18.0,12.0,19.0,16.0,32.0,GFGFAAGFGAHADGGHGEBABFEDBHBDFHHHHBGBHDHDEAACBFBFBEAEHCDDGDFHHEDGHGBGBGADHFHDHCCGAEACDCDCAHAHFHFHFHDBDADHCCCHBACACBHFHFEFECACGEBBFDHCHDHBHEFGCECHFFBHBH,False +956,21.0,23.0,17.0,24.0,20.0,16.0,15.0,22.0,DADEHFHDCBCBCAHGBGFDFDGBAFDFDHHFDBDBACACFEHEAEAHAEEBAGCHCFCFAHAGDGDADADHHGHGECCFCFGFCHAHGDGBCCHADBDEAHGCFBHBHBHEEEEEHEBEAEGDBBFBHHCDCEBBBDBDBAADGFABADFEEGEDDB,False +957,10.0,10.0,8.0,10.0,12.0,10.0,10.0,2.0,FGFBFDFCGGFGABBBDGAAAFHFDGDBDGDEDECECECECGBAEHECGDACEBGBDFCAEAFFEDEBABAE,False +958,23.0,37.0,29.0,27.0,20.0,20.0,23.0,19.0,ADBDBAFABHBADGGCCCHFHGBBDDCACACBBAGDHDHCHFECBHFEGEBEDCCFEDEFBFBCBCBHEHBGDCDGBGAGAFFGCGEGAADACADBGFEDGBGFDBHBCAHEEFFDCDADBDBACDCDCDBHBHFEFHFDBGBGEFHFHBACECEDEBCBCBCGCGBBACAGEFBFBABGDGDHEHEGBCDCBHEAAA,False +959,12.0,18.0,18.0,8.0,12.0,10.0,17.0,15.0,BEBEBGBGBHBCBCECGCGCDCFGGHGBCHEACCCEFGAAAEHBHEHBGBHAEABHGFCFCDCEABACAHEHCGCHFEAEGDBDHDCGFDCDAHBHGFDFGGGHFBBBAF,False +960,6.0,8.0,14.0,11.0,10.0,8.0,6.0,15.0,EADADHGFDEEHFHDHBHBHCECDFDBDECHFFAFGFBEDECBCECHHHHGCGDGDHCCCCCCEEDHHAHABCGFABB,False +961,20.0,29.0,25.0,20.0,25.0,26.0,26.0,18.0,BHBEFEABGFAEGDGDFFBDHDGBGBFFFHEEEEEDFAFADABGGCGCBCBAFCFABCCHEHGDDEDEGFFAAEEEEAGCGAGHGFDCCBCHGACACEDHGHGAFBFBFAHEBEBEDGBHCCEAEADDDHDCBCFHAHCHBHBFBFBGGGBHECGFGECBCBCDHDBBFDCACACBFGFGEGCDEBFBF,False +962,27.0,19.0,27.0,18.0,20.0,32.0,29.0,28.0,GEGECAFAHHHHEAEBDBDCHHGHFEFHDBFAFBFDGDBCBCGHGHFCFCFCFDEGADHHCCADADAGEHEHGACCHGHBHEHCHCHFECGCFAFBFAFGFBCAEFCDHAGFBFHGEGAAHGFGEDEACDCFHDDCDCFCHCGCEDGHBDAAFAGBFBFHEGAFACADEFEBEGGGCGCBBFBFGAGAGAFABAGFBEHF,False +963,18.0,20.0,27.0,19.0,14.0,17.0,15.0,25.0,FFACCGCGCDDHCHCDGGGEHFBCBHFCAAAAHAGFGDGAGDGHFBDEDHCBCACACGCGAFEBBCECEAEHEHBBCHHHHAACDCDBDFCFBFBHCHBHDGCEEEHEDGBBBFEFHFHDCDBDADAHFBCBABDCEAHHDACFCGHBHFHDCFE,False +964,12.0,10.0,8.0,9.0,12.0,10.0,10.0,9.0,FGFAEAEAGADFEECEHBBBAHAEBECECAGGHBAAGEHFHDHAEFDFECDCBFBFBABDDFDGGFGCCCEHAHBHGDGD,False +965,17.0,22.0,24.0,31.0,26.0,22.0,22.0,27.0,CGCEHFCFCEBDBDBEHEHGHGHFABABHEHFBEBGHDHDFCBDBEBGGCHCFDFHEHDHDGDFFBCAHAHGEEFHBHBEBADFFAFAHDHGAGAHEDDHDEBEFEBEFHFHACADDDFDEEEECCCDAGADBGAGFEHBGGHDCCCDEDGHCECDDABFBEBCGEGCGCFCDCAAEDCBGHGDFDGDCDF,False +966,27.0,18.0,26.0,14.0,26.0,27.0,37.0,24.0,AACDCHCFGHAHAGAGACFHEHABFHFAGHBCBDBFBFBABFHHHFHFCEDEFACHCECFGFEFECGDGHGCGFGEHECDCBCBGBECEDFAEECAGGFAFBHEFDGBGEGHFEEGEHCGEGDGDGDFCCCCHBAEACHGHGAGHGAGEHEGEGBCAGGGFABHDADADAGAFHBEDCFAEECFGFGFGCGABEFGABA,False +967,19.0,30.0,23.0,20.0,26.0,19.0,25.0,21.0,BBABCBGGAGFDFGHDHEGBGCGBBAFDCBCEFHDCDFBCBGEFBHBEEEEEBADAHAHBGGGEDBFBHCCCECBGHDHDFGBDCDFBEHECGBGBGFCFAHEHDGEGEFDFDECCCHCHEGEGHGBCEAGABEBABABABADADABAEADCCEFBABFECDFHFHCHFEFCGGEHEHGDADH,False +968,22.0,15.0,29.0,26.0,37.0,20.0,22.0,24.0,AEGBABEFGGEGDHDHAHEFECEFACEEACHBECFBABCDCACAHGHDEEFECECDAAAEHGHGHDHDFGFHCADFDBDEDEAEDEDEDEDGGECEABBGFADADEHGHFECBCAEAEGECECAGDBEGAACCCCCCBHEGECDCDFHFHFHFHFCGEGHBDFEBBBGECHDEFEHHGDADCGHGDDCEFHFCFC,False +969,16.0,6.0,14.0,15.0,9.0,8.0,13.0,13.0,HHHHFEFDDCAHGGEGDGDCBBHCCDADGGHAAADADFDFDGDGDGABEBAFABECDHAAFAFEFGDGCHEHCDCGCEEHHHAEACCCCBCGAA,False +970,21.0,25.0,9.0,17.0,8.0,13.0,18.0,16.0,GBGHGACACAFHFBCADGGGFGFGAGAGBBDBGCHHEHEBFDEABGDGDGBHBCDFFFFHFHAHBDACAHDHCCGAEADBHBDFABABABEBEAECGGBHBHDFBBBBAFDDAGBHHABDDADADBE,False +971,9.0,10.0,11.0,9.0,15.0,9.0,14.0,12.0,EAEDFCFBFBAGHGHGDGBHBGFHEHCFAFAGHECGCHCADAHCEGDGCGBBBBDBDEGFGCCFHEEEHEDEAEDBCGHGCADHEFEAE,False +972,18.0,16.0,12.0,13.0,15.0,19.0,12.0,21.0,BEHFBBABAHGEEAEAFAFCDEHFHAHCGCFBEAAFGCABHHFHFHCHBGADCDHDHCHCEEAGBFDFGADFFFFBFBGDGAGAEADHDHDAEEEBCBCBHBDEEHGFGFBFBDEHCHGHAHFCAD,False +973,27.0,25.0,26.0,28.0,24.0,17.0,20.0,27.0,HCHEFEACGCFDFGCBCHADFCFBADCGHBHCDDDCBAAHAEEDADGDGHGHGHGDAAEBEHAHGDADADEBEHHCEBADAHHHHCHCAAAHBFBDCGBFCHEEFBFBFHAEADDBFBFBDGDEHEHBHGCGAHACECAFBFBEEEBECEFDCCABDBDEDEGAGADEDEDCFBBACHGGFGBGCGDADCHCBC,False +974,2.0,9.0,5.0,14.0,10.0,16.0,13.0,8.0,HBEGFBDBDHEEFHFEGDBFBFBGHFAFDFGFCFDBDBDHDHBGGCFFEGEGECADGFECEHFGDCDHDEDGFGFGD,True +975,7.0,10.0,11.0,8.0,6.0,8.0,11.0,11.0,CECFCDCHGGGGHGAFCECEAECDCGHHBADHDHDBDBFBFDAHGBBBBBBGCFFFAAEHDFCHGAGHCHGE,False +976,22.0,16.0,20.0,24.0,18.0,27.0,21.0,14.0,GDBDHEGEBFHFHDDCFCDAAGEFBFEDBAHGBGBGDFEBBADGHGFABAFAFDCDCBCAHADDDCAHECCDAAFAFGHCCECFGECECEFDHCHAHGBGBGDECECECEAEAEBFBFGHGHAADDFDBDGAFCFBHACAEEFGFAFDFDFGFGDCDGGFFF,False +977,16.0,17.0,23.0,22.0,27.0,15.0,19.0,22.0,EEGGFDFHCHEEAEDEHEHGCEFGBEBEBHBDDCBAHAHDGDAEGEGDHFECBDDDHDCGCFAAAAAFCEHBBEECEFDFDBDBCCCCEFEGAFFCFCFCEBEAHAHAHAGGHGHCHCBGEDBDGEEHCDGHBCBDAHFHBHFGGDHDEDAGECECBCDCG,False +978,5.0,8.0,11.0,18.0,14.0,13.0,11.0,18.0,HFHDBAGHGEFEHCGGEGDAAFHFEFEFDHDGCECHHEHEDEDHGHDFBFCDHHHAHEHBCBCBCDCDGDECEDGDEBFGDCDEBGHFBFDCDFHFDA,False +979,22.0,10.0,19.0,14.0,19.0,26.0,19.0,18.0,HBGDGHGCGBGEFEAEFBDEHEAAHGGGGHDHDHFGEABAFAHEHCACFFDFDFAFECGCDCDCDCFCHCFCHAHFDCBGAGDEHBGEAFAHAHEFAGHEAGACEEEFFFFEFHFBFCFBACGCAFAFCBEFEGEFCGBDDDCAAAH,False +980,9.0,10.0,16.0,13.0,13.0,13.0,17.0,6.0,CDCEBDGFGFACEBDHFCEHACADBDBHBCBGACCECEFEFGFGACHCACDEEGGGEGEGDGCFFFGFDBDFGGAGAHACDDDDGEGFCFCEHBBEB,False +981,19.0,23.0,15.0,12.0,16.0,18.0,17.0,17.0,ECEDHFHFHFAGAHBHDAEFGFBEHGBGBCBHBCEDGDCBHEAGADEGHFHDBBABEBAGAGCCDADHDCGBBBEGAGAGEBBBGFGFCCBFBFEGHAEGHFCFCFCACEDHDAAAAAHDBFFHFEFCBCBEBEFHA,False +982,21.0,16.0,13.0,14.0,20.0,12.0,19.0,12.0,EBEBGBGDGEGECHCHFAAEHBCAEBHBECECACGCDCDCDBABAFABGHGHAAEAHABDEDEFHFGBCDAEAGFGECDHGFGDDDEHAGGGEGBCFDFAFBEGECEHAFDFGABADAGAEBHFAEB,False +983,22.0,16.0,20.0,28.0,16.0,18.0,28.0,14.0,CGCGBDCDCGHACGFDFDGDBDCFEFEFADAECBDDDEAEAEAHAHABGDFAAGFGFGCAAGEDEGFDFDCGBGAGBGHHHGABCBDBDFDFCFDFGCAHAGACABAFEFAGEEDEHBCCHEGBBBDBDHGEDCHCEFAHHGCDHGGFGDGDGDBEGACDCD,False +984,26.0,22.0,19.0,22.0,24.0,27.0,32.0,24.0,ADHHEFAFADABADAFABCGCGAGFGFEDADABEFHFHGHDFGEGADCCFHHHGHGEFCFCEBDGEFEFEGAFBFBFAHGBEBEAGDFAHABAEGHGCECEHBHBDCFFHBAAGAEAGBCCDCDHDHDBDBGBEDDDCBBFBGEDFDHGEGEGEAFAGGBGBHEGBGFGDECHFAFEHHFCGCGEGCCHCHAAFDG,False +985,7.0,9.0,7.0,9.0,13.0,11.0,7.0,5.0,FCBCHEDFAFHEGBGFAEAEAEAFGDGDBDBABAFGEGDCHCHEEBFCEEHEBEDEFFDFGBDBCCFD,False +986,8.0,13.0,17.0,13.0,13.0,11.0,14.0,10.0,HGEDFDFDFDHDHDHDBFEFAGAEBEDGDHHFBBEEABBBFBHGHCCBCEEGECFBACDCDAAGCFCGBGFFEAGDGHCCDGEGCGCGCHCECBCACEB,False +987,20.0,12.0,18.0,25.0,18.0,18.0,21.0,30.0,AAADFHFAADFECBCECEHEHADCDGDGDCFHFHGCGCGFGFCFHDCAHEEGDGCECHCHEBFBHGHGEFHBHFGDADEDHDAFADEHBBBEGEFHADFDBCGDHHGHGHGDGDHDGDFCFEGGFGCAAEAEBHAHADBHEAADHDCECHDADHCHBHFHAB,False +988,20.0,13.0,12.0,16.0,10.0,14.0,25.0,12.0,BBBCHGHGAGFGHGDCACHCHCAAAAAAEHBDBAFDGDGDFCGGEBAFDEDEHEDGDEDADABCBFDGAGAGHGAEDBGGGGDGBFBHAAGBGHDFEFGAEECCGFFBFGFGHCHAFFCACD,False +989,12.0,14.0,12.0,10.0,10.0,5.0,11.0,8.0,AEFEBABAHACGFBABGBGDEDGDEBBCBCHCECBCACDCGHGHGEACFCBBBEFGDDDCDBDADGEHAACHEGAGFBEHAH,False +990,22.0,22.0,18.0,21.0,13.0,23.0,11.0,18.0,AHAHEFFDDCDFGHDFDECHDHABEBCBCEAFBGGGGFCHCBCHHBEDFAFABCHCBCBCBABDDGHHDBFGEEDADFECGBAECEADADADAFFDFBFBFBFAHDFDBHBDEAEFHFGAHAHAHACCBBABGCGCFHFAFDFDEBCA,False +991,10.0,6.0,7.0,9.0,6.0,4.0,5.0,5.0,FDCBCGFHFHBBBABGDFDAGACACEEECAHDDGDEAAADADAECECHDBGH,False +992,9.0,13.0,4.0,15.0,7.0,15.0,17.0,13.0,DEAHFHGHBEGEBBGFFFAFDFDHDGDGHGHFHFDDDCEGBACGDBDGDEHEHGHGBGBGHFBABABFFFAGADHDGGGHFACBFEDDBCAFB,False +993,1.0,1.0,4.0,3.0,4.0,6.0,1.0,3.0,EFEFEFAFCEGDFHHHDFCBCDC,True +994,16.0,14.0,21.0,15.0,11.0,19.0,16.0,24.0,AHACCCDCAAFBFEFBDBAAGAHHCHDHEHAHEHEBGAGAFHFCGCEFEFEDACHCHCGGGFDFCHCDDDHDHAECHGBGBEHCFBDBGGFHFGBAFHFCDADCFCBCBCEHAHFHBCEGGGFAHBHDCDFHFGDB,False +995,7.0,6.0,13.0,6.0,12.0,13.0,4.0,9.0,CEAFHCHFHECCHEACFCFGGAGFCHCHFAFEDHHCECFBDBDGECHDFEEEEEEBABACFCFDFDFBAB,True +996,4.0,9.0,13.0,8.0,5.0,3.0,3.0,5.0,AGAEADDCACBCBCDCDEHECCFHEDBCBCDDDFEBHBHCCCBBFHGCGB,True +997,3.0,1.0,1.0,6.0,4.0,5.0,7.0,3.0,DDDFHEHCGFGFGFGEDAGAEHFDEDBGAG,True +998,18.0,17.0,15.0,15.0,11.0,15.0,12.0,20.0,EBCFCHHAACHCHCHGBCBCBCHDADAFAFEFDFDGHGHCBCFFHCACDFAFAHAEAEAEFEBCHAFBHBFGAEDBDHDHFBCDEAGABBHGADDBDBDHHHEBAGCEEHFHBGGDGFGAGDB,False +999,6.0,13.0,8.0,13.0,6.0,19.0,12.0,12.0,GDGCGCHCAFGFEFBFDEDHFBFBDBGFDADBFBACGBGDGEFBHHHHBDAFGFGBGHCFFECEFEFBAHFDFBFDAHCHDHCHDFDGB,False diff --git a/tests/results/nb_gm_002_2back_240trials.csv b/tests/results/nb_gm_002_2back_240trials.csv new file mode 100644 index 0000000..1c50201 --- /dev/null +++ b/tests/results/nb_gm_002_2back_240trials.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,ralph_skewed +0,30.0,39.0,31.0,30.0,32.0,24.0,27.0,27.0,False +1,33.0,23.0,27.0,32.0,37.0,34.0,25.0,29.0,False +2,31.0,20.0,37.0,28.0,31.0,32.0,26.0,35.0,False +3,27.0,32.0,39.0,24.0,25.0,34.0,35.0,24.0,False +4,34.0,24.0,38.0,28.0,31.0,29.0,28.0,28.0,False +5,29.0,24.0,36.0,31.0,32.0,32.0,31.0,25.0,False +6,25.0,38.0,28.0,30.0,33.0,30.0,26.0,30.0,False +7,27.0,30.0,30.0,29.0,32.0,26.0,33.0,33.0,False +8,24.0,36.0,32.0,23.0,30.0,29.0,35.0,31.0,False +9,35.0,34.0,30.0,29.0,35.0,26.0,23.0,28.0,False +10,30.0,25.0,33.0,31.0,27.0,37.0,30.0,27.0,False +11,28.0,28.0,29.0,26.0,28.0,27.0,34.0,40.0,False +12,35.0,27.0,30.0,29.0,26.0,30.0,36.0,27.0,False +13,38.0,27.0,31.0,27.0,34.0,23.0,27.0,33.0,False +14,29.0,30.0,28.0,35.0,19.0,30.0,37.0,32.0,False 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+9,11.0,23.0,19.0,24.0,13.0,20.0,28.0,13.0,DFDDFDGFDGCDFFDFEDCCDEGDAHEEDGGGGDAGHFBHFGEDAFGCHGFDBCDBDEBCHDEBGEAFBCHEFEAFBHFCCGEDGADGBCBCDACGCCGFAGBBDCGDBBBEBBECHACFAGFBGABCBBGFHHFHHFGHGGDGGBGBCDB,False +10,10.0,15.0,13.0,9.0,5.0,13.0,10.0,23.0,CAHCFDCFBGFGCFHBHAGHABAAHGFBAFDFBDBHDHCBGEFGDCBDHDEABHHHHGCFCEFCDHCFHBHHGHHGFHGBBABCABCABHEHEFHDCH,False +11,29.0,21.0,32.0,27.0,25.0,25.0,8.0,18.0,HEFAEFGCBEBDCBEADAADADCADABDHHFFEDFBCHACAAFBAFDAFDBCCCFDCEACAACEABFDCFDCFHHFBHDEFDAFCABGAEFDCDCCBCCDCDFAEFDCGCCECCBCBHDEGACBAHBEBEEFDBDHAFHAEAEECEGGHDBHDHCDEADEAHEHFEBFCBAHBHDEGAEFFCFCG,False +12,28.0,27.0,32.0,14.0,15.0,33.0,26.0,13.0,FFFAAFBAHCHHDHGCBBCEBFDGEGBFAACBACBACBAGBGBAGFFGFAHDGHEEFCAAHAHHECFBBFACFACAACDBCAEAHDFHFFCFFEFCAFBEFBFCBCABDBGGFECFGCBCDGGBGFDGDABBCCBEFBEFBAFDACGCCEHGAFCABDGEDFFDCFDGFGGCGGEEGCBGAAGCCCHC,False +13,29.0,16.0,17.0,15.0,16.0,11.0,15.0,11.0,CBECBEFBDDCDCAACAABFAGFEGACCECBEHBEGADFADFBBABCAHCABAABHEEEACEHHAGHABACGDHGDFGCHGCAGDAFAAFCCFEAEBAEDFDDGEABHAGAAGDGBAEDHHGABFEGDCD,False +14,17.0,24.0,25.0,11.0,18.0,20.0,15.0,30.0,DDCDHHAABGECDACBCCFHGEDGAHBABBHFBFFBCFHCHECHECACABHHBHEBHBHDCHCFBAHBFHBEBEDCEDEABCHCHFCHCAFBFBBHGEHGEHGHFCHACHCGGCGCDECFEGHEDFBAFGEFDAAHAHHGFHFABGEBGABGFFEFCEBC,False +15,8.0,6.0,1.0,3.0,4.0,2.0,2.0,6.0,EHBEDEHGEGFABBADBAHCAHAABDAHHABF,True +16,20.0,17.0,20.0,17.0,21.0,21.0,26.0,21.0,DEHCHAEHFEDFDHFCHGCGGCGAFBDDBDCFGEFGEFCEFHDHEFFAGDGDEGAHGFECFACFEEHBEHBGHBGHBGCECEDAHHBGFCCCADHAGHDEDBADGHEBDCHCCFAGEAFAABGABAHBAHBGHCACBEFEGAEFCECBGFDGFDGAGBAGBFG,False +17,12.0,3.0,7.0,9.0,7.0,12.0,9.0,8.0,ADGAGCADCFDFHEFDGHCEHAGGCDAHDCHDAHAFDAFEGFACFECFEBFGBAGAFFAEBDEHGHF,False +18,18.0,19.0,24.0,16.0,21.0,13.0,23.0,20.0,GGEGFBDFGDGEDAHGFBGHAGCDGCAAAHACECDECEBBEDEEDECDFDHBCCDHBHHACBACFHEAEEGHEGDEGAHBAFBEEHCBHCBGGFCGECGECBCAFCGHCBHFHHFHDGGAAEBFCBFDBCBECDCADCACGBHGEHGBFGADHA,False +19,10.0,14.0,15.0,8.0,25.0,14.0,11.0,20.0,EEEEBEEFHEHEEFEEGHEAFFAFHACGDCDDCFDCBDCBFFBCEAHEAHGCGGHGCHEEAEAHEAHEHHCCFGHABHGFGCHGCFDFHEHBBBDFBFBCEAEBHCDGCEEEHBBHB,False +20,16.0,9.0,19.0,17.0,10.0,22.0,10.0,24.0,HFGDDAFEAFEDCGHAADEHDBHAHDCGBAHBECEFFFFFEFEEDHEDCACEGHBGCFGAGGABDHFCHFCHCCDCFHHADFCFFCFFCBFCDHHHHDFFGHHDACDAFDACDCBHCHHAGHABHAB,False +21,6.0,10.0,3.0,4.0,7.0,3.0,3.0,4.0,EABBAEFHEFABAACHDCDDEFBEGHEGBDABHBBCBGEB,True +22,6.0,11.0,12.0,6.0,9.0,6.0,9.0,10.0,AEDBCDECBCHBCBBGFBGFHGEHACHAGAEFBDAECHCFHFDCCECGBCGECGAHGBHBHEBHDFGDE,False +23,11.0,8.0,12.0,13.0,7.0,5.0,13.0,9.0,EAAGACDACDHEEGGGGGBEGEABEAHGCHCCAFCFFGDHGDGCBGBDDEAFAADCDDCDDHBCGBCAFCBDDHHBHH,False +24,36.0,26.0,18.0,26.0,33.0,19.0,21.0,15.0,GBCHFHAAHAFFGBBEFBCFAEFDFGEGEEBECBEBBABBAEBEEAEEABGDBADBACFFBEFCECGACFADABCFDCDBCBBHDHHACGGEHDEGDEGAHAAFAAEDCCHHDDGDDBDGBDBDDCDAGAAFHEDHGDACDACDBGEEACGAEEBEHAFHBGAAAAAAAEEFBEDCDAEEEFGEGGHGFEAFED,False +25,11.0,17.0,16.0,9.0,15.0,15.0,6.0,9.0,CEEFABDBGDBFDFFDGADECBFCBCCACFABEABFABEGBEHBAHEAHEAECCFFCHDCBBBFGBAGCDFHHFBDFDCCHHEHAEBEGCCBFEECEF,False +26,8.0,5.0,15.0,9.0,10.0,7.0,11.0,5.0,ECAGCHDBBDCCDCGHBBEEFDHFEEEHBHGADADGFDEFGAFGAFCCCCCACCDCDGGECGECGEAGFA,False +27,9.0,11.0,8.0,5.0,8.0,4.0,2.0,4.0,FCAFDBEDBABAABAEEAEHDBHCEHCDBCFBABEEGECGBDABFCCAHCB,True +28,6.0,8.0,11.0,7.0,10.0,5.0,9.0,9.0,CFBCBCCBACBEHBEGCADHDGFEGFHGHDAFBAFBEDCDGCHGAACHCHBCEEEEDHEDGEGGH,False +29,24.0,16.0,18.0,25.0,13.0,19.0,26.0,18.0,HEFHCDEGDHFBACGGDEHDGHDGFDEAHFDHGBHEBGEGADFFGCCGDHFBFABDACDABAGFGDAGDAGCAFFAGHHCDHCHACEDDAFDCCDCAECAEDGEDGAFGFCGFAGBBGFBDBBAABAAGADGAFCHBEEGHBGCBFCGFAHHCHDBDDE,False +30,6.0,5.0,2.0,9.0,2.0,4.0,3.0,8.0,DADBAFBDFHDHHBAHEADGFBHFGHEAHDHBDGDCADC,True +31,19.0,18.0,16.0,13.0,19.0,13.0,14.0,15.0,FCHGCAEHAEBDEBABAABHAFEBDCBDCBHCGEAGEFBAFCCECCBCFHEHGEGAEDAECBECEAFEBDHBDEAGFGHDGCDGADFAHGCFCBFDEHEGCEABFADHAFHGBHABHBHDAEBGDFG,False +32,7.0,12.0,12.0,10.0,7.0,5.0,5.0,9.0,EBDGBGBBDCBACGHBDAAHEBGCBFHBFGAFEHFCCCHDCHDCHDAHDCDDEBDEAFECBAHBECC,False +33,1.0,4.0,8.0,1.0,4.0,4.0,5.0,3.0,GAECEGFBHFGHBGCBFCECCECCBCHDGF,True +34,5.0,4.0,6.0,9.0,13.0,13.0,5.0,7.0,CHHEFFDFFDFFDFDGGDFGDHCEAEAHEAFEBFCFEEFEECAECHCHFDEBDBGEGABDEH,True +35,3.0,2.0,3.0,3.0,5.0,4.0,0.0,6.0,CBDEEHHEAHCAEBDFADFHFCHFEH,True +36,13.0,2.0,13.0,8.0,7.0,6.0,16.0,9.0,DEGDECDHGAHGEDGEGACAFCADGACGACHFDACHCCHCEECGHDHBEGGGGCADCAFAGFGGBAGCAHFHFA,True +37,18.0,19.0,17.0,17.0,13.0,17.0,15.0,23.0,HBCABCGHCEEADEDCEDGAGFFFHDFADHHBHHGCHFHHAGHEHEBBBDEFECFEBHCDAADFGDFHDCDCCDCCFACAACHGGBGGBFBCFBFFCFGEDABDBBDAAGAABACBEGBAHAHHFGEDGHDHHEBHBHF,False +38,4.0,6.0,5.0,9.0,6.0,4.0,4.0,6.0,AGDAGHABHCEEFBEFDEHDBHDECDFCDBHDEGBBGCCADFDH,False +39,3.0,5.0,6.0,8.0,8.0,2.0,8.0,6.0,DCEDEEGEEGAAFEHFGHDGDBHDBGBBGECECDGHBGCDDCHCAH,False +40,0.0,0.0,1.0,3.0,1.0,3.0,5.0,1.0,GDGGDCEHFGFDGF,True +41,20.0,19.0,22.0,21.0,30.0,22.0,10.0,26.0,BADBABGCFGFDDDADEFHAAHAAHEAHBBHECFGFDEHDCDBBBHGEDEECCDCCDGCHHBGHCHACFDCFCFEDFEDAHHHBHAECABDABAAEHFEADCFEBFAGFGEABECFEFFECEEFEHFEHEEHDHDCHBBHBDHCEHCDHBDCFAEFAGHEGECBCFEEFE,False +42,3.0,7.0,4.0,4.0,5.0,2.0,5.0,3.0,EBBEAEEHDCHDCGDGGBACBEHBDGBAFBFCG,False +43,21.0,15.0,21.0,27.0,18.0,33.0,14.0,23.0,DDDDDDBCGFEFFABFDHDAGCEFHHACHGBHGBEFEHFEHFCFFCHDGHDFHDAGFECCCAAEAAGHGDFCHFCHBBBFABDEFDFFBBDBAAFDAFAGHACHACEFFEFDHABCAFGDFEDCGACFADFDDFBHFAFFBEHBEHFCHEADEGHEGCDGHDHDEECCFCCD,False +44,27.0,34.0,20.0,19.0,15.0,29.0,27.0,26.0,FGCFGADGADGDDBDBAFGAFDHHHAFBAEEAGGBDBFCEFAHFAHFAECDCBBCGBHAFHABHDCHAHHGBCGECFDCEHCFBCHBGHCABFBCFBEHBECBAHBGDECHFDFBDEAFBBGECGEBBHDBHDBEABEBFCDFHHFGHFAFFGCACFGDGGHGAABCDBHBGGBGGFHGHGGBEADABFABAAFAFF,False +45,15.0,12.0,15.0,7.0,7.0,15.0,11.0,5.0,CAFCDGCFACFCCFACGBBGCAEAEGAHFADBCHACHFCFBEFGEGBDGBDGBEGEHAEFGBFCDFBFBHACAFCAFGABDAFACDB,False +46,12.0,10.0,7.0,5.0,4.0,11.0,11.0,13.0,ECFFHGFGGFCGACGFGGAHFABBHDEDCHABFBHGAHGAHCAHDABDFHDFGCHGBEABAHEHBFHBFCBAA,False +47,15.0,6.0,13.0,11.0,17.0,21.0,13.0,9.0,EDCEFAEFAFFAGHCFCEEAFGFFHFDECECCEGCDGHDGHDGHACFFCFFCDFEHEEFEEGHEDAFBGEAAHAAGCABAEFAFDABGFCFHCDEDBABFGBGGD,False +48,11.0,17.0,17.0,9.0,17.0,17.0,13.0,15.0,GAFGHHGCHBCACCFBCFHHECHBHAFHEEGBAFCAGHGEFGEDGFCBBEBGABCFDCFDCFDBEEEGAAHDAEDFECBGCBHDBFEGHHBFGBFEBFCBCCHEFAEDAEDCEFHB,False +49,13.0,16.0,15.0,12.0,16.0,9.0,12.0,15.0,BGCBAEBCDBEDBECBDCBABDCDFCDBCEGDABDFFEHCEDGECHACHEBDECDGHFFHFHEAHAHHEFFBAGAGHCHCCHGCEEAAAAGEEGDEGBFGBAGBHHBH,False +50,13.0,6.0,16.0,14.0,12.0,13.0,9.0,12.0,DAEAAGAAGCHCCHDFHEFCCBEGFEGFHAHEAGBGCBFCBFCDACDAFDCHECEBFBAFCFFDEHAGHDEFDGCDECEHCHDGADEHHFADCDD,False +51,22.0,27.0,26.0,19.0,24.0,22.0,28.0,20.0,FDCGDAACFACHGCDGEBFCBDCBGBEGBEGAGGFGGCHGDHGDCAACHADHCFHAAEEBBCBCCBAEDAGBFGAFGEGGDGHCEEEDEHCBBCDECEBGEFCCHCFBCFBHFEABEBDEDHABHDBFFFCEFCEDHFFHBFABHAGGECAEADBGGEGAABHAGHAGEFGBFBFHHDHBEGBFCCDD,False +52,19.0,24.0,24.0,17.0,11.0,20.0,12.0,18.0,FBDFCFECGDCFBBFHBFHBAHECHAAHAFCAHCHCFBDFCDHCDBDDBAGAAGAGHFGBDABCFEEAHHGDHBDCCGCCDAEBAEFEBCHBHECHDABFFBHECFDCBDBFDGGDBFABGHBGFCFCBDCBACBFGHEACEACA,False +53,11.0,13.0,7.0,11.0,11.0,7.0,5.0,12.0,HABDABEADFFDABBHBEDAEDACBEHBEGBDDEAAHAHGBHBDEBAEDECCHFDHFGHFGHFDCCEBHEBHGCACF,False +54,11.0,20.0,14.0,17.0,12.0,15.0,15.0,22.0,DFABFDGCDCDDCBHCBECBDHHHBEFBGFEGHGFHEFEAFAHDBHDGDGEDFBAFBGFBGAGGHHCHHEDBDDBCFFCGFCHEEECDDADHBHHCDHCBHFAEGBCBBAHBAGEFGAHABHCBHG,False +55,17.0,24.0,24.0,12.0,23.0,20.0,17.0,26.0,GAECBGBFHAHHEFEGCGFBGBCHHADCACHBGGBHBAHBAEFAFGGFBCCAFCFHCGHCFHCBEFBEFBCHBGFECFGDHBEHCCACGFHEDAEBAEDDEDCEHBEBBEGEEHHACHECBDFFDFADFAEFHCFHCBECDEHDEHCBAGBAGADGBCBHHEH,False +56,17.0,25.0,29.0,22.0,21.0,19.0,27.0,22.0,FFFFFGGHDEHDFGAFGEEAFEGCEADDBBDHDCHECDGCDAAFCDHBGCBGBBECCDCCDAHGBHCBGCHCCEFEGFAABBEHFEHBCGFHGCHBDHCDHCFBDEBEABEDBCDGCHCCFGCFDAGGBGBBCBFABFEGGADGHEGHEDFBBCBCGACDAEEABDADGGEGHEGCCHHAHH,False +57,12.0,11.0,4.0,15.0,9.0,3.0,6.0,8.0,HABCEHAECBEDEDDHBDGAAFHAGCBGBEAAABADEADGHDFBAFBDEBEEBGDCDDGDDHDAHDBH,True +58,9.0,8.0,9.0,9.0,4.0,9.0,12.0,13.0,CAGCGGCBAHDEFDHHGHDFDBFBBFGAFEBFECHABGGDGDEGDHGBHADGFDCACAACHBFHFGHCHHCHA,False +59,15.0,19.0,20.0,23.0,14.0,16.0,21.0,18.0,GDGGBGGCFGABBABFGEFGCDDCFBCDBEBACHABGEBCDCCDFDDFDAACEBCEGGGFHHFDHGGHFGADHFHHGDHDFFGHGGHDEBDCAACGACFADDHDDCBDBBFEBHDDHFCEGBEHCABEAHEAHEFCCHBAEBCEDC,False +60,9.0,8.0,2.0,6.0,8.0,11.0,5.0,10.0,FEBDCDFHFEHFEHEGHBHFBHFEDCHBBBAGEAGEAGHADABFHFFDBFAEFADAAHG,False +61,26.0,25.0,20.0,16.0,13.0,13.0,17.0,12.0,CBACHGCFDHEBHBBEBBFAHCCEAEEABDDBDGEGADGHDAHEABBBEFCFFDEFDAGDADBBHGGCEGBAADABCHGCHGBDBBGCBGCHFAEFCHFBFDDCAACHACFACAACABFEBFAAEGGCGBCGBAGBDDACAA,False +62,9.0,9.0,5.0,7.0,5.0,5.0,11.0,6.0,FAADDAGBGGBGBCHBCAGEADACGAHGACFECDABBFEFDGGDFGHBGHDEHBEHB,False +63,7.0,8.0,8.0,6.0,13.0,12.0,11.0,4.0,GGBDGFEGCEGCECHDCFGFGABGFEHFCGGBHFBHEGEEAEEAFEDBCFBDFDEADACBABFACFEEF,False +64,20.0,11.0,23.0,13.0,16.0,11.0,12.0,18.0,AEDAHACHEFAEFAHCAEDAEDCBAGGCBGFBCHCHFCEACHCEHCFHCEAEAAEAHCAGBDCDHCEHEGBFCHHCGHFBHFAAGEADHBDCADCFDGFDCHDCBGCGAAHCGFGDEBDEBECB,False +65,19.0,12.0,22.0,18.0,18.0,14.0,20.0,17.0,CCDCCAFHAECADDGDGACGADGHDFHEBGEFEAFDHBDGBCGCFHBGHEGAEGBDHFDFDCGDHGDAGDCBHEBHEBGBAFHGCGCCFEEFCDCCDCHECHFCFAAAGECHBBEEBHDAGAAEAAEAHEGHCFCEFGAD,False +66,26.0,13.0,22.0,33.0,10.0,21.0,25.0,20.0,CDFGDFAHFEHDHBBCDECDAHDGGGFBCDBADHHDGADEBDEGDHFFCFFDHDGADHCFHDAGEGCEACGBGGEAGFAGBBDABCABGADGAHADDADCADHAFCFGDGEFBEAHDCGDHDCADFADFGHCCHGFHCFHGDHGHGECCCCCADBFDGAABAFDAFDAFC,False +67,3.0,0.0,0.0,5.0,2.0,3.0,2.0,1.0,FDFEDHDGAFGADEAD,True +68,21.0,30.0,10.0,18.0,20.0,13.0,15.0,10.0,ABBHBEEEHDEHDGFFGDBDBBCABFGDCCDHFHHAAAAABFAEEDBEDBGBBEABEABFBBFBBDDAEEAGCFHEBAFAGDGGBBEDBHDFEFEEBEEBABDHBFBGCBGCGGBGCCGCEGAADAABCDDADEAHF,False +69,23.0,30.0,20.0,17.0,29.0,22.0,24.0,20.0,BHBBFBBEEAEGAEHBCABCBGCGEFHEGHFFBFCBFCHEEDEGCCGBCHFHBAACDGBFBEAEAFEHFEHGHGGACBEDDDBDFBGBAGBAGEDGEHAEDDHGDFEDFEHFACCAEHFBCGBCECFGFFAEGAEAHHBGABGAEGDCGDCHDBBEFAECDHCDHABAFBACBAFBFGEDEEHGB,False +70,16.0,21.0,23.0,21.0,35.0,31.0,21.0,19.0,FEGHEGHEHFBHEBDEGDABDAGFAGCDGCEAEABGGEFEBAEBHDFEFACFEHFHHEBFGGDGBAGBAEEAFBACBCBDFFDGEECFEDFEAFEFFEDFBBFHFFCGFBFCECEHCHFFHGFDGFHECEGCDDBDDEECCBDHADHADEEEECDBCBFHGFHGBCGFCHCCBGDEEAEHAECDCCF,False +71,21.0,21.0,25.0,23.0,34.0,29.0,19.0,27.0,CGCABAFBECCEGAEFEEHEDHEFBAFBFFGFDCBDFHDFDDHCCAEGAEGEECFCDFGDHCDAFDFFHBAEGDECFHHFHHEAABFABAAHCCCCHHGBBCBHGGHEFDFFCGFDGHDAHAGHCEEBBEDBEGEHBEGCHAEHDEHFEBDECFHABHABAAFDDFDDFBEFGHGCEECFDCDCEECEEAHEGHEFBBG,False +72,26.0,9.0,19.0,24.0,24.0,27.0,21.0,27.0,DDGBDCADHEDABHHHAEHAHDCHDBFFEEFAEFAHGACFFEEDHACFCCFGCDACDCCDCEDBADHFEGDHDFHGCHFAEFHDFGFGEFGEGGEHEHHAHFEHCAAEAFCHDCFFFGABAFEAGGBGHCHDFHDAAGAFCADGADHAGHBGBBEEEGEEFAEFAEFCGDCFDHGDH,False +73,24.0,24.0,23.0,19.0,22.0,18.0,26.0,30.0,HGFHGHHBBHDBAGCEDEHDHCDAAGCBCCHCCDGGHAGHGHHFAEFGEGBEBFDFAEAHBBHBDCBDCBCCDECHHFHDDHCGAAAAEAEEDBGDBGCFACGAHGDFGCGHABBACBAHGHHBHGBEDDACFACFEBFGHCAEBGEBGEDGEDHEFFECEEAEFGGHHFBBFCHFBAFGAEHACD,False +74,26.0,17.0,19.0,17.0,28.0,19.0,13.0,23.0,EGCAHEHHEHABADBADECBECEEABEACFACACFFBFGBFBDFCFCCACAHEBHEGHDBHBBAFEADEHBCHEEHEGBFGBFDCGDEFDEADEDHEAAFFEFFHHFACDCCEAHDADDEEEFAFGADBHEBEAGAGDAHBCHCGHCAHGACGEEFAHGHHD,False +75,3.0,1.0,2.0,0.0,2.0,1.0,0.0,4.0,EAHBCHCAHEAHF,True +76,10.0,5.0,4.0,6.0,10.0,5.0,10.0,8.0,HGHHAEEAEDAECGDCAHGFBGAGEFGFBEFAFCGCEAEEBGEBGDDHDBHDAHGAHA,False +77,6.0,2.0,4.0,1.0,4.0,1.0,1.0,0.0,AACCDECAEBAEBAGFECA,True +78,26.0,21.0,24.0,22.0,21.0,23.0,16.0,22.0,AEAFDAFGAFHAHCGFCGFHDCBDCBABADBCDGGFGHEBBDFBFFDCDEAEEGGFHAHDCDDBGEHCEFCHFGEFDADGFHFBDFCCCBCGBCABDFHAEBCHBCHBCDECEGFFAHFAHFCHFDDCAEHAGHBGHBAEECDDDDAABAHECHEBHEAHABGEBAEACEACEAF,False +79,23.0,23.0,29.0,21.0,13.0,23.0,22.0,17.0,CDHBACEAHEFDEGHAGAAGFAHFADFCBBBEFBCDGFBCDBDHGGGGCGFBDBBCFBFDEGEEHEGGBGEHFCCFCBDCEDAEABFDHHBFBBCAGDDCHDCHDAHBACAGCAGCADDBDFHAFCAFCGHDEBGHBCHGCHFBEGBFACFCCACAADACFACFCCFGFDG,False +80,12.0,12.0,23.0,9.0,27.0,13.0,18.0,19.0,EGFECEECHEBEEHHFBDCGCAACFBCGEHEEGCEACEGDEADAGBAGBCDBFBHFHACHCDHCDHCECCEGFHGFBABCGDCBDCEACHBCGGAEEAECFEHHAFFEEFHFCEFCHGGGGDHBEHGGHEEHE,False +81,25.0,15.0,14.0,17.0,20.0,16.0,15.0,15.0,DGDFFBFFCAFHADGAEEAFDABDEGGEBGDGEDEBAHAAEGABAHCACEACAHBAGGECFCDDEDBEFHEBGAFCAFCAHDEHDAFAGFCDBCHCCHCEDBGFGHBADBHGBEAAHAAHAEFECFEDFEDHEBHGB,False +82,23.0,16.0,15.0,28.0,9.0,16.0,15.0,26.0,FAHGHHFHGDHGDHDHCCHFBHEDGDGADGBDFDHFBBEDBADEDDBDHFDACDBFGBFAHCDDDGDBGBBGAAADCHFCHCDGABFHDDHDAEDCEDCGDFEAAEACHHGHDGCFFCHABHAHHAFCFHAAHAACBABBHFEAGEAC,False +83,16.0,17.0,21.0,14.0,11.0,17.0,24.0,19.0,EGHCBBCBBHFAHAAGAFGHBCDFAGFBDABDADEEDBCDBCHBCBGEGFFGFGGCHGCGGHHADHDHCDHAFGACCEHDGHFFCDFEDAHDFFAFFHEGBDGCGCBECECHBGHGGHCGBCHBCEGFGGFCACAABAE,False +84,25.0,24.0,34.0,20.0,21.0,23.0,18.0,22.0,GCCGAFHHFBGFBCFBDFBGFCGDEGCAHEBCAFCBFHEFEDCGFCAFCHCHBCHEAHAFBAFDAHBHBDGAABAFBACACHHCFDAFDGBAHBEBBEDFCFECAEBGFHECCCCCCHHEEHAAFDGFDHBDGBEFBEDDHDDEBHECCECCEBAEBAGACGEDGADCBCCGGCDEAGCADCAFHHD,False +85,14.0,17.0,15.0,14.0,15.0,14.0,16.0,10.0,GGCGDDEBFFHGFBGFBHFHHEDAACAABGFFFCDBGBEHBEDBFDBCDCDGCDEFBCHBEGBEGBEFHGFBAEBCEFAAGGCHCCFCCBCHEHEAACADDEDDAGDAGEAEBAG,False +86,5.0,2.0,1.0,1.0,1.0,1.0,3.0,1.0,ADFAGGAHGBEABCA,True +87,28.0,33.0,23.0,19.0,20.0,25.0,30.0,22.0,FFGDBGHBGEGAADDHGEEDEHBBACDFCGFCGEHFBBFHBFBCCGCCFHDFCGHBECBAAFFDBBCBECGGFEGECCAGABBABHAEHBBHBHDEFDCHDBAFFDDFAAHAAHCDFCAHEAHGAHFAHAGHAGAAGEEDFGBEBECBGCBAFBGCCGAFAAFHAGGFGGBGGBDEEGEGBFGBFHBCHBDDBDDBECCA,False +88,27.0,30.0,28.0,20.0,23.0,12.0,23.0,29.0,EGBCBBCEBCHHGDBECBCDBEDGEHGAGACGEHGCDACFECFCBHBBFDAHCACBACBEFGGAGGADAAEBAHDFHDCDBAHCHHBHABGCBEEDHGHHGFHAHDAEDABDGCDECDBADBHHGHHGFGECBEABDHFDGAHEACFGCAGCABCHBFECHCBFCBFAEABDAGEHEEAECABDHBHHCEBG,False +89,14.0,15.0,7.0,17.0,10.0,11.0,15.0,9.0,CHBADFABGHBGFGGAGGADGDEBHADHGHGFDFDDCDBGAAGHAGFAEEBBEDBEBCEBFAFDAFDFGDEADEGDFACCCGBHBBHABHDEDCBDFE,False +90,5.0,3.0,3.0,1.0,8.0,0.0,6.0,3.0,CCACEGHEGDEGBBAHEHGBAGEAEEAEG,True +91,0.0,0.0,4.0,2.0,4.0,2.0,2.0,1.0,GDCFDCEECGEHFEC,True +92,14.0,4.0,7.0,10.0,8.0,6.0,12.0,5.0,DCDAEFAFCECEEAFEDFEGCCGACBDGHFAHBGEBGAGGAGGDGAEGHHGAADAFDADDCBAHDA,False +93,10.0,8.0,8.0,3.0,8.0,14.0,16.0,15.0,FAGFDGHDHHEHEEGGFFACFHEHACCACHFGHFGHCGCAGCGBCFFEGFGBHABHFDHGBGBHABHAFFAGFEHEEBBAGG,True +94,21.0,25.0,21.0,30.0,27.0,13.0,12.0,17.0,HHBEBCAACEABDGDGBDFBGFCAEHGDCADCHDCEDFEDCEDGDCEDAEGEHAADBBDAADHCDHDFHBEEBEEBCEGAECDEBBCGAHEBBFFHEBHEHDAHDAECFFDFEDFBDABDCCACEDEBDHDDAGFAEABECBHGFDDFEDCCBHCBHGBEGBACBA,False +95,4.0,6.0,6.0,8.0,7.0,6.0,6.0,9.0,EDGEBHEFHACBBCFEGHCHDAHDEHDBHDBDDEHFCGECGFGBFACFAHGD,False +96,8.0,5.0,5.0,6.0,5.0,8.0,12.0,12.0,AFACCAGAGGFBEHEGHECFDFFDGFHGAHGHHFDGAGCAGEFGHBBHEBHDDHDHHGCBA,False +97,20.0,25.0,21.0,20.0,27.0,26.0,25.0,26.0,BFCFGDFBECHDCEBGEFGBABHGDDGAFBEBCEFEEFGDAHFBHEHHCHDDHGEFDFFBGBBAEGCCFDDABEBBEBFHBHHBCCECEDCAFCGFGHFCBGHBEAFCBFDEEAEEAFECEBBGGAGHBDHFHHFHHFHHFHHEEHGCDABGABGACGAFGAGGDDEDDCADCFGAFGDCAHEAHEAEGC,False +98,4.0,3.0,1.0,1.0,6.0,1.0,5.0,3.0,BBAHAEDECGEAGBAGEEGHEGHF,True +99,21.0,17.0,15.0,21.0,17.0,23.0,10.0,21.0,AHDDHEDGFFGCFHDHAGHGHHDDFADFABHDBCCACAAHGDDFDDFGBHEBHBHEEHEFCFFBBDDBAABCEEHDACDHCEEAAEBHBFABFABCABFFFFDFFDFEEFCEHCEBDEBFCAGAGGDGCHBCHAAHEFFECAADH,False +100,21.0,17.0,13.0,22.0,21.0,22.0,21.0,31.0,GCAADDGBDEBDABDGDGGEADEDDFHHHEHDGHFGHFDHGAFAHEHDCHDHFEBGEACDACGABGABGFGGDGBHEEHEFFGHFABDHEDAECBFHAGHAHBAEAAEAFEHFEBGGBCFDFEEAHCHHCFDAFDCFDBFHBAHCHHFFGEHDECCGCBHFHHFBHBE,False +101,3.0,4.0,2.0,2.0,2.0,1.0,2.0,2.0,BCFBEABEABHADGCHGD,False +102,3.0,5.0,4.0,4.0,2.0,1.0,3.0,10.0,BGHBGHCCHCDHEHHABDFHDBHEGCDAHBAH,True +103,22.0,16.0,17.0,17.0,11.0,10.0,13.0,12.0,DECDFCDFEDCCBCCBCADGAGFAEAAHHCGECAAFHAHBAGEFDEFHHGGFBFCBACBABDACDAHDAGDGBDBADHFDBCEHGEHGDHABGBCEDEEHBAABADCGGCFCABDABA,False +104,12.0,15.0,10.0,16.0,25.0,15.0,20.0,17.0,GBFDCFDGDDBHDAADEBGBDEBEEFGHFGHFGHCGHEGDEADHBDHGGBGHEDCFHAAHACHGGEGGEFEBFGADCCEBHEGFEHDEHEEFAGDCHFEEAEEBCEGEDBEDBECBFFBHHCAFAEGAFB,False +105,7.0,10.0,8.0,8.0,6.0,8.0,6.0,10.0,HBEHAGHFGHBGDBAAGCDEHFEBEHBEBCABAACDFHBCHDFGDFGDFHCHCCACBFDBEDF,False +106,17.0,20.0,9.0,15.0,13.0,17.0,14.0,15.0,FBEAGDAGAABAHBGEFFBFFEDHEGHEGHEFHFDBBCBBDBCHCAHGAHCHBEGFDGFAEBAEGADCAHBDFBDFDFBABHEFGBCDAFDBCAGCFBHFBAFAEDHEDCEDHBDGGHGA,False +107,5.0,5.0,1.0,5.0,1.0,5.0,5.0,2.0,FABAAGDGFDFHBFEBAGBAGBFDDHGDC,True +108,17.0,16.0,20.0,15.0,16.0,19.0,21.0,30.0,CBHCHHDDDGADGAFCEHEBHEFEAAEBHFHCBGFAEDHEFEFFCFFAHEHHAHBGCDCHFGHBGFCGFBEABFBHHGHHGCHEAHEADABGHBHHBDHGDHGAGGBGGEFCFFCDBGDFDAECEECGCAGCGDCFDFHHAHHDHBBCCACGAC,False +109,19.0,26.0,19.0,10.0,27.0,23.0,8.0,14.0,EBCAAAGFADFADFEFBBBCBEABEABEAEEHEEHEECEBGACCAFCBHCDCCECFBCAGGAFEAFEFBHHBDFAHEHFEGFHCFBBHCCABCHFFBFFBDGCEGEBAEGCFFEEDHFFBFBADBDBBDBBEHEEFCHACBAHDEE,False +110,19.0,10.0,10.0,17.0,15.0,14.0,13.0,9.0,EACEADEDDGDAEBCFACEAEBFHFFGDFEDBBGBHGCADCFBBBHCAHEAHFAHAAHCDGCDGAEGAEGEDDFGEAEBAGFCGDGDDABDFCDFGFFAAEDFEHAH,False +111,6.0,10.0,13.0,9.0,4.0,7.0,3.0,10.0,CCCAFBAFBEHDFBCCBCHBCBCGHDAHDAGDCDFCHCEHDAFDFHDHHDEEBFBAGBCHBC,True +112,14.0,15.0,18.0,9.0,20.0,11.0,10.0,7.0,DEFDEFBEACFGEFCACCBGGBHAAEBEHCEGGEDEEFEEDBECBABGADFADFADGCHCCHCHACEDHEGAFAEFBFBAEACCAEBBGBBGEBEBHCCDCCFC,False +113,18.0,25.0,13.0,24.0,29.0,22.0,19.0,30.0,HCAHEABDACHBBDDHADBEHEEHCABCFBHFBABBABDHBEHFGAFGFHCHGCAEFHEFHGHCGCEHDDFEBFEFFDDHDEEDGEFCBGBDGAHHCHDCFDEEDGCFHHFEEFGBGGEEHBFAGFDHBEGFEDCEDEBDEFHEAHEAHABBEDBGFBGEHGAHFADBADHADHEDBGGB,False +114,13.0,9.0,15.0,32.0,17.0,18.0,11.0,14.0,HDHDDAGGFDDFHBFBCAEDGEDCEACDDEEDFHFAGFDECDCCDFADECFECHDCHDGAGAHGHDFEDCEDCEHBHDAHDCFDBFHHGDBDAFCGFAHFDCCDAEDGEDEEFADFAGFBBDEBDEBDF,False +115,21.0,18.0,26.0,25.0,21.0,27.0,25.0,34.0,AACCECDFFBBDABHAGHGFHGHAFHBFHFEHCBHFDAGHAGEDBEACHDCAGCDCCDBEDBDDEGGEHGAHFAHDBFGHFGCDCCFCBFCBHCHHFFDFGEEEDHFHHFHDFEDFDCBHAGAAGHBEEDCFFCHEDAEBAGDEGDEDBFBGCBECHCGHCDAGGAHGHCGHCFHBFHCFHDADAEGEGHCGAFFEH,False +116,25.0,15.0,25.0,18.0,19.0,11.0,22.0,30.0,BGGBGDHGBAECHEFABDHBHHBHDADBEEGFGGDGCCGFCHHHAHAFHBFEEGEAHCGEAGDCCHCGDAGBAGBAEADBADHADFCGHEDHCABCHHEHDFHFAHEAHCHCAHBDHBGHFGEFCAGCHGAAACAACHHDHCCGECEDDFCDACDACBCCEEGEE,False +117,28.0,24.0,15.0,28.0,23.0,30.0,14.0,19.0,CHACHAGEBEFDCFAGFADDEDDBDGBDBFEBEDHHDGDECDEBFABFAFFABAAHHAHHDFHFBHDBEDADCBGHEDFFDEDDEBEBAGADDFFFBDFBFFBFFBHACFDBFDFAEBACBACGEGGCFAFEHEAHECHBDGGFCAECFEFHEHHAGACBDCBAHAAEAAEDECDAFGGFB,False +118,0.0,3.0,1.0,0.0,4.0,1.0,0.0,2.0,FHBBEEBEECH,True +119,15.0,14.0,10.0,15.0,7.0,12.0,18.0,9.0,BGDBGBFEBDCFAFFADCGGAGDABAAHHAHHACEBCDDCBDAGDGBBGDGDDACEFCFFCGFHGBEFCGACHAGAGHAGDABBEEFHGFBFDBEDGHDG,False +120,18.0,23.0,21.0,12.0,21.0,14.0,26.0,15.0,GBBHAAEBAEHEEFEGFGCAECABAGCADBEFAAGDABCAGGFGGCHGCHGAHEAHFFCEHCEBBFBBEHBCGECGACGDCGDHGCGGHGGDDGHACBBGDBDECDCFABECFEBFECEBGBBEDDEGFCDFEGBHGBHAHFACEBCHBF,False +121,18.0,17.0,15.0,11.0,14.0,12.0,17.0,17.0,AGGAFDDFCDBBHECHBCHADHCBACFACDDGFACEBCBBGBHAAHEAEEHGFGCFGBHEBAFHAHHADHBEGBHHCEFEEFGHFGFGCBDCADGBDHHEBEBBAADAAFCAGCGGEGGEC,False +122,19.0,12.0,14.0,16.0,13.0,13.0,22.0,12.0,DFAEFDEBHGFEEDAEDFGGCGGFGGFGGAGGAFFDEAGEAGDBBABDHHCHHBDHBDGCGGDHDAGCACCBFCBABHEFHCCHECBCGDDAHDCEEFACFBCAGDAGAAGAEFAGDBEHA,False +123,3.0,8.0,5.0,11.0,9.0,10.0,4.0,11.0,EBFFHHFADFCHFGHEGHFGFACDEDDEGHFAEDHBDEBDECDCDDFHBFEBHHBCEBHDB,True +124,4.0,5.0,6.0,11.0,9.0,6.0,5.0,8.0,ACEACEADEDEHDCFFCDCCEHHEHEBHGBDGHDFDFEGFEDBHDHDBBGFAGD,False +125,11.0,14.0,19.0,12.0,21.0,14.0,17.0,9.0,CCDCBDBEDHEGHAFEECDGCFGCEGCBGEFAEDACCHCDHGFEFFBBEABEAHHAFCCFBFFCFCBEGDACDGCAEBAEGGEDGEDCAGGEDHEBHBBACBHGFEGEGDEGEFCBF,False +126,7.0,15.0,16.0,15.0,17.0,19.0,21.0,17.0,CHHHDBCCEFEEBEGBHFEDGEBFFBGFGHHGHHGEHDHCDHCDFAFFDCABAFBHGBCGBFHBDHCEGAGGHHGDEAFECHDBFGBDBCDECGEFEEBECBDFFDECGGCGADGEDGFGCFGCFAF,False +127,1.0,2.0,2.0,2.0,3.0,3.0,7.0,2.0,BEGGGGACFHCFHEFDGGDEGB,True +128,24.0,27.0,28.0,25.0,25.0,12.0,31.0,20.0,GGGBGGBDBCDHGACGEHDCHDCBDCHHEHBGHADDADDEBGGHGDDEADFAHFAGGEGEEABEHDEHCEBAEBECBACBACGACGADFADBBBBFCCAEGHFBEBCAAHBCHFCEFCDFCDCCBAEGEGCAGCGCCGEHFEHGCCACAACBDDBHGBEBDAFGEFGBBGHHEDGDABCGFHDEGGEDEADB,False +129,8.0,19.0,18.0,15.0,11.0,19.0,15.0,9.0,BEEBFHGAACFBCEBFHFADFCDHCDBCGBGGEGBDAADFDCHECHECEGCFGCFGFBCFGCAGDFGFFHHBDDFCDFBBEDBFDGDBBFBHABCEBCDAEGCBFHBFCGECGD,False +130,19.0,16.0,11.0,13.0,12.0,17.0,19.0,19.0,AGFEGFGGEGDAFDBFDBCGACBHEHHAHHDFADABHAGHBFHDFCDCADEEFEGBDGBEGADBAHFGBDGBAEFAGFBCAECHGBGFBGBBFBHAHHAHDEGEFAHADCACCHCEHGAHFHGFCF,False +131,4.0,4.0,2.0,0.0,2.0,2.0,3.0,2.0,FBECAGHAHCAGBAGBEFB,True +132,21.0,22.0,26.0,22.0,19.0,22.0,19.0,31.0,HHACHAGHDFHCACFECAECGDFFDFCAACEBEDHHAHDCGBCBBCAHCAFCDBGFGDCHBHECHCFACFGCHECBBCFBGHDGHEGHDGFBAADFGBGGFCGHCBHAGHFEEEDAEDAHHABFABHAHHGHBFDAFDGDDFEDGBDFEDHDDHCEHEAHECEECEADBGCBFFHCFBBBBH,False +133,16.0,18.0,20.0,18.0,16.0,13.0,27.0,16.0,DGGBCEDCEFHDGHFBDCHFHHBACBADAAHADEACBGHFGEDGCBCABGAGFCGDCGDGBEGBEGBECEEHGEHGHHDAAGGACBDGBGCBACDEBDBGCFHFEHCEGCEAEFCHFABFEGGCDHFDCDDCDBFGBFGAGHAG,False +134,19.0,21.0,15.0,10.0,12.0,12.0,10.0,11.0,DAGDAGAAHHFHABCBBCEBCFBCGDCGEEACACBACEAFGBDAAFEAFEHBBBFECDEADGFFACGECBBCBBGEBFEBDAACHADHFEFBCHBFGBHDBCGBHADHAH,False +135,13.0,9.0,13.0,6.0,13.0,9.0,17.0,10.0,ACEEHFBHFBGFCHABEADHHCGACGDHBCABEGBEDBGGCGHHAHCEDAEFAEGCEACEAGGFCGCDGBFGAFGAFBEGCEGAFGECHD,False +136,12.0,12.0,9.0,6.0,6.0,6.0,7.0,12.0,DGFDCFBCHHHHHHHBHBBABEAFGBEGCFDFGCCBDABAAEAAHACCAGHADEACGHGEBEFBCDBHAB,False +137,8.0,7.0,7.0,10.0,12.0,16.0,11.0,8.0,EEHEGHGAHFFEFEDBGDBEBBGGFGDCGFCFCGFDDFHDFHAFCFDGAAFFAEHAEDFEGFEDCEGAEFBHBCDBCHA,False +138,16.0,20.0,15.0,26.0,16.0,10.0,21.0,11.0,BCEFDBCDBAHBEFBCAHCAEBDCCDHGHHCHDDDEGBFDFGCACAEEDGADGEDBEGCEHCHBGHBEDDADDGBDGBCGBDHCFGCGGFGGAAEAADAEDGEDBEBADDADGCDGBAGBDGBHGFFBEDAEFBF,False +139,13.0,8.0,3.0,6.0,6.0,4.0,5.0,4.0,EDGABAADGAECAGAAGAACHFFHABGFBABBEDBEHBAHCABDFDEED,True +140,3.0,7.0,9.0,8.0,11.0,8.0,12.0,4.0,FGFCGCCEEDFEBFEBDACHADEBCEDFBDEHEFBEHCEDCGGBGFBEFCGGDGHDGCGGAG,False +141,7.0,6.0,3.0,11.0,10.0,4.0,8.0,7.0,EEAAECEEGHEHDFDCHCGHEAAEHBDFBDBGDBADBEHFEAFGGDHDDGBDGADG,False +142,25.0,23.0,17.0,19.0,29.0,25.0,18.0,29.0,EEBEEBHHHHBCHEFDGCDECDEDBEFHAFGBFBHFBHFCHFEDFBBFEAEGBCBAAAADAHEEFAEFDFACHHCHBEHBHHDGECFEFBEGHEGHAFHCDBCAGHEGHGDHGEGGFAAFAHEEHBFABDACHABDCDAFGFFGCFECFHBFEEDDGDBFCAHAEDDEACEAGDBGAAGAHCBHB,False +143,1.0,2.0,2.0,3.0,4.0,5.0,2.0,3.0,CFDCBDHGEEGAEDFEFFBHFH,True +144,9.0,4.0,7.0,5.0,3.0,7.0,3.0,7.0,EFAFABHACHECHGCBADBADAADGCFFAHGHDFHDCHFCBECAF,False +145,21.0,27.0,26.0,22.0,15.0,22.0,16.0,17.0,FCDFDDECEHCFGCEGDABBGHCGBBFABAEFEEFACHBGFEABEDBHCCFGAFEEFHAFECFHCEBCDBCBAHFAHFCFFCFFBFAGGAECDCCBBDDCDDCABBAGGAGBAGHCHECDACBAFHECGBGGBAGBHBACCADDDDCHHHFHHBDDBDDBDBADBF,False +146,23.0,23.0,27.0,18.0,23.0,27.0,25.0,28.0,DEGHEGFDBFGHDEACECDFDDFDBBBGCEAFHFFHFEBGEBDEBFBBFHFFEFCGFCGCHGAHBCFGAAECGEGDDGCHGAHAAHAADDADCAFBFFBHBHEGCAHCHHBEACCBBABBDBHCBDFAHAEBCEGEGCBHEHFAGCAFCACEFHEFADBCGGCGHAGHGEHEFHCAHCGHDGHCEHCEFCGFDF,False +147,19.0,22.0,21.0,22.0,15.0,18.0,18.0,18.0,ADDADEFBADAHFBBFBBCHGCGBCBHEDCCDHDDACGEGBEACEBCGCFABFHEAHFGDCDDCGFCGHEHHEHBFHDFBFFBAFAABAADACDFCEFHADGADCCECDBHDBCGBAEBAHDHHDHACFCGFGEFHEGGCGEFGBDGBGBBDE,False +148,23.0,18.0,18.0,17.0,20.0,20.0,23.0,19.0,GHBGCBDAFDAFHCBEFGACAECHHGEGFEGDEDDBCAAGFAGCGECAEFBEACEHGEHAEAFEAFBCGCCFCBBGHBAFBFCBFAEHBEHBEGAACFABGEDGHAGBCGCEBDGDDHEAHCADFFGHAHDGHDGHDGBDABHAEDDFHDFCFFHGFE,False +149,11.0,9.0,14.0,14.0,12.0,13.0,8.0,11.0,CCFCGFCDFHHHGGHEDDFHDFEEGCEAHAHCADFEBBBCBFCAHBAHEACDDCDACDADDBDDBEGBDFFCEHEFBEFEAGEGFCGFCAHA,False +150,20.0,17.0,22.0,21.0,18.0,23.0,27.0,26.0,FDDHHBGAEAABAAFAHBGFFHEHCEBEBBEDBGDCGHCGHCFFEGFEDFCDACDAEBFEDAEDHHHFGHGDHGAEFCFGBEDAADCCGFGGAAGCHCDDBDCGGFGGFGGFHGFBGBCGECHFHHACHABDFHDHCAEBBEBGCCFHEHGFHFEHFEHBCACCACGAGHDDDD,False +151,25.0,32.0,23.0,18.0,29.0,30.0,21.0,16.0,CHFAFBDBCEHGEHEEFEACEFCFHHFCAGAEGBCABCAECHDDFDFFEFFGHABFFEHBBDBGABGACGACEDCGDEBDEBCEBFDCHBADBFDAADEFBFHGAACAACHDEADHCBGCAFBFFBFFBEBBGBEEBHDBFDGDAGFEGCABEEBEHBGHBGFBGBAGFGCEGCACFDGAEBEEFCEFAFHBCE,False +152,2.0,5.0,8.0,6.0,3.0,7.0,7.0,3.0,ECBDCEGFFGHCGCGGFBDFDDADDHEBFCBCCBFCGFGAH,True +153,20.0,20.0,31.0,26.0,22.0,23.0,14.0,22.0,GBGFBFFBHCBHCBHGBEFCGFHHHHEHDCHCCDGCFFCDDHFDEDGEGCHHADHCEECFECHECDGCDGADCAGAAHEDHCFBEFEDCHFFAADEADHADCGBCFBCFEEEEBGBCCCCBCDBDHBAHDABCAGCBCFBEHDEBDCFDHFEFDAACAEDADAFGEFABFDCEDAFAB,False +154,14.0,22.0,13.0,6.0,19.0,16.0,15.0,9.0,EEBFEFCBFDAAGAHBCCBGCEEAEEAEEAEEAEGGFHBCHBCBCHBCFACFGDECBAGFFDBHBBHGGFAGBGCBEHGADBFBBGGAFCAFCEGBEGBEFBDFBHEHEFDAFB,False +155,13.0,9.0,8.0,9.0,16.0,11.0,16.0,26.0,HGHDBHECHGCDGAEGFEHDEGGHHFBHFGHBGBEFEAHEAHBFHFDHADHBCHEAHEAHDGHDHHEFFACDCEBFGGEGAEHEGHEGCCGFHGAAAHAFHAHDEBBC,False +156,21.0,23.0,28.0,17.0,32.0,20.0,26.0,33.0,AGBGFFGFGGCEFCBFGBECECGECBECAGHDHEDHCBHEEAEEBFGGHEEHAGFFGFHHCCHADABEGBHGCHGCFBHEHHEHHGFHFFHEFAEHADCEDCHAADBADHEDAFHEDDCCDCFEHBHGGHEFHEBHEBHGBCGCADAAHACBDFBGCBECBCCEHEADEGEEAFCDBHGBCGBCDFAGEAEHAHDCBBCG,False +157,3.0,5.0,10.0,12.0,6.0,7.0,9.0,8.0,CDDCFDCHDGGFGDBGDHFHHEGCCHDCADCAGBFHEGEEGCEDEFDBFDHAHGCBFCBD,False +158,27.0,19.0,22.0,22.0,21.0,22.0,30.0,32.0,AEAADDGDGHBHDGHBGHBHHBCHCAHCABEEBDBDHGFHGHHGBBAHAGFGBAGAGGAGHHCFFBHHGDHAACAGCAHDADGAFHCCHGHHCHGCFGEEDEDBECGAFEDFEDBEGBCACHFCDFGDCDCCBGCFGDFGHFAAEDHFBHFGFFEAEEHEDBECFEABGAFEEEAFDCFDAFDBCGHCGHAEHAG,False +159,6.0,10.0,10.0,5.0,6.0,6.0,5.0,10.0,HCEECDECAFABHBBFADFCGACGABHFEHCBBCBBHFHCDCEDCHGGHEGHFBHABD,False +160,18.0,20.0,20.0,17.0,21.0,19.0,20.0,20.0,FEDBECCGDCDBGDBGDGGDCDFCAHCEHAGAABACFCFFCAACHADAACEGEEGBFBHEHHBGHBACGFDFCHFCHEAEBBEDFFGCFGBEBBEHDDHABGEEEEFABHABHGEHGEHGEHBFDFDHGDHGBEGBECCFCAFHFGCCDAFAHDB,False +161,12.0,21.0,28.0,20.0,19.0,21.0,30.0,23.0,BEBCAAFGAFGBFGEEEFCCHCGHFGHGDDCCHBCGACGEHGHCEHCFCBHCBHDAHDHHDCHEABGHFGBGGCGHCGCEGFDGDDEFGEAHBGEADDCFDGBDGDCFECFCGFCHEGAFCDFCDGDFFEHFBHFCCBECHEBHCBFDBFBBGBDAEDGECGBHEBDABGGGAH,False +162,21.0,14.0,18.0,20.0,18.0,17.0,19.0,20.0,GHBEAFEGBGGHDEEDEABEBBEFECFCCABAAEAAEACBAFBHFHHAEDBCDECDAFBAFBAGEHEHGDAAHGAEDCCDHDDHGAHAFCCECAFCHHCHEGBCDCCBFFEFFGBFDDDDDGGCGDAFDGCGFHHDHHDHGFHGAGG,False +163,7.0,8.0,10.0,9.0,10.0,6.0,9.0,12.0,FBCCDDCAHADHEHHAGCGGHECHECHGBFABFADFGDHBDHDDCDHCEBFHGECEEAEFHECEBGBGGBA,False +164,2.0,1.0,4.0,3.0,2.0,6.0,3.0,7.0,CHCFEGFCGHHEABGAHDFHDFHCFHFD,True +165,27.0,21.0,24.0,26.0,31.0,11.0,22.0,21.0,CAADGACHHEAHDFHCAHCFBCFBEBHGCEFCHCGECDEABEACDDGHDAFCCDCADCAGBDGBEGBCDEHAHHAEFBEGDEFCEABBDBGAHAACAAEACBFBBFGEEHEBDEGDEGDCCDCABHEEEGCDGCDGHEGEEGEHDEGDHDAEFEGBDGADHFDGCDGBAAAAHHEEHDEBABB,False +166,7.0,16.0,7.0,13.0,4.0,10.0,9.0,15.0,BDDEDDGCAHEFHCFHCBHAGFDBDDBDDGFFBAHAHHFGBBDFBDHACHBCEBFEHHGHHBADBCFBHDGABGHBGFBGC,False +167,15.0,15.0,9.0,10.0,9.0,15.0,18.0,14.0,GGABCADCGHHGEHBDHCDHDEGGGFGGAGAABECBCFBEABEBEGAACBBFEAFBHFBHFBGFCAFGHFGHDGCBCEHFFGBFEDFBDAHHAHHGFDDAGDAFA,False +168,21.0,14.0,14.0,15.0,25.0,21.0,7.0,17.0,FDABDAHCHHFDACBGCBGCHFAACGEEBCBFABAEEAEEAFEADDHFAHFEHAHHCEHEFDGFEHFEGFDFHCCAEAAEADBHCFHEBBCFACFDEADFAECAEBBEDBEGFDAFEFDHFDHFEEBCEBGEHD,False +169,11.0,25.0,11.0,15.0,12.0,14.0,16.0,19.0,CDFBBCHGCEBDBACBDCGHFHHFHDFHBEGBEDBFDAFCAHBACFAGGAGEAGBAGBHBBDEBHGHHGHFEABDHFCBECBFDFEGHDFHBFHAEHECHBHBGDBGBCEBABDEGDGGDFDB,False +170,11.0,10.0,15.0,10.0,14.0,10.0,14.0,13.0,EEGCEHAGADCDEADGBDBHDFGDHCDFCDHBAEAHEHCGFCGFCEFDHGHHGHFGCAACHACHAEGEBDCFGCFBBFBBEEBGACGFHEECEBCGA,False +171,15.0,14.0,17.0,21.0,14.0,11.0,20.0,12.0,CBGBFHBCEACEAGAACBDBBDCDDCDDAGGAFGFGDHADEDDEFFAFFCBFCBFCFAHDDBGGGEADHHBHBBDEEGEEGCAGCDCCGCEBHHCGGCDBCHHEAHGAEGHEFADGDGEDGDDA,False +172,6.0,4.0,6.0,6.0,3.0,10.0,5.0,4.0,GBFGHFGDEDFCDAGDHCDACBECDECAHAFFAFBCBHAFFGFF,False +173,2.0,0.0,4.0,3.0,0.0,0.0,1.0,0.0,DDGDCCACCA,True +174,3.0,6.0,8.0,12.0,9.0,8.0,4.0,7.0,FGBDDHHDCFABFABCBCCHDEHEFAEFEBFEDDHDBCDECFHCFGEGGEDDCDDHE,False +175,4.0,4.0,3.0,0.0,0.0,0.0,2.0,1.0,GACGABHBBAABCC,True +176,4.0,2.0,4.0,1.0,2.0,1.0,1.0,1.0,HCDACAAEABCFBCEG,True +177,22.0,20.0,10.0,18.0,13.0,13.0,19.0,20.0,CBHCGHGEHEEADBHGAEGFEGFBAEBCFAFEGHCBABFADFDDCHBCHDHAGGADBAHFEEFHBBHBGDDDHDGHGFHAFAAEGBBDAADHGBEGBAGBADBAHCHHADHDGGDFGDFDCABCABCABEFHEGA,False +178,22.0,19.0,25.0,28.0,26.0,27.0,22.0,13.0,CCCCCCCDCAGHEHCGDGHCADEADBADHFDGGGBDACFHCFHDGBDGDAGDCDDBBCEBFBAABDCDDEDFEFEECDEBAFBDDBFEHEEAEFGEFGEAGBFFBFFBCFCFDGHEFCAFCAHEEGEEBEAHDGEFBFHDFEDCDHCDACGGBGCAGDAFAAFEAFHDFEGECBBGFAEFAG,False +179,3.0,7.0,11.0,8.0,19.0,13.0,15.0,4.0,BEEBAEFHEBGCBCEBFHFDECDCGHGFEGEEBECGFCGFDGDDGFAFFAEGCEFCEFDECEEGDEGCGGFGEBDHCEGF,True +180,23.0,18.0,16.0,19.0,17.0,9.0,16.0,16.0,DACDHCDECEHCBACDAFDAFABCEDHDGHBCFFABCDDFDDHCAHBAEDABHABDGDFCBECAEAAHGEFABFGBGBHABHCEAEGAEGEHGFHEAAEAHGCEGCHGAEGCBGCDGDEGHHADBAGBEDBDBB,False +181,7.0,4.0,3.0,4.0,1.0,4.0,0.0,2.0,CDDAFABHAECADFHCFABFABDAB,True +182,7.0,17.0,14.0,12.0,11.0,8.0,17.0,16.0,ECEECHEGDCFDCFDCEDBBGBGECGBHGFFGCBHEBHABAGBHFBHDGHBECBEHHGCGCCGCFGHABADDDHGDHEBHBCGGFFACHAEADBHDGHBGDB,False +183,18.0,19.0,14.0,22.0,20.0,25.0,20.0,18.0,FBAHCEHGHHGAEDEDDHDHGFACFDBFGCCBHGHHGBHGECBHFDEFBEBHECHFGDFHDEHAGGEGDBGAADFADAADGADGHFFEGCABDGFDBDECDFAFAEFCEFCADGFDFFBFFBHFCECGEBGEBHEADBBDFBCFDCFAAEGBEABE,False +184,9.0,17.0,14.0,14.0,12.0,19.0,15.0,10.0,DBDDHCBBBBGGFEBFEAFGCFDCADCDFEFGHFDHBDCECCFDCAEBEDHFDCBDGBACACGECFEHDBACBFFBFFGGDEGHHGCHFBHFBEFAEAABGFBGEGGFGH,False +185,5.0,15.0,12.0,28.0,11.0,16.0,11.0,13.0,FBEBDDHEDCEGFGGBGEBDBBHCDGDDHBDHECBDFBDEGHEFHEFEDCDHGDADDABHABDCBDBFDHGDFDCGHCGDCHHGDADDEDDAFDFFHFFECDCBBFFCFFC,False +186,3.0,2.0,0.0,4.0,2.0,3.0,6.0,2.0,EGADGADADBGHFGBDGHFGEF,True +187,7.0,12.0,9.0,16.0,4.0,16.0,12.0,10.0,BDFDFFBBBEBBFCHHCHHFFEGDADDFDFHAFDAFBBGDBGDBDDGCDFFDGDGCBCADGEHGDHCCHACABHAHGCFGFFGEFG,False +188,9.0,14.0,12.0,11.0,9.0,6.0,5.0,4.0,DFBEFDCDCBAFBADEFDEGCEBCGFCECHDBADBADBEEBABGHBACBACBECGACBBCADDHFGHECD,False +189,15.0,22.0,16.0,23.0,11.0,18.0,13.0,25.0,CHGBHDEHBEHDGCDFHFHHCHHGHEDDBGHACHECHBHGDHDCHDEAGEABFAEFACBBDDBDBADACDABFAHDABACBHHDHCAHFFBBDBGAFGFFBBABCGEEFEDCCDCBDBFDBFEFGGFHHFHDCADBDGFCGFH,False +190,23.0,11.0,18.0,25.0,19.0,12.0,19.0,38.0,DEHHAGHADHGCHACEDCAGEGFDADHADHDDGEEEEHFHGCAGEDDFHHEHHDHDGBDADHECEEGAFHDBHGBHGBDAHAEHABHBBFDDCDAHHGHHEHFGHCHDDECBFCADCGDCGHCGHGAHGABFHFHHFHHEHHBBAEDAEDFCCECAAGACCACAF,False +191,5.0,6.0,1.0,7.0,12.0,13.0,5.0,13.0,HEEFEHAEHFFHFGDFEDGEGAFGFHGEHDBHAFHFFEAHEBEBDFADBHHHEHBECFDBFD,True +192,14.0,9.0,19.0,16.0,17.0,13.0,14.0,12.0,FBCCBDDFFDHDDHGEFGEFGFHGFBDFCEEHACCAEEDBFDEDCHFCBAEFCGGAHFADGAHEHHAHBACBCEDEEDCCDCGACGCCGCEGDECAECAFGABGBHGDDEAEHA,False +193,13.0,11.0,10.0,13.0,18.0,18.0,16.0,24.0,BFHBGDBGHEFHEGEEGAAFHDFECFEAHEAHDFHCHHEHFAGEGCCHHEDHEDCCDAGGAGGBDCBDAFHFFAFDAFHGCHGCFGHGHHCHDBHBFFADFEDEBHGGFBADHAEEEHEEBFB,False +194,4.0,3.0,4.0,0.0,0.0,3.0,1.0,3.0,HCHBAHBAGFABCAFCFC,True +195,5.0,5.0,1.0,2.0,4.0,4.0,7.0,2.0,EFBGHBGABGADGABHAGDBECGAFGFFEE,True +196,16.0,12.0,12.0,7.0,4.0,7.0,9.0,12.0,ACGACAHFFCEACGGDEADCAGCFHBFBEFDHDBHAAAAGHBBHCBHGBAGBACBDCBHCBACDECHHAGHFHBGADFA,False +197,11.0,6.0,8.0,7.0,7.0,10.0,12.0,14.0,GHFFHACEECGEGGDBGBBFAGFGCHGHDGAEGCCBHCBHAFHAHDAFGAFADCADHAHHBCDFGEAHEHHFDEF,False +198,21.0,16.0,17.0,15.0,22.0,24.0,21.0,20.0,AEFABCDCDABGHHEHDFBBFCAGGAEFCGGCGABGACGHHGDGBDBBCFACBDFHHEHFCHFCECHFCHGEHGBFFECFBHFGHFEDFDCFCEAEEADDGDEGFEGFABFHBFAEHEDDADAAGAACEACBHEBFEDFAAAGGEGGBHEEHFEHF,False +199,3.0,4.0,1.0,2.0,7.0,5.0,9.0,5.0,HFFFEGEEGAHGBHGAHDADCBGGEEGEGBEGBFFH,True +200,27.0,17.0,26.0,18.0,16.0,17.0,15.0,13.0,BDEBEEBCBBCDFCHCCABDEGCGACGACACFGDDGAACBACEEDBDDCCCHCDFAHBGEBCHGGFCGHHHABHBGAEHCBGCDAEDFEFBEAHEAFFGDFHDHHDFDBFEBAAGAAGAGFCBCCEACEACECFAFAAFAADCFDAFDA,False +201,14.0,18.0,22.0,18.0,23.0,25.0,18.0,25.0,EHGEHCBHCHHAEHDEHDEAEBCEBCEGFAHFAHCEHBFHBHHBHEBCFADGHFGCFBAFBDHCHCEHADGBDFBFFBHBGGEFFFDFEBCDFDHCDHBECDEHECBECEFAGFCGCAGEHGEDEFHFCGCCDACAAFDAHDFFDBGDGAFGCBCDFEGFGGE,False +202,6.0,4.0,6.0,6.0,4.0,7.0,2.0,1.0,BADGAEAACFACGEFBACCEFCEFBDHDDFDBFDCF,True +203,4.0,8.0,7.0,5.0,6.0,6.0,6.0,7.0,EHAECAEHBEHBFHBCDBAEFEGGCFGDGHHACBBCGBDHCDFCDFGBF,False +204,6.0,15.0,10.0,9.0,18.0,10.0,16.0,17.0,EHHEDFBDFGDGEDGHFEEDDBGFADFCBHCBHFEEFAECGHHGBCEDCEHFACGHEGHEGCBGHBCHBEFFEHADBAGBGHCHEEBEAGEBGBHGBHCBG,False +205,6.0,8.0,4.0,6.0,11.0,10.0,4.0,7.0,BDFBFFCHFBADBGFCGCCEEAAHFAHFGFEEFBEAHEBDEBDFHDHEGEEBEHDA,False +206,7.0,11.0,7.0,14.0,12.0,11.0,11.0,15.0,DFFHFBABAHBEHBEHDHGCHFDFAGCGHEBADHGDHCEHCEFCEFGFFGHGCDAADGBBGDBGEBFEDHABHDBCDHHEFDEGDEDE,False +207,14.0,19.0,19.0,16.0,15.0,16.0,25.0,15.0,BHBBDBDDGDAHEGEGGECDCCBCDAEBGEDGHDCHFEHACACCEDCGFGFEGDGGAGGAGGHFBEGCEGCEBCAFGHEBHDAEGAFHHCADFBBFBFFDHFCHFBBGBBCBACGFDAFHBCGFCGEDGADEAHFCHBG,False +208,14.0,24.0,23.0,25.0,20.0,23.0,13.0,19.0,CGFHBECCCACGAFFHDFHDAHCCFBDFBCCBGFDAHDABGABGHBFHCDGDDHBHEBCEDEFFEFFEFFCDDGGECDEFDADDHEACEAHEAEEBFBFGBDBBFCBDCFDGFHBBDBCGCDAHDCCDHCEEFEGGECBBABDCBDEFEHHEHHBHBADFA,False +209,5.0,7.0,7.0,12.0,11.0,5.0,6.0,4.0,BEEGAGCAHCFDCAHCEFCAFGGDDEDCBDBEFBEDDADDHDDBBDBEEEGCEGHEF,False +210,21.0,21.0,29.0,26.0,25.0,22.0,25.0,25.0,HGGGCBGCBGFDHCEGCBADBADBDFHCBHDBEBBEHBEFBCABCACCFCEFHAFHGFGDDGDDHHDEDDHCBEDDEDCBGGFAADADGACHAFDBEBEECDECEFGGHECHEFHEBHEDGCDCABCEFGEGHFGHEECDBHDFDFGCAEAGEAHCHFAHDGHACFACGHHGDHGCAAEFAFBCBECGFCFFCA,False +211,25.0,20.0,15.0,18.0,16.0,31.0,22.0,17.0,GDHFDBEDFEFGAHDFFDBECFDAFDBFGBDAEGAEGFDCFDCEACBAFHGHHFBFFBHHEAFBAFDCFBGAGGACBACFCEACEACHHGDHGCGFHGHAGABGBGDFHHFCACEBHEDDAFDAGCADBEGBFGBFEFFEAFGCFBHFEHGABAABAEGAFDFB,False +212,11.0,12.0,15.0,21.0,14.0,13.0,13.0,22.0,FDHBAHAHFDBFDFCHHEFHDFAGBADBADCHDFFDABDHCDHCGAGFHDDHEEHBHHEHBCBGDGCDCDECDEGEBHEHHGHDFBCFDAGCAGCACCEFCDBGEBGEDEFGHCGHEDHEA,False +213,26.0,25.0,22.0,24.0,22.0,21.0,23.0,28.0,DGGABBFFGEFGHFBHBHFAGAHGECGEBAACCADCHDBGDHCDFEDCCCFBFAHDEGGBGECFEABGHDEADGBGGFDEFAABAAHAAHCAHGFHBFABFAEHHCHHCFBEEDEEFEGDEHDHHDHCBEABAGGAFGDFDCBCHBCHBHEBAAGCADCHFCFDBBDBCDECHACHDBEDHEFGADGHDBE,False +214,17.0,18.0,21.0,25.0,26.0,17.0,17.0,17.0,FEFAEAHHABBGBGGCDGDEEDAEBGFHHCADDHDDEDDEAFECGGAGGEBGBACEEDEEDHDDHGBHEBCBHADFEDEGGCDDBDCFCHFEFAHFHDBHDBHAGCFEFFEBEEBEEDGEACFABBCBFDBFHFECGHCGACDCCDCCECFHAACADC,False +215,3.0,8.0,12.0,3.0,11.0,1.0,8.0,8.0,ECHEGGEHEEBCEHGGHBAADGCHBCBBCHBCHBCEDFEGHEDCGCCECEBCGA,True +216,3.0,7.0,2.0,4.0,7.0,5.0,4.0,9.0,EEBACHABHEFDEHHEBHAFHFCHEDGEBBDFBHGBHGFDG,True +217,24.0,19.0,23.0,32.0,19.0,19.0,18.0,19.0,BDFHFFHEAGCGGEHGAHGADAEDAEGACABCBFDEDDEHDGDDEDDGCDGAFBBEBHFBDEADCDDCHBCEAHDBHCBHCACBGCGFCGFCGDHFABCACCABHEEHDGBFFDFFBHADDDCAAHDAEFEEFBDFADGADHADFGDCGCCBECADAHHCFDCGBEFEEDHBA,False +218,15.0,9.0,15.0,14.0,9.0,15.0,10.0,14.0,EDDHBDCEDAHHCDHCDEFECFDDBDEGDCAFCAGCHCFHBFBDFCABCEGEEHHGFHAFCABHABDAFAHBHHGFCGFHGBAAFDAFAAFEDFAGGCCGC,False +219,24.0,26.0,20.0,28.0,17.0,21.0,17.0,23.0,FBGGAGHAGHGGBGGFFDAFDHDCFBFFHFDHDDHFDHFHCFGDHBEFCEACHFEHCBADHDBADCEBCDDAGDAFDAEDEHCAFDAFDFBBAGBGHBCHAFECHDCEBBEABGFHEBHDGCEFCBACBACBCCBHBFGDADAAHAHBGDBDEBGECEDHDAEBAEBAEHADCDBC,False +220,10.0,6.0,12.0,8.0,3.0,8.0,5.0,9.0,DEDDFFBCFCCAGBFHBACAACAHFAHBEGGAGCDCCDFCDFCAHCACDHEHHABGDBHFH,False +221,18.0,20.0,25.0,20.0,16.0,11.0,30.0,25.0,BFFBEGBGFBGHBEFEDHBDCAAHAGHFGDADCBDBBDECAEBAHGHGABBHHBGCGECEECADDDGHDGBBGBCGHHGCHCCHCFHGGHAAHAHGAHGEHGDHBEGFHFAHGADFEGBDHFDGCDGCFGAGCCGACGHEGDCCCABCECGEHDEDDCCECADCB,False +222,19.0,19.0,21.0,28.0,17.0,28.0,23.0,16.0,FFFFGGBAGBFCDFCBFDGDDEDDFDEFCHDCHACAAFFDGFHCFBCDGEGEECCCBBAHHDEHDECFGGGDDGDDGDDCBACBABHCDCFDCEBEGBCHEFHGBHABAGFGFADHAGFAEFHEBBFBEFCGFHAFGADGAFHBCABDEDDCHFEHFEGAEDCGDFADBAG,False +223,23.0,19.0,28.0,13.0,18.0,28.0,23.0,33.0,GHBCHBGHEHEAHDHGDCFBHGCHGCFGCBGBGCDHEFAGHEGAABBHECFCFGDEHCEHAFCADAGDFGDHACBACHACHCHFBEFCFGCHHHHCHBCBEDBFHBEHBAGEACHACFAGGHGDHFFAFEADEAHFAHCCHEFGEFBFCBHDFGFFGAFDACDECECBEBFHBAGCHGCAFFAFF,False +224,3.0,2.0,2.0,3.0,1.0,3.0,0.0,0.0,DAADFBDFBCACFE,True +225,18.0,28.0,26.0,15.0,16.0,22.0,28.0,24.0,CCBGHAGAEGAFGBHGCHGBBBHBBHCBDDBFDFGECEECAGHEBBGBAGBFGCHCCDGCDHEAGCBBFBBFCBGGAGBDGHGGHGHHFHDCEDAFGHBGABHBEAACGCCHCCHBHHFFFFGCFHCFEDACFGEFCAAGDCDDHDBAABFACDABEGCEGFEHFEFCEDBFHBEHF,False +226,0.0,1.0,4.0,5.0,1.0,5.0,5.0,2.0,DBGCFGDHGFCGDHGEFCFDCFD,True +227,9.0,11.0,5.0,9.0,13.0,8.0,7.0,11.0,DGHBGEBGHACBAFHAFHFHDDHCGEAGEDEEBEAGFDFBDFBHFHCDHCEEAFBABBEEBEBDHADHGEEAC,False +228,3.0,5.0,4.0,5.0,8.0,4.0,5.0,8.0,DCEDEHGEHGFCEFGBDHBDCBDHFFHEAHEACGBGHAEHEB,False +229,5.0,2.0,1.0,1.0,0.0,2.0,0.0,0.0,ABABFACFADA,True +230,17.0,15.0,18.0,10.0,25.0,10.0,12.0,11.0,ECCHCABEAEAABAEBGEBCEBGAAGBBDFHDEHDEHCHHCHCEHEEHCGBAFCDEEFGEGGCFDEFBBADBEEFHEAHECGFCDAAAFBBCCCACBGGBAEDDEGDECCEFAEFAEG,False +231,31.0,18.0,29.0,27.0,23.0,14.0,25.0,29.0,DGBAGHGHDGCGACBADBDDEADFCHGDBFEBHEBHEFHFCDFCDACFGHDDDDDCGCEAEEADCBDBGGHCAACAEDACHEHHAHDDFDEHCEHCECEHHEAFEABCGEGABHEDHEFAGCGGCGACDAGDACAAHACBBCDACAACHCDHGAHGFBDAACEACECFEHGGHBGHBCFFGDBGHBEFEHHAHBAG,False +232,9.0,27.0,30.0,27.0,17.0,16.0,18.0,20.0,HDBHDCCCHHCHECBBCGCEDCHCADGDBBEBGEGGFDFDDGDBBFHCEEDFFFHFHHDGCEBCABABDEHDHCDHFDHFDHBDHGGEECBEHBDFDDBCDCCBCCGCAHDBBBBFBEHBEGBEDDGAAHCBECBCCBCFFEDFEDCCGBAGACGDCAFCGFGG,False +233,13.0,14.0,9.0,12.0,10.0,11.0,7.0,12.0,CACBADGHDGHDFHDFHDEEDGEBBEDHACHABBFCFAEHACFDCEAHEABFFBFEAAEBCHDGBDBBGCBFEAFGDCDHHABHABGF,False +234,27.0,12.0,19.0,20.0,14.0,11.0,16.0,19.0,DCEACEBHDGHAGFBGABGABGABCHFEADDADAHDHDGBFAECCBCHHFADFEFAHDAEDCHCHADBFDCGDCHECGAAAAGBAEEHGCCGEAGEFCDFDGGCGACHCEHCEHDEHBCADAADADDFHGAHBAHBAF,False +235,10.0,14.0,16.0,10.0,22.0,13.0,14.0,12.0,BCEFFEFBBGBBGEDGEABFACCDCCDHEGHCBDGHEEEFAGBHGBEEHEEHDEFDEFCECDECHGGAGFFEDGHBECBHCGFEAAEAHGBHGBHEBAFACCEDCACFDCF,False +236,7.0,11.0,9.0,8.0,13.0,11.0,4.0,12.0,AEBEHFHFFGFHBFHFAHBHHBHFEFABBEBAEFCEACHHDGDEGABCCBCEBDEDCEACFHCFDCHDEEDBGDE,False +237,23.0,30.0,14.0,18.0,17.0,26.0,17.0,30.0,DGDDFCEFCGCBBHACAFCEEEEAADADEHFABBADHADHFDBFHHFHDFDAFEADBADCAFAFBEBBEBBCBBCFBEFBGFBHBBFFHFAHABHEFHBFHEGHAAHBAGBGFHAFABEGEGGDCGBHBCHGHFGHGHHCDEFFHCBHBBHGEHGDHFDHCDBDAHGHBEAACFG,False +238,19.0,27.0,27.0,14.0,19.0,23.0,28.0,21.0,CCCACCFBHFGEBABBGFFGBCHBFAAFBAHCAHCBGABGADDABDAFDBCGECFEHBCHGHHGHEGDEBFBBCGBGHBGFBCCBDGDCHACHADFADEHDEHEGADGAFBFGBEGHFHEADFCCGCCGFCEFGHFEFBCDBGHHECGBCFAEBBCDGAGCAGFFEHGEGFEGBECHE,False +239,12.0,6.0,10.0,11.0,16.0,6.0,12.0,10.0,DBDGGDGCDECGHCHEAHGDEFEEFEBBHABCCDACGFEGHECAFAEDAHAGCBGAHGAGFABFDEEDGEHEECEDCEAHDAH,False +240,12.0,11.0,10.0,12.0,15.0,7.0,12.0,8.0,EHCEBGEBCADCDFCEGBEBCEBHDGAAGDGHDCFDEEGBEFEEFGEHGHBEABEAFCFHCGHCBADAADADGAEBBDDHDFGACGA,False +241,24.0,20.0,23.0,18.0,18.0,16.0,33.0,12.0,DCADHACHFFHADCCDEEDCEDCFAAFGBCGACGAGGACHBBDBCCBEFBGCDGHFECABCACGAEFAECBFFFHGCAECAGHEHBFHBAGEFGECGHBABCADDGGDGGDGGCGCFFHGGEAGEGEEBBEGAGFFGDGGBGDBGDCGHAAABGEBEBDDBDAA,False +242,2.0,5.0,2.0,2.0,7.0,2.0,2.0,4.0,EHCHBDECDEGFEAHHABBEBFEBGE,True +243,5.0,8.0,9.0,5.0,11.0,13.0,13.0,9.0,ECEEGBGFFHFBEFHFDBGDBGFHFFHGHCGHEACEABBFEEEEGCGGCFBCDCCEHCDHGAFGABGHFGAFD,False +244,8.0,13.0,8.0,11.0,10.0,14.0,17.0,10.0,EGDHGCEDHEAHFBCGBAABGEDAEDAEGGDDFDCFGCEGCGFADFCFEBBCBFDGFAGFEDFBGFGHBBHEDHGGHBAFBFHCFHGBHGB,False +245,10.0,16.0,19.0,10.0,13.0,11.0,21.0,15.0,BEEBGHAGHCCFEDFGFHBHHDFDDHCFAGFAHABFABGAFAACBECGGGHGCAGCHCEFGEHBEHBGFGEFCHDHHDEBCABDGBGGCGGCBGEBGDCCCCDCBDEBGEBECCH,False +246,9.0,13.0,8.0,9.0,4.0,11.0,15.0,3.0,BDDBDDBAGAEGABGEDFCBCCFCDABHCBGDGGEGCEFAGBAFBGGBGGBDFFAFBCGDHGHFFCFAGFAB,False +247,24.0,29.0,19.0,27.0,21.0,19.0,25.0,36.0,AGGDCEDBEDGADBCBEDBHDFHDBEFHEFEEGEGDEABEFHDBHBHHFFAFBGGHCFFEAFDABEAFCHDCABBBCBEEBFBGAGHBGHCABCAFHDGHCHHCDGADHADGFHGFCGDBHBCHBDAEGHHGHHAHCAHDDBGHBGCEAHGADDHDECGEHHEDEGFEDABHABHABCABDABDACHGCBGDHHFHFFGC,False +248,23.0,15.0,19.0,20.0,20.0,17.0,12.0,20.0,AEDAEDAEFADFAHFAHEEHBBCBBDBCAFAAGCCGACEHEADFHDFCDAHGBEFFEFDAFGACGECEHHGADGBCAFCGCHDDDGCFFDBCHECFEHEABEABDCBHFDHECAFDABDAGEBGHGEHDBADBADCHCHHCFHEEH,False +249,5.0,8.0,8.0,6.0,8.0,12.0,5.0,4.0,DDADDFEDFHACECHGGHCDBBFFBEEBGEBCECCGBEAAGAEBFCFFHFFBFFCF,False +250,9.0,9.0,5.0,9.0,9.0,5.0,9.0,6.0,EBGEGDECAEBBGBFDBACGCBBCBBFDADDACDGEDGHDHDAHEFHFGAEGHFGAAEHAE,False +251,3.0,4.0,6.0,7.0,2.0,6.0,5.0,5.0,FCHFEBDGHDHADFGGFGFFEDBCCBCCHGCHDBDDAA,False +252,23.0,16.0,22.0,22.0,17.0,24.0,15.0,22.0,GDGADAHGFBBFBCHBDHBDCCDHEGADCHBBDFHCGGCEFBECHECEACFDBADEACEDFFDFFDFCEFCGFCHFGAFADGAFHAEABFDEDHHBAAAAHGABGDBFEHFHHFCHDCEAEEAEDCFFAFHCHHADHACHAEDABDCCGGCGFCBFGEHBD,False +253,28.0,21.0,24.0,17.0,16.0,23.0,19.0,22.0,HBGAFCHGAFDHGAHGHGDDGADGECAACFACBDGFCBAHBHDBFDEFABFACAEGFHGBDGBFHDFHCGBAGCABEGHEFHECCEAEHADHFDCCDCCEAFBDDBFHHFGHFCHCDHCFFCBAEFAEFEEAAEBFCBAABAAHEABBAFBGCBGCBDFGAGCCDECAHH,False +254,22.0,21.0,35.0,22.0,18.0,16.0,18.0,17.0,CGFCBBCBBCFBDHEGBFDEHCCAECAHAFDEEDAEHAEBCHFHBFHCHBGEACCCCDCABFABCDBDHCGCCGDCDDADDGGEHFEGCCBCBAFDEFDAADFAGGHECHECHECHAHGCFBBBBAGGEDBFDAFDCEDCEDCADCBHEFCAGCAGCBGFDACAACGGH,False +255,16.0,23.0,16.0,16.0,20.0,17.0,25.0,22.0,FBDCDGFHBEHADAEBABHAGDEEDGEAABDDEEFEEDBCGGDHHDHGDABBCBBCDHCDBGDBGCHGHAGFECEEBEHFGDFACHGHHGBHCEHCECABHADHACFBBAEFCEHAGHGEHGFHGFGGFGBFBFCBGCFGEFGEHBBGFCAFGAB,False +256,4.0,5.0,1.0,1.0,3.0,4.0,5.0,7.0,BHFAGFAFHABDAEHHGHHGEGBEGBCBHF,True +257,15.0,16.0,15.0,21.0,14.0,16.0,23.0,29.0,BBAHCCDBGFHGFGFFCFGCGHCGHDGAGHDCHDEABEBGGFDDFHDHHGHBAHDGCAGBGEBHBCHGEFGEHGEBFECHEDGEHBAHBEHDACDHHHBCHBCHAFHDCHAHGAGGDDBDDEACBAEEAHDDFFHGFHFFDAEDACDFG,False +258,25.0,18.0,28.0,20.0,16.0,20.0,26.0,30.0,GBDGBHAEEAHBAHBCHCCHCEBCECDEAAFHHCGGCFFDFBAGBHGFHDAHBACCADCAECAFFAFFGGEGCEACECCFCBEAAGFCFFGGHCDECBGHBHACAAFDGHDCHDCFDHFEHFDGDGHDCHAEADGGEADCHDHBGBDGAGGFFHHFHAGHCHHCDBGHBEHDEHGABBADBCG,False +259,10.0,4.0,2.0,8.0,6.0,7.0,4.0,6.0,BFAHHADDBDEBDAHFACEADEFDEHDGAGFDGFAEFBGFEAACHAH,False +260,17.0,18.0,20.0,22.0,23.0,26.0,23.0,18.0,CGCHEEDEBDHDGEGFEFFCAHGBHBEHBACAAFAFFDBFDCFAEFADFAEGBBHADAGGHFGCCGCGFBDFEEEEADHGDCEDFGDEBDHBGHBFFCAFCECGEDADDBHGBECFEBFEDFDDEGDHCAHCFFGFFGAHCDHADCBECBHHBHCGFGGABGCEGFE,False +261,27.0,24.0,20.0,19.0,30.0,32.0,21.0,26.0,GEHGECEEBEDACCACGBFGFCDBHEFEEFGEFBFACFACFAFFAGDACBAGDEBABFAEDAGHAHBAECAFDFEEBBBFEBDEFCHFHBFHFEHDGHBGHCCFDDAADEAEECGGHGFECFEDFEAFACHACEFBEFHHBHHFEAFHBFBBFBHFCAGHHFHHGHDCHDCHFGAGDDGCAGDEEAGEBEDAGHADBBB,False +262,24.0,26.0,23.0,23.0,21.0,23.0,28.0,24.0,CFDHHBBHEEHEHHEFHBDAADAFDBCDHDDFGAFCACEADGBEGCGCHEAHGADGABGADCFFBFEDDAFDCFHBBCFBGDGCHECBEBBCABDAECAHAHHAHEBHDHHFAHGEBEHFAAGBAGBGGCAFAFBAFBDCDCCDGGDGBHBBCBGFGEEGECGEHECDFCBFGBDGCACEFGEGGFHGFDGF,False +263,0.0,1.0,9.0,1.0,3.0,4.0,6.0,1.0,CHCCEFCGGBGFDGEGCECCFCFGC,True +264,6.0,5.0,5.0,2.0,0.0,4.0,6.0,0.0,CCAGBBGDBGDBACACGAGGFFFAFBAC,True +265,4.0,10.0,10.0,7.0,1.0,8.0,4.0,4.0,BEFBDFGDFABCABCHFCDGBHBCAFCAFDBDBGGBDFCCBCFHCDHC,True +266,22.0,29.0,31.0,16.0,20.0,28.0,16.0,14.0,EHAHCBHCBECFGBBCHEEBAFBHHAFGBFDBFCBFCBFCBFCGFGECBBGFCEFBEFDEDDGFCFCAGCAFCEGAAGAACDCFGAFGAFHBGABDAGAHCAECABBBCFBCDEAAEBFBBFCCFCCFABFDDFBEHBFGEDBEDEHAECBGCFHCDECACCDEFDADEHCGDBHH,False +267,19.0,18.0,7.0,10.0,13.0,13.0,13.0,11.0,HAHCGEBDCBCBBEGHFGBCGAAGBGGFDGCAEADBAHBFEFFEAGEHCHHBAHAADEFGEAGFFEFAEFCBAABAABEAFGAEGDEDBBABBFBHHDDHDBFD,False +268,17.0,10.0,10.0,7.0,8.0,5.0,14.0,9.0,DCADHDGHAGBAEHECHCGADHCGAEGBEGAEGAEGACAHGHDCBGHBGFBCAAAACBBEEBGBCFCAFDAFDHFGABGA,False +269,1.0,3.0,0.0,1.0,3.0,4.0,3.0,1.0,GHGGEBEFBFABFEDF,True +270,23.0,19.0,18.0,18.0,15.0,13.0,11.0,15.0,AHDAFCAECAFBHBCEFDEFCEFEDAADBADCDDFDAFGEHGEAGHADBBEACFGBDHADGCCABHHGHFBEDGHFEACEFCBAGAAEABEABGABHBEABGABFCBACGDDHFCHBCHBHHCEDCDDCDBC,False +271,7.0,9.0,4.0,6.0,4.0,10.0,14.0,6.0,GDDGADGAHAAHABDGFFFECFBHBEGEGHEGDCABGGFFHFFHFBGABGDBGCBGFGCB,False +272,9.0,5.0,1.0,2.0,6.0,2.0,1.0,1.0,EDAEAFECFGHAABAEDEBBEBAABAA,True +273,6.0,7.0,5.0,6.0,3.0,4.0,5.0,6.0,DBGDAGHAGECGFBHFBGDDFEDFHCBBEHHCAHBACBACAD,False +274,13.0,30.0,20.0,14.0,22.0,14.0,15.0,16.0,HBGBBDCBAHEFEBDBCABCGFGEHGECGCDECDBFDECGHBFHACDCBBHEHGGHFGBBBBHBBHBBGBEABHDBGDEGEFDECCFHEBHEHGEFCFBCFCDABAAHEECEECEDCEDGEBFEBAABGABCBCAAFDAFDHFC,False +275,5.0,8.0,10.0,12.0,2.0,10.0,10.0,5.0,HGDDCDFCDBGFCGDBGEAFACFDBDDBHDBCDCCFGCHGDFGCFDABHGBAGCGFABFEHF,True +276,5.0,1.0,0.0,3.0,1.0,2.0,0.0,3.0,BDDHFAHAAHAFEAD,True +277,24.0,23.0,18.0,24.0,16.0,33.0,19.0,28.0,ADCABCHCAHCAHEADEAHBGBCGFGFFGAFBDFGFBGDEGDGHHGHHACDDGFFAFFBFFEFADHDDADDFFAFGBFBBFHFCHBDADEAHECEDFDGFDFFDCBBHDAHBBHCEGEBHHBFFCCHHHHCHBBHDHAGCAGEDEHDGHDAFAFBBFABFAEAAGABGFEHCCBCHECFEDFGFE,False +278,12.0,29.0,23.0,26.0,19.0,18.0,23.0,13.0,BEBBEHBCAFAHEDDCDBBDBBDAFFAFCADCGGBGGCGHCFECEBDECGEHGEADBFDHFDGCDGCBCCHDBEABDCBDEBEEBDCGECBDHBEHEAGAFGHFHEFBBDBGEBFHGGHFGFDGCDGDDCFFFDFECCGCGGFBDBAACHEDBDDBGCAGBBC,False +279,16.0,11.0,17.0,16.0,19.0,22.0,19.0,14.0,GFAAFDCCEGCHGBEGDABFBDFEFEEBEBGFCGHHHFHAFDADEAHACBFCDFHFGCDACDFCGFEDFEGADGAFCEHCAHBBHEGCDDHDCAFCAFGEEGEEFBEFEHAHFDEFDBGDBGAFCAGCGGCGHE,False +280,10.0,14.0,13.0,11.0,22.0,14.0,17.0,12.0,EHCECEHBFGCGGCAHCDGCGGEDBBBFHCFBFBBFGHGHFABEAEGACGACBFDBCEECDEBFEBDGHDEBEGGECGEHGEDEEHFEHFEGFAADGADEHDAFDHFEEFCBA,False +281,32.0,31.0,18.0,18.0,36.0,28.0,25.0,12.0,GAHFABEGCGAEFADGADFABCADAEBAEFEHFGBGCBHDAHAABBBECFEAEEFEEFEDAEBAECADCDDBBBCBBEDBFAAFHEEGFCGEEGEFGEFAFDABCABDAFGFBGFEGBEACGGHFGAFHBBDEEEGGBHGFFAFFGEFGEBGDCHCHGBBGABEABEFEDADCEEFDCDHCDBGABAACAHCEFCEFBEB,False +282,19.0,24.0,17.0,28.0,20.0,14.0,18.0,11.0,CEGDBCDFGFGCADCEEGFABEDBDBBDEFDEADBGBEGBACDDFDHFBHGGCGAEGHEGHECDDGDFGEFABAEEHDFBDFBEEBHCDCCEHHDCGDBHDFDDADDEEDBBBBABHAHDABAAGADBCFBCBECDAGECGACGACFABFA,False +283,26.0,21.0,30.0,21.0,22.0,23.0,22.0,14.0,ABEAFHABHEFEEFBHDAHFBHFBAFBCBGGHGDHFDHFBEBBACCAECAECACGBCFFEFCEGGACBCDFAAHABGDEGDEGDACFEGDEGAFAACCBEABGAFDCFDFFGACHCEGCFGABCHGAHCDHCDCCDCGABDFBDEDCGFFBFEACCDCHDGGCGEEAEBAGDCDDCEEB,False +284,14.0,18.0,15.0,12.0,15.0,14.0,12.0,12.0,DHBFHFFADGAHCABFABEEFDEAGEAGDDBACBCCBGCBEEBEAHEHCFFCEFCBCGDCGDEGHGGABADBEEBEHCHHDBEGGFFEFDADHAHBBDFBCCBGABCFHCFA,False +285,16.0,15.0,17.0,12.0,11.0,20.0,18.0,11.0,HGHCBHCECFEHFEGDAFFGFEGFEAFGFBGABDBBGBACBGFBECAAFDAHHFGGAGGAEGCBDBBDHEFGGDGEHAHADEADEFCCFCFADDBCCBCABHAFFCFGCFDCFACDBCGH,False +286,11.0,13.0,7.0,7.0,10.0,17.0,12.0,13.0,FDGFDGFHABDDHFAHBHFFGCFHBGAGFFGFHHAGHEGHCGBCECDECDBHBEHBEHCAFGABAFBGFBEFGEABFBFDEFAEAHEABC,False +287,8.0,6.0,3.0,14.0,2.0,6.0,4.0,6.0,BGDFDCCDGAFBADBDHHDHCDHAAFAADBADBFDEFABDGHEGDDFHD,True +288,13.0,9.0,15.0,13.0,19.0,11.0,16.0,13.0,GGEDADGABGCBHAGACCFCHECDDCBAFEEHEBBEABEACFACEDHEAFEGFGDAEAAECDEFEHHEHBFFDCFDCDAGDHEBHCGHGGHCEFCGFEGEDGDCGHBGH,False +289,21.0,24.0,27.0,24.0,13.0,22.0,21.0,28.0,EBFBBCGBDHCAHFAHBBHBDHBDHADECDCAHCGHGFHADHDCHFBBAHBDHECABFBFFCDFGDFECBECBCHEAHFHHEHGGFAGBDCEHCFHCGGBEGFHBFGAFCADDFDDBDFCAFCHFDDACGACGDCGAGGHDEDECDAGHBFABABBEFBCCDEAHGAHGCCGCFAHDGHC,False +290,11.0,5.0,20.0,12.0,8.0,15.0,4.0,7.0,CBCCHDDHADEADEFDAACCCFFDFCAFCADCGDFEDCECCECFFHFFAGFCEDEBFFHCHGCDBHGCFDAFBAEHACCACB,True +291,20.0,16.0,14.0,23.0,25.0,13.0,17.0,18.0,GBEGBEGFEGFBFDBFDBADHAFBDFGDEGDGGECCECAEAADAACHHHHBHEGDADDBHAAAEHEBDEBGEAEHDGHAAHFABCEGDFGFCECDGDABDHBDECCABFBEEDEGFEHFEHGAHBDCDAEHAECDCFDCEDHGHEC,False +292,22.0,21.0,19.0,22.0,30.0,26.0,23.0,31.0,AHGAHGABADGFGGEEAEFDCABCFBCGBCBHCBCFEDFEDHADEFDFBHCBHAHEAHEHHEHEBGEAGEDCEHGACGDCFCEFDEBDEBDFHACEEHBDDGGEBCEBCGHFGEABFAEEBHABGAHGAHDHHDHEABEGBFAEGHEHCADFFDFGAFCDDGFHFFGFFDEBCHFEGFCDFHHCHFBEGHHADH,False +293,16.0,24.0,24.0,18.0,24.0,17.0,14.0,18.0,BDDACEACHABHABHECHGHEGEEFCHFAFAGFBBBGBEECEEHEFDBDDBDDGCGBCEHCEDCBFABFBBCCECCGBEBAABHECEGCEDDECFECFHCFHCGBCFFDDFADFAHHCGBBBCAFEBHGDGADGAHCBEAAFGDBHHEDCEDFEH,False +294,32.0,23.0,12.0,12.0,9.0,21.0,14.0,23.0,BCGBDHDCGGGDAFDFFBCABCABCFGGFAAFBHEBHGBGGDAFAACABHBFFDAFAHHBHHDHGDEADBHGBHBBHBBFACCBECAAAHABHAEAEDFGCCEAFFHEBHFHHEHDABAAGAGHADAAHAACEAHAAFFBFFBFFH,True +295,25.0,28.0,34.0,29.0,21.0,15.0,21.0,21.0,GBBDDFEAEADECDAGBCFBADECDBBDCCGCAGCDBCBBCBDCBGCEHCGACACFBHFDDBCHFCGAGGECFFABDEGDEFDHFHHBBHDAEDBEDCDDCDDCDAADFACEDHHGACGBBGAGAEGFGGHCACCDHGEHGEHGHCEACBHFEAAEACEACHHCHBCBECHHFEBBDCBFCBDDBDABAEFAHG,False +296,10.0,5.0,3.0,10.0,3.0,6.0,4.0,2.0,FCDBCACHBFABDAGEAGDADEBDFDAFGABAADEADHGDFFD,True +297,18.0,24.0,24.0,26.0,29.0,26.0,24.0,26.0,HAEHBEAEEHCACDDCFDHFGCBHCBCDHFDEADBBGCBGABFAFGGHGEAGDBCCGCBDFDDFBEFBEGDEGAADHADHBHADHCDFEFFEGGEBAHBCFGCEGEBGBFGEAAEDHFDAAGHFGEEGEEDHECGEDFEBBDCCDBDECFCBBEFHFCGFEHHEHHAGHCEHCDFCDFCDHCHGGHFEFFBFHBADB,False +298,13.0,9.0,11.0,21.0,12.0,21.0,9.0,8.0,DDADBAGGAGEAGECGEFHFCCFBCABCABHAEFABFDFCHHDDEDDHADHCHABFFFEAEDCFDEGGFDDFCDFEFFEDFEBADFDDFBDFCHBGFCEDDAFG,False +299,9.0,10.0,7.0,5.0,4.0,5.0,9.0,5.0,AEBFBGFGGAGGADCADGDHGHEBHBBGEBGFCHBCHAAFAABCECCFDDBCAB,False +300,9.0,10.0,14.0,12.0,10.0,5.0,22.0,10.0,GBDGFGGEGEHGDGGEGCCGACBDBBDABDAEFABBCEAEHAGCFHDGHGGDGADGHGGBFCDHCDGCGBDAACEHCEGCEGDHCHECHCBF,False +301,23.0,15.0,14.0,8.0,21.0,17.0,19.0,20.0,FGCEGAEGEDHEDBGGECFFHEBBBFDAHHEBAEBHCHEGAAHABEEFEEFGBHGCHCAHDAFGGHGDHGFAGBABFAFHEEGEAAEDAGFAEFACFACBHFDCEHBAHCAHGAHCCGCCGEAGEACFADFHBBHBF,False +302,27.0,23.0,30.0,20.0,17.0,18.0,24.0,20.0,AACCCBGDBFHBAECFFHBHHGHAACGCHDDBFBGGCHGAFGAGGAGGAHGCHGCDGCHBHABFDBDDEEDEEDBCFCCFCHBHFBAFBDFHFBAAAFCCGHCDBADAFCABEACGBFBEEBAEHAEGAHGACBBDACDFCDGCDGHDEEDEBCFFCAACHECGCBGCEGCDAAEEHGD,False +303,30.0,27.0,22.0,22.0,20.0,20.0,25.0,21.0,FCHFDBBDBGCAADEBGFBGABGFEGHAHBADAEDACBECFFCFFGDBGAHHAEHFCAFAACEDCFFBEFAEABHDGAEHDDBGCBGEBGEAEEFBEBDHDAAACCHCCHGDAGDFCFABFHBFHBGBBDHBDHEEHECHDCADAEDGBCCBAGEHGEBGFBGCCACCAGAADAHGHHGFDABGGGD,False +304,29.0,17.0,17.0,22.0,14.0,23.0,28.0,17.0,DABGFCFHAEGAFGFBCCBEDDHFCADEHDEHGHDGADGHGGCCFFFFCCEGHEGBDDDDDFDFGDFGCEABADBCHADBGDCDAHFFBGFGGHAGHAGAEGEGCAAHAAGAAEBAGBGFBHBBHBGDCGFCDFBAEBHCFEAAEAAHGAHGAGFACFDCFEAFDAB,False +305,11.0,12.0,13.0,10.0,10.0,17.0,17.0,13.0,BFDDADEGGFGEFBEAGHAGBACAECAFFBBFHBCHGFHGHGFFGCFCBBAGCDGDDGCGHCBHDGGFHFFHGDECDFCDEAGFAFBAECAECHBHHEHCEBF,False +306,7.0,10.0,4.0,3.0,5.0,2.0,7.0,5.0,BHBHADABBABGABHDGHDBCEFEEFCEBCEHGGCGBAABGAG,True +307,17.0,17.0,13.0,19.0,19.0,19.0,22.0,12.0,FDEAAHFFBFBGFBDFGDFGDBGDBGFBFFHFFABEGGGHAAHEAFEDFCBFCEDCDAGBAFBGHDHCGHGDEGDGCBBDHGABCDHCFHEGGDBCHECEECEADEAEGAGBAEEDDEGCEGCHACBAFBDEDAFGAE,False +308,16.0,19.0,32.0,19.0,25.0,21.0,28.0,24.0,BCGCCBFCFGGDHGDADAACACGGBADDGDDGFBCHHCFECDGGAEBAEGHCDBCHEEHAEHFEFFEGFEHDCCCEGHFHHGBGDEGFHCFBFHBGEGFCGFCBHGBHEBEEBGBAGEEGHEAHEBFEBHCBGGDGDCHCCACCADBAHEDFGCACCHHCHHFBAFAEEDCECCDFCDFCDFEG,False +309,12.0,7.0,7.0,14.0,8.0,9.0,9.0,23.0,HFHHBHGACFAHHHHHDHBGHCEHEHCFHCBHDAHDAHFGDDHEBGFDDHADHBDGEEGDACDAHDAHCGHAADAECBEGEFFAFBDFG,False +310,7.0,9.0,2.0,2.0,5.0,3.0,5.0,9.0,BBABAGEAHBGHFEHBEHBHHAHBEGBGGBDACFCHFDHAAE,True +311,26.0,28.0,24.0,21.0,11.0,21.0,26.0,17.0,BFBEHBHGFHFHDDGADGADGFDCFBCHGFAEAAEAAEAABDDGHDBEDCCGFCFFCBBGGBFHCGGGDBGDBDEBCFBCABGDBGDFGEGCCAAHBGHGGFFBAHBAEGCFBCECHFADGGCECCFCBACBGBBGCCDAEHABFADDADDAFBHFCHAAFAABHHCHBCDBGA,False +312,23.0,13.0,12.0,13.0,21.0,13.0,8.0,13.0,FBAFBAECDHHEEEEAACADHEDAEAEFAEFAEGAEGAEAAEAGGBCDDFHAHHFFHFCCACAEFAHFAECHEAEDDHDGBBCBDFEHEAHBAHBAGCCDDDFGEGEFBBDBBCCB,False +313,3.0,1.0,2.0,0.0,2.0,1.0,1.0,1.0,HACAACEFGEB,True +314,19.0,17.0,14.0,10.0,16.0,21.0,10.0,13.0,AHDAHEEFAEAGCADFEHCEBCGCCGADDADFADFAHAAHFEHFEHFEFFCBFEBAAHEHBEBCCGHEBHCBFCFFGEAHEACBABBABFFGFFGBBBFBGDGCCBEDADAFBFFCHEDG,False +315,3.0,8.0,4.0,7.0,12.0,10.0,4.0,14.0,DHEDBEDBECHEFFFCHDAEBAHHFHFEGFECEEDEGHBGFBAHBHEBEDCFHHFHFDHGBH,True +316,19.0,13.0,26.0,20.0,13.0,13.0,16.0,14.0,AFCBGBFCAFCEECHBBAGCDGCFGHEBHEDCCAHCFEAEDDEDAGCAFCACCADCGDEBFAGDHGDCBACHAGHBFHCGECDCAGCADADFGDCGDGEDFADCADFFDAEDHCCHCBHGBHEBFGBCABHHDE,False +317,16.0,18.0,21.0,25.0,22.0,16.0,21.0,17.0,GDDGDDEDFEGFEDEEDHBDHBCHDHBBBBBBCCBCCHFCHBCHEHADGCDGCBGAFABCEDFFAEBCHBDDEADCGDEFAEGAGCCDCCGFDFBDHCGHGAAFEADAAHEBHEAHFCCDCEAHEAFGBGEBGDGEFGFHGEHFAFDGEDGECEDG,False +318,23.0,22.0,20.0,24.0,12.0,20.0,16.0,25.0,AABCHBFHCDHCGFGHDHHFGAGHBGHBGCEECAEHGBCGDDDHCFHGBHGBHEBHDCCAHCAHAHCAFCDFHHEBDDBGDGEABBAEBCDDFDDFEDFACFABFCHHCHHGBFAEFBCGBDHFDBFDFDAADAFDCEHCBBDFAAAAGECDABDAEFABFG,False +319,9.0,5.0,11.0,3.0,6.0,3.0,10.0,12.0,HABHDEGCCCDFCBHCHHGHAGHCGHCDHCEGCGCEGHEAHFABAECGBBAAFGAEHAG,True +320,31.0,18.0,28.0,29.0,18.0,25.0,23.0,22.0,ADEFDADBAGBEGHEGDCAHAAHCFGCHGFEGFHGCGBFDAFDCFCEBABHDBAFAFFDGDAAHABGGCAFCACCDEBDCCGCCDCCAFGGCHBDHGCHAHBBBBBCCGAADCBDEFDHCAHCHHFHAECDCHDGHDEADEDFADBADEEDGCBGCBGDGEFHAFEAFAAFGEEDCFDHFAHFAFFAEFHEDGD,False +321,11.0,11.0,8.0,16.0,26.0,18.0,18.0,26.0,HFGEAHHHHDBHGEHDFAGGDEFDEFDEFAEFBDFHDEEDEEBGEHEHHEHACGGEBHEGHEFHEHAEGFDGDDGBCEAEGAECDHCGHFEHGAGFCHHEHHFGDFEFFHBFABHDGFFBCEBAECGDABDHBC,False +322,6.0,3.0,4.0,2.0,1.0,1.0,3.0,2.0,CAAFAEHAGBDHCDBCGBAGCA,True +323,10.0,11.0,20.0,18.0,16.0,14.0,16.0,14.0,FCGBEHDGCCHABGBCGACFEFEEFEDCCCBGCFHCDAGDAGDEDFHGBAGEDFECGACGEFGEFEHCDHCDEFHGBHGEFDEFDEADBAEHFCBGCHDCHDCBDCFHBDABGAHDHCD,False +324,14.0,16.0,12.0,17.0,15.0,23.0,16.0,14.0,HDEBDGFAFHDDHDHECHEBHGHEGEGFADHGEFGDFBCEBGAFFAGFHBDHGDCGDCACFECFEHFAFBCEHCFBEFCEADHABCBBCFBAFAGFAEEAGBBECBDGBFGHGBFDDFDDFGAFDAF,False +325,15.0,13.0,7.0,9.0,15.0,10.0,11.0,11.0,BDABDCBEEECAECHCFHBBHDHEAHEAGEDEABEDHEGGFGGFEFBEHEEFBHAAAAAADAADFAEFGHHDFHGAGBBBBCDCGBFGFCG,False +326,18.0,22.0,21.0,20.0,18.0,16.0,22.0,11.0,FAHEBHABFAHGAEGHHBBBCBGCBECAAGDACFBCFEHGDHDDCDDFFCEGHEBHCFCDFCDGCHBAGCEBCBDGBDCBDHGEFADGEFABFGCFCDBCGACGABFACDEDEBDAFAFFABGEBGEGEEDEGDAGAGGEBGCBDCED,False +327,13.0,17.0,20.0,5.0,21.0,19.0,14.0,10.0,CACCAECGEGAFABCCDFAFFHFCEFCHAHBGEECEECGEFDECDECEEABFBEAEEBEDHCAHAADBABFGFFGFGGFBGBHEBHGFGEFBBGCBCCBCBECBCGFEHFHBGHACEFF,False +328,21.0,20.0,17.0,13.0,23.0,15.0,20.0,19.0,HECGCCHADAADGADBEGBEABEHFGFGGFGCBECFHBAAEAHDFHFFBGEBGCBFHAABAABDCBDCAFAAHCGDCGEEGHGDEGCHGHBFHDHCDBCFEAGCAHCEHEEFEFBDHHDEBEEDEBGGAHGAHBEFBECEFABGABEC,False +329,24.0,23.0,29.0,30.0,30.0,21.0,23.0,19.0,HADHFBHFEHCEHDHCDFCBABEEBDEHDACBGDBCDBGDBADCCDABAGCEGBDGBEGCDFAFFGEFGAGEAGEADCGHGBDEDAADEHBAHCAEGBGFBFHBGEBDBBAEEDEEFAEDGCABCEDGFFGECCDACHBDGBDFCHECHECEACEADDDEDFADFAFHCFGCADCEECFCCFCCAEBGGHHCHFDHFEG,False +330,7.0,6.0,9.0,9.0,7.0,8.0,16.0,10.0,HGGAAGEEFBEDHFDAFBAEDFGHFAHGDHEECGHCGCCACGFGHFAHEBHCGGCBGDHGDCGDCGBGDBDF,False +331,15.0,22.0,24.0,18.0,22.0,22.0,16.0,24.0,ABAFBECDEDAHCCGCAAHHCHHGBBGBAGBDGEDEHAECACBBFHHEHHEHHFHDCHDCBGFHFFHAEBFEFGDHAECEECBEFEGCCFBCGBCDEGHBGHFAHFGDBGEAGFADCBCCHCFFDEFEEFBEFHEHDCDDBHDBGFAFFBCCBCFBDADCGDE,False +332,9.0,18.0,16.0,12.0,7.0,14.0,10.0,14.0,AADCABGADACDAEDCHGCBFHBFHBEHGEFGHGECFBCDDGDAECHBCEBCFBCHHFDHDHHFFDFBGFGHBGECCFDFHDBHGBCFFABBACBCBBCB,False +333,24.0,10.0,12.0,14.0,8.0,11.0,24.0,18.0,AHAAHAADADGFHEEGBECBDCEACAHEGHEFHADAADFHGBHGBGBCGAGADGADGAHCAHFHFGEGGBACDCCDGFGBHCFGAFGBGEHACHAGGCDDHDAADGHDGFCGAHBAHBGFF,False +334,17.0,19.0,16.0,21.0,12.0,28.0,7.0,21.0,BCEAFGACAHCFEBBDBBDFFDBCDBFDFFDHFABDGBDFFGFDHFCGFGHCBHAFCEFHHBHHAHFADFBFCBFCBDCHEHDCADFDDEHDECDFCAFAAHABFBDFHFCDGHDHHCHECBEAEHAEFABDEFAFBGHEA,False +335,5.0,1.0,17.0,8.0,5.0,13.0,6.0,9.0,HFEEFACCHDCHDCHFBHDDCACCFCCGCFFDEFAFGCFHAEGFEGFDCCAFCHCGDCGDCHFH,True +336,7.0,5.0,7.0,10.0,4.0,6.0,4.0,9.0,CABCEBDDFADCAFCFGCEGEHDDBFGBFHCHHGHHDFDEHDAACAADHBDH,False +337,17.0,14.0,20.0,15.0,14.0,12.0,26.0,25.0,FEFFADAGDAGFCHHBHHBAFEECECAFCDFDDGGCHGCHFCGDGGBBGDAHDHECHGCBBBHDEHCCHFGHFCHBCHDAHCAGCAGEBHEBAAACEECEGGDHCEBFEHGHCGHCGDABAGHGGBBGFGGDGHHEHDDAAGA,False +338,17.0,17.0,8.0,23.0,13.0,10.0,15.0,13.0,DFFDBGEBEBCDBFDBAEEAFGAHDDDBBDEBGEBGBAGBGBCGEDEAHHADHDDHEDHGGHADDBDHHDCHDAGAECADCHDFBBFABDAFCAGDFFCAEGAEGEFGBDGCHAHA,False +339,18.0,24.0,23.0,25.0,16.0,22.0,30.0,24.0,DGBDGDDCDGCBGFEHEAAFCACGBFEBGCGCABCAFAGEAGEAHDCHBFEGHEBDDBDDBGABGFDGFBHCAEEAGDHEHFEFEHFGHFBFFGCAGCACCDHDDHBDFGDFGEEGBFDHHBCHDFFDCCABGBDGECBEGGGHDCHACHBHHGGHBGABDABHFCHFHHDBABGFCGFCDC,False +340,2.0,2.0,13.0,7.0,3.0,3.0,2.0,4.0,ECCCDCCACCBDCDFCDGAHHFEDFBDCDCCHGCHE,True +341,4.0,3.0,4.0,1.0,4.0,2.0,6.0,4.0,GAEGBCHBCFGAHGAHBACEECEGHGDF,False +342,10.0,14.0,13.0,18.0,10.0,15.0,4.0,7.0,BFBBADBAGACCABFAECCFCCEDEHDABBAFGGBDBCEBFDBFDEHDGHFAEECCDCCFHBFDEDDFDDCDDEHDEFFBDFBDFACHAFH,False +343,2.0,3.0,3.0,5.0,8.0,5.0,2.0,1.0,EAFDCDDCHEBFEFDEFEABECBFGEDGE,True +344,16.0,17.0,10.0,12.0,19.0,14.0,18.0,24.0,DGDFEBGECFCBBGFFEFHEHBEHGCBACBEGFGGHCBHGBHAEFBFFBHHBEHAGAADFAGFAHFAHGACGAEHABFGEGHEHHEHCABDAHEABCDHGEHGAHDDHDDBEFBGDBADGCHECHDHEEE,False +345,12.0,6.0,8.0,11.0,11.0,7.0,6.0,8.0,EEABBCDDGADCAECADHABGABECBECFEFFECDEGHAFHDGHFHAFAABDAHCEHAEHFDCDEGDGD,False +346,14.0,12.0,14.0,18.0,13.0,23.0,16.0,8.0,ECHBFBAFEFGCCDDGFDBFEGFEAFECFEHFEGBDDCHDHAAGAAGFBDBGDADDHGDCFFHEEHCEBGDGCFECFEBFDACDFGDAGDGGCGBABDCBCBAFFAFFAFEAFDHFCG,False +347,13.0,9.0,9.0,6.0,6.0,16.0,14.0,5.0,GEACFCDFGAFGAFCFFDDGGDBGDEGBAAHGAHFFBFFEEFBFFBFCEGBGGCECCAAHAGHAFAAHACGGFBCBBD,False +348,2.0,2.0,2.0,3.0,4.0,6.0,4.0,5.0,EFGDDADHEFBAFECFECFHBFGGHHGH,True +349,25.0,25.0,26.0,14.0,12.0,22.0,23.0,17.0,GCCGCCGEEDFADFDCCEHCBHCBGBBCBFGBAGFGHBGABFAGFBFFACCHHFHABAABCABGHEGBCGBFFAFGACCDDCBFGFAAAAAEACEFCEFCADCAGHAFABFDGADHHGBBCHGEBGCBHCBFDHGHHCEHBBBBEFAFHDDGFDCAGCAGDEDE,False +350,26.0,15.0,7.0,12.0,18.0,16.0,17.0,8.0,GFECAAAAAHFADABEGCECDGDAGEABEGBGBBGBBGCHEFFDFFAAAGEAFBAGDHHFGGAGEADFAEEBEFCGFDDFGDFDBFBEHHAHEAGEABEABEBBADAADAFFCEGCHAE,False +351,19.0,24.0,27.0,20.0,25.0,23.0,28.0,19.0,HHCHFCDGDBGDFGCBGDFGBFEDFBGABHABCABGBGAHGBHGBABCCEEBDFGDHGDBGHFGCFGCBHFBHECGCCBCGBFGACGDCHEEDFBGABFAFFGHDAEAAHDAFDEFDEDEECFEGHECAGCECCFCBABFADCAEGEDDFHFECFEGABGAHDHECBACDGHEEEEHECBECGFC,False +352,11.0,14.0,21.0,19.0,18.0,15.0,12.0,19.0,CGFBDFCAEDFEHEHCEACEAEEFGDAGBACBFCBFABDDGHDEHFGADGHDHCBHCEHCDHBBEFGFBADCGBHEADECDCBDCBACBACBDCHFHHCHFDGCDECGHCEEGHEHFFFFGEHDCHDED,False +353,14.0,12.0,11.0,22.0,22.0,10.0,7.0,14.0,BDEBEHDFDDCDEADEHCFHCAACAABBCDBHHEDHEFBAFDACABGEEDEADFADFBGFAGCGHCFEAEDGDDFDEEBEEBEHHEHHEDEEBHHCADCACHDDGGBFEDDE,False +354,25.0,23.0,25.0,17.0,15.0,24.0,9.0,25.0,FHABBAFCCFBCFBEDDHCHGBAEHCEBDAADFADFHFHHFHBFBCHBHHEHDACDFFAGBGDEGHHGDDCCCAHCEECAEDECFBBHDFCEFBAHAAHAFHAFHBFAAFAGGACEAEDAFDHEGFCFFCDFHGFHACHABBABECCCCACCBBCDBEBBHDB,False +355,17.0,20.0,28.0,20.0,27.0,26.0,18.0,20.0,FCDHEAHEGECAEDAEFCHFEFCCCCBECHEHEDHDHHEGHEDFEHAEDGEDGEFEECECHGCDGCBEDDEDDFDDBGGCGBHHAACABGGBCGBCGDCFHCFBCFBHFAHFEFFCFFBDACFCHBHEEFBGFBHFDGGCECAAFACFBBBABBDBEHCAFFEGCADEADFFBCGA,False +356,11.0,9.0,19.0,9.0,17.0,23.0,24.0,22.0,DCFDCHHGFEAECFFCFFGEFGFFGAHGBHAADAACEFFGGEHCAHCBDFFDGGHHBFHBHHAHFFGGFEGFCGFCHCGGGGEEEFCDHCDECHECEBCFGCHBCHAEHCEGFDGCHBEHBGHBGHFAEAEGGD,False +357,15.0,19.0,23.0,15.0,30.0,8.0,15.0,12.0,EDGEGBEGAEFADGHEFEEDEDDEGGFDAEEAGDAEEADEAEBBCFBCGECBEGGACEFBGDHECHEAHEHGGABCEDDFDDEDBHDBCBACACCGCABEGHCHCCBCCAFCHBEHEHHCCBCEBCEBCEBFBBECA,False +358,8.0,10.0,3.0,16.0,6.0,11.0,10.0,8.0,EADHDFFDBFEGFGCCAFCBHDGEDHDDFBBFEBHHDAHDHEDHGDAGDAEDGDGFBGABGFDGFABBADBF,False +359,20.0,14.0,12.0,8.0,11.0,4.0,10.0,13.0,BAHGAEDBEDCADCAHBABAAFAACGBHGBHABHEHCCHBCGAEACGDCADCHGAECADFAEBDEHFCHEAADHAGHFBEBCEAGEBGBGHB,False +360,26.0,15.0,17.0,18.0,13.0,10.0,21.0,9.0,HCBGGBGGBCCDDCDCCHCHHEGGEAFEDFAGEBDHBGAFGDGAABCADCEGCFGAEABEADHABGAEGFEAFAFCACGADDBEAGAABAHGDCDEADECDBCDBCBHCFDDFAGAEGAHGAGAAFBDB,False +361,15.0,32.0,16.0,34.0,25.0,18.0,29.0,23.0,HDFHFFDABBBBEEBGEBGEDEEGAHGBGBBHDAEGCDACHECHBGDBGDBGDGDDFBGGDEBFAHHHHEHHAHDADDEDBEBBHABHAFGDDBEDHEDHDDHGCHCEFDGGDGGBCFCCFEHFGGFHAEDFDFFCAEGABDFEDGBAGBGDBCFBCHEDADDCDCBBBDEBDEBGHCGBEABFCGGEFCEG,False +362,22.0,28.0,20.0,25.0,21.0,16.0,11.0,16.0,BHCHFBFFBDDBHHBAHBADBAHBAHGCCFCBBDBBECAEFEDHHBCCFDCBBBEBHEBFGBHGDHCFFCFAHHAGAGDBFDGFDBCGEADBFBBAAFEDGEDFDAAGBAGAABEDDACBECBEFDAHCCCCGCEEHAEADEDDEDCEACEAEDDEDDE,False +363,11.0,11.0,7.0,6.0,9.0,8.0,12.0,8.0,FBADHHEHFGGCGAFEAFEGFGGHGHCCHCCBCABAEBAHDDCGFABEABFABABDEBDBHAGGFBGEEGDE,False +364,5.0,2.0,8.0,2.0,1.0,2.0,9.0,6.0,AHGACBAGHCGHGBEFDAFGACHCCGCDGCHGHGC,True +365,33.0,17.0,16.0,24.0,25.0,19.0,21.0,11.0,GDDGDDGBDBAABAFECGEDGEDFAGCACCFHCGHCDAADBACFCHEDAEHABGGHCEEEBAEFEDFDCFDHFDAFAGFBCDAFGEDDEHBEDBDCBHCAGFHFDACAGDABEABGABGAHCAGDAFFGEFDEFGFGEEEAEAAEAAEAEFBBAHBABCEGEDGAA,False +366,24.0,28.0,22.0,9.0,23.0,15.0,15.0,17.0,HEGHECCBBCBBFAEDHBFCBFBBFABGEGCFDCHCCBAAHAADABBBBAECHECEEHEEBAECDDAGDFGDFCDCGBCEBCABEABAAEHGCHEFHEDHFGGAGEHGCBBAFBAHCFEEGAEGABAABAHFHBCCCEHAEBBEGCGFFBHFA,False +367,22.0,19.0,28.0,25.0,31.0,21.0,23.0,26.0,HGHDGHDGEBCDDCAEEADEDEEHAHBDCEEBEFGAHAADGDHBHFCEGEDBFDEFEEBEBCEFCEFCBACBADHADEGDAHCCEDDEDHFAHECDDCBEFBEGBDCHCHAABAACCHCCHCDHAGCAGEBEEAFECHBCHGCGGHFCFAGGEDAFDCBECBEHDEFFGFDGFHGFGGFGFFBFHBCCGAGHAHH,False +368,19.0,23.0,22.0,14.0,18.0,18.0,13.0,20.0,GAHHDGFBGDBFFBHGADABEHCCFDCBDAGDBFBBFBBFBFFEFFAHCAFGAHADHEBFBAFBECCEBCDDAEDGEHBBBBACBAEBDECHEGFCHACFDBGCHHCHGEHCCHCGHCGECEAGACHFCHFCHDEEEEEBDACAAHA,False +369,8.0,9.0,10.0,4.0,11.0,7.0,17.0,8.0,GEHGEBGFGGFCGEHAFBBFCBHCFDCGEHAEGCCGAEGBBCHBHFEAFGBCGADGADEADCGCHGEBAEGHEG,False +370,14.0,14.0,22.0,16.0,19.0,13.0,17.0,12.0,AEAAGFACECCFHBFDEGEAGADCEHCECCADHDEGFGGCCGBHGBHGBAFDGECGECGHBDHBABFACDDEBFECFEFFCAFGEGEEGHGCBACBCBDABCGBDFEDEDDHDFBDHCCHCCHEADE,False +371,24.0,19.0,21.0,13.0,20.0,18.0,17.0,23.0,GEGEADCDGEHBDCBDHAHCEFCEFEEFCDFBEGAGFHGFCCHCCFFCFFAADAFCABBBHGCHDHEAAGCAGDABHHCHHCHGBEFAAFHAFHGHHGDADEABEGBCGCDBADEHHEHACDABGECFEFEEABEBBHBBABCAGCFGEFABHAH,False +372,3.0,3.0,3.0,4.0,0.0,2.0,1.0,2.0,DDFDDBCABHABACFGCH,True +373,11.0,27.0,14.0,16.0,27.0,12.0,14.0,25.0,BGEGGBDBADECHGHHEHADHDGAEAHEFHBFHEEDGEDECBHFEHEBHDDCEABEAHEAHEBEEBEGAHCHHCBBBBBBBCCGDFGEBBEFHFDHFDHFDEFDEDEHGEAEEFBBHBBADBCBCCBGFDGHEFABBGHCCCGCHH,False +374,3.0,9.0,10.0,10.0,8.0,7.0,11.0,11.0,GCGGBBHHCCGFDGFDHDDHFDBFEGEEBECDDAECCBBCHGCHGFHADHACBEFHEBHDBHDGGFGEC,False +375,23.0,33.0,18.0,22.0,30.0,18.0,26.0,23.0,EBDEBDHHGCCGCFGADGBCGHCEHFEHDEHBEGDDGBHGAHDAHDBCBAABCFBCHEFDADCAEBBBBHBAFBAEBAHBHFBCAGCFHDADEAFECEECEFBBGGCCGEHHBBHEDCAFAHEEFFEAGABGCDGBBGBDFBDFGDBEDBHFBGDDGAEBAGAFGEEBEECEABEHGGADGDGFHGFEAEHHE,False +376,26.0,12.0,16.0,23.0,9.0,18.0,21.0,30.0,ADDFFDFFDFFHCFCBFAGFBGHEDHEAHECHCABFAEAAGAAGDDDDCFGCAHABDEGFHBCBCADGHDGADGHEGHDGHFBHGDHCDEABHGEHBDADAACHHHHFHAGHEGHDGHDHHCCCAHDHHGGFAAAAFABFHCFGBHGAACBGCDD,False +377,14.0,10.0,11.0,6.0,8.0,8.0,6.0,11.0,FCEFBBABDCHECFBCGBHGFHECGCFAFAEFDBACADCABCHHEAHGAEBAHAAHAAGFDCBDCBDGAEHHEH,False +378,10.0,13.0,11.0,8.0,10.0,9.0,5.0,12.0,ADCHBEECEEADBACBGBBAHBGHCCHGBHCCACCFHCDBDDFFDFFBFEAEHABHDBDAFHECBAHEGHEGHEFBAF,False +379,26.0,14.0,13.0,28.0,14.0,24.0,18.0,23.0,ACEAFGAGABGAGGEHAFHDCDDFFCGHCDHAAAEFFEGABGAHHADFGDFBCAGCAGBACDDDBDDEADCCHGEAGEABHHFHCCBDABHFEEDGHBGBBHFDFCDFBDADDEDDEDHFDHFDHEDHAAFAHDGDBGEFFABAECAHHFFHFFHDFHFG,False +380,21.0,15.0,24.0,10.0,21.0,16.0,24.0,20.0,GBFFDHFBFGEFHHHHHECHEDEEBCAFAABGACGBCAECBCCBEDFCDGCEEEAEGAGGACDAFDCGBBGBBCAFFDFHBAGGDGGCCHEAFEAFCAFCAHCGGAHCACCAEGHEHEEGEEGDCHDHHGCEGAFHHEHACBCFGHBGBAG,False +381,15.0,21.0,27.0,23.0,28.0,27.0,27.0,20.0,BCBHCAFBBGEBDEDHCDGCGGCGDCFECDECEBCEBFEBFGCGGBGABFAEHCFDCHEGEFFFBGFECCEHCGFFGFHGBECCFCFAEDAGAHDAGEFFFAFDACCHCHBBHFCDAGDHGDEGDBDEHDHHFHFBHDBFDEAGCADBDDBDDEEFEEAGEGGBCGEFEEFDGHHCHFEHCAGGABCE,False +382,0.0,4.0,3.0,2.0,1.0,1.0,2.0,3.0,BCDBHDBHFEHGGCBC,True +383,1.0,2.0,2.0,6.0,6.0,2.0,4.0,2.0,CHDAEDGEDCEGEBGEFDEDGHDFB,True +384,12.0,14.0,12.0,10.0,21.0,16.0,19.0,20.0,GDHEBFGHDHCEABECBDCAHGAEGCEBCEHDEAEBHEBHFHHBBFFAFDCGHAGDCBFHGHCADBAHBGHBGADHFCHFDHCHECEECEGFEGEAGEGGEBFEGAEBAFFFEGFGGDGHFEHF,False +385,9.0,9.0,5.0,9.0,10.0,4.0,7.0,7.0,BCCBABGHBGDEGDACDBEFBHDGADGAEHHCFCEFDEBDBBDAAEEAEHADAGEHGFHE,False +386,15.0,9.0,11.0,11.0,15.0,15.0,12.0,13.0,EGCFFCFGCFHFDHCHCCHACHECAGHFFABEAHEFHEDDEBDHBDHBECDEADGFGFBGFAGFAFAHEEEBDCDGEHGAGGABAAGDFDBEABEHECFAA,False +387,17.0,16.0,9.0,11.0,9.0,4.0,15.0,11.0,DADCFEBAEAGCBBHBEGBDABFBDFDHCAFEGGEAGEACHABHAGHDGHBHHBGDEGHCAAGDAHACEGBBGABAACGACGBDGBDHBDCE,False +388,10.0,3.0,8.0,5.0,5.0,8.0,6.0,3.0,BDDGGCAECAFGAFCACADCEGCAHCADCBFFAFFHHFADEGFEGBEA,False +389,17.0,13.0,28.0,32.0,15.0,31.0,24.0,29.0,HGHCCHGBFDBGAAAAEDAFHHDEGFECFHGFCFFEHFDHGDCCFCHFCFDCFDGEHBEHGHHAACAEDAHDACGEGFEBHDHCFHEFHGFAGFACDACBHCDHCDCCDEFDEFDHFECDHDDCGDGBBCCFDHBDFBDFCGBBHAEHCDGGFHGHAGFBDBDCGFCGFDGDDFDHGHAFFAGDCEDCF,False +390,23.0,24.0,19.0,26.0,25.0,15.0,25.0,27.0,FADECFEGAEGHCFDCBGCBDDHDDHDDAGAHHAEBAGDAHBHGBFGBGGFGDCADCBHBEHDEAEHGEHDBHGBHEBDGBHECAEDADDAEHFFHFHGGCCHHEFECCGDEACEHHAHGAFAADBBDCBGABDACCADABFABEHFEBEEBDDACDEEDGGGGBHGBHCFGCFHFBHCBEGEE,False +391,4.0,5.0,5.0,5.0,10.0,9.0,7.0,10.0,FGGFGCEGEEHHDHGDCEDAHBFHFGDFEBHBHHAHFCCFACFGBFEEHEEDEAB,False +392,2.0,1.0,3.0,2.0,5.0,3.0,4.0,3.0,FBGCCGDCAHEFHFDHAGEEGEE,False +393,32.0,34.0,23.0,23.0,23.0,22.0,17.0,26.0,AABCCBCADCAHAAEFAFBABBHCCFBFGDHDHCAHFGBBCCBHCBHBFCDFBHBEABEAGEDGECBEBHEBAEFHEBEBDHAHHBGCCFDDFDFBDHBGAAACEACDACHADFAGFAGFHGFDFADFAHEAEEBEAGDDHCDEFDBHCGGDGDAHABHEBHEBEEBEHFABAHBGEBHCFDGFGFEDADCACHACBGBB,False +394,10.0,5.0,5.0,10.0,12.0,9.0,5.0,11.0,DCDEADHACFADFADABDHGHHDAHGAGEEBEFFCFAEDAGBAEBCEHDBHFFCEFHEHHEGEEDHF,False +395,9.0,8.0,7.0,6.0,6.0,3.0,2.0,9.0,BAGBECDECDCHEAHAFGBFHBAHDHHAACAACHHFHBDDBEEAEDBCCB,False +396,28.0,25.0,16.0,17.0,19.0,17.0,23.0,14.0,FBGFAAAHBHHGFCGDGGBGGEGGEFCEHCDGBBHEACEGBEADCADGEGHDGAAAAABFABFADFCCBHCADEFGEDDBDACAABAAHHHFACFBDAADBAGBGEHDEDBBFBBFBBCEAGEBHEBHEBEFBCFECFEGDGBAGDACDHCFCFGAGAE,False +397,11.0,7.0,11.0,10.0,5.0,9.0,10.0,7.0,BCHBAHFDBFCHFCDDBHGAGCHGCGGCGGFGEAEECDDFADEBFCHDCHBGABGEFDCFDFAAADAACA,False +398,21.0,30.0,21.0,28.0,27.0,13.0,18.0,24.0,CBDCAGAAEHGBHBHHFHHAHHCGHDBDABFBEHDEBCEDFDCFDCFBCEDCBAEBEDBEBBABEDGFBGFEEAEBGHBGCBACBDCEECBDCDDCAAGDGEAGEAFEGEEBEHFDHDGCEBFEBDGDFHAFHFDHECHGCDGHEGDBDBHEBHGBDAAAAEADDDCABHDCHCEHCHGBBA,False +399,8.0,12.0,5.0,5.0,7.0,5.0,5.0,13.0,HHGHBAEGABBCBBCBBCFBCBHADAAFBAEBEBFHDECEEFHGAHGHHDFHDGHAHHED,False +400,7.0,6.0,11.0,5.0,6.0,14.0,10.0,3.0,AEFAEBCFDCFCFAEFCGGCGECHFGADCBDFGCHCCABCAGGEFHEFGAFBFBGFDGFDBF,True +401,5.0,2.0,3.0,1.0,8.0,3.0,7.0,1.0,BAGCFGEEAEBHEGFAGFDGEEGECAEGAC,True +402,7.0,14.0,22.0,10.0,18.0,10.0,12.0,15.0,GHECCAABBCBBEEBEGBDCEECFGGHCHACHAHFBGGCCCCHCEFCFDCHDCHDFHECHACDBCBAEBDEBDGGEGHDCEGHECEECEEHBEHDFBFBAFHDFGFCG,False +403,14.0,14.0,19.0,22.0,20.0,22.0,14.0,19.0,ECCEDFDGEDEEBCBHDAFBAFAAECCFDCEBBEBDAHCADCFDHEBFEDFEFEGFEAFHAFHGCHEEHDDFEDFDCFDCFCBAHFAHFHHFBDFDDEHCGGBGHBAHCAGCEGAHBHCGCEDEFDFGDHGFCGBBGCHGHDDA,False +404,9.0,11.0,17.0,12.0,11.0,7.0,12.0,10.0,BCBDCEGCECEGCDCCDGGAHGEBGBHCFCAFHAFHADEAHFDHEBCCDCCDCBDHEDHADBAHCHDDGBEGFGGBECFEFEGBAGCAB,False +405,5.0,5.0,3.0,4.0,12.0,4.0,3.0,6.0,DBGAEGEEDAEHAEBBEBEEHFDCBEFGEFCAFCEHHAHEDH,False +406,15.0,17.0,23.0,27.0,15.0,22.0,16.0,20.0,EFCEGEFDBFHCCACBDDHDCFBHFHGFCECAEABGBGDHCDBCABGADFDDFECCACFAEFHDGHDBHDAHDHHDHBFEFDEADFADBDCHDEHFCHFGGFHGHHEAACAFCFBDDCEBCGBDGDEGDBGDHFCCFDEHCBBCBGDFGAFEAGC,False +407,11.0,16.0,12.0,20.0,16.0,15.0,13.0,15.0,HBGBDGBDGFGEFCCHCDHCDHFFCDBCFBEEECEFCEABEHDEDBEFHFDAFDBHBBHDACAHFAFBAEBDDDADDAFDGGGEEGHEGDFHBFHGDBGCBGBACDAHHCEAEEDHGF,False +408,16.0,12.0,20.0,13.0,15.0,13.0,22.0,14.0,HACHAGEAGFHHDDCEDCBFEDFEACBBFHBFHBCGBCACCBDDGDDBEFEGGHDBDDGGFHGAHFEGAEACDACGABAAHEABECECCECGGCAHFAHFGGFEECEHAFDGGGGCFHCGGCGBC,False +409,4.0,7.0,9.0,5.0,9.0,7.0,4.0,6.0,EFCBHCFAFFACFDHHBHCBGBBGBCEHGECBAGDCEFCDFCDEEHEEAED,False +410,12.0,11.0,9.0,6.0,6.0,6.0,2.0,5.0,DDCDHBBABBACFACEBDEHDHBFBAFBAGCAEAEEFHCBCCFHCAAEAABDABGFC,False +411,10.0,13.0,4.0,12.0,8.0,3.0,7.0,11.0,BBHBBDDDDDEEAAHAAHBAHGEHGHHAEDEEDACDBBDGCDBBABHHCGCFGFEGBAGBFDDAEHBH,True +412,2.0,7.0,4.0,0.0,2.0,6.0,5.0,2.0,BGBFGBFGBCGCEACFBHFEABHCBGFF,True +413,28.0,23.0,16.0,19.0,25.0,12.0,17.0,19.0,BHADEAEEHEEAGEFBBCDDAGHHGHAEBDFBAFBAHAEHBECBDCGDGBFGEEAEEDBDDBHDEHGECAACGACABCABFABCADEAHEDBCGFEBFEADEBEGADAAFAFHADBACHABHCCDCDBFABGAEGCGFHACDEGHHGHGDHFBHEBEGC,False +414,4.0,13.0,10.0,10.0,10.0,2.0,11.0,8.0,EEGCECCGBBGBCGDEEAGEDBHCHHADHDBHEHCFBDBGDBDDBDEADEHBCAGCBGEGCBGCBGFH,False +415,13.0,21.0,20.0,13.0,22.0,19.0,15.0,24.0,HFDBGDBHHBCCFHHFBHFBHFBHACEFEHFCBGBBFBHFDGECGFCAABGCFGCHHBHHEGFEABCBECEECGDCHHFEDAHBAEEDECDHDGHFGHFAECAFBAGBDECDCHBHHDCEFCAFEHEEGEAGEAFEDEBACBDCBGG,False +416,21.0,17.0,11.0,9.0,12.0,14.0,19.0,7.0,CGHHGBDBAGBAGBDGACGAHFFBFAGCACDAGAAEAEFCCAEFBCFGCAACGEFFBDAEDABDCEGEFCEBBHFBHEBHEAGGBGFAHFEBFBBDABFAGGAGGDGADE,False +417,6.0,8.0,8.0,1.0,1.0,6.0,7.0,5.0,BADAECHCCHCCHAAFCGFBGBBHBBGFCFHCGGBGGBFFAA,True +418,11.0,22.0,19.0,15.0,20.0,16.0,14.0,28.0,CCEHHDBHECHCGAGDCCABHFHHEHDEGBEGBDDBDEBHBBGFFCFFHBDHBCHBEHBAHFFGFCDHHDCHBEABHDBHCBAAEFDCBCCDFHEFGBDABGFBCADEFDGFAGEHGBHCBCGFAAHEEHEFHEGEEHEEHCGHC,False +419,25.0,19.0,13.0,15.0,18.0,30.0,15.0,15.0,FHCDCFBEHCABEAFAFHEFDGFDCDEHAFGAFBDBBFBBGBAHFAGFBFFBDBDDEGFBDEBHCBFCEFCEFAECAEFECGADBABAEHFDGFGGBGFBGDAAAHAAHDFHGCHFCAFEAEEDECDHBFAGHAGFEEFAFFAFAHCAHG,False +420,5.0,4.0,3.0,9.0,10.0,5.0,4.0,4.0,DEBDADFEFCEHEABEAEEFEDHGDHEDCFGCFDDGBDGBEAAH,False +421,21.0,22.0,19.0,21.0,16.0,23.0,24.0,24.0,BGGDDGBHHHHGHHDAGFAGFBBFGGFGEHBAHECFACAGHEFCEADEAEBAHBGBBACDACDHCDHCHBCDBDDGCFHHFHHAHEEHCGCBGAADFBGEGFCCFCGFDHHDHCBFDAADABBCBFCFGDECBEFDEGDEDFABFADFGBFGFAGFADHHEGABCFBGEE,False +422,5.0,3.0,3.0,1.0,0.0,2.0,1.0,4.0,ABCABCBGAHHHFHAFCAD,True +423,8.0,5.0,10.0,3.0,2.0,6.0,4.0,7.0,CAHCAGAAEDGFCGDCFHCAHCAHBBDFAFFGBFBBCCCHCEHAH,True +424,4.0,2.0,3.0,3.0,3.0,5.0,4.0,1.0,GDFGCGACDACDEBFEGHEFFAAFB,False +425,20.0,29.0,28.0,22.0,37.0,21.0,18.0,23.0,DCDEFDAGCHCHFDAFEFFEHDEDBEABEHBEBFCBEDBCDCCEGCEBCEAHDHHDAHGAHBBBFABFABACBADHEEHEEAEAAEACDCHBCEDEEBEGGEBEFDGCBBBAFDAFCAFCHEDBEDGECHBHGFGECEDGDFECFDCFGHECEEHFEBCABCADEAFEGBBHBFGBEHCCHBCGBEFCHHCHGGGGDF,False +426,3.0,6.0,6.0,5.0,11.0,8.0,8.0,8.0,ECEBAECEDDEBDGBGHDGEBGECGFHGFHACHFGHFCFBEFHHBHEADEFGCFE,False +427,9.0,21.0,17.0,17.0,18.0,17.0,9.0,12.0,BHBBHBBAFBCCHEBDECFECDEFFGHCEFCAFAEHDGHDBHABEEBEEDAECBDCECABDAFDHDGEDBBDBFAFFCCBHCDHDBFDGFGBFCHACDBCGGDGGCBFFBFEEFHECEED,False +428,13.0,9.0,6.0,7.0,7.0,9.0,7.0,6.0,HDAAECHEGFFGFGCFHCBGAADAADAAFABFBEEAFFBBCBBEABECGHDGEDGDABDAFHCH,False +429,8.0,15.0,19.0,18.0,20.0,20.0,16.0,22.0,FGDFDDFHDGAFGFHEBABCDBHFGHFCHACACCECEACEBCFGDBHFEHFBHGHHEHEBGEAFFHCFDEFDADDBDGHFBDFBCFBGAHFBECHECBECHECECCEDCHGEEGEGFDFEDBEHBHCDGDHCHHGGDG,False +430,13.0,25.0,20.0,21.0,26.0,17.0,24.0,16.0,EFFGFCDFCEHCGHDGEECAEBBEGBECFEGHAADDAFCAFCBCEECFFCFCAGDACHBHHBGDCGDGGDEEDBHHGCHEDBEGEECEEBEBBDBAEEFDGBGGBDAEDHEFCGBCGFCGAHGFHDBGGBFBFFHEHBCDBADCEDEBBGAAGHBGHBDBDD,False +431,13.0,21.0,18.0,12.0,10.0,10.0,17.0,15.0,GAFBBBBFHGFAFBGCGGBBCABCAGDHGDHBCHBHBAHGGHEGHDCDBCFBCGECAEDDHBAEBDHBDHBDACECGEGGDHADBEFCDBGACEAHBCFBEHAEHAFGCCGCCFFC,False +432,14.0,11.0,9.0,15.0,14.0,12.0,12.0,18.0,DFAFFAHDHEDFEHHEDHCFHCECBABBDGEFGEDCDCGDHHFCHFCGGCEGABGDBEABAAHAEBDEBHEGHFGHDHEBADGADBAEHCEHDDHBFAGAAFFGH,False +433,16.0,16.0,12.0,20.0,13.0,18.0,9.0,14.0,FDCFDADDBDDAHDCBDCDDCDAEHAFAABADBECFAFBCFADAGCAGCDBAFCFFEHFHBFBEHGCGGDFGDABDEECGGDFEFBHCBHBEHBEABEHBAHGAEFBEHHHFEHFDFD,False +434,15.0,21.0,15.0,6.0,12.0,5.0,12.0,17.0,CBBDBGABGCDGCEADBCCADEFCCAHCHCDHCAHCHHABHBBHABEFCGCBGAFAAHEAFGAEGAHGEEGHEGBFBEECHEBBAHHCHDBHBBHBBABBGEG,False +435,0.0,0.0,3.0,2.0,2.0,2.0,2.0,3.0,CHDCEDEHCGHFGF,True +436,22.0,21.0,21.0,13.0,7.0,14.0,20.0,13.0,BHBGDAADEDFGCFGDHGAGGAFDCCACCHEADBCFBCGBFABEHDCHCEGBGDAGAADCAHGHHGHFFDEHAGAGGABCAFAFFACHACGBDGBDCBDHAGCFEBFACHBCABCGFCAFGBEBBCBBCBB,False +437,18.0,12.0,15.0,15.0,9.0,15.0,19.0,9.0,BEAEFBCFAADCBFGDGGHFCADAADGADHCBHDGDBGDBGDCGAHEFHGFAEBAHBADGCDGCGFCHFDEFEHFCAAAFBAHAEGDEGFEDCCBCGBFGBFGACGCCADFG,False +438,9.0,15.0,11.0,10.0,6.0,5.0,12.0,8.0,CBBCECABBAHBHBCHGGEGGDAEBEDCDFADBGDBGDBGBBCDGABHCFGBFGHFGHFEAAEAABHDDCGCCDCH,False +439,21.0,34.0,13.0,20.0,9.0,14.0,18.0,22.0,DBGDFCCFEAGHBHHCHHCBHBGHBDABCCBAFBAGBDCBDBBGBAFFDHEHGCBACBAEFGHBGAFGCFBAGHAHHAGHGCDEAHABHBDFEDBDDADDHFBHFBEABEABADBHFHDBABBHBAEBGCDCFHGGGBBGFDGDABDABDE,False +440,5.0,7.0,4.0,9.0,2.0,7.0,1.0,7.0,DEBHHHHHHDFAAFGADHABBFFDFFDBEDCCCCFBDDBDAB,True +441,9.0,3.0,11.0,9.0,5.0,3.0,13.0,6.0,GCHGCHBCDDAEAHEAGAGGCGEAEHACDFBDBDGCDGDGGHGCFGCAHCACDGCAEFD,True +442,26.0,15.0,9.0,16.0,20.0,21.0,20.0,20.0,EEHEFAFDDHDDBDEEFFEDFCHFAAGHAEHADBAGHAGBADAAEABCGBCBBFGCFGEFGEFGHDEAEEAFHFGHDGFAGACGCHBCHEAHGABGBGADGFFGEEBCFDHAEBAGBADAABBHFHHCEEFFEDFHAHHAHADDGFG,False +443,5.0,11.0,13.0,10.0,14.0,14.0,10.0,14.0,FCEHCEHCEDGDBBDGEDHEABEFGAFGAFCCFHFFHFBAEEGDFFAHECHGCHDCHBGFEHFHFFBBCBBEHCHHBECDEDBEDCGGGDC,False +444,9.0,3.0,12.0,6.0,9.0,11.0,10.0,6.0,GACGCGACGBHABFCEFCEFCAFGFEGDCFBCHHHHGAAAEADCDGAGEEEEECFFCDFGDFCDFH,False +445,9.0,10.0,13.0,13.0,17.0,11.0,15.0,15.0,DGCDBCDFEFHEHHEDDEGCCFCFFCGDEECEFHHFAHFAEDGGBBGHHGCHGBACAAHEEHEEDGGDGGDGEEFEBGHBCDCAACAHDHBFEFCEDBHBBAG,False +446,4.0,1.0,6.0,9.0,11.0,4.0,5.0,7.0,GACEFGGACGDFDECDEHDEHDEHEEDAHDCDFCDBEHAGFCHEEHE,True +447,26.0,19.0,18.0,11.0,16.0,16.0,12.0,21.0,EEHFFHCBABHABHAEHAEHEFFGFAGHBHAEEAEEAGAAGCCGABDACECFHGHHEDHCBHCBHCBAGDABDCHAHEFHFHHDDFBFFAFCACABEDFEDAGDBFCBDAGFACEACAGHABBFBBEBACCCGHCDBAG,False +448,6.0,5.0,7.0,6.0,1.0,1.0,3.0,5.0,HADHAHCACGDGBDGBAECACBABDCHDBHDCCF,True +449,11.0,2.0,6.0,6.0,9.0,16.0,8.0,5.0,AGAAHAAGFDFEEFBEDGEGEEFEAFCCDEDFFGFFGFFCFAEFAFHDFCBHADHFGHACCAG,True +450,11.0,4.0,8.0,12.0,7.0,9.0,7.0,8.0,FDEFCADCGCEBAHBGECHEFHCDACDABHGBFFDFAEFAEADGADFEDHCAHGDHDFCDAGDAGH,False +451,31.0,20.0,20.0,33.0,22.0,23.0,32.0,17.0,BCCAGAAGFAGCEGDBGDACDHDHGFBGBBDBFGBHBAHECEECDEDHHDFADFEDCEGHAFBCCBFADGCBADDFEFGEHGEFGDHECAEAGEDDEBDEADAADBCBGEDHDDFCEAAHBGBGFAGFDGFDEFEGHBAHFAGFDGDDFDFABCABCAFCAFCAGCAHEGHGDAADAGEFGHDGCDGBGHCFAGDEGA,False +452,6.0,6.0,6.0,10.0,8.0,9.0,9.0,6.0,AFEABEBDGBAFEDHGFHGEDGEHCHAGHECHCCFDADDFEDFEBAGCFGFFGCBGDBDD,False +453,13.0,18.0,14.0,23.0,17.0,19.0,19.0,12.0,DCGDCDDCADEBFFBFFCAACDACDCCABCDDFDFAAEGFHFADCBGCDGEDAFGGEHHEFBFFBFFBGFCDFCGAGDDHDDHFEHGEBGHDGHAEHBGBDEFCBDDEABHAGEBEEBHEDEGBHGBFGBGEEGB,False +454,18.0,22.0,18.0,14.0,25.0,31.0,12.0,21.0,FHADBACFDHAHHDGHBFFFCFGCBGDHFFFGFFGFGGFAHCHEEHFHDFHFFHFAHAHEACEGEEBDEDFAFFBFFBFBEFDCBBEAEHDFDEEEBBGCBFCFCBGBBFEHGCDEHDECDECBADEAEEACEACECCABBECBECBFAFAGHEHHABHAB,False +455,8.0,7.0,7.0,9.0,13.0,7.0,12.0,7.0,AGEBFEADAAGFABFHDEAFFCGFDEHGABGCBHCBGBDHBDFDEGCEGCEDCEHEDHGDAGEHEEGCEG,False +456,26.0,25.0,17.0,12.0,23.0,17.0,8.0,10.0,BCAFCEBDBGCAAFAAFGCBEAEDDBADBADCHEFFEADEAEEFEEGAEGEHBEGAFHAFHDFBBAEACCAECBBBBBFABEABDBBDABDCEDFECACHFHAFHGHDCCAGFEEACEABFABFBEFAEBBGHBCHCC,False +457,17.0,13.0,15.0,8.0,13.0,12.0,8.0,11.0,HFCEBGABGABDAECBBCBBEBEEBFEAADACFHFEHFBACAACDAFHHFAHGAHAAEAHGHCGFCDFDAEEBDECCHCCFFGBEGCDFCBCAEDHG,False +458,4.0,0.0,3.0,1.0,6.0,6.0,4.0,0.0,FEEFEFFGCFAEAGCAGEADEFGC,True +459,21.0,25.0,18.0,16.0,17.0,17.0,23.0,17.0,HDAGCGGBBGBCEDCBBBEGFEGFEGFAFFCGFCBECBFFBEBBGBFABCAFAHEHEDHGDCCEAAGAAGBCGHCBHCAEDHHDFFDABEFECCABHABEDBEGBEGDGDFGAFEAGCDGCBHHDHCAHGABFDEADBADBHGAGAHFHGCHDB,False +460,10.0,14.0,5.0,9.0,15.0,9.0,9.0,8.0,EDEEGEAGEGBEDBDFGDEABFAFDAGEBBABDAGDBGFFHAEHDEABGBHABEACEFBDFBCHGCEBCEBEHHHFHCF,False +461,5.0,3.0,5.0,6.0,2.0,12.0,7.0,4.0,CEAFFGFFGFFDFHDFBDADACCGGCABAHGFBFFDGHDGHEFC,True +462,6.0,6.0,14.0,9.0,5.0,9.0,18.0,19.0,FGCDHCHHGHDGADGECGHCGCGHCEDGEFFHHFHFGBAHEFGBCGHFDHFHHCGHCGHEGBCCBDAHDHGBHACGCGFCDABDAG,True +463,3.0,5.0,4.0,8.0,5.0,3.0,5.0,5.0,DGAFBBFAHGEGGEGBECECCAHHDDDEDDHFDHBDCB,False +464,8.0,5.0,4.0,6.0,7.0,4.0,8.0,3.0,DACBACHAGHBEHDEFEADGGCFEDGEBGEAGBAGFDGFDAAEBC,False +465,13.0,13.0,10.0,12.0,11.0,18.0,10.0,10.0,DFBGFDFFDGBBBEDGEDBECEEDFHAAACAAHHHHHBGGAAAFHACDACEFFHFFHAGCBEFBEBAFGAHGDEGFFBFDBFDECCECCGBCDBFDF,False +466,1.0,7.0,5.0,6.0,4.0,4.0,5.0,8.0,DHBECBCDBGDBHDBHFHECAECFFGHDGBBGHCGHDHFE,False +467,8.0,10.0,7.0,7.0,13.0,10.0,14.0,7.0,GGBEGHAGEGBEDBCAFFBHEEAEFBEGCFGCFHBFEGFEBFHFCHFDGDDGHDGDCHAEGCEGAEDCEBAABABG,False +468,7.0,9.0,14.0,4.0,4.0,10.0,8.0,4.0,FECAECBDFBGFCCFECFDCBGCBGBFDAHGAFGBBEBCHBCAAHGAGCCCFHCFGCDAF,True +469,11.0,8.0,10.0,17.0,9.0,15.0,9.0,16.0,FHDFDDEACFHCFCAHDEHAGHACHDGBAGBEGBAGEHHDGHFEHADHAEFAGGCFECFBCDGDHHDADBCDBEDFFDFFCCBEDHFHAFHDFDB,False +470,1.0,3.0,1.0,1.0,2.0,1.0,2.0,3.0,CHADBEEBGHBGHF,True +471,17.0,15.0,26.0,18.0,19.0,21.0,23.0,27.0,GFFCCCHCDHAGAEGFGCBGCBFCFFHDFBDCHDGHFEAFEAEEAEGDHGHCGABGDCGDGGFFFACHBEAEEDEAHFAHDHHGCHFHHGGHBBECGECEEDAHCACCBBCFBCHGCHACFDCEDAHCAHFFFDABEEBCBAHFCHBHBGDGECGEHDHGDHGDFD,False +472,2.0,5.0,3.0,5.0,4.0,6.0,6.0,2.0,EGHFGBFEBFEDFHGCCFEABDADDBDGBGCFG,False +473,20.0,30.0,26.0,33.0,27.0,26.0,18.0,15.0,CGAHFAGFAFDBCDEGDEHBEGBEBFDGFECFHBFHBEEFEECCEFEFFHCDGAHABDFBAGBADBADBDGFGCDCABGAEGDDDDACFACEAFEBEGDCGCEFDEBEEDFEFFDABDHBDEBCHBHHFDDBCDFGDAGHBDABFBDDDFFBBACBCCBCABCACCHGCBFBDDEEBCGDCGDCEDCHFEHEAHE,False +474,19.0,17.0,14.0,18.0,11.0,17.0,20.0,12.0,GAGCCFFCGFEDEBFFAFCGDHGEHGEHGHGFDFAAFDADDADCACCBFBDGBGGBFEBCABDAGHGBDBBHFGEAGCDGFDCFCHFAGCBBABBABAEBCFCDEDHGHAEHAEDAEDGFDGDAHHAB,False +475,29.0,21.0,29.0,16.0,8.0,11.0,32.0,19.0,GGHBGAGFAHFBGAHFBHGBHGCEACHGBAAAFHHFHHCBGCGAHBDCCDGAAGHHDBDCBDFBDBEACAFCEDCBGABGAFEACGACGCCGBCGHAGADEAHGDCGCBBAFBADCGBEGBEGBAGCGGAGABCCHCDACGHDGEAHAADFCCHACDGCDGCDFC,True +476,1.0,0.0,5.0,0.0,0.0,3.0,1.0,0.0,CCCGCCFFAF,True +477,12.0,12.0,12.0,10.0,3.0,21.0,15.0,7.0,FDFAGACBDCBGCEFEFDGAGGBBDBBAFCADCADCFCGFCFFHFFHBFCCDAGAAGBFDCFCAFHDBBGHDGHFGBFBEFGFFAHGAGGFH,False +478,17.0,16.0,18.0,22.0,16.0,25.0,17.0,21.0,ACEFGEHAECACCHBGAFFBCFECADCEFAEDEFAECBCGBCHFGHGEBAEAADHGDGAFGDDCEHCHAEHDEFGHHHBHABFABFHCFHCFHCFBDFBHBEFFEDFCDBGDAFDGBHFBHAEDCFHBDDGADGDFCDFGDGBDGDFHDFHG,False +479,10.0,7.0,13.0,9.0,7.0,6.0,9.0,3.0,HGCDGCAGAEGAGCCBCCFCEFEAFEACGGCHDABDECHFABFEBEBADBDDBAACGCFDCDDG,False +480,1.0,0.0,4.0,0.0,2.0,0.0,5.0,0.0,GCEGEGGCCGCA,True +481,21.0,16.0,14.0,17.0,11.0,10.0,25.0,16.0,FDGEEGBBDHAHGDHBHGBGCBCCFACEAEGAHHDHBGFDGADAAEAAFHCFHDFABGCBGAGGADCHDCECEDBDACDAHDAGDBHHBAGFAEFGBFGBGHAGAAEDCBCEBHEGHDDBGGGGCAGCFG,False +482,12.0,17.0,21.0,17.0,21.0,22.0,20.0,24.0,HCBHEEHCEHCBHADGBCGBEEHHFGHFDHFCHCGHGGHBGCBCHGDDACDFFFFFGBACFECGCFHFAEDHDDBDDHDEGDECAGCAGHAEHAHFEFDEACCDGGGFGCEBCEDHFCHBHBEHDDABHFFFAFFBFEBEBBGAEGCEGCEBFE,False +483,19.0,21.0,17.0,13.0,22.0,21.0,20.0,24.0,GDGGEGFHAHAEHADHCEHDAACCBEFBEAAFFAFGHHBHDBFDFFACBGDDGDHHBACBFDHFDBFEFFGABDACDFFHGFCCAEBBHGBHBBEBGCDGCHGCHEFHEAHEHHGACCACGAHHEBGECGACFEEEBEFBCFEEGEHGEAGBFHBEB,False +484,14.0,17.0,19.0,19.0,23.0,9.0,30.0,14.0,DBADEECEEGGGCGGCHGAEDCGDCDDHDGGDEBHBBCAHHADGGGEGCECCACHAGHAEDABCHGGHAGDADBEFHHFBCEAGAGGDGGHGGACFFBFGCFGBBDBECBEDBGFEHDEBDEFHEBCEBAEGEECEGBGFCDECD,False +485,23.0,20.0,17.0,18.0,15.0,7.0,16.0,20.0,ADAADBBFAFFAFAAGCDHCHABGABCAGHBGHCAHEECBECGDHHAHDEFBGDGDBGDBAAEABGHBDCECCBGGHCEHBFABFABCACAECBCDDCBEEADEADHHDHDDGEHGEHGEDCBDCHAAGGBHHBHE,False +486,19.0,15.0,16.0,14.0,11.0,13.0,25.0,19.0,GDCGHFGHCBDBAAAAAACAGHBGADDCCHEGBCBDAFDBGDBDEAAGAHBAHADCDDEHHFHEAGCGGCGGBGHCGCBGCBDCGGGFEGBEDFHCFEBFEAFGAEGCFGCFGDEGAHFEHABFFBHHHHHH,False +487,17.0,28.0,19.0,19.0,12.0,13.0,19.0,22.0,DBDEFAHAGFBGHEGHDDBBEBHEBHDCHFEHGEHGBBACBAGAAGEBBHBDFBDFBDCCHCCAEBGDGDCEBCACFAEGAHDFCCBHCEHDEGCBGABGBDFHCFDDFDBFGAGGFHBCHCABDABHAHCAGCHGBBBCBHFDHADHG,False +488,11.0,5.0,10.0,9.0,17.0,10.0,8.0,12.0,HFEBAGAEFADDEHDEHAEHDEHAEDEEDGBCHCFECFBCHGCHGEDBEABGAHFAHFHEEGFHACECCADEDCEFCAFGFG,False +489,15.0,27.0,19.0,19.0,24.0,16.0,18.0,23.0,GDHCDCEEBEBBHABHFBGFEGDDHDFACCAGGADEBDEHABHAFHGBHAFCAFCBFCFHCHDEHDBBFABDEGCECHDDDDGEAGHAFHFEBBEAHCAHFGHABEFEHDHHDCGBEHBEBCCBGDGEBGEBEECEGBECBEBDEBFGHABHFFDGCCGBC,False +490,3.0,2.0,6.0,3.0,7.0,0.0,1.0,4.0,CBCEHEADEACEADEDBCGHHECHEC,True +491,14.0,16.0,16.0,14.0,17.0,13.0,22.0,10.0,FADFCGFCEFCEBCGBCBBCBBAFBGGBGBEEEFDBBDHEEHGHAGHAGDDGBEAAGDFCHADHGDHGHFBDEDDEFECCEGGGGGADGCBEEHDCGCCGABHDBFAFEEECCAGAFGAFCA,False +492,26.0,18.0,20.0,24.0,26.0,19.0,29.0,28.0,DCADFADCEHGDGGFGEAHEHHAHFCCCGHBAHEAECBBGGBHGBHDBAAFECHEBHGFHCAHDAHDAHACHCGHCAAEGGGDBGDGGDEGHHDCGEEGEDAEDCGFCDFEFFADHGBCABHDBEGBGBHCHFGDFEFFEBBEDBEAAEFEBFGBAHAAHECDGDDFDACCAFAEHGEDGEDCEHFGHFA,False +493,1.0,0.0,2.0,1.0,4.0,2.0,0.0,0.0,ECEECEAFFD,True +494,11.0,16.0,14.0,24.0,25.0,15.0,20.0,16.0,HFCEDHDDCEGCFADBEDCEDAFBACGFFGHDDDGBDFEAFCAFHDFHEFBAFBDEBEHCEDBHDGHDFAEFCECCBGGBFDBCDHAHBGEBEEHGGHABDGDGGDHADGAEEBFECEECGEGGEBEEBHGCHGDHGDEDE,False +495,15.0,21.0,13.0,15.0,18.0,25.0,20.0,12.0,GFGGDGBFFFDCCDGCDECAEFFFHCECCEDEEAEEBEFHDHBGGBGGEGHAGEAGBGEAFAHFACFCHGBBGBBCCDEGDFFFFABBBEBDAGDAHFACFAFDABDBBEFDEFAFBBFBBFEHHGHDDHBFGAFHEGC,False +496,14.0,17.0,8.0,12.0,24.0,10.0,23.0,11.0,GBFGBDGAFGBGEBFEHDGAFEBCGGGBABDAEDGEFBAFHEFHBFHEEBGEBAEGGEFGEABAHBGHBCFGEGCAGCEHEGHDDEBAGCAGBECDECDEGDEGDBDHEEHAEHDCAAE,False +497,8.0,11.0,13.0,8.0,7.0,15.0,9.0,16.0,EHBHFAFCAGEGGCCGCAGBAGHDFFCFHBHHDDHFCAECHDBHCBHAFFDFEHCGDFGAFCAFCGFEBBCBBCFHDHEDHFBHEBH,False +498,3.0,6.0,8.0,3.0,3.0,7.0,4.0,5.0,CHECBEABACCGCBGFHFFBGDBFDAFDEFCGBCHFHHC,False +499,7.0,4.0,9.0,5.0,5.0,8.0,3.0,3.0,ECEEFHFFACFAHAABEABDCCGFDGFCCFCCFGDABDCDEBAH,False +500,7.0,8.0,5.0,8.0,4.0,3.0,2.0,4.0,CAEFHGBDDBDDBDDBCGBCFDFDHCAEAEHBEABAAHACB,True +501,22.0,26.0,22.0,26.0,16.0,25.0,21.0,27.0,EBHCGHBFHBFBAEEAHFAHEADFGDFBFHCHCCHGAAAAAHAGBBBDBCHCEHBHHGDDFBEFDECDBFFHFFDDDDDFDAACHBDABDHGCEGCGHFGAFDCFGCFGBBGFACDAGHFGHEEAEEAHHBDDAABBCBCDDCDCGHFGHEBHABGFCGCEGCBCHBCHDGFFBFGEFDEHDBAD,False +502,10.0,11.0,12.0,13.0,8.0,15.0,13.0,13.0,GFHHEHDCHDEFDADGCDGBDFADFHFACFACACBFCGFCAFEECBECBACAFDEHBGGAAFDGHCBDCBHGBHDFHDHGEFGFHGFHDBEBGGB,False +503,5.0,6.0,10.0,4.0,4.0,8.0,9.0,0.0,FEDCEDCGBGGBCFCFEDBEGAACABCGCCGFFGFFDAGGBCABCF,True +504,7.0,14.0,10.0,11.0,12.0,9.0,6.0,15.0,BDBBGBFCEDCHDCHEFFECHGDEEHEDHDBCDHGABFABFBBDBBCEECHEGFAHCGFBHFAHFAHDCEAHBDCBDHGEHAEH,False +505,21.0,9.0,16.0,11.0,15.0,16.0,15.0,15.0,DFAGEAGEAFCCECCECFEGFHGDHAFBCHEDHEHBEAGFCHDHGAHFFCAAGAAGAAGAFEDGCDFHGEHFEDFBDCAHGAHBABEABGABEDFFHGFCEACHADEBCCBGFDCCHA,False +506,17.0,15.0,12.0,11.0,15.0,5.0,18.0,14.0,BHGDHFBGBBABHAEGAEDAEAEDBEDGCGHADCFEHAGHAHHAFADCBBGEGGBDBBDEHHHGGBGADGACHCEGCEHAABFAEHAECAECEECFBCGDCGBCGDG,False +507,23.0,16.0,18.0,17.0,15.0,30.0,19.0,16.0,CAHCHFAHFDGFDGEHAABDAFCAFBAGBHGHCDBAAFGFFGADAHDGDGGFEDFEDCCCCDHGFFGFFCHFAFEAFEFHGBEFEEFEECDBGGHHGHCEHEGCADCEBAFBFDBGBCHBFFBFFBCDBDGAGFABEAEAAFFCBFCADCADHA,False +508,2.0,2.0,6.0,5.0,8.0,2.0,3.0,4.0,AECAHCEDEEGEDCFFCBECDDGGDHECHEBH,True +509,10.0,15.0,13.0,10.0,20.0,25.0,8.0,14.0,BFFFFGHDGHBEECGECGEHFEFAGBHGBEDEGAEAHHFFHCFCFFHEFADFBCEHCEGFAHFHEFECBDCBDABDCBFCBDHBEFCEFCHFEBEBFEAFACFHFBAFEADDDBE,False +510,9.0,6.0,15.0,8.0,8.0,15.0,8.0,4.0,CGFCHFDFCDFADGADECCCFCAFBFFCCFEGFDGFCGCCEBBEAEEAEFGHDGDFCHFEFAGDABBCBCAHA,False +511,1.0,1.0,2.0,5.0,3.0,1.0,4.0,3.0,GDDGCBGCHDEEDHEDFAGH,True +512,16.0,13.0,8.0,20.0,20.0,20.0,19.0,18.0,GEEGAEDHBDFBGBGGHGEEDHEHEGFEGBEGFHGEDBBAHGFDAFDAEDGFFHFFHEEHDEHDGDGADCADFADABFHDFCEFCHFDGAGABHAFHGHCBFCHEHBEAAEAAEBCEDFGABDCHFCBFDFDDG,False +513,2.0,0.0,0.0,0.0,3.0,1.0,1.0,4.0,HHEHHEAGAFE,True +514,16.0,32.0,27.0,32.0,20.0,18.0,31.0,18.0,FFCEHGEAGHCGDDGHDFEDFDDBDCHDAABHAGDEGDEGEFCBDAEABBAGBCGHEEDCCBCCAECAGBDFBCHGHHDHADGGGCCFFAGBGFDGACBHCBDAEDBEDAGDHCDGCEGFGCEGDADDCHBGHBAHBEGBEFBFGBHDHGEBBDBBFCCCDEBDFBDBBGFBGFBGFBGFHDBCCCEBCGDCED,False +515,26.0,15.0,26.0,29.0,17.0,18.0,23.0,22.0,GFHDAEAAEGAEGCEDCDDCAHCABBAEBECGEBHHGAADFECFBCFECEDGDDCDCGDBDFGCGHDAHFADDAHCADDGDFGDEAAGAFDHGCHDCBDCGCBGCBFABGAHHBHDFHDFDDGDCFFAHBEHECCFCBACHACEGCEHHBHFGHCGDAGDAGECBFHAAGFFDEAH,False +516,12.0,12.0,20.0,17.0,22.0,17.0,13.0,11.0,EEBEADDAFDADAHHEEBGEBFFBEBCCDFCEFCEFCEFCABEFHEFCEFGFCGCGHCHDCGFBECACAGDAHDGGDHFDHADEADBFHBFABDHECFDCHCEGGDCDDCGBEAFEBECGECGE,False +517,17.0,18.0,11.0,13.0,13.0,9.0,14.0,20.0,BEFHACHEDBAAHAHHAGBAGCGGHAADEHDEHBBHGEHAEHGEDGEBCEBCHAAHBCHADHCDBGFBGHAABBFFFCCFACBGDBGDBFDCFDCBEHFHHEGBADEDHEGGABD,False +518,20.0,13.0,17.0,15.0,17.0,19.0,27.0,13.0,CFECBCGACDECDHCHAGGAGGAGGAGEAGHBGFFGHHDEHDHDDGAAGDDGDHBEFDAGBABEECEAABAAFAGFGDFCDCEFGECBCGGEGHEGHBGEFHFFDCCAFGAFEAEEFCFACFGBDCBCAHGBEGFDFHBFB,False +519,4.0,10.0,8.0,8.0,7.0,6.0,3.0,5.0,EABADFAHCBFGDFCDCCBACBEFDGBHGBHFEHFECEDHBCCBEDBEDBD,False +520,21.0,21.0,12.0,9.0,4.0,4.0,12.0,8.0,FAACBBBAABGAFADBABBDBBABHACGACBABBHHCECAACAHGDHGABCBDABAGBDGDAEDGCDGCABFEHEAHFBHGADGCCGBCGB,True +521,7.0,6.0,5.0,6.0,9.0,6.0,4.0,9.0,HDFFDAFDAFBFEAGABCHCHHBFHBGEBHEHHEHEDAECEEGACDECDBGA,False +522,7.0,13.0,6.0,12.0,9.0,15.0,17.0,9.0,FEHCDBCDGGDGGDHFBHAEFDEFDFGEAABAFBHCBEFBACDGBDGHHBFGDFEDEEGGBGGBHGFGFEGHCFBFFBGFGHBADCAD,False +523,13.0,18.0,26.0,23.0,24.0,18.0,20.0,22.0,HDCHAFHBBHAEFFCCGDFGAFCFDBHGFGEFBEGCEHDHHEGCEGEDBDDBGAFHCFHCAECHBFHADHFDHECFBCBBEEDGBCGEEEDGHFGECCECDACDGFBCACCDDGDDEBDGBDGAACABCABCFBEFEDHEDHDGHEFHECDECGAHGEHGCCBH,False +524,23.0,26.0,27.0,25.0,18.0,14.0,25.0,20.0,AHEABADDECBHGBEGDCHHCEDCECAFCACEFEEGGDGGDGEDGCFBAEAHFGDFCACHEBDDBADBADBDDACFAFAGCBBHBGGFDBFDGAAGAHGDHFBEEDCCDCBACHHCHECFDDHABAACAAGHHGBGGBGFBGFHDCBDCBHBHHCDFCDEBGHBGACGCCGECBBBEE,False +525,9.0,5.0,7.0,9.0,10.0,14.0,16.0,12.0,GDEGFEHFGFFECEBCBHHAHAGHAGDFCDHBDAFFFGFGGHBDHFDCFDCDGFEGEGCEGAGAAHAGEGHEHFEHFGCDBA,False +526,21.0,20.0,28.0,24.0,24.0,22.0,22.0,28.0,FBFFHFFDFEBCDDDFBEABCGECGECFHFFCFDAACAAHAHCDHGHHFHCBHBDHGDGDHAHCDHGABAABGCGAAFBGFCDFCDFCABEHDEAGHABHEBAEFHCAEABHGHHACFEGEEFEEGDFGDCCDCEDHHGBHGEHGECGDHDDAFCEBDHBGGECBDCBGCAGCEBCECEBCEHCDHEDF,False +527,20.0,11.0,8.0,13.0,17.0,8.0,13.0,14.0,DDHGDHCDHDDHEGFEDECAEHFFHAABEGBEHBCAGADGACFACECDEAHGABBCEAAEAGFABAABAHGFHEEGGDCEBAFGFHGAEDHEDHEABEABDHBG,False +528,9.0,13.0,8.0,10.0,8.0,6.0,9.0,7.0,ECDBCHEGHFFBEDBGDBHDBHDFHFEBBCDFDACACCBEHBAGBAGFDGADGACHABDAEABGGEGCEB,False +529,2.0,5.0,6.0,3.0,4.0,6.0,5.0,4.0,FCBFCBFCDCHDEHBFGFFGAEAHEGBCGCHDEBG,False +530,5.0,3.0,3.0,2.0,4.0,2.0,5.0,5.0,AFBAEGACGFGHCEHEBGEHGHDAHDACB,False +531,14.0,18.0,15.0,23.0,16.0,17.0,15.0,32.0,HBAHEDHGDHCDHDEHDEHDEHDHFAGADFEEHBBDFHDAEDEEHHHBHDFHDFHCFCFECABGGBEGCEBFBBDBDCCHCAACFACFHEEHCHHDHGFHGFHDCDDBEBGHAFFCGBAEBAHBGHAGFBGAHCFFBDGDCBDHGHGDHA,False +532,8.0,6.0,17.0,12.0,9.0,14.0,14.0,11.0,DEGAFHFDCCDGCHHBHCFDCFDCEGGFHHCAGEGBFGBDGDAGHCGCCGDCHDGEDBEFFCFDCGHCEHEGHACCAFAFFDFFAEBAEBC,False +533,15.0,11.0,12.0,12.0,16.0,22.0,21.0,18.0,GAAFFACGGFHDCBDFBAFBAGEAFEBFGGFDDEGFEACHFFBDFGEGDFFAHFHHAHHEHHFHFABECBDHHDCHDGGDGGEFGEHACGACGECEECEEBDBHDHHFHEFGGCABCAFEFCGGGBA,False +534,6.0,6.0,12.0,13.0,5.0,12.0,12.0,8.0,HDGAGHFGHFCHABHFEHFACCCBCEGCGDCDEADCFDHGDGFDGFBGCDCHFFEGFAFDDFDDGADCBECBGB,False +535,22.0,16.0,25.0,15.0,17.0,33.0,16.0,16.0,FBFFEECEEDFEFEEBGGDGFEAAEFCGFDGHDGDEGAAAHACFECDACDCHFCHFAFFAFEGFBDFECHHBACBCCACDAGFGDFEDFCCFHCBCCFACAAGADGHEFFCBFHDFCDHBHGECAFFGBGBFGAAAFBHFHHFEBFCDFCBACBHCBHAB,False +536,20.0,17.0,26.0,15.0,22.0,17.0,17.0,16.0,BHHBAFEEFAEFAEDBBDFEEBCEHHAAHAGBDGBHBECECCBFFAFEACEGCEFEECDDDGBDABEEBEHAAHCFCCEACDAHAGHBGFACFHCGHCFCCBCFGHDHCDHCDGCEAHGAFBADGGFCBFCGDCGCCFADECDGGEGAEB,False +537,13.0,10.0,5.0,5.0,10.0,8.0,9.0,7.0,EADEDEAAGAEEBGGHHBFFBFEBFBBDEAHEABCAHCAEFAGDAEDBFFGFAGAHGCHGHABCGBC,False +538,10.0,10.0,16.0,12.0,12.0,14.0,12.0,13.0,DFCGBCDFCDGBDCFCFFCFDAHDCBECEEBEDBEHECFECGAHGDHEAHAHHGFHGDHFFCGGCEGFGGCGCAAHHAEHCBDFBDEBAFADFAEBCBH,False +539,2.0,2.0,4.0,2.0,0.0,2.0,1.0,0.0,ACCFCAFCBDDBG,True +540,3.0,8.0,6.0,4.0,2.0,10.0,5.0,6.0,FGBFBFDBFDBFHFFGCEAFHCCBFCBECFABGDGHDGHBHHAC,True +541,4.0,4.0,3.0,5.0,9.0,9.0,6.0,7.0,HHFDFBDFAFFAEFEHGEHGEBGEAHFDEBCGHGGFEAFDDHCEBCE,False +542,1.0,6.0,4.0,1.0,3.0,1.0,2.0,0.0,EGEEDACCFCCBBBBBGB,True +543,11.0,8.0,11.0,8.0,8.0,12.0,13.0,10.0,CGFCHFHAFHGCGCCHCGHGACBDDBCDFADFADFBBEDAEGACFAHHGBHGDAEFGEAGEABHBGFBAEEGEHDFCGFCF,False +544,1.0,2.0,1.0,1.0,0.0,0.0,2.0,3.0,GDAHBCHBGH,True +545,20.0,18.0,24.0,26.0,24.0,22.0,18.0,33.0,CBHDDADAHFAEFCEHCEHEBHCBGCHAAHAFHFFEAFDAFBEEGHAGDDDACDHCEECEGDEGDEGBADBEDBAACEECHFBFCHFHHEEDBHHAEFCCHHFDBFDHCHHAHHAHGCHCCGFCGBGGFGDFBHFDGGDCEDADDADCFBCHBCBFHEHBEGAFHCCBEFFHDHGAEGDBGDEHD,False +546,29.0,23.0,21.0,19.0,21.0,27.0,25.0,20.0,BHEADFCDFGBFAFFACEAGFABFACFACFHEBHBFHDFGEGCEHCGDCDFCACAGDEBDEFAEFGEGGHCEHEAFEGECAAGAAEFFFFDFGGGCDGBGEBGHBGEBADFGCAGEADDBDDBACCCBDBBHAAABAHBACGECDDHGHHGBFEACHBFHEDCFDAHEAGCBGBAHFAHFBHFBH,False +547,8.0,14.0,13.0,15.0,21.0,12.0,10.0,20.0,CHCHGGHDDADDEGDBGFHCBECDEFBGHEECEGCFAEHHEHHCHHCHFFAAEDAHDEGBEHAAGBEHDEDBCFFEFCEFCHHEHBEHBEHEDDEGDGABCEBDBBCBFFBDF,False +548,5.0,4.0,1.0,2.0,4.0,2.0,2.0,2.0,ACBADGEEGEEBAFBFHDAHBA,True +549,14.0,13.0,9.0,11.0,17.0,24.0,19.0,14.0,EHAEHGEDBEDCEGGEHFBFBBGBGGFHAFHBFEACBACEADGFEACGFEGFADHGDAGCBGHGCFEBAHBGHAHADDAFDHGGHGFFGFFCFFEAFEGEEFFHFDBBDCBEHFFDFAEFC,False +550,8.0,20.0,16.0,21.0,30.0,20.0,19.0,15.0,FHEAEECEEGBBBBBHBBDDCDDCDBCBFFEGFBCEHEEHEEBEEHFDCEECGBBGAGAHCAFCAFGDEGCEFEHCDBEDHGCGFFGEEGEECBEFEHFHCDHBDFDDGGDHEFHGDECDEHEGACFAFFGFBGBGAFGDDDDDBEFBH,False +551,8.0,3.0,13.0,5.0,6.0,13.0,5.0,7.0,BDFEDFGCFCHFCGCAFFAFFHFGCAGHAEHCBCCEHCHDCADCFFAEFCCDHGEFAEBA,True +552,10.0,10.0,17.0,16.0,16.0,11.0,4.0,13.0,CABEDBDDCCDFHBACBAEEDFGACHECHECEDHDDBDDHAHCBHEFHEFHEDDGACAECHEFBEFDEDDHCBHCHFGBFEBDCFACEGCAACFCEF,False +553,29.0,25.0,19.0,15.0,29.0,33.0,22.0,26.0,EABECBEDDEFBHACGBHHEHFFAFFEDBAGFCHDGEDEHDGDDCADHAFFABHCFEEBAECAECHHHACCAEABEABCCECFECEGCHGCFFBFFBEFDGGAGAECHEHHDHHABDEHAEFFEAFAFFAGFHGEAGFFGFAACAEFFEGBAABFGBEGDFHDFHEFBBHDHHGHBCABABBFBBGBGGEAGBFGCFH,False +554,19.0,13.0,14.0,11.0,11.0,13.0,12.0,8.0,ABGABGBBFEBEDGCDFCEAGEAGHAGFAGHACHCDHADCADFGDCDDAFEGFEDHHAGCGCFDEHBEFCFFCFEABGABFCHEBABBACADEAFBABACC,False +555,4.0,7.0,2.0,2.0,5.0,4.0,2.0,1.0,ABBABDFBHFBEFEGBAGEAEEFDCCB,True +556,33.0,24.0,13.0,22.0,28.0,22.0,18.0,30.0,EEFABBCDBADEGEHHHCAHGEHABDDBDAGAABDGBABBAGBEBHEFDEDCHDAEDBFHEAHFAHFABFCBEHBEHAEHCHHFEHBEHFEFFHAFHAGHEGDDHBCEDGAFGECHHDHFAEFAECAGAGCEGADDAEBABAAHHAHGAHFEEECAACGFCDFDDFAFEBBGHBGBAFBEHDFGDCGDFA,False +557,21.0,20.0,17.0,15.0,9.0,13.0,11.0,17.0,FFFCCBHDBHDBDDBDDHDCGFBAHBHCCDAADHAHHADGADCCHBCFECEACECCFDABDCEHEHHEBHDFFABAABAGBEGAHGACGCGGFBBHBAFBABAGHAFHFGCGDEFBBCABAAE,False +558,17.0,17.0,12.0,11.0,13.0,15.0,10.0,21.0,AACABFAEFAEGCEBAFBFHBDHEAHEBEEHDHHBHCBFGAFGFCACBFBDFADFCDBHHBHDACECHHDABGBBGFGHDACEBCEBCAFHDEBDCAAHHFHHFGHEGAEGHFGHD,False +559,14.0,31.0,29.0,20.0,24.0,28.0,19.0,25.0,CBHCBFCBGABHAFHAGDBEEHABFAEDGEDECFFCBFDFFDEAEHDDCECEHCBACBDFBCEECGGCGFCFHEABDABDGBDAHFHHGADGEFHDGHEFHEBBEBGCBFBBDCEGFFAHGBHAFFGFFHEFHCCHBBHFEHGBDDHCBCFBCFBCADCDBCGCCBBCBECGDCHDFHBGHFGFCEEHEE,False +560,11.0,11.0,9.0,9.0,7.0,8.0,12.0,11.0,FDCFDGECEACDHCFAFGAFAFECFCHECHABHGBHBBHBGEGGAGGAFDBHDCHDBEDGABEAGACHBHDBDABGHG,False +561,17.0,20.0,22.0,24.0,12.0,25.0,33.0,19.0,GFGGFCGFGDHGBCGHGHHGHCGHDGCGCDDCHGCFGFAHCHFDFCDEBDEBGFCEFCFFGAFCCGCHACBFDFGEEBBDDBECAFGAFGADGADGDDGADGFDEBDBBDBGCAGHGGDGGBBDFHCCDCEFABHHBHEEHBDHAFAGEAGDABFAHHAFBFGDCEBCBFFA,False +562,11.0,10.0,11.0,8.0,5.0,15.0,7.0,5.0,GBAGDDBFDHFDGFAACAACBBGFGEBGFFCFFCEFBEFBCBACFFCAHCAHEEDBAHFCFFCDDAGCAHDB,False +563,20.0,11.0,17.0,13.0,14.0,9.0,14.0,23.0,BAGDHGEHCAGCGEFAEFBCCHCCBDADHBDHADHCGHAGAFEAHHAHHACGCEACAHCDHBDGGDFEBFHHDHHCAHGAHFEEDGFDECDHHEHACFGHFECEGBBCAACAABDABEGBE,False +564,25.0,13.0,20.0,11.0,13.0,16.0,8.0,5.0,AAAAFFCFFBBFABDAGEAGAHGACCFEFGEGAEAACACEFCFFCDCHFBBCBCCADFBHFDCCBGABGCBABBDFACAAFGACACDEEDECDBDAEDAHDAECAECEEHF,False +565,28.0,15.0,20.0,25.0,16.0,15.0,18.0,16.0,AADAACACCACGGBEGAEGBEGFHCHCCEBCEBDBBDBCDAEDEBDABDFFHHEAADAHHGHGBDGCAGFADAADADFHEFHFGDEBDFCAFEHFBBFDHCDADDACDHFHAGCGDAGCABADCADEAGEGCHDDBDCAGFHGHCGAEFFECE,False +566,7.0,8.0,2.0,9.0,6.0,8.0,0.0,5.0,HEFHDFDDHDBEDBEFBDBBECBAFBFDAFHAFEDDBCEAAAFHA,True +567,12.0,8.0,8.0,9.0,5.0,12.0,6.0,5.0,DADDAGBGGBCHFGFDAFCACAEFADFGBFABCDDFEDFECHECDBAEAHCAHBACBFFAFFBGH,False +568,27.0,25.0,25.0,24.0,19.0,25.0,34.0,18.0,GGBDADGGGAGEFFECFEBGEADDADDAFHBBHBCFBCGGEGEDHDHBDFBACBGCFACBCGBEGHHGCAGHGBAFAHHBFHAFECHCABFGHCDHEFEFCEDCEGBGGDAGFFGFFGAFBEFEAFEGFDBFCAGCAGCABAHHHCEACBGEBDEAACCFGGFGDBGDCCDBEGBCDFADBAGBADDADHCDHCDGA,False +569,17.0,19.0,19.0,27.0,20.0,24.0,19.0,16.0,DCECCEHDBFDEDGEAGFGFBCHBCAGAHGFDAFDBHAGEADCHDCDGCBHCEFCHFCGFAADABFABFEECGFHHDHBDEBDBCFEEFEEAECGDBFCBDHBDEBDAFDAHCGDEBDEHDFADFDDFGAFEFCAFHDBEBBDGGACDBCHGFFGFGGEGH,False +570,14.0,23.0,26.0,22.0,21.0,32.0,13.0,35.0,DEACHFHFDHEHFCHFCEFBFHBECFECHDGEDFFDEFHFBCCACCHGDFCHFEHCAHCHHCEHEEHCHHCAHDDGFBHCBEAGGDBGFBEHBHFBADBFDAFGGGABHAGHABDFBFHCFDCFDHEHCEAAEGCBGDFCFFEFDBFBBFBCHBHDBEDHDDBAFFCFHAEHCEHCBHDBCDEGFH,False +571,12.0,18.0,32.0,29.0,10.0,22.0,15.0,20.0,DAHAAEGCCHHEBCEBHDDGDDFFCCCCCHCFHDDHDHADBEFBECBCDBCDFEDGHDHCECGACDAEGGDGDBFHCFDGDDGAEFDCFDAADAADHBCBBCGEDBBHCFHCABFDHFBFCBCCBCCHCFFDGCGGCHCBFDFFDFFCFHHBHGFCGD,False +572,19.0,12.0,16.0,19.0,24.0,11.0,17.0,21.0,AEAGEAEEBDEGDECBBDAHDAFECHEFHGFGGDEHDECGGCAEHEHHCBHDDHDEGCEGAHGFEGEEGEECFADFEDEGCCABAGBAHAHHAEHACACHAFHBCBBAEAFBHDDADDGDBFHGCHFCHCCGFDHDDBE,False +573,5.0,2.0,3.0,2.0,1.0,4.0,3.0,2.0,ACEFDDFABGAGGACFAHFCHB,True +574,17.0,18.0,22.0,17.0,4.0,9.0,12.0,14.0,CCBCGGAHDAEDBCFCCHCFACFAEDAHDAHGBGDFDDCACAAFBBDDBDBBFCBECADDACBFCBHCHHABCAHGBBGBADDACHAGHDGHDHBEHBGBGGCFDAGCCCFHC,False +575,13.0,19.0,23.0,32.0,16.0,20.0,25.0,19.0,GGDDGDDCHDBGDFDDHBBHGBHBFHCEAFEHFGFEGEGGDGDFCHFAEFBCFGHDGDEGDBHDAAGHDDADEBCEGCEFCEFEDBACHAHFDEFCGFGHBBBABDCBFCHDCFFCHDDGDDGECGEDAAHAADDAFDCGCHBCGBCEHDEGFFHBDCBDBGCCGCC,False +576,9.0,9.0,12.0,4.0,5.0,6.0,12.0,11.0,BHFCHFGHEGHBGEFHADCDCGGCFGCBDABAEBACGHEGFBGBAHCDHCGHAGEAHHCCFCBGABCA,False +577,6.0,7.0,11.0,9.0,9.0,12.0,13.0,8.0,EDDGBABEGCGACGECECCBCCHGEFDEFGGFGBCGDAGHGCHBFGBFDEFCFFAGFDHBDADFADFHHFHEEHC,False +578,0.0,1.0,2.0,1.0,0.0,2.0,4.0,0.0,GCGDCGFFGB,True +579,5.0,1.0,1.0,3.0,1.0,1.0,1.0,4.0,HGAHAACAAEHDFDDHB,True +580,23.0,6.0,7.0,14.0,17.0,10.0,20.0,6.0,EEAEEHDHGCBEABGFBGEACAADADGADHCGFGGEHGAGGDEAFEAGEDEAAAAAAEGCFGDFGDEGAEAFBAHBAGDFGDFECCECGDBAAGDEGHAFDDF,True +581,26.0,18.0,18.0,18.0,15.0,22.0,19.0,23.0,FFFAFECGECGHCGACGACAFFGHGEHADHFDHBDHCACGABGAFHHGAFGABDABAFBHEBAEAHFAGCAGCGFAEDGHFGAEBAEHDDHBDFAFBHDBFCHEHHGFDDBAEHAECAHGHECDFDDHHBFHBFCBADFFDCCDBCABGEBCEBDEGAC,False +582,21.0,17.0,16.0,25.0,18.0,9.0,13.0,8.0,GAHDCGBCBACDDBDGADCEDBFDAFDADEAEEBEHADFAHEGDBGFHGHCBAAHDEHEEACDACDECFEAHAGGAEGAEFADBGEBGCDDCFDABDCCAGBADBDFFDGDECDBCDCCEEBBEBBA,False +583,3.0,13.0,7.0,7.0,6.0,7.0,7.0,14.0,CGGBGGBGFBHBBHCAEBHEBHFFFDFADCDBFEBGCBCHHHDHHDBHEGDECBAHFDHBEHCH,False +584,19.0,16.0,23.0,16.0,22.0,21.0,12.0,29.0,CGHFFHFFHCFGDFDEECFDCDDABFAEAADFBEAECAEGAECHHCHAEHFECCHGCHGEGGEDHBABFAHEEBGEHHHBHHCDBCDBADCACABCBCCBHBGHDFHBFHCABGDCFCCADHAHHEHHEHFEABEGGAFDFEEFEAFCDDEHFBHCHF,False +585,5.0,14.0,11.0,11.0,4.0,5.0,12.0,10.0,DGDBCBFGBDAEHACCEHCDCCBHFBHFBHCAHGGGCGGBGCBEDBGBAGHFCHDCGDBHABEFBDDBDDHG,False +586,11.0,24.0,18.0,11.0,8.0,6.0,17.0,13.0,GBBGABCCDDEGDFGAHEAHCAEGBEGAEABEAHHCHBBHCBHCBGGGGGGBHCBCCBDDDCGGBEFFADFGBCABGBBDCBDBHABHBBHFBDFCHCBGDHACCCEC,False +587,14.0,18.0,17.0,13.0,15.0,17.0,25.0,21.0,ECCAFEAGBAGCGFCGHADHEBGCGGCBDCGABDHBEGBCGHHGFHGHHGHDGCACAEHBBBABGFHGFDGFDBDGBAHHGGBCEFCFHHFEHFEFFAFFAGFCHCHGABCHEFHCFEBDEBDACGAEGEEHBBDEDDGD,False +588,13.0,15.0,14.0,18.0,15.0,14.0,13.0,9.0,EFAHGBHGDHGDCADGDDEEEECFACDGDGHCCFCEDCBHFBGDBCDBCGFCGBCEDDEAFEAECAFCDFDDBHABHFEEBBHBACBADBGDEABFGFFADGAGFAEFEBH,False +589,12.0,8.0,10.0,3.0,6.0,15.0,8.0,10.0,FDAFCFFHFGHFGBFHAHAADACFCCBBCBBHADHACFAHBBCGGEBECHGAHEAEEAFFFCFFHGFCGAEG,False +590,17.0,15.0,7.0,14.0,11.0,14.0,9.0,6.0,HEAFCADCHBHAFEFFEDAAFBABCGDDFAAGDGDCBEBFEBDEBAEAEBAEBAFBGFBHFCGCHGHDGFAAFCADBDDBDDGFAGFABEDBE,False +591,10.0,3.0,10.0,5.0,10.0,14.0,7.0,11.0,CFGCFEAFHGFCGAHACGFEADCAECAEBEDGFDHFEHFEHBEHFECFAAFHAECDHGDBFHHFAHCCFG,False +592,19.0,16.0,12.0,22.0,13.0,29.0,15.0,13.0,GHBEBBFBGFCCFDDECDGGDFGAFABCHFAFFABBCHBAFGHFBEFDEFGEFGDDGDDACDBCEAFEACEDDFFAHEAEDDHHFFDFBGFHGDBFHECCCFBDEBAHFAEFAGFBGDHADAFDAFDAFHAFGAGCHDB,False +593,7.0,6.0,8.0,6.0,8.0,9.0,6.0,6.0,DCHBFDCFDGACEACBBCBGHAGHFEHFEHDEGAEAACGFBFCHFCAEDFEBEDGF,False +594,30.0,31.0,17.0,16.0,20.0,23.0,18.0,23.0,ECHGCHGBBGFBGABGCDGHFFBFABDADAFEAFEHGBAABEABHABHACFACBEFADDADFBCGHHABFEBEGBCGEHFEFEBGEHGDAFBHDAFBAHBAHFAFACGDCHDCHDGBEBHEFEAFEDHACEBCFBCHBFHBAACFCBAHGHDDEADHAECACGBBABAFBFEBGEHGD,False +595,9.0,14.0,16.0,12.0,7.0,14.0,15.0,6.0,FEGFGGFDBAGEFGEFCCHCBEFBCGACBACFCCBCAFCAGGFFCBHGBHDBADADHADGBDGBDEBCHFCFCCGBDGDHEDADDFEBGGCFB,False +596,26.0,34.0,20.0,24.0,21.0,26.0,22.0,25.0,FEEBEHGEHEFHEFEEACGABBDHDDHGCGFDACBGBHGFHDADCFGCGBDAHHCFHGFEEFEAHEBHGBAABDABFAHFHDDADDFDBGGBFHBAEBAEBAHBAFACFADADDAGGBBGBBCCACFFBDFHDFHDBCBCABAECDFGDGHHEECCAFDBDEFCEFGDBBHBBHGGHFBHEGGEBCABCFBCFCAHBA,False +597,16.0,18.0,17.0,23.0,22.0,17.0,16.0,28.0,EECBEAGEDFCFADAHFCHFCHECDBGDBHDCHAAHDDBDDCDHHFHBAHBEHDEHAFHAHHEEGEEGDEBDEDDHBEBGEHGEHCACFHBDBACHECEBCACCGCGGEHHDHBFGEABFDFFDGFAHCGHCFHBGHGDABDAFGBEGFDFBDEHFA,False +598,14.0,9.0,12.0,11.0,20.0,14.0,7.0,8.0,EEAFAGFHFFBEAGHBCFFFFDFFBAFCEGEEGDCGDCBAADAHFFHAGHACDECBEDBEAACDGCEACHDDADBECBECHEAHFDEEEEEEEBC,False +599,31.0,15.0,28.0,34.0,25.0,28.0,16.0,23.0,EADADBADCDDCGEGGEAFEFGBDDCFACDECFECFBCHAEHABGFCCAECDEDGCDGCDGEAHDBBDBACEAFBFEBEDBEBEEFGAAGADGDFFCEFAFAABDFHDFHDGCDGHDFCDFHEFAEGCFDAFDAFDEFHBCDAFEECHHDDHDCFFAHHHHCHADEADADBADBCGCCHFAFCEHHAFHAHHAEGACCCH,False +600,10.0,11.0,5.0,10.0,8.0,10.0,7.0,10.0,HBFHBHGFGEFGEFAAFAGFGEBBHBDGBHHAHCDHEHBEAFDDBBABDFDCFHEBCECCADGADFADAED,False +601,1.0,4.0,4.0,5.0,1.0,4.0,5.0,0.0,EGCDDCBDCFDFBGBDGCAGFBGF,True +602,4.0,2.0,2.0,6.0,6.0,0.0,2.0,3.0,EDEEBAEDHEAGEABCHDCDDADGH,True +603,22.0,28.0,15.0,26.0,22.0,27.0,16.0,24.0,EADBBCFGEFEAGAFEACAHCDBABGHBHAEDGGDCGFBBFHFCEFCEFEDAEGEHGABFHBFDBGDBABGGCGBCGBABHAFDDFBDFBGFHFCHFCHFHECHDFFDFABFDBHDFDCFDCABHABHEHADCDDCDHFEEDAEDFEBHHAFHGBHBBEEBDHDHEDABDABAEGEEHAF,False +604,21.0,11.0,14.0,19.0,11.0,12.0,18.0,29.0,GHHGHHAHADHAHCGBCGBDGBDHDFAABAEHFCDDAACAFHBHHDEBEGAGGEBGEHDEGFGGCHGDBDHHDAAAACFACFHBHEAAEHADHGCHGHDBCFHEFHEFECDDHFDCGDFGAFHAHHCHBCGDCAD,False +605,9.0,11.0,6.0,10.0,8.0,6.0,9.0,4.0,DCGDAGDABEBBEBGEBGDDGHAHHBCCECAHAFFAEDCEFFEDCBGBBGEGDFGDBAAFDAB,False +606,28.0,22.0,23.0,19.0,24.0,23.0,22.0,23.0,GHDEEDGFDEHCEBCEBAGAAGEGGEGABFHGFAGAHGDCCDHFBADBDDBCDBFHFDGEEGCEHFFHCCHAGHABEACCACDFEEFAFGEFBCGBCBFAFFBFFDGEEGBEHBHHDCACFHCACAABAABAECCDFHHFHBDAEFHEFEECGFBGCDGEHCBGDBAAAHCAHDEHDBHABAAG,False +607,13.0,16.0,14.0,14.0,17.0,12.0,10.0,10.0,BGHBGADGDDGCECBEDBECAECGECGECFACFBEEBEADEDHFAHAAHBFEBHDCFDGDBFFBEGCAFADDHCABDACDABDHGFFGEEBFEBABCEFEHCHHCB,False +608,9.0,17.0,16.0,8.0,12.0,15.0,18.0,16.0,BGGGDCHHBHGBEACEACEGCEHFHCBGBBGFBGFAHCDGCFFCFGCBGBBGBFGBFAHFBGFBABCEGCEADHHEHHCHFEGEDHDDCDABGHECCFCFFGBADEAEHFH,False +609,34.0,28.0,25.0,20.0,27.0,20.0,18.0,15.0,FHGFEGEBBEGBEGHFHDFDAAEAAEDCFDBFEFCDCDDGEAFEADBCCACCDFHHBCHFEDABBABBABHAFGACGEEEACCACDDCBFCDHBFGBAGCGFADEADGABFABAGEEEBHBFDBFEBGEBEBHCCDCAGCAECAECAFCHGEEBFEAGEDECAHHABABBABDFDAHCABCAGHAGA,False +610,27.0,20.0,29.0,19.0,16.0,20.0,23.0,16.0,EDGGDCDCCDCCFAHFACFEEAAGGAHFADGADAEDCEACDAGDAHDCHFAFFHCGHCGDEBAEBAFHADHCBFBBDAECAECACGGGGFFCDGBHGECFBABDABGECGEFBFCBHDBHAHGACBAHEACCACHBHEFCBDCGDBGCBGHGCBFCADEFBFFGABGCEF,False +611,22.0,21.0,24.0,24.0,11.0,17.0,21.0,18.0,CGCHDBGDBABGACGAEAACCDDCDGCDGFDEHBABFCHACHAFGDEBDEBDABHGBCFBCBAHBDFBHFCFECFECGAGEAEBDGCGGCHGDFGDFCFBHFAFGAGHHFBHDAADCAHCAGEABCCBDDEDDHCCAAHFHHDADDBGHCGBFFBEDG,False +612,15.0,15.0,16.0,7.0,8.0,15.0,11.0,10.0,BBGABCABCFCHFCBCAGHHFHFFBFAAFAGBAGDEFFCFECACDACAFCABEEGCEGCAGDBCHBDDFDDFAFHACBGBHGBHCEEEGHCGFBHBA,False +613,1.0,6.0,10.0,13.0,4.0,6.0,8.0,9.0,GCDDCDCAHCHEDFDCCDGGDBHDCHDBHCGGFGCFGHFGFFHHCBBEEBDEDDBDH,True +614,10.0,16.0,11.0,12.0,14.0,10.0,10.0,10.0,DECEGBDAEDAEGGGHGAAEBAEHDGHGEBCHBCHBFEBCBFCBAHEDFEDFGAFDCFBCFBDFBCHCCHDHBDBBABFDGEEEDCEGAHBAF,False +615,1.0,1.0,2.0,4.0,6.0,3.0,0.0,3.0,HDEHFEDCEABEHFEDDECF,True +616,10.0,6.0,9.0,12.0,6.0,14.0,6.0,4.0,DFHDFBBECCFCCFBCDGAFFABDAGEADBDDACECFECGAAGHFHFFHFFDGDAFDEFDEBDAAGC,True +617,6.0,1.0,4.0,3.0,5.0,2.0,0.0,4.0,BDEHDAAFACHECHECDEFHCAAEA,True +618,22.0,16.0,36.0,14.0,21.0,16.0,20.0,16.0,BBGEBEHHHHHACECCGBEDBCDHHAHDCHDCECAFHAFDAFCAECGCCACCGFFDEGACGCCGCEGCGGEGACGACBDGGDEAEBAEGFECAECFBGECAEFFHBCCBCHEFADFDECDBCBFDHDECDGAABHCFGCAGCFGABEABCABCECCFFAHH,False +619,26.0,17.0,24.0,18.0,27.0,15.0,23.0,23.0,ADFABEBGDCGDEAEHBHDBCGECBECEEGAHGCCECGFCAFCHECFACBAHBACBAEBDEHFEDDEHGHHGHHGAHGAHFADAAGEAEDAFAADADHEGHEGHGBHDBCEECGFCHEBHBBFAHDCGAEGEEGECGHCFCFGCDDFDCBCFEAAAFEAHGBGDCDBEFCHAG,False +620,7.0,2.0,1.0,9.0,6.0,2.0,5.0,5.0,GBEGBDDHGCFGDGHEEHDEFAADAAHAAEAHEDDDD,True +621,16.0,26.0,22.0,21.0,29.0,29.0,17.0,19.0,EAFBDDEEGGEGGEGDFBBFADADCGDCBCCHCDDEDFEDFADFEDFGBFHBECAHCDBCGFCFECEEHAFHAFCGFBEHGFHEEHFEBCGBGGHABFGDAGCABFDBFDFFDEFBBBDHBEECFEHEACBFBDFHAHHEHHEHCCHGBAEBDCCEEFBBFAFCBDCBFBAFEACEGHE,False +622,7.0,7.0,8.0,11.0,8.0,4.0,10.0,8.0,DAGDCGDHGDACDBCFHHEGDEDEFHCBHEBHFDHEHBCGGEGBCGDCFDGEDCAABAABEAG,False +623,28.0,16.0,21.0,17.0,19.0,16.0,21.0,15.0,DEHGEHCAACGFGGBEFBEGGGBGFADAEDADDCCHGGACAACEBDGFCBDAAFBCCCCCAEEEECHDCEDAEFAHFABFACFGHHBEGCEFBAHCDHDBCEBCEAHAAHAABEDGECGFAGFABFAHFAHEAHDHBFCBDDAFDAGBGGDGG,False +624,3.0,1.0,2.0,2.0,0.0,4.0,3.0,0.0,GAAFDAFGGFCDFCB,True +625,2.0,3.0,2.0,8.0,3.0,1.0,2.0,1.0,DHDDBDABEGDDGBFAEDCEDC,True +626,25.0,22.0,16.0,18.0,24.0,24.0,24.0,13.0,EBGFHAFDBGEBGEFGEDHADHADAAFCAFCHGEAGACBDGBFBDFEDGEHGEHGDHGCFCEFBEACEBHGFHEBHEGFEBAECFBABCACCABAEDEDGEGCABEEDGEAGAAGCFFDBCGHAGCAFFGFDAFHFFGEBBBHBDAGDABDBDGBAFEDFCAFCEF,False +627,29.0,21.0,28.0,24.0,31.0,21.0,20.0,20.0,FAHFBGFACEAEHGHHCFHGAGFFCCDDBDGBDGBDBHEBHECCEHCAFEGEHGEHGEGGBCABADDACDEEBCHCGAAEAFCABCEBDABEABCAECAEAHHFCFGDFHDFHBCECEDCDFCDACEFBEDBFDBEBEHHECCEDAFDGFDHEEHEGHCDDADAAEGAFADCGCGFEGFEABACFAEBACBGDA,False +628,12.0,14.0,20.0,9.0,14.0,5.0,7.0,10.0,BAHEECEFDEACFADDABAECEHFDHCCCACBAEDHEBHEBHFHCFCCGCDACAADGEGCCGCGBCBBCGBCEBEHBEDCADBEGBCABHH,False +629,5.0,5.0,7.0,3.0,4.0,2.0,2.0,2.0,EFAECAECHGHFCDABDBCDBCBCABCGEA,True +630,23.0,22.0,17.0,29.0,22.0,31.0,12.0,12.0,CCDECDBBHBBHBGFACDAEHBFBGFCCEHGEHEECEFDDFDDBEDBAFEHBDHBFFFFFFFAFFAFHDFAEFACFCCGAFAAFGADGADFFEBHEGEAAFBDGBDADDAGEACECCFBBEEGGEBDBBCAADFEDCADFFDFAEFBHDDDDBCCBFGDAEHEHDDAD,False +631,27.0,22.0,17.0,34.0,24.0,29.0,22.0,24.0,FFDCFDCHHBFADFAGECGECGBFBAFBGGACBFCBACHEFEEFBEFEEFCBAEECEHAEGAEFACFADFDBFBHHDHAFHADDGHHEHDDGEBEEGFFDDGEDGADGBDHFDHFBHFHAABAADHAEHBHGDFGEAADDFDCCDCDDFBAGCFDCGDHBDHEAFDGBEGBADEFGCDBADGADHEHGFHBDHADGACB,False +632,14.0,22.0,9.0,14.0,13.0,13.0,20.0,23.0,BCFBCFAHGDHGAHEDGEBBCBHEGHDDDBAGBAGCECBBGBDABAGHDGHEFFBHEEEEHDEBDEFAAFAHGDGCDAFHAHGADGAGCDDHHFHGFHEBHBGHBFBBFGBFHHFAHCHHBECBGBGG,False +633,24.0,22.0,20.0,25.0,23.0,16.0,19.0,23.0,DBBDHHDHHEFEEFGABGFEGADFACHGEHGEHAFFAHECCEACEBBHBEFADDDDGGHGGHAABCFDCFBGFAECDGBDABEAFECFEHBAHFDBFDBDEFCBCCGDEACAAGBBGBDEAEAAGAAHBGHACCAECGCCDCGDEHAHGBDDEDDHDBHDHHFCHDBHEBCE,False +634,17.0,21.0,22.0,24.0,23.0,23.0,16.0,18.0,CBHDBHCEHCHBGDBECHEHFBCFDFBDFCGFCACCACCGDEAFGADEADFCDFBAHAGHGEBDDBDEBDHBGBDAEDBEDCEFCEFHBHCGDAHAAEDEEGGECBEHDGDBGEHFEFGEFBFFAFFCCFECEDHEGCAGBACFDGFDHFBABHADFBEFHADC,False +635,16.0,6.0,8.0,5.0,5.0,8.0,8.0,4.0,FFABFACAAFAAHAFHCEACEABFCDGCFACABGGDGCABAEBGEAGBAGHACHFEDDDG,False +636,0.0,0.0,0.0,2.0,3.0,1.0,3.0,2.0,EHGEHDEDGFG,True +637,9.0,16.0,10.0,10.0,13.0,11.0,8.0,12.0,FEDBEDBEBBEFBEHBFBFCBEGBAGBHGHDBDDEGBECEFHDDHCFHGBHEBCGBEFAACBDEFCGFAAHAHHFFAADAHDCHGCECC,False +638,12.0,9.0,9.0,12.0,9.0,15.0,8.0,15.0,EFGFDCDAGDHFCBFEAFHACHBGADEEHEFGEDHFDGDDGAECCFHBFHBCACHACHACFAFBGDBGDBHBHHBHDEHDAAAEFFFHF,False +639,14.0,20.0,11.0,14.0,9.0,16.0,14.0,14.0,BFBHEBAEDADCGDAGDAFBHCBACBAEAHHCGBCGFCGAABFCBFGADBFFFDFCDFEAGGDHDDEFFHGHHGHHEFEBHBBGDBCHBEHBEFBCABDGGDCGAFHBFABD,False +640,8.0,6.0,17.0,2.0,13.0,12.0,17.0,7.0,HCFFGFCHCCACAADFGBFCFFCGFCABGBEABGCEGCEGCACCFGDGECGHCAEGBEGEEGHBGEAFEHFEHGHGEECCGF,True +641,14.0,17.0,15.0,14.0,30.0,13.0,21.0,15.0,BBGEDAHDBBEHBCBEHAEGAFGECGACGADAFGFFGFEGDBCCBFCHDHABHEBGEDADDHEGHBBHEGCGCHEEHEEHGEHACACCEGCGGEDGFGAFDBFCAFBAFEEEHGEGFEBEEBHEFDECEEDEBGEDCAD,False +642,26.0,25.0,28.0,26.0,13.0,16.0,19.0,13.0,EBDECDGCAACBAHFACDCCBCDDHDFBDBDAHGAHGBHGBCFDEADGADGHFGBAHBCCDHBDFDFHAEEFDCGGCFCAFGACGCCFADBAEBGBGGBFGDFBFCAACAACECBBHBBGABGFCAHCDFGDCCEBCDACHBCAAEDEEDFEHEDABDACDAGDBB,False +643,14.0,19.0,17.0,9.0,14.0,22.0,18.0,8.0,GCCFBFFBEABEHDEBDGBDFAHFBHCBDEBDGBDHHFFGAFGCGHCACFBGGAGGFEGFCAFCADGGCFECECGFAGFAGACHAFHDCBBCBFABFEBCCBGFEAECDBBFFBAEEEEFG,False +644,15.0,27.0,16.0,22.0,21.0,27.0,27.0,18.0,EDFEFFDFBDGBEGBHCFHCFHFAHFGFFEHGEBGEBGABGCGEBGFFHADEDGEBFABGAEFEGFGGAGFDHFBHCBADAEFBCFCCHDFBEADEDBBBGDBDCACCFCEFDDFBHHAGHGGBGBEGCFCBFEGDAGDEHCEHEBHEBADHDHHDGCDGBAFBDCGAFGDBB,False +645,14.0,11.0,10.0,13.0,16.0,12.0,10.0,15.0,EEHEEHGEFGEDEDBGCBHHFHBFDBEEBEBAHBDGACGADGHEHHECDFHDFDFAEFACFBEBHEHAGDCHDCDGCFAAFAAGCDGCAAAHHFBCDBAFE,False +646,3.0,5.0,2.0,4.0,7.0,6.0,2.0,5.0,EEDEFDFHDFHGFHCBHFBEEEABHABFDBGCEA,True +647,17.0,19.0,20.0,19.0,12.0,18.0,17.0,19.0,HCFBAFBDFDHBCACEAFHCGGCAHBHHBHFECADGBGCDACAECGDCFDFEHBABGADGACGBEFHGFBDBCCBCFBDFADFGGFEGFHGFEBDDBDDADBFGCFGHECHCHHGGBECECCEBDEDHADHADHAFHAHAB,False +648,10.0,10.0,6.0,7.0,5.0,10.0,7.0,10.0,CHGDHGHAECAEAGBCGCEDFBGFCGBCFBHAEAFHDFBEHBGFAFFDDABDABDFBHFHHABHA,False +649,23.0,19.0,18.0,23.0,11.0,22.0,22.0,16.0,DFGDAGAEGAEDABBFDGADBHHAEGECAFDAEDACGBCGDCGHCGBCHEGACCAFDBFHBGGGDBGBFCBEGFHAHHCEDAEDBBAFAFFAFGAHCHCCDCCGBDEFHFFDBFBCFDCDDAAAGDEBDBBHBFHGFHFFHFAHGDGGDACDAF,False +650,4.0,5.0,4.0,4.0,6.0,3.0,2.0,5.0,DDHGDFGEFAECAFCDBCHEEAEEHHBACBHBB,False +651,29.0,15.0,14.0,25.0,15.0,16.0,23.0,19.0,GAFBABHAGGACGAGGAGHABDGFCGDEGEFDFACFBDAHAAHCGECDHFEHCDDEDDECGFDDFEDADAFDBFDBEGHFBAGBADBCDGAFFCEDEHAAHAACGAGDFDDFDAADCAFHBEHGEHGCGEBBHHBCDBCDHEBAEGGHGHHAAHAA,False +652,17.0,19.0,21.0,19.0,20.0,33.0,24.0,19.0,EBHGBHEFHAFCFFEAFEADEBHCBFCEFDEFHBGHGFDGDAHEGFEABBBBFBBFBBFAFEBDHBCBCGFEHACDCFDBGHGEFGACCFFFFDADGFDCFGEGHHGEHFFHEFHCFAGFBGCCGDCDDCGECGHAHEAGEDBCDEHDGHFGFCCDAAFAAFGAFDCGECGD,False +653,4.0,2.0,1.0,5.0,5.0,3.0,4.0,8.0,GBFEDEDGEDEADHGHHGHHDBHAHEFHCFAA,True +654,20.0,23.0,22.0,29.0,18.0,18.0,13.0,18.0,EDEBAEGHHFAHFBDDBGFBGDDABDABDADCCBBCEHGFCGFCDEHDFDGHDCBDHFDCBHBFHECCADGHGGEGBCBACHAEGEEFDEHDCHBEHFDBFCEACFAEDAFBGDBDDBDDBFDCFDCHDAACAABACGFCACDHHAFBAFBHEDCEBEEAC,False +655,7.0,8.0,11.0,11.0,11.0,5.0,11.0,11.0,CHBCHDCHBAHBCGDEGDACDEBAAAFBEFHFBGFEDEEAEEGDGGDGHDAHDHBEEGDECCBHCGCCGHCFHDG,False +656,23.0,22.0,23.0,10.0,19.0,19.0,24.0,14.0,FCGFCGAAEBHECHECHCGABAAFFEHBAHBCBBDEBEFDFADFGDFACFAFAHFBCEACECCDGBFEBFCCCCEGAAHAGEBGABCFBAAGFDFCEABEABECDGCGAHGHCCHBAFBHEEHCGBFGBAHBGGEGGEDBEDBDFGGGGGGACH,False +657,17.0,18.0,13.0,17.0,9.0,17.0,17.0,24.0,BDHBDGBFEBCHBDFBDHBAHBHHAAGABHACFFHHBBDDHHDHGFCFFCGHHBAHADGFDCFHCHCCBDFFGAFGAEEAGEHHBGFFGFAGHADHDCBDEFDECGAGADCAGCHGEHBEHFDABDGBCGAE,False +658,8.0,8.0,5.0,2.0,2.0,4.0,5.0,8.0,CEGBBGBHCFHBHBBABGEBHHGCFAAHADHAHGACFACFAD,True +659,34.0,21.0,21.0,17.0,21.0,20.0,30.0,25.0,HAFHDCDEGEEGAAGBGCBEAGEBGEAHCAHEAHCAHAAHFBHECECABCAHGGFGHHGEHDADFACFACFCGFCGFBBFAAHAAHBFFDAFDGFCAEAGFAEDBGBCEEFFFDEAGGADGCDFHGGHBCABCABCABHDGDGGEGGEGHEAHBDGBHHBCHDFAECGDBHAGHADABBACEFHBDEGC,False +660,14.0,30.0,12.0,19.0,8.0,11.0,20.0,13.0,DEBHHDCGGHGCHBFBFGBFDDFDDGDGBDBBABHDBHACECCACEABBAEBDBBGGGCGDAHCADCABHEFHBFDCDCGGFBGDBDBBGGBCGBEBBEBBHHBHFFHFAADGBBGBGADDFEAAGA,False +661,11.0,26.0,15.0,26.0,16.0,14.0,18.0,26.0,FEBHBBCBDCEDFABGAGEABBHBGCDGFDEBBEBBDBEGBEDDHHDHFBHEBEEGAHHDHHCBHCAHDHCAACEGBEGBDGBHBHDFHDHDFHECHCHEAHBGCFCFHDDHDDFDDAGEGGCCGDFGFAGFGDBBBHBDHFDACDCHFGDE,False +662,5.0,2.0,4.0,1.0,4.0,3.0,0.0,4.0,HCDFCFHCACAEEAEFBHABHAE,True +663,14.0,22.0,18.0,13.0,14.0,22.0,18.0,29.0,DHBHHBGHGDDFFFCBHCBFCHGCGGHHHHABCCBAFAEGBBDBFCFECFADFHBCHADBADGHDGCDACFHBFGFFBFGCFAAEACHAFHEEEEHGEHAEBGBGGBFCBFBGGBGAHDHHBECEHCHBFECFHAFHDCHDEHDEHGFHB,False +664,22.0,13.0,19.0,20.0,21.0,19.0,24.0,26.0,AACFEGGECAHDGHDGDBEHBGDGGCBEAGEFEAGBGGBFFBGGGGDCEEAAFFAHEBFEFACFECEABEFHGFHDAHCBHCFGDFHDAHGEHEAHEAGCCCHDAHFCEFCDCAFCGCHFCHGCHGCBGFBGHHDAHEAHDHHDHEEADEFDHADADDHDBADB,False +665,19.0,16.0,20.0,18.0,23.0,17.0,22.0,24.0,DAACFCEFCEHBFHAEHDBHBHABHABHAHCCGGCGCEDBDHBACCCCCAEDHEACEHEDGECGEFGCGDEFHCAHADFDEEDBECEACDGEDGFHFAEFAGBHHAHHDHAGBBFCGFEGHBHFDEFDHFHHABGABGEDGEDGEGGBCEBGDFGFFGA,False +666,21.0,15.0,10.0,14.0,9.0,13.0,18.0,9.0,ACFGBACCACCADCDGADGADGHBABGDFEDEGAGFADADDBEABDABEABAFBAFBGFGGACGBFEBFEHFHGACGCFEDGBGABCEHFGBAGFEDADBAFHHGHHDH,False +667,8.0,7.0,10.0,12.0,11.0,15.0,18.0,9.0,FAGEGGDGEAGDFCFFHBFDBGDFGBAGHCGFCDBCGBDFHGFHEACECCECAEFGCFGHFEDGHGBHFCHAEDAEDGDFGFGEBEDHAD,False +668,10.0,9.0,8.0,13.0,5.0,7.0,10.0,7.0,GFDGECCECCFHAGBGDBDFADGEDAADAADAADCGBGHBHBDHFGHFAHFACDEHBEBDDCGGCDFBB,False +669,7.0,12.0,7.0,12.0,9.0,2.0,15.0,14.0,HBGHAGHEGBCADABEEHFCCGHGGEGGCDGCHGEDGDBADBHDBGEAGAACEDDFBHBBHBDHBDHGCHGHDEEBHD,True +670,0.0,5.0,2.0,3.0,7.0,4.0,3.0,4.0,FGCFHFEDBHBBHFBGEBEEDEEGEHCD,True +671,5.0,12.0,12.0,3.0,8.0,4.0,5.0,4.0,BBCBBAECHCGHCHFCFCCBDBECBEBFEBCGHCEFGGBAGEAEEACCBDABD,True +672,11.0,18.0,12.0,10.0,18.0,18.0,25.0,17.0,AGBBGFGCFCEFCBHCADEBHCHDEBGGGGGAGGCGFHFBHDBFFAFHAEHFEFFAGBEDHHHHBBCFHAFCGCCBEHBEHGDBFEAGEHGEAGEAGEGDBGDCGDGGDFHEFEBBCBAGBEDHEFGEF,False +673,9.0,13.0,14.0,18.0,14.0,11.0,8.0,15.0,CGDBHCCHGBFGAFEEHEHCEHCACCADCDDCGBCDBHDHCBHEHABHEEGDFHDGACBAGDFEDFEDECDBDHFEHBEFFEBCEBDABAAGFHFDDFDDHB,False +674,8.0,13.0,7.0,9.0,11.0,13.0,8.0,11.0,GHHFHFCGFBEFDEDDBFDBAHFHHFCHEDGEHGCBDBHHAEGAEAAEBAGBAEFCFGCFAHBGEFECBCBBDBBDEFDF,False +675,1.0,9.0,5.0,1.0,4.0,4.0,4.0,4.0,BECBCFDGHHBEBBFBBFBCFBHGAHGCEECG,True +676,7.0,7.0,1.0,4.0,6.0,8.0,6.0,3.0,ECHEDFEAHHDFABGEBEABEDGFAGBAFBAFGFGGFABFDB,False +677,14.0,18.0,19.0,11.0,14.0,16.0,16.0,25.0,EEHFECBGCECHDBHGHHGHHGABBDFBDFBAFHAGDABCABFHHABGAEGDBHHGHFFHDFEDFHFGACBCCGCAAFFAHACDGCDBCHBFGBHEFHAFCCEBBDHCHFAHEGHEGCEHCECCHGEGBECBD,False +678,9.0,12.0,6.0,10.0,11.0,11.0,13.0,11.0,CDEAGGDGGCGBCGBAGBGEBDCAFGHFGBFEHEEACFAGFDEFGBHHFHHEHFCGDADHHDHEDAADFBFBBFBEEHEABBD,False +679,27.0,20.0,25.0,20.0,31.0,18.0,23.0,23.0,EFHEDHDDBECBDAFEEFEEAADGGCGEBGADEECEEFEECAFCGEGGBFCBFABGACDAEHBHCFGCHGCHGCFDCBHHBEABAHBABAHEAHGADGCCFECDHDFAGECHAFBADBGDBCABHADDBHCEHCEHBFHGFEEDCDHCEECGCDBCAHGHBGEAGEAFFAFGAEEAFAHGEHGDACD,False +680,27.0,26.0,27.0,28.0,20.0,19.0,14.0,25.0,GDCFDCFHCBAEGAFACFAGFDBEABDBCAHCGFFFCFBBBADBGFCDACDGDDHCEHAEHBFGBHECDEGAACBHCHEAHEFCGACDBHDACGACHAHHAHDEHFCBBABBABCHBFDCGBCHBCHFDHEEBDEHEEHGEFABHAHCAEDBCDBCDEEDCBDBHAFAGEADDADFADFDDHGDEC,False +681,3.0,1.0,1.0,3.0,4.0,8.0,7.0,1.0,HGFEDDABGFGGFGFFGCGAFDAFEEFE,True +682,15.0,12.0,11.0,14.0,15.0,27.0,23.0,14.0,FHFFHFCHGEDCEDGABGDBGFFGFHGDDFFDGCHECAEGEBCEFCEAAAAGACFAGGGBEGBFBAFBAGGAEHAEHBDGGDFDAHGGEGGHAFHGCEFDBFEHDDBGFBCFAFFEHFCHFHDFCFFDEFB,False +683,3.0,2.0,5.0,6.0,4.0,4.0,5.0,2.0,GGFDFADFADECDCGBCGEDHEDHGCBCAEF,False +684,13.0,18.0,21.0,19.0,20.0,13.0,21.0,11.0,FEEGGCAGBEGFECBEGBDHBDCCGACGFBFEHHEHBCHCCFDCDDCEACEAFHHFCFDEBBGBDCBDBADEDEGCFDHABEDGEGFDCFECDEAHEDGEAGFAEAAGHADABDBGCGGBGFBDCBDGBCGECGHC,False +685,10.0,7.0,12.0,11.0,9.0,18.0,8.0,9.0,HDHAGFAFFAFFAEBDCBDBEAFEACEACDGDDGFCHFCBCCACHGCFFCGDEFDFHEFHDCBEHGEGFFDFAAFBEFCDGHBH,False +686,6.0,12.0,8.0,11.0,9.0,7.0,20.0,10.0,BCEBCDBHAGDAGDHGDEDAGDGHBEHDDFGDGEDAEGGGCEBCBGGGCHECBFHHGGFGGFGGHGAHFBBCBECBHABFDEF,False +687,12.0,20.0,16.0,25.0,15.0,20.0,20.0,33.0,DFDHAGHAEHBHBFCFFDHFDBGGCCBDABHGGHBBCBFCHCEEADDACDFCAFBHBHDBHFBADGHDGHDGFEEBHHGGHGHFGDFCDHEEHCECCHDBDAGDABDCBFHAGEAHEHHEHFDHFDHFDEFDCCGBCHEDHBDGEHGBBGFDHAHHFEFGG,False +688,3.0,9.0,2.0,3.0,7.0,7.0,3.0,4.0,CFEHFBFBBEDBCHAFABFEBEEBDEHFEDFHBGGBGA,True +689,15.0,26.0,20.0,34.0,29.0,23.0,27.0,17.0,GAAGDABHABEGDEBDFFDHFEHFBFCBGCBCCDGFDEHDCFDBHEBEFBEBCGCDGADBDGGGAAFCEDCEDBHGBDDBEDFFGFEHBEFFCAHCHHGFDDBCDBDFEHFGAFHFFDBEABEFBGFAGHGGEECCGABDDBEEBECBEAGCHGDHGDEDHFDHDAECAECDEDGEDEBCEDDGGDEGBCG,False +690,2.0,5.0,5.0,7.0,3.0,8.0,3.0,2.0,GFGFFGFDHHAEBCCBCDFCDEADFDBFDCEDBBF,True +691,11.0,14.0,14.0,3.0,13.0,5.0,13.0,10.0,ABGFGEEGEEGEHAHBCHBDDGHBBABACBCEEGECGECGHCABCABCHBEGAEFCCGBFGCAEFGECBFHACHACHDHBGBA,False +692,17.0,27.0,23.0,13.0,20.0,16.0,15.0,12.0,BCCBCGFCGFADAABEDHEHBEADCFFEFFCABCGBABBEGBADBABBFCACGEDBEBBGFBGHBGHDEHBEHBCHACHFGEECHGFHGCCGECGDBBDGAEADFCGECDEFEFCCFAHFEHEABAFCCECEBDDBADBABBC,False +693,27.0,22.0,19.0,22.0,14.0,28.0,28.0,25.0,FCDFEDBEDFECFBHAAHEACBFDEGDCGFFHHFADGABFAFAAGGBHFECAECAGCGBDGBDHBHCBHFEHBBAFAAFAFFCHFGGFHAADCCGCCGBHGDDGFDGBDGBABHAGFDBFGBHAEFFDGFDGCAACAGGHDGAGCDEHDHBGHEFCEFADHEHABHAFHEHHDBGGBFCBGCHAD,False +694,18.0,13.0,19.0,10.0,11.0,15.0,13.0,6.0,GDGHAABAGDGHFBFGBCGACGAEAFDAFDECHECACBFCBACBEBDGBFACEEBEDCEACEBBDDBGFAFFDCFECDHCACCGBFGHGCEGCAAHAAFCAFCFF,False +695,10.0,11.0,11.0,10.0,20.0,12.0,15.0,5.0,DBDBFDEGDBGEEGEGFAAEGDFCFECEEAEEBHGGHCGHCFACGHEGEEGAEFCEFBAFBAEEACCGFDBFCHACEDFADFGBGCBDEBEGBD,False +696,11.0,15.0,9.0,15.0,19.0,14.0,16.0,14.0,BBEABEBFEDFHBEDCFCEDEFDECCEFGFGBHGBCGHGFHEBDGBFGCFGDGDACDAFBFHBHGECGEHDEHBBFDEEDGEFCAAHEABEHHEAHEAHDAHDGGDBGFAGAD,False +697,4.0,10.0,3.0,4.0,4.0,9.0,13.0,9.0,EFFBHHHHHCADDEGDFGBBGHFGBBBBHBACEHCFBEGDGGFGGFGAFGAGHFGB,True +698,8.0,6.0,6.0,10.0,3.0,3.0,10.0,9.0,CHGBHGEHGAAGHDGDAGDBDHADHBDHDAFACBCFBGEHCEFCGABGAGDCDDH,True +699,23.0,20.0,26.0,25.0,24.0,29.0,20.0,24.0,CDBFFGEGEACCACDGBDCHACHACHBGDBCFBHFHHFHHAGHAGHCHAEEGCEHEEFFCDFDDFDFAAEEFEEFBEDAEDFGDFGDHHDBCBBCEBEABADDAEDGGGCEHAGBEFBCFDHFBEFADFDCEHFEHFHADCFDAFHAFBFCEDDBCAHAACGCBFCDHBFHDAGFEGFGGCCGCBBCAHGE,False +700,29.0,20.0,21.0,24.0,24.0,23.0,13.0,26.0,EBHEBHBADGAHAAEEACGAFAAFBBFCHDBHAGCDEBDCDDAHHBCEAAFHAFCABDDEDEEDFHDFCDFBEGCFGEFAFGCHGDHFFEFHEDDEADBACACEFCBHCEHCAAEAECAEBFDAFHAHGAHGBGCBDHBDABDHBDHADFGEBABHFCFFAHFDECHHCHHCFCGDEGEE,False +701,3.0,7.0,7.0,3.0,6.0,6.0,4.0,11.0,CEFCFHGFHBHEAHECHEBBAHAEECHCDHCFFCHBGFBDDBGHBGH,False +702,9.0,6.0,16.0,15.0,12.0,8.0,10.0,9.0,FDCFDCDAHDGHFAACBCHDEHEGDEDDFDDEGCGCDBCDEAFCBCCBCGACGACHHEEHADDAEDCECFECFAGGBBEHFGHEG,False +703,6.0,1.0,3.0,5.0,2.0,9.0,6.0,6.0,DABEAHCFGGFAGFHHFCFFHDFHDCGFFGDEGDHAAA,True +704,4.0,1.0,0.0,2.0,2.0,1.0,3.0,0.0,BGGAAGEADEFDA,True +705,18.0,19.0,12.0,21.0,25.0,19.0,18.0,24.0,FDAHBFHDCHACHAEAEEBDDDDDGFHHFEHDDBDAAAFHAGGAGDABCHGCEGCFDBGCBEFHFDHFHHEGCFABHEBHCAHBBHEAEEAEGAEDEBGFCDHEEHGEFGEFBDFEGFGHFDHFBHDBGDACBAFBDFEHEECBEGBDGAEGEHBC,False +706,17.0,12.0,10.0,18.0,25.0,13.0,22.0,21.0,AGEHCDCDAEDAEBAGGHGGHDCHEHEFCEABEGBEBHAGABHABFFGGFGAFGDBGAEDAGFAHEEBFFAEFBEHCEFDEFEHDCHDCHDGAEGAHHFHEBEEGABGDHGDHBDHDHGCEDCHFCEEDDEHDGAGGE,False +707,18.0,24.0,22.0,26.0,29.0,18.0,27.0,19.0,HFHHGDEGFHCDHCEGFEGBDCEDEEFFBFCAEBBGABHADAAGABFDCGCBHABAGHDEDEEHBAHDAGDBGCBDHHDBEEGCFGCHCFHBFDEGDHDFHAEDAGDFGEFCEGGEBGCCCCECGECGCHACEGCEFCDFBDFBGBEABECBEBBGAHGDHDDAABGGBEGAEBEDFDDFEDE,False +708,20.0,10.0,10.0,16.0,13.0,13.0,19.0,23.0,FFHDFHCCACGGGHEEHDGGAGEAGHAEBAHDGHGGHBGAGFCBDCDDADDCEHADDDHBAHBAHBGGAFAAGAGGBGFHAHHDHGEHEFHCFHCBACEDBDDFCEFAHFAHEAEFHFABEDHE,False +709,5.0,8.0,2.0,9.0,7.0,8.0,16.0,8.0,CGDAGDFHDGABHDEFFBFFBEDGGAGGCEGHHGADEFDEDHEDGFBGHGGHGGBGBBAHEFB,False +710,2.0,0.0,1.0,2.0,0.0,3.0,1.0,3.0,FGHDDHAFHAFC,True +711,11.0,11.0,7.0,14.0,11.0,15.0,19.0,23.0,DHDDADGHBGFBGHHGDGAHHHGHHGBCEDCHDHDECGGFDDAGBHGBGDAHBFFBFFCHFCFFHBFHEHHGAFGAHGHDCDDAGEHGEHBFHEGBAGFAEFCEABEAEEF,False +712,22.0,16.0,19.0,9.0,22.0,12.0,19.0,16.0,HDGBAGAAGFEEFADBADHGCGCDBCABEACGHGEABEAFGHFEHFGHFGHCGEFGEFHHACDAHFCGECEABEAEEBBABHEFEAGEDGBCEHDEADCBDABCHCCHBCGAGHACEACHFCEEBAEBAGBGFCC,False +713,10.0,16.0,20.0,25.0,19.0,11.0,23.0,14.0,FDCDDBFDGCEFFEBBEBBFDBHCFAAHGDHDBFFGFDACDAEDGEGGDCADCDDGEDGEGCEGDADCGDCBBHEBDECEHCEHGBHACEGGDCGHHGHDGCGGCGCDHHDECCEBEEDABBAGBGEAGEFDHFBHCC,False +714,7.0,8.0,11.0,9.0,14.0,8.0,8.0,14.0,AADAFBHGCCGCDHHFHBCHDCHDEHEEBFBAFHDGHDHHEAFEFCEGDHBEHCCFCHBBEDEEAFEAECGECGEGDBG,False +715,4.0,5.0,2.0,4.0,4.0,2.0,5.0,7.0,BEEHHBHHCDHCGEBGDBDHEFHFAAGAAGBDG,False +716,2.0,4.0,4.0,2.0,5.0,4.0,1.0,3.0,GBACBHFFEFFDHBDHEAEECECCB,True +717,15.0,12.0,19.0,9.0,14.0,21.0,18.0,23.0,DBHAHHEFBFAGHAGHAEHFEAAGCGHBFHBAHDCHCCDAGGHGFDAFEEEGECHCCEBGDAGCAGHGFACDHBDGBAFCFFCDFCFFCEGCBGFBCHBHAGHFHCBHAFHCFGCEGCEHFEBEEFFHDFH,False +718,21.0,29.0,17.0,17.0,19.0,12.0,14.0,21.0,BHBBDDFDBFDBDHADHBCABAHFADGBECCFDBADGEHHBBEGHEDHCHEBHBHHBEEBCABFBBFBFDAFABDGCEGCEGBEACEBBBBCDCHGEDEEGGHGAFGABGABAAHAHHAHGAHGEHCDCFDCFEEDEBHCCCACAAFABE,False +719,15.0,18.0,17.0,14.0,22.0,18.0,20.0,22.0,GGECFCHFHBEHBEDBEFBEHBDHBGAGFAHFAFECFDFHGFBGDEHECDGCAEFHEFBDGHDGDBGBBGBHGCCGCCGCHHEBBBBEEAHHBFEACADDACGCFEHFEHFAGAHGEHFAAFCHDCEGCEFDEGBHGDHEECAADA,False +720,4.0,4.0,3.0,2.0,1.0,3.0,4.0,4.0,BFBBFHBCHAHDAGEAFCADCGGGH,False +721,22.0,14.0,33.0,22.0,22.0,16.0,25.0,18.0,EGACBDEEDAADHAHBABBAEGAEGBHCBADGFBCFBAACFEEFEDHBDCGECHHHAGEAFECFEGFGAFGHCGAFGEFECFGCABEEGGDAGDCCHCCHGDEGBEDBACAHDACCCBHCAHCHDGHAECDDCDHCFCDAHHCECGECGDCGFGECCCFCCDDGDDGDFGBF,False +722,15.0,12.0,9.0,7.0,14.0,11.0,9.0,13.0,HFDHFEHEGDBCFBCAAHFAEFGGDBADEAFEAHEAHFBGFHEAGEDGBBABHGEHGECCABCEHDBADCFEEFAHFGHEAHACCABCBB,False +723,25.0,27.0,19.0,19.0,29.0,24.0,29.0,27.0,CHBDGEDBEGCHBAGECBACBGCEACAGCAGEFHHHGHAGAEDHGCGBBACHDGDAGDAGBFFBGFBDFEAFBABACDEFFEAHHAEHGHHBFABFACHHHEBGBBEABEAHEDGEDBFDCHDBGGEHHEGHFCHFHAFDAFEGGHGECDFGGBGCFEAGECBECBECFEAFEBFEHFEHBDDAEDADDFCBFEBFGHG,False +724,7.0,6.0,4.0,4.0,2.0,2.0,7.0,4.0,BACDABGAGDBGHFGHFCHAEGADGBEGBAADCBHC,False +725,13.0,14.0,14.0,9.0,9.0,11.0,7.0,5.0,ADEDDFDEGBCACCABCADGAFGFGAEGAGBAFCFFHBBHCBDBFEGAEDBDFHCEECEAFBAFHCFCCDBCABCABHBBEC,False +726,6.0,1.0,2.0,1.0,0.0,2.0,3.0,0.0,ADAAGACFACFBGGA,True +727,22.0,23.0,26.0,27.0,23.0,28.0,17.0,22.0,ECCBCCADCDDGGAHBAHFHCGHEGHCAHGHHGBEFCAFBAFHDFAFCCBACDGCBGHGEAGCDECFEBEEDFDFBHGBAGBADFEDAHDACDGEFEEHGEHFAHFAEBDBBEBFEDAEDHDDCFDGDABEGDFHBCBFDFFACFAFHEFHABDCCEABEFFHCFBFFBFCBDCBDCEDGDAHDCHCE,False +728,0.0,0.0,3.0,1.0,3.0,4.0,2.0,2.0,CEHCFCGFHDFEGFE,True +729,17.0,19.0,22.0,26.0,19.0,16.0,18.0,23.0,GFHGAGFACDAEAGFDCBCCBCBBGBDGEGCEHDDADHEDBADHDEFBEDBDGBCGAHHAEAAEBDGDGGDGABBECDEFDEFHCAHBDHBHGGDFFEFDCCDACBAHEABCHEEFCEFHGFHDEBGEBHHHHCFHEAHBAHCDDDDCGFCHFCHCCFCD,False +730,10.0,12.0,10.0,12.0,5.0,3.0,7.0,9.0,GGBHAHCBEBDABDCEDEGDCGDAFAHGAHDADDACHACGECADHABCCGCBBCBBHHBFDEHDBDFB,False +731,8.0,9.0,15.0,9.0,17.0,19.0,15.0,6.0,BHGBCGBCDBCFBCBACFAFEGFECFEGFGCEGCGADEFECHEDEEFFEFFGFFGDFCEGCACBAFADCGEEGDBADFAHHDGHGFEEDCEHFFBGEC,True +732,15.0,25.0,16.0,23.0,8.0,23.0,16.0,19.0,CCGCCHDFHDFABAHDHGDBFDHDDBBDHBGHGFDDFGGHEHABDFCHFAFCACBBDDBDFBDABHABGBEDBEDAFCFBCFGEBBHCBABGABGHBGHFGCFGCFGEBEFADCHFHFFCDDCHAEHBDGADAADGFCFFBFEBH,False +733,26.0,12.0,25.0,16.0,6.0,12.0,11.0,16.0,DDEFFEHBCBCAGCHGBHAAHCAHAHHBHHGGHCFDCADCADABFCCGAFDAGHCCCACFADFADAHBGBCFFDBCHAFAAEDEBAHBAEFAFBADBDDADCCCCCCCACCGCDGADGAEAHGH,True +734,24.0,26.0,16.0,18.0,21.0,14.0,24.0,22.0,HGDGADCHDBBAEBDEBDEBEEDECFBCAGCBCHGDBGEBDEBEEBDGBGHHFCDDHGDAGHADEBDAAHBGBAHAEEGEBGEBAACFHCFACFHFAHFAHFDHCBEAHEHBCHAHAEDGFBGDBGFBHBEGDGGACEACACBACFAGGEGBFBHAGHAGCFGHF,False +735,22.0,22.0,29.0,19.0,27.0,26.0,31.0,18.0,FACFCCFCAHCGBBDADAGDFEEFAEFAHADEGDACBFCBFBHGCGGCFFBGFGFBBHHBCAADGCDECGGCGGCAGCEGEGGDDGAGHAGHFCFCEGDGCFFBDEBDFBFEEEHEHBEAEEAEEAGEFDEGDBBEHGAGFDGEDHBCHGAAAAABCECCECCHCCDFHBFCEGEDGFBFCBFHBFHDHHCGEB,False +736,3.0,2.0,3.0,3.0,1.0,1.0,2.0,0.0,DCBDCBGCAGADEAF,True +737,25.0,20.0,13.0,20.0,9.0,15.0,15.0,17.0,BBCBGDDHBCECEDCBDHGDAGDAEAACDBCDAAHFAEFDCFAFBAGAGBABHABDABFAFFDDHHHHBFHDFGGHDCFGGHHGAAEAABCAGCBGCEGABCADEBBEFBDFHGFHDFHCFHAADEBDGADABH,False +738,15.0,21.0,15.0,20.0,23.0,14.0,16.0,14.0,HBDCBCCDFDDBDABDABDFDHHBEGEFGEFGECGECGECABBEGFEGFGFBABDGBHGBHCAEBBEBEDDDBHDAFCACCEBHGGDEDAEACFBFFBGFGEEHHEHEAHADFCDCAFCDEBDCDEGEHGAHAHEABE,False +739,6.0,4.0,7.0,3.0,11.0,9.0,13.0,4.0,CEEGFEGFDGBBEFGGDEDHCCEAFEAFBAFGACCAGAFEBFEGFGCHGEHGECGHG,True +740,18.0,18.0,17.0,21.0,22.0,23.0,24.0,19.0,CHFCHDGHDGBDCFEEFEDGHDAHDAECAFGFFHFCDEGAHBDBEDHEGAEGAEFBEHAEHABBAHFGECAHBFCDFDEEDEGDACBFHDFBGFGFEEFAEFCFBCHBDFAGGAGGAGBAGBEGEGDDGCDBBDBGEFGDDGHBBECHFCHCCFAGHCFCAH,False +741,9.0,8.0,14.0,9.0,12.0,8.0,10.0,8.0,HHAGBAGCACBHFBHFDEADGBFGCDABDCEDCEFABGECCEBCDGEEEEECECCFACHAEFGGFCGFDGDACDHHBH,False +742,12.0,15.0,13.0,8.0,14.0,16.0,4.0,12.0,AFFFBFFBCEAFAAEBHDAEAHBCHFCHBDHBFHBDEBAHGFHFBEGCFHCEAFEAHABDBEDEEFECHECGECFHCFCCDCCGBDABDBBEFA,False +743,10.0,6.0,7.0,8.0,13.0,10.0,9.0,5.0,AFAAEBGEBEECEEDFCGGHDGDFCFGHFBHEHDDAADEDDECBEFBECHCGAAFFAFEAGEAGFBGC,False +744,4.0,4.0,4.0,5.0,4.0,3.0,5.0,8.0,FHDHHGAHBHDDHGDAFEACEACEGGFHBCHBCGEDB,False +745,5.0,2.0,6.0,1.0,2.0,4.0,4.0,5.0,CHHCFFGFGAAGAHGCHABEACEHCBFCD,True +746,6.0,7.0,9.0,8.0,5.0,5.0,6.0,0.0,GDGGFGCEDBEDACDCCFACFCDABDACAACBEBBCFBFEEGBDGD,False +747,23.0,21.0,27.0,20.0,27.0,21.0,28.0,26.0,DEADBCCGHHGHDBADBADBEEBFEBEBGGCAEDAHDFDGHEAHEAGEDGEFGBAGHFHECBCAEEBEGFFFHHHDHHGACGEEDCADBAFBHGBAFBDFCDCBGHFHAFCCDCGACGAFGCEGCHBBDGCHFDAFGGGBHGBHAAHCAGEDCCGCCHBCHFFHEFCEFAAGACGCEECECHEBHEGEDFEDF,False +748,3.0,5.0,1.0,5.0,3.0,2.0,3.0,3.0,DBGHEAHDADDADECFEGBGHBFBB,False +749,11.0,7.0,13.0,10.0,10.0,9.0,18.0,6.0,AGEGGFDHECGGCGBCGECBCCEFCADCGHCGEGBEBDECGGCAFHDDHGDAGDAEAEFDGADGAFCCFBAFEFDGFAGBAHBH,False +750,19.0,21.0,8.0,26.0,26.0,23.0,18.0,20.0,FEHFHBCHBCHAAHDGEABEDCECBDDAFFAFDGDHCDEGDFADCHDEDEEGHAGDFGCFGDFAEBDFBAGHAEEAEAAFAFBAFBEBBDDBDHEFHEHDEBDEFEBBAAEAEGBEDFHDHGBEGEFBHCHFBHEGGEFGEFGDFHFHGDBGDBFDBHDGA,False +751,10.0,15.0,9.0,6.0,11.0,12.0,12.0,15.0,GDEEDHHBBFGBHHBEHFHFBDCEGGEGCBCCAFCEFBECHEHEBHBAABFABFABFGFEGAEBDHCGHAGHAFCACGAHDHFDHGBBGF,False +752,16.0,16.0,21.0,19.0,22.0,24.0,24.0,17.0,HHEEFGDFCDFCDFGHFHABEGECBCGBCGBFGDFBCBAFFGCAGCAGBAGHGDHDDHGDHGEHAECADCEFFAFFDEGBAGBCEBAHFACCDCBGEHDEGAEFCEDBEHFHAEDBGAGFECFGGAGGEFHDHECHECFECFCBDCGABDBHDFEFFED,False +753,5.0,5.0,9.0,7.0,8.0,5.0,5.0,7.0,DHCDCBFEBACFGCHGCHGEDGDDEDHAGEACFACEAHEFCCFBDHBHBEE,False +754,1.0,1.0,2.0,5.0,0.0,0.0,2.0,1.0,GGBCDDCDDADH,True +755,3.0,4.0,2.0,11.0,7.0,7.0,7.0,3.0,DDGGDGFFEFFGGDECDEDFEDFBBHBGFBHDAGCADHDDEAEE,True +756,13.0,13.0,9.0,10.0,17.0,10.0,13.0,12.0,CGAEDBDFGGHCGBCFAEEAGFBFFBFFBEGEEBEEHEECDEGACGEHAFGADHABHAHHCGHFGHEHEAHGDDCAHFAEBAEDCBBCBBGBDEDDA,False +757,8.0,8.0,4.0,5.0,4.0,3.0,10.0,2.0,BDEBGHGGFDGFDAFCGGCEBBAACEDCADHABGGBGBAABGAE,True +758,26.0,19.0,23.0,17.0,12.0,22.0,20.0,22.0,DDGDEFCHCHHDHHCHGGHDBAFBFGBFEBCAFCAFHFFDCCDCEACACBFEGGHGGDFGDHCBGAFCAFEDBEAEEBDFGDAGBHBHHADGCDFCAHCHFCGFCGHCBHABDABAACHAFAAHCBHBFABFAGFDBFHBEECGAGAAGFAEDABACCEGH,False +759,4.0,1.0,4.0,4.0,4.0,6.0,8.0,4.0,GDFGAFGDGCFGCFCAHAHDFHEEHEEGDGAFGCB,False +760,2.0,2.0,0.0,1.0,4.0,1.0,5.0,1.0,ABEDBHAEGFGGEGGE,True +761,21.0,26.0,28.0,30.0,24.0,24.0,21.0,23.0,FDCHDHHDFHCCGFFAFAAGABBDGBCGBHGEHFHFBCEACEHEHBEABDBBABAGBFFBHDEEDBGFCGFCGFBBCBBDBGGGCDECDCFECFEABGCDAEHEHBEDDADFADGAEEAEFDCFHCFBCHBCHAEDDEBGEDGFHEDCBACDGFFCEGCDACABEGCDGHEECFCFHDFBDHADHADHACGDCDDHH,False +762,24.0,12.0,13.0,17.0,17.0,14.0,9.0,11.0,CEAAEBDEFDBCCBABBACBDBDDADGCGHAEHAEHBEFAEFAFCACHBHFEHADHFEFAGFGCDADDACDEDGEBGECAEBFEBEADGACFAHAACAAEADDFFGAFGCDHDHEFH,False +763,6.0,8.0,13.0,10.0,5.0,9.0,19.0,14.0,HGDFBDFGCHDCBGCEGCEGHGHHGACGFCAEEHBBGDHGCCGFAGHADHBCGDDBEAFDHFBHFDGCAGCGFFGHBGHCGHCD,False +764,27.0,23.0,30.0,22.0,19.0,28.0,33.0,17.0,AACCCCCCFBCDCCGCFBEFDGGDCGFCFFCAECBGBFCBGEHDEFGHFGHACHGFAGEAFFFCHFDGCHGDGCFGCFGCAGDBFFBECEGCGGBGHBDAEDABFABFDBDDBDAADGHHFBAECEBHAHHEFADFADFACAACGECEEAGEABADBDHEGEDGEDBFAHGAHGAGCDFBAGBGFFDCHBHEACGGBGB,False +765,18.0,15.0,16.0,11.0,14.0,19.0,16.0,15.0,CEFGFFADDDDCFAFGAFEEEAEHBEHCECAEBAECABHACHFCFGBGGBDABCFFFGFHGHGDEDABBABBAHFACGDFGDFGCBEEDFHACHGCHGBHFEGFAACECDGCHGBHCBHBAHAF,False +766,2.0,0.0,3.0,2.0,3.0,1.0,2.0,7.0,HHEHHCCHDGHDFCEHAEGA,True +767,17.0,7.0,6.0,11.0,18.0,9.0,7.0,8.0,HEEBEFBEBEEGHEFCEACFABFHBGEAEAACAADAADADDAFABDAGDEDAGDEDHCHFABEGDEFDEAEECEGHHHFGFAC,False +768,7.0,8.0,17.0,12.0,13.0,9.0,9.0,18.0,EBDDBCDHEEEGCEFDAFDABCBBHFGHGGHDCHFEHFAHAEHCFHCAHEHBEGECHEGDECCCCDCBHCGHCBFGECACHAFHDCDDHFDHG,False +769,20.0,21.0,9.0,15.0,21.0,8.0,21.0,20.0,HEDAEDGBFGHEDHEDHEBCGAEAAFAABHDHAEHGGGBEFDFFAAEAEHCHBCHACDBFGBGABHBBEBBAHBHHDABDAGDHEFEGBGGDCGEBGCHECHECHGBEDBEDBAAFGADBAGAHGBGDCGEEGEH,False +770,21.0,9.0,20.0,15.0,18.0,14.0,11.0,20.0,AGHAHEGHACBCDEHDEHEECGABBADBFCHFEABCBDEAGEAFEAFECFDCHDBDFADCAGCADCHDEADAAHFABFEDCEGCHFHHCEACGDDGHFGAFGAHHHECAEHDHHABCEFCHFCGCCEF,False +771,4.0,4.0,4.0,6.0,5.0,8.0,8.0,13.0,HGCHGCEBAEDFEDHAHHGEHDDBGDEGBHGFHGFCFFCHADFFBHGAHFHH,True +772,4.0,7.0,15.0,14.0,7.0,5.0,7.0,12.0,FCECCEHCHDDHEFHDDAEHECCGDDBDDBEDBFCGHHHBHHBCABCHBCDEDGCHFDACDFCDGCGGAGC,True +773,15.0,15.0,19.0,12.0,10.0,13.0,9.0,11.0,CDFCAAHAADAADBHCGEAHFBGCBCCEGCDCCDEAGHAGECHFHFFBFBHFBADCADEHBECBABBHFECAGCDDCFFFHDFHDFAEGAEGBCCBCEDGBBCB,False +774,17.0,15.0,18.0,13.0,14.0,14.0,9.0,11.0,BDADABGFCGHCGAGHAGFFDCCBAGFHDFHCFHCBACEACBAGBACBECFEBGABFBFFBHHBDEEDEAHEAGFDEFAFFBDHBECCCCDCEACEHCEAADDCBAEDDEH,False +775,12.0,10.0,12.0,10.0,14.0,18.0,9.0,17.0,FFDFGDFEBAEBHFHFFBFCBFCBACEGDDCHCHDGBEEAEHAEBACCCCCAHEAFFFFFHGBHDAADAHEFHGFHEDCAHHADHGFGCHGFEEHDEHBEGB,False +776,15.0,9.0,14.0,7.0,14.0,8.0,10.0,14.0,FGGCGFEGFEGEBBABCCDCHEHHCHGFDGAEHCEFCEGCAACEACADHABADBFDCEDAABEACDGCHHCHAFAGHEHBEFEAHBAHBEH,False +777,3.0,5.0,7.0,4.0,6.0,7.0,4.0,2.0,ACHDGDFECAEGAFGEBDFBCFCCFHCEECDBGFBEFB,False +778,13.0,16.0,17.0,23.0,18.0,12.0,11.0,15.0,HGEDGCCFHBDHDDECFEHAEBAEBHDCCDFCDCHGHFGHAABCAFCGHCGCEFFEBAEBABBEHBGHBFFDDGDAEDAEABBHBBHEDFEFCDCEDCEDHHCGDDDDDAGFEBBCDDADCAEEG,False +779,0.0,0.0,2.0,3.0,0.0,5.0,2.0,1.0,DCFGFFCDFHDFG,True +780,4.0,14.0,9.0,15.0,13.0,16.0,18.0,13.0,GFHBCDDGGEFBDFGDFEDHCBBGEFEAFEHBDHGFFECCDHGHCGBBGBEDHDDEDEEDBCFHGDHGFHGFHGFGGFGBFGAFHCDCAECAEBBEDBGFBH,False +781,14.0,11.0,9.0,17.0,16.0,19.0,16.0,13.0,AHAEEAEBDCFCAFEACDFGBGHHFBHDBFDCHDHHEHFDGFAFEABDGEEEFHFABFCGFGGBCHBEGBHACEADGACGCFGBFGAFDAGBAGFDHEDEEDEFDEFDGHDGDDF,False +782,17.0,30.0,15.0,20.0,20.0,24.0,22.0,25.0,GBEGHHGHFDDAEABGCBGDDCCHFEBFGBGDBGDBGCAAFGAFDEFGEFEFAEFACBGEBAEBHBBHBCHEHHEAHDDCBCFDADDHDGHFEHBHFBDBDHAFHFFHGGAFCFGCHEEHEDFAGBCHBFGBCGDCGBHBBCFBDBDEBFEFHHCBHGBEBAEBHEFAAFDAG,False +783,18.0,12.0,19.0,16.0,8.0,23.0,23.0,21.0,CAEAGEACHFBBCABCACFADGBFCCFGDFGFBGHEGHCCHABHGBHFBGEAGCCFDAFDCHBGHCGHDFEGEHGEHFDHBDFAHFAHCGGCGDBFAGFHHFHGFDDHGHFDAGBHFHEDDDDCCGCCGADFAFGAFAAF,False +784,26.0,24.0,29.0,15.0,21.0,16.0,22.0,14.0,GEEGAEGABFAFGEBBHCCCGGBHGBFDAADAAGAFGBEBBCCGCAAHAAHDBEEBGEDADDADDAECAECBEBHEFFADBCGECGCCDCGACBACFDCFHFDHGHBBHDBCECEGCBGEBCEFAECCCHFGECGCBACBFFBGFHCECAFBAHBHHAFDAGDECAG,False +785,1.0,0.0,2.0,2.0,2.0,6.0,1.0,1.0,FFFEFFEDFCDCGAH,True +786,20.0,28.0,18.0,25.0,30.0,17.0,20.0,19.0,ECEDCEBGECGBDDAGEBEEHHADHDECGEDEEFEADEAFEAGDBDFCEFBDHBHAGAAGCAGCHHCHDBDFFEECADBAGFCBBEBDEHHEBHFAHFBCEBFEGEHADBDHBDHCDBGDBHDCGBFEADEADHAEAGBBCBACEACFDCBDHBDGEGGEBGEFGBFCBGHFGFFAB,False +787,5.0,3.0,2.0,6.0,9.0,8.0,2.0,4.0,DAEDAECHGCHBEFFEFEDFEDADHEDAEFBFABFHFEG,True +788,5.0,9.0,7.0,1.0,4.0,3.0,1.0,5.0,EBABAACHBEHFACBBFBBEABCDECHGCHBCHFC,True +789,12.0,4.0,13.0,8.0,13.0,16.0,10.0,11.0,ADAAEBAEGDFGHFGEBGADFAFFAFFEFCECEEFEGFEDFCCECHHAFDCFGHEHBBFAGFGHACECGHCDCCHCCHDFHDGAAEH,False +790,6.0,10.0,8.0,9.0,9.0,8.0,9.0,13.0,CEAHHCFHCFHBEACFACDBGDBEHBGGCGGAFDHFCHFEHBABBHDHGDEAHGBEBEGBEDHEDGCDFHDF,False +791,8.0,14.0,12.0,15.0,11.0,8.0,8.0,8.0,EBHEBDCADCAGCABCGDEADEAEECBEDADFEHECHDBHGEGCFDCFBBBHBBDGHDFFDFFGBGHBACBFCHGCDCDDEBDA,False +792,10.0,22.0,18.0,14.0,21.0,20.0,16.0,23.0,DBGEHGFDGFECFHGFEGFBAECAHFHECBABHGFACEBDGBCGHCECAEGBBCDBEGEEGHEAAECGBFHBFHAFHCFBCDHCDHDBHEAEEBHHBCCBFHBCCBHCEDDEDDEFFHHFHFFHEFDAGBFEBHCBHDBFDGGG,False +793,23.0,21.0,27.0,21.0,31.0,27.0,29.0,18.0,AGFCEBGEFGHCGECBEFEGFCBFDBFHCCHCBEDDAGFBDCCDCCDEGHEGHAFHGGHDGDBADBAGEAEAGFFCDACFACFGCFGHFHEFHEDECBEBHFGDEGCEGDBAFCCFACEEBDDHCECDEADFGBBEABHACFAEFAEHAEHEGBFCAHGEFDEAAHACGDBEFBDBBCBCEHGEFGFGGFAGDAGEG,False +794,24.0,20.0,28.0,18.0,24.0,31.0,23.0,26.0,HHAHBAHDAHGAHECHECDEHEEGEFCECEFDEDDFCDFCHBBHBHFCGGEHCAHCDGAGADGCHGHFGEEGAEBABBAEFDGDHFFEGCBFBGHBGABDBCAGCEFEBFCFAAAGAGBABCAEAAFFBFFBEBDDFFCFFHFFECFHDFGCCACFAFHCFECECCFGHFGBAGBCDHHHCCHDCEDAEDGHFG,False +795,31.0,20.0,15.0,24.0,20.0,24.0,18.0,24.0,DDFDGFDGAGEBGEBGFHEDHBDBGHCFHBDCEACAGHADHGHFGBFHCDHDHEEHGGDGGEGDFGAEAEECGFCBFABFADAADAHGCFFHBFBAFDAFDBEBAAHAAHAAHAAFABCABEBEFDHDHEFHEDABHCDDDHBHCCGDHAECAEBEHAFBACEADFBFFEAFCAFC,False +796,6.0,5.0,4.0,8.0,8.0,11.0,14.0,10.0,AGGGDBHDBEDHHCHFAGFGEECFFAFFAEDAEFEGDBGHHFHDFGCGHAGHGGHGEBCEBDFGDF,False +797,13.0,13.0,14.0,16.0,20.0,20.0,14.0,14.0,FDCFDCDGCDGAFFFFHFBDGAEEFDHFGHGBFDAFHGFHGDEDDEADCHGBHGBACAHBECACHEEEEBBDFCEBBEBFEHAGCEBAEFCEFAGFAHFGHFGCFECADCGEADEHDEBDECHB,False +798,16.0,22.0,7.0,24.0,22.0,17.0,26.0,9.0,EFHFGCFGEDGFBGFBHACDACDAGBBGECEBBBDDADDADHGGGBGGBFEEDEFDEAGEAGEAFEDDBDGCDBBBGHGDHCDBDDEGEAFEADEABABBHFBFDBFDFEEFADGADECHBGEGFFGBBHEGGFDGAGAHGEE,False +799,20.0,13.0,23.0,31.0,20.0,22.0,27.0,27.0,ACCDDCDDCHDEGDBGEBHAHGDDDCDAHDGFAGHAEBFECFBCDECBAHEACGAEGFEFFGHADDGDDACEACECCFFFDFGHBHDBHDCFGCGACFCDHCBHEFDBDGCDCDEFDEFAGHAFHAHHCEGGDBGFEGHEHHAGFEBFGAHCBHCAHDADFGDEHDHHAGHFEHGEGGDGGBF,False +800,7.0,7.0,4.0,8.0,5.0,4.0,9.0,2.0,BFADCAGBDGDDGDDAEDEFBEABEBECGDGHAGHAGFGBABCGFC,True +801,27.0,24.0,11.0,26.0,22.0,20.0,24.0,21.0,FDEFHBBHDBDFECFEGGEGBBBFGBAGBGFBAEHFGHCAACHBBHBDHEABEFBAFGEDECDEGFGGHDGAGGAHCBHEEEFHEDHADFDHGEGFAAACDFDDFBDCEAHEBHEAAEFBDABAABHABDAGDADFAHFGHFGHCGDFGEBCDBDAGDBGHAHDADAGECDACDE,False +802,24.0,16.0,21.0,28.0,24.0,24.0,17.0,24.0,EHGDHECEADBDCGFCGDCFDEFDHFEEBHECAGBDHDDAAAAGEHGCCGBEGCEGEFDEBDAAGEFCAFABFBEAGEAFECCDDCDDHDHFDEFGAACEEEHGHHADHFHADHFCCAHGACGAHECBEBBDFBCFBHADDAGDCDFAHFAHFABFEBFECFHDBHDBHDGHFHFCDF,False +803,20.0,21.0,21.0,27.0,21.0,19.0,21.0,15.0,CHCDAADHHDHFEEFGGDBGABGCBCFAHFHFFGBDEBFEAFEHBEFDEFDAHCGGCDFCGCGECGEAGDBCEBGAADFADFCDAEDBDAHAEHAEGGEGAHGADFCHCCHBDBBGEADDADDBFDBCBBCBEGDDCEEAGDCGDFDEGBEBBFBAHCEHCFCFD,False +804,1.0,2.0,0.0,1.0,3.0,0.0,1.0,2.0,HBEHBEDEAG,True +805,17.0,17.0,12.0,11.0,12.0,11.0,11.0,14.0,CACCACHGBBBBABBDBGEGCAGFBEFAEBAECGBHHHHHHHFDEFGCGGBBBAFFAFFACAACGACDDEFEEDEADHAHCBHDGHABHEBGCFAHBEDDDFEDA,False +806,8.0,5.0,13.0,9.0,8.0,4.0,5.0,7.0,AABDACCACDACDBCBEEHEHCDHEDGEDADGFFCCBCGBEHCHHDGHECCFDCFAEGA,False +807,2.0,3.0,6.0,1.0,2.0,2.0,5.0,2.0,CCGFCGCAGEGGHBBHBDCFECA,True +808,8.0,11.0,13.0,11.0,20.0,5.0,10.0,7.0,EDGEBEBGEBGECCCADEEEBCEGEDBECBCCDAEDHECHAGHGCDDFDBFEBFEBEEGEFHAAGABGDFHDCHACBEDGECAHC,False +809,19.0,18.0,17.0,18.0,21.0,24.0,23.0,21.0,GGGGAGFDDEHDEHAEFAGHHHHCBECAGCEGEBGABGFBDCHDBHEHHGHFAHGCBGFDCFDCFBEFHHDAGFFGCEEDHGDCADAAHEEDEBHHFAFFABFACCBCABHGCGDBEDFEGFCGFBFBBCBBDFEGFECFAHDAEDAEAEEDCBGGFFFHA,False +810,20.0,16.0,11.0,12.0,13.0,19.0,22.0,18.0,AGFCHFDDFBEHGEHGBHGDCGFCHEGAGADFAGGAHAFBABBFBBGGAABAAEADEBDGCHHEBGCAEAHEGCAGFHDFHFEHAGDGFDBFBBFADCGDBGHFGHCCCGCDGBBAAFFAFHHFEHFEHEE,False +811,17.0,22.0,15.0,31.0,25.0,25.0,18.0,24.0,HAFEGGECCHDGGGHDGCDGDEAAEHGEFGBGGHGBEFEEBCHAEHCFHDFHDFGDGDBGDAFBFFBFHEECEDBEDHDBEDBFDBFABDEFCHAEFEDHCDAFDCBDABDABFCBCDHEHFCAFCDBEDACDEHFFHFFEEEBDEHEBHBHHAHGBHDHGDBCABDADDFDAFGAF,False +812,13.0,7.0,5.0,13.0,10.0,18.0,4.0,11.0,FGEADHABHAEHFCHFAAEEAFEAFDAFABEGGHFFBBDBHCAHADHBFADCCHEDFGDFDDBDFEDFEHFDAFDFFEHFC,True +813,30.0,25.0,17.0,27.0,18.0,16.0,23.0,20.0,DGAGBDGFDGFAAACAGCEFHDAHDBHCBACFACFGHFEFBHHBDHBAEDAHCEFDGCAADABGABDEGDGCAGCEGBABEABDFGDFADFABGBHGAFGDDGHDAHDCDDEDGECHEHGFBBFHBEBBCBDGGHHCEHBEGBCGADAADBHEFDEFHEAADCCHEDECAAABABB,False +814,24.0,14.0,14.0,18.0,16.0,18.0,16.0,21.0,ACBABDDGDGCCHAEHAEFDEFGHFGHFGDCGEBFDBGGBFACACFAGEHGBAFBAEAAEFHEGHCAEAADDHCABFHHEDHDHACHAGHACHGCHCHDDHABAAFADDBBABFHCFGCFEDDEDDHFEHFEGFBGEAFEB,False +815,13.0,9.0,13.0,16.0,13.0,6.0,10.0,11.0,EBHEDEGACDDCDGCDACHFCECCHGBHGBHCBEDAEDHFAFEAHEADAAEADDFFEGBDGEHHABGGHGCCADCDDCDHCABEFBEDBAG,False +816,3.0,7.0,5.0,5.0,0.0,0.0,5.0,2.0,DDCDBADBHGBGBBGCCCACBAGBDGH,True +817,5.0,5.0,2.0,2.0,3.0,8.0,12.0,6.0,HCHGCGFHGAEAFGHFGHFGFEADEHDFBGGGGGGFBFABABB,True +818,1.0,11.0,9.0,4.0,7.0,7.0,8.0,7.0,GABGHBHDBHCBECBFGHFGBCBBFEBECCEFCDFCGHCFCDHEFGEGBEBHDG,False +819,2.0,2.0,5.0,5.0,0.0,2.0,1.0,5.0,CDACFHHFAHDBHCCDCHDBGD,True +820,11.0,24.0,12.0,20.0,8.0,10.0,7.0,16.0,DDBDDECFEFFEBFBBABHAFHGGCCADEHHABDDDDCGHFABFABFHDCBDBGDBCDBFEHHCBHADHADBADCHDCBDHBEHBHABCGBEGBCDCGHBDAEFBBBH,False +821,9.0,5.0,8.0,7.0,7.0,2.0,8.0,6.0,DCDGGAGGCHGCHBBEEAGEGEFCEDADAADAAFCABCEHCBHBEHCAHDDG,False +822,4.0,6.0,4.0,6.0,8.0,10.0,6.0,8.0,DGEHGBHAFDDFEAHBFCBFCDFADFCDHGEHGBFCBHEHGEBEEHEFGFFA,False +823,11.0,21.0,15.0,29.0,14.0,28.0,25.0,13.0,GCBACBGFGGFADDGDDHCCBEGFEGBDBBDFFEFECFBCFBFFGFFGDDHHDFHEFDEDDAFAGFDEBEBBDDHDEHGCHFCGCAGCFGDGGHCFBBFBDCGGEGDEBAHFDEADEADFCDGABFDDFGDCGBFADABDGBHGHGFHFDHFEBCB,False +824,9.0,9.0,18.0,17.0,22.0,11.0,12.0,16.0,HDHHDBHCFHEEAEBDEDAEDBEDBHHAFFDDFCHGCHECDDCEEEFEDGADGCDCCHCAHCAHCEHGECGEGGHFDCCEECACBGCEGFGDEBAFFAGCGBEEEFDEFDBHBH,False +825,13.0,14.0,23.0,11.0,13.0,29.0,17.0,16.0,CFBCFDDFBDFBHFHGFAGEAFFBHFCCFCFACFACFDCAEBHFGGBAGDEEHBGFAGFHEDHGFEBFHHFGFDCFCBHEEGGCFGEFBCADHHDBFDBHDHACHCCGCEGAGGFFACCAECFHCGBCEFCEFCAB,False +826,5.0,8.0,5.0,6.0,10.0,4.0,3.0,7.0,DDEDAGAAGAHCDDBBHBGEEFHECEFHEBHEFHECEECBBCHBDFBA,False +827,20.0,17.0,26.0,28.0,18.0,27.0,26.0,26.0,ECFEGFEHFHHFABFABFEHABHAGDBHDBHDBGDGCDGHABHAFCEHDBHGCDCEFEEADECDAFBGFEGFBAAGDGDDEEDHDABDABFAGFDGDDADCBDAHGHHGHHFFFFFGCDEDGGCBCFEDGCCGCCDCEFFHHAHDBHAFCCFDGBCCHACHDEGGEGCCDCCHCBGFAAFEGFGCHHF,False +828,10.0,8.0,14.0,9.0,25.0,17.0,21.0,17.0,ECHGCHBCGEFDEFDECDEGBECBHBHHFFGGFGGHDGHACCAHHBDCFGAFGAGEEHEAHECEEHEEBEEGDECFEBFECFHFFGGGAEGHEGFCFBAGAHEEGDAAHFHCFGEEDFGDC,False +829,3.0,3.0,1.0,2.0,3.0,6.0,4.0,4.0,DHEHHDFHGGBAGAFEACEGFBFFBF,False +830,13.0,14.0,5.0,14.0,12.0,16.0,14.0,22.0,GDABFFCGFEHEGFFBHCBHEDHFGFBBFEDEHDHHGFHAEHAEHCEHABHADGEDGAFGHBCHAGHADHEFHFFGFGBAABAABDGBDCHDGBEAFHHDDBDHBFHDEG,False +831,30.0,21.0,25.0,25.0,16.0,20.0,17.0,32.0,ABDAGCAGBEEEEFEEFGBFGACGBHGBHCAACAACGCHGHADHACEECHDHACHFEGEAGDAHDAHDGBBHBFHGCHEHHAFGFFDDBGHHDHDEHABBACBHCADFDDHBDHBDCDCBDAHFFHDDBFHAGCDBFFEECCECCGHAHCAHBEHDACDAHDFCDAHDBBFFBAFCFFCAHAAGAC,False +832,25.0,27.0,23.0,20.0,26.0,20.0,20.0,27.0,AADBAGBCFACEEGDFBFFBFHCGDBHEFHCFBFBEEBHCCHCHBEBGABDAHDFHDHHFEHGECGFCBHDFHABBDDBDFHDGCGCCGCDGCHBHEEDEHDHBDEEHEGHBBHFBHFBGCEGEDAEGAECCEAAEACBAHDEBAEBFGACGAFAHDABAHDGCDEAHEAFECFGAACBACHAGBFGE,False +833,25.0,13.0,14.0,24.0,17.0,12.0,19.0,18.0,AEBDEBFCFGAEEHEAHBAHDCFDHFBFAGFAGAEGCCDCAAGAHEHHGAHEACFDEGDCFBAGGABGADGCDGFEBFEAAAGAAECBGDFCDBEDHEBCDDHDDHDGHDHHGCHGEBGHCAHDEEDCDDBADAAGABHDDF,False +834,15.0,10.0,18.0,19.0,15.0,14.0,14.0,17.0,GFDGHHGDHFHCFDBEBGADGACECCHHCHFAHCEHCHHDEHAEBADDGDBGDEEDECDFCAFEEFEDDHDCGAHBAGBDEADGHEFDFABCEBFGBCABCFGCFACGDHDEHACACCAFGF,False +835,20.0,10.0,18.0,14.0,16.0,28.0,23.0,12.0,CBFFGFCHEDBFHGFEGFEGFEDCEDAEHAGGGGFGGCCCDGCFGCFHAFBAFBDFCFFHAAGCEGAEGHEGDFAFFCDFADECHEAHGFGEHGEBDDBABFABABECHCFGCDDFFGFAACAAEDHGGHECDBAFCAFAF,False +836,30.0,20.0,19.0,16.0,19.0,13.0,25.0,21.0,GEHGEGBFGFCGFAGHHGFGGFDHAAHECBAGGAGHCGBCABFHBECAAHAFCEBCEACEADDADCGHBDHGFEDBCAEGAHGHCGHCGEBBHGDHEDHDFBEBBFADEAHEACBAEGFDCAABAABAABGAEACHBHDGADHAEBACHDGDAGCEDCEFCBF,False +837,11.0,6.0,11.0,21.0,12.0,11.0,14.0,20.0,CCGFFHDFDCHECHGCEGCGGDDGABGAEHDEHGGHGHDDHDABDHBHFFGEFHDAEDFEDFGFAHHHCFHAEDGEHCHFDADDGDBADAHDAHDCDCCBEHBEAE,False +838,2.0,11.0,5.0,5.0,5.0,11.0,2.0,7.0,HHAFDBFCBFHBFCBHCFEBHEBCFBFEBEHBDDDEDCABBFFGFFGH,True +839,10.0,18.0,12.0,15.0,22.0,22.0,14.0,20.0,GHGGHDGHEHCFHBHHGHGFDFFBHGBDFBCFBFEBAHAACAEBAFCEFHEABGAHCBCCADAEHFDHFEFFEHFEHCECGHFEBFGCFDBBDBDDCEDEEDEEFBFFGDBBEBGEAEHFDCEGEEDHGDHBF,False +840,6.0,5.0,3.0,4.0,8.0,4.0,5.0,6.0,HFAHFAGABEEHFEBBEABCGBGAFGAECDEDHEHHEDGDC,False +841,22.0,25.0,12.0,20.0,30.0,18.0,24.0,19.0,CFDABGGBGGDGGBGDBGDFEHGEHAEDEEDEEAEGABBABHABFEGAAAAFAAGHFEEEAHFBBFBDHEHAGHADHFDHEDHEDCFAHFEHGEHEEHCBBDBBGBGEBCEBFEHDCFAGFECABGDHEFFEBEACCHEGEGCAFDACECDGDBHEFCGFGGBBBDBDDA,False +842,26.0,32.0,18.0,28.0,33.0,16.0,26.0,21.0,BDFEACGAHGEHBEFBDDCDDEBGFBAHCGBBGCEDEHBAFGGFBDFDABCCBFCBHEBEAFGAEGFEGEDGAABBHBDCAAEAEEBEBGDGGDGHDHHCACBEGGDHADHGEFEBDEBDHBDHBEHBHDDCDFCDCGAGGEGGEGFECAEABEAHDAHCFFCDHAAHAACAABFEEEBDEBDGBDBCEEHDBGEBEAHF,False +843,17.0,15.0,21.0,18.0,10.0,19.0,19.0,11.0,GCGCCGCDBAAFCFFCGCCFCBGCBHBGADGFEEEBEDCFDCFBEFAEGDDDDDAGACDEFDBFGCFGEFDDHCGGGGGAFACHACHACGADGHHCHBFAAFDFFDABBEBFHBHEBHCAHBADGABFDC,False +844,28.0,20.0,25.0,32.0,29.0,10.0,34.0,16.0,GCBGCEAHBHHGHCGADBHDGAFGCFEEFDEAABAAFACGACHAGEEEEEBDBDDGEAEBGCFGAFGCGACGAGFEDAGDAGDBGDFEBECDGBDHBDBBDAEHADAAHGDCGDEBAHBEDCGBEGHEDHCCEDDEDCEGCDHDACAABADGEEFCEFGGAHGCCGCBECECBDHDCADAGDGGDGGDECHEBD,False +845,9.0,18.0,18.0,15.0,16.0,16.0,18.0,30.0,FHHFCHBCEBFEBFBHCGHEGFEDEHABHBHCEHCGGEGGCGGDGHDFHBFHAGACEDBBBBBFHEDHAHHBHEGHEHFDHEBHDDHCDCDHCACADBHDAAEGHFCCECCFHHBHGDHCDHFDGFBGFGGECAFBFCEG,False +846,25.0,21.0,20.0,25.0,14.0,20.0,19.0,27.0,DHHAHHGHBEBFFBHACHBCHFEAFHAGEAGEDFFDHACGDCGEBDDBGEAFAAGAAHAAFCFDCAEFBEGHGDCFAEDABDABHGBHGFHFDGDDGDDHFBABCADDACHBCHCGECACDBCGBCFHEHCCBBHHHFHFBHECEDHDAHDFDDFBBFDBEGACGACGADG,False +847,19.0,22.0,26.0,32.0,24.0,20.0,17.0,30.0,FFFFFBEBBCDDHBEHDHHFHCDHCDBCDAFBHDGHDECDEDGEDCBFEFEHAHHAEDBDGHDCHECDEFHHADHCHBCHCDDCHBBHBEECCDFEDFDBGDBDFBEBAEFAHAGFECCACDHCEHCGGCGGCAGABCAGAGCDBADGEDFEGAEGAEHACHCBHABDBEDEDDHADGGFBFFHEFHCAH,False +848,9.0,6.0,11.0,10.0,14.0,15.0,7.0,8.0,EBECBHGDFECFDGFDHFDCEAAGDEFDEFDFFHCAHGBDDHDHFEGEGBAFCEFCAFCACCACBAFHFEHEEFEGAEBC,False +849,4.0,12.0,3.0,4.0,4.0,6.0,9.0,4.0,BADBFBBDBCDAGGEGGAHFBHFECBBGGCGGBBGBDFFHFEHAEB,True +850,11.0,16.0,15.0,13.0,9.0,18.0,8.0,14.0,AHEFHEDHAHCBEFAEABEBBDHGAGCECCECCEDGADFFBFFBFFACACDFCDECHHFDFFHFFGFBAHBCDBGDBGHHGHFBDBHDBCCFHDACABDGBCBF,False +851,14.0,6.0,9.0,8.0,8.0,11.0,8.0,4.0,CADAAFAFGGBDGBECHEGAEGCEGHEAFCGCCAFCAFDBEHBAAAFAFFECEDADGACFBDFHDFBD,False +852,13.0,17.0,14.0,11.0,14.0,23.0,28.0,19.0,AHFBHFEDBHCBHGDHDDBEFGAFBEDCEDCGGCAGCHGCHGCDCEEGFBBFHCGHAGDCFEGABFCBECBAFBAFHHGHEBCFAEGGEGAFBFGGGDGBDBFAEEBGAGHAFHCFHFFAGFHGFHFFHGGBGGHDGFE,False +853,17.0,14.0,15.0,18.0,12.0,25.0,14.0,18.0,FEEDCEDAEDABFABGHCGEGBAFBAFADFDDFBDFGDGEEAEHDGHCFHCHGBHFHFACAEBGHHGHAGAAFFDCCDHCGGCFDCFHCGECADCFDBFEBFBDGHDCHCHDAFFFHFBBEAFADFHBFHFAB,False +854,4.0,8.0,7.0,9.0,7.0,13.0,4.0,5.0,HAHBAEBCEFDHFGBFDDFDDFCGFBBCBFCFFCAFEDFBCGCDGEHEEDFDHFEBA,False +855,8.0,9.0,7.0,8.0,14.0,11.0,8.0,11.0,FCGGHEGHCAHEGDGCDHEBHEGEEFAEFCEAAFAHDEHFEHBGFBFFBFEAHEADCBBCBBCEGDDHFDFBHEAD,False +856,15.0,19.0,19.0,21.0,20.0,23.0,9.0,21.0,EHCABCEDCEDCHDBADEFFEAHGADFHBFEBFEHFEGCHGBBFBDFDCFHCFCGHCDHEHADFFEFHCGHCBABEEBEFBCDBCEHDACDBBDCBACBAEBDDCADFAEFEEHDGHDEEFBFFDHGHFGAFAHFCGFHBHDADAHC,False +857,8.0,14.0,12.0,26.0,12.0,12.0,24.0,18.0,DDGDGFHGDEEDEHGEDDCHGCAGDGBBHHAHDBHDBGACHCCHFCHGGHDGHDBFABCHGHGFDCEAGEADEGDADEGHBCFBGFGDCGBFDFFDCBDCGDGBEGBFGEHHEFHDFGDAEDBDDB,False +858,3.0,12.0,7.0,10.0,7.0,11.0,5.0,6.0,EHBFDFFCEGCEBFAFCCFECFHDGCEHAEFDBFDBAHBGHBGEBCDFDDFBDBDGBHBBD,False +859,15.0,8.0,5.0,5.0,11.0,6.0,8.0,9.0,AFHEGGEGBEDBACAADADGGHGFEGCEHCDAFECBBABHHEHAECFHBAHGABDEBAEFAEFAHAA,False +860,24.0,23.0,16.0,29.0,25.0,13.0,28.0,31.0,ABDBGHHDBEAACAHBDDDDHHGAHBDHDAHCGHCAEGFECFECGHAGBBDBDDBDGBDBAEBACDAHDBGDBCEBGEDDEBDBBABGGGGGEHAEGGGDFHDAHAHFAFDCHDCHEFBEAGECHFCHGGEGGAGFDHADEGHAFHBGHEFBCAGCAEBHEDHEDEEDFEGFHCEHDHHFCHEAGECHA,False +861,19.0,16.0,16.0,18.0,22.0,19.0,15.0,18.0,HBDHADGAFFFCFDCFDHFAEEDEEABBABHHEAEDAHDEHCGFEECHECEFGHFDHFEEGCBDFDGHDGHDCBDCAECAHBACGEFBFFAFBAFBEDHDAHBBDGEGCEGBGDFGAFGAHCHGFECAEGABAHBACBECECD,False +862,23.0,28.0,34.0,23.0,21.0,19.0,19.0,23.0,AADEFDECBCFBFEGCHHCBCAHCAEDAEDFGBAHBGBBGEDGEFBAFBABEABFAHFAHADGBHAAHAAHCFCAECBEHBACDDCDCHDHHDAHDAHCFBCDHCBBGDEDEHFBCCCCCDGEDEEBCBHCDEBEHBCGCDECGCCGBCGBCFAGGACBHBFCAGCFBDHBFHFECFGHEGCEFDDFGDG,False +863,11.0,5.0,11.0,10.0,13.0,17.0,9.0,9.0,HGFAGHEGFFAEFGCHCCHCFACEAFEAFBFFBEEDDDGGDFEBHDFEDFEFCEHCDAAFBAFHCFECHEDDABDAGCCGAHGEF,False +864,8.0,4.0,8.0,5.0,6.0,11.0,2.0,13.0,CGDDADAFHFEHACHFFHAFHAGABEFBHHCHFCFBEHCEHDEFDCFEFHCAHCAHB,True +865,6.0,7.0,13.0,8.0,5.0,5.0,10.0,8.0,EBBEADDABHGBFBHDAHDFCCCCCGDCGACEFCEGCGGCDHHBGHCGCGBFDDFEAHCAHG,False +866,13.0,18.0,13.0,24.0,13.0,21.0,16.0,22.0,CECHEHGAHDBHAACGDDGDDGBGFBACBAFGCFGEBHHBHBBFBBFGDFEBHDBAEEAGEHFEDGEDFFHFADDADFHCHEADCFDBEDCDDFFBFFHFGEFGHCDFBHADHFDHFHCGCAGDACEBDHBDGDHGCHBH,False +867,3.0,4.0,1.0,1.0,0.0,0.0,2.0,1.0,BGHBGBAABACD,True +868,12.0,15.0,8.0,11.0,24.0,11.0,16.0,16.0,GBGAFGAHEABDAHEEHEGHFBEGHCHHCBDFECAADDGHFHFGEAGEBCDGEDBEFEEFGDGGAHGDHEEHBEHGEAGECGEAHECHBBEFBHBBDBBDCBFEFEEFECAAD,False +869,14.0,6.0,19.0,11.0,20.0,15.0,11.0,18.0,AFHAEHAEHGFHACHADFFGGFEGFEGDEDBAFBDECHHGHCCDBCFECHCHFBEDEECHACDGFDCHCEHFHCFACEACEACBCGBGEADECEEGFEHFACEDHEDHAGHFCA,False +870,7.0,10.0,10.0,16.0,6.0,4.0,11.0,16.0,HCBDCBHCBACDCCDHFHAGHCCDECGEDGDAFHGHGBDDFADHGDHBDHBGHFHEAABGBDHEDHEHHEGDDGADGCBB,False +871,6.0,1.0,1.0,3.0,2.0,4.0,9.0,6.0,AHCGEDGAHEAHAFGAGGBHGAHGFGDFGFHD,True +872,3.0,5.0,3.0,3.0,6.0,1.0,1.0,2.0,BBBDCBEGHEFHDBADAECAECEE,True +873,2.0,1.0,1.0,2.0,5.0,1.0,2.0,3.0,HEGAEHAEBCFDEHDEG,True +874,7.0,21.0,14.0,14.0,9.0,12.0,13.0,10.0,FDBFBBDBADBHBAGDHHCGEFDEBGEGGFGBCGEADAGGADHBDFCDECGBCEDFHFGHFEAFGHEDCEDCBFCBCCBHBBHBBDCBFGBCBHDBCAFC,False +875,6.0,6.0,10.0,12.0,5.0,8.0,13.0,6.0,GCGGCGGHBFDDADDBDFBDGCFGAEGAFBBCBHHFDHADHAGCDGEDEFGGCECCHDCEACGDFF,False +876,19.0,14.0,14.0,17.0,5.0,8.0,26.0,9.0,ADBACAGCHGCFGHDADABGEDABDABAFGCFDCADGGGGGGGGGBGGBACCHHAAGAADAGDAGDCGDBFFBCFBEBCEBGBBHEGDDCCCBHHAFGDGADGDDAFCGHHE,True +877,11.0,23.0,26.0,15.0,25.0,13.0,27.0,20.0,DHHEHGFGGCEHCGDGEDHCDHBFEDFEAFHBDGFCBHCEECEECBHCACGACACHGBHGBGGECGBDHCFEEEHCGHCGHCEBEFBGABCDDEGGEGGEGFEDBEBBGBCGBHABGEDCABCFECAHHBBCBDCAGBDGBAGCAHFHEBCEGCDFFDEF,False +878,10.0,21.0,12.0,20.0,16.0,27.0,18.0,16.0,EGCEHFAFAEBBGACGEEDEBDEFDBBDCBDEDFFAFGHBDFBHBGHBEBEGDDGDGBHGBHBFFGDFCFGCFAEGHEDEEDEAFFFFFFCHGGDGAFGAFHDBHEBCAGHBFDFFBHFCHFCHCCDCFDHBDGBDBHFA,False +879,13.0,7.0,15.0,3.0,11.0,11.0,9.0,9.0,CHBCFBFGEFEHCCAFAAFCEECBBHEEGEFBEABAADGAGGFGFCGACEHCHCFECADCACCACFAHFHDGHGAHEB,False +880,18.0,17.0,11.0,7.0,12.0,11.0,12.0,19.0,GACGHHGCCDAEAEBAFGHFGHEHABHBDHGCHGCHBABEEBECDDBABBHFHGCBGCBFAAGDAGHHHCAFCABAABAABHAFDAFBGDCHFEBEEHEFHEFBFHE,False +881,15.0,14.0,12.0,18.0,16.0,16.0,10.0,24.0,EFDEFDHBEHAEFFBHEBGEFABHGEHDFHAFEBCDGDAFDAHAACDACDGCEHDBBBBHDHEAEFAHGDFDABHABHAEHFEHFHHFHBFHAFHAEDCGBGGDDHDEHCBCCHCEFDGGHCDCC,False +882,1.0,3.0,4.0,5.0,7.0,5.0,2.0,5.0,HDHBCGDFACFECFEFBDFDGHEEHEBHEDCE,True +883,10.0,19.0,13.0,15.0,16.0,14.0,11.0,10.0,FDEBDAHCBEFHFHGGHGEBGCHCEECDACEFBAFHCBCEBAGBFGCEGBEHDDHBDHCDAFDEBDFBDEADBADBAECAGDABCGDCFBGFBDFBEFBFGBEHEECF,False +884,4.0,20.0,14.0,12.0,17.0,18.0,12.0,16.0,DHCFHCBHGFHFEDFEDBCDBFHHGCDFADCGHFBDCBDHAGEFBEHBEDCEGCABFHBHCCCCBHCGGFGFFBFBBEGFEBBBCGEGHHHFDAFDEFBEFHEGDEBEEBEEB,False +885,4.0,5.0,7.0,5.0,3.0,5.0,11.0,4.0,GBBEAFCABHGBGEFGDDCBDCFGCAGCDGCGHEGHFCHFGAGD,False +886,4.0,2.0,5.0,6.0,4.0,7.0,8.0,6.0,DEGFEGHBGCGHBGHDFAFFAFDADGCHECDECFFCHADHGG,False +887,7.0,10.0,2.0,12.0,7.0,8.0,10.0,7.0,HDGHAEDCDDBGDBAEBGCBDAEGFGFBGFBDDBFHBEHADFGDFHHFHEDGADGAFEAGEBB,False +888,22.0,21.0,26.0,15.0,24.0,25.0,19.0,23.0,HFHEFEAADAGDBCEBGEBEFHEGHAGEDGADFEBFCBFBBFCEHADFEHGHHFDFCHFCHDBGDHAAHFCFAEBAEGCEGCFFAHHGHHFHHCHCBABGDHHDFABGCFACFECDEAGEAGFBCFGCEGCBBBEBAGHGGCBAFACFDCDDCFCAHCACCBEEBEEBEADCCEF,False +889,14.0,18.0,14.0,7.0,16.0,10.0,10.0,16.0,FHAHHEDDECCCHBCBBFBFCBACDAGHAGHBFHBCHBEGEEGBBGBBGEAEAHHBEFFEAFEDHECEEGABGBDGCABEABAFCHCAACGBHHAHCDHFECFED,False +890,18.0,20.0,25.0,21.0,23.0,27.0,22.0,23.0,ECFEGEBFABFABCDBFHBHABHBDHGFGBFGECGCFHADHDEACCBHFEGFACHECHFBACCCBEBBDFDAEAABDAECCCFCFFCFFCEGCHBEGDEDFBDEGHFCHFCFDCFEGGEGDDGHDHHCGHFDFBDHGHHAAHAEHFGAFGAEADEFCEFBEGBGGHDAEDCEHCDGBDG,False +891,21.0,17.0,16.0,20.0,21.0,17.0,22.0,30.0,GEDGFABBHBBHFAGAEEAEAAECAEHHHBDDCABHGGHGCBAAFABFBFCGEBFEGEHHEHHDDHFGEEHDGHCAHFADBADCCGACHDGHAGHAFHAFBECBEDHGCHGAHGBDCEDCDBFDEGHGADGDHGFHCDGDFHBHHBHAECFECFEGFHFEDCED,False +892,2.0,4.0,1.0,8.0,1.0,2.0,5.0,5.0,HHHHBDABDGBDFFDCAHGGGBDGDDED,True +893,15.0,5.0,9.0,8.0,9.0,2.0,15.0,5.0,GGEGEEDAFGECACCAGFGEEDECDBAEGADGABAACCACCAHGAHADHGDGGHGBACBHBDEGAAGD,True +894,15.0,20.0,23.0,20.0,17.0,18.0,26.0,16.0,FGDFCFCCGBFEBEEDACGECGHCFFEDBBCHBFHBDAFHBGCFCCFAGHDGDGGBFEEGCEGAFGAEAFEDFEDBBDHBHGGGGCFDCEHBEHGCAAAAAGHCHHCHBGDDCDBGBBCABCABADBADBFDGGCCEDEEDGCGGDDGHCFHEFH,False +895,17.0,14.0,14.0,9.0,18.0,14.0,9.0,18.0,BGCDCCFADADBGDGCAEEAGEBEFBHHAEFFEHFEBEBCGCEBCEDAGGAHEABEABDAFDHBHHAAHBAHAHBAHCEHCAHFHBEHFCFFCEFCEHCHHCAEDFEDBGFGF,False +896,10.0,10.0,7.0,13.0,14.0,14.0,10.0,8.0,HCBCDHHGEAFHFCDGHEBDEAFBCFEDFADEADEADABBHCAEDGDDGFDAFHHFDGFGGFABFBCDBCEAGBBGEFGEFEEFEE,False +897,1.0,6.0,2.0,6.0,4.0,12.0,5.0,5.0,FBDGCGGDFEBFEFFEGFBGFHFFDFHBAHFEDFCHBBHDD,True +898,8.0,2.0,6.0,2.0,1.0,5.0,2.0,3.0,CFFCHDCFEHHAADAACCABAACGAFGBF,True +899,13.0,11.0,11.0,13.0,12.0,11.0,12.0,9.0,FCCGCABEBEEFCBGCDGCAECEEHAEGDCFFHDBCABDABEAFCBHABHADHGDFGDFBDFEDGHBGDGDAGAFECHEGDEGHFAHDABAF,False +900,11.0,8.0,16.0,15.0,15.0,12.0,12.0,10.0,HFDECDECFHCHGDEDEEBGHDAHDABCCDDFGDCGBCACCDGGFCGFEHEAGEAGEAFCCHCCAFEAFADEADHGDBFBBFBBFGCEAHFCDEEDHEG,False +901,6.0,5.0,13.0,12.0,14.0,4.0,0.0,2.0,DEEDEFCACAAEHEECDECAHCBDDECCBCFFDBFBCDECEECEDCADEDDEDACB,True +902,5.0,2.0,3.0,0.0,2.0,4.0,3.0,0.0,CFECFBAGAACAAGFFGBE,True +903,1.0,3.0,5.0,2.0,2.0,3.0,3.0,5.0,HEAGEFBCDBCBCFHCFHCDHGHG,False +904,8.0,10.0,8.0,10.0,10.0,10.0,8.0,8.0,HAEHAEDAEDGHFGFFAFFBFFGDABDECDEGGEGHBHBBCCFEDGECBCCBACHDCAFBDDEEDAHGBHBF,False +905,19.0,35.0,22.0,16.0,17.0,18.0,22.0,17.0,BEDEDGGBEBBDBGHBCBBCBHCAEAHBAGBCBHDBHDCHGCBGDAGDCCAGDGCDFCBFCBDBBDHAAEAGEGGEGBAFBHFGFGBFHEACECCGHCFFEFBCFBAFAABBBBBHDBEFBHFAGBEFCDGCFCDEEHBBFBDCGDEGFHGACAACAHHFGHEABE,False +906,6.0,6.0,11.0,1.0,5.0,2.0,8.0,3.0,GGECBACGCCGHCBFEGGAACAACDACBBCHCEFCEHBEGBG,True +907,10.0,11.0,15.0,22.0,12.0,15.0,10.0,11.0,CBDCFAHHHHCHDBDDBEDHCAECDFFDACDGBDABCFBCFBGDCFFCFEEHGGHGADGDFAFACGDCADFBCFGDFEDFDDADGAHEBHFCHDCDEEBEEDEGBE,False +908,4.0,0.0,2.0,5.0,3.0,0.0,2.0,3.0,GHACDADAEDAEDEGDHHC,True +909,1.0,4.0,0.0,5.0,2.0,3.0,1.0,1.0,FDHBDABFEBDDBDEGF,True +910,9.0,19.0,26.0,20.0,13.0,12.0,16.0,22.0,BHDCHGCHBCHDCBGCAEDFEBFBHDBHDGHEGECGCFDCHHGHHBHGFGCCBCCDCHAADFFDFFHEDCFBCEHCEHCDDFAGECGDBDBGFGEECBHCBACBACHCDEFDAHBCHCEGBGGCDDHDEHBAGBADB,False +911,5.0,1.0,2.0,3.0,2.0,3.0,0.0,2.0,HAHAADAFBAFEFCEDCD,True +912,26.0,20.0,25.0,15.0,11.0,21.0,19.0,28.0,BGFDDHABFAGCACFBCDBGDCCAAAHAAHFCHCEGGFFHHFBCABCGGGGBHEAHCAHBAHAHHACHFDHDAHABHCBFEBFADFGDCGFFHCGBCFBDFEDCHBBHBCGECGEHGFHAEHACHADAABHFDECEGBAGDHFDHCCFGAEGAECABFFBHCCHD,False +913,7.0,7.0,5.0,3.0,0.0,6.0,1.0,6.0,CDFCAFHACADCBBHBFHBFHFDGCABBABFHHAA,True +914,20.0,24.0,25.0,24.0,19.0,23.0,23.0,19.0,BDHFDGCHCAHFAHFGGCHBCHDFEDAEHCBFEBCGHCGFEACCAHDFGDFDBFBEFBEBGDBGDBCDECBFHEEEBCGBDDFDECHEHBFCAFADGADAHFCFFGFAGFEGEHGADDHDCHDBDDGEDBHABGGBEGBAHBHBDCFDCACCGEAACCACGAEGBEFBAFCCFGBAG,False +915,6.0,10.0,1.0,9.0,16.0,12.0,5.0,11.0,BFGFHGADDEEEEBEEHEHHEHFEBEGHFDHFBHFBDFDFFEBGDHCEBEEBEAGDADHAFAAFHBBEDF,True +916,19.0,25.0,17.0,15.0,26.0,25.0,27.0,16.0,EBBHBCGEEAEBCECGECHHCGDCECGECDBCDBAGCHGBFDBDBCEBFAAGAAHBGDFGAEGAEHEEHECGFFAFBEEAEEABEHBGHBFHDGCCFEFFCFFGFDHBAHAGFDGFDGHGGEDGEBGHGFFECBAFBHGEFBFGDFHDAADGGBAGBFCBFDEFAFBABE,False +917,1.0,1.0,0.0,2.0,5.0,1.0,1.0,0.0,DABDEEEEGFE,True +918,3.0,4.0,4.0,5.0,6.0,2.0,1.0,2.0,FCHDCBDCDEADEBDEBFBGACAEHEE,True +919,29.0,30.0,27.0,23.0,18.0,16.0,15.0,25.0,CECCDDBFGBEHCFACFCCAAAAABGDBDCBDABFBCEACABCGBHGDCGFBGHCDHCEHCBAFBFGHFHHDHFEHFEHCDBDDACBACGACGACFEDEBDHBDHAAEEGFBHHBHDAHBGBCGDAAHAFEBCCBDBEEAHEHFGHAHAABBABDHBDADDAECGBCEDCDCGEHAEHABBFF,False +920,6.0,8.0,6.0,2.0,10.0,1.0,2.0,2.0,ABABBFGBDGEECCEACECHEHBEABDBEEEACEACB,True +921,9.0,6.0,2.0,9.0,10.0,5.0,13.0,15.0,EBEDHGAHGFHGFBDEDDGCDGDHFAEABEGEGAHGAFEAGHAHHEHDEHDABDBGEGGBGHHACHFHH,True +922,0.0,4.0,4.0,4.0,5.0,3.0,8.0,5.0,BFCBHEBHDBCDFGGEGFEGEHGHCDHGDGGEC,False +923,9.0,18.0,18.0,28.0,20.0,33.0,20.0,19.0,FCFHEFDEBCBBCFACFDCDCAFCAHBDHBFGFHAFEAFEHGCHGDHCDHCFCGDCHBEGFFGDFGBHGDFGDFGFAHDBGGHHABEDFFDFFDFFEBFHDCEDFEFHEHHDGACFFGHBBHBADDDDCDEGDGGCEFCDBEBGEDEEBCEFGFFBEDGEDBFDE,False +924,2.0,5.0,0.0,7.0,6.0,1.0,0.0,3.0,EEDEEHEBAEBDDDADBHDFHBBD,True +925,12.0,20.0,17.0,18.0,18.0,15.0,13.0,21.0,GHHFHBACCFFHHFHHABHGDHFDEBABDDBCAEHABDEDCGDGDDGCDFFDHEBAEBAEBDCBGCEGBEHBFCEFDBGBFGBHBHHFFEEGECGECGECBHGBHDCHDAFDCFDEAHAHEAHACCEEFBBDCC,False 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+976,27.0,32.0,25.0,20.0,17.0,19.0,24.0,36.0,HCFABFDBGEFGFDCBDCAEBHEDADCADCGBCDACDBBHBBDAHAHHFFGEFHHBBHEFAEDHEHHBHHDAHCACCDDDAHCEECBBHBHHBGDBGBBGHCAHCFHFHGCHGAEGFFBBHCBHAAABACEGCGGCGACFACGHBDCBHCGGEHEBGAFFAEHHDFHDFEGFABDABGBBECBEBGAAFAACGHGHHGDH,False +977,21.0,23.0,33.0,29.0,26.0,21.0,26.0,19.0,BFCBCBEGFEGDEGFEBDACFGCDGADCDDCBBCGCDDCGCCGDDGBFBEEBAABAACFCCFHDDHDEBDEFCEBBGBEEDAEAHFCHFHHEBEEFFEFHEADEGEGGCGGADDFBCADDDCCGCCGCDGEDFADGDFGFFBCAAHAHEFHECAGFGDCEDCADBAHHHHEHHEFHBCCCCBBAABCAHHDGBEGCGG,False +978,7.0,8.0,10.0,5.0,10.0,5.0,5.0,1.0,DECDEBFCGFADFEBAECABABEGGECDFCGBEGCEHCBDCBCABCAEAFE,True +979,1.0,2.0,1.0,6.0,0.0,1.0,0.0,1.0,DCADFBDHDDBD,True +980,24.0,21.0,18.0,12.0,17.0,7.0,12.0,18.0,BBAHBHDDHBHFAHACBEBBCBAEEACHAHHEGBBGBCDCCAECAHCAGGAFFACFAHHEEAEHFGCACEACHFCHDDEDDEDDCBCCHEBHBAHEABBGBBADBGBBEAAGAADHEGEGGEGAFDACC,False +981,22.0,33.0,18.0,23.0,27.0,28.0,28.0,13.0,EAEDGBCFBAFBGFDAFAAGHAEBFHFFHFFGACDBDFCDFGDBEBBDHCFBEEGGDAGECGEFABFGBEDAEAHEGDDBEGCDABHBBGBDFBDHBGBBEBBHABAABDCEFGAFGAFBFCEFBGGHAGAFEDGEDCHFHBFGDHCFHCAGFDGCGECFECBECBECECABCAEFBEFEEGDBGDEGDBGD,False +982,22.0,20.0,15.0,16.0,27.0,17.0,27.0,21.0,GDFGHEGBEHCEBCHBEHBAHGCGGEGBBFDEADFFHADHEBHGDACDACDEBEEGEHBEGBEGHEBFAAFGFFGDFGDFABGHFHCEECHDGBDCBFFBGCBDDHDCGBCFAFHGGHEGACHECAEAAHCABAACAHEEDEADEFEGBGGEGAAGEBGFAHHAE,False +983,6.0,5.0,6.0,11.0,8.0,8.0,5.0,7.0,HBFHDFCEABBADECDEGDFCDFHBFEDECCFGHFAHGHHADEADFCDGDDGEBAE,False +984,9.0,13.0,13.0,13.0,32.0,25.0,15.0,18.0,EEAEEGEABEGHGFDADEEFAHHCBFGDCBBCHBCFDCFDCFDEFDEFCHFEFECFEHFHGFHGFHEBBCGECBDHHEEDEFCEGAADEFEHGEDFEHFEDFEGBHHFHGEEGEGAACFABFGFDGBEECEEFHBFHB,False +985,14.0,10.0,10.0,7.0,7.0,11.0,13.0,6.0,FAFAHGABAACAAGAFCDDCGCEFDBGBGACHECAECAEBAHDDFDBFDBFGBAGCHBEHBAGBECFFCEFGGGGGFH,False 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For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/src/main/scala/org/xcit/nback/markov/models/State.scala b/src/main/scala/org/xcit/nback/markov/models/State.scala deleted file mode 100644 index fbbd844..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/State.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * A Single state with a label in Markov chain - * @param label A simple string label, representing the state and node - */ -class State(val label: String) { - - /** - * Keep track of transitions from this state to other states. - */ - val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() -} diff --git a/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/src/main/scala/org/xcit/nback/markov/models/Transition.scala deleted file mode 100644 index bc20a9e..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/Transition.scala +++ /dev/null @@ -1,8 +0,0 @@ -package org.xcit.nback.markov.models - -/** - * A Single transition in Markov chain graph. It is stored in "from" node. - * @param to the ending node of the edge - * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). - */ -case class Transition(to: State, probability: Double = 0.0) diff --git a/src/test/scala/ThreeBackBenchmark.scala b/src/test/scala/ThreeBackBenchmark.scala deleted file mode 100644 index 0c7dad9..0000000 --- a/src/test/scala/ThreeBackBenchmark.scala +++ /dev/null @@ -1,7 +0,0 @@ - -/** - * TODO Benchmark 3-back simple sequence generator - */ -class ThreeBackBenchmark { - -} diff --git a/tests/benchmark_diagrams.py b/tests/benchmark_diagrams.py new file mode 100644 index 0000000..8fa448e --- /dev/null +++ b/tests/benchmark_diagrams.py @@ -0,0 +1,159 @@ +import pandas as pd +import numpy as np +from matplotlib import pyplot as plt + +import benchmarks.common as common + + +def tlratio(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2,ignore_index=True) + stats = [] + for trials in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == trials) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == trials) + targets2 = data[alg2].targets if alg2.shape[0] > 0 else np.nan + targets4 = data[alg4].targets if alg4.shape[0] > 0 else np.nan + lures2 = data[alg2].lures if alg2.shape[0] > 0 else np.nan + lures4 = data[alg4].lures if alg4.shape[0] > 0 else np.nan + stats.append([trials, (targets2/lures2).mean(), (targets4/lures4).mean()]) + stats = pd.DataFrame(stats, columns=['trials', 'tl2', 'tl4']) #.dropna(subset=['skewness']) + + plt.style.use('ggplot') + + plt.ylim(bottom=0, top=30) + plt.scatter(stats.trials, stats.tl2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl2[idx], 1)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.tl4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl4[idx], 2)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('T:L Ratio') + plt.ylabel('T:L Ratio') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_tlratio.png', bbox_inches='tight') + plt.show() + + +def time_per_trial(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for t in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == t) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == t) + time2 = data[alg2].time.mean() * 1000 if alg2.shape[0] > 0 else np.nan + time4 = data[alg4].time.mean() * 1000 if alg4.shape[0] > 0 else np.nan + stats.append([t, time2, time4]) + stats = pd.DataFrame(stats, columns=['trials', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.trials, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time2[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time4[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2v4_time_trials.png', bbox_inches='tight') + plt.show() + +def time_profiles(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 8): + alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + time2 = data[alg2].time.mean() * 1000 + time4 = data[alg4].time.mean() * 1000 + stats.append([ni, time2, time4]) + stats = pd.DataFrame(stats, columns=['n', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.n, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.time2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + plt.scatter(stats.n, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.time4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_time_n.png', bbox_inches='tight') + plt.show() + +def skewness(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 9): + all_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + skewed_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) & data.skewed + all_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + skewed_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) & data.skewed + num_of_sequences2 = data[all_alg2].shape[0] + skewed_sequences2 = data[skewed_alg2].shape[0] + num_of_sequences4 = data[all_alg4].shape[0] + skewed_sequences4 = data[skewed_alg4].shape[0] + skewness2 = skewed_sequences2 * 100.0 / num_of_sequences2 if (num_of_sequences2>0) else 0 + skewness4 = skewed_sequences4 * 100.0 / num_of_sequences4 if (num_of_sequences4>0) else 0 + stats.append([ni, skewness2, skewness4]) + stats = pd.DataFrame(stats, columns=['n', 'skewness2', 'skewness4']) #.dropna(subset=['skewness']) + + + plt.style.use('ggplot') + plt.scatter(stats.n, stats.skewness2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.skewness2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + + plt.scatter(stats.n, stats.skewness4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.skewness4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Skewness') + plt.ylabel('Skewed Blocks (%)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_skewness.png', bbox_inches='tight') + plt.show() + +if __name__ == "__main__": + tlratio() + skewness() + time_profiles() + time_per_trial() diff --git a/tests/benchmark_skewness.py b/tests/benchmark_skewness.py new file mode 100644 index 0000000..f468b4d --- /dev/null +++ b/tests/benchmark_skewness.py @@ -0,0 +1,97 @@ +import random +import heapq +import csv + +# Common parameters +alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'] +trials_range = (10, 40) +n = 3 +sample_size = 100 + + +def to_benchmark_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [str(ralph_skewed)] + +def benchmark_nb_gm_001(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_001') + + +def benchmark_nb_gm_002(filename): + import generators.nb_gm_002 as nb_gm_002 + + generator = nb_gm_002.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + # print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_002') + + +def benchmark_nb_gm_003(filename): + import generators.nb_gm_003 as nb_gm_003 + + generator = nb_gm_003.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + print(f"sequence {i}/{sample_size}: {trials} trials") + seq = generator.generate(trials) + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_003') + + +def show_skweness_diagram(filename, choices, title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + print(filename) + data = pd.read_csv(filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) #.dropna(subset=['skewness']) + #print(stats.trials) + #plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'{title}.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + benchmark_nb_gm_003('../benchmarks/nb_gm_003_2back.csv') diff --git a/tests/common.py b/tests/common.py new file mode 100644 index 0000000..e40c0df --- /dev/null +++ b/tests/common.py @@ -0,0 +1,27 @@ + + +# Common benchmark parameters +choices = alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F'] +trials_range = (10, 65) +n = 4 +sample_size = 100 + + +def count_targets_and_lures(seq, n): + mask = 'D'*n + for index in range(n, len(seq)): + if seq[index] == seq[index - n]: + mask += 'T' + elif seq[index] in seq[index - n - 1:index - n + 1]: + mask += 'L' + else: + mask += 'D' + return mask.count('T'), mask.count('L') + + +def skewness(seq, choices): + import heapq + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return ralph_skewed diff --git a/tests/nb_gm_001_bm.py b/tests/nb_gm_001_bm.py new file mode 100644 index 0000000..54f6cb3 --- /dev/null +++ b/tests/nb_gm_001_bm.py @@ -0,0 +1,75 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq) , str(ralph_skewed)] + + +def benchmark(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets / s.trials, axis=1) + plt.scatter(data.trials, data.targets_ratio, alpha=0.2) + plt.show() + +if __name__ == '__main__': + alg = 'nb_gm_001' + fn = f'results/{alg}_{n}back.csv' + benchmark(fn) + # skewness_diagram(fn, alg) + targets_ratio_diagram(fn, alg) diff --git a/tests/nb_gm_002_bm.py b/tests/nb_gm_002_bm.py new file mode 100644 index 0000000..c8af543 --- /dev/null +++ b/tests/nb_gm_002_bm.py @@ -0,0 +1,105 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq), str(ralph_skewed)] + + +def benchmark(filename): + from generators.nb_gm_002 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials, int(trials/3), 0, 0) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +import time +import numpy as np +import pandas as pd + +import benchmarks.common as common + +def profile(): + from generators.nb_gm_002 import SequenceGenerator + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, int(lures/2), int(lures/2)) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('benchmarks/results/nb_gm_002_profile.csv', sep=',', encoding='utf-8') + +if __name__ == '__main__': + alg = 'nb_gm_002' + fn = f'results/{alg}_{n}back.csv' + profile() diff --git a/tests/nb_gm_003_bm.py b/tests/nb_gm_003_bm.py new file mode 100644 index 0000000..fa6c19a --- /dev/null +++ b/tests/nb_gm_003_bm.py @@ -0,0 +1,114 @@ +import heapq +import csv +import random +import time + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq, time_per_block): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [time_per_block, ''.join(seq), str(ralph_skewed)] + + +def benchmark_skewness(filename): + from generators.nb_gm_003 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['time_per_block', 'seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + targets = trials / 3 + t = time.time() + seq = generator.generate(trials, targets) + t = time.time() - t + print(f"sequence {i}/{sample_size}: {trials} trials, took {t}s.") + writer.writerow(to_csv_row(i, seq, t)) + plot_skewness(fn, 'nb_gm_003') + + +def plot_skewness(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def plot_targets_ratio(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +def benchmark_targets_ratio(): + pass + +def benchmark_chunking(): + pass + + +def benchmark_n(): + pass + + +def plot_timing(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['time_per_trial'] = data.apply(lambda s: s.time_per_block / s.trials, axis=1) + plt.style.use('ggplot') + plt.title(f"{figure_title} - average time to generate a trial") + plt.ylabel('time (s)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.time_per_trial, alpha=0.5) + + # draw fitted curve + # import numpy as np + # p = np.poly1d(np.polyfit(data.trials, data.time_per_trial, 3)) + # plt.plot(data.trials, p(data.trials), color='red') + + plt.savefig(f'results/{figure_title}_timing.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + alg = 'nb_gm_003' + fn = f'results/{alg}_{n}back.csv' + benchmark_skewness(fn) diff --git a/tests/nb_gm_004_bm.py b/tests/nb_gm_004_bm.py new file mode 100644 index 0000000..b4ad4a8 --- /dev/null +++ b/tests/nb_gm_004_bm.py @@ -0,0 +1,26 @@ +import time +import numpy as np +import pandas as pd + +import tests.common as common +from generators.nb_gm_004 import SequenceGenerator + +def run(): + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, lures) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('tests/results/nb_gm_004_profile.csv', sep=',', encoding='utf-8') diff --git a/tests/results/2v4_time_trials.png b/tests/results/2v4_time_trials.png new file mode 100644 index 0000000..9be91b4 --- /dev/null +++ b/tests/results/2v4_time_trials.png Binary files differ diff --git a/tests/results/2vs4_skewness.png b/tests/results/2vs4_skewness.png new file mode 100644 index 0000000..a488e1f --- /dev/null +++ b/tests/results/2vs4_skewness.png Binary files differ diff --git a/tests/results/2vs4_time_n.png b/tests/results/2vs4_time_n.png new file mode 100644 index 0000000..d022ed0 --- /dev/null +++ b/tests/results/2vs4_time_n.png Binary files differ diff --git a/tests/results/2vs4_tlratio.png b/tests/results/2vs4_tlratio.png new file mode 100644 index 0000000..b76f296 --- /dev/null +++ b/tests/results/2vs4_tlratio.png Binary files differ diff --git a/tests/results/nb_gm_001_2back.csv b/tests/results/nb_gm_001_2back.csv new file mode 100644 index 0000000..f6ad25e --- /dev/null +++ b/tests/results/nb_gm_001_2back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,0.0,1.0,0.0,55.0,56.0,0.0,0.0,0.0,BEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True 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+364,0.0,0.0,0.0,1.0,0.0,31.0,0.0,31.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +365,0.0,0.0,0.0,24.0,0.0,23.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +366,0.0,15.0,0.0,0.0,16.0,0.0,0.0,0.0,EEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +367,22.0,0.0,0.0,0.0,0.0,0.0,1.0,22.0,GHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +368,0.0,25.0,0.0,0.0,0.0,0.0,25.0,0.0,BGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +369,0.0,0.0,0.0,100.0,1.0,0.0,0.0,0.0,EDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +370,0.0,17.0,0.0,17.0,1.0,0.0,0.0,0.0,EBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +371,0.0,1.0,49.0,0.0,49.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True 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+377,27.0,0.0,0.0,29.0,0.0,0.0,0.0,0.0,DDADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +378,81.0,0.0,0.0,81.0,0.0,0.0,0.0,1.0,HADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +379,1.0,0.0,9.0,0.0,8.0,0.0,0.0,0.0,ACECECECECECECECEC,True +380,1.0,0.0,0.0,32.0,33.0,0.0,0.0,0.0,AEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +381,5.0,0.0,5.0,0.0,1.0,0.0,0.0,0.0,ECACACACACA,True +382,0.0,0.0,0.0,96.0,0.0,0.0,98.0,0.0,GGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +383,0.0,86.0,0.0,0.0,0.0,85.0,0.0,0.0,BBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +384,0.0,0.0,28.0,0.0,1.0,0.0,0.0,28.0,ECHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +385,0.0,1.0,119.0,0.0,0.0,0.0,0.0,0.0,BCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +386,0.0,0.0,93.0,0.0,0.0,93.0,1.0,0.0,GCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCF,True +387,92.0,0.0,1.0,0.0,92.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +388,0.0,186.0,0.0,0.0,0.0,0.0,0.0,0.0,BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +389,1.0,74.0,0.0,0.0,0.0,0.0,0.0,0.0,ABBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +390,0.0,0.0,0.0,0.0,1.0,86.0,0.0,87.0,EHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +391,61.0,0.0,0.0,61.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +392,0.0,0.0,0.0,1.0,16.0,0.0,0.0,15.0,DEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +393,118.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +394,0.0,0.0,0.0,0.0,0.0,75.0,0.0,1.0,HFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +395,30.0,0.0,0.0,0.0,0.0,0.0,0.0,30.0,AHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +396,65.0,0.0,0.0,0.0,0.0,1.0,0.0,65.0,FAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +397,0.0,0.0,0.0,55.0,56.0,0.0,0.0,0.0,EEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +398,26.0,0.0,0.0,25.0,1.0,0.0,0.0,0.0,EADADADADADADADADADADADADADADADADADADADADADADADADADA,True +399,0.0,0.0,60.0,0.0,0.0,0.0,1.0,59.0,GCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +400,1.0,0.0,0.0,0.0,160.0,0.0,0.0,0.0,AEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +401,1.0,0.0,31.0,0.0,0.0,31.0,0.0,0.0,AFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +402,0.0,0.0,0.0,15.0,1.0,0.0,0.0,0.0,EDDDDDDDDDDDDDDD,True +403,0.0,0.0,0.0,54.0,55.0,0.0,0.0,1.0,HEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +404,0.0,0.0,0.0,27.0,0.0,27.0,0.0,1.0,HFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +405,0.0,0.0,0.0,1.0,0.0,15.0,0.0,15.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +406,0.0,95.0,0.0,94.0,0.0,1.0,0.0,0.0,FBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +407,0.0,0.0,15.0,14.0,0.0,0.0,0.0,0.0,CCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +408,78.0,78.0,0.0,0.0,0.0,0.0,1.0,0.0,GBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +409,0.0,0.0,72.0,1.0,0.0,0.0,72.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +410,55.0,0.0,1.0,0.0,0.0,0.0,55.0,0.0,CAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +411,0.0,59.0,0.0,0.0,0.0,60.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +412,61.0,0.0,0.0,61.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +413,0.0,1.0,0.0,75.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +414,0.0,53.0,0.0,0.0,0.0,0.0,52.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +415,0.0,0.0,16.0,0.0,1.0,0.0,0.0,15.0,ECHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +416,0.0,0.0,0.0,39.0,0.0,0.0,0.0,38.0,DHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +417,96.0,0.0,1.0,95.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +418,28.0,0.0,1.0,27.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +419,0.0,1.0,92.0,92.0,0.0,0.0,0.0,0.0,BCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +420,1.0,0.0,20.0,0.0,20.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECE,True +421,0.0,90.0,0.0,0.0,0.0,0.0,89.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +422,10.0,0.0,0.0,0.0,0.0,1.0,11.0,0.0,FGAGAGAGAGAGAGAGAGAGAG,True +423,0.0,0.0,0.0,74.0,73.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +424,0.0,0.0,127.0,0.0,0.0,0.0,1.0,0.0,GCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +425,1.0,9.0,0.0,0.0,0.0,9.0,0.0,0.0,AFBFBFBFBFBFBFBFBFB,True +426,0.0,0.0,84.0,0.0,0.0,0.0,0.0,84.0,HCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +427,33.0,0.0,0.0,34.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +428,1.0,30.0,0.0,30.0,0.0,0.0,0.0,0.0,ABDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +429,0.0,0.0,67.0,0.0,1.0,67.0,0.0,0.0,EFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +430,62.0,0.0,0.0,63.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +431,1.0,9.0,9.0,0.0,0.0,0.0,0.0,0.0,ABCBCBCBCBCBCBCBCBC,True +432,15.0,0.0,0.0,0.0,0.0,0.0,14.0,0.0,AAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +433,0.0,1.0,0.0,65.0,66.0,0.0,0.0,0.0,BEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +434,0.0,160.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +435,0.0,0.0,1.0,0.0,42.0,42.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +436,0.0,0.0,55.0,0.0,55.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +437,0.0,0.0,0.0,1.0,0.0,73.0,0.0,73.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +438,79.0,0.0,0.0,0.0,78.0,0.0,0.0,0.0,AAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +439,0.0,0.0,67.0,0.0,0.0,0.0,66.0,1.0,HCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +440,0.0,0.0,77.0,0.0,0.0,1.0,0.0,76.0,FCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +441,0.0,0.0,0.0,0.0,153.0,0.0,0.0,1.0,HEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +442,0.0,88.0,88.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +443,0.0,0.0,0.0,20.0,22.0,0.0,0.0,0.0,EEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +444,41.0,0.0,42.0,0.0,0.0,0.0,1.0,0.0,GCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +445,0.0,0.0,0.0,47.0,0.0,46.0,0.0,1.0,HDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +446,1.0,0.0,0.0,0.0,86.0,0.0,0.0,87.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +447,56.0,56.0,0.0,0.0,0.0,0.0,0.0,1.0,HABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +448,0.0,0.0,0.0,0.0,11.0,0.0,0.0,10.0,EEHEHEHEHEHEHEHEHEHEH,True +449,0.0,0.0,0.0,0.0,0.0,1.0,92.0,92.0,FGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +450,0.0,0.0,0.0,6.0,5.0,1.0,0.0,0.0,FDEDEDEDEDED,True +451,66.0,1.0,67.0,0.0,0.0,0.0,0.0,0.0,BCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +452,0.0,0.0,0.0,13.0,0.0,1.0,12.0,0.0,FDGDGDGDGDGDGDGDGDGDGDGDGD,True +453,1.0,0.0,0.0,0.0,56.0,0.0,56.0,0.0,AEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +454,15.0,0.0,0.0,0.0,0.0,0.0,0.0,16.0,HAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +455,0.0,21.0,1.0,0.0,21.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True +456,93.0,0.0,1.0,0.0,92.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +457,1.0,0.0,0.0,0.0,35.0,0.0,0.0,35.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +458,13.0,0.0,0.0,0.0,1.0,0.0,13.0,0.0,EAGAGAGAGAGAGAGAGAGAGAGAGAG,True +459,0.0,0.0,65.0,0.0,1.0,0.0,65.0,0.0,ECGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +460,0.0,0.0,95.0,1.0,0.0,95.0,0.0,0.0,DFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +461,15.0,0.0,0.0,0.0,1.0,0.0,0.0,15.0,EHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +462,0.0,0.0,198.0,0.0,1.0,0.0,0.0,0.0,ECCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +463,84.0,84.0,0.0,0.0,1.0,0.0,0.0,0.0,EABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +464,0.0,0.0,0.0,0.0,0.0,60.0,0.0,61.0,HFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +465,0.0,179.0,0.0,1.0,0.0,0.0,0.0,0.0,DBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +466,1.0,0.0,90.0,0.0,89.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +467,0.0,35.0,0.0,0.0,0.0,34.0,0.0,0.0,BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +468,0.0,0.0,0.0,1.0,7.0,0.0,0.0,7.0,DHEHEHEHEHEHEHE,True +469,0.0,0.0,0.0,0.0,92.0,0.0,91.0,0.0,EEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +470,0.0,0.0,46.0,0.0,0.0,1.0,46.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +471,0.0,0.0,0.0,0.0,0.0,1.0,158.0,0.0,FGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +472,1.0,0.0,0.0,0.0,0.0,58.0,0.0,59.0,AHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +473,0.0,0.0,6.0,1.0,0.0,0.0,6.0,0.0,DCGCGCGCGCGCG,True +474,0.0,0.0,0.0,0.0,0.0,98.0,0.0,97.0,FFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +475,0.0,87.0,0.0,0.0,0.0,0.0,0.0,85.0,BBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +476,0.0,0.0,33.0,0.0,0.0,0.0,1.0,33.0,GHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +477,45.0,0.0,0.0,0.0,46.0,0.0,0.0,0.0,EAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +478,0.0,0.0,0.0,77.0,0.0,0.0,75.0,0.0,DDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +479,73.0,1.0,73.0,0.0,0.0,0.0,0.0,0.0,BACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +480,0.0,1.0,0.0,0.0,37.0,37.0,0.0,0.0,BEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +481,0.0,92.0,93.0,0.0,0.0,1.0,0.0,0.0,FCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +482,0.0,0.0,0.0,1.0,0.0,0.0,0.0,24.0,DHHHHHHHHHHHHHHHHHHHHHHHH,True +483,25.0,0.0,0.0,1.0,0.0,25.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +484,0.0,0.0,0.0,0.0,0.0,37.0,0.0,36.0,FHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +485,21.0,0.0,0.0,1.0,0.0,20.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +486,0.0,35.0,0.0,36.0,0.0,0.0,0.0,1.0,HDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +487,0.0,0.0,1.0,0.0,97.0,98.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +488,0.0,93.0,0.0,0.0,0.0,1.0,0.0,94.0,FHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +489,0.0,1.0,0.0,93.0,0.0,0.0,93.0,0.0,BGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +490,0.0,0.0,0.0,70.0,0.0,0.0,72.0,0.0,GGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +491,86.0,0.0,0.0,0.0,1.0,86.0,0.0,0.0,EFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +492,0.0,65.0,1.0,0.0,0.0,65.0,0.0,0.0,CBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +493,0.0,0.0,0.0,69.0,0.0,0.0,0.0,1.0,HDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +494,0.0,0.0,144.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +495,0.0,45.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +496,0.0,0.0,0.0,28.0,0.0,27.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +497,0.0,72.0,0.0,0.0,0.0,1.0,73.0,0.0,FGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +498,0.0,0.0,41.0,0.0,1.0,0.0,40.0,0.0,ECGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +499,0.0,1.0,0.0,0.0,0.0,131.0,0.0,0.0,BFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +500,17.0,0.0,0.0,1.0,0.0,17.0,0.0,0.0,DFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +501,19.0,0.0,0.0,19.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADA,True +502,1.0,0.0,0.0,0.0,51.0,0.0,52.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +503,1.0,0.0,0.0,0.0,0.0,0.0,29.0,29.0,AGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +504,36.0,0.0,0.0,1.0,0.0,35.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +505,0.0,0.0,0.0,20.0,0.0,0.0,1.0,20.0,GDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +506,0.0,0.0,0.0,163.0,0.0,0.0,0.0,1.0,HDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +507,22.0,23.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABAB,True +508,0.0,1.0,0.0,0.0,0.0,0.0,41.0,42.0,BHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +509,0.0,0.0,0.0,45.0,1.0,0.0,0.0,44.0,EDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True 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+671,99.0,0.0,1.0,0.0,98.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +672,68.0,0.0,0.0,0.0,0.0,0.0,67.0,1.0,HAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGA,True +673,0.0,0.0,0.0,26.0,27.0,0.0,1.0,0.0,GEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +674,31.0,0.0,0.0,0.0,32.0,0.0,0.0,1.0,HEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +675,0.0,0.0,0.0,0.0,42.0,0.0,41.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +676,0.0,0.0,50.0,0.0,0.0,0.0,1.0,50.0,GCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +677,0.0,25.0,0.0,24.0,0.0,0.0,0.0,0.0,BBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +678,0.0,0.0,0.0,0.0,1.0,10.0,9.0,0.0,EFGFGFGFGFGFGFGFGFGF,True +679,65.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,DAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +680,0.0,23.0,0.0,0.0,0.0,0.0,23.0,1.0,HGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +681,0.0,1.0,58.0,0.0,0.0,0.0,57.0,0.0,BCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +682,0.0,0.0,0.0,0.0,0.0,68.0,1.0,68.0,GFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +683,0.0,0.0,0.0,0.0,96.0,0.0,96.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +684,1.0,0.0,0.0,0.0,66.0,0.0,66.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +685,0.0,0.0,0.0,0.0,0.0,1.0,0.0,21.0,FHHHHHHHHHHHHHHHHHHHHH,True +686,0.0,88.0,0.0,87.0,0.0,0.0,0.0,0.0,BDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +687,0.0,0.0,19.0,19.0,0.0,0.0,1.0,0.0,GDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +688,0.0,42.0,1.0,0.0,41.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +689,0.0,0.0,0.0,0.0,0.0,60.0,61.0,0.0,GGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +690,0.0,23.0,23.0,0.0,0.0,0.0,1.0,0.0,GBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +691,86.0,86.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +692,35.0,35.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +693,57.0,0.0,0.0,0.0,0.0,58.0,1.0,0.0,GFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +694,0.0,0.0,30.0,30.0,1.0,0.0,0.0,0.0,EDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +695,19.0,18.0,0.0,1.0,0.0,0.0,0.0,0.0,DABABABABABABABABABABABABABABABABABABA,True +696,0.0,0.0,0.0,1.0,0.0,56.0,0.0,57.0,DHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +697,10.0,0.0,1.0,0.0,0.0,0.0,0.0,11.0,CHAHAHAHAHAHAHAHAHAHAH,True +698,0.0,0.0,89.0,0.0,88.0,0.0,1.0,0.0,GCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +699,0.0,0.0,87.0,0.0,86.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +700,17.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAA,True +701,0.0,0.0,66.0,65.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +702,0.0,0.0,1.0,0.0,0.0,0.0,123.0,0.0,CGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +703,0.0,118.0,0.0,0.0,1.0,0.0,0.0,0.0,EBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +704,0.0,0.0,0.0,0.0,0.0,0.0,0.0,132.0,HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +705,0.0,0.0,0.0,0.0,0.0,23.0,1.0,23.0,GHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +706,0.0,0.0,0.0,0.0,6.0,5.0,0.0,0.0,EFEFEFEFEFE,True +707,18.0,0.0,0.0,16.0,0.0,0.0,0.0,0.0,AADADADADADADADADADADADADADADADADA,True +708,0.0,72.0,0.0,0.0,0.0,71.0,0.0,1.0,HBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +709,0.0,0.0,54.0,0.0,0.0,1.0,0.0,55.0,FHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +710,0.0,1.0,87.0,0.0,87.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +711,0.0,0.0,1.0,63.0,0.0,0.0,0.0,64.0,CHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +712,78.0,0.0,78.0,0.0,0.0,1.0,0.0,0.0,FCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +713,0.0,80.0,0.0,0.0,0.0,81.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +714,0.0,1.0,0.0,0.0,0.0,0.0,40.0,39.0,BGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +715,0.0,0.0,7.0,0.0,6.0,0.0,0.0,0.0,CCECECECECECE,True +716,35.0,0.0,0.0,0.0,0.0,0.0,0.0,33.0,AAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +717,0.0,0.0,0.0,1.0,73.0,0.0,0.0,72.0,DEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +718,0.0,0.0,90.0,0.0,0.0,1.0,89.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +719,1.0,0.0,0.0,67.0,0.0,0.0,0.0,66.0,ADHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +720,56.0,0.0,0.0,0.0,56.0,0.0,1.0,0.0,GAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +721,0.0,0.0,0.0,1.0,0.0,0.0,49.0,49.0,DHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +722,0.0,0.0,0.0,117.0,0.0,1.0,0.0,0.0,FDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +723,0.0,0.0,86.0,1.0,0.0,0.0,85.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +724,0.0,0.0,31.0,0.0,0.0,0.0,0.0,30.0,CCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +725,1.0,0.0,0.0,0.0,98.0,0.0,98.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +726,1.0,84.0,84.0,0.0,0.0,0.0,0.0,0.0,ACBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +727,0.0,56.0,56.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +728,0.0,1.0,0.0,24.0,24.0,0.0,0.0,0.0,BDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +729,37.0,0.0,0.0,0.0,0.0,37.0,0.0,0.0,FAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +730,0.0,0.0,91.0,0.0,0.0,0.0,91.0,0.0,GCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +731,98.0,0.0,99.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +732,0.0,0.0,0.0,0.0,99.0,1.0,98.0,0.0,FEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +733,0.0,0.0,30.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +734,12.0,1.0,13.0,0.0,0.0,0.0,0.0,0.0,BCACACACACACACACACACACACAC,True +735,0.0,93.0,1.0,0.0,93.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True 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+852,0.0,1.0,0.0,0.0,136.0,0.0,0.0,0.0,BEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +853,0.0,0.0,0.0,0.0,1.0,0.0,0.0,163.0,EHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +854,74.0,0.0,75.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +855,0.0,0.0,0.0,19.0,0.0,0.0,17.0,0.0,DDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +856,0.0,73.0,0.0,1.0,0.0,0.0,74.0,0.0,DGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True 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+863,0.0,0.0,0.0,32.0,1.0,0.0,32.0,0.0,EGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +864,0.0,0.0,15.0,0.0,1.0,14.0,0.0,0.0,ECFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +865,0.0,1.0,98.0,0.0,0.0,0.0,98.0,0.0,BGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +866,1.0,0.0,0.0,0.0,19.0,0.0,0.0,0.0,AEEEEEEEEEEEEEEEEEEE,True +867,24.0,0.0,0.0,0.0,24.0,0.0,0.0,0.0,AEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +868,0.0,0.0,0.0,74.0,0.0,0.0,0.0,73.0,DHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +869,0.0,78.0,1.0,0.0,0.0,0.0,77.0,0.0,CBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +870,0.0,0.0,1.0,0.0,50.0,0.0,51.0,0.0,CGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +871,0.0,0.0,16.0,0.0,0.0,16.0,0.0,1.0,HFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +872,0.0,0.0,0.0,1.0,28.0,28.0,0.0,0.0,DFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +873,0.0,0.0,65.0,65.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +874,0.0,34.0,0.0,0.0,0.0,35.0,0.0,0.0,FBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +875,0.0,0.0,9.0,0.0,8.0,0.0,0.0,1.0,HCECECECECECECECEC,True +876,0.0,0.0,0.0,0.0,94.0,0.0,94.0,1.0,HEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +877,0.0,18.0,0.0,16.0,0.0,0.0,0.0,0.0,BBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True 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+885,0.0,0.0,0.0,93.0,0.0,93.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDF,True +886,0.0,1.0,0.0,89.0,0.0,89.0,0.0,0.0,BFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +887,0.0,1.0,0.0,0.0,42.0,0.0,0.0,42.0,BHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +888,68.0,0.0,0.0,0.0,1.0,0.0,0.0,67.0,EAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +889,55.0,0.0,0.0,0.0,0.0,57.0,0.0,0.0,FFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +890,25.0,1.0,0.0,0.0,0.0,0.0,26.0,0.0,BGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +891,81.0,0.0,0.0,0.0,80.0,0.0,0.0,0.0,AAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +892,0.0,0.0,1.0,0.0,10.0,0.0,10.0,0.0,CGEGEGEGEGEGEGEGEGEGE,True +893,1.0,0.0,43.0,42.0,0.0,0.0,0.0,0.0,ACDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +894,55.0,54.0,0.0,0.0,0.0,0.0,0.0,0.0,AABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +895,43.0,0.0,0.0,0.0,0.0,1.0,0.0,43.0,FAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +896,1.0,0.0,0.0,0.0,97.0,97.0,0.0,0.0,AEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +897,0.0,25.0,0.0,1.0,0.0,25.0,0.0,0.0,DFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +898,0.0,0.0,0.0,0.0,26.0,26.0,1.0,0.0,GEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +899,0.0,0.0,36.0,0.0,36.0,0.0,0.0,0.0,ECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +900,0.0,0.0,0.0,0.0,1.0,0.0,89.0,88.0,EGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +901,0.0,1.0,142.0,0.0,0.0,0.0,0.0,0.0,BCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +902,1.0,83.0,0.0,83.0,0.0,0.0,0.0,0.0,ABDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +903,0.0,0.0,17.0,0.0,17.0,0.0,0.0,1.0,HECECECECECECECECECECECECECECECECEC,True +904,77.0,77.0,0.0,0.0,0.0,0.0,0.0,0.0,BABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +905,0.0,0.0,0.0,0.0,0.0,0.0,164.0,0.0,GGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +906,0.0,0.0,0.0,89.0,0.0,1.0,0.0,90.0,FHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +907,0.0,0.0,41.0,0.0,0.0,0.0,42.0,0.0,GCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +908,28.0,0.0,0.0,0.0,0.0,28.0,1.0,0.0,GAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +909,0.0,0.0,94.0,0.0,1.0,0.0,95.0,0.0,EGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +910,0.0,0.0,27.0,1.0,27.0,0.0,0.0,0.0,DECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +911,0.0,0.0,0.0,100.0,0.0,1.0,0.0,0.0,FDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +912,0.0,1.0,66.0,0.0,0.0,0.0,66.0,0.0,BGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +913,0.0,23.0,23.0,0.0,0.0,1.0,0.0,0.0,FCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +914,0.0,0.0,0.0,0.0,0.0,0.0,150.0,0.0,GGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +915,0.0,0.0,0.0,0.0,0.0,0.0,1.0,42.0,GHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +916,0.0,147.0,0.0,0.0,0.0,0.0,1.0,0.0,GBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +917,0.0,56.0,0.0,1.0,0.0,0.0,0.0,56.0,DHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +918,0.0,0.0,0.0,0.0,0.0,76.0,76.0,1.0,HFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFG,True +919,0.0,53.0,0.0,0.0,0.0,0.0,0.0,52.0,BHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +920,0.0,0.0,147.0,0.0,0.0,1.0,0.0,0.0,FCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +921,0.0,0.0,0.0,40.0,40.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +922,0.0,82.0,0.0,84.0,0.0,0.0,0.0,0.0,DDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +923,1.0,0.0,0.0,0.0,0.0,0.0,0.0,97.0,AHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +924,0.0,29.0,0.0,0.0,0.0,0.0,0.0,30.0,HHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +925,25.0,0.0,0.0,1.0,0.0,0.0,0.0,25.0,DHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +926,0.0,164.0,0.0,0.0,0.0,0.0,1.0,0.0,GBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +927,89.0,0.0,0.0,0.0,1.0,0.0,90.0,0.0,EGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +928,0.0,0.0,1.0,0.0,41.0,41.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +929,0.0,0.0,1.0,19.0,18.0,0.0,0.0,0.0,CDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +930,0.0,0.0,0.0,0.0,1.0,75.0,75.0,0.0,EGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +931,0.0,0.0,21.0,0.0,0.0,22.0,0.0,0.0,FCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCF,True +932,0.0,0.0,81.0,0.0,80.0,1.0,0.0,0.0,FCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +933,20.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAAAAA,True +934,0.0,40.0,0.0,0.0,0.0,40.0,0.0,0.0,BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +935,0.0,72.0,0.0,0.0,72.0,0.0,1.0,0.0,GBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True +936,56.0,1.0,0.0,56.0,0.0,0.0,0.0,0.0,BADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +937,0.0,0.0,0.0,0.0,0.0,96.0,1.0,0.0,GFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +938,0.0,1.0,0.0,88.0,0.0,0.0,0.0,88.0,BHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +939,1.0,0.0,0.0,0.0,0.0,0.0,0.0,175.0,AHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +940,0.0,0.0,84.0,1.0,83.0,0.0,0.0,0.0,DCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +941,0.0,0.0,83.0,0.0,0.0,0.0,0.0,85.0,HHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +942,1.0,5.0,5.0,0.0,0.0,0.0,0.0,0.0,ABCBCBCBCBC,True +943,0.0,0.0,0.0,68.0,0.0,0.0,0.0,69.0,HHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +944,29.0,0.0,0.0,0.0,0.0,29.0,1.0,0.0,GAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +945,0.0,0.0,1.0,0.0,0.0,0.0,81.0,82.0,CHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +946,89.0,0.0,89.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +947,0.0,0.0,0.0,78.0,1.0,0.0,0.0,0.0,EDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +948,90.0,1.0,0.0,0.0,0.0,0.0,91.0,0.0,BGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +949,0.0,0.0,0.0,86.0,1.0,0.0,0.0,86.0,EHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +950,0.0,0.0,0.0,42.0,1.0,0.0,42.0,0.0,EDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +951,85.0,0.0,0.0,84.0,1.0,0.0,0.0,0.0,EADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +952,90.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +953,0.0,0.0,1.0,0.0,0.0,90.0,0.0,0.0,CFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +954,62.0,0.0,0.0,1.0,0.0,62.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +955,0.0,20.0,20.0,0.0,1.0,0.0,0.0,0.0,EBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +956,0.0,0.0,37.0,0.0,0.0,1.0,0.0,38.0,FHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +957,98.0,1.0,0.0,0.0,0.0,98.0,0.0,0.0,BFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +958,0.0,1.0,0.0,0.0,189.0,0.0,0.0,0.0,BEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +959,0.0,0.0,0.0,9.0,0.0,1.0,8.0,0.0,FDGDGDGDGDGDGDGDGD,True +960,0.0,68.0,0.0,0.0,0.0,0.0,0.0,69.0,HHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +961,0.0,0.0,0.0,138.0,0.0,0.0,0.0,0.0,DDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +962,0.0,0.0,0.0,0.0,1.0,30.0,0.0,30.0,EHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +963,0.0,0.0,0.0,80.0,80.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +964,77.0,0.0,0.0,1.0,0.0,0.0,0.0,78.0,DHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +965,0.0,0.0,0.0,58.0,58.0,0.0,1.0,0.0,GEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +966,0.0,0.0,0.0,1.0,35.0,34.0,0.0,0.0,DEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +967,0.0,60.0,0.0,60.0,0.0,1.0,0.0,0.0,FDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +968,0.0,1.0,80.0,0.0,81.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +969,0.0,1.0,0.0,0.0,0.0,0.0,81.0,81.0,BGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +970,16.0,0.0,0.0,16.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADA,True +971,0.0,0.0,0.0,0.0,78.0,77.0,0.0,0.0,EFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +972,0.0,0.0,10.0,1.0,0.0,10.0,0.0,0.0,DFCFCFCFCFCFCFCFCFCFC,True +973,0.0,0.0,0.0,0.0,0.0,44.0,1.0,44.0,GHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +974,0.0,36.0,0.0,0.0,0.0,36.0,1.0,0.0,GFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +975,0.0,87.0,0.0,0.0,0.0,0.0,87.0,0.0,BGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +976,42.0,0.0,42.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True 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b/tests/results/nb_gm_001_3back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,0.0,65.0,132.0,0.0,0.0,0.0,0.0,1.0,HCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCC,True +1,51.0,0.0,52.0,52.0,0.0,0.0,0.0,1.0,HCDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACD,True +2,0.0,61.0,0.0,62.0,0.0,0.0,61.0,1.0,HDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGD,True +3,40.0,0.0,0.0,1.0,0.0,0.0,0.0,80.0,DHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHA,True +4,4.0,0.0,1.0,0.0,0.0,6.0,0.0,0.0,CAFFAFFAFFA,True 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+62,0.0,1.0,0.0,0.0,59.0,0.0,60.0,59.0,BGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEG,True +63,0.0,0.0,0.0,0.0,0.0,0.0,1.0,167.0,GHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +64,48.0,0.0,0.0,0.0,1.0,0.0,0.0,95.0,EHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHA,True +65,0.0,0.0,0.0,65.0,66.0,0.0,67.0,0.0,GGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGE,True +66,35.0,71.0,0.0,0.0,0.0,0.0,0.0,0.0,BBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBAB,True +67,50.0,0.0,0.0,50.0,50.0,0.0,0.0,1.0,HAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAED,True +68,0.0,0.0,4.0,0.0,0.0,0.0,5.0,3.0,GCGHCGHCGHCG,True +69,0.0,0.0,5.0,0.0,0.0,0.0,1.0,10.0,GCHHCHHCHHCHHCHH,True +70,0.0,0.0,19.0,0.0,19.0,20.0,0.0,0.0,FECFECFECFECFECFECFECFECFECFECFECFECFECFECFECFECFECFECFECF,True +71,0.0,0.0,1.0,0.0,0.0,0.0,43.0,84.0,CGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHG,True +72,6.0,0.0,0.0,0.0,6.0,6.0,0.0,0.0,FAEFAEFAEFAEFAEFAE,True +73,0.0,0.0,35.0,35.0,35.0,0.0,0.0,1.0,HECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECD,True +74,25.0,0.0,26.0,0.0,1.0,0.0,0.0,25.0,ECAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHC,True +75,61.0,0.0,0.0,60.0,0.0,60.0,0.0,1.0,HAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDA,True +76,0.0,0.0,0.0,41.0,0.0,0.0,0.0,20.0,DHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDD,True +77,0.0,0.0,1.0,0.0,0.0,15.0,15.0,14.0,CGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGF,True +78,6.0,0.0,1.0,6.0,0.0,0.0,0.0,6.0,CHDAHDAHDAHDAHDAHDA,True +79,0.0,124.0,0.0,62.0,0.0,0.0,0.0,0.0,BBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBD,True +80,0.0,0.0,32.0,0.0,0.0,31.0,31.0,0.0,CGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCF,True 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+317,61.0,0.0,0.0,0.0,0.0,61.0,1.0,61.0,GFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHA,True +318,0.0,0.0,0.0,7.0,7.0,8.0,1.0,0.0,GFEDFEDFEDFEDFEDFEDFEDF,True +319,7.0,0.0,0.0,0.0,1.0,3.0,0.0,0.0,EAAFAAFAAFA,True +320,0.0,48.0,0.0,48.0,0.0,0.0,0.0,48.0,BHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHD,True +321,0.0,23.0,23.0,0.0,0.0,0.0,0.0,24.0,HBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCH,True +322,0.0,0.0,1.0,0.0,0.0,30.0,30.0,30.0,CGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFH,True +323,48.0,0.0,0.0,47.0,47.0,0.0,1.0,0.0,GADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEA,True 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+401,0.0,55.0,55.0,0.0,0.0,1.0,54.0,0.0,FCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCB,True +402,47.0,0.0,0.0,0.0,1.0,47.0,0.0,47.0,EAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFH,True +403,56.0,0.0,0.0,0.0,58.0,0.0,0.0,56.0,EEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAE,True +404,0.0,39.0,0.0,0.0,39.0,1.0,40.0,0.0,FGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEG,True 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+951,0.0,0.0,0.0,0.0,35.0,1.0,35.0,35.0,FHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEG,True +952,0.0,0.0,1.0,0.0,0.0,0.0,36.0,71.0,CHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHG,True +953,0.0,42.0,0.0,0.0,21.0,0.0,0.0,1.0,HEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBB,True +954,0.0,49.0,0.0,50.0,0.0,0.0,49.0,0.0,DDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBG,True +955,11.0,0.0,0.0,0.0,22.0,0.0,1.0,0.0,GEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAE,True +956,0.0,0.0,0.0,1.0,0.0,18.0,0.0,38.0,DHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHH,True +957,58.0,58.0,60.0,0.0,0.0,0.0,0.0,0.0,CCBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBAC,True +958,19.0,19.0,0.0,0.0,19.0,0.0,0.0,0.0,BEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEA,True +959,0.0,0.0,39.0,0.0,0.0,38.0,0.0,38.0,CFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHC,True +960,0.0,0.0,0.0,80.0,41.0,0.0,0.0,1.0,HEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDE,True +961,0.0,21.0,0.0,22.0,0.0,23.0,0.0,0.0,FDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDF,True +962,0.0,0.0,0.0,0.0,6.0,10.0,0.0,0.0,EFEFFEFFEFFEFFEF,True +963,65.0,65.0,1.0,0.0,65.0,0.0,0.0,0.0,CBEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEA,True +964,0.0,46.0,1.0,0.0,45.0,46.0,0.0,0.0,CFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFB,True +965,64.0,64.0,0.0,0.0,63.0,0.0,1.0,0.0,GABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEAB,True +966,1.0,0.0,47.0,0.0,0.0,48.0,47.0,0.0,AFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGF,True +967,54.0,0.0,54.0,53.0,0.0,0.0,0.0,0.0,ACADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADC,True +968,10.0,0.0,10.0,0.0,12.0,0.0,0.0,0.0,EEACEACEACEACEACEACEACEACEACEACE,True +969,0.0,0.0,0.0,0.0,0.0,0.0,125.0,62.0,GGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGH,True +970,0.0,8.0,1.0,9.0,0.0,0.0,8.0,0.0,CDBGDBGDBGDBGDBGDBGDBGDBGD,True +971,0.0,0.0,0.0,66.0,66.0,67.0,1.0,0.0,GFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEF,True +972,63.0,0.0,0.0,0.0,127.0,0.0,1.0,0.0,GEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAE,True +973,0.0,0.0,11.0,0.0,0.0,0.0,21.0,1.0,HCGGCGGCGGCGGCGGCGGCGGCGGCGGCGGCG,True +974,0.0,0.0,39.0,0.0,0.0,40.0,40.0,0.0,FGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFG,True +975,0.0,0.0,1.0,31.0,0.0,0.0,62.0,0.0,CDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGG,True +976,0.0,54.0,0.0,0.0,0.0,1.0,54.0,55.0,FHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBH,True +977,0.0,0.0,18.0,19.0,0.0,18.0,0.0,0.0,DFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCD,True +978,126.0,63.0,0.0,0.0,1.0,0.0,0.0,0.0,EAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAAB,True +979,19.0,0.0,0.0,0.0,0.0,1.0,0.0,9.0,FAHAAHAAHAAHAAHAAHAAHAAHAAHAA,True +980,0.0,0.0,32.0,32.0,0.0,33.0,0.0,0.0,FDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFC,True +981,15.0,0.0,15.0,0.0,16.0,0.0,0.0,0.0,ECEACEACEACEACEACEACEACEACEACEACEACEACEACEACEA,True +982,0.0,0.0,55.0,0.0,0.0,56.0,57.0,0.0,GFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFG,True +983,0.0,0.0,32.0,0.0,1.0,32.0,31.0,0.0,EFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFC,True +984,0.0,0.0,0.0,41.0,1.0,40.0,40.0,0.0,EDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGD,True +985,0.0,0.0,0.0,0.0,5.0,6.0,5.0,1.0,HFGEFGEFGEFGEFGEF,True +986,0.0,19.0,17.0,0.0,0.0,0.0,0.0,18.0,BBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBH,True +987,0.0,0.0,0.0,0.0,0.0,0.0,6.0,10.0,GHGHHGHHGHHGHHGH,True +988,0.0,0.0,69.0,0.0,36.0,0.0,0.0,0.0,ECECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCE,True +989,1.0,0.0,0.0,0.0,0.0,19.0,0.0,37.0,AHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHF,True +990,67.0,0.0,0.0,0.0,0.0,0.0,0.0,33.0,AHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAA,True +991,0.0,0.0,16.0,18.0,0.0,17.0,0.0,0.0,DFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFD,True +992,1.0,0.0,50.0,50.0,0.0,0.0,49.0,0.0,ACDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCD,True +993,0.0,40.0,39.0,0.0,39.0,0.0,0.0,1.0,HBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEB,True +994,0.0,30.0,1.0,0.0,0.0,0.0,30.0,30.0,CBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGH,True +995,126.0,0.0,1.0,0.0,0.0,0.0,0.0,63.0,CHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAA,True +996,45.0,0.0,45.0,1.0,0.0,0.0,0.0,45.0,DHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHAC,True +997,15.0,0.0,0.0,0.0,29.0,0.0,0.0,0.0,AEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEE,True +998,0.0,4.0,1.0,0.0,0.0,4.0,0.0,4.0,CHBFHBFHBFHBF,True +999,0.0,100.0,0.0,0.0,0.0,0.0,0.0,51.0,HBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBH,True diff --git a/tests/results/nb_gm_002_2back.csv b/tests/results/nb_gm_002_2back.csv new file mode 100644 index 0000000..33538c3 --- /dev/null +++ b/tests/results/nb_gm_002_2back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,4.0,2.0,2.0,2.0,2.0,1.0,0.0,5.0,BHCHDHDAEBEHAFAHAC,True +1,0.0,4.0,1.0,2.0,4.0,0.0,0.0,0.0,DBEBDBCEEBE,True +2,5.0,10.0,14.0,6.0,16.0,18.0,12.0,12.0,CFFGHCFCGHEDCCACECBGEGFGAEBGHFDCEEDCCEGEGCBBBHCCECHBHEHBHDEDAFAFAFHFGFGFGHGHEFFFEFEDHFEFEFBBB,False +3,12.0,15.0,11.0,20.0,13.0,17.0,17.0,22.0,AFAHGHGHGBEBCDDDDHHHABCEHEHEBBBAHADADCFHHHHHFEFCBDDFDGDEFCAGGFEFBDGEHECCBCFFFFFFHGEBBHHCBCACHHDDBFGGGGEGEAFDGDADGDGDGBEBAAHDDFH,False +4,4.0,4.0,8.0,8.0,5.0,7.0,4.0,2.0,FGDGECDCECGCDADAHFDFCFCGAFCDDDABEBHBEFEFBC,False +5,15.0,15.0,15.0,16.0,16.0,14.0,9.0,13.0,HGDGBFDHDADHBBBBBHBAAGBCEABCGFAFAFBGBCBFGDDDEAAAHDFACECECHFHFHFCFHEGEFEFDFDAAHDEECDABFCCCCGBEBDAHCECHCHEDEDEDAGEE,False +6,17.0,17.0,9.0,6.0,15.0,13.0,15.0,12.0,BEBEBHAGCFEHHABAHDEDGHFBFGFCAABAGFFFAFGECEBEAEAFBFCEBEGHGDBEFABABEGEHEHBGBGDADACAGHGHGBGBACGCAHFFBHAECDC,False +7,12.0,7.0,7.0,6.0,9.0,8.0,5.0,6.0,CEGBFEFEFEHCCDEBCCHBBBGAHACBGGDBDADACADHDHFEAEAEFGFAAEAHAFAF,False +8,9.0,13.0,10.0,11.0,12.0,15.0,11.0,12.0,CGCFDBDFHHEHFFGCDHEHCFCFAAEGDCEGHGCFCBBBCBGFGHGDFDBDADHBBEGAGABABHBEBEHGHADAFEFCFDBDEFEHEFEFA,False +9,13.0,26.0,23.0,14.0,20.0,18.0,19.0,27.0,HECEBEFFHFDCCFGBCBDBAHGHGCBBABHEFAFEBEBHBHGGCHBGGCCCCCFCBDDDEDHDEEEAAFAFGFDFCGBGHEHDHGHAFABCGGEHEHFBGBADEBEBEAAHBDCCFGGHHHBHBHGHBDBEEAEGCGCBCHCEFFFFCHDHCHDHABCB,False +10,14.0,18.0,15.0,13.0,15.0,19.0,18.0,11.0,AFACABDDFBBBEBECECGHFBFBECDCEEEDGDBHHGCBDDAFCBAAAGHCHCHEAFBFDHAHCFFAAAHBBBFBFBHGFBCBCFGGGHGDGDFEGEFCFEDGDGAGEGCGEGEFEFAFDGC,False +11,21.0,20.0,21.0,13.0,15.0,26.0,21.0,21.0,EECEFFHGCADHGEGEABCCFDEBABEBGGCACHFHFBFBFBAHGBGCGHDCDABHHAGABFHEBCFEGDFDFDFAFBCBCAHACFGFBFBFBFBDACCBCHFHEGEDFDFCAAAGGEBFAAACACHCHFGFBFGHGHAEAGCCEDDFHHHGHGHGDE,False +12,17.0,26.0,17.0,23.0,17.0,11.0,26.0,21.0,ABGCACGDDFHFHBCEHEAGBGBEBAHEBEBFAAHAFBCEGDGBAHGGGGFGDDDBABABHGGGCGDGHGHDACAEDEFECHGEGDABGCHCDDDDCBCBADAHCHGBGBGEHDCDBBFBABHBHBFBACHDEEHGHECDCDHDEFEDECFGHGBFBD,False +13,24.0,21.0,23.0,20.0,15.0,14.0,30.0,24.0,AHHHHAFEDHAFBFGFCFGADADCDGBBBBGDGEGBCBHGGGGCGFBFAGGGGHEEFEGHGHABCBFHGAGACBBDEDHDHDGBCACAHGCACEHECACHBHDCGCECADGDGDABADHFGCGAGAHHBGFDCHBHCAAABEEFDFDBDBEADAHGEGEHECCCBCFCAHD,False +14,1.0,0.0,2.0,1.0,1.0,1.0,2.0,2.0,DECGCGAHFH,True +15,7.0,7.0,10.0,5.0,8.0,4.0,8.0,9.0,HBABHHEEGAGAGEGHCDEECHCHGBCBCDDAEGCBCGEAEFDFBFBFAGCHCHCHAD,False +16,14.0,19.0,14.0,7.0,10.0,15.0,19.0,7.0,CEAFFGHGEGFDFDCACAGBDEAFCEDDFAHHFDFGBEACGCGBGAFECECFGHCEBAFGEGCBABEBHBHBACAGAGDGHBABCBCBGFGFGFGBBBBFBCBGA,False +17,17.0,15.0,14.0,12.0,10.0,9.0,17.0,6.0,EBACADACGBGBAFGHGHADCDGAAFFFADABAHGDGABBCBCACACECHFBFHDCACDGEBADDEGGGEDADFGFGCGFBBABCBEBDBCHGEGEGECE,False +18,14.0,22.0,17.0,9.0,14.0,10.0,25.0,20.0,EHCHAHEHAHCHCGBGCGCGAEBFBFGGCEFGBGHAHCBABABHHGHGCACHDEDBBABGGDGDEBBBHHGCAEGBFHGEGEGBCCGCDFBBGBFBDAEEHHHCFEFECEHGCGCBHDADFDAGAGAGFBB,False +19,13.0,27.0,12.0,18.0,19.0,17.0,20.0,18.0,BFGCGBHAHAHEFEDBABEBEDADGGGGBAFCGEBDFHBHGHGCBBEGEGBHDHDHBCBCACDBFHHCHBGAGAGEDADADCDCACGHEEEEBDFDFDHDCGGBGDEBBBABEHFHGEFFFBADHEFFCFDEBEBFFEBHBFBG,False +20,11.0,10.0,7.0,8.0,8.0,7.0,11.0,4.0,BGBABGHGCGFBFAEBGGEDEFAHEHACDCDADBGGAGAGADFBFBCBCEFBFDHDACCDAGAEEE,False +21,22.0,20.0,18.0,24.0,13.0,11.0,16.0,21.0,DADADHCACFCHEDAAAHGDDHAGCDEDEGBHAHBDBDBGHHHCHCECAAAEFEDECEDBHFABGBCAGDBEGEBABHFCBBABDFDGHGCBFBCCDHDHDGDHDHCHBGADAFACHEHBDCDAFAFAFAGGCGCFHGBDBEBEG,False +22,8.0,10.0,11.0,7.0,8.0,15.0,4.0,11.0,CBAEGDGEHEBGBFBFBDHCHFHBAEHFFGFCFBFCFEEHABECFFFFACAEHHDCDCDHDHAHCFCBCBAADF,False +23,32.0,19.0,21.0,23.0,13.0,27.0,21.0,27.0,GHCABDGDFFFAHHHEAEHGAGAGHEFEGBCFAFBFGCHCHFHBGCAFFDFDBACACHCHCHBFGFEACAFABEBEBHHGHFHAHGGAGAHAFCGDHDHAFGCBCHDAAAAAAFCFHGEFFBEBEDDDFDBCBDDDCGFAFADBDBEBCAGGHDFDFBCDEAGAHCCEHGHAHCDDDDABAFA,False +24,26.0,30.0,18.0,21.0,29.0,16.0,21.0,21.0,GDGDADAGAGDEHCDBDHAHEHFHAHAFBHBHGCEBHBDBHBHBEEABABABAEECEGEGAGADHDBEEGBCAADHGBFBCEAAHDEBEBFBFBFCCGCEFBABAEDBGFGBGCFCGEACDFEFBHDADFHCEAEBDHDCGBEFGCDCACDEBEGAGAEAEFDFBBEHEGEGHCACEFBHDH,False +25,17.0,15.0,10.0,21.0,16.0,11.0,16.0,22.0,BDBDBHHHAAGAEHEHCHCDADEBGHDAGEBHGAABADADEDECEHAHFBGCGBEHCGADFBHECGHHFFFHFBDDDDDFDFDFHFEDEDACAEAEBDCHHBFBABCBGDGEAECHHGHGEGHDAGGG,False +26,12.0,13.0,16.0,11.0,17.0,10.0,17.0,12.0,GEECBGFEEDHCEFGFEAEAHGEGEDDDHDCDCBHBCBCFCECEGAGAGAHECFCEAAFGFGCEHGHBBBGBGBCBDHEAEFHFHGBCDGGACHCGCDADAEBFBADH,False +27,14.0,11.0,17.0,13.0,14.0,21.0,16.0,19.0,AAECGGEGHCACACACHBHADCECBDHDHDFCFGHGDDEDHHHAHDFDACHBHAFBHHAEEECGGFGEGEBEFCFAEAEFFBFBFDGDGDGHFACCDFHFCGBBHBCGGFGEHEFFFFHFCBCAF,False +28,14.0,15.0,12.0,21.0,15.0,9.0,13.0,21.0,GGHGEDHFCFCACBCADAEEEEAHDGAGHGHEHEHBBECEDBBBDBEGDGBAEABCCABBECDDDFDFHGHGHDHGHGHDADHHCHBHCCBAFHFDDDEDHFHAABDFDFEGEAADBDCH,False +29,18.0,19.0,27.0,26.0,29.0,30.0,16.0,16.0,DEFFFAFAGDGEEBFBFGEBADACADFDCEEDEDFDCDEBBGDGHGHGFFFDFBEBEHCHFDCDCEGFGFHFEFCGBBDCHCGCDADEGEGCFAAEHEHFDACGCEABBDECBCBCEFEFBFCFCFEHEHDGACEBAGCEFEBACCCAEDHDHBCFCDEFFHDHDHDCFCAAAEBEBFDHA,False +30,5.0,11.0,5.0,8.0,3.0,2.0,5.0,1.0,BBFGGBABFGCCCDADAHBEDCDBABGEAECBDBDBDBDG,True +31,28.0,17.0,19.0,16.0,18.0,11.0,17.0,33.0,DHAFAHAEAHDHFHFAFADHCGGGDGDGHEBDHCHBHAEBCBCFEGHHHBHCAFDHEHEHCDAGBCBAAAGACCBCAFGBHEHBBEAHAHAFAEACGGEHAFABEDEDFDCGHEBGAGEEAEBBHDEDECHCGABHGHAHAHBHCHCHCHDGACACDFD,False +32,5.0,10.0,12.0,17.0,19.0,17.0,17.0,11.0,EEBHBFFFDDEDCCAGEFEGGDGDFFGEGEAEDEFCFCGCGCGFAEGECDHHCEFDDHDFDABFDECECEHEFDDGDGBBFBFHHGCECEFEHAHDHDGBBFBGHGBG,False +33,4.0,13.0,10.0,7.0,4.0,8.0,11.0,7.0,CGBHBCBCBHFHFECBADGBGBGBDBCFAGDBHGFGECEHBGBCCACFGFGFGDDDFCADHEHB,False +34,22.0,27.0,22.0,21.0,21.0,28.0,21.0,21.0,BABFBCCCCGCDCAGABAHFBAHCBDBDHDCDCDEFFHBHBCBCBEHDAGAEFBBEEEBEGAGHGDGCGEBFBDEAECCFCFGDGDGHBHAEFFFECCADHFFBGHDHEGAAEDEFEFCDCDCDEFCHADAEHFDFHBBEBEBFBFAFGFAAHGHGFFAFGGBABGHGBFBFDFHCHAHEGDA,False +35,24.0,23.0,21.0,17.0,28.0,15.0,20.0,21.0,EGHGAGEGCGDFFCEEEEEAHGEGFGFBCBGBDBACHCAGDDDDEDEHACGCECAFAFEFHCHCEFHDHEHBAEADBDBAFCHCEEEEHBHBECEAEAFGGGGCCHBHAAACABBEHFHBDFHHDHBGCAABEBGAGABBFADADEBBBBCDCACFGFHDCEHEBGADE,False +36,16.0,12.0,18.0,16.0,29.0,20.0,25.0,11.0,EEEBCFFDHDBBGHGHGEFDFACCCFCGAECECEAGFFFCFDAHAEEHGGGBGBGADDGDGEGCCBFEHEGEHACDGDGCCCFCEAFAEGEGBGFGBBBHFGDGFGAAHADADCEEEEDEAEFEAEBFFFHEGECEGEHECAFDDDB,False +37,1.0,6.0,2.0,11.0,2.0,11.0,4.0,7.0,DBFFFHHADFFEFBDBFBGDFFEBHBHFHGDGDGCCDDDDHDHF,True +38,11.0,12.0,15.0,5.0,3.0,15.0,15.0,13.0,HCCCCAEBGFCFBGAHHHHBAFGCGCGCGFGCAABFBABHBFBCAFHFAFGCDBGBGAGFCBBAADHDHDCGEGHGCGFFHFHDEFHFC,False +39,33.0,14.0,21.0,23.0,21.0,18.0,25.0,28.0,DHAHAHADGDAFAFGCHCHEHCHABACEDDDCGBHAEFFGCADADGBGCFFFGGHBAAFGGHFHFHECFCHCHBDEFGADDCGGGHEBEDEBEBEDFHCAAAACFGFBFBFADAEGBDCAGACACAFGEEECDDDDCGGGEEEEEGCADHHHHAHABAHGBBCACHEGGHDADADAHAHEHAH,False +40,9.0,21.0,8.0,6.0,13.0,11.0,9.0,15.0,HEBEGEGAGEBBBHFAFABCBCBEBCBEAFHGGGHEHCHBEDFFAFAHDBFBFBEBDFHHDHBHCHBHBDEFABGBCEDEBCACHHEAGBGF,False +41,13.0,18.0,18.0,16.0,8.0,20.0,16.0,13.0,AGDGBCDHFADAGFFFHHCFCFEBGBGFGFGCGCHHHHCGFBFGDHABCBCGDGECEFBFCACBDBDCFAFBDEDCFFBHGHBEBABDFDFDHDHACABDBAFAFDHEGACACBEECGCBDG,False +42,21.0,15.0,14.0,22.0,14.0,22.0,16.0,21.0,ACFDFDEDFDBAFDCDCDFFFFFACHCHGEDFCFEHADACEHEDEBAFAGGHGEDADFDHDHDHGADAGCCCFHBDBGBDEGEBHGFGHAHFBFBFEAABABACDDAHHGFGBGEGHFEABHBFEHHHGDFDCACABABGECHAH,False +43,17.0,19.0,23.0,19.0,19.0,21.0,20.0,22.0,GDGFGEDDDDDDFDFDFEHBHDGAECBHDEGHGEEDEBEDECGGAADAFAFADECFCDGDGFBHGCBHBACAGACFCGGGBGCHFHEHECECAHFHFGCGHBFCGCBCFEHEGEHBBAAABDHFBCCCCFFFHFCABFBHBHBEDAFEHBHACABECHCH,False +44,2.0,1.0,3.0,4.0,5.0,3.0,6.0,5.0,CHCHFGBGEHFDAGADEDEGGFGEDEHCH,True +45,17.0,20.0,26.0,20.0,18.0,24.0,15.0,12.0,BDEFBBBHHECFCFCBBFEDDADADGECEHEFCGCAFDCGCFFEDDGGHHHHHAFAFEFAFDFDFDEDFAACFCFCDCBBBCGCGDGDFCGCGBDCACBHDHEECBBEBECFCHGBGEGABCDCEFHFGACDFAFAECEBEBDACABAGFBA,False +46,5.0,7.0,11.0,5.0,5.0,3.0,8.0,10.0,CBDHFHCDCEGEHCHCHCHEGCGCGBBBBADAHGDGBACGEAHBHFGFCECAHD,False +47,5.0,4.0,4.0,5.0,0.0,1.0,5.0,3.0,ACABGBHBHBGDCACHCDAGFGAGDDD,True +48,21.0,22.0,13.0,24.0,16.0,18.0,24.0,19.0,DBDGAGBGFHFCABGFECEGBGHHEACDFDGCGBEBGDAFAHADADAHHBHBHAGABADEBFDGDBDGDGCFAFAFDDDDECGFEFEAHAHEHEHCBCDADGBFBFAEBCAHFHEDEGBBFDEHEBDHFGCGHGHGBGCDABCBDGHGBGDCEAFAF,False +49,5.0,12.0,11.0,8.0,8.0,7.0,11.0,9.0,FCFDGDHBEBECFBBHFCFCGDBCCCGCECECBDBGBEHDDBCAGAEHEDFDHGEGAHBHGAGAGFHBHBG,False +50,2.0,7.0,7.0,4.0,6.0,13.0,10.0,11.0,BBFEFEFHAHFDFGHEBABDFHBHEFGFGHEHGGGFDFEHCBGBFDFHFHCCGCGHGCCC,True +51,5.0,7.0,11.0,12.0,13.0,9.0,8.0,13.0,EFFBFDAAECCCHDHBHFEDBHBHDHDGGGGECDGHCFEFEDEDCDCDEDCCHFEFEGCGBHEHBHAHAGDFCEAEHB,False +52,15.0,6.0,11.0,6.0,11.0,16.0,3.0,8.0,BAEGCCEAHBFCCHFABEHEFDCHEBECACECEAFGFEFEFBFBFAFADADACACDFGFAFAFEFDAAHFDCAHHH,True +53,20.0,14.0,19.0,11.0,13.0,12.0,10.0,17.0,CHCECEHEGAHBFGHCHABCBCDCECEDAHACGCADDBBGFGFGFHAAACACFBEGGAGAEHCAAAFDFDCHBDBHGDFDHCBEFEBCBABHHHHDHCHDFEFABEBECAAAEACF,False +54,18.0,14.0,15.0,22.0,24.0,20.0,25.0,23.0,EGGCGCGDEDEBCBFDDDBFHDDGFBFEEEGDBDBEHFDFEACACADABEFDCECGGHBDCDBAGHGFBFECHCFEDEHEHAHEEAGCEEEEFGFHFAAGEEHHHHAHAHDEFGDGDBCGAGHFHFHAHAHDHDBFBFCEGGGGGGGHAADAGCDFFAHCB,False +55,3.0,4.0,2.0,5.0,2.0,5.0,3.0,1.0,EHAABABGBFDFGFGEDDFDCBCDF,True +56,9.0,9.0,8.0,11.0,11.0,13.0,8.0,11.0,ECFFFBCDEDAFEBEAFGFHFHFDEHEBEHEGBFEFHBABCCAGAGBGBDFHAHGHFCFDHDABADEDEDAHGGCDCHCD,False +57,10.0,13.0,10.0,15.0,7.0,9.0,16.0,11.0,HHCFEGEGEDFGABEHEADCHGHBDFDGDGHGCGBBDDCDCDBDBHCDEBAHACCFDGDFAFAFDDAGAGHGCGBGBHACBGBGAHEBFBF,False +58,15.0,15.0,14.0,21.0,27.0,24.0,20.0,28.0,FAFEFAADAGFBFACBCBHHCGFGFAFHCEGEGHHBDBFHFHBEGDGDAEEHEGCGDGHCDGDEHFHGCEEEGEGEDBDEEEEHHHHCHDAGFEBHFHAHFHFDDDCACHFBDDHDGDFDAGGEAEFBHEEEEBEHEFFCFCFDBHAFADCGCGFHDHEBABHB,False +59,11.0,16.0,18.0,17.0,22.0,31.0,15.0,17.0,FCECFCFCFBHCHBGBFHGEDADADEFEFHFDFDADEEADHGAEAECGDGCCFHFGFHFHFHFBFBFCEEEBEFFDEGGBHBEBHFCDDDDGHAFBFBFCACHCAFGCGHHEDCBFEFABCDCEGGGDAEBBBEDEFFFFECGHEHF,False +60,11.0,9.0,7.0,2.0,10.0,10.0,11.0,9.0,HGHCDCHCACBCEGEGEGEBBHCFGABEBFAEHHFBFAAGHGHFHABABCGEGFDEAAABFEFEFGFGA,False +61,23.0,23.0,21.0,24.0,24.0,17.0,27.0,24.0,EDGGCBCFCGCGCFCGCDCBAACHFHFHECACAGAHFHDBDEHAGADHGEGEBCAEAGDHAADDDDCEAEADBGFDBBBBDHDGDBBGCAAEHEGDGBGBFHCGCDBBBEFHFDAGHCDCHFHFGEHEGEGHGBEFACADAFCBGBGBFHDEDEDFBFEGHGHAHAEEEEGEDHAHACEFBHB,False +62,21.0,13.0,9.0,12.0,17.0,15.0,25.0,10.0,HFGFGBGEDEHGHAHFHGAAAFGHBFACGDBEBGAAFEGEFEFBGAHDEDECBCBFBEGAGAFCCBBDBAGABAGGGGGECDADAGAEFEDGACADDCDHDEAFHFHFGGGFGCABAEEEGE,False +63,6.0,6.0,3.0,12.0,7.0,8.0,6.0,13.0,FHEBEBHGHDAGHDCDEDEAFCFCHEEBAAFDDDFDHDAGBGFDHGHAHDHEHFHFHBDBG,False +64,6.0,15.0,15.0,8.0,14.0,13.0,8.0,8.0,CCEDEDBHHGDCBEFEFCCGCEAGFGEGECAHAHGBCFHACEBEBEGEFFFFBDBFBHBDDEDCBCBHBFGFHEAEBCBCFCBCAFD,False +65,6.0,4.0,3.0,4.0,6.0,8.0,5.0,5.0,CGCFEFAFAEEDEHCHBBDAAFAGHEHEBFDHDBAGFGFGF,False +66,17.0,8.0,15.0,6.0,16.0,16.0,11.0,12.0,AFGFGFGHGFECECECHAECCCFAHAFAEHGGCEBAFAEAEFGGHCBFAAEHFHFGBHEHGAFBFHCECEADFDBDBCACACAEAEBEDDACBDFHFHEGC,False +67,24.0,12.0,23.0,14.0,18.0,18.0,15.0,12.0,CCCFCFBHAEEDFDBAADAEAEABDBDGEHEGCCCACECHGEGEDECACFCFCHBFBAGAFFGHADBEBAAAAFAEECEDHDHECGGBHHCHDBGBABAGEFFGFAFADACADAGADCHFECGFGFHFCDCEGFCC,False +68,31.0,17.0,27.0,38.0,29.0,28.0,14.0,16.0,ACACBCFDGBHBDEGEAHDDEFEFEFEFDDHECEBDFDAEAEFECECGCHAHAHCBCDAHBDDDDEDEBEHGDDAFEFCFDDBCGAGACCECAADADABAFEDACGCAFAHDFDBDGCECBGBFFCHCGAEDFFFHADFDADGFAFADEDHABAGAGEHEFBFECEDEDCGEADADFDHBHDFDCBCFCDAFAECFCEHB,False +69,5.0,4.0,3.0,4.0,2.0,3.0,6.0,4.0,DAHAGAHAHAHFGCGEBDFDEDGGCFBBGBC,False +70,5.0,7.0,9.0,5.0,2.0,11.0,6.0,10.0,HAHDHDHBGBFCACDCHFBBHBHGDEACACEGFCDHBGFGFGFCCHBFFHFCFAF,True +71,11.0,10.0,6.0,19.0,14.0,23.0,11.0,9.0,FHFEADABECHFFDFDFHFEDECEFEFEFAFHDADAEADDCAGFGBBHGDGABDDFFFFDDDADEEGFGDABCDGGBHDHFGAGBHBHBEBEGFFFFFCCEDE,False +72,25.0,17.0,20.0,19.0,16.0,13.0,17.0,22.0,GDCDHGBEAEGDGEBDBDHDCDCBHDEAEHDCEFAAABCDCDABAGADADCFAFCGCACAFFBAHGCGCGEGEACHHECACECEHEGGFBDHFHAHAHGGDGFCECHFHFHCHFABABFDGABDEDABABHEACAFDHHGHAHBBBBEH,False +73,15.0,19.0,20.0,23.0,23.0,21.0,22.0,23.0,GFGFECGCEEGHFCBCFDDDHHGBGHGHDCDCFHAHCCCFHAADEBEHEDEDADCDCABEGEFDFHCHGGAHAHFCFCEADFFECGBDBDBDCCACADHGCGEGHFHGHGBFADEBEBEDGDBBACEEEHGBDBFFFFDGEGDGDGFBEHHHHAAEAEFBBBBEFH,False +74,3.0,11.0,6.0,11.0,10.0,12.0,5.0,7.0,ECHFHDHEFFHHDCFGEGFDBEBEFFFDBCBFEDCDCFEBBFADDBDBGBGBGBAHAHFDEDECE,True +75,21.0,13.0,22.0,19.0,30.0,19.0,18.0,19.0,HAHEEEFEDHDFDBHBGCCEEFEGGHGHCCCCCHGECEAHDBDBEFGHCACGBEFEHAFDFACAFEEEHABAGAFDGDADADAGBCBAEADAEFHCDCFGEHFHDEDCDFEFCCCEAEAEGGABFGEDBDBHBCCECEHEAEFGHGHDDAEAEHCFGFGFB,False +76,14.0,30.0,18.0,20.0,25.0,19.0,27.0,30.0,FCFBAEDEGEHEBGHGFEFCGDBDGGCGCGBEBHBHEAAAEECBCBCFHFCFDGAEHHFGGGGGHCHEHBABGBGHHDFAEBDBDBDBCCHAGGEGDGCCBCHFGFGHGHBHEFGHBFBCBHEHBBABCBHBCGEHEADDDBHFHAADEDBFHFEEGEDHDHDEDBDFEFEHCHAEGDHBFBA,False +77,25.0,17.0,30.0,29.0,22.0,22.0,23.0,24.0,CCHEAEHBBCBDADBDBDHGFEECBDFGFEAHDCGCDHHEHEHCGCFHGDGAGAGACACDDDFDFDGECCHDHCCEFAFEBAFGGHDCCGEDBDBDBCHCACDBAHCGCGAHAHAFFFHADCDCFCFHHCDCAEAGAGAGABFHGEGBGDFHEBEFCFAGBEEAABAGDGDFDFEABHCDEDEHEHEFCFCD,False +78,9.0,16.0,9.0,5.0,4.0,15.0,4.0,5.0,BCEADCBBBBABABCCEHFBDHFAAGAGHCFCBCBFDFAGAGBFBDBABFFFFFCEHEBDHFFFBFC,True +79,19.0,17.0,10.0,29.0,13.0,8.0,14.0,14.0,DEDEAEAEDDDDDDDHDGEBEFADAGBFFHDGFBBBBGBABFCHGDFDEACBBBAHADAHCGCAHDHEHABAGCGCGEDAGBDAACAHDBCBGBGBEDDDDDADGDFDHHFDAHAEEEHCDCHG,False +80,9.0,11.0,7.0,9.0,14.0,3.0,11.0,16.0,HEHEACBHBHAGEBEAEBHBHBDEDCFABCGAEABHEHDADABABGGGDGHECEHHDGDHHCHCDGFFHCBEDEGEGHGE,False +81,4.0,9.0,4.0,9.0,3.0,6.0,6.0,5.0,BGBACACHDGDFDFBFEAHFBDDEDEGHGHBBBFBADHDGCGDBFC,False +82,11.0,21.0,22.0,24.0,26.0,28.0,21.0,21.0,EDGDCDCFGEDEFFFFGEEEDEDEDADACHCEBAFAFCHEDBFEDHDCCAHGFDFDGAGEFECEDBHCECDGGGGGBGFGBHCGDGFFDCAGDBCEHEGBBBBHFHADFHCHCHCACHCBBEFAGBGBEBFFFHFBCEDFFEFHDHFHFCCECBHBDBDEDEHBHEHFBFEGAG,False +83,2.0,4.0,1.0,3.0,2.0,4.0,2.0,1.0,CBFHFBBDGDFDFEGEABA,True +84,18.0,13.0,21.0,13.0,16.0,19.0,15.0,8.0,CBCEEADAFGDCFHFHDHFACACEDGACFGGGCBABDCCCCCCBABABABDBDFACGCGCFCAGEFEFBDBCFEFEAGFDBEFEHEHBAEADAFAFGEGECAHFEDGDHHCAEDEFCFGGGBF,False +85,14.0,12.0,10.0,10.0,16.0,19.0,9.0,12.0,FGBGHDEEEGBFAEAEDHGHGFEDEFEGEDEFEFCBAHCHCFBFDGECFFFGAECBBBDGFAFACACBEDABEBFHFHFHAHAHFEDCDCFCAAHBHADAFB,False +86,14.0,13.0,10.0,16.0,18.0,7.0,14.0,15.0,GGGGHADGCGCEEEDEDBAAGBCDAEABAGAFFFDBEFEAHAHBDBDBDBGHAACDHHGHGHDHEFBCDCHCHDEEBEBDADABEFECCGHGHFHDGEEEADBEEHC,False +87,9.0,13.0,17.0,12.0,12.0,23.0,13.0,12.0,EHCHBDDCECFCFCFABABGBFDFDCDHBGDHDGBGCGCGCFCDHEHEFCHGEAFBFBFDFHCEBAFEDEDFFGHCFGBGFGCDCEBGFHFAFBEEEBGFFCFAACAHAHF,False +88,6.0,3.0,0.0,1.0,3.0,3.0,5.0,4.0,GBGAGBHAGAGFEBEFEHHAHAFAD,True +89,11.0,11.0,12.0,15.0,16.0,12.0,7.0,10.0,BHBHDDADCGCAEHHDCEAFAFBFCDEDECBGFCECHAHGCAEDDBDEAFAFHFDCHEBEGEGADBDBHEHDFGFGFDECECECAAEBEBDBFF,False +90,18.0,21.0,18.0,8.0,15.0,18.0,18.0,10.0,BCBDGCBCHGHAAFAFEFAFDFHGGGCCECEHBHFCADAFAFEGBAAAGAFBEBEBEGCBHBFADAECDGHGBGECCBCBABHFFDCEFEHGBGBGBEFGABCBFBDBEEAHACGCGEGFCFCFDA,False +91,21.0,22.0,23.0,29.0,25.0,21.0,20.0,16.0,EDECECBBDBGGGDHDFCFDFAFGBACHDHDADFDHBEAACACACEDECEDGDGEGEGEDEAFCFEGGBEBGFGEDECGFAFAFGHEDFHFCFBFBDEDFDGBHEADHDCCFBABABACGEHAHFHCEGEGHBHDACADFCCHBHDCDCFBHAGDBABEBFBGCDBEBCDDADAEEC,False +92,22.0,26.0,23.0,24.0,20.0,30.0,22.0,18.0,ADAFEGHDHFFFFDFECADDDFHBHDCBFAHCHCACHEGFBFBCDHEFEGABAFAEBGBFFFBFCFGBHBEBAACAHAEDEDEGCDCDCDCGHACFCFHFHGCFCEHEHCGCDCEFGDGBGBGEGBABGBGCCABBBDBAFGDABFBFEFEDADBFEFDBHGHDFEFECBAGGCGADDDGBHAEA,False +93,2.0,2.0,1.0,3.0,0.0,2.0,1.0,2.0,DBDCDGFFAHAHB,True +94,18.0,8.0,12.0,13.0,10.0,9.0,12.0,11.0,HHFAEHCHCHCDDAFACACACGGFEFGCHDEEGCGCGFDDADGDFDEBHCDABGBABDGAGEEBAFABGBDAHAFAFADADEHHCHCBGEAEA,False +95,4.0,5.0,6.0,3.0,5.0,4.0,4.0,3.0,AHBFEADADAGFHFGGCBCBCBCFCEHEBDCEEG,False +96,6.0,10.0,15.0,4.0,14.0,9.0,14.0,11.0,ECECEGHGHEHGDACGHHHFGFGCCCGFEEHEAAACCHCFCFEGEDHFHFDFGEABBBBEBHGCGBEBGCACBEBEGCCDBFG,False +97,3.0,4.0,3.0,4.0,3.0,2.0,2.0,6.0,BGHFHDHDCDBDECAHAHAEGBFBHCE,False +98,14.0,9.0,9.0,12.0,16.0,15.0,11.0,5.0,BGGACFEGEGEAFGFGFGFAADADACBCFDADGEBHBFDFGBBDCGAFAEEFECHCDCBFEAEAEADADCEBDDHDBGEFCHEHEFEAEFF,False +99,24.0,22.0,16.0,19.0,18.0,22.0,22.0,17.0,BABDFDEDEDEHAACABAEAFFGBHFGAHDBCAGADEDCHBBGEGAGAGAGAGFGABEDEDEFCBABDBECECEAGFGEGBGACBFEHEHAHAFBFBCHEFGDADAEEBCBHHHFHFBAGGGFFFFGHDCCHAHBCBCHFGDBCCAFBDGGFDHDFDFDC,False +100,10.0,7.0,6.0,7.0,6.0,11.0,8.0,15.0,GGHGHGFEFDCHAHFHEHEBACCBCHFHFBCBEBFFEFHAHGHDAGADAEGBGHHBAAADCFHFDADFDH,False +101,21.0,23.0,9.0,23.0,25.0,21.0,22.0,21.0,EEEEEACAHEHDDADHFBFBAHGHGBGDGFECGBBBBFBFEFHFGFGFAEHDHAHAHBHGHFBBHGGGGGEHDDDDHEAFBHHDEFEHEDDGBCDCHBGDDFFCAHADEDEGEGEAABBEBDFGEBABCDFEACFDADAGAGEGBAFABHBDGDCEEEAFAFBFC,False +102,1.0,8.0,5.0,3.0,5.0,5.0,6.0,8.0,HCGCHDEBGFEFECBBBFBFGHGHGDGBAHCFCHHHEDEBB,False +103,29.0,22.0,27.0,17.0,23.0,16.0,31.0,26.0,GGHCFGEBEDGCCDEBFFFEFHGCDCBCBCECFCHCHCHGHCEGAGCECABHEEEBEBEGAGBBBABABFBHBHDHGGDADCCFAFEDECEABGBFAFHDAGHGHADEFGBDCHHDEDCHGABABFGDEAAAEBGAAEGGGGFGHAHDBDCCHGHBDGEGHGEAEACCHCACAHGHGHAHDCACAFAGAFA,False +104,7.0,6.0,18.0,7.0,11.0,12.0,24.0,18.0,GDGEHCGGGEFECEBECGCGHGCFHFHFHCDFDFGACHHHGBGHACDCGAGADBCAHECACGHGHBBCFGHEDEFEHGHBHGGCGCGCHCEGGDGEAFFHFCF,True +105,16.0,23.0,21.0,18.0,22.0,17.0,10.0,18.0,ACEGEHEHAFACDCDCHFBFBGBHDFFFCAGHBBBHBHFABABABAHEGCAEEEFGBGBADGEBCDEHEBCFCHBHEFEBDDDDDDDGFEDEFEHAHBCACACBDBDHDCBCEDEHEGCCFEEEDHHAABCFCHAECBCBFFCFG,False +106,9.0,10.0,12.0,6.0,8.0,7.0,13.0,7.0,FABABHCEGEGBGBGCCCHCAAABGEGDGFGFAFCBCGCEHDCCAGHDHCAEHFBFAGBGBGHFDCDBEEDE,False +107,17.0,15.0,17.0,17.0,16.0,26.0,15.0,17.0,EFBHGEAFDGCGFGFGDEEAEGBDEFBGGFAHHCAFAFHBHBDGDGEGEGDFFFDFHHHAHBCDADBCBFGFCBCBGBFEHADAHCECFCECHBFFFFCDEDEDCDEFEFCHHHCACAEBCGAAAAHADAFHFBDBCFDF,False +108,20.0,24.0,27.0,23.0,19.0,28.0,19.0,18.0,AFAEGFGFGAHFCFEHEGDBBBEBEBEBCDDDHDFGFDCDCECFAFAHAGBBBEBFDEBCBAHGFGAGABDBEAGFCCCBEBHCDBDFDFBBHCHGGCDCDFHEHECGCFFFADAHHHDCDAEEBFGAEHCDDGACACACFCBEFFHAGCCCCEFEFCABDBFFFGHCHDHDFDGBGA,False +109,9.0,16.0,17.0,17.0,16.0,16.0,12.0,24.0,EGDDDAHBEAEABDCEBFFHFHFHCDGHAHCCFDFDFDFBBEBFBFEHGHGDCFCGHGHGCBCEDHBCDHFHFBFGDGACCCGAEBHBABCHHEHBDDEHEDEDEGEAHDHCECFCFCBHAHEGBHH,False +110,5.0,7.0,7.0,3.0,11.0,14.0,10.0,14.0,AHEHDHGFEFGCHFGFBBCAEFEFEFECEHFHBHAHFCBGFABHBEDEGCGFDFACGCGBFEFGHHHHEHG,True +111,20.0,16.0,22.0,22.0,11.0,17.0,13.0,10.0,ACAFFCDCDCACBFAFGDAACDCDEDEFFCBHDGDCDGDEABFEAADDCAHHDHEGACEFBCBCACACABBHDHDHEHCAAFAFCDDEDFDFBFCFBFDEDFFGGAGCCBEBCBHBAGGGGGEGACBHBDB,False +112,26.0,22.0,28.0,29.0,20.0,26.0,21.0,19.0,GCDCBAEHEHGGFABGFFFFBDBDBHCHCHAAADGFCBCDCFFFDCHCECEDEAFBFEFEGGCDCDAEAECFCEEACCBABGFDABADAFHBHFEFEAHAEADFCFHHBHAHAGGDHCCCDHBCADABHBDCGHGAGAGDDDFCAGBCBDBCFCFEHEDEBGGFGFDBCGAGDCDEDGDBDBEFEHAFADD,False +113,4.0,0.0,3.0,3.0,1.0,0.0,3.0,3.0,HAHADDGDHAGAECCCG,True +114,15.0,25.0,14.0,19.0,17.0,16.0,17.0,18.0,GDGCHHEBEBHBEFAFEFBFHFBGHEFEFEBAAAGFGDDFDFDFDBDBDBABABDHCBGDHCEBBGBCBEBAGHCHBEBGHEHEHEACACACACBBGGFGHCHDGBCDGEFDFDBEHECDGBCEHAHDHACFGADFDBAGD,False +115,4.0,7.0,3.0,5.0,3.0,0.0,6.0,6.0,HGHBHBDBABACEGDGEAHBHADGEGCHCBDGDB,True +116,18.0,19.0,11.0,27.0,26.0,22.0,18.0,28.0,FDFEHEBGBGBCFDFDFBEGFABHCHEEFAFAFAFBDHEHEABBDCHCDDGEHEADAFAFBHHCHBFBEDHGHGBFDFGECHHABDEGECEDADEHEDCAHAGEBABCDCDAHEDEDEDFFFFFBFHGAFEGEGDHDHGHGHGEDHDGEGDAHABBHHDHBCDADHEGE,False +117,9.0,10.0,11.0,5.0,12.0,11.0,5.0,12.0,HFBFCFBAAEABGHCHAFABBBBCCCHCECECHCGEHEHEHFHAHCEDDFDCEEBFFFFGEBEAFAHDGBGDEHA,False +118,1.0,8.0,6.0,3.0,6.0,11.0,9.0,8.0,BEBFGFGFBFBGBCDFEHBHAGEFHGDEFBFHHCGCDBGFGFGHCHFHCECE,True +119,16.0,21.0,23.0,14.0,8.0,20.0,24.0,21.0,EEGFBBADAFCBHFACCCFCFEFDGAFHFDABHBCGHHHBHGHCHEGCAABBGDHBHBGFGCGCGCGHFEFCFGABAGGCGAGACFCBCBHBFCFADHDHGHGFDEBEGCGCDBHBEAACHDDFDCDCFBFBGGGGCBHDHDHFABA,False +120,23.0,16.0,16.0,25.0,12.0,20.0,24.0,21.0,DFHFBBDGFFEDCHEEGGGEEADAGAGDBDAABFDFCGDGAABABABABACAGGHDHFACECBDDFDHGHGHBCBCAGFGBGCFFFDFDCGHGDEEHBCDCBHBCFGFDFDHAGCHHHHHGAFADDHEHEAGAGAGHCBAEAEDCDADCFGFDHDHF,False +121,19.0,17.0,15.0,20.0,28.0,24.0,23.0,17.0,DCDFFGAAFFFBGAGDGCACHEHDADADFEHEGGFFEFAABBHGGGFHEHACACBEEEHBAGAGFDFEBEGEBECECDCHBHGDGBEFEAEAEAECCGCEHBHCFFGBDBDCDAEEEAEFFFBHAHGEDEBGFGFGHGBGBDFDCDHEHDDDEBAFDFEGCFH,False +122,24.0,21.0,31.0,19.0,20.0,33.0,21.0,17.0,CBDGEGCBFGFHFHFEFBDAECCCBCBGHDCCCAFADHDHDEDACBDBGAHABFDGEGCHEECECDAFBGBGBFFFFHEAECHFHFHGEEBCFCFDGEGFFFFGCDCGBGBGFFBFBFAAAAAFGBAFABECAGEGBGFHFCADDCECHFAFADAHFHEDEHCFBACAEAEFDCCCCCBCHDADCG,False +123,23.0,22.0,33.0,26.0,18.0,14.0,26.0,19.0,DGDGCACABHFCADADGHGEEHGACAHAGACEDEDEDGDFCHDECFCBCGHGECHCHBEEDEDEDEDCBGBGBABCBCBHAGDGECAGDCCCFCDCFHFDABECGBGFHBBFBEBEBACEDBHHCCGCDAGGGFCCCGDDFCBCBGBGHGHGCBADHFFAHDGAAAAABAFDHDHCFCEAD,False +124,14.0,14.0,13.0,14.0,9.0,17.0,19.0,18.0,DCBFBFAFAHBHGFBABECACGGBGCGCFAFHHDGDGEBDADFFHHHHDAABHFFEGAGFDBGHGAGBGHFHFGCHCDGEGEFCGDGDCDCDCECBFAFCFHAHEBEGHBEBHHADAD,False +125,22.0,17.0,18.0,14.0,19.0,23.0,19.0,20.0,AFFEGCACEHAHBHFHECADBDEDHDHDACHCBCBHFDDAGHGHCECEAEAHBHGGCEAFAFBDGFFFFBAGAFAFHHCGDFFAEBBABADADBCGHHHGACACFCFDFBCGHGEGEGBGBCBEEAFHEBBGGECEFECEHGGEAFDFDFAF,False +126,2.0,2.0,5.0,1.0,2.0,0.0,0.0,0.0,CBABCCCECEAD,True +127,9.0,13.0,13.0,20.0,8.0,15.0,15.0,18.0,GGEFDFEHDHDHBAGABBBFFHFCFHGHGHGHGDADHDEDFCEDAGAGCBDFDHDHCBCDFDBHFHGHFBCGDDDDDABGHDHCHAAECFBDBEBCBCEGECCFFHCGAGF,False +128,26.0,16.0,20.0,13.0,15.0,14.0,8.0,14.0,AFAFGCBFDCCGCBCACACAFACECBAFAFDBBABABHECBGAHADEDCBADABABAHEHCHCHGECDHDHBHBAEDEAEAHBGFAHBBCACACAFEDCAHHEADGEGECEFFFCGHDFDEAEFFD,False +129,3.0,2.0,3.0,1.0,2.0,1.0,0.0,1.0,AHABFBEAECCDC,True +130,3.0,10.0,5.0,11.0,10.0,4.0,3.0,9.0,DBGBHBAEDEBCCEBAAFHHDHDCBEDHBHBHBDECECEDDDFDGDFBEGEHEHF,True +131,18.0,19.0,23.0,22.0,20.0,20.0,15.0,23.0,FGBCAABCBCDCDCBBAAADCEGHAFDFEBHBHAHGDAEAEAHGECHCDDFDBEBHHHDBCFCABFHHHABFHHEGEHBAFAFCDCHGEGEFBFEFEDEHCHCHDHDGFAFEBEBGBGFCDCAEDEGFFFHFBEAGACFDDDDHDCCCCDCDGEGBGCEH,False +132,27.0,13.0,16.0,13.0,20.0,12.0,27.0,15.0,HAACDHGHEBFFCDAGADAEABAGHFHDHCCAEHFHBGBECGGGGAGABACDEDCACACFGFGFHBBEBHGGGDABGGGEDECEAEAEAFCEGBBBAGAEAEABHEAEGGGCEHFHDGAGEDEDFDHDEAAGAHAFFGCCCCG,False +133,5.0,7.0,9.0,1.0,6.0,7.0,8.0,7.0,BGCFEBHHHHACABFBFHFCFGGGCCECGCGCHAEBBHFGCGDAEAEBEF,False +134,14.0,15.0,11.0,16.0,21.0,17.0,16.0,20.0,HBHDHFHDDEFEGEFEBGDFDFBBHBAGEGCFHBHDADHHFAFAHECEFADECEDDDBDBDACBEAFHFHGEGCGDECECBAGACHBHGHFHFHGEGFFHEHCHCEGEGEAEGDGEABDBABFFGECABA,False +135,8.0,3.0,1.0,2.0,4.0,6.0,9.0,3.0,GFGEGHGFEFGCGDBAHAFDEAEGBGBAAAFAGAHF,True +136,14.0,29.0,20.0,23.0,25.0,22.0,18.0,18.0,DGDCEBGFHDBFBECHFEFBDEDCACGCGHEFEFEFAFGGGDCFGFHFHAHADEBBCBCEEEFEBABCBEBACACBHHCFCEAEAGBGDCDBDEDGBACECBHEHBDGDFDGCGAFEFDBHBEBEAHGFCFBFBHEDFDGDBBBBACDBDHGBEAEGFCHBHEHDHDFD,False +137,3.0,5.0,1.0,6.0,8.0,6.0,3.0,5.0,FDFDBBBEDEHEHEFEACFFGDHDFGBHAEAEBEGDH,True +138,17.0,19.0,28.0,23.0,19.0,29.0,14.0,27.0,EEHFCDHDHBAADFECECFFFCDGBAHAHFHBCDDFDGDADBCAAHABAEGFHFHDHDEGCGHGHCFDFEFGBHAHBCBABEEECDCDEHFHFBABHCCCACHEACHDGDFHFHBHFGDGDGDFBCDCGABFFDFECHCFFFHFCDGEFCACHCHCHEGACFCFBFEEECEBBBBD,False +139,18.0,10.0,15.0,7.0,19.0,9.0,15.0,15.0,BCDGAGEBBAAFCBEFDFHCAAHABFEADAHGCCCACEDEDEDEDEHCBCFEHCHEACACHGGGGBGEGFGFEHECGFEAHGHEHEHEHACAFBGGABABHGHEAEAC,False +140,12.0,11.0,10.0,15.0,15.0,9.0,10.0,21.0,GGDEDEDHDABGBDCAFADADEEFHFEEBBAHECFCAHGHGHEBBCBABAFHHHHAFADHECEGGBGECECHBHECFCDDDEEHHHHHDHDHDHFACGDABFG,False +141,6.0,7.0,16.0,10.0,19.0,4.0,7.0,3.0,GAGEECEDBGBGFCFCHCFBDBDECEAEDBDCHBEEFAHAEAEGCBCEADDDDEGCCEEEECCCECDCGCEE,True +142,17.0,14.0,17.0,18.0,21.0,18.0,15.0,9.0,BADAGADHDGDGFHFAFDFGEEDDDADCCCGGECCCGEHAHAHEEEEAECFCDHDFABABFBGBCACEFFDADAEEHBHFDFCBEBGHGCFCDAGFDBEFFGFGEGCBAEDEBCBAACDCBEBEFEFEG,False +143,1.0,3.0,4.0,4.0,2.0,3.0,3.0,3.0,DHDCCGCGAGHBBFEFCFDHDEB,False +144,3.0,1.0,7.0,1.0,1.0,3.0,7.0,2.0,CDCFHGGFBCCCCGAGAGAEHFGCG,True +145,3.0,5.0,7.0,4.0,3.0,11.0,6.0,3.0,DHGEGBGBGCCFDFAFHCBEBEBDFCFCFGFCCAHFFFDGAF,True +146,4.0,13.0,6.0,8.0,6.0,15.0,9.0,3.0,FABGBGFGFDBBBCGEEEEBFGCBFBDBCFDFGFGFAFECCDDADAFBDGHGBFBFHFEFHCBD,True +147,16.0,16.0,22.0,23.0,21.0,20.0,35.0,29.0,FBFEECGAGFGFGHDHDFAGEGEHFHFHFEGHGCEEAHDGDEHEGEFHFCFHGHBECDBDBHHGGGGGGCBHAHACAHAGEBDCEAGGHGHGEGEBDAHHHCHADGCFBFHGBGCHDFDFDGHCBCHHAGBEBDACHCFFGGGDADEEAGCEDEDCCCGDFDBDGFBFBGBDEACACDCDCH,False +148,16.0,20.0,20.0,23.0,21.0,16.0,31.0,18.0,EBEHGGGHCACFDDDDDAFCHEGCACFCFDFAGADEGGGAGEECEGEGEGAFFDCBHBHDHEGCDCGBGBGCCCCCBDGEBCGFHCHGHAHBBCEGEGEBFBGAHABDBDAGAGFGBEEEFEDGDAFCHBABGBADADEGFFDHDCFGGDHBFBDEDEDGHHHBH,False +149,3.0,7.0,4.0,6.0,10.0,7.0,3.0,5.0,EBEHEBEDCFCBBADCHFHFGBGBDEEEECHBDADADEFFFGFHE,False +150,6.0,2.0,7.0,6.0,2.0,3.0,8.0,0.0,DDDCGCADFDFGGGACACAGBECGGDGABACFCE,True +151,5.0,2.0,2.0,0.0,5.0,4.0,2.0,3.0,GAGAFBFEFECEFHABAEHEACH,True +152,14.0,12.0,9.0,7.0,12.0,11.0,10.0,17.0,FDHDFEHDHCFCBCDGHGCFFFBFHACCHBGAGAHEHEBEAADAHBGBFBFBABABAHAHEEAFHEHBHEHABGGECDCECEAGDHAHEFGG,False +153,19.0,24.0,27.0,19.0,23.0,23.0,26.0,24.0,CDCGGGFAAGACHFHDHDHBBCCHCGFAHABGBEDHBGBGBABADECFFFFAGGCHDDGDGCGHGHGDCFHDHAFEFEFEHDCCGGBGEGAAFCEEDFDFGBEAFHFCGEBCBHBFBDCDGBCBEHADABCHCHEHEHBHDGFGAGEGBBEBHDEEHAHAEAECCFFFCCCECECEFBFBDECBA,False +154,13.0,10.0,11.0,9.0,11.0,8.0,12.0,4.0,GEAEAFAGADADAEFCGCGCGCAFBFBEECEGADADACBGBCHHBFEECACBEHEFBFBDADEDBCGGGBDFHCAGGD,False +155,23.0,15.0,20.0,21.0,22.0,13.0,16.0,23.0,FEBEBEBFDHDHCCDDBCBEGFDFGBHCHFDAEBCBFHAHGHDADCBGDHDHDFCAHHHDBCEHDFDAAECDCDCBCAFEEEEEAEAGACHCEGEAEGGGGAEABAFAFHHGEAAACHFHAHFGEAEDEDEDADHDBCGAGACBCHHBGGCHC,False +156,1.0,2.0,8.0,2.0,1.0,1.0,0.0,3.0,CCCCCHCHBACDCBHEDF,True +157,11.0,6.0,5.0,14.0,10.0,10.0,2.0,6.0,EFAHAHFBFGGABADFCBEDEDADAHAFAHBFEDEDCDEDEDEDFFCBEDFDFBACDDAEHCHA,True +158,15.0,22.0,16.0,16.0,9.0,21.0,17.0,9.0,CFCFCAEBDGDHBBFBHCAAGFFFAGGGGFGHCHDBDBECECECFHBBCBAFHFDFBCACHCAAAEFDBDBCFGAADADAGGBBBGCGBGCFBEEGHGFGFDFDFABABDFHFDBDCEFEBGDDB,False +159,3.0,6.0,10.0,6.0,2.0,3.0,4.0,5.0,GGGFDFDBCBHBHBCCHCBCEHHFCACDCBEDDDACGCA,True +160,7.0,12.0,7.0,6.0,6.0,8.0,8.0,5.0,AEFEFEBCBADCEFHHCHGBBECAABFBFBDBGBHECGDADADGBGAHFFCFCGDGBGB,False +161,25.0,18.0,13.0,27.0,15.0,21.0,17.0,28.0,HFHGDDBDFDGHGADHGFBHGCFDAECCHHEFEFEDDBEBAHAHFHFBFHAHDFDFAEDFBBCEHADGFGAHDGDGDGDFCBCEAEBCBHDHDHAHAEADHHFHFHEGBHEDABABACDCAEFDDGFGAGABAHDHDGDGDBHBFAABAGAECECHCACBFAFH,False +162,18.0,23.0,16.0,12.0,17.0,23.0,24.0,31.0,AEABABCBCHCHCFFFBHHEGBABDDDDDHHFHEECFCFCBEDDBHBHBCGHDFAFHCHFGCHHHHHHHCFGFGEHDBAAEGGHEBBHGDAHFHBHBECGFAFBGCAHEHGBBFBDCHHGEAEHGFFFADGEGBGBGCGFFCHGEGEGAGAFABABAEAEGFGF,False +163,24.0,23.0,17.0,16.0,25.0,31.0,34.0,30.0,FHFHFEFGFBAEHHHDHDHFGGDGDGFGDHACAFGDGDECECHCGAHAHBBBBBFFFCGBGEFFHFEAECGGBBAGABABAFHFHECGDECFCHDBACDEHBFBHBFEFDDGCHBHGHGHBEAGFGCEHFBAHACEHEACFCFEAEGEGAGACFEAEBGGFDBDBGEGECEAHHHAGBGHAFDFAFDFGBGHGFGAGHEE,False +164,16.0,17.0,19.0,27.0,19.0,29.0,35.0,19.0,GDGBCCGCAFBFGFDHGHBFAFGFGDDECECDGDCDFHFGFCFHFEABACFHFBFHEEECEDFDEDGGGDGCCBBDBFBABFBGDEDEGBHBDDDGGGGCFHFGFGFHFEABBDCDCHCGGGDGFGEDADHDECEAGAFAHEHADAFFGGGCABEGHCAEFGFGAGDDHDHBCEHGAEHFH,False +165,10.0,7.0,7.0,12.0,6.0,6.0,5.0,8.0,DGFFDCDCDAEGDBDCEBGACECHCECDBABDEAHDHGAAHHHFHFBFBGBHDADADAFAE,False +166,17.0,18.0,17.0,16.0,20.0,19.0,17.0,15.0,CACAHAFBDAAADADHBGFAFDGDGDGHHFHFGFGFHHCAAEBFBFCFAHEBABEEGEGEGEBAHGDCDGEBCHEGDGCFCEEFECBCFHBHBHBADDFBFBGDCBCFFEGCAEGEFBACDCECECFDDADEEEGHBHB,False +167,15.0,4.0,11.0,15.0,21.0,12.0,17.0,17.0,HHAHDEDGHFHEHCHGFGFCECEGEACFGDGDCDCHADCEHEGGAEEBEBFHHHCHCHCFDAHAGDGFGDDHEEGCAEDEABAEGEGHGDDFAAEFGAGAEAFAFDFEEBED,False +168,8.0,4.0,9.0,2.0,9.0,7.0,3.0,7.0,ECECBCHFHCGFGFEEEHEHECAAHAFFBAEAFHBGAEAHDBDACCCFC,True +169,16.0,14.0,9.0,11.0,11.0,11.0,12.0,11.0,DFDFDGAGAGAGFGHHACBHBHGFFDFGBCEAHBDAEADACCECAAEABBHEAEAEDEDCABABCBGGGGFFACHHBDBFFDFEEGBCDHEHBHB,False +170,4.0,2.0,1.0,1.0,6.0,4.0,5.0,2.0,GGDBEEEEBEAGFFCFGFHAHAEAG,True +171,28.0,14.0,20.0,10.0,8.0,25.0,20.0,36.0,HCHCDCGCDAGAGHGBABAFAFCFAFDFGFGEGHFEFHBHGFGCHEHABFGFHHHCFDACHEFBHHHCHAHGBAADCHBHBFAAAHHHFEGCGDAHAGFBFAADAEACFFGAEAGABFCHCBFDEAGAHBHBAAHHHFHFHCCACGHGHDHDHCHCFCBGF,True +172,3.0,11.0,4.0,4.0,5.0,7.0,5.0,5.0,BBBEBHHCCFEFGFGHGBBBGBDFAFACEHFGFHDBDBABCDEE,False +173,8.0,13.0,6.0,15.0,4.0,10.0,15.0,7.0,ACDCGBGFFFGEGBGFHBHDADHDFGBGBGHCDAGGGCHDHGADDDDDDEBBHBFBFGFAEADGCCBDBDGAAEFBFB,True +174,10.0,11.0,8.0,10.0,13.0,7.0,14.0,11.0,GCGCGCGFGEBCAAEEHEAEHDHDGAADADADFBEDECHCGGGHGEEHBHAHABFBEBHFADGDHEECHBBFBGEGBGDCFBFD,False +175,23.0,12.0,12.0,24.0,26.0,34.0,26.0,24.0,CDBFHAHBGAAFEGHAFGCAFGFGBGBEBEAFGDGDFDADCFGEGBFCHABFCGADHFFEFHFEFEFEDHFGCGEGEAABEGAGHGEAFAFAFCFAEDEDEDHDHDHFFFGFHACEFHHHDHDAGFDFGEGBGDHDBABAFEEEHEBGFGEEAEAHHFDDDGHGHDFCFCACHDDEDEFHC,False +176,18.0,8.0,20.0,16.0,15.0,17.0,11.0,11.0,FCFBECGAFAFABAEEEEDCDAECEDGAAADFHBDBECEHEABABCDCHBGEHAHAGAECHHHADCCCCFCDCDAGCFFEEAFAFGDDFHFHFHDBGGDGDADFGCECFCGCDCFF,False +177,13.0,12.0,13.0,12.0,6.0,11.0,5.0,9.0,DABFHGHCBDBDCFFGABAFEBACAHECGDFFHFHFDFEFCHCBCBAECGCGCHEAEADDDBDADAHHBACABACDCDBFB,False +178,7.0,14.0,10.0,12.0,19.0,22.0,10.0,9.0,FDECFBFDFDFHFGCEDEDEFHGBACCEGGAEBEGABFDFDFCHGHFFEDBFBFBFEGEHADAEFEFEFEABCFHDHDAECFCGBFBGBFBEECECDBEBHGH,False +179,2.0,2.0,2.0,1.0,5.0,4.0,1.0,6.0,HGFEHEHEFEDAFHFEABBCHCH,True +180,2.0,5.0,1.0,3.0,3.0,4.0,0.0,0.0,FAADBBBBEBEFEFDDCF,True +181,6.0,7.0,5.0,2.0,1.0,4.0,3.0,6.0,BHBDBAAGAHCHFHACAHEHBBBFCFCACGGDBF,True +182,2.0,3.0,10.0,6.0,8.0,6.0,4.0,4.0,BCBCECEAEDEDHCCCCHEHEGDGCFFFAHGBFFFECDDECGD,True +183,27.0,20.0,35.0,20.0,19.0,18.0,17.0,19.0,CHCHCFCBDEHBHEHCCCCBDBAADFFECCGCAEAFAHCFGDGAGACABFEAHCBDBDBDACGDEDEDEHEBGDGDCAGABEBEAECEGAGFGCABFGFCEAEAGACFCDCFFGFEHBDBDECACAFHBHCHBHBFAHDBCADHEHACAGDDDGCEBFBFCCCCGAHCFCACAHH,False +184,21.0,29.0,29.0,14.0,13.0,23.0,22.0,20.0,HBBEFAHAHDHCHCGCBCAFABDDHDFAAADBDBEBCBCBEACGCGFFBFAFHGHFCFEHCHDADFCFCEDBGBCCFCFGFHCHCACBEAFBECFCDAGGCGFGHGFGEGACCDCBHBACGFGFHFBFGEGBCHCBCDEBBCHGGBGBDDFAAAEBEBABHBABHGEGBHA,False +185,16.0,21.0,7.0,5.0,16.0,12.0,3.0,15.0,BBBHGHBACDBEAAAFDHEHAGAGAEEEHHCAEAFBBABFBCECAFAFBFHFEDABBBFBEBEBEBACHFHFHDHBFEAEBHAFCHEDECEHBHB,True +186,26.0,34.0,20.0,22.0,24.0,21.0,26.0,17.0,HFACACHCBBBBHBGBEHFHFEAHAEAEFDBHECAHAHDDBGEDCBEGGFGECAAADBEBGCGCFCFCFBFBFBAGCBBABEHGCGCGFGBBCHCEDAHBCEAEHDBAHGGDDDDHEADDDDDFFGBGAGBGBEBABDBDGDGBFBDBDBDHEFEFCFEAAFGEBCGEGBFFGCGAABAGCHEEEAFAEA,False +187,3.0,5.0,0.0,1.0,1.0,2.0,2.0,4.0,DEBGHGAFBFHHBHBABA,True +188,8.0,11.0,10.0,11.0,8.0,19.0,14.0,12.0,HGFBFHFBFGGAHDDEBAHFHFHFCEGFGFGFGBGEGBCEEAFDBBBHFHDBDBGACHCHFGCGFGCGFBCDCDFFAEAHAEFDFDHAECDCD,False +189,24.0,32.0,23.0,32.0,21.0,21.0,20.0,22.0,BBBABAEECDDDEDEHEBECEDEDHHHFHFDFHCDAHAHDBGBGEGFGFGFGFBAGCGDFBFHDHBBCHGHGFAEBEDCAAGFDDADADBDCFGHBABDHECBDBAAHADAGCDCBABABGBHDCGCBCGFEBDCHAHCCCFCFEBABHDDBGBHHCCCGBABDBCEEGHAFEFEDDBAFFFDFDCEAEAEGDBD,False +190,13.0,10.0,11.0,9.0,7.0,16.0,9.0,11.0,AGCHAGCBAHCBGBEBEACADADHDBFBDDAGEFCFCBHDEFEFHFHGHDFGFACAEFHAEAGGBGFCFCFHFDFCFCBBFDAHAH,False +191,14.0,3.0,6.0,9.0,14.0,7.0,4.0,6.0,EAEFDGEEFCCCFCFEAAAEADCDAEAEGGAFHHHHEAAADADEFEBDBAEGECEADFDHDHB,True +192,6.0,4.0,7.0,3.0,3.0,3.0,1.0,4.0,CFGEHCCFCBCEAEHCHDADADABBBACAFH,True +193,29.0,36.0,21.0,12.0,18.0,14.0,23.0,24.0,BBHFFFCEHEGEHDHBGBHBHDEBHBHBEAEBDBFHFHEHABADACGGGADBBHHFBBBAAAAABECDCACHCAGACFCFAEAFAFAGGDAEBDBHBEBGACBHFAFGFGBBCAGGBGHDCBBDGEHEGEACACACEBEBCACAEGDGHCBDGHGHBBABCCHCHCHGBAEAGBFBG,False +194,6.0,3.0,5.0,1.0,2.0,4.0,8.0,5.0,HBHGGFCFCACAEABGEACDCHBGGHGAGAFHFG,True +195,3.0,6.0,4.0,7.0,9.0,15.0,5.0,10.0,HAHEHFGFHHGHGFFCFCEDEFEDBGBDEDACBDFHEBFHFHFEFDFCFDFABEBGHFE,True +196,2.0,2.0,8.0,2.0,3.0,5.0,4.0,4.0,CCECHCDCDCEBHCGEHBHGAAFFFFGFGC,True +197,0.0,3.0,4.0,2.0,1.0,2.0,3.0,2.0,DBHBDFCCCGCGBGEFH,True +198,9.0,8.0,9.0,4.0,11.0,7.0,12.0,11.0,AAAFADHGGGFGCBCBCHEGEFEHDCABDHGEGEGDACBFHFBEBGBECEHAHAHGBECFCGEGAHEHCHF,False +199,9.0,8.0,10.0,11.0,7.0,10.0,5.0,6.0,ACADDFDHDABGCDEBEHAFFBECECDBBABAFAFAEAFHDDDHCCDCGCGHGDGHFCBCBFFEFE,False +200,15.0,9.0,5.0,13.0,12.0,23.0,15.0,22.0,CHGFEHBDGDHEHAHDFDFAEBDAHEFEFEGGGGAAAGEDAHGHGHECEGFGFGAGBFEFAFBFBGBDFAFHDHBHFHFHGDEDHFFCFEDBDHFFFAAHBHAHFCFDHHCHAA,False +201,8.0,4.0,6.0,6.0,2.0,3.0,2.0,2.0,AGCFBBCBCDAHABACEHDADADCDADAEFGFC,True +202,15.0,30.0,30.0,30.0,15.0,29.0,25.0,23.0,DFBBDGHBCEDBFBHBHBCBHEGGGEBEBHHEHCFFHFGBHEGBDFDFGBGDFDFHCEFHCGCFDHDFDEHADADEBCFEFDFEFECDAAHFGDDDCACACACACDBABGGEDAABBBGCACABFBGDCDAGGGGDCDFFFGFCBBBDBDHECGHGDGCGCHCHFBFHHHDHCEBFDFDFCFCGCBCBCFCDABHCG,False +203,14.0,19.0,19.0,3.0,12.0,14.0,16.0,22.0,CHAEADAHBHBHBHBGGDBHFHEAAABCBGEFCCHFEBHCHABABFHCCCHBHAGAFCFBFAAAHCFCGEGEHEHEHFHBHEGFGHBEGGGCCFGFGCDAECGCBBGBFBCHCHCGBFE,False +204,9.0,15.0,19.0,11.0,9.0,19.0,20.0,15.0,FAAACCHEGCGDGBHDCCCEBAHDGDFDBDBHCFGFCFCBCBFGFGHGBFBHHHFHEGBGBCAEBCCCFCFCHGAEFEAGCDHGHGFGFGCGBGBGFDACEBFDFDEHEDGHABFHF,False +205,20.0,16.0,16.0,34.0,30.0,20.0,29.0,29.0,CDCFGDGDEFHGHEHEGGBGBGBHBGEFECDCEBGDAHGCBDDGDHDHEBEDDDDHAFAFDEGCHEGFHFADBEEGAGDGDHFHBDEAEAHAHDDDECGBADEHEFEFDACAGEGFGBDEDECHHHEAEFFBADDDDAEAHHDHDCCFCAAAHCFCFEGHHHHGBGBDCHCHDFDGGEGBFBGHFAFEGEGEAE,False +206,20.0,18.0,16.0,14.0,21.0,4.0,6.0,11.0,ABABAFADEDBAECHGDDAAHEBBDBACECGAAAACHEFEBCDHGBCECECEBEFEAECBCEHEDGAHACADAHACECGDDEEECEHHHFECBCBEBHBDBDBDBAGDBA,True +207,1.0,3.0,2.0,6.0,1.0,4.0,1.0,1.0,FCADBDBGBFEFDFHCDDD,True +208,5.0,3.0,5.0,6.0,4.0,0.0,1.0,2.0,DCCBCDCDCAAAAHDHBGAEEDBDEE,True +209,9.0,6.0,7.0,6.0,5.0,8.0,3.0,2.0,FCFEAEGDADABCBCFGAGCFAFABABCBDHCFDFEFEACBDHEAD,False +210,21.0,21.0,15.0,16.0,11.0,15.0,20.0,12.0,CACFFACCCEHFDBGBGBFHFAGDGDADACGGDGBAACABBECECEGEDHDHCABDFDFDAGHGHGBGBFBGEGBFDFAGAEHFDAHEGABABFGAGEBCCGCHBDEDGBCACFBFAFHDBEBHBABADAH,False +211,10.0,24.0,13.0,13.0,14.0,11.0,16.0,23.0,EDEABACHGHAEGGBBBBECECEBBBAHGHGHCBCECDCBFBHBHFHFHFBBDAGFEBHAHDHGCFAGABCDDBEBEDHGHBCCACFDDBAHHHGBGBGEGEGHGFEFHHHDDBBCDEFGFHDH,False +212,19.0,7.0,17.0,13.0,17.0,11.0,21.0,24.0,FGCAHAHFGEHAAAAAHGDGHGFEEGDHHAEAEDCDFGBGDHDGFECECGGEEHGHGHCFBBHBFEEHGHGHDHFHDHDAAAHDECAAACBCECACAHFDFCCCCCCGGGGGEEEDHBHEFCGDHAHAB,False +213,10.0,20.0,7.0,7.0,13.0,11.0,10.0,5.0,HACBEBEBAGEEHEDAFABBFEEEBGBGBGBAAEBBDDFDFDFHCHDDAFECHBBAFAGGGFAFCGBEBEBEGGBFFCBCBCB,False +214,6.0,9.0,11.0,6.0,13.0,4.0,11.0,19.0,ECECBCFDGEGBHEDDHGEBHHGCGCBHHHHHEHEGACABADHFFGCGBGHDDCEEEEBEFHAECBCHGHGHBHAHAHC,True +215,3.0,0.0,0.0,3.0,3.0,2.0,6.0,5.0,HDFDHEHGGGGHAHAEGEAFDG,True +216,1.0,8.0,11.0,12.0,14.0,8.0,9.0,12.0,GEBDBDCCADDBGFGFEEGEGCDCEFEGEBEDCCFBHCEDDGEHEHDDFCHHHBHBHBCDFDEGEGCHCHEHFHF,False +217,10.0,10.0,22.0,13.0,14.0,8.0,15.0,10.0,DCHGECECEAGHEFGACFBGBECGCAEBEHHAGEGFDFDFHEDDCDBFBABACDDHDBDGCCCGHGACFCFDGCGCBCBGAGACECACBCECGDHEHEHECD,False +218,7.0,10.0,14.0,5.0,9.0,7.0,7.0,16.0,CFCECECDHHHHHHHHBBBHEFCCEBDBABAGDFDHCHGACCHCHEFEGHGDACFBGBCEEEFGHGFCBCHAAAB,False +219,15.0,20.0,16.0,12.0,13.0,12.0,14.0,14.0,AGAEAEAHGHFBFEHBHFGGEEHCFCDADACBDBFBCBFGFBBBCCAEGDGFAACAHBCBCDAFHFHECAFFEGEBCBGGCDCDCDEBBDBDBHHHHHDGAGDCHCAGEGABBEBE,False +220,0.0,1.0,1.0,0.0,3.0,3.0,1.0,3.0,HEHEHFFFGCBE,True +221,4.0,7.0,18.0,11.0,9.0,20.0,14.0,16.0,GGGBFCCCFBFDGCFCFDFHFHCDCDHHHGHFDCAGHCBAEEFEFEFHAEFCHCGEFCCCHCHEHCDCDAGBGBGCDDFDFGFHEHDHFGEGFHFGFBB,True +222,19.0,32.0,14.0,24.0,24.0,23.0,30.0,29.0,EAEAGFDFDCBHFAFADGBHBDAGCDEABDFGEEFFFEEAECHDHBHDGAHHGBGBGBGHCDFDBDBDEDADHFFAFEFGBHBGDCHEDABGBEBCDCHCBFAFBGBAHFHFGEDFHHHBBBBDBDBDBGEGBHEACCHEGEGEDEHECGHGFBHGHCBGAGHGHGEGEGEHAHAHFCCEFHFAGBGBGDADFBB,False +223,6.0,4.0,7.0,6.0,14.0,14.0,8.0,15.0,CEEFAGEBDFAHHDHFAFAHBFFHFCFEHHHHFDEGEGEDEDGAGHDFGBGBEFGFHHCHCHEHECFCACEEFE,True +224,11.0,10.0,13.0,13.0,21.0,14.0,25.0,19.0,CGBAEGEGEHHCGGHGCCBCAEBEGHCHDFDFDFEGBDFDFEFAGDGAGEGCGBHEEGCGBEEGEADACECABEDCDFFFDCAGAGHFHAHGEGEGEGBGBGHHHHHHDABCEDHHFFDHEHEGFF,False +225,6.0,19.0,5.0,11.0,12.0,6.0,9.0,5.0,GBHBDBABHBCBDEDBGBGBEBEBCCFDHDFEBBDDEAEAEAECFGFGEGABCFGBBDHDEFBGBGEEABHDD,True +226,11.0,18.0,23.0,14.0,12.0,26.0,20.0,26.0,EFEFEFGDCDFBHBHADECHHEHEFGFGHCBGACBGACFDFGFCFGFCCCHHHBHFHFHDADFFEBGFFFFFDBCCFCFHFCDGEHDFDBDCAGGHHHHHHBACGCGAGBGHAAAFFCHGBGCADGBBBCGDHEBEBEBEBHCHDHCCCG,False +227,23.0,20.0,28.0,18.0,25.0,23.0,23.0,21.0,FCCBCEFEDAGGBEHCHCHAFCCADFFHFEFAHCHDGCCHAEDEDFDGAGAGAGEFEBEBHHEFEFHFCGDFBGBDHAHBGAHFFFBFCDDADCDEEAGABHBHGHCHCABADABCHCHCDFGHGHBAFFEGECBGADCECGCGCBFEFDFCGCGDEECAGAEAGAGBBBBBCEEAEDECE,False +228,5.0,3.0,9.0,5.0,8.0,2.0,3.0,5.0,DDDACEHGFBCEAECCCCCFCEHEHEHEBCDAEBDHAGAG,True +229,15.0,19.0,18.0,23.0,23.0,15.0,10.0,23.0,HHFHGHEBFHHBCBDEEHCBGBAHAEDEDCGCGEBBDDDDEDBDHDFDEDACCEEDFCEEECBCBCBCDAFEHCFAHBEDACAGHHHHHHHAHGFACACAFBEBEFFFFFDEBEAEGCBEEDADACBHGCGBGDHDHDFDHDEABF,False +230,15.0,10.0,14.0,14.0,7.0,9.0,3.0,6.0,EDADBFADCDCDEBFBFAFEFEDCBADFBFBAHACCBCGEHEHBCCAGDCFFBAAABAGACHCHDDCCCEDHDADADA,True +231,21.0,19.0,19.0,16.0,21.0,13.0,13.0,23.0,EHBFBHBCDAEACABABEHCAAAAAEBDHDCECACAHGFCFBFBDCCBDBDECHCGCAAHHDDCDCDEEHHHADAFBFGFGDGFGHGAGEEFEHBBDBGHAHGHEBCCACACGEDEAABDBCEDEFEHBHEEEHGHFHEHFFGHB,False +232,10.0,11.0,13.0,7.0,8.0,12.0,12.0,9.0,EFGGGHCHBAEHFDFEADAHBBFBCGFGBCBCBCFHFAFAGCGCEBEDCCCHCHDGGGCGCADFEBEBDAFAFAHEFGBHDA,False +233,16.0,18.0,26.0,21.0,12.0,11.0,22.0,9.0,GBGCHBGDHEHDGAFCFCGCBBDDDHHGCEDEDCDBGBEBCCCCDBGBCACBGGEHEDGGAGACFCFCHCGGDGABDCCCGDBDEDEBBCHCDCDBDAGECECAFEFBFEAGAFAGBGAGDDDACAFAFAFCHBA,False +234,8.0,5.0,2.0,10.0,3.0,5.0,9.0,5.0,GAGBBEDFDFDBDGDAEADHGAGHBDGDFDFCGAGACABAGHHHFED,True +235,28.0,16.0,21.0,19.0,24.0,21.0,12.0,20.0,EDHFBEAFADABHFHFCFHFACCBBBHAHDHBADGDBCBDFEFDHHADACBHBEAEDDDGAGACAEHECFCECHHHEABFCFEEHGAFFFADADCDGEEEGEBECEBBCACAHAHADADFFAFAFHGDEEFEBCGCGCGCDCAHBGEEFGADECECAFAHA,False +236,13.0,6.0,14.0,8.0,9.0,13.0,7.0,14.0,FCFAFAFAHAHCDCDGFFEFECEDBCECDCFHEEFAFACHCHCEBGDHEHFHAHBHDHFCGGAGDHHACCBHDCGFGBAAEABA,False +237,4.0,7.0,4.0,12.0,6.0,4.0,7.0,10.0,DGGHBHDDDGDGCGCGADBHEDEDAGFCFEBDHDEBAHAFEHEHCHDBDBHFHB,False +238,25.0,27.0,17.0,20.0,11.0,20.0,27.0,24.0,BGGGHACECEFEAEDBDBHCGDGDHDHBHBHAHAHFBFGCGCAHFHABABEFFDDAAFHFHDAGADFDGBACCCHGHDAACHCHGBEBCCCBDAFAEGHAHGHGEDBDBCBHBGFEAGAGBGBABDHDGAGADFBFGFGCAEBGFFEHBBGDGBBBFFHFBFCDAGCGHDA,False +239,27.0,19.0,14.0,12.0,26.0,20.0,17.0,18.0,CACHFHBABHBABAHEGBDDEBFAFAEACABAFAHAHGHDFEGEFEBEBEAFCDCHABAGEGEDFBGBACAFDCDCAEHEHFHFEEEFABABCGEEEGHDHAHBHDFGEGBAAAFDHECEAGCGEBEDCDHFAFAGAGBGFFCGCEHGFEBEF,False +240,13.0,5.0,13.0,8.0,10.0,9.0,13.0,11.0,HCHAGAEFGBGAGFGCDCAGAECGCGEFEDHGFADADACHDFDGBCBCFEDEFEFBAHHHHHHAAFGCECACBCGEHEADCG,False +241,15.0,13.0,22.0,21.0,14.0,24.0,13.0,15.0,CECEBACABEFHFGBEFDCDBABGDAEADCDHGFGFDDDFDFDFGFEFGCGEAHGHGHCFCDABFEHHABCECBCHFHCACFBFBHBADFEFEFDFDHDHCHCDEDAGGECHAFDHCABFCFDFDGBGCFCACDCEA,False +242,10.0,3.0,9.0,4.0,10.0,22.0,6.0,6.0,CBAAFFFFGBDAFFFFFFFDGAGEHFGECEFEFHCHCEEEDCFAFAHAFBDEHGHCFEFCFCFEAAFAGC,True +243,16.0,18.0,13.0,25.0,8.0,14.0,16.0,17.0,CFHGHAFGFCFEDAGEBBFDGBGHDHAHBGBGBDCHHEBDBDBDCDHDHFAGGHGHABADDCDFBHAGDDDBCACECAGEGDDHDFDFHFHCGCGCDBAFAFDBDEFEACADADADBCFAHBHGEBB,False +244,14.0,10.0,26.0,18.0,17.0,28.0,19.0,21.0,HEHEHDFDFEGEGFGDCBBDAFHFHFDCEGBBDHFAGBHFHCECHCGAFCCDDADGHGCGAGBDCDHDHDACFCFGACEHEGDGFCFCFCAEFHHHFBFDFDCBCFEFCDGAGDEEFEFHFHFEECCCAAABECFHACECFAFGFCBCGHGHG,False +245,30.0,27.0,23.0,25.0,28.0,19.0,14.0,26.0,AAACACBCAEDEBEFCCHCAEGEDEFGAGCEAEADFEBBBEFAGBBBFDAEAEHHHHCFCHCHADFDEBHFACBFBGBFBCHHAHAEEGHHEAEGHGHGHGCAHADADAEAEAGDGBECHDDDDEFFDCDCACAFBFHCHEHEADFBFBGBDBCGABHBHDACCECDDBDBDFDBEEEEHCBAFHHDBBADF,False +246,9.0,17.0,16.0,9.0,17.0,6.0,11.0,16.0,HGEGACAHDHDCDEGFHBHDHECEDEDFDEEHCFCFHBEGGFABEHHHHGAABCCDBEBECHCHFBAHGCGABCBEBECCCCCEGEBBBBDBABEBHGEGA,False +247,10.0,6.0,15.0,20.0,23.0,16.0,16.0,6.0,AFDGEGEFEDCDFHEGEGFGBCACECEAEHEDDHEGEDEFGDDDCCCCGAGEDBABEFEFDGDHDGDCBHBGFFCFCEEEEFCHEFGDGFCDADCFCAEGFGBEFDADADAE,True +248,1.0,1.0,5.0,2.0,5.0,7.0,7.0,2.0,EFCFDAGFCFGFCHEHECEGGCGDGFGFBE,True +249,20.0,25.0,23.0,25.0,18.0,22.0,28.0,20.0,DGDBDAABACHGHEBDCCABFBAHGGBGEAAGDDFGFAHADADEDFHFHGGGFGFDHDEDBACDGDGBFACABBGBGEGEGECFFFEABDEDHFAFGBCBCACHHFHFBFBFHCHCHCECDGDCEHEGCGBBFBGEFEFHCGCBHGDGFHFEABCCEBDBHGDGDGBHCEDADCDCBAEAC,False +250,27.0,24.0,20.0,16.0,26.0,17.0,25.0,11.0,CHCBCACHBABAGHFEEBEGECEBEBEACDGDHHGAAFGEGABEGAGEGADADABAECFGBGAGAEBEADFGFECACGGFGEGDGFBFGCGBFBFEAEBEFAFAFEDEAAAAGBBBCDCDGECCCBCFADABHDEDEGEAHHBDEDFDFGCCCDBBHAHGBCBEHF,False +251,23.0,19.0,20.0,25.0,22.0,22.0,28.0,26.0,ACACGEBFHHCAGAGHGHGCGCGBEHFHFCAGFGCGHEHAHADDDDAEEEECCFBGHAHAHGBDECFADGCECEGEGDGAADBEAEFHFDGDGAEAFDECBGECCHDEEBGBABEHHAFFFFEFDADHBHBDDGGCGCBAGAHABDBDEFEBCBDHGHGFDFDFDFHBAFCBDBDFFGGCHHHDH,False +252,22.0,23.0,23.0,11.0,21.0,24.0,27.0,23.0,CGGAGEGECECECDBFFFHAHGEGCGAGACEDBBBFGFGHGHFCBGHFHBHGEAHAHABDHABABDBECHAHFCFEFAAGGGBGFCDCBEADADHFHDHCEABCGGGFGAHEEAECCCCGBBEHEHBHBHDCDFFAFBFCEBAGAGCCBCAGFDHHEHFFFCFEFBBEBFGEGA,False +253,21.0,15.0,11.0,10.0,10.0,18.0,15.0,19.0,CFCEEFHBGDEEFEFDAGAHAHGHFHFHGHAHAHGFFFGBDBGAAAABABGBFBFBEACGCEDHFACCFFFGECBAECDGGAFAHDHDHBCCGHAHAFAEDHDHGBBABDFCAGABHBH,False +254,16.0,7.0,14.0,11.0,13.0,17.0,11.0,13.0,CDFHFHECACEDEAECCHFHFHGHGCAHAGAGDEDFDCHCFDADFEGAAEAFFDEDCCEDBFCGCGEBEBHGAGFBABAGFHDHAHAEFFFFFBEBCGHACA,False +255,14.0,24.0,17.0,17.0,23.0,22.0,12.0,11.0,EDGFFFGBBBCACDDDBDCFCFCEEAFGFGFGFDBBBFBDCFEFADAHEDBDFHAAGHCHFGACABEDEDEAECEFEFDAABHHAHCECBFBCBFFDBDGHGHFBCDCECEDEAAGEGFBEBCBEEGEBEBEBHCEFBBH,False +256,15.0,18.0,13.0,27.0,17.0,28.0,20.0,24.0,FBDBCHCGDEDCGAGAGDDFBBBFFFFEDACGCHAGGGEGEBABFHFEDHFHFCBDGHGBGDHBCBGAEHFAFHHHDBDCHBFGFGFHFHEGEBDFFFHAHGHCHAHDHEBEFEDGDGAFABDBEHACFCFCEDADEFBDDEAEADFDFHFHFDGHEDDDDC,False +257,6.0,7.0,12.0,13.0,9.0,11.0,8.0,10.0,DDACHGHGHDHEFCCEGEGACCDCDCDADHBFEFEDEGCFBFDFBFEHCHDAGEDECBCBHFGFDFHAHCGABDBF,False +258,17.0,20.0,27.0,16.0,18.0,18.0,19.0,20.0,AGEHCDAGCGFGDCDCHCACDFEAGFGAAAADADCCHGHGHCCEEEGCADACAHECEGDGFBFBFCHCHCBBDBDBDEFCGCBBBEHFHACAGBCHFFBCBCGGGGHDBECEHEHGHBCAGEDEBFCEEBEBDFCFAFHBADDHFHFHFHECFBB,False +259,1.0,5.0,4.0,1.0,1.0,0.0,6.0,2.0,GGGGBGAHBHCGDBECCBCB,True +260,2.0,3.0,4.0,1.0,3.0,5.0,1.0,3.0,BFBCBFHEEGEHCACACHFFDF,True +261,2.0,4.0,3.0,2.0,3.0,2.0,6.0,2.0,CDCABEHHGFGFGEBABCBGDGEG,False +262,17.0,17.0,32.0,25.0,20.0,22.0,15.0,15.0,DHDCDCDGEHCBGBEBACGDFDCBCFCBCEAEAFCDEBAAEADHCEAEHECDDDBDCDBBFFEFGFBCBHAHFCCECGHDHFHAHACDEHECFCDEAAHABBCHGEGDGFHDDCDGDCCCGCACACFCFDADFGFBFBFEGEGEHDACGDFCFCFGBEBEFCF,False +263,7.0,4.0,7.0,4.0,5.0,5.0,7.0,12.0,GCACAHGHECGCHFGFEDHDHDHGHBAEAHBHFHGCCBCHEGEBHAFADAF,False +264,6.0,6.0,13.0,6.0,11.0,2.0,9.0,8.0,DCFBDBEEEEEEADAHGHGCGDHCHGEACBCGCAHEHGGAFAGCCCCCBEBHDCBCEGEHD,True +265,20.0,25.0,22.0,32.0,26.0,23.0,23.0,27.0,DCHBHBCEHHGHDCGCAHHGHDEEHEHBBECDCGBBACACADDDDDFCGEABGBABEBEBEACFHFBEGHFBABCGHGEGDDDEGAHAEFBFDGDHBFGFCDCDCDFGFHEBEHEHBDEAEACBDADHFBDDDDAFEFBGGGGHGHCHEHFCFGFGADDDDBDADHFEBEBECEADACBCFAFHFDFGFAEGHHCCFE,False +266,7.0,6.0,7.0,3.0,4.0,2.0,13.0,8.0,BGHCABHHCHGGBDBABAFCGEGDGAHCEEGEGBGCAHAHACGCGHGFGD,True +267,8.0,8.0,22.0,12.0,15.0,14.0,10.0,10.0,DCBAAGBEBEHECCCCFEDDDFGHGDEDCBCGEGEGEBFFAEHECFCHCHFHDCDCBHGGCCBCFCHHFAFGHGDFCEADCDCDCEBFAFACECAFEFE,False +268,20.0,11.0,17.0,15.0,11.0,11.0,19.0,11.0,FACAFGDHCEFHAECBCBEBEAEGBGBGFHCCBCAHDCFCDGDAEEEFBACADABACECHGGDBDGGGFHEHADAFGFGFGHGHGCFCDCDEGAAAABDDDGHBACACDGDHAGA,False +269,6.0,1.0,7.0,4.0,8.0,4.0,3.0,3.0,DBGECEAEAEAEAGDGFCHCECFAAHHFEFCCDEDC,True +270,18.0,16.0,20.0,26.0,19.0,21.0,22.0,23.0,BFBCDDGAGACDBDGDGDADHCAEACGCGDEBGDFDCDBDGHEHCFFFFFHFBFAFHDDGBHHHHFEFABGGDGDEFCDGHCHEFCFHBADHHCFCBGBFEEEEEFEDEDAFGHGDGCACDEAEACDEDHBHGHBHBHCDGAEACCEHGHAHACAGACBEBGFDF,False +271,0.0,3.0,1.0,4.0,2.0,4.0,2.0,3.0,HFHFEFDBEBHFDDBDGCG,True +272,16.0,16.0,17.0,14.0,11.0,14.0,8.0,16.0,FCHEHAFAFBFBDHGAFABBCDCDHBHEFABCHCHDAGABEBAHDHDFCEBGDFECECECEHECACDBDBDCGAGAGACAGBFBGDDACCDDBHEHBACFBFHHHFHFCFAE,False +273,13.0,11.0,14.0,14.0,11.0,17.0,18.0,16.0,CDFDGBHBFGFGFGEDABABCHHDDEDCHCGAGFBFDADHDCDCECAGEFEBEAFAEHEHGGEFBHCHFHFAFDFACGGFGHHDHGHAHCFAFGEBCBGBGCACDCDEHGFBAG,False +274,30.0,26.0,12.0,16.0,14.0,36.0,17.0,16.0,GGHCBABACFGFHFBBHAEAEACADADABABFFDABBFFEFBAGFHFBFCFBAHHHHGGDGFGBHBFEECEFDCHCHBHGEAHADDGAFAFDDBDGFGBEFFFFFGFACABGFFFAABAFACAGAGHDABABGDACFEAEADBBFBEDEAFFBFBFCFCDBHEHEDF,False +275,6.0,13.0,13.0,9.0,7.0,9.0,12.0,6.0,CEFBGCCCCHDBDBCAFDFDFGFHHCCGCGBGDGDBCBCBHFGAAEGBGBFBGBGECHCDAEGEFADAHEDEBBF,False +276,7.0,5.0,3.0,5.0,6.0,7.0,3.0,5.0,BCCDFEFEFEBADABCFDDHDHAAEAGFGFHFBAEAGHBHE,False +277,6.0,5.0,1.0,2.0,3.0,3.0,6.0,7.0,HBBFBFDHCGEGAHAHGHGFEBHBGGAEAHADA,True +278,4.0,8.0,15.0,16.0,12.0,11.0,10.0,10.0,DHCHAEEEHEHEFEHGFBHEDEGEGFCDCFCGCDCBFFFCEGDBHFDDADGGCGDEDEDGACDCFCFBGBHBDBCFCHCDDDHCAB,False +279,15.0,15.0,14.0,9.0,20.0,30.0,10.0,19.0,EAFFEFEFHBHBHBHCHCFAAACFCAHGBGBFEEBECEGEFDCEFEGCBFHFBEAFDBBGDDCGFDCBBHBHFEFEHCHFBFDGCHFHFHFGFGAAAAEECEFDBEFECEHDFCFHDHFFEAAAAAFGFHFH,False +280,20.0,27.0,17.0,23.0,26.0,20.0,26.0,25.0,AEDGCEBACABABGBGFDCEBHBCBCGHBAEACBHHHCDDEGFHAAFABCEHDBDBDFFGFCBGGGFGEEFEDEAEDEDHHHFHEEEGEGCBCBHBEBGBGECEAEHGHABBBFHEAFGBGDGFFEFDGDGDGHGDAFAGDHDECEHHHAHDDGHGCGEBEFABCBDBFCFCFHBADADFDAHH,False +281,10.0,6.0,6.0,8.0,8.0,11.0,10.0,7.0,GBFFDHAEAECDDBEGDGAEECGGGDHDAFADAEAHBHDEFFFFBCBCECAFABAHGFGFGFGHCH,False +282,21.0,33.0,19.0,20.0,21.0,12.0,19.0,26.0,CAADABABCEABHBABDCHEAEGHBBCCCCCHCBGGGGHHDHGHGDGDGDBDAAGCBHDFEEEEEEBEBAHHGHEHCCGHFBFBFBFGHBDBHAFAGACCHAHFBCCFDEDEHCHABDBEGADBBCBHEHEDDDDBDEDBBHAHBEEEDBBBBHGGGCEFBFAFBGAHAFA,False +283,12.0,9.0,6.0,10.0,12.0,16.0,15.0,10.0,CFCEDFGCGFHFBGCGFGABEGAGAGAGAFADBHGHDEFHHDGCADEGBBCHDAAAGEBEBABFDFEFEFHFHFHFHGBFEGEDDDEFEA,False +284,0.0,7.0,2.0,2.0,5.0,4.0,3.0,5.0,FBBHBHECBFDFGEHCHEHEBEBDGFGB,True +285,18.0,10.0,10.0,8.0,8.0,13.0,19.0,13.0,HHHFGFAHCCBCHCBFAGCGBABDBDGAFDCDAEAEHDADBHBAGFGFGHEFFGHGHBHAFFBFCFCAAABEEEAGGGAGCGFGAGADAGEHAHCDGEG,False +286,17.0,19.0,13.0,13.0,17.0,16.0,12.0,9.0,DBDADABCGDAFEFEFEDABCBEBGDGFEBEBEBEADBDGHCADABFDADADABGFGFCBCDCFBGGEEFCFAFEFBAGGEFHCGAFAHBHBFFEBACECACBCHAHEHEHCGBEH,False +287,11.0,13.0,8.0,14.0,5.0,10.0,1.0,11.0,ADDCHBHFDEACFDBDBABCBCDDDBAAADHFBFBABEHEHBHBCCHFDABAHCDDDCDAFHFEFEFHFHGAB,True +288,21.0,32.0,21.0,22.0,23.0,17.0,23.0,21.0,CFCBBDADEDEDBDHDADCCCEHEHBFBHADADBGBGDCBBHFAEBDHDFDFBEBHDEDBCECEGABCFGFHDHGHEHAAGHGEDEAEABGFCCBEBCFDFAEGGAGADECFFGFBBHCGEBEGAFABDBHFFAHAHAHBHBEBEBCBABDEGCGCHCHBHBGEGEGCAAGGBBFCCGDG,False +289,10.0,13.0,5.0,12.0,9.0,19.0,21.0,12.0,GBFAEDDDGGFEFDHHGHGFGFGDGFGHHHHEGDBHFGGHECBAGAEACFBBDBCADFGEGDBBBBCBHHFFBFBFDAAAEFGFAFAFDFDFHGGGGGECE,False +290,10.0,11.0,9.0,13.0,3.0,16.0,8.0,5.0,DBDBDCFFGFGABEBEDEFFGFGFAFABHCAFABCDHDADAHBGBDDDADFHCBCDCAAGHBFGFGFCCBFFCFD,False +291,22.0,19.0,25.0,28.0,18.0,24.0,23.0,17.0,FCFEFEFAGEGCGEAAAEGEHFHEGFGDGDEDBDEEECBBBEDFHFAGHCAGAFAHABFBFDDGECEBGFDFCFCDBEFABGEDACACDHDHDFFCDCACHCDBBGCDBHBHCFCDHHHBHBGFGFADDGDCDCHCDCACAGAGCDDABCEGHDHFGGDDEAFBFACACABGBGFD,False +292,22.0,21.0,17.0,19.0,16.0,16.0,15.0,29.0,EFHHAHDCDEBEHEHEHEHEHCFDBCBDHCAFEGGHDDBDFGFGHCFDDDDAFADCGCFDFBFBHGAFCCBBEEAAGAGDEDAHAHAHBHBHBHEHCABABHBCCCHCBBBDAHGFDEAEAFHGBGEHAFBGHAFAFAHABCDDECGCHHGHGAB,False +293,14.0,10.0,22.0,19.0,17.0,10.0,11.0,13.0,FDGGCACGCDCACBCDCDGHHDHBHFGGCCFBFBCBDFDAGEHAHEFECBHGDDDCEBBADCDFDADEEEEDEBHAHAGCGCBDGECEHEHAACADAHFHFEFCCECEDECCDAEA,False +294,21.0,23.0,11.0,16.0,19.0,13.0,19.0,13.0,ECDFDEAGAEAGHBFEFGHBBGBABABGDGCCAGHBHFEFGGCBDGDGDGHFHABAECEAGHFDFEFBFECECEFDHGFGABAEHEGEBBBBEBADFEHEHBDBDADADGBHADADHGAEBBBDCACECBCAAGA,False +295,16.0,21.0,15.0,23.0,14.0,18.0,17.0,12.0,DDBBHFDFGBGBHBFFFFFFFGEBCFCGHABBEHDDDDBBBBDGFHFAEDHDHCFCHCECBAHACDCDHAAADDECACAGABAGEFEBCAEACGDGFEFBGBDBCBGGDDAEFEDGCGEGEDEDGDBABADFHCHG,False +296,2.0,5.0,5.0,3.0,8.0,3.0,7.0,5.0,GHDHFBBGGCGBHEHBCACHCGCGEEEEFDADBEGEFE,False +297,8.0,7.0,6.0,6.0,3.0,4.0,7.0,7.0,GDGFBFEFAAEBDBDBAGAEHBDBHCHDGBGCGHGHAAACHCHAFCCD,False +298,10.0,8.0,9.0,8.0,12.0,10.0,12.0,8.0,AAAAAADGHGAEEEHFHEHEFFAGAFHCDCGEBCBCBFBFAFHFGGCGHEDGDFDBGEDEDCBEGEGHCBEBCCDGF,False +299,2.0,2.0,2.0,2.0,1.0,0.0,0.0,1.0,CHCEABDBDA,True +300,21.0,16.0,12.0,20.0,12.0,15.0,16.0,21.0,HFHGDDEFBFBFAGCFAGBGDHEHBHBHAEFBDGACHGHAHFFDFHFHEBBCBDBDBCFCDCACAEDEDHAHBHECABAGCEBHBGEDEGAAHAFAHADCDEGEGADFGAGAHCDAGADAHCHDDGDGDHFBF,False +301,18.0,17.0,21.0,18.0,14.0,17.0,20.0,23.0,BEBFFCAGAGAGHGHFHDHCFDFDEDEBEBEAGFBCCHCDCBCHHGHEACAEFGBGBEDEBCDADHFAADBHBHCHFDFDFHGBGBAEFGFAAEHEHEHCCGHDDDGHCCCCAABCGCGCADACABFEHDBCFHGHGDAHHDFGBGFG,False +302,17.0,9.0,16.0,15.0,18.0,20.0,16.0,20.0,CFEHGDGCGHFADAFGFBFHABACDEDEDGAEHEHCCCBCEFHGHAEAEAHAHEHEHCDFFAHDEAFDFGBGDHHFHFAGGFFBEHEAEAFFFDGBGCGEECAFFHEHEHDACBCFCDDDDCBCBHGAGCG,False +303,17.0,9.0,12.0,14.0,11.0,11.0,11.0,15.0,DFDFAGHHDEDEHEHECGFACAEADDHDEDCHCECFHBBBEGHBACGGGAGAHDHAAADEHEAFADGDBDFHFGBABABHBFCHAHACCFCGCEADFCFG,False +304,32.0,22.0,21.0,20.0,17.0,21.0,22.0,16.0,HABACGCBCGHGHADEGABAFHHGFCCGFFFHFHAHAGACFGEEAHAHABABFBAEAEDGDBDFFFFEGHGDDDCHFAFGECACECECEDFBEAAFBCGAGECECFCFCBGGADADGHACAEBHAHABGGDDADCDADBBBGHEFEDDDGEFBDBDBCBABCBAAAACFGB,False +305,22.0,14.0,10.0,9.0,20.0,15.0,19.0,12.0,GAGABHEFGHGABAEDECGAFABBEFEAECCAAHGHBEEEEEFHFGFGAEAGAGDGHGFAAAHAGAGFBECEFFBBGHGFCBCGCADEDBDBDBDFEECEBEDGAAEAFAHHBFCFCDHGH,False +306,7.0,13.0,6.0,7.0,4.0,5.0,5.0,12.0,BABAFAHDFDGBHHEHBDACHGHGDDBDHFFAFACEBEBEBHBCAHBHDHCGBHBCGCB,False +307,27.0,19.0,23.0,17.0,31.0,29.0,21.0,17.0,FADCDEGEBEGHDAEFEAEBHBCBAFAHAFGEGFBFCAHAHCCBDFHGCEFFCFEFEAEAFCBDADADHDFBFBEBADFCFEFBFBFDFCFGFEAHBBCCCCHHBHAAEGEBECEGDAEFDGECEFEHGAGEFEDGBABABHDHDCDCGHAEACAGFCECGGHEDCFAAAGAGCEHEGEGFGFE,False +308,16.0,23.0,23.0,25.0,22.0,21.0,28.0,27.0,BHGEFEDACAGADADGDGDBBFBCGGHGFCFCEHHDCDCEGFCFBEBEHDHCHCBEDDHBBEBGGFDECHCHCBFDFBGEHEGEDEGAHDBDAHGBGDGBCFCGCGBBAFAFABBBFGFHAHAEAGFFFGDDCABHECEDEBEHDGDEDEGCHCDCACHCAFGGGHFHFHGHGCAEHHHHDDBEF,False +309,11.0,10.0,14.0,4.0,9.0,15.0,8.0,17.0,CECHBGAHBHAHGCACBEFEFDCCCCCBCDCGAFFFFFBCBAFHFHFHDAEAHGHBHBHEHBHCGFBHAAGEFEFEGHAHDFFCAEHG,False +310,7.0,7.0,11.0,8.0,8.0,14.0,8.0,4.0,AFACGFEEDBGHDDADFCFCFCFDBGBHEHFAGDCACFCFEFBDBGBEBFCFCFCADGEGEAHCFGE,False +311,1.0,3.0,3.0,4.0,1.0,4.0,5.0,3.0,DHHBHDGDGCFAFGEBCBCGFGFD,False +312,9.0,6.0,12.0,3.0,7.0,3.0,4.0,5.0,AAEAECGCDFDHACECEAEBHBACCHCHEGCGCHCACBBAFAFCDGEBB,True +313,10.0,20.0,11.0,11.0,10.0,21.0,14.0,10.0,FHEBEBCAHAHBFGFGHGFAFCFDBDFDCHBECCCHEACABDGFBFEFAFAHGBFBDBDBFCCCEBFGGBGFAFABEEAEGBBFFDFBFBDBGBGCGDEDHFHDGGH,False +314,11.0,11.0,19.0,12.0,11.0,7.0,10.0,11.0,GBHBFGDABADADBDCDADHBGCECHCHCGCEAGCGCDCFEAGAEAEHECEFFBECDCGEHCBBBCGDHDBDADCFFEFCACAEBHHCHGHC,False +315,15.0,20.0,19.0,23.0,12.0,16.0,12.0,15.0,CCCCEFDBDHDCDFDCHFHFDEBACECHCGGFGAHDDDBACFFFDFBBABABDBACADAHCHDGCFFBHHDHDHGCCACEDBDECEHEBABHFDDDDGEFBFBGBEBFAGAGBGHEHDFEBABAEADBCGCG,False +316,6.0,8.0,6.0,3.0,8.0,2.0,0.0,9.0,CBCDFDHABAFEHBHBHECEBECHHBEEECEHAHCDAHABAB,True +317,5.0,12.0,12.0,7.0,8.0,8.0,7.0,11.0,CHGBGBFBFDABACAFFFCECHCEGDBBGHCCBGDGFGHEHDHCHBBCCECEBEAEAEHDCDHHBHBDFF,False +318,19.0,29.0,24.0,19.0,24.0,39.0,20.0,15.0,CFEFGHBHFHCEABFCCCFFEFEGBGBAHAHDBABCBGBGBGAGAGABHCCCFFFEHEDGBHEEDHDEDBHFDBCBGBFCFBEDFAFCFGACEFGFGAAFFFFDFEFECCGEGBDAAECECABEFDFCEAEAHFDBABDCHGBGBGBCACBCBEFGFGFCFHDDFAEHDFFEDDFDFBFBEBEBFHFCD,False +319,8.0,5.0,5.0,2.0,5.0,4.0,3.0,7.0,HAAEAHDHCBDEAHCGFGCEABAEAFAFHFHBHBCBCEG,False +320,4.0,0.0,2.0,0.0,3.0,0.0,0.0,1.0,CACAEAHAEE,True +321,19.0,25.0,20.0,14.0,21.0,25.0,19.0,10.0,ECEAHAGAGDCFHAHAHABEGAGBEBFFFFFGFDFDFGCDCBABEBGBFFFAGADFDGHGABAHAGCBABGDGEEACAEDBCBCEEFHGDDCBCEGEFEBEBFGCHBHBEDFHBCGEBCDCFCEBEFEBCBCBCBAGFFAFAFDCGEEFDCBF,False +322,4.0,3.0,7.0,8.0,3.0,3.0,6.0,6.0,AGDFDFDAGECEDDHCHGHCBFDEBCBCHCHCDDAHAGGG,True +323,20.0,23.0,10.0,13.0,14.0,23.0,24.0,21.0,AGAFFGHGEBBCDCEEEGBFAHAEGEGCGFGAAEBGHEBDGAGEBABEFCHAHADFBFDFBHBHBGBEBFBFHCACGCGBFBFAHAHFEFDBGGGBGFGBBEDHGHGHFHDHDGDHBFBFDFHFHFACADAGEFHCAADHBHCADFGA,False +324,6.0,10.0,13.0,15.0,5.0,10.0,12.0,7.0,ABBDDDDGDHDCBBHCHGDGBAEGEGHDBCFGFBEBADGCGCGHFFFFFCFCBDBDGDCAAAFDHCCCECDFDHCGEG,False +325,14.0,17.0,16.0,18.0,24.0,25.0,25.0,12.0,EAGDFBFEHEFGADABCCEGEAEGEGHGBFBDEAEDHDFEFDHCHGBGEECDCDCDCHCDEAEACCBEGAGEBFBFBFCCGFBEBCCDEDFDHHGAGAGEEFFFFFBGHGHBDECEBAFAFDFDGGGAHBEFGFGFHDGDEFGCABFBFGG,False +326,10.0,8.0,13.0,7.0,11.0,10.0,9.0,12.0,HGFCFAFCFAGADEDBHFCFCHHAHACEBECCCCEGEFEFGDBFBHBGBCEEABCECAADDEDHDHBGEGAHCHFHGAGH,False +327,13.0,9.0,7.0,7.0,11.0,9.0,9.0,4.0,EFEGEFABAFHDBFAFGGEBEFECCCEFFDADBDGEGAGABABABFBDDAEAHAHGHEAAGDECCCGCB,False +328,11.0,7.0,14.0,13.0,15.0,16.0,11.0,12.0,HHHHFDGEGFHFHGDGCCHFBFEDBAHGFCDCGGDDACACEDBGEDEHHGHEFEFCFGFAAACADHFAFCFCFCBDBAEEEEGDFBFAEAEDEDEBCCC,False +329,14.0,9.0,16.0,7.0,13.0,4.0,16.0,18.0,GCAEFCFCACAEDGGEGBGBGBHBHAHECAAAAHAHECECHGHADDCBCFCHHGAGEGDGEAECGBHDACECBHDCDGHCHGEBHBHEHCFGEGHHA,False +330,6.0,12.0,18.0,17.0,8.0,10.0,10.0,6.0,GGFCECDCDCAABEBEHEFDDADGDBDHGFBFBEDHDFBHGGCBCBCDCBCHDGCBCBEDCDGDBECADACCCFEFGFGFHDADFCC,False +331,11.0,25.0,21.0,16.0,17.0,27.0,21.0,23.0,FFFCHCBCGHHHGGCEBEDFCHAEFCFHDBDBABFBFEFBFHDHFBGCACHHFBFDFGFBHHDBEFAFAFHFEEEGEGEGEDBHCDCACHHGFGFHHBDBDBHCHGEDBDECECECFGBDBCEGGGGCCBCAAADAHBBBGBGFGHDAEFGFBBGHDCFCF,False +332,31.0,34.0,15.0,23.0,18.0,19.0,14.0,23.0,HBFBAAACBDEABCHDHAHDFEFHAAACDEBHBHBHBCBHBHBGCAFGBGBFFDFGAEAEBDFFADADACADDDHAHAEEBFDFGCCCFCAEGBCBAHCGEEEEEEBFDFEHBBBABAHADBDEDFGHHBHBDDABBHBHDHFCFCGEBAAAEGFDFDGDBBBAGAGABAGHBHCAD,False +333,20.0,17.0,9.0,14.0,13.0,13.0,13.0,14.0,ABGCECACBHDHGEEHEHBDAAAFDEDGDFAFABCCGHBABEBEGADADFDEHEHEGBGAHADDHHGHGCGFFABAFDBDHABEFDCDFFAFBEBHBAFAFABABGCECHGBG,False +334,7.0,5.0,2.0,4.0,6.0,6.0,4.0,9.0,GCGBFBHAHEBEAEDCGEAEHHFHAHABFGFHFHDEDADAFHB,False +335,17.0,13.0,10.0,10.0,9.0,12.0,9.0,20.0,AGHHAHAHCBABFGADADEFEFEDBBBBHHGHDHBCECEHFHFHBHAHDEAEAEBEHACAGADHCHBGGFFFHACBDFDAGHCDGDCFCACFHFBBHGAA,False +336,10.0,13.0,6.0,5.0,11.0,4.0,11.0,9.0,EGEBEBEGEBAHEFBCBEHGDFHFAFCBHBGDABHGGGBGCGBABADHDCEABABADAEEGAGCHCHEH,False +337,17.0,16.0,15.0,8.0,14.0,17.0,17.0,24.0,HBGBABHBHDFFAHAHAGAEAEAFACGCBCECFGDGCCEFEFHHHABGFCHDHGBCBHBDGDHEHGHCFCHGHDHFHFBFDABHBGBAFHEEGEGECBAGEHBHCHEFEADCBFGHCEFGCGFAAAAF,False +338,18.0,20.0,22.0,16.0,18.0,27.0,14.0,22.0,AEAEAEAFHDHAAEFBDHGFGFCAAAGADFFEFBADCHCHEGBBEBGFGFGEHEDCFHAEBHCDCBCGAECGCHCHBFBEBHHHGCBHFDDGHHHCHBDEDECBDFEFBFGFCFBFBCBFBFCDEAFDGABADADBFFFFECECADHHHCHCFCFCG,False +339,24.0,25.0,25.0,23.0,21.0,21.0,28.0,25.0,ABAFDFCFCGHGCDBDGEGEGCAAEBHBHGHGHDADCGCHFECEBDHDABHGCGHDHEEEBFBFBDDCDGEEEHBFFCFBFAFAFGCCCHGGFGCACHEDEHGDDBHEHDACAFHEABGCACABDBEBFDGHGHFHEAEAEADACGGBBBCGCGDGBGBFCHAHAHFBABFCEHBADGDEBACGCGFAFDHD,False +340,14.0,19.0,9.0,8.0,9.0,16.0,11.0,11.0,CAADABAEACBCBGAADHBFFFBDBDEGABHHHAEFHBCFHBEBGFDFBFBDBDBDAEGEGEFCGBFBAEGBGFGFHFHFGFCBCAAGAFEHHHCBC,False +341,2.0,6.0,2.0,4.0,1.0,4.0,1.0,1.0,ECBDBFAFDFDBGBHBCBAFD,True +342,10.0,9.0,6.0,7.0,9.0,12.0,7.0,13.0,AEAHAHFEGEGBGAEBBHFDBGBHHGHAFAFAFHFDDCDHECFCACFHFHCDCDHBEBFAFGFABEEEGBDHH,False +343,12.0,23.0,13.0,17.0,19.0,18.0,25.0,20.0,GCGCGCFABHCGAFCFDFBHBHEECDDBEHEAEABABAHHFFDFGEBEBGCABAGGEGEDEDHBCFDHDGBGDGHAEAGDHAEEECHHFBDGCFCDBDHFHBBBDHHCBEHFHGGGFGFBEBEFEFCFGFGHGDGDBHBGBABDGEG,False +344,8.0,19.0,17.0,14.0,18.0,17.0,16.0,26.0,BFBHCHCACDDFCHEHAFAFEEEDHGHBEEFADGGFGEEDEDEFEFBFBHHGHGHDEFCGCGHDHDBCHDBCFCGEBHBHEHFDEAEBEGCGBHBFBHBCBCBCBGACCHHHGHFDFCFHGDGHEHDCBAAFHBG,False +345,14.0,25.0,9.0,16.0,24.0,29.0,24.0,20.0,BDBDFDFEGEDADGGGGDFAABHGFGFEBHFECHCEDBABFBEDGGCFCEAAHGHFBBHHHHHHEBEBFAEEBEDGDCHEFBFBFBHEGEGEAEBGGCAFFGDGAGAGHFFFFFGCHAHBHDEDEFHBBBFDFHFBFBFBHDEFGBEDEGEGBAFFCACEG,False +346,20.0,21.0,26.0,20.0,28.0,15.0,21.0,20.0,EDEDFHFHEDCCECEHEHCGBBAEFDDHBGBEBGAEHECGCACECGCGCDEHCAFAECHBBDGDFCFBBHBEBEHDGDBDCAGACAHAHDHCEBEHEACDDDFFAGAFAFCGEACACGEEAHAGAGAGEFEFHFBGCHBDBHBCGDGCECHDHFBFDCGCBBEBDAEGEGE,False +347,9.0,10.0,7.0,7.0,9.0,11.0,7.0,1.0,DAFCBCBAFDEGEGEFAADGEGEAEAFGFBFEFCFGFCFHEDCBGBEBAFDDABCBABDBC,False +348,23.0,21.0,22.0,23.0,12.0,21.0,19.0,12.0,DBGBGFCCGCDHGFGFGFDCDEAEAFBFBHGHBCBABAFFFBBAFHFCDBFECCDCACAEADFDEDGCFCHBBBBDFDCGAHFGEADDGHFFDADEGEAEFEDECACACAFADCFCAGBBABEDGDHCGCACACHBDGGAGBGBHAHADDDHB,False +349,24.0,18.0,28.0,33.0,14.0,23.0,32.0,22.0,DBDACACDEGGCFCBGBHFGDGDEDHHADCFBFDFDAAFAGDGCFCECEGDGFBAGHDDCDCDGHCFFAFGDGDHDHFGGBGHDCDCAHFEDBFBFCDDEDGHAHADABHBEAAACADGBGAGAFHCCGFGCGDGAEAGDGHFHFEBAHCFCFGGGEGEGAGHBBBDCCHCHFHCHDFDBDCDEHECBCEAABC,False +350,8.0,4.0,6.0,7.0,7.0,4.0,16.0,7.0,EDGFGACAGBHBEBAGACAGEEEEEGGAGCGCDAFHGDCDHGHCHGBGAFDFDGGGDHH,False +351,14.0,22.0,13.0,15.0,4.0,11.0,14.0,13.0,ABCCHHFHCDBDBDBCCGCGFFDFBFGGBAHADDGDCDCBAHABEFHBBDBDBDBEBEBGDAEABDGFHBHGAGCBFHHHHHACGBGACFBBDGDBFAGAGACACF,False +352,23.0,10.0,18.0,19.0,18.0,25.0,14.0,15.0,GFADHDHFCGCBFFFHHEDFDHAEEFECAGBGEAHAHADAEGCBFBFEGEFHHEGGCFCHHAHAHEBAADAGBEBEDEDGFEFAFADADFGFAFCECECFFAFACACHCDFDADCDGGFDHCCCCDGDAFBFBEADBDAECF,False +353,28.0,26.0,15.0,29.0,24.0,17.0,31.0,29.0,EFGDADGCGBGBGBEAEHGHFDDEDEDEGHGEGEGHGHEHGDGBGFEAEGDCHCHDHFHEHAGDHDFEBEBEBEDCDCACAFGFCABFEGBGAGHHBDBABABHHAHAECEAGBGBHBFEDHCFCDGAFDHBEACFHHGDADHCFCBAAHFFGFDADBBEBHACABAHGDGBEAFABDBGGGGDDDAAHDDDHCHAABE,False +354,2.0,5.0,6.0,7.0,4.0,6.0,4.0,6.0,BHGHAECCCFADBDHDEDBFBHDCDCDFGCGFGFHHEFEB,False +355,6.0,5.0,6.0,6.0,6.0,7.0,2.0,4.0,HFHCGCGBFEAAAHAFBCBDEDEDEDCDFFABBCFCADFEHE,False +356,6.0,7.0,14.0,10.0,18.0,19.0,15.0,16.0,FBEHFGEHFDCDGGGEHCDCDFFFHBABDFDFHCCFEFECEHEFCAAGFGBCBFGFEBCACACDFFGHGBEHEHEHFHCCEGEGEGECAHEDEDGDGEHHHGHFF,False +357,14.0,24.0,11.0,19.0,13.0,13.0,20.0,12.0,CAHGEBBDBFBEGHAEDBDHDGDGECACACEFBDBFFGADBHBCCDCDHDEGEAFAFEGBFBABHFHAEDEDGHGBEBGBGBGFFBCGEGDAFAFAHAEBCGDDAGHHBCBDBDBFBDBDCGGGGH,False +358,14.0,23.0,16.0,16.0,14.0,16.0,6.0,16.0,HBCBHFHFHDBAGAEDCCCBFDFHFHDHDHGHABCFCFAGEGBBBFDADADBEBHFCFDFCBADDBCBCBCAEGEFCBABAFAHBFBEBEBCCEEHEDECBFAEHGADHDHEHBDEFBCDA,False +359,13.0,21.0,20.0,21.0,14.0,16.0,20.0,15.0,GFDBDCACAEBEBEBHBCBCECEGACHCHAHAGGBADADBDFCFHGDGDGEBHBDGGFGFGDBDAGABDGDGEHFDAEFFGFDHEBCCDCHCFCECHGDBCEHEFDFDABEBGDGHACFFBDCEAFGDBCGCBCFHBHBH,False +360,2.0,2.0,1.0,1.0,3.0,6.0,2.0,3.0,GFFFEFEBDBEHGCAHAHFF,True +361,14.0,17.0,14.0,17.0,23.0,22.0,11.0,18.0,DHACABDDDFEFBCAEAEAEFCFEFCFDFHFAFBCBCHGHFHEAEGBHBGCFCHAEBEFECECGFEDEFCCHAFAFAFADGHGBGDHDEDAHBHBHGEEBDHDBEEHGDEDEFBFBFHFGFBDAEBDGCHEEDCHB,False +362,7.0,7.0,14.0,4.0,6.0,6.0,6.0,3.0,CCBCGEGCAFAEADAGFGFCFCBCGHBBDBCGEAHAFCDCACBCHCEEFECBD,False +363,10.0,8.0,17.0,16.0,17.0,20.0,8.0,12.0,FEADABEGEHEBEBECFCDCHBHCAEEGHCFGFGFHHEFEFDFGFDECCACHFFFCDCGADAFGDCDCDCEFFFFAHAHBEECCDADAFFBEDEDEDHCFCDBHGHDB,False +364,8.0,4.0,4.0,12.0,13.0,9.0,10.0,11.0,FFHEHDFFAGEGEHEHFGDDDEDECEDABHFGFGDGAFADAEECGGABDBGHHCDCBGFDHDHAEAEHEHE,False +365,6.0,2.0,5.0,1.0,4.0,5.0,1.0,5.0,FEACAGFEFHCEABABAHFFEHAHCHCDC,True +366,11.0,5.0,9.0,15.0,4.0,9.0,12.0,5.0,CCFDEDFDFEFEHDBDCDHGGGGDFDAACADABFGCBCAGAFDFCGCGAHAGAHDBDHCGEBFDADADGG,True +367,22.0,11.0,14.0,10.0,20.0,19.0,35.0,19.0,DGGGBCECGDADABABHEHBHGAGHGFAFAGBGBGEEACACFEFGGGEFHCDEEBEBAHCEFFFFHAHAHGFECBHGGEGEHAHFGBDFHEEGCGFDAAAGEGAGFEFHFGAGAGDHAACAGHGCGAGDGBFHFGCGCECEHFHDGEGCD,False +368,2.0,3.0,4.0,0.0,3.0,2.0,2.0,2.0,BCECECHFHFAGEGBBCA,False +369,2.0,7.0,10.0,3.0,12.0,8.0,6.0,9.0,HHDHDCCEGEFFFHCBBHDEGEHEFEFEFEFBCBEBHBCCGCHEHBGGACECEFGAC,True +370,17.0,20.0,13.0,14.0,12.0,20.0,18.0,16.0,HEFEBECCHDECGCEBBGCDBDBDGFGFAFHGDDFDHBBBFAGDFAGACEFHGBFDFHFHFHCGBEDHFCFCFGAAEDECEFBFAHABACAGAGACAHABFBFGEGDBFBHBHDHDGBABAGCGEBAHGH,False +371,14.0,16.0,16.0,7.0,13.0,5.0,11.0,14.0,GBGBEHFHFBBBECAABDEABAGAEDEDBCEGECCACAGACACBCHCECEGABDBEBHBHFHCDAEADHCHCHFHCEABBCDHEGFGCHBGGHGHA,False +372,9.0,15.0,11.0,10.0,12.0,17.0,13.0,14.0,BEBEBGFFBFGFDFGCGCGFHDGGCFAFAFBFDHDEAEHEHAFBFEGHHEBGAGCHHHDDCECGCABFBFHFEDEDHBBCBGBCAGACAHBECEDDHBHFF,False +373,14.0,9.0,8.0,14.0,6.0,19.0,18.0,14.0,BHEFAHAHDDDDFBFDFGFEFHGBBFAAAGADHGBFCDGBEFGFCHHGFGHGHFHGEGAGEEAGDDABGGCCCBHBHCHDFAFAFAFGFDFDADADCGCGHF,False +374,13.0,6.0,13.0,5.0,8.0,10.0,12.0,6.0,CBGADAHAHAFAFGCGFGCDEAEADADCBHDFAACCCAFHBBCEGEGECFHAEBEHCGFGFGEGCGCFCGABF,False +375,8.0,5.0,6.0,3.0,11.0,9.0,8.0,4.0,EEEEHFFBFGGCGHGEBABEEFCFCBHGDBHFAFAFDFGAGDGAECECECAAAE,False +376,6.0,8.0,6.0,9.0,8.0,5.0,12.0,5.0,AEGEBACACHCGGHDBDBCEGEBEBHFDDGDCDBDBEGCAFBFGGGEHEAADFDFHGGG,False +377,2.0,3.0,2.0,5.0,6.0,4.0,2.0,2.0,EDEDECEBHBGFGAEADFHBDFEFDC,True +378,18.0,11.0,12.0,20.0,13.0,19.0,14.0,21.0,GAEHGHAADADADBFCECDCFCGDDFCGHAADFFFGHBHFDCDBFHFHGHFAGAGABADDHAEDECFFFAFAFDEDEBABFBGGHBCBAACBHHHFFEDEDADBEHFHGCGEEDHDCDGHGHEHEHCH,False +379,15.0,10.0,10.0,14.0,7.0,13.0,13.0,11.0,FHGHGHBBCDDDDABABGCEDADCHGAAHAFCFBDBDADFCFDDHCHFHAHCHCBCGGAACAHGGGGAGBEDFDFEAGDGFEBEFFAFAEBEF,False +380,20.0,20.0,27.0,28.0,18.0,28.0,19.0,15.0,FAEAEHHHHHHECBHFFFCFCDAGFGDEDCDCBGFFCGBGEGBAEAGFCADGGBEBEFHFDCBAEFDFDEDAHAHGEDAGBGFEBEGFDDDFDFAFCCCCCCBCBCGCGCACDDBFAFBCDADCDEDBCBCGHGFGBBAFDCDHBHDDBDCECACDFDGABFEDEAEFHHAAFFF,False +381,9.0,4.0,8.0,8.0,10.0,3.0,5.0,2.0,DEDECFCECEDAAACHEGDDFDFCACECGAABDGCHBEBGDGBAEAEAE,True +382,28.0,23.0,23.0,25.0,22.0,19.0,22.0,24.0,EBAHHEDEDBDHHGADFEFEHDHDGFFDFDADHDGEACBEHEFGDGAGAGEBCDCBBAFECHGGBHCHCGGGCGAFCHCHBBEBFBFHFCGCGEDEAAADABABADFEFDCDCECDCHCHCBAAAAAAHAFEGEADCCFHFEBEBFHDHFAAAGCBBBCDHDEDFBEGHCBDBGHGCGHDEAGABA,False +383,4.0,5.0,2.0,2.0,4.0,7.0,4.0,2.0,FAFBFGCGAGAGFBDEFEFHABFBDCHEBE,False +384,23.0,10.0,11.0,21.0,17.0,14.0,20.0,15.0,CBEFFDDBFAGHDAGAGAGDDBEGCCCDCBHHEAEFGFEEEHEACACAGAGBDAAHFHFAFADEHCACGDAEEFGGHEHBCDAGAEDEBFGHDHEHDHFHAGAGAGAFAFABBCDGGGDBDGDEDEDFDHD,False +385,16.0,15.0,15.0,12.0,17.0,20.0,20.0,23.0,FGBHBHAHAHBDFEFEBCAEEDEAHBHBHEFDCBAFCFAFAGHGHGACDHBCAEHGHBABFCFDGDFDFHFDBGFGHHACADACHCGBEBEHEACGEGFGFGDGEGEGECEADACBGFHHDFFHFHFGGBHCGCEEHC,False +386,22.0,28.0,19.0,25.0,19.0,24.0,12.0,27.0,BHDGBHDFDFDBABGDHAFAECECBCBCFCBEBHHHEEEBAFDFAFADECBDFDFAEHBHEHEGEADHHHFHFHDBFHAHADADFDFCAHBCGCDCBBBGBFAFCFHAGADDBFEFEAAHCDCECBDFFHFHBHBFEDCACAGEFDHGBEHGBCBHEEGAGHBDBDGHADADCBCB,False +387,16.0,23.0,23.0,12.0,27.0,6.0,20.0,14.0,EDEBGBEBCGGHCACBHBEGAGHGCGEGFCHBDCHGHBHGDADADBBCHCBEBACGEGEGEBABABDEEHECCCCBBBGAGAEAGFGHACCBBABAGFBEEEEEECGDDCDHEEEAEAECDCECGCFHFCBCEADDHEBFH,False +388,29.0,22.0,29.0,26.0,26.0,22.0,19.0,18.0,CECEGHFBFDDCDHGAFBGDFAAHACACAEEBEACFCAEECCGCGCFFFABGBGDCDGDEAEABHBHBFBHAHDCECECHFEFBACDDDEHAGABADFDFDBDBDECECEDHDAAAAEBEGAAADGFBFADACHEAACFGFGCGEHFHFCCCDGGBCEGFAFEBHCDAGBCBCDCEEGDBDBDHFHEBEHH,False +389,6.0,5.0,9.0,6.0,6.0,10.0,3.0,6.0,AFFFACCCEHHHHACDFDEGCBCDEDCFBFBDBFHFHADGCGCEFAFAEBE,False +390,5.0,5.0,8.0,6.0,3.0,4.0,2.0,9.0,CHCGBFDADACBFDFCHHDHDHCGCBFAEAEAECHCHBBDHH,False +391,17.0,18.0,29.0,20.0,13.0,16.0,17.0,22.0,GDCDGHHBEBFCFHGHAAAHBCDCDHFHEHBDDDDDCDCACHEBDBCBFDACBCBHACCDCGGGGCBCFCFBACADHHCFCADHHHGCBBGDGCGEEHEACAGGFGCABABDBEECECECFAFAGHHDHDFBFGFHECEFDFAHBHFGCACE,False +392,4.0,11.0,10.0,5.0,8.0,5.0,3.0,15.0,HHHHEEDDBGHGFABEBECCBHBCBEDECBCHCBEFEHDBDHAHBHFAGCHCHCBCAHFHF,True +393,5.0,6.0,6.0,2.0,4.0,4.0,5.0,6.0,HGFGHHHAGCGEFEBDFDAAHAFCBCBCECBGBEBHCA,False +394,21.0,28.0,17.0,22.0,17.0,15.0,15.0,14.0,DHAAAAFCDBDBDGGABBBCHCACGHFBBBBBBBAAAAFBBBBBEGEABCGFDHEHEDBAADEDEDEHCFEBEGDHFGGECDCHCHBDCEFEHDBDBDBDCECGCBFDGBADHGGFAFAFACEGEFDFBABFFEGDAACACHEHDHDCG,False +395,17.0,17.0,23.0,13.0,25.0,16.0,32.0,27.0,ACFCFGGGEEHEGGDEHBACACECEFEFHDEDFDGEGBGFHCCACEEFDACHGHGHBEEHBACCCCHCEFDAGAGEGCBHBHBGGGDGCFAHGHGHCAEFBBBHBGBHHEHEBGGEGEFHFHFHGHGCFCGHGDEDAAAGCBBBCHAEAHDHDFGGGEGBAHECDFDCAE,False +396,2.0,4.0,1.0,7.0,6.0,10.0,8.0,9.0,GCGFGFGHBFAEGFHFHGBDHEFEDHDEFEFDFEFBGHHAHGDBDHD,True +397,12.0,14.0,13.0,17.0,13.0,20.0,12.0,15.0,CEBHFCBGHGEGEACAHBHBDBGBADFDHDFDADHHEHFHBAAFACECECEDDGDGDCCCHCGBBDGFBECGDGACFFFFFFDHDHAEFEFBBGBFHFHECAFDBEHDFAFAEGFD,False +398,28.0,19.0,7.0,24.0,27.0,19.0,20.0,15.0,DHEAEADDHGAAHAGEHEBDBDHFCFEFEFEGAGHGBFHECAAGDCDADFCHDADADFDHGBGAEHDGFBFAFAFEFEFEHCAAAGGBBABDBCEADADFEGEFHADEGGGEGEGBGBDADEEBDBDHEEEDADEBBFHEEFCFEFAAAGABABDBHBG,False +399,0.0,3.0,1.0,3.0,3.0,3.0,0.0,4.0,DDHFBFEFDHBHCHEBE,True +400,14.0,15.0,8.0,10.0,12.0,16.0,15.0,13.0,BABABGHFHEHEAEBFGHDBCBGDCFFGAGDGFEFEFEFHDCAGAGHHAHACBCBGAGEGEDBDHDEBCACBHAHCFAFEBEDFFFBFGEGFABHGDADFBHG,False +401,11.0,5.0,16.0,15.0,7.0,18.0,6.0,17.0,EGDHHBGCGFFFFECHDAFAFBFDHGHAACFFFAEHBFDFHEHDFDFDABBEAFCCCCCCCFHAGADDDCCEHEHCHDHAHFHCCCFDHDHDADG,True +402,3.0,10.0,24.0,13.0,15.0,13.0,11.0,19.0,CBBEDHAHBDBDBGCECHHDHGHDCGCGEHCHCGCEEEEHFHFECEGBDDFBHEDBDADGFHCHCGCBCDCEAFGFGHGHCECFDECCCCCDHHEBFHFCFCEHFFCF,False +403,1.0,2.0,2.0,2.0,0.0,1.0,2.0,2.0,DGDABGBCHCHF,False +404,5.0,16.0,6.0,12.0,8.0,5.0,12.0,9.0,DGDHBCBCHGEEHEFGFBAGABADDCDBBBBBGAGEEDCDGHGHFHBHGGCEEDBDBDBCBDBGFAEBHFHGD,True +405,21.0,16.0,12.0,16.0,13.0,10.0,25.0,18.0,GFEFBFGGBGBGBHFHEBEBGBGFGFCEAGCDHAABHBEGCGHDHAHDCEGDGDBFGCAAAAEAGADFDGDAACACECEBFDHBAEACHGHAHDEDEFHHHBGEGACDBAGGBCBHHCDGAGDGHGHADAD,False +406,4.0,4.0,3.0,5.0,1.0,0.0,4.0,3.0,GBDDABCBCGDGDCHBHDHAGAEA,True +407,16.0,7.0,6.0,14.0,13.0,6.0,14.0,8.0,BFCAAAAAEFEBDFCFCADGDBDBDAGAHAEDEGHGHGFDBDGAEHEAEAGCEDHAEADGDAFADGGEGHGHDEBEHDGBGCCE,True +408,12.0,15.0,11.0,21.0,18.0,14.0,12.0,11.0,DBDBDBDBCBGGABCEFEFGGDBDAAAEHEFEBGBECCFCBGEEAEHCBFEFHFCEBFBHGADFDACABEBEAECDCGFDDDDDDHGEGFDHDHDHFCDDEDGAAFAFHHGHEE,False +409,20.0,21.0,28.0,22.0,20.0,26.0,20.0,22.0,FCFDFHADGDHDHBBCCHHDHDHDGAABAGCGCDCDFFFAEAFBHHGHCHEFEGBDCDAAHABBCFHFEEGEFFFCHCDBDEDEFEDAFAFABEHCCCEBHBDGDECCAAACDGFFEDHDFBHBAGAEAEFECGGGCHCDAHBGBDBCBEHGFCFCFCFCEGEGHFCBGFGCGCEABBB,False +410,3.0,1.0,3.0,3.0,0.0,0.0,1.0,2.0,DGACBHDHDCACA,True +411,10.0,24.0,18.0,15.0,16.0,10.0,24.0,18.0,HHFBFECHGHAHFGGDCBCBCEGHGBBAAGCCHCBDBGBDHHHBFBDBGGCGHGABABACEHEHCDGDECBAAEFGGDGEADDDHDHBEBEGEFEGEGCGDGDEDBCCCHCEBEDCGFGHGEGFBFBACHBBBBF,False +412,7.0,7.0,14.0,10.0,10.0,6.0,9.0,5.0,GEDFDFBAGCDABADDGAHEDEDFDCDCDFHCBCBCGCHBGCFCAEEEEEGEGCCCHHGCBEBCAGAF,False +413,1.0,1.0,2.0,0.0,2.0,2.0,3.0,2.0,FGCGCHEHEABGF,True +414,3.0,7.0,4.0,3.0,7.0,6.0,6.0,8.0,HCHGEEBABABFBEGFGAGBDFDEHEFCFBHHHFHCHCBEEGGD,False +415,17.0,22.0,23.0,22.0,24.0,17.0,20.0,16.0,BCBGBADDEHEBECCCCDGAGEGEAACEHEHGFABAEHECECFCGCECDBACAHADECGCBBFGFEHEFGDGEGCGFGDHDCBCAFGDGDAEFHFCFBEEHEBDDFHHHBAFAHDEDGDBDEDECFCFHFAGCFFAEGDGDADCBBBBCGHHABBBBBDED,False +416,23.0,23.0,29.0,23.0,28.0,15.0,36.0,18.0,HDFEEHAHFECBCGDFDFBAGABBGGADFDGEGECECGDHCECECEDEDACACGEGCGFBCBCACEEDEGGABHEDCHBGGGHGCGCBDBCCCEHEBGBCDDGGHGEFEGBBBDBAFAFAGBFFHHADEGEDBCCCACGCDCGEAHAEADGGGDGDBFBFCGCGBGBGACAHAHGEFDADEHEHAFGHBHDEAEA,False +417,6.0,3.0,6.0,6.0,13.0,9.0,7.0,12.0,HGCCECEAEHGHGCFAFHDDBDEGBGHHEEDAFGFHEHAAADBCHCGFEEEHEHEFEFDFHF,False +418,7.0,7.0,9.0,13.0,10.0,16.0,6.0,11.0,HEFFFEDECCHHBHFDFACACEDHDBDBDBDFCFDEDEBHGEFFAFADAFHGBGCGCFDEAHDFDHGHFHCGEFEFABC,False +419,6.0,2.0,4.0,3.0,3.0,0.0,2.0,0.0,EEBDBAAAACACEGGCCDAD,True +420,20.0,21.0,13.0,17.0,21.0,27.0,25.0,13.0,HAGAGAECCFDBEADDGAGFFDCBFFCABGBEBAGCGBFBGEGEFDCDEBFBEDCAHBHBDFDFBADGFFEGEGEFEFEFHFBBABAHHDGDGBGAGFGFGEEDEDAFAGDHEACACFFGFGFGEDECBFBFHHHGEAFAEAHFBEBGBCHCHGADC,False +421,9.0,14.0,14.0,8.0,6.0,14.0,12.0,12.0,FHFDFDBBBGBEBCBFDGDHFGABCGABBGEAFAHACACHDDFHCBBFHFHFGCHCHGBBHHGCGCACACHCEFEFADDFEFEGGCGCB,False +422,2.0,4.0,4.0,2.0,2.0,3.0,4.0,6.0,HFCFCECBGGGDGBEHFBAHAHBHDHC,False +423,19.0,10.0,8.0,8.0,6.0,9.0,8.0,8.0,DEABABCFEFDAAABFHFAFAFADACCGBABAGHBABABAGHEHCGDGDCDCGEHEGDAABAEHBAGACDFFCFHH,False +424,22.0,16.0,21.0,30.0,13.0,19.0,17.0,12.0,BCBEBDAEAEAHAHGHCBCAAEADGFGDGDCACFCDEGCDHBCADDDDDEABADADADAEGBGBHCGFAFDCDBDFACDBDBCFEHEHAHGFGFGFGECHFHCCGDGACDFDECFDADEBHFFDFDFBFBEHAGCGDFCBGDACBCFDAD,False +425,12.0,15.0,7.0,11.0,10.0,19.0,9.0,9.0,CADACAFHFDDCDBFBDBEBEDEHFABACFFHHGFDFDGDGHAHACCBEFDFGEGEADFFCEGBABAEHHBHBGBEBABGBEFFFFABGFFF,False +426,10.0,14.0,11.0,11.0,11.0,17.0,18.0,9.0,BFBAAEFEHCHGAFEBCFCGCGBGFHFCGGAFAFBFCFHBBFEFEFEBGCECBGBGCDFDBDBDGAGEFEGHGHAADEGCGHDBAEGDDDDCDFGFGABHH,False +427,37.0,20.0,35.0,16.0,24.0,26.0,23.0,17.0,AGAEEHGHGCCCGBGCHCHCHFGGAAAEAEAFHCHCGCACADEEECBABEFEHDFBFEEBBBCEFAFADACAFFCFDHDGBFFACDGDFDBBBCGCBAAAEAECGCDHFBDBCAAGACACAFAGGBEHECECEABFEGDFDHHAAAACHCHGHCHABEGCGFACCECFFBFBABAGFFDAECEDEFFACGCGAGCDFD,False +428,16.0,17.0,31.0,28.0,15.0,17.0,26.0,26.0,FGFCCACBEDEDBCGCGFDCAAECEAAFFGGGGHCHCAGDGDBHBHFHFHFHDHAGGDDADHDHBACGCGEDHBCDFDGDHDCCCBBBBGCCCCFBDDDBCCCHCFEHHGFBFCCAAGGDADGDHEHAGCGCBDBFBFEGAGEGHCFDHHHHEHEBEHDFDGDHAAECCCEDEDGH,False +429,8.0,4.0,6.0,7.0,12.0,5.0,7.0,6.0,AAHAGBFHFCEAEBECGFGFGEEECBCDCAEHEAEDEDHGHBCFDGEGDHDEDAA,False +430,5.0,7.0,8.0,4.0,4.0,3.0,11.0,4.0,HGDCHCBCBFGAGBGBEDHAEAEGFGCGEGAFCGCGDHDBBBCCGA,True +431,8.0,19.0,9.0,16.0,16.0,15.0,11.0,12.0,FABCEHHCGDGDFDFHFAEDGDFDFBBBBFEDEAGBEEEFEGEBEFDDGBBAAAFHFHEEDCDCGEDBDAEHEHBHBHBFGCDCHEDBFBGHGFBFBCBCGCBAHD,False +432,25.0,23.0,17.0,34.0,27.0,19.0,18.0,34.0,GBHHHFEGGFGFGHBABDBDBHGGEBBDEDHHHHAHFHEHFFFGBDDEAAAAADCDHACAFDBDCGCGDDDHAGBDHGHCHABAFEFEFEFDDBDBABGFAFEEDEDEAEBFDFDHAHABEBEDDDFHCEFEAAAECCBABHDADHCBFGDHEHAGBDHHEHEDEAECEDGCEEHDDGHCHCHEDDHBHCHCACBCG,False +433,11.0,10.0,8.0,8.0,5.0,5.0,7.0,5.0,GEEEBADHCHEBEACABDBDAHABABABCDCGCDABFDCACABGGAGHCHFFDDGFGFB,False +434,8.0,2.0,9.0,3.0,9.0,11.0,9.0,7.0,CECFFFHGHBHCFCFBFHDACEEFCGEDEDAAAGCGCEFFAAGGGHFHFHEGEGECAA,False +435,15.0,9.0,12.0,17.0,12.0,13.0,11.0,8.0,FEFHFAFEDEDBCGGFBHACGCFCHADADAFAEAEADHDBDFHEDEDBBGBDADAGAGEGECCHEAACBCDCEGFGFDADGHHFDFCCCBDGEFADB,False +436,9.0,4.0,4.0,2.0,2.0,7.0,7.0,7.0,HEFBABCEFAFABGGAAACFCFGHBHACGFGAGAGHHDHDHF,True +437,13.0,14.0,15.0,27.0,27.0,6.0,29.0,26.0,DDDEHABAHEHAHDCBGDHFCEGBBHBHADDEAGGEGDGDGCCDCDBDBHBHBAAHGGGGACECEGGGECCDGDGEGADADGFHEEDEGACAGHDDDFDFBEHCHGHFHEEEHEHEHEHEGEFDGDGHBCCEDHBCGDHEEBAGHGEGEGEDHBHCD,True +438,22.0,9.0,13.0,21.0,26.0,17.0,18.0,21.0,GAGEHFHCEGEDAFAHAHEDBDFDABAHEDGDBCAEGDDDGGGGAGEHHHGCCFHHBHBHBHAGECAGDGDGDGEHDFAGCEEFEHEAEAEFFCECFFFBDADFDADADAFEEEEAFAEEBABAHEFDGHEHFCDCDCECHCHFEAH,False +439,24.0,19.0,22.0,19.0,24.0,22.0,19.0,24.0,DCDCAAAAABAFGFDFDHGCGCGBDACCCCEHFACHEDAAEABAHABAEFHFCFCFBBHFHEHEGCGDHFECBBBGBEHEAEAHDGDGHCHFBFEFEBEDFAACDHDFBHADCCEHEHDBFGFHDHDGEGADADEDEBECHFGGAGEFCCBCGFBBAGEHFHGHEHEFECBGA,False +440,23.0,14.0,11.0,16.0,9.0,11.0,13.0,16.0,DCDGBGBAAHECEFGFGAGHHEDGBCFDFGHGEEFADAEGFBAAAABFBFDAACCCEDHHHDDAAEBHCHABCHAHAHABEDGFGBGDDDDDDGAAHACACACABFFHBHBHB,False +441,5.0,9.0,7.0,7.0,5.0,6.0,6.0,2.0,CFDBDGCADBDBDGAAEAEBFBCBFGHBEGDHDECECBCGFGFBFAC,False +442,21.0,17.0,17.0,31.0,26.0,21.0,12.0,20.0,AAAGDEAFCHCBEDDBDBDHCAAHBDBDADHFHFHFHFHFDFEADADHHCHDDCFBFACHDEEEDABADAFEFHCACFFFEFBBEHGDGEGFDDCDGEGECCCCCFCHDEEECGCFDEDGBBDBGGHBFAFEDADFDHEHDHAGDGDBAEEEBEDAHAEBEBEAE,False +443,22.0,20.0,27.0,22.0,26.0,31.0,22.0,17.0,EDEAHFDFEBGFEFHGAFAFEDEAHDFBEDACCCBCBAFADAHFCGHGHDCDCGGHBBGACADFEFEFBFBFBHBHAHAGGGEGAGACECECBAEFFDEECDFECECBCEHDFCABHBCGDHBFBFBFAEDCFFHFCFGFDEDEDGFGFGFBCHEGGCEDGCCHDGFGCCCACEDEAEABABADFDH,False +444,25.0,15.0,17.0,18.0,21.0,13.0,21.0,25.0,GCAFBBBBAFGHBACAFHCECHBEDEHHHEDAHABCGDEAAABDBHAHBEGGDGACDBGGGGHGHGCECEFHFCCGBEEEEEDFCGDGDADADCECBFFCAEAEADGDHAHAHEHDHAHEFEHDGFHFHBDDAHAGAGAGAGEFBHECFCACHDH,False +445,4.0,5.0,1.0,1.0,6.0,3.0,0.0,1.0,FEBBABEBEAFHFEAEAEBDC,True +446,3.0,5.0,3.0,4.0,0.0,2.0,5.0,1.0,DBDAGBGCGCGCBBBAGFDHDFA,True +447,27.0,17.0,19.0,29.0,21.0,26.0,19.0,16.0,AAEEEEFDFHEADAGFGFGAGHFABBBBDADAHFDGCHFDFAFGCCBFFHDHDADEBHGCAHAFCCGCHEEADCBFFDFAFACAEECDCDBHBDCCEDEAGABDBDGGGGHFHFHDEAFDCDAAABAGCGFDFEEEBGAGAHBGDGDFDFDHHACCDCEBEAECEFEFDFDBDB,False +448,12.0,3.0,7.0,7.0,6.0,6.0,10.0,15.0,GCACACAFHFHGHDHAHDDEDCFAHACAHGEFHBHBFGDEHEAAAGAGCDAEGEBHDGFGHHCHGH,False +449,27.0,20.0,31.0,20.0,16.0,31.0,25.0,16.0,CCFCACAHBDGCGCBCGCDCBBEBAGFFFCFCDCBHBEFDFDHGGDCFEDBDFDCDCFFDBAECHADBCHCHCAAAAFAFADDGFCECGCGDDEHGHFFEHGHGFGFGAEFBFEFDBHAFDGGCFAFHHHBHEAGAEAEABGHFAFACACBCACGBBAGACAFFGFGFDBCBCGEEEECFADGBGA,False +450,2.0,7.0,4.0,2.0,6.0,1.0,3.0,3.0,DGCGCBDBHCECHBEGEABFBHEAEBEB,True +451,8.0,7.0,6.0,1.0,2.0,4.0,4.0,3.0,FGFHEABCCCDBABAHCHEAGCGCBAAAABBBFGF,True +452,12.0,16.0,17.0,11.0,29.0,15.0,19.0,16.0,EGDGEGHCFCFDDBECFHFHGEBEBEBEBDBAHAHADCEEEEEEEBECCBBBGDCDCFGHHEACAGBGHFEGEAECFDEGFHCEDFDFDCBHEAEAEFBGCGBAHFHGGEEBFGFGEHAGAGAFCBHHHCCECEG,False +453,4.0,3.0,6.0,2.0,6.0,8.0,4.0,3.0,CCFCEEHCHBDEFAFAFHGDFEGEFBFBFCECGAGA,False +454,17.0,13.0,25.0,22.0,19.0,16.0,28.0,27.0,AGAHHCDEDGGGDHHFEEGEHHCGGHGABCDCDAAFCFCGAGCFFFHEEEHEBGBCFHDAEEBDCDCGCGCBHBFCFHDHGBGDHCHFHBHDHBEAFCCDEDAGCGCDCFFHGHGHGAGADACAEABFCECECEBEHAGAHHDGDGHGHGFDFDEBCHDDCDGBGEA,False +455,3.0,8.0,5.0,6.0,3.0,3.0,1.0,4.0,ADHHHDFFACBCBCHCBDDGDBDBEBEAEFCBB,True +456,17.0,25.0,25.0,21.0,21.0,26.0,24.0,21.0,GEGBFBFBFBGAHAFACDEDCCHFFGBGAACFCHGFCFGHDAEFEFGFGHEBEBDAFGFAFCCBABEHCGFEDEDGBGBFBEHEGGCDCDCBGHDCCCDFAGBHBDEDHCHCHEHCBCDDDDFBEEEEGGBFCFCHAHACGFBBHDHBABGBGDGDFAFAECECEFDFDBGCHBAAHHEH,False +457,12.0,10.0,8.0,8.0,4.0,11.0,8.0,8.0,DBDFDFCCCHBEGFBHEFACBDBGHGBFAFGHAHAHGDDDCCACGCEHGFGFBFBABABDHFAAAEAFA,False +458,20.0,11.0,18.0,22.0,26.0,28.0,20.0,28.0,BFGHCHEAEAFFFFGABCFGFECECECECHCHGHDHAHEEEFHAAFBCGHDHDHCABGHCFDGHGACFDDDBCGDDFGGGGEEABGFAFEHAFEHAFAEAEABAGFDFEEHEFECDADHDHBHEHDHCHFHDHFHGDDDDEDEFEFGDCHCECEFHFAGBFFEFCADGBGBHA,False +459,18.0,25.0,19.0,16.0,13.0,17.0,21.0,14.0,CACACDEDBCBHAAGHBHBCEDEDAGGHDFDEDCHFHECFBFACAHAGGGGGAGDFBABFFGFBHBHBGBHBACABHBGCGBGEFADCDCHAHDHDBACABBBGEGEFCFBGBEFDFABABFCEGECDCBCGDBEGFFCFDGE,False +460,21.0,19.0,19.0,30.0,29.0,19.0,23.0,32.0,FDEDECCDEEHFDFEFEFHAHDCGCGCFDDDCGAGAECDHBEBAHGCGEFEDHDHDGDBHBADCDCHHFECHBGBEHADBDHGHGHGHDHFBGAGHBFBAECGGFEFEFDGDCDAEGEBACHGGDDADFHAEABBGBABDFDFABEDAHBHAHAEDEAEHEHCFCHEHEHBHBHGGCACAHEEEEFDFCGDH,False +461,9.0,19.0,19.0,25.0,19.0,17.0,20.0,16.0,BEGCGDAEHEDBDCEHECACAEAEAFCEGHGHFHGHCEDDDHDEGGFEHEFDFGFDBDBDGDEDCFCFHECBDHACCBCBFGDGCHBHDDBGBGFCBCDDGDACFGGGGFGBEBEGHDBDFCFBFDFDBHHAHAEDFBCBEBEC,False +462,9.0,14.0,11.0,15.0,9.0,10.0,15.0,17.0,CHCHCGCBEBDHEHFBGDGDGDGDBDGEGCHHBDBDACFCHGFEAHFFDCGAGBFHEDEHHAHAEBHBHGAGBFBDBCFCBCBADAGEGHHEFDFDGDAH,False +463,15.0,16.0,16.0,16.0,13.0,12.0,15.0,14.0,EDEGEDHBHDHDACHCBCAHADGDGAEEHFGFGFAEGEDECGGAFAFDBCHCGCEBABABABDEACHCBABAFGEACFDBBCBEGEGCDCDADBDFHHHHHBDCDGBFFGFHCBCFG,False +464,20.0,13.0,10.0,7.0,14.0,12.0,14.0,15.0,HHHBDFFCHCGCGAGDFDGEBFBABAFAFHGHBAGEGEHBACFCEDBACCCABADAGBGAGEEAAFAFACGCFAHEHEDEBAGEHEHEGAGAEFHHHHABEBDBF,False +465,32.0,28.0,23.0,18.0,15.0,22.0,28.0,21.0,CAHHBFBGCACEGFGAAABABAGGCGCGEAAGCGEEDBDGDCDHDBBABAFABAEDBGCEDBDBAHABFHEDEDBFFGAGHHEGAGHEECDCFBHCGBDBDBFGFDFCFAAACACFGHGAGDCFGAGFFBHCHCEABHBFBFHFAFHFEFBABGBGBGHHHAHAGEFCCHBHCAGBCDCECADADAG,False +466,14.0,31.0,26.0,20.0,17.0,27.0,15.0,13.0,BBBBBCGFEFDFDFCCDCHHDAFADACCEAGGCGCACFFEGECEFECCACGEBAGDGHBABDBHBHFCBHFCFCAHDCDHBGFEEDEDFAFHHGBBFAFCCCFAFDFEBBABACHHBDBDBFBCCFFFFFFDBBBBBEBECEGEGDGDGEGCHEBCDFBBBDD,False +467,15.0,12.0,15.0,11.0,17.0,18.0,18.0,13.0,HAGECCBCFHEGGGGBGBDBGBAFACCFCFCBDFAAAAACEEEFECDFDCDCDHBGGGFGDABAGAFFEAEFHBEDEDEFBAHGCGCHFGFGFHHDHECEAEGFAFHHEHEBBGEHFDC,False +468,22.0,12.0,14.0,17.0,19.0,18.0,16.0,15.0,DADADADAHAGABAEHFGFGEGBHBGADHDGGACHEHCHGEFFBCGCAFGDGAEHEAAFCFGAHAHEDDFDCHFEFEDEBECABEFGBGAGCCECFCBBBBHAEBECCADEDHHHEDEDEDFFFFGDAAAFCF,False +469,18.0,26.0,29.0,20.0,29.0,19.0,16.0,15.0,CGCGCHCFCGHHCHCHCHCFAEAFFECEBFGDHDCECECHCFFDBDEDBGGEGAGEHBBCCACABEEEAEBEBACECGADBBHBDBEFEFEFCDDGCCBAHHFCBHBADAGFDBEFEFEAECBFFHABDBAEDECECEDBFBDBDBDACGEGEBADCDGBGDGACFEFBAEH,False +470,6.0,1.0,5.0,5.0,3.0,4.0,4.0,6.0,CBCAGGHDHDHDHFHFEECACADHCAFAFGEADG,False +471,8.0,12.0,3.0,4.0,7.0,8.0,8.0,2.0,GAAFBEGEFDAGEGEFEHGBCFFFFGBBBEBABABDBDBEBDHGCABACAGF,True +472,9.0,4.0,9.0,5.0,3.0,6.0,1.0,7.0,HACGCABHCEAFHBHDAAACFCBEDEDADAHFHFCFAFBCDCHC,True +473,2.0,1.0,5.0,2.0,7.0,3.0,2.0,10.0,CCHCDDGFHAEBEHHFACHHFHEHEHEHECEG,True +474,8.0,7.0,5.0,9.0,9.0,4.0,1.0,12.0,BCDHBCBADCDHHAHDHAHEDEDBHEEDHCHAFAHAHCEGDADEFEFEFABHBEB,True +475,11.0,5.0,2.0,1.0,3.0,2.0,5.0,4.0,AACDCFHAGAGAEBGBHBFEAGBGAAAHAHABE,True +476,25.0,30.0,25.0,21.0,26.0,22.0,25.0,24.0,HGHEDBDBCHEHEDEDEDEDCAHDCGCFDFGEGDGAGAGHGDGDCAAHABAFACBCBCEDEAEDEAGDFEBEBEHGHFHFCBBFGHGFEFBBBFHGBCFCEBABADHBCACGFHFACACDFABHEAEHHDGACHFBFBHBHBABGGDBABGFEFBHGHAHEBGBGCFBEBECGCACEFAGECACFDFEAECCBGHCDD,False +477,15.0,14.0,22.0,19.0,17.0,22.0,25.0,22.0,DFGGGFHHCHEHBGDEEBFBAAHGFGFGACCCGHFHBHCDEEFEFBFAFBFCGCEDEHEHEBFAFAFAFGCGCGDBCBFFCHCDDDEAEAGDEDECGDGABBHDHDFDFDGCGAHEHFHCHAACDDBHHACBGBGAGFFHCCGHHCCGDGDGCGEE,False +478,14.0,12.0,9.0,13.0,13.0,17.0,7.0,13.0,AFAFBFBDAAADFFBFBEHGFEFHAHFGDDFDHAHADABFBFHEHECCACGFBDBGAEHCDCHGHGEAECECEFECADFDBGBHBHEHDDFEFDBEAC,False +479,29.0,20.0,16.0,24.0,27.0,18.0,17.0,26.0,GEHHHAHEGBGCHCBCFGDGBFDHCCBCHFHAEFEGGDHDACEDDDCDFDFDHBAADHFHBEFEHCHCDFAFABAEGBHBABABAEHEAEAEDEAFHEDAGEBEFGCEDEFEDHBFFDFAHHDBDGDHEAEGCBDEDBAGAGAGAEAHACACAEAEBHAHGFGEBEADADBHBHFCC,False +480,11.0,14.0,7.0,9.0,18.0,15.0,6.0,9.0,FAFEGDGBBEFEDEFEFABAGEGEFFFBBCBEDABEGAAAFHFDEHHFBFDFAFCDCDEGHHCHBABCBEHEHEBEBEDEHABEFACDC,False +481,8.0,4.0,7.0,16.0,11.0,8.0,9.0,4.0,EEADADFDEAFBFGEGFGDGCHDDCDEBEGEGCFCHDAGCGDGAECFCEDDFDEABABADDDDEHFH,False +482,11.0,7.0,25.0,5.0,16.0,24.0,10.0,11.0,EAEAEACFCBCEFEGAGAGCCFFEFGBCFFHFCFAHACFCEEHCCFDFEEHBHFHAGFFEFEBDAGCGFAFEFEHECGCGCFCFHFHCCCBCDDBCCCCFDFHAECBHG,True +483,24.0,31.0,31.0,29.0,20.0,23.0,19.0,21.0,HAHEECBBBBGBECEFBFHHCHFHDBGBHEGEADAEAEBBFBCECFCACABHCHCEBFDFCFCFBFHHHEGCDCDCDHDCECGABADDDBAGAGAHEDEBBDGCBCFAFABAHCBCFHGHBDEDGBGEHCDCFCFCAHFBCDCDGDHABGFEBDBDBDGAFAGAFDDCEFABAFDDGAFEFDGCBABHCGDGDCDCAE,False +484,10.0,14.0,9.0,7.0,6.0,9.0,6.0,9.0,HCACBFBFCFCFHAHADACABDCHGHGCBFDHCBGBABFBDBFBEEHADADHBBEBADAGECEFHBGEGF,False +485,10.0,4.0,11.0,5.0,13.0,7.0,15.0,10.0,AEAEHCHCGCGCBEGEGFGBGAGFGEHAFGCHDECCAHADDFDFHFHEGEGACCBHDHAEGEGCGHBEEEGAFAC,False +486,10.0,4.0,4.0,3.0,10.0,7.0,9.0,8.0,HGHCFDHAFAECEFHFHEGECHDDACABAEEEGGAEAGAGAGAHFGFEHEFGBBB,True +487,5.0,6.0,9.0,7.0,10.0,8.0,5.0,12.0,FCFCFHFAFAFGEDCBEHHGGEHEHAGBHCHFEAEDEDBHADCBCDHDHDFBEBCCHCGEHE,False +488,11.0,11.0,11.0,8.0,15.0,8.0,13.0,12.0,CBABEBFHFGEGHCDCAGDGEABBCGGBBHEFBBABGBADEHCHCEAEAEGEFFFCGCEHDHDHECDCAFAGAGAGEHEGFDHCHEHED,False +489,22.0,25.0,26.0,26.0,18.0,25.0,28.0,23.0,BEBEBEBFFHDHDHCHDHCCGCFAGCHCHCDCGCABABAFCHEHBCBCDCGCEHAHAEGGABFDHEBECGCHCHFDADAHHEGFBHAHFDGDCCCHFFGGGGBFAFABGFEFAGGFGDBAHFEGEGEDBBEDDBHBDFDFGGCEFGFBFHGADADHCEGEGDGDFDBBCBCDGBADABAFCFAFADDDBCGAE,False +490,19.0,24.0,22.0,16.0,30.0,19.0,23.0,31.0,FGGAFEFECGHHEGEHEDEFEHAGFBFBFHAEAHAEAEACDEBBHCECACEGBBFBDBCHDHGCFEHHAHAHBEBECGGDGCHBHGFGBDFCGHGHDHBHBACACHBEAABDHEHDHFFBFHFHEBCDEDEDFDGEGAGADBCHFHABDBDCFAEAEBEBECGCGEHHCCBCHCEGEGHFCGEG,False +491,16.0,23.0,19.0,29.0,31.0,20.0,28.0,25.0,DHDBCECECAGFGBBEEEECEDEGHCDGGAFDFGFGCGCEHGHGEDFGCDFGFDDDCDEFEABDEDEBEBHBHBGGHBDBHAFABDGHCECGAEAEAGABHDHDHDHBBBGEHEFEDHBEEEGGCDEFGHGHAHAFCFGFEDCFEABHFHEBEBDHDHACBCFGAGFGHEHBGBCHFGDDADCDADFDECB,False +492,2.0,8.0,8.0,4.0,4.0,4.0,9.0,3.0,GEGFACBGAGECCHCHCBFDGHCCGCGBDBDBEBEFDFBGBG,True +493,21.0,13.0,20.0,26.0,11.0,13.0,10.0,15.0,AACGHHEEDBDBDCDCDBEBFBFEGDCEADDDFAFAEAHHHFAFADEDCHCBCAAGACDDDDDBCAGDCDBEHGHGFGABDHDHCCCCHADAEAEDHDAACAFAFBFEDGBHCCADHBGBDFCFCHCFG,False +494,4.0,3.0,5.0,3.0,3.0,7.0,4.0,3.0,AHFEBAHCHGFGFEFDADBFFCFCGCGCBEAD,False +495,0.0,4.0,1.0,1.0,4.0,0.0,2.0,1.0,BDEEBEGEGHBCB,True +496,6.0,16.0,13.0,12.0,12.0,13.0,12.0,10.0,DHFEEBAFCHCHCEFHABBCBCFGECECEGEBDCDCBBBBFAFEBEGGCGAGFHEDGBGEGCHEBDBHBHCGBHAGDFDFDFDFDHCADFDFGB,False +497,19.0,9.0,12.0,22.0,14.0,24.0,20.0,18.0,DEDAHEBAAGDBHHGABAGCHCDCACFCGCEEACBFAFAGEDDDHHHCHCGFGHBAGAFAHDDDDDGDFDFHFEEDEHFHEBFDFHBAGHGHFHFEDEDFDFDCGBFACAGAFHFEABGEGFGFGFECADAGGDGFFF,False +498,8.0,3.0,6.0,14.0,8.0,17.0,6.0,15.0,GFFDFEGGBEBHAEDGFAFEFDDDAFHCHCDCDGFHAHFHFGDHCEFHCHCFDHDHAFDFEFAFABAEHFHDHDEDH,True +499,0.0,6.0,1.0,2.0,2.0,3.0,3.0,4.0,EDECHDBGBGBHBHFGFBHBF,True +500,9.0,11.0,8.0,10.0,19.0,12.0,9.0,5.0,GCFDBACGFBFAAAAGBFAEGFGCGHEAGHDFFCEDEDEDEDECHBEGDDEAEFDFAFEBEHEHEDEBEBEBCBCBFFEGBCE,False +501,8.0,14.0,12.0,11.0,8.0,12.0,9.0,4.0,DBDBEBDBDFDAGCGFBCBCFFGCDCDEDBBBECECFBFECABDDAFAFAGEFBHAGAFCHCDCGHGHBFBEGEFCAG,False +502,5.0,5.0,5.0,5.0,9.0,6.0,4.0,8.0,FEFEBHHHAHABEBDDFDHDCAFFECEAHCBCEAEBHGHGCGFDEGE,False +503,12.0,12.0,13.0,25.0,16.0,10.0,18.0,21.0,GBGBDECCCFHHBACGDGDGDADCGCBBHDHDHDBDFDFDHEHGCEDEGEFAFHBEFFGCEHFFDDHDHGHGDAACAGBDHGHEDEDGAHCGDGDACEGAHAHDHEHEBEBCBFBEHEADDGDCAHE,False +504,10.0,15.0,9.0,13.0,14.0,7.0,8.0,9.0,CBEEFBBGBGBDBABADFBAAHEBEDEDGFCEBDBHAHBCBCBGGFDFCAGAFDGDHDHGEBEHFHECECEAHCDDEHEAEADCD,False +505,18.0,16.0,17.0,23.0,12.0,18.0,20.0,12.0,FGFABEFDHDHFHGDBDBGBGCACDDDHAHBHFFFBGCGEAEAGABHBGDGCECEDHFAGBDEAAHCEGHDEDEDFGHDDDDEFFAFGDGCFCFDFDACFCEAABGBABCBCFHGGBGEGAACCCCFCGBADADBD,False +506,22.0,16.0,25.0,22.0,25.0,11.0,27.0,18.0,AGCDCDHDBGCGAGDDCDGBGDCBCGFGHCECGHGAEFEDEAEGEFHGBCBCAAAAGGDGEHEAEDEDEBCBGFCFGDDEDECFDHDBEAEDEHGHCCCCABAFABCBAHCHGHCCDCEFAGEHAGAGHEBCHEGBHBHDHFEEEACACDEDEHGGGFBFBGDAAA,False +507,13.0,17.0,22.0,10.0,17.0,14.0,17.0,13.0,GGGCBBBEBHAEAGHDCGCDHFEAEABHCHGFGHGCCFFBCAAHEHEDCGCGCDADEHAHFDFAFCHCFCBDEEAEFHAHFCFABBDBDEGECEBGBGCGCDEEBEBFBEACBCGCGBGCFCF,False +508,17.0,21.0,24.0,12.0,17.0,20.0,19.0,17.0,ECHCHCHCGCFBGAGEBEBEBDCCFHFGCDFFHHBGBGDDDGFCFCGDGFAACACGFHDHGAAHAEBEGCCCFGFADADHBBBBABEBEBCGCHDHBGEHCACECEDDCFFAFEBACAEHEHBGBHEFAFBGHGFBCBEAEAGFFCF,False +509,4.0,0.0,5.0,5.0,1.0,0.0,3.0,4.0,GHDCDCDCDCAEHGCDHHAAAG,True +510,10.0,11.0,3.0,4.0,7.0,2.0,18.0,3.0,HAGGGGAFAGCGEGBGAEBGGEBEBDCEGDBDADEBEGAGAGBBBCGGBGAGHBHAFA,True +511,2.0,4.0,2.0,2.0,1.0,2.0,3.0,1.0,DEDFHGABBBBFAGCGC,False +512,2.0,4.0,2.0,1.0,1.0,1.0,0.0,1.0,HDBABCBCBFEA,True +513,4.0,5.0,8.0,7.0,6.0,8.0,11.0,4.0,GGHGHGDBCECECEGFHDABADEGGCGCECBFEGACFFFFBFCFHBAGGDDDD,False +514,20.0,26.0,19.0,15.0,24.0,22.0,24.0,21.0,FGFEFEFBHGHBEDHHHHEDCDEHEHCBFHGAFAFBFDCACAGGGGGGGHBBABFBFBCHGGBACGCGDFEEEEAEFFFFDECECFCBCBEAHCBADEDAGFDEDBBEBEHACAFAFABHEEDCFGHDAABEBEDGGHGHGDDFEFAHAHBGCGBGCCCABBHBAGCBHBE,False +515,22.0,23.0,26.0,33.0,16.0,30.0,25.0,23.0,GGGGCBEHCBCFEGGFADHDHCGDACCDBDGFCFHBHGAABFBAHAHDGDBDADACGCFDFGFDDHBGGGEBEBEFGFHBEFABEGCGCGHAHFHFHDBDBDCDCDCHFFFHFDFAGEGBABFEDBDCECBCDDHDBGECADEDEFFFFAFDFDECGHDFDFBCGFECHHAHAHGCBCDADAEAFCFCDHDABAHABC,False +516,17.0,13.0,13.0,12.0,15.0,20.0,10.0,20.0,FDFAGABHFHCEEAFCEGGBEBCBCBEBDHFACGHGCACACAHFHDBGFGDAEAEABFDEDHDFAFEBDHHHFHFHFHAHAHAEAFADCCFBBCEHFFFDGDGBEHHHHGCBEFEAEDFC,False +517,26.0,21.0,23.0,17.0,23.0,30.0,24.0,22.0,ABAEAEAEBGGGGGAECECEDFCEBAGHFHAEADCCGGGAGBEBEBEDCDFAFHFHGCCBHAFAFAFHFGBCDDFACGFGHDEEGEFEGBGFGADFCFCFCBAEABCDHHHCHFHFHBHAEFFFCFBECCCFFDFDBCHCADAFHBABDFDBBAHGGEAEHCGEGCDAGAHDGDFHFHFEBABEBH,False +518,7.0,13.0,9.0,12.0,7.0,6.0,7.0,5.0,CGCECBHDEBGBAFCDBDBDACEBDDGDGEGEFAFAFAHCFEHEDBCBDBDCDBBBDCHFBAGAGH,False +519,15.0,23.0,14.0,11.0,17.0,17.0,14.0,16.0,AFGEDCHBBBBBBGGECEFFBACACBCGCBHFAAABCCEEDDDHBBFBFBGEHEFDAEAFFFEHAGABAFHFBDBHHHBEBEACGCGCACDCHEEBEGGDGHGHGDDDCBGAEBEFEFAFHHHFHFB,False +520,18.0,12.0,17.0,12.0,18.0,12.0,16.0,36.0,EGEHCHDHDGDGCADAHAHFCEEBACEEEADAHHBCBEHEHEBAHCEEGCFEFAFABHBHGHDCGCGDHDHFHDHDHAHCHABCGCFBHHAHFHFHFCEHEAAHHBHGEAHHBFCCGBGFHAEAEGCHBHGDGDGAGFHHC,False +521,4.0,11.0,9.0,6.0,9.0,15.0,6.0,12.0,FFFCCHBHCFCBCBFDDGDGBFAGCFEFCHCGFBBBHCHDEDEAEBHBHGAEAFFBEGEHEHEHBHFFFFHD,False +522,17.0,10.0,12.0,14.0,22.0,13.0,17.0,18.0,EEEEDEABAGFEFEHGHBDAAABDBDAEHHAHGHGHDHAEABHHHHHBCGCFCFCDBAGACEEGCGAADGDHAFCFCEBEFDFEEACGHBEFEFEFEDCGFGHGEGDBAEGEDCHAHGDFDGC,False +523,0.0,4.0,3.0,2.0,1.0,0.0,4.0,2.0,DDEBCHCGBGCGBGBH,True +524,25.0,20.0,21.0,11.0,21.0,16.0,21.0,28.0,FGHGHEHEHBHFHFBFBDBEGDCHCGAEAFCDEAAACHEHEHBFFFFAAHCGGHGBGBHCHCDCGAGAGBHHHFDCDAEABBBCECBGGFACHCECEAFAGHFAEHGGEDEDEBHHACCCACBCHDGDGAAABAGFEBHAGBGCFEEDEAEAFBECHHAHBHB,False +525,5.0,5.0,3.0,6.0,5.0,16.0,3.0,8.0,DHFHFEFEADAGEGECBDFCBDDFHCHFAAAFEHHFBBBGDFFFFFFFHFH,True +526,1.0,0.0,1.0,1.0,2.0,0.0,4.0,6.0,HGHCHEHEGGHGDAH,True +527,14.0,26.0,15.0,11.0,16.0,18.0,25.0,17.0,BHFABADGFABCDGGECEBEFEDBDHGFCFDBDBCEFBFHAGBFEFGFHFHCHBHEHFHFHCHCEDBDBEGHGHGCBCBGDEEFCFBGBGBGBCBDBGAEAGBGAGECEAFGGGHGCCAFGGEAEDBHAGABAFAGHHCBBB,False +528,26.0,33.0,22.0,21.0,21.0,26.0,21.0,23.0,HDBFBDGDGHHEBFFCECFBABGGEBEGGAHEHABGBCCCABDFEFGFADACCGABDBFBADADBDAHAHBEGHFHBEGEBCBCBHAHABADCHBGCDEDEDHGGGGGCDBFFFFFAEECHCHCFEBEAADFBFBABDBGEEHEGEFCFCFEAEADCGFADHHFBDBAHAHACABABFBFCFHBHBHCDFGCD,False +529,19.0,28.0,16.0,26.0,16.0,17.0,19.0,17.0,ABADGCGBHDFFFGFGDGFBDGGFAFCGGFHHAAFFFEAAHAHCBCBABADDFFFABDBDBHGDACHCHGBBBBBGEDADAGCBEBHHEDBCBCBDEEGADABABADADCCBCBDFDFCBCHFEEEDEHHHGHBHDEECHGDGDBEEEDEDGDGCBBD,False +530,10.0,4.0,8.0,6.0,5.0,11.0,7.0,6.0,FFBFCDCGAGFEDCDBEGEGFCFCFCBAFDBHAHAHAGACAHAHEGDFCFADEGAFH,False +531,13.0,7.0,11.0,9.0,7.0,13.0,13.0,17.0,GCABEBFBAHHHGHGAAHCHBEBCDAFHFHBCDCDCDFGEGCHAHEHCHDFFFGFGCGAAAHGGGHFCECHHHGAAEADFBFDFDEDAGF,False +532,6.0,4.0,4.0,4.0,4.0,11.0,3.0,7.0,ABCDHFHFECEDADFGHAFCFCFBFBGADEHGBFHEHFHFAFA,False +533,14.0,30.0,24.0,27.0,22.0,23.0,21.0,29.0,CEBEDGCHDGAAABHEHGCGBFBEGDDDCDCHHDEGFHCEFBGBCCFBAEAGABEDFDCDCDHDHGFGHGCGDDFBBBBBDFDADCDGBFEFDBCFCFBDHDGFACAGFDFDEAECFBBHBHCACAHFDEHEHBDBGBHBFBEDCFEEHBHBCBCBHEFEFCHCHEAFHBHBHEHFGCAEGHGHGHGHED,False +534,7.0,14.0,11.0,10.0,12.0,6.0,11.0,7.0,ABADCBEGAGABDBHCECDBEHGCBCBCGCFCFHFHFBBCBGEGHGDGEGEDDDCDEDABAHCFEEAEFEBBGDEHBG,False +535,1.0,8.0,7.0,5.0,5.0,7.0,1.0,7.0,BHBGFHEDDFCBBBBHHHFEFHFCFCACBDBDEHEFECCCD,True +536,5.0,4.0,11.0,11.0,13.0,6.0,6.0,8.0,CDDDEBHHGHDFGCCACEDEDECEGEACACHEBFFEFEFGFGDGDHAEEEABCBHEDCDCHHDC,True +537,28.0,21.0,11.0,18.0,13.0,11.0,21.0,19.0,HGAGAGFDDHGEBDCGAAHGHEDBDFDEGAGHDECCAAAADDGBBCBHBHBHGCGCBBBFBFGABAGCHBGAFHFAACAGDFEFEGGBFHAADADFDADBBBDAEAFHGHEHEHAHAHAHAGEGDCDCHBABABECDGAEBE,False +538,3.0,5.0,4.0,4.0,5.0,2.0,1.0,6.0,HCHGHAFBEBEAEACDCHBEBFCEHBHDDD,False +539,6.0,6.0,7.0,4.0,9.0,4.0,6.0,1.0,CCAGDGDGEFBCACBCGDDBFEFCFEABABCEEEABAEGEGEH,False +540,4.0,1.0,2.0,4.0,0.0,6.0,5.0,0.0,FDDGAGFGCGAGAFFFBCDADF,True +541,9.0,14.0,13.0,6.0,8.0,6.0,10.0,5.0,CBCGEGEFEHAGEDBGEGAGHDCBCGAGAGHDFGAACBBDBDFFCFHFDACACBBEBECCCCHEACBBBBB,False +542,16.0,16.0,8.0,16.0,13.0,11.0,10.0,17.0,EAHAGFDCGCGDEHCHBAAADHDHEHEFBGBABFDAAADBDADADHDGEGCGHGBFAFEBBBBHFDFDEBEFAHEBDGFHCHCHGDFABABDHHHAEBEHEDEBCCF,False +543,21.0,26.0,17.0,27.0,29.0,23.0,26.0,18.0,GDEHHBFFAHDHDCBHBGEDBDGAGDHCEEEBFFACBBEDGFCFBEBECAFDDHBHDEFEFEFEGGCGBHFFCFEHBHEFBHBADAEAGAFBFGEGEGCGDEDEGCGCBDFDFDADABCFEBBBDBGGGFGCDCDCACFEDBGEGEGHABGEGEAAAACCHEBEDEHBABFGFHHEHADGDADADAD,False +544,22.0,22.0,21.0,19.0,23.0,23.0,21.0,20.0,CGDGDBCFDADCCGDBDHAHCHCEDFFGGGECECEAFAHCFDDEDAGCGCBDEDEAEHCHCEEECEFBFHDHGHGEGCHFEAEAEFFCFEDEABHHHGFBAGAGBDEGECECECHBHAHGBBFBGBDFDGAAFAFGBBCBGBFHEHCBDFFFHFBAAHBFBAAAFAGABDB,False +545,23.0,25.0,25.0,15.0,25.0,17.0,21.0,33.0,GAGAGEEHHHFHFHFHEHDCFHABBHBHBEBHFGBCCACACACGHBADHBECECEBABECCHCFEGHDCEBGGEBEBEFHHADCDCDFDHBHCAEEHEHFHGHGHFADCGFHCACACACBCEGDFHCABGDGEGFCDHGHAAAHBHBHBEBHBHAGABEEGEDEGFBFCGEDAGADDBBEAFCF,False +546,3.0,2.0,2.0,4.0,0.0,4.0,0.0,0.0,ADADAFCFDBBFCFD,True +547,13.0,21.0,3.0,11.0,13.0,5.0,12.0,11.0,GHBADHBHBGBEHDHEEFGHDHGFEDDDEGEAEDFAAGBBCBAGAGAEDEHBHBABABAGADBEBECEAEBBBBGBHBDFGCADBFBHG,False +548,25.0,24.0,22.0,17.0,28.0,18.0,39.0,21.0,CDCABDBHBGBGBGBCECBABGBGAHAHBFEEAEBGAGEHFACACDEGEGECHAEGEHFHFABEGHFHAHGHCDCEBEGDBFAFHGEGBGAGDBDBDBEFECHFHEBFGEGEGECAFABEBGBGHGFGEGCCCCHGFACGBHAHAECFGAEDHGHGDDDEAFADGDGDCAEGGACFBFAGEGACCEHDCDGGFG,False +549,3.0,2.0,4.0,4.0,5.0,8.0,5.0,2.0,HFEFGDGFBFDFEEEFEFGBGCCACDCAGAHFD,False +550,1.0,3.0,4.0,3.0,7.0,2.0,2.0,6.0,ECEBHBHGHBECEFDHAHECEDEDGCHF,True +551,16.0,22.0,21.0,26.0,28.0,20.0,19.0,21.0,EGEDEBEAEADDDCFCABGEFFHDBECHBBBBAHAFFCCDDDDDDHGHEFAAAAAGGBGFGBGCCHEHFBFHHDCDFFBFDGEGFCABBEBEBECDGFEECACDDBCFEDEHHDBDFHFHCHCEGGGEGEADCDCEGEFFHHGCCBCBDBEBEAEAEAGDFHCDGDHBHEHEH,False +552,4.0,5.0,6.0,11.0,3.0,11.0,11.0,5.0,GCCDFHFBDDEDECGCGDGHABDDGGGDHAHAFGFGEGFGFABDFHFCFDBDBFFC,True +553,5.0,13.0,12.0,7.0,6.0,1.0,8.0,8.0,BGDACECGDGCCCBCHCGCDBHHGBEAEAEFBCBEBDGCGDGCBABABEDCHHHHHBBDB,True +554,21.0,23.0,19.0,23.0,24.0,21.0,32.0,21.0,FAGAHAHFHGHBEEFGADABCBGBGFAHEDEFGFBHCECEHEHDGDEAAHGGGEGFFDFBCHGAGHCDGGGABDGDADHFEBHBHGGCACBCBCBGBCFADADGDEDACBGHEFDFHFHFBDDDDBHBGGGCDEFEGEGECHCBCBEBEBEFFAGBBFACECECDAEFECGAGEFDGGAADHDH,False +555,11.0,14.0,17.0,9.0,22.0,14.0,9.0,22.0,CGEEDCDADADBDBFFFHCAAEHHHEHEHAHEFFCFBGHHHFHCHDHEBGFGFBEECFCEEECGCGHEEEEADHBHAABCCACFCEDHCHCHBHBDBECGCEFFGFABBEBEGHAHBE,False +556,4.0,3.0,4.0,4.0,4.0,1.0,0.0,1.0,BABHECAAFBDCDEDEDECAC,True +557,11.0,15.0,15.0,16.0,14.0,18.0,14.0,14.0,BCBCBGDGCGEAHHEHGAFFCFHFCGAGACEBEBEBAFGCCDGBCEFDFDAEADDFDCEBFBFBEHDHEHEGEGBGHFHDDDDCCBGBCBHAHDEFFFGGCHBEAAAHFFDFDFDHC,False +558,5.0,2.0,3.0,3.0,1.0,2.0,3.0,2.0,DGDGACBFHFHAEACABACDG,False +559,29.0,26.0,17.0,17.0,20.0,26.0,24.0,23.0,DADCDFFHFAFACAFBDBACAGABFGFBHCHCFFEFEFGHGCBCAEGGGDBDBABFHFAEADDDEDEHAAGGDBHGFFFFCGAHBBGBGECEGEGEGEBEDCFFDFCCEAAFDHAEBFBFAHAGFHCCGBGBGBGAGABEDADHEBEHHAEFHAHABCBCHAEAFAEBHGHBBBAGDHHHHC,False +560,7.0,9.0,14.0,11.0,8.0,12.0,13.0,5.0,FCDCEFEFGHDAABACGCGCGDEBAHHBCCFCFGEGDBDBDBAFECDFDFEGGCAFABCFGFGEGHCDEDGDGFCBCBH,False +561,16.0,32.0,21.0,19.0,21.0,20.0,22.0,22.0,AFBGBGHGEDFAACDCDCEFEBCFCGHGHFDABABAHCCEAHBEDEDBDCCHGHEBEBEBCDEFGDGFBFEDHDHDBBBFFEGBGHEDGDFBGBACDGEBEBHBHCCGHGHGDGDGHGHBCAFHGHGFABAFAHAFCBCBFAHDHBBCBGFEBABCBCFCFEEBCFEDEAHBE,False +562,18.0,21.0,6.0,6.0,14.0,3.0,15.0,20.0,DGAAHCHBAFHBHBGCAEAEAHAEAHHHBCBGGEBDFAHAEAEBGAGAHDEGHAHBEAEGHGHBABHBHEDCGHGBEDGBGEGBGBABDBAEEHFHBCBCBHB,True +563,19.0,18.0,15.0,19.0,14.0,16.0,17.0,24.0,FAFAFABBHDCDCDFDCAABFCEDBBECDCDFFAGADBCHGGFHDHGHEECEGDADABEHHHHCHDHDFAHGFGFBDBCBFHAGABDBGBFDGGFCFCBHBHFHEHEHEGAGAHAGABAGABEECDCHHEBEDEHAGCGHDH,False +564,3.0,3.0,2.0,1.0,0.0,0.0,0.0,2.0,BABCBDAHCHA,True +565,8.0,12.0,12.0,9.0,13.0,13.0,12.0,17.0,BFBFEEHBFAFGGGCHDHDHGCDCGEHAHEEBBAEFGCGCHCFCFDBBBHCEBEHEHFGAGFFHFHABDGDFDFBHAHDHEAABCEGEGEDCHCHC,False +566,24.0,19.0,7.0,22.0,15.0,14.0,18.0,21.0,AEADAHECBGBFHGHDHAGDGHGBGBHFHBDDDHGHDHDADHDHAHDEDADGFEFGFBDBDFAAAAABEFDHHHEGBGAAEDEGEGAFAFHHBEEHCGBEADAEFFBFDFDBDBGBHAGBCBEFDHGCACBCBAAACAGE,False +567,18.0,34.0,25.0,23.0,26.0,29.0,16.0,24.0,CHFDFHBCBDBFBHEEAEABABCGAFDFDADADADBBBCBDBFCEEEFFAFDBDBGHDHBBBFFFDABFHGCABABABAHHHHDFBFEFHBCDCFCFBFEEGECFHEGEGBBDDHDEDHFHDHDFBAECCBHBEBHBCCCBDBEGHGCFCACEFAGEGEGCCFBFEHEHCGFECGFDAGFGHCCCEEEBEHAHDG,False +568,10.0,3.0,8.0,11.0,10.0,4.0,2.0,8.0,EGEDEHEHCDCEAEAEAFFEHCDDDCACHBHBDDDHAAACAEBFAGAHDCCFEDHD,True +569,16.0,11.0,9.0,12.0,15.0,17.0,17.0,12.0,EAEDEACHEAGBHHFFAGGDADADHBHAFFGDEDEHFBFCGBGFFDGHAEAFBCBEAECDADCGCGFGEGEGAGDEDBFFAFAFCBHAEAEGEGFGFDCHCGFBHBHBH,False +570,5.0,3.0,10.0,3.0,5.0,7.0,4.0,6.0,DADCHHGACACECHCFCFHDEGABAFFFFECECFGGHBCBCEH,False +571,19.0,19.0,10.0,25.0,20.0,11.0,12.0,21.0,EGEGEDDDADCBFBFCHCHGAGDHDHDADGHEDDDDHBHBHCADEEEDDHDBCEAABABFEEAEGHGHFEADDDCABHBHBHFHFEEEEFDCEEGCBCHGAEAGABFBHAHEHAFABHBFDDDBDBHAAFBBAGGCD,False +572,9.0,14.0,14.0,11.0,15.0,15.0,19.0,10.0,EFEAEGGGDGDADFHFGFBFBFGDGBBEBEADHGCBCBCGCECGFDCBCBFDFGEDBDHCAFEFEBGCHAFGFGEEHBGCGCEEEBHCHBADCCGGHAHADAGFHFE,False +573,4.0,10.0,13.0,15.0,11.0,8.0,6.0,4.0,AFCCGEEDEBEBAHAHADFBCBCBEFDGHBEGEFFBFDDBCECDCDCECEDDDDDGDCDCEBBGDHFCCGF,True +574,15.0,27.0,18.0,27.0,33.0,20.0,18.0,26.0,FACGCDEDBABABADHDBEFECGDFHHEBCBCGHHAEBHBHGDADGDGDEEEDEBCBDBEAFHFEDGDGDBCHEAADEDEAEDHCHAFDEDHDACHBHBHEHECFBABHDEEEFEGBGDDHGFBFBFCFCEBEBFFCECEGEFEDGDCBGEGHFCECEBGBHBHDHCEFFFBGBHHHEFAAHDG,False +575,16.0,17.0,13.0,14.0,16.0,19.0,22.0,14.0,HBCFCFDFEGAGAHHGEGBGDGFHEHAFBDBDCHCHGFDEDEFHFBEBHBHBEBHBDFDEDEHEGEFFACACGFHADGFADGBAEADAFBCHEFFBEBGBGBACGGFGFAABGGDGFCCACAEAECDGGGC,False +576,21.0,18.0,24.0,12.0,15.0,14.0,8.0,14.0,CDCDFBACHGHECECEDECECHHAHBGFAAHAGFEBCHAGBBBABCBADCFEGABABCGCFAFEBHAHDHECACHHFCBBBEBECFCFAFAHAFCGDFDFDBEBDCACACADBDEHEFEDGCACAC,False +577,11.0,6.0,10.0,4.0,4.0,6.0,15.0,11.0,HHGHAHGDGCEBABABGCHCGCECHCACHDFBABFHFCAHAHFFBFGGGGGGGACAGECDGAADEHG,True +578,13.0,11.0,13.0,13.0,10.0,10.0,11.0,13.0,HDHDFAHCHGEAAAACGBEEHHDEEEDADCDCACACDGDBDBCFEAGHCFCABFBFGCEFBHHHHGBGCGCGEEHAHFBFDDBDBCGDGAFAFB,False +579,16.0,20.0,17.0,10.0,16.0,13.0,17.0,18.0,HBHCDAHECCCCBHGEFCBCGFFAFACBDGDCHBHBCBEBEDGDFEHGHBHECCCEFAGAEHDGDGHBFAFAGAGBGBGBEECCAFAFDBBHFECBGHCHBHDHBHBAEEEAEHEAGAGFGFGDABA,False +580,19.0,23.0,27.0,23.0,24.0,28.0,24.0,26.0,FGFGCHDADGDHFFDCDABFFFFBCEAECEHADCDFDFABAHABDEDBAHCCCHBAAFAEGEGFGHDHGHBHGHDCFCFCADEFEHBAEEFGCDCGGGGGEHFGCGCFFHFHGHBCBDBDCCCGEBEHFBFCFEECFGHGHFHCAEBEBEGHGHFEFDCHCBCBGBDBEAAABCCEAFBHBHDHEEGABDDDED,False +581,14.0,16.0,19.0,20.0,20.0,20.0,13.0,20.0,ACAFBEAHDHEHBHCABBCHFHCEEGCHHFCDCBBEBHFABGDHFHFHBHBHBGDDDCFFHFBFGFECDCEAGAGACCCGCDCDEDEDADADFFFAFAGHCDAGHFEEGHCEEEHECECEGEFDFEEGDDDGDBBFBFBADH,False +582,13.0,15.0,13.0,20.0,21.0,19.0,19.0,16.0,EGGAGAHBFFEFEHECDCFCBGHFFGAGAGEGCGAGBFCFDDDEBEHEHCFBDDDDDDADAFAHHCFDEDBFFFFHAGCBDAFBHBEDGFGCBCBGEGEDCDCDCFHEHGHBDGEHABEGAGHFEDAHEEEEEBHB,False +583,6.0,13.0,10.0,9.0,17.0,8.0,10.0,9.0,FHFGBBBBABCCDHBEDHGFDEHCGCBEBEHCFCFBFBDBACFHGHGEEECECEDEDEHEDGCAEADFDGEAEGGGEBABEH,False +584,18.0,27.0,27.0,16.0,19.0,28.0,14.0,16.0,FHFCFAFHHBEBFBDCHBGEDBAFFCBHBCFGFGCGCEEEDEDBABGEFBGBAFAFHEGCGCDCDBHHCHAHAHGCECAHFHFDEGHBBCACABABFBFBFAFCDCDBABEBECFFGBECCCHCFAFDDDDFDBECEAEDBFCDCEFGFABABCCGEHCABGFEF,False +585,26.0,16.0,22.0,22.0,20.0,21.0,22.0,26.0,FHDHDHFCEBBDBAAAAGFGCBEDHDHGHAEAECDCBEBHCHAHGGFDAEFCFHHHEECCCDCDCDHAHABBECACADAHCDCDFBBEDAAGAFFHCEEEAFAFGFCECEFACAEAFFHEGFHCAGECFFGBGFGDBDBABAGGGGGHHHAHDDDHHHAHDGEGFGBGBFCEDGD,False +586,8.0,5.0,12.0,4.0,4.0,13.0,13.0,7.0,DFDCCCCCCFEBEBDFFAFGCGCBFDFBAAFHGHGCGAAHGFAFGFGCGAGBCHFHCGGHFHEAEG,True +587,4.0,3.0,2.0,3.0,2.0,5.0,3.0,1.0,BGGGDBDHDFCAEAFCFBFEFAA,False +588,7.0,14.0,10.0,16.0,16.0,9.0,9.0,13.0,BCDFHCGFGAEFFFDDBBHBFBHHGAEDDFDEHEGEGEHADFEEHEGEDEDEDEHHBHBDBHBDCDCDBBFBABACACEHECGHEBDGDCCCAG,False +589,41.0,28.0,27.0,20.0,22.0,14.0,25.0,23.0,EDEHHHEACAEAEGECBBHBHBEFAFEBAFHHGHAHACAGBDBEGCDEHAHADACACGEDCCCFBBBBBFAADACAGECDFHGDDBDCDCECDABAFCBEGEDFCGBGDHACABGHECBGGCDCGEFEAGCGDAAABABABDHGEAHBGAEHGBGBFCFCFEFBHGHBAAAAHABABADAGACACGCACHDHDHAFAGEG,False +590,25.0,17.0,16.0,9.0,20.0,24.0,14.0,17.0,HDFDEGEFBBECCBDBABFFAFDFCECBAGAEABGFHCACAFAFAFHEHEHECFCHEHEHECGBDBAFEBCFAFCFAGGCFCABHGABFFEGAHAGAGCHHEHFDFBEBCBEFAFAHAEFEAAHAHBHBGDGDGCEADAGEF,False +591,17.0,13.0,25.0,18.0,20.0,19.0,18.0,19.0,ADCFCHDBAEHEHEFEACAFAFDFEFECEGADHDHEBCCCCEHHGBDBDGCCFBGDDCGABAEAEDEAFAFCGCFHFEGAGDGFHCGCEHEAGCHCBDEDCFEDHCBEBFBAGEGAHCHCBCBAHACDBDCDCHFHEGFGFGDGHGFFH,False +592,4.0,14.0,3.0,5.0,17.0,15.0,9.0,5.0,HGFEEHBHFFEFHFEGBABFBGDFBBEFEDGDEDECEBEFEAEBBBBEBFAHAGFDFEFEBGCGFGBGFECE,True +593,13.0,8.0,10.0,11.0,8.0,10.0,5.0,8.0,EAEADADGFGCDDFBFHHGADABAFHHBAEABHHGBCFCFDFAFDHDCDCBFBCCCBCEEEAEAEFDAHACDG,False +594,16.0,13.0,15.0,7.0,3.0,9.0,20.0,22.0,BGBGCGHHHEHGAAFGCGBDFAFBHCHBDBCCCFDAHHBGBAAABHHHGHGBABABCCCCCDGHGHCHAHGEGDBFGFGCGAHAGFCHGGGAHAHCHFEDHDAAF,True +595,12.0,10.0,9.0,7.0,8.0,10.0,12.0,10.0,AEFDFGFGABHBHBACAHFFEECEFDFGBCAABBCDCGEBEBHHHHFBAEADGDGHGDGDCACGCACAEFHAHGGGBF,False +596,12.0,14.0,7.0,5.0,7.0,8.0,16.0,11.0,DBGBABFCGCGEGBGCHCABEEHGGGHGHFBEBABFBFBGGGGFDFCGABABAFAHHHHBEAAADDHCFEHAHBGACDGE,False +597,12.0,31.0,25.0,23.0,29.0,22.0,19.0,20.0,GBCAEDEGEDHCHGFBEGCCDCGAFBFAFEGBBDBDBDGGCEHEHFHDCDCDEDFHHBGBGCHABGCGCFHFDEBCDHDAABFBGBHDCDCEHEBFBFEFBFHEHEGEBBDBEBABCDGDBHBDFDFDACCEFBCBFHFGCEAEDFCCDCFGGEEEAEAFAFBHBEBCBCHEHCHGEEEBE,False +598,3.0,2.0,2.0,2.0,0.0,4.0,2.0,0.0,DADAGFCFCBGAFBF,True +599,18.0,18.0,17.0,19.0,19.0,25.0,24.0,26.0,EFEFADADEGEGBBHHABBHCCGAFDHDFEHHHHHHGAAADGHFHGGGGDEACHCHCFCGEGEFABEEGEHFCFDFEBGAHCHGFGFGFGFDDHEFCFEBDFEACAFHCHFBADGCGBADGDAFCHCHDDDFDFHCHBHEEEBEBGBABABABCBFFHFDGCGBGD,False +600,18.0,13.0,8.0,18.0,9.0,20.0,11.0,10.0,FAHEFAFAHDGGGGHCBEGABABFEFAAGAGAGAGAGBHBHCFFDHBHDEDEDABCFCEDEBEFADDBFFCFHFAAGDDDDDDFFFFHADFFFBBBCDADCCADHBE,False +601,28.0,16.0,18.0,22.0,25.0,31.0,31.0,28.0,DHDHCHCEGGGGGGHGHGABHGABAGDGEGBACHDHBGADFBHGAGFGDDADGEAEACHBBFFHFEGEFFAFAFGFEFAGADDFAFCFGHBFFEDBACABFHFCCCEEDFDCDAAHFHEHDDEDGHEFCAHFFBCGCGCACABAEAEHDHFHFHFCEDEDGAGAEEEEEFDAGGGHGHFHAGEBHBAEFCFBFCEHBHD,False +602,19.0,22.0,22.0,6.0,18.0,28.0,18.0,32.0,BEHEHCBFBFGAGFFFHEEGEFFGCHCHFABHHCCBFHFABBEBCACAEAFHFABHCHGBBAHEEEEAHAHBHECACAHEHEHCGBFFHFGAGCCBCBEFEGHDDGDHFHCDAHHHHDAFBFAFHFHGHGACCCACBHBGBGBCFGFHFHFGFGFAEBCGCBDEF,False +603,6.0,3.0,3.0,0.0,3.0,1.0,2.0,3.0,AAAAHHHEAEBFCEGAGCBCB,True +604,20.0,12.0,4.0,14.0,4.0,16.0,10.0,13.0,BHADGGGBAFFHAEDBAFGFCFHFHDHBHBGFFHADDEHFFBFGHAHAHABACADFFAAGADAGAGACADDEFEFDADAHBGBABDBDBDCHF,True +605,13.0,12.0,3.0,10.0,9.0,12.0,19.0,5.0,BFBFCDGDBDAGAFCHBBBDHGADCEAABAGFGFGEGEGDGFAFEGBGAGEFFGFGEDADBBGAGAGEFEBBHGHGEDDAFAH,True +606,25.0,22.0,15.0,23.0,20.0,14.0,29.0,17.0,ABABABGDEFEFEHBAAAFDDBDGDGAGEEBHFFCAHAGABACACHEGDGDFDHGGFFHFBEDECFGHCBAGDGCHBGBGCGFDADECEBEAEADAFEBEAEFCBCBCBHBABGBHAHAGAGDDEEEHBCEADGDGDHHFDGABDBDGGCGCADGGHHDHGGEGC,False +607,7.0,12.0,19.0,9.0,3.0,6.0,12.0,7.0,CHGGCADECECGBGCGCEHDAFACDBGGFABCBCBCBCBFBCGCBCBCBFHADACADHDCGGGDFCHGFCHDHDB,True +608,15.0,15.0,12.0,14.0,12.0,4.0,21.0,15.0,BGBEFEGDBCGCGHHEGCFAGEBFGHBCCEGAHACGBDBGBHAHGHGHEHEHACABADADAHACBGDAEHGHBDBDBEBAAAFCGCGDEDCDEDHDAGHGDGBGEGDC,False +609,11.0,19.0,6.0,5.0,9.0,14.0,11.0,10.0,BBBBGBFBFBABDHAHFBBAHEHFCAHGGDGDFCBCFCGAHBDBGBGFGHAHGBEEAFFFBFEFEACACEEGEAEDGFHAHBBBF,False +610,7.0,6.0,1.0,2.0,7.0,8.0,15.0,3.0,GGGGGDGFBAEAEBFHGHDFAGBEFEFGFGBHAGAGBCEAEGBGEGAFF,True +611,9.0,11.0,18.0,12.0,13.0,14.0,18.0,18.0,DABAEGBGEGEGEGFDHCGCHAHFHFCCCCHHGADFBGEHAHEHECFHEHEAGABDGEBCBFFFGDGBGACHHHDHCFCDCHHGDCHCBCDCGCBBDADGGGEDECBFFFFEF,False +612,1.0,6.0,5.0,8.0,3.0,4.0,3.0,4.0,BEBEBGBFBFDDCHBDFCHDGACHFHGDCDCDED,True +613,5.0,7.0,4.0,9.0,3.0,12.0,4.0,8.0,DEEHBFGFCHBHDHFAGDBDHDFCFEBHHHBFBABAGAGDFDCDFFFFCFDA,True +614,5.0,4.0,10.0,9.0,2.0,6.0,6.0,7.0,GCBCBCGGBFHHCFCHHDDDDCBGAEACACFDADCCAFHFHDHDEDGFG,False +615,20.0,20.0,21.0,19.0,32.0,21.0,14.0,26.0,FCCGGEHECEDEDBBECHCHCFGBEHECCCCCHCGCDCDEHAGCECEDDBEBABABEBEAAAAHAHEFAFHFEFBFBFAFGEEEAEHEBGHEHDBCBDAAEFFHCGFHHHGCEAGDBEHEFEGDFBFAHHDBCHFFBEGEGFHECEADADADBHFHAHDDFDFHEAEBDBDGH,False +616,4.0,1.0,4.0,5.0,3.0,3.0,4.0,3.0,AGAHCHBGDFDCHEDEDEFCFCDAGAG,False +617,14.0,17.0,16.0,17.0,18.0,16.0,11.0,15.0,EFEFHFABEBEGEAEBEAECBDHFEEGEGBGDHHHHHBHBHBHAFAHDBFHABDDFDHBGDECECEFEFGDABAFAFABDHFBFCGCGBEFCDCEADDDFACAHDCCGDDCBCGCFCABECGCD,False +618,29.0,30.0,26.0,14.0,18.0,25.0,13.0,17.0,HACCBHBFAFBFBFHFCBAAGAEBEFDDBDAAACACACEEDDAEFGBGFEFCABAGAGAGFGCHCAGFBBDFHAABFCFCFDHEHCFBFBHADBBBBHDDBCFABBEBFBADAEBCBHBHFHCBDDHCHGHCACAGAGDFCFEAEBECECECFCECECGHEBAFAEAGHBCF,False +619,31.0,22.0,24.0,19.0,30.0,25.0,19.0,29.0,CFHEHCGFFACEHBDEEGGACFCACAGAHAEAFDCGBACEFGAECCAGHBHBDBAEAGFBABAGACAHHHAHCHCDCDAGGGAHAEAEDGGCEHFHFHFDGBHBCEHEDEFEFEFEAADACHFBDBDBDBFBFAEHFHBHEHEGEDEDCCEBFBFCFCAHDBFEAEFEACAFADEBEHHDEGEAHBHCHDBGBCDHFGF,False +620,18.0,17.0,15.0,24.0,21.0,15.0,18.0,13.0,ECDGDBDGDGDEAEBEBCFGFGAGAGHCDEHEHBGGGFEAAFBBDFHCDCEEEEGAGAGEDFDHDHAFAFHEHDADADBDECACEDDBHFEGECADDCFHBCBCHCDDFDGBBBEAECEDEFABAHCHGDABFBFGFCBGA,False +621,0.0,2.0,1.0,1.0,4.0,1.0,0.0,1.0,FEEDEBEBHC,True +622,14.0,20.0,14.0,20.0,27.0,29.0,12.0,26.0,CDCACEHFHFHBHEFEDEBBFFFFBFECHHAHEHEDGDEEBFHFHAACEDECCCCEFEHAHBHDHFHFAFABEEEGEGEBDAHEEEEFHDDDGDEDABHBAFGFEHABFBABDBFFFHFCFHFBGCABBGBHFHFDDAHGFEFEDHCHDEBGGGBCDDDCGF,False +623,16.0,25.0,17.0,19.0,21.0,19.0,21.0,15.0,BFDFDFGBGDHBHEDCACFCEHEDEBCFDEDADBDACADDEGEGHAHBHFEBCCCAHEHEBEBAAAAGCFCFGFBEEEHBHEHGBDBDAGAEAGBDBGFEFGBCBCFGEGBGHDHGCCAADCDCBFBAGGFGEHDFBEBFBFDFCFHBGGGEB,False +624,23.0,27.0,21.0,27.0,12.0,19.0,33.0,26.0,DHAGAGFBFCCHHGGBCBFDFACGBGBGHCABACAHFHCDCDGFGFCFGFCAEGHGABABEDEDHFHFDFBGHGEGHAHBHCDAGAGAGBBAEAFGCACBFBDDHGHBHDGDGBGDAAAAEBBGBDBDCACFCHCBDBCCCBGFFHDHDHEGEDEHHDDDHBGBHDFFEBDDEEGGGGAGHCHDBAGD,False +625,17.0,22.0,27.0,7.0,24.0,19.0,26.0,18.0,GHECEGFGAGCBEEGBGHGBEBEAEFGFAFCFHGGGGEEECBFBDGGCGCEDGFBHBCBCBCAGABEGEAEABFFFBFBFHEGFGACAEFDBCBCAGAGAGFFCCBEHCCBCBDHCBEHCHCACEBFBCGDAHFCECEDACAEHHHHHDAFGHCHCEGEH,False +626,21.0,20.0,18.0,14.0,19.0,24.0,20.0,19.0,FGFGDBFGAAHHDABADDECCHFBGCEEHGHGHGAFHCHAHBCBFAFAFABBBABADDGEBBFCFCFCFCBCDCDHFAGGHGHGAGEHBFAFCHHEGEFBHDHAHAEDGAGAGEGCDEHECCCBBBAFFFEFDADBBEDEGCFBFCGAEEEEFEF,False +627,22.0,20.0,15.0,21.0,16.0,16.0,15.0,16.0,GBGEFDACFGFGHBHECCFAAAEEGBCHCBCFADHDHDBDBDFDADABAEDFBADACBCFCFEHGCEFEAEBHDHDFDEEBBHBGAGDGAEAEGGHAHDDDDFDGBBBAAAABDHGHFAFECCCECHBDBCBFEFGAGAHH,False +628,7.0,15.0,8.0,13.0,14.0,12.0,11.0,8.0,DEDBDHFHDCDCBBBCBDBFBFCGHGAGEFAFAEADBFBGBGHGDCFADBDFEFEDECEFHHCBEAGGGDEBECEABBGHGFDHEEFE,False +629,1.0,3.0,3.0,8.0,6.0,2.0,4.0,5.0,HEHDHDHDEFBGBGDDCDHBEDECGCEEFGAD,True +630,11.0,10.0,7.0,6.0,8.0,14.0,8.0,5.0,CAHAHABFCFCACFCAHAGDBCEGHFHEBDFAGAGABBBEBCFEFEFBFAFBDEDEGGDFDABFFEFGG,False +631,14.0,11.0,20.0,21.0,13.0,15.0,14.0,16.0,HCFAAHBFCFAFHFGDHFCFBBBEBEAEAEHEHGDDBHHHFHDCDEGECFHFDFDADACADHGEDADHDHDCDCGADDECEAGBBCECDGGCGCABAHFGCDCGFBHBDCDGAGCCCDCGEFEF,False +632,4.0,8.0,5.0,12.0,1.0,8.0,6.0,3.0,CAHAEDBCCFGDBDFFBFBHDDDDDADCGBGBCFAGDGFGFHDBDBF,True +633,3.0,4.0,7.0,2.0,2.0,6.0,5.0,5.0,CBCECACAFEFDAHBCGFGFBHCHDHCHGGFBFG,True +634,15.0,14.0,8.0,23.0,21.0,16.0,17.0,8.0,GDDDADADACBFGFGFAFACADAEEBEBFCGBFHFHGEDDDFCGABCBDHDHEEFHAHGEFDFEFBFAGAFEGDGDGBGDEDEBHBDCEEEEGEBCDDEAECDDDEGGGAFAEBFBGHEDAB,False +635,16.0,23.0,27.0,12.0,33.0,22.0,20.0,34.0,HEHACECAHFBGBEBHHHHFFCECEHEAEGDGDHAHBFFFFFFFGABCEFEBECECHABGCGFHEEEEEEGBCAHEHCHDFBGBCBCBHHGFBHDHCHEHEHCFCGCGEFHHHCDGDEDECBCAFEFAGHDCABHDAEACCHGHFBBHDEAGBGAFDDGCACEFEFEHEHEBEGCCEGBGBCAHBHB,False +636,18.0,21.0,19.0,22.0,14.0,15.0,21.0,26.0,GHABCDDDAGGFFEFDFHBACHDHDECGBFBFAAGECECDAFBHCDCEBGBAAAGHHEHEHEHEBAFDFCACECECEHHHCHDHAHAHCDBDGGGDHDBCCFCGHHHGDDDBEBFCFDGAFBFBDBDBGBGBABHHCHGHGDBEGAAHDCGAGBGF,False +637,7.0,11.0,15.0,9.0,7.0,9.0,10.0,13.0,DAFBFHGDGAGCDCDGHBCECFCGCDEDHDHBHBFBEGEHDADBBBBGFHHAECHGHGHBFCFAACCCFFHGACHCBCECE,False +638,23.0,18.0,27.0,21.0,18.0,14.0,17.0,30.0,DEDCHCBFEAEAEABAHGDGDADEBEHCFDGGCCCCDCBFGFCCHDHDHFBABDHEHAHFHCAFAEADHDHCHEDACCGCGCGCBAFHHHECDDDBGHHHCHBHAHECFBBGBDBFHAHGHCDGHGCGCBBBGBABFGCGAEEDFDAEHFHDHEEACAEFEACHCAAA,False +639,8.0,5.0,5.0,6.0,7.0,4.0,6.0,5.0,FGEBDBDBGHGDGCAHAHCDAGAFAFBEBEGEFDCHAEECEDACAH,False +640,25.0,30.0,19.0,18.0,18.0,25.0,21.0,28.0,DBGBFBFHFHCAFAFACGCHCHEHEGFGADHHFEAEGEGHGEAEBDADHBABDGGGGHBHDDGAEBDFCGCFFGACDHBHFHCHFAGHEDACAHBDDDAHHEBEBABACAGBDEDGHBHFHFCGCDFBFBFAHGCBDDCBAEAEFCABABACACEFHFBAEHEGBGBHBFFHBEBFBFBFHCBC,False +641,10.0,7.0,19.0,15.0,18.0,26.0,16.0,17.0,EBEBEADCFGFGAADCEFHCAEDEAEFBHEHDGDGDBHCGCFHFHCHFEFGFGCECFCGCEDAFEGDFCAEADCFEFHHHFDFGFGAGDGDFHHGACFBHDHCGFGFCHCHCHCDEECFFFFEBEBFD,False +642,17.0,19.0,31.0,20.0,20.0,27.0,31.0,22.0,EFGFHEBFAHAHFHGCFCFGFHFBFDHDAGAGBECCHCBGBFEABDEGEGFCBDDFEFADADBFEGEBBAEHEHAHAFGCGCGCBCBFGFCACHCECGCBCAGFHDBDCAFGCGCGCGCDDDCDGDGFBHGFFAHCFCFHECDGDBECCCDCEGEFBFEHHGAGCGDHAHGHEFDHAGBGBGHDECE,False +643,10.0,16.0,8.0,13.0,16.0,18.0,19.0,19.0,DBDFCEGABABHBFGAHEGFFDHCFCFBDHHACAFECHHHHGFGBEHEGEGEGFGBBDBFEFHFCEDECFAAGFGFEBAGHEHEHEGDBDFDFBEBDBDFDBGEHCAAGHGHGBGHGHD,False +644,23.0,23.0,24.0,17.0,10.0,17.0,18.0,14.0,BGGGGGEGBACCECHCHCACDBAEFEFHAHACFGGADDCDCDCDGHGCBHBAAFGFGFABBBBFBHGFAAADADCDEACDEACBHEEFCCHCHAFBCHGEGBFDFHEBBHBDBCHDBDBGFCFBDCGFGFACABBBAAAAAFDCDC,False +645,19.0,20.0,19.0,12.0,21.0,19.0,19.0,26.0,BCHEHEABABAHAHDHBEDEAEGECEBECAHDGCFEFCHHAHDHDHFBDACABGCEBHBCFHGCCCAEEDAACABBHGHGHFHBEBHDECEBDBCBFEFHHHGHGHGHFHFBDGEGACEFDFHFEFCGGGAEFDFGCGABFFCFCGBGAGFBAEA,False +646,24.0,19.0,25.0,16.0,26.0,22.0,27.0,28.0,DADGFHCDDBDHDHGGAEECHHHFCAGACFCFEDCCECEGFBFBCBGEHEACBCBGGHGAGFHCGCGEFEDAHAHFHEBBBHHAAEAECBGAAFBGBHBHAAFEEAECEGHGFCDCHHHHBDFGFGFGBEAFHFDAHAHCBCEHGHGFCDGDGCGEFABDBFBAAAHADEDEGCGHECEFEFECECG,False +647,19.0,19.0,11.0,23.0,12.0,13.0,15.0,22.0,FGFAADEGEAEADGDFHAHBHDGGGHDFBHBDDGDCDHBHBHEHECEDBDBEBHHDHEABCCGFAHGGEADAGFDAHEHDHDCDGDHHEHFFFGEGBDCACACDFDHBBBBDCGAAFAHABABACACFDFBBHB,False +648,14.0,18.0,21.0,17.0,4.0,13.0,14.0,14.0,HDCCBGAGBGFGFHCCACHCGCBCBEDEBCBDBHFCFCFGAGACBGFDFBHBADAGHCHBHFCACDFDBABAEGCHHDBDCFBECGCGBDAFFGHDBDBDADADACFDADCHHGH,False +649,18.0,10.0,20.0,21.0,15.0,23.0,20.0,19.0,CDCFFDAABAFGFDBHFHGADADAHGHGBDFCHHHCDCHAHADCDGDGDGCEFGFCECFCFCGCAAAAEAEDBDBFFHHHFECECGGEGAABHECFHDEDGHGAEADFFHGDGDGEEBDCFGEHFCGCECEDDFFFFBFBCBHHAG,False +650,2.0,8.0,12.0,4.0,7.0,2.0,3.0,2.0,BECADGCCCCCBCBCBDGGFECECDBDBHECEFABHBCEE,True +651,23.0,17.0,14.0,13.0,18.0,7.0,9.0,12.0,HGFCACACFCDEEAGBGBADADABCGDAEADGDBACFHBEDAABHBHGHCAAEBECECACEDECEGFGAAHABAEAHDHABABADEBCFCFBEEEHEBFBAEHEHDCDBGBHD,False +652,9.0,5.0,7.0,3.0,3.0,4.0,7.0,7.0,FHAHAGGGGHGCGCEHEAFAFCHDECHBABCFGBHBACDCDAABA,False +653,17.0,14.0,10.0,12.0,16.0,15.0,12.0,13.0,FFDCCCGHBHEFBAEAHDFFFHBBBBGAFABABAEADAEFCBDEEHFDACHCHDAFCFEDGBCBCBEBEGGGCHHDDAGAEAEDEDEBEHDHAHEFGFGFGHGAAEAFG,False +654,18.0,23.0,28.0,27.0,18.0,13.0,30.0,25.0,CGCBCACGBGHACACADFEBGBCAEHBDBCHAEDGDFDCCAEHDGDFDFAFBGBGEDCFBFBFDAHGCCCBGBHEHAHGGGCECEHEAGCGDGDHBBDGCECHAHDFDGEGAGDGEADHCACBGBCHAHAGBGHHCHCHGEBEAEDECHBGBGDGFGEGHCHBDDDCDHDFDHCFEHDBDBF,False +655,15.0,11.0,8.0,7.0,7.0,6.0,7.0,13.0,EFAFACBEEDCAHAHGEAEFFHBHBFBFHGAAHGHGAGDCBHHHABDBEBAGAGDDDADHBCBEACHCACACHB,False +656,23.0,17.0,14.0,15.0,23.0,23.0,21.0,14.0,DBBBEEGCGFABAGAHAHFDEEHECBHBFBEAEADGDACGFGFCFDFGFGFGBEBEDEHHCFEHAHAFAHEBABEDEFGFGBGAAECFCHCEAGDGDCBCAFHFDFDFCFEEEEECFDBGGGAAADBGBHDAGEEBHDAAAHFGCGFAFC,False +657,22.0,13.0,20.0,11.0,19.0,20.0,13.0,19.0,AAAEEECFGGCCCDBDAFHFAFCCBAAHBBBEBFBAGCGEGHCAEACDCEADBDEAFCDGECEGGAGABAHAEBHHHHHCFCFEHCHFHGHCHCFAFDFDFDHBEGEFFFFAEAECEDEDHFGABFEGCHCHAHABF,False +658,13.0,8.0,9.0,8.0,6.0,14.0,16.0,11.0,DFDAACADGHGFECCGBFFFHEAAFACAGFHCGCFAFDFBBHHFGAGABABAGEFEFGDEBFBDBGACHCHCHGDGHGHGEGDGH,False +659,24.0,22.0,11.0,20.0,12.0,19.0,20.0,10.0,ECECBBAAAFHDHDHCBGFGFACABAGGHADBEAFFDFDFDEGCGCBBBFAGABBEDGGAGFDAGHGDDAEABBGBHDGEBFBHDFGCBCBEBFDFDADADBBFEHEFEFDFHFEGDCDCDCGBGAAAAAGAFAHBGA,False +660,9.0,8.0,11.0,8.0,16.0,14.0,26.0,11.0,FEGEHCHBGBGEGHGHGEGHDEBHAFACGDGFGACHHGAFCGGFEHDFDEEGBGBGFGFGCCECFAFDFDHBGDAAHAGEGDGEGFGAGEBCCCCBEEGEFEF,False +661,21.0,16.0,26.0,12.0,16.0,24.0,13.0,16.0,AHBFGAHHBCBABABCCGBEFACECGHGFDAHHCCECFFFDFAHACACBCBGBDFEFEHEDACAEDEDEGEGDGBBBGCGAHACACEFAFDFAFBDACAFFHFCFCAGEGBFDFBFEGCFCBCFHACADDCHFHFCECEHHHCE,False +662,19.0,21.0,19.0,34.0,20.0,23.0,22.0,19.0,AFAFBGBGBABGDDADCFCECGGEAEACHDHDEFCFDFDECHHGDEDEGGFEBBBBBEFEDDFAHCBEDDBACDCDAHAHGHDCFCFDFEFEDHCHDDADBGCABDHEBBFBDCDHDEDEABDHEBFBCEAGGHFHEAGFGFGCGDGFGDGAGAGABFBFDDHDCDHHGHECDCFAF,False +663,30.0,32.0,21.0,26.0,25.0,15.0,23.0,18.0,GBDHGHGHGBGFGABAEEDBCBCAHAEEDFDADEGCCCGHDBBBEDHGGFCBBHEAACDBGAGBGFEAAAAAABADGGBGCDCFCFDFCBHAHBBBHBHGDBDEHBHBHBEAABABDDEAEDFDEBEBECEGEFAFCFCADEGCGBABABFBCEADAEGEGDCDGBFHAEAEFCDDHEHAHFDCDEDCAC,False +664,14.0,12.0,16.0,18.0,20.0,25.0,19.0,23.0,GFFDFGFDEAHBCEEHCFEEEABFGFGHGAGAGCGCFDBDBDEDEABABDBHFCFHDGAGEHEHEGDCDCFAAGAEEHFGFEDCHFHGGEHDDGBADDGHFHEHEHECFCFCDCAEFFFGFGCBHHCCFCFBFHFHEDADHHHHABB,False +665,1.0,1.0,5.0,0.0,2.0,0.0,2.0,0.0,CCCBGGAECEC,True +666,13.0,18.0,8.0,9.0,12.0,13.0,18.0,15.0,FADABCFAFAFGFGFBCBGGGFGDCDCABDHDAEHEDGDGEFFHCGEHHFHBGAGAHEGEGABFCGBGEEBEHFHBHBHBHBFBHCABBHGEEDCDBABABHGGAE,False +667,12.0,9.0,6.0,10.0,3.0,13.0,8.0,9.0,CBCHGHFADHGAGBCFDFAADDFCFHDAAAAAFCFEAAFADCDGDGHFHFHGBFBFBEBHGHGBBDFDEB,False +668,25.0,23.0,24.0,17.0,11.0,21.0,16.0,12.0,GDAFFFFHBBGCACGCECBHAEDBBFFFBCBCACACGBABEBEDDBFAHBHDAGAGBGBGAGBGAGEDBAFCCDCGAGHCDADACAEDFHACBEAACFDDBDBHBDBDFFFCFCFCFCAAAEDHFAFHCHCACHCGAGFFCEEBEBGDH,False +669,3.0,6.0,1.0,5.0,4.0,4.0,3.0,1.0,EABGBEBGBFBGDFDFDADEDBFHEAC,True +670,5.0,9.0,11.0,15.0,8.0,21.0,12.0,11.0,DFDCHCFFDHHAHACGGFBDBDCDCDAHEFFFHBDBDBEECFGDGHGBFCDADABHBHGGEGCCFFFFFDFHEBGCEFDFGFEFEHDGFGFC,False +671,9.0,14.0,11.0,13.0,12.0,14.0,11.0,23.0,HDHCHCFCFCHCFCDADADEHFHBAEGFGHCEDHFCCDEHAHFEBBBADCHHHHDHBHEDDDADHDBGBGBCBFHEBEFGBGHGFFHAHGHBAFAGBEFEBEHEGFG,False +672,3.0,4.0,0.0,0.0,2.0,6.0,4.0,2.0,HFHFAAGEGFGFABBFGFBEB,True +673,17.0,21.0,20.0,5.0,12.0,13.0,17.0,15.0,BCBDBECHCAAADCGGGGFBABABEBCBCACAGHBHDHBFEEEEAABCBCBAAHBGGCGBGHGFGAGFFCHGHGHBABFBFHCHADDFCCCECECHHEAFBFBCHHBCEGGCFAEAEGFF,False +674,14.0,34.0,17.0,24.0,19.0,23.0,30.0,24.0,BBGEGHHHEHEFABDCHCFBDAGBBBBDBFCFCFAHHEHAFGHGEGEDBDBDHCFCHCEDEDEDGCGCDDDGDGAGAGEGBHHCHADFDBBBCDDACGHGEGEHBGBGHFEFGFBBDBHBFBDGGCGCDFGCBBBDADGHFCFADGEHFCFAFGBHFHBGEAEBBBAFGGDGFEFBBHEHEBABF,False +675,22.0,22.0,20.0,24.0,22.0,17.0,36.0,34.0,CHGHGHAHAHCECDBGCADHEEGECDGBFCCHCHFGFGBBHFHFHEGFGAGCGCGDGDCBFBFEFEHEDECCHBGBDADHFHEBDBGFGBAHGHGEACGGAEAHGBDCDGDHFHBHCECBDHGGGGHBBDFDFHAAAAAHADADHGHEHAGFGDGAEDGDEEBHACFGHBHBHCGGGCAHEEAEHEFDDDGDBBBAE,False +676,5.0,3.0,7.0,7.0,6.0,1.0,5.0,6.0,EHCHEBAGEGDGDCCCCABHEGBAEDEDCDFDADAHHCHG,False +677,14.0,12.0,18.0,20.0,14.0,12.0,11.0,15.0,CCADHGFACAHGHDDDDDGFGHBADGBEBCCDDDADADABBHCFCFHBHGAGEEEEEEEGEFHCDFAFCCADBDCDCDCBBBBCHCBDAGAEHDHAHAEEHEHFFCGCDFGECFFH,False +678,20.0,18.0,16.0,16.0,18.0,22.0,18.0,25.0,DFFHFHFGFBADAGHCBCAGBCBFGFACBEFEGABBBEGHHFHFDFHEEGEBECFCEBEGGADEDEAEACHCHABEHAHAFAHAHAFBFAECECHCHGHAHBHCHFHGDCHGHEBDBDGCADEDGGFBFGDBDCFFEHDFDFDGDHCHBGAAA,False +679,13.0,13.0,11.0,11.0,12.0,13.0,13.0,10.0,DADAHACGEBDGEGEDEAACHFGEGEGFGFCFAFEBCBFEFHCCFCHCHEHAFFDBBBHGCEBGBGAAHFHGHBFDEGAGBBBBDDADADEDACFC,False +680,21.0,9.0,11.0,23.0,10.0,11.0,13.0,22.0,BHEFDAEAEGGAGBCHCBAAHAFDFGGGGBHADEDACFCFAEABHBHBAAADFFACDDDHDHCBCFHDHCHGDAHAHDDDCDADEHFFAFDEHHDHECDADAGAGBHHGHEHEHCDGDGD,False +681,29.0,26.0,19.0,24.0,29.0,20.0,27.0,23.0,AAHAECBCBAADACAFFGCEADCBGHGFEFEAEDEDBDHDEBHDHAACAHAEBCBDFFHFBFBFBFGFBEAHBCAEAGAGBEEEEEEEEDCABFGFBDHFAFAGBGHGCGEGDADHDFGBCBHBHACEBDADEDEDGGGGGGGBHBHDHCFGBBEHCCAHHFABDCGGECFBAHGDGDCEAEHECEGHDFDEDGAHA,False +682,12.0,18.0,15.0,23.0,25.0,24.0,20.0,8.0,DADHGFBFDADAEECECBFDHDBCBABAHFFFFEFEFBFBFBEDFDEAFCCHEBBGECCCCFAGBBDBGCEEDHGGEGEAEAEFDDDGDAFEGCGCGCFEDDGDFHEDGGGGGEBEDFDEDHBEBDCCEFFFEFEBABFGAGHGD,False +683,10.0,19.0,7.0,19.0,5.0,6.0,8.0,11.0,CHCGBDFEGADBBBBBEGHAFAHBGFACAGAHDBDBDADHDGDBDCCCEDDHDADADCDBBBHBFBDBDFDADEHHHBHGGEFBB,True +684,10.0,3.0,3.0,5.0,2.0,4.0,6.0,12.0,DBCHHBHEDEGAGAHFGGHFAAAGAGADBCHAHAFDFDACHHHHH,True +685,10.0,19.0,16.0,24.0,9.0,16.0,18.0,17.0,DGDFEBDHDADCDBDHFHFHAGCHCHAGEEBGBGBAFDHCBADCDHAHEEABDDFDFABBCDDADCDFDFBBGBGHECCGCGDECGDBFGGEGECHCGFFBFBDGFHBHBHBCGCGCGBDDDFHFHFHA,False +686,11.0,7.0,14.0,17.0,14.0,20.0,12.0,14.0,HDHABCEFFBEHCGCACACBHBGEGEFFFBGCECDCDEHEDEGFGFDDDDGDGAHDHDADADFFFAHAEDHFBADEDBCCGHAEEECFFEFCFHFGCGAHDFGFHFCFH,False +687,19.0,24.0,19.0,21.0,13.0,20.0,17.0,22.0,GBGCDCDHFCAHAHBFFDCAGBFBABCFFBFACBGHGHBFFGHDDADHFHFHBGGHGAFDFCGAGEDEGEADDFCBABFBABAHEDEGFGFCBCFDDADACECEBEBCHCACFEGCHBBBDDDGHHDHAHAFABDHEHEHEGEDBABCBDBHCHC,False +688,11.0,6.0,12.0,7.0,7.0,10.0,7.0,5.0,CCBGGGGFABECFADHEACFCFGFGEDFCFAFBHBCBHBDCCHCAAAAAEDDDDAFCFCEGEAEH,False +689,1.0,5.0,2.0,2.0,0.0,1.0,2.0,2.0,DHDGFGCBBBBBCHA,True +690,15.0,19.0,20.0,21.0,26.0,23.0,15.0,18.0,GBGBGEFEGECEDHDHDHDHDCGAEACGCFBFECCACGCDEDFDHDFBBBEBDHGHDCBAAAFBHADFBFHFHFHFEDDADEDEFCBBAEEGEACCHCEGACEDECECFFFFHAHEGEBABEDFBHEDEAEADFDCHFHFCGEBHCFFFGBBECGBG,False +691,16.0,20.0,16.0,13.0,21.0,17.0,19.0,17.0,EEBEDECEAEBBBBEHFBFBFDCDCBCBCAFGHGCECGGDHAHCDCFCEHDHDBBFHFGEECBGBFHDHGHEBEBEAEFBAAAAEAGGGFEFCFBABDFGFDFHAEEGHHHGDFHFGCGCGDAAACADEGBBCAHGEGH,False +692,15.0,18.0,25.0,15.0,20.0,16.0,23.0,15.0,DCAGACABGEGHGBBCAEGHHDAAAFGCBCBCGGDGCGCHCDCDAFCFGHGCGCEEEHBGGECACADEDFDFGFDBBFBCDCFCDCEEHEHFDBDBGEGFFBFBFEECHGHBAGABABEHEHGCEHBFDCCGDHEHEGBFAFAECEC,False +693,18.0,15.0,17.0,18.0,19.0,18.0,17.0,13.0,DAEAFACADHDHCFCBBBDFDEGEGEFDGBEFEBGHGHEHGGAFAFAGAEDEBHDADAEAEDEAHGHAHCECEHFHBGFAEAFBCGFDFGCACADFCGCBCBDAHFBCDEBCFCFGECDBDBGBGECECFDDHFG,False +694,7.0,11.0,9.0,10.0,9.0,4.0,5.0,10.0,CDDDBBCGFGDHDHEHBHEHEBEBEAEAFHDEGEDHBAAFHCBFEGCBCBCBAAHACCCGBHDDD,False +695,9.0,7.0,7.0,14.0,15.0,8.0,16.0,16.0,DFDCDCDEAHDDDBHHFHFCDCHCFBAEEDGAEAGGFGHAEECHGHGHEEGDGFEFEDEGBGEDDBHBHGEGFAHAEAHAHGBGHGHGDECB,False +696,24.0,23.0,24.0,22.0,20.0,19.0,26.0,26.0,ADGDAEBHCGCHCEADABGBGBFEEGFAFAFBFGDGDHHACDCHFACHCGGHGHDHCBGDHBACHBHGHGAAEBFAHGGDGHGFGDCDCGCDCAEGGGEEEEEHDFDAAAHADAFADEBBBHEHECACBEEEBABFCFCFCECFCHBHBAGABHHFHBHFCDEBCDGDFDFDCBFBCBEAGDGH,False +697,19.0,24.0,22.0,23.0,29.0,24.0,25.0,34.0,FCFEAEAHCGEDABFEFDHCHCGCGCFHABDGEGFGFGBHBCAEEHGBCBCBCGHDHFHABGHDHCCCAADDFDHDCDHFBEHEHEGFBBHHHADEEEBEBFACHHHHGHGABBBBEDCBBBEDEDFFFFFFHCHDAEFEGDGHFBDGEHHGFBDADECEDEDGFBFEGCGHHCHCHGHEFEAAGAGEGDGCAHAEAEBD,False +698,13.0,19.0,14.0,18.0,18.0,16.0,11.0,16.0,BDBFFDFDFGGHAHBHBHBHFGAGAHDHBEBDBHBFBFHCBEGEGEDCCCCBGHECDCACDBFCEDBDFDFDHDFEFHFHEHEFEBABDEHBCDDHAAADEBAGAEACGEAEFBCEGEDFCCAGE,False +699,20.0,17.0,18.0,13.0,20.0,22.0,16.0,23.0,ADHHHHFDFBFAGADBEFFFEFEGCFBDHCAEABAEAEBHFECCFDFHHHHHFHCHCHEHEAEBGHACABFCFGAGDFDFCBHGCFCBCHDEDHGHAFDFAGECECEFAGCDEGEHEAABCBGBGBGBABGEAHGEAFHFGCECADBDB,False +700,7.0,10.0,13.0,7.0,8.0,14.0,8.0,3.0,FAAEFBFCFBFBEDGHCCCCCEDEDFHECDBDGFGFADGBEFCFCGAAAHEDECACFBFBGGGFCFCBBB,False +701,16.0,27.0,21.0,29.0,23.0,22.0,14.0,18.0,ABAEADACBDBFAFDCGBDEDBBFBFADHHAABHDGABACDBDEAFCHCECHDDACAFDFDFEAEDHDFBFBFCEEBECDCDHABFBGEGFHFHGBDEDEDEDCDHDHFAGDGHGHGHBCBCBFHCEBEHCCDCBFBFBECFDGGGFCECEDHBGBCFEEDGBFBEHEDE,False +702,22.0,31.0,14.0,20.0,15.0,20.0,18.0,12.0,GHADBDAFCHAEBDBDBDFDEAAABADEDCAABBEGEGFGEGFDFBFBAEGBBCBCBEGDCDAHCHBADADGFBFBHBGBDCFGDGHCDCFCBEAGFGFHFEBECAFBFBHBHBFBEGEGEBEDAHABADABBGBCAAGDFBAGHCCFDFHF,False +703,21.0,26.0,13.0,16.0,14.0,14.0,14.0,17.0,CHABCBFGFAABAGAHAHAHACBDFHAHEHGCACDBEHDGBHCECEHFAACABHBABABECGBGAGEFCGDEFHBBFAFHFHAHEBEFEGBGBEBEDDDDDDDAHHCBCDDGEADABGBDBFGFBFBFBGEDCBB,False +704,1.0,0.0,1.0,1.0,3.0,1.0,3.0,0.0,DEECEGFGAG,True +705,7.0,6.0,9.0,6.0,4.0,3.0,8.0,5.0,AGABCBCEHFACGFHHCHEACADDDDGBGBGBCEFHBDEDACGCGCGA,False +706,6.0,5.0,9.0,7.0,4.0,10.0,8.0,4.0,BGHGEDCHCHCGCFFGDGDGCBCBAADFFAFEFGAGADFHBAFCBCEDEFCFD,False +707,10.0,10.0,4.0,9.0,12.0,8.0,9.0,7.0,EECFAEAHAHAEAEBEHFDFDAGCDHBHGGEGEGFDFDEBADDCHFDDBFGEGBGBEBEAHAGBFBABC,False +708,11.0,14.0,22.0,17.0,26.0,26.0,22.0,25.0,ADBFFHCHCHCDGFCFBHBHBAGACHDFEFHCBGECDDGEHEHDHEGEGEGECBHAECDHDCDEEFHFDFDABHGDEHEGDHDGFCCCHCHDHDHBAEEGEHEHGGGBBFEFEDEFHFCFAEHECGCAFFFCFBBCAFBCHEEGEGFFECGCGFGFGFAFAGB,False +709,20.0,25.0,16.0,17.0,13.0,14.0,18.0,22.0,CDEHBHBHAHBHBGDGEGBACAHAHGBGBGBAAAGFDEEBGBABABFGACACHGHDFDADHEFDHHECFDACABGHFHDDDAEAEDGDCDCFCBCFHBCBEBEBEBFCGCHFEGGDDBBBCEHGDACABGHGAFHHHBFAFCFHB,False +710,30.0,23.0,16.0,22.0,21.0,35.0,15.0,23.0,FAFAFAFEFEHAHAEBEFDFDBDHFCEAHHHHBEFDADHEHBCCCADEHFHFHFCGGDECGCBDBGAFAFBCDAHADBECEFHCBCBAAAFAGBFADDFDFHBGAAEABFDEDFHAGAHAGAGEGHFEFCABAFCBEBEBHFDDDFDADEEEFBFDACEGFBDBHBHBFGFBFCFGGHAHAFGFC,False +711,6.0,6.0,12.0,7.0,12.0,9.0,12.0,10.0,HGEDHDGCGCGBHBHGCFAGABCBGGEBCHCHFGDEEEHEHAHFHCGDFEFAFAFDECECDCFABCGEGFCEDE,False +712,23.0,31.0,32.0,27.0,25.0,14.0,31.0,14.0,CGABCFCEHDFDHEHBDBDECCFBDGHGAGBGCHCBAEHEHDFDBDCEFGCGCFBAGGGEFEABFBGEAAAAHAGACACECACBGDGDBHBCFGHGBCAAAFBDDDDDDFGFCECBBEEGDADCBEAEAFDGEGCCBCBCBDGCECGCGCGCECECBFBDBABDBDHDCEHEBECGAABDBGGGDEEGEBBAHGGDH,False +713,4.0,5.0,5.0,9.0,4.0,5.0,6.0,6.0,BEFEACAHDHDHGHBDCHCDEDFDGDBEFGDGDFAFBBGACHCG,False +714,18.0,19.0,22.0,14.0,25.0,27.0,18.0,19.0,GEHFCECFCAEFBFAHBCCEBFFEFECDADEDEAEFEBECECGHGAAADAGHBFGFAFHDEABBDGDEHEFEFDBCHEGCCEFBFEHHHHGHGCAFAFHFHFGEHEHCGDFEAEAGFFBADAFFCFABGBABFBCBGBGCDCDHFHCECECDHDBGBCBCGG,False +715,17.0,8.0,11.0,12.0,13.0,12.0,12.0,14.0,BAGDHBHDHABAEGHFDADFECDCGCGADHDHDHABCBHGAAFBFBEHEAFCFAGHEBCDFDFDCHCHCADAEHEGEAEGCGCFEHAGGFAFEFEAEAG,False +716,16.0,17.0,24.0,24.0,21.0,17.0,16.0,24.0,FCBCBHBCBCECDCDAFFHHHCHDBEFABAEDEDEDECFDGGGAEFEFEHCADAFACEEECFCGAEDEDGHGDGAGFBHDHFHCCGEGBDHGEBHHHEHACAEGFDFDHCECBADECHHHBBBFBFBDADCCFCDCBCDEDHHCGDDAAAHBHGHGDGF,False +717,30.0,23.0,30.0,24.0,12.0,21.0,21.0,16.0,ECEDACAHEHCACECDCGCBHAGDFACBCBAFGFGBACCCCACFGEGFHHAHABGBEFFBFDFCGABCDCBBBBBAADADGDFDFHFDCDCHFBFAAGAGAGAGFCCCHABGDGDBDCDEBHDCDCDBGFFHHGBEAAHAHDFDEDAHAGDCDBHAFGGGBABDFCACACBCFEEAE,False +718,8.0,9.0,11.0,13.0,10.0,18.0,7.0,15.0,BHBGDHDHDEAEFFAGAGABHFFFADHDHDGAFCDCAHBDECFAHDHCCBGHFCECEHEFDBDCDGEGDBHBECFCFCFHBEFFFFFHFHE,False +719,12.0,23.0,32.0,23.0,25.0,25.0,24.0,32.0,ACHDECHBHFHGHGHDADAGHCCEBEBCCGHFFGFCBEGCCDDDBGFDHDHDHGFGBCFCGCDCDCDCFGEDBDBEGGCFEFEHEBEHECBFDCDGBGEGBGEGCFEEECGFGADCFEAEADBBCECEHEBEDFHFCFCAABGHHHHHFAFABCCHCFCAHEHFBFBFHCGFBDGDEBHBHCECGDBAFHHHHHDH,False +720,9.0,6.0,1.0,2.0,6.0,3.0,3.0,2.0,AAABABDBGEHAGABCBGFHEAEDEAEFEFBA,True +721,4.0,4.0,5.0,4.0,1.0,4.0,3.0,0.0,BGBCACGCDDFDFABACECBFAFDG,True +722,16.0,8.0,13.0,19.0,18.0,17.0,9.0,17.0,DFEFCHCGADHDEDAHEDEBFHFEFEAEDEDHAHADCBAFACAHEHDCGCGCDCDHDFECEBEDEDEFGGABFBFGCACFDFAFBDGFHCADHEHEGDAEAHHHBHFHFADCFEBGA,False +723,20.0,21.0,15.0,7.0,15.0,20.0,22.0,15.0,AFCDCFCFGFGAGBCACBHAAFGFBBEEAEGHDEDBHBHEHBCGEGFACEGHGHGCGEGECAFFGEGEGEGBBFAFDCBCFCFADADBHEAEHGBGHGBAFAHCBADFBHBCBFAFHBABABAFABHFGFGEHCG,False +724,22.0,23.0,14.0,13.0,20.0,26.0,11.0,21.0,DEBABADADEGBGBEBHBCCAAEAFFDAAAAFEFAFGFCFCBHBCFFFCFBFDFEHHDHCHCFDEDHBHBGAACEFAHHFABAEEEEGBCHCECACGDHAFDFHFHFEFHAGGGFCHBBDBHBEBFBFHHEHBBBABEEFGFEDGDAHAE,False +725,21.0,25.0,25.0,29.0,21.0,32.0,25.0,20.0,FGGGCGEGDFAHHHCCCGAEABFBEBDBDHDCDEDAFGDGAEFCFCEAEADABCBGGGGGCDCDCFFFEHACBCBCGCFCFDBDFCFAHBDDFDFBEHEADCDFHEHFFEGGDGFHEGEBBBDHEAEAGAGAHBHAAGAHAHDDCBCFFFHFEDGDHDBFBEAHBFBEDFCHGFGDCFEGCHCFBFDEDFDABBFBCB,False +726,16.0,20.0,16.0,17.0,10.0,18.0,13.0,17.0,BBBBGCACACBFBABFBCDHGBCHCBADABFCFCFGAHEGBGEEEFDGDFAGAGCBCEFHFHGHFHAHFDFCHAHAGEBDBDGDCDCHFHBDDADCBFADEEEHHDGFGFHADEDHFHCBCBABADF,False +727,10.0,29.0,22.0,26.0,22.0,17.0,21.0,19.0,BCBCBCBDAFHFCECDCDCBHECFCGAGDGBHFDGDGBGBEDEDEDBCBAFAGHBHDHAADBDCGFGHDBDEGEFBBBCBEBEHECDHEGDADCDHDBBGCEHFGCAEAEBEBFBHADCECFCFEDGHGHBHFHGHBCFGBCEFDHGBGFGEBEHEFFDDBDECGD,False +728,11.0,13.0,13.0,11.0,13.0,20.0,15.0,18.0,EFFFEBCDCHCAAAADFHFHGAFDFHFCFBEBGCGAFBCACAHAHEDBBGEDEDCDGBGFGFGCHCFFDHEBBCGGGGGDFHAHDHBFFCHHDHEHEFBHBHECAGEGEFEFBH,False +729,26.0,25.0,13.0,24.0,26.0,16.0,21.0,19.0,DBDFABGGFGHEHAAAAABFBFBGBDBABAGEGCGFEEGEBEDHAEDCHABCDEFAFAGDHHAHADAFAFGBGAGHBDGCHHHBFFEAEDBDBEHDBBEDDHDHDCBCBEHCACDHFCGAGEGDDBEBEBEAGAEADABAFFFFEHGCGCEEEEBEGDHDGECEABHDCD,False +730,16.0,17.0,13.0,13.0,6.0,15.0,8.0,16.0,CCHDADACCDBABEBHDFBEAGBGFCECHBAAEAEDEGCHCHAFBHGHDBDADAFBDBGBHCHCAGAGHHCDCFFDFBFBADFBFBFHAAADBFCFGFBFHHHH,False +731,16.0,23.0,24.0,23.0,24.0,17.0,32.0,25.0,FFFFFFFDDEDGGHGHGHGFDHBCACGEGEBEBECFFBFBDECCDEHCFGEACHDHDHCFDHEGABHEGBGEAEHBAGCGHGHEEEDEDHFCGDGBAHAGAGDGBACCEAGAGAGAHFBCHCGCDCHCHBDBGBEBGCDFDBCBHEHEHGCGHBCBCGCAADDDGHGBDEDEGBBDFEAEGBCH,False +732,2.0,3.0,2.0,0.0,1.0,3.0,2.0,1.0,FCFGFHCBGBAEAB,True +733,6.0,2.0,3.0,2.0,1.0,4.0,1.0,4.0,BFFCHCHCHAAFADBGFDAHAEA,True +734,5.0,4.0,6.0,8.0,4.0,8.0,3.0,7.0,DGHGDEDEFAFBFBDDEAADFDHCHFAFBDGHHHHCCCCFCFBEA,False +735,11.0,7.0,8.0,6.0,4.0,4.0,8.0,5.0,CHCACAGAEDFDCBHDHFHBCDDHAFGGGCACAGAGBBBGBEBDFAAGAECEA,False +736,20.0,16.0,16.0,26.0,10.0,23.0,15.0,12.0,BDBHCCEBDBACHCDFGFCADHDFDHAECDAGAGCFEFCFEDDDDDDDCFHHADFDABEGGGAGAGADABAFCFAFDBEBEGACADDDHAHBECHDGBGBDDEGEGDBFCFHBADGHGHFFFBFAFAFCFCFBFCFBA,False +737,23.0,11.0,24.0,14.0,10.0,9.0,22.0,11.0,FHADCDEAAAABDBHAFADADFCGGGHGAEAHCGDDCDCDHAHCGGGGCACFCBCBCGCHAAFAHEBADAECGCGCGDGECEDGBFCDBAGACFHAEGCGEGBGCECHGGFHFABABABCCDCE,True +738,26.0,23.0,28.0,29.0,22.0,16.0,18.0,26.0,EHDFFHFHEAFFBBEHDBBBDBDCGEGEGCBCDGHAHDEDEDFAFGCCCACBDAGAEFHFHADAFHCDCDBDHAAAAAHCHCHFHFEFHCHFBAEDHCBCBCBEBDADGDAHAGACACBHEDDDEHCHBDECCGBGBHDCDHDBGCCBGDGCHHGFBAEGEAFACACBCEEEEHEGCGAADAEBGDDD,False +739,8.0,2.0,10.0,6.0,9.0,6.0,10.0,6.0,CGBDCDCHHEEAEACAEEGFHFDDDDFGFEAHCCCCCBFGAGAGEFAGAGHCEGEGH,False +740,11.0,8.0,17.0,13.0,9.0,9.0,18.0,8.0,BGAGBECGDGHFHBHBGDGDGCCCCCCFCFDFAFHBDADGDGBBCACAFEDGDHCECHAEEEBDCGGAGFGCGDAAEDEACHEHCCFGAGDGF,False +741,4.0,2.0,8.0,8.0,5.0,1.0,3.0,4.0,CECEAEHCCADDHDHGGEBHBECFCDDDDCDAGAC,True +742,2.0,9.0,1.0,2.0,5.0,5.0,1.0,4.0,CBHEDBAFFDBABEBEBHFHBHBFBGEFE,True +743,18.0,19.0,21.0,21.0,22.0,11.0,26.0,21.0,EAACDDDHDGEGBHHHHEBEBABHEHBFGCGDGEGCDCDGGCGHFFDFBBGACADADHHADCDGDGBCCCBEDECAGHGHBFCFEDEDEGGCBEFEBEBEHADBHBGGGADADFGFDAEAGBBHGDBHGHCHCACACAEFEGHCECEAFHCHBGEGECA,False +744,31.0,23.0,20.0,24.0,21.0,22.0,28.0,21.0,DADEBEBEDADABCBFGGGGGHGHAFFGBGBGCGDGFGHBCCFDEHEADABAGGBGFCFCAGAHHEDBHBHFFEHAGAGBCDFAEBHDDDDEHHACFBHDGDGACFFBDBAAADAHAHCHCEGAHAGEEEEEBHFFGADABABEBEBCDCBHFHFAADFCGCGBAADDDFCCCHFEFECEAGACAGDGFE,False +745,5.0,11.0,15.0,7.0,10.0,9.0,7.0,16.0,EFHFBCACFCEHBCBABABCECFHHHHFEFHCHCFCBHHGGEGEDDDHAFGEGCBDDDHEEAFBBCHCHEHGHBCBCDCG,False +746,1.0,0.0,6.0,5.0,2.0,2.0,2.0,0.0,GDCDCACECEDFDGCCFD,True +747,14.0,8.0,8.0,12.0,14.0,15.0,12.0,12.0,HCHDFEEGCBCDCAEEEBEFEFCABABFBFDEGFAHEHAHCHGGFCFDEDAHCHDFDGDGABHEAAFAFHFEEGAGDDFBHBHGDGEGAGAFAFD,False +748,23.0,22.0,15.0,27.0,27.0,24.0,31.0,19.0,CFEFAHGBGDEAEBEAEBHBDDGBFAHCGFHFHGEGFAFADBEFHBEBCCFCGEGADBBGGCGBGHHBEGEGABBEEEAHAGEGFGAGFCCBFAGBGFGFGFADDBDBGBFEFGFAAAABHCDDDDDDFDFHFHBGDEAEDDDEDEGEDEDECHDHCFAGAHAEAGADFGHEHDHCCGEGEDBDFCHC,False +749,18.0,23.0,17.0,19.0,17.0,23.0,21.0,21.0,EAADEDBDBFBEECFCDEGFDFHBDAFFBCCCGCHCHAFAFAGGHGECECEBEGAGDGDHEFEHCBAADAFBFBHBABGBGCFCDHFBDEDECFGFBCHHDBBCHDGDFFBFBGDGBHHAHABADADEEGHGHBHFFFFEFGCGCDEHHGHGAAAGBBH,False +750,26.0,15.0,24.0,31.0,22.0,18.0,27.0,36.0,HFCEEEDBCEHFDCDCDGDAHEDGBCCDCGHDEECFHFAFADHFCGEEAEHEHECGABAHFBFBFDACBDBDCDHDHGFBFACAHAHABAHHHCDGHGHGHAABFHFGGHADDDDDADCDEDGDEAGGGGAGBGACCHBHBFDDEEHEDDHCHCHCHGFGAHHHBHFGCGHEEDEDFBAGHGHCECGCAHAGFEADAGA,False +751,2.0,2.0,6.0,6.0,5.0,4.0,2.0,6.0,DCHAHGHCHCEBEGDFCHCDCFEFEDEFHADBD,True +752,12.0,16.0,4.0,9.0,13.0,13.0,11.0,4.0,EBEBDBDBFAHAHADAGBCBFHEEAFAEEBEFGFEFAAAGGGBAFCFCFDGEBBBBBBGAFEEDDDGAGFGCEFEGBDDFHB,False +753,20.0,22.0,13.0,25.0,23.0,25.0,27.0,11.0,DBDAFFDEDEDEFEFDBCFFHDDEEEBEFDFEFEGBGCHCEBEHEHAABAGGGDEAFDFBGGGDFAFAFACHEEBHACBFECCGGGGGGFDFAFCGEGEFHBDBACAHAEFDBDFGABFBEGCGCDHDHDGDBDBDGCFBGCAHGDGBBFAFABEGEGABADADGB,False +754,13.0,24.0,24.0,21.0,25.0,16.0,20.0,11.0,BHBDGCGFGFGFGHGHBFGCEEFEFBAHEHEHEBCDEDEDBBCBCEFECGCDBACAGDGDBBHCCGDAAEAHCEFECABABDGDGCBEDHGFEDEDBGGCACDDBEBCBDFGGGEEHECECEFDFDBBBDCHAFDCBCBCGCFFACAEAEDBFE,False +755,21.0,23.0,12.0,20.0,22.0,23.0,13.0,24.0,FBFBCBFBFECEBHBHDHBBBFBACGBGBDAGFDACHHGCGHFDBHEEEFEAEBEBFGAGAGEDDFDFEFBCAFDFEAEAEDFDBDHECDCFCEAHAFEEHAHGHGHCBDAEGHBDDDBDEHGBAHAFCHGBFHFHEHEADHFHFHFDEBCAAAAHAD,False +756,9.0,16.0,8.0,17.0,8.0,7.0,7.0,4.0,EFEFGFGCCBABHBDDDDGDABBGBFBFEACDBDEDHCGEGBCBCBFDDDEAFABADAHEBADHDCCEDGDBBBAD,False +757,15.0,20.0,18.0,27.0,18.0,16.0,16.0,19.0,GHFBGBCEEAHDBDAHAHEBFFDDDDBFBEEAGBDHDBEGHAHADDEDCFCFBHAHBHDDGDGDECECGHGFGDADEFCFCFDADBGEEBCDEDGABABHBHBHCDCECECEGACCEABFBFBCCHABGHFHFACDDDDDGHECGFGFH,False +758,24.0,10.0,20.0,10.0,13.0,18.0,25.0,18.0,HEHAHAFAHCGCGCHEBGCGHGHGFGCGEABGHGFGHCHEAACABAHACFEAGCECBGGGGGACDFHFAFDFDFDFBEEAEAECFCAADAGFCHHECFHGAGHGEAHFGCCDBDBGACAGADABBDBDCFAFHGEFCF,False +759,5.0,2.0,3.0,3.0,1.0,2.0,7.0,3.0,CFAGGHGHGHBDGDGACEDACAGABF,True +760,23.0,15.0,19.0,10.0,31.0,25.0,21.0,16.0,FGFGHGDGBHACAFAFEFEGEBFGFGFECEDBFEFEHHCFAEACFBBBAFEDCGCEAECFCBBHEGEDEAEFBFGFGADCCCBHAAEEBABAHAHACECFHFEDEABFEDEAEBECACECGFGFEAGAFEFACHGDGAEAEGHHHHGDCBEDEHFHGGCG,False +761,4.0,5.0,6.0,6.0,5.0,5.0,6.0,6.0,EFBFBFGDHCHFEFGGBDAGACHCHDHBAAECCBCDEDEDGHG,False +762,5.0,7.0,14.0,5.0,9.0,9.0,6.0,9.0,EGEFHBHFGFHCEDEBEFACAEAECHCHCHCHBGCFDFCCACBCDHDFGABHBCECDGGEFCFB,False +763,7.0,10.0,9.0,14.0,6.0,13.0,15.0,4.0,FHBHAHAFAEDCDEAEHFDDGFBFBFDGGFGBGBCBFDGDBCGEGECAGAGDGDFDCDCDFGCGEBDGFBACFBFDCG,False +764,18.0,17.0,21.0,10.0,17.0,19.0,30.0,14.0,GFCBGAFBBEFFCGHGEADAHFHEAEAHAHFGGGEGECCFAGAGFFCACBFAFAFGGGAEHGHFHBHCACHFAFDEDHGEGDFBCGCAHGCEBEHCBGBDDCAGBDAGECECACBCBCGGGBBBBBECFCFEFHGDGDGDGEGEGC,False +765,16.0,9.0,24.0,14.0,21.0,12.0,17.0,12.0,FCCCCEGDGDFBEGCBCDDDDCHFGACDHECCCEEAHGHGCCCFEAAADAHGEBEFDDDCDCEAGCGDHEAEAGADAGEFCFCFGFGEAFHEECECEGHGBFCECEBFBCAEBGBGHAHAHAHBE,False +766,2.0,5.0,3.0,5.0,5.0,3.0,5.0,14.0,GCCBCDHEEEFHHEBEHGHBHDHDHAHFGAHDGDGHHHHBFB,True +767,25.0,19.0,25.0,19.0,30.0,21.0,34.0,24.0,AABAGCCCGCDFDAEECGCHBHGHGHDAGCGDFDCEGEBAGFEEEHHAGAGAGFECEHGCECEHFHABEEEBEFEBEFEBCGGGDGABEDEDADGFGFCHHHHDDFBFBAEAEAHGFCFAAAAABAFHECGCDCGFADDBHBGCEHFBBGDHFAFHBHCHFHAGGGGGGAGCGEDEBEDECHFHGBDEDBFGCCCCE,False +768,25.0,18.0,18.0,14.0,17.0,14.0,28.0,21.0,DBBECABABAFFCHGBFEAEHGGEEEHGHGAGADAHGCCFDFDGAFCECECDBBBFBDHHGHEHBHAHGCGFGHHCCFAEAECGAGFHHCEGGGCDCEHEHEDGDHDAGABACCBCBGFFBBHBABADAGGGGHGAGAGAECFBAGAFADAEHDD,False +769,1.0,3.0,1.0,7.0,6.0,6.0,6.0,3.0,EFGFHFCEBGHFBDEDEHEAFDDGDGDGDGBEF,True +770,10.0,20.0,19.0,21.0,15.0,21.0,16.0,16.0,CDHDGGGCGEGECDCDCDABFBDBFBFDFHFHDDBEAEHBGBGCDBGBCHHDGFGCHDHCGCAAHABAFHHBDEFEFCFDFCFCFAHEFBFBGHGDDDCBEGGFEBEAEBDBHCHAEFCDCBFEFEBHCGCBFDFDEA,False +771,4.0,6.0,5.0,4.0,2.0,2.0,2.0,5.0,DBACDGDBBHBHCFDECECACAHAHGBFBH,False +772,20.0,21.0,27.0,26.0,23.0,24.0,13.0,18.0,HHGDAACADHDEDCABDHDFCFDBCFCABDCCCCFFFDFBCBHBGEGHGADACFDGAADDDDDECEHEHDFEBEFCFHFAFCFCFAFCHHHCEBEBEGECECFCHEFDCGBAFADAEAEDEDEFEHEGDAAEBCAEABBFBFBEADGCHDBGBDCDFGGBCBCBEHGHCHBF,False +773,23.0,11.0,12.0,12.0,15.0,10.0,15.0,14.0,HHBEBEDEBGBDFCECGCGEGCHDHGHGBCHAGAGAFAFAHAEEEAEAGBGEGCGAACABBHDABFDFAHADGHFBCDDHAAEAEAEAEACDFDEAAAHFDCCGCHHGDBFF,False +774,17.0,24.0,28.0,15.0,15.0,16.0,18.0,18.0,EFEFEBGCDADCEHBHBHBFBECECBFBFCGCEDEDCCFCGCGFGFACCDFHAHGHBHCHEHECCCGGFCHCADBBBGHHEGCCCGCBHGEGBBBAADCDCDCDADADABFHFAGBDBAHGBBABFEFGBEAHBGCCHFHGDABACAFDEA,False +775,3.0,0.0,2.0,1.0,0.0,2.0,2.0,3.0,AGHGHFDFCHCAA,True +776,17.0,9.0,11.0,6.0,12.0,12.0,17.0,14.0,GCGDABAFGFGCCECFABAEAEBGADHHEHAAAEDEAEABDFCGBADAEHGHFFFGAGFCFDBHBFGHHCGAGHGEGHBHCECEAEAGFCFCBHGHGH,False +777,4.0,6.0,1.0,5.0,7.0,2.0,6.0,4.0,HEFEAEAEDBBGDCDHDFEBAAHEHEDGBBBGGGG,True +778,6.0,7.0,4.0,4.0,5.0,13.0,4.0,5.0,HEHEAFGFAFAFBGBAFFFDEDECBCFGDBEHFAFBFDFHFHGBACCB,False +779,9.0,7.0,5.0,6.0,9.0,8.0,7.0,9.0,DGBEBEDHAFAFHFHFCFCEDEGEDEDGHAFBHBAGAFBCBHFAGADAECCBGEGHHEHA,False +780,19.0,21.0,16.0,16.0,23.0,19.0,26.0,22.0,FFCAGEGEGAHBBEBEGCDFEFCFGHHDHDHDBEFFAGEGAGAGAHEHFAEDBACCCEDGBEACFCFEDEABABABFHFBGBGAGEHHACBCGCHCHGHEABACDBDHEGFGEADHFBDCDCEBBAGHGHEHEHGHDHDGDGFHABECEBDGGFGBGBEFFF,False +781,15.0,24.0,23.0,18.0,23.0,14.0,17.0,21.0,FEAGCCBABABAFAHCDGHFCAEGBGBGHHBBCBFBABAEDEDADHFECGDGAHEBEBECCGCHCHEBCFEDDDCGCGDGDHEFGGCHCBEFECAHDEDFDEHEGEFBBHGGCECECFBDBDBAHAHEHDHECFBFDCECABABHBGBCHFHDHE,False +782,14.0,24.0,23.0,18.0,18.0,17.0,19.0,17.0,GAECGCBBAGAGAGFEEDDFBEEEBBGGEECCCCBEGEGFGDGCHCHCHEADBDBHBHFGADBFGDHHGAGADDDDDCBCDHFBFHDAGFHFHFHCBCFEHHHBFCFHFCGCBCAGFEBDFCECHCACBDBCEAGDBDBEBEBEBABAFC,False +783,17.0,21.0,14.0,26.0,20.0,11.0,14.0,15.0,CHAHEHDHGCCADABAEDBDBFAEABGDDCGADADBBAFCEGDBEBDHGEGFHEHEHEFCFDGHADADBDBDCDCGBABDECEDEDFDCDCDADEDBDHGBGBECDHEHFFBAEAEBEBGHGEBCGGBEFHBHCFAFA,False +784,9.0,13.0,21.0,19.0,11.0,19.0,13.0,15.0,ADHDFGEBBCCDCDCFHAGDBCBCECEAGAHCDEAHBHEFEAHHGDCHCHDHDHFBEADFCGCHDHAFBGBGBEFDFGFECACFEFGFDCDEBGBGCFBFCDGDGCFDFHFHFCFCDCDB,False +785,3.0,4.0,10.0,4.0,5.0,8.0,5.0,7.0,FCFCGCGEAAGFCECECHFFDHCACGCGEBHFEFHBHDFDBDBHHC,False +786,13.0,15.0,20.0,21.0,12.0,14.0,14.0,18.0,BFDGDGDADECHCHCEDGDBDGHCHDGCABEEFEFGGDDBDHDHDGCCEBDFDFBHBHBHFHFAECEBAAAFAEAHBHGHDFEFBHBABECCCCCDEGHGBFFGHCDCBGDCCCFHDCACAFGHADA,False +787,12.0,21.0,22.0,19.0,22.0,24.0,29.0,14.0,CGCGEECEGGBEAGCFFFCDCEEACFBFBGBGDGDHDHCBCGADEHGHBFGFGFDFDBGEGEBFCFCFCFABDBCAFFGDGBFHCHEECDFDFCBEBFHGCGEGAGAFDFCEGEGEAAHHHBGCGCGAGDGDBDFGEDBDFDBCHADEEGEHEHABBFEHBCB,False +788,17.0,13.0,19.0,20.0,16.0,16.0,19.0,15.0,BDCEGHGDAFFHFHDADAHEEEECFCGDHBHGGGAGAEFGBCADGCCCCCCGCDCBEFEFDFECADABAFEBGBGAADGEGHADABHFHFCEDHDGGCDCDFDADGHCFBBCBCEHBHFHDEDEDEGHGAAAFBF,False +789,28.0,17.0,13.0,32.0,28.0,13.0,27.0,17.0,AEADADBGBAFAEADGBAAGDDEGEBEFCFCFHFHAEGEHDHAADEDHDCFCBAEGEGDGCGAGBGBGBFDDDEDGBGBGBDDGGADCDBGAEAGDBCADEDHBABAECHCECAFEHAFACDCDGEHEHFBEHDDDDFEAABDHGHGHDAGECEGEGDHEAEGEGEAFHDHDFAE,False +790,20.0,14.0,14.0,14.0,17.0,15.0,16.0,18.0,FCFDDDHCHCEGHADCBGFEFCFEEEEBEADABHBDEFCABABAGAGEHHBHBDAECGDEAAAFAEADBHCGGBGBGBEFEFEFABAGFHHGACDBDHHGFDACEHDHGHFCFDHCHCHCEFAGAGAG,False +791,18.0,17.0,18.0,19.0,20.0,20.0,6.0,18.0,FHFHFDEAADAFBBACGHDCDFAGGFEFADEDBFBFECEAFAFACCCEFHBHFHBBACHFDGDCDHDHGBAHCDCBHBEEEEAECBABCBCEDHDFDEDEDEAEADACAHFHFHEDCCABEHEBEHCFBFGFBDHC,False +792,14.0,17.0,13.0,12.0,11.0,16.0,16.0,11.0,DDBDBDAFBDBFAFAGBDEGCCECHCHCGFABGBCFEFECHFBABAEECBDHDGDGHGHGFCFHEAEGDHBCBEFHBGAGACAHAFGFGFDEABFBABGFGFGBHCAEDC,False +793,9.0,19.0,17.0,11.0,13.0,16.0,16.0,13.0,DCGHBFFCGEEBEGGAGFDEEBFGHCHCDFDBCBCFCFCGCGBBBCBCBFHFGCAEABHBABGBDBDFDHAHFGFHBBBGHGHECFDECEGHGHDAAGDBCECDAEAEFEFCFH,False +794,18.0,14.0,23.0,18.0,18.0,15.0,28.0,20.0,GBGBGFGAEFECEBGBECECFGDEDGFCFGGHCHCFGDAHHCHCFCFCGCGCEAHAEABACDBDBAGGCGHAHBDFDHEHEGAGEGEHHDCDGFHBHGHFADECACAEABFCAHGHGBDCDFDFBAGACDGGCDBGGADHDBFHEHEAEGDCEC,False +795,2.0,6.0,5.0,6.0,3.0,1.0,4.0,1.0,GDGECBCHDEDECBBFBCBABDGDGACD,True +796,20.0,15.0,22.0,19.0,22.0,17.0,35.0,28.0,EHGHCDCDAEBCBFBACHCGEFEFEFDFHGHDCGAHDCGCDCACBGEEHEHGGGEHEFEGGAAAAHAFFECCAGHGHGHBACACDCFEAGGGGGGGCGAFCBEHHGDGHGADAHGHBDGAGBCDCABAHDDEEFGGEHHHBBBDBDHDHDHFHEHBCDCGFGECEFFGFGEGHFBEDA,False +797,22.0,14.0,14.0,13.0,13.0,14.0,15.0,9.0,HCHGGBDEFAFAGAHDCGCGCHCGFAADEDEABAGABFEFEFEBDFGABHFDAABCHCFCADBBAGDGDGDCDFEFGBDBDFFGCBCBEBGAAAAAAHEHEBEGCAAAFHECEC,False +798,15.0,14.0,14.0,26.0,14.0,22.0,16.0,23.0,DCGAADDDHDHFFDBGGFGEGBBDHAHFFFFAFCFBDDFEAEDHDHGHGDCHCFAGBDFCFEFGAGHECFCEDAHAGEBFBABDEDADCDHAFCFAFHBDFAFADEGEHEHBHGFGCGHGCDCDBBHHHHBCBCHDEDEDEDHH,False +799,27.0,20.0,19.0,24.0,17.0,17.0,26.0,21.0,GFGDGDCDFGBGBEBGBHHFDADAHEHEBBBHFFGGCADACAGHBHAAFACACHBECEFAHADGDAEHECFABCGCAHBHAHDGEEHFDFHFDFCAHDBDBFEGDGDGHBDBGAGEGBGCCECEBEHAGABADADADECGCGCAFHGHBFACACFDEDEBGACAGHGFDDD,False +800,14.0,22.0,27.0,22.0,29.0,27.0,20.0,20.0,BCBCBCACACAHDBFCHEHEFBGGCGCABBHBEEEBECECBDHDEBAACGCGFGFDFGBCDAHHHHFFEDDDDEFFHFDEGGGHEAEDEGBBDFEADFCGCGCHFHGHGEDCHFFFDFDCHFBCBCBCEEEGACAEHEFGFDFCFBAEHECGDEFGHGAFAEBBBBDCEHFCFEFDCDEDE,False +801,5.0,1.0,4.0,0.0,2.0,1.0,0.0,1.0,HCAEACAFBEACAC,True +802,15.0,14.0,17.0,11.0,11.0,11.0,14.0,5.0,DGAEAFAFCFDADEFEFCACGEHEFGCHABACABHBADDFDFCGEGEAAACHCGDGCGBEBFDCABBBBDBABFGGCCCEGFBBBEDAHCGCGCGCED,False +803,19.0,24.0,22.0,27.0,21.0,24.0,25.0,26.0,HFAFEFEFCCCHCHGDDHEHEDEACCFAFBHDEDEBGCGBFAHAHAHFGDBAGAHBHFEFBFEFABCDHDGACACBGDGHAFBDBCFHFHDHDGDADBCFGGBDACGHGCECEGGAGDGDGEGECADHDABGBDDCECEHFHBGGEGEHBFBDHFACAFBBBBHEEEGCDHGFDFDFEFHDHDCBBBC,False +804,14.0,12.0,12.0,16.0,9.0,14.0,9.0,8.0,ABCBAFDEDFDHDCDBAFCBGBDBEAEGEBCDGAACABDECECEHEAGHGDBHFFFCGDADFFFGFDBDFAHCHCHCHCBADADADABFFGGEF,False +805,10.0,5.0,7.0,4.0,17.0,8.0,9.0,3.0,AAGAGAGAGAHECEFEGEHEBEAEFDADFEEEECEDECHGFEFAFBEDFGBEACBCEFBCCGG,True +806,16.0,25.0,13.0,17.0,23.0,16.0,21.0,18.0,CBGEEFEGBBBCHGHBAAAAGAGEGCHCEDBBBBBHHHHDAFFEEDEDAAADFEBHGHDHEGEGHCECEBBDADGGGGGDGHEHEHEBBBFGFAFDFEFEBEBCFFEBHBECDBDFAFAGHDFDGBHDCFCAABCBHEGDGDEBGCCAF,False +807,3.0,8.0,5.0,8.0,9.0,8.0,9.0,9.0,HFFFBHCHEBEBEBGBDCGCECEFDFBFGAGHHDHFACHDHDEFBGDGEHEADGDBEGG,False +808,18.0,19.0,24.0,19.0,15.0,25.0,23.0,17.0,CDGFCFCAGHEAEADCGEGACBGFGDHEEECACECECFAHAFDCDHDFEBEHDFDFHFGBEBGGGBBBHBHFAEAFGFAHAGAFCGCHCHGHBCDDFDFDGDFBEBEBFAFCFGDCCHGHADCBFBGBGHFCGDGBCAHFDFCFCBCBDAEABADGFGHC,False +809,24.0,16.0,20.0,18.0,20.0,16.0,26.0,18.0,HBEFGCGHAHADGCACAFBFAFCEBGBFDGAGAEHHCDDHDFDHDHDEECGABCBFEAEHDGGGGBABGFEBCAEGBCFCHGHBHBABGBHFEFCCCCAHGEGEFHFDGAEBHDADCGHEAEAEAEAEGEDCDADGDGAGAGAEHDGCCFCFCADBGF,False +810,7.0,10.0,7.0,14.0,17.0,13.0,14.0,8.0,DEAEGEFECACABGEGEAHGHGHAEFEFECHDDFDBDBCBDBDFGCGEBECEDDDADBEFEBDFGBDFHGCFFDGGFEHEHFHBGAGEGF,False +811,11.0,12.0,11.0,18.0,16.0,11.0,15.0,16.0,EBEBABDHDHDHEHGHFAAGGCAFEDDGEFAFHDBDBDHEGGGGBCBCFDDDDDEDBHFEBHCHABEFEFGHECECBFGGGEDHCHCGEGACAEAECHABCHDADFDFHG,False +812,7.0,8.0,5.0,1.0,6.0,6.0,5.0,5.0,HHHHAEACACBEBCCAFAGEFCFDBHBFBFEGAGEGBGFABBE,False +813,7.0,6.0,14.0,17.0,20.0,8.0,11.0,16.0,BCHCAFAGAHCEFEDEHEDCHGHAEDGDFCFHGHGHAEGEGFHBBDFEHEDEDHDEDEBGDDFBEHGABCEDECCCADGHEHEHCHCDCDCDCEEGEFD,True +814,27.0,14.0,15.0,25.0,17.0,16.0,12.0,25.0,HFFCACAHFFCBCFFGDDECEFEHCBCBCDAAAGAHAHDECEFHAHAHDEABBEBCFGBGDEAEAEADGHAHACDHHHBCBEDFFAFHFEEGAAAAAHAHEHEDDDDGAGDHDBDFFAHDBACACAGHHDGBGBEDDBDHFHECGDDDHDH,False +815,9.0,8.0,11.0,6.0,5.0,16.0,9.0,7.0,DDGCCHAAADDFEFBHDFFFDFCFCFCFEBEGGGCFCGHGHEAAAFFHBCBGBEBCBFFFCFCAAGAHHGB,False +816,27.0,23.0,14.0,24.0,26.0,27.0,25.0,22.0,DABHHHEHAHAEFDBAGABDBGHDAAGAGFBAHAHEEDABFGGEEADAFBCACGCGCEFEBEBDFDCDGDEFEHEHFAGAGCBCGCBCBEDAGGBABHDFBFBDEHEHGBFEFEBDFHFHFDEECAFGFGFEADHDAGAGADCDCHFHCEADFDGEAFBFCFDBEEDGAGBEFEHDHGAGHGHFBFBF,False +817,1.0,1.0,2.0,2.0,3.0,7.0,3.0,4.0,FFFFADHDHEHEGCFBGECFHFG,True +818,10.0,14.0,17.0,5.0,12.0,5.0,16.0,9.0,CACBHAACABGDCAEAFGBEHEGCGCGEGEDBGAGFHBGCECEFEGEGBHBFGAGHEABDFDBCBCBHEHGHGBDCACBGBECCCCCH,True +819,20.0,12.0,13.0,11.0,16.0,13.0,21.0,6.0,ADCECACDCEGDFFAFBGBGBGBAAAEBEBGFDADEDAACACDCHHBGGGGGGGEGAAHFEFCGDGBCFABAFEGCDHFECEDEHABCDAHFGAGEGAGAEAGBFBCEFEFE,False +820,24.0,22.0,18.0,21.0,20.0,19.0,14.0,22.0,ECFBHAHAHAEAFBFGDGDCBCGAEAHABCBHFEDEDGBCDCDADABAEAEBHDGDHCBAHFDCDHHBHEGAAFAFCHCDDEHBFBFDGDGHBAFCEDEHFCEHEHEHGCGAHABCBEFHFGCDCDFBFBFAFGBDEDAGCHBEBCBADAGEBEAEAFFH,False +821,24.0,21.0,19.0,22.0,19.0,13.0,20.0,29.0,DAHAHAFEGCDEECECAAEHEFDDDGAGAGAGABHBGEHDHFHEHAHAHAFBHBHCAADCEBBGDECHGFGHGAGEDFDFDHHHCGAEABFDGBECECAHACFCHGFBDHGFDHBHDDDDGGHEHAHBGBGBHEABBFBDBFBDAEEBECCCCCACHCBCHAHDGDB,False +822,16.0,25.0,27.0,23.0,14.0,15.0,16.0,28.0,BHCHCDCAGFGAGBFHEHBABGDHBABFBGBDCHCHCHEHAHEHCHDBGBHACADADAFFHAADACBCBEGEFDFDFDFCHEHDDBDEGEDHHHCDEGHCFGFDEDBBGFGCGHAHBDCECHCABHFCCHCDEDCDCGBBEHDHBGBFEFCACHCBBABCBDGC,False +823,19.0,16.0,17.0,19.0,13.0,21.0,12.0,12.0,AAFGBDHDCDFDEHBBFHFCDCABBFDFGEGEBCHDDDBDGDACAGABEGECECECEFEHCHAGDDHCCDAEFFAFBFBGDAEHHBABAHADABGBFCFGDCDFHFHAGAFAFDFBACACFGFEFECBC,False +824,23.0,14.0,24.0,16.0,17.0,21.0,26.0,11.0,EEEECEBHDFDBDCFAABFDEEGGCGEGFHDGAGBCFCHCFAFAGAGFFBGAFAEABCGAEADADAHBBEHCHCBCBCDCECGHBHAFDEDEAAACACFFECEFFGACCDCFGGCGCGFDFHFGCGCGAEAGGHHFBFDADABBCGGGDGDG,False +825,16.0,23.0,19.0,19.0,25.0,21.0,19.0,16.0,BCECEGEHBGBGDACADFFBABGGEBEGCGAGDBCFCEADAEFEDDCHCDEDGBGCFHFGBEBEBEHCHCEBEDEBFBFEFHFHFGDEAEBGBEDDCBHDFGFCACAGAHBDBDBCCFCFAFDDDADHEEEFHAEAGBGCAHHHEHFGFBFGECHABF,False +826,8.0,5.0,4.0,4.0,6.0,3.0,1.0,4.0,CDGDCFEEEEABABADAHBFBHACAFHEAEAHCBD,False +827,24.0,26.0,18.0,19.0,16.0,34.0,27.0,29.0,CFAFCHHGFDHDBDBDCDCHEFBGBGBHBDADCGCGHGFDFBAHDDAFECBFFFHFAGECAHAEBEAAACGEGHGEABAFGCEAGFFHFGACBGHGAFHCHGHGBFAHGHBHBGBGAGCFBEDHBFBHEHEBFGECEADHFHFHFDABFEFHFEFBFBABDBDFDADGDGCAEAFCFCFCDAGGFGFBHHHHB,False +828,2.0,3.0,1.0,7.0,4.0,6.0,1.0,1.0,ADDDFDFEFEDEBFBEGFDADFHCB,True +829,18.0,8.0,19.0,22.0,14.0,21.0,12.0,12.0,EGEGCHAFEECHDBDBDCFAFEFDFEGEAFCFDADADCHFHEADAEHDHCCFCFDFHFDFDACACACEFDFDGBFBCGEGFGCGCAHADACEDDGCCACHBABDBHAHFFFDDHACBDEAEGGGFD,False +830,14.0,17.0,12.0,13.0,7.0,7.0,14.0,9.0,EGEBHBDCDGECBABADDGCABACFCEBDCCADADFGHGHGFGBGBGHGFDDCDAGABACHHDHDFDCBBGBAAFACEHAGAGBEBHBCBEBF,False +831,13.0,21.0,11.0,11.0,12.0,12.0,12.0,8.0,EAEDGBFBDBCHEBEBEBCHCHAFGGBCDDDCDCBADAFAFABADFCBCGEAEDBAFAEHEHADFHBBEHEFBFGEBHFGBCBCBFGGAGAGBGCGFBDB,False +832,14.0,20.0,21.0,16.0,26.0,24.0,30.0,17.0,BGGGEEEBFFFEFCDGGGGGCGABDFGHCAFFFDFEHDHAGAGAEBEBCBCAGBBDBFBFEEEDDFCCGCGEGBBDBHEDCFCHGFEEBGCFAEGEGECFCGCHEDDCBEDDDHHHCGBGEHEHGDDCGCGBGEGEBEHECGGAEABAFAHAFAFHFHCHCFFFHFBA,False +833,0.0,0.0,2.0,1.0,0.0,7.0,1.0,2.0,GFFCFHDHCFFFF,True +834,15.0,17.0,13.0,12.0,21.0,19.0,18.0,23.0,DEFBAGHEHEABHDFGFHFHCHDHECEHBHDGDGFFCGBFBEEHHCDEFECEDEBCBGEGEGACAGHGHAHDFCBHGFFFFDACEHEBFBHBHGAAEADGGADHHHHGHGFAFCFCGEDFFABABGECACABEBEBEB,False +835,9.0,17.0,15.0,12.0,13.0,15.0,12.0,18.0,AEAFDHGHGFDEDBFBABACCCFCHEHCFEDHFGFDHBHBHEFAACHEDECFCGCBCECEGHBHCABDBEGFDFDBDBEGEFFCCGHAHAHGHDFBBGBGDGHBHBCBFHE,False +836,24.0,27.0,17.0,31.0,24.0,22.0,21.0,23.0,DCGBEBCDEDADFBFEDADADBDCDCDEDFDGBGCGBHBHBHEHEDEDAGBGFDAHGHBCECADBDEDBFFAFAFAFEHHGCGFEFDDGDGFBFGEGEBAHAFDDHFABBBDADAHAGAFFFCGGEECHGAGAEECEBFBCBHHGEFDAAECFADHGHCHBBBBDEDHBBBEHHAHCHCAEFEHADGDC,False +837,8.0,2.0,11.0,12.0,11.0,8.0,3.0,11.0,BHCHEDEHFAFHDHCHFDCDFDFDAAHCFDDADHDECECACECAFEHEGDGEHEDEHFCBCGCAEA,True +838,12.0,19.0,12.0,11.0,20.0,17.0,13.0,16.0,DEFEFEHEFBFECEAEAGBGAFEBEDFGFGAHFHFCGBBBBBBHEFEBHBGBGHCHFBCDFHAACCHEHACDBFEGEDFBCBABHHCHEHACACEDDDDFDGHGHCAGFDFBEEEGEGBA,False +839,1.0,4.0,3.0,4.0,6.0,6.0,4.0,1.0,GBEECAGBFBFBEDCDFDFEEHEDGFGFC,True +840,5.0,4.0,4.0,1.0,6.0,4.0,2.0,2.0,GEBEFEHEAADACACFCFBBHCAGEBEF,True +841,15.0,12.0,13.0,8.0,18.0,15.0,11.0,15.0,FHFHFEAAHFEFCGEHEHCHCBCAEBBBCHAHAEGFGABHBEBEFCBCAHDHBEAFGBHAFEFBGCFEFCDADBDEDEDEGEFEFAACHDHAEACGEGHGCGAGFDC,False +842,17.0,27.0,15.0,15.0,25.0,21.0,18.0,18.0,DBEBDBEEGGGBGEHCACBCBABGEDEDGFAFCCBEDCGGFGBHAHDBBHBHECACEDBDHAAFAEBEDCDCHGBEDECHAFAFECECEFHGHGHBEBGBGBFFFFHFEFHFHEBEGEAEFFAFGBBBFHCHADFDFBABCGAEAGFHDADEBHBE,False +843,20.0,14.0,16.0,25.0,17.0,16.0,12.0,24.0,HBHEDGBFBCADADACHHDHDAEAHDDDDDHFFDHDGCGCBHEGABAHEDEABACDCEFGFHAGGBACGHAFFGDCAAGHDEGEGEDABACABHFDEEBEBDBDBDHDADAHCHBEFEDEDCFCFCHCHFHFHFHFCAEHHFCE,False +844,6.0,6.0,6.0,6.0,7.0,4.0,7.0,2.0,GCECFBDBDBEGHDEAEAFFECECACBGBDADGDGHFABGEGCA,False +845,14.0,10.0,13.0,17.0,13.0,16.0,16.0,22.0,DADFGHGHFHCBGAFEFCFCGDGDEDBABABECDCDBBGAFAGAHDDDDFDGDGDCEGGFHFHCHGAGDHHHFFCGCHHEFEAHHHFHGEGDAHECDCHHAHAEAEBCFHFBFCEHBBEEA,False +846,13.0,21.0,15.0,9.0,8.0,13.0,6.0,10.0,AGBCBCBDGCBFGHABCBCBEBABCGHEHBAFAFDFECDBBAAHBHBHCFCFDBABDCDFFCGHAHBHBEBEBCFCACDEHACEBFDFGFAFAED,False +847,8.0,14.0,10.0,15.0,9.0,10.0,9.0,7.0,DECFAHHBGBCEAACBCBADDEBHDHDEDFFFGEAEBGCGBGDGDFDADBDBDCFCGCBCHABFBDEDGDGBHBFFCFEAEH,False +848,10.0,5.0,6.0,10.0,12.0,17.0,10.0,11.0,DHDEDCDFDFAFAHCFGABAGFCFBGGGGAHCFDFAFEEEEBBABHFAFGFEEHDHECEHFHFEAHAHEDFDFHFDGGGEC,False +849,22.0,14.0,13.0,19.0,14.0,18.0,13.0,19.0,AACFCFBBHBGFDADADAHHCGFBCHHFHBHDGDCAHAHABDEDBDAHAGFGEBEBACHCDEGAFFDGBHFCFDDBABAEEDEGEFEAAGAGABADAHFGFCFAAGCFHEHFGFBFEEDEHEDCDCDCDHHH,False +850,12.0,11.0,24.0,25.0,18.0,37.0,27.0,36.0,GEGEAEAEDHDEDECECGGGEFEFEGCBFBFCFCDCHEHDDGEGFGDHFGEGAGCGFDHCHFHDGCCHEBBDACHCFCHGHCHCHGDFFFFDFHGHDFFFGFGHHHGCDFBFCHHFHDDBACHEEFDCAHDHBHFFFHHCHBHFHDGFGFGBEAHFHFHFCAGGDCBGDGDFFAACDCAFDFDFBHHAHE,False +851,8.0,20.0,9.0,10.0,16.0,10.0,11.0,18.0,GAGAGFFHFHCHGHEFEGADABHBHBFEEEBAHCHCEEHEDCAGGBBDBFGFHFHAHFHBABEHEBFBCHEBBBDDDCDBECEGDBCBEBEBHBGCHEDDHG,False +852,8.0,4.0,3.0,3.0,5.0,4.0,5.0,3.0,CEHEHBGFGBABDCGAGHFDCGAAAAEADAFEFEB,False +853,2.0,2.0,4.0,5.0,2.0,8.0,1.0,9.0,BHFHFHFADCCGFDFDBDEFAHHHHHFHECCFD,True +854,0.0,3.0,1.0,7.0,1.0,4.0,3.0,3.0,BGEDFDHDHGFBDBCGHDFDFD,True +855,13.0,9.0,23.0,8.0,13.0,14.0,12.0,14.0,CFCFCGHEACCCEEEGDHHAHBGBCFCDCDCFFGCAFDCABHCHCDFFCECGCGCAABFDEDACCHHAFAEBEBHGHBHFGEGCGCGAEBCBAGEFEFEFDHAHAH,False +856,10.0,14.0,21.0,25.0,13.0,22.0,18.0,15.0,HDAFAFDFBGDDCEEGEDFGBDBGCCCCDDDGDGHFDGHEFECHCHCFEDBDBACGFBFBFDCGEGCABABDEGCGCECEBAFGHHBDDDHHHGGDCDCACAFBEBECFCFAEHHFFFDGDGHGHDDFDFHFCFCBAF,False +857,5.0,7.0,6.0,6.0,3.0,6.0,3.0,6.0,HBHCDAHAFGBACABHBDBDEFGCHCHCBEFEFGFCFDDBDA,False +858,5.0,6.0,10.0,9.0,8.0,7.0,3.0,10.0,BGCHCHCBDDHDGDGABCBABFECECECDCDFHHCEDDFFFHHEHEAEAFHBEDHCAF,False +859,5.0,3.0,3.0,10.0,1.0,2.0,6.0,6.0,DADADBGHEADDDCDGHGHGCDCDBFAHHFHAGDGB,True +860,23.0,20.0,27.0,31.0,27.0,21.0,22.0,20.0,GBHCDCFCFDEDHCHGEFEFECCCCCADABAHFHFHFDGDAEEHACDDGBADFDEECFAFCFEGCGEEHFAFEFBABCDADEDEHBHGHBBAECECGBHAGFHHBGECCDEDBFHCACGCDAGAGADDDDDCDGFCFCEEEDEBHGHGHGCGCBDADHBGDDEDABABAEDEBFCDEBABGBDAFAFGEGH,False +861,7.0,7.0,14.0,4.0,11.0,5.0,11.0,5.0,GCGFGBGCCCGFAAEAECECECGBABHHCAEAHAEFEBEHDCDCGFGFBCGCGCDBEEHDGECB,True +862,12.0,3.0,10.0,5.0,8.0,8.0,5.0,6.0,GFCAHAHAGACCEHDBBAAAHADECEDECGCBCECFCFHFHAGGEDEFFCFAEAFAD,False +863,24.0,14.0,29.0,24.0,18.0,18.0,12.0,25.0,ACACHBEBEDABHBGCDCFCEDFCGCACGFADCCCCBCDEAEBDHEEGAGCDFDFDFGEHAHFEEAEHCCFHFEFCHCHDAAHGDCDAHFHEHDHDHAHADEBEBEGADAHEBFHFHACGFGCGCBCDCDCACFCFABCBADDBCBHHDHGAAHAHFFDHDEDA,False +864,12.0,14.0,8.0,8.0,15.0,8.0,10.0,15.0,EBEBGHCABAFAFDFDADGBHCEBGBGBCFCAEEDHCHGHBHDGDHEHEHEHCFGFBEEHAAAHGHGEGBFCABHFHEEBADCDABEBEA,False +865,3.0,2.0,2.0,3.0,0.0,3.0,0.0,4.0,BHDHBCFDFCAHAHAFD,True +866,5.0,8.0,8.0,6.0,13.0,7.0,15.0,8.0,FHCDEDADBEBGAGCCCEBGGFGEGEGAGAGHDHGBEHEDGAGEBECHCGFEEHEHGGFBFBFCFHEBCD,False +867,15.0,8.0,10.0,4.0,10.0,7.0,12.0,11.0,GCHHEHGBDBCGCBCFEAAHAHADFCFCFGAGAFBGAHAEGFBECEABHCHAEAEHGHGFBDCHGEGEGDACABAEA,False +868,13.0,19.0,24.0,20.0,14.0,16.0,12.0,20.0,HCHAHAGDDCDBGGHGHGCEEAEGFBFDEAEFCFHDHGFAFGEHDBDBDCECDFECHCDCFCHCHBBBBGAFDCACEDBFFAFAFBEHCACDHBCBCBHBCADDDBDHDHCHCBABHHEFGAECGCGCBDBDCFHFEE,False +869,11.0,10.0,12.0,15.0,14.0,12.0,10.0,5.0,CBGECDGDGDADCGAHDBDFFFFEAHFEFDBDGDGECECDDFDADBEACGFEBEBECCCGCBCBEAEAFGBAAAEDEGHHDHCFAFEFB,False +870,8.0,16.0,15.0,5.0,12.0,6.0,10.0,5.0,GEGAAFBCBCEGAAEBEBEFHHCBAAGACBBBBEBCGCGCECECBABCFCGCFEDEHCCDGBGFDFDEHCHBBGBDE,True +871,7.0,10.0,13.0,4.0,10.0,7.0,7.0,8.0,GAAHGCBADEDHDCCCACAFHEBBBBBCBEGEGFCHCBEGEGEHDHCFFABCFCFHGHABFECECE,False +872,5.0,6.0,11.0,4.0,5.0,6.0,7.0,6.0,FCCCACBDAFCCCFGBBHBGAGEGDGCGHGHDHDEBHCCFCBAEFEFEHA,False +873,6.0,3.0,2.0,8.0,3.0,5.0,4.0,1.0,AADDDCDCGGFFEBADADADEDGBGFFEFAHB,True +874,16.0,16.0,9.0,13.0,16.0,16.0,11.0,18.0,DGAGHBHCEFGDAAEAFAFBBDFHEDEDHBHGHGHDDEDFCFCAAADAHFBCBCGEHEBFDFAFCFAFAFBECCBEDHHEHEGBGCDFGFHHHBHBEBEBHAEADBEBAAGEGHF,False +875,10.0,10.0,11.0,9.0,10.0,8.0,13.0,16.0,AFADADEDEFHCHCFGBGEHDFGHCHEGBGHFABHEACHBHBHBHGDGBAAAHAHCHCGGGCGEDEBCDDGBGAECEFFFBCHCHDE,False +876,10.0,18.0,8.0,11.0,7.0,15.0,11.0,9.0,FCHDHBFBGCDHAGCCHDHAGFFHBHEFAFAFDBBBDBDEACGGGBGFECECACHDBABFBDBDGEADADFFFGEGEBBBFBFBGBFAH,False +877,4.0,5.0,14.0,13.0,6.0,8.0,11.0,11.0,ACACGHADGCECGGGDCCCFCFBFDFDHDHDADHDHFFBHGHCHCGCDCDHDEEBGFDEHBHGEEBDFCCGG,True +878,22.0,17.0,15.0,16.0,16.0,19.0,13.0,15.0,CCFCHHDBEGEGDCFHFBAGFEDDFDCECEGBCBABADADBGGDBACAFAEABHHHFHCHDBFBDBDBEHHCHCHEEGFGFHAEAEAEADFEAABCFCEAHFGAAADFDFBFBEGCGCDAFAFAEDGBHBGFA,False +879,11.0,12.0,5.0,10.0,10.0,9.0,11.0,9.0,BCBCEAFGFGHBHBHDDFEFGBGHGFBDCAAGEHDBDGHGHFADAEEFEDEDEAHABABACAGHEDFAGEDBGBCBF,False +880,22.0,23.0,20.0,22.0,17.0,22.0,27.0,22.0,AFEFEHDHDHDBFBGBGEGBGFGFGEHEABABGGGABAHDHEBCGCGCFCDBDFEEAAAFDCBFHGHBCGAEDFDFDBCECFBAGAGAFEHGGCGDBBCCGBDDCDBDCFCAHDBAFFHCHDHFHCEEDHDHBHCCBFBAEAEAFGDCDHAHFHEHADAGAGAFBGCGHGFBEGG,False +881,26.0,17.0,21.0,13.0,20.0,12.0,23.0,19.0,BAEAGCGHGAEADABEEEGAAHHDDBDFGAGACCHHEHEBFBHEEEDFGFEAGHCCACGEFEDCGCHCGFHHBHBGBCCCDCGBGBABABFDDHEAEFEGGGGEHAHACACDGBGBGBEAFACEHFAAAHGHGDCCECFCBCBHDAAAFAD,False +882,1.0,1.0,3.0,2.0,1.0,1.0,0.0,5.0,DHHFADEBCHCHCH,True +883,7.0,3.0,8.0,7.0,4.0,4.0,4.0,4.0,GDEDCFHFHDHDEGEACDCABBGFACACGCFCDADBCAEAH,False +884,21.0,12.0,14.0,11.0,9.0,9.0,15.0,13.0,EHEAEGDDAGGBGFFAGHDHDCDCDCFCGGGGGAAEGCHEDEAEFHFAFGCBHBCCCCADBBAGAGHBCACAHAHBFEDBGBCBEDDHHABAFAHAHFBCAAAA,False +885,16.0,26.0,24.0,20.0,25.0,24.0,19.0,20.0,DFDGGAEAEAEDHGHGCCABBEECFCFGBGBDCGFFDBDECEADADHGHFDBDCEEBCGCGAFBFBCHDFDFEFEFHFHFHBHFEFHCHCBAFDFBFCAGAECBBBBEAEBGCECFHEHDCCEGBGBGFGFHHEHCHBDACECABABDBHAEDDCGGBBEFDFDCBAEHEHECG,False +886,13.0,28.0,17.0,8.0,23.0,25.0,17.0,16.0,GFFBFBHCFBBBCGCGEEBCBABFDEBGBGCACEHFHFHBADDCGEGEBHAAACFCEHBHBDAEFFFFDFDFEFEFECEBBBHFGBBHBEGCBEAEDCHEEEFBGHGECEHFHBABFCFCFCGCEAGDGAGAFBGGAFHHHBEBEBF,False +887,12.0,16.0,10.0,18.0,15.0,11.0,14.0,8.0,EEHEFGDCAFDGDCBFBFGFBEAFBBBAGFGBGCHCHCAGADCFCDBDEHEAEDGDBHBFGEBEBDBDADCDHDEABDDEDFCAGDGAGAFDEAGCGBEBEHEH,False +888,18.0,13.0,17.0,15.0,11.0,10.0,18.0,15.0,DEGEDEFAHAHAHGHGHGCGCFDDDADFCBGDGDCBABCBEACAGAGCEDBABDHFGAGAGDEEHAFCDCBCACBEBHCGBFAHAHCDFHBGBGHFHGHFBACEGEGCHAECFCDAD,False +889,22.0,5.0,11.0,9.0,14.0,19.0,10.0,13.0,HEHFADEFGFCEHEFDFHFAFGGGGAGAFADGDFAEAHBCECEDFCFHFCFDFDAACACABBFGCHEAAABCDHEAEABFHFHEGEFHAAAAACAGDHCHEFE,False +890,27.0,36.0,17.0,27.0,26.0,14.0,25.0,25.0,FHDGFABEECADAEBECEABAGHECDCDADGDADADEHEHGHBFBCBGDEEEEEBABABHBHAGCEDEDEHAHAGGCDCDHBABHBCACAGFCFGHHFDFDGBGHGAGCGFFBHADFCECEHBDBGBABACAHEBBHGHEHBBEDEFEBGBDBCGEDBBBBBEBDHDBAHGFGAEBHAADGHGDABFCFDAGBGDHD,False +891,18.0,15.0,22.0,14.0,25.0,27.0,18.0,19.0,FHFHEHAHCFEDCDHFFFHCCCCCCFAFGEAHAFGGEGEGEGFGFAEHDCDFHGAGEBHFHCHBHBEDHDCFCACGBFCDDEHBCEGAFABEBFDEGAFDCACFEFEDEAAGAGAGCBCDFEHAHEHBCBCBFBEEFEHGGGCEFEFEBEAFFBDADB,False +892,15.0,15.0,17.0,14.0,25.0,21.0,15.0,21.0,EGAHHHDHDFEAEDEGGGGAGFHFAFEEEHHBCBGHGBGDFAAEAECEFEDDBFCFCAGFFHFHFHBCFCDHFHCHADBHFGFGBEBHHEEDDCDGBCEEEBGBHEHEDEAFCBCECEBGAAAEDCDCACABEHHCFEFCFBF,False +893,5.0,2.0,1.0,1.0,3.0,2.0,5.0,2.0,BHAHAEEEGFGFACGBDAGAG,True +894,1.0,2.0,2.0,3.0,4.0,6.0,4.0,3.0,FCFCHHEFEFGGGGHDBEBFAFDDE,True +895,12.0,25.0,10.0,17.0,18.0,19.0,18.0,17.0,CECBHFGFGEBBHFEFDBDBABDGAGAEABCBGAGAHCEEHEHEHDDCDBFHFHEDFCFBFBFAGGGGGFGEHBBBHDHBHDEBEFGDCBBBDBGCAHHEGBGBCDFDEEEDEACAFFGBBHFHFDFAFHGBADED,False +896,16.0,8.0,11.0,13.0,10.0,11.0,7.0,7.0,GEDEHEHBBDADFDADCDCAAAHFHFGFECACAEDCDGAEAEBBCBGEACAHDBDEGFHFBCDCFAADACBCHFAFAFEGGDF,False +897,11.0,6.0,9.0,7.0,10.0,14.0,15.0,10.0,HDBFBGCFCGCGBGDEDGHAHGHAAFHFCGBGCAHHGFCFAFEBGHGBDCHCHDEEFEFEAEAEFEFGDGFAFACGEFDAGA,False +898,17.0,13.0,21.0,30.0,28.0,20.0,12.0,19.0,EDDBGCECEDBCBCDHGFECBGBEHHHEHFHDGDHHAFAHCHDBEFDADCDHEEEHEGDGDGFEDCACEDEAEAEFDFDFDADCCACFEFCFEFCBBHCCFEEDHDFGEGAFCFCACABABCGDEDAHEDDDDGDGFHDHDABFCFDFAHEEBEBEHEAA,False +899,3.0,3.0,2.0,3.0,3.0,3.0,8.0,3.0,BCEFGHGHGAGBGBGDFDCHEGEFAADG,False +900,16.0,24.0,17.0,15.0,11.0,13.0,13.0,18.0,DDCDADAECDHHHCHADDHCHCBCADAECGHGEAHFHGBBHDADAEHHFHGACACFCFBEBEDCGCGBBBBGEFFHFBBGCGBABABAHFEFBBECCHGFDFBFAFAHBBEBEACDGDGCBHBGBDB,False +901,25.0,30.0,29.0,16.0,34.0,19.0,24.0,19.0,FFGCECEBBBCDCBFEEEECGCABAFEFGHBDAACECGHDFCHBFBGGGBGHCHCBCECBGBEFDHBHBHCHAHAGABABGEGFCFBEGEBBCBCDHHHCHCHDBDCFCAEDHGAGEBEGEBEDEFFDBDEFBCEFEAGGFGEGFBFHHACACAEAEAEBEHEBAGAEAECGABADDDAECECFAAEDDAGCECBG,False +902,24.0,23.0,19.0,24.0,26.0,27.0,19.0,14.0,FAAAEACAEEEGEDAHEBADAGGHEDCABGFFDFDFEBEBEDEDGAHFDGBCBFDFGECFBFGFBFEFCFEDADBEFEFACACACAHADBBBEHAHBGBFAGBEEGGFGCGCFAFDFEBHGCAAGDGFHFCFCHCDCBFBGBCBEHFHCHCBEDGDACAEBDBHFHEDDDDDEAED,False +903,29.0,29.0,25.0,18.0,19.0,26.0,26.0,24.0,GABBEDADAGFHBHFHGCBCBDADGBGDGHEDBGBGDAEBEAGFGACEBEDADFFFBBBCFCGAFAHEHEHGBAAAAAAGGCCHBGBABHEEFHFHAHFBGCHDHFEBEGEAEDFGCHBHACADBHGDGCEDFFHFEFBCBABAHAEAGGFFCFAHADGDGCBCBCGCGCBCBCFHEHDFFEFHFCFABCHCDCAC,False +904,6.0,3.0,10.0,6.0,5.0,4.0,4.0,1.0,ACGCFCACDCHCDDDEDCGGEFBCBCBFGFEEAEDCAAA,True +905,3.0,18.0,9.0,11.0,14.0,16.0,4.0,13.0,DCFBBCBEBDBFFEFDCGHBHGDCFBFDEHEFBHBFEFHFHFGCAEHFAFBEHEHEHCACHGFDCBEFEHEBDBDBHBDEDEDBCBFB,True +906,16.0,25.0,37.0,22.0,24.0,10.0,28.0,28.0,DFDCDCEAEHCHEACBHBGBHCCGCECADDDDDDCHHHAHCCCGDECECEBECHCFCFBHBACGCBABCBHGEBBBHGHGBCBCDEEAAGAGDHFCCEDEDGDGDGBGHHDFFGEEBFAGHGFCBBGEHHBCBDBABCEAGACACGBEHEHCFDHAHEGGGHGHGACEDECHCGCGCDHFHBEGEDBCGC,False +907,25.0,18.0,28.0,21.0,19.0,32.0,30.0,20.0,GCGCEBHGCGCEDDHHGCCCCGHGHDHEHACGGGBGFGBEACGHGCFDFDCCCHCFDFAFAEAGABACAGACEBHBFGFBFBDHCFAFGFACAGDEHCDBGHAHBBDFDFCFAEBDCGFAHGHGFGFGBADFEFHBDADABBEAFHDDFDFGBGDEDEFAFEFEFGFAFDFEFCACHFHBEEECGCGCAAEAC,False +908,28.0,27.0,16.0,15.0,23.0,29.0,25.0,24.0,FAFEFGFBABHFFBHDCCGAABEBCACAEFFCFAGAEEGEGFGFDFHFHBAGFGBGDHBHBHBCGEGFAAHAHAHAEGEBEAHABCBDFGFGEGBFBHBDBFBFGFGHGHBEBEBDGHGFAFCHADEEECECFBACCBCDDHGGEHEGCAAFAFBDHHHDHDFDADGFAAEAFABEECGHHDBEACB,False +909,22.0,23.0,20.0,21.0,31.0,23.0,29.0,28.0,EAGGGDCHHHHCDDEDBCHAEDGBGAGADBHAFFHGBGBDEGEGHGAGDBEGAGCCHFHFGEGHHEAEBDDDDADHCBBBCACFCGAGECEAEFEGEDDAAEFEHBHBGBFCFCHGBBDBFBFDEAEAEFCDDEGFGFCECAGHGFGFEHHDAFHFHGHGHFHFEEEHAFBBBEAECGCBCBCEEAHACBFDFEHEH,False +910,35.0,20.0,17.0,22.0,15.0,17.0,23.0,20.0,BABABADGDFFFFFADHEEAEHCBGBGDGEGCACHEFAAHAHAHBHGHBABCBCGCFDFAFCFCEAEHEDGFGBAAADBGADADBDBECGGFCBDBHCAADAHAGADCGFGFGCGCEDAAEAHDEDBAGFGBADDDCDHHHCHAHDEAHGFAEAFBDHAGAEHBBGCGA,False +911,20.0,22.0,16.0,16.0,19.0,34.0,24.0,21.0,HHBBFFAHAHEFAFCDBDBDGCEEBFBDCCBCHDFAFDBDBFCFAHGEDBGFFFDFHACEDGDBFBFCECHCHBFAFADAFFFFFFFGFBHGHGHGHAFABACHCFGGGAFHFHGGGGFAFEEGHGEEEGECDGECBCBHDGDGHEHDBAGEBEAEABABFEGACHEBGFAF,False +912,14.0,22.0,22.0,16.0,10.0,16.0,13.0,11.0,GABHDHAHACDCBFFFECHFHEBEGABCEHEBBFBACHCHCACABEFFDBACDHFADAFBFBGGCGCGCHFBFCGDFAFGBCBCBDHDGDCBCBCGDGCGAGABCBCACEDFDEEFBBDDDEDB,False +913,20.0,27.0,29.0,23.0,22.0,31.0,29.0,18.0,GFGEECFDFAGEFHFACDEGCGCGHGHDHDCGCFDBAGAGAGDGHFDFBFGFGAGHDAGAFABDCFFECECEFFDCDCBCGDBABFFHFDDDGACHHDBEBEBFCEEBEHAHECBABGGAGDHDCEEGFCFBDECACAFHFAFACBEAGGGBGBCBHFCFCFCFCHDFAEBBBHBEBECFCHEEGBGBFCDBDBDBHGC,False +914,12.0,9.0,6.0,2.0,6.0,6.0,2.0,13.0,BFBHEHEHBADCHBAGFHFEBHAAACABHBHAAACECBBACGCHFHAHAHEHEFFD,True +915,10.0,12.0,24.0,13.0,16.0,14.0,13.0,16.0,CEBDBDBDCDCDCDBDAHHBFBFCFGFGEDFHCBCFGECFCEBEBHBCCFCFDFEHAFBHAHAHFCACHCECEHACBCHCFEDEAGACDCHCGAHCDEGGHEEFHAGGGECEGEHDGG,False +916,4.0,4.0,9.0,4.0,6.0,12.0,3.0,4.0,CECDADFBACFCFDFBFGFCFGHCCGBEHEHEHEFFCACBEFFFAD,True +917,15.0,18.0,12.0,11.0,16.0,11.0,18.0,15.0,AEAEAEAEAHAHAGEEFHGHBHBEDABABADHGFGDHBCDDFHGBEFFFAFGGHBDFCBEHECECGFHBHEEGDBEGEBBGDCDHDCACGFGHGCABABHFACCCCBGBGBGDGBE,False +918,14.0,16.0,12.0,30.0,16.0,18.0,12.0,16.0,DHDAEBFADADADADADGDFAFHFHDEFGBGBGBGFHCGEHECEAACACGCDDDFEBEBHBFAFHCDDDDFCFDFGHCFDHEFEFDCHBBBHAEDEDBAAHCEFDCDBDFDBEEDBDHEBDHDGFHDHEGGGCB,False +919,5.0,11.0,3.0,9.0,10.0,8.0,8.0,5.0,BFBHEEEBCBHEHGAGAGDDBDEEEHABFCFBAGDCDGDBDGAFEFEFDBDGGFBFBHE,False +920,5.0,0.0,5.0,4.0,1.0,1.0,4.0,2.0,CGAAFADHDCACGCECGDGDHA,True +921,24.0,17.0,18.0,26.0,23.0,31.0,24.0,25.0,EDEDCDADFGBABAGGFCFDFEGCGBHHECEADGDEDFDFDBEGEFCAGFEFEFDHEADHCHAHFHFHEGEDDDDBGEGEFBCDCEAAHDBAGHDHFGGHEHAHAHAHFHFDFBGBHCGAGFEFEFADACAFEBGCCDBEBADAFBGCFAFCHCHAFEFGCGBGCAFABCDAFBFBHDHFHEGDGHFH,False +922,12.0,3.0,17.0,8.0,6.0,8.0,19.0,16.0,GDFCHCHAADGBHCHAFEHCHCBGBCHFACAFADGGGGGGCGCAADHEHECEAEDDCCEGFGFGAGAHHGHGCDADCCHHGCGFHFHGC,True +923,13.0,7.0,15.0,17.0,15.0,11.0,14.0,5.0,GDDDHCCBCDADAEABADADGHFDCCACAEAGGDEEEDFHFBDGCHBFBFDGGBCDDDFCFCFEEGCFEFADADACAGGGGEGCCAEBEHEGEFECE,False +924,19.0,22.0,14.0,20.0,28.0,12.0,19.0,18.0,CGCDHBFBHGEBEADBDGDGDCBCDCHCEBHGEGEHEGDFFCEAEDGCGEGFDEEEEEBABCBCBCBCBGFDFAEAFDHDHEHFDAAHHHHEAEADAFEFEDBABDHEFEAGCBBFHDHBHBGBADHEEDBDEGBAEAGGCGHBEGGAAAEA,False +925,20.0,23.0,18.0,19.0,19.0,27.0,21.0,22.0,FEHEHEGDGCBDBHBEBCAGACHFEFHAHADAFGBGFFEGECEHDGDAHAHEDCCEAGFDFEGCCBGBFBFHDADCBCBFBCCHBHAHBDCECDFHFGFADCFFFFBFADBGGHADFDBBCBGHHHEHEHBAEAEFGBHBHGAGEFEFGFGFDCDFBFACAGAEADGDB,False +926,8.0,4.0,5.0,5.0,6.0,5.0,4.0,8.0,FGFDECECEADFBFBHEHAHADAHAEACGDADHHHBHFACBEGCG,False +927,4.0,9.0,2.0,4.0,9.0,4.0,11.0,2.0,GHGBGDGBGBEAGFGBBBBDDEBGFGEGEDECEAEAGBFCEHFAE,True +928,19.0,13.0,20.0,26.0,25.0,21.0,11.0,20.0,DDDFAGCFCHADFCCECECFBEHDBEBEDEHEHCFAEAEAEFDFBFADAEAEAEADHDFDFGBGBADEDBHCGCFCBEEAEHECFHAGACCCDDEDHHHHAHDDDACGHBACFCFGDEFEBHFHFCDDDHDACECBDHGHEEFGBGFGFEDHFBA,False +929,31.0,26.0,25.0,22.0,30.0,19.0,16.0,16.0,GADBEEEAEAHACCCCFGFEHBGBGCFCFDDADGBAAAFEFAABEHADFDFACAHBHGEFBAAACFCGABEGFABGFGEGFBFBEBFDEDEHGFEECHAHADADADCHEHEBEDABHBEACADBDBDGDGDCDCACHEHGCEHDCEABCFAEDFDGCEBFBAAEHEDEBCBCBCBCBEEAEBCHC,False +930,5.0,6.0,16.0,9.0,2.0,8.0,6.0,8.0,FCFCBBGDGDBABHCHCGEBEDDGACFCFCFCHCGCABHCCCCHFHCAGFHHCAFDDDDD,True +931,13.0,10.0,13.0,5.0,17.0,8.0,8.0,11.0,AEAEAHAEECBHBHGHAEBFCEEAEBEGCHBFBGEGFACADAEGEDBFCCHHBHBHFHCGEGHDDCDCACAEAFBCGCFEFECEA,False +932,13.0,15.0,7.0,16.0,20.0,10.0,5.0,18.0,AEABBCHEBEHEFEDEAFBHBADFHHDBDEHBABABABACDCFEFHFEGGACEDEHEBBAFGHCEDEDBGCHHDBDBEHCHDADGDEDEDHFEEEAHAHFHFHD,False +933,4.0,6.0,3.0,4.0,2.0,6.0,4.0,5.0,AGAGAHBEEDCGBGBCBDFDFDHHAFBFHFCBHF,False +934,5.0,12.0,3.0,2.0,5.0,4.0,9.0,11.0,CEDBABACFFGFAEAGCGBGHGHBHGHEBBHBHGDFHHHHBEBEAGBBBGH,True +935,8.0,6.0,1.0,11.0,7.0,1.0,14.0,7.0,GEBHGHGDBAEEDAGGEGDGBGBHHHHDDAAAAGDGDGDADABCEGEHEDDFGGB,True +936,12.0,13.0,17.0,16.0,15.0,22.0,16.0,19.0,HHEDDDDGDGAFACACHCFEEECACADBGHGFFFFFFEHEHCAGBDFEFDFEFEHEFFBBABFCHEGFGDHBCBCBEEAHCCECDDBFBHCHFHFHDEDGGGDGBGHCBGAFDGDGCAHBCCHGHFHFAA,False +937,3.0,4.0,1.0,4.0,2.0,0.0,0.0,2.0,ADDEDEHBHBACADBB,True +938,5.0,10.0,7.0,7.0,2.0,7.0,13.0,13.0,FCGGGHHAFEFBFBGBABAEGGGGCFCFHBABHHDHDHFHACDBBGHGDGDHCBDHCHGBGDHC,True +939,0.0,2.0,2.0,0.0,2.0,1.0,2.0,1.0,CGEGEBFBHC,True +940,15.0,12.0,17.0,12.0,18.0,16.0,21.0,10.0,DADACBCEGEGCCAHFCDCDAEACDCFGDAEBEBEACABEGGGABACDFDCGGFDDHCGFGEGBCBDEDGHGFEFBFGGCBCEEFAFGFHFAFHGHGCEFEBHBHGEGEGEFAFAHACBHE,False +941,21.0,9.0,18.0,19.0,23.0,21.0,20.0,26.0,EGEDHBHBHGHGHCEAAGBHBDDDGGGDGFGFEFGFGADHEFEAEAFAHAEAHBFECDCAAGDFAFHEHCCDCEFHFHFAEAHACFCFCHCECEHDDGDHDHDADEBHFEGAAEAFBHCCEGGDEDBCHADAHFBFCFCGGEDECFHGAGHECEHFH,False +942,23.0,23.0,25.0,23.0,16.0,18.0,18.0,24.0,CAHDBDHDEGCADHGHGHGHFCDCHCDFGEDEDHDHBHFDFEEADAEABFFGFGACFBBCFCBBFAHCHCEEDCCFHACACABHBFFFDFECACHHEGDGDEDBHBCBHBHADABHBHBCGHACBCBEBABCGEEFEAEAGGCDDDDAGAGAHBHDGBCFGFDCAGACAB,False +943,9.0,5.0,6.0,3.0,2.0,3.0,4.0,6.0,DBDHCFFHCEAEGBGBGAHCHBBAGFCAHAHACADACA,True +944,1.0,5.0,5.0,2.0,2.0,3.0,5.0,5.0,EGGDGHCBBAEGHGCFCFBHBHBHCFCD,True +945,23.0,12.0,17.0,23.0,21.0,25.0,31.0,23.0,AHAHBHBHCHCEDDFCACDCDFGFBHBCCGFGHGAAHDEEGECFAHAHFHDHEADFGCGCGFGEADBEAEBEDDBCBHAAFAFAFDGDHABAEHDHGEEEHDADGFGHGFEFGFCFAFHFEFADGGEGEGECFDHCHDFGHGDGCAAGAGEGFDBGCEBGBGDEDHFFCFGAGDG,False +946,7.0,6.0,9.0,5.0,3.0,13.0,9.0,7.0,BEBECFHFHAHGCAABCCFGBGFFCFGFBFDFGGAGHGFFFFDBCGHHCHCDDADAEAC,False +947,12.0,14.0,22.0,9.0,8.0,15.0,19.0,16.0,GGGGGADFDBBBCHGACAHBFGHGHGFGCCFDACHGHEFFBCBGEGDGFHHHBHDGDCCCCGBFHACACECDCFGBHBHBCEFECHCBCBCHGFGDAAAADAEEFCFCACFFEHB,False +948,23.0,29.0,24.0,18.0,9.0,25.0,25.0,32.0,BBBHGFAEAEBEBCFCFAFAFCFDFBHBGCHFAEGDACAGBHCHFDBCBGGCCBBHHABDCFGHBDCDBDGFBCAFAHHGHFHEHACEGDABGBGHABABGHHHFBFCFHFABAEAGACBCFHHBABCBCBCACFCHGHCHBGBHDDFGAAFFFEDDDGDHDHGHGHGHDHGHGHDCDCGFGFEA,False +949,7.0,6.0,5.0,7.0,7.0,6.0,6.0,12.0,HHCHADDCGBGFFHDHBBCHCHBFADAEAGAFAEAHBHEEEEHHHBGDGEGCDFDF,False +950,24.0,23.0,22.0,11.0,20.0,30.0,30.0,14.0,EHFBFBFBCCFCAAACEGBFAEEBHCHFHEAEAGBGHGHGCGCFEFAFBEAGAEBGDGCGHGHBBGBGBFBFDFECAGGFEBEGCAEBEDGHAFBHBFBDGDGFGDACCGCECACAGFCECHDFBCGCGFFFGFGCBCGABADFBHGGFGDHDEFBHCAAAAAAFFFFFDEEAE,False +951,16.0,19.0,15.0,15.0,20.0,28.0,15.0,17.0,DGGFECEHGHFHCBCEHGDGCBCGCEEFAFAFAHEHFAABHEGDGAGBGEEBHDHBBCBCHFBDBDBHEDFCAEAFFFDFDFAGBCBDECFFFEFDFBFGFGEECECEFEFEDHGCDAHAEABBDGFBFHHBHDAFHFCFAFABA,False +952,9.0,0.0,6.0,3.0,8.0,5.0,2.0,3.0,EFACCCFAAAAHFFFDGAAEAEHGHECECEDECEAD,True +953,2.0,1.0,1.0,1.0,6.0,2.0,3.0,1.0,ECEHDAAGBGEEEEFGF,True +954,11.0,9.0,7.0,13.0,13.0,4.0,8.0,8.0,CADHDHDFDABBEACAFDBBHFHGAGECBGEGEGEBEHEDEAHBGDADADADFDEBEDDCAABHEHCGEGECC,False +955,17.0,19.0,17.0,18.0,12.0,19.0,16.0,32.0,GFGFAAGFGAHADGGHGEBABFEDBHBDFHHHHBGBHDHDEAACBFBFBEAEHCDDGDFHHEDGHGBGBGADHFHDHCCGAEACDCDCAHAHFHFHFHDBDADHCCCHBACACBHFHFEFECACGEBBFDHCHDHBHEFGCECHFFBHBH,False +956,21.0,23.0,17.0,24.0,20.0,16.0,15.0,22.0,DADEHFHDCBCBCAHGBGFDFDGBAFDFDHHFDBDBACACFEHEAEAHAEEBAGCHCFCFAHAGDGDADADHHGHGECCFCFGFCHAHGDGBCCHADBDEAHGCFBHBHBHEEEEEHEBEAEGDBBFBHHCDCEBBBDBDBAADGFABADFEEGEDDB,False +957,10.0,10.0,8.0,10.0,12.0,10.0,10.0,2.0,FGFBFDFCGGFGABBBDGAAAFHFDGDBDGDEDECECECECGBAEHECGDACEBGBDFCAEAFFEDEBABAE,False +958,23.0,37.0,29.0,27.0,20.0,20.0,23.0,19.0,ADBDBAFABHBADGGCCCHFHGBBDDCACACBBAGDHDHCHFECBHFEGEBEDCCFEDEFBFBCBCBHEHBGDCDGBGAGAFFGCGEGAADACADBGFEDGBGFDBHBCAHEEFFDCDADBDBACDCDCDBHBHFEFHFDBGBGEFHFHBACECEDEBCBCBCGCGBBACAGEFBFBABGDGDHEHEGBCDCBHEAAA,False +959,12.0,18.0,18.0,8.0,12.0,10.0,17.0,15.0,BEBEBGBGBHBCBCECGCGCDCFGGHGBCHEACCCEFGAAAEHBHEHBGBHAEABHGFCFCDCEABACAHEHCGCHFEAEGDBDHDCGFDCDAHBHGFDFGGGHFBBBAF,False +960,6.0,8.0,14.0,11.0,10.0,8.0,6.0,15.0,EADADHGFDEEHFHDHBHBHCECDFDBDECHFFAFGFBEDECBCECHHHHGCGDGDHCCCCCCEEDHHAHABCGFABB,False +961,20.0,29.0,25.0,20.0,25.0,26.0,26.0,18.0,BHBEFEABGFAEGDGDFFBDHDGBGBFFFHEEEEEDFAFADABGGCGCBCBAFCFABCCHEHGDDEDEGFFAAEEEEAGCGAGHGFDCCBCHGACACEDHGHGAFBFBFAHEBEBEDGBHCCEAEADDDHDCBCFHAHCHBHBFBFBGGGBHECGFGECBCBCDHDBBFDCACACBFGFGEGCDEBFBF,False +962,27.0,19.0,27.0,18.0,20.0,32.0,29.0,28.0,GEGECAFAHHHHEAEBDBDCHHGHFEFHDBFAFBFDGDBCBCGHGHFCFCFCFDEGADHHCCADADAGEHEHGACCHGHBHEHCHCHFECGCFAFBFAFGFBCAEFCDHAGFBFHGEGAAHGFGEDEACDCFHDDCDCFCHCGCEDGHBDAAFAGBFBFHEGAFACADEFEBEGGGCGCBBFBFGAGAGAFABAGFBEHF,False +963,18.0,20.0,27.0,19.0,14.0,17.0,15.0,25.0,FFACCGCGCDDHCHCDGGGEHFBCBHFCAAAAHAGFGDGAGDGHFBDEDHCBCACACGCGAFEBBCECEAEHEHBBCHHHHAACDCDBDFCFBFBHCHBHDGCEEEHEDGBBBFEFHFHDCDBDADAHFBCBABDCEAHHDACFCGHBHFHDCFE,False +964,12.0,10.0,8.0,9.0,12.0,10.0,10.0,9.0,FGFAEAEAGADFEECEHBBBAHAEBECECAGGHBAAGEHFHDHAEFDFECDCBFBFBABDDFDGGFGCCCEHAHBHGDGD,False +965,17.0,22.0,24.0,31.0,26.0,22.0,22.0,27.0,CGCEHFCFCEBDBDBEHEHGHGHFABABHEHFBEBGHDHDFCBDBEBGGCHCFDFHEHDHDGDFFBCAHAHGEEFHBHBEBADFFAFAHDHGAGAHEDDHDEBEFEBEFHFHACADDDFDEEEECCCDAGADBGAGFEHBGGHDCCCDEDGHCECDDABFBEBCGEGCGCFCDCAAEDCBGHGDFDGDCDF,False +966,27.0,18.0,26.0,14.0,26.0,27.0,37.0,24.0,AACDCHCFGHAHAGAGACFHEHABFHFAGHBCBDBFBFBABFHHHFHFCEDEFACHCECFGFEFECGDGHGCGFGEHECDCBCBGBECEDFAEECAGGFAFBHEFDGBGEGHFEEGEHCGEGDGDGDFCCCCHBAEACHGHGAGHGAGEHEGEGBCAGGGFABHDADADAGAFHBEDCFAEECFGFGFGCGABEFGABA,False +967,19.0,30.0,23.0,20.0,26.0,19.0,25.0,21.0,BBABCBGGAGFDFGHDHEGBGCGBBAFDCBCEFHDCDFBCBGEFBHBEEEEEBADAHAHBGGGEDBFBHCCCECBGHDHDFGBDCDFBEHECGBGBGFCFAHEHDGEGEFDFDECCCHCHEGEGHGBCEAGABEBABABABADADABAEADCCEFBABFECDFHFHCHFEFCGGEHEHGDADH,False +968,22.0,15.0,29.0,26.0,37.0,20.0,22.0,24.0,AEGBABEFGGEGDHDHAHEFECEFACEEACHBECFBABCDCACAHGHDEEFECECDAAAEHGHGHDHDFGFHCADFDBDEDEAEDEDEDEDGGECEABBGFADADEHGHFECBCAEAEGECECAGDBEGAACCCCCCBHEGECDCDFHFHFHFHFCGEGHBDFEBBBGECHDEFEHHGDADCGHGDDCEFHFCFC,False +969,16.0,6.0,14.0,15.0,9.0,8.0,13.0,13.0,HHHHFEFDDCAHGGEGDGDCBBHCCDADGGHAAADADFDFDGDGDGABEBAFABECDHAAFAFEFGDGCHEHCDCGCEEHHHAEACCCCBCGAA,False +970,21.0,25.0,9.0,17.0,8.0,13.0,18.0,16.0,GBGHGACACAFHFBCADGGGFGFGAGAGBBDBGCHHEHEBFDEABGDGDGBHBCDFFFFHFHAHBDACAHDHCCGAEADBHBDFABABABEBEAECGGBHBHDFBBBBAFDDAGBHHABDDADADBE,False +971,9.0,10.0,11.0,9.0,15.0,9.0,14.0,12.0,EAEDFCFBFBAGHGHGDGBHBGFHEHCFAFAGHECGCHCADAHCEGDGCGBBBBDBDEGFGCCFHEEEHEDEAEDBCGHGCADHEFEAE,False +972,18.0,16.0,12.0,13.0,15.0,19.0,12.0,21.0,BEHFBBABAHGEEAEAFAFCDEHFHAHCGCFBEAAFGCABHHFHFHCHBGADCDHDHCHCEEAGBFDFGADFFFFBFBGDGAGAEADHDHDAEEEBCBCBHBDEEHGFGFBFBDEHCHGHAHFCAD,False +973,27.0,25.0,26.0,28.0,24.0,17.0,20.0,27.0,HCHEFEACGCFDFGCBCHADFCFBADCGHBHCDDDCBAAHAEEDADGDGHGHGHGDAAEBEHAHGDADADEBEHHCEBADAHHHHCHCAAAHBFBDCGBFCHEEFBFBFHAEADDBFBFBDGDEHEHBHGCGAHACECAFBFBEEEBECEFDCCABDBDEDEGAGADEDEDCFBBACHGGFGBGCGDADCHCBC,False +974,2.0,9.0,5.0,14.0,10.0,16.0,13.0,8.0,HBEGFBDBDHEEFHFEGDBFBFBGHFAFDFGFCFDBDBDHDHBGGCFFEGEGECADGFECEHFGDCDHDEDGFGFGD,True +975,7.0,10.0,11.0,8.0,6.0,8.0,11.0,11.0,CECFCDCHGGGGHGAFCECEAECDCGHHBADHDHDBDBFBFDAHGBBBBBBGCFFFAAEHDFCHGAGHCHGE,False +976,22.0,16.0,20.0,24.0,18.0,27.0,21.0,14.0,GDBDHEGEBFHFHDDCFCDAAGEFBFEDBAHGBGBGDFEBBADGHGFABAFAFDCDCBCAHADDDCAHECCDAAFAFGHCCECFGECECEFDHCHAHGBGBGDECECECEAEAEBFBFGHGHAADDFDBDGAFCFBHACAEEFGFAFDFDFGFGDCDGGFFF,False +977,16.0,17.0,23.0,22.0,27.0,15.0,19.0,22.0,EEGGFDFHCHEEAEDEHEHGCEFGBEBEBHBDDCBAHAHDGDAEGEGDHFECBDDDHDCGCFAAAAAFCEHBBEECEFDFDBDBCCCCEFEGAFFCFCFCEBEAHAHAHAGGHGHCHCBGEDBDGEEHCDGHBCBDAHFHBHFGGDHDEDAGECECBCDCG,False +978,5.0,8.0,11.0,18.0,14.0,13.0,11.0,18.0,HFHDBAGHGEFEHCGGEGDAAFHFEFEFDHDGCECHHEHEDEDHGHDFBFCDHHHAHEHBCBCBCDCDGDECEDGDEBFGDCDEBGHFBFDCDFHFDA,False +979,22.0,10.0,19.0,14.0,19.0,26.0,19.0,18.0,HBGDGHGCGBGEFEAEFBDEHEAAHGGGGHDHDHFGEABAFAHEHCACFFDFDFAFECGCDCDCDCFCHCFCHAHFDCBGAGDEHBGEAFAHAHEFAGHEAGACEEEFFFFEFHFBFCFBACGCAFAFCBEFEGEFCGBDDDCAAAH,False +980,9.0,10.0,16.0,13.0,13.0,13.0,17.0,6.0,CDCEBDGFGFACEBDHFCEHACADBDBHBCBGACCECEFEFGFGACHCACDEEGGGEGEGDGCFFFGFDBDFGGAGAHACDDDDGEGFCFCEHBBEB,False +981,19.0,23.0,15.0,12.0,16.0,18.0,17.0,17.0,ECEDHFHFHFAGAHBHDAEFGFBEHGBGBCBHBCEDGDCBHEAGADEGHFHDBBABEBAGAGCCDADHDCGBBBEGAGAGEBBBGFGFCCBFBFEGHAEGHFCFCFCACEDHDAAAAAHDBFFHFEFCBCBEBEFHA,False +982,21.0,16.0,13.0,14.0,20.0,12.0,19.0,12.0,EBEBGBGDGEGECHCHFAAEHBCAEBHBECECACGCDCDCDBABAFABGHGHAAEAHABDEDEFHFGBCDAEAGFGECDHGFGDDDEHAGGGEGBCFDFAFBEGECEHAFDFGABADAGAEBHFAEB,False +983,22.0,16.0,20.0,28.0,16.0,18.0,28.0,14.0,CGCGBDCDCGHACGFDFDGDBDCFEFEFADAECBDDDEAEAEAHAHABGDFAAGFGFGCAAGEDEGFDFDCGBGAGBGHHHGABCBDBDFDFCFDFGCAHAGACABAFEFAGEEDEHBCCHEGBBBDBDHGEDCHCEFAHHGCDHGGFGDGDGDBEGACDCD,False +984,26.0,22.0,19.0,22.0,24.0,27.0,32.0,24.0,ADHHEFAFADABADAFABCGCGAGFGFEDADABEFHFHGHDFGEGADCCFHHHGHGEFCFCEBDGEFEFEGAFBFBFAHGBEBEAGDFAHABAEGHGCECEHBHBDCFFHBAAGAEAGBCCDCDHDHDBDBGBEDDDCBBFBGEDFDHGEGEGEAFAGGBGBHEGBGFGDECHFAFEHHFCGCGEGCCHCHAAFDG,False +985,7.0,9.0,7.0,9.0,13.0,11.0,7.0,5.0,FCBCHEDFAFHEGBGFAEAEAEAFGDGDBDBABAFGEGDCHCHEEBFCEEHEBEDEFFDFGBDBCCFD,False +986,8.0,13.0,17.0,13.0,13.0,11.0,14.0,10.0,HGEDFDFDFDHDHDHDBFEFAGAEBEDGDHHFBBEEABBBFBHGHCCBCEEGECFBACDCDAAGCFCGBGFFEAGDGHCCDGEGCGCGCHCECBCACEB,False +987,20.0,12.0,18.0,25.0,18.0,18.0,21.0,30.0,AAADFHFAADFECBCECEHEHADCDGDGDCFHFHGCGCGFGFCFHDCAHEEGDGCECHCHEBFBHGHGEFHBHFGDADEDHDAFADEHBBBEGEFHADFDBCGDHHGHGHGDGDHDGDFCFEGGFGCAAEAEBHAHADBHEAADHDCECHDADHCHBHFHAB,False +988,20.0,13.0,12.0,16.0,10.0,14.0,25.0,12.0,BBBCHGHGAGFGHGDCACHCHCAAAAAAEHBDBAFDGDGDFCGGEBAFDEDEHEDGDEDADABCBFDGAGAGHGAEDBGGGGDGBFBHAAGBGHDFEFGAEECCGFFBFGFGHCHAFFCACD,False +989,12.0,14.0,12.0,10.0,10.0,5.0,11.0,8.0,AEFEBABAHACGFBABGBGDEDGDEBBCBCHCECBCACDCGHGHGEACFCBBBEFGDDDCDBDADGEHAACHEGAGFBEHAH,False +990,22.0,22.0,18.0,21.0,13.0,23.0,11.0,18.0,AHAHEFFDDCDFGHDFDECHDHABEBCBCEAFBGGGGFCHCBCHHBEDFAFABCHCBCBCBABDDGHHDBFGEEDADFECGBAECEADADADAFFDFBFBFBFAHDFDBHBDEAEFHFGAHAHAHACCBBABGCGCFHFAFDFDEBCA,False +991,10.0,6.0,7.0,9.0,6.0,4.0,5.0,5.0,FDCBCGFHFHBBBABGDFDAGACACEEECAHDDGDEAAADADAECECHDBGH,False +992,9.0,13.0,4.0,15.0,7.0,15.0,17.0,13.0,DEAHFHGHBEGEBBGFFFAFDFDHDGDGHGHFHFDDDCEGBACGDBDGDEHEHGHGBGBGHFBABABFFFAGADHDGGGHFACBFEDDBCAFB,False +993,1.0,1.0,4.0,3.0,4.0,6.0,1.0,3.0,EFEFEFAFCEGDFHHHDFCBCDC,True +994,16.0,14.0,21.0,15.0,11.0,19.0,16.0,24.0,AHACCCDCAAFBFEFBDBAAGAHHCHDHEHAHEHEBGAGAFHFCGCEFEFEDACHCHCGGGFDFCHCDDDHDHAECHGBGBEHCFBDBGGFHFGBAFHFCDADCFCBCBCEHAHFHBCEGGGFAHBHDCDFHFGDB,False +995,7.0,6.0,13.0,6.0,12.0,13.0,4.0,9.0,CEAFHCHFHECCHEACFCFGGAGFCHCHFAFEDHHCECFBDBDGECHDFEEEEEEBABACFCFDFDFBAB,True +996,4.0,9.0,13.0,8.0,5.0,3.0,3.0,5.0,AGAEADDCACBCBCDCDEHECCFHEDBCBCDDDFEBHBHCCCBBFHGCGB,True +997,3.0,1.0,1.0,6.0,4.0,5.0,7.0,3.0,DDDFHEHCGFGFGFGEDAGAEHFDEDBGAG,True +998,18.0,17.0,15.0,15.0,11.0,15.0,12.0,20.0,EBCFCHHAACHCHCHGBCBCBCHDADAFAFEFDFDGHGHCBCFFHCACDFAFAHAEAEAEFEBCHAFBHBFGAEDBDHDHFBCDEAGABBHGADDBDBDHHHEBAGCEEHFHBGGDGFGAGDB,False +999,6.0,13.0,8.0,13.0,6.0,19.0,12.0,12.0,GDGCGCHCAFGFEFBFDEDHFBFBDBGFDADBFBACGBGDGEFBHHHHBDAFGFGBGHCFFECEFEFBAHFDFBFDAHCHDHCHDFDGB,False diff --git a/tests/results/nb_gm_002_2back_240trials.csv b/tests/results/nb_gm_002_2back_240trials.csv new file mode 100644 index 0000000..1c50201 --- /dev/null +++ b/tests/results/nb_gm_002_2back_240trials.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,ralph_skewed +0,30.0,39.0,31.0,30.0,32.0,24.0,27.0,27.0,False +1,33.0,23.0,27.0,32.0,37.0,34.0,25.0,29.0,False +2,31.0,20.0,37.0,28.0,31.0,32.0,26.0,35.0,False +3,27.0,32.0,39.0,24.0,25.0,34.0,35.0,24.0,False +4,34.0,24.0,38.0,28.0,31.0,29.0,28.0,28.0,False +5,29.0,24.0,36.0,31.0,32.0,32.0,31.0,25.0,False +6,25.0,38.0,28.0,30.0,33.0,30.0,26.0,30.0,False +7,27.0,30.0,30.0,29.0,32.0,26.0,33.0,33.0,False +8,24.0,36.0,32.0,23.0,30.0,29.0,35.0,31.0,False +9,35.0,34.0,30.0,29.0,35.0,26.0,23.0,28.0,False +10,30.0,25.0,33.0,31.0,27.0,37.0,30.0,27.0,False +11,28.0,28.0,29.0,26.0,28.0,27.0,34.0,40.0,False +12,35.0,27.0,30.0,29.0,26.0,30.0,36.0,27.0,False +13,38.0,27.0,31.0,27.0,34.0,23.0,27.0,33.0,False +14,29.0,30.0,28.0,35.0,19.0,30.0,37.0,32.0,False 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+19,10.0,14.0,15.0,8.0,25.0,14.0,11.0,20.0,EEEEBEEFHEHEEFEEGHEAFFAFHACGDCDDCFDCBDCBFFBCEAHEAHGCGGHGCHEEAEAHEAHEHHCCFGHABHGFGCHGCFDFHEHBBBDFBFBCEAEBHCDGCEEEHBBHB,False +20,16.0,9.0,19.0,17.0,10.0,22.0,10.0,24.0,HFGDDAFEAFEDCGHAADEHDBHAHDCGBAHBECEFFFFFEFEEDHEDCACEGHBGCFGAGGABDHFCHFCHCCDCFHHADFCFFCFFCBFCDHHHHDFFGHHDACDAFDACDCBHCHHAGHABHAB,False +21,6.0,10.0,3.0,4.0,7.0,3.0,3.0,4.0,EABBAEFHEFABAACHDCDDEFBEGHEGBDABHBBCBGEB,True +22,6.0,11.0,12.0,6.0,9.0,6.0,9.0,10.0,AEDBCDECBCHBCBBGFBGFHGEHACHAGAEFBDAECHCFHFDCCECGBCGECGAHGBHBHEBHDFGDE,False +23,11.0,8.0,12.0,13.0,7.0,5.0,13.0,9.0,EAAGACDACDHEEGGGGGBEGEABEAHGCHCCAFCFFGDHGDGCBGBDDEAFAADCDDCDDHBCGBCAFCBDDHHBHH,False +24,36.0,26.0,18.0,26.0,33.0,19.0,21.0,15.0,GBCHFHAAHAFFGBBEFBCFAEFDFGEGEEBECBEBBABBAEBEEAEEABGDBADBACFFBEFCECGACFADABCFDCDBCBBHDHHACGGEHDEGDEGAHAAFAAEDCCHHDDGDDBDGBDBDDCDAGAAFHEDHGDACDACDBGEEACGAEEBEHAFHBGAAAAAAAEEFBEDCDAEEEFGEGGHGFEAFED,False +25,11.0,17.0,16.0,9.0,15.0,15.0,6.0,9.0,CEEFABDBGDBFDFFDGADECBFCBCCACFABEABFABEGBEHBAHEAHEAECCFFCHDCBBBFGBAGCDFHHFBDFDCCHHEHAEBEGCCBFEECEF,False +26,8.0,5.0,15.0,9.0,10.0,7.0,11.0,5.0,ECAGCHDBBDCCDCGHBBEEFDHFEEEHBHGADADGFDEFGAFGAFCCCCCACCDCDGGECGECGEAGFA,False +27,9.0,11.0,8.0,5.0,8.0,4.0,2.0,4.0,FCAFDBEDBABAABAEEAEHDBHCEHCDBCFBABEEGECGBDABFCCAHCB,True +28,6.0,8.0,11.0,7.0,10.0,5.0,9.0,9.0,CFBCBCCBACBEHBEGCADHDGFEGFHGHDAFBAFBEDCDGCHGAACHCHBCEEEEDHEDGEGGH,False +29,24.0,16.0,18.0,25.0,13.0,19.0,26.0,18.0,HEFHCDEGDHFBACGGDEHDGHDGFDEAHFDHGBHEBGEGADFFGCCGDHFBFABDACDABAGFGDAGDAGCAFFAGHHCDHCHACEDDAFDCCDCAECAEDGEDGAFGFCGFAGBBGFBDBBAABAAGADGAFCHBEEGHBGCBFCGFAHHCHDBDDE,False +30,6.0,5.0,2.0,9.0,2.0,4.0,3.0,8.0,DADBAFBDFHDHHBAHEADGFBHFGHEAHDHBDGDCADC,True +31,19.0,18.0,16.0,13.0,19.0,13.0,14.0,15.0,FCHGCAEHAEBDEBABAABHAFEBDCBDCBHCGEAGEFBAFCCECCBCFHEHGEGAEDAECBECEAFEBDHBDEAGFGHDGCDGADFAHGCFCBFDEHEGCEABFADHAFHGBHABHBHDAEBGDFG,False +32,7.0,12.0,12.0,10.0,7.0,5.0,5.0,9.0,EBDGBGBBDCBACGHBDAAHEBGCBFHBFGAFEHFCCCHDCHDCHDAHDCDDEBDEAFECBAHBECC,False +33,1.0,4.0,8.0,1.0,4.0,4.0,5.0,3.0,GAECEGFBHFGHBGCBFCECCECCBCHDGF,True +34,5.0,4.0,6.0,9.0,13.0,13.0,5.0,7.0,CHHEFFDFFDFFDFDGGDFGDHCEAEAHEAFEBFCFEEFEECAECHCHFDEBDBGEGABDEH,True +35,3.0,2.0,3.0,3.0,5.0,4.0,0.0,6.0,CBDEEHHEAHCAEBDFADFHFCHFEH,True +36,13.0,2.0,13.0,8.0,7.0,6.0,16.0,9.0,DEGDECDHGAHGEDGEGACAFCADGACGACHFDACHCCHCEECGHDHBEGGGGCADCAFAGFGGBAGCAHFHFA,True +37,18.0,19.0,17.0,17.0,13.0,17.0,15.0,23.0,HBCABCGHCEEADEDCEDGAGFFFHDFADHHBHHGCHFHHAGHEHEBBBDEFECFEBHCDAADFGDFHDCDCCDCCFACAACHGGBGGBFBCFBFFCFGEDABDBBDAAGAABACBEGBAHAHHFGEDGHDHHEBHBHF,False +38,4.0,6.0,5.0,9.0,6.0,4.0,4.0,6.0,AGDAGHABHCEEFBEFDEHDBHDECDFCDBHDEGBBGCCADFDH,False +39,3.0,5.0,6.0,8.0,8.0,2.0,8.0,6.0,DCEDEEGEEGAAFEHFGHDGDBHDBGBBGECECDGHBGCDDCHCAH,False +40,0.0,0.0,1.0,3.0,1.0,3.0,5.0,1.0,GDGGDCEHFGFDGF,True +41,20.0,19.0,22.0,21.0,30.0,22.0,10.0,26.0,BADBABGCFGFDDDADEFHAAHAAHEAHBBHECFGFDEHDCDBBBHGEDEECCDCCDGCHHBGHCHACFDCFCFEDFEDAHHHBHAECABDABAAEHFEADCFEBFAGFGEABECFEFFECEEFEHFEHEEHDHDCHBBHBDHCEHCDHBDCFAEFAGHEGECBCFEEFE,False +42,3.0,7.0,4.0,4.0,5.0,2.0,5.0,3.0,EBBEAEEHDCHDCGDGGBACBEHBDGBAFBFCG,False +43,21.0,15.0,21.0,27.0,18.0,33.0,14.0,23.0,DDDDDDBCGFEFFABFDHDAGCEFHHACHGBHGBEFEHFEHFCFFCHDGHDFHDAGFECCCAAEAAGHGDFCHFCHBBBFABDEFDFFBBDBAAFDAFAGHACHACEFFEFDHABCAFGDFEDCGACFADFDDFBHFAFFBEHBEHFCHEADEGHEGCDGHDHDEECCFCCD,False +44,27.0,34.0,20.0,19.0,15.0,29.0,27.0,26.0,FGCFGADGADGDDBDBAFGAFDHHHAFBAEEAGGBDBFCEFAHFAHFAECDCBBCGBHAFHABHDCHAHHGBCGECFDCEHCFBCHBGHCABFBCFBEHBECBAHBGDECHFDFBDEAFBBGECGEBBHDBHDBEABEBFCDFHHFGHFAFFGCACFGDGGHGAABCDBHBGGBGGFHGHGGBEADABFABAAFAFF,False +45,15.0,12.0,15.0,7.0,7.0,15.0,11.0,5.0,CAFCDGCFACFCCFACGBBGCAEAEGAHFADBCHACHFCFBEFGEGBDGBDGBEGEHAEFGBFCDFBFBHACAFCAFGABDAFACDB,False +46,12.0,10.0,7.0,5.0,4.0,11.0,11.0,13.0,ECFFHGFGGFCGACGFGGAHFABBHDEDCHABFBHGAHGAHCAHDABDFHDFGCHGBEABAHEHBFHBFCBAA,False +47,15.0,6.0,13.0,11.0,17.0,21.0,13.0,9.0,EDCEFAEFAFFAGHCFCEEAFGFFHFDECECCEGCDGHDGHDGHACFFCFFCDFEHEEFEEGHEDAFBGEAAHAAGCABAEFAFDABGFCFHCDEDBABFGBGGD,False +48,11.0,17.0,17.0,9.0,17.0,17.0,13.0,15.0,GAFGHHGCHBCACCFBCFHHECHBHAFHEEGBAFCAGHGEFGEDGFCBBEBGABCFDCFDCFDBEEEGAAHDAEDFECBGCBHDBFEGHHBFGBFEBFCBCCHEFAEDAEDCEFHB,False +49,13.0,16.0,15.0,12.0,16.0,9.0,12.0,15.0,BGCBAEBCDBEDBECBDCBABDCDFCDBCEGDABDFFEHCEDGECHACHEBDECDGHFFHFHEAHAHHEFFBAGAGHCHCCHGCEEAAAAGEEGDEGBFGBAGBHHBH,False +50,13.0,6.0,16.0,14.0,12.0,13.0,9.0,12.0,DAEAAGAAGCHCCHDFHEFCCBEGFEGFHAHEAGBGCBFCBFCDACDAFDCHECEBFBAFCFFDEHAGHDEFDGCDECEHCHDGADEHHFADCDD,False +51,22.0,27.0,26.0,19.0,24.0,22.0,28.0,20.0,FDCGDAACFACHGCDGEBFCBDCBGBEGBEGAGGFGGCHGDHGDCAACHADHCFHAAEEBBCBCCBAEDAGBFGAFGEGGDGHCEEEDEHCBBCDECEBGEFCCHCFBCFBHFEABEBDEDHABHDBFFFCEFCEDHFFHBFABHAGGECAEADBGGEGAABHAGHAGEFGBFBFHHDHBEGBFCCDD,False 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+79,23.0,23.0,29.0,21.0,13.0,23.0,22.0,17.0,CDHBACEAHEFDEGHAGAAGFAHFADFCBBBEFBCDGFBCDBDHGGGGCGFBDBBCFBFDEGEEHEGGBGEHFCCFCBDCEDAEABFDHHBFBBCAGDDCHDCHDAHBACAGCAGCADDBDFHAFCAFCGHDEBGHBCHGCHFBEGBFACFCCACAADACFACFCCFGFDG,False +80,12.0,12.0,23.0,9.0,27.0,13.0,18.0,19.0,EGFECEECHEBEEHHFBDCGCAACFBCGEHEEGCEACEGDEADAGBAGBCDBFBHFHACHCDHCDHCECCEGFHGFBABCGDCBDCEACHBCGGAEEAECFEHHAFFEEFHFCEFCHGGGGDHBEHGGHEEHE,False +81,25.0,15.0,14.0,17.0,20.0,16.0,15.0,15.0,DGDFFBFFCAFHADGAEEAFDABDEGGEBGDGEDEBAHAAEGABAHCACEACAHBAGGECFCDDEDBEFHEBGAFCAFCAHDEHDAFAGFCDBCHCCHCEDBGFGHBADBHGBEAAHAAHAEFECFEDFEDHEBHGB,False +82,23.0,16.0,15.0,28.0,9.0,16.0,15.0,26.0,FAHGHHFHGDHGDHDHCCHFBHEDGDGADGBDFDHFBBEDBADEDDBDHFDACDBFGBFAHCDDDGDBGBBGAAADCHFCHCDGABFHDDHDAEDCEDCGDFEAAEACHHGHDGCFFCHABHAHHAFCFHAAHAACBABBHFEAGEAC,False +83,16.0,17.0,21.0,14.0,11.0,17.0,24.0,19.0,EGHCBBCBBHFAHAAGAFGHBCDFAGFBDABDADEEDBCDBCHBCBGEGFFGFGGCHGCGGHHADHDHCDHAFGACCEHDGHFFCDFEDAHDFFAFFHEGBDGCGCBECECHBGHGGHCGBCHBCEGFGGFCACAABAE,False +84,25.0,24.0,34.0,20.0,21.0,23.0,18.0,22.0,GCCGAFHHFBGFBCFBDFBGFCGDEGCAHEBCAFCBFHEFEDCGFCAFCHCHBCHEAHAFBAFDAHBHBDGAABAFBACACHHCFDAFDGBAHBEBBEDFCFECAEBGFHECCCCCCHHEEHAAFDGFDHBDGBEFBEDDHDDEBHECCECCEBAEBAGACGEDGADCBCCGGCDEAGCADCAFHHD,False +85,14.0,17.0,15.0,14.0,15.0,14.0,16.0,10.0,GGCGDDEBFFHGFBGFBHFHHEDAACAABGFFFCDBGBEHBEDBFDBCDCDGCDEFBCHBEGBEGBEFHGFBAEBCEFAAGGCHCCFCCBCHEHEAACADDEDDAGDAGEAEBAG,False +86,5.0,2.0,1.0,1.0,1.0,1.0,3.0,1.0,ADFAGGAHGBEABCA,True +87,28.0,33.0,23.0,19.0,20.0,25.0,30.0,22.0,FFGDBGHBGEGAADDHGEEDEHBBACDFCGFCGEHFBBFHBFBCCGCCFHDFCGHBECBAAFFDBBCBECGGFEGECCAGABBABHAEHBBHBHDEFDCHDBAFFDDFAAHAAHCDFCAHEAHGAHFAHAGHAGAAGEEDFGBEBECBGCBAFBGCCGAFAAFHAGGFGGBGGBDEEGEGBFGBFHBCHBDDBDDBECCA,False +88,27.0,30.0,28.0,20.0,23.0,12.0,23.0,29.0,EGBCBBCEBCHHGDBECBCDBEDGEHGAGACGEHGCDACFECFCBHBBFDAHCACBACBEFGGAGGADAAEBAHDFHDCDBAHCHHBHABGCBEEDHGHHGFHAHDAEDABDGCDECDBADBHHGHHGFGECBEABDHFDGAHEACFGCAGCABCHBFECHCBFCBFAEABDAGEHEEAECABDHBHHCEBG,False +89,14.0,15.0,7.0,17.0,10.0,11.0,15.0,9.0,CHBADFABGHBGFGGAGGADGDEBHADHGHGFDFDDCDBGAAGHAGFAEEBBEDBEBCEBFAFDAFDFGDEADEGDFACCCGBHBBHABHDEDCBDFE,False +90,5.0,3.0,3.0,1.0,8.0,0.0,6.0,3.0,CCACEGHEGDEGBBAHEHGBAGEAEEAEG,True +91,0.0,0.0,4.0,2.0,4.0,2.0,2.0,1.0,GDCFDCEECGEHFEC,True +92,14.0,4.0,7.0,10.0,8.0,6.0,12.0,5.0,DCDAEFAFCECEEAFEDFEGCCGACBDGHFAHBGEBGAGGAGGDGAEGHHGAADAFDADDCBAHDA,False +93,10.0,8.0,8.0,3.0,8.0,14.0,16.0,15.0,FAGFDGHDHHEHEEGGFFACFHEHACCACHFGHFGHCGCAGCGBCFFEGFGBHABHFDHGBGBHABHAFFAGFEHEEBBAGG,True +94,21.0,25.0,21.0,30.0,27.0,13.0,12.0,17.0,HHBEBCAACEABDGDGBDFBGFCAEHGDCADCHDCEDFEDCEDGDCEDAEGEHAADBBDAADHCDHDFHBEEBEEBCEGAECDEBBCGAHEBBFFHEBHEHDAHDAECFFDFEDFBDABDCCACEDEBDHDDAGFAEABECBHGFDDFEDCCBHCBHGBEGBACBA,False +95,4.0,6.0,6.0,8.0,7.0,6.0,6.0,9.0,EDGEBHEFHACBBCFEGHCHDAHDEHDBHDBDDEHFCGECGFGBFACFAHGD,False +96,8.0,5.0,5.0,6.0,5.0,8.0,12.0,12.0,AFACCAGAGGFBEHEGHECFDFFDGFHGAHGHHFDGAGCAGEFGHBBHEBHDDHDHHGCBA,False +97,20.0,25.0,21.0,20.0,27.0,26.0,25.0,26.0,BFCFGDFBECHDCEBGEFGBABHGDDGAFBEBCEFEEFGDAHFBHEHHCHDDHGEFDFFBGBBAEGCCFDDABEBBEBFHBHHBCCECEDCAFCGFGHFCBGHBEAFCBFDEEAEEAFECEBBGGAGHBDHFHHFHHFHHFHHEEHGCDABGABGACGAFGAGGDDEDDCADCFGAFGDCAHEAHEAEGC,False +98,4.0,3.0,1.0,1.0,6.0,1.0,5.0,3.0,BBAHAEDECGEAGBAGEEGHEGHF,True +99,21.0,17.0,15.0,21.0,17.0,23.0,10.0,21.0,AHDDHEDGFFGCFHDHAGHGHHDDFADFABHDBCCACAAHGDDFDDFGBHEBHBHEEHEFCFFBBDDBAABCEEHDACDHCEEAAEBHBFABFABCABFFFFDFFDFEEFCEHCEBDEBFCAGAGGDGCHBCHAAHEFFECAADH,False +100,21.0,17.0,13.0,22.0,21.0,22.0,21.0,31.0,GCAADDGBDEBDABDGDGGEADEDDFHHHEHDGHFGHFDHGAFAHEHDCHDHFEBGEACDACGABGABGFGGDGBHEEHEFFGHFABDHEDAECBFHAGHAHBAEAAEAFEHFEBGGBCFDFEEAHCHHCFDAFDCFDBFHBAHCHHFFGEHDECCGCBHFHHFBHBE,False +101,3.0,4.0,2.0,2.0,2.0,1.0,2.0,2.0,BCFBEABEABHADGCHGD,False +102,3.0,5.0,4.0,4.0,2.0,1.0,3.0,10.0,BGHBGHCCHCDHEHHABDFHDBHEGCDAHBAH,True +103,22.0,16.0,17.0,17.0,11.0,10.0,13.0,12.0,DECDFCDFEDCCBCCBCADGAGFAEAAHHCGECAAFHAHBAGEFDEFHHGGFBFCBACBABDACDAHDAGDGBDBADHFDBCEHGEHGDHABGBCEDEEHBAABADCGGCFCABDABA,False +104,12.0,15.0,10.0,16.0,25.0,15.0,20.0,17.0,GBFDCFDGDDBHDAADEBGBDEBEEFGHFGHFGHCGHEGDEADHBDHGGBGHEDCFHAAHACHGGEGGEFEBFGADCCEBHEGFEHDEHEEFAGDCHFEEAEEBCEGEDBEDBECBFFBHHCAFAEGAFB,False +105,7.0,10.0,8.0,8.0,6.0,8.0,6.0,10.0,HBEHAGHFGHBGDBAAGCDEHFEBEHBEBCABAACDFHBCHDFGDFGDFHCHCCACBFDBEDF,False +106,17.0,20.0,9.0,15.0,13.0,17.0,14.0,15.0,FBEAGDAGAABAHBGEFFBFFEDHEGHEGHEFHFDBBCBBDBCHCAHGAHCHBEGFDGFAEBAEGADCAHBDFBDFDFBABHEFGBCDAFDBCAGCFBHFBAFAEDHEDCEDHBDGGHGA,False +107,5.0,5.0,1.0,5.0,1.0,5.0,5.0,2.0,FABAAGDGFDFHBFEBAGBAGBFDDHGDC,True +108,17.0,16.0,20.0,15.0,16.0,19.0,21.0,30.0,CBHCHHDDDGADGAFCEHEBHEFEAAEBHFHCBGFAEDHEFEFFCFFAHEHHAHBGCDCHFGHBGFCGFBEABFBHHGHHGCHEAHEADABGHBHHBDHGDHGAGGBGGEFCFFCDBGDFDAECEECGCAGCGDCFDFHHAHHDHBBCCACGAC,False +109,19.0,26.0,19.0,10.0,27.0,23.0,8.0,14.0,EBCAAAGFADFADFEFBBBCBEABEABEAEEHEEHEECEBGACCAFCBHCDCCECFBCAGGAFEAFEFBHHBDFAHEHFEGFHCFBBHCCABCHFFBFFBDGCEGEBAEGCFFEEDHFFBFBADBDBBDBBEHEEFCHACBAHDEE,False +110,19.0,10.0,10.0,17.0,15.0,14.0,13.0,9.0,EACEADEDDGDAEBCFACEAEBFHFFGDFEDBBGBHGCADCFBBBHCAHEAHFAHAAHCDGCDGAEGAEGEDDFGEAEBAGFCGDGDDABDFCDFGFFAAEDFEHAH,False +111,6.0,10.0,13.0,9.0,4.0,7.0,3.0,10.0,CCCAFBAFBEHDFBCCBCHBCBCGHDAHDAGDCDFCHCEHDAFDFHDHHDEEBFBAGBCHBC,True +112,14.0,15.0,18.0,9.0,20.0,11.0,10.0,7.0,DEFDEFBEACFGEFCACCBGGBHAAEBEHCEGGEDEEFEEDBECBABGADFADFADGCHCCHCHACEDHEGAFAEFBFBAEACCAEBBGBBGEBEBHCCDCCFC,False +113,18.0,25.0,13.0,24.0,29.0,22.0,19.0,30.0,HCAHEABDACHBBDDHADBEHEEHCABCFBHFBABBABDHBEHFGAFGFHCHGCAEFHEFHGHCGCEHDDFEBFEFFDDHDEEDGEFCBGBDGAHHCHDCFDEEDGCFHHFEEFGBGGEEHBFAGFDHBEGFEDCEDEBDEFHEAHEAHABBEDBGFBGEHGAHFADBADHADHEDBGGB,False +114,13.0,9.0,15.0,32.0,17.0,18.0,11.0,14.0,HDHDDAGGFDDFHBFBCAEDGEDCEACDDEEDFHFAGFDECDCCDFADECFECHDCHDGAGAHGHDFEDCEDCEHBHDAHDCFDBFHHGDBDAFCGFAHFDCCDAEDGEDEEFADFAGFBBDEBDEBDF,False +115,21.0,18.0,26.0,25.0,21.0,27.0,25.0,34.0,AACCECDFFBBDABHAGHGFHGHAFHBFHFEHCBHFDAGHAGEDBEACHDCAGCDCCDBEDBDDEGGEHGAHFAHDBFGHFGCDCCFCBFCBHCHHFFDFGEEEDHFHHFHDFEDFDCBHAGAAGHBEEDCFFCHEDAEBAGDEGDEDBFBGCBECHCGHCDAGGAHGHCGHCFHBFHCFHDADAEGEGHCGAFFEH,False +116,25.0,15.0,25.0,18.0,19.0,11.0,22.0,30.0,BGGBGDHGBAECHEFABDHBHHBHDADBEEGFGGDGCCGFCHHHAHAFHBFEEGEAHCGEAGDCCHCGDAGBAGBAEADBADHADFCGHEDHCABCHHEHDFHFAHEAHCHCAHBDHBGHFGEFCAGCHGAAACAACHHDHCCGECEDDFCDACDACBCCEEGEE,False +117,28.0,24.0,15.0,28.0,23.0,30.0,14.0,19.0,CHACHAGEBEFDCFAGFADDEDDBDGBDBFEBEDHHDGDECDEBFABFAFFABAAHHAHHDFHFBHDBEDADCBGHEDFFDEDDEBEBAGADDFFFBDFBFFBFFBHACFDBFDFAEBACBACGEGGCFAFEHEAHECHBDGGFCAECFEFHEHHAGACBDCBAHAAEAAEDECDAFGGFB,False +118,0.0,3.0,1.0,0.0,4.0,1.0,0.0,2.0,FHBBEEBEECH,True +119,15.0,14.0,10.0,15.0,7.0,12.0,18.0,9.0,BGDBGBFEBDCFAFFADCGGAGDABAAHHAHHACEBCDDCBDAGDGBBGDGDDACEFCFFCGFHGBEFCGACHAGAGHAGDABBEEFHGFBFDBEDGHDG,False +120,18.0,23.0,21.0,12.0,21.0,14.0,26.0,15.0,GBBHAAEBAEHEEFEGFGCAECABAGCADBEFAAGDABCAGGFGGCHGCHGAHEAHFFCEHCEBBFBBEHBCGECGACGDCGDHGCGGHGGDDGHACBBGDBDECDCFABECFEBFECEBGBBEDDEGFCDFEGBHGBHAHFACEBCHBF,False +121,18.0,17.0,15.0,11.0,14.0,12.0,17.0,17.0,AGGAFDDFCDBBHECHBCHADHCBACFACDDGFACEBCBBGBHAAHEAEEHGFGCFGBHEBAFHAHHADHBEGBHHCEFEEFGHFGFGCBDCADGBDHHEBEBBAADAAFCAGCGGEGGEC,False +122,19.0,12.0,14.0,16.0,13.0,13.0,22.0,12.0,DFAEFDEBHGFEEDAEDFGGCGGFGGFGGAGGAFFDEAGEAGDBBABDHHCHHBDHBDGCGGDHDAGCACCBFCBABHEFHCCHECBCGDDAHDCEEFACFBCAGDAGAAGAEFAGDBEHA,False +123,3.0,8.0,5.0,11.0,9.0,10.0,4.0,11.0,EBFFHHFADFCHFGHEGHFGFACDEDDEGHFAEDHBDEBDECDCDDFHBFEBHHBCEBHDB,True +124,4.0,5.0,6.0,11.0,9.0,6.0,5.0,8.0,ACEACEADEDEHDCFFCDCCEHHEHEBHGBDGHDFDFEGFEDBHDHDBBGFAGD,False +125,11.0,14.0,19.0,12.0,21.0,14.0,17.0,9.0,CCDCBDBEDHEGHAFEECDGCFGCEGCBGEFAEDACCHCDHGFEFFBBEABEAHHAFCCFBFFCFCBEGDACDGCAEBAEGGEDGEDCAGGEDHEBHBBACBHGFEGEGDEGEFCBF,False +126,7.0,15.0,16.0,15.0,17.0,19.0,21.0,17.0,CHHHDBCCEFEEBEGBHFEDGEBFFBGFGHHGHHGEHDHCDHCDFAFFDCABAFBHGBCGBFHBDHCEGAGGHHGDEAFECHDBFGBDBCDECGEFEEBECBDFFDECGGCGADGEDGFGCFGCFAF,False +127,1.0,2.0,2.0,2.0,3.0,3.0,7.0,2.0,BEGGGGACFHCFHEFDGGDEGB,True +128,24.0,27.0,28.0,25.0,25.0,12.0,31.0,20.0,GGGBGGBDBCDHGACGEHDCHDCBDCHHEHBGHADDADDEBGGHGDDEADFAHFAGGEGEEABEHDEHCEBAEBECBACBACGACGADFADBBBBFCCAEGHFBEBCAAHBCHFCEFCDFCDCCBAEGEGCAGCGCCGEHFEHGCCACAACBDDBHGBEBDAFGEFGBBGHHEDGDABCGFHDEGGEDEADB,False +129,8.0,19.0,18.0,15.0,11.0,19.0,15.0,9.0,BEEBFHGAACFBCEBFHFADFCDHCDBCGBGGEGBDAADFDCHECHECEGCFGCFGFBCFGCAGDFGFFHHBDDFCDFBBEDBFDGDBBFBHABCEBCDAEGCBFHBFCGECGD,False +130,19.0,16.0,11.0,13.0,12.0,17.0,19.0,19.0,AGFEGFGGEGDAFDBFDBCGACBHEHHAHHDFADABHAGHBFHDFCDCADEEFEGBDGBEGADBAHFGBDGBAEFAGFBCAECHGBGFBGBBFBHAHHAHDEGEFAHADCACCHCEHGAHFHGFCF,False +131,4.0,4.0,2.0,0.0,2.0,2.0,3.0,2.0,FBECAGHAHCAGBAGBEFB,True +132,21.0,22.0,26.0,22.0,19.0,22.0,19.0,31.0,HHACHAGHDFHCACFECAECGDFFDFCAACEBEDHHAHDCGBCBBCAHCAFCDBGFGDCHBHECHCFACFGCHECBBCFBGHDGHEGHDGFBAADFGBGGFCGHCBHAGHFEEEDAEDAHHABFABHAHHGHBFDAFDGDDFEDGBDFEDHDDHCEHEAHECEECEADBGCBFFHCFBBBBH,False +133,16.0,18.0,20.0,18.0,16.0,13.0,27.0,16.0,DGGBCEDCEFHDGHFBDCHFHHBACBADAAHADEACBGHFGEDGCBCABGAGFCGDCGDGBEGBEGBECEEHGEHGHHDAAGGACBDGBGCBACDEBDBGCFHFEHCEGCEAEFCHFABFEGGCDHFDCDDCDBFGBFGAGHAG,False +134,19.0,21.0,15.0,10.0,12.0,12.0,10.0,11.0,DAGDAGAAHHFHABCBBCEBCFBCGDCGEEACACBACEAFGBDAAFEAFEHBBBFECDEADGFFACGECBBCBBGEBFEBDAACHADHFEFBCHBFGBHDBCGBHADHAH,False +135,13.0,9.0,13.0,6.0,13.0,9.0,17.0,10.0,ACEEHFBHFBGFCHABEADHHCGACGDHBCABEGBEDBGGCGHHAHCEDAEFAEGCEACEAGGFCGCDGBFGAFGAFBEGCEGAFGECHD,False +136,12.0,12.0,9.0,6.0,6.0,6.0,7.0,12.0,DGFDCFBCHHHHHHHBHBBABEAFGBEGCFDFGCCBDABAAEAAHACCAGHADEACGHGEBEFBCDBHAB,False +137,8.0,7.0,7.0,10.0,12.0,16.0,11.0,8.0,EEHEGHGAHFFEFEDBGDBEBBGGFGDCGFCFCGFDDFHDFHAFCFDGAAFFAEHAEDFEGFEDCEGAEFBHBCDBCHA,False +138,16.0,20.0,15.0,26.0,16.0,10.0,21.0,11.0,BCEFDBCDBAHBEFBCAHCAEBDCCDHGHHCHDDDEGBFDFGCACAEEDGADGEDBEGCEHCHBGHBEDDADDGBDGBCGBDHCFGCGGFGGAAEAADAEDGEDBEBADDADGCDGBAGBDGBHGFFBEDAEFBF,False +139,13.0,8.0,3.0,6.0,6.0,4.0,5.0,4.0,EDGABAADGAECAGAAGAACHFFHABGFBABBEDBEHBAHCABDFDEED,True +140,3.0,7.0,9.0,8.0,11.0,8.0,12.0,4.0,FGFCGCCEEDFEBFEBDACHADEBCEDFBDEHEFBEHCEDCGGBGFBEFCGGDGHDGCGGAG,False +141,7.0,6.0,3.0,11.0,10.0,4.0,8.0,7.0,EEAAECEEGHEHDFDCHCGHEAAEHBDFBDBGDBADBEHFEAFGGDHDDGBDGADG,False +142,25.0,23.0,17.0,19.0,29.0,25.0,18.0,29.0,EEBEEBHHHHBCHEFDGCDECDEDBEFHAFGBFBHFBHFCHFEDFBBFEAEGBCBAAAADAHEEFAEFDFACHHCHBEHBHHDGECFEFBEGHEGHAFHCDBCAGHEGHGDHGEGGFAAFAHEEHBFABDACHABDCDAFGFFGCFECFHBFEEDDGDBFCAHAEDDEACEAGDBGAAGAHCBHB,False +143,1.0,2.0,2.0,3.0,4.0,5.0,2.0,3.0,CFDCBDHGEEGAEDFEFFBHFH,True +144,9.0,4.0,7.0,5.0,3.0,7.0,3.0,7.0,EFAFABHACHECHGCBADBADAADGCFFAHGHDFHDCHFCBECAF,False +145,21.0,27.0,26.0,22.0,15.0,22.0,16.0,17.0,FCDFDDECEHCFGCEGDABBGHCGBBFABAEFEEFACHBGFEABEDBHCCFGAFEEFHAFECFHCEBCDBCBAHFAHFCFFCFFBFAGGAECDCCBBDDCDDCABBAGGAGBAGHCHECDACBAFHECGBGGBAGBHBACCADDDDCHHHFHHBDDBDDBDBADBF,False +146,23.0,23.0,27.0,18.0,23.0,27.0,25.0,28.0,DEGHEGFDBFGHDEACECDFDDFDBBBGCEAFHFFHFEBGEBDEBFBBFHFFEFCGFCGCHGAHBCFGAAECGEGDDGCHGAHAAHAADDADCAFBFFBHBHEGCAHCHHBEACCBBABBDBHCBDFAHAEBCEGEGCBHEHFAGCAFCACEFHEFADBCGGCGHAGHGEHEFHCAHCGHDGHCEHCEFCGFDF,False +147,19.0,22.0,21.0,22.0,15.0,18.0,18.0,18.0,ADDADEFBADAHFBBFBBCHGCGBCBHEDCCDHDDACGEGBEACEBCGCFABFHEAHFGDCDDCGFCGHEHHEHBFHDFBFFBAFAABAADACDFCEFHADGADCCECDBHDBCGBAEBAHDHHDHACFCGFGEFHEGGCGEFGBDGBGBBDE,False +148,23.0,18.0,18.0,17.0,20.0,20.0,23.0,19.0,GHBGCBDAFDAFHCBEFGACAECHHGEGFEGDEDDBCAAGFAGCGECAEFBEACEHGEHAEAFEAFBCGCCFCBBGHBAFBFCBFAEHBEHBEGAACFABGEDGHAGBCGCEBDGDDHEAHCADFFGHAHDGHDGHDGBDABHAEDDFHDFCFFHGFE,False +149,11.0,9.0,14.0,14.0,12.0,13.0,8.0,11.0,CCFCGFCDFHHHGGHEDDFHDFEEGCEAHAHCADFEBBBCBFCAHBAHEACDDCDACDADDBDDBEGBDFFCEHEFBEFEAGEGFCGFCAHA,False +150,20.0,17.0,22.0,21.0,18.0,23.0,27.0,26.0,FDDHHBGAEAABAAFAHBGFFHEHCEBEBBEDBGDCGHCGHCFFEGFEDFCDACDAEBFEDAEDHHHFGHGDHGAEFCFGBEDAADCCGFGGAAGCHCDDBDCGGFGGFGGFHGFBGBCGECHFHHACHABDFHDHCAEBBEBGCCFHEHGFHFEHFEHBCACCACGAGHDDDD,False +151,25.0,32.0,23.0,18.0,29.0,30.0,21.0,16.0,CHFAFBDBCEHGEHEEFEACEFCFHHFCAGAEGBCABCAECHDDFDFFEFFGHABFFEHBBDBGABGACGACEDCGDEBDEBCEBFDCHBADBFDAADEFBFHGAACAACHDEADHCBGCAFBFFBFFBEBBGBEEBHDBFDGDAGFEGCABEEBEHBGHBGFBGBAGFGCEGCACFDGAEBEEFCEFAFHBCE,False +152,2.0,5.0,8.0,6.0,3.0,7.0,7.0,3.0,ECBDCEGFFGHCGCGGFBDFDDADDHEBFCBCCBFCGFGAH,True +153,20.0,20.0,31.0,26.0,22.0,23.0,14.0,22.0,GBGFBFFBHCBHCBHGBEFCGFHHHHEHDCHCCDGCFFCDDHFDEDGEGCHHADHCEECFECHECDGCDGADCAGAAHEDHCFBEFEDCHFFAADEADHADCGBCFBCFEEEEBGBCCCCBCDBDHBAHDABCAGCBCFBEHDEBDCFDHFEFDAACAEDADAFGEFABFDCEDAFAB,False +154,14.0,22.0,13.0,6.0,19.0,16.0,15.0,9.0,EEBFEFCBFDAAGAHBCCBGCEEAEEAEEAEEAEGGFHBCHBCBCHBCFACFGDECBAGFFDBHBBHGGFAGBGCBEHGADBFBBGGAFCAFCEGBEGBEFBDFBHEHEFDAFB,False +155,13.0,9.0,8.0,9.0,16.0,11.0,16.0,26.0,HGHDBHECHGCDGAEGFEHDEGGHHFBHFGHBGBEFEAHEAHBFHFDHADHBCHEAHEAHDGHDHHEFFACDCEBFGGEGAEHEGHEGCCGFHGAAAHAFHAHDEBBC,False +156,21.0,23.0,28.0,17.0,32.0,20.0,26.0,33.0,AGBGFFGFGGCEFCBFGBECECGECBECAGHDHEDHCBHEEAEEBFGGHEEHAGFFGFHHCCHADABEGBHGCHGCFBHEHHEHHGFHFFHEFAEHADCEDCHAADBADHEDAFHEDDCCDCFEHBHGGHEFHEBHEBHGBCGCADAAHACBDFBGCBECBCCEHEADEGEEAFCDBHGBCGBCDFAGEAEHAHDCBBCG,False +157,3.0,5.0,10.0,12.0,6.0,7.0,9.0,8.0,CDDCFDCHDGGFGDBGDHFHHEGCCHDCADCAGBFHEGEEGCEDEFDBFDHAHGCBFCBD,False +158,27.0,19.0,22.0,22.0,21.0,22.0,30.0,32.0,AEAADDGDGHBHDGHBGHBHHBCHCAHCABEEBDBDHGFHGHHGBBAHAGFGBAGAGGAGHHCFFBHHGDHAACAGCAHDADGAFHCCHGHHCHGCFGEEDEDBECGAFEDFEDBEGBCACHFCDFGDCDCCBGCFGDFGHFAAEDHFBHFGFFEAEEHEDBECFEABGAFEEEAFDCFDAFDBCGHCGHAEHAG,False +159,6.0,10.0,10.0,5.0,6.0,6.0,5.0,10.0,HCEECDECAFABHBBFADFCGACGABHFEHCBBCBBHFHCDCEDCHGGHEGHFBHABD,False +160,18.0,20.0,20.0,17.0,21.0,19.0,20.0,20.0,FEDBECCGDCDBGDBGDGGDCDFCAHCEHAGAABACFCFFCAACHADAACEGEEGBFBHEHHBGHBACGFDFCHFCHEAEBBEDFFGCFGBEBBEHDDHABGEEEEFABHABHGEHGEHGEHBFDFDHGDHGBEGBECCFCAFHFGCCDAFAHDB,False +161,12.0,21.0,28.0,20.0,19.0,21.0,30.0,23.0,BEBCAAFGAFGBFGEEEFCCHCGHFGHGDDCCHBCGACGEHGHCEHCFCBHCBHDAHDHHDCHEABGHFGBGGCGHCGCEGFDGDDEFGEAHBGEADDCFDGBDGDCFECFCGFCHEGAFCDFCDGDFFEHFBHFCCBECHEBHCBFDBFBBGBDAEDGECGBHEBDABGGGAH,False +162,21.0,14.0,18.0,20.0,18.0,17.0,19.0,20.0,GHBEAFEGBGGHDEEDEABEBBEFECFCCABAAEAAEACBAFBHFHHAEDBCDECDAFBAFBAGEHEHGDAAHGAEDCCDHDDHGAHAFCCECAFCHHCHEGBCDCCBFFEFFGBFDDDDDGGCGDAFDGCGFHHDHHDHGFHGAGG,False +163,7.0,8.0,10.0,9.0,10.0,6.0,9.0,12.0,FBCCDDCAHADHEHHAGCGGHECHECHGBFABFADFGDHBDHDDCDHCEBFHGECEEAEFHECEBGBGGBA,False +164,2.0,1.0,4.0,3.0,2.0,6.0,3.0,7.0,CHCFEGFCGHHEABGAHDFHDFHCFHFD,True +165,27.0,21.0,24.0,26.0,31.0,11.0,22.0,21.0,CAADGACHHEAHDFHCAHCFBCFBEBHGCEFCHCGECDEABEACDDGHDAFCCDCADCAGBDGBEGBCDEHAHHAEFBEGDEFCEABBDBGAHAACAAEACBFBBFGEEHEBDEGDEGDCCDCABHEEEGCDGCDGHEGEEGEHDEGDHDAEFEGBDGADHFDGCDGBAAAAHHEEHDEBABB,False +166,7.0,16.0,7.0,13.0,4.0,10.0,9.0,15.0,BDDEDDGCAHEFHCFHCBHAGFDBDDBDDGFFBAHAHHFGBBDFBDHACHBCEBFEHHGHHBADBCFBHDGABGHBGFBGC,False +167,15.0,15.0,9.0,10.0,9.0,15.0,18.0,14.0,GGABCADCGHHGEHBDHCDHDEGGGFGGAGAABECBCFBEABEBEGAACBBFEAFBHFBHFBGFCAFGHFGHDGCBCEHFFGBFEDFBDAHHAHHGFDDAGDAFA,False +168,21.0,14.0,14.0,15.0,25.0,21.0,7.0,17.0,FDABDAHCHHFDACBGCBGCHFAACGEEBCBFABAEEAEEAFEADDHFAHFEHAHHCEHEFDGFEHFEGFDFHCCAEAAEADBHCFHEBBCFACFDEADFAECAEBBEDBEGFDAFEFDHFDHFEEBCEBGEHD,False +169,11.0,25.0,11.0,15.0,12.0,14.0,16.0,19.0,CDFBBCHGCEBDBACBDCGHFHHFHDFHBEGBEDBFDAFCAHBACFAGGAGEAGBAGBHBBDEBHGHHGHFEABDHFCBECBFDFEGHDFHBFHAEHECHBHBGDBGBCEBABDEGDGGDFDB,False +170,11.0,10.0,15.0,10.0,14.0,10.0,14.0,13.0,EEGCEHAGADCDEADGBDBHDFGDHCDFCDHBAEAHEHCGFCGFCEFDHGHHGHFGCAACHACHAEGEBDCFGCFBBFBBEEBGACGFHEECEBCGA,False +171,15.0,14.0,17.0,21.0,14.0,11.0,20.0,12.0,CBGBFHBCEACEAGAACBDBBDCDDCDDAGGAFGFGDHADEDDEFFAFFCBFCBFCFAHDDBGGGEADHHBHBBDEEGEEGCAGCDCCGCEBHHCGGCDBCHHEAHGAEGHEFADGDGEDGDDA,False +172,6.0,4.0,6.0,6.0,3.0,10.0,5.0,4.0,GBFGHFGDEDFCDAGDHCDACBECDECAHAFFAFBCBHAFFGFF,False +173,2.0,0.0,4.0,3.0,0.0,0.0,1.0,0.0,DDGDCCACCA,True +174,3.0,6.0,8.0,12.0,9.0,8.0,4.0,7.0,FGBDDHHDCFABFABCBCCHDEHEFAEFEBFEDDHDBCDECFHCFGEGGEDDCDDHE,False +175,4.0,4.0,3.0,0.0,0.0,0.0,2.0,1.0,GACGABHBBAABCC,True +176,4.0,2.0,4.0,1.0,2.0,1.0,1.0,1.0,HCDACAAEABCFBCEG,True +177,22.0,20.0,10.0,18.0,13.0,13.0,19.0,20.0,CBHCGHGEHEEADBHGAEGFEGFBAEBCFAFEGHCBABFADFDDCHBCHDHAGGADBAHFEEFHBBHBGDDDHDGHGFHAFAAEGBBDAADHGBEGBAGBADBAHCHHADHDGGDFGDFDCABCABCABEFHEGA,False +178,22.0,19.0,25.0,28.0,26.0,27.0,22.0,13.0,CCCCCCCDCAGHEHCGDGHCADEADBADHFDGGGBDACFHCFHDGBDGDAGDCDDBBCEBFBAABDCDDEDFEFEECDEBAFBDDBFEHEEAEFGEFGEAGBFFBFFBCFCFDGHEFCAFCAHEEGEEBEAHDGEFBFHDFEDCDHCDACGGBGCAGDAFAAFEAFHDFEGECBBGFAEFAG,False +179,3.0,7.0,11.0,8.0,19.0,13.0,15.0,4.0,BEEBAEFHEBGCBCEBFHFDECDCGHGFEGEEBECGFCGFDGDDGFAFFAEGCEFCEFDECEEGDEGCGGFGEBDHCEGF,True +180,23.0,18.0,16.0,19.0,17.0,9.0,16.0,16.0,DACDHCDECEHCBACDAFDAFABCEDHDGHBCFFABCDDFDDHCAHBAEDABHABDGDFCBECAEAAHGEFABFGBGBHABHCEAEGAEGEHGFHEAAEAHGCEGCHGAEGCBGCDGDEGHHADBAGBEDBDBB,False +181,7.0,4.0,3.0,4.0,1.0,4.0,0.0,2.0,CDDAFABHAECADFHCFABFABDAB,True +182,7.0,17.0,14.0,12.0,11.0,8.0,17.0,16.0,ECEECHEGDCFDCFDCEDBBGBGECGBHGFFGCBHEBHABAGBHFBHDGHBECBEHHGCGCCGCFGHABADDDHGDHEBHBCGGFFACHAEADBHDGHBGDB,False +183,18.0,19.0,14.0,22.0,20.0,25.0,20.0,18.0,FBAHCEHGHHGAEDEDDHDHGFACFDBFGCCBHGHHGBHGECBHFDEFBEBHECHFGDFHDEHAGGEGDBGAADFADAADGADGHFFEGCABDGFDBDECDFAFAEFCEFCADGFDFFBFFBHFCECGEBGEBHEADBBDFBCFDCFAAEGBEABE,False +184,9.0,17.0,14.0,14.0,12.0,19.0,15.0,10.0,DBDDHCBBBBGGFEBFEAFGCFDCADCDFEFGHFDHBDCECCFDCAEBEDHFDCBDGBACACGECFEHDBACBFFBFFGGDEGHHGCHFBHFBEFAEAABGFBGEGGFGH,False +185,5.0,15.0,12.0,28.0,11.0,16.0,11.0,13.0,FBEBDDHEDCEGFGGBGEBDBBHCDGDDHBDHECBDFBDEGHEFHEFEDCDHGDADDABHABDCBDBFDHGDFDCGHCGDCHHGDADDEDDAFDFFHFFECDCBBFFCFFC,False +186,3.0,2.0,0.0,4.0,2.0,3.0,6.0,2.0,EGADGADADBGHFGBDGHFGEF,True +187,7.0,12.0,9.0,16.0,4.0,16.0,12.0,10.0,BDFDFFBBBEBBFCHHCHHFFEGDADDFDFHAFDAFBBGDBGDBDDGCDFFDGDGCBCADGEHGDHCCHACABHAHGCFGFFGEFG,False +188,9.0,14.0,12.0,11.0,9.0,6.0,5.0,4.0,DFBEFDCDCBAFBADEFDEGCEBCGFCECHDBADBADBEEBABGHBACBACBECGACBBCADDHFGHECD,False +189,15.0,22.0,16.0,23.0,11.0,18.0,13.0,25.0,CHGBHDEHBEHDGCDFHFHHCHHGHEDDBGHACHECHBHGDHDCHDEAGEABFAEFACBBDDBDBADACDABFAHDABACBHHDHCAHFFBBDBGAFGFFBBABCGEEFEDCCDCBDBFDBFEFGGFHHFHDCADBDGFCGFH,False +190,23.0,11.0,18.0,25.0,19.0,12.0,19.0,38.0,DEHHAGHADHGCHACEDCAGEGFDADHADHDDGEEEEHFHGCAGEDDFHHEHHDHDGBDADHECEEGAFHDBHGBHGBDAHAEHABHBBFDDCDAHHGHHEHFGHCHDDECBFCADCGDCGHCGHGAHGABFHFHHFHHEHHBBAEDAEDFCCECAAGACCACAF,False +191,5.0,6.0,1.0,7.0,12.0,13.0,5.0,13.0,HEEFEHAEHFFHFGDFEDGEGAFGFHGEHDBHAFHFFEAHEBEBDFADBHHHEHBECFDBFD,True +192,14.0,9.0,19.0,16.0,17.0,13.0,14.0,12.0,FBCCBDDFFDHDDHGEFGEFGFHGFBDFCEEHACCAEEDBFDEDCHFCBAEFCGGAHFADGAHEHHAHBACBCEDEEDCCDCGACGCCGCEGDECAECAFGABGBHGDDEAEHA,False +193,13.0,11.0,10.0,13.0,18.0,18.0,16.0,24.0,BFHBGDBGHEFHEGEEGAAFHDFECFEAHEAHDFHCHHEHFAGEGCCHHEDHEDCCDAGGAGGBDCBDAFHFFAFDAFHGCHGCFGHGHHCHDBHBFFADFEDEBHGGFBADHAEEEHEEBFB,False +194,4.0,3.0,4.0,0.0,0.0,3.0,1.0,3.0,HCHBAHBAGFABCAFCFC,True +195,5.0,5.0,1.0,2.0,4.0,4.0,7.0,2.0,EFBGHBGABGADGABHAGDBECGAFGFFEE,True +196,16.0,12.0,12.0,7.0,4.0,7.0,9.0,12.0,ACGACAHFFCEACGGDEADCAGCFHBFBEFDHDBHAAAAGHBBHCBHGBAGBACBDCBHCBACDECHHAGHFHBGADFA,False +197,11.0,6.0,8.0,7.0,7.0,10.0,12.0,14.0,GHFFHACEECGEGGDBGBBFAGFGCHGHDGAEGCCBHCBHAFHAHDAFGAFADCADHAHHBCDFGEAHEHHFDEF,False +198,21.0,16.0,17.0,15.0,22.0,24.0,21.0,20.0,AEFABCDCDABGHHEHDFBBFCAGGAEFCGGCGABGACGHHGDGBDBBCFACBDFHHEHFCHFCECHFCHGEHGBFFECFBHFGHFEDFDCFCEAEEADDGDEGFEGFABFHBFAEHEDDADAAGAACEACBHEBFEDFAAAGGEGGBHEEHFEHF,False +199,3.0,4.0,1.0,2.0,7.0,5.0,9.0,5.0,HFFFEGEEGAHGBHGAHDADCBGGEEGEGBEGBFFH,True +200,27.0,17.0,26.0,18.0,16.0,17.0,15.0,13.0,BDEBEEBCBBCDFCHCCABDEGCGACGACACFGDDGAACBACEEDBDDCCCHCDFAHBGEBCHGGFCGHHHABHBGAEHCBGCDAEDFEFBEAHEAFFGDFHDHHDFDBFEBAAGAAGAGFCBCCEACEACECFAFAAFAADCFDAFDA,False +201,14.0,18.0,22.0,18.0,23.0,25.0,18.0,25.0,EHGEHCBHCHHAEHDEHDEAEBCEBCEGFAHFAHCEHBFHBHHBHEBCFADGHFGCFBAFBDHCHCEHADGBDFBFFBHBGGEFFFDFEBCDFDHCDHBECDEHECBECEFAGFCGCAGEHGEDEFHFCGCCDACAAFDAHDFFDBGDGAFGCBCDFEGFGGE,False +202,6.0,4.0,6.0,6.0,4.0,7.0,2.0,1.0,BADGAEAACFACGEFBACCEFCEFBDHDDFDBFDCF,True +203,4.0,8.0,7.0,5.0,6.0,6.0,6.0,7.0,EHAECAEHBEHBFHBCDBAEFEGGCFGDGHHACBBCGBDHCDFCDFGBF,False +204,6.0,15.0,10.0,9.0,18.0,10.0,16.0,17.0,EHHEDFBDFGDGEDGHFEEDDBGFADFCBHCBHFEEFAECGHHGBCEDCEHFACGHEGHEGCBGHBCHBEFFEHADBAGBGHCHEEBEAGEBGBHGBHCBG,False +205,6.0,8.0,4.0,6.0,11.0,10.0,4.0,7.0,BDFBFFCHFBADBGFCGCCEEAAHFAHFGFEEFBEAHEBDEBDFHDHEGEEBEHDA,False +206,7.0,11.0,7.0,14.0,12.0,11.0,11.0,15.0,DFFHFBABAHBEHBEHDHGCHFDFAGCGHEBADHGDHCEHCEFCEFGFFGHGCDAADGBBGDBGEBFEDHABHDBCDHHEFDEGDEDE,False +207,14.0,19.0,19.0,16.0,15.0,16.0,25.0,15.0,BHBBDBDDGDAHEGEGGECDCCBCDAEBGEDGHDCHFEHACACCEDCGFGFEGDGGAGGAGGHFBEGCEGCEBCAFGHEBHDAEGAFHHCADFBBFBFFDHFCHFBBGBBCBACGFDAFHBCGFCGEDGADEAHFCHBG,False +208,14.0,24.0,23.0,25.0,20.0,23.0,13.0,19.0,CGFHBECCCACGAFFHDFHDAHCCFBDFBCCBGFDAHDABGABGHBFHCDGDDHBHEBCEDEFFEFFEFFCDDGGECDEFDADDHEACEAHEAEEBFBFGBDBBFCBDCFDGFHBBDBCGCDAHDCCDHCEEFEGGECBBABDCBDEFEHHEHHBHBADFA,False +209,5.0,7.0,7.0,12.0,11.0,5.0,6.0,4.0,BEEGAGCAHCFDCAHCEFCAFGGDDEDCBDBEFBEDDADDHDDBBDBEEEGCEGHEF,False +210,21.0,21.0,29.0,26.0,25.0,22.0,25.0,25.0,HGGGCBGCBGFDHCEGCBADBADBDFHCBHDBEBBEHBEFBCABCACCFCEFHAFHGFGDDGDDHHDEDDHCBEDDEDCBGGFAADADGACHAFDBEBEECDECEFGGHECHEFHEBHEDGCDCABCEFGEGHFGHEECDBHDFDFGCAEAGEAHCHFAHDGHACFACGHHGDHGCAAEFAFBCBECGFCFFCA,False +211,25.0,20.0,15.0,18.0,16.0,31.0,22.0,17.0,GDHFDBEDFEFGAHDFFDBECFDAFDBFGBDAEGAEGFDCFDCEACBAFHGHHFBFFBHHEAFBAFDCFBGAGGACBACFCEACEACHHGDHGCGFHGHAGABGBGDFHHFCACEBHEDDAFDAGCADBEGBFGBFEFFEAFGCFBHFEHGABAABAEGAFDFB,False +212,11.0,12.0,15.0,21.0,14.0,13.0,13.0,22.0,FDHBAHAHFDBFDFCHHEFHDFAGBADBADCHDFFDABDHCDHCGAGFHDDHEEHBHHEHBCBGDGCDCDECDEGEBHEHHGHDFBCFDAGCAGCACCEFCDBGEBGEDEFGHCGHEDHEA,False +213,26.0,25.0,22.0,24.0,22.0,21.0,23.0,28.0,DGGABBFFGEFGHFBHBHFAGAHGECGEBAACCADCHDBGDHCDFEDCCCFBFAHDEGGBGECFEABGHDEADGBGGFDEFAABAAHAAHCAHGFHBFABFAEHHCHHCFBEEDEEFEGDEHDHHDHCBEABAGGAFGDFDCBCHBCHBHEBAAGCADCHFCFDBBDBCDECHACHDBEDHEFGADGHDBE,False +214,17.0,18.0,21.0,25.0,26.0,17.0,17.0,17.0,FEFAEAHHABBGBGGCDGDEEDAEBGFHHCADDHDDEDDEAFECGGAGGEBGBACEEDEEDHDDHGBHEBCBHADFEDEGGCDDBDCFCHFEFAHFHDBHDBHAGCFEFFEBEEBEEDGEACFABBCBFDBFHFECGHCGACDCCDCCECFHAACADC,False +215,3.0,8.0,12.0,3.0,11.0,1.0,8.0,8.0,ECHEGGEHEEBCEHGGHBAADGCHBCBBCHBCHBCEDFEGHEDCGCCECEBCGA,True +216,3.0,7.0,2.0,4.0,7.0,5.0,4.0,9.0,EEBACHABHEFDEHHEBHAFHFCHEDGEBBDFBHGBHGFDG,True +217,24.0,19.0,23.0,32.0,19.0,19.0,18.0,19.0,BDFHFFHEAGCGGEHGAHGADAEDAEGACABCBFDEDDEHDGDDEDDGCDGAFBBEBHFBDEADCDDCHBCEAHDBHCBHCACBGCGFCGFCGDHFABCACCABHEEHDGBFFDFFBHADDDCAAHDAEFEEFBDFADGADHADFGDCGCCBECADAHHCFDCGBEFEEDHBA,False +218,15.0,9.0,15.0,14.0,9.0,15.0,10.0,14.0,EDDHBDCEDAHHCDHCDEFECFDDBDEGDCAFCAGCHCFHBFBDFCABCEGEEHHGFHAFCABHABDAFAHBHHGFCGFHGBAAFDAFAAFEDFAGGCCGC,False +219,24.0,26.0,20.0,28.0,17.0,21.0,17.0,23.0,FBGGAGHAGHGGBGGFFDAFDHDCFBFFHFDHDDHFDHFHCFGDHBEFCEACHFEHCBADHDBADCEBCDDAGDAFDAEDEHCAFDAFDFBBAGBGHBCHAFECHDCEBBEABGFHEBHDGCEFCBACBACBCCBHBFGDADAAHAHBGDBDEBGECEDHDAEBAEBAEHADCDBC,False +220,10.0,6.0,12.0,8.0,3.0,8.0,5.0,9.0,DEDDFFBCFCCAGBFHBACAACAHFAHBEGGAGCDCCDFCDFCAHCACDHEHHABGDBHFH,False +221,18.0,20.0,25.0,20.0,16.0,11.0,30.0,25.0,BFFBEGBGFBGHBEFEDHBDCAAHAGHFGDADCBDBBDECAEBAHGHGABBHHBGCGECEECADDDGHDGBBGBCGHHGCHCCHCFHGGHAAHAHGAHGEHGDHBEGFHFAHGADFEGBDHFDGCDGCFGAGCCGACGHEGDCCCABCECGEHDEDDCCECADCB,False +222,19.0,19.0,21.0,28.0,17.0,28.0,23.0,16.0,FFFFGGBAGBFCDFCBFDGDDEDDFDEFCHDCHACAAFFDGFHCFBCDGEGEECCCBBAHHDEHDECFGGGDDGDDGDDCBACBABHCDCFDCEBEGBCHEFHGBHABAGFGFADHAGFAEFHEBBFBEFCGFHAFGADGAFHBCABDEDDCHFEHFEGAEDCGDFADBAG,False +223,23.0,19.0,28.0,13.0,18.0,28.0,23.0,33.0,GHBCHBGHEHEAHDHGDCFBHGCHGCFGCBGBGCDHEFAGHEGAABBHECFCFGDEHCEHAFCADAGDFGDHACBACHACHCHFBEFCFGCHHHHCHBCBEDBFHBEHBAGEACHACFAGGHGDHFFAFEADEAHFAHCCHEFGEFBFCBHDFGFFGAFDACDECECBEBFHBAGCHGCAFFAFF,False +224,3.0,2.0,2.0,3.0,1.0,3.0,0.0,0.0,DAADFBDFBCACFE,True +225,18.0,28.0,26.0,15.0,16.0,22.0,28.0,24.0,CCBGHAGAEGAFGBHGCHGBBBHBBHCBDDBFDFGECEECAGHEBBGBAGBFGCHCCDGCDHEAGCBBFBBFCBGGAGBDGHGGHGHHFHDCEDAFGHBGABHBEAACGCCHCCHBHHFFFFGCFHCFEDACFGEFCAAGDCDDHDBAABFACDABEGCEGFEHFEFCEDBFHBEHF,False +226,0.0,1.0,4.0,5.0,1.0,5.0,5.0,2.0,DBGCFGDHGFCGDHGEFCFDCFD,True +227,9.0,11.0,5.0,9.0,13.0,8.0,7.0,11.0,DGHBGEBGHACBAFHAFHFHDDHCGEAGEDEEBEAGFDFBDFBHFHCDHCEEAFBABBEEBEBDHADHGEEAC,False +228,3.0,5.0,4.0,5.0,8.0,4.0,5.0,8.0,DCEDEHGEHGFCEFGBDHBDCBDHFFHEAHEACGBGHAEHEB,False +229,5.0,2.0,1.0,1.0,0.0,2.0,0.0,0.0,ABABFACFADA,True +230,17.0,15.0,18.0,10.0,25.0,10.0,12.0,11.0,ECCHCABEAEAABAEBGEBCEBGAAGBBDFHDEHDEHCHHCHCEHEEHCGBAFCDEEFGEGGCFDEFBBADBEEFHEAHECGFCDAAAFBBCCCACBGGBAEDDEGDECCEFAEFAEG,False +231,31.0,18.0,29.0,27.0,23.0,14.0,25.0,29.0,DGBAGHGHDGCGACBADBDDEADFCHGDBFEBHEBHEFHFCDFCDACFGHDDDDDCGCEAEEADCBDBGGHCAACAEDACHEHHAHDDFDEHCEHCECEHHEAFEABCGEGABHEDHEFAGCGGCGACDAGDACAAHACBBCDACAACHCDHGAHGFBDAACEACECFEHGGHBGHBCFFGDBGHBEFEHHAHBAG,False +232,9.0,27.0,30.0,27.0,17.0,16.0,18.0,20.0,HDBHDCCCHHCHECBBCGCEDCHCADGDBBEBGEGGFDFDDGDBBFHCEEDFFFHFHHDGCEBCABABDEHDHCDHFDHFDHBDHGGEECBEHBDFDDBCDCCBCCGCAHDBBBBFBEHBEGBEDDGAAHCBECBCCBCFFEDFEDCCGBAGACGDCAFCGFGG,False +233,13.0,14.0,9.0,12.0,10.0,11.0,7.0,12.0,CACBADGHDGHDFHDFHDEEDGEBBEDHACHABBFCFAEHACFDCEAHEABFFBFEAAEBCHDGBDBBGCBFEAFGDCDHHABHABGF,False +234,27.0,12.0,19.0,20.0,14.0,11.0,16.0,19.0,DCEACEBHDGHAGFBGABGABGABCHFEADDADAHDHDGBFAECCBCHHFADFEFAHDAEDCHCHADBFDCGDCHECGAAAAGBAEEHGCCGEAGEFCDFDGGCGACHCEHCEHDEHBCADAADADDFHGAHBAHBAF,False +235,10.0,14.0,16.0,10.0,22.0,13.0,14.0,12.0,BCEFFEFBBGBBGEDGEABFACCDCCDHEGHCBDGHEEEFAGBHGBEEHEEHDEFDEFCECDECHGGAGFFEDGHBECBHCGFEAAEAHGBHGBHEBAFACCEDCACFDCF,False +236,7.0,11.0,9.0,8.0,13.0,11.0,4.0,12.0,AEBEHFHFFGFHBFHFAHBHHBHFEFABBEBAEFCEACHHDGDEGABCCBCEBDEDCEACFHCFDCHDEEDBGDE,False +237,23.0,30.0,14.0,18.0,17.0,26.0,17.0,30.0,DGDDFCEFCGCBBHACAFCEEEEAADADEHFABBADHADHFDBFHHFHDFDAFEADBADCAFAFBEBBEBBCBBCFBEFBGFBHBBFFHFAHABHEFHBFHEGHAAHBAGBGFHAFABEGEGGDCGBHBCHGHFGHGHHCDEFFHCBHBBHGEHGDHFDHCDBDAHGHBEAACFG,False +238,19.0,27.0,27.0,14.0,19.0,23.0,28.0,21.0,CCCACCFBHFGEBABBGFFGBCHBFAAFBAHCAHCBGABGADDABDAFDBCGECFEHBCHGHHGHEGDEBFBBCGBGHBGFBCCBDGDCHACHADFADEHDEHEGADGAFBFGBEGHFHEADFCCGCCGFCEFGHFEFBCDBGHHECGBCFAEBBCDGAGCAGFFEHGEGFEGBECHE,False +239,12.0,6.0,10.0,11.0,16.0,6.0,12.0,10.0,DBDGGDGCDECGHCHEAHGDEFEEFEBBHABCCDACGFEGHECAFAEDAHAGCBGAHGAGFABFDEEDGEHEECEDCEAHDAH,False +240,12.0,11.0,10.0,12.0,15.0,7.0,12.0,8.0,EHCEBGEBCADCDFCEGBEBCEBHDGAAGDGHDCFDEEGBEFEEFGEHGHBEABEAFCFHCGHCBADAADADGAEBBDDHDFGACGA,False +241,24.0,20.0,23.0,18.0,18.0,16.0,33.0,12.0,DCADHACHFFHADCCDEEDCEDCFAAFGBCGACGAGGACHBBDBCCBEFBGCDGHFECABCACGAEFAECBFFFHGCAECAGHEHBFHBAGEFGECGHBABCADDGGDGGDGGCGCFFHGGEAGEGEEBBEGAGFFGDGGBGDBGDCGHAAABGEBEBDDBDAA,False +242,2.0,5.0,2.0,2.0,7.0,2.0,2.0,4.0,EHCHBDECDEGFEAHHABBEBFEBGE,True +243,5.0,8.0,9.0,5.0,11.0,13.0,13.0,9.0,ECEEGBGFFHFBEFHFDBGDBGFHFFHGHCGHEACEABBFEEEEGCGGCFBCDCCEHCDHGAFGABGHFGAFD,False +244,8.0,13.0,8.0,11.0,10.0,14.0,17.0,10.0,EGDHGCEDHEAHFBCGBAABGEDAEDAEGGDDFDCFGCEGCGFADFCFEBBCBFDGFAGFEDFBGFGHBBHEDHGGHBAFBFHCFHGBHGB,False +245,10.0,16.0,19.0,10.0,13.0,11.0,21.0,15.0,BEEBGHAGHCCFEDFGFHBHHDFDDHCFAGFAHABFABGAFAACBECGGGHGCAGCHCEFGEHBEHBGFGEFCHDHHDEBCABDGBGGCGGCBGEBGDCCCCDCBDEBGEBECCH,False +246,9.0,13.0,8.0,9.0,4.0,11.0,15.0,3.0,BDDBDDBAGAEGABGEDFCBCCFCDABHCBGDGGEGCEFAGBAFBGGBGGBDFFAFBCGDHGHFFCFAGFAB,False +247,24.0,29.0,19.0,27.0,21.0,19.0,25.0,36.0,AGGDCEDBEDGADBCBEDBHDFHDBEFHEFEEGEGDEABEFHDBHBHHFFAFBGGHCFFEAFDABEAFCHDCABBBCBEEBFBGAGHBGHCABCAFHDGHCHHCDGADHADGFHGFCGDBHBCHBDAEGHHGHHAHCAHDDBGHBGCEAHGADDHDECGEHHEDEGFEDABHABHABCABDABDACHGCBGDHHFHFFGC,False +248,23.0,15.0,19.0,20.0,20.0,17.0,12.0,20.0,AEDAEDAEFADFAHFAHEEHBBCBBDBCAFAAGCCGACEHEADFHDFCDAHGBEFFEFDAFGACGECEHHGADGBCAFCGCHDDDGCFFDBCHECFEHEABEABDCBHFDHECAFDABDAGEBGHGEHDBADBADCHCHHCFHEEH,False +249,5.0,8.0,8.0,6.0,8.0,12.0,5.0,4.0,DDADDFEDFHACECHGGHCDBBFFBEEBGEBCECCGBEAAGAEBFCFFHFFBFFCF,False +250,9.0,9.0,5.0,9.0,9.0,5.0,9.0,6.0,EBGEGDECAEBBGBFDBACGCBBCBBFDADDACDGEDGHDHDAHEFHFGAEGHFGAAEHAE,False +251,3.0,4.0,6.0,7.0,2.0,6.0,5.0,5.0,FCHFEBDGHDHADFGGFGFFEDBCCBCCHGCHDBDDAA,False +252,23.0,16.0,22.0,22.0,17.0,24.0,15.0,22.0,GDGADAHGFBBFBCHBDHBDCCDHEGADCHBBDFHCGGCEFBECHECEACFDBADEACEDFFDFFDFCEFCGFCHFGAFADGAFHAEABFDEDHHBAAAAHGABGDBFEHFHHFCHDCEAEEAEDCFFAFHCHHADHACHAEDABDCCGGCGFCBFGEHBD,False +253,28.0,21.0,24.0,17.0,16.0,23.0,19.0,22.0,HBGAFCHGAFDHGAHGHGDDGADGECAACFACBDGFCBAHBHDBFDEFABFACAEGFHGBDGBFHDFHCGBAGCABEGHEFHECCEAEHADHFDCCDCCEAFBDDBFHHFGHFCHCDHCFFCBAEFAEFEEAAEBFCBAABAAHEABBAFBGCBGCBDFGAGCCDECAHH,False +254,22.0,21.0,35.0,22.0,18.0,16.0,18.0,17.0,CGFCBBCBBCFBDHEGBFDEHCCAECAHAFDEEDAEHAEBCHFHBFHCHBGEACCCCDCABFABCDBDHCGCCGDCDDADDGGEHFEGCCBCBAFDEFDAADFAGGHECHECHECHAHGCFBBBBAGGEDBFDAFDCEDCEDCADCBHEFCAGCAGCBGFDACAACGGH,False +255,16.0,23.0,16.0,16.0,20.0,17.0,25.0,22.0,FBDCDGFHBEHADAEBABHAGDEEDGEAABDDEEFEEDBCGGDHHDHGDABBCBBCDHCDBGDBGCHGHAGFECEEBEHFGDFACHGHHGBHCEHCECABHADHACFBBAEFCEHAGHGEHGFHGFGGFGBFBFCBGCFGEFGEHBBGFCAFGAB,False +256,4.0,5.0,1.0,1.0,3.0,4.0,5.0,7.0,BHFAGFAFHABDAEHHGHHGEGBEGBCBHF,True +257,15.0,16.0,15.0,21.0,14.0,16.0,23.0,29.0,BBAHCCDBGFHGFGFFCFGCGHCGHDGAGHDCHDEABEBGGFDDFHDHHGHBAHDGCAGBGEBHBCHGEFGEHGEBFECHEDGEHBAHBEHDACDHHHBCHBCHAFHDCHAHGAGGDDBDDEACBAEEAHDDFFHGFHFFDAEDACDFG,False +258,25.0,18.0,28.0,20.0,16.0,20.0,26.0,30.0,GBDGBHAEEAHBAHBCHCCHCEBCECDEAAFHHCGGCFFDFBAGBHGFHDAHBACCADCAECAFFAFFGGEGCEACECCFCBEAAGFCFFGGHCDECBGHBHACAAFDGHDCHDCFDHFEHFDGDGHDCHAEADGGEADCHDHBGBDGAGGFFHHFHAGHCHHCDBGHBEHDEHGABBADBCG,False +259,10.0,4.0,2.0,8.0,6.0,7.0,4.0,6.0,BFAHHADDBDEBDAHFACEADEFDEHDGAGFDGFAEFBGFEAACHAH,False +260,17.0,18.0,20.0,22.0,23.0,26.0,23.0,18.0,CGCHEEDEBDHDGEGFEFFCAHGBHBEHBACAAFAFFDBFDCFAEFADFAEGBBHADAGGHFGCCGCGFBDFEEEEADHGDCEDFGDEBDHBGHBFFCAFCECGEDADDBHGBECFEBFEDFDDEGDHCAHCFFGFFGAHCDHADCBECBHHBHCGFGGABGCEGFE,False +261,27.0,24.0,20.0,19.0,30.0,32.0,21.0,26.0,GEHGECEEBEDACCACGBFGFCDBHEFEEFGEFBFACFACFAFFAGDACBAGDEBABFAEDAGHAHBAECAFDFEEBBBFEBDEFCHFHBFHFEHDGHBGHCCFDDAADEAEECGGHGFECFEDFEAFACHACEFBEFHHBHHFEAFHBFBBFBHFCAGHHFHHGHDCHDCHFGAGDDGCAGDEEAGEBEDAGHADBBB,False +262,24.0,26.0,23.0,23.0,21.0,23.0,28.0,24.0,CFDHHBBHEEHEHHEFHBDAADAFDBCDHDDFGAFCACEADGBEGCGCHEAHGADGABGADCFFBFEDDAFDCFHBBCFBGDGCHECBEBBCABDAECAHAHHAHEBHDHHFAHGEBEHFAAGBAGBGGCAFAFBAFBDCDCCDGGDGBHBBCBGFGEEGECGEHECDFCBFGBDGCACEFGEGGFHGFDGF,False +263,0.0,1.0,9.0,1.0,3.0,4.0,6.0,1.0,CHCCEFCGGBGFDGEGCECCFCFGC,True +264,6.0,5.0,5.0,2.0,0.0,4.0,6.0,0.0,CCAGBBGDBGDBACACGAGGFFFAFBAC,True +265,4.0,10.0,10.0,7.0,1.0,8.0,4.0,4.0,BEFBDFGDFABCABCHFCDGBHBCAFCAFDBDBGGBDFCCBCFHCDHC,True +266,22.0,29.0,31.0,16.0,20.0,28.0,16.0,14.0,EHAHCBHCBECFGBBCHEEBAFBHHAFGBFDBFCBFCBFCBFCGFGECBBGFCEFBEFDEDDGFCFCAGCAFCEGAAGAACDCFGAFGAFHBGABDAGAHCAECABBBCFBCDEAAEBFBBFCCFCCFABFDDFBEHBFGEDBEDEHAECBGCFHCDECACCDEFDADEHCGDBHH,False +267,19.0,18.0,7.0,10.0,13.0,13.0,13.0,11.0,HAHCGEBDCBCBBEGHFGBCGAAGBGGFDGCAEADBAHBFEFFEAGEHCHHBAHAADEFGEAGFFEFAEFCBAABAABEAFGAEGDEDBBABBFBHHDDHDBFD,False +268,17.0,10.0,10.0,7.0,8.0,5.0,14.0,9.0,DCADHDGHAGBAEHECHCGADHCGAEGBEGAEGAEGACAHGHDCBGHBGFBCAAAACBBEEBGBCFCAFDAFDHFGABGA,False +269,1.0,3.0,0.0,1.0,3.0,4.0,3.0,1.0,GHGGEBEFBFABFEDF,True +270,23.0,19.0,18.0,18.0,15.0,13.0,11.0,15.0,AHDAFCAECAFBHBCEFDEFCEFEDAADBADCDDFDAFGEHGEAGHADBBEACFGBDHADGCCABHHGHFBEDGHFEACEFCBAGAAEABEABGABHBEABGABFCBACGDDHFCHBCHBHHCEDCDDCDBC,False +271,7.0,9.0,4.0,6.0,4.0,10.0,14.0,6.0,GDDGADGAHAAHABDGFFFECFBHBEGEGHEGDCABGGFFHFFHFBGABGDBGCBGFGCB,False +272,9.0,5.0,1.0,2.0,6.0,2.0,1.0,1.0,EDAEAFECFGHAABAEDEBBEBAABAA,True +273,6.0,7.0,5.0,6.0,3.0,4.0,5.0,6.0,DBGDAGHAGECGFBHFBGDDFEDFHCBBEHHCAHBACBACAD,False +274,13.0,30.0,20.0,14.0,22.0,14.0,15.0,16.0,HBGBBDCBAHEFEBDBCABCGFGEHGECGCDECDBFDECGHBFHACDCBBHEHGGHFGBBBBHBBHBBGBEABHDBGDEGEFDECCFHEBHEHGEFCFBCFCDABAAHEECEECEDCEDGEBFEBAABGABCBCAAFDAFDHFC,False +275,5.0,8.0,10.0,12.0,2.0,10.0,10.0,5.0,HGDDCDFCDBGFCGDBGEAFACFDBDDBHDBCDCCFGCHGDFGCFDABHGBAGCGFABFEHF,True +276,5.0,1.0,0.0,3.0,1.0,2.0,0.0,3.0,BDDHFAHAAHAFEAD,True +277,24.0,23.0,18.0,24.0,16.0,33.0,19.0,28.0,ADCABCHCAHCAHEADEAHBGBCGFGFFGAFBDFGFBGDEGDGHHGHHACDDGFFAFFBFFEFADHDDADDFFAFGBFBBFHFCHBDADEAHECEDFDGFDFFDCBBHDAHBBHCEGEBHHBFFCCHHHHCHBBHDHAGCAGEDEHDGHDAFAFBBFABFAEAAGABGFEHCCBCHECFEDFGFE,False +278,12.0,29.0,23.0,26.0,19.0,18.0,23.0,13.0,BEBBEHBCAFAHEDDCDBBDBBDAFFAFCADCGGBGGCGHCFECEBDECGEHGEADBFDHFDGCDGCBCCHDBEABDCBDEBEEBDCGECBDHBEHEAGAFGHFHEFBBDBGEBFHGGHFGFDGCDGDDCFFFDFECCGCGGFBDBAACHEDBDDBGCAGBBC,False +279,16.0,11.0,17.0,16.0,19.0,22.0,19.0,14.0,GFAAFDCCEGCHGBEGDABFBDFEFEEBEBGFCGHHHFHAFDADEAHACBFCDFHFGCDACDFCGFEDFEGADGAFCEHCAHBBHEGCDDHDCAFCAFGEEGEEFBEFEHAHFDEFDBGDBGAFCAGCGGCGHE,False +280,10.0,14.0,13.0,11.0,22.0,14.0,17.0,12.0,EHCECEHBFGCGGCAHCDGCGGEDBBBFHCFBFBBFGHGHFABEAEGACGACBFDBCEECDEBFEBDGHDEBEGGECGEHGEDEEHFEHFEGFAADGADEHDAFDHFEEFCBA,False +281,32.0,31.0,18.0,18.0,36.0,28.0,25.0,12.0,GAHFABEGCGAEFADGADFABCADAEBAEFEHFGBGCBHDAHAABBBECFEAEEFEEFEDAEBAECADCDDBBBCBBEDBFAAFHEEGFCGEEGEFGEFAFDABCABDAFGFBGFEGBEACGGHFGAFHBBDEEEGGBHGFFAFFGEFGEBGDCHCHGBBGABEABEFEDADCEEFDCDHCDBGABAACAHCEFCEFBEB,False +282,19.0,24.0,17.0,28.0,20.0,14.0,18.0,11.0,CEGDBCDFGFGCADCEEGFABEDBDBBDEFDEADBGBEGBACDDFDHFBHGGCGAEGHEGHECDDGDFGEFABAEEHDFBDFBEEBHCDCCEHHDCGDBHDFDDADDEEDBBBBABHAHDABAAGADBCFBCBECDAGECGACGACFABFA,False +283,26.0,21.0,30.0,21.0,22.0,23.0,22.0,14.0,ABEAFHABHEFEEFBHDAHFBHFBAFBCBGGHGDHFDHFBEBBACCAECAECACGBCFFEFCEGGACBCDFAAHABGDEGDEGDACFEGDEGAFAACCBEABGAFDCFDFFGACHCEGCFGABCHGAHCDHCDCCDCGABDFBDEDCGFFBFEACCDCHDGGCGEEAEBAGDCDDCEEB,False +284,14.0,18.0,15.0,12.0,15.0,14.0,12.0,12.0,DHBFHFFADGAHCABFABEEFDEAGEAGDDBACBCCBGCBEEBEAHEHCFFCEFCBCGDCGDEGHGGABADBEEBEHCHHDBEGGFFEFDADHAHBBDFBCCBGABCFHCFA,False +285,16.0,15.0,17.0,12.0,11.0,20.0,18.0,11.0,HGHCBHCECFEHFEGDAFFGFEGFEAFGFBGABDBBGBACBGFBECAAFDAHHFGGAGGAEGCBDBBDHEFGGDGEHAHADEADEFCCFCFADDBCCBCABHAFFCFGCFDCFACDBCGH,False +286,11.0,13.0,7.0,7.0,10.0,17.0,12.0,13.0,FDGFDGFHABDDHFAHBHFFGCFHBGAGFFGFHHAGHEGHCGBCECDECDBHBEHBEHCAFGABAFBGFBEFGEABFBFDEFAEAHEABC,False +287,8.0,6.0,3.0,14.0,2.0,6.0,4.0,6.0,BGDFDCCDGAFBADBDHHDHCDHAAFAADBADBFDEFABDGHEGDDFHD,True +288,13.0,9.0,15.0,13.0,19.0,11.0,16.0,13.0,GGEDADGABGCBHAGACCFCHECDDCBAFEEHEBBEABEACFACEDHEAFEGFGDAEAAECDEFEHHEHBFFDCFDCDAGDHEBHCGHGGHCEFCGFEGEDGDCGHBGH,False +289,21.0,24.0,27.0,24.0,13.0,22.0,21.0,28.0,EBFBBCGBDHCAHFAHBBHBDHBDHADECDCAHCGHGFHADHDCHFBBAHBDHECABFBFFCDFGDFECBECBCHEAHFHHEHGGFAGBDCEHCFHCGGBEGFHBFGAFCADDFDDBDFCAFCHFDDACGACGDCGAGGHDEDECDAGHBFABABBEFBCCDEAHGAHGCCGCFAHDGHC,False +290,11.0,5.0,20.0,12.0,8.0,15.0,4.0,7.0,CBCCHDDHADEADEFDAACCCFFDFCAFCADCGDFEDCECCECFFHFFAGFCEDEBFFHCHGCDBHGCFDAFBAEHACCACB,True +291,20.0,16.0,14.0,23.0,25.0,13.0,17.0,18.0,GBEGBEGFEGFBFDBFDBADHAFBDFGDEGDGGECCECAEAADAACHHHHBHEGDADDBHAAAEHEBDEBGEAEHDGHAAHFABCEGDFGFCECDGDABDHBDECCABFBEEDEGFEHFEHGAHBDCDAEHAECDCFDCEDHGHEC,False +292,22.0,21.0,19.0,22.0,30.0,26.0,23.0,31.0,AHGAHGABADGFGGEEAEFDCABCFBCGBCBHCBCFEDFEDHADEFDFBHCBHAHEAHEHHEHEBGEAGEDCEHGACGDCFCEFDEBDEBDFHACEEHBDDGGEBCEBCGHFGEABFAEEBHABGAHGAHDHHDHEABEGBFAEGHEHCADFFDFGAFCDDGFHFFGFFDEBCHFEGFCDFHHCHFBEGHHADH,False +293,16.0,24.0,24.0,18.0,24.0,17.0,14.0,18.0,BDDACEACHABHABHECHGHEGEEFCHFAFAGFBBBGBEECEEHEFDBDDBDDGCGBCEHCEDCBFABFBBCCECCGBEBAABHECEGCEDDECFECFHCFHCGBCFFDDFADFAHHCGBBBCAFEBHGDGADGAHCBEAAFGDBHHEDCEDFEH,False +294,32.0,23.0,12.0,12.0,9.0,21.0,14.0,23.0,BCGBDHDCGGGDAFDFFBCABCABCFGGFAAFBHEBHGBGGDAFAACABHBFFDAFAHHBHHDHGDEADBHGBHBBHBBFACCBECAAAHABHAEAEDFGCCEAFFHEBHFHHEHDABAAGAGHADAAHAACEAHAAFFBFFBFFH,True +295,25.0,28.0,34.0,29.0,21.0,15.0,21.0,21.0,GBBDDFEAEADECDAGBCFBADECDBBDCCGCAGCDBCBBCBDCBGCEHCGACACFBHFDDBCHFCGAGGECFFABDEGDEFDHFHHBBHDAEDBEDCDDCDDCDAADFACEDHHGACGBBGAGAEGFGGHCACCDHGEHGEHGHCEACBHFEAAEACEACHHCHBCBECHHFEBBDCBFCBDDBDABAEFAHG,False +296,10.0,5.0,3.0,10.0,3.0,6.0,4.0,2.0,FCDBCACHBFABDAGEAGDADEBDFDAFGABAADEADHGDFFD,True +297,18.0,24.0,24.0,26.0,29.0,26.0,24.0,26.0,HAEHBEAEEHCACDDCFDHFGCBHCBCDHFDEADBBGCBGABFAFGGHGEAGDBCCGCBDFDDFBEFBEGDEGAADHADHBHADHCDFEFFEGGEBAHBCFGCEGEBGBFGEAAEDHFDAAGHFGEEGEEDHECGEDFEBBDCCDBDECFCBBEFHFCGFEHHEHHAGHCEHCDFCDFCDHCHGGHFEFFBFHBADB,False +298,13.0,9.0,11.0,21.0,12.0,21.0,9.0,8.0,DDADBAGGAGEAGECGEFHFCCFBCABCABHAEFABFDFCHHDDEDDHADHCHABFFFEAEDCFDEGGFDDFCDFEFFEDFEBADFDDFBDFCHBGFCEDDAFG,False +299,9.0,10.0,7.0,5.0,4.0,5.0,9.0,5.0,AEBFBGFGGAGGADCADGDHGHEBHBBGEBGFCHBCHAAFAABCECCFDDBCAB,False +300,9.0,10.0,14.0,12.0,10.0,5.0,22.0,10.0,GBDGFGGEGEHGDGGEGCCGACBDBBDABDAEFABBCEAEHAGCFHDGHGGDGADGHGGBFCDHCDGCGBDAACEHCEGCEGDHCHECHCBF,False +301,23.0,15.0,14.0,8.0,21.0,17.0,19.0,20.0,FGCEGAEGEDHEDBGGECFFHEBBBFDAHHEBAEBHCHEGAAHABEEFEEFGBHGCHCAHDAFGGHGDHGFAGBABFAFHEEGEAAEDAGFAEFACFACBHFDCEHBAHCAHGAHCCGCCGEAGEACFADFHBBHBF,False +302,27.0,23.0,30.0,20.0,17.0,18.0,24.0,20.0,AACCCBGDBFHBAECFFHBHHGHAACGCHDDBFBGGCHGAFGAGGAGGAHGCHGCDGCHBHABFDBDDEEDEEDBCFCCFCHBHFBAFBDFHFBAAAFCCGHCDBADAFCABEACGBFBEEBAEHAEGAHGACBBDACDFCDGCDGHDEEDEBCFFCAACHECGCBGCEGCDAAEEHGD,False +303,30.0,27.0,22.0,22.0,20.0,20.0,25.0,21.0,FCHFDBBDBGCAADEBGFBGABGFEGHAHBADAEDACBECFFCFFGDBGAHHAEHFCAFAACEDCFFBEFAEABHDGAEHDDBGCBGEBGEAEEFBEBDHDAAACCHCCHGDAGDFCFABFHBFHBGBBDHBDHEEHECHDCADAEDGBCCBAGEHGEBGFBGCCACCAGAADAHGHHGFDABGGGD,False +304,29.0,17.0,17.0,22.0,14.0,23.0,28.0,17.0,DABGFCFHAEGAFGFBCCBEDDHFCADEHDEHGHDGADGHGGCCFFFFCCEGHEGBDDDDDFDFGDFGCEABADBCHADBGDCDAHFFBGFGGHAGHAGAEGEGCAAHAAGAAEBAGBGFBHBBHBGDCGFCDFBAEBHCFEAAEAAHGAHGAGFACFDCFEAFDAB,False +305,11.0,12.0,13.0,10.0,10.0,17.0,17.0,13.0,BFDDADEGGFGEFBEAGHAGBACAECAFFBBFHBCHGFHGHGFFGCFCBBAGCDGDDGCGHCBHDGGFHFFHGDECDFCDEAGFAFBAECAECHBHHEHCEBF,False +306,7.0,10.0,4.0,3.0,5.0,2.0,7.0,5.0,BHBHADABBABGABHDGHDBCEFEEFCEBCEHGGCGBAABGAG,True +307,17.0,17.0,13.0,19.0,19.0,19.0,22.0,12.0,FDEAAHFFBFBGFBDFGDFGDBGDBGFBFFHFFABEGGGHAAHEAFEDFCBFCEDCDAGBAFBGHDHCGHGDEGDGCBBDHGABCDHCFHEGGDBCHECEECEADEAEGAGBAEEDDEGCEGCHACBAFBDEDAFGAE,False +308,16.0,19.0,32.0,19.0,25.0,21.0,28.0,24.0,BCGCCBFCFGGDHGDADAACACGGBADDGDDGFBCHHCFECDGGAEBAEGHCDBCHEEHAEHFEFFEGFEHDCCCEGHFHHGBGDEGFHCFBFHBGEGFCGFCBHGBHEBEEBGBAGEEGHEAHEBFEBHCBGGDGDCHCCACCADBAHEDFGCACCHHCHHFBAFAEEDCECCDFCDFCDFEG,False +309,12.0,7.0,7.0,14.0,8.0,9.0,9.0,23.0,HFHHBHGACFAHHHHHDHBGHCEHEHCFHCBHDAHDAHFGDDHEBGFDDHADHBDGEEGDACDAHDAHCGHAADAECBEGEFFAFBDFG,False +310,7.0,9.0,2.0,2.0,5.0,3.0,5.0,9.0,BBABAGEAHBGHFEHBEHBHHAHBEGBGGBDACFCHFDHAAE,True +311,26.0,28.0,24.0,21.0,11.0,21.0,26.0,17.0,BFBEHBHGFHFHDDGADGADGFDCFBCHGFAEAAEAAEAABDDGHDBEDCCGFCFFCBBGGBFHCGGGDBGDBDEBCFBCABGDBGDFGEGCCAAHBGHGGFFBAHBAEGCFBCECHFADGGCECCFCBACBGBBGCCDAEHABFADDADDAFBHFCHAAFAABHHCHBCDBGA,False +312,23.0,13.0,12.0,13.0,21.0,13.0,8.0,13.0,FBAFBAECDHHEEEEAACADHEDAEAEFAEFAEGAEGAEAAEAGGBCDDFHAHHFFHFCCACAEFAHFAECHEAEDDHDGBBCBDFEHEAHBAHBAGCCDDDFGEGEFBBDBBCCB,False +313,3.0,1.0,2.0,0.0,2.0,1.0,1.0,1.0,HACAACEFGEB,True +314,19.0,17.0,14.0,10.0,16.0,21.0,10.0,13.0,AHDAHEEFAEAGCADFEHCEBCGCCGADDADFADFAHAAHFEHFEHFEFFCBFEBAAHEHBEBCCGHEBHCBFCFFGEAHEACBABBABFFGFFGBBBFBGDGCCBEDADAFBFFCHEDG,False +315,3.0,8.0,4.0,7.0,12.0,10.0,4.0,14.0,DHEDBEDBECHEFFFCHDAEBAHHFHFEGFECEEDEGHBGFBAHBHEBEDCFHHFHFDHGBH,True +316,19.0,13.0,26.0,20.0,13.0,13.0,16.0,14.0,AFCBGBFCAFCEECHBBAGCDGCFGHEBHEDCCAHCFEAEDDEDAGCAFCACCADCGDEBFAGDHGDCBACHAGHBFHCGECDCAGCADADFGDCGDGEDFADCADFFDAEDHCCHCBHGBHEBFGBCABHHDE,False +317,16.0,18.0,21.0,25.0,22.0,16.0,21.0,17.0,GDDGDDEDFEGFEDEEDHBDHBCHDHBBBBBBCCBCCHFCHBCHEHADGCDGCBGAFABCEDFFAEBCHBDDEADCGDEFAEGAGCCDCCGFDFBDHCGHGAAFEADAAHEBHEAHFCCDCEAHEAFGBGEBGDGEFGFHGEHFAFDGEDGECEDG,False +318,23.0,22.0,20.0,24.0,12.0,20.0,16.0,25.0,AABCHBFHCDHCGFGHDHHFGAGHBGHBGCEECAEHGBCGDDDHCFHGBHGBHEBHDCCAHCAHAHCAFCDFHHEBDDBGDGEABBAEBCDDFDDFEDFACFABFCHHCHHGBFAEFBCGBDHFDBFDFDAADAFDCEHCBBDFAAAAGECDABDAEFABFG,False +319,9.0,5.0,11.0,3.0,6.0,3.0,10.0,12.0,HABHDEGCCCDFCBHCHHGHAGHCGHCDHCEGCGCEGHEAHFABAECGBBAAFGAEHAG,True +320,31.0,18.0,28.0,29.0,18.0,25.0,23.0,22.0,ADEFDADBAGBEGHEGDCAHAAHCFGCHGFEGFHGCGBFDAFDCFCEBABHDBAFAFFDGDAAHABGGCAFCACCDEBDCCGCCDCCAFGGCHBDHGCHAHBBBBBCCGAADCBDEFDHCAHCHHFHAECDCHDGHDEADEDFADBADEEDGCBGCBGDGEFHAFEAFAAFGEEDCFDHFAHFAFFAEFHEDGD,False +321,11.0,11.0,8.0,16.0,26.0,18.0,18.0,26.0,HFGEAHHHHDBHGEHDFAGGDEFDEFDEFAEFBDFHDEEDEEBGEHEHHEHACGGEBHEGHEFHEHAEGFDGDDGBCEAEGAECDHCGHFEHGAGFCHHEHHFGDFEFFHBFABHDGFFBCEBAECGDABDHBC,False +322,6.0,3.0,4.0,2.0,1.0,1.0,3.0,2.0,CAAFAEHAGBDHCDBCGBAGCA,True +323,10.0,11.0,20.0,18.0,16.0,14.0,16.0,14.0,FCGBEHDGCCHABGBCGACFEFEEFEDCCCBGCFHCDAGDAGDEDFHGBAGEDFECGACGEFGEFEHCDHCDEFHGBHGEFDEFDEADBAEHFCBGCHDCHDCBDCFHBDABGAHDHCD,False +324,14.0,16.0,12.0,17.0,15.0,23.0,16.0,14.0,HDEBDGFAFHDDHDHECHEBHGHEGEGFADHGEFGDFBCEBGAFFAGFHBDHGDCGDCACFECFEHFAFBCEHCFBEFCEADHABCBBCFBAFAGFAEEAGBBECBDGBFGHGBFDDFDDFGAFDAF,False +325,15.0,13.0,7.0,9.0,15.0,10.0,11.0,11.0,BDABDCBEEECAECHCFHBBHDHEAHEAGEDEABEDHEGGFGGFEFBEHEEFBHAAAAAADAADFAEFGHHDFHGAGBBBBCDCGBFGFCG,False +326,18.0,22.0,21.0,20.0,18.0,16.0,22.0,11.0,FAHEBHABFAHGAEGHHBBBCBGCBECAAGDACFBCFEHGDHDDCDDFFCEGHEBHCFCDFCDGCHBAGCEBCBDGBDCBDHGEFADGEFABFGCFCDBCGACGABFACDEDEBDAFAFFABGEBGEGEEDEGDAGAGGEBGCBDCED,False +327,13.0,17.0,20.0,5.0,21.0,19.0,14.0,10.0,CACCAECGEGAFABCCDFAFFHFCEFCHAHBGEECEECGEFDECDECEEABFBEAEEBEDHCAHAADBABFGFFGFGGFBGBHEBHGFGEFBBGCBCCBCBECBCGFEHFHBGHACEFF,False +328,21.0,20.0,17.0,13.0,23.0,15.0,20.0,19.0,HECGCCHADAADGADBEGBEABEHFGFGGFGCBECFHBAAEAHDFHFFBGEBGCBFHAABAABDCBDCAFAAHCGDCGEEGHGDEGCHGHBFHDHCDBCFEAGCAHCEHEEFEFBDHHDEBEEDEBGGAHGAHBEFBECEFABGABEC,False +329,24.0,23.0,29.0,30.0,30.0,21.0,23.0,19.0,HADHFBHFEHCEHDHCDFCBABEEBDEHDACBGDBCDBGDBADCCDABAGCEGBDGBEGCDFAFFGEFGAGEAGEADCGHGBDEDAADEHBAHCAEGBGFBFHBGEBDBBAEEDEEFAEDGCABCEDGFFGECCDACHBDGBDFCHECHECEACEADDDEDFADFAFHCFGCADCEECFCCFCCAEBGGHHCHFDHFEG,False +330,7.0,6.0,9.0,9.0,7.0,8.0,16.0,10.0,HGGAAGEEFBEDHFDAFBAEDFGHFAHGDHEECGHCGCCACGFGHFAHEBHCGGCBGDHGDCGDCGBGDBDF,False +331,15.0,22.0,24.0,18.0,22.0,22.0,16.0,24.0,ABAFBECDEDAHCCGCAAHHCHHGBBGBAGBDGEDEHAECACBBFHHEHHEHHFHDCHDCBGFHFFHAEBFEFGDHAECEECBEFEGCCFBCGBCDEGHBGHFAHFGDBGEAGFADCBCCHCFFDEFEEFBEFHEHDCDDBHDBGFAFFBCCBCFBDADCGDE,False +332,9.0,18.0,16.0,12.0,7.0,14.0,10.0,14.0,AADCABGADACDAEDCHGCBFHBFHBEHGEFGHGECFBCDDGDAECHBCEBCFBCHHFDHDHHFFDFBGFGHBGECCFDFHDBHGBCFFABBACBCBBCB,False +333,24.0,10.0,12.0,14.0,8.0,11.0,24.0,18.0,AHAAHAADADGFHEEGBECBDCEACAHEGHEFHADAADFHGBHGBGBCGAGADGADGAHCAHFHFGEGGBACDCCDGFGBHCFGAFGBGEHACHAGGCDDHDAADGHDGFCGAHBAHBGFF,False +334,17.0,19.0,16.0,21.0,12.0,28.0,7.0,21.0,BCEAFGACAHCFEBBDBBDFFDBCDBFDFFDHFABDGBDFFGFDHFCGFGHCBHAFCEFHHBHHAHFADFBFCBFCBDCHEHDCADFDDEHDECDFCAFAAHABFBDFHFCDGHDHHCHECBEAEHAEFABDEFAFBGHEA,False +335,5.0,1.0,17.0,8.0,5.0,13.0,6.0,9.0,HFEEFACCHDCHDCHFBHDDCACCFCCGCFFDEFAFGCFHAEGFEGFDCCAFCHCGDCGDCHFH,True +336,7.0,5.0,7.0,10.0,4.0,6.0,4.0,9.0,CABCEBDDFADCAFCFGCEGEHDDBFGBFHCHHGHHDFDEHDAACAADHBDH,False +337,17.0,14.0,20.0,15.0,14.0,12.0,26.0,25.0,FEFFADAGDAGFCHHBHHBAFEECECAFCDFDDGGCHGCHFCGDGGBBGDAHDHECHGCBBBHDEHCCHFGHFCHBCHDAHCAGCAGEBHEBAAACEECEGGDHCEBFEHGHCGHCGDABAGHGGBBGFGGDGHHEHDDAAGA,False +338,17.0,17.0,8.0,23.0,13.0,10.0,15.0,13.0,DFFDBGEBEBCDBFDBAEEAFGAHDDDBBDEBGEBGBAGBGBCGEDEAHHADHDDHEDHGGHADDBDHHDCHDAGAECADCHDFBBFABDAFCAGDFFCAEGAEGEFGBDGCHAHA,False +339,18.0,24.0,23.0,25.0,16.0,22.0,30.0,24.0,DGBDGDDCDGCBGFEHEAAFCACGBFEBGCGCABCAFAGEAGEAHDCHBFEGHEBDDBDDBGABGFDGFBHCAEEAGDHEHFEFEHFGHFBFFGCAGCACCDHDDHBDFGDFGEEGBFDHHBCHDFFDCCABGBDGECBEGGGHDCHACHBHHGGHBGABDABHFCHFHHDBABGFCGFCDC,False +340,2.0,2.0,13.0,7.0,3.0,3.0,2.0,4.0,ECCCDCCACCBDCDFCDGAHHFEDFBDCDCCHGCHE,True +341,4.0,3.0,4.0,1.0,4.0,2.0,6.0,4.0,GAEGBCHBCFGAHGAHBACEECEGHGDF,False +342,10.0,14.0,13.0,18.0,10.0,15.0,4.0,7.0,BFBBADBAGACCABFAECCFCCEDEHDABBAFGGBDBCEBFDBFDEHDGHFAEECCDCCFHBFDEDDFDDCDDEHDEFFBDFBDFACHAFH,False +343,2.0,3.0,3.0,5.0,8.0,5.0,2.0,1.0,EAFDCDDCHEBFEFDEFEABECBFGEDGE,True +344,16.0,17.0,10.0,12.0,19.0,14.0,18.0,24.0,DGDFEBGECFCBBGFFEFHEHBEHGCBACBEGFGGHCBHGBHAEFBFFBHHBEHAGAADFAGFAHFAHGACGAEHABFGEGHEHHEHCABDAHEABCDHGEHGAHDDHDDBEFBGDBADGCHECHDHEEE,False +345,12.0,6.0,8.0,11.0,11.0,7.0,6.0,8.0,EEABBCDDGADCAECADHABGABECBECFEFFECDEGHAFHDGHFHAFAABDAHCEHAEHFDCDEGDGD,False +346,14.0,12.0,14.0,18.0,13.0,23.0,16.0,8.0,ECHBFBAFEFGCCDDGFDBFEGFEAFECFEHFEGBDDCHDHAAGAAGFBDBGDADDHGDCFFHEEHCEBGDGCFECFEBFDACDFGDAGDGGCGBABDCBCBAFFAFFAFEAFDHFCG,False +347,13.0,9.0,9.0,6.0,6.0,16.0,14.0,5.0,GEACFCDFGAFGAFCFFDDGGDBGDEGBAAHGAHFFBFFEEFBFFBFCEGBGGCECCAAHAGHAFAAHACGGFBCBBD,False +348,2.0,2.0,2.0,3.0,4.0,6.0,4.0,5.0,EFGDDADHEFBAFECFECFHBFGGHHGH,True +349,25.0,25.0,26.0,14.0,12.0,22.0,23.0,17.0,GCCGCCGEEDFADFDCCEHCBHCBGBBCBFGBAGFGHBGABFAGFBFFACCHHFHABAABCABGHEGBCGBFFAFGACCDDCBFGFAAAAAEACEFCEFCADCAGHAFABFDGADHHGBBCHGEBGCBHCBFDHGHHCEHBBBBEFAFHDDGFDCAGCAGDEDE,False +350,26.0,15.0,7.0,12.0,18.0,16.0,17.0,8.0,GFECAAAAAHFADABEGCECDGDAGEABEGBGBBGBBGCHEFFDFFAAAGEAFBAGDHHFGGAGEADFAEEBEFCGFDDFGDFDBFBEHHAHEAGEABEABEBBADAADAFFCEGCHAE,False +351,19.0,24.0,27.0,20.0,25.0,23.0,28.0,19.0,HHCHFCDGDBGDFGCBGDFGBFEDFBGABHABCABGBGAHGBHGBABCCEEBDFGDHGDBGHFGCFGCBHFBHECGCCBCGBFGACGDCHEEDFBGABFAFFGHDAEAAHDAFDEFDEDEECFEGHECAGCECCFCBABFADCAEGEDDFHFECFEGABGAHDHECBACDGHEEEEHECBECGFC,False +352,11.0,14.0,21.0,19.0,18.0,15.0,12.0,19.0,CGFBDFCAEDFEHEHCEACEAEEFGDAGBACBFCBFABDDGHDEHFGADGHDHCBHCEHCDHBBEFGFBADCGBHEADECDCBDCBACBACBDCHFHHCHFDGCDECGHCEEGHEHFFFFGEHDCHDED,False +353,14.0,12.0,11.0,22.0,22.0,10.0,7.0,14.0,BDEBEHDFDDCDEADEHCFHCAACAABBCDBHHEDHEFBAFDACABGEEDEADFADFBGFAGCGHCFEAEDGDDFDEEBEEBEHHEHHEDEEBHHCADCACHDDGGBFEDDE,False +354,25.0,23.0,25.0,17.0,15.0,24.0,9.0,25.0,FHABBAFCCFBCFBEDDHCHGBAEHCEBDAADFADFHFHHFHBFBCHBHHEHDACDFFAGBGDEGHHGDDCCCAHCEECAEDECFBBHDFCEFBAHAAHAFHAFHBFAAFAGGACEAEDAFDHEGFCFFCDFHGFHACHABBABECCCCACCBBCDBEBBHDB,False +355,17.0,20.0,28.0,20.0,27.0,26.0,18.0,20.0,FCDHEAHEGECAEDAEFCHFEFCCCCBECHEHEDHDHHEGHEDFEHAEDGEDGEFEECECHGCDGCBEDDEDDFDDBGGCGBHHAACABGGBCGBCGDCFHCFBCFBHFAHFEFFCFFBDACFCHBHEEFBGFBHFDGGCECAAFACFBBBABBDBEHCAFFEGCADEADFFBCGA,False +356,11.0,9.0,19.0,9.0,17.0,23.0,24.0,22.0,DCFDCHHGFEAECFFCFFGEFGFFGAHGBHAADAACEFFGGEHCAHCBDFFDGGHHBFHBHHAHFFGGFEGFCGFCHCGGGGEEEFCDHCDECHECEBCFGCHBCHAEHCEGFDGCHBEHBGHBGHFAEAEGGD,False +357,15.0,19.0,23.0,15.0,30.0,8.0,15.0,12.0,EDGEGBEGAEFADGHEFEEDEDDEGGFDAEEAGDAEEADEAEBBCFBCGECBEGGACEFBGDHECHEAHEHGGABCEDDFDDEDBHDBCBACACCGCABEGHCHCCBCCAFCHBEHEHHCCBCEBCEBCEBFBBECA,False +358,8.0,10.0,3.0,16.0,6.0,11.0,10.0,8.0,EADHDFFDBFEGFGCCAFCBHDGEDHDDFBBFEBHHDAHDHEDHGDAGDAEDGDGFBGABGFDGFABBADBF,False +359,20.0,14.0,12.0,8.0,11.0,4.0,10.0,13.0,BAHGAEDBEDCADCAHBABAAFAACGBHGBHABHEHCCHBCGAEACGDCADCHGAECADFAEBDEHFCHEAADHAGHFBEBCEAGEBGBGHB,False +360,26.0,15.0,17.0,18.0,13.0,10.0,21.0,9.0,HCBGGBGGBCCDDCDCCHCHHEGGEAFEDFAGEBDHBGAFGDGAABCADCEGCFGAEABEADHABGAEGFEAFAFCACGADDBEAGAABAHGDCDEADECDBCDBCBHCFDDFAGAEGAHGAGAAFBDB,False +361,15.0,32.0,16.0,34.0,25.0,18.0,29.0,23.0,HDFHFFDABBBBEEBGEBGEDEEGAHGBGBBHDAEGCDACHECHBGDBGDBGDGDDFBGGDEBFAHHHHEHHAHDADDEDBEBBHABHAFGDDBEDHEDHDDHGCHCEFDGGDGGBCFCCFEHFGGFHAEDFDFFCAEGABDFEDGBAGBGDBCFBCHEDADDCDCBBBDEBDEBGHCGBEABFCGGEFCEG,False +362,22.0,28.0,20.0,25.0,21.0,16.0,11.0,16.0,BHCHFBFFBDDBHHBAHBADBAHBAHGCCFCBBDBBECAEFEDHHBCCFDCBBBEBHEBFGBHGDHCFFCFAHHAGAGDBFDGFDBCGEADBFBBAAFEDGEDFDAAGBAGAABEDDACBECBEFDAHCCCCGCEEHAEADEDDEDCEACEAEDDEDDE,False +363,11.0,11.0,7.0,6.0,9.0,8.0,12.0,8.0,FBADHHEHFGGCGAFEAFEGFGGHGHCCHCCBCABAEBAHDDCGFABEABFABABDEBDBHAGGFBGEEGDE,False +364,5.0,2.0,8.0,2.0,1.0,2.0,9.0,6.0,AHGACBAGHCGHGBEFDAFGACHCCGCDGCHGHGC,True +365,33.0,17.0,16.0,24.0,25.0,19.0,21.0,11.0,GDDGDDGBDBAABAFECGEDGEDFAGCACCFHCGHCDAADBACFCHEDAEHABGGHCEEEBAEFEDFDCFDHFDAFAGFBCDAFGEDDEHBEDBDCBHCAGFHFDACAGDABEABGABGAHCAGDAFFGEFDEFGFGEEEAEAAEAAEAEFBBAHBABCEGEDGAA,False +366,24.0,28.0,22.0,9.0,23.0,15.0,15.0,17.0,HEGHECCBBCBBFAEDHBFCBFBBFABGEGCFDCHCCBAAHAADABBBBAECHECEEHEEBAECDDAGDFGDFCDCGBCEBCABEABAAEHGCHEFHEDHFGGAGEHGCBBAFBAHCFEEGAEGABAABAHFHBCCCEHAEBBEGCGFFBHFA,False +367,22.0,19.0,28.0,25.0,31.0,21.0,23.0,26.0,HGHDGHDGEBCDDCAEEADEDEEHAHBDCEEBEFGAHAADGDHBHFCEGEDBFDEFEEBEBCEFCEFCBACBADHADEGDAHCCEDDEDHFAHECDDCBEFBEGBDCHCHAABAACCHCCHCDHAGCAGEBEEAFECHBCHGCGGHFCFAGGEDAFDCBECBEHDEFFGFDGFHGFGGFGFFBFHBCCGAGHAHH,False +368,19.0,23.0,22.0,14.0,18.0,18.0,13.0,20.0,GAHHDGFBGDBFFBHGADABEHCCFDCBDAGDBFBBFBBFBFFEFFAHCAFGAHADHEBFBAFBECCEBCDDAEDGEHBBBBACBAEBDECHEGFCHACFDBGCHHCHGEHCCHCGHCGECEAGACHFCHFCHDEEEEEBDACAAHA,False +369,8.0,9.0,10.0,4.0,11.0,7.0,17.0,8.0,GEHGEBGFGGFCGEHAFBBFCBHCFDCGEHAEGCCGAEGBBCHBHFEAFGBCGADGADEADCGCHGEBAEGHEG,False +370,14.0,14.0,22.0,16.0,19.0,13.0,17.0,12.0,AEAAGFACECCFHBFDEGEAGADCEHCECCADHDEGFGGCCGBHGBHGBAFDGECGECGHBDHBABFACDDEBFECFEFFCAFGEGEEGHGCBACBCBDABCGBDFEDEDDHDFBDHCCHCCHEADE,False +371,24.0,19.0,21.0,13.0,20.0,18.0,17.0,23.0,GEGEADCDGEHBDCBDHAHCEFCEFEEFCDFBEGAGFHGFCCHCCFFCFFAADAFCABBBHGCHDHEAAGCAGDABHHCHHCHGBEFAAFHAFHGHHGDADEABEGBCGCDBADEHHEHACDABGECFEFEEABEBBHBBABCAGCFGEFABHAH,False +372,3.0,3.0,3.0,4.0,0.0,2.0,1.0,2.0,DDFDDBCABHABACFGCH,True +373,11.0,27.0,14.0,16.0,27.0,12.0,14.0,25.0,BGEGGBDBADECHGHHEHADHDGAEAHEFHBFHEEDGEDECBHFEHEBHDDCEABEAHEAHEBEEBEGAHCHHCBBBBBBBCCGDFGEBBEFHFDHFDHFDEFDEDEHGEAEEFBBHBBADBCBCCBGFDGHEFABBGHCCCGCHH,False +374,3.0,9.0,10.0,10.0,8.0,7.0,11.0,11.0,GCGGBBHHCCGFDGFDHDDHFDBFEGEEBECDDAECCBBCHGCHGFHADHACBEFHEBHDBHDGGFGEC,False +375,23.0,33.0,18.0,22.0,30.0,18.0,26.0,23.0,EBDEBDHHGCCGCFGADGBCGHCEHFEHDEHBEGDDGBHGAHDAHDBCBAABCFBCHEFDADCAEBBBBHBAFBAEBAHBHFBCAGCFHDADEAFECEECEFBBGGCCGEHHBBHEDCAFAHEEFFEAGABGCDGBBGBDFBDFGDBEDBHFBGDDGAEBAGAFGEEBEECEABEHGGADGDGFHGFEAEHHE,False +376,26.0,12.0,16.0,23.0,9.0,18.0,21.0,30.0,ADDFFDFFDFFHCFCBFAGFBGHEDHEAHECHCABFAEAAGAAGDDDDCFGCAHABDEGFHBCBCADGHDGADGHEGHDGHFBHGDHCDEABHGEHBDADAACHHHHFHAGHEGHDGHDHHCCCAHDHHGGFAAAAFABFHCFGBHGAACBGCDD,False +377,14.0,10.0,11.0,6.0,8.0,8.0,6.0,11.0,FCEFBBABDCHECFBCGBHGFHECGCFAFAEFDBACADCABCHHEAHGAEBAHAAHAAGFDCBDCBDGAEHHEH,False +378,10.0,13.0,11.0,8.0,10.0,9.0,5.0,12.0,ADCHBEECEEADBACBGBBAHBGHCCHGBHCCACCFHCDBDDFFDFFBFEAEHABHDBDAFHECBAHEGHEGHEFBAF,False +379,26.0,14.0,13.0,28.0,14.0,24.0,18.0,23.0,ACEAFGAGABGAGGEHAFHDCDDFFCGHCDHAAAEFFEGABGAHHADFGDFBCAGCAGBACDDDBDDEADCCHGEAGEABHHFHCCBDABHFEEDGHBGBBHFDFCDFBDADDEDDEDHFDHFDHEDHAAFAHDGDBGEFFABAECAHHFFHFFHDFHFG,False +380,21.0,15.0,24.0,10.0,21.0,16.0,24.0,20.0,GBFFDHFBFGEFHHHHHECHEDEEBCAFAABGACGBCAECBCCBEDFCDGCEEEAEGAGGACDAFDCGBBGBBCAFFDFHBAGGDGGCCHEAFEAFCAFCAHCGGAHCACCAEGHEHEEGEEGDCHDHHGCEGAFHHEHACBCFGHBGBAG,False +381,15.0,21.0,27.0,23.0,28.0,27.0,27.0,20.0,BCBHCAFBBGEBDEDHCDGCGGCGDCFECDECEBCEBFEBFGCGGBGABFAEHCFDCHEGEFFFBGFECCEHCGFFGFHGBECCFCFAEDAGAHDAGEFFFAFDACCHCHBBHFCDAGDHGDEGDBDEHDHHFHFBHDBFDEAGCADBDDBDDEEFEEAGEGGBCGEFEEFDGHHCHFEHCAGGABCE,False +382,0.0,4.0,3.0,2.0,1.0,1.0,2.0,3.0,BCDBHDBHFEHGGCBC,True +383,1.0,2.0,2.0,6.0,6.0,2.0,4.0,2.0,CHDAEDGEDCEGEBGEFDEDGHDFB,True +384,12.0,14.0,12.0,10.0,21.0,16.0,19.0,20.0,GDHEBFGHDHCEABECBDCAHGAEGCEBCEHDEAEBHEBHFHHBBFFAFDCGHAGDCBFHGHCADBAHBGHBGADHFCHFDHCHECEECEGFEGEAGEGGEBFEGAEBAFFFEGFGGDGHFEHF,False +385,9.0,9.0,5.0,9.0,10.0,4.0,7.0,7.0,BCCBABGHBGDEGDACDBEFBHDGADGAEHHCFCEFDEBDBBDAAEEAEHADAGEHGFHE,False +386,15.0,9.0,11.0,11.0,15.0,15.0,12.0,13.0,EGCFFCFGCFHFDHCHCCHACHECAGHFFABEAHEFHEDDEBDHBDHBECDEADGFGFBGFAGFAFAHEEEBDCDGEHGAGGABAAGDFDBEABEHECFAA,False +387,17.0,16.0,9.0,11.0,9.0,4.0,15.0,11.0,DADCFEBAEAGCBBHBEGBDABFBDFDHCAFEGGEAGEACHABHAGHDGHBHHBGDEGHCAAGDAHACEGBBGABAACGACGBDGBDHBDCE,False +388,10.0,3.0,8.0,5.0,5.0,8.0,6.0,3.0,BDDGGCAECAFGAFCACADCEGCAHCADCBFFAFFHHFADEGFEGBEA,False +389,17.0,13.0,28.0,32.0,15.0,31.0,24.0,29.0,HGHCCHGBFDBGAAAAEDAFHHDEGFECFHGFCFFEHFDHGDCCFCHFCFDCFDGEHBEHGHHAACAEDAHDACGEGFEBHDHCFHEFHGFAGFACDACBHCDHCDCCDEFDEFDHFECDHDDCGDGBBCCFDHBDFBDFCGBBHAEHCDGGFHGHAGFBDBDCGFCGFDGDDFDHGHAFFAGDCEDCF,False +390,23.0,24.0,19.0,26.0,25.0,15.0,25.0,27.0,FADECFEGAEGHCFDCBGCBDDHDDHDDAGAHHAEBAGDAHBHGBFGBGGFGDCADCBHBEHDEAEHGEHDBHGBHEBDGBHECAEDADDAEHFFHFHGGCCHHEFECCGDEACEHHAHGAFAADBBDCBGABDACCADABFABEHFEBEEBDDACDEEDGGGGBHGBHCFGCFHFBHCBEGEE,False +391,4.0,5.0,5.0,5.0,10.0,9.0,7.0,10.0,FGGFGCEGEEHHDHGDCEDAHBFHFGDFEBHBHHAHFCCFACFGBFEEHEEDEAB,False +392,2.0,1.0,3.0,2.0,5.0,3.0,4.0,3.0,FBGCCGDCAHEFHFDHAGEEGEE,False +393,32.0,34.0,23.0,23.0,23.0,22.0,17.0,26.0,AABCCBCADCAHAAEFAFBABBHCCFBFGDHDHCAHFGBBCCBHCBHBFCDFBHBEABEAGEDGECBEBHEBAEFHEBEBDHAHHBGCCFDDFDFBDHBGAAACEACDACHADFAGFAGFHGFDFADFAHEAEEBEAGDDHCDEFDBHCGGDGDAHABHEBHEBEEBEHFABAHBGEBHCFDGFGFEDADCACHACBGBB,False +394,10.0,5.0,5.0,10.0,12.0,9.0,5.0,11.0,DCDEADHACFADFADABDHGHHDAHGAGEEBEFFCFAEDAGBAEBCEHDBHFFCEFHEHHEGEEDHF,False +395,9.0,8.0,7.0,6.0,6.0,3.0,2.0,9.0,BAGBECDECDCHEAHAFGBFHBAHDHHAACAACHHFHBDDBEEAEDBCCB,False +396,28.0,25.0,16.0,17.0,19.0,17.0,23.0,14.0,FBGFAAAHBHHGFCGDGGBGGEGGEFCEHCDGBBHEACEGBEADCADGEGHDGAAAAABFABFADFCCBHCADEFGEDDBDACAABAAHHHFACFBDAADBAGBGEHDEDBBFBBFBBCEAGEBHEBHEBEFBCFECFEGDGBAGDACDHCFCFGAGAE,False +397,11.0,7.0,11.0,10.0,5.0,9.0,10.0,7.0,BCHBAHFDBFCHFCDDBHGAGCHGCGGCGGFGEAEECDDFADEBFCHDCHBGABGEFDCFDFAAADAACA,False +398,21.0,30.0,21.0,28.0,27.0,13.0,18.0,24.0,CBDCAGAAEHGBHBHHFHHAHHCGHDBDABFBEHDEBCEDFDCFDCFBCEDCBAEBEDBEBBABEDGFBGFEEAEBGHBGCBACBDCEECBDCDDCAAGDGEAGEAFEGEEBEHFDHDGCEBFEBDGDFHAFHFDHECHGCDGHEGDBDBHEBHGBDAAAAEADDDCABHDCHCEHCHGBBA,False +399,8.0,12.0,5.0,5.0,7.0,5.0,5.0,13.0,HHGHBAEGABBCBBCBBCFBCBHADAAFBAEBEBFHDECEEFHGAHGHHDFHDGHAHHED,False +400,7.0,6.0,11.0,5.0,6.0,14.0,10.0,3.0,AEFAEBCFDCFCFAEFCGGCGECHFGADCBDFGCHCCABCAGGEFHEFGAFBFBGFDGFDBF,True +401,5.0,2.0,3.0,1.0,8.0,3.0,7.0,1.0,BAGCFGEEAEBHEGFAGFDGEEGECAEGAC,True +402,7.0,14.0,22.0,10.0,18.0,10.0,12.0,15.0,GHECCAABBCBBEEBEGBDCEECFGGHCHACHAHFBGGCCCCHCEFCFDCHDCHDFHECHACDBCBAEBDEBDGGEGHDCEGHECEECEEHBEHDFBFBAFHDFGFCG,False +403,14.0,14.0,19.0,22.0,20.0,22.0,14.0,19.0,ECCEDFDGEDEEBCBHDAFBAFAAECCFDCEBBEBDAHCADCFDHEBFEDFEFEGFEAFHAFHGCHEEHDDFEDFDCFDCFCBAHFAHFHHFBDFDDEHCGGBGHBAHCAGCEGAHBHCGCEDEFDFGDHGFCGBBGCHGHDDA,False +404,9.0,11.0,17.0,12.0,11.0,7.0,12.0,10.0,BCBDCEGCECEGCDCCDGGAHGEBGBHCFCAFHAFHADEAHFDHEBCCDCCDCBDHEDHADBAHCHDDGBEGFGGBECFEFEGBAGCAB,False +405,5.0,5.0,3.0,4.0,12.0,4.0,3.0,6.0,DBGAEGEEDAEHAEBBEBEEHFDCBEFGEFCAFCEHHAHEDH,False +406,15.0,17.0,23.0,27.0,15.0,22.0,16.0,20.0,EFCEGEFDBFHCCACBDDHDCFBHFHGFCECAEABGBGDHCDBCABGADFDDFECCACFAEFHDGHDBHDAHDHHDHBFEFDEADFADBDCHDEHFCHFGGFHGHHEAACAFCFBDDCEBCGBDGDEGDBGDHFCCFDEHCBBCBGDFGAFEAGC,False +407,11.0,16.0,12.0,20.0,16.0,15.0,13.0,15.0,HBGBDGBDGFGEFCCHCDHCDHFFCDBCFBEEECEFCEABEHDEDBEFHFDAFDBHBBHDACAHFAFBAEBDDDADDAFDGGGEEGHEGDFHBFHGDBGCBGBACDAHHCEAEEDHGF,False +408,16.0,12.0,20.0,13.0,15.0,13.0,22.0,14.0,HACHAGEAGFHHDDCEDCBFEDFEACBBFHBFHBCGBCACCBDDGDDBEFEGGHDBDDGGFHGAHFEGAEACDACGABAAHEABECECCECGGCAHFAHFGGFEECEHAFDGGGGCFHCGGCGBC,False +409,4.0,7.0,9.0,5.0,9.0,7.0,4.0,6.0,EFCBHCFAFFACFDHHBHCBGBBGBCEHGECBAGDCEFCDFCDEEHEEAED,False +410,12.0,11.0,9.0,6.0,6.0,6.0,2.0,5.0,DDCDHBBABBACFACEBDEHDHBFBAFBAGCAEAEEFHCBCCFHCAAEAABDABGFC,False +411,10.0,13.0,4.0,12.0,8.0,3.0,7.0,11.0,BBHBBDDDDDEEAAHAAHBAHGEHGHHAEDEEDACDBBDGCDBBABHHCGCFGFEGBAGBFDDAEHBH,True +412,2.0,7.0,4.0,0.0,2.0,6.0,5.0,2.0,BGBFGBFGBCGCEACFBHFEABHCBGFF,True +413,28.0,23.0,16.0,19.0,25.0,12.0,17.0,19.0,BHADEAEEHEEAGEFBBCDDAGHHGHAEBDFBAFBAHAEHBECBDCGDGBFGEEAEEDBDDBHDEHGECAACGACABCABFABCADEAHEDBCGFEBFEADEBEGADAAFAFHADBACHABHCCDCDBFABGAEGCGFHACDEGHHGHGDHFBHEBEGC,False +414,4.0,13.0,10.0,10.0,10.0,2.0,11.0,8.0,EEGCECCGBBGBCGDEEAGEDBHCHHADHDBHEHCFBDBGDBDDBDEADEHBCAGCBGEGCBGCBGFH,False +415,13.0,21.0,20.0,13.0,22.0,19.0,15.0,24.0,HFDBGDBHHBCCFHHFBHFBHFBHACEFEHFCBGBBFBHFDGECGFCAABGCFGCHHBHHEGFEABCBECEECGDCHHFEDAHBAEEDECDHDGHFGHFAECAFBAGBDECDCHBHHDCEFCAFEHEEGEAGEAFEDEBACBDCBGG,False +416,21.0,17.0,11.0,9.0,12.0,14.0,19.0,7.0,CGHHGBDBAGBAGBDGACGAHFFBFAGCACDAGAAEAEFCCAEFBCFGCAACGEFFBDAEDABDCEGEFCEBBHFBHEBHEAGGBGFAHFEBFBBDABFAGGAGGDGADE,False +417,6.0,8.0,8.0,1.0,1.0,6.0,7.0,5.0,BADAECHCCHCCHAAFCGFBGBBHBBGFCFHCGGBGGBFFAA,True +418,11.0,22.0,19.0,15.0,20.0,16.0,14.0,28.0,CCEHHDBHECHCGAGDCCABHFHHEHDEGBEGBDDBDEBHBBGFFCFFHBDHBCHBEHBAHFFGFCDHHDCHBEABHDBHCBAAEFDCBCCDFHEFGBDABGFBCADEFDGFAGEHGBHCBCGFAAHEEHEFHEGEEHEEHCGHC,False +419,25.0,19.0,13.0,15.0,18.0,30.0,15.0,15.0,FHCDCFBEHCABEAFAFHEFDGFDCDEHAFGAFBDBBFBBGBAHFAGFBFFBDBDDEGFBDEBHCBFCEFCEFAECAEFECGADBABAEHFDGFGGBGFBGDAAAHAAHDFHGCHFCAFEAEEDECDHBFAGHAGFEEFAFFAFAHCAHG,False +420,5.0,4.0,3.0,9.0,10.0,5.0,4.0,4.0,DEBDADFEFCEHEABEAEEFEDHGDHEDCFGCFDDGBDGBEAAH,False +421,21.0,22.0,19.0,21.0,16.0,23.0,24.0,24.0,BGGDDGBHHHHGHHDAGFAGFBBFGGFGEHBAHECFACAGHEFCEADEAEBAHBGBBACDACDHCDHCHBCDBDDGCFHHFHHAHEEHCGCBGAADFBGEGFCCFCGFDHHDHCBFDAADABBCBFCFGDECBEFDEGDEDFABFADFGBFGFAGFADHHEGABCFBGEE,False +422,5.0,3.0,3.0,1.0,0.0,2.0,1.0,4.0,ABCABCBGAHHHFHAFCAD,True +423,8.0,5.0,10.0,3.0,2.0,6.0,4.0,7.0,CAHCAGAAEDGFCGDCFHCAHCAHBBDFAFFGBFBBCCCHCEHAH,True +424,4.0,2.0,3.0,3.0,3.0,5.0,4.0,1.0,GDFGCGACDACDEBFEGHEFFAAFB,False +425,20.0,29.0,28.0,22.0,37.0,21.0,18.0,23.0,DCDEFDAGCHCHFDAFEFFEHDEDBEABEHBEBFCBEDBCDCCEGCEBCEAHDHHDAHGAHBBBFABFABACBADHEEHEEAEAAEACDCHBCEDEEBEGGEBEFDGCBBBAFDAFCAFCHEDBEDGECHBHGFGECEDGDFECFDCFGHECEEHFEBCABCADEAFEGBBHBFGBEHCCHBCGBEFCHHCHGGGGDF,False +426,3.0,6.0,6.0,5.0,11.0,8.0,8.0,8.0,ECEBAECEDDEBDGBGHDGEBGECGFHGFHACHFGHFCFBEFHHBHEADEFGCFE,False +427,9.0,21.0,17.0,17.0,18.0,17.0,9.0,12.0,BHBBHBBAFBCCHEBDECFECDEFFGHCEFCAFAEHDGHDBHABEEBEEDAECBDCECABDAFDHDGEDBBDBFAFFCCBHCDHDBFDGFGBFCHACDBCGGDGGCBFFBFEEFHECEED,False +428,13.0,9.0,6.0,7.0,7.0,9.0,7.0,6.0,HDAAECHEGFFGFGCFHCBGAADAADAAFABFBEEAFFBBCBBEABECGHDGEDGDABDAFHCH,False +429,8.0,15.0,19.0,18.0,20.0,20.0,16.0,22.0,FGDFDDFHDGAFGFHEBABCDBHFGHFCHACACCECEACEBCFGDBHFEHFBHGHHEHEBGEAFFHCFDEFDADDBDGHFBDFBCFBGAHFBECHECBECHECECCEDCHGEEGEGFDFEDBEHBHCDGDHCHHGGDG,False +430,13.0,25.0,20.0,21.0,26.0,17.0,24.0,16.0,EFFGFCDFCEHCGHDGEECAEBBEGBECFEGHAADDAFCAFCBCEECFFCFCAGDACHBHHBGDCGDGGDEEDBHHGCHEDBEGEECEEBEBBDBAEEFDGBGGBDAEDHEFCGBCGFCGAHGFHDBGGBFBFFHEHBCDBADCEDEBBGAAGHBGHBDBDD,False +431,13.0,21.0,18.0,12.0,10.0,10.0,17.0,15.0,GAFBBBBFHGFAFBGCGGBBCABCAGDHGDHBCHBHBAHGGHEGHDCDBCFBCGECAEDDHBAEBDHBDHBDACECGEGGDHADBEFCDBGACEAHBCFBEHAEHAFGCCGCCFFC,False +432,14.0,11.0,9.0,15.0,14.0,12.0,12.0,18.0,DFAFFAHDHEDFEHHEDHCFHCECBABBDGEFGEDCDCGDHHFCHFCGGCEGABGDBEABAAHAEBDEBHEGHFGHDHEBADGADBAEHCEHDDHBFAGAAFFGH,False +433,16.0,16.0,12.0,20.0,13.0,18.0,9.0,14.0,FDCFDADDBDDAHDCBDCDDCDAEHAFAABADBECFAFBCFADAGCAGCDBAFCFFEHFHBFBEHGCGGDFGDABDEECGGDFEFBHCBHBEHBEABEHBAHGAEFBEHHHFEHFDFD,False +434,15.0,21.0,15.0,6.0,12.0,5.0,12.0,17.0,CBBDBGABGCDGCEADBCCADEFCCAHCHCDHCAHCHHABHBBHABEFCGCBGAFAAHEAFGAEGAHGEEGHEGBFBEECHEBBAHHCHDBHBBHBBABBGEG,False +435,0.0,0.0,3.0,2.0,2.0,2.0,2.0,3.0,CHDCEDEHCGHFGF,True +436,22.0,21.0,21.0,13.0,7.0,14.0,20.0,13.0,BHBGDAADEDFGCFGDHGAGGAFDCCACCHEADBCFBCGBFABEHDCHCEGBGDAGAADCAHGHHGHFFDEHAGAGGABCAFAFFACHACGBDGBDCBDHAGCFEBFACHBCABCGFCAFGBEBBCBBCBB,False +437,18.0,12.0,15.0,15.0,9.0,15.0,19.0,9.0,BEAEFBCFAADCBFGDGGHFCADAADGADHCBHDGDBGDBGDCGAHEFHGFAEBAHBADGCDGCGFCHFDEFEHFCAAAFBAHAEGDEGFEDCCBCGBFGBFGACGCCADFG,False +438,9.0,15.0,11.0,10.0,6.0,5.0,12.0,8.0,CBBCECABBAHBHBCHGGEGGDAEBEDCDFADBGDBGDBGBBCDGABHCFGBFGHFGHFEAAEAABHDDCGCCDCH,False +439,21.0,34.0,13.0,20.0,9.0,14.0,18.0,22.0,DBGDFCCFEAGHBHHCHHCBHBGHBDABCCBAFBAGBDCBDBBGBAFFDHEHGCBACBAEFGHBGAFGCFBAGHAHHAGHGCDEAHABHBDFEDBDDADDHFBHFBEABEABADBHFHDBABBHBAEBGCDCFHGGGBBGFDGDABDABDE,False +440,5.0,7.0,4.0,9.0,2.0,7.0,1.0,7.0,DEBHHHHHHDFAAFGADHABBFFDFFDBEDCCCCFBDDBDAB,True +441,9.0,3.0,11.0,9.0,5.0,3.0,13.0,6.0,GCHGCHBCDDAEAHEAGAGGCGEAEHACDFBDBDGCDGDGGHGCFGCAHCACDGCAEFD,True +442,26.0,15.0,9.0,16.0,20.0,21.0,20.0,20.0,EEHEFAFDDHDDBDEEFFEDFCHFAAGHAEHADBAGHAGBADAAEABCGBCBBFGCFGEFGEFGHDEAEEAFHFGHDGFAGACGCHBCHEAHGABGBGADGFFGEEBCFDHAEBAGBADAABBHFHHCEEFFEDFHAHHAHADDGFG,False +443,5.0,11.0,13.0,10.0,14.0,14.0,10.0,14.0,FCEHCEHCEDGDBBDGEDHEABEFGAFGAFCCFHFFHFBAEEGDFFAHECHGCHDCHBGFEHFHFFBBCBBEHCHHBECDEDBEDCGGGDC,False +444,9.0,3.0,12.0,6.0,9.0,11.0,10.0,6.0,GACGCGACGBHABFCEFCEFCAFGFEGDCFBCHHHHGAAAEADCDGAGEEEEECFFCDFGDFCDFH,False +445,9.0,10.0,13.0,13.0,17.0,11.0,15.0,15.0,DGCDBCDFEFHEHHEDDEGCCFCFFCGDEECEFHHFAHFAEDGGBBGHHGCHGBACAAHEEHEEDGGDGGDGEEFEBGHBCDCAACAHDHBFEFCEDBHBBAG,False +446,4.0,1.0,6.0,9.0,11.0,4.0,5.0,7.0,GACEFGGACGDFDECDEHDEHDEHEEDAHDCDFCDBEHAGFCHEEHE,True +447,26.0,19.0,18.0,11.0,16.0,16.0,12.0,21.0,EEHFFHCBABHABHAEHAEHEFFGFAGHBHAEEAEEAGAAGCCGABDACECFHGHHEDHCBHCBHCBAGDABDCHAHEFHFHHDDFBFFAFCACABEDFEDAGDBFCBDAGFACEACAGHABBFBBEBACCCGHCDBAG,False +448,6.0,5.0,7.0,6.0,1.0,1.0,3.0,5.0,HADHAHCACGDGBDGBAECACBABDCHDBHDCCF,True +449,11.0,2.0,6.0,6.0,9.0,16.0,8.0,5.0,AGAAHAAGFDFEEFBEDGEGEEFEAFCCDEDFFGFFGFFCFAEFAFHDFCBHADHFGHACCAG,True +450,11.0,4.0,8.0,12.0,7.0,9.0,7.0,8.0,FDEFCADCGCEBAHBGECHEFHCDACDABHGBFFDFAEFAEADGADFEDHCAHGDHDFCDAGDAGH,False +451,31.0,20.0,20.0,33.0,22.0,23.0,32.0,17.0,BCCAGAAGFAGCEGDBGDACDHDHGFBGBBDBFGBHBAHECEECDEDHHDFADFEDCEGHAFBCCBFADGCBADDFEFGEHGEFGDHECAEAGEDDEBDEADAADBCBGEDHDDFCEAAHBGBGFAGFDGFDEFEGHBAHFAGFDGDDFDFABCABCAFCAFCAGCAHEGHGDAADAGEFGHDGCDGBGHCFAGDEGA,False +452,6.0,6.0,6.0,10.0,8.0,9.0,9.0,6.0,AFEABEBDGBAFEDHGFHGEDGEHCHAGHECHCCFDADDFEDFEBAGCFGFFGCBGDBDD,False +453,13.0,18.0,14.0,23.0,17.0,19.0,19.0,12.0,DCGDCDDCADEBFFBFFCAACDACDCCABCDDFDFAAEGFHFADCBGCDGEDAFGGEHHEFBFFBFFBGFCDFCGAGDDHDDHFEHGEBGHDGHAEHBGBDEFCBDDEABHAGEBEEBHEDEGBHGBFGBGEEGB,False +454,18.0,22.0,18.0,14.0,25.0,31.0,12.0,21.0,FHADBACFDHAHHDGHBFFFCFGCBGDHFFFGFFGFGGFAHCHEEHFHDFHFFHFAHAHEACEGEEBDEDFAFFBFFBFBEFDCBBEAEHDFDEEEBBGCBFCFCBGBBFEHGCDEHDECDECBADEAEEACEACECCABBECBECBFAFAGHEHHABHAB,False +455,8.0,7.0,7.0,9.0,13.0,7.0,12.0,7.0,AGEBFEADAAGFABFHDEAFFCGFDEHGABGCBHCBGBDHBDFDEGCEGCEDCEHEDHGDAGEHEEGCEG,False +456,26.0,25.0,17.0,12.0,23.0,17.0,8.0,10.0,BCAFCEBDBGCAAFAAFGCBEAEDDBADBADCHEFFEADEAEEFEEGAEGEHBEGAFHAFHDFBBAEACCAECBBBBBFABEABDBBDABDCEDFECACHFHAFHGHDCCAGFEEACEABFABFBEFAEBBGHBCHCC,False +457,17.0,13.0,15.0,8.0,13.0,12.0,8.0,11.0,HFCEBGABGABDAECBBCBBEBEEBFEAADACFHFEHFBACAACDAFHHFAHGAHAAEAHGHCGFCDFDAEEBDECCHCCFFGBEGCDFCBCAEDHG,False +458,4.0,0.0,3.0,1.0,6.0,6.0,4.0,0.0,FEEFEFFGCFAEAGCAGEADEFGC,True +459,21.0,25.0,18.0,16.0,17.0,17.0,23.0,17.0,HDAGCGGBBGBCEDCBBBEGFEGFEGFAFFCGFCBECBFFBEBBGBFABCAFAHEHEDHGDCCEAAGAAGBCGHCBHCAEDHHDFFDABEFECCABHABEDBEGBEGDGDFGAFEAGCDGCBHHDHCAHGABFDEADBADBHGAGAHFHGCHDB,False +460,10.0,14.0,5.0,9.0,15.0,9.0,9.0,8.0,EDEEGEAGEGBEDBDFGDEABFAFDAGEBBABDAGDBGFFHAEHDEABGBHABEACEFBDFBCHGCEBCEBEHHHFHCF,False +461,5.0,3.0,5.0,6.0,2.0,12.0,7.0,4.0,CEAFFGFFGFFDFHDFBDADACCGGCABAHGFBFFDGHDGHEFC,True +462,6.0,6.0,14.0,9.0,5.0,9.0,18.0,19.0,FGCDHCHHGHDGADGECGHCGCGHCEDGEFFHHFHFGBAHEFGBCGHFDHFHHCGHCGHEGBCCBDAHDHGBHACGCGFCDABDAG,True +463,3.0,5.0,4.0,8.0,5.0,3.0,5.0,5.0,DGAFBBFAHGEGGEGBECECCAHHDDDEDDHFDHBDCB,False +464,8.0,5.0,4.0,6.0,7.0,4.0,8.0,3.0,DACBACHAGHBEHDEFEADGGCFEDGEBGEAGBAGFDGFDAAEBC,False +465,13.0,13.0,10.0,12.0,11.0,18.0,10.0,10.0,DFBGFDFFDGBBBEDGEDBECEEDFHAAACAAHHHHHBGGAAAFHACDACEFFHFFHAGCBEFBEBAFGAHGDEGFFBFDBFDECCECCGBCDBFDF,False +466,1.0,7.0,5.0,6.0,4.0,4.0,5.0,8.0,DHBECBCDBGDBHDBHFHECAECFFGHDGBBGHCGHDHFE,False +467,8.0,10.0,7.0,7.0,13.0,10.0,14.0,7.0,GGBEGHAGEGBEDBCAFFBHEEAEFBEGCFGCFHBFEGFEBFHFCHFDGDDGHDGDCHAEGCEGAEDCEBAABABG,False +468,7.0,9.0,14.0,4.0,4.0,10.0,8.0,4.0,FECAECBDFBGFCCFECFDCBGCBGBFDAHGAFGBBEBCHBCAAHGAGCCCFHCFGCDAF,True +469,11.0,8.0,10.0,17.0,9.0,15.0,9.0,16.0,FHDFDDEACFHCFCAHDEHAGHACHDGBAGBEGBAGEHHDGHFEHADHAEFAGGCFECFBCDGDHHDADBCDBEDFFDFFCCBEDHFHAFHDFDB,False +470,1.0,3.0,1.0,1.0,2.0,1.0,2.0,3.0,CHADBEEBGHBGHF,True +471,17.0,15.0,26.0,18.0,19.0,21.0,23.0,27.0,GFFCCCHCDHAGAEGFGCBGCBFCFFHDFBDCHDGHFEAFEAEEAEGDHGHCGABGDCGDGGFFFACHBEAEEDEAHFAHDHHGCHFHHGGHBBECGECEEDAHCACCBBCFBCHGCHACFDCEDAHCAHFFFDABEEBCBAHFCHBHBGDGECGEHDHGDHGDFD,False +472,2.0,5.0,3.0,5.0,4.0,6.0,6.0,2.0,EGHFGBFEBFEDFHGCCFEABDADDBDGBGCFG,False +473,20.0,30.0,26.0,33.0,27.0,26.0,18.0,15.0,CGAHFAGFAFDBCDEGDEHBEGBEBFDGFECFHBFHBEEFEECCEFEFFHCDGAHABDFBAGBADBADBDGFGCDCABGAEGDDDDACFACEAFEBEGDCGCEFDEBEEDFEFFDABDHBDEBCHBHHFDDBCDFGDAGHBDABFBDDDFFBBACBCCBCABCACCHGCBFBDDEEBCGDCGDCEDCHFEHEAHE,False +474,19.0,17.0,14.0,18.0,11.0,17.0,20.0,12.0,GAGCCFFCGFEDEBFFAFCGDHGEHGEHGHGFDFAAFDADDADCACCBFBDGBGGBFEBCABDAGHGBDBBHFGEAGCDGFDCFCHFAGCBBABBABAEBCFCDEDHGHAEHAEDAEDGFDGDAHHAB,False +475,29.0,21.0,29.0,16.0,8.0,11.0,32.0,19.0,GGHBGAGFAHFBGAHFBHGBHGCEACHGBAAAFHHFHHCBGCGAHBDCCDGAAGHHDBDCBDFBDBEACAFCEDCBGABGAFEACGACGCCGBCGHAGADEAHGDCGCBBAFBADCGBEGBEGBAGCGGAGABCCHCDACGHDGEAHAADFCCHACDGCDGCDFC,True +476,1.0,0.0,5.0,0.0,0.0,3.0,1.0,0.0,CCCGCCFFAF,True +477,12.0,12.0,12.0,10.0,3.0,21.0,15.0,7.0,FDFAGACBDCBGCEFEFDGAGGBBDBBAFCADCADCFCGFCFFHFFHBFCCDAGAAGBFDCFCAFHDBBGHDGHFGBFBEFGFFAHGAGGFH,False +478,17.0,16.0,18.0,22.0,16.0,25.0,17.0,21.0,ACEFGEHAECACCHBGAFFBCFECADCEFAEDEFAECBCGBCHFGHGEBAEAADHGDGAFGDDCEHCHAEHDEFGHHHBHABFABFHCFHCFHCFBDFBHBEFFEDFCDBGDAFDGBHFBHAEDCFHBDDGADGDFCDFGDGBDGDFHDFHG,False +479,10.0,7.0,13.0,9.0,7.0,6.0,9.0,3.0,HGCDGCAGAEGAGCCBCCFCEFEAFEACGGCHDABDECHFABFEBEBADBDDBAACGCFDCDDG,False +480,1.0,0.0,4.0,0.0,2.0,0.0,5.0,0.0,GCEGEGGCCGCA,True +481,21.0,16.0,14.0,17.0,11.0,10.0,25.0,16.0,FDGEEGBBDHAHGDHBHGBGCBCCFACEAEGAHHDHBGFDGADAAEAAFHCFHDFABGCBGAGGADCHDCECEDBDACDAHDAGDBHHBAGFAEFGBFGBGHAGAAEDCBCEBHEGHDDBGGGGCAGCFG,False +482,12.0,17.0,21.0,17.0,21.0,22.0,20.0,24.0,HCBHEEHCEHCBHADGBCGBEEHHFGHFDHFCHCGHGGHBGCBCHGDDACDFFFFFGBACFECGCFHFAEDHDDBDDHDEGDECAGCAGHAEHAHFEFDEACCDGGGFGCEBCEDHFCHBHBEHDDABHFFFAFFBFEBEBBGAEGCEGCEBFE,False +483,19.0,21.0,17.0,13.0,22.0,21.0,20.0,24.0,GDGGEGFHAHAEHADHCEHDAACCBEFBEAAFFAFGHHBHDBFDFFACBGDDGDHHBACBFDHFDBFEFFGABDACDFFHGFCCAEBBHGBHBBEBGCDGCHGCHEFHEAHEHHGACCACGAHHEBGECGACFEEEBEFBCFEEGEHGEAGBFHBEB,False +484,14.0,17.0,19.0,19.0,23.0,9.0,30.0,14.0,DBADEECEEGGGCGGCHGAEDCGDCDDHDGGDEBHBBCAHHADGGGEGCECCACHAGHAEDABCHGGHAGDADBEFHHFBCEAGAGGDGGHGGACFFBFGCFGBBDBECBEDBGFEHDEBDEFHEBCEBAEGEECEGBGFCDECD,False +485,23.0,20.0,17.0,18.0,15.0,7.0,16.0,20.0,ADAADBBFAFFAFAAGCDHCHABGABCAGHBGHCAHEECBECGDHHAHDEFBGDGDBGDBAAEABGHBDCECCBGGHCEHBFABFABCACAECBCDDCBEEADEADHHDHDDGEHGEHGEDCBDCHAAGGBHHBHE,False +486,19.0,15.0,16.0,14.0,11.0,13.0,25.0,19.0,GDCGHFGHCBDBAAAAAACAGHBGADDCCHEGBCBDAFDBGDBDEAAGAHBAHADCDDEHHFHEAGCGGCGGBGHCGCBGCBDCGGGFEGBEDFHCFEBFEAFGAEGCFGCFGDEGAHFEHABFFBHHHHHH,False +487,17.0,28.0,19.0,19.0,12.0,13.0,19.0,22.0,DBDEFAHAGFBGHEGHDDBBEBHEBHDCHFEHGEHGBBACBAGAAGEBBHBDFBDFBDCCHCCAEBGDGDCEBCACFAEGAHDFCCBHCEHDEGCBGABGBDFHCFDDFDBFGAGGFHBCHCABDABHAHCAGCHGBBBCBHFDHADHG,False +488,11.0,5.0,10.0,9.0,17.0,10.0,8.0,12.0,HFEBAGAEFADDEHDEHAEHDEHAEDEEDGBCHCFECFBCHGCHGEDBEABGAHFAHFHEEGFHACECCADEDCEFCAFGFG,False +489,15.0,27.0,19.0,19.0,24.0,16.0,18.0,23.0,GDHCDCEEBEBBHABHFBGFEGDDHDFACCAGGADEBDEHABHAFHGBHAFCAFCBFCFHCHDEHDBBFABDEGCECHDDDDGEAGHAFHFEBBEAHCAHFGHABEFEHDHHDCGBEHBEBCCBGDGEBGEBEECEGBECBEBDEBFGHABHFFDGCCGBC,False +490,3.0,2.0,6.0,3.0,7.0,0.0,1.0,4.0,CBCEHEADEACEADEDBCGHHECHEC,True +491,14.0,16.0,16.0,14.0,17.0,13.0,22.0,10.0,FADFCGFCEFCEBCGBCBBCBBAFBGGBGBEEEFDBBDHEEHGHAGHAGDDGBEAAGDFCHADHGDHGHFBDEDDEFECCEGGGGGADGCBEEHDCGCCGABHDBFAFEEECCAGAFGAFCA,False +492,26.0,18.0,20.0,24.0,26.0,19.0,29.0,28.0,DCADFADCEHGDGGFGEAHEHHAHFCCCGHBAHEAECBBGGBHGBHDBAAFECHEBHGFHCAHDAHDAHACHCGHCAAEGGGDBGDGGDEGHHDCGEEGEDAEDCGFCDFEFFADHGBCABHDBEGBGBHCHFGDFEFFEBBEDBEAAEFEBFGBAHAAHECDGDDFDACCAFAEHGEDGEDCEHFGHFA,False +493,1.0,0.0,2.0,1.0,4.0,2.0,0.0,0.0,ECEECEAFFD,True +494,11.0,16.0,14.0,24.0,25.0,15.0,20.0,16.0,HFCEDHDDCEGCFADBEDCEDAFBACGFFGHDDDGBDFEAFCAFHDFHEFBAFBDEBEHCEDBHDGHDFAEFCECCBGGBFDBCDHAHBGEBEEHGGHABDGDGGDHADGAEEBFECEECGEGGEBEEBHGCHGDHGDEDE,False +495,15.0,21.0,13.0,15.0,18.0,25.0,20.0,12.0,GFGGDGBFFFDCCDGCDECAEFFFHCECCEDEEAEEBEFHDHBGGBGGEGHAGEAGBGEAFAHFACFCHGBBGBBCCDEGDFFFFABBBEBDAGDAHFACFAFDABDBBEFDEFAFBBFBBFEHHGHDDHBFGAFHEGC,False +496,14.0,17.0,8.0,12.0,24.0,10.0,23.0,11.0,GBFGBDGAFGBGEBFEHDGAFEBCGGGBABDAEDGEFBAFHEFHBFHEEBGEBAEGGEFGEABAHBGHBCFGEGCAGCEHEGHDDEBAGCAGBECDECDEGDEGDBDHEEHAEHDCAAE,False +497,8.0,11.0,13.0,8.0,7.0,15.0,9.0,16.0,EHBHFAFCAGEGGCCGCAGBAGHDFFCFHBHHDDHFCAECHDBHCBHAFFDFEHCGDFGAFCAFCGFEBBCBBCFHDHEDHFBHEBH,False +498,3.0,6.0,8.0,3.0,3.0,7.0,4.0,5.0,CHECBEABACCGCBGFHFFBGDBFDAFDEFCGBCHFHHC,False +499,7.0,4.0,9.0,5.0,5.0,8.0,3.0,3.0,ECEEFHFFACFAHAABEABDCCGFDGFCCFCCFGDABDCDEBAH,False +500,7.0,8.0,5.0,8.0,4.0,3.0,2.0,4.0,CAEFHGBDDBDDBDDBCGBCFDFDHCAEAEHBEABAAHACB,True +501,22.0,26.0,22.0,26.0,16.0,25.0,21.0,27.0,EBHCGHBFHBFBAEEAHFAHEADFGDFBFHCHCCHGAAAAAHAGBBBDBCHCEHBHHGDDFBEFDECDBFFHFFDDDDDFDAACHBDABDHGCEGCGHFGAFDCFGCFGBBGFACDAGHFGHEEAEEAHHBDDAABBCBCDDCDCGHFGHEBHABGFCGCEGCBCHBCHDGFFBFGEFDEHDBAD,False +502,10.0,11.0,12.0,13.0,8.0,15.0,13.0,13.0,GFHHEHDCHDEFDADGCDGBDFADFHFACFACACBFCGFCAFEECBECBACAFDEHBGGAAFDGHCBDCBHGBHDFHDHGEFGFHGFHDBEBGGB,False +503,5.0,6.0,10.0,4.0,4.0,8.0,9.0,0.0,FEDCEDCGBGGBCFCFEDBEGAACABCGCCGFFGFFDAGGBCABCF,True +504,7.0,14.0,10.0,11.0,12.0,9.0,6.0,15.0,BDBBGBFCEDCHDCHEFFECHGDEEHEDHDBCDHGABFABFBBDBBCEECHEGFAHCGFBHFAHFAHDCEAHBDCBDHGEHAEH,False +505,21.0,9.0,16.0,11.0,15.0,16.0,15.0,15.0,DFAGEAGEAFCCECCECFEGFHGDHAFBCHEDHEHBEAGFCHDHGAHFFCAAGAAGAAGAFEDGCDFHGEHFEDFBDCAHGAHBABEABGABEDFFHGFCEACHADEBCCBGFDCCHA,False +506,17.0,15.0,12.0,11.0,15.0,5.0,18.0,14.0,BHGDHFBGBBABHAEGAEDAEAEDBEDGCGHADCFEHAGHAHHAFADCBBGEGGBDBBDEHHHGGBGADGACHCEGCEHAABFAEHAECAECEECFBCGDCGBCGDG,False +507,23.0,16.0,18.0,17.0,15.0,30.0,19.0,16.0,CAHCHFAHFDGFDGEHAABDAFCAFBAGBHGHCDBAAFGFFGADAHDGDGGFEDFEDCCCCDHGFFGFFCHFAFEAFEFHGBEFEEFEECDBGGHHGHCEHEGCADCEBAFBFDBGBCHBFFBFFBCDBDGAGFABEAEAAFFCBFCADCADHA,False +508,2.0,2.0,6.0,5.0,8.0,2.0,3.0,4.0,AECAHCEDEEGEDCFFCBECDDGGDHECHEBH,True +509,10.0,15.0,13.0,10.0,20.0,25.0,8.0,14.0,BFFFFGHDGHBEECGECGEHFEFAGBHGBEDEGAEAHHFFHCFCFFHEFADFBCEHCEGFAHFHEFECBDCBDABDCBFCBDHBEFCEFCHFEBEBFEAFACFHFBAFEADDDBE,False +510,9.0,6.0,15.0,8.0,8.0,15.0,8.0,4.0,CGFCHFDFCDFADGADECCCFCAFBFFCCFEGFDGFCGCCEBBEAEEAEFGHDGDFCHFEFAGDABBCBCAHA,False +511,1.0,1.0,2.0,5.0,3.0,1.0,4.0,3.0,GDDGCBGCHDEEDHEDFAGH,True +512,16.0,13.0,8.0,20.0,20.0,20.0,19.0,18.0,GEEGAEDHBDFBGBGGHGEEDHEHEGFEGBEGFHGEDBBAHGFDAFDAEDGFFHFFHEEHDEHDGDGADCADFADABFHDFCEFCHFDGAGABHAFHGHCBFCHEHBEAAEAAEBCEDFGABDCHFCBFDFDDG,False +513,2.0,0.0,0.0,0.0,3.0,1.0,1.0,4.0,HHEHHEAGAFE,True +514,16.0,32.0,27.0,32.0,20.0,18.0,31.0,18.0,FFCEHGEAGHCGDDGHDFEDFDDBDCHDAABHAGDEGDEGEFCBDAEABBAGBCGHEEDCCBCCAECAGBDFBCHGHHDHADGGGCCFFAGBGFDGACBHCBDAEDBEDAGDHCDGCEGFGCEGDADDCHBGHBAHBEGBEFBFGBHDHGEBBDBBFCCCDEBDFBDBBGFBGFBGFBGFHDBCCCEBCGDCED,False +515,26.0,15.0,26.0,29.0,17.0,18.0,23.0,22.0,GFHDAEAAEGAEGCEDCDDCAHCABBAEBECGEBHHGAADFECFBCFECEDGDDCDCGDBDFGCGHDAHFADDAHCADDGDFGDEAAGAFDHGCHDCBDCGCBGCBFABGAHHBHDFHDFDDGDCFFAHBEHECCFCBACHACEGCEHHBHFGHCGDAGDAGECBFHAAGFFDEAH,False +516,12.0,12.0,20.0,17.0,22.0,17.0,13.0,11.0,EEBEADDAFDADAHHEEBGEBFFBEBCCDFCEFCEFCEFCABEFHEFCEFGFCGCGHCHDCGFBECACAGDAHDGGDHFDHADEADBFHBFABDHECFDCHCEGGDCDDCGBEAFEBECGECGE,False +517,17.0,18.0,11.0,13.0,13.0,9.0,14.0,20.0,BEFHACHEDBAAHAHHAGBAGCGGHAADEHDEHBBHGEHAEHGEDGEBCEBCHAAHBCHADHCDBGFBGHAABBFFFCCFACBGDBGDBFDCFDCBEHFHHEGBADEDHEGGABD,False +518,20.0,13.0,17.0,15.0,17.0,19.0,27.0,13.0,CFECBCGACDECDHCHAGGAGGAGGAGEAGHBGFFGHHDEHDHDDGAAGDDGDHBEFDAGBABEECEAABAAFAGFGDFCDCEFGECBCGGEGHEGHBGEFHFFDCCAFGAFEAEEFCFACFGBDCBCAHGBEGFDFHBFB,False +519,4.0,10.0,8.0,8.0,7.0,6.0,3.0,5.0,EABADFAHCBFGDFCDCCBACBEFDGBHGBHFEHFECEDHBCCBEDBEDBD,False +520,21.0,21.0,12.0,9.0,4.0,4.0,12.0,8.0,FAACBBBAABGAFADBABBDBBABHACGACBABBHHCECAACAHGDHGABCBDABAGBDGDAEDGCDGCABFEHEAHFBHGADGCCGBCGB,True +521,7.0,6.0,5.0,6.0,9.0,6.0,4.0,9.0,HDFFDAFDAFBFEAGABCHCHHBFHBGEBHEHHEHEDAECEEGACDECDBGA,False +522,7.0,13.0,6.0,12.0,9.0,15.0,17.0,9.0,FEHCDBCDGGDGGDHFBHAEFDEFDFGEAABAFBHCBEFBACDGBDGHHBFGDFEDEEGGBGGBHGFGFEGHCFBFFBGFGHBADCAD,False +523,13.0,18.0,26.0,23.0,24.0,18.0,20.0,22.0,HDCHAFHBBHAEFFCCGDFGAFCFDBHGFGEFBEGCEHDHHEGCEGEDBDDBGAFHCFHCAECHBFHADHFDHECFBCBBEEDGBCGEEEDGHFGECCECDACDGFBCACCDDGDDEBDGBDGAACABCABCFBEFEDHEDHDGHEFHECDECGAHGEHGCCBH,False +524,23.0,26.0,27.0,25.0,18.0,14.0,25.0,20.0,AHEABADDECBHGBEGDCHHCEDCECAFCACEFEEGGDGGDGEDGCFBAEAHFGDFCACHEBDDBADBADBDDACFAFAGCBBHBGGFDBFDGAAGAHGDHFBEEDCCDCBACHHCHECFDDHABAACAAGHHGBGGBGFBGFHDCBDCBHBHHCDFCDEBGHBGACGCCGECBBBEE,False +525,9.0,5.0,7.0,9.0,10.0,14.0,16.0,12.0,GDEGFEHFGFFECEBCBHHAHAGHAGDFCDHBDAFFFGFGGHBDHFDCFDCDGFEGEGCEGAGAAHAGEGHEHFEHFGCDBA,False +526,21.0,20.0,28.0,24.0,24.0,22.0,22.0,28.0,FBFFHFFDFEBCDDDFBEABCGECGECFHFFCFDAACAAHAHCDHGHHFHCBHBDHGDGDHAHCDHGABAABGCGAAFBGFCDFCDFCABEHDEAGHABHEBAEFHCAEABHGHHACFEGEEFEEGDFGDCCDCEDHHGBHGEHGECGDHDDAFCEBDHBGGECBDCBGCAGCEBCECEBCEHCDHEDF,False +527,20.0,11.0,8.0,13.0,17.0,8.0,13.0,14.0,DDHGDHCDHDDHEGFEDECAEHFFHAABEGBEHBCAGADGACFACECDEAHGABBCEAAEAGFABAABAHGFHEEGGDCEBAFGFHGAEDHEDHEABEABDHBG,False +528,9.0,13.0,8.0,10.0,8.0,6.0,9.0,7.0,ECDBCHEGHFFBEDBGDBHDBHDFHFEBBCDFDACACCBEHBAGBAGFDGADGACHABDAEABGGEGCEB,False +529,2.0,5.0,6.0,3.0,4.0,6.0,5.0,4.0,FCBFCBFCDCHDEHBFGFFGAEAHEGBCGCHDEBG,False +530,5.0,3.0,3.0,2.0,4.0,2.0,5.0,5.0,AFBAEGACGFGHCEHEBGEHGHDAHDACB,False +531,14.0,18.0,15.0,23.0,16.0,17.0,15.0,32.0,HBAHEDHGDHCDHDEHDEHDEHDHFAGADFEEHBBDFHDAEDEEHHHBHDFHDFHCFCFECABGGBEGCEBFBBDBDCCHCAACFACFHEEHCHHDHGFHGFHDCDDBEBGHAFFCGBAEBAHBGHAGFBGAHCFFBDGDCBDHGHGDHA,False +532,8.0,6.0,17.0,12.0,9.0,14.0,14.0,11.0,DEGAFHFDCCDGCHHBHCFDCFDCEGGFHHCAGEGBFGBDGDAGHCGCCGDCHDGEDBEFFCFDCGHCEHEGHACCAFAFFDFFAEBAEBC,False +533,15.0,11.0,12.0,12.0,16.0,22.0,21.0,18.0,GAAFFACGGFHDCBDFBAFBAGEAFEBFGGFDDEGFEACHFFBDFGEGDFFAHFHHAHHEHHFHFABECBDHHDCHDGGDGGEFGEHACGACGECEECEEBDBHDHHFHEFGGCABCAFEFCGGGBA,False +534,6.0,6.0,12.0,13.0,5.0,12.0,12.0,8.0,HDGAGHFGHFCHABHFEHFACCCBCEGCGDCDEADCFDHGDGFDGFBGCDCHFFEGFAFDDFDDGADCBECBGB,False +535,22.0,16.0,25.0,15.0,17.0,33.0,16.0,16.0,FBFFEECEEDFEFEEBGGDGFEAAEFCGFDGHDGDEGAAAHACFECDACDCHFCHFAFFAFEGFBDFECHHBACBCCACDAGFGDFEDFCCFHCBCCFACAAGADGHEFFCBFHDFCDHBHGECAFFGBGBFGAAAFBHFHHFEBFCDFCBACBHCBHAB,False +536,20.0,17.0,26.0,15.0,22.0,17.0,17.0,16.0,BHHBAFEEFAEFAEDBBDFEEBCEHHAAHAGBDGBHBECECCBFFAFEACEGCEFEECDDDGBDABEEBEHAAHCFCCEACDAHAGHBGFACFHCGHCFCCBCFGHDHCDHCDGCEAHGAFBADGGFCBFCGDCGCCFADECDGGEGAEB,False +537,13.0,10.0,5.0,5.0,10.0,8.0,9.0,7.0,EADEDEAAGAEEBGGHHBFFBFEBFBBDEAHEABCAHCAEFAGDAEDBFFGFAGAHGCHGHABCGBC,False +538,10.0,10.0,16.0,12.0,12.0,14.0,12.0,13.0,DFCGBCDFCDGBDCFCFFCFDAHDCBECEEBEDBEHECFECGAHGDHEAHAHHGFHGDHFFCGGCEGFGGCGCAAHHAEHCBDFBDEBAFADFAEBCBH,False +539,2.0,2.0,4.0,2.0,0.0,2.0,1.0,0.0,ACCFCAFCBDDBG,True +540,3.0,8.0,6.0,4.0,2.0,10.0,5.0,6.0,FGBFBFDBFDBFHFFGCEAFHCCBFCBECFABGDGHDGHBHHAC,True +541,4.0,4.0,3.0,5.0,9.0,9.0,6.0,7.0,HHFDFBDFAFFAEFEHGEHGEBGEAHFDEBCGHGGFEAFDDHCEBCE,False +542,1.0,6.0,4.0,1.0,3.0,1.0,2.0,0.0,EGEEDACCFCCBBBBBGB,True +543,11.0,8.0,11.0,8.0,8.0,12.0,13.0,10.0,CGFCHFHAFHGCGCCHCGHGACBDDBCDFADFADFBBEDAEGACFAHHGBHGDAEFGEAGEABHBGFBAEEGEHDFCGFCF,False +544,1.0,2.0,1.0,1.0,0.0,0.0,2.0,3.0,GDAHBCHBGH,True +545,20.0,18.0,24.0,26.0,24.0,22.0,18.0,33.0,CBHDDADAHFAEFCEHCEHEBHCBGCHAAHAFHFFEAFDAFBEEGHAGDDDACDHCEECEGDEGDEGBADBEDBAACEECHFBFCHFHHEEDBHHAEFCCHHFDBFDHCHHAHHAHGCHCCGFCGBGGFGDFBHFDGGDCEDADDADCFBCHBCBFHEHBEGAFHCCBEFFHDHGAEGDBGDEHD,False +546,29.0,23.0,21.0,19.0,21.0,27.0,25.0,20.0,BHEADFCDFGBFAFFACEAGFABFACFACFHEBHBFHDFGEGCEHCGDCDFCACAGDEBDEFAEFGEGGHCEHEAFEGECAAGAAEFFFFDFGGGCDGBGEBGHBGEBADFGCAGEADDBDDBACCCBDBBHAAABAHBACGECDDHGHHGBFEACHBFHEDCFDAHEAGCBGBAHFAHFBHFBH,False +547,8.0,14.0,13.0,15.0,21.0,12.0,10.0,20.0,CHCHGGHDDADDEGDBGFHCBECDEFBGHEECEGCFAEHHEHHCHHCHFFAAEDAHDEGBEHAAGBEHDEDBCFFEFCEFCHHEHBEHBEHEDDEGDGABCEBDBBCBFFBDF,False +548,5.0,4.0,1.0,2.0,4.0,2.0,2.0,2.0,ACBADGEEGEEBAFBFHDAHBA,True +549,14.0,13.0,9.0,11.0,17.0,24.0,19.0,14.0,EHAEHGEDBEDCEGGEHFBFBBGBGGFHAFHBFEACBACEADGFEACGFEGFADHGDAGCBGHGCFEBAHBGHAHADDAFDHGGHGFFGFFCFFEAFEGEEFFHFDBBDCBEHFFDFAEFC,False +550,8.0,20.0,16.0,21.0,30.0,20.0,19.0,15.0,FHEAEECEEGBBBBBHBBDDCDDCDBCBFFEGFBCEHEEHEEBEEHFDCEECGBBGAGAHCAFCAFGDEGCEFEHCDBEDHGCGFFGEEGEECBEFEHFHCDHBDFDDGGDHEFHGDECDEHEGACFAFFGFBGBGAFGDDDDDBEFBH,False +551,8.0,3.0,13.0,5.0,6.0,13.0,5.0,7.0,BDFEDFGCFCHFCGCAFFAFFHFGCAGHAEHCBCCEHCHDCADCFFAEFCCDHGEFAEBA,True +552,10.0,10.0,17.0,16.0,16.0,11.0,4.0,13.0,CABEDBDDCCDFHBACBAEEDFGACHECHECEDHDDBDDHAHCBHEFHEFHEDDGACAECHEFBEFDEDDHCBHCHFGBFEBDCFACEGCAACFCEF,False +553,29.0,25.0,19.0,15.0,29.0,33.0,22.0,26.0,EABECBEDDEFBHACGBHHEHFFAFFEDBAGFCHDGEDEHDGDDCADHAFFABHCFEEBAECAECHHHACCAEABEABCCECFECEGCHGCFFBFFBEFDGGAGAECHEHHDHHABDEHAEFFEAFAFFAGFHGEAGFFGFAACAEFFEGBAABFGBEGDFHDFHEFBBHDHHGHBCABABBFBBGBGGEAGBFGCFH,False +554,19.0,13.0,14.0,11.0,11.0,13.0,12.0,8.0,ABGABGBBFEBEDGCDFCEAGEAGHAGFAGHACHCDHADCADFGDCDDAFEGFEDHHAGCGCFDEHBEFCFFCFEABGABFCHEBABBACADEAFBABACC,False +555,4.0,7.0,2.0,2.0,5.0,4.0,2.0,1.0,ABBABDFBHFBEFEGBAGEAEEFDCCB,True +556,33.0,24.0,13.0,22.0,28.0,22.0,18.0,30.0,EEFABBCDBADEGEHHHCAHGEHABDDBDAGAABDGBABBAGBEBHEFDEDCHDAEDBFHEAHFAHFABFCBEHBEHAEHCHHFEHBEHFEFFHAFHAGHEGDDHBCEDGAFGECHHDHFAEFAECAGAGCEGADDAEBABAAHHAHGAHFEEECAACGFCDFDDFAFEBBGHBGBAFBEHDFGDCGDFA,False +557,21.0,20.0,17.0,15.0,9.0,13.0,11.0,17.0,FFFCCBHDBHDBDDBDDHDCGFBAHBHCCDAADHAHHADGADCCHBCFECEACECCFDABDCEHEHHEBHDFFABAABAGBEGAHGACGCGGFBBHBAFBABAGHAFHFGCGDEFBBCABAAE,False +558,17.0,17.0,12.0,11.0,13.0,15.0,10.0,21.0,AACABFAEFAEGCEBAFBFHBDHEAHEBEEHDHHBHCBFGAFGFCACBFBDFADFCDBHHBHDACECHHDABGBBGFGHDACEBCEBCAFHDEBDCAAHHFHHFGHEGAEGHFGHD,False +559,14.0,31.0,29.0,20.0,24.0,28.0,19.0,25.0,CBHCBFCBGABHAFHAGDBEEHABFAEDGEDECFFCBFDFFDEAEHDDCECEHCBACBDFBCEECGGCGFCFHEABDABDGBDAHFHHGADGEFHDGHEFHEBBEBGCBFBBDCEGFFAHGBHAFFGFFHEFHCCHBBHFEHGBDDHCBCFBCFBCADCDBCGCCBBCBECGDCHDFHBGHFGFCEEHEE,False +560,11.0,11.0,9.0,9.0,7.0,8.0,12.0,11.0,FDCFDGECEACDHCFAFGAFAFECFCHECHABHGBHBBHBGEGGAGGAFDBHDCHDBEDGABEAGACHBHDBDABGHG,False +561,17.0,20.0,22.0,24.0,12.0,25.0,33.0,19.0,GFGGFCGFGDHGBCGHGHHGHCGHDGCGCDDCHGCFGFAHCHFDFCDEBDEBGFCEFCFFGAFCCGCHACBFDFGEEBBDDBECAFGAFGADGADGDDGADGFDEBDBBDBGCAGHGGDGGBBDFHCCDCEFABHHBHEEHBDHAFAGEAGDABFAHHAFBFGDCEBCBFFA,False +562,11.0,10.0,11.0,8.0,5.0,15.0,7.0,5.0,GBAGDDBFDHFDGFAACAACBBGFGEBGFFCFFCEFBEFBCBACFFCAHCAHEEDBAHFCFFCDDAGCAHDB,False +563,20.0,11.0,17.0,13.0,14.0,9.0,14.0,23.0,BAGDHGEHCAGCGEFAEFBCCHCCBDADHBDHADHCGHAGAFEAHHAHHACGCEACAHCDHBDGGDFEBFHHDHHCAHGAHFEEDGFDECDHHEHACFGHFECEGBBCAACAABDABEGBE,False +564,25.0,13.0,20.0,11.0,13.0,16.0,8.0,5.0,AAAAFFCFFBBFABDAGEAGAHGACCFEFGEGAEAACACEFCFFCDCHFBBCBCCADFBHFDCCBGABGCBABBDFACAAFGACACDEEDECDBDAEDAHDAECAECEEHF,False +565,28.0,15.0,20.0,25.0,16.0,15.0,18.0,16.0,AADAACACCACGGBEGAEGBEGFHCHCCEBCEBDBBDBCDAEDEBDABDFFHHEAADAHHGHGBDGCAGFADAADADFHEFHFGDEBDFCAFEHFBBFDHCDADDACDHFHAGCGDAGCABADCADEAGEGCHDDBDCAGFHGHCGAEFFECE,False +566,7.0,8.0,2.0,9.0,6.0,8.0,0.0,5.0,HEFHDFDDHDBEDBEFBDBBECBAFBFDAFHAFEDDBCEAAAFHA,True +567,12.0,8.0,8.0,9.0,5.0,12.0,6.0,5.0,DADDAGBGGBCHFGFDAFCACAEFADFGBFABCDDFEDFECHECDBAEAHCAHBACBFFAFFBGH,False +568,27.0,25.0,25.0,24.0,19.0,25.0,34.0,18.0,GGBDADGGGAGEFFECFEBGEADDADDAFHBBHBCFBCGGEGEDHDHBDFBACBGCFACBCGBEGHHGCAGHGBAFAHHBFHAFECHCABFGHCDHEFEFCEDCEGBGGDAGFFGFFGAFBEFEAFEGFDBFCAGCAGCABAHHHCEACBGEBDEAACCFGGFGDBGDCCDBEGBCDFADBAGBADDADHCDHCDGA,False +569,17.0,19.0,19.0,27.0,20.0,24.0,19.0,16.0,DCECCEHDBFDEDGEAGFGFBCHBCAGAHGFDAFDBHAGEADCHDCDGCBHCEFCHFCGFAADABFABFEECGFHHDHBDEBDBCFEEFEEAECGDBFCBDHBDEBDAFDAHCGDEBDEHDFADFDDFGAFEFCAFHDBEBBDGGACDBCHGFFGFGGEGH,False +570,14.0,23.0,26.0,22.0,21.0,32.0,13.0,35.0,DEACHFHFDHEHFCHFCEFBFHBECFECHDGEDFFDEFHFBCCACCHGDFCHFEHCAHCHHCEHEEHCHHCAHDDGFBHCBEAGGDBGFBEHBHFBADBFDAFGGGABHAGHABDFBFHCFDCFDHEHCEAAEGCBGDFCFFEFDBFBBFBCHBHDBEDHDDBAFFCFHAEHCEHCBHDBCDEGFH,False +571,12.0,18.0,32.0,29.0,10.0,22.0,15.0,20.0,DAHAAEGCCHHEBCEBHDDGDDFFCCCCCHCFHDDHDHADBEFBECBCDBCDFEDGHDHCECGACDAEGGDGDBFHCFDGDDGAEFDCFDAADAADHBCBBCGEDBBHCFHCABFDHFBFCBCCBCCHCFFDGCGGCHCBFDFFDFFCFHHBHGFCGD,False +572,19.0,12.0,16.0,19.0,24.0,11.0,17.0,21.0,AEAGEAEEBDEGDECBBDAHDAFECHEFHGFGGDEHDECGGCAEHEHHCBHDDHDEGCEGAHGFEGEEGEECFADFEDEGCCABAGBAHAHHAEHACACHAFHBCBBAEAFBHDDADDGDBFHGCHFCHCCGFDHDDBE,False +573,5.0,2.0,3.0,2.0,1.0,4.0,3.0,2.0,ACEFDDFABGAGGACFAHFCHB,True +574,17.0,18.0,22.0,17.0,4.0,9.0,12.0,14.0,CCBCGGAHDAEDBCFCCHCFACFAEDAHDAHGBGDFDDCACAAFBBDDBDBBFCBECADDACBFCBHCHHABCAHGBBGBADDACHAGHDGHDHBEHBGBGGCFDAGCCCFHC,False +575,13.0,19.0,23.0,32.0,16.0,20.0,25.0,19.0,GGDDGDDCHDBGDFDDHBBHGBHBFHCEAFEHFGFEGEGGDGDFCHFAEFBCFGHDGDEGDBHDAAGHDDADEBCEGCEFCEFEDBACHAHFDEFCGFGHBBBABDCBFCHDCFFCHDDGDDGECGEDAAHAADDAFDCGCHBCGBCEHDEGFFHBDCBDBGCCGCC,False +576,9.0,9.0,12.0,4.0,5.0,6.0,12.0,11.0,BHFCHFGHEGHBGEFHADCDCGGCFGCBDABAEBACGHEGFBGBAHCDHCGHAGEAHHCCFCBGABCA,False +577,6.0,7.0,11.0,9.0,9.0,12.0,13.0,8.0,EDDGBABEGCGACGECECCBCCHGEFDEFGGFGBCGDAGHGCHBFGBFDEFCFFAGFDHBDADFADFHHFHEEHC,False +578,0.0,1.0,2.0,1.0,0.0,2.0,4.0,0.0,GCGDCGFFGB,True +579,5.0,1.0,1.0,3.0,1.0,1.0,1.0,4.0,HGAHAACAAEHDFDDHB,True +580,23.0,6.0,7.0,14.0,17.0,10.0,20.0,6.0,EEAEEHDHGCBEABGFBGEACAADADGADHCGFGGEHGAGGDEAFEAGEDEAAAAAAEGCFGDFGDEGAEAFBAHBAGDFGDFECCECGDBAAGDEGHAFDDF,True +581,26.0,18.0,18.0,18.0,15.0,22.0,19.0,23.0,FFFAFECGECGHCGACGACAFFGHGEHADHFDHBDHCACGABGAFHHGAFGABDABAFBHEBAEAHFAGCAGCGFAEDGHFGAEBAEHDDHBDFAFBHDBFCHEHHGFDDBAEHAECAHGHECDFDDHHBFHBFCBADFFDCCDBCABGEBCEBDEGAC,False +582,21.0,17.0,16.0,25.0,18.0,9.0,13.0,8.0,GAHDCGBCBACDDBDGADCEDBFDAFDADEAEEBEHADFAHEGDBGFHGHCBAAHDEHEEACDACDECFEAHAGGAEGAEFADBGEBGCDDCFDABDCCAGBADBDFFDGDECDBCDCCEEBBEBBA,False +583,3.0,13.0,7.0,7.0,6.0,7.0,7.0,14.0,CGGBGGBGFBHBBHCAEBHEBHFFFDFADCDBFEBGCBCHHHDHHDBHEGDECBAHFDHBEHCH,False +584,19.0,16.0,23.0,16.0,22.0,21.0,12.0,29.0,CGHFFHFFHCFGDFDEECFDCDDABFAEAADFBEAECAEGAECHHCHAEHFECCHGCHGEGGEDHBABFAHEEBGEHHHBHHCDBCDBADCACABCBCCBHBGHDFHBFHCABGDCFCCADHAHHEHHEHFEABEGGAFDFEEFEAFCDDEHFBHCHF,False +585,5.0,14.0,11.0,11.0,4.0,5.0,12.0,10.0,DGDBCBFGBDAEHACCEHCDCCBHFBHFBHCAHGGGCGGBGCBEDBGBAGHFCHDCGDBHABEFBDDBDDHG,False +586,11.0,24.0,18.0,11.0,8.0,6.0,17.0,13.0,GBBGABCCDDEGDFGAHEAHCAEGBEGAEABEAHHCHBBHCBHCBGGGGGGBHCBCCBDDDCGGBEFFADFGBCABGBBDCBDBHABHBBHFBDFCHCBGDHACCCEC,False +587,14.0,18.0,17.0,13.0,15.0,17.0,25.0,21.0,ECCAFEAGBAGCGFCGHADHEBGCGGCBDCGABDHBEGBCGHHGFHGHHGHDGCACAEHBBBABGFHGFDGFDBDGBAHHGGBCEFCFHHFEHFEFFAFFAGFCHCHGABCHEFHCFEBDEBDACGAEGEEHBBDEDDGD,False +588,13.0,15.0,14.0,18.0,15.0,14.0,13.0,9.0,EFAHGBHGDHGDCADGDDEEEECFACDGDGHCCFCEDCBHFBGDBCDBCGFCGBCEDDEAFEAECAFCDFDDBHABHFEEBBHBACBADBGDEABFGFFADGAGFAEFEBH,False +589,12.0,8.0,10.0,3.0,6.0,15.0,8.0,10.0,FDAFCFFHFGHFGBFHAHAADACFCCBBCBBHADHACFAHBBCGGEBECHGAHEAEEAFFFCFFHGFCGAEG,False +590,17.0,15.0,7.0,14.0,11.0,14.0,9.0,6.0,HEAFCADCHBHAFEFFEDAAFBABCGDDFAAGDGDCBEBFEBDEBAEAEBAEBAFBGFBHFCGCHGHDGFAAFCADBDDBDDGFAGFABEDBE,False +591,10.0,3.0,10.0,5.0,10.0,14.0,7.0,11.0,CFGCFEAFHGFCGAHACGFEADCAECAEBEDGFDHFEHFEHBEHFECFAAFHAECDHGDBFHHFAHCCFG,False +592,19.0,16.0,12.0,22.0,13.0,29.0,15.0,13.0,GHBEBBFBGFCCFDDECDGGDFGAFABCHFAFFABBCHBAFGHFBEFDEFGEFGDDGDDACDBCEAFEACEDDFFAHEAEDDHHFFDFBGFHGDBFHECCCFBDEBAHFAEFAGFBGDHADAFDAFDAFHAFGAGCHDB,False +593,7.0,6.0,8.0,6.0,8.0,9.0,6.0,6.0,DCHBFDCFDGACEACBBCBGHAGHFEHFEHDEGAEAACGFBFCHFCAEDFEBEDGF,False +594,30.0,31.0,17.0,16.0,20.0,23.0,18.0,23.0,ECHGCHGBBGFBGABGCDGHFFBFABDADAFEAFEHGBAABEABHABHACFACBEFADDADFBCGHHABFEBEGBCGEHFEFEBGEHGDAFBHDAFBAHBAHFAFACGDCHDCHDGBEBHEFEAFEDHACEBCFBCHBFHBAACFCBAHGHDDEADHAECACGBBABAFBFEBGEHGD,False +595,9.0,14.0,16.0,12.0,7.0,14.0,15.0,6.0,FEGFGGFDBAGEFGEFCCHCBEFBCGACBACFCCBCAFCAGGFFCBHGBHDBADADHADGBDGBDEBCHFCFCCGBDGDHEDADDFEBGGCFB,False +596,26.0,34.0,20.0,24.0,21.0,26.0,22.0,25.0,FEEBEHGEHEFHEFEEACGABBDHDDHGCGFDACBGBHGFHDADCFGCGBDAHHCFHGFEEFEAHEBHGBAABDABFAHFHDDADDFDBGGBFHBAEBAEBAHBAFACFADADDAGGBBGBBCCACFFBDFHDFHDBCBCABAECDFGDGHHEECCAFDBDEFCEFGDBBHBBHGGHFBHEGGEBCABCFBCFCAHBA,False +597,16.0,18.0,17.0,23.0,22.0,17.0,16.0,28.0,EECBEAGEDFCFADAHFCHFCHECDBGDBHDCHAAHDDBDDCDHHFHBAHBEHDEHAFHAHHEEGEEGDEBDEDDHBEBGEHGEHCACFHBDBACHECEBCACCGCGGEHHDHBFGEABFDFFDGFAHCGHCFHBGHGDABDAFGBEGFDFBDEHFA,False +598,14.0,9.0,12.0,11.0,20.0,14.0,7.0,8.0,EEAFAGFHFFBEAGHBCFFFFDFFBAFCEGEEGDCGDCBAADAHFFHAGHACDECBEDBEAACDGCEACHDDADBECBECHEAHFDEEEEEEEBC,False +599,31.0,15.0,28.0,34.0,25.0,28.0,16.0,23.0,EADADBADCDDCGEGGEAFEFGBDDCFACDECFECFBCHAEHABGFCCAECDEDGCDGCDGEAHDBBDBACEAFBFEBEDBEBEEFGAAGADGDFFCEFAFAABDFHDFHDGCDGHDFCDFHEFAEGCFDAFDAFDEFHBCDAFEECHHDDHDCFFAHHHHCHADEADADBADBCGCCHFAFCEHHAFHAHHAEGACCCH,False +600,10.0,11.0,5.0,10.0,8.0,10.0,7.0,10.0,HBFHBHGFGEFGEFAAFAGFGEBBHBDGBHHAHCDHEHBEAFDDBBABDFDCFHEBCECCADGADFADAED,False +601,1.0,4.0,4.0,5.0,1.0,4.0,5.0,0.0,EGCDDCBDCFDFBGBDGCAGFBGF,True +602,4.0,2.0,2.0,6.0,6.0,0.0,2.0,3.0,EDEEBAEDHEAGEABCHDCDDADGH,True +603,22.0,28.0,15.0,26.0,22.0,27.0,16.0,24.0,EADBBCFGEFEAGAFEACAHCDBABGHBHAEDGGDCGFBBFHFCEFCEFEDAEGEHGABFHBFDBGDBABGGCGBCGBABHAFDDFBDFBGFHFCHFCHFHECHDFFDFABFDBHDFDCFDCABHABHEHADCDDCDHFEEDAEDFEBHHAFHGBHBBEEBDHDHEDABDABAEGEEHAF,False +604,21.0,11.0,14.0,19.0,11.0,12.0,18.0,29.0,GHHGHHAHADHAHCGBCGBDGBDHDFAABAEHFCDDAACAFHBHHDEBEGAGGEBGEHDEGFGGCHGDBDHHDAAAACFACFHBHEAAEHADHGCHGHDBCFHEFHEFECDDHFDCGDFGAFHAHHCHBCGDCAD,False +605,9.0,11.0,6.0,10.0,8.0,6.0,9.0,4.0,DCGDAGDABEBBEBGEBGDDGHAHHBCCECAHAFFAEDCEFFEDCBGBBGEGDFGDBAAFDAB,False +606,28.0,22.0,23.0,19.0,24.0,23.0,22.0,23.0,GHDEEDGFDEHCEBCEBAGAAGEGGEGABFHGFAGAHGDCCDHFBADBDDBCDBFHFDGEEGCEHFFHCCHAGHABEACCACDFEEFAFGEFBCGBCBFAFFBFFDGEEGBEHBHHDCACFHCACAABAABAECCDFHHFHBDAEFHEFEECGFBGCDGEHCBGDBAAAHCAHDEHDBHABAAG,False +607,13.0,16.0,14.0,14.0,17.0,12.0,10.0,10.0,BGHBGADGDDGCECBEDBECAECGECGECFACFBEEBEADEDHFAHAAHBFEBHDCFDGDBFFBEGCAFADDHCABDACDABDHGFFGEEBFEBABCEFEHCHHCB,False +608,9.0,17.0,16.0,8.0,12.0,15.0,18.0,16.0,BGGGDCHHBHGBEACEACEGCEHFHCBGBBGFBGFAHCDGCFFCFGCBGBBGBFGBFAHFBGFBABCEGCEADHHEHHCHFEGEDHDDCDABGHECCFCFFGBADEAEHFH,False +609,34.0,28.0,25.0,20.0,27.0,20.0,18.0,15.0,FHGFEGEBBEGBEGHFHDFDAAEAAEDCFDBFEFCDCDDGEAFEADBCCACCDFHHBCHFEDABBABBABHAFGACGEEEACCACDDCBFCDHBFGBAGCGFADEADGABFABAGEEEBHBFDBFEBGEBEBHCCDCAGCAECAECAFCHGEEBFEAGEDECAHHABABBABDFDAHCABCAGHAGA,False +610,27.0,20.0,29.0,19.0,16.0,20.0,23.0,16.0,EDGGDCDCCDCCFAHFACFEEAAGGAHFADGADAEDCEACDAGDAHDCHFAFFHCGHCGDEBAEBAFHADHCBFBBDAECAECACGGGGFFCDGBHGECFBABDABGECGEFBFCBHDBHAHGACBAHEACCACHBHEFCBDCGDBGCBGHGCBFCADEFBFFGABGCEF,False +611,22.0,21.0,24.0,24.0,11.0,17.0,21.0,18.0,CGCHDBGDBABGACGAEAACCDDCDGCDGFDEHBABFCHACHAFGDEBDEBDABHGBCFBCBAHBDFBHFCFECFECGAGEAEBDGCGGCHGDFGDFCFBHFAFGAGHHFBHDAADCAHCAGEABCCBDDEDDHCCAAHFHHDADDBGHCGBFFBEDG,False +612,15.0,15.0,16.0,7.0,8.0,15.0,11.0,10.0,BBGABCABCFCHFCBCAGHHFHFFBFAAFAGBAGDEFFCFECACDACAFCABEEGCEGCAGDBCHBDDFDDFAFHACBGBHGBHCEEEGHCGFBHBA,False +613,1.0,6.0,10.0,13.0,4.0,6.0,8.0,9.0,GCDDCDCAHCHEDFDCCDGGDBHDCHDBHCGGFGCFGHFGFFHHCBBEEBDEDDBDH,True +614,10.0,16.0,11.0,12.0,14.0,10.0,10.0,10.0,DECEGBDAEDAEGGGHGAAEBAEHDGHGEBCHBCHBFEBCBFCBAHEDFEDFGAFDCFBCFBDFBCHCCHDHBDBBABFDGEEEDCEGAHBAF,False +615,1.0,1.0,2.0,4.0,6.0,3.0,0.0,3.0,HDEHFEDCEABEHFEDDECF,True +616,10.0,6.0,9.0,12.0,6.0,14.0,6.0,4.0,DFHDFBBECCFCCFBCDGAFFABDAGEADBDDACECFECGAAGHFHFFHFFDGDAFDEFDEBDAAGC,True +617,6.0,1.0,4.0,3.0,5.0,2.0,0.0,4.0,BDEHDAAFACHECHECDEFHCAAEA,True +618,22.0,16.0,36.0,14.0,21.0,16.0,20.0,16.0,BBGEBEHHHHHACECCGBEDBCDHHAHDCHDCECAFHAFDAFCAECGCCACCGFFDEGACGCCGCEGCGGEGACGACBDGGDEAEBAEGFECAECFBGECAEFFHBCCBCHEFADFDECDBCBFDHDECDGAABHCFGCAGCFGABEABCABCECCFFAHH,False +619,26.0,17.0,24.0,18.0,27.0,15.0,23.0,23.0,ADFABEBGDCGDEAEHBHDBCGECBECEEGAHGCCECGFCAFCHECFACBAHBACBAEBDEHFEDDEHGHHGHHGAHGAHFADAAGEAEDAFAADADHEGHEGHGBHDBCEECGFCHEBHBBFAHDCGAEGEEGECGHCFCFGCDDFDCBCFEAAAFEAHGBGDCDBEFCHAG,False +620,7.0,2.0,1.0,9.0,6.0,2.0,5.0,5.0,GBEGBDDHGCFGDGHEEHDEFAADAAHAAEAHEDDDD,True +621,16.0,26.0,22.0,21.0,29.0,29.0,17.0,19.0,EAFBDDEEGGEGGEGDFBBFADADCGDCBCCHCDDEDFEDFADFEDFGBFHBECAHCDBCGFCFECEEHAFHAFCGFBEHGFHEEHFEBCGBGGHABFGDAGCABFDBFDFFDEFBBBDHBEECFEHEACBFBDFHAHHEHHEHCCHGBAEBDCCEEFBBFAFCBDCBFBAFEACEGHE,False +622,7.0,7.0,8.0,11.0,8.0,4.0,10.0,8.0,DAGDCGDHGDACDBCFHHEGDEDEFHCBHEBHFDHEHBCGGEGBCGDCFDGEDCAABAABEAG,False +623,28.0,16.0,21.0,17.0,19.0,16.0,21.0,15.0,DEHGEHCAACGFGGBEFBEGGGBGFADAEDADDCCHGGACAACEBDGFCBDAAFBCCCCCAEEEECHDCEDAEFAHFABFACFGHHBEGCEFBAHCDHDBCEBCEAHAAHAABEDGECGFAGFABFAHFAHEAHDHBFCBDDAFDAGBGGDGG,False +624,3.0,1.0,2.0,2.0,0.0,4.0,3.0,0.0,GAAFDAFGGFCDFCB,True +625,2.0,3.0,2.0,8.0,3.0,1.0,2.0,1.0,DHDDBDABEGDDGBFAEDCEDC,True +626,25.0,22.0,16.0,18.0,24.0,24.0,24.0,13.0,EBGFHAFDBGEBGEFGEDHADHADAAFCAFCHGEAGACBDGBFBDFEDGEHGEHGDHGCFCEFBEACEBHGFHEBHEGFEBAECFBABCACCABAEDEDGEGCABEEDGEAGAAGCFFDBCGHAGCAFFGFDAFHFFGEBBBHBDAGDABDBDGBAFEDFCAFCEF,False +627,29.0,21.0,28.0,24.0,31.0,21.0,20.0,20.0,FAHFBGFACEAEHGHHCFHGAGFFCCDDBDGBDGBDBHEBHECCEHCAFEGEHGEHGEGGBCABADDACDEEBCHCGAAEAFCABCEBDABEABCAECAEAHHFCFGDFHDFHBCECEDCDFCDACEFBEDBFDBEBEHHECCEDAFDGFDHEEHEGHCDDADAAEGAFADCGCGFEGFEABACFAEBACBGDA,False +628,12.0,14.0,20.0,9.0,14.0,5.0,7.0,10.0,BAHEECEFDEACFADDABAECEHFDHCCCACBAEDHEBHEBHFHCFCCGCDACAADGEGCCGCGBCBBCGBCEBEHBEDCADBEGBCABHH,False +629,5.0,5.0,7.0,3.0,4.0,2.0,2.0,2.0,EFAECAECHGHFCDABDBCDBCBCABCGEA,True +630,23.0,22.0,17.0,29.0,22.0,31.0,12.0,12.0,CCDECDBBHBBHBGFACDAEHBFBGFCCEHGEHEECEFDDFDDBEDBAFEHBDHBFFFFFFFAFFAFHDFAEFACFCCGAFAAFGADGADFFEBHEGEAAFBDGBDADDAGEACECCFBBEEGGEBDBBCAADFEDCADFFDFAEFBHDDDDBCCBFGDAEHEHDDAD,False +631,27.0,22.0,17.0,34.0,24.0,29.0,22.0,24.0,FFDCFDCHHBFADFAGECGECGBFBAFBGGACBFCBACHEFEEFBEFEEFCBAEECEHAEGAEFACFADFDBFBHHDHAFHADDGHHEHDDGEBEEGFFDDGEDGADGBDHFDHFBHFHAABAADHAEHBHGDFGEAADDFDCCDCDDFBAGCFDCGDHBDHEAFDGBEGBADEFGCDBADGADHEHGFHBDHADGACB,False +632,14.0,22.0,9.0,14.0,13.0,13.0,20.0,23.0,BCFBCFAHGDHGAHEDGEBBCBHEGHDDDBAGBAGCECBBGBDABAGHDGHEFFBHEEEEHDEBDEFAAFAHGDGCDAFHAHGADGAGCDDHHFHGFHEBHBGHBFBBFGBFHHFAHCHHBECBGBGG,False +633,24.0,22.0,20.0,25.0,23.0,16.0,19.0,23.0,DBBDHHDHHEFEEFGABGFEGADFACHGEHGEHAFFAHECCEACEBBHBEFADDDDGGHGGHAABCFDCFBGFAECDGBDABEAFECFEHBAHFDBFDBDEFCBCCGDEACAAGBBGBDEAEAAGAAHBGHACCAECGCCDCGDEHAHGBDDEDDHDBHDHHFCHDBHEBCE,False +634,17.0,21.0,22.0,24.0,23.0,23.0,16.0,18.0,CBHDBHCEHCHBGDBECHEHFBCFDFBDFCGFCACCACCGDEAFGADEADFCDFBAHAGHGEBDDBDEBDHBGBDAEDBEDCEFCEFHBHCGDAHAAEDEEGGECBEHDGDBGEHFEFGEFBFFAFFCCFECEDHEGCAGBACFDGFDHFBABHADFBEFHADC,False +635,16.0,6.0,8.0,5.0,5.0,8.0,8.0,4.0,FFABFACAAFAAHAFHCEACEABFCDGCFACABGGDGCABAEBGEAGBAGHACHFEDDDG,False +636,0.0,0.0,0.0,2.0,3.0,1.0,3.0,2.0,EHGEHDEDGFG,True +637,9.0,16.0,10.0,10.0,13.0,11.0,8.0,12.0,FEDBEDBEBBEFBEHBFBFCBEGBAGBHGHDBDDEGBECEFHDDHCFHGBHEBCGBEFAACBDEFCGFAAHAHHFFAADAHDCHGCECC,False +638,12.0,9.0,9.0,12.0,9.0,15.0,8.0,15.0,EFGFDCDAGDHFCBFEAFHACHBGADEEHEFGEDHFDGDDGAECCFHBFHBCACHACHACFAFBGDBGDBHBHHBHDEHDAAAEFFFHF,False +639,14.0,20.0,11.0,14.0,9.0,16.0,14.0,14.0,BFBHEBAEDADCGDAGDAFBHCBACBAEAHHCGBCGFCGAABFCBFGADBFFFDFCDFEAGGDHDDEFFHGHHGHHEFEBHBBGDBCHBEHBEFBCABDGGDCGAFHBFABD,False +640,8.0,6.0,17.0,2.0,13.0,12.0,17.0,7.0,HCFFGFCHCCACAADFGBFCFFCGFCABGBEABGCEGCEGCACCFGDGECGHCAEGBEGEEGHBGEAFEHFEHGHGEECCGF,True +641,14.0,17.0,15.0,14.0,30.0,13.0,21.0,15.0,BBGEDAHDBBEHBCBEHAEGAFGECGACGADAFGFFGFEGDBCCBFCHDHABHEBGEDADDHEGHBBHEGCGCHEEHEEHGEHACACCEGCGGEDGFGAFDBFCAFBAFEEEHGEGFEBEEBHEFDECEEDEBGEDCAD,False +642,26.0,25.0,28.0,26.0,13.0,16.0,19.0,13.0,EBDECDGCAACBAHFACDCCBCDDHDFBDBDAHGAHGBHGBCFDEADGADGHFGBAHBCCDHBDFDFHAEEFDCGGCFCAFGACGCCFADBAEBGBGGBFGDFBFCAACAACECBBHBBGABGFCAHCDFGDCCEBCDACHBCAAEDEEDFEHEDABDACDAGDBB,False +643,14.0,19.0,17.0,9.0,14.0,22.0,18.0,8.0,GCCFBFFBEABEHDEBDGBDFAHFBHCBDEBDGBDHHFFGAFGCGHCACFBGGAGGFEGFCAFCADGGCFECECGFAGFAGACHAFHDCBBCBFABFEBCCBGFEAECDBBFFBAEEEEFG,False +644,15.0,27.0,16.0,22.0,21.0,27.0,27.0,18.0,EDFEFFDFBDGBEGBHCFHCFHFAHFGFFEHGEBGEBGABGCGEBGFFHADEDGEBFABGAEFEGFGGAGFDHFBHCBADAEFBCFCCHDFBEADEDBBBGDBDCACCFCEFDDFBHHAGHGGBGBEGCFCBFEGDAGDEHCEHEBHEBADHDHHDGCDGBAFBDCGAFGDBB,False +645,14.0,11.0,10.0,13.0,16.0,12.0,10.0,15.0,EEHEEHGEFGEDEDBGCBHHFHBFDBEEBEBAHBDGACGADGHEHHECDFHDFDFAEFACFBEBHEHAGDCHDCDGCFAAFAAGCDGCAAAHHFBCDBAFE,False +646,3.0,5.0,2.0,4.0,7.0,6.0,2.0,5.0,EEDEFDFHDFHGFHCBHFBEEEABHABFDBGCEA,True +647,17.0,19.0,20.0,19.0,12.0,18.0,17.0,19.0,HCFBAFBDFDHBCACEAFHCGGCAHBHHBHFECADGBGCDACAECGDCFDFEHBABGADGACGBEFHGFBDBCCBCFBDFADFGGFEGFHGFEBDDBDDADBFGCFGHECHCHHGGBECECCEBDEDHADHADHAFHAHAB,False +648,10.0,10.0,6.0,7.0,5.0,10.0,7.0,10.0,CHGDHGHAECAEAGBCGCEDFBGFCGBCFBHAEAFHDFBEHBGFAFFDDABDABDFBHFHHABHA,False +649,23.0,19.0,18.0,23.0,11.0,22.0,22.0,16.0,DFGDAGAEGAEDABBFDGADBHHAEGECAFDAEDACGBCGDCGHCGBCHEGACCAFDBFHBGGGDBGBFCBEGFHAHHCEDAEDBBAFAFFAFGAHCHCCDCCGBDEFHFFDBFBCFDCDDAAAGDEBDBBHBFHGFHFFHFAHGDGGDACDAF,False +650,4.0,5.0,4.0,4.0,6.0,3.0,2.0,5.0,DDHGDFGEFAECAFCDBCHEEAEEHHBACBHBB,False +651,29.0,15.0,14.0,25.0,15.0,16.0,23.0,19.0,GAFBABHAGGACGAGGAGHABDGFCGDEGEFDFACFBDAHAAHCGECDHFEHCDDEDDECGFDDFEDADAFDBFDBEGHFBAGBADBCDGAFFCEDEHAAHAACGAGDFDDFDAADCAFHBEHGEHGCGEBBHHBCDBCDHEBAEGGHGHHAAHAA,False +652,17.0,19.0,21.0,19.0,20.0,33.0,24.0,19.0,EBHGBHEFHAFCFFEAFEADEBHCBFCEFDEFHBGHGFDGDAHEGFEABBBBFBBFBBFAFEBDHBCBCGFEHACDCFDBGHGEFGACCFFFFDADGFDCFGEGHHGEHFFHEFHCFAGFBGCCGDCDDCGECGHAHEAGEDBCDEHDGHFGFCCDAAFAAFGAFDCGECGD,False +653,4.0,2.0,1.0,5.0,5.0,3.0,4.0,8.0,GBFEDEDGEDEADHGHHGHHDBHAHEFHCFAA,True +654,20.0,23.0,22.0,29.0,18.0,18.0,13.0,18.0,EDEBAEGHHFAHFBDDBGFBGDDABDABDADCCBBCEHGFCGFCDEHDFDGHDCBDHFDCBHBFHECCADGHGGEGBCBACHAEGEEFDEHDCHBEHFDBFCEACFAEDAFBGDBDDBDDBFDCFDCHDAACAABACGFCACDHHAFBAFBHEDCEBEEAC,False +655,7.0,8.0,11.0,11.0,11.0,5.0,11.0,11.0,CHBCHDCHBAHBCGDEGDACDEBAAAFBEFHFBGFEDEEAEEGDGGDGHDAHDHBEEGDECCBHCGCCGHCFHDG,False +656,23.0,22.0,23.0,10.0,19.0,19.0,24.0,14.0,FCGFCGAAEBHECHECHCGABAAFFEHBAHBCBBDEBEFDFADFGDFACFAFAHFBCEACECCDGBFEBFCCCCEGAAHAGEBGABCFBAAGFDFCEABEABECDGCGAHGHCCHBAFBHEEHCGBFGBAHBGGEGGEDBEDBDFGGGGGGACH,False +657,17.0,18.0,13.0,17.0,9.0,17.0,17.0,24.0,BDHBDGBFEBCHBDFBDHBAHBHHAAGABHACFFHHBBDDHHDHGFCFFCGHHBAHADGFDCFHCHCCBDFFGAFGAEEAGEHHBGFFGFAGHADHDCBDEFDECGAGADCAGCHGEHBEHFDABDGBCGAE,False +658,8.0,8.0,5.0,2.0,2.0,4.0,5.0,8.0,CEGBBGBHCFHBHBBABGEBHHGCFAAHADHAHGACFACFAD,True +659,34.0,21.0,21.0,17.0,21.0,20.0,30.0,25.0,HAFHDCDEGEEGAAGBGCBEAGEBGEAHCAHEAHCAHAAHFBHECECABCAHGGFGHHGEHDADFACFACFCGFCGFBBFAAHAAHBFFDAFDGFCAEAGFAEDBGBCEEFFFDEAGGADGCDFHGGHBCABCABCABHDGDGGEGGEGHEAHBDGBHHBCHDFAECGDBHAGHADABBACEFHBDEGC,False +660,14.0,30.0,12.0,19.0,8.0,11.0,20.0,13.0,DEBHHDCGGHGCHBFBFGBFDDFDDGDGBDBBABHDBHACECCACEABBAEBDBBGGGCGDAHCADCABHEFHBFDCDCGGFBGDBDBBGGBCGBEBBEBBHHBHFFHFAADGBBGBGADDFEAAGA,False +661,11.0,26.0,15.0,26.0,16.0,14.0,18.0,26.0,FEBHBBCBDCEDFABGAGEABBHBGCDGFDEBBEBBDBEGBEDDHHDHFBHEBEEGAHHDHHCBHCAHDHCAACEGBEGBDGBHBHDFHDHDFHECHCHEAHBGCFCFHDDHDDFDDAGEGGCCGDFGFAGFGDBBBHBDHFDACDCHFGDE,False +662,5.0,2.0,4.0,1.0,4.0,3.0,0.0,4.0,HCDFCFHCACAEEAEFBHABHAE,True +663,14.0,22.0,18.0,13.0,14.0,22.0,18.0,29.0,DHBHHBGHGDDFFFCBHCBFCHGCGGHHHHABCCBAFAEGBBDBFCFECFADFHBCHADBADGHDGCDACFHBFGFFBFGCFAAEACHAFHEEEEHGEHAEBGBGGBFCBFBGGBGAHDHHBECEHCHBFECFHAFHDCHDEHDEHGFHB,False +664,22.0,13.0,19.0,20.0,21.0,19.0,24.0,26.0,AACFEGGECAHDGHDGDBEHBGDGGCBEAGEFEAGBGGBFFBGGGGDCEEAAFFAHEBFEFACFECEABEFHGFHDAHCBHCFGDFHDAHGEHEAHEAGCCCHDAHFCEFCDCAFCGCHFCHGCHGCBGFBGHHDAHEAHDHHDHEEADEFDHADADDHDBADB,False +665,19.0,16.0,20.0,18.0,23.0,17.0,22.0,24.0,DAACFCEFCEHBFHAEHDBHBHABHABHAHCCGGCGCEDBDHBACCCCCAEDHEACEHEDGECGEFGCGDEFHCAHADFDEEDBECEACDGEDGFHFAEFAGBHHAHHDHAGBBFCGFEGHBHFDEFDHFHHABGABGEDGEDGEGGBCEBGDFGFFGA,False +666,21.0,15.0,10.0,14.0,9.0,13.0,18.0,9.0,ACFGBACCACCADCDGADGADGHBABGDFEDEGAGFADADDBEABDABEABAFBAFBGFGGACGBFEBFEHFHGACGCFEDGBGABCEHFGBAGFEDADBAFHHGHHDH,False +667,8.0,7.0,10.0,12.0,11.0,15.0,18.0,9.0,FAGEGGDGEAGDFCFFHBFDBGDFGBAGHCGFCDBCGBDFHGFHEACECCECAEFGCFGHFEDGHGBHFCHAEDAEDGDFGFGEBEDHAD,False +668,10.0,9.0,8.0,13.0,5.0,7.0,10.0,7.0,GFDGECCECCFHAGBGDBDFADGEDAADAADAADCGBGHBHBDHFGHFAHFACDEHBEBDDCGGCDFBB,False +669,7.0,12.0,7.0,12.0,9.0,2.0,15.0,14.0,HBGHAGHEGBCADABEEHFCCGHGGEGGCDGCHGEDGDBADBHDBGEAGAACEDDFBHBBHBDHBDHGCHGHDEEBHD,True +670,0.0,5.0,2.0,3.0,7.0,4.0,3.0,4.0,FGCFHFEDBHBBHFBGEBEEDEEGEHCD,True +671,5.0,12.0,12.0,3.0,8.0,4.0,5.0,4.0,BBCBBAECHCGHCHFCFCCBDBECBEBFEBCGHCEFGGBAGEAEEACCBDABD,True +672,11.0,18.0,12.0,10.0,18.0,18.0,25.0,17.0,AGBBGFGCFCEFCBHCADEBHCHDEBGGGGGAGGCGFHFBHDBFFAFHAEHFEFFAGBEDHHHHBBCFHAFCGCCBEHBEHGDBFEAGEHGEAGEAGEGDBGDCGDGGDFHEFEBBCBAGBEDHEFGEF,False +673,9.0,13.0,14.0,18.0,14.0,11.0,8.0,15.0,CGDBHCCHGBFGAFEEHEHCEHCACCADCDDCGBCDBHDHCBHEHABHEEGDFHDGACBAGDFEDFEDECDBDHFEHBEFFEBCEBDABAAGFHFDDFDDHB,False +674,8.0,13.0,7.0,9.0,11.0,13.0,8.0,11.0,GHHFHFCGFBEFDEDDBFDBAHFHHFCHEDGEHGCBDBHHAEGAEAAEBAGBAEFCFGCFAHBGEFECBCBBDBBDEFDF,False +675,1.0,9.0,5.0,1.0,4.0,4.0,4.0,4.0,BECBCFDGHHBEBBFBBFBCFBHGAHGCEECG,True +676,7.0,7.0,1.0,4.0,6.0,8.0,6.0,3.0,ECHEDFEAHHDFABGEBEABEDGFAGBAFBAFGFGGFABFDB,False +677,14.0,18.0,19.0,11.0,14.0,16.0,16.0,25.0,EEHFECBGCECHDBHGHHGHHGABBDFBDFBAFHAGDABCABFHHABGAEGDBHHGHFFHDFEDFHFGACBCCGCAAFFAHACDGCDBCHBFGBHEFHAFCCEBBDHCHFAHEGHEGCEHCECCHGEGBECBD,False +678,9.0,12.0,6.0,10.0,11.0,11.0,13.0,11.0,CDEAGGDGGCGBCGBAGBGEBDCAFGHFGBFEHEEACFAGFDEFGBHHFHHEHFCGDADHHDHEDAADFBFBBFBEEHEABBD,False +679,27.0,20.0,25.0,20.0,31.0,18.0,23.0,23.0,EFHEDHDDBECBDAFEEFEEAADGGCGEBGADEECEEFEECAFCGEGGBFCBFABGACDAEHBHCFGCHGCHGCFDCBHHBEABAHBABAHEAHGADGCCFECDHDFAGECHAFBADBGDBCABHADDBHCEHCEHBFHGFEEDCDHCEECGCDBCAHGHBGEAGEAFFAFGAEEAFAHGEHGDACD,False +680,27.0,26.0,27.0,28.0,20.0,19.0,14.0,25.0,GDCFDCFHCBAEGAFACFAGFDBEABDBCAHCGFFFCFBBBADBGFCDACDGDDHCEHAEHBFGBHECDEGAACBHCHEAHEFCGACDBHDACGACHAHHAHDEHFCBBABBABCHBFDCGBCHBCHFDHEEBDEHEEHGEFABHAHCAEDBCDBCDEEDCBDBHAFAGEADDADFADFDDHGDEC,False +681,3.0,1.0,1.0,3.0,4.0,8.0,7.0,1.0,HGFEDDABGFGGFGFFGCGAFDAFEEFE,True +682,15.0,12.0,11.0,14.0,15.0,27.0,23.0,14.0,FHFFHFCHGEDCEDGABGDBGFFGFHGDDFFDGCHECAEGEBCEFCEAAAAGACFAGGGBEGBFBAFBAGGAEHAEHBDGGDFDAHGGEGGHAFHGCEFDBFEHDDBGFBCFAFFEHFCHFHDFCFFDEFB,False +683,3.0,2.0,5.0,6.0,4.0,4.0,5.0,2.0,GGFDFADFADECDCGBCGEDHEDHGCBCAEF,False +684,13.0,18.0,21.0,19.0,20.0,13.0,21.0,11.0,FEEGGCAGBEGFECBEGBDHBDCCGACGFBFEHHEHBCHCCFDCDDCEACEAFHHFCFDEBBGBDCBDBADEDEGCFDHABEDGEGFDCFECDEAHEDGEAGFAEAAGHADABDBGCGGBGFBDCBDGBCGECGHC,False +685,10.0,7.0,12.0,11.0,9.0,18.0,8.0,9.0,HDHAGFAFFAFFAEBDCBDBEAFEACEACDGDDGFCHFCBCCACHGCFFCGDEFDFHEFHDCBEHGEGFFDFAAFBEFCDGHBH,False +686,6.0,12.0,8.0,11.0,9.0,7.0,20.0,10.0,BCEBCDBHAGDAGDHGDEDAGDGHBEHDDFGDGEDAEGGGCEBCBGGGCHECBFHHGGFGGFGGHGAHFBBCBECBHABFDEF,False +687,12.0,20.0,16.0,25.0,15.0,20.0,20.0,33.0,DFDHAGHAEHBHBFCFFDHFDBGGCCBDABHGGHBBCBFCHCEEADDACDFCAFBHBHDBHFBADGHDGHDGFEEBHHGGHGHFGDFCDHEEHCECCHDBDAGDABDCBFHAGEAHEHHEHFDHFDHFDEFDCCGBCHEDHBDGEHGBBGFDHAHHFEFGG,False +688,3.0,9.0,2.0,3.0,7.0,7.0,3.0,4.0,CFEHFBFBBEDBCHAFABFEBEEBDEHFEDFHBGGBGA,True +689,15.0,26.0,20.0,34.0,29.0,23.0,27.0,17.0,GAAGDABHABEGDEBDFFDHFEHFBFCBGCBCCDGFDEHDCFDBHEBEFBEBCGCDGADBDGGGAAFCEDCEDBHGBDDBEDFFGFEHBEFFCAHCHHGFDDBCDBDFEHFGAFHFFDBEABEFBGFAGHGGEECCGABDDBEEBECBEAGCHGDHGDEDHFDHDAECAECDEDGEDEBCEDDGGDEGBCG,False +690,2.0,5.0,5.0,7.0,3.0,8.0,3.0,2.0,GFGFFGFDHHAEBCCBCDFCDEADFDBFDCEDBBF,True +691,11.0,14.0,14.0,3.0,13.0,5.0,13.0,10.0,ABGFGEEGEEGEHAHBCHBDDGHBBABACBCEEGECGECGHCABCABCHBEGAEFCCGBFGCAEFGECBFHACHACHDHBGBA,False +692,17.0,27.0,23.0,13.0,20.0,16.0,15.0,12.0,BCCBCGFCGFADAABEDHEHBEADCFFEFFCABCGBABBEGBADBABBFCACGEDBEBBGFBGHBGHDEHBEHBCHACHFGEECHGFHGCCGECGDBBDGAEADFCGECDEFEFCCFAHFEHEABAFCCECEBDDBADBABBC,False +693,27.0,22.0,19.0,22.0,14.0,28.0,28.0,25.0,FCDFEDBEDFECFBHAAHEACBFDEGDCGFFHHFADGABFAFAAGGBHFECAECAGCGBDGBDHBHCBHFEHBBAFAAFAFFCHFGGFHAADCCGCCGBHGDDGFDGBDGBABHAGFDBFGBHAEFFDGFDGCAACAGGHDGAGCDEHDHBGHEFCEFADHEHABHAFHEHHDBGGBFCBGCHAD,False +694,18.0,13.0,19.0,10.0,11.0,15.0,13.0,6.0,GDGHAABAGDGHFBFGBCGACGAEAFDAFDECHECACBFCBACBEBDGBFACEEBEDCEACEBBDDBGFAFFDCFECDHCACCGBFGHGCEGCAAHAAFCAFCFF,False +695,10.0,11.0,11.0,10.0,20.0,12.0,15.0,5.0,DBDBFDEGDBGEEGEGFAAEGDFCFECEEAEEBHGGHCGHCFACGHEGEEGAEFCEFBAFBAEEACCGFDBFCHACEDFADFGBGCBDEBEGBD,False +696,11.0,15.0,9.0,15.0,19.0,14.0,16.0,14.0,BBEABEBFEDFHBEDCFCEDEFDECCEFGFGBHGBCGHGFHEBDGBFGCFGDGDACDAFBFHBHGECGEHDEHBBFDEEDGEFCAAHEABEHHEAHEAHDAHDGGDBGFAGAD,False +697,4.0,10.0,3.0,4.0,4.0,9.0,13.0,9.0,EFFBHHHHHCADDEGDFGBBGHFGBBBBHBACEHCFBEGDGGFGGFGAFGAGHFGB,True +698,8.0,6.0,6.0,10.0,3.0,3.0,10.0,9.0,CHGBHGEHGAAGHDGDAGDBDHADHBDHDAFACBCFBGEHCEFCGABGAGDCDDH,True +699,23.0,20.0,26.0,25.0,24.0,29.0,20.0,24.0,CDBFFGEGEACCACDGBDCHACHACHBGDBCFBHFHHFHHAGHAGHCHAEEGCEHEEFFCDFDDFDFAAEEFEEFBEDAEDFGDFGDHHDBCBBCEBEABADDAEDGGGCEHAGBEFBCFDHFBEFADFDCEHFEHFHADCFDAFHAFBFCEDDBCAHAACGCBFCDHBFHDAGFEGFGGCCGCBBCAHGE,False +700,29.0,20.0,21.0,24.0,24.0,23.0,13.0,26.0,EBHEBHBADGAHAAEEACGAFAAFBBFCHDBHAGCDEBDCDDAHHBCEAAFHAFCABDDEDEEDFHDFCDFBEGCFGEFAFGCHGDHFFEFHEDDEADBACACEFCBHCEHCAAEAECAEBFDAFHAHGAHGBGCBDHBDABDHBDHADFGEBABHFCFFAHFDECHHCHHCFCGDEGEE,False +701,3.0,7.0,7.0,3.0,6.0,6.0,4.0,11.0,CEFCFHGFHBHEAHECHEBBAHAEECHCDHCFFCHBGFBDDBGHBGH,False +702,9.0,6.0,16.0,15.0,12.0,8.0,10.0,9.0,FDCFDCDAHDGHFAACBCHDEHEGDEDDFDDEGCGCDBCDEAFCBCCBCGACGACHHEEHADDAEDCECFECFAGGBBEHFGHEG,False +703,6.0,1.0,3.0,5.0,2.0,9.0,6.0,6.0,DABEAHCFGGFAGFHHFCFFHDFHDCGFFGDEGDHAAA,True +704,4.0,1.0,0.0,2.0,2.0,1.0,3.0,0.0,BGGAAGEADEFDA,True +705,18.0,19.0,12.0,21.0,25.0,19.0,18.0,24.0,FDAHBFHDCHACHAEAEEBDDDDDGFHHFEHDDBDAAAFHAGGAGDABCHGCEGCFDBGCBEFHFDHFHHEGCFABHEBHCAHBBHEAEEAEGAEDEBGFCDHEEHGEFGEFBDFEGFGHFDHFBHDBGDACBAFBDFEHEECBEGBDGAEGEHBC,False +706,17.0,12.0,10.0,18.0,25.0,13.0,22.0,21.0,AGEHCDCDAEDAEBAGGHGGHDCHEHEFCEABEGBEBHAGABHABFFGGFGAFGDBGAEDAGFAHEEBFFAEFBEHCEFDEFEHDCHDCHDGAEGAHHFHEBEEGABGDHGDHBDHDHGCEDCHFCEEDDEHDGAGGE,False +707,18.0,24.0,22.0,26.0,29.0,18.0,27.0,19.0,HFHHGDEGFHCDHCEGFEGBDCEDEEFFBFCAEBBGABHADAAGABFDCGCBHABAGHDEDEEHBAHDAGDBGCBDHHDBEEGCFGCHCFHBFDEGDHDFHAEDAGDFGEFCEGGEBGCCCCECGECGCHACEGCEFCDFBDFBGBEABECBEBBGAHGDHDDAABGGBEGAEBEDFDDFEDE,False +708,20.0,10.0,10.0,16.0,13.0,13.0,19.0,23.0,FFHDFHCCACGGGHEEHDGGAGEAGHAEBAHDGHGGHBGAGFCBDCDDADDCEHADDDHBAHBAHBGGAFAAGAGGBGFHAHHDHGEHEFHCFHCBACEDBDDFCEFAHFAHEAEFHFABEDHE,False +709,5.0,8.0,2.0,9.0,7.0,8.0,16.0,8.0,CGDAGDFHDGABHDEFFBFFBEDGGAGGCEGHHGADEFDEDHEDGFBGHGGHGGBGBBAHEFB,False +710,2.0,0.0,1.0,2.0,0.0,3.0,1.0,3.0,FGHDDHAFHAFC,True +711,11.0,11.0,7.0,14.0,11.0,15.0,19.0,23.0,DHDDADGHBGFBGHHGDGAHHHGHHGBCEDCHDHDECGGFDDAGBHGBGDAHBFFBFFCHFCFFHBFHEHHGAFGAHGHDCDDAGEHGEHBFHEGBAGFAEFCEABEAEEF,False +712,22.0,16.0,19.0,9.0,22.0,12.0,19.0,16.0,HDGBAGAAGFEEFADBADHGCGCDBCABEACGHGEABEAFGHFEHFGHFGHCGEFGEFHHACDAHFCGECEABEAEEBBABHEFEAGEDGBCEHDEADCBDABCHCCHBCGAGHACEACHFCEEBAEBAGBGFCC,False +713,10.0,16.0,20.0,25.0,19.0,11.0,23.0,14.0,FDCDDBFDGCEFFEBBEBBFDBHCFAAHGDHDBFFGFDACDAEDGEGGDCADCDDGEDGEGCEGDADCGDCBBHEBDECEHCEHGBHACEGGDCGHHGHDGCGGCGCDHHDECCEBEEDABBAGBGEAGEFDHFBHCC,False +714,7.0,8.0,11.0,9.0,14.0,8.0,8.0,14.0,AADAFBHGCCGCDHHFHBCHDCHDEHEEBFBAFHDGHDHHEAFEFCEGDHBEHCCFCHBBEDEEAFEAECGECGEGDBG,False +715,4.0,5.0,2.0,4.0,4.0,2.0,5.0,7.0,BEEHHBHHCDHCGEBGDBDHEFHFAAGAAGBDG,False +716,2.0,4.0,4.0,2.0,5.0,4.0,1.0,3.0,GBACBHFFEFFDHBDHEAEECECCB,True +717,15.0,12.0,19.0,9.0,14.0,21.0,18.0,23.0,DBHAHHEFBFAGHAGHAEHFEAAGCGHBFHBAHDCHCCDAGGHGFDAFEEEGECHCCEBGDAGCAGHGFACDHBDGBAFCFFCDFCFFCEGCBGFBCHBHAGHFHCBHAFHCFGCEGCEHFEBEEFFHDFH,False +718,21.0,29.0,17.0,17.0,19.0,12.0,14.0,21.0,BHBBDDFDBFDBDHADHBCABAHFADGBECCFDBADGEHHBBEGHEDHCHEBHBHHBEEBCABFBBFBFDAFABDGCEGCEGBEACEBBBBCDCHGEDEEGGHGAFGABGABAAHAHHAHGAHGEHCDCFDCFEEDEBHCCCACAAFABE,False +719,15.0,18.0,17.0,14.0,22.0,18.0,20.0,22.0,GGECFCHFHBEHBEDBEFBEHBDHBGAGFAHFAFECFDFHGFBGDEHECDGCAEFHEFBDGHDGDBGBBGBHGCCGCCGCHHEBBBBEEAHHBFEACADDACGCFEHFEHFAGAHGEHFAAFCHDCEGCEFDEGBHGDHEECAADA,False +720,4.0,4.0,3.0,2.0,1.0,3.0,4.0,4.0,BFBBFHBCHAHDAGEAFCADCGGGH,False +721,22.0,14.0,33.0,22.0,22.0,16.0,25.0,18.0,EGACBDEEDAADHAHBABBAEGAEGBHCBADGFBCFBAACFEEFEDHBDCGECHHHAGEAFECFEGFGAFGHCGAFGEFECFGCABEEGGDAGDCCHCCHGDEGBEDBACAHDACCCBHCAHCHDGHAECDDCDHCFCDAHHCECGECGDCGFGECCCFCCDDGDDGDFGBF,False +722,15.0,12.0,9.0,7.0,14.0,11.0,9.0,13.0,HFDHFEHEGDBCFBCAAHFAEFGGDBADEAFEAHEAHFBGFHEAGEDGBBABHGEHGECCABCEHDBADCFEEFAHFGHEAHACCABCBB,False +723,25.0,27.0,19.0,19.0,29.0,24.0,29.0,27.0,CHBDGEDBEGCHBAGECBACBGCEACAGCAGEFHHHGHAGAEDHGCGBBACHDGDAGDAGBFFBGFBDFEAFBABACDEFFEAHHAEHGHHBFABFACHHHEBGBBEABEAHEDGEDBFDCHDBGGEHHEGHFCHFHAFDAFEGGHGECDFGGBGCFEAGECBECBECFEAFEBFEHFEHBDDAEDADDFCBFEBFGHG,False +724,7.0,6.0,4.0,4.0,2.0,2.0,7.0,4.0,BACDABGAGDBGHFGHFCHAEGADGBEGBAADCBHC,False +725,13.0,14.0,14.0,9.0,9.0,11.0,7.0,5.0,ADEDDFDEGBCACCABCADGAFGFGAEGAGBAFCFFHBBHCBDBFEGAEDBDFHCEECEAFBAFHCFCCDBCABCABHBBEC,False +726,6.0,1.0,2.0,1.0,0.0,2.0,3.0,0.0,ADAAGACFACFBGGA,True +727,22.0,23.0,26.0,27.0,23.0,28.0,17.0,22.0,ECCBCCADCDDGGAHBAHFHCGHEGHCAHGHHGBEFCAFBAFHDFAFCCBACDGCBGHGEAGCDECFEBEEDFDFBHGBAGBADFEDAHDACDGEFEEHGEHFAHFAEBDBBEBFEDAEDHDDCFDGDABEGDFHBCBFDFFACFAFHEFHABDCCEABEFFHCFBFFBFCBDCBDCEDGDAHDCHCE,False +728,0.0,0.0,3.0,1.0,3.0,4.0,2.0,2.0,CEHCFCGFHDFEGFE,True +729,17.0,19.0,22.0,26.0,19.0,16.0,18.0,23.0,GFHGAGFACDAEAGFDCBCCBCBBGBDGEGCEHDDADHEDBADHDEFBEDBDGBCGAHHAEAAEBDGDGGDGABBECDEFDEFHCAHBDHBHGGDFFEFDCCDACBAHEABCHEEFCEFHGFHDEBGEBHHHHCFHEAHBAHCDDDDCGFCHFCHCCFCD,False +730,10.0,12.0,10.0,12.0,5.0,3.0,7.0,9.0,GGBHAHCBEBDABDCEDEGDCGDAFAHGAHDADDACHACGECADHABCCGCBBCBBHHBFDEHDBDFB,False +731,8.0,9.0,15.0,9.0,17.0,19.0,15.0,6.0,BHGBCGBCDBCFBCBACFAFEGFECFEGFGCEGCGADEFECHEDEEFFEFFGFFGDFCEGCACBAFADCGEEGDBADFAHHDGHGFEEDCEHFFBGEC,True +732,15.0,25.0,16.0,23.0,8.0,23.0,16.0,19.0,CCGCCHDFHDFABAHDHGDBFDHDDBBDHBGHGFDDFGGHEHABDFCHFAFCACBBDDBDFBDABHABGBEDBEDAFCFBCFGEBBHCBABGABGHBGHFGCFGCFGEBEFADCHFHFFCDDCHAEHBDGADAADGFCFFBFEBH,False +733,26.0,12.0,25.0,16.0,6.0,12.0,11.0,16.0,DDEFFEHBCBCAGCHGBHAAHCAHAHHBHHGGHCFDCADCADABFCCGAFDAGHCCCACFADFADAHBGBCFFDBCHAFAAEDEBAHBAEFAFBADBDDADCCCCCCCACCGCDGADGAEAHGH,True +734,24.0,26.0,16.0,18.0,21.0,14.0,24.0,22.0,HGDGADCHDBBAEBDEBDEBEEDECFBCAGCBCHGDBGEBDEBEEBDGBGHHFCDDHGDAGHADEBDAAHBGBAHAEEGEBGEBAACFHCFACFHFAHFAHFDHCBEAHEHBCHAHAEDGFBGDBGFBHBEGDGGACEACACBACFAGGEGBFBHAGHAGCFGHF,False +735,22.0,22.0,29.0,19.0,27.0,26.0,31.0,18.0,FACFCCFCAHCGBBDADAGDFEEFAEFAHADEGDACBFCBFBHGCGGCFFBGFGFBBHHBCAADGCDECGGCGGCAGCEGEGGDDGAGHAGHFCFCEGDGCFFBDEBDFBFEEEHEHBEAEEAEEAGEFDEGDBBEHGAGFDGEDHBCHGAAAAABCECCECCHCCDFHBFCEGEDGFBFCBFHBFHDHHCGEB,False +736,3.0,2.0,3.0,3.0,1.0,1.0,2.0,0.0,DCBDCBGCAGADEAF,True +737,25.0,20.0,13.0,20.0,9.0,15.0,15.0,17.0,BBCBGDDHBCECEDCBDHGDAGDAEAACDBCDAAHFAEFDCFAFBAGAGBABHABDABFAFFDDHHHHBFHDFGGHDCFGGHHGAAEAABCAGCBGCEGABCADEBBEFBDFHGFHDFHCFHAADEBDGADABH,False +738,15.0,21.0,15.0,20.0,23.0,14.0,16.0,14.0,HBDCBCCDFDDBDABDABDFDHHBEGEFGEFGECGECGECABBEGFEGFGFBABDGBHGBHCAEBBEBEDDDBHDAFCACCEBHGGDEDAEACFBFFBGFGEEHHEHEAHADFCDCAFCDEBDCDEGEHGAHAHEABE,False +739,6.0,4.0,7.0,3.0,11.0,9.0,13.0,4.0,CEEGFEGFDGBBEFGGDEDHCCEAFEAFBAFGACCAGAFEBFEGFGCHGEHGECGHG,True +740,18.0,18.0,17.0,21.0,22.0,23.0,24.0,19.0,CHFCHDGHDGBDCFEEFEDGHDAHDAECAFGFFHFCDEGAHBDBEDHEGAEGAEFBEHAEHABBAHFGECAHBFCDFDEEDEGDACBFHDFBGFGFEEFAEFCFBCHBDFAGGAGGAGBAGBEGEGDDGCDBBDBGEFGDDGHBBECHFCHCCFAGHCFCAH,False +741,9.0,8.0,14.0,9.0,12.0,8.0,10.0,8.0,HHAGBAGCACBHFBHFDEADGBFGCDABDCEDCEFABGECCEBCDGEEEEECECCFACHAEFGGFCGFDGDACDHHBH,False +742,12.0,15.0,13.0,8.0,14.0,16.0,4.0,12.0,AFFFBFFBCEAFAAEBHDAEAHBCHFCHBDHBFHBDEBAHGFHFBEGCFHCEAFEAHABDBEDEEFECHECGECFHCFCCDCCGBDABDBBEFA,False +743,10.0,6.0,7.0,8.0,13.0,10.0,9.0,5.0,AFAAEBGEBEECEEDFCGGHDGDFCFGHFBHEHDDAADEDDECBEFBECHCGAAFFAFEAGEAGFBGC,False +744,4.0,4.0,4.0,5.0,4.0,3.0,5.0,8.0,FHDHHGAHBHDDHGDAFEACEACEGGFHBCHBCGEDB,False +745,5.0,2.0,6.0,1.0,2.0,4.0,4.0,5.0,CHHCFFGFGAAGAHGCHABEACEHCBFCD,True +746,6.0,7.0,9.0,8.0,5.0,5.0,6.0,0.0,GDGGFGCEDBEDACDCCFACFCDABDACAACBEBBCFBFEEGBDGD,False +747,23.0,21.0,27.0,20.0,27.0,21.0,28.0,26.0,DEADBCCGHHGHDBADBADBEEBFEBEBGGCAEDAHDFDGHEAHEAGEDGEFGBAGHFHECBCAEEBEGFFFHHHDHHGACGEEDCADBAFBHGBAFBDFCDCBGHFHAFCCDCGACGAFGCEGCHBBDGCHFDAFGGGBHGBHAAHCAGEDCCGCCHBCHFFHEFCEFAAGACGCEECECHEBHEGEDFEDF,False +748,3.0,5.0,1.0,5.0,3.0,2.0,3.0,3.0,DBGHEAHDADDADECFEGBGHBFBB,False +749,11.0,7.0,13.0,10.0,10.0,9.0,18.0,6.0,AGEGGFDHECGGCGBCGECBCCEFCADCGHCGEGBEBDECGGCAFHDDHGDAGDAEAEFDGADGAFCCFBAFEFDGFAGBAHBH,False +750,19.0,21.0,8.0,26.0,26.0,23.0,18.0,20.0,FEHFHBCHBCHAAHDGEABEDCECBDDAFFAFDGDHCDEGDFADCHDEDEEGHAGDFGCFGDFAEBDFBAGHAEEAEAAFAFBAFBEBBDDBDHEFHEHDEBDEFEBBAAEAEGBEDFHDHGBEGEFBHCHFBHEGGEFGEFGDFHFHGDBGDBFDBHDGA,False +751,10.0,15.0,9.0,6.0,11.0,12.0,12.0,15.0,GDEEDHHBBFGBHHBEHFHFBDCEGGEGCBCCAFCEFBECHEHEBHBAABFABFABFGFEGAEBDHCGHAGHAFCACGAHDHFDHGBBGF,False +752,16.0,16.0,21.0,19.0,22.0,24.0,24.0,17.0,HHEEFGDFCDFCDFGHFHABEGECBCGBCGBFGDFBCBAFFGCAGCAGBAGHGDHDDHGDHGEHAECADCEFFAFFDEGBAGBCEBAHFACCDCBGEHDEGAEFCEDBEHFHAEDBGAGFECFGGAGGEFHDHECHECFECFCBDCGABDBHDFEFFED,False +753,5.0,5.0,9.0,7.0,8.0,5.0,5.0,7.0,DHCDCBFEBACFGCHGCHGEDGDDEDHAGEACFACEAHEFCCFBDHBHBEE,False +754,1.0,1.0,2.0,5.0,0.0,0.0,2.0,1.0,GGBCDDCDDADH,True +755,3.0,4.0,2.0,11.0,7.0,7.0,7.0,3.0,DDGGDGFFEFFGGDECDEDFEDFBBHBGFBHDAGCADHDDEAEE,True +756,13.0,13.0,9.0,10.0,17.0,10.0,13.0,12.0,CGAEDBDFGGHCGBCFAEEAGFBFFBFFBEGEEBEEHEECDEGACGEHAFGADHABHAHHCGHFGHEHEAHGDDCAHFAEBAEDCBBCBBGBDEDDA,False +757,8.0,8.0,4.0,5.0,4.0,3.0,10.0,2.0,BDEBGHGGFDGFDAFCGGCEBBAACEDCADHABGGBGBAABGAE,True +758,26.0,19.0,23.0,17.0,12.0,22.0,20.0,22.0,DDGDEFCHCHHDHHCHGGHDBAFBFGBFEBCAFCAFHFFDCCDCEACACBFEGGHGGDFGDHCBGAFCAFEDBEAEEBDFGDAGBHBHHADGCDFCAHCHFCGFCGHCBHABDABAACHAFAAHCBHBFABFAGFDBFHBEECGAGAAGFAEDABACCEGH,False +759,4.0,1.0,4.0,4.0,4.0,6.0,8.0,4.0,GDFGAFGDGCFGCFCAHAHDFHEEHEEGDGAFGCB,False +760,2.0,2.0,0.0,1.0,4.0,1.0,5.0,1.0,ABEDBHAEGFGGEGGE,True +761,21.0,26.0,28.0,30.0,24.0,24.0,21.0,23.0,FDCHDHHDFHCCGFFAFAAGABBDGBCGBHGEHFHFBCEACEHEHBEABDBBABAGBFFBHDEEDBGFCGFCGFBBCBBDBGGGCDECDCFECFEABGCDAEHEHBEDDADFADGAEEAEFDCFHCFBCHBCHAEDDEBGEDGFHEDCBACDGFFCEGCDACABEGCDGHEECFCFHDFBDHADHADHACGDCDDHH,False +762,24.0,12.0,13.0,17.0,17.0,14.0,9.0,11.0,CEAAEBDEFDBCCBABBACBDBDDADGCGHAEHAEHBEFAEFAFCACHBHFEHADHFEFAGFGCDADDACDEDGEBGECAEBFEBEADGACFAHAACAAEADDFFGAFGCDHDHEFH,False +763,6.0,8.0,13.0,10.0,5.0,9.0,19.0,14.0,HGDFBDFGCHDCBGCEGCEGHGHHGACGFCAEEHBBGDHGCCGFAGHADHBCGDDBEAFDHFBHFDGCAGCGFFGHBGHCGHCD,False +764,27.0,23.0,30.0,22.0,19.0,28.0,33.0,17.0,AACCCCCCFBCDCCGCFBEFDGGDCGFCFFCAECBGBFCBGEHDEFGHFGHACHGFAGEAFFFCHFDGCHGDGCFGCFGCAGDBFFBECEGCGGBGHBDAEDABFABFDBDDBDAADGHHFBAECEBHAHHEFADFADFACAACGECEEAGEABADBDHEGEDGEDBFAHGAHGAGCDFBAGBGFFDCHBHEACGGBGB,False +765,18.0,15.0,16.0,11.0,14.0,19.0,16.0,15.0,CEFGFFADDDDCFAFGAFEEEAEHBEHCECAEBAECABHACHFCFGBGGBDABCFFFGFHGHGDEDABBABBAHFACGDFGDFGCBEEDFHACHGCHGBHFEGFAACECDGCHGBHCBHBAHAF,False +766,2.0,0.0,3.0,2.0,3.0,1.0,2.0,7.0,HHEHHCCHDGHDFCEHAEGA,True +767,17.0,7.0,6.0,11.0,18.0,9.0,7.0,8.0,HEEBEFBEBEEGHEFCEACFABFHBGEAEAACAADAADADDAFABDAGDEDAGDEDHCHFABEGDEFDEAEECEGHHHFGFAC,False +768,7.0,8.0,17.0,12.0,13.0,9.0,9.0,18.0,EBDDBCDHEEEGCEFDAFDABCBBHFGHGGHDCHFEHFAHAEHCFHCAHEHBEGECHEGDECCCCDCBHCGHCBFGECACHAFHDCDDHFDHG,False +769,20.0,21.0,9.0,15.0,21.0,8.0,21.0,20.0,HEDAEDGBFGHEDHEDHEBCGAEAAFAABHDHAEHGGGBEFDFFAAEAEHCHBCHACDBFGBGABHBBEBBAHBHHDABDAGDHEFEGBGGDCGEBGCHECHECHGBEDBEDBAAFGADBAGAHGBGDCGEEGEH,False +770,21.0,9.0,20.0,15.0,18.0,14.0,11.0,20.0,AGHAHEGHACBCDEHDEHEECGABBADBFCHFEABCBDEAGEAFEAFECFDCHDBDFADCAGCADCHDEADAAHFABFEDCEGCHFHHCEACGDDGHFGAFGAHHHECAEHDHHABCEFCHFCGCCEF,False +771,4.0,4.0,4.0,6.0,5.0,8.0,8.0,13.0,HGCHGCEBAEDFEDHAHHGEHDDBGDEGBHGFHGFCFFCHADFFBHGAHFHH,True +772,4.0,7.0,15.0,14.0,7.0,5.0,7.0,12.0,FCECCEHCHDDHEFHDDAEHECCGDDBDDBEDBFCGHHHBHHBCABCHBCDEDGCHFDACDFCDGCGGAGC,True +773,15.0,15.0,19.0,12.0,10.0,13.0,9.0,11.0,CDFCAAHAADAADBHCGEAHFBGCBCCEGCDCCDEAGHAGECHFHFFBFBHFBADCADEHBECBABBHFECAGCDDCFFFHDFHDFAEGAEGBCCBCEDGBBCB,False +774,17.0,15.0,18.0,13.0,14.0,14.0,9.0,11.0,BDADABGFCGHCGAGHAGFFDCCBAGFHDFHCFHCBACEACBAGBACBECFEBGABFBFFBHHBDEEDEAHEAGFDEFAFFBDHBECCCCDCEACEHCEAADDCBAEDDEH,False +775,12.0,10.0,12.0,10.0,14.0,18.0,9.0,17.0,FFDFGDFEBAEBHFHFFBFCBFCBACEGDDCHCHDGBEEAEHAEBACCCCCAHEAFFFFFHGBHDAADAHEFHGFHEDCAHHADHGFGCHGFEEHDEHBEGB,False +776,15.0,9.0,14.0,7.0,14.0,8.0,10.0,14.0,FGGCGFEGFEGEBBABCCDCHEHHCHGFDGAEHCEFCEGCAACEACADHABADBFDCEDAABEACDGCHHCHAFAGHEHBEFEAHBAHBEH,False +777,3.0,5.0,7.0,4.0,6.0,7.0,4.0,2.0,ACHDGDFECAEGAFGEBDFBCFCCFHCEECDBGFBEFB,False +778,13.0,16.0,17.0,23.0,18.0,12.0,11.0,15.0,HGEDGCCFHBDHDDECFEHAEBAEBHDCCDFCDCHGHFGHAABCAFCGHCGCEFFEBAEBABBEHBGHBFFDDGDAEDAEABBHBBHEDFEFCDCEDCEDHHCGDDDDDAGFEBBCDDADCAEEG,False +779,0.0,0.0,2.0,3.0,0.0,5.0,2.0,1.0,DCFGFFCDFHDFG,True +780,4.0,14.0,9.0,15.0,13.0,16.0,18.0,13.0,GFHBCDDGGEFBDFGDFEDHCBBGEFEAFEHBDHGFFECCDHGHCGBBGBEDHDDEDEEDBCFHGDHGFHGFHGFGGFGBFGAFHCDCAECAEBBEDBGFBH,False +781,14.0,11.0,9.0,17.0,16.0,19.0,16.0,13.0,AHAEEAEBDCFCAFEACDFGBGHHFBHDBFDCHDHHEHFDGFAFEABDGEEEFHFABFCGFGGBCHBEGBHACEADGACGCFGBFGAFDAGBAGFDHEDEEDEFDEFDGHDGDDF,False +782,17.0,30.0,15.0,20.0,20.0,24.0,22.0,25.0,GBEGHHGHFDDAEABGCBGDDCCHFEBFGBGDBGDBGCAAFGAFDEFGEFEFAEFACBGEBAEBHBBHBCHEHHEAHDDCBCFDADDHDGHFEHBHFBDBDHAFHFFHGGAFCFGCHEEHEDFAGBCHBFGBCGDCGBHBBCFBDBDEBFEFHHCBHGBEBAEBHEFAAFDAG,False +783,18.0,12.0,19.0,16.0,8.0,23.0,23.0,21.0,CAEAGEACHFBBCABCACFADGBFCCFGDFGFBGHEGHCCHABHGBHFBGEAGCCFDAFDCHBGHCGHDFEGEHGEHFDHBDFAHFAHCGGCGDBFAGFHHFHGFDDHGHFDAGBHFHEDDDDCCGCCGADFAFGAFAAF,False +784,26.0,24.0,29.0,15.0,21.0,16.0,22.0,14.0,GEEGAEGABFAFGEBBHCCCGGBHGBFDAADAAGAFGBEBBCCGCAAHAAHDBEEBGEDADDADDAECAECBEBHEFFADBCGECGCCDCGACBACFDCFHFDHGHBBHDBCECEGCBGEBCEFAECCCHFGECGCBACBFFBGFHCECAFBAHBHHAFDAGDECAG,False +785,1.0,0.0,2.0,2.0,2.0,6.0,1.0,1.0,FFFEFFEDFCDCGAH,True +786,20.0,28.0,18.0,25.0,30.0,17.0,20.0,19.0,ECEDCEBGECGBDDAGEBEEHHADHDECGEDEEFEADEAFEAGDBDFCEFBDHBHAGAAGCAGCHHCHDBDFFEECADBAGFCBBEBDEHHEBHFAHFBCEBFEGEHADBDHBDHCDBGDBHDCGBFEADEADHAEAGBBCBACEACFDCBDHBDGEGGEBGEFGBFCBGHFGFFAB,False +787,5.0,3.0,2.0,6.0,9.0,8.0,2.0,4.0,DAEDAECHGCHBEFFEFEDFEDADHEDAEFBFABFHFEG,True +788,5.0,9.0,7.0,1.0,4.0,3.0,1.0,5.0,EBABAACHBEHFACBBFBBEABCDECHGCHBCHFC,True +789,12.0,4.0,13.0,8.0,13.0,16.0,10.0,11.0,ADAAEBAEGDFGHFGEBGADFAFFAFFEFCECEEFEGFEDFCCECHHAFDCFGHEHBBFAGFGHACECGHCDCCHCCHDFHDGAAEH,False +790,6.0,10.0,8.0,9.0,9.0,8.0,9.0,13.0,CEAHHCFHCFHBEACFACDBGDBEHBGGCGGAFDHFCHFEHBABBHDHGDEAHGBEBEGBEDHEDGCDFHDF,False +791,8.0,14.0,12.0,15.0,11.0,8.0,8.0,8.0,EBHEBDCADCAGCABCGDEADEAEECBEDADFEHECHDBHGEGCFDCFBBBHBBDGHDFFDFFGBGHBACBFCHGCDCDDEBDA,False +792,10.0,22.0,18.0,14.0,21.0,20.0,16.0,23.0,DBGEHGFDGFECFHGFEGFBAECAHFHECBABHGFACEBDGBCGHCECAEGBBCDBEGEEGHEAAECGBFHBFHAFHCFBCDHCDHDBHEAEEBHHBCCBFHBCCBHCEDDEDDEFFHHFHFFHEFDAGBFEBHCBHDBFDGGG,False +793,23.0,21.0,27.0,21.0,31.0,27.0,29.0,18.0,AGFCEBGEFGHCGECBEFEGFCBFDBFHCCHCBEDDAGFBDCCDCCDEGHEGHAFHGGHDGDBADBAGEAEAGFFCDACFACFGCFGHFHEFHEDECBEBHFGDEGCEGDBAFCCFACEEBDDHCECDEADFGBBEABHACFAEFAEHAEHEGBFCAHGEFDEAAHACGDBEFBDBBCBCEHGEFGFGGFAGDAGEG,False +794,24.0,20.0,28.0,18.0,24.0,31.0,23.0,26.0,HHAHBAHDAHGAHECHECDEHEEGEFCECEFDEDDFCDFCHBBHBHFCGGEHCAHCDGAGADGCHGHFGEEGAEBABBAEFDGDHFFEGCBFBGHBGABDBCAGCEFEBFCFAAAGAGBABCAEAAFFBFFBEBDDFFCFFHFFECFHDFGCCACFAFHCFECECCFGHFGBAGBCDHHHCCHDCEDAEDGHFG,False +795,31.0,20.0,15.0,24.0,20.0,24.0,18.0,24.0,DDFDGFDGAGEBGEBGFHEDHBDBGHCFHBDCEACAGHADHGHFGBFHCDHDHEEHGGDGGEGDFGAEAEECGFCBFABFADAADAHGCFFHBFBAFDAFDBEBAAHAAHAAHAAFABCABEBEFDHDHEFHEDABHCDDDHBHCCGDHAECAEBEHAFBACEADFBFFEAFCAFC,False +796,6.0,5.0,4.0,8.0,8.0,11.0,14.0,10.0,AGGGDBHDBEDHHCHFAGFGEECFFAFFAEDAEFEGDBGHHFHDFGCGHAGHGGHGEBCEBDFGDF,False +797,13.0,13.0,14.0,16.0,20.0,20.0,14.0,14.0,FDCFDCDGCDGAFFFFHFBDGAEEFDHFGHGBFDAFHGFHGDEDDEADCHGBHGBACAHBECACHEEEEBBDFCEBBEBFEHAGCEBAEFCEFAGFAHFGHFGCFECADCGEADEHDEBDECHB,False +798,16.0,22.0,7.0,24.0,22.0,17.0,26.0,9.0,EFHFGCFGEDGFBGFBHACDACDAGBBGECEBBBDDADDADHGGGBGGBFEEDEFDEAGEAGEAFEDDBDGCDBBBGHGDHCDBDDEGEAFEADEABABBHFBFDBFDFEEFADGADECHBGEGFFGBBHEGGFDGAGAHGEE,False +799,20.0,13.0,23.0,31.0,20.0,22.0,27.0,27.0,ACCDDCDDCHDEGDBGEBHAHGDDDCDAHDGFAGHAEBFECFBCDECBAHEACGAEGFEFFGHADDGDDACEACECCFFFDFGHBHDBHDCFGCGACFCDHCBHEFDBDGCDCDEFDEFAGHAFHAHHCEGGDBGFEGHEHHAGFEBFGAHCBHCAHDADFGDEHDHHAGHFEHGEGGDGGBF,False +800,7.0,7.0,4.0,8.0,5.0,4.0,9.0,2.0,BFADCAGBDGDDGDDAEDEFBEABEBECGDGHAGHAGFGBABCGFC,True +801,27.0,24.0,11.0,26.0,22.0,20.0,24.0,21.0,FDEFHBBHDBDFECFEGGEGBBBFGBAGBGFBAEHFGHCAACHBBHBDHEABEFBAFGEDECDEGFGGHDGAGGAHCBHEEEFHEDHADFDHGEGFAAACDFDDFBDCEAHEBHEAAEFBDABAABHABDAGDADFAHFGHFGHCGDFGEBCDBDAGDBGHAHDADAGECDACDE,False +802,24.0,16.0,21.0,28.0,24.0,24.0,17.0,24.0,EHGDHECEADBDCGFCGDCFDEFDHFEEBHECAGBDHDDAAAAGEHGCCGBEGCEGEFDEBDAAGEFCAFABFBEAGEAFECCDDCDDHDHFDEFGAACEEEHGHHADHFHADHFCCAHGACGAHECBEBBDFBCFBHADDAGDCDFAHFAHFABFEBFECFHDBHDBHDGHFHFCDF,False +803,20.0,21.0,21.0,27.0,21.0,19.0,21.0,15.0,CHCDAADHHDHFEEFGGDBGABGCBCFAHFHFFGBDEBFEAFEHBEFDEFDAHCGGCDFCGCGECGEAGDBCEBGAADFADFCDAEDBDAHAEHAEGGEGAHGADFCHCCHBDBBGEADDADDBFDBCBBCBEGDDCEEAGDCGDFDEGBEBBFBAHCEHCFCFD,False +804,1.0,2.0,0.0,1.0,3.0,0.0,1.0,2.0,HBEHBEDEAG,True +805,17.0,17.0,12.0,11.0,12.0,11.0,11.0,14.0,CACCACHGBBBBABBDBGEGCAGFBEFAEBAECGBHHHHHHHFDEFGCGGBBBAFFAFFACAACGACDDEFEEDEADHAHCBHDGHABHEBGCFAHBEDDDFEDA,False +806,8.0,5.0,13.0,9.0,8.0,4.0,5.0,7.0,AABDACCACDACDBCBEEHEHCDHEDGEDADGFFCCBCGBEHCHHDGHECCFDCFAEGA,False +807,2.0,3.0,6.0,1.0,2.0,2.0,5.0,2.0,CCGFCGCAGEGGHBBHBDCFECA,True +808,8.0,11.0,13.0,11.0,20.0,5.0,10.0,7.0,EDGEBEBGEBGECCCADEEEBCEGEDBECBCCDAEDHECHAGHGCDDFDBFEBFEBEEGEFHAAGABGDFHDCHACBEDGECAHC,False +809,19.0,18.0,17.0,18.0,21.0,24.0,23.0,21.0,GGGGAGFDDEHDEHAEFAGHHHHCBECAGCEGEBGABGFBDCHDBHEHHGHFAHGCBGFDCFDCFBEFHHDAGFFGCEEDHGDCADAAHEEDEBHHFAFFABFACCBCABHGCGDBEDFEGFCGFBFBBCBBDFEGFECFAHDAEDAEAEEDCBGGFFFHA,False +810,20.0,16.0,11.0,12.0,13.0,19.0,22.0,18.0,AGFCHFDDFBEHGEHGBHGDCGFCHEGAGADFAGGAHAFBABBFBBGGAABAAEADEBDGCHHEBGCAEAHEGCAGFHDFHFEHAGDGFDBFBBFADCGDBGHFGHCCCGCDGBBAAFFAFHHFEHFEHEE,False +811,17.0,22.0,15.0,31.0,25.0,25.0,18.0,24.0,HAFEGGECCHDGGGHDGCDGDEAAEHGEFGBGGHGBEFEEBCHAEHCFHDFHDFGDGDBGDAFBFFBFHEECEDBEDHDBEDBFDBFABDEFCHAEFEDHCDAFDCBDABDABFCBCDHEHFCAFCDBEDACDEHFFHFFEEEBDEHEBHBHHAHGBHDHGDBCABDADDFDAFGAF,False +812,13.0,7.0,5.0,13.0,10.0,18.0,4.0,11.0,FGEADHABHAEHFCHFAAEEAFEAFDAFABEGGHFFBBDBHCAHADHBFADCCHEDFGDFDDBDFEDFEHFDAFDFFEHFC,True +813,30.0,25.0,17.0,27.0,18.0,16.0,23.0,20.0,DGAGBDGFDGFAAACAGCEFHDAHDBHCBACFACFGHFEFBHHBDHBAEDAHCEFDGCAADABGABDEGDGCAGCEGBABEABDFGDFADFABGBHGAFGDDGHDAHDCDDEDGECHEHGFBBFHBEBBCBDGGHHCEHBEGBCGADAADBHEFDEFHEAADCCHEDECAAABABB,False +814,24.0,14.0,14.0,18.0,16.0,18.0,16.0,21.0,ACBABDDGDGCCHAEHAEFDEFGHFGHFGDCGEBFDBGGBFACACFAGEHGBAFBAEAAEFHEGHCAEAADDHCABFHHEDHDHACHAGHACHGCHCHDDHABAAFADDBBABFHCFGCFEDDEDDHFEHFEGFBGEAFEB,False +815,13.0,9.0,13.0,16.0,13.0,6.0,10.0,11.0,EBHEDEGACDDCDGCDACHFCECCHGBHGBHCBEDAEDHFAFEAHEADAAEADDFFEGBDGEHHABGGHGCCADCDDCDHCABEFBEDBAG,False +816,3.0,7.0,5.0,5.0,0.0,0.0,5.0,2.0,DDCDBADBHGBGBBGCCCACBAGBDGH,True +817,5.0,5.0,2.0,2.0,3.0,8.0,12.0,6.0,HCHGCGFHGAEAFGHFGHFGFEADEHDFBGGGGGGFBFABABB,True +818,1.0,11.0,9.0,4.0,7.0,7.0,8.0,7.0,GABGHBHDBHCBECBFGHFGBCBBFEBECCEFCDFCGHCFCDHEFGEGBEBHDG,False +819,2.0,2.0,5.0,5.0,0.0,2.0,1.0,5.0,CDACFHHFAHDBHCCDCHDBGD,True +820,11.0,24.0,12.0,20.0,8.0,10.0,7.0,16.0,DDBDDECFEFFEBFBBABHAFHGGCCADEHHABDDDDCGHFABFABFHDCBDBGDBCDBFEHHCBHADHADBADCHDCBDHBEHBHABCGBEGBCDCGHBDAEFBBBH,False +821,9.0,5.0,8.0,7.0,7.0,2.0,8.0,6.0,DCDGGAGGCHGCHBBEEAGEGEFCEDADAADAAFCABCEHCBHBEHCAHDDG,False +822,4.0,6.0,4.0,6.0,8.0,10.0,6.0,8.0,DGEHGBHAFDDFEAHBFCBFCDFADFCDHGEHGBFCBHEHGEBEEHEFGFFA,False +823,11.0,21.0,15.0,29.0,14.0,28.0,25.0,13.0,GCBACBGFGGFADDGDDHCCBEGFEGBDBBDFFEFECFBCFBFFGFFGDDHHDFHEFDEDDAFAGFDEBEBBDDHDEHGCHFCGCAGCFGDGGHCFBBFBDCGGEGDEBAHFDEADEADFCDGABFDDFGDCGBFADABDGBHGHGFHFDHFEBCB,False +824,9.0,9.0,18.0,17.0,22.0,11.0,12.0,16.0,HDHHDBHCFHEEAEBDEDAEDBEDBHHAFFDDFCHGCHECDDCEEEFEDGADGCDCCHCAHCAHCEHGECGEGGHFDCCEECACBGCEGFGDEBAFFAGCGBEEEFDEFDBHBH,False +825,13.0,14.0,23.0,11.0,13.0,29.0,17.0,16.0,CFBCFDDFBDFBHFHGFAGEAFFBHFCCFCFACFACFDCAEBHFGGBAGDEEHBGFAGFHEDHGFEBFHHFGFDCFCBHEEGGCFGEFBCADHHDBFDBHDHACHCCGCEGAGGFFACCAECFHCGBCEFCEFCAB,False +826,5.0,8.0,5.0,6.0,10.0,4.0,3.0,7.0,DDEDAGAAGAHCDDBBHBGEEFHECEFHEBHEFHECEECBBCHBDFBA,False +827,20.0,17.0,26.0,28.0,18.0,27.0,26.0,26.0,ECFEGFEHFHHFABFABFEHABHAGDBHDBHDBGDGCDGHABHAFCEHDBHGCDCEFEEADECDAFBGFEGFBAAGDGDDEEDHDABDABFAGFDGDDADCBDAHGHHGHHFFFFFGCDEDGGCBCFEDGCCGCCDCEFFHHAHDBHAFCCFDGBCCHACHDEGGEGCCDCCHCBGFAAFEGFGCHHF,False +828,10.0,8.0,14.0,9.0,25.0,17.0,21.0,17.0,ECHGCHBCGEFDEFDECDEGBECBHBHHFFGGFGGHDGHACCAHHBDCFGAFGAGEEHEAHECEEHEEBEEGDECFEBFECFHFFGGGAEGHEGFCFBAGAHEEGDAAHFHCFGEEDFGDC,False +829,3.0,3.0,1.0,2.0,3.0,6.0,4.0,4.0,DHEHHDFHGGBAGAFEACEGFBFFBF,False +830,13.0,14.0,5.0,14.0,12.0,16.0,14.0,22.0,GDABFFCGFEHEGFFBHCBHEDHFGFBBFEDEHDHHGFHAEHAEHCEHABHADGEDGAFGHBCHAGHADHEFHFFGFGBAABAABDGBDCHDGBEAFHHDDBDHBFHDEG,False +831,30.0,21.0,25.0,25.0,16.0,20.0,17.0,32.0,ABDAGCAGBEEEEFEEFGBFGACGBHGBHCAACAACGCHGHADHACEECHDHACHFEGEAGDAHDAHDGBBHBFHGCHEHHAFGFFDDBGHHDHDEHABBACBHCADFDDHBDHBDCDCBDAHFFHDDBFHAGCDBFFEECCECCGHAHCAHBEHDACDAHDFCDAHDBBFFBAFCFFCAHAAGAC,False +832,25.0,27.0,23.0,20.0,26.0,20.0,20.0,27.0,AADBAGBCFACEEGDFBFFBFHCGDBHEFHCFBFBEEBHCCHCHBEBGABDAHDFHDHHFEHGECGFCBHDFHABBDDBDFHDGCGCCGCDGCHBHEEDEHDHBDEEHEGHBBHFBHFBGCEGEDAEGAECCEAAEACBAHDEBAEBFGACGAFAHDABAHDGCDEAHEAFECFGAACBACHAGBFGE,False +833,25.0,13.0,14.0,24.0,17.0,12.0,19.0,18.0,AEBDEBFCFGAEEHEAHBAHDCFDHFBFAGFAGAEGCCDCAAGAHEHHGAHEACFDEGDCFBAGGABGADGCDGFEBFEAAAGAAECBGDFCDBEDHEBCDDHDDHDGHDHHGCHGEBGHCAHDEEDCDDBADAAGABHDDF,False +834,15.0,10.0,18.0,19.0,15.0,14.0,14.0,17.0,GFDGHHGDHFHCFDBEBGADGACECCHHCHFAHCEHCHHDEHAEBADDGDBGDEEDECDFCAFEEFEDDHDCGAHBAGBDEADGHEFDFABCEBFGBCABCFGCFACGDHDEHACACCAFGF,False +835,20.0,10.0,18.0,14.0,16.0,28.0,23.0,12.0,CBFFGFCHEDBFHGFEGFEGFEDCEDAEHAGGGGFGGCCCDGCFGCFHAFBAFBDFCFFHAAGCEGAEGHEGDFAFFCDFADECHEAHGFGEHGEBDDBABFABABECHCFGCDDFFGFAACAAEDHGGHECDBAFCAFAF,False +836,30.0,20.0,19.0,16.0,19.0,13.0,25.0,21.0,GEHGEGBFGFCGFAGHHGFGGFDHAAHECBAGGAGHCGBCABFHBECAAHAFCEBCEACEADDADCGHBDHGFEDBCAEGAHGHCGHCGEBBHGDHEDHDFBEBBFADEAHEACBAEGFDCAABAABAABGAEACHBHDGADHAEBACHDGDAGCEDCEFCBF,False +837,11.0,6.0,11.0,21.0,12.0,11.0,14.0,20.0,CCGFFHDFDCHECHGCEGCGGDDGABGAEHDEHGGHGHDDHDABDHBHFFGEFHDAEDFEDFGFAHHHCFHAEDGEHCHFDADDGDBADAHDAHDCDCCBEHBEAE,False +838,2.0,11.0,5.0,5.0,5.0,11.0,2.0,7.0,HHAFDBFCBFHBFCBHCFEBHEBCFBFEBEHBDDDEDCABBFFGFFGH,True +839,10.0,18.0,12.0,15.0,22.0,22.0,14.0,20.0,GHGGHDGHEHCFHBHHGHGFDFFBHGBDFBCFBFEBAHAACAEBAFCEFHEABGAHCBCCADAEHFDHFEFFEHFEHCECGHFEBFGCFDBBDBDDCEDEEDEEFBFFGDBBEBGEAEHFDCEGEEDHGDHBF,False +840,6.0,5.0,3.0,4.0,8.0,4.0,5.0,6.0,HFAHFAGABEEHFEBBEABCGBGAFGAECDEDHEHHEDGDC,False +841,22.0,25.0,12.0,20.0,30.0,18.0,24.0,19.0,CFDABGGBGGDGGBGDBGDFEHGEHAEDEEDEEAEGABBABHABFEGAAAAFAAGHFEEEAHFBBFBDHEHAGHADHFDHEDHEDCFAHFEHGEHEEHCBBDBBGBGEBCEBFEHDCFAGFECABGDHEFFEBEACCHEGEGCAFDACECDGDBHEFCGFGGBBBDBDDA,False +842,26.0,32.0,18.0,28.0,33.0,16.0,26.0,21.0,BDFEACGAHGEHBEFBDDCDDEBGFBAHCGBBGCEDEHBAFGGFBDFDABCCBFCBHEBEAFGAEGFEGEDGAABBHBDCAAEAEEBEBGDGGDGHDHHCACBEGGDHADHGEFEBDEBDHBDHBEHBHDDCDFCDCGAGGEGGEGFECAEABEAHDAHCFFCDHAAHAACAABFEEEBDEBDGBDBCEEHDBGEBEAHF,False +843,17.0,15.0,21.0,18.0,10.0,19.0,19.0,11.0,GCGCCGCDBAAFCFFCGCCFCBGCBHBGADGFEEEBEDCFDCFBEFAEGDDDDDAGACDEFDBFGCFGEFDDHCGGGGGAFACHACHACGADGHHCHBFAAFDFFDABBEBFHBHEBHCAHBADGABFDC,False +844,28.0,20.0,25.0,32.0,29.0,10.0,34.0,16.0,GCBGCEAHBHHGHCGADBHDGAFGCFEEFDEAABAAFACGACHAGEEEEEBDBDDGEAEBGCFGAFGCGACGAGFEDAGDAGDBGDFEBECDGBDHBDBBDAEHADAAHGDCGDEBAHBEDCGBEGHEDHCCEDDEDCEGCDHDACAABADGEEFCEFGGAHGCCGCBECECBDHDCADAGDGGDGGDECHEBD,False +845,9.0,18.0,18.0,15.0,16.0,16.0,18.0,30.0,FHHFCHBCEBFEBFBHCGHEGFEDEHABHBHCEHCGGEGGCGGDGHDFHBFHAGACEDBBBBBFHEDHAHHBHEGHEHFDHEBHDDHCDCDHCACADBHDAAEGHFCCECCFHHBHGDHCDHFDGFBGFGGECAFBFCEG,False +846,25.0,21.0,20.0,25.0,14.0,20.0,19.0,27.0,DHHAHHGHBEBFFBHACHBCHFEAFHAGEAGEDFFDHACGDCGEBDDBGEAFAAGAAHAAFCFDCAEFBEGHGDCFAEDABDABHGBHGFHFDGDDGDDHFBABCADDACHBCHCGECACDBCGBCFHEHCCBBHHHFHFBHECEDHDAHDFDDFBBFDBEGACGACGADG,False +847,19.0,22.0,26.0,32.0,24.0,20.0,17.0,30.0,FFFFFBEBBCDDHBEHDHHFHCDHCDBCDAFBHDGHDECDEDGEDCBFEFEHAHHAEDBDGHDCHECDEFHHADHCHBCHCDDCHBBHBEECCDFEDFDBGDBDFBEBAEFAHAGFECCACDHCEHCGGCGGCAGABCAGAGCDBADGEDFEGAEGAEHACHCBHABDBEDEDDHADGGFBFFHEFHCAH,False +848,9.0,6.0,11.0,10.0,14.0,15.0,7.0,8.0,EBECBHGDFECFDGFDHFDCEAAGDEFDEFDFFHCAHGBDDHDHFEGEGBAFCEFCAFCACCACBAFHFEHEEFEGAEBC,False +849,4.0,12.0,3.0,4.0,4.0,6.0,9.0,4.0,BADBFBBDBCDAGGEGGAHFBHFECBBGGCGGBBGBDFFHFEHAEB,True +850,11.0,16.0,15.0,13.0,9.0,18.0,8.0,14.0,AHEFHEDHAHCBEFAEABEBBDHGAGCECCECCEDGADFFBFFBFFACACDFCDECHHFDFFHFFGFBAHBCDBGDBGHHGHFBDBHDBCCFHDACABDGBCBF,False +851,14.0,6.0,9.0,8.0,8.0,11.0,8.0,4.0,CADAAFAFGGBDGBECHEGAEGCEGHEAFCGCCAFCAFDBEHBAAAFAFFECEDADGACFBDFHDFBD,False +852,13.0,17.0,14.0,11.0,14.0,23.0,28.0,19.0,AHFBHFEDBHCBHGDHDDBEFGAFBEDCEDCGGCAGCHGCHGCDCEEGFBBFHCGHAGDCFEGABFCBECBAFBAFHHGHEBCFAEGGEGAFBFGGGDGBDBFAEEBGAGHAFHCFHFFAGFHGFHFFHGGBGGHDGFE,False +853,17.0,14.0,15.0,18.0,12.0,25.0,14.0,18.0,FEEDCEDAEDABFABGHCGEGBAFBAFADFDDFBDFGDGEEAEHDGHCFHCHGBHFHFACAEBGHHGHAGAAFFDCCDHCGGCFDCFHCGECADCFDBFEBFBDGHDCHCHDAFFFHFBBEAFADFHBFHFAB,False +854,4.0,8.0,7.0,9.0,7.0,13.0,4.0,5.0,HAHBAEBCEFDHFGBFDDFDDFCGFBBCBFCFFCAFEDFBCGCDGEHEEDFDHFEBA,False +855,8.0,9.0,7.0,8.0,14.0,11.0,8.0,11.0,FCGGHEGHCAHEGDGCDHEBHEGEEFAEFCEAAFAHDEHFEHBGFBFFBFEAHEADCBBCBBCEGDDHFDFBHEAD,False +856,15.0,19.0,19.0,21.0,20.0,23.0,9.0,21.0,EHCABCEDCEDCHDBADEFFEAHGADFHBFEBFEHFEGCHGBBFBDFDCFHCFCGHCDHEHADFFEFHCGHCBABEEBEFBCDBCEHDACDBBDCBACBAEBDDCADFAEFEEHDGHDEEFBFFDHGHFGAFAHFCGFHBHDADAHC,False +857,8.0,14.0,12.0,26.0,12.0,12.0,24.0,18.0,DDGDGFHGDEEDEHGEDDCHGCAGDGBBHHAHDBHDBGACHCCHFCHGGHDGHDBFABCHGHGFDCEAGEADEGDADEGHBCFBGFGDCGBFDFFDCBDCGDGBEGBFGEHHEFHDFGDAEDBDDB,False +858,3.0,12.0,7.0,10.0,7.0,11.0,5.0,6.0,EHBFDFFCEGCEBFAFCCFECFHDGCEHAEFDBFDBAHBGHBGEBCDFDDFBDBDGBHBBD,False +859,15.0,8.0,5.0,5.0,11.0,6.0,8.0,9.0,AFHEGGEGBEDBACAADADGGHGFEGCEHCDAFECBBABHHEHAECFHBAHGABDEBAEFAEFAHAA,False +860,24.0,23.0,16.0,29.0,25.0,13.0,28.0,31.0,ABDBGHHDBEAACAHBDDDDHHGAHBDHDAHCGHCAEGFECFECGHAGBBDBDDBDGBDBAEBACDAHDBGDBCEBGEDDEBDBBABGGGGGEHAEGGGDFHDAHAHFAFDCHDCHEFBEAGECHFCHGGEGGAGFDHADEGHAFHBGHEFBCAGCAEBHEDHEDEEDFEGFHCEHDHHFCHEAGECHA,False +861,19.0,16.0,16.0,18.0,22.0,19.0,15.0,18.0,HBDHADGAFFFCFDCFDHFAEEDEEABBABHHEAEDAHDEHCGFEECHECEFGHFDHFEEGCBDFDGHDGHDCBDCAECAHBACGEFBFFAFBAFBEDHDAHBBDGEGCEGBGDFGAFGAHCHGFECAEGABAHBACBECECD,False +862,23.0,28.0,34.0,23.0,21.0,19.0,19.0,23.0,AADEFDECBCFBFEGCHHCBCAHCAEDAEDFGBAHBGBBGEDGEFBAFBABEABFAHFAHADGBHAAHAAHCFCAECBEHBACDDCDCHDHHDAHDAHCFBCDHCBBGDEDEHFBCCCCCDGEDEEBCBHCDEBEHBCGCDECGCCGBCGBCFAGGACBHBFCAGCFBDHBFHFECFGHEGCEFDDFGDG,False +863,11.0,5.0,11.0,10.0,13.0,17.0,9.0,9.0,HGFAGHEGFFAEFGCHCCHCFACEAFEAFBFFBEEDDDGGDFEBHDFEDFEFCEHCDAAFBAFHCFECHEDDABDAGCCGAHGEF,False +864,8.0,4.0,8.0,5.0,6.0,11.0,2.0,13.0,CGDDADAFHFEHACHFFHAFHAGABEFBHHCHFCFBEHCEHDEFDCFEFHCAHCAHB,True +865,6.0,7.0,13.0,8.0,5.0,5.0,10.0,8.0,EBBEADDABHGBFBHDAHDFCCCCCGDCGACEFCEGCGGCDHHBGHCGCGBFDDFEAHCAHG,False +866,13.0,18.0,13.0,24.0,13.0,21.0,16.0,22.0,CECHEHGAHDBHAACGDDGDDGBGFBACBAFGCFGEBHHBHBBFBBFGDFEBHDBAEEAGEHFEDGEDFFHFADDADFHCHEADCFDBEDCDDFFBFFHFGEFGHCDFBHADHFDHFHCGCAGDACEBDHBDGDHGCHBH,False +867,3.0,4.0,1.0,1.0,0.0,0.0,2.0,1.0,BGHBGBAABACD,True +868,12.0,15.0,8.0,11.0,24.0,11.0,16.0,16.0,GBGAFGAHEABDAHEEHEGHFBEGHCHHCBDFECAADDGHFHFGEAGEBCDGEDBEFEEFGDGGAHGDHEEHBEHGEAGECGEAHECHBBEFBHBBDBBDCBFEFEEFECAAD,False +869,14.0,6.0,19.0,11.0,20.0,15.0,11.0,18.0,AFHAEHAEHGFHACHADFFGGFEGFEGDEDBAFBDECHHGHCCDBCFECHCHFBEDEECHACDGFDCHCEHFHCFACEACEACBCGBGEADECEEGFEHFACEDHEDHAGHFCA,False +870,7.0,10.0,10.0,16.0,6.0,4.0,11.0,16.0,HCBDCBHCBACDCCDHFHAGHCCDECGEDGDAFHGHGBDDFADHGDHBDHBGHFHEAABGBDHEDHEHHEGDDGADGCBB,False +871,6.0,1.0,1.0,3.0,2.0,4.0,9.0,6.0,AHCGEDGAHEAHAFGAGGBHGAHGFGDFGFHD,True +872,3.0,5.0,3.0,3.0,6.0,1.0,1.0,2.0,BBBDCBEGHEFHDBADAECAECEE,True +873,2.0,1.0,1.0,2.0,5.0,1.0,2.0,3.0,HEGAEHAEBCFDEHDEG,True +874,7.0,21.0,14.0,14.0,9.0,12.0,13.0,10.0,FDBFBBDBADBHBAGDHHCGEFDEBGEGGFGBCGEADAGGADHBDFCDECGBCEDFHFGHFEAFGHEDCEDCBFCBCCBHBBHBBDCBFGBCBHDBCAFC,False +875,6.0,6.0,10.0,12.0,5.0,8.0,13.0,6.0,GCGGCGGHBFDDADDBDFBDGCFGAEGAFBBCBHHFDHADHAGCDGEDEFGGCECCHDCEACGDFF,False +876,19.0,14.0,14.0,17.0,5.0,8.0,26.0,9.0,ADBACAGCHGCFGHDADABGEDABDABAFGCFDCADGGGGGGGGGBGGBACCHHAAGAADAGDAGDCGDBFFBCFBEBCEBGBBHEGDDCCCBHHAFGDGADGDDAFCGHHE,True +877,11.0,23.0,26.0,15.0,25.0,13.0,27.0,20.0,DHHEHGFGGCEHCGDGEDHCDHBFEDFEAFHBDGFCBHCEECEECBHCACGACACHGBHGBGGECGBDHCFEEEHCGHCGHCEBEFBGABCDDEGGEGGEGFEDBEBBGBCGBHABGEDCABCFECAHHBBCBDCAGBDGBAGCAHFHEBCEGCDFFDEF,False +878,10.0,21.0,12.0,20.0,16.0,27.0,18.0,16.0,EGCEHFAFAEBBGACGEEDEBDEFDBBDCBDEDFFAFGHBDFBHBGHBEBEGDDGDGBHGBHBFFGDFCFGCFAEGHEDEEDEAFFFFFFCHGGDGAFGAFHDBHEBCAGHBFDFFBHFCHFCHCCDCFDHBDGBDBHFA,False +879,13.0,7.0,15.0,3.0,11.0,11.0,9.0,9.0,CHBCFBFGEFEHCCAFAAFCEECBBHEEGEFBEABAADGAGGFGFCGACEHCHCFECADCACCACFAHFHDGHGAHEB,False +880,18.0,17.0,11.0,7.0,12.0,11.0,12.0,19.0,GACGHHGCCDAEAEBAFGHFGHEHABHBDHGCHGCHBABEEBECDDBABBHFHGCBGCBFAAGDAGHHHCAFCABAABAABHAFDAFBGDCHFEBEEHEFHEFBFHE,False +881,15.0,14.0,12.0,18.0,16.0,16.0,10.0,24.0,EFDEFDHBEHAEFFBHEBGEFABHGEHDFHAFEBCDGDAFDAHAACDACDGCEHDBBBBHDHEAEFAHGDFDABHABHAEHFEHFHHFHBFHAFHAEDCGBGGDDHDEHCBCCHCEFDGGHCDCC,False +882,1.0,3.0,4.0,5.0,7.0,5.0,2.0,5.0,HDHBCGDFACFECFEFBDFDGHEEHEBHEDCE,True +883,10.0,19.0,13.0,15.0,16.0,14.0,11.0,10.0,FDEBDAHCBEFHFHGGHGEBGCHCEECDACEFBAFHCBCEBAGBFGCEGBEHDDHBDHCDAFDEBDFBDEADBADBAECAGDABCGDCFBGFBDFBEFBFGBEHEECF,False +884,4.0,20.0,14.0,12.0,17.0,18.0,12.0,16.0,DHCFHCBHGFHFEDFEDBCDBFHHGCDFADCGHFBDCBDHAGEFBEHBEDCEGCABFHBHCCCCBHCGGFGFFBFBBEGFEBBBCGEGHHHFDAFDEFBEFHEGDEBEEBEEB,False +885,4.0,5.0,7.0,5.0,3.0,5.0,11.0,4.0,GBBEAFCABHGBGEFGDDCBDCFGCAGCDGCGHEGHFCHFGAGD,False +886,4.0,2.0,5.0,6.0,4.0,7.0,8.0,6.0,DEGFEGHBGCGHBGHDFAFFAFDADGCHECDECFFCHADHGG,False +887,7.0,10.0,2.0,12.0,7.0,8.0,10.0,7.0,HDGHAEDCDDBGDBAEBGCBDAEGFGFBGFBDDBFHBEHADFGDFHHFHEDGADGAFEAGEBB,False +888,22.0,21.0,26.0,15.0,24.0,25.0,19.0,23.0,HFHEFEAADAGDBCEBGEBEFHEGHAGEDGADFEBFCBFBBFCEHADFEHGHHFDFCHFCHDBGDHAAHFCFAEBAEGCEGCFFAHHGHHFHHCHCBABGDHHDFABGCFACFECDEAGEAGFBCFGCEGCBBBEBAGHGGCBAFACFDCDDCFCAHCACCBEEBEEBEADCCEF,False +889,14.0,18.0,14.0,7.0,16.0,10.0,10.0,16.0,FHAHHEDDECCCHBCBBFBFCBACDAGHAGHBFHBCHBEGEEGBBGBBGEAEAHHBEFFEAFEDHECEEGABGBDGCABEABAFCHCAACGBHHAHCDHFECFED,False +890,18.0,20.0,25.0,21.0,23.0,27.0,22.0,23.0,ECFEGEBFABFABCDBFHBHABHBDHGFGBFGECGCFHADHDEACCBHFEGFACHECHFBACCCBEBBDFDAEAABDAECCCFCFFCFFCEGCHBEGDEDFBDEGHFCHFCFDCFEGGEGDDGHDHHCGHFDFBDHGHHAAHAEHFGAFGAEADEFCEFBEGBGGHDAEDCEHCDGBDG,False +891,21.0,17.0,16.0,20.0,21.0,17.0,22.0,30.0,GEDGFABBHBBHFAGAEEAEAAECAEHHHBDDCABHGGHGCBAAFABFBFCGEBFEGEHHEHHDDHFGEEHDGHCAHFADBADCCGACHDGHAGHAFHAFBECBEDHGCHGAHGBDCEDCDBFDEGHGADGDHGFHCDGDFHBHHBHAECFECFEGFHFEDCED,False +892,2.0,4.0,1.0,8.0,1.0,2.0,5.0,5.0,HHHHBDABDGBDFFDCAHGGGBDGDDED,True +893,15.0,5.0,9.0,8.0,9.0,2.0,15.0,5.0,GGEGEEDAFGECACCAGFGEEDECDBAEGADGABAACCACCAHGAHADHGDGGHGBACBHBDEGAAGD,True +894,15.0,20.0,23.0,20.0,17.0,18.0,26.0,16.0,FGDFCFCCGBFEBEEDACGECGHCFFEDBBCHBFHBDAFHBGCFCCFAGHDGDGGBFEEGCEGAFGAEAFEDFEDBBDHBHGGGGCFDCEHBEHGCAAAAAGHCHHCHBGDDCDBGBBCABCABADBADBFDGGCCEDEEDGCGGDDGHCFHEFH,False +895,17.0,14.0,14.0,9.0,18.0,14.0,9.0,18.0,BGCDCCFADADBGDGCAEEAGEBEFBHHAEFFEHFEBEBCGCEBCEDAGGAHEABEABDAFDHBHHAAHBAHAHBAHCEHCAHFHBEHFCFFCEFCEHCHHCAEDFEDBGFGF,False +896,10.0,10.0,7.0,13.0,14.0,14.0,10.0,8.0,HCBCDHHGEAFHFCDGHEBDEAFBCFEDFADEADEADABBHCAEDGDDGFDAFHHFDGFGGFABFBCDBCEAGBBGEFGEFEEFEE,False +897,1.0,6.0,2.0,6.0,4.0,12.0,5.0,5.0,FBDGCGGDFEBFEFFEGFBGFHFFDFHBAHFEDFCHBBHDD,True +898,8.0,2.0,6.0,2.0,1.0,5.0,2.0,3.0,CFFCHDCFEHHAADAACCABAACGAFGBF,True +899,13.0,11.0,11.0,13.0,12.0,11.0,12.0,9.0,FCCGCABEBEEFCBGCDGCAECEEHAEGDCFFHDBCABDABEAFCBHABHADHGDFGDFBDFEDGHBGDGDAGAFECHEGDEGHFAHDABAF,False +900,11.0,8.0,16.0,15.0,15.0,12.0,12.0,10.0,HFDECDECFHCHGDEDEEBGHDAHDABCCDDFGDCGBCACCDGGFCGFEHEAGEAGEAFCCHCCAFEAFADEADHGDBFBBFBBFGCEAHFCDEEDHEG,False +901,6.0,5.0,13.0,12.0,14.0,4.0,0.0,2.0,DEEDEFCACAAEHEECDECAHCBDDECCBCFFDBFBCDECEECEDCADEDDEDACB,True +902,5.0,2.0,3.0,0.0,2.0,4.0,3.0,0.0,CFECFBAGAACAAGFFGBE,True +903,1.0,3.0,5.0,2.0,2.0,3.0,3.0,5.0,HEAGEFBCDBCBCFHCFHCDHGHG,False +904,8.0,10.0,8.0,10.0,10.0,10.0,8.0,8.0,HAEHAEDAEDGHFGFFAFFBFFGDABDECDEGGEGHBHBBCCFEDGECBCCBACHDCAFBDDEEDAHGBHBF,False +905,19.0,35.0,22.0,16.0,17.0,18.0,22.0,17.0,BEDEDGGBEBBDBGHBCBBCBHCAEAHBAGBCBHDBHDCHGCBGDAGDCCAGDGCDFCBFCBDBBDHAAEAGEGGEGBAFBHFGFGBFHEACECCGHCFFEFBCFBAFAABBBBBHDBEFBHFAGBEFCDGCFCDEEHBBFBDCGDEGFHGACAACAHHFGHEABE,False +906,6.0,6.0,11.0,1.0,5.0,2.0,8.0,3.0,GGECBACGCCGHCBFEGGAACAACDACBBCHCEFCEHBEGBG,True +907,10.0,11.0,15.0,22.0,12.0,15.0,10.0,11.0,CBDCFAHHHHCHDBDDBEDHCAECDFFDACDGBDABCFBCFBGDCFFCFEEHGGHGADGDFAFACGDCADFBCFGDFEDFDDADGAHEBHFCHDCDEEBEEDEGBE,False +908,4.0,0.0,2.0,5.0,3.0,0.0,2.0,3.0,GHACDADAEDAEDEGDHHC,True +909,1.0,4.0,0.0,5.0,2.0,3.0,1.0,1.0,FDHBDABFEBDDBDEGF,True +910,9.0,19.0,26.0,20.0,13.0,12.0,16.0,22.0,BHDCHGCHBCHDCBGCAEDFEBFBHDBHDGHEGECGCFDCHHGHHBHGFGCCBCCDCHAADFFDFFHEDCFBCEHCEHCDDFAGECGDBDBGFGEECBHCBACBACHCDEFDAHBCHCEGBGGCDDHDEHBAGBADB,False +911,5.0,1.0,2.0,3.0,2.0,3.0,0.0,2.0,HAHAADAFBAFEFCEDCD,True +912,26.0,20.0,25.0,15.0,11.0,21.0,19.0,28.0,BGFDDHABFAGCACFBCDBGDCCAAAHAAHFCHCEGGFFHHFBCABCGGGGBHEAHCAHBAHAHHACHFDHDAHABHCBFEBFADFGDCGFFHCGBCFBDFEDCHBBHBCGECGEHGFHAEHACHADAABHFDECEGBAGDHFDHCCFGAEGAECABFFBHCCHD,False +913,7.0,7.0,5.0,3.0,0.0,6.0,1.0,6.0,CDFCAFHACADCBBHBFHBFHFDGCABBABFHHAA,True +914,20.0,24.0,25.0,24.0,19.0,23.0,23.0,19.0,BDHFDGCHCAHFAHFGGCHBCHDFEDAEHCBFEBCGHCGFEACCAHDFGDFDBFBEFBEBGDBGDBCDECBFHEEEBCGBDDFDECHEHBFCAFADGADAHFCFFGFAGFEGEHGADDHDCHDBDDGEDBHABGGBEGBAHBHBDCFDCACCGEAACCACGAEGBEFBAFCCFGBAG,False +915,6.0,10.0,1.0,9.0,16.0,12.0,5.0,11.0,BFGFHGADDEEEEBEEHEHHEHFEBEGHFDHFBHFBDFDFFEBGDHCEBEEBEAGDADHAFAAFHBBEDF,True +916,19.0,25.0,17.0,15.0,26.0,25.0,27.0,16.0,EBBHBCGEEAEBCECGECHHCGDCECGECDBCDBAGCHGBFDBDBCEBFAAGAAHBGDFGAEGAEHEEHECGFFAFBEEAEEABEHBGHBFHDGCCFEFFCFFGFDHBAHAGFDGFDGHGGEDGEBGHGFFECBAFBHGEFBFGDFHDAADGGBAGBFCBFDEFAFBABE,False +917,1.0,1.0,0.0,2.0,5.0,1.0,1.0,0.0,DABDEEEEGFE,True +918,3.0,4.0,4.0,5.0,6.0,2.0,1.0,2.0,FCHDCBDCDEADEBDEBFBGACAEHEE,True +919,29.0,30.0,27.0,23.0,18.0,16.0,15.0,25.0,CECCDDBFGBEHCFACFCCAAAAABGDBDCBDABFBCEACABCGBHGDCGFBGHCDHCEHCBAFBFGHFHHDHFEHFEHCDBDDACBACGACGACFEDEBDHBDHAAEEGFBHHBHDAHBGBCGDAAHAFEBCCBDBEEAHEHFGHAHAABBABDHBDADDAECGBCEDCDCGEHAEHABBFF,False +920,6.0,8.0,6.0,2.0,10.0,1.0,2.0,2.0,ABABBFGBDGEECCEACECHEHBEABDBEEEACEACB,True +921,9.0,6.0,2.0,9.0,10.0,5.0,13.0,15.0,EBEDHGAHGFHGFBDEDDGCDGDHFAEABEGEGAHGAFEAGHAHHEHDEHDABDBGEGGBGHHACHFHH,True +922,0.0,4.0,4.0,4.0,5.0,3.0,8.0,5.0,BFCBHEBHDBCDFGGEGFEGEHGHCDHGDGGEC,False +923,9.0,18.0,18.0,28.0,20.0,33.0,20.0,19.0,FCFHEFDEBCBBCFACFDCDCAFCAHBDHBFGFHAFEAFEHGCHGDHCDHCFCGDCHBEGFFGDFGBHGDFGDFGFAHDBGGHHABEDFFDFFDFFEBFHDCEDFEFHEHHDGACFFGHBBHBADDDDCDEGDGGCEFCDBEBGEDEEBCEFGFFBEDGEDBFDE,False +924,2.0,5.0,0.0,7.0,6.0,1.0,0.0,3.0,EEDEEHEBAEBDDDADBHDFHBBD,True +925,12.0,20.0,17.0,18.0,18.0,15.0,13.0,21.0,GHHFHBACCFFHHFHHABHGDHFDEBABDDBCAEHABDEDCGDGDDGCDFFDHEBAEBAEBDCBGCEGBEHBFCEFDBGBFGBHBHHFFEEGECGECGECBHGBHDCHDAFDCFDEAHAHEAHACCEEFBBDCC,False +926,4.0,3.0,0.0,1.0,0.0,3.0,0.0,2.0,FHBFBBAAHAFDA,True +927,18.0,22.0,21.0,28.0,13.0,24.0,11.0,19.0,CBHHDCBAGFEDFBGBCGDCEFHFGHFGBFDDDDCDDCFHGFBDEBAFBEDACDAFEGFEDFCHEDADFBEFBABDGCCACBACHDCFDFAACCACBHFBHFBHADDADHACBBCDHCFFBFAEAACDBCHHFHGFHGHBGHBDEDDEDFEAHDBE,False +928,1.0,4.0,0.0,2.0,0.0,5.0,1.0,1.0,HBBFFDFFGFBADB,True +929,3.0,12.0,7.0,6.0,3.0,6.0,4.0,12.0,DHGHFACCACBAFHGDEGDCCBBFEBDEBHHCHHBHBBHBFHFCBFHGDBBDH,True +930,4.0,2.0,2.0,0.0,0.0,4.0,2.0,2.0,HCAACAFFGBFGBHAF,True +931,5.0,1.0,3.0,1.0,0.0,1.0,1.0,3.0,FGAADCACHACHAHB,True +932,6.0,4.0,3.0,4.0,3.0,1.0,3.0,2.0,DGCABBECFGCBGAADHAEHAEDABD,False +933,9.0,5.0,1.0,9.0,8.0,8.0,7.0,8.0,EFBCBAHBDFADADEAFFGGDEHDEHDHAAEABBFEDHEDHGFHGFEGFGGADHA,False +934,4.0,7.0,1.0,3.0,1.0,1.0,4.0,5.0,AEBGGBGBHABDFGDBADBHHCHHBA,True +935,14.0,14.0,13.0,12.0,23.0,12.0,15.0,6.0,EDAGFAGECGAGGACEACGGEHGEHCEBCFBEGECGEDEECFCBFBAFADBBDFBGCEEBEEDCDDFHFHEFDBCEGABGAFDAFDABDAEEEHBEDBEFCEAAGBGHC,False +936,16.0,21.0,7.0,13.0,13.0,15.0,22.0,19.0,GFBGHEGBBAABABEAHHADCEHFAHFACEGBHHBEFGAGEAHADDGDFGDFDAGHCGFFGBFAFEGFHGAHADGBDHCDHEHEGDEGDCGBHGBCGBFEAHCGHEBDBBEBBFBHFBHFBDAGGB,False +937,24.0,12.0,20.0,15.0,16.0,11.0,15.0,24.0,HAECEECEEBBAGGADHAHCGHDDAGBFGAHEHCAABGAHGAFGADHEDGFDHADBBCABGABDDCCDBHBEEBEEHAHHAGHAHHDHCFCAHAACCDCGHCHFCHFCHFADGAHFAFFCCFEDEEBGECCACEHDG,False +938,3.0,5.0,0.0,6.0,7.0,6.0,5.0,5.0,DGBFHAFEFDHBDHBDGGGEEHBEHBFDEGAEFAEFD,False +939,22.0,26.0,26.0,14.0,18.0,22.0,25.0,26.0,ACFACFGFBAFBGBHHBDHBGGEAHFAHFAFEHGECCECCFAEGABGABEAHGBEGFHCHBBDBCHFDEFHEABEFCEBHEBHDBADACDEFBCHDGBBCCBCHBEHFCGFCGCEGCHHCHGAFCADDBHDGFFHBAGCACABCGDGGBFHDCBFGBFEEFHEHAGHGGHCCDAGDAGA,False +940,8.0,10.0,2.0,5.0,4.0,6.0,1.0,9.0,BGDEHABAADAFBAFHHFHHFHBAHDCEABDBBHEDHEBBFBAFC,True +941,29.0,18.0,34.0,25.0,27.0,21.0,24.0,19.0,DEDAEGFBGFBGCBFCHECFEFAGBABDCBEHHEHGADEHDFHFFCEAAEAFEAFCGGDGFEHEECGCCDCCECCDHFAHCACDGDBGFBCFADEABHABDABDHBGHGDADDADFCDAGFAGBBBECFCCECCEDGGDCDEGGAHHFEEAEACBDCDHCHEEAEACFAGDHFEGCAGHABDACHCCBCFGCAGEAC,False +942,22.0,23.0,26.0,28.0,25.0,25.0,28.0,22.0,HHDBFEGFEGCHBDEBHGCHGBDFHDBHFBHBGHCCECADHADGAGGCGCFDCFAFGDFAHGEDEEAEFDBCHBDHGHECFAFFAEFBGFHAFBGFAHFCCGHDBABEGBDBHFACAADAGDGECGEGGHCGFCFFEDFCCACEDDHDDEADECDGBBGBCHAEHEEFCBCCACGFBDFCDEADBGBEGBEGDEADEAD,False +943,10.0,5.0,3.0,10.0,7.0,4.0,2.0,3.0,DEBBHAGEABHDCADAADEEBCEFEDFADAADAGDABDCHDFFE,True +944,12.0,16.0,22.0,10.0,9.0,17.0,15.0,10.0,CBFHFFBDFBAGECGCCHCAHCFECDDFFDECBBCBBCBFCAFCFFEFABFGBEAHAGBGGCCGBADCADHDGBFGCEGCEGCGHFGCFEFBDHADACGABBHHDAHCGCE,False +945,14.0,9.0,10.0,9.0,9.0,9.0,8.0,11.0,GBHGAHFAHFBGGDDGCHFAAFACDEFDACDHCEEAHEAFCBHCBGFBAEBAEBAFCAHDAEGCHDEBAEFGDDCHBCH,False +946,25.0,17.0,25.0,19.0,25.0,14.0,14.0,31.0,ECDHCBBCFADECDCDBGDBECEEGEEGFAGHACFDHBEEBAFCCBAHBAGBEGBGFHHDHHAHHAHCFHFHAFHEFBGBAHBEDCEDCEHHAHEABAGGAEGACAFCADEEECDACHADECFCDDEHAEFAEFBBADEHHHHCDHCDHCEHGFHGHHBCCAADHAGCCD,False +947,9.0,11.0,9.0,14.0,8.0,14.0,11.0,13.0,AFGAFHBFDGCGGDFFBBDCBDHFDHCECGHDFHDCHGGHAEHCEAAEFDEFAAFBBDBFDBFDBHDBECBFCEGGHGAEDHGHHACDF,False +948,13.0,8.0,5.0,13.0,9.0,10.0,22.0,12.0,AGDCGDCEDGFHFEAAEAAHADGGGBGHFGHDGHDHCBHFGEGGHAEBEDFADEGGEGGAGFHCDABDHBGGAGGDDBDFBCFEFAHFABGH,False +949,21.0,23.0,21.0,26.0,19.0,22.0,10.0,18.0,AAAEAHBDFFHFCGEGBDFDFADHEDBEABCAGDDBHEHFBHFBHBAEGABDDFDFECEECBCABADBEDFEBECCHBBABBEBBHBEDDHGHCGHCGDEGDGDDEDDHDCHDFDBFHHHCFACEAFAACHACFECFDCFCFFAAFDABCCBCDFCAFGE,False +950,20.0,25.0,18.0,22.0,18.0,18.0,14.0,12.0,GEDGBHAHGAHGCCDAADBDEADBDDBFFHFBHFBACBFCAFADDCHCGEFBEABFFGGDBGBBEFCEFBDHBDHDEEFEADEDDFDDFDCBDHEDEEBEBAECCEBGBHCBHCEGFBBCBACAGCAEFGCFGCFBAAAAGCBHAAD,False 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+970,16.0,13.0,19.0,11.0,15.0,16.0,18.0,14.0,FGHFHAFEAGGHFBHEBABAFBGFDFHEEGEDAEBBEBDECAFAACCBCDACFHCAHCFHGHHGCBCFGHGHHADGDDCDBCECDBGDGEDGEFCCGHAGECGECGAGAAEAFFCFFCEBCB,False +971,4.0,3.0,0.0,5.0,2.0,3.0,5.0,1.0,DAGAHGDGBDEFAEFABFGDGBD,True +972,7.0,2.0,1.0,3.0,2.0,2.0,4.0,4.0,HCFDAHGAHABGADEHDEABGAFGA,True +973,2.0,6.0,7.0,4.0,4.0,5.0,7.0,4.0,FBGDEGHCGHAGBDGCEGCGCCFDCAHFBCFBHEBDFBE,False +974,17.0,19.0,14.0,32.0,17.0,26.0,26.0,16.0,EBDHBAEGEFDDBGDAGDHGFFBFDGGDAGAAEFAEFCEHCBCCAGCBDFBDFADHGDHEDAEBHFDHBDHBDGBGEBDCCDGCDFCEFBEGEFHAGHAGFAGFAHDDDDGDFGAEDEBDCHGGEEGDBCCHDGAFGHBGABDFFFCBFAEDDHCFFFFDFDHGGBF,False +975,8.0,18.0,16.0,11.0,10.0,10.0,17.0,15.0,EBFCBFCBCBBGFAFFCHFHHBDHBDBCEGDHGBGEBGDBDDHCDEBACCGHDGEFGAGCCGCCGAEHDCHECHGCDFFGGBGGBAHBFHADGAEHBBAEHCEHB,False +976,27.0,32.0,25.0,20.0,17.0,19.0,24.0,36.0,HCFABFDBGEFGFDCBDCAEBHEDADCADCGBCDACDBBHBBDAHAHHFFGEFHHBBHEFAEDHEHHBHHDAHCACCDDDAHCEECBBHBHHBGDBGBBGHCAHCFHFHGCHGAEGFFBBHCBHAAABACEGCGGCGACFACGHBDCBHCGGEHEBGAFFAEHHDFHDFEGFABDABGBBECBEBGAAFAACGHGHHGDH,False +977,21.0,23.0,33.0,29.0,26.0,21.0,26.0,19.0,BFCBCBEGFEGDEGFEBDACFGCDGADCDDCBBCGCDDCGCCGDDGBFBEEBAABAACFCCFHDDHDEBDEFCEBBGBEEDAEAHFCHFHHEBEEFFEFHEADEGEGGCGGADDFBCADDDCCGCCGCDGEDFADGDFGFFBCAAHAHEFHECAGFGDCEDCADBAHHHHEHHEFHBCCCCBBAABCAHHDGBEGCGG,False +978,7.0,8.0,10.0,5.0,10.0,5.0,5.0,1.0,DECDEBFCGFADFEBAECABABEGGECDFCGBEGCEHCBDCBCABCAEAFE,True +979,1.0,2.0,1.0,6.0,0.0,1.0,0.0,1.0,DCADFBDHDDBD,True +980,24.0,21.0,18.0,12.0,17.0,7.0,12.0,18.0,BBAHBHDDHBHFAHACBEBBCBAEEACHAHHEGBBGBCDCCAECAHCAGGAFFACFAHHEEAEHFGCACEACHFCHDDEDDEDDCBCCHEBHBAHEABBGBBADBGBBEAAGAADHEGEGGEGAFDACC,False +981,22.0,33.0,18.0,23.0,27.0,28.0,28.0,13.0,EAEDGBCFBAFBGFDAFAAGHAEBFHFFHFFGACDBDFCDFGDBEBBDHCFBEEGGDAGECGEFABFGBEDAEAHEGDDBEGCDABHBBGBDFBDHBGBBEBBHABAABDCEFGAFGAFBFCEFBGGHAGAFEDGEDCHFHBFGDHCFHCAGFDGCGECFECBECBECECABCAEFBEFEEGDBGDEGDBGD,False +982,22.0,20.0,15.0,16.0,27.0,17.0,27.0,21.0,GDFGHEGBEHCEBCHBEHBAHGCGGEGBBFDEADFFHADHEBHGDACDACDEBEEGEHBEGBEGHEBFAAFGFFGDFGDFABGHFHCEECHDGBDCBFFBGCBDDHDCGBCFAFHGGHEGACHECAEAAHCABAACAHEEDEADEFEGBGGEGAAGEBGFAHHAE,False +983,6.0,5.0,6.0,11.0,8.0,8.0,5.0,7.0,HBFHDFCEABBADECDEGDFCDFHBFEDECCFGHFAHGHHADEADFCDGDDGEBAE,False +984,9.0,13.0,13.0,13.0,32.0,25.0,15.0,18.0,EEAEEGEABEGHGFDADEEFAHHCBFGDCBBCHBCFDCFDCFDEFDEFCHFEFECFEHFHGFHGFHEBBCGECBDHHEEDEFCEGAADEFEHGEDFEHFEDFEGBHHFHGEEGEGAACFABFGFDGBEECEEFHBFHB,False +985,14.0,10.0,10.0,7.0,7.0,11.0,13.0,6.0,FAFAHGABAACAAGAFCDDCGCEFDBGBGACHECAECAEBAHDDFDBFDBFGBAGCHBEHBAGBECFFCEFGGGGGFH,False 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+991,18.0,26.0,30.0,28.0,39.0,25.0,17.0,17.0,ACBACBFFBACEFCFACFBDEBDEHCFHCDHEDAFCAFEAGEDGEGBEDEDGEFADCEDGECCCDFEDGEBEHBCFBCBDCBEFHDFAEECEFCEFBBFEBDEADEGEEAEEHEDFADGDHGBBACBGHFGHABBACCDCCECGECDHHHAEBBHBHGBCFFAEDDGFDEBHEBFEHCCFDGEDCDCHEBDEGDEGFFCA,False +992,19.0,14.0,13.0,21.0,20.0,19.0,18.0,15.0,GGFGDFGACGCFHCEHFECCAGBDFBDGADCDEBHFBHDAHEHCBHBEDBEDFADBHDFDEBDEGAAHAAEFAEFGEFGDFGEHAEDCDDHGDHDFADFEEAEBADBCHCHGCAGEGGFDEFEFGAAACACFHBGBBEF,False +993,25.0,22.0,19.0,27.0,20.0,17.0,20.0,31.0,GHDGEDGEGAEGFEHDBHDEFDEACEAGEHFDFFDFFHGEADEBHGHDDBDGBAEFCHCBHGBADBDFCHCABGDCDDHEDHDCBBAHACHGHHEAHBAHBCHAHBGHEDDEAHEDCGCCDAHAFHFBBABBHBFHBAGBCGBFFHFEGEEACCAGCABFAGGADHCDHCDHAHADDACEF,False +994,11.0,8.0,14.0,13.0,20.0,15.0,19.0,10.0,DHBGHCGCCAFEBGCDAEGAEGADDAGEEBEGBEGDFGHECFACFHEEBEECCEBDAGFBFEGHEGDABCEEGEAGDDHCAHCGHFGDDEFHEFHFFCFGCFGFAGFDCD,False +995,4.0,5.0,0.0,4.0,3.0,4.0,11.0,4.0,HGFEAHEADDGFGGFHGFBGBGGBGBBHAGGDDAE,True 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100644 --- a/README.md +++ b/README.md @@ -1,36 +1,10 @@ -# N-Back Sequence Generator with [Hidden] Markov Chain +# N-Back Sequence Generators -**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/src/main/scala/org/xcit/nback/markov/models/State.scala b/src/main/scala/org/xcit/nback/markov/models/State.scala deleted file mode 100644 index fbbd844..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/State.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * A Single state with a label in Markov chain - * @param label A simple string label, representing the state and node - */ -class State(val label: String) { - - /** - * Keep track of transitions from this state to other states. - */ - val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() -} diff --git a/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/src/main/scala/org/xcit/nback/markov/models/Transition.scala deleted file mode 100644 index bc20a9e..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/Transition.scala +++ /dev/null @@ -1,8 +0,0 @@ -package org.xcit.nback.markov.models - -/** - * A Single transition in Markov chain graph. It is stored in "from" node. - * @param to the ending node of the edge - * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). - */ -case class Transition(to: State, probability: Double = 0.0) diff --git a/src/test/scala/ThreeBackBenchmark.scala b/src/test/scala/ThreeBackBenchmark.scala deleted file mode 100644 index 0c7dad9..0000000 --- a/src/test/scala/ThreeBackBenchmark.scala +++ /dev/null @@ -1,7 +0,0 @@ - -/** - * TODO Benchmark 3-back simple sequence generator - */ -class ThreeBackBenchmark { - -} diff --git a/tests/benchmark_diagrams.py b/tests/benchmark_diagrams.py new file mode 100644 index 0000000..8fa448e --- /dev/null +++ b/tests/benchmark_diagrams.py @@ -0,0 +1,159 @@ +import pandas as pd +import numpy as np +from matplotlib import pyplot as plt + +import benchmarks.common as common + + +def tlratio(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2,ignore_index=True) + stats = [] + for trials in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == trials) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == trials) + targets2 = data[alg2].targets if alg2.shape[0] > 0 else np.nan + targets4 = data[alg4].targets if alg4.shape[0] > 0 else np.nan + lures2 = data[alg2].lures if alg2.shape[0] > 0 else np.nan + lures4 = data[alg4].lures if alg4.shape[0] > 0 else np.nan + stats.append([trials, (targets2/lures2).mean(), (targets4/lures4).mean()]) + stats = pd.DataFrame(stats, columns=['trials', 'tl2', 'tl4']) #.dropna(subset=['skewness']) + + plt.style.use('ggplot') + + plt.ylim(bottom=0, top=30) + plt.scatter(stats.trials, stats.tl2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl2[idx], 1)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.tl4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl4[idx], 2)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('T:L Ratio') + plt.ylabel('T:L Ratio') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_tlratio.png', bbox_inches='tight') + plt.show() + + +def time_per_trial(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for t in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == t) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == t) + time2 = data[alg2].time.mean() * 1000 if alg2.shape[0] > 0 else np.nan + time4 = data[alg4].time.mean() * 1000 if alg4.shape[0] > 0 else np.nan + stats.append([t, time2, time4]) + stats = pd.DataFrame(stats, columns=['trials', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.trials, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time2[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time4[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2v4_time_trials.png', bbox_inches='tight') + plt.show() + +def time_profiles(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 8): + alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + time2 = data[alg2].time.mean() * 1000 + time4 = data[alg4].time.mean() * 1000 + stats.append([ni, time2, time4]) + stats = pd.DataFrame(stats, columns=['n', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.n, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.time2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + plt.scatter(stats.n, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.time4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_time_n.png', bbox_inches='tight') + plt.show() + +def skewness(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 9): + all_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + skewed_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) & data.skewed + all_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + skewed_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) & data.skewed + num_of_sequences2 = data[all_alg2].shape[0] + skewed_sequences2 = data[skewed_alg2].shape[0] + num_of_sequences4 = data[all_alg4].shape[0] + skewed_sequences4 = data[skewed_alg4].shape[0] + skewness2 = skewed_sequences2 * 100.0 / num_of_sequences2 if (num_of_sequences2>0) else 0 + skewness4 = skewed_sequences4 * 100.0 / num_of_sequences4 if (num_of_sequences4>0) else 0 + stats.append([ni, skewness2, skewness4]) + stats = pd.DataFrame(stats, columns=['n', 'skewness2', 'skewness4']) #.dropna(subset=['skewness']) + + + plt.style.use('ggplot') + plt.scatter(stats.n, stats.skewness2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.skewness2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + + plt.scatter(stats.n, stats.skewness4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.skewness4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Skewness') + plt.ylabel('Skewed Blocks (%)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_skewness.png', bbox_inches='tight') + plt.show() + +if __name__ == "__main__": + tlratio() + skewness() + time_profiles() + time_per_trial() diff --git a/tests/benchmark_skewness.py b/tests/benchmark_skewness.py new file mode 100644 index 0000000..f468b4d --- /dev/null +++ b/tests/benchmark_skewness.py @@ -0,0 +1,97 @@ +import random +import heapq +import csv + +# Common parameters +alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'] +trials_range = (10, 40) +n = 3 +sample_size = 100 + + +def to_benchmark_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [str(ralph_skewed)] + +def benchmark_nb_gm_001(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_001') + + +def benchmark_nb_gm_002(filename): + import generators.nb_gm_002 as nb_gm_002 + + generator = nb_gm_002.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + # print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_002') + + +def benchmark_nb_gm_003(filename): + import generators.nb_gm_003 as nb_gm_003 + + generator = nb_gm_003.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + print(f"sequence {i}/{sample_size}: {trials} trials") + seq = generator.generate(trials) + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_003') + + +def show_skweness_diagram(filename, choices, title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + print(filename) + data = pd.read_csv(filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) #.dropna(subset=['skewness']) + #print(stats.trials) + #plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'{title}.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + benchmark_nb_gm_003('../benchmarks/nb_gm_003_2back.csv') diff --git a/tests/common.py b/tests/common.py new file mode 100644 index 0000000..e40c0df --- /dev/null +++ b/tests/common.py @@ -0,0 +1,27 @@ + + +# Common benchmark parameters +choices = alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F'] +trials_range = (10, 65) +n = 4 +sample_size = 100 + + +def count_targets_and_lures(seq, n): + mask = 'D'*n + for index in range(n, len(seq)): + if seq[index] == seq[index - n]: + mask += 'T' + elif seq[index] in seq[index - n - 1:index - n + 1]: + mask += 'L' + else: + mask += 'D' + return mask.count('T'), mask.count('L') + + +def skewness(seq, choices): + import heapq + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return ralph_skewed diff --git a/tests/nb_gm_001_bm.py b/tests/nb_gm_001_bm.py new file mode 100644 index 0000000..54f6cb3 --- /dev/null +++ b/tests/nb_gm_001_bm.py @@ -0,0 +1,75 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq) , str(ralph_skewed)] + + +def benchmark(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets / s.trials, axis=1) + plt.scatter(data.trials, data.targets_ratio, alpha=0.2) + plt.show() + +if __name__ == '__main__': + alg = 'nb_gm_001' + fn = f'results/{alg}_{n}back.csv' + benchmark(fn) + # skewness_diagram(fn, alg) + targets_ratio_diagram(fn, alg) diff --git a/tests/nb_gm_002_bm.py b/tests/nb_gm_002_bm.py new file mode 100644 index 0000000..c8af543 --- /dev/null +++ b/tests/nb_gm_002_bm.py @@ -0,0 +1,105 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq), str(ralph_skewed)] + + +def benchmark(filename): + from generators.nb_gm_002 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials, int(trials/3), 0, 0) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +import time +import numpy as np +import pandas as pd + +import benchmarks.common as common + +def profile(): + from generators.nb_gm_002 import SequenceGenerator + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, int(lures/2), int(lures/2)) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('benchmarks/results/nb_gm_002_profile.csv', sep=',', encoding='utf-8') + +if __name__ == '__main__': + alg = 'nb_gm_002' + fn = f'results/{alg}_{n}back.csv' + profile() diff --git a/tests/nb_gm_003_bm.py b/tests/nb_gm_003_bm.py new file mode 100644 index 0000000..fa6c19a --- /dev/null +++ b/tests/nb_gm_003_bm.py @@ -0,0 +1,114 @@ +import heapq +import csv +import random +import time + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq, time_per_block): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [time_per_block, ''.join(seq), str(ralph_skewed)] + + +def benchmark_skewness(filename): + from generators.nb_gm_003 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['time_per_block', 'seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + targets = trials / 3 + t = time.time() + seq = generator.generate(trials, targets) + t = time.time() - t + print(f"sequence {i}/{sample_size}: {trials} trials, took {t}s.") + writer.writerow(to_csv_row(i, seq, t)) + plot_skewness(fn, 'nb_gm_003') + + +def plot_skewness(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def plot_targets_ratio(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +def benchmark_targets_ratio(): + pass + +def benchmark_chunking(): + pass + + +def benchmark_n(): + pass + + +def plot_timing(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['time_per_trial'] = data.apply(lambda s: s.time_per_block / s.trials, axis=1) + plt.style.use('ggplot') + plt.title(f"{figure_title} - average time to generate a trial") + plt.ylabel('time (s)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.time_per_trial, alpha=0.5) + + # draw fitted curve + # import numpy as np + # p = np.poly1d(np.polyfit(data.trials, data.time_per_trial, 3)) + # plt.plot(data.trials, p(data.trials), color='red') + + plt.savefig(f'results/{figure_title}_timing.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + alg = 'nb_gm_003' + fn = f'results/{alg}_{n}back.csv' + benchmark_skewness(fn) diff --git a/tests/nb_gm_004_bm.py b/tests/nb_gm_004_bm.py new file mode 100644 index 0000000..b4ad4a8 --- /dev/null +++ b/tests/nb_gm_004_bm.py @@ -0,0 +1,26 @@ +import time +import numpy as np +import pandas as pd + +import tests.common as common +from generators.nb_gm_004 import SequenceGenerator + +def run(): + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, lures) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('tests/results/nb_gm_004_profile.csv', sep=',', encoding='utf-8') diff --git a/tests/results/2v4_time_trials.png b/tests/results/2v4_time_trials.png new file mode 100644 index 0000000..9be91b4 --- /dev/null +++ b/tests/results/2v4_time_trials.png Binary files differ diff --git a/tests/results/2vs4_skewness.png b/tests/results/2vs4_skewness.png new file mode 100644 index 0000000..a488e1f --- /dev/null +++ b/tests/results/2vs4_skewness.png Binary files differ diff --git a/tests/results/2vs4_time_n.png b/tests/results/2vs4_time_n.png new file mode 100644 index 0000000..d022ed0 --- /dev/null +++ b/tests/results/2vs4_time_n.png Binary files differ diff --git a/tests/results/2vs4_tlratio.png b/tests/results/2vs4_tlratio.png new file mode 100644 index 0000000..b76f296 --- /dev/null +++ b/tests/results/2vs4_tlratio.png Binary files differ diff --git a/tests/results/nb_gm_001_2back.csv b/tests/results/nb_gm_001_2back.csv new file mode 100644 index 0000000..f6ad25e --- /dev/null +++ b/tests/results/nb_gm_001_2back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,0.0,1.0,0.0,55.0,56.0,0.0,0.0,0.0,BEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True 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+364,0.0,0.0,0.0,1.0,0.0,31.0,0.0,31.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +365,0.0,0.0,0.0,24.0,0.0,23.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +366,0.0,15.0,0.0,0.0,16.0,0.0,0.0,0.0,EEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +367,22.0,0.0,0.0,0.0,0.0,0.0,1.0,22.0,GHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +368,0.0,25.0,0.0,0.0,0.0,0.0,25.0,0.0,BGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +369,0.0,0.0,0.0,100.0,1.0,0.0,0.0,0.0,EDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +370,0.0,17.0,0.0,17.0,1.0,0.0,0.0,0.0,EBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +371,0.0,1.0,49.0,0.0,49.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True 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+377,27.0,0.0,0.0,29.0,0.0,0.0,0.0,0.0,DDADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +378,81.0,0.0,0.0,81.0,0.0,0.0,0.0,1.0,HADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +379,1.0,0.0,9.0,0.0,8.0,0.0,0.0,0.0,ACECECECECECECECEC,True +380,1.0,0.0,0.0,32.0,33.0,0.0,0.0,0.0,AEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +381,5.0,0.0,5.0,0.0,1.0,0.0,0.0,0.0,ECACACACACA,True +382,0.0,0.0,0.0,96.0,0.0,0.0,98.0,0.0,GGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +383,0.0,86.0,0.0,0.0,0.0,85.0,0.0,0.0,BBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +384,0.0,0.0,28.0,0.0,1.0,0.0,0.0,28.0,ECHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +385,0.0,1.0,119.0,0.0,0.0,0.0,0.0,0.0,BCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +386,0.0,0.0,93.0,0.0,0.0,93.0,1.0,0.0,GCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCF,True +387,92.0,0.0,1.0,0.0,92.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +388,0.0,186.0,0.0,0.0,0.0,0.0,0.0,0.0,BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +389,1.0,74.0,0.0,0.0,0.0,0.0,0.0,0.0,ABBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +390,0.0,0.0,0.0,0.0,1.0,86.0,0.0,87.0,EHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +391,61.0,0.0,0.0,61.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +392,0.0,0.0,0.0,1.0,16.0,0.0,0.0,15.0,DEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +393,118.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +394,0.0,0.0,0.0,0.0,0.0,75.0,0.0,1.0,HFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +395,30.0,0.0,0.0,0.0,0.0,0.0,0.0,30.0,AHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +396,65.0,0.0,0.0,0.0,0.0,1.0,0.0,65.0,FAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +397,0.0,0.0,0.0,55.0,56.0,0.0,0.0,0.0,EEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +398,26.0,0.0,0.0,25.0,1.0,0.0,0.0,0.0,EADADADADADADADADADADADADADADADADADADADADADADADADADA,True +399,0.0,0.0,60.0,0.0,0.0,0.0,1.0,59.0,GCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +400,1.0,0.0,0.0,0.0,160.0,0.0,0.0,0.0,AEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +401,1.0,0.0,31.0,0.0,0.0,31.0,0.0,0.0,AFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +402,0.0,0.0,0.0,15.0,1.0,0.0,0.0,0.0,EDDDDDDDDDDDDDDD,True +403,0.0,0.0,0.0,54.0,55.0,0.0,0.0,1.0,HEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +404,0.0,0.0,0.0,27.0,0.0,27.0,0.0,1.0,HFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +405,0.0,0.0,0.0,1.0,0.0,15.0,0.0,15.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +406,0.0,95.0,0.0,94.0,0.0,1.0,0.0,0.0,FBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +407,0.0,0.0,15.0,14.0,0.0,0.0,0.0,0.0,CCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +408,78.0,78.0,0.0,0.0,0.0,0.0,1.0,0.0,GBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +409,0.0,0.0,72.0,1.0,0.0,0.0,72.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +410,55.0,0.0,1.0,0.0,0.0,0.0,55.0,0.0,CAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +411,0.0,59.0,0.0,0.0,0.0,60.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +412,61.0,0.0,0.0,61.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +413,0.0,1.0,0.0,75.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +414,0.0,53.0,0.0,0.0,0.0,0.0,52.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +415,0.0,0.0,16.0,0.0,1.0,0.0,0.0,15.0,ECHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +416,0.0,0.0,0.0,39.0,0.0,0.0,0.0,38.0,DHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +417,96.0,0.0,1.0,95.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +418,28.0,0.0,1.0,27.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +419,0.0,1.0,92.0,92.0,0.0,0.0,0.0,0.0,BCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +420,1.0,0.0,20.0,0.0,20.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECE,True +421,0.0,90.0,0.0,0.0,0.0,0.0,89.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +422,10.0,0.0,0.0,0.0,0.0,1.0,11.0,0.0,FGAGAGAGAGAGAGAGAGAGAG,True +423,0.0,0.0,0.0,74.0,73.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +424,0.0,0.0,127.0,0.0,0.0,0.0,1.0,0.0,GCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +425,1.0,9.0,0.0,0.0,0.0,9.0,0.0,0.0,AFBFBFBFBFBFBFBFBFB,True +426,0.0,0.0,84.0,0.0,0.0,0.0,0.0,84.0,HCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +427,33.0,0.0,0.0,34.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +428,1.0,30.0,0.0,30.0,0.0,0.0,0.0,0.0,ABDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +429,0.0,0.0,67.0,0.0,1.0,67.0,0.0,0.0,EFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +430,62.0,0.0,0.0,63.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +431,1.0,9.0,9.0,0.0,0.0,0.0,0.0,0.0,ABCBCBCBCBCBCBCBCBC,True +432,15.0,0.0,0.0,0.0,0.0,0.0,14.0,0.0,AAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +433,0.0,1.0,0.0,65.0,66.0,0.0,0.0,0.0,BEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +434,0.0,160.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +435,0.0,0.0,1.0,0.0,42.0,42.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +436,0.0,0.0,55.0,0.0,55.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +437,0.0,0.0,0.0,1.0,0.0,73.0,0.0,73.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +438,79.0,0.0,0.0,0.0,78.0,0.0,0.0,0.0,AAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +439,0.0,0.0,67.0,0.0,0.0,0.0,66.0,1.0,HCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +440,0.0,0.0,77.0,0.0,0.0,1.0,0.0,76.0,FCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +441,0.0,0.0,0.0,0.0,153.0,0.0,0.0,1.0,HEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +442,0.0,88.0,88.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +443,0.0,0.0,0.0,20.0,22.0,0.0,0.0,0.0,EEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +444,41.0,0.0,42.0,0.0,0.0,0.0,1.0,0.0,GCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +445,0.0,0.0,0.0,47.0,0.0,46.0,0.0,1.0,HDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +446,1.0,0.0,0.0,0.0,86.0,0.0,0.0,87.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +447,56.0,56.0,0.0,0.0,0.0,0.0,0.0,1.0,HABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +448,0.0,0.0,0.0,0.0,11.0,0.0,0.0,10.0,EEHEHEHEHEHEHEHEHEHEH,True +449,0.0,0.0,0.0,0.0,0.0,1.0,92.0,92.0,FGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +450,0.0,0.0,0.0,6.0,5.0,1.0,0.0,0.0,FDEDEDEDEDED,True +451,66.0,1.0,67.0,0.0,0.0,0.0,0.0,0.0,BCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +452,0.0,0.0,0.0,13.0,0.0,1.0,12.0,0.0,FDGDGDGDGDGDGDGDGDGDGDGDGD,True +453,1.0,0.0,0.0,0.0,56.0,0.0,56.0,0.0,AEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +454,15.0,0.0,0.0,0.0,0.0,0.0,0.0,16.0,HAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +455,0.0,21.0,1.0,0.0,21.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True +456,93.0,0.0,1.0,0.0,92.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +457,1.0,0.0,0.0,0.0,35.0,0.0,0.0,35.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +458,13.0,0.0,0.0,0.0,1.0,0.0,13.0,0.0,EAGAGAGAGAGAGAGAGAGAGAGAGAG,True +459,0.0,0.0,65.0,0.0,1.0,0.0,65.0,0.0,ECGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +460,0.0,0.0,95.0,1.0,0.0,95.0,0.0,0.0,DFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +461,15.0,0.0,0.0,0.0,1.0,0.0,0.0,15.0,EHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +462,0.0,0.0,198.0,0.0,1.0,0.0,0.0,0.0,ECCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +463,84.0,84.0,0.0,0.0,1.0,0.0,0.0,0.0,EABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +464,0.0,0.0,0.0,0.0,0.0,60.0,0.0,61.0,HFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +465,0.0,179.0,0.0,1.0,0.0,0.0,0.0,0.0,DBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +466,1.0,0.0,90.0,0.0,89.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +467,0.0,35.0,0.0,0.0,0.0,34.0,0.0,0.0,BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +468,0.0,0.0,0.0,1.0,7.0,0.0,0.0,7.0,DHEHEHEHEHEHEHE,True +469,0.0,0.0,0.0,0.0,92.0,0.0,91.0,0.0,EEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +470,0.0,0.0,46.0,0.0,0.0,1.0,46.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +471,0.0,0.0,0.0,0.0,0.0,1.0,158.0,0.0,FGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +472,1.0,0.0,0.0,0.0,0.0,58.0,0.0,59.0,AHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +473,0.0,0.0,6.0,1.0,0.0,0.0,6.0,0.0,DCGCGCGCGCGCG,True +474,0.0,0.0,0.0,0.0,0.0,98.0,0.0,97.0,FFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +475,0.0,87.0,0.0,0.0,0.0,0.0,0.0,85.0,BBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +476,0.0,0.0,33.0,0.0,0.0,0.0,1.0,33.0,GHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +477,45.0,0.0,0.0,0.0,46.0,0.0,0.0,0.0,EAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +478,0.0,0.0,0.0,77.0,0.0,0.0,75.0,0.0,DDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +479,73.0,1.0,73.0,0.0,0.0,0.0,0.0,0.0,BACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +480,0.0,1.0,0.0,0.0,37.0,37.0,0.0,0.0,BEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +481,0.0,92.0,93.0,0.0,0.0,1.0,0.0,0.0,FCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +482,0.0,0.0,0.0,1.0,0.0,0.0,0.0,24.0,DHHHHHHHHHHHHHHHHHHHHHHHH,True +483,25.0,0.0,0.0,1.0,0.0,25.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +484,0.0,0.0,0.0,0.0,0.0,37.0,0.0,36.0,FHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +485,21.0,0.0,0.0,1.0,0.0,20.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +486,0.0,35.0,0.0,36.0,0.0,0.0,0.0,1.0,HDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +487,0.0,0.0,1.0,0.0,97.0,98.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +488,0.0,93.0,0.0,0.0,0.0,1.0,0.0,94.0,FHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +489,0.0,1.0,0.0,93.0,0.0,0.0,93.0,0.0,BGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +490,0.0,0.0,0.0,70.0,0.0,0.0,72.0,0.0,GGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +491,86.0,0.0,0.0,0.0,1.0,86.0,0.0,0.0,EFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +492,0.0,65.0,1.0,0.0,0.0,65.0,0.0,0.0,CBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +493,0.0,0.0,0.0,69.0,0.0,0.0,0.0,1.0,HDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +494,0.0,0.0,144.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +495,0.0,45.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +496,0.0,0.0,0.0,28.0,0.0,27.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +497,0.0,72.0,0.0,0.0,0.0,1.0,73.0,0.0,FGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +498,0.0,0.0,41.0,0.0,1.0,0.0,40.0,0.0,ECGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +499,0.0,1.0,0.0,0.0,0.0,131.0,0.0,0.0,BFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +500,17.0,0.0,0.0,1.0,0.0,17.0,0.0,0.0,DFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +501,19.0,0.0,0.0,19.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADA,True +502,1.0,0.0,0.0,0.0,51.0,0.0,52.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +503,1.0,0.0,0.0,0.0,0.0,0.0,29.0,29.0,AGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +504,36.0,0.0,0.0,1.0,0.0,35.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +505,0.0,0.0,0.0,20.0,0.0,0.0,1.0,20.0,GDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +506,0.0,0.0,0.0,163.0,0.0,0.0,0.0,1.0,HDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +507,22.0,23.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABAB,True +508,0.0,1.0,0.0,0.0,0.0,0.0,41.0,42.0,BHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +509,0.0,0.0,0.0,45.0,1.0,0.0,0.0,44.0,EDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True 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+671,99.0,0.0,1.0,0.0,98.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +672,68.0,0.0,0.0,0.0,0.0,0.0,67.0,1.0,HAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGA,True +673,0.0,0.0,0.0,26.0,27.0,0.0,1.0,0.0,GEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +674,31.0,0.0,0.0,0.0,32.0,0.0,0.0,1.0,HEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +675,0.0,0.0,0.0,0.0,42.0,0.0,41.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +676,0.0,0.0,50.0,0.0,0.0,0.0,1.0,50.0,GCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +677,0.0,25.0,0.0,24.0,0.0,0.0,0.0,0.0,BBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +678,0.0,0.0,0.0,0.0,1.0,10.0,9.0,0.0,EFGFGFGFGFGFGFGFGFGF,True +679,65.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,DAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +680,0.0,23.0,0.0,0.0,0.0,0.0,23.0,1.0,HGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +681,0.0,1.0,58.0,0.0,0.0,0.0,57.0,0.0,BCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +682,0.0,0.0,0.0,0.0,0.0,68.0,1.0,68.0,GFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +683,0.0,0.0,0.0,0.0,96.0,0.0,96.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +684,1.0,0.0,0.0,0.0,66.0,0.0,66.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +685,0.0,0.0,0.0,0.0,0.0,1.0,0.0,21.0,FHHHHHHHHHHHHHHHHHHHHH,True +686,0.0,88.0,0.0,87.0,0.0,0.0,0.0,0.0,BDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +687,0.0,0.0,19.0,19.0,0.0,0.0,1.0,0.0,GDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +688,0.0,42.0,1.0,0.0,41.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +689,0.0,0.0,0.0,0.0,0.0,60.0,61.0,0.0,GGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +690,0.0,23.0,23.0,0.0,0.0,0.0,1.0,0.0,GBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +691,86.0,86.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +692,35.0,35.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +693,57.0,0.0,0.0,0.0,0.0,58.0,1.0,0.0,GFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +694,0.0,0.0,30.0,30.0,1.0,0.0,0.0,0.0,EDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +695,19.0,18.0,0.0,1.0,0.0,0.0,0.0,0.0,DABABABABABABABABABABABABABABABABABABA,True +696,0.0,0.0,0.0,1.0,0.0,56.0,0.0,57.0,DHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +697,10.0,0.0,1.0,0.0,0.0,0.0,0.0,11.0,CHAHAHAHAHAHAHAHAHAHAH,True +698,0.0,0.0,89.0,0.0,88.0,0.0,1.0,0.0,GCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +699,0.0,0.0,87.0,0.0,86.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +700,17.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAA,True +701,0.0,0.0,66.0,65.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +702,0.0,0.0,1.0,0.0,0.0,0.0,123.0,0.0,CGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +703,0.0,118.0,0.0,0.0,1.0,0.0,0.0,0.0,EBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +704,0.0,0.0,0.0,0.0,0.0,0.0,0.0,132.0,HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +705,0.0,0.0,0.0,0.0,0.0,23.0,1.0,23.0,GHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +706,0.0,0.0,0.0,0.0,6.0,5.0,0.0,0.0,EFEFEFEFEFE,True +707,18.0,0.0,0.0,16.0,0.0,0.0,0.0,0.0,AADADADADADADADADADADADADADADADADA,True +708,0.0,72.0,0.0,0.0,0.0,71.0,0.0,1.0,HBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +709,0.0,0.0,54.0,0.0,0.0,1.0,0.0,55.0,FHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +710,0.0,1.0,87.0,0.0,87.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +711,0.0,0.0,1.0,63.0,0.0,0.0,0.0,64.0,CHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +712,78.0,0.0,78.0,0.0,0.0,1.0,0.0,0.0,FCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +713,0.0,80.0,0.0,0.0,0.0,81.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +714,0.0,1.0,0.0,0.0,0.0,0.0,40.0,39.0,BGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +715,0.0,0.0,7.0,0.0,6.0,0.0,0.0,0.0,CCECECECECECE,True +716,35.0,0.0,0.0,0.0,0.0,0.0,0.0,33.0,AAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +717,0.0,0.0,0.0,1.0,73.0,0.0,0.0,72.0,DEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +718,0.0,0.0,90.0,0.0,0.0,1.0,89.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +719,1.0,0.0,0.0,67.0,0.0,0.0,0.0,66.0,ADHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +720,56.0,0.0,0.0,0.0,56.0,0.0,1.0,0.0,GAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +721,0.0,0.0,0.0,1.0,0.0,0.0,49.0,49.0,DHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +722,0.0,0.0,0.0,117.0,0.0,1.0,0.0,0.0,FDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +723,0.0,0.0,86.0,1.0,0.0,0.0,85.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +724,0.0,0.0,31.0,0.0,0.0,0.0,0.0,30.0,CCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +725,1.0,0.0,0.0,0.0,98.0,0.0,98.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +726,1.0,84.0,84.0,0.0,0.0,0.0,0.0,0.0,ACBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +727,0.0,56.0,56.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +728,0.0,1.0,0.0,24.0,24.0,0.0,0.0,0.0,BDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +729,37.0,0.0,0.0,0.0,0.0,37.0,0.0,0.0,FAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +730,0.0,0.0,91.0,0.0,0.0,0.0,91.0,0.0,GCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +731,98.0,0.0,99.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +732,0.0,0.0,0.0,0.0,99.0,1.0,98.0,0.0,FEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +733,0.0,0.0,30.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +734,12.0,1.0,13.0,0.0,0.0,0.0,0.0,0.0,BCACACACACACACACACACACACAC,True +735,0.0,93.0,1.0,0.0,93.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True 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+852,0.0,1.0,0.0,0.0,136.0,0.0,0.0,0.0,BEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +853,0.0,0.0,0.0,0.0,1.0,0.0,0.0,163.0,EHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +854,74.0,0.0,75.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +855,0.0,0.0,0.0,19.0,0.0,0.0,17.0,0.0,DDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +856,0.0,73.0,0.0,1.0,0.0,0.0,74.0,0.0,DGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True 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+863,0.0,0.0,0.0,32.0,1.0,0.0,32.0,0.0,EGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +864,0.0,0.0,15.0,0.0,1.0,14.0,0.0,0.0,ECFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +865,0.0,1.0,98.0,0.0,0.0,0.0,98.0,0.0,BGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +866,1.0,0.0,0.0,0.0,19.0,0.0,0.0,0.0,AEEEEEEEEEEEEEEEEEEE,True +867,24.0,0.0,0.0,0.0,24.0,0.0,0.0,0.0,AEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +868,0.0,0.0,0.0,74.0,0.0,0.0,0.0,73.0,DHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +869,0.0,78.0,1.0,0.0,0.0,0.0,77.0,0.0,CBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +870,0.0,0.0,1.0,0.0,50.0,0.0,51.0,0.0,CGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +871,0.0,0.0,16.0,0.0,0.0,16.0,0.0,1.0,HFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +872,0.0,0.0,0.0,1.0,28.0,28.0,0.0,0.0,DFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +873,0.0,0.0,65.0,65.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +874,0.0,34.0,0.0,0.0,0.0,35.0,0.0,0.0,FBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +875,0.0,0.0,9.0,0.0,8.0,0.0,0.0,1.0,HCECECECECECECECEC,True +876,0.0,0.0,0.0,0.0,94.0,0.0,94.0,1.0,HEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +877,0.0,18.0,0.0,16.0,0.0,0.0,0.0,0.0,BBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True 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+885,0.0,0.0,0.0,93.0,0.0,93.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDF,True +886,0.0,1.0,0.0,89.0,0.0,89.0,0.0,0.0,BFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +887,0.0,1.0,0.0,0.0,42.0,0.0,0.0,42.0,BHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +888,68.0,0.0,0.0,0.0,1.0,0.0,0.0,67.0,EAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +889,55.0,0.0,0.0,0.0,0.0,57.0,0.0,0.0,FFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +890,25.0,1.0,0.0,0.0,0.0,0.0,26.0,0.0,BGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +891,81.0,0.0,0.0,0.0,80.0,0.0,0.0,0.0,AAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +892,0.0,0.0,1.0,0.0,10.0,0.0,10.0,0.0,CGEGEGEGEGEGEGEGEGEGE,True +893,1.0,0.0,43.0,42.0,0.0,0.0,0.0,0.0,ACDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +894,55.0,54.0,0.0,0.0,0.0,0.0,0.0,0.0,AABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +895,43.0,0.0,0.0,0.0,0.0,1.0,0.0,43.0,FAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +896,1.0,0.0,0.0,0.0,97.0,97.0,0.0,0.0,AEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +897,0.0,25.0,0.0,1.0,0.0,25.0,0.0,0.0,DFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +898,0.0,0.0,0.0,0.0,26.0,26.0,1.0,0.0,GEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +899,0.0,0.0,36.0,0.0,36.0,0.0,0.0,0.0,ECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +900,0.0,0.0,0.0,0.0,1.0,0.0,89.0,88.0,EGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +901,0.0,1.0,142.0,0.0,0.0,0.0,0.0,0.0,BCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +902,1.0,83.0,0.0,83.0,0.0,0.0,0.0,0.0,ABDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +903,0.0,0.0,17.0,0.0,17.0,0.0,0.0,1.0,HECECECECECECECECECECECECECECECECEC,True +904,77.0,77.0,0.0,0.0,0.0,0.0,0.0,0.0,BABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +905,0.0,0.0,0.0,0.0,0.0,0.0,164.0,0.0,GGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +906,0.0,0.0,0.0,89.0,0.0,1.0,0.0,90.0,FHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +907,0.0,0.0,41.0,0.0,0.0,0.0,42.0,0.0,GCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +908,28.0,0.0,0.0,0.0,0.0,28.0,1.0,0.0,GAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +909,0.0,0.0,94.0,0.0,1.0,0.0,95.0,0.0,EGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +910,0.0,0.0,27.0,1.0,27.0,0.0,0.0,0.0,DECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +911,0.0,0.0,0.0,100.0,0.0,1.0,0.0,0.0,FDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +912,0.0,1.0,66.0,0.0,0.0,0.0,66.0,0.0,BGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +913,0.0,23.0,23.0,0.0,0.0,1.0,0.0,0.0,FCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +914,0.0,0.0,0.0,0.0,0.0,0.0,150.0,0.0,GGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +915,0.0,0.0,0.0,0.0,0.0,0.0,1.0,42.0,GHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +916,0.0,147.0,0.0,0.0,0.0,0.0,1.0,0.0,GBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +917,0.0,56.0,0.0,1.0,0.0,0.0,0.0,56.0,DHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +918,0.0,0.0,0.0,0.0,0.0,76.0,76.0,1.0,HFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFG,True +919,0.0,53.0,0.0,0.0,0.0,0.0,0.0,52.0,BHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +920,0.0,0.0,147.0,0.0,0.0,1.0,0.0,0.0,FCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +921,0.0,0.0,0.0,40.0,40.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +922,0.0,82.0,0.0,84.0,0.0,0.0,0.0,0.0,DDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +923,1.0,0.0,0.0,0.0,0.0,0.0,0.0,97.0,AHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +924,0.0,29.0,0.0,0.0,0.0,0.0,0.0,30.0,HHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +925,25.0,0.0,0.0,1.0,0.0,0.0,0.0,25.0,DHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +926,0.0,164.0,0.0,0.0,0.0,0.0,1.0,0.0,GBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +927,89.0,0.0,0.0,0.0,1.0,0.0,90.0,0.0,EGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +928,0.0,0.0,1.0,0.0,41.0,41.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +929,0.0,0.0,1.0,19.0,18.0,0.0,0.0,0.0,CDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +930,0.0,0.0,0.0,0.0,1.0,75.0,75.0,0.0,EGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +931,0.0,0.0,21.0,0.0,0.0,22.0,0.0,0.0,FCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCF,True +932,0.0,0.0,81.0,0.0,80.0,1.0,0.0,0.0,FCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +933,20.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAAAAA,True +934,0.0,40.0,0.0,0.0,0.0,40.0,0.0,0.0,BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +935,0.0,72.0,0.0,0.0,72.0,0.0,1.0,0.0,GBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True +936,56.0,1.0,0.0,56.0,0.0,0.0,0.0,0.0,BADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +937,0.0,0.0,0.0,0.0,0.0,96.0,1.0,0.0,GFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +938,0.0,1.0,0.0,88.0,0.0,0.0,0.0,88.0,BHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +939,1.0,0.0,0.0,0.0,0.0,0.0,0.0,175.0,AHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +940,0.0,0.0,84.0,1.0,83.0,0.0,0.0,0.0,DCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +941,0.0,0.0,83.0,0.0,0.0,0.0,0.0,85.0,HHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +942,1.0,5.0,5.0,0.0,0.0,0.0,0.0,0.0,ABCBCBCBCBC,True +943,0.0,0.0,0.0,68.0,0.0,0.0,0.0,69.0,HHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +944,29.0,0.0,0.0,0.0,0.0,29.0,1.0,0.0,GAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +945,0.0,0.0,1.0,0.0,0.0,0.0,81.0,82.0,CHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +946,89.0,0.0,89.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +947,0.0,0.0,0.0,78.0,1.0,0.0,0.0,0.0,EDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +948,90.0,1.0,0.0,0.0,0.0,0.0,91.0,0.0,BGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +949,0.0,0.0,0.0,86.0,1.0,0.0,0.0,86.0,EHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +950,0.0,0.0,0.0,42.0,1.0,0.0,42.0,0.0,EDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +951,85.0,0.0,0.0,84.0,1.0,0.0,0.0,0.0,EADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +952,90.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +953,0.0,0.0,1.0,0.0,0.0,90.0,0.0,0.0,CFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +954,62.0,0.0,0.0,1.0,0.0,62.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +955,0.0,20.0,20.0,0.0,1.0,0.0,0.0,0.0,EBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +956,0.0,0.0,37.0,0.0,0.0,1.0,0.0,38.0,FHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +957,98.0,1.0,0.0,0.0,0.0,98.0,0.0,0.0,BFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +958,0.0,1.0,0.0,0.0,189.0,0.0,0.0,0.0,BEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +959,0.0,0.0,0.0,9.0,0.0,1.0,8.0,0.0,FDGDGDGDGDGDGDGDGD,True +960,0.0,68.0,0.0,0.0,0.0,0.0,0.0,69.0,HHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +961,0.0,0.0,0.0,138.0,0.0,0.0,0.0,0.0,DDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +962,0.0,0.0,0.0,0.0,1.0,30.0,0.0,30.0,EHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +963,0.0,0.0,0.0,80.0,80.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +964,77.0,0.0,0.0,1.0,0.0,0.0,0.0,78.0,DHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +965,0.0,0.0,0.0,58.0,58.0,0.0,1.0,0.0,GEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +966,0.0,0.0,0.0,1.0,35.0,34.0,0.0,0.0,DEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +967,0.0,60.0,0.0,60.0,0.0,1.0,0.0,0.0,FDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +968,0.0,1.0,80.0,0.0,81.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +969,0.0,1.0,0.0,0.0,0.0,0.0,81.0,81.0,BGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +970,16.0,0.0,0.0,16.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADA,True +971,0.0,0.0,0.0,0.0,78.0,77.0,0.0,0.0,EFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +972,0.0,0.0,10.0,1.0,0.0,10.0,0.0,0.0,DFCFCFCFCFCFCFCFCFCFC,True +973,0.0,0.0,0.0,0.0,0.0,44.0,1.0,44.0,GHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +974,0.0,36.0,0.0,0.0,0.0,36.0,1.0,0.0,GFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +975,0.0,87.0,0.0,0.0,0.0,0.0,87.0,0.0,BGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +976,42.0,0.0,42.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True 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b/tests/results/nb_gm_001_3back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,0.0,65.0,132.0,0.0,0.0,0.0,0.0,1.0,HCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCC,True +1,51.0,0.0,52.0,52.0,0.0,0.0,0.0,1.0,HCDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACD,True +2,0.0,61.0,0.0,62.0,0.0,0.0,61.0,1.0,HDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGD,True +3,40.0,0.0,0.0,1.0,0.0,0.0,0.0,80.0,DHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHA,True +4,4.0,0.0,1.0,0.0,0.0,6.0,0.0,0.0,CAFFAFFAFFA,True 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+62,0.0,1.0,0.0,0.0,59.0,0.0,60.0,59.0,BGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEG,True +63,0.0,0.0,0.0,0.0,0.0,0.0,1.0,167.0,GHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +64,48.0,0.0,0.0,0.0,1.0,0.0,0.0,95.0,EHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHA,True +65,0.0,0.0,0.0,65.0,66.0,0.0,67.0,0.0,GGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGE,True +66,35.0,71.0,0.0,0.0,0.0,0.0,0.0,0.0,BBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBAB,True +67,50.0,0.0,0.0,50.0,50.0,0.0,0.0,1.0,HAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAED,True +68,0.0,0.0,4.0,0.0,0.0,0.0,5.0,3.0,GCGHCGHCGHCG,True +69,0.0,0.0,5.0,0.0,0.0,0.0,1.0,10.0,GCHHCHHCHHCHHCHH,True +70,0.0,0.0,19.0,0.0,19.0,20.0,0.0,0.0,FECFECFECFECFECFECFECFECFECFECFECFECFECFECFECFECFECFECFECF,True +71,0.0,0.0,1.0,0.0,0.0,0.0,43.0,84.0,CGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHG,True +72,6.0,0.0,0.0,0.0,6.0,6.0,0.0,0.0,FAEFAEFAEFAEFAEFAE,True +73,0.0,0.0,35.0,35.0,35.0,0.0,0.0,1.0,HECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECD,True +74,25.0,0.0,26.0,0.0,1.0,0.0,0.0,25.0,ECAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHC,True +75,61.0,0.0,0.0,60.0,0.0,60.0,0.0,1.0,HAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDA,True +76,0.0,0.0,0.0,41.0,0.0,0.0,0.0,20.0,DHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDD,True +77,0.0,0.0,1.0,0.0,0.0,15.0,15.0,14.0,CGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGF,True +78,6.0,0.0,1.0,6.0,0.0,0.0,0.0,6.0,CHDAHDAHDAHDAHDAHDA,True +79,0.0,124.0,0.0,62.0,0.0,0.0,0.0,0.0,BBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBD,True +80,0.0,0.0,32.0,0.0,0.0,31.0,31.0,0.0,CGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCF,True 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+317,61.0,0.0,0.0,0.0,0.0,61.0,1.0,61.0,GFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHA,True +318,0.0,0.0,0.0,7.0,7.0,8.0,1.0,0.0,GFEDFEDFEDFEDFEDFEDFEDF,True +319,7.0,0.0,0.0,0.0,1.0,3.0,0.0,0.0,EAAFAAFAAFA,True +320,0.0,48.0,0.0,48.0,0.0,0.0,0.0,48.0,BHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHD,True +321,0.0,23.0,23.0,0.0,0.0,0.0,0.0,24.0,HBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCH,True +322,0.0,0.0,1.0,0.0,0.0,30.0,30.0,30.0,CGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFH,True +323,48.0,0.0,0.0,47.0,47.0,0.0,1.0,0.0,GADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEA,True 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+401,0.0,55.0,55.0,0.0,0.0,1.0,54.0,0.0,FCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCB,True +402,47.0,0.0,0.0,0.0,1.0,47.0,0.0,47.0,EAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFH,True +403,56.0,0.0,0.0,0.0,58.0,0.0,0.0,56.0,EEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAE,True +404,0.0,39.0,0.0,0.0,39.0,1.0,40.0,0.0,FGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEG,True 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+951,0.0,0.0,0.0,0.0,35.0,1.0,35.0,35.0,FHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEG,True +952,0.0,0.0,1.0,0.0,0.0,0.0,36.0,71.0,CHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHG,True +953,0.0,42.0,0.0,0.0,21.0,0.0,0.0,1.0,HEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBB,True +954,0.0,49.0,0.0,50.0,0.0,0.0,49.0,0.0,DDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBG,True +955,11.0,0.0,0.0,0.0,22.0,0.0,1.0,0.0,GEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAE,True +956,0.0,0.0,0.0,1.0,0.0,18.0,0.0,38.0,DHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHH,True +957,58.0,58.0,60.0,0.0,0.0,0.0,0.0,0.0,CCBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBAC,True +958,19.0,19.0,0.0,0.0,19.0,0.0,0.0,0.0,BEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEA,True +959,0.0,0.0,39.0,0.0,0.0,38.0,0.0,38.0,CFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHC,True +960,0.0,0.0,0.0,80.0,41.0,0.0,0.0,1.0,HEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDE,True +961,0.0,21.0,0.0,22.0,0.0,23.0,0.0,0.0,FDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDF,True +962,0.0,0.0,0.0,0.0,6.0,10.0,0.0,0.0,EFEFFEFFEFFEFFEF,True +963,65.0,65.0,1.0,0.0,65.0,0.0,0.0,0.0,CBEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEA,True +964,0.0,46.0,1.0,0.0,45.0,46.0,0.0,0.0,CFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFB,True +965,64.0,64.0,0.0,0.0,63.0,0.0,1.0,0.0,GABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEAB,True +966,1.0,0.0,47.0,0.0,0.0,48.0,47.0,0.0,AFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGF,True +967,54.0,0.0,54.0,53.0,0.0,0.0,0.0,0.0,ACADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADC,True +968,10.0,0.0,10.0,0.0,12.0,0.0,0.0,0.0,EEACEACEACEACEACEACEACEACEACEACE,True +969,0.0,0.0,0.0,0.0,0.0,0.0,125.0,62.0,GGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGH,True +970,0.0,8.0,1.0,9.0,0.0,0.0,8.0,0.0,CDBGDBGDBGDBGDBGDBGDBGDBGD,True +971,0.0,0.0,0.0,66.0,66.0,67.0,1.0,0.0,GFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEF,True +972,63.0,0.0,0.0,0.0,127.0,0.0,1.0,0.0,GEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAE,True +973,0.0,0.0,11.0,0.0,0.0,0.0,21.0,1.0,HCGGCGGCGGCGGCGGCGGCGGCGGCGGCGGCG,True +974,0.0,0.0,39.0,0.0,0.0,40.0,40.0,0.0,FGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFG,True +975,0.0,0.0,1.0,31.0,0.0,0.0,62.0,0.0,CDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGG,True +976,0.0,54.0,0.0,0.0,0.0,1.0,54.0,55.0,FHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBH,True +977,0.0,0.0,18.0,19.0,0.0,18.0,0.0,0.0,DFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCD,True +978,126.0,63.0,0.0,0.0,1.0,0.0,0.0,0.0,EAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAAB,True +979,19.0,0.0,0.0,0.0,0.0,1.0,0.0,9.0,FAHAAHAAHAAHAAHAAHAAHAAHAAHAA,True +980,0.0,0.0,32.0,32.0,0.0,33.0,0.0,0.0,FDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFC,True +981,15.0,0.0,15.0,0.0,16.0,0.0,0.0,0.0,ECEACEACEACEACEACEACEACEACEACEACEACEACEACEACEA,True +982,0.0,0.0,55.0,0.0,0.0,56.0,57.0,0.0,GFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFG,True +983,0.0,0.0,32.0,0.0,1.0,32.0,31.0,0.0,EFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFC,True +984,0.0,0.0,0.0,41.0,1.0,40.0,40.0,0.0,EDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGD,True +985,0.0,0.0,0.0,0.0,5.0,6.0,5.0,1.0,HFGEFGEFGEFGEFGEF,True +986,0.0,19.0,17.0,0.0,0.0,0.0,0.0,18.0,BBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBH,True +987,0.0,0.0,0.0,0.0,0.0,0.0,6.0,10.0,GHGHHGHHGHHGHHGH,True +988,0.0,0.0,69.0,0.0,36.0,0.0,0.0,0.0,ECECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCE,True +989,1.0,0.0,0.0,0.0,0.0,19.0,0.0,37.0,AHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHF,True +990,67.0,0.0,0.0,0.0,0.0,0.0,0.0,33.0,AHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAA,True +991,0.0,0.0,16.0,18.0,0.0,17.0,0.0,0.0,DFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFD,True +992,1.0,0.0,50.0,50.0,0.0,0.0,49.0,0.0,ACDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCD,True +993,0.0,40.0,39.0,0.0,39.0,0.0,0.0,1.0,HBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEB,True +994,0.0,30.0,1.0,0.0,0.0,0.0,30.0,30.0,CBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGH,True +995,126.0,0.0,1.0,0.0,0.0,0.0,0.0,63.0,CHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAA,True +996,45.0,0.0,45.0,1.0,0.0,0.0,0.0,45.0,DHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHAC,True +997,15.0,0.0,0.0,0.0,29.0,0.0,0.0,0.0,AEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEE,True +998,0.0,4.0,1.0,0.0,0.0,4.0,0.0,4.0,CHBFHBFHBFHBF,True +999,0.0,100.0,0.0,0.0,0.0,0.0,0.0,51.0,HBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBH,True diff --git a/tests/results/nb_gm_002_2back.csv b/tests/results/nb_gm_002_2back.csv new file mode 100644 index 0000000..33538c3 --- /dev/null +++ b/tests/results/nb_gm_002_2back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,4.0,2.0,2.0,2.0,2.0,1.0,0.0,5.0,BHCHDHDAEBEHAFAHAC,True +1,0.0,4.0,1.0,2.0,4.0,0.0,0.0,0.0,DBEBDBCEEBE,True +2,5.0,10.0,14.0,6.0,16.0,18.0,12.0,12.0,CFFGHCFCGHEDCCACECBGEGFGAEBGHFDCEEDCCEGEGCBBBHCCECHBHEHBHDEDAFAFAFHFGFGFGHGHEFFFEFEDHFEFEFBBB,False +3,12.0,15.0,11.0,20.0,13.0,17.0,17.0,22.0,AFAHGHGHGBEBCDDDDHHHABCEHEHEBBBAHADADCFHHHHHFEFCBDDFDGDEFCAGGFEFBDGEHECCBCFFFFFFHGEBBHHCBCACHHDDBFGGGGEGEAFDGDADGDGDGBEBAAHDDFH,False +4,4.0,4.0,8.0,8.0,5.0,7.0,4.0,2.0,FGDGECDCECGCDADAHFDFCFCGAFCDDDABEBHBEFEFBC,False +5,15.0,15.0,15.0,16.0,16.0,14.0,9.0,13.0,HGDGBFDHDADHBBBBBHBAAGBCEABCGFAFAFBGBCBFGDDDEAAAHDFACECECHFHFHFCFHEGEFEFDFDAAHDEECDABFCCCCGBEBDAHCECHCHEDEDEDAGEE,False +6,17.0,17.0,9.0,6.0,15.0,13.0,15.0,12.0,BEBEBHAGCFEHHABAHDEDGHFBFGFCAABAGFFFAFGECEBEAEAFBFCEBEGHGDBEFABABEGEHEHBGBGDADACAGHGHGBGBACGCAHFFBHAECDC,False +7,12.0,7.0,7.0,6.0,9.0,8.0,5.0,6.0,CEGBFEFEFEHCCDEBCCHBBBGAHACBGGDBDADACADHDHFEAEAEFGFAAEAHAFAF,False +8,9.0,13.0,10.0,11.0,12.0,15.0,11.0,12.0,CGCFDBDFHHEHFFGCDHEHCFCFAAEGDCEGHGCFCBBBCBGFGHGDFDBDADHBBEGAGABABHBEBEHGHADAFEFCFDBDEFEHEFEFA,False +9,13.0,26.0,23.0,14.0,20.0,18.0,19.0,27.0,HECEBEFFHFDCCFGBCBDBAHGHGCBBABHEFAFEBEBHBHGGCHBGGCCCCCFCBDDDEDHDEEEAAFAFGFDFCGBGHEHDHGHAFABCGGEHEHFBGBADEBEBEAAHBDCCFGGHHHBHBHGHBDBEEAEGCGCBCHCEFFFFCHDHCHDHABCB,False +10,14.0,18.0,15.0,13.0,15.0,19.0,18.0,11.0,AFACABDDFBBBEBECECGHFBFBECDCEEEDGDBHHGCBDDAFCBAAAGHCHCHEAFBFDHAHCFFAAAHBBBFBFBHGFBCBCFGGGHGDGDFEGEFCFEDGDGAGEGCGEGEFEFAFDGC,False +11,21.0,20.0,21.0,13.0,15.0,26.0,21.0,21.0,EECEFFHGCADHGEGEABCCFDEBABEBGGCACHFHFBFBFBAHGBGCGHDCDABHHAGABFHEBCFEGDFDFDFAFBCBCAHACFGFBFBFBFBDACCBCHFHEGEDFDFCAAAGGEBFAAACACHCHFGFBFGHGHAEAGCCEDDFHHHGHGHGDE,False +12,17.0,26.0,17.0,23.0,17.0,11.0,26.0,21.0,ABGCACGDDFHFHBCEHEAGBGBEBAHEBEBFAAHAFBCEGDGBAHGGGGFGDDDBABABHGGGCGDGHGHDACAEDEFECHGEGDABGCHCDDDDCBCBADAHCHGBGBGEHDCDBBFBABHBHBFBACHDEEHGHECDCDHDEFEDECFGHGBFBD,False +13,24.0,21.0,23.0,20.0,15.0,14.0,30.0,24.0,AHHHHAFEDHAFBFGFCFGADADCDGBBBBGDGEGBCBHGGGGCGFBFAGGGGHEEFEGHGHABCBFHGAGACBBDEDHDHDGBCACAHGCACEHECACHBHDCGCECADGDGDABADHFGCGAGAHHBGFDCHBHCAAABEEFDFDBDBEADAHGEGEHECCCBCFCAHD,False +14,1.0,0.0,2.0,1.0,1.0,1.0,2.0,2.0,DECGCGAHFH,True +15,7.0,7.0,10.0,5.0,8.0,4.0,8.0,9.0,HBABHHEEGAGAGEGHCDEECHCHGBCBCDDAEGCBCGEAEFDFBFBFAGCHCHCHAD,False +16,14.0,19.0,14.0,7.0,10.0,15.0,19.0,7.0,CEAFFGHGEGFDFDCACAGBDEAFCEDDFAHHFDFGBEACGCGBGAFECECFGHCEBAFGEGCBABEBHBHBACAGAGDGHBABCBCBGFGFGFGBBBBFBCBGA,False +17,17.0,15.0,14.0,12.0,10.0,9.0,17.0,6.0,EBACADACGBGBAFGHGHADCDGAAFFFADABAHGDGABBCBCACACECHFBFHDCACDGEBADDEGGGEDADFGFGCGFBBABCBEBDBCHGEGEGECE,False +18,14.0,22.0,17.0,9.0,14.0,10.0,25.0,20.0,EHCHAHEHAHCHCGBGCGCGAEBFBFGGCEFGBGHAHCBABABHHGHGCACHDEDBBABGGDGDEBBBHHGCAEGBFHGEGEGBCCGCDFBBGBFBDAEEHHHCFEFECEHGCGCBHDADFDAGAGAGFBB,False +19,13.0,27.0,12.0,18.0,19.0,17.0,20.0,18.0,BFGCGBHAHAHEFEDBABEBEDADGGGGBAFCGEBDFHBHGHGCBBEGEGBHDHDHBCBCACDBFHHCHBGAGAGEDADADCDCACGHEEEEBDFDFDHDCGGBGDEBBBABEHFHGEFFFBADHEFFCFDEBEBFFEBHBFBG,False +20,11.0,10.0,7.0,8.0,8.0,7.0,11.0,4.0,BGBABGHGCGFBFAEBGGEDEFAHEHACDCDADBGGAGAGADFBFBCBCEFBFDHDACCDAGAEEE,False +21,22.0,20.0,18.0,24.0,13.0,11.0,16.0,21.0,DADADHCACFCHEDAAAHGDDHAGCDEDEGBHAHBDBDBGHHHCHCECAAAEFEDECEDBHFABGBCAGDBEGEBABHFCBBABDFDGHGCBFBCCDHDHDGDHDHCHBGADAFACHEHBDCDAFAFAFAGGCGCFHGBDBEBEG,False +22,8.0,10.0,11.0,7.0,8.0,15.0,4.0,11.0,CBAEGDGEHEBGBFBFBDHCHFHBAEHFFGFCFBFCFEEHABECFFFFACAEHHDCDCDHDHAHCFCBCBAADF,False +23,32.0,19.0,21.0,23.0,13.0,27.0,21.0,27.0,GHCABDGDFFFAHHHEAEHGAGAGHEFEGBCFAFBFGCHCHFHBGCAFFDFDBACACHCHCHBFGFEACAFABEBEBHHGHFHAHGGAGAHAFCGDHDHAFGCBCHDAAAAAAFCFHGEFFBEBEDDDFDBCBDDDCGFAFADBDBEBCAGGHDFDFBCDEAGAHCCEHGHAHCDDDDABAFA,False +24,26.0,30.0,18.0,21.0,29.0,16.0,21.0,21.0,GDGDADAGAGDEHCDBDHAHEHFHAHAFBHBHGCEBHBDBHBHBEEABABABAEECEGEGAGADHDBEEGBCAADHGBFBCEAAHDEBEBFBFBFCCGCEFBABAEDBGFGBGCFCGEACDFEFBHDADFHCEAEBDHDCGBEFGCDCACDEBEGAGAEAEFDFBBEHEGEGHCACEFBHDH,False +25,17.0,15.0,10.0,21.0,16.0,11.0,16.0,22.0,BDBDBHHHAAGAEHEHCHCDADEBGHDAGEBHGAABADADEDECEHAHFBGCGBEHCGADFBHECGHHFFFHFBDDDDDFDFDFHFEDEDACAEAEBDCHHBFBABCBGDGEAECHHGHGEGHDAGGG,False +26,12.0,13.0,16.0,11.0,17.0,10.0,17.0,12.0,GEECBGFEEDHCEFGFEAEAHGEGEDDDHDCDCBHBCBCFCECEGAGAGAHECFCEAAFGFGCEHGHBBBGBGBCBDHEAEFHFHGBCDGGACHCGCDADAEBFBADH,False +27,14.0,11.0,17.0,13.0,14.0,21.0,16.0,19.0,AAECGGEGHCACACACHBHADCECBDHDHDFCFGHGDDEDHHHAHDFDACHBHAFBHHAEEECGGFGEGEBEFCFAEAEFFBFBFDGDGDGHFACCDFHFCGBBHBCGGFGEHEFFFFHFCBCAF,False +28,14.0,15.0,12.0,21.0,15.0,9.0,13.0,21.0,GGHGEDHFCFCACBCADAEEEEAHDGAGHGHEHEHBBECEDBBBDBEGDGBAEABCCABBECDDDFDFHGHGHDHGHGHDADHHCHBHCCBAFHFDDDEDHFHAABDFDFEGEAADBDCH,False +29,18.0,19.0,27.0,26.0,29.0,30.0,16.0,16.0,DEFFFAFAGDGEEBFBFGEBADACADFDCEEDEDFDCDEBBGDGHGHGFFFDFBEBEHCHFDCDCEGFGFHFEFCGBBDCHCGCDADEGEGCFAAEHEHFDACGCEABBDECBCBCEFEFBFCFCFEHEHDGACEBAGCEFEBACCCAEDHDHBCFCDEFFHDHDHDCFCAAAEBEBFDHA,False +30,5.0,11.0,5.0,8.0,3.0,2.0,5.0,1.0,BBFGGBABFGCCCDADAHBEDCDBABGEAECBDBDBDBDG,True +31,28.0,17.0,19.0,16.0,18.0,11.0,17.0,33.0,DHAFAHAEAHDHFHFAFADHCGGGDGDGHEBDHCHBHAEBCBCFEGHHHBHCAFDHEHEHCDAGBCBAAAGACCBCAFGBHEHBBEAHAHAFAEACGGEHAFABEDEDFDCGHEBGAGEEAEBBHDEDECHCGABHGHAHAHBHCHCHCHDGACACDFD,False +32,5.0,10.0,12.0,17.0,19.0,17.0,17.0,11.0,EEBHBFFFDDEDCCAGEFEGGDGDFFGEGEAEDEFCFCGCGCGFAEGECDHHCEFDDHDFDABFDECECEHEFDDGDGBBFBFHHGCECEFEHAHDHDGBBFBGHGBG,False +33,4.0,13.0,10.0,7.0,4.0,8.0,11.0,7.0,CGBHBCBCBHFHFECBADGBGBGBDBCFAGDBHGFGECEHBGBCCACFGFGFGDDDFCADHEHB,False +34,22.0,27.0,22.0,21.0,21.0,28.0,21.0,21.0,BABFBCCCCGCDCAGABAHFBAHCBDBDHDCDCDEFFHBHBCBCBEHDAGAEFBBEEEBEGAGHGDGCGEBFBDEAECCFCFGDGDGHBHAEFFFECCADHFFBGHDHEGAAEDEFEFCDCDCDEFCHADAEHFDFHBBEBEBFBFAFGFAAHGHGFFAFGGBABGHGBFBFDFHCHAHEGDA,False +35,24.0,23.0,21.0,17.0,28.0,15.0,20.0,21.0,EGHGAGEGCGDFFCEEEEEAHGEGFGFBCBGBDBACHCAGDDDDEDEHACGCECAFAFEFHCHCEFHDHEHBAEADBDBAFCHCEEEEHBHBECEAEAFGGGGCCHBHAAACABBEHFHBDFHHDHBGCAABEBGAGABBFADADEBBBBCDCACFGFHDCEHEBGADE,False +36,16.0,12.0,18.0,16.0,29.0,20.0,25.0,11.0,EEEBCFFDHDBBGHGHGEFDFACCCFCGAECECEAGFFFCFDAHAEEHGGGBGBGADDGDGEGCCBFEHEGEHACDGDGCCCFCEAFAEGEGBGFGBBBHFGDGFGAAHADADCEEEEDEAEFEAEBFFFHEGECEGEHECAFDDDB,False +37,1.0,6.0,2.0,11.0,2.0,11.0,4.0,7.0,DBFFFHHADFFEFBDBFBGDFFEBHBHFHGDGDGCCDDDDHDHF,True +38,11.0,12.0,15.0,5.0,3.0,15.0,15.0,13.0,HCCCCAEBGFCFBGAHHHHBAFGCGCGCGFGCAABFBABHBFBCAFHFAFGCDBGBGAGFCBBAADHDHDCGEGHGCGFFHFHDEFHFC,False +39,33.0,14.0,21.0,23.0,21.0,18.0,25.0,28.0,DHAHAHADGDAFAFGCHCHEHCHABACEDDDCGBHAEFFGCADADGBGCFFFGGHBAAFGGHFHFHECFCHCHBDEFGADDCGGGHEBEDEBEBEDFHCAAAACFGFBFBFADAEGBDCAGACACAFGEEECDDDDCGGGEEEEEGCADHHHHAHABAHGBBCACHEGGHDADADAHAHEHAH,False +40,9.0,21.0,8.0,6.0,13.0,11.0,9.0,15.0,HEBEGEGAGEBBBHFAFABCBCBEBCBEAFHGGGHEHCHBEDFFAFAHDBFBFBEBDFHHDHBHCHBHBDEFABGBCEDEBCACHHEAGBGF,False +41,13.0,18.0,18.0,16.0,8.0,20.0,16.0,13.0,AGDGBCDHFADAGFFFHHCFCFEBGBGFGFGCGCHHHHCGFBFGDHABCBCGDGECEFBFCACBDBDCFAFBDEDCFFBHGHBEBABDFDFDHDHACABDBAFAFDHEGACACBEECGCBDG,False +42,21.0,15.0,14.0,22.0,14.0,22.0,16.0,21.0,ACFDFDEDFDBAFDCDCDFFFFFACHCHGEDFCFEHADACEHEDEBAFAGGHGEDADFDHDHDHGADAGCCCFHBDBGBDEGEBHGFGHAHFBFBFEAABABACDDAHHGFGBGEGHFEABHBFEHHHGDFDCACABABGECHAH,False +43,17.0,19.0,23.0,19.0,19.0,21.0,20.0,22.0,GDGFGEDDDDDDFDFDFEHBHDGAECBHDEGHGEEDEBEDECGGAADAFAFADECFCDGDGFBHGCBHBACAGACFCGGGBGCHFHEHECECAHFHFGCGHBFCGCBCFEHEGEHBBAAABDHFBCCCCFFFHFCABFBHBHBEDAFEHBHACABECHCH,False +44,2.0,1.0,3.0,4.0,5.0,3.0,6.0,5.0,CHCHFGBGEHFDAGADEDEGGFGEDEHCH,True +45,17.0,20.0,26.0,20.0,18.0,24.0,15.0,12.0,BDEFBBBHHECFCFCBBFEDDADADGECEHEFCGCAFDCGCFFEDDGGHHHHHAFAFEFAFDFDFDEDFAACFCFCDCBBBCGCGDGDFCGCGBDCACBHDHEECBBEBECFCHGBGEGABCDCEFHFGACDFAFAECEBEBDACABAGFBA,False +46,5.0,7.0,11.0,5.0,5.0,3.0,8.0,10.0,CBDHFHCDCEGEHCHCHCHEGCGCGBBBBADAHGDGBACGEAHBHFGFCECAHD,False +47,5.0,4.0,4.0,5.0,0.0,1.0,5.0,3.0,ACABGBHBHBGDCACHCDAGFGAGDDD,True +48,21.0,22.0,13.0,24.0,16.0,18.0,24.0,19.0,DBDGAGBGFHFCABGFECEGBGHHEACDFDGCGBEBGDAFAHADADAHHBHBHAGABADEBFDGDBDGDGCFAFAFDDDDECGFEFEAHAHEHEHCBCDADGBFBFAEBCAHFHEDEGBBFDEHEBDHFGCGHGHGBGCDABCBDGHGBGDCEAFAF,False +49,5.0,12.0,11.0,8.0,8.0,7.0,11.0,9.0,FCFDGDHBEBECFBBHFCFCGDBCCCGCECECBDBGBEHDDBCAGAEHEDFDHGEGAHBHGAGAGFHBHBG,False +50,2.0,7.0,7.0,4.0,6.0,13.0,10.0,11.0,BBFEFEFHAHFDFGHEBABDFHBHEFGFGHEHGGGFDFEHCBGBFDFHFHCCGCGHGCCC,True +51,5.0,7.0,11.0,12.0,13.0,9.0,8.0,13.0,EFFBFDAAECCCHDHBHFEDBHBHDHDGGGGECDGHCFEFEDEDCDCDEDCCHFEFEGCGBHEHBHAHAGDFCEAEHB,False +52,15.0,6.0,11.0,6.0,11.0,16.0,3.0,8.0,BAEGCCEAHBFCCHFABEHEFDCHEBECACECEAFGFEFEFBFBFAFADADACACDFGFAFAFEFDAAHFDCAHHH,True +53,20.0,14.0,19.0,11.0,13.0,12.0,10.0,17.0,CHCECEHEGAHBFGHCHABCBCDCECEDAHACGCADDBBGFGFGFHAAACACFBEGGAGAEHCAAAFDFDCHBDBHGDFDHCBEFEBCBABHHHHDHCHDFEFABEBECAAAEACF,False +54,18.0,14.0,15.0,22.0,24.0,20.0,25.0,23.0,EGGCGCGDEDEBCBFDDDBFHDDGFBFEEEGDBDBEHFDFEACACADABEFDCECGGHBDCDBAGHGFBFECHCFEDEHEHAHEEAGCEEEEFGFHFAAGEEHHHHAHAHDEFGDGDBCGAGHFHFHAHAHDHDBFBFCEGGGGGGGHAADAGCDFFAHCB,False +55,3.0,4.0,2.0,5.0,2.0,5.0,3.0,1.0,EHAABABGBFDFGFGEDDFDCBCDF,True +56,9.0,9.0,8.0,11.0,11.0,13.0,8.0,11.0,ECFFFBCDEDAFEBEAFGFHFHFDEHEBEHEGBFEFHBABCCAGAGBGBDFHAHGHFCFDHDABADEDEDAHGGCDCHCD,False +57,10.0,13.0,10.0,15.0,7.0,9.0,16.0,11.0,HHCFEGEGEDFGABEHEADCHGHBDFDGDGHGCGBBDDCDCDBDBHCDEBAHACCFDGDFAFAFDDAGAGHGCGBGBHACBGBGAHEBFBF,False +58,15.0,15.0,14.0,21.0,27.0,24.0,20.0,28.0,FAFEFAADAGFBFACBCBHHCGFGFAFHCEGEGHHBDBFHFHBEGDGDAEEHEGCGDGHCDGDEHFHGCEEEGEGEDBDEEEEHHHHCHDAGFEBHFHAHFHFDDDCACHFBDDHDGDFDAGGEAEFBHEEEEBEHEFFCFCFDBHAFADCGCGFHDHEBABHB,False +59,11.0,16.0,18.0,17.0,22.0,31.0,15.0,17.0,FCECFCFCFBHCHBGBFHGEDADADEFEFHFDFDADEEADHGAEAECGDGCCFHFGFHFHFHFBFBFCEEEBEFFDEGGBHBEBHFCDDDDGHAFBFBFCACHCAFGCGHHEDCBFEFABCDCEGGGDAEBBBEDEFFFFECGHEHF,False +60,11.0,9.0,7.0,2.0,10.0,10.0,11.0,9.0,HGHCDCHCACBCEGEGEGEBBHCFGABEBFAEHHFBFAAGHGHFHABABCGEGFDEAAABFEFEFGFGA,False +61,23.0,23.0,21.0,24.0,24.0,17.0,27.0,24.0,EDGGCBCFCGCGCFCGCDCBAACHFHFHECACAGAHFHDBDEHAGADHGEGEBCAEAGDHAADDDDCEAEADBGFDBBBBDHDGDBBGCAAEHEGDGBGBFHCGCDBBBEFHFDAGHCDCHFHFGEHEGEGHGBEFACADAFCBGBGBFHDEDEDFBFEGHGHAHAEEEEGEDHAHACEFBHB,False +62,21.0,13.0,9.0,12.0,17.0,15.0,25.0,10.0,HFGFGBGEDEHGHAHFHGAAAFGHBFACGDBEBGAAFEGEFEFBGAHDEDECBCBFBEGAGAFCCBBDBAGABAGGGGGECDADAGAEFEDGACADDCDHDEAFHFHFGGGFGCABAEEEGE,False +63,6.0,6.0,3.0,12.0,7.0,8.0,6.0,13.0,FHEBEBHGHDAGHDCDEDEAFCFCHEEBAAFDDDFDHDAGBGFDHGHAHDHEHFHFHBDBG,False +64,6.0,15.0,15.0,8.0,14.0,13.0,8.0,8.0,CCEDEDBHHGDCBEFEFCCGCEAGFGEGECAHAHGBCFHACEBEBEGEFFFFBDBFBHBDDEDCBCBHBFGFHEAEBCBCFCBCAFD,False +65,6.0,4.0,3.0,4.0,6.0,8.0,5.0,5.0,CGCFEFAFAEEDEHCHBBDAAFAGHEHEBFDHDBAGFGFGF,False +66,17.0,8.0,15.0,6.0,16.0,16.0,11.0,12.0,AFGFGFGHGFECECECHAECCCFAHAFAEHGGCEBAFAEAEFGGHCBFAAEHFHFGBHEHGAFBFHCECEADFDBDBCACACAEAEBEDDACBDFHFHEGC,False +67,24.0,12.0,23.0,14.0,18.0,18.0,15.0,12.0,CCCFCFBHAEEDFDBAADAEAEABDBDGEHEGCCCACECHGEGEDECACFCFCHBFBAGAFFGHADBEBAAAAFAEECEDHDHECGGBHHCHDBGBABAGEFFGFAFADACADAGADCHFECGFGFHFCDCEGFCC,False +68,31.0,17.0,27.0,38.0,29.0,28.0,14.0,16.0,ACACBCFDGBHBDEGEAHDDEFEFEFEFDDHECEBDFDAEAEFECECGCHAHAHCBCDAHBDDDDEDEBEHGDDAFEFCFDDBCGAGACCECAADADABAFEDACGCAFAHDFDBDGCECBGBFFCHCGAEDFFFHADFDADGFAFADEDHABAGAGEHEFBFECEDEDCGEADADFDHBHDFDCBCFCDAFAECFCEHB,False +69,5.0,4.0,3.0,4.0,2.0,3.0,6.0,4.0,DAHAGAHAHAHFGCGEBDFDEDGGCFBBGBC,False +70,5.0,7.0,9.0,5.0,2.0,11.0,6.0,10.0,HAHDHDHBGBFCACDCHFBBHBHGDEACACEGFCDHBGFGFGFCCHBFFHFCFAF,True +71,11.0,10.0,6.0,19.0,14.0,23.0,11.0,9.0,FHFEADABECHFFDFDFHFEDECEFEFEFAFHDADAEADDCAGFGBBHGDGABDDFFFFDDDADEEGFGDABCDGGBHDHFGAGBHBHBEBEGFFFFFCCEDE,False +72,25.0,17.0,20.0,19.0,16.0,13.0,17.0,22.0,GDCDHGBEAEGDGEBDBDHDCDCBHDEAEHDCEFAAABCDCDABAGADADCFAFCGCACAFFBAHGCGCGEGEACHHECACECEHEGGFBDHFHAHAHGGDGFCECHFHFHCHFABABFDGABDEDABABHEACAFDHHGHAHBBBBEH,False +73,15.0,19.0,20.0,23.0,23.0,21.0,22.0,23.0,GFGFECGCEEGHFCBCFDDDHHGBGHGHDCDCFHAHCCCFHAADEBEHEDEDADCDCABEGEFDFHCHGGAHAHFCFCEADFFECGBDBDBDCCACADHGCGEGHFHGHGBFADEBEBEDGDBBACEEEHGBDBFFFFDGEGDGDGFBEHHHHAAEAEFBBBBEFH,False +74,3.0,11.0,6.0,11.0,10.0,12.0,5.0,7.0,ECHFHDHEFFHHDCFGEGFDBEBEFFFDBCBFEDCDCFEBBFADDBDBGBGBGBAHAHFDEDECE,True +75,21.0,13.0,22.0,19.0,30.0,19.0,18.0,19.0,HAHEEEFEDHDFDBHBGCCEEFEGGHGHCCCCCHGECEAHDBDBEFGHCACGBEFEHAFDFACAFEEEHABAGAFDGDADADAGBCBAEADAEFHCDCFGEHFHDEDCDFEFCCCEAEAEGGABFGEDBDBHBCCECEHEAEFGHGHDDAEAEHCFGFGFB,False +76,14.0,30.0,18.0,20.0,25.0,19.0,27.0,30.0,FCFBAEDEGEHEBGHGFEFCGDBDGGCGCGBEBHBHEAAAEECBCBCFHFCFDGAEHHFGGGGGHCHEHBABGBGHHDFAEBDBDBDBCCHAGGEGDGCCBCHFGFGHGHBHEFGHBFBCBHEHBBABCBHBCGEHEADDDBHFHAADEDBFHFEEGEDHDHDEDBDFEFEHCHAEGDHBFBA,False +77,25.0,17.0,30.0,29.0,22.0,22.0,23.0,24.0,CCHEAEHBBCBDADBDBDHGFEECBDFGFEAHDCGCDHHEHEHCGCFHGDGAGAGACACDDDFDFDGECCHDHCCEFAFEBAFGGHDCCGEDBDBDBCHCACDBAHCGCGAHAHAFFFHADCDCFCFHHCDCAEAGAGAGABFHGEGBGDFHEBEFCFAGBEEAABAGDGDFDFEABHCDEDEHEHEFCFCD,False +78,9.0,16.0,9.0,5.0,4.0,15.0,4.0,5.0,BCEADCBBBBABABCCEHFBDHFAAGAGHCFCBCBFDFAGAGBFBDBABFFFFFCEHEBDHFFFBFC,True +79,19.0,17.0,10.0,29.0,13.0,8.0,14.0,14.0,DEDEAEAEDDDDDDDHDGEBEFADAGBFFHDGFBBBBGBABFCHGDFDEACBBBAHADAHCGCAHDHEHABAGCGCGEDAGBDAACAHDBCBGBGBEDDDDDADGDFDHHFDAHAEEEHCDCHG,False +80,9.0,11.0,7.0,9.0,14.0,3.0,11.0,16.0,HEHEACBHBHAGEBEAEBHBHBDEDCFABCGAEABHEHDADABABGGGDGHECEHHDGDHHCHCDGFFHCBEDEGEGHGE,False +81,4.0,9.0,4.0,9.0,3.0,6.0,6.0,5.0,BGBACACHDGDFDFBFEAHFBDDEDEGHGHBBBFBADHDGCGDBFC,False +82,11.0,21.0,22.0,24.0,26.0,28.0,21.0,21.0,EDGDCDCFGEDEFFFFGEEEDEDEDADACHCEBAFAFCHEDBFEDHDCCAHGFDFDGAGEFECEDBHCECDGGGGGBGFGBHCGDGFFDCAGDBCEHEGBBBBHFHADFHCHCHCACHCBBEFAGBGBEBFFFHFBCEDFFEFHDHFHFCCECBHBDBDEDEHBHEHFBFEGAG,False +83,2.0,4.0,1.0,3.0,2.0,4.0,2.0,1.0,CBFHFBBDGDFDFEGEABA,True +84,18.0,13.0,21.0,13.0,16.0,19.0,15.0,8.0,CBCEEADAFGDCFHFHDHFACACEDGACFGGGCBABDCCCCCCBABABABDBDFACGCGCFCAGEFEFBDBCFEFEAGFDBEFEHEHBAEADAFAFGEGECAHFEDGDHHCAEDEFCFGGGBF,False +85,14.0,12.0,10.0,10.0,16.0,19.0,9.0,12.0,FGBGHDEEEGBFAEAEDHGHGFEDEFEGEDEFEFCBAHCHCFBFDGECFFFGAECBBBDGFAFACACBEDABEBFHFHFHAHAHFEDCDCFCAAHBHADAFB,False +86,14.0,13.0,10.0,16.0,18.0,7.0,14.0,15.0,GGGGHADGCGCEEEDEDBAAGBCDAEABAGAFFFDBEFEAHAHBDBDBDBGHAACDHHGHGHDHEFBCDCHCHDEEBEBDADABEFECCGHGHFHDGEEEADBEEHC,False +87,9.0,13.0,17.0,12.0,12.0,23.0,13.0,12.0,EHCHBDDCECFCFCFABABGBFDFDCDHBGDHDGBGCGCGCFCDHEHEFCHGEAFBFBFDFHCEBAFEDEDFFGHCFGBGFGCDCEBGFHFAFBEEEBGFFCFAACAHAHF,False +88,6.0,3.0,0.0,1.0,3.0,3.0,5.0,4.0,GBGAGBHAGAGFEBEFEHHAHAFAD,True +89,11.0,11.0,12.0,15.0,16.0,12.0,7.0,10.0,BHBHDDADCGCAEHHDCEAFAFBFCDEDECBGFCECHAHGCAEDDBDEAFAFHFDCHEBEGEGADBDBHEHDFGFGFDECECECAAEBEBDBFF,False +90,18.0,21.0,18.0,8.0,15.0,18.0,18.0,10.0,BCBDGCBCHGHAAFAFEFAFDFHGGGCCECEHBHFCADAFAFEGBAAAGAFBEBEBEGCBHBFADAECDGHGBGECCBCBABHFFDCEFEHGBGBGBEFGABCBFBDBEEAHACGCGEGFCFCFDA,False +91,21.0,22.0,23.0,29.0,25.0,21.0,20.0,16.0,EDECECBBDBGGGDHDFCFDFAFGBACHDHDADFDHBEAACACACEDECEDGDGEGEGEDEAFCFEGGBEBGFGEDECGFAFAFGHEDFHFCFBFBDEDFDGBHEADHDCCFBABABACGEHAHFHCEGEGHBHDACADFCCHBHDCDCFBHAGDBABEBFBGCDBEBCDDADAEEC,False +92,22.0,26.0,23.0,24.0,20.0,30.0,22.0,18.0,ADAFEGHDHFFFFDFECADDDFHBHDCBFAHCHCACHEGFBFBCDHEFEGABAFAEBGBFFFBFCFGBHBEBAACAHAEDEDEGCDCDCDCGHACFCFHFHGCFCEHEHCGCDCEFGDGBGBGEGBABGBGCCABBBDBAFGDABFBFEFEDADBFEFDBHGHDFEFECBAGGCGADDDGBHAEA,False +93,2.0,2.0,1.0,3.0,0.0,2.0,1.0,2.0,DBDCDGFFAHAHB,True +94,18.0,8.0,12.0,13.0,10.0,9.0,12.0,11.0,HHFAEHCHCHCDDAFACACACGGFEFGCHDEEGCGCGFDDADGDFDEBHCDABGBABDGAGEEBAFABGBDAHAFAFADADEHHCHCBGEAEA,False +95,4.0,5.0,6.0,3.0,5.0,4.0,4.0,3.0,AHBFEADADAGFHFGGCBCBCBCFCEHEBDCEEG,False +96,6.0,10.0,15.0,4.0,14.0,9.0,14.0,11.0,ECECEGHGHEHGDACGHHHFGFGCCCGFEEHEAAACCHCFCFEGEDHFHFDFGEABBBBEBHGCGBEBGCACBEBEGCCDBFG,False +97,3.0,4.0,3.0,4.0,3.0,2.0,2.0,6.0,BGHFHDHDCDBDECAHAHAEGBFBHCE,False +98,14.0,9.0,9.0,12.0,16.0,15.0,11.0,5.0,BGGACFEGEGEAFGFGFGFAADADACBCFDADGEBHBFDFGBBDCGAFAEEFECHCDCBFEAEAEADADCEBDDHDBGEFCHEHEFEAEFF,False +99,24.0,22.0,16.0,19.0,18.0,22.0,22.0,17.0,BABDFDEDEDEHAACABAEAFFGBHFGAHDBCAGADEDCHBBGEGAGAGAGAGFGABEDEDEFCBABDBECECEAGFGEGBGACBFEHEHAHAFBFBCHEFGDADAEEBCBHHHFHFBAGGGFFFFGHDCCHAHBCBCHFGDBCCAFBDGGFDHDFDFDC,False +100,10.0,7.0,6.0,7.0,6.0,11.0,8.0,15.0,GGHGHGFEFDCHAHFHEHEBACCBCHFHFBCBEBFFEFHAHGHDAGADAEGBGHHBAAADCFHFDADFDH,False +101,21.0,23.0,9.0,23.0,25.0,21.0,22.0,21.0,EEEEEACAHEHDDADHFBFBAHGHGBGDGFECGBBBBFBFEFHFGFGFAEHDHAHAHBHGHFBBHGGGGGEHDDDDHEAFBHHDEFEHEDDGBCDCHBGDDFFCAHADEDEGEGEAABBEBDFGEBABCDFEACFDADAGAGEGBAFABHBDGDCEEEAFAFBFC,False +102,1.0,8.0,5.0,3.0,5.0,5.0,6.0,8.0,HCGCHDEBGFEFECBBBFBFGHGHGDGBAHCFCHHHEDEBB,False +103,29.0,22.0,27.0,17.0,23.0,16.0,31.0,26.0,GGHCFGEBEDGCCDEBFFFEFHGCDCBCBCECFCHCHCHGHCEGAGCECABHEEEBEBEGAGBBBABABFBHBHDHGGDADCCFAFEDECEABGBFAFHDAGHGHADEFGBDCHHDEDCHGABABFGDEAAAEBGAAEGGGGFGHAHDBDCCHGHBDGEGHGEAEACCHCACAHGHGHAHDCACAFAGAFA,False +104,7.0,6.0,18.0,7.0,11.0,12.0,24.0,18.0,GDGEHCGGGEFECEBECGCGHGCFHFHFHCDFDFGACHHHGBGHACDCGAGADBCAHECACGHGHBBCFGHEDEFEHGHBHGGCGCGCHCEGGDGEAFFHFCF,True +105,16.0,23.0,21.0,18.0,22.0,17.0,10.0,18.0,ACEGEHEHAFACDCDCHFBFBGBHDFFFCAGHBBBHBHFABABABAHEGCAEEEFGBGBADGEBCDEHEBCFCHBHEFEBDDDDDDDGFEDEFEHAHBCACACBDBDHDCBCEDEHEGCCFEEEDHHAABCFCHAECBCBFFCFG,False +106,9.0,10.0,12.0,6.0,8.0,7.0,13.0,7.0,FABABHCEGEGBGBGCCCHCAAABGEGDGFGFAFCBCGCEHDCCAGHDHCAEHFBFAGBGBGHFDCDBEEDE,False +107,17.0,15.0,17.0,17.0,16.0,26.0,15.0,17.0,EFBHGEAFDGCGFGFGDEEAEGBDEFBGGFAHHCAFAFHBHBDGDGEGEGDFFFDFHHHAHBCDADBCBFGFCBCBGBFEHADAHCECFCECHBFFFFCDEDEDCDEFEFCHHHCACAEBCGAAAAHADAFHFBDBCFDF,False +108,20.0,24.0,27.0,23.0,19.0,28.0,19.0,18.0,AFAEGFGFGAHFCFEHEGDBBBEBEBEBCDDDHDFGFDCDCECFAFAHAGBBBEBFDEBCBAHGFGAGABDBEAGFCCCBEBHCDBDFDFBBHCHGGCDCDFHEHECGCFFFADAHHHDCDAEEBFGAEHCDDGACACACFCBEFFHAGCCCCEFEFCABDBFFFGHCHDHDFDGBGA,False +109,9.0,16.0,17.0,17.0,16.0,16.0,12.0,24.0,EGDDDAHBEAEABDCEBFFHFHFHCDGHAHCCFDFDFDFBBEBFBFEHGHGDCFCGHGHGCBCEDHBCDHFHFBFGDGACCCGAEBHBABCHHEHBDDEHEDEDEGEAHDHCECFCFCBHAHEGBHH,False +110,5.0,7.0,7.0,3.0,11.0,14.0,10.0,14.0,AHEHDHGFEFGCHFGFBBCAEFEFEFECEHFHBHAHFCBGFABHBEDEGCGFDFACGCGBFEFGHHHHEHG,True +111,20.0,16.0,22.0,22.0,11.0,17.0,13.0,10.0,ACAFFCDCDCACBFAFGDAACDCDEDEFFCBHDGDCDGDEABFEAADDCAHHDHEGACEFBCBCACACABBHDHDHEHCAAFAFCDDEDFDFBFCFBFDEDFFGGAGCCBEBCBHBAGGGGGEGACBHBDB,False +112,26.0,22.0,28.0,29.0,20.0,26.0,21.0,19.0,GCDCBAEHEHGGFABGFFFFBDBDBHCHCHAAADGFCBCDCFFFDCHCECEDEAFBFEFEGGCDCDAEAECFCEEACCBABGFDABADAFHBHFEFEAHAEADFCFHHBHAHAGGDHCCCDHBCADABHBDCGHGAGAGDDDFCAGBCBDBCFCFEHEDEBGGFGFDBCGAGDCDEDGDBDBEFEHAFADD,False +113,4.0,0.0,3.0,3.0,1.0,0.0,3.0,3.0,HAHADDGDHAGAECCCG,True +114,15.0,25.0,14.0,19.0,17.0,16.0,17.0,18.0,GDGCHHEBEBHBEFAFEFBFHFBGHEFEFEBAAAGFGDDFDFDFDBDBDBABABDHCBGDHCEBBGBCBEBAGHCHBEBGHEHEHEACACACACBBGGFGHCHDGBCDGEFDFDBEHECDGBCEHAHDHACFGADFDBAGD,False +115,4.0,7.0,3.0,5.0,3.0,0.0,6.0,6.0,HGHBHBDBABACEGDGEAHBHADGEGCHCBDGDB,True +116,18.0,19.0,11.0,27.0,26.0,22.0,18.0,28.0,FDFEHEBGBGBCFDFDFBEGFABHCHEEFAFAFAFBDHEHEABBDCHCDDGEHEADAFAFBHHCHBFBEDHGHGBFDFGECHHABDEGECEDADEHEDCAHAGEBABCDCDAHEDEDEDFFFFFBFHGAFEGEGDHDHGHGHGEDHDGEGDAHABBHHDHBCDADHEGE,False +117,9.0,10.0,11.0,5.0,12.0,11.0,5.0,12.0,HFBFCFBAAEABGHCHAFABBBBCCCHCECECHCGEHEHEHFHAHCEDDFDCEEBFFFFGEBEAFAHDGBGDEHA,False +118,1.0,8.0,6.0,3.0,6.0,11.0,9.0,8.0,BEBFGFGFBFBGBCDFEHBHAGEFHGDEFBFHHCGCDBGFGFGHCHFHCECE,True +119,16.0,21.0,23.0,14.0,8.0,20.0,24.0,21.0,EEGFBBADAFCBHFACCCFCFEFDGAFHFDABHBCGHHHBHGHCHEGCAABBGDHBHBGFGCGCGCGHFEFCFGABAGGCGAGACFCBCBHBFCFADHDHGHGFDEBEGCGCDBHBEAACHDDFDCDCFBFBGGGGCBHDHDHFABA,False +120,23.0,16.0,16.0,25.0,12.0,20.0,24.0,21.0,DFHFBBDGFFEDCHEEGGGEEADAGAGDBDAABFDFCGDGAABABABABACAGGHDHFACECBDDFDHGHGHBCBCAGFGBGCFFFDFDCGHGDEEHBCDCBHBCFGFDFDHAGCHHHHHGAFADDHEHEAGAGAGHCBAEAEDCDADCFGFDHDHF,False +121,19.0,17.0,15.0,20.0,28.0,24.0,23.0,17.0,DCDFFGAAFFFBGAGDGCACHEHDADADFEHEGGFFEFAABBHGGGFHEHACACBEEEHBAGAGFDFEBEGEBECECDCHBHGDGBEFEAEAEAECCGCEHBHCFFGBDBDCDAEEEAEFFFBHAHGEDEBGFGFGHGBGBDFDCDHEHDDDEBAFDFEGCFH,False +122,24.0,21.0,31.0,19.0,20.0,33.0,21.0,17.0,CBDGEGCBFGFHFHFEFBDAECCCBCBGHDCCCAFADHDHDEDACBDBGAHABFDGEGCHEECECDAFBGBGBFFFFHEAECHFHFHGEEBCFCFDGEGFFFFGCDCGBGBGFFBFBFAAAAAFGBAFABECAGEGBGFHFCADDCECHFAFADAHFHEDEHCFBACAEAEFDCCCCCBCHDADCG,False +123,23.0,22.0,33.0,26.0,18.0,14.0,26.0,19.0,DGDGCACABHFCADADGHGEEHGACAHAGACEDEDEDGDFCHDECFCBCGHGECHCHBEEDEDEDEDCBGBGBABCBCBHAGDGECAGDCCCFCDCFHFDABECGBGFHBBFBEBEBACEDBHHCCGCDAGGGFCCCGDDFCBCBGBGHGHGCBADHFFAHDGAAAAABAFDHDHCFCEAD,False +124,14.0,14.0,13.0,14.0,9.0,17.0,19.0,18.0,DCBFBFAFAHBHGFBABECACGGBGCGCFAFHHDGDGEBDADFFHHHHDAABHFFEGAGFDBGHGAGBGHFHFGCHCDGEGEFCGDGDCDCDCECBFAFCFHAHEBEGHBEBHHADAD,False +125,22.0,17.0,18.0,14.0,19.0,23.0,19.0,20.0,AFFEGCACEHAHBHFHECADBDEDHDHDACHCBCBHFDDAGHGHCECEAEAHBHGGCEAFAFBDGFFFFBAGAFAFHHCGDFFAEBBABADADBCGHHHGACACFCFDFBCGHGEGEGBGBCBEEAFHEBBGGECEFECEHGGEAFDFDFAF,False +126,2.0,2.0,5.0,1.0,2.0,0.0,0.0,0.0,CBABCCCECEAD,True +127,9.0,13.0,13.0,20.0,8.0,15.0,15.0,18.0,GGEFDFEHDHDHBAGABBBFFHFCFHGHGHGHGDADHDEDFCEDAGAGCBDFDHDHCBCDFDBHFHGHFBCGDDDDDABGHDHCHAAECFBDBEBCBCEGECCFFHCGAGF,False +128,26.0,16.0,20.0,13.0,15.0,14.0,8.0,14.0,AFAFGCBFDCCGCBCACACAFACECBAFAFDBBABABHECBGAHADEDCBADABABAHEHCHCHGECDHDHBHBAEDEAEAHBGFAHBBCACACAFEDCAHHEADGEGECEFFFCGHDFDEAEFFD,False +129,3.0,2.0,3.0,1.0,2.0,1.0,0.0,1.0,AHABFBEAECCDC,True +130,3.0,10.0,5.0,11.0,10.0,4.0,3.0,9.0,DBGBHBAEDEBCCEBAAFHHDHDCBEDHBHBHBDECECEDDDFDGDFBEGEHEHF,True +131,18.0,19.0,23.0,22.0,20.0,20.0,15.0,23.0,FGBCAABCBCDCDCBBAAADCEGHAFDFEBHBHAHGDAEAEAHGECHCDDFDBEBHHHDBCFCABFHHHABFHHEGEHBAFAFCDCHGEGEFBFEFEDEHCHCHDHDGFAFEBEBGBGFCDCAEDEGFFFHFBEAGACFDDDDHDCCCCDCDGEGBGCEH,False +132,27.0,13.0,16.0,13.0,20.0,12.0,27.0,15.0,HAACDHGHEBFFCDAGADAEABAGHFHDHCCAEHFHBGBECGGGGAGABACDEDCACACFGFGFHBBEBHGGGDABGGGEDECEAEAEAFCEGBBBAGAEAEABHEAEGGGCEHFHDGAGEDEDFDHDEAAGAHAFFGCCCCG,False +133,5.0,7.0,9.0,1.0,6.0,7.0,8.0,7.0,BGCFEBHHHHACABFBFHFCFGGGCCECGCGCHAEBBHFGCGDAEAEBEF,False +134,14.0,15.0,11.0,16.0,21.0,17.0,16.0,20.0,HBHDHFHDDEFEGEFEBGDFDFBBHBAGEGCFHBHDADHHFAFAHECEFADECEDDDBDBDACBEAFHFHGEGCGDECECBAGACHBHGHFHFHGEGFFHEHCHCEGEGEAEGDGEABDBABFFGECABA,False +135,8.0,3.0,1.0,2.0,4.0,6.0,9.0,3.0,GFGEGHGFEFGCGDBAHAFDEAEGBGBAAAFAGAHF,True +136,14.0,29.0,20.0,23.0,25.0,22.0,18.0,18.0,DGDCEBGFHDBFBECHFEFBDEDCACGCGHEFEFEFAFGGGDCFGFHFHAHADEBBCBCEEEFEBABCBEBACACBHHCFCEAEAGBGDCDBDEDGBACECBHEHBDGDFDGCGAFEFDBHBEBEAHGFCFBFBHEDFDGDBBBBACDBDHGBEAEGFCHBHEHDHDFD,False +137,3.0,5.0,1.0,6.0,8.0,6.0,3.0,5.0,FDFDBBBEDEHEHEFEACFFGDHDFGBHAEAEBEGDH,True +138,17.0,19.0,28.0,23.0,19.0,29.0,14.0,27.0,EEHFCDHDHBAADFECECFFFCDGBAHAHFHBCDDFDGDADBCAAHABAEGFHFHDHDEGCGHGHCFDFEFGBHAHBCBABEEECDCDEHFHFBABHCCCACHEACHDGDFHFHBHFGDGDGDFBCDCGABFFDFECHCFFFHFCDGEFCACHCHCHEGACFCFBFEEECEBBBBD,False +139,18.0,10.0,15.0,7.0,19.0,9.0,15.0,15.0,BCDGAGEBBAAFCBEFDFHCAAHABFEADAHGCCCACEDEDEDEDEHCBCFEHCHEACACHGGGGBGEGFGFEHECGFEAHGHEHEHEHACAFBGGABABHGHEAEAC,False +140,12.0,11.0,10.0,15.0,15.0,9.0,10.0,21.0,GGDEDEDHDABGBDCAFADADEEFHFEEBBAHECFCAHGHGHEBBCBABAFHHHHAFADHECEGGBGECECHBHECFCDDDEEHHHHHDHDHDHFACGDABFG,False +141,6.0,7.0,16.0,10.0,19.0,4.0,7.0,3.0,GAGEECEDBGBGFCFCHCFBDBDECEAEDBDCHBEEFAHAEAEGCBCEADDDDEGCCEEEECCCECDCGCEE,True +142,17.0,14.0,17.0,18.0,21.0,18.0,15.0,9.0,BADAGADHDGDGFHFAFDFGEEDDDADCCCGGECCCGEHAHAHEEEEAECFCDHDFABABFBGBCACEFFDADAEEHBHFDFCBEBGHGCFCDAGFDBEFFGFGEGCBAEDEBCBAACDCBEBEFEFEG,False +143,1.0,3.0,4.0,4.0,2.0,3.0,3.0,3.0,DHDCCGCGAGHBBFEFCFDHDEB,False +144,3.0,1.0,7.0,1.0,1.0,3.0,7.0,2.0,CDCFHGGFBCCCCGAGAGAEHFGCG,True +145,3.0,5.0,7.0,4.0,3.0,11.0,6.0,3.0,DHGEGBGBGCCFDFAFHCBEBEBDFCFCFGFCCAHFFFDGAF,True +146,4.0,13.0,6.0,8.0,6.0,15.0,9.0,3.0,FABGBGFGFDBBBCGEEEEBFGCBFBDBCFDFGFGFAFECCDDADAFBDGHGBFBFHFEFHCBD,True +147,16.0,16.0,22.0,23.0,21.0,20.0,35.0,29.0,FBFEECGAGFGFGHDHDFAGEGEHFHFHFEGHGCEEAHDGDEHEGEFHFCFHGHBECDBDBHHGGGGGGCBHAHACAHAGEBDCEAGGHGHGEGEBDAHHHCHADGCFBFHGBGCHDFDFDGHCBCHHAGBEBDACHCFFGGGDADEEAGCEDEDCCCGDFDBDGFBFBGBDEACACDCDCH,False +148,16.0,20.0,20.0,23.0,21.0,16.0,31.0,18.0,EBEHGGGHCACFDDDDDAFCHEGCACFCFDFAGADEGGGAGEECEGEGEGAFFDCBHBHDHEGCDCGBGBGCCCCCBDGEBCGFHCHGHAHBBCEGEGEBFBGAHABDBDAGAGFGBEEEFEDGDAFCHBABGBADADEGFFDHDCFGGDHBFBDEDEDGHHHBH,False +149,3.0,7.0,4.0,6.0,10.0,7.0,3.0,5.0,EBEHEBEDCFCBBADCHFHFGBGBDEEEECHBDADADEFFFGFHE,False +150,6.0,2.0,7.0,6.0,2.0,3.0,8.0,0.0,DDDCGCADFDFGGGACACAGBECGGDGABACFCE,True +151,5.0,2.0,2.0,0.0,5.0,4.0,2.0,3.0,GAGAFBFEFECEFHABAEHEACH,True +152,14.0,12.0,9.0,7.0,12.0,11.0,10.0,17.0,FDHDFEHDHCFCBCDGHGCFFFBFHACCHBGAGAHEHEBEAADAHBGBFBFBABABAHAHEEAFHEHBHEHABGGECDCECEAGDHAHEFGG,False +153,19.0,24.0,27.0,19.0,23.0,23.0,26.0,24.0,CDCGGGFAAGACHFHDHDHBBCCHCGFAHABGBEDHBGBGBABADECFFFFAGGCHDDGDGCGHGHGDCFHDHAFEFEFEHDCCGGBGEGAAFCEEDFDFGBEAFHFCGEBCBHBFBDCDGBCBEHADABCHCHEHEHBHDGFGAGEGBBEBHDEEHAHAEAECCFFFCCCECECEFBFBDECBA,False +154,13.0,10.0,11.0,9.0,11.0,8.0,12.0,4.0,GEAEAFAGADADAEFCGCGCGCAFBFBEECEGADADACBGBCHHBFEECACBEHEFBFBDADEDBCGGGBDFHCAGGD,False +155,23.0,15.0,20.0,21.0,22.0,13.0,16.0,23.0,FEBEBEBFDHDHCCDDBCBEGFDFGBHCHFDAEBCBFHAHGHDADCBGDHDHDFCAHHHDBCEHDFDAAECDCDCBCAFEEEEEAEAGACHCEGEAEGGGGAEABAFAFHHGEAAACHFHAHFGEAEDEDEDADHDBCGAGACBCHHBGGCHC,False +156,1.0,2.0,8.0,2.0,1.0,1.0,0.0,3.0,CCCCCHCHBACDCBHEDF,True +157,11.0,6.0,5.0,14.0,10.0,10.0,2.0,6.0,EFAHAHFBFGGABADFCBEDEDADAHAFAHBFEDEDCDEDEDEDFFCBEDFDFBACDDAEHCHA,True +158,15.0,22.0,16.0,16.0,9.0,21.0,17.0,9.0,CFCFCAEBDGDHBBFBHCAAGFFFAGGGGFGHCHDBDBECECECFHBBCBAFHFDFBCACHCAAAEFDBDBCFGAADADAGGBBBGCGBGCFBEEGHGFGFDFDFABABDFHFDBDCEFEBGDDB,False +159,3.0,6.0,10.0,6.0,2.0,3.0,4.0,5.0,GGGFDFDBCBHBHBCCHCBCEHHFCACDCBEDDDACGCA,True +160,7.0,12.0,7.0,6.0,6.0,8.0,8.0,5.0,AEFEFEBCBADCEFHHCHGBBECAABFBFBDBGBHECGDADADGBGAHFFCFCGDGBGB,False +161,25.0,18.0,13.0,27.0,15.0,21.0,17.0,28.0,HFHGDDBDFDGHGADHGFBHGCFDAECCHHEFEFEDDBEBAHAHFHFBFHAHDFDFAEDFBBCEHADGFGAHDGDGDGDFCBCEAEBCBHDHDHAHAEADHHFHFHEGBHEDABABACDCAEFDDGFGAGABAHDHDGDGDBHBFAABAGAECECHCACBFAFH,False +162,18.0,23.0,16.0,12.0,17.0,23.0,24.0,31.0,AEABABCBCHCHCFFFBHHEGBABDDDDDHHFHEECFCFCBEDDBHBHBCGHDFAFHCHFGCHHHHHHHCFGFGEHDBAAEGGHEBBHGDAHFHBHBECGFAFBGCAHEHGBBFBDCHHGEAEHGFFFADGEGBGBGCGFFCHGEGEGAGAFABABAEAEGFGF,False +163,24.0,23.0,17.0,16.0,25.0,31.0,34.0,30.0,FHFHFEFGFBAEHHHDHDHFGGDGDGFGDHACAFGDGDECECHCGAHAHBBBBBFFFCGBGEFFHFEAECGGBBAGABABAFHFHECGDECFCHDBACDEHBFBHBFEFDDGCHBHGHGHBEAGFGCEHFBAHACEHEACFCFEAEGEGAGACFEAEBGGFDBDBGEGECEAHHHAGBGHAFDFAFDFGBGHGFGAGHEE,False +164,16.0,17.0,19.0,27.0,19.0,29.0,35.0,19.0,GDGBCCGCAFBFGFDHGHBFAFGFGDDECECDGDCDFHFGFCFHFEABACFHFBFHEEECEDFDEDGGGDGCCBBDBFBABFBGDEDEGBHBDDDGGGGCFHFGFGFHFEABBDCDCHCGGGDGFGEDADHDECEAGAFAHEHADAFFGGGCABEGHCAEFGFGAGDDHDHBCEHGAEHFH,False +165,10.0,7.0,7.0,12.0,6.0,6.0,5.0,8.0,DGFFDCDCDAEGDBDCEBGACECHCECDBABDEAHDHGAAHHHFHFBFBGBHDADADAFAE,False +166,17.0,18.0,17.0,16.0,20.0,19.0,17.0,15.0,CACAHAFBDAAADADHBGFAFDGDGDGHHFHFGFGFHHCAAEBFBFCFAHEBABEEGEGEGEBAHGDCDGEBCHEGDGCFCEEFECBCFHBHBHBADDFBFBGDCBCFFEGCAEGEFBACDCECECFDDADEEEGHBHB,False +167,15.0,4.0,11.0,15.0,21.0,12.0,17.0,17.0,HHAHDEDGHFHEHCHGFGFCECEGEACFGDGDCDCHADCEHEGGAEEBEBFHHHCHCHCFDAHAGDGFGDDHEEGCAEDEABAEGEGHGDDFAAEFGAGAEAFAFDFEEBED,False +168,8.0,4.0,9.0,2.0,9.0,7.0,3.0,7.0,ECECBCHFHCGFGFEEEHEHECAAHAFFBAEAFHBGAEAHDBDACCCFC,True +169,16.0,14.0,9.0,11.0,11.0,11.0,12.0,11.0,DFDFDGAGAGAGFGHHACBHBHGFFDFGBCEAHBDAEADACCECAAEABBHEAEAEDEDCABABCBGGGGFFACHHBDBFFDFEEGBCDHEHBHB,False +170,4.0,2.0,1.0,1.0,6.0,4.0,5.0,2.0,GGDBEEEEBEAGFFCFGFHAHAEAG,True +171,28.0,14.0,20.0,10.0,8.0,25.0,20.0,36.0,HCHCDCGCDAGAGHGBABAFAFCFAFDFGFGEGHFEFHBHGFGCHEHABFGFHHHCFDACHEFBHHHCHAHGBAADCHBHBFAAAHHHFEGCGDAHAGFBFAADAEACFFGAEAGABFCHCBFDEAGAHBHBAAHHHFHFHCCACGHGHDHDHCHCFCBGF,True +172,3.0,11.0,4.0,4.0,5.0,7.0,5.0,5.0,BBBEBHHCCFEFGFGHGBBBGBDFAFACEHFGFHDBDBABCDEE,False +173,8.0,13.0,6.0,15.0,4.0,10.0,15.0,7.0,ACDCGBGFFFGEGBGFHBHDADHDFGBGBGHCDAGGGCHDHGADDDDDDEBBHBFBFGFAEADGCCBDBDGAAEFBFB,True +174,10.0,11.0,8.0,10.0,13.0,7.0,14.0,11.0,GCGCGCGFGEBCAAEEHEAEHDHDGAADADADFBEDECHCGGGHGEEHBHAHABFBEBHFADGDHEECHBBFBGEGBGDCFBFD,False +175,23.0,12.0,12.0,24.0,26.0,34.0,26.0,24.0,CDBFHAHBGAAFEGHAFGCAFGFGBGBEBEAFGDGDFDADCFGEGBFCHABFCGADHFFEFHFEFEFEDHFGCGEGEAABEGAGHGEAFAFAFCFAEDEDEDHDHDHFFFGFHACEFHHHDHDAGFDFGEGBGDHDBABAFEEEHEBGFGEEAEAHHFDDDGHGHDFCFCACHDDEDEFHC,False +176,18.0,8.0,20.0,16.0,15.0,17.0,11.0,11.0,FCFBECGAFAFABAEEEEDCDAECEDGAAADFHBDBECEHEABABCDCHBGEHAHAGAECHHHADCCCCFCDCDAGCFFEEAFAFGDDFHFHFHDBGGDGDADFGCECFCGCDCFF,False +177,13.0,12.0,13.0,12.0,6.0,11.0,5.0,9.0,DABFHGHCBDBDCFFGABAFEBACAHECGDFFHFHFDFEFCHCBCBAECGCGCHEAEADDDBDADAHHBACABACDCDBFB,False +178,7.0,14.0,10.0,12.0,19.0,22.0,10.0,9.0,FDECFBFDFDFHFGCEDEDEFHGBACCEGGAEBEGABFDFDFCHGHFFEDBFBFBFEGEHADAEFEFEFEABCFHDHDAECFCGBFBGBFBEECECDBEBHGH,False +179,2.0,2.0,2.0,1.0,5.0,4.0,1.0,6.0,HGFEHEHEFEDAFHFEABBCHCH,True +180,2.0,5.0,1.0,3.0,3.0,4.0,0.0,0.0,FAADBBBBEBEFEFDDCF,True +181,6.0,7.0,5.0,2.0,1.0,4.0,3.0,6.0,BHBDBAAGAHCHFHACAHEHBBBFCFCACGGDBF,True +182,2.0,3.0,10.0,6.0,8.0,6.0,4.0,4.0,BCBCECEAEDEDHCCCCHEHEGDGCFFFAHGBFFFECDDECGD,True +183,27.0,20.0,35.0,20.0,19.0,18.0,17.0,19.0,CHCHCFCBDEHBHEHCCCCBDBAADFFECCGCAEAFAHCFGDGAGACABFEAHCBDBDBDACGDEDEDEHEBGDGDCAGABEBEAECEGAGFGCABFGFCEAEAGACFCDCFFGFEHBDBDECACAFHBHCHBHBFAHDBCADHEHACAGDDDGCEBFBFCCCCGAHCFCACAHH,False +184,21.0,29.0,29.0,14.0,13.0,23.0,22.0,20.0,HBBEFAHAHDHCHCGCBCAFABDDHDFAAADBDBEBCBCBEACGCGFFBFAFHGHFCFEHCHDADFCFCEDBGBCCFCFGFHCHCACBEAFBECFCDAGGCGFGHGFGEGACCDCBHBACGFGFHFBFGEGBCHCBCDEBBCHGGBGBDDFAAAEBEBABHBABHGEGBHA,False +185,16.0,21.0,7.0,5.0,16.0,12.0,3.0,15.0,BBBHGHBACDBEAAAFDHEHAGAGAEEEHHCAEAFBBABFBCECAFAFBFHFEDABBBFBEBEBEBACHFHFHDHBFEAEBHAFCHEDECEHBHB,True +186,26.0,34.0,20.0,22.0,24.0,21.0,26.0,17.0,HFACACHCBBBBHBGBEHFHFEAHAEAEFDBHECAHAHDDBGEDCBEGGFGECAAADBEBGCGCFCFCFBFBFBAGCBBABEHGCGCGFGBBCHCEDAHBCEAEHDBAHGGDDDDHEADDDDDFFGBGAGBGBEBABDBDGDGBFBDBDBDHEFEFCFEAAFGEBCGEGBFFGCGAABAGCHEEEAFAEA,False +187,3.0,5.0,0.0,1.0,1.0,2.0,2.0,4.0,DEBGHGAFBFHHBHBABA,True +188,8.0,11.0,10.0,11.0,8.0,19.0,14.0,12.0,HGFBFHFBFGGAHDDEBAHFHFHFCEGFGFGFGBGEGBCEEAFDBBBHFHDBDBGACHCHFGCGFGCGFBCDCDFFAEAHAEFDFDHAECDCD,False +189,24.0,32.0,23.0,32.0,21.0,21.0,20.0,22.0,BBBABAEECDDDEDEHEBECEDEDHHHFHFDFHCDAHAHDBGBGEGFGFGFGFBAGCGDFBFHDHBBCHGHGFAEBEDCAAGFDDADADBDCFGHBABDHECBDBAAHADAGCDCBABABGBHDCGCBCGFEBDCHAHCCCFCFEBABHDDBGBHHCCCGBABDBCEEGHAFEFEDDBAFFFDFDCEAEAEGDBD,False +190,13.0,10.0,11.0,9.0,7.0,16.0,9.0,11.0,AGCHAGCBAHCBGBEBEACADADHDBFBDDAGEFCFCBHDEFEFHFHGHDFGFACAEFHAEAGGBGFCFCFHFDFCFCBBFDAHAH,False +191,14.0,3.0,6.0,9.0,14.0,7.0,4.0,6.0,EAEFDGEEFCCCFCFEAAAEADCDAEAEGGAFHHHHEAAADADEFEBDBAEGECEADFDHDHB,True +192,6.0,4.0,7.0,3.0,3.0,3.0,1.0,4.0,CFGEHCCFCBCEAEHCHDADADABBBACAFH,True +193,29.0,36.0,21.0,12.0,18.0,14.0,23.0,24.0,BBHFFFCEHEGEHDHBGBHBHDEBHBHBEAEBDBFHFHEHABADACGGGADBBHHFBBBAAAAABECDCACHCAGACFCFAEAFAFAGGDAEBDBHBEBGACBHFAFGFGBBCAGGBGHDCBBDGEHEGEACACACEBEBCACAEGDGHCBDGHGHBBABCCHCHCHGBAEAGBFBG,False +194,6.0,3.0,5.0,1.0,2.0,4.0,8.0,5.0,HBHGGFCFCACAEABGEACDCHBGGHGAGAFHFG,True +195,3.0,6.0,4.0,7.0,9.0,15.0,5.0,10.0,HAHEHFGFHHGHGFFCFCEDEFEDBGBDEDACBDFHEBFHFHFEFDFCFDFABEBGHFE,True +196,2.0,2.0,8.0,2.0,3.0,5.0,4.0,4.0,CCECHCDCDCEBHCGEHBHGAAFFFFGFGC,True +197,0.0,3.0,4.0,2.0,1.0,2.0,3.0,2.0,DBHBDFCCCGCGBGEFH,True +198,9.0,8.0,9.0,4.0,11.0,7.0,12.0,11.0,AAAFADHGGGFGCBCBCHEGEFEHDCABDHGEGEGDACBFHFBEBGBECEHAHAHGBECFCGEGAHEHCHF,False +199,9.0,8.0,10.0,11.0,7.0,10.0,5.0,6.0,ACADDFDHDABGCDEBEHAFFBECECDBBABAFAFAEAFHDDDHCCDCGCGHGDGHFCBCBFFEFE,False +200,15.0,9.0,5.0,13.0,12.0,23.0,15.0,22.0,CHGFEHBDGDHEHAHDFDFAEBDAHEFEFEGGGGAAAGEDAHGHGHECEGFGFGAGBFEFAFBFBGBDFAFHDHBHFHFHGDEDHFFCFEDBDHFFFAAHBHAHFCFDHHCHAA,False +201,8.0,4.0,6.0,6.0,2.0,3.0,2.0,2.0,AGCFBBCBCDAHABACEHDADADCDADAEFGFC,True +202,15.0,30.0,30.0,30.0,15.0,29.0,25.0,23.0,DFBBDGHBCEDBFBHBHBCBHEGGGEBEBHHEHCFFHFGBHEGBDFDFGBGDFDFHCEFHCGCFDHDFDEHADADEBCFEFDFEFECDAAHFGDDDCACACACACDBABGGEDAABBBGCACABFBGDCDAGGGGDCDFFFGFCBBBDBDHECGHGDGCGCHCHFBFHHHDHCEBFDFDFCFCGCBCBCFCDABHCG,False +203,14.0,19.0,19.0,3.0,12.0,14.0,16.0,22.0,CHAEADAHBHBHBHBGGDBHFHEAAABCBGEFCCHFEBHCHABABFHCCCHBHAGAFCFBFAAAHCFCGEGEHEHEHFHBHEGFGHBEGGGCCFGFGCDAECGCBBGBFBCHCHCGBFE,False +204,9.0,15.0,19.0,11.0,9.0,19.0,20.0,15.0,FAAACCHEGCGDGBHDCCCEBAHDGDFDBDBHCFGFCFCBCBFGFGHGBFBHHHFHEGBGBCAEBCCCFCFCHGAEFEAGCDHGHGFGFGCGBGBGFDACEBFDFDEHEDGHABFHF,False +205,20.0,16.0,16.0,34.0,30.0,20.0,29.0,29.0,CDCFGDGDEFHGHEHEGGBGBGBHBGEFECDCEBGDAHGCBDDGDHDHEBEDDDDHAFAFDEGCHEGFHFADBEEGAGDGDHFHBDEAEAHAHDDDECGBADEHEFEFDACAGEGFGBDEDECHHHEAEFFBADDDDAEAHHDHDCCFCAAAHCFCFEGHHHHGBGBDCHCHDFDGGEGBFBGHFAFEGEGEAE,False +206,20.0,18.0,16.0,14.0,21.0,4.0,6.0,11.0,ABABAFADEDBAECHGDDAAHEBBDBACECGAAAACHEFEBCDHGBCECECEBEFEAECBCEHEDGAHACADAHACECGDDEEECEHHHFECBCBEBHBDBDBDBAGDBA,True +207,1.0,3.0,2.0,6.0,1.0,4.0,1.0,1.0,FCADBDBGBFEFDFHCDDD,True +208,5.0,3.0,5.0,6.0,4.0,0.0,1.0,2.0,DCCBCDCDCAAAAHDHBGAEEDBDEE,True +209,9.0,6.0,7.0,6.0,5.0,8.0,3.0,2.0,FCFEAEGDADABCBCFGAGCFAFABABCBDHCFDFEFEACBDHEAD,False +210,21.0,21.0,15.0,16.0,11.0,15.0,20.0,12.0,CACFFACCCEHFDBGBGBFHFAGDGDADACGGDGBAACABBECECEGEDHDHCABDFDFDAGHGHGBGBFBGEGBFDFAGAEHFDAHEGABABFGAGEBCCGCHBDEDGBCACFBFAFHDBEBHBABADAH,False +211,10.0,24.0,13.0,13.0,14.0,11.0,16.0,23.0,EDEABACHGHAEGGBBBBECECEBBBAHGHGHCBCECDCBFBHBHFHFHFBBDAGFEBHAHDHGCFAGABCDDBEBEDHGHBCCACFDDBAHHHGBGBGEGEGHGFEFHHHDDBBCDEFGFHDH,False +212,19.0,7.0,17.0,13.0,17.0,11.0,21.0,24.0,FGCAHAHFGEHAAAAAHGDGHGFEEGDHHAEAEDCDFGBGDHDGFECECGGEEHGHGHCFBBHBFEEHGHGHDHFHDHDAAAHDECAAACBCECACAHFDFCCCCCCGGGGGEEEDHBHEFCGDHAHAB,False +213,10.0,20.0,7.0,7.0,13.0,11.0,10.0,5.0,HACBEBEBAGEEHEDAFABBFEEEBGBGBGBAAEBBDDFDFDFHCHDDAFECHBBAFAGGGFAFCGBEBEBEGGBFFCBCBCB,False +214,6.0,9.0,11.0,6.0,13.0,4.0,11.0,19.0,ECECBCFDGEGBHEDDHGEBHHGCGCBHHHHHEHEGACABADHFFGCGBGHDDCEEEEBEFHAECBCHGHGHBHAHAHC,True +215,3.0,0.0,0.0,3.0,3.0,2.0,6.0,5.0,HDFDHEHGGGGHAHAEGEAFDG,True +216,1.0,8.0,11.0,12.0,14.0,8.0,9.0,12.0,GEBDBDCCADDBGFGFEEGEGCDCEFEGEBEDCCFBHCEDDGEHEHDDFCHHHBHBHBCDFDEGEGCHCHEHFHF,False +217,10.0,10.0,22.0,13.0,14.0,8.0,15.0,10.0,DCHGECECEAGHEFGACFBGBECGCAEBEHHAGEGFDFDFHEDDCDBFBABACDDHDBDGCCCGHGACFCFDGCGCBCBGAGACECACBCECGDHEHEHECD,False +218,7.0,10.0,14.0,5.0,9.0,7.0,7.0,16.0,CFCECECDHHHHHHHHBBBHEFCCEBDBABAGDFDHCHGACCHCHEFEGHGDACFBGBCEEEFGHGFCBCHAAAB,False +219,15.0,20.0,16.0,12.0,13.0,12.0,14.0,14.0,AGAEAEAHGHFBFEHBHFGGEEHCFCDADACBDBFBCBFGFBBBCCAEGDGFAACAHBCBCDAFHFHECAFFEGEBCBGGCDCDCDEBBDBDBHHHHHDGAGDCHCAGEGABBEBE,False +220,0.0,1.0,1.0,0.0,3.0,3.0,1.0,3.0,HEHEHFFFGCBE,True +221,4.0,7.0,18.0,11.0,9.0,20.0,14.0,16.0,GGGBFCCCFBFDGCFCFDFHFHCDCDHHHGHFDCAGHCBAEEFEFEFHAEFCHCGEFCCCHCHEHCDCDAGBGBGCDDFDFGFHEHDHFGEGFHFGFBB,True +222,19.0,32.0,14.0,24.0,24.0,23.0,30.0,29.0,EAEAGFDFDCBHFAFADGBHBDAGCDEABDFGEEFFFEEAECHDHBHDGAHHGBGBGBGHCDFDBDBDEDADHFFAFEFGBHBGDCHEDABGBEBCDCHCBFAFBGBAHFHFGEDFHHHBBBBDBDBDBGEGBHEACCHEGEGEDEHECGHGFBHGHCBGAGHGHGEGEGEHAHAHFCCEFHFAGBGBGDADFBB,False +223,6.0,4.0,7.0,6.0,14.0,14.0,8.0,15.0,CEEFAGEBDFAHHDHFAFAHBFFHFCFEHHHHFDEGEGEDEDGAGHDFGBGBEFGFHHCHCHEHECFCACEEFE,True +224,11.0,10.0,13.0,13.0,21.0,14.0,25.0,19.0,CGBAEGEGEHHCGGHGCCBCAEBEGHCHDFDFDFEGBDFDFEFAGDGAGEGCGBHEEGCGBEEGEADACECABEDCDFFFDCAGAGHFHAHGEGEGEGBGBGHHHHHHDABCEDHHFFDHEHEGFF,False +225,6.0,19.0,5.0,11.0,12.0,6.0,9.0,5.0,GBHBDBABHBCBDEDBGBGBEBEBCCFDHDFEBBDDEAEAEAECFGFGEGABCFGBBDHDEFBGBGEEABHDD,True +226,11.0,18.0,23.0,14.0,12.0,26.0,20.0,26.0,EFEFEFGDCDFBHBHADECHHEHEFGFGHCBGACBGACFDFGFCFGFCCCHHHBHFHFHDADFFEBGFFFFFDBCCFCFHFCDGEHDFDBDCAGGHHHHHHBACGCGAGBGHAAAFFCHGBGCADGBBBCGDHEBEBEBEBHCHDHCCCG,False +227,23.0,20.0,28.0,18.0,25.0,23.0,23.0,21.0,FCCBCEFEDAGGBEHCHCHAFCCADFFHFEFAHCHDGCCHAEDEDFDGAGAGAGEFEBEBHHEFEFHFCGDFBGBDHAHBGAHFFFBFCDDADCDEEAGABHBHGHCHCABADABCHCHCDFGHGHBAFFEGECBGADCECGCGCBFEFDFCGCGDEECAGAEAGAGBBBBBCEEAEDECE,False +228,5.0,3.0,9.0,5.0,8.0,2.0,3.0,5.0,DDDACEHGFBCEAECCCCCFCEHEHEHEBCDAEBDHAGAG,True +229,15.0,19.0,18.0,23.0,23.0,15.0,10.0,23.0,HHFHGHEBFHHBCBDEEHCBGBAHAEDEDCGCGEBBDDDDEDBDHDFDEDACCEEDFCEEECBCBCBCDAFEHCFAHBEDACAGHHHHHHHAHGFACACAFBEBEFFFFFDEBEAEGCBEEDADACBHGCGBGDHDHDFDHDEABF,False +230,15.0,10.0,14.0,14.0,7.0,9.0,3.0,6.0,EDADBFADCDCDEBFBFAFEFEDCBADFBFBAHACCBCGEHEHBCCAGDCFFBAAABAGACHCHDDCCCEDHDADADA,True +231,21.0,19.0,19.0,16.0,21.0,13.0,13.0,23.0,EHBFBHBCDAEACABABEHCAAAAAEBDHDCECACAHGFCFBFBDCCBDBDECHCGCAAHHDDCDCDEEHHHADAFBFGFGDGFGHGAGEEFEHBBDBGHAHGHEBCCACACGEDEAABDBCEDEFEHBHEEEHGHFHEHFFGHB,False +232,10.0,11.0,13.0,7.0,8.0,12.0,12.0,9.0,EFGGGHCHBAEHFDFEADAHBBFBCGFGBCBCBCFHFAFAGCGCEBEDCCCHCHDGGGCGCADFEBEBDAFAFAHEFGBHDA,False +233,16.0,18.0,26.0,21.0,12.0,11.0,22.0,9.0,GBGCHBGDHEHDGAFCFCGCBBDDDHHGCEDEDCDBGBEBCCCCDBGBCACBGGEHEDGGAGACFCFCHCGGDGABDCCCGDBDEDEBBCHCDCDBDAGECECAFEFBFEAGAFAGBGAGDDDACAFAFAFCHBA,False +234,8.0,5.0,2.0,10.0,3.0,5.0,9.0,5.0,GAGBBEDFDFDBDGDAEADHGAGHBDGDFDFCGAGACABAGHHHFED,True +235,28.0,16.0,21.0,19.0,24.0,21.0,12.0,20.0,EDHFBEAFADABHFHFCFHFACCBBBHAHDHBADGDBCBDFEFDHHADACBHBEAEDDDGAGACAEHECFCECHHHEABFCFEEHGAFFFADADCDGEEEGEBECEBBCACAHAHADADFFAFAFHGDEEFEBCGCGCGCDCAHBGEEFGADECECAFAHA,False +236,13.0,6.0,14.0,8.0,9.0,13.0,7.0,14.0,FCFAFAFAHAHCDCDGFFEFECEDBCECDCFHEEFAFACHCHCEBGDHEHFHAHBHDHFCGGAGDHHACCBHDCGFGBAAEABA,False +237,4.0,7.0,4.0,12.0,6.0,4.0,7.0,10.0,DGGHBHDDDGDGCGCGADBHEDEDAGFCFEBDHDEBAHAFEHEHCHDBDBHFHB,False +238,25.0,27.0,17.0,20.0,11.0,20.0,27.0,24.0,BGGGHACECEFEAEDBDBHCGDGDHDHBHBHAHAHFBFGCGCAHFHABABEFFDDAAFHFHDAGADFDGBACCCHGHDAACHCHGBEBCCCBDAFAEGHAHGHGEDBDBCBHBGFEAGAGBGBABDHDGAGADFBFGFGCAEBGFFEHBBGDGBBBFFHFBFCDAGCGHDA,False +239,27.0,19.0,14.0,12.0,26.0,20.0,17.0,18.0,CACHFHBABHBABAHEGBDDEBFAFAEACABAFAHAHGHDFEGEFEBEBEAFCDCHABAGEGEDFBGBACAFDCDCAEHEHFHFEEEFABABCGEEEGHDHAHBHDFGEGBAAAFDHECEAGCGEBEDCDHFAFAGAGBGFFCGCEHGFEBEF,False +240,13.0,5.0,13.0,8.0,10.0,9.0,13.0,11.0,HCHAGAEFGBGAGFGCDCAGAECGCGEFEDHGFADADACHDFDGBCBCFEDEFEFBAHHHHHHAAFGCECACBCGEHEADCG,False +241,15.0,13.0,22.0,21.0,14.0,24.0,13.0,15.0,CECEBACABEFHFGBEFDCDBABGDAEADCDHGFGFDDDFDFDFGFEFGCGEAHGHGHCFCDABFEHHABCECBCHFHCACFBFBHBADFEFEFDFDHDHCHCDEDAGGECHAFDHCABFCFDFDGBGCFCACDCEA,False +242,10.0,3.0,9.0,4.0,10.0,22.0,6.0,6.0,CBAAFFFFGBDAFFFFFFFDGAGEHFGECEFEFHCHCEEEDCFAFAHAFBDEHGHCFEFCFCFEAAFAGC,True +243,16.0,18.0,13.0,25.0,8.0,14.0,16.0,17.0,CFHGHAFGFCFEDAGEBBFDGBGHDHAHBGBGBDCHHEBDBDBDCDHDHFAGGHGHABADDCDFBHAGDDDBCACECAGEGDDHDFDFHFHCGCGCDBAFAFDBDEFEACADADADBCFAHBHGEBB,False +244,14.0,10.0,26.0,18.0,17.0,28.0,19.0,21.0,HEHEHDFDFEGEGFGDCBBDAFHFHFDCEGBBDHFAGBHFHCECHCGAFCCDDADGHGCGAGBDCDHDHDACFCFGACEHEGDGFCFCFCAEFHHHFBFDFDCBCFEFCDGAGDEEFEFHFHFEECCCAAABECFHACECFAFGFCBCGHGHG,False +245,30.0,27.0,23.0,25.0,28.0,19.0,14.0,26.0,AAACACBCAEDEBEFCCHCAEGEDEFGAGCEAEADFEBBBEFAGBBBFDAEAEHHHHCFCHCHADFDEBHFACBFBGBFBCHHAHAEEGHHEAEGHGHGHGCAHADADAEAEAGDGBECHDDDDEFFDCDCACAFBFHCHEHEADFBFBGBDBCGABHBHDACCECDDBDBDFDBEEEEHCBAFHHDBBADF,False +246,9.0,17.0,16.0,9.0,17.0,6.0,11.0,16.0,HGEGACAHDHDCDEGFHBHDHECEDEDFDEEHCFCFHBEGGFABEHHHHGAABCCDBEBECHCHFBAHGCGABCBEBECCCCCEGEBBBBDBABEBHGEGA,False +247,10.0,6.0,15.0,20.0,23.0,16.0,16.0,6.0,AFDGEGEFEDCDFHEGEGFGBCACECEAEHEDDHEGEDEFGDDDCCCCGAGEDBABEFEFDGDHDGDCBHBGFFCFCEEEEFCHEFGDGFCDADCFCAEGFGBEFDADADAE,True +248,1.0,1.0,5.0,2.0,5.0,7.0,7.0,2.0,EFCFDAGFCFGFCHEHECEGGCGDGFGFBE,True +249,20.0,25.0,23.0,25.0,18.0,22.0,28.0,20.0,DGDBDAABACHGHEBDCCABFBAHGGBGEAAGDDFGFAHADADEDFHFHGGGFGFDHDEDBACDGDGBFACABBGBGEGEGECFFFEABDEDHFAFGBCBCACHHFHFBFBFHCHCHCECDGDCEHEGCGBBFBGEFEFHCGCBHGDGFHFEABCCEBDBHGDGDGBHCEDADCDCBAEAC,False +250,27.0,24.0,20.0,16.0,26.0,17.0,25.0,11.0,CHCBCACHBABAGHFEEBEGECEBEBEACDGDHHGAAFGEGABEGAGEGADADABAECFGBGAGAEBEADFGFECACGGFGEGDGFBFGCGBFBFEAEBEFAFAFEDEAAAAGBBBCDCDGECCCBCFADABHDEDEGEAHHBDEDFDFGCCCDBBHAHGBCBEHF,False +251,23.0,19.0,20.0,25.0,22.0,22.0,28.0,26.0,ACACGEBFHHCAGAGHGHGCGCGBEHFHFCAGFGCGHEHAHADDDDAEEEECCFBGHAHAHGBDECFADGCECEGEGDGAADBEAEFHFDGDGAEAFDECBGECCHDEEBGBABEHHAFFFFEFDADHBHBDDGGCGCBAGAHABDBDEFEBCBDHGHGFDFDFDFHBAFCBDBDFFGGCHHHDH,False +252,22.0,23.0,23.0,11.0,21.0,24.0,27.0,23.0,CGGAGEGECECECDBFFFHAHGEGCGAGACEDBBBFGFGHGHFCBGHFHBHGEAHAHABDHABABDBECHAHFCFEFAAGGGBGFCDCBEADADHFHDHCEABCGGGFGAHEEAECCCCGBBEHEHBHBHDCDFFAFBFCEBAGAGCCBCAGFDHHEHFFFCFEFBBEBFGEGA,False +253,21.0,15.0,11.0,10.0,10.0,18.0,15.0,19.0,CFCEEFHBGDEEFEFDAGAHAHGHFHFHGHAHAHGFFFGBDBGAAAABABGBFBFBEACGCEDHFACCFFFGECBAECDGGAFAHDHDHBCCGHAHAFAEDHDHGBBABDFCAGABHBH,False +254,16.0,7.0,14.0,11.0,13.0,17.0,11.0,13.0,CDFHFHECACEDEAECCHFHFHGHGCAHAGAGDEDFDCHCFDADFEGAAEAFFDEDCCEDBFCGCGEBEBHGAGFBABAGFHDHAHAEFFFFFBEBCGHACA,False +255,14.0,24.0,17.0,17.0,23.0,22.0,12.0,11.0,EDGFFFGBBBCACDDDBDCFCFCEEAFGFGFGFDBBBFBDCFEFADAHEDBDFHAAGHCHFGACABEDEDEAECEFEFDAABHHAHCECBFBCBFFDBDGHGHFBCDCECEDEAAGEGFBEBCBEEGEBEBEBHCEFBBH,False +256,15.0,18.0,13.0,27.0,17.0,28.0,20.0,24.0,FBDBCHCGDEDCGAGAGDDFBBBFFFFEDACGCHAGGGEGEBABFHFEDHFHFCBDGHGBGDHBCBGAEHFAFHHHDBDCHBFGFGFHFHEGEBDFFFHAHGHCHAHDHEBEFEDGDGAFABDBEHACFCFCEDADEFBDDEAEADFDFHFHFDGHEDDDDC,False +257,6.0,7.0,12.0,13.0,9.0,11.0,8.0,10.0,DDACHGHGHDHEFCCEGEGACCDCDCDADHBFEFEDEGCFBFDFBFEHCHDAGEDECBCBHFGFDFHAHCGABDBF,False +258,17.0,20.0,27.0,16.0,18.0,18.0,19.0,20.0,AGEHCDAGCGFGDCDCHCACDFEAGFGAAAADADCCHGHGHCCEEEGCADACAHECEGDGFBFBFCHCHCBBDBDBDEFCGCBBBEHFHACAGBCHFFBCBCGGGGHDBECEHEHGHBCAGEDEBFCEEBEBDFCFAFHBADDHFHFHFHECFBB,False +259,1.0,5.0,4.0,1.0,1.0,0.0,6.0,2.0,GGGGBGAHBHCGDBECCBCB,True +260,2.0,3.0,4.0,1.0,3.0,5.0,1.0,3.0,BFBCBFHEEGEHCACACHFFDF,True +261,2.0,4.0,3.0,2.0,3.0,2.0,6.0,2.0,CDCABEHHGFGFGEBABCBGDGEG,False +262,17.0,17.0,32.0,25.0,20.0,22.0,15.0,15.0,DHDCDCDGEHCBGBEBACGDFDCBCFCBCEAEAFCDEBAAEADHCEAEHECDDDBDCDBBFFEFGFBCBHAHFCCECGHDHFHAHACDEHECFCDEAAHABBCHGEGDGFHDDCDGDCCCGCACACFCFDADFGFBFBFEGEGEHDACGDFCFCFGBEBEFCF,False +263,7.0,4.0,7.0,4.0,5.0,5.0,7.0,12.0,GCACAHGHECGCHFGFEDHDHDHGHBAEAHBHFHGCCBCHEGEBHAFADAF,False +264,6.0,6.0,13.0,6.0,11.0,2.0,9.0,8.0,DCFBDBEEEEEEADAHGHGCGDHCHGEACBCGCAHEHGGAFAGCCCCCBEBHDCBCEGEHD,True +265,20.0,25.0,22.0,32.0,26.0,23.0,23.0,27.0,DCHBHBCEHHGHDCGCAHHGHDEEHEHBBECDCGBBACACADDDDDFCGEABGBABEBEBEACFHFBEGHFBABCGHGEGDDDEGAHAEFBFDGDHBFGFCDCDCDFGFHEBEHEHBDEAEACBDADHFBDDDDAFEFBGGGGHGHCHEHFCFGFGADDDDBDADHFEBEBECEADACBCFAFHFDFGFAEGHHCCFE,False +266,7.0,6.0,7.0,3.0,4.0,2.0,13.0,8.0,BGHCABHHCHGGBDBABAFCGEGDGAHCEEGEGBGCAHAHACGCGHGFGD,True +267,8.0,8.0,22.0,12.0,15.0,14.0,10.0,10.0,DCBAAGBEBEHECCCCFEDDDFGHGDEDCBCGEGEGEBFFAEHECFCHCHFHDCDCBHGGCCBCFCHHFAFGHGDFCEADCDCDCEBFAFACECAFEFE,False +268,20.0,11.0,17.0,15.0,11.0,11.0,19.0,11.0,FACAFGDHCEFHAECBCBEBEAEGBGBGFHCCBCAHDCFCDGDAEEEFBACADABACECHGGDBDGGGFHEHADAFGFGFGHGHGCFCDCDEGAAAABDDDGHBACACDGDHAGA,False +269,6.0,1.0,7.0,4.0,8.0,4.0,3.0,3.0,DBGECEAEAEAEAGDGFCHCECFAAHHFEFCCDEDC,True +270,18.0,16.0,20.0,26.0,19.0,21.0,22.0,23.0,BFBCDDGAGACDBDGDGDADHCAEACGCGDEBGDFDCDBDGHEHCFFFFFHFBFAFHDDGBHHHHFEFABGGDGDEFCDGHCHEFCFHBADHHCFCBGBFEEEEEFEDEDAFGHGDGCACDEAEACDEDHBHGHBHBHCDGAEACCEHGHAHACAGACBEBGFDF,False +271,0.0,3.0,1.0,4.0,2.0,4.0,2.0,3.0,HFHFEFDBEBHFDDBDGCG,True +272,16.0,16.0,17.0,14.0,11.0,14.0,8.0,16.0,FCHEHAFAFBFBDHGAFABBCDCDHBHEFABCHCHDAGABEBAHDHDFCEBGDFECECECEHECACDBDBDCGAGAGACAGBFBGDDACCDDBHEHBACFBFHHHFHFCFAE,False +273,13.0,11.0,14.0,14.0,11.0,17.0,18.0,16.0,CDFDGBHBFGFGFGEDABABCHHDDEDCHCGAGFBFDADHDCDCECAGEFEBEAFAEHEHGGEFBHCHFHFAFDFACGGFGHHDHGHAHCFAFGEBCBGBGCACDCDEHGFBAG,False +274,30.0,26.0,12.0,16.0,14.0,36.0,17.0,16.0,GGHCBABACFGFHFBBHAEAEACADADABABFFDABBFFEFBAGFHFBFCFBAHHHHGGDGFGBHBFEECEFDCHCHBHGEAHADDGAFAFDDBDGFGBEFFFFFGFACABGFFFAABAFACAGAGHDABABGDACFEAEADBBFBEDEAFFBFBFCFCDBHEHEDF,False +275,6.0,13.0,13.0,9.0,7.0,9.0,12.0,6.0,CEFBGCCCCHDBDBCAFDFDFGFHHCCGCGBGDGDBCBCBHFGAAEGBGBFBGBGECHCDAEGEFADAHEDEBBF,False +276,7.0,5.0,3.0,5.0,6.0,7.0,3.0,5.0,BCCDFEFEFEBADABCFDDHDHAAEAGFGFHFBAEAGHBHE,False +277,6.0,5.0,1.0,2.0,3.0,3.0,6.0,7.0,HBBFBFDHCGEGAHAHGHGFEBHBGGAEAHADA,True +278,4.0,8.0,15.0,16.0,12.0,11.0,10.0,10.0,DHCHAEEEHEHEFEHGFBHEDEGEGFCDCFCGCDCBFFFCEGDBHFDDADGGCGDEDEDGACDCFCFBGBHBDBCFCHCDDDHCAB,False +279,15.0,15.0,14.0,9.0,20.0,30.0,10.0,19.0,EAFFEFEFHBHBHBHCHCFAAACFCAHGBGBFEEBECEGEFDCEFEGCBFHFBEAFDBBGDDCGFDCBBHBHFEFEHCHFBFDGCHFHFHFGFGAAAAEECEFDBEFECEHDFCFHDHFFEAAAAAFGFHFH,False +280,20.0,27.0,17.0,23.0,26.0,20.0,26.0,25.0,AEDGCEBACABABGBGFDCEBHBCBCGHBAEACBHHHCDDEGFHAAFABCEHDBDBDFFGFCBGGGFGEEFEDEAEDEDHHHFHEEEGEGCBCBHBEBGBGECEAEHGHABBBFHEAFGBGDGFFEFDGDGDGHGDAFAGDHDECEHHHAHDDGHGCGEBEFABCBDBFCFCFHBADADFDAHH,False +281,10.0,6.0,6.0,8.0,8.0,11.0,10.0,7.0,GBFFDHAEAECDDBEGDGAEECGGGDHDAFADAEAHBHDEFFFFBCBCECAFABAHGFGFGFGHCH,False +282,21.0,33.0,19.0,20.0,21.0,12.0,19.0,26.0,CAADABABCEABHBABDCHEAEGHBBCCCCCHCBGGGGHHDHGHGDGDGDBDAAGCBHDFEEEEEEBEBAHHGHEHCCGHFBFBFBFGHBDBHAFAGACCHAHFBCCFDEDEHCHABDBEGADBBCBHEHEDDDDBDEDBBHAHBEEEDBBBBHGGGCEFBFAFBGAHAFA,False +283,12.0,9.0,6.0,10.0,12.0,16.0,15.0,10.0,CFCEDFGCGFHFBGCGFGABEGAGAGAGAFADBHGHDEFHHDGCADEGBBCHDAAAGEBEBABFDFEFEFHFHFHFHGBFEGEDDDEFEA,False +284,0.0,7.0,2.0,2.0,5.0,4.0,3.0,5.0,FBBHBHECBFDFGEHCHEHEBEBDGFGB,True +285,18.0,10.0,10.0,8.0,8.0,13.0,19.0,13.0,HHHFGFAHCCBCHCBFAGCGBABDBDGAFDCDAEAEHDADBHBAGFGFGHEFFGHGHBHAFFBFCFCAAABEEEAGGGAGCGFGAGADAGEHAHCDGEG,False +286,17.0,19.0,13.0,13.0,17.0,16.0,12.0,9.0,DBDADABCGDAFEFEFEDABCBEBGDGFEBEBEBEADBDGHCADABFDADADABGFGFCBCDCFBGGEEFCFAFEFBAGGEFHCGAFAHBHBFFEBACECACBCHAHEHEHCGBEH,False +287,11.0,13.0,8.0,14.0,5.0,10.0,1.0,11.0,ADDCHBHFDEACFDBDBABCBCDDDBAAADHFBFBABEHEHBHBCCHFDABAHCDDDCDAFHFEFEFHFHGAB,True +288,21.0,32.0,21.0,22.0,23.0,17.0,23.0,21.0,CFCBBDADEDEDBDHDADCCCEHEHBFBHADADBGBGDCBBHFAEBDHDFDFBEBHDEDBCECEGABCFGFHDHGHEHAAGHGEDEAEABGFCCBEBCFDFAEGGAGADECFFGFBBHCGEBEGAFABDBHFFAHAHAHBHBEBEBCBABDEGCGCHCHBHBGEGEGCAAGGBBFCCGDG,False +289,10.0,13.0,5.0,12.0,9.0,19.0,21.0,12.0,GBFAEDDDGGFEFDHHGHGFGFGDGFGHHHHEGDBHFGGHECBAGAEACFBBDBCADFGEGDBBBBCBHHFFBFBFDAAAEFGFAFAFDFDFHGGGGGECE,False +290,10.0,11.0,9.0,13.0,3.0,16.0,8.0,5.0,DBDBDCFFGFGABEBEDEFFGFGFAFABHCAFABCDHDADAHBGBDDDADFHCBCDCAAGHBFGFGFCCBFFCFD,False +291,22.0,19.0,25.0,28.0,18.0,24.0,23.0,17.0,FCFEFEFAGEGCGEAAAEGEHFHEGFGDGDEDBDEEECBBBEDFHFAGHCAGAFAHABFBFDDGECEBGFDFCFCDBEFABGEDACACDHDHDFFCDCACHCDBBGCDBHBHCFCDHHHBHBGFGFADDGDCDCHCDCACAGAGCDDABCEGHDHFGGDDEAFBFACACABGBGFD,False +292,22.0,21.0,17.0,19.0,16.0,16.0,15.0,29.0,EFHHAHDCDEBEHEHEHEHEHCFDBCBDHCAFEGGHDDBDFGFGHCFDDDDAFADCGCFDFBFBHGAFCCBBEEAAGAGDEDAHAHAHBHBHBHEHCABABHBCCCHCBBBDAHGFDEAEAFHGBGEHAFBGHAFAFAHABCDDECGCHHGHGAB,False +293,14.0,10.0,22.0,19.0,17.0,10.0,11.0,13.0,FDGGCACGCDCACBCDCDGHHDHBHFGGCCFBFBCBDFDAGEHAHEFECBHGDDDCEBBADCDFDADEEEEDEBHAHAGCGCBDGECEHEHAACADAHFHFEFCCECEDECCDAEA,False +294,21.0,23.0,11.0,16.0,19.0,13.0,19.0,13.0,ECDFDEAGAEAGHBFEFGHBBGBABABGDGCCAGHBHFEFGGCBDGDGDGHFHABAECEAGHFDFEFBFECECEFDHGFGABAEHEGEBBBBEBADFEHEHBDBDADADGBHADADHGAEBBBDCACECBCAAGA,False +295,16.0,21.0,15.0,23.0,14.0,18.0,17.0,12.0,DDBBHFDFGBGBHBFFFFFFFGEBCFCGHABBEHDDDDBBBBDGFHFAEDHDHCFCHCECBAHACDCDHAAADDECACAGABAGEFEBCAEACGDGFEFBGBDBCBGGDDAEFEDGCGEGEDEDGDBABADFHCHG,False +296,2.0,5.0,5.0,3.0,8.0,3.0,7.0,5.0,GHDHFBBGGCGBHEHBCACHCGCGEEEEFDADBEGEFE,False +297,8.0,7.0,6.0,6.0,3.0,4.0,7.0,7.0,GDGFBFEFAAEBDBDBAGAEHBDBHCHDGBGCGHGHAAACHCHAFCCD,False +298,10.0,8.0,9.0,8.0,12.0,10.0,12.0,8.0,AAAAAADGHGAEEEHFHEHEFFAGAFHCDCGEBCBCBFBFAFHFGGCGHEDGDFDBGEDEDCBEGEGHCBEBCCDGF,False +299,2.0,2.0,2.0,2.0,1.0,0.0,0.0,1.0,CHCEABDBDA,True +300,21.0,16.0,12.0,20.0,12.0,15.0,16.0,21.0,HFHGDDEFBFBFAGCFAGBGDHEHBHBHAEFBDGACHGHAHFFDFHFHEBBCBDBDBCFCDCACAEDEDHAHBHECABAGCEBHBGEDEGAAHAFAHADCDEGEGADFGAGAHCDAGADAHCHDDGDGDHFBF,False +301,18.0,17.0,21.0,18.0,14.0,17.0,20.0,23.0,BEBFFCAGAGAGHGHFHDHCFDFDEDEBEBEAGFBCCHCDCBCHHGHEACAEFGBGBEDEBCDADHFAADBHBHCHFDFDFHGBGBAEFGFAAEHEHEHCCGHDDDGHCCCCAABCGCGCADACABFEHDBCFHGHGDAHHDFGBGFG,False +302,17.0,9.0,16.0,15.0,18.0,20.0,16.0,20.0,CFEHGDGCGHFADAFGFBFHABACDEDEDGAEHEHCCCBCEFHGHAEAEAHAHEHEHCDFFAHDEAFDFGBGDHHFHFAGGFFBEHEAEAFFFDGBGCGEECAFFHEHEHDACBCFCDDDDCBCBHGAGCG,False +303,17.0,9.0,12.0,14.0,11.0,11.0,11.0,15.0,DFDFAGHHDEDEHEHECGFACAEADDHDEDCHCECFHBBBEGHBACGGGAGAHDHAAADEHEAFADGDBDFHFGBABABHBFCHAHACCFCGCEADFCFG,False +304,32.0,22.0,21.0,20.0,17.0,21.0,22.0,16.0,HABACGCBCGHGHADEGABAFHHGFCCGFFFHFHAHAGACFGEEAHAHABABFBAEAEDGDBDFFFFEGHGDDDCHFAFGECACECECEDFBEAAFBCGAGECECFCFCBGGADADGHACAEBHAHABGGDDADCDADBBBGHEFEDDDGEFBDBDBCBABCBAAAACFGB,False +305,22.0,14.0,10.0,9.0,20.0,15.0,19.0,12.0,GAGABHEFGHGABAEDECGAFABBEFEAECCAAHGHBEEEEEFHFGFGAEAGAGDGHGFAAAHAGAGFBECEFFBBGHGFCBCGCADEDBDBDBDFEECEBEDGAAEAFAHHBFCFCDHGH,False +306,7.0,13.0,6.0,7.0,4.0,5.0,5.0,12.0,BABAFAHDFDGBHHEHBDACHGHGDDBDHFFAFACEBEBEBHBCAHBHDHCGBHBCGCB,False +307,27.0,19.0,23.0,17.0,31.0,29.0,21.0,17.0,FADCDEGEBEGHDAEFEAEBHBCBAFAHAFGEGFBFCAHAHCCBDFHGCEFFCFEFEAEAFCBDADADHDFBFBEBADFCFEFBFBFDFCFGFEAHBBCCCCHHBHAAEGEBECEGDAEFDGECEFEHGAGEFEDGBABABHDHDCDCGHAEACAGFCECGGHEDCFAAAGAGCEHEGEGFGFE,False +308,16.0,23.0,23.0,25.0,22.0,21.0,28.0,27.0,BHGEFEDACAGADADGDGDBBFBCGGHGFCFCEHHDCDCEGFCFBEBEHDHCHCBEDDHBBEBGGFDECHCHCBFDFBGEHEGEDEGAHDBDAHGBGDGBCFCGCGBBAFAFABBBFGFHAHAEAGFFFGDDCABHECEDEBEHDGDEDEGCHCDCACHCAFGGGHFHFHGHGCAEHHHHDDBEF,False +309,11.0,10.0,14.0,4.0,9.0,15.0,8.0,17.0,CECHBGAHBHAHGCACBEFEFDCCCCCBCDCGAFFFFFBCBAFHFHFHDAEAHGHBHBHEHBHCGFBHAAGEFEFEGHAHDFFCAEHG,False +310,7.0,7.0,11.0,8.0,8.0,14.0,8.0,4.0,AFACGFEEDBGHDDADFCFCFCFDBGBHEHFAGDCACFCFEFBDBGBEBFCFCFCADGEGEAHCFGE,False +311,1.0,3.0,3.0,4.0,1.0,4.0,5.0,3.0,DHHBHDGDGCFAFGEBCBCGFGFD,False +312,9.0,6.0,12.0,3.0,7.0,3.0,4.0,5.0,AAEAECGCDFDHACECEAEBHBACCHCHEGCGCHCACBBAFAFCDGEBB,True +313,10.0,20.0,11.0,11.0,10.0,21.0,14.0,10.0,FHEBEBCAHAHBFGFGHGFAFCFDBDFDCHBECCCHEACABDGFBFEFAFAHGBFBDBDBFCCCEBFGGBGFAFABEEAEGBBFFDFBFBDBGBGCGDEDHFHDGGH,False +314,11.0,11.0,19.0,12.0,11.0,7.0,10.0,11.0,GBHBFGDABADADBDCDADHBGCECHCHCGCEAGCGCDCFEAGAEAEHECEFFBECDCGEHCBBBCGDHDBDADCFFEFCACAEBHHCHGHC,False +315,15.0,20.0,19.0,23.0,12.0,16.0,12.0,15.0,CCCCEFDBDHDCDFDCHFHFDEBACECHCGGFGAHDDDBACFFFDFBBABABDBACADAHCHDGCFFBHHDHDHGCCACEDBDECEHEBABHFDDDDGEFBFBGBEBFAGAGBGHEHDFEBABAEADBCGCG,False +316,6.0,8.0,6.0,3.0,8.0,2.0,0.0,9.0,CBCDFDHABAFEHBHBHECEBECHHBEEECEHAHCDAHABAB,True +317,5.0,12.0,12.0,7.0,8.0,8.0,7.0,11.0,CHGBGBFBFDABACAFFFCECHCEGDBBGHCCBGDGFGHEHDHCHBBCCECEBEAEAEHDCDHHBHBDFF,False +318,19.0,29.0,24.0,19.0,24.0,39.0,20.0,15.0,CFEFGHBHFHCEABFCCCFFEFEGBGBAHAHDBABCBGBGBGAGAGABHCCCFFFEHEDGBHEEDHDEDBHFDBCBGBFCFBEDFAFCFGACEFGFGAAFFFFDFEFECCGEGBDAAECECABEFDFCEAEAHFDBABDCHGBGBGBCACBCBEFGFGFCFHDDFAEHDFFEDDFDFBFBEBEBFHFCD,False +319,8.0,5.0,5.0,2.0,5.0,4.0,3.0,7.0,HAAEAHDHCBDEAHCGFGCEABAEAFAFHFHBHBCBCEG,False +320,4.0,0.0,2.0,0.0,3.0,0.0,0.0,1.0,CACAEAHAEE,True +321,19.0,25.0,20.0,14.0,21.0,25.0,19.0,10.0,ECEAHAGAGDCFHAHAHABEGAGBEBFFFFFGFDFDFGCDCBABEBGBFFFAGADFDGHGABAHAGCBABGDGEEACAEDBCBCEEFHGDDCBCEGEFEBEBFGCHBHBEDFHBCGEBCDCFCEBEFEBCBCBCBAGFFAFAFDCGEEFDCBF,False +322,4.0,3.0,7.0,8.0,3.0,3.0,6.0,6.0,AGDFDFDAGECEDDHCHGHCBFDEBCBCHCHCDDAHAGGG,True +323,20.0,23.0,10.0,13.0,14.0,23.0,24.0,21.0,AGAFFGHGEBBCDCEEEGBFAHAEGEGCGFGAAEBGHEBDGAGEBABEFCHAHADFBFDFBHBHBGBEBFBFHCACGCGBFBFAHAHFEFDBGGGBGFGBBEDHGHGHFHDHDGDHBFBFDFHFHFACADAGEFHCAADHBHCADFGA,False +324,6.0,10.0,13.0,15.0,5.0,10.0,12.0,7.0,ABBDDDDGDHDCBBHCHGDGBAEGEGHDBCFGFBEBADGCGCGHFFFFFCFCBDBDGDCAAAFDHCCCECDFDHCGEG,False +325,14.0,17.0,16.0,18.0,24.0,25.0,25.0,12.0,EAGDFBFEHEFGADABCCEGEAEGEGHGBFBDEAEDHDFEFDHCHGBGEECDCDCDCHCDEAEACCBEGAGEBFBFBFCCGFBEBCCDEDFDHHGAGAGEEFFFFFBGHGHBDECEBAFAFDFDGGGAHBEFGFGFHDGDEFGCABFBFGG,False +326,10.0,8.0,13.0,7.0,11.0,10.0,9.0,12.0,HGFCFAFCFAGADEDBHFCFCHHAHACEBECCCCEGEFEFGDBFBHBGBCEEABCECAADDEDHDHBGEGAHCHFHGAGH,False +327,13.0,9.0,7.0,7.0,11.0,9.0,9.0,4.0,EFEGEFABAFHDBFAFGGEBEFECCCEFFDADBDGEGAGABABABFBDDAEAHAHGHEAAGDECCCGCB,False +328,11.0,7.0,14.0,13.0,15.0,16.0,11.0,12.0,HHHHFDGEGFHFHGDGCCHFBFEDBAHGFCDCGGDDACACEDBGEDEHHGHEFEFCFGFAAACADHFAFCFCFCBDBAEEEEGDFBFAEAEDEDEBCCC,False +329,14.0,9.0,16.0,7.0,13.0,4.0,16.0,18.0,GCAEFCFCACAEDGGEGBGBGBHBHAHECAAAAHAHECECHGHADDCBCFCHHGAGEGDGEAECGBHDACECBHDCDGHCHGEBHBHEHCFGEGHHA,False +330,6.0,12.0,18.0,17.0,8.0,10.0,10.0,6.0,GGFCECDCDCAABEBEHEFDDADGDBDHGFBFBEDHDFBHGGCBCBCDCBCHDGCBCBEDCDGDBECADACCCFEFGFGFHDADFCC,False +331,11.0,25.0,21.0,16.0,17.0,27.0,21.0,23.0,FFFCHCBCGHHHGGCEBEDFCHAEFCFHDBDBABFBFEFBFHDHFBGCACHHFBFDFGFBHHDBEFAFAFHFEEEGEGEGEDBHCDCACHHGFGFHHBDBDBHCHGEDBDECECECFGBDBCEGGGGCCBCAAADAHBBBGBGFGHDAEFGFBBGHDCFCF,False +332,31.0,34.0,15.0,23.0,18.0,19.0,14.0,23.0,HBFBAAACBDEABCHDHAHDFEFHAAACDEBHBHBHBCBHBHBGCAFGBGBFFDFGAEAEBDFFADADACADDDHAHAEEBFDFGCCCFCAEGBCBAHCGEEEEEEBFDFEHBBBABAHADBDEDFGHHBHBDDABBHBHDHFCFCGEBAAAEGFDFDGDBBBAGAGABAGHBHCAD,False +333,20.0,17.0,9.0,14.0,13.0,13.0,13.0,14.0,ABGCECACBHDHGEEHEHBDAAAFDEDGDFAFABCCGHBABEBEGADADFDEHEHEGBGAHADDHHGHGCGFFABAFDBDHABEFDCDFFAFBEBHBAFAFABABGCECHGBG,False +334,7.0,5.0,2.0,4.0,6.0,6.0,4.0,9.0,GCGBFBHAHEBEAEDCGEAEHHFHAHABFGFHFHDEDADAFHB,False +335,17.0,13.0,10.0,10.0,9.0,12.0,9.0,20.0,AGHHAHAHCBABFGADADEFEFEDBBBBHHGHDHBCECEHFHFHBHAHDEAEAEBEHACAGADHCHBGGFFFHACBDFDAGHCDGDCFCACFHFBBHGAA,False +336,10.0,13.0,6.0,5.0,11.0,4.0,11.0,9.0,EGEBEBEGEBAHEFBCBEHGDFHFAFCBHBGDABHGGGBGCGBABADHDCEABABADAEEGAGCHCHEH,False +337,17.0,16.0,15.0,8.0,14.0,17.0,17.0,24.0,HBGBABHBHDFFAHAHAGAEAEAFACGCBCECFGDGCCEFEFHHHABGFCHDHGBCBHBDGDHEHGHCFCHGHDHFHFBFDABHBGBAFHEEGEGECBAGEHBHCHEFEADCBFGHCEFGCGFAAAAF,False +338,18.0,20.0,22.0,16.0,18.0,27.0,14.0,22.0,AEAEAEAFHDHAAEFBDHGFGFCAAAGADFFEFBADCHCHEGBBEBGFGFGEHEDCFHAEBHCDCBCGAECGCHCHBFBEBHHHGCBHFDDGHHHCHBDEDECBDFEFBFGFCFBFBCBFBFCDEAFDGABADADBFFFFECECADHHHCHCFCFCG,False +339,24.0,25.0,25.0,23.0,21.0,21.0,28.0,25.0,ABAFDFCFCGHGCDBDGEGEGCAAEBHBHGHGHDADCGCHFECEBDHDABHGCGHDHEEEBFBFBDDCDGEEEHBFFCFBFAFAFGCCCHGGFGCACHEDEHGDDBHEHDACAFHEABGCACABDBEBFDGHGHFHEAEAEADACGGBBBCGCGDGBGBFCHAHAHFBABFCEHBADGDEBACGCGFAFDHD,False +340,14.0,19.0,9.0,8.0,9.0,16.0,11.0,11.0,CAADABAEACBCBGAADHBFFFBDBDEGABHHHAEFHBCFHBEBGFDFBFBDBDBDAEGEGEFCGBFBAEGBGFGFHFHFGFCBCAAGAFEHHHCBC,False +341,2.0,6.0,2.0,4.0,1.0,4.0,1.0,1.0,ECBDBFAFDFDBGBHBCBAFD,True +342,10.0,9.0,6.0,7.0,9.0,12.0,7.0,13.0,AEAHAHFEGEGBGAEBBHFDBGBHHGHAFAFAFHFDDCDHECFCACFHFHCDCDHBEBFAFGFABEEEGBDHH,False +343,12.0,23.0,13.0,17.0,19.0,18.0,25.0,20.0,GCGCGCFABHCGAFCFDFBHBHEECDDBEHEAEABABAHHFFDFGEBEBGCABAGGEGEDEDHBCFDHDGBGDGHAEAGDHAEEECHHFBDGCFCDBDHFHBBBDHHCBEHFHGGGFGFBEBEFEFCFGFGHGDGDBHBGBABDGEG,False +344,8.0,19.0,17.0,14.0,18.0,17.0,16.0,26.0,BFBHCHCACDDFCHEHAFAFEEEDHGHBEEFADGGFGEEDEDEFEFBFBHHGHGHDEFCGCGHDHDBCHDBCFCGEBHBHEHFDEAEBEGCGBHBFBHBCBCBCBGACCHHHGHFDFCFHGDGHEHDCBAAFHBG,False +345,14.0,25.0,9.0,16.0,24.0,29.0,24.0,20.0,BDBDFDFEGEDADGGGGDFAABHGFGFEBHFECHCEDBABFBEDGGCFCEAAHGHFBBHHHHHHEBEBFAEEBEDGDCHEFBFBFBHEGEGEAEBGGCAFFGDGAGAGHFFFFFGCHAHBHDEDEFHBBBFDFHFBFBFBHDEFGBEDEGEGBAFFCACEG,False +346,20.0,21.0,26.0,20.0,28.0,15.0,21.0,20.0,EDEDFHFHEDCCECEHEHCGBBAEFDDHBGBEBGAEHECGCACECGCGCDEHCAFAECHBBDGDFCFBBHBEBEHDGDBDCAGACAHAHDHCEBEHEACDDDFFAGAFAFCGEACACGEEAHAGAGAGEFEFHFBGCHBDBHBCGDGCECHDHFBFDCGCBBEBDAEGEGE,False +347,9.0,10.0,7.0,7.0,9.0,11.0,7.0,1.0,DAFCBCBAFDEGEGEFAADGEGEAEAFGFBFEFCFGFCFHEDCBGBEBAFDDABCBABDBC,False +348,23.0,21.0,22.0,23.0,12.0,21.0,19.0,12.0,DBGBGFCCGCDHGFGFGFDCDEAEAFBFBHGHBCBABAFFFBBAFHFCDBFECCDCACAEADFDEDGCFCHBBBBDFDCGAHFGEADDGHFFDADEGEAEFEDECACACAFADCFCAGBBABEDGDHCGCACACHBDGGAGBGBHAHADDDHB,False +349,24.0,18.0,28.0,33.0,14.0,23.0,32.0,22.0,DBDACACDEGGCFCBGBHFGDGDEDHHADCFBFDFDAAFAGDGCFCECEGDGFBAGHDDCDCDGHCFFAFGDGDHDHFGGBGHDCDCAHFEDBFBFCDDEDGHAHADABHBEAAACADGBGAGAFHCCGFGCGDGAEAGDGHFHFEBAHCFCFGGGEGEGAGHBBBDCCHCHFHCHDFDBDCDEHECBCEAABC,False +350,8.0,4.0,6.0,7.0,7.0,4.0,16.0,7.0,EDGFGACAGBHBEBAGACAGEEEEEGGAGCGCDAFHGDCDHGHCHGBGAFDFDGGGDHH,False +351,14.0,22.0,13.0,15.0,4.0,11.0,14.0,13.0,ABCCHHFHCDBDBDBCCGCGFFDFBFGGBAHADDGDCDCBAHABEFHBBDBDBDBEBEBGDAEABDGFHBHGAGCBFHHHHHACGBGACFBBDGDBFAGAGACACF,False +352,23.0,10.0,18.0,19.0,18.0,25.0,14.0,15.0,GFADHDHFCGCBFFFHHEDFDHAEEFECAGBGEAHAHADAEGCBFBFEGEFHHEGGCFCHHAHAHEBAADAGBEBEDEDGFEFAFADADFGFAFCECECFFAFACACHCDFDADCDGGFDHCCCCDGDAFBFBEADBDAECF,False +353,28.0,26.0,15.0,29.0,24.0,17.0,31.0,29.0,EFGDADGCGBGBGBEAEHGHFDDEDEDEGHGEGEGHGHEHGDGBGFEAEGDCHCHDHFHEHAGDHDFEBEBEBEDCDCACAFGFCABFEGBGAGHHBDBABABHHAHAECEAGBGBHBFEDHCFCDGAFDHBEACFHHGDADHCFCBAAHFFGFDADBBEBHACABAHGDGBEAFABDBGGGGDDDAAHDDDHCHAABE,False +354,2.0,5.0,6.0,7.0,4.0,6.0,4.0,6.0,BHGHAECCCFADBDHDEDBFBHDCDCDFGCGFGFHHEFEB,False +355,6.0,5.0,6.0,6.0,6.0,7.0,2.0,4.0,HFHCGCGBFEAAAHAFBCBDEDEDEDCDFFABBCFCADFEHE,False +356,6.0,7.0,14.0,10.0,18.0,19.0,15.0,16.0,FBEHFGEHFDCDGGGEHCDCDFFFHBABDFDFHCCFEFECEHEFCAAGFGBCBFGFEBCACACDFFGHGBEHEHEHFHCCEGEGEGECAHEDEDGDGEHHHGHFF,False +357,14.0,24.0,11.0,19.0,13.0,13.0,20.0,12.0,CAHGEBBDBFBEGHAEDBDHDGDGECACACEFBDBFFGADBHBCCDCDHDEGEAFAFEGBFBABHFHAEDEDGHGBEBGBGBGFFBCGEGDAFAFAHAEBCGDDAGHHBCBDBDBFBDBDCGGGGH,False +358,14.0,23.0,16.0,16.0,14.0,16.0,6.0,16.0,HBCBHFHFHDBAGAEDCCCBFDFHFHDHDHGHABCFCFAGEGBBBFDADADBEBHFCFDFCBADDBCBCBCAEGEFCBABAFAHBFBEBEBCCEEHEDECBFAEHGADHDHEHBDEFBCDA,False +359,13.0,21.0,20.0,21.0,14.0,16.0,20.0,15.0,GFDBDCACAEBEBEBHBCBCECEGACHCHAHAGGBADADBDFCFHGDGDGEBHBDGGFGFGDBDAGABDGDGEHFDAEFFGFDHEBCCDCHCFCECHGDBCEHEFDFDABEBGDGHACFFBDCEAFGDBCGCBCFHBHBH,False +360,2.0,2.0,1.0,1.0,3.0,6.0,2.0,3.0,GFFFEFEBDBEHGCAHAHFF,True +361,14.0,17.0,14.0,17.0,23.0,22.0,11.0,18.0,DHACABDDDFEFBCAEAEAEFCFEFCFDFHFAFBCBCHGHFHEAEGBHBGCFCHAEBEFECECGFEDEFCCHAFAFAFADGHGBGDHDEDAHBHBHGEEBDHDBEEHGDEDEFBFBFHFGFBDAEBDGCHEEDCHB,False +362,7.0,7.0,14.0,4.0,6.0,6.0,6.0,3.0,CCBCGEGCAFAEADAGFGFCFCBCGHBBDBCGEAHAFCDCACBCHCEEFECBD,False +363,10.0,8.0,17.0,16.0,17.0,20.0,8.0,12.0,FEADABEGEHEBEBECFCDCHBHCAEEGHCFGFGFHHEFEFDFGFDECCACHFFFCDCGADAFGDCDCDCEFFFFAHAHBEECCDADAFFBEDEDEDHCFCDBHGHDB,False +364,8.0,4.0,4.0,12.0,13.0,9.0,10.0,11.0,FFHEHDFFAGEGEHEHFGDDDEDECEDABHFGFGDGAFADAEECGGABDBGHHCDCBGFDHDHAEAEHEHE,False +365,6.0,2.0,5.0,1.0,4.0,5.0,1.0,5.0,FEACAGFEFHCEABABAHFFEHAHCHCDC,True +366,11.0,5.0,9.0,15.0,4.0,9.0,12.0,5.0,CCFDEDFDFEFEHDBDCDHGGGGDFDAACADABFGCBCAGAFDFCGCGAHAGAHDBDHCGEBFDADADGG,True +367,22.0,11.0,14.0,10.0,20.0,19.0,35.0,19.0,DGGGBCECGDADABABHEHBHGAGHGFAFAGBGBGEEACACFEFGGGEFHCDEEBEBAHCEFFFFHAHAHGFECBHGGEGEHAHFGBDFHEEGCGFDAAAGEGAGFEFHFGAGAGDHAACAGHGCGAGDGBFHFGCGCECEHFHDGEGCD,False +368,2.0,3.0,4.0,0.0,3.0,2.0,2.0,2.0,BCECECHFHFAGEGBBCA,False +369,2.0,7.0,10.0,3.0,12.0,8.0,6.0,9.0,HHDHDCCEGEFFFHCBBHDEGEHEFEFEFEFBCBEBHBCCGCHEHBGGACECEFGAC,True +370,17.0,20.0,13.0,14.0,12.0,20.0,18.0,16.0,HEFEBECCHDECGCEBBGCDBDBDGFGFAFHGDDFDHBBBFAGDFAGACEFHGBFDFHFHFHCGBEDHFCFCFGAAEDECEFBFAHABACAGAGACAHABFBFGEGDBFBHBHDHDGBABAGCGEBAHGH,False +371,14.0,16.0,16.0,7.0,13.0,5.0,11.0,14.0,GBGBEHFHFBBBECAABDEABAGAEDEDBCEGECCACAGACACBCHCECEGABDBEBHBHFHCDAEADHCHCHFHCEABBCDHEGFGCHBGGHGHA,False +372,9.0,15.0,11.0,10.0,12.0,17.0,13.0,14.0,BEBEBGFFBFGFDFGCGCGFHDGGCFAFAFBFDHDEAEHEHAFBFEGHHEBGAGCHHHDDCECGCABFBFHFEDEDHBBCBGBCAGACAHBECEDDHBHFF,False +373,14.0,9.0,8.0,14.0,6.0,19.0,18.0,14.0,BHEFAHAHDDDDFBFDFGFEFHGBBFAAAGADHGBFCDGBEFGFCHHGFGHGHFHGEGAGEEAGDDABGGCCCBHBHCHDFAFAFAFGFDFDADADCGCGHF,False +374,13.0,6.0,13.0,5.0,8.0,10.0,12.0,6.0,CBGADAHAHAFAFGCGFGCDEAEADADCBHDFAACCCAFHBBCEGEGECFHAEBEHCGFGFGEGCGCFCGABF,False +375,8.0,5.0,6.0,3.0,11.0,9.0,8.0,4.0,EEEEHFFBFGGCGHGEBABEEFCFCBHGDBHFAFAFDFGAGDGAECECECAAAE,False +376,6.0,8.0,6.0,9.0,8.0,5.0,12.0,5.0,AEGEBACACHCGGHDBDBCEGEBEBHFDDGDCDBDBEGCAFBFGGGEHEAADFDFHGGG,False +377,2.0,3.0,2.0,5.0,6.0,4.0,2.0,2.0,EDEDECEBHBGFGAEADFHBDFEFDC,True +378,18.0,11.0,12.0,20.0,13.0,19.0,14.0,21.0,GAEHGHAADADADBFCECDCFCGDDFCGHAADFFFGHBHFDCDBFHFHGHFAGAGABADDHAEDECFFFAFAFDEDEBABFBGGHBCBAACBHHHFFEDEDADBEHFHGCGEEDHDCDGHGHEHEHCH,False +379,15.0,10.0,10.0,14.0,7.0,13.0,13.0,11.0,FHGHGHBBCDDDDABABGCEDADCHGAAHAFCFBDBDADFCFDDHCHFHAHCHCBCGGAACAHGGGGAGBEDFDFEAGDGFEBEFFAFAEBEF,False +380,20.0,20.0,27.0,28.0,18.0,28.0,19.0,15.0,FAEAEHHHHHHECBHFFFCFCDAGFGDEDCDCBGFFCGBGEGBAEAGFCADGGBEBEFHFDCBAEFDFDEDAHAHGEDAGBGFEBEGFDDDFDFAFCCCCCCBCBCGCGCACDDBFAFBCDADCDEDBCBCGHGFGBBAFDCDHBHDDBDCECACDFDGABFEDEAEFHHAAFFF,False +381,9.0,4.0,8.0,8.0,10.0,3.0,5.0,2.0,DEDECFCECEDAAACHEGDDFDFCACECGAABDGCHBEBGDGBAEAEAE,True +382,28.0,23.0,23.0,25.0,22.0,19.0,22.0,24.0,EBAHHEDEDBDHHGADFEFEHDHDGFFDFDADHDGEACBEHEFGDGAGAGEBCDCBBAFECHGGBHCHCGGGCGAFCHCHBBEBFBFHFCGCGEDEAAADABABADFEFDCDCECDCHCHCBAAAAAAHAFEGEADCCFHFEBEBFHDHFAAAGCBBBCDHDEDFBEGHCBDBGHGCGHDEAGABA,False +383,4.0,5.0,2.0,2.0,4.0,7.0,4.0,2.0,FAFBFGCGAGAGFBDEFEFHABFBDCHEBE,False +384,23.0,10.0,11.0,21.0,17.0,14.0,20.0,15.0,CBEFFDDBFAGHDAGAGAGDDBEGCCCDCBHHEAEFGFEEEHEACACAGAGBDAAHFHFAFADEHCACGDAEEFGGHEHBCDAGAEDEBFGHDHEHDHFHAGAGAGAFAFABBCDGGGDBDGDEDEDFDHD,False +385,16.0,15.0,15.0,12.0,17.0,20.0,20.0,23.0,FGBHBHAHAHBDFEFEBCAEEDEAHBHBHEFDCBAFCFAFAGHGHGACDHBCAEHGHBABFCFDGDFDFHFDBGFGHHACADACHCGBEBEHEACGEGFGFGDGEGEGECEADACBGFHHDFFHFHFGGBHCGCEEHC,False +386,22.0,28.0,19.0,25.0,19.0,24.0,12.0,27.0,BHDGBHDFDFDBABGDHAFAECECBCBCFCBEBHHHEEEBAFDFAFADECBDFDFAEHBHEHEGEADHHHFHFHDBFHAHADADFDFCAHBCGCDCBBBGBFAFCFHAGADDBFEFEAAHCDCECBDFFHFHBHBFEDCACAGEFDHGBEHGBCBHEEGAGHBDBDGHADADCBCB,False +387,16.0,23.0,23.0,12.0,27.0,6.0,20.0,14.0,EDEBGBEBCGGHCACBHBEGAGHGCGEGFCHBDCHGHBHGDADADBBCHCBEBACGEGEGEBABABDEEHECCCCBBBGAGAEAGFGHACCBBABAGFBEEEEEECGDDCDHEEEAEAECDCECGCFHFCBCEADDHEBFH,False +388,29.0,22.0,29.0,26.0,26.0,22.0,19.0,18.0,CECEGHFBFDDCDHGAFBGDFAAHACACAEEBEACFCAEECCGCGCFFFABGBGDCDGDEAEABHBHBFBHAHDCECECHFEFBACDDDEHAGABADFDFDBDBDECECEDHDAAAAEBEGAAADGFBFADACHEAACFGFGCGEHFHFCCCDGGBCEGFAFEBHCDAGBCBCDCEEGDBDBDHFHEBEHH,False +389,6.0,5.0,9.0,6.0,6.0,10.0,3.0,6.0,AFFFACCCEHHHHACDFDEGCBCDEDCFBFBDBFHFHADGCGCEFAFAEBE,False +390,5.0,5.0,8.0,6.0,3.0,4.0,2.0,9.0,CHCGBFDADACBFDFCHHDHDHCGCBFAEAEAECHCHBBDHH,False +391,17.0,18.0,29.0,20.0,13.0,16.0,17.0,22.0,GDCDGHHBEBFCFHGHAAAHBCDCDHFHEHBDDDDDCDCACHEBDBCBFDACBCBHACCDCGGGGCBCFCFBACADHHCFCADHHHGCBBGDGCGEEHEACAGGFGCABABDBEECECECFAFAGHHDHDFBFGFHECEFDFAHBHFGCACE,False +392,4.0,11.0,10.0,5.0,8.0,5.0,3.0,15.0,HHHHEEDDBGHGFABEBECCBHBCBEDECBCHCBEFEHDBDHAHBHFAGCHCHCBCAHFHF,True +393,5.0,6.0,6.0,2.0,4.0,4.0,5.0,6.0,HGFGHHHAGCGEFEBDFDAAHAFCBCBCECBGBEBHCA,False +394,21.0,28.0,17.0,22.0,17.0,15.0,15.0,14.0,DHAAAAFCDBDBDGGABBBCHCACGHFBBBBBBBAAAAFBBBBBEGEABCGFDHEHEDBAADEDEDEHCFEBEGDHFGGECDCHCHBDCEFEHDBDBDBDCECGCBFDGBADHGGFAFAFACEGEFDFBABFFEGDAACACHEHDHDCG,False +395,17.0,17.0,23.0,13.0,25.0,16.0,32.0,27.0,ACFCFGGGEEHEGGDEHBACACECEFEFHDEDFDGEGBGFHCCACEEFDACHGHGHBEEHBACCCCHCEFDAGAGEGCBHBHBGGGDGCFAHGHGHCAEFBBBHBGBHHEHEBGGEGEFHFHFHGHGCFCGHGDEDAAAGCBBBCHAEAHDHDFGGGEGBAHECDFDCAE,False +396,2.0,4.0,1.0,7.0,6.0,10.0,8.0,9.0,GCGFGFGHBFAEGFHFHGBDHEFEDHDEFEFDFEFBGHHAHGDBDHD,True +397,12.0,14.0,13.0,17.0,13.0,20.0,12.0,15.0,CEBHFCBGHGEGEACAHBHBDBGBADFDHDFDADHHEHFHBAAFACECECEDDGDGDCCCHCGBBDGFBECGDGACFFFFFFDHDHAEFEFBBGBFHFHECAFDBEHDFAFAEGFD,False +398,28.0,19.0,7.0,24.0,27.0,19.0,20.0,15.0,DHEAEADDHGAAHAGEHEBDBDHFCFEFEFEGAGHGBFHECAAGDCDADFCHDADADFDHGBGAEHDGFBFAFAFEFEFEHCAAAGGBBABDBCEADADFEGEFHADEGGGEGEGBGBDADEEBDBDHEEEDADEBBFHEEFCFEFAAAGABABDBHBG,False +399,0.0,3.0,1.0,3.0,3.0,3.0,0.0,4.0,DDHFBFEFDHBHCHEBE,True +400,14.0,15.0,8.0,10.0,12.0,16.0,15.0,13.0,BABABGHFHEHEAEBFGHDBCBGDCFFGAGDGFEFEFEFHDCAGAGHHAHACBCBGAGEGEDBDHDEBCACBHAHCFAFEBEDFFFBFGEGFABHGDADFBHG,False +401,11.0,5.0,16.0,15.0,7.0,18.0,6.0,17.0,EGDHHBGCGFFFFECHDAFAFBFDHGHAACFFFAEHBFDFHEHDFDFDABBEAFCCCCCCCFHAGADDDCCEHEHCHDHAHFHCCCFDHDHDADG,True +402,3.0,10.0,24.0,13.0,15.0,13.0,11.0,19.0,CBBEDHAHBDBDBGCECHHDHGHDCGCGEHCHCGCEEEEHFHFECEGBDDFBHEDBDADGFHCHCGCBCDCEAFGFGHGHCECFDECCCCCDHHEBFHFCFCEHFFCF,False +403,1.0,2.0,2.0,2.0,0.0,1.0,2.0,2.0,DGDABGBCHCHF,False +404,5.0,16.0,6.0,12.0,8.0,5.0,12.0,9.0,DGDHBCBCHGEEHEFGFBAGABADDCDBBBBBGAGEEDCDGHGHFHBHGGCEEDBDBDBCBDBGFAEBHFHGD,True +405,21.0,16.0,12.0,16.0,13.0,10.0,25.0,18.0,GFEFBFGGBGBGBHFHEBEBGBGFGFCEAGCDHAABHBEGCGHDHAHDCEGDGDBFGCAAAAEAGADFDGDAACACECEBFDHBAEACHGHAHDEDEFHHHBGEGACDBAGGBCBHHCDGAGDGHGHADAD,False +406,4.0,4.0,3.0,5.0,1.0,0.0,4.0,3.0,GBDDABCBCGDGDCHBHDHAGAEA,True +407,16.0,7.0,6.0,14.0,13.0,6.0,14.0,8.0,BFCAAAAAEFEBDFCFCADGDBDBDAGAHAEDEGHGHGFDBDGAEHEAEAGCEDHAEADGDAFADGGEGHGHDEBEHDGBGCCE,True +408,12.0,15.0,11.0,21.0,18.0,14.0,12.0,11.0,DBDBDBDBCBGGABCEFEFGGDBDAAAEHEFEBGBECCFCBGEEAEHCBFEFHFCEBFBHGADFDACABEBEAECDCGFDDDDDDHGEGFDHDHDHFCDDEDGAAFAFHHGHEE,False +409,20.0,21.0,28.0,22.0,20.0,26.0,20.0,22.0,FCFDFHADGDHDHBBCCHHDHDHDGAABAGCGCDCDFFFAEAFBHHGHCHEFEGBDCDAAHABBCFHFEEGEFFFCHCDBDEDEFEDAFAFABEHCCCEBHBDGDECCAAACDGFFEDHDFBHBAGAEAEFECGGGCHCDAHBGBDBCBEHGFCFCFCFCEGEGHFCBGFGCGCEABBB,False +410,3.0,1.0,3.0,3.0,0.0,0.0,1.0,2.0,DGACBHDHDCACA,True +411,10.0,24.0,18.0,15.0,16.0,10.0,24.0,18.0,HHFBFECHGHAHFGGDCBCBCEGHGBBAAGCCHCBDBGBDHHHBFBDBGGCGHGABABACEHEHCDGDECBAAEFGGDGEADDDHDHBEBEGEFEGEGCGDGDEDBCCCHCEBEDCGFGHGEGFBFBACHBBBBF,False +412,7.0,7.0,14.0,10.0,10.0,6.0,9.0,5.0,GEDFDFBAGCDABADDGAHEDEDFDCDCDFHCBCBCGCHBGCFCAEEEEEGEGCCCHHGCBEBCAGAF,False +413,1.0,1.0,2.0,0.0,2.0,2.0,3.0,2.0,FGCGCHEHEABGF,True +414,3.0,7.0,4.0,3.0,7.0,6.0,6.0,8.0,HCHGEEBABABFBEGFGAGBDFDEHEFCFBHHHFHCHCBEEGGD,False +415,17.0,22.0,23.0,22.0,24.0,17.0,20.0,16.0,BCBGBADDEHEBECCCCDGAGEGEAACEHEHGFABAEHECECFCGCECDBACAHADECGCBBFGFEHEFGDGEGCGFGDHDCBCAFGDGDAEFHFCFBEEHEBDDFHHHBAFAHDEDGDBDEDECFCFHFAGCFFAEGDGDADCBBBBCGHHABBBBBDED,False +416,23.0,23.0,29.0,23.0,28.0,15.0,36.0,18.0,HDFEEHAHFECBCGDFDFBAGABBGGADFDGEGECECGDHCECECEDEDACACGEGCGFBCBCACEEDEGGABHEDCHBGGGHGCGCBDBCCCEHEBGBCDDGGHGEFEGBBBDBAFAFAGBFFHHADEGEDBCCCACGCDCGEAHAEADGGGDGDBFBFCGCGBGBGACAHAHGEFDADEHEHAFGHBHDEAEA,False +417,6.0,3.0,6.0,6.0,13.0,9.0,7.0,12.0,HGCCECEAEHGHGCFAFHDDBDEGBGHHEEDAFGFHEHAAADBCHCGFEEEHEHEFEFDFHF,False +418,7.0,7.0,9.0,13.0,10.0,16.0,6.0,11.0,HEFFFEDECCHHBHFDFACACEDHDBDBDBDFCFDEDEBHGEFFAFADAFHGBGCGCFDEAHDFDHGHFHCGEFEFABC,False +419,6.0,2.0,4.0,3.0,3.0,0.0,2.0,0.0,EEBDBAAAACACEGGCCDAD,True +420,20.0,21.0,13.0,17.0,21.0,27.0,25.0,13.0,HAGAGAECCFDBEADDGAGFFDCBFFCABGBEBAGCGBFBGEGEFDCDEBFBEDCAHBHBDFDFBADGFFEGEGEFEFEFHFBBABAHHDGDGBGAGFGFGEEDEDAFAGDHEACACFFGFGFGEDECBFBFHHHGEAFAEAHFBEBGBCHCHGADC,False +421,9.0,14.0,14.0,8.0,6.0,14.0,12.0,12.0,FHFDFDBBBGBEBCBFDGDHFGABCGABBGEAFAHACACHDDFHCBBFHFHFGCHCHGBBHHGCGCACACHCEFEFADDFEFEGGCGCB,False +422,2.0,4.0,4.0,2.0,2.0,3.0,4.0,6.0,HFCFCECBGGGDGBEHFBAHAHBHDHC,False +423,19.0,10.0,8.0,8.0,6.0,9.0,8.0,8.0,DEABABCFEFDAAABFHFAFAFADACCGBABAGHBABABAGHEHCGDGDCDCGEHEGDAABAEHBAGACDFFCFHH,False +424,22.0,16.0,21.0,30.0,13.0,19.0,17.0,12.0,BCBEBDAEAEAHAHGHCBCAAEADGFGDGDCACFCDEGCDHBCADDDDDEABADADADAEGBGBHCGFAFDCDBDFACDBDBCFEHEHAHGFGFGFGECHFHCCGDGACDFDECFDADEBHFFDFDFBFBEHAGCGDFCBGDACBCFDAD,False +425,12.0,15.0,7.0,11.0,10.0,19.0,9.0,9.0,CADACAFHFDDCDBFBDBEBEDEHFABACFFHHGFDFDGDGHAHACCBEFDFGEGEADFFCEGBABAEHHBHBGBEBABGBEFFFFABGFFF,False +426,10.0,14.0,11.0,11.0,11.0,17.0,18.0,9.0,BFBAAEFEHCHGAFEBCFCGCGBGFHFCGGAFAFBFCFHBBFEFEFEBGCECBGBGCDFDBDBDGAGEFEGHGHAADEGCGHDBAEGDDDDCDFGFGABHH,False +427,37.0,20.0,35.0,16.0,24.0,26.0,23.0,17.0,AGAEEHGHGCCCGBGCHCHCHFGGAAAEAEAFHCHCGCACADEEECBABEFEHDFBFEEBBBCEFAFADACAFFCFDHDGBFFACDGDFDBBBCGCBAAAEAECGCDHFBDBCAAGACACAFAGGBEHECECEABFEGDFDHHAAAACHCHGHCHABEGCGFACCECFFBFBABAGFFDAECEDEFFACGCGAGCDFD,False +428,16.0,17.0,31.0,28.0,15.0,17.0,26.0,26.0,FGFCCACBEDEDBCGCGFDCAAECEAAFFGGGGHCHCAGDGDBHBHFHFHFHDHAGGDDADHDHBACGCGEDHBCDFDGDHDCCCBBBBGCCCCFBDDDBCCCHCFEHHGFBFCCAAGGDADGDHEHAGCGCBDBFBFEGAGEGHCFDHHHHEHEBEHDFDGDHAAECCCEDEDGH,False +429,8.0,4.0,6.0,7.0,12.0,5.0,7.0,6.0,AAHAGBFHFCEAEBECGFGFGEEECBCDCAEHEAEDEDHGHBCFDGEGDHDEDAA,False +430,5.0,7.0,8.0,4.0,4.0,3.0,11.0,4.0,HGDCHCBCBFGAGBGBEDHAEAEGFGCGEGAFCGCGDHDBBBCCGA,True +431,8.0,19.0,9.0,16.0,16.0,15.0,11.0,12.0,FABCEHHCGDGDFDFHFAEDGDFDFBBBBFEDEAGBEEEFEGEBEFDDGBBAAAFHFHEEDCDCGEDBDAEHEHBHBHBFGCDCHEDBFBGHGFBFBCBCGCBAHD,False +432,25.0,23.0,17.0,34.0,27.0,19.0,18.0,34.0,GBHHHFEGGFGFGHBABDBDBHGGEBBDEDHHHHAHFHEHFFFGBDDEAAAAADCDHACAFDBDCGCGDDDHAGBDHGHCHABAFEFEFEFDDBDBABGFAFEEDEDEAEBFDFDHAHABEBEDDDFHCEFEAAAECCBABHDADHCBFGDHEHAGBDHHEHEDEAECEDGCEEHDDGHCHCHEDDHBHCHCACBCG,False +433,11.0,10.0,8.0,8.0,5.0,5.0,7.0,5.0,GEEEBADHCHEBEACABDBDAHABABABCDCGCDABFDCACABGGAGHCHFFDDGFGFB,False +434,8.0,2.0,9.0,3.0,9.0,11.0,9.0,7.0,CECFFFHGHBHCFCFBFHDACEEFCGEDEDAAAGCGCEFFAAGGGHFHFHEGEGECAA,False +435,15.0,9.0,12.0,17.0,12.0,13.0,11.0,8.0,FEFHFAFEDEDBCGGFBHACGCFCHADADAFAEAEADHDBDFHEDEDBBGBDADAGAGEGECCHEAACBCDCEGFGFDADGHHFDFCCCBDGEFADB,False +436,9.0,4.0,4.0,2.0,2.0,7.0,7.0,7.0,HEFBABCEFAFABGGAAACFCFGHBHACGFGAGAGHHDHDHF,True +437,13.0,14.0,15.0,27.0,27.0,6.0,29.0,26.0,DDDEHABAHEHAHDCBGDHFCEGBBHBHADDEAGGEGDGDGCCDCDBDBHBHBAAHGGGGACECEGGGECCDGDGEGADADGFHEEDEGACAGHDDDFDFBEHCHGHFHEEEHEHEHEHEGEFDGDGHBCCEDHBCGDHEEBAGHGEGEGEDHBHCD,True +438,22.0,9.0,13.0,21.0,26.0,17.0,18.0,21.0,GAGEHFHCEGEDAFAHAHEDBDFDABAHEDGDBCAEGDDDGGGGAGEHHHGCCFHHBHBHBHAGECAGDGDGDGEHDFAGCEEFEHEAEAEFFCECFFFBDADFDADADAFEEEEAFAEEBABAHEFDGHEHFCDCDCECHCHFEAH,False +439,24.0,19.0,22.0,19.0,24.0,22.0,19.0,24.0,DCDCAAAAABAFGFDFDHGCGCGBDACCCCEHFACHEDAAEABAHABAEFHFCFCFBBHFHEHEGCGDHFECBBBGBEHEAEAHDGDGHCHFBFEFEBEDFAACDHDFBHADCCEHEHDBFGFHDHDGEGADADEDEBECHFGGAGEFCCBCGFBBAGEHFHGHEHEFECBGA,False +440,23.0,14.0,11.0,16.0,9.0,11.0,13.0,16.0,DCDGBGBAAHECEFGFGAGHHEDGBCFDFGHGEEFADAEGFBAAAABFBFDAACCCEDHHHDDAAEBHCHABCHAHAHABEDGFGBGDDDDDDGAAHACACACABFFHBHBHB,False +441,5.0,9.0,7.0,7.0,5.0,6.0,6.0,2.0,CFDBDGCADBDBDGAAEAEBFBCBFGHBEGDHDECECBCGFGFBFAC,False +442,21.0,17.0,17.0,31.0,26.0,21.0,12.0,20.0,AAAGDEAFCHCBEDDBDBDHCAAHBDBDADHFHFHFHFHFDFEADADHHCHDDCFBFACHDEEEDABADAFEFHCACFFFEFBBEHGDGEGFDDCDGEGECCCCCFCHDEEECGCFDEDGBBDBGGHBFAFEDADFDHEHDHAGDGDBAEEEBEDAHAEBEBEAE,False +443,22.0,20.0,27.0,22.0,26.0,31.0,22.0,17.0,EDEAHFDFEBGFEFHGAFAFEDEAHDFBEDACCCBCBAFADAHFCGHGHDCDCGGHBBGACADFEFEFBFBFBHBHAHAGGGEGAGACECECBAEFFDEECDFECECBCEHDFCABHBCGDHBFBFBFAEDCFFHFCFGFDEDEDGFGFGFBCHEGGCEDGCCHDGFGCCCACEDEAEABABADFDH,False +444,25.0,15.0,17.0,18.0,21.0,13.0,21.0,25.0,GCAFBBBBAFGHBACAFHCECHBEDEHHHEDAHABCGDEAAABDBHAHBEGGDGACDBGGGGHGHGCECEFHFCCGBEEEEEDFCGDGDADADCECBFFCAEAEADGDHAHAHEHDHAHEFEHDGFHFHBDDAHAGAGAGAGEFBHECFCACHDH,False +445,4.0,5.0,1.0,1.0,6.0,3.0,0.0,1.0,FEBBABEBEAFHFEAEAEBDC,True +446,3.0,5.0,3.0,4.0,0.0,2.0,5.0,1.0,DBDAGBGCGCGCBBBAGFDHDFA,True +447,27.0,17.0,19.0,29.0,21.0,26.0,19.0,16.0,AAEEEEFDFHEADAGFGFGAGHFABBBBDADAHFDGCHFDFAFGCCBFFHDHDADEBHGCAHAFCCGCHEEADCBFFDFAFACAEECDCDBHBDCCEDEAGABDBDGGGGHFHFHDEAFDCDAAABAGCGFDFEEEBGAGAHBGDGDFDFDHHACCDCEBEAECEFEFDFDBDB,False +448,12.0,3.0,7.0,7.0,6.0,6.0,10.0,15.0,GCACACAFHFHGHDHAHDDEDCFAHACAHGEFHBHBFGDEHEAAAGAGCDAEGEBHDGFGHHCHGH,False +449,27.0,20.0,31.0,20.0,16.0,31.0,25.0,16.0,CCFCACAHBDGCGCBCGCDCBBEBAGFFFCFCDCBHBEFDFDHGGDCFEDBDFDCDCFFDBAECHADBCHCHCAAAAFAFADDGFCECGCGDDEHGHFFEHGHGFGFGAEFBFEFDBHAFDGGCFAFHHHBHEAGAEAEABGHFAFACACBCACGBBAGACAFFGFGFDBCBCGEEEECFADGBGA,False +450,2.0,7.0,4.0,2.0,6.0,1.0,3.0,3.0,DGCGCBDBHCECHBEGEABFBHEAEBEB,True +451,8.0,7.0,6.0,1.0,2.0,4.0,4.0,3.0,FGFHEABCCCDBABAHCHEAGCGCBAAAABBBFGF,True +452,12.0,16.0,17.0,11.0,29.0,15.0,19.0,16.0,EGDGEGHCFCFDDBECFHFHGEBEBEBEBDBAHAHADCEEEEEEEBECCBBBGDCDCFGHHEACAGBGHFEGEAECFDEGFHCEDFDFDCBHEAEAEFBGCGBAHFHGGEEBFGFGEHAGAGAFCBHHHCCECEG,False +453,4.0,3.0,6.0,2.0,6.0,8.0,4.0,3.0,CCFCEEHCHBDEFAFAFHGDFEGEFBFBFCECGAGA,False +454,17.0,13.0,25.0,22.0,19.0,16.0,28.0,27.0,AGAHHCDEDGGGDHHFEEGEHHCGGHGABCDCDAAFCFCGAGCFFFHEEEHEBGBCFHDAEEBDCDCGCGCBHBFCFHDHGBGDHCHFHBHDHBEAFCCDEDAGCGCDCFFHGHGHGAGADACAEABFCECECEBEHAGAHHDGDGHGHGFDFDEBCHDDCDGBGEA,False +455,3.0,8.0,5.0,6.0,3.0,3.0,1.0,4.0,ADHHHDFFACBCBCHCBDDGDBDBEBEAEFCBB,True +456,17.0,25.0,25.0,21.0,21.0,26.0,24.0,21.0,GEGBFBFBFBGAHAFACDEDCCHFFGBGAACFCHGFCFGHDAEFEFGFGHEBEBDAFGFAFCCBABEHCGFEDEDGBGBFBEHEGGCDCDCBGHDCCCDFAGBHBDEDHCHCHEHCBCDDDDFBEEEEGGBFCFCHAHACGFBBHDHBABGBGDGDFAFAECECEFDFDBGCHBAAHHEH,False +457,12.0,10.0,8.0,8.0,4.0,11.0,8.0,8.0,DBDFDFCCCHBEGFBHEFACBDBGHGBFAFGHAHAHGDDDCCACGCEHGFGFBFBABABDHFAAAEAFA,False +458,20.0,11.0,18.0,22.0,26.0,28.0,20.0,28.0,BFGHCHEAEAFFFFGABCFGFECECECECHCHGHDHAHEEEFHAAFBCGHDHDHCABGHCFDGHGACFDDDBCGDDFGGGGEEABGFAFEHAFEHAFAEAEABAGFDFEEHEFECDADHDHBHEHDHCHFHDHFHGDDDDEDEFEFGDCHCECEFHFAGBFFEFCADGBGBHA,False +459,18.0,25.0,19.0,16.0,13.0,17.0,21.0,14.0,CACACDEDBCBHAAGHBHBCEDEDAGGHDFDEDCHFHECFBFACAHAGGGGGAGDFBABFFGFBHBHBGBHBACABHBGCGBGEFADCDCHAHDHDBACABBBGEGEFCFBGBEFDFABABFCEGECDCBCGDBEGFFCFDGE,False +460,21.0,19.0,19.0,30.0,29.0,19.0,23.0,32.0,FDEDECCDEEHFDFEFEFHAHDCGCGCFDDDCGAGAECDHBEBAHGCGEFEDHDHDGDBHBADCDCHHFECHBGBEHADBDHGHGHGHDHFBGAGHBFBAECGGFEFEFDGDCDAEGEBACHGGDDADFHAEABBGBABDFDFABEDAHBHAHAEDEAEHEHCFCHEHEHBHBHGGCACAHEEEEFDFCGDH,False +461,9.0,19.0,19.0,25.0,19.0,17.0,20.0,16.0,BEGCGDAEHEDBDCEHECACAEAEAFCEGHGHFHGHCEDDDHDEGGFEHEFDFGFDBDBDGDEDCFCFHECBDHACCBCBFGDGCHBHDDBGBGFCBCDDGDACFGGGGFGBEBEGHDBDFCFBFDFDBHHAHAEDFBCBEBEC,False +462,9.0,14.0,11.0,15.0,9.0,10.0,15.0,17.0,CHCHCGCBEBDHEHFBGDGDGDGDBDGEGCHHBDBDACFCHGFEAHFFDCGAGBFHEDEHHAHAEBHBHGAGBFBDBCFCBCBADAGEGHHEFDFDGDAH,False +463,15.0,16.0,16.0,16.0,13.0,12.0,15.0,14.0,EDEGEDHBHDHDACHCBCAHADGDGAEEHFGFGFAEGEDECGGAFAFDBCHCGCEBABABABDEACHCBABAFGEACFDBBCBEGEGCDCDADBDFHHHHHBDCDGBFFGFHCBCFG,False +464,20.0,13.0,10.0,7.0,14.0,12.0,14.0,15.0,HHHBDFFCHCGCGAGDFDGEBFBABAFAFHGHBAGEGEHBACFCEDBACCCABADAGBGAGEEAAFAFACGCFAHEHEDEBAGEHEHEGAGAEFHHHHABEBDBF,False +465,32.0,28.0,23.0,18.0,15.0,22.0,28.0,21.0,CAHHBFBGCACEGFGAAABABAGGCGCGEAAGCGEEDBDGDCDHDBBABAFABAEDBGCEDBDBAHABFHEDEDBFFGAGHHEGAGHEECDCFBHCGBDBDBFGFDFCFAAACACFGHGAGDCFGAGFFBHCHCEABHBFBFHFAFHFEFBABGBGBGHHHAHAGEFCCHBHCAGBCDCECADADAG,False +466,14.0,31.0,26.0,20.0,17.0,27.0,15.0,13.0,BBBBBCGFEFDFDFCCDCHHDAFADACCEAGGCGCACFFEGECEFECCACGEBAGDGHBABDBHBHFCBHFCFCAHDCDHBGFEEDEDFAFHHGBBFAFCCCFAFDFEBBABACHHBDBDBFBCCFFFFFFDBBBBBEBECEGEGDGDGEGCHEBCDFBBBDD,False +467,15.0,12.0,15.0,11.0,17.0,18.0,18.0,13.0,HAGECCBCFHEGGGGBGBDBGBAFACCFCFCBDFAAAAACEEEFECDFDCDCDHBGGGFGDABAGAFFEAEFHBEDEDEFBAHGCGCHFGFGFHHDHECEAEGFAFHHEHEBBGEHFDC,False +468,22.0,12.0,14.0,17.0,19.0,18.0,16.0,15.0,DADADADAHAGABAEHFGFGEGBHBGADHDGGACHEHCHGEFFBCGCAFGDGAEHEAAFCFGAHAHEDDFDCHFEFEDEBECABEFGBGAGCCECFCBBBBHAEBECCADEDHHHEDEDEDFFFFGDAAAFCF,False +469,18.0,26.0,29.0,20.0,29.0,19.0,16.0,15.0,CGCGCHCFCGHHCHCHCHCFAEAFFECEBFGDHDCECECHCFFDBDEDBGGEGAGEHBBCCACABEEEAEBEBACECGADBBHBDBEFEFEFCDDGCCBAHHFCBHBADAGFDBEFEFEAECBFFHABDBAEDECECEDBFBDBDBDACGEGEBADCDGBGDGACFEFBAEH,False +470,6.0,1.0,5.0,5.0,3.0,4.0,4.0,6.0,CBCAGGHDHDHDHFHFEECACADHCAFAFGEADG,False +471,8.0,12.0,3.0,4.0,7.0,8.0,8.0,2.0,GAAFBEGEFDAGEGEFEHGBCFFFFGBBBEBABABDBDBEBDHGCABACAGF,True +472,9.0,4.0,9.0,5.0,3.0,6.0,1.0,7.0,HACGCABHCEAFHBHDAAACFCBEDEDADAHFHFCFAFBCDCHC,True +473,2.0,1.0,5.0,2.0,7.0,3.0,2.0,10.0,CCHCDDGFHAEBEHHFACHHFHEHEHEHECEG,True +474,8.0,7.0,5.0,9.0,9.0,4.0,1.0,12.0,BCDHBCBADCDHHAHDHAHEDEDBHEEDHCHAFAHAHCEGDADEFEFEFABHBEB,True +475,11.0,5.0,2.0,1.0,3.0,2.0,5.0,4.0,AACDCFHAGAGAEBGBHBFEAGBGAAAHAHABE,True +476,25.0,30.0,25.0,21.0,26.0,22.0,25.0,24.0,HGHEDBDBCHEHEDEDEDEDCAHDCGCFDFGEGDGAGAGHGDGDCAAHABAFACBCBCEDEAEDEAGDFEBEBEHGHFHFCBBFGHGFEFBBBFHGBCFCEBABADHBCACGFHFACACDFABHEAEHHDGACHFBFBHBHBABGGDBABGFEFBHGHAHEBGBGCFBEBECGCACEFAGECACFDFEAECCBGHCDD,False +477,15.0,14.0,22.0,19.0,17.0,22.0,25.0,22.0,DFGGGFHHCHEHBGDEEBFBAAHGFGFGACCCGHFHBHCDEEFEFBFAFBFCGCEDEHEHEBFAFAFAFGCGCGDBCBFFCHCDDDEAEAGDEDECGDGABBHDHDFDFDGCGAHEHFHCHAACDDBHHACBGBGAGFFHCCGHHCCGDGDGCGEE,False +478,14.0,12.0,9.0,13.0,13.0,17.0,7.0,13.0,AFAFBFBDAAADFFBFBEHGFEFHAHFGDDFDHAHADABFBFHEHECCACGFBDBGAEHCDCHGHGEAECECEFECADFDBGBHBHEHDDFEFDBEAC,False +479,29.0,20.0,16.0,24.0,27.0,18.0,17.0,26.0,GEHHHAHEGBGCHCBCFGDGBFDHCCBCHFHAEFEGGDHDACEDDDCDFDFDHBAADHFHBEFEHCHCDFAFABAEGBHBABABAEHEAEAEDEAFHEDAGEBEFGCEDEFEDHBFFDFAHHDBDGDHEAEGCBDEDBAGAGAGAEAHACACAEAEBHAHGFGEBEADADBHBHFCC,False +480,11.0,14.0,7.0,9.0,18.0,15.0,6.0,9.0,FAFEGDGBBEFEDEFEFABAGEGEFFFBBCBEDABEGAAAFHFDEHHFBFDFAFCDCDEGHHCHBABCBEHEHEBEBEDEHABEFACDC,False +481,8.0,4.0,7.0,16.0,11.0,8.0,9.0,4.0,EEADADFDEAFBFGEGFGDGCHDDCDEBEGEGCFCHDAGCGDGAECFCEDDFDEABABADDDDEHFH,False +482,11.0,7.0,25.0,5.0,16.0,24.0,10.0,11.0,EAEAEACFCBCEFEGAGAGCCFFEFGBCFFHFCFAHACFCEEHCCFDFEEHBHFHAGFFEFEBDAGCGFAFEFEHECGCGCFCFHFHCCCBCDDBCCCCFDFHAECBHG,True +483,24.0,31.0,31.0,29.0,20.0,23.0,19.0,21.0,HAHEECBBBBGBECEFBFHHCHFHDBGBHEGEADAEAEBBFBCECFCACABHCHCEBFDFCFCFBFHHHEGCDCDCDHDCECGABADDDBAGAGAHEDEBBDGCBCFAFABAHCBCFHGHBDEDGBGEHCDCFCFCAHFBCDCDGDHABGFEBDBDBDGAFAGAFDDCEFABAFDDGAFEFDGCBABHCGDGDCDCAE,False +484,10.0,14.0,9.0,7.0,6.0,9.0,6.0,9.0,HCACBFBFCFCFHAHADACABDCHGHGCBFDHCBGBABFBDBFBEEHADADHBBEBADAGECEFHBGEGF,False +485,10.0,4.0,11.0,5.0,13.0,7.0,15.0,10.0,AEAEHCHCGCGCBEGEGFGBGAGFGEHAFGCHDECCAHADDFDFHFHEGEGACCBHDHAEGEGCGHBEEEGAFAC,False +486,10.0,4.0,4.0,3.0,10.0,7.0,9.0,8.0,HGHCFDHAFAECEFHFHEGECHDDACABAEEEGGAEAGAGAGAHFGFEHEFGBBB,True +487,5.0,6.0,9.0,7.0,10.0,8.0,5.0,12.0,FCFCFHFAFAFGEDCBEHHGGEHEHAGBHCHFEAEDEDBHADCBCDHDHDFBEBCCHCGEHE,False +488,11.0,11.0,11.0,8.0,15.0,8.0,13.0,12.0,CBABEBFHFGEGHCDCAGDGEABBCGGBBHEFBBABGBADEHCHCEAEAEGEFFFCGCEHDHDHECDCAFAGAGAGEHEGFDHCHEHED,False +489,22.0,25.0,26.0,26.0,18.0,25.0,28.0,23.0,BEBEBEBFFHDHDHCHDHCCGCFAGCHCHCDCGCABABAFCHEHBCBCDCGCEHAHAEGGABFDHEBECGCHCHFDADAHHEGFBHAHFDGDCCCHFFGGGGBFAFABGFEFAGGFGDBAHFEGEGEDBBEDDBHBDFDFGGCEFGFBFHGADADHCEGEGDGDFDBBCBCDGBADABAFCFAFADDDBCGAE,False +490,19.0,24.0,22.0,16.0,30.0,19.0,23.0,31.0,FGGAFEFECGHHEGEHEDEFEHAGFBFBFHAEAHAEAEACDEBBHCECACEGBBFBDBCHDHGCFEHHAHAHBEBECGGDGCHBHGFGBDFCGHGHDHBHBACACHBEAABDHEHDHFFBFHFHEBCDEDEDFDGEGAGADBCHFHABDBDCFAEAEBEBECGCGEHHCCBCHCEGEGHFCGEG,False +491,16.0,23.0,19.0,29.0,31.0,20.0,28.0,25.0,DHDBCECECAGFGBBEEEECEDEGHCDGGAFDFGFGCGCEHGHGEDFGCDFGFDDDCDEFEABDEDEBEBHBHBGGHBDBHAFABDGHCECGAEAEAGABHDHDHDHBBBGEHEFEDHBEEEGGCDEFGHGHAHAFCFGFEDCFEABHFHEBEBDHDHACBCFGAGFGHEHBGBCHFGDDADCDADFDECB,False +492,2.0,8.0,8.0,4.0,4.0,4.0,9.0,3.0,GEGFACBGAGECCHCHCBFDGHCCGCGBDBDBEBEFDFBGBG,True +493,21.0,13.0,20.0,26.0,11.0,13.0,10.0,15.0,AACGHHEEDBDBDCDCDBEBFBFEGDCEADDDFAFAEAHHHFAFADEDCHCBCAAGACDDDDDBCAGDCDBEHGHGFGABDHDHCCCCHADAEAEDHDAACAFAFBFEDGBHCCADHBGBDFCFCHCFG,False +494,4.0,3.0,5.0,3.0,3.0,7.0,4.0,3.0,AHFEBAHCHGFGFEFDADBFFCFCGCGCBEAD,False +495,0.0,4.0,1.0,1.0,4.0,0.0,2.0,1.0,BDEEBEGEGHBCB,True +496,6.0,16.0,13.0,12.0,12.0,13.0,12.0,10.0,DHFEEBAFCHCHCEFHABBCBCFGECECEGEBDCDCBBBBFAFEBEGGCGAGFHEDGBGEGCHEBDBHBHCGBHAGDFDFDFDFDHCADFDFGB,False +497,19.0,9.0,12.0,22.0,14.0,24.0,20.0,18.0,DEDAHEBAAGDBHHGABAGCHCDCACFCGCEEACBFAFAGEDDDHHHCHCGFGHBAGAFAHDDDDDGDFDFHFEEDEHFHEBFDFHBAGHGHFHFEDEDFDFDCGBFACAGAFHFEABGEGFGFGFECADAGGDGFFF,False +498,8.0,3.0,6.0,14.0,8.0,17.0,6.0,15.0,GFFDFEGGBEBHAEDGFAFEFDDDAFHCHCDCDGFHAHFHFGDHCEFHCHCFDHDHAFDFEFAFABAEHFHDHDEDH,True +499,0.0,6.0,1.0,2.0,2.0,3.0,3.0,4.0,EDECHDBGBGBHBHFGFBHBF,True +500,9.0,11.0,8.0,10.0,19.0,12.0,9.0,5.0,GCFDBACGFBFAAAAGBFAEGFGCGHEAGHDFFCEDEDEDEDECHBEGDDEAEFDFAFEBEHEHEDEBEBEBCBCBFFEGBCE,False +501,8.0,14.0,12.0,11.0,8.0,12.0,9.0,4.0,DBDBEBDBDFDAGCGFBCBCFFGCDCDEDBBBECECFBFECABDDAFAFAGEFBHAGAFCHCDCGHGHBFBEGEFCAG,False +502,5.0,5.0,5.0,5.0,9.0,6.0,4.0,8.0,FEFEBHHHAHABEBDDFDHDCAFFECEAHCBCEAEBHGHGCGFDEGE,False +503,12.0,12.0,13.0,25.0,16.0,10.0,18.0,21.0,GBGBDECCCFHHBACGDGDGDADCGCBBHDHDHDBDFDFDHEHGCEDEGEFAFHBEFFGCEHFFDDHDHGHGDAACAGBDHGHEDEDGAHCGDGDACEGAHAHDHEHEBEBCBFBEHEADDGDCAHE,False +504,10.0,15.0,9.0,13.0,14.0,7.0,8.0,9.0,CBEEFBBGBGBDBABADFBAAHEBEDEDGFCEBDBHAHBCBCBGGFDFCAGAFDGDHDHGEBEHFHECECEAHCDDEHEAEADCD,False +505,18.0,16.0,17.0,23.0,12.0,18.0,20.0,12.0,FGFABEFDHDHFHGDBDBGBGCACDDDHAHBHFFFBGCGEAEAGABHBGDGCECEDHFAGBDEAAHCEGHDEDEDFGHDDDDEFFAFGDGCFCFDFDACFCEAABGBABCBCFHGGBGEGAACCCCFCGBADADBD,False +506,22.0,16.0,25.0,22.0,25.0,11.0,27.0,18.0,AGCDCDHDBGCGAGDDCDGBGDCBCGFGHCECGHGAEFEDEAEGEFHGBCBCAAAAGGDGEHEAEDEDEBCBGFCFGDDEDECFDHDBEAEDEHGHCCCCABAFABCBAHCHGHCCDCEFAGEHAGAGHEBCHEGBHBHDHFEEEACACDEDEHGGGFBFBGDAAA,False +507,13.0,17.0,22.0,10.0,17.0,14.0,17.0,13.0,GGGCBBBEBHAEAGHDCGCDHFEAEABHCHGFGHGCCFFBCAAHEHEDCGCGCDADEHAHFDFAFCHCFCBDEEAEFHAHFCFABBDBDEGECEBGBGCGCDEEBEBFBEACBCGCGBGCFCF,False +508,17.0,21.0,24.0,12.0,17.0,20.0,19.0,17.0,ECHCHCHCGCFBGAGEBEBEBDCCFHFGCDFFHHBGBGDDDGFCFCGDGFAACACGFHDHGAAHAEBEGCCCFGFADADHBBBBABEBEBCGCHDHBGEHCACECEDDCFFAFEBACAEHEHBGBHEFAFBGHGFBCBEAEAGFFCF,False +509,4.0,0.0,5.0,5.0,1.0,0.0,3.0,4.0,GHDCDCDCDCAEHGCDHHAAAG,True +510,10.0,11.0,3.0,4.0,7.0,2.0,18.0,3.0,HAGGGGAFAGCGEGBGAEBGGEBEBDCEGDBDADEBEGAGAGBBBCGGBGAGHBHAFA,True +511,2.0,4.0,2.0,2.0,1.0,2.0,3.0,1.0,DEDFHGABBBBFAGCGC,False +512,2.0,4.0,2.0,1.0,1.0,1.0,0.0,1.0,HDBABCBCBFEA,True +513,4.0,5.0,8.0,7.0,6.0,8.0,11.0,4.0,GGHGHGDBCECECEGFHDABADEGGCGCECBFEGACFFFFBFCFHBAGGDDDD,False +514,20.0,26.0,19.0,15.0,24.0,22.0,24.0,21.0,FGFEFEFBHGHBEDHHHHEDCDEHEHCBFHGAFAFBFDCACAGGGGGGGHBBABFBFBCHGGBACGCGDFEEEEAEFFFFDECECFCBCBEAHCBADEDAGFDEDBBEBEHACAFAFABHEEDCFGHDAABEBEDGGHGHGDDFEFAHAHBGCGBGCCCABBHBAGCBHBE,False +515,22.0,23.0,26.0,33.0,16.0,30.0,25.0,23.0,GGGGCBEHCBCFEGGFADHDHCGDACCDBDGFCFHBHGAABFBAHAHDGDBDADACGCFDFGFDDHBGGGEBEBEFGFHBEFABEGCGCGHAHFHFHDBDBDCDCDCHFFFHFDFAGEGBABFEDBDCECBCDDHDBGECADEDEFFFFAFDFDECGHDFDFBCGFECHHAHAHGCBCDADAEAFCFCDHDABAHABC,False +516,17.0,13.0,13.0,12.0,15.0,20.0,10.0,20.0,FDFAGABHFHCEEAFCEGGBEBCBCBEBDHFACGHGCACACAHFHDBGFGDAEAEABFDEDHDFAFEBDHHHFHFHFHAHAHAEAFADCCFBBCEHFFFDGDGBEHHHHGCBEFEAEDFC,False +517,26.0,21.0,23.0,17.0,23.0,30.0,24.0,22.0,ABAEAEAEBGGGGGAECECEDFCEBAGHFHAEADCCGGGAGBEBEBEDCDFAFHFHGCCBHAFAFAFHFGBCDDFACGFGHDEEGEFEGBGFGADFCFCFCBAEABCDHHHCHFHFHBHAEFFFCFBECCCFFDFDBCHCADAFHBABDFDBBAHGGEAEHCGEGCDAGAHDGDFHFHFEBABEBH,False +518,7.0,13.0,9.0,12.0,7.0,6.0,7.0,5.0,CGCECBHDEBGBAFCDBDBDACEBDDGDGEGEFAFAFAHCFEHEDBCBDBDCDBBBDCHFBAGAGH,False +519,15.0,23.0,14.0,11.0,17.0,17.0,14.0,16.0,AFGEDCHBBBBBBGGECEFFBACACBCGCBHFAAABCCEEDDDHBBFBFBGEHEFDAEAFFFEHAGABAFHFBDBHHHBEBEACGCGCACDCHEEBEGGDGHGHGDDDCBGAEBEFEFAFHHHFHFB,False +520,18.0,12.0,17.0,12.0,18.0,12.0,16.0,36.0,EGEHCHDHDGDGCADAHAHFCEEBACEEEADAHHBCBEHEHEBAHCEEGCFEFAFABHBHGHDCGCGDHDHFHDHDHAHCHABCGCFBHHAHFHFHFCEHEAAHHBHGEAHHBFCCGBGFHAEAEGCHBHGDGDGAGFHHC,False +521,4.0,11.0,9.0,6.0,9.0,15.0,6.0,12.0,FFFCCHBHCFCBCBFDDGDGBFAGCFEFCHCGFBBBHCHDEDEAEBHBHGAEAFFBEGEHEHEHBHFFFFHD,False +522,17.0,10.0,12.0,14.0,22.0,13.0,17.0,18.0,EEEEDEABAGFEFEHGHBDAAABDBDAEHHAHGHGHDHAEABHHHHHBCGCFCFCDBAGACEEGCGAADGDHAFCFCEBEFDFEEACGHBEFEFEFEDCGFGHGEGDBAEGEDCHAHGDFDGC,False +523,0.0,4.0,3.0,2.0,1.0,0.0,4.0,2.0,DDEBCHCGBGCGBGBH,True +524,25.0,20.0,21.0,11.0,21.0,16.0,21.0,28.0,FGHGHEHEHBHFHFBFBDBEGDCHCGAEAFCDEAAACHEHEHBFFFFAAHCGGHGBGBHCHCDCGAGAGBHHHFDCDAEABBBCECBGGFACHCECEAFAGHFAEHGGEDEDEBHHACCCACBCHDGDGAAABAGFEBHAGBGCFEEDEAEAFBECHHAHBHB,False +525,5.0,5.0,3.0,6.0,5.0,16.0,3.0,8.0,DHFHFEFEADAGEGECBDFCBDDFHCHFAAAFEHHFBBBGDFFFFFFFHFH,True +526,1.0,0.0,1.0,1.0,2.0,0.0,4.0,6.0,HGHCHEHEGGHGDAH,True +527,14.0,26.0,15.0,11.0,16.0,18.0,25.0,17.0,BHFABADGFABCDGGECEBEFEDBDHGFCFDBDBCEFBFHAGBFEFGFHFHCHBHEHFHFHCHCEDBDBEGHGHGCBCBGDEEFCFBGBGBGBCBDBGAEAGBGAGECEAFGGGHGCCAFGGEAEDBHAGABAFAGHHCBBB,False +528,26.0,33.0,22.0,21.0,21.0,26.0,21.0,23.0,HDBFBDGDGHHEBFFCECFBABGGEBEGGAHEHABGBCCCABDFEFGFADACCGABDBFBADADBDAHAHBEGHFHBEGEBCBCBHAHABADCHBGCDEDEDHGGGGGCDBFFFFFAEECHCHCFEBEAADFBFBABDBGEEHEGEFCFCFEAEADCGFADHHFBDBAHAHACABABFBFCFHBHBHCDFGCD,False +529,19.0,28.0,16.0,26.0,16.0,17.0,19.0,17.0,ABADGCGBHDFFFGFGDGFBDGGFAFCGGFHHAAFFFEAAHAHCBCBABADDFFFABDBDBHGDACHCHGBBBBBGEDADAGCBEBHHEDBCBCBDEEGADABABADADCCBCBDFDFCBCHFEEEDEHHHGHBHDEECHGDGDBEEEDEDGDGCBBD,False +530,10.0,4.0,8.0,6.0,5.0,11.0,7.0,6.0,FFBFCDCGAGFEDCDBEGEGFCFCFCBAFDBHAHAHAGACAHAHEGDFCFADEGAFH,False +531,13.0,7.0,11.0,9.0,7.0,13.0,13.0,17.0,GCABEBFBAHHHGHGAAHCHBEBCDAFHFHBCDCDCDFGEGCHAHEHCHDFFFGFGCGAAAHGGGHFCECHHHGAAEADFBFDFDEDAGF,False +532,6.0,4.0,4.0,4.0,4.0,11.0,3.0,7.0,ABCDHFHFECEDADFGHAFCFCFBFBGADEHGBFHEHFHFAFA,False +533,14.0,30.0,24.0,27.0,22.0,23.0,21.0,29.0,CEBEDGCHDGAAABHEHGCGBFBEGDDDCDCHHDEGFHCEFBGBCCFBAEAGABEDFDCDCDHDHGFGHGCGDDFBBBBBDFDADCDGBFEFDBCFCFBDHDGFACAGFDFDEAECFBBHBHCACAHFDEHEHBDBGBHBFBEDCFEEHBHBCBCBHEFEFCHCHEAFHBHBHEHFGCAEGHGHGHGHED,False +534,7.0,14.0,11.0,10.0,12.0,6.0,11.0,7.0,ABADCBEGAGABDBHCECDBEHGCBCBCGCFCFHFHFBBCBGEGHGDGEGEDDDCDEDABAHCFEEAEFEBBGDEHBG,False +535,1.0,8.0,7.0,5.0,5.0,7.0,1.0,7.0,BHBGFHEDDFCBBBBHHHFEFHFCFCACBDBDEHEFECCCD,True +536,5.0,4.0,11.0,11.0,13.0,6.0,6.0,8.0,CDDDEBHHGHDFGCCACEDEDECEGEACACHEBFFEFEFGFGDGDHAEEEABCBHEDCDCHHDC,True +537,28.0,21.0,11.0,18.0,13.0,11.0,21.0,19.0,HGAGAGFDDHGEBDCGAAHGHEDBDFDEGAGHDECCAAAADDGBBCBHBHBHGCGCBBBFBFGABAGCHBGAFHFAACAGDFEFEGGBFHAADADFDADBBBDAEAFHGHEHEHAHAHAHAGEGDCDCHBABABECDGAEBE,False +538,3.0,5.0,4.0,4.0,5.0,2.0,1.0,6.0,HCHGHAFBEBEAEACDCHBEBFCEHBHDDD,False +539,6.0,6.0,7.0,4.0,9.0,4.0,6.0,1.0,CCAGDGDGEFBCACBCGDDBFEFCFEABABCEEEABAEGEGEH,False +540,4.0,1.0,2.0,4.0,0.0,6.0,5.0,0.0,FDDGAGFGCGAGAFFFBCDADF,True +541,9.0,14.0,13.0,6.0,8.0,6.0,10.0,5.0,CBCGEGEFEHAGEDBGEGAGHDCBCGAGAGHDFGAACBBDBDFFCFHFDACACBBEBECCCCHEACBBBBB,False +542,16.0,16.0,8.0,16.0,13.0,11.0,10.0,17.0,EAHAGFDCGCGDEHCHBAAADHDHEHEFBGBABFDAAADBDADADHDGEGCGHGBFAFEBBBBHFDFDEBEFAHEBDGFHCHCHGDFABABDHHHAEBEHEDEBCCF,False +543,21.0,26.0,17.0,27.0,29.0,23.0,26.0,18.0,GDEHHBFFAHDHDCBHBGEDBDGAGDHCEEEBFFACBBEDGFCFBEBECAFDDHBHDEFEFEFEGGCGBHFFCFEHBHEFBHBADAEAGAFBFGEGEGCGDEDEGCGCBDFDFDADABCFEBBBDBGGGFGCDCDCACFEDBGEGEGHABGEGEAAAACCHEBEDEHBABFGFHHEHADGDADADAD,False +544,22.0,22.0,21.0,19.0,23.0,23.0,21.0,20.0,CGDGDBCFDADCCGDBDHAHCHCEDFFGGGECECEAFAHCFDDEDAGCGCBDEDEAEHCHCEEECEFBFHDHGHGEGCHFEAEAEFFCFEDEABHHHGFBAGAGBDEGECECECHBHAHGBBFBGBDFDGAAFAFGBBCBGBFHEHCBDFFFHFBAAHBFBAAAFAGABDB,False +545,23.0,25.0,25.0,15.0,25.0,17.0,21.0,33.0,GAGAGEEHHHFHFHFHEHDCFHABBHBHBEBHFGBCCACACACGHBADHBECECEBABECCHCFEGHDCEBGGEBEBEFHHADCDCDFDHBHCAEEHEHFHGHGHFADCGFHCACACACBCEGDFHCABGDGEGFCDHGHAAAHBHBHBEBHBHAGABEEGEDEGFBFCGEDAGADDBBEAFCF,False +546,3.0,2.0,2.0,4.0,0.0,4.0,0.0,0.0,ADADAFCFDBBFCFD,True +547,13.0,21.0,3.0,11.0,13.0,5.0,12.0,11.0,GHBADHBHBGBEHDHEEFGHDHGFEDDDEGEAEDFAAGBBCBAGAGAEDEHBHBABABAGADBEBECEAEBBBBGBHBDFGCADBFBHG,False +548,25.0,24.0,22.0,17.0,28.0,18.0,39.0,21.0,CDCABDBHBGBGBGBCECBABGBGAHAHBFEEAEBGAGEHFACACDEGEGECHAEGEHFHFABEGHFHAHGHCDCEBEGDBFAFHGEGBGAGDBDBDBEFECHFHEBFGEGEGECAFABEBGBGHGFGEGCCCCHGFACGBHAHAECFGAEDHGHGDDDEAFADGDGDCAEGGACFBFAGEGACCEHDCDGGFG,False +549,3.0,2.0,4.0,4.0,5.0,8.0,5.0,2.0,HFEFGDGFBFDFEEEFEFGBGCCACDCAGAHFD,False +550,1.0,3.0,4.0,3.0,7.0,2.0,2.0,6.0,ECEBHBHGHBECEFDHAHECEDEDGCHF,True +551,16.0,22.0,21.0,26.0,28.0,20.0,19.0,21.0,EGEDEBEAEADDDCFCABGEFFHDBECHBBBBAHAFFCCDDDDDDHGHEFAAAAAGGBGFGBGCCHEHFBFHHDCDFFBFDGEGFCABBEBEBECDGFEECACDDBCFEDEHHDBDFHFHCHCEGGGEGEADCDCEGEFFHHGCCBCBDBEBEAEAEAGDFHCDGDHBHEHEH,False +552,4.0,5.0,6.0,11.0,3.0,11.0,11.0,5.0,GCCDFHFBDDEDECGCGDGHABDDGGGDHAHAFGFGEGFGFABDFHFCFDBDBFFC,True +553,5.0,13.0,12.0,7.0,6.0,1.0,8.0,8.0,BGDACECGDGCCCBCHCGCDBHHGBEAEAEFBCBEBDGCGDGCBABABEDCHHHHHBBDB,True +554,21.0,23.0,19.0,23.0,24.0,21.0,32.0,21.0,FAGAHAHFHGHBEEFGADABCBGBGFAHEDEFGFBHCECEHEHDGDEAAHGGGEGFFDFBCHGAGHCDGGGABDGDADHFEBHBHGGCACBCBCBGBCFADADGDEDACBGHEFDFHFHFBDDDDBHBGGGCDEFEGEGECHCBCBEBEBEFFAGBBFACECECDAEFECGAGEFDGGAADHDH,False +555,11.0,14.0,17.0,9.0,22.0,14.0,9.0,22.0,CGEEDCDADADBDBFFFHCAAEHHHEHEHAHEFFCFBGHHHFHCHDHEBGFGFBEECFCEEECGCGHEEEEADHBHAABCCACFCEDHCHCHBHBDBECGCEFFGFABBEBEGHAHBE,False +556,4.0,3.0,4.0,4.0,4.0,1.0,0.0,1.0,BABHECAAFBDCDEDEDECAC,True +557,11.0,15.0,15.0,16.0,14.0,18.0,14.0,14.0,BCBCBGDGCGEAHHEHGAFFCFHFCGAGACEBEBEBAFGCCDGBCEFDFDAEADDFDCEBFBFBEHDHEHEGEGBGHFHDDDDCCBGBCBHAHDEFFFGGCHBEAAAHFFDFDFDHC,False +558,5.0,2.0,3.0,3.0,1.0,2.0,3.0,2.0,DGDGACBFHFHAEACABACDG,False +559,29.0,26.0,17.0,17.0,20.0,26.0,24.0,23.0,DADCDFFHFAFACAFBDBACAGABFGFBHCHCFFEFEFGHGCBCAEGGGDBDBABFHFAEADDDEDEHAAGGDBHGFFFFCGAHBBGBGECEGEGEGEBEDCFFDFCCEAAFDHAEBFBFAHAGFHCCGBGBGBGAGABEDADHEBEHHAEFHAHABCBCHAEAFAEBHGHBBBAGDHHHHC,False +560,7.0,9.0,14.0,11.0,8.0,12.0,13.0,5.0,FCDCEFEFGHDAABACGCGCGDEBAHHBCCFCFGEGDBDBDBAFECDFDFEGGCAFABCFGFGEGHCDEDGDGFCBCBH,False +561,16.0,32.0,21.0,19.0,21.0,20.0,22.0,22.0,AFBGBGHGEDFAACDCDCEFEBCFCGHGHFDABABAHCCEAHBEDEDBDCCHGHEBEBEBCDEFGDGFBFEDHDHDBBBFFEGBGHEDGDFBGBACDGEBEBHBHCCGHGHGDGDGHGHBCAFHGHGFABAFAHAFCBCBFAHDHBBCBGFEBABCBCFCFEEBCFEDEAHBE,False +562,18.0,21.0,6.0,6.0,14.0,3.0,15.0,20.0,DGAAHCHBAFHBHBGCAEAEAHAEAHHHBCBGGEBDFAHAEAEBGAGAHDEGHAHBEAEGHGHBABHBHEDCGHGBEDGBGEGBGBABDBAEEHFHBCBCBHB,True +563,19.0,18.0,15.0,19.0,14.0,16.0,17.0,24.0,FAFAFABBHDCDCDFDCAABFCEDBBECDCDFFAGADBCHGGFHDHGHEECEGDADABEHHHHCHDHDFAHGFGFBDBCBFHAGABDBGBFDGGFCFCBHBHFHEHEHEGAGAHAGABAGABEECDCHHEBEDEHAGCGHDH,False +564,3.0,3.0,2.0,1.0,0.0,0.0,0.0,2.0,BABCBDAHCHA,True +565,8.0,12.0,12.0,9.0,13.0,13.0,12.0,17.0,BFBFEEHBFAFGGGCHDHDHGCDCGEHAHEEBBAEFGCGCHCFCFDBBBHCEBEHEHFGAGFFHFHABDGDFDFBHAHDHEAABCEGEGEDCHCHC,False +566,24.0,19.0,7.0,22.0,15.0,14.0,18.0,21.0,AEADAHECBGBFHGHDHAGDGHGBGBHFHBDDDHGHDHDADHDHAHDEDADGFEFGFBDBDFAAAAABEFDHHHEGBGAAEDEGEGAFAFHHBEEHCGBEADAEFFBFDFDBDBGBHAGBCBEFDHGCACBCBAAACAGE,False +567,18.0,34.0,25.0,23.0,26.0,29.0,16.0,24.0,CHFDFHBCBDBFBHEEAEABABCGAFDFDADADADBBBCBDBFCEEEFFAFDBDBGHDHBBBFFFDABFHGCABABABAHHHHDFBFEFHBCDCFCFBFEEGECFHEGEGBBDDHDEDHFHDHDFBAECCBHBEBHBCCCBDBEGHGCFCACEFAGEGEGCCFBFEHEHCGFECGFDAGFGHCCCEEEBEHAHDG,False +568,10.0,3.0,8.0,11.0,10.0,4.0,2.0,8.0,EGEDEHEHCDCEAEAEAFFEHCDDDCACHBHBDDDHAAACAEBFAGAHDCCFEDHD,True +569,16.0,11.0,9.0,12.0,15.0,17.0,17.0,12.0,EAEDEACHEAGBHHFFAGGDADADHBHAFFGDEDEHFBFCGBGFFDGHAEAFBCBEAECDADCGCGFGEGEGAGDEDBFFAFAFCBHAEAEGEGFGFDCHCGFBHBHBH,False +570,5.0,3.0,10.0,3.0,5.0,7.0,4.0,6.0,DADCHHGACACECHCFCFHDEGABAFFFFECECFGGHBCBCEH,False +571,19.0,19.0,10.0,25.0,20.0,11.0,12.0,21.0,EGEGEDDDADCBFBFCHCHGAGDHDHDADGHEDDDDHBHBHCADEEEDDHDBCEAABABFEEAEGHGHFEADDDCABHBHBHFHFEEEEFDCEEGCBCHGAEAGABFBHAHEHAFABHBFDDDBDBHAAFBBAGGCD,False +572,9.0,14.0,14.0,11.0,15.0,15.0,19.0,10.0,EFEAEGGGDGDADFHFGFBFBFGDGBBEBEADHGCBCBCGCECGFDCBCBFDFGEDBDHCAFEFEBGCHAFGFGEEHBGCGCEEEBHCHBADCCGGHAHADAGFHFE,False +573,4.0,10.0,13.0,15.0,11.0,8.0,6.0,4.0,AFCCGEEDEBEBAHAHADFBCBCBEFDGHBEGEFFBFDDBCECDCDCECEDDDDDGDCDCEBBGDHFCCGF,True +574,15.0,27.0,18.0,27.0,33.0,20.0,18.0,26.0,FACGCDEDBABABADHDBEFECGDFHHEBCBCGHHAEBHBHGDADGDGDEEEDEBCBDBEAFHFEDGDGDBCHEAADEDEAEDHCHAFDEDHDACHBHBHEHECFBABHDEEEFEGBGDDHGFBFBFCFCEBEBFFCECEGEFEDGDCBGEGHFCECEBGBHBHDHCEFFFBGBHHHEFAAHDG,False +575,16.0,17.0,13.0,14.0,16.0,19.0,22.0,14.0,HBCFCFDFEGAGAHHGEGBGDGFHEHAFBDBDCHCHGFDEDEFHFBEBHBHBEBHBDFDEDEHEGEFFACACGFHADGFADGBAEADAFBCHEFFBEBGBGBACGGFGFAABGGDGFCCACAEAECDGGGC,False +576,21.0,18.0,24.0,12.0,15.0,14.0,8.0,14.0,CDCDFBACHGHECECEDECECHHAHBGFAAHAGFEBCHAGBBBABCBADCFEGABABCGCFAFEBHAHDHECACHHFCBBBEBECFCFAFAHAFCGDFDFDBEBDCACACADBDEHEFEDGCACAC,False +577,11.0,6.0,10.0,4.0,4.0,6.0,15.0,11.0,HHGHAHGDGCEBABABGCHCGCECHCACHDFBABFHFCAHAHFFBFGGGGGGGACAGECDGAADEHG,True +578,13.0,11.0,13.0,13.0,10.0,10.0,11.0,13.0,HDHDFAHCHGEAAAACGBEEHHDEEEDADCDCACACDGDBDBCFEAGHCFCABFBFGCEFBHHHHGBGCGCGEEHAHFBFDDBDBCGDGAFAFB,False +579,16.0,20.0,17.0,10.0,16.0,13.0,17.0,18.0,HBHCDAHECCCCBHGEFCBCGFFAFACBDGDCHBHBCBEBEDGDFEHGHBHECCCEFAGAEHDGDGHBFAFAGAGBGBGBEECCAFAFDBBHFECBGHCHBHDHBHBAEEEAEHEAGAGFGFGDABA,False +580,19.0,23.0,27.0,23.0,24.0,28.0,24.0,26.0,FGFGCHDADGDHFFDCDABFFFFBCEAECEHADCDFDFABAHABDEDBAHCCCHBAAFAEGEGFGHDHGHBHGHDCFCFCADEFEHBAEEFGCDCGGGGGEHFGCGCFFHFHGHBCBDBDCCCGEBEHFBFCFEECFGHGHFHCAEBEBEGHGHFEFDCHCBCBGBDBEAAABCCEAFBHBHDHEEGABDDDED,False +581,14.0,16.0,19.0,20.0,20.0,20.0,13.0,20.0,ACAFBEAHDHEHBHCABBCHFHCEEGCHHFCDCBBEBHFABGDHFHFHBHBHBGDDDCFFHFBFGFECDCEAGAGACCCGCDCDEDEDADADFFFAFAGHCDAGHFEEGHCEEEHECECEGEFDFEEGDDDGDBBFBFBADH,False +582,13.0,15.0,13.0,20.0,21.0,19.0,19.0,16.0,EGGAGAHBFFEFEHECDCFCBGHFFGAGAGEGCGAGBFCFDDDEBEHEHCFBDDDDDDADAFAHHCFDEDBFFFFHAGCBDAFBHBEDGFGCBCBGEGEDCDCDCFHEHGHBDGEHABEGAGHFEDAHEEEEEBHB,False +583,6.0,13.0,10.0,9.0,17.0,8.0,10.0,9.0,FHFGBBBBABCCDHBEDHGFDEHCGCBEBEHCFCFBFBDBACFHGHGEEECECEDEDEHEDGCAEADFDGEAEGGGEBABEH,False +584,18.0,27.0,27.0,16.0,19.0,28.0,14.0,16.0,FHFCFAFHHBEBFBDCHBGEDBAFFCBHBCFGFGCGCEEEDEDBABGEFBGBAFAFHEGCGCDCDBHHCHAHAHGCECAHFHFDEGHBBCACABABFBFBFAFCDCDBABEBECFFGBECCCHCFAFDDDDFDBECEAEDBFCDCEFGFABABCCGEHCABGFEF,False +585,26.0,16.0,22.0,22.0,20.0,21.0,22.0,26.0,FHDHDHFCEBBDBAAAAGFGCBEDHDHGHAEAECDCBEBHCHAHGGFDAEFCFHHHEECCCDCDCDHAHABBECACADAHCDCDFBBEDAAGAFFHCEEEAFAFGFCECEFACAEAFFHEGFHCAGECFFGBGFGDBDBABAGGGGGHHHAHDDDHHHAHDGEGFGBGBFCEDGD,False +586,8.0,5.0,12.0,4.0,4.0,13.0,13.0,7.0,DFDCCCCCCFEBEBDFFAFGCGCBFDFBAAFHGHGCGAAHGFAFGFGCGAGBCHFHCGGHFHEAEG,True +587,4.0,3.0,2.0,3.0,2.0,5.0,3.0,1.0,BGGGDBDHDFCAEAFCFBFEFAA,False +588,7.0,14.0,10.0,16.0,16.0,9.0,9.0,13.0,BCDFHCGFGAEFFFDDBBHBFBHHGAEDDFDEHEGEGEHADFEEHEGEDEDEDEHHBHBDBHBDCDCDBBFBABACACEHECGHEBDGDCCCAG,False +589,41.0,28.0,27.0,20.0,22.0,14.0,25.0,23.0,EDEHHHEACAEAEGECBBHBHBEFAFEBAFHHGHAHACAGBDBEGCDEHAHADACACGEDCCCFBBBBBFAADACAGECDFHGDDBDCDCECDABAFCBEGEDFCGBGDHACABGHECBGGCDCGEFEAGCGDAAABABABDHGEAHBGAEHGBGBFCFCFEFBHGHBAAAAHABABADAGACACGCACHDHDHAFAGEG,False +590,25.0,17.0,16.0,9.0,20.0,24.0,14.0,17.0,HDFDEGEFBBECCBDBABFFAFDFCECBAGAEABGFHCACAFAFAFHEHEHECFCHEHEHECGBDBAFEBCFAFCFAGGCFCABHGABFFEGAHAGAGCHHEHFDFBEBCBEFAFAHAEFEAAHAHBHBGDGDGCEADAGEF,False +591,17.0,13.0,25.0,18.0,20.0,19.0,18.0,19.0,ADCFCHDBAEHEHEFEACAFAFDFEFECEGADHDHEBCCCCEHHGBDBDGCCFBGDDCGABAEAEDEAFAFCGCFHFEGAGDGFHCGCEHEAGCHCBDEDCFEDHCBEBFBAGEGAHCHCBCBAHACDBDCDCHFHEGFGFGDGHGFFH,False +592,4.0,14.0,3.0,5.0,17.0,15.0,9.0,5.0,HGFEEHBHFFEFHFEGBABFBGDFBBEFEDGDEDECEBEFEAEBBBBEBFAHAGFDFEFEBGCGFGBGFECE,True +593,13.0,8.0,10.0,11.0,8.0,10.0,5.0,8.0,EAEADADGFGCDDFBFHHGADABAFHHBAEABHHGBCFCFDFAFDHDCDCBFBCCCBCEEEAEAEFDAHACDG,False +594,16.0,13.0,15.0,7.0,3.0,9.0,20.0,22.0,BGBGCGHHHEHGAAFGCGBDFAFBHCHBDBCCCFDAHHBGBAAABHHHGHGBABABCCCCCDGHGHCHAHGEGDBFGFGCGAHAGFCHGGGAHAHCHFEDHDAAF,True +595,12.0,10.0,9.0,7.0,8.0,10.0,12.0,10.0,AEFDFGFGABHBHBACAHFFEECEFDFGBCAABBCDCGEBEBHHHHFBAEADGDGHGDGDCACGCACAEFHAHGGGBF,False +596,12.0,14.0,7.0,5.0,7.0,8.0,16.0,11.0,DBGBABFCGCGEGBGCHCABEEHGGGHGHFBEBABFBFBGGGGFDFCGABABAFAHHHHBEAAADDHCFEHAHBGACDGE,False +597,12.0,31.0,25.0,23.0,29.0,22.0,19.0,20.0,GBCAEDEGEDHCHGFBEGCCDCGAFBFAFEGBBDBDBDGGCEHEHFHDCDCDEDFHHBGBGCHABGCGCFHFDEBCDHDAABFBGBHDCDCEHEBFBFEFBFHEHEGEBBDBEBABCDGDBHBDFDFDACCEFBCBFHFGCEAEDFCCDCFGGEEEAEAFAFBHBEBCBCHEHCHGEEEBE,False +598,3.0,2.0,2.0,2.0,0.0,4.0,2.0,0.0,DADAGFCFCBGAFBF,True +599,18.0,18.0,17.0,19.0,19.0,25.0,24.0,26.0,EFEFADADEGEGBBHHABBHCCGAFDHDFEHHHHHHGAAADGHFHGGGGDEACHCHCFCGEGEFABEEGEHFCFDFEBGAHCHGFGFGFGFDDHEFCFEBDFEACAFHCHFBADGCGBADGDAFCHCHDDDFDFHCHBHEEEBEBGBABABABCBFFHFDGCGBGD,False +600,18.0,13.0,8.0,18.0,9.0,20.0,11.0,10.0,FAHEFAFAHDGGGGHCBEGABABFEFAAGAGAGAGAGBHBHCFFDHBHDEDEDABCFCEDEBEFADDBFFCFHFAAGDDDDDDFFFFHADFFFBBBCDADCCADHBE,False +601,28.0,16.0,18.0,22.0,25.0,31.0,31.0,28.0,DHDHCHCEGGGGGGHGHGABHGABAGDGEGBACHDHBGADFBHGAGFGDDADGEAEACHBBFFHFEGEFFAFAFGFEFAGADDFAFCFGHBFFEDBACABFHFCCCEEDFDCDAAHFHEHDDEDGHEFCAHFFBCGCGCACABAEAEHDHFHFHFCEDEDGAGAEEEEEFDAGGGHGHFHAGEBHBAEFCFBFCEHBHD,False +602,19.0,22.0,22.0,6.0,18.0,28.0,18.0,32.0,BEHEHCBFBFGAGFFFHEEGEFFGCHCHFABHHCCBFHFABBEBCACAEAFHFABHCHGBBAHEEEEAHAHBHECACAHEHEHCGBFFHFGAGCCBCBEFEGHDDGDHFHCDAHHHHDAFBFAFHFHGHGACCCACBHBGBGBCFGFHFHFGFGFAEBCGCBDEF,False +603,6.0,3.0,3.0,0.0,3.0,1.0,2.0,3.0,AAAAHHHEAEBFCEGAGCBCB,True +604,20.0,12.0,4.0,14.0,4.0,16.0,10.0,13.0,BHADGGGBAFFHAEDBAFGFCFHFHDHBHBGFFHADDEHFFBFGHAHAHABACADFFAAGADAGAGACADDEFEFDADAHBGBABDBDBDCHF,True +605,13.0,12.0,3.0,10.0,9.0,12.0,19.0,5.0,BFBFCDGDBDAGAFCHBBBDHGADCEAABAGFGFGEGEGDGFAFEGBGAGEFFGFGEDADBBGAGAGEFEBBHGHGEDDAFAH,True +606,25.0,22.0,15.0,23.0,20.0,14.0,29.0,17.0,ABABABGDEFEFEHBAAAFDDBDGDGAGEEBHFFCAHAGABACACHEGDGDFDHGGFFHFBEDECFGHCBAGDGCHBGBGCGFDADECEBEAEADAFEBEAEFCBCBCBHBABGBHAHAGAGDDEEEHBCEADGDGDHHFDGABDBDGGCGCADGGHHDHGGEGC,False +607,7.0,12.0,19.0,9.0,3.0,6.0,12.0,7.0,CHGGCADECECGBGCGCEHDAFACDBGGFABCBCBCBCBFBCGCBCBCBFHADACADHDCGGGDFCHGFCHDHDB,True +608,15.0,15.0,12.0,14.0,12.0,4.0,21.0,15.0,BGBEFEGDBCGCGHHEGCFAGEBFGHBCCEGAHACGBDBGBHAHGHGHEHEHACABADADAHACBGDAEHGHBDBDBEBAAAFCGCGDEDCDEDHDAGHGDGBGEGDC,False +609,11.0,19.0,6.0,5.0,9.0,14.0,11.0,10.0,BBBBGBFBFBABDHAHFBBAHEHFCAHGGDGDFCBCFCGAHBDBGBGFGHAHGBEEAFFFBFEFEACACEEGEAEDGFHAHBBBF,False +610,7.0,6.0,1.0,2.0,7.0,8.0,15.0,3.0,GGGGGDGFBAEAEBFHGHDFAGBEFEFGFGBHAGAGBCEAEGBGEGAFF,True +611,9.0,11.0,18.0,12.0,13.0,14.0,18.0,18.0,DABAEGBGEGEGEGFDHCGCHAHFHFCCCCHHGADFBGEHAHEHECFHEHEAGABDGEBCBFFFGDGBGACHHHDHCFCDCHHGDCHCBCDCGCBBDADGGGEDECBFFFFEF,False +612,1.0,6.0,5.0,8.0,3.0,4.0,3.0,4.0,BEBEBGBFBFDDCHBDFCHDGACHFHGDCDCDED,True +613,5.0,7.0,4.0,9.0,3.0,12.0,4.0,8.0,DEEHBFGFCHBHDHFAGDBDHDFCFEBHHHBFBABAGAGDFDCDFFFFCFDA,True +614,5.0,4.0,10.0,9.0,2.0,6.0,6.0,7.0,GCBCBCGGBFHHCFCHHDDDDCBGAEACACFDADCCAFHFHDHDEDGFG,False +615,20.0,20.0,21.0,19.0,32.0,21.0,14.0,26.0,FCCGGEHECEDEDBBECHCHCFGBEHECCCCCHCGCDCDEHAGCECEDDBEBABABEBEAAAAHAHEFAFHFEFBFBFAFGEEEAEHEBGHEHDBCBDAAEFFHCGFHHHGCEAGDBEHEFEGDFBFAHHDBCHFFBEGEGFHECEADADADBHFHAHDDFDFHEAEBDBDGH,False +616,4.0,1.0,4.0,5.0,3.0,3.0,4.0,3.0,AGAHCHBGDFDCHEDEDEFCFCDAGAG,False +617,14.0,17.0,16.0,17.0,18.0,16.0,11.0,15.0,EFEFHFABEBEGEAEBEAECBDHFEEGEGBGDHHHHHBHBHBHAFAHDBFHABDDFDHBGDECECEFEFGDABAFAFABDHFBFCGCGBEFCDCEADDDFACAHDCCGDDCBCGCFCABECGCD,False +618,29.0,30.0,26.0,14.0,18.0,25.0,13.0,17.0,HACCBHBFAFBFBFHFCBAAGAEBEFDDBDAAACACACEEDDAEFGBGFEFCABAGAGAGFGCHCAGFBBDFHAABFCFCFDHEHCFBFBHADBBBBHDDBCFABBEBFBADAEBCBHBHFHCBDDHCHGHCACAGAGDFCFEAEBECECECFCECECGHEBAFAEAGHBCF,False +619,31.0,22.0,24.0,19.0,30.0,25.0,19.0,29.0,CFHEHCGFFACEHBDEEGGACFCACAGAHAEAFDCGBACEFGAECCAGHBHBDBAEAGFBABAGACAHHHAHCHCDCDAGGGAHAEAEDGGCEHFHFHFDGBHBCEHEDEFEFEFEAADACHFBDBDBDBFBFAEHFHBHEHEGEDEDCCEBFBFCFCAHDBFEAEFEACAFADEBEHHDEGEAHBHCHDBGBCDHFGF,False +620,18.0,17.0,15.0,24.0,21.0,15.0,18.0,13.0,ECDGDBDGDGDEAEBEBCFGFGAGAGHCDEHEHBGGGFEAAFBBDFHCDCEEEEGAGAGEDFDHDHAFAFHEHDADADBDECACEDDBHFEGECADDCFHBCBCHCDDFDGBBBEAECEDEFABAHCHGDABFBFGFCBGA,False +621,0.0,2.0,1.0,1.0,4.0,1.0,0.0,1.0,FEEDEBEBHC,True +622,14.0,20.0,14.0,20.0,27.0,29.0,12.0,26.0,CDCACEHFHFHBHEFEDEBBFFFFBFECHHAHEHEDGDEEBFHFHAACEDECCCCEFEHAHBHDHFHFAFABEEEGEGEBDAHEEEEFHDDDGDEDABHBAFGFEHABFBABDBFFFHFCFHFBGCABBGBHFHFDDAHGFEFEDHCHDEBGGGBCDDDCGF,False +623,16.0,25.0,17.0,19.0,21.0,19.0,21.0,15.0,BFDFDFGBGDHBHEDCACFCEHEDEBCFDEDADBDACADDEGEGHAHBHFEBCCCAHEHEBEBAAAAGCFCFGFBEEEHBHEHGBDBDAGAEAGBDBGFEFGBCBCFGEGBGHDHGCCAADCDCBFBAGGFGEHDFBEBFBFDFCFHBGGGEB,False +624,23.0,27.0,21.0,27.0,12.0,19.0,33.0,26.0,DHAGAGFBFCCHHGGBCBFDFACGBGBGHCABACAHFHCDCDGFGFCFGFCAEGHGABABEDEDHFHFDFBGHGEGHAHBHCDAGAGAGBBAEAFGCACBFBDDHGHBHDGDGBGDAAAAEBBGBDBDCACFCHCBDBCCCBGFFHDHDHEGEDEHHDDDHBGBHDFFEBDDEEGGGGAGHCHDBAGD,False +625,17.0,22.0,27.0,7.0,24.0,19.0,26.0,18.0,GHECEGFGAGCBEEGBGHGBEBEAEFGFAFCFHGGGGEEECBFBDGGCGCEDGFBHBCBCBCAGABEGEAEABFFFBFBFHEGFGACAEFDBCBCAGAGAGFFCCBEHCCBCBDHCBEHCHCACEBFBCGDAHFCECEDACAEHHHHHDAFGHCHCEGEH,False +626,21.0,20.0,18.0,14.0,19.0,24.0,20.0,19.0,FGFGDBFGAAHHDABADDECCHFBGCEEHGHGHGAFHCHAHBCBFAFAFABBBABADDGEBBFCFCFCFCBCDCDHFAGGHGHGAGEHBFAFCHHEGEFBHDHAHAEDGAGAGEGCDEHECCCBBBAFFFEFDADBBEDEGCFBFCGAEEEEFEF,False +627,22.0,20.0,15.0,21.0,16.0,16.0,15.0,16.0,GBGEFDACFGFGHBHECCFAAAEEGBCHCBCFADHDHDBDBDFDADABAEDFBADACBCFCFEHGCEFEAEBHDHDFDEEBBHBGAGDGAEAEGGHAHDDDDFDGBBBAAAABDHGHFAFECCCECHBDBCBFEFGAGAHH,False +628,7.0,15.0,8.0,13.0,14.0,12.0,11.0,8.0,DEDBDHFHDCDCBBBCBDBFBFCGHGAGEFAFAEADBFBGBGHGDCFADBDFEFEDECEFHHCBEAGGGDEBECEABBGHGFDHEEFE,False +629,1.0,3.0,3.0,8.0,6.0,2.0,4.0,5.0,HEHDHDHDEFBGBGDDCDHBEDECGCEEFGAD,True +630,11.0,10.0,7.0,6.0,8.0,14.0,8.0,5.0,CAHAHABFCFCACFCAHAGDBCEGHFHEBDFAGAGABBBEBCFEFEFBFAFBDEDEGGDFDABFFEFGG,False +631,14.0,11.0,20.0,21.0,13.0,15.0,14.0,16.0,HCFAAHBFCFAFHFGDHFCFBBBEBEAEAEHEHGDDBHHHFHDCDEGECFHFDFDADACADHGEDADHDHDCDCGADDECEAGBBCECDGGCGCABAHFGCDCGFBHBDCDGAGCCCDCGEFEF,False +632,4.0,8.0,5.0,12.0,1.0,8.0,6.0,3.0,CAHAEDBCCFGDBDFFBFBHDDDDDADCGBGBCFAGDGFGFHDBDBF,True +633,3.0,4.0,7.0,2.0,2.0,6.0,5.0,5.0,CBCECACAFEFDAHBCGFGFBHCHDHCHGGFBFG,True +634,15.0,14.0,8.0,23.0,21.0,16.0,17.0,8.0,GDDDADADACBFGFGFAFACADAEEBEBFCGBFHFHGEDDDFCGABCBDHDHEEFHAHGEFDFEFBFAGAFEGDGDGBGDEDEBHBDCEEEEGEBCDDEAECDDDEGGGAFAEBFBGHEDAB,False +635,16.0,23.0,27.0,12.0,33.0,22.0,20.0,34.0,HEHACECAHFBGBEBHHHHFFCECEHEAEGDGDHAHBFFFFFFFGABCEFEBECECHABGCGFHEEEEEEGBCAHEHCHDFBGBCBCBHHGFBHDHCHEHEHCFCGCGEFHHHCDGDEDECBCAFEFAGHDCABHDAEACCHGHFBBHDEAGBGAFDDGCACEFEFEHEHEBEGCCEGBGBCAHBHB,False +636,18.0,21.0,19.0,22.0,14.0,15.0,21.0,26.0,GHABCDDDAGGFFEFDFHBACHDHDECGBFBFAAGECECDAFBHCDCEBGBAAAGHHEHEHEHEBAFDFCACECECEHHHCHDHAHAHCDBDGGGDHDBCCFCGHHHGDDDBEBFCFDGAFBFBDBDBGBGBABHHCHGHGDBEGAAHDCGAGBGF,False +637,7.0,11.0,15.0,9.0,7.0,9.0,10.0,13.0,DAFBFHGDGAGCDCDGHBCECFCGCDEDHDHBHBFBEGEHDADBBBBGFHHAECHGHGHBFCFAACCCFFHGACHCBCECE,False +638,23.0,18.0,27.0,21.0,18.0,14.0,17.0,30.0,DEDCHCBFEAEAEABAHGDGDADEBEHCFDGGCCCCDCBFGFCCHDHDHFBABDHEHAHFHCAFAEADHDHCHEDACCGCGCGCBAFHHHECDDDBGHHHCHBHAHECFBBGBDBFHAHGHCDGHGCGCBBBGBABFGCGAEEDFDAEHFHDHEEACAEFEACHCAAA,False +639,8.0,5.0,5.0,6.0,7.0,4.0,6.0,5.0,FGEBDBDBGHGDGCAHAHCDAGAFAFBEBEGEFDCHAEECEDACAH,False +640,25.0,30.0,19.0,18.0,18.0,25.0,21.0,28.0,DBGBFBFHFHCAFAFACGCHCHEHEGFGADHHFEAEGEGHGEAEBDADHBABDGGGGHBHDDGAEBDFCGCFFGACDHBHFHCHFAGHEDACAHBDDDAHHEBEBABACAGBDEDGHBHFHFCGCDFBFBFAHGCBDDCBAEAEFCABABACACEFHFBAEHEGBGBHBFFHBEBFBFBFHCBC,False +641,10.0,7.0,19.0,15.0,18.0,26.0,16.0,17.0,EBEBEADCFGFGAADCEFHCAEDEAEFBHEHDGDGDBHCGCFHFHCHFEFGFGCECFCGCEDAFEGDFCAEADCFEFHHHFDFGFGAGDGDFHHGACFBHDHCGFGFCHCHCHCDEECFFFFEBEBFD,False +642,17.0,19.0,31.0,20.0,20.0,27.0,31.0,22.0,EFGFHEBFAHAHFHGCFCFGFHFBFDHDAGAGBECCHCBGBFEABDEGEGFCBDDFEFADADBFEGEBBAEHEHAHAFGCGCGCBCBFGFCACHCECGCBCAGFHDBDCAFGCGCGCGCDDDCDGDGFBHGFFAHCFCFHECDGDBECCCDCEGEFBFEHHGAGCGDHAHGHEFDHAGBGBGHDECE,False +643,10.0,16.0,8.0,13.0,16.0,18.0,19.0,19.0,DBDFCEGABABHBFGAHEGFFDHCFCFBDHHACAFECHHHHGFGBEHEGEGEGFGBBDBFEFHFCEDECFAAGFGFEBAGHEHEHEGDBDFDFBEBDBDFDBGEHCAAGHGHGBGHGHD,False +644,23.0,23.0,24.0,17.0,10.0,17.0,18.0,14.0,BGGGGGEGBACCECHCHCACDBAEFEFHAHACFGGADDCDCDCDGHGCBHBAAFGFGFABBBBFBHGFAAADADCDEACDEACBHEEFCCHCHAFBCHGEGBFDFHEBBHBDBCHDBDBGFCFBDCGFGFACABBBAAAAAFDCDC,False +645,19.0,20.0,19.0,12.0,21.0,19.0,19.0,26.0,BCHEHEABABAHAHDHBEDEAEGECEBECAHDGCFEFCHHAHDHDHFBDACABGCEBHBCFHGCCCAEEDAACABBHGHGHFHBEBHDECEBDBCBFEFHHHGHGHGHFHFBDGEGACEFDFHFEFCGGGAEFDFGCGABFFCFCGBGAGFBAEA,False +646,24.0,19.0,25.0,16.0,26.0,22.0,27.0,28.0,DADGFHCDDBDHDHGGAEECHHHFCAGACFCFEDCCECEGFBFBCBGEHEACBCBGGHGAGFHCGCGEFEDAHAHFHEBBBHHAAEAECBGAAFBGBHBHAAFEEAECEGHGFCDCHHHHBDFGFGFGBEAFHFDAHAHCBCEHGHGFCDGDGCGEFABDBFBAAAHADEDEGCGHECEFEFECECG,False +647,19.0,19.0,11.0,23.0,12.0,13.0,15.0,22.0,FGFAADEGEAEADGDFHAHBHDGGGHDFBHBDDGDCDHBHBHEHECEDBDBEBHHDHEABCCGFAHGGEADAGFDAHEHDHDCDGDHHEHFFFGEGBDCACACDFDHBBBBDCGAAFAHABABACACFDFBBHB,False +648,14.0,18.0,21.0,17.0,4.0,13.0,14.0,14.0,HDCCBGAGBGFGFHCCACHCGCBCBEDEBCBDBHFCFCFGAGACBGFDFBHBADAGHCHBHFCACDFDBABAEGCHHDBDCFBECGCGBDAFFGHDBDBDADADACFDADCHHGH,False +649,18.0,10.0,20.0,21.0,15.0,23.0,20.0,19.0,CDCFFDAABAFGFDBHFHGADADAHGHGBDFCHHHCDCHAHADCDGDGDGCEFGFCECFCFCGCAAAAEAEDBDBFFHHHFECECGGEGAABHECFHDEDGHGAEADFFHGDGDGEEBDCFGEHFCGCECEDDFFFFBFBCBHHAG,False +650,2.0,8.0,12.0,4.0,7.0,2.0,3.0,2.0,BECADGCCCCCBCBCBDGGFECECDBDBHECEFABHBCEE,True +651,23.0,17.0,14.0,13.0,18.0,7.0,9.0,12.0,HGFCACACFCDEEAGBGBADADABCGDAEADGDBACFHBEDAABHBHGHCAAEBECECACEDECEGFGAAHABAEAHDHABABADEBCFCFBEEEHEBFBAEHEHDCDBGBHD,False +652,9.0,5.0,7.0,3.0,3.0,4.0,7.0,7.0,FHAHAGGGGHGCGCEHEAFAFCHDECHBABCFGBHBACDCDAABA,False +653,17.0,14.0,10.0,12.0,16.0,15.0,12.0,13.0,FFDCCCGHBHEFBAEAHDFFFHBBBBGAFABABAEADAEFCBDEEHFDACHCHDAFCFEDGBCBCBEBEGGGCHHDDAGAEAEDEDEBEHDHAHEFGFGFGHGAAEAFG,False +654,18.0,23.0,28.0,27.0,18.0,13.0,30.0,25.0,CGCBCACGBGHACACADFEBGBCAEHBDBCHAEDGDFDCCAEHDGDFDFAFBGBGEDCFBFBFDAHGCCCBGBHEHAHGGGCECEHEAGCGDGDHBBDGCECHAHDFDGEGAGDGEADHCACBGBCHAHAGBGHHCHCHGEBEAEDECHBGBGDGFGEGHCHBDDDCDHDFDHCFEHDBDBF,False +655,15.0,11.0,8.0,7.0,7.0,6.0,7.0,13.0,EFAFACBEEDCAHAHGEAEFFHBHBFBFHGAAHGHGAGDCBHHHABDBEBAGAGDDDADHBCBEACHCACACHB,False +656,23.0,17.0,14.0,15.0,23.0,23.0,21.0,14.0,DBBBEEGCGFABAGAHAHFDEEHECBHBFBEAEADGDACGFGFCFDFGFGFGBEBEDEHHCFEHAHAFAHEBABEDEFGFGBGAAECFCHCEAGDGDCBCAFHFDFDFCFEEEEECFDBGGGAAADBGBHDAGEEBHDAAAHFGCGFAFC,False +657,22.0,13.0,20.0,11.0,19.0,20.0,13.0,19.0,AAAEEECFGGCCCDBDAFHFAFCCBAAHBBBEBFBAGCGEGHCAEACDCEADBDEAFCDGECEGGAGABAHAEBHHHHHCFCFEHCHFHGHCHCFAFDFDFDHBEGEFFFFAEAECEDEDHFGABFEGCHCHAHABF,False +658,13.0,8.0,9.0,8.0,6.0,14.0,16.0,11.0,DFDAACADGHGFECCGBFFFHEAAFACAGFHCGCFAFDFBBHHFGAGABABAGEFEFGDEBFBDBGACHCHCHGDGHGHGEGDGH,False +659,24.0,22.0,11.0,20.0,12.0,19.0,20.0,10.0,ECECBBAAAFHDHDHCBGFGFACABAGGHADBEAFFDFDFDEGCGCBBBFAGABBEDGGAGFDAGHGDDAEABBGBHDGEBFBHDFGCBCBEBFDFDADADBBFEHEFEFDFHFEGDCDCDCGBGAAAAAGAFAHBGA,False +660,9.0,8.0,11.0,8.0,16.0,14.0,26.0,11.0,FEGEHCHBGBGEGHGHGEGHDEBHAFACGDGFGACHHGAFCGGFEHDFDEEGBGBGFGFGCCECFAFDFDHBGDAAHAGEGDGEGFGAGEBCCCCBEEGEFEF,False +661,21.0,16.0,26.0,12.0,16.0,24.0,13.0,16.0,AHBFGAHHBCBABABCCGBEFACECGHGFDAHHCCECFFFDFAHACACBCBGBDFEFEHEDACAEDEDEGEGDGBBBGCGAHACACEFAFDFAFBDACAFFHFCFCAGEGBFDFBFEGCFCBCFHACADDCHFHFCECEHHHCE,False +662,19.0,21.0,19.0,34.0,20.0,23.0,22.0,19.0,AFAFBGBGBABGDDADCFCECGGEAEACHDHDEFCFDFDECHHGDEDEGGFEBBBBBEFEDDFAHCBEDDBACDCDAHAHGHDCFCFDFEFEDHCHDDADBGCABDHEBBFBDCDHDEDEABDHEBFBCEAGGHFHEAGFGFGCGDGFGDGAGAGABFBFDDHDCDHHGHECDCFAF,False +663,30.0,32.0,21.0,26.0,25.0,15.0,23.0,18.0,GBDHGHGHGBGFGABAEEDBCBCAHAEEDFDADEGCCCGHDBBBEDHGGFCBBHEAACDBGAGBGFEAAAAAABADGGBGCDCFCFDFCBHAHBBBHBHGDBDEHBHBHBEAABABDDEAEDFDEBEBECEGEFAFCFCADEGCGBABABFBCEADAEGEGDCDGBFHAEAEFCDDHEHAHFDCDEDCAC,False +664,14.0,12.0,16.0,18.0,20.0,25.0,19.0,23.0,GFFDFGFDEAHBCEEHCFEEEABFGFGHGAGAGCGCFDBDBDEDEABABDBHFCFHDGAGEHEHEGDCDCFAAGAEEHFGFEDCHFHGGEHDDGBADDGHFHEHEHECFCFCDCAEFFFGFGCBHHCCFCFBFHFHEDADHHHHABB,False +665,1.0,1.0,5.0,0.0,2.0,0.0,2.0,0.0,CCCBGGAECEC,True +666,13.0,18.0,8.0,9.0,12.0,13.0,18.0,15.0,FADABCFAFAFGFGFBCBGGGFGDCDCABDHDAEHEDGDGEFFHCGEHHFHBGAGAHEGEGABFCGBGEEBEHFHBHBHBHBFBHCABBHGEEDCDBABABHGGAE,False +667,12.0,9.0,6.0,10.0,3.0,13.0,8.0,9.0,CBCHGHFADHGAGBCFDFAADDFCFHDAAAAAFCFEAAFADCDGDGHFHFHGBFBFBEBHGHGBBDFDEB,False +668,25.0,23.0,24.0,17.0,11.0,21.0,16.0,12.0,GDAFFFFHBBGCACGCECBHAEDBBFFFBCBCACACGBABEBEDDBFAHBHDAGAGBGBGAGBGAGEDBAFCCDCGAGHCDADACAEDFHACBEAACFDDBDBHBDBDFFFCFCFCFCAAAEDHFAFHCHCACHCGAGFFCEEBEBGDH,False +669,3.0,6.0,1.0,5.0,4.0,4.0,3.0,1.0,EABGBEBGBFBGDFDFDADEDBFHEAC,True +670,5.0,9.0,11.0,15.0,8.0,21.0,12.0,11.0,DFDCHCFFDHHAHACGGFBDBDCDCDAHEFFFHBDBDBEECFGDGHGBFCDADABHBHGGEGCCFFFFFDFHEBGCEFDFGFEFEHDGFGFC,False +671,9.0,14.0,11.0,13.0,12.0,14.0,11.0,23.0,HDHCHCFCFCHCFCDADADEHFHBAEGFGHCEDHFCCDEHAHFEBBBADCHHHHDHBHEDDDADHDBGBGBCBFHEBEFGBGHGFFHAHGHBAFAGBEFEBEHEGFG,False +672,3.0,4.0,0.0,0.0,2.0,6.0,4.0,2.0,HFHFAAGEGFGFABBFGFBEB,True +673,17.0,21.0,20.0,5.0,12.0,13.0,17.0,15.0,BCBDBECHCAAADCGGGGFBABABEBCBCACAGHBHDHBFEEEEAABCBCBAAHBGGCGBGHGFGAGFFCHGHGHBABFBFHCHADDFCCCECECHHEAFBFBCHHBCEGGCFAEAEGFF,False +674,14.0,34.0,17.0,24.0,19.0,23.0,30.0,24.0,BBGEGHHHEHEFABDCHCFBDAGBBBBDBFCFCFAHHEHAFGHGEGEDBDBDHCFCHCEDEDEDGCGCDDDGDGAGAGEGBHHCHADFDBBBCDDACGHGEGEHBGBGHFEFGFBBDBHBFBDGGCGCDFGCBBBDADGHFCFADGEHFCFAFGBHFHBGEAEBBBAFGGDGFEFBBHEHEBABF,False +675,22.0,22.0,20.0,24.0,22.0,17.0,36.0,34.0,CHGHGHAHAHCECDBGCADHEEGECDGBFCCHCHFGFGBBHFHFHEGFGAGCGCGDGDCBFBFEFEHEDECCHBGBDADHFHEBDBGFGBAHGHGEACGGAEAHGBDCDGDHFHBHCECBDHGGGGHBBDFDFHAAAAAHADADHGHEHAGFGDGAEDGDEEBHACFGHBHBHCGGGCAHEEAEHEFDDDGDBBBAE,False +676,5.0,3.0,7.0,7.0,6.0,1.0,5.0,6.0,EHCHEBAGEGDGDCCCCABHEGBAEDEDCDFDADAHHCHG,False +677,14.0,12.0,18.0,20.0,14.0,12.0,11.0,15.0,CCADHGFACAHGHDDDDDGFGHBADGBEBCCDDDADADABBHCFCFHBHGAGEEEEEEEGEFHCDFAFCCADBDCDCDCBBBBCHCBDAGAEHDHAHAEEHEHFFCGCDFGECFFH,False +678,20.0,18.0,16.0,16.0,18.0,22.0,18.0,25.0,DFFHFHFGFBADAGHCBCAGBCBFGFACBEFEGABBBEGHHFHFDFHEEGEBECFCEBEGGADEDEAEACHCHABEHAHAFAHAHAFBFAECECHCHGHAHBHCHFHGDCHGHEBDBDGCADEDGGFBFGDBDCFFEHDFDFDGDHCHBGAAA,False +679,13.0,13.0,11.0,11.0,12.0,13.0,13.0,10.0,DADAHACGEBDGEGEDEAACHFGEGEGFGFCFAFEBCBFEFHCCFCHCHEHAFFDBBBHGCEBGBGAAHFHGHBFDEGAGBBBBDDADADEDACFC,False +680,21.0,9.0,11.0,23.0,10.0,11.0,13.0,22.0,BHEFDAEAEGGAGBCHCBAAHAFDFGGGGBHADEDACFCFAEABHBHBAAADFFACDDDHDHCBCFHDHCHGDAHAHDDDCDADEHFFAFDEHHDHECDADAGAGBHHGHEHEHCDGDGD,False +681,29.0,26.0,19.0,24.0,29.0,20.0,27.0,23.0,AAHAECBCBAADACAFFGCEADCBGHGFEFEAEDEDBDHDEBHDHAACAHAEBCBDFFHFBFBFBFGFBEAHBCAEAGAGBEEEEEEEEDCABFGFBDHFAFAGBGHGCGEGDADHDFGBCBHBHACEBDADEDEDGGGGGGGBHBHDHCFGBBEHCCAHHFABDCGGECFBAHGDGDCEAEHECEGHDFDEDGAHA,False +682,12.0,18.0,15.0,23.0,25.0,24.0,20.0,8.0,DADHGFBFDADAEECECBFDHDBCBABAHFFFFEFEFBFBFBEDFDEAFCCHEBBGECCCCFAGBBDBGCEEDHGGEGEAEAEFDDDGDAFEGCGCGCFEDDGDFHEDGGGGGEBEDFDEDHBEBDCCEFFFEFEBABFGAGHGD,False +683,10.0,19.0,7.0,19.0,5.0,6.0,8.0,11.0,CHCGBDFEGADBBBBBEGHAFAHBGFACAGAHDBDBDADHDGDBDCCCEDDHDADADCDBBBHBFBDBDFDADEHHHBHGGEFBB,True +684,10.0,3.0,3.0,5.0,2.0,4.0,6.0,12.0,DBCHHBHEDEGAGAHFGGHFAAAGAGADBCHAHAFDFDACHHHHH,True +685,10.0,19.0,16.0,24.0,9.0,16.0,18.0,17.0,DGDFEBDHDADCDBDHFHFHAGCHCHAGEEBGBGBAFDHCBADCDHAHEEABDDFDFABBCDDADCDFDFBBGBGHECCGCGDECGDBFGGEGECHCGFFBFBDGFHBHBHBCGCGCGBDDDFHFHFHA,False +686,11.0,7.0,14.0,17.0,14.0,20.0,12.0,14.0,HDHABCEFFBEHCGCACACBHBGEGEFFFBGCECDCDEHEDEGFGFDDDDGDGAHDHDADADFFFAHAEDHFBADEDBCCGHAEEECFFEFCFHFGCGAHDFGFHFCFH,False +687,19.0,24.0,19.0,21.0,13.0,20.0,17.0,22.0,GBGCDCDHFCAHAHBFFDCAGBFBABCFFBFACBGHGHBFFGHDDADHFHFHBGGHGAFDFCGAGEDEGEADDFCBABFBABAHEDEGFGFCBCFDDADACECEBEBCHCACFEGCHBBBDDDGHHDHAHAFABDHEHEHEGEDBABCBDBHCHC,False +688,11.0,6.0,12.0,7.0,7.0,10.0,7.0,5.0,CCBGGGGFABECFADHEACFCFGFGEDFCFAFBHBCBHBDCCHCAAAAAEDDDDAFCFCEGEAEH,False +689,1.0,5.0,2.0,2.0,0.0,1.0,2.0,2.0,DHDGFGCBBBBBCHA,True +690,15.0,19.0,20.0,21.0,26.0,23.0,15.0,18.0,GBGBGEFEGECEDHDHDHDHDCGAEACGCFBFECCACGCDEDFDHDFBBBEBDHGHDCBAAAFBHADFBFHFHFHFEDDADEDEFCBBAEEGEACCHCEGACEDECECFFFFHAHEGEBABEDFBHEDEAEADFDCHFHFCGEBHCFFFGBBECGBG,False +691,16.0,20.0,16.0,13.0,21.0,17.0,19.0,17.0,EEBEDECEAEBBBBEHFBFBFDCDCBCBCAFGHGCECGGDHAHCDCFCEHDHDBBFHFGEECBGBFHDHGHEBEBEAEFBAAAAEAGGGFEFCFBABDFGFDFHAEEGHHHGDFHFGCGCGDAAACADEGBBCAHGEGH,False +692,15.0,18.0,25.0,15.0,20.0,16.0,23.0,15.0,DCAGACABGEGHGBBCAEGHHDAAAFGCBCBCGGDGCGCHCDCDAFCFGHGCGCEEEHBGGECACADEDFDFGFDBBFBCDCFCDCEEHEHFDBDBGEGFFBFBFEECHGHBAGABABEHEHGCEHBFDCCGDHEHEGBFAFAECEC,False +693,18.0,15.0,17.0,18.0,19.0,18.0,17.0,13.0,DAEAFACADHDHCFCBBBDFDEGEGEFDGBEFEBGHGHEHGGAFAFAGAEDEBHDADAEAEDEAHGHAHCECEHFHBGFAEAFBCGFDFGCACADFCGCBCBDAHFBCDEBCFCFGECDBDBGBGECECFDDHFG,False +694,7.0,11.0,9.0,10.0,9.0,4.0,5.0,10.0,CDDDBBCGFGDHDHEHBHEHEBEBEAEAFHDEGEDHBAAFHCBFEGCBCBCBAAHACCCGBHDDD,False +695,9.0,7.0,7.0,14.0,15.0,8.0,16.0,16.0,DFDCDCDEAHDDDBHHFHFCDCHCFBAEEDGAEAGGFGHAEECHGHGHEEGDGFEFEDEGBGEDDBHBHGEGFAHAEAHAHGBGHGHGDECB,False +696,24.0,23.0,24.0,22.0,20.0,19.0,26.0,26.0,ADGDAEBHCGCHCEADABGBGBFEEGFAFAFBFGDGDHHACDCHFACHCGGHGHDHCBGDHBACHBHGHGAAEBFAHGGDGHGFGDCDCGCDCAEGGGEEEEEHDFDAAAHADAFADEBBBHEHECACBEEEBABFCFCFCECFCHBHBAGABHHFHBHFCDEBCDGDFDFDCBFBCBEAGDGH,False +697,19.0,24.0,22.0,23.0,29.0,24.0,25.0,34.0,FCFEAEAHCGEDABFEFDHCHCGCGCFHABDGEGFGFGBHBCAEEHGBCBCBCGHDHFHABGHDHCCCAADDFDHDCDHFBEHEHEGFBBHHHADEEEBEBFACHHHHGHGABBBBEDCBBBEDEDFFFFFFHCHDAEFEGDGHFBDGEHHGFBDADECEDEDGFBFEGCGHHCHCHGHEFEAAGAGEGDGCAHAEAEBD,False +698,13.0,19.0,14.0,18.0,18.0,16.0,11.0,16.0,BDBFFDFDFGGHAHBHBHBHFGAGAHDHBEBDBHBFBFHCBEGEGEDCCCCBGHECDCACDBFCEDBDFDFDHDFEFHFHEHEFEBABDEHBCDDHAAADEBAGAEACGEAEFBCEGEDFCCAGE,False +699,20.0,17.0,18.0,13.0,20.0,22.0,16.0,23.0,ADHHHHFDFBFAGADBEFFFEFEGCFBDHCAEABAEAEBHFECCFDFHHHHHFHCHCHEHEAEBGHACABFCFGAGDFDFCBHGCFCBCHDEDHGHAFDFAGECECEFAGCDEGEHEAABCBGBGBGBABGEAHGEAFHFGCECADBDB,False +700,7.0,10.0,13.0,7.0,8.0,14.0,8.0,3.0,FAAEFBFCFBFBEDGHCCCCCEDEDFHECDBDGFGFADGBEFCFCGAAAHEDECACFBFBGGGFCFCBBB,False +701,16.0,27.0,21.0,29.0,23.0,22.0,14.0,18.0,ABAEADACBDBFAFDCGBDEDBBFBFADHHAABHDGABACDBDEAFCHCECHDDACAFDFDFEAEDHDFBFBFCEEBECDCDHABFBGEGFHFHGBDEDEDEDCDHDHFAGDGHGHGHBCBCBFHCEBEHCCDCBFBFBECFDGGGFCECEDHBGBCFEEDGBFBEHEDE,False +702,22.0,31.0,14.0,20.0,15.0,20.0,18.0,12.0,GHADBDAFCHAEBDBDBDFDEAAABADEDCAABBEGEGFGEGFDFBFBAEGBBCBCBEGDCDAHCHBADADGFBFBHBGBDCFGDGHCDCFCBEAGFGFHFEBECAFBFBHBHBFBEGEGEBEDAHABADABBGBCAAGDFBAGHCCFDFHF,False +703,21.0,26.0,13.0,16.0,14.0,14.0,14.0,17.0,CHABCBFGFAABAGAHAHAHACBDFHAHEHGCACDBEHDGBHCECEHFAACABHBABABECGBGAGEFCGDEFHBBFAFHFHAHEBEFEGBGBEBEDDDDDDDAHHCBCDDGEADABGBDBFGFBFBFBGEDCBB,False +704,1.0,0.0,1.0,1.0,3.0,1.0,3.0,0.0,DEECEGFGAG,True +705,7.0,6.0,9.0,6.0,4.0,3.0,8.0,5.0,AGABCBCEHFACGFHHCHEACADDDDGBGBGBCEFHBDEDACGCGCGA,False +706,6.0,5.0,9.0,7.0,4.0,10.0,8.0,4.0,BGHGEDCHCHCGCFFGDGDGCBCBAADFFAFEFGAGADFHBAFCBCEDEFCFD,False +707,10.0,10.0,4.0,9.0,12.0,8.0,9.0,7.0,EECFAEAHAHAEAEBEHFDFDAGCDHBHGGEGEGFDFDEBADDCHFDDBFGEGBGBEBEAHAGBFBABC,False +708,11.0,14.0,22.0,17.0,26.0,26.0,22.0,25.0,ADBFFHCHCHCDGFCFBHBHBAGACHDFEFHCBGECDDGEHEHDHEGEGEGECBHAECDHDCDEEFHFDFDABHGDEHEGDHDGFCCCHCHDHDHBAEEGEHEHGGGBBFEFEDEFHFCFAEHECGCAFFFCFBBCAFBCHEEGEGFFECGCGFGFGFAFAGB,False +709,20.0,25.0,16.0,17.0,13.0,14.0,18.0,22.0,CDEHBHBHAHBHBGDGEGBACAHAHGBGBGBAAAGFDEEBGBABABFGACACHGHDFDADHEFDHHECFDACABGHFHDDDAEAEDGDCDCFCBCFHBCBEBEBEBFCGCHFEGGDDBBBCEHGDACABGHGAFHHHBFAFCFHB,False +710,30.0,23.0,16.0,22.0,21.0,35.0,15.0,23.0,FAFAFAFEFEHAHAEBEFDFDBDHFCEAHHHHBEFDADHEHBCCCADEHFHFHFCGGDECGCBDBGAFAFBCDAHADBECEFHCBCBAAAFAGBFADDFDFHBGAAEABFDEDFHAGAHAGAGEGHFEFCABAFCBEBEBHFDDDFDADEEEFBFDACEGFBDBHBHBFGFBFCFGGHAHAFGFC,False +711,6.0,6.0,12.0,7.0,12.0,9.0,12.0,10.0,HGEDHDGCGCGBHBHGCFAGABCBGGEBCHCHFGDEEEHEHAHFHCGDFEFAFAFDECECDCFABCGEGFCEDE,False +712,23.0,31.0,32.0,27.0,25.0,14.0,31.0,14.0,CGABCFCEHDFDHEHBDBDECCFBDGHGAGBGCHCBAEHEHDFDBDCEFGCGCFBAGGGEFEABFBGEAAAAHAGACACECACBGDGDBHBCFGHGBCAAAFBDDDDDDFGFCECBBEEGDADCBEAEAFDGEGCCBCBCBDGCECGCGCGCECECBFBDBABDBDHDCEHEBECGAABDBGGGDEEGEBBAHGGDH,False +713,4.0,5.0,5.0,9.0,4.0,5.0,6.0,6.0,BEFEACAHDHDHGHBDCHCDEDFDGDBEFGDGDFAFBBGACHCG,False +714,18.0,19.0,22.0,14.0,25.0,27.0,18.0,19.0,GEHFCECFCAEFBFAHBCCEBFFEFECDADEDEAEFEBECECGHGAAADAGHBFGFAFHDEABBDGDEHEFEFDBCHEGCCEFBFEHHHHGHGCAFAFHFHFGEHEHCGDFEAEAGFFBADAFFCFABGBABFBCBGBGCDCDHFHCECECDHDBGBCBCGG,False +715,17.0,8.0,11.0,12.0,13.0,12.0,12.0,14.0,BAGDHBHDHABAEGHFDADFECDCGCGADHDHDHABCBHGAAFBFBEHEAFCFAGHEBCDFDFDCHCHCADAEHEGEAEGCGCFEHAGGFAFEFEAEAG,False +716,16.0,17.0,24.0,24.0,21.0,17.0,16.0,24.0,FCBCBHBCBCECDCDAFFHHHCHDBEFABAEDEDEDECFDGGGAEFEFEHCADAFACEEECFCGAEDEDGHGDGAGFBHDHFHCCGEGBDHGEBHHHEHACAEGFDFDHCECBADECHHHBBBFBFBDADCCFCDCBCDEDHHCGDDAAAHBHGHGDGF,False +717,30.0,23.0,30.0,24.0,12.0,21.0,21.0,16.0,ECEDACAHEHCACECDCGCBHAGDFACBCBAFGFGBACCCCACFGEGFHHAHABGBEFFBFDFCGABCDCBBBBBAADADGDFDFHFDCDCHFBFAAGAGAGAGFCCCHABGDGDBDCDEBHDCDCDBGFFHHGBEAAHAHDFDEDAHAGDCDBHAFGGGBABDFCACACBCFEEAE,False +718,8.0,9.0,11.0,13.0,10.0,18.0,7.0,15.0,BHBGDHDHDEAEFFAGAGABHFFFADHDHDGAFCDCAHBDECFAHDHCCBGHFCECEHEFDBDCDGEGDBHBECFCFCFHBEFFFFFHFHE,False +719,12.0,23.0,32.0,23.0,25.0,25.0,24.0,32.0,ACHDECHBHFHGHGHDADAGHCCEBEBCCGHFFGFCBEGCCDDDBGFDHDHDHGFGBCFCGCDCDCDCFGEDBDBEGGCFEFEHEBEHECBFDCDGBGEGBGEGCFEEECGFGADCFEAEADBBCECEHEBEDFHFCFCAABGHHHHHFAFABCCHCFCAHEHFBFBFHCGFBDGDEBHBHCECGDBAFHHHHHDH,False +720,9.0,6.0,1.0,2.0,6.0,3.0,3.0,2.0,AAABABDBGEHAGABCBGFHEAEDEAEFEFBA,True +721,4.0,4.0,5.0,4.0,1.0,4.0,3.0,0.0,BGBCACGCDDFDFABACECBFAFDG,True +722,16.0,8.0,13.0,19.0,18.0,17.0,9.0,17.0,DFEFCHCGADHDEDAHEDEBFHFEFEAEDEDHAHADCBAFACAHEHDCGCGCDCDHDFECEBEDEDEFGGABFBFGCACFDFAFBDGFHCADHEHEGDAEAHHHBHFHFADCFEBGA,False +723,20.0,21.0,15.0,7.0,15.0,20.0,22.0,15.0,AFCDCFCFGFGAGBCACBHAAFGFBBEEAEGHDEDBHBHEHBCGEGFACEGHGHGCGEGECAFFGEGEGEGBBFAFDCBCFCFADADBHEAEHGBGHGBAFAHCBADFBHBCBFAFHBABABAFABHFGFGEHCG,False +724,22.0,23.0,14.0,13.0,20.0,26.0,11.0,21.0,DEBABADADEGBGBEBHBCCAAEAFFDAAAAFEFAFGFCFCBHBCFFFCFBFDFEHHDHCHCFDEDHBHBGAACEFAHHFABAEEEEGBCHCECACGDHAFDFHFHFEFHAGGGFCHBBDBHBEBFBFHHEHBBBABEEFGFEDGDAHAE,False +725,21.0,25.0,25.0,29.0,21.0,32.0,25.0,20.0,FGGGCGEGDFAHHHCCCGAEABFBEBDBDHDCDEDAFGDGAEFCFCEAEADABCBGGGGGCDCDCFFFEHACBCBCGCFCFDBDFCFAHBDDFDFBEHEADCDFHEHFFEGGDGFHEGEBBBDHEAEAGAGAHBHAAGAHAHDDCBCFFFHFEDGDHDBFBEAHBFBEDFCHGFGDCFEGCHCFBFDEDFDABBFBCB,False +726,16.0,20.0,16.0,17.0,10.0,18.0,13.0,17.0,BBBBGCACACBFBABFBCDHGBCHCBADABFCFCFGAHEGBGEEEFDGDFAGAGCBCEFHFHGHFHAHFDFCHAHAGEBDBDGDCDCHFHBDDADCBFADEEEHHDGFGFHADEDHFHCBCBABADF,False +727,10.0,29.0,22.0,26.0,22.0,17.0,21.0,19.0,BCBCBCBDAFHFCECDCDCBHECFCGAGDGBHFDGDGBGBEDEDEDBCBAFAGHBHDHAADBDCGFGHDBDEGEFBBBCBEBEHECDHEGDADCDHDBBGCEHFGCAEAEBEBFBHADCECFCFEDGHGHBHFHGHBCFGBCEFDHGBGFGEBEHEFFDDBDECGD,False +728,11.0,13.0,13.0,11.0,13.0,20.0,15.0,18.0,EFFFEBCDCHCAAAADFHFHGAFDFHFCFBEBGCGAFBCACAHAHEDBBGEDEDCDGBGFGFGCHCFFDHEBBCGGGGGDFHAHDHBFFCHHDHEHEFBHBHECAGEGEFEFBH,False +729,26.0,25.0,13.0,24.0,26.0,16.0,21.0,19.0,DBDFABGGFGHEHAAAAABFBFBGBDBABAGEGCGFEEGEBEDHAEDCHABCDEFAFAGDHHAHADAFAFGBGAGHBDGCHHHBFFEAEDBDBEHDBBEDDHDHDCBCBEHCACDHFCGAGEGDDBEBEBEAGAEADABAFFFFEHGCGCEEEEBEGDHDGECEABHDCD,False +730,16.0,17.0,13.0,13.0,6.0,15.0,8.0,16.0,CCHDADACCDBABEBHDFBEAGBGFCECHBAAEAEDEGCHCHAFBHGHDBDADAFBDBGBHCHCAGAGHHCDCFFDFBFBADFBFBFHAAADBFCFGFBFHHHH,False +731,16.0,23.0,24.0,23.0,24.0,17.0,32.0,25.0,FFFFFFFDDEDGGHGHGHGFDHBCACGEGEBEBECFFBFBDECCDEHCFGEACHDHDHCFDHEGABHEGBGEAEHBAGCGHGHEEEDEDHFCGDGBAHAGAGDGBACCEAGAGAGAHFBCHCGCDCHCHBDBGBEBGCDFDBCBHEHEHGCGHBCBCGCAADDDGHGBDEDEGBBDFEAEGBCH,False +732,2.0,3.0,2.0,0.0,1.0,3.0,2.0,1.0,FCFGFHCBGBAEAB,True +733,6.0,2.0,3.0,2.0,1.0,4.0,1.0,4.0,BFFCHCHCHAAFADBGFDAHAEA,True +734,5.0,4.0,6.0,8.0,4.0,8.0,3.0,7.0,DGHGDEDEFAFBFBDDEAADFDHCHFAFBDGHHHHCCCCFCFBEA,False +735,11.0,7.0,8.0,6.0,4.0,4.0,8.0,5.0,CHCACAGAEDFDCBHDHFHBCDDHAFGGGCACAGAGBBBGBEBDFAAGAECEA,False +736,20.0,16.0,16.0,26.0,10.0,23.0,15.0,12.0,BDBHCCEBDBACHCDFGFCADHDFDHAECDAGAGCFEFCFEDDDDDDDCFHHADFDABEGGGAGAGADABAFCFAFDBEBEGACADDDHAHBECHDGBGBDDEGEGDBFCFHBADGHGHFFFBFAFAFCFCFBFCFBA,False +737,23.0,11.0,24.0,14.0,10.0,9.0,22.0,11.0,FHADCDEAAAABDBHAFADADFCGGGHGAEAHCGDDCDCDHAHCGGGGCACFCBCBCGCHAAFAHEBADAECGCGCGDGECEDGBFCDBAGACFHAEGCGEGBGCECHGGFHFABABABCCDCE,True +738,26.0,23.0,28.0,29.0,22.0,16.0,18.0,26.0,EHDFFHFHEAFFBBEHDBBBDBDCGEGEGCBCDGHAHDEDEDFAFGCCCACBDAGAEFHFHADAFHCDCDBDHAAAAAHCHCHFHFEFHCHFBAEDHCBCBCBEBDADGDAHAGACACBHEDDDEHCHBDECCGBGBHDCDHDBGCCBGDGCHHGFBAEGEAFACACBCEEEEHEGCGAADAEBGDDD,False +739,8.0,2.0,10.0,6.0,9.0,6.0,10.0,6.0,CGBDCDCHHEEAEACAEEGFHFDDDDFGFEAHCCCCCBFGAGAGEFAGAGHCEGEGH,False +740,11.0,8.0,17.0,13.0,9.0,9.0,18.0,8.0,BGAGBECGDGHFHBHBGDGDGCCCCCCFCFDFAFHBDADGDGBBCACAFEDGDHCECHAEEEBDCGGAGFGCGDAAEDEACHEHCCFGAGDGF,False +741,4.0,2.0,8.0,8.0,5.0,1.0,3.0,4.0,CECEAEHCCADDHDHGGEBHBECFCDDDDCDAGAC,True +742,2.0,9.0,1.0,2.0,5.0,5.0,1.0,4.0,CBHEDBAFFDBABEBEBHFHBHBFBGEFE,True +743,18.0,19.0,21.0,21.0,22.0,11.0,26.0,21.0,EAACDDDHDGEGBHHHHEBEBABHEHBFGCGDGEGCDCDGGCGHFFDFBBGACADADHHADCDGDGBCCCBEDECAGHGHBFCFEDEDEGGCBEFEBEBEHADBHBGGGADADFGFDAEAGBBHGDBHGHCHCACACAEFEGHCECEAFHCHBGEGECA,False +744,31.0,23.0,20.0,24.0,21.0,22.0,28.0,21.0,DADEBEBEDADABCBFGGGGGHGHAFFGBGBGCGDGFGHBCCFDEHEADABAGGBGFCFCAGAHHEDBHBHFFEHAGAGBCDFAEBHDDDDEHHACFBHDGDGACFFBDBAAADAHAHCHCEGAHAGEEEEEBHFFGADABABEBEBCDCBHFHFAADFCGCGBAADDDFCCCHFEFECEAGACAGDGFE,False +745,5.0,11.0,15.0,7.0,10.0,9.0,7.0,16.0,EFHFBCACFCEHBCBABABCECFHHHHFEFHCHCFCBHHGGEGEDDDHAFGEGCBDDDHEEAFBBCHCHEHGHBCBCDCG,False +746,1.0,0.0,6.0,5.0,2.0,2.0,2.0,0.0,GDCDCACECEDFDGCCFD,True +747,14.0,8.0,8.0,12.0,14.0,15.0,12.0,12.0,HCHDFEEGCBCDCAEEEBEFEFCABABFBFDEGFAHEHAHCHGGFCFDEDAHCHDFDGDGABHEAAFAFHFEEGAGDDFBHBHGDGEGAGAFAFD,False +748,23.0,22.0,15.0,27.0,27.0,24.0,31.0,19.0,CFEFAHGBGDEAEBEAEBHBDDGBFAHCGFHFHGEGFAFADBEFHBEBCCFCGEGADBBGGCGBGHHBEGEGABBEEEAHAGEGFGAGFCCBFAGBGFGFGFADDBDBGBFEFGFAAAABHCDDDDDDFDFHFHBGDEAEDDDEDEGEDEDECHDHCFAGAHAEAGADFGHEHDHCCGEGEDBDFCHC,False +749,18.0,23.0,17.0,19.0,17.0,23.0,21.0,21.0,EAADEDBDBFBEECFCDEGFDFHBDAFFBCCCGCHCHAFAFAGGHGECECEBEGAGDGDHEFEHCBAADAFBFBHBABGBGCFCDHFBDEDECFGFBCHHDBBCHDGDFFBFBGDGBHHAHABADADEEGHGHBHFFFFEFGCGCDEHHGHGAAAGBBH,False +750,26.0,15.0,24.0,31.0,22.0,18.0,27.0,36.0,HFCEEEDBCEHFDCDCDGDAHEDGBCCDCGHDEECFHFAFADHFCGEEAEHEHECGABAHFBFBFDACBDBDCDHDHGFBFACAHAHABAHHHCDGHGHGHAABFHFGGHADDDDDADCDEDGDEAGGGGAGBGACCHBHBFDDEEHEDDHCHCHCHGFGAHHHBHFGCGHEEDEDFBAGHGHCECGCAHAGFEADAGA,False +751,2.0,2.0,6.0,6.0,5.0,4.0,2.0,6.0,DCHAHGHCHCEBEGDFCHCDCFEFEDEFHADBD,True +752,12.0,16.0,4.0,9.0,13.0,13.0,11.0,4.0,EBEBDBDBFAHAHADAGBCBFHEEAFAEEBEFGFEFAAAGGGBAFCFCFDGEBBBBBBGAFEEDDDGAGFGCEFEGBDDFHB,False +753,20.0,22.0,13.0,25.0,23.0,25.0,27.0,11.0,DBDAFFDEDEDEFEFDBCFFHDDEEEBEFDFEFEGBGCHCEBEHEHAABAGGGDEAFDFBGGGDFAFAFACHEEBHACBFECCGGGGGGFDFAFCGEGEFHBDBACAHAEFDBDFGABFBEGCGCDHDHDGDBDBDGCFBGCAHGDGBBFAFABEGEGABADADGB,False +754,13.0,24.0,24.0,21.0,25.0,16.0,20.0,11.0,BHBDGCGFGFGFGHGHBFGCEEFEFBAHEHEHEBCDEDEDBBCBCEFECGCDBACAGDGDBBHCCGDAAEAHCEFECABABDGDGCBEDHGFEDEDBGGCACDDBEBCBDFGGGEEHECECEFDFDBBBDCHAFDCBCBCGCFFACAEAEDBFE,False +755,21.0,23.0,12.0,20.0,22.0,23.0,13.0,24.0,FBFBCBFBFECEBHBHDHBBBFBACGBGBDAGFDACHHGCGHFDBHEEEFEAEBEBFGAGAGEDDFDFEFBCAFDFEAEAEDFDBDHECDCFCEAHAFEEHAHGHGHCBDAEGHBDDDBDEHGBAHAFCHGBFHFHEHEADHFHFHFDEBCAAAAHAD,False +756,9.0,16.0,8.0,17.0,8.0,7.0,7.0,4.0,EFEFGFGCCBABHBDDDDGDABBGBFBFEACDBDEDHCGEGBCBCBFDDDEAFABADAHEBADHDCCEDGDBBBAD,False +757,15.0,20.0,18.0,27.0,18.0,16.0,16.0,19.0,GHFBGBCEEAHDBDAHAHEBFFDDDDBFBEEAGBDHDBEGHAHADDEDCFCFBHAHBHDDGDGDECECGHGFGDADEFCFCFDADBGEEBCDEDGABABHBHBHCDCECECEGACCEABFBFBCCHABGHFHFACDDDDDGHECGFGFH,False +758,24.0,10.0,20.0,10.0,13.0,18.0,25.0,18.0,HEHAHAFAHCGCGCHEBGCGHGHGFGCGEABGHGFGHCHEAACABAHACFEAGCECBGGGGGACDFHFAFDFDFDFBEEAEAECFCAADAGFCHHECFHGAGHGEAHFGCCDBDBGACAGADABBDBDCFAFHGEFCF,False +759,5.0,2.0,3.0,3.0,1.0,2.0,7.0,3.0,CFAGGHGHGHBDGDGACEDACAGABF,True +760,23.0,15.0,19.0,10.0,31.0,25.0,21.0,16.0,FGFGHGDGBHACAFAFEFEGEBFGFGFECEDBFEFEHHCFAEACFBBBAFEDCGCEAECFCBBHEGEDEAEFBFGFGADCCCBHAAEEBABAHAHACECFHFEDEABFEDEAEBECACECGFGFEAGAFEFACHGDGAEAEGHHHHGDCBEDEHFHGGCG,False +761,4.0,5.0,6.0,6.0,5.0,5.0,6.0,6.0,EFBFBFGDHCHFEFGGBDAGACHCHDHBAAECCBCDEDEDGHG,False +762,5.0,7.0,14.0,5.0,9.0,9.0,6.0,9.0,EGEFHBHFGFHCEDEBEFACAEAECHCHCHCHBGCFDFCCACBCDHDFGABHBCECDGGEFCFB,False +763,7.0,10.0,9.0,14.0,6.0,13.0,15.0,4.0,FHBHAHAFAEDCDEAEHFDDGFBFBFDGGFGBGBCBFDGDBCGEGECAGAGDGDFDCDCDFGCGEBDGFBACFBFDCG,False +764,18.0,17.0,21.0,10.0,17.0,19.0,30.0,14.0,GFCBGAFBBEFFCGHGEADAHFHEAEAHAHFGGGEGECCFAGAGFFCACBFAFAFGGGAEHGHFHBHCACHFAFDEDHGEGDFBCGCAHGCEBEHCBGBDDCAGBDAGECECACBCBCGGGBBBBBECFCFEFHGDGDGDGEGEGC,False +765,16.0,9.0,24.0,14.0,21.0,12.0,17.0,12.0,FCCCCEGDGDFBEGCBCDDDDCHFGACDHECCCEEAHGHGCCCFEAAADAHGEBEFDDDCDCEAGCGDHEAEAGADAGEFCFCFGFGEAFHEECECEGHGBFCECEBFBCAEBGBGHAHAHAHBE,False +766,2.0,5.0,3.0,5.0,5.0,3.0,5.0,14.0,GCCBCDHEEEFHHEBEHGHBHDHDHAHFGAHDGDGHHHHBFB,True +767,25.0,19.0,25.0,19.0,30.0,21.0,34.0,24.0,AABAGCCCGCDFDAEECGCHBHGHGHDAGCGDFDCEGEBAGFEEEHHAGAGAGFECEHGCECEHFHABEEEBEFEBEFEBCGGGDGABEDEDADGFGFCHHHHDDFBFBAEAEAHGFCFAAAAABAFHECGCDCGFADDBHBGCEHFBBGDHFAFHBHCHFHAGGGGGGAGCGEDEBEDECHFHGBDEDBFGCCCCE,False +768,25.0,18.0,18.0,14.0,17.0,14.0,28.0,21.0,DBBECABABAFFCHGBFEAEHGGEEEHGHGAGADAHGCCFDFDGAFCECECDBBBFBDHHGHEHBHAHGCGFGHHCCFAEAECGAGFHHCEGGGCDCEHEHEDGDHDAGABACCBCBGFFBBHBABADAGGGGHGAGAGAECFBAGAFADAEHDD,False +769,1.0,3.0,1.0,7.0,6.0,6.0,6.0,3.0,EFGFHFCEBGHFBDEDEHEAFDDGDGDGDGBEF,True +770,10.0,20.0,19.0,21.0,15.0,21.0,16.0,16.0,CDHDGGGCGEGECDCDCDABFBDBFBFDFHFHDDBEAEHBGBGCDBGBCHHDGFGCHDHCGCAAHABAFHHBDEFEFCFDFCFCFAHEFBFBGHGDDDCBEGGFEBEAEBDBHCHAEFCDCBFEFEBHCGCBFDFDEA,False +771,4.0,6.0,5.0,4.0,2.0,2.0,2.0,5.0,DBACDGDBBHBHCFDECECACAHAHGBFBH,False +772,20.0,21.0,27.0,26.0,23.0,24.0,13.0,18.0,HHGDAACADHDEDCABDHDFCFDBCFCABDCCCCFFFDFBCBHBGEGHGADACFDGAADDDDDECEHEHDFEBEFCFHFAFCFCFAFCHHHCEBEBEGECECFCHEFDCGBAFADAEAEDEDEFEHEGDAAEBCAEABBFBFBEADGCHDBGBDCDFGGBCBCBEHGHCHBF,False +773,23.0,11.0,12.0,12.0,15.0,10.0,15.0,14.0,HHBEBEDEBGBDFCECGCGEGCHDHGHGBCHAGAGAFAFAHAEEEAEAGBGEGCGAACABBHDABFDFAHADGHFBCDDHAAEAEAEAEACDFDEAAAHFDCCGCHHGDBFF,False +774,17.0,24.0,28.0,15.0,15.0,16.0,18.0,18.0,EFEFEBGCDADCEHBHBHBFBECECBFBFCGCEDEDCCFCGCGFGFACCDFHAHGHBHCHEHECCCGGFCHCADBBBGHHEGCCCGCBHGEGBBBAADCDCDCDADADABFHFAGBDBAHGBBABFEFGBEAHBGCCHFHGDABACAFDEA,False +775,3.0,0.0,2.0,1.0,0.0,2.0,2.0,3.0,AGHGHFDFCHCAA,True +776,17.0,9.0,11.0,6.0,12.0,12.0,17.0,14.0,GCGDABAFGFGCCECFABAEAEBGADHHEHAAAEDEAEABDFCGBADAEHGHFFFGAGFCFDBHBFGHHCGAGHGEGHBHCECEAEAGFCFCBHGHGH,False +777,4.0,6.0,1.0,5.0,7.0,2.0,6.0,4.0,HEFEAEAEDBBGDCDHDFEBAAHEHEDGBBBGGGG,True +778,6.0,7.0,4.0,4.0,5.0,13.0,4.0,5.0,HEHEAFGFAFAFBGBAFFFDEDECBCFGDBEHFAFBFDFHFHGBACCB,False +779,9.0,7.0,5.0,6.0,9.0,8.0,7.0,9.0,DGBEBEDHAFAFHFHFCFCEDEGEDEDGHAFBHBAGAFBCBHFAGADAECCBGEGHHEHA,False +780,19.0,21.0,16.0,16.0,23.0,19.0,26.0,22.0,FFCAGEGEGAHBBEBEGCDFEFCFGHHDHDHDBEFFAGEGAGAGAHEHFAEDBACCCEDGBEACFCFEDEABABABFHFBGBGAGEHHACBCGCHCHGHEABACDBDHEGFGEADHFBDCDCEBBAGHGHEHEHGHDHDGDGFHABECEBDGGFGBGBEFFF,False +781,15.0,24.0,23.0,18.0,23.0,14.0,17.0,21.0,FEAGCCBABABAFAHCDGHFCAEGBGBGHHBBCBFBABAEDEDADHFECGDGAHEBEBECCGCHCHEBCFEDDDCGCGDGDHEFGGCHCBEFECAHDEDFDEHEGEFBBHGGCECECFBDBDBAHAHEHDHECFBFDCECABABHBGBCHFHDHE,False +782,14.0,24.0,23.0,18.0,18.0,17.0,19.0,17.0,GAECGCBBAGAGAGFEEDDFBEEEBBGGEECCCCBEGEGFGDGCHCHCHEADBDBHBHFGADBFGDHHGAGADDDDDCBCDHFBFHDAGFHFHFHCBCFEHHHBFCFHFCGCBCAGFEBDFCECHCACBDBCEAGDBDBEBEBEBABAFC,False +783,17.0,21.0,14.0,26.0,20.0,11.0,14.0,15.0,CHAHEHDHGCCADABAEDBDBFAEABGDDCGADADBBAFCEGDBEBDHGEGFHEHEHEFCFDGHADADBDBDCDCGBABDECEDEDFDCDCDADEDBDHGBGBECDHEHFFBAEAEBEBGHGEBCGGBEFHBHCFAFA,False +784,9.0,13.0,21.0,19.0,11.0,19.0,13.0,15.0,ADHDFGEBBCCDCDCFHAGDBCBCECEAGAHCDEAHBHEFEAHHGDCHCHDHDHFBEADFCGCHDHAFBGBGBEFDFGFECACFEFGFDCDEBGBGCFBFCDGDGCFDFHFHFCFCDCDB,False +785,3.0,4.0,10.0,4.0,5.0,8.0,5.0,7.0,FCFCGCGEAAGFCECECHFFDHCACGCGEBHFEFHBHDFDBDBHHC,False +786,13.0,15.0,20.0,21.0,12.0,14.0,14.0,18.0,BFDGDGDADECHCHCEDGDBDGHCHDGCABEEFEFGGDDBDHDHDGCCEBDFDFBHBHBHFHFAECEBAAAFAEAHBHGHDFEFBHBABECCCCCDEGHGBFFGHCDCBGDCCCFHDCACAFGHADA,False +787,12.0,21.0,22.0,19.0,22.0,24.0,29.0,14.0,CGCGEECEGGBEAGCFFFCDCEEACFBFBGBGDGDHDHCBCGADEHGHBFGFGFDFDBGEGEBFCFCFCFABDBCAFFGDGBFHCHEECDFDFCBEBFHGCGEGAGAFDFCEGEGEAAHHHBGCGCGAGDGDBDFGEDBDFDBCHADEEGEHEHABBFEHBCB,False +788,17.0,13.0,19.0,20.0,16.0,16.0,19.0,15.0,BDCEGHGDAFFHFHDADAHEEEECFCGDHBHGGGAGAEFGBCADGCCCCCCGCDCBEFEFDFECADABAFEBGBGAADGEGHADABHFHFCEDHDGGCDCDFDADGHCFBBCBCEHBHFHDEDEDEGHGAAAFBF,False +789,28.0,17.0,13.0,32.0,28.0,13.0,27.0,17.0,AEADADBGBAFAEADGBAAGDDEGEBEFCFCFHFHAEGEHDHAADEDHDCFCBAEGEGDGCGAGBGBGBFDDDEDGBGBGBDDGGADCDBGAEAGDBCADEDHBABAECHCECAFEHAFACDCDGEHEHFBEHDDDDFEAABDHGHGHDAGECEGEGDHEAEGEGEAFHDHDFAE,False +790,20.0,14.0,14.0,14.0,17.0,15.0,16.0,18.0,FCFDDDHCHCEGHADCBGFEFCFEEEEBEADABHBDEFCABABAGAGEHHBHBDAECGDEAAAFAEADBHCGGBGBGBEFEFEFABAGFHHGACDBDHHGFDACEHDHGHFCFDHCHCHCEFAGAGAG,False +791,18.0,17.0,18.0,19.0,20.0,20.0,6.0,18.0,FHFHFDEAADAFBBACGHDCDFAGGFEFADEDBFBFECEAFAFACCCEFHBHFHBBACHFDGDCDHDHGBAHCDCBHBEEEEAECBABCBCEDHDFDEDEDEAEADACAHFHFHEDCCABEHEBEHCFBFGFBDHC,False +792,14.0,17.0,13.0,12.0,11.0,16.0,16.0,11.0,DDBDBDAFBDBFAFAGBDEGCCECHCHCGFABGBCFEFECHFBABAEECBDHDGDGHGHGFCFHEAEGDHBCBEFHBGAGACAHAFGFGFDEABFBABGFGFGBHCAEDC,False +793,9.0,19.0,17.0,11.0,13.0,16.0,16.0,13.0,DCGHBFFCGEEBEGGAGFDEEBFGHCHCDFDBCBCFCFCGCGBBBCBCBFHFGCAEABHBABGBDBDFDHAHFGFHBBBGHGHECFDECEGHGHDAAGDBCECDAEAEFEFCFH,False +794,18.0,14.0,23.0,18.0,18.0,15.0,28.0,20.0,GBGBGFGAEFECEBGBECECFGDEDGFCFGGHCHCFGDAHHCHCFCFCGCGCEAHAEABACDBDBAGGCGHAHBDFDHEHEGAGEGEHHDCDGFHBHGHFADECACAEABFCAHGHGBDCDFDFBAGACDGGCDBGGADHDBFHEHEAEGDCEC,False +795,2.0,6.0,5.0,6.0,3.0,1.0,4.0,1.0,GDGECBCHDEDECBBFBCBABDGDGACD,True +796,20.0,15.0,22.0,19.0,22.0,17.0,35.0,28.0,EHGHCDCDAEBCBFBACHCGEFEFEFDFHGHDCGAHDCGCDCACBGEEHEHGGGEHEFEGGAAAAHAFFECCAGHGHGHBACACDCFEAGGGGGGGCGAFCBEHHGDGHGADAHGHBDGAGBCDCABAHDDEEFGGEHHHBBBDBDHDHDHFHEHBCDCGFGECEFFGFGEGHFBEDA,False +797,22.0,14.0,14.0,13.0,13.0,14.0,15.0,9.0,HCHGGBDEFAFAGAHDCGCGCHCGFAADEDEABAGABFEFEFEBDFGABHFDAABCHCFCADBBAGDGDGDCDFEFGBDBDFFGCBCBEBGAAAAAAHEHEBEGCAAAFHECEC,False +798,15.0,14.0,14.0,26.0,14.0,22.0,16.0,23.0,DCGAADDDHDHFFDBGGFGEGBBDHAHFFFFAFCFBDDFEAEDHDHGHGDCHCFAGBDFCFEFGAGHECFCEDAHAGEBFBABDEDADCDHAFCFAFHBDFAFADEGEHEHBHGFGCGHGCDCDBBHHHHBCBCHDEDEDEDHH,False +799,27.0,20.0,19.0,24.0,17.0,17.0,26.0,21.0,GFGDGDCDFGBGBEBGBHHFDADAHEHEBBBHFFGGCADACAGHBHAAFACACHBECEFAHADGDAEHECFABCGCAHBHAHDGEEHFDFHFDFCAHDBDBFEGDGDGHBDBGAGEGBGCCECEBEHAGABADADADECGCGCAFHGHBFACACFDEDEBGACAGHGFDDD,False +800,14.0,22.0,27.0,22.0,29.0,27.0,20.0,20.0,BCBCBCACACAHDBFCHEHEFBGGCGCABBHBEEEBECECBDHDEBAACGCGFGFDFGBCDAHHHHFFEDDDDEFFHFDEGGGHEAEDEGBBDFEADFCGCGCHFHGHGEDCHFFFDFDCHFBCBCBCEEEGACAEHEFGFDFCFBAEHECGDEFGHGAFAEBBBBDCEHFCFEFDCDEDE,False +801,5.0,1.0,4.0,0.0,2.0,1.0,0.0,1.0,HCAEACAFBEACAC,True +802,15.0,14.0,17.0,11.0,11.0,11.0,14.0,5.0,DGAEAFAFCFDADEFEFCACGEHEFGCHABACABHBADDFDFCGEGEAAACHCGDGCGBEBFDCABBBBDBABFGGCCCEGFBBBEDAHCGCGCGCED,False +803,19.0,24.0,22.0,27.0,21.0,24.0,25.0,26.0,HFAFEFEFCCCHCHGDDHEHEDEACCFAFBHDEDEBGCGBFAHAHAHFGDBAGAHBHFEFBFEFABCDHDGACACBGDGHAFBDBCFHFHDHDGDADBCFGGBDACGHGCECEGGAGDGDGEGECADHDABGBDDCECEHFHBGGEGEHBFBDHFACAFBBBBHEEEGCDHGFDFDFEFHDHDCBBBC,False +804,14.0,12.0,12.0,16.0,9.0,14.0,9.0,8.0,ABCBAFDEDFDHDCDBAFCBGBDBEAEGEBCDGAACABDECECEHEAGHGDBHFFFCGDADFFFGFDBDFAHCHCHCHCBADADADABFFGGEF,False +805,10.0,5.0,7.0,4.0,17.0,8.0,9.0,3.0,AAGAGAGAGAHECEFEGEHEBEAEFDADFEEEECEDECHGFEFAFBEDFGBEACBCEFBCCGG,True +806,16.0,25.0,13.0,17.0,23.0,16.0,21.0,18.0,CBGEEFEGBBBCHGHBAAAAGAGEGCHCEDBBBBBHHHHDAFFEEDEDAAADFEBHGHDHEGEGHCECEBBDADGGGGGDGHEHEHEBBBFGFAFDFEFEBEBCFFEBHBECDBDFAFAGHDFDGBHDCFCAABCBHEGDGDEBGCCAF,False +807,3.0,8.0,5.0,8.0,9.0,8.0,9.0,9.0,HFFFBHCHEBEBEBGBDCGCECEFDFBFGAGHHDHFACHDHDEFBGDGEHEADGDBEGG,False +808,18.0,19.0,24.0,19.0,15.0,25.0,23.0,17.0,CDGFCFCAGHEAEADCGEGACBGFGDHEEECACECECFAHAFDCDHDFEBEHDFDFHFGBEBGGGBBBHBHFAEAFGFAHAGAFCGCHCHGHBCDDFDFDGDFBEBEBFAFCFGDCCHGHADCBFBGBGHFCGDGBCAHFDFCFCBCBDAEABADGFGHC,False +809,24.0,16.0,20.0,18.0,20.0,16.0,26.0,18.0,HBEFGCGHAHADGCACAFBFAFCEBGBFDGAGAEHHCDDHDFDHDHDEECGABCBFEAEHDGGGGBABGFEBCAEGBCFCHGHBHBABGBHFEFCCCCAHGEGEFHFDGAEBHDADCGHEAEAEAEAEGEDCDADGDGAGAGAEHDGCCFCFCADBGF,False +810,7.0,10.0,7.0,14.0,17.0,13.0,14.0,8.0,DEAEGEFECACABGEGEAHGHGHAEFEFECHDDFDBDBCBDBDFGCGEBECEDDDADBEFEBDFGBDFHGCFFDGGFEHEHFHBGAGEGF,False +811,11.0,12.0,11.0,18.0,16.0,11.0,15.0,16.0,EBEBABDHDHDHEHGHFAAGGCAFEDDGEFAFHDBDBDHEGGGGBCBCFDDDDDEDBHFEBHCHABEFEFGHECECBFGGGEDHCHCGEGACAEAECHABCHDADFDFHG,False +812,7.0,8.0,5.0,1.0,6.0,6.0,5.0,5.0,HHHHAEACACBEBCCAFAGEFCFDBHBFBFEGAGEGBGFABBE,False +813,7.0,6.0,14.0,17.0,20.0,8.0,11.0,16.0,BCHCAFAGAHCEFEDEHEDCHGHAEDGDFCFHGHGHAEGEGFHBBDFEHEDEDHDEDEBGDDFBEHGABCEDECCCADGHEHEHCHCDCDCDCEEGEFD,True +814,27.0,14.0,15.0,25.0,17.0,16.0,12.0,25.0,HFFCACAHFFCBCFFGDDECEFEHCBCBCDAAAGAHAHDECEFHAHAHDEABBEBCFGBGDEAEAEADGHAHACDHHHBCBEDFFAFHFEEGAAAAAHAHEHEDDDDGAGDHDBDFFAHDBACACAGHHDGBGBEDDBDHFHECGDDDHDH,False +815,9.0,8.0,11.0,6.0,5.0,16.0,9.0,7.0,DDGCCHAAADDFEFBHDFFFDFCFCFCFEBEGGGCFCGHGHEAAAFFHBCBGBEBCBFFFCFCAAGAHHGB,False +816,27.0,23.0,14.0,24.0,26.0,27.0,25.0,22.0,DABHHHEHAHAEFDBAGABDBGHDAAGAGFBAHAHEEDABFGGEEADAFBCACGCGCEFEBEBDFDCDGDEFEHEHFAGAGCBCGCBCBEDAGGBABHDFBFBDEHEHGBFEFEBDFHFHFDEECAFGFGFEADHDAGAGADCDCHFHCEADFDGEAFBFCFDBEEDGAGBEFEHDHGAGHGHFBFBF,False +817,1.0,1.0,2.0,2.0,3.0,7.0,3.0,4.0,FFFFADHDHEHEGCFBGECFHFG,True +818,10.0,14.0,17.0,5.0,12.0,5.0,16.0,9.0,CACBHAACABGDCAEAFGBEHEGCGCGEGEDBGAGFHBGCECEFEGEGBHBFGAGHEABDFDBCBCBHEHGHGBDCACBGBECCCCCH,True +819,20.0,12.0,13.0,11.0,16.0,13.0,21.0,6.0,ADCECACDCEGDFFAFBGBGBGBAAAEBEBGFDADEDAACACDCHHBGGGGGGGEGAAHFEFCGDGBCFABAFEGCDHFECEDEHABCDAHFGAGEGAGAEAGBFBCEFEFE,False +820,24.0,22.0,18.0,21.0,20.0,19.0,14.0,22.0,ECFBHAHAHAEAFBFGDGDCBCGAEAHABCBHFEDEDGBCDCDADABAEAEBHDGDHCBAHFDCDHHBHEGAAFAFCHCDDEHBFBFDGDGHBAFCEDEHFCEHEHEHGCGAHABCBEFHFGCDCDFBFBFAFGBDEDAGCHBEBCBADAGEBEAEAFFH,False +821,24.0,21.0,19.0,22.0,19.0,13.0,20.0,29.0,DAHAHAFEGCDEECECAAEHEFDDDGAGAGAGABHBGEHDHFHEHAHAHAFBHBHCAADCEBBGDECHGFGHGAGEDFDFDHHHCGAEABFDGBECECAHACFCHGFBDHGFDHBHDDDDGGHEHAHBGBGBHEABBFBDBFBDAEEBECCCCCACHCBCHAHDGDB,False +822,16.0,25.0,27.0,23.0,14.0,15.0,16.0,28.0,BHCHCDCAGFGAGBFHEHBABGDHBABFBGBDCHCHCHEHAHEHCHDBGBHACADADAFFHAADACBCBEGEFDFDFDFCHEHDDBDEGEDHHHCDEGHCFGFDEDBBGFGCGHAHBDCECHCABHFCCHCDEDCDCGBBEHDHBGBFEFCACHCBBABCBDGC,False +823,19.0,16.0,17.0,19.0,13.0,21.0,12.0,12.0,AAFGBDHDCDFDEHBBFHFCDCABBFDFGEGEBCHDDDBDGDACAGABEGECECECEFEHCHAGDDHCCDAEFFAFBFBGDAEHHBABAHADABGBFCFGDCDFHFHAGAFAFDFBACACFGFEFECBC,False +824,23.0,14.0,24.0,16.0,17.0,21.0,26.0,11.0,EEEECEBHDFDBDCFAABFDEEGGCGEGFHDGAGBCFCHCFAFAGAGFFBGAFAEABCGAEADADAHBBEHCHCBCBCDCECGHBHAFDEDEAAACACFFECEFFGACCDCFGGCGCGFDFHFGCGCGAEAGGHHFBFDADABBCGGGDGDG,False +825,16.0,23.0,19.0,19.0,25.0,21.0,19.0,16.0,BCECEGEHBGBGDACADFFBABGGEBEGCGAGDBCFCEADAEFEDDCHCDEDGBGCFHFGBEBEBEHCHCEBEDEBFBFEFHFHFGDEAEBGBEDDCBHDFGFCACAGAHBDBDBCCFCFAFDDDADHEEEFHAEAGBGCAHHHEHFGFBFGECHABF,False +826,8.0,5.0,4.0,4.0,6.0,3.0,1.0,4.0,CDGDCFEEEEABABADAHBFBHACAFHEAEAHCBD,False +827,24.0,26.0,18.0,19.0,16.0,34.0,27.0,29.0,CFAFCHHGFDHDBDBDCDCHEFBGBGBHBDADCGCGHGFDFBAHDDAFECBFFFHFAGECAHAEBEAAACGEGHGEABAFGCEAGFFHFGACBGHGAFHCHGHGBFAHGHBHBGBGAGCFBEDHBFBHEHEBFGECEADHFHFHFDABFEFHFEFBFBABDBDFDADGDGCAEAFCFCFCDAGGFGFBHHHHB,False +828,2.0,3.0,1.0,7.0,4.0,6.0,1.0,1.0,ADDDFDFEFEDEBFBEGFDADFHCB,True +829,18.0,8.0,19.0,22.0,14.0,21.0,12.0,12.0,EGEGCHAFEECHDBDBDCFAFEFDFEGEAFCFDADADCHFHEADAEHDHCCFCFDFHFDFDACACACEFDFDGBFBCGEGFGCGCAHADACEDDGCCACHBABDBHAHFFFDDHACBDEAEGGGFD,False +830,14.0,17.0,12.0,13.0,7.0,7.0,14.0,9.0,EGEBHBDCDGECBABADDGCABACFCEBDCCADADFGHGHGFGBGBGHGFDDCDAGABACHHDHDFDCBBGBAAFACEHAGAGBEBHBCBEBF,False +831,13.0,21.0,11.0,11.0,12.0,12.0,12.0,8.0,EAEDGBFBDBCHEBEBEBCHCHAFGGBCDDDCDCBADAFAFABADFCBCGEAEDBAFAEHEHADFHBBEHEFBFGEBHFGBCBCBFGGAGAGBGCGFBDB,False +832,14.0,20.0,21.0,16.0,26.0,24.0,30.0,17.0,BGGGEEEBFFFEFCDGGGGGCGABDFGHCAFFFDFEHDHAGAGAEBEBCBCAGBBDBFBFEEEDDFCCGCGEGBBDBHEDCFCHGFEEBGCFAEGEGECFCGCHEDDCBEDDDHHHCGBGEHEHGDDCGCGBGEGEBEHECGGAEABAFAHAFAFHFHCHCFFFHFBA,False +833,0.0,0.0,2.0,1.0,0.0,7.0,1.0,2.0,GFFCFHDHCFFFF,True +834,15.0,17.0,13.0,12.0,21.0,19.0,18.0,23.0,DEFBAGHEHEABHDFGFHFHCHDHECEHBHDGDGFFCGBFBEEHHCDEFECEDEBCBGEGEGACAGHGHAHDFCBHGFFFFDACEHEBFBHBHGAAEADGGADHHHHGHGFAFCFCGEDFFABABGECACABEBEBEB,False +835,9.0,17.0,15.0,12.0,13.0,15.0,12.0,18.0,AEAFDHGHGFDEDBFBABACCCFCHEHCFEDHFGFDHBHBHEFAACHEDECFCGCBCECEGHBHCABDBEGFDFDBDBEGEFFCCGHAHAHGHDFBBGBGDGHBHBCBFHE,False +836,24.0,27.0,17.0,31.0,24.0,22.0,21.0,23.0,DCGBEBCDEDADFBFEDADADBDCDCDEDFDGBGCGBHBHBHEHEDEDAGBGFDAHGHBCECADBDEDBFFAFAFAFEHHGCGFEFDDGDGFBFGEGEBAHAFDDHFABBBDADAHAGAFFFCGGEECHGAGAEECEBFBCBHHGEFDAAECFADHGHCHBBBBDEDHBBBEHHAHCHCAEFEHADGDC,False +837,8.0,2.0,11.0,12.0,11.0,8.0,3.0,11.0,BHCHEDEHFAFHDHCHFDCDFDFDAAHCFDDADHDECECACECAFEHEGDGEHEDEHFCBCGCAEA,True +838,12.0,19.0,12.0,11.0,20.0,17.0,13.0,16.0,DEFEFEHEFBFECEAEAGBGAFEBEDFGFGAHFHFCGBBBBBBHEFEBHBGBGHCHFBCDFHAACCHEHACDBFEGEDFBCBABHHCHEHACACEDDDDFDGHGHCAGFDFBEEEGEGBA,False +839,1.0,4.0,3.0,4.0,6.0,6.0,4.0,1.0,GBEECAGBFBFBEDCDFDFEEHEDGFGFC,True +840,5.0,4.0,4.0,1.0,6.0,4.0,2.0,2.0,GEBEFEHEAADACACFCFBBHCAGEBEF,True +841,15.0,12.0,13.0,8.0,18.0,15.0,11.0,15.0,FHFHFEAAHFEFCGEHEHCHCBCAEBBBCHAHAEGFGABHBEBEFCBCAHDHBEAFGBHAFEFBGCFEFCDADBDEDEDEGEFEFAACHDHAEACGEGHGCGAGFDC,False +842,17.0,27.0,15.0,15.0,25.0,21.0,18.0,18.0,DBEBDBEEGGGBGEHCACBCBABGEDEDGFAFCCBEDCGGFGBHAHDBBHBHECACEDBDHAAFAEBEDCDCHGBEDECHAFAFECECEFHGHGHBEBGBGBFFFFHFEFHFHEBEGEAEFFAFGBBBFHCHADFDFBABCGAEAGFHDADEBHBE,False +843,20.0,14.0,16.0,25.0,17.0,16.0,12.0,24.0,HBHEDGBFBCADADACHHDHDAEAHDDDDDHFFDHDGCGCBHEGABAHEDEABACDCEFGFHAGGBACGHAFFGDCAAGHDEGEGEDABACABHFDEEBEBDBDBDHDADAHCHBEFEDEDCFCFCHCHFHFHFHFCAEHHFCE,False +844,6.0,6.0,6.0,6.0,7.0,4.0,7.0,2.0,GCECFBDBDBEGHDEAEAFFECECACBGBDADGDGHFABGEGCA,False +845,14.0,10.0,13.0,17.0,13.0,16.0,16.0,22.0,DADFGHGHFHCBGAFEFCFCGDGDEDBABABECDCDBBGAFAGAHDDDDFDGDGDCEGGFHFHCHGAGDHHHFFCGCHHEFEAHHHFHGEGDAHECDCHHAHAEAEBCFHFBFCEHBBEEA,False +846,13.0,21.0,15.0,9.0,8.0,13.0,6.0,10.0,AGBCBCBDGCBFGHABCBCBEBABCGHEHBAFAFDFECDBBAAHBHBHCFCFDBABDCDFFCGHAHBHBEBEBCFCACDEHACEBFDFGFAFAED,False +847,8.0,14.0,10.0,15.0,9.0,10.0,9.0,7.0,DECFAHHBGBCEAACBCBADDEBHDHDEDFFFGEAEBGCGBGDGDFDADBDBDCFCGCBCHABFBDEDGDGBHBFFCFEAEH,False +848,10.0,5.0,6.0,10.0,12.0,17.0,10.0,11.0,DHDEDCDFDFAFAHCFGABAGFCFBGGGGAHCFDFAFEEEEBBABHFAFGFEEHDHECEHFHFEAHAHEDFDFHFDGGGEC,False +849,22.0,14.0,13.0,19.0,14.0,18.0,13.0,19.0,AACFCFBBHBGFDADADAHHCGFBCHHFHBHDGDCAHAHABDEDBDAHAGFGEBEBACHCDEGAFFDGBHFCFDDBABAEEDEGEFEAAGAGABADAHFGFCFAAGCFHEHFGFBFEEDEHEDCDCDCDHHH,False +850,12.0,11.0,24.0,25.0,18.0,37.0,27.0,36.0,GEGEAEAEDHDEDECECGGGEFEFEGCBFBFCFCDCHEHDDGEGFGDHFGEGAGCGFDHCHFHDGCCHEBBDACHCFCHGHCHCHGDFFFFDFHGHDFFFGFGHHHGCDFBFCHHFHDDBACHEEFDCAHDHBHFFFHHCHBHFHDGFGFGBEAHFHFHFCAGGDCBGDGDFFAACDCAFDFDFBHHAHE,False +851,8.0,20.0,9.0,10.0,16.0,10.0,11.0,18.0,GAGAGFFHFHCHGHEFEGADABHBHBFEEEBAHCHCEEHEDCAGGBBDBFGFHFHAHFHBABEHEBFBCHEBBBDDDCDBECEGDBCBEBEBHBGCHEDDHG,False +852,8.0,4.0,3.0,3.0,5.0,4.0,5.0,3.0,CEHEHBGFGBABDCGAGHFDCGAAAAEADAFEFEB,False +853,2.0,2.0,4.0,5.0,2.0,8.0,1.0,9.0,BHFHFHFADCCGFDFDBDEFAHHHHHFHECCFD,True +854,0.0,3.0,1.0,7.0,1.0,4.0,3.0,3.0,BGEDFDHDHGFBDBCGHDFDFD,True +855,13.0,9.0,23.0,8.0,13.0,14.0,12.0,14.0,CFCFCGHEACCCEEEGDHHAHBGBCFCDCDCFFGCAFDCABHCHCDFFCECGCGCAABFDEDACCHHAFAEBEBHGHBHFGEGCGCGAEBCBAGEFEFEFDHAHAH,False +856,10.0,14.0,21.0,25.0,13.0,22.0,18.0,15.0,HDAFAFDFBGDDCEEGEDFGBDBGCCCCDDDGDGHFDGHEFECHCHCFEDBDBACGFBFBFDCGEGCABABDEGCGCECEBAFGHHBDDDHHHGGDCDCACAFBEBECFCFAEHHFFFDGDGHGHDDFDFHFCFCBAF,False +857,5.0,7.0,6.0,6.0,3.0,6.0,3.0,6.0,HBHCDAHAFGBACABHBDBDEFGCHCHCBEFEFGFCFDDBDA,False +858,5.0,6.0,10.0,9.0,8.0,7.0,3.0,10.0,BGCHCHCBDDHDGDGABCBABFECECECDCDFHHCEDDFFFHHEHEAEAFHBEDHCAF,False +859,5.0,3.0,3.0,10.0,1.0,2.0,6.0,6.0,DADADBGHEADDDCDGHGHGCDCDBFAHHFHAGDGB,True +860,23.0,20.0,27.0,31.0,27.0,21.0,22.0,20.0,GBHCDCFCFDEDHCHGEFEFECCCCCADABAHFHFHFDGDAEEHACDDGBADFDEECFAFCFEGCGEEHFAFEFBABCDADEDEHBHGHBBAECECGBHAGFHHBGECCDEDBFHCACGCDAGAGADDDDDCDGFCFCEEEDEBHGHGHGCGCBDADHBGDDEDABABAEDEBFCDEBABGBDAFAFGEGH,False +861,7.0,7.0,14.0,4.0,11.0,5.0,11.0,5.0,GCGFGBGCCCGFAAEAECECECGBABHHCAEAHAEFEBEHDCDCGFGFBCGCGCDBEEHDGECB,True +862,12.0,3.0,10.0,5.0,8.0,8.0,5.0,6.0,GFCAHAHAGACCEHDBBAAAHADECEDECGCBCECFCFHFHAGGEDEFFCFAEAFAD,False +863,24.0,14.0,29.0,24.0,18.0,18.0,12.0,25.0,ACACHBEBEDABHBGCDCFCEDFCGCACGFADCCCCBCDEAEBDHEEGAGCDFDFDFGEHAHFEEAEHCCFHFEFCHCHDAAHGDCDAHFHEHDHDHAHADEBEBEGADAHEBFHFHACGFGCGCBCDCDCACFCFABCBADDBCBHHDHGAAHAHFFDHDEDA,False +864,12.0,14.0,8.0,8.0,15.0,8.0,10.0,15.0,EBEBGHCABAFAFDFDADGBHCEBGBGBCFCAEEDHCHGHBHDGDHEHEHEHCFGFBEEHAAAHGHGEGBFCABHFHEEBADCDABEBEA,False +865,3.0,2.0,2.0,3.0,0.0,3.0,0.0,4.0,BHDHBCFDFCAHAHAFD,True +866,5.0,8.0,8.0,6.0,13.0,7.0,15.0,8.0,FHCDEDADBEBGAGCCCEBGGFGEGEGAGAGHDHGBEHEDGAGEBECHCGFEEHEHGGFBFBFCFHEBCD,False +867,15.0,8.0,10.0,4.0,10.0,7.0,12.0,11.0,GCHHEHGBDBCGCBCFEAAHAHADFCFCFGAGAFBGAHAEGFBECEABHCHAEAEHGHGFBDCHGEGEGDACABAEA,False +868,13.0,19.0,24.0,20.0,14.0,16.0,12.0,20.0,HCHAHAGDDCDBGGHGHGCEEAEGFBFDEAEFCFHDHGFAFGEHDBDBDCECDFECHCDCFCHCHBBBBGAFDCACEDBFFAFAFBEHCACDHBCBCBHBCADDDBDHDHCHCBABHHEFGAECGCGCBDBDCFHFEE,False +869,11.0,10.0,12.0,15.0,14.0,12.0,10.0,5.0,CBGECDGDGDADCGAHDBDFFFFEAHFEFDBDGDGECECDDFDADBEACGFEBEBECCCGCBCBEAEAFGBAAAEDEGHHDHCFAFEFB,False +870,8.0,16.0,15.0,5.0,12.0,6.0,10.0,5.0,GEGAAFBCBCEGAAEBEBEFHHCBAAGACBBBBEBCGCGCECECBABCFCGCFEDEHCCDGBGFDFDEHCHBBGBDE,True +871,7.0,10.0,13.0,4.0,10.0,7.0,7.0,8.0,GAAHGCBADEDHDCCCACAFHEBBBBBCBEGEGFCHCBEGEGEHDHCFFABCFCFHGHABFECECE,False +872,5.0,6.0,11.0,4.0,5.0,6.0,7.0,6.0,FCCCACBDAFCCCFGBBHBGAGEGDGCGHGHDHDEBHCCFCBAEFEFEHA,False +873,6.0,3.0,2.0,8.0,3.0,5.0,4.0,1.0,AADDDCDCGGFFEBADADADEDGBGFFEFAHB,True +874,16.0,16.0,9.0,13.0,16.0,16.0,11.0,18.0,DGAGHBHCEFGDAAEAFAFBBDFHEDEDHBHGHGHDDEDFCFCAAADAHFBCBCGEHEBFDFAFCFAFAFBECCBEDHHEHEGBGCDFGFHHHBHBEBEBHAEADBEBAAGEGHF,False +875,10.0,10.0,11.0,9.0,10.0,8.0,13.0,16.0,AFADADEDEFHCHCFGBGEHDFGHCHEGBGHFABHEACHBHBHBHGDGBAAAHAHCHCGGGCGEDEBCDDGBGAECEFFFBCHCHDE,False +876,10.0,18.0,8.0,11.0,7.0,15.0,11.0,9.0,FCHDHBFBGCDHAGCCHDHAGFFHBHEFAFAFDBBBDBDEACGGGBGFECECACHDBABFBDBDGEADADFFFGEGEBBBFBFBGBFAH,False +877,4.0,5.0,14.0,13.0,6.0,8.0,11.0,11.0,ACACGHADGCECGGGDCCCFCFBFDFDHDHDADHDHFFBHGHCHCGCDCDHDEEBGFDEHBHGEEBDFCCGG,True +878,22.0,17.0,15.0,16.0,16.0,19.0,13.0,15.0,CCFCHHDBEGEGDCFHFBAGFEDDFDCECEGBCBABADADBGGDBACAFAEABHHHFHCHDBFBDBDBEHHCHCHEEGFGFHAEAEAEADFEAABCFCEAHFGAAADFDFBFBEGCGCDAFAFAEDGBHBGFA,False +879,11.0,12.0,5.0,10.0,10.0,9.0,11.0,9.0,BCBCEAFGFGHBHBHDDFEFGBGHGFBDCAAGEHDBDGHGHFADAEEFEDEDEAHABABACAGHEDFAGEDBGBCBF,False +880,22.0,23.0,20.0,22.0,17.0,22.0,27.0,22.0,AFEFEHDHDHDBFBGBGEGBGFGFGEHEABABGGGABAHDHEBCGCGCFCDBDFEEAAAFDCBFHGHBCGAEDFDFDBCECFBAGAGAFEHGGCGDBBCCGBDDCDBDCFCAHDBAFFHCHDHFHCEEDHDHBHCCBFBAEAEAFGDCDHAHFHEHADAGAGAFBGCGHGFBEGG,False +881,26.0,17.0,21.0,13.0,20.0,12.0,23.0,19.0,BAEAGCGHGAEADABEEEGAAHHDDBDFGAGACCHHEHEBFBHEEEDFGFEAGHCCACGEFEDCGCHCGFHHBHBGBCCCDCGBGBABABFDDHEAEFEGGGGEHAHACACDGBGBGBEAFACEHFAAAHGHGDCCECFCBCBHDAAAFAD,False +882,1.0,1.0,3.0,2.0,1.0,1.0,0.0,5.0,DHHFADEBCHCHCH,True +883,7.0,3.0,8.0,7.0,4.0,4.0,4.0,4.0,GDEDCFHFHDHDEGEACDCABBGFACACGCFCDADBCAEAH,False +884,21.0,12.0,14.0,11.0,9.0,9.0,15.0,13.0,EHEAEGDDAGGBGFFAGHDHDCDCDCFCGGGGGAAEGCHEDEAEFHFAFGCBHBCCCCADBBAGAGHBCACAHAHBFEDBGBCBEDDHHABAFAHAHFBCAAAA,False +885,16.0,26.0,24.0,20.0,25.0,24.0,19.0,20.0,DFDGGAEAEAEDHGHGCCABBEECFCFGBGBDCGFFDBDECEADADHGHFDBDCEEBCGCGAFBFBCHDFDFEFEFHFHFHBHFEFHCHCBAFDFBFCAGAECBBBBEAEBGCECFHEHDCCEGBGBGFGFHHEHCHBDACECABABDBHAEDDCGGBBEFDFDCBAEHEHECG,False +886,13.0,28.0,17.0,8.0,23.0,25.0,17.0,16.0,GFFBFBHCFBBBCGCGEEBCBABFDEBGBGCACEHFHFHBADDCGEGEBHAAACFCEHBHBDAEFFFFDFDFEFEFECEBBBHFGBBHBEGCBEAEDCHEEEFBGHGECEHFHBABFCFCFCGCEAGDGAGAFBGGAFHHHBEBEBF,False +887,12.0,16.0,10.0,18.0,15.0,11.0,14.0,8.0,EEHEFGDCAFDGDCBFBFGFBEAFBBBAGFGBGCHCHCAGADCFCDBDEHEAEDGDBHBFGEBEBDBDADCDHDEABDDEDFCAGDGAGAFDEAGCGBEBEHEH,False +888,18.0,13.0,17.0,15.0,11.0,10.0,18.0,15.0,DEGEDEFAHAHAHGHGHGCGCFDDDADFCBGDGDCBABCBEACAGAGCEDBABDHFGAGAGDEEHAFCDCBCACBEBHCGBFAHAHCDFHBGBGHFHGHFBACEGEGCHAECFCDAD,False +889,22.0,5.0,11.0,9.0,14.0,19.0,10.0,13.0,HEHFADEFGFCEHEFDFHFAFGGGGAGAFADGDFAEAHBCECEDFCFHFCFDFDAACACABBFGCHEAAABCDHEAEABFHFHEGEFHAAAAACAGDHCHEFE,False +890,27.0,36.0,17.0,27.0,26.0,14.0,25.0,25.0,FHDGFABEECADAEBECEABAGHECDCDADGDADADEHEHGHBFBCBGDEEEEEBABABHBHAGCEDEDEHAHAGGCDCDHBABHBCACAGFCFGHHFDFDGBGHGAGCGFFBHADFCECEHBDBGBABACAHEBBHGHEHBBEDEFEBGBDBCGEDBBBBBEBDHDBAHGFGAEBHAADGHGDABFCFDAGBGDHD,False +891,18.0,15.0,22.0,14.0,25.0,27.0,18.0,19.0,FHFHEHAHCFEDCDHFFFHCCCCCCFAFGEAHAFGGEGEGEGFGFAEHDCDFHGAGEBHFHCHBHBEDHDCFCACGBFCDDEHBCEGAFABEBFDEGAFDCACFEFEDEAAGAGAGCBCDFEHAHEHBCBCBFBEEFEHGGGCEFEFEBEAFFBDADB,False +892,15.0,15.0,17.0,14.0,25.0,21.0,15.0,21.0,EGAHHHDHDFEAEDEGGGGAGFHFAFEEEHHBCBGHGBGDFAAEAECEFEDDBFCFCAGFFHFHFHBCFCDHFHCHADBHFGFGBEBHHEEDDCDGBCEEEBGBHEHEDEAFCBCECEBGAAAEDCDCACABEHHCFEFCFBF,False +893,5.0,2.0,1.0,1.0,3.0,2.0,5.0,2.0,BHAHAEEEGFGFACGBDAGAG,True +894,1.0,2.0,2.0,3.0,4.0,6.0,4.0,3.0,FCFCHHEFEFGGGGHDBEBFAFDDE,True +895,12.0,25.0,10.0,17.0,18.0,19.0,18.0,17.0,CECBHFGFGEBBHFEFDBDBABDGAGAEABCBGAGAHCEEHEHEHDDCDBFHFHEDFCFBFBFAGGGGGFGEHBBBHDHBHDEBEFGDCBBBDBGCAHHEGBGBCDFDEEEDEACAFFGBBHFHFDFAFHGBADED,False +896,16.0,8.0,11.0,13.0,10.0,11.0,7.0,7.0,GEDEHEHBBDADFDADCDCAAAHFHFGFECACAEDCDGAEAEBBCBGEACAHDBDEGFHFBCDCFAADACBCHFAFAFEGGDF,False +897,11.0,6.0,9.0,7.0,10.0,14.0,15.0,10.0,HDBFBGCFCGCGBGDEDGHAHGHAAFHFCGBGCAHHGFCFAFEBGHGBDCHCHDEEFEFEAEAEFEFGDGFAFACGEFDAGA,False +898,17.0,13.0,21.0,30.0,28.0,20.0,12.0,19.0,EDDBGCECEDBCBCDHGFECBGBEHHHEHFHDGDHHAFAHCHDBEFDADCDHEEEHEGDGDGFEDCACEDEAEAEFDFDFDADCCACFEFCFEFCBBHCCFEEDHDFGEGAFCFCACABABCGDEDAHEDDDDGDGFHDHDABFCFDFAHEEBEBEHEAA,False +899,3.0,3.0,2.0,3.0,3.0,3.0,8.0,3.0,BCEFGHGHGAGBGBGDFDCHEGEFAADG,False +900,16.0,24.0,17.0,15.0,11.0,13.0,13.0,18.0,DDCDADAECDHHHCHADDHCHCBCADAECGHGEAHFHGBBHDADAEHHFHGACACFCFBEBEDCGCGBBBBGEFFHFBBGCGBABABAHFEFBBECCHGFDFBFAFAHBBEBEACDGDGCBHBGBDB,False +901,25.0,30.0,29.0,16.0,34.0,19.0,24.0,19.0,FFGCECEBBBCDCBFEEEECGCABAFEFGHBDAACECGHDFCHBFBGGGBGHCHCBCECBGBEFDHBHBHCHAHAGABABGEGFCFBEGEBBCBCDHHHCHCHDBDCFCAEDHGAGEBEGEBEDEFFDBDEFBCEFEAGGFGEGFBFHHACACAEAEAEBEHEBAGAEAECGABADDDAECECFAAEDDAGCECBG,False +902,24.0,23.0,19.0,24.0,26.0,27.0,19.0,14.0,FAAAEACAEEEGEDAHEBADAGGHEDCABGFFDFDFEBEBEDEDGAHFDGBCBFDFGECFBFGFBFEFCFEDADBEFEFACACACAHADBBBEHAHBGBFAGBEEGGFGCGCFAFDFEBHGCAAGDGFHFCFCHCDCBFBGBCBEHFHCHCBEDGDACAEBDBHFHEDDDDDEAED,False +903,29.0,29.0,25.0,18.0,19.0,26.0,26.0,24.0,GABBEDADAGFHBHFHGCBCBDADGBGDGHEDBGBGDAEBEAGFGACEBEDADFFFBBBCFCGAFAHEHEHGBAAAAAAGGCCHBGBABHEEFHFHAHFBGCHDHFEBEGEAEDFGCHBHACADBHGDGCEDFFHFEFBCBABAHAEAGGFFCFAHADGDGCBCBCGCGCBCBCFHEHDFFEFHFCFABCHCDCAC,False +904,6.0,3.0,10.0,6.0,5.0,4.0,4.0,1.0,ACGCFCACDCHCDDDEDCGGEFBCBCBFGFEEAEDCAAA,True +905,3.0,18.0,9.0,11.0,14.0,16.0,4.0,13.0,DCFBBCBEBDBFFEFDCGHBHGDCFBFDEHEFBHBFEFHFHFGCAEHFAFBEHEHEHCACHGFDCBEFEHEBDBDBHBDEDEDBCBFB,True +906,16.0,25.0,37.0,22.0,24.0,10.0,28.0,28.0,DFDCDCEAEHCHEACBHBGBHCCGCECADDDDDDCHHHAHCCCGDECECEBECHCFCFBHBACGCBABCBHGEBBBHGHGBCBCDEEAAGAGDHFCCEDEDGDGDGBGHHDFFGEEBFAGHGFCBBGEHHBCBDBABCEAGACACGBEHEHCFDHAHEGGGHGHGACEDECHCGCGCDHFHBEGEDBCGC,False +907,25.0,18.0,28.0,21.0,19.0,32.0,30.0,20.0,GCGCEBHGCGCEDDHHGCCCCGHGHDHEHACGGGBGFGBEACGHGCFDFDCCCHCFDFAFAEAGABACAGACEBHBFGFBFBDHCFAFGFACAGDEHCDBGHAHBBDFDFCFAEBDCGFAHGHGFGFGBADFEFHBDADABBEAFHDDFDFGBGDEDEFAFEFEFGFAFDFEFCACHFHBEEECGCGCAAEAC,False +908,28.0,27.0,16.0,15.0,23.0,29.0,25.0,24.0,FAFEFGFBABHFFBHDCCGAABEBCACAEFFCFAGAEEGEGFGFDFHFHBAGFGBGDHBHBHBCGEGFAAHAHAHAEGEBEAHABCBDFGFGEGBFBHBDBFBFGFGHGHBEBEBDGHGFAFCHADEEECECFBACCBCDDHGGEHEGCAAFAFBDHHHDHDFDADGFAAEAFABEECGHHDBEACB,False +909,22.0,23.0,20.0,21.0,31.0,23.0,29.0,28.0,EAGGGDCHHHHCDDEDBCHAEDGBGAGADBHAFFHGBGBDEGEGHGAGDBEGAGCCHFHFGEGHHEAEBDDDDADHCBBBCACFCGAGECEAEFEGEDDAAEFEHBHBGBFCFCHGBBDBFBFDEAEAEFCDDEGFGFCECAGHGFGFEHHDAFHFHGHGHFHFEEEHAFBBBEAECGCBCBCEEAHACBFDFEHEH,False +910,35.0,20.0,17.0,22.0,15.0,17.0,23.0,20.0,BABABADGDFFFFFADHEEAEHCBGBGDGEGCACHEFAAHAHAHBHGHBABCBCGCFDFAFCFCEAEHEDGFGBAAADBGADADBDBECGGFCBDBHCAADAHAGADCGFGFGCGCEDAAEAHDEDBAGFGBADDDCDHHHCHAHDEAHGFAEAFBDHAGAEHBBGCGA,False +911,20.0,22.0,16.0,16.0,19.0,34.0,24.0,21.0,HHBBFFAHAHEFAFCDBDBDGCEEBFBDCCBCHDFAFDBDBFCFAHGEDBGFFFDFHACEDGDBFBFCECHCHBFAFADAFFFFFFFGFBHGHGHGHAFABACHCFGGGAFHFHGGGGFAFEEGHGEEEGECDGECBCBHDGDGHEHDBAGEBEAEABABFEGACHEBGFAF,False +912,14.0,22.0,22.0,16.0,10.0,16.0,13.0,11.0,GABHDHAHACDCBFFFECHFHEBEGABCEHEBBFBACHCHCACABEFFDBACDHFADAFBFBGGCGCGCHFBFCGDFAFGBCBCBDHDGDCBCBCGDGCGAGABCBCACEDFDEEFBBDDDEDB,False +913,20.0,27.0,29.0,23.0,22.0,31.0,29.0,18.0,GFGEECFDFAGEFHFACDEGCGCGHGHDHDCGCFDBAGAGAGDGHFDFBFGFGAGHDAGAFABDCFFECECEFFDCDCBCGDBABFFHFDDDGACHHDBEBEBFCEEBEHAHECBABGGAGDHDCEEGFCFBDECACAFHFAFACBEAGGGBGBCBHFCFCFCFCHDFAEBBBHBEBECFCHEEGBGBFCDBDBDBHGC,False +914,12.0,9.0,6.0,2.0,6.0,6.0,2.0,13.0,BFBHEHEHBADCHBAGFHFEBHAAACABHBHAAACECBBACGCHFHAHAHEHEFFD,True +915,10.0,12.0,24.0,13.0,16.0,14.0,13.0,16.0,CEBDBDBDCDCDCDBDAHHBFBFCFGFGEDFHCBCFGECFCEBEBHBCCFCFDFEHAFBHAHAHFCACHCECEHACBCHCFEDEAGACDCHCGAHCDEGGHEEFHAGGGECEGEHDGG,False +916,4.0,4.0,9.0,4.0,6.0,12.0,3.0,4.0,CECDADFBACFCFDFBFGFCFGHCCGBEHEHEHEFFCACBEFFFAD,True +917,15.0,18.0,12.0,11.0,16.0,11.0,18.0,15.0,AEAEAEAEAHAHAGEEFHGHBHBEDABABADHGFGDHBCDDFHGBEFFFAFGGHBDFCBEHECECGFHBHEEGDBEGEBBGDCDHDCACGFGHGCABABHFACCCCBGBGBGDGBE,False +918,14.0,16.0,12.0,30.0,16.0,18.0,12.0,16.0,DHDAEBFADADADADADGDFAFHFHDEFGBGBGBGFHCGEHECEAACACGCDDDFEBEBHBFAFHCDDDDFCFDFGHCFDHEFEFDCHBBBHAEDEDBAAHCEFDCDBDFDBEEDBDHEBDHDGFHDHEGGGCB,False +919,5.0,11.0,3.0,9.0,10.0,8.0,8.0,5.0,BFBHEEEBCBHEHGAGAGDDBDEEEHABFCFBAGDCDGDBDGAFEFEFDBDGGFBFBHE,False +920,5.0,0.0,5.0,4.0,1.0,1.0,4.0,2.0,CGAAFADHDCACGCECGDGDHA,True +921,24.0,17.0,18.0,26.0,23.0,31.0,24.0,25.0,EDEDCDADFGBABAGGFCFDFEGCGBHHECEADGDEDFDFDBEGEFCAGFEFEFDHEADHCHAHFHFHEGEDDDDBGEGEFBCDCEAAHDBAGHDHFGGHEHAHAHAHFHFDFBGBHCGAGFEFEFADACAFEBGCCDBEBADAFBGCFAFCHCHAFEFGCGBGCAFABCDAFBFBHDHFHEGDGHFH,False +922,12.0,3.0,17.0,8.0,6.0,8.0,19.0,16.0,GDFCHCHAADGBHCHAFEHCHCBGBCHFACAFADGGGGGGCGCAADHEHECEAEDDCCEGFGFGAGAHHGHGCDADCCHHGCGFHFHGC,True +923,13.0,7.0,15.0,17.0,15.0,11.0,14.0,5.0,GDDDHCCBCDADAEABADADGHFDCCACAEAGGDEEEDFHFBDGCHBFBFDGGBCDDDFCFCFEEGCFEFADADACAGGGGEGCCAEBEHEGEFECE,False +924,19.0,22.0,14.0,20.0,28.0,12.0,19.0,18.0,CGCDHBFBHGEBEADBDGDGDCBCDCHCEBHGEGEHEGDFFCEAEDGCGEGFDEEEEEBABCBCBCBCBGFDFAEAFDHDHEHFDAAHHHHEAEADAFEFEDBABDHEFEAGCBBFHDHBHBGBADHEEDBDEGBAEAGGCGHBEGGAAAEA,False +925,20.0,23.0,18.0,19.0,19.0,27.0,21.0,22.0,FEHEHEGDGCBDBHBEBCAGACHFEFHAHADAFGBGFFEGECEHDGDAHAHEDCCEAGFDFEGCCBGBFBFHDADCBCBFBCCHBHAHBDCECDFHFGFADCFFFFBFADBGGHADFDBBCBGHHHEHEHBAEAEFGBHBHGAGEFEFGFGFDCDFBFACAGAEADGDB,False +926,8.0,4.0,5.0,5.0,6.0,5.0,4.0,8.0,FGFDECECEADFBFBHEHAHADAHAEACGDADHHHBHFACBEGCG,False +927,4.0,9.0,2.0,4.0,9.0,4.0,11.0,2.0,GHGBGDGBGBEAGFGBBBBDDEBGFGEGEDECEAEAGBFCEHFAE,True +928,19.0,13.0,20.0,26.0,25.0,21.0,11.0,20.0,DDDFAGCFCHADFCCECECFBEHDBEBEDEHEHCFAEAEAEFDFBFADAEAEAEADHDFDFGBGBADEDBHCGCFCBEEAEHECFHAGACCCDDEDHHHHAHDDDACGHBACFCFGDEFEBHFHFCDDDHDACECBDHGHEEFGBGFGFEDHFBA,False +929,31.0,26.0,25.0,22.0,30.0,19.0,16.0,16.0,GADBEEEAEAHACCCCFGFEHBGBGCFCFDDADGBAAAFEFAABEHADFDFACAHBHGEFBAAACFCGABEGFABGFGEGFBFBEBFDEDEHGFEECHAHADADADCHEHEBEDABHBEACADBDBDGDGDCDCACHEHGCEHDCEABCFAEDFDGCEBFBAAEHEDEBCBCBCBCBEEAEBCHC,False +930,5.0,6.0,16.0,9.0,2.0,8.0,6.0,8.0,FCFCBBGDGDBABHCHCGEBEDDGACFCFCFCHCGCABHCCCCHFHCAGFHHCAFDDDDD,True +931,13.0,10.0,13.0,5.0,17.0,8.0,8.0,11.0,AEAEAHAEECBHBHGHAEBFCEEAEBEGCHBFBGEGFACADAEGEDBFCCHHBHBHFHCGEGHDDCDCACAEAFBCGCFEFECEA,False +932,13.0,15.0,7.0,16.0,20.0,10.0,5.0,18.0,AEABBCHEBEHEFEDEAFBHBADFHHDBDEHBABABABACDCFEFHFEGGACEDEHEBBAFGHCEDEDBGCHHDBDBEHCHDADGDEDEDHFEEEAHAHFHFHD,False +933,4.0,6.0,3.0,4.0,2.0,6.0,4.0,5.0,AGAGAHBEEDCGBGBCBDFDFDHHAFBFHFCBHF,False +934,5.0,12.0,3.0,2.0,5.0,4.0,9.0,11.0,CEDBABACFFGFAEAGCGBGHGHBHGHEBBHBHGDFHHHHBEBEAGBBBGH,True +935,8.0,6.0,1.0,11.0,7.0,1.0,14.0,7.0,GEBHGHGDBAEEDAGGEGDGBGBHHHHDDAAAAGDGDGDADABCEGEHEDDFGGB,True +936,12.0,13.0,17.0,16.0,15.0,22.0,16.0,19.0,HHEDDDDGDGAFACACHCFEEECACADBGHGFFFFFFEHEHCAGBDFEFDFEFEHEFFBBABFCHEGFGDHBCBCBEEAHCCECDDBFBHCHFHFHDEDGGGDGBGHCBGAFDGDGCAHBCCHGHFHFAA,False +937,3.0,4.0,1.0,4.0,2.0,0.0,0.0,2.0,ADDEDEHBHBACADBB,True +938,5.0,10.0,7.0,7.0,2.0,7.0,13.0,13.0,FCGGGHHAFEFBFBGBABAEGGGGCFCFHBABHHDHDHFHACDBBGHGDGDHCBDHCHGBGDHC,True +939,0.0,2.0,2.0,0.0,2.0,1.0,2.0,1.0,CGEGEBFBHC,True +940,15.0,12.0,17.0,12.0,18.0,16.0,21.0,10.0,DADACBCEGEGCCAHFCDCDAEACDCFGDAEBEBEACABEGGGABACDFDCGGFDDHCGFGEGBCBDEDGHGFEFBFGGCBCEEFAFGFHFAFHGHGCEFEBHBHGEGEGEFAFAHACBHE,False +941,21.0,9.0,18.0,19.0,23.0,21.0,20.0,26.0,EGEDHBHBHGHGHCEAAGBHBDDDGGGDGFGFEFGFGADHEFEAEAFAHAEAHBFECDCAAGDFAFHEHCCDCEFHFHFAEAHACFCFCHCECEHDDGDHDHDADEBHFEGAAEAFBHCCEGGDEDBCHADAHFBFCFCGGEDECFHGAGHECEHFH,False +942,23.0,23.0,25.0,23.0,16.0,18.0,18.0,24.0,CAHDBDHDEGCADHGHGHGHFCDCHCDFGEDEDHDHBHFDFEEADAEABFFGFGACFBBCFCBBFAHCHCEEDCCFHACACABHBFFFDFECACHHEGDGDEDBHBCBHBHADABHBHBCGHACBCBEBABCGEEFEAEAGGCDDDDAGAGAHBHDGBCFGFDCAGACAB,False +943,9.0,5.0,6.0,3.0,2.0,3.0,4.0,6.0,DBDHCFFHCEAEGBGBGAHCHBBAGFCAHAHACADACA,True +944,1.0,5.0,5.0,2.0,2.0,3.0,5.0,5.0,EGGDGHCBBAEGHGCFCFBHBHBHCFCD,True +945,23.0,12.0,17.0,23.0,21.0,25.0,31.0,23.0,AHAHBHBHCHCEDDFCACDCDFGFBHBCCGFGHGAAHDEEGECFAHAHFHDHEADFGCGCGFGEADBEAEBEDDBCBHAAFAFAFDGDHABAEHDHGEEEHDADGFGHGFEFGFCFAFHFEFADGGEGEGECFDHCHDFGHGDGCAAGAGEGFDBGCEBGBGDEDHFFCFGAGDG,False +946,7.0,6.0,9.0,5.0,3.0,13.0,9.0,7.0,BEBECFHFHAHGCAABCCFGBGFFCFGFBFDFGGAGHGFFFFDBCGHHCHCDDADAEAC,False +947,12.0,14.0,22.0,9.0,8.0,15.0,19.0,16.0,GGGGGADFDBBBCHGACAHBFGHGHGFGCCFDACHGHEFFBCBGEGDGFHHHBHDGDCCCCGBFHACACECDCFGBHBHBCEFECHCBCBCHGFGDAAAADAEEFCFCACFFEHB,False +948,23.0,29.0,24.0,18.0,9.0,25.0,25.0,32.0,BBBHGFAEAEBEBCFCFAFAFCFDFBHBGCHFAEGDACAGBHCHFDBCBGGCCBBHHABDCFGHBDCDBDGFBCAFAHHGHFHEHACEGDABGBGHABABGHHHFBFCFHFABAEAGACBCFHHBABCBCBCACFCHGHCHBGBHDDFGAAFFFEDDDGDHDHGHGHGHDHGHGHDCDCGFGFEA,False +949,7.0,6.0,5.0,7.0,7.0,6.0,6.0,12.0,HHCHADDCGBGFFHDHBBCHCHBFADAEAGAFAEAHBHEEEEHHHBGDGEGCDFDF,False +950,24.0,23.0,22.0,11.0,20.0,30.0,30.0,14.0,EHFBFBFBCCFCAAACEGBFAEEBHCHFHEAEAGBGHGHGCGCFEFAFBEAGAEBGDGCGHGHBBGBGBFBFDFECAGGFEBEGCAEBEDGHAFBHBFBDGDGFGDACCGCECACAGFCECHDFBCGCGFFFGFGCBCGABADFBHGGFGDHDEFBHCAAAAAAFFFFFDEEAE,False +951,16.0,19.0,15.0,15.0,20.0,28.0,15.0,17.0,DGGFECEHGHFHCBCEHGDGCBCGCEEFAFAFAHEHFAABHEGDGAGBGEEBHDHBBCBCHFBDBDBHEDFCAEAFFFDFDFAGBCBDECFFFEFDFBFGFGEECECEFEFEDHGCDAHAEABBDGFBFHHBHDAFHFCFAFABA,False +952,9.0,0.0,6.0,3.0,8.0,5.0,2.0,3.0,EFACCCFAAAAHFFFDGAAEAEHGHECECEDECEAD,True +953,2.0,1.0,1.0,1.0,6.0,2.0,3.0,1.0,ECEHDAAGBGEEEEFGF,True +954,11.0,9.0,7.0,13.0,13.0,4.0,8.0,8.0,CADHDHDFDABBEACAFDBBHFHGAGECBGEGEGEBEHEDEAHBGDADADADFDEBEDDCAABHEHCGEGECC,False +955,17.0,19.0,17.0,18.0,12.0,19.0,16.0,32.0,GFGFAAGFGAHADGGHGEBABFEDBHBDFHHHHBGBHDHDEAACBFBFBEAEHCDDGDFHHEDGHGBGBGADHFHDHCCGAEACDCDCAHAHFHFHFHDBDADHCCCHBACACBHFHFEFECACGEBBFDHCHDHBHEFGCECHFFBHBH,False +956,21.0,23.0,17.0,24.0,20.0,16.0,15.0,22.0,DADEHFHDCBCBCAHGBGFDFDGBAFDFDHHFDBDBACACFEHEAEAHAEEBAGCHCFCFAHAGDGDADADHHGHGECCFCFGFCHAHGDGBCCHADBDEAHGCFBHBHBHEEEEEHEBEAEGDBBFBHHCDCEBBBDBDBAADGFABADFEEGEDDB,False +957,10.0,10.0,8.0,10.0,12.0,10.0,10.0,2.0,FGFBFDFCGGFGABBBDGAAAFHFDGDBDGDEDECECECECGBAEHECGDACEBGBDFCAEAFFEDEBABAE,False +958,23.0,37.0,29.0,27.0,20.0,20.0,23.0,19.0,ADBDBAFABHBADGGCCCHFHGBBDDCACACBBAGDHDHCHFECBHFEGEBEDCCFEDEFBFBCBCBHEHBGDCDGBGAGAFFGCGEGAADACADBGFEDGBGFDBHBCAHEEFFDCDADBDBACDCDCDBHBHFEFHFDBGBGEFHFHBACECEDEBCBCBCGCGBBACAGEFBFBABGDGDHEHEGBCDCBHEAAA,False +959,12.0,18.0,18.0,8.0,12.0,10.0,17.0,15.0,BEBEBGBGBHBCBCECGCGCDCFGGHGBCHEACCCEFGAAAEHBHEHBGBHAEABHGFCFCDCEABACAHEHCGCHFEAEGDBDHDCGFDCDAHBHGFDFGGGHFBBBAF,False +960,6.0,8.0,14.0,11.0,10.0,8.0,6.0,15.0,EADADHGFDEEHFHDHBHBHCECDFDBDECHFFAFGFBEDECBCECHHHHGCGDGDHCCCCCCEEDHHAHABCGFABB,False +961,20.0,29.0,25.0,20.0,25.0,26.0,26.0,18.0,BHBEFEABGFAEGDGDFFBDHDGBGBFFFHEEEEEDFAFADABGGCGCBCBAFCFABCCHEHGDDEDEGFFAAEEEEAGCGAGHGFDCCBCHGACACEDHGHGAFBFBFAHEBEBEDGBHCCEAEADDDHDCBCFHAHCHBHBFBFBGGGBHECGFGECBCBCDHDBBFDCACACBFGFGEGCDEBFBF,False +962,27.0,19.0,27.0,18.0,20.0,32.0,29.0,28.0,GEGECAFAHHHHEAEBDBDCHHGHFEFHDBFAFBFDGDBCBCGHGHFCFCFCFDEGADHHCCADADAGEHEHGACCHGHBHEHCHCHFECGCFAFBFAFGFBCAEFCDHAGFBFHGEGAAHGFGEDEACDCFHDDCDCFCHCGCEDGHBDAAFAGBFBFHEGAFACADEFEBEGGGCGCBBFBFGAGAGAFABAGFBEHF,False +963,18.0,20.0,27.0,19.0,14.0,17.0,15.0,25.0,FFACCGCGCDDHCHCDGGGEHFBCBHFCAAAAHAGFGDGAGDGHFBDEDHCBCACACGCGAFEBBCECEAEHEHBBCHHHHAACDCDBDFCFBFBHCHBHDGCEEEHEDGBBBFEFHFHDCDBDADAHFBCBABDCEAHHDACFCGHBHFHDCFE,False +964,12.0,10.0,8.0,9.0,12.0,10.0,10.0,9.0,FGFAEAEAGADFEECEHBBBAHAEBECECAGGHBAAGEHFHDHAEFDFECDCBFBFBABDDFDGGFGCCCEHAHBHGDGD,False +965,17.0,22.0,24.0,31.0,26.0,22.0,22.0,27.0,CGCEHFCFCEBDBDBEHEHGHGHFABABHEHFBEBGHDHDFCBDBEBGGCHCFDFHEHDHDGDFFBCAHAHGEEFHBHBEBADFFAFAHDHGAGAHEDDHDEBEFEBEFHFHACADDDFDEEEECCCDAGADBGAGFEHBGGHDCCCDEDGHCECDDABFBEBCGEGCGCFCDCAAEDCBGHGDFDGDCDF,False +966,27.0,18.0,26.0,14.0,26.0,27.0,37.0,24.0,AACDCHCFGHAHAGAGACFHEHABFHFAGHBCBDBFBFBABFHHHFHFCEDEFACHCECFGFEFECGDGHGCGFGEHECDCBCBGBECEDFAEECAGGFAFBHEFDGBGEGHFEEGEHCGEGDGDGDFCCCCHBAEACHGHGAGHGAGEHEGEGBCAGGGFABHDADADAGAFHBEDCFAEECFGFGFGCGABEFGABA,False +967,19.0,30.0,23.0,20.0,26.0,19.0,25.0,21.0,BBABCBGGAGFDFGHDHEGBGCGBBAFDCBCEFHDCDFBCBGEFBHBEEEEEBADAHAHBGGGEDBFBHCCCECBGHDHDFGBDCDFBEHECGBGBGFCFAHEHDGEGEFDFDECCCHCHEGEGHGBCEAGABEBABABABADADABAEADCCEFBABFECDFHFHCHFEFCGGEHEHGDADH,False +968,22.0,15.0,29.0,26.0,37.0,20.0,22.0,24.0,AEGBABEFGGEGDHDHAHEFECEFACEEACHBECFBABCDCACAHGHDEEFECECDAAAEHGHGHDHDFGFHCADFDBDEDEAEDEDEDEDGGECEABBGFADADEHGHFECBCAEAEGECECAGDBEGAACCCCCCBHEGECDCDFHFHFHFHFCGEGHBDFEBBBGECHDEFEHHGDADCGHGDDCEFHFCFC,False +969,16.0,6.0,14.0,15.0,9.0,8.0,13.0,13.0,HHHHFEFDDCAHGGEGDGDCBBHCCDADGGHAAADADFDFDGDGDGABEBAFABECDHAAFAFEFGDGCHEHCDCGCEEHHHAEACCCCBCGAA,False +970,21.0,25.0,9.0,17.0,8.0,13.0,18.0,16.0,GBGHGACACAFHFBCADGGGFGFGAGAGBBDBGCHHEHEBFDEABGDGDGBHBCDFFFFHFHAHBDACAHDHCCGAEADBHBDFABABABEBEAECGGBHBHDFBBBBAFDDAGBHHABDDADADBE,False +971,9.0,10.0,11.0,9.0,15.0,9.0,14.0,12.0,EAEDFCFBFBAGHGHGDGBHBGFHEHCFAFAGHECGCHCADAHCEGDGCGBBBBDBDEGFGCCFHEEEHEDEAEDBCGHGCADHEFEAE,False +972,18.0,16.0,12.0,13.0,15.0,19.0,12.0,21.0,BEHFBBABAHGEEAEAFAFCDEHFHAHCGCFBEAAFGCABHHFHFHCHBGADCDHDHCHCEEAGBFDFGADFFFFBFBGDGAGAEADHDHDAEEEBCBCBHBDEEHGFGFBFBDEHCHGHAHFCAD,False +973,27.0,25.0,26.0,28.0,24.0,17.0,20.0,27.0,HCHEFEACGCFDFGCBCHADFCFBADCGHBHCDDDCBAAHAEEDADGDGHGHGHGDAAEBEHAHGDADADEBEHHCEBADAHHHHCHCAAAHBFBDCGBFCHEEFBFBFHAEADDBFBFBDGDEHEHBHGCGAHACECAFBFBEEEBECEFDCCABDBDEDEGAGADEDEDCFBBACHGGFGBGCGDADCHCBC,False +974,2.0,9.0,5.0,14.0,10.0,16.0,13.0,8.0,HBEGFBDBDHEEFHFEGDBFBFBGHFAFDFGFCFDBDBDHDHBGGCFFEGEGECADGFECEHFGDCDHDEDGFGFGD,True +975,7.0,10.0,11.0,8.0,6.0,8.0,11.0,11.0,CECFCDCHGGGGHGAFCECEAECDCGHHBADHDHDBDBFBFDAHGBBBBBBGCFFFAAEHDFCHGAGHCHGE,False +976,22.0,16.0,20.0,24.0,18.0,27.0,21.0,14.0,GDBDHEGEBFHFHDDCFCDAAGEFBFEDBAHGBGBGDFEBBADGHGFABAFAFDCDCBCAHADDDCAHECCDAAFAFGHCCECFGECECEFDHCHAHGBGBGDECECECEAEAEBFBFGHGHAADDFDBDGAFCFBHACAEEFGFAFDFDFGFGDCDGGFFF,False +977,16.0,17.0,23.0,22.0,27.0,15.0,19.0,22.0,EEGGFDFHCHEEAEDEHEHGCEFGBEBEBHBDDCBAHAHDGDAEGEGDHFECBDDDHDCGCFAAAAAFCEHBBEECEFDFDBDBCCCCEFEGAFFCFCFCEBEAHAHAHAGGHGHCHCBGEDBDGEEHCDGHBCBDAHFHBHFGGDHDEDAGECECBCDCG,False +978,5.0,8.0,11.0,18.0,14.0,13.0,11.0,18.0,HFHDBAGHGEFEHCGGEGDAAFHFEFEFDHDGCECHHEHEDEDHGHDFBFCDHHHAHEHBCBCBCDCDGDECEDGDEBFGDCDEBGHFBFDCDFHFDA,False +979,22.0,10.0,19.0,14.0,19.0,26.0,19.0,18.0,HBGDGHGCGBGEFEAEFBDEHEAAHGGGGHDHDHFGEABAFAHEHCACFFDFDFAFECGCDCDCDCFCHCFCHAHFDCBGAGDEHBGEAFAHAHEFAGHEAGACEEEFFFFEFHFBFCFBACGCAFAFCBEFEGEFCGBDDDCAAAH,False +980,9.0,10.0,16.0,13.0,13.0,13.0,17.0,6.0,CDCEBDGFGFACEBDHFCEHACADBDBHBCBGACCECEFEFGFGACHCACDEEGGGEGEGDGCFFFGFDBDFGGAGAHACDDDDGEGFCFCEHBBEB,False +981,19.0,23.0,15.0,12.0,16.0,18.0,17.0,17.0,ECEDHFHFHFAGAHBHDAEFGFBEHGBGBCBHBCEDGDCBHEAGADEGHFHDBBABEBAGAGCCDADHDCGBBBEGAGAGEBBBGFGFCCBFBFEGHAEGHFCFCFCACEDHDAAAAAHDBFFHFEFCBCBEBEFHA,False +982,21.0,16.0,13.0,14.0,20.0,12.0,19.0,12.0,EBEBGBGDGEGECHCHFAAEHBCAEBHBECECACGCDCDCDBABAFABGHGHAAEAHABDEDEFHFGBCDAEAGFGECDHGFGDDDEHAGGGEGBCFDFAFBEGECEHAFDFGABADAGAEBHFAEB,False +983,22.0,16.0,20.0,28.0,16.0,18.0,28.0,14.0,CGCGBDCDCGHACGFDFDGDBDCFEFEFADAECBDDDEAEAEAHAHABGDFAAGFGFGCAAGEDEGFDFDCGBGAGBGHHHGABCBDBDFDFCFDFGCAHAGACABAFEFAGEEDEHBCCHEGBBBDBDHGEDCHCEFAHHGCDHGGFGDGDGDBEGACDCD,False +984,26.0,22.0,19.0,22.0,24.0,27.0,32.0,24.0,ADHHEFAFADABADAFABCGCGAGFGFEDADABEFHFHGHDFGEGADCCFHHHGHGEFCFCEBDGEFEFEGAFBFBFAHGBEBEAGDFAHABAEGHGCECEHBHBDCFFHBAAGAEAGBCCDCDHDHDBDBGBEDDDCBBFBGEDFDHGEGEGEAFAGGBGBHEGBGFGDECHFAFEHHFCGCGEGCCHCHAAFDG,False +985,7.0,9.0,7.0,9.0,13.0,11.0,7.0,5.0,FCBCHEDFAFHEGBGFAEAEAEAFGDGDBDBABAFGEGDCHCHEEBFCEEHEBEDEFFDFGBDBCCFD,False +986,8.0,13.0,17.0,13.0,13.0,11.0,14.0,10.0,HGEDFDFDFDHDHDHDBFEFAGAEBEDGDHHFBBEEABBBFBHGHCCBCEEGECFBACDCDAAGCFCGBGFFEAGDGHCCDGEGCGCGCHCECBCACEB,False +987,20.0,12.0,18.0,25.0,18.0,18.0,21.0,30.0,AAADFHFAADFECBCECEHEHADCDGDGDCFHFHGCGCGFGFCFHDCAHEEGDGCECHCHEBFBHGHGEFHBHFGDADEDHDAFADEHBBBEGEFHADFDBCGDHHGHGHGDGDHDGDFCFEGGFGCAAEAEBHAHADBHEAADHDCECHDADHCHBHFHAB,False +988,20.0,13.0,12.0,16.0,10.0,14.0,25.0,12.0,BBBCHGHGAGFGHGDCACHCHCAAAAAAEHBDBAFDGDGDFCGGEBAFDEDEHEDGDEDADABCBFDGAGAGHGAEDBGGGGDGBFBHAAGBGHDFEFGAEECCGFFBFGFGHCHAFFCACD,False +989,12.0,14.0,12.0,10.0,10.0,5.0,11.0,8.0,AEFEBABAHACGFBABGBGDEDGDEBBCBCHCECBCACDCGHGHGEACFCBBBEFGDDDCDBDADGEHAACHEGAGFBEHAH,False +990,22.0,22.0,18.0,21.0,13.0,23.0,11.0,18.0,AHAHEFFDDCDFGHDFDECHDHABEBCBCEAFBGGGGFCHCBCHHBEDFAFABCHCBCBCBABDDGHHDBFGEEDADFECGBAECEADADADAFFDFBFBFBFAHDFDBHBDEAEFHFGAHAHAHACCBBABGCGCFHFAFDFDEBCA,False +991,10.0,6.0,7.0,9.0,6.0,4.0,5.0,5.0,FDCBCGFHFHBBBABGDFDAGACACEEECAHDDGDEAAADADAECECHDBGH,False +992,9.0,13.0,4.0,15.0,7.0,15.0,17.0,13.0,DEAHFHGHBEGEBBGFFFAFDFDHDGDGHGHFHFDDDCEGBACGDBDGDEHEHGHGBGBGHFBABABFFFAGADHDGGGHFACBFEDDBCAFB,False +993,1.0,1.0,4.0,3.0,4.0,6.0,1.0,3.0,EFEFEFAFCEGDFHHHDFCBCDC,True +994,16.0,14.0,21.0,15.0,11.0,19.0,16.0,24.0,AHACCCDCAAFBFEFBDBAAGAHHCHDHEHAHEHEBGAGAFHFCGCEFEFEDACHCHCGGGFDFCHCDDDHDHAECHGBGBEHCFBDBGGFHFGBAFHFCDADCFCBCBCEHAHFHBCEGGGFAHBHDCDFHFGDB,False +995,7.0,6.0,13.0,6.0,12.0,13.0,4.0,9.0,CEAFHCHFHECCHEACFCFGGAGFCHCHFAFEDHHCECFBDBDGECHDFEEEEEEBABACFCFDFDFBAB,True +996,4.0,9.0,13.0,8.0,5.0,3.0,3.0,5.0,AGAEADDCACBCBCDCDEHECCFHEDBCBCDDDFEBHBHCCCBBFHGCGB,True +997,3.0,1.0,1.0,6.0,4.0,5.0,7.0,3.0,DDDFHEHCGFGFGFGEDAGAEHFDEDBGAG,True +998,18.0,17.0,15.0,15.0,11.0,15.0,12.0,20.0,EBCFCHHAACHCHCHGBCBCBCHDADAFAFEFDFDGHGHCBCFFHCACDFAFAHAEAEAEFEBCHAFBHBFGAEDBDHDHFBCDEAGABBHGADDBDBDHHHEBAGCEEHFHBGGDGFGAGDB,False +999,6.0,13.0,8.0,13.0,6.0,19.0,12.0,12.0,GDGCGCHCAFGFEFBFDEDHFBFBDBGFDADBFBACGBGDGEFBHHHHBDAFGFGBGHCFFECEFEFBAHFDFBFDAHCHDHCHDFDGB,False diff --git a/tests/results/nb_gm_002_2back_240trials.csv b/tests/results/nb_gm_002_2back_240trials.csv new file mode 100644 index 0000000..1c50201 --- /dev/null +++ b/tests/results/nb_gm_002_2back_240trials.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,ralph_skewed +0,30.0,39.0,31.0,30.0,32.0,24.0,27.0,27.0,False +1,33.0,23.0,27.0,32.0,37.0,34.0,25.0,29.0,False +2,31.0,20.0,37.0,28.0,31.0,32.0,26.0,35.0,False +3,27.0,32.0,39.0,24.0,25.0,34.0,35.0,24.0,False +4,34.0,24.0,38.0,28.0,31.0,29.0,28.0,28.0,False +5,29.0,24.0,36.0,31.0,32.0,32.0,31.0,25.0,False +6,25.0,38.0,28.0,30.0,33.0,30.0,26.0,30.0,False +7,27.0,30.0,30.0,29.0,32.0,26.0,33.0,33.0,False +8,24.0,36.0,32.0,23.0,30.0,29.0,35.0,31.0,False +9,35.0,34.0,30.0,29.0,35.0,26.0,23.0,28.0,False +10,30.0,25.0,33.0,31.0,27.0,37.0,30.0,27.0,False +11,28.0,28.0,29.0,26.0,28.0,27.0,34.0,40.0,False +12,35.0,27.0,30.0,29.0,26.0,30.0,36.0,27.0,False +13,38.0,27.0,31.0,27.0,34.0,23.0,27.0,33.0,False +14,29.0,30.0,28.0,35.0,19.0,30.0,37.0,32.0,False 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+19,10.0,14.0,15.0,8.0,25.0,14.0,11.0,20.0,EEEEBEEFHEHEEFEEGHEAFFAFHACGDCDDCFDCBDCBFFBCEAHEAHGCGGHGCHEEAEAHEAHEHHCCFGHABHGFGCHGCFDFHEHBBBDFBFBCEAEBHCDGCEEEHBBHB,False +20,16.0,9.0,19.0,17.0,10.0,22.0,10.0,24.0,HFGDDAFEAFEDCGHAADEHDBHAHDCGBAHBECEFFFFFEFEEDHEDCACEGHBGCFGAGGABDHFCHFCHCCDCFHHADFCFFCFFCBFCDHHHHDFFGHHDACDAFDACDCBHCHHAGHABHAB,False +21,6.0,10.0,3.0,4.0,7.0,3.0,3.0,4.0,EABBAEFHEFABAACHDCDDEFBEGHEGBDABHBBCBGEB,True +22,6.0,11.0,12.0,6.0,9.0,6.0,9.0,10.0,AEDBCDECBCHBCBBGFBGFHGEHACHAGAEFBDAECHCFHFDCCECGBCGECGAHGBHBHEBHDFGDE,False +23,11.0,8.0,12.0,13.0,7.0,5.0,13.0,9.0,EAAGACDACDHEEGGGGGBEGEABEAHGCHCCAFCFFGDHGDGCBGBDDEAFAADCDDCDDHBCGBCAFCBDDHHBHH,False +24,36.0,26.0,18.0,26.0,33.0,19.0,21.0,15.0,GBCHFHAAHAFFGBBEFBCFAEFDFGEGEEBECBEBBABBAEBEEAEEABGDBADBACFFBEFCECGACFADABCFDCDBCBBHDHHACGGEHDEGDEGAHAAFAAEDCCHHDDGDDBDGBDBDDCDAGAAFHEDHGDACDACDBGEEACGAEEBEHAFHBGAAAAAAAEEFBEDCDAEEEFGEGGHGFEAFED,False +25,11.0,17.0,16.0,9.0,15.0,15.0,6.0,9.0,CEEFABDBGDBFDFFDGADECBFCBCCACFABEABFABEGBEHBAHEAHEAECCFFCHDCBBBFGBAGCDFHHFBDFDCCHHEHAEBEGCCBFEECEF,False +26,8.0,5.0,15.0,9.0,10.0,7.0,11.0,5.0,ECAGCHDBBDCCDCGHBBEEFDHFEEEHBHGADADGFDEFGAFGAFCCCCCACCDCDGGECGECGEAGFA,False +27,9.0,11.0,8.0,5.0,8.0,4.0,2.0,4.0,FCAFDBEDBABAABAEEAEHDBHCEHCDBCFBABEEGECGBDABFCCAHCB,True +28,6.0,8.0,11.0,7.0,10.0,5.0,9.0,9.0,CFBCBCCBACBEHBEGCADHDGFEGFHGHDAFBAFBEDCDGCHGAACHCHBCEEEEDHEDGEGGH,False +29,24.0,16.0,18.0,25.0,13.0,19.0,26.0,18.0,HEFHCDEGDHFBACGGDEHDGHDGFDEAHFDHGBHEBGEGADFFGCCGDHFBFABDACDABAGFGDAGDAGCAFFAGHHCDHCHACEDDAFDCCDCAECAEDGEDGAFGFCGFAGBBGFBDBBAABAAGADGAFCHBEEGHBGCBFCGFAHHCHDBDDE,False +30,6.0,5.0,2.0,9.0,2.0,4.0,3.0,8.0,DADBAFBDFHDHHBAHEADGFBHFGHEAHDHBDGDCADC,True +31,19.0,18.0,16.0,13.0,19.0,13.0,14.0,15.0,FCHGCAEHAEBDEBABAABHAFEBDCBDCBHCGEAGEFBAFCCECCBCFHEHGEGAEDAECBECEAFEBDHBDEAGFGHDGCDGADFAHGCFCBFDEHEGCEABFADHAFHGBHABHBHDAEBGDFG,False +32,7.0,12.0,12.0,10.0,7.0,5.0,5.0,9.0,EBDGBGBBDCBACGHBDAAHEBGCBFHBFGAFEHFCCCHDCHDCHDAHDCDDEBDEAFECBAHBECC,False +33,1.0,4.0,8.0,1.0,4.0,4.0,5.0,3.0,GAECEGFBHFGHBGCBFCECCECCBCHDGF,True +34,5.0,4.0,6.0,9.0,13.0,13.0,5.0,7.0,CHHEFFDFFDFFDFDGGDFGDHCEAEAHEAFEBFCFEEFEECAECHCHFDEBDBGEGABDEH,True +35,3.0,2.0,3.0,3.0,5.0,4.0,0.0,6.0,CBDEEHHEAHCAEBDFADFHFCHFEH,True +36,13.0,2.0,13.0,8.0,7.0,6.0,16.0,9.0,DEGDECDHGAHGEDGEGACAFCADGACGACHFDACHCCHCEECGHDHBEGGGGCADCAFAGFGGBAGCAHFHFA,True +37,18.0,19.0,17.0,17.0,13.0,17.0,15.0,23.0,HBCABCGHCEEADEDCEDGAGFFFHDFADHHBHHGCHFHHAGHEHEBBBDEFECFEBHCDAADFGDFHDCDCCDCCFACAACHGGBGGBFBCFBFFCFGEDABDBBDAAGAABACBEGBAHAHHFGEDGHDHHEBHBHF,False +38,4.0,6.0,5.0,9.0,6.0,4.0,4.0,6.0,AGDAGHABHCEEFBEFDEHDBHDECDFCDBHDEGBBGCCADFDH,False +39,3.0,5.0,6.0,8.0,8.0,2.0,8.0,6.0,DCEDEEGEEGAAFEHFGHDGDBHDBGBBGECECDGHBGCDDCHCAH,False +40,0.0,0.0,1.0,3.0,1.0,3.0,5.0,1.0,GDGGDCEHFGFDGF,True +41,20.0,19.0,22.0,21.0,30.0,22.0,10.0,26.0,BADBABGCFGFDDDADEFHAAHAAHEAHBBHECFGFDEHDCDBBBHGEDEECCDCCDGCHHBGHCHACFDCFCFEDFEDAHHHBHAECABDABAAEHFEADCFEBFAGFGEABECFEFFECEEFEHFEHEEHDHDCHBBHBDHCEHCDHBDCFAEFAGHEGECBCFEEFE,False +42,3.0,7.0,4.0,4.0,5.0,2.0,5.0,3.0,EBBEAEEHDCHDCGDGGBACBEHBDGBAFBFCG,False +43,21.0,15.0,21.0,27.0,18.0,33.0,14.0,23.0,DDDDDDBCGFEFFABFDHDAGCEFHHACHGBHGBEFEHFEHFCFFCHDGHDFHDAGFECCCAAEAAGHGDFCHFCHBBBFABDEFDFFBBDBAAFDAFAGHACHACEFFEFDHABCAFGDFEDCGACFADFDDFBHFAFFBEHBEHFCHEADEGHEGCDGHDHDEECCFCCD,False +44,27.0,34.0,20.0,19.0,15.0,29.0,27.0,26.0,FGCFGADGADGDDBDBAFGAFDHHHAFBAEEAGGBDBFCEFAHFAHFAECDCBBCGBHAFHABHDCHAHHGBCGECFDCEHCFBCHBGHCABFBCFBEHBECBAHBGDECHFDFBDEAFBBGECGEBBHDBHDBEABEBFCDFHHFGHFAFFGCACFGDGGHGAABCDBHBGGBGGFHGHGGBEADABFABAAFAFF,False +45,15.0,12.0,15.0,7.0,7.0,15.0,11.0,5.0,CAFCDGCFACFCCFACGBBGCAEAEGAHFADBCHACHFCFBEFGEGBDGBDGBEGEHAEFGBFCDFBFBHACAFCAFGABDAFACDB,False +46,12.0,10.0,7.0,5.0,4.0,11.0,11.0,13.0,ECFFHGFGGFCGACGFGGAHFABBHDEDCHABFBHGAHGAHCAHDABDFHDFGCHGBEABAHEHBFHBFCBAA,False +47,15.0,6.0,13.0,11.0,17.0,21.0,13.0,9.0,EDCEFAEFAFFAGHCFCEEAFGFFHFDECECCEGCDGHDGHDGHACFFCFFCDFEHEEFEEGHEDAFBGEAAHAAGCABAEFAFDABGFCFHCDEDBABFGBGGD,False +48,11.0,17.0,17.0,9.0,17.0,17.0,13.0,15.0,GAFGHHGCHBCACCFBCFHHECHBHAFHEEGBAFCAGHGEFGEDGFCBBEBGABCFDCFDCFDBEEEGAAHDAEDFECBGCBHDBFEGHHBFGBFEBFCBCCHEFAEDAEDCEFHB,False +49,13.0,16.0,15.0,12.0,16.0,9.0,12.0,15.0,BGCBAEBCDBEDBECBDCBABDCDFCDBCEGDABDFFEHCEDGECHACHEBDECDGHFFHFHEAHAHHEFFBAGAGHCHCCHGCEEAAAAGEEGDEGBFGBAGBHHBH,False +50,13.0,6.0,16.0,14.0,12.0,13.0,9.0,12.0,DAEAAGAAGCHCCHDFHEFCCBEGFEGFHAHEAGBGCBFCBFCDACDAFDCHECEBFBAFCFFDEHAGHDEFDGCDECEHCHDGADEHHFADCDD,False +51,22.0,27.0,26.0,19.0,24.0,22.0,28.0,20.0,FDCGDAACFACHGCDGEBFCBDCBGBEGBEGAGGFGGCHGDHGDCAACHADHCFHAAEEBBCBCCBAEDAGBFGAFGEGGDGHCEEEDEHCBBCDECEBGEFCCHCFBCFBHFEABEBDEDHABHDBFFFCEFCEDHFFHBFABHAGGECAEADBGGEGAABHAGHAGEFGBFBFHHDHBEGBFCCDD,False 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+79,23.0,23.0,29.0,21.0,13.0,23.0,22.0,17.0,CDHBACEAHEFDEGHAGAAGFAHFADFCBBBEFBCDGFBCDBDHGGGGCGFBDBBCFBFDEGEEHEGGBGEHFCCFCBDCEDAEABFDHHBFBBCAGDDCHDCHDAHBACAGCAGCADDBDFHAFCAFCGHDEBGHBCHGCHFBEGBFACFCCACAADACFACFCCFGFDG,False +80,12.0,12.0,23.0,9.0,27.0,13.0,18.0,19.0,EGFECEECHEBEEHHFBDCGCAACFBCGEHEEGCEACEGDEADAGBAGBCDBFBHFHACHCDHCDHCECCEGFHGFBABCGDCBDCEACHBCGGAEEAECFEHHAFFEEFHFCEFCHGGGGDHBEHGGHEEHE,False +81,25.0,15.0,14.0,17.0,20.0,16.0,15.0,15.0,DGDFFBFFCAFHADGAEEAFDABDEGGEBGDGEDEBAHAAEGABAHCACEACAHBAGGECFCDDEDBEFHEBGAFCAFCAHDEHDAFAGFCDBCHCCHCEDBGFGHBADBHGBEAAHAAHAEFECFEDFEDHEBHGB,False +82,23.0,16.0,15.0,28.0,9.0,16.0,15.0,26.0,FAHGHHFHGDHGDHDHCCHFBHEDGDGADGBDFDHFBBEDBADEDDBDHFDACDBFGBFAHCDDDGDBGBBGAAADCHFCHCDGABFHDDHDAEDCEDCGDFEAAEACHHGHDGCFFCHABHAHHAFCFHAAHAACBABBHFEAGEAC,False +83,16.0,17.0,21.0,14.0,11.0,17.0,24.0,19.0,EGHCBBCBBHFAHAAGAFGHBCDFAGFBDABDADEEDBCDBCHBCBGEGFFGFGGCHGCGGHHADHDHCDHAFGACCEHDGHFFCDFEDAHDFFAFFHEGBDGCGCBECECHBGHGGHCGBCHBCEGFGGFCACAABAE,False +84,25.0,24.0,34.0,20.0,21.0,23.0,18.0,22.0,GCCGAFHHFBGFBCFBDFBGFCGDEGCAHEBCAFCBFHEFEDCGFCAFCHCHBCHEAHAFBAFDAHBHBDGAABAFBACACHHCFDAFDGBAHBEBBEDFCFECAEBGFHECCCCCCHHEEHAAFDGFDHBDGBEFBEDDHDDEBHECCECCEBAEBAGACGEDGADCBCCGGCDEAGCADCAFHHD,False +85,14.0,17.0,15.0,14.0,15.0,14.0,16.0,10.0,GGCGDDEBFFHGFBGFBHFHHEDAACAABGFFFCDBGBEHBEDBFDBCDCDGCDEFBCHBEGBEGBEFHGFBAEBCEFAAGGCHCCFCCBCHEHEAACADDEDDAGDAGEAEBAG,False +86,5.0,2.0,1.0,1.0,1.0,1.0,3.0,1.0,ADFAGGAHGBEABCA,True +87,28.0,33.0,23.0,19.0,20.0,25.0,30.0,22.0,FFGDBGHBGEGAADDHGEEDEHBBACDFCGFCGEHFBBFHBFBCCGCCFHDFCGHBECBAAFFDBBCBECGGFEGECCAGABBABHAEHBBHBHDEFDCHDBAFFDDFAAHAAHCDFCAHEAHGAHFAHAGHAGAAGEEDFGBEBECBGCBAFBGCCGAFAAFHAGGFGGBGGBDEEGEGBFGBFHBCHBDDBDDBECCA,False +88,27.0,30.0,28.0,20.0,23.0,12.0,23.0,29.0,EGBCBBCEBCHHGDBECBCDBEDGEHGAGACGEHGCDACFECFCBHBBFDAHCACBACBEFGGAGGADAAEBAHDFHDCDBAHCHHBHABGCBEEDHGHHGFHAHDAEDABDGCDECDBADBHHGHHGFGECBEABDHFDGAHEACFGCAGCABCHBFECHCBFCBFAEABDAGEHEEAECABDHBHHCEBG,False +89,14.0,15.0,7.0,17.0,10.0,11.0,15.0,9.0,CHBADFABGHBGFGGAGGADGDEBHADHGHGFDFDDCDBGAAGHAGFAEEBBEDBEBCEBFAFDAFDFGDEADEGDFACCCGBHBBHABHDEDCBDFE,False +90,5.0,3.0,3.0,1.0,8.0,0.0,6.0,3.0,CCACEGHEGDEGBBAHEHGBAGEAEEAEG,True +91,0.0,0.0,4.0,2.0,4.0,2.0,2.0,1.0,GDCFDCEECGEHFEC,True +92,14.0,4.0,7.0,10.0,8.0,6.0,12.0,5.0,DCDAEFAFCECEEAFEDFEGCCGACBDGHFAHBGEBGAGGAGGDGAEGHHGAADAFDADDCBAHDA,False +93,10.0,8.0,8.0,3.0,8.0,14.0,16.0,15.0,FAGFDGHDHHEHEEGGFFACFHEHACCACHFGHFGHCGCAGCGBCFFEGFGBHABHFDHGBGBHABHAFFAGFEHEEBBAGG,True +94,21.0,25.0,21.0,30.0,27.0,13.0,12.0,17.0,HHBEBCAACEABDGDGBDFBGFCAEHGDCADCHDCEDFEDCEDGDCEDAEGEHAADBBDAADHCDHDFHBEEBEEBCEGAECDEBBCGAHEBBFFHEBHEHDAHDAECFFDFEDFBDABDCCACEDEBDHDDAGFAEABECBHGFDDFEDCCBHCBHGBEGBACBA,False +95,4.0,6.0,6.0,8.0,7.0,6.0,6.0,9.0,EDGEBHEFHACBBCFEGHCHDAHDEHDBHDBDDEHFCGECGFGBFACFAHGD,False +96,8.0,5.0,5.0,6.0,5.0,8.0,12.0,12.0,AFACCAGAGGFBEHEGHECFDFFDGFHGAHGHHFDGAGCAGEFGHBBHEBHDDHDHHGCBA,False +97,20.0,25.0,21.0,20.0,27.0,26.0,25.0,26.0,BFCFGDFBECHDCEBGEFGBABHGDDGAFBEBCEFEEFGDAHFBHEHHCHDDHGEFDFFBGBBAEGCCFDDABEBBEBFHBHHBCCECEDCAFCGFGHFCBGHBEAFCBFDEEAEEAFECEBBGGAGHBDHFHHFHHFHHFHHEEHGCDABGABGACGAFGAGGDDEDDCADCFGAFGDCAHEAHEAEGC,False +98,4.0,3.0,1.0,1.0,6.0,1.0,5.0,3.0,BBAHAEDECGEAGBAGEEGHEGHF,True +99,21.0,17.0,15.0,21.0,17.0,23.0,10.0,21.0,AHDDHEDGFFGCFHDHAGHGHHDDFADFABHDBCCACAAHGDDFDDFGBHEBHBHEEHEFCFFBBDDBAABCEEHDACDHCEEAAEBHBFABFABCABFFFFDFFDFEEFCEHCEBDEBFCAGAGGDGCHBCHAAHEFFECAADH,False +100,21.0,17.0,13.0,22.0,21.0,22.0,21.0,31.0,GCAADDGBDEBDABDGDGGEADEDDFHHHEHDGHFGHFDHGAFAHEHDCHDHFEBGEACDACGABGABGFGGDGBHEEHEFFGHFABDHEDAECBFHAGHAHBAEAAEAFEHFEBGGBCFDFEEAHCHHCFDAFDCFDBFHBAHCHHFFGEHDECCGCBHFHHFBHBE,False +101,3.0,4.0,2.0,2.0,2.0,1.0,2.0,2.0,BCFBEABEABHADGCHGD,False +102,3.0,5.0,4.0,4.0,2.0,1.0,3.0,10.0,BGHBGHCCHCDHEHHABDFHDBHEGCDAHBAH,True +103,22.0,16.0,17.0,17.0,11.0,10.0,13.0,12.0,DECDFCDFEDCCBCCBCADGAGFAEAAHHCGECAAFHAHBAGEFDEFHHGGFBFCBACBABDACDAHDAGDGBDBADHFDBCEHGEHGDHABGBCEDEEHBAABADCGGCFCABDABA,False +104,12.0,15.0,10.0,16.0,25.0,15.0,20.0,17.0,GBFDCFDGDDBHDAADEBGBDEBEEFGHFGHFGHCGHEGDEADHBDHGGBGHEDCFHAAHACHGGEGGEFEBFGADCCEBHEGFEHDEHEEFAGDCHFEEAEEBCEGEDBEDBECBFFBHHCAFAEGAFB,False +105,7.0,10.0,8.0,8.0,6.0,8.0,6.0,10.0,HBEHAGHFGHBGDBAAGCDEHFEBEHBEBCABAACDFHBCHDFGDFGDFHCHCCACBFDBEDF,False +106,17.0,20.0,9.0,15.0,13.0,17.0,14.0,15.0,FBEAGDAGAABAHBGEFFBFFEDHEGHEGHEFHFDBBCBBDBCHCAHGAHCHBEGFDGFAEBAEGADCAHBDFBDFDFBABHEFGBCDAFDBCAGCFBHFBAFAEDHEDCEDHBDGGHGA,False +107,5.0,5.0,1.0,5.0,1.0,5.0,5.0,2.0,FABAAGDGFDFHBFEBAGBAGBFDDHGDC,True +108,17.0,16.0,20.0,15.0,16.0,19.0,21.0,30.0,CBHCHHDDDGADGAFCEHEBHEFEAAEBHFHCBGFAEDHEFEFFCFFAHEHHAHBGCDCHFGHBGFCGFBEABFBHHGHHGCHEAHEADABGHBHHBDHGDHGAGGBGGEFCFFCDBGDFDAECEECGCAGCGDCFDFHHAHHDHBBCCACGAC,False +109,19.0,26.0,19.0,10.0,27.0,23.0,8.0,14.0,EBCAAAGFADFADFEFBBBCBEABEABEAEEHEEHEECEBGACCAFCBHCDCCECFBCAGGAFEAFEFBHHBDFAHEHFEGFHCFBBHCCABCHFFBFFBDGCEGEBAEGCFFEEDHFFBFBADBDBBDBBEHEEFCHACBAHDEE,False +110,19.0,10.0,10.0,17.0,15.0,14.0,13.0,9.0,EACEADEDDGDAEBCFACEAEBFHFFGDFEDBBGBHGCADCFBBBHCAHEAHFAHAAHCDGCDGAEGAEGEDDFGEAEBAGFCGDGDDABDFCDFGFFAAEDFEHAH,False +111,6.0,10.0,13.0,9.0,4.0,7.0,3.0,10.0,CCCAFBAFBEHDFBCCBCHBCBCGHDAHDAGDCDFCHCEHDAFDFHDHHDEEBFBAGBCHBC,True +112,14.0,15.0,18.0,9.0,20.0,11.0,10.0,7.0,DEFDEFBEACFGEFCACCBGGBHAAEBEHCEGGEDEEFEEDBECBABGADFADFADGCHCCHCHACEDHEGAFAEFBFBAEACCAEBBGBBGEBEBHCCDCCFC,False +113,18.0,25.0,13.0,24.0,29.0,22.0,19.0,30.0,HCAHEABDACHBBDDHADBEHEEHCABCFBHFBABBABDHBEHFGAFGFHCHGCAEFHEFHGHCGCEHDDFEBFEFFDDHDEEDGEFCBGBDGAHHCHDCFDEEDGCFHHFEEFGBGGEEHBFAGFDHBEGFEDCEDEBDEFHEAHEAHABBEDBGFBGEHGAHFADBADHADHEDBGGB,False +114,13.0,9.0,15.0,32.0,17.0,18.0,11.0,14.0,HDHDDAGGFDDFHBFBCAEDGEDCEACDDEEDFHFAGFDECDCCDFADECFECHDCHDGAGAHGHDFEDCEDCEHBHDAHDCFDBFHHGDBDAFCGFAHFDCCDAEDGEDEEFADFAGFBBDEBDEBDF,False +115,21.0,18.0,26.0,25.0,21.0,27.0,25.0,34.0,AACCECDFFBBDABHAGHGFHGHAFHBFHFEHCBHFDAGHAGEDBEACHDCAGCDCCDBEDBDDEGGEHGAHFAHDBFGHFGCDCCFCBFCBHCHHFFDFGEEEDHFHHFHDFEDFDCBHAGAAGHBEEDCFFCHEDAEBAGDEGDEDBFBGCBECHCGHCDAGGAHGHCGHCFHBFHCFHDADAEGEGHCGAFFEH,False +116,25.0,15.0,25.0,18.0,19.0,11.0,22.0,30.0,BGGBGDHGBAECHEFABDHBHHBHDADBEEGFGGDGCCGFCHHHAHAFHBFEEGEAHCGEAGDCCHCGDAGBAGBAEADBADHADFCGHEDHCABCHHEHDFHFAHEAHCHCAHBDHBGHFGEFCAGCHGAAACAACHHDHCCGECEDDFCDACDACBCCEEGEE,False +117,28.0,24.0,15.0,28.0,23.0,30.0,14.0,19.0,CHACHAGEBEFDCFAGFADDEDDBDGBDBFEBEDHHDGDECDEBFABFAFFABAAHHAHHDFHFBHDBEDADCBGHEDFFDEDDEBEBAGADDFFFBDFBFFBFFBHACFDBFDFAEBACBACGEGGCFAFEHEAHECHBDGGFCAECFEFHEHHAGACBDCBAHAAEAAEDECDAFGGFB,False +118,0.0,3.0,1.0,0.0,4.0,1.0,0.0,2.0,FHBBEEBEECH,True +119,15.0,14.0,10.0,15.0,7.0,12.0,18.0,9.0,BGDBGBFEBDCFAFFADCGGAGDABAAHHAHHACEBCDDCBDAGDGBBGDGDDACEFCFFCGFHGBEFCGACHAGAGHAGDABBEEFHGFBFDBEDGHDG,False +120,18.0,23.0,21.0,12.0,21.0,14.0,26.0,15.0,GBBHAAEBAEHEEFEGFGCAECABAGCADBEFAAGDABCAGGFGGCHGCHGAHEAHFFCEHCEBBFBBEHBCGECGACGDCGDHGCGGHGGDDGHACBBGDBDECDCFABECFEBFECEBGBBEDDEGFCDFEGBHGBHAHFACEBCHBF,False +121,18.0,17.0,15.0,11.0,14.0,12.0,17.0,17.0,AGGAFDDFCDBBHECHBCHADHCBACFACDDGFACEBCBBGBHAAHEAEEHGFGCFGBHEBAFHAHHADHBEGBHHCEFEEFGHFGFGCBDCADGBDHHEBEBBAADAAFCAGCGGEGGEC,False +122,19.0,12.0,14.0,16.0,13.0,13.0,22.0,12.0,DFAEFDEBHGFEEDAEDFGGCGGFGGFGGAGGAFFDEAGEAGDBBABDHHCHHBDHBDGCGGDHDAGCACCBFCBABHEFHCCHECBCGDDAHDCEEFACFBCAGDAGAAGAEFAGDBEHA,False +123,3.0,8.0,5.0,11.0,9.0,10.0,4.0,11.0,EBFFHHFADFCHFGHEGHFGFACDEDDEGHFAEDHBDEBDECDCDDFHBFEBHHBCEBHDB,True +124,4.0,5.0,6.0,11.0,9.0,6.0,5.0,8.0,ACEACEADEDEHDCFFCDCCEHHEHEBHGBDGHDFDFEGFEDBHDHDBBGFAGD,False +125,11.0,14.0,19.0,12.0,21.0,14.0,17.0,9.0,CCDCBDBEDHEGHAFEECDGCFGCEGCBGEFAEDACCHCDHGFEFFBBEABEAHHAFCCFBFFCFCBEGDACDGCAEBAEGGEDGEDCAGGEDHEBHBBACBHGFEGEGDEGEFCBF,False +126,7.0,15.0,16.0,15.0,17.0,19.0,21.0,17.0,CHHHDBCCEFEEBEGBHFEDGEBFFBGFGHHGHHGEHDHCDHCDFAFFDCABAFBHGBCGBFHBDHCEGAGGHHGDEAFECHDBFGBDBCDECGEFEEBECBDFFDECGGCGADGEDGFGCFGCFAF,False +127,1.0,2.0,2.0,2.0,3.0,3.0,7.0,2.0,BEGGGGACFHCFHEFDGGDEGB,True +128,24.0,27.0,28.0,25.0,25.0,12.0,31.0,20.0,GGGBGGBDBCDHGACGEHDCHDCBDCHHEHBGHADDADDEBGGHGDDEADFAHFAGGEGEEABEHDEHCEBAEBECBACBACGACGADFADBBBBFCCAEGHFBEBCAAHBCHFCEFCDFCDCCBAEGEGCAGCGCCGEHFEHGCCACAACBDDBHGBEBDAFGEFGBBGHHEDGDABCGFHDEGGEDEADB,False +129,8.0,19.0,18.0,15.0,11.0,19.0,15.0,9.0,BEEBFHGAACFBCEBFHFADFCDHCDBCGBGGEGBDAADFDCHECHECEGCFGCFGFBCFGCAGDFGFFHHBDDFCDFBBEDBFDGDBBFBHABCEBCDAEGCBFHBFCGECGD,False +130,19.0,16.0,11.0,13.0,12.0,17.0,19.0,19.0,AGFEGFGGEGDAFDBFDBCGACBHEHHAHHDFADABHAGHBFHDFCDCADEEFEGBDGBEGADBAHFGBDGBAEFAGFBCAECHGBGFBGBBFBHAHHAHDEGEFAHADCACCHCEHGAHFHGFCF,False +131,4.0,4.0,2.0,0.0,2.0,2.0,3.0,2.0,FBECAGHAHCAGBAGBEFB,True +132,21.0,22.0,26.0,22.0,19.0,22.0,19.0,31.0,HHACHAGHDFHCACFECAECGDFFDFCAACEBEDHHAHDCGBCBBCAHCAFCDBGFGDCHBHECHCFACFGCHECBBCFBGHDGHEGHDGFBAADFGBGGFCGHCBHAGHFEEEDAEDAHHABFABHAHHGHBFDAFDGDDFEDGBDFEDHDDHCEHEAHECEECEADBGCBFFHCFBBBBH,False +133,16.0,18.0,20.0,18.0,16.0,13.0,27.0,16.0,DGGBCEDCEFHDGHFBDCHFHHBACBADAAHADEACBGHFGEDGCBCABGAGFCGDCGDGBEGBEGBECEEHGEHGHHDAAGGACBDGBGCBACDEBDBGCFHFEHCEGCEAEFCHFABFEGGCDHFDCDDCDBFGBFGAGHAG,False +134,19.0,21.0,15.0,10.0,12.0,12.0,10.0,11.0,DAGDAGAAHHFHABCBBCEBCFBCGDCGEEACACBACEAFGBDAAFEAFEHBBBFECDEADGFFACGECBBCBBGEBFEBDAACHADHFEFBCHBFGBHDBCGBHADHAH,False +135,13.0,9.0,13.0,6.0,13.0,9.0,17.0,10.0,ACEEHFBHFBGFCHABEADHHCGACGDHBCABEGBEDBGGCGHHAHCEDAEFAEGCEACEAGGFCGCDGBFGAFGAFBEGCEGAFGECHD,False +136,12.0,12.0,9.0,6.0,6.0,6.0,7.0,12.0,DGFDCFBCHHHHHHHBHBBABEAFGBEGCFDFGCCBDABAAEAAHACCAGHADEACGHGEBEFBCDBHAB,False +137,8.0,7.0,7.0,10.0,12.0,16.0,11.0,8.0,EEHEGHGAHFFEFEDBGDBEBBGGFGDCGFCFCGFDDFHDFHAFCFDGAAFFAEHAEDFEGFEDCEGAEFBHBCDBCHA,False +138,16.0,20.0,15.0,26.0,16.0,10.0,21.0,11.0,BCEFDBCDBAHBEFBCAHCAEBDCCDHGHHCHDDDEGBFDFGCACAEEDGADGEDBEGCEHCHBGHBEDDADDGBDGBCGBDHCFGCGGFGGAAEAADAEDGEDBEBADDADGCDGBAGBDGBHGFFBEDAEFBF,False +139,13.0,8.0,3.0,6.0,6.0,4.0,5.0,4.0,EDGABAADGAECAGAAGAACHFFHABGFBABBEDBEHBAHCABDFDEED,True +140,3.0,7.0,9.0,8.0,11.0,8.0,12.0,4.0,FGFCGCCEEDFEBFEBDACHADEBCEDFBDEHEFBEHCEDCGGBGFBEFCGGDGHDGCGGAG,False +141,7.0,6.0,3.0,11.0,10.0,4.0,8.0,7.0,EEAAECEEGHEHDFDCHCGHEAAEHBDFBDBGDBADBEHFEAFGGDHDDGBDGADG,False +142,25.0,23.0,17.0,19.0,29.0,25.0,18.0,29.0,EEBEEBHHHHBCHEFDGCDECDEDBEFHAFGBFBHFBHFCHFEDFBBFEAEGBCBAAAADAHEEFAEFDFACHHCHBEHBHHDGECFEFBEGHEGHAFHCDBCAGHEGHGDHGEGGFAAFAHEEHBFABDACHABDCDAFGFFGCFECFHBFEEDDGDBFCAHAEDDEACEAGDBGAAGAHCBHB,False +143,1.0,2.0,2.0,3.0,4.0,5.0,2.0,3.0,CFDCBDHGEEGAEDFEFFBHFH,True +144,9.0,4.0,7.0,5.0,3.0,7.0,3.0,7.0,EFAFABHACHECHGCBADBADAADGCFFAHGHDFHDCHFCBECAF,False +145,21.0,27.0,26.0,22.0,15.0,22.0,16.0,17.0,FCDFDDECEHCFGCEGDABBGHCGBBFABAEFEEFACHBGFEABEDBHCCFGAFEEFHAFECFHCEBCDBCBAHFAHFCFFCFFBFAGGAECDCCBBDDCDDCABBAGGAGBAGHCHECDACBAFHECGBGGBAGBHBACCADDDDCHHHFHHBDDBDDBDBADBF,False +146,23.0,23.0,27.0,18.0,23.0,27.0,25.0,28.0,DEGHEGFDBFGHDEACECDFDDFDBBBGCEAFHFFHFEBGEBDEBFBBFHFFEFCGFCGCHGAHBCFGAAECGEGDDGCHGAHAAHAADDADCAFBFFBHBHEGCAHCHHBEACCBBABBDBHCBDFAHAEBCEGEGCBHEHFAGCAFCACEFHEFADBCGGCGHAGHGEHEFHCAHCGHDGHCEHCEFCGFDF,False +147,19.0,22.0,21.0,22.0,15.0,18.0,18.0,18.0,ADDADEFBADAHFBBFBBCHGCGBCBHEDCCDHDDACGEGBEACEBCGCFABFHEAHFGDCDDCGFCGHEHHEHBFHDFBFFBAFAABAADACDFCEFHADGADCCECDBHDBCGBAEBAHDHHDHACFCGFGEFHEGGCGEFGBDGBGBBDE,False +148,23.0,18.0,18.0,17.0,20.0,20.0,23.0,19.0,GHBGCBDAFDAFHCBEFGACAECHHGEGFEGDEDDBCAAGFAGCGECAEFBEACEHGEHAEAFEAFBCGCCFCBBGHBAFBFCBFAEHBEHBEGAACFABGEDGHAGBCGCEBDGDDHEAHCADFFGHAHDGHDGHDGBDABHAEDDFHDFCFFHGFE,False +149,11.0,9.0,14.0,14.0,12.0,13.0,8.0,11.0,CCFCGFCDFHHHGGHEDDFHDFEEGCEAHAHCADFEBBBCBFCAHBAHEACDDCDACDADDBDDBEGBDFFCEHEFBEFEAGEGFCGFCAHA,False +150,20.0,17.0,22.0,21.0,18.0,23.0,27.0,26.0,FDDHHBGAEAABAAFAHBGFFHEHCEBEBBEDBGDCGHCGHCFFEGFEDFCDACDAEBFEDAEDHHHFGHGDHGAEFCFGBEDAADCCGFGGAAGCHCDDBDCGGFGGFGGFHGFBGBCGECHFHHACHABDFHDHCAEBBEBGCCFHEHGFHFEHFEHBCACCACGAGHDDDD,False +151,25.0,32.0,23.0,18.0,29.0,30.0,21.0,16.0,CHFAFBDBCEHGEHEEFEACEFCFHHFCAGAEGBCABCAECHDDFDFFEFFGHABFFEHBBDBGABGACGACEDCGDEBDEBCEBFDCHBADBFDAADEFBFHGAACAACHDEADHCBGCAFBFFBFFBEBBGBEEBHDBFDGDAGFEGCABEEBEHBGHBGFBGBAGFGCEGCACFDGAEBEEFCEFAFHBCE,False +152,2.0,5.0,8.0,6.0,3.0,7.0,7.0,3.0,ECBDCEGFFGHCGCGGFBDFDDADDHEBFCBCCBFCGFGAH,True +153,20.0,20.0,31.0,26.0,22.0,23.0,14.0,22.0,GBGFBFFBHCBHCBHGBEFCGFHHHHEHDCHCCDGCFFCDDHFDEDGEGCHHADHCEECFECHECDGCDGADCAGAAHEDHCFBEFEDCHFFAADEADHADCGBCFBCFEEEEBGBCCCCBCDBDHBAHDABCAGCBCFBEHDEBDCFDHFEFDAACAEDADAFGEFABFDCEDAFAB,False +154,14.0,22.0,13.0,6.0,19.0,16.0,15.0,9.0,EEBFEFCBFDAAGAHBCCBGCEEAEEAEEAEEAEGGFHBCHBCBCHBCFACFGDECBAGFFDBHBBHGGFAGBGCBEHGADBFBBGGAFCAFCEGBEGBEFBDFBHEHEFDAFB,False +155,13.0,9.0,8.0,9.0,16.0,11.0,16.0,26.0,HGHDBHECHGCDGAEGFEHDEGGHHFBHFGHBGBEFEAHEAHBFHFDHADHBCHEAHEAHDGHDHHEFFACDCEBFGGEGAEHEGHEGCCGFHGAAAHAFHAHDEBBC,False +156,21.0,23.0,28.0,17.0,32.0,20.0,26.0,33.0,AGBGFFGFGGCEFCBFGBECECGECBECAGHDHEDHCBHEEAEEBFGGHEEHAGFFGFHHCCHADABEGBHGCHGCFBHEHHEHHGFHFFHEFAEHADCEDCHAADBADHEDAFHEDDCCDCFEHBHGGHEFHEBHEBHGBCGCADAAHACBDFBGCBECBCCEHEADEGEEAFCDBHGBCGBCDFAGEAEHAHDCBBCG,False +157,3.0,5.0,10.0,12.0,6.0,7.0,9.0,8.0,CDDCFDCHDGGFGDBGDHFHHEGCCHDCADCAGBFHEGEEGCEDEFDBFDHAHGCBFCBD,False +158,27.0,19.0,22.0,22.0,21.0,22.0,30.0,32.0,AEAADDGDGHBHDGHBGHBHHBCHCAHCABEEBDBDHGFHGHHGBBAHAGFGBAGAGGAGHHCFFBHHGDHAACAGCAHDADGAFHCCHGHHCHGCFGEEDEDBECGAFEDFEDBEGBCACHFCDFGDCDCCBGCFGDFGHFAAEDHFBHFGFFEAEEHEDBECFEABGAFEEEAFDCFDAFDBCGHCGHAEHAG,False +159,6.0,10.0,10.0,5.0,6.0,6.0,5.0,10.0,HCEECDECAFABHBBFADFCGACGABHFEHCBBCBBHFHCDCEDCHGGHEGHFBHABD,False +160,18.0,20.0,20.0,17.0,21.0,19.0,20.0,20.0,FEDBECCGDCDBGDBGDGGDCDFCAHCEHAGAABACFCFFCAACHADAACEGEEGBFBHEHHBGHBACGFDFCHFCHEAEBBEDFFGCFGBEBBEHDDHABGEEEEFABHABHGEHGEHGEHBFDFDHGDHGBEGBECCFCAFHFGCCDAFAHDB,False +161,12.0,21.0,28.0,20.0,19.0,21.0,30.0,23.0,BEBCAAFGAFGBFGEEEFCCHCGHFGHGDDCCHBCGACGEHGHCEHCFCBHCBHDAHDHHDCHEABGHFGBGGCGHCGCEGFDGDDEFGEAHBGEADDCFDGBDGDCFECFCGFCHEGAFCDFCDGDFFEHFBHFCCBECHEBHCBFDBFBBGBDAEDGECGBHEBDABGGGAH,False +162,21.0,14.0,18.0,20.0,18.0,17.0,19.0,20.0,GHBEAFEGBGGHDEEDEABEBBEFECFCCABAAEAAEACBAFBHFHHAEDBCDECDAFBAFBAGEHEHGDAAHGAEDCCDHDDHGAHAFCCECAFCHHCHEGBCDCCBFFEFFGBFDDDDDGGCGDAFDGCGFHHDHHDHGFHGAGG,False +163,7.0,8.0,10.0,9.0,10.0,6.0,9.0,12.0,FBCCDDCAHADHEHHAGCGGHECHECHGBFABFADFGDHBDHDDCDHCEBFHGECEEAEFHECEBGBGGBA,False +164,2.0,1.0,4.0,3.0,2.0,6.0,3.0,7.0,CHCFEGFCGHHEABGAHDFHDFHCFHFD,True +165,27.0,21.0,24.0,26.0,31.0,11.0,22.0,21.0,CAADGACHHEAHDFHCAHCFBCFBEBHGCEFCHCGECDEABEACDDGHDAFCCDCADCAGBDGBEGBCDEHAHHAEFBEGDEFCEABBDBGAHAACAAEACBFBBFGEEHEBDEGDEGDCCDCABHEEEGCDGCDGHEGEEGEHDEGDHDAEFEGBDGADHFDGCDGBAAAAHHEEHDEBABB,False +166,7.0,16.0,7.0,13.0,4.0,10.0,9.0,15.0,BDDEDDGCAHEFHCFHCBHAGFDBDDBDDGFFBAHAHHFGBBDFBDHACHBCEBFEHHGHHBADBCFBHDGABGHBGFBGC,False +167,15.0,15.0,9.0,10.0,9.0,15.0,18.0,14.0,GGABCADCGHHGEHBDHCDHDEGGGFGGAGAABECBCFBEABEBEGAACBBFEAFBHFBHFBGFCAFGHFGHDGCBCEHFFGBFEDFBDAHHAHHGFDDAGDAFA,False +168,21.0,14.0,14.0,15.0,25.0,21.0,7.0,17.0,FDABDAHCHHFDACBGCBGCHFAACGEEBCBFABAEEAEEAFEADDHFAHFEHAHHCEHEFDGFEHFEGFDFHCCAEAAEADBHCFHEBBCFACFDEADFAECAEBBEDBEGFDAFEFDHFDHFEEBCEBGEHD,False +169,11.0,25.0,11.0,15.0,12.0,14.0,16.0,19.0,CDFBBCHGCEBDBACBDCGHFHHFHDFHBEGBEDBFDAFCAHBACFAGGAGEAGBAGBHBBDEBHGHHGHFEABDHFCBECBFDFEGHDFHBFHAEHECHBHBGDBGBCEBABDEGDGGDFDB,False +170,11.0,10.0,15.0,10.0,14.0,10.0,14.0,13.0,EEGCEHAGADCDEADGBDBHDFGDHCDFCDHBAEAHEHCGFCGFCEFDHGHHGHFGCAACHACHAEGEBDCFGCFBBFBBEEBGACGFHEECEBCGA,False +171,15.0,14.0,17.0,21.0,14.0,11.0,20.0,12.0,CBGBFHBCEACEAGAACBDBBDCDDCDDAGGAFGFGDHADEDDEFFAFFCBFCBFCFAHDDBGGGEADHHBHBBDEEGEEGCAGCDCCGCEBHHCGGCDBCHHEAHGAEGHEFADGDGEDGDDA,False +172,6.0,4.0,6.0,6.0,3.0,10.0,5.0,4.0,GBFGHFGDEDFCDAGDHCDACBECDECAHAFFAFBCBHAFFGFF,False +173,2.0,0.0,4.0,3.0,0.0,0.0,1.0,0.0,DDGDCCACCA,True +174,3.0,6.0,8.0,12.0,9.0,8.0,4.0,7.0,FGBDDHHDCFABFABCBCCHDEHEFAEFEBFEDDHDBCDECFHCFGEGGEDDCDDHE,False +175,4.0,4.0,3.0,0.0,0.0,0.0,2.0,1.0,GACGABHBBAABCC,True +176,4.0,2.0,4.0,1.0,2.0,1.0,1.0,1.0,HCDACAAEABCFBCEG,True +177,22.0,20.0,10.0,18.0,13.0,13.0,19.0,20.0,CBHCGHGEHEEADBHGAEGFEGFBAEBCFAFEGHCBABFADFDDCHBCHDHAGGADBAHFEEFHBBHBGDDDHDGHGFHAFAAEGBBDAADHGBEGBAGBADBAHCHHADHDGGDFGDFDCABCABCABEFHEGA,False +178,22.0,19.0,25.0,28.0,26.0,27.0,22.0,13.0,CCCCCCCDCAGHEHCGDGHCADEADBADHFDGGGBDACFHCFHDGBDGDAGDCDDBBCEBFBAABDCDDEDFEFEECDEBAFBDDBFEHEEAEFGEFGEAGBFFBFFBCFCFDGHEFCAFCAHEEGEEBEAHDGEFBFHDFEDCDHCDACGGBGCAGDAFAAFEAFHDFEGECBBGFAEFAG,False +179,3.0,7.0,11.0,8.0,19.0,13.0,15.0,4.0,BEEBAEFHEBGCBCEBFHFDECDCGHGFEGEEBECGFCGFDGDDGFAFFAEGCEFCEFDECEEGDEGCGGFGEBDHCEGF,True +180,23.0,18.0,16.0,19.0,17.0,9.0,16.0,16.0,DACDHCDECEHCBACDAFDAFABCEDHDGHBCFFABCDDFDDHCAHBAEDABHABDGDFCBECAEAAHGEFABFGBGBHABHCEAEGAEGEHGFHEAAEAHGCEGCHGAEGCBGCDGDEGHHADBAGBEDBDBB,False +181,7.0,4.0,3.0,4.0,1.0,4.0,0.0,2.0,CDDAFABHAECADFHCFABFABDAB,True +182,7.0,17.0,14.0,12.0,11.0,8.0,17.0,16.0,ECEECHEGDCFDCFDCEDBBGBGECGBHGFFGCBHEBHABAGBHFBHDGHBECBEHHGCGCCGCFGHABADDDHGDHEBHBCGGFFACHAEADBHDGHBGDB,False +183,18.0,19.0,14.0,22.0,20.0,25.0,20.0,18.0,FBAHCEHGHHGAEDEDDHDHGFACFDBFGCCBHGHHGBHGECBHFDEFBEBHECHFGDFHDEHAGGEGDBGAADFADAADGADGHFFEGCABDGFDBDECDFAFAEFCEFCADGFDFFBFFBHFCECGEBGEBHEADBBDFBCFDCFAAEGBEABE,False +184,9.0,17.0,14.0,14.0,12.0,19.0,15.0,10.0,DBDDHCBBBBGGFEBFEAFGCFDCADCDFEFGHFDHBDCECCFDCAEBEDHFDCBDGBACACGECFEHDBACBFFBFFGGDEGHHGCHFBHFBEFAEAABGFBGEGGFGH,False +185,5.0,15.0,12.0,28.0,11.0,16.0,11.0,13.0,FBEBDDHEDCEGFGGBGEBDBBHCDGDDHBDHECBDFBDEGHEFHEFEDCDHGDADDABHABDCBDBFDHGDFDCGHCGDCHHGDADDEDDAFDFFHFFECDCBBFFCFFC,False +186,3.0,2.0,0.0,4.0,2.0,3.0,6.0,2.0,EGADGADADBGHFGBDGHFGEF,True +187,7.0,12.0,9.0,16.0,4.0,16.0,12.0,10.0,BDFDFFBBBEBBFCHHCHHFFEGDADDFDFHAFDAFBBGDBGDBDDGCDFFDGDGCBCADGEHGDHCCHACABHAHGCFGFFGEFG,False +188,9.0,14.0,12.0,11.0,9.0,6.0,5.0,4.0,DFBEFDCDCBAFBADEFDEGCEBCGFCECHDBADBADBEEBABGHBACBACBECGACBBCADDHFGHECD,False +189,15.0,22.0,16.0,23.0,11.0,18.0,13.0,25.0,CHGBHDEHBEHDGCDFHFHHCHHGHEDDBGHACHECHBHGDHDCHDEAGEABFAEFACBBDDBDBADACDABFAHDABACBHHDHCAHFFBBDBGAFGFFBBABCGEEFEDCCDCBDBFDBFEFGGFHHFHDCADBDGFCGFH,False +190,23.0,11.0,18.0,25.0,19.0,12.0,19.0,38.0,DEHHAGHADHGCHACEDCAGEGFDADHADHDDGEEEEHFHGCAGEDDFHHEHHDHDGBDADHECEEGAFHDBHGBHGBDAHAEHABHBBFDDCDAHHGHHEHFGHCHDDECBFCADCGDCGHCGHGAHGABFHFHHFHHEHHBBAEDAEDFCCECAAGACCACAF,False +191,5.0,6.0,1.0,7.0,12.0,13.0,5.0,13.0,HEEFEHAEHFFHFGDFEDGEGAFGFHGEHDBHAFHFFEAHEBEBDFADBHHHEHBECFDBFD,True +192,14.0,9.0,19.0,16.0,17.0,13.0,14.0,12.0,FBCCBDDFFDHDDHGEFGEFGFHGFBDFCEEHACCAEEDBFDEDCHFCBAEFCGGAHFADGAHEHHAHBACBCEDEEDCCDCGACGCCGCEGDECAECAFGABGBHGDDEAEHA,False +193,13.0,11.0,10.0,13.0,18.0,18.0,16.0,24.0,BFHBGDBGHEFHEGEEGAAFHDFECFEAHEAHDFHCHHEHFAGEGCCHHEDHEDCCDAGGAGGBDCBDAFHFFAFDAFHGCHGCFGHGHHCHDBHBFFADFEDEBHGGFBADHAEEEHEEBFB,False +194,4.0,3.0,4.0,0.0,0.0,3.0,1.0,3.0,HCHBAHBAGFABCAFCFC,True +195,5.0,5.0,1.0,2.0,4.0,4.0,7.0,2.0,EFBGHBGABGADGABHAGDBECGAFGFFEE,True +196,16.0,12.0,12.0,7.0,4.0,7.0,9.0,12.0,ACGACAHFFCEACGGDEADCAGCFHBFBEFDHDBHAAAAGHBBHCBHGBAGBACBDCBHCBACDECHHAGHFHBGADFA,False +197,11.0,6.0,8.0,7.0,7.0,10.0,12.0,14.0,GHFFHACEECGEGGDBGBBFAGFGCHGHDGAEGCCBHCBHAFHAHDAFGAFADCADHAHHBCDFGEAHEHHFDEF,False +198,21.0,16.0,17.0,15.0,22.0,24.0,21.0,20.0,AEFABCDCDABGHHEHDFBBFCAGGAEFCGGCGABGACGHHGDGBDBBCFACBDFHHEHFCHFCECHFCHGEHGBFFECFBHFGHFEDFDCFCEAEEADDGDEGFEGFABFHBFAEHEDDADAAGAACEACBHEBFEDFAAAGGEGGBHEEHFEHF,False +199,3.0,4.0,1.0,2.0,7.0,5.0,9.0,5.0,HFFFEGEEGAHGBHGAHDADCBGGEEGEGBEGBFFH,True +200,27.0,17.0,26.0,18.0,16.0,17.0,15.0,13.0,BDEBEEBCBBCDFCHCCABDEGCGACGACACFGDDGAACBACEEDBDDCCCHCDFAHBGEBCHGGFCGHHHABHBGAEHCBGCDAEDFEFBEAHEAFFGDFHDHHDFDBFEBAAGAAGAGFCBCCEACEACECFAFAAFAADCFDAFDA,False +201,14.0,18.0,22.0,18.0,23.0,25.0,18.0,25.0,EHGEHCBHCHHAEHDEHDEAEBCEBCEGFAHFAHCEHBFHBHHBHEBCFADGHFGCFBAFBDHCHCEHADGBDFBFFBHBGGEFFFDFEBCDFDHCDHBECDEHECBECEFAGFCGCAGEHGEDEFHFCGCCDACAAFDAHDFFDBGDGAFGCBCDFEGFGGE,False +202,6.0,4.0,6.0,6.0,4.0,7.0,2.0,1.0,BADGAEAACFACGEFBACCEFCEFBDHDDFDBFDCF,True +203,4.0,8.0,7.0,5.0,6.0,6.0,6.0,7.0,EHAECAEHBEHBFHBCDBAEFEGGCFGDGHHACBBCGBDHCDFCDFGBF,False +204,6.0,15.0,10.0,9.0,18.0,10.0,16.0,17.0,EHHEDFBDFGDGEDGHFEEDDBGFADFCBHCBHFEEFAECGHHGBCEDCEHFACGHEGHEGCBGHBCHBEFFEHADBAGBGHCHEEBEAGEBGBHGBHCBG,False +205,6.0,8.0,4.0,6.0,11.0,10.0,4.0,7.0,BDFBFFCHFBADBGFCGCCEEAAHFAHFGFEEFBEAHEBDEBDFHDHEGEEBEHDA,False +206,7.0,11.0,7.0,14.0,12.0,11.0,11.0,15.0,DFFHFBABAHBEHBEHDHGCHFDFAGCGHEBADHGDHCEHCEFCEFGFFGHGCDAADGBBGDBGEBFEDHABHDBCDHHEFDEGDEDE,False +207,14.0,19.0,19.0,16.0,15.0,16.0,25.0,15.0,BHBBDBDDGDAHEGEGGECDCCBCDAEBGEDGHDCHFEHACACCEDCGFGFEGDGGAGGAGGHFBEGCEGCEBCAFGHEBHDAEGAFHHCADFBBFBFFDHFCHFBBGBBCBACGFDAFHBCGFCGEDGADEAHFCHBG,False +208,14.0,24.0,23.0,25.0,20.0,23.0,13.0,19.0,CGFHBECCCACGAFFHDFHDAHCCFBDFBCCBGFDAHDABGABGHBFHCDGDDHBHEBCEDEFFEFFEFFCDDGGECDEFDADDHEACEAHEAEEBFBFGBDBBFCBDCFDGFHBBDBCGCDAHDCCDHCEEFEGGECBBABDCBDEFEHHEHHBHBADFA,False +209,5.0,7.0,7.0,12.0,11.0,5.0,6.0,4.0,BEEGAGCAHCFDCAHCEFCAFGGDDEDCBDBEFBEDDADDHDDBBDBEEEGCEGHEF,False +210,21.0,21.0,29.0,26.0,25.0,22.0,25.0,25.0,HGGGCBGCBGFDHCEGCBADBADBDFHCBHDBEBBEHBEFBCABCACCFCEFHAFHGFGDDGDDHHDEDDHCBEDDEDCBGGFAADADGACHAFDBEBEECDECEFGGHECHEFHEBHEDGCDCABCEFGEGHFGHEECDBHDFDFGCAEAGEAHCHFAHDGHACFACGHHGDHGCAAEFAFBCBECGFCFFCA,False +211,25.0,20.0,15.0,18.0,16.0,31.0,22.0,17.0,GDHFDBEDFEFGAHDFFDBECFDAFDBFGBDAEGAEGFDCFDCEACBAFHGHHFBFFBHHEAFBAFDCFBGAGGACBACFCEACEACHHGDHGCGFHGHAGABGBGDFHHFCACEBHEDDAFDAGCADBEGBFGBFEFFEAFGCFBHFEHGABAABAEGAFDFB,False +212,11.0,12.0,15.0,21.0,14.0,13.0,13.0,22.0,FDHBAHAHFDBFDFCHHEFHDFAGBADBADCHDFFDABDHCDHCGAGFHDDHEEHBHHEHBCBGDGCDCDECDEGEBHEHHGHDFBCFDAGCAGCACCEFCDBGEBGEDEFGHCGHEDHEA,False +213,26.0,25.0,22.0,24.0,22.0,21.0,23.0,28.0,DGGABBFFGEFGHFBHBHFAGAHGECGEBAACCADCHDBGDHCDFEDCCCFBFAHDEGGBGECFEABGHDEADGBGGFDEFAABAAHAAHCAHGFHBFABFAEHHCHHCFBEEDEEFEGDEHDHHDHCBEABAGGAFGDFDCBCHBCHBHEBAAGCADCHFCFDBBDBCDECHACHDBEDHEFGADGHDBE,False +214,17.0,18.0,21.0,25.0,26.0,17.0,17.0,17.0,FEFAEAHHABBGBGGCDGDEEDAEBGFHHCADDHDDEDDEAFECGGAGGEBGBACEEDEEDHDDHGBHEBCBHADFEDEGGCDDBDCFCHFEFAHFHDBHDBHAGCFEFFEBEEBEEDGEACFABBCBFDBFHFECGHCGACDCCDCCECFHAACADC,False +215,3.0,8.0,12.0,3.0,11.0,1.0,8.0,8.0,ECHEGGEHEEBCEHGGHBAADGCHBCBBCHBCHBCEDFEGHEDCGCCECEBCGA,True +216,3.0,7.0,2.0,4.0,7.0,5.0,4.0,9.0,EEBACHABHEFDEHHEBHAFHFCHEDGEBBDFBHGBHGFDG,True +217,24.0,19.0,23.0,32.0,19.0,19.0,18.0,19.0,BDFHFFHEAGCGGEHGAHGADAEDAEGACABCBFDEDDEHDGDDEDDGCDGAFBBEBHFBDEADCDDCHBCEAHDBHCBHCACBGCGFCGFCGDHFABCACCABHEEHDGBFFDFFBHADDDCAAHDAEFEEFBDFADGADHADFGDCGCCBECADAHHCFDCGBEFEEDHBA,False +218,15.0,9.0,15.0,14.0,9.0,15.0,10.0,14.0,EDDHBDCEDAHHCDHCDEFECFDDBDEGDCAFCAGCHCFHBFBDFCABCEGEEHHGFHAFCABHABDAFAHBHHGFCGFHGBAAFDAFAAFEDFAGGCCGC,False +219,24.0,26.0,20.0,28.0,17.0,21.0,17.0,23.0,FBGGAGHAGHGGBGGFFDAFDHDCFBFFHFDHDDHFDHFHCFGDHBEFCEACHFEHCBADHDBADCEBCDDAGDAFDAEDEHCAFDAFDFBBAGBGHBCHAFECHDCEBBEABGFHEBHDGCEFCBACBACBCCBHBFGDADAAHAHBGDBDEBGECEDHDAEBAEBAEHADCDBC,False +220,10.0,6.0,12.0,8.0,3.0,8.0,5.0,9.0,DEDDFFBCFCCAGBFHBACAACAHFAHBEGGAGCDCCDFCDFCAHCACDHEHHABGDBHFH,False +221,18.0,20.0,25.0,20.0,16.0,11.0,30.0,25.0,BFFBEGBGFBGHBEFEDHBDCAAHAGHFGDADCBDBBDECAEBAHGHGABBHHBGCGECEECADDDGHDGBBGBCGHHGCHCCHCFHGGHAAHAHGAHGEHGDHBEGFHFAHGADFEGBDHFDGCDGCFGAGCCGACGHEGDCCCABCECGEHDEDDCCECADCB,False +222,19.0,19.0,21.0,28.0,17.0,28.0,23.0,16.0,FFFFGGBAGBFCDFCBFDGDDEDDFDEFCHDCHACAAFFDGFHCFBCDGEGEECCCBBAHHDEHDECFGGGDDGDDGDDCBACBABHCDCFDCEBEGBCHEFHGBHABAGFGFADHAGFAEFHEBBFBEFCGFHAFGADGAFHBCABDEDDCHFEHFEGAEDCGDFADBAG,False +223,23.0,19.0,28.0,13.0,18.0,28.0,23.0,33.0,GHBCHBGHEHEAHDHGDCFBHGCHGCFGCBGBGCDHEFAGHEGAABBHECFCFGDEHCEHAFCADAGDFGDHACBACHACHCHFBEFCFGCHHHHCHBCBEDBFHBEHBAGEACHACFAGGHGDHFFAFEADEAHFAHCCHEFGEFBFCBHDFGFFGAFDACDECECBEBFHBAGCHGCAFFAFF,False +224,3.0,2.0,2.0,3.0,1.0,3.0,0.0,0.0,DAADFBDFBCACFE,True +225,18.0,28.0,26.0,15.0,16.0,22.0,28.0,24.0,CCBGHAGAEGAFGBHGCHGBBBHBBHCBDDBFDFGECEECAGHEBBGBAGBFGCHCCDGCDHEAGCBBFBBFCBGGAGBDGHGGHGHHFHDCEDAFGHBGABHBEAACGCCHCCHBHHFFFFGCFHCFEDACFGEFCAAGDCDDHDBAABFACDABEGCEGFEHFEFCEDBFHBEHF,False +226,0.0,1.0,4.0,5.0,1.0,5.0,5.0,2.0,DBGCFGDHGFCGDHGEFCFDCFD,True +227,9.0,11.0,5.0,9.0,13.0,8.0,7.0,11.0,DGHBGEBGHACBAFHAFHFHDDHCGEAGEDEEBEAGFDFBDFBHFHCDHCEEAFBABBEEBEBDHADHGEEAC,False +228,3.0,5.0,4.0,5.0,8.0,4.0,5.0,8.0,DCEDEHGEHGFCEFGBDHBDCBDHFFHEAHEACGBGHAEHEB,False +229,5.0,2.0,1.0,1.0,0.0,2.0,0.0,0.0,ABABFACFADA,True +230,17.0,15.0,18.0,10.0,25.0,10.0,12.0,11.0,ECCHCABEAEAABAEBGEBCEBGAAGBBDFHDEHDEHCHHCHCEHEEHCGBAFCDEEFGEGGCFDEFBBADBEEFHEAHECGFCDAAAFBBCCCACBGGBAEDDEGDECCEFAEFAEG,False +231,31.0,18.0,29.0,27.0,23.0,14.0,25.0,29.0,DGBAGHGHDGCGACBADBDDEADFCHGDBFEBHEBHEFHFCDFCDACFGHDDDDDCGCEAEEADCBDBGGHCAACAEDACHEHHAHDDFDEHCEHCECEHHEAFEABCGEGABHEDHEFAGCGGCGACDAGDACAAHACBBCDACAACHCDHGAHGFBDAACEACECFEHGGHBGHBCFFGDBGHBEFEHHAHBAG,False +232,9.0,27.0,30.0,27.0,17.0,16.0,18.0,20.0,HDBHDCCCHHCHECBBCGCEDCHCADGDBBEBGEGGFDFDDGDBBFHCEEDFFFHFHHDGCEBCABABDEHDHCDHFDHFDHBDHGGEECBEHBDFDDBCDCCBCCGCAHDBBBBFBEHBEGBEDDGAAHCBECBCCBCFFEDFEDCCGBAGACGDCAFCGFGG,False +233,13.0,14.0,9.0,12.0,10.0,11.0,7.0,12.0,CACBADGHDGHDFHDFHDEEDGEBBEDHACHABBFCFAEHACFDCEAHEABFFBFEAAEBCHDGBDBBGCBFEAFGDCDHHABHABGF,False +234,27.0,12.0,19.0,20.0,14.0,11.0,16.0,19.0,DCEACEBHDGHAGFBGABGABGABCHFEADDADAHDHDGBFAECCBCHHFADFEFAHDAEDCHCHADBFDCGDCHECGAAAAGBAEEHGCCGEAGEFCDFDGGCGACHCEHCEHDEHBCADAADADDFHGAHBAHBAF,False +235,10.0,14.0,16.0,10.0,22.0,13.0,14.0,12.0,BCEFFEFBBGBBGEDGEABFACCDCCDHEGHCBDGHEEEFAGBHGBEEHEEHDEFDEFCECDECHGGAGFFEDGHBECBHCGFEAAEAHGBHGBHEBAFACCEDCACFDCF,False +236,7.0,11.0,9.0,8.0,13.0,11.0,4.0,12.0,AEBEHFHFFGFHBFHFAHBHHBHFEFABBEBAEFCEACHHDGDEGABCCBCEBDEDCEACFHCFDCHDEEDBGDE,False +237,23.0,30.0,14.0,18.0,17.0,26.0,17.0,30.0,DGDDFCEFCGCBBHACAFCEEEEAADADEHFABBADHADHFDBFHHFHDFDAFEADBADCAFAFBEBBEBBCBBCFBEFBGFBHBBFFHFAHABHEFHBFHEGHAAHBAGBGFHAFABEGEGGDCGBHBCHGHFGHGHHCDEFFHCBHBBHGEHGDHFDHCDBDAHGHBEAACFG,False +238,19.0,27.0,27.0,14.0,19.0,23.0,28.0,21.0,CCCACCFBHFGEBABBGFFGBCHBFAAFBAHCAHCBGABGADDABDAFDBCGECFEHBCHGHHGHEGDEBFBBCGBGHBGFBCCBDGDCHACHADFADEHDEHEGADGAFBFGBEGHFHEADFCCGCCGFCEFGHFEFBCDBGHHECGBCFAEBBCDGAGCAGFFEHGEGFEGBECHE,False +239,12.0,6.0,10.0,11.0,16.0,6.0,12.0,10.0,DBDGGDGCDECGHCHEAHGDEFEEFEBBHABCCDACGFEGHECAFAEDAHAGCBGAHGAGFABFDEEDGEHEECEDCEAHDAH,False +240,12.0,11.0,10.0,12.0,15.0,7.0,12.0,8.0,EHCEBGEBCADCDFCEGBEBCEBHDGAAGDGHDCFDEEGBEFEEFGEHGHBEABEAFCFHCGHCBADAADADGAEBBDDHDFGACGA,False +241,24.0,20.0,23.0,18.0,18.0,16.0,33.0,12.0,DCADHACHFFHADCCDEEDCEDCFAAFGBCGACGAGGACHBBDBCCBEFBGCDGHFECABCACGAEFAECBFFFHGCAECAGHEHBFHBAGEFGECGHBABCADDGGDGGDGGCGCFFHGGEAGEGEEBBEGAGFFGDGGBGDBGDCGHAAABGEBEBDDBDAA,False +242,2.0,5.0,2.0,2.0,7.0,2.0,2.0,4.0,EHCHBDECDEGFEAHHABBEBFEBGE,True +243,5.0,8.0,9.0,5.0,11.0,13.0,13.0,9.0,ECEEGBGFFHFBEFHFDBGDBGFHFFHGHCGHEACEABBFEEEEGCGGCFBCDCCEHCDHGAFGABGHFGAFD,False +244,8.0,13.0,8.0,11.0,10.0,14.0,17.0,10.0,EGDHGCEDHEAHFBCGBAABGEDAEDAEGGDDFDCFGCEGCGFADFCFEBBCBFDGFAGFEDFBGFGHBBHEDHGGHBAFBFHCFHGBHGB,False +245,10.0,16.0,19.0,10.0,13.0,11.0,21.0,15.0,BEEBGHAGHCCFEDFGFHBHHDFDDHCFAGFAHABFABGAFAACBECGGGHGCAGCHCEFGEHBEHBGFGEFCHDHHDEBCABDGBGGCGGCBGEBGDCCCCDCBDEBGEBECCH,False +246,9.0,13.0,8.0,9.0,4.0,11.0,15.0,3.0,BDDBDDBAGAEGABGEDFCBCCFCDABHCBGDGGEGCEFAGBAFBGGBGGBDFFAFBCGDHGHFFCFAGFAB,False +247,24.0,29.0,19.0,27.0,21.0,19.0,25.0,36.0,AGGDCEDBEDGADBCBEDBHDFHDBEFHEFEEGEGDEABEFHDBHBHHFFAFBGGHCFFEAFDABEAFCHDCABBBCBEEBFBGAGHBGHCABCAFHDGHCHHCDGADHADGFHGFCGDBHBCHBDAEGHHGHHAHCAHDDBGHBGCEAHGADDHDECGEHHEDEGFEDABHABHABCABDABDACHGCBGDHHFHFFGC,False +248,23.0,15.0,19.0,20.0,20.0,17.0,12.0,20.0,AEDAEDAEFADFAHFAHEEHBBCBBDBCAFAAGCCGACEHEADFHDFCDAHGBEFFEFDAFGACGECEHHGADGBCAFCGCHDDDGCFFDBCHECFEHEABEABDCBHFDHECAFDABDAGEBGHGEHDBADBADCHCHHCFHEEH,False +249,5.0,8.0,8.0,6.0,8.0,12.0,5.0,4.0,DDADDFEDFHACECHGGHCDBBFFBEEBGEBCECCGBEAAGAEBFCFFHFFBFFCF,False +250,9.0,9.0,5.0,9.0,9.0,5.0,9.0,6.0,EBGEGDECAEBBGBFDBACGCBBCBBFDADDACDGEDGHDHDAHEFHFGAEGHFGAAEHAE,False +251,3.0,4.0,6.0,7.0,2.0,6.0,5.0,5.0,FCHFEBDGHDHADFGGFGFFEDBCCBCCHGCHDBDDAA,False +252,23.0,16.0,22.0,22.0,17.0,24.0,15.0,22.0,GDGADAHGFBBFBCHBDHBDCCDHEGADCHBBDFHCGGCEFBECHECEACFDBADEACEDFFDFFDFCEFCGFCHFGAFADGAFHAEABFDEDHHBAAAAHGABGDBFEHFHHFCHDCEAEEAEDCFFAFHCHHADHACHAEDABDCCGGCGFCBFGEHBD,False +253,28.0,21.0,24.0,17.0,16.0,23.0,19.0,22.0,HBGAFCHGAFDHGAHGHGDDGADGECAACFACBDGFCBAHBHDBFDEFABFACAEGFHGBDGBFHDFHCGBAGCABEGHEFHECCEAEHADHFDCCDCCEAFBDDBFHHFGHFCHCDHCFFCBAEFAEFEEAAEBFCBAABAAHEABBAFBGCBGCBDFGAGCCDECAHH,False +254,22.0,21.0,35.0,22.0,18.0,16.0,18.0,17.0,CGFCBBCBBCFBDHEGBFDEHCCAECAHAFDEEDAEHAEBCHFHBFHCHBGEACCCCDCABFABCDBDHCGCCGDCDDADDGGEHFEGCCBCBAFDEFDAADFAGGHECHECHECHAHGCFBBBBAGGEDBFDAFDCEDCEDCADCBHEFCAGCAGCBGFDACAACGGH,False +255,16.0,23.0,16.0,16.0,20.0,17.0,25.0,22.0,FBDCDGFHBEHADAEBABHAGDEEDGEAABDDEEFEEDBCGGDHHDHGDABBCBBCDHCDBGDBGCHGHAGFECEEBEHFGDFACHGHHGBHCEHCECABHADHACFBBAEFCEHAGHGEHGFHGFGGFGBFBFCBGCFGEFGEHBBGFCAFGAB,False +256,4.0,5.0,1.0,1.0,3.0,4.0,5.0,7.0,BHFAGFAFHABDAEHHGHHGEGBEGBCBHF,True +257,15.0,16.0,15.0,21.0,14.0,16.0,23.0,29.0,BBAHCCDBGFHGFGFFCFGCGHCGHDGAGHDCHDEABEBGGFDDFHDHHGHBAHDGCAGBGEBHBCHGEFGEHGEBFECHEDGEHBAHBEHDACDHHHBCHBCHAFHDCHAHGAGGDDBDDEACBAEEAHDDFFHGFHFFDAEDACDFG,False +258,25.0,18.0,28.0,20.0,16.0,20.0,26.0,30.0,GBDGBHAEEAHBAHBCHCCHCEBCECDEAAFHHCGGCFFDFBAGBHGFHDAHBACCADCAECAFFAFFGGEGCEACECCFCBEAAGFCFFGGHCDECBGHBHACAAFDGHDCHDCFDHFEHFDGDGHDCHAEADGGEADCHDHBGBDGAGGFFHHFHAGHCHHCDBGHBEHDEHGABBADBCG,False +259,10.0,4.0,2.0,8.0,6.0,7.0,4.0,6.0,BFAHHADDBDEBDAHFACEADEFDEHDGAGFDGFAEFBGFEAACHAH,False +260,17.0,18.0,20.0,22.0,23.0,26.0,23.0,18.0,CGCHEEDEBDHDGEGFEFFCAHGBHBEHBACAAFAFFDBFDCFAEFADFAEGBBHADAGGHFGCCGCGFBDFEEEEADHGDCEDFGDEBDHBGHBFFCAFCECGEDADDBHGBECFEBFEDFDDEGDHCAHCFFGFFGAHCDHADCBECBHHBHCGFGGABGCEGFE,False +261,27.0,24.0,20.0,19.0,30.0,32.0,21.0,26.0,GEHGECEEBEDACCACGBFGFCDBHEFEEFGEFBFACFACFAFFAGDACBAGDEBABFAEDAGHAHBAECAFDFEEBBBFEBDEFCHFHBFHFEHDGHBGHCCFDDAADEAEECGGHGFECFEDFEAFACHACEFBEFHHBHHFEAFHBFBBFBHFCAGHHFHHGHDCHDCHFGAGDDGCAGDEEAGEBEDAGHADBBB,False +262,24.0,26.0,23.0,23.0,21.0,23.0,28.0,24.0,CFDHHBBHEEHEHHEFHBDAADAFDBCDHDDFGAFCACEADGBEGCGCHEAHGADGABGADCFFBFEDDAFDCFHBBCFBGDGCHECBEBBCABDAECAHAHHAHEBHDHHFAHGEBEHFAAGBAGBGGCAFAFBAFBDCDCCDGGDGBHBBCBGFGEEGECGEHECDFCBFGBDGCACEFGEGGFHGFDGF,False +263,0.0,1.0,9.0,1.0,3.0,4.0,6.0,1.0,CHCCEFCGGBGFDGEGCECCFCFGC,True +264,6.0,5.0,5.0,2.0,0.0,4.0,6.0,0.0,CCAGBBGDBGDBACACGAGGFFFAFBAC,True +265,4.0,10.0,10.0,7.0,1.0,8.0,4.0,4.0,BEFBDFGDFABCABCHFCDGBHBCAFCAFDBDBGGBDFCCBCFHCDHC,True +266,22.0,29.0,31.0,16.0,20.0,28.0,16.0,14.0,EHAHCBHCBECFGBBCHEEBAFBHHAFGBFDBFCBFCBFCBFCGFGECBBGFCEFBEFDEDDGFCFCAGCAFCEGAAGAACDCFGAFGAFHBGABDAGAHCAECABBBCFBCDEAAEBFBBFCCFCCFABFDDFBEHBFGEDBEDEHAECBGCFHCDECACCDEFDADEHCGDBHH,False +267,19.0,18.0,7.0,10.0,13.0,13.0,13.0,11.0,HAHCGEBDCBCBBEGHFGBCGAAGBGGFDGCAEADBAHBFEFFEAGEHCHHBAHAADEFGEAGFFEFAEFCBAABAABEAFGAEGDEDBBABBFBHHDDHDBFD,False +268,17.0,10.0,10.0,7.0,8.0,5.0,14.0,9.0,DCADHDGHAGBAEHECHCGADHCGAEGBEGAEGAEGACAHGHDCBGHBGFBCAAAACBBEEBGBCFCAFDAFDHFGABGA,False +269,1.0,3.0,0.0,1.0,3.0,4.0,3.0,1.0,GHGGEBEFBFABFEDF,True +270,23.0,19.0,18.0,18.0,15.0,13.0,11.0,15.0,AHDAFCAECAFBHBCEFDEFCEFEDAADBADCDDFDAFGEHGEAGHADBBEACFGBDHADGCCABHHGHFBEDGHFEACEFCBAGAAEABEABGABHBEABGABFCBACGDDHFCHBCHBHHCEDCDDCDBC,False +271,7.0,9.0,4.0,6.0,4.0,10.0,14.0,6.0,GDDGADGAHAAHABDGFFFECFBHBEGEGHEGDCABGGFFHFFHFBGABGDBGCBGFGCB,False +272,9.0,5.0,1.0,2.0,6.0,2.0,1.0,1.0,EDAEAFECFGHAABAEDEBBEBAABAA,True +273,6.0,7.0,5.0,6.0,3.0,4.0,5.0,6.0,DBGDAGHAGECGFBHFBGDDFEDFHCBBEHHCAHBACBACAD,False +274,13.0,30.0,20.0,14.0,22.0,14.0,15.0,16.0,HBGBBDCBAHEFEBDBCABCGFGEHGECGCDECDBFDECGHBFHACDCBBHEHGGHFGBBBBHBBHBBGBEABHDBGDEGEFDECCFHEBHEHGEFCFBCFCDABAAHEECEECEDCEDGEBFEBAABGABCBCAAFDAFDHFC,False +275,5.0,8.0,10.0,12.0,2.0,10.0,10.0,5.0,HGDDCDFCDBGFCGDBGEAFACFDBDDBHDBCDCCFGCHGDFGCFDABHGBAGCGFABFEHF,True +276,5.0,1.0,0.0,3.0,1.0,2.0,0.0,3.0,BDDHFAHAAHAFEAD,True +277,24.0,23.0,18.0,24.0,16.0,33.0,19.0,28.0,ADCABCHCAHCAHEADEAHBGBCGFGFFGAFBDFGFBGDEGDGHHGHHACDDGFFAFFBFFEFADHDDADDFFAFGBFBBFHFCHBDADEAHECEDFDGFDFFDCBBHDAHBBHCEGEBHHBFFCCHHHHCHBBHDHAGCAGEDEHDGHDAFAFBBFABFAEAAGABGFEHCCBCHECFEDFGFE,False +278,12.0,29.0,23.0,26.0,19.0,18.0,23.0,13.0,BEBBEHBCAFAHEDDCDBBDBBDAFFAFCADCGGBGGCGHCFECEBDECGEHGEADBFDHFDGCDGCBCCHDBEABDCBDEBEEBDCGECBDHBEHEAGAFGHFHEFBBDBGEBFHGGHFGFDGCDGDDCFFFDFECCGCGGFBDBAACHEDBDDBGCAGBBC,False +279,16.0,11.0,17.0,16.0,19.0,22.0,19.0,14.0,GFAAFDCCEGCHGBEGDABFBDFEFEEBEBGFCGHHHFHAFDADEAHACBFCDFHFGCDACDFCGFEDFEGADGAFCEHCAHBBHEGCDDHDCAFCAFGEEGEEFBEFEHAHFDEFDBGDBGAFCAGCGGCGHE,False +280,10.0,14.0,13.0,11.0,22.0,14.0,17.0,12.0,EHCECEHBFGCGGCAHCDGCGGEDBBBFHCFBFBBFGHGHFABEAEGACGACBFDBCEECDEBFEBDGHDEBEGGECGEHGEDEEHFEHFEGFAADGADEHDAFDHFEEFCBA,False +281,32.0,31.0,18.0,18.0,36.0,28.0,25.0,12.0,GAHFABEGCGAEFADGADFABCADAEBAEFEHFGBGCBHDAHAABBBECFEAEEFEEFEDAEBAECADCDDBBBCBBEDBFAAFHEEGFCGEEGEFGEFAFDABCABDAFGFBGFEGBEACGGHFGAFHBBDEEEGGBHGFFAFFGEFGEBGDCHCHGBBGABEABEFEDADCEEFDCDHCDBGABAACAHCEFCEFBEB,False +282,19.0,24.0,17.0,28.0,20.0,14.0,18.0,11.0,CEGDBCDFGFGCADCEEGFABEDBDBBDEFDEADBGBEGBACDDFDHFBHGGCGAEGHEGHECDDGDFGEFABAEEHDFBDFBEEBHCDCCEHHDCGDBHDFDDADDEEDBBBBABHAHDABAAGADBCFBCBECDAGECGACGACFABFA,False +283,26.0,21.0,30.0,21.0,22.0,23.0,22.0,14.0,ABEAFHABHEFEEFBHDAHFBHFBAFBCBGGHGDHFDHFBEBBACCAECAECACGBCFFEFCEGGACBCDFAAHABGDEGDEGDACFEGDEGAFAACCBEABGAFDCFDFFGACHCEGCFGABCHGAHCDHCDCCDCGABDFBDEDCGFFBFEACCDCHDGGCGEEAEBAGDCDDCEEB,False +284,14.0,18.0,15.0,12.0,15.0,14.0,12.0,12.0,DHBFHFFADGAHCABFABEEFDEAGEAGDDBACBCCBGCBEEBEAHEHCFFCEFCBCGDCGDEGHGGABADBEEBEHCHHDBEGGFFEFDADHAHBBDFBCCBGABCFHCFA,False +285,16.0,15.0,17.0,12.0,11.0,20.0,18.0,11.0,HGHCBHCECFEHFEGDAFFGFEGFEAFGFBGABDBBGBACBGFBECAAFDAHHFGGAGGAEGCBDBBDHEFGGDGEHAHADEADEFCCFCFADDBCCBCABHAFFCFGCFDCFACDBCGH,False +286,11.0,13.0,7.0,7.0,10.0,17.0,12.0,13.0,FDGFDGFHABDDHFAHBHFFGCFHBGAGFFGFHHAGHEGHCGBCECDECDBHBEHBEHCAFGABAFBGFBEFGEABFBFDEFAEAHEABC,False +287,8.0,6.0,3.0,14.0,2.0,6.0,4.0,6.0,BGDFDCCDGAFBADBDHHDHCDHAAFAADBADBFDEFABDGHEGDDFHD,True +288,13.0,9.0,15.0,13.0,19.0,11.0,16.0,13.0,GGEDADGABGCBHAGACCFCHECDDCBAFEEHEBBEABEACFACEDHEAFEGFGDAEAAECDEFEHHEHBFFDCFDCDAGDHEBHCGHGGHCEFCGFEGEDGDCGHBGH,False +289,21.0,24.0,27.0,24.0,13.0,22.0,21.0,28.0,EBFBBCGBDHCAHFAHBBHBDHBDHADECDCAHCGHGFHADHDCHFBBAHBDHECABFBFFCDFGDFECBECBCHEAHFHHEHGGFAGBDCEHCFHCGGBEGFHBFGAFCADDFDDBDFCAFCHFDDACGACGDCGAGGHDEDECDAGHBFABABBEFBCCDEAHGAHGCCGCFAHDGHC,False +290,11.0,5.0,20.0,12.0,8.0,15.0,4.0,7.0,CBCCHDDHADEADEFDAACCCFFDFCAFCADCGDFEDCECCECFFHFFAGFCEDEBFFHCHGCDBHGCFDAFBAEHACCACB,True +291,20.0,16.0,14.0,23.0,25.0,13.0,17.0,18.0,GBEGBEGFEGFBFDBFDBADHAFBDFGDEGDGGECCECAEAADAACHHHHBHEGDADDBHAAAEHEBDEBGEAEHDGHAAHFABCEGDFGFCECDGDABDHBDECCABFBEEDEGFEHFEHGAHBDCDAEHAECDCFDCEDHGHEC,False +292,22.0,21.0,19.0,22.0,30.0,26.0,23.0,31.0,AHGAHGABADGFGGEEAEFDCABCFBCGBCBHCBCFEDFEDHADEFDFBHCBHAHEAHEHHEHEBGEAGEDCEHGACGDCFCEFDEBDEBDFHACEEHBDDGGEBCEBCGHFGEABFAEEBHABGAHGAHDHHDHEABEGBFAEGHEHCADFFDFGAFCDDGFHFFGFFDEBCHFEGFCDFHHCHFBEGHHADH,False +293,16.0,24.0,24.0,18.0,24.0,17.0,14.0,18.0,BDDACEACHABHABHECHGHEGEEFCHFAFAGFBBBGBEECEEHEFDBDDBDDGCGBCEHCEDCBFABFBBCCECCGBEBAABHECEGCEDDECFECFHCFHCGBCFFDDFADFAHHCGBBBCAFEBHGDGADGAHCBEAAFGDBHHEDCEDFEH,False +294,32.0,23.0,12.0,12.0,9.0,21.0,14.0,23.0,BCGBDHDCGGGDAFDFFBCABCABCFGGFAAFBHEBHGBGGDAFAACABHBFFDAFAHHBHHDHGDEADBHGBHBBHBBFACCBECAAAHABHAEAEDFGCCEAFFHEBHFHHEHDABAAGAGHADAAHAACEAHAAFFBFFBFFH,True +295,25.0,28.0,34.0,29.0,21.0,15.0,21.0,21.0,GBBDDFEAEADECDAGBCFBADECDBBDCCGCAGCDBCBBCBDCBGCEHCGACACFBHFDDBCHFCGAGGECFFABDEGDEFDHFHHBBHDAEDBEDCDDCDDCDAADFACEDHHGACGBBGAGAEGFGGHCACCDHGEHGEHGHCEACBHFEAAEACEACHHCHBCBECHHFEBBDCBFCBDDBDABAEFAHG,False +296,10.0,5.0,3.0,10.0,3.0,6.0,4.0,2.0,FCDBCACHBFABDAGEAGDADEBDFDAFGABAADEADHGDFFD,True +297,18.0,24.0,24.0,26.0,29.0,26.0,24.0,26.0,HAEHBEAEEHCACDDCFDHFGCBHCBCDHFDEADBBGCBGABFAFGGHGEAGDBCCGCBDFDDFBEFBEGDEGAADHADHBHADHCDFEFFEGGEBAHBCFGCEGEBGBFGEAAEDHFDAAGHFGEEGEEDHECGEDFEBBDCCDBDECFCBBEFHFCGFEHHEHHAGHCEHCDFCDFCDHCHGGHFEFFBFHBADB,False +298,13.0,9.0,11.0,21.0,12.0,21.0,9.0,8.0,DDADBAGGAGEAGECGEFHFCCFBCABCABHAEFABFDFCHHDDEDDHADHCHABFFFEAEDCFDEGGFDDFCDFEFFEDFEBADFDDFBDFCHBGFCEDDAFG,False +299,9.0,10.0,7.0,5.0,4.0,5.0,9.0,5.0,AEBFBGFGGAGGADCADGDHGHEBHBBGEBGFCHBCHAAFAABCECCFDDBCAB,False +300,9.0,10.0,14.0,12.0,10.0,5.0,22.0,10.0,GBDGFGGEGEHGDGGEGCCGACBDBBDABDAEFABBCEAEHAGCFHDGHGGDGADGHGGBFCDHCDGCGBDAACEHCEGCEGDHCHECHCBF,False +301,23.0,15.0,14.0,8.0,21.0,17.0,19.0,20.0,FGCEGAEGEDHEDBGGECFFHEBBBFDAHHEBAEBHCHEGAAHABEEFEEFGBHGCHCAHDAFGGHGDHGFAGBABFAFHEEGEAAEDAGFAEFACFACBHFDCEHBAHCAHGAHCCGCCGEAGEACFADFHBBHBF,False +302,27.0,23.0,30.0,20.0,17.0,18.0,24.0,20.0,AACCCBGDBFHBAECFFHBHHGHAACGCHDDBFBGGCHGAFGAGGAGGAHGCHGCDGCHBHABFDBDDEEDEEDBCFCCFCHBHFBAFBDFHFBAAAFCCGHCDBADAFCABEACGBFBEEBAEHAEGAHGACBBDACDFCDGCDGHDEEDEBCFFCAACHECGCBGCEGCDAAEEHGD,False +303,30.0,27.0,22.0,22.0,20.0,20.0,25.0,21.0,FCHFDBBDBGCAADEBGFBGABGFEGHAHBADAEDACBECFFCFFGDBGAHHAEHFCAFAACEDCFFBEFAEABHDGAEHDDBGCBGEBGEAEEFBEBDHDAAACCHCCHGDAGDFCFABFHBFHBGBBDHBDHEEHECHDCADAEDGBCCBAGEHGEBGFBGCCACCAGAADAHGHHGFDABGGGD,False +304,29.0,17.0,17.0,22.0,14.0,23.0,28.0,17.0,DABGFCFHAEGAFGFBCCBEDDHFCADEHDEHGHDGADGHGGCCFFFFCCEGHEGBDDDDDFDFGDFGCEABADBCHADBGDCDAHFFBGFGGHAGHAGAEGEGCAAHAAGAAEBAGBGFBHBBHBGDCGFCDFBAEBHCFEAAEAAHGAHGAGFACFDCFEAFDAB,False +305,11.0,12.0,13.0,10.0,10.0,17.0,17.0,13.0,BFDDADEGGFGEFBEAGHAGBACAECAFFBBFHBCHGFHGHGFFGCFCBBAGCDGDDGCGHCBHDGGFHFFHGDECDFCDEAGFAFBAECAECHBHHEHCEBF,False +306,7.0,10.0,4.0,3.0,5.0,2.0,7.0,5.0,BHBHADABBABGABHDGHDBCEFEEFCEBCEHGGCGBAABGAG,True +307,17.0,17.0,13.0,19.0,19.0,19.0,22.0,12.0,FDEAAHFFBFBGFBDFGDFGDBGDBGFBFFHFFABEGGGHAAHEAFEDFCBFCEDCDAGBAFBGHDHCGHGDEGDGCBBDHGABCDHCFHEGGDBCHECEECEADEAEGAGBAEEDDEGCEGCHACBAFBDEDAFGAE,False +308,16.0,19.0,32.0,19.0,25.0,21.0,28.0,24.0,BCGCCBFCFGGDHGDADAACACGGBADDGDDGFBCHHCFECDGGAEBAEGHCDBCHEEHAEHFEFFEGFEHDCCCEGHFHHGBGDEGFHCFBFHBGEGFCGFCBHGBHEBEEBGBAGEEGHEAHEBFEBHCBGGDGDCHCCACCADBAHEDFGCACCHHCHHFBAFAEEDCECCDFCDFCDFEG,False +309,12.0,7.0,7.0,14.0,8.0,9.0,9.0,23.0,HFHHBHGACFAHHHHHDHBGHCEHEHCFHCBHDAHDAHFGDDHEBGFDDHADHBDGEEGDACDAHDAHCGHAADAECBEGEFFAFBDFG,False +310,7.0,9.0,2.0,2.0,5.0,3.0,5.0,9.0,BBABAGEAHBGHFEHBEHBHHAHBEGBGGBDACFCHFDHAAE,True +311,26.0,28.0,24.0,21.0,11.0,21.0,26.0,17.0,BFBEHBHGFHFHDDGADGADGFDCFBCHGFAEAAEAAEAABDDGHDBEDCCGFCFFCBBGGBFHCGGGDBGDBDEBCFBCABGDBGDFGEGCCAAHBGHGGFFBAHBAEGCFBCECHFADGGCECCFCBACBGBBGCCDAEHABFADDADDAFBHFCHAAFAABHHCHBCDBGA,False +312,23.0,13.0,12.0,13.0,21.0,13.0,8.0,13.0,FBAFBAECDHHEEEEAACADHEDAEAEFAEFAEGAEGAEAAEAGGBCDDFHAHHFFHFCCACAEFAHFAECHEAEDDHDGBBCBDFEHEAHBAHBAGCCDDDFGEGEFBBDBBCCB,False +313,3.0,1.0,2.0,0.0,2.0,1.0,1.0,1.0,HACAACEFGEB,True +314,19.0,17.0,14.0,10.0,16.0,21.0,10.0,13.0,AHDAHEEFAEAGCADFEHCEBCGCCGADDADFADFAHAAHFEHFEHFEFFCBFEBAAHEHBEBCCGHEBHCBFCFFGEAHEACBABBABFFGFFGBBBFBGDGCCBEDADAFBFFCHEDG,False +315,3.0,8.0,4.0,7.0,12.0,10.0,4.0,14.0,DHEDBEDBECHEFFFCHDAEBAHHFHFEGFECEEDEGHBGFBAHBHEBEDCFHHFHFDHGBH,True +316,19.0,13.0,26.0,20.0,13.0,13.0,16.0,14.0,AFCBGBFCAFCEECHBBAGCDGCFGHEBHEDCCAHCFEAEDDEDAGCAFCACCADCGDEBFAGDHGDCBACHAGHBFHCGECDCAGCADADFGDCGDGEDFADCADFFDAEDHCCHCBHGBHEBFGBCABHHDE,False +317,16.0,18.0,21.0,25.0,22.0,16.0,21.0,17.0,GDDGDDEDFEGFEDEEDHBDHBCHDHBBBBBBCCBCCHFCHBCHEHADGCDGCBGAFABCEDFFAEBCHBDDEADCGDEFAEGAGCCDCCGFDFBDHCGHGAAFEADAAHEBHEAHFCCDCEAHEAFGBGEBGDGEFGFHGEHFAFDGEDGECEDG,False +318,23.0,22.0,20.0,24.0,12.0,20.0,16.0,25.0,AABCHBFHCDHCGFGHDHHFGAGHBGHBGCEECAEHGBCGDDDHCFHGBHGBHEBHDCCAHCAHAHCAFCDFHHEBDDBGDGEABBAEBCDDFDDFEDFACFABFCHHCHHGBFAEFBCGBDHFDBFDFDAADAFDCEHCBBDFAAAAGECDABDAEFABFG,False +319,9.0,5.0,11.0,3.0,6.0,3.0,10.0,12.0,HABHDEGCCCDFCBHCHHGHAGHCGHCDHCEGCGCEGHEAHFABAECGBBAAFGAEHAG,True +320,31.0,18.0,28.0,29.0,18.0,25.0,23.0,22.0,ADEFDADBAGBEGHEGDCAHAAHCFGCHGFEGFHGCGBFDAFDCFCEBABHDBAFAFFDGDAAHABGGCAFCACCDEBDCCGCCDCCAFGGCHBDHGCHAHBBBBBCCGAADCBDEFDHCAHCHHFHAECDCHDGHDEADEDFADBADEEDGCBGCBGDGEFHAFEAFAAFGEEDCFDHFAHFAFFAEFHEDGD,False +321,11.0,11.0,8.0,16.0,26.0,18.0,18.0,26.0,HFGEAHHHHDBHGEHDFAGGDEFDEFDEFAEFBDFHDEEDEEBGEHEHHEHACGGEBHEGHEFHEHAEGFDGDDGBCEAEGAECDHCGHFEHGAGFCHHEHHFGDFEFFHBFABHDGFFBCEBAECGDABDHBC,False +322,6.0,3.0,4.0,2.0,1.0,1.0,3.0,2.0,CAAFAEHAGBDHCDBCGBAGCA,True +323,10.0,11.0,20.0,18.0,16.0,14.0,16.0,14.0,FCGBEHDGCCHABGBCGACFEFEEFEDCCCBGCFHCDAGDAGDEDFHGBAGEDFECGACGEFGEFEHCDHCDEFHGBHGEFDEFDEADBAEHFCBGCHDCHDCBDCFHBDABGAHDHCD,False +324,14.0,16.0,12.0,17.0,15.0,23.0,16.0,14.0,HDEBDGFAFHDDHDHECHEBHGHEGEGFADHGEFGDFBCEBGAFFAGFHBDHGDCGDCACFECFEHFAFBCEHCFBEFCEADHABCBBCFBAFAGFAEEAGBBECBDGBFGHGBFDDFDDFGAFDAF,False +325,15.0,13.0,7.0,9.0,15.0,10.0,11.0,11.0,BDABDCBEEECAECHCFHBBHDHEAHEAGEDEABEDHEGGFGGFEFBEHEEFBHAAAAAADAADFAEFGHHDFHGAGBBBBCDCGBFGFCG,False +326,18.0,22.0,21.0,20.0,18.0,16.0,22.0,11.0,FAHEBHABFAHGAEGHHBBBCBGCBECAAGDACFBCFEHGDHDDCDDFFCEGHEBHCFCDFCDGCHBAGCEBCBDGBDCBDHGEFADGEFABFGCFCDBCGACGABFACDEDEBDAFAFFABGEBGEGEEDEGDAGAGGEBGCBDCED,False +327,13.0,17.0,20.0,5.0,21.0,19.0,14.0,10.0,CACCAECGEGAFABCCDFAFFHFCEFCHAHBGEECEECGEFDECDECEEABFBEAEEBEDHCAHAADBABFGFFGFGGFBGBHEBHGFGEFBBGCBCCBCBECBCGFEHFHBGHACEFF,False +328,21.0,20.0,17.0,13.0,23.0,15.0,20.0,19.0,HECGCCHADAADGADBEGBEABEHFGFGGFGCBECFHBAAEAHDFHFFBGEBGCBFHAABAABDCBDCAFAAHCGDCGEEGHGDEGCHGHBFHDHCDBCFEAGCAHCEHEEFEFBDHHDEBEEDEBGGAHGAHBEFBECEFABGABEC,False +329,24.0,23.0,29.0,30.0,30.0,21.0,23.0,19.0,HADHFBHFEHCEHDHCDFCBABEEBDEHDACBGDBCDBGDBADCCDABAGCEGBDGBEGCDFAFFGEFGAGEAGEADCGHGBDEDAADEHBAHCAEGBGFBFHBGEBDBBAEEDEEFAEDGCABCEDGFFGECCDACHBDGBDFCHECHECEACEADDDEDFADFAFHCFGCADCEECFCCFCCAEBGGHHCHFDHFEG,False +330,7.0,6.0,9.0,9.0,7.0,8.0,16.0,10.0,HGGAAGEEFBEDHFDAFBAEDFGHFAHGDHEECGHCGCCACGFGHFAHEBHCGGCBGDHGDCGDCGBGDBDF,False +331,15.0,22.0,24.0,18.0,22.0,22.0,16.0,24.0,ABAFBECDEDAHCCGCAAHHCHHGBBGBAGBDGEDEHAECACBBFHHEHHEHHFHDCHDCBGFHFFHAEBFEFGDHAECEECBEFEGCCFBCGBCDEGHBGHFAHFGDBGEAGFADCBCCHCFFDEFEEFBEFHEHDCDDBHDBGFAFFBCCBCFBDADCGDE,False +332,9.0,18.0,16.0,12.0,7.0,14.0,10.0,14.0,AADCABGADACDAEDCHGCBFHBFHBEHGEFGHGECFBCDDGDAECHBCEBCFBCHHFDHDHHFFDFBGFGHBGECCFDFHDBHGBCFFABBACBCBBCB,False +333,24.0,10.0,12.0,14.0,8.0,11.0,24.0,18.0,AHAAHAADADGFHEEGBECBDCEACAHEGHEFHADAADFHGBHGBGBCGAGADGADGAHCAHFHFGEGGBACDCCDGFGBHCFGAFGBGEHACHAGGCDDHDAADGHDGFCGAHBAHBGFF,False +334,17.0,19.0,16.0,21.0,12.0,28.0,7.0,21.0,BCEAFGACAHCFEBBDBBDFFDBCDBFDFFDHFABDGBDFFGFDHFCGFGHCBHAFCEFHHBHHAHFADFBFCBFCBDCHEHDCADFDDEHDECDFCAFAAHABFBDFHFCDGHDHHCHECBEAEHAEFABDEFAFBGHEA,False +335,5.0,1.0,17.0,8.0,5.0,13.0,6.0,9.0,HFEEFACCHDCHDCHFBHDDCACCFCCGCFFDEFAFGCFHAEGFEGFDCCAFCHCGDCGDCHFH,True +336,7.0,5.0,7.0,10.0,4.0,6.0,4.0,9.0,CABCEBDDFADCAFCFGCEGEHDDBFGBFHCHHGHHDFDEHDAACAADHBDH,False +337,17.0,14.0,20.0,15.0,14.0,12.0,26.0,25.0,FEFFADAGDAGFCHHBHHBAFEECECAFCDFDDGGCHGCHFCGDGGBBGDAHDHECHGCBBBHDEHCCHFGHFCHBCHDAHCAGCAGEBHEBAAACEECEGGDHCEBFEHGHCGHCGDABAGHGGBBGFGGDGHHEHDDAAGA,False +338,17.0,17.0,8.0,23.0,13.0,10.0,15.0,13.0,DFFDBGEBEBCDBFDBAEEAFGAHDDDBBDEBGEBGBAGBGBCGEDEAHHADHDDHEDHGGHADDBDHHDCHDAGAECADCHDFBBFABDAFCAGDFFCAEGAEGEFGBDGCHAHA,False +339,18.0,24.0,23.0,25.0,16.0,22.0,30.0,24.0,DGBDGDDCDGCBGFEHEAAFCACGBFEBGCGCABCAFAGEAGEAHDCHBFEGHEBDDBDDBGABGFDGFBHCAEEAGDHEHFEFEHFGHFBFFGCAGCACCDHDDHBDFGDFGEEGBFDHHBCHDFFDCCABGBDGECBEGGGHDCHACHBHHGGHBGABDABHFCHFHHDBABGFCGFCDC,False +340,2.0,2.0,13.0,7.0,3.0,3.0,2.0,4.0,ECCCDCCACCBDCDFCDGAHHFEDFBDCDCCHGCHE,True +341,4.0,3.0,4.0,1.0,4.0,2.0,6.0,4.0,GAEGBCHBCFGAHGAHBACEECEGHGDF,False +342,10.0,14.0,13.0,18.0,10.0,15.0,4.0,7.0,BFBBADBAGACCABFAECCFCCEDEHDABBAFGGBDBCEBFDBFDEHDGHFAEECCDCCFHBFDEDDFDDCDDEHDEFFBDFBDFACHAFH,False +343,2.0,3.0,3.0,5.0,8.0,5.0,2.0,1.0,EAFDCDDCHEBFEFDEFEABECBFGEDGE,True +344,16.0,17.0,10.0,12.0,19.0,14.0,18.0,24.0,DGDFEBGECFCBBGFFEFHEHBEHGCBACBEGFGGHCBHGBHAEFBFFBHHBEHAGAADFAGFAHFAHGACGAEHABFGEGHEHHEHCABDAHEABCDHGEHGAHDDHDDBEFBGDBADGCHECHDHEEE,False +345,12.0,6.0,8.0,11.0,11.0,7.0,6.0,8.0,EEABBCDDGADCAECADHABGABECBECFEFFECDEGHAFHDGHFHAFAABDAHCEHAEHFDCDEGDGD,False +346,14.0,12.0,14.0,18.0,13.0,23.0,16.0,8.0,ECHBFBAFEFGCCDDGFDBFEGFEAFECFEHFEGBDDCHDHAAGAAGFBDBGDADDHGDCFFHEEHCEBGDGCFECFEBFDACDFGDAGDGGCGBABDCBCBAFFAFFAFEAFDHFCG,False +347,13.0,9.0,9.0,6.0,6.0,16.0,14.0,5.0,GEACFCDFGAFGAFCFFDDGGDBGDEGBAAHGAHFFBFFEEFBFFBFCEGBGGCECCAAHAGHAFAAHACGGFBCBBD,False +348,2.0,2.0,2.0,3.0,4.0,6.0,4.0,5.0,EFGDDADHEFBAFECFECFHBFGGHHGH,True +349,25.0,25.0,26.0,14.0,12.0,22.0,23.0,17.0,GCCGCCGEEDFADFDCCEHCBHCBGBBCBFGBAGFGHBGABFAGFBFFACCHHFHABAABCABGHEGBCGBFFAFGACCDDCBFGFAAAAAEACEFCEFCADCAGHAFABFDGADHHGBBCHGEBGCBHCBFDHGHHCEHBBBBEFAFHDDGFDCAGCAGDEDE,False +350,26.0,15.0,7.0,12.0,18.0,16.0,17.0,8.0,GFECAAAAAHFADABEGCECDGDAGEABEGBGBBGBBGCHEFFDFFAAAGEAFBAGDHHFGGAGEADFAEEBEFCGFDDFGDFDBFBEHHAHEAGEABEABEBBADAADAFFCEGCHAE,False +351,19.0,24.0,27.0,20.0,25.0,23.0,28.0,19.0,HHCHFCDGDBGDFGCBGDFGBFEDFBGABHABCABGBGAHGBHGBABCCEEBDFGDHGDBGHFGCFGCBHFBHECGCCBCGBFGACGDCHEEDFBGABFAFFGHDAEAAHDAFDEFDEDEECFEGHECAGCECCFCBABFADCAEGEDDFHFECFEGABGAHDHECBACDGHEEEEHECBECGFC,False +352,11.0,14.0,21.0,19.0,18.0,15.0,12.0,19.0,CGFBDFCAEDFEHEHCEACEAEEFGDAGBACBFCBFABDDGHDEHFGADGHDHCBHCEHCDHBBEFGFBADCGBHEADECDCBDCBACBACBDCHFHHCHFDGCDECGHCEEGHEHFFFFGEHDCHDED,False +353,14.0,12.0,11.0,22.0,22.0,10.0,7.0,14.0,BDEBEHDFDDCDEADEHCFHCAACAABBCDBHHEDHEFBAFDACABGEEDEADFADFBGFAGCGHCFEAEDGDDFDEEBEEBEHHEHHEDEEBHHCADCACHDDGGBFEDDE,False +354,25.0,23.0,25.0,17.0,15.0,24.0,9.0,25.0,FHABBAFCCFBCFBEDDHCHGBAEHCEBDAADFADFHFHHFHBFBCHBHHEHDACDFFAGBGDEGHHGDDCCCAHCEECAEDECFBBHDFCEFBAHAAHAFHAFHBFAAFAGGACEAEDAFDHEGFCFFCDFHGFHACHABBABECCCCACCBBCDBEBBHDB,False +355,17.0,20.0,28.0,20.0,27.0,26.0,18.0,20.0,FCDHEAHEGECAEDAEFCHFEFCCCCBECHEHEDHDHHEGHEDFEHAEDGEDGEFEECECHGCDGCBEDDEDDFDDBGGCGBHHAACABGGBCGBCGDCFHCFBCFBHFAHFEFFCFFBDACFCHBHEEFBGFBHFDGGCECAAFACFBBBABBDBEHCAFFEGCADEADFFBCGA,False +356,11.0,9.0,19.0,9.0,17.0,23.0,24.0,22.0,DCFDCHHGFEAECFFCFFGEFGFFGAHGBHAADAACEFFGGEHCAHCBDFFDGGHHBFHBHHAHFFGGFEGFCGFCHCGGGGEEEFCDHCDECHECEBCFGCHBCHAEHCEGFDGCHBEHBGHBGHFAEAEGGD,False +357,15.0,19.0,23.0,15.0,30.0,8.0,15.0,12.0,EDGEGBEGAEFADGHEFEEDEDDEGGFDAEEAGDAEEADEAEBBCFBCGECBEGGACEFBGDHECHEAHEHGGABCEDDFDDEDBHDBCBACACCGCABEGHCHCCBCCAFCHBEHEHHCCBCEBCEBCEBFBBECA,False +358,8.0,10.0,3.0,16.0,6.0,11.0,10.0,8.0,EADHDFFDBFEGFGCCAFCBHDGEDHDDFBBFEBHHDAHDHEDHGDAGDAEDGDGFBGABGFDGFABBADBF,False +359,20.0,14.0,12.0,8.0,11.0,4.0,10.0,13.0,BAHGAEDBEDCADCAHBABAAFAACGBHGBHABHEHCCHBCGAEACGDCADCHGAECADFAEBDEHFCHEAADHAGHFBEBCEAGEBGBGHB,False +360,26.0,15.0,17.0,18.0,13.0,10.0,21.0,9.0,HCBGGBGGBCCDDCDCCHCHHEGGEAFEDFAGEBDHBGAFGDGAABCADCEGCFGAEABEADHABGAEGFEAFAFCACGADDBEAGAABAHGDCDEADECDBCDBCBHCFDDFAGAEGAHGAGAAFBDB,False +361,15.0,32.0,16.0,34.0,25.0,18.0,29.0,23.0,HDFHFFDABBBBEEBGEBGEDEEGAHGBGBBHDAEGCDACHECHBGDBGDBGDGDDFBGGDEBFAHHHHEHHAHDADDEDBEBBHABHAFGDDBEDHEDHDDHGCHCEFDGGDGGBCFCCFEHFGGFHAEDFDFFCAEGABDFEDGBAGBGDBCFBCHEDADDCDCBBBDEBDEBGHCGBEABFCGGEFCEG,False +362,22.0,28.0,20.0,25.0,21.0,16.0,11.0,16.0,BHCHFBFFBDDBHHBAHBADBAHBAHGCCFCBBDBBECAEFEDHHBCCFDCBBBEBHEBFGBHGDHCFFCFAHHAGAGDBFDGFDBCGEADBFBBAAFEDGEDFDAAGBAGAABEDDACBECBEFDAHCCCCGCEEHAEADEDDEDCEACEAEDDEDDE,False +363,11.0,11.0,7.0,6.0,9.0,8.0,12.0,8.0,FBADHHEHFGGCGAFEAFEGFGGHGHCCHCCBCABAEBAHDDCGFABEABFABABDEBDBHAGGFBGEEGDE,False +364,5.0,2.0,8.0,2.0,1.0,2.0,9.0,6.0,AHGACBAGHCGHGBEFDAFGACHCCGCDGCHGHGC,True +365,33.0,17.0,16.0,24.0,25.0,19.0,21.0,11.0,GDDGDDGBDBAABAFECGEDGEDFAGCACCFHCGHCDAADBACFCHEDAEHABGGHCEEEBAEFEDFDCFDHFDAFAGFBCDAFGEDDEHBEDBDCBHCAGFHFDACAGDABEABGABGAHCAGDAFFGEFDEFGFGEEEAEAAEAAEAEFBBAHBABCEGEDGAA,False +366,24.0,28.0,22.0,9.0,23.0,15.0,15.0,17.0,HEGHECCBBCBBFAEDHBFCBFBBFABGEGCFDCHCCBAAHAADABBBBAECHECEEHEEBAECDDAGDFGDFCDCGBCEBCABEABAAEHGCHEFHEDHFGGAGEHGCBBAFBAHCFEEGAEGABAABAHFHBCCCEHAEBBEGCGFFBHFA,False +367,22.0,19.0,28.0,25.0,31.0,21.0,23.0,26.0,HGHDGHDGEBCDDCAEEADEDEEHAHBDCEEBEFGAHAADGDHBHFCEGEDBFDEFEEBEBCEFCEFCBACBADHADEGDAHCCEDDEDHFAHECDDCBEFBEGBDCHCHAABAACCHCCHCDHAGCAGEBEEAFECHBCHGCGGHFCFAGGEDAFDCBECBEHDEFFGFDGFHGFGGFGFFBFHBCCGAGHAHH,False +368,19.0,23.0,22.0,14.0,18.0,18.0,13.0,20.0,GAHHDGFBGDBFFBHGADABEHCCFDCBDAGDBFBBFBBFBFFEFFAHCAFGAHADHEBFBAFBECCEBCDDAEDGEHBBBBACBAEBDECHEGFCHACFDBGCHHCHGEHCCHCGHCGECEAGACHFCHFCHDEEEEEBDACAAHA,False +369,8.0,9.0,10.0,4.0,11.0,7.0,17.0,8.0,GEHGEBGFGGFCGEHAFBBFCBHCFDCGEHAEGCCGAEGBBCHBHFEAFGBCGADGADEADCGCHGEBAEGHEG,False +370,14.0,14.0,22.0,16.0,19.0,13.0,17.0,12.0,AEAAGFACECCFHBFDEGEAGADCEHCECCADHDEGFGGCCGBHGBHGBAFDGECGECGHBDHBABFACDDEBFECFEFFCAFGEGEEGHGCBACBCBDABCGBDFEDEDDHDFBDHCCHCCHEADE,False +371,24.0,19.0,21.0,13.0,20.0,18.0,17.0,23.0,GEGEADCDGEHBDCBDHAHCEFCEFEEFCDFBEGAGFHGFCCHCCFFCFFAADAFCABBBHGCHDHEAAGCAGDABHHCHHCHGBEFAAFHAFHGHHGDADEABEGBCGCDBADEHHEHACDABGECFEFEEABEBBHBBABCAGCFGEFABHAH,False +372,3.0,3.0,3.0,4.0,0.0,2.0,1.0,2.0,DDFDDBCABHABACFGCH,True +373,11.0,27.0,14.0,16.0,27.0,12.0,14.0,25.0,BGEGGBDBADECHGHHEHADHDGAEAHEFHBFHEEDGEDECBHFEHEBHDDCEABEAHEAHEBEEBEGAHCHHCBBBBBBBCCGDFGEBBEFHFDHFDHFDEFDEDEHGEAEEFBBHBBADBCBCCBGFDGHEFABBGHCCCGCHH,False +374,3.0,9.0,10.0,10.0,8.0,7.0,11.0,11.0,GCGGBBHHCCGFDGFDHDDHFDBFEGEEBECDDAECCBBCHGCHGFHADHACBEFHEBHDBHDGGFGEC,False +375,23.0,33.0,18.0,22.0,30.0,18.0,26.0,23.0,EBDEBDHHGCCGCFGADGBCGHCEHFEHDEHBEGDDGBHGAHDAHDBCBAABCFBCHEFDADCAEBBBBHBAFBAEBAHBHFBCAGCFHDADEAFECEECEFBBGGCCGEHHBBHEDCAFAHEEFFEAGABGCDGBBGBDFBDFGDBEDBHFBGDDGAEBAGAFGEEBEECEABEHGGADGDGFHGFEAEHHE,False +376,26.0,12.0,16.0,23.0,9.0,18.0,21.0,30.0,ADDFFDFFDFFHCFCBFAGFBGHEDHEAHECHCABFAEAAGAAGDDDDCFGCAHABDEGFHBCBCADGHDGADGHEGHDGHFBHGDHCDEABHGEHBDADAACHHHHFHAGHEGHDGHDHHCCCAHDHHGGFAAAAFABFHCFGBHGAACBGCDD,False +377,14.0,10.0,11.0,6.0,8.0,8.0,6.0,11.0,FCEFBBABDCHECFBCGBHGFHECGCFAFAEFDBACADCABCHHEAHGAEBAHAAHAAGFDCBDCBDGAEHHEH,False +378,10.0,13.0,11.0,8.0,10.0,9.0,5.0,12.0,ADCHBEECEEADBACBGBBAHBGHCCHGBHCCACCFHCDBDDFFDFFBFEAEHABHDBDAFHECBAHEGHEGHEFBAF,False +379,26.0,14.0,13.0,28.0,14.0,24.0,18.0,23.0,ACEAFGAGABGAGGEHAFHDCDDFFCGHCDHAAAEFFEGABGAHHADFGDFBCAGCAGBACDDDBDDEADCCHGEAGEABHHFHCCBDABHFEEDGHBGBBHFDFCDFBDADDEDDEDHFDHFDHEDHAAFAHDGDBGEFFABAECAHHFFHFFHDFHFG,False +380,21.0,15.0,24.0,10.0,21.0,16.0,24.0,20.0,GBFFDHFBFGEFHHHHHECHEDEEBCAFAABGACGBCAECBCCBEDFCDGCEEEAEGAGGACDAFDCGBBGBBCAFFDFHBAGGDGGCCHEAFEAFCAFCAHCGGAHCACCAEGHEHEEGEEGDCHDHHGCEGAFHHEHACBCFGHBGBAG,False +381,15.0,21.0,27.0,23.0,28.0,27.0,27.0,20.0,BCBHCAFBBGEBDEDHCDGCGGCGDCFECDECEBCEBFEBFGCGGBGABFAEHCFDCHEGEFFFBGFECCEHCGFFGFHGBECCFCFAEDAGAHDAGEFFFAFDACCHCHBBHFCDAGDHGDEGDBDEHDHHFHFBHDBFDEAGCADBDDBDDEEFEEAGEGGBCGEFEEFDGHHCHFEHCAGGABCE,False +382,0.0,4.0,3.0,2.0,1.0,1.0,2.0,3.0,BCDBHDBHFEHGGCBC,True +383,1.0,2.0,2.0,6.0,6.0,2.0,4.0,2.0,CHDAEDGEDCEGEBGEFDEDGHDFB,True +384,12.0,14.0,12.0,10.0,21.0,16.0,19.0,20.0,GDHEBFGHDHCEABECBDCAHGAEGCEBCEHDEAEBHEBHFHHBBFFAFDCGHAGDCBFHGHCADBAHBGHBGADHFCHFDHCHECEECEGFEGEAGEGGEBFEGAEBAFFFEGFGGDGHFEHF,False +385,9.0,9.0,5.0,9.0,10.0,4.0,7.0,7.0,BCCBABGHBGDEGDACDBEFBHDGADGAEHHCFCEFDEBDBBDAAEEAEHADAGEHGFHE,False +386,15.0,9.0,11.0,11.0,15.0,15.0,12.0,13.0,EGCFFCFGCFHFDHCHCCHACHECAGHFFABEAHEFHEDDEBDHBDHBECDEADGFGFBGFAGFAFAHEEEBDCDGEHGAGGABAAGDFDBEABEHECFAA,False +387,17.0,16.0,9.0,11.0,9.0,4.0,15.0,11.0,DADCFEBAEAGCBBHBEGBDABFBDFDHCAFEGGEAGEACHABHAGHDGHBHHBGDEGHCAAGDAHACEGBBGABAACGACGBDGBDHBDCE,False +388,10.0,3.0,8.0,5.0,5.0,8.0,6.0,3.0,BDDGGCAECAFGAFCACADCEGCAHCADCBFFAFFHHFADEGFEGBEA,False +389,17.0,13.0,28.0,32.0,15.0,31.0,24.0,29.0,HGHCCHGBFDBGAAAAEDAFHHDEGFECFHGFCFFEHFDHGDCCFCHFCFDCFDGEHBEHGHHAACAEDAHDACGEGFEBHDHCFHEFHGFAGFACDACBHCDHCDCCDEFDEFDHFECDHDDCGDGBBCCFDHBDFBDFCGBBHAEHCDGGFHGHAGFBDBDCGFCGFDGDDFDHGHAFFAGDCEDCF,False +390,23.0,24.0,19.0,26.0,25.0,15.0,25.0,27.0,FADECFEGAEGHCFDCBGCBDDHDDHDDAGAHHAEBAGDAHBHGBFGBGGFGDCADCBHBEHDEAEHGEHDBHGBHEBDGBHECAEDADDAEHFFHFHGGCCHHEFECCGDEACEHHAHGAFAADBBDCBGABDACCADABFABEHFEBEEBDDACDEEDGGGGBHGBHCFGCFHFBHCBEGEE,False +391,4.0,5.0,5.0,5.0,10.0,9.0,7.0,10.0,FGGFGCEGEEHHDHGDCEDAHBFHFGDFEBHBHHAHFCCFACFGBFEEHEEDEAB,False +392,2.0,1.0,3.0,2.0,5.0,3.0,4.0,3.0,FBGCCGDCAHEFHFDHAGEEGEE,False +393,32.0,34.0,23.0,23.0,23.0,22.0,17.0,26.0,AABCCBCADCAHAAEFAFBABBHCCFBFGDHDHCAHFGBBCCBHCBHBFCDFBHBEABEAGEDGECBEBHEBAEFHEBEBDHAHHBGCCFDDFDFBDHBGAAACEACDACHADFAGFAGFHGFDFADFAHEAEEBEAGDDHCDEFDBHCGGDGDAHABHEBHEBEEBEHFABAHBGEBHCFDGFGFEDADCACHACBGBB,False +394,10.0,5.0,5.0,10.0,12.0,9.0,5.0,11.0,DCDEADHACFADFADABDHGHHDAHGAGEEBEFFCFAEDAGBAEBCEHDBHFFCEFHEHHEGEEDHF,False +395,9.0,8.0,7.0,6.0,6.0,3.0,2.0,9.0,BAGBECDECDCHEAHAFGBFHBAHDHHAACAACHHFHBDDBEEAEDBCCB,False +396,28.0,25.0,16.0,17.0,19.0,17.0,23.0,14.0,FBGFAAAHBHHGFCGDGGBGGEGGEFCEHCDGBBHEACEGBEADCADGEGHDGAAAAABFABFADFCCBHCADEFGEDDBDACAABAAHHHFACFBDAADBAGBGEHDEDBBFBBFBBCEAGEBHEBHEBEFBCFECFEGDGBAGDACDHCFCFGAGAE,False +397,11.0,7.0,11.0,10.0,5.0,9.0,10.0,7.0,BCHBAHFDBFCHFCDDBHGAGCHGCGGCGGFGEAEECDDFADEBFCHDCHBGABGEFDCFDFAAADAACA,False +398,21.0,30.0,21.0,28.0,27.0,13.0,18.0,24.0,CBDCAGAAEHGBHBHHFHHAHHCGHDBDABFBEHDEBCEDFDCFDCFBCEDCBAEBEDBEBBABEDGFBGFEEAEBGHBGCBACBDCEECBDCDDCAAGDGEAGEAFEGEEBEHFDHDGCEBFEBDGDFHAFHFDHECHGCDGHEGDBDBHEBHGBDAAAAEADDDCABHDCHCEHCHGBBA,False +399,8.0,12.0,5.0,5.0,7.0,5.0,5.0,13.0,HHGHBAEGABBCBBCBBCFBCBHADAAFBAEBEBFHDECEEFHGAHGHHDFHDGHAHHED,False +400,7.0,6.0,11.0,5.0,6.0,14.0,10.0,3.0,AEFAEBCFDCFCFAEFCGGCGECHFGADCBDFGCHCCABCAGGEFHEFGAFBFBGFDGFDBF,True +401,5.0,2.0,3.0,1.0,8.0,3.0,7.0,1.0,BAGCFGEEAEBHEGFAGFDGEEGECAEGAC,True +402,7.0,14.0,22.0,10.0,18.0,10.0,12.0,15.0,GHECCAABBCBBEEBEGBDCEECFGGHCHACHAHFBGGCCCCHCEFCFDCHDCHDFHECHACDBCBAEBDEBDGGEGHDCEGHECEECEEHBEHDFBFBAFHDFGFCG,False +403,14.0,14.0,19.0,22.0,20.0,22.0,14.0,19.0,ECCEDFDGEDEEBCBHDAFBAFAAECCFDCEBBEBDAHCADCFDHEBFEDFEFEGFEAFHAFHGCHEEHDDFEDFDCFDCFCBAHFAHFHHFBDFDDEHCGGBGHBAHCAGCEGAHBHCGCEDEFDFGDHGFCGBBGCHGHDDA,False +404,9.0,11.0,17.0,12.0,11.0,7.0,12.0,10.0,BCBDCEGCECEGCDCCDGGAHGEBGBHCFCAFHAFHADEAHFDHEBCCDCCDCBDHEDHADBAHCHDDGBEGFGGBECFEFEGBAGCAB,False +405,5.0,5.0,3.0,4.0,12.0,4.0,3.0,6.0,DBGAEGEEDAEHAEBBEBEEHFDCBEFGEFCAFCEHHAHEDH,False +406,15.0,17.0,23.0,27.0,15.0,22.0,16.0,20.0,EFCEGEFDBFHCCACBDDHDCFBHFHGFCECAEABGBGDHCDBCABGADFDDFECCACFAEFHDGHDBHDAHDHHDHBFEFDEADFADBDCHDEHFCHFGGFHGHHEAACAFCFBDDCEBCGBDGDEGDBGDHFCCFDEHCBBCBGDFGAFEAGC,False +407,11.0,16.0,12.0,20.0,16.0,15.0,13.0,15.0,HBGBDGBDGFGEFCCHCDHCDHFFCDBCFBEEECEFCEABEHDEDBEFHFDAFDBHBBHDACAHFAFBAEBDDDADDAFDGGGEEGHEGDFHBFHGDBGCBGBACDAHHCEAEEDHGF,False +408,16.0,12.0,20.0,13.0,15.0,13.0,22.0,14.0,HACHAGEAGFHHDDCEDCBFEDFEACBBFHBFHBCGBCACCBDDGDDBEFEGGHDBDDGGFHGAHFEGAEACDACGABAAHEABECECCECGGCAHFAHFGGFEECEHAFDGGGGCFHCGGCGBC,False +409,4.0,7.0,9.0,5.0,9.0,7.0,4.0,6.0,EFCBHCFAFFACFDHHBHCBGBBGBCEHGECBAGDCEFCDFCDEEHEEAED,False +410,12.0,11.0,9.0,6.0,6.0,6.0,2.0,5.0,DDCDHBBABBACFACEBDEHDHBFBAFBAGCAEAEEFHCBCCFHCAAEAABDABGFC,False +411,10.0,13.0,4.0,12.0,8.0,3.0,7.0,11.0,BBHBBDDDDDEEAAHAAHBAHGEHGHHAEDEEDACDBBDGCDBBABHHCGCFGFEGBAGBFDDAEHBH,True +412,2.0,7.0,4.0,0.0,2.0,6.0,5.0,2.0,BGBFGBFGBCGCEACFBHFEABHCBGFF,True +413,28.0,23.0,16.0,19.0,25.0,12.0,17.0,19.0,BHADEAEEHEEAGEFBBCDDAGHHGHAEBDFBAFBAHAEHBECBDCGDGBFGEEAEEDBDDBHDEHGECAACGACABCABFABCADEAHEDBCGFEBFEADEBEGADAAFAFHADBACHABHCCDCDBFABGAEGCGFHACDEGHHGHGDHFBHEBEGC,False +414,4.0,13.0,10.0,10.0,10.0,2.0,11.0,8.0,EEGCECCGBBGBCGDEEAGEDBHCHHADHDBHEHCFBDBGDBDDBDEADEHBCAGCBGEGCBGCBGFH,False +415,13.0,21.0,20.0,13.0,22.0,19.0,15.0,24.0,HFDBGDBHHBCCFHHFBHFBHFBHACEFEHFCBGBBFBHFDGECGFCAABGCFGCHHBHHEGFEABCBECEECGDCHHFEDAHBAEEDECDHDGHFGHFAECAFBAGBDECDCHBHHDCEFCAFEHEEGEAGEAFEDEBACBDCBGG,False +416,21.0,17.0,11.0,9.0,12.0,14.0,19.0,7.0,CGHHGBDBAGBAGBDGACGAHFFBFAGCACDAGAAEAEFCCAEFBCFGCAACGEFFBDAEDABDCEGEFCEBBHFBHEBHEAGGBGFAHFEBFBBDABFAGGAGGDGADE,False +417,6.0,8.0,8.0,1.0,1.0,6.0,7.0,5.0,BADAECHCCHCCHAAFCGFBGBBHBBGFCFHCGGBGGBFFAA,True +418,11.0,22.0,19.0,15.0,20.0,16.0,14.0,28.0,CCEHHDBHECHCGAGDCCABHFHHEHDEGBEGBDDBDEBHBBGFFCFFHBDHBCHBEHBAHFFGFCDHHDCHBEABHDBHCBAAEFDCBCCDFHEFGBDABGFBCADEFDGFAGEHGBHCBCGFAAHEEHEFHEGEEHEEHCGHC,False +419,25.0,19.0,13.0,15.0,18.0,30.0,15.0,15.0,FHCDCFBEHCABEAFAFHEFDGFDCDEHAFGAFBDBBFBBGBAHFAGFBFFBDBDDEGFBDEBHCBFCEFCEFAECAEFECGADBABAEHFDGFGGBGFBGDAAAHAAHDFHGCHFCAFEAEEDECDHBFAGHAGFEEFAFFAFAHCAHG,False +420,5.0,4.0,3.0,9.0,10.0,5.0,4.0,4.0,DEBDADFEFCEHEABEAEEFEDHGDHEDCFGCFDDGBDGBEAAH,False +421,21.0,22.0,19.0,21.0,16.0,23.0,24.0,24.0,BGGDDGBHHHHGHHDAGFAGFBBFGGFGEHBAHECFACAGHEFCEADEAEBAHBGBBACDACDHCDHCHBCDBDDGCFHHFHHAHEEHCGCBGAADFBGEGFCCFCGFDHHDHCBFDAADABBCBFCFGDECBEFDEGDEDFABFADFGBFGFAGFADHHEGABCFBGEE,False +422,5.0,3.0,3.0,1.0,0.0,2.0,1.0,4.0,ABCABCBGAHHHFHAFCAD,True +423,8.0,5.0,10.0,3.0,2.0,6.0,4.0,7.0,CAHCAGAAEDGFCGDCFHCAHCAHBBDFAFFGBFBBCCCHCEHAH,True +424,4.0,2.0,3.0,3.0,3.0,5.0,4.0,1.0,GDFGCGACDACDEBFEGHEFFAAFB,False +425,20.0,29.0,28.0,22.0,37.0,21.0,18.0,23.0,DCDEFDAGCHCHFDAFEFFEHDEDBEABEHBEBFCBEDBCDCCEGCEBCEAHDHHDAHGAHBBBFABFABACBADHEEHEEAEAAEACDCHBCEDEEBEGGEBEFDGCBBBAFDAFCAFCHEDBEDGECHBHGFGECEDGDFECFDCFGHECEEHFEBCABCADEAFEGBBHBFGBEHCCHBCGBEFCHHCHGGGGDF,False +426,3.0,6.0,6.0,5.0,11.0,8.0,8.0,8.0,ECEBAECEDDEBDGBGHDGEBGECGFHGFHACHFGHFCFBEFHHBHEADEFGCFE,False +427,9.0,21.0,17.0,17.0,18.0,17.0,9.0,12.0,BHBBHBBAFBCCHEBDECFECDEFFGHCEFCAFAEHDGHDBHABEEBEEDAECBDCECABDAFDHDGEDBBDBFAFFCCBHCDHDBFDGFGBFCHACDBCGGDGGCBFFBFEEFHECEED,False +428,13.0,9.0,6.0,7.0,7.0,9.0,7.0,6.0,HDAAECHEGFFGFGCFHCBGAADAADAAFABFBEEAFFBBCBBEABECGHDGEDGDABDAFHCH,False +429,8.0,15.0,19.0,18.0,20.0,20.0,16.0,22.0,FGDFDDFHDGAFGFHEBABCDBHFGHFCHACACCECEACEBCFGDBHFEHFBHGHHEHEBGEAFFHCFDEFDADDBDGHFBDFBCFBGAHFBECHECBECHECECCEDCHGEEGEGFDFEDBEHBHCDGDHCHHGGDG,False +430,13.0,25.0,20.0,21.0,26.0,17.0,24.0,16.0,EFFGFCDFCEHCGHDGEECAEBBEGBECFEGHAADDAFCAFCBCEECFFCFCAGDACHBHHBGDCGDGGDEEDBHHGCHEDBEGEECEEBEBBDBAEEFDGBGGBDAEDHEFCGBCGFCGAHGFHDBGGBFBFFHEHBCDBADCEDEBBGAAGHBGHBDBDD,False +431,13.0,21.0,18.0,12.0,10.0,10.0,17.0,15.0,GAFBBBBFHGFAFBGCGGBBCABCAGDHGDHBCHBHBAHGGHEGHDCDBCFBCGECAEDDHBAEBDHBDHBDACECGEGGDHADBEFCDBGACEAHBCFBEHAEHAFGCCGCCFFC,False +432,14.0,11.0,9.0,15.0,14.0,12.0,12.0,18.0,DFAFFAHDHEDFEHHEDHCFHCECBABBDGEFGEDCDCGDHHFCHFCGGCEGABGDBEABAAHAEBDEBHEGHFGHDHEBADGADBAEHCEHDDHBFAGAAFFGH,False +433,16.0,16.0,12.0,20.0,13.0,18.0,9.0,14.0,FDCFDADDBDDAHDCBDCDDCDAEHAFAABADBECFAFBCFADAGCAGCDBAFCFFEHFHBFBEHGCGGDFGDABDEECGGDFEFBHCBHBEHBEABEHBAHGAEFBEHHHFEHFDFD,False +434,15.0,21.0,15.0,6.0,12.0,5.0,12.0,17.0,CBBDBGABGCDGCEADBCCADEFCCAHCHCDHCAHCHHABHBBHABEFCGCBGAFAAHEAFGAEGAHGEEGHEGBFBEECHEBBAHHCHDBHBBHBBABBGEG,False +435,0.0,0.0,3.0,2.0,2.0,2.0,2.0,3.0,CHDCEDEHCGHFGF,True +436,22.0,21.0,21.0,13.0,7.0,14.0,20.0,13.0,BHBGDAADEDFGCFGDHGAGGAFDCCACCHEADBCFBCGBFABEHDCHCEGBGDAGAADCAHGHHGHFFDEHAGAGGABCAFAFFACHACGBDGBDCBDHAGCFEBFACHBCABCGFCAFGBEBBCBBCBB,False +437,18.0,12.0,15.0,15.0,9.0,15.0,19.0,9.0,BEAEFBCFAADCBFGDGGHFCADAADGADHCBHDGDBGDBGDCGAHEFHGFAEBAHBADGCDGCGFCHFDEFEHFCAAAFBAHAEGDEGFEDCCBCGBFGBFGACGCCADFG,False +438,9.0,15.0,11.0,10.0,6.0,5.0,12.0,8.0,CBBCECABBAHBHBCHGGEGGDAEBEDCDFADBGDBGDBGBBCDGABHCFGBFGHFGHFEAAEAABHDDCGCCDCH,False +439,21.0,34.0,13.0,20.0,9.0,14.0,18.0,22.0,DBGDFCCFEAGHBHHCHHCBHBGHBDABCCBAFBAGBDCBDBBGBAFFDHEHGCBACBAEFGHBGAFGCFBAGHAHHAGHGCDEAHABHBDFEDBDDADDHFBHFBEABEABADBHFHDBABBHBAEBGCDCFHGGGBBGFDGDABDABDE,False +440,5.0,7.0,4.0,9.0,2.0,7.0,1.0,7.0,DEBHHHHHHDFAAFGADHABBFFDFFDBEDCCCCFBDDBDAB,True +441,9.0,3.0,11.0,9.0,5.0,3.0,13.0,6.0,GCHGCHBCDDAEAHEAGAGGCGEAEHACDFBDBDGCDGDGGHGCFGCAHCACDGCAEFD,True +442,26.0,15.0,9.0,16.0,20.0,21.0,20.0,20.0,EEHEFAFDDHDDBDEEFFEDFCHFAAGHAEHADBAGHAGBADAAEABCGBCBBFGCFGEFGEFGHDEAEEAFHFGHDGFAGACGCHBCHEAHGABGBGADGFFGEEBCFDHAEBAGBADAABBHFHHCEEFFEDFHAHHAHADDGFG,False +443,5.0,11.0,13.0,10.0,14.0,14.0,10.0,14.0,FCEHCEHCEDGDBBDGEDHEABEFGAFGAFCCFHFFHFBAEEGDFFAHECHGCHDCHBGFEHFHFFBBCBBEHCHHBECDEDBEDCGGGDC,False +444,9.0,3.0,12.0,6.0,9.0,11.0,10.0,6.0,GACGCGACGBHABFCEFCEFCAFGFEGDCFBCHHHHGAAAEADCDGAGEEEEECFFCDFGDFCDFH,False +445,9.0,10.0,13.0,13.0,17.0,11.0,15.0,15.0,DGCDBCDFEFHEHHEDDEGCCFCFFCGDEECEFHHFAHFAEDGGBBGHHGCHGBACAAHEEHEEDGGDGGDGEEFEBGHBCDCAACAHDHBFEFCEDBHBBAG,False +446,4.0,1.0,6.0,9.0,11.0,4.0,5.0,7.0,GACEFGGACGDFDECDEHDEHDEHEEDAHDCDFCDBEHAGFCHEEHE,True +447,26.0,19.0,18.0,11.0,16.0,16.0,12.0,21.0,EEHFFHCBABHABHAEHAEHEFFGFAGHBHAEEAEEAGAAGCCGABDACECFHGHHEDHCBHCBHCBAGDABDCHAHEFHFHHDDFBFFAFCACABEDFEDAGDBFCBDAGFACEACAGHABBFBBEBACCCGHCDBAG,False +448,6.0,5.0,7.0,6.0,1.0,1.0,3.0,5.0,HADHAHCACGDGBDGBAECACBABDCHDBHDCCF,True +449,11.0,2.0,6.0,6.0,9.0,16.0,8.0,5.0,AGAAHAAGFDFEEFBEDGEGEEFEAFCCDEDFFGFFGFFCFAEFAFHDFCBHADHFGHACCAG,True +450,11.0,4.0,8.0,12.0,7.0,9.0,7.0,8.0,FDEFCADCGCEBAHBGECHEFHCDACDABHGBFFDFAEFAEADGADFEDHCAHGDHDFCDAGDAGH,False +451,31.0,20.0,20.0,33.0,22.0,23.0,32.0,17.0,BCCAGAAGFAGCEGDBGDACDHDHGFBGBBDBFGBHBAHECEECDEDHHDFADFEDCEGHAFBCCBFADGCBADDFEFGEHGEFGDHECAEAGEDDEBDEADAADBCBGEDHDDFCEAAHBGBGFAGFDGFDEFEGHBAHFAGFDGDDFDFABCABCAFCAFCAGCAHEGHGDAADAGEFGHDGCDGBGHCFAGDEGA,False +452,6.0,6.0,6.0,10.0,8.0,9.0,9.0,6.0,AFEABEBDGBAFEDHGFHGEDGEHCHAGHECHCCFDADDFEDFEBAGCFGFFGCBGDBDD,False +453,13.0,18.0,14.0,23.0,17.0,19.0,19.0,12.0,DCGDCDDCADEBFFBFFCAACDACDCCABCDDFDFAAEGFHFADCBGCDGEDAFGGEHHEFBFFBFFBGFCDFCGAGDDHDDHFEHGEBGHDGHAEHBGBDEFCBDDEABHAGEBEEBHEDEGBHGBFGBGEEGB,False +454,18.0,22.0,18.0,14.0,25.0,31.0,12.0,21.0,FHADBACFDHAHHDGHBFFFCFGCBGDHFFFGFFGFGGFAHCHEEHFHDFHFFHFAHAHEACEGEEBDEDFAFFBFFBFBEFDCBBEAEHDFDEEEBBGCBFCFCBGBBFEHGCDEHDECDECBADEAEEACEACECCABBECBECBFAFAGHEHHABHAB,False +455,8.0,7.0,7.0,9.0,13.0,7.0,12.0,7.0,AGEBFEADAAGFABFHDEAFFCGFDEHGABGCBHCBGBDHBDFDEGCEGCEDCEHEDHGDAGEHEEGCEG,False +456,26.0,25.0,17.0,12.0,23.0,17.0,8.0,10.0,BCAFCEBDBGCAAFAAFGCBEAEDDBADBADCHEFFEADEAEEFEEGAEGEHBEGAFHAFHDFBBAEACCAECBBBBBFABEABDBBDABDCEDFECACHFHAFHGHDCCAGFEEACEABFABFBEFAEBBGHBCHCC,False +457,17.0,13.0,15.0,8.0,13.0,12.0,8.0,11.0,HFCEBGABGABDAECBBCBBEBEEBFEAADACFHFEHFBACAACDAFHHFAHGAHAAEAHGHCGFCDFDAEEBDECCHCCFFGBEGCDFCBCAEDHG,False +458,4.0,0.0,3.0,1.0,6.0,6.0,4.0,0.0,FEEFEFFGCFAEAGCAGEADEFGC,True +459,21.0,25.0,18.0,16.0,17.0,17.0,23.0,17.0,HDAGCGGBBGBCEDCBBBEGFEGFEGFAFFCGFCBECBFFBEBBGBFABCAFAHEHEDHGDCCEAAGAAGBCGHCBHCAEDHHDFFDABEFECCABHABEDBEGBEGDGDFGAFEAGCDGCBHHDHCAHGABFDEADBADBHGAGAHFHGCHDB,False +460,10.0,14.0,5.0,9.0,15.0,9.0,9.0,8.0,EDEEGEAGEGBEDBDFGDEABFAFDAGEBBABDAGDBGFFHAEHDEABGBHABEACEFBDFBCHGCEBCEBEHHHFHCF,False +461,5.0,3.0,5.0,6.0,2.0,12.0,7.0,4.0,CEAFFGFFGFFDFHDFBDADACCGGCABAHGFBFFDGHDGHEFC,True +462,6.0,6.0,14.0,9.0,5.0,9.0,18.0,19.0,FGCDHCHHGHDGADGECGHCGCGHCEDGEFFHHFHFGBAHEFGBCGHFDHFHHCGHCGHEGBCCBDAHDHGBHACGCGFCDABDAG,True +463,3.0,5.0,4.0,8.0,5.0,3.0,5.0,5.0,DGAFBBFAHGEGGEGBECECCAHHDDDEDDHFDHBDCB,False +464,8.0,5.0,4.0,6.0,7.0,4.0,8.0,3.0,DACBACHAGHBEHDEFEADGGCFEDGEBGEAGBAGFDGFDAAEBC,False +465,13.0,13.0,10.0,12.0,11.0,18.0,10.0,10.0,DFBGFDFFDGBBBEDGEDBECEEDFHAAACAAHHHHHBGGAAAFHACDACEFFHFFHAGCBEFBEBAFGAHGDEGFFBFDBFDECCECCGBCDBFDF,False +466,1.0,7.0,5.0,6.0,4.0,4.0,5.0,8.0,DHBECBCDBGDBHDBHFHECAECFFGHDGBBGHCGHDHFE,False +467,8.0,10.0,7.0,7.0,13.0,10.0,14.0,7.0,GGBEGHAGEGBEDBCAFFBHEEAEFBEGCFGCFHBFEGFEBFHFCHFDGDDGHDGDCHAEGCEGAEDCEBAABABG,False +468,7.0,9.0,14.0,4.0,4.0,10.0,8.0,4.0,FECAECBDFBGFCCFECFDCBGCBGBFDAHGAFGBBEBCHBCAAHGAGCCCFHCFGCDAF,True +469,11.0,8.0,10.0,17.0,9.0,15.0,9.0,16.0,FHDFDDEACFHCFCAHDEHAGHACHDGBAGBEGBAGEHHDGHFEHADHAEFAGGCFECFBCDGDHHDADBCDBEDFFDFFCCBEDHFHAFHDFDB,False +470,1.0,3.0,1.0,1.0,2.0,1.0,2.0,3.0,CHADBEEBGHBGHF,True +471,17.0,15.0,26.0,18.0,19.0,21.0,23.0,27.0,GFFCCCHCDHAGAEGFGCBGCBFCFFHDFBDCHDGHFEAFEAEEAEGDHGHCGABGDCGDGGFFFACHBEAEEDEAHFAHDHHGCHFHHGGHBBECGECEEDAHCACCBBCFBCHGCHACFDCEDAHCAHFFFDABEEBCBAHFCHBHBGDGECGEHDHGDHGDFD,False +472,2.0,5.0,3.0,5.0,4.0,6.0,6.0,2.0,EGHFGBFEBFEDFHGCCFEABDADDBDGBGCFG,False +473,20.0,30.0,26.0,33.0,27.0,26.0,18.0,15.0,CGAHFAGFAFDBCDEGDEHBEGBEBFDGFECFHBFHBEEFEECCEFEFFHCDGAHABDFBAGBADBADBDGFGCDCABGAEGDDDDACFACEAFEBEGDCGCEFDEBEEDFEFFDABDHBDEBCHBHHFDDBCDFGDAGHBDABFBDDDFFBBACBCCBCABCACCHGCBFBDDEEBCGDCGDCEDCHFEHEAHE,False +474,19.0,17.0,14.0,18.0,11.0,17.0,20.0,12.0,GAGCCFFCGFEDEBFFAFCGDHGEHGEHGHGFDFAAFDADDADCACCBFBDGBGGBFEBCABDAGHGBDBBHFGEAGCDGFDCFCHFAGCBBABBABAEBCFCDEDHGHAEHAEDAEDGFDGDAHHAB,False +475,29.0,21.0,29.0,16.0,8.0,11.0,32.0,19.0,GGHBGAGFAHFBGAHFBHGBHGCEACHGBAAAFHHFHHCBGCGAHBDCCDGAAGHHDBDCBDFBDBEACAFCEDCBGABGAFEACGACGCCGBCGHAGADEAHGDCGCBBAFBADCGBEGBEGBAGCGGAGABCCHCDACGHDGEAHAADFCCHACDGCDGCDFC,True +476,1.0,0.0,5.0,0.0,0.0,3.0,1.0,0.0,CCCGCCFFAF,True +477,12.0,12.0,12.0,10.0,3.0,21.0,15.0,7.0,FDFAGACBDCBGCEFEFDGAGGBBDBBAFCADCADCFCGFCFFHFFHBFCCDAGAAGBFDCFCAFHDBBGHDGHFGBFBEFGFFAHGAGGFH,False +478,17.0,16.0,18.0,22.0,16.0,25.0,17.0,21.0,ACEFGEHAECACCHBGAFFBCFECADCEFAEDEFAECBCGBCHFGHGEBAEAADHGDGAFGDDCEHCHAEHDEFGHHHBHABFABFHCFHCFHCFBDFBHBEFFEDFCDBGDAFDGBHFBHAEDCFHBDDGADGDFCDFGDGBDGDFHDFHG,False +479,10.0,7.0,13.0,9.0,7.0,6.0,9.0,3.0,HGCDGCAGAEGAGCCBCCFCEFEAFEACGGCHDABDECHFABFEBEBADBDDBAACGCFDCDDG,False +480,1.0,0.0,4.0,0.0,2.0,0.0,5.0,0.0,GCEGEGGCCGCA,True +481,21.0,16.0,14.0,17.0,11.0,10.0,25.0,16.0,FDGEEGBBDHAHGDHBHGBGCBCCFACEAEGAHHDHBGFDGADAAEAAFHCFHDFABGCBGAGGADCHDCECEDBDACDAHDAGDBHHBAGFAEFGBFGBGHAGAAEDCBCEBHEGHDDBGGGGCAGCFG,False +482,12.0,17.0,21.0,17.0,21.0,22.0,20.0,24.0,HCBHEEHCEHCBHADGBCGBEEHHFGHFDHFCHCGHGGHBGCBCHGDDACDFFFFFGBACFECGCFHFAEDHDDBDDHDEGDECAGCAGHAEHAHFEFDEACCDGGGFGCEBCEDHFCHBHBEHDDABHFFFAFFBFEBEBBGAEGCEGCEBFE,False +483,19.0,21.0,17.0,13.0,22.0,21.0,20.0,24.0,GDGGEGFHAHAEHADHCEHDAACCBEFBEAAFFAFGHHBHDBFDFFACBGDDGDHHBACBFDHFDBFEFFGABDACDFFHGFCCAEBBHGBHBBEBGCDGCHGCHEFHEAHEHHGACCACGAHHEBGECGACFEEEBEFBCFEEGEHGEAGBFHBEB,False +484,14.0,17.0,19.0,19.0,23.0,9.0,30.0,14.0,DBADEECEEGGGCGGCHGAEDCGDCDDHDGGDEBHBBCAHHADGGGEGCECCACHAGHAEDABCHGGHAGDADBEFHHFBCEAGAGGDGGHGGACFFBFGCFGBBDBECBEDBGFEHDEBDEFHEBCEBAEGEECEGBGFCDECD,False +485,23.0,20.0,17.0,18.0,15.0,7.0,16.0,20.0,ADAADBBFAFFAFAAGCDHCHABGABCAGHBGHCAHEECBECGDHHAHDEFBGDGDBGDBAAEABGHBDCECCBGGHCEHBFABFABCACAECBCDDCBEEADEADHHDHDDGEHGEHGEDCBDCHAAGGBHHBHE,False +486,19.0,15.0,16.0,14.0,11.0,13.0,25.0,19.0,GDCGHFGHCBDBAAAAAACAGHBGADDCCHEGBCBDAFDBGDBDEAAGAHBAHADCDDEHHFHEAGCGGCGGBGHCGCBGCBDCGGGFEGBEDFHCFEBFEAFGAEGCFGCFGDEGAHFEHABFFBHHHHHH,False +487,17.0,28.0,19.0,19.0,12.0,13.0,19.0,22.0,DBDEFAHAGFBGHEGHDDBBEBHEBHDCHFEHGEHGBBACBAGAAGEBBHBDFBDFBDCCHCCAEBGDGDCEBCACFAEGAHDFCCBHCEHDEGCBGABGBDFHCFDDFDBFGAGGFHBCHCABDABHAHCAGCHGBBBCBHFDHADHG,False +488,11.0,5.0,10.0,9.0,17.0,10.0,8.0,12.0,HFEBAGAEFADDEHDEHAEHDEHAEDEEDGBCHCFECFBCHGCHGEDBEABGAHFAHFHEEGFHACECCADEDCEFCAFGFG,False +489,15.0,27.0,19.0,19.0,24.0,16.0,18.0,23.0,GDHCDCEEBEBBHABHFBGFEGDDHDFACCAGGADEBDEHABHAFHGBHAFCAFCBFCFHCHDEHDBBFABDEGCECHDDDDGEAGHAFHFEBBEAHCAHFGHABEFEHDHHDCGBEHBEBCCBGDGEBGEBEECEGBECBEBDEBFGHABHFFDGCCGBC,False +490,3.0,2.0,6.0,3.0,7.0,0.0,1.0,4.0,CBCEHEADEACEADEDBCGHHECHEC,True +491,14.0,16.0,16.0,14.0,17.0,13.0,22.0,10.0,FADFCGFCEFCEBCGBCBBCBBAFBGGBGBEEEFDBBDHEEHGHAGHAGDDGBEAAGDFCHADHGDHGHFBDEDDEFECCEGGGGGADGCBEEHDCGCCGABHDBFAFEEECCAGAFGAFCA,False +492,26.0,18.0,20.0,24.0,26.0,19.0,29.0,28.0,DCADFADCEHGDGGFGEAHEHHAHFCCCGHBAHEAECBBGGBHGBHDBAAFECHEBHGFHCAHDAHDAHACHCGHCAAEGGGDBGDGGDEGHHDCGEEGEDAEDCGFCDFEFFADHGBCABHDBEGBGBHCHFGDFEFFEBBEDBEAAEFEBFGBAHAAHECDGDDFDACCAFAEHGEDGEDCEHFGHFA,False +493,1.0,0.0,2.0,1.0,4.0,2.0,0.0,0.0,ECEECEAFFD,True +494,11.0,16.0,14.0,24.0,25.0,15.0,20.0,16.0,HFCEDHDDCEGCFADBEDCEDAFBACGFFGHDDDGBDFEAFCAFHDFHEFBAFBDEBEHCEDBHDGHDFAEFCECCBGGBFDBCDHAHBGEBEEHGGHABDGDGGDHADGAEEBFECEECGEGGEBEEBHGCHGDHGDEDE,False +495,15.0,21.0,13.0,15.0,18.0,25.0,20.0,12.0,GFGGDGBFFFDCCDGCDECAEFFFHCECCEDEEAEEBEFHDHBGGBGGEGHAGEAGBGEAFAHFACFCHGBBGBBCCDEGDFFFFABBBEBDAGDAHFACFAFDABDBBEFDEFAFBBFBBFEHHGHDDHBFGAFHEGC,False +496,14.0,17.0,8.0,12.0,24.0,10.0,23.0,11.0,GBFGBDGAFGBGEBFEHDGAFEBCGGGBABDAEDGEFBAFHEFHBFHEEBGEBAEGGEFGEABAHBGHBCFGEGCAGCEHEGHDDEBAGCAGBECDECDEGDEGDBDHEEHAEHDCAAE,False +497,8.0,11.0,13.0,8.0,7.0,15.0,9.0,16.0,EHBHFAFCAGEGGCCGCAGBAGHDFFCFHBHHDDHFCAECHDBHCBHAFFDFEHCGDFGAFCAFCGFEBBCBBCFHDHEDHFBHEBH,False +498,3.0,6.0,8.0,3.0,3.0,7.0,4.0,5.0,CHECBEABACCGCBGFHFFBGDBFDAFDEFCGBCHFHHC,False +499,7.0,4.0,9.0,5.0,5.0,8.0,3.0,3.0,ECEEFHFFACFAHAABEABDCCGFDGFCCFCCFGDABDCDEBAH,False +500,7.0,8.0,5.0,8.0,4.0,3.0,2.0,4.0,CAEFHGBDDBDDBDDBCGBCFDFDHCAEAEHBEABAAHACB,True +501,22.0,26.0,22.0,26.0,16.0,25.0,21.0,27.0,EBHCGHBFHBFBAEEAHFAHEADFGDFBFHCHCCHGAAAAAHAGBBBDBCHCEHBHHGDDFBEFDECDBFFHFFDDDDDFDAACHBDABDHGCEGCGHFGAFDCFGCFGBBGFACDAGHFGHEEAEEAHHBDDAABBCBCDDCDCGHFGHEBHABGFCGCEGCBCHBCHDGFFBFGEFDEHDBAD,False +502,10.0,11.0,12.0,13.0,8.0,15.0,13.0,13.0,GFHHEHDCHDEFDADGCDGBDFADFHFACFACACBFCGFCAFEECBECBACAFDEHBGGAAFDGHCBDCBHGBHDFHDHGEFGFHGFHDBEBGGB,False +503,5.0,6.0,10.0,4.0,4.0,8.0,9.0,0.0,FEDCEDCGBGGBCFCFEDBEGAACABCGCCGFFGFFDAGGBCABCF,True +504,7.0,14.0,10.0,11.0,12.0,9.0,6.0,15.0,BDBBGBFCEDCHDCHEFFECHGDEEHEDHDBCDHGABFABFBBDBBCEECHEGFAHCGFBHFAHFAHDCEAHBDCBDHGEHAEH,False +505,21.0,9.0,16.0,11.0,15.0,16.0,15.0,15.0,DFAGEAGEAFCCECCECFEGFHGDHAFBCHEDHEHBEAGFCHDHGAHFFCAAGAAGAAGAFEDGCDFHGEHFEDFBDCAHGAHBABEABGABEDFFHGFCEACHADEBCCBGFDCCHA,False +506,17.0,15.0,12.0,11.0,15.0,5.0,18.0,14.0,BHGDHFBGBBABHAEGAEDAEAEDBEDGCGHADCFEHAGHAHHAFADCBBGEGGBDBBDEHHHGGBGADGACHCEGCEHAABFAEHAECAECEECFBCGDCGBCGDG,False +507,23.0,16.0,18.0,17.0,15.0,30.0,19.0,16.0,CAHCHFAHFDGFDGEHAABDAFCAFBAGBHGHCDBAAFGFFGADAHDGDGGFEDFEDCCCCDHGFFGFFCHFAFEAFEFHGBEFEEFEECDBGGHHGHCEHEGCADCEBAFBFDBGBCHBFFBFFBCDBDGAGFABEAEAAFFCBFCADCADHA,False +508,2.0,2.0,6.0,5.0,8.0,2.0,3.0,4.0,AECAHCEDEEGEDCFFCBECDDGGDHECHEBH,True +509,10.0,15.0,13.0,10.0,20.0,25.0,8.0,14.0,BFFFFGHDGHBEECGECGEHFEFAGBHGBEDEGAEAHHFFHCFCFFHEFADFBCEHCEGFAHFHEFECBDCBDABDCBFCBDHBEFCEFCHFEBEBFEAFACFHFBAFEADDDBE,False +510,9.0,6.0,15.0,8.0,8.0,15.0,8.0,4.0,CGFCHFDFCDFADGADECCCFCAFBFFCCFEGFDGFCGCCEBBEAEEAEFGHDGDFCHFEFAGDABBCBCAHA,False +511,1.0,1.0,2.0,5.0,3.0,1.0,4.0,3.0,GDDGCBGCHDEEDHEDFAGH,True +512,16.0,13.0,8.0,20.0,20.0,20.0,19.0,18.0,GEEGAEDHBDFBGBGGHGEEDHEHEGFEGBEGFHGEDBBAHGFDAFDAEDGFFHFFHEEHDEHDGDGADCADFADABFHDFCEFCHFDGAGABHAFHGHCBFCHEHBEAAEAAEBCEDFGABDCHFCBFDFDDG,False +513,2.0,0.0,0.0,0.0,3.0,1.0,1.0,4.0,HHEHHEAGAFE,True +514,16.0,32.0,27.0,32.0,20.0,18.0,31.0,18.0,FFCEHGEAGHCGDDGHDFEDFDDBDCHDAABHAGDEGDEGEFCBDAEABBAGBCGHEEDCCBCCAECAGBDFBCHGHHDHADGGGCCFFAGBGFDGACBHCBDAEDBEDAGDHCDGCEGFGCEGDADDCHBGHBAHBEGBEFBFGBHDHGEBBDBBFCCCDEBDFBDBBGFBGFBGFBGFHDBCCCEBCGDCED,False +515,26.0,15.0,26.0,29.0,17.0,18.0,23.0,22.0,GFHDAEAAEGAEGCEDCDDCAHCABBAEBECGEBHHGAADFECFBCFECEDGDDCDCGDBDFGCGHDAHFADDAHCADDGDFGDEAAGAFDHGCHDCBDCGCBGCBFABGAHHBHDFHDFDDGDCFFAHBEHECCFCBACHACEGCEHHBHFGHCGDAGDAGECBFHAAGFFDEAH,False +516,12.0,12.0,20.0,17.0,22.0,17.0,13.0,11.0,EEBEADDAFDADAHHEEBGEBFFBEBCCDFCEFCEFCEFCABEFHEFCEFGFCGCGHCHDCGFBECACAGDAHDGGDHFDHADEADBFHBFABDHECFDCHCEGGDCDDCGBEAFEBECGECGE,False +517,17.0,18.0,11.0,13.0,13.0,9.0,14.0,20.0,BEFHACHEDBAAHAHHAGBAGCGGHAADEHDEHBBHGEHAEHGEDGEBCEBCHAAHBCHADHCDBGFBGHAABBFFFCCFACBGDBGDBFDCFDCBEHFHHEGBADEDHEGGABD,False +518,20.0,13.0,17.0,15.0,17.0,19.0,27.0,13.0,CFECBCGACDECDHCHAGGAGGAGGAGEAGHBGFFGHHDEHDHDDGAAGDDGDHBEFDAGBABEECEAABAAFAGFGDFCDCEFGECBCGGEGHEGHBGEFHFFDCCAFGAFEAEEFCFACFGBDCBCAHGBEGFDFHBFB,False +519,4.0,10.0,8.0,8.0,7.0,6.0,3.0,5.0,EABADFAHCBFGDFCDCCBACBEFDGBHGBHFEHFECEDHBCCBEDBEDBD,False +520,21.0,21.0,12.0,9.0,4.0,4.0,12.0,8.0,FAACBBBAABGAFADBABBDBBABHACGACBABBHHCECAACAHGDHGABCBDABAGBDGDAEDGCDGCABFEHEAHFBHGADGCCGBCGB,True +521,7.0,6.0,5.0,6.0,9.0,6.0,4.0,9.0,HDFFDAFDAFBFEAGABCHCHHBFHBGEBHEHHEHEDAECEEGACDECDBGA,False +522,7.0,13.0,6.0,12.0,9.0,15.0,17.0,9.0,FEHCDBCDGGDGGDHFBHAEFDEFDFGEAABAFBHCBEFBACDGBDGHHBFGDFEDEEGGBGGBHGFGFEGHCFBFFBGFGHBADCAD,False +523,13.0,18.0,26.0,23.0,24.0,18.0,20.0,22.0,HDCHAFHBBHAEFFCCGDFGAFCFDBHGFGEFBEGCEHDHHEGCEGEDBDDBGAFHCFHCAECHBFHADHFDHECFBCBBEEDGBCGEEEDGHFGECCECDACDGFBCACCDDGDDEBDGBDGAACABCABCFBEFEDHEDHDGHEFHECDECGAHGEHGCCBH,False +524,23.0,26.0,27.0,25.0,18.0,14.0,25.0,20.0,AHEABADDECBHGBEGDCHHCEDCECAFCACEFEEGGDGGDGEDGCFBAEAHFGDFCACHEBDDBADBADBDDACFAFAGCBBHBGGFDBFDGAAGAHGDHFBEEDCCDCBACHHCHECFDDHABAACAAGHHGBGGBGFBGFHDCBDCBHBHHCDFCDEBGHBGACGCCGECBBBEE,False +525,9.0,5.0,7.0,9.0,10.0,14.0,16.0,12.0,GDEGFEHFGFFECEBCBHHAHAGHAGDFCDHBDAFFFGFGGHBDHFDCFDCDGFEGEGCEGAGAAHAGEGHEHFEHFGCDBA,False +526,21.0,20.0,28.0,24.0,24.0,22.0,22.0,28.0,FBFFHFFDFEBCDDDFBEABCGECGECFHFFCFDAACAAHAHCDHGHHFHCBHBDHGDGDHAHCDHGABAABGCGAAFBGFCDFCDFCABEHDEAGHABHEBAEFHCAEABHGHHACFEGEEFEEGDFGDCCDCEDHHGBHGEHGECGDHDDAFCEBDHBGGECBDCBGCAGCEBCECEBCEHCDHEDF,False +527,20.0,11.0,8.0,13.0,17.0,8.0,13.0,14.0,DDHGDHCDHDDHEGFEDECAEHFFHAABEGBEHBCAGADGACFACECDEAHGABBCEAAEAGFABAABAHGFHEEGGDCEBAFGFHGAEDHEDHEABEABDHBG,False +528,9.0,13.0,8.0,10.0,8.0,6.0,9.0,7.0,ECDBCHEGHFFBEDBGDBHDBHDFHFEBBCDFDACACCBEHBAGBAGFDGADGACHABDAEABGGEGCEB,False +529,2.0,5.0,6.0,3.0,4.0,6.0,5.0,4.0,FCBFCBFCDCHDEHBFGFFGAEAHEGBCGCHDEBG,False +530,5.0,3.0,3.0,2.0,4.0,2.0,5.0,5.0,AFBAEGACGFGHCEHEBGEHGHDAHDACB,False +531,14.0,18.0,15.0,23.0,16.0,17.0,15.0,32.0,HBAHEDHGDHCDHDEHDEHDEHDHFAGADFEEHBBDFHDAEDEEHHHBHDFHDFHCFCFECABGGBEGCEBFBBDBDCCHCAACFACFHEEHCHHDHGFHGFHDCDDBEBGHAFFCGBAEBAHBGHAGFBGAHCFFBDGDCBDHGHGDHA,False +532,8.0,6.0,17.0,12.0,9.0,14.0,14.0,11.0,DEGAFHFDCCDGCHHBHCFDCFDCEGGFHHCAGEGBFGBDGDAGHCGCCGDCHDGEDBEFFCFDCGHCEHEGHACCAFAFFDFFAEBAEBC,False +533,15.0,11.0,12.0,12.0,16.0,22.0,21.0,18.0,GAAFFACGGFHDCBDFBAFBAGEAFEBFGGFDDEGFEACHFFBDFGEGDFFAHFHHAHHEHHFHFABECBDHHDCHDGGDGGEFGEHACGACGECEECEEBDBHDHHFHEFGGCABCAFEFCGGGBA,False +534,6.0,6.0,12.0,13.0,5.0,12.0,12.0,8.0,HDGAGHFGHFCHABHFEHFACCCBCEGCGDCDEADCFDHGDGFDGFBGCDCHFFEGFAFDDFDDGADCBECBGB,False +535,22.0,16.0,25.0,15.0,17.0,33.0,16.0,16.0,FBFFEECEEDFEFEEBGGDGFEAAEFCGFDGHDGDEGAAAHACFECDACDCHFCHFAFFAFEGFBDFECHHBACBCCACDAGFGDFEDFCCFHCBCCFACAAGADGHEFFCBFHDFCDHBHGECAFFGBGBFGAAAFBHFHHFEBFCDFCBACBHCBHAB,False +536,20.0,17.0,26.0,15.0,22.0,17.0,17.0,16.0,BHHBAFEEFAEFAEDBBDFEEBCEHHAAHAGBDGBHBECECCBFFAFEACEGCEFEECDDDGBDABEEBEHAAHCFCCEACDAHAGHBGFACFHCGHCFCCBCFGHDHCDHCDGCEAHGAFBADGGFCBFCGDCGCCFADECDGGEGAEB,False +537,13.0,10.0,5.0,5.0,10.0,8.0,9.0,7.0,EADEDEAAGAEEBGGHHBFFBFEBFBBDEAHEABCAHCAEFAGDAEDBFFGFAGAHGCHGHABCGBC,False +538,10.0,10.0,16.0,12.0,12.0,14.0,12.0,13.0,DFCGBCDFCDGBDCFCFFCFDAHDCBECEEBEDBEHECFECGAHGDHEAHAHHGFHGDHFFCGGCEGFGGCGCAAHHAEHCBDFBDEBAFADFAEBCBH,False +539,2.0,2.0,4.0,2.0,0.0,2.0,1.0,0.0,ACCFCAFCBDDBG,True +540,3.0,8.0,6.0,4.0,2.0,10.0,5.0,6.0,FGBFBFDBFDBFHFFGCEAFHCCBFCBECFABGDGHDGHBHHAC,True +541,4.0,4.0,3.0,5.0,9.0,9.0,6.0,7.0,HHFDFBDFAFFAEFEHGEHGEBGEAHFDEBCGHGGFEAFDDHCEBCE,False +542,1.0,6.0,4.0,1.0,3.0,1.0,2.0,0.0,EGEEDACCFCCBBBBBGB,True +543,11.0,8.0,11.0,8.0,8.0,12.0,13.0,10.0,CGFCHFHAFHGCGCCHCGHGACBDDBCDFADFADFBBEDAEGACFAHHGBHGDAEFGEAGEABHBGFBAEEGEHDFCGFCF,False +544,1.0,2.0,1.0,1.0,0.0,0.0,2.0,3.0,GDAHBCHBGH,True +545,20.0,18.0,24.0,26.0,24.0,22.0,18.0,33.0,CBHDDADAHFAEFCEHCEHEBHCBGCHAAHAFHFFEAFDAFBEEGHAGDDDACDHCEECEGDEGDEGBADBEDBAACEECHFBFCHFHHEEDBHHAEFCCHHFDBFDHCHHAHHAHGCHCCGFCGBGGFGDFBHFDGGDCEDADDADCFBCHBCBFHEHBEGAFHCCBEFFHDHGAEGDBGDEHD,False +546,29.0,23.0,21.0,19.0,21.0,27.0,25.0,20.0,BHEADFCDFGBFAFFACEAGFABFACFACFHEBHBFHDFGEGCEHCGDCDFCACAGDEBDEFAEFGEGGHCEHEAFEGECAAGAAEFFFFDFGGGCDGBGEBGHBGEBADFGCAGEADDBDDBACCCBDBBHAAABAHBACGECDDHGHHGBFEACHBFHEDCFDAHEAGCBGBAHFAHFBHFBH,False +547,8.0,14.0,13.0,15.0,21.0,12.0,10.0,20.0,CHCHGGHDDADDEGDBGFHCBECDEFBGHEECEGCFAEHHEHHCHHCHFFAAEDAHDEGBEHAAGBEHDEDBCFFEFCEFCHHEHBEHBEHEDDEGDGABCEBDBBCBFFBDF,False +548,5.0,4.0,1.0,2.0,4.0,2.0,2.0,2.0,ACBADGEEGEEBAFBFHDAHBA,True +549,14.0,13.0,9.0,11.0,17.0,24.0,19.0,14.0,EHAEHGEDBEDCEGGEHFBFBBGBGGFHAFHBFEACBACEADGFEACGFEGFADHGDAGCBGHGCFEBAHBGHAHADDAFDHGGHGFFGFFCFFEAFEGEEFFHFDBBDCBEHFFDFAEFC,False +550,8.0,20.0,16.0,21.0,30.0,20.0,19.0,15.0,FHEAEECEEGBBBBBHBBDDCDDCDBCBFFEGFBCEHEEHEEBEEHFDCEECGBBGAGAHCAFCAFGDEGCEFEHCDBEDHGCGFFGEEGEECBEFEHFHCDHBDFDDGGDHEFHGDECDEHEGACFAFFGFBGBGAFGDDDDDBEFBH,False +551,8.0,3.0,13.0,5.0,6.0,13.0,5.0,7.0,BDFEDFGCFCHFCGCAFFAFFHFGCAGHAEHCBCCEHCHDCADCFFAEFCCDHGEFAEBA,True +552,10.0,10.0,17.0,16.0,16.0,11.0,4.0,13.0,CABEDBDDCCDFHBACBAEEDFGACHECHECEDHDDBDDHAHCBHEFHEFHEDDGACAECHEFBEFDEDDHCBHCHFGBFEBDCFACEGCAACFCEF,False +553,29.0,25.0,19.0,15.0,29.0,33.0,22.0,26.0,EABECBEDDEFBHACGBHHEHFFAFFEDBAGFCHDGEDEHDGDDCADHAFFABHCFEEBAECAECHHHACCAEABEABCCECFECEGCHGCFFBFFBEFDGGAGAECHEHHDHHABDEHAEFFEAFAFFAGFHGEAGFFGFAACAEFFEGBAABFGBEGDFHDFHEFBBHDHHGHBCABABBFBBGBGGEAGBFGCFH,False +554,19.0,13.0,14.0,11.0,11.0,13.0,12.0,8.0,ABGABGBBFEBEDGCDFCEAGEAGHAGFAGHACHCDHADCADFGDCDDAFEGFEDHHAGCGCFDEHBEFCFFCFEABGABFCHEBABBACADEAFBABACC,False +555,4.0,7.0,2.0,2.0,5.0,4.0,2.0,1.0,ABBABDFBHFBEFEGBAGEAEEFDCCB,True +556,33.0,24.0,13.0,22.0,28.0,22.0,18.0,30.0,EEFABBCDBADEGEHHHCAHGEHABDDBDAGAABDGBABBAGBEBHEFDEDCHDAEDBFHEAHFAHFABFCBEHBEHAEHCHHFEHBEHFEFFHAFHAGHEGDDHBCEDGAFGECHHDHFAEFAECAGAGCEGADDAEBABAAHHAHGAHFEEECAACGFCDFDDFAFEBBGHBGBAFBEHDFGDCGDFA,False +557,21.0,20.0,17.0,15.0,9.0,13.0,11.0,17.0,FFFCCBHDBHDBDDBDDHDCGFBAHBHCCDAADHAHHADGADCCHBCFECEACECCFDABDCEHEHHEBHDFFABAABAGBEGAHGACGCGGFBBHBAFBABAGHAFHFGCGDEFBBCABAAE,False +558,17.0,17.0,12.0,11.0,13.0,15.0,10.0,21.0,AACABFAEFAEGCEBAFBFHBDHEAHEBEEHDHHBHCBFGAFGFCACBFBDFADFCDBHHBHDACECHHDABGBBGFGHDACEBCEBCAFHDEBDCAAHHFHHFGHEGAEGHFGHD,False +559,14.0,31.0,29.0,20.0,24.0,28.0,19.0,25.0,CBHCBFCBGABHAFHAGDBEEHABFAEDGEDECFFCBFDFFDEAEHDDCECEHCBACBDFBCEECGGCGFCFHEABDABDGBDAHFHHGADGEFHDGHEFHEBBEBGCBFBBDCEGFFAHGBHAFFGFFHEFHCCHBBHFEHGBDDHCBCFBCFBCADCDBCGCCBBCBECGDCHDFHBGHFGFCEEHEE,False +560,11.0,11.0,9.0,9.0,7.0,8.0,12.0,11.0,FDCFDGECEACDHCFAFGAFAFECFCHECHABHGBHBBHBGEGGAGGAFDBHDCHDBEDGABEAGACHBHDBDABGHG,False +561,17.0,20.0,22.0,24.0,12.0,25.0,33.0,19.0,GFGGFCGFGDHGBCGHGHHGHCGHDGCGCDDCHGCFGFAHCHFDFCDEBDEBGFCEFCFFGAFCCGCHACBFDFGEEBBDDBECAFGAFGADGADGDDGADGFDEBDBBDBGCAGHGGDGGBBDFHCCDCEFABHHBHEEHBDHAFAGEAGDABFAHHAFBFGDCEBCBFFA,False +562,11.0,10.0,11.0,8.0,5.0,15.0,7.0,5.0,GBAGDDBFDHFDGFAACAACBBGFGEBGFFCFFCEFBEFBCBACFFCAHCAHEEDBAHFCFFCDDAGCAHDB,False +563,20.0,11.0,17.0,13.0,14.0,9.0,14.0,23.0,BAGDHGEHCAGCGEFAEFBCCHCCBDADHBDHADHCGHAGAFEAHHAHHACGCEACAHCDHBDGGDFEBFHHDHHCAHGAHFEEDGFDECDHHEHACFGHFECEGBBCAACAABDABEGBE,False +564,25.0,13.0,20.0,11.0,13.0,16.0,8.0,5.0,AAAAFFCFFBBFABDAGEAGAHGACCFEFGEGAEAACACEFCFFCDCHFBBCBCCADFBHFDCCBGABGCBABBDFACAAFGACACDEEDECDBDAEDAHDAECAECEEHF,False +565,28.0,15.0,20.0,25.0,16.0,15.0,18.0,16.0,AADAACACCACGGBEGAEGBEGFHCHCCEBCEBDBBDBCDAEDEBDABDFFHHEAADAHHGHGBDGCAGFADAADADFHEFHFGDEBDFCAFEHFBBFDHCDADDACDHFHAGCGDAGCABADCADEAGEGCHDDBDCAGFHGHCGAEFFECE,False +566,7.0,8.0,2.0,9.0,6.0,8.0,0.0,5.0,HEFHDFDDHDBEDBEFBDBBECBAFBFDAFHAFEDDBCEAAAFHA,True +567,12.0,8.0,8.0,9.0,5.0,12.0,6.0,5.0,DADDAGBGGBCHFGFDAFCACAEFADFGBFABCDDFEDFECHECDBAEAHCAHBACBFFAFFBGH,False +568,27.0,25.0,25.0,24.0,19.0,25.0,34.0,18.0,GGBDADGGGAGEFFECFEBGEADDADDAFHBBHBCFBCGGEGEDHDHBDFBACBGCFACBCGBEGHHGCAGHGBAFAHHBFHAFECHCABFGHCDHEFEFCEDCEGBGGDAGFFGFFGAFBEFEAFEGFDBFCAGCAGCABAHHHCEACBGEBDEAACCFGGFGDBGDCCDBEGBCDFADBAGBADDADHCDHCDGA,False +569,17.0,19.0,19.0,27.0,20.0,24.0,19.0,16.0,DCECCEHDBFDEDGEAGFGFBCHBCAGAHGFDAFDBHAGEADCHDCDGCBHCEFCHFCGFAADABFABFEECGFHHDHBDEBDBCFEEFEEAECGDBFCBDHBDEBDAFDAHCGDEBDEHDFADFDDFGAFEFCAFHDBEBBDGGACDBCHGFFGFGGEGH,False +570,14.0,23.0,26.0,22.0,21.0,32.0,13.0,35.0,DEACHFHFDHEHFCHFCEFBFHBECFECHDGEDFFDEFHFBCCACCHGDFCHFEHCAHCHHCEHEEHCHHCAHDDGFBHCBEAGGDBGFBEHBHFBADBFDAFGGGABHAGHABDFBFHCFDCFDHEHCEAAEGCBGDFCFFEFDBFBBFBCHBHDBEDHDDBAFFCFHAEHCEHCBHDBCDEGFH,False +571,12.0,18.0,32.0,29.0,10.0,22.0,15.0,20.0,DAHAAEGCCHHEBCEBHDDGDDFFCCCCCHCFHDDHDHADBEFBECBCDBCDFEDGHDHCECGACDAEGGDGDBFHCFDGDDGAEFDCFDAADAADHBCBBCGEDBBHCFHCABFDHFBFCBCCBCCHCFFDGCGGCHCBFDFFDFFCFHHBHGFCGD,False +572,19.0,12.0,16.0,19.0,24.0,11.0,17.0,21.0,AEAGEAEEBDEGDECBBDAHDAFECHEFHGFGGDEHDECGGCAEHEHHCBHDDHDEGCEGAHGFEGEEGEECFADFEDEGCCABAGBAHAHHAEHACACHAFHBCBBAEAFBHDDADDGDBFHGCHFCHCCGFDHDDBE,False +573,5.0,2.0,3.0,2.0,1.0,4.0,3.0,2.0,ACEFDDFABGAGGACFAHFCHB,True +574,17.0,18.0,22.0,17.0,4.0,9.0,12.0,14.0,CCBCGGAHDAEDBCFCCHCFACFAEDAHDAHGBGDFDDCACAAFBBDDBDBBFCBECADDACBFCBHCHHABCAHGBBGBADDACHAGHDGHDHBEHBGBGGCFDAGCCCFHC,False +575,13.0,19.0,23.0,32.0,16.0,20.0,25.0,19.0,GGDDGDDCHDBGDFDDHBBHGBHBFHCEAFEHFGFEGEGGDGDFCHFAEFBCFGHDGDEGDBHDAAGHDDADEBCEGCEFCEFEDBACHAHFDEFCGFGHBBBABDCBFCHDCFFCHDDGDDGECGEDAAHAADDAFDCGCHBCGBCEHDEGFFHBDCBDBGCCGCC,False +576,9.0,9.0,12.0,4.0,5.0,6.0,12.0,11.0,BHFCHFGHEGHBGEFHADCDCGGCFGCBDABAEBACGHEGFBGBAHCDHCGHAGEAHHCCFCBGABCA,False +577,6.0,7.0,11.0,9.0,9.0,12.0,13.0,8.0,EDDGBABEGCGACGECECCBCCHGEFDEFGGFGBCGDAGHGCHBFGBFDEFCFFAGFDHBDADFADFHHFHEEHC,False +578,0.0,1.0,2.0,1.0,0.0,2.0,4.0,0.0,GCGDCGFFGB,True +579,5.0,1.0,1.0,3.0,1.0,1.0,1.0,4.0,HGAHAACAAEHDFDDHB,True +580,23.0,6.0,7.0,14.0,17.0,10.0,20.0,6.0,EEAEEHDHGCBEABGFBGEACAADADGADHCGFGGEHGAGGDEAFEAGEDEAAAAAAEGCFGDFGDEGAEAFBAHBAGDFGDFECCECGDBAAGDEGHAFDDF,True +581,26.0,18.0,18.0,18.0,15.0,22.0,19.0,23.0,FFFAFECGECGHCGACGACAFFGHGEHADHFDHBDHCACGABGAFHHGAFGABDABAFBHEBAEAHFAGCAGCGFAEDGHFGAEBAEHDDHBDFAFBHDBFCHEHHGFDDBAEHAECAHGHECDFDDHHBFHBFCBADFFDCCDBCABGEBCEBDEGAC,False +582,21.0,17.0,16.0,25.0,18.0,9.0,13.0,8.0,GAHDCGBCBACDDBDGADCEDBFDAFDADEAEEBEHADFAHEGDBGFHGHCBAAHDEHEEACDACDECFEAHAGGAEGAEFADBGEBGCDDCFDABDCCAGBADBDFFDGDECDBCDCCEEBBEBBA,False +583,3.0,13.0,7.0,7.0,6.0,7.0,7.0,14.0,CGGBGGBGFBHBBHCAEBHEBHFFFDFADCDBFEBGCBCHHHDHHDBHEGDECBAHFDHBEHCH,False +584,19.0,16.0,23.0,16.0,22.0,21.0,12.0,29.0,CGHFFHFFHCFGDFDEECFDCDDABFAEAADFBEAECAEGAECHHCHAEHFECCHGCHGEGGEDHBABFAHEEBGEHHHBHHCDBCDBADCACABCBCCBHBGHDFHBFHCABGDCFCCADHAHHEHHEHFEABEGGAFDFEEFEAFCDDEHFBHCHF,False +585,5.0,14.0,11.0,11.0,4.0,5.0,12.0,10.0,DGDBCBFGBDAEHACCEHCDCCBHFBHFBHCAHGGGCGGBGCBEDBGBAGHFCHDCGDBHABEFBDDBDDHG,False +586,11.0,24.0,18.0,11.0,8.0,6.0,17.0,13.0,GBBGABCCDDEGDFGAHEAHCAEGBEGAEABEAHHCHBBHCBHCBGGGGGGBHCBCCBDDDCGGBEFFADFGBCABGBBDCBDBHABHBBHFBDFCHCBGDHACCCEC,False +587,14.0,18.0,17.0,13.0,15.0,17.0,25.0,21.0,ECCAFEAGBAGCGFCGHADHEBGCGGCBDCGABDHBEGBCGHHGFHGHHGHDGCACAEHBBBABGFHGFDGFDBDGBAHHGGBCEFCFHHFEHFEFFAFFAGFCHCHGABCHEFHCFEBDEBDACGAEGEEHBBDEDDGD,False +588,13.0,15.0,14.0,18.0,15.0,14.0,13.0,9.0,EFAHGBHGDHGDCADGDDEEEECFACDGDGHCCFCEDCBHFBGDBCDBCGFCGBCEDDEAFEAECAFCDFDDBHABHFEEBBHBACBADBGDEABFGFFADGAGFAEFEBH,False +589,12.0,8.0,10.0,3.0,6.0,15.0,8.0,10.0,FDAFCFFHFGHFGBFHAHAADACFCCBBCBBHADHACFAHBBCGGEBECHGAHEAEEAFFFCFFHGFCGAEG,False +590,17.0,15.0,7.0,14.0,11.0,14.0,9.0,6.0,HEAFCADCHBHAFEFFEDAAFBABCGDDFAAGDGDCBEBFEBDEBAEAEBAEBAFBGFBHFCGCHGHDGFAAFCADBDDBDDGFAGFABEDBE,False +591,10.0,3.0,10.0,5.0,10.0,14.0,7.0,11.0,CFGCFEAFHGFCGAHACGFEADCAECAEBEDGFDHFEHFEHBEHFECFAAFHAECDHGDBFHHFAHCCFG,False +592,19.0,16.0,12.0,22.0,13.0,29.0,15.0,13.0,GHBEBBFBGFCCFDDECDGGDFGAFABCHFAFFABBCHBAFGHFBEFDEFGEFGDDGDDACDBCEAFEACEDDFFAHEAEDDHHFFDFBGFHGDBFHECCCFBDEBAHFAEFAGFBGDHADAFDAFDAFHAFGAGCHDB,False +593,7.0,6.0,8.0,6.0,8.0,9.0,6.0,6.0,DCHBFDCFDGACEACBBCBGHAGHFEHFEHDEGAEAACGFBFCHFCAEDFEBEDGF,False +594,30.0,31.0,17.0,16.0,20.0,23.0,18.0,23.0,ECHGCHGBBGFBGABGCDGHFFBFABDADAFEAFEHGBAABEABHABHACFACBEFADDADFBCGHHABFEBEGBCGEHFEFEBGEHGDAFBHDAFBAHBAHFAFACGDCHDCHDGBEBHEFEAFEDHACEBCFBCHBFHBAACFCBAHGHDDEADHAECACGBBABAFBFEBGEHGD,False +595,9.0,14.0,16.0,12.0,7.0,14.0,15.0,6.0,FEGFGGFDBAGEFGEFCCHCBEFBCGACBACFCCBCAFCAGGFFCBHGBHDBADADHADGBDGBDEBCHFCFCCGBDGDHEDADDFEBGGCFB,False +596,26.0,34.0,20.0,24.0,21.0,26.0,22.0,25.0,FEEBEHGEHEFHEFEEACGABBDHDDHGCGFDACBGBHGFHDADCFGCGBDAHHCFHGFEEFEAHEBHGBAABDABFAHFHDDADDFDBGGBFHBAEBAEBAHBAFACFADADDAGGBBGBBCCACFFBDFHDFHDBCBCABAECDFGDGHHEECCAFDBDEFCEFGDBBHBBHGGHFBHEGGEBCABCFBCFCAHBA,False +597,16.0,18.0,17.0,23.0,22.0,17.0,16.0,28.0,EECBEAGEDFCFADAHFCHFCHECDBGDBHDCHAAHDDBDDCDHHFHBAHBEHDEHAFHAHHEEGEEGDEBDEDDHBEBGEHGEHCACFHBDBACHECEBCACCGCGGEHHDHBFGEABFDFFDGFAHCGHCFHBGHGDABDAFGBEGFDFBDEHFA,False +598,14.0,9.0,12.0,11.0,20.0,14.0,7.0,8.0,EEAFAGFHFFBEAGHBCFFFFDFFBAFCEGEEGDCGDCBAADAHFFHAGHACDECBEDBEAACDGCEACHDDADBECBECHEAHFDEEEEEEEBC,False +599,31.0,15.0,28.0,34.0,25.0,28.0,16.0,23.0,EADADBADCDDCGEGGEAFEFGBDDCFACDECFECFBCHAEHABGFCCAECDEDGCDGCDGEAHDBBDBACEAFBFEBEDBEBEEFGAAGADGDFFCEFAFAABDFHDFHDGCDGHDFCDFHEFAEGCFDAFDAFDEFHBCDAFEECHHDDHDCFFAHHHHCHADEADADBADBCGCCHFAFCEHHAFHAHHAEGACCCH,False +600,10.0,11.0,5.0,10.0,8.0,10.0,7.0,10.0,HBFHBHGFGEFGEFAAFAGFGEBBHBDGBHHAHCDHEHBEAFDDBBABDFDCFHEBCECCADGADFADAED,False +601,1.0,4.0,4.0,5.0,1.0,4.0,5.0,0.0,EGCDDCBDCFDFBGBDGCAGFBGF,True +602,4.0,2.0,2.0,6.0,6.0,0.0,2.0,3.0,EDEEBAEDHEAGEABCHDCDDADGH,True +603,22.0,28.0,15.0,26.0,22.0,27.0,16.0,24.0,EADBBCFGEFEAGAFEACAHCDBABGHBHAEDGGDCGFBBFHFCEFCEFEDAEGEHGABFHBFDBGDBABGGCGBCGBABHAFDDFBDFBGFHFCHFCHFHECHDFFDFABFDBHDFDCFDCABHABHEHADCDDCDHFEEDAEDFEBHHAFHGBHBBEEBDHDHEDABDABAEGEEHAF,False +604,21.0,11.0,14.0,19.0,11.0,12.0,18.0,29.0,GHHGHHAHADHAHCGBCGBDGBDHDFAABAEHFCDDAACAFHBHHDEBEGAGGEBGEHDEGFGGCHGDBDHHDAAAACFACFHBHEAAEHADHGCHGHDBCFHEFHEFECDDHFDCGDFGAFHAHHCHBCGDCAD,False +605,9.0,11.0,6.0,10.0,8.0,6.0,9.0,4.0,DCGDAGDABEBBEBGEBGDDGHAHHBCCECAHAFFAEDCEFFEDCBGBBGEGDFGDBAAFDAB,False +606,28.0,22.0,23.0,19.0,24.0,23.0,22.0,23.0,GHDEEDGFDEHCEBCEBAGAAGEGGEGABFHGFAGAHGDCCDHFBADBDDBCDBFHFDGEEGCEHFFHCCHAGHABEACCACDFEEFAFGEFBCGBCBFAFFBFFDGEEGBEHBHHDCACFHCACAABAABAECCDFHHFHBDAEFHEFEECGFBGCDGEHCBGDBAAAHCAHDEHDBHABAAG,False +607,13.0,16.0,14.0,14.0,17.0,12.0,10.0,10.0,BGHBGADGDDGCECBEDBECAECGECGECFACFBEEBEADEDHFAHAAHBFEBHDCFDGDBFFBEGCAFADDHCABDACDABDHGFFGEEBFEBABCEFEHCHHCB,False +608,9.0,17.0,16.0,8.0,12.0,15.0,18.0,16.0,BGGGDCHHBHGBEACEACEGCEHFHCBGBBGFBGFAHCDGCFFCFGCBGBBGBFGBFAHFBGFBABCEGCEADHHEHHCHFEGEDHDDCDABGHECCFCFFGBADEAEHFH,False +609,34.0,28.0,25.0,20.0,27.0,20.0,18.0,15.0,FHGFEGEBBEGBEGHFHDFDAAEAAEDCFDBFEFCDCDDGEAFEADBCCACCDFHHBCHFEDABBABBABHAFGACGEEEACCACDDCBFCDHBFGBAGCGFADEADGABFABAGEEEBHBFDBFEBGEBEBHCCDCAGCAECAECAFCHGEEBFEAGEDECAHHABABBABDFDAHCABCAGHAGA,False +610,27.0,20.0,29.0,19.0,16.0,20.0,23.0,16.0,EDGGDCDCCDCCFAHFACFEEAAGGAHFADGADAEDCEACDAGDAHDCHFAFFHCGHCGDEBAEBAFHADHCBFBBDAECAECACGGGGFFCDGBHGECFBABDABGECGEFBFCBHDBHAHGACBAHEACCACHBHEFCBDCGDBGCBGHGCBFCADEFBFFGABGCEF,False +611,22.0,21.0,24.0,24.0,11.0,17.0,21.0,18.0,CGCHDBGDBABGACGAEAACCDDCDGCDGFDEHBABFCHACHAFGDEBDEBDABHGBCFBCBAHBDFBHFCFECFECGAGEAEBDGCGGCHGDFGDFCFBHFAFGAGHHFBHDAADCAHCAGEABCCBDDEDDHCCAAHFHHDADDBGHCGBFFBEDG,False +612,15.0,15.0,16.0,7.0,8.0,15.0,11.0,10.0,BBGABCABCFCHFCBCAGHHFHFFBFAAFAGBAGDEFFCFECACDACAFCABEEGCEGCAGDBCHBDDFDDFAFHACBGBHGBHCEEEGHCGFBHBA,False +613,1.0,6.0,10.0,13.0,4.0,6.0,8.0,9.0,GCDDCDCAHCHEDFDCCDGGDBHDCHDBHCGGFGCFGHFGFFHHCBBEEBDEDDBDH,True +614,10.0,16.0,11.0,12.0,14.0,10.0,10.0,10.0,DECEGBDAEDAEGGGHGAAEBAEHDGHGEBCHBCHBFEBCBFCBAHEDFEDFGAFDCFBCFBDFBCHCCHDHBDBBABFDGEEEDCEGAHBAF,False +615,1.0,1.0,2.0,4.0,6.0,3.0,0.0,3.0,HDEHFEDCEABEHFEDDECF,True +616,10.0,6.0,9.0,12.0,6.0,14.0,6.0,4.0,DFHDFBBECCFCCFBCDGAFFABDAGEADBDDACECFECGAAGHFHFFHFFDGDAFDEFDEBDAAGC,True +617,6.0,1.0,4.0,3.0,5.0,2.0,0.0,4.0,BDEHDAAFACHECHECDEFHCAAEA,True +618,22.0,16.0,36.0,14.0,21.0,16.0,20.0,16.0,BBGEBEHHHHHACECCGBEDBCDHHAHDCHDCECAFHAFDAFCAECGCCACCGFFDEGACGCCGCEGCGGEGACGACBDGGDEAEBAEGFECAECFBGECAEFFHBCCBCHEFADFDECDBCBFDHDECDGAABHCFGCAGCFGABEABCABCECCFFAHH,False +619,26.0,17.0,24.0,18.0,27.0,15.0,23.0,23.0,ADFABEBGDCGDEAEHBHDBCGECBECEEGAHGCCECGFCAFCHECFACBAHBACBAEBDEHFEDDEHGHHGHHGAHGAHFADAAGEAEDAFAADADHEGHEGHGBHDBCEECGFCHEBHBBFAHDCGAEGEEGECGHCFCFGCDDFDCBCFEAAAFEAHGBGDCDBEFCHAG,False +620,7.0,2.0,1.0,9.0,6.0,2.0,5.0,5.0,GBEGBDDHGCFGDGHEEHDEFAADAAHAAEAHEDDDD,True +621,16.0,26.0,22.0,21.0,29.0,29.0,17.0,19.0,EAFBDDEEGGEGGEGDFBBFADADCGDCBCCHCDDEDFEDFADFEDFGBFHBECAHCDBCGFCFECEEHAFHAFCGFBEHGFHEEHFEBCGBGGHABFGDAGCABFDBFDFFDEFBBBDHBEECFEHEACBFBDFHAHHEHHEHCCHGBAEBDCCEEFBBFAFCBDCBFBAFEACEGHE,False +622,7.0,7.0,8.0,11.0,8.0,4.0,10.0,8.0,DAGDCGDHGDACDBCFHHEGDEDEFHCBHEBHFDHEHBCGGEGBCGDCFDGEDCAABAABEAG,False +623,28.0,16.0,21.0,17.0,19.0,16.0,21.0,15.0,DEHGEHCAACGFGGBEFBEGGGBGFADAEDADDCCHGGACAACEBDGFCBDAAFBCCCCCAEEEECHDCEDAEFAHFABFACFGHHBEGCEFBAHCDHDBCEBCEAHAAHAABEDGECGFAGFABFAHFAHEAHDHBFCBDDAFDAGBGGDGG,False +624,3.0,1.0,2.0,2.0,0.0,4.0,3.0,0.0,GAAFDAFGGFCDFCB,True +625,2.0,3.0,2.0,8.0,3.0,1.0,2.0,1.0,DHDDBDABEGDDGBFAEDCEDC,True +626,25.0,22.0,16.0,18.0,24.0,24.0,24.0,13.0,EBGFHAFDBGEBGEFGEDHADHADAAFCAFCHGEAGACBDGBFBDFEDGEHGEHGDHGCFCEFBEACEBHGFHEBHEGFEBAECFBABCACCABAEDEDGEGCABEEDGEAGAAGCFFDBCGHAGCAFFGFDAFHFFGEBBBHBDAGDABDBDGBAFEDFCAFCEF,False +627,29.0,21.0,28.0,24.0,31.0,21.0,20.0,20.0,FAHFBGFACEAEHGHHCFHGAGFFCCDDBDGBDGBDBHEBHECCEHCAFEGEHGEHGEGGBCABADDACDEEBCHCGAAEAFCABCEBDABEABCAECAEAHHFCFGDFHDFHBCECEDCDFCDACEFBEDBFDBEBEHHECCEDAFDGFDHEEHEGHCDDADAAEGAFADCGCGFEGFEABACFAEBACBGDA,False +628,12.0,14.0,20.0,9.0,14.0,5.0,7.0,10.0,BAHEECEFDEACFADDABAECEHFDHCCCACBAEDHEBHEBHFHCFCCGCDACAADGEGCCGCGBCBBCGBCEBEHBEDCADBEGBCABHH,False +629,5.0,5.0,7.0,3.0,4.0,2.0,2.0,2.0,EFAECAECHGHFCDABDBCDBCBCABCGEA,True +630,23.0,22.0,17.0,29.0,22.0,31.0,12.0,12.0,CCDECDBBHBBHBGFACDAEHBFBGFCCEHGEHEECEFDDFDDBEDBAFEHBDHBFFFFFFFAFFAFHDFAEFACFCCGAFAAFGADGADFFEBHEGEAAFBDGBDADDAGEACECCFBBEEGGEBDBBCAADFEDCADFFDFAEFBHDDDDBCCBFGDAEHEHDDAD,False +631,27.0,22.0,17.0,34.0,24.0,29.0,22.0,24.0,FFDCFDCHHBFADFAGECGECGBFBAFBGGACBFCBACHEFEEFBEFEEFCBAEECEHAEGAEFACFADFDBFBHHDHAFHADDGHHEHDDGEBEEGFFDDGEDGADGBDHFDHFBHFHAABAADHAEHBHGDFGEAADDFDCCDCDDFBAGCFDCGDHBDHEAFDGBEGBADEFGCDBADGADHEHGFHBDHADGACB,False +632,14.0,22.0,9.0,14.0,13.0,13.0,20.0,23.0,BCFBCFAHGDHGAHEDGEBBCBHEGHDDDBAGBAGCECBBGBDABAGHDGHEFFBHEEEEHDEBDEFAAFAHGDGCDAFHAHGADGAGCDDHHFHGFHEBHBGHBFBBFGBFHHFAHCHHBECBGBGG,False +633,24.0,22.0,20.0,25.0,23.0,16.0,19.0,23.0,DBBDHHDHHEFEEFGABGFEGADFACHGEHGEHAFFAHECCEACEBBHBEFADDDDGGHGGHAABCFDCFBGFAECDGBDABEAFECFEHBAHFDBFDBDEFCBCCGDEACAAGBBGBDEAEAAGAAHBGHACCAECGCCDCGDEHAHGBDDEDDHDBHDHHFCHDBHEBCE,False +634,17.0,21.0,22.0,24.0,23.0,23.0,16.0,18.0,CBHDBHCEHCHBGDBECHEHFBCFDFBDFCGFCACCACCGDEAFGADEADFCDFBAHAGHGEBDDBDEBDHBGBDAEDBEDCEFCEFHBHCGDAHAAEDEEGGECBEHDGDBGEHFEFGEFBFFAFFCCFECEDHEGCAGBACFDGFDHFBABHADFBEFHADC,False +635,16.0,6.0,8.0,5.0,5.0,8.0,8.0,4.0,FFABFACAAFAAHAFHCEACEABFCDGCFACABGGDGCABAEBGEAGBAGHACHFEDDDG,False +636,0.0,0.0,0.0,2.0,3.0,1.0,3.0,2.0,EHGEHDEDGFG,True +637,9.0,16.0,10.0,10.0,13.0,11.0,8.0,12.0,FEDBEDBEBBEFBEHBFBFCBEGBAGBHGHDBDDEGBECEFHDDHCFHGBHEBCGBEFAACBDEFCGFAAHAHHFFAADAHDCHGCECC,False +638,12.0,9.0,9.0,12.0,9.0,15.0,8.0,15.0,EFGFDCDAGDHFCBFEAFHACHBGADEEHEFGEDHFDGDDGAECCFHBFHBCACHACHACFAFBGDBGDBHBHHBHDEHDAAAEFFFHF,False +639,14.0,20.0,11.0,14.0,9.0,16.0,14.0,14.0,BFBHEBAEDADCGDAGDAFBHCBACBAEAHHCGBCGFCGAABFCBFGADBFFFDFCDFEAGGDHDDEFFHGHHGHHEFEBHBBGDBCHBEHBEFBCABDGGDCGAFHBFABD,False +640,8.0,6.0,17.0,2.0,13.0,12.0,17.0,7.0,HCFFGFCHCCACAADFGBFCFFCGFCABGBEABGCEGCEGCACCFGDGECGHCAEGBEGEEGHBGEAFEHFEHGHGEECCGF,True +641,14.0,17.0,15.0,14.0,30.0,13.0,21.0,15.0,BBGEDAHDBBEHBCBEHAEGAFGECGACGADAFGFFGFEGDBCCBFCHDHABHEBGEDADDHEGHBBHEGCGCHEEHEEHGEHACACCEGCGGEDGFGAFDBFCAFBAFEEEHGEGFEBEEBHEFDECEEDEBGEDCAD,False +642,26.0,25.0,28.0,26.0,13.0,16.0,19.0,13.0,EBDECDGCAACBAHFACDCCBCDDHDFBDBDAHGAHGBHGBCFDEADGADGHFGBAHBCCDHBDFDFHAEEFDCGGCFCAFGACGCCFADBAEBGBGGBFGDFBFCAACAACECBBHBBGABGFCAHCDFGDCCEBCDACHBCAAEDEEDFEHEDABDACDAGDBB,False +643,14.0,19.0,17.0,9.0,14.0,22.0,18.0,8.0,GCCFBFFBEABEHDEBDGBDFAHFBHCBDEBDGBDHHFFGAFGCGHCACFBGGAGGFEGFCAFCADGGCFECECGFAGFAGACHAFHDCBBCBFABFEBCCBGFEAECDBBFFBAEEEEFG,False +644,15.0,27.0,16.0,22.0,21.0,27.0,27.0,18.0,EDFEFFDFBDGBEGBHCFHCFHFAHFGFFEHGEBGEBGABGCGEBGFFHADEDGEBFABGAEFEGFGGAGFDHFBHCBADAEFBCFCCHDFBEADEDBBBGDBDCACCFCEFDDFBHHAGHGGBGBEGCFCBFEGDAGDEHCEHEBHEBADHDHHDGCDGBAFBDCGAFGDBB,False +645,14.0,11.0,10.0,13.0,16.0,12.0,10.0,15.0,EEHEEHGEFGEDEDBGCBHHFHBFDBEEBEBAHBDGACGADGHEHHECDFHDFDFAEFACFBEBHEHAGDCHDCDGCFAAFAAGCDGCAAAHHFBCDBAFE,False +646,3.0,5.0,2.0,4.0,7.0,6.0,2.0,5.0,EEDEFDFHDFHGFHCBHFBEEEABHABFDBGCEA,True +647,17.0,19.0,20.0,19.0,12.0,18.0,17.0,19.0,HCFBAFBDFDHBCACEAFHCGGCAHBHHBHFECADGBGCDACAECGDCFDFEHBABGADGACGBEFHGFBDBCCBCFBDFADFGGFEGFHGFEBDDBDDADBFGCFGHECHCHHGGBECECCEBDEDHADHADHAFHAHAB,False +648,10.0,10.0,6.0,7.0,5.0,10.0,7.0,10.0,CHGDHGHAECAEAGBCGCEDFBGFCGBCFBHAEAFHDFBEHBGFAFFDDABDABDFBHFHHABHA,False +649,23.0,19.0,18.0,23.0,11.0,22.0,22.0,16.0,DFGDAGAEGAEDABBFDGADBHHAEGECAFDAEDACGBCGDCGHCGBCHEGACCAFDBFHBGGGDBGBFCBEGFHAHHCEDAEDBBAFAFFAFGAHCHCCDCCGBDEFHFFDBFBCFDCDDAAAGDEBDBBHBFHGFHFFHFAHGDGGDACDAF,False +650,4.0,5.0,4.0,4.0,6.0,3.0,2.0,5.0,DDHGDFGEFAECAFCDBCHEEAEEHHBACBHBB,False +651,29.0,15.0,14.0,25.0,15.0,16.0,23.0,19.0,GAFBABHAGGACGAGGAGHABDGFCGDEGEFDFACFBDAHAAHCGECDHFEHCDDEDDECGFDDFEDADAFDBFDBEGHFBAGBADBCDGAFFCEDEHAAHAACGAGDFDDFDAADCAFHBEHGEHGCGEBBHHBCDBCDHEBAEGGHGHHAAHAA,False +652,17.0,19.0,21.0,19.0,20.0,33.0,24.0,19.0,EBHGBHEFHAFCFFEAFEADEBHCBFCEFDEFHBGHGFDGDAHEGFEABBBBFBBFBBFAFEBDHBCBCGFEHACDCFDBGHGEFGACCFFFFDADGFDCFGEGHHGEHFFHEFHCFAGFBGCCGDCDDCGECGHAHEAGEDBCDEHDGHFGFCCDAAFAAFGAFDCGECGD,False +653,4.0,2.0,1.0,5.0,5.0,3.0,4.0,8.0,GBFEDEDGEDEADHGHHGHHDBHAHEFHCFAA,True +654,20.0,23.0,22.0,29.0,18.0,18.0,13.0,18.0,EDEBAEGHHFAHFBDDBGFBGDDABDABDADCCBBCEHGFCGFCDEHDFDGHDCBDHFDCBHBFHECCADGHGGEGBCBACHAEGEEFDEHDCHBEHFDBFCEACFAEDAFBGDBDDBDDBFDCFDCHDAACAABACGFCACDHHAFBAFBHEDCEBEEAC,False +655,7.0,8.0,11.0,11.0,11.0,5.0,11.0,11.0,CHBCHDCHBAHBCGDEGDACDEBAAAFBEFHFBGFEDEEAEEGDGGDGHDAHDHBEEGDECCBHCGCCGHCFHDG,False +656,23.0,22.0,23.0,10.0,19.0,19.0,24.0,14.0,FCGFCGAAEBHECHECHCGABAAFFEHBAHBCBBDEBEFDFADFGDFACFAFAHFBCEACECCDGBFEBFCCCCEGAAHAGEBGABCFBAAGFDFCEABEABECDGCGAHGHCCHBAFBHEEHCGBFGBAHBGGEGGEDBEDBDFGGGGGGACH,False +657,17.0,18.0,13.0,17.0,9.0,17.0,17.0,24.0,BDHBDGBFEBCHBDFBDHBAHBHHAAGABHACFFHHBBDDHHDHGFCFFCGHHBAHADGFDCFHCHCCBDFFGAFGAEEAGEHHBGFFGFAGHADHDCBDEFDECGAGADCAGCHGEHBEHFDABDGBCGAE,False +658,8.0,8.0,5.0,2.0,2.0,4.0,5.0,8.0,CEGBBGBHCFHBHBBABGEBHHGCFAAHADHAHGACFACFAD,True +659,34.0,21.0,21.0,17.0,21.0,20.0,30.0,25.0,HAFHDCDEGEEGAAGBGCBEAGEBGEAHCAHEAHCAHAAHFBHECECABCAHGGFGHHGEHDADFACFACFCGFCGFBBFAAHAAHBFFDAFDGFCAEAGFAEDBGBCEEFFFDEAGGADGCDFHGGHBCABCABCABHDGDGGEGGEGHEAHBDGBHHBCHDFAECGDBHAGHADABBACEFHBDEGC,False +660,14.0,30.0,12.0,19.0,8.0,11.0,20.0,13.0,DEBHHDCGGHGCHBFBFGBFDDFDDGDGBDBBABHDBHACECCACEABBAEBDBBGGGCGDAHCADCABHEFHBFDCDCGGFBGDBDBBGGBCGBEBBEBBHHBHFFHFAADGBBGBGADDFEAAGA,False +661,11.0,26.0,15.0,26.0,16.0,14.0,18.0,26.0,FEBHBBCBDCEDFABGAGEABBHBGCDGFDEBBEBBDBEGBEDDHHDHFBHEBEEGAHHDHHCBHCAHDHCAACEGBEGBDGBHBHDFHDHDFHECHCHEAHBGCFCFHDDHDDFDDAGEGGCCGDFGFAGFGDBBBHBDHFDACDCHFGDE,False +662,5.0,2.0,4.0,1.0,4.0,3.0,0.0,4.0,HCDFCFHCACAEEAEFBHABHAE,True +663,14.0,22.0,18.0,13.0,14.0,22.0,18.0,29.0,DHBHHBGHGDDFFFCBHCBFCHGCGGHHHHABCCBAFAEGBBDBFCFECFADFHBCHADBADGHDGCDACFHBFGFFBFGCFAAEACHAFHEEEEHGEHAEBGBGGBFCBFBGGBGAHDHHBECEHCHBFECFHAFHDCHDEHDEHGFHB,False +664,22.0,13.0,19.0,20.0,21.0,19.0,24.0,26.0,AACFEGGECAHDGHDGDBEHBGDGGCBEAGEFEAGBGGBFFBGGGGDCEEAAFFAHEBFEFACFECEABEFHGFHDAHCBHCFGDFHDAHGEHEAHEAGCCCHDAHFCEFCDCAFCGCHFCHGCHGCBGFBGHHDAHEAHDHHDHEEADEFDHADADDHDBADB,False +665,19.0,16.0,20.0,18.0,23.0,17.0,22.0,24.0,DAACFCEFCEHBFHAEHDBHBHABHABHAHCCGGCGCEDBDHBACCCCCAEDHEACEHEDGECGEFGCGDEFHCAHADFDEEDBECEACDGEDGFHFAEFAGBHHAHHDHAGBBFCGFEGHBHFDEFDHFHHABGABGEDGEDGEGGBCEBGDFGFFGA,False +666,21.0,15.0,10.0,14.0,9.0,13.0,18.0,9.0,ACFGBACCACCADCDGADGADGHBABGDFEDEGAGFADADDBEABDABEABAFBAFBGFGGACGBFEBFEHFHGACGCFEDGBGABCEHFGBAGFEDADBAFHHGHHDH,False +667,8.0,7.0,10.0,12.0,11.0,15.0,18.0,9.0,FAGEGGDGEAGDFCFFHBFDBGDFGBAGHCGFCDBCGBDFHGFHEACECCECAEFGCFGHFEDGHGBHFCHAEDAEDGDFGFGEBEDHAD,False +668,10.0,9.0,8.0,13.0,5.0,7.0,10.0,7.0,GFDGECCECCFHAGBGDBDFADGEDAADAADAADCGBGHBHBDHFGHFAHFACDEHBEBDDCGGCDFBB,False +669,7.0,12.0,7.0,12.0,9.0,2.0,15.0,14.0,HBGHAGHEGBCADABEEHFCCGHGGEGGCDGCHGEDGDBADBHDBGEAGAACEDDFBHBBHBDHBDHGCHGHDEEBHD,True +670,0.0,5.0,2.0,3.0,7.0,4.0,3.0,4.0,FGCFHFEDBHBBHFBGEBEEDEEGEHCD,True +671,5.0,12.0,12.0,3.0,8.0,4.0,5.0,4.0,BBCBBAECHCGHCHFCFCCBDBECBEBFEBCGHCEFGGBAGEAEEACCBDABD,True +672,11.0,18.0,12.0,10.0,18.0,18.0,25.0,17.0,AGBBGFGCFCEFCBHCADEBHCHDEBGGGGGAGGCGFHFBHDBFFAFHAEHFEFFAGBEDHHHHBBCFHAFCGCCBEHBEHGDBFEAGEHGEAGEAGEGDBGDCGDGGDFHEFEBBCBAGBEDHEFGEF,False +673,9.0,13.0,14.0,18.0,14.0,11.0,8.0,15.0,CGDBHCCHGBFGAFEEHEHCEHCACCADCDDCGBCDBHDHCBHEHABHEEGDFHDGACBAGDFEDFEDECDBDHFEHBEFFEBCEBDABAAGFHFDDFDDHB,False +674,8.0,13.0,7.0,9.0,11.0,13.0,8.0,11.0,GHHFHFCGFBEFDEDDBFDBAHFHHFCHEDGEHGCBDBHHAEGAEAAEBAGBAEFCFGCFAHBGEFECBCBBDBBDEFDF,False +675,1.0,9.0,5.0,1.0,4.0,4.0,4.0,4.0,BECBCFDGHHBEBBFBBFBCFBHGAHGCEECG,True +676,7.0,7.0,1.0,4.0,6.0,8.0,6.0,3.0,ECHEDFEAHHDFABGEBEABEDGFAGBAFBAFGFGGFABFDB,False +677,14.0,18.0,19.0,11.0,14.0,16.0,16.0,25.0,EEHFECBGCECHDBHGHHGHHGABBDFBDFBAFHAGDABCABFHHABGAEGDBHHGHFFHDFEDFHFGACBCCGCAAFFAHACDGCDBCHBFGBHEFHAFCCEBBDHCHFAHEGHEGCEHCECCHGEGBECBD,False +678,9.0,12.0,6.0,10.0,11.0,11.0,13.0,11.0,CDEAGGDGGCGBCGBAGBGEBDCAFGHFGBFEHEEACFAGFDEFGBHHFHHEHFCGDADHHDHEDAADFBFBBFBEEHEABBD,False +679,27.0,20.0,25.0,20.0,31.0,18.0,23.0,23.0,EFHEDHDDBECBDAFEEFEEAADGGCGEBGADEECEEFEECAFCGEGGBFCBFABGACDAEHBHCFGCHGCHGCFDCBHHBEABAHBABAHEAHGADGCCFECDHDFAGECHAFBADBGDBCABHADDBHCEHCEHBFHGFEEDCDHCEECGCDBCAHGHBGEAGEAFFAFGAEEAFAHGEHGDACD,False +680,27.0,26.0,27.0,28.0,20.0,19.0,14.0,25.0,GDCFDCFHCBAEGAFACFAGFDBEABDBCAHCGFFFCFBBBADBGFCDACDGDDHCEHAEHBFGBHECDEGAACBHCHEAHEFCGACDBHDACGACHAHHAHDEHFCBBABBABCHBFDCGBCHBCHFDHEEBDEHEEHGEFABHAHCAEDBCDBCDEEDCBDBHAFAGEADDADFADFDDHGDEC,False +681,3.0,1.0,1.0,3.0,4.0,8.0,7.0,1.0,HGFEDDABGFGGFGFFGCGAFDAFEEFE,True +682,15.0,12.0,11.0,14.0,15.0,27.0,23.0,14.0,FHFFHFCHGEDCEDGABGDBGFFGFHGDDFFDGCHECAEGEBCEFCEAAAAGACFAGGGBEGBFBAFBAGGAEHAEHBDGGDFDAHGGEGGHAFHGCEFDBFEHDDBGFBCFAFFEHFCHFHDFCFFDEFB,False +683,3.0,2.0,5.0,6.0,4.0,4.0,5.0,2.0,GGFDFADFADECDCGBCGEDHEDHGCBCAEF,False +684,13.0,18.0,21.0,19.0,20.0,13.0,21.0,11.0,FEEGGCAGBEGFECBEGBDHBDCCGACGFBFEHHEHBCHCCFDCDDCEACEAFHHFCFDEBBGBDCBDBADEDEGCFDHABEDGEGFDCFECDEAHEDGEAGFAEAAGHADABDBGCGGBGFBDCBDGBCGECGHC,False +685,10.0,7.0,12.0,11.0,9.0,18.0,8.0,9.0,HDHAGFAFFAFFAEBDCBDBEAFEACEACDGDDGFCHFCBCCACHGCFFCGDEFDFHEFHDCBEHGEGFFDFAAFBEFCDGHBH,False +686,6.0,12.0,8.0,11.0,9.0,7.0,20.0,10.0,BCEBCDBHAGDAGDHGDEDAGDGHBEHDDFGDGEDAEGGGCEBCBGGGCHECBFHHGGFGGFGGHGAHFBBCBECBHABFDEF,False +687,12.0,20.0,16.0,25.0,15.0,20.0,20.0,33.0,DFDHAGHAEHBHBFCFFDHFDBGGCCBDABHGGHBBCBFCHCEEADDACDFCAFBHBHDBHFBADGHDGHDGFEEBHHGGHGHFGDFCDHEEHCECCHDBDAGDABDCBFHAGEAHEHHEHFDHFDHFDEFDCCGBCHEDHBDGEHGBBGFDHAHHFEFGG,False +688,3.0,9.0,2.0,3.0,7.0,7.0,3.0,4.0,CFEHFBFBBEDBCHAFABFEBEEBDEHFEDFHBGGBGA,True +689,15.0,26.0,20.0,34.0,29.0,23.0,27.0,17.0,GAAGDABHABEGDEBDFFDHFEHFBFCBGCBCCDGFDEHDCFDBHEBEFBEBCGCDGADBDGGGAAFCEDCEDBHGBDDBEDFFGFEHBEFFCAHCHHGFDDBCDBDFEHFGAFHFFDBEABEFBGFAGHGGEECCGABDDBEEBECBEAGCHGDHGDEDHFDHDAECAECDEDGEDEBCEDDGGDEGBCG,False +690,2.0,5.0,5.0,7.0,3.0,8.0,3.0,2.0,GFGFFGFDHHAEBCCBCDFCDEADFDBFDCEDBBF,True +691,11.0,14.0,14.0,3.0,13.0,5.0,13.0,10.0,ABGFGEEGEEGEHAHBCHBDDGHBBABACBCEEGECGECGHCABCABCHBEGAEFCCGBFGCAEFGECBFHACHACHDHBGBA,False +692,17.0,27.0,23.0,13.0,20.0,16.0,15.0,12.0,BCCBCGFCGFADAABEDHEHBEADCFFEFFCABCGBABBEGBADBABBFCACGEDBEBBGFBGHBGHDEHBEHBCHACHFGEECHGFHGCCGECGDBBDGAEADFCGECDEFEFCCFAHFEHEABAFCCECEBDDBADBABBC,False +693,27.0,22.0,19.0,22.0,14.0,28.0,28.0,25.0,FCDFEDBEDFECFBHAAHEACBFDEGDCGFFHHFADGABFAFAAGGBHFECAECAGCGBDGBDHBHCBHFEHBBAFAAFAFFCHFGGFHAADCCGCCGBHGDDGFDGBDGBABHAGFDBFGBHAEFFDGFDGCAACAGGHDGAGCDEHDHBGHEFCEFADHEHABHAFHEHHDBGGBFCBGCHAD,False +694,18.0,13.0,19.0,10.0,11.0,15.0,13.0,6.0,GDGHAABAGDGHFBFGBCGACGAEAFDAFDECHECACBFCBACBEBDGBFACEEBEDCEACEBBDDBGFAFFDCFECDHCACCGBFGHGCEGCAAHAAFCAFCFF,False +695,10.0,11.0,11.0,10.0,20.0,12.0,15.0,5.0,DBDBFDEGDBGEEGEGFAAEGDFCFECEEAEEBHGGHCGHCFACGHEGEEGAEFCEFBAFBAEEACCGFDBFCHACEDFADFGBGCBDEBEGBD,False +696,11.0,15.0,9.0,15.0,19.0,14.0,16.0,14.0,BBEABEBFEDFHBEDCFCEDEFDECCEFGFGBHGBCGHGFHEBDGBFGCFGDGDACDAFBFHBHGECGEHDEHBBFDEEDGEFCAAHEABEHHEAHEAHDAHDGGDBGFAGAD,False +697,4.0,10.0,3.0,4.0,4.0,9.0,13.0,9.0,EFFBHHHHHCADDEGDFGBBGHFGBBBBHBACEHCFBEGDGGFGGFGAFGAGHFGB,True +698,8.0,6.0,6.0,10.0,3.0,3.0,10.0,9.0,CHGBHGEHGAAGHDGDAGDBDHADHBDHDAFACBCFBGEHCEFCGABGAGDCDDH,True +699,23.0,20.0,26.0,25.0,24.0,29.0,20.0,24.0,CDBFFGEGEACCACDGBDCHACHACHBGDBCFBHFHHFHHAGHAGHCHAEEGCEHEEFFCDFDDFDFAAEEFEEFBEDAEDFGDFGDHHDBCBBCEBEABADDAEDGGGCEHAGBEFBCFDHFBEFADFDCEHFEHFHADCFDAFHAFBFCEDDBCAHAACGCBFCDHBFHDAGFEGFGGCCGCBBCAHGE,False +700,29.0,20.0,21.0,24.0,24.0,23.0,13.0,26.0,EBHEBHBADGAHAAEEACGAFAAFBBFCHDBHAGCDEBDCDDAHHBCEAAFHAFCABDDEDEEDFHDFCDFBEGCFGEFAFGCHGDHFFEFHEDDEADBACACEFCBHCEHCAAEAECAEBFDAFHAHGAHGBGCBDHBDABDHBDHADFGEBABHFCFFAHFDECHHCHHCFCGDEGEE,False +701,3.0,7.0,7.0,3.0,6.0,6.0,4.0,11.0,CEFCFHGFHBHEAHECHEBBAHAEECHCDHCFFCHBGFBDDBGHBGH,False +702,9.0,6.0,16.0,15.0,12.0,8.0,10.0,9.0,FDCFDCDAHDGHFAACBCHDEHEGDEDDFDDEGCGCDBCDEAFCBCCBCGACGACHHEEHADDAEDCECFECFAGGBBEHFGHEG,False +703,6.0,1.0,3.0,5.0,2.0,9.0,6.0,6.0,DABEAHCFGGFAGFHHFCFFHDFHDCGFFGDEGDHAAA,True +704,4.0,1.0,0.0,2.0,2.0,1.0,3.0,0.0,BGGAAGEADEFDA,True +705,18.0,19.0,12.0,21.0,25.0,19.0,18.0,24.0,FDAHBFHDCHACHAEAEEBDDDDDGFHHFEHDDBDAAAFHAGGAGDABCHGCEGCFDBGCBEFHFDHFHHEGCFABHEBHCAHBBHEAEEAEGAEDEBGFCDHEEHGEFGEFBDFEGFGHFDHFBHDBGDACBAFBDFEHEECBEGBDGAEGEHBC,False +706,17.0,12.0,10.0,18.0,25.0,13.0,22.0,21.0,AGEHCDCDAEDAEBAGGHGGHDCHEHEFCEABEGBEBHAGABHABFFGGFGAFGDBGAEDAGFAHEEBFFAEFBEHCEFDEFEHDCHDCHDGAEGAHHFHEBEEGABGDHGDHBDHDHGCEDCHFCEEDDEHDGAGGE,False +707,18.0,24.0,22.0,26.0,29.0,18.0,27.0,19.0,HFHHGDEGFHCDHCEGFEGBDCEDEEFFBFCAEBBGABHADAAGABFDCGCBHABAGHDEDEEHBAHDAGDBGCBDHHDBEEGCFGCHCFHBFDEGDHDFHAEDAGDFGEFCEGGEBGCCCCECGECGCHACEGCEFCDFBDFBGBEABECBEBBGAHGDHDDAABGGBEGAEBEDFDDFEDE,False +708,20.0,10.0,10.0,16.0,13.0,13.0,19.0,23.0,FFHDFHCCACGGGHEEHDGGAGEAGHAEBAHDGHGGHBGAGFCBDCDDADDCEHADDDHBAHBAHBGGAFAAGAGGBGFHAHHDHGEHEFHCFHCBACEDBDDFCEFAHFAHEAEFHFABEDHE,False +709,5.0,8.0,2.0,9.0,7.0,8.0,16.0,8.0,CGDAGDFHDGABHDEFFBFFBEDGGAGGCEGHHGADEFDEDHEDGFBGHGGHGGBGBBAHEFB,False +710,2.0,0.0,1.0,2.0,0.0,3.0,1.0,3.0,FGHDDHAFHAFC,True +711,11.0,11.0,7.0,14.0,11.0,15.0,19.0,23.0,DHDDADGHBGFBGHHGDGAHHHGHHGBCEDCHDHDECGGFDDAGBHGBGDAHBFFBFFCHFCFFHBFHEHHGAFGAHGHDCDDAGEHGEHBFHEGBAGFAEFCEABEAEEF,False +712,22.0,16.0,19.0,9.0,22.0,12.0,19.0,16.0,HDGBAGAAGFEEFADBADHGCGCDBCABEACGHGEABEAFGHFEHFGHFGHCGEFGEFHHACDAHFCGECEABEAEEBBABHEFEAGEDGBCEHDEADCBDABCHCCHBCGAGHACEACHFCEEBAEBAGBGFCC,False +713,10.0,16.0,20.0,25.0,19.0,11.0,23.0,14.0,FDCDDBFDGCEFFEBBEBBFDBHCFAAHGDHDBFFGFDACDAEDGEGGDCADCDDGEDGEGCEGDADCGDCBBHEBDECEHCEHGBHACEGGDCGHHGHDGCGGCGCDHHDECCEBEEDABBAGBGEAGEFDHFBHCC,False +714,7.0,8.0,11.0,9.0,14.0,8.0,8.0,14.0,AADAFBHGCCGCDHHFHBCHDCHDEHEEBFBAFHDGHDHHEAFEFCEGDHBEHCCFCHBBEDEEAFEAECGECGEGDBG,False +715,4.0,5.0,2.0,4.0,4.0,2.0,5.0,7.0,BEEHHBHHCDHCGEBGDBDHEFHFAAGAAGBDG,False +716,2.0,4.0,4.0,2.0,5.0,4.0,1.0,3.0,GBACBHFFEFFDHBDHEAEECECCB,True +717,15.0,12.0,19.0,9.0,14.0,21.0,18.0,23.0,DBHAHHEFBFAGHAGHAEHFEAAGCGHBFHBAHDCHCCDAGGHGFDAFEEEGECHCCEBGDAGCAGHGFACDHBDGBAFCFFCDFCFFCEGCBGFBCHBHAGHFHCBHAFHCFGCEGCEHFEBEEFFHDFH,False +718,21.0,29.0,17.0,17.0,19.0,12.0,14.0,21.0,BHBBDDFDBFDBDHADHBCABAHFADGBECCFDBADGEHHBBEGHEDHCHEBHBHHBEEBCABFBBFBFDAFABDGCEGCEGBEACEBBBBCDCHGEDEEGGHGAFGABGABAAHAHHAHGAHGEHCDCFDCFEEDEBHCCCACAAFABE,False +719,15.0,18.0,17.0,14.0,22.0,18.0,20.0,22.0,GGECFCHFHBEHBEDBEFBEHBDHBGAGFAHFAFECFDFHGFBGDEHECDGCAEFHEFBDGHDGDBGBBGBHGCCGCCGCHHEBBBBEEAHHBFEACADDACGCFEHFEHFAGAHGEHFAAFCHDCEGCEFDEGBHGDHEECAADA,False +720,4.0,4.0,3.0,2.0,1.0,3.0,4.0,4.0,BFBBFHBCHAHDAGEAFCADCGGGH,False +721,22.0,14.0,33.0,22.0,22.0,16.0,25.0,18.0,EGACBDEEDAADHAHBABBAEGAEGBHCBADGFBCFBAACFEEFEDHBDCGECHHHAGEAFECFEGFGAFGHCGAFGEFECFGCABEEGGDAGDCCHCCHGDEGBEDBACAHDACCCBHCAHCHDGHAECDDCDHCFCDAHHCECGECGDCGFGECCCFCCDDGDDGDFGBF,False +722,15.0,12.0,9.0,7.0,14.0,11.0,9.0,13.0,HFDHFEHEGDBCFBCAAHFAEFGGDBADEAFEAHEAHFBGFHEAGEDGBBABHGEHGECCABCEHDBADCFEEFAHFGHEAHACCABCBB,False +723,25.0,27.0,19.0,19.0,29.0,24.0,29.0,27.0,CHBDGEDBEGCHBAGECBACBGCEACAGCAGEFHHHGHAGAEDHGCGBBACHDGDAGDAGBFFBGFBDFEAFBABACDEFFEAHHAEHGHHBFABFACHHHEBGBBEABEAHEDGEDBFDCHDBGGEHHEGHFCHFHAFDAFEGGHGECDFGGBGCFEAGECBECBECFEAFEBFEHFEHBDDAEDADDFCBFEBFGHG,False +724,7.0,6.0,4.0,4.0,2.0,2.0,7.0,4.0,BACDABGAGDBGHFGHFCHAEGADGBEGBAADCBHC,False +725,13.0,14.0,14.0,9.0,9.0,11.0,7.0,5.0,ADEDDFDEGBCACCABCADGAFGFGAEGAGBAFCFFHBBHCBDBFEGAEDBDFHCEECEAFBAFHCFCCDBCABCABHBBEC,False +726,6.0,1.0,2.0,1.0,0.0,2.0,3.0,0.0,ADAAGACFACFBGGA,True +727,22.0,23.0,26.0,27.0,23.0,28.0,17.0,22.0,ECCBCCADCDDGGAHBAHFHCGHEGHCAHGHHGBEFCAFBAFHDFAFCCBACDGCBGHGEAGCDECFEBEEDFDFBHGBAGBADFEDAHDACDGEFEEHGEHFAHFAEBDBBEBFEDAEDHDDCFDGDABEGDFHBCBFDFFACFAFHEFHABDCCEABEFFHCFBFFBFCBDCBDCEDGDAHDCHCE,False +728,0.0,0.0,3.0,1.0,3.0,4.0,2.0,2.0,CEHCFCGFHDFEGFE,True +729,17.0,19.0,22.0,26.0,19.0,16.0,18.0,23.0,GFHGAGFACDAEAGFDCBCCBCBBGBDGEGCEHDDADHEDBADHDEFBEDBDGBCGAHHAEAAEBDGDGGDGABBECDEFDEFHCAHBDHBHGGDFFEFDCCDACBAHEABCHEEFCEFHGFHDEBGEBHHHHCFHEAHBAHCDDDDCGFCHFCHCCFCD,False +730,10.0,12.0,10.0,12.0,5.0,3.0,7.0,9.0,GGBHAHCBEBDABDCEDEGDCGDAFAHGAHDADDACHACGECADHABCCGCBBCBBHHBFDEHDBDFB,False +731,8.0,9.0,15.0,9.0,17.0,19.0,15.0,6.0,BHGBCGBCDBCFBCBACFAFEGFECFEGFGCEGCGADEFECHEDEEFFEFFGFFGDFCEGCACBAFADCGEEGDBADFAHHDGHGFEEDCEHFFBGEC,True +732,15.0,25.0,16.0,23.0,8.0,23.0,16.0,19.0,CCGCCHDFHDFABAHDHGDBFDHDDBBDHBGHGFDDFGGHEHABDFCHFAFCACBBDDBDFBDABHABGBEDBEDAFCFBCFGEBBHCBABGABGHBGHFGCFGCFGEBEFADCHFHFFCDDCHAEHBDGADAADGFCFFBFEBH,False +733,26.0,12.0,25.0,16.0,6.0,12.0,11.0,16.0,DDEFFEHBCBCAGCHGBHAAHCAHAHHBHHGGHCFDCADCADABFCCGAFDAGHCCCACFADFADAHBGBCFFDBCHAFAAEDEBAHBAEFAFBADBDDADCCCCCCCACCGCDGADGAEAHGH,True +734,24.0,26.0,16.0,18.0,21.0,14.0,24.0,22.0,HGDGADCHDBBAEBDEBDEBEEDECFBCAGCBCHGDBGEBDEBEEBDGBGHHFCDDHGDAGHADEBDAAHBGBAHAEEGEBGEBAACFHCFACFHFAHFAHFDHCBEAHEHBCHAHAEDGFBGDBGFBHBEGDGGACEACACBACFAGGEGBFBHAGHAGCFGHF,False +735,22.0,22.0,29.0,19.0,27.0,26.0,31.0,18.0,FACFCCFCAHCGBBDADAGDFEEFAEFAHADEGDACBFCBFBHGCGGCFFBGFGFBBHHBCAADGCDECGGCGGCAGCEGEGGDDGAGHAGHFCFCEGDGCFFBDEBDFBFEEEHEHBEAEEAEEAGEFDEGDBBEHGAGFDGEDHBCHGAAAAABCECCECCHCCDFHBFCEGEDGFBFCBFHBFHDHHCGEB,False +736,3.0,2.0,3.0,3.0,1.0,1.0,2.0,0.0,DCBDCBGCAGADEAF,True +737,25.0,20.0,13.0,20.0,9.0,15.0,15.0,17.0,BBCBGDDHBCECEDCBDHGDAGDAEAACDBCDAAHFAEFDCFAFBAGAGBABHABDABFAFFDDHHHHBFHDFGGHDCFGGHHGAAEAABCAGCBGCEGABCADEBBEFBDFHGFHDFHCFHAADEBDGADABH,False +738,15.0,21.0,15.0,20.0,23.0,14.0,16.0,14.0,HBDCBCCDFDDBDABDABDFDHHBEGEFGEFGECGECGECABBEGFEGFGFBABDGBHGBHCAEBBEBEDDDBHDAFCACCEBHGGDEDAEACFBFFBGFGEEHHEHEAHADFCDCAFCDEBDCDEGEHGAHAHEABE,False +739,6.0,4.0,7.0,3.0,11.0,9.0,13.0,4.0,CEEGFEGFDGBBEFGGDEDHCCEAFEAFBAFGACCAGAFEBFEGFGCHGEHGECGHG,True +740,18.0,18.0,17.0,21.0,22.0,23.0,24.0,19.0,CHFCHDGHDGBDCFEEFEDGHDAHDAECAFGFFHFCDEGAHBDBEDHEGAEGAEFBEHAEHABBAHFGECAHBFCDFDEEDEGDACBFHDFBGFGFEEFAEFCFBCHBDFAGGAGGAGBAGBEGEGDDGCDBBDBGEFGDDGHBBECHFCHCCFAGHCFCAH,False +741,9.0,8.0,14.0,9.0,12.0,8.0,10.0,8.0,HHAGBAGCACBHFBHFDEADGBFGCDABDCEDCEFABGECCEBCDGEEEEECECCFACHAEFGGFCGFDGDACDHHBH,False +742,12.0,15.0,13.0,8.0,14.0,16.0,4.0,12.0,AFFFBFFBCEAFAAEBHDAEAHBCHFCHBDHBFHBDEBAHGFHFBEGCFHCEAFEAHABDBEDEEFECHECGECFHCFCCDCCGBDABDBBEFA,False +743,10.0,6.0,7.0,8.0,13.0,10.0,9.0,5.0,AFAAEBGEBEECEEDFCGGHDGDFCFGHFBHEHDDAADEDDECBEFBECHCGAAFFAFEAGEAGFBGC,False +744,4.0,4.0,4.0,5.0,4.0,3.0,5.0,8.0,FHDHHGAHBHDDHGDAFEACEACEGGFHBCHBCGEDB,False +745,5.0,2.0,6.0,1.0,2.0,4.0,4.0,5.0,CHHCFFGFGAAGAHGCHABEACEHCBFCD,True +746,6.0,7.0,9.0,8.0,5.0,5.0,6.0,0.0,GDGGFGCEDBEDACDCCFACFCDABDACAACBEBBCFBFEEGBDGD,False +747,23.0,21.0,27.0,20.0,27.0,21.0,28.0,26.0,DEADBCCGHHGHDBADBADBEEBFEBEBGGCAEDAHDFDGHEAHEAGEDGEFGBAGHFHECBCAEEBEGFFFHHHDHHGACGEEDCADBAFBHGBAFBDFCDCBGHFHAFCCDCGACGAFGCEGCHBBDGCHFDAFGGGBHGBHAAHCAGEDCCGCCHBCHFFHEFCEFAAGACGCEECECHEBHEGEDFEDF,False +748,3.0,5.0,1.0,5.0,3.0,2.0,3.0,3.0,DBGHEAHDADDADECFEGBGHBFBB,False +749,11.0,7.0,13.0,10.0,10.0,9.0,18.0,6.0,AGEGGFDHECGGCGBCGECBCCEFCADCGHCGEGBEBDECGGCAFHDDHGDAGDAEAEFDGADGAFCCFBAFEFDGFAGBAHBH,False +750,19.0,21.0,8.0,26.0,26.0,23.0,18.0,20.0,FEHFHBCHBCHAAHDGEABEDCECBDDAFFAFDGDHCDEGDFADCHDEDEEGHAGDFGCFGDFAEBDFBAGHAEEAEAAFAFBAFBEBBDDBDHEFHEHDEBDEFEBBAAEAEGBEDFHDHGBEGEFBHCHFBHEGGEFGEFGDFHFHGDBGDBFDBHDGA,False +751,10.0,15.0,9.0,6.0,11.0,12.0,12.0,15.0,GDEEDHHBBFGBHHBEHFHFBDCEGGEGCBCCAFCEFBECHEHEBHBAABFABFABFGFEGAEBDHCGHAGHAFCACGAHDHFDHGBBGF,False +752,16.0,16.0,21.0,19.0,22.0,24.0,24.0,17.0,HHEEFGDFCDFCDFGHFHABEGECBCGBCGBFGDFBCBAFFGCAGCAGBAGHGDHDDHGDHGEHAECADCEFFAFFDEGBAGBCEBAHFACCDCBGEHDEGAEFCEDBEHFHAEDBGAGFECFGGAGGEFHDHECHECFECFCBDCGABDBHDFEFFED,False +753,5.0,5.0,9.0,7.0,8.0,5.0,5.0,7.0,DHCDCBFEBACFGCHGCHGEDGDDEDHAGEACFACEAHEFCCFBDHBHBEE,False +754,1.0,1.0,2.0,5.0,0.0,0.0,2.0,1.0,GGBCDDCDDADH,True +755,3.0,4.0,2.0,11.0,7.0,7.0,7.0,3.0,DDGGDGFFEFFGGDECDEDFEDFBBHBGFBHDAGCADHDDEAEE,True +756,13.0,13.0,9.0,10.0,17.0,10.0,13.0,12.0,CGAEDBDFGGHCGBCFAEEAGFBFFBFFBEGEEBEEHEECDEGACGEHAFGADHABHAHHCGHFGHEHEAHGDDCAHFAEBAEDCBBCBBGBDEDDA,False +757,8.0,8.0,4.0,5.0,4.0,3.0,10.0,2.0,BDEBGHGGFDGFDAFCGGCEBBAACEDCADHABGGBGBAABGAE,True +758,26.0,19.0,23.0,17.0,12.0,22.0,20.0,22.0,DDGDEFCHCHHDHHCHGGHDBAFBFGBFEBCAFCAFHFFDCCDCEACACBFEGGHGGDFGDHCBGAFCAFEDBEAEEBDFGDAGBHBHHADGCDFCAHCHFCGFCGHCBHABDABAACHAFAAHCBHBFABFAGFDBFHBEECGAGAAGFAEDABACCEGH,False +759,4.0,1.0,4.0,4.0,4.0,6.0,8.0,4.0,GDFGAFGDGCFGCFCAHAHDFHEEHEEGDGAFGCB,False +760,2.0,2.0,0.0,1.0,4.0,1.0,5.0,1.0,ABEDBHAEGFGGEGGE,True +761,21.0,26.0,28.0,30.0,24.0,24.0,21.0,23.0,FDCHDHHDFHCCGFFAFAAGABBDGBCGBHGEHFHFBCEACEHEHBEABDBBABAGBFFBHDEEDBGFCGFCGFBBCBBDBGGGCDECDCFECFEABGCDAEHEHBEDDADFADGAEEAEFDCFHCFBCHBCHAEDDEBGEDGFHEDCBACDGFFCEGCDACABEGCDGHEECFCFHDFBDHADHADHACGDCDDHH,False +762,24.0,12.0,13.0,17.0,17.0,14.0,9.0,11.0,CEAAEBDEFDBCCBABBACBDBDDADGCGHAEHAEHBEFAEFAFCACHBHFEHADHFEFAGFGCDADDACDEDGEBGECAEBFEBEADGACFAHAACAAEADDFFGAFGCDHDHEFH,False +763,6.0,8.0,13.0,10.0,5.0,9.0,19.0,14.0,HGDFBDFGCHDCBGCEGCEGHGHHGACGFCAEEHBBGDHGCCGFAGHADHBCGDDBEAFDHFBHFDGCAGCGFFGHBGHCGHCD,False +764,27.0,23.0,30.0,22.0,19.0,28.0,33.0,17.0,AACCCCCCFBCDCCGCFBEFDGGDCGFCFFCAECBGBFCBGEHDEFGHFGHACHGFAGEAFFFCHFDGCHGDGCFGCFGCAGDBFFBECEGCGGBGHBDAEDABFABFDBDDBDAADGHHFBAECEBHAHHEFADFADFACAACGECEEAGEABADBDHEGEDGEDBFAHGAHGAGCDFBAGBGFFDCHBHEACGGBGB,False +765,18.0,15.0,16.0,11.0,14.0,19.0,16.0,15.0,CEFGFFADDDDCFAFGAFEEEAEHBEHCECAEBAECABHACHFCFGBGGBDABCFFFGFHGHGDEDABBABBAHFACGDFGDFGCBEEDFHACHGCHGBHFEGFAACECDGCHGBHCBHBAHAF,False +766,2.0,0.0,3.0,2.0,3.0,1.0,2.0,7.0,HHEHHCCHDGHDFCEHAEGA,True +767,17.0,7.0,6.0,11.0,18.0,9.0,7.0,8.0,HEEBEFBEBEEGHEFCEACFABFHBGEAEAACAADAADADDAFABDAGDEDAGDEDHCHFABEGDEFDEAEECEGHHHFGFAC,False +768,7.0,8.0,17.0,12.0,13.0,9.0,9.0,18.0,EBDDBCDHEEEGCEFDAFDABCBBHFGHGGHDCHFEHFAHAEHCFHCAHEHBEGECHEGDECCCCDCBHCGHCBFGECACHAFHDCDDHFDHG,False +769,20.0,21.0,9.0,15.0,21.0,8.0,21.0,20.0,HEDAEDGBFGHEDHEDHEBCGAEAAFAABHDHAEHGGGBEFDFFAAEAEHCHBCHACDBFGBGABHBBEBBAHBHHDABDAGDHEFEGBGGDCGEBGCHECHECHGBEDBEDBAAFGADBAGAHGBGDCGEEGEH,False +770,21.0,9.0,20.0,15.0,18.0,14.0,11.0,20.0,AGHAHEGHACBCDEHDEHEECGABBADBFCHFEABCBDEAGEAFEAFECFDCHDBDFADCAGCADCHDEADAAHFABFEDCEGCHFHHCEACGDDGHFGAFGAHHHECAEHDHHABCEFCHFCGCCEF,False +771,4.0,4.0,4.0,6.0,5.0,8.0,8.0,13.0,HGCHGCEBAEDFEDHAHHGEHDDBGDEGBHGFHGFCFFCHADFFBHGAHFHH,True +772,4.0,7.0,15.0,14.0,7.0,5.0,7.0,12.0,FCECCEHCHDDHEFHDDAEHECCGDDBDDBEDBFCGHHHBHHBCABCHBCDEDGCHFDACDFCDGCGGAGC,True +773,15.0,15.0,19.0,12.0,10.0,13.0,9.0,11.0,CDFCAAHAADAADBHCGEAHFBGCBCCEGCDCCDEAGHAGECHFHFFBFBHFBADCADEHBECBABBHFECAGCDDCFFFHDFHDFAEGAEGBCCBCEDGBBCB,False +774,17.0,15.0,18.0,13.0,14.0,14.0,9.0,11.0,BDADABGFCGHCGAGHAGFFDCCBAGFHDFHCFHCBACEACBAGBACBECFEBGABFBFFBHHBDEEDEAHEAGFDEFAFFBDHBECCCCDCEACEHCEAADDCBAEDDEH,False +775,12.0,10.0,12.0,10.0,14.0,18.0,9.0,17.0,FFDFGDFEBAEBHFHFFBFCBFCBACEGDDCHCHDGBEEAEHAEBACCCCCAHEAFFFFFHGBHDAADAHEFHGFHEDCAHHADHGFGCHGFEEHDEHBEGB,False +776,15.0,9.0,14.0,7.0,14.0,8.0,10.0,14.0,FGGCGFEGFEGEBBABCCDCHEHHCHGFDGAEHCEFCEGCAACEACADHABADBFDCEDAABEACDGCHHCHAFAGHEHBEFEAHBAHBEH,False +777,3.0,5.0,7.0,4.0,6.0,7.0,4.0,2.0,ACHDGDFECAEGAFGEBDFBCFCCFHCEECDBGFBEFB,False +778,13.0,16.0,17.0,23.0,18.0,12.0,11.0,15.0,HGEDGCCFHBDHDDECFEHAEBAEBHDCCDFCDCHGHFGHAABCAFCGHCGCEFFEBAEBABBEHBGHBFFDDGDAEDAEABBHBBHEDFEFCDCEDCEDHHCGDDDDDAGFEBBCDDADCAEEG,False +779,0.0,0.0,2.0,3.0,0.0,5.0,2.0,1.0,DCFGFFCDFHDFG,True +780,4.0,14.0,9.0,15.0,13.0,16.0,18.0,13.0,GFHBCDDGGEFBDFGDFEDHCBBGEFEAFEHBDHGFFECCDHGHCGBBGBEDHDDEDEEDBCFHGDHGFHGFHGFGGFGBFGAFHCDCAECAEBBEDBGFBH,False +781,14.0,11.0,9.0,17.0,16.0,19.0,16.0,13.0,AHAEEAEBDCFCAFEACDFGBGHHFBHDBFDCHDHHEHFDGFAFEABDGEEEFHFABFCGFGGBCHBEGBHACEADGACGCFGBFGAFDAGBAGFDHEDEEDEFDEFDGHDGDDF,False +782,17.0,30.0,15.0,20.0,20.0,24.0,22.0,25.0,GBEGHHGHFDDAEABGCBGDDCCHFEBFGBGDBGDBGCAAFGAFDEFGEFEFAEFACBGEBAEBHBBHBCHEHHEAHDDCBCFDADDHDGHFEHBHFBDBDHAFHFFHGGAFCFGCHEEHEDFAGBCHBFGBCGDCGBHBBCFBDBDEBFEFHHCBHGBEBAEBHEFAAFDAG,False +783,18.0,12.0,19.0,16.0,8.0,23.0,23.0,21.0,CAEAGEACHFBBCABCACFADGBFCCFGDFGFBGHEGHCCHABHGBHFBGEAGCCFDAFDCHBGHCGHDFEGEHGEHFDHBDFAHFAHCGGCGDBFAGFHHFHGFDDHGHFDAGBHFHEDDDDCCGCCGADFAFGAFAAF,False +784,26.0,24.0,29.0,15.0,21.0,16.0,22.0,14.0,GEEGAEGABFAFGEBBHCCCGGBHGBFDAADAAGAFGBEBBCCGCAAHAAHDBEEBGEDADDADDAECAECBEBHEFFADBCGECGCCDCGACBACFDCFHFDHGHBBHDBCECEGCBGEBCEFAECCCHFGECGCBACBFFBGFHCECAFBAHBHHAFDAGDECAG,False +785,1.0,0.0,2.0,2.0,2.0,6.0,1.0,1.0,FFFEFFEDFCDCGAH,True +786,20.0,28.0,18.0,25.0,30.0,17.0,20.0,19.0,ECEDCEBGECGBDDAGEBEEHHADHDECGEDEEFEADEAFEAGDBDFCEFBDHBHAGAAGCAGCHHCHDBDFFEECADBAGFCBBEBDEHHEBHFAHFBCEBFEGEHADBDHBDHCDBGDBHDCGBFEADEADHAEAGBBCBACEACFDCBDHBDGEGGEBGEFGBFCBGHFGFFAB,False +787,5.0,3.0,2.0,6.0,9.0,8.0,2.0,4.0,DAEDAECHGCHBEFFEFEDFEDADHEDAEFBFABFHFEG,True +788,5.0,9.0,7.0,1.0,4.0,3.0,1.0,5.0,EBABAACHBEHFACBBFBBEABCDECHGCHBCHFC,True +789,12.0,4.0,13.0,8.0,13.0,16.0,10.0,11.0,ADAAEBAEGDFGHFGEBGADFAFFAFFEFCECEEFEGFEDFCCECHHAFDCFGHEHBBFAGFGHACECGHCDCCHCCHDFHDGAAEH,False +790,6.0,10.0,8.0,9.0,9.0,8.0,9.0,13.0,CEAHHCFHCFHBEACFACDBGDBEHBGGCGGAFDHFCHFEHBABBHDHGDEAHGBEBEGBEDHEDGCDFHDF,False +791,8.0,14.0,12.0,15.0,11.0,8.0,8.0,8.0,EBHEBDCADCAGCABCGDEADEAEECBEDADFEHECHDBHGEGCFDCFBBBHBBDGHDFFDFFGBGHBACBFCHGCDCDDEBDA,False +792,10.0,22.0,18.0,14.0,21.0,20.0,16.0,23.0,DBGEHGFDGFECFHGFEGFBAECAHFHECBABHGFACEBDGBCGHCECAEGBBCDBEGEEGHEAAECGBFHBFHAFHCFBCDHCDHDBHEAEEBHHBCCBFHBCCBHCEDDEDDEFFHHFHFFHEFDAGBFEBHCBHDBFDGGG,False +793,23.0,21.0,27.0,21.0,31.0,27.0,29.0,18.0,AGFCEBGEFGHCGECBEFEGFCBFDBFHCCHCBEDDAGFBDCCDCCDEGHEGHAFHGGHDGDBADBAGEAEAGFFCDACFACFGCFGHFHEFHEDECBEBHFGDEGCEGDBAFCCFACEEBDDHCECDEADFGBBEABHACFAEFAEHAEHEGBFCAHGEFDEAAHACGDBEFBDBBCBCEHGEFGFGGFAGDAGEG,False +794,24.0,20.0,28.0,18.0,24.0,31.0,23.0,26.0,HHAHBAHDAHGAHECHECDEHEEGEFCECEFDEDDFCDFCHBBHBHFCGGEHCAHCDGAGADGCHGHFGEEGAEBABBAEFDGDHFFEGCBFBGHBGABDBCAGCEFEBFCFAAAGAGBABCAEAAFFBFFBEBDDFFCFFHFFECFHDFGCCACFAFHCFECECCFGHFGBAGBCDHHHCCHDCEDAEDGHFG,False +795,31.0,20.0,15.0,24.0,20.0,24.0,18.0,24.0,DDFDGFDGAGEBGEBGFHEDHBDBGHCFHBDCEACAGHADHGHFGBFHCDHDHEEHGGDGGEGDFGAEAEECGFCBFABFADAADAHGCFFHBFBAFDAFDBEBAAHAAHAAHAAFABCABEBEFDHDHEFHEDABHCDDDHBHCCGDHAECAEBEHAFBACEADFBFFEAFCAFC,False +796,6.0,5.0,4.0,8.0,8.0,11.0,14.0,10.0,AGGGDBHDBEDHHCHFAGFGEECFFAFFAEDAEFEGDBGHHFHDFGCGHAGHGGHGEBCEBDFGDF,False +797,13.0,13.0,14.0,16.0,20.0,20.0,14.0,14.0,FDCFDCDGCDGAFFFFHFBDGAEEFDHFGHGBFDAFHGFHGDEDDEADCHGBHGBACAHBECACHEEEEBBDFCEBBEBFEHAGCEBAEFCEFAGFAHFGHFGCFECADCGEADEHDEBDECHB,False +798,16.0,22.0,7.0,24.0,22.0,17.0,26.0,9.0,EFHFGCFGEDGFBGFBHACDACDAGBBGECEBBBDDADDADHGGGBGGBFEEDEFDEAGEAGEAFEDDBDGCDBBBGHGDHCDBDDEGEAFEADEABABBHFBFDBFDFEEFADGADECHBGEGFFGBBHEGGFDGAGAHGEE,False +799,20.0,13.0,23.0,31.0,20.0,22.0,27.0,27.0,ACCDDCDDCHDEGDBGEBHAHGDDDCDAHDGFAGHAEBFECFBCDECBAHEACGAEGFEFFGHADDGDDACEACECCFFFDFGHBHDBHDCFGCGACFCDHCBHEFDBDGCDCDEFDEFAGHAFHAHHCEGGDBGFEGHEHHAGFEBFGAHCBHCAHDADFGDEHDHHAGHFEHGEGGDGGBF,False +800,7.0,7.0,4.0,8.0,5.0,4.0,9.0,2.0,BFADCAGBDGDDGDDAEDEFBEABEBECGDGHAGHAGFGBABCGFC,True +801,27.0,24.0,11.0,26.0,22.0,20.0,24.0,21.0,FDEFHBBHDBDFECFEGGEGBBBFGBAGBGFBAEHFGHCAACHBBHBDHEABEFBAFGEDECDEGFGGHDGAGGAHCBHEEEFHEDHADFDHGEGFAAACDFDDFBDCEAHEBHEAAEFBDABAABHABDAGDADFAHFGHFGHCGDFGEBCDBDAGDBGHAHDADAGECDACDE,False +802,24.0,16.0,21.0,28.0,24.0,24.0,17.0,24.0,EHGDHECEADBDCGFCGDCFDEFDHFEEBHECAGBDHDDAAAAGEHGCCGBEGCEGEFDEBDAAGEFCAFABFBEAGEAFECCDDCDDHDHFDEFGAACEEEHGHHADHFHADHFCCAHGACGAHECBEBBDFBCFBHADDAGDCDFAHFAHFABFEBFECFHDBHDBHDGHFHFCDF,False +803,20.0,21.0,21.0,27.0,21.0,19.0,21.0,15.0,CHCDAADHHDHFEEFGGDBGABGCBCFAHFHFFGBDEBFEAFEHBEFDEFDAHCGGCDFCGCGECGEAGDBCEBGAADFADFCDAEDBDAHAEHAEGGEGAHGADFCHCCHBDBBGEADDADDBFDBCBBCBEGDDCEEAGDCGDFDEGBEBBFBAHCEHCFCFD,False +804,1.0,2.0,0.0,1.0,3.0,0.0,1.0,2.0,HBEHBEDEAG,True +805,17.0,17.0,12.0,11.0,12.0,11.0,11.0,14.0,CACCACHGBBBBABBDBGEGCAGFBEFAEBAECGBHHHHHHHFDEFGCGGBBBAFFAFFACAACGACDDEFEEDEADHAHCBHDGHABHEBGCFAHBEDDDFEDA,False +806,8.0,5.0,13.0,9.0,8.0,4.0,5.0,7.0,AABDACCACDACDBCBEEHEHCDHEDGEDADGFFCCBCGBEHCHHDGHECCFDCFAEGA,False +807,2.0,3.0,6.0,1.0,2.0,2.0,5.0,2.0,CCGFCGCAGEGGHBBHBDCFECA,True +808,8.0,11.0,13.0,11.0,20.0,5.0,10.0,7.0,EDGEBEBGEBGECCCADEEEBCEGEDBECBCCDAEDHECHAGHGCDDFDBFEBFEBEEGEFHAAGABGDFHDCHACBEDGECAHC,False +809,19.0,18.0,17.0,18.0,21.0,24.0,23.0,21.0,GGGGAGFDDEHDEHAEFAGHHHHCBECAGCEGEBGABGFBDCHDBHEHHGHFAHGCBGFDCFDCFBEFHHDAGFFGCEEDHGDCADAAHEEDEBHHFAFFABFACCBCABHGCGDBEDFEGFCGFBFBBCBBDFEGFECFAHDAEDAEAEEDCBGGFFFHA,False +810,20.0,16.0,11.0,12.0,13.0,19.0,22.0,18.0,AGFCHFDDFBEHGEHGBHGDCGFCHEGAGADFAGGAHAFBABBFBBGGAABAAEADEBDGCHHEBGCAEAHEGCAGFHDFHFEHAGDGFDBFBBFADCGDBGHFGHCCCGCDGBBAAFFAFHHFEHFEHEE,False +811,17.0,22.0,15.0,31.0,25.0,25.0,18.0,24.0,HAFEGGECCHDGGGHDGCDGDEAAEHGEFGBGGHGBEFEEBCHAEHCFHDFHDFGDGDBGDAFBFFBFHEECEDBEDHDBEDBFDBFABDEFCHAEFEDHCDAFDCBDABDABFCBCDHEHFCAFCDBEDACDEHFFHFFEEEBDEHEBHBHHAHGBHDHGDBCABDADDFDAFGAF,False +812,13.0,7.0,5.0,13.0,10.0,18.0,4.0,11.0,FGEADHABHAEHFCHFAAEEAFEAFDAFABEGGHFFBBDBHCAHADHBFADCCHEDFGDFDDBDFEDFEHFDAFDFFEHFC,True +813,30.0,25.0,17.0,27.0,18.0,16.0,23.0,20.0,DGAGBDGFDGFAAACAGCEFHDAHDBHCBACFACFGHFEFBHHBDHBAEDAHCEFDGCAADABGABDEGDGCAGCEGBABEABDFGDFADFABGBHGAFGDDGHDAHDCDDEDGECHEHGFBBFHBEBBCBDGGHHCEHBEGBCGADAADBHEFDEFHEAADCCHEDECAAABABB,False +814,24.0,14.0,14.0,18.0,16.0,18.0,16.0,21.0,ACBABDDGDGCCHAEHAEFDEFGHFGHFGDCGEBFDBGGBFACACFAGEHGBAFBAEAAEFHEGHCAEAADDHCABFHHEDHDHACHAGHACHGCHCHDDHABAAFADDBBABFHCFGCFEDDEDDHFEHFEGFBGEAFEB,False +815,13.0,9.0,13.0,16.0,13.0,6.0,10.0,11.0,EBHEDEGACDDCDGCDACHFCECCHGBHGBHCBEDAEDHFAFEAHEADAAEADDFFEGBDGEHHABGGHGCCADCDDCDHCABEFBEDBAG,False +816,3.0,7.0,5.0,5.0,0.0,0.0,5.0,2.0,DDCDBADBHGBGBBGCCCACBAGBDGH,True +817,5.0,5.0,2.0,2.0,3.0,8.0,12.0,6.0,HCHGCGFHGAEAFGHFGHFGFEADEHDFBGGGGGGFBFABABB,True +818,1.0,11.0,9.0,4.0,7.0,7.0,8.0,7.0,GABGHBHDBHCBECBFGHFGBCBBFEBECCEFCDFCGHCFCDHEFGEGBEBHDG,False +819,2.0,2.0,5.0,5.0,0.0,2.0,1.0,5.0,CDACFHHFAHDBHCCDCHDBGD,True +820,11.0,24.0,12.0,20.0,8.0,10.0,7.0,16.0,DDBDDECFEFFEBFBBABHAFHGGCCADEHHABDDDDCGHFABFABFHDCBDBGDBCDBFEHHCBHADHADBADCHDCBDHBEHBHABCGBEGBCDCGHBDAEFBBBH,False +821,9.0,5.0,8.0,7.0,7.0,2.0,8.0,6.0,DCDGGAGGCHGCHBBEEAGEGEFCEDADAADAAFCABCEHCBHBEHCAHDDG,False +822,4.0,6.0,4.0,6.0,8.0,10.0,6.0,8.0,DGEHGBHAFDDFEAHBFCBFCDFADFCDHGEHGBFCBHEHGEBEEHEFGFFA,False +823,11.0,21.0,15.0,29.0,14.0,28.0,25.0,13.0,GCBACBGFGGFADDGDDHCCBEGFEGBDBBDFFEFECFBCFBFFGFFGDDHHDFHEFDEDDAFAGFDEBEBBDDHDEHGCHFCGCAGCFGDGGHCFBBFBDCGGEGDEBAHFDEADEADFCDGABFDDFGDCGBFADABDGBHGHGFHFDHFEBCB,False +824,9.0,9.0,18.0,17.0,22.0,11.0,12.0,16.0,HDHHDBHCFHEEAEBDEDAEDBEDBHHAFFDDFCHGCHECDDCEEEFEDGADGCDCCHCAHCAHCEHGECGEGGHFDCCEECACBGCEGFGDEBAFFAGCGBEEEFDEFDBHBH,False +825,13.0,14.0,23.0,11.0,13.0,29.0,17.0,16.0,CFBCFDDFBDFBHFHGFAGEAFFBHFCCFCFACFACFDCAEBHFGGBAGDEEHBGFAGFHEDHGFEBFHHFGFDCFCBHEEGGCFGEFBCADHHDBFDBHDHACHCCGCEGAGGFFACCAECFHCGBCEFCEFCAB,False +826,5.0,8.0,5.0,6.0,10.0,4.0,3.0,7.0,DDEDAGAAGAHCDDBBHBGEEFHECEFHEBHEFHECEECBBCHBDFBA,False +827,20.0,17.0,26.0,28.0,18.0,27.0,26.0,26.0,ECFEGFEHFHHFABFABFEHABHAGDBHDBHDBGDGCDGHABHAFCEHDBHGCDCEFEEADECDAFBGFEGFBAAGDGDDEEDHDABDABFAGFDGDDADCBDAHGHHGHHFFFFFGCDEDGGCBCFEDGCCGCCDCEFFHHAHDBHAFCCFDGBCCHACHDEGGEGCCDCCHCBGFAAFEGFGCHHF,False +828,10.0,8.0,14.0,9.0,25.0,17.0,21.0,17.0,ECHGCHBCGEFDEFDECDEGBECBHBHHFFGGFGGHDGHACCAHHBDCFGAFGAGEEHEAHECEEHEEBEEGDECFEBFECFHFFGGGAEGHEGFCFBAGAHEEGDAAHFHCFGEEDFGDC,False +829,3.0,3.0,1.0,2.0,3.0,6.0,4.0,4.0,DHEHHDFHGGBAGAFEACEGFBFFBF,False +830,13.0,14.0,5.0,14.0,12.0,16.0,14.0,22.0,GDABFFCGFEHEGFFBHCBHEDHFGFBBFEDEHDHHGFHAEHAEHCEHABHADGEDGAFGHBCHAGHADHEFHFFGFGBAABAABDGBDCHDGBEAFHHDDBDHBFHDEG,False +831,30.0,21.0,25.0,25.0,16.0,20.0,17.0,32.0,ABDAGCAGBEEEEFEEFGBFGACGBHGBHCAACAACGCHGHADHACEECHDHACHFEGEAGDAHDAHDGBBHBFHGCHEHHAFGFFDDBGHHDHDEHABBACBHCADFDDHBDHBDCDCBDAHFFHDDBFHAGCDBFFEECCECCGHAHCAHBEHDACDAHDFCDAHDBBFFBAFCFFCAHAAGAC,False +832,25.0,27.0,23.0,20.0,26.0,20.0,20.0,27.0,AADBAGBCFACEEGDFBFFBFHCGDBHEFHCFBFBEEBHCCHCHBEBGABDAHDFHDHHFEHGECGFCBHDFHABBDDBDFHDGCGCCGCDGCHBHEEDEHDHBDEEHEGHBBHFBHFBGCEGEDAEGAECCEAAEACBAHDEBAEBFGACGAFAHDABAHDGCDEAHEAFECFGAACBACHAGBFGE,False +833,25.0,13.0,14.0,24.0,17.0,12.0,19.0,18.0,AEBDEBFCFGAEEHEAHBAHDCFDHFBFAGFAGAEGCCDCAAGAHEHHGAHEACFDEGDCFBAGGABGADGCDGFEBFEAAAGAAECBGDFCDBEDHEBCDDHDDHDGHDHHGCHGEBGHCAHDEEDCDDBADAAGABHDDF,False +834,15.0,10.0,18.0,19.0,15.0,14.0,14.0,17.0,GFDGHHGDHFHCFDBEBGADGACECCHHCHFAHCEHCHHDEHAEBADDGDBGDEEDECDFCAFEEFEDDHDCGAHBAGBDEADGHEFDFABCEBFGBCABCFGCFACGDHDEHACACCAFGF,False +835,20.0,10.0,18.0,14.0,16.0,28.0,23.0,12.0,CBFFGFCHEDBFHGFEGFEGFEDCEDAEHAGGGGFGGCCCDGCFGCFHAFBAFBDFCFFHAAGCEGAEGHEGDFAFFCDFADECHEAHGFGEHGEBDDBABFABABECHCFGCDDFFGFAACAAEDHGGHECDBAFCAFAF,False +836,30.0,20.0,19.0,16.0,19.0,13.0,25.0,21.0,GEHGEGBFGFCGFAGHHGFGGFDHAAHECBAGGAGHCGBCABFHBECAAHAFCEBCEACEADDADCGHBDHGFEDBCAEGAHGHCGHCGEBBHGDHEDHDFBEBBFADEAHEACBAEGFDCAABAABAABGAEACHBHDGADHAEBACHDGDAGCEDCEFCBF,False +837,11.0,6.0,11.0,21.0,12.0,11.0,14.0,20.0,CCGFFHDFDCHECHGCEGCGGDDGABGAEHDEHGGHGHDDHDABDHBHFFGEFHDAEDFEDFGFAHHHCFHAEDGEHCHFDADDGDBADAHDAHDCDCCBEHBEAE,False +838,2.0,11.0,5.0,5.0,5.0,11.0,2.0,7.0,HHAFDBFCBFHBFCBHCFEBHEBCFBFEBEHBDDDEDCABBFFGFFGH,True +839,10.0,18.0,12.0,15.0,22.0,22.0,14.0,20.0,GHGGHDGHEHCFHBHHGHGFDFFBHGBDFBCFBFEBAHAACAEBAFCEFHEABGAHCBCCADAEHFDHFEFFEHFEHCECGHFEBFGCFDBBDBDDCEDEEDEEFBFFGDBBEBGEAEHFDCEGEEDHGDHBF,False +840,6.0,5.0,3.0,4.0,8.0,4.0,5.0,6.0,HFAHFAGABEEHFEBBEABCGBGAFGAECDEDHEHHEDGDC,False +841,22.0,25.0,12.0,20.0,30.0,18.0,24.0,19.0,CFDABGGBGGDGGBGDBGDFEHGEHAEDEEDEEAEGABBABHABFEGAAAAFAAGHFEEEAHFBBFBDHEHAGHADHFDHEDHEDCFAHFEHGEHEEHCBBDBBGBGEBCEBFEHDCFAGFECABGDHEFFEBEACCHEGEGCAFDACECDGDBHEFCGFGGBBBDBDDA,False +842,26.0,32.0,18.0,28.0,33.0,16.0,26.0,21.0,BDFEACGAHGEHBEFBDDCDDEBGFBAHCGBBGCEDEHBAFGGFBDFDABCCBFCBHEBEAFGAEGFEGEDGAABBHBDCAAEAEEBEBGDGGDGHDHHCACBEGGDHADHGEFEBDEBDHBDHBEHBHDDCDFCDCGAGGEGGEGFECAEABEAHDAHCFFCDHAAHAACAABFEEEBDEBDGBDBCEEHDBGEBEAHF,False +843,17.0,15.0,21.0,18.0,10.0,19.0,19.0,11.0,GCGCCGCDBAAFCFFCGCCFCBGCBHBGADGFEEEBEDCFDCFBEFAEGDDDDDAGACDEFDBFGCFGEFDDHCGGGGGAFACHACHACGADGHHCHBFAAFDFFDABBEBFHBHEBHCAHBADGABFDC,False +844,28.0,20.0,25.0,32.0,29.0,10.0,34.0,16.0,GCBGCEAHBHHGHCGADBHDGAFGCFEEFDEAABAAFACGACHAGEEEEEBDBDDGEAEBGCFGAFGCGACGAGFEDAGDAGDBGDFEBECDGBDHBDBBDAEHADAAHGDCGDEBAHBEDCGBEGHEDHCCEDDEDCEGCDHDACAABADGEEFCEFGGAHGCCGCBECECBDHDCADAGDGGDGGDECHEBD,False +845,9.0,18.0,18.0,15.0,16.0,16.0,18.0,30.0,FHHFCHBCEBFEBFBHCGHEGFEDEHABHBHCEHCGGEGGCGGDGHDFHBFHAGACEDBBBBBFHEDHAHHBHEGHEHFDHEBHDDHCDCDHCACADBHDAAEGHFCCECCFHHBHGDHCDHFDGFBGFGGECAFBFCEG,False +846,25.0,21.0,20.0,25.0,14.0,20.0,19.0,27.0,DHHAHHGHBEBFFBHACHBCHFEAFHAGEAGEDFFDHACGDCGEBDDBGEAFAAGAAHAAFCFDCAEFBEGHGDCFAEDABDABHGBHGFHFDGDDGDDHFBABCADDACHBCHCGECACDBCGBCFHEHCCBBHHHFHFBHECEDHDAHDFDDFBBFDBEGACGACGADG,False +847,19.0,22.0,26.0,32.0,24.0,20.0,17.0,30.0,FFFFFBEBBCDDHBEHDHHFHCDHCDBCDAFBHDGHDECDEDGEDCBFEFEHAHHAEDBDGHDCHECDEFHHADHCHBCHCDDCHBBHBEECCDFEDFDBGDBDFBEBAEFAHAGFECCACDHCEHCGGCGGCAGABCAGAGCDBADGEDFEGAEGAEHACHCBHABDBEDEDDHADGGFBFFHEFHCAH,False +848,9.0,6.0,11.0,10.0,14.0,15.0,7.0,8.0,EBECBHGDFECFDGFDHFDCEAAGDEFDEFDFFHCAHGBDDHDHFEGEGBAFCEFCAFCACCACBAFHFEHEEFEGAEBC,False +849,4.0,12.0,3.0,4.0,4.0,6.0,9.0,4.0,BADBFBBDBCDAGGEGGAHFBHFECBBGGCGGBBGBDFFHFEHAEB,True +850,11.0,16.0,15.0,13.0,9.0,18.0,8.0,14.0,AHEFHEDHAHCBEFAEABEBBDHGAGCECCECCEDGADFFBFFBFFACACDFCDECHHFDFFHFFGFBAHBCDBGDBGHHGHFBDBHDBCCFHDACABDGBCBF,False +851,14.0,6.0,9.0,8.0,8.0,11.0,8.0,4.0,CADAAFAFGGBDGBECHEGAEGCEGHEAFCGCCAFCAFDBEHBAAAFAFFECEDADGACFBDFHDFBD,False +852,13.0,17.0,14.0,11.0,14.0,23.0,28.0,19.0,AHFBHFEDBHCBHGDHDDBEFGAFBEDCEDCGGCAGCHGCHGCDCEEGFBBFHCGHAGDCFEGABFCBECBAFBAFHHGHEBCFAEGGEGAFBFGGGDGBDBFAEEBGAGHAFHCFHFFAGFHGFHFFHGGBGGHDGFE,False +853,17.0,14.0,15.0,18.0,12.0,25.0,14.0,18.0,FEEDCEDAEDABFABGHCGEGBAFBAFADFDDFBDFGDGEEAEHDGHCFHCHGBHFHFACAEBGHHGHAGAAFFDCCDHCGGCFDCFHCGECADCFDBFEBFBDGHDCHCHDAFFFHFBBEAFADFHBFHFAB,False +854,4.0,8.0,7.0,9.0,7.0,13.0,4.0,5.0,HAHBAEBCEFDHFGBFDDFDDFCGFBBCBFCFFCAFEDFBCGCDGEHEEDFDHFEBA,False +855,8.0,9.0,7.0,8.0,14.0,11.0,8.0,11.0,FCGGHEGHCAHEGDGCDHEBHEGEEFAEFCEAAFAHDEHFEHBGFBFFBFEAHEADCBBCBBCEGDDHFDFBHEAD,False +856,15.0,19.0,19.0,21.0,20.0,23.0,9.0,21.0,EHCABCEDCEDCHDBADEFFEAHGADFHBFEBFEHFEGCHGBBFBDFDCFHCFCGHCDHEHADFFEFHCGHCBABEEBEFBCDBCEHDACDBBDCBACBAEBDDCADFAEFEEHDGHDEEFBFFDHGHFGAFAHFCGFHBHDADAHC,False +857,8.0,14.0,12.0,26.0,12.0,12.0,24.0,18.0,DDGDGFHGDEEDEHGEDDCHGCAGDGBBHHAHDBHDBGACHCCHFCHGGHDGHDBFABCHGHGFDCEAGEADEGDADEGHBCFBGFGDCGBFDFFDCBDCGDGBEGBFGEHHEFHDFGDAEDBDDB,False +858,3.0,12.0,7.0,10.0,7.0,11.0,5.0,6.0,EHBFDFFCEGCEBFAFCCFECFHDGCEHAEFDBFDBAHBGHBGEBCDFDDFBDBDGBHBBD,False +859,15.0,8.0,5.0,5.0,11.0,6.0,8.0,9.0,AFHEGGEGBEDBACAADADGGHGFEGCEHCDAFECBBABHHEHAECFHBAHGABDEBAEFAEFAHAA,False +860,24.0,23.0,16.0,29.0,25.0,13.0,28.0,31.0,ABDBGHHDBEAACAHBDDDDHHGAHBDHDAHCGHCAEGFECFECGHAGBBDBDDBDGBDBAEBACDAHDBGDBCEBGEDDEBDBBABGGGGGEHAEGGGDFHDAHAHFAFDCHDCHEFBEAGECHFCHGGEGGAGFDHADEGHAFHBGHEFBCAGCAEBHEDHEDEEDFEGFHCEHDHHFCHEAGECHA,False +861,19.0,16.0,16.0,18.0,22.0,19.0,15.0,18.0,HBDHADGAFFFCFDCFDHFAEEDEEABBABHHEAEDAHDEHCGFEECHECEFGHFDHFEEGCBDFDGHDGHDCBDCAECAHBACGEFBFFAFBAFBEDHDAHBBDGEGCEGBGDFGAFGAHCHGFECAEGABAHBACBECECD,False +862,23.0,28.0,34.0,23.0,21.0,19.0,19.0,23.0,AADEFDECBCFBFEGCHHCBCAHCAEDAEDFGBAHBGBBGEDGEFBAFBABEABFAHFAHADGBHAAHAAHCFCAECBEHBACDDCDCHDHHDAHDAHCFBCDHCBBGDEDEHFBCCCCCDGEDEEBCBHCDEBEHBCGCDECGCCGBCGBCFAGGACBHBFCAGCFBDHBFHFECFGHEGCEFDDFGDG,False +863,11.0,5.0,11.0,10.0,13.0,17.0,9.0,9.0,HGFAGHEGFFAEFGCHCCHCFACEAFEAFBFFBEEDDDGGDFEBHDFEDFEFCEHCDAAFBAFHCFECHEDDABDAGCCGAHGEF,False +864,8.0,4.0,8.0,5.0,6.0,11.0,2.0,13.0,CGDDADAFHFEHACHFFHAFHAGABEFBHHCHFCFBEHCEHDEFDCFEFHCAHCAHB,True +865,6.0,7.0,13.0,8.0,5.0,5.0,10.0,8.0,EBBEADDABHGBFBHDAHDFCCCCCGDCGACEFCEGCGGCDHHBGHCGCGBFDDFEAHCAHG,False +866,13.0,18.0,13.0,24.0,13.0,21.0,16.0,22.0,CECHEHGAHDBHAACGDDGDDGBGFBACBAFGCFGEBHHBHBBFBBFGDFEBHDBAEEAGEHFEDGEDFFHFADDADFHCHEADCFDBEDCDDFFBFFHFGEFGHCDFBHADHFDHFHCGCAGDACEBDHBDGDHGCHBH,False +867,3.0,4.0,1.0,1.0,0.0,0.0,2.0,1.0,BGHBGBAABACD,True +868,12.0,15.0,8.0,11.0,24.0,11.0,16.0,16.0,GBGAFGAHEABDAHEEHEGHFBEGHCHHCBDFECAADDGHFHFGEAGEBCDGEDBEFEEFGDGGAHGDHEEHBEHGEAGECGEAHECHBBEFBHBBDBBDCBFEFEEFECAAD,False +869,14.0,6.0,19.0,11.0,20.0,15.0,11.0,18.0,AFHAEHAEHGFHACHADFFGGFEGFEGDEDBAFBDECHHGHCCDBCFECHCHFBEDEECHACDGFDCHCEHFHCFACEACEACBCGBGEADECEEGFEHFACEDHEDHAGHFCA,False +870,7.0,10.0,10.0,16.0,6.0,4.0,11.0,16.0,HCBDCBHCBACDCCDHFHAGHCCDECGEDGDAFHGHGBDDFADHGDHBDHBGHFHEAABGBDHEDHEHHEGDDGADGCBB,False +871,6.0,1.0,1.0,3.0,2.0,4.0,9.0,6.0,AHCGEDGAHEAHAFGAGGBHGAHGFGDFGFHD,True +872,3.0,5.0,3.0,3.0,6.0,1.0,1.0,2.0,BBBDCBEGHEFHDBADAECAECEE,True +873,2.0,1.0,1.0,2.0,5.0,1.0,2.0,3.0,HEGAEHAEBCFDEHDEG,True +874,7.0,21.0,14.0,14.0,9.0,12.0,13.0,10.0,FDBFBBDBADBHBAGDHHCGEFDEBGEGGFGBCGEADAGGADHBDFCDECGBCEDFHFGHFEAFGHEDCEDCBFCBCCBHBBHBBDCBFGBCBHDBCAFC,False +875,6.0,6.0,10.0,12.0,5.0,8.0,13.0,6.0,GCGGCGGHBFDDADDBDFBDGCFGAEGAFBBCBHHFDHADHAGCDGEDEFGGCECCHDCEACGDFF,False +876,19.0,14.0,14.0,17.0,5.0,8.0,26.0,9.0,ADBACAGCHGCFGHDADABGEDABDABAFGCFDCADGGGGGGGGGBGGBACCHHAAGAADAGDAGDCGDBFFBCFBEBCEBGBBHEGDDCCCBHHAFGDGADGDDAFCGHHE,True +877,11.0,23.0,26.0,15.0,25.0,13.0,27.0,20.0,DHHEHGFGGCEHCGDGEDHCDHBFEDFEAFHBDGFCBHCEECEECBHCACGACACHGBHGBGGECGBDHCFEEEHCGHCGHCEBEFBGABCDDEGGEGGEGFEDBEBBGBCGBHABGEDCABCFECAHHBBCBDCAGBDGBAGCAHFHEBCEGCDFFDEF,False +878,10.0,21.0,12.0,20.0,16.0,27.0,18.0,16.0,EGCEHFAFAEBBGACGEEDEBDEFDBBDCBDEDFFAFGHBDFBHBGHBEBEGDDGDGBHGBHBFFGDFCFGCFAEGHEDEEDEAFFFFFFCHGGDGAFGAFHDBHEBCAGHBFDFFBHFCHFCHCCDCFDHBDGBDBHFA,False +879,13.0,7.0,15.0,3.0,11.0,11.0,9.0,9.0,CHBCFBFGEFEHCCAFAAFCEECBBHEEGEFBEABAADGAGGFGFCGACEHCHCFECADCACCACFAHFHDGHGAHEB,False +880,18.0,17.0,11.0,7.0,12.0,11.0,12.0,19.0,GACGHHGCCDAEAEBAFGHFGHEHABHBDHGCHGCHBABEEBECDDBABBHFHGCBGCBFAAGDAGHHHCAFCABAABAABHAFDAFBGDCHFEBEEHEFHEFBFHE,False +881,15.0,14.0,12.0,18.0,16.0,16.0,10.0,24.0,EFDEFDHBEHAEFFBHEBGEFABHGEHDFHAFEBCDGDAFDAHAACDACDGCEHDBBBBHDHEAEFAHGDFDABHABHAEHFEHFHHFHBFHAFHAEDCGBGGDDHDEHCBCCHCEFDGGHCDCC,False +882,1.0,3.0,4.0,5.0,7.0,5.0,2.0,5.0,HDHBCGDFACFECFEFBDFDGHEEHEBHEDCE,True +883,10.0,19.0,13.0,15.0,16.0,14.0,11.0,10.0,FDEBDAHCBEFHFHGGHGEBGCHCEECDACEFBAFHCBCEBAGBFGCEGBEHDDHBDHCDAFDEBDFBDEADBADBAECAGDABCGDCFBGFBDFBEFBFGBEHEECF,False +884,4.0,20.0,14.0,12.0,17.0,18.0,12.0,16.0,DHCFHCBHGFHFEDFEDBCDBFHHGCDFADCGHFBDCBDHAGEFBEHBEDCEGCABFHBHCCCCBHCGGFGFFBFBBEGFEBBBCGEGHHHFDAFDEFBEFHEGDEBEEBEEB,False +885,4.0,5.0,7.0,5.0,3.0,5.0,11.0,4.0,GBBEAFCABHGBGEFGDDCBDCFGCAGCDGCGHEGHFCHFGAGD,False +886,4.0,2.0,5.0,6.0,4.0,7.0,8.0,6.0,DEGFEGHBGCGHBGHDFAFFAFDADGCHECDECFFCHADHGG,False +887,7.0,10.0,2.0,12.0,7.0,8.0,10.0,7.0,HDGHAEDCDDBGDBAEBGCBDAEGFGFBGFBDDBFHBEHADFGDFHHFHEDGADGAFEAGEBB,False +888,22.0,21.0,26.0,15.0,24.0,25.0,19.0,23.0,HFHEFEAADAGDBCEBGEBEFHEGHAGEDGADFEBFCBFBBFCEHADFEHGHHFDFCHFCHDBGDHAAHFCFAEBAEGCEGCFFAHHGHHFHHCHCBABGDHHDFABGCFACFECDEAGEAGFBCFGCEGCBBBEBAGHGGCBAFACFDCDDCFCAHCACCBEEBEEBEADCCEF,False +889,14.0,18.0,14.0,7.0,16.0,10.0,10.0,16.0,FHAHHEDDECCCHBCBBFBFCBACDAGHAGHBFHBCHBEGEEGBBGBBGEAEAHHBEFFEAFEDHECEEGABGBDGCABEABAFCHCAACGBHHAHCDHFECFED,False +890,18.0,20.0,25.0,21.0,23.0,27.0,22.0,23.0,ECFEGEBFABFABCDBFHBHABHBDHGFGBFGECGCFHADHDEACCBHFEGFACHECHFBACCCBEBBDFDAEAABDAECCCFCFFCFFCEGCHBEGDEDFBDEGHFCHFCFDCFEGGEGDDGHDHHCGHFDFBDHGHHAAHAEHFGAFGAEADEFCEFBEGBGGHDAEDCEHCDGBDG,False +891,21.0,17.0,16.0,20.0,21.0,17.0,22.0,30.0,GEDGFABBHBBHFAGAEEAEAAECAEHHHBDDCABHGGHGCBAAFABFBFCGEBFEGEHHEHHDDHFGEEHDGHCAHFADBADCCGACHDGHAGHAFHAFBECBEDHGCHGAHGBDCEDCDBFDEGHGADGDHGFHCDGDFHBHHBHAECFECFEGFHFEDCED,False +892,2.0,4.0,1.0,8.0,1.0,2.0,5.0,5.0,HHHHBDABDGBDFFDCAHGGGBDGDDED,True +893,15.0,5.0,9.0,8.0,9.0,2.0,15.0,5.0,GGEGEEDAFGECACCAGFGEEDECDBAEGADGABAACCACCAHGAHADHGDGGHGBACBHBDEGAAGD,True +894,15.0,20.0,23.0,20.0,17.0,18.0,26.0,16.0,FGDFCFCCGBFEBEEDACGECGHCFFEDBBCHBFHBDAFHBGCFCCFAGHDGDGGBFEEGCEGAFGAEAFEDFEDBBDHBHGGGGCFDCEHBEHGCAAAAAGHCHHCHBGDDCDBGBBCABCABADBADBFDGGCCEDEEDGCGGDDGHCFHEFH,False +895,17.0,14.0,14.0,9.0,18.0,14.0,9.0,18.0,BGCDCCFADADBGDGCAEEAGEBEFBHHAEFFEHFEBEBCGCEBCEDAGGAHEABEABDAFDHBHHAAHBAHAHBAHCEHCAHFHBEHFCFFCEFCEHCHHCAEDFEDBGFGF,False +896,10.0,10.0,7.0,13.0,14.0,14.0,10.0,8.0,HCBCDHHGEAFHFCDGHEBDEAFBCFEDFADEADEADABBHCAEDGDDGFDAFHHFDGFGGFABFBCDBCEAGBBGEFGEFEEFEE,False +897,1.0,6.0,2.0,6.0,4.0,12.0,5.0,5.0,FBDGCGGDFEBFEFFEGFBGFHFFDFHBAHFEDFCHBBHDD,True +898,8.0,2.0,6.0,2.0,1.0,5.0,2.0,3.0,CFFCHDCFEHHAADAACCABAACGAFGBF,True +899,13.0,11.0,11.0,13.0,12.0,11.0,12.0,9.0,FCCGCABEBEEFCBGCDGCAECEEHAEGDCFFHDBCABDABEAFCBHABHADHGDFGDFBDFEDGHBGDGDAGAFECHEGDEGHFAHDABAF,False +900,11.0,8.0,16.0,15.0,15.0,12.0,12.0,10.0,HFDECDECFHCHGDEDEEBGHDAHDABCCDDFGDCGBCACCDGGFCGFEHEAGEAGEAFCCHCCAFEAFADEADHGDBFBBFBBFGCEAHFCDEEDHEG,False +901,6.0,5.0,13.0,12.0,14.0,4.0,0.0,2.0,DEEDEFCACAAEHEECDECAHCBDDECCBCFFDBFBCDECEECEDCADEDDEDACB,True +902,5.0,2.0,3.0,0.0,2.0,4.0,3.0,0.0,CFECFBAGAACAAGFFGBE,True +903,1.0,3.0,5.0,2.0,2.0,3.0,3.0,5.0,HEAGEFBCDBCBCFHCFHCDHGHG,False +904,8.0,10.0,8.0,10.0,10.0,10.0,8.0,8.0,HAEHAEDAEDGHFGFFAFFBFFGDABDECDEGGEGHBHBBCCFEDGECBCCBACHDCAFBDDEEDAHGBHBF,False +905,19.0,35.0,22.0,16.0,17.0,18.0,22.0,17.0,BEDEDGGBEBBDBGHBCBBCBHCAEAHBAGBCBHDBHDCHGCBGDAGDCCAGDGCDFCBFCBDBBDHAAEAGEGGEGBAFBHFGFGBFHEACECCGHCFFEFBCFBAFAABBBBBHDBEFBHFAGBEFCDGCFCDEEHBBFBDCGDEGFHGACAACAHHFGHEABE,False +906,6.0,6.0,11.0,1.0,5.0,2.0,8.0,3.0,GGECBACGCCGHCBFEGGAACAACDACBBCHCEFCEHBEGBG,True +907,10.0,11.0,15.0,22.0,12.0,15.0,10.0,11.0,CBDCFAHHHHCHDBDDBEDHCAECDFFDACDGBDABCFBCFBGDCFFCFEEHGGHGADGDFAFACGDCADFBCFGDFEDFDDADGAHEBHFCHDCDEEBEEDEGBE,False +908,4.0,0.0,2.0,5.0,3.0,0.0,2.0,3.0,GHACDADAEDAEDEGDHHC,True +909,1.0,4.0,0.0,5.0,2.0,3.0,1.0,1.0,FDHBDABFEBDDBDEGF,True +910,9.0,19.0,26.0,20.0,13.0,12.0,16.0,22.0,BHDCHGCHBCHDCBGCAEDFEBFBHDBHDGHEGECGCFDCHHGHHBHGFGCCBCCDCHAADFFDFFHEDCFBCEHCEHCDDFAGECGDBDBGFGEECBHCBACBACHCDEFDAHBCHCEGBGGCDDHDEHBAGBADB,False +911,5.0,1.0,2.0,3.0,2.0,3.0,0.0,2.0,HAHAADAFBAFEFCEDCD,True +912,26.0,20.0,25.0,15.0,11.0,21.0,19.0,28.0,BGFDDHABFAGCACFBCDBGDCCAAAHAAHFCHCEGGFFHHFBCABCGGGGBHEAHCAHBAHAHHACHFDHDAHABHCBFEBFADFGDCGFFHCGBCFBDFEDCHBBHBCGECGEHGFHAEHACHADAABHFDECEGBAGDHFDHCCFGAEGAECABFFBHCCHD,False +913,7.0,7.0,5.0,3.0,0.0,6.0,1.0,6.0,CDFCAFHACADCBBHBFHBFHFDGCABBABFHHAA,True +914,20.0,24.0,25.0,24.0,19.0,23.0,23.0,19.0,BDHFDGCHCAHFAHFGGCHBCHDFEDAEHCBFEBCGHCGFEACCAHDFGDFDBFBEFBEBGDBGDBCDECBFHEEEBCGBDDFDECHEHBFCAFADGADAHFCFFGFAGFEGEHGADDHDCHDBDDGEDBHABGGBEGBAHBHBDCFDCACCGEAACCACGAEGBEFBAFCCFGBAG,False +915,6.0,10.0,1.0,9.0,16.0,12.0,5.0,11.0,BFGFHGADDEEEEBEEHEHHEHFEBEGHFDHFBHFBDFDFFEBGDHCEBEEBEAGDADHAFAAFHBBEDF,True +916,19.0,25.0,17.0,15.0,26.0,25.0,27.0,16.0,EBBHBCGEEAEBCECGECHHCGDCECGECDBCDBAGCHGBFDBDBCEBFAAGAAHBGDFGAEGAEHEEHECGFFAFBEEAEEABEHBGHBFHDGCCFEFFCFFGFDHBAHAGFDGFDGHGGEDGEBGHGFFECBAFBHGEFBFGDFHDAADGGBAGBFCBFDEFAFBABE,False +917,1.0,1.0,0.0,2.0,5.0,1.0,1.0,0.0,DABDEEEEGFE,True +918,3.0,4.0,4.0,5.0,6.0,2.0,1.0,2.0,FCHDCBDCDEADEBDEBFBGACAEHEE,True +919,29.0,30.0,27.0,23.0,18.0,16.0,15.0,25.0,CECCDDBFGBEHCFACFCCAAAAABGDBDCBDABFBCEACABCGBHGDCGFBGHCDHCEHCBAFBFGHFHHDHFEHFEHCDBDDACBACGACGACFEDEBDHBDHAAEEGFBHHBHDAHBGBCGDAAHAFEBCCBDBEEAHEHFGHAHAABBABDHBDADDAECGBCEDCDCGEHAEHABBFF,False +920,6.0,8.0,6.0,2.0,10.0,1.0,2.0,2.0,ABABBFGBDGEECCEACECHEHBEABDBEEEACEACB,True +921,9.0,6.0,2.0,9.0,10.0,5.0,13.0,15.0,EBEDHGAHGFHGFBDEDDGCDGDHFAEABEGEGAHGAFEAGHAHHEHDEHDABDBGEGGBGHHACHFHH,True +922,0.0,4.0,4.0,4.0,5.0,3.0,8.0,5.0,BFCBHEBHDBCDFGGEGFEGEHGHCDHGDGGEC,False +923,9.0,18.0,18.0,28.0,20.0,33.0,20.0,19.0,FCFHEFDEBCBBCFACFDCDCAFCAHBDHBFGFHAFEAFEHGCHGDHCDHCFCGDCHBEGFFGDFGBHGDFGDFGFAHDBGGHHABEDFFDFFDFFEBFHDCEDFEFHEHHDGACFFGHBBHBADDDDCDEGDGGCEFCDBEBGEDEEBCEFGFFBEDGEDBFDE,False +924,2.0,5.0,0.0,7.0,6.0,1.0,0.0,3.0,EEDEEHEBAEBDDDADBHDFHBBD,True +925,12.0,20.0,17.0,18.0,18.0,15.0,13.0,21.0,GHHFHBACCFFHHFHHABHGDHFDEBABDDBCAEHABDEDCGDGDDGCDFFDHEBAEBAEBDCBGCEGBEHBFCEFDBGBFGBHBHHFFEEGECGECGECBHGBHDCHDAFDCFDEAHAHEAHACCEEFBBDCC,False +926,4.0,3.0,0.0,1.0,0.0,3.0,0.0,2.0,FHBFBBAAHAFDA,True +927,18.0,22.0,21.0,28.0,13.0,24.0,11.0,19.0,CBHHDCBAGFEDFBGBCGDCEFHFGHFGBFDDDDCDDCFHGFBDEBAFBEDACDAFEGFEDFCHEDADFBEFBABDGCCACBACHDCFDFAACCACBHFBHFBHADDADHACBBCDHCFFBFAEAACDBCHHFHGFHGHBGHBDEDDEDFEAHDBE,False +928,1.0,4.0,0.0,2.0,0.0,5.0,1.0,1.0,HBBFFDFFGFBADB,True +929,3.0,12.0,7.0,6.0,3.0,6.0,4.0,12.0,DHGHFACCACBAFHGDEGDCCBBFEBDEBHHCHHBHBBHBFHFCBFHGDBBDH,True +930,4.0,2.0,2.0,0.0,0.0,4.0,2.0,2.0,HCAACAFFGBFGBHAF,True +931,5.0,1.0,3.0,1.0,0.0,1.0,1.0,3.0,FGAADCACHACHAHB,True +932,6.0,4.0,3.0,4.0,3.0,1.0,3.0,2.0,DGCABBECFGCBGAADHAEHAEDABD,False +933,9.0,5.0,1.0,9.0,8.0,8.0,7.0,8.0,EFBCBAHBDFADADEAFFGGDEHDEHDHAAEABBFEDHEDHGFHGFEGFGGADHA,False +934,4.0,7.0,1.0,3.0,1.0,1.0,4.0,5.0,AEBGGBGBHABDFGDBADBHHCHHBA,True +935,14.0,14.0,13.0,12.0,23.0,12.0,15.0,6.0,EDAGFAGECGAGGACEACGGEHGEHCEBCFBEGECGEDEECFCBFBAFADBBDFBGCEEBEEDCDDFHFHEFDBCEGABGAFDAFDABDAEEEHBEDBEFCEAAGBGHC,False +936,16.0,21.0,7.0,13.0,13.0,15.0,22.0,19.0,GFBGHEGBBAABABEAHHADCEHFAHFACEGBHHBEFGAGEAHADDGDFGDFDAGHCGFFGBFAFEGFHGAHADGBDHCDHEHEGDEGDCGBHGBCGBFEAHCGHEBDBBEBBFBHFBHFBDAGGB,False +937,24.0,12.0,20.0,15.0,16.0,11.0,15.0,24.0,HAECEECEEBBAGGADHAHCGHDDAGBFGAHEHCAABGAHGAFGADHEDGFDHADBBCABGABDDCCDBHBEEBEEHAHHAGHAHHDHCFCAHAACCDCGHCHFCHFCHFADGAHFAFFCCFEDEEBGECCACEHDG,False +938,3.0,5.0,0.0,6.0,7.0,6.0,5.0,5.0,DGBFHAFEFDHBDHBDGGGEEHBEHBFDEGAEFAEFD,False +939,22.0,26.0,26.0,14.0,18.0,22.0,25.0,26.0,ACFACFGFBAFBGBHHBDHBGGEAHFAHFAFEHGECCECCFAEGABGABEAHGBEGFHCHBBDBCHFDEFHEABEFCEBHEBHDBADACDEFBCHDGBBCCBCHBEHFCGFCGCEGCHHCHGAFCADDBHDGFFHBAGCACABCGDGGBFHDCBFGBFEEFHEHAGHGGHCCDAGDAGA,False +940,8.0,10.0,2.0,5.0,4.0,6.0,1.0,9.0,BGDEHABAADAFBAFHHFHHFHBAHDCEABDBBHEDHEBBFBAFC,True +941,29.0,18.0,34.0,25.0,27.0,21.0,24.0,19.0,DEDAEGFBGFBGCBFCHECFEFAGBABDCBEHHEHGADEHDFHFFCEAAEAFEAFCGGDGFEHEECGCCDCCECCDHFAHCACDGDBGFBCFADEABHABDABDHBGHGDADDADFCDAGFAGBBBECFCCECCEDGGDCDEGGAHHFEEAEACBDCDHCHEEAEACFAGDHFEGCAGHABDACHCCBCFGCAGEAC,False +942,22.0,23.0,26.0,28.0,25.0,25.0,28.0,22.0,HHDBFEGFEGCHBDEBHGCHGBDFHDBHFBHBGHCCECADHADGAGGCGCFDCFAFGDFAHGEDEEAEFDBCHBDHGHECFAFFAEFBGFHAFBGFAHFCCGHDBABEGBDBHFACAADAGDGECGEGGHCGFCFFEDFCCACEDDHDDEADECDGBBGBCHAEHEEFCBCCACGFBDFCDEADBGBEGBEGDEADEAD,False +943,10.0,5.0,3.0,10.0,7.0,4.0,2.0,3.0,DEBBHAGEABHDCADAADEEBCEFEDFADAADAGDABDCHDFFE,True +944,12.0,16.0,22.0,10.0,9.0,17.0,15.0,10.0,CBFHFFBDFBAGECGCCHCAHCFECDDFFDECBBCBBCBFCAFCFFEFABFGBEAHAGBGGCCGBADCADHDGBFGCEGCEGCGHFGCFEFBDHADACGABBHHDAHCGCE,False +945,14.0,9.0,10.0,9.0,9.0,9.0,8.0,11.0,GBHGAHFAHFBGGDDGCHFAAFACDEFDACDHCEEAHEAFCBHCBGFBAEBAEBAFCAHDAEGCHDEBAEFGDDCHBCH,False +946,25.0,17.0,25.0,19.0,25.0,14.0,14.0,31.0,ECDHCBBCFADECDCDBGDBECEEGEEGFAGHACFDHBEEBAFCCBAHBAGBEGBGFHHDHHAHHAHCFHFHAFHEFBGBAHBEDCEDCEHHAHEABAGGAEGACAFCADEEECDACHADECFCDDEHAEFAEFBBADEHHHHCDHCDHCEHGFHGHHBCCAADHAGCCD,False +947,9.0,11.0,9.0,14.0,8.0,14.0,11.0,13.0,AFGAFHBFDGCGGDFFBBDCBDHFDHCECGHDFHDCHGGHAEHCEAAEFDEFAAFBBDBFDBFDBHDBECBFCEGGHGAEDHGHHACDF,False +948,13.0,8.0,5.0,13.0,9.0,10.0,22.0,12.0,AGDCGDCEDGFHFEAAEAAHADGGGBGHFGHDGHDHCBHFGEGGHAEBEDFADEGGEGGAGFHCDABDHBGGAGGDDBDFBCFEFAHFABGH,False +949,21.0,23.0,21.0,26.0,19.0,22.0,10.0,18.0,AAAEAHBDFFHFCGEGBDFDFADHEDBEABCAGDDBHEHFBHFBHBAEGABDDFDFECEECBCABADBEDFEBECCHBBABBEBBHBEDDHGHCGHCGDEGDGDDEDDHDCHDFDBFHHHCFACEAFAACHACFECFDCFCFFAAFDABCCBCDFCAFGE,False +950,20.0,25.0,18.0,22.0,18.0,18.0,14.0,12.0,GEDGBHAHGAHGCCDAADBDEADBDDBFFHFBHFBACBFCAFADDCHCGEFBEABFFGGDBGBBEFCEFBDHBDHDEEFEADEDDFDDFDCBDHEDEEBEBAECCEBGBHCBHCEGFBBCBACAGCAEFGCFGCFBAAAAGCBHAAD,False 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+970,16.0,13.0,19.0,11.0,15.0,16.0,18.0,14.0,FGHFHAFEAGGHFBHEBABAFBGFDFHEEGEDAEBBEBDECAFAACCBCDACFHCAHCFHGHHGCBCFGHGHHADGDDCDBCECDBGDGEDGEFCCGHAGECGECGAGAAEAFFCFFCEBCB,False +971,4.0,3.0,0.0,5.0,2.0,3.0,5.0,1.0,DAGAHGDGBDEFAEFABFGDGBD,True +972,7.0,2.0,1.0,3.0,2.0,2.0,4.0,4.0,HCFDAHGAHABGADEHDEABGAFGA,True +973,2.0,6.0,7.0,4.0,4.0,5.0,7.0,4.0,FBGDEGHCGHAGBDGCEGCGCCFDCAHFBCFBHEBDFBE,False +974,17.0,19.0,14.0,32.0,17.0,26.0,26.0,16.0,EBDHBAEGEFDDBGDAGDHGFFBFDGGDAGAAEFAEFCEHCBCCAGCBDFBDFADHGDHEDAEBHFDHBDHBDGBGEBDCCDGCDFCEFBEGEFHAGHAGFAGFAHDDDDGDFGAEDEBDCHGGEEGDBCCHDGAFGHBGABDFFFCBFAEDDHCFFFFDFDHGGBF,False +975,8.0,18.0,16.0,11.0,10.0,10.0,17.0,15.0,EBFCBFCBCBBGFAFFCHFHHBDHBDBCEGDHGBGEBGDBDDHCDEBACCGHDGEFGAGCCGCCGAEHDCHECHGCDFFGGBGGBAHBFHADGAEHBBAEHCEHB,False +976,27.0,32.0,25.0,20.0,17.0,19.0,24.0,36.0,HCFABFDBGEFGFDCBDCAEBHEDADCADCGBCDACDBBHBBDAHAHHFFGEFHHBBHEFAEDHEHHBHHDAHCACCDDDAHCEECBBHBHHBGDBGBBGHCAHCFHFHGCHGAEGFFBBHCBHAAABACEGCGGCGACFACGHBDCBHCGGEHEBGAFFAEHHDFHDFEGFABDABGBBECBEBGAAFAACGHGHHGDH,False +977,21.0,23.0,33.0,29.0,26.0,21.0,26.0,19.0,BFCBCBEGFEGDEGFEBDACFGCDGADCDDCBBCGCDDCGCCGDDGBFBEEBAABAACFCCFHDDHDEBDEFCEBBGBEEDAEAHFCHFHHEBEEFFEFHEADEGEGGCGGADDFBCADDDCCGCCGCDGEDFADGDFGFFBCAAHAHEFHECAGFGDCEDCADBAHHHHEHHEFHBCCCCBBAABCAHHDGBEGCGG,False +978,7.0,8.0,10.0,5.0,10.0,5.0,5.0,1.0,DECDEBFCGFADFEBAECABABEGGECDFCGBEGCEHCBDCBCABCAEAFE,True +979,1.0,2.0,1.0,6.0,0.0,1.0,0.0,1.0,DCADFBDHDDBD,True +980,24.0,21.0,18.0,12.0,17.0,7.0,12.0,18.0,BBAHBHDDHBHFAHACBEBBCBAEEACHAHHEGBBGBCDCCAECAHCAGGAFFACFAHHEEAEHFGCACEACHFCHDDEDDEDDCBCCHEBHBAHEABBGBBADBGBBEAAGAADHEGEGGEGAFDACC,False +981,22.0,33.0,18.0,23.0,27.0,28.0,28.0,13.0,EAEDGBCFBAFBGFDAFAAGHAEBFHFFHFFGACDBDFCDFGDBEBBDHCFBEEGGDAGECGEFABFGBEDAEAHEGDDBEGCDABHBBGBDFBDHBGBBEBBHABAABDCEFGAFGAFBFCEFBGGHAGAFEDGEDCHFHBFGDHCFHCAGFDGCGECFECBECBECECABCAEFBEFEEGDBGDEGDBGD,False +982,22.0,20.0,15.0,16.0,27.0,17.0,27.0,21.0,GDFGHEGBEHCEBCHBEHBAHGCGGEGBBFDEADFFHADHEBHGDACDACDEBEEGEHBEGBEGHEBFAAFGFFGDFGDFABGHFHCEECHDGBDCBFFBGCBDDHDCGBCFAFHGGHEGACHECAEAAHCABAACAHEEDEADEFEGBGGEGAAGEBGFAHHAE,False +983,6.0,5.0,6.0,11.0,8.0,8.0,5.0,7.0,HBFHDFCEABBADECDEGDFCDFHBFEDECCFGHFAHGHHADEADFCDGDDGEBAE,False +984,9.0,13.0,13.0,13.0,32.0,25.0,15.0,18.0,EEAEEGEABEGHGFDADEEFAHHCBFGDCBBCHBCFDCFDCFDEFDEFCHFEFECFEHFHGFHGFHEBBCGECBDHHEEDEFCEGAADEFEHGEDFEHFEDFEGBHHFHGEEGEGAACFABFGFDGBEECEEFHBFHB,False +985,14.0,10.0,10.0,7.0,7.0,11.0,13.0,6.0,FAFAHGABAACAAGAFCDDCGCEFDBGBGACHECAECAEBAHDDFDBFDBFGBAGCHBEHBAGBECFFCEFGGGGGFH,False 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+991,18.0,26.0,30.0,28.0,39.0,25.0,17.0,17.0,ACBACBFFBACEFCFACFBDEBDEHCFHCDHEDAFCAFEAGEDGEGBEDEDGEFADCEDGECCCDFEDGEBEHBCFBCBDCBEFHDFAEECEFCEFBBFEBDEADEGEEAEEHEDFADGDHGBBACBGHFGHABBACCDCCECGECDHHHAEBBHBHGBCFFAEDDGFDEBHEBFEHCCFDGEDCDCHEBDEGDEGFFCA,False +992,19.0,14.0,13.0,21.0,20.0,19.0,18.0,15.0,GGFGDFGACGCFHCEHFECCAGBDFBDGADCDEBHFBHDAHEHCBHBEDBEDFADBHDFDEBDEGAAHAAEFAEFGEFGDFGEHAEDCDDHGDHDFADFEEAEBADBCHCHGCAGEGGFDEFEFGAAACACFHBGBBEF,False +993,25.0,22.0,19.0,27.0,20.0,17.0,20.0,31.0,GHDGEDGEGAEGFEHDBHDEFDEACEAGEHFDFFDFFHGEADEBHGHDDBDGBAEFCHCBHGBADBDFCHCABGDCDDHEDHDCBBAHACHGHHEAHBAHBCHAHBGHEDDEAHEDCGCCDAHAFHFBBABBHBFHBAGBCGBFFHFEGEEACCAGCABFAGGADHCDHCDHAHADDACEF,False +994,11.0,8.0,14.0,13.0,20.0,15.0,19.0,10.0,DHBGHCGCCAFEBGCDAEGAEGADDAGEEBEGBEGDFGHECFACFHEEBEECCEBDAGFBFEGHEGDABCEEGEAGDDHCAHCGHFGDDEFHEFHFFCFGCFGFAGFDCD,False +995,4.0,5.0,0.0,4.0,3.0,4.0,11.0,4.0,HGFEAHEADDGFGGFHGFBGBGGBGBBHAGGDDAE,True 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For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/src/main/scala/org/xcit/nback/markov/models/State.scala b/src/main/scala/org/xcit/nback/markov/models/State.scala deleted file mode 100644 index fbbd844..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/State.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * A Single state with a label in Markov chain - * @param label A simple string label, representing the state and node - */ -class State(val label: String) { - - /** - * Keep track of transitions from this state to other states. - */ - val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() -} diff --git a/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/src/main/scala/org/xcit/nback/markov/models/Transition.scala deleted file mode 100644 index bc20a9e..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/Transition.scala +++ /dev/null @@ -1,8 +0,0 @@ -package org.xcit.nback.markov.models - -/** - * A Single transition in Markov chain graph. It is stored in "from" node. - * @param to the ending node of the edge - * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). - */ -case class Transition(to: State, probability: Double = 0.0) diff --git a/src/test/scala/ThreeBackBenchmark.scala b/src/test/scala/ThreeBackBenchmark.scala deleted file mode 100644 index 0c7dad9..0000000 --- a/src/test/scala/ThreeBackBenchmark.scala +++ /dev/null @@ -1,7 +0,0 @@ - -/** - * TODO Benchmark 3-back simple sequence generator - */ -class ThreeBackBenchmark { - -} diff --git a/tests/benchmark_diagrams.py b/tests/benchmark_diagrams.py new file mode 100644 index 0000000..8fa448e --- /dev/null +++ b/tests/benchmark_diagrams.py @@ -0,0 +1,159 @@ +import pandas as pd +import numpy as np +from matplotlib import pyplot as plt + +import benchmarks.common as common + + +def tlratio(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2,ignore_index=True) + stats = [] + for trials in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == trials) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == trials) + targets2 = data[alg2].targets if alg2.shape[0] > 0 else np.nan + targets4 = data[alg4].targets if alg4.shape[0] > 0 else np.nan + lures2 = data[alg2].lures if alg2.shape[0] > 0 else np.nan + lures4 = data[alg4].lures if alg4.shape[0] > 0 else np.nan + stats.append([trials, (targets2/lures2).mean(), (targets4/lures4).mean()]) + stats = pd.DataFrame(stats, columns=['trials', 'tl2', 'tl4']) #.dropna(subset=['skewness']) + + plt.style.use('ggplot') + + plt.ylim(bottom=0, top=30) + plt.scatter(stats.trials, stats.tl2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl2[idx], 1)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.tl4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl4[idx], 2)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('T:L Ratio') + plt.ylabel('T:L Ratio') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_tlratio.png', bbox_inches='tight') + plt.show() + + +def time_per_trial(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for t in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == t) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == t) + time2 = data[alg2].time.mean() * 1000 if alg2.shape[0] > 0 else np.nan + time4 = data[alg4].time.mean() * 1000 if alg4.shape[0] > 0 else np.nan + stats.append([t, time2, time4]) + stats = pd.DataFrame(stats, columns=['trials', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.trials, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time2[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time4[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2v4_time_trials.png', bbox_inches='tight') + plt.show() + +def time_profiles(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 8): + alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + time2 = data[alg2].time.mean() * 1000 + time4 = data[alg4].time.mean() * 1000 + stats.append([ni, time2, time4]) + stats = pd.DataFrame(stats, columns=['n', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.n, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.time2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + plt.scatter(stats.n, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.time4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_time_n.png', bbox_inches='tight') + plt.show() + +def skewness(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 9): + all_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + skewed_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) & data.skewed + all_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + skewed_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) & data.skewed + num_of_sequences2 = data[all_alg2].shape[0] + skewed_sequences2 = data[skewed_alg2].shape[0] + num_of_sequences4 = data[all_alg4].shape[0] + skewed_sequences4 = data[skewed_alg4].shape[0] + skewness2 = skewed_sequences2 * 100.0 / num_of_sequences2 if (num_of_sequences2>0) else 0 + skewness4 = skewed_sequences4 * 100.0 / num_of_sequences4 if (num_of_sequences4>0) else 0 + stats.append([ni, skewness2, skewness4]) + stats = pd.DataFrame(stats, columns=['n', 'skewness2', 'skewness4']) #.dropna(subset=['skewness']) + + + plt.style.use('ggplot') + plt.scatter(stats.n, stats.skewness2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.skewness2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + + plt.scatter(stats.n, stats.skewness4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.skewness4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Skewness') + plt.ylabel('Skewed Blocks (%)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_skewness.png', bbox_inches='tight') + plt.show() + +if __name__ == "__main__": + tlratio() + skewness() + time_profiles() + time_per_trial() diff --git a/tests/benchmark_skewness.py b/tests/benchmark_skewness.py new file mode 100644 index 0000000..f468b4d --- /dev/null +++ b/tests/benchmark_skewness.py @@ -0,0 +1,97 @@ +import random +import heapq +import csv + +# Common parameters +alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'] +trials_range = (10, 40) +n = 3 +sample_size = 100 + + +def to_benchmark_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [str(ralph_skewed)] + +def benchmark_nb_gm_001(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_001') + + +def benchmark_nb_gm_002(filename): + import generators.nb_gm_002 as nb_gm_002 + + generator = nb_gm_002.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + # print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_002') + + +def benchmark_nb_gm_003(filename): + import generators.nb_gm_003 as nb_gm_003 + + generator = nb_gm_003.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + print(f"sequence {i}/{sample_size}: {trials} trials") + seq = generator.generate(trials) + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_003') + + +def show_skweness_diagram(filename, choices, title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + print(filename) + data = pd.read_csv(filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) #.dropna(subset=['skewness']) + #print(stats.trials) + #plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'{title}.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + benchmark_nb_gm_003('../benchmarks/nb_gm_003_2back.csv') diff --git a/tests/common.py b/tests/common.py new file mode 100644 index 0000000..e40c0df --- /dev/null +++ b/tests/common.py @@ -0,0 +1,27 @@ + + +# Common benchmark parameters +choices = alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F'] +trials_range = (10, 65) +n = 4 +sample_size = 100 + + +def count_targets_and_lures(seq, n): + mask = 'D'*n + for index in range(n, len(seq)): + if seq[index] == seq[index - n]: + mask += 'T' + elif seq[index] in seq[index - n - 1:index - n + 1]: + mask += 'L' + else: + mask += 'D' + return mask.count('T'), mask.count('L') + + +def skewness(seq, choices): + import heapq + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return ralph_skewed diff --git a/tests/nb_gm_001_bm.py b/tests/nb_gm_001_bm.py new file mode 100644 index 0000000..54f6cb3 --- /dev/null +++ b/tests/nb_gm_001_bm.py @@ -0,0 +1,75 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq) , str(ralph_skewed)] + + +def benchmark(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets / s.trials, axis=1) + plt.scatter(data.trials, data.targets_ratio, alpha=0.2) + plt.show() + +if __name__ == '__main__': + alg = 'nb_gm_001' + fn = f'results/{alg}_{n}back.csv' + benchmark(fn) + # skewness_diagram(fn, alg) + targets_ratio_diagram(fn, alg) diff --git a/tests/nb_gm_002_bm.py b/tests/nb_gm_002_bm.py new file mode 100644 index 0000000..c8af543 --- /dev/null +++ b/tests/nb_gm_002_bm.py @@ -0,0 +1,105 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq), str(ralph_skewed)] + + +def benchmark(filename): + from generators.nb_gm_002 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials, int(trials/3), 0, 0) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +import time +import numpy as np +import pandas as pd + +import benchmarks.common as common + +def profile(): + from generators.nb_gm_002 import SequenceGenerator + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, int(lures/2), int(lures/2)) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('benchmarks/results/nb_gm_002_profile.csv', sep=',', encoding='utf-8') + +if __name__ == '__main__': + alg = 'nb_gm_002' + fn = f'results/{alg}_{n}back.csv' + profile() diff --git a/tests/nb_gm_003_bm.py b/tests/nb_gm_003_bm.py new file mode 100644 index 0000000..fa6c19a --- /dev/null +++ b/tests/nb_gm_003_bm.py @@ -0,0 +1,114 @@ +import heapq +import csv +import random +import time + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq, time_per_block): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [time_per_block, ''.join(seq), str(ralph_skewed)] + + +def benchmark_skewness(filename): + from generators.nb_gm_003 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['time_per_block', 'seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + targets = trials / 3 + t = time.time() + seq = generator.generate(trials, targets) + t = time.time() - t + print(f"sequence {i}/{sample_size}: {trials} trials, took {t}s.") + writer.writerow(to_csv_row(i, seq, t)) + plot_skewness(fn, 'nb_gm_003') + + +def plot_skewness(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def plot_targets_ratio(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +def benchmark_targets_ratio(): + pass + +def benchmark_chunking(): + pass + + +def benchmark_n(): + pass + + +def plot_timing(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['time_per_trial'] = data.apply(lambda s: s.time_per_block / s.trials, axis=1) + plt.style.use('ggplot') + plt.title(f"{figure_title} - average time to generate a trial") + plt.ylabel('time (s)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.time_per_trial, alpha=0.5) + + # draw fitted curve + # import numpy as np + # p = np.poly1d(np.polyfit(data.trials, data.time_per_trial, 3)) + # plt.plot(data.trials, p(data.trials), color='red') + + plt.savefig(f'results/{figure_title}_timing.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + alg = 'nb_gm_003' + fn = f'results/{alg}_{n}back.csv' + benchmark_skewness(fn) diff --git a/tests/nb_gm_004_bm.py b/tests/nb_gm_004_bm.py new file mode 100644 index 0000000..b4ad4a8 --- /dev/null +++ b/tests/nb_gm_004_bm.py @@ -0,0 +1,26 @@ +import time +import numpy as np +import pandas as pd + +import tests.common as common +from generators.nb_gm_004 import SequenceGenerator + +def run(): + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, lures) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('tests/results/nb_gm_004_profile.csv', sep=',', encoding='utf-8') diff --git a/tests/results/2v4_time_trials.png b/tests/results/2v4_time_trials.png new file mode 100644 index 0000000..9be91b4 --- /dev/null +++ b/tests/results/2v4_time_trials.png Binary files differ diff --git a/tests/results/2vs4_skewness.png b/tests/results/2vs4_skewness.png new file mode 100644 index 0000000..a488e1f --- /dev/null +++ b/tests/results/2vs4_skewness.png Binary files differ diff --git a/tests/results/2vs4_time_n.png b/tests/results/2vs4_time_n.png new file mode 100644 index 0000000..d022ed0 --- /dev/null +++ b/tests/results/2vs4_time_n.png Binary files differ diff --git a/tests/results/2vs4_tlratio.png b/tests/results/2vs4_tlratio.png new file mode 100644 index 0000000..b76f296 --- /dev/null +++ b/tests/results/2vs4_tlratio.png Binary files differ diff --git a/tests/results/nb_gm_001_2back.csv b/tests/results/nb_gm_001_2back.csv new file mode 100644 index 0000000..f6ad25e --- /dev/null +++ b/tests/results/nb_gm_001_2back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,0.0,1.0,0.0,55.0,56.0,0.0,0.0,0.0,BEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True 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+364,0.0,0.0,0.0,1.0,0.0,31.0,0.0,31.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +365,0.0,0.0,0.0,24.0,0.0,23.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +366,0.0,15.0,0.0,0.0,16.0,0.0,0.0,0.0,EEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +367,22.0,0.0,0.0,0.0,0.0,0.0,1.0,22.0,GHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +368,0.0,25.0,0.0,0.0,0.0,0.0,25.0,0.0,BGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +369,0.0,0.0,0.0,100.0,1.0,0.0,0.0,0.0,EDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +370,0.0,17.0,0.0,17.0,1.0,0.0,0.0,0.0,EBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +371,0.0,1.0,49.0,0.0,49.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True 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+377,27.0,0.0,0.0,29.0,0.0,0.0,0.0,0.0,DDADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +378,81.0,0.0,0.0,81.0,0.0,0.0,0.0,1.0,HADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +379,1.0,0.0,9.0,0.0,8.0,0.0,0.0,0.0,ACECECECECECECECEC,True +380,1.0,0.0,0.0,32.0,33.0,0.0,0.0,0.0,AEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +381,5.0,0.0,5.0,0.0,1.0,0.0,0.0,0.0,ECACACACACA,True +382,0.0,0.0,0.0,96.0,0.0,0.0,98.0,0.0,GGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +383,0.0,86.0,0.0,0.0,0.0,85.0,0.0,0.0,BBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +384,0.0,0.0,28.0,0.0,1.0,0.0,0.0,28.0,ECHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +385,0.0,1.0,119.0,0.0,0.0,0.0,0.0,0.0,BCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +386,0.0,0.0,93.0,0.0,0.0,93.0,1.0,0.0,GCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCF,True +387,92.0,0.0,1.0,0.0,92.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +388,0.0,186.0,0.0,0.0,0.0,0.0,0.0,0.0,BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +389,1.0,74.0,0.0,0.0,0.0,0.0,0.0,0.0,ABBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +390,0.0,0.0,0.0,0.0,1.0,86.0,0.0,87.0,EHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +391,61.0,0.0,0.0,61.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +392,0.0,0.0,0.0,1.0,16.0,0.0,0.0,15.0,DEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +393,118.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +394,0.0,0.0,0.0,0.0,0.0,75.0,0.0,1.0,HFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +395,30.0,0.0,0.0,0.0,0.0,0.0,0.0,30.0,AHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +396,65.0,0.0,0.0,0.0,0.0,1.0,0.0,65.0,FAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +397,0.0,0.0,0.0,55.0,56.0,0.0,0.0,0.0,EEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +398,26.0,0.0,0.0,25.0,1.0,0.0,0.0,0.0,EADADADADADADADADADADADADADADADADADADADADADADADADADA,True +399,0.0,0.0,60.0,0.0,0.0,0.0,1.0,59.0,GCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +400,1.0,0.0,0.0,0.0,160.0,0.0,0.0,0.0,AEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +401,1.0,0.0,31.0,0.0,0.0,31.0,0.0,0.0,AFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +402,0.0,0.0,0.0,15.0,1.0,0.0,0.0,0.0,EDDDDDDDDDDDDDDD,True +403,0.0,0.0,0.0,54.0,55.0,0.0,0.0,1.0,HEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +404,0.0,0.0,0.0,27.0,0.0,27.0,0.0,1.0,HFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +405,0.0,0.0,0.0,1.0,0.0,15.0,0.0,15.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +406,0.0,95.0,0.0,94.0,0.0,1.0,0.0,0.0,FBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +407,0.0,0.0,15.0,14.0,0.0,0.0,0.0,0.0,CCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +408,78.0,78.0,0.0,0.0,0.0,0.0,1.0,0.0,GBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +409,0.0,0.0,72.0,1.0,0.0,0.0,72.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +410,55.0,0.0,1.0,0.0,0.0,0.0,55.0,0.0,CAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +411,0.0,59.0,0.0,0.0,0.0,60.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +412,61.0,0.0,0.0,61.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +413,0.0,1.0,0.0,75.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +414,0.0,53.0,0.0,0.0,0.0,0.0,52.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +415,0.0,0.0,16.0,0.0,1.0,0.0,0.0,15.0,ECHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +416,0.0,0.0,0.0,39.0,0.0,0.0,0.0,38.0,DHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +417,96.0,0.0,1.0,95.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +418,28.0,0.0,1.0,27.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +419,0.0,1.0,92.0,92.0,0.0,0.0,0.0,0.0,BCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +420,1.0,0.0,20.0,0.0,20.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECE,True +421,0.0,90.0,0.0,0.0,0.0,0.0,89.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +422,10.0,0.0,0.0,0.0,0.0,1.0,11.0,0.0,FGAGAGAGAGAGAGAGAGAGAG,True +423,0.0,0.0,0.0,74.0,73.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +424,0.0,0.0,127.0,0.0,0.0,0.0,1.0,0.0,GCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +425,1.0,9.0,0.0,0.0,0.0,9.0,0.0,0.0,AFBFBFBFBFBFBFBFBFB,True +426,0.0,0.0,84.0,0.0,0.0,0.0,0.0,84.0,HCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +427,33.0,0.0,0.0,34.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +428,1.0,30.0,0.0,30.0,0.0,0.0,0.0,0.0,ABDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +429,0.0,0.0,67.0,0.0,1.0,67.0,0.0,0.0,EFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +430,62.0,0.0,0.0,63.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +431,1.0,9.0,9.0,0.0,0.0,0.0,0.0,0.0,ABCBCBCBCBCBCBCBCBC,True +432,15.0,0.0,0.0,0.0,0.0,0.0,14.0,0.0,AAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +433,0.0,1.0,0.0,65.0,66.0,0.0,0.0,0.0,BEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +434,0.0,160.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +435,0.0,0.0,1.0,0.0,42.0,42.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +436,0.0,0.0,55.0,0.0,55.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +437,0.0,0.0,0.0,1.0,0.0,73.0,0.0,73.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +438,79.0,0.0,0.0,0.0,78.0,0.0,0.0,0.0,AAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +439,0.0,0.0,67.0,0.0,0.0,0.0,66.0,1.0,HCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +440,0.0,0.0,77.0,0.0,0.0,1.0,0.0,76.0,FCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +441,0.0,0.0,0.0,0.0,153.0,0.0,0.0,1.0,HEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +442,0.0,88.0,88.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +443,0.0,0.0,0.0,20.0,22.0,0.0,0.0,0.0,EEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +444,41.0,0.0,42.0,0.0,0.0,0.0,1.0,0.0,GCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +445,0.0,0.0,0.0,47.0,0.0,46.0,0.0,1.0,HDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +446,1.0,0.0,0.0,0.0,86.0,0.0,0.0,87.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +447,56.0,56.0,0.0,0.0,0.0,0.0,0.0,1.0,HABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +448,0.0,0.0,0.0,0.0,11.0,0.0,0.0,10.0,EEHEHEHEHEHEHEHEHEHEH,True +449,0.0,0.0,0.0,0.0,0.0,1.0,92.0,92.0,FGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +450,0.0,0.0,0.0,6.0,5.0,1.0,0.0,0.0,FDEDEDEDEDED,True +451,66.0,1.0,67.0,0.0,0.0,0.0,0.0,0.0,BCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +452,0.0,0.0,0.0,13.0,0.0,1.0,12.0,0.0,FDGDGDGDGDGDGDGDGDGDGDGDGD,True +453,1.0,0.0,0.0,0.0,56.0,0.0,56.0,0.0,AEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +454,15.0,0.0,0.0,0.0,0.0,0.0,0.0,16.0,HAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +455,0.0,21.0,1.0,0.0,21.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True +456,93.0,0.0,1.0,0.0,92.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +457,1.0,0.0,0.0,0.0,35.0,0.0,0.0,35.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +458,13.0,0.0,0.0,0.0,1.0,0.0,13.0,0.0,EAGAGAGAGAGAGAGAGAGAGAGAGAG,True +459,0.0,0.0,65.0,0.0,1.0,0.0,65.0,0.0,ECGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +460,0.0,0.0,95.0,1.0,0.0,95.0,0.0,0.0,DFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +461,15.0,0.0,0.0,0.0,1.0,0.0,0.0,15.0,EHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +462,0.0,0.0,198.0,0.0,1.0,0.0,0.0,0.0,ECCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +463,84.0,84.0,0.0,0.0,1.0,0.0,0.0,0.0,EABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +464,0.0,0.0,0.0,0.0,0.0,60.0,0.0,61.0,HFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +465,0.0,179.0,0.0,1.0,0.0,0.0,0.0,0.0,DBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +466,1.0,0.0,90.0,0.0,89.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +467,0.0,35.0,0.0,0.0,0.0,34.0,0.0,0.0,BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +468,0.0,0.0,0.0,1.0,7.0,0.0,0.0,7.0,DHEHEHEHEHEHEHE,True +469,0.0,0.0,0.0,0.0,92.0,0.0,91.0,0.0,EEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +470,0.0,0.0,46.0,0.0,0.0,1.0,46.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +471,0.0,0.0,0.0,0.0,0.0,1.0,158.0,0.0,FGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +472,1.0,0.0,0.0,0.0,0.0,58.0,0.0,59.0,AHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +473,0.0,0.0,6.0,1.0,0.0,0.0,6.0,0.0,DCGCGCGCGCGCG,True +474,0.0,0.0,0.0,0.0,0.0,98.0,0.0,97.0,FFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +475,0.0,87.0,0.0,0.0,0.0,0.0,0.0,85.0,BBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +476,0.0,0.0,33.0,0.0,0.0,0.0,1.0,33.0,GHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +477,45.0,0.0,0.0,0.0,46.0,0.0,0.0,0.0,EAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +478,0.0,0.0,0.0,77.0,0.0,0.0,75.0,0.0,DDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +479,73.0,1.0,73.0,0.0,0.0,0.0,0.0,0.0,BACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +480,0.0,1.0,0.0,0.0,37.0,37.0,0.0,0.0,BEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +481,0.0,92.0,93.0,0.0,0.0,1.0,0.0,0.0,FCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +482,0.0,0.0,0.0,1.0,0.0,0.0,0.0,24.0,DHHHHHHHHHHHHHHHHHHHHHHHH,True +483,25.0,0.0,0.0,1.0,0.0,25.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +484,0.0,0.0,0.0,0.0,0.0,37.0,0.0,36.0,FHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +485,21.0,0.0,0.0,1.0,0.0,20.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +486,0.0,35.0,0.0,36.0,0.0,0.0,0.0,1.0,HDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +487,0.0,0.0,1.0,0.0,97.0,98.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +488,0.0,93.0,0.0,0.0,0.0,1.0,0.0,94.0,FHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +489,0.0,1.0,0.0,93.0,0.0,0.0,93.0,0.0,BGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +490,0.0,0.0,0.0,70.0,0.0,0.0,72.0,0.0,GGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +491,86.0,0.0,0.0,0.0,1.0,86.0,0.0,0.0,EFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +492,0.0,65.0,1.0,0.0,0.0,65.0,0.0,0.0,CBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +493,0.0,0.0,0.0,69.0,0.0,0.0,0.0,1.0,HDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +494,0.0,0.0,144.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +495,0.0,45.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +496,0.0,0.0,0.0,28.0,0.0,27.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +497,0.0,72.0,0.0,0.0,0.0,1.0,73.0,0.0,FGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +498,0.0,0.0,41.0,0.0,1.0,0.0,40.0,0.0,ECGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +499,0.0,1.0,0.0,0.0,0.0,131.0,0.0,0.0,BFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +500,17.0,0.0,0.0,1.0,0.0,17.0,0.0,0.0,DFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +501,19.0,0.0,0.0,19.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADA,True +502,1.0,0.0,0.0,0.0,51.0,0.0,52.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +503,1.0,0.0,0.0,0.0,0.0,0.0,29.0,29.0,AGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +504,36.0,0.0,0.0,1.0,0.0,35.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +505,0.0,0.0,0.0,20.0,0.0,0.0,1.0,20.0,GDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +506,0.0,0.0,0.0,163.0,0.0,0.0,0.0,1.0,HDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +507,22.0,23.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABAB,True +508,0.0,1.0,0.0,0.0,0.0,0.0,41.0,42.0,BHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +509,0.0,0.0,0.0,45.0,1.0,0.0,0.0,44.0,EDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True 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+671,99.0,0.0,1.0,0.0,98.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +672,68.0,0.0,0.0,0.0,0.0,0.0,67.0,1.0,HAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGA,True +673,0.0,0.0,0.0,26.0,27.0,0.0,1.0,0.0,GEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +674,31.0,0.0,0.0,0.0,32.0,0.0,0.0,1.0,HEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +675,0.0,0.0,0.0,0.0,42.0,0.0,41.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +676,0.0,0.0,50.0,0.0,0.0,0.0,1.0,50.0,GCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +677,0.0,25.0,0.0,24.0,0.0,0.0,0.0,0.0,BBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +678,0.0,0.0,0.0,0.0,1.0,10.0,9.0,0.0,EFGFGFGFGFGFGFGFGFGF,True +679,65.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,DAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +680,0.0,23.0,0.0,0.0,0.0,0.0,23.0,1.0,HGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +681,0.0,1.0,58.0,0.0,0.0,0.0,57.0,0.0,BCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +682,0.0,0.0,0.0,0.0,0.0,68.0,1.0,68.0,GFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +683,0.0,0.0,0.0,0.0,96.0,0.0,96.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +684,1.0,0.0,0.0,0.0,66.0,0.0,66.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +685,0.0,0.0,0.0,0.0,0.0,1.0,0.0,21.0,FHHHHHHHHHHHHHHHHHHHHH,True +686,0.0,88.0,0.0,87.0,0.0,0.0,0.0,0.0,BDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +687,0.0,0.0,19.0,19.0,0.0,0.0,1.0,0.0,GDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +688,0.0,42.0,1.0,0.0,41.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +689,0.0,0.0,0.0,0.0,0.0,60.0,61.0,0.0,GGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +690,0.0,23.0,23.0,0.0,0.0,0.0,1.0,0.0,GBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +691,86.0,86.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +692,35.0,35.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +693,57.0,0.0,0.0,0.0,0.0,58.0,1.0,0.0,GFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +694,0.0,0.0,30.0,30.0,1.0,0.0,0.0,0.0,EDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +695,19.0,18.0,0.0,1.0,0.0,0.0,0.0,0.0,DABABABABABABABABABABABABABABABABABABA,True +696,0.0,0.0,0.0,1.0,0.0,56.0,0.0,57.0,DHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +697,10.0,0.0,1.0,0.0,0.0,0.0,0.0,11.0,CHAHAHAHAHAHAHAHAHAHAH,True +698,0.0,0.0,89.0,0.0,88.0,0.0,1.0,0.0,GCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +699,0.0,0.0,87.0,0.0,86.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +700,17.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAA,True +701,0.0,0.0,66.0,65.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +702,0.0,0.0,1.0,0.0,0.0,0.0,123.0,0.0,CGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +703,0.0,118.0,0.0,0.0,1.0,0.0,0.0,0.0,EBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +704,0.0,0.0,0.0,0.0,0.0,0.0,0.0,132.0,HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +705,0.0,0.0,0.0,0.0,0.0,23.0,1.0,23.0,GHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +706,0.0,0.0,0.0,0.0,6.0,5.0,0.0,0.0,EFEFEFEFEFE,True +707,18.0,0.0,0.0,16.0,0.0,0.0,0.0,0.0,AADADADADADADADADADADADADADADADADA,True +708,0.0,72.0,0.0,0.0,0.0,71.0,0.0,1.0,HBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +709,0.0,0.0,54.0,0.0,0.0,1.0,0.0,55.0,FHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +710,0.0,1.0,87.0,0.0,87.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +711,0.0,0.0,1.0,63.0,0.0,0.0,0.0,64.0,CHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +712,78.0,0.0,78.0,0.0,0.0,1.0,0.0,0.0,FCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +713,0.0,80.0,0.0,0.0,0.0,81.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +714,0.0,1.0,0.0,0.0,0.0,0.0,40.0,39.0,BGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +715,0.0,0.0,7.0,0.0,6.0,0.0,0.0,0.0,CCECECECECECE,True +716,35.0,0.0,0.0,0.0,0.0,0.0,0.0,33.0,AAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +717,0.0,0.0,0.0,1.0,73.0,0.0,0.0,72.0,DEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +718,0.0,0.0,90.0,0.0,0.0,1.0,89.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +719,1.0,0.0,0.0,67.0,0.0,0.0,0.0,66.0,ADHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +720,56.0,0.0,0.0,0.0,56.0,0.0,1.0,0.0,GAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +721,0.0,0.0,0.0,1.0,0.0,0.0,49.0,49.0,DHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +722,0.0,0.0,0.0,117.0,0.0,1.0,0.0,0.0,FDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +723,0.0,0.0,86.0,1.0,0.0,0.0,85.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +724,0.0,0.0,31.0,0.0,0.0,0.0,0.0,30.0,CCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +725,1.0,0.0,0.0,0.0,98.0,0.0,98.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +726,1.0,84.0,84.0,0.0,0.0,0.0,0.0,0.0,ACBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +727,0.0,56.0,56.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +728,0.0,1.0,0.0,24.0,24.0,0.0,0.0,0.0,BDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +729,37.0,0.0,0.0,0.0,0.0,37.0,0.0,0.0,FAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +730,0.0,0.0,91.0,0.0,0.0,0.0,91.0,0.0,GCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +731,98.0,0.0,99.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +732,0.0,0.0,0.0,0.0,99.0,1.0,98.0,0.0,FEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +733,0.0,0.0,30.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +734,12.0,1.0,13.0,0.0,0.0,0.0,0.0,0.0,BCACACACACACACACACACACACAC,True +735,0.0,93.0,1.0,0.0,93.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True 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+852,0.0,1.0,0.0,0.0,136.0,0.0,0.0,0.0,BEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +853,0.0,0.0,0.0,0.0,1.0,0.0,0.0,163.0,EHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +854,74.0,0.0,75.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +855,0.0,0.0,0.0,19.0,0.0,0.0,17.0,0.0,DDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +856,0.0,73.0,0.0,1.0,0.0,0.0,74.0,0.0,DGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True 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+863,0.0,0.0,0.0,32.0,1.0,0.0,32.0,0.0,EGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +864,0.0,0.0,15.0,0.0,1.0,14.0,0.0,0.0,ECFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +865,0.0,1.0,98.0,0.0,0.0,0.0,98.0,0.0,BGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +866,1.0,0.0,0.0,0.0,19.0,0.0,0.0,0.0,AEEEEEEEEEEEEEEEEEEE,True +867,24.0,0.0,0.0,0.0,24.0,0.0,0.0,0.0,AEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +868,0.0,0.0,0.0,74.0,0.0,0.0,0.0,73.0,DHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +869,0.0,78.0,1.0,0.0,0.0,0.0,77.0,0.0,CBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +870,0.0,0.0,1.0,0.0,50.0,0.0,51.0,0.0,CGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +871,0.0,0.0,16.0,0.0,0.0,16.0,0.0,1.0,HFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +872,0.0,0.0,0.0,1.0,28.0,28.0,0.0,0.0,DFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +873,0.0,0.0,65.0,65.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +874,0.0,34.0,0.0,0.0,0.0,35.0,0.0,0.0,FBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +875,0.0,0.0,9.0,0.0,8.0,0.0,0.0,1.0,HCECECECECECECECEC,True +876,0.0,0.0,0.0,0.0,94.0,0.0,94.0,1.0,HEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +877,0.0,18.0,0.0,16.0,0.0,0.0,0.0,0.0,BBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True 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+885,0.0,0.0,0.0,93.0,0.0,93.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDF,True +886,0.0,1.0,0.0,89.0,0.0,89.0,0.0,0.0,BFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +887,0.0,1.0,0.0,0.0,42.0,0.0,0.0,42.0,BHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +888,68.0,0.0,0.0,0.0,1.0,0.0,0.0,67.0,EAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +889,55.0,0.0,0.0,0.0,0.0,57.0,0.0,0.0,FFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +890,25.0,1.0,0.0,0.0,0.0,0.0,26.0,0.0,BGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +891,81.0,0.0,0.0,0.0,80.0,0.0,0.0,0.0,AAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +892,0.0,0.0,1.0,0.0,10.0,0.0,10.0,0.0,CGEGEGEGEGEGEGEGEGEGE,True +893,1.0,0.0,43.0,42.0,0.0,0.0,0.0,0.0,ACDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +894,55.0,54.0,0.0,0.0,0.0,0.0,0.0,0.0,AABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +895,43.0,0.0,0.0,0.0,0.0,1.0,0.0,43.0,FAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +896,1.0,0.0,0.0,0.0,97.0,97.0,0.0,0.0,AEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +897,0.0,25.0,0.0,1.0,0.0,25.0,0.0,0.0,DFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +898,0.0,0.0,0.0,0.0,26.0,26.0,1.0,0.0,GEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +899,0.0,0.0,36.0,0.0,36.0,0.0,0.0,0.0,ECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +900,0.0,0.0,0.0,0.0,1.0,0.0,89.0,88.0,EGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +901,0.0,1.0,142.0,0.0,0.0,0.0,0.0,0.0,BCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +902,1.0,83.0,0.0,83.0,0.0,0.0,0.0,0.0,ABDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +903,0.0,0.0,17.0,0.0,17.0,0.0,0.0,1.0,HECECECECECECECECECECECECECECECECEC,True +904,77.0,77.0,0.0,0.0,0.0,0.0,0.0,0.0,BABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +905,0.0,0.0,0.0,0.0,0.0,0.0,164.0,0.0,GGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +906,0.0,0.0,0.0,89.0,0.0,1.0,0.0,90.0,FHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +907,0.0,0.0,41.0,0.0,0.0,0.0,42.0,0.0,GCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +908,28.0,0.0,0.0,0.0,0.0,28.0,1.0,0.0,GAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +909,0.0,0.0,94.0,0.0,1.0,0.0,95.0,0.0,EGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +910,0.0,0.0,27.0,1.0,27.0,0.0,0.0,0.0,DECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +911,0.0,0.0,0.0,100.0,0.0,1.0,0.0,0.0,FDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +912,0.0,1.0,66.0,0.0,0.0,0.0,66.0,0.0,BGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +913,0.0,23.0,23.0,0.0,0.0,1.0,0.0,0.0,FCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +914,0.0,0.0,0.0,0.0,0.0,0.0,150.0,0.0,GGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +915,0.0,0.0,0.0,0.0,0.0,0.0,1.0,42.0,GHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +916,0.0,147.0,0.0,0.0,0.0,0.0,1.0,0.0,GBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +917,0.0,56.0,0.0,1.0,0.0,0.0,0.0,56.0,DHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +918,0.0,0.0,0.0,0.0,0.0,76.0,76.0,1.0,HFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFG,True +919,0.0,53.0,0.0,0.0,0.0,0.0,0.0,52.0,BHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +920,0.0,0.0,147.0,0.0,0.0,1.0,0.0,0.0,FCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +921,0.0,0.0,0.0,40.0,40.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +922,0.0,82.0,0.0,84.0,0.0,0.0,0.0,0.0,DDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +923,1.0,0.0,0.0,0.0,0.0,0.0,0.0,97.0,AHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +924,0.0,29.0,0.0,0.0,0.0,0.0,0.0,30.0,HHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +925,25.0,0.0,0.0,1.0,0.0,0.0,0.0,25.0,DHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +926,0.0,164.0,0.0,0.0,0.0,0.0,1.0,0.0,GBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +927,89.0,0.0,0.0,0.0,1.0,0.0,90.0,0.0,EGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +928,0.0,0.0,1.0,0.0,41.0,41.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +929,0.0,0.0,1.0,19.0,18.0,0.0,0.0,0.0,CDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +930,0.0,0.0,0.0,0.0,1.0,75.0,75.0,0.0,EGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +931,0.0,0.0,21.0,0.0,0.0,22.0,0.0,0.0,FCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCF,True +932,0.0,0.0,81.0,0.0,80.0,1.0,0.0,0.0,FCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +933,20.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAAAAA,True +934,0.0,40.0,0.0,0.0,0.0,40.0,0.0,0.0,BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +935,0.0,72.0,0.0,0.0,72.0,0.0,1.0,0.0,GBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True +936,56.0,1.0,0.0,56.0,0.0,0.0,0.0,0.0,BADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +937,0.0,0.0,0.0,0.0,0.0,96.0,1.0,0.0,GFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +938,0.0,1.0,0.0,88.0,0.0,0.0,0.0,88.0,BHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +939,1.0,0.0,0.0,0.0,0.0,0.0,0.0,175.0,AHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +940,0.0,0.0,84.0,1.0,83.0,0.0,0.0,0.0,DCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +941,0.0,0.0,83.0,0.0,0.0,0.0,0.0,85.0,HHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +942,1.0,5.0,5.0,0.0,0.0,0.0,0.0,0.0,ABCBCBCBCBC,True +943,0.0,0.0,0.0,68.0,0.0,0.0,0.0,69.0,HHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +944,29.0,0.0,0.0,0.0,0.0,29.0,1.0,0.0,GAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +945,0.0,0.0,1.0,0.0,0.0,0.0,81.0,82.0,CHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +946,89.0,0.0,89.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +947,0.0,0.0,0.0,78.0,1.0,0.0,0.0,0.0,EDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +948,90.0,1.0,0.0,0.0,0.0,0.0,91.0,0.0,BGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +949,0.0,0.0,0.0,86.0,1.0,0.0,0.0,86.0,EHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +950,0.0,0.0,0.0,42.0,1.0,0.0,42.0,0.0,EDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +951,85.0,0.0,0.0,84.0,1.0,0.0,0.0,0.0,EADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +952,90.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +953,0.0,0.0,1.0,0.0,0.0,90.0,0.0,0.0,CFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +954,62.0,0.0,0.0,1.0,0.0,62.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +955,0.0,20.0,20.0,0.0,1.0,0.0,0.0,0.0,EBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +956,0.0,0.0,37.0,0.0,0.0,1.0,0.0,38.0,FHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +957,98.0,1.0,0.0,0.0,0.0,98.0,0.0,0.0,BFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +958,0.0,1.0,0.0,0.0,189.0,0.0,0.0,0.0,BEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +959,0.0,0.0,0.0,9.0,0.0,1.0,8.0,0.0,FDGDGDGDGDGDGDGDGD,True +960,0.0,68.0,0.0,0.0,0.0,0.0,0.0,69.0,HHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +961,0.0,0.0,0.0,138.0,0.0,0.0,0.0,0.0,DDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +962,0.0,0.0,0.0,0.0,1.0,30.0,0.0,30.0,EHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +963,0.0,0.0,0.0,80.0,80.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +964,77.0,0.0,0.0,1.0,0.0,0.0,0.0,78.0,DHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +965,0.0,0.0,0.0,58.0,58.0,0.0,1.0,0.0,GEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +966,0.0,0.0,0.0,1.0,35.0,34.0,0.0,0.0,DEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +967,0.0,60.0,0.0,60.0,0.0,1.0,0.0,0.0,FDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +968,0.0,1.0,80.0,0.0,81.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +969,0.0,1.0,0.0,0.0,0.0,0.0,81.0,81.0,BGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +970,16.0,0.0,0.0,16.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADA,True +971,0.0,0.0,0.0,0.0,78.0,77.0,0.0,0.0,EFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +972,0.0,0.0,10.0,1.0,0.0,10.0,0.0,0.0,DFCFCFCFCFCFCFCFCFCFC,True +973,0.0,0.0,0.0,0.0,0.0,44.0,1.0,44.0,GHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +974,0.0,36.0,0.0,0.0,0.0,36.0,1.0,0.0,GFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +975,0.0,87.0,0.0,0.0,0.0,0.0,87.0,0.0,BGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +976,42.0,0.0,42.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True 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b/tests/results/nb_gm_001_3back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,0.0,65.0,132.0,0.0,0.0,0.0,0.0,1.0,HCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCC,True +1,51.0,0.0,52.0,52.0,0.0,0.0,0.0,1.0,HCDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACD,True +2,0.0,61.0,0.0,62.0,0.0,0.0,61.0,1.0,HDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGD,True +3,40.0,0.0,0.0,1.0,0.0,0.0,0.0,80.0,DHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHA,True +4,4.0,0.0,1.0,0.0,0.0,6.0,0.0,0.0,CAFFAFFAFFA,True 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+62,0.0,1.0,0.0,0.0,59.0,0.0,60.0,59.0,BGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEG,True +63,0.0,0.0,0.0,0.0,0.0,0.0,1.0,167.0,GHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +64,48.0,0.0,0.0,0.0,1.0,0.0,0.0,95.0,EHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHA,True +65,0.0,0.0,0.0,65.0,66.0,0.0,67.0,0.0,GGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGE,True +66,35.0,71.0,0.0,0.0,0.0,0.0,0.0,0.0,BBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBABBAB,True +67,50.0,0.0,0.0,50.0,50.0,0.0,0.0,1.0,HAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAEDAED,True +68,0.0,0.0,4.0,0.0,0.0,0.0,5.0,3.0,GCGHCGHCGHCG,True +69,0.0,0.0,5.0,0.0,0.0,0.0,1.0,10.0,GCHHCHHCHHCHHCHH,True +70,0.0,0.0,19.0,0.0,19.0,20.0,0.0,0.0,FECFECFECFECFECFECFECFECFECFECFECFECFECFECFECFECFECFECFECF,True +71,0.0,0.0,1.0,0.0,0.0,0.0,43.0,84.0,CGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHG,True +72,6.0,0.0,0.0,0.0,6.0,6.0,0.0,0.0,FAEFAEFAEFAEFAEFAE,True +73,0.0,0.0,35.0,35.0,35.0,0.0,0.0,1.0,HECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECD,True +74,25.0,0.0,26.0,0.0,1.0,0.0,0.0,25.0,ECAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHC,True +75,61.0,0.0,0.0,60.0,0.0,60.0,0.0,1.0,HAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDA,True +76,0.0,0.0,0.0,41.0,0.0,0.0,0.0,20.0,DHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDD,True +77,0.0,0.0,1.0,0.0,0.0,15.0,15.0,14.0,CGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGF,True +78,6.0,0.0,1.0,6.0,0.0,0.0,0.0,6.0,CHDAHDAHDAHDAHDAHDA,True +79,0.0,124.0,0.0,62.0,0.0,0.0,0.0,0.0,BBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBD,True +80,0.0,0.0,32.0,0.0,0.0,31.0,31.0,0.0,CGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCF,True 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+317,61.0,0.0,0.0,0.0,0.0,61.0,1.0,61.0,GFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHA,True +318,0.0,0.0,0.0,7.0,7.0,8.0,1.0,0.0,GFEDFEDFEDFEDFEDFEDFEDF,True +319,7.0,0.0,0.0,0.0,1.0,3.0,0.0,0.0,EAAFAAFAAFA,True +320,0.0,48.0,0.0,48.0,0.0,0.0,0.0,48.0,BHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHDBHD,True +321,0.0,23.0,23.0,0.0,0.0,0.0,0.0,24.0,HBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCHBCH,True +322,0.0,0.0,1.0,0.0,0.0,30.0,30.0,30.0,CGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFH,True +323,48.0,0.0,0.0,47.0,47.0,0.0,1.0,0.0,GADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEADEA,True 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+401,0.0,55.0,55.0,0.0,0.0,1.0,54.0,0.0,FCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCB,True +402,47.0,0.0,0.0,0.0,1.0,47.0,0.0,47.0,EAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFH,True +403,56.0,0.0,0.0,0.0,58.0,0.0,0.0,56.0,EEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAE,True +404,0.0,39.0,0.0,0.0,39.0,1.0,40.0,0.0,FGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEG,True 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+951,0.0,0.0,0.0,0.0,35.0,1.0,35.0,35.0,FHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEGHEG,True +952,0.0,0.0,1.0,0.0,0.0,0.0,36.0,71.0,CHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHGHHG,True +953,0.0,42.0,0.0,0.0,21.0,0.0,0.0,1.0,HEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBBEBB,True +954,0.0,49.0,0.0,50.0,0.0,0.0,49.0,0.0,DDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBG,True +955,11.0,0.0,0.0,0.0,22.0,0.0,1.0,0.0,GEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAE,True +956,0.0,0.0,0.0,1.0,0.0,18.0,0.0,38.0,DHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHH,True +957,58.0,58.0,60.0,0.0,0.0,0.0,0.0,0.0,CCBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBACBAC,True +958,19.0,19.0,0.0,0.0,19.0,0.0,0.0,0.0,BEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEA,True +959,0.0,0.0,39.0,0.0,0.0,38.0,0.0,38.0,CFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHCFHC,True +960,0.0,0.0,0.0,80.0,41.0,0.0,0.0,1.0,HEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDEDDE,True +961,0.0,21.0,0.0,22.0,0.0,23.0,0.0,0.0,FDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDFBDF,True +962,0.0,0.0,0.0,0.0,6.0,10.0,0.0,0.0,EFEFFEFFEFFEFFEF,True +963,65.0,65.0,1.0,0.0,65.0,0.0,0.0,0.0,CBEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEA,True +964,0.0,46.0,1.0,0.0,45.0,46.0,0.0,0.0,CFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFBEFB,True +965,64.0,64.0,0.0,0.0,63.0,0.0,1.0,0.0,GABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEABEAB,True +966,1.0,0.0,47.0,0.0,0.0,48.0,47.0,0.0,AFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGF,True +967,54.0,0.0,54.0,53.0,0.0,0.0,0.0,0.0,ACADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADC,True +968,10.0,0.0,10.0,0.0,12.0,0.0,0.0,0.0,EEACEACEACEACEACEACEACEACEACEACE,True +969,0.0,0.0,0.0,0.0,0.0,0.0,125.0,62.0,GGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGH,True +970,0.0,8.0,1.0,9.0,0.0,0.0,8.0,0.0,CDBGDBGDBGDBGDBGDBGDBGDBGD,True +971,0.0,0.0,0.0,66.0,66.0,67.0,1.0,0.0,GFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEF,True +972,63.0,0.0,0.0,0.0,127.0,0.0,1.0,0.0,GEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAE,True +973,0.0,0.0,11.0,0.0,0.0,0.0,21.0,1.0,HCGGCGGCGGCGGCGGCGGCGGCGGCGGCGGCG,True +974,0.0,0.0,39.0,0.0,0.0,40.0,40.0,0.0,FGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFG,True +975,0.0,0.0,1.0,31.0,0.0,0.0,62.0,0.0,CDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGG,True +976,0.0,54.0,0.0,0.0,0.0,1.0,54.0,55.0,FHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBH,True +977,0.0,0.0,18.0,19.0,0.0,18.0,0.0,0.0,DFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCD,True +978,126.0,63.0,0.0,0.0,1.0,0.0,0.0,0.0,EAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAAB,True +979,19.0,0.0,0.0,0.0,0.0,1.0,0.0,9.0,FAHAAHAAHAAHAAHAAHAAHAAHAAHAA,True +980,0.0,0.0,32.0,32.0,0.0,33.0,0.0,0.0,FDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFC,True +981,15.0,0.0,15.0,0.0,16.0,0.0,0.0,0.0,ECEACEACEACEACEACEACEACEACEACEACEACEACEACEACEA,True +982,0.0,0.0,55.0,0.0,0.0,56.0,57.0,0.0,GFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFG,True +983,0.0,0.0,32.0,0.0,1.0,32.0,31.0,0.0,EFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFC,True +984,0.0,0.0,0.0,41.0,1.0,40.0,40.0,0.0,EDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGD,True +985,0.0,0.0,0.0,0.0,5.0,6.0,5.0,1.0,HFGEFGEFGEFGEFGEF,True +986,0.0,19.0,17.0,0.0,0.0,0.0,0.0,18.0,BBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBH,True +987,0.0,0.0,0.0,0.0,0.0,0.0,6.0,10.0,GHGHHGHHGHHGHHGH,True +988,0.0,0.0,69.0,0.0,36.0,0.0,0.0,0.0,ECECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCE,True +989,1.0,0.0,0.0,0.0,0.0,19.0,0.0,37.0,AHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHF,True +990,67.0,0.0,0.0,0.0,0.0,0.0,0.0,33.0,AHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAA,True +991,0.0,0.0,16.0,18.0,0.0,17.0,0.0,0.0,DFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFD,True +992,1.0,0.0,50.0,50.0,0.0,0.0,49.0,0.0,ACDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCD,True +993,0.0,40.0,39.0,0.0,39.0,0.0,0.0,1.0,HBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEB,True +994,0.0,30.0,1.0,0.0,0.0,0.0,30.0,30.0,CBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGH,True +995,126.0,0.0,1.0,0.0,0.0,0.0,0.0,63.0,CHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAA,True +996,45.0,0.0,45.0,1.0,0.0,0.0,0.0,45.0,DHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHAC,True +997,15.0,0.0,0.0,0.0,29.0,0.0,0.0,0.0,AEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEE,True +998,0.0,4.0,1.0,0.0,0.0,4.0,0.0,4.0,CHBFHBFHBFHBF,True +999,0.0,100.0,0.0,0.0,0.0,0.0,0.0,51.0,HBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBH,True diff --git a/tests/results/nb_gm_002_2back.csv b/tests/results/nb_gm_002_2back.csv new file mode 100644 index 0000000..33538c3 --- /dev/null +++ b/tests/results/nb_gm_002_2back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,4.0,2.0,2.0,2.0,2.0,1.0,0.0,5.0,BHCHDHDAEBEHAFAHAC,True +1,0.0,4.0,1.0,2.0,4.0,0.0,0.0,0.0,DBEBDBCEEBE,True +2,5.0,10.0,14.0,6.0,16.0,18.0,12.0,12.0,CFFGHCFCGHEDCCACECBGEGFGAEBGHFDCEEDCCEGEGCBBBHCCECHBHEHBHDEDAFAFAFHFGFGFGHGHEFFFEFEDHFEFEFBBB,False +3,12.0,15.0,11.0,20.0,13.0,17.0,17.0,22.0,AFAHGHGHGBEBCDDDDHHHABCEHEHEBBBAHADADCFHHHHHFEFCBDDFDGDEFCAGGFEFBDGEHECCBCFFFFFFHGEBBHHCBCACHHDDBFGGGGEGEAFDGDADGDGDGBEBAAHDDFH,False +4,4.0,4.0,8.0,8.0,5.0,7.0,4.0,2.0,FGDGECDCECGCDADAHFDFCFCGAFCDDDABEBHBEFEFBC,False +5,15.0,15.0,15.0,16.0,16.0,14.0,9.0,13.0,HGDGBFDHDADHBBBBBHBAAGBCEABCGFAFAFBGBCBFGDDDEAAAHDFACECECHFHFHFCFHEGEFEFDFDAAHDEECDABFCCCCGBEBDAHCECHCHEDEDEDAGEE,False +6,17.0,17.0,9.0,6.0,15.0,13.0,15.0,12.0,BEBEBHAGCFEHHABAHDEDGHFBFGFCAABAGFFFAFGECEBEAEAFBFCEBEGHGDBEFABABEGEHEHBGBGDADACAGHGHGBGBACGCAHFFBHAECDC,False +7,12.0,7.0,7.0,6.0,9.0,8.0,5.0,6.0,CEGBFEFEFEHCCDEBCCHBBBGAHACBGGDBDADACADHDHFEAEAEFGFAAEAHAFAF,False +8,9.0,13.0,10.0,11.0,12.0,15.0,11.0,12.0,CGCFDBDFHHEHFFGCDHEHCFCFAAEGDCEGHGCFCBBBCBGFGHGDFDBDADHBBEGAGABABHBEBEHGHADAFEFCFDBDEFEHEFEFA,False +9,13.0,26.0,23.0,14.0,20.0,18.0,19.0,27.0,HECEBEFFHFDCCFGBCBDBAHGHGCBBABHEFAFEBEBHBHGGCHBGGCCCCCFCBDDDEDHDEEEAAFAFGFDFCGBGHEHDHGHAFABCGGEHEHFBGBADEBEBEAAHBDCCFGGHHHBHBHGHBDBEEAEGCGCBCHCEFFFFCHDHCHDHABCB,False +10,14.0,18.0,15.0,13.0,15.0,19.0,18.0,11.0,AFACABDDFBBBEBECECGHFBFBECDCEEEDGDBHHGCBDDAFCBAAAGHCHCHEAFBFDHAHCFFAAAHBBBFBFBHGFBCBCFGGGHGDGDFEGEFCFEDGDGAGEGCGEGEFEFAFDGC,False +11,21.0,20.0,21.0,13.0,15.0,26.0,21.0,21.0,EECEFFHGCADHGEGEABCCFDEBABEBGGCACHFHFBFBFBAHGBGCGHDCDABHHAGABFHEBCFEGDFDFDFAFBCBCAHACFGFBFBFBFBDACCBCHFHEGEDFDFCAAAGGEBFAAACACHCHFGFBFGHGHAEAGCCEDDFHHHGHGHGDE,False +12,17.0,26.0,17.0,23.0,17.0,11.0,26.0,21.0,ABGCACGDDFHFHBCEHEAGBGBEBAHEBEBFAAHAFBCEGDGBAHGGGGFGDDDBABABHGGGCGDGHGHDACAEDEFECHGEGDABGCHCDDDDCBCBADAHCHGBGBGEHDCDBBFBABHBHBFBACHDEEHGHECDCDHDEFEDECFGHGBFBD,False +13,24.0,21.0,23.0,20.0,15.0,14.0,30.0,24.0,AHHHHAFEDHAFBFGFCFGADADCDGBBBBGDGEGBCBHGGGGCGFBFAGGGGHEEFEGHGHABCBFHGAGACBBDEDHDHDGBCACAHGCACEHECACHBHDCGCECADGDGDABADHFGCGAGAHHBGFDCHBHCAAABEEFDFDBDBEADAHGEGEHECCCBCFCAHD,False +14,1.0,0.0,2.0,1.0,1.0,1.0,2.0,2.0,DECGCGAHFH,True +15,7.0,7.0,10.0,5.0,8.0,4.0,8.0,9.0,HBABHHEEGAGAGEGHCDEECHCHGBCBCDDAEGCBCGEAEFDFBFBFAGCHCHCHAD,False +16,14.0,19.0,14.0,7.0,10.0,15.0,19.0,7.0,CEAFFGHGEGFDFDCACAGBDEAFCEDDFAHHFDFGBEACGCGBGAFECECFGHCEBAFGEGCBABEBHBHBACAGAGDGHBABCBCBGFGFGFGBBBBFBCBGA,False +17,17.0,15.0,14.0,12.0,10.0,9.0,17.0,6.0,EBACADACGBGBAFGHGHADCDGAAFFFADABAHGDGABBCBCACACECHFBFHDCACDGEBADDEGGGEDADFGFGCGFBBABCBEBDBCHGEGEGECE,False +18,14.0,22.0,17.0,9.0,14.0,10.0,25.0,20.0,EHCHAHEHAHCHCGBGCGCGAEBFBFGGCEFGBGHAHCBABABHHGHGCACHDEDBBABGGDGDEBBBHHGCAEGBFHGEGEGBCCGCDFBBGBFBDAEEHHHCFEFECEHGCGCBHDADFDAGAGAGFBB,False +19,13.0,27.0,12.0,18.0,19.0,17.0,20.0,18.0,BFGCGBHAHAHEFEDBABEBEDADGGGGBAFCGEBDFHBHGHGCBBEGEGBHDHDHBCBCACDBFHHCHBGAGAGEDADADCDCACGHEEEEBDFDFDHDCGGBGDEBBBABEHFHGEFFFBADHEFFCFDEBEBFFEBHBFBG,False +20,11.0,10.0,7.0,8.0,8.0,7.0,11.0,4.0,BGBABGHGCGFBFAEBGGEDEFAHEHACDCDADBGGAGAGADFBFBCBCEFBFDHDACCDAGAEEE,False +21,22.0,20.0,18.0,24.0,13.0,11.0,16.0,21.0,DADADHCACFCHEDAAAHGDDHAGCDEDEGBHAHBDBDBGHHHCHCECAAAEFEDECEDBHFABGBCAGDBEGEBABHFCBBABDFDGHGCBFBCCDHDHDGDHDHCHBGADAFACHEHBDCDAFAFAFAGGCGCFHGBDBEBEG,False +22,8.0,10.0,11.0,7.0,8.0,15.0,4.0,11.0,CBAEGDGEHEBGBFBFBDHCHFHBAEHFFGFCFBFCFEEHABECFFFFACAEHHDCDCDHDHAHCFCBCBAADF,False +23,32.0,19.0,21.0,23.0,13.0,27.0,21.0,27.0,GHCABDGDFFFAHHHEAEHGAGAGHEFEGBCFAFBFGCHCHFHBGCAFFDFDBACACHCHCHBFGFEACAFABEBEBHHGHFHAHGGAGAHAFCGDHDHAFGCBCHDAAAAAAFCFHGEFFBEBEDDDFDBCBDDDCGFAFADBDBEBCAGGHDFDFBCDEAGAHCCEHGHAHCDDDDABAFA,False +24,26.0,30.0,18.0,21.0,29.0,16.0,21.0,21.0,GDGDADAGAGDEHCDBDHAHEHFHAHAFBHBHGCEBHBDBHBHBEEABABABAEECEGEGAGADHDBEEGBCAADHGBFBCEAAHDEBEBFBFBFCCGCEFBABAEDBGFGBGCFCGEACDFEFBHDADFHCEAEBDHDCGBEFGCDCACDEBEGAGAEAEFDFBBEHEGEGHCACEFBHDH,False +25,17.0,15.0,10.0,21.0,16.0,11.0,16.0,22.0,BDBDBHHHAAGAEHEHCHCDADEBGHDAGEBHGAABADADEDECEHAHFBGCGBEHCGADFBHECGHHFFFHFBDDDDDFDFDFHFEDEDACAEAEBDCHHBFBABCBGDGEAECHHGHGEGHDAGGG,False +26,12.0,13.0,16.0,11.0,17.0,10.0,17.0,12.0,GEECBGFEEDHCEFGFEAEAHGEGEDDDHDCDCBHBCBCFCECEGAGAGAHECFCEAAFGFGCEHGHBBBGBGBCBDHEAEFHFHGBCDGGACHCGCDADAEBFBADH,False +27,14.0,11.0,17.0,13.0,14.0,21.0,16.0,19.0,AAECGGEGHCACACACHBHADCECBDHDHDFCFGHGDDEDHHHAHDFDACHBHAFBHHAEEECGGFGEGEBEFCFAEAEFFBFBFDGDGDGHFACCDFHFCGBBHBCGGFGEHEFFFFHFCBCAF,False +28,14.0,15.0,12.0,21.0,15.0,9.0,13.0,21.0,GGHGEDHFCFCACBCADAEEEEAHDGAGHGHEHEHBBECEDBBBDBEGDGBAEABCCABBECDDDFDFHGHGHDHGHGHDADHHCHBHCCBAFHFDDDEDHFHAABDFDFEGEAADBDCH,False +29,18.0,19.0,27.0,26.0,29.0,30.0,16.0,16.0,DEFFFAFAGDGEEBFBFGEBADACADFDCEEDEDFDCDEBBGDGHGHGFFFDFBEBEHCHFDCDCEGFGFHFEFCGBBDCHCGCDADEGEGCFAAEHEHFDACGCEABBDECBCBCEFEFBFCFCFEHEHDGACEBAGCEFEBACCCAEDHDHBCFCDEFFHDHDHDCFCAAAEBEBFDHA,False +30,5.0,11.0,5.0,8.0,3.0,2.0,5.0,1.0,BBFGGBABFGCCCDADAHBEDCDBABGEAECBDBDBDBDG,True +31,28.0,17.0,19.0,16.0,18.0,11.0,17.0,33.0,DHAFAHAEAHDHFHFAFADHCGGGDGDGHEBDHCHBHAEBCBCFEGHHHBHCAFDHEHEHCDAGBCBAAAGACCBCAFGBHEHBBEAHAHAFAEACGGEHAFABEDEDFDCGHEBGAGEEAEBBHDEDECHCGABHGHAHAHBHCHCHCHDGACACDFD,False +32,5.0,10.0,12.0,17.0,19.0,17.0,17.0,11.0,EEBHBFFFDDEDCCAGEFEGGDGDFFGEGEAEDEFCFCGCGCGFAEGECDHHCEFDDHDFDABFDECECEHEFDDGDGBBFBFHHGCECEFEHAHDHDGBBFBGHGBG,False +33,4.0,13.0,10.0,7.0,4.0,8.0,11.0,7.0,CGBHBCBCBHFHFECBADGBGBGBDBCFAGDBHGFGECEHBGBCCACFGFGFGDDDFCADHEHB,False +34,22.0,27.0,22.0,21.0,21.0,28.0,21.0,21.0,BABFBCCCCGCDCAGABAHFBAHCBDBDHDCDCDEFFHBHBCBCBEHDAGAEFBBEEEBEGAGHGDGCGEBFBDEAECCFCFGDGDGHBHAEFFFECCADHFFBGHDHEGAAEDEFEFCDCDCDEFCHADAEHFDFHBBEBEBFBFAFGFAAHGHGFFAFGGBABGHGBFBFDFHCHAHEGDA,False +35,24.0,23.0,21.0,17.0,28.0,15.0,20.0,21.0,EGHGAGEGCGDFFCEEEEEAHGEGFGFBCBGBDBACHCAGDDDDEDEHACGCECAFAFEFHCHCEFHDHEHBAEADBDBAFCHCEEEEHBHBECEAEAFGGGGCCHBHAAACABBEHFHBDFHHDHBGCAABEBGAGABBFADADEBBBBCDCACFGFHDCEHEBGADE,False +36,16.0,12.0,18.0,16.0,29.0,20.0,25.0,11.0,EEEBCFFDHDBBGHGHGEFDFACCCFCGAECECEAGFFFCFDAHAEEHGGGBGBGADDGDGEGCCBFEHEGEHACDGDGCCCFCEAFAEGEGBGFGBBBHFGDGFGAAHADADCEEEEDEAEFEAEBFFFHEGECEGEHECAFDDDB,False +37,1.0,6.0,2.0,11.0,2.0,11.0,4.0,7.0,DBFFFHHADFFEFBDBFBGDFFEBHBHFHGDGDGCCDDDDHDHF,True +38,11.0,12.0,15.0,5.0,3.0,15.0,15.0,13.0,HCCCCAEBGFCFBGAHHHHBAFGCGCGCGFGCAABFBABHBFBCAFHFAFGCDBGBGAGFCBBAADHDHDCGEGHGCGFFHFHDEFHFC,False +39,33.0,14.0,21.0,23.0,21.0,18.0,25.0,28.0,DHAHAHADGDAFAFGCHCHEHCHABACEDDDCGBHAEFFGCADADGBGCFFFGGHBAAFGGHFHFHECFCHCHBDEFGADDCGGGHEBEDEBEBEDFHCAAAACFGFBFBFADAEGBDCAGACACAFGEEECDDDDCGGGEEEEEGCADHHHHAHABAHGBBCACHEGGHDADADAHAHEHAH,False +40,9.0,21.0,8.0,6.0,13.0,11.0,9.0,15.0,HEBEGEGAGEBBBHFAFABCBCBEBCBEAFHGGGHEHCHBEDFFAFAHDBFBFBEBDFHHDHBHCHBHBDEFABGBCEDEBCACHHEAGBGF,False +41,13.0,18.0,18.0,16.0,8.0,20.0,16.0,13.0,AGDGBCDHFADAGFFFHHCFCFEBGBGFGFGCGCHHHHCGFBFGDHABCBCGDGECEFBFCACBDBDCFAFBDEDCFFBHGHBEBABDFDFDHDHACABDBAFAFDHEGACACBEECGCBDG,False +42,21.0,15.0,14.0,22.0,14.0,22.0,16.0,21.0,ACFDFDEDFDBAFDCDCDFFFFFACHCHGEDFCFEHADACEHEDEBAFAGGHGEDADFDHDHDHGADAGCCCFHBDBGBDEGEBHGFGHAHFBFBFEAABABACDDAHHGFGBGEGHFEABHBFEHHHGDFDCACABABGECHAH,False +43,17.0,19.0,23.0,19.0,19.0,21.0,20.0,22.0,GDGFGEDDDDDDFDFDFEHBHDGAECBHDEGHGEEDEBEDECGGAADAFAFADECFCDGDGFBHGCBHBACAGACFCGGGBGCHFHEHECECAHFHFGCGHBFCGCBCFEHEGEHBBAAABDHFBCCCCFFFHFCABFBHBHBEDAFEHBHACABECHCH,False +44,2.0,1.0,3.0,4.0,5.0,3.0,6.0,5.0,CHCHFGBGEHFDAGADEDEGGFGEDEHCH,True +45,17.0,20.0,26.0,20.0,18.0,24.0,15.0,12.0,BDEFBBBHHECFCFCBBFEDDADADGECEHEFCGCAFDCGCFFEDDGGHHHHHAFAFEFAFDFDFDEDFAACFCFCDCBBBCGCGDGDFCGCGBDCACBHDHEECBBEBECFCHGBGEGABCDCEFHFGACDFAFAECEBEBDACABAGFBA,False +46,5.0,7.0,11.0,5.0,5.0,3.0,8.0,10.0,CBDHFHCDCEGEHCHCHCHEGCGCGBBBBADAHGDGBACGEAHBHFGFCECAHD,False +47,5.0,4.0,4.0,5.0,0.0,1.0,5.0,3.0,ACABGBHBHBGDCACHCDAGFGAGDDD,True +48,21.0,22.0,13.0,24.0,16.0,18.0,24.0,19.0,DBDGAGBGFHFCABGFECEGBGHHEACDFDGCGBEBGDAFAHADADAHHBHBHAGABADEBFDGDBDGDGCFAFAFDDDDECGFEFEAHAHEHEHCBCDADGBFBFAEBCAHFHEDEGBBFDEHEBDHFGCGHGHGBGCDABCBDGHGBGDCEAFAF,False +49,5.0,12.0,11.0,8.0,8.0,7.0,11.0,9.0,FCFDGDHBEBECFBBHFCFCGDBCCCGCECECBDBGBEHDDBCAGAEHEDFDHGEGAHBHGAGAGFHBHBG,False +50,2.0,7.0,7.0,4.0,6.0,13.0,10.0,11.0,BBFEFEFHAHFDFGHEBABDFHBHEFGFGHEHGGGFDFEHCBGBFDFHFHCCGCGHGCCC,True +51,5.0,7.0,11.0,12.0,13.0,9.0,8.0,13.0,EFFBFDAAECCCHDHBHFEDBHBHDHDGGGGECDGHCFEFEDEDCDCDEDCCHFEFEGCGBHEHBHAHAGDFCEAEHB,False +52,15.0,6.0,11.0,6.0,11.0,16.0,3.0,8.0,BAEGCCEAHBFCCHFABEHEFDCHEBECACECEAFGFEFEFBFBFAFADADACACDFGFAFAFEFDAAHFDCAHHH,True +53,20.0,14.0,19.0,11.0,13.0,12.0,10.0,17.0,CHCECEHEGAHBFGHCHABCBCDCECEDAHACGCADDBBGFGFGFHAAACACFBEGGAGAEHCAAAFDFDCHBDBHGDFDHCBEFEBCBABHHHHDHCHDFEFABEBECAAAEACF,False +54,18.0,14.0,15.0,22.0,24.0,20.0,25.0,23.0,EGGCGCGDEDEBCBFDDDBFHDDGFBFEEEGDBDBEHFDFEACACADABEFDCECGGHBDCDBAGHGFBFECHCFEDEHEHAHEEAGCEEEEFGFHFAAGEEHHHHAHAHDEFGDGDBCGAGHFHFHAHAHDHDBFBFCEGGGGGGGHAADAGCDFFAHCB,False +55,3.0,4.0,2.0,5.0,2.0,5.0,3.0,1.0,EHAABABGBFDFGFGEDDFDCBCDF,True +56,9.0,9.0,8.0,11.0,11.0,13.0,8.0,11.0,ECFFFBCDEDAFEBEAFGFHFHFDEHEBEHEGBFEFHBABCCAGAGBGBDFHAHGHFCFDHDABADEDEDAHGGCDCHCD,False +57,10.0,13.0,10.0,15.0,7.0,9.0,16.0,11.0,HHCFEGEGEDFGABEHEADCHGHBDFDGDGHGCGBBDDCDCDBDBHCDEBAHACCFDGDFAFAFDDAGAGHGCGBGBHACBGBGAHEBFBF,False +58,15.0,15.0,14.0,21.0,27.0,24.0,20.0,28.0,FAFEFAADAGFBFACBCBHHCGFGFAFHCEGEGHHBDBFHFHBEGDGDAEEHEGCGDGHCDGDEHFHGCEEEGEGEDBDEEEEHHHHCHDAGFEBHFHAHFHFDDDCACHFBDDHDGDFDAGGEAEFBHEEEEBEHEFFCFCFDBHAFADCGCGFHDHEBABHB,False +59,11.0,16.0,18.0,17.0,22.0,31.0,15.0,17.0,FCECFCFCFBHCHBGBFHGEDADADEFEFHFDFDADEEADHGAEAECGDGCCFHFGFHFHFHFBFBFCEEEBEFFDEGGBHBEBHFCDDDDGHAFBFBFCACHCAFGCGHHEDCBFEFABCDCEGGGDAEBBBEDEFFFFECGHEHF,False +60,11.0,9.0,7.0,2.0,10.0,10.0,11.0,9.0,HGHCDCHCACBCEGEGEGEBBHCFGABEBFAEHHFBFAAGHGHFHABABCGEGFDEAAABFEFEFGFGA,False +61,23.0,23.0,21.0,24.0,24.0,17.0,27.0,24.0,EDGGCBCFCGCGCFCGCDCBAACHFHFHECACAGAHFHDBDEHAGADHGEGEBCAEAGDHAADDDDCEAEADBGFDBBBBDHDGDBBGCAAEHEGDGBGBFHCGCDBBBEFHFDAGHCDCHFHFGEHEGEGHGBEFACADAFCBGBGBFHDEDEDFBFEGHGHAHAEEEEGEDHAHACEFBHB,False +62,21.0,13.0,9.0,12.0,17.0,15.0,25.0,10.0,HFGFGBGEDEHGHAHFHGAAAFGHBFACGDBEBGAAFEGEFEFBGAHDEDECBCBFBEGAGAFCCBBDBAGABAGGGGGECDADAGAEFEDGACADDCDHDEAFHFHFGGGFGCABAEEEGE,False +63,6.0,6.0,3.0,12.0,7.0,8.0,6.0,13.0,FHEBEBHGHDAGHDCDEDEAFCFCHEEBAAFDDDFDHDAGBGFDHGHAHDHEHFHFHBDBG,False +64,6.0,15.0,15.0,8.0,14.0,13.0,8.0,8.0,CCEDEDBHHGDCBEFEFCCGCEAGFGEGECAHAHGBCFHACEBEBEGEFFFFBDBFBHBDDEDCBCBHBFGFHEAEBCBCFCBCAFD,False +65,6.0,4.0,3.0,4.0,6.0,8.0,5.0,5.0,CGCFEFAFAEEDEHCHBBDAAFAGHEHEBFDHDBAGFGFGF,False +66,17.0,8.0,15.0,6.0,16.0,16.0,11.0,12.0,AFGFGFGHGFECECECHAECCCFAHAFAEHGGCEBAFAEAEFGGHCBFAAEHFHFGBHEHGAFBFHCECEADFDBDBCACACAEAEBEDDACBDFHFHEGC,False +67,24.0,12.0,23.0,14.0,18.0,18.0,15.0,12.0,CCCFCFBHAEEDFDBAADAEAEABDBDGEHEGCCCACECHGEGEDECACFCFCHBFBAGAFFGHADBEBAAAAFAEECEDHDHECGGBHHCHDBGBABAGEFFGFAFADACADAGADCHFECGFGFHFCDCEGFCC,False +68,31.0,17.0,27.0,38.0,29.0,28.0,14.0,16.0,ACACBCFDGBHBDEGEAHDDEFEFEFEFDDHECEBDFDAEAEFECECGCHAHAHCBCDAHBDDDDEDEBEHGDDAFEFCFDDBCGAGACCECAADADABAFEDACGCAFAHDFDBDGCECBGBFFCHCGAEDFFFHADFDADGFAFADEDHABAGAGEHEFBFECEDEDCGEADADFDHBHDFDCBCFCDAFAECFCEHB,False +69,5.0,4.0,3.0,4.0,2.0,3.0,6.0,4.0,DAHAGAHAHAHFGCGEBDFDEDGGCFBBGBC,False +70,5.0,7.0,9.0,5.0,2.0,11.0,6.0,10.0,HAHDHDHBGBFCACDCHFBBHBHGDEACACEGFCDHBGFGFGFCCHBFFHFCFAF,True +71,11.0,10.0,6.0,19.0,14.0,23.0,11.0,9.0,FHFEADABECHFFDFDFHFEDECEFEFEFAFHDADAEADDCAGFGBBHGDGABDDFFFFDDDADEEGFGDABCDGGBHDHFGAGBHBHBEBEGFFFFFCCEDE,False +72,25.0,17.0,20.0,19.0,16.0,13.0,17.0,22.0,GDCDHGBEAEGDGEBDBDHDCDCBHDEAEHDCEFAAABCDCDABAGADADCFAFCGCACAFFBAHGCGCGEGEACHHECACECEHEGGFBDHFHAHAHGGDGFCECHFHFHCHFABABFDGABDEDABABHEACAFDHHGHAHBBBBEH,False +73,15.0,19.0,20.0,23.0,23.0,21.0,22.0,23.0,GFGFECGCEEGHFCBCFDDDHHGBGHGHDCDCFHAHCCCFHAADEBEHEDEDADCDCABEGEFDFHCHGGAHAHFCFCEADFFECGBDBDBDCCACADHGCGEGHFHGHGBFADEBEBEDGDBBACEEEHGBDBFFFFDGEGDGDGFBEHHHHAAEAEFBBBBEFH,False +74,3.0,11.0,6.0,11.0,10.0,12.0,5.0,7.0,ECHFHDHEFFHHDCFGEGFDBEBEFFFDBCBFEDCDCFEBBFADDBDBGBGBGBAHAHFDEDECE,True +75,21.0,13.0,22.0,19.0,30.0,19.0,18.0,19.0,HAHEEEFEDHDFDBHBGCCEEFEGGHGHCCCCCHGECEAHDBDBEFGHCACGBEFEHAFDFACAFEEEHABAGAFDGDADADAGBCBAEADAEFHCDCFGEHFHDEDCDFEFCCCEAEAEGGABFGEDBDBHBCCECEHEAEFGHGHDDAEAEHCFGFGFB,False +76,14.0,30.0,18.0,20.0,25.0,19.0,27.0,30.0,FCFBAEDEGEHEBGHGFEFCGDBDGGCGCGBEBHBHEAAAEECBCBCFHFCFDGAEHHFGGGGGHCHEHBABGBGHHDFAEBDBDBDBCCHAGGEGDGCCBCHFGFGHGHBHEFGHBFBCBHEHBBABCBHBCGEHEADDDBHFHAADEDBFHFEEGEDHDHDEDBDFEFEHCHAEGDHBFBA,False +77,25.0,17.0,30.0,29.0,22.0,22.0,23.0,24.0,CCHEAEHBBCBDADBDBDHGFEECBDFGFEAHDCGCDHHEHEHCGCFHGDGAGAGACACDDDFDFDGECCHDHCCEFAFEBAFGGHDCCGEDBDBDBCHCACDBAHCGCGAHAHAFFFHADCDCFCFHHCDCAEAGAGAGABFHGEGBGDFHEBEFCFAGBEEAABAGDGDFDFEABHCDEDEHEHEFCFCD,False +78,9.0,16.0,9.0,5.0,4.0,15.0,4.0,5.0,BCEADCBBBBABABCCEHFBDHFAAGAGHCFCBCBFDFAGAGBFBDBABFFFFFCEHEBDHFFFBFC,True +79,19.0,17.0,10.0,29.0,13.0,8.0,14.0,14.0,DEDEAEAEDDDDDDDHDGEBEFADAGBFFHDGFBBBBGBABFCHGDFDEACBBBAHADAHCGCAHDHEHABAGCGCGEDAGBDAACAHDBCBGBGBEDDDDDADGDFDHHFDAHAEEEHCDCHG,False +80,9.0,11.0,7.0,9.0,14.0,3.0,11.0,16.0,HEHEACBHBHAGEBEAEBHBHBDEDCFABCGAEABHEHDADABABGGGDGHECEHHDGDHHCHCDGFFHCBEDEGEGHGE,False +81,4.0,9.0,4.0,9.0,3.0,6.0,6.0,5.0,BGBACACHDGDFDFBFEAHFBDDEDEGHGHBBBFBADHDGCGDBFC,False +82,11.0,21.0,22.0,24.0,26.0,28.0,21.0,21.0,EDGDCDCFGEDEFFFFGEEEDEDEDADACHCEBAFAFCHEDBFEDHDCCAHGFDFDGAGEFECEDBHCECDGGGGGBGFGBHCGDGFFDCAGDBCEHEGBBBBHFHADFHCHCHCACHCBBEFAGBGBEBFFFHFBCEDFFEFHDHFHFCCECBHBDBDEDEHBHEHFBFEGAG,False +83,2.0,4.0,1.0,3.0,2.0,4.0,2.0,1.0,CBFHFBBDGDFDFEGEABA,True +84,18.0,13.0,21.0,13.0,16.0,19.0,15.0,8.0,CBCEEADAFGDCFHFHDHFACACEDGACFGGGCBABDCCCCCCBABABABDBDFACGCGCFCAGEFEFBDBCFEFEAGFDBEFEHEHBAEADAFAFGEGECAHFEDGDHHCAEDEFCFGGGBF,False +85,14.0,12.0,10.0,10.0,16.0,19.0,9.0,12.0,FGBGHDEEEGBFAEAEDHGHGFEDEFEGEDEFEFCBAHCHCFBFDGECFFFGAECBBBDGFAFACACBEDABEBFHFHFHAHAHFEDCDCFCAAHBHADAFB,False +86,14.0,13.0,10.0,16.0,18.0,7.0,14.0,15.0,GGGGHADGCGCEEEDEDBAAGBCDAEABAGAFFFDBEFEAHAHBDBDBDBGHAACDHHGHGHDHEFBCDCHCHDEEBEBDADABEFECCGHGHFHDGEEEADBEEHC,False +87,9.0,13.0,17.0,12.0,12.0,23.0,13.0,12.0,EHCHBDDCECFCFCFABABGBFDFDCDHBGDHDGBGCGCGCFCDHEHEFCHGEAFBFBFDFHCEBAFEDEDFFGHCFGBGFGCDCEBGFHFAFBEEEBGFFCFAACAHAHF,False +88,6.0,3.0,0.0,1.0,3.0,3.0,5.0,4.0,GBGAGBHAGAGFEBEFEHHAHAFAD,True +89,11.0,11.0,12.0,15.0,16.0,12.0,7.0,10.0,BHBHDDADCGCAEHHDCEAFAFBFCDEDECBGFCECHAHGCAEDDBDEAFAFHFDCHEBEGEGADBDBHEHDFGFGFDECECECAAEBEBDBFF,False +90,18.0,21.0,18.0,8.0,15.0,18.0,18.0,10.0,BCBDGCBCHGHAAFAFEFAFDFHGGGCCECEHBHFCADAFAFEGBAAAGAFBEBEBEGCBHBFADAECDGHGBGECCBCBABHFFDCEFEHGBGBGBEFGABCBFBDBEEAHACGCGEGFCFCFDA,False +91,21.0,22.0,23.0,29.0,25.0,21.0,20.0,16.0,EDECECBBDBGGGDHDFCFDFAFGBACHDHDADFDHBEAACACACEDECEDGDGEGEGEDEAFCFEGGBEBGFGEDECGFAFAFGHEDFHFCFBFBDEDFDGBHEADHDCCFBABABACGEHAHFHCEGEGHBHDACADFCCHBHDCDCFBHAGDBABEBFBGCDBEBCDDADAEEC,False +92,22.0,26.0,23.0,24.0,20.0,30.0,22.0,18.0,ADAFEGHDHFFFFDFECADDDFHBHDCBFAHCHCACHEGFBFBCDHEFEGABAFAEBGBFFFBFCFGBHBEBAACAHAEDEDEGCDCDCDCGHACFCFHFHGCFCEHEHCGCDCEFGDGBGBGEGBABGBGCCABBBDBAFGDABFBFEFEDADBFEFDBHGHDFEFECBAGGCGADDDGBHAEA,False +93,2.0,2.0,1.0,3.0,0.0,2.0,1.0,2.0,DBDCDGFFAHAHB,True +94,18.0,8.0,12.0,13.0,10.0,9.0,12.0,11.0,HHFAEHCHCHCDDAFACACACGGFEFGCHDEEGCGCGFDDADGDFDEBHCDABGBABDGAGEEBAFABGBDAHAFAFADADEHHCHCBGEAEA,False +95,4.0,5.0,6.0,3.0,5.0,4.0,4.0,3.0,AHBFEADADAGFHFGGCBCBCBCFCEHEBDCEEG,False +96,6.0,10.0,15.0,4.0,14.0,9.0,14.0,11.0,ECECEGHGHEHGDACGHHHFGFGCCCGFEEHEAAACCHCFCFEGEDHFHFDFGEABBBBEBHGCGBEBGCACBEBEGCCDBFG,False +97,3.0,4.0,3.0,4.0,3.0,2.0,2.0,6.0,BGHFHDHDCDBDECAHAHAEGBFBHCE,False +98,14.0,9.0,9.0,12.0,16.0,15.0,11.0,5.0,BGGACFEGEGEAFGFGFGFAADADACBCFDADGEBHBFDFGBBDCGAFAEEFECHCDCBFEAEAEADADCEBDDHDBGEFCHEHEFEAEFF,False +99,24.0,22.0,16.0,19.0,18.0,22.0,22.0,17.0,BABDFDEDEDEHAACABAEAFFGBHFGAHDBCAGADEDCHBBGEGAGAGAGAGFGABEDEDEFCBABDBECECEAGFGEGBGACBFEHEHAHAFBFBCHEFGDADAEEBCBHHHFHFBAGGGFFFFGHDCCHAHBCBCHFGDBCCAFBDGGFDHDFDFDC,False +100,10.0,7.0,6.0,7.0,6.0,11.0,8.0,15.0,GGHGHGFEFDCHAHFHEHEBACCBCHFHFBCBEBFFEFHAHGHDAGADAEGBGHHBAAADCFHFDADFDH,False +101,21.0,23.0,9.0,23.0,25.0,21.0,22.0,21.0,EEEEEACAHEHDDADHFBFBAHGHGBGDGFECGBBBBFBFEFHFGFGFAEHDHAHAHBHGHFBBHGGGGGEHDDDDHEAFBHHDEFEHEDDGBCDCHBGDDFFCAHADEDEGEGEAABBEBDFGEBABCDFEACFDADAGAGEGBAFABHBDGDCEEEAFAFBFC,False +102,1.0,8.0,5.0,3.0,5.0,5.0,6.0,8.0,HCGCHDEBGFEFECBBBFBFGHGHGDGBAHCFCHHHEDEBB,False +103,29.0,22.0,27.0,17.0,23.0,16.0,31.0,26.0,GGHCFGEBEDGCCDEBFFFEFHGCDCBCBCECFCHCHCHGHCEGAGCECABHEEEBEBEGAGBBBABABFBHBHDHGGDADCCFAFEDECEABGBFAFHDAGHGHADEFGBDCHHDEDCHGABABFGDEAAAEBGAAEGGGGFGHAHDBDCCHGHBDGEGHGEAEACCHCACAHGHGHAHDCACAFAGAFA,False +104,7.0,6.0,18.0,7.0,11.0,12.0,24.0,18.0,GDGEHCGGGEFECEBECGCGHGCFHFHFHCDFDFGACHHHGBGHACDCGAGADBCAHECACGHGHBBCFGHEDEFEHGHBHGGCGCGCHCEGGDGEAFFHFCF,True +105,16.0,23.0,21.0,18.0,22.0,17.0,10.0,18.0,ACEGEHEHAFACDCDCHFBFBGBHDFFFCAGHBBBHBHFABABABAHEGCAEEEFGBGBADGEBCDEHEBCFCHBHEFEBDDDDDDDGFEDEFEHAHBCACACBDBDHDCBCEDEHEGCCFEEEDHHAABCFCHAECBCBFFCFG,False +106,9.0,10.0,12.0,6.0,8.0,7.0,13.0,7.0,FABABHCEGEGBGBGCCCHCAAABGEGDGFGFAFCBCGCEHDCCAGHDHCAEHFBFAGBGBGHFDCDBEEDE,False +107,17.0,15.0,17.0,17.0,16.0,26.0,15.0,17.0,EFBHGEAFDGCGFGFGDEEAEGBDEFBGGFAHHCAFAFHBHBDGDGEGEGDFFFDFHHHAHBCDADBCBFGFCBCBGBFEHADAHCECFCECHBFFFFCDEDEDCDEFEFCHHHCACAEBCGAAAAHADAFHFBDBCFDF,False +108,20.0,24.0,27.0,23.0,19.0,28.0,19.0,18.0,AFAEGFGFGAHFCFEHEGDBBBEBEBEBCDDDHDFGFDCDCECFAFAHAGBBBEBFDEBCBAHGFGAGABDBEAGFCCCBEBHCDBDFDFBBHCHGGCDCDFHEHECGCFFFADAHHHDCDAEEBFGAEHCDDGACACACFCBEFFHAGCCCCEFEFCABDBFFFGHCHDHDFDGBGA,False +109,9.0,16.0,17.0,17.0,16.0,16.0,12.0,24.0,EGDDDAHBEAEABDCEBFFHFHFHCDGHAHCCFDFDFDFBBEBFBFEHGHGDCFCGHGHGCBCEDHBCDHFHFBFGDGACCCGAEBHBABCHHEHBDDEHEDEDEGEAHDHCECFCFCBHAHEGBHH,False +110,5.0,7.0,7.0,3.0,11.0,14.0,10.0,14.0,AHEHDHGFEFGCHFGFBBCAEFEFEFECEHFHBHAHFCBGFABHBEDEGCGFDFACGCGBFEFGHHHHEHG,True +111,20.0,16.0,22.0,22.0,11.0,17.0,13.0,10.0,ACAFFCDCDCACBFAFGDAACDCDEDEFFCBHDGDCDGDEABFEAADDCAHHDHEGACEFBCBCACACABBHDHDHEHCAAFAFCDDEDFDFBFCFBFDEDFFGGAGCCBEBCBHBAGGGGGEGACBHBDB,False +112,26.0,22.0,28.0,29.0,20.0,26.0,21.0,19.0,GCDCBAEHEHGGFABGFFFFBDBDBHCHCHAAADGFCBCDCFFFDCHCECEDEAFBFEFEGGCDCDAEAECFCEEACCBABGFDABADAFHBHFEFEAHAEADFCFHHBHAHAGGDHCCCDHBCADABHBDCGHGAGAGDDDFCAGBCBDBCFCFEHEDEBGGFGFDBCGAGDCDEDGDBDBEFEHAFADD,False +113,4.0,0.0,3.0,3.0,1.0,0.0,3.0,3.0,HAHADDGDHAGAECCCG,True +114,15.0,25.0,14.0,19.0,17.0,16.0,17.0,18.0,GDGCHHEBEBHBEFAFEFBFHFBGHEFEFEBAAAGFGDDFDFDFDBDBDBABABDHCBGDHCEBBGBCBEBAGHCHBEBGHEHEHEACACACACBBGGFGHCHDGBCDGEFDFDBEHECDGBCEHAHDHACFGADFDBAGD,False +115,4.0,7.0,3.0,5.0,3.0,0.0,6.0,6.0,HGHBHBDBABACEGDGEAHBHADGEGCHCBDGDB,True +116,18.0,19.0,11.0,27.0,26.0,22.0,18.0,28.0,FDFEHEBGBGBCFDFDFBEGFABHCHEEFAFAFAFBDHEHEABBDCHCDDGEHEADAFAFBHHCHBFBEDHGHGBFDFGECHHABDEGECEDADEHEDCAHAGEBABCDCDAHEDEDEDFFFFFBFHGAFEGEGDHDHGHGHGEDHDGEGDAHABBHHDHBCDADHEGE,False +117,9.0,10.0,11.0,5.0,12.0,11.0,5.0,12.0,HFBFCFBAAEABGHCHAFABBBBCCCHCECECHCGEHEHEHFHAHCEDDFDCEEBFFFFGEBEAFAHDGBGDEHA,False +118,1.0,8.0,6.0,3.0,6.0,11.0,9.0,8.0,BEBFGFGFBFBGBCDFEHBHAGEFHGDEFBFHHCGCDBGFGFGHCHFHCECE,True +119,16.0,21.0,23.0,14.0,8.0,20.0,24.0,21.0,EEGFBBADAFCBHFACCCFCFEFDGAFHFDABHBCGHHHBHGHCHEGCAABBGDHBHBGFGCGCGCGHFEFCFGABAGGCGAGACFCBCBHBFCFADHDHGHGFDEBEGCGCDBHBEAACHDDFDCDCFBFBGGGGCBHDHDHFABA,False +120,23.0,16.0,16.0,25.0,12.0,20.0,24.0,21.0,DFHFBBDGFFEDCHEEGGGEEADAGAGDBDAABFDFCGDGAABABABABACAGGHDHFACECBDDFDHGHGHBCBCAGFGBGCFFFDFDCGHGDEEHBCDCBHBCFGFDFDHAGCHHHHHGAFADDHEHEAGAGAGHCBAEAEDCDADCFGFDHDHF,False +121,19.0,17.0,15.0,20.0,28.0,24.0,23.0,17.0,DCDFFGAAFFFBGAGDGCACHEHDADADFEHEGGFFEFAABBHGGGFHEHACACBEEEHBAGAGFDFEBEGEBECECDCHBHGDGBEFEAEAEAECCGCEHBHCFFGBDBDCDAEEEAEFFFBHAHGEDEBGFGFGHGBGBDFDCDHEHDDDEBAFDFEGCFH,False +122,24.0,21.0,31.0,19.0,20.0,33.0,21.0,17.0,CBDGEGCBFGFHFHFEFBDAECCCBCBGHDCCCAFADHDHDEDACBDBGAHABFDGEGCHEECECDAFBGBGBFFFFHEAECHFHFHGEEBCFCFDGEGFFFFGCDCGBGBGFFBFBFAAAAAFGBAFABECAGEGBGFHFCADDCECHFAFADAHFHEDEHCFBACAEAEFDCCCCCBCHDADCG,False +123,23.0,22.0,33.0,26.0,18.0,14.0,26.0,19.0,DGDGCACABHFCADADGHGEEHGACAHAGACEDEDEDGDFCHDECFCBCGHGECHCHBEEDEDEDEDCBGBGBABCBCBHAGDGECAGDCCCFCDCFHFDABECGBGFHBBFBEBEBACEDBHHCCGCDAGGGFCCCGDDFCBCBGBGHGHGCBADHFFAHDGAAAAABAFDHDHCFCEAD,False +124,14.0,14.0,13.0,14.0,9.0,17.0,19.0,18.0,DCBFBFAFAHBHGFBABECACGGBGCGCFAFHHDGDGEBDADFFHHHHDAABHFFEGAGFDBGHGAGBGHFHFGCHCDGEGEFCGDGDCDCDCECBFAFCFHAHEBEGHBEBHHADAD,False +125,22.0,17.0,18.0,14.0,19.0,23.0,19.0,20.0,AFFEGCACEHAHBHFHECADBDEDHDHDACHCBCBHFDDAGHGHCECEAEAHBHGGCEAFAFBDGFFFFBAGAFAFHHCGDFFAEBBABADADBCGHHHGACACFCFDFBCGHGEGEGBGBCBEEAFHEBBGGECEFECEHGGEAFDFDFAF,False +126,2.0,2.0,5.0,1.0,2.0,0.0,0.0,0.0,CBABCCCECEAD,True +127,9.0,13.0,13.0,20.0,8.0,15.0,15.0,18.0,GGEFDFEHDHDHBAGABBBFFHFCFHGHGHGHGDADHDEDFCEDAGAGCBDFDHDHCBCDFDBHFHGHFBCGDDDDDABGHDHCHAAECFBDBEBCBCEGECCFFHCGAGF,False +128,26.0,16.0,20.0,13.0,15.0,14.0,8.0,14.0,AFAFGCBFDCCGCBCACACAFACECBAFAFDBBABABHECBGAHADEDCBADABABAHEHCHCHGECDHDHBHBAEDEAEAHBGFAHBBCACACAFEDCAHHEADGEGECEFFFCGHDFDEAEFFD,False +129,3.0,2.0,3.0,1.0,2.0,1.0,0.0,1.0,AHABFBEAECCDC,True +130,3.0,10.0,5.0,11.0,10.0,4.0,3.0,9.0,DBGBHBAEDEBCCEBAAFHHDHDCBEDHBHBHBDECECEDDDFDGDFBEGEHEHF,True +131,18.0,19.0,23.0,22.0,20.0,20.0,15.0,23.0,FGBCAABCBCDCDCBBAAADCEGHAFDFEBHBHAHGDAEAEAHGECHCDDFDBEBHHHDBCFCABFHHHABFHHEGEHBAFAFCDCHGEGEFBFEFEDEHCHCHDHDGFAFEBEBGBGFCDCAEDEGFFFHFBEAGACFDDDDHDCCCCDCDGEGBGCEH,False +132,27.0,13.0,16.0,13.0,20.0,12.0,27.0,15.0,HAACDHGHEBFFCDAGADAEABAGHFHDHCCAEHFHBGBECGGGGAGABACDEDCACACFGFGFHBBEBHGGGDABGGGEDECEAEAEAFCEGBBBAGAEAEABHEAEGGGCEHFHDGAGEDEDFDHDEAAGAHAFFGCCCCG,False +133,5.0,7.0,9.0,1.0,6.0,7.0,8.0,7.0,BGCFEBHHHHACABFBFHFCFGGGCCECGCGCHAEBBHFGCGDAEAEBEF,False +134,14.0,15.0,11.0,16.0,21.0,17.0,16.0,20.0,HBHDHFHDDEFEGEFEBGDFDFBBHBAGEGCFHBHDADHHFAFAHECEFADECEDDDBDBDACBEAFHFHGEGCGDECECBAGACHBHGHFHFHGEGFFHEHCHCEGEGEAEGDGEABDBABFFGECABA,False +135,8.0,3.0,1.0,2.0,4.0,6.0,9.0,3.0,GFGEGHGFEFGCGDBAHAFDEAEGBGBAAAFAGAHF,True +136,14.0,29.0,20.0,23.0,25.0,22.0,18.0,18.0,DGDCEBGFHDBFBECHFEFBDEDCACGCGHEFEFEFAFGGGDCFGFHFHAHADEBBCBCEEEFEBABCBEBACACBHHCFCEAEAGBGDCDBDEDGBACECBHEHBDGDFDGCGAFEFDBHBEBEAHGFCFBFBHEDFDGDBBBBACDBDHGBEAEGFCHBHEHDHDFD,False +137,3.0,5.0,1.0,6.0,8.0,6.0,3.0,5.0,FDFDBBBEDEHEHEFEACFFGDHDFGBHAEAEBEGDH,True +138,17.0,19.0,28.0,23.0,19.0,29.0,14.0,27.0,EEHFCDHDHBAADFECECFFFCDGBAHAHFHBCDDFDGDADBCAAHABAEGFHFHDHDEGCGHGHCFDFEFGBHAHBCBABEEECDCDEHFHFBABHCCCACHEACHDGDFHFHBHFGDGDGDFBCDCGABFFDFECHCFFFHFCDGEFCACHCHCHEGACFCFBFEEECEBBBBD,False +139,18.0,10.0,15.0,7.0,19.0,9.0,15.0,15.0,BCDGAGEBBAAFCBEFDFHCAAHABFEADAHGCCCACEDEDEDEDEHCBCFEHCHEACACHGGGGBGEGFGFEHECGFEAHGHEHEHEHACAFBGGABABHGHEAEAC,False +140,12.0,11.0,10.0,15.0,15.0,9.0,10.0,21.0,GGDEDEDHDABGBDCAFADADEEFHFEEBBAHECFCAHGHGHEBBCBABAFHHHHAFADHECEGGBGECECHBHECFCDDDEEHHHHHDHDHDHFACGDABFG,False +141,6.0,7.0,16.0,10.0,19.0,4.0,7.0,3.0,GAGEECEDBGBGFCFCHCFBDBDECEAEDBDCHBEEFAHAEAEGCBCEADDDDEGCCEEEECCCECDCGCEE,True +142,17.0,14.0,17.0,18.0,21.0,18.0,15.0,9.0,BADAGADHDGDGFHFAFDFGEEDDDADCCCGGECCCGEHAHAHEEEEAECFCDHDFABABFBGBCACEFFDADAEEHBHFDFCBEBGHGCFCDAGFDBEFFGFGEGCBAEDEBCBAACDCBEBEFEFEG,False +143,1.0,3.0,4.0,4.0,2.0,3.0,3.0,3.0,DHDCCGCGAGHBBFEFCFDHDEB,False +144,3.0,1.0,7.0,1.0,1.0,3.0,7.0,2.0,CDCFHGGFBCCCCGAGAGAEHFGCG,True +145,3.0,5.0,7.0,4.0,3.0,11.0,6.0,3.0,DHGEGBGBGCCFDFAFHCBEBEBDFCFCFGFCCAHFFFDGAF,True +146,4.0,13.0,6.0,8.0,6.0,15.0,9.0,3.0,FABGBGFGFDBBBCGEEEEBFGCBFBDBCFDFGFGFAFECCDDADAFBDGHGBFBFHFEFHCBD,True +147,16.0,16.0,22.0,23.0,21.0,20.0,35.0,29.0,FBFEECGAGFGFGHDHDFAGEGEHFHFHFEGHGCEEAHDGDEHEGEFHFCFHGHBECDBDBHHGGGGGGCBHAHACAHAGEBDCEAGGHGHGEGEBDAHHHCHADGCFBFHGBGCHDFDFDGHCBCHHAGBEBDACHCFFGGGDADEEAGCEDEDCCCGDFDBDGFBFBGBDEACACDCDCH,False +148,16.0,20.0,20.0,23.0,21.0,16.0,31.0,18.0,EBEHGGGHCACFDDDDDAFCHEGCACFCFDFAGADEGGGAGEECEGEGEGAFFDCBHBHDHEGCDCGBGBGCCCCCBDGEBCGFHCHGHAHBBCEGEGEBFBGAHABDBDAGAGFGBEEEFEDGDAFCHBABGBADADEGFFDHDCFGGDHBFBDEDEDGHHHBH,False +149,3.0,7.0,4.0,6.0,10.0,7.0,3.0,5.0,EBEHEBEDCFCBBADCHFHFGBGBDEEEECHBDADADEFFFGFHE,False +150,6.0,2.0,7.0,6.0,2.0,3.0,8.0,0.0,DDDCGCADFDFGGGACACAGBECGGDGABACFCE,True +151,5.0,2.0,2.0,0.0,5.0,4.0,2.0,3.0,GAGAFBFEFECEFHABAEHEACH,True +152,14.0,12.0,9.0,7.0,12.0,11.0,10.0,17.0,FDHDFEHDHCFCBCDGHGCFFFBFHACCHBGAGAHEHEBEAADAHBGBFBFBABABAHAHEEAFHEHBHEHABGGECDCECEAGDHAHEFGG,False +153,19.0,24.0,27.0,19.0,23.0,23.0,26.0,24.0,CDCGGGFAAGACHFHDHDHBBCCHCGFAHABGBEDHBGBGBABADECFFFFAGGCHDDGDGCGHGHGDCFHDHAFEFEFEHDCCGGBGEGAAFCEEDFDFGBEAFHFCGEBCBHBFBDCDGBCBEHADABCHCHEHEHBHDGFGAGEGBBEBHDEEHAHAEAECCFFFCCCECECEFBFBDECBA,False +154,13.0,10.0,11.0,9.0,11.0,8.0,12.0,4.0,GEAEAFAGADADAEFCGCGCGCAFBFBEECEGADADACBGBCHHBFEECACBEHEFBFBDADEDBCGGGBDFHCAGGD,False +155,23.0,15.0,20.0,21.0,22.0,13.0,16.0,23.0,FEBEBEBFDHDHCCDDBCBEGFDFGBHCHFDAEBCBFHAHGHDADCBGDHDHDFCAHHHDBCEHDFDAAECDCDCBCAFEEEEEAEAGACHCEGEAEGGGGAEABAFAFHHGEAAACHFHAHFGEAEDEDEDADHDBCGAGACBCHHBGGCHC,False +156,1.0,2.0,8.0,2.0,1.0,1.0,0.0,3.0,CCCCCHCHBACDCBHEDF,True +157,11.0,6.0,5.0,14.0,10.0,10.0,2.0,6.0,EFAHAHFBFGGABADFCBEDEDADAHAFAHBFEDEDCDEDEDEDFFCBEDFDFBACDDAEHCHA,True +158,15.0,22.0,16.0,16.0,9.0,21.0,17.0,9.0,CFCFCAEBDGDHBBFBHCAAGFFFAGGGGFGHCHDBDBECECECFHBBCBAFHFDFBCACHCAAAEFDBDBCFGAADADAGGBBBGCGBGCFBEEGHGFGFDFDFABABDFHFDBDCEFEBGDDB,False +159,3.0,6.0,10.0,6.0,2.0,3.0,4.0,5.0,GGGFDFDBCBHBHBCCHCBCEHHFCACDCBEDDDACGCA,True +160,7.0,12.0,7.0,6.0,6.0,8.0,8.0,5.0,AEFEFEBCBADCEFHHCHGBBECAABFBFBDBGBHECGDADADGBGAHFFCFCGDGBGB,False +161,25.0,18.0,13.0,27.0,15.0,21.0,17.0,28.0,HFHGDDBDFDGHGADHGFBHGCFDAECCHHEFEFEDDBEBAHAHFHFBFHAHDFDFAEDFBBCEHADGFGAHDGDGDGDFCBCEAEBCBHDHDHAHAEADHHFHFHEGBHEDABABACDCAEFDDGFGAGABAHDHDGDGDBHBFAABAGAECECHCACBFAFH,False +162,18.0,23.0,16.0,12.0,17.0,23.0,24.0,31.0,AEABABCBCHCHCFFFBHHEGBABDDDDDHHFHEECFCFCBEDDBHBHBCGHDFAFHCHFGCHHHHHHHCFGFGEHDBAAEGGHEBBHGDAHFHBHBECGFAFBGCAHEHGBBFBDCHHGEAEHGFFFADGEGBGBGCGFFCHGEGEGAGAFABABAEAEGFGF,False +163,24.0,23.0,17.0,16.0,25.0,31.0,34.0,30.0,FHFHFEFGFBAEHHHDHDHFGGDGDGFGDHACAFGDGDECECHCGAHAHBBBBBFFFCGBGEFFHFEAECGGBBAGABABAFHFHECGDECFCHDBACDEHBFBHBFEFDDGCHBHGHGHBEAGFGCEHFBAHACEHEACFCFEAEGEGAGACFEAEBGGFDBDBGEGECEAHHHAGBGHAFDFAFDFGBGHGFGAGHEE,False +164,16.0,17.0,19.0,27.0,19.0,29.0,35.0,19.0,GDGBCCGCAFBFGFDHGHBFAFGFGDDECECDGDCDFHFGFCFHFEABACFHFBFHEEECEDFDEDGGGDGCCBBDBFBABFBGDEDEGBHBDDDGGGGCFHFGFGFHFEABBDCDCHCGGGDGFGEDADHDECEAGAFAHEHADAFFGGGCABEGHCAEFGFGAGDDHDHBCEHGAEHFH,False +165,10.0,7.0,7.0,12.0,6.0,6.0,5.0,8.0,DGFFDCDCDAEGDBDCEBGACECHCECDBABDEAHDHGAAHHHFHFBFBGBHDADADAFAE,False +166,17.0,18.0,17.0,16.0,20.0,19.0,17.0,15.0,CACAHAFBDAAADADHBGFAFDGDGDGHHFHFGFGFHHCAAEBFBFCFAHEBABEEGEGEGEBAHGDCDGEBCHEGDGCFCEEFECBCFHBHBHBADDFBFBGDCBCFFEGCAEGEFBACDCECECFDDADEEEGHBHB,False +167,15.0,4.0,11.0,15.0,21.0,12.0,17.0,17.0,HHAHDEDGHFHEHCHGFGFCECEGEACFGDGDCDCHADCEHEGGAEEBEBFHHHCHCHCFDAHAGDGFGDDHEEGCAEDEABAEGEGHGDDFAAEFGAGAEAFAFDFEEBED,False +168,8.0,4.0,9.0,2.0,9.0,7.0,3.0,7.0,ECECBCHFHCGFGFEEEHEHECAAHAFFBAEAFHBGAEAHDBDACCCFC,True +169,16.0,14.0,9.0,11.0,11.0,11.0,12.0,11.0,DFDFDGAGAGAGFGHHACBHBHGFFDFGBCEAHBDAEADACCECAAEABBHEAEAEDEDCABABCBGGGGFFACHHBDBFFDFEEGBCDHEHBHB,False +170,4.0,2.0,1.0,1.0,6.0,4.0,5.0,2.0,GGDBEEEEBEAGFFCFGFHAHAEAG,True +171,28.0,14.0,20.0,10.0,8.0,25.0,20.0,36.0,HCHCDCGCDAGAGHGBABAFAFCFAFDFGFGEGHFEFHBHGFGCHEHABFGFHHHCFDACHEFBHHHCHAHGBAADCHBHBFAAAHHHFEGCGDAHAGFBFAADAEACFFGAEAGABFCHCBFDEAGAHBHBAAHHHFHFHCCACGHGHDHDHCHCFCBGF,True +172,3.0,11.0,4.0,4.0,5.0,7.0,5.0,5.0,BBBEBHHCCFEFGFGHGBBBGBDFAFACEHFGFHDBDBABCDEE,False +173,8.0,13.0,6.0,15.0,4.0,10.0,15.0,7.0,ACDCGBGFFFGEGBGFHBHDADHDFGBGBGHCDAGGGCHDHGADDDDDDEBBHBFBFGFAEADGCCBDBDGAAEFBFB,True +174,10.0,11.0,8.0,10.0,13.0,7.0,14.0,11.0,GCGCGCGFGEBCAAEEHEAEHDHDGAADADADFBEDECHCGGGHGEEHBHAHABFBEBHFADGDHEECHBBFBGEGBGDCFBFD,False +175,23.0,12.0,12.0,24.0,26.0,34.0,26.0,24.0,CDBFHAHBGAAFEGHAFGCAFGFGBGBEBEAFGDGDFDADCFGEGBFCHABFCGADHFFEFHFEFEFEDHFGCGEGEAABEGAGHGEAFAFAFCFAEDEDEDHDHDHFFFGFHACEFHHHDHDAGFDFGEGBGDHDBABAFEEEHEBGFGEEAEAHHFDDDGHGHDFCFCACHDDEDEFHC,False +176,18.0,8.0,20.0,16.0,15.0,17.0,11.0,11.0,FCFBECGAFAFABAEEEEDCDAECEDGAAADFHBDBECEHEABABCDCHBGEHAHAGAECHHHADCCCCFCDCDAGCFFEEAFAFGDDFHFHFHDBGGDGDADFGCECFCGCDCFF,False +177,13.0,12.0,13.0,12.0,6.0,11.0,5.0,9.0,DABFHGHCBDBDCFFGABAFEBACAHECGDFFHFHFDFEFCHCBCBAECGCGCHEAEADDDBDADAHHBACABACDCDBFB,False +178,7.0,14.0,10.0,12.0,19.0,22.0,10.0,9.0,FDECFBFDFDFHFGCEDEDEFHGBACCEGGAEBEGABFDFDFCHGHFFEDBFBFBFEGEHADAEFEFEFEABCFHDHDAECFCGBFBGBFBEECECDBEBHGH,False +179,2.0,2.0,2.0,1.0,5.0,4.0,1.0,6.0,HGFEHEHEFEDAFHFEABBCHCH,True +180,2.0,5.0,1.0,3.0,3.0,4.0,0.0,0.0,FAADBBBBEBEFEFDDCF,True +181,6.0,7.0,5.0,2.0,1.0,4.0,3.0,6.0,BHBDBAAGAHCHFHACAHEHBBBFCFCACGGDBF,True +182,2.0,3.0,10.0,6.0,8.0,6.0,4.0,4.0,BCBCECEAEDEDHCCCCHEHEGDGCFFFAHGBFFFECDDECGD,True +183,27.0,20.0,35.0,20.0,19.0,18.0,17.0,19.0,CHCHCFCBDEHBHEHCCCCBDBAADFFECCGCAEAFAHCFGDGAGACABFEAHCBDBDBDACGDEDEDEHEBGDGDCAGABEBEAECEGAGFGCABFGFCEAEAGACFCDCFFGFEHBDBDECACAFHBHCHBHBFAHDBCADHEHACAGDDDGCEBFBFCCCCGAHCFCACAHH,False +184,21.0,29.0,29.0,14.0,13.0,23.0,22.0,20.0,HBBEFAHAHDHCHCGCBCAFABDDHDFAAADBDBEBCBCBEACGCGFFBFAFHGHFCFEHCHDADFCFCEDBGBCCFCFGFHCHCACBEAFBECFCDAGGCGFGHGFGEGACCDCBHBACGFGFHFBFGEGBCHCBCDEBBCHGGBGBDDFAAAEBEBABHBABHGEGBHA,False +185,16.0,21.0,7.0,5.0,16.0,12.0,3.0,15.0,BBBHGHBACDBEAAAFDHEHAGAGAEEEHHCAEAFBBABFBCECAFAFBFHFEDABBBFBEBEBEBACHFHFHDHBFEAEBHAFCHEDECEHBHB,True +186,26.0,34.0,20.0,22.0,24.0,21.0,26.0,17.0,HFACACHCBBBBHBGBEHFHFEAHAEAEFDBHECAHAHDDBGEDCBEGGFGECAAADBEBGCGCFCFCFBFBFBAGCBBABEHGCGCGFGBBCHCEDAHBCEAEHDBAHGGDDDDHEADDDDDFFGBGAGBGBEBABDBDGDGBFBDBDBDHEFEFCFEAAFGEBCGEGBFFGCGAABAGCHEEEAFAEA,False +187,3.0,5.0,0.0,1.0,1.0,2.0,2.0,4.0,DEBGHGAFBFHHBHBABA,True +188,8.0,11.0,10.0,11.0,8.0,19.0,14.0,12.0,HGFBFHFBFGGAHDDEBAHFHFHFCEGFGFGFGBGEGBCEEAFDBBBHFHDBDBGACHCHFGCGFGCGFBCDCDFFAEAHAEFDFDHAECDCD,False +189,24.0,32.0,23.0,32.0,21.0,21.0,20.0,22.0,BBBABAEECDDDEDEHEBECEDEDHHHFHFDFHCDAHAHDBGBGEGFGFGFGFBAGCGDFBFHDHBBCHGHGFAEBEDCAAGFDDADADBDCFGHBABDHECBDBAAHADAGCDCBABABGBHDCGCBCGFEBDCHAHCCCFCFEBABHDDBGBHHCCCGBABDBCEEGHAFEFEDDBAFFFDFDCEAEAEGDBD,False +190,13.0,10.0,11.0,9.0,7.0,16.0,9.0,11.0,AGCHAGCBAHCBGBEBEACADADHDBFBDDAGEFCFCBHDEFEFHFHGHDFGFACAEFHAEAGGBGFCFCFHFDFCFCBBFDAHAH,False +191,14.0,3.0,6.0,9.0,14.0,7.0,4.0,6.0,EAEFDGEEFCCCFCFEAAAEADCDAEAEGGAFHHHHEAAADADEFEBDBAEGECEADFDHDHB,True +192,6.0,4.0,7.0,3.0,3.0,3.0,1.0,4.0,CFGEHCCFCBCEAEHCHDADADABBBACAFH,True +193,29.0,36.0,21.0,12.0,18.0,14.0,23.0,24.0,BBHFFFCEHEGEHDHBGBHBHDEBHBHBEAEBDBFHFHEHABADACGGGADBBHHFBBBAAAAABECDCACHCAGACFCFAEAFAFAGGDAEBDBHBEBGACBHFAFGFGBBCAGGBGHDCBBDGEHEGEACACACEBEBCACAEGDGHCBDGHGHBBABCCHCHCHGBAEAGBFBG,False +194,6.0,3.0,5.0,1.0,2.0,4.0,8.0,5.0,HBHGGFCFCACAEABGEACDCHBGGHGAGAFHFG,True +195,3.0,6.0,4.0,7.0,9.0,15.0,5.0,10.0,HAHEHFGFHHGHGFFCFCEDEFEDBGBDEDACBDFHEBFHFHFEFDFCFDFABEBGHFE,True +196,2.0,2.0,8.0,2.0,3.0,5.0,4.0,4.0,CCECHCDCDCEBHCGEHBHGAAFFFFGFGC,True +197,0.0,3.0,4.0,2.0,1.0,2.0,3.0,2.0,DBHBDFCCCGCGBGEFH,True +198,9.0,8.0,9.0,4.0,11.0,7.0,12.0,11.0,AAAFADHGGGFGCBCBCHEGEFEHDCABDHGEGEGDACBFHFBEBGBECEHAHAHGBECFCGEGAHEHCHF,False +199,9.0,8.0,10.0,11.0,7.0,10.0,5.0,6.0,ACADDFDHDABGCDEBEHAFFBECECDBBABAFAFAEAFHDDDHCCDCGCGHGDGHFCBCBFFEFE,False +200,15.0,9.0,5.0,13.0,12.0,23.0,15.0,22.0,CHGFEHBDGDHEHAHDFDFAEBDAHEFEFEGGGGAAAGEDAHGHGHECEGFGFGAGBFEFAFBFBGBDFAFHDHBHFHFHGDEDHFFCFEDBDHFFFAAHBHAHFCFDHHCHAA,False +201,8.0,4.0,6.0,6.0,2.0,3.0,2.0,2.0,AGCFBBCBCDAHABACEHDADADCDADAEFGFC,True +202,15.0,30.0,30.0,30.0,15.0,29.0,25.0,23.0,DFBBDGHBCEDBFBHBHBCBHEGGGEBEBHHEHCFFHFGBHEGBDFDFGBGDFDFHCEFHCGCFDHDFDEHADADEBCFEFDFEFECDAAHFGDDDCACACACACDBABGGEDAABBBGCACABFBGDCDAGGGGDCDFFFGFCBBBDBDHECGHGDGCGCHCHFBFHHHDHCEBFDFDFCFCGCBCBCFCDABHCG,False +203,14.0,19.0,19.0,3.0,12.0,14.0,16.0,22.0,CHAEADAHBHBHBHBGGDBHFHEAAABCBGEFCCHFEBHCHABABFHCCCHBHAGAFCFBFAAAHCFCGEGEHEHEHFHBHEGFGHBEGGGCCFGFGCDAECGCBBGBFBCHCHCGBFE,False +204,9.0,15.0,19.0,11.0,9.0,19.0,20.0,15.0,FAAACCHEGCGDGBHDCCCEBAHDGDFDBDBHCFGFCFCBCBFGFGHGBFBHHHFHEGBGBCAEBCCCFCFCHGAEFEAGCDHGHGFGFGCGBGBGFDACEBFDFDEHEDGHABFHF,False +205,20.0,16.0,16.0,34.0,30.0,20.0,29.0,29.0,CDCFGDGDEFHGHEHEGGBGBGBHBGEFECDCEBGDAHGCBDDGDHDHEBEDDDDHAFAFDEGCHEGFHFADBEEGAGDGDHFHBDEAEAHAHDDDECGBADEHEFEFDACAGEGFGBDEDECHHHEAEFFBADDDDAEAHHDHDCCFCAAAHCFCFEGHHHHGBGBDCHCHDFDGGEGBFBGHFAFEGEGEAE,False +206,20.0,18.0,16.0,14.0,21.0,4.0,6.0,11.0,ABABAFADEDBAECHGDDAAHEBBDBACECGAAAACHEFEBCDHGBCECECEBEFEAECBCEHEDGAHACADAHACECGDDEEECEHHHFECBCBEBHBDBDBDBAGDBA,True +207,1.0,3.0,2.0,6.0,1.0,4.0,1.0,1.0,FCADBDBGBFEFDFHCDDD,True +208,5.0,3.0,5.0,6.0,4.0,0.0,1.0,2.0,DCCBCDCDCAAAAHDHBGAEEDBDEE,True +209,9.0,6.0,7.0,6.0,5.0,8.0,3.0,2.0,FCFEAEGDADABCBCFGAGCFAFABABCBDHCFDFEFEACBDHEAD,False +210,21.0,21.0,15.0,16.0,11.0,15.0,20.0,12.0,CACFFACCCEHFDBGBGBFHFAGDGDADACGGDGBAACABBECECEGEDHDHCABDFDFDAGHGHGBGBFBGEGBFDFAGAEHFDAHEGABABFGAGEBCCGCHBDEDGBCACFBFAFHDBEBHBABADAH,False +211,10.0,24.0,13.0,13.0,14.0,11.0,16.0,23.0,EDEABACHGHAEGGBBBBECECEBBBAHGHGHCBCECDCBFBHBHFHFHFBBDAGFEBHAHDHGCFAGABCDDBEBEDHGHBCCACFDDBAHHHGBGBGEGEGHGFEFHHHDDBBCDEFGFHDH,False +212,19.0,7.0,17.0,13.0,17.0,11.0,21.0,24.0,FGCAHAHFGEHAAAAAHGDGHGFEEGDHHAEAEDCDFGBGDHDGFECECGGEEHGHGHCFBBHBFEEHGHGHDHFHDHDAAAHDECAAACBCECACAHFDFCCCCCCGGGGGEEEDHBHEFCGDHAHAB,False +213,10.0,20.0,7.0,7.0,13.0,11.0,10.0,5.0,HACBEBEBAGEEHEDAFABBFEEEBGBGBGBAAEBBDDFDFDFHCHDDAFECHBBAFAGGGFAFCGBEBEBEGGBFFCBCBCB,False +214,6.0,9.0,11.0,6.0,13.0,4.0,11.0,19.0,ECECBCFDGEGBHEDDHGEBHHGCGCBHHHHHEHEGACABADHFFGCGBGHDDCEEEEBEFHAECBCHGHGHBHAHAHC,True +215,3.0,0.0,0.0,3.0,3.0,2.0,6.0,5.0,HDFDHEHGGGGHAHAEGEAFDG,True +216,1.0,8.0,11.0,12.0,14.0,8.0,9.0,12.0,GEBDBDCCADDBGFGFEEGEGCDCEFEGEBEDCCFBHCEDDGEHEHDDFCHHHBHBHBCDFDEGEGCHCHEHFHF,False +217,10.0,10.0,22.0,13.0,14.0,8.0,15.0,10.0,DCHGECECEAGHEFGACFBGBECGCAEBEHHAGEGFDFDFHEDDCDBFBABACDDHDBDGCCCGHGACFCFDGCGCBCBGAGACECACBCECGDHEHEHECD,False +218,7.0,10.0,14.0,5.0,9.0,7.0,7.0,16.0,CFCECECDHHHHHHHHBBBHEFCCEBDBABAGDFDHCHGACCHCHEFEGHGDACFBGBCEEEFGHGFCBCHAAAB,False +219,15.0,20.0,16.0,12.0,13.0,12.0,14.0,14.0,AGAEAEAHGHFBFEHBHFGGEEHCFCDADACBDBFBCBFGFBBBCCAEGDGFAACAHBCBCDAFHFHECAFFEGEBCBGGCDCDCDEBBDBDBHHHHHDGAGDCHCAGEGABBEBE,False +220,0.0,1.0,1.0,0.0,3.0,3.0,1.0,3.0,HEHEHFFFGCBE,True +221,4.0,7.0,18.0,11.0,9.0,20.0,14.0,16.0,GGGBFCCCFBFDGCFCFDFHFHCDCDHHHGHFDCAGHCBAEEFEFEFHAEFCHCGEFCCCHCHEHCDCDAGBGBGCDDFDFGFHEHDHFGEGFHFGFBB,True +222,19.0,32.0,14.0,24.0,24.0,23.0,30.0,29.0,EAEAGFDFDCBHFAFADGBHBDAGCDEABDFGEEFFFEEAECHDHBHDGAHHGBGBGBGHCDFDBDBDEDADHFFAFEFGBHBGDCHEDABGBEBCDCHCBFAFBGBAHFHFGEDFHHHBBBBDBDBDBGEGBHEACCHEGEGEDEHECGHGFBHGHCBGAGHGHGEGEGEHAHAHFCCEFHFAGBGBGDADFBB,False +223,6.0,4.0,7.0,6.0,14.0,14.0,8.0,15.0,CEEFAGEBDFAHHDHFAFAHBFFHFCFEHHHHFDEGEGEDEDGAGHDFGBGBEFGFHHCHCHEHECFCACEEFE,True +224,11.0,10.0,13.0,13.0,21.0,14.0,25.0,19.0,CGBAEGEGEHHCGGHGCCBCAEBEGHCHDFDFDFEGBDFDFEFAGDGAGEGCGBHEEGCGBEEGEADACECABEDCDFFFDCAGAGHFHAHGEGEGEGBGBGHHHHHHDABCEDHHFFDHEHEGFF,False +225,6.0,19.0,5.0,11.0,12.0,6.0,9.0,5.0,GBHBDBABHBCBDEDBGBGBEBEBCCFDHDFEBBDDEAEAEAECFGFGEGABCFGBBDHDEFBGBGEEABHDD,True +226,11.0,18.0,23.0,14.0,12.0,26.0,20.0,26.0,EFEFEFGDCDFBHBHADECHHEHEFGFGHCBGACBGACFDFGFCFGFCCCHHHBHFHFHDADFFEBGFFFFFDBCCFCFHFCDGEHDFDBDCAGGHHHHHHBACGCGAGBGHAAAFFCHGBGCADGBBBCGDHEBEBEBEBHCHDHCCCG,False +227,23.0,20.0,28.0,18.0,25.0,23.0,23.0,21.0,FCCBCEFEDAGGBEHCHCHAFCCADFFHFEFAHCHDGCCHAEDEDFDGAGAGAGEFEBEBHHEFEFHFCGDFBGBDHAHBGAHFFFBFCDDADCDEEAGABHBHGHCHCABADABCHCHCDFGHGHBAFFEGECBGADCECGCGCBFEFDFCGCGDEECAGAEAGAGBBBBBCEEAEDECE,False +228,5.0,3.0,9.0,5.0,8.0,2.0,3.0,5.0,DDDACEHGFBCEAECCCCCFCEHEHEHEBCDAEBDHAGAG,True +229,15.0,19.0,18.0,23.0,23.0,15.0,10.0,23.0,HHFHGHEBFHHBCBDEEHCBGBAHAEDEDCGCGEBBDDDDEDBDHDFDEDACCEEDFCEEECBCBCBCDAFEHCFAHBEDACAGHHHHHHHAHGFACACAFBEBEFFFFFDEBEAEGCBEEDADACBHGCGBGDHDHDFDHDEABF,False +230,15.0,10.0,14.0,14.0,7.0,9.0,3.0,6.0,EDADBFADCDCDEBFBFAFEFEDCBADFBFBAHACCBCGEHEHBCCAGDCFFBAAABAGACHCHDDCCCEDHDADADA,True +231,21.0,19.0,19.0,16.0,21.0,13.0,13.0,23.0,EHBFBHBCDAEACABABEHCAAAAAEBDHDCECACAHGFCFBFBDCCBDBDECHCGCAAHHDDCDCDEEHHHADAFBFGFGDGFGHGAGEEFEHBBDBGHAHGHEBCCACACGEDEAABDBCEDEFEHBHEEEHGHFHEHFFGHB,False +232,10.0,11.0,13.0,7.0,8.0,12.0,12.0,9.0,EFGGGHCHBAEHFDFEADAHBBFBCGFGBCBCBCFHFAFAGCGCEBEDCCCHCHDGGGCGCADFEBEBDAFAFAHEFGBHDA,False +233,16.0,18.0,26.0,21.0,12.0,11.0,22.0,9.0,GBGCHBGDHEHDGAFCFCGCBBDDDHHGCEDEDCDBGBEBCCCCDBGBCACBGGEHEDGGAGACFCFCHCGGDGABDCCCGDBDEDEBBCHCDCDBDAGECECAFEFBFEAGAFAGBGAGDDDACAFAFAFCHBA,False +234,8.0,5.0,2.0,10.0,3.0,5.0,9.0,5.0,GAGBBEDFDFDBDGDAEADHGAGHBDGDFDFCGAGACABAGHHHFED,True +235,28.0,16.0,21.0,19.0,24.0,21.0,12.0,20.0,EDHFBEAFADABHFHFCFHFACCBBBHAHDHBADGDBCBDFEFDHHADACBHBEAEDDDGAGACAEHECFCECHHHEABFCFEEHGAFFFADADCDGEEEGEBECEBBCACAHAHADADFFAFAFHGDEEFEBCGCGCGCDCAHBGEEFGADECECAFAHA,False +236,13.0,6.0,14.0,8.0,9.0,13.0,7.0,14.0,FCFAFAFAHAHCDCDGFFEFECEDBCECDCFHEEFAFACHCHCEBGDHEHFHAHBHDHFCGGAGDHHACCBHDCGFGBAAEABA,False +237,4.0,7.0,4.0,12.0,6.0,4.0,7.0,10.0,DGGHBHDDDGDGCGCGADBHEDEDAGFCFEBDHDEBAHAFEHEHCHDBDBHFHB,False +238,25.0,27.0,17.0,20.0,11.0,20.0,27.0,24.0,BGGGHACECEFEAEDBDBHCGDGDHDHBHBHAHAHFBFGCGCAHFHABABEFFDDAAFHFHDAGADFDGBACCCHGHDAACHCHGBEBCCCBDAFAEGHAHGHGEDBDBCBHBGFEAGAGBGBABDHDGAGADFBFGFGCAEBGFFEHBBGDGBBBFFHFBFCDAGCGHDA,False +239,27.0,19.0,14.0,12.0,26.0,20.0,17.0,18.0,CACHFHBABHBABAHEGBDDEBFAFAEACABAFAHAHGHDFEGEFEBEBEAFCDCHABAGEGEDFBGBACAFDCDCAEHEHFHFEEEFABABCGEEEGHDHAHBHDFGEGBAAAFDHECEAGCGEBEDCDHFAFAGAGBGFFCGCEHGFEBEF,False +240,13.0,5.0,13.0,8.0,10.0,9.0,13.0,11.0,HCHAGAEFGBGAGFGCDCAGAECGCGEFEDHGFADADACHDFDGBCBCFEDEFEFBAHHHHHHAAFGCECACBCGEHEADCG,False +241,15.0,13.0,22.0,21.0,14.0,24.0,13.0,15.0,CECEBACABEFHFGBEFDCDBABGDAEADCDHGFGFDDDFDFDFGFEFGCGEAHGHGHCFCDABFEHHABCECBCHFHCACFBFBHBADFEFEFDFDHDHCHCDEDAGGECHAFDHCABFCFDFDGBGCFCACDCEA,False +242,10.0,3.0,9.0,4.0,10.0,22.0,6.0,6.0,CBAAFFFFGBDAFFFFFFFDGAGEHFGECEFEFHCHCEEEDCFAFAHAFBDEHGHCFEFCFCFEAAFAGC,True +243,16.0,18.0,13.0,25.0,8.0,14.0,16.0,17.0,CFHGHAFGFCFEDAGEBBFDGBGHDHAHBGBGBDCHHEBDBDBDCDHDHFAGGHGHABADDCDFBHAGDDDBCACECAGEGDDHDFDFHFHCGCGCDBAFAFDBDEFEACADADADBCFAHBHGEBB,False +244,14.0,10.0,26.0,18.0,17.0,28.0,19.0,21.0,HEHEHDFDFEGEGFGDCBBDAFHFHFDCEGBBDHFAGBHFHCECHCGAFCCDDADGHGCGAGBDCDHDHDACFCFGACEHEGDGFCFCFCAEFHHHFBFDFDCBCFEFCDGAGDEEFEFHFHFEECCCAAABECFHACECFAFGFCBCGHGHG,False +245,30.0,27.0,23.0,25.0,28.0,19.0,14.0,26.0,AAACACBCAEDEBEFCCHCAEGEDEFGAGCEAEADFEBBBEFAGBBBFDAEAEHHHHCFCHCHADFDEBHFACBFBGBFBCHHAHAEEGHHEAEGHGHGHGCAHADADAEAEAGDGBECHDDDDEFFDCDCACAFBFHCHEHEADFBFBGBDBCGABHBHDACCECDDBDBDFDBEEEEHCBAFHHDBBADF,False +246,9.0,17.0,16.0,9.0,17.0,6.0,11.0,16.0,HGEGACAHDHDCDEGFHBHDHECEDEDFDEEHCFCFHBEGGFABEHHHHGAABCCDBEBECHCHFBAHGCGABCBEBECCCCCEGEBBBBDBABEBHGEGA,False +247,10.0,6.0,15.0,20.0,23.0,16.0,16.0,6.0,AFDGEGEFEDCDFHEGEGFGBCACECEAEHEDDHEGEDEFGDDDCCCCGAGEDBABEFEFDGDHDGDCBHBGFFCFCEEEEFCHEFGDGFCDADCFCAEGFGBEFDADADAE,True +248,1.0,1.0,5.0,2.0,5.0,7.0,7.0,2.0,EFCFDAGFCFGFCHEHECEGGCGDGFGFBE,True +249,20.0,25.0,23.0,25.0,18.0,22.0,28.0,20.0,DGDBDAABACHGHEBDCCABFBAHGGBGEAAGDDFGFAHADADEDFHFHGGGFGFDHDEDBACDGDGBFACABBGBGEGEGECFFFEABDEDHFAFGBCBCACHHFHFBFBFHCHCHCECDGDCEHEGCGBBFBGEFEFHCGCBHGDGFHFEABCCEBDBHGDGDGBHCEDADCDCBAEAC,False +250,27.0,24.0,20.0,16.0,26.0,17.0,25.0,11.0,CHCBCACHBABAGHFEEBEGECEBEBEACDGDHHGAAFGEGABEGAGEGADADABAECFGBGAGAEBEADFGFECACGGFGEGDGFBFGCGBFBFEAEBEFAFAFEDEAAAAGBBBCDCDGECCCBCFADABHDEDEGEAHHBDEDFDFGCCCDBBHAHGBCBEHF,False +251,23.0,19.0,20.0,25.0,22.0,22.0,28.0,26.0,ACACGEBFHHCAGAGHGHGCGCGBEHFHFCAGFGCGHEHAHADDDDAEEEECCFBGHAHAHGBDECFADGCECEGEGDGAADBEAEFHFDGDGAEAFDECBGECCHDEEBGBABEHHAFFFFEFDADHBHBDDGGCGCBAGAHABDBDEFEBCBDHGHGFDFDFDFHBAFCBDBDFFGGCHHHDH,False +252,22.0,23.0,23.0,11.0,21.0,24.0,27.0,23.0,CGGAGEGECECECDBFFFHAHGEGCGAGACEDBBBFGFGHGHFCBGHFHBHGEAHAHABDHABABDBECHAHFCFEFAAGGGBGFCDCBEADADHFHDHCEABCGGGFGAHEEAECCCCGBBEHEHBHBHDCDFFAFBFCEBAGAGCCBCAGFDHHEHFFFCFEFBBEBFGEGA,False +253,21.0,15.0,11.0,10.0,10.0,18.0,15.0,19.0,CFCEEFHBGDEEFEFDAGAHAHGHFHFHGHAHAHGFFFGBDBGAAAABABGBFBFBEACGCEDHFACCFFFGECBAECDGGAFAHDHDHBCCGHAHAFAEDHDHGBBABDFCAGABHBH,False +254,16.0,7.0,14.0,11.0,13.0,17.0,11.0,13.0,CDFHFHECACEDEAECCHFHFHGHGCAHAGAGDEDFDCHCFDADFEGAAEAFFDEDCCEDBFCGCGEBEBHGAGFBABAGFHDHAHAEFFFFFBEBCGHACA,False +255,14.0,24.0,17.0,17.0,23.0,22.0,12.0,11.0,EDGFFFGBBBCACDDDBDCFCFCEEAFGFGFGFDBBBFBDCFEFADAHEDBDFHAAGHCHFGACABEDEDEAECEFEFDAABHHAHCECBFBCBFFDBDGHGHFBCDCECEDEAAGEGFBEBCBEEGEBEBEBHCEFBBH,False +256,15.0,18.0,13.0,27.0,17.0,28.0,20.0,24.0,FBDBCHCGDEDCGAGAGDDFBBBFFFFEDACGCHAGGGEGEBABFHFEDHFHFCBDGHGBGDHBCBGAEHFAFHHHDBDCHBFGFGFHFHEGEBDFFFHAHGHCHAHDHEBEFEDGDGAFABDBEHACFCFCEDADEFBDDEAEADFDFHFHFDGHEDDDDC,False +257,6.0,7.0,12.0,13.0,9.0,11.0,8.0,10.0,DDACHGHGHDHEFCCEGEGACCDCDCDADHBFEFEDEGCFBFDFBFEHCHDAGEDECBCBHFGFDFHAHCGABDBF,False +258,17.0,20.0,27.0,16.0,18.0,18.0,19.0,20.0,AGEHCDAGCGFGDCDCHCACDFEAGFGAAAADADCCHGHGHCCEEEGCADACAHECEGDGFBFBFCHCHCBBDBDBDEFCGCBBBEHFHACAGBCHFFBCBCGGGGHDBECEHEHGHBCAGEDEBFCEEBEBDFCFAFHBADDHFHFHFHECFBB,False +259,1.0,5.0,4.0,1.0,1.0,0.0,6.0,2.0,GGGGBGAHBHCGDBECCBCB,True +260,2.0,3.0,4.0,1.0,3.0,5.0,1.0,3.0,BFBCBFHEEGEHCACACHFFDF,True +261,2.0,4.0,3.0,2.0,3.0,2.0,6.0,2.0,CDCABEHHGFGFGEBABCBGDGEG,False +262,17.0,17.0,32.0,25.0,20.0,22.0,15.0,15.0,DHDCDCDGEHCBGBEBACGDFDCBCFCBCEAEAFCDEBAAEADHCEAEHECDDDBDCDBBFFEFGFBCBHAHFCCECGHDHFHAHACDEHECFCDEAAHABBCHGEGDGFHDDCDGDCCCGCACACFCFDADFGFBFBFEGEGEHDACGDFCFCFGBEBEFCF,False +263,7.0,4.0,7.0,4.0,5.0,5.0,7.0,12.0,GCACAHGHECGCHFGFEDHDHDHGHBAEAHBHFHGCCBCHEGEBHAFADAF,False +264,6.0,6.0,13.0,6.0,11.0,2.0,9.0,8.0,DCFBDBEEEEEEADAHGHGCGDHCHGEACBCGCAHEHGGAFAGCCCCCBEBHDCBCEGEHD,True +265,20.0,25.0,22.0,32.0,26.0,23.0,23.0,27.0,DCHBHBCEHHGHDCGCAHHGHDEEHEHBBECDCGBBACACADDDDDFCGEABGBABEBEBEACFHFBEGHFBABCGHGEGDDDEGAHAEFBFDGDHBFGFCDCDCDFGFHEBEHEHBDEAEACBDADHFBDDDDAFEFBGGGGHGHCHEHFCFGFGADDDDBDADHFEBEBECEADACBCFAFHFDFGFAEGHHCCFE,False +266,7.0,6.0,7.0,3.0,4.0,2.0,13.0,8.0,BGHCABHHCHGGBDBABAFCGEGDGAHCEEGEGBGCAHAHACGCGHGFGD,True +267,8.0,8.0,22.0,12.0,15.0,14.0,10.0,10.0,DCBAAGBEBEHECCCCFEDDDFGHGDEDCBCGEGEGEBFFAEHECFCHCHFHDCDCBHGGCCBCFCHHFAFGHGDFCEADCDCDCEBFAFACECAFEFE,False +268,20.0,11.0,17.0,15.0,11.0,11.0,19.0,11.0,FACAFGDHCEFHAECBCBEBEAEGBGBGFHCCBCAHDCFCDGDAEEEFBACADABACECHGGDBDGGGFHEHADAFGFGFGHGHGCFCDCDEGAAAABDDDGHBACACDGDHAGA,False +269,6.0,1.0,7.0,4.0,8.0,4.0,3.0,3.0,DBGECEAEAEAEAGDGFCHCECFAAHHFEFCCDEDC,True +270,18.0,16.0,20.0,26.0,19.0,21.0,22.0,23.0,BFBCDDGAGACDBDGDGDADHCAEACGCGDEBGDFDCDBDGHEHCFFFFFHFBFAFHDDGBHHHHFEFABGGDGDEFCDGHCHEFCFHBADHHCFCBGBFEEEEEFEDEDAFGHGDGCACDEAEACDEDHBHGHBHBHCDGAEACCEHGHAHACAGACBEBGFDF,False +271,0.0,3.0,1.0,4.0,2.0,4.0,2.0,3.0,HFHFEFDBEBHFDDBDGCG,True +272,16.0,16.0,17.0,14.0,11.0,14.0,8.0,16.0,FCHEHAFAFBFBDHGAFABBCDCDHBHEFABCHCHDAGABEBAHDHDFCEBGDFECECECEHECACDBDBDCGAGAGACAGBFBGDDACCDDBHEHBACFBFHHHFHFCFAE,False +273,13.0,11.0,14.0,14.0,11.0,17.0,18.0,16.0,CDFDGBHBFGFGFGEDABABCHHDDEDCHCGAGFBFDADHDCDCECAGEFEBEAFAEHEHGGEFBHCHFHFAFDFACGGFGHHDHGHAHCFAFGEBCBGBGCACDCDEHGFBAG,False +274,30.0,26.0,12.0,16.0,14.0,36.0,17.0,16.0,GGHCBABACFGFHFBBHAEAEACADADABABFFDABBFFEFBAGFHFBFCFBAHHHHGGDGFGBHBFEECEFDCHCHBHGEAHADDGAFAFDDBDGFGBEFFFFFGFACABGFFFAABAFACAGAGHDABABGDACFEAEADBBFBEDEAFFBFBFCFCDBHEHEDF,False +275,6.0,13.0,13.0,9.0,7.0,9.0,12.0,6.0,CEFBGCCCCHDBDBCAFDFDFGFHHCCGCGBGDGDBCBCBHFGAAEGBGBFBGBGECHCDAEGEFADAHEDEBBF,False +276,7.0,5.0,3.0,5.0,6.0,7.0,3.0,5.0,BCCDFEFEFEBADABCFDDHDHAAEAGFGFHFBAEAGHBHE,False +277,6.0,5.0,1.0,2.0,3.0,3.0,6.0,7.0,HBBFBFDHCGEGAHAHGHGFEBHBGGAEAHADA,True +278,4.0,8.0,15.0,16.0,12.0,11.0,10.0,10.0,DHCHAEEEHEHEFEHGFBHEDEGEGFCDCFCGCDCBFFFCEGDBHFDDADGGCGDEDEDGACDCFCFBGBHBDBCFCHCDDDHCAB,False +279,15.0,15.0,14.0,9.0,20.0,30.0,10.0,19.0,EAFFEFEFHBHBHBHCHCFAAACFCAHGBGBFEEBECEGEFDCEFEGCBFHFBEAFDBBGDDCGFDCBBHBHFEFEHCHFBFDGCHFHFHFGFGAAAAEECEFDBEFECEHDFCFHDHFFEAAAAAFGFHFH,False +280,20.0,27.0,17.0,23.0,26.0,20.0,26.0,25.0,AEDGCEBACABABGBGFDCEBHBCBCGHBAEACBHHHCDDEGFHAAFABCEHDBDBDFFGFCBGGGFGEEFEDEAEDEDHHHFHEEEGEGCBCBHBEBGBGECEAEHGHABBBFHEAFGBGDGFFEFDGDGDGHGDAFAGDHDECEHHHAHDDGHGCGEBEFABCBDBFCFCFHBADADFDAHH,False +281,10.0,6.0,6.0,8.0,8.0,11.0,10.0,7.0,GBFFDHAEAECDDBEGDGAEECGGGDHDAFADAEAHBHDEFFFFBCBCECAFABAHGFGFGFGHCH,False +282,21.0,33.0,19.0,20.0,21.0,12.0,19.0,26.0,CAADABABCEABHBABDCHEAEGHBBCCCCCHCBGGGGHHDHGHGDGDGDBDAAGCBHDFEEEEEEBEBAHHGHEHCCGHFBFBFBFGHBDBHAFAGACCHAHFBCCFDEDEHCHABDBEGADBBCBHEHEDDDDBDEDBBHAHBEEEDBBBBHGGGCEFBFAFBGAHAFA,False +283,12.0,9.0,6.0,10.0,12.0,16.0,15.0,10.0,CFCEDFGCGFHFBGCGFGABEGAGAGAGAFADBHGHDEFHHDGCADEGBBCHDAAAGEBEBABFDFEFEFHFHFHFHGBFEGEDDDEFEA,False +284,0.0,7.0,2.0,2.0,5.0,4.0,3.0,5.0,FBBHBHECBFDFGEHCHEHEBEBDGFGB,True +285,18.0,10.0,10.0,8.0,8.0,13.0,19.0,13.0,HHHFGFAHCCBCHCBFAGCGBABDBDGAFDCDAEAEHDADBHBAGFGFGHEFFGHGHBHAFFBFCFCAAABEEEAGGGAGCGFGAGADAGEHAHCDGEG,False +286,17.0,19.0,13.0,13.0,17.0,16.0,12.0,9.0,DBDADABCGDAFEFEFEDABCBEBGDGFEBEBEBEADBDGHCADABFDADADABGFGFCBCDCFBGGEEFCFAFEFBAGGEFHCGAFAHBHBFFEBACECACBCHAHEHEHCGBEH,False +287,11.0,13.0,8.0,14.0,5.0,10.0,1.0,11.0,ADDCHBHFDEACFDBDBABCBCDDDBAAADHFBFBABEHEHBHBCCHFDABAHCDDDCDAFHFEFEFHFHGAB,True +288,21.0,32.0,21.0,22.0,23.0,17.0,23.0,21.0,CFCBBDADEDEDBDHDADCCCEHEHBFBHADADBGBGDCBBHFAEBDHDFDFBEBHDEDBCECEGABCFGFHDHGHEHAAGHGEDEAEABGFCCBEBCFDFAEGGAGADECFFGFBBHCGEBEGAFABDBHFFAHAHAHBHBEBEBCBABDEGCGCHCHBHBGEGEGCAAGGBBFCCGDG,False +289,10.0,13.0,5.0,12.0,9.0,19.0,21.0,12.0,GBFAEDDDGGFEFDHHGHGFGFGDGFGHHHHEGDBHFGGHECBAGAEACFBBDBCADFGEGDBBBBCBHHFFBFBFDAAAEFGFAFAFDFDFHGGGGGECE,False +290,10.0,11.0,9.0,13.0,3.0,16.0,8.0,5.0,DBDBDCFFGFGABEBEDEFFGFGFAFABHCAFABCDHDADAHBGBDDDADFHCBCDCAAGHBFGFGFCCBFFCFD,False +291,22.0,19.0,25.0,28.0,18.0,24.0,23.0,17.0,FCFEFEFAGEGCGEAAAEGEHFHEGFGDGDEDBDEEECBBBEDFHFAGHCAGAFAHABFBFDDGECEBGFDFCFCDBEFABGEDACACDHDHDFFCDCACHCDBBGCDBHBHCFCDHHHBHBGFGFADDGDCDCHCDCACAGAGCDDABCEGHDHFGGDDEAFBFACACABGBGFD,False +292,22.0,21.0,17.0,19.0,16.0,16.0,15.0,29.0,EFHHAHDCDEBEHEHEHEHEHCFDBCBDHCAFEGGHDDBDFGFGHCFDDDDAFADCGCFDFBFBHGAFCCBBEEAAGAGDEDAHAHAHBHBHBHEHCABABHBCCCHCBBBDAHGFDEAEAFHGBGEHAFBGHAFAFAHABCDDECGCHHGHGAB,False +293,14.0,10.0,22.0,19.0,17.0,10.0,11.0,13.0,FDGGCACGCDCACBCDCDGHHDHBHFGGCCFBFBCBDFDAGEHAHEFECBHGDDDCEBBADCDFDADEEEEDEBHAHAGCGCBDGECEHEHAACADAHFHFEFCCECEDECCDAEA,False +294,21.0,23.0,11.0,16.0,19.0,13.0,19.0,13.0,ECDFDEAGAEAGHBFEFGHBBGBABABGDGCCAGHBHFEFGGCBDGDGDGHFHABAECEAGHFDFEFBFECECEFDHGFGABAEHEGEBBBBEBADFEHEHBDBDADADGBHADADHGAEBBBDCACECBCAAGA,False +295,16.0,21.0,15.0,23.0,14.0,18.0,17.0,12.0,DDBBHFDFGBGBHBFFFFFFFGEBCFCGHABBEHDDDDBBBBDGFHFAEDHDHCFCHCECBAHACDCDHAAADDECACAGABAGEFEBCAEACGDGFEFBGBDBCBGGDDAEFEDGCGEGEDEDGDBABADFHCHG,False +296,2.0,5.0,5.0,3.0,8.0,3.0,7.0,5.0,GHDHFBBGGCGBHEHBCACHCGCGEEEEFDADBEGEFE,False +297,8.0,7.0,6.0,6.0,3.0,4.0,7.0,7.0,GDGFBFEFAAEBDBDBAGAEHBDBHCHDGBGCGHGHAAACHCHAFCCD,False +298,10.0,8.0,9.0,8.0,12.0,10.0,12.0,8.0,AAAAAADGHGAEEEHFHEHEFFAGAFHCDCGEBCBCBFBFAFHFGGCGHEDGDFDBGEDEDCBEGEGHCBEBCCDGF,False +299,2.0,2.0,2.0,2.0,1.0,0.0,0.0,1.0,CHCEABDBDA,True +300,21.0,16.0,12.0,20.0,12.0,15.0,16.0,21.0,HFHGDDEFBFBFAGCFAGBGDHEHBHBHAEFBDGACHGHAHFFDFHFHEBBCBDBDBCFCDCACAEDEDHAHBHECABAGCEBHBGEDEGAAHAFAHADCDEGEGADFGAGAHCDAGADAHCHDDGDGDHFBF,False +301,18.0,17.0,21.0,18.0,14.0,17.0,20.0,23.0,BEBFFCAGAGAGHGHFHDHCFDFDEDEBEBEAGFBCCHCDCBCHHGHEACAEFGBGBEDEBCDADHFAADBHBHCHFDFDFHGBGBAEFGFAAEHEHEHCCGHDDDGHCCCCAABCGCGCADACABFEHDBCFHGHGDAHHDFGBGFG,False +302,17.0,9.0,16.0,15.0,18.0,20.0,16.0,20.0,CFEHGDGCGHFADAFGFBFHABACDEDEDGAEHEHCCCBCEFHGHAEAEAHAHEHEHCDFFAHDEAFDFGBGDHHFHFAGGFFBEHEAEAFFFDGBGCGEECAFFHEHEHDACBCFCDDDDCBCBHGAGCG,False +303,17.0,9.0,12.0,14.0,11.0,11.0,11.0,15.0,DFDFAGHHDEDEHEHECGFACAEADDHDEDCHCECFHBBBEGHBACGGGAGAHDHAAADEHEAFADGDBDFHFGBABABHBFCHAHACCFCGCEADFCFG,False +304,32.0,22.0,21.0,20.0,17.0,21.0,22.0,16.0,HABACGCBCGHGHADEGABAFHHGFCCGFFFHFHAHAGACFGEEAHAHABABFBAEAEDGDBDFFFFEGHGDDDCHFAFGECACECECEDFBEAAFBCGAGECECFCFCBGGADADGHACAEBHAHABGGDDADCDADBBBGHEFEDDDGEFBDBDBCBABCBAAAACFGB,False +305,22.0,14.0,10.0,9.0,20.0,15.0,19.0,12.0,GAGABHEFGHGABAEDECGAFABBEFEAECCAAHGHBEEEEEFHFGFGAEAGAGDGHGFAAAHAGAGFBECEFFBBGHGFCBCGCADEDBDBDBDFEECEBEDGAAEAFAHHBFCFCDHGH,False +306,7.0,13.0,6.0,7.0,4.0,5.0,5.0,12.0,BABAFAHDFDGBHHEHBDACHGHGDDBDHFFAFACEBEBEBHBCAHBHDHCGBHBCGCB,False +307,27.0,19.0,23.0,17.0,31.0,29.0,21.0,17.0,FADCDEGEBEGHDAEFEAEBHBCBAFAHAFGEGFBFCAHAHCCBDFHGCEFFCFEFEAEAFCBDADADHDFBFBEBADFCFEFBFBFDFCFGFEAHBBCCCCHHBHAAEGEBECEGDAEFDGECEFEHGAGEFEDGBABABHDHDCDCGHAEACAGFCECGGHEDCFAAAGAGCEHEGEGFGFE,False +308,16.0,23.0,23.0,25.0,22.0,21.0,28.0,27.0,BHGEFEDACAGADADGDGDBBFBCGGHGFCFCEHHDCDCEGFCFBEBEHDHCHCBEDDHBBEBGGFDECHCHCBFDFBGEHEGEDEGAHDBDAHGBGDGBCFCGCGBBAFAFABBBFGFHAHAEAGFFFGDDCABHECEDEBEHDGDEDEGCHCDCACHCAFGGGHFHFHGHGCAEHHHHDDBEF,False +309,11.0,10.0,14.0,4.0,9.0,15.0,8.0,17.0,CECHBGAHBHAHGCACBEFEFDCCCCCBCDCGAFFFFFBCBAFHFHFHDAEAHGHBHBHEHBHCGFBHAAGEFEFEGHAHDFFCAEHG,False +310,7.0,7.0,11.0,8.0,8.0,14.0,8.0,4.0,AFACGFEEDBGHDDADFCFCFCFDBGBHEHFAGDCACFCFEFBDBGBEBFCFCFCADGEGEAHCFGE,False +311,1.0,3.0,3.0,4.0,1.0,4.0,5.0,3.0,DHHBHDGDGCFAFGEBCBCGFGFD,False +312,9.0,6.0,12.0,3.0,7.0,3.0,4.0,5.0,AAEAECGCDFDHACECEAEBHBACCHCHEGCGCHCACBBAFAFCDGEBB,True +313,10.0,20.0,11.0,11.0,10.0,21.0,14.0,10.0,FHEBEBCAHAHBFGFGHGFAFCFDBDFDCHBECCCHEACABDGFBFEFAFAHGBFBDBDBFCCCEBFGGBGFAFABEEAEGBBFFDFBFBDBGBGCGDEDHFHDGGH,False +314,11.0,11.0,19.0,12.0,11.0,7.0,10.0,11.0,GBHBFGDABADADBDCDADHBGCECHCHCGCEAGCGCDCFEAGAEAEHECEFFBECDCGEHCBBBCGDHDBDADCFFEFCACAEBHHCHGHC,False +315,15.0,20.0,19.0,23.0,12.0,16.0,12.0,15.0,CCCCEFDBDHDCDFDCHFHFDEBACECHCGGFGAHDDDBACFFFDFBBABABDBACADAHCHDGCFFBHHDHDHGCCACEDBDECEHEBABHFDDDDGEFBFBGBEBFAGAGBGHEHDFEBABAEADBCGCG,False +316,6.0,8.0,6.0,3.0,8.0,2.0,0.0,9.0,CBCDFDHABAFEHBHBHECEBECHHBEEECEHAHCDAHABAB,True +317,5.0,12.0,12.0,7.0,8.0,8.0,7.0,11.0,CHGBGBFBFDABACAFFFCECHCEGDBBGHCCBGDGFGHEHDHCHBBCCECEBEAEAEHDCDHHBHBDFF,False +318,19.0,29.0,24.0,19.0,24.0,39.0,20.0,15.0,CFEFGHBHFHCEABFCCCFFEFEGBGBAHAHDBABCBGBGBGAGAGABHCCCFFFEHEDGBHEEDHDEDBHFDBCBGBFCFBEDFAFCFGACEFGFGAAFFFFDFEFECCGEGBDAAECECABEFDFCEAEAHFDBABDCHGBGBGBCACBCBEFGFGFCFHDDFAEHDFFEDDFDFBFBEBEBFHFCD,False +319,8.0,5.0,5.0,2.0,5.0,4.0,3.0,7.0,HAAEAHDHCBDEAHCGFGCEABAEAFAFHFHBHBCBCEG,False +320,4.0,0.0,2.0,0.0,3.0,0.0,0.0,1.0,CACAEAHAEE,True +321,19.0,25.0,20.0,14.0,21.0,25.0,19.0,10.0,ECEAHAGAGDCFHAHAHABEGAGBEBFFFFFGFDFDFGCDCBABEBGBFFFAGADFDGHGABAHAGCBABGDGEEACAEDBCBCEEFHGDDCBCEGEFEBEBFGCHBHBEDFHBCGEBCDCFCEBEFEBCBCBCBAGFFAFAFDCGEEFDCBF,False +322,4.0,3.0,7.0,8.0,3.0,3.0,6.0,6.0,AGDFDFDAGECEDDHCHGHCBFDEBCBCHCHCDDAHAGGG,True +323,20.0,23.0,10.0,13.0,14.0,23.0,24.0,21.0,AGAFFGHGEBBCDCEEEGBFAHAEGEGCGFGAAEBGHEBDGAGEBABEFCHAHADFBFDFBHBHBGBEBFBFHCACGCGBFBFAHAHFEFDBGGGBGFGBBEDHGHGHFHDHDGDHBFBFDFHFHFACADAGEFHCAADHBHCADFGA,False +324,6.0,10.0,13.0,15.0,5.0,10.0,12.0,7.0,ABBDDDDGDHDCBBHCHGDGBAEGEGHDBCFGFBEBADGCGCGHFFFFFCFCBDBDGDCAAAFDHCCCECDFDHCGEG,False +325,14.0,17.0,16.0,18.0,24.0,25.0,25.0,12.0,EAGDFBFEHEFGADABCCEGEAEGEGHGBFBDEAEDHDFEFDHCHGBGEECDCDCDCHCDEAEACCBEGAGEBFBFBFCCGFBEBCCDEDFDHHGAGAGEEFFFFFBGHGHBDECEBAFAFDFDGGGAHBEFGFGFHDGDEFGCABFBFGG,False +326,10.0,8.0,13.0,7.0,11.0,10.0,9.0,12.0,HGFCFAFCFAGADEDBHFCFCHHAHACEBECCCCEGEFEFGDBFBHBGBCEEABCECAADDEDHDHBGEGAHCHFHGAGH,False +327,13.0,9.0,7.0,7.0,11.0,9.0,9.0,4.0,EFEGEFABAFHDBFAFGGEBEFECCCEFFDADBDGEGAGABABABFBDDAEAHAHGHEAAGDECCCGCB,False +328,11.0,7.0,14.0,13.0,15.0,16.0,11.0,12.0,HHHHFDGEGFHFHGDGCCHFBFEDBAHGFCDCGGDDACACEDBGEDEHHGHEFEFCFGFAAACADHFAFCFCFCBDBAEEEEGDFBFAEAEDEDEBCCC,False +329,14.0,9.0,16.0,7.0,13.0,4.0,16.0,18.0,GCAEFCFCACAEDGGEGBGBGBHBHAHECAAAAHAHECECHGHADDCBCFCHHGAGEGDGEAECGBHDACECBHDCDGHCHGEBHBHEHCFGEGHHA,False +330,6.0,12.0,18.0,17.0,8.0,10.0,10.0,6.0,GGFCECDCDCAABEBEHEFDDADGDBDHGFBFBEDHDFBHGGCBCBCDCBCHDGCBCBEDCDGDBECADACCCFEFGFGFHDADFCC,False +331,11.0,25.0,21.0,16.0,17.0,27.0,21.0,23.0,FFFCHCBCGHHHGGCEBEDFCHAEFCFHDBDBABFBFEFBFHDHFBGCACHHFBFDFGFBHHDBEFAFAFHFEEEGEGEGEDBHCDCACHHGFGFHHBDBDBHCHGEDBDECECECFGBDBCEGGGGCCBCAAADAHBBBGBGFGHDAEFGFBBGHDCFCF,False +332,31.0,34.0,15.0,23.0,18.0,19.0,14.0,23.0,HBFBAAACBDEABCHDHAHDFEFHAAACDEBHBHBHBCBHBHBGCAFGBGBFFDFGAEAEBDFFADADACADDDHAHAEEBFDFGCCCFCAEGBCBAHCGEEEEEEBFDFEHBBBABAHADBDEDFGHHBHBDDABBHBHDHFCFCGEBAAAEGFDFDGDBBBAGAGABAGHBHCAD,False +333,20.0,17.0,9.0,14.0,13.0,13.0,13.0,14.0,ABGCECACBHDHGEEHEHBDAAAFDEDGDFAFABCCGHBABEBEGADADFDEHEHEGBGAHADDHHGHGCGFFABAFDBDHABEFDCDFFAFBEBHBAFAFABABGCECHGBG,False +334,7.0,5.0,2.0,4.0,6.0,6.0,4.0,9.0,GCGBFBHAHEBEAEDCGEAEHHFHAHABFGFHFHDEDADAFHB,False +335,17.0,13.0,10.0,10.0,9.0,12.0,9.0,20.0,AGHHAHAHCBABFGADADEFEFEDBBBBHHGHDHBCECEHFHFHBHAHDEAEAEBEHACAGADHCHBGGFFFHACBDFDAGHCDGDCFCACFHFBBHGAA,False +336,10.0,13.0,6.0,5.0,11.0,4.0,11.0,9.0,EGEBEBEGEBAHEFBCBEHGDFHFAFCBHBGDABHGGGBGCGBABADHDCEABABADAEEGAGCHCHEH,False +337,17.0,16.0,15.0,8.0,14.0,17.0,17.0,24.0,HBGBABHBHDFFAHAHAGAEAEAFACGCBCECFGDGCCEFEFHHHABGFCHDHGBCBHBDGDHEHGHCFCHGHDHFHFBFDABHBGBAFHEEGEGECBAGEHBHCHEFEADCBFGHCEFGCGFAAAAF,False +338,18.0,20.0,22.0,16.0,18.0,27.0,14.0,22.0,AEAEAEAFHDHAAEFBDHGFGFCAAAGADFFEFBADCHCHEGBBEBGFGFGEHEDCFHAEBHCDCBCGAECGCHCHBFBEBHHHGCBHFDDGHHHCHBDEDECBDFEFBFGFCFBFBCBFBFCDEAFDGABADADBFFFFECECADHHHCHCFCFCG,False +339,24.0,25.0,25.0,23.0,21.0,21.0,28.0,25.0,ABAFDFCFCGHGCDBDGEGEGCAAEBHBHGHGHDADCGCHFECEBDHDABHGCGHDHEEEBFBFBDDCDGEEEHBFFCFBFAFAFGCCCHGGFGCACHEDEHGDDBHEHDACAFHEABGCACABDBEBFDGHGHFHEAEAEADACGGBBBCGCGDGBGBFCHAHAHFBABFCEHBADGDEBACGCGFAFDHD,False +340,14.0,19.0,9.0,8.0,9.0,16.0,11.0,11.0,CAADABAEACBCBGAADHBFFFBDBDEGABHHHAEFHBCFHBEBGFDFBFBDBDBDAEGEGEFCGBFBAEGBGFGFHFHFGFCBCAAGAFEHHHCBC,False +341,2.0,6.0,2.0,4.0,1.0,4.0,1.0,1.0,ECBDBFAFDFDBGBHBCBAFD,True +342,10.0,9.0,6.0,7.0,9.0,12.0,7.0,13.0,AEAHAHFEGEGBGAEBBHFDBGBHHGHAFAFAFHFDDCDHECFCACFHFHCDCDHBEBFAFGFABEEEGBDHH,False +343,12.0,23.0,13.0,17.0,19.0,18.0,25.0,20.0,GCGCGCFABHCGAFCFDFBHBHEECDDBEHEAEABABAHHFFDFGEBEBGCABAGGEGEDEDHBCFDHDGBGDGHAEAGDHAEEECHHFBDGCFCDBDHFHBBBDHHCBEHFHGGGFGFBEBEFEFCFGFGHGDGDBHBGBABDGEG,False +344,8.0,19.0,17.0,14.0,18.0,17.0,16.0,26.0,BFBHCHCACDDFCHEHAFAFEEEDHGHBEEFADGGFGEEDEDEFEFBFBHHGHGHDEFCGCGHDHDBCHDBCFCGEBHBHEHFDEAEBEGCGBHBFBHBCBCBCBGACCHHHGHFDFCFHGDGHEHDCBAAFHBG,False +345,14.0,25.0,9.0,16.0,24.0,29.0,24.0,20.0,BDBDFDFEGEDADGGGGDFAABHGFGFEBHFECHCEDBABFBEDGGCFCEAAHGHFBBHHHHHHEBEBFAEEBEDGDCHEFBFBFBHEGEGEAEBGGCAFFGDGAGAGHFFFFFGCHAHBHDEDEFHBBBFDFHFBFBFBHDEFGBEDEGEGBAFFCACEG,False +346,20.0,21.0,26.0,20.0,28.0,15.0,21.0,20.0,EDEDFHFHEDCCECEHEHCGBBAEFDDHBGBEBGAEHECGCACECGCGCDEHCAFAECHBBDGDFCFBBHBEBEHDGDBDCAGACAHAHDHCEBEHEACDDDFFAGAFAFCGEACACGEEAHAGAGAGEFEFHFBGCHBDBHBCGDGCECHDHFBFDCGCBBEBDAEGEGE,False +347,9.0,10.0,7.0,7.0,9.0,11.0,7.0,1.0,DAFCBCBAFDEGEGEFAADGEGEAEAFGFBFEFCFGFCFHEDCBGBEBAFDDABCBABDBC,False +348,23.0,21.0,22.0,23.0,12.0,21.0,19.0,12.0,DBGBGFCCGCDHGFGFGFDCDEAEAFBFBHGHBCBABAFFFBBAFHFCDBFECCDCACAEADFDEDGCFCHBBBBDFDCGAHFGEADDGHFFDADEGEAEFEDECACACAFADCFCAGBBABEDGDHCGCACACHBDGGAGBGBHAHADDDHB,False +349,24.0,18.0,28.0,33.0,14.0,23.0,32.0,22.0,DBDACACDEGGCFCBGBHFGDGDEDHHADCFBFDFDAAFAGDGCFCECEGDGFBAGHDDCDCDGHCFFAFGDGDHDHFGGBGHDCDCAHFEDBFBFCDDEDGHAHADABHBEAAACADGBGAGAFHCCGFGCGDGAEAGDGHFHFEBAHCFCFGGGEGEGAGHBBBDCCHCHFHCHDFDBDCDEHECBCEAABC,False +350,8.0,4.0,6.0,7.0,7.0,4.0,16.0,7.0,EDGFGACAGBHBEBAGACAGEEEEEGGAGCGCDAFHGDCDHGHCHGBGAFDFDGGGDHH,False +351,14.0,22.0,13.0,15.0,4.0,11.0,14.0,13.0,ABCCHHFHCDBDBDBCCGCGFFDFBFGGBAHADDGDCDCBAHABEFHBBDBDBDBEBEBGDAEABDGFHBHGAGCBFHHHHHACGBGACFBBDGDBFAGAGACACF,False +352,23.0,10.0,18.0,19.0,18.0,25.0,14.0,15.0,GFADHDHFCGCBFFFHHEDFDHAEEFECAGBGEAHAHADAEGCBFBFEGEFHHEGGCFCHHAHAHEBAADAGBEBEDEDGFEFAFADADFGFAFCECECFFAFACACHCDFDADCDGGFDHCCCCDGDAFBFBEADBDAECF,False +353,28.0,26.0,15.0,29.0,24.0,17.0,31.0,29.0,EFGDADGCGBGBGBEAEHGHFDDEDEDEGHGEGEGHGHEHGDGBGFEAEGDCHCHDHFHEHAGDHDFEBEBEBEDCDCACAFGFCABFEGBGAGHHBDBABABHHAHAECEAGBGBHBFEDHCFCDGAFDHBEACFHHGDADHCFCBAAHFFGFDADBBEBHACABAHGDGBEAFABDBGGGGDDDAAHDDDHCHAABE,False +354,2.0,5.0,6.0,7.0,4.0,6.0,4.0,6.0,BHGHAECCCFADBDHDEDBFBHDCDCDFGCGFGFHHEFEB,False +355,6.0,5.0,6.0,6.0,6.0,7.0,2.0,4.0,HFHCGCGBFEAAAHAFBCBDEDEDEDCDFFABBCFCADFEHE,False +356,6.0,7.0,14.0,10.0,18.0,19.0,15.0,16.0,FBEHFGEHFDCDGGGEHCDCDFFFHBABDFDFHCCFEFECEHEFCAAGFGBCBFGFEBCACACDFFGHGBEHEHEHFHCCEGEGEGECAHEDEDGDGEHHHGHFF,False +357,14.0,24.0,11.0,19.0,13.0,13.0,20.0,12.0,CAHGEBBDBFBEGHAEDBDHDGDGECACACEFBDBFFGADBHBCCDCDHDEGEAFAFEGBFBABHFHAEDEDGHGBEBGBGBGFFBCGEGDAFAFAHAEBCGDDAGHHBCBDBDBFBDBDCGGGGH,False +358,14.0,23.0,16.0,16.0,14.0,16.0,6.0,16.0,HBCBHFHFHDBAGAEDCCCBFDFHFHDHDHGHABCFCFAGEGBBBFDADADBEBHFCFDFCBADDBCBCBCAEGEFCBABAFAHBFBEBEBCCEEHEDECBFAEHGADHDHEHBDEFBCDA,False +359,13.0,21.0,20.0,21.0,14.0,16.0,20.0,15.0,GFDBDCACAEBEBEBHBCBCECEGACHCHAHAGGBADADBDFCFHGDGDGEBHBDGGFGFGDBDAGABDGDGEHFDAEFFGFDHEBCCDCHCFCECHGDBCEHEFDFDABEBGDGHACFFBDCEAFGDBCGCBCFHBHBH,False +360,2.0,2.0,1.0,1.0,3.0,6.0,2.0,3.0,GFFFEFEBDBEHGCAHAHFF,True +361,14.0,17.0,14.0,17.0,23.0,22.0,11.0,18.0,DHACABDDDFEFBCAEAEAEFCFEFCFDFHFAFBCBCHGHFHEAEGBHBGCFCHAEBEFECECGFEDEFCCHAFAFAFADGHGBGDHDEDAHBHBHGEEBDHDBEEHGDEDEFBFBFHFGFBDAEBDGCHEEDCHB,False +362,7.0,7.0,14.0,4.0,6.0,6.0,6.0,3.0,CCBCGEGCAFAEADAGFGFCFCBCGHBBDBCGEAHAFCDCACBCHCEEFECBD,False +363,10.0,8.0,17.0,16.0,17.0,20.0,8.0,12.0,FEADABEGEHEBEBECFCDCHBHCAEEGHCFGFGFHHEFEFDFGFDECCACHFFFCDCGADAFGDCDCDCEFFFFAHAHBEECCDADAFFBEDEDEDHCFCDBHGHDB,False +364,8.0,4.0,4.0,12.0,13.0,9.0,10.0,11.0,FFHEHDFFAGEGEHEHFGDDDEDECEDABHFGFGDGAFADAEECGGABDBGHHCDCBGFDHDHAEAEHEHE,False +365,6.0,2.0,5.0,1.0,4.0,5.0,1.0,5.0,FEACAGFEFHCEABABAHFFEHAHCHCDC,True +366,11.0,5.0,9.0,15.0,4.0,9.0,12.0,5.0,CCFDEDFDFEFEHDBDCDHGGGGDFDAACADABFGCBCAGAFDFCGCGAHAGAHDBDHCGEBFDADADGG,True +367,22.0,11.0,14.0,10.0,20.0,19.0,35.0,19.0,DGGGBCECGDADABABHEHBHGAGHGFAFAGBGBGEEACACFEFGGGEFHCDEEBEBAHCEFFFFHAHAHGFECBHGGEGEHAHFGBDFHEEGCGFDAAAGEGAGFEFHFGAGAGDHAACAGHGCGAGDGBFHFGCGCECEHFHDGEGCD,False +368,2.0,3.0,4.0,0.0,3.0,2.0,2.0,2.0,BCECECHFHFAGEGBBCA,False +369,2.0,7.0,10.0,3.0,12.0,8.0,6.0,9.0,HHDHDCCEGEFFFHCBBHDEGEHEFEFEFEFBCBEBHBCCGCHEHBGGACECEFGAC,True +370,17.0,20.0,13.0,14.0,12.0,20.0,18.0,16.0,HEFEBECCHDECGCEBBGCDBDBDGFGFAFHGDDFDHBBBFAGDFAGACEFHGBFDFHFHFHCGBEDHFCFCFGAAEDECEFBFAHABACAGAGACAHABFBFGEGDBFBHBHDHDGBABAGCGEBAHGH,False +371,14.0,16.0,16.0,7.0,13.0,5.0,11.0,14.0,GBGBEHFHFBBBECAABDEABAGAEDEDBCEGECCACAGACACBCHCECEGABDBEBHBHFHCDAEADHCHCHFHCEABBCDHEGFGCHBGGHGHA,False +372,9.0,15.0,11.0,10.0,12.0,17.0,13.0,14.0,BEBEBGFFBFGFDFGCGCGFHDGGCFAFAFBFDHDEAEHEHAFBFEGHHEBGAGCHHHDDCECGCABFBFHFEDEDHBBCBGBCAGACAHBECEDDHBHFF,False +373,14.0,9.0,8.0,14.0,6.0,19.0,18.0,14.0,BHEFAHAHDDDDFBFDFGFEFHGBBFAAAGADHGBFCDGBEFGFCHHGFGHGHFHGEGAGEEAGDDABGGCCCBHBHCHDFAFAFAFGFDFDADADCGCGHF,False +374,13.0,6.0,13.0,5.0,8.0,10.0,12.0,6.0,CBGADAHAHAFAFGCGFGCDEAEADADCBHDFAACCCAFHBBCEGEGECFHAEBEHCGFGFGEGCGCFCGABF,False +375,8.0,5.0,6.0,3.0,11.0,9.0,8.0,4.0,EEEEHFFBFGGCGHGEBABEEFCFCBHGDBHFAFAFDFGAGDGAECECECAAAE,False +376,6.0,8.0,6.0,9.0,8.0,5.0,12.0,5.0,AEGEBACACHCGGHDBDBCEGEBEBHFDDGDCDBDBEGCAFBFGGGEHEAADFDFHGGG,False +377,2.0,3.0,2.0,5.0,6.0,4.0,2.0,2.0,EDEDECEBHBGFGAEADFHBDFEFDC,True +378,18.0,11.0,12.0,20.0,13.0,19.0,14.0,21.0,GAEHGHAADADADBFCECDCFCGDDFCGHAADFFFGHBHFDCDBFHFHGHFAGAGABADDHAEDECFFFAFAFDEDEBABFBGGHBCBAACBHHHFFEDEDADBEHFHGCGEEDHDCDGHGHEHEHCH,False +379,15.0,10.0,10.0,14.0,7.0,13.0,13.0,11.0,FHGHGHBBCDDDDABABGCEDADCHGAAHAFCFBDBDADFCFDDHCHFHAHCHCBCGGAACAHGGGGAGBEDFDFEAGDGFEBEFFAFAEBEF,False +380,20.0,20.0,27.0,28.0,18.0,28.0,19.0,15.0,FAEAEHHHHHHECBHFFFCFCDAGFGDEDCDCBGFFCGBGEGBAEAGFCADGGBEBEFHFDCBAEFDFDEDAHAHGEDAGBGFEBEGFDDDFDFAFCCCCCCBCBCGCGCACDDBFAFBCDADCDEDBCBCGHGFGBBAFDCDHBHDDBDCECACDFDGABFEDEAEFHHAAFFF,False +381,9.0,4.0,8.0,8.0,10.0,3.0,5.0,2.0,DEDECFCECEDAAACHEGDDFDFCACECGAABDGCHBEBGDGBAEAEAE,True +382,28.0,23.0,23.0,25.0,22.0,19.0,22.0,24.0,EBAHHEDEDBDHHGADFEFEHDHDGFFDFDADHDGEACBEHEFGDGAGAGEBCDCBBAFECHGGBHCHCGGGCGAFCHCHBBEBFBFHFCGCGEDEAAADABABADFEFDCDCECDCHCHCBAAAAAAHAFEGEADCCFHFEBEBFHDHFAAAGCBBBCDHDEDFBEGHCBDBGHGCGHDEAGABA,False +383,4.0,5.0,2.0,2.0,4.0,7.0,4.0,2.0,FAFBFGCGAGAGFBDEFEFHABFBDCHEBE,False +384,23.0,10.0,11.0,21.0,17.0,14.0,20.0,15.0,CBEFFDDBFAGHDAGAGAGDDBEGCCCDCBHHEAEFGFEEEHEACACAGAGBDAAHFHFAFADEHCACGDAEEFGGHEHBCDAGAEDEBFGHDHEHDHFHAGAGAGAFAFABBCDGGGDBDGDEDEDFDHD,False +385,16.0,15.0,15.0,12.0,17.0,20.0,20.0,23.0,FGBHBHAHAHBDFEFEBCAEEDEAHBHBHEFDCBAFCFAFAGHGHGACDHBCAEHGHBABFCFDGDFDFHFDBGFGHHACADACHCGBEBEHEACGEGFGFGDGEGEGECEADACBGFHHDFFHFHFGGBHCGCEEHC,False +386,22.0,28.0,19.0,25.0,19.0,24.0,12.0,27.0,BHDGBHDFDFDBABGDHAFAECECBCBCFCBEBHHHEEEBAFDFAFADECBDFDFAEHBHEHEGEADHHHFHFHDBFHAHADADFDFCAHBCGCDCBBBGBFAFCFHAGADDBFEFEAAHCDCECBDFFHFHBHBFEDCACAGEFDHGBEHGBCBHEEGAGHBDBDGHADADCBCB,False +387,16.0,23.0,23.0,12.0,27.0,6.0,20.0,14.0,EDEBGBEBCGGHCACBHBEGAGHGCGEGFCHBDCHGHBHGDADADBBCHCBEBACGEGEGEBABABDEEHECCCCBBBGAGAEAGFGHACCBBABAGFBEEEEEECGDDCDHEEEAEAECDCECGCFHFCBCEADDHEBFH,False +388,29.0,22.0,29.0,26.0,26.0,22.0,19.0,18.0,CECEGHFBFDDCDHGAFBGDFAAHACACAEEBEACFCAEECCGCGCFFFABGBGDCDGDEAEABHBHBFBHAHDCECECHFEFBACDDDEHAGABADFDFDBDBDECECEDHDAAAAEBEGAAADGFBFADACHEAACFGFGCGEHFHFCCCDGGBCEGFAFEBHCDAGBCBCDCEEGDBDBDHFHEBEHH,False +389,6.0,5.0,9.0,6.0,6.0,10.0,3.0,6.0,AFFFACCCEHHHHACDFDEGCBCDEDCFBFBDBFHFHADGCGCEFAFAEBE,False +390,5.0,5.0,8.0,6.0,3.0,4.0,2.0,9.0,CHCGBFDADACBFDFCHHDHDHCGCBFAEAEAECHCHBBDHH,False +391,17.0,18.0,29.0,20.0,13.0,16.0,17.0,22.0,GDCDGHHBEBFCFHGHAAAHBCDCDHFHEHBDDDDDCDCACHEBDBCBFDACBCBHACCDCGGGGCBCFCFBACADHHCFCADHHHGCBBGDGCGEEHEACAGGFGCABABDBEECECECFAFAGHHDHDFBFGFHECEFDFAHBHFGCACE,False +392,4.0,11.0,10.0,5.0,8.0,5.0,3.0,15.0,HHHHEEDDBGHGFABEBECCBHBCBEDECBCHCBEFEHDBDHAHBHFAGCHCHCBCAHFHF,True +393,5.0,6.0,6.0,2.0,4.0,4.0,5.0,6.0,HGFGHHHAGCGEFEBDFDAAHAFCBCBCECBGBEBHCA,False +394,21.0,28.0,17.0,22.0,17.0,15.0,15.0,14.0,DHAAAAFCDBDBDGGABBBCHCACGHFBBBBBBBAAAAFBBBBBEGEABCGFDHEHEDBAADEDEDEHCFEBEGDHFGGECDCHCHBDCEFEHDBDBDBDCECGCBFDGBADHGGFAFAFACEGEFDFBABFFEGDAACACHEHDHDCG,False +395,17.0,17.0,23.0,13.0,25.0,16.0,32.0,27.0,ACFCFGGGEEHEGGDEHBACACECEFEFHDEDFDGEGBGFHCCACEEFDACHGHGHBEEHBACCCCHCEFDAGAGEGCBHBHBGGGDGCFAHGHGHCAEFBBBHBGBHHEHEBGGEGEFHFHFHGHGCFCGHGDEDAAAGCBBBCHAEAHDHDFGGGEGBAHECDFDCAE,False +396,2.0,4.0,1.0,7.0,6.0,10.0,8.0,9.0,GCGFGFGHBFAEGFHFHGBDHEFEDHDEFEFDFEFBGHHAHGDBDHD,True +397,12.0,14.0,13.0,17.0,13.0,20.0,12.0,15.0,CEBHFCBGHGEGEACAHBHBDBGBADFDHDFDADHHEHFHBAAFACECECEDDGDGDCCCHCGBBDGFBECGDGACFFFFFFDHDHAEFEFBBGBFHFHECAFDBEHDFAFAEGFD,False +398,28.0,19.0,7.0,24.0,27.0,19.0,20.0,15.0,DHEAEADDHGAAHAGEHEBDBDHFCFEFEFEGAGHGBFHECAAGDCDADFCHDADADFDHGBGAEHDGFBFAFAFEFEFEHCAAAGGBBABDBCEADADFEGEFHADEGGGEGEGBGBDADEEBDBDHEEEDADEBBFHEEFCFEFAAAGABABDBHBG,False +399,0.0,3.0,1.0,3.0,3.0,3.0,0.0,4.0,DDHFBFEFDHBHCHEBE,True +400,14.0,15.0,8.0,10.0,12.0,16.0,15.0,13.0,BABABGHFHEHEAEBFGHDBCBGDCFFGAGDGFEFEFEFHDCAGAGHHAHACBCBGAGEGEDBDHDEBCACBHAHCFAFEBEDFFFBFGEGFABHGDADFBHG,False +401,11.0,5.0,16.0,15.0,7.0,18.0,6.0,17.0,EGDHHBGCGFFFFECHDAFAFBFDHGHAACFFFAEHBFDFHEHDFDFDABBEAFCCCCCCCFHAGADDDCCEHEHCHDHAHFHCCCFDHDHDADG,True +402,3.0,10.0,24.0,13.0,15.0,13.0,11.0,19.0,CBBEDHAHBDBDBGCECHHDHGHDCGCGEHCHCGCEEEEHFHFECEGBDDFBHEDBDADGFHCHCGCBCDCEAFGFGHGHCECFDECCCCCDHHEBFHFCFCEHFFCF,False +403,1.0,2.0,2.0,2.0,0.0,1.0,2.0,2.0,DGDABGBCHCHF,False +404,5.0,16.0,6.0,12.0,8.0,5.0,12.0,9.0,DGDHBCBCHGEEHEFGFBAGABADDCDBBBBBGAGEEDCDGHGHFHBHGGCEEDBDBDBCBDBGFAEBHFHGD,True +405,21.0,16.0,12.0,16.0,13.0,10.0,25.0,18.0,GFEFBFGGBGBGBHFHEBEBGBGFGFCEAGCDHAABHBEGCGHDHAHDCEGDGDBFGCAAAAEAGADFDGDAACACECEBFDHBAEACHGHAHDEDEFHHHBGEGACDBAGGBCBHHCDGAGDGHGHADAD,False +406,4.0,4.0,3.0,5.0,1.0,0.0,4.0,3.0,GBDDABCBCGDGDCHBHDHAGAEA,True +407,16.0,7.0,6.0,14.0,13.0,6.0,14.0,8.0,BFCAAAAAEFEBDFCFCADGDBDBDAGAHAEDEGHGHGFDBDGAEHEAEAGCEDHAEADGDAFADGGEGHGHDEBEHDGBGCCE,True +408,12.0,15.0,11.0,21.0,18.0,14.0,12.0,11.0,DBDBDBDBCBGGABCEFEFGGDBDAAAEHEFEBGBECCFCBGEEAEHCBFEFHFCEBFBHGADFDACABEBEAECDCGFDDDDDDHGEGFDHDHDHFCDDEDGAAFAFHHGHEE,False +409,20.0,21.0,28.0,22.0,20.0,26.0,20.0,22.0,FCFDFHADGDHDHBBCCHHDHDHDGAABAGCGCDCDFFFAEAFBHHGHCHEFEGBDCDAAHABBCFHFEEGEFFFCHCDBDEDEFEDAFAFABEHCCCEBHBDGDECCAAACDGFFEDHDFBHBAGAEAEFECGGGCHCDAHBGBDBCBEHGFCFCFCFCEGEGHFCBGFGCGCEABBB,False +410,3.0,1.0,3.0,3.0,0.0,0.0,1.0,2.0,DGACBHDHDCACA,True +411,10.0,24.0,18.0,15.0,16.0,10.0,24.0,18.0,HHFBFECHGHAHFGGDCBCBCEGHGBBAAGCCHCBDBGBDHHHBFBDBGGCGHGABABACEHEHCDGDECBAAEFGGDGEADDDHDHBEBEGEFEGEGCGDGDEDBCCCHCEBEDCGFGHGEGFBFBACHBBBBF,False +412,7.0,7.0,14.0,10.0,10.0,6.0,9.0,5.0,GEDFDFBAGCDABADDGAHEDEDFDCDCDFHCBCBCGCHBGCFCAEEEEEGEGCCCHHGCBEBCAGAF,False +413,1.0,1.0,2.0,0.0,2.0,2.0,3.0,2.0,FGCGCHEHEABGF,True +414,3.0,7.0,4.0,3.0,7.0,6.0,6.0,8.0,HCHGEEBABABFBEGFGAGBDFDEHEFCFBHHHFHCHCBEEGGD,False +415,17.0,22.0,23.0,22.0,24.0,17.0,20.0,16.0,BCBGBADDEHEBECCCCDGAGEGEAACEHEHGFABAEHECECFCGCECDBACAHADECGCBBFGFEHEFGDGEGCGFGDHDCBCAFGDGDAEFHFCFBEEHEBDDFHHHBAFAHDEDGDBDEDECFCFHFAGCFFAEGDGDADCBBBBCGHHABBBBBDED,False +416,23.0,23.0,29.0,23.0,28.0,15.0,36.0,18.0,HDFEEHAHFECBCGDFDFBAGABBGGADFDGEGECECGDHCECECEDEDACACGEGCGFBCBCACEEDEGGABHEDCHBGGGHGCGCBDBCCCEHEBGBCDDGGHGEFEGBBBDBAFAFAGBFFHHADEGEDBCCCACGCDCGEAHAEADGGGDGDBFBFCGCGBGBGACAHAHGEFDADEHEHAFGHBHDEAEA,False +417,6.0,3.0,6.0,6.0,13.0,9.0,7.0,12.0,HGCCECEAEHGHGCFAFHDDBDEGBGHHEEDAFGFHEHAAADBCHCGFEEEHEHEFEFDFHF,False +418,7.0,7.0,9.0,13.0,10.0,16.0,6.0,11.0,HEFFFEDECCHHBHFDFACACEDHDBDBDBDFCFDEDEBHGEFFAFADAFHGBGCGCFDEAHDFDHGHFHCGEFEFABC,False +419,6.0,2.0,4.0,3.0,3.0,0.0,2.0,0.0,EEBDBAAAACACEGGCCDAD,True +420,20.0,21.0,13.0,17.0,21.0,27.0,25.0,13.0,HAGAGAECCFDBEADDGAGFFDCBFFCABGBEBAGCGBFBGEGEFDCDEBFBEDCAHBHBDFDFBADGFFEGEGEFEFEFHFBBABAHHDGDGBGAGFGFGEEDEDAFAGDHEACACFFGFGFGEDECBFBFHHHGEAFAEAHFBEBGBCHCHGADC,False +421,9.0,14.0,14.0,8.0,6.0,14.0,12.0,12.0,FHFDFDBBBGBEBCBFDGDHFGABCGABBGEAFAHACACHDDFHCBBFHFHFGCHCHGBBHHGCGCACACHCEFEFADDFEFEGGCGCB,False +422,2.0,4.0,4.0,2.0,2.0,3.0,4.0,6.0,HFCFCECBGGGDGBEHFBAHAHBHDHC,False +423,19.0,10.0,8.0,8.0,6.0,9.0,8.0,8.0,DEABABCFEFDAAABFHFAFAFADACCGBABAGHBABABAGHEHCGDGDCDCGEHEGDAABAEHBAGACDFFCFHH,False +424,22.0,16.0,21.0,30.0,13.0,19.0,17.0,12.0,BCBEBDAEAEAHAHGHCBCAAEADGFGDGDCACFCDEGCDHBCADDDDDEABADADADAEGBGBHCGFAFDCDBDFACDBDBCFEHEHAHGFGFGFGECHFHCCGDGACDFDECFDADEBHFFDFDFBFBEHAGCGDFCBGDACBCFDAD,False +425,12.0,15.0,7.0,11.0,10.0,19.0,9.0,9.0,CADACAFHFDDCDBFBDBEBEDEHFABACFFHHGFDFDGDGHAHACCBEFDFGEGEADFFCEGBABAEHHBHBGBEBABGBEFFFFABGFFF,False +426,10.0,14.0,11.0,11.0,11.0,17.0,18.0,9.0,BFBAAEFEHCHGAFEBCFCGCGBGFHFCGGAFAFBFCFHBBFEFEFEBGCECBGBGCDFDBDBDGAGEFEGHGHAADEGCGHDBAEGDDDDCDFGFGABHH,False +427,37.0,20.0,35.0,16.0,24.0,26.0,23.0,17.0,AGAEEHGHGCCCGBGCHCHCHFGGAAAEAEAFHCHCGCACADEEECBABEFEHDFBFEEBBBCEFAFADACAFFCFDHDGBFFACDGDFDBBBCGCBAAAEAECGCDHFBDBCAAGACACAFAGGBEHECECEABFEGDFDHHAAAACHCHGHCHABEGCGFACCECFFBFBABAGFFDAECEDEFFACGCGAGCDFD,False +428,16.0,17.0,31.0,28.0,15.0,17.0,26.0,26.0,FGFCCACBEDEDBCGCGFDCAAECEAAFFGGGGHCHCAGDGDBHBHFHFHFHDHAGGDDADHDHBACGCGEDHBCDFDGDHDCCCBBBBGCCCCFBDDDBCCCHCFEHHGFBFCCAAGGDADGDHEHAGCGCBDBFBFEGAGEGHCFDHHHHEHEBEHDFDGDHAAECCCEDEDGH,False +429,8.0,4.0,6.0,7.0,12.0,5.0,7.0,6.0,AAHAGBFHFCEAEBECGFGFGEEECBCDCAEHEAEDEDHGHBCFDGEGDHDEDAA,False +430,5.0,7.0,8.0,4.0,4.0,3.0,11.0,4.0,HGDCHCBCBFGAGBGBEDHAEAEGFGCGEGAFCGCGDHDBBBCCGA,True +431,8.0,19.0,9.0,16.0,16.0,15.0,11.0,12.0,FABCEHHCGDGDFDFHFAEDGDFDFBBBBFEDEAGBEEEFEGEBEFDDGBBAAAFHFHEEDCDCGEDBDAEHEHBHBHBFGCDCHEDBFBGHGFBFBCBCGCBAHD,False +432,25.0,23.0,17.0,34.0,27.0,19.0,18.0,34.0,GBHHHFEGGFGFGHBABDBDBHGGEBBDEDHHHHAHFHEHFFFGBDDEAAAAADCDHACAFDBDCGCGDDDHAGBDHGHCHABAFEFEFEFDDBDBABGFAFEEDEDEAEBFDFDHAHABEBEDDDFHCEFEAAAECCBABHDADHCBFGDHEHAGBDHHEHEDEAECEDGCEEHDDGHCHCHEDDHBHCHCACBCG,False +433,11.0,10.0,8.0,8.0,5.0,5.0,7.0,5.0,GEEEBADHCHEBEACABDBDAHABABABCDCGCDABFDCACABGGAGHCHFFDDGFGFB,False +434,8.0,2.0,9.0,3.0,9.0,11.0,9.0,7.0,CECFFFHGHBHCFCFBFHDACEEFCGEDEDAAAGCGCEFFAAGGGHFHFHEGEGECAA,False +435,15.0,9.0,12.0,17.0,12.0,13.0,11.0,8.0,FEFHFAFEDEDBCGGFBHACGCFCHADADAFAEAEADHDBDFHEDEDBBGBDADAGAGEGECCHEAACBCDCEGFGFDADGHHFDFCCCBDGEFADB,False +436,9.0,4.0,4.0,2.0,2.0,7.0,7.0,7.0,HEFBABCEFAFABGGAAACFCFGHBHACGFGAGAGHHDHDHF,True +437,13.0,14.0,15.0,27.0,27.0,6.0,29.0,26.0,DDDEHABAHEHAHDCBGDHFCEGBBHBHADDEAGGEGDGDGCCDCDBDBHBHBAAHGGGGACECEGGGECCDGDGEGADADGFHEEDEGACAGHDDDFDFBEHCHGHFHEEEHEHEHEHEGEFDGDGHBCCEDHBCGDHEEBAGHGEGEGEDHBHCD,True +438,22.0,9.0,13.0,21.0,26.0,17.0,18.0,21.0,GAGEHFHCEGEDAFAHAHEDBDFDABAHEDGDBCAEGDDDGGGGAGEHHHGCCFHHBHBHBHAGECAGDGDGDGEHDFAGCEEFEHEAEAEFFCECFFFBDADFDADADAFEEEEAFAEEBABAHEFDGHEHFCDCDCECHCHFEAH,False +439,24.0,19.0,22.0,19.0,24.0,22.0,19.0,24.0,DCDCAAAAABAFGFDFDHGCGCGBDACCCCEHFACHEDAAEABAHABAEFHFCFCFBBHFHEHEGCGDHFECBBBGBEHEAEAHDGDGHCHFBFEFEBEDFAACDHDFBHADCCEHEHDBFGFHDHDGEGADADEDEBECHFGGAGEFCCBCGFBBAGEHFHGHEHEFECBGA,False +440,23.0,14.0,11.0,16.0,9.0,11.0,13.0,16.0,DCDGBGBAAHECEFGFGAGHHEDGBCFDFGHGEEFADAEGFBAAAABFBFDAACCCEDHHHDDAAEBHCHABCHAHAHABEDGFGBGDDDDDDGAAHACACACABFFHBHBHB,False +441,5.0,9.0,7.0,7.0,5.0,6.0,6.0,2.0,CFDBDGCADBDBDGAAEAEBFBCBFGHBEGDHDECECBCGFGFBFAC,False +442,21.0,17.0,17.0,31.0,26.0,21.0,12.0,20.0,AAAGDEAFCHCBEDDBDBDHCAAHBDBDADHFHFHFHFHFDFEADADHHCHDDCFBFACHDEEEDABADAFEFHCACFFFEFBBEHGDGEGFDDCDGEGECCCCCFCHDEEECGCFDEDGBBDBGGHBFAFEDADFDHEHDHAGDGDBAEEEBEDAHAEBEBEAE,False +443,22.0,20.0,27.0,22.0,26.0,31.0,22.0,17.0,EDEAHFDFEBGFEFHGAFAFEDEAHDFBEDACCCBCBAFADAHFCGHGHDCDCGGHBBGACADFEFEFBFBFBHBHAHAGGGEGAGACECECBAEFFDEECDFECECBCEHDFCABHBCGDHBFBFBFAEDCFFHFCFGFDEDEDGFGFGFBCHEGGCEDGCCHDGFGCCCACEDEAEABABADFDH,False +444,25.0,15.0,17.0,18.0,21.0,13.0,21.0,25.0,GCAFBBBBAFGHBACAFHCECHBEDEHHHEDAHABCGDEAAABDBHAHBEGGDGACDBGGGGHGHGCECEFHFCCGBEEEEEDFCGDGDADADCECBFFCAEAEADGDHAHAHEHDHAHEFEHDGFHFHBDDAHAGAGAGAGEFBHECFCACHDH,False +445,4.0,5.0,1.0,1.0,6.0,3.0,0.0,1.0,FEBBABEBEAFHFEAEAEBDC,True +446,3.0,5.0,3.0,4.0,0.0,2.0,5.0,1.0,DBDAGBGCGCGCBBBAGFDHDFA,True +447,27.0,17.0,19.0,29.0,21.0,26.0,19.0,16.0,AAEEEEFDFHEADAGFGFGAGHFABBBBDADAHFDGCHFDFAFGCCBFFHDHDADEBHGCAHAFCCGCHEEADCBFFDFAFACAEECDCDBHBDCCEDEAGABDBDGGGGHFHFHDEAFDCDAAABAGCGFDFEEEBGAGAHBGDGDFDFDHHACCDCEBEAECEFEFDFDBDB,False +448,12.0,3.0,7.0,7.0,6.0,6.0,10.0,15.0,GCACACAFHFHGHDHAHDDEDCFAHACAHGEFHBHBFGDEHEAAAGAGCDAEGEBHDGFGHHCHGH,False +449,27.0,20.0,31.0,20.0,16.0,31.0,25.0,16.0,CCFCACAHBDGCGCBCGCDCBBEBAGFFFCFCDCBHBEFDFDHGGDCFEDBDFDCDCFFDBAECHADBCHCHCAAAAFAFADDGFCECGCGDDEHGHFFEHGHGFGFGAEFBFEFDBHAFDGGCFAFHHHBHEAGAEAEABGHFAFACACBCACGBBAGACAFFGFGFDBCBCGEEEECFADGBGA,False +450,2.0,7.0,4.0,2.0,6.0,1.0,3.0,3.0,DGCGCBDBHCECHBEGEABFBHEAEBEB,True +451,8.0,7.0,6.0,1.0,2.0,4.0,4.0,3.0,FGFHEABCCCDBABAHCHEAGCGCBAAAABBBFGF,True +452,12.0,16.0,17.0,11.0,29.0,15.0,19.0,16.0,EGDGEGHCFCFDDBECFHFHGEBEBEBEBDBAHAHADCEEEEEEEBECCBBBGDCDCFGHHEACAGBGHFEGEAECFDEGFHCEDFDFDCBHEAEAEFBGCGBAHFHGGEEBFGFGEHAGAGAFCBHHHCCECEG,False +453,4.0,3.0,6.0,2.0,6.0,8.0,4.0,3.0,CCFCEEHCHBDEFAFAFHGDFEGEFBFBFCECGAGA,False +454,17.0,13.0,25.0,22.0,19.0,16.0,28.0,27.0,AGAHHCDEDGGGDHHFEEGEHHCGGHGABCDCDAAFCFCGAGCFFFHEEEHEBGBCFHDAEEBDCDCGCGCBHBFCFHDHGBGDHCHFHBHDHBEAFCCDEDAGCGCDCFFHGHGHGAGADACAEABFCECECEBEHAGAHHDGDGHGHGFDFDEBCHDDCDGBGEA,False +455,3.0,8.0,5.0,6.0,3.0,3.0,1.0,4.0,ADHHHDFFACBCBCHCBDDGDBDBEBEAEFCBB,True +456,17.0,25.0,25.0,21.0,21.0,26.0,24.0,21.0,GEGBFBFBFBGAHAFACDEDCCHFFGBGAACFCHGFCFGHDAEFEFGFGHEBEBDAFGFAFCCBABEHCGFEDEDGBGBFBEHEGGCDCDCBGHDCCCDFAGBHBDEDHCHCHEHCBCDDDDFBEEEEGGBFCFCHAHACGFBBHDHBABGBGDGDFAFAECECEFDFDBGCHBAAHHEH,False +457,12.0,10.0,8.0,8.0,4.0,11.0,8.0,8.0,DBDFDFCCCHBEGFBHEFACBDBGHGBFAFGHAHAHGDDDCCACGCEHGFGFBFBABABDHFAAAEAFA,False +458,20.0,11.0,18.0,22.0,26.0,28.0,20.0,28.0,BFGHCHEAEAFFFFGABCFGFECECECECHCHGHDHAHEEEFHAAFBCGHDHDHCABGHCFDGHGACFDDDBCGDDFGGGGEEABGFAFEHAFEHAFAEAEABAGFDFEEHEFECDADHDHBHEHDHCHFHDHFHGDDDDEDEFEFGDCHCECEFHFAGBFFEFCADGBGBHA,False +459,18.0,25.0,19.0,16.0,13.0,17.0,21.0,14.0,CACACDEDBCBHAAGHBHBCEDEDAGGHDFDEDCHFHECFBFACAHAGGGGGAGDFBABFFGFBHBHBGBHBACABHBGCGBGEFADCDCHAHDHDBACABBBGEGEFCFBGBEFDFABABFCEGECDCBCGDBEGFFCFDGE,False +460,21.0,19.0,19.0,30.0,29.0,19.0,23.0,32.0,FDEDECCDEEHFDFEFEFHAHDCGCGCFDDDCGAGAECDHBEBAHGCGEFEDHDHDGDBHBADCDCHHFECHBGBEHADBDHGHGHGHDHFBGAGHBFBAECGGFEFEFDGDCDAEGEBACHGGDDADFHAEABBGBABDFDFABEDAHBHAHAEDEAEHEHCFCHEHEHBHBHGGCACAHEEEEFDFCGDH,False +461,9.0,19.0,19.0,25.0,19.0,17.0,20.0,16.0,BEGCGDAEHEDBDCEHECACAEAEAFCEGHGHFHGHCEDDDHDEGGFEHEFDFGFDBDBDGDEDCFCFHECBDHACCBCBFGDGCHBHDDBGBGFCBCDDGDACFGGGGFGBEBEGHDBDFCFBFDFDBHHAHAEDFBCBEBEC,False +462,9.0,14.0,11.0,15.0,9.0,10.0,15.0,17.0,CHCHCGCBEBDHEHFBGDGDGDGDBDGEGCHHBDBDACFCHGFEAHFFDCGAGBFHEDEHHAHAEBHBHGAGBFBDBCFCBCBADAGEGHHEFDFDGDAH,False +463,15.0,16.0,16.0,16.0,13.0,12.0,15.0,14.0,EDEGEDHBHDHDACHCBCAHADGDGAEEHFGFGFAEGEDECGGAFAFDBCHCGCEBABABABDEACHCBABAFGEACFDBBCBEGEGCDCDADBDFHHHHHBDCDGBFFGFHCBCFG,False +464,20.0,13.0,10.0,7.0,14.0,12.0,14.0,15.0,HHHBDFFCHCGCGAGDFDGEBFBABAFAFHGHBAGEGEHBACFCEDBACCCABADAGBGAGEEAAFAFACGCFAHEHEDEBAGEHEHEGAGAEFHHHHABEBDBF,False +465,32.0,28.0,23.0,18.0,15.0,22.0,28.0,21.0,CAHHBFBGCACEGFGAAABABAGGCGCGEAAGCGEEDBDGDCDHDBBABAFABAEDBGCEDBDBAHABFHEDEDBFFGAGHHEGAGHEECDCFBHCGBDBDBFGFDFCFAAACACFGHGAGDCFGAGFFBHCHCEABHBFBFHFAFHFEFBABGBGBGHHHAHAGEFCCHBHCAGBCDCECADADAG,False +466,14.0,31.0,26.0,20.0,17.0,27.0,15.0,13.0,BBBBBCGFEFDFDFCCDCHHDAFADACCEAGGCGCACFFEGECEFECCACGEBAGDGHBABDBHBHFCBHFCFCAHDCDHBGFEEDEDFAFHHGBBFAFCCCFAFDFEBBABACHHBDBDBFBCCFFFFFFDBBBBBEBECEGEGDGDGEGCHEBCDFBBBDD,False +467,15.0,12.0,15.0,11.0,17.0,18.0,18.0,13.0,HAGECCBCFHEGGGGBGBDBGBAFACCFCFCBDFAAAAACEEEFECDFDCDCDHBGGGFGDABAGAFFEAEFHBEDEDEFBAHGCGCHFGFGFHHDHECEAEGFAFHHEHEBBGEHFDC,False +468,22.0,12.0,14.0,17.0,19.0,18.0,16.0,15.0,DADADADAHAGABAEHFGFGEGBHBGADHDGGACHEHCHGEFFBCGCAFGDGAEHEAAFCFGAHAHEDDFDCHFEFEDEBECABEFGBGAGCCECFCBBBBHAEBECCADEDHHHEDEDEDFFFFGDAAAFCF,False +469,18.0,26.0,29.0,20.0,29.0,19.0,16.0,15.0,CGCGCHCFCGHHCHCHCHCFAEAFFECEBFGDHDCECECHCFFDBDEDBGGEGAGEHBBCCACABEEEAEBEBACECGADBBHBDBEFEFEFCDDGCCBAHHFCBHBADAGFDBEFEFEAECBFFHABDBAEDECECEDBFBDBDBDACGEGEBADCDGBGDGACFEFBAEH,False +470,6.0,1.0,5.0,5.0,3.0,4.0,4.0,6.0,CBCAGGHDHDHDHFHFEECACADHCAFAFGEADG,False +471,8.0,12.0,3.0,4.0,7.0,8.0,8.0,2.0,GAAFBEGEFDAGEGEFEHGBCFFFFGBBBEBABABDBDBEBDHGCABACAGF,True +472,9.0,4.0,9.0,5.0,3.0,6.0,1.0,7.0,HACGCABHCEAFHBHDAAACFCBEDEDADAHFHFCFAFBCDCHC,True +473,2.0,1.0,5.0,2.0,7.0,3.0,2.0,10.0,CCHCDDGFHAEBEHHFACHHFHEHEHEHECEG,True +474,8.0,7.0,5.0,9.0,9.0,4.0,1.0,12.0,BCDHBCBADCDHHAHDHAHEDEDBHEEDHCHAFAHAHCEGDADEFEFEFABHBEB,True +475,11.0,5.0,2.0,1.0,3.0,2.0,5.0,4.0,AACDCFHAGAGAEBGBHBFEAGBGAAAHAHABE,True +476,25.0,30.0,25.0,21.0,26.0,22.0,25.0,24.0,HGHEDBDBCHEHEDEDEDEDCAHDCGCFDFGEGDGAGAGHGDGDCAAHABAFACBCBCEDEAEDEAGDFEBEBEHGHFHFCBBFGHGFEFBBBFHGBCFCEBABADHBCACGFHFACACDFABHEAEHHDGACHFBFBHBHBABGGDBABGFEFBHGHAHEBGBGCFBEBECGCACEFAGECACFDFEAECCBGHCDD,False +477,15.0,14.0,22.0,19.0,17.0,22.0,25.0,22.0,DFGGGFHHCHEHBGDEEBFBAAHGFGFGACCCGHFHBHCDEEFEFBFAFBFCGCEDEHEHEBFAFAFAFGCGCGDBCBFFCHCDDDEAEAGDEDECGDGABBHDHDFDFDGCGAHEHFHCHAACDDBHHACBGBGAGFFHCCGHHCCGDGDGCGEE,False +478,14.0,12.0,9.0,13.0,13.0,17.0,7.0,13.0,AFAFBFBDAAADFFBFBEHGFEFHAHFGDDFDHAHADABFBFHEHECCACGFBDBGAEHCDCHGHGEAECECEFECADFDBGBHBHEHDDFEFDBEAC,False +479,29.0,20.0,16.0,24.0,27.0,18.0,17.0,26.0,GEHHHAHEGBGCHCBCFGDGBFDHCCBCHFHAEFEGGDHDACEDDDCDFDFDHBAADHFHBEFEHCHCDFAFABAEGBHBABABAEHEAEAEDEAFHEDAGEBEFGCEDEFEDHBFFDFAHHDBDGDHEAEGCBDEDBAGAGAGAEAHACACAEAEBHAHGFGEBEADADBHBHFCC,False +480,11.0,14.0,7.0,9.0,18.0,15.0,6.0,9.0,FAFEGDGBBEFEDEFEFABAGEGEFFFBBCBEDABEGAAAFHFDEHHFBFDFAFCDCDEGHHCHBABCBEHEHEBEBEDEHABEFACDC,False +481,8.0,4.0,7.0,16.0,11.0,8.0,9.0,4.0,EEADADFDEAFBFGEGFGDGCHDDCDEBEGEGCFCHDAGCGDGAECFCEDDFDEABABADDDDEHFH,False +482,11.0,7.0,25.0,5.0,16.0,24.0,10.0,11.0,EAEAEACFCBCEFEGAGAGCCFFEFGBCFFHFCFAHACFCEEHCCFDFEEHBHFHAGFFEFEBDAGCGFAFEFEHECGCGCFCFHFHCCCBCDDBCCCCFDFHAECBHG,True +483,24.0,31.0,31.0,29.0,20.0,23.0,19.0,21.0,HAHEECBBBBGBECEFBFHHCHFHDBGBHEGEADAEAEBBFBCECFCACABHCHCEBFDFCFCFBFHHHEGCDCDCDHDCECGABADDDBAGAGAHEDEBBDGCBCFAFABAHCBCFHGHBDEDGBGEHCDCFCFCAHFBCDCDGDHABGFEBDBDBDGAFAGAFDDCEFABAFDDGAFEFDGCBABHCGDGDCDCAE,False +484,10.0,14.0,9.0,7.0,6.0,9.0,6.0,9.0,HCACBFBFCFCFHAHADACABDCHGHGCBFDHCBGBABFBDBFBEEHADADHBBEBADAGECEFHBGEGF,False +485,10.0,4.0,11.0,5.0,13.0,7.0,15.0,10.0,AEAEHCHCGCGCBEGEGFGBGAGFGEHAFGCHDECCAHADDFDFHFHEGEGACCBHDHAEGEGCGHBEEEGAFAC,False +486,10.0,4.0,4.0,3.0,10.0,7.0,9.0,8.0,HGHCFDHAFAECEFHFHEGECHDDACABAEEEGGAEAGAGAGAHFGFEHEFGBBB,True +487,5.0,6.0,9.0,7.0,10.0,8.0,5.0,12.0,FCFCFHFAFAFGEDCBEHHGGEHEHAGBHCHFEAEDEDBHADCBCDHDHDFBEBCCHCGEHE,False +488,11.0,11.0,11.0,8.0,15.0,8.0,13.0,12.0,CBABEBFHFGEGHCDCAGDGEABBCGGBBHEFBBABGBADEHCHCEAEAEGEFFFCGCEHDHDHECDCAFAGAGAGEHEGFDHCHEHED,False +489,22.0,25.0,26.0,26.0,18.0,25.0,28.0,23.0,BEBEBEBFFHDHDHCHDHCCGCFAGCHCHCDCGCABABAFCHEHBCBCDCGCEHAHAEGGABFDHEBECGCHCHFDADAHHEGFBHAHFDGDCCCHFFGGGGBFAFABGFEFAGGFGDBAHFEGEGEDBBEDDBHBDFDFGGCEFGFBFHGADADHCEGEGDGDFDBBCBCDGBADABAFCFAFADDDBCGAE,False +490,19.0,24.0,22.0,16.0,30.0,19.0,23.0,31.0,FGGAFEFECGHHEGEHEDEFEHAGFBFBFHAEAHAEAEACDEBBHCECACEGBBFBDBCHDHGCFEHHAHAHBEBECGGDGCHBHGFGBDFCGHGHDHBHBACACHBEAABDHEHDHFFBFHFHEBCDEDEDFDGEGAGADBCHFHABDBDCFAEAEBEBECGCGEHHCCBCHCEGEGHFCGEG,False +491,16.0,23.0,19.0,29.0,31.0,20.0,28.0,25.0,DHDBCECECAGFGBBEEEECEDEGHCDGGAFDFGFGCGCEHGHGEDFGCDFGFDDDCDEFEABDEDEBEBHBHBGGHBDBHAFABDGHCECGAEAEAGABHDHDHDHBBBGEHEFEDHBEEEGGCDEFGHGHAHAFCFGFEDCFEABHFHEBEBDHDHACBCFGAGFGHEHBGBCHFGDDADCDADFDECB,False +492,2.0,8.0,8.0,4.0,4.0,4.0,9.0,3.0,GEGFACBGAGECCHCHCBFDGHCCGCGBDBDBEBEFDFBGBG,True +493,21.0,13.0,20.0,26.0,11.0,13.0,10.0,15.0,AACGHHEEDBDBDCDCDBEBFBFEGDCEADDDFAFAEAHHHFAFADEDCHCBCAAGACDDDDDBCAGDCDBEHGHGFGABDHDHCCCCHADAEAEDHDAACAFAFBFEDGBHCCADHBGBDFCFCHCFG,False +494,4.0,3.0,5.0,3.0,3.0,7.0,4.0,3.0,AHFEBAHCHGFGFEFDADBFFCFCGCGCBEAD,False +495,0.0,4.0,1.0,1.0,4.0,0.0,2.0,1.0,BDEEBEGEGHBCB,True +496,6.0,16.0,13.0,12.0,12.0,13.0,12.0,10.0,DHFEEBAFCHCHCEFHABBCBCFGECECEGEBDCDCBBBBFAFEBEGGCGAGFHEDGBGEGCHEBDBHBHCGBHAGDFDFDFDFDHCADFDFGB,False +497,19.0,9.0,12.0,22.0,14.0,24.0,20.0,18.0,DEDAHEBAAGDBHHGABAGCHCDCACFCGCEEACBFAFAGEDDDHHHCHCGFGHBAGAFAHDDDDDGDFDFHFEEDEHFHEBFDFHBAGHGHFHFEDEDFDFDCGBFACAGAFHFEABGEGFGFGFECADAGGDGFFF,False +498,8.0,3.0,6.0,14.0,8.0,17.0,6.0,15.0,GFFDFEGGBEBHAEDGFAFEFDDDAFHCHCDCDGFHAHFHFGDHCEFHCHCFDHDHAFDFEFAFABAEHFHDHDEDH,True +499,0.0,6.0,1.0,2.0,2.0,3.0,3.0,4.0,EDECHDBGBGBHBHFGFBHBF,True +500,9.0,11.0,8.0,10.0,19.0,12.0,9.0,5.0,GCFDBACGFBFAAAAGBFAEGFGCGHEAGHDFFCEDEDEDEDECHBEGDDEAEFDFAFEBEHEHEDEBEBEBCBCBFFEGBCE,False +501,8.0,14.0,12.0,11.0,8.0,12.0,9.0,4.0,DBDBEBDBDFDAGCGFBCBCFFGCDCDEDBBBECECFBFECABDDAFAFAGEFBHAGAFCHCDCGHGHBFBEGEFCAG,False +502,5.0,5.0,5.0,5.0,9.0,6.0,4.0,8.0,FEFEBHHHAHABEBDDFDHDCAFFECEAHCBCEAEBHGHGCGFDEGE,False +503,12.0,12.0,13.0,25.0,16.0,10.0,18.0,21.0,GBGBDECCCFHHBACGDGDGDADCGCBBHDHDHDBDFDFDHEHGCEDEGEFAFHBEFFGCEHFFDDHDHGHGDAACAGBDHGHEDEDGAHCGDGDACEGAHAHDHEHEBEBCBFBEHEADDGDCAHE,False +504,10.0,15.0,9.0,13.0,14.0,7.0,8.0,9.0,CBEEFBBGBGBDBABADFBAAHEBEDEDGFCEBDBHAHBCBCBGGFDFCAGAFDGDHDHGEBEHFHECECEAHCDDEHEAEADCD,False +505,18.0,16.0,17.0,23.0,12.0,18.0,20.0,12.0,FGFABEFDHDHFHGDBDBGBGCACDDDHAHBHFFFBGCGEAEAGABHBGDGCECEDHFAGBDEAAHCEGHDEDEDFGHDDDDEFFAFGDGCFCFDFDACFCEAABGBABCBCFHGGBGEGAACCCCFCGBADADBD,False +506,22.0,16.0,25.0,22.0,25.0,11.0,27.0,18.0,AGCDCDHDBGCGAGDDCDGBGDCBCGFGHCECGHGAEFEDEAEGEFHGBCBCAAAAGGDGEHEAEDEDEBCBGFCFGDDEDECFDHDBEAEDEHGHCCCCABAFABCBAHCHGHCCDCEFAGEHAGAGHEBCHEGBHBHDHFEEEACACDEDEHGGGFBFBGDAAA,False +507,13.0,17.0,22.0,10.0,17.0,14.0,17.0,13.0,GGGCBBBEBHAEAGHDCGCDHFEAEABHCHGFGHGCCFFBCAAHEHEDCGCGCDADEHAHFDFAFCHCFCBDEEAEFHAHFCFABBDBDEGECEBGBGCGCDEEBEBFBEACBCGCGBGCFCF,False +508,17.0,21.0,24.0,12.0,17.0,20.0,19.0,17.0,ECHCHCHCGCFBGAGEBEBEBDCCFHFGCDFFHHBGBGDDDGFCFCGDGFAACACGFHDHGAAHAEBEGCCCFGFADADHBBBBABEBEBCGCHDHBGEHCACECEDDCFFAFEBACAEHEHBGBHEFAFBGHGFBCBEAEAGFFCF,False +509,4.0,0.0,5.0,5.0,1.0,0.0,3.0,4.0,GHDCDCDCDCAEHGCDHHAAAG,True +510,10.0,11.0,3.0,4.0,7.0,2.0,18.0,3.0,HAGGGGAFAGCGEGBGAEBGGEBEBDCEGDBDADEBEGAGAGBBBCGGBGAGHBHAFA,True +511,2.0,4.0,2.0,2.0,1.0,2.0,3.0,1.0,DEDFHGABBBBFAGCGC,False +512,2.0,4.0,2.0,1.0,1.0,1.0,0.0,1.0,HDBABCBCBFEA,True +513,4.0,5.0,8.0,7.0,6.0,8.0,11.0,4.0,GGHGHGDBCECECEGFHDABADEGGCGCECBFEGACFFFFBFCFHBAGGDDDD,False +514,20.0,26.0,19.0,15.0,24.0,22.0,24.0,21.0,FGFEFEFBHGHBEDHHHHEDCDEHEHCBFHGAFAFBFDCACAGGGGGGGHBBABFBFBCHGGBACGCGDFEEEEAEFFFFDECECFCBCBEAHCBADEDAGFDEDBBEBEHACAFAFABHEEDCFGHDAABEBEDGGHGHGDDFEFAHAHBGCGBGCCCABBHBAGCBHBE,False +515,22.0,23.0,26.0,33.0,16.0,30.0,25.0,23.0,GGGGCBEHCBCFEGGFADHDHCGDACCDBDGFCFHBHGAABFBAHAHDGDBDADACGCFDFGFDDHBGGGEBEBEFGFHBEFABEGCGCGHAHFHFHDBDBDCDCDCHFFFHFDFAGEGBABFEDBDCECBCDDHDBGECADEDEFFFFAFDFDECGHDFDFBCGFECHHAHAHGCBCDADAEAFCFCDHDABAHABC,False +516,17.0,13.0,13.0,12.0,15.0,20.0,10.0,20.0,FDFAGABHFHCEEAFCEGGBEBCBCBEBDHFACGHGCACACAHFHDBGFGDAEAEABFDEDHDFAFEBDHHHFHFHFHAHAHAEAFADCCFBBCEHFFFDGDGBEHHHHGCBEFEAEDFC,False +517,26.0,21.0,23.0,17.0,23.0,30.0,24.0,22.0,ABAEAEAEBGGGGGAECECEDFCEBAGHFHAEADCCGGGAGBEBEBEDCDFAFHFHGCCBHAFAFAFHFGBCDDFACGFGHDEEGEFEGBGFGADFCFCFCBAEABCDHHHCHFHFHBHAEFFFCFBECCCFFDFDBCHCADAFHBABDFDBBAHGGEAEHCGEGCDAGAHDGDFHFHFEBABEBH,False +518,7.0,13.0,9.0,12.0,7.0,6.0,7.0,5.0,CGCECBHDEBGBAFCDBDBDACEBDDGDGEGEFAFAFAHCFEHEDBCBDBDCDBBBDCHFBAGAGH,False +519,15.0,23.0,14.0,11.0,17.0,17.0,14.0,16.0,AFGEDCHBBBBBBGGECEFFBACACBCGCBHFAAABCCEEDDDHBBFBFBGEHEFDAEAFFFEHAGABAFHFBDBHHHBEBEACGCGCACDCHEEBEGGDGHGHGDDDCBGAEBEFEFAFHHHFHFB,False +520,18.0,12.0,17.0,12.0,18.0,12.0,16.0,36.0,EGEHCHDHDGDGCADAHAHFCEEBACEEEADAHHBCBEHEHEBAHCEEGCFEFAFABHBHGHDCGCGDHDHFHDHDHAHCHABCGCFBHHAHFHFHFCEHEAAHHBHGEAHHBFCCGBGFHAEAEGCHBHGDGDGAGFHHC,False +521,4.0,11.0,9.0,6.0,9.0,15.0,6.0,12.0,FFFCCHBHCFCBCBFDDGDGBFAGCFEFCHCGFBBBHCHDEDEAEBHBHGAEAFFBEGEHEHEHBHFFFFHD,False +522,17.0,10.0,12.0,14.0,22.0,13.0,17.0,18.0,EEEEDEABAGFEFEHGHBDAAABDBDAEHHAHGHGHDHAEABHHHHHBCGCFCFCDBAGACEEGCGAADGDHAFCFCEBEFDFEEACGHBEFEFEFEDCGFGHGEGDBAEGEDCHAHGDFDGC,False +523,0.0,4.0,3.0,2.0,1.0,0.0,4.0,2.0,DDEBCHCGBGCGBGBH,True +524,25.0,20.0,21.0,11.0,21.0,16.0,21.0,28.0,FGHGHEHEHBHFHFBFBDBEGDCHCGAEAFCDEAAACHEHEHBFFFFAAHCGGHGBGBHCHCDCGAGAGBHHHFDCDAEABBBCECBGGFACHCECEAFAGHFAEHGGEDEDEBHHACCCACBCHDGDGAAABAGFEBHAGBGCFEEDEAEAFBECHHAHBHB,False +525,5.0,5.0,3.0,6.0,5.0,16.0,3.0,8.0,DHFHFEFEADAGEGECBDFCBDDFHCHFAAAFEHHFBBBGDFFFFFFFHFH,True +526,1.0,0.0,1.0,1.0,2.0,0.0,4.0,6.0,HGHCHEHEGGHGDAH,True +527,14.0,26.0,15.0,11.0,16.0,18.0,25.0,17.0,BHFABADGFABCDGGECEBEFEDBDHGFCFDBDBCEFBFHAGBFEFGFHFHCHBHEHFHFHCHCEDBDBEGHGHGCBCBGDEEFCFBGBGBGBCBDBGAEAGBGAGECEAFGGGHGCCAFGGEAEDBHAGABAFAGHHCBBB,False +528,26.0,33.0,22.0,21.0,21.0,26.0,21.0,23.0,HDBFBDGDGHHEBFFCECFBABGGEBEGGAHEHABGBCCCABDFEFGFADACCGABDBFBADADBDAHAHBEGHFHBEGEBCBCBHAHABADCHBGCDEDEDHGGGGGCDBFFFFFAEECHCHCFEBEAADFBFBABDBGEEHEGEFCFCFEAEADCGFADHHFBDBAHAHACABABFBFCFHBHBHCDFGCD,False +529,19.0,28.0,16.0,26.0,16.0,17.0,19.0,17.0,ABADGCGBHDFFFGFGDGFBDGGFAFCGGFHHAAFFFEAAHAHCBCBABADDFFFABDBDBHGDACHCHGBBBBBGEDADAGCBEBHHEDBCBCBDEEGADABABADADCCBCBDFDFCBCHFEEEDEHHHGHBHDEECHGDGDBEEEDEDGDGCBBD,False +530,10.0,4.0,8.0,6.0,5.0,11.0,7.0,6.0,FFBFCDCGAGFEDCDBEGEGFCFCFCBAFDBHAHAHAGACAHAHEGDFCFADEGAFH,False +531,13.0,7.0,11.0,9.0,7.0,13.0,13.0,17.0,GCABEBFBAHHHGHGAAHCHBEBCDAFHFHBCDCDCDFGEGCHAHEHCHDFFFGFGCGAAAHGGGHFCECHHHGAAEADFBFDFDEDAGF,False +532,6.0,4.0,4.0,4.0,4.0,11.0,3.0,7.0,ABCDHFHFECEDADFGHAFCFCFBFBGADEHGBFHEHFHFAFA,False +533,14.0,30.0,24.0,27.0,22.0,23.0,21.0,29.0,CEBEDGCHDGAAABHEHGCGBFBEGDDDCDCHHDEGFHCEFBGBCCFBAEAGABEDFDCDCDHDHGFGHGCGDDFBBBBBDFDADCDGBFEFDBCFCFBDHDGFACAGFDFDEAECFBBHBHCACAHFDEHEHBDBGBHBFBEDCFEEHBHBCBCBHEFEFCHCHEAFHBHBHEHFGCAEGHGHGHGHED,False +534,7.0,14.0,11.0,10.0,12.0,6.0,11.0,7.0,ABADCBEGAGABDBHCECDBEHGCBCBCGCFCFHFHFBBCBGEGHGDGEGEDDDCDEDABAHCFEEAEFEBBGDEHBG,False +535,1.0,8.0,7.0,5.0,5.0,7.0,1.0,7.0,BHBGFHEDDFCBBBBHHHFEFHFCFCACBDBDEHEFECCCD,True +536,5.0,4.0,11.0,11.0,13.0,6.0,6.0,8.0,CDDDEBHHGHDFGCCACEDEDECEGEACACHEBFFEFEFGFGDGDHAEEEABCBHEDCDCHHDC,True +537,28.0,21.0,11.0,18.0,13.0,11.0,21.0,19.0,HGAGAGFDDHGEBDCGAAHGHEDBDFDEGAGHDECCAAAADDGBBCBHBHBHGCGCBBBFBFGABAGCHBGAFHFAACAGDFEFEGGBFHAADADFDADBBBDAEAFHGHEHEHAHAHAHAGEGDCDCHBABABECDGAEBE,False +538,3.0,5.0,4.0,4.0,5.0,2.0,1.0,6.0,HCHGHAFBEBEAEACDCHBEBFCEHBHDDD,False +539,6.0,6.0,7.0,4.0,9.0,4.0,6.0,1.0,CCAGDGDGEFBCACBCGDDBFEFCFEABABCEEEABAEGEGEH,False +540,4.0,1.0,2.0,4.0,0.0,6.0,5.0,0.0,FDDGAGFGCGAGAFFFBCDADF,True +541,9.0,14.0,13.0,6.0,8.0,6.0,10.0,5.0,CBCGEGEFEHAGEDBGEGAGHDCBCGAGAGHDFGAACBBDBDFFCFHFDACACBBEBECCCCHEACBBBBB,False +542,16.0,16.0,8.0,16.0,13.0,11.0,10.0,17.0,EAHAGFDCGCGDEHCHBAAADHDHEHEFBGBABFDAAADBDADADHDGEGCGHGBFAFEBBBBHFDFDEBEFAHEBDGFHCHCHGDFABABDHHHAEBEHEDEBCCF,False +543,21.0,26.0,17.0,27.0,29.0,23.0,26.0,18.0,GDEHHBFFAHDHDCBHBGEDBDGAGDHCEEEBFFACBBEDGFCFBEBECAFDDHBHDEFEFEFEGGCGBHFFCFEHBHEFBHBADAEAGAFBFGEGEGCGDEDEGCGCBDFDFDADABCFEBBBDBGGGFGCDCDCACFEDBGEGEGHABGEGEAAAACCHEBEDEHBABFGFHHEHADGDADADAD,False +544,22.0,22.0,21.0,19.0,23.0,23.0,21.0,20.0,CGDGDBCFDADCCGDBDHAHCHCEDFFGGGECECEAFAHCFDDEDAGCGCBDEDEAEHCHCEEECEFBFHDHGHGEGCHFEAEAEFFCFEDEABHHHGFBAGAGBDEGECECECHBHAHGBBFBGBDFDGAAFAFGBBCBGBFHEHCBDFFFHFBAAHBFBAAAFAGABDB,False +545,23.0,25.0,25.0,15.0,25.0,17.0,21.0,33.0,GAGAGEEHHHFHFHFHEHDCFHABBHBHBEBHFGBCCACACACGHBADHBECECEBABECCHCFEGHDCEBGGEBEBEFHHADCDCDFDHBHCAEEHEHFHGHGHFADCGFHCACACACBCEGDFHCABGDGEGFCDHGHAAAHBHBHBEBHBHAGABEEGEDEGFBFCGEDAGADDBBEAFCF,False +546,3.0,2.0,2.0,4.0,0.0,4.0,0.0,0.0,ADADAFCFDBBFCFD,True +547,13.0,21.0,3.0,11.0,13.0,5.0,12.0,11.0,GHBADHBHBGBEHDHEEFGHDHGFEDDDEGEAEDFAAGBBCBAGAGAEDEHBHBABABAGADBEBECEAEBBBBGBHBDFGCADBFBHG,False +548,25.0,24.0,22.0,17.0,28.0,18.0,39.0,21.0,CDCABDBHBGBGBGBCECBABGBGAHAHBFEEAEBGAGEHFACACDEGEGECHAEGEHFHFABEGHFHAHGHCDCEBEGDBFAFHGEGBGAGDBDBDBEFECHFHEBFGEGEGECAFABEBGBGHGFGEGCCCCHGFACGBHAHAECFGAEDHGHGDDDEAFADGDGDCAEGGACFBFAGEGACCEHDCDGGFG,False +549,3.0,2.0,4.0,4.0,5.0,8.0,5.0,2.0,HFEFGDGFBFDFEEEFEFGBGCCACDCAGAHFD,False +550,1.0,3.0,4.0,3.0,7.0,2.0,2.0,6.0,ECEBHBHGHBECEFDHAHECEDEDGCHF,True +551,16.0,22.0,21.0,26.0,28.0,20.0,19.0,21.0,EGEDEBEAEADDDCFCABGEFFHDBECHBBBBAHAFFCCDDDDDDHGHEFAAAAAGGBGFGBGCCHEHFBFHHDCDFFBFDGEGFCABBEBEBECDGFEECACDDBCFEDEHHDBDFHFHCHCEGGGEGEADCDCEGEFFHHGCCBCBDBEBEAEAEAGDFHCDGDHBHEHEH,False +552,4.0,5.0,6.0,11.0,3.0,11.0,11.0,5.0,GCCDFHFBDDEDECGCGDGHABDDGGGDHAHAFGFGEGFGFABDFHFCFDBDBFFC,True +553,5.0,13.0,12.0,7.0,6.0,1.0,8.0,8.0,BGDACECGDGCCCBCHCGCDBHHGBEAEAEFBCBEBDGCGDGCBABABEDCHHHHHBBDB,True +554,21.0,23.0,19.0,23.0,24.0,21.0,32.0,21.0,FAGAHAHFHGHBEEFGADABCBGBGFAHEDEFGFBHCECEHEHDGDEAAHGGGEGFFDFBCHGAGHCDGGGABDGDADHFEBHBHGGCACBCBCBGBCFADADGDEDACBGHEFDFHFHFBDDDDBHBGGGCDEFEGEGECHCBCBEBEBEFFAGBBFACECECDAEFECGAGEFDGGAADHDH,False +555,11.0,14.0,17.0,9.0,22.0,14.0,9.0,22.0,CGEEDCDADADBDBFFFHCAAEHHHEHEHAHEFFCFBGHHHFHCHDHEBGFGFBEECFCEEECGCGHEEEEADHBHAABCCACFCEDHCHCHBHBDBECGCEFFGFABBEBEGHAHBE,False +556,4.0,3.0,4.0,4.0,4.0,1.0,0.0,1.0,BABHECAAFBDCDEDEDECAC,True +557,11.0,15.0,15.0,16.0,14.0,18.0,14.0,14.0,BCBCBGDGCGEAHHEHGAFFCFHFCGAGACEBEBEBAFGCCDGBCEFDFDAEADDFDCEBFBFBEHDHEHEGEGBGHFHDDDDCCBGBCBHAHDEFFFGGCHBEAAAHFFDFDFDHC,False +558,5.0,2.0,3.0,3.0,1.0,2.0,3.0,2.0,DGDGACBFHFHAEACABACDG,False +559,29.0,26.0,17.0,17.0,20.0,26.0,24.0,23.0,DADCDFFHFAFACAFBDBACAGABFGFBHCHCFFEFEFGHGCBCAEGGGDBDBABFHFAEADDDEDEHAAGGDBHGFFFFCGAHBBGBGECEGEGEGEBEDCFFDFCCEAAFDHAEBFBFAHAGFHCCGBGBGBGAGABEDADHEBEHHAEFHAHABCBCHAEAFAEBHGHBBBAGDHHHHC,False +560,7.0,9.0,14.0,11.0,8.0,12.0,13.0,5.0,FCDCEFEFGHDAABACGCGCGDEBAHHBCCFCFGEGDBDBDBAFECDFDFEGGCAFABCFGFGEGHCDEDGDGFCBCBH,False +561,16.0,32.0,21.0,19.0,21.0,20.0,22.0,22.0,AFBGBGHGEDFAACDCDCEFEBCFCGHGHFDABABAHCCEAHBEDEDBDCCHGHEBEBEBCDEFGDGFBFEDHDHDBBBFFEGBGHEDGDFBGBACDGEBEBHBHCCGHGHGDGDGHGHBCAFHGHGFABAFAHAFCBCBFAHDHBBCBGFEBABCBCFCFEEBCFEDEAHBE,False +562,18.0,21.0,6.0,6.0,14.0,3.0,15.0,20.0,DGAAHCHBAFHBHBGCAEAEAHAEAHHHBCBGGEBDFAHAEAEBGAGAHDEGHAHBEAEGHGHBABHBHEDCGHGBEDGBGEGBGBABDBAEEHFHBCBCBHB,True +563,19.0,18.0,15.0,19.0,14.0,16.0,17.0,24.0,FAFAFABBHDCDCDFDCAABFCEDBBECDCDFFAGADBCHGGFHDHGHEECEGDADABEHHHHCHDHDFAHGFGFBDBCBFHAGABDBGBFDGGFCFCBHBHFHEHEHEGAGAHAGABAGABEECDCHHEBEDEHAGCGHDH,False +564,3.0,3.0,2.0,1.0,0.0,0.0,0.0,2.0,BABCBDAHCHA,True +565,8.0,12.0,12.0,9.0,13.0,13.0,12.0,17.0,BFBFEEHBFAFGGGCHDHDHGCDCGEHAHEEBBAEFGCGCHCFCFDBBBHCEBEHEHFGAGFFHFHABDGDFDFBHAHDHEAABCEGEGEDCHCHC,False +566,24.0,19.0,7.0,22.0,15.0,14.0,18.0,21.0,AEADAHECBGBFHGHDHAGDGHGBGBHFHBDDDHGHDHDADHDHAHDEDADGFEFGFBDBDFAAAAABEFDHHHEGBGAAEDEGEGAFAFHHBEEHCGBEADAEFFBFDFDBDBGBHAGBCBEFDHGCACBCBAAACAGE,False +567,18.0,34.0,25.0,23.0,26.0,29.0,16.0,24.0,CHFDFHBCBDBFBHEEAEABABCGAFDFDADADADBBBCBDBFCEEEFFAFDBDBGHDHBBBFFFDABFHGCABABABAHHHHDFBFEFHBCDCFCFBFEEGECFHEGEGBBDDHDEDHFHDHDFBAECCBHBEBHBCCCBDBEGHGCFCACEFAGEGEGCCFBFEHEHCGFECGFDAGFGHCCCEEEBEHAHDG,False +568,10.0,3.0,8.0,11.0,10.0,4.0,2.0,8.0,EGEDEHEHCDCEAEAEAFFEHCDDDCACHBHBDDDHAAACAEBFAGAHDCCFEDHD,True +569,16.0,11.0,9.0,12.0,15.0,17.0,17.0,12.0,EAEDEACHEAGBHHFFAGGDADADHBHAFFGDEDEHFBFCGBGFFDGHAEAFBCBEAECDADCGCGFGEGEGAGDEDBFFAFAFCBHAEAEGEGFGFDCHCGFBHBHBH,False +570,5.0,3.0,10.0,3.0,5.0,7.0,4.0,6.0,DADCHHGACACECHCFCFHDEGABAFFFFECECFGGHBCBCEH,False +571,19.0,19.0,10.0,25.0,20.0,11.0,12.0,21.0,EGEGEDDDADCBFBFCHCHGAGDHDHDADGHEDDDDHBHBHCADEEEDDHDBCEAABABFEEAEGHGHFEADDDCABHBHBHFHFEEEEFDCEEGCBCHGAEAGABFBHAHEHAFABHBFDDDBDBHAAFBBAGGCD,False +572,9.0,14.0,14.0,11.0,15.0,15.0,19.0,10.0,EFEAEGGGDGDADFHFGFBFBFGDGBBEBEADHGCBCBCGCECGFDCBCBFDFGEDBDHCAFEFEBGCHAFGFGEEHBGCGCEEEBHCHBADCCGGHAHADAGFHFE,False +573,4.0,10.0,13.0,15.0,11.0,8.0,6.0,4.0,AFCCGEEDEBEBAHAHADFBCBCBEFDGHBEGEFFBFDDBCECDCDCECEDDDDDGDCDCEBBGDHFCCGF,True +574,15.0,27.0,18.0,27.0,33.0,20.0,18.0,26.0,FACGCDEDBABABADHDBEFECGDFHHEBCBCGHHAEBHBHGDADGDGDEEEDEBCBDBEAFHFEDGDGDBCHEAADEDEAEDHCHAFDEDHDACHBHBHEHECFBABHDEEEFEGBGDDHGFBFBFCFCEBEBFFCECEGEFEDGDCBGEGHFCECEBGBHBHDHCEFFFBGBHHHEFAAHDG,False +575,16.0,17.0,13.0,14.0,16.0,19.0,22.0,14.0,HBCFCFDFEGAGAHHGEGBGDGFHEHAFBDBDCHCHGFDEDEFHFBEBHBHBEBHBDFDEDEHEGEFFACACGFHADGFADGBAEADAFBCHEFFBEBGBGBACGGFGFAABGGDGFCCACAEAECDGGGC,False +576,21.0,18.0,24.0,12.0,15.0,14.0,8.0,14.0,CDCDFBACHGHECECEDECECHHAHBGFAAHAGFEBCHAGBBBABCBADCFEGABABCGCFAFEBHAHDHECACHHFCBBBEBECFCFAFAHAFCGDFDFDBEBDCACACADBDEHEFEDGCACAC,False +577,11.0,6.0,10.0,4.0,4.0,6.0,15.0,11.0,HHGHAHGDGCEBABABGCHCGCECHCACHDFBABFHFCAHAHFFBFGGGGGGGACAGECDGAADEHG,True +578,13.0,11.0,13.0,13.0,10.0,10.0,11.0,13.0,HDHDFAHCHGEAAAACGBEEHHDEEEDADCDCACACDGDBDBCFEAGHCFCABFBFGCEFBHHHHGBGCGCGEEHAHFBFDDBDBCGDGAFAFB,False +579,16.0,20.0,17.0,10.0,16.0,13.0,17.0,18.0,HBHCDAHECCCCBHGEFCBCGFFAFACBDGDCHBHBCBEBEDGDFEHGHBHECCCEFAGAEHDGDGHBFAFAGAGBGBGBEECCAFAFDBBHFECBGHCHBHDHBHBAEEEAEHEAGAGFGFGDABA,False +580,19.0,23.0,27.0,23.0,24.0,28.0,24.0,26.0,FGFGCHDADGDHFFDCDABFFFFBCEAECEHADCDFDFABAHABDEDBAHCCCHBAAFAEGEGFGHDHGHBHGHDCFCFCADEFEHBAEEFGCDCGGGGGEHFGCGCFFHFHGHBCBDBDCCCGEBEHFBFCFEECFGHGHFHCAEBEBEGHGHFEFDCHCBCBGBDBEAAABCCEAFBHBHDHEEGABDDDED,False +581,14.0,16.0,19.0,20.0,20.0,20.0,13.0,20.0,ACAFBEAHDHEHBHCABBCHFHCEEGCHHFCDCBBEBHFABGDHFHFHBHBHBGDDDCFFHFBFGFECDCEAGAGACCCGCDCDEDEDADADFFFAFAGHCDAGHFEEGHCEEEHECECEGEFDFEEGDDDGDBBFBFBADH,False +582,13.0,15.0,13.0,20.0,21.0,19.0,19.0,16.0,EGGAGAHBFFEFEHECDCFCBGHFFGAGAGEGCGAGBFCFDDDEBEHEHCFBDDDDDDADAFAHHCFDEDBFFFFHAGCBDAFBHBEDGFGCBCBGEGEDCDCDCFHEHGHBDGEHABEGAGHFEDAHEEEEEBHB,False +583,6.0,13.0,10.0,9.0,17.0,8.0,10.0,9.0,FHFGBBBBABCCDHBEDHGFDEHCGCBEBEHCFCFBFBDBACFHGHGEEECECEDEDEHEDGCAEADFDGEAEGGGEBABEH,False +584,18.0,27.0,27.0,16.0,19.0,28.0,14.0,16.0,FHFCFAFHHBEBFBDCHBGEDBAFFCBHBCFGFGCGCEEEDEDBABGEFBGBAFAFHEGCGCDCDBHHCHAHAHGCECAHFHFDEGHBBCACABABFBFBFAFCDCDBABEBECFFGBECCCHCFAFDDDDFDBECEAEDBFCDCEFGFABABCCGEHCABGFEF,False +585,26.0,16.0,22.0,22.0,20.0,21.0,22.0,26.0,FHDHDHFCEBBDBAAAAGFGCBEDHDHGHAEAECDCBEBHCHAHGGFDAEFCFHHHEECCCDCDCDHAHABBECACADAHCDCDFBBEDAAGAFFHCEEEAFAFGFCECEFACAEAFFHEGFHCAGECFFGBGFGDBDBABAGGGGGHHHAHDDDHHHAHDGEGFGBGBFCEDGD,False +586,8.0,5.0,12.0,4.0,4.0,13.0,13.0,7.0,DFDCCCCCCFEBEBDFFAFGCGCBFDFBAAFHGHGCGAAHGFAFGFGCGAGBCHFHCGGHFHEAEG,True +587,4.0,3.0,2.0,3.0,2.0,5.0,3.0,1.0,BGGGDBDHDFCAEAFCFBFEFAA,False +588,7.0,14.0,10.0,16.0,16.0,9.0,9.0,13.0,BCDFHCGFGAEFFFDDBBHBFBHHGAEDDFDEHEGEGEHADFEEHEGEDEDEDEHHBHBDBHBDCDCDBBFBABACACEHECGHEBDGDCCCAG,False +589,41.0,28.0,27.0,20.0,22.0,14.0,25.0,23.0,EDEHHHEACAEAEGECBBHBHBEFAFEBAFHHGHAHACAGBDBEGCDEHAHADACACGEDCCCFBBBBBFAADACAGECDFHGDDBDCDCECDABAFCBEGEDFCGBGDHACABGHECBGGCDCGEFEAGCGDAAABABABDHGEAHBGAEHGBGBFCFCFEFBHGHBAAAAHABABADAGACACGCACHDHDHAFAGEG,False +590,25.0,17.0,16.0,9.0,20.0,24.0,14.0,17.0,HDFDEGEFBBECCBDBABFFAFDFCECBAGAEABGFHCACAFAFAFHEHEHECFCHEHEHECGBDBAFEBCFAFCFAGGCFCABHGABFFEGAHAGAGCHHEHFDFBEBCBEFAFAHAEFEAAHAHBHBGDGDGCEADAGEF,False +591,17.0,13.0,25.0,18.0,20.0,19.0,18.0,19.0,ADCFCHDBAEHEHEFEACAFAFDFEFECEGADHDHEBCCCCEHHGBDBDGCCFBGDDCGABAEAEDEAFAFCGCFHFEGAGDGFHCGCEHEAGCHCBDEDCFEDHCBEBFBAGEGAHCHCBCBAHACDBDCDCHFHEGFGFGDGHGFFH,False +592,4.0,14.0,3.0,5.0,17.0,15.0,9.0,5.0,HGFEEHBHFFEFHFEGBABFBGDFBBEFEDGDEDECEBEFEAEBBBBEBFAHAGFDFEFEBGCGFGBGFECE,True +593,13.0,8.0,10.0,11.0,8.0,10.0,5.0,8.0,EAEADADGFGCDDFBFHHGADABAFHHBAEABHHGBCFCFDFAFDHDCDCBFBCCCBCEEEAEAEFDAHACDG,False +594,16.0,13.0,15.0,7.0,3.0,9.0,20.0,22.0,BGBGCGHHHEHGAAFGCGBDFAFBHCHBDBCCCFDAHHBGBAAABHHHGHGBABABCCCCCDGHGHCHAHGEGDBFGFGCGAHAGFCHGGGAHAHCHFEDHDAAF,True +595,12.0,10.0,9.0,7.0,8.0,10.0,12.0,10.0,AEFDFGFGABHBHBACAHFFEECEFDFGBCAABBCDCGEBEBHHHHFBAEADGDGHGDGDCACGCACAEFHAHGGGBF,False +596,12.0,14.0,7.0,5.0,7.0,8.0,16.0,11.0,DBGBABFCGCGEGBGCHCABEEHGGGHGHFBEBABFBFBGGGGFDFCGABABAFAHHHHBEAAADDHCFEHAHBGACDGE,False +597,12.0,31.0,25.0,23.0,29.0,22.0,19.0,20.0,GBCAEDEGEDHCHGFBEGCCDCGAFBFAFEGBBDBDBDGGCEHEHFHDCDCDEDFHHBGBGCHABGCGCFHFDEBCDHDAABFBGBHDCDCEHEBFBFEFBFHEHEGEBBDBEBABCDGDBHBDFDFDACCEFBCBFHFGCEAEDFCCDCFGGEEEAEAFAFBHBEBCBCHEHCHGEEEBE,False +598,3.0,2.0,2.0,2.0,0.0,4.0,2.0,0.0,DADAGFCFCBGAFBF,True +599,18.0,18.0,17.0,19.0,19.0,25.0,24.0,26.0,EFEFADADEGEGBBHHABBHCCGAFDHDFEHHHHHHGAAADGHFHGGGGDEACHCHCFCGEGEFABEEGEHFCFDFEBGAHCHGFGFGFGFDDHEFCFEBDFEACAFHCHFBADGCGBADGDAFCHCHDDDFDFHCHBHEEEBEBGBABABABCBFFHFDGCGBGD,False +600,18.0,13.0,8.0,18.0,9.0,20.0,11.0,10.0,FAHEFAFAHDGGGGHCBEGABABFEFAAGAGAGAGAGBHBHCFFDHBHDEDEDABCFCEDEBEFADDBFFCFHFAAGDDDDDDFFFFHADFFFBBBCDADCCADHBE,False +601,28.0,16.0,18.0,22.0,25.0,31.0,31.0,28.0,DHDHCHCEGGGGGGHGHGABHGABAGDGEGBACHDHBGADFBHGAGFGDDADGEAEACHBBFFHFEGEFFAFAFGFEFAGADDFAFCFGHBFFEDBACABFHFCCCEEDFDCDAAHFHEHDDEDGHEFCAHFFBCGCGCACABAEAEHDHFHFHFCEDEDGAGAEEEEEFDAGGGHGHFHAGEBHBAEFCFBFCEHBHD,False +602,19.0,22.0,22.0,6.0,18.0,28.0,18.0,32.0,BEHEHCBFBFGAGFFFHEEGEFFGCHCHFABHHCCBFHFABBEBCACAEAFHFABHCHGBBAHEEEEAHAHBHECACAHEHEHCGBFFHFGAGCCBCBEFEGHDDGDHFHCDAHHHHDAFBFAFHFHGHGACCCACBHBGBGBCFGFHFHFGFGFAEBCGCBDEF,False +603,6.0,3.0,3.0,0.0,3.0,1.0,2.0,3.0,AAAAHHHEAEBFCEGAGCBCB,True +604,20.0,12.0,4.0,14.0,4.0,16.0,10.0,13.0,BHADGGGBAFFHAEDBAFGFCFHFHDHBHBGFFHADDEHFFBFGHAHAHABACADFFAAGADAGAGACADDEFEFDADAHBGBABDBDBDCHF,True +605,13.0,12.0,3.0,10.0,9.0,12.0,19.0,5.0,BFBFCDGDBDAGAFCHBBBDHGADCEAABAGFGFGEGEGDGFAFEGBGAGEFFGFGEDADBBGAGAGEFEBBHGHGEDDAFAH,True +606,25.0,22.0,15.0,23.0,20.0,14.0,29.0,17.0,ABABABGDEFEFEHBAAAFDDBDGDGAGEEBHFFCAHAGABACACHEGDGDFDHGGFFHFBEDECFGHCBAGDGCHBGBGCGFDADECEBEAEADAFEBEAEFCBCBCBHBABGBHAHAGAGDDEEEHBCEADGDGDHHFDGABDBDGGCGCADGGHHDHGGEGC,False +607,7.0,12.0,19.0,9.0,3.0,6.0,12.0,7.0,CHGGCADECECGBGCGCEHDAFACDBGGFABCBCBCBCBFBCGCBCBCBFHADACADHDCGGGDFCHGFCHDHDB,True +608,15.0,15.0,12.0,14.0,12.0,4.0,21.0,15.0,BGBEFEGDBCGCGHHEGCFAGEBFGHBCCEGAHACGBDBGBHAHGHGHEHEHACABADADAHACBGDAEHGHBDBDBEBAAAFCGCGDEDCDEDHDAGHGDGBGEGDC,False +609,11.0,19.0,6.0,5.0,9.0,14.0,11.0,10.0,BBBBGBFBFBABDHAHFBBAHEHFCAHGGDGDFCBCFCGAHBDBGBGFGHAHGBEEAFFFBFEFEACACEEGEAEDGFHAHBBBF,False +610,7.0,6.0,1.0,2.0,7.0,8.0,15.0,3.0,GGGGGDGFBAEAEBFHGHDFAGBEFEFGFGBHAGAGBCEAEGBGEGAFF,True +611,9.0,11.0,18.0,12.0,13.0,14.0,18.0,18.0,DABAEGBGEGEGEGFDHCGCHAHFHFCCCCHHGADFBGEHAHEHECFHEHEAGABDGEBCBFFFGDGBGACHHHDHCFCDCHHGDCHCBCDCGCBBDADGGGEDECBFFFFEF,False +612,1.0,6.0,5.0,8.0,3.0,4.0,3.0,4.0,BEBEBGBFBFDDCHBDFCHDGACHFHGDCDCDED,True +613,5.0,7.0,4.0,9.0,3.0,12.0,4.0,8.0,DEEHBFGFCHBHDHFAGDBDHDFCFEBHHHBFBABAGAGDFDCDFFFFCFDA,True +614,5.0,4.0,10.0,9.0,2.0,6.0,6.0,7.0,GCBCBCGGBFHHCFCHHDDDDCBGAEACACFDADCCAFHFHDHDEDGFG,False +615,20.0,20.0,21.0,19.0,32.0,21.0,14.0,26.0,FCCGGEHECEDEDBBECHCHCFGBEHECCCCCHCGCDCDEHAGCECEDDBEBABABEBEAAAAHAHEFAFHFEFBFBFAFGEEEAEHEBGHEHDBCBDAAEFFHCGFHHHGCEAGDBEHEFEGDFBFAHHDBCHFFBEGEGFHECEADADADBHFHAHDDFDFHEAEBDBDGH,False +616,4.0,1.0,4.0,5.0,3.0,3.0,4.0,3.0,AGAHCHBGDFDCHEDEDEFCFCDAGAG,False +617,14.0,17.0,16.0,17.0,18.0,16.0,11.0,15.0,EFEFHFABEBEGEAEBEAECBDHFEEGEGBGDHHHHHBHBHBHAFAHDBFHABDDFDHBGDECECEFEFGDABAFAFABDHFBFCGCGBEFCDCEADDDFACAHDCCGDDCBCGCFCABECGCD,False +618,29.0,30.0,26.0,14.0,18.0,25.0,13.0,17.0,HACCBHBFAFBFBFHFCBAAGAEBEFDDBDAAACACACEEDDAEFGBGFEFCABAGAGAGFGCHCAGFBBDFHAABFCFCFDHEHCFBFBHADBBBBHDDBCFABBEBFBADAEBCBHBHFHCBDDHCHGHCACAGAGDFCFEAEBECECECFCECECGHEBAFAEAGHBCF,False +619,31.0,22.0,24.0,19.0,30.0,25.0,19.0,29.0,CFHEHCGFFACEHBDEEGGACFCACAGAHAEAFDCGBACEFGAECCAGHBHBDBAEAGFBABAGACAHHHAHCHCDCDAGGGAHAEAEDGGCEHFHFHFDGBHBCEHEDEFEFEFEAADACHFBDBDBDBFBFAEHFHBHEHEGEDEDCCEBFBFCFCAHDBFEAEFEACAFADEBEHHDEGEAHBHCHDBGBCDHFGF,False +620,18.0,17.0,15.0,24.0,21.0,15.0,18.0,13.0,ECDGDBDGDGDEAEBEBCFGFGAGAGHCDEHEHBGGGFEAAFBBDFHCDCEEEEGAGAGEDFDHDHAFAFHEHDADADBDECACEDDBHFEGECADDCFHBCBCHCDDFDGBBBEAECEDEFABAHCHGDABFBFGFCBGA,False +621,0.0,2.0,1.0,1.0,4.0,1.0,0.0,1.0,FEEDEBEBHC,True +622,14.0,20.0,14.0,20.0,27.0,29.0,12.0,26.0,CDCACEHFHFHBHEFEDEBBFFFFBFECHHAHEHEDGDEEBFHFHAACEDECCCCEFEHAHBHDHFHFAFABEEEGEGEBDAHEEEEFHDDDGDEDABHBAFGFEHABFBABDBFFFHFCFHFBGCABBGBHFHFDDAHGFEFEDHCHDEBGGGBCDDDCGF,False +623,16.0,25.0,17.0,19.0,21.0,19.0,21.0,15.0,BFDFDFGBGDHBHEDCACFCEHEDEBCFDEDADBDACADDEGEGHAHBHFEBCCCAHEHEBEBAAAAGCFCFGFBEEEHBHEHGBDBDAGAEAGBDBGFEFGBCBCFGEGBGHDHGCCAADCDCBFBAGGFGEHDFBEBFBFDFCFHBGGGEB,False +624,23.0,27.0,21.0,27.0,12.0,19.0,33.0,26.0,DHAGAGFBFCCHHGGBCBFDFACGBGBGHCABACAHFHCDCDGFGFCFGFCAEGHGABABEDEDHFHFDFBGHGEGHAHBHCDAGAGAGBBAEAFGCACBFBDDHGHBHDGDGBGDAAAAEBBGBDBDCACFCHCBDBCCCBGFFHDHDHEGEDEHHDDDHBGBHDFFEBDDEEGGGGAGHCHDBAGD,False +625,17.0,22.0,27.0,7.0,24.0,19.0,26.0,18.0,GHECEGFGAGCBEEGBGHGBEBEAEFGFAFCFHGGGGEEECBFBDGGCGCEDGFBHBCBCBCAGABEGEAEABFFFBFBFHEGFGACAEFDBCBCAGAGAGFFCCBEHCCBCBDHCBEHCHCACEBFBCGDAHFCECEDACAEHHHHHDAFGHCHCEGEH,False +626,21.0,20.0,18.0,14.0,19.0,24.0,20.0,19.0,FGFGDBFGAAHHDABADDECCHFBGCEEHGHGHGAFHCHAHBCBFAFAFABBBABADDGEBBFCFCFCFCBCDCDHFAGGHGHGAGEHBFAFCHHEGEFBHDHAHAEDGAGAGEGCDEHECCCBBBAFFFEFDADBBEDEGCFBFCGAEEEEFEF,False +627,22.0,20.0,15.0,21.0,16.0,16.0,15.0,16.0,GBGEFDACFGFGHBHECCFAAAEEGBCHCBCFADHDHDBDBDFDADABAEDFBADACBCFCFEHGCEFEAEBHDHDFDEEBBHBGAGDGAEAEGGHAHDDDDFDGBBBAAAABDHGHFAFECCCECHBDBCBFEFGAGAHH,False +628,7.0,15.0,8.0,13.0,14.0,12.0,11.0,8.0,DEDBDHFHDCDCBBBCBDBFBFCGHGAGEFAFAEADBFBGBGHGDCFADBDFEFEDECEFHHCBEAGGGDEBECEABBGHGFDHEEFE,False +629,1.0,3.0,3.0,8.0,6.0,2.0,4.0,5.0,HEHDHDHDEFBGBGDDCDHBEDECGCEEFGAD,True +630,11.0,10.0,7.0,6.0,8.0,14.0,8.0,5.0,CAHAHABFCFCACFCAHAGDBCEGHFHEBDFAGAGABBBEBCFEFEFBFAFBDEDEGGDFDABFFEFGG,False +631,14.0,11.0,20.0,21.0,13.0,15.0,14.0,16.0,HCFAAHBFCFAFHFGDHFCFBBBEBEAEAEHEHGDDBHHHFHDCDEGECFHFDFDADACADHGEDADHDHDCDCGADDECEAGBBCECDGGCGCABAHFGCDCGFBHBDCDGAGCCCDCGEFEF,False +632,4.0,8.0,5.0,12.0,1.0,8.0,6.0,3.0,CAHAEDBCCFGDBDFFBFBHDDDDDADCGBGBCFAGDGFGFHDBDBF,True +633,3.0,4.0,7.0,2.0,2.0,6.0,5.0,5.0,CBCECACAFEFDAHBCGFGFBHCHDHCHGGFBFG,True +634,15.0,14.0,8.0,23.0,21.0,16.0,17.0,8.0,GDDDADADACBFGFGFAFACADAEEBEBFCGBFHFHGEDDDFCGABCBDHDHEEFHAHGEFDFEFBFAGAFEGDGDGBGDEDEBHBDCEEEEGEBCDDEAECDDDEGGGAFAEBFBGHEDAB,False +635,16.0,23.0,27.0,12.0,33.0,22.0,20.0,34.0,HEHACECAHFBGBEBHHHHFFCECEHEAEGDGDHAHBFFFFFFFGABCEFEBECECHABGCGFHEEEEEEGBCAHEHCHDFBGBCBCBHHGFBHDHCHEHEHCFCGCGEFHHHCDGDEDECBCAFEFAGHDCABHDAEACCHGHFBBHDEAGBGAFDDGCACEFEFEHEHEBEGCCEGBGBCAHBHB,False +636,18.0,21.0,19.0,22.0,14.0,15.0,21.0,26.0,GHABCDDDAGGFFEFDFHBACHDHDECGBFBFAAGECECDAFBHCDCEBGBAAAGHHEHEHEHEBAFDFCACECECEHHHCHDHAHAHCDBDGGGDHDBCCFCGHHHGDDDBEBFCFDGAFBFBDBDBGBGBABHHCHGHGDBEGAAHDCGAGBGF,False +637,7.0,11.0,15.0,9.0,7.0,9.0,10.0,13.0,DAFBFHGDGAGCDCDGHBCECFCGCDEDHDHBHBFBEGEHDADBBBBGFHHAECHGHGHBFCFAACCCFFHGACHCBCECE,False +638,23.0,18.0,27.0,21.0,18.0,14.0,17.0,30.0,DEDCHCBFEAEAEABAHGDGDADEBEHCFDGGCCCCDCBFGFCCHDHDHFBABDHEHAHFHCAFAEADHDHCHEDACCGCGCGCBAFHHHECDDDBGHHHCHBHAHECFBBGBDBFHAHGHCDGHGCGCBBBGBABFGCGAEEDFDAEHFHDHEEACAEFEACHCAAA,False +639,8.0,5.0,5.0,6.0,7.0,4.0,6.0,5.0,FGEBDBDBGHGDGCAHAHCDAGAFAFBEBEGEFDCHAEECEDACAH,False +640,25.0,30.0,19.0,18.0,18.0,25.0,21.0,28.0,DBGBFBFHFHCAFAFACGCHCHEHEGFGADHHFEAEGEGHGEAEBDADHBABDGGGGHBHDDGAEBDFCGCFFGACDHBHFHCHFAGHEDACAHBDDDAHHEBEBABACAGBDEDGHBHFHFCGCDFBFBFAHGCBDDCBAEAEFCABABACACEFHFBAEHEGBGBHBFFHBEBFBFBFHCBC,False +641,10.0,7.0,19.0,15.0,18.0,26.0,16.0,17.0,EBEBEADCFGFGAADCEFHCAEDEAEFBHEHDGDGDBHCGCFHFHCHFEFGFGCECFCGCEDAFEGDFCAEADCFEFHHHFDFGFGAGDGDFHHGACFBHDHCGFGFCHCHCHCDEECFFFFEBEBFD,False +642,17.0,19.0,31.0,20.0,20.0,27.0,31.0,22.0,EFGFHEBFAHAHFHGCFCFGFHFBFDHDAGAGBECCHCBGBFEABDEGEGFCBDDFEFADADBFEGEBBAEHEHAHAFGCGCGCBCBFGFCACHCECGCBCAGFHDBDCAFGCGCGCGCDDDCDGDGFBHGFFAHCFCFHECDGDBECCCDCEGEFBFEHHGAGCGDHAHGHEFDHAGBGBGHDECE,False +643,10.0,16.0,8.0,13.0,16.0,18.0,19.0,19.0,DBDFCEGABABHBFGAHEGFFDHCFCFBDHHACAFECHHHHGFGBEHEGEGEGFGBBDBFEFHFCEDECFAAGFGFEBAGHEHEHEGDBDFDFBEBDBDFDBGEHCAAGHGHGBGHGHD,False +644,23.0,23.0,24.0,17.0,10.0,17.0,18.0,14.0,BGGGGGEGBACCECHCHCACDBAEFEFHAHACFGGADDCDCDCDGHGCBHBAAFGFGFABBBBFBHGFAAADADCDEACDEACBHEEFCCHCHAFBCHGEGBFDFHEBBHBDBCHDBDBGFCFBDCGFGFACABBBAAAAAFDCDC,False +645,19.0,20.0,19.0,12.0,21.0,19.0,19.0,26.0,BCHEHEABABAHAHDHBEDEAEGECEBECAHDGCFEFCHHAHDHDHFBDACABGCEBHBCFHGCCCAEEDAACABBHGHGHFHBEBHDECEBDBCBFEFHHHGHGHGHFHFBDGEGACEFDFHFEFCGGGAEFDFGCGABFFCFCGBGAGFBAEA,False +646,24.0,19.0,25.0,16.0,26.0,22.0,27.0,28.0,DADGFHCDDBDHDHGGAEECHHHFCAGACFCFEDCCECEGFBFBCBGEHEACBCBGGHGAGFHCGCGEFEDAHAHFHEBBBHHAAEAECBGAAFBGBHBHAAFEEAECEGHGFCDCHHHHBDFGFGFGBEAFHFDAHAHCBCEHGHGFCDGDGCGEFABDBFBAAAHADEDEGCGHECEFEFECECG,False +647,19.0,19.0,11.0,23.0,12.0,13.0,15.0,22.0,FGFAADEGEAEADGDFHAHBHDGGGHDFBHBDDGDCDHBHBHEHECEDBDBEBHHDHEABCCGFAHGGEADAGFDAHEHDHDCDGDHHEHFFFGEGBDCACACDFDHBBBBDCGAAFAHABABACACFDFBBHB,False +648,14.0,18.0,21.0,17.0,4.0,13.0,14.0,14.0,HDCCBGAGBGFGFHCCACHCGCBCBEDEBCBDBHFCFCFGAGACBGFDFBHBADAGHCHBHFCACDFDBABAEGCHHDBDCFBECGCGBDAFFGHDBDBDADADACFDADCHHGH,False +649,18.0,10.0,20.0,21.0,15.0,23.0,20.0,19.0,CDCFFDAABAFGFDBHFHGADADAHGHGBDFCHHHCDCHAHADCDGDGDGCEFGFCECFCFCGCAAAAEAEDBDBFFHHHFECECGGEGAABHECFHDEDGHGAEADFFHGDGDGEEBDCFGEHFCGCECEDDFFFFBFBCBHHAG,False +650,2.0,8.0,12.0,4.0,7.0,2.0,3.0,2.0,BECADGCCCCCBCBCBDGGFECECDBDBHECEFABHBCEE,True +651,23.0,17.0,14.0,13.0,18.0,7.0,9.0,12.0,HGFCACACFCDEEAGBGBADADABCGDAEADGDBACFHBEDAABHBHGHCAAEBECECACEDECEGFGAAHABAEAHDHABABADEBCFCFBEEEHEBFBAEHEHDCDBGBHD,False +652,9.0,5.0,7.0,3.0,3.0,4.0,7.0,7.0,FHAHAGGGGHGCGCEHEAFAFCHDECHBABCFGBHBACDCDAABA,False +653,17.0,14.0,10.0,12.0,16.0,15.0,12.0,13.0,FFDCCCGHBHEFBAEAHDFFFHBBBBGAFABABAEADAEFCBDEEHFDACHCHDAFCFEDGBCBCBEBEGGGCHHDDAGAEAEDEDEBEHDHAHEFGFGFGHGAAEAFG,False +654,18.0,23.0,28.0,27.0,18.0,13.0,30.0,25.0,CGCBCACGBGHACACADFEBGBCAEHBDBCHAEDGDFDCCAEHDGDFDFAFBGBGEDCFBFBFDAHGCCCBGBHEHAHGGGCECEHEAGCGDGDHBBDGCECHAHDFDGEGAGDGEADHCACBGBCHAHAGBGHHCHCHGEBEAEDECHBGBGDGFGEGHCHBDDDCDHDFDHCFEHDBDBF,False +655,15.0,11.0,8.0,7.0,7.0,6.0,7.0,13.0,EFAFACBEEDCAHAHGEAEFFHBHBFBFHGAAHGHGAGDCBHHHABDBEBAGAGDDDADHBCBEACHCACACHB,False +656,23.0,17.0,14.0,15.0,23.0,23.0,21.0,14.0,DBBBEEGCGFABAGAHAHFDEEHECBHBFBEAEADGDACGFGFCFDFGFGFGBEBEDEHHCFEHAHAFAHEBABEDEFGFGBGAAECFCHCEAGDGDCBCAFHFDFDFCFEEEEECFDBGGGAAADBGBHDAGEEBHDAAAHFGCGFAFC,False +657,22.0,13.0,20.0,11.0,19.0,20.0,13.0,19.0,AAAEEECFGGCCCDBDAFHFAFCCBAAHBBBEBFBAGCGEGHCAEACDCEADBDEAFCDGECEGGAGABAHAEBHHHHHCFCFEHCHFHGHCHCFAFDFDFDHBEGEFFFFAEAECEDEDHFGABFEGCHCHAHABF,False +658,13.0,8.0,9.0,8.0,6.0,14.0,16.0,11.0,DFDAACADGHGFECCGBFFFHEAAFACAGFHCGCFAFDFBBHHFGAGABABAGEFEFGDEBFBDBGACHCHCHGDGHGHGEGDGH,False +659,24.0,22.0,11.0,20.0,12.0,19.0,20.0,10.0,ECECBBAAAFHDHDHCBGFGFACABAGGHADBEAFFDFDFDEGCGCBBBFAGABBEDGGAGFDAGHGDDAEABBGBHDGEBFBHDFGCBCBEBFDFDADADBBFEHEFEFDFHFEGDCDCDCGBGAAAAAGAFAHBGA,False +660,9.0,8.0,11.0,8.0,16.0,14.0,26.0,11.0,FEGEHCHBGBGEGHGHGEGHDEBHAFACGDGFGACHHGAFCGGFEHDFDEEGBGBGFGFGCCECFAFDFDHBGDAAHAGEGDGEGFGAGEBCCCCBEEGEFEF,False +661,21.0,16.0,26.0,12.0,16.0,24.0,13.0,16.0,AHBFGAHHBCBABABCCGBEFACECGHGFDAHHCCECFFFDFAHACACBCBGBDFEFEHEDACAEDEDEGEGDGBBBGCGAHACACEFAFDFAFBDACAFFHFCFCAGEGBFDFBFEGCFCBCFHACADDCHFHFCECEHHHCE,False +662,19.0,21.0,19.0,34.0,20.0,23.0,22.0,19.0,AFAFBGBGBABGDDADCFCECGGEAEACHDHDEFCFDFDECHHGDEDEGGFEBBBBBEFEDDFAHCBEDDBACDCDAHAHGHDCFCFDFEFEDHCHDDADBGCABDHEBBFBDCDHDEDEABDHEBFBCEAGGHFHEAGFGFGCGDGFGDGAGAGABFBFDDHDCDHHGHECDCFAF,False +663,30.0,32.0,21.0,26.0,25.0,15.0,23.0,18.0,GBDHGHGHGBGFGABAEEDBCBCAHAEEDFDADEGCCCGHDBBBEDHGGFCBBHEAACDBGAGBGFEAAAAAABADGGBGCDCFCFDFCBHAHBBBHBHGDBDEHBHBHBEAABABDDEAEDFDEBEBECEGEFAFCFCADEGCGBABABFBCEADAEGEGDCDGBFHAEAEFCDDHEHAHFDCDEDCAC,False +664,14.0,12.0,16.0,18.0,20.0,25.0,19.0,23.0,GFFDFGFDEAHBCEEHCFEEEABFGFGHGAGAGCGCFDBDBDEDEABABDBHFCFHDGAGEHEHEGDCDCFAAGAEEHFGFEDCHFHGGEHDDGBADDGHFHEHEHECFCFCDCAEFFFGFGCBHHCCFCFBFHFHEDADHHHHABB,False +665,1.0,1.0,5.0,0.0,2.0,0.0,2.0,0.0,CCCBGGAECEC,True +666,13.0,18.0,8.0,9.0,12.0,13.0,18.0,15.0,FADABCFAFAFGFGFBCBGGGFGDCDCABDHDAEHEDGDGEFFHCGEHHFHBGAGAHEGEGABFCGBGEEBEHFHBHBHBHBFBHCABBHGEEDCDBABABHGGAE,False +667,12.0,9.0,6.0,10.0,3.0,13.0,8.0,9.0,CBCHGHFADHGAGBCFDFAADDFCFHDAAAAAFCFEAAFADCDGDGHFHFHGBFBFBEBHGHGBBDFDEB,False +668,25.0,23.0,24.0,17.0,11.0,21.0,16.0,12.0,GDAFFFFHBBGCACGCECBHAEDBBFFFBCBCACACGBABEBEDDBFAHBHDAGAGBGBGAGBGAGEDBAFCCDCGAGHCDADACAEDFHACBEAACFDDBDBHBDBDFFFCFCFCFCAAAEDHFAFHCHCACHCGAGFFCEEBEBGDH,False +669,3.0,6.0,1.0,5.0,4.0,4.0,3.0,1.0,EABGBEBGBFBGDFDFDADEDBFHEAC,True +670,5.0,9.0,11.0,15.0,8.0,21.0,12.0,11.0,DFDCHCFFDHHAHACGGFBDBDCDCDAHEFFFHBDBDBEECFGDGHGBFCDADABHBHGGEGCCFFFFFDFHEBGCEFDFGFEFEHDGFGFC,False +671,9.0,14.0,11.0,13.0,12.0,14.0,11.0,23.0,HDHCHCFCFCHCFCDADADEHFHBAEGFGHCEDHFCCDEHAHFEBBBADCHHHHDHBHEDDDADHDBGBGBCBFHEBEFGBGHGFFHAHGHBAFAGBEFEBEHEGFG,False +672,3.0,4.0,0.0,0.0,2.0,6.0,4.0,2.0,HFHFAAGEGFGFABBFGFBEB,True +673,17.0,21.0,20.0,5.0,12.0,13.0,17.0,15.0,BCBDBECHCAAADCGGGGFBABABEBCBCACAGHBHDHBFEEEEAABCBCBAAHBGGCGBGHGFGAGFFCHGHGHBABFBFHCHADDFCCCECECHHEAFBFBCHHBCEGGCFAEAEGFF,False +674,14.0,34.0,17.0,24.0,19.0,23.0,30.0,24.0,BBGEGHHHEHEFABDCHCFBDAGBBBBDBFCFCFAHHEHAFGHGEGEDBDBDHCFCHCEDEDEDGCGCDDDGDGAGAGEGBHHCHADFDBBBCDDACGHGEGEHBGBGHFEFGFBBDBHBFBDGGCGCDFGCBBBDADGHFCFADGEHFCFAFGBHFHBGEAEBBBAFGGDGFEFBBHEHEBABF,False +675,22.0,22.0,20.0,24.0,22.0,17.0,36.0,34.0,CHGHGHAHAHCECDBGCADHEEGECDGBFCCHCHFGFGBBHFHFHEGFGAGCGCGDGDCBFBFEFEHEDECCHBGBDADHFHEBDBGFGBAHGHGEACGGAEAHGBDCDGDHFHBHCECBDHGGGGHBBDFDFHAAAAAHADADHGHEHAGFGDGAEDGDEEBHACFGHBHBHCGGGCAHEEAEHEFDDDGDBBBAE,False +676,5.0,3.0,7.0,7.0,6.0,1.0,5.0,6.0,EHCHEBAGEGDGDCCCCABHEGBAEDEDCDFDADAHHCHG,False +677,14.0,12.0,18.0,20.0,14.0,12.0,11.0,15.0,CCADHGFACAHGHDDDDDGFGHBADGBEBCCDDDADADABBHCFCFHBHGAGEEEEEEEGEFHCDFAFCCADBDCDCDCBBBBCHCBDAGAEHDHAHAEEHEHFFCGCDFGECFFH,False +678,20.0,18.0,16.0,16.0,18.0,22.0,18.0,25.0,DFFHFHFGFBADAGHCBCAGBCBFGFACBEFEGABBBEGHHFHFDFHEEGEBECFCEBEGGADEDEAEACHCHABEHAHAFAHAHAFBFAECECHCHGHAHBHCHFHGDCHGHEBDBDGCADEDGGFBFGDBDCFFEHDFDFDGDHCHBGAAA,False +679,13.0,13.0,11.0,11.0,12.0,13.0,13.0,10.0,DADAHACGEBDGEGEDEAACHFGEGEGFGFCFAFEBCBFEFHCCFCHCHEHAFFDBBBHGCEBGBGAAHFHGHBFDEGAGBBBBDDADADEDACFC,False +680,21.0,9.0,11.0,23.0,10.0,11.0,13.0,22.0,BHEFDAEAEGGAGBCHCBAAHAFDFGGGGBHADEDACFCFAEABHBHBAAADFFACDDDHDHCBCFHDHCHGDAHAHDDDCDADEHFFAFDEHHDHECDADAGAGBHHGHEHEHCDGDGD,False +681,29.0,26.0,19.0,24.0,29.0,20.0,27.0,23.0,AAHAECBCBAADACAFFGCEADCBGHGFEFEAEDEDBDHDEBHDHAACAHAEBCBDFFHFBFBFBFGFBEAHBCAEAGAGBEEEEEEEEDCABFGFBDHFAFAGBGHGCGEGDADHDFGBCBHBHACEBDADEDEDGGGGGGGBHBHDHCFGBBEHCCAHHFABDCGGECFBAHGDGDCEAEHECEGHDFDEDGAHA,False +682,12.0,18.0,15.0,23.0,25.0,24.0,20.0,8.0,DADHGFBFDADAEECECBFDHDBCBABAHFFFFEFEFBFBFBEDFDEAFCCHEBBGECCCCFAGBBDBGCEEDHGGEGEAEAEFDDDGDAFEGCGCGCFEDDGDFHEDGGGGGEBEDFDEDHBEBDCCEFFFEFEBABFGAGHGD,False +683,10.0,19.0,7.0,19.0,5.0,6.0,8.0,11.0,CHCGBDFEGADBBBBBEGHAFAHBGFACAGAHDBDBDADHDGDBDCCCEDDHDADADCDBBBHBFBDBDFDADEHHHBHGGEFBB,True +684,10.0,3.0,3.0,5.0,2.0,4.0,6.0,12.0,DBCHHBHEDEGAGAHFGGHFAAAGAGADBCHAHAFDFDACHHHHH,True +685,10.0,19.0,16.0,24.0,9.0,16.0,18.0,17.0,DGDFEBDHDADCDBDHFHFHAGCHCHAGEEBGBGBAFDHCBADCDHAHEEABDDFDFABBCDDADCDFDFBBGBGHECCGCGDECGDBFGGEGECHCGFFBFBDGFHBHBHBCGCGCGBDDDFHFHFHA,False +686,11.0,7.0,14.0,17.0,14.0,20.0,12.0,14.0,HDHABCEFFBEHCGCACACBHBGEGEFFFBGCECDCDEHEDEGFGFDDDDGDGAHDHDADADFFFAHAEDHFBADEDBCCGHAEEECFFEFCFHFGCGAHDFGFHFCFH,False +687,19.0,24.0,19.0,21.0,13.0,20.0,17.0,22.0,GBGCDCDHFCAHAHBFFDCAGBFBABCFFBFACBGHGHBFFGHDDADHFHFHBGGHGAFDFCGAGEDEGEADDFCBABFBABAHEDEGFGFCBCFDDADACECEBEBCHCACFEGCHBBBDDDGHHDHAHAFABDHEHEHEGEDBABCBDBHCHC,False +688,11.0,6.0,12.0,7.0,7.0,10.0,7.0,5.0,CCBGGGGFABECFADHEACFCFGFGEDFCFAFBHBCBHBDCCHCAAAAAEDDDDAFCFCEGEAEH,False +689,1.0,5.0,2.0,2.0,0.0,1.0,2.0,2.0,DHDGFGCBBBBBCHA,True +690,15.0,19.0,20.0,21.0,26.0,23.0,15.0,18.0,GBGBGEFEGECEDHDHDHDHDCGAEACGCFBFECCACGCDEDFDHDFBBBEBDHGHDCBAAAFBHADFBFHFHFHFEDDADEDEFCBBAEEGEACCHCEGACEDECECFFFFHAHEGEBABEDFBHEDEAEADFDCHFHFCGEBHCFFFGBBECGBG,False +691,16.0,20.0,16.0,13.0,21.0,17.0,19.0,17.0,EEBEDECEAEBBBBEHFBFBFDCDCBCBCAFGHGCECGGDHAHCDCFCEHDHDBBFHFGEECBGBFHDHGHEBEBEAEFBAAAAEAGGGFEFCFBABDFGFDFHAEEGHHHGDFHFGCGCGDAAACADEGBBCAHGEGH,False +692,15.0,18.0,25.0,15.0,20.0,16.0,23.0,15.0,DCAGACABGEGHGBBCAEGHHDAAAFGCBCBCGGDGCGCHCDCDAFCFGHGCGCEEEHBGGECACADEDFDFGFDBBFBCDCFCDCEEHEHFDBDBGEGFFBFBFEECHGHBAGABABEHEHGCEHBFDCCGDHEHEGBFAFAECEC,False +693,18.0,15.0,17.0,18.0,19.0,18.0,17.0,13.0,DAEAFACADHDHCFCBBBDFDEGEGEFDGBEFEBGHGHEHGGAFAFAGAEDEBHDADAEAEDEAHGHAHCECEHFHBGFAEAFBCGFDFGCACADFCGCBCBDAHFBCDEBCFCFGECDBDBGBGECECFDDHFG,False +694,7.0,11.0,9.0,10.0,9.0,4.0,5.0,10.0,CDDDBBCGFGDHDHEHBHEHEBEBEAEAFHDEGEDHBAAFHCBFEGCBCBCBAAHACCCGBHDDD,False +695,9.0,7.0,7.0,14.0,15.0,8.0,16.0,16.0,DFDCDCDEAHDDDBHHFHFCDCHCFBAEEDGAEAGGFGHAEECHGHGHEEGDGFEFEDEGBGEDDBHBHGEGFAHAEAHAHGBGHGHGDECB,False +696,24.0,23.0,24.0,22.0,20.0,19.0,26.0,26.0,ADGDAEBHCGCHCEADABGBGBFEEGFAFAFBFGDGDHHACDCHFACHCGGHGHDHCBGDHBACHBHGHGAAEBFAHGGDGHGFGDCDCGCDCAEGGGEEEEEHDFDAAAHADAFADEBBBHEHECACBEEEBABFCFCFCECFCHBHBAGABHHFHBHFCDEBCDGDFDFDCBFBCBEAGDGH,False +697,19.0,24.0,22.0,23.0,29.0,24.0,25.0,34.0,FCFEAEAHCGEDABFEFDHCHCGCGCFHABDGEGFGFGBHBCAEEHGBCBCBCGHDHFHABGHDHCCCAADDFDHDCDHFBEHEHEGFBBHHHADEEEBEBFACHHHHGHGABBBBEDCBBBEDEDFFFFFFHCHDAEFEGDGHFBDGEHHGFBDADECEDEDGFBFEGCGHHCHCHGHEFEAAGAGEGDGCAHAEAEBD,False +698,13.0,19.0,14.0,18.0,18.0,16.0,11.0,16.0,BDBFFDFDFGGHAHBHBHBHFGAGAHDHBEBDBHBFBFHCBEGEGEDCCCCBGHECDCACDBFCEDBDFDFDHDFEFHFHEHEFEBABDEHBCDDHAAADEBAGAEACGEAEFBCEGEDFCCAGE,False +699,20.0,17.0,18.0,13.0,20.0,22.0,16.0,23.0,ADHHHHFDFBFAGADBEFFFEFEGCFBDHCAEABAEAEBHFECCFDFHHHHHFHCHCHEHEAEBGHACABFCFGAGDFDFCBHGCFCBCHDEDHGHAFDFAGECECEFAGCDEGEHEAABCBGBGBGBABGEAHGEAFHFGCECADBDB,False +700,7.0,10.0,13.0,7.0,8.0,14.0,8.0,3.0,FAAEFBFCFBFBEDGHCCCCCEDEDFHECDBDGFGFADGBEFCFCGAAAHEDECACFBFBGGGFCFCBBB,False +701,16.0,27.0,21.0,29.0,23.0,22.0,14.0,18.0,ABAEADACBDBFAFDCGBDEDBBFBFADHHAABHDGABACDBDEAFCHCECHDDACAFDFDFEAEDHDFBFBFCEEBECDCDHABFBGEGFHFHGBDEDEDEDCDHDHFAGDGHGHGHBCBCBFHCEBEHCCDCBFBFBECFDGGGFCECEDHBGBCFEEDGBFBEHEDE,False +702,22.0,31.0,14.0,20.0,15.0,20.0,18.0,12.0,GHADBDAFCHAEBDBDBDFDEAAABADEDCAABBEGEGFGEGFDFBFBAEGBBCBCBEGDCDAHCHBADADGFBFBHBGBDCFGDGHCDCFCBEAGFGFHFEBECAFBFBHBHBFBEGEGEBEDAHABADABBGBCAAGDFBAGHCCFDFHF,False +703,21.0,26.0,13.0,16.0,14.0,14.0,14.0,17.0,CHABCBFGFAABAGAHAHAHACBDFHAHEHGCACDBEHDGBHCECEHFAACABHBABABECGBGAGEFCGDEFHBBFAFHFHAHEBEFEGBGBEBEDDDDDDDAHHCBCDDGEADABGBDBFGFBFBFBGEDCBB,False +704,1.0,0.0,1.0,1.0,3.0,1.0,3.0,0.0,DEECEGFGAG,True +705,7.0,6.0,9.0,6.0,4.0,3.0,8.0,5.0,AGABCBCEHFACGFHHCHEACADDDDGBGBGBCEFHBDEDACGCGCGA,False +706,6.0,5.0,9.0,7.0,4.0,10.0,8.0,4.0,BGHGEDCHCHCGCFFGDGDGCBCBAADFFAFEFGAGADFHBAFCBCEDEFCFD,False +707,10.0,10.0,4.0,9.0,12.0,8.0,9.0,7.0,EECFAEAHAHAEAEBEHFDFDAGCDHBHGGEGEGFDFDEBADDCHFDDBFGEGBGBEBEAHAGBFBABC,False +708,11.0,14.0,22.0,17.0,26.0,26.0,22.0,25.0,ADBFFHCHCHCDGFCFBHBHBAGACHDFEFHCBGECDDGEHEHDHEGEGEGECBHAECDHDCDEEFHFDFDABHGDEHEGDHDGFCCCHCHDHDHBAEEGEHEHGGGBBFEFEDEFHFCFAEHECGCAFFFCFBBCAFBCHEEGEGFFECGCGFGFGFAFAGB,False +709,20.0,25.0,16.0,17.0,13.0,14.0,18.0,22.0,CDEHBHBHAHBHBGDGEGBACAHAHGBGBGBAAAGFDEEBGBABABFGACACHGHDFDADHEFDHHECFDACABGHFHDDDAEAEDGDCDCFCBCFHBCBEBEBEBFCGCHFEGGDDBBBCEHGDACABGHGAFHHHBFAFCFHB,False +710,30.0,23.0,16.0,22.0,21.0,35.0,15.0,23.0,FAFAFAFEFEHAHAEBEFDFDBDHFCEAHHHHBEFDADHEHBCCCADEHFHFHFCGGDECGCBDBGAFAFBCDAHADBECEFHCBCBAAAFAGBFADDFDFHBGAAEABFDEDFHAGAHAGAGEGHFEFCABAFCBEBEBHFDDDFDADEEEFBFDACEGFBDBHBHBFGFBFCFGGHAHAFGFC,False +711,6.0,6.0,12.0,7.0,12.0,9.0,12.0,10.0,HGEDHDGCGCGBHBHGCFAGABCBGGEBCHCHFGDEEEHEHAHFHCGDFEFAFAFDECECDCFABCGEGFCEDE,False +712,23.0,31.0,32.0,27.0,25.0,14.0,31.0,14.0,CGABCFCEHDFDHEHBDBDECCFBDGHGAGBGCHCBAEHEHDFDBDCEFGCGCFBAGGGEFEABFBGEAAAAHAGACACECACBGDGDBHBCFGHGBCAAAFBDDDDDDFGFCECBBEEGDADCBEAEAFDGEGCCBCBCBDGCECGCGCGCECECBFBDBABDBDHDCEHEBECGAABDBGGGDEEGEBBAHGGDH,False +713,4.0,5.0,5.0,9.0,4.0,5.0,6.0,6.0,BEFEACAHDHDHGHBDCHCDEDFDGDBEFGDGDFAFBBGACHCG,False +714,18.0,19.0,22.0,14.0,25.0,27.0,18.0,19.0,GEHFCECFCAEFBFAHBCCEBFFEFECDADEDEAEFEBECECGHGAAADAGHBFGFAFHDEABBDGDEHEFEFDBCHEGCCEFBFEHHHHGHGCAFAFHFHFGEHEHCGDFEAEAGFFBADAFFCFABGBABFBCBGBGCDCDHFHCECECDHDBGBCBCGG,False +715,17.0,8.0,11.0,12.0,13.0,12.0,12.0,14.0,BAGDHBHDHABAEGHFDADFECDCGCGADHDHDHABCBHGAAFBFBEHEAFCFAGHEBCDFDFDCHCHCADAEHEGEAEGCGCFEHAGGFAFEFEAEAG,False +716,16.0,17.0,24.0,24.0,21.0,17.0,16.0,24.0,FCBCBHBCBCECDCDAFFHHHCHDBEFABAEDEDEDECFDGGGAEFEFEHCADAFACEEECFCGAEDEDGHGDGAGFBHDHFHCCGEGBDHGEBHHHEHACAEGFDFDHCECBADECHHHBBBFBFBDADCCFCDCBCDEDHHCGDDAAAHBHGHGDGF,False +717,30.0,23.0,30.0,24.0,12.0,21.0,21.0,16.0,ECEDACAHEHCACECDCGCBHAGDFACBCBAFGFGBACCCCACFGEGFHHAHABGBEFFBFDFCGABCDCBBBBBAADADGDFDFHFDCDCHFBFAAGAGAGAGFCCCHABGDGDBDCDEBHDCDCDBGFFHHGBEAAHAHDFDEDAHAGDCDBHAFGGGBABDFCACACBCFEEAE,False +718,8.0,9.0,11.0,13.0,10.0,18.0,7.0,15.0,BHBGDHDHDEAEFFAGAGABHFFFADHDHDGAFCDCAHBDECFAHDHCCBGHFCECEHEFDBDCDGEGDBHBECFCFCFHBEFFFFFHFHE,False +719,12.0,23.0,32.0,23.0,25.0,25.0,24.0,32.0,ACHDECHBHFHGHGHDADAGHCCEBEBCCGHFFGFCBEGCCDDDBGFDHDHDHGFGBCFCGCDCDCDCFGEDBDBEGGCFEFEHEBEHECBFDCDGBGEGBGEGCFEEECGFGADCFEAEADBBCECEHEBEDFHFCFCAABGHHHHHFAFABCCHCFCAHEHFBFBFHCGFBDGDEBHBHCECGDBAFHHHHHDH,False +720,9.0,6.0,1.0,2.0,6.0,3.0,3.0,2.0,AAABABDBGEHAGABCBGFHEAEDEAEFEFBA,True +721,4.0,4.0,5.0,4.0,1.0,4.0,3.0,0.0,BGBCACGCDDFDFABACECBFAFDG,True +722,16.0,8.0,13.0,19.0,18.0,17.0,9.0,17.0,DFEFCHCGADHDEDAHEDEBFHFEFEAEDEDHAHADCBAFACAHEHDCGCGCDCDHDFECEBEDEDEFGGABFBFGCACFDFAFBDGFHCADHEHEGDAEAHHHBHFHFADCFEBGA,False +723,20.0,21.0,15.0,7.0,15.0,20.0,22.0,15.0,AFCDCFCFGFGAGBCACBHAAFGFBBEEAEGHDEDBHBHEHBCGEGFACEGHGHGCGEGECAFFGEGEGEGBBFAFDCBCFCFADADBHEAEHGBGHGBAFAHCBADFBHBCBFAFHBABABAFABHFGFGEHCG,False +724,22.0,23.0,14.0,13.0,20.0,26.0,11.0,21.0,DEBABADADEGBGBEBHBCCAAEAFFDAAAAFEFAFGFCFCBHBCFFFCFBFDFEHHDHCHCFDEDHBHBGAACEFAHHFABAEEEEGBCHCECACGDHAFDFHFHFEFHAGGGFCHBBDBHBEBFBFHHEHBBBABEEFGFEDGDAHAE,False +725,21.0,25.0,25.0,29.0,21.0,32.0,25.0,20.0,FGGGCGEGDFAHHHCCCGAEABFBEBDBDHDCDEDAFGDGAEFCFCEAEADABCBGGGGGCDCDCFFFEHACBCBCGCFCFDBDFCFAHBDDFDFBEHEADCDFHEHFFEGGDGFHEGEBBBDHEAEAGAGAHBHAAGAHAHDDCBCFFFHFEDGDHDBFBEAHBFBEDFCHGFGDCFEGCHCFBFDEDFDABBFBCB,False +726,16.0,20.0,16.0,17.0,10.0,18.0,13.0,17.0,BBBBGCACACBFBABFBCDHGBCHCBADABFCFCFGAHEGBGEEEFDGDFAGAGCBCEFHFHGHFHAHFDFCHAHAGEBDBDGDCDCHFHBDDADCBFADEEEHHDGFGFHADEDHFHCBCBABADF,False +727,10.0,29.0,22.0,26.0,22.0,17.0,21.0,19.0,BCBCBCBDAFHFCECDCDCBHECFCGAGDGBHFDGDGBGBEDEDEDBCBAFAGHBHDHAADBDCGFGHDBDEGEFBBBCBEBEHECDHEGDADCDHDBBGCEHFGCAEAEBEBFBHADCECFCFEDGHGHBHFHGHBCFGBCEFDHGBGFGEBEHEFFDDBDECGD,False +728,11.0,13.0,13.0,11.0,13.0,20.0,15.0,18.0,EFFFEBCDCHCAAAADFHFHGAFDFHFCFBEBGCGAFBCACAHAHEDBBGEDEDCDGBGFGFGCHCFFDHEBBCGGGGGDFHAHDHBFFCHHDHEHEFBHBHECAGEGEFEFBH,False +729,26.0,25.0,13.0,24.0,26.0,16.0,21.0,19.0,DBDFABGGFGHEHAAAAABFBFBGBDBABAGEGCGFEEGEBEDHAEDCHABCDEFAFAGDHHAHADAFAFGBGAGHBDGCHHHBFFEAEDBDBEHDBBEDDHDHDCBCBEHCACDHFCGAGEGDDBEBEBEAGAEADABAFFFFEHGCGCEEEEBEGDHDGECEABHDCD,False +730,16.0,17.0,13.0,13.0,6.0,15.0,8.0,16.0,CCHDADACCDBABEBHDFBEAGBGFCECHBAAEAEDEGCHCHAFBHGHDBDADAFBDBGBHCHCAGAGHHCDCFFDFBFBADFBFBFHAAADBFCFGFBFHHHH,False +731,16.0,23.0,24.0,23.0,24.0,17.0,32.0,25.0,FFFFFFFDDEDGGHGHGHGFDHBCACGEGEBEBECFFBFBDECCDEHCFGEACHDHDHCFDHEGABHEGBGEAEHBAGCGHGHEEEDEDHFCGDGBAHAGAGDGBACCEAGAGAGAHFBCHCGCDCHCHBDBGBEBGCDFDBCBHEHEHGCGHBCBCGCAADDDGHGBDEDEGBBDFEAEGBCH,False +732,2.0,3.0,2.0,0.0,1.0,3.0,2.0,1.0,FCFGFHCBGBAEAB,True +733,6.0,2.0,3.0,2.0,1.0,4.0,1.0,4.0,BFFCHCHCHAAFADBGFDAHAEA,True +734,5.0,4.0,6.0,8.0,4.0,8.0,3.0,7.0,DGHGDEDEFAFBFBDDEAADFDHCHFAFBDGHHHHCCCCFCFBEA,False +735,11.0,7.0,8.0,6.0,4.0,4.0,8.0,5.0,CHCACAGAEDFDCBHDHFHBCDDHAFGGGCACAGAGBBBGBEBDFAAGAECEA,False +736,20.0,16.0,16.0,26.0,10.0,23.0,15.0,12.0,BDBHCCEBDBACHCDFGFCADHDFDHAECDAGAGCFEFCFEDDDDDDDCFHHADFDABEGGGAGAGADABAFCFAFDBEBEGACADDDHAHBECHDGBGBDDEGEGDBFCFHBADGHGHFFFBFAFAFCFCFBFCFBA,False +737,23.0,11.0,24.0,14.0,10.0,9.0,22.0,11.0,FHADCDEAAAABDBHAFADADFCGGGHGAEAHCGDDCDCDHAHCGGGGCACFCBCBCGCHAAFAHEBADAECGCGCGDGECEDGBFCDBAGACFHAEGCGEGBGCECHGGFHFABABABCCDCE,True +738,26.0,23.0,28.0,29.0,22.0,16.0,18.0,26.0,EHDFFHFHEAFFBBEHDBBBDBDCGEGEGCBCDGHAHDEDEDFAFGCCCACBDAGAEFHFHADAFHCDCDBDHAAAAAHCHCHFHFEFHCHFBAEDHCBCBCBEBDADGDAHAGACACBHEDDDEHCHBDECCGBGBHDCDHDBGCCBGDGCHHGFBAEGEAFACACBCEEEEHEGCGAADAEBGDDD,False +739,8.0,2.0,10.0,6.0,9.0,6.0,10.0,6.0,CGBDCDCHHEEAEACAEEGFHFDDDDFGFEAHCCCCCBFGAGAGEFAGAGHCEGEGH,False +740,11.0,8.0,17.0,13.0,9.0,9.0,18.0,8.0,BGAGBECGDGHFHBHBGDGDGCCCCCCFCFDFAFHBDADGDGBBCACAFEDGDHCECHAEEEBDCGGAGFGCGDAAEDEACHEHCCFGAGDGF,False +741,4.0,2.0,8.0,8.0,5.0,1.0,3.0,4.0,CECEAEHCCADDHDHGGEBHBECFCDDDDCDAGAC,True +742,2.0,9.0,1.0,2.0,5.0,5.0,1.0,4.0,CBHEDBAFFDBABEBEBHFHBHBFBGEFE,True +743,18.0,19.0,21.0,21.0,22.0,11.0,26.0,21.0,EAACDDDHDGEGBHHHHEBEBABHEHBFGCGDGEGCDCDGGCGHFFDFBBGACADADHHADCDGDGBCCCBEDECAGHGHBFCFEDEDEGGCBEFEBEBEHADBHBGGGADADFGFDAEAGBBHGDBHGHCHCACACAEFEGHCECEAFHCHBGEGECA,False +744,31.0,23.0,20.0,24.0,21.0,22.0,28.0,21.0,DADEBEBEDADABCBFGGGGGHGHAFFGBGBGCGDGFGHBCCFDEHEADABAGGBGFCFCAGAHHEDBHBHFFEHAGAGBCDFAEBHDDDDEHHACFBHDGDGACFFBDBAAADAHAHCHCEGAHAGEEEEEBHFFGADABABEBEBCDCBHFHFAADFCGCGBAADDDFCCCHFEFECEAGACAGDGFE,False +745,5.0,11.0,15.0,7.0,10.0,9.0,7.0,16.0,EFHFBCACFCEHBCBABABCECFHHHHFEFHCHCFCBHHGGEGEDDDHAFGEGCBDDDHEEAFBBCHCHEHGHBCBCDCG,False +746,1.0,0.0,6.0,5.0,2.0,2.0,2.0,0.0,GDCDCACECEDFDGCCFD,True +747,14.0,8.0,8.0,12.0,14.0,15.0,12.0,12.0,HCHDFEEGCBCDCAEEEBEFEFCABABFBFDEGFAHEHAHCHGGFCFDEDAHCHDFDGDGABHEAAFAFHFEEGAGDDFBHBHGDGEGAGAFAFD,False +748,23.0,22.0,15.0,27.0,27.0,24.0,31.0,19.0,CFEFAHGBGDEAEBEAEBHBDDGBFAHCGFHFHGEGFAFADBEFHBEBCCFCGEGADBBGGCGBGHHBEGEGABBEEEAHAGEGFGAGFCCBFAGBGFGFGFADDBDBGBFEFGFAAAABHCDDDDDDFDFHFHBGDEAEDDDEDEGEDEDECHDHCFAGAHAEAGADFGHEHDHCCGEGEDBDFCHC,False +749,18.0,23.0,17.0,19.0,17.0,23.0,21.0,21.0,EAADEDBDBFBEECFCDEGFDFHBDAFFBCCCGCHCHAFAFAGGHGECECEBEGAGDGDHEFEHCBAADAFBFBHBABGBGCFCDHFBDEDECFGFBCHHDBBCHDGDFFBFBGDGBHHAHABADADEEGHGHBHFFFFEFGCGCDEHHGHGAAAGBBH,False +750,26.0,15.0,24.0,31.0,22.0,18.0,27.0,36.0,HFCEEEDBCEHFDCDCDGDAHEDGBCCDCGHDEECFHFAFADHFCGEEAEHEHECGABAHFBFBFDACBDBDCDHDHGFBFACAHAHABAHHHCDGHGHGHAABFHFGGHADDDDDADCDEDGDEAGGGGAGBGACCHBHBFDDEEHEDDHCHCHCHGFGAHHHBHFGCGHEEDEDFBAGHGHCECGCAHAGFEADAGA,False +751,2.0,2.0,6.0,6.0,5.0,4.0,2.0,6.0,DCHAHGHCHCEBEGDFCHCDCFEFEDEFHADBD,True +752,12.0,16.0,4.0,9.0,13.0,13.0,11.0,4.0,EBEBDBDBFAHAHADAGBCBFHEEAFAEEBEFGFEFAAAGGGBAFCFCFDGEBBBBBBGAFEEDDDGAGFGCEFEGBDDFHB,False +753,20.0,22.0,13.0,25.0,23.0,25.0,27.0,11.0,DBDAFFDEDEDEFEFDBCFFHDDEEEBEFDFEFEGBGCHCEBEHEHAABAGGGDEAFDFBGGGDFAFAFACHEEBHACBFECCGGGGGGFDFAFCGEGEFHBDBACAHAEFDBDFGABFBEGCGCDHDHDGDBDBDGCFBGCAHGDGBBFAFABEGEGABADADGB,False +754,13.0,24.0,24.0,21.0,25.0,16.0,20.0,11.0,BHBDGCGFGFGFGHGHBFGCEEFEFBAHEHEHEBCDEDEDBBCBCEFECGCDBACAGDGDBBHCCGDAAEAHCEFECABABDGDGCBEDHGFEDEDBGGCACDDBEBCBDFGGGEEHECECEFDFDBBBDCHAFDCBCBCGCFFACAEAEDBFE,False +755,21.0,23.0,12.0,20.0,22.0,23.0,13.0,24.0,FBFBCBFBFECEBHBHDHBBBFBACGBGBDAGFDACHHGCGHFDBHEEEFEAEBEBFGAGAGEDDFDFEFBCAFDFEAEAEDFDBDHECDCFCEAHAFEEHAHGHGHCBDAEGHBDDDBDEHGBAHAFCHGBFHFHEHEADHFHFHFDEBCAAAAHAD,False +756,9.0,16.0,8.0,17.0,8.0,7.0,7.0,4.0,EFEFGFGCCBABHBDDDDGDABBGBFBFEACDBDEDHCGEGBCBCBFDDDEAFABADAHEBADHDCCEDGDBBBAD,False +757,15.0,20.0,18.0,27.0,18.0,16.0,16.0,19.0,GHFBGBCEEAHDBDAHAHEBFFDDDDBFBEEAGBDHDBEGHAHADDEDCFCFBHAHBHDDGDGDECECGHGFGDADEFCFCFDADBGEEBCDEDGABABHBHBHCDCECECEGACCEABFBFBCCHABGHFHFACDDDDDGHECGFGFH,False +758,24.0,10.0,20.0,10.0,13.0,18.0,25.0,18.0,HEHAHAFAHCGCGCHEBGCGHGHGFGCGEABGHGFGHCHEAACABAHACFEAGCECBGGGGGACDFHFAFDFDFDFBEEAEAECFCAADAGFCHHECFHGAGHGEAHFGCCDBDBGACAGADABBDBDCFAFHGEFCF,False +759,5.0,2.0,3.0,3.0,1.0,2.0,7.0,3.0,CFAGGHGHGHBDGDGACEDACAGABF,True +760,23.0,15.0,19.0,10.0,31.0,25.0,21.0,16.0,FGFGHGDGBHACAFAFEFEGEBFGFGFECEDBFEFEHHCFAEACFBBBAFEDCGCEAECFCBBHEGEDEAEFBFGFGADCCCBHAAEEBABAHAHACECFHFEDEABFEDEAEBECACECGFGFEAGAFEFACHGDGAEAEGHHHHGDCBEDEHFHGGCG,False +761,4.0,5.0,6.0,6.0,5.0,5.0,6.0,6.0,EFBFBFGDHCHFEFGGBDAGACHCHDHBAAECCBCDEDEDGHG,False +762,5.0,7.0,14.0,5.0,9.0,9.0,6.0,9.0,EGEFHBHFGFHCEDEBEFACAEAECHCHCHCHBGCFDFCCACBCDHDFGABHBCECDGGEFCFB,False +763,7.0,10.0,9.0,14.0,6.0,13.0,15.0,4.0,FHBHAHAFAEDCDEAEHFDDGFBFBFDGGFGBGBCBFDGDBCGEGECAGAGDGDFDCDCDFGCGEBDGFBACFBFDCG,False +764,18.0,17.0,21.0,10.0,17.0,19.0,30.0,14.0,GFCBGAFBBEFFCGHGEADAHFHEAEAHAHFGGGEGECCFAGAGFFCACBFAFAFGGGAEHGHFHBHCACHFAFDEDHGEGDFBCGCAHGCEBEHCBGBDDCAGBDAGECECACBCBCGGGBBBBBECFCFEFHGDGDGDGEGEGC,False +765,16.0,9.0,24.0,14.0,21.0,12.0,17.0,12.0,FCCCCEGDGDFBEGCBCDDDDCHFGACDHECCCEEAHGHGCCCFEAAADAHGEBEFDDDCDCEAGCGDHEAEAGADAGEFCFCFGFGEAFHEECECEGHGBFCECEBFBCAEBGBGHAHAHAHBE,False +766,2.0,5.0,3.0,5.0,5.0,3.0,5.0,14.0,GCCBCDHEEEFHHEBEHGHBHDHDHAHFGAHDGDGHHHHBFB,True +767,25.0,19.0,25.0,19.0,30.0,21.0,34.0,24.0,AABAGCCCGCDFDAEECGCHBHGHGHDAGCGDFDCEGEBAGFEEEHHAGAGAGFECEHGCECEHFHABEEEBEFEBEFEBCGGGDGABEDEDADGFGFCHHHHDDFBFBAEAEAHGFCFAAAAABAFHECGCDCGFADDBHBGCEHFBBGDHFAFHBHCHFHAGGGGGGAGCGEDEBEDECHFHGBDEDBFGCCCCE,False +768,25.0,18.0,18.0,14.0,17.0,14.0,28.0,21.0,DBBECABABAFFCHGBFEAEHGGEEEHGHGAGADAHGCCFDFDGAFCECECDBBBFBDHHGHEHBHAHGCGFGHHCCFAEAECGAGFHHCEGGGCDCEHEHEDGDHDAGABACCBCBGFFBBHBABADAGGGGHGAGAGAECFBAGAFADAEHDD,False +769,1.0,3.0,1.0,7.0,6.0,6.0,6.0,3.0,EFGFHFCEBGHFBDEDEHEAFDDGDGDGDGBEF,True +770,10.0,20.0,19.0,21.0,15.0,21.0,16.0,16.0,CDHDGGGCGEGECDCDCDABFBDBFBFDFHFHDDBEAEHBGBGCDBGBCHHDGFGCHDHCGCAAHABAFHHBDEFEFCFDFCFCFAHEFBFBGHGDDDCBEGGFEBEAEBDBHCHAEFCDCBFEFEBHCGCBFDFDEA,False +771,4.0,6.0,5.0,4.0,2.0,2.0,2.0,5.0,DBACDGDBBHBHCFDECECACAHAHGBFBH,False +772,20.0,21.0,27.0,26.0,23.0,24.0,13.0,18.0,HHGDAACADHDEDCABDHDFCFDBCFCABDCCCCFFFDFBCBHBGEGHGADACFDGAADDDDDECEHEHDFEBEFCFHFAFCFCFAFCHHHCEBEBEGECECFCHEFDCGBAFADAEAEDEDEFEHEGDAAEBCAEABBFBFBEADGCHDBGBDCDFGGBCBCBEHGHCHBF,False +773,23.0,11.0,12.0,12.0,15.0,10.0,15.0,14.0,HHBEBEDEBGBDFCECGCGEGCHDHGHGBCHAGAGAFAFAHAEEEAEAGBGEGCGAACABBHDABFDFAHADGHFBCDDHAAEAEAEAEACDFDEAAAHFDCCGCHHGDBFF,False +774,17.0,24.0,28.0,15.0,15.0,16.0,18.0,18.0,EFEFEBGCDADCEHBHBHBFBECECBFBFCGCEDEDCCFCGCGFGFACCDFHAHGHBHCHEHECCCGGFCHCADBBBGHHEGCCCGCBHGEGBBBAADCDCDCDADADABFHFAGBDBAHGBBABFEFGBEAHBGCCHFHGDABACAFDEA,False +775,3.0,0.0,2.0,1.0,0.0,2.0,2.0,3.0,AGHGHFDFCHCAA,True +776,17.0,9.0,11.0,6.0,12.0,12.0,17.0,14.0,GCGDABAFGFGCCECFABAEAEBGADHHEHAAAEDEAEABDFCGBADAEHGHFFFGAGFCFDBHBFGHHCGAGHGEGHBHCECEAEAGFCFCBHGHGH,False +777,4.0,6.0,1.0,5.0,7.0,2.0,6.0,4.0,HEFEAEAEDBBGDCDHDFEBAAHEHEDGBBBGGGG,True +778,6.0,7.0,4.0,4.0,5.0,13.0,4.0,5.0,HEHEAFGFAFAFBGBAFFFDEDECBCFGDBEHFAFBFDFHFHGBACCB,False +779,9.0,7.0,5.0,6.0,9.0,8.0,7.0,9.0,DGBEBEDHAFAFHFHFCFCEDEGEDEDGHAFBHBAGAFBCBHFAGADAECCBGEGHHEHA,False +780,19.0,21.0,16.0,16.0,23.0,19.0,26.0,22.0,FFCAGEGEGAHBBEBEGCDFEFCFGHHDHDHDBEFFAGEGAGAGAHEHFAEDBACCCEDGBEACFCFEDEABABABFHFBGBGAGEHHACBCGCHCHGHEABACDBDHEGFGEADHFBDCDCEBBAGHGHEHEHGHDHDGDGFHABECEBDGGFGBGBEFFF,False +781,15.0,24.0,23.0,18.0,23.0,14.0,17.0,21.0,FEAGCCBABABAFAHCDGHFCAEGBGBGHHBBCBFBABAEDEDADHFECGDGAHEBEBECCGCHCHEBCFEDDDCGCGDGDHEFGGCHCBEFECAHDEDFDEHEGEFBBHGGCECECFBDBDBAHAHEHDHECFBFDCECABABHBGBCHFHDHE,False +782,14.0,24.0,23.0,18.0,18.0,17.0,19.0,17.0,GAECGCBBAGAGAGFEEDDFBEEEBBGGEECCCCBEGEGFGDGCHCHCHEADBDBHBHFGADBFGDHHGAGADDDDDCBCDHFBFHDAGFHFHFHCBCFEHHHBFCFHFCGCBCAGFEBDFCECHCACBDBCEAGDBDBEBEBEBABAFC,False +783,17.0,21.0,14.0,26.0,20.0,11.0,14.0,15.0,CHAHEHDHGCCADABAEDBDBFAEABGDDCGADADBBAFCEGDBEBDHGEGFHEHEHEFCFDGHADADBDBDCDCGBABDECEDEDFDCDCDADEDBDHGBGBECDHEHFFBAEAEBEBGHGEBCGGBEFHBHCFAFA,False +784,9.0,13.0,21.0,19.0,11.0,19.0,13.0,15.0,ADHDFGEBBCCDCDCFHAGDBCBCECEAGAHCDEAHBHEFEAHHGDCHCHDHDHFBEADFCGCHDHAFBGBGBEFDFGFECACFEFGFDCDEBGBGCFBFCDGDGCFDFHFHFCFCDCDB,False +785,3.0,4.0,10.0,4.0,5.0,8.0,5.0,7.0,FCFCGCGEAAGFCECECHFFDHCACGCGEBHFEFHBHDFDBDBHHC,False +786,13.0,15.0,20.0,21.0,12.0,14.0,14.0,18.0,BFDGDGDADECHCHCEDGDBDGHCHDGCABEEFEFGGDDBDHDHDGCCEBDFDFBHBHBHFHFAECEBAAAFAEAHBHGHDFEFBHBABECCCCCDEGHGBFFGHCDCBGDCCCFHDCACAFGHADA,False +787,12.0,21.0,22.0,19.0,22.0,24.0,29.0,14.0,CGCGEECEGGBEAGCFFFCDCEEACFBFBGBGDGDHDHCBCGADEHGHBFGFGFDFDBGEGEBFCFCFCFABDBCAFFGDGBFHCHEECDFDFCBEBFHGCGEGAGAFDFCEGEGEAAHHHBGCGCGAGDGDBDFGEDBDFDBCHADEEGEHEHABBFEHBCB,False +788,17.0,13.0,19.0,20.0,16.0,16.0,19.0,15.0,BDCEGHGDAFFHFHDADAHEEEECFCGDHBHGGGAGAEFGBCADGCCCCCCGCDCBEFEFDFECADABAFEBGBGAADGEGHADABHFHFCEDHDGGCDCDFDADGHCFBBCBCEHBHFHDEDEDEGHGAAAFBF,False +789,28.0,17.0,13.0,32.0,28.0,13.0,27.0,17.0,AEADADBGBAFAEADGBAAGDDEGEBEFCFCFHFHAEGEHDHAADEDHDCFCBAEGEGDGCGAGBGBGBFDDDEDGBGBGBDDGGADCDBGAEAGDBCADEDHBABAECHCECAFEHAFACDCDGEHEHFBEHDDDDFEAABDHGHGHDAGECEGEGDHEAEGEGEAFHDHDFAE,False +790,20.0,14.0,14.0,14.0,17.0,15.0,16.0,18.0,FCFDDDHCHCEGHADCBGFEFCFEEEEBEADABHBDEFCABABAGAGEHHBHBDAECGDEAAAFAEADBHCGGBGBGBEFEFEFABAGFHHGACDBDHHGFDACEHDHGHFCFDHCHCHCEFAGAGAG,False +791,18.0,17.0,18.0,19.0,20.0,20.0,6.0,18.0,FHFHFDEAADAFBBACGHDCDFAGGFEFADEDBFBFECEAFAFACCCEFHBHFHBBACHFDGDCDHDHGBAHCDCBHBEEEEAECBABCBCEDHDFDEDEDEAEADACAHFHFHEDCCABEHEBEHCFBFGFBDHC,False +792,14.0,17.0,13.0,12.0,11.0,16.0,16.0,11.0,DDBDBDAFBDBFAFAGBDEGCCECHCHCGFABGBCFEFECHFBABAEECBDHDGDGHGHGFCFHEAEGDHBCBEFHBGAGACAHAFGFGFDEABFBABGFGFGBHCAEDC,False +793,9.0,19.0,17.0,11.0,13.0,16.0,16.0,13.0,DCGHBFFCGEEBEGGAGFDEEBFGHCHCDFDBCBCFCFCGCGBBBCBCBFHFGCAEABHBABGBDBDFDHAHFGFHBBBGHGHECFDECEGHGHDAAGDBCECDAEAEFEFCFH,False +794,18.0,14.0,23.0,18.0,18.0,15.0,28.0,20.0,GBGBGFGAEFECEBGBECECFGDEDGFCFGGHCHCFGDAHHCHCFCFCGCGCEAHAEABACDBDBAGGCGHAHBDFDHEHEGAGEGEHHDCDGFHBHGHFADECACAEABFCAHGHGBDCDFDFBAGACDGGCDBGGADHDBFHEHEAEGDCEC,False +795,2.0,6.0,5.0,6.0,3.0,1.0,4.0,1.0,GDGECBCHDEDECBBFBCBABDGDGACD,True +796,20.0,15.0,22.0,19.0,22.0,17.0,35.0,28.0,EHGHCDCDAEBCBFBACHCGEFEFEFDFHGHDCGAHDCGCDCACBGEEHEHGGGEHEFEGGAAAAHAFFECCAGHGHGHBACACDCFEAGGGGGGGCGAFCBEHHGDGHGADAHGHBDGAGBCDCABAHDDEEFGGEHHHBBBDBDHDHDHFHEHBCDCGFGECEFFGFGEGHFBEDA,False +797,22.0,14.0,14.0,13.0,13.0,14.0,15.0,9.0,HCHGGBDEFAFAGAHDCGCGCHCGFAADEDEABAGABFEFEFEBDFGABHFDAABCHCFCADBBAGDGDGDCDFEFGBDBDFFGCBCBEBGAAAAAAHEHEBEGCAAAFHECEC,False +798,15.0,14.0,14.0,26.0,14.0,22.0,16.0,23.0,DCGAADDDHDHFFDBGGFGEGBBDHAHFFFFAFCFBDDFEAEDHDHGHGDCHCFAGBDFCFEFGAGHECFCEDAHAGEBFBABDEDADCDHAFCFAFHBDFAFADEGEHEHBHGFGCGHGCDCDBBHHHHBCBCHDEDEDEDHH,False +799,27.0,20.0,19.0,24.0,17.0,17.0,26.0,21.0,GFGDGDCDFGBGBEBGBHHFDADAHEHEBBBHFFGGCADACAGHBHAAFACACHBECEFAHADGDAEHECFABCGCAHBHAHDGEEHFDFHFDFCAHDBDBFEGDGDGHBDBGAGEGBGCCECEBEHAGABADADADECGCGCAFHGHBFACACFDEDEBGACAGHGFDDD,False +800,14.0,22.0,27.0,22.0,29.0,27.0,20.0,20.0,BCBCBCACACAHDBFCHEHEFBGGCGCABBHBEEEBECECBDHDEBAACGCGFGFDFGBCDAHHHHFFEDDDDEFFHFDEGGGHEAEDEGBBDFEADFCGCGCHFHGHGEDCHFFFDFDCHFBCBCBCEEEGACAEHEFGFDFCFBAEHECGDEFGHGAFAEBBBBDCEHFCFEFDCDEDE,False +801,5.0,1.0,4.0,0.0,2.0,1.0,0.0,1.0,HCAEACAFBEACAC,True +802,15.0,14.0,17.0,11.0,11.0,11.0,14.0,5.0,DGAEAFAFCFDADEFEFCACGEHEFGCHABACABHBADDFDFCGEGEAAACHCGDGCGBEBFDCABBBBDBABFGGCCCEGFBBBEDAHCGCGCGCED,False +803,19.0,24.0,22.0,27.0,21.0,24.0,25.0,26.0,HFAFEFEFCCCHCHGDDHEHEDEACCFAFBHDEDEBGCGBFAHAHAHFGDBAGAHBHFEFBFEFABCDHDGACACBGDGHAFBDBCFHFHDHDGDADBCFGGBDACGHGCECEGGAGDGDGEGECADHDABGBDDCECEHFHBGGEGEHBFBDHFACAFBBBBHEEEGCDHGFDFDFEFHDHDCBBBC,False +804,14.0,12.0,12.0,16.0,9.0,14.0,9.0,8.0,ABCBAFDEDFDHDCDBAFCBGBDBEAEGEBCDGAACABDECECEHEAGHGDBHFFFCGDADFFFGFDBDFAHCHCHCHCBADADADABFFGGEF,False +805,10.0,5.0,7.0,4.0,17.0,8.0,9.0,3.0,AAGAGAGAGAHECEFEGEHEBEAEFDADFEEEECEDECHGFEFAFBEDFGBEACBCEFBCCGG,True +806,16.0,25.0,13.0,17.0,23.0,16.0,21.0,18.0,CBGEEFEGBBBCHGHBAAAAGAGEGCHCEDBBBBBHHHHDAFFEEDEDAAADFEBHGHDHEGEGHCECEBBDADGGGGGDGHEHEHEBBBFGFAFDFEFEBEBCFFEBHBECDBDFAFAGHDFDGBHDCFCAABCBHEGDGDEBGCCAF,False +807,3.0,8.0,5.0,8.0,9.0,8.0,9.0,9.0,HFFFBHCHEBEBEBGBDCGCECEFDFBFGAGHHDHFACHDHDEFBGDGEHEADGDBEGG,False +808,18.0,19.0,24.0,19.0,15.0,25.0,23.0,17.0,CDGFCFCAGHEAEADCGEGACBGFGDHEEECACECECFAHAFDCDHDFEBEHDFDFHFGBEBGGGBBBHBHFAEAFGFAHAGAFCGCHCHGHBCDDFDFDGDFBEBEBFAFCFGDCCHGHADCBFBGBGHFCGDGBCAHFDFCFCBCBDAEABADGFGHC,False +809,24.0,16.0,20.0,18.0,20.0,16.0,26.0,18.0,HBEFGCGHAHADGCACAFBFAFCEBGBFDGAGAEHHCDDHDFDHDHDEECGABCBFEAEHDGGGGBABGFEBCAEGBCFCHGHBHBABGBHFEFCCCCAHGEGEFHFDGAEBHDADCGHEAEAEAEAEGEDCDADGDGAGAGAEHDGCCFCFCADBGF,False +810,7.0,10.0,7.0,14.0,17.0,13.0,14.0,8.0,DEAEGEFECACABGEGEAHGHGHAEFEFECHDDFDBDBCBDBDFGCGEBECEDDDADBEFEBDFGBDFHGCFFDGGFEHEHFHBGAGEGF,False +811,11.0,12.0,11.0,18.0,16.0,11.0,15.0,16.0,EBEBABDHDHDHEHGHFAAGGCAFEDDGEFAFHDBDBDHEGGGGBCBCFDDDDDEDBHFEBHCHABEFEFGHECECBFGGGEDHCHCGEGACAEAECHABCHDADFDFHG,False +812,7.0,8.0,5.0,1.0,6.0,6.0,5.0,5.0,HHHHAEACACBEBCCAFAGEFCFDBHBFBFEGAGEGBGFABBE,False +813,7.0,6.0,14.0,17.0,20.0,8.0,11.0,16.0,BCHCAFAGAHCEFEDEHEDCHGHAEDGDFCFHGHGHAEGEGFHBBDFEHEDEDHDEDEBGDDFBEHGABCEDECCCADGHEHEHCHCDCDCDCEEGEFD,True +814,27.0,14.0,15.0,25.0,17.0,16.0,12.0,25.0,HFFCACAHFFCBCFFGDDECEFEHCBCBCDAAAGAHAHDECEFHAHAHDEABBEBCFGBGDEAEAEADGHAHACDHHHBCBEDFFAFHFEEGAAAAAHAHEHEDDDDGAGDHDBDFFAHDBACACAGHHDGBGBEDDBDHFHECGDDDHDH,False +815,9.0,8.0,11.0,6.0,5.0,16.0,9.0,7.0,DDGCCHAAADDFEFBHDFFFDFCFCFCFEBEGGGCFCGHGHEAAAFFHBCBGBEBCBFFFCFCAAGAHHGB,False +816,27.0,23.0,14.0,24.0,26.0,27.0,25.0,22.0,DABHHHEHAHAEFDBAGABDBGHDAAGAGFBAHAHEEDABFGGEEADAFBCACGCGCEFEBEBDFDCDGDEFEHEHFAGAGCBCGCBCBEDAGGBABHDFBFBDEHEHGBFEFEBDFHFHFDEECAFGFGFEADHDAGAGADCDCHFHCEADFDGEAFBFCFDBEEDGAGBEFEHDHGAGHGHFBFBF,False +817,1.0,1.0,2.0,2.0,3.0,7.0,3.0,4.0,FFFFADHDHEHEGCFBGECFHFG,True +818,10.0,14.0,17.0,5.0,12.0,5.0,16.0,9.0,CACBHAACABGDCAEAFGBEHEGCGCGEGEDBGAGFHBGCECEFEGEGBHBFGAGHEABDFDBCBCBHEHGHGBDCACBGBECCCCCH,True +819,20.0,12.0,13.0,11.0,16.0,13.0,21.0,6.0,ADCECACDCEGDFFAFBGBGBGBAAAEBEBGFDADEDAACACDCHHBGGGGGGGEGAAHFEFCGDGBCFABAFEGCDHFECEDEHABCDAHFGAGEGAGAEAGBFBCEFEFE,False +820,24.0,22.0,18.0,21.0,20.0,19.0,14.0,22.0,ECFBHAHAHAEAFBFGDGDCBCGAEAHABCBHFEDEDGBCDCDADABAEAEBHDGDHCBAHFDCDHHBHEGAAFAFCHCDDEHBFBFDGDGHBAFCEDEHFCEHEHEHGCGAHABCBEFHFGCDCDFBFBFAFGBDEDAGCHBEBCBADAGEBEAEAFFH,False +821,24.0,21.0,19.0,22.0,19.0,13.0,20.0,29.0,DAHAHAFEGCDEECECAAEHEFDDDGAGAGAGABHBGEHDHFHEHAHAHAFBHBHCAADCEBBGDECHGFGHGAGEDFDFDHHHCGAEABFDGBECECAHACFCHGFBDHGFDHBHDDDDGGHEHAHBGBGBHEABBFBDBFBDAEEBECCCCCACHCBCHAHDGDB,False +822,16.0,25.0,27.0,23.0,14.0,15.0,16.0,28.0,BHCHCDCAGFGAGBFHEHBABGDHBABFBGBDCHCHCHEHAHEHCHDBGBHACADADAFFHAADACBCBEGEFDFDFDFCHEHDDBDEGEDHHHCDEGHCFGFDEDBBGFGCGHAHBDCECHCABHFCCHCDEDCDCGBBEHDHBGBFEFCACHCBBABCBDGC,False +823,19.0,16.0,17.0,19.0,13.0,21.0,12.0,12.0,AAFGBDHDCDFDEHBBFHFCDCABBFDFGEGEBCHDDDBDGDACAGABEGECECECEFEHCHAGDDHCCDAEFFAFBFBGDAEHHBABAHADABGBFCFGDCDFHFHAGAFAFDFBACACFGFEFECBC,False +824,23.0,14.0,24.0,16.0,17.0,21.0,26.0,11.0,EEEECEBHDFDBDCFAABFDEEGGCGEGFHDGAGBCFCHCFAFAGAGFFBGAFAEABCGAEADADAHBBEHCHCBCBCDCECGHBHAFDEDEAAACACFFECEFFGACCDCFGGCGCGFDFHFGCGCGAEAGGHHFBFDADABBCGGGDGDG,False +825,16.0,23.0,19.0,19.0,25.0,21.0,19.0,16.0,BCECEGEHBGBGDACADFFBABGGEBEGCGAGDBCFCEADAEFEDDCHCDEDGBGCFHFGBEBEBEHCHCEBEDEBFBFEFHFHFGDEAEBGBEDDCBHDFGFCACAGAHBDBDBCCFCFAFDDDADHEEEFHAEAGBGCAHHHEHFGFBFGECHABF,False +826,8.0,5.0,4.0,4.0,6.0,3.0,1.0,4.0,CDGDCFEEEEABABADAHBFBHACAFHEAEAHCBD,False +827,24.0,26.0,18.0,19.0,16.0,34.0,27.0,29.0,CFAFCHHGFDHDBDBDCDCHEFBGBGBHBDADCGCGHGFDFBAHDDAFECBFFFHFAGECAHAEBEAAACGEGHGEABAFGCEAGFFHFGACBGHGAFHCHGHGBFAHGHBHBGBGAGCFBEDHBFBHEHEBFGECEADHFHFHFDABFEFHFEFBFBABDBDFDADGDGCAEAFCFCFCDAGGFGFBHHHHB,False +828,2.0,3.0,1.0,7.0,4.0,6.0,1.0,1.0,ADDDFDFEFEDEBFBEGFDADFHCB,True +829,18.0,8.0,19.0,22.0,14.0,21.0,12.0,12.0,EGEGCHAFEECHDBDBDCFAFEFDFEGEAFCFDADADCHFHEADAEHDHCCFCFDFHFDFDACACACEFDFDGBFBCGEGFGCGCAHADACEDDGCCACHBABDBHAHFFFDDHACBDEAEGGGFD,False +830,14.0,17.0,12.0,13.0,7.0,7.0,14.0,9.0,EGEBHBDCDGECBABADDGCABACFCEBDCCADADFGHGHGFGBGBGHGFDDCDAGABACHHDHDFDCBBGBAAFACEHAGAGBEBHBCBEBF,False +831,13.0,21.0,11.0,11.0,12.0,12.0,12.0,8.0,EAEDGBFBDBCHEBEBEBCHCHAFGGBCDDDCDCBADAFAFABADFCBCGEAEDBAFAEHEHADFHBBEHEFBFGEBHFGBCBCBFGGAGAGBGCGFBDB,False +832,14.0,20.0,21.0,16.0,26.0,24.0,30.0,17.0,BGGGEEEBFFFEFCDGGGGGCGABDFGHCAFFFDFEHDHAGAGAEBEBCBCAGBBDBFBFEEEDDFCCGCGEGBBDBHEDCFCHGFEEBGCFAEGEGECFCGCHEDDCBEDDDHHHCGBGEHEHGDDCGCGBGEGEBEHECGGAEABAFAHAFAFHFHCHCFFFHFBA,False +833,0.0,0.0,2.0,1.0,0.0,7.0,1.0,2.0,GFFCFHDHCFFFF,True +834,15.0,17.0,13.0,12.0,21.0,19.0,18.0,23.0,DEFBAGHEHEABHDFGFHFHCHDHECEHBHDGDGFFCGBFBEEHHCDEFECEDEBCBGEGEGACAGHGHAHDFCBHGFFFFDACEHEBFBHBHGAAEADGGADHHHHGHGFAFCFCGEDFFABABGECACABEBEBEB,False +835,9.0,17.0,15.0,12.0,13.0,15.0,12.0,18.0,AEAFDHGHGFDEDBFBABACCCFCHEHCFEDHFGFDHBHBHEFAACHEDECFCGCBCECEGHBHCABDBEGFDFDBDBEGEFFCCGHAHAHGHDFBBGBGDGHBHBCBFHE,False +836,24.0,27.0,17.0,31.0,24.0,22.0,21.0,23.0,DCGBEBCDEDADFBFEDADADBDCDCDEDFDGBGCGBHBHBHEHEDEDAGBGFDAHGHBCECADBDEDBFFAFAFAFEHHGCGFEFDDGDGFBFGEGEBAHAFDDHFABBBDADAHAGAFFFCGGEECHGAGAEECEBFBCBHHGEFDAAECFADHGHCHBBBBDEDHBBBEHHAHCHCAEFEHADGDC,False +837,8.0,2.0,11.0,12.0,11.0,8.0,3.0,11.0,BHCHEDEHFAFHDHCHFDCDFDFDAAHCFDDADHDECECACECAFEHEGDGEHEDEHFCBCGCAEA,True +838,12.0,19.0,12.0,11.0,20.0,17.0,13.0,16.0,DEFEFEHEFBFECEAEAGBGAFEBEDFGFGAHFHFCGBBBBBBHEFEBHBGBGHCHFBCDFHAACCHEHACDBFEGEDFBCBABHHCHEHACACEDDDDFDGHGHCAGFDFBEEEGEGBA,False +839,1.0,4.0,3.0,4.0,6.0,6.0,4.0,1.0,GBEECAGBFBFBEDCDFDFEEHEDGFGFC,True +840,5.0,4.0,4.0,1.0,6.0,4.0,2.0,2.0,GEBEFEHEAADACACFCFBBHCAGEBEF,True +841,15.0,12.0,13.0,8.0,18.0,15.0,11.0,15.0,FHFHFEAAHFEFCGEHEHCHCBCAEBBBCHAHAEGFGABHBEBEFCBCAHDHBEAFGBHAFEFBGCFEFCDADBDEDEDEGEFEFAACHDHAEACGEGHGCGAGFDC,False +842,17.0,27.0,15.0,15.0,25.0,21.0,18.0,18.0,DBEBDBEEGGGBGEHCACBCBABGEDEDGFAFCCBEDCGGFGBHAHDBBHBHECACEDBDHAAFAEBEDCDCHGBEDECHAFAFECECEFHGHGHBEBGBGBFFFFHFEFHFHEBEGEAEFFAFGBBBFHCHADFDFBABCGAEAGFHDADEBHBE,False +843,20.0,14.0,16.0,25.0,17.0,16.0,12.0,24.0,HBHEDGBFBCADADACHHDHDAEAHDDDDDHFFDHDGCGCBHEGABAHEDEABACDCEFGFHAGGBACGHAFFGDCAAGHDEGEGEDABACABHFDEEBEBDBDBDHDADAHCHBEFEDEDCFCFCHCHFHFHFHFCAEHHFCE,False +844,6.0,6.0,6.0,6.0,7.0,4.0,7.0,2.0,GCECFBDBDBEGHDEAEAFFECECACBGBDADGDGHFABGEGCA,False +845,14.0,10.0,13.0,17.0,13.0,16.0,16.0,22.0,DADFGHGHFHCBGAFEFCFCGDGDEDBABABECDCDBBGAFAGAHDDDDFDGDGDCEGGFHFHCHGAGDHHHFFCGCHHEFEAHHHFHGEGDAHECDCHHAHAEAEBCFHFBFCEHBBEEA,False +846,13.0,21.0,15.0,9.0,8.0,13.0,6.0,10.0,AGBCBCBDGCBFGHABCBCBEBABCGHEHBAFAFDFECDBBAAHBHBHCFCFDBABDCDFFCGHAHBHBEBEBCFCACDEHACEBFDFGFAFAED,False +847,8.0,14.0,10.0,15.0,9.0,10.0,9.0,7.0,DECFAHHBGBCEAACBCBADDEBHDHDEDFFFGEAEBGCGBGDGDFDADBDBDCFCGCBCHABFBDEDGDGBHBFFCFEAEH,False +848,10.0,5.0,6.0,10.0,12.0,17.0,10.0,11.0,DHDEDCDFDFAFAHCFGABAGFCFBGGGGAHCFDFAFEEEEBBABHFAFGFEEHDHECEHFHFEAHAHEDFDFHFDGGGEC,False +849,22.0,14.0,13.0,19.0,14.0,18.0,13.0,19.0,AACFCFBBHBGFDADADAHHCGFBCHHFHBHDGDCAHAHABDEDBDAHAGFGEBEBACHCDEGAFFDGBHFCFDDBABAEEDEGEFEAAGAGABADAHFGFCFAAGCFHEHFGFBFEEDEHEDCDCDCDHHH,False +850,12.0,11.0,24.0,25.0,18.0,37.0,27.0,36.0,GEGEAEAEDHDEDECECGGGEFEFEGCBFBFCFCDCHEHDDGEGFGDHFGEGAGCGFDHCHFHDGCCHEBBDACHCFCHGHCHCHGDFFFFDFHGHDFFFGFGHHHGCDFBFCHHFHDDBACHEEFDCAHDHBHFFFHHCHBHFHDGFGFGBEAHFHFHFCAGGDCBGDGDFFAACDCAFDFDFBHHAHE,False +851,8.0,20.0,9.0,10.0,16.0,10.0,11.0,18.0,GAGAGFFHFHCHGHEFEGADABHBHBFEEEBAHCHCEEHEDCAGGBBDBFGFHFHAHFHBABEHEBFBCHEBBBDDDCDBECEGDBCBEBEBHBGCHEDDHG,False +852,8.0,4.0,3.0,3.0,5.0,4.0,5.0,3.0,CEHEHBGFGBABDCGAGHFDCGAAAAEADAFEFEB,False +853,2.0,2.0,4.0,5.0,2.0,8.0,1.0,9.0,BHFHFHFADCCGFDFDBDEFAHHHHHFHECCFD,True +854,0.0,3.0,1.0,7.0,1.0,4.0,3.0,3.0,BGEDFDHDHGFBDBCGHDFDFD,True +855,13.0,9.0,23.0,8.0,13.0,14.0,12.0,14.0,CFCFCGHEACCCEEEGDHHAHBGBCFCDCDCFFGCAFDCABHCHCDFFCECGCGCAABFDEDACCHHAFAEBEBHGHBHFGEGCGCGAEBCBAGEFEFEFDHAHAH,False +856,10.0,14.0,21.0,25.0,13.0,22.0,18.0,15.0,HDAFAFDFBGDDCEEGEDFGBDBGCCCCDDDGDGHFDGHEFECHCHCFEDBDBACGFBFBFDCGEGCABABDEGCGCECEBAFGHHBDDDHHHGGDCDCACAFBEBECFCFAEHHFFFDGDGHGHDDFDFHFCFCBAF,False +857,5.0,7.0,6.0,6.0,3.0,6.0,3.0,6.0,HBHCDAHAFGBACABHBDBDEFGCHCHCBEFEFGFCFDDBDA,False +858,5.0,6.0,10.0,9.0,8.0,7.0,3.0,10.0,BGCHCHCBDDHDGDGABCBABFECECECDCDFHHCEDDFFFHHEHEAEAFHBEDHCAF,False +859,5.0,3.0,3.0,10.0,1.0,2.0,6.0,6.0,DADADBGHEADDDCDGHGHGCDCDBFAHHFHAGDGB,True +860,23.0,20.0,27.0,31.0,27.0,21.0,22.0,20.0,GBHCDCFCFDEDHCHGEFEFECCCCCADABAHFHFHFDGDAEEHACDDGBADFDEECFAFCFEGCGEEHFAFEFBABCDADEDEHBHGHBBAECECGBHAGFHHBGECCDEDBFHCACGCDAGAGADDDDDCDGFCFCEEEDEBHGHGHGCGCBDADHBGDDEDABABAEDEBFCDEBABGBDAFAFGEGH,False +861,7.0,7.0,14.0,4.0,11.0,5.0,11.0,5.0,GCGFGBGCCCGFAAEAECECECGBABHHCAEAHAEFEBEHDCDCGFGFBCGCGCDBEEHDGECB,True +862,12.0,3.0,10.0,5.0,8.0,8.0,5.0,6.0,GFCAHAHAGACCEHDBBAAAHADECEDECGCBCECFCFHFHAGGEDEFFCFAEAFAD,False +863,24.0,14.0,29.0,24.0,18.0,18.0,12.0,25.0,ACACHBEBEDABHBGCDCFCEDFCGCACGFADCCCCBCDEAEBDHEEGAGCDFDFDFGEHAHFEEAEHCCFHFEFCHCHDAAHGDCDAHFHEHDHDHAHADEBEBEGADAHEBFHFHACGFGCGCBCDCDCACFCFABCBADDBCBHHDHGAAHAHFFDHDEDA,False +864,12.0,14.0,8.0,8.0,15.0,8.0,10.0,15.0,EBEBGHCABAFAFDFDADGBHCEBGBGBCFCAEEDHCHGHBHDGDHEHEHEHCFGFBEEHAAAHGHGEGBFCABHFHEEBADCDABEBEA,False +865,3.0,2.0,2.0,3.0,0.0,3.0,0.0,4.0,BHDHBCFDFCAHAHAFD,True +866,5.0,8.0,8.0,6.0,13.0,7.0,15.0,8.0,FHCDEDADBEBGAGCCCEBGGFGEGEGAGAGHDHGBEHEDGAGEBECHCGFEEHEHGGFBFBFCFHEBCD,False +867,15.0,8.0,10.0,4.0,10.0,7.0,12.0,11.0,GCHHEHGBDBCGCBCFEAAHAHADFCFCFGAGAFBGAHAEGFBECEABHCHAEAEHGHGFBDCHGEGEGDACABAEA,False +868,13.0,19.0,24.0,20.0,14.0,16.0,12.0,20.0,HCHAHAGDDCDBGGHGHGCEEAEGFBFDEAEFCFHDHGFAFGEHDBDBDCECDFECHCDCFCHCHBBBBGAFDCACEDBFFAFAFBEHCACDHBCBCBHBCADDDBDHDHCHCBABHHEFGAECGCGCBDBDCFHFEE,False +869,11.0,10.0,12.0,15.0,14.0,12.0,10.0,5.0,CBGECDGDGDADCGAHDBDFFFFEAHFEFDBDGDGECECDDFDADBEACGFEBEBECCCGCBCBEAEAFGBAAAEDEGHHDHCFAFEFB,False +870,8.0,16.0,15.0,5.0,12.0,6.0,10.0,5.0,GEGAAFBCBCEGAAEBEBEFHHCBAAGACBBBBEBCGCGCECECBABCFCGCFEDEHCCDGBGFDFDEHCHBBGBDE,True +871,7.0,10.0,13.0,4.0,10.0,7.0,7.0,8.0,GAAHGCBADEDHDCCCACAFHEBBBBBCBEGEGFCHCBEGEGEHDHCFFABCFCFHGHABFECECE,False +872,5.0,6.0,11.0,4.0,5.0,6.0,7.0,6.0,FCCCACBDAFCCCFGBBHBGAGEGDGCGHGHDHDEBHCCFCBAEFEFEHA,False +873,6.0,3.0,2.0,8.0,3.0,5.0,4.0,1.0,AADDDCDCGGFFEBADADADEDGBGFFEFAHB,True +874,16.0,16.0,9.0,13.0,16.0,16.0,11.0,18.0,DGAGHBHCEFGDAAEAFAFBBDFHEDEDHBHGHGHDDEDFCFCAAADAHFBCBCGEHEBFDFAFCFAFAFBECCBEDHHEHEGBGCDFGFHHHBHBEBEBHAEADBEBAAGEGHF,False +875,10.0,10.0,11.0,9.0,10.0,8.0,13.0,16.0,AFADADEDEFHCHCFGBGEHDFGHCHEGBGHFABHEACHBHBHBHGDGBAAAHAHCHCGGGCGEDEBCDDGBGAECEFFFBCHCHDE,False +876,10.0,18.0,8.0,11.0,7.0,15.0,11.0,9.0,FCHDHBFBGCDHAGCCHDHAGFFHBHEFAFAFDBBBDBDEACGGGBGFECECACHDBABFBDBDGEADADFFFGEGEBBBFBFBGBFAH,False +877,4.0,5.0,14.0,13.0,6.0,8.0,11.0,11.0,ACACGHADGCECGGGDCCCFCFBFDFDHDHDADHDHFFBHGHCHCGCDCDHDEEBGFDEHBHGEEBDFCCGG,True +878,22.0,17.0,15.0,16.0,16.0,19.0,13.0,15.0,CCFCHHDBEGEGDCFHFBAGFEDDFDCECEGBCBABADADBGGDBACAFAEABHHHFHCHDBFBDBDBEHHCHCHEEGFGFHAEAEAEADFEAABCFCEAHFGAAADFDFBFBEGCGCDAFAFAEDGBHBGFA,False +879,11.0,12.0,5.0,10.0,10.0,9.0,11.0,9.0,BCBCEAFGFGHBHBHDDFEFGBGHGFBDCAAGEHDBDGHGHFADAEEFEDEDEAHABABACAGHEDFAGEDBGBCBF,False +880,22.0,23.0,20.0,22.0,17.0,22.0,27.0,22.0,AFEFEHDHDHDBFBGBGEGBGFGFGEHEABABGGGABAHDHEBCGCGCFCDBDFEEAAAFDCBFHGHBCGAEDFDFDBCECFBAGAGAFEHGGCGDBBCCGBDDCDBDCFCAHDBAFFHCHDHFHCEEDHDHBHCCBFBAEAEAFGDCDHAHFHEHADAGAGAFBGCGHGFBEGG,False +881,26.0,17.0,21.0,13.0,20.0,12.0,23.0,19.0,BAEAGCGHGAEADABEEEGAAHHDDBDFGAGACCHHEHEBFBHEEEDFGFEAGHCCACGEFEDCGCHCGFHHBHBGBCCCDCGBGBABABFDDHEAEFEGGGGEHAHACACDGBGBGBEAFACEHFAAAHGHGDCCECFCBCBHDAAAFAD,False +882,1.0,1.0,3.0,2.0,1.0,1.0,0.0,5.0,DHHFADEBCHCHCH,True +883,7.0,3.0,8.0,7.0,4.0,4.0,4.0,4.0,GDEDCFHFHDHDEGEACDCABBGFACACGCFCDADBCAEAH,False +884,21.0,12.0,14.0,11.0,9.0,9.0,15.0,13.0,EHEAEGDDAGGBGFFAGHDHDCDCDCFCGGGGGAAEGCHEDEAEFHFAFGCBHBCCCCADBBAGAGHBCACAHAHBFEDBGBCBEDDHHABAFAHAHFBCAAAA,False +885,16.0,26.0,24.0,20.0,25.0,24.0,19.0,20.0,DFDGGAEAEAEDHGHGCCABBEECFCFGBGBDCGFFDBDECEADADHGHFDBDCEEBCGCGAFBFBCHDFDFEFEFHFHFHBHFEFHCHCBAFDFBFCAGAECBBBBEAEBGCECFHEHDCCEGBGBGFGFHHEHCHBDACECABABDBHAEDDCGGBBEFDFDCBAEHEHECG,False +886,13.0,28.0,17.0,8.0,23.0,25.0,17.0,16.0,GFFBFBHCFBBBCGCGEEBCBABFDEBGBGCACEHFHFHBADDCGEGEBHAAACFCEHBHBDAEFFFFDFDFEFEFECEBBBHFGBBHBEGCBEAEDCHEEEFBGHGECEHFHBABFCFCFCGCEAGDGAGAFBGGAFHHHBEBEBF,False +887,12.0,16.0,10.0,18.0,15.0,11.0,14.0,8.0,EEHEFGDCAFDGDCBFBFGFBEAFBBBAGFGBGCHCHCAGADCFCDBDEHEAEDGDBHBFGEBEBDBDADCDHDEABDDEDFCAGDGAGAFDEAGCGBEBEHEH,False +888,18.0,13.0,17.0,15.0,11.0,10.0,18.0,15.0,DEGEDEFAHAHAHGHGHGCGCFDDDADFCBGDGDCBABCBEACAGAGCEDBABDHFGAGAGDEEHAFCDCBCACBEBHCGBFAHAHCDFHBGBGHFHGHFBACEGEGCHAECFCDAD,False +889,22.0,5.0,11.0,9.0,14.0,19.0,10.0,13.0,HEHFADEFGFCEHEFDFHFAFGGGGAGAFADGDFAEAHBCECEDFCFHFCFDFDAACACABBFGCHEAAABCDHEAEABFHFHEGEFHAAAAACAGDHCHEFE,False +890,27.0,36.0,17.0,27.0,26.0,14.0,25.0,25.0,FHDGFABEECADAEBECEABAGHECDCDADGDADADEHEHGHBFBCBGDEEEEEBABABHBHAGCEDEDEHAHAGGCDCDHBABHBCACAGFCFGHHFDFDGBGHGAGCGFFBHADFCECEHBDBGBABACAHEBBHGHEHBBEDEFEBGBDBCGEDBBBBBEBDHDBAHGFGAEBHAADGHGDABFCFDAGBGDHD,False +891,18.0,15.0,22.0,14.0,25.0,27.0,18.0,19.0,FHFHEHAHCFEDCDHFFFHCCCCCCFAFGEAHAFGGEGEGEGFGFAEHDCDFHGAGEBHFHCHBHBEDHDCFCACGBFCDDEHBCEGAFABEBFDEGAFDCACFEFEDEAAGAGAGCBCDFEHAHEHBCBCBFBEEFEHGGGCEFEFEBEAFFBDADB,False +892,15.0,15.0,17.0,14.0,25.0,21.0,15.0,21.0,EGAHHHDHDFEAEDEGGGGAGFHFAFEEEHHBCBGHGBGDFAAEAECEFEDDBFCFCAGFFHFHFHBCFCDHFHCHADBHFGFGBEBHHEEDDCDGBCEEEBGBHEHEDEAFCBCECEBGAAAEDCDCACABEHHCFEFCFBF,False +893,5.0,2.0,1.0,1.0,3.0,2.0,5.0,2.0,BHAHAEEEGFGFACGBDAGAG,True +894,1.0,2.0,2.0,3.0,4.0,6.0,4.0,3.0,FCFCHHEFEFGGGGHDBEBFAFDDE,True +895,12.0,25.0,10.0,17.0,18.0,19.0,18.0,17.0,CECBHFGFGEBBHFEFDBDBABDGAGAEABCBGAGAHCEEHEHEHDDCDBFHFHEDFCFBFBFAGGGGGFGEHBBBHDHBHDEBEFGDCBBBDBGCAHHEGBGBCDFDEEEDEACAFFGBBHFHFDFAFHGBADED,False +896,16.0,8.0,11.0,13.0,10.0,11.0,7.0,7.0,GEDEHEHBBDADFDADCDCAAAHFHFGFECACAEDCDGAEAEBBCBGEACAHDBDEGFHFBCDCFAADACBCHFAFAFEGGDF,False +897,11.0,6.0,9.0,7.0,10.0,14.0,15.0,10.0,HDBFBGCFCGCGBGDEDGHAHGHAAFHFCGBGCAHHGFCFAFEBGHGBDCHCHDEEFEFEAEAEFEFGDGFAFACGEFDAGA,False +898,17.0,13.0,21.0,30.0,28.0,20.0,12.0,19.0,EDDBGCECEDBCBCDHGFECBGBEHHHEHFHDGDHHAFAHCHDBEFDADCDHEEEHEGDGDGFEDCACEDEAEAEFDFDFDADCCACFEFCFEFCBBHCCFEEDHDFGEGAFCFCACABABCGDEDAHEDDDDGDGFHDHDABFCFDFAHEEBEBEHEAA,False +899,3.0,3.0,2.0,3.0,3.0,3.0,8.0,3.0,BCEFGHGHGAGBGBGDFDCHEGEFAADG,False +900,16.0,24.0,17.0,15.0,11.0,13.0,13.0,18.0,DDCDADAECDHHHCHADDHCHCBCADAECGHGEAHFHGBBHDADAEHHFHGACACFCFBEBEDCGCGBBBBGEFFHFBBGCGBABABAHFEFBBECCHGFDFBFAFAHBBEBEACDGDGCBHBGBDB,False +901,25.0,30.0,29.0,16.0,34.0,19.0,24.0,19.0,FFGCECEBBBCDCBFEEEECGCABAFEFGHBDAACECGHDFCHBFBGGGBGHCHCBCECBGBEFDHBHBHCHAHAGABABGEGFCFBEGEBBCBCDHHHCHCHDBDCFCAEDHGAGEBEGEBEDEFFDBDEFBCEFEAGGFGEGFBFHHACACAEAEAEBEHEBAGAEAECGABADDDAECECFAAEDDAGCECBG,False +902,24.0,23.0,19.0,24.0,26.0,27.0,19.0,14.0,FAAAEACAEEEGEDAHEBADAGGHEDCABGFFDFDFEBEBEDEDGAHFDGBCBFDFGECFBFGFBFEFCFEDADBEFEFACACACAHADBBBEHAHBGBFAGBEEGGFGCGCFAFDFEBHGCAAGDGFHFCFCHCDCBFBGBCBEHFHCHCBEDGDACAEBDBHFHEDDDDDEAED,False +903,29.0,29.0,25.0,18.0,19.0,26.0,26.0,24.0,GABBEDADAGFHBHFHGCBCBDADGBGDGHEDBGBGDAEBEAGFGACEBEDADFFFBBBCFCGAFAHEHEHGBAAAAAAGGCCHBGBABHEEFHFHAHFBGCHDHFEBEGEAEDFGCHBHACADBHGDGCEDFFHFEFBCBABAHAEAGGFFCFAHADGDGCBCBCGCGCBCBCFHEHDFFEFHFCFABCHCDCAC,False +904,6.0,3.0,10.0,6.0,5.0,4.0,4.0,1.0,ACGCFCACDCHCDDDEDCGGEFBCBCBFGFEEAEDCAAA,True +905,3.0,18.0,9.0,11.0,14.0,16.0,4.0,13.0,DCFBBCBEBDBFFEFDCGHBHGDCFBFDEHEFBHBFEFHFHFGCAEHFAFBEHEHEHCACHGFDCBEFEHEBDBDBHBDEDEDBCBFB,True +906,16.0,25.0,37.0,22.0,24.0,10.0,28.0,28.0,DFDCDCEAEHCHEACBHBGBHCCGCECADDDDDDCHHHAHCCCGDECECEBECHCFCFBHBACGCBABCBHGEBBBHGHGBCBCDEEAAGAGDHFCCEDEDGDGDGBGHHDFFGEEBFAGHGFCBBGEHHBCBDBABCEAGACACGBEHEHCFDHAHEGGGHGHGACEDECHCGCGCDHFHBEGEDBCGC,False +907,25.0,18.0,28.0,21.0,19.0,32.0,30.0,20.0,GCGCEBHGCGCEDDHHGCCCCGHGHDHEHACGGGBGFGBEACGHGCFDFDCCCHCFDFAFAEAGABACAGACEBHBFGFBFBDHCFAFGFACAGDEHCDBGHAHBBDFDFCFAEBDCGFAHGHGFGFGBADFEFHBDADABBEAFHDDFDFGBGDEDEFAFEFEFGFAFDFEFCACHFHBEEECGCGCAAEAC,False +908,28.0,27.0,16.0,15.0,23.0,29.0,25.0,24.0,FAFEFGFBABHFFBHDCCGAABEBCACAEFFCFAGAEEGEGFGFDFHFHBAGFGBGDHBHBHBCGEGFAAHAHAHAEGEBEAHABCBDFGFGEGBFBHBDBFBFGFGHGHBEBEBDGHGFAFCHADEEECECFBACCBCDDHGGEHEGCAAFAFBDHHHDHDFDADGFAAEAFABEECGHHDBEACB,False +909,22.0,23.0,20.0,21.0,31.0,23.0,29.0,28.0,EAGGGDCHHHHCDDEDBCHAEDGBGAGADBHAFFHGBGBDEGEGHGAGDBEGAGCCHFHFGEGHHEAEBDDDDADHCBBBCACFCGAGECEAEFEGEDDAAEFEHBHBGBFCFCHGBBDBFBFDEAEAEFCDDEGFGFCECAGHGFGFEHHDAFHFHGHGHFHFEEEHAFBBBEAECGCBCBCEEAHACBFDFEHEH,False +910,35.0,20.0,17.0,22.0,15.0,17.0,23.0,20.0,BABABADGDFFFFFADHEEAEHCBGBGDGEGCACHEFAAHAHAHBHGHBABCBCGCFDFAFCFCEAEHEDGFGBAAADBGADADBDBECGGFCBDBHCAADAHAGADCGFGFGCGCEDAAEAHDEDBAGFGBADDDCDHHHCHAHDEAHGFAEAFBDHAGAEHBBGCGA,False +911,20.0,22.0,16.0,16.0,19.0,34.0,24.0,21.0,HHBBFFAHAHEFAFCDBDBDGCEEBFBDCCBCHDFAFDBDBFCFAHGEDBGFFFDFHACEDGDBFBFCECHCHBFAFADAFFFFFFFGFBHGHGHGHAFABACHCFGGGAFHFHGGGGFAFEEGHGEEEGECDGECBCBHDGDGHEHDBAGEBEAEABABFEGACHEBGFAF,False +912,14.0,22.0,22.0,16.0,10.0,16.0,13.0,11.0,GABHDHAHACDCBFFFECHFHEBEGABCEHEBBFBACHCHCACABEFFDBACDHFADAFBFBGGCGCGCHFBFCGDFAFGBCBCBDHDGDCBCBCGDGCGAGABCBCACEDFDEEFBBDDDEDB,False +913,20.0,27.0,29.0,23.0,22.0,31.0,29.0,18.0,GFGEECFDFAGEFHFACDEGCGCGHGHDHDCGCFDBAGAGAGDGHFDFBFGFGAGHDAGAFABDCFFECECEFFDCDCBCGDBABFFHFDDDGACHHDBEBEBFCEEBEHAHECBABGGAGDHDCEEGFCFBDECACAFHFAFACBEAGGGBGBCBHFCFCFCFCHDFAEBBBHBEBECFCHEEGBGBFCDBDBDBHGC,False +914,12.0,9.0,6.0,2.0,6.0,6.0,2.0,13.0,BFBHEHEHBADCHBAGFHFEBHAAACABHBHAAACECBBACGCHFHAHAHEHEFFD,True +915,10.0,12.0,24.0,13.0,16.0,14.0,13.0,16.0,CEBDBDBDCDCDCDBDAHHBFBFCFGFGEDFHCBCFGECFCEBEBHBCCFCFDFEHAFBHAHAHFCACHCECEHACBCHCFEDEAGACDCHCGAHCDEGGHEEFHAGGGECEGEHDGG,False +916,4.0,4.0,9.0,4.0,6.0,12.0,3.0,4.0,CECDADFBACFCFDFBFGFCFGHCCGBEHEHEHEFFCACBEFFFAD,True +917,15.0,18.0,12.0,11.0,16.0,11.0,18.0,15.0,AEAEAEAEAHAHAGEEFHGHBHBEDABABADHGFGDHBCDDFHGBEFFFAFGGHBDFCBEHECECGFHBHEEGDBEGEBBGDCDHDCACGFGHGCABABHFACCCCBGBGBGDGBE,False +918,14.0,16.0,12.0,30.0,16.0,18.0,12.0,16.0,DHDAEBFADADADADADGDFAFHFHDEFGBGBGBGFHCGEHECEAACACGCDDDFEBEBHBFAFHCDDDDFCFDFGHCFDHEFEFDCHBBBHAEDEDBAAHCEFDCDBDFDBEEDBDHEBDHDGFHDHEGGGCB,False +919,5.0,11.0,3.0,9.0,10.0,8.0,8.0,5.0,BFBHEEEBCBHEHGAGAGDDBDEEEHABFCFBAGDCDGDBDGAFEFEFDBDGGFBFBHE,False +920,5.0,0.0,5.0,4.0,1.0,1.0,4.0,2.0,CGAAFADHDCACGCECGDGDHA,True +921,24.0,17.0,18.0,26.0,23.0,31.0,24.0,25.0,EDEDCDADFGBABAGGFCFDFEGCGBHHECEADGDEDFDFDBEGEFCAGFEFEFDHEADHCHAHFHFHEGEDDDDBGEGEFBCDCEAAHDBAGHDHFGGHEHAHAHAHFHFDFBGBHCGAGFEFEFADACAFEBGCCDBEBADAFBGCFAFCHCHAFEFGCGBGCAFABCDAFBFBHDHFHEGDGHFH,False +922,12.0,3.0,17.0,8.0,6.0,8.0,19.0,16.0,GDFCHCHAADGBHCHAFEHCHCBGBCHFACAFADGGGGGGCGCAADHEHECEAEDDCCEGFGFGAGAHHGHGCDADCCHHGCGFHFHGC,True +923,13.0,7.0,15.0,17.0,15.0,11.0,14.0,5.0,GDDDHCCBCDADAEABADADGHFDCCACAEAGGDEEEDFHFBDGCHBFBFDGGBCDDDFCFCFEEGCFEFADADACAGGGGEGCCAEBEHEGEFECE,False +924,19.0,22.0,14.0,20.0,28.0,12.0,19.0,18.0,CGCDHBFBHGEBEADBDGDGDCBCDCHCEBHGEGEHEGDFFCEAEDGCGEGFDEEEEEBABCBCBCBCBGFDFAEAFDHDHEHFDAAHHHHEAEADAFEFEDBABDHEFEAGCBBFHDHBHBGBADHEEDBDEGBAEAGGCGHBEGGAAAEA,False +925,20.0,23.0,18.0,19.0,19.0,27.0,21.0,22.0,FEHEHEGDGCBDBHBEBCAGACHFEFHAHADAFGBGFFEGECEHDGDAHAHEDCCEAGFDFEGCCBGBFBFHDADCBCBFBCCHBHAHBDCECDFHFGFADCFFFFBFADBGGHADFDBBCBGHHHEHEHBAEAEFGBHBHGAGEFEFGFGFDCDFBFACAGAEADGDB,False +926,8.0,4.0,5.0,5.0,6.0,5.0,4.0,8.0,FGFDECECEADFBFBHEHAHADAHAEACGDADHHHBHFACBEGCG,False +927,4.0,9.0,2.0,4.0,9.0,4.0,11.0,2.0,GHGBGDGBGBEAGFGBBBBDDEBGFGEGEDECEAEAGBFCEHFAE,True +928,19.0,13.0,20.0,26.0,25.0,21.0,11.0,20.0,DDDFAGCFCHADFCCECECFBEHDBEBEDEHEHCFAEAEAEFDFBFADAEAEAEADHDFDFGBGBADEDBHCGCFCBEEAEHECFHAGACCCDDEDHHHHAHDDDACGHBACFCFGDEFEBHFHFCDDDHDACECBDHGHEEFGBGFGFEDHFBA,False +929,31.0,26.0,25.0,22.0,30.0,19.0,16.0,16.0,GADBEEEAEAHACCCCFGFEHBGBGCFCFDDADGBAAAFEFAABEHADFDFACAHBHGEFBAAACFCGABEGFABGFGEGFBFBEBFDEDEHGFEECHAHADADADCHEHEBEDABHBEACADBDBDGDGDCDCACHEHGCEHDCEABCFAEDFDGCEBFBAAEHEDEBCBCBCBCBEEAEBCHC,False +930,5.0,6.0,16.0,9.0,2.0,8.0,6.0,8.0,FCFCBBGDGDBABHCHCGEBEDDGACFCFCFCHCGCABHCCCCHFHCAGFHHCAFDDDDD,True +931,13.0,10.0,13.0,5.0,17.0,8.0,8.0,11.0,AEAEAHAEECBHBHGHAEBFCEEAEBEGCHBFBGEGFACADAEGEDBFCCHHBHBHFHCGEGHDDCDCACAEAFBCGCFEFECEA,False +932,13.0,15.0,7.0,16.0,20.0,10.0,5.0,18.0,AEABBCHEBEHEFEDEAFBHBADFHHDBDEHBABABABACDCFEFHFEGGACEDEHEBBAFGHCEDEDBGCHHDBDBEHCHDADGDEDEDHFEEEAHAHFHFHD,False +933,4.0,6.0,3.0,4.0,2.0,6.0,4.0,5.0,AGAGAHBEEDCGBGBCBDFDFDHHAFBFHFCBHF,False +934,5.0,12.0,3.0,2.0,5.0,4.0,9.0,11.0,CEDBABACFFGFAEAGCGBGHGHBHGHEBBHBHGDFHHHHBEBEAGBBBGH,True +935,8.0,6.0,1.0,11.0,7.0,1.0,14.0,7.0,GEBHGHGDBAEEDAGGEGDGBGBHHHHDDAAAAGDGDGDADABCEGEHEDDFGGB,True +936,12.0,13.0,17.0,16.0,15.0,22.0,16.0,19.0,HHEDDDDGDGAFACACHCFEEECACADBGHGFFFFFFEHEHCAGBDFEFDFEFEHEFFBBABFCHEGFGDHBCBCBEEAHCCECDDBFBHCHFHFHDEDGGGDGBGHCBGAFDGDGCAHBCCHGHFHFAA,False +937,3.0,4.0,1.0,4.0,2.0,0.0,0.0,2.0,ADDEDEHBHBACADBB,True +938,5.0,10.0,7.0,7.0,2.0,7.0,13.0,13.0,FCGGGHHAFEFBFBGBABAEGGGGCFCFHBABHHDHDHFHACDBBGHGDGDHCBDHCHGBGDHC,True +939,0.0,2.0,2.0,0.0,2.0,1.0,2.0,1.0,CGEGEBFBHC,True +940,15.0,12.0,17.0,12.0,18.0,16.0,21.0,10.0,DADACBCEGEGCCAHFCDCDAEACDCFGDAEBEBEACABEGGGABACDFDCGGFDDHCGFGEGBCBDEDGHGFEFBFGGCBCEEFAFGFHFAFHGHGCEFEBHBHGEGEGEFAFAHACBHE,False +941,21.0,9.0,18.0,19.0,23.0,21.0,20.0,26.0,EGEDHBHBHGHGHCEAAGBHBDDDGGGDGFGFEFGFGADHEFEAEAFAHAEAHBFECDCAAGDFAFHEHCCDCEFHFHFAEAHACFCFCHCECEHDDGDHDHDADEBHFEGAAEAFBHCCEGGDEDBCHADAHFBFCFCGGEDECFHGAGHECEHFH,False +942,23.0,23.0,25.0,23.0,16.0,18.0,18.0,24.0,CAHDBDHDEGCADHGHGHGHFCDCHCDFGEDEDHDHBHFDFEEADAEABFFGFGACFBBCFCBBFAHCHCEEDCCFHACACABHBFFFDFECACHHEGDGDEDBHBCBHBHADABHBHBCGHACBCBEBABCGEEFEAEAGGCDDDDAGAGAHBHDGBCFGFDCAGACAB,False +943,9.0,5.0,6.0,3.0,2.0,3.0,4.0,6.0,DBDHCFFHCEAEGBGBGAHCHBBAGFCAHAHACADACA,True +944,1.0,5.0,5.0,2.0,2.0,3.0,5.0,5.0,EGGDGHCBBAEGHGCFCFBHBHBHCFCD,True +945,23.0,12.0,17.0,23.0,21.0,25.0,31.0,23.0,AHAHBHBHCHCEDDFCACDCDFGFBHBCCGFGHGAAHDEEGECFAHAHFHDHEADFGCGCGFGEADBEAEBEDDBCBHAAFAFAFDGDHABAEHDHGEEEHDADGFGHGFEFGFCFAFHFEFADGGEGEGECFDHCHDFGHGDGCAAGAGEGFDBGCEBGBGDEDHFFCFGAGDG,False +946,7.0,6.0,9.0,5.0,3.0,13.0,9.0,7.0,BEBECFHFHAHGCAABCCFGBGFFCFGFBFDFGGAGHGFFFFDBCGHHCHCDDADAEAC,False +947,12.0,14.0,22.0,9.0,8.0,15.0,19.0,16.0,GGGGGADFDBBBCHGACAHBFGHGHGFGCCFDACHGHEFFBCBGEGDGFHHHBHDGDCCCCGBFHACACECDCFGBHBHBCEFECHCBCBCHGFGDAAAADAEEFCFCACFFEHB,False +948,23.0,29.0,24.0,18.0,9.0,25.0,25.0,32.0,BBBHGFAEAEBEBCFCFAFAFCFDFBHBGCHFAEGDACAGBHCHFDBCBGGCCBBHHABDCFGHBDCDBDGFBCAFAHHGHFHEHACEGDABGBGHABABGHHHFBFCFHFABAEAGACBCFHHBABCBCBCACFCHGHCHBGBHDDFGAAFFFEDDDGDHDHGHGHGHDHGHGHDCDCGFGFEA,False +949,7.0,6.0,5.0,7.0,7.0,6.0,6.0,12.0,HHCHADDCGBGFFHDHBBCHCHBFADAEAGAFAEAHBHEEEEHHHBGDGEGCDFDF,False +950,24.0,23.0,22.0,11.0,20.0,30.0,30.0,14.0,EHFBFBFBCCFCAAACEGBFAEEBHCHFHEAEAGBGHGHGCGCFEFAFBEAGAEBGDGCGHGHBBGBGBFBFDFECAGGFEBEGCAEBEDGHAFBHBFBDGDGFGDACCGCECACAGFCECHDFBCGCGFFFGFGCBCGABADFBHGGFGDHDEFBHCAAAAAAFFFFFDEEAE,False +951,16.0,19.0,15.0,15.0,20.0,28.0,15.0,17.0,DGGFECEHGHFHCBCEHGDGCBCGCEEFAFAFAHEHFAABHEGDGAGBGEEBHDHBBCBCHFBDBDBHEDFCAEAFFFDFDFAGBCBDECFFFEFDFBFGFGEECECEFEFEDHGCDAHAEABBDGFBFHHBHDAFHFCFAFABA,False +952,9.0,0.0,6.0,3.0,8.0,5.0,2.0,3.0,EFACCCFAAAAHFFFDGAAEAEHGHECECEDECEAD,True +953,2.0,1.0,1.0,1.0,6.0,2.0,3.0,1.0,ECEHDAAGBGEEEEFGF,True +954,11.0,9.0,7.0,13.0,13.0,4.0,8.0,8.0,CADHDHDFDABBEACAFDBBHFHGAGECBGEGEGEBEHEDEAHBGDADADADFDEBEDDCAABHEHCGEGECC,False +955,17.0,19.0,17.0,18.0,12.0,19.0,16.0,32.0,GFGFAAGFGAHADGGHGEBABFEDBHBDFHHHHBGBHDHDEAACBFBFBEAEHCDDGDFHHEDGHGBGBGADHFHDHCCGAEACDCDCAHAHFHFHFHDBDADHCCCHBACACBHFHFEFECACGEBBFDHCHDHBHEFGCECHFFBHBH,False +956,21.0,23.0,17.0,24.0,20.0,16.0,15.0,22.0,DADEHFHDCBCBCAHGBGFDFDGBAFDFDHHFDBDBACACFEHEAEAHAEEBAGCHCFCFAHAGDGDADADHHGHGECCFCFGFCHAHGDGBCCHADBDEAHGCFBHBHBHEEEEEHEBEAEGDBBFBHHCDCEBBBDBDBAADGFABADFEEGEDDB,False +957,10.0,10.0,8.0,10.0,12.0,10.0,10.0,2.0,FGFBFDFCGGFGABBBDGAAAFHFDGDBDGDEDECECECECGBAEHECGDACEBGBDFCAEAFFEDEBABAE,False +958,23.0,37.0,29.0,27.0,20.0,20.0,23.0,19.0,ADBDBAFABHBADGGCCCHFHGBBDDCACACBBAGDHDHCHFECBHFEGEBEDCCFEDEFBFBCBCBHEHBGDCDGBGAGAFFGCGEGAADACADBGFEDGBGFDBHBCAHEEFFDCDADBDBACDCDCDBHBHFEFHFDBGBGEFHFHBACECEDEBCBCBCGCGBBACAGEFBFBABGDGDHEHEGBCDCBHEAAA,False +959,12.0,18.0,18.0,8.0,12.0,10.0,17.0,15.0,BEBEBGBGBHBCBCECGCGCDCFGGHGBCHEACCCEFGAAAEHBHEHBGBHAEABHGFCFCDCEABACAHEHCGCHFEAEGDBDHDCGFDCDAHBHGFDFGGGHFBBBAF,False +960,6.0,8.0,14.0,11.0,10.0,8.0,6.0,15.0,EADADHGFDEEHFHDHBHBHCECDFDBDECHFFAFGFBEDECBCECHHHHGCGDGDHCCCCCCEEDHHAHABCGFABB,False +961,20.0,29.0,25.0,20.0,25.0,26.0,26.0,18.0,BHBEFEABGFAEGDGDFFBDHDGBGBFFFHEEEEEDFAFADABGGCGCBCBAFCFABCCHEHGDDEDEGFFAAEEEEAGCGAGHGFDCCBCHGACACEDHGHGAFBFBFAHEBEBEDGBHCCEAEADDDHDCBCFHAHCHBHBFBFBGGGBHECGFGECBCBCDHDBBFDCACACBFGFGEGCDEBFBF,False +962,27.0,19.0,27.0,18.0,20.0,32.0,29.0,28.0,GEGECAFAHHHHEAEBDBDCHHGHFEFHDBFAFBFDGDBCBCGHGHFCFCFCFDEGADHHCCADADAGEHEHGACCHGHBHEHCHCHFECGCFAFBFAFGFBCAEFCDHAGFBFHGEGAAHGFGEDEACDCFHDDCDCFCHCGCEDGHBDAAFAGBFBFHEGAFACADEFEBEGGGCGCBBFBFGAGAGAFABAGFBEHF,False +963,18.0,20.0,27.0,19.0,14.0,17.0,15.0,25.0,FFACCGCGCDDHCHCDGGGEHFBCBHFCAAAAHAGFGDGAGDGHFBDEDHCBCACACGCGAFEBBCECEAEHEHBBCHHHHAACDCDBDFCFBFBHCHBHDGCEEEHEDGBBBFEFHFHDCDBDADAHFBCBABDCEAHHDACFCGHBHFHDCFE,False +964,12.0,10.0,8.0,9.0,12.0,10.0,10.0,9.0,FGFAEAEAGADFEECEHBBBAHAEBECECAGGHBAAGEHFHDHAEFDFECDCBFBFBABDDFDGGFGCCCEHAHBHGDGD,False +965,17.0,22.0,24.0,31.0,26.0,22.0,22.0,27.0,CGCEHFCFCEBDBDBEHEHGHGHFABABHEHFBEBGHDHDFCBDBEBGGCHCFDFHEHDHDGDFFBCAHAHGEEFHBHBEBADFFAFAHDHGAGAHEDDHDEBEFEBEFHFHACADDDFDEEEECCCDAGADBGAGFEHBGGHDCCCDEDGHCECDDABFBEBCGEGCGCFCDCAAEDCBGHGDFDGDCDF,False +966,27.0,18.0,26.0,14.0,26.0,27.0,37.0,24.0,AACDCHCFGHAHAGAGACFHEHABFHFAGHBCBDBFBFBABFHHHFHFCEDEFACHCECFGFEFECGDGHGCGFGEHECDCBCBGBECEDFAEECAGGFAFBHEFDGBGEGHFEEGEHCGEGDGDGDFCCCCHBAEACHGHGAGHGAGEHEGEGBCAGGGFABHDADADAGAFHBEDCFAEECFGFGFGCGABEFGABA,False +967,19.0,30.0,23.0,20.0,26.0,19.0,25.0,21.0,BBABCBGGAGFDFGHDHEGBGCGBBAFDCBCEFHDCDFBCBGEFBHBEEEEEBADAHAHBGGGEDBFBHCCCECBGHDHDFGBDCDFBEHECGBGBGFCFAHEHDGEGEFDFDECCCHCHEGEGHGBCEAGABEBABABABADADABAEADCCEFBABFECDFHFHCHFEFCGGEHEHGDADH,False +968,22.0,15.0,29.0,26.0,37.0,20.0,22.0,24.0,AEGBABEFGGEGDHDHAHEFECEFACEEACHBECFBABCDCACAHGHDEEFECECDAAAEHGHGHDHDFGFHCADFDBDEDEAEDEDEDEDGGECEABBGFADADEHGHFECBCAEAEGECECAGDBEGAACCCCCCBHEGECDCDFHFHFHFHFCGEGHBDFEBBBGECHDEFEHHGDADCGHGDDCEFHFCFC,False +969,16.0,6.0,14.0,15.0,9.0,8.0,13.0,13.0,HHHHFEFDDCAHGGEGDGDCBBHCCDADGGHAAADADFDFDGDGDGABEBAFABECDHAAFAFEFGDGCHEHCDCGCEEHHHAEACCCCBCGAA,False +970,21.0,25.0,9.0,17.0,8.0,13.0,18.0,16.0,GBGHGACACAFHFBCADGGGFGFGAGAGBBDBGCHHEHEBFDEABGDGDGBHBCDFFFFHFHAHBDACAHDHCCGAEADBHBDFABABABEBEAECGGBHBHDFBBBBAFDDAGBHHABDDADADBE,False +971,9.0,10.0,11.0,9.0,15.0,9.0,14.0,12.0,EAEDFCFBFBAGHGHGDGBHBGFHEHCFAFAGHECGCHCADAHCEGDGCGBBBBDBDEGFGCCFHEEEHEDEAEDBCGHGCADHEFEAE,False +972,18.0,16.0,12.0,13.0,15.0,19.0,12.0,21.0,BEHFBBABAHGEEAEAFAFCDEHFHAHCGCFBEAAFGCABHHFHFHCHBGADCDHDHCHCEEAGBFDFGADFFFFBFBGDGAGAEADHDHDAEEEBCBCBHBDEEHGFGFBFBDEHCHGHAHFCAD,False +973,27.0,25.0,26.0,28.0,24.0,17.0,20.0,27.0,HCHEFEACGCFDFGCBCHADFCFBADCGHBHCDDDCBAAHAEEDADGDGHGHGHGDAAEBEHAHGDADADEBEHHCEBADAHHHHCHCAAAHBFBDCGBFCHEEFBFBFHAEADDBFBFBDGDEHEHBHGCGAHACECAFBFBEEEBECEFDCCABDBDEDEGAGADEDEDCFBBACHGGFGBGCGDADCHCBC,False +974,2.0,9.0,5.0,14.0,10.0,16.0,13.0,8.0,HBEGFBDBDHEEFHFEGDBFBFBGHFAFDFGFCFDBDBDHDHBGGCFFEGEGECADGFECEHFGDCDHDEDGFGFGD,True +975,7.0,10.0,11.0,8.0,6.0,8.0,11.0,11.0,CECFCDCHGGGGHGAFCECEAECDCGHHBADHDHDBDBFBFDAHGBBBBBBGCFFFAAEHDFCHGAGHCHGE,False +976,22.0,16.0,20.0,24.0,18.0,27.0,21.0,14.0,GDBDHEGEBFHFHDDCFCDAAGEFBFEDBAHGBGBGDFEBBADGHGFABAFAFDCDCBCAHADDDCAHECCDAAFAFGHCCECFGECECEFDHCHAHGBGBGDECECECEAEAEBFBFGHGHAADDFDBDGAFCFBHACAEEFGFAFDFDFGFGDCDGGFFF,False +977,16.0,17.0,23.0,22.0,27.0,15.0,19.0,22.0,EEGGFDFHCHEEAEDEHEHGCEFGBEBEBHBDDCBAHAHDGDAEGEGDHFECBDDDHDCGCFAAAAAFCEHBBEECEFDFDBDBCCCCEFEGAFFCFCFCEBEAHAHAHAGGHGHCHCBGEDBDGEEHCDGHBCBDAHFHBHFGGDHDEDAGECECBCDCG,False +978,5.0,8.0,11.0,18.0,14.0,13.0,11.0,18.0,HFHDBAGHGEFEHCGGEGDAAFHFEFEFDHDGCECHHEHEDEDHGHDFBFCDHHHAHEHBCBCBCDCDGDECEDGDEBFGDCDEBGHFBFDCDFHFDA,False +979,22.0,10.0,19.0,14.0,19.0,26.0,19.0,18.0,HBGDGHGCGBGEFEAEFBDEHEAAHGGGGHDHDHFGEABAFAHEHCACFFDFDFAFECGCDCDCDCFCHCFCHAHFDCBGAGDEHBGEAFAHAHEFAGHEAGACEEEFFFFEFHFBFCFBACGCAFAFCBEFEGEFCGBDDDCAAAH,False +980,9.0,10.0,16.0,13.0,13.0,13.0,17.0,6.0,CDCEBDGFGFACEBDHFCEHACADBDBHBCBGACCECEFEFGFGACHCACDEEGGGEGEGDGCFFFGFDBDFGGAGAHACDDDDGEGFCFCEHBBEB,False +981,19.0,23.0,15.0,12.0,16.0,18.0,17.0,17.0,ECEDHFHFHFAGAHBHDAEFGFBEHGBGBCBHBCEDGDCBHEAGADEGHFHDBBABEBAGAGCCDADHDCGBBBEGAGAGEBBBGFGFCCBFBFEGHAEGHFCFCFCACEDHDAAAAAHDBFFHFEFCBCBEBEFHA,False +982,21.0,16.0,13.0,14.0,20.0,12.0,19.0,12.0,EBEBGBGDGEGECHCHFAAEHBCAEBHBECECACGCDCDCDBABAFABGHGHAAEAHABDEDEFHFGBCDAEAGFGECDHGFGDDDEHAGGGEGBCFDFAFBEGECEHAFDFGABADAGAEBHFAEB,False +983,22.0,16.0,20.0,28.0,16.0,18.0,28.0,14.0,CGCGBDCDCGHACGFDFDGDBDCFEFEFADAECBDDDEAEAEAHAHABGDFAAGFGFGCAAGEDEGFDFDCGBGAGBGHHHGABCBDBDFDFCFDFGCAHAGACABAFEFAGEEDEHBCCHEGBBBDBDHGEDCHCEFAHHGCDHGGFGDGDGDBEGACDCD,False +984,26.0,22.0,19.0,22.0,24.0,27.0,32.0,24.0,ADHHEFAFADABADAFABCGCGAGFGFEDADABEFHFHGHDFGEGADCCFHHHGHGEFCFCEBDGEFEFEGAFBFBFAHGBEBEAGDFAHABAEGHGCECEHBHBDCFFHBAAGAEAGBCCDCDHDHDBDBGBEDDDCBBFBGEDFDHGEGEGEAFAGGBGBHEGBGFGDECHFAFEHHFCGCGEGCCHCHAAFDG,False +985,7.0,9.0,7.0,9.0,13.0,11.0,7.0,5.0,FCBCHEDFAFHEGBGFAEAEAEAFGDGDBDBABAFGEGDCHCHEEBFCEEHEBEDEFFDFGBDBCCFD,False +986,8.0,13.0,17.0,13.0,13.0,11.0,14.0,10.0,HGEDFDFDFDHDHDHDBFEFAGAEBEDGDHHFBBEEABBBFBHGHCCBCEEGECFBACDCDAAGCFCGBGFFEAGDGHCCDGEGCGCGCHCECBCACEB,False +987,20.0,12.0,18.0,25.0,18.0,18.0,21.0,30.0,AAADFHFAADFECBCECEHEHADCDGDGDCFHFHGCGCGFGFCFHDCAHEEGDGCECHCHEBFBHGHGEFHBHFGDADEDHDAFADEHBBBEGEFHADFDBCGDHHGHGHGDGDHDGDFCFEGGFGCAAEAEBHAHADBHEAADHDCECHDADHCHBHFHAB,False +988,20.0,13.0,12.0,16.0,10.0,14.0,25.0,12.0,BBBCHGHGAGFGHGDCACHCHCAAAAAAEHBDBAFDGDGDFCGGEBAFDEDEHEDGDEDADABCBFDGAGAGHGAEDBGGGGDGBFBHAAGBGHDFEFGAEECCGFFBFGFGHCHAFFCACD,False +989,12.0,14.0,12.0,10.0,10.0,5.0,11.0,8.0,AEFEBABAHACGFBABGBGDEDGDEBBCBCHCECBCACDCGHGHGEACFCBBBEFGDDDCDBDADGEHAACHEGAGFBEHAH,False +990,22.0,22.0,18.0,21.0,13.0,23.0,11.0,18.0,AHAHEFFDDCDFGHDFDECHDHABEBCBCEAFBGGGGFCHCBCHHBEDFAFABCHCBCBCBABDDGHHDBFGEEDADFECGBAECEADADADAFFDFBFBFBFAHDFDBHBDEAEFHFGAHAHAHACCBBABGCGCFHFAFDFDEBCA,False +991,10.0,6.0,7.0,9.0,6.0,4.0,5.0,5.0,FDCBCGFHFHBBBABGDFDAGACACEEECAHDDGDEAAADADAECECHDBGH,False +992,9.0,13.0,4.0,15.0,7.0,15.0,17.0,13.0,DEAHFHGHBEGEBBGFFFAFDFDHDGDGHGHFHFDDDCEGBACGDBDGDEHEHGHGBGBGHFBABABFFFAGADHDGGGHFACBFEDDBCAFB,False +993,1.0,1.0,4.0,3.0,4.0,6.0,1.0,3.0,EFEFEFAFCEGDFHHHDFCBCDC,True +994,16.0,14.0,21.0,15.0,11.0,19.0,16.0,24.0,AHACCCDCAAFBFEFBDBAAGAHHCHDHEHAHEHEBGAGAFHFCGCEFEFEDACHCHCGGGFDFCHCDDDHDHAECHGBGBEHCFBDBGGFHFGBAFHFCDADCFCBCBCEHAHFHBCEGGGFAHBHDCDFHFGDB,False +995,7.0,6.0,13.0,6.0,12.0,13.0,4.0,9.0,CEAFHCHFHECCHEACFCFGGAGFCHCHFAFEDHHCECFBDBDGECHDFEEEEEEBABACFCFDFDFBAB,True +996,4.0,9.0,13.0,8.0,5.0,3.0,3.0,5.0,AGAEADDCACBCBCDCDEHECCFHEDBCBCDDDFEBHBHCCCBBFHGCGB,True +997,3.0,1.0,1.0,6.0,4.0,5.0,7.0,3.0,DDDFHEHCGFGFGFGEDAGAEHFDEDBGAG,True +998,18.0,17.0,15.0,15.0,11.0,15.0,12.0,20.0,EBCFCHHAACHCHCHGBCBCBCHDADAFAFEFDFDGHGHCBCFFHCACDFAFAHAEAEAEFEBCHAFBHBFGAEDBDHDHFBCDEAGABBHGADDBDBDHHHEBAGCEEHFHBGGDGFGAGDB,False +999,6.0,13.0,8.0,13.0,6.0,19.0,12.0,12.0,GDGCGCHCAFGFEFBFDEDHFBFBDBGFDADBFBACGBGDGEFBHHHHBDAFGFGBGHCFFECEFEFBAHFDFBFDAHCHDHCHDFDGB,False diff --git a/tests/results/nb_gm_002_2back_240trials.csv b/tests/results/nb_gm_002_2back_240trials.csv new file mode 100644 index 0000000..1c50201 --- /dev/null +++ b/tests/results/nb_gm_002_2back_240trials.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,ralph_skewed +0,30.0,39.0,31.0,30.0,32.0,24.0,27.0,27.0,False +1,33.0,23.0,27.0,32.0,37.0,34.0,25.0,29.0,False +2,31.0,20.0,37.0,28.0,31.0,32.0,26.0,35.0,False +3,27.0,32.0,39.0,24.0,25.0,34.0,35.0,24.0,False +4,34.0,24.0,38.0,28.0,31.0,29.0,28.0,28.0,False +5,29.0,24.0,36.0,31.0,32.0,32.0,31.0,25.0,False +6,25.0,38.0,28.0,30.0,33.0,30.0,26.0,30.0,False +7,27.0,30.0,30.0,29.0,32.0,26.0,33.0,33.0,False +8,24.0,36.0,32.0,23.0,30.0,29.0,35.0,31.0,False +9,35.0,34.0,30.0,29.0,35.0,26.0,23.0,28.0,False +10,30.0,25.0,33.0,31.0,27.0,37.0,30.0,27.0,False +11,28.0,28.0,29.0,26.0,28.0,27.0,34.0,40.0,False +12,35.0,27.0,30.0,29.0,26.0,30.0,36.0,27.0,False +13,38.0,27.0,31.0,27.0,34.0,23.0,27.0,33.0,False +14,29.0,30.0,28.0,35.0,19.0,30.0,37.0,32.0,False 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+19,10.0,14.0,15.0,8.0,25.0,14.0,11.0,20.0,EEEEBEEFHEHEEFEEGHEAFFAFHACGDCDDCFDCBDCBFFBCEAHEAHGCGGHGCHEEAEAHEAHEHHCCFGHABHGFGCHGCFDFHEHBBBDFBFBCEAEBHCDGCEEEHBBHB,False +20,16.0,9.0,19.0,17.0,10.0,22.0,10.0,24.0,HFGDDAFEAFEDCGHAADEHDBHAHDCGBAHBECEFFFFFEFEEDHEDCACEGHBGCFGAGGABDHFCHFCHCCDCFHHADFCFFCFFCBFCDHHHHDFFGHHDACDAFDACDCBHCHHAGHABHAB,False +21,6.0,10.0,3.0,4.0,7.0,3.0,3.0,4.0,EABBAEFHEFABAACHDCDDEFBEGHEGBDABHBBCBGEB,True +22,6.0,11.0,12.0,6.0,9.0,6.0,9.0,10.0,AEDBCDECBCHBCBBGFBGFHGEHACHAGAEFBDAECHCFHFDCCECGBCGECGAHGBHBHEBHDFGDE,False +23,11.0,8.0,12.0,13.0,7.0,5.0,13.0,9.0,EAAGACDACDHEEGGGGGBEGEABEAHGCHCCAFCFFGDHGDGCBGBDDEAFAADCDDCDDHBCGBCAFCBDDHHBHH,False +24,36.0,26.0,18.0,26.0,33.0,19.0,21.0,15.0,GBCHFHAAHAFFGBBEFBCFAEFDFGEGEEBECBEBBABBAEBEEAEEABGDBADBACFFBEFCECGACFADABCFDCDBCBBHDHHACGGEHDEGDEGAHAAFAAEDCCHHDDGDDBDGBDBDDCDAGAAFHEDHGDACDACDBGEEACGAEEBEHAFHBGAAAAAAAEEFBEDCDAEEEFGEGGHGFEAFED,False +25,11.0,17.0,16.0,9.0,15.0,15.0,6.0,9.0,CEEFABDBGDBFDFFDGADECBFCBCCACFABEABFABEGBEHBAHEAHEAECCFFCHDCBBBFGBAGCDFHHFBDFDCCHHEHAEBEGCCBFEECEF,False +26,8.0,5.0,15.0,9.0,10.0,7.0,11.0,5.0,ECAGCHDBBDCCDCGHBBEEFDHFEEEHBHGADADGFDEFGAFGAFCCCCCACCDCDGGECGECGEAGFA,False +27,9.0,11.0,8.0,5.0,8.0,4.0,2.0,4.0,FCAFDBEDBABAABAEEAEHDBHCEHCDBCFBABEEGECGBDABFCCAHCB,True +28,6.0,8.0,11.0,7.0,10.0,5.0,9.0,9.0,CFBCBCCBACBEHBEGCADHDGFEGFHGHDAFBAFBEDCDGCHGAACHCHBCEEEEDHEDGEGGH,False +29,24.0,16.0,18.0,25.0,13.0,19.0,26.0,18.0,HEFHCDEGDHFBACGGDEHDGHDGFDEAHFDHGBHEBGEGADFFGCCGDHFBFABDACDABAGFGDAGDAGCAFFAGHHCDHCHACEDDAFDCCDCAECAEDGEDGAFGFCGFAGBBGFBDBBAABAAGADGAFCHBEEGHBGCBFCGFAHHCHDBDDE,False +30,6.0,5.0,2.0,9.0,2.0,4.0,3.0,8.0,DADBAFBDFHDHHBAHEADGFBHFGHEAHDHBDGDCADC,True +31,19.0,18.0,16.0,13.0,19.0,13.0,14.0,15.0,FCHGCAEHAEBDEBABAABHAFEBDCBDCBHCGEAGEFBAFCCECCBCFHEHGEGAEDAECBECEAFEBDHBDEAGFGHDGCDGADFAHGCFCBFDEHEGCEABFADHAFHGBHABHBHDAEBGDFG,False +32,7.0,12.0,12.0,10.0,7.0,5.0,5.0,9.0,EBDGBGBBDCBACGHBDAAHEBGCBFHBFGAFEHFCCCHDCHDCHDAHDCDDEBDEAFECBAHBECC,False +33,1.0,4.0,8.0,1.0,4.0,4.0,5.0,3.0,GAECEGFBHFGHBGCBFCECCECCBCHDGF,True +34,5.0,4.0,6.0,9.0,13.0,13.0,5.0,7.0,CHHEFFDFFDFFDFDGGDFGDHCEAEAHEAFEBFCFEEFEECAECHCHFDEBDBGEGABDEH,True +35,3.0,2.0,3.0,3.0,5.0,4.0,0.0,6.0,CBDEEHHEAHCAEBDFADFHFCHFEH,True +36,13.0,2.0,13.0,8.0,7.0,6.0,16.0,9.0,DEGDECDHGAHGEDGEGACAFCADGACGACHFDACHCCHCEECGHDHBEGGGGCADCAFAGFGGBAGCAHFHFA,True +37,18.0,19.0,17.0,17.0,13.0,17.0,15.0,23.0,HBCABCGHCEEADEDCEDGAGFFFHDFADHHBHHGCHFHHAGHEHEBBBDEFECFEBHCDAADFGDFHDCDCCDCCFACAACHGGBGGBFBCFBFFCFGEDABDBBDAAGAABACBEGBAHAHHFGEDGHDHHEBHBHF,False +38,4.0,6.0,5.0,9.0,6.0,4.0,4.0,6.0,AGDAGHABHCEEFBEFDEHDBHDECDFCDBHDEGBBGCCADFDH,False +39,3.0,5.0,6.0,8.0,8.0,2.0,8.0,6.0,DCEDEEGEEGAAFEHFGHDGDBHDBGBBGECECDGHBGCDDCHCAH,False +40,0.0,0.0,1.0,3.0,1.0,3.0,5.0,1.0,GDGGDCEHFGFDGF,True +41,20.0,19.0,22.0,21.0,30.0,22.0,10.0,26.0,BADBABGCFGFDDDADEFHAAHAAHEAHBBHECFGFDEHDCDBBBHGEDEECCDCCDGCHHBGHCHACFDCFCFEDFEDAHHHBHAECABDABAAEHFEADCFEBFAGFGEABECFEFFECEEFEHFEHEEHDHDCHBBHBDHCEHCDHBDCFAEFAGHEGECBCFEEFE,False +42,3.0,7.0,4.0,4.0,5.0,2.0,5.0,3.0,EBBEAEEHDCHDCGDGGBACBEHBDGBAFBFCG,False +43,21.0,15.0,21.0,27.0,18.0,33.0,14.0,23.0,DDDDDDBCGFEFFABFDHDAGCEFHHACHGBHGBEFEHFEHFCFFCHDGHDFHDAGFECCCAAEAAGHGDFCHFCHBBBFABDEFDFFBBDBAAFDAFAGHACHACEFFEFDHABCAFGDFEDCGACFADFDDFBHFAFFBEHBEHFCHEADEGHEGCDGHDHDEECCFCCD,False +44,27.0,34.0,20.0,19.0,15.0,29.0,27.0,26.0,FGCFGADGADGDDBDBAFGAFDHHHAFBAEEAGGBDBFCEFAHFAHFAECDCBBCGBHAFHABHDCHAHHGBCGECFDCEHCFBCHBGHCABFBCFBEHBECBAHBGDECHFDFBDEAFBBGECGEBBHDBHDBEABEBFCDFHHFGHFAFFGCACFGDGGHGAABCDBHBGGBGGFHGHGGBEADABFABAAFAFF,False +45,15.0,12.0,15.0,7.0,7.0,15.0,11.0,5.0,CAFCDGCFACFCCFACGBBGCAEAEGAHFADBCHACHFCFBEFGEGBDGBDGBEGEHAEFGBFCDFBFBHACAFCAFGABDAFACDB,False +46,12.0,10.0,7.0,5.0,4.0,11.0,11.0,13.0,ECFFHGFGGFCGACGFGGAHFABBHDEDCHABFBHGAHGAHCAHDABDFHDFGCHGBEABAHEHBFHBFCBAA,False +47,15.0,6.0,13.0,11.0,17.0,21.0,13.0,9.0,EDCEFAEFAFFAGHCFCEEAFGFFHFDECECCEGCDGHDGHDGHACFFCFFCDFEHEEFEEGHEDAFBGEAAHAAGCABAEFAFDABGFCFHCDEDBABFGBGGD,False +48,11.0,17.0,17.0,9.0,17.0,17.0,13.0,15.0,GAFGHHGCHBCACCFBCFHHECHBHAFHEEGBAFCAGHGEFGEDGFCBBEBGABCFDCFDCFDBEEEGAAHDAEDFECBGCBHDBFEGHHBFGBFEBFCBCCHEFAEDAEDCEFHB,False +49,13.0,16.0,15.0,12.0,16.0,9.0,12.0,15.0,BGCBAEBCDBEDBECBDCBABDCDFCDBCEGDABDFFEHCEDGECHACHEBDECDGHFFHFHEAHAHHEFFBAGAGHCHCCHGCEEAAAAGEEGDEGBFGBAGBHHBH,False +50,13.0,6.0,16.0,14.0,12.0,13.0,9.0,12.0,DAEAAGAAGCHCCHDFHEFCCBEGFEGFHAHEAGBGCBFCBFCDACDAFDCHECEBFBAFCFFDEHAGHDEFDGCDECEHCHDGADEHHFADCDD,False +51,22.0,27.0,26.0,19.0,24.0,22.0,28.0,20.0,FDCGDAACFACHGCDGEBFCBDCBGBEGBEGAGGFGGCHGDHGDCAACHADHCFHAAEEBBCBCCBAEDAGBFGAFGEGGDGHCEEEDEHCBBCDECEBGEFCCHCFBCFBHFEABEBDEDHABHDBFFFCEFCEDHFFHBFABHAGGECAEADBGGEGAABHAGHAGEFGBFBFHHDHBEGBFCCDD,False 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+79,23.0,23.0,29.0,21.0,13.0,23.0,22.0,17.0,CDHBACEAHEFDEGHAGAAGFAHFADFCBBBEFBCDGFBCDBDHGGGGCGFBDBBCFBFDEGEEHEGGBGEHFCCFCBDCEDAEABFDHHBFBBCAGDDCHDCHDAHBACAGCAGCADDBDFHAFCAFCGHDEBGHBCHGCHFBEGBFACFCCACAADACFACFCCFGFDG,False +80,12.0,12.0,23.0,9.0,27.0,13.0,18.0,19.0,EGFECEECHEBEEHHFBDCGCAACFBCGEHEEGCEACEGDEADAGBAGBCDBFBHFHACHCDHCDHCECCEGFHGFBABCGDCBDCEACHBCGGAEEAECFEHHAFFEEFHFCEFCHGGGGDHBEHGGHEEHE,False +81,25.0,15.0,14.0,17.0,20.0,16.0,15.0,15.0,DGDFFBFFCAFHADGAEEAFDABDEGGEBGDGEDEBAHAAEGABAHCACEACAHBAGGECFCDDEDBEFHEBGAFCAFCAHDEHDAFAGFCDBCHCCHCEDBGFGHBADBHGBEAAHAAHAEFECFEDFEDHEBHGB,False +82,23.0,16.0,15.0,28.0,9.0,16.0,15.0,26.0,FAHGHHFHGDHGDHDHCCHFBHEDGDGADGBDFDHFBBEDBADEDDBDHFDACDBFGBFAHCDDDGDBGBBGAAADCHFCHCDGABFHDDHDAEDCEDCGDFEAAEACHHGHDGCFFCHABHAHHAFCFHAAHAACBABBHFEAGEAC,False +83,16.0,17.0,21.0,14.0,11.0,17.0,24.0,19.0,EGHCBBCBBHFAHAAGAFGHBCDFAGFBDABDADEEDBCDBCHBCBGEGFFGFGGCHGCGGHHADHDHCDHAFGACCEHDGHFFCDFEDAHDFFAFFHEGBDGCGCBECECHBGHGGHCGBCHBCEGFGGFCACAABAE,False +84,25.0,24.0,34.0,20.0,21.0,23.0,18.0,22.0,GCCGAFHHFBGFBCFBDFBGFCGDEGCAHEBCAFCBFHEFEDCGFCAFCHCHBCHEAHAFBAFDAHBHBDGAABAFBACACHHCFDAFDGBAHBEBBEDFCFECAEBGFHECCCCCCHHEEHAAFDGFDHBDGBEFBEDDHDDEBHECCECCEBAEBAGACGEDGADCBCCGGCDEAGCADCAFHHD,False +85,14.0,17.0,15.0,14.0,15.0,14.0,16.0,10.0,GGCGDDEBFFHGFBGFBHFHHEDAACAABGFFFCDBGBEHBEDBFDBCDCDGCDEFBCHBEGBEGBEFHGFBAEBCEFAAGGCHCCFCCBCHEHEAACADDEDDAGDAGEAEBAG,False +86,5.0,2.0,1.0,1.0,1.0,1.0,3.0,1.0,ADFAGGAHGBEABCA,True +87,28.0,33.0,23.0,19.0,20.0,25.0,30.0,22.0,FFGDBGHBGEGAADDHGEEDEHBBACDFCGFCGEHFBBFHBFBCCGCCFHDFCGHBECBAAFFDBBCBECGGFEGECCAGABBABHAEHBBHBHDEFDCHDBAFFDDFAAHAAHCDFCAHEAHGAHFAHAGHAGAAGEEDFGBEBECBGCBAFBGCCGAFAAFHAGGFGGBGGBDEEGEGBFGBFHBCHBDDBDDBECCA,False +88,27.0,30.0,28.0,20.0,23.0,12.0,23.0,29.0,EGBCBBCEBCHHGDBECBCDBEDGEHGAGACGEHGCDACFECFCBHBBFDAHCACBACBEFGGAGGADAAEBAHDFHDCDBAHCHHBHABGCBEEDHGHHGFHAHDAEDABDGCDECDBADBHHGHHGFGECBEABDHFDGAHEACFGCAGCABCHBFECHCBFCBFAEABDAGEHEEAECABDHBHHCEBG,False +89,14.0,15.0,7.0,17.0,10.0,11.0,15.0,9.0,CHBADFABGHBGFGGAGGADGDEBHADHGHGFDFDDCDBGAAGHAGFAEEBBEDBEBCEBFAFDAFDFGDEADEGDFACCCGBHBBHABHDEDCBDFE,False +90,5.0,3.0,3.0,1.0,8.0,0.0,6.0,3.0,CCACEGHEGDEGBBAHEHGBAGEAEEAEG,True +91,0.0,0.0,4.0,2.0,4.0,2.0,2.0,1.0,GDCFDCEECGEHFEC,True +92,14.0,4.0,7.0,10.0,8.0,6.0,12.0,5.0,DCDAEFAFCECEEAFEDFEGCCGACBDGHFAHBGEBGAGGAGGDGAEGHHGAADAFDADDCBAHDA,False +93,10.0,8.0,8.0,3.0,8.0,14.0,16.0,15.0,FAGFDGHDHHEHEEGGFFACFHEHACCACHFGHFGHCGCAGCGBCFFEGFGBHABHFDHGBGBHABHAFFAGFEHEEBBAGG,True +94,21.0,25.0,21.0,30.0,27.0,13.0,12.0,17.0,HHBEBCAACEABDGDGBDFBGFCAEHGDCADCHDCEDFEDCEDGDCEDAEGEHAADBBDAADHCDHDFHBEEBEEBCEGAECDEBBCGAHEBBFFHEBHEHDAHDAECFFDFEDFBDABDCCACEDEBDHDDAGFAEABECBHGFDDFEDCCBHCBHGBEGBACBA,False +95,4.0,6.0,6.0,8.0,7.0,6.0,6.0,9.0,EDGEBHEFHACBBCFEGHCHDAHDEHDBHDBDDEHFCGECGFGBFACFAHGD,False +96,8.0,5.0,5.0,6.0,5.0,8.0,12.0,12.0,AFACCAGAGGFBEHEGHECFDFFDGFHGAHGHHFDGAGCAGEFGHBBHEBHDDHDHHGCBA,False +97,20.0,25.0,21.0,20.0,27.0,26.0,25.0,26.0,BFCFGDFBECHDCEBGEFGBABHGDDGAFBEBCEFEEFGDAHFBHEHHCHDDHGEFDFFBGBBAEGCCFDDABEBBEBFHBHHBCCECEDCAFCGFGHFCBGHBEAFCBFDEEAEEAFECEBBGGAGHBDHFHHFHHFHHFHHEEHGCDABGABGACGAFGAGGDDEDDCADCFGAFGDCAHEAHEAEGC,False +98,4.0,3.0,1.0,1.0,6.0,1.0,5.0,3.0,BBAHAEDECGEAGBAGEEGHEGHF,True +99,21.0,17.0,15.0,21.0,17.0,23.0,10.0,21.0,AHDDHEDGFFGCFHDHAGHGHHDDFADFABHDBCCACAAHGDDFDDFGBHEBHBHEEHEFCFFBBDDBAABCEEHDACDHCEEAAEBHBFABFABCABFFFFDFFDFEEFCEHCEBDEBFCAGAGGDGCHBCHAAHEFFECAADH,False +100,21.0,17.0,13.0,22.0,21.0,22.0,21.0,31.0,GCAADDGBDEBDABDGDGGEADEDDFHHHEHDGHFGHFDHGAFAHEHDCHDHFEBGEACDACGABGABGFGGDGBHEEHEFFGHFABDHEDAECBFHAGHAHBAEAAEAFEHFEBGGBCFDFEEAHCHHCFDAFDCFDBFHBAHCHHFFGEHDECCGCBHFHHFBHBE,False +101,3.0,4.0,2.0,2.0,2.0,1.0,2.0,2.0,BCFBEABEABHADGCHGD,False +102,3.0,5.0,4.0,4.0,2.0,1.0,3.0,10.0,BGHBGHCCHCDHEHHABDFHDBHEGCDAHBAH,True +103,22.0,16.0,17.0,17.0,11.0,10.0,13.0,12.0,DECDFCDFEDCCBCCBCADGAGFAEAAHHCGECAAFHAHBAGEFDEFHHGGFBFCBACBABDACDAHDAGDGBDBADHFDBCEHGEHGDHABGBCEDEEHBAABADCGGCFCABDABA,False +104,12.0,15.0,10.0,16.0,25.0,15.0,20.0,17.0,GBFDCFDGDDBHDAADEBGBDEBEEFGHFGHFGHCGHEGDEADHBDHGGBGHEDCFHAAHACHGGEGGEFEBFGADCCEBHEGFEHDEHEEFAGDCHFEEAEEBCEGEDBEDBECBFFBHHCAFAEGAFB,False +105,7.0,10.0,8.0,8.0,6.0,8.0,6.0,10.0,HBEHAGHFGHBGDBAAGCDEHFEBEHBEBCABAACDFHBCHDFGDFGDFHCHCCACBFDBEDF,False +106,17.0,20.0,9.0,15.0,13.0,17.0,14.0,15.0,FBEAGDAGAABAHBGEFFBFFEDHEGHEGHEFHFDBBCBBDBCHCAHGAHCHBEGFDGFAEBAEGADCAHBDFBDFDFBABHEFGBCDAFDBCAGCFBHFBAFAEDHEDCEDHBDGGHGA,False +107,5.0,5.0,1.0,5.0,1.0,5.0,5.0,2.0,FABAAGDGFDFHBFEBAGBAGBFDDHGDC,True +108,17.0,16.0,20.0,15.0,16.0,19.0,21.0,30.0,CBHCHHDDDGADGAFCEHEBHEFEAAEBHFHCBGFAEDHEFEFFCFFAHEHHAHBGCDCHFGHBGFCGFBEABFBHHGHHGCHEAHEADABGHBHHBDHGDHGAGGBGGEFCFFCDBGDFDAECEECGCAGCGDCFDFHHAHHDHBBCCACGAC,False +109,19.0,26.0,19.0,10.0,27.0,23.0,8.0,14.0,EBCAAAGFADFADFEFBBBCBEABEABEAEEHEEHEECEBGACCAFCBHCDCCECFBCAGGAFEAFEFBHHBDFAHEHFEGFHCFBBHCCABCHFFBFFBDGCEGEBAEGCFFEEDHFFBFBADBDBBDBBEHEEFCHACBAHDEE,False +110,19.0,10.0,10.0,17.0,15.0,14.0,13.0,9.0,EACEADEDDGDAEBCFACEAEBFHFFGDFEDBBGBHGCADCFBBBHCAHEAHFAHAAHCDGCDGAEGAEGEDDFGEAEBAGFCGDGDDABDFCDFGFFAAEDFEHAH,False +111,6.0,10.0,13.0,9.0,4.0,7.0,3.0,10.0,CCCAFBAFBEHDFBCCBCHBCBCGHDAHDAGDCDFCHCEHDAFDFHDHHDEEBFBAGBCHBC,True +112,14.0,15.0,18.0,9.0,20.0,11.0,10.0,7.0,DEFDEFBEACFGEFCACCBGGBHAAEBEHCEGGEDEEFEEDBECBABGADFADFADGCHCCHCHACEDHEGAFAEFBFBAEACCAEBBGBBGEBEBHCCDCCFC,False +113,18.0,25.0,13.0,24.0,29.0,22.0,19.0,30.0,HCAHEABDACHBBDDHADBEHEEHCABCFBHFBABBABDHBEHFGAFGFHCHGCAEFHEFHGHCGCEHDDFEBFEFFDDHDEEDGEFCBGBDGAHHCHDCFDEEDGCFHHFEEFGBGGEEHBFAGFDHBEGFEDCEDEBDEFHEAHEAHABBEDBGFBGEHGAHFADBADHADHEDBGGB,False +114,13.0,9.0,15.0,32.0,17.0,18.0,11.0,14.0,HDHDDAGGFDDFHBFBCAEDGEDCEACDDEEDFHFAGFDECDCCDFADECFECHDCHDGAGAHGHDFEDCEDCEHBHDAHDCFDBFHHGDBDAFCGFAHFDCCDAEDGEDEEFADFAGFBBDEBDEBDF,False +115,21.0,18.0,26.0,25.0,21.0,27.0,25.0,34.0,AACCECDFFBBDABHAGHGFHGHAFHBFHFEHCBHFDAGHAGEDBEACHDCAGCDCCDBEDBDDEGGEHGAHFAHDBFGHFGCDCCFCBFCBHCHHFFDFGEEEDHFHHFHDFEDFDCBHAGAAGHBEEDCFFCHEDAEBAGDEGDEDBFBGCBECHCGHCDAGGAHGHCGHCFHBFHCFHDADAEGEGHCGAFFEH,False +116,25.0,15.0,25.0,18.0,19.0,11.0,22.0,30.0,BGGBGDHGBAECHEFABDHBHHBHDADBEEGFGGDGCCGFCHHHAHAFHBFEEGEAHCGEAGDCCHCGDAGBAGBAEADBADHADFCGHEDHCABCHHEHDFHFAHEAHCHCAHBDHBGHFGEFCAGCHGAAACAACHHDHCCGECEDDFCDACDACBCCEEGEE,False +117,28.0,24.0,15.0,28.0,23.0,30.0,14.0,19.0,CHACHAGEBEFDCFAGFADDEDDBDGBDBFEBEDHHDGDECDEBFABFAFFABAAHHAHHDFHFBHDBEDADCBGHEDFFDEDDEBEBAGADDFFFBDFBFFBFFBHACFDBFDFAEBACBACGEGGCFAFEHEAHECHBDGGFCAECFEFHEHHAGACBDCBAHAAEAAEDECDAFGGFB,False +118,0.0,3.0,1.0,0.0,4.0,1.0,0.0,2.0,FHBBEEBEECH,True +119,15.0,14.0,10.0,15.0,7.0,12.0,18.0,9.0,BGDBGBFEBDCFAFFADCGGAGDABAAHHAHHACEBCDDCBDAGDGBBGDGDDACEFCFFCGFHGBEFCGACHAGAGHAGDABBEEFHGFBFDBEDGHDG,False +120,18.0,23.0,21.0,12.0,21.0,14.0,26.0,15.0,GBBHAAEBAEHEEFEGFGCAECABAGCADBEFAAGDABCAGGFGGCHGCHGAHEAHFFCEHCEBBFBBEHBCGECGACGDCGDHGCGGHGGDDGHACBBGDBDECDCFABECFEBFECEBGBBEDDEGFCDFEGBHGBHAHFACEBCHBF,False +121,18.0,17.0,15.0,11.0,14.0,12.0,17.0,17.0,AGGAFDDFCDBBHECHBCHADHCBACFACDDGFACEBCBBGBHAAHEAEEHGFGCFGBHEBAFHAHHADHBEGBHHCEFEEFGHFGFGCBDCADGBDHHEBEBBAADAAFCAGCGGEGGEC,False +122,19.0,12.0,14.0,16.0,13.0,13.0,22.0,12.0,DFAEFDEBHGFEEDAEDFGGCGGFGGFGGAGGAFFDEAGEAGDBBABDHHCHHBDHBDGCGGDHDAGCACCBFCBABHEFHCCHECBCGDDAHDCEEFACFBCAGDAGAAGAEFAGDBEHA,False +123,3.0,8.0,5.0,11.0,9.0,10.0,4.0,11.0,EBFFHHFADFCHFGHEGHFGFACDEDDEGHFAEDHBDEBDECDCDDFHBFEBHHBCEBHDB,True +124,4.0,5.0,6.0,11.0,9.0,6.0,5.0,8.0,ACEACEADEDEHDCFFCDCCEHHEHEBHGBDGHDFDFEGFEDBHDHDBBGFAGD,False +125,11.0,14.0,19.0,12.0,21.0,14.0,17.0,9.0,CCDCBDBEDHEGHAFEECDGCFGCEGCBGEFAEDACCHCDHGFEFFBBEABEAHHAFCCFBFFCFCBEGDACDGCAEBAEGGEDGEDCAGGEDHEBHBBACBHGFEGEGDEGEFCBF,False +126,7.0,15.0,16.0,15.0,17.0,19.0,21.0,17.0,CHHHDBCCEFEEBEGBHFEDGEBFFBGFGHHGHHGEHDHCDHCDFAFFDCABAFBHGBCGBFHBDHCEGAGGHHGDEAFECHDBFGBDBCDECGEFEEBECBDFFDECGGCGADGEDGFGCFGCFAF,False +127,1.0,2.0,2.0,2.0,3.0,3.0,7.0,2.0,BEGGGGACFHCFHEFDGGDEGB,True +128,24.0,27.0,28.0,25.0,25.0,12.0,31.0,20.0,GGGBGGBDBCDHGACGEHDCHDCBDCHHEHBGHADDADDEBGGHGDDEADFAHFAGGEGEEABEHDEHCEBAEBECBACBACGACGADFADBBBBFCCAEGHFBEBCAAHBCHFCEFCDFCDCCBAEGEGCAGCGCCGEHFEHGCCACAACBDDBHGBEBDAFGEFGBBGHHEDGDABCGFHDEGGEDEADB,False +129,8.0,19.0,18.0,15.0,11.0,19.0,15.0,9.0,BEEBFHGAACFBCEBFHFADFCDHCDBCGBGGEGBDAADFDCHECHECEGCFGCFGFBCFGCAGDFGFFHHBDDFCDFBBEDBFDGDBBFBHABCEBCDAEGCBFHBFCGECGD,False +130,19.0,16.0,11.0,13.0,12.0,17.0,19.0,19.0,AGFEGFGGEGDAFDBFDBCGACBHEHHAHHDFADABHAGHBFHDFCDCADEEFEGBDGBEGADBAHFGBDGBAEFAGFBCAECHGBGFBGBBFBHAHHAHDEGEFAHADCACCHCEHGAHFHGFCF,False +131,4.0,4.0,2.0,0.0,2.0,2.0,3.0,2.0,FBECAGHAHCAGBAGBEFB,True +132,21.0,22.0,26.0,22.0,19.0,22.0,19.0,31.0,HHACHAGHDFHCACFECAECGDFFDFCAACEBEDHHAHDCGBCBBCAHCAFCDBGFGDCHBHECHCFACFGCHECBBCFBGHDGHEGHDGFBAADFGBGGFCGHCBHAGHFEEEDAEDAHHABFABHAHHGHBFDAFDGDDFEDGBDFEDHDDHCEHEAHECEECEADBGCBFFHCFBBBBH,False +133,16.0,18.0,20.0,18.0,16.0,13.0,27.0,16.0,DGGBCEDCEFHDGHFBDCHFHHBACBADAAHADEACBGHFGEDGCBCABGAGFCGDCGDGBEGBEGBECEEHGEHGHHDAAGGACBDGBGCBACDEBDBGCFHFEHCEGCEAEFCHFABFEGGCDHFDCDDCDBFGBFGAGHAG,False +134,19.0,21.0,15.0,10.0,12.0,12.0,10.0,11.0,DAGDAGAAHHFHABCBBCEBCFBCGDCGEEACACBACEAFGBDAAFEAFEHBBBFECDEADGFFACGECBBCBBGEBFEBDAACHADHFEFBCHBFGBHDBCGBHADHAH,False +135,13.0,9.0,13.0,6.0,13.0,9.0,17.0,10.0,ACEEHFBHFBGFCHABEADHHCGACGDHBCABEGBEDBGGCGHHAHCEDAEFAEGCEACEAGGFCGCDGBFGAFGAFBEGCEGAFGECHD,False +136,12.0,12.0,9.0,6.0,6.0,6.0,7.0,12.0,DGFDCFBCHHHHHHHBHBBABEAFGBEGCFDFGCCBDABAAEAAHACCAGHADEACGHGEBEFBCDBHAB,False +137,8.0,7.0,7.0,10.0,12.0,16.0,11.0,8.0,EEHEGHGAHFFEFEDBGDBEBBGGFGDCGFCFCGFDDFHDFHAFCFDGAAFFAEHAEDFEGFEDCEGAEFBHBCDBCHA,False +138,16.0,20.0,15.0,26.0,16.0,10.0,21.0,11.0,BCEFDBCDBAHBEFBCAHCAEBDCCDHGHHCHDDDEGBFDFGCACAEEDGADGEDBEGCEHCHBGHBEDDADDGBDGBCGBDHCFGCGGFGGAAEAADAEDGEDBEBADDADGCDGBAGBDGBHGFFBEDAEFBF,False +139,13.0,8.0,3.0,6.0,6.0,4.0,5.0,4.0,EDGABAADGAECAGAAGAACHFFHABGFBABBEDBEHBAHCABDFDEED,True +140,3.0,7.0,9.0,8.0,11.0,8.0,12.0,4.0,FGFCGCCEEDFEBFEBDACHADEBCEDFBDEHEFBEHCEDCGGBGFBEFCGGDGHDGCGGAG,False +141,7.0,6.0,3.0,11.0,10.0,4.0,8.0,7.0,EEAAECEEGHEHDFDCHCGHEAAEHBDFBDBGDBADBEHFEAFGGDHDDGBDGADG,False +142,25.0,23.0,17.0,19.0,29.0,25.0,18.0,29.0,EEBEEBHHHHBCHEFDGCDECDEDBEFHAFGBFBHFBHFCHFEDFBBFEAEGBCBAAAADAHEEFAEFDFACHHCHBEHBHHDGECFEFBEGHEGHAFHCDBCAGHEGHGDHGEGGFAAFAHEEHBFABDACHABDCDAFGFFGCFECFHBFEEDDGDBFCAHAEDDEACEAGDBGAAGAHCBHB,False +143,1.0,2.0,2.0,3.0,4.0,5.0,2.0,3.0,CFDCBDHGEEGAEDFEFFBHFH,True +144,9.0,4.0,7.0,5.0,3.0,7.0,3.0,7.0,EFAFABHACHECHGCBADBADAADGCFFAHGHDFHDCHFCBECAF,False +145,21.0,27.0,26.0,22.0,15.0,22.0,16.0,17.0,FCDFDDECEHCFGCEGDABBGHCGBBFABAEFEEFACHBGFEABEDBHCCFGAFEEFHAFECFHCEBCDBCBAHFAHFCFFCFFBFAGGAECDCCBBDDCDDCABBAGGAGBAGHCHECDACBAFHECGBGGBAGBHBACCADDDDCHHHFHHBDDBDDBDBADBF,False +146,23.0,23.0,27.0,18.0,23.0,27.0,25.0,28.0,DEGHEGFDBFGHDEACECDFDDFDBBBGCEAFHFFHFEBGEBDEBFBBFHFFEFCGFCGCHGAHBCFGAAECGEGDDGCHGAHAAHAADDADCAFBFFBHBHEGCAHCHHBEACCBBABBDBHCBDFAHAEBCEGEGCBHEHFAGCAFCACEFHEFADBCGGCGHAGHGEHEFHCAHCGHDGHCEHCEFCGFDF,False +147,19.0,22.0,21.0,22.0,15.0,18.0,18.0,18.0,ADDADEFBADAHFBBFBBCHGCGBCBHEDCCDHDDACGEGBEACEBCGCFABFHEAHFGDCDDCGFCGHEHHEHBFHDFBFFBAFAABAADACDFCEFHADGADCCECDBHDBCGBAEBAHDHHDHACFCGFGEFHEGGCGEFGBDGBGBBDE,False +148,23.0,18.0,18.0,17.0,20.0,20.0,23.0,19.0,GHBGCBDAFDAFHCBEFGACAECHHGEGFEGDEDDBCAAGFAGCGECAEFBEACEHGEHAEAFEAFBCGCCFCBBGHBAFBFCBFAEHBEHBEGAACFABGEDGHAGBCGCEBDGDDHEAHCADFFGHAHDGHDGHDGBDABHAEDDFHDFCFFHGFE,False +149,11.0,9.0,14.0,14.0,12.0,13.0,8.0,11.0,CCFCGFCDFHHHGGHEDDFHDFEEGCEAHAHCADFEBBBCBFCAHBAHEACDDCDACDADDBDDBEGBDFFCEHEFBEFEAGEGFCGFCAHA,False +150,20.0,17.0,22.0,21.0,18.0,23.0,27.0,26.0,FDDHHBGAEAABAAFAHBGFFHEHCEBEBBEDBGDCGHCGHCFFEGFEDFCDACDAEBFEDAEDHHHFGHGDHGAEFCFGBEDAADCCGFGGAAGCHCDDBDCGGFGGFGGFHGFBGBCGECHFHHACHABDFHDHCAEBBEBGCCFHEHGFHFEHFEHBCACCACGAGHDDDD,False +151,25.0,32.0,23.0,18.0,29.0,30.0,21.0,16.0,CHFAFBDBCEHGEHEEFEACEFCFHHFCAGAEGBCABCAECHDDFDFFEFFGHABFFEHBBDBGABGACGACEDCGDEBDEBCEBFDCHBADBFDAADEFBFHGAACAACHDEADHCBGCAFBFFBFFBEBBGBEEBHDBFDGDAGFEGCABEEBEHBGHBGFBGBAGFGCEGCACFDGAEBEEFCEFAFHBCE,False +152,2.0,5.0,8.0,6.0,3.0,7.0,7.0,3.0,ECBDCEGFFGHCGCGGFBDFDDADDHEBFCBCCBFCGFGAH,True +153,20.0,20.0,31.0,26.0,22.0,23.0,14.0,22.0,GBGFBFFBHCBHCBHGBEFCGFHHHHEHDCHCCDGCFFCDDHFDEDGEGCHHADHCEECFECHECDGCDGADCAGAAHEDHCFBEFEDCHFFAADEADHADCGBCFBCFEEEEBGBCCCCBCDBDHBAHDABCAGCBCFBEHDEBDCFDHFEFDAACAEDADAFGEFABFDCEDAFAB,False +154,14.0,22.0,13.0,6.0,19.0,16.0,15.0,9.0,EEBFEFCBFDAAGAHBCCBGCEEAEEAEEAEEAEGGFHBCHBCBCHBCFACFGDECBAGFFDBHBBHGGFAGBGCBEHGADBFBBGGAFCAFCEGBEGBEFBDFBHEHEFDAFB,False +155,13.0,9.0,8.0,9.0,16.0,11.0,16.0,26.0,HGHDBHECHGCDGAEGFEHDEGGHHFBHFGHBGBEFEAHEAHBFHFDHADHBCHEAHEAHDGHDHHEFFACDCEBFGGEGAEHEGHEGCCGFHGAAAHAFHAHDEBBC,False +156,21.0,23.0,28.0,17.0,32.0,20.0,26.0,33.0,AGBGFFGFGGCEFCBFGBECECGECBECAGHDHEDHCBHEEAEEBFGGHEEHAGFFGFHHCCHADABEGBHGCHGCFBHEHHEHHGFHFFHEFAEHADCEDCHAADBADHEDAFHEDDCCDCFEHBHGGHEFHEBHEBHGBCGCADAAHACBDFBGCBECBCCEHEADEGEEAFCDBHGBCGBCDFAGEAEHAHDCBBCG,False +157,3.0,5.0,10.0,12.0,6.0,7.0,9.0,8.0,CDDCFDCHDGGFGDBGDHFHHEGCCHDCADCAGBFHEGEEGCEDEFDBFDHAHGCBFCBD,False +158,27.0,19.0,22.0,22.0,21.0,22.0,30.0,32.0,AEAADDGDGHBHDGHBGHBHHBCHCAHCABEEBDBDHGFHGHHGBBAHAGFGBAGAGGAGHHCFFBHHGDHAACAGCAHDADGAFHCCHGHHCHGCFGEEDEDBECGAFEDFEDBEGBCACHFCDFGDCDCCBGCFGDFGHFAAEDHFBHFGFFEAEEHEDBECFEABGAFEEEAFDCFDAFDBCGHCGHAEHAG,False +159,6.0,10.0,10.0,5.0,6.0,6.0,5.0,10.0,HCEECDECAFABHBBFADFCGACGABHFEHCBBCBBHFHCDCEDCHGGHEGHFBHABD,False +160,18.0,20.0,20.0,17.0,21.0,19.0,20.0,20.0,FEDBECCGDCDBGDBGDGGDCDFCAHCEHAGAABACFCFFCAACHADAACEGEEGBFBHEHHBGHBACGFDFCHFCHEAEBBEDFFGCFGBEBBEHDDHABGEEEEFABHABHGEHGEHGEHBFDFDHGDHGBEGBECCFCAFHFGCCDAFAHDB,False +161,12.0,21.0,28.0,20.0,19.0,21.0,30.0,23.0,BEBCAAFGAFGBFGEEEFCCHCGHFGHGDDCCHBCGACGEHGHCEHCFCBHCBHDAHDHHDCHEABGHFGBGGCGHCGCEGFDGDDEFGEAHBGEADDCFDGBDGDCFECFCGFCHEGAFCDFCDGDFFEHFBHFCCBECHEBHCBFDBFBBGBDAEDGECGBHEBDABGGGAH,False +162,21.0,14.0,18.0,20.0,18.0,17.0,19.0,20.0,GHBEAFEGBGGHDEEDEABEBBEFECFCCABAAEAAEACBAFBHFHHAEDBCDECDAFBAFBAGEHEHGDAAHGAEDCCDHDDHGAHAFCCECAFCHHCHEGBCDCCBFFEFFGBFDDDDDGGCGDAFDGCGFHHDHHDHGFHGAGG,False +163,7.0,8.0,10.0,9.0,10.0,6.0,9.0,12.0,FBCCDDCAHADHEHHAGCGGHECHECHGBFABFADFGDHBDHDDCDHCEBFHGECEEAEFHECEBGBGGBA,False +164,2.0,1.0,4.0,3.0,2.0,6.0,3.0,7.0,CHCFEGFCGHHEABGAHDFHDFHCFHFD,True +165,27.0,21.0,24.0,26.0,31.0,11.0,22.0,21.0,CAADGACHHEAHDFHCAHCFBCFBEBHGCEFCHCGECDEABEACDDGHDAFCCDCADCAGBDGBEGBCDEHAHHAEFBEGDEFCEABBDBGAHAACAAEACBFBBFGEEHEBDEGDEGDCCDCABHEEEGCDGCDGHEGEEGEHDEGDHDAEFEGBDGADHFDGCDGBAAAAHHEEHDEBABB,False +166,7.0,16.0,7.0,13.0,4.0,10.0,9.0,15.0,BDDEDDGCAHEFHCFHCBHAGFDBDDBDDGFFBAHAHHFGBBDFBDHACHBCEBFEHHGHHBADBCFBHDGABGHBGFBGC,False +167,15.0,15.0,9.0,10.0,9.0,15.0,18.0,14.0,GGABCADCGHHGEHBDHCDHDEGGGFGGAGAABECBCFBEABEBEGAACBBFEAFBHFBHFBGFCAFGHFGHDGCBCEHFFGBFEDFBDAHHAHHGFDDAGDAFA,False +168,21.0,14.0,14.0,15.0,25.0,21.0,7.0,17.0,FDABDAHCHHFDACBGCBGCHFAACGEEBCBFABAEEAEEAFEADDHFAHFEHAHHCEHEFDGFEHFEGFDFHCCAEAAEADBHCFHEBBCFACFDEADFAECAEBBEDBEGFDAFEFDHFDHFEEBCEBGEHD,False +169,11.0,25.0,11.0,15.0,12.0,14.0,16.0,19.0,CDFBBCHGCEBDBACBDCGHFHHFHDFHBEGBEDBFDAFCAHBACFAGGAGEAGBAGBHBBDEBHGHHGHFEABDHFCBECBFDFEGHDFHBFHAEHECHBHBGDBGBCEBABDEGDGGDFDB,False +170,11.0,10.0,15.0,10.0,14.0,10.0,14.0,13.0,EEGCEHAGADCDEADGBDBHDFGDHCDFCDHBAEAHEHCGFCGFCEFDHGHHGHFGCAACHACHAEGEBDCFGCFBBFBBEEBGACGFHEECEBCGA,False +171,15.0,14.0,17.0,21.0,14.0,11.0,20.0,12.0,CBGBFHBCEACEAGAACBDBBDCDDCDDAGGAFGFGDHADEDDEFFAFFCBFCBFCFAHDDBGGGEADHHBHBBDEEGEEGCAGCDCCGCEBHHCGGCDBCHHEAHGAEGHEFADGDGEDGDDA,False +172,6.0,4.0,6.0,6.0,3.0,10.0,5.0,4.0,GBFGHFGDEDFCDAGDHCDACBECDECAHAFFAFBCBHAFFGFF,False +173,2.0,0.0,4.0,3.0,0.0,0.0,1.0,0.0,DDGDCCACCA,True +174,3.0,6.0,8.0,12.0,9.0,8.0,4.0,7.0,FGBDDHHDCFABFABCBCCHDEHEFAEFEBFEDDHDBCDECFHCFGEGGEDDCDDHE,False +175,4.0,4.0,3.0,0.0,0.0,0.0,2.0,1.0,GACGABHBBAABCC,True +176,4.0,2.0,4.0,1.0,2.0,1.0,1.0,1.0,HCDACAAEABCFBCEG,True +177,22.0,20.0,10.0,18.0,13.0,13.0,19.0,20.0,CBHCGHGEHEEADBHGAEGFEGFBAEBCFAFEGHCBABFADFDDCHBCHDHAGGADBAHFEEFHBBHBGDDDHDGHGFHAFAAEGBBDAADHGBEGBAGBADBAHCHHADHDGGDFGDFDCABCABCABEFHEGA,False +178,22.0,19.0,25.0,28.0,26.0,27.0,22.0,13.0,CCCCCCCDCAGHEHCGDGHCADEADBADHFDGGGBDACFHCFHDGBDGDAGDCDDBBCEBFBAABDCDDEDFEFEECDEBAFBDDBFEHEEAEFGEFGEAGBFFBFFBCFCFDGHEFCAFCAHEEGEEBEAHDGEFBFHDFEDCDHCDACGGBGCAGDAFAAFEAFHDFEGECBBGFAEFAG,False +179,3.0,7.0,11.0,8.0,19.0,13.0,15.0,4.0,BEEBAEFHEBGCBCEBFHFDECDCGHGFEGEEBECGFCGFDGDDGFAFFAEGCEFCEFDECEEGDEGCGGFGEBDHCEGF,True +180,23.0,18.0,16.0,19.0,17.0,9.0,16.0,16.0,DACDHCDECEHCBACDAFDAFABCEDHDGHBCFFABCDDFDDHCAHBAEDABHABDGDFCBECAEAAHGEFABFGBGBHABHCEAEGAEGEHGFHEAAEAHGCEGCHGAEGCBGCDGDEGHHADBAGBEDBDBB,False +181,7.0,4.0,3.0,4.0,1.0,4.0,0.0,2.0,CDDAFABHAECADFHCFABFABDAB,True +182,7.0,17.0,14.0,12.0,11.0,8.0,17.0,16.0,ECEECHEGDCFDCFDCEDBBGBGECGBHGFFGCBHEBHABAGBHFBHDGHBECBEHHGCGCCGCFGHABADDDHGDHEBHBCGGFFACHAEADBHDGHBGDB,False +183,18.0,19.0,14.0,22.0,20.0,25.0,20.0,18.0,FBAHCEHGHHGAEDEDDHDHGFACFDBFGCCBHGHHGBHGECBHFDEFBEBHECHFGDFHDEHAGGEGDBGAADFADAADGADGHFFEGCABDGFDBDECDFAFAEFCEFCADGFDFFBFFBHFCECGEBGEBHEADBBDFBCFDCFAAEGBEABE,False +184,9.0,17.0,14.0,14.0,12.0,19.0,15.0,10.0,DBDDHCBBBBGGFEBFEAFGCFDCADCDFEFGHFDHBDCECCFDCAEBEDHFDCBDGBACACGECFEHDBACBFFBFFGGDEGHHGCHFBHFBEFAEAABGFBGEGGFGH,False +185,5.0,15.0,12.0,28.0,11.0,16.0,11.0,13.0,FBEBDDHEDCEGFGGBGEBDBBHCDGDDHBDHECBDFBDEGHEFHEFEDCDHGDADDABHABDCBDBFDHGDFDCGHCGDCHHGDADDEDDAFDFFHFFECDCBBFFCFFC,False +186,3.0,2.0,0.0,4.0,2.0,3.0,6.0,2.0,EGADGADADBGHFGBDGHFGEF,True +187,7.0,12.0,9.0,16.0,4.0,16.0,12.0,10.0,BDFDFFBBBEBBFCHHCHHFFEGDADDFDFHAFDAFBBGDBGDBDDGCDFFDGDGCBCADGEHGDHCCHACABHAHGCFGFFGEFG,False +188,9.0,14.0,12.0,11.0,9.0,6.0,5.0,4.0,DFBEFDCDCBAFBADEFDEGCEBCGFCECHDBADBADBEEBABGHBACBACBECGACBBCADDHFGHECD,False +189,15.0,22.0,16.0,23.0,11.0,18.0,13.0,25.0,CHGBHDEHBEHDGCDFHFHHCHHGHEDDBGHACHECHBHGDHDCHDEAGEABFAEFACBBDDBDBADACDABFAHDABACBHHDHCAHFFBBDBGAFGFFBBABCGEEFEDCCDCBDBFDBFEFGGFHHFHDCADBDGFCGFH,False +190,23.0,11.0,18.0,25.0,19.0,12.0,19.0,38.0,DEHHAGHADHGCHACEDCAGEGFDADHADHDDGEEEEHFHGCAGEDDFHHEHHDHDGBDADHECEEGAFHDBHGBHGBDAHAEHABHBBFDDCDAHHGHHEHFGHCHDDECBFCADCGDCGHCGHGAHGABFHFHHFHHEHHBBAEDAEDFCCECAAGACCACAF,False +191,5.0,6.0,1.0,7.0,12.0,13.0,5.0,13.0,HEEFEHAEHFFHFGDFEDGEGAFGFHGEHDBHAFHFFEAHEBEBDFADBHHHEHBECFDBFD,True +192,14.0,9.0,19.0,16.0,17.0,13.0,14.0,12.0,FBCCBDDFFDHDDHGEFGEFGFHGFBDFCEEHACCAEEDBFDEDCHFCBAEFCGGAHFADGAHEHHAHBACBCEDEEDCCDCGACGCCGCEGDECAECAFGABGBHGDDEAEHA,False +193,13.0,11.0,10.0,13.0,18.0,18.0,16.0,24.0,BFHBGDBGHEFHEGEEGAAFHDFECFEAHEAHDFHCHHEHFAGEGCCHHEDHEDCCDAGGAGGBDCBDAFHFFAFDAFHGCHGCFGHGHHCHDBHBFFADFEDEBHGGFBADHAEEEHEEBFB,False +194,4.0,3.0,4.0,0.0,0.0,3.0,1.0,3.0,HCHBAHBAGFABCAFCFC,True +195,5.0,5.0,1.0,2.0,4.0,4.0,7.0,2.0,EFBGHBGABGADGABHAGDBECGAFGFFEE,True +196,16.0,12.0,12.0,7.0,4.0,7.0,9.0,12.0,ACGACAHFFCEACGGDEADCAGCFHBFBEFDHDBHAAAAGHBBHCBHGBAGBACBDCBHCBACDECHHAGHFHBGADFA,False +197,11.0,6.0,8.0,7.0,7.0,10.0,12.0,14.0,GHFFHACEECGEGGDBGBBFAGFGCHGHDGAEGCCBHCBHAFHAHDAFGAFADCADHAHHBCDFGEAHEHHFDEF,False +198,21.0,16.0,17.0,15.0,22.0,24.0,21.0,20.0,AEFABCDCDABGHHEHDFBBFCAGGAEFCGGCGABGACGHHGDGBDBBCFACBDFHHEHFCHFCECHFCHGEHGBFFECFBHFGHFEDFDCFCEAEEADDGDEGFEGFABFHBFAEHEDDADAAGAACEACBHEBFEDFAAAGGEGGBHEEHFEHF,False +199,3.0,4.0,1.0,2.0,7.0,5.0,9.0,5.0,HFFFEGEEGAHGBHGAHDADCBGGEEGEGBEGBFFH,True +200,27.0,17.0,26.0,18.0,16.0,17.0,15.0,13.0,BDEBEEBCBBCDFCHCCABDEGCGACGACACFGDDGAACBACEEDBDDCCCHCDFAHBGEBCHGGFCGHHHABHBGAEHCBGCDAEDFEFBEAHEAFFGDFHDHHDFDBFEBAAGAAGAGFCBCCEACEACECFAFAAFAADCFDAFDA,False +201,14.0,18.0,22.0,18.0,23.0,25.0,18.0,25.0,EHGEHCBHCHHAEHDEHDEAEBCEBCEGFAHFAHCEHBFHBHHBHEBCFADGHFGCFBAFBDHCHCEHADGBDFBFFBHBGGEFFFDFEBCDFDHCDHBECDEHECBECEFAGFCGCAGEHGEDEFHFCGCCDACAAFDAHDFFDBGDGAFGCBCDFEGFGGE,False +202,6.0,4.0,6.0,6.0,4.0,7.0,2.0,1.0,BADGAEAACFACGEFBACCEFCEFBDHDDFDBFDCF,True +203,4.0,8.0,7.0,5.0,6.0,6.0,6.0,7.0,EHAECAEHBEHBFHBCDBAEFEGGCFGDGHHACBBCGBDHCDFCDFGBF,False +204,6.0,15.0,10.0,9.0,18.0,10.0,16.0,17.0,EHHEDFBDFGDGEDGHFEEDDBGFADFCBHCBHFEEFAECGHHGBCEDCEHFACGHEGHEGCBGHBCHBEFFEHADBAGBGHCHEEBEAGEBGBHGBHCBG,False +205,6.0,8.0,4.0,6.0,11.0,10.0,4.0,7.0,BDFBFFCHFBADBGFCGCCEEAAHFAHFGFEEFBEAHEBDEBDFHDHEGEEBEHDA,False +206,7.0,11.0,7.0,14.0,12.0,11.0,11.0,15.0,DFFHFBABAHBEHBEHDHGCHFDFAGCGHEBADHGDHCEHCEFCEFGFFGHGCDAADGBBGDBGEBFEDHABHDBCDHHEFDEGDEDE,False +207,14.0,19.0,19.0,16.0,15.0,16.0,25.0,15.0,BHBBDBDDGDAHEGEGGECDCCBCDAEBGEDGHDCHFEHACACCEDCGFGFEGDGGAGGAGGHFBEGCEGCEBCAFGHEBHDAEGAFHHCADFBBFBFFDHFCHFBBGBBCBACGFDAFHBCGFCGEDGADEAHFCHBG,False +208,14.0,24.0,23.0,25.0,20.0,23.0,13.0,19.0,CGFHBECCCACGAFFHDFHDAHCCFBDFBCCBGFDAHDABGABGHBFHCDGDDHBHEBCEDEFFEFFEFFCDDGGECDEFDADDHEACEAHEAEEBFBFGBDBBFCBDCFDGFHBBDBCGCDAHDCCDHCEEFEGGECBBABDCBDEFEHHEHHBHBADFA,False +209,5.0,7.0,7.0,12.0,11.0,5.0,6.0,4.0,BEEGAGCAHCFDCAHCEFCAFGGDDEDCBDBEFBEDDADDHDDBBDBEEEGCEGHEF,False +210,21.0,21.0,29.0,26.0,25.0,22.0,25.0,25.0,HGGGCBGCBGFDHCEGCBADBADBDFHCBHDBEBBEHBEFBCABCACCFCEFHAFHGFGDDGDDHHDEDDHCBEDDEDCBGGFAADADGACHAFDBEBEECDECEFGGHECHEFHEBHEDGCDCABCEFGEGHFGHEECDBHDFDFGCAEAGEAHCHFAHDGHACFACGHHGDHGCAAEFAFBCBECGFCFFCA,False +211,25.0,20.0,15.0,18.0,16.0,31.0,22.0,17.0,GDHFDBEDFEFGAHDFFDBECFDAFDBFGBDAEGAEGFDCFDCEACBAFHGHHFBFFBHHEAFBAFDCFBGAGGACBACFCEACEACHHGDHGCGFHGHAGABGBGDFHHFCACEBHEDDAFDAGCADBEGBFGBFEFFEAFGCFBHFEHGABAABAEGAFDFB,False +212,11.0,12.0,15.0,21.0,14.0,13.0,13.0,22.0,FDHBAHAHFDBFDFCHHEFHDFAGBADBADCHDFFDABDHCDHCGAGFHDDHEEHBHHEHBCBGDGCDCDECDEGEBHEHHGHDFBCFDAGCAGCACCEFCDBGEBGEDEFGHCGHEDHEA,False +213,26.0,25.0,22.0,24.0,22.0,21.0,23.0,28.0,DGGABBFFGEFGHFBHBHFAGAHGECGEBAACCADCHDBGDHCDFEDCCCFBFAHDEGGBGECFEABGHDEADGBGGFDEFAABAAHAAHCAHGFHBFABFAEHHCHHCFBEEDEEFEGDEHDHHDHCBEABAGGAFGDFDCBCHBCHBHEBAAGCADCHFCFDBBDBCDECHACHDBEDHEFGADGHDBE,False +214,17.0,18.0,21.0,25.0,26.0,17.0,17.0,17.0,FEFAEAHHABBGBGGCDGDEEDAEBGFHHCADDHDDEDDEAFECGGAGGEBGBACEEDEEDHDDHGBHEBCBHADFEDEGGCDDBDCFCHFEFAHFHDBHDBHAGCFEFFEBEEBEEDGEACFABBCBFDBFHFECGHCGACDCCDCCECFHAACADC,False +215,3.0,8.0,12.0,3.0,11.0,1.0,8.0,8.0,ECHEGGEHEEBCEHGGHBAADGCHBCBBCHBCHBCEDFEGHEDCGCCECEBCGA,True +216,3.0,7.0,2.0,4.0,7.0,5.0,4.0,9.0,EEBACHABHEFDEHHEBHAFHFCHEDGEBBDFBHGBHGFDG,True +217,24.0,19.0,23.0,32.0,19.0,19.0,18.0,19.0,BDFHFFHEAGCGGEHGAHGADAEDAEGACABCBFDEDDEHDGDDEDDGCDGAFBBEBHFBDEADCDDCHBCEAHDBHCBHCACBGCGFCGFCGDHFABCACCABHEEHDGBFFDFFBHADDDCAAHDAEFEEFBDFADGADHADFGDCGCCBECADAHHCFDCGBEFEEDHBA,False +218,15.0,9.0,15.0,14.0,9.0,15.0,10.0,14.0,EDDHBDCEDAHHCDHCDEFECFDDBDEGDCAFCAGCHCFHBFBDFCABCEGEEHHGFHAFCABHABDAFAHBHHGFCGFHGBAAFDAFAAFEDFAGGCCGC,False +219,24.0,26.0,20.0,28.0,17.0,21.0,17.0,23.0,FBGGAGHAGHGGBGGFFDAFDHDCFBFFHFDHDDHFDHFHCFGDHBEFCEACHFEHCBADHDBADCEBCDDAGDAFDAEDEHCAFDAFDFBBAGBGHBCHAFECHDCEBBEABGFHEBHDGCEFCBACBACBCCBHBFGDADAAHAHBGDBDEBGECEDHDAEBAEBAEHADCDBC,False +220,10.0,6.0,12.0,8.0,3.0,8.0,5.0,9.0,DEDDFFBCFCCAGBFHBACAACAHFAHBEGGAGCDCCDFCDFCAHCACDHEHHABGDBHFH,False +221,18.0,20.0,25.0,20.0,16.0,11.0,30.0,25.0,BFFBEGBGFBGHBEFEDHBDCAAHAGHFGDADCBDBBDECAEBAHGHGABBHHBGCGECEECADDDGHDGBBGBCGHHGCHCCHCFHGGHAAHAHGAHGEHGDHBEGFHFAHGADFEGBDHFDGCDGCFGAGCCGACGHEGDCCCABCECGEHDEDDCCECADCB,False +222,19.0,19.0,21.0,28.0,17.0,28.0,23.0,16.0,FFFFGGBAGBFCDFCBFDGDDEDDFDEFCHDCHACAAFFDGFHCFBCDGEGEECCCBBAHHDEHDECFGGGDDGDDGDDCBACBABHCDCFDCEBEGBCHEFHGBHABAGFGFADHAGFAEFHEBBFBEFCGFHAFGADGAFHBCABDEDDCHFEHFEGAEDCGDFADBAG,False +223,23.0,19.0,28.0,13.0,18.0,28.0,23.0,33.0,GHBCHBGHEHEAHDHGDCFBHGCHGCFGCBGBGCDHEFAGHEGAABBHECFCFGDEHCEHAFCADAGDFGDHACBACHACHCHFBEFCFGCHHHHCHBCBEDBFHBEHBAGEACHACFAGGHGDHFFAFEADEAHFAHCCHEFGEFBFCBHDFGFFGAFDACDECECBEBFHBAGCHGCAFFAFF,False +224,3.0,2.0,2.0,3.0,1.0,3.0,0.0,0.0,DAADFBDFBCACFE,True +225,18.0,28.0,26.0,15.0,16.0,22.0,28.0,24.0,CCBGHAGAEGAFGBHGCHGBBBHBBHCBDDBFDFGECEECAGHEBBGBAGBFGCHCCDGCDHEAGCBBFBBFCBGGAGBDGHGGHGHHFHDCEDAFGHBGABHBEAACGCCHCCHBHHFFFFGCFHCFEDACFGEFCAAGDCDDHDBAABFACDABEGCEGFEHFEFCEDBFHBEHF,False +226,0.0,1.0,4.0,5.0,1.0,5.0,5.0,2.0,DBGCFGDHGFCGDHGEFCFDCFD,True +227,9.0,11.0,5.0,9.0,13.0,8.0,7.0,11.0,DGHBGEBGHACBAFHAFHFHDDHCGEAGEDEEBEAGFDFBDFBHFHCDHCEEAFBABBEEBEBDHADHGEEAC,False +228,3.0,5.0,4.0,5.0,8.0,4.0,5.0,8.0,DCEDEHGEHGFCEFGBDHBDCBDHFFHEAHEACGBGHAEHEB,False +229,5.0,2.0,1.0,1.0,0.0,2.0,0.0,0.0,ABABFACFADA,True +230,17.0,15.0,18.0,10.0,25.0,10.0,12.0,11.0,ECCHCABEAEAABAEBGEBCEBGAAGBBDFHDEHDEHCHHCHCEHEEHCGBAFCDEEFGEGGCFDEFBBADBEEFHEAHECGFCDAAAFBBCCCACBGGBAEDDEGDECCEFAEFAEG,False +231,31.0,18.0,29.0,27.0,23.0,14.0,25.0,29.0,DGBAGHGHDGCGACBADBDDEADFCHGDBFEBHEBHEFHFCDFCDACFGHDDDDDCGCEAEEADCBDBGGHCAACAEDACHEHHAHDDFDEHCEHCECEHHEAFEABCGEGABHEDHEFAGCGGCGACDAGDACAAHACBBCDACAACHCDHGAHGFBDAACEACECFEHGGHBGHBCFFGDBGHBEFEHHAHBAG,False +232,9.0,27.0,30.0,27.0,17.0,16.0,18.0,20.0,HDBHDCCCHHCHECBBCGCEDCHCADGDBBEBGEGGFDFDDGDBBFHCEEDFFFHFHHDGCEBCABABDEHDHCDHFDHFDHBDHGGEECBEHBDFDDBCDCCBCCGCAHDBBBBFBEHBEGBEDDGAAHCBECBCCBCFFEDFEDCCGBAGACGDCAFCGFGG,False +233,13.0,14.0,9.0,12.0,10.0,11.0,7.0,12.0,CACBADGHDGHDFHDFHDEEDGEBBEDHACHABBFCFAEHACFDCEAHEABFFBFEAAEBCHDGBDBBGCBFEAFGDCDHHABHABGF,False +234,27.0,12.0,19.0,20.0,14.0,11.0,16.0,19.0,DCEACEBHDGHAGFBGABGABGABCHFEADDADAHDHDGBFAECCBCHHFADFEFAHDAEDCHCHADBFDCGDCHECGAAAAGBAEEHGCCGEAGEFCDFDGGCGACHCEHCEHDEHBCADAADADDFHGAHBAHBAF,False +235,10.0,14.0,16.0,10.0,22.0,13.0,14.0,12.0,BCEFFEFBBGBBGEDGEABFACCDCCDHEGHCBDGHEEEFAGBHGBEEHEEHDEFDEFCECDECHGGAGFFEDGHBECBHCGFEAAEAHGBHGBHEBAFACCEDCACFDCF,False +236,7.0,11.0,9.0,8.0,13.0,11.0,4.0,12.0,AEBEHFHFFGFHBFHFAHBHHBHFEFABBEBAEFCEACHHDGDEGABCCBCEBDEDCEACFHCFDCHDEEDBGDE,False +237,23.0,30.0,14.0,18.0,17.0,26.0,17.0,30.0,DGDDFCEFCGCBBHACAFCEEEEAADADEHFABBADHADHFDBFHHFHDFDAFEADBADCAFAFBEBBEBBCBBCFBEFBGFBHBBFFHFAHABHEFHBFHEGHAAHBAGBGFHAFABEGEGGDCGBHBCHGHFGHGHHCDEFFHCBHBBHGEHGDHFDHCDBDAHGHBEAACFG,False +238,19.0,27.0,27.0,14.0,19.0,23.0,28.0,21.0,CCCACCFBHFGEBABBGFFGBCHBFAAFBAHCAHCBGABGADDABDAFDBCGECFEHBCHGHHGHEGDEBFBBCGBGHBGFBCCBDGDCHACHADFADEHDEHEGADGAFBFGBEGHFHEADFCCGCCGFCEFGHFEFBCDBGHHECGBCFAEBBCDGAGCAGFFEHGEGFEGBECHE,False +239,12.0,6.0,10.0,11.0,16.0,6.0,12.0,10.0,DBDGGDGCDECGHCHEAHGDEFEEFEBBHABCCDACGFEGHECAFAEDAHAGCBGAHGAGFABFDEEDGEHEECEDCEAHDAH,False +240,12.0,11.0,10.0,12.0,15.0,7.0,12.0,8.0,EHCEBGEBCADCDFCEGBEBCEBHDGAAGDGHDCFDEEGBEFEEFGEHGHBEABEAFCFHCGHCBADAADADGAEBBDDHDFGACGA,False +241,24.0,20.0,23.0,18.0,18.0,16.0,33.0,12.0,DCADHACHFFHADCCDEEDCEDCFAAFGBCGACGAGGACHBBDBCCBEFBGCDGHFECABCACGAEFAECBFFFHGCAECAGHEHBFHBAGEFGECGHBABCADDGGDGGDGGCGCFFHGGEAGEGEEBBEGAGFFGDGGBGDBGDCGHAAABGEBEBDDBDAA,False +242,2.0,5.0,2.0,2.0,7.0,2.0,2.0,4.0,EHCHBDECDEGFEAHHABBEBFEBGE,True +243,5.0,8.0,9.0,5.0,11.0,13.0,13.0,9.0,ECEEGBGFFHFBEFHFDBGDBGFHFFHGHCGHEACEABBFEEEEGCGGCFBCDCCEHCDHGAFGABGHFGAFD,False +244,8.0,13.0,8.0,11.0,10.0,14.0,17.0,10.0,EGDHGCEDHEAHFBCGBAABGEDAEDAEGGDDFDCFGCEGCGFADFCFEBBCBFDGFAGFEDFBGFGHBBHEDHGGHBAFBFHCFHGBHGB,False +245,10.0,16.0,19.0,10.0,13.0,11.0,21.0,15.0,BEEBGHAGHCCFEDFGFHBHHDFDDHCFAGFAHABFABGAFAACBECGGGHGCAGCHCEFGEHBEHBGFGEFCHDHHDEBCABDGBGGCGGCBGEBGDCCCCDCBDEBGEBECCH,False +246,9.0,13.0,8.0,9.0,4.0,11.0,15.0,3.0,BDDBDDBAGAEGABGEDFCBCCFCDABHCBGDGGEGCEFAGBAFBGGBGGBDFFAFBCGDHGHFFCFAGFAB,False +247,24.0,29.0,19.0,27.0,21.0,19.0,25.0,36.0,AGGDCEDBEDGADBCBEDBHDFHDBEFHEFEEGEGDEABEFHDBHBHHFFAFBGGHCFFEAFDABEAFCHDCABBBCBEEBFBGAGHBGHCABCAFHDGHCHHCDGADHADGFHGFCGDBHBCHBDAEGHHGHHAHCAHDDBGHBGCEAHGADDHDECGEHHEDEGFEDABHABHABCABDABDACHGCBGDHHFHFFGC,False +248,23.0,15.0,19.0,20.0,20.0,17.0,12.0,20.0,AEDAEDAEFADFAHFAHEEHBBCBBDBCAFAAGCCGACEHEADFHDFCDAHGBEFFEFDAFGACGECEHHGADGBCAFCGCHDDDGCFFDBCHECFEHEABEABDCBHFDHECAFDABDAGEBGHGEHDBADBADCHCHHCFHEEH,False +249,5.0,8.0,8.0,6.0,8.0,12.0,5.0,4.0,DDADDFEDFHACECHGGHCDBBFFBEEBGEBCECCGBEAAGAEBFCFFHFFBFFCF,False +250,9.0,9.0,5.0,9.0,9.0,5.0,9.0,6.0,EBGEGDECAEBBGBFDBACGCBBCBBFDADDACDGEDGHDHDAHEFHFGAEGHFGAAEHAE,False +251,3.0,4.0,6.0,7.0,2.0,6.0,5.0,5.0,FCHFEBDGHDHADFGGFGFFEDBCCBCCHGCHDBDDAA,False +252,23.0,16.0,22.0,22.0,17.0,24.0,15.0,22.0,GDGADAHGFBBFBCHBDHBDCCDHEGADCHBBDFHCGGCEFBECHECEACFDBADEACEDFFDFFDFCEFCGFCHFGAFADGAFHAEABFDEDHHBAAAAHGABGDBFEHFHHFCHDCEAEEAEDCFFAFHCHHADHACHAEDABDCCGGCGFCBFGEHBD,False +253,28.0,21.0,24.0,17.0,16.0,23.0,19.0,22.0,HBGAFCHGAFDHGAHGHGDDGADGECAACFACBDGFCBAHBHDBFDEFABFACAEGFHGBDGBFHDFHCGBAGCABEGHEFHECCEAEHADHFDCCDCCEAFBDDBFHHFGHFCHCDHCFFCBAEFAEFEEAAEBFCBAABAAHEABBAFBGCBGCBDFGAGCCDECAHH,False +254,22.0,21.0,35.0,22.0,18.0,16.0,18.0,17.0,CGFCBBCBBCFBDHEGBFDEHCCAECAHAFDEEDAEHAEBCHFHBFHCHBGEACCCCDCABFABCDBDHCGCCGDCDDADDGGEHFEGCCBCBAFDEFDAADFAGGHECHECHECHAHGCFBBBBAGGEDBFDAFDCEDCEDCADCBHEFCAGCAGCBGFDACAACGGH,False +255,16.0,23.0,16.0,16.0,20.0,17.0,25.0,22.0,FBDCDGFHBEHADAEBABHAGDEEDGEAABDDEEFEEDBCGGDHHDHGDABBCBBCDHCDBGDBGCHGHAGFECEEBEHFGDFACHGHHGBHCEHCECABHADHACFBBAEFCEHAGHGEHGFHGFGGFGBFBFCBGCFGEFGEHBBGFCAFGAB,False +256,4.0,5.0,1.0,1.0,3.0,4.0,5.0,7.0,BHFAGFAFHABDAEHHGHHGEGBEGBCBHF,True +257,15.0,16.0,15.0,21.0,14.0,16.0,23.0,29.0,BBAHCCDBGFHGFGFFCFGCGHCGHDGAGHDCHDEABEBGGFDDFHDHHGHBAHDGCAGBGEBHBCHGEFGEHGEBFECHEDGEHBAHBEHDACDHHHBCHBCHAFHDCHAHGAGGDDBDDEACBAEEAHDDFFHGFHFFDAEDACDFG,False +258,25.0,18.0,28.0,20.0,16.0,20.0,26.0,30.0,GBDGBHAEEAHBAHBCHCCHCEBCECDEAAFHHCGGCFFDFBAGBHGFHDAHBACCADCAECAFFAFFGGEGCEACECCFCBEAAGFCFFGGHCDECBGHBHACAAFDGHDCHDCFDHFEHFDGDGHDCHAEADGGEADCHDHBGBDGAGGFFHHFHAGHCHHCDBGHBEHDEHGABBADBCG,False +259,10.0,4.0,2.0,8.0,6.0,7.0,4.0,6.0,BFAHHADDBDEBDAHFACEADEFDEHDGAGFDGFAEFBGFEAACHAH,False +260,17.0,18.0,20.0,22.0,23.0,26.0,23.0,18.0,CGCHEEDEBDHDGEGFEFFCAHGBHBEHBACAAFAFFDBFDCFAEFADFAEGBBHADAGGHFGCCGCGFBDFEEEEADHGDCEDFGDEBDHBGHBFFCAFCECGEDADDBHGBECFEBFEDFDDEGDHCAHCFFGFFGAHCDHADCBECBHHBHCGFGGABGCEGFE,False +261,27.0,24.0,20.0,19.0,30.0,32.0,21.0,26.0,GEHGECEEBEDACCACGBFGFCDBHEFEEFGEFBFACFACFAFFAGDACBAGDEBABFAEDAGHAHBAECAFDFEEBBBFEBDEFCHFHBFHFEHDGHBGHCCFDDAADEAEECGGHGFECFEDFEAFACHACEFBEFHHBHHFEAFHBFBBFBHFCAGHHFHHGHDCHDCHFGAGDDGCAGDEEAGEBEDAGHADBBB,False +262,24.0,26.0,23.0,23.0,21.0,23.0,28.0,24.0,CFDHHBBHEEHEHHEFHBDAADAFDBCDHDDFGAFCACEADGBEGCGCHEAHGADGABGADCFFBFEDDAFDCFHBBCFBGDGCHECBEBBCABDAECAHAHHAHEBHDHHFAHGEBEHFAAGBAGBGGCAFAFBAFBDCDCCDGGDGBHBBCBGFGEEGECGEHECDFCBFGBDGCACEFGEGGFHGFDGF,False +263,0.0,1.0,9.0,1.0,3.0,4.0,6.0,1.0,CHCCEFCGGBGFDGEGCECCFCFGC,True +264,6.0,5.0,5.0,2.0,0.0,4.0,6.0,0.0,CCAGBBGDBGDBACACGAGGFFFAFBAC,True +265,4.0,10.0,10.0,7.0,1.0,8.0,4.0,4.0,BEFBDFGDFABCABCHFCDGBHBCAFCAFDBDBGGBDFCCBCFHCDHC,True +266,22.0,29.0,31.0,16.0,20.0,28.0,16.0,14.0,EHAHCBHCBECFGBBCHEEBAFBHHAFGBFDBFCBFCBFCBFCGFGECBBGFCEFBEFDEDDGFCFCAGCAFCEGAAGAACDCFGAFGAFHBGABDAGAHCAECABBBCFBCDEAAEBFBBFCCFCCFABFDDFBEHBFGEDBEDEHAECBGCFHCDECACCDEFDADEHCGDBHH,False +267,19.0,18.0,7.0,10.0,13.0,13.0,13.0,11.0,HAHCGEBDCBCBBEGHFGBCGAAGBGGFDGCAEADBAHBFEFFEAGEHCHHBAHAADEFGEAGFFEFAEFCBAABAABEAFGAEGDEDBBABBFBHHDDHDBFD,False +268,17.0,10.0,10.0,7.0,8.0,5.0,14.0,9.0,DCADHDGHAGBAEHECHCGADHCGAEGBEGAEGAEGACAHGHDCBGHBGFBCAAAACBBEEBGBCFCAFDAFDHFGABGA,False +269,1.0,3.0,0.0,1.0,3.0,4.0,3.0,1.0,GHGGEBEFBFABFEDF,True +270,23.0,19.0,18.0,18.0,15.0,13.0,11.0,15.0,AHDAFCAECAFBHBCEFDEFCEFEDAADBADCDDFDAFGEHGEAGHADBBEACFGBDHADGCCABHHGHFBEDGHFEACEFCBAGAAEABEABGABHBEABGABFCBACGDDHFCHBCHBHHCEDCDDCDBC,False +271,7.0,9.0,4.0,6.0,4.0,10.0,14.0,6.0,GDDGADGAHAAHABDGFFFECFBHBEGEGHEGDCABGGFFHFFHFBGABGDBGCBGFGCB,False +272,9.0,5.0,1.0,2.0,6.0,2.0,1.0,1.0,EDAEAFECFGHAABAEDEBBEBAABAA,True +273,6.0,7.0,5.0,6.0,3.0,4.0,5.0,6.0,DBGDAGHAGECGFBHFBGDDFEDFHCBBEHHCAHBACBACAD,False +274,13.0,30.0,20.0,14.0,22.0,14.0,15.0,16.0,HBGBBDCBAHEFEBDBCABCGFGEHGECGCDECDBFDECGHBFHACDCBBHEHGGHFGBBBBHBBHBBGBEABHDBGDEGEFDECCFHEBHEHGEFCFBCFCDABAAHEECEECEDCEDGEBFEBAABGABCBCAAFDAFDHFC,False +275,5.0,8.0,10.0,12.0,2.0,10.0,10.0,5.0,HGDDCDFCDBGFCGDBGEAFACFDBDDBHDBCDCCFGCHGDFGCFDABHGBAGCGFABFEHF,True +276,5.0,1.0,0.0,3.0,1.0,2.0,0.0,3.0,BDDHFAHAAHAFEAD,True +277,24.0,23.0,18.0,24.0,16.0,33.0,19.0,28.0,ADCABCHCAHCAHEADEAHBGBCGFGFFGAFBDFGFBGDEGDGHHGHHACDDGFFAFFBFFEFADHDDADDFFAFGBFBBFHFCHBDADEAHECEDFDGFDFFDCBBHDAHBBHCEGEBHHBFFCCHHHHCHBBHDHAGCAGEDEHDGHDAFAFBBFABFAEAAGABGFEHCCBCHECFEDFGFE,False +278,12.0,29.0,23.0,26.0,19.0,18.0,23.0,13.0,BEBBEHBCAFAHEDDCDBBDBBDAFFAFCADCGGBGGCGHCFECEBDECGEHGEADBFDHFDGCDGCBCCHDBEABDCBDEBEEBDCGECBDHBEHEAGAFGHFHEFBBDBGEBFHGGHFGFDGCDGDDCFFFDFECCGCGGFBDBAACHEDBDDBGCAGBBC,False +279,16.0,11.0,17.0,16.0,19.0,22.0,19.0,14.0,GFAAFDCCEGCHGBEGDABFBDFEFEEBEBGFCGHHHFHAFDADEAHACBFCDFHFGCDACDFCGFEDFEGADGAFCEHCAHBBHEGCDDHDCAFCAFGEEGEEFBEFEHAHFDEFDBGDBGAFCAGCGGCGHE,False +280,10.0,14.0,13.0,11.0,22.0,14.0,17.0,12.0,EHCECEHBFGCGGCAHCDGCGGEDBBBFHCFBFBBFGHGHFABEAEGACGACBFDBCEECDEBFEBDGHDEBEGGECGEHGEDEEHFEHFEGFAADGADEHDAFDHFEEFCBA,False +281,32.0,31.0,18.0,18.0,36.0,28.0,25.0,12.0,GAHFABEGCGAEFADGADFABCADAEBAEFEHFGBGCBHDAHAABBBECFEAEEFEEFEDAEBAECADCDDBBBCBBEDBFAAFHEEGFCGEEGEFGEFAFDABCABDAFGFBGFEGBEACGGHFGAFHBBDEEEGGBHGFFAFFGEFGEBGDCHCHGBBGABEABEFEDADCEEFDCDHCDBGABAACAHCEFCEFBEB,False +282,19.0,24.0,17.0,28.0,20.0,14.0,18.0,11.0,CEGDBCDFGFGCADCEEGFABEDBDBBDEFDEADBGBEGBACDDFDHFBHGGCGAEGHEGHECDDGDFGEFABAEEHDFBDFBEEBHCDCCEHHDCGDBHDFDDADDEEDBBBBABHAHDABAAGADBCFBCBECDAGECGACGACFABFA,False +283,26.0,21.0,30.0,21.0,22.0,23.0,22.0,14.0,ABEAFHABHEFEEFBHDAHFBHFBAFBCBGGHGDHFDHFBEBBACCAECAECACGBCFFEFCEGGACBCDFAAHABGDEGDEGDACFEGDEGAFAACCBEABGAFDCFDFFGACHCEGCFGABCHGAHCDHCDCCDCGABDFBDEDCGFFBFEACCDCHDGGCGEEAEBAGDCDDCEEB,False +284,14.0,18.0,15.0,12.0,15.0,14.0,12.0,12.0,DHBFHFFADGAHCABFABEEFDEAGEAGDDBACBCCBGCBEEBEAHEHCFFCEFCBCGDCGDEGHGGABADBEEBEHCHHDBEGGFFEFDADHAHBBDFBCCBGABCFHCFA,False +285,16.0,15.0,17.0,12.0,11.0,20.0,18.0,11.0,HGHCBHCECFEHFEGDAFFGFEGFEAFGFBGABDBBGBACBGFBECAAFDAHHFGGAGGAEGCBDBBDHEFGGDGEHAHADEADEFCCFCFADDBCCBCABHAFFCFGCFDCFACDBCGH,False +286,11.0,13.0,7.0,7.0,10.0,17.0,12.0,13.0,FDGFDGFHABDDHFAHBHFFGCFHBGAGFFGFHHAGHEGHCGBCECDECDBHBEHBEHCAFGABAFBGFBEFGEABFBFDEFAEAHEABC,False +287,8.0,6.0,3.0,14.0,2.0,6.0,4.0,6.0,BGDFDCCDGAFBADBDHHDHCDHAAFAADBADBFDEFABDGHEGDDFHD,True +288,13.0,9.0,15.0,13.0,19.0,11.0,16.0,13.0,GGEDADGABGCBHAGACCFCHECDDCBAFEEHEBBEABEACFACEDHEAFEGFGDAEAAECDEFEHHEHBFFDCFDCDAGDHEBHCGHGGHCEFCGFEGEDGDCGHBGH,False +289,21.0,24.0,27.0,24.0,13.0,22.0,21.0,28.0,EBFBBCGBDHCAHFAHBBHBDHBDHADECDCAHCGHGFHADHDCHFBBAHBDHECABFBFFCDFGDFECBECBCHEAHFHHEHGGFAGBDCEHCFHCGGBEGFHBFGAFCADDFDDBDFCAFCHFDDACGACGDCGAGGHDEDECDAGHBFABABBEFBCCDEAHGAHGCCGCFAHDGHC,False +290,11.0,5.0,20.0,12.0,8.0,15.0,4.0,7.0,CBCCHDDHADEADEFDAACCCFFDFCAFCADCGDFEDCECCECFFHFFAGFCEDEBFFHCHGCDBHGCFDAFBAEHACCACB,True +291,20.0,16.0,14.0,23.0,25.0,13.0,17.0,18.0,GBEGBEGFEGFBFDBFDBADHAFBDFGDEGDGGECCECAEAADAACHHHHBHEGDADDBHAAAEHEBDEBGEAEHDGHAAHFABCEGDFGFCECDGDABDHBDECCABFBEEDEGFEHFEHGAHBDCDAEHAECDCFDCEDHGHEC,False +292,22.0,21.0,19.0,22.0,30.0,26.0,23.0,31.0,AHGAHGABADGFGGEEAEFDCABCFBCGBCBHCBCFEDFEDHADEFDFBHCBHAHEAHEHHEHEBGEAGEDCEHGACGDCFCEFDEBDEBDFHACEEHBDDGGEBCEBCGHFGEABFAEEBHABGAHGAHDHHDHEABEGBFAEGHEHCADFFDFGAFCDDGFHFFGFFDEBCHFEGFCDFHHCHFBEGHHADH,False +293,16.0,24.0,24.0,18.0,24.0,17.0,14.0,18.0,BDDACEACHABHABHECHGHEGEEFCHFAFAGFBBBGBEECEEHEFDBDDBDDGCGBCEHCEDCBFABFBBCCECCGBEBAABHECEGCEDDECFECFHCFHCGBCFFDDFADFAHHCGBBBCAFEBHGDGADGAHCBEAAFGDBHHEDCEDFEH,False +294,32.0,23.0,12.0,12.0,9.0,21.0,14.0,23.0,BCGBDHDCGGGDAFDFFBCABCABCFGGFAAFBHEBHGBGGDAFAACABHBFFDAFAHHBHHDHGDEADBHGBHBBHBBFACCBECAAAHABHAEAEDFGCCEAFFHEBHFHHEHDABAAGAGHADAAHAACEAHAAFFBFFBFFH,True +295,25.0,28.0,34.0,29.0,21.0,15.0,21.0,21.0,GBBDDFEAEADECDAGBCFBADECDBBDCCGCAGCDBCBBCBDCBGCEHCGACACFBHFDDBCHFCGAGGECFFABDEGDEFDHFHHBBHDAEDBEDCDDCDDCDAADFACEDHHGACGBBGAGAEGFGGHCACCDHGEHGEHGHCEACBHFEAAEACEACHHCHBCBECHHFEBBDCBFCBDDBDABAEFAHG,False +296,10.0,5.0,3.0,10.0,3.0,6.0,4.0,2.0,FCDBCACHBFABDAGEAGDADEBDFDAFGABAADEADHGDFFD,True +297,18.0,24.0,24.0,26.0,29.0,26.0,24.0,26.0,HAEHBEAEEHCACDDCFDHFGCBHCBCDHFDEADBBGCBGABFAFGGHGEAGDBCCGCBDFDDFBEFBEGDEGAADHADHBHADHCDFEFFEGGEBAHBCFGCEGEBGBFGEAAEDHFDAAGHFGEEGEEDHECGEDFEBBDCCDBDECFCBBEFHFCGFEHHEHHAGHCEHCDFCDFCDHCHGGHFEFFBFHBADB,False +298,13.0,9.0,11.0,21.0,12.0,21.0,9.0,8.0,DDADBAGGAGEAGECGEFHFCCFBCABCABHAEFABFDFCHHDDEDDHADHCHABFFFEAEDCFDEGGFDDFCDFEFFEDFEBADFDDFBDFCHBGFCEDDAFG,False +299,9.0,10.0,7.0,5.0,4.0,5.0,9.0,5.0,AEBFBGFGGAGGADCADGDHGHEBHBBGEBGFCHBCHAAFAABCECCFDDBCAB,False +300,9.0,10.0,14.0,12.0,10.0,5.0,22.0,10.0,GBDGFGGEGEHGDGGEGCCGACBDBBDABDAEFABBCEAEHAGCFHDGHGGDGADGHGGBFCDHCDGCGBDAACEHCEGCEGDHCHECHCBF,False +301,23.0,15.0,14.0,8.0,21.0,17.0,19.0,20.0,FGCEGAEGEDHEDBGGECFFHEBBBFDAHHEBAEBHCHEGAAHABEEFEEFGBHGCHCAHDAFGGHGDHGFAGBABFAFHEEGEAAEDAGFAEFACFACBHFDCEHBAHCAHGAHCCGCCGEAGEACFADFHBBHBF,False +302,27.0,23.0,30.0,20.0,17.0,18.0,24.0,20.0,AACCCBGDBFHBAECFFHBHHGHAACGCHDDBFBGGCHGAFGAGGAGGAHGCHGCDGCHBHABFDBDDEEDEEDBCFCCFCHBHFBAFBDFHFBAAAFCCGHCDBADAFCABEACGBFBEEBAEHAEGAHGACBBDACDFCDGCDGHDEEDEBCFFCAACHECGCBGCEGCDAAEEHGD,False +303,30.0,27.0,22.0,22.0,20.0,20.0,25.0,21.0,FCHFDBBDBGCAADEBGFBGABGFEGHAHBADAEDACBECFFCFFGDBGAHHAEHFCAFAACEDCFFBEFAEABHDGAEHDDBGCBGEBGEAEEFBEBDHDAAACCHCCHGDAGDFCFABFHBFHBGBBDHBDHEEHECHDCADAEDGBCCBAGEHGEBGFBGCCACCAGAADAHGHHGFDABGGGD,False +304,29.0,17.0,17.0,22.0,14.0,23.0,28.0,17.0,DABGFCFHAEGAFGFBCCBEDDHFCADEHDEHGHDGADGHGGCCFFFFCCEGHEGBDDDDDFDFGDFGCEABADBCHADBGDCDAHFFBGFGGHAGHAGAEGEGCAAHAAGAAEBAGBGFBHBBHBGDCGFCDFBAEBHCFEAAEAAHGAHGAGFACFDCFEAFDAB,False +305,11.0,12.0,13.0,10.0,10.0,17.0,17.0,13.0,BFDDADEGGFGEFBEAGHAGBACAECAFFBBFHBCHGFHGHGFFGCFCBBAGCDGDDGCGHCBHDGGFHFFHGDECDFCDEAGFAFBAECAECHBHHEHCEBF,False +306,7.0,10.0,4.0,3.0,5.0,2.0,7.0,5.0,BHBHADABBABGABHDGHDBCEFEEFCEBCEHGGCGBAABGAG,True +307,17.0,17.0,13.0,19.0,19.0,19.0,22.0,12.0,FDEAAHFFBFBGFBDFGDFGDBGDBGFBFFHFFABEGGGHAAHEAFEDFCBFCEDCDAGBAFBGHDHCGHGDEGDGCBBDHGABCDHCFHEGGDBCHECEECEADEAEGAGBAEEDDEGCEGCHACBAFBDEDAFGAE,False +308,16.0,19.0,32.0,19.0,25.0,21.0,28.0,24.0,BCGCCBFCFGGDHGDADAACACGGBADDGDDGFBCHHCFECDGGAEBAEGHCDBCHEEHAEHFEFFEGFEHDCCCEGHFHHGBGDEGFHCFBFHBGEGFCGFCBHGBHEBEEBGBAGEEGHEAHEBFEBHCBGGDGDCHCCACCADBAHEDFGCACCHHCHHFBAFAEEDCECCDFCDFCDFEG,False +309,12.0,7.0,7.0,14.0,8.0,9.0,9.0,23.0,HFHHBHGACFAHHHHHDHBGHCEHEHCFHCBHDAHDAHFGDDHEBGFDDHADHBDGEEGDACDAHDAHCGHAADAECBEGEFFAFBDFG,False +310,7.0,9.0,2.0,2.0,5.0,3.0,5.0,9.0,BBABAGEAHBGHFEHBEHBHHAHBEGBGGBDACFCHFDHAAE,True +311,26.0,28.0,24.0,21.0,11.0,21.0,26.0,17.0,BFBEHBHGFHFHDDGADGADGFDCFBCHGFAEAAEAAEAABDDGHDBEDCCGFCFFCBBGGBFHCGGGDBGDBDEBCFBCABGDBGDFGEGCCAAHBGHGGFFBAHBAEGCFBCECHFADGGCECCFCBACBGBBGCCDAEHABFADDADDAFBHFCHAAFAABHHCHBCDBGA,False +312,23.0,13.0,12.0,13.0,21.0,13.0,8.0,13.0,FBAFBAECDHHEEEEAACADHEDAEAEFAEFAEGAEGAEAAEAGGBCDDFHAHHFFHFCCACAEFAHFAECHEAEDDHDGBBCBDFEHEAHBAHBAGCCDDDFGEGEFBBDBBCCB,False +313,3.0,1.0,2.0,0.0,2.0,1.0,1.0,1.0,HACAACEFGEB,True +314,19.0,17.0,14.0,10.0,16.0,21.0,10.0,13.0,AHDAHEEFAEAGCADFEHCEBCGCCGADDADFADFAHAAHFEHFEHFEFFCBFEBAAHEHBEBCCGHEBHCBFCFFGEAHEACBABBABFFGFFGBBBFBGDGCCBEDADAFBFFCHEDG,False +315,3.0,8.0,4.0,7.0,12.0,10.0,4.0,14.0,DHEDBEDBECHEFFFCHDAEBAHHFHFEGFECEEDEGHBGFBAHBHEBEDCFHHFHFDHGBH,True +316,19.0,13.0,26.0,20.0,13.0,13.0,16.0,14.0,AFCBGBFCAFCEECHBBAGCDGCFGHEBHEDCCAHCFEAEDDEDAGCAFCACCADCGDEBFAGDHGDCBACHAGHBFHCGECDCAGCADADFGDCGDGEDFADCADFFDAEDHCCHCBHGBHEBFGBCABHHDE,False +317,16.0,18.0,21.0,25.0,22.0,16.0,21.0,17.0,GDDGDDEDFEGFEDEEDHBDHBCHDHBBBBBBCCBCCHFCHBCHEHADGCDGCBGAFABCEDFFAEBCHBDDEADCGDEFAEGAGCCDCCGFDFBDHCGHGAAFEADAAHEBHEAHFCCDCEAHEAFGBGEBGDGEFGFHGEHFAFDGEDGECEDG,False +318,23.0,22.0,20.0,24.0,12.0,20.0,16.0,25.0,AABCHBFHCDHCGFGHDHHFGAGHBGHBGCEECAEHGBCGDDDHCFHGBHGBHEBHDCCAHCAHAHCAFCDFHHEBDDBGDGEABBAEBCDDFDDFEDFACFABFCHHCHHGBFAEFBCGBDHFDBFDFDAADAFDCEHCBBDFAAAAGECDABDAEFABFG,False +319,9.0,5.0,11.0,3.0,6.0,3.0,10.0,12.0,HABHDEGCCCDFCBHCHHGHAGHCGHCDHCEGCGCEGHEAHFABAECGBBAAFGAEHAG,True +320,31.0,18.0,28.0,29.0,18.0,25.0,23.0,22.0,ADEFDADBAGBEGHEGDCAHAAHCFGCHGFEGFHGCGBFDAFDCFCEBABHDBAFAFFDGDAAHABGGCAFCACCDEBDCCGCCDCCAFGGCHBDHGCHAHBBBBBCCGAADCBDEFDHCAHCHHFHAECDCHDGHDEADEDFADBADEEDGCBGCBGDGEFHAFEAFAAFGEEDCFDHFAHFAFFAEFHEDGD,False +321,11.0,11.0,8.0,16.0,26.0,18.0,18.0,26.0,HFGEAHHHHDBHGEHDFAGGDEFDEFDEFAEFBDFHDEEDEEBGEHEHHEHACGGEBHEGHEFHEHAEGFDGDDGBCEAEGAECDHCGHFEHGAGFCHHEHHFGDFEFFHBFABHDGFFBCEBAECGDABDHBC,False +322,6.0,3.0,4.0,2.0,1.0,1.0,3.0,2.0,CAAFAEHAGBDHCDBCGBAGCA,True +323,10.0,11.0,20.0,18.0,16.0,14.0,16.0,14.0,FCGBEHDGCCHABGBCGACFEFEEFEDCCCBGCFHCDAGDAGDEDFHGBAGEDFECGACGEFGEFEHCDHCDEFHGBHGEFDEFDEADBAEHFCBGCHDCHDCBDCFHBDABGAHDHCD,False +324,14.0,16.0,12.0,17.0,15.0,23.0,16.0,14.0,HDEBDGFAFHDDHDHECHEBHGHEGEGFADHGEFGDFBCEBGAFFAGFHBDHGDCGDCACFECFEHFAFBCEHCFBEFCEADHABCBBCFBAFAGFAEEAGBBECBDGBFGHGBFDDFDDFGAFDAF,False +325,15.0,13.0,7.0,9.0,15.0,10.0,11.0,11.0,BDABDCBEEECAECHCFHBBHDHEAHEAGEDEABEDHEGGFGGFEFBEHEEFBHAAAAAADAADFAEFGHHDFHGAGBBBBCDCGBFGFCG,False +326,18.0,22.0,21.0,20.0,18.0,16.0,22.0,11.0,FAHEBHABFAHGAEGHHBBBCBGCBECAAGDACFBCFEHGDHDDCDDFFCEGHEBHCFCDFCDGCHBAGCEBCBDGBDCBDHGEFADGEFABFGCFCDBCGACGABFACDEDEBDAFAFFABGEBGEGEEDEGDAGAGGEBGCBDCED,False +327,13.0,17.0,20.0,5.0,21.0,19.0,14.0,10.0,CACCAECGEGAFABCCDFAFFHFCEFCHAHBGEECEECGEFDECDECEEABFBEAEEBEDHCAHAADBABFGFFGFGGFBGBHEBHGFGEFBBGCBCCBCBECBCGFEHFHBGHACEFF,False +328,21.0,20.0,17.0,13.0,23.0,15.0,20.0,19.0,HECGCCHADAADGADBEGBEABEHFGFGGFGCBECFHBAAEAHDFHFFBGEBGCBFHAABAABDCBDCAFAAHCGDCGEEGHGDEGCHGHBFHDHCDBCFEAGCAHCEHEEFEFBDHHDEBEEDEBGGAHGAHBEFBECEFABGABEC,False +329,24.0,23.0,29.0,30.0,30.0,21.0,23.0,19.0,HADHFBHFEHCEHDHCDFCBABEEBDEHDACBGDBCDBGDBADCCDABAGCEGBDGBEGCDFAFFGEFGAGEAGEADCGHGBDEDAADEHBAHCAEGBGFBFHBGEBDBBAEEDEEFAEDGCABCEDGFFGECCDACHBDGBDFCHECHECEACEADDDEDFADFAFHCFGCADCEECFCCFCCAEBGGHHCHFDHFEG,False +330,7.0,6.0,9.0,9.0,7.0,8.0,16.0,10.0,HGGAAGEEFBEDHFDAFBAEDFGHFAHGDHEECGHCGCCACGFGHFAHEBHCGGCBGDHGDCGDCGBGDBDF,False +331,15.0,22.0,24.0,18.0,22.0,22.0,16.0,24.0,ABAFBECDEDAHCCGCAAHHCHHGBBGBAGBDGEDEHAECACBBFHHEHHEHHFHDCHDCBGFHFFHAEBFEFGDHAECEECBEFEGCCFBCGBCDEGHBGHFAHFGDBGEAGFADCBCCHCFFDEFEEFBEFHEHDCDDBHDBGFAFFBCCBCFBDADCGDE,False +332,9.0,18.0,16.0,12.0,7.0,14.0,10.0,14.0,AADCABGADACDAEDCHGCBFHBFHBEHGEFGHGECFBCDDGDAECHBCEBCFBCHHFDHDHHFFDFBGFGHBGECCFDFHDBHGBCFFABBACBCBBCB,False +333,24.0,10.0,12.0,14.0,8.0,11.0,24.0,18.0,AHAAHAADADGFHEEGBECBDCEACAHEGHEFHADAADFHGBHGBGBCGAGADGADGAHCAHFHFGEGGBACDCCDGFGBHCFGAFGBGEHACHAGGCDDHDAADGHDGFCGAHBAHBGFF,False +334,17.0,19.0,16.0,21.0,12.0,28.0,7.0,21.0,BCEAFGACAHCFEBBDBBDFFDBCDBFDFFDHFABDGBDFFGFDHFCGFGHCBHAFCEFHHBHHAHFADFBFCBFCBDCHEHDCADFDDEHDECDFCAFAAHABFBDFHFCDGHDHHCHECBEAEHAEFABDEFAFBGHEA,False +335,5.0,1.0,17.0,8.0,5.0,13.0,6.0,9.0,HFEEFACCHDCHDCHFBHDDCACCFCCGCFFDEFAFGCFHAEGFEGFDCCAFCHCGDCGDCHFH,True +336,7.0,5.0,7.0,10.0,4.0,6.0,4.0,9.0,CABCEBDDFADCAFCFGCEGEHDDBFGBFHCHHGHHDFDEHDAACAADHBDH,False +337,17.0,14.0,20.0,15.0,14.0,12.0,26.0,25.0,FEFFADAGDAGFCHHBHHBAFEECECAFCDFDDGGCHGCHFCGDGGBBGDAHDHECHGCBBBHDEHCCHFGHFCHBCHDAHCAGCAGEBHEBAAACEECEGGDHCEBFEHGHCGHCGDABAGHGGBBGFGGDGHHEHDDAAGA,False +338,17.0,17.0,8.0,23.0,13.0,10.0,15.0,13.0,DFFDBGEBEBCDBFDBAEEAFGAHDDDBBDEBGEBGBAGBGBCGEDEAHHADHDDHEDHGGHADDBDHHDCHDAGAECADCHDFBBFABDAFCAGDFFCAEGAEGEFGBDGCHAHA,False +339,18.0,24.0,23.0,25.0,16.0,22.0,30.0,24.0,DGBDGDDCDGCBGFEHEAAFCACGBFEBGCGCABCAFAGEAGEAHDCHBFEGHEBDDBDDBGABGFDGFBHCAEEAGDHEHFEFEHFGHFBFFGCAGCACCDHDDHBDFGDFGEEGBFDHHBCHDFFDCCABGBDGECBEGGGHDCHACHBHHGGHBGABDABHFCHFHHDBABGFCGFCDC,False +340,2.0,2.0,13.0,7.0,3.0,3.0,2.0,4.0,ECCCDCCACCBDCDFCDGAHHFEDFBDCDCCHGCHE,True +341,4.0,3.0,4.0,1.0,4.0,2.0,6.0,4.0,GAEGBCHBCFGAHGAHBACEECEGHGDF,False +342,10.0,14.0,13.0,18.0,10.0,15.0,4.0,7.0,BFBBADBAGACCABFAECCFCCEDEHDABBAFGGBDBCEBFDBFDEHDGHFAEECCDCCFHBFDEDDFDDCDDEHDEFFBDFBDFACHAFH,False +343,2.0,3.0,3.0,5.0,8.0,5.0,2.0,1.0,EAFDCDDCHEBFEFDEFEABECBFGEDGE,True +344,16.0,17.0,10.0,12.0,19.0,14.0,18.0,24.0,DGDFEBGECFCBBGFFEFHEHBEHGCBACBEGFGGHCBHGBHAEFBFFBHHBEHAGAADFAGFAHFAHGACGAEHABFGEGHEHHEHCABDAHEABCDHGEHGAHDDHDDBEFBGDBADGCHECHDHEEE,False +345,12.0,6.0,8.0,11.0,11.0,7.0,6.0,8.0,EEABBCDDGADCAECADHABGABECBECFEFFECDEGHAFHDGHFHAFAABDAHCEHAEHFDCDEGDGD,False +346,14.0,12.0,14.0,18.0,13.0,23.0,16.0,8.0,ECHBFBAFEFGCCDDGFDBFEGFEAFECFEHFEGBDDCHDHAAGAAGFBDBGDADDHGDCFFHEEHCEBGDGCFECFEBFDACDFGDAGDGGCGBABDCBCBAFFAFFAFEAFDHFCG,False +347,13.0,9.0,9.0,6.0,6.0,16.0,14.0,5.0,GEACFCDFGAFGAFCFFDDGGDBGDEGBAAHGAHFFBFFEEFBFFBFCEGBGGCECCAAHAGHAFAAHACGGFBCBBD,False +348,2.0,2.0,2.0,3.0,4.0,6.0,4.0,5.0,EFGDDADHEFBAFECFECFHBFGGHHGH,True +349,25.0,25.0,26.0,14.0,12.0,22.0,23.0,17.0,GCCGCCGEEDFADFDCCEHCBHCBGBBCBFGBAGFGHBGABFAGFBFFACCHHFHABAABCABGHEGBCGBFFAFGACCDDCBFGFAAAAAEACEFCEFCADCAGHAFABFDGADHHGBBCHGEBGCBHCBFDHGHHCEHBBBBEFAFHDDGFDCAGCAGDEDE,False +350,26.0,15.0,7.0,12.0,18.0,16.0,17.0,8.0,GFECAAAAAHFADABEGCECDGDAGEABEGBGBBGBBGCHEFFDFFAAAGEAFBAGDHHFGGAGEADFAEEBEFCGFDDFGDFDBFBEHHAHEAGEABEABEBBADAADAFFCEGCHAE,False +351,19.0,24.0,27.0,20.0,25.0,23.0,28.0,19.0,HHCHFCDGDBGDFGCBGDFGBFEDFBGABHABCABGBGAHGBHGBABCCEEBDFGDHGDBGHFGCFGCBHFBHECGCCBCGBFGACGDCHEEDFBGABFAFFGHDAEAAHDAFDEFDEDEECFEGHECAGCECCFCBABFADCAEGEDDFHFECFEGABGAHDHECBACDGHEEEEHECBECGFC,False +352,11.0,14.0,21.0,19.0,18.0,15.0,12.0,19.0,CGFBDFCAEDFEHEHCEACEAEEFGDAGBACBFCBFABDDGHDEHFGADGHDHCBHCEHCDHBBEFGFBADCGBHEADECDCBDCBACBACBDCHFHHCHFDGCDECGHCEEGHEHFFFFGEHDCHDED,False +353,14.0,12.0,11.0,22.0,22.0,10.0,7.0,14.0,BDEBEHDFDDCDEADEHCFHCAACAABBCDBHHEDHEFBAFDACABGEEDEADFADFBGFAGCGHCFEAEDGDDFDEEBEEBEHHEHHEDEEBHHCADCACHDDGGBFEDDE,False +354,25.0,23.0,25.0,17.0,15.0,24.0,9.0,25.0,FHABBAFCCFBCFBEDDHCHGBAEHCEBDAADFADFHFHHFHBFBCHBHHEHDACDFFAGBGDEGHHGDDCCCAHCEECAEDECFBBHDFCEFBAHAAHAFHAFHBFAAFAGGACEAEDAFDHEGFCFFCDFHGFHACHABBABECCCCACCBBCDBEBBHDB,False +355,17.0,20.0,28.0,20.0,27.0,26.0,18.0,20.0,FCDHEAHEGECAEDAEFCHFEFCCCCBECHEHEDHDHHEGHEDFEHAEDGEDGEFEECECHGCDGCBEDDEDDFDDBGGCGBHHAACABGGBCGBCGDCFHCFBCFBHFAHFEFFCFFBDACFCHBHEEFBGFBHFDGGCECAAFACFBBBABBDBEHCAFFEGCADEADFFBCGA,False +356,11.0,9.0,19.0,9.0,17.0,23.0,24.0,22.0,DCFDCHHGFEAECFFCFFGEFGFFGAHGBHAADAACEFFGGEHCAHCBDFFDGGHHBFHBHHAHFFGGFEGFCGFCHCGGGGEEEFCDHCDECHECEBCFGCHBCHAEHCEGFDGCHBEHBGHBGHFAEAEGGD,False +357,15.0,19.0,23.0,15.0,30.0,8.0,15.0,12.0,EDGEGBEGAEFADGHEFEEDEDDEGGFDAEEAGDAEEADEAEBBCFBCGECBEGGACEFBGDHECHEAHEHGGABCEDDFDDEDBHDBCBACACCGCABEGHCHCCBCCAFCHBEHEHHCCBCEBCEBCEBFBBECA,False +358,8.0,10.0,3.0,16.0,6.0,11.0,10.0,8.0,EADHDFFDBFEGFGCCAFCBHDGEDHDDFBBFEBHHDAHDHEDHGDAGDAEDGDGFBGABGFDGFABBADBF,False +359,20.0,14.0,12.0,8.0,11.0,4.0,10.0,13.0,BAHGAEDBEDCADCAHBABAAFAACGBHGBHABHEHCCHBCGAEACGDCADCHGAECADFAEBDEHFCHEAADHAGHFBEBCEAGEBGBGHB,False +360,26.0,15.0,17.0,18.0,13.0,10.0,21.0,9.0,HCBGGBGGBCCDDCDCCHCHHEGGEAFEDFAGEBDHBGAFGDGAABCADCEGCFGAEABEADHABGAEGFEAFAFCACGADDBEAGAABAHGDCDEADECDBCDBCBHCFDDFAGAEGAHGAGAAFBDB,False +361,15.0,32.0,16.0,34.0,25.0,18.0,29.0,23.0,HDFHFFDABBBBEEBGEBGEDEEGAHGBGBBHDAEGCDACHECHBGDBGDBGDGDDFBGGDEBFAHHHHEHHAHDADDEDBEBBHABHAFGDDBEDHEDHDDHGCHCEFDGGDGGBCFCCFEHFGGFHAEDFDFFCAEGABDFEDGBAGBGDBCFBCHEDADDCDCBBBDEBDEBGHCGBEABFCGGEFCEG,False +362,22.0,28.0,20.0,25.0,21.0,16.0,11.0,16.0,BHCHFBFFBDDBHHBAHBADBAHBAHGCCFCBBDBBECAEFEDHHBCCFDCBBBEBHEBFGBHGDHCFFCFAHHAGAGDBFDGFDBCGEADBFBBAAFEDGEDFDAAGBAGAABEDDACBECBEFDAHCCCCGCEEHAEADEDDEDCEACEAEDDEDDE,False +363,11.0,11.0,7.0,6.0,9.0,8.0,12.0,8.0,FBADHHEHFGGCGAFEAFEGFGGHGHCCHCCBCABAEBAHDDCGFABEABFABABDEBDBHAGGFBGEEGDE,False +364,5.0,2.0,8.0,2.0,1.0,2.0,9.0,6.0,AHGACBAGHCGHGBEFDAFGACHCCGCDGCHGHGC,True +365,33.0,17.0,16.0,24.0,25.0,19.0,21.0,11.0,GDDGDDGBDBAABAFECGEDGEDFAGCACCFHCGHCDAADBACFCHEDAEHABGGHCEEEBAEFEDFDCFDHFDAFAGFBCDAFGEDDEHBEDBDCBHCAGFHFDACAGDABEABGABGAHCAGDAFFGEFDEFGFGEEEAEAAEAAEAEFBBAHBABCEGEDGAA,False +366,24.0,28.0,22.0,9.0,23.0,15.0,15.0,17.0,HEGHECCBBCBBFAEDHBFCBFBBFABGEGCFDCHCCBAAHAADABBBBAECHECEEHEEBAECDDAGDFGDFCDCGBCEBCABEABAAEHGCHEFHEDHFGGAGEHGCBBAFBAHCFEEGAEGABAABAHFHBCCCEHAEBBEGCGFFBHFA,False +367,22.0,19.0,28.0,25.0,31.0,21.0,23.0,26.0,HGHDGHDGEBCDDCAEEADEDEEHAHBDCEEBEFGAHAADGDHBHFCEGEDBFDEFEEBEBCEFCEFCBACBADHADEGDAHCCEDDEDHFAHECDDCBEFBEGBDCHCHAABAACCHCCHCDHAGCAGEBEEAFECHBCHGCGGHFCFAGGEDAFDCBECBEHDEFFGFDGFHGFGGFGFFBFHBCCGAGHAHH,False +368,19.0,23.0,22.0,14.0,18.0,18.0,13.0,20.0,GAHHDGFBGDBFFBHGADABEHCCFDCBDAGDBFBBFBBFBFFEFFAHCAFGAHADHEBFBAFBECCEBCDDAEDGEHBBBBACBAEBDECHEGFCHACFDBGCHHCHGEHCCHCGHCGECEAGACHFCHFCHDEEEEEBDACAAHA,False +369,8.0,9.0,10.0,4.0,11.0,7.0,17.0,8.0,GEHGEBGFGGFCGEHAFBBFCBHCFDCGEHAEGCCGAEGBBCHBHFEAFGBCGADGADEADCGCHGEBAEGHEG,False +370,14.0,14.0,22.0,16.0,19.0,13.0,17.0,12.0,AEAAGFACECCFHBFDEGEAGADCEHCECCADHDEGFGGCCGBHGBHGBAFDGECGECGHBDHBABFACDDEBFECFEFFCAFGEGEEGHGCBACBCBDABCGBDFEDEDDHDFBDHCCHCCHEADE,False +371,24.0,19.0,21.0,13.0,20.0,18.0,17.0,23.0,GEGEADCDGEHBDCBDHAHCEFCEFEEFCDFBEGAGFHGFCCHCCFFCFFAADAFCABBBHGCHDHEAAGCAGDABHHCHHCHGBEFAAFHAFHGHHGDADEABEGBCGCDBADEHHEHACDABGECFEFEEABEBBHBBABCAGCFGEFABHAH,False +372,3.0,3.0,3.0,4.0,0.0,2.0,1.0,2.0,DDFDDBCABHABACFGCH,True +373,11.0,27.0,14.0,16.0,27.0,12.0,14.0,25.0,BGEGGBDBADECHGHHEHADHDGAEAHEFHBFHEEDGEDECBHFEHEBHDDCEABEAHEAHEBEEBEGAHCHHCBBBBBBBCCGDFGEBBEFHFDHFDHFDEFDEDEHGEAEEFBBHBBADBCBCCBGFDGHEFABBGHCCCGCHH,False +374,3.0,9.0,10.0,10.0,8.0,7.0,11.0,11.0,GCGGBBHHCCGFDGFDHDDHFDBFEGEEBECDDAECCBBCHGCHGFHADHACBEFHEBHDBHDGGFGEC,False +375,23.0,33.0,18.0,22.0,30.0,18.0,26.0,23.0,EBDEBDHHGCCGCFGADGBCGHCEHFEHDEHBEGDDGBHGAHDAHDBCBAABCFBCHEFDADCAEBBBBHBAFBAEBAHBHFBCAGCFHDADEAFECEECEFBBGGCCGEHHBBHEDCAFAHEEFFEAGABGCDGBBGBDFBDFGDBEDBHFBGDDGAEBAGAFGEEBEECEABEHGGADGDGFHGFEAEHHE,False +376,26.0,12.0,16.0,23.0,9.0,18.0,21.0,30.0,ADDFFDFFDFFHCFCBFAGFBGHEDHEAHECHCABFAEAAGAAGDDDDCFGCAHABDEGFHBCBCADGHDGADGHEGHDGHFBHGDHCDEABHGEHBDADAACHHHHFHAGHEGHDGHDHHCCCAHDHHGGFAAAAFABFHCFGBHGAACBGCDD,False +377,14.0,10.0,11.0,6.0,8.0,8.0,6.0,11.0,FCEFBBABDCHECFBCGBHGFHECGCFAFAEFDBACADCABCHHEAHGAEBAHAAHAAGFDCBDCBDGAEHHEH,False +378,10.0,13.0,11.0,8.0,10.0,9.0,5.0,12.0,ADCHBEECEEADBACBGBBAHBGHCCHGBHCCACCFHCDBDDFFDFFBFEAEHABHDBDAFHECBAHEGHEGHEFBAF,False +379,26.0,14.0,13.0,28.0,14.0,24.0,18.0,23.0,ACEAFGAGABGAGGEHAFHDCDDFFCGHCDHAAAEFFEGABGAHHADFGDFBCAGCAGBACDDDBDDEADCCHGEAGEABHHFHCCBDABHFEEDGHBGBBHFDFCDFBDADDEDDEDHFDHFDHEDHAAFAHDGDBGEFFABAECAHHFFHFFHDFHFG,False +380,21.0,15.0,24.0,10.0,21.0,16.0,24.0,20.0,GBFFDHFBFGEFHHHHHECHEDEEBCAFAABGACGBCAECBCCBEDFCDGCEEEAEGAGGACDAFDCGBBGBBCAFFDFHBAGGDGGCCHEAFEAFCAFCAHCGGAHCACCAEGHEHEEGEEGDCHDHHGCEGAFHHEHACBCFGHBGBAG,False +381,15.0,21.0,27.0,23.0,28.0,27.0,27.0,20.0,BCBHCAFBBGEBDEDHCDGCGGCGDCFECDECEBCEBFEBFGCGGBGABFAEHCFDCHEGEFFFBGFECCEHCGFFGFHGBECCFCFAEDAGAHDAGEFFFAFDACCHCHBBHFCDAGDHGDEGDBDEHDHHFHFBHDBFDEAGCADBDDBDDEEFEEAGEGGBCGEFEEFDGHHCHFEHCAGGABCE,False +382,0.0,4.0,3.0,2.0,1.0,1.0,2.0,3.0,BCDBHDBHFEHGGCBC,True +383,1.0,2.0,2.0,6.0,6.0,2.0,4.0,2.0,CHDAEDGEDCEGEBGEFDEDGHDFB,True +384,12.0,14.0,12.0,10.0,21.0,16.0,19.0,20.0,GDHEBFGHDHCEABECBDCAHGAEGCEBCEHDEAEBHEBHFHHBBFFAFDCGHAGDCBFHGHCADBAHBGHBGADHFCHFDHCHECEECEGFEGEAGEGGEBFEGAEBAFFFEGFGGDGHFEHF,False +385,9.0,9.0,5.0,9.0,10.0,4.0,7.0,7.0,BCCBABGHBGDEGDACDBEFBHDGADGAEHHCFCEFDEBDBBDAAEEAEHADAGEHGFHE,False +386,15.0,9.0,11.0,11.0,15.0,15.0,12.0,13.0,EGCFFCFGCFHFDHCHCCHACHECAGHFFABEAHEFHEDDEBDHBDHBECDEADGFGFBGFAGFAFAHEEEBDCDGEHGAGGABAAGDFDBEABEHECFAA,False +387,17.0,16.0,9.0,11.0,9.0,4.0,15.0,11.0,DADCFEBAEAGCBBHBEGBDABFBDFDHCAFEGGEAGEACHABHAGHDGHBHHBGDEGHCAAGDAHACEGBBGABAACGACGBDGBDHBDCE,False +388,10.0,3.0,8.0,5.0,5.0,8.0,6.0,3.0,BDDGGCAECAFGAFCACADCEGCAHCADCBFFAFFHHFADEGFEGBEA,False +389,17.0,13.0,28.0,32.0,15.0,31.0,24.0,29.0,HGHCCHGBFDBGAAAAEDAFHHDEGFECFHGFCFFEHFDHGDCCFCHFCFDCFDGEHBEHGHHAACAEDAHDACGEGFEBHDHCFHEFHGFAGFACDACBHCDHCDCCDEFDEFDHFECDHDDCGDGBBCCFDHBDFBDFCGBBHAEHCDGGFHGHAGFBDBDCGFCGFDGDDFDHGHAFFAGDCEDCF,False +390,23.0,24.0,19.0,26.0,25.0,15.0,25.0,27.0,FADECFEGAEGHCFDCBGCBDDHDDHDDAGAHHAEBAGDAHBHGBFGBGGFGDCADCBHBEHDEAEHGEHDBHGBHEBDGBHECAEDADDAEHFFHFHGGCCHHEFECCGDEACEHHAHGAFAADBBDCBGABDACCADABFABEHFEBEEBDDACDEEDGGGGBHGBHCFGCFHFBHCBEGEE,False +391,4.0,5.0,5.0,5.0,10.0,9.0,7.0,10.0,FGGFGCEGEEHHDHGDCEDAHBFHFGDFEBHBHHAHFCCFACFGBFEEHEEDEAB,False +392,2.0,1.0,3.0,2.0,5.0,3.0,4.0,3.0,FBGCCGDCAHEFHFDHAGEEGEE,False +393,32.0,34.0,23.0,23.0,23.0,22.0,17.0,26.0,AABCCBCADCAHAAEFAFBABBHCCFBFGDHDHCAHFGBBCCBHCBHBFCDFBHBEABEAGEDGECBEBHEBAEFHEBEBDHAHHBGCCFDDFDFBDHBGAAACEACDACHADFAGFAGFHGFDFADFAHEAEEBEAGDDHCDEFDBHCGGDGDAHABHEBHEBEEBEHFABAHBGEBHCFDGFGFEDADCACHACBGBB,False +394,10.0,5.0,5.0,10.0,12.0,9.0,5.0,11.0,DCDEADHACFADFADABDHGHHDAHGAGEEBEFFCFAEDAGBAEBCEHDBHFFCEFHEHHEGEEDHF,False +395,9.0,8.0,7.0,6.0,6.0,3.0,2.0,9.0,BAGBECDECDCHEAHAFGBFHBAHDHHAACAACHHFHBDDBEEAEDBCCB,False +396,28.0,25.0,16.0,17.0,19.0,17.0,23.0,14.0,FBGFAAAHBHHGFCGDGGBGGEGGEFCEHCDGBBHEACEGBEADCADGEGHDGAAAAABFABFADFCCBHCADEFGEDDBDACAABAAHHHFACFBDAADBAGBGEHDEDBBFBBFBBCEAGEBHEBHEBEFBCFECFEGDGBAGDACDHCFCFGAGAE,False +397,11.0,7.0,11.0,10.0,5.0,9.0,10.0,7.0,BCHBAHFDBFCHFCDDBHGAGCHGCGGCGGFGEAEECDDFADEBFCHDCHBGABGEFDCFDFAAADAACA,False +398,21.0,30.0,21.0,28.0,27.0,13.0,18.0,24.0,CBDCAGAAEHGBHBHHFHHAHHCGHDBDABFBEHDEBCEDFDCFDCFBCEDCBAEBEDBEBBABEDGFBGFEEAEBGHBGCBACBDCEECBDCDDCAAGDGEAGEAFEGEEBEHFDHDGCEBFEBDGDFHAFHFDHECHGCDGHEGDBDBHEBHGBDAAAAEADDDCABHDCHCEHCHGBBA,False +399,8.0,12.0,5.0,5.0,7.0,5.0,5.0,13.0,HHGHBAEGABBCBBCBBCFBCBHADAAFBAEBEBFHDECEEFHGAHGHHDFHDGHAHHED,False +400,7.0,6.0,11.0,5.0,6.0,14.0,10.0,3.0,AEFAEBCFDCFCFAEFCGGCGECHFGADCBDFGCHCCABCAGGEFHEFGAFBFBGFDGFDBF,True +401,5.0,2.0,3.0,1.0,8.0,3.0,7.0,1.0,BAGCFGEEAEBHEGFAGFDGEEGECAEGAC,True +402,7.0,14.0,22.0,10.0,18.0,10.0,12.0,15.0,GHECCAABBCBBEEBEGBDCEECFGGHCHACHAHFBGGCCCCHCEFCFDCHDCHDFHECHACDBCBAEBDEBDGGEGHDCEGHECEECEEHBEHDFBFBAFHDFGFCG,False +403,14.0,14.0,19.0,22.0,20.0,22.0,14.0,19.0,ECCEDFDGEDEEBCBHDAFBAFAAECCFDCEBBEBDAHCADCFDHEBFEDFEFEGFEAFHAFHGCHEEHDDFEDFDCFDCFCBAHFAHFHHFBDFDDEHCGGBGHBAHCAGCEGAHBHCGCEDEFDFGDHGFCGBBGCHGHDDA,False +404,9.0,11.0,17.0,12.0,11.0,7.0,12.0,10.0,BCBDCEGCECEGCDCCDGGAHGEBGBHCFCAFHAFHADEAHFDHEBCCDCCDCBDHEDHADBAHCHDDGBEGFGGBECFEFEGBAGCAB,False +405,5.0,5.0,3.0,4.0,12.0,4.0,3.0,6.0,DBGAEGEEDAEHAEBBEBEEHFDCBEFGEFCAFCEHHAHEDH,False +406,15.0,17.0,23.0,27.0,15.0,22.0,16.0,20.0,EFCEGEFDBFHCCACBDDHDCFBHFHGFCECAEABGBGDHCDBCABGADFDDFECCACFAEFHDGHDBHDAHDHHDHBFEFDEADFADBDCHDEHFCHFGGFHGHHEAACAFCFBDDCEBCGBDGDEGDBGDHFCCFDEHCBBCBGDFGAFEAGC,False +407,11.0,16.0,12.0,20.0,16.0,15.0,13.0,15.0,HBGBDGBDGFGEFCCHCDHCDHFFCDBCFBEEECEFCEABEHDEDBEFHFDAFDBHBBHDACAHFAFBAEBDDDADDAFDGGGEEGHEGDFHBFHGDBGCBGBACDAHHCEAEEDHGF,False +408,16.0,12.0,20.0,13.0,15.0,13.0,22.0,14.0,HACHAGEAGFHHDDCEDCBFEDFEACBBFHBFHBCGBCACCBDDGDDBEFEGGHDBDDGGFHGAHFEGAEACDACGABAAHEABECECCECGGCAHFAHFGGFEECEHAFDGGGGCFHCGGCGBC,False +409,4.0,7.0,9.0,5.0,9.0,7.0,4.0,6.0,EFCBHCFAFFACFDHHBHCBGBBGBCEHGECBAGDCEFCDFCDEEHEEAED,False +410,12.0,11.0,9.0,6.0,6.0,6.0,2.0,5.0,DDCDHBBABBACFACEBDEHDHBFBAFBAGCAEAEEFHCBCCFHCAAEAABDABGFC,False +411,10.0,13.0,4.0,12.0,8.0,3.0,7.0,11.0,BBHBBDDDDDEEAAHAAHBAHGEHGHHAEDEEDACDBBDGCDBBABHHCGCFGFEGBAGBFDDAEHBH,True +412,2.0,7.0,4.0,0.0,2.0,6.0,5.0,2.0,BGBFGBFGBCGCEACFBHFEABHCBGFF,True +413,28.0,23.0,16.0,19.0,25.0,12.0,17.0,19.0,BHADEAEEHEEAGEFBBCDDAGHHGHAEBDFBAFBAHAEHBECBDCGDGBFGEEAEEDBDDBHDEHGECAACGACABCABFABCADEAHEDBCGFEBFEADEBEGADAAFAFHADBACHABHCCDCDBFABGAEGCGFHACDEGHHGHGDHFBHEBEGC,False +414,4.0,13.0,10.0,10.0,10.0,2.0,11.0,8.0,EEGCECCGBBGBCGDEEAGEDBHCHHADHDBHEHCFBDBGDBDDBDEADEHBCAGCBGEGCBGCBGFH,False +415,13.0,21.0,20.0,13.0,22.0,19.0,15.0,24.0,HFDBGDBHHBCCFHHFBHFBHFBHACEFEHFCBGBBFBHFDGECGFCAABGCFGCHHBHHEGFEABCBECEECGDCHHFEDAHBAEEDECDHDGHFGHFAECAFBAGBDECDCHBHHDCEFCAFEHEEGEAGEAFEDEBACBDCBGG,False +416,21.0,17.0,11.0,9.0,12.0,14.0,19.0,7.0,CGHHGBDBAGBAGBDGACGAHFFBFAGCACDAGAAEAEFCCAEFBCFGCAACGEFFBDAEDABDCEGEFCEBBHFBHEBHEAGGBGFAHFEBFBBDABFAGGAGGDGADE,False +417,6.0,8.0,8.0,1.0,1.0,6.0,7.0,5.0,BADAECHCCHCCHAAFCGFBGBBHBBGFCFHCGGBGGBFFAA,True +418,11.0,22.0,19.0,15.0,20.0,16.0,14.0,28.0,CCEHHDBHECHCGAGDCCABHFHHEHDEGBEGBDDBDEBHBBGFFCFFHBDHBCHBEHBAHFFGFCDHHDCHBEABHDBHCBAAEFDCBCCDFHEFGBDABGFBCADEFDGFAGEHGBHCBCGFAAHEEHEFHEGEEHEEHCGHC,False +419,25.0,19.0,13.0,15.0,18.0,30.0,15.0,15.0,FHCDCFBEHCABEAFAFHEFDGFDCDEHAFGAFBDBBFBBGBAHFAGFBFFBDBDDEGFBDEBHCBFCEFCEFAECAEFECGADBABAEHFDGFGGBGFBGDAAAHAAHDFHGCHFCAFEAEEDECDHBFAGHAGFEEFAFFAFAHCAHG,False +420,5.0,4.0,3.0,9.0,10.0,5.0,4.0,4.0,DEBDADFEFCEHEABEAEEFEDHGDHEDCFGCFDDGBDGBEAAH,False +421,21.0,22.0,19.0,21.0,16.0,23.0,24.0,24.0,BGGDDGBHHHHGHHDAGFAGFBBFGGFGEHBAHECFACAGHEFCEADEAEBAHBGBBACDACDHCDHCHBCDBDDGCFHHFHHAHEEHCGCBGAADFBGEGFCCFCGFDHHDHCBFDAADABBCBFCFGDECBEFDEGDEDFABFADFGBFGFAGFADHHEGABCFBGEE,False +422,5.0,3.0,3.0,1.0,0.0,2.0,1.0,4.0,ABCABCBGAHHHFHAFCAD,True +423,8.0,5.0,10.0,3.0,2.0,6.0,4.0,7.0,CAHCAGAAEDGFCGDCFHCAHCAHBBDFAFFGBFBBCCCHCEHAH,True +424,4.0,2.0,3.0,3.0,3.0,5.0,4.0,1.0,GDFGCGACDACDEBFEGHEFFAAFB,False +425,20.0,29.0,28.0,22.0,37.0,21.0,18.0,23.0,DCDEFDAGCHCHFDAFEFFEHDEDBEABEHBEBFCBEDBCDCCEGCEBCEAHDHHDAHGAHBBBFABFABACBADHEEHEEAEAAEACDCHBCEDEEBEGGEBEFDGCBBBAFDAFCAFCHEDBEDGECHBHGFGECEDGDFECFDCFGHECEEHFEBCABCADEAFEGBBHBFGBEHCCHBCGBEFCHHCHGGGGDF,False +426,3.0,6.0,6.0,5.0,11.0,8.0,8.0,8.0,ECEBAECEDDEBDGBGHDGEBGECGFHGFHACHFGHFCFBEFHHBHEADEFGCFE,False +427,9.0,21.0,17.0,17.0,18.0,17.0,9.0,12.0,BHBBHBBAFBCCHEBDECFECDEFFGHCEFCAFAEHDGHDBHABEEBEEDAECBDCECABDAFDHDGEDBBDBFAFFCCBHCDHDBFDGFGBFCHACDBCGGDGGCBFFBFEEFHECEED,False +428,13.0,9.0,6.0,7.0,7.0,9.0,7.0,6.0,HDAAECHEGFFGFGCFHCBGAADAADAAFABFBEEAFFBBCBBEABECGHDGEDGDABDAFHCH,False +429,8.0,15.0,19.0,18.0,20.0,20.0,16.0,22.0,FGDFDDFHDGAFGFHEBABCDBHFGHFCHACACCECEACEBCFGDBHFEHFBHGHHEHEBGEAFFHCFDEFDADDBDGHFBDFBCFBGAHFBECHECBECHECECCEDCHGEEGEGFDFEDBEHBHCDGDHCHHGGDG,False +430,13.0,25.0,20.0,21.0,26.0,17.0,24.0,16.0,EFFGFCDFCEHCGHDGEECAEBBEGBECFEGHAADDAFCAFCBCEECFFCFCAGDACHBHHBGDCGDGGDEEDBHHGCHEDBEGEECEEBEBBDBAEEFDGBGGBDAEDHEFCGBCGFCGAHGFHDBGGBFBFFHEHBCDBADCEDEBBGAAGHBGHBDBDD,False +431,13.0,21.0,18.0,12.0,10.0,10.0,17.0,15.0,GAFBBBBFHGFAFBGCGGBBCABCAGDHGDHBCHBHBAHGGHEGHDCDBCFBCGECAEDDHBAEBDHBDHBDACECGEGGDHADBEFCDBGACEAHBCFBEHAEHAFGCCGCCFFC,False +432,14.0,11.0,9.0,15.0,14.0,12.0,12.0,18.0,DFAFFAHDHEDFEHHEDHCFHCECBABBDGEFGEDCDCGDHHFCHFCGGCEGABGDBEABAAHAEBDEBHEGHFGHDHEBADGADBAEHCEHDDHBFAGAAFFGH,False +433,16.0,16.0,12.0,20.0,13.0,18.0,9.0,14.0,FDCFDADDBDDAHDCBDCDDCDAEHAFAABADBECFAFBCFADAGCAGCDBAFCFFEHFHBFBEHGCGGDFGDABDEECGGDFEFBHCBHBEHBEABEHBAHGAEFBEHHHFEHFDFD,False +434,15.0,21.0,15.0,6.0,12.0,5.0,12.0,17.0,CBBDBGABGCDGCEADBCCADEFCCAHCHCDHCAHCHHABHBBHABEFCGCBGAFAAHEAFGAEGAHGEEGHEGBFBEECHEBBAHHCHDBHBBHBBABBGEG,False +435,0.0,0.0,3.0,2.0,2.0,2.0,2.0,3.0,CHDCEDEHCGHFGF,True +436,22.0,21.0,21.0,13.0,7.0,14.0,20.0,13.0,BHBGDAADEDFGCFGDHGAGGAFDCCACCHEADBCFBCGBFABEHDCHCEGBGDAGAADCAHGHHGHFFDEHAGAGGABCAFAFFACHACGBDGBDCBDHAGCFEBFACHBCABCGFCAFGBEBBCBBCBB,False +437,18.0,12.0,15.0,15.0,9.0,15.0,19.0,9.0,BEAEFBCFAADCBFGDGGHFCADAADGADHCBHDGDBGDBGDCGAHEFHGFAEBAHBADGCDGCGFCHFDEFEHFCAAAFBAHAEGDEGFEDCCBCGBFGBFGACGCCADFG,False +438,9.0,15.0,11.0,10.0,6.0,5.0,12.0,8.0,CBBCECABBAHBHBCHGGEGGDAEBEDCDFADBGDBGDBGBBCDGABHCFGBFGHFGHFEAAEAABHDDCGCCDCH,False +439,21.0,34.0,13.0,20.0,9.0,14.0,18.0,22.0,DBGDFCCFEAGHBHHCHHCBHBGHBDABCCBAFBAGBDCBDBBGBAFFDHEHGCBACBAEFGHBGAFGCFBAGHAHHAGHGCDEAHABHBDFEDBDDADDHFBHFBEABEABADBHFHDBABBHBAEBGCDCFHGGGBBGFDGDABDABDE,False +440,5.0,7.0,4.0,9.0,2.0,7.0,1.0,7.0,DEBHHHHHHDFAAFGADHABBFFDFFDBEDCCCCFBDDBDAB,True +441,9.0,3.0,11.0,9.0,5.0,3.0,13.0,6.0,GCHGCHBCDDAEAHEAGAGGCGEAEHACDFBDBDGCDGDGGHGCFGCAHCACDGCAEFD,True +442,26.0,15.0,9.0,16.0,20.0,21.0,20.0,20.0,EEHEFAFDDHDDBDEEFFEDFCHFAAGHAEHADBAGHAGBADAAEABCGBCBBFGCFGEFGEFGHDEAEEAFHFGHDGFAGACGCHBCHEAHGABGBGADGFFGEEBCFDHAEBAGBADAABBHFHHCEEFFEDFHAHHAHADDGFG,False +443,5.0,11.0,13.0,10.0,14.0,14.0,10.0,14.0,FCEHCEHCEDGDBBDGEDHEABEFGAFGAFCCFHFFHFBAEEGDFFAHECHGCHDCHBGFEHFHFFBBCBBEHCHHBECDEDBEDCGGGDC,False +444,9.0,3.0,12.0,6.0,9.0,11.0,10.0,6.0,GACGCGACGBHABFCEFCEFCAFGFEGDCFBCHHHHGAAAEADCDGAGEEEEECFFCDFGDFCDFH,False +445,9.0,10.0,13.0,13.0,17.0,11.0,15.0,15.0,DGCDBCDFEFHEHHEDDEGCCFCFFCGDEECEFHHFAHFAEDGGBBGHHGCHGBACAAHEEHEEDGGDGGDGEEFEBGHBCDCAACAHDHBFEFCEDBHBBAG,False +446,4.0,1.0,6.0,9.0,11.0,4.0,5.0,7.0,GACEFGGACGDFDECDEHDEHDEHEEDAHDCDFCDBEHAGFCHEEHE,True +447,26.0,19.0,18.0,11.0,16.0,16.0,12.0,21.0,EEHFFHCBABHABHAEHAEHEFFGFAGHBHAEEAEEAGAAGCCGABDACECFHGHHEDHCBHCBHCBAGDABDCHAHEFHFHHDDFBFFAFCACABEDFEDAGDBFCBDAGFACEACAGHABBFBBEBACCCGHCDBAG,False +448,6.0,5.0,7.0,6.0,1.0,1.0,3.0,5.0,HADHAHCACGDGBDGBAECACBABDCHDBHDCCF,True +449,11.0,2.0,6.0,6.0,9.0,16.0,8.0,5.0,AGAAHAAGFDFEEFBEDGEGEEFEAFCCDEDFFGFFGFFCFAEFAFHDFCBHADHFGHACCAG,True +450,11.0,4.0,8.0,12.0,7.0,9.0,7.0,8.0,FDEFCADCGCEBAHBGECHEFHCDACDABHGBFFDFAEFAEADGADFEDHCAHGDHDFCDAGDAGH,False +451,31.0,20.0,20.0,33.0,22.0,23.0,32.0,17.0,BCCAGAAGFAGCEGDBGDACDHDHGFBGBBDBFGBHBAHECEECDEDHHDFADFEDCEGHAFBCCBFADGCBADDFEFGEHGEFGDHECAEAGEDDEBDEADAADBCBGEDHDDFCEAAHBGBGFAGFDGFDEFEGHBAHFAGFDGDDFDFABCABCAFCAFCAGCAHEGHGDAADAGEFGHDGCDGBGHCFAGDEGA,False +452,6.0,6.0,6.0,10.0,8.0,9.0,9.0,6.0,AFEABEBDGBAFEDHGFHGEDGEHCHAGHECHCCFDADDFEDFEBAGCFGFFGCBGDBDD,False +453,13.0,18.0,14.0,23.0,17.0,19.0,19.0,12.0,DCGDCDDCADEBFFBFFCAACDACDCCABCDDFDFAAEGFHFADCBGCDGEDAFGGEHHEFBFFBFFBGFCDFCGAGDDHDDHFEHGEBGHDGHAEHBGBDEFCBDDEABHAGEBEEBHEDEGBHGBFGBGEEGB,False +454,18.0,22.0,18.0,14.0,25.0,31.0,12.0,21.0,FHADBACFDHAHHDGHBFFFCFGCBGDHFFFGFFGFGGFAHCHEEHFHDFHFFHFAHAHEACEGEEBDEDFAFFBFFBFBEFDCBBEAEHDFDEEEBBGCBFCFCBGBBFEHGCDEHDECDECBADEAEEACEACECCABBECBECBFAFAGHEHHABHAB,False +455,8.0,7.0,7.0,9.0,13.0,7.0,12.0,7.0,AGEBFEADAAGFABFHDEAFFCGFDEHGABGCBHCBGBDHBDFDEGCEGCEDCEHEDHGDAGEHEEGCEG,False +456,26.0,25.0,17.0,12.0,23.0,17.0,8.0,10.0,BCAFCEBDBGCAAFAAFGCBEAEDDBADBADCHEFFEADEAEEFEEGAEGEHBEGAFHAFHDFBBAEACCAECBBBBBFABEABDBBDABDCEDFECACHFHAFHGHDCCAGFEEACEABFABFBEFAEBBGHBCHCC,False +457,17.0,13.0,15.0,8.0,13.0,12.0,8.0,11.0,HFCEBGABGABDAECBBCBBEBEEBFEAADACFHFEHFBACAACDAFHHFAHGAHAAEAHGHCGFCDFDAEEBDECCHCCFFGBEGCDFCBCAEDHG,False +458,4.0,0.0,3.0,1.0,6.0,6.0,4.0,0.0,FEEFEFFGCFAEAGCAGEADEFGC,True +459,21.0,25.0,18.0,16.0,17.0,17.0,23.0,17.0,HDAGCGGBBGBCEDCBBBEGFEGFEGFAFFCGFCBECBFFBEBBGBFABCAFAHEHEDHGDCCEAAGAAGBCGHCBHCAEDHHDFFDABEFECCABHABEDBEGBEGDGDFGAFEAGCDGCBHHDHCAHGABFDEADBADBHGAGAHFHGCHDB,False +460,10.0,14.0,5.0,9.0,15.0,9.0,9.0,8.0,EDEEGEAGEGBEDBDFGDEABFAFDAGEBBABDAGDBGFFHAEHDEABGBHABEACEFBDFBCHGCEBCEBEHHHFHCF,False +461,5.0,3.0,5.0,6.0,2.0,12.0,7.0,4.0,CEAFFGFFGFFDFHDFBDADACCGGCABAHGFBFFDGHDGHEFC,True +462,6.0,6.0,14.0,9.0,5.0,9.0,18.0,19.0,FGCDHCHHGHDGADGECGHCGCGHCEDGEFFHHFHFGBAHEFGBCGHFDHFHHCGHCGHEGBCCBDAHDHGBHACGCGFCDABDAG,True +463,3.0,5.0,4.0,8.0,5.0,3.0,5.0,5.0,DGAFBBFAHGEGGEGBECECCAHHDDDEDDHFDHBDCB,False +464,8.0,5.0,4.0,6.0,7.0,4.0,8.0,3.0,DACBACHAGHBEHDEFEADGGCFEDGEBGEAGBAGFDGFDAAEBC,False +465,13.0,13.0,10.0,12.0,11.0,18.0,10.0,10.0,DFBGFDFFDGBBBEDGEDBECEEDFHAAACAAHHHHHBGGAAAFHACDACEFFHFFHAGCBEFBEBAFGAHGDEGFFBFDBFDECCECCGBCDBFDF,False +466,1.0,7.0,5.0,6.0,4.0,4.0,5.0,8.0,DHBECBCDBGDBHDBHFHECAECFFGHDGBBGHCGHDHFE,False +467,8.0,10.0,7.0,7.0,13.0,10.0,14.0,7.0,GGBEGHAGEGBEDBCAFFBHEEAEFBEGCFGCFHBFEGFEBFHFCHFDGDDGHDGDCHAEGCEGAEDCEBAABABG,False +468,7.0,9.0,14.0,4.0,4.0,10.0,8.0,4.0,FECAECBDFBGFCCFECFDCBGCBGBFDAHGAFGBBEBCHBCAAHGAGCCCFHCFGCDAF,True +469,11.0,8.0,10.0,17.0,9.0,15.0,9.0,16.0,FHDFDDEACFHCFCAHDEHAGHACHDGBAGBEGBAGEHHDGHFEHADHAEFAGGCFECFBCDGDHHDADBCDBEDFFDFFCCBEDHFHAFHDFDB,False +470,1.0,3.0,1.0,1.0,2.0,1.0,2.0,3.0,CHADBEEBGHBGHF,True +471,17.0,15.0,26.0,18.0,19.0,21.0,23.0,27.0,GFFCCCHCDHAGAEGFGCBGCBFCFFHDFBDCHDGHFEAFEAEEAEGDHGHCGABGDCGDGGFFFACHBEAEEDEAHFAHDHHGCHFHHGGHBBECGECEEDAHCACCBBCFBCHGCHACFDCEDAHCAHFFFDABEEBCBAHFCHBHBGDGECGEHDHGDHGDFD,False +472,2.0,5.0,3.0,5.0,4.0,6.0,6.0,2.0,EGHFGBFEBFEDFHGCCFEABDADDBDGBGCFG,False +473,20.0,30.0,26.0,33.0,27.0,26.0,18.0,15.0,CGAHFAGFAFDBCDEGDEHBEGBEBFDGFECFHBFHBEEFEECCEFEFFHCDGAHABDFBAGBADBADBDGFGCDCABGAEGDDDDACFACEAFEBEGDCGCEFDEBEEDFEFFDABDHBDEBCHBHHFDDBCDFGDAGHBDABFBDDDFFBBACBCCBCABCACCHGCBFBDDEEBCGDCGDCEDCHFEHEAHE,False +474,19.0,17.0,14.0,18.0,11.0,17.0,20.0,12.0,GAGCCFFCGFEDEBFFAFCGDHGEHGEHGHGFDFAAFDADDADCACCBFBDGBGGBFEBCABDAGHGBDBBHFGEAGCDGFDCFCHFAGCBBABBABAEBCFCDEDHGHAEHAEDAEDGFDGDAHHAB,False +475,29.0,21.0,29.0,16.0,8.0,11.0,32.0,19.0,GGHBGAGFAHFBGAHFBHGBHGCEACHGBAAAFHHFHHCBGCGAHBDCCDGAAGHHDBDCBDFBDBEACAFCEDCBGABGAFEACGACGCCGBCGHAGADEAHGDCGCBBAFBADCGBEGBEGBAGCGGAGABCCHCDACGHDGEAHAADFCCHACDGCDGCDFC,True +476,1.0,0.0,5.0,0.0,0.0,3.0,1.0,0.0,CCCGCCFFAF,True +477,12.0,12.0,12.0,10.0,3.0,21.0,15.0,7.0,FDFAGACBDCBGCEFEFDGAGGBBDBBAFCADCADCFCGFCFFHFFHBFCCDAGAAGBFDCFCAFHDBBGHDGHFGBFBEFGFFAHGAGGFH,False +478,17.0,16.0,18.0,22.0,16.0,25.0,17.0,21.0,ACEFGEHAECACCHBGAFFBCFECADCEFAEDEFAECBCGBCHFGHGEBAEAADHGDGAFGDDCEHCHAEHDEFGHHHBHABFABFHCFHCFHCFBDFBHBEFFEDFCDBGDAFDGBHFBHAEDCFHBDDGADGDFCDFGDGBDGDFHDFHG,False +479,10.0,7.0,13.0,9.0,7.0,6.0,9.0,3.0,HGCDGCAGAEGAGCCBCCFCEFEAFEACGGCHDABDECHFABFEBEBADBDDBAACGCFDCDDG,False +480,1.0,0.0,4.0,0.0,2.0,0.0,5.0,0.0,GCEGEGGCCGCA,True +481,21.0,16.0,14.0,17.0,11.0,10.0,25.0,16.0,FDGEEGBBDHAHGDHBHGBGCBCCFACEAEGAHHDHBGFDGADAAEAAFHCFHDFABGCBGAGGADCHDCECEDBDACDAHDAGDBHHBAGFAEFGBFGBGHAGAAEDCBCEBHEGHDDBGGGGCAGCFG,False +482,12.0,17.0,21.0,17.0,21.0,22.0,20.0,24.0,HCBHEEHCEHCBHADGBCGBEEHHFGHFDHFCHCGHGGHBGCBCHGDDACDFFFFFGBACFECGCFHFAEDHDDBDDHDEGDECAGCAGHAEHAHFEFDEACCDGGGFGCEBCEDHFCHBHBEHDDABHFFFAFFBFEBEBBGAEGCEGCEBFE,False +483,19.0,21.0,17.0,13.0,22.0,21.0,20.0,24.0,GDGGEGFHAHAEHADHCEHDAACCBEFBEAAFFAFGHHBHDBFDFFACBGDDGDHHBACBFDHFDBFEFFGABDACDFFHGFCCAEBBHGBHBBEBGCDGCHGCHEFHEAHEHHGACCACGAHHEBGECGACFEEEBEFBCFEEGEHGEAGBFHBEB,False +484,14.0,17.0,19.0,19.0,23.0,9.0,30.0,14.0,DBADEECEEGGGCGGCHGAEDCGDCDDHDGGDEBHBBCAHHADGGGEGCECCACHAGHAEDABCHGGHAGDADBEFHHFBCEAGAGGDGGHGGACFFBFGCFGBBDBECBEDBGFEHDEBDEFHEBCEBAEGEECEGBGFCDECD,False +485,23.0,20.0,17.0,18.0,15.0,7.0,16.0,20.0,ADAADBBFAFFAFAAGCDHCHABGABCAGHBGHCAHEECBECGDHHAHDEFBGDGDBGDBAAEABGHBDCECCBGGHCEHBFABFABCACAECBCDDCBEEADEADHHDHDDGEHGEHGEDCBDCHAAGGBHHBHE,False +486,19.0,15.0,16.0,14.0,11.0,13.0,25.0,19.0,GDCGHFGHCBDBAAAAAACAGHBGADDCCHEGBCBDAFDBGDBDEAAGAHBAHADCDDEHHFHEAGCGGCGGBGHCGCBGCBDCGGGFEGBEDFHCFEBFEAFGAEGCFGCFGDEGAHFEHABFFBHHHHHH,False +487,17.0,28.0,19.0,19.0,12.0,13.0,19.0,22.0,DBDEFAHAGFBGHEGHDDBBEBHEBHDCHFEHGEHGBBACBAGAAGEBBHBDFBDFBDCCHCCAEBGDGDCEBCACFAEGAHDFCCBHCEHDEGCBGABGBDFHCFDDFDBFGAGGFHBCHCABDABHAHCAGCHGBBBCBHFDHADHG,False +488,11.0,5.0,10.0,9.0,17.0,10.0,8.0,12.0,HFEBAGAEFADDEHDEHAEHDEHAEDEEDGBCHCFECFBCHGCHGEDBEABGAHFAHFHEEGFHACECCADEDCEFCAFGFG,False +489,15.0,27.0,19.0,19.0,24.0,16.0,18.0,23.0,GDHCDCEEBEBBHABHFBGFEGDDHDFACCAGGADEBDEHABHAFHGBHAFCAFCBFCFHCHDEHDBBFABDEGCECHDDDDGEAGHAFHFEBBEAHCAHFGHABEFEHDHHDCGBEHBEBCCBGDGEBGEBEECEGBECBEBDEBFGHABHFFDGCCGBC,False +490,3.0,2.0,6.0,3.0,7.0,0.0,1.0,4.0,CBCEHEADEACEADEDBCGHHECHEC,True +491,14.0,16.0,16.0,14.0,17.0,13.0,22.0,10.0,FADFCGFCEFCEBCGBCBBCBBAFBGGBGBEEEFDBBDHEEHGHAGHAGDDGBEAAGDFCHADHGDHGHFBDEDDEFECCEGGGGGADGCBEEHDCGCCGABHDBFAFEEECCAGAFGAFCA,False +492,26.0,18.0,20.0,24.0,26.0,19.0,29.0,28.0,DCADFADCEHGDGGFGEAHEHHAHFCCCGHBAHEAECBBGGBHGBHDBAAFECHEBHGFHCAHDAHDAHACHCGHCAAEGGGDBGDGGDEGHHDCGEEGEDAEDCGFCDFEFFADHGBCABHDBEGBGBHCHFGDFEFFEBBEDBEAAEFEBFGBAHAAHECDGDDFDACCAFAEHGEDGEDCEHFGHFA,False +493,1.0,0.0,2.0,1.0,4.0,2.0,0.0,0.0,ECEECEAFFD,True +494,11.0,16.0,14.0,24.0,25.0,15.0,20.0,16.0,HFCEDHDDCEGCFADBEDCEDAFBACGFFGHDDDGBDFEAFCAFHDFHEFBAFBDEBEHCEDBHDGHDFAEFCECCBGGBFDBCDHAHBGEBEEHGGHABDGDGGDHADGAEEBFECEECGEGGEBEEBHGCHGDHGDEDE,False +495,15.0,21.0,13.0,15.0,18.0,25.0,20.0,12.0,GFGGDGBFFFDCCDGCDECAEFFFHCECCEDEEAEEBEFHDHBGGBGGEGHAGEAGBGEAFAHFACFCHGBBGBBCCDEGDFFFFABBBEBDAGDAHFACFAFDABDBBEFDEFAFBBFBBFEHHGHDDHBFGAFHEGC,False +496,14.0,17.0,8.0,12.0,24.0,10.0,23.0,11.0,GBFGBDGAFGBGEBFEHDGAFEBCGGGBABDAEDGEFBAFHEFHBFHEEBGEBAEGGEFGEABAHBGHBCFGEGCAGCEHEGHDDEBAGCAGBECDECDEGDEGDBDHEEHAEHDCAAE,False +497,8.0,11.0,13.0,8.0,7.0,15.0,9.0,16.0,EHBHFAFCAGEGGCCGCAGBAGHDFFCFHBHHDDHFCAECHDBHCBHAFFDFEHCGDFGAFCAFCGFEBBCBBCFHDHEDHFBHEBH,False +498,3.0,6.0,8.0,3.0,3.0,7.0,4.0,5.0,CHECBEABACCGCBGFHFFBGDBFDAFDEFCGBCHFHHC,False +499,7.0,4.0,9.0,5.0,5.0,8.0,3.0,3.0,ECEEFHFFACFAHAABEABDCCGFDGFCCFCCFGDABDCDEBAH,False +500,7.0,8.0,5.0,8.0,4.0,3.0,2.0,4.0,CAEFHGBDDBDDBDDBCGBCFDFDHCAEAEHBEABAAHACB,True +501,22.0,26.0,22.0,26.0,16.0,25.0,21.0,27.0,EBHCGHBFHBFBAEEAHFAHEADFGDFBFHCHCCHGAAAAAHAGBBBDBCHCEHBHHGDDFBEFDECDBFFHFFDDDDDFDAACHBDABDHGCEGCGHFGAFDCFGCFGBBGFACDAGHFGHEEAEEAHHBDDAABBCBCDDCDCGHFGHEBHABGFCGCEGCBCHBCHDGFFBFGEFDEHDBAD,False +502,10.0,11.0,12.0,13.0,8.0,15.0,13.0,13.0,GFHHEHDCHDEFDADGCDGBDFADFHFACFACACBFCGFCAFEECBECBACAFDEHBGGAAFDGHCBDCBHGBHDFHDHGEFGFHGFHDBEBGGB,False +503,5.0,6.0,10.0,4.0,4.0,8.0,9.0,0.0,FEDCEDCGBGGBCFCFEDBEGAACABCGCCGFFGFFDAGGBCABCF,True +504,7.0,14.0,10.0,11.0,12.0,9.0,6.0,15.0,BDBBGBFCEDCHDCHEFFECHGDEEHEDHDBCDHGABFABFBBDBBCEECHEGFAHCGFBHFAHFAHDCEAHBDCBDHGEHAEH,False +505,21.0,9.0,16.0,11.0,15.0,16.0,15.0,15.0,DFAGEAGEAFCCECCECFEGFHGDHAFBCHEDHEHBEAGFCHDHGAHFFCAAGAAGAAGAFEDGCDFHGEHFEDFBDCAHGAHBABEABGABEDFFHGFCEACHADEBCCBGFDCCHA,False +506,17.0,15.0,12.0,11.0,15.0,5.0,18.0,14.0,BHGDHFBGBBABHAEGAEDAEAEDBEDGCGHADCFEHAGHAHHAFADCBBGEGGBDBBDEHHHGGBGADGACHCEGCEHAABFAEHAECAECEECFBCGDCGBCGDG,False +507,23.0,16.0,18.0,17.0,15.0,30.0,19.0,16.0,CAHCHFAHFDGFDGEHAABDAFCAFBAGBHGHCDBAAFGFFGADAHDGDGGFEDFEDCCCCDHGFFGFFCHFAFEAFEFHGBEFEEFEECDBGGHHGHCEHEGCADCEBAFBFDBGBCHBFFBFFBCDBDGAGFABEAEAAFFCBFCADCADHA,False +508,2.0,2.0,6.0,5.0,8.0,2.0,3.0,4.0,AECAHCEDEEGEDCFFCBECDDGGDHECHEBH,True +509,10.0,15.0,13.0,10.0,20.0,25.0,8.0,14.0,BFFFFGHDGHBEECGECGEHFEFAGBHGBEDEGAEAHHFFHCFCFFHEFADFBCEHCEGFAHFHEFECBDCBDABDCBFCBDHBEFCEFCHFEBEBFEAFACFHFBAFEADDDBE,False +510,9.0,6.0,15.0,8.0,8.0,15.0,8.0,4.0,CGFCHFDFCDFADGADECCCFCAFBFFCCFEGFDGFCGCCEBBEAEEAEFGHDGDFCHFEFAGDABBCBCAHA,False +511,1.0,1.0,2.0,5.0,3.0,1.0,4.0,3.0,GDDGCBGCHDEEDHEDFAGH,True +512,16.0,13.0,8.0,20.0,20.0,20.0,19.0,18.0,GEEGAEDHBDFBGBGGHGEEDHEHEGFEGBEGFHGEDBBAHGFDAFDAEDGFFHFFHEEHDEHDGDGADCADFADABFHDFCEFCHFDGAGABHAFHGHCBFCHEHBEAAEAAEBCEDFGABDCHFCBFDFDDG,False +513,2.0,0.0,0.0,0.0,3.0,1.0,1.0,4.0,HHEHHEAGAFE,True +514,16.0,32.0,27.0,32.0,20.0,18.0,31.0,18.0,FFCEHGEAGHCGDDGHDFEDFDDBDCHDAABHAGDEGDEGEFCBDAEABBAGBCGHEEDCCBCCAECAGBDFBCHGHHDHADGGGCCFFAGBGFDGACBHCBDAEDBEDAGDHCDGCEGFGCEGDADDCHBGHBAHBEGBEFBFGBHDHGEBBDBBFCCCDEBDFBDBBGFBGFBGFBGFHDBCCCEBCGDCED,False +515,26.0,15.0,26.0,29.0,17.0,18.0,23.0,22.0,GFHDAEAAEGAEGCEDCDDCAHCABBAEBECGEBHHGAADFECFBCFECEDGDDCDCGDBDFGCGHDAHFADDAHCADDGDFGDEAAGAFDHGCHDCBDCGCBGCBFABGAHHBHDFHDFDDGDCFFAHBEHECCFCBACHACEGCEHHBHFGHCGDAGDAGECBFHAAGFFDEAH,False +516,12.0,12.0,20.0,17.0,22.0,17.0,13.0,11.0,EEBEADDAFDADAHHEEBGEBFFBEBCCDFCEFCEFCEFCABEFHEFCEFGFCGCGHCHDCGFBECACAGDAHDGGDHFDHADEADBFHBFABDHECFDCHCEGGDCDDCGBEAFEBECGECGE,False +517,17.0,18.0,11.0,13.0,13.0,9.0,14.0,20.0,BEFHACHEDBAAHAHHAGBAGCGGHAADEHDEHBBHGEHAEHGEDGEBCEBCHAAHBCHADHCDBGFBGHAABBFFFCCFACBGDBGDBFDCFDCBEHFHHEGBADEDHEGGABD,False +518,20.0,13.0,17.0,15.0,17.0,19.0,27.0,13.0,CFECBCGACDECDHCHAGGAGGAGGAGEAGHBGFFGHHDEHDHDDGAAGDDGDHBEFDAGBABEECEAABAAFAGFGDFCDCEFGECBCGGEGHEGHBGEFHFFDCCAFGAFEAEEFCFACFGBDCBCAHGBEGFDFHBFB,False +519,4.0,10.0,8.0,8.0,7.0,6.0,3.0,5.0,EABADFAHCBFGDFCDCCBACBEFDGBHGBHFEHFECEDHBCCBEDBEDBD,False +520,21.0,21.0,12.0,9.0,4.0,4.0,12.0,8.0,FAACBBBAABGAFADBABBDBBABHACGACBABBHHCECAACAHGDHGABCBDABAGBDGDAEDGCDGCABFEHEAHFBHGADGCCGBCGB,True +521,7.0,6.0,5.0,6.0,9.0,6.0,4.0,9.0,HDFFDAFDAFBFEAGABCHCHHBFHBGEBHEHHEHEDAECEEGACDECDBGA,False +522,7.0,13.0,6.0,12.0,9.0,15.0,17.0,9.0,FEHCDBCDGGDGGDHFBHAEFDEFDFGEAABAFBHCBEFBACDGBDGHHBFGDFEDEEGGBGGBHGFGFEGHCFBFFBGFGHBADCAD,False +523,13.0,18.0,26.0,23.0,24.0,18.0,20.0,22.0,HDCHAFHBBHAEFFCCGDFGAFCFDBHGFGEFBEGCEHDHHEGCEGEDBDDBGAFHCFHCAECHBFHADHFDHECFBCBBEEDGBCGEEEDGHFGECCECDACDGFBCACCDDGDDEBDGBDGAACABCABCFBEFEDHEDHDGHEFHECDECGAHGEHGCCBH,False +524,23.0,26.0,27.0,25.0,18.0,14.0,25.0,20.0,AHEABADDECBHGBEGDCHHCEDCECAFCACEFEEGGDGGDGEDGCFBAEAHFGDFCACHEBDDBADBADBDDACFAFAGCBBHBGGFDBFDGAAGAHGDHFBEEDCCDCBACHHCHECFDDHABAACAAGHHGBGGBGFBGFHDCBDCBHBHHCDFCDEBGHBGACGCCGECBBBEE,False +525,9.0,5.0,7.0,9.0,10.0,14.0,16.0,12.0,GDEGFEHFGFFECEBCBHHAHAGHAGDFCDHBDAFFFGFGGHBDHFDCFDCDGFEGEGCEGAGAAHAGEGHEHFEHFGCDBA,False +526,21.0,20.0,28.0,24.0,24.0,22.0,22.0,28.0,FBFFHFFDFEBCDDDFBEABCGECGECFHFFCFDAACAAHAHCDHGHHFHCBHBDHGDGDHAHCDHGABAABGCGAAFBGFCDFCDFCABEHDEAGHABHEBAEFHCAEABHGHHACFEGEEFEEGDFGDCCDCEDHHGBHGEHGECGDHDDAFCEBDHBGGECBDCBGCAGCEBCECEBCEHCDHEDF,False +527,20.0,11.0,8.0,13.0,17.0,8.0,13.0,14.0,DDHGDHCDHDDHEGFEDECAEHFFHAABEGBEHBCAGADGACFACECDEAHGABBCEAAEAGFABAABAHGFHEEGGDCEBAFGFHGAEDHEDHEABEABDHBG,False +528,9.0,13.0,8.0,10.0,8.0,6.0,9.0,7.0,ECDBCHEGHFFBEDBGDBHDBHDFHFEBBCDFDACACCBEHBAGBAGFDGADGACHABDAEABGGEGCEB,False +529,2.0,5.0,6.0,3.0,4.0,6.0,5.0,4.0,FCBFCBFCDCHDEHBFGFFGAEAHEGBCGCHDEBG,False +530,5.0,3.0,3.0,2.0,4.0,2.0,5.0,5.0,AFBAEGACGFGHCEHEBGEHGHDAHDACB,False +531,14.0,18.0,15.0,23.0,16.0,17.0,15.0,32.0,HBAHEDHGDHCDHDEHDEHDEHDHFAGADFEEHBBDFHDAEDEEHHHBHDFHDFHCFCFECABGGBEGCEBFBBDBDCCHCAACFACFHEEHCHHDHGFHGFHDCDDBEBGHAFFCGBAEBAHBGHAGFBGAHCFFBDGDCBDHGHGDHA,False +532,8.0,6.0,17.0,12.0,9.0,14.0,14.0,11.0,DEGAFHFDCCDGCHHBHCFDCFDCEGGFHHCAGEGBFGBDGDAGHCGCCGDCHDGEDBEFFCFDCGHCEHEGHACCAFAFFDFFAEBAEBC,False +533,15.0,11.0,12.0,12.0,16.0,22.0,21.0,18.0,GAAFFACGGFHDCBDFBAFBAGEAFEBFGGFDDEGFEACHFFBDFGEGDFFAHFHHAHHEHHFHFABECBDHHDCHDGGDGGEFGEHACGACGECEECEEBDBHDHHFHEFGGCABCAFEFCGGGBA,False +534,6.0,6.0,12.0,13.0,5.0,12.0,12.0,8.0,HDGAGHFGHFCHABHFEHFACCCBCEGCGDCDEADCFDHGDGFDGFBGCDCHFFEGFAFDDFDDGADCBECBGB,False +535,22.0,16.0,25.0,15.0,17.0,33.0,16.0,16.0,FBFFEECEEDFEFEEBGGDGFEAAEFCGFDGHDGDEGAAAHACFECDACDCHFCHFAFFAFEGFBDFECHHBACBCCACDAGFGDFEDFCCFHCBCCFACAAGADGHEFFCBFHDFCDHBHGECAFFGBGBFGAAAFBHFHHFEBFCDFCBACBHCBHAB,False +536,20.0,17.0,26.0,15.0,22.0,17.0,17.0,16.0,BHHBAFEEFAEFAEDBBDFEEBCEHHAAHAGBDGBHBECECCBFFAFEACEGCEFEECDDDGBDABEEBEHAAHCFCCEACDAHAGHBGFACFHCGHCFCCBCFGHDHCDHCDGCEAHGAFBADGGFCBFCGDCGCCFADECDGGEGAEB,False +537,13.0,10.0,5.0,5.0,10.0,8.0,9.0,7.0,EADEDEAAGAEEBGGHHBFFBFEBFBBDEAHEABCAHCAEFAGDAEDBFFGFAGAHGCHGHABCGBC,False +538,10.0,10.0,16.0,12.0,12.0,14.0,12.0,13.0,DFCGBCDFCDGBDCFCFFCFDAHDCBECEEBEDBEHECFECGAHGDHEAHAHHGFHGDHFFCGGCEGFGGCGCAAHHAEHCBDFBDEBAFADFAEBCBH,False +539,2.0,2.0,4.0,2.0,0.0,2.0,1.0,0.0,ACCFCAFCBDDBG,True +540,3.0,8.0,6.0,4.0,2.0,10.0,5.0,6.0,FGBFBFDBFDBFHFFGCEAFHCCBFCBECFABGDGHDGHBHHAC,True +541,4.0,4.0,3.0,5.0,9.0,9.0,6.0,7.0,HHFDFBDFAFFAEFEHGEHGEBGEAHFDEBCGHGGFEAFDDHCEBCE,False +542,1.0,6.0,4.0,1.0,3.0,1.0,2.0,0.0,EGEEDACCFCCBBBBBGB,True +543,11.0,8.0,11.0,8.0,8.0,12.0,13.0,10.0,CGFCHFHAFHGCGCCHCGHGACBDDBCDFADFADFBBEDAEGACFAHHGBHGDAEFGEAGEABHBGFBAEEGEHDFCGFCF,False +544,1.0,2.0,1.0,1.0,0.0,0.0,2.0,3.0,GDAHBCHBGH,True +545,20.0,18.0,24.0,26.0,24.0,22.0,18.0,33.0,CBHDDADAHFAEFCEHCEHEBHCBGCHAAHAFHFFEAFDAFBEEGHAGDDDACDHCEECEGDEGDEGBADBEDBAACEECHFBFCHFHHEEDBHHAEFCCHHFDBFDHCHHAHHAHGCHCCGFCGBGGFGDFBHFDGGDCEDADDADCFBCHBCBFHEHBEGAFHCCBEFFHDHGAEGDBGDEHD,False +546,29.0,23.0,21.0,19.0,21.0,27.0,25.0,20.0,BHEADFCDFGBFAFFACEAGFABFACFACFHEBHBFHDFGEGCEHCGDCDFCACAGDEBDEFAEFGEGGHCEHEAFEGECAAGAAEFFFFDFGGGCDGBGEBGHBGEBADFGCAGEADDBDDBACCCBDBBHAAABAHBACGECDDHGHHGBFEACHBFHEDCFDAHEAGCBGBAHFAHFBHFBH,False +547,8.0,14.0,13.0,15.0,21.0,12.0,10.0,20.0,CHCHGGHDDADDEGDBGFHCBECDEFBGHEECEGCFAEHHEHHCHHCHFFAAEDAHDEGBEHAAGBEHDEDBCFFEFCEFCHHEHBEHBEHEDDEGDGABCEBDBBCBFFBDF,False +548,5.0,4.0,1.0,2.0,4.0,2.0,2.0,2.0,ACBADGEEGEEBAFBFHDAHBA,True +549,14.0,13.0,9.0,11.0,17.0,24.0,19.0,14.0,EHAEHGEDBEDCEGGEHFBFBBGBGGFHAFHBFEACBACEADGFEACGFEGFADHGDAGCBGHGCFEBAHBGHAHADDAFDHGGHGFFGFFCFFEAFEGEEFFHFDBBDCBEHFFDFAEFC,False +550,8.0,20.0,16.0,21.0,30.0,20.0,19.0,15.0,FHEAEECEEGBBBBBHBBDDCDDCDBCBFFEGFBCEHEEHEEBEEHFDCEECGBBGAGAHCAFCAFGDEGCEFEHCDBEDHGCGFFGEEGEECBEFEHFHCDHBDFDDGGDHEFHGDECDEHEGACFAFFGFBGBGAFGDDDDDBEFBH,False +551,8.0,3.0,13.0,5.0,6.0,13.0,5.0,7.0,BDFEDFGCFCHFCGCAFFAFFHFGCAGHAEHCBCCEHCHDCADCFFAEFCCDHGEFAEBA,True +552,10.0,10.0,17.0,16.0,16.0,11.0,4.0,13.0,CABEDBDDCCDFHBACBAEEDFGACHECHECEDHDDBDDHAHCBHEFHEFHEDDGACAECHEFBEFDEDDHCBHCHFGBFEBDCFACEGCAACFCEF,False +553,29.0,25.0,19.0,15.0,29.0,33.0,22.0,26.0,EABECBEDDEFBHACGBHHEHFFAFFEDBAGFCHDGEDEHDGDDCADHAFFABHCFEEBAECAECHHHACCAEABEABCCECFECEGCHGCFFBFFBEFDGGAGAECHEHHDHHABDEHAEFFEAFAFFAGFHGEAGFFGFAACAEFFEGBAABFGBEGDFHDFHEFBBHDHHGHBCABABBFBBGBGGEAGBFGCFH,False +554,19.0,13.0,14.0,11.0,11.0,13.0,12.0,8.0,ABGABGBBFEBEDGCDFCEAGEAGHAGFAGHACHCDHADCADFGDCDDAFEGFEDHHAGCGCFDEHBEFCFFCFEABGABFCHEBABBACADEAFBABACC,False +555,4.0,7.0,2.0,2.0,5.0,4.0,2.0,1.0,ABBABDFBHFBEFEGBAGEAEEFDCCB,True +556,33.0,24.0,13.0,22.0,28.0,22.0,18.0,30.0,EEFABBCDBADEGEHHHCAHGEHABDDBDAGAABDGBABBAGBEBHEFDEDCHDAEDBFHEAHFAHFABFCBEHBEHAEHCHHFEHBEHFEFFHAFHAGHEGDDHBCEDGAFGECHHDHFAEFAECAGAGCEGADDAEBABAAHHAHGAHFEEECAACGFCDFDDFAFEBBGHBGBAFBEHDFGDCGDFA,False +557,21.0,20.0,17.0,15.0,9.0,13.0,11.0,17.0,FFFCCBHDBHDBDDBDDHDCGFBAHBHCCDAADHAHHADGADCCHBCFECEACECCFDABDCEHEHHEBHDFFABAABAGBEGAHGACGCGGFBBHBAFBABAGHAFHFGCGDEFBBCABAAE,False +558,17.0,17.0,12.0,11.0,13.0,15.0,10.0,21.0,AACABFAEFAEGCEBAFBFHBDHEAHEBEEHDHHBHCBFGAFGFCACBFBDFADFCDBHHBHDACECHHDABGBBGFGHDACEBCEBCAFHDEBDCAAHHFHHFGHEGAEGHFGHD,False +559,14.0,31.0,29.0,20.0,24.0,28.0,19.0,25.0,CBHCBFCBGABHAFHAGDBEEHABFAEDGEDECFFCBFDFFDEAEHDDCECEHCBACBDFBCEECGGCGFCFHEABDABDGBDAHFHHGADGEFHDGHEFHEBBEBGCBFBBDCEGFFAHGBHAFFGFFHEFHCCHBBHFEHGBDDHCBCFBCFBCADCDBCGCCBBCBECGDCHDFHBGHFGFCEEHEE,False +560,11.0,11.0,9.0,9.0,7.0,8.0,12.0,11.0,FDCFDGECEACDHCFAFGAFAFECFCHECHABHGBHBBHBGEGGAGGAFDBHDCHDBEDGABEAGACHBHDBDABGHG,False +561,17.0,20.0,22.0,24.0,12.0,25.0,33.0,19.0,GFGGFCGFGDHGBCGHGHHGHCGHDGCGCDDCHGCFGFAHCHFDFCDEBDEBGFCEFCFFGAFCCGCHACBFDFGEEBBDDBECAFGAFGADGADGDDGADGFDEBDBBDBGCAGHGGDGGBBDFHCCDCEFABHHBHEEHBDHAFAGEAGDABFAHHAFBFGDCEBCBFFA,False +562,11.0,10.0,11.0,8.0,5.0,15.0,7.0,5.0,GBAGDDBFDHFDGFAACAACBBGFGEBGFFCFFCEFBEFBCBACFFCAHCAHEEDBAHFCFFCDDAGCAHDB,False +563,20.0,11.0,17.0,13.0,14.0,9.0,14.0,23.0,BAGDHGEHCAGCGEFAEFBCCHCCBDADHBDHADHCGHAGAFEAHHAHHACGCEACAHCDHBDGGDFEBFHHDHHCAHGAHFEEDGFDECDHHEHACFGHFECEGBBCAACAABDABEGBE,False +564,25.0,13.0,20.0,11.0,13.0,16.0,8.0,5.0,AAAAFFCFFBBFABDAGEAGAHGACCFEFGEGAEAACACEFCFFCDCHFBBCBCCADFBHFDCCBGABGCBABBDFACAAFGACACDEEDECDBDAEDAHDAECAECEEHF,False +565,28.0,15.0,20.0,25.0,16.0,15.0,18.0,16.0,AADAACACCACGGBEGAEGBEGFHCHCCEBCEBDBBDBCDAEDEBDABDFFHHEAADAHHGHGBDGCAGFADAADADFHEFHFGDEBDFCAFEHFBBFDHCDADDACDHFHAGCGDAGCABADCADEAGEGCHDDBDCAGFHGHCGAEFFECE,False +566,7.0,8.0,2.0,9.0,6.0,8.0,0.0,5.0,HEFHDFDDHDBEDBEFBDBBECBAFBFDAFHAFEDDBCEAAAFHA,True +567,12.0,8.0,8.0,9.0,5.0,12.0,6.0,5.0,DADDAGBGGBCHFGFDAFCACAEFADFGBFABCDDFEDFECHECDBAEAHCAHBACBFFAFFBGH,False +568,27.0,25.0,25.0,24.0,19.0,25.0,34.0,18.0,GGBDADGGGAGEFFECFEBGEADDADDAFHBBHBCFBCGGEGEDHDHBDFBACBGCFACBCGBEGHHGCAGHGBAFAHHBFHAFECHCABFGHCDHEFEFCEDCEGBGGDAGFFGFFGAFBEFEAFEGFDBFCAGCAGCABAHHHCEACBGEBDEAACCFGGFGDBGDCCDBEGBCDFADBAGBADDADHCDHCDGA,False +569,17.0,19.0,19.0,27.0,20.0,24.0,19.0,16.0,DCECCEHDBFDEDGEAGFGFBCHBCAGAHGFDAFDBHAGEADCHDCDGCBHCEFCHFCGFAADABFABFEECGFHHDHBDEBDBCFEEFEEAECGDBFCBDHBDEBDAFDAHCGDEBDEHDFADFDDFGAFEFCAFHDBEBBDGGACDBCHGFFGFGGEGH,False +570,14.0,23.0,26.0,22.0,21.0,32.0,13.0,35.0,DEACHFHFDHEHFCHFCEFBFHBECFECHDGEDFFDEFHFBCCACCHGDFCHFEHCAHCHHCEHEEHCHHCAHDDGFBHCBEAGGDBGFBEHBHFBADBFDAFGGGABHAGHABDFBFHCFDCFDHEHCEAAEGCBGDFCFFEFDBFBBFBCHBHDBEDHDDBAFFCFHAEHCEHCBHDBCDEGFH,False +571,12.0,18.0,32.0,29.0,10.0,22.0,15.0,20.0,DAHAAEGCCHHEBCEBHDDGDDFFCCCCCHCFHDDHDHADBEFBECBCDBCDFEDGHDHCECGACDAEGGDGDBFHCFDGDDGAEFDCFDAADAADHBCBBCGEDBBHCFHCABFDHFBFCBCCBCCHCFFDGCGGCHCBFDFFDFFCFHHBHGFCGD,False +572,19.0,12.0,16.0,19.0,24.0,11.0,17.0,21.0,AEAGEAEEBDEGDECBBDAHDAFECHEFHGFGGDEHDECGGCAEHEHHCBHDDHDEGCEGAHGFEGEEGEECFADFEDEGCCABAGBAHAHHAEHACACHAFHBCBBAEAFBHDDADDGDBFHGCHFCHCCGFDHDDBE,False +573,5.0,2.0,3.0,2.0,1.0,4.0,3.0,2.0,ACEFDDFABGAGGACFAHFCHB,True +574,17.0,18.0,22.0,17.0,4.0,9.0,12.0,14.0,CCBCGGAHDAEDBCFCCHCFACFAEDAHDAHGBGDFDDCACAAFBBDDBDBBFCBECADDACBFCBHCHHABCAHGBBGBADDACHAGHDGHDHBEHBGBGGCFDAGCCCFHC,False +575,13.0,19.0,23.0,32.0,16.0,20.0,25.0,19.0,GGDDGDDCHDBGDFDDHBBHGBHBFHCEAFEHFGFEGEGGDGDFCHFAEFBCFGHDGDEGDBHDAAGHDDADEBCEGCEFCEFEDBACHAHFDEFCGFGHBBBABDCBFCHDCFFCHDDGDDGECGEDAAHAADDAFDCGCHBCGBCEHDEGFFHBDCBDBGCCGCC,False +576,9.0,9.0,12.0,4.0,5.0,6.0,12.0,11.0,BHFCHFGHEGHBGEFHADCDCGGCFGCBDABAEBACGHEGFBGBAHCDHCGHAGEAHHCCFCBGABCA,False +577,6.0,7.0,11.0,9.0,9.0,12.0,13.0,8.0,EDDGBABEGCGACGECECCBCCHGEFDEFGGFGBCGDAGHGCHBFGBFDEFCFFAGFDHBDADFADFHHFHEEHC,False +578,0.0,1.0,2.0,1.0,0.0,2.0,4.0,0.0,GCGDCGFFGB,True +579,5.0,1.0,1.0,3.0,1.0,1.0,1.0,4.0,HGAHAACAAEHDFDDHB,True +580,23.0,6.0,7.0,14.0,17.0,10.0,20.0,6.0,EEAEEHDHGCBEABGFBGEACAADADGADHCGFGGEHGAGGDEAFEAGEDEAAAAAAEGCFGDFGDEGAEAFBAHBAGDFGDFECCECGDBAAGDEGHAFDDF,True +581,26.0,18.0,18.0,18.0,15.0,22.0,19.0,23.0,FFFAFECGECGHCGACGACAFFGHGEHADHFDHBDHCACGABGAFHHGAFGABDABAFBHEBAEAHFAGCAGCGFAEDGHFGAEBAEHDDHBDFAFBHDBFCHEHHGFDDBAEHAECAHGHECDFDDHHBFHBFCBADFFDCCDBCABGEBCEBDEGAC,False +582,21.0,17.0,16.0,25.0,18.0,9.0,13.0,8.0,GAHDCGBCBACDDBDGADCEDBFDAFDADEAEEBEHADFAHEGDBGFHGHCBAAHDEHEEACDACDECFEAHAGGAEGAEFADBGEBGCDDCFDABDCCAGBADBDFFDGDECDBCDCCEEBBEBBA,False +583,3.0,13.0,7.0,7.0,6.0,7.0,7.0,14.0,CGGBGGBGFBHBBHCAEBHEBHFFFDFADCDBFEBGCBCHHHDHHDBHEGDECBAHFDHBEHCH,False +584,19.0,16.0,23.0,16.0,22.0,21.0,12.0,29.0,CGHFFHFFHCFGDFDEECFDCDDABFAEAADFBEAECAEGAECHHCHAEHFECCHGCHGEGGEDHBABFAHEEBGEHHHBHHCDBCDBADCACABCBCCBHBGHDFHBFHCABGDCFCCADHAHHEHHEHFEABEGGAFDFEEFEAFCDDEHFBHCHF,False +585,5.0,14.0,11.0,11.0,4.0,5.0,12.0,10.0,DGDBCBFGBDAEHACCEHCDCCBHFBHFBHCAHGGGCGGBGCBEDBGBAGHFCHDCGDBHABEFBDDBDDHG,False +586,11.0,24.0,18.0,11.0,8.0,6.0,17.0,13.0,GBBGABCCDDEGDFGAHEAHCAEGBEGAEABEAHHCHBBHCBHCBGGGGGGBHCBCCBDDDCGGBEFFADFGBCABGBBDCBDBHABHBBHFBDFCHCBGDHACCCEC,False +587,14.0,18.0,17.0,13.0,15.0,17.0,25.0,21.0,ECCAFEAGBAGCGFCGHADHEBGCGGCBDCGABDHBEGBCGHHGFHGHHGHDGCACAEHBBBABGFHGFDGFDBDGBAHHGGBCEFCFHHFEHFEFFAFFAGFCHCHGABCHEFHCFEBDEBDACGAEGEEHBBDEDDGD,False +588,13.0,15.0,14.0,18.0,15.0,14.0,13.0,9.0,EFAHGBHGDHGDCADGDDEEEECFACDGDGHCCFCEDCBHFBGDBCDBCGFCGBCEDDEAFEAECAFCDFDDBHABHFEEBBHBACBADBGDEABFGFFADGAGFAEFEBH,False +589,12.0,8.0,10.0,3.0,6.0,15.0,8.0,10.0,FDAFCFFHFGHFGBFHAHAADACFCCBBCBBHADHACFAHBBCGGEBECHGAHEAEEAFFFCFFHGFCGAEG,False +590,17.0,15.0,7.0,14.0,11.0,14.0,9.0,6.0,HEAFCADCHBHAFEFFEDAAFBABCGDDFAAGDGDCBEBFEBDEBAEAEBAEBAFBGFBHFCGCHGHDGFAAFCADBDDBDDGFAGFABEDBE,False +591,10.0,3.0,10.0,5.0,10.0,14.0,7.0,11.0,CFGCFEAFHGFCGAHACGFEADCAECAEBEDGFDHFEHFEHBEHFECFAAFHAECDHGDBFHHFAHCCFG,False +592,19.0,16.0,12.0,22.0,13.0,29.0,15.0,13.0,GHBEBBFBGFCCFDDECDGGDFGAFABCHFAFFABBCHBAFGHFBEFDEFGEFGDDGDDACDBCEAFEACEDDFFAHEAEDDHHFFDFBGFHGDBFHECCCFBDEBAHFAEFAGFBGDHADAFDAFDAFHAFGAGCHDB,False +593,7.0,6.0,8.0,6.0,8.0,9.0,6.0,6.0,DCHBFDCFDGACEACBBCBGHAGHFEHFEHDEGAEAACGFBFCHFCAEDFEBEDGF,False +594,30.0,31.0,17.0,16.0,20.0,23.0,18.0,23.0,ECHGCHGBBGFBGABGCDGHFFBFABDADAFEAFEHGBAABEABHABHACFACBEFADDADFBCGHHABFEBEGBCGEHFEFEBGEHGDAFBHDAFBAHBAHFAFACGDCHDCHDGBEBHEFEAFEDHACEBCFBCHBFHBAACFCBAHGHDDEADHAECACGBBABAFBFEBGEHGD,False +595,9.0,14.0,16.0,12.0,7.0,14.0,15.0,6.0,FEGFGGFDBAGEFGEFCCHCBEFBCGACBACFCCBCAFCAGGFFCBHGBHDBADADHADGBDGBDEBCHFCFCCGBDGDHEDADDFEBGGCFB,False +596,26.0,34.0,20.0,24.0,21.0,26.0,22.0,25.0,FEEBEHGEHEFHEFEEACGABBDHDDHGCGFDACBGBHGFHDADCFGCGBDAHHCFHGFEEFEAHEBHGBAABDABFAHFHDDADDFDBGGBFHBAEBAEBAHBAFACFADADDAGGBBGBBCCACFFBDFHDFHDBCBCABAECDFGDGHHEECCAFDBDEFCEFGDBBHBBHGGHFBHEGGEBCABCFBCFCAHBA,False +597,16.0,18.0,17.0,23.0,22.0,17.0,16.0,28.0,EECBEAGEDFCFADAHFCHFCHECDBGDBHDCHAAHDDBDDCDHHFHBAHBEHDEHAFHAHHEEGEEGDEBDEDDHBEBGEHGEHCACFHBDBACHECEBCACCGCGGEHHDHBFGEABFDFFDGFAHCGHCFHBGHGDABDAFGBEGFDFBDEHFA,False +598,14.0,9.0,12.0,11.0,20.0,14.0,7.0,8.0,EEAFAGFHFFBEAGHBCFFFFDFFBAFCEGEEGDCGDCBAADAHFFHAGHACDECBEDBEAACDGCEACHDDADBECBECHEAHFDEEEEEEEBC,False +599,31.0,15.0,28.0,34.0,25.0,28.0,16.0,23.0,EADADBADCDDCGEGGEAFEFGBDDCFACDECFECFBCHAEHABGFCCAECDEDGCDGCDGEAHDBBDBACEAFBFEBEDBEBEEFGAAGADGDFFCEFAFAABDFHDFHDGCDGHDFCDFHEFAEGCFDAFDAFDEFHBCDAFEECHHDDHDCFFAHHHHCHADEADADBADBCGCCHFAFCEHHAFHAHHAEGACCCH,False +600,10.0,11.0,5.0,10.0,8.0,10.0,7.0,10.0,HBFHBHGFGEFGEFAAFAGFGEBBHBDGBHHAHCDHEHBEAFDDBBABDFDCFHEBCECCADGADFADAED,False +601,1.0,4.0,4.0,5.0,1.0,4.0,5.0,0.0,EGCDDCBDCFDFBGBDGCAGFBGF,True +602,4.0,2.0,2.0,6.0,6.0,0.0,2.0,3.0,EDEEBAEDHEAGEABCHDCDDADGH,True +603,22.0,28.0,15.0,26.0,22.0,27.0,16.0,24.0,EADBBCFGEFEAGAFEACAHCDBABGHBHAEDGGDCGFBBFHFCEFCEFEDAEGEHGABFHBFDBGDBABGGCGBCGBABHAFDDFBDFBGFHFCHFCHFHECHDFFDFABFDBHDFDCFDCABHABHEHADCDDCDHFEEDAEDFEBHHAFHGBHBBEEBDHDHEDABDABAEGEEHAF,False +604,21.0,11.0,14.0,19.0,11.0,12.0,18.0,29.0,GHHGHHAHADHAHCGBCGBDGBDHDFAABAEHFCDDAACAFHBHHDEBEGAGGEBGEHDEGFGGCHGDBDHHDAAAACFACFHBHEAAEHADHGCHGHDBCFHEFHEFECDDHFDCGDFGAFHAHHCHBCGDCAD,False +605,9.0,11.0,6.0,10.0,8.0,6.0,9.0,4.0,DCGDAGDABEBBEBGEBGDDGHAHHBCCECAHAFFAEDCEFFEDCBGBBGEGDFGDBAAFDAB,False +606,28.0,22.0,23.0,19.0,24.0,23.0,22.0,23.0,GHDEEDGFDEHCEBCEBAGAAGEGGEGABFHGFAGAHGDCCDHFBADBDDBCDBFHFDGEEGCEHFFHCCHAGHABEACCACDFEEFAFGEFBCGBCBFAFFBFFDGEEGBEHBHHDCACFHCACAABAABAECCDFHHFHBDAEFHEFEECGFBGCDGEHCBGDBAAAHCAHDEHDBHABAAG,False +607,13.0,16.0,14.0,14.0,17.0,12.0,10.0,10.0,BGHBGADGDDGCECBEDBECAECGECGECFACFBEEBEADEDHFAHAAHBFEBHDCFDGDBFFBEGCAFADDHCABDACDABDHGFFGEEBFEBABCEFEHCHHCB,False +608,9.0,17.0,16.0,8.0,12.0,15.0,18.0,16.0,BGGGDCHHBHGBEACEACEGCEHFHCBGBBGFBGFAHCDGCFFCFGCBGBBGBFGBFAHFBGFBABCEGCEADHHEHHCHFEGEDHDDCDABGHECCFCFFGBADEAEHFH,False +609,34.0,28.0,25.0,20.0,27.0,20.0,18.0,15.0,FHGFEGEBBEGBEGHFHDFDAAEAAEDCFDBFEFCDCDDGEAFEADBCCACCDFHHBCHFEDABBABBABHAFGACGEEEACCACDDCBFCDHBFGBAGCGFADEADGABFABAGEEEBHBFDBFEBGEBEBHCCDCAGCAECAECAFCHGEEBFEAGEDECAHHABABBABDFDAHCABCAGHAGA,False +610,27.0,20.0,29.0,19.0,16.0,20.0,23.0,16.0,EDGGDCDCCDCCFAHFACFEEAAGGAHFADGADAEDCEACDAGDAHDCHFAFFHCGHCGDEBAEBAFHADHCBFBBDAECAECACGGGGFFCDGBHGECFBABDABGECGEFBFCBHDBHAHGACBAHEACCACHBHEFCBDCGDBGCBGHGCBFCADEFBFFGABGCEF,False +611,22.0,21.0,24.0,24.0,11.0,17.0,21.0,18.0,CGCHDBGDBABGACGAEAACCDDCDGCDGFDEHBABFCHACHAFGDEBDEBDABHGBCFBCBAHBDFBHFCFECFECGAGEAEBDGCGGCHGDFGDFCFBHFAFGAGHHFBHDAADCAHCAGEABCCBDDEDDHCCAAHFHHDADDBGHCGBFFBEDG,False +612,15.0,15.0,16.0,7.0,8.0,15.0,11.0,10.0,BBGABCABCFCHFCBCAGHHFHFFBFAAFAGBAGDEFFCFECACDACAFCABEEGCEGCAGDBCHBDDFDDFAFHACBGBHGBHCEEEGHCGFBHBA,False +613,1.0,6.0,10.0,13.0,4.0,6.0,8.0,9.0,GCDDCDCAHCHEDFDCCDGGDBHDCHDBHCGGFGCFGHFGFFHHCBBEEBDEDDBDH,True +614,10.0,16.0,11.0,12.0,14.0,10.0,10.0,10.0,DECEGBDAEDAEGGGHGAAEBAEHDGHGEBCHBCHBFEBCBFCBAHEDFEDFGAFDCFBCFBDFBCHCCHDHBDBBABFDGEEEDCEGAHBAF,False +615,1.0,1.0,2.0,4.0,6.0,3.0,0.0,3.0,HDEHFEDCEABEHFEDDECF,True +616,10.0,6.0,9.0,12.0,6.0,14.0,6.0,4.0,DFHDFBBECCFCCFBCDGAFFABDAGEADBDDACECFECGAAGHFHFFHFFDGDAFDEFDEBDAAGC,True +617,6.0,1.0,4.0,3.0,5.0,2.0,0.0,4.0,BDEHDAAFACHECHECDEFHCAAEA,True +618,22.0,16.0,36.0,14.0,21.0,16.0,20.0,16.0,BBGEBEHHHHHACECCGBEDBCDHHAHDCHDCECAFHAFDAFCAECGCCACCGFFDEGACGCCGCEGCGGEGACGACBDGGDEAEBAEGFECAECFBGECAEFFHBCCBCHEFADFDECDBCBFDHDECDGAABHCFGCAGCFGABEABCABCECCFFAHH,False +619,26.0,17.0,24.0,18.0,27.0,15.0,23.0,23.0,ADFABEBGDCGDEAEHBHDBCGECBECEEGAHGCCECGFCAFCHECFACBAHBACBAEBDEHFEDDEHGHHGHHGAHGAHFADAAGEAEDAFAADADHEGHEGHGBHDBCEECGFCHEBHBBFAHDCGAEGEEGECGHCFCFGCDDFDCBCFEAAAFEAHGBGDCDBEFCHAG,False +620,7.0,2.0,1.0,9.0,6.0,2.0,5.0,5.0,GBEGBDDHGCFGDGHEEHDEFAADAAHAAEAHEDDDD,True +621,16.0,26.0,22.0,21.0,29.0,29.0,17.0,19.0,EAFBDDEEGGEGGEGDFBBFADADCGDCBCCHCDDEDFEDFADFEDFGBFHBECAHCDBCGFCFECEEHAFHAFCGFBEHGFHEEHFEBCGBGGHABFGDAGCABFDBFDFFDEFBBBDHBEECFEHEACBFBDFHAHHEHHEHCCHGBAEBDCCEEFBBFAFCBDCBFBAFEACEGHE,False +622,7.0,7.0,8.0,11.0,8.0,4.0,10.0,8.0,DAGDCGDHGDACDBCFHHEGDEDEFHCBHEBHFDHEHBCGGEGBCGDCFDGEDCAABAABEAG,False +623,28.0,16.0,21.0,17.0,19.0,16.0,21.0,15.0,DEHGEHCAACGFGGBEFBEGGGBGFADAEDADDCCHGGACAACEBDGFCBDAAFBCCCCCAEEEECHDCEDAEFAHFABFACFGHHBEGCEFBAHCDHDBCEBCEAHAAHAABEDGECGFAGFABFAHFAHEAHDHBFCBDDAFDAGBGGDGG,False +624,3.0,1.0,2.0,2.0,0.0,4.0,3.0,0.0,GAAFDAFGGFCDFCB,True +625,2.0,3.0,2.0,8.0,3.0,1.0,2.0,1.0,DHDDBDABEGDDGBFAEDCEDC,True +626,25.0,22.0,16.0,18.0,24.0,24.0,24.0,13.0,EBGFHAFDBGEBGEFGEDHADHADAAFCAFCHGEAGACBDGBFBDFEDGEHGEHGDHGCFCEFBEACEBHGFHEBHEGFEBAECFBABCACCABAEDEDGEGCABEEDGEAGAAGCFFDBCGHAGCAFFGFDAFHFFGEBBBHBDAGDABDBDGBAFEDFCAFCEF,False +627,29.0,21.0,28.0,24.0,31.0,21.0,20.0,20.0,FAHFBGFACEAEHGHHCFHGAGFFCCDDBDGBDGBDBHEBHECCEHCAFEGEHGEHGEGGBCABADDACDEEBCHCGAAEAFCABCEBDABEABCAECAEAHHFCFGDFHDFHBCECEDCDFCDACEFBEDBFDBEBEHHECCEDAFDGFDHEEHEGHCDDADAAEGAFADCGCGFEGFEABACFAEBACBGDA,False +628,12.0,14.0,20.0,9.0,14.0,5.0,7.0,10.0,BAHEECEFDEACFADDABAECEHFDHCCCACBAEDHEBHEBHFHCFCCGCDACAADGEGCCGCGBCBBCGBCEBEHBEDCADBEGBCABHH,False +629,5.0,5.0,7.0,3.0,4.0,2.0,2.0,2.0,EFAECAECHGHFCDABDBCDBCBCABCGEA,True +630,23.0,22.0,17.0,29.0,22.0,31.0,12.0,12.0,CCDECDBBHBBHBGFACDAEHBFBGFCCEHGEHEECEFDDFDDBEDBAFEHBDHBFFFFFFFAFFAFHDFAEFACFCCGAFAAFGADGADFFEBHEGEAAFBDGBDADDAGEACECCFBBEEGGEBDBBCAADFEDCADFFDFAEFBHDDDDBCCBFGDAEHEHDDAD,False +631,27.0,22.0,17.0,34.0,24.0,29.0,22.0,24.0,FFDCFDCHHBFADFAGECGECGBFBAFBGGACBFCBACHEFEEFBEFEEFCBAEECEHAEGAEFACFADFDBFBHHDHAFHADDGHHEHDDGEBEEGFFDDGEDGADGBDHFDHFBHFHAABAADHAEHBHGDFGEAADDFDCCDCDDFBAGCFDCGDHBDHEAFDGBEGBADEFGCDBADGADHEHGFHBDHADGACB,False +632,14.0,22.0,9.0,14.0,13.0,13.0,20.0,23.0,BCFBCFAHGDHGAHEDGEBBCBHEGHDDDBAGBAGCECBBGBDABAGHDGHEFFBHEEEEHDEBDEFAAFAHGDGCDAFHAHGADGAGCDDHHFHGFHEBHBGHBFBBFGBFHHFAHCHHBECBGBGG,False +633,24.0,22.0,20.0,25.0,23.0,16.0,19.0,23.0,DBBDHHDHHEFEEFGABGFEGADFACHGEHGEHAFFAHECCEACEBBHBEFADDDDGGHGGHAABCFDCFBGFAECDGBDABEAFECFEHBAHFDBFDBDEFCBCCGDEACAAGBBGBDEAEAAGAAHBGHACCAECGCCDCGDEHAHGBDDEDDHDBHDHHFCHDBHEBCE,False +634,17.0,21.0,22.0,24.0,23.0,23.0,16.0,18.0,CBHDBHCEHCHBGDBECHEHFBCFDFBDFCGFCACCACCGDEAFGADEADFCDFBAHAGHGEBDDBDEBDHBGBDAEDBEDCEFCEFHBHCGDAHAAEDEEGGECBEHDGDBGEHFEFGEFBFFAFFCCFECEDHEGCAGBACFDGFDHFBABHADFBEFHADC,False +635,16.0,6.0,8.0,5.0,5.0,8.0,8.0,4.0,FFABFACAAFAAHAFHCEACEABFCDGCFACABGGDGCABAEBGEAGBAGHACHFEDDDG,False +636,0.0,0.0,0.0,2.0,3.0,1.0,3.0,2.0,EHGEHDEDGFG,True +637,9.0,16.0,10.0,10.0,13.0,11.0,8.0,12.0,FEDBEDBEBBEFBEHBFBFCBEGBAGBHGHDBDDEGBECEFHDDHCFHGBHEBCGBEFAACBDEFCGFAAHAHHFFAADAHDCHGCECC,False +638,12.0,9.0,9.0,12.0,9.0,15.0,8.0,15.0,EFGFDCDAGDHFCBFEAFHACHBGADEEHEFGEDHFDGDDGAECCFHBFHBCACHACHACFAFBGDBGDBHBHHBHDEHDAAAEFFFHF,False +639,14.0,20.0,11.0,14.0,9.0,16.0,14.0,14.0,BFBHEBAEDADCGDAGDAFBHCBACBAEAHHCGBCGFCGAABFCBFGADBFFFDFCDFEAGGDHDDEFFHGHHGHHEFEBHBBGDBCHBEHBEFBCABDGGDCGAFHBFABD,False +640,8.0,6.0,17.0,2.0,13.0,12.0,17.0,7.0,HCFFGFCHCCACAADFGBFCFFCGFCABGBEABGCEGCEGCACCFGDGECGHCAEGBEGEEGHBGEAFEHFEHGHGEECCGF,True +641,14.0,17.0,15.0,14.0,30.0,13.0,21.0,15.0,BBGEDAHDBBEHBCBEHAEGAFGECGACGADAFGFFGFEGDBCCBFCHDHABHEBGEDADDHEGHBBHEGCGCHEEHEEHGEHACACCEGCGGEDGFGAFDBFCAFBAFEEEHGEGFEBEEBHEFDECEEDEBGEDCAD,False +642,26.0,25.0,28.0,26.0,13.0,16.0,19.0,13.0,EBDECDGCAACBAHFACDCCBCDDHDFBDBDAHGAHGBHGBCFDEADGADGHFGBAHBCCDHBDFDFHAEEFDCGGCFCAFGACGCCFADBAEBGBGGBFGDFBFCAACAACECBBHBBGABGFCAHCDFGDCCEBCDACHBCAAEDEEDFEHEDABDACDAGDBB,False +643,14.0,19.0,17.0,9.0,14.0,22.0,18.0,8.0,GCCFBFFBEABEHDEBDGBDFAHFBHCBDEBDGBDHHFFGAFGCGHCACFBGGAGGFEGFCAFCADGGCFECECGFAGFAGACHAFHDCBBCBFABFEBCCBGFEAECDBBFFBAEEEEFG,False +644,15.0,27.0,16.0,22.0,21.0,27.0,27.0,18.0,EDFEFFDFBDGBEGBHCFHCFHFAHFGFFEHGEBGEBGABGCGEBGFFHADEDGEBFABGAEFEGFGGAGFDHFBHCBADAEFBCFCCHDFBEADEDBBBGDBDCACCFCEFDDFBHHAGHGGBGBEGCFCBFEGDAGDEHCEHEBHEBADHDHHDGCDGBAFBDCGAFGDBB,False +645,14.0,11.0,10.0,13.0,16.0,12.0,10.0,15.0,EEHEEHGEFGEDEDBGCBHHFHBFDBEEBEBAHBDGACGADGHEHHECDFHDFDFAEFACFBEBHEHAGDCHDCDGCFAAFAAGCDGCAAAHHFBCDBAFE,False +646,3.0,5.0,2.0,4.0,7.0,6.0,2.0,5.0,EEDEFDFHDFHGFHCBHFBEEEABHABFDBGCEA,True +647,17.0,19.0,20.0,19.0,12.0,18.0,17.0,19.0,HCFBAFBDFDHBCACEAFHCGGCAHBHHBHFECADGBGCDACAECGDCFDFEHBABGADGACGBEFHGFBDBCCBCFBDFADFGGFEGFHGFEBDDBDDADBFGCFGHECHCHHGGBECECCEBDEDHADHADHAFHAHAB,False +648,10.0,10.0,6.0,7.0,5.0,10.0,7.0,10.0,CHGDHGHAECAEAGBCGCEDFBGFCGBCFBHAEAFHDFBEHBGFAFFDDABDABDFBHFHHABHA,False +649,23.0,19.0,18.0,23.0,11.0,22.0,22.0,16.0,DFGDAGAEGAEDABBFDGADBHHAEGECAFDAEDACGBCGDCGHCGBCHEGACCAFDBFHBGGGDBGBFCBEGFHAHHCEDAEDBBAFAFFAFGAHCHCCDCCGBDEFHFFDBFBCFDCDDAAAGDEBDBBHBFHGFHFFHFAHGDGGDACDAF,False +650,4.0,5.0,4.0,4.0,6.0,3.0,2.0,5.0,DDHGDFGEFAECAFCDBCHEEAEEHHBACBHBB,False +651,29.0,15.0,14.0,25.0,15.0,16.0,23.0,19.0,GAFBABHAGGACGAGGAGHABDGFCGDEGEFDFACFBDAHAAHCGECDHFEHCDDEDDECGFDDFEDADAFDBFDBEGHFBAGBADBCDGAFFCEDEHAAHAACGAGDFDDFDAADCAFHBEHGEHGCGEBBHHBCDBCDHEBAEGGHGHHAAHAA,False +652,17.0,19.0,21.0,19.0,20.0,33.0,24.0,19.0,EBHGBHEFHAFCFFEAFEADEBHCBFCEFDEFHBGHGFDGDAHEGFEABBBBFBBFBBFAFEBDHBCBCGFEHACDCFDBGHGEFGACCFFFFDADGFDCFGEGHHGEHFFHEFHCFAGFBGCCGDCDDCGECGHAHEAGEDBCDEHDGHFGFCCDAAFAAFGAFDCGECGD,False +653,4.0,2.0,1.0,5.0,5.0,3.0,4.0,8.0,GBFEDEDGEDEADHGHHGHHDBHAHEFHCFAA,True +654,20.0,23.0,22.0,29.0,18.0,18.0,13.0,18.0,EDEBAEGHHFAHFBDDBGFBGDDABDABDADCCBBCEHGFCGFCDEHDFDGHDCBDHFDCBHBFHECCADGHGGEGBCBACHAEGEEFDEHDCHBEHFDBFCEACFAEDAFBGDBDDBDDBFDCFDCHDAACAABACGFCACDHHAFBAFBHEDCEBEEAC,False +655,7.0,8.0,11.0,11.0,11.0,5.0,11.0,11.0,CHBCHDCHBAHBCGDEGDACDEBAAAFBEFHFBGFEDEEAEEGDGGDGHDAHDHBEEGDECCBHCGCCGHCFHDG,False +656,23.0,22.0,23.0,10.0,19.0,19.0,24.0,14.0,FCGFCGAAEBHECHECHCGABAAFFEHBAHBCBBDEBEFDFADFGDFACFAFAHFBCEACECCDGBFEBFCCCCEGAAHAGEBGABCFBAAGFDFCEABEABECDGCGAHGHCCHBAFBHEEHCGBFGBAHBGGEGGEDBEDBDFGGGGGGACH,False +657,17.0,18.0,13.0,17.0,9.0,17.0,17.0,24.0,BDHBDGBFEBCHBDFBDHBAHBHHAAGABHACFFHHBBDDHHDHGFCFFCGHHBAHADGFDCFHCHCCBDFFGAFGAEEAGEHHBGFFGFAGHADHDCBDEFDECGAGADCAGCHGEHBEHFDABDGBCGAE,False +658,8.0,8.0,5.0,2.0,2.0,4.0,5.0,8.0,CEGBBGBHCFHBHBBABGEBHHGCFAAHADHAHGACFACFAD,True +659,34.0,21.0,21.0,17.0,21.0,20.0,30.0,25.0,HAFHDCDEGEEGAAGBGCBEAGEBGEAHCAHEAHCAHAAHFBHECECABCAHGGFGHHGEHDADFACFACFCGFCGFBBFAAHAAHBFFDAFDGFCAEAGFAEDBGBCEEFFFDEAGGADGCDFHGGHBCABCABCABHDGDGGEGGEGHEAHBDGBHHBCHDFAECGDBHAGHADABBACEFHBDEGC,False +660,14.0,30.0,12.0,19.0,8.0,11.0,20.0,13.0,DEBHHDCGGHGCHBFBFGBFDDFDDGDGBDBBABHDBHACECCACEABBAEBDBBGGGCGDAHCADCABHEFHBFDCDCGGFBGDBDBBGGBCGBEBBEBBHHBHFFHFAADGBBGBGADDFEAAGA,False +661,11.0,26.0,15.0,26.0,16.0,14.0,18.0,26.0,FEBHBBCBDCEDFABGAGEABBHBGCDGFDEBBEBBDBEGBEDDHHDHFBHEBEEGAHHDHHCBHCAHDHCAACEGBEGBDGBHBHDFHDHDFHECHCHEAHBGCFCFHDDHDDFDDAGEGGCCGDFGFAGFGDBBBHBDHFDACDCHFGDE,False +662,5.0,2.0,4.0,1.0,4.0,3.0,0.0,4.0,HCDFCFHCACAEEAEFBHABHAE,True +663,14.0,22.0,18.0,13.0,14.0,22.0,18.0,29.0,DHBHHBGHGDDFFFCBHCBFCHGCGGHHHHABCCBAFAEGBBDBFCFECFADFHBCHADBADGHDGCDACFHBFGFFBFGCFAAEACHAFHEEEEHGEHAEBGBGGBFCBFBGGBGAHDHHBECEHCHBFECFHAFHDCHDEHDEHGFHB,False +664,22.0,13.0,19.0,20.0,21.0,19.0,24.0,26.0,AACFEGGECAHDGHDGDBEHBGDGGCBEAGEFEAGBGGBFFBGGGGDCEEAAFFAHEBFEFACFECEABEFHGFHDAHCBHCFGDFHDAHGEHEAHEAGCCCHDAHFCEFCDCAFCGCHFCHGCHGCBGFBGHHDAHEAHDHHDHEEADEFDHADADDHDBADB,False +665,19.0,16.0,20.0,18.0,23.0,17.0,22.0,24.0,DAACFCEFCEHBFHAEHDBHBHABHABHAHCCGGCGCEDBDHBACCCCCAEDHEACEHEDGECGEFGCGDEFHCAHADFDEEDBECEACDGEDGFHFAEFAGBHHAHHDHAGBBFCGFEGHBHFDEFDHFHHABGABGEDGEDGEGGBCEBGDFGFFGA,False +666,21.0,15.0,10.0,14.0,9.0,13.0,18.0,9.0,ACFGBACCACCADCDGADGADGHBABGDFEDEGAGFADADDBEABDABEABAFBAFBGFGGACGBFEBFEHFHGACGCFEDGBGABCEHFGBAGFEDADBAFHHGHHDH,False +667,8.0,7.0,10.0,12.0,11.0,15.0,18.0,9.0,FAGEGGDGEAGDFCFFHBFDBGDFGBAGHCGFCDBCGBDFHGFHEACECCECAEFGCFGHFEDGHGBHFCHAEDAEDGDFGFGEBEDHAD,False +668,10.0,9.0,8.0,13.0,5.0,7.0,10.0,7.0,GFDGECCECCFHAGBGDBDFADGEDAADAADAADCGBGHBHBDHFGHFAHFACDEHBEBDDCGGCDFBB,False +669,7.0,12.0,7.0,12.0,9.0,2.0,15.0,14.0,HBGHAGHEGBCADABEEHFCCGHGGEGGCDGCHGEDGDBADBHDBGEAGAACEDDFBHBBHBDHBDHGCHGHDEEBHD,True +670,0.0,5.0,2.0,3.0,7.0,4.0,3.0,4.0,FGCFHFEDBHBBHFBGEBEEDEEGEHCD,True +671,5.0,12.0,12.0,3.0,8.0,4.0,5.0,4.0,BBCBBAECHCGHCHFCFCCBDBECBEBFEBCGHCEFGGBAGEAEEACCBDABD,True +672,11.0,18.0,12.0,10.0,18.0,18.0,25.0,17.0,AGBBGFGCFCEFCBHCADEBHCHDEBGGGGGAGGCGFHFBHDBFFAFHAEHFEFFAGBEDHHHHBBCFHAFCGCCBEHBEHGDBFEAGEHGEAGEAGEGDBGDCGDGGDFHEFEBBCBAGBEDHEFGEF,False +673,9.0,13.0,14.0,18.0,14.0,11.0,8.0,15.0,CGDBHCCHGBFGAFEEHEHCEHCACCADCDDCGBCDBHDHCBHEHABHEEGDFHDGACBAGDFEDFEDECDBDHFEHBEFFEBCEBDABAAGFHFDDFDDHB,False +674,8.0,13.0,7.0,9.0,11.0,13.0,8.0,11.0,GHHFHFCGFBEFDEDDBFDBAHFHHFCHEDGEHGCBDBHHAEGAEAAEBAGBAEFCFGCFAHBGEFECBCBBDBBDEFDF,False +675,1.0,9.0,5.0,1.0,4.0,4.0,4.0,4.0,BECBCFDGHHBEBBFBBFBCFBHGAHGCEECG,True +676,7.0,7.0,1.0,4.0,6.0,8.0,6.0,3.0,ECHEDFEAHHDFABGEBEABEDGFAGBAFBAFGFGGFABFDB,False +677,14.0,18.0,19.0,11.0,14.0,16.0,16.0,25.0,EEHFECBGCECHDBHGHHGHHGABBDFBDFBAFHAGDABCABFHHABGAEGDBHHGHFFHDFEDFHFGACBCCGCAAFFAHACDGCDBCHBFGBHEFHAFCCEBBDHCHFAHEGHEGCEHCECCHGEGBECBD,False +678,9.0,12.0,6.0,10.0,11.0,11.0,13.0,11.0,CDEAGGDGGCGBCGBAGBGEBDCAFGHFGBFEHEEACFAGFDEFGBHHFHHEHFCGDADHHDHEDAADFBFBBFBEEHEABBD,False +679,27.0,20.0,25.0,20.0,31.0,18.0,23.0,23.0,EFHEDHDDBECBDAFEEFEEAADGGCGEBGADEECEEFEECAFCGEGGBFCBFABGACDAEHBHCFGCHGCHGCFDCBHHBEABAHBABAHEAHGADGCCFECDHDFAGECHAFBADBGDBCABHADDBHCEHCEHBFHGFEEDCDHCEECGCDBCAHGHBGEAGEAFFAFGAEEAFAHGEHGDACD,False +680,27.0,26.0,27.0,28.0,20.0,19.0,14.0,25.0,GDCFDCFHCBAEGAFACFAGFDBEABDBCAHCGFFFCFBBBADBGFCDACDGDDHCEHAEHBFGBHECDEGAACBHCHEAHEFCGACDBHDACGACHAHHAHDEHFCBBABBABCHBFDCGBCHBCHFDHEEBDEHEEHGEFABHAHCAEDBCDBCDEEDCBDBHAFAGEADDADFADFDDHGDEC,False +681,3.0,1.0,1.0,3.0,4.0,8.0,7.0,1.0,HGFEDDABGFGGFGFFGCGAFDAFEEFE,True +682,15.0,12.0,11.0,14.0,15.0,27.0,23.0,14.0,FHFFHFCHGEDCEDGABGDBGFFGFHGDDFFDGCHECAEGEBCEFCEAAAAGACFAGGGBEGBFBAFBAGGAEHAEHBDGGDFDAHGGEGGHAFHGCEFDBFEHDDBGFBCFAFFEHFCHFHDFCFFDEFB,False +683,3.0,2.0,5.0,6.0,4.0,4.0,5.0,2.0,GGFDFADFADECDCGBCGEDHEDHGCBCAEF,False +684,13.0,18.0,21.0,19.0,20.0,13.0,21.0,11.0,FEEGGCAGBEGFECBEGBDHBDCCGACGFBFEHHEHBCHCCFDCDDCEACEAFHHFCFDEBBGBDCBDBADEDEGCFDHABEDGEGFDCFECDEAHEDGEAGFAEAAGHADABDBGCGGBGFBDCBDGBCGECGHC,False +685,10.0,7.0,12.0,11.0,9.0,18.0,8.0,9.0,HDHAGFAFFAFFAEBDCBDBEAFEACEACDGDDGFCHFCBCCACHGCFFCGDEFDFHEFHDCBEHGEGFFDFAAFBEFCDGHBH,False +686,6.0,12.0,8.0,11.0,9.0,7.0,20.0,10.0,BCEBCDBHAGDAGDHGDEDAGDGHBEHDDFGDGEDAEGGGCEBCBGGGCHECBFHHGGFGGFGGHGAHFBBCBECBHABFDEF,False +687,12.0,20.0,16.0,25.0,15.0,20.0,20.0,33.0,DFDHAGHAEHBHBFCFFDHFDBGGCCBDABHGGHBBCBFCHCEEADDACDFCAFBHBHDBHFBADGHDGHDGFEEBHHGGHGHFGDFCDHEEHCECCHDBDAGDABDCBFHAGEAHEHHEHFDHFDHFDEFDCCGBCHEDHBDGEHGBBGFDHAHHFEFGG,False +688,3.0,9.0,2.0,3.0,7.0,7.0,3.0,4.0,CFEHFBFBBEDBCHAFABFEBEEBDEHFEDFHBGGBGA,True +689,15.0,26.0,20.0,34.0,29.0,23.0,27.0,17.0,GAAGDABHABEGDEBDFFDHFEHFBFCBGCBCCDGFDEHDCFDBHEBEFBEBCGCDGADBDGGGAAFCEDCEDBHGBDDBEDFFGFEHBEFFCAHCHHGFDDBCDBDFEHFGAFHFFDBEABEFBGFAGHGGEECCGABDDBEEBECBEAGCHGDHGDEDHFDHDAECAECDEDGEDEBCEDDGGDEGBCG,False +690,2.0,5.0,5.0,7.0,3.0,8.0,3.0,2.0,GFGFFGFDHHAEBCCBCDFCDEADFDBFDCEDBBF,True +691,11.0,14.0,14.0,3.0,13.0,5.0,13.0,10.0,ABGFGEEGEEGEHAHBCHBDDGHBBABACBCEEGECGECGHCABCABCHBEGAEFCCGBFGCAEFGECBFHACHACHDHBGBA,False +692,17.0,27.0,23.0,13.0,20.0,16.0,15.0,12.0,BCCBCGFCGFADAABEDHEHBEADCFFEFFCABCGBABBEGBADBABBFCACGEDBEBBGFBGHBGHDEHBEHBCHACHFGEECHGFHGCCGECGDBBDGAEADFCGECDEFEFCCFAHFEHEABAFCCECEBDDBADBABBC,False +693,27.0,22.0,19.0,22.0,14.0,28.0,28.0,25.0,FCDFEDBEDFECFBHAAHEACBFDEGDCGFFHHFADGABFAFAAGGBHFECAECAGCGBDGBDHBHCBHFEHBBAFAAFAFFCHFGGFHAADCCGCCGBHGDDGFDGBDGBABHAGFDBFGBHAEFFDGFDGCAACAGGHDGAGCDEHDHBGHEFCEFADHEHABHAFHEHHDBGGBFCBGCHAD,False +694,18.0,13.0,19.0,10.0,11.0,15.0,13.0,6.0,GDGHAABAGDGHFBFGBCGACGAEAFDAFDECHECACBFCBACBEBDGBFACEEBEDCEACEBBDDBGFAFFDCFECDHCACCGBFGHGCEGCAAHAAFCAFCFF,False +695,10.0,11.0,11.0,10.0,20.0,12.0,15.0,5.0,DBDBFDEGDBGEEGEGFAAEGDFCFECEEAEEBHGGHCGHCFACGHEGEEGAEFCEFBAFBAEEACCGFDBFCHACEDFADFGBGCBDEBEGBD,False +696,11.0,15.0,9.0,15.0,19.0,14.0,16.0,14.0,BBEABEBFEDFHBEDCFCEDEFDECCEFGFGBHGBCGHGFHEBDGBFGCFGDGDACDAFBFHBHGECGEHDEHBBFDEEDGEFCAAHEABEHHEAHEAHDAHDGGDBGFAGAD,False +697,4.0,10.0,3.0,4.0,4.0,9.0,13.0,9.0,EFFBHHHHHCADDEGDFGBBGHFGBBBBHBACEHCFBEGDGGFGGFGAFGAGHFGB,True +698,8.0,6.0,6.0,10.0,3.0,3.0,10.0,9.0,CHGBHGEHGAAGHDGDAGDBDHADHBDHDAFACBCFBGEHCEFCGABGAGDCDDH,True +699,23.0,20.0,26.0,25.0,24.0,29.0,20.0,24.0,CDBFFGEGEACCACDGBDCHACHACHBGDBCFBHFHHFHHAGHAGHCHAEEGCEHEEFFCDFDDFDFAAEEFEEFBEDAEDFGDFGDHHDBCBBCEBEABADDAEDGGGCEHAGBEFBCFDHFBEFADFDCEHFEHFHADCFDAFHAFBFCEDDBCAHAACGCBFCDHBFHDAGFEGFGGCCGCBBCAHGE,False +700,29.0,20.0,21.0,24.0,24.0,23.0,13.0,26.0,EBHEBHBADGAHAAEEACGAFAAFBBFCHDBHAGCDEBDCDDAHHBCEAAFHAFCABDDEDEEDFHDFCDFBEGCFGEFAFGCHGDHFFEFHEDDEADBACACEFCBHCEHCAAEAECAEBFDAFHAHGAHGBGCBDHBDABDHBDHADFGEBABHFCFFAHFDECHHCHHCFCGDEGEE,False +701,3.0,7.0,7.0,3.0,6.0,6.0,4.0,11.0,CEFCFHGFHBHEAHECHEBBAHAEECHCDHCFFCHBGFBDDBGHBGH,False +702,9.0,6.0,16.0,15.0,12.0,8.0,10.0,9.0,FDCFDCDAHDGHFAACBCHDEHEGDEDDFDDEGCGCDBCDEAFCBCCBCGACGACHHEEHADDAEDCECFECFAGGBBEHFGHEG,False +703,6.0,1.0,3.0,5.0,2.0,9.0,6.0,6.0,DABEAHCFGGFAGFHHFCFFHDFHDCGFFGDEGDHAAA,True +704,4.0,1.0,0.0,2.0,2.0,1.0,3.0,0.0,BGGAAGEADEFDA,True +705,18.0,19.0,12.0,21.0,25.0,19.0,18.0,24.0,FDAHBFHDCHACHAEAEEBDDDDDGFHHFEHDDBDAAAFHAGGAGDABCHGCEGCFDBGCBEFHFDHFHHEGCFABHEBHCAHBBHEAEEAEGAEDEBGFCDHEEHGEFGEFBDFEGFGHFDHFBHDBGDACBAFBDFEHEECBEGBDGAEGEHBC,False +706,17.0,12.0,10.0,18.0,25.0,13.0,22.0,21.0,AGEHCDCDAEDAEBAGGHGGHDCHEHEFCEABEGBEBHAGABHABFFGGFGAFGDBGAEDAGFAHEEBFFAEFBEHCEFDEFEHDCHDCHDGAEGAHHFHEBEEGABGDHGDHBDHDHGCEDCHFCEEDDEHDGAGGE,False +707,18.0,24.0,22.0,26.0,29.0,18.0,27.0,19.0,HFHHGDEGFHCDHCEGFEGBDCEDEEFFBFCAEBBGABHADAAGABFDCGCBHABAGHDEDEEHBAHDAGDBGCBDHHDBEEGCFGCHCFHBFDEGDHDFHAEDAGDFGEFCEGGEBGCCCCECGECGCHACEGCEFCDFBDFBGBEABECBEBBGAHGDHDDAABGGBEGAEBEDFDDFEDE,False +708,20.0,10.0,10.0,16.0,13.0,13.0,19.0,23.0,FFHDFHCCACGGGHEEHDGGAGEAGHAEBAHDGHGGHBGAGFCBDCDDADDCEHADDDHBAHBAHBGGAFAAGAGGBGFHAHHDHGEHEFHCFHCBACEDBDDFCEFAHFAHEAEFHFABEDHE,False +709,5.0,8.0,2.0,9.0,7.0,8.0,16.0,8.0,CGDAGDFHDGABHDEFFBFFBEDGGAGGCEGHHGADEFDEDHEDGFBGHGGHGGBGBBAHEFB,False +710,2.0,0.0,1.0,2.0,0.0,3.0,1.0,3.0,FGHDDHAFHAFC,True +711,11.0,11.0,7.0,14.0,11.0,15.0,19.0,23.0,DHDDADGHBGFBGHHGDGAHHHGHHGBCEDCHDHDECGGFDDAGBHGBGDAHBFFBFFCHFCFFHBFHEHHGAFGAHGHDCDDAGEHGEHBFHEGBAGFAEFCEABEAEEF,False +712,22.0,16.0,19.0,9.0,22.0,12.0,19.0,16.0,HDGBAGAAGFEEFADBADHGCGCDBCABEACGHGEABEAFGHFEHFGHFGHCGEFGEFHHACDAHFCGECEABEAEEBBABHEFEAGEDGBCEHDEADCBDABCHCCHBCGAGHACEACHFCEEBAEBAGBGFCC,False +713,10.0,16.0,20.0,25.0,19.0,11.0,23.0,14.0,FDCDDBFDGCEFFEBBEBBFDBHCFAAHGDHDBFFGFDACDAEDGEGGDCADCDDGEDGEGCEGDADCGDCBBHEBDECEHCEHGBHACEGGDCGHHGHDGCGGCGCDHHDECCEBEEDABBAGBGEAGEFDHFBHCC,False +714,7.0,8.0,11.0,9.0,14.0,8.0,8.0,14.0,AADAFBHGCCGCDHHFHBCHDCHDEHEEBFBAFHDGHDHHEAFEFCEGDHBEHCCFCHBBEDEEAFEAECGECGEGDBG,False +715,4.0,5.0,2.0,4.0,4.0,2.0,5.0,7.0,BEEHHBHHCDHCGEBGDBDHEFHFAAGAAGBDG,False +716,2.0,4.0,4.0,2.0,5.0,4.0,1.0,3.0,GBACBHFFEFFDHBDHEAEECECCB,True +717,15.0,12.0,19.0,9.0,14.0,21.0,18.0,23.0,DBHAHHEFBFAGHAGHAEHFEAAGCGHBFHBAHDCHCCDAGGHGFDAFEEEGECHCCEBGDAGCAGHGFACDHBDGBAFCFFCDFCFFCEGCBGFBCHBHAGHFHCBHAFHCFGCEGCEHFEBEEFFHDFH,False +718,21.0,29.0,17.0,17.0,19.0,12.0,14.0,21.0,BHBBDDFDBFDBDHADHBCABAHFADGBECCFDBADGEHHBBEGHEDHCHEBHBHHBEEBCABFBBFBFDAFABDGCEGCEGBEACEBBBBCDCHGEDEEGGHGAFGABGABAAHAHHAHGAHGEHCDCFDCFEEDEBHCCCACAAFABE,False +719,15.0,18.0,17.0,14.0,22.0,18.0,20.0,22.0,GGECFCHFHBEHBEDBEFBEHBDHBGAGFAHFAFECFDFHGFBGDEHECDGCAEFHEFBDGHDGDBGBBGBHGCCGCCGCHHEBBBBEEAHHBFEACADDACGCFEHFEHFAGAHGEHFAAFCHDCEGCEFDEGBHGDHEECAADA,False +720,4.0,4.0,3.0,2.0,1.0,3.0,4.0,4.0,BFBBFHBCHAHDAGEAFCADCGGGH,False +721,22.0,14.0,33.0,22.0,22.0,16.0,25.0,18.0,EGACBDEEDAADHAHBABBAEGAEGBHCBADGFBCFBAACFEEFEDHBDCGECHHHAGEAFECFEGFGAFGHCGAFGEFECFGCABEEGGDAGDCCHCCHGDEGBEDBACAHDACCCBHCAHCHDGHAECDDCDHCFCDAHHCECGECGDCGFGECCCFCCDDGDDGDFGBF,False +722,15.0,12.0,9.0,7.0,14.0,11.0,9.0,13.0,HFDHFEHEGDBCFBCAAHFAEFGGDBADEAFEAHEAHFBGFHEAGEDGBBABHGEHGECCABCEHDBADCFEEFAHFGHEAHACCABCBB,False +723,25.0,27.0,19.0,19.0,29.0,24.0,29.0,27.0,CHBDGEDBEGCHBAGECBACBGCEACAGCAGEFHHHGHAGAEDHGCGBBACHDGDAGDAGBFFBGFBDFEAFBABACDEFFEAHHAEHGHHBFABFACHHHEBGBBEABEAHEDGEDBFDCHDBGGEHHEGHFCHFHAFDAFEGGHGECDFGGBGCFEAGECBECBECFEAFEBFEHFEHBDDAEDADDFCBFEBFGHG,False +724,7.0,6.0,4.0,4.0,2.0,2.0,7.0,4.0,BACDABGAGDBGHFGHFCHAEGADGBEGBAADCBHC,False +725,13.0,14.0,14.0,9.0,9.0,11.0,7.0,5.0,ADEDDFDEGBCACCABCADGAFGFGAEGAGBAFCFFHBBHCBDBFEGAEDBDFHCEECEAFBAFHCFCCDBCABCABHBBEC,False +726,6.0,1.0,2.0,1.0,0.0,2.0,3.0,0.0,ADAAGACFACFBGGA,True +727,22.0,23.0,26.0,27.0,23.0,28.0,17.0,22.0,ECCBCCADCDDGGAHBAHFHCGHEGHCAHGHHGBEFCAFBAFHDFAFCCBACDGCBGHGEAGCDECFEBEEDFDFBHGBAGBADFEDAHDACDGEFEEHGEHFAHFAEBDBBEBFEDAEDHDDCFDGDABEGDFHBCBFDFFACFAFHEFHABDCCEABEFFHCFBFFBFCBDCBDCEDGDAHDCHCE,False +728,0.0,0.0,3.0,1.0,3.0,4.0,2.0,2.0,CEHCFCGFHDFEGFE,True +729,17.0,19.0,22.0,26.0,19.0,16.0,18.0,23.0,GFHGAGFACDAEAGFDCBCCBCBBGBDGEGCEHDDADHEDBADHDEFBEDBDGBCGAHHAEAAEBDGDGGDGABBECDEFDEFHCAHBDHBHGGDFFEFDCCDACBAHEABCHEEFCEFHGFHDEBGEBHHHHCFHEAHBAHCDDDDCGFCHFCHCCFCD,False +730,10.0,12.0,10.0,12.0,5.0,3.0,7.0,9.0,GGBHAHCBEBDABDCEDEGDCGDAFAHGAHDADDACHACGECADHABCCGCBBCBBHHBFDEHDBDFB,False +731,8.0,9.0,15.0,9.0,17.0,19.0,15.0,6.0,BHGBCGBCDBCFBCBACFAFEGFECFEGFGCEGCGADEFECHEDEEFFEFFGFFGDFCEGCACBAFADCGEEGDBADFAHHDGHGFEEDCEHFFBGEC,True +732,15.0,25.0,16.0,23.0,8.0,23.0,16.0,19.0,CCGCCHDFHDFABAHDHGDBFDHDDBBDHBGHGFDDFGGHEHABDFCHFAFCACBBDDBDFBDABHABGBEDBEDAFCFBCFGEBBHCBABGABGHBGHFGCFGCFGEBEFADCHFHFFCDDCHAEHBDGADAADGFCFFBFEBH,False +733,26.0,12.0,25.0,16.0,6.0,12.0,11.0,16.0,DDEFFEHBCBCAGCHGBHAAHCAHAHHBHHGGHCFDCADCADABFCCGAFDAGHCCCACFADFADAHBGBCFFDBCHAFAAEDEBAHBAEFAFBADBDDADCCCCCCCACCGCDGADGAEAHGH,True +734,24.0,26.0,16.0,18.0,21.0,14.0,24.0,22.0,HGDGADCHDBBAEBDEBDEBEEDECFBCAGCBCHGDBGEBDEBEEBDGBGHHFCDDHGDAGHADEBDAAHBGBAHAEEGEBGEBAACFHCFACFHFAHFAHFDHCBEAHEHBCHAHAEDGFBGDBGFBHBEGDGGACEACACBACFAGGEGBFBHAGHAGCFGHF,False +735,22.0,22.0,29.0,19.0,27.0,26.0,31.0,18.0,FACFCCFCAHCGBBDADAGDFEEFAEFAHADEGDACBFCBFBHGCGGCFFBGFGFBBHHBCAADGCDECGGCGGCAGCEGEGGDDGAGHAGHFCFCEGDGCFFBDEBDFBFEEEHEHBEAEEAEEAGEFDEGDBBEHGAGFDGEDHBCHGAAAAABCECCECCHCCDFHBFCEGEDGFBFCBFHBFHDHHCGEB,False +736,3.0,2.0,3.0,3.0,1.0,1.0,2.0,0.0,DCBDCBGCAGADEAF,True +737,25.0,20.0,13.0,20.0,9.0,15.0,15.0,17.0,BBCBGDDHBCECEDCBDHGDAGDAEAACDBCDAAHFAEFDCFAFBAGAGBABHABDABFAFFDDHHHHBFHDFGGHDCFGGHHGAAEAABCAGCBGCEGABCADEBBEFBDFHGFHDFHCFHAADEBDGADABH,False +738,15.0,21.0,15.0,20.0,23.0,14.0,16.0,14.0,HBDCBCCDFDDBDABDABDFDHHBEGEFGEFGECGECGECABBEGFEGFGFBABDGBHGBHCAEBBEBEDDDBHDAFCACCEBHGGDEDAEACFBFFBGFGEEHHEHEAHADFCDCAFCDEBDCDEGEHGAHAHEABE,False +739,6.0,4.0,7.0,3.0,11.0,9.0,13.0,4.0,CEEGFEGFDGBBEFGGDEDHCCEAFEAFBAFGACCAGAFEBFEGFGCHGEHGECGHG,True +740,18.0,18.0,17.0,21.0,22.0,23.0,24.0,19.0,CHFCHDGHDGBDCFEEFEDGHDAHDAECAFGFFHFCDEGAHBDBEDHEGAEGAEFBEHAEHABBAHFGECAHBFCDFDEEDEGDACBFHDFBGFGFEEFAEFCFBCHBDFAGGAGGAGBAGBEGEGDDGCDBBDBGEFGDDGHBBECHFCHCCFAGHCFCAH,False +741,9.0,8.0,14.0,9.0,12.0,8.0,10.0,8.0,HHAGBAGCACBHFBHFDEADGBFGCDABDCEDCEFABGECCEBCDGEEEEECECCFACHAEFGGFCGFDGDACDHHBH,False +742,12.0,15.0,13.0,8.0,14.0,16.0,4.0,12.0,AFFFBFFBCEAFAAEBHDAEAHBCHFCHBDHBFHBDEBAHGFHFBEGCFHCEAFEAHABDBEDEEFECHECGECFHCFCCDCCGBDABDBBEFA,False +743,10.0,6.0,7.0,8.0,13.0,10.0,9.0,5.0,AFAAEBGEBEECEEDFCGGHDGDFCFGHFBHEHDDAADEDDECBEFBECHCGAAFFAFEAGEAGFBGC,False +744,4.0,4.0,4.0,5.0,4.0,3.0,5.0,8.0,FHDHHGAHBHDDHGDAFEACEACEGGFHBCHBCGEDB,False +745,5.0,2.0,6.0,1.0,2.0,4.0,4.0,5.0,CHHCFFGFGAAGAHGCHABEACEHCBFCD,True +746,6.0,7.0,9.0,8.0,5.0,5.0,6.0,0.0,GDGGFGCEDBEDACDCCFACFCDABDACAACBEBBCFBFEEGBDGD,False +747,23.0,21.0,27.0,20.0,27.0,21.0,28.0,26.0,DEADBCCGHHGHDBADBADBEEBFEBEBGGCAEDAHDFDGHEAHEAGEDGEFGBAGHFHECBCAEEBEGFFFHHHDHHGACGEEDCADBAFBHGBAFBDFCDCBGHFHAFCCDCGACGAFGCEGCHBBDGCHFDAFGGGBHGBHAAHCAGEDCCGCCHBCHFFHEFCEFAAGACGCEECECHEBHEGEDFEDF,False +748,3.0,5.0,1.0,5.0,3.0,2.0,3.0,3.0,DBGHEAHDADDADECFEGBGHBFBB,False +749,11.0,7.0,13.0,10.0,10.0,9.0,18.0,6.0,AGEGGFDHECGGCGBCGECBCCEFCADCGHCGEGBEBDECGGCAFHDDHGDAGDAEAEFDGADGAFCCFBAFEFDGFAGBAHBH,False +750,19.0,21.0,8.0,26.0,26.0,23.0,18.0,20.0,FEHFHBCHBCHAAHDGEABEDCECBDDAFFAFDGDHCDEGDFADCHDEDEEGHAGDFGCFGDFAEBDFBAGHAEEAEAAFAFBAFBEBBDDBDHEFHEHDEBDEFEBBAAEAEGBEDFHDHGBEGEFBHCHFBHEGGEFGEFGDFHFHGDBGDBFDBHDGA,False +751,10.0,15.0,9.0,6.0,11.0,12.0,12.0,15.0,GDEEDHHBBFGBHHBEHFHFBDCEGGEGCBCCAFCEFBECHEHEBHBAABFABFABFGFEGAEBDHCGHAGHAFCACGAHDHFDHGBBGF,False +752,16.0,16.0,21.0,19.0,22.0,24.0,24.0,17.0,HHEEFGDFCDFCDFGHFHABEGECBCGBCGBFGDFBCBAFFGCAGCAGBAGHGDHDDHGDHGEHAECADCEFFAFFDEGBAGBCEBAHFACCDCBGEHDEGAEFCEDBEHFHAEDBGAGFECFGGAGGEFHDHECHECFECFCBDCGABDBHDFEFFED,False +753,5.0,5.0,9.0,7.0,8.0,5.0,5.0,7.0,DHCDCBFEBACFGCHGCHGEDGDDEDHAGEACFACEAHEFCCFBDHBHBEE,False +754,1.0,1.0,2.0,5.0,0.0,0.0,2.0,1.0,GGBCDDCDDADH,True +755,3.0,4.0,2.0,11.0,7.0,7.0,7.0,3.0,DDGGDGFFEFFGGDECDEDFEDFBBHBGFBHDAGCADHDDEAEE,True +756,13.0,13.0,9.0,10.0,17.0,10.0,13.0,12.0,CGAEDBDFGGHCGBCFAEEAGFBFFBFFBEGEEBEEHEECDEGACGEHAFGADHABHAHHCGHFGHEHEAHGDDCAHFAEBAEDCBBCBBGBDEDDA,False +757,8.0,8.0,4.0,5.0,4.0,3.0,10.0,2.0,BDEBGHGGFDGFDAFCGGCEBBAACEDCADHABGGBGBAABGAE,True +758,26.0,19.0,23.0,17.0,12.0,22.0,20.0,22.0,DDGDEFCHCHHDHHCHGGHDBAFBFGBFEBCAFCAFHFFDCCDCEACACBFEGGHGGDFGDHCBGAFCAFEDBEAEEBDFGDAGBHBHHADGCDFCAHCHFCGFCGHCBHABDABAACHAFAAHCBHBFABFAGFDBFHBEECGAGAAGFAEDABACCEGH,False +759,4.0,1.0,4.0,4.0,4.0,6.0,8.0,4.0,GDFGAFGDGCFGCFCAHAHDFHEEHEEGDGAFGCB,False +760,2.0,2.0,0.0,1.0,4.0,1.0,5.0,1.0,ABEDBHAEGFGGEGGE,True +761,21.0,26.0,28.0,30.0,24.0,24.0,21.0,23.0,FDCHDHHDFHCCGFFAFAAGABBDGBCGBHGEHFHFBCEACEHEHBEABDBBABAGBFFBHDEEDBGFCGFCGFBBCBBDBGGGCDECDCFECFEABGCDAEHEHBEDDADFADGAEEAEFDCFHCFBCHBCHAEDDEBGEDGFHEDCBACDGFFCEGCDACABEGCDGHEECFCFHDFBDHADHADHACGDCDDHH,False +762,24.0,12.0,13.0,17.0,17.0,14.0,9.0,11.0,CEAAEBDEFDBCCBABBACBDBDDADGCGHAEHAEHBEFAEFAFCACHBHFEHADHFEFAGFGCDADDACDEDGEBGECAEBFEBEADGACFAHAACAAEADDFFGAFGCDHDHEFH,False +763,6.0,8.0,13.0,10.0,5.0,9.0,19.0,14.0,HGDFBDFGCHDCBGCEGCEGHGHHGACGFCAEEHBBGDHGCCGFAGHADHBCGDDBEAFDHFBHFDGCAGCGFFGHBGHCGHCD,False +764,27.0,23.0,30.0,22.0,19.0,28.0,33.0,17.0,AACCCCCCFBCDCCGCFBEFDGGDCGFCFFCAECBGBFCBGEHDEFGHFGHACHGFAGEAFFFCHFDGCHGDGCFGCFGCAGDBFFBECEGCGGBGHBDAEDABFABFDBDDBDAADGHHFBAECEBHAHHEFADFADFACAACGECEEAGEABADBDHEGEDGEDBFAHGAHGAGCDFBAGBGFFDCHBHEACGGBGB,False +765,18.0,15.0,16.0,11.0,14.0,19.0,16.0,15.0,CEFGFFADDDDCFAFGAFEEEAEHBEHCECAEBAECABHACHFCFGBGGBDABCFFFGFHGHGDEDABBABBAHFACGDFGDFGCBEEDFHACHGCHGBHFEGFAACECDGCHGBHCBHBAHAF,False +766,2.0,0.0,3.0,2.0,3.0,1.0,2.0,7.0,HHEHHCCHDGHDFCEHAEGA,True +767,17.0,7.0,6.0,11.0,18.0,9.0,7.0,8.0,HEEBEFBEBEEGHEFCEACFABFHBGEAEAACAADAADADDAFABDAGDEDAGDEDHCHFABEGDEFDEAEECEGHHHFGFAC,False +768,7.0,8.0,17.0,12.0,13.0,9.0,9.0,18.0,EBDDBCDHEEEGCEFDAFDABCBBHFGHGGHDCHFEHFAHAEHCFHCAHEHBEGECHEGDECCCCDCBHCGHCBFGECACHAFHDCDDHFDHG,False +769,20.0,21.0,9.0,15.0,21.0,8.0,21.0,20.0,HEDAEDGBFGHEDHEDHEBCGAEAAFAABHDHAEHGGGBEFDFFAAEAEHCHBCHACDBFGBGABHBBEBBAHBHHDABDAGDHEFEGBGGDCGEBGCHECHECHGBEDBEDBAAFGADBAGAHGBGDCGEEGEH,False +770,21.0,9.0,20.0,15.0,18.0,14.0,11.0,20.0,AGHAHEGHACBCDEHDEHEECGABBADBFCHFEABCBDEAGEAFEAFECFDCHDBDFADCAGCADCHDEADAAHFABFEDCEGCHFHHCEACGDDGHFGAFGAHHHECAEHDHHABCEFCHFCGCCEF,False +771,4.0,4.0,4.0,6.0,5.0,8.0,8.0,13.0,HGCHGCEBAEDFEDHAHHGEHDDBGDEGBHGFHGFCFFCHADFFBHGAHFHH,True +772,4.0,7.0,15.0,14.0,7.0,5.0,7.0,12.0,FCECCEHCHDDHEFHDDAEHECCGDDBDDBEDBFCGHHHBHHBCABCHBCDEDGCHFDACDFCDGCGGAGC,True +773,15.0,15.0,19.0,12.0,10.0,13.0,9.0,11.0,CDFCAAHAADAADBHCGEAHFBGCBCCEGCDCCDEAGHAGECHFHFFBFBHFBADCADEHBECBABBHFECAGCDDCFFFHDFHDFAEGAEGBCCBCEDGBBCB,False +774,17.0,15.0,18.0,13.0,14.0,14.0,9.0,11.0,BDADABGFCGHCGAGHAGFFDCCBAGFHDFHCFHCBACEACBAGBACBECFEBGABFBFFBHHBDEEDEAHEAGFDEFAFFBDHBECCCCDCEACEHCEAADDCBAEDDEH,False +775,12.0,10.0,12.0,10.0,14.0,18.0,9.0,17.0,FFDFGDFEBAEBHFHFFBFCBFCBACEGDDCHCHDGBEEAEHAEBACCCCCAHEAFFFFFHGBHDAADAHEFHGFHEDCAHHADHGFGCHGFEEHDEHBEGB,False +776,15.0,9.0,14.0,7.0,14.0,8.0,10.0,14.0,FGGCGFEGFEGEBBABCCDCHEHHCHGFDGAEHCEFCEGCAACEACADHABADBFDCEDAABEACDGCHHCHAFAGHEHBEFEAHBAHBEH,False +777,3.0,5.0,7.0,4.0,6.0,7.0,4.0,2.0,ACHDGDFECAEGAFGEBDFBCFCCFHCEECDBGFBEFB,False +778,13.0,16.0,17.0,23.0,18.0,12.0,11.0,15.0,HGEDGCCFHBDHDDECFEHAEBAEBHDCCDFCDCHGHFGHAABCAFCGHCGCEFFEBAEBABBEHBGHBFFDDGDAEDAEABBHBBHEDFEFCDCEDCEDHHCGDDDDDAGFEBBCDDADCAEEG,False +779,0.0,0.0,2.0,3.0,0.0,5.0,2.0,1.0,DCFGFFCDFHDFG,True +780,4.0,14.0,9.0,15.0,13.0,16.0,18.0,13.0,GFHBCDDGGEFBDFGDFEDHCBBGEFEAFEHBDHGFFECCDHGHCGBBGBEDHDDEDEEDBCFHGDHGFHGFHGFGGFGBFGAFHCDCAECAEBBEDBGFBH,False +781,14.0,11.0,9.0,17.0,16.0,19.0,16.0,13.0,AHAEEAEBDCFCAFEACDFGBGHHFBHDBFDCHDHHEHFDGFAFEABDGEEEFHFABFCGFGGBCHBEGBHACEADGACGCFGBFGAFDAGBAGFDHEDEEDEFDEFDGHDGDDF,False +782,17.0,30.0,15.0,20.0,20.0,24.0,22.0,25.0,GBEGHHGHFDDAEABGCBGDDCCHFEBFGBGDBGDBGCAAFGAFDEFGEFEFAEFACBGEBAEBHBBHBCHEHHEAHDDCBCFDADDHDGHFEHBHFBDBDHAFHFFHGGAFCFGCHEEHEDFAGBCHBFGBCGDCGBHBBCFBDBDEBFEFHHCBHGBEBAEBHEFAAFDAG,False +783,18.0,12.0,19.0,16.0,8.0,23.0,23.0,21.0,CAEAGEACHFBBCABCACFADGBFCCFGDFGFBGHEGHCCHABHGBHFBGEAGCCFDAFDCHBGHCGHDFEGEHGEHFDHBDFAHFAHCGGCGDBFAGFHHFHGFDDHGHFDAGBHFHEDDDDCCGCCGADFAFGAFAAF,False +784,26.0,24.0,29.0,15.0,21.0,16.0,22.0,14.0,GEEGAEGABFAFGEBBHCCCGGBHGBFDAADAAGAFGBEBBCCGCAAHAAHDBEEBGEDADDADDAECAECBEBHEFFADBCGECGCCDCGACBACFDCFHFDHGHBBHDBCECEGCBGEBCEFAECCCHFGECGCBACBFFBGFHCECAFBAHBHHAFDAGDECAG,False +785,1.0,0.0,2.0,2.0,2.0,6.0,1.0,1.0,FFFEFFEDFCDCGAH,True +786,20.0,28.0,18.0,25.0,30.0,17.0,20.0,19.0,ECEDCEBGECGBDDAGEBEEHHADHDECGEDEEFEADEAFEAGDBDFCEFBDHBHAGAAGCAGCHHCHDBDFFEECADBAGFCBBEBDEHHEBHFAHFBCEBFEGEHADBDHBDHCDBGDBHDCGBFEADEADHAEAGBBCBACEACFDCBDHBDGEGGEBGEFGBFCBGHFGFFAB,False +787,5.0,3.0,2.0,6.0,9.0,8.0,2.0,4.0,DAEDAECHGCHBEFFEFEDFEDADHEDAEFBFABFHFEG,True +788,5.0,9.0,7.0,1.0,4.0,3.0,1.0,5.0,EBABAACHBEHFACBBFBBEABCDECHGCHBCHFC,True +789,12.0,4.0,13.0,8.0,13.0,16.0,10.0,11.0,ADAAEBAEGDFGHFGEBGADFAFFAFFEFCECEEFEGFEDFCCECHHAFDCFGHEHBBFAGFGHACECGHCDCCHCCHDFHDGAAEH,False +790,6.0,10.0,8.0,9.0,9.0,8.0,9.0,13.0,CEAHHCFHCFHBEACFACDBGDBEHBGGCGGAFDHFCHFEHBABBHDHGDEAHGBEBEGBEDHEDGCDFHDF,False +791,8.0,14.0,12.0,15.0,11.0,8.0,8.0,8.0,EBHEBDCADCAGCABCGDEADEAEECBEDADFEHECHDBHGEGCFDCFBBBHBBDGHDFFDFFGBGHBACBFCHGCDCDDEBDA,False +792,10.0,22.0,18.0,14.0,21.0,20.0,16.0,23.0,DBGEHGFDGFECFHGFEGFBAECAHFHECBABHGFACEBDGBCGHCECAEGBBCDBEGEEGHEAAECGBFHBFHAFHCFBCDHCDHDBHEAEEBHHBCCBFHBCCBHCEDDEDDEFFHHFHFFHEFDAGBFEBHCBHDBFDGGG,False +793,23.0,21.0,27.0,21.0,31.0,27.0,29.0,18.0,AGFCEBGEFGHCGECBEFEGFCBFDBFHCCHCBEDDAGFBDCCDCCDEGHEGHAFHGGHDGDBADBAGEAEAGFFCDACFACFGCFGHFHEFHEDECBEBHFGDEGCEGDBAFCCFACEEBDDHCECDEADFGBBEABHACFAEFAEHAEHEGBFCAHGEFDEAAHACGDBEFBDBBCBCEHGEFGFGGFAGDAGEG,False +794,24.0,20.0,28.0,18.0,24.0,31.0,23.0,26.0,HHAHBAHDAHGAHECHECDEHEEGEFCECEFDEDDFCDFCHBBHBHFCGGEHCAHCDGAGADGCHGHFGEEGAEBABBAEFDGDHFFEGCBFBGHBGABDBCAGCEFEBFCFAAAGAGBABCAEAAFFBFFBEBDDFFCFFHFFECFHDFGCCACFAFHCFECECCFGHFGBAGBCDHHHCCHDCEDAEDGHFG,False +795,31.0,20.0,15.0,24.0,20.0,24.0,18.0,24.0,DDFDGFDGAGEBGEBGFHEDHBDBGHCFHBDCEACAGHADHGHFGBFHCDHDHEEHGGDGGEGDFGAEAEECGFCBFABFADAADAHGCFFHBFBAFDAFDBEBAAHAAHAAHAAFABCABEBEFDHDHEFHEDABHCDDDHBHCCGDHAECAEBEHAFBACEADFBFFEAFCAFC,False +796,6.0,5.0,4.0,8.0,8.0,11.0,14.0,10.0,AGGGDBHDBEDHHCHFAGFGEECFFAFFAEDAEFEGDBGHHFHDFGCGHAGHGGHGEBCEBDFGDF,False +797,13.0,13.0,14.0,16.0,20.0,20.0,14.0,14.0,FDCFDCDGCDGAFFFFHFBDGAEEFDHFGHGBFDAFHGFHGDEDDEADCHGBHGBACAHBECACHEEEEBBDFCEBBEBFEHAGCEBAEFCEFAGFAHFGHFGCFECADCGEADEHDEBDECHB,False +798,16.0,22.0,7.0,24.0,22.0,17.0,26.0,9.0,EFHFGCFGEDGFBGFBHACDACDAGBBGECEBBBDDADDADHGGGBGGBFEEDEFDEAGEAGEAFEDDBDGCDBBBGHGDHCDBDDEGEAFEADEABABBHFBFDBFDFEEFADGADECHBGEGFFGBBHEGGFDGAGAHGEE,False +799,20.0,13.0,23.0,31.0,20.0,22.0,27.0,27.0,ACCDDCDDCHDEGDBGEBHAHGDDDCDAHDGFAGHAEBFECFBCDECBAHEACGAEGFEFFGHADDGDDACEACECCFFFDFGHBHDBHDCFGCGACFCDHCBHEFDBDGCDCDEFDEFAGHAFHAHHCEGGDBGFEGHEHHAGFEBFGAHCBHCAHDADFGDEHDHHAGHFEHGEGGDGGBF,False +800,7.0,7.0,4.0,8.0,5.0,4.0,9.0,2.0,BFADCAGBDGDDGDDAEDEFBEABEBECGDGHAGHAGFGBABCGFC,True +801,27.0,24.0,11.0,26.0,22.0,20.0,24.0,21.0,FDEFHBBHDBDFECFEGGEGBBBFGBAGBGFBAEHFGHCAACHBBHBDHEABEFBAFGEDECDEGFGGHDGAGGAHCBHEEEFHEDHADFDHGEGFAAACDFDDFBDCEAHEBHEAAEFBDABAABHABDAGDADFAHFGHFGHCGDFGEBCDBDAGDBGHAHDADAGECDACDE,False +802,24.0,16.0,21.0,28.0,24.0,24.0,17.0,24.0,EHGDHECEADBDCGFCGDCFDEFDHFEEBHECAGBDHDDAAAAGEHGCCGBEGCEGEFDEBDAAGEFCAFABFBEAGEAFECCDDCDDHDHFDEFGAACEEEHGHHADHFHADHFCCAHGACGAHECBEBBDFBCFBHADDAGDCDFAHFAHFABFEBFECFHDBHDBHDGHFHFCDF,False +803,20.0,21.0,21.0,27.0,21.0,19.0,21.0,15.0,CHCDAADHHDHFEEFGGDBGABGCBCFAHFHFFGBDEBFEAFEHBEFDEFDAHCGGCDFCGCGECGEAGDBCEBGAADFADFCDAEDBDAHAEHAEGGEGAHGADFCHCCHBDBBGEADDADDBFDBCBBCBEGDDCEEAGDCGDFDEGBEBBFBAHCEHCFCFD,False +804,1.0,2.0,0.0,1.0,3.0,0.0,1.0,2.0,HBEHBEDEAG,True +805,17.0,17.0,12.0,11.0,12.0,11.0,11.0,14.0,CACCACHGBBBBABBDBGEGCAGFBEFAEBAECGBHHHHHHHFDEFGCGGBBBAFFAFFACAACGACDDEFEEDEADHAHCBHDGHABHEBGCFAHBEDDDFEDA,False +806,8.0,5.0,13.0,9.0,8.0,4.0,5.0,7.0,AABDACCACDACDBCBEEHEHCDHEDGEDADGFFCCBCGBEHCHHDGHECCFDCFAEGA,False +807,2.0,3.0,6.0,1.0,2.0,2.0,5.0,2.0,CCGFCGCAGEGGHBBHBDCFECA,True +808,8.0,11.0,13.0,11.0,20.0,5.0,10.0,7.0,EDGEBEBGEBGECCCADEEEBCEGEDBECBCCDAEDHECHAGHGCDDFDBFEBFEBEEGEFHAAGABGDFHDCHACBEDGECAHC,False +809,19.0,18.0,17.0,18.0,21.0,24.0,23.0,21.0,GGGGAGFDDEHDEHAEFAGHHHHCBECAGCEGEBGABGFBDCHDBHEHHGHFAHGCBGFDCFDCFBEFHHDAGFFGCEEDHGDCADAAHEEDEBHHFAFFABFACCBCABHGCGDBEDFEGFCGFBFBBCBBDFEGFECFAHDAEDAEAEEDCBGGFFFHA,False +810,20.0,16.0,11.0,12.0,13.0,19.0,22.0,18.0,AGFCHFDDFBEHGEHGBHGDCGFCHEGAGADFAGGAHAFBABBFBBGGAABAAEADEBDGCHHEBGCAEAHEGCAGFHDFHFEHAGDGFDBFBBFADCGDBGHFGHCCCGCDGBBAAFFAFHHFEHFEHEE,False +811,17.0,22.0,15.0,31.0,25.0,25.0,18.0,24.0,HAFEGGECCHDGGGHDGCDGDEAAEHGEFGBGGHGBEFEEBCHAEHCFHDFHDFGDGDBGDAFBFFBFHEECEDBEDHDBEDBFDBFABDEFCHAEFEDHCDAFDCBDABDABFCBCDHEHFCAFCDBEDACDEHFFHFFEEEBDEHEBHBHHAHGBHDHGDBCABDADDFDAFGAF,False +812,13.0,7.0,5.0,13.0,10.0,18.0,4.0,11.0,FGEADHABHAEHFCHFAAEEAFEAFDAFABEGGHFFBBDBHCAHADHBFADCCHEDFGDFDDBDFEDFEHFDAFDFFEHFC,True +813,30.0,25.0,17.0,27.0,18.0,16.0,23.0,20.0,DGAGBDGFDGFAAACAGCEFHDAHDBHCBACFACFGHFEFBHHBDHBAEDAHCEFDGCAADABGABDEGDGCAGCEGBABEABDFGDFADFABGBHGAFGDDGHDAHDCDDEDGECHEHGFBBFHBEBBCBDGGHHCEHBEGBCGADAADBHEFDEFHEAADCCHEDECAAABABB,False +814,24.0,14.0,14.0,18.0,16.0,18.0,16.0,21.0,ACBABDDGDGCCHAEHAEFDEFGHFGHFGDCGEBFDBGGBFACACFAGEHGBAFBAEAAEFHEGHCAEAADDHCABFHHEDHDHACHAGHACHGCHCHDDHABAAFADDBBABFHCFGCFEDDEDDHFEHFEGFBGEAFEB,False +815,13.0,9.0,13.0,16.0,13.0,6.0,10.0,11.0,EBHEDEGACDDCDGCDACHFCECCHGBHGBHCBEDAEDHFAFEAHEADAAEADDFFEGBDGEHHABGGHGCCADCDDCDHCABEFBEDBAG,False +816,3.0,7.0,5.0,5.0,0.0,0.0,5.0,2.0,DDCDBADBHGBGBBGCCCACBAGBDGH,True +817,5.0,5.0,2.0,2.0,3.0,8.0,12.0,6.0,HCHGCGFHGAEAFGHFGHFGFEADEHDFBGGGGGGFBFABABB,True +818,1.0,11.0,9.0,4.0,7.0,7.0,8.0,7.0,GABGHBHDBHCBECBFGHFGBCBBFEBECCEFCDFCGHCFCDHEFGEGBEBHDG,False +819,2.0,2.0,5.0,5.0,0.0,2.0,1.0,5.0,CDACFHHFAHDBHCCDCHDBGD,True +820,11.0,24.0,12.0,20.0,8.0,10.0,7.0,16.0,DDBDDECFEFFEBFBBABHAFHGGCCADEHHABDDDDCGHFABFABFHDCBDBGDBCDBFEHHCBHADHADBADCHDCBDHBEHBHABCGBEGBCDCGHBDAEFBBBH,False +821,9.0,5.0,8.0,7.0,7.0,2.0,8.0,6.0,DCDGGAGGCHGCHBBEEAGEGEFCEDADAADAAFCABCEHCBHBEHCAHDDG,False +822,4.0,6.0,4.0,6.0,8.0,10.0,6.0,8.0,DGEHGBHAFDDFEAHBFCBFCDFADFCDHGEHGBFCBHEHGEBEEHEFGFFA,False +823,11.0,21.0,15.0,29.0,14.0,28.0,25.0,13.0,GCBACBGFGGFADDGDDHCCBEGFEGBDBBDFFEFECFBCFBFFGFFGDDHHDFHEFDEDDAFAGFDEBEBBDDHDEHGCHFCGCAGCFGDGGHCFBBFBDCGGEGDEBAHFDEADEADFCDGABFDDFGDCGBFADABDGBHGHGFHFDHFEBCB,False +824,9.0,9.0,18.0,17.0,22.0,11.0,12.0,16.0,HDHHDBHCFHEEAEBDEDAEDBEDBHHAFFDDFCHGCHECDDCEEEFEDGADGCDCCHCAHCAHCEHGECGEGGHFDCCEECACBGCEGFGDEBAFFAGCGBEEEFDEFDBHBH,False +825,13.0,14.0,23.0,11.0,13.0,29.0,17.0,16.0,CFBCFDDFBDFBHFHGFAGEAFFBHFCCFCFACFACFDCAEBHFGGBAGDEEHBGFAGFHEDHGFEBFHHFGFDCFCBHEEGGCFGEFBCADHHDBFDBHDHACHCCGCEGAGGFFACCAECFHCGBCEFCEFCAB,False +826,5.0,8.0,5.0,6.0,10.0,4.0,3.0,7.0,DDEDAGAAGAHCDDBBHBGEEFHECEFHEBHEFHECEECBBCHBDFBA,False +827,20.0,17.0,26.0,28.0,18.0,27.0,26.0,26.0,ECFEGFEHFHHFABFABFEHABHAGDBHDBHDBGDGCDGHABHAFCEHDBHGCDCEFEEADECDAFBGFEGFBAAGDGDDEEDHDABDABFAGFDGDDADCBDAHGHHGHHFFFFFGCDEDGGCBCFEDGCCGCCDCEFFHHAHDBHAFCCFDGBCCHACHDEGGEGCCDCCHCBGFAAFEGFGCHHF,False +828,10.0,8.0,14.0,9.0,25.0,17.0,21.0,17.0,ECHGCHBCGEFDEFDECDEGBECBHBHHFFGGFGGHDGHACCAHHBDCFGAFGAGEEHEAHECEEHEEBEEGDECFEBFECFHFFGGGAEGHEGFCFBAGAHEEGDAAHFHCFGEEDFGDC,False +829,3.0,3.0,1.0,2.0,3.0,6.0,4.0,4.0,DHEHHDFHGGBAGAFEACEGFBFFBF,False +830,13.0,14.0,5.0,14.0,12.0,16.0,14.0,22.0,GDABFFCGFEHEGFFBHCBHEDHFGFBBFEDEHDHHGFHAEHAEHCEHABHADGEDGAFGHBCHAGHADHEFHFFGFGBAABAABDGBDCHDGBEAFHHDDBDHBFHDEG,False +831,30.0,21.0,25.0,25.0,16.0,20.0,17.0,32.0,ABDAGCAGBEEEEFEEFGBFGACGBHGBHCAACAACGCHGHADHACEECHDHACHFEGEAGDAHDAHDGBBHBFHGCHEHHAFGFFDDBGHHDHDEHABBACBHCADFDDHBDHBDCDCBDAHFFHDDBFHAGCDBFFEECCECCGHAHCAHBEHDACDAHDFCDAHDBBFFBAFCFFCAHAAGAC,False +832,25.0,27.0,23.0,20.0,26.0,20.0,20.0,27.0,AADBAGBCFACEEGDFBFFBFHCGDBHEFHCFBFBEEBHCCHCHBEBGABDAHDFHDHHFEHGECGFCBHDFHABBDDBDFHDGCGCCGCDGCHBHEEDEHDHBDEEHEGHBBHFBHFBGCEGEDAEGAECCEAAEACBAHDEBAEBFGACGAFAHDABAHDGCDEAHEAFECFGAACBACHAGBFGE,False +833,25.0,13.0,14.0,24.0,17.0,12.0,19.0,18.0,AEBDEBFCFGAEEHEAHBAHDCFDHFBFAGFAGAEGCCDCAAGAHEHHGAHEACFDEGDCFBAGGABGADGCDGFEBFEAAAGAAECBGDFCDBEDHEBCDDHDDHDGHDHHGCHGEBGHCAHDEEDCDDBADAAGABHDDF,False +834,15.0,10.0,18.0,19.0,15.0,14.0,14.0,17.0,GFDGHHGDHFHCFDBEBGADGACECCHHCHFAHCEHCHHDEHAEBADDGDBGDEEDECDFCAFEEFEDDHDCGAHBAGBDEADGHEFDFABCEBFGBCABCFGCFACGDHDEHACACCAFGF,False +835,20.0,10.0,18.0,14.0,16.0,28.0,23.0,12.0,CBFFGFCHEDBFHGFEGFEGFEDCEDAEHAGGGGFGGCCCDGCFGCFHAFBAFBDFCFFHAAGCEGAEGHEGDFAFFCDFADECHEAHGFGEHGEBDDBABFABABECHCFGCDDFFGFAACAAEDHGGHECDBAFCAFAF,False +836,30.0,20.0,19.0,16.0,19.0,13.0,25.0,21.0,GEHGEGBFGFCGFAGHHGFGGFDHAAHECBAGGAGHCGBCABFHBECAAHAFCEBCEACEADDADCGHBDHGFEDBCAEGAHGHCGHCGEBBHGDHEDHDFBEBBFADEAHEACBAEGFDCAABAABAABGAEACHBHDGADHAEBACHDGDAGCEDCEFCBF,False +837,11.0,6.0,11.0,21.0,12.0,11.0,14.0,20.0,CCGFFHDFDCHECHGCEGCGGDDGABGAEHDEHGGHGHDDHDABDHBHFFGEFHDAEDFEDFGFAHHHCFHAEDGEHCHFDADDGDBADAHDAHDCDCCBEHBEAE,False +838,2.0,11.0,5.0,5.0,5.0,11.0,2.0,7.0,HHAFDBFCBFHBFCBHCFEBHEBCFBFEBEHBDDDEDCABBFFGFFGH,True +839,10.0,18.0,12.0,15.0,22.0,22.0,14.0,20.0,GHGGHDGHEHCFHBHHGHGFDFFBHGBDFBCFBFEBAHAACAEBAFCEFHEABGAHCBCCADAEHFDHFEFFEHFEHCECGHFEBFGCFDBBDBDDCEDEEDEEFBFFGDBBEBGEAEHFDCEGEEDHGDHBF,False +840,6.0,5.0,3.0,4.0,8.0,4.0,5.0,6.0,HFAHFAGABEEHFEBBEABCGBGAFGAECDEDHEHHEDGDC,False +841,22.0,25.0,12.0,20.0,30.0,18.0,24.0,19.0,CFDABGGBGGDGGBGDBGDFEHGEHAEDEEDEEAEGABBABHABFEGAAAAFAAGHFEEEAHFBBFBDHEHAGHADHFDHEDHEDCFAHFEHGEHEEHCBBDBBGBGEBCEBFEHDCFAGFECABGDHEFFEBEACCHEGEGCAFDACECDGDBHEFCGFGGBBBDBDDA,False +842,26.0,32.0,18.0,28.0,33.0,16.0,26.0,21.0,BDFEACGAHGEHBEFBDDCDDEBGFBAHCGBBGCEDEHBAFGGFBDFDABCCBFCBHEBEAFGAEGFEGEDGAABBHBDCAAEAEEBEBGDGGDGHDHHCACBEGGDHADHGEFEBDEBDHBDHBEHBHDDCDFCDCGAGGEGGEGFECAEABEAHDAHCFFCDHAAHAACAABFEEEBDEBDGBDBCEEHDBGEBEAHF,False +843,17.0,15.0,21.0,18.0,10.0,19.0,19.0,11.0,GCGCCGCDBAAFCFFCGCCFCBGCBHBGADGFEEEBEDCFDCFBEFAEGDDDDDAGACDEFDBFGCFGEFDDHCGGGGGAFACHACHACGADGHHCHBFAAFDFFDABBEBFHBHEBHCAHBADGABFDC,False +844,28.0,20.0,25.0,32.0,29.0,10.0,34.0,16.0,GCBGCEAHBHHGHCGADBHDGAFGCFEEFDEAABAAFACGACHAGEEEEEBDBDDGEAEBGCFGAFGCGACGAGFEDAGDAGDBGDFEBECDGBDHBDBBDAEHADAAHGDCGDEBAHBEDCGBEGHEDHCCEDDEDCEGCDHDACAABADGEEFCEFGGAHGCCGCBECECBDHDCADAGDGGDGGDECHEBD,False +845,9.0,18.0,18.0,15.0,16.0,16.0,18.0,30.0,FHHFCHBCEBFEBFBHCGHEGFEDEHABHBHCEHCGGEGGCGGDGHDFHBFHAGACEDBBBBBFHEDHAHHBHEGHEHFDHEBHDDHCDCDHCACADBHDAAEGHFCCECCFHHBHGDHCDHFDGFBGFGGECAFBFCEG,False +846,25.0,21.0,20.0,25.0,14.0,20.0,19.0,27.0,DHHAHHGHBEBFFBHACHBCHFEAFHAGEAGEDFFDHACGDCGEBDDBGEAFAAGAAHAAFCFDCAEFBEGHGDCFAEDABDABHGBHGFHFDGDDGDDHFBABCADDACHBCHCGECACDBCGBCFHEHCCBBHHHFHFBHECEDHDAHDFDDFBBFDBEGACGACGADG,False +847,19.0,22.0,26.0,32.0,24.0,20.0,17.0,30.0,FFFFFBEBBCDDHBEHDHHFHCDHCDBCDAFBHDGHDECDEDGEDCBFEFEHAHHAEDBDGHDCHECDEFHHADHCHBCHCDDCHBBHBEECCDFEDFDBGDBDFBEBAEFAHAGFECCACDHCEHCGGCGGCAGABCAGAGCDBADGEDFEGAEGAEHACHCBHABDBEDEDDHADGGFBFFHEFHCAH,False +848,9.0,6.0,11.0,10.0,14.0,15.0,7.0,8.0,EBECBHGDFECFDGFDHFDCEAAGDEFDEFDFFHCAHGBDDHDHFEGEGBAFCEFCAFCACCACBAFHFEHEEFEGAEBC,False +849,4.0,12.0,3.0,4.0,4.0,6.0,9.0,4.0,BADBFBBDBCDAGGEGGAHFBHFECBBGGCGGBBGBDFFHFEHAEB,True +850,11.0,16.0,15.0,13.0,9.0,18.0,8.0,14.0,AHEFHEDHAHCBEFAEABEBBDHGAGCECCECCEDGADFFBFFBFFACACDFCDECHHFDFFHFFGFBAHBCDBGDBGHHGHFBDBHDBCCFHDACABDGBCBF,False +851,14.0,6.0,9.0,8.0,8.0,11.0,8.0,4.0,CADAAFAFGGBDGBECHEGAEGCEGHEAFCGCCAFCAFDBEHBAAAFAFFECEDADGACFBDFHDFBD,False +852,13.0,17.0,14.0,11.0,14.0,23.0,28.0,19.0,AHFBHFEDBHCBHGDHDDBEFGAFBEDCEDCGGCAGCHGCHGCDCEEGFBBFHCGHAGDCFEGABFCBECBAFBAFHHGHEBCFAEGGEGAFBFGGGDGBDBFAEEBGAGHAFHCFHFFAGFHGFHFFHGGBGGHDGFE,False +853,17.0,14.0,15.0,18.0,12.0,25.0,14.0,18.0,FEEDCEDAEDABFABGHCGEGBAFBAFADFDDFBDFGDGEEAEHDGHCFHCHGBHFHFACAEBGHHGHAGAAFFDCCDHCGGCFDCFHCGECADCFDBFEBFBDGHDCHCHDAFFFHFBBEAFADFHBFHFAB,False +854,4.0,8.0,7.0,9.0,7.0,13.0,4.0,5.0,HAHBAEBCEFDHFGBFDDFDDFCGFBBCBFCFFCAFEDFBCGCDGEHEEDFDHFEBA,False +855,8.0,9.0,7.0,8.0,14.0,11.0,8.0,11.0,FCGGHEGHCAHEGDGCDHEBHEGEEFAEFCEAAFAHDEHFEHBGFBFFBFEAHEADCBBCBBCEGDDHFDFBHEAD,False +856,15.0,19.0,19.0,21.0,20.0,23.0,9.0,21.0,EHCABCEDCEDCHDBADEFFEAHGADFHBFEBFEHFEGCHGBBFBDFDCFHCFCGHCDHEHADFFEFHCGHCBABEEBEFBCDBCEHDACDBBDCBACBAEBDDCADFAEFEEHDGHDEEFBFFDHGHFGAFAHFCGFHBHDADAHC,False +857,8.0,14.0,12.0,26.0,12.0,12.0,24.0,18.0,DDGDGFHGDEEDEHGEDDCHGCAGDGBBHHAHDBHDBGACHCCHFCHGGHDGHDBFABCHGHGFDCEAGEADEGDADEGHBCFBGFGDCGBFDFFDCBDCGDGBEGBFGEHHEFHDFGDAEDBDDB,False +858,3.0,12.0,7.0,10.0,7.0,11.0,5.0,6.0,EHBFDFFCEGCEBFAFCCFECFHDGCEHAEFDBFDBAHBGHBGEBCDFDDFBDBDGBHBBD,False +859,15.0,8.0,5.0,5.0,11.0,6.0,8.0,9.0,AFHEGGEGBEDBACAADADGGHGFEGCEHCDAFECBBABHHEHAECFHBAHGABDEBAEFAEFAHAA,False +860,24.0,23.0,16.0,29.0,25.0,13.0,28.0,31.0,ABDBGHHDBEAACAHBDDDDHHGAHBDHDAHCGHCAEGFECFECGHAGBBDBDDBDGBDBAEBACDAHDBGDBCEBGEDDEBDBBABGGGGGEHAEGGGDFHDAHAHFAFDCHDCHEFBEAGECHFCHGGEGGAGFDHADEGHAFHBGHEFBCAGCAEBHEDHEDEEDFEGFHCEHDHHFCHEAGECHA,False +861,19.0,16.0,16.0,18.0,22.0,19.0,15.0,18.0,HBDHADGAFFFCFDCFDHFAEEDEEABBABHHEAEDAHDEHCGFEECHECEFGHFDHFEEGCBDFDGHDGHDCBDCAECAHBACGEFBFFAFBAFBEDHDAHBBDGEGCEGBGDFGAFGAHCHGFECAEGABAHBACBECECD,False +862,23.0,28.0,34.0,23.0,21.0,19.0,19.0,23.0,AADEFDECBCFBFEGCHHCBCAHCAEDAEDFGBAHBGBBGEDGEFBAFBABEABFAHFAHADGBHAAHAAHCFCAECBEHBACDDCDCHDHHDAHDAHCFBCDHCBBGDEDEHFBCCCCCDGEDEEBCBHCDEBEHBCGCDECGCCGBCGBCFAGGACBHBFCAGCFBDHBFHFECFGHEGCEFDDFGDG,False +863,11.0,5.0,11.0,10.0,13.0,17.0,9.0,9.0,HGFAGHEGFFAEFGCHCCHCFACEAFEAFBFFBEEDDDGGDFEBHDFEDFEFCEHCDAAFBAFHCFECHEDDABDAGCCGAHGEF,False +864,8.0,4.0,8.0,5.0,6.0,11.0,2.0,13.0,CGDDADAFHFEHACHFFHAFHAGABEFBHHCHFCFBEHCEHDEFDCFEFHCAHCAHB,True +865,6.0,7.0,13.0,8.0,5.0,5.0,10.0,8.0,EBBEADDABHGBFBHDAHDFCCCCCGDCGACEFCEGCGGCDHHBGHCGCGBFDDFEAHCAHG,False +866,13.0,18.0,13.0,24.0,13.0,21.0,16.0,22.0,CECHEHGAHDBHAACGDDGDDGBGFBACBAFGCFGEBHHBHBBFBBFGDFEBHDBAEEAGEHFEDGEDFFHFADDADFHCHEADCFDBEDCDDFFBFFHFGEFGHCDFBHADHFDHFHCGCAGDACEBDHBDGDHGCHBH,False +867,3.0,4.0,1.0,1.0,0.0,0.0,2.0,1.0,BGHBGBAABACD,True +868,12.0,15.0,8.0,11.0,24.0,11.0,16.0,16.0,GBGAFGAHEABDAHEEHEGHFBEGHCHHCBDFECAADDGHFHFGEAGEBCDGEDBEFEEFGDGGAHGDHEEHBEHGEAGECGEAHECHBBEFBHBBDBBDCBFEFEEFECAAD,False +869,14.0,6.0,19.0,11.0,20.0,15.0,11.0,18.0,AFHAEHAEHGFHACHADFFGGFEGFEGDEDBAFBDECHHGHCCDBCFECHCHFBEDEECHACDGFDCHCEHFHCFACEACEACBCGBGEADECEEGFEHFACEDHEDHAGHFCA,False +870,7.0,10.0,10.0,16.0,6.0,4.0,11.0,16.0,HCBDCBHCBACDCCDHFHAGHCCDECGEDGDAFHGHGBDDFADHGDHBDHBGHFHEAABGBDHEDHEHHEGDDGADGCBB,False +871,6.0,1.0,1.0,3.0,2.0,4.0,9.0,6.0,AHCGEDGAHEAHAFGAGGBHGAHGFGDFGFHD,True +872,3.0,5.0,3.0,3.0,6.0,1.0,1.0,2.0,BBBDCBEGHEFHDBADAECAECEE,True +873,2.0,1.0,1.0,2.0,5.0,1.0,2.0,3.0,HEGAEHAEBCFDEHDEG,True +874,7.0,21.0,14.0,14.0,9.0,12.0,13.0,10.0,FDBFBBDBADBHBAGDHHCGEFDEBGEGGFGBCGEADAGGADHBDFCDECGBCEDFHFGHFEAFGHEDCEDCBFCBCCBHBBHBBDCBFGBCBHDBCAFC,False +875,6.0,6.0,10.0,12.0,5.0,8.0,13.0,6.0,GCGGCGGHBFDDADDBDFBDGCFGAEGAFBBCBHHFDHADHAGCDGEDEFGGCECCHDCEACGDFF,False +876,19.0,14.0,14.0,17.0,5.0,8.0,26.0,9.0,ADBACAGCHGCFGHDADABGEDABDABAFGCFDCADGGGGGGGGGBGGBACCHHAAGAADAGDAGDCGDBFFBCFBEBCEBGBBHEGDDCCCBHHAFGDGADGDDAFCGHHE,True +877,11.0,23.0,26.0,15.0,25.0,13.0,27.0,20.0,DHHEHGFGGCEHCGDGEDHCDHBFEDFEAFHBDGFCBHCEECEECBHCACGACACHGBHGBGGECGBDHCFEEEHCGHCGHCEBEFBGABCDDEGGEGGEGFEDBEBBGBCGBHABGEDCABCFECAHHBBCBDCAGBDGBAGCAHFHEBCEGCDFFDEF,False +878,10.0,21.0,12.0,20.0,16.0,27.0,18.0,16.0,EGCEHFAFAEBBGACGEEDEBDEFDBBDCBDEDFFAFGHBDFBHBGHBEBEGDDGDGBHGBHBFFGDFCFGCFAEGHEDEEDEAFFFFFFCHGGDGAFGAFHDBHEBCAGHBFDFFBHFCHFCHCCDCFDHBDGBDBHFA,False +879,13.0,7.0,15.0,3.0,11.0,11.0,9.0,9.0,CHBCFBFGEFEHCCAFAAFCEECBBHEEGEFBEABAADGAGGFGFCGACEHCHCFECADCACCACFAHFHDGHGAHEB,False +880,18.0,17.0,11.0,7.0,12.0,11.0,12.0,19.0,GACGHHGCCDAEAEBAFGHFGHEHABHBDHGCHGCHBABEEBECDDBABBHFHGCBGCBFAAGDAGHHHCAFCABAABAABHAFDAFBGDCHFEBEEHEFHEFBFHE,False +881,15.0,14.0,12.0,18.0,16.0,16.0,10.0,24.0,EFDEFDHBEHAEFFBHEBGEFABHGEHDFHAFEBCDGDAFDAHAACDACDGCEHDBBBBHDHEAEFAHGDFDABHABHAEHFEHFHHFHBFHAFHAEDCGBGGDDHDEHCBCCHCEFDGGHCDCC,False +882,1.0,3.0,4.0,5.0,7.0,5.0,2.0,5.0,HDHBCGDFACFECFEFBDFDGHEEHEBHEDCE,True +883,10.0,19.0,13.0,15.0,16.0,14.0,11.0,10.0,FDEBDAHCBEFHFHGGHGEBGCHCEECDACEFBAFHCBCEBAGBFGCEGBEHDDHBDHCDAFDEBDFBDEADBADBAECAGDABCGDCFBGFBDFBEFBFGBEHEECF,False +884,4.0,20.0,14.0,12.0,17.0,18.0,12.0,16.0,DHCFHCBHGFHFEDFEDBCDBFHHGCDFADCGHFBDCBDHAGEFBEHBEDCEGCABFHBHCCCCBHCGGFGFFBFBBEGFEBBBCGEGHHHFDAFDEFBEFHEGDEBEEBEEB,False +885,4.0,5.0,7.0,5.0,3.0,5.0,11.0,4.0,GBBEAFCABHGBGEFGDDCBDCFGCAGCDGCGHEGHFCHFGAGD,False +886,4.0,2.0,5.0,6.0,4.0,7.0,8.0,6.0,DEGFEGHBGCGHBGHDFAFFAFDADGCHECDECFFCHADHGG,False +887,7.0,10.0,2.0,12.0,7.0,8.0,10.0,7.0,HDGHAEDCDDBGDBAEBGCBDAEGFGFBGFBDDBFHBEHADFGDFHHFHEDGADGAFEAGEBB,False +888,22.0,21.0,26.0,15.0,24.0,25.0,19.0,23.0,HFHEFEAADAGDBCEBGEBEFHEGHAGEDGADFEBFCBFBBFCEHADFEHGHHFDFCHFCHDBGDHAAHFCFAEBAEGCEGCFFAHHGHHFHHCHCBABGDHHDFABGCFACFECDEAGEAGFBCFGCEGCBBBEBAGHGGCBAFACFDCDDCFCAHCACCBEEBEEBEADCCEF,False +889,14.0,18.0,14.0,7.0,16.0,10.0,10.0,16.0,FHAHHEDDECCCHBCBBFBFCBACDAGHAGHBFHBCHBEGEEGBBGBBGEAEAHHBEFFEAFEDHECEEGABGBDGCABEABAFCHCAACGBHHAHCDHFECFED,False +890,18.0,20.0,25.0,21.0,23.0,27.0,22.0,23.0,ECFEGEBFABFABCDBFHBHABHBDHGFGBFGECGCFHADHDEACCBHFEGFACHECHFBACCCBEBBDFDAEAABDAECCCFCFFCFFCEGCHBEGDEDFBDEGHFCHFCFDCFEGGEGDDGHDHHCGHFDFBDHGHHAAHAEHFGAFGAEADEFCEFBEGBGGHDAEDCEHCDGBDG,False +891,21.0,17.0,16.0,20.0,21.0,17.0,22.0,30.0,GEDGFABBHBBHFAGAEEAEAAECAEHHHBDDCABHGGHGCBAAFABFBFCGEBFEGEHHEHHDDHFGEEHDGHCAHFADBADCCGACHDGHAGHAFHAFBECBEDHGCHGAHGBDCEDCDBFDEGHGADGDHGFHCDGDFHBHHBHAECFECFEGFHFEDCED,False +892,2.0,4.0,1.0,8.0,1.0,2.0,5.0,5.0,HHHHBDABDGBDFFDCAHGGGBDGDDED,True +893,15.0,5.0,9.0,8.0,9.0,2.0,15.0,5.0,GGEGEEDAFGECACCAGFGEEDECDBAEGADGABAACCACCAHGAHADHGDGGHGBACBHBDEGAAGD,True +894,15.0,20.0,23.0,20.0,17.0,18.0,26.0,16.0,FGDFCFCCGBFEBEEDACGECGHCFFEDBBCHBFHBDAFHBGCFCCFAGHDGDGGBFEEGCEGAFGAEAFEDFEDBBDHBHGGGGCFDCEHBEHGCAAAAAGHCHHCHBGDDCDBGBBCABCABADBADBFDGGCCEDEEDGCGGDDGHCFHEFH,False +895,17.0,14.0,14.0,9.0,18.0,14.0,9.0,18.0,BGCDCCFADADBGDGCAEEAGEBEFBHHAEFFEHFEBEBCGCEBCEDAGGAHEABEABDAFDHBHHAAHBAHAHBAHCEHCAHFHBEHFCFFCEFCEHCHHCAEDFEDBGFGF,False +896,10.0,10.0,7.0,13.0,14.0,14.0,10.0,8.0,HCBCDHHGEAFHFCDGHEBDEAFBCFEDFADEADEADABBHCAEDGDDGFDAFHHFDGFGGFABFBCDBCEAGBBGEFGEFEEFEE,False +897,1.0,6.0,2.0,6.0,4.0,12.0,5.0,5.0,FBDGCGGDFEBFEFFEGFBGFHFFDFHBAHFEDFCHBBHDD,True +898,8.0,2.0,6.0,2.0,1.0,5.0,2.0,3.0,CFFCHDCFEHHAADAACCABAACGAFGBF,True +899,13.0,11.0,11.0,13.0,12.0,11.0,12.0,9.0,FCCGCABEBEEFCBGCDGCAECEEHAEGDCFFHDBCABDABEAFCBHABHADHGDFGDFBDFEDGHBGDGDAGAFECHEGDEGHFAHDABAF,False +900,11.0,8.0,16.0,15.0,15.0,12.0,12.0,10.0,HFDECDECFHCHGDEDEEBGHDAHDABCCDDFGDCGBCACCDGGFCGFEHEAGEAGEAFCCHCCAFEAFADEADHGDBFBBFBBFGCEAHFCDEEDHEG,False +901,6.0,5.0,13.0,12.0,14.0,4.0,0.0,2.0,DEEDEFCACAAEHEECDECAHCBDDECCBCFFDBFBCDECEECEDCADEDDEDACB,True +902,5.0,2.0,3.0,0.0,2.0,4.0,3.0,0.0,CFECFBAGAACAAGFFGBE,True +903,1.0,3.0,5.0,2.0,2.0,3.0,3.0,5.0,HEAGEFBCDBCBCFHCFHCDHGHG,False +904,8.0,10.0,8.0,10.0,10.0,10.0,8.0,8.0,HAEHAEDAEDGHFGFFAFFBFFGDABDECDEGGEGHBHBBCCFEDGECBCCBACHDCAFBDDEEDAHGBHBF,False +905,19.0,35.0,22.0,16.0,17.0,18.0,22.0,17.0,BEDEDGGBEBBDBGHBCBBCBHCAEAHBAGBCBHDBHDCHGCBGDAGDCCAGDGCDFCBFCBDBBDHAAEAGEGGEGBAFBHFGFGBFHEACECCGHCFFEFBCFBAFAABBBBBHDBEFBHFAGBEFCDGCFCDEEHBBFBDCGDEGFHGACAACAHHFGHEABE,False +906,6.0,6.0,11.0,1.0,5.0,2.0,8.0,3.0,GGECBACGCCGHCBFEGGAACAACDACBBCHCEFCEHBEGBG,True +907,10.0,11.0,15.0,22.0,12.0,15.0,10.0,11.0,CBDCFAHHHHCHDBDDBEDHCAECDFFDACDGBDABCFBCFBGDCFFCFEEHGGHGADGDFAFACGDCADFBCFGDFEDFDDADGAHEBHFCHDCDEEBEEDEGBE,False +908,4.0,0.0,2.0,5.0,3.0,0.0,2.0,3.0,GHACDADAEDAEDEGDHHC,True +909,1.0,4.0,0.0,5.0,2.0,3.0,1.0,1.0,FDHBDABFEBDDBDEGF,True +910,9.0,19.0,26.0,20.0,13.0,12.0,16.0,22.0,BHDCHGCHBCHDCBGCAEDFEBFBHDBHDGHEGECGCFDCHHGHHBHGFGCCBCCDCHAADFFDFFHEDCFBCEHCEHCDDFAGECGDBDBGFGEECBHCBACBACHCDEFDAHBCHCEGBGGCDDHDEHBAGBADB,False +911,5.0,1.0,2.0,3.0,2.0,3.0,0.0,2.0,HAHAADAFBAFEFCEDCD,True +912,26.0,20.0,25.0,15.0,11.0,21.0,19.0,28.0,BGFDDHABFAGCACFBCDBGDCCAAAHAAHFCHCEGGFFHHFBCABCGGGGBHEAHCAHBAHAHHACHFDHDAHABHCBFEBFADFGDCGFFHCGBCFBDFEDCHBBHBCGECGEHGFHAEHACHADAABHFDECEGBAGDHFDHCCFGAEGAECABFFBHCCHD,False +913,7.0,7.0,5.0,3.0,0.0,6.0,1.0,6.0,CDFCAFHACADCBBHBFHBFHFDGCABBABFHHAA,True +914,20.0,24.0,25.0,24.0,19.0,23.0,23.0,19.0,BDHFDGCHCAHFAHFGGCHBCHDFEDAEHCBFEBCGHCGFEACCAHDFGDFDBFBEFBEBGDBGDBCDECBFHEEEBCGBDDFDECHEHBFCAFADGADAHFCFFGFAGFEGEHGADDHDCHDBDDGEDBHABGGBEGBAHBHBDCFDCACCGEAACCACGAEGBEFBAFCCFGBAG,False +915,6.0,10.0,1.0,9.0,16.0,12.0,5.0,11.0,BFGFHGADDEEEEBEEHEHHEHFEBEGHFDHFBHFBDFDFFEBGDHCEBEEBEAGDADHAFAAFHBBEDF,True +916,19.0,25.0,17.0,15.0,26.0,25.0,27.0,16.0,EBBHBCGEEAEBCECGECHHCGDCECGECDBCDBAGCHGBFDBDBCEBFAAGAAHBGDFGAEGAEHEEHECGFFAFBEEAEEABEHBGHBFHDGCCFEFFCFFGFDHBAHAGFDGFDGHGGEDGEBGHGFFECBAFBHGEFBFGDFHDAADGGBAGBFCBFDEFAFBABE,False +917,1.0,1.0,0.0,2.0,5.0,1.0,1.0,0.0,DABDEEEEGFE,True +918,3.0,4.0,4.0,5.0,6.0,2.0,1.0,2.0,FCHDCBDCDEADEBDEBFBGACAEHEE,True +919,29.0,30.0,27.0,23.0,18.0,16.0,15.0,25.0,CECCDDBFGBEHCFACFCCAAAAABGDBDCBDABFBCEACABCGBHGDCGFBGHCDHCEHCBAFBFGHFHHDHFEHFEHCDBDDACBACGACGACFEDEBDHBDHAAEEGFBHHBHDAHBGBCGDAAHAFEBCCBDBEEAHEHFGHAHAABBABDHBDADDAECGBCEDCDCGEHAEHABBFF,False +920,6.0,8.0,6.0,2.0,10.0,1.0,2.0,2.0,ABABBFGBDGEECCEACECHEHBEABDBEEEACEACB,True +921,9.0,6.0,2.0,9.0,10.0,5.0,13.0,15.0,EBEDHGAHGFHGFBDEDDGCDGDHFAEABEGEGAHGAFEAGHAHHEHDEHDABDBGEGGBGHHACHFHH,True +922,0.0,4.0,4.0,4.0,5.0,3.0,8.0,5.0,BFCBHEBHDBCDFGGEGFEGEHGHCDHGDGGEC,False +923,9.0,18.0,18.0,28.0,20.0,33.0,20.0,19.0,FCFHEFDEBCBBCFACFDCDCAFCAHBDHBFGFHAFEAFEHGCHGDHCDHCFCGDCHBEGFFGDFGBHGDFGDFGFAHDBGGHHABEDFFDFFDFFEBFHDCEDFEFHEHHDGACFFGHBBHBADDDDCDEGDGGCEFCDBEBGEDEEBCEFGFFBEDGEDBFDE,False +924,2.0,5.0,0.0,7.0,6.0,1.0,0.0,3.0,EEDEEHEBAEBDDDADBHDFHBBD,True +925,12.0,20.0,17.0,18.0,18.0,15.0,13.0,21.0,GHHFHBACCFFHHFHHABHGDHFDEBABDDBCAEHABDEDCGDGDDGCDFFDHEBAEBAEBDCBGCEGBEHBFCEFDBGBFGBHBHHFFEEGECGECGECBHGBHDCHDAFDCFDEAHAHEAHACCEEFBBDCC,False +926,4.0,3.0,0.0,1.0,0.0,3.0,0.0,2.0,FHBFBBAAHAFDA,True +927,18.0,22.0,21.0,28.0,13.0,24.0,11.0,19.0,CBHHDCBAGFEDFBGBCGDCEFHFGHFGBFDDDDCDDCFHGFBDEBAFBEDACDAFEGFEDFCHEDADFBEFBABDGCCACBACHDCFDFAACCACBHFBHFBHADDADHACBBCDHCFFBFAEAACDBCHHFHGFHGHBGHBDEDDEDFEAHDBE,False +928,1.0,4.0,0.0,2.0,0.0,5.0,1.0,1.0,HBBFFDFFGFBADB,True +929,3.0,12.0,7.0,6.0,3.0,6.0,4.0,12.0,DHGHFACCACBAFHGDEGDCCBBFEBDEBHHCHHBHBBHBFHFCBFHGDBBDH,True +930,4.0,2.0,2.0,0.0,0.0,4.0,2.0,2.0,HCAACAFFGBFGBHAF,True +931,5.0,1.0,3.0,1.0,0.0,1.0,1.0,3.0,FGAADCACHACHAHB,True +932,6.0,4.0,3.0,4.0,3.0,1.0,3.0,2.0,DGCABBECFGCBGAADHAEHAEDABD,False +933,9.0,5.0,1.0,9.0,8.0,8.0,7.0,8.0,EFBCBAHBDFADADEAFFGGDEHDEHDHAAEABBFEDHEDHGFHGFEGFGGADHA,False +934,4.0,7.0,1.0,3.0,1.0,1.0,4.0,5.0,AEBGGBGBHABDFGDBADBHHCHHBA,True +935,14.0,14.0,13.0,12.0,23.0,12.0,15.0,6.0,EDAGFAGECGAGGACEACGGEHGEHCEBCFBEGECGEDEECFCBFBAFADBBDFBGCEEBEEDCDDFHFHEFDBCEGABGAFDAFDABDAEEEHBEDBEFCEAAGBGHC,False +936,16.0,21.0,7.0,13.0,13.0,15.0,22.0,19.0,GFBGHEGBBAABABEAHHADCEHFAHFACEGBHHBEFGAGEAHADDGDFGDFDAGHCGFFGBFAFEGFHGAHADGBDHCDHEHEGDEGDCGBHGBCGBFEAHCGHEBDBBEBBFBHFBHFBDAGGB,False +937,24.0,12.0,20.0,15.0,16.0,11.0,15.0,24.0,HAECEECEEBBAGGADHAHCGHDDAGBFGAHEHCAABGAHGAFGADHEDGFDHADBBCABGABDDCCDBHBEEBEEHAHHAGHAHHDHCFCAHAACCDCGHCHFCHFCHFADGAHFAFFCCFEDEEBGECCACEHDG,False +938,3.0,5.0,0.0,6.0,7.0,6.0,5.0,5.0,DGBFHAFEFDHBDHBDGGGEEHBEHBFDEGAEFAEFD,False +939,22.0,26.0,26.0,14.0,18.0,22.0,25.0,26.0,ACFACFGFBAFBGBHHBDHBGGEAHFAHFAFEHGECCECCFAEGABGABEAHGBEGFHCHBBDBCHFDEFHEABEFCEBHEBHDBADACDEFBCHDGBBCCBCHBEHFCGFCGCEGCHHCHGAFCADDBHDGFFHBAGCACABCGDGGBFHDCBFGBFEEFHEHAGHGGHCCDAGDAGA,False +940,8.0,10.0,2.0,5.0,4.0,6.0,1.0,9.0,BGDEHABAADAFBAFHHFHHFHBAHDCEABDBBHEDHEBBFBAFC,True +941,29.0,18.0,34.0,25.0,27.0,21.0,24.0,19.0,DEDAEGFBGFBGCBFCHECFEFAGBABDCBEHHEHGADEHDFHFFCEAAEAFEAFCGGDGFEHEECGCCDCCECCDHFAHCACDGDBGFBCFADEABHABDABDHBGHGDADDADFCDAGFAGBBBECFCCECCEDGGDCDEGGAHHFEEAEACBDCDHCHEEAEACFAGDHFEGCAGHABDACHCCBCFGCAGEAC,False +942,22.0,23.0,26.0,28.0,25.0,25.0,28.0,22.0,HHDBFEGFEGCHBDEBHGCHGBDFHDBHFBHBGHCCECADHADGAGGCGCFDCFAFGDFAHGEDEEAEFDBCHBDHGHECFAFFAEFBGFHAFBGFAHFCCGHDBABEGBDBHFACAADAGDGECGEGGHCGFCFFEDFCCACEDDHDDEADECDGBBGBCHAEHEEFCBCCACGFBDFCDEADBGBEGBEGDEADEAD,False +943,10.0,5.0,3.0,10.0,7.0,4.0,2.0,3.0,DEBBHAGEABHDCADAADEEBCEFEDFADAADAGDABDCHDFFE,True +944,12.0,16.0,22.0,10.0,9.0,17.0,15.0,10.0,CBFHFFBDFBAGECGCCHCAHCFECDDFFDECBBCBBCBFCAFCFFEFABFGBEAHAGBGGCCGBADCADHDGBFGCEGCEGCGHFGCFEFBDHADACGABBHHDAHCGCE,False +945,14.0,9.0,10.0,9.0,9.0,9.0,8.0,11.0,GBHGAHFAHFBGGDDGCHFAAFACDEFDACDHCEEAHEAFCBHCBGFBAEBAEBAFCAHDAEGCHDEBAEFGDDCHBCH,False +946,25.0,17.0,25.0,19.0,25.0,14.0,14.0,31.0,ECDHCBBCFADECDCDBGDBECEEGEEGFAGHACFDHBEEBAFCCBAHBAGBEGBGFHHDHHAHHAHCFHFHAFHEFBGBAHBEDCEDCEHHAHEABAGGAEGACAFCADEEECDACHADECFCDDEHAEFAEFBBADEHHHHCDHCDHCEHGFHGHHBCCAADHAGCCD,False +947,9.0,11.0,9.0,14.0,8.0,14.0,11.0,13.0,AFGAFHBFDGCGGDFFBBDCBDHFDHCECGHDFHDCHGGHAEHCEAAEFDEFAAFBBDBFDBFDBHDBECBFCEGGHGAEDHGHHACDF,False +948,13.0,8.0,5.0,13.0,9.0,10.0,22.0,12.0,AGDCGDCEDGFHFEAAEAAHADGGGBGHFGHDGHDHCBHFGEGGHAEBEDFADEGGEGGAGFHCDABDHBGGAGGDDBDFBCFEFAHFABGH,False +949,21.0,23.0,21.0,26.0,19.0,22.0,10.0,18.0,AAAEAHBDFFHFCGEGBDFDFADHEDBEABCAGDDBHEHFBHFBHBAEGABDDFDFECEECBCABADBEDFEBECCHBBABBEBBHBEDDHGHCGHCGDEGDGDDEDDHDCHDFDBFHHHCFACEAFAACHACFECFDCFCFFAAFDABCCBCDFCAFGE,False +950,20.0,25.0,18.0,22.0,18.0,18.0,14.0,12.0,GEDGBHAHGAHGCCDAADBDEADBDDBFFHFBHFBACBFCAFADDCHCGEFBEABFFGGDBGBBEFCEFBDHBDHDEEFEADEDDFDDFDCBDHEDEEBEBAECCEBGBHCBHCEGFBBCBACAGCAEFGCFGCFBAAAAGCBHAAD,False 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+970,16.0,13.0,19.0,11.0,15.0,16.0,18.0,14.0,FGHFHAFEAGGHFBHEBABAFBGFDFHEEGEDAEBBEBDECAFAACCBCDACFHCAHCFHGHHGCBCFGHGHHADGDDCDBCECDBGDGEDGEFCCGHAGECGECGAGAAEAFFCFFCEBCB,False +971,4.0,3.0,0.0,5.0,2.0,3.0,5.0,1.0,DAGAHGDGBDEFAEFABFGDGBD,True +972,7.0,2.0,1.0,3.0,2.0,2.0,4.0,4.0,HCFDAHGAHABGADEHDEABGAFGA,True +973,2.0,6.0,7.0,4.0,4.0,5.0,7.0,4.0,FBGDEGHCGHAGBDGCEGCGCCFDCAHFBCFBHEBDFBE,False +974,17.0,19.0,14.0,32.0,17.0,26.0,26.0,16.0,EBDHBAEGEFDDBGDAGDHGFFBFDGGDAGAAEFAEFCEHCBCCAGCBDFBDFADHGDHEDAEBHFDHBDHBDGBGEBDCCDGCDFCEFBEGEFHAGHAGFAGFAHDDDDGDFGAEDEBDCHGGEEGDBCCHDGAFGHBGABDFFFCBFAEDDHCFFFFDFDHGGBF,False +975,8.0,18.0,16.0,11.0,10.0,10.0,17.0,15.0,EBFCBFCBCBBGFAFFCHFHHBDHBDBCEGDHGBGEBGDBDDHCDEBACCGHDGEFGAGCCGCCGAEHDCHECHGCDFFGGBGGBAHBFHADGAEHBBAEHCEHB,False +976,27.0,32.0,25.0,20.0,17.0,19.0,24.0,36.0,HCFABFDBGEFGFDCBDCAEBHEDADCADCGBCDACDBBHBBDAHAHHFFGEFHHBBHEFAEDHEHHBHHDAHCACCDDDAHCEECBBHBHHBGDBGBBGHCAHCFHFHGCHGAEGFFBBHCBHAAABACEGCGGCGACFACGHBDCBHCGGEHEBGAFFAEHHDFHDFEGFABDABGBBECBEBGAAFAACGHGHHGDH,False +977,21.0,23.0,33.0,29.0,26.0,21.0,26.0,19.0,BFCBCBEGFEGDEGFEBDACFGCDGADCDDCBBCGCDDCGCCGDDGBFBEEBAABAACFCCFHDDHDEBDEFCEBBGBEEDAEAHFCHFHHEBEEFFEFHEADEGEGGCGGADDFBCADDDCCGCCGCDGEDFADGDFGFFBCAAHAHEFHECAGFGDCEDCADBAHHHHEHHEFHBCCCCBBAABCAHHDGBEGCGG,False +978,7.0,8.0,10.0,5.0,10.0,5.0,5.0,1.0,DECDEBFCGFADFEBAECABABEGGECDFCGBEGCEHCBDCBCABCAEAFE,True +979,1.0,2.0,1.0,6.0,0.0,1.0,0.0,1.0,DCADFBDHDDBD,True +980,24.0,21.0,18.0,12.0,17.0,7.0,12.0,18.0,BBAHBHDDHBHFAHACBEBBCBAEEACHAHHEGBBGBCDCCAECAHCAGGAFFACFAHHEEAEHFGCACEACHFCHDDEDDEDDCBCCHEBHBAHEABBGBBADBGBBEAAGAADHEGEGGEGAFDACC,False +981,22.0,33.0,18.0,23.0,27.0,28.0,28.0,13.0,EAEDGBCFBAFBGFDAFAAGHAEBFHFFHFFGACDBDFCDFGDBEBBDHCFBEEGGDAGECGEFABFGBEDAEAHEGDDBEGCDABHBBGBDFBDHBGBBEBBHABAABDCEFGAFGAFBFCEFBGGHAGAFEDGEDCHFHBFGDHCFHCAGFDGCGECFECBECBECECABCAEFBEFEEGDBGDEGDBGD,False +982,22.0,20.0,15.0,16.0,27.0,17.0,27.0,21.0,GDFGHEGBEHCEBCHBEHBAHGCGGEGBBFDEADFFHADHEBHGDACDACDEBEEGEHBEGBEGHEBFAAFGFFGDFGDFABGHFHCEECHDGBDCBFFBGCBDDHDCGBCFAFHGGHEGACHECAEAAHCABAACAHEEDEADEFEGBGGEGAAGEBGFAHHAE,False +983,6.0,5.0,6.0,11.0,8.0,8.0,5.0,7.0,HBFHDFCEABBADECDEGDFCDFHBFEDECCFGHFAHGHHADEADFCDGDDGEBAE,False +984,9.0,13.0,13.0,13.0,32.0,25.0,15.0,18.0,EEAEEGEABEGHGFDADEEFAHHCBFGDCBBCHBCFDCFDCFDEFDEFCHFEFECFEHFHGFHGFHEBBCGECBDHHEEDEFCEGAADEFEHGEDFEHFEDFEGBHHFHGEEGEGAACFABFGFDGBEECEEFHBFHB,False +985,14.0,10.0,10.0,7.0,7.0,11.0,13.0,6.0,FAFAHGABAACAAGAFCDDCGCEFDBGBGACHECAECAEBAHDDFDBFDBFGBAGCHBEHBAGBECFFCEFGGGGGFH,False 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+991,18.0,26.0,30.0,28.0,39.0,25.0,17.0,17.0,ACBACBFFBACEFCFACFBDEBDEHCFHCDHEDAFCAFEAGEDGEGBEDEDGEFADCEDGECCCDFEDGEBEHBCFBCBDCBEFHDFAEECEFCEFBBFEBDEADEGEEAEEHEDFADGDHGBBACBGHFGHABBACCDCCECGECDHHHAEBBHBHGBCFFAEDDGFDEBHEBFEHCCFDGEDCDCHEBDEGDEGFFCA,False +992,19.0,14.0,13.0,21.0,20.0,19.0,18.0,15.0,GGFGDFGACGCFHCEHFECCAGBDFBDGADCDEBHFBHDAHEHCBHBEDBEDFADBHDFDEBDEGAAHAAEFAEFGEFGDFGEHAEDCDDHGDHDFADFEEAEBADBCHCHGCAGEGGFDEFEFGAAACACFHBGBBEF,False +993,25.0,22.0,19.0,27.0,20.0,17.0,20.0,31.0,GHDGEDGEGAEGFEHDBHDEFDEACEAGEHFDFFDFFHGEADEBHGHDDBDGBAEFCHCBHGBADBDFCHCABGDCDDHEDHDCBBAHACHGHHEAHBAHBCHAHBGHEDDEAHEDCGCCDAHAFHFBBABBHBFHBAGBCGBFFHFEGEEACCAGCABFAGGADHCDHCDHAHADDACEF,False +994,11.0,8.0,14.0,13.0,20.0,15.0,19.0,10.0,DHBGHCGCCAFEBGCDAEGAEGADDAGEEBEGBEGDFGHECFACFHEEBEECCEBDAGFBFEGHEGDABCEEGEAGDDHCAHCGHFGDDEFHEFHFFCFGCFGFAGFDCD,False +995,4.0,5.0,0.0,4.0,3.0,4.0,11.0,4.0,HGFEAHEADDGFGGFHGFBGBGGBGBBHAGGDDAE,True 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it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/src/main/scala/org/xcit/nback/markov/models/State.scala b/src/main/scala/org/xcit/nback/markov/models/State.scala deleted file mode 100644 index fbbd844..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/State.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * A Single state with a label in Markov chain - * @param label A simple string label, representing the state and node - */ -class State(val label: String) { - - /** - * Keep track of transitions from this state to other states. - */ - val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() -} diff --git a/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/src/main/scala/org/xcit/nback/markov/models/Transition.scala deleted file mode 100644 index bc20a9e..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/Transition.scala +++ /dev/null @@ -1,8 +0,0 @@ -package org.xcit.nback.markov.models - -/** - * A Single transition in Markov chain graph. It is stored in "from" node. - * @param to the ending node of the edge - * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). - */ -case class Transition(to: State, probability: Double = 0.0) diff --git a/src/test/scala/ThreeBackBenchmark.scala b/src/test/scala/ThreeBackBenchmark.scala deleted file mode 100644 index 0c7dad9..0000000 --- a/src/test/scala/ThreeBackBenchmark.scala +++ /dev/null @@ -1,7 +0,0 @@ - -/** - * TODO Benchmark 3-back simple sequence generator - */ -class ThreeBackBenchmark { - -} diff --git a/tests/benchmark_diagrams.py b/tests/benchmark_diagrams.py new file mode 100644 index 0000000..8fa448e --- /dev/null +++ b/tests/benchmark_diagrams.py @@ -0,0 +1,159 @@ +import pandas as pd +import numpy as np +from matplotlib import pyplot as plt + +import benchmarks.common as common + + +def tlratio(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2,ignore_index=True) + stats = [] + for trials in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == trials) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == trials) + targets2 = data[alg2].targets if alg2.shape[0] > 0 else np.nan + targets4 = data[alg4].targets if alg4.shape[0] > 0 else np.nan + lures2 = data[alg2].lures if alg2.shape[0] > 0 else np.nan + lures4 = data[alg4].lures if alg4.shape[0] > 0 else np.nan + stats.append([trials, (targets2/lures2).mean(), (targets4/lures4).mean()]) + stats = pd.DataFrame(stats, columns=['trials', 'tl2', 'tl4']) #.dropna(subset=['skewness']) + + plt.style.use('ggplot') + + plt.ylim(bottom=0, top=30) + plt.scatter(stats.trials, stats.tl2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl2[idx], 1)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.tl4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl4[idx], 2)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('T:L Ratio') + plt.ylabel('T:L Ratio') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_tlratio.png', bbox_inches='tight') + plt.show() + + +def time_per_trial(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for t in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == t) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == t) + time2 = data[alg2].time.mean() * 1000 if alg2.shape[0] > 0 else np.nan + time4 = data[alg4].time.mean() * 1000 if alg4.shape[0] > 0 else np.nan + stats.append([t, time2, time4]) + stats = pd.DataFrame(stats, columns=['trials', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.trials, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time2[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time4[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2v4_time_trials.png', bbox_inches='tight') + plt.show() + +def time_profiles(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 8): + alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + time2 = data[alg2].time.mean() * 1000 + time4 = data[alg4].time.mean() * 1000 + stats.append([ni, time2, time4]) + stats = pd.DataFrame(stats, columns=['n', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.n, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.time2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + plt.scatter(stats.n, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.time4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_time_n.png', bbox_inches='tight') + plt.show() + +def skewness(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 9): + all_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + skewed_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) & data.skewed + all_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + skewed_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) & data.skewed + num_of_sequences2 = data[all_alg2].shape[0] + skewed_sequences2 = data[skewed_alg2].shape[0] + num_of_sequences4 = data[all_alg4].shape[0] + skewed_sequences4 = data[skewed_alg4].shape[0] + skewness2 = skewed_sequences2 * 100.0 / num_of_sequences2 if (num_of_sequences2>0) else 0 + skewness4 = skewed_sequences4 * 100.0 / num_of_sequences4 if (num_of_sequences4>0) else 0 + stats.append([ni, skewness2, skewness4]) + stats = pd.DataFrame(stats, columns=['n', 'skewness2', 'skewness4']) #.dropna(subset=['skewness']) + + + plt.style.use('ggplot') + plt.scatter(stats.n, stats.skewness2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.skewness2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + + plt.scatter(stats.n, stats.skewness4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.skewness4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Skewness') + plt.ylabel('Skewed Blocks (%)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_skewness.png', bbox_inches='tight') + plt.show() + +if __name__ == "__main__": + tlratio() + skewness() + time_profiles() + time_per_trial() diff --git a/tests/benchmark_skewness.py b/tests/benchmark_skewness.py new file mode 100644 index 0000000..f468b4d --- /dev/null +++ b/tests/benchmark_skewness.py @@ -0,0 +1,97 @@ +import random +import heapq +import csv + +# Common parameters +alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'] +trials_range = (10, 40) +n = 3 +sample_size = 100 + + +def to_benchmark_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [str(ralph_skewed)] + +def benchmark_nb_gm_001(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_001') + + +def benchmark_nb_gm_002(filename): + import generators.nb_gm_002 as nb_gm_002 + + generator = nb_gm_002.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + # print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_002') + + +def benchmark_nb_gm_003(filename): + import generators.nb_gm_003 as nb_gm_003 + + generator = nb_gm_003.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + print(f"sequence {i}/{sample_size}: {trials} trials") + seq = generator.generate(trials) + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_003') + + +def show_skweness_diagram(filename, choices, title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + print(filename) + data = pd.read_csv(filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) #.dropna(subset=['skewness']) + #print(stats.trials) + #plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'{title}.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + benchmark_nb_gm_003('../benchmarks/nb_gm_003_2back.csv') diff --git a/tests/common.py b/tests/common.py new file mode 100644 index 0000000..e40c0df --- /dev/null +++ b/tests/common.py @@ -0,0 +1,27 @@ + + +# Common benchmark parameters +choices = alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F'] +trials_range = (10, 65) +n = 4 +sample_size = 100 + + +def count_targets_and_lures(seq, n): + mask = 'D'*n + for index in range(n, len(seq)): + if seq[index] == seq[index - n]: + mask += 'T' + elif seq[index] in seq[index - n - 1:index - n + 1]: + mask += 'L' + else: + mask += 'D' + return mask.count('T'), mask.count('L') + + +def skewness(seq, choices): + import heapq + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return ralph_skewed diff --git a/tests/nb_gm_001_bm.py b/tests/nb_gm_001_bm.py new file mode 100644 index 0000000..54f6cb3 --- /dev/null +++ b/tests/nb_gm_001_bm.py @@ -0,0 +1,75 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq) , str(ralph_skewed)] + + +def benchmark(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets / s.trials, axis=1) + plt.scatter(data.trials, data.targets_ratio, alpha=0.2) + plt.show() + +if __name__ == '__main__': + alg = 'nb_gm_001' + fn = f'results/{alg}_{n}back.csv' + benchmark(fn) + # skewness_diagram(fn, alg) + targets_ratio_diagram(fn, alg) diff --git a/tests/nb_gm_002_bm.py b/tests/nb_gm_002_bm.py new file mode 100644 index 0000000..c8af543 --- /dev/null +++ b/tests/nb_gm_002_bm.py @@ -0,0 +1,105 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq), str(ralph_skewed)] + + +def benchmark(filename): + from generators.nb_gm_002 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials, int(trials/3), 0, 0) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +import time +import numpy as np +import pandas as pd + +import benchmarks.common as common + +def profile(): + from generators.nb_gm_002 import SequenceGenerator + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, int(lures/2), int(lures/2)) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('benchmarks/results/nb_gm_002_profile.csv', sep=',', encoding='utf-8') + +if __name__ == '__main__': + alg = 'nb_gm_002' + fn = f'results/{alg}_{n}back.csv' + profile() diff --git a/tests/nb_gm_003_bm.py b/tests/nb_gm_003_bm.py new file mode 100644 index 0000000..fa6c19a --- /dev/null +++ b/tests/nb_gm_003_bm.py @@ -0,0 +1,114 @@ +import heapq +import csv +import random +import time + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq, time_per_block): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [time_per_block, ''.join(seq), str(ralph_skewed)] + + +def benchmark_skewness(filename): + from generators.nb_gm_003 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['time_per_block', 'seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + targets = trials / 3 + t = time.time() + seq = generator.generate(trials, targets) + t = time.time() - t + print(f"sequence {i}/{sample_size}: {trials} trials, took {t}s.") + writer.writerow(to_csv_row(i, seq, t)) + plot_skewness(fn, 'nb_gm_003') + + +def plot_skewness(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def plot_targets_ratio(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +def benchmark_targets_ratio(): + pass + +def benchmark_chunking(): + pass + + +def benchmark_n(): + pass + + +def plot_timing(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['time_per_trial'] = data.apply(lambda s: s.time_per_block / s.trials, axis=1) + plt.style.use('ggplot') + plt.title(f"{figure_title} - average time to generate a trial") + plt.ylabel('time (s)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.time_per_trial, alpha=0.5) + + # draw fitted curve + # import numpy as np + # p = np.poly1d(np.polyfit(data.trials, data.time_per_trial, 3)) + # plt.plot(data.trials, p(data.trials), color='red') + + plt.savefig(f'results/{figure_title}_timing.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + alg = 'nb_gm_003' + fn = f'results/{alg}_{n}back.csv' + benchmark_skewness(fn) diff --git a/tests/nb_gm_004_bm.py b/tests/nb_gm_004_bm.py new file mode 100644 index 0000000..b4ad4a8 --- /dev/null +++ b/tests/nb_gm_004_bm.py @@ -0,0 +1,26 @@ +import time +import numpy as np +import pandas as pd + +import tests.common as common +from generators.nb_gm_004 import SequenceGenerator + +def run(): + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, lures) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('tests/results/nb_gm_004_profile.csv', sep=',', encoding='utf-8') diff --git a/tests/results/2v4_time_trials.png b/tests/results/2v4_time_trials.png new file mode 100644 index 0000000..9be91b4 --- /dev/null +++ b/tests/results/2v4_time_trials.png Binary files differ diff --git a/tests/results/2vs4_skewness.png b/tests/results/2vs4_skewness.png new file mode 100644 index 0000000..a488e1f --- /dev/null +++ b/tests/results/2vs4_skewness.png Binary files differ diff --git a/tests/results/2vs4_time_n.png b/tests/results/2vs4_time_n.png new file mode 100644 index 0000000..d022ed0 --- /dev/null +++ b/tests/results/2vs4_time_n.png Binary files differ diff --git a/tests/results/2vs4_tlratio.png b/tests/results/2vs4_tlratio.png new file mode 100644 index 0000000..b76f296 --- /dev/null +++ b/tests/results/2vs4_tlratio.png Binary files differ diff --git a/tests/results/nb_gm_001_2back.csv b/tests/results/nb_gm_001_2back.csv new file mode 100644 index 0000000..f6ad25e --- /dev/null +++ b/tests/results/nb_gm_001_2back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,0.0,1.0,0.0,55.0,56.0,0.0,0.0,0.0,BEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +1,0.0,94.0,0.0,94.0,0.0,0.0,0.0,1.0,HDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +2,0.0,96.0,95.0,1.0,0.0,0.0,0.0,0.0,DBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +3,0.0,9.0,0.0,1.0,9.0,0.0,0.0,0.0,DBEBEBEBEBEBEBEBEBE,True +4,1.0,80.0,0.0,0.0,80.0,0.0,0.0,0.0,ABEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True +5,0.0,0.0,0.0,66.0,0.0,0.0,65.0,1.0,HDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +6,0.0,0.0,0.0,0.0,0.0,0.0,0.0,57.0,HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +7,1.0,0.0,0.0,0.0,0.0,20.0,0.0,21.0,AHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +8,0.0,21.0,21.0,0.0,0.0,0.0,1.0,0.0,GBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +9,0.0,0.0,0.0,1.0,25.0,0.0,0.0,24.0,DEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +10,0.0,0.0,64.0,0.0,0.0,0.0,1.0,64.0,GCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +11,0.0,0.0,0.0,0.0,0.0,0.0,41.0,41.0,HGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +12,14.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,AAAAAAAAAAAAAA,True +13,0.0,1.0,0.0,0.0,77.0,0.0,78.0,0.0,BGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +14,0.0,1.0,0.0,145.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +15,0.0,0.0,58.0,60.0,0.0,0.0,0.0,0.0,DDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +16,1.0,0.0,0.0,73.0,0.0,0.0,0.0,73.0,ADHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +17,47.0,1.0,0.0,0.0,0.0,0.0,48.0,0.0,BGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +18,92.0,91.0,0.0,1.0,0.0,0.0,0.0,0.0,DABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +19,0.0,0.0,0.0,0.0,44.0,0.0,0.0,0.0,EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True 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+26,0.0,75.0,0.0,0.0,0.0,0.0,75.0,0.0,BGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +27,0.0,0.0,54.0,0.0,0.0,0.0,0.0,53.0,CCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +28,1.0,0.0,0.0,10.0,0.0,10.0,0.0,0.0,ADFDFDFDFDFDFDFDFDFDF,True +29,0.0,1.0,40.0,0.0,0.0,0.0,0.0,41.0,BHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +30,15.0,0.0,16.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACAC,True +31,0.0,0.0,80.0,0.0,0.0,0.0,0.0,81.0,HCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +32,60.0,0.0,0.0,60.0,0.0,0.0,1.0,0.0,GADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +33,0.0,0.0,0.0,0.0,33.0,0.0,0.0,35.0,HHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +34,0.0,0.0,0.0,0.0,89.0,88.0,0.0,0.0,EFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +35,0.0,0.0,0.0,1.0,27.0,27.0,0.0,0.0,DEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +36,0.0,0.0,23.0,0.0,23.0,0.0,1.0,0.0,GECECECECECECECECECECECECECECECECECECECECECECEC,True +37,0.0,1.0,0.0,0.0,85.0,0.0,0.0,86.0,BHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +38,22.0,0.0,0.0,0.0,0.0,0.0,1.0,21.0,GAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +39,0.0,96.0,0.0,0.0,0.0,0.0,1.0,95.0,GBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +40,0.0,10.0,0.0,0.0,0.0,0.0,1.0,10.0,GHBHBHBHBHBHBHBHBHBHB,True +41,0.0,0.0,30.0,31.0,0.0,0.0,1.0,0.0,GDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +42,0.0,0.0,0.0,1.0,48.0,49.0,0.0,0.0,DFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +43,0.0,65.0,0.0,1.0,0.0,65.0,0.0,0.0,DFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +44,11.0,0.0,0.0,11.0,1.0,0.0,0.0,0.0,EDADADADADADADADADADADA,True +45,35.0,0.0,1.0,34.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True 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+64,0.0,0.0,0.0,1.0,0.0,199.0,0.0,0.0,DFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +65,0.0,0.0,0.0,1.0,0.0,13.0,0.0,0.0,DFFFFFFFFFFFFF,True +66,0.0,84.0,0.0,0.0,0.0,84.0,0.0,0.0,FBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +67,48.0,0.0,1.0,0.0,0.0,0.0,0.0,48.0,CAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +68,0.0,0.0,0.0,49.0,0.0,48.0,0.0,0.0,DDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDF,True +69,0.0,48.0,1.0,0.0,47.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True 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+145,0.0,86.0,0.0,0.0,0.0,0.0,85.0,1.0,HBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +146,0.0,0.0,1.0,0.0,0.0,33.0,0.0,32.0,CFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +147,0.0,11.0,0.0,0.0,0.0,0.0,0.0,12.0,HHBHBHBHBHBHBHBHBHBHBHB,True +148,0.0,56.0,0.0,0.0,0.0,0.0,0.0,56.0,BHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +149,0.0,0.0,83.0,0.0,1.0,0.0,83.0,0.0,EGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +150,0.0,78.0,1.0,0.0,0.0,77.0,0.0,0.0,CBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True 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+159,0.0,62.0,0.0,0.0,0.0,0.0,62.0,0.0,GBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +160,0.0,0.0,0.0,1.0,0.0,0.0,0.0,88.0,DHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +161,1.0,7.0,0.0,0.0,8.0,0.0,0.0,0.0,AEBEBEBEBEBEBEBE,True +162,14.0,0.0,0.0,14.0,0.0,0.0,0.0,0.0,DADADADADADADADADADADADADADA,True +163,0.0,0.0,1.0,0.0,51.0,0.0,0.0,50.0,CEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +164,68.0,0.0,0.0,0.0,0.0,68.0,0.0,0.0,FAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +165,0.0,0.0,72.0,0.0,0.0,1.0,72.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +166,0.0,0.0,0.0,1.0,0.0,0.0,29.0,28.0,DGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +167,0.0,0.0,0.0,111.0,0.0,0.0,0.0,0.0,DDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +168,0.0,1.0,0.0,73.0,73.0,0.0,0.0,0.0,BEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +169,0.0,1.0,0.0,0.0,67.0,66.0,0.0,0.0,BEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +170,17.0,0.0,0.0,1.0,0.0,16.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +171,37.0,1.0,0.0,37.0,0.0,0.0,0.0,0.0,BADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +172,0.0,79.0,1.0,79.0,0.0,0.0,0.0,0.0,CBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +173,0.0,0.0,0.0,0.0,35.0,0.0,0.0,0.0,EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +174,0.0,0.0,0.0,0.0,1.0,40.0,0.0,39.0,EFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +175,0.0,0.0,85.0,1.0,0.0,0.0,0.0,85.0,DHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +176,0.0,25.0,1.0,0.0,0.0,0.0,0.0,0.0,CBBBBBBBBBBBBBBBBBBBBBBBBB,True +177,0.0,18.0,17.0,0.0,0.0,0.0,0.0,1.0,HBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +178,0.0,1.0,0.0,0.0,0.0,0.0,0.0,125.0,BHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +179,0.0,0.0,0.0,77.0,76.0,0.0,0.0,0.0,DDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +180,1.0,0.0,0.0,0.0,0.0,19.0,20.0,0.0,AGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFG,True +181,0.0,1.0,92.0,0.0,0.0,0.0,0.0,92.0,BCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +182,0.0,0.0,0.0,0.0,1.0,50.0,50.0,0.0,EGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +183,0.0,0.0,0.0,37.0,0.0,1.0,0.0,0.0,FDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +184,80.0,0.0,1.0,0.0,0.0,81.0,0.0,0.0,CFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +185,0.0,0.0,0.0,16.0,16.0,0.0,0.0,0.0,DEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +186,0.0,16.0,0.0,0.0,0.0,15.0,0.0,1.0,HBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +187,7.0,0.0,0.0,0.0,8.0,1.0,0.0,0.0,FEAEAEAEAEAEAEAE,True +188,0.0,21.0,0.0,0.0,0.0,0.0,1.0,21.0,GHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +189,0.0,0.0,0.0,0.0,29.0,29.0,0.0,0.0,EFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +190,63.0,0.0,0.0,0.0,0.0,63.0,0.0,0.0,FAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +191,8.0,0.0,8.0,0.0,0.0,0.0,1.0,0.0,GACACACACACACACAC,True +192,69.0,1.0,0.0,0.0,0.0,0.0,0.0,70.0,BHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +193,0.0,42.0,0.0,41.0,0.0,0.0,1.0,0.0,GBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +194,91.0,0.0,93.0,0.0,0.0,0.0,0.0,0.0,CCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +195,0.0,16.0,0.0,0.0,0.0,1.0,16.0,0.0,FGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +196,0.0,0.0,1.0,0.0,0.0,72.0,72.0,0.0,CFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFG,True +197,0.0,0.0,0.0,0.0,85.0,0.0,0.0,86.0,HHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +198,0.0,0.0,0.0,0.0,57.0,57.0,1.0,0.0,GFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +199,76.0,0.0,0.0,0.0,0.0,1.0,0.0,76.0,FHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +200,0.0,1.0,0.0,31.0,0.0,0.0,31.0,0.0,BGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +201,0.0,0.0,34.0,1.0,35.0,0.0,0.0,0.0,DECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +202,0.0,0.0,76.0,0.0,1.0,0.0,75.0,0.0,ECGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +203,0.0,88.0,0.0,0.0,0.0,88.0,0.0,1.0,HBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +204,0.0,0.0,0.0,0.0,0.0,0.0,84.0,85.0,HHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +205,0.0,0.0,81.0,0.0,0.0,0.0,81.0,0.0,GCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +206,0.0,0.0,0.0,0.0,70.0,70.0,0.0,1.0,HEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +207,0.0,0.0,0.0,57.0,1.0,0.0,56.0,0.0,EDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +208,0.0,1.0,0.0,53.0,0.0,0.0,52.0,0.0,BDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +209,0.0,0.0,0.0,0.0,12.0,0.0,11.0,1.0,HEGEGEGEGEGEGEGEGEGEGEGE,True +210,87.0,0.0,0.0,88.0,1.0,0.0,0.0,0.0,EDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +211,0.0,0.0,12.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCC,True +212,0.0,0.0,0.0,66.0,0.0,65.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +213,1.0,0.0,0.0,0.0,0.0,21.0,22.0,0.0,AGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFG,True +214,74.0,73.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +215,0.0,5.0,0.0,0.0,6.0,0.0,0.0,1.0,HEBEBEBEBEBE,True +216,0.0,1.0,0.0,0.0,0.0,53.0,0.0,54.0,BHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +217,70.0,0.0,0.0,0.0,0.0,70.0,0.0,0.0,AFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +218,0.0,0.0,0.0,0.0,0.0,0.0,36.0,35.0,GGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +219,0.0,90.0,90.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +220,0.0,0.0,0.0,0.0,0.0,0.0,37.0,38.0,HHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +221,0.0,0.0,44.0,0.0,0.0,1.0,44.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +222,0.0,0.0,0.0,67.0,67.0,0.0,0.0,1.0,HDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +223,6.0,0.0,0.0,0.0,5.0,1.0,0.0,0.0,FAEAEAEAEAEA,True +224,0.0,38.0,0.0,38.0,0.0,0.0,1.0,0.0,GBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +225,0.0,0.0,0.0,128.0,1.0,0.0,0.0,0.0,EDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +226,0.0,90.0,0.0,89.0,1.0,0.0,0.0,0.0,EBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +227,0.0,51.0,0.0,1.0,0.0,0.0,0.0,52.0,DHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +228,0.0,0.0,7.0,0.0,0.0,0.0,8.0,1.0,HGCGCGCGCGCGCGCG,True +229,18.0,0.0,0.0,0.0,0.0,0.0,1.0,18.0,GHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True 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+384,0.0,0.0,28.0,0.0,1.0,0.0,0.0,28.0,ECHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +385,0.0,1.0,119.0,0.0,0.0,0.0,0.0,0.0,BCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +386,0.0,0.0,93.0,0.0,0.0,93.0,1.0,0.0,GCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCF,True +387,92.0,0.0,1.0,0.0,92.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +388,0.0,186.0,0.0,0.0,0.0,0.0,0.0,0.0,BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True 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+396,65.0,0.0,0.0,0.0,0.0,1.0,0.0,65.0,FAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +397,0.0,0.0,0.0,55.0,56.0,0.0,0.0,0.0,EEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +398,26.0,0.0,0.0,25.0,1.0,0.0,0.0,0.0,EADADADADADADADADADADADADADADADADADADADADADADADADADA,True +399,0.0,0.0,60.0,0.0,0.0,0.0,1.0,59.0,GCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +400,1.0,0.0,0.0,0.0,160.0,0.0,0.0,0.0,AEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +401,1.0,0.0,31.0,0.0,0.0,31.0,0.0,0.0,AFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +402,0.0,0.0,0.0,15.0,1.0,0.0,0.0,0.0,EDDDDDDDDDDDDDDD,True +403,0.0,0.0,0.0,54.0,55.0,0.0,0.0,1.0,HEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +404,0.0,0.0,0.0,27.0,0.0,27.0,0.0,1.0,HFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +405,0.0,0.0,0.0,1.0,0.0,15.0,0.0,15.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +406,0.0,95.0,0.0,94.0,0.0,1.0,0.0,0.0,FBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +407,0.0,0.0,15.0,14.0,0.0,0.0,0.0,0.0,CCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +408,78.0,78.0,0.0,0.0,0.0,0.0,1.0,0.0,GBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +409,0.0,0.0,72.0,1.0,0.0,0.0,72.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +410,55.0,0.0,1.0,0.0,0.0,0.0,55.0,0.0,CAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +411,0.0,59.0,0.0,0.0,0.0,60.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +412,61.0,0.0,0.0,61.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +413,0.0,1.0,0.0,75.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +414,0.0,53.0,0.0,0.0,0.0,0.0,52.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +415,0.0,0.0,16.0,0.0,1.0,0.0,0.0,15.0,ECHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +416,0.0,0.0,0.0,39.0,0.0,0.0,0.0,38.0,DHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +417,96.0,0.0,1.0,95.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +418,28.0,0.0,1.0,27.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +419,0.0,1.0,92.0,92.0,0.0,0.0,0.0,0.0,BCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +420,1.0,0.0,20.0,0.0,20.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECE,True +421,0.0,90.0,0.0,0.0,0.0,0.0,89.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +422,10.0,0.0,0.0,0.0,0.0,1.0,11.0,0.0,FGAGAGAGAGAGAGAGAGAGAG,True +423,0.0,0.0,0.0,74.0,73.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +424,0.0,0.0,127.0,0.0,0.0,0.0,1.0,0.0,GCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +425,1.0,9.0,0.0,0.0,0.0,9.0,0.0,0.0,AFBFBFBFBFBFBFBFBFB,True +426,0.0,0.0,84.0,0.0,0.0,0.0,0.0,84.0,HCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +427,33.0,0.0,0.0,34.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +428,1.0,30.0,0.0,30.0,0.0,0.0,0.0,0.0,ABDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +429,0.0,0.0,67.0,0.0,1.0,67.0,0.0,0.0,EFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +430,62.0,0.0,0.0,63.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +431,1.0,9.0,9.0,0.0,0.0,0.0,0.0,0.0,ABCBCBCBCBCBCBCBCBC,True +432,15.0,0.0,0.0,0.0,0.0,0.0,14.0,0.0,AAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +433,0.0,1.0,0.0,65.0,66.0,0.0,0.0,0.0,BEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +434,0.0,160.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +435,0.0,0.0,1.0,0.0,42.0,42.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +436,0.0,0.0,55.0,0.0,55.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +437,0.0,0.0,0.0,1.0,0.0,73.0,0.0,73.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +438,79.0,0.0,0.0,0.0,78.0,0.0,0.0,0.0,AAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +439,0.0,0.0,67.0,0.0,0.0,0.0,66.0,1.0,HCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +440,0.0,0.0,77.0,0.0,0.0,1.0,0.0,76.0,FCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +441,0.0,0.0,0.0,0.0,153.0,0.0,0.0,1.0,HEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +442,0.0,88.0,88.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +443,0.0,0.0,0.0,20.0,22.0,0.0,0.0,0.0,EEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +444,41.0,0.0,42.0,0.0,0.0,0.0,1.0,0.0,GCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +445,0.0,0.0,0.0,47.0,0.0,46.0,0.0,1.0,HDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +446,1.0,0.0,0.0,0.0,86.0,0.0,0.0,87.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +447,56.0,56.0,0.0,0.0,0.0,0.0,0.0,1.0,HABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +448,0.0,0.0,0.0,0.0,11.0,0.0,0.0,10.0,EEHEHEHEHEHEHEHEHEHEH,True +449,0.0,0.0,0.0,0.0,0.0,1.0,92.0,92.0,FGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +450,0.0,0.0,0.0,6.0,5.0,1.0,0.0,0.0,FDEDEDEDEDED,True +451,66.0,1.0,67.0,0.0,0.0,0.0,0.0,0.0,BCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +452,0.0,0.0,0.0,13.0,0.0,1.0,12.0,0.0,FDGDGDGDGDGDGDGDGDGDGDGDGD,True +453,1.0,0.0,0.0,0.0,56.0,0.0,56.0,0.0,AEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +454,15.0,0.0,0.0,0.0,0.0,0.0,0.0,16.0,HAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +455,0.0,21.0,1.0,0.0,21.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True +456,93.0,0.0,1.0,0.0,92.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +457,1.0,0.0,0.0,0.0,35.0,0.0,0.0,35.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +458,13.0,0.0,0.0,0.0,1.0,0.0,13.0,0.0,EAGAGAGAGAGAGAGAGAGAGAGAGAG,True +459,0.0,0.0,65.0,0.0,1.0,0.0,65.0,0.0,ECGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +460,0.0,0.0,95.0,1.0,0.0,95.0,0.0,0.0,DFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +461,15.0,0.0,0.0,0.0,1.0,0.0,0.0,15.0,EHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +462,0.0,0.0,198.0,0.0,1.0,0.0,0.0,0.0,ECCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +463,84.0,84.0,0.0,0.0,1.0,0.0,0.0,0.0,EABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +464,0.0,0.0,0.0,0.0,0.0,60.0,0.0,61.0,HFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +465,0.0,179.0,0.0,1.0,0.0,0.0,0.0,0.0,DBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +466,1.0,0.0,90.0,0.0,89.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +467,0.0,35.0,0.0,0.0,0.0,34.0,0.0,0.0,BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +468,0.0,0.0,0.0,1.0,7.0,0.0,0.0,7.0,DHEHEHEHEHEHEHE,True +469,0.0,0.0,0.0,0.0,92.0,0.0,91.0,0.0,EEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +470,0.0,0.0,46.0,0.0,0.0,1.0,46.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +471,0.0,0.0,0.0,0.0,0.0,1.0,158.0,0.0,FGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +472,1.0,0.0,0.0,0.0,0.0,58.0,0.0,59.0,AHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +473,0.0,0.0,6.0,1.0,0.0,0.0,6.0,0.0,DCGCGCGCGCGCG,True 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+766,56.0,0.0,0.0,0.0,56.0,0.0,0.0,0.0,EAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +767,73.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,BAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +768,0.0,47.0,0.0,0.0,0.0,47.0,0.0,0.0,FBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +769,76.0,0.0,1.0,0.0,0.0,0.0,76.0,0.0,CAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +770,43.0,43.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +771,0.0,0.0,0.0,0.0,1.0,80.0,0.0,0.0,EFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +772,0.0,68.0,0.0,0.0,0.0,0.0,0.0,67.0,BBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +773,60.0,1.0,0.0,0.0,0.0,61.0,0.0,0.0,BFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +774,0.0,1.0,0.0,57.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +775,0.0,78.0,0.0,0.0,1.0,0.0,0.0,0.0,EBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +776,1.0,0.0,0.0,0.0,0.0,96.0,96.0,0.0,AGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +777,43.0,0.0,0.0,0.0,0.0,1.0,44.0,0.0,FGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +778,0.0,0.0,49.0,0.0,50.0,0.0,0.0,1.0,HECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +779,0.0,0.0,0.0,118.0,0.0,0.0,0.0,1.0,HDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +780,0.0,80.0,79.0,0.0,0.0,0.0,0.0,0.0,BCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +781,77.0,0.0,0.0,0.0,0.0,0.0,78.0,1.0,HGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +782,1.0,0.0,0.0,62.0,61.0,0.0,0.0,0.0,ADEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +783,0.0,0.0,0.0,0.0,0.0,10.0,10.0,1.0,HGFGFGFGFGFGFGFGFGFGF,True +784,0.0,0.0,18.0,1.0,17.0,0.0,0.0,0.0,DCECECECECECECECECECECECECECECECECEC,True +785,0.0,1.0,0.0,0.0,67.0,0.0,67.0,0.0,BGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +786,0.0,0.0,0.0,48.0,0.0,0.0,48.0,1.0,HGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +787,0.0,0.0,1.0,0.0,47.0,0.0,0.0,47.0,CEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +788,0.0,28.0,0.0,0.0,1.0,0.0,29.0,0.0,EGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +789,0.0,11.0,0.0,0.0,0.0,11.0,0.0,1.0,HBFBFBFBFBFBFBFBFBFBFBF,True +790,0.0,0.0,0.0,10.0,9.0,0.0,0.0,1.0,HDEDEDEDEDEDEDEDEDED,True +791,0.0,0.0,1.0,0.0,73.0,0.0,0.0,73.0,CHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True 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+798,0.0,0.0,0.0,0.0,0.0,126.0,0.0,0.0,FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +799,1.0,0.0,20.0,20.0,0.0,0.0,0.0,0.0,ADCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +800,1.0,0.0,0.0,0.0,66.0,0.0,0.0,66.0,AEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +801,0.0,0.0,0.0,67.0,0.0,1.0,66.0,0.0,FDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +802,0.0,0.0,0.0,41.0,0.0,0.0,0.0,42.0,HDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +803,1.0,0.0,81.0,0.0,82.0,0.0,0.0,0.0,AECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +804,0.0,1.0,74.0,0.0,0.0,0.0,75.0,0.0,BGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +805,0.0,57.0,58.0,0.0,0.0,0.0,0.0,0.0,CCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +806,45.0,44.0,0.0,0.0,1.0,0.0,0.0,0.0,EABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +807,0.0,0.0,65.0,0.0,0.0,0.0,66.0,0.0,GGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +808,18.0,0.0,0.0,0.0,19.0,1.0,0.0,0.0,FEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +809,0.0,65.0,0.0,64.0,1.0,0.0,0.0,0.0,EBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +810,77.0,0.0,0.0,0.0,77.0,1.0,0.0,0.0,FEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +811,38.0,0.0,38.0,0.0,0.0,0.0,1.0,0.0,GCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +812,0.0,0.0,17.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCCCCCCC,True +813,0.0,0.0,0.0,0.0,191.0,0.0,1.0,0.0,GEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +814,0.0,0.0,0.0,0.0,0.0,0.0,88.0,87.0,GHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +815,78.0,0.0,0.0,0.0,80.0,0.0,0.0,0.0,EEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +816,0.0,34.0,1.0,0.0,0.0,0.0,0.0,0.0,CBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +817,0.0,0.0,71.0,1.0,0.0,0.0,71.0,0.0,DGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +818,0.0,1.0,194.0,0.0,0.0,0.0,0.0,0.0,BCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +819,0.0,0.0,65.0,0.0,1.0,0.0,0.0,0.0,ECCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +820,0.0,0.0,1.0,0.0,0.0,0.0,68.0,68.0,CHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +821,1.0,0.0,0.0,64.0,0.0,65.0,0.0,0.0,AFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDF,True +822,0.0,0.0,0.0,0.0,1.0,0.0,12.0,11.0,EGHGHGHGHGHGHGHGHGHGHGHG,True +823,39.0,0.0,0.0,1.0,39.0,0.0,0.0,0.0,DEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +824,79.0,0.0,0.0,79.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +825,0.0,0.0,0.0,9.0,0.0,0.0,9.0,1.0,HDGDGDGDGDGDGDGDGDG,True +826,1.0,193.0,0.0,0.0,0.0,0.0,0.0,0.0,ABBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +827,0.0,1.0,48.0,0.0,0.0,0.0,48.0,0.0,BGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +828,0.0,31.0,0.0,32.0,0.0,0.0,0.0,0.0,DBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +829,79.0,78.0,0.0,1.0,0.0,0.0,0.0,0.0,DABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +830,0.0,0.0,25.0,0.0,26.0,0.0,0.0,0.0,EECECECECECECECECECECECECECECECECECECECECECECECECEC,True +831,0.0,0.0,163.0,0.0,0.0,1.0,0.0,0.0,FCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +832,0.0,0.0,0.0,67.0,0.0,0.0,0.0,0.0,DDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +833,0.0,0.0,21.0,22.0,0.0,0.0,1.0,0.0,GDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +834,0.0,0.0,0.0,70.0,0.0,0.0,0.0,68.0,DDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +835,0.0,1.0,0.0,76.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +836,0.0,0.0,61.0,0.0,0.0,1.0,60.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +837,0.0,0.0,36.0,0.0,1.0,36.0,0.0,0.0,EFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +838,0.0,1.0,0.0,48.0,0.0,0.0,47.0,0.0,BDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +839,0.0,89.0,0.0,0.0,0.0,0.0,0.0,89.0,BHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +840,10.0,0.0,0.0,0.0,10.0,0.0,1.0,0.0,GEAEAEAEAEAEAEAEAEAEA,True +841,0.0,0.0,0.0,0.0,0.0,90.0,0.0,0.0,FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +842,0.0,0.0,0.0,1.0,0.0,0.0,0.0,183.0,DHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +843,0.0,0.0,0.0,8.0,0.0,1.0,0.0,8.0,FDHDHDHDHDHDHDHDH,True +844,0.0,1.0,0.0,0.0,40.0,40.0,0.0,0.0,BFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +845,1.0,0.0,0.0,11.0,0.0,0.0,0.0,12.0,AHDHDHDHDHDHDHDHDHDHDHDH,True +846,0.0,0.0,23.0,0.0,22.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECEC,True +847,0.0,0.0,31.0,0.0,0.0,1.0,0.0,31.0,FHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +848,0.0,0.0,0.0,0.0,93.0,0.0,1.0,92.0,GEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +849,1.0,0.0,0.0,0.0,0.0,0.0,96.0,96.0,AHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +850,1.0,0.0,0.0,142.0,0.0,0.0,0.0,0.0,ADDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +851,0.0,0.0,0.0,1.0,84.0,0.0,84.0,0.0,DGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True 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+870,0.0,0.0,1.0,0.0,50.0,0.0,51.0,0.0,CGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +871,0.0,0.0,16.0,0.0,0.0,16.0,0.0,1.0,HFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +872,0.0,0.0,0.0,1.0,28.0,28.0,0.0,0.0,DFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +873,0.0,0.0,65.0,65.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +874,0.0,34.0,0.0,0.0,0.0,35.0,0.0,0.0,FBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +875,0.0,0.0,9.0,0.0,8.0,0.0,0.0,1.0,HCECECECECECECECEC,True +876,0.0,0.0,0.0,0.0,94.0,0.0,94.0,1.0,HEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +877,0.0,18.0,0.0,16.0,0.0,0.0,0.0,0.0,BBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True 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+885,0.0,0.0,0.0,93.0,0.0,93.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDF,True +886,0.0,1.0,0.0,89.0,0.0,89.0,0.0,0.0,BFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +887,0.0,1.0,0.0,0.0,42.0,0.0,0.0,42.0,BHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +888,68.0,0.0,0.0,0.0,1.0,0.0,0.0,67.0,EAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +889,55.0,0.0,0.0,0.0,0.0,57.0,0.0,0.0,FFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +890,25.0,1.0,0.0,0.0,0.0,0.0,26.0,0.0,BGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +891,81.0,0.0,0.0,0.0,80.0,0.0,0.0,0.0,AAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +892,0.0,0.0,1.0,0.0,10.0,0.0,10.0,0.0,CGEGEGEGEGEGEGEGEGEGE,True +893,1.0,0.0,43.0,42.0,0.0,0.0,0.0,0.0,ACDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +894,55.0,54.0,0.0,0.0,0.0,0.0,0.0,0.0,AABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +895,43.0,0.0,0.0,0.0,0.0,1.0,0.0,43.0,FAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +896,1.0,0.0,0.0,0.0,97.0,97.0,0.0,0.0,AEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +897,0.0,25.0,0.0,1.0,0.0,25.0,0.0,0.0,DFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +898,0.0,0.0,0.0,0.0,26.0,26.0,1.0,0.0,GEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +899,0.0,0.0,36.0,0.0,36.0,0.0,0.0,0.0,ECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +900,0.0,0.0,0.0,0.0,1.0,0.0,89.0,88.0,EGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +901,0.0,1.0,142.0,0.0,0.0,0.0,0.0,0.0,BCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +902,1.0,83.0,0.0,83.0,0.0,0.0,0.0,0.0,ABDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +903,0.0,0.0,17.0,0.0,17.0,0.0,0.0,1.0,HECECECECECECECECECECECECECECECECEC,True +904,77.0,77.0,0.0,0.0,0.0,0.0,0.0,0.0,BABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +905,0.0,0.0,0.0,0.0,0.0,0.0,164.0,0.0,GGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +906,0.0,0.0,0.0,89.0,0.0,1.0,0.0,90.0,FHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +907,0.0,0.0,41.0,0.0,0.0,0.0,42.0,0.0,GCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +908,28.0,0.0,0.0,0.0,0.0,28.0,1.0,0.0,GAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +909,0.0,0.0,94.0,0.0,1.0,0.0,95.0,0.0,EGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +910,0.0,0.0,27.0,1.0,27.0,0.0,0.0,0.0,DECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +911,0.0,0.0,0.0,100.0,0.0,1.0,0.0,0.0,FDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +912,0.0,1.0,66.0,0.0,0.0,0.0,66.0,0.0,BGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +913,0.0,23.0,23.0,0.0,0.0,1.0,0.0,0.0,FCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +914,0.0,0.0,0.0,0.0,0.0,0.0,150.0,0.0,GGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +915,0.0,0.0,0.0,0.0,0.0,0.0,1.0,42.0,GHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +916,0.0,147.0,0.0,0.0,0.0,0.0,1.0,0.0,GBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +917,0.0,56.0,0.0,1.0,0.0,0.0,0.0,56.0,DHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +918,0.0,0.0,0.0,0.0,0.0,76.0,76.0,1.0,HFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFG,True +919,0.0,53.0,0.0,0.0,0.0,0.0,0.0,52.0,BHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +920,0.0,0.0,147.0,0.0,0.0,1.0,0.0,0.0,FCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +921,0.0,0.0,0.0,40.0,40.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +922,0.0,82.0,0.0,84.0,0.0,0.0,0.0,0.0,DDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +923,1.0,0.0,0.0,0.0,0.0,0.0,0.0,97.0,AHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +924,0.0,29.0,0.0,0.0,0.0,0.0,0.0,30.0,HHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +925,25.0,0.0,0.0,1.0,0.0,0.0,0.0,25.0,DHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +926,0.0,164.0,0.0,0.0,0.0,0.0,1.0,0.0,GBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +927,89.0,0.0,0.0,0.0,1.0,0.0,90.0,0.0,EGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +928,0.0,0.0,1.0,0.0,41.0,41.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +929,0.0,0.0,1.0,19.0,18.0,0.0,0.0,0.0,CDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +930,0.0,0.0,0.0,0.0,1.0,75.0,75.0,0.0,EGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +931,0.0,0.0,21.0,0.0,0.0,22.0,0.0,0.0,FCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCF,True +932,0.0,0.0,81.0,0.0,80.0,1.0,0.0,0.0,FCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +933,20.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAAAAA,True +934,0.0,40.0,0.0,0.0,0.0,40.0,0.0,0.0,BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +935,0.0,72.0,0.0,0.0,72.0,0.0,1.0,0.0,GBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True +936,56.0,1.0,0.0,56.0,0.0,0.0,0.0,0.0,BADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +937,0.0,0.0,0.0,0.0,0.0,96.0,1.0,0.0,GFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +938,0.0,1.0,0.0,88.0,0.0,0.0,0.0,88.0,BHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +939,1.0,0.0,0.0,0.0,0.0,0.0,0.0,175.0,AHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +940,0.0,0.0,84.0,1.0,83.0,0.0,0.0,0.0,DCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +941,0.0,0.0,83.0,0.0,0.0,0.0,0.0,85.0,HHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +942,1.0,5.0,5.0,0.0,0.0,0.0,0.0,0.0,ABCBCBCBCBC,True +943,0.0,0.0,0.0,68.0,0.0,0.0,0.0,69.0,HHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +944,29.0,0.0,0.0,0.0,0.0,29.0,1.0,0.0,GAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +945,0.0,0.0,1.0,0.0,0.0,0.0,81.0,82.0,CHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +946,89.0,0.0,89.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +947,0.0,0.0,0.0,78.0,1.0,0.0,0.0,0.0,EDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +948,90.0,1.0,0.0,0.0,0.0,0.0,91.0,0.0,BGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +949,0.0,0.0,0.0,86.0,1.0,0.0,0.0,86.0,EHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +950,0.0,0.0,0.0,42.0,1.0,0.0,42.0,0.0,EDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +951,85.0,0.0,0.0,84.0,1.0,0.0,0.0,0.0,EADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +952,90.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +953,0.0,0.0,1.0,0.0,0.0,90.0,0.0,0.0,CFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +954,62.0,0.0,0.0,1.0,0.0,62.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +955,0.0,20.0,20.0,0.0,1.0,0.0,0.0,0.0,EBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +956,0.0,0.0,37.0,0.0,0.0,1.0,0.0,38.0,FHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +957,98.0,1.0,0.0,0.0,0.0,98.0,0.0,0.0,BFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +958,0.0,1.0,0.0,0.0,189.0,0.0,0.0,0.0,BEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +959,0.0,0.0,0.0,9.0,0.0,1.0,8.0,0.0,FDGDGDGDGDGDGDGDGD,True +960,0.0,68.0,0.0,0.0,0.0,0.0,0.0,69.0,HHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +961,0.0,0.0,0.0,138.0,0.0,0.0,0.0,0.0,DDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +962,0.0,0.0,0.0,0.0,1.0,30.0,0.0,30.0,EHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +963,0.0,0.0,0.0,80.0,80.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +964,77.0,0.0,0.0,1.0,0.0,0.0,0.0,78.0,DHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +965,0.0,0.0,0.0,58.0,58.0,0.0,1.0,0.0,GEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +966,0.0,0.0,0.0,1.0,35.0,34.0,0.0,0.0,DEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +967,0.0,60.0,0.0,60.0,0.0,1.0,0.0,0.0,FDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +968,0.0,1.0,80.0,0.0,81.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +969,0.0,1.0,0.0,0.0,0.0,0.0,81.0,81.0,BGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +970,16.0,0.0,0.0,16.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADA,True +971,0.0,0.0,0.0,0.0,78.0,77.0,0.0,0.0,EFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +972,0.0,0.0,10.0,1.0,0.0,10.0,0.0,0.0,DFCFCFCFCFCFCFCFCFCFC,True +973,0.0,0.0,0.0,0.0,0.0,44.0,1.0,44.0,GHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +974,0.0,36.0,0.0,0.0,0.0,36.0,1.0,0.0,GFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +975,0.0,87.0,0.0,0.0,0.0,0.0,87.0,0.0,BGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +976,42.0,0.0,42.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +977,0.0,0.0,0.0,57.0,0.0,55.0,0.0,0.0,DDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +978,0.0,0.0,0.0,0.0,0.0,0.0,64.0,63.0,GGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +979,0.0,0.0,0.0,0.0,1.0,96.0,0.0,0.0,EFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +980,1.0,0.0,0.0,71.0,71.0,0.0,0.0,0.0,ADEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +981,0.0,80.0,1.0,0.0,0.0,0.0,0.0,81.0,CHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +982,0.0,0.0,0.0,0.0,0.0,0.0,27.0,27.0,HGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +983,52.0,51.0,0.0,0.0,0.0,0.0,1.0,0.0,GABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +984,38.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +985,1.0,73.0,0.0,0.0,0.0,0.0,0.0,0.0,ABBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +986,0.0,0.0,0.0,1.0,0.0,0.0,61.0,0.0,DGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +987,82.0,81.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +988,0.0,1.0,0.0,0.0,72.0,0.0,0.0,72.0,BEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +989,93.0,0.0,92.0,0.0,0.0,0.0,0.0,1.0,HACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +990,0.0,1.0,0.0,0.0,60.0,0.0,0.0,61.0,BHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +991,0.0,1.0,0.0,0.0,0.0,0.0,32.0,32.0,BHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +992,0.0,0.0,34.0,35.0,0.0,0.0,1.0,0.0,GDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +993,0.0,0.0,0.0,0.0,54.0,0.0,54.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +994,0.0,0.0,0.0,1.0,0.0,39.0,0.0,38.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +995,0.0,0.0,0.0,0.0,99.0,98.0,0.0,1.0,HEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +996,86.0,1.0,0.0,0.0,0.0,86.0,0.0,0.0,BFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +997,0.0,76.0,77.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +998,0.0,0.0,19.0,0.0,0.0,0.0,0.0,1.0,HCCCCCCCCCCCCCCCCCCC,True +999,0.0,0.0,37.0,1.0,0.0,0.0,38.0,0.0,DGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True diff --git a/tests/results/nb_gm_001_3back.csv b/tests/results/nb_gm_001_3back.csv new file mode 100644 index 0000000..b2f89a4 --- /dev/null +++ b/tests/results/nb_gm_001_3back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,0.0,65.0,132.0,0.0,0.0,0.0,0.0,1.0,HCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCC,True +1,51.0,0.0,52.0,52.0,0.0,0.0,0.0,1.0,HCDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACD,True +2,0.0,61.0,0.0,62.0,0.0,0.0,61.0,1.0,HDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGD,True +3,40.0,0.0,0.0,1.0,0.0,0.0,0.0,80.0,DHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHA,True +4,4.0,0.0,1.0,0.0,0.0,6.0,0.0,0.0,CAFFAFFAFFA,True +5,0.0,123.0,1.0,0.0,0.0,0.0,0.0,0.0,CBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +6,49.0,0.0,49.0,0.0,49.0,0.0,0.0,1.0,HCAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAE,True +7,0.0,53.0,53.0,53.0,0.0,1.0,0.0,0.0,FBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCD,True +8,0.0,0.0,54.0,55.0,0.0,55.0,0.0,0.0,FDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFD,True +9,57.0,0.0,57.0,0.0,0.0,0.0,58.0,1.0,HGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAG,True 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+74,25.0,0.0,26.0,0.0,1.0,0.0,0.0,25.0,ECAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHC,True +75,61.0,0.0,0.0,60.0,0.0,60.0,0.0,1.0,HAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDA,True +76,0.0,0.0,0.0,41.0,0.0,0.0,0.0,20.0,DHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDD,True +77,0.0,0.0,1.0,0.0,0.0,15.0,15.0,14.0,CGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGF,True +78,6.0,0.0,1.0,6.0,0.0,0.0,0.0,6.0,CHDAHDAHDAHDAHDAHDA,True +79,0.0,124.0,0.0,62.0,0.0,0.0,0.0,0.0,BBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBD,True +80,0.0,0.0,32.0,0.0,0.0,31.0,31.0,0.0,CGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCF,True +81,0.0,0.0,0.0,64.0,64.0,0.0,64.0,1.0,HGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGED,True +82,0.0,0.0,83.0,0.0,0.0,1.0,41.0,0.0,FCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGC,True +83,0.0,1.0,0.0,48.0,48.0,48.0,0.0,0.0,BFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFED,True +84,1.0,58.0,0.0,0.0,0.0,59.0,0.0,58.0,AFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBF,True +85,31.0,0.0,0.0,1.0,0.0,0.0,61.0,0.0,DAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAG,True 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+92,0.0,0.0,22.0,22.0,22.0,0.0,0.0,0.0,DCEDCEDCEDCEDCEDCEDCEDCEDCEDCEDCEDCEDCEDCEDCEDCEDCEDCEDCEDCEDCEDCE,True +93,0.0,28.0,0.0,1.0,29.0,0.0,28.0,0.0,DEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGE,True +94,1.0,0.0,54.0,0.0,0.0,0.0,54.0,54.0,AHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGC,True +95,0.0,1.0,0.0,49.0,49.0,0.0,0.0,50.0,BHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEH,True +96,15.0,0.0,0.0,0.0,14.0,14.0,0.0,0.0,AEAFEAFEAFEAFEAFEAFEAFEAFEAFEAFEAFEAFEAFEAF,True +97,0.0,50.0,1.0,51.0,51.0,0.0,0.0,0.0,CEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBED,True +98,0.0,54.0,0.0,0.0,0.0,0.0,55.0,53.0,GBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBG,True +99,0.0,0.0,50.0,51.0,49.0,0.0,0.0,0.0,DCDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECD,True +100,0.0,29.0,0.0,0.0,0.0,0.0,29.0,29.0,HBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBG,True +101,0.0,0.0,0.0,33.0,0.0,0.0,1.0,65.0,GHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHD,True +102,1.0,49.0,0.0,0.0,49.0,0.0,0.0,50.0,AHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBH,True +103,22.0,1.0,0.0,0.0,23.0,0.0,0.0,23.0,BEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEH,True +104,114.0,0.0,1.0,0.0,0.0,57.0,0.0,0.0,CFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAA,True +105,0.0,0.0,34.0,0.0,68.0,0.0,0.0,0.0,ECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECE,True +106,27.0,1.0,0.0,0.0,27.0,0.0,26.0,0.0,BEAGEAGEAGEAGEAGEAGEAGEAGEAGEAGEAGEAGEAGEAGEAGEAGEAGEAGEAGEAGEAGEAGEAGEAGEAGEAGEA,True +107,59.0,59.0,0.0,0.0,1.0,59.0,0.0,0.0,EABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABF,True +108,0.0,0.0,1.0,17.0,16.0,0.0,17.0,0.0,CGDEGDEGDEGDEGDEGDEGDEGDEGDEGDEGDEGDEGDEGDEGDEGDEGD,True +109,9.0,0.0,9.0,0.0,0.0,0.0,11.0,0.0,GGACGACGACGACGACGACGACGACGACG,True +110,64.0,63.0,0.0,0.0,0.0,0.0,0.0,63.0,ABAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAH,True +111,1.0,66.0,0.0,0.0,67.0,66.0,0.0,0.0,AEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFE,True +112,0.0,19.0,0.0,0.0,0.0,0.0,0.0,36.0,BBHHBHHBHHBHHBHHBHHBHHBHHBHHBHHBHHBHHBHHBHHBHHBHHBHHBHH,True +113,0.0,0.0,20.0,1.0,19.0,0.0,0.0,20.0,DHCEHCEHCEHCEHCEHCEHCEHCEHCEHCEHCEHCEHCEHCEHCEHCEHCEHCEHCEHC,True +114,21.0,1.0,21.0,0.0,0.0,21.0,0.0,0.0,BFCAFCAFCAFCAFCAFCAFCAFCAFCAFCAFCAFCAFCAFCAFCAFCAFCAFCAFCAFCAFCA,True +115,0.0,0.0,0.0,44.0,0.0,0.0,43.0,45.0,HDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDH,True +116,0.0,0.0,48.0,0.0,1.0,0.0,0.0,97.0,EHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHH,True +117,1.0,0.0,0.0,0.0,0.0,51.0,0.0,26.0,AFHFFHFFHFFHFFHFFHFFHFFHFFHFFHFFHFFHFFHFFHFFHFFHFFHFFHFFHFFHFFHFFHFFHFFHFFHFFH,True +118,32.0,0.0,0.0,33.0,0.0,0.0,0.0,32.0,DHADHADHADHADHADHADHADHADHADHADHADHADHADHADHADHADHADHADHADHADHADHADHADHADHADHADHADHADHADHADHADHAD,True +119,1.0,0.0,41.0,0.0,0.0,0.0,41.0,40.0,ACGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCG,True +120,0.0,29.0,0.0,30.0,29.0,0.0,0.0,0.0,DEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBD,True +121,0.0,0.0,54.0,1.0,54.0,0.0,54.0,0.0,DEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGC,True +122,1.0,0.0,0.0,18.0,0.0,17.0,17.0,0.0,ADGFDGFDGFDGFDGFDGFDGFDGFDGFDGFDGFDGFDGFDGFDGFDGFDGFD,True +123,13.0,0.0,0.0,14.0,0.0,1.0,14.0,0.0,FGDAGDAGDAGDAGDAGDAGDAGDAGDAGDAGDAGDAGDAGD,True +124,0.0,0.0,62.0,0.0,63.0,0.0,62.0,0.0,ECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGE,True +125,0.0,0.0,0.0,0.0,52.0,1.0,0.0,104.0,FHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHE,True +126,39.0,0.0,0.0,39.0,0.0,0.0,1.0,38.0,GDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDA,True +127,0.0,31.0,0.0,63.0,0.0,0.0,0.0,0.0,DDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBD,True +128,0.0,1.0,0.0,56.0,0.0,57.0,0.0,57.0,BFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFH,True +129,1.0,0.0,42.0,42.0,42.0,0.0,0.0,0.0,ACDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDE,True +130,0.0,4.0,0.0,4.0,0.0,0.0,4.0,1.0,HBDGBDGBDGBDG,True +131,0.0,0.0,0.0,0.0,1.0,24.0,24.0,25.0,EHFGHFGHFGHFGHFGHFGHFGHFGHFGHFGHFGHFGHFGHFGHFGHFGHFGHFGHFGHFGHFGHFGHFGHFGH,True +132,0.0,0.0,131.0,0.0,0.0,0.0,0.0,64.0,CCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCC,True 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+967,54.0,0.0,54.0,53.0,0.0,0.0,0.0,0.0,ACADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADC,True +968,10.0,0.0,10.0,0.0,12.0,0.0,0.0,0.0,EEACEACEACEACEACEACEACEACEACEACE,True +969,0.0,0.0,0.0,0.0,0.0,0.0,125.0,62.0,GGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGH,True +970,0.0,8.0,1.0,9.0,0.0,0.0,8.0,0.0,CDBGDBGDBGDBGDBGDBGDBGDBGD,True +971,0.0,0.0,0.0,66.0,66.0,67.0,1.0,0.0,GFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEF,True +972,63.0,0.0,0.0,0.0,127.0,0.0,1.0,0.0,GEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAE,True +973,0.0,0.0,11.0,0.0,0.0,0.0,21.0,1.0,HCGGCGGCGGCGGCGGCGGCGGCGGCGGCGGCG,True +974,0.0,0.0,39.0,0.0,0.0,40.0,40.0,0.0,FGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFG,True +975,0.0,0.0,1.0,31.0,0.0,0.0,62.0,0.0,CDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGG,True +976,0.0,54.0,0.0,0.0,0.0,1.0,54.0,55.0,FHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBH,True +977,0.0,0.0,18.0,19.0,0.0,18.0,0.0,0.0,DFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCD,True +978,126.0,63.0,0.0,0.0,1.0,0.0,0.0,0.0,EAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAAB,True +979,19.0,0.0,0.0,0.0,0.0,1.0,0.0,9.0,FAHAAHAAHAAHAAHAAHAAHAAHAAHAA,True +980,0.0,0.0,32.0,32.0,0.0,33.0,0.0,0.0,FDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFC,True +981,15.0,0.0,15.0,0.0,16.0,0.0,0.0,0.0,ECEACEACEACEACEACEACEACEACEACEACEACEACEACEACEA,True +982,0.0,0.0,55.0,0.0,0.0,56.0,57.0,0.0,GFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFG,True +983,0.0,0.0,32.0,0.0,1.0,32.0,31.0,0.0,EFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFC,True +984,0.0,0.0,0.0,41.0,1.0,40.0,40.0,0.0,EDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGD,True +985,0.0,0.0,0.0,0.0,5.0,6.0,5.0,1.0,HFGEFGEFGEFGEFGEF,True +986,0.0,19.0,17.0,0.0,0.0,0.0,0.0,18.0,BBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBH,True +987,0.0,0.0,0.0,0.0,0.0,0.0,6.0,10.0,GHGHHGHHGHHGHHGH,True +988,0.0,0.0,69.0,0.0,36.0,0.0,0.0,0.0,ECECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCE,True +989,1.0,0.0,0.0,0.0,0.0,19.0,0.0,37.0,AHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHF,True +990,67.0,0.0,0.0,0.0,0.0,0.0,0.0,33.0,AHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAA,True +991,0.0,0.0,16.0,18.0,0.0,17.0,0.0,0.0,DFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFD,True +992,1.0,0.0,50.0,50.0,0.0,0.0,49.0,0.0,ACDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCD,True +993,0.0,40.0,39.0,0.0,39.0,0.0,0.0,1.0,HBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEB,True +994,0.0,30.0,1.0,0.0,0.0,0.0,30.0,30.0,CBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGH,True +995,126.0,0.0,1.0,0.0,0.0,0.0,0.0,63.0,CHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAA,True +996,45.0,0.0,45.0,1.0,0.0,0.0,0.0,45.0,DHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHAC,True +997,15.0,0.0,0.0,0.0,29.0,0.0,0.0,0.0,AEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEE,True +998,0.0,4.0,1.0,0.0,0.0,4.0,0.0,4.0,CHBFHBFHBFHBF,True +999,0.0,100.0,0.0,0.0,0.0,0.0,0.0,51.0,HBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBH,True diff --git a/tests/results/nb_gm_002_2back.csv b/tests/results/nb_gm_002_2back.csv new file mode 100644 index 0000000..33538c3 --- /dev/null +++ b/tests/results/nb_gm_002_2back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,4.0,2.0,2.0,2.0,2.0,1.0,0.0,5.0,BHCHDHDAEBEHAFAHAC,True +1,0.0,4.0,1.0,2.0,4.0,0.0,0.0,0.0,DBEBDBCEEBE,True +2,5.0,10.0,14.0,6.0,16.0,18.0,12.0,12.0,CFFGHCFCGHEDCCACECBGEGFGAEBGHFDCEEDCCEGEGCBBBHCCECHBHEHBHDEDAFAFAFHFGFGFGHGHEFFFEFEDHFEFEFBBB,False +3,12.0,15.0,11.0,20.0,13.0,17.0,17.0,22.0,AFAHGHGHGBEBCDDDDHHHABCEHEHEBBBAHADADCFHHHHHFEFCBDDFDGDEFCAGGFEFBDGEHECCBCFFFFFFHGEBBHHCBCACHHDDBFGGGGEGEAFDGDADGDGDGBEBAAHDDFH,False +4,4.0,4.0,8.0,8.0,5.0,7.0,4.0,2.0,FGDGECDCECGCDADAHFDFCFCGAFCDDDABEBHBEFEFBC,False +5,15.0,15.0,15.0,16.0,16.0,14.0,9.0,13.0,HGDGBFDHDADHBBBBBHBAAGBCEABCGFAFAFBGBCBFGDDDEAAAHDFACECECHFHFHFCFHEGEFEFDFDAAHDEECDABFCCCCGBEBDAHCECHCHEDEDEDAGEE,False +6,17.0,17.0,9.0,6.0,15.0,13.0,15.0,12.0,BEBEBHAGCFEHHABAHDEDGHFBFGFCAABAGFFFAFGECEBEAEAFBFCEBEGHGDBEFABABEGEHEHBGBGDADACAGHGHGBGBACGCAHFFBHAECDC,False +7,12.0,7.0,7.0,6.0,9.0,8.0,5.0,6.0,CEGBFEFEFEHCCDEBCCHBBBGAHACBGGDBDADACADHDHFEAEAEFGFAAEAHAFAF,False +8,9.0,13.0,10.0,11.0,12.0,15.0,11.0,12.0,CGCFDBDFHHEHFFGCDHEHCFCFAAEGDCEGHGCFCBBBCBGFGHGDFDBDADHBBEGAGABABHBEBEHGHADAFEFCFDBDEFEHEFEFA,False +9,13.0,26.0,23.0,14.0,20.0,18.0,19.0,27.0,HECEBEFFHFDCCFGBCBDBAHGHGCBBABHEFAFEBEBHBHGGCHBGGCCCCCFCBDDDEDHDEEEAAFAFGFDFCGBGHEHDHGHAFABCGGEHEHFBGBADEBEBEAAHBDCCFGGHHHBHBHGHBDBEEAEGCGCBCHCEFFFFCHDHCHDHABCB,False +10,14.0,18.0,15.0,13.0,15.0,19.0,18.0,11.0,AFACABDDFBBBEBECECGHFBFBECDCEEEDGDBHHGCBDDAFCBAAAGHCHCHEAFBFDHAHCFFAAAHBBBFBFBHGFBCBCFGGGHGDGDFEGEFCFEDGDGAGEGCGEGEFEFAFDGC,False +11,21.0,20.0,21.0,13.0,15.0,26.0,21.0,21.0,EECEFFHGCADHGEGEABCCFDEBABEBGGCACHFHFBFBFBAHGBGCGHDCDABHHAGABFHEBCFEGDFDFDFAFBCBCAHACFGFBFBFBFBDACCBCHFHEGEDFDFCAAAGGEBFAAACACHCHFGFBFGHGHAEAGCCEDDFHHHGHGHGDE,False +12,17.0,26.0,17.0,23.0,17.0,11.0,26.0,21.0,ABGCACGDDFHFHBCEHEAGBGBEBAHEBEBFAAHAFBCEGDGBAHGGGGFGDDDBABABHGGGCGDGHGHDACAEDEFECHGEGDABGCHCDDDDCBCBADAHCHGBGBGEHDCDBBFBABHBHBFBACHDEEHGHECDCDHDEFEDECFGHGBFBD,False +13,24.0,21.0,23.0,20.0,15.0,14.0,30.0,24.0,AHHHHAFEDHAFBFGFCFGADADCDGBBBBGDGEGBCBHGGGGCGFBFAGGGGHEEFEGHGHABCBFHGAGACBBDEDHDHDGBCACAHGCACEHECACHBHDCGCECADGDGDABADHFGCGAGAHHBGFDCHBHCAAABEEFDFDBDBEADAHGEGEHECCCBCFCAHD,False +14,1.0,0.0,2.0,1.0,1.0,1.0,2.0,2.0,DECGCGAHFH,True +15,7.0,7.0,10.0,5.0,8.0,4.0,8.0,9.0,HBABHHEEGAGAGEGHCDEECHCHGBCBCDDAEGCBCGEAEFDFBFBFAGCHCHCHAD,False +16,14.0,19.0,14.0,7.0,10.0,15.0,19.0,7.0,CEAFFGHGEGFDFDCACAGBDEAFCEDDFAHHFDFGBEACGCGBGAFECECFGHCEBAFGEGCBABEBHBHBACAGAGDGHBABCBCBGFGFGFGBBBBFBCBGA,False +17,17.0,15.0,14.0,12.0,10.0,9.0,17.0,6.0,EBACADACGBGBAFGHGHADCDGAAFFFADABAHGDGABBCBCACACECHFBFHDCACDGEBADDEGGGEDADFGFGCGFBBABCBEBDBCHGEGEGECE,False +18,14.0,22.0,17.0,9.0,14.0,10.0,25.0,20.0,EHCHAHEHAHCHCGBGCGCGAEBFBFGGCEFGBGHAHCBABABHHGHGCACHDEDBBABGGDGDEBBBHHGCAEGBFHGEGEGBCCGCDFBBGBFBDAEEHHHCFEFECEHGCGCBHDADFDAGAGAGFBB,False +19,13.0,27.0,12.0,18.0,19.0,17.0,20.0,18.0,BFGCGBHAHAHEFEDBABEBEDADGGGGBAFCGEBDFHBHGHGCBBEGEGBHDHDHBCBCACDBFHHCHBGAGAGEDADADCDCACGHEEEEBDFDFDHDCGGBGDEBBBABEHFHGEFFFBADHEFFCFDEBEBFFEBHBFBG,False +20,11.0,10.0,7.0,8.0,8.0,7.0,11.0,4.0,BGBABGHGCGFBFAEBGGEDEFAHEHACDCDADBGGAGAGADFBFBCBCEFBFDHDACCDAGAEEE,False +21,22.0,20.0,18.0,24.0,13.0,11.0,16.0,21.0,DADADHCACFCHEDAAAHGDDHAGCDEDEGBHAHBDBDBGHHHCHCECAAAEFEDECEDBHFABGBCAGDBEGEBABHFCBBABDFDGHGCBFBCCDHDHDGDHDHCHBGADAFACHEHBDCDAFAFAFAGGCGCFHGBDBEBEG,False +22,8.0,10.0,11.0,7.0,8.0,15.0,4.0,11.0,CBAEGDGEHEBGBFBFBDHCHFHBAEHFFGFCFBFCFEEHABECFFFFACAEHHDCDCDHDHAHCFCBCBAADF,False +23,32.0,19.0,21.0,23.0,13.0,27.0,21.0,27.0,GHCABDGDFFFAHHHEAEHGAGAGHEFEGBCFAFBFGCHCHFHBGCAFFDFDBACACHCHCHBFGFEACAFABEBEBHHGHFHAHGGAGAHAFCGDHDHAFGCBCHDAAAAAAFCFHGEFFBEBEDDDFDBCBDDDCGFAFADBDBEBCAGGHDFDFBCDEAGAHCCEHGHAHCDDDDABAFA,False +24,26.0,30.0,18.0,21.0,29.0,16.0,21.0,21.0,GDGDADAGAGDEHCDBDHAHEHFHAHAFBHBHGCEBHBDBHBHBEEABABABAEECEGEGAGADHDBEEGBCAADHGBFBCEAAHDEBEBFBFBFCCGCEFBABAEDBGFGBGCFCGEACDFEFBHDADFHCEAEBDHDCGBEFGCDCACDEBEGAGAEAEFDFBBEHEGEGHCACEFBHDH,False +25,17.0,15.0,10.0,21.0,16.0,11.0,16.0,22.0,BDBDBHHHAAGAEHEHCHCDADEBGHDAGEBHGAABADADEDECEHAHFBGCGBEHCGADFBHECGHHFFFHFBDDDDDFDFDFHFEDEDACAEAEBDCHHBFBABCBGDGEAECHHGHGEGHDAGGG,False +26,12.0,13.0,16.0,11.0,17.0,10.0,17.0,12.0,GEECBGFEEDHCEFGFEAEAHGEGEDDDHDCDCBHBCBCFCECEGAGAGAHECFCEAAFGFGCEHGHBBBGBGBCBDHEAEFHFHGBCDGGACHCGCDADAEBFBADH,False +27,14.0,11.0,17.0,13.0,14.0,21.0,16.0,19.0,AAECGGEGHCACACACHBHADCECBDHDHDFCFGHGDDEDHHHAHDFDACHBHAFBHHAEEECGGFGEGEBEFCFAEAEFFBFBFDGDGDGHFACCDFHFCGBBHBCGGFGEHEFFFFHFCBCAF,False +28,14.0,15.0,12.0,21.0,15.0,9.0,13.0,21.0,GGHGEDHFCFCACBCADAEEEEAHDGAGHGHEHEHBBECEDBBBDBEGDGBAEABCCABBECDDDFDFHGHGHDHGHGHDADHHCHBHCCBAFHFDDDEDHFHAABDFDFEGEAADBDCH,False +29,18.0,19.0,27.0,26.0,29.0,30.0,16.0,16.0,DEFFFAFAGDGEEBFBFGEBADACADFDCEEDEDFDCDEBBGDGHGHGFFFDFBEBEHCHFDCDCEGFGFHFEFCGBBDCHCGCDADEGEGCFAAEHEHFDACGCEABBDECBCBCEFEFBFCFCFEHEHDGACEBAGCEFEBACCCAEDHDHBCFCDEFFHDHDHDCFCAAAEBEBFDHA,False +30,5.0,11.0,5.0,8.0,3.0,2.0,5.0,1.0,BBFGGBABFGCCCDADAHBEDCDBABGEAECBDBDBDBDG,True +31,28.0,17.0,19.0,16.0,18.0,11.0,17.0,33.0,DHAFAHAEAHDHFHFAFADHCGGGDGDGHEBDHCHBHAEBCBCFEGHHHBHCAFDHEHEHCDAGBCBAAAGACCBCAFGBHEHBBEAHAHAFAEACGGEHAFABEDEDFDCGHEBGAGEEAEBBHDEDECHCGABHGHAHAHBHCHCHCHDGACACDFD,False +32,5.0,10.0,12.0,17.0,19.0,17.0,17.0,11.0,EEBHBFFFDDEDCCAGEFEGGDGDFFGEGEAEDEFCFCGCGCGFAEGECDHHCEFDDHDFDABFDECECEHEFDDGDGBBFBFHHGCECEFEHAHDHDGBBFBGHGBG,False +33,4.0,13.0,10.0,7.0,4.0,8.0,11.0,7.0,CGBHBCBCBHFHFECBADGBGBGBDBCFAGDBHGFGECEHBGBCCACFGFGFGDDDFCADHEHB,False +34,22.0,27.0,22.0,21.0,21.0,28.0,21.0,21.0,BABFBCCCCGCDCAGABAHFBAHCBDBDHDCDCDEFFHBHBCBCBEHDAGAEFBBEEEBEGAGHGDGCGEBFBDEAECCFCFGDGDGHBHAEFFFECCADHFFBGHDHEGAAEDEFEFCDCDCDEFCHADAEHFDFHBBEBEBFBFAFGFAAHGHGFFAFGGBABGHGBFBFDFHCHAHEGDA,False +35,24.0,23.0,21.0,17.0,28.0,15.0,20.0,21.0,EGHGAGEGCGDFFCEEEEEAHGEGFGFBCBGBDBACHCAGDDDDEDEHACGCECAFAFEFHCHCEFHDHEHBAEADBDBAFCHCEEEEHBHBECEAEAFGGGGCCHBHAAACABBEHFHBDFHHDHBGCAABEBGAGABBFADADEBBBBCDCACFGFHDCEHEBGADE,False +36,16.0,12.0,18.0,16.0,29.0,20.0,25.0,11.0,EEEBCFFDHDBBGHGHGEFDFACCCFCGAECECEAGFFFCFDAHAEEHGGGBGBGADDGDGEGCCBFEHEGEHACDGDGCCCFCEAFAEGEGBGFGBBBHFGDGFGAAHADADCEEEEDEAEFEAEBFFFHEGECEGEHECAFDDDB,False +37,1.0,6.0,2.0,11.0,2.0,11.0,4.0,7.0,DBFFFHHADFFEFBDBFBGDFFEBHBHFHGDGDGCCDDDDHDHF,True +38,11.0,12.0,15.0,5.0,3.0,15.0,15.0,13.0,HCCCCAEBGFCFBGAHHHHBAFGCGCGCGFGCAABFBABHBFBCAFHFAFGCDBGBGAGFCBBAADHDHDCGEGHGCGFFHFHDEFHFC,False +39,33.0,14.0,21.0,23.0,21.0,18.0,25.0,28.0,DHAHAHADGDAFAFGCHCHEHCHABACEDDDCGBHAEFFGCADADGBGCFFFGGHBAAFGGHFHFHECFCHCHBDEFGADDCGGGHEBEDEBEBEDFHCAAAACFGFBFBFADAEGBDCAGACACAFGEEECDDDDCGGGEEEEEGCADHHHHAHABAHGBBCACHEGGHDADADAHAHEHAH,False +40,9.0,21.0,8.0,6.0,13.0,11.0,9.0,15.0,HEBEGEGAGEBBBHFAFABCBCBEBCBEAFHGGGHEHCHBEDFFAFAHDBFBFBEBDFHHDHBHCHBHBDEFABGBCEDEBCACHHEAGBGF,False +41,13.0,18.0,18.0,16.0,8.0,20.0,16.0,13.0,AGDGBCDHFADAGFFFHHCFCFEBGBGFGFGCGCHHHHCGFBFGDHABCBCGDGECEFBFCACBDBDCFAFBDEDCFFBHGHBEBABDFDFDHDHACABDBAFAFDHEGACACBEECGCBDG,False +42,21.0,15.0,14.0,22.0,14.0,22.0,16.0,21.0,ACFDFDEDFDBAFDCDCDFFFFFACHCHGEDFCFEHADACEHEDEBAFAGGHGEDADFDHDHDHGADAGCCCFHBDBGBDEGEBHGFGHAHFBFBFEAABABACDDAHHGFGBGEGHFEABHBFEHHHGDFDCACABABGECHAH,False +43,17.0,19.0,23.0,19.0,19.0,21.0,20.0,22.0,GDGFGEDDDDDDFDFDFEHBHDGAECBHDEGHGEEDEBEDECGGAADAFAFADECFCDGDGFBHGCBHBACAGACFCGGGBGCHFHEHECECAHFHFGCGHBFCGCBCFEHEGEHBBAAABDHFBCCCCFFFHFCABFBHBHBEDAFEHBHACABECHCH,False +44,2.0,1.0,3.0,4.0,5.0,3.0,6.0,5.0,CHCHFGBGEHFDAGADEDEGGFGEDEHCH,True +45,17.0,20.0,26.0,20.0,18.0,24.0,15.0,12.0,BDEFBBBHHECFCFCBBFEDDADADGECEHEFCGCAFDCGCFFEDDGGHHHHHAFAFEFAFDFDFDEDFAACFCFCDCBBBCGCGDGDFCGCGBDCACBHDHEECBBEBECFCHGBGEGABCDCEFHFGACDFAFAECEBEBDACABAGFBA,False +46,5.0,7.0,11.0,5.0,5.0,3.0,8.0,10.0,CBDHFHCDCEGEHCHCHCHEGCGCGBBBBADAHGDGBACGEAHBHFGFCECAHD,False +47,5.0,4.0,4.0,5.0,0.0,1.0,5.0,3.0,ACABGBHBHBGDCACHCDAGFGAGDDD,True +48,21.0,22.0,13.0,24.0,16.0,18.0,24.0,19.0,DBDGAGBGFHFCABGFECEGBGHHEACDFDGCGBEBGDAFAHADADAHHBHBHAGABADEBFDGDBDGDGCFAFAFDDDDECGFEFEAHAHEHEHCBCDADGBFBFAEBCAHFHEDEGBBFDEHEBDHFGCGHGHGBGCDABCBDGHGBGDCEAFAF,False +49,5.0,12.0,11.0,8.0,8.0,7.0,11.0,9.0,FCFDGDHBEBECFBBHFCFCGDBCCCGCECECBDBGBEHDDBCAGAEHEDFDHGEGAHBHGAGAGFHBHBG,False +50,2.0,7.0,7.0,4.0,6.0,13.0,10.0,11.0,BBFEFEFHAHFDFGHEBABDFHBHEFGFGHEHGGGFDFEHCBGBFDFHFHCCGCGHGCCC,True +51,5.0,7.0,11.0,12.0,13.0,9.0,8.0,13.0,EFFBFDAAECCCHDHBHFEDBHBHDHDGGGGECDGHCFEFEDEDCDCDEDCCHFEFEGCGBHEHBHAHAGDFCEAEHB,False +52,15.0,6.0,11.0,6.0,11.0,16.0,3.0,8.0,BAEGCCEAHBFCCHFABEHEFDCHEBECACECEAFGFEFEFBFBFAFADADACACDFGFAFAFEFDAAHFDCAHHH,True +53,20.0,14.0,19.0,11.0,13.0,12.0,10.0,17.0,CHCECEHEGAHBFGHCHABCBCDCECEDAHACGCADDBBGFGFGFHAAACACFBEGGAGAEHCAAAFDFDCHBDBHGDFDHCBEFEBCBABHHHHDHCHDFEFABEBECAAAEACF,False +54,18.0,14.0,15.0,22.0,24.0,20.0,25.0,23.0,EGGCGCGDEDEBCBFDDDBFHDDGFBFEEEGDBDBEHFDFEACACADABEFDCECGGHBDCDBAGHGFBFECHCFEDEHEHAHEEAGCEEEEFGFHFAAGEEHHHHAHAHDEFGDGDBCGAGHFHFHAHAHDHDBFBFCEGGGGGGGHAADAGCDFFAHCB,False +55,3.0,4.0,2.0,5.0,2.0,5.0,3.0,1.0,EHAABABGBFDFGFGEDDFDCBCDF,True +56,9.0,9.0,8.0,11.0,11.0,13.0,8.0,11.0,ECFFFBCDEDAFEBEAFGFHFHFDEHEBEHEGBFEFHBABCCAGAGBGBDFHAHGHFCFDHDABADEDEDAHGGCDCHCD,False +57,10.0,13.0,10.0,15.0,7.0,9.0,16.0,11.0,HHCFEGEGEDFGABEHEADCHGHBDFDGDGHGCGBBDDCDCDBDBHCDEBAHACCFDGDFAFAFDDAGAGHGCGBGBHACBGBGAHEBFBF,False +58,15.0,15.0,14.0,21.0,27.0,24.0,20.0,28.0,FAFEFAADAGFBFACBCBHHCGFGFAFHCEGEGHHBDBFHFHBEGDGDAEEHEGCGDGHCDGDEHFHGCEEEGEGEDBDEEEEHHHHCHDAGFEBHFHAHFHFDDDCACHFBDDHDGDFDAGGEAEFBHEEEEBEHEFFCFCFDBHAFADCGCGFHDHEBABHB,False +59,11.0,16.0,18.0,17.0,22.0,31.0,15.0,17.0,FCECFCFCFBHCHBGBFHGEDADADEFEFHFDFDADEEADHGAEAECGDGCCFHFGFHFHFHFBFBFCEEEBEFFDEGGBHBEBHFCDDDDGHAFBFBFCACHCAFGCGHHEDCBFEFABCDCEGGGDAEBBBEDEFFFFECGHEHF,False +60,11.0,9.0,7.0,2.0,10.0,10.0,11.0,9.0,HGHCDCHCACBCEGEGEGEBBHCFGABEBFAEHHFBFAAGHGHFHABABCGEGFDEAAABFEFEFGFGA,False +61,23.0,23.0,21.0,24.0,24.0,17.0,27.0,24.0,EDGGCBCFCGCGCFCGCDCBAACHFHFHECACAGAHFHDBDEHAGADHGEGEBCAEAGDHAADDDDCEAEADBGFDBBBBDHDGDBBGCAAEHEGDGBGBFHCGCDBBBEFHFDAGHCDCHFHFGEHEGEGHGBEFACADAFCBGBGBFHDEDEDFBFEGHGHAHAEEEEGEDHAHACEFBHB,False +62,21.0,13.0,9.0,12.0,17.0,15.0,25.0,10.0,HFGFGBGEDEHGHAHFHGAAAFGHBFACGDBEBGAAFEGEFEFBGAHDEDECBCBFBEGAGAFCCBBDBAGABAGGGGGECDADAGAEFEDGACADDCDHDEAFHFHFGGGFGCABAEEEGE,False +63,6.0,6.0,3.0,12.0,7.0,8.0,6.0,13.0,FHEBEBHGHDAGHDCDEDEAFCFCHEEBAAFDDDFDHDAGBGFDHGHAHDHEHFHFHBDBG,False +64,6.0,15.0,15.0,8.0,14.0,13.0,8.0,8.0,CCEDEDBHHGDCBEFEFCCGCEAGFGEGECAHAHGBCFHACEBEBEGEFFFFBDBFBHBDDEDCBCBHBFGFHEAEBCBCFCBCAFD,False +65,6.0,4.0,3.0,4.0,6.0,8.0,5.0,5.0,CGCFEFAFAEEDEHCHBBDAAFAGHEHEBFDHDBAGFGFGF,False +66,17.0,8.0,15.0,6.0,16.0,16.0,11.0,12.0,AFGFGFGHGFECECECHAECCCFAHAFAEHGGCEBAFAEAEFGGHCBFAAEHFHFGBHEHGAFBFHCECEADFDBDBCACACAEAEBEDDACBDFHFHEGC,False +67,24.0,12.0,23.0,14.0,18.0,18.0,15.0,12.0,CCCFCFBHAEEDFDBAADAEAEABDBDGEHEGCCCACECHGEGEDECACFCFCHBFBAGAFFGHADBEBAAAAFAEECEDHDHECGGBHHCHDBGBABAGEFFGFAFADACADAGADCHFECGFGFHFCDCEGFCC,False +68,31.0,17.0,27.0,38.0,29.0,28.0,14.0,16.0,ACACBCFDGBHBDEGEAHDDEFEFEFEFDDHECEBDFDAEAEFECECGCHAHAHCBCDAHBDDDDEDEBEHGDDAFEFCFDDBCGAGACCECAADADABAFEDACGCAFAHDFDBDGCECBGBFFCHCGAEDFFFHADFDADGFAFADEDHABAGAGEHEFBFECEDEDCGEADADFDHBHDFDCBCFCDAFAECFCEHB,False +69,5.0,4.0,3.0,4.0,2.0,3.0,6.0,4.0,DAHAGAHAHAHFGCGEBDFDEDGGCFBBGBC,False +70,5.0,7.0,9.0,5.0,2.0,11.0,6.0,10.0,HAHDHDHBGBFCACDCHFBBHBHGDEACACEGFCDHBGFGFGFCCHBFFHFCFAF,True +71,11.0,10.0,6.0,19.0,14.0,23.0,11.0,9.0,FHFEADABECHFFDFDFHFEDECEFEFEFAFHDADAEADDCAGFGBBHGDGABDDFFFFDDDADEEGFGDABCDGGBHDHFGAGBHBHBEBEGFFFFFCCEDE,False +72,25.0,17.0,20.0,19.0,16.0,13.0,17.0,22.0,GDCDHGBEAEGDGEBDBDHDCDCBHDEAEHDCEFAAABCDCDABAGADADCFAFCGCACAFFBAHGCGCGEGEACHHECACECEHEGGFBDHFHAHAHGGDGFCECHFHFHCHFABABFDGABDEDABABHEACAFDHHGHAHBBBBEH,False +73,15.0,19.0,20.0,23.0,23.0,21.0,22.0,23.0,GFGFECGCEEGHFCBCFDDDHHGBGHGHDCDCFHAHCCCFHAADEBEHEDEDADCDCABEGEFDFHCHGGAHAHFCFCEADFFECGBDBDBDCCACADHGCGEGHFHGHGBFADEBEBEDGDBBACEEEHGBDBFFFFDGEGDGDGFBEHHHHAAEAEFBBBBEFH,False +74,3.0,11.0,6.0,11.0,10.0,12.0,5.0,7.0,ECHFHDHEFFHHDCFGEGFDBEBEFFFDBCBFEDCDCFEBBFADDBDBGBGBGBAHAHFDEDECE,True +75,21.0,13.0,22.0,19.0,30.0,19.0,18.0,19.0,HAHEEEFEDHDFDBHBGCCEEFEGGHGHCCCCCHGECEAHDBDBEFGHCACGBEFEHAFDFACAFEEEHABAGAFDGDADADAGBCBAEADAEFHCDCFGEHFHDEDCDFEFCCCEAEAEGGABFGEDBDBHBCCECEHEAEFGHGHDDAEAEHCFGFGFB,False +76,14.0,30.0,18.0,20.0,25.0,19.0,27.0,30.0,FCFBAEDEGEHEBGHGFEFCGDBDGGCGCGBEBHBHEAAAEECBCBCFHFCFDGAEHHFGGGGGHCHEHBABGBGHHDFAEBDBDBDBCCHAGGEGDGCCBCHFGFGHGHBHEFGHBFBCBHEHBBABCBHBCGEHEADDDBHFHAADEDBFHFEEGEDHDHDEDBDFEFEHCHAEGDHBFBA,False +77,25.0,17.0,30.0,29.0,22.0,22.0,23.0,24.0,CCHEAEHBBCBDADBDBDHGFEECBDFGFEAHDCGCDHHEHEHCGCFHGDGAGAGACACDDDFDFDGECCHDHCCEFAFEBAFGGHDCCGEDBDBDBCHCACDBAHCGCGAHAHAFFFHADCDCFCFHHCDCAEAGAGAGABFHGEGBGDFHEBEFCFAGBEEAABAGDGDFDFEABHCDEDEHEHEFCFCD,False +78,9.0,16.0,9.0,5.0,4.0,15.0,4.0,5.0,BCEADCBBBBABABCCEHFBDHFAAGAGHCFCBCBFDFAGAGBFBDBABFFFFFCEHEBDHFFFBFC,True +79,19.0,17.0,10.0,29.0,13.0,8.0,14.0,14.0,DEDEAEAEDDDDDDDHDGEBEFADAGBFFHDGFBBBBGBABFCHGDFDEACBBBAHADAHCGCAHDHEHABAGCGCGEDAGBDAACAHDBCBGBGBEDDDDDADGDFDHHFDAHAEEEHCDCHG,False +80,9.0,11.0,7.0,9.0,14.0,3.0,11.0,16.0,HEHEACBHBHAGEBEAEBHBHBDEDCFABCGAEABHEHDADABABGGGDGHECEHHDGDHHCHCDGFFHCBEDEGEGHGE,False +81,4.0,9.0,4.0,9.0,3.0,6.0,6.0,5.0,BGBACACHDGDFDFBFEAHFBDDEDEGHGHBBBFBADHDGCGDBFC,False +82,11.0,21.0,22.0,24.0,26.0,28.0,21.0,21.0,EDGDCDCFGEDEFFFFGEEEDEDEDADACHCEBAFAFCHEDBFEDHDCCAHGFDFDGAGEFECEDBHCECDGGGGGBGFGBHCGDGFFDCAGDBCEHEGBBBBHFHADFHCHCHCACHCBBEFAGBGBEBFFFHFBCEDFFEFHDHFHFCCECBHBDBDEDEHBHEHFBFEGAG,False +83,2.0,4.0,1.0,3.0,2.0,4.0,2.0,1.0,CBFHFBBDGDFDFEGEABA,True +84,18.0,13.0,21.0,13.0,16.0,19.0,15.0,8.0,CBCEEADAFGDCFHFHDHFACACEDGACFGGGCBABDCCCCCCBABABABDBDFACGCGCFCAGEFEFBDBCFEFEAGFDBEFEHEHBAEADAFAFGEGECAHFEDGDHHCAEDEFCFGGGBF,False +85,14.0,12.0,10.0,10.0,16.0,19.0,9.0,12.0,FGBGHDEEEGBFAEAEDHGHGFEDEFEGEDEFEFCBAHCHCFBFDGECFFFGAECBBBDGFAFACACBEDABEBFHFHFHAHAHFEDCDCFCAAHBHADAFB,False +86,14.0,13.0,10.0,16.0,18.0,7.0,14.0,15.0,GGGGHADGCGCEEEDEDBAAGBCDAEABAGAFFFDBEFEAHAHBDBDBDBGHAACDHHGHGHDHEFBCDCHCHDEEBEBDADABEFECCGHGHFHDGEEEADBEEHC,False +87,9.0,13.0,17.0,12.0,12.0,23.0,13.0,12.0,EHCHBDDCECFCFCFABABGBFDFDCDHBGDHDGBGCGCGCFCDHEHEFCHGEAFBFBFDFHCEBAFEDEDFFGHCFGBGFGCDCEBGFHFAFBEEEBGFFCFAACAHAHF,False +88,6.0,3.0,0.0,1.0,3.0,3.0,5.0,4.0,GBGAGBHAGAGFEBEFEHHAHAFAD,True +89,11.0,11.0,12.0,15.0,16.0,12.0,7.0,10.0,BHBHDDADCGCAEHHDCEAFAFBFCDEDECBGFCECHAHGCAEDDBDEAFAFHFDCHEBEGEGADBDBHEHDFGFGFDECECECAAEBEBDBFF,False +90,18.0,21.0,18.0,8.0,15.0,18.0,18.0,10.0,BCBDGCBCHGHAAFAFEFAFDFHGGGCCECEHBHFCADAFAFEGBAAAGAFBEBEBEGCBHBFADAECDGHGBGECCBCBABHFFDCEFEHGBGBGBEFGABCBFBDBEEAHACGCGEGFCFCFDA,False +91,21.0,22.0,23.0,29.0,25.0,21.0,20.0,16.0,EDECECBBDBGGGDHDFCFDFAFGBACHDHDADFDHBEAACACACEDECEDGDGEGEGEDEAFCFEGGBEBGFGEDECGFAFAFGHEDFHFCFBFBDEDFDGBHEADHDCCFBABABACGEHAHFHCEGEGHBHDACADFCCHBHDCDCFBHAGDBABEBFBGCDBEBCDDADAEEC,False +92,22.0,26.0,23.0,24.0,20.0,30.0,22.0,18.0,ADAFEGHDHFFFFDFECADDDFHBHDCBFAHCHCACHEGFBFBCDHEFEGABAFAEBGBFFFBFCFGBHBEBAACAHAEDEDEGCDCDCDCGHACFCFHFHGCFCEHEHCGCDCEFGDGBGBGEGBABGBGCCABBBDBAFGDABFBFEFEDADBFEFDBHGHDFEFECBAGGCGADDDGBHAEA,False +93,2.0,2.0,1.0,3.0,0.0,2.0,1.0,2.0,DBDCDGFFAHAHB,True +94,18.0,8.0,12.0,13.0,10.0,9.0,12.0,11.0,HHFAEHCHCHCDDAFACACACGGFEFGCHDEEGCGCGFDDADGDFDEBHCDABGBABDGAGEEBAFABGBDAHAFAFADADEHHCHCBGEAEA,False +95,4.0,5.0,6.0,3.0,5.0,4.0,4.0,3.0,AHBFEADADAGFHFGGCBCBCBCFCEHEBDCEEG,False +96,6.0,10.0,15.0,4.0,14.0,9.0,14.0,11.0,ECECEGHGHEHGDACGHHHFGFGCCCGFEEHEAAACCHCFCFEGEDHFHFDFGEABBBBEBHGCGBEBGCACBEBEGCCDBFG,False +97,3.0,4.0,3.0,4.0,3.0,2.0,2.0,6.0,BGHFHDHDCDBDECAHAHAEGBFBHCE,False +98,14.0,9.0,9.0,12.0,16.0,15.0,11.0,5.0,BGGACFEGEGEAFGFGFGFAADADACBCFDADGEBHBFDFGBBDCGAFAEEFECHCDCBFEAEAEADADCEBDDHDBGEFCHEHEFEAEFF,False +99,24.0,22.0,16.0,19.0,18.0,22.0,22.0,17.0,BABDFDEDEDEHAACABAEAFFGBHFGAHDBCAGADEDCHBBGEGAGAGAGAGFGABEDEDEFCBABDBECECEAGFGEGBGACBFEHEHAHAFBFBCHEFGDADAEEBCBHHHFHFBAGGGFFFFGHDCCHAHBCBCHFGDBCCAFBDGGFDHDFDFDC,False +100,10.0,7.0,6.0,7.0,6.0,11.0,8.0,15.0,GGHGHGFEFDCHAHFHEHEBACCBCHFHFBCBEBFFEFHAHGHDAGADAEGBGHHBAAADCFHFDADFDH,False +101,21.0,23.0,9.0,23.0,25.0,21.0,22.0,21.0,EEEEEACAHEHDDADHFBFBAHGHGBGDGFECGBBBBFBFEFHFGFGFAEHDHAHAHBHGHFBBHGGGGGEHDDDDHEAFBHHDEFEHEDDGBCDCHBGDDFFCAHADEDEGEGEAABBEBDFGEBABCDFEACFDADAGAGEGBAFABHBDGDCEEEAFAFBFC,False +102,1.0,8.0,5.0,3.0,5.0,5.0,6.0,8.0,HCGCHDEBGFEFECBBBFBFGHGHGDGBAHCFCHHHEDEBB,False +103,29.0,22.0,27.0,17.0,23.0,16.0,31.0,26.0,GGHCFGEBEDGCCDEBFFFEFHGCDCBCBCECFCHCHCHGHCEGAGCECABHEEEBEBEGAGBBBABABFBHBHDHGGDADCCFAFEDECEABGBFAFHDAGHGHADEFGBDCHHDEDCHGABABFGDEAAAEBGAAEGGGGFGHAHDBDCCHGHBDGEGHGEAEACCHCACAHGHGHAHDCACAFAGAFA,False +104,7.0,6.0,18.0,7.0,11.0,12.0,24.0,18.0,GDGEHCGGGEFECEBECGCGHGCFHFHFHCDFDFGACHHHGBGHACDCGAGADBCAHECACGHGHBBCFGHEDEFEHGHBHGGCGCGCHCEGGDGEAFFHFCF,True +105,16.0,23.0,21.0,18.0,22.0,17.0,10.0,18.0,ACEGEHEHAFACDCDCHFBFBGBHDFFFCAGHBBBHBHFABABABAHEGCAEEEFGBGBADGEBCDEHEBCFCHBHEFEBDDDDDDDGFEDEFEHAHBCACACBDBDHDCBCEDEHEGCCFEEEDHHAABCFCHAECBCBFFCFG,False +106,9.0,10.0,12.0,6.0,8.0,7.0,13.0,7.0,FABABHCEGEGBGBGCCCHCAAABGEGDGFGFAFCBCGCEHDCCAGHDHCAEHFBFAGBGBGHFDCDBEEDE,False +107,17.0,15.0,17.0,17.0,16.0,26.0,15.0,17.0,EFBHGEAFDGCGFGFGDEEAEGBDEFBGGFAHHCAFAFHBHBDGDGEGEGDFFFDFHHHAHBCDADBCBFGFCBCBGBFEHADAHCECFCECHBFFFFCDEDEDCDEFEFCHHHCACAEBCGAAAAHADAFHFBDBCFDF,False +108,20.0,24.0,27.0,23.0,19.0,28.0,19.0,18.0,AFAEGFGFGAHFCFEHEGDBBBEBEBEBCDDDHDFGFDCDCECFAFAHAGBBBEBFDEBCBAHGFGAGABDBEAGFCCCBEBHCDBDFDFBBHCHGGCDCDFHEHECGCFFFADAHHHDCDAEEBFGAEHCDDGACACACFCBEFFHAGCCCCEFEFCABDBFFFGHCHDHDFDGBGA,False +109,9.0,16.0,17.0,17.0,16.0,16.0,12.0,24.0,EGDDDAHBEAEABDCEBFFHFHFHCDGHAHCCFDFDFDFBBEBFBFEHGHGDCFCGHGHGCBCEDHBCDHFHFBFGDGACCCGAEBHBABCHHEHBDDEHEDEDEGEAHDHCECFCFCBHAHEGBHH,False +110,5.0,7.0,7.0,3.0,11.0,14.0,10.0,14.0,AHEHDHGFEFGCHFGFBBCAEFEFEFECEHFHBHAHFCBGFABHBEDEGCGFDFACGCGBFEFGHHHHEHG,True +111,20.0,16.0,22.0,22.0,11.0,17.0,13.0,10.0,ACAFFCDCDCACBFAFGDAACDCDEDEFFCBHDGDCDGDEABFEAADDCAHHDHEGACEFBCBCACACABBHDHDHEHCAAFAFCDDEDFDFBFCFBFDEDFFGGAGCCBEBCBHBAGGGGGEGACBHBDB,False +112,26.0,22.0,28.0,29.0,20.0,26.0,21.0,19.0,GCDCBAEHEHGGFABGFFFFBDBDBHCHCHAAADGFCBCDCFFFDCHCECEDEAFBFEFEGGCDCDAEAECFCEEACCBABGFDABADAFHBHFEFEAHAEADFCFHHBHAHAGGDHCCCDHBCADABHBDCGHGAGAGDDDFCAGBCBDBCFCFEHEDEBGGFGFDBCGAGDCDEDGDBDBEFEHAFADD,False +113,4.0,0.0,3.0,3.0,1.0,0.0,3.0,3.0,HAHADDGDHAGAECCCG,True +114,15.0,25.0,14.0,19.0,17.0,16.0,17.0,18.0,GDGCHHEBEBHBEFAFEFBFHFBGHEFEFEBAAAGFGDDFDFDFDBDBDBABABDHCBGDHCEBBGBCBEBAGHCHBEBGHEHEHEACACACACBBGGFGHCHDGBCDGEFDFDBEHECDGBCEHAHDHACFGADFDBAGD,False +115,4.0,7.0,3.0,5.0,3.0,0.0,6.0,6.0,HGHBHBDBABACEGDGEAHBHADGEGCHCBDGDB,True +116,18.0,19.0,11.0,27.0,26.0,22.0,18.0,28.0,FDFEHEBGBGBCFDFDFBEGFABHCHEEFAFAFAFBDHEHEABBDCHCDDGEHEADAFAFBHHCHBFBEDHGHGBFDFGECHHABDEGECEDADEHEDCAHAGEBABCDCDAHEDEDEDFFFFFBFHGAFEGEGDHDHGHGHGEDHDGEGDAHABBHHDHBCDADHEGE,False +117,9.0,10.0,11.0,5.0,12.0,11.0,5.0,12.0,HFBFCFBAAEABGHCHAFABBBBCCCHCECECHCGEHEHEHFHAHCEDDFDCEEBFFFFGEBEAFAHDGBGDEHA,False +118,1.0,8.0,6.0,3.0,6.0,11.0,9.0,8.0,BEBFGFGFBFBGBCDFEHBHAGEFHGDEFBFHHCGCDBGFGFGHCHFHCECE,True +119,16.0,21.0,23.0,14.0,8.0,20.0,24.0,21.0,EEGFBBADAFCBHFACCCFCFEFDGAFHFDABHBCGHHHBHGHCHEGCAABBGDHBHBGFGCGCGCGHFEFCFGABAGGCGAGACFCBCBHBFCFADHDHGHGFDEBEGCGCDBHBEAACHDDFDCDCFBFBGGGGCBHDHDHFABA,False +120,23.0,16.0,16.0,25.0,12.0,20.0,24.0,21.0,DFHFBBDGFFEDCHEEGGGEEADAGAGDBDAABFDFCGDGAABABABABACAGGHDHFACECBDDFDHGHGHBCBCAGFGBGCFFFDFDCGHGDEEHBCDCBHBCFGFDFDHAGCHHHHHGAFADDHEHEAGAGAGHCBAEAEDCDADCFGFDHDHF,False +121,19.0,17.0,15.0,20.0,28.0,24.0,23.0,17.0,DCDFFGAAFFFBGAGDGCACHEHDADADFEHEGGFFEFAABBHGGGFHEHACACBEEEHBAGAGFDFEBEGEBECECDCHBHGDGBEFEAEAEAECCGCEHBHCFFGBDBDCDAEEEAEFFFBHAHGEDEBGFGFGHGBGBDFDCDHEHDDDEBAFDFEGCFH,False +122,24.0,21.0,31.0,19.0,20.0,33.0,21.0,17.0,CBDGEGCBFGFHFHFEFBDAECCCBCBGHDCCCAFADHDHDEDACBDBGAHABFDGEGCHEECECDAFBGBGBFFFFHEAECHFHFHGEEBCFCFDGEGFFFFGCDCGBGBGFFBFBFAAAAAFGBAFABECAGEGBGFHFCADDCECHFAFADAHFHEDEHCFBACAEAEFDCCCCCBCHDADCG,False +123,23.0,22.0,33.0,26.0,18.0,14.0,26.0,19.0,DGDGCACABHFCADADGHGEEHGACAHAGACEDEDEDGDFCHDECFCBCGHGECHCHBEEDEDEDEDCBGBGBABCBCBHAGDGECAGDCCCFCDCFHFDABECGBGFHBBFBEBEBACEDBHHCCGCDAGGGFCCCGDDFCBCBGBGHGHGCBADHFFAHDGAAAAABAFDHDHCFCEAD,False +124,14.0,14.0,13.0,14.0,9.0,17.0,19.0,18.0,DCBFBFAFAHBHGFBABECACGGBGCGCFAFHHDGDGEBDADFFHHHHDAABHFFEGAGFDBGHGAGBGHFHFGCHCDGEGEFCGDGDCDCDCECBFAFCFHAHEBEGHBEBHHADAD,False +125,22.0,17.0,18.0,14.0,19.0,23.0,19.0,20.0,AFFEGCACEHAHBHFHECADBDEDHDHDACHCBCBHFDDAGHGHCECEAEAHBHGGCEAFAFBDGFFFFBAGAFAFHHCGDFFAEBBABADADBCGHHHGACACFCFDFBCGHGEGEGBGBCBEEAFHEBBGGECEFECEHGGEAFDFDFAF,False +126,2.0,2.0,5.0,1.0,2.0,0.0,0.0,0.0,CBABCCCECEAD,True +127,9.0,13.0,13.0,20.0,8.0,15.0,15.0,18.0,GGEFDFEHDHDHBAGABBBFFHFCFHGHGHGHGDADHDEDFCEDAGAGCBDFDHDHCBCDFDBHFHGHFBCGDDDDDABGHDHCHAAECFBDBEBCBCEGECCFFHCGAGF,False +128,26.0,16.0,20.0,13.0,15.0,14.0,8.0,14.0,AFAFGCBFDCCGCBCACACAFACECBAFAFDBBABABHECBGAHADEDCBADABABAHEHCHCHGECDHDHBHBAEDEAEAHBGFAHBBCACACAFEDCAHHEADGEGECEFFFCGHDFDEAEFFD,False +129,3.0,2.0,3.0,1.0,2.0,1.0,0.0,1.0,AHABFBEAECCDC,True +130,3.0,10.0,5.0,11.0,10.0,4.0,3.0,9.0,DBGBHBAEDEBCCEBAAFHHDHDCBEDHBHBHBDECECEDDDFDGDFBEGEHEHF,True +131,18.0,19.0,23.0,22.0,20.0,20.0,15.0,23.0,FGBCAABCBCDCDCBBAAADCEGHAFDFEBHBHAHGDAEAEAHGECHCDDFDBEBHHHDBCFCABFHHHABFHHEGEHBAFAFCDCHGEGEFBFEFEDEHCHCHDHDGFAFEBEBGBGFCDCAEDEGFFFHFBEAGACFDDDDHDCCCCDCDGEGBGCEH,False +132,27.0,13.0,16.0,13.0,20.0,12.0,27.0,15.0,HAACDHGHEBFFCDAGADAEABAGHFHDHCCAEHFHBGBECGGGGAGABACDEDCACACFGFGFHBBEBHGGGDABGGGEDECEAEAEAFCEGBBBAGAEAEABHEAEGGGCEHFHDGAGEDEDFDHDEAAGAHAFFGCCCCG,False +133,5.0,7.0,9.0,1.0,6.0,7.0,8.0,7.0,BGCFEBHHHHACABFBFHFCFGGGCCECGCGCHAEBBHFGCGDAEAEBEF,False +134,14.0,15.0,11.0,16.0,21.0,17.0,16.0,20.0,HBHDHFHDDEFEGEFEBGDFDFBBHBAGEGCFHBHDADHHFAFAHECEFADECEDDDBDBDACBEAFHFHGEGCGDECECBAGACHBHGHFHFHGEGFFHEHCHCEGEGEAEGDGEABDBABFFGECABA,False +135,8.0,3.0,1.0,2.0,4.0,6.0,9.0,3.0,GFGEGHGFEFGCGDBAHAFDEAEGBGBAAAFAGAHF,True +136,14.0,29.0,20.0,23.0,25.0,22.0,18.0,18.0,DGDCEBGFHDBFBECHFEFBDEDCACGCGHEFEFEFAFGGGDCFGFHFHAHADEBBCBCEEEFEBABCBEBACACBHHCFCEAEAGBGDCDBDEDGBACECBHEHBDGDFDGCGAFEFDBHBEBEAHGFCFBFBHEDFDGDBBBBACDBDHGBEAEGFCHBHEHDHDFD,False +137,3.0,5.0,1.0,6.0,8.0,6.0,3.0,5.0,FDFDBBBEDEHEHEFEACFFGDHDFGBHAEAEBEGDH,True +138,17.0,19.0,28.0,23.0,19.0,29.0,14.0,27.0,EEHFCDHDHBAADFECECFFFCDGBAHAHFHBCDDFDGDADBCAAHABAEGFHFHDHDEGCGHGHCFDFEFGBHAHBCBABEEECDCDEHFHFBABHCCCACHEACHDGDFHFHBHFGDGDGDFBCDCGABFFDFECHCFFFHFCDGEFCACHCHCHEGACFCFBFEEECEBBBBD,False +139,18.0,10.0,15.0,7.0,19.0,9.0,15.0,15.0,BCDGAGEBBAAFCBEFDFHCAAHABFEADAHGCCCACEDEDEDEDEHCBCFEHCHEACACHGGGGBGEGFGFEHECGFEAHGHEHEHEHACAFBGGABABHGHEAEAC,False +140,12.0,11.0,10.0,15.0,15.0,9.0,10.0,21.0,GGDEDEDHDABGBDCAFADADEEFHFEEBBAHECFCAHGHGHEBBCBABAFHHHHAFADHECEGGBGECECHBHECFCDDDEEHHHHHDHDHDHFACGDABFG,False +141,6.0,7.0,16.0,10.0,19.0,4.0,7.0,3.0,GAGEECEDBGBGFCFCHCFBDBDECEAEDBDCHBEEFAHAEAEGCBCEADDDDEGCCEEEECCCECDCGCEE,True +142,17.0,14.0,17.0,18.0,21.0,18.0,15.0,9.0,BADAGADHDGDGFHFAFDFGEEDDDADCCCGGECCCGEHAHAHEEEEAECFCDHDFABABFBGBCACEFFDADAEEHBHFDFCBEBGHGCFCDAGFDBEFFGFGEGCBAEDEBCBAACDCBEBEFEFEG,False +143,1.0,3.0,4.0,4.0,2.0,3.0,3.0,3.0,DHDCCGCGAGHBBFEFCFDHDEB,False +144,3.0,1.0,7.0,1.0,1.0,3.0,7.0,2.0,CDCFHGGFBCCCCGAGAGAEHFGCG,True +145,3.0,5.0,7.0,4.0,3.0,11.0,6.0,3.0,DHGEGBGBGCCFDFAFHCBEBEBDFCFCFGFCCAHFFFDGAF,True +146,4.0,13.0,6.0,8.0,6.0,15.0,9.0,3.0,FABGBGFGFDBBBCGEEEEBFGCBFBDBCFDFGFGFAFECCDDADAFBDGHGBFBFHFEFHCBD,True +147,16.0,16.0,22.0,23.0,21.0,20.0,35.0,29.0,FBFEECGAGFGFGHDHDFAGEGEHFHFHFEGHGCEEAHDGDEHEGEFHFCFHGHBECDBDBHHGGGGGGCBHAHACAHAGEBDCEAGGHGHGEGEBDAHHHCHADGCFBFHGBGCHDFDFDGHCBCHHAGBEBDACHCFFGGGDADEEAGCEDEDCCCGDFDBDGFBFBGBDEACACDCDCH,False +148,16.0,20.0,20.0,23.0,21.0,16.0,31.0,18.0,EBEHGGGHCACFDDDDDAFCHEGCACFCFDFAGADEGGGAGEECEGEGEGAFFDCBHBHDHEGCDCGBGBGCCCCCBDGEBCGFHCHGHAHBBCEGEGEBFBGAHABDBDAGAGFGBEEEFEDGDAFCHBABGBADADEGFFDHDCFGGDHBFBDEDEDGHHHBH,False +149,3.0,7.0,4.0,6.0,10.0,7.0,3.0,5.0,EBEHEBEDCFCBBADCHFHFGBGBDEEEECHBDADADEFFFGFHE,False +150,6.0,2.0,7.0,6.0,2.0,3.0,8.0,0.0,DDDCGCADFDFGGGACACAGBECGGDGABACFCE,True +151,5.0,2.0,2.0,0.0,5.0,4.0,2.0,3.0,GAGAFBFEFECEFHABAEHEACH,True +152,14.0,12.0,9.0,7.0,12.0,11.0,10.0,17.0,FDHDFEHDHCFCBCDGHGCFFFBFHACCHBGAGAHEHEBEAADAHBGBFBFBABABAHAHEEAFHEHBHEHABGGECDCECEAGDHAHEFGG,False +153,19.0,24.0,27.0,19.0,23.0,23.0,26.0,24.0,CDCGGGFAAGACHFHDHDHBBCCHCGFAHABGBEDHBGBGBABADECFFFFAGGCHDDGDGCGHGHGDCFHDHAFEFEFEHDCCGGBGEGAAFCEEDFDFGBEAFHFCGEBCBHBFBDCDGBCBEHADABCHCHEHEHBHDGFGAGEGBBEBHDEEHAHAEAECCFFFCCCECECEFBFBDECBA,False +154,13.0,10.0,11.0,9.0,11.0,8.0,12.0,4.0,GEAEAFAGADADAEFCGCGCGCAFBFBEECEGADADACBGBCHHBFEECACBEHEFBFBDADEDBCGGGBDFHCAGGD,False +155,23.0,15.0,20.0,21.0,22.0,13.0,16.0,23.0,FEBEBEBFDHDHCCDDBCBEGFDFGBHCHFDAEBCBFHAHGHDADCBGDHDHDFCAHHHDBCEHDFDAAECDCDCBCAFEEEEEAEAGACHCEGEAEGGGGAEABAFAFHHGEAAACHFHAHFGEAEDEDEDADHDBCGAGACBCHHBGGCHC,False +156,1.0,2.0,8.0,2.0,1.0,1.0,0.0,3.0,CCCCCHCHBACDCBHEDF,True +157,11.0,6.0,5.0,14.0,10.0,10.0,2.0,6.0,EFAHAHFBFGGABADFCBEDEDADAHAFAHBFEDEDCDEDEDEDFFCBEDFDFBACDDAEHCHA,True +158,15.0,22.0,16.0,16.0,9.0,21.0,17.0,9.0,CFCFCAEBDGDHBBFBHCAAGFFFAGGGGFGHCHDBDBECECECFHBBCBAFHFDFBCACHCAAAEFDBDBCFGAADADAGGBBBGCGBGCFBEEGHGFGFDFDFABABDFHFDBDCEFEBGDDB,False +159,3.0,6.0,10.0,6.0,2.0,3.0,4.0,5.0,GGGFDFDBCBHBHBCCHCBCEHHFCACDCBEDDDACGCA,True +160,7.0,12.0,7.0,6.0,6.0,8.0,8.0,5.0,AEFEFEBCBADCEFHHCHGBBECAABFBFBDBGBHECGDADADGBGAHFFCFCGDGBGB,False +161,25.0,18.0,13.0,27.0,15.0,21.0,17.0,28.0,HFHGDDBDFDGHGADHGFBHGCFDAECCHHEFEFEDDBEBAHAHFHFBFHAHDFDFAEDFBBCEHADGFGAHDGDGDGDFCBCEAEBCBHDHDHAHAEADHHFHFHEGBHEDABABACDCAEFDDGFGAGABAHDHDGDGDBHBFAABAGAECECHCACBFAFH,False +162,18.0,23.0,16.0,12.0,17.0,23.0,24.0,31.0,AEABABCBCHCHCFFFBHHEGBABDDDDDHHFHEECFCFCBEDDBHBHBCGHDFAFHCHFGCHHHHHHHCFGFGEHDBAAEGGHEBBHGDAHFHBHBECGFAFBGCAHEHGBBFBDCHHGEAEHGFFFADGEGBGBGCGFFCHGEGEGAGAFABABAEAEGFGF,False +163,24.0,23.0,17.0,16.0,25.0,31.0,34.0,30.0,FHFHFEFGFBAEHHHDHDHFGGDGDGFGDHACAFGDGDECECHCGAHAHBBBBBFFFCGBGEFFHFEAECGGBBAGABABAFHFHECGDECFCHDBACDEHBFBHBFEFDDGCHBHGHGHBEAGFGCEHFBAHACEHEACFCFEAEGEGAGACFEAEBGGFDBDBGEGECEAHHHAGBGHAFDFAFDFGBGHGFGAGHEE,False +164,16.0,17.0,19.0,27.0,19.0,29.0,35.0,19.0,GDGBCCGCAFBFGFDHGHBFAFGFGDDECECDGDCDFHFGFCFHFEABACFHFBFHEEECEDFDEDGGGDGCCBBDBFBABFBGDEDEGBHBDDDGGGGCFHFGFGFHFEABBDCDCHCGGGDGFGEDADHDECEAGAFAHEHADAFFGGGCABEGHCAEFGFGAGDDHDHBCEHGAEHFH,False +165,10.0,7.0,7.0,12.0,6.0,6.0,5.0,8.0,DGFFDCDCDAEGDBDCEBGACECHCECDBABDEAHDHGAAHHHFHFBFBGBHDADADAFAE,False +166,17.0,18.0,17.0,16.0,20.0,19.0,17.0,15.0,CACAHAFBDAAADADHBGFAFDGDGDGHHFHFGFGFHHCAAEBFBFCFAHEBABEEGEGEGEBAHGDCDGEBCHEGDGCFCEEFECBCFHBHBHBADDFBFBGDCBCFFEGCAEGEFBACDCECECFDDADEEEGHBHB,False +167,15.0,4.0,11.0,15.0,21.0,12.0,17.0,17.0,HHAHDEDGHFHEHCHGFGFCECEGEACFGDGDCDCHADCEHEGGAEEBEBFHHHCHCHCFDAHAGDGFGDDHEEGCAEDEABAEGEGHGDDFAAEFGAGAEAFAFDFEEBED,False +168,8.0,4.0,9.0,2.0,9.0,7.0,3.0,7.0,ECECBCHFHCGFGFEEEHEHECAAHAFFBAEAFHBGAEAHDBDACCCFC,True +169,16.0,14.0,9.0,11.0,11.0,11.0,12.0,11.0,DFDFDGAGAGAGFGHHACBHBHGFFDFGBCEAHBDAEADACCECAAEABBHEAEAEDEDCABABCBGGGGFFACHHBDBFFDFEEGBCDHEHBHB,False +170,4.0,2.0,1.0,1.0,6.0,4.0,5.0,2.0,GGDBEEEEBEAGFFCFGFHAHAEAG,True +171,28.0,14.0,20.0,10.0,8.0,25.0,20.0,36.0,HCHCDCGCDAGAGHGBABAFAFCFAFDFGFGEGHFEFHBHGFGCHEHABFGFHHHCFDACHEFBHHHCHAHGBAADCHBHBFAAAHHHFEGCGDAHAGFBFAADAEACFFGAEAGABFCHCBFDEAGAHBHBAAHHHFHFHCCACGHGHDHDHCHCFCBGF,True +172,3.0,11.0,4.0,4.0,5.0,7.0,5.0,5.0,BBBEBHHCCFEFGFGHGBBBGBDFAFACEHFGFHDBDBABCDEE,False +173,8.0,13.0,6.0,15.0,4.0,10.0,15.0,7.0,ACDCGBGFFFGEGBGFHBHDADHDFGBGBGHCDAGGGCHDHGADDDDDDEBBHBFBFGFAEADGCCBDBDGAAEFBFB,True +174,10.0,11.0,8.0,10.0,13.0,7.0,14.0,11.0,GCGCGCGFGEBCAAEEHEAEHDHDGAADADADFBEDECHCGGGHGEEHBHAHABFBEBHFADGDHEECHBBFBGEGBGDCFBFD,False +175,23.0,12.0,12.0,24.0,26.0,34.0,26.0,24.0,CDBFHAHBGAAFEGHAFGCAFGFGBGBEBEAFGDGDFDADCFGEGBFCHABFCGADHFFEFHFEFEFEDHFGCGEGEAABEGAGHGEAFAFAFCFAEDEDEDHDHDHFFFGFHACEFHHHDHDAGFDFGEGBGDHDBABAFEEEHEBGFGEEAEAHHFDDDGHGHDFCFCACHDDEDEFHC,False +176,18.0,8.0,20.0,16.0,15.0,17.0,11.0,11.0,FCFBECGAFAFABAEEEEDCDAECEDGAAADFHBDBECEHEABABCDCHBGEHAHAGAECHHHADCCCCFCDCDAGCFFEEAFAFGDDFHFHFHDBGGDGDADFGCECFCGCDCFF,False +177,13.0,12.0,13.0,12.0,6.0,11.0,5.0,9.0,DABFHGHCBDBDCFFGABAFEBACAHECGDFFHFHFDFEFCHCBCBAECGCGCHEAEADDDBDADAHHBACABACDCDBFB,False +178,7.0,14.0,10.0,12.0,19.0,22.0,10.0,9.0,FDECFBFDFDFHFGCEDEDEFHGBACCEGGAEBEGABFDFDFCHGHFFEDBFBFBFEGEHADAEFEFEFEABCFHDHDAECFCGBFBGBFBEECECDBEBHGH,False +179,2.0,2.0,2.0,1.0,5.0,4.0,1.0,6.0,HGFEHEHEFEDAFHFEABBCHCH,True +180,2.0,5.0,1.0,3.0,3.0,4.0,0.0,0.0,FAADBBBBEBEFEFDDCF,True +181,6.0,7.0,5.0,2.0,1.0,4.0,3.0,6.0,BHBDBAAGAHCHFHACAHEHBBBFCFCACGGDBF,True +182,2.0,3.0,10.0,6.0,8.0,6.0,4.0,4.0,BCBCECEAEDEDHCCCCHEHEGDGCFFFAHGBFFFECDDECGD,True +183,27.0,20.0,35.0,20.0,19.0,18.0,17.0,19.0,CHCHCFCBDEHBHEHCCCCBDBAADFFECCGCAEAFAHCFGDGAGACABFEAHCBDBDBDACGDEDEDEHEBGDGDCAGABEBEAECEGAGFGCABFGFCEAEAGACFCDCFFGFEHBDBDECACAFHBHCHBHBFAHDBCADHEHACAGDDDGCEBFBFCCCCGAHCFCACAHH,False +184,21.0,29.0,29.0,14.0,13.0,23.0,22.0,20.0,HBBEFAHAHDHCHCGCBCAFABDDHDFAAADBDBEBCBCBEACGCGFFBFAFHGHFCFEHCHDADFCFCEDBGBCCFCFGFHCHCACBEAFBECFCDAGGCGFGHGFGEGACCDCBHBACGFGFHFBFGEGBCHCBCDEBBCHGGBGBDDFAAAEBEBABHBABHGEGBHA,False +185,16.0,21.0,7.0,5.0,16.0,12.0,3.0,15.0,BBBHGHBACDBEAAAFDHEHAGAGAEEEHHCAEAFBBABFBCECAFAFBFHFEDABBBFBEBEBEBACHFHFHDHBFEAEBHAFCHEDECEHBHB,True +186,26.0,34.0,20.0,22.0,24.0,21.0,26.0,17.0,HFACACHCBBBBHBGBEHFHFEAHAEAEFDBHECAHAHDDBGEDCBEGGFGECAAADBEBGCGCFCFCFBFBFBAGCBBABEHGCGCGFGBBCHCEDAHBCEAEHDBAHGGDDDDHEADDDDDFFGBGAGBGBEBABDBDGDGBFBDBDBDHEFEFCFEAAFGEBCGEGBFFGCGAABAGCHEEEAFAEA,False +187,3.0,5.0,0.0,1.0,1.0,2.0,2.0,4.0,DEBGHGAFBFHHBHBABA,True +188,8.0,11.0,10.0,11.0,8.0,19.0,14.0,12.0,HGFBFHFBFGGAHDDEBAHFHFHFCEGFGFGFGBGEGBCEEAFDBBBHFHDBDBGACHCHFGCGFGCGFBCDCDFFAEAHAEFDFDHAECDCD,False +189,24.0,32.0,23.0,32.0,21.0,21.0,20.0,22.0,BBBABAEECDDDEDEHEBECEDEDHHHFHFDFHCDAHAHDBGBGEGFGFGFGFBAGCGDFBFHDHBBCHGHGFAEBEDCAAGFDDADADBDCFGHBABDHECBDBAAHADAGCDCBABABGBHDCGCBCGFEBDCHAHCCCFCFEBABHDDBGBHHCCCGBABDBCEEGHAFEFEDDBAFFFDFDCEAEAEGDBD,False +190,13.0,10.0,11.0,9.0,7.0,16.0,9.0,11.0,AGCHAGCBAHCBGBEBEACADADHDBFBDDAGEFCFCBHDEFEFHFHGHDFGFACAEFHAEAGGBGFCFCFHFDFCFCBBFDAHAH,False +191,14.0,3.0,6.0,9.0,14.0,7.0,4.0,6.0,EAEFDGEEFCCCFCFEAAAEADCDAEAEGGAFHHHHEAAADADEFEBDBAEGECEADFDHDHB,True +192,6.0,4.0,7.0,3.0,3.0,3.0,1.0,4.0,CFGEHCCFCBCEAEHCHDADADABBBACAFH,True +193,29.0,36.0,21.0,12.0,18.0,14.0,23.0,24.0,BBHFFFCEHEGEHDHBGBHBHDEBHBHBEAEBDBFHFHEHABADACGGGADBBHHFBBBAAAAABECDCACHCAGACFCFAEAFAFAGGDAEBDBHBEBGACBHFAFGFGBBCAGGBGHDCBBDGEHEGEACACACEBEBCACAEGDGHCBDGHGHBBABCCHCHCHGBAEAGBFBG,False +194,6.0,3.0,5.0,1.0,2.0,4.0,8.0,5.0,HBHGGFCFCACAEABGEACDCHBGGHGAGAFHFG,True +195,3.0,6.0,4.0,7.0,9.0,15.0,5.0,10.0,HAHEHFGFHHGHGFFCFCEDEFEDBGBDEDACBDFHEBFHFHFEFDFCFDFABEBGHFE,True +196,2.0,2.0,8.0,2.0,3.0,5.0,4.0,4.0,CCECHCDCDCEBHCGEHBHGAAFFFFGFGC,True +197,0.0,3.0,4.0,2.0,1.0,2.0,3.0,2.0,DBHBDFCCCGCGBGEFH,True +198,9.0,8.0,9.0,4.0,11.0,7.0,12.0,11.0,AAAFADHGGGFGCBCBCHEGEFEHDCABDHGEGEGDACBFHFBEBGBECEHAHAHGBECFCGEGAHEHCHF,False +199,9.0,8.0,10.0,11.0,7.0,10.0,5.0,6.0,ACADDFDHDABGCDEBEHAFFBECECDBBABAFAFAEAFHDDDHCCDCGCGHGDGHFCBCBFFEFE,False +200,15.0,9.0,5.0,13.0,12.0,23.0,15.0,22.0,CHGFEHBDGDHEHAHDFDFAEBDAHEFEFEGGGGAAAGEDAHGHGHECEGFGFGAGBFEFAFBFBGBDFAFHDHBHFHFHGDEDHFFCFEDBDHFFFAAHBHAHFCFDHHCHAA,False +201,8.0,4.0,6.0,6.0,2.0,3.0,2.0,2.0,AGCFBBCBCDAHABACEHDADADCDADAEFGFC,True +202,15.0,30.0,30.0,30.0,15.0,29.0,25.0,23.0,DFBBDGHBCEDBFBHBHBCBHEGGGEBEBHHEHCFFHFGBHEGBDFDFGBGDFDFHCEFHCGCFDHDFDEHADADEBCFEFDFEFECDAAHFGDDDCACACACACDBABGGEDAABBBGCACABFBGDCDAGGGGDCDFFFGFCBBBDBDHECGHGDGCGCHCHFBFHHHDHCEBFDFDFCFCGCBCBCFCDABHCG,False +203,14.0,19.0,19.0,3.0,12.0,14.0,16.0,22.0,CHAEADAHBHBHBHBGGDBHFHEAAABCBGEFCCHFEBHCHABABFHCCCHBHAGAFCFBFAAAHCFCGEGEHEHEHFHBHEGFGHBEGGGCCFGFGCDAECGCBBGBFBCHCHCGBFE,False +204,9.0,15.0,19.0,11.0,9.0,19.0,20.0,15.0,FAAACCHEGCGDGBHDCCCEBAHDGDFDBDBHCFGFCFCBCBFGFGHGBFBHHHFHEGBGBCAEBCCCFCFCHGAEFEAGCDHGHGFGFGCGBGBGFDACEBFDFDEHEDGHABFHF,False +205,20.0,16.0,16.0,34.0,30.0,20.0,29.0,29.0,CDCFGDGDEFHGHEHEGGBGBGBHBGEFECDCEBGDAHGCBDDGDHDHEBEDDDDHAFAFDEGCHEGFHFADBEEGAGDGDHFHBDEAEAHAHDDDECGBADEHEFEFDACAGEGFGBDEDECHHHEAEFFBADDDDAEAHHDHDCCFCAAAHCFCFEGHHHHGBGBDCHCHDFDGGEGBFBGHFAFEGEGEAE,False +206,20.0,18.0,16.0,14.0,21.0,4.0,6.0,11.0,ABABAFADEDBAECHGDDAAHEBBDBACECGAAAACHEFEBCDHGBCECECEBEFEAECBCEHEDGAHACADAHACECGDDEEECEHHHFECBCBEBHBDBDBDBAGDBA,True +207,1.0,3.0,2.0,6.0,1.0,4.0,1.0,1.0,FCADBDBGBFEFDFHCDDD,True +208,5.0,3.0,5.0,6.0,4.0,0.0,1.0,2.0,DCCBCDCDCAAAAHDHBGAEEDBDEE,True +209,9.0,6.0,7.0,6.0,5.0,8.0,3.0,2.0,FCFEAEGDADABCBCFGAGCFAFABABCBDHCFDFEFEACBDHEAD,False +210,21.0,21.0,15.0,16.0,11.0,15.0,20.0,12.0,CACFFACCCEHFDBGBGBFHFAGDGDADACGGDGBAACABBECECEGEDHDHCABDFDFDAGHGHGBGBFBGEGBFDFAGAEHFDAHEGABABFGAGEBCCGCHBDEDGBCACFBFAFHDBEBHBABADAH,False +211,10.0,24.0,13.0,13.0,14.0,11.0,16.0,23.0,EDEABACHGHAEGGBBBBECECEBBBAHGHGHCBCECDCBFBHBHFHFHFBBDAGFEBHAHDHGCFAGABCDDBEBEDHGHBCCACFDDBAHHHGBGBGEGEGHGFEFHHHDDBBCDEFGFHDH,False +212,19.0,7.0,17.0,13.0,17.0,11.0,21.0,24.0,FGCAHAHFGEHAAAAAHGDGHGFEEGDHHAEAEDCDFGBGDHDGFECECGGEEHGHGHCFBBHBFEEHGHGHDHFHDHDAAAHDECAAACBCECACAHFDFCCCCCCGGGGGEEEDHBHEFCGDHAHAB,False +213,10.0,20.0,7.0,7.0,13.0,11.0,10.0,5.0,HACBEBEBAGEEHEDAFABBFEEEBGBGBGBAAEBBDDFDFDFHCHDDAFECHBBAFAGGGFAFCGBEBEBEGGBFFCBCBCB,False +214,6.0,9.0,11.0,6.0,13.0,4.0,11.0,19.0,ECECBCFDGEGBHEDDHGEBHHGCGCBHHHHHEHEGACABADHFFGCGBGHDDCEEEEBEFHAECBCHGHGHBHAHAHC,True +215,3.0,0.0,0.0,3.0,3.0,2.0,6.0,5.0,HDFDHEHGGGGHAHAEGEAFDG,True +216,1.0,8.0,11.0,12.0,14.0,8.0,9.0,12.0,GEBDBDCCADDBGFGFEEGEGCDCEFEGEBEDCCFBHCEDDGEHEHDDFCHHHBHBHBCDFDEGEGCHCHEHFHF,False +217,10.0,10.0,22.0,13.0,14.0,8.0,15.0,10.0,DCHGECECEAGHEFGACFBGBECGCAEBEHHAGEGFDFDFHEDDCDBFBABACDDHDBDGCCCGHGACFCFDGCGCBCBGAGACECACBCECGDHEHEHECD,False +218,7.0,10.0,14.0,5.0,9.0,7.0,7.0,16.0,CFCECECDHHHHHHHHBBBHEFCCEBDBABAGDFDHCHGACCHCHEFEGHGDACFBGBCEEEFGHGFCBCHAAAB,False +219,15.0,20.0,16.0,12.0,13.0,12.0,14.0,14.0,AGAEAEAHGHFBFEHBHFGGEEHCFCDADACBDBFBCBFGFBBBCCAEGDGFAACAHBCBCDAFHFHECAFFEGEBCBGGCDCDCDEBBDBDBHHHHHDGAGDCHCAGEGABBEBE,False +220,0.0,1.0,1.0,0.0,3.0,3.0,1.0,3.0,HEHEHFFFGCBE,True +221,4.0,7.0,18.0,11.0,9.0,20.0,14.0,16.0,GGGBFCCCFBFDGCFCFDFHFHCDCDHHHGHFDCAGHCBAEEFEFEFHAEFCHCGEFCCCHCHEHCDCDAGBGBGCDDFDFGFHEHDHFGEGFHFGFBB,True +222,19.0,32.0,14.0,24.0,24.0,23.0,30.0,29.0,EAEAGFDFDCBHFAFADGBHBDAGCDEABDFGEEFFFEEAECHDHBHDGAHHGBGBGBGHCDFDBDBDEDADHFFAFEFGBHBGDCHEDABGBEBCDCHCBFAFBGBAHFHFGEDFHHHBBBBDBDBDBGEGBHEACCHEGEGEDEHECGHGFBHGHCBGAGHGHGEGEGEHAHAHFCCEFHFAGBGBGDADFBB,False +223,6.0,4.0,7.0,6.0,14.0,14.0,8.0,15.0,CEEFAGEBDFAHHDHFAFAHBFFHFCFEHHHHFDEGEGEDEDGAGHDFGBGBEFGFHHCHCHEHECFCACEEFE,True +224,11.0,10.0,13.0,13.0,21.0,14.0,25.0,19.0,CGBAEGEGEHHCGGHGCCBCAEBEGHCHDFDFDFEGBDFDFEFAGDGAGEGCGBHEEGCGBEEGEADACECABEDCDFFFDCAGAGHFHAHGEGEGEGBGBGHHHHHHDABCEDHHFFDHEHEGFF,False +225,6.0,19.0,5.0,11.0,12.0,6.0,9.0,5.0,GBHBDBABHBCBDEDBGBGBEBEBCCFDHDFEBBDDEAEAEAECFGFGEGABCFGBBDHDEFBGBGEEABHDD,True +226,11.0,18.0,23.0,14.0,12.0,26.0,20.0,26.0,EFEFEFGDCDFBHBHADECHHEHEFGFGHCBGACBGACFDFGFCFGFCCCHHHBHFHFHDADFFEBGFFFFFDBCCFCFHFCDGEHDFDBDCAGGHHHHHHBACGCGAGBGHAAAFFCHGBGCADGBBBCGDHEBEBEBEBHCHDHCCCG,False +227,23.0,20.0,28.0,18.0,25.0,23.0,23.0,21.0,FCCBCEFEDAGGBEHCHCHAFCCADFFHFEFAHCHDGCCHAEDEDFDGAGAGAGEFEBEBHHEFEFHFCGDFBGBDHAHBGAHFFFBFCDDADCDEEAGABHBHGHCHCABADABCHCHCDFGHGHBAFFEGECBGADCECGCGCBFEFDFCGCGDEECAGAEAGAGBBBBBCEEAEDECE,False +228,5.0,3.0,9.0,5.0,8.0,2.0,3.0,5.0,DDDACEHGFBCEAECCCCCFCEHEHEHEBCDAEBDHAGAG,True +229,15.0,19.0,18.0,23.0,23.0,15.0,10.0,23.0,HHFHGHEBFHHBCBDEEHCBGBAHAEDEDCGCGEBBDDDDEDBDHDFDEDACCEEDFCEEECBCBCBCDAFEHCFAHBEDACAGHHHHHHHAHGFACACAFBEBEFFFFFDEBEAEGCBEEDADACBHGCGBGDHDHDFDHDEABF,False +230,15.0,10.0,14.0,14.0,7.0,9.0,3.0,6.0,EDADBFADCDCDEBFBFAFEFEDCBADFBFBAHACCBCGEHEHBCCAGDCFFBAAABAGACHCHDDCCCEDHDADADA,True +231,21.0,19.0,19.0,16.0,21.0,13.0,13.0,23.0,EHBFBHBCDAEACABABEHCAAAAAEBDHDCECACAHGFCFBFBDCCBDBDECHCGCAAHHDDCDCDEEHHHADAFBFGFGDGFGHGAGEEFEHBBDBGHAHGHEBCCACACGEDEAABDBCEDEFEHBHEEEHGHFHEHFFGHB,False +232,10.0,11.0,13.0,7.0,8.0,12.0,12.0,9.0,EFGGGHCHBAEHFDFEADAHBBFBCGFGBCBCBCFHFAFAGCGCEBEDCCCHCHDGGGCGCADFEBEBDAFAFAHEFGBHDA,False +233,16.0,18.0,26.0,21.0,12.0,11.0,22.0,9.0,GBGCHBGDHEHDGAFCFCGCBBDDDHHGCEDEDCDBGBEBCCCCDBGBCACBGGEHEDGGAGACFCFCHCGGDGABDCCCGDBDEDEBBCHCDCDBDAGECECAFEFBFEAGAFAGBGAGDDDACAFAFAFCHBA,False +234,8.0,5.0,2.0,10.0,3.0,5.0,9.0,5.0,GAGBBEDFDFDBDGDAEADHGAGHBDGDFDFCGAGACABAGHHHFED,True +235,28.0,16.0,21.0,19.0,24.0,21.0,12.0,20.0,EDHFBEAFADABHFHFCFHFACCBBBHAHDHBADGDBCBDFEFDHHADACBHBEAEDDDGAGACAEHECFCECHHHEABFCFEEHGAFFFADADCDGEEEGEBECEBBCACAHAHADADFFAFAFHGDEEFEBCGCGCGCDCAHBGEEFGADECECAFAHA,False +236,13.0,6.0,14.0,8.0,9.0,13.0,7.0,14.0,FCFAFAFAHAHCDCDGFFEFECEDBCECDCFHEEFAFACHCHCEBGDHEHFHAHBHDHFCGGAGDHHACCBHDCGFGBAAEABA,False +237,4.0,7.0,4.0,12.0,6.0,4.0,7.0,10.0,DGGHBHDDDGDGCGCGADBHEDEDAGFCFEBDHDEBAHAFEHEHCHDBDBHFHB,False +238,25.0,27.0,17.0,20.0,11.0,20.0,27.0,24.0,BGGGHACECEFEAEDBDBHCGDGDHDHBHBHAHAHFBFGCGCAHFHABABEFFDDAAFHFHDAGADFDGBACCCHGHDAACHCHGBEBCCCBDAFAEGHAHGHGEDBDBCBHBGFEAGAGBGBABDHDGAGADFBFGFGCAEBGFFEHBBGDGBBBFFHFBFCDAGCGHDA,False +239,27.0,19.0,14.0,12.0,26.0,20.0,17.0,18.0,CACHFHBABHBABAHEGBDDEBFAFAEACABAFAHAHGHDFEGEFEBEBEAFCDCHABAGEGEDFBGBACAFDCDCAEHEHFHFEEEFABABCGEEEGHDHAHBHDFGEGBAAAFDHECEAGCGEBEDCDHFAFAGAGBGFFCGCEHGFEBEF,False +240,13.0,5.0,13.0,8.0,10.0,9.0,13.0,11.0,HCHAGAEFGBGAGFGCDCAGAECGCGEFEDHGFADADACHDFDGBCBCFEDEFEFBAHHHHHHAAFGCECACBCGEHEADCG,False +241,15.0,13.0,22.0,21.0,14.0,24.0,13.0,15.0,CECEBACABEFHFGBEFDCDBABGDAEADCDHGFGFDDDFDFDFGFEFGCGEAHGHGHCFCDABFEHHABCECBCHFHCACFBFBHBADFEFEFDFDHDHCHCDEDAGGECHAFDHCABFCFDFDGBGCFCACDCEA,False +242,10.0,3.0,9.0,4.0,10.0,22.0,6.0,6.0,CBAAFFFFGBDAFFFFFFFDGAGEHFGECEFEFHCHCEEEDCFAFAHAFBDEHGHCFEFCFCFEAAFAGC,True +243,16.0,18.0,13.0,25.0,8.0,14.0,16.0,17.0,CFHGHAFGFCFEDAGEBBFDGBGHDHAHBGBGBDCHHEBDBDBDCDHDHFAGGHGHABADDCDFBHAGDDDBCACECAGEGDDHDFDFHFHCGCGCDBAFAFDBDEFEACADADADBCFAHBHGEBB,False +244,14.0,10.0,26.0,18.0,17.0,28.0,19.0,21.0,HEHEHDFDFEGEGFGDCBBDAFHFHFDCEGBBDHFAGBHFHCECHCGAFCCDDADGHGCGAGBDCDHDHDACFCFGACEHEGDGFCFCFCAEFHHHFBFDFDCBCFEFCDGAGDEEFEFHFHFEECCCAAABECFHACECFAFGFCBCGHGHG,False +245,30.0,27.0,23.0,25.0,28.0,19.0,14.0,26.0,AAACACBCAEDEBEFCCHCAEGEDEFGAGCEAEADFEBBBEFAGBBBFDAEAEHHHHCFCHCHADFDEBHFACBFBGBFBCHHAHAEEGHHEAEGHGHGHGCAHADADAEAEAGDGBECHDDDDEFFDCDCACAFBFHCHEHEADFBFBGBDBCGABHBHDACCECDDBDBDFDBEEEEHCBAFHHDBBADF,False +246,9.0,17.0,16.0,9.0,17.0,6.0,11.0,16.0,HGEGACAHDHDCDEGFHBHDHECEDEDFDEEHCFCFHBEGGFABEHHHHGAABCCDBEBECHCHFBAHGCGABCBEBECCCCCEGEBBBBDBABEBHGEGA,False +247,10.0,6.0,15.0,20.0,23.0,16.0,16.0,6.0,AFDGEGEFEDCDFHEGEGFGBCACECEAEHEDDHEGEDEFGDDDCCCCGAGEDBABEFEFDGDHDGDCBHBGFFCFCEEEEFCHEFGDGFCDADCFCAEGFGBEFDADADAE,True +248,1.0,1.0,5.0,2.0,5.0,7.0,7.0,2.0,EFCFDAGFCFGFCHEHECEGGCGDGFGFBE,True +249,20.0,25.0,23.0,25.0,18.0,22.0,28.0,20.0,DGDBDAABACHGHEBDCCABFBAHGGBGEAAGDDFGFAHADADEDFHFHGGGFGFDHDEDBACDGDGBFACABBGBGEGEGECFFFEABDEDHFAFGBCBCACHHFHFBFBFHCHCHCECDGDCEHEGCGBBFBGEFEFHCGCBHGDGFHFEABCCEBDBHGDGDGBHCEDADCDCBAEAC,False +250,27.0,24.0,20.0,16.0,26.0,17.0,25.0,11.0,CHCBCACHBABAGHFEEBEGECEBEBEACDGDHHGAAFGEGABEGAGEGADADABAECFGBGAGAEBEADFGFECACGGFGEGDGFBFGCGBFBFEAEBEFAFAFEDEAAAAGBBBCDCDGECCCBCFADABHDEDEGEAHHBDEDFDFGCCCDBBHAHGBCBEHF,False +251,23.0,19.0,20.0,25.0,22.0,22.0,28.0,26.0,ACACGEBFHHCAGAGHGHGCGCGBEHFHFCAGFGCGHEHAHADDDDAEEEECCFBGHAHAHGBDECFADGCECEGEGDGAADBEAEFHFDGDGAEAFDECBGECCHDEEBGBABEHHAFFFFEFDADHBHBDDGGCGCBAGAHABDBDEFEBCBDHGHGFDFDFDFHBAFCBDBDFFGGCHHHDH,False +252,22.0,23.0,23.0,11.0,21.0,24.0,27.0,23.0,CGGAGEGECECECDBFFFHAHGEGCGAGACEDBBBFGFGHGHFCBGHFHBHGEAHAHABDHABABDBECHAHFCFEFAAGGGBGFCDCBEADADHFHDHCEABCGGGFGAHEEAECCCCGBBEHEHBHBHDCDFFAFBFCEBAGAGCCBCAGFDHHEHFFFCFEFBBEBFGEGA,False +253,21.0,15.0,11.0,10.0,10.0,18.0,15.0,19.0,CFCEEFHBGDEEFEFDAGAHAHGHFHFHGHAHAHGFFFGBDBGAAAABABGBFBFBEACGCEDHFACCFFFGECBAECDGGAFAHDHDHBCCGHAHAFAEDHDHGBBABDFCAGABHBH,False +254,16.0,7.0,14.0,11.0,13.0,17.0,11.0,13.0,CDFHFHECACEDEAECCHFHFHGHGCAHAGAGDEDFDCHCFDADFEGAAEAFFDEDCCEDBFCGCGEBEBHGAGFBABAGFHDHAHAEFFFFFBEBCGHACA,False +255,14.0,24.0,17.0,17.0,23.0,22.0,12.0,11.0,EDGFFFGBBBCACDDDBDCFCFCEEAFGFGFGFDBBBFBDCFEFADAHEDBDFHAAGHCHFGACABEDEDEAECEFEFDAABHHAHCECBFBCBFFDBDGHGHFBCDCECEDEAAGEGFBEBCBEEGEBEBEBHCEFBBH,False +256,15.0,18.0,13.0,27.0,17.0,28.0,20.0,24.0,FBDBCHCGDEDCGAGAGDDFBBBFFFFEDACGCHAGGGEGEBABFHFEDHFHFCBDGHGBGDHBCBGAEHFAFHHHDBDCHBFGFGFHFHEGEBDFFFHAHGHCHAHDHEBEFEDGDGAFABDBEHACFCFCEDADEFBDDEAEADFDFHFHFDGHEDDDDC,False +257,6.0,7.0,12.0,13.0,9.0,11.0,8.0,10.0,DDACHGHGHDHEFCCEGEGACCDCDCDADHBFEFEDEGCFBFDFBFEHCHDAGEDECBCBHFGFDFHAHCGABDBF,False +258,17.0,20.0,27.0,16.0,18.0,18.0,19.0,20.0,AGEHCDAGCGFGDCDCHCACDFEAGFGAAAADADCCHGHGHCCEEEGCADACAHECEGDGFBFBFCHCHCBBDBDBDEFCGCBBBEHFHACAGBCHFFBCBCGGGGHDBECEHEHGHBCAGEDEBFCEEBEBDFCFAFHBADDHFHFHFHECFBB,False +259,1.0,5.0,4.0,1.0,1.0,0.0,6.0,2.0,GGGGBGAHBHCGDBECCBCB,True +260,2.0,3.0,4.0,1.0,3.0,5.0,1.0,3.0,BFBCBFHEEGEHCACACHFFDF,True +261,2.0,4.0,3.0,2.0,3.0,2.0,6.0,2.0,CDCABEHHGFGFGEBABCBGDGEG,False +262,17.0,17.0,32.0,25.0,20.0,22.0,15.0,15.0,DHDCDCDGEHCBGBEBACGDFDCBCFCBCEAEAFCDEBAAEADHCEAEHECDDDBDCDBBFFEFGFBCBHAHFCCECGHDHFHAHACDEHECFCDEAAHABBCHGEGDGFHDDCDGDCCCGCACACFCFDADFGFBFBFEGEGEHDACGDFCFCFGBEBEFCF,False +263,7.0,4.0,7.0,4.0,5.0,5.0,7.0,12.0,GCACAHGHECGCHFGFEDHDHDHGHBAEAHBHFHGCCBCHEGEBHAFADAF,False +264,6.0,6.0,13.0,6.0,11.0,2.0,9.0,8.0,DCFBDBEEEEEEADAHGHGCGDHCHGEACBCGCAHEHGGAFAGCCCCCBEBHDCBCEGEHD,True +265,20.0,25.0,22.0,32.0,26.0,23.0,23.0,27.0,DCHBHBCEHHGHDCGCAHHGHDEEHEHBBECDCGBBACACADDDDDFCGEABGBABEBEBEACFHFBEGHFBABCGHGEGDDDEGAHAEFBFDGDHBFGFCDCDCDFGFHEBEHEHBDEAEACBDADHFBDDDDAFEFBGGGGHGHCHEHFCFGFGADDDDBDADHFEBEBECEADACBCFAFHFDFGFAEGHHCCFE,False +266,7.0,6.0,7.0,3.0,4.0,2.0,13.0,8.0,BGHCABHHCHGGBDBABAFCGEGDGAHCEEGEGBGCAHAHACGCGHGFGD,True +267,8.0,8.0,22.0,12.0,15.0,14.0,10.0,10.0,DCBAAGBEBEHECCCCFEDDDFGHGDEDCBCGEGEGEBFFAEHECFCHCHFHDCDCBHGGCCBCFCHHFAFGHGDFCEADCDCDCEBFAFACECAFEFE,False +268,20.0,11.0,17.0,15.0,11.0,11.0,19.0,11.0,FACAFGDHCEFHAECBCBEBEAEGBGBGFHCCBCAHDCFCDGDAEEEFBACADABACECHGGDBDGGGFHEHADAFGFGFGHGHGCFCDCDEGAAAABDDDGHBACACDGDHAGA,False +269,6.0,1.0,7.0,4.0,8.0,4.0,3.0,3.0,DBGECEAEAEAEAGDGFCHCECFAAHHFEFCCDEDC,True +270,18.0,16.0,20.0,26.0,19.0,21.0,22.0,23.0,BFBCDDGAGACDBDGDGDADHCAEACGCGDEBGDFDCDBDGHEHCFFFFFHFBFAFHDDGBHHHHFEFABGGDGDEFCDGHCHEFCFHBADHHCFCBGBFEEEEEFEDEDAFGHGDGCACDEAEACDEDHBHGHBHBHCDGAEACCEHGHAHACAGACBEBGFDF,False +271,0.0,3.0,1.0,4.0,2.0,4.0,2.0,3.0,HFHFEFDBEBHFDDBDGCG,True +272,16.0,16.0,17.0,14.0,11.0,14.0,8.0,16.0,FCHEHAFAFBFBDHGAFABBCDCDHBHEFABCHCHDAGABEBAHDHDFCEBGDFECECECEHECACDBDBDCGAGAGACAGBFBGDDACCDDBHEHBACFBFHHHFHFCFAE,False +273,13.0,11.0,14.0,14.0,11.0,17.0,18.0,16.0,CDFDGBHBFGFGFGEDABABCHHDDEDCHCGAGFBFDADHDCDCECAGEFEBEAFAEHEHGGEFBHCHFHFAFDFACGGFGHHDHGHAHCFAFGEBCBGBGCACDCDEHGFBAG,False +274,30.0,26.0,12.0,16.0,14.0,36.0,17.0,16.0,GGHCBABACFGFHFBBHAEAEACADADABABFFDABBFFEFBAGFHFBFCFBAHHHHGGDGFGBHBFEECEFDCHCHBHGEAHADDGAFAFDDBDGFGBEFFFFFGFACABGFFFAABAFACAGAGHDABABGDACFEAEADBBFBEDEAFFBFBFCFCDBHEHEDF,False +275,6.0,13.0,13.0,9.0,7.0,9.0,12.0,6.0,CEFBGCCCCHDBDBCAFDFDFGFHHCCGCGBGDGDBCBCBHFGAAEGBGBFBGBGECHCDAEGEFADAHEDEBBF,False +276,7.0,5.0,3.0,5.0,6.0,7.0,3.0,5.0,BCCDFEFEFEBADABCFDDHDHAAEAGFGFHFBAEAGHBHE,False +277,6.0,5.0,1.0,2.0,3.0,3.0,6.0,7.0,HBBFBFDHCGEGAHAHGHGFEBHBGGAEAHADA,True +278,4.0,8.0,15.0,16.0,12.0,11.0,10.0,10.0,DHCHAEEEHEHEFEHGFBHEDEGEGFCDCFCGCDCBFFFCEGDBHFDDADGGCGDEDEDGACDCFCFBGBHBDBCFCHCDDDHCAB,False +279,15.0,15.0,14.0,9.0,20.0,30.0,10.0,19.0,EAFFEFEFHBHBHBHCHCFAAACFCAHGBGBFEEBECEGEFDCEFEGCBFHFBEAFDBBGDDCGFDCBBHBHFEFEHCHFBFDGCHFHFHFGFGAAAAEECEFDBEFECEHDFCFHDHFFEAAAAAFGFHFH,False +280,20.0,27.0,17.0,23.0,26.0,20.0,26.0,25.0,AEDGCEBACABABGBGFDCEBHBCBCGHBAEACBHHHCDDEGFHAAFABCEHDBDBDFFGFCBGGGFGEEFEDEAEDEDHHHFHEEEGEGCBCBHBEBGBGECEAEHGHABBBFHEAFGBGDGFFEFDGDGDGHGDAFAGDHDECEHHHAHDDGHGCGEBEFABCBDBFCFCFHBADADFDAHH,False +281,10.0,6.0,6.0,8.0,8.0,11.0,10.0,7.0,GBFFDHAEAECDDBEGDGAEECGGGDHDAFADAEAHBHDEFFFFBCBCECAFABAHGFGFGFGHCH,False +282,21.0,33.0,19.0,20.0,21.0,12.0,19.0,26.0,CAADABABCEABHBABDCHEAEGHBBCCCCCHCBGGGGHHDHGHGDGDGDBDAAGCBHDFEEEEEEBEBAHHGHEHCCGHFBFBFBFGHBDBHAFAGACCHAHFBCCFDEDEHCHABDBEGADBBCBHEHEDDDDBDEDBBHAHBEEEDBBBBHGGGCEFBFAFBGAHAFA,False +283,12.0,9.0,6.0,10.0,12.0,16.0,15.0,10.0,CFCEDFGCGFHFBGCGFGABEGAGAGAGAFADBHGHDEFHHDGCADEGBBCHDAAAGEBEBABFDFEFEFHFHFHFHGBFEGEDDDEFEA,False +284,0.0,7.0,2.0,2.0,5.0,4.0,3.0,5.0,FBBHBHECBFDFGEHCHEHEBEBDGFGB,True +285,18.0,10.0,10.0,8.0,8.0,13.0,19.0,13.0,HHHFGFAHCCBCHCBFAGCGBABDBDGAFDCDAEAEHDADBHBAGFGFGHEFFGHGHBHAFFBFCFCAAABEEEAGGGAGCGFGAGADAGEHAHCDGEG,False +286,17.0,19.0,13.0,13.0,17.0,16.0,12.0,9.0,DBDADABCGDAFEFEFEDABCBEBGDGFEBEBEBEADBDGHCADABFDADADABGFGFCBCDCFBGGEEFCFAFEFBAGGEFHCGAFAHBHBFFEBACECACBCHAHEHEHCGBEH,False +287,11.0,13.0,8.0,14.0,5.0,10.0,1.0,11.0,ADDCHBHFDEACFDBDBABCBCDDDBAAADHFBFBABEHEHBHBCCHFDABAHCDDDCDAFHFEFEFHFHGAB,True +288,21.0,32.0,21.0,22.0,23.0,17.0,23.0,21.0,CFCBBDADEDEDBDHDADCCCEHEHBFBHADADBGBGDCBBHFAEBDHDFDFBEBHDEDBCECEGABCFGFHDHGHEHAAGHGEDEAEABGFCCBEBCFDFAEGGAGADECFFGFBBHCGEBEGAFABDBHFFAHAHAHBHBEBEBCBABDEGCGCHCHBHBGEGEGCAAGGBBFCCGDG,False +289,10.0,13.0,5.0,12.0,9.0,19.0,21.0,12.0,GBFAEDDDGGFEFDHHGHGFGFGDGFGHHHHEGDBHFGGHECBAGAEACFBBDBCADFGEGDBBBBCBHHFFBFBFDAAAEFGFAFAFDFDFHGGGGGECE,False +290,10.0,11.0,9.0,13.0,3.0,16.0,8.0,5.0,DBDBDCFFGFGABEBEDEFFGFGFAFABHCAFABCDHDADAHBGBDDDADFHCBCDCAAGHBFGFGFCCBFFCFD,False +291,22.0,19.0,25.0,28.0,18.0,24.0,23.0,17.0,FCFEFEFAGEGCGEAAAEGEHFHEGFGDGDEDBDEEECBBBEDFHFAGHCAGAFAHABFBFDDGECEBGFDFCFCDBEFABGEDACACDHDHDFFCDCACHCDBBGCDBHBHCFCDHHHBHBGFGFADDGDCDCHCDCACAGAGCDDABCEGHDHFGGDDEAFBFACACABGBGFD,False +292,22.0,21.0,17.0,19.0,16.0,16.0,15.0,29.0,EFHHAHDCDEBEHEHEHEHEHCFDBCBDHCAFEGGHDDBDFGFGHCFDDDDAFADCGCFDFBFBHGAFCCBBEEAAGAGDEDAHAHAHBHBHBHEHCABABHBCCCHCBBBDAHGFDEAEAFHGBGEHAFBGHAFAFAHABCDDECGCHHGHGAB,False +293,14.0,10.0,22.0,19.0,17.0,10.0,11.0,13.0,FDGGCACGCDCACBCDCDGHHDHBHFGGCCFBFBCBDFDAGEHAHEFECBHGDDDCEBBADCDFDADEEEEDEBHAHAGCGCBDGECEHEHAACADAHFHFEFCCECEDECCDAEA,False +294,21.0,23.0,11.0,16.0,19.0,13.0,19.0,13.0,ECDFDEAGAEAGHBFEFGHBBGBABABGDGCCAGHBHFEFGGCBDGDGDGHFHABAECEAGHFDFEFBFECECEFDHGFGABAEHEGEBBBBEBADFEHEHBDBDADADGBHADADHGAEBBBDCACECBCAAGA,False +295,16.0,21.0,15.0,23.0,14.0,18.0,17.0,12.0,DDBBHFDFGBGBHBFFFFFFFGEBCFCGHABBEHDDDDBBBBDGFHFAEDHDHCFCHCECBAHACDCDHAAADDECACAGABAGEFEBCAEACGDGFEFBGBDBCBGGDDAEFEDGCGEGEDEDGDBABADFHCHG,False +296,2.0,5.0,5.0,3.0,8.0,3.0,7.0,5.0,GHDHFBBGGCGBHEHBCACHCGCGEEEEFDADBEGEFE,False +297,8.0,7.0,6.0,6.0,3.0,4.0,7.0,7.0,GDGFBFEFAAEBDBDBAGAEHBDBHCHDGBGCGHGHAAACHCHAFCCD,False +298,10.0,8.0,9.0,8.0,12.0,10.0,12.0,8.0,AAAAAADGHGAEEEHFHEHEFFAGAFHCDCGEBCBCBFBFAFHFGGCGHEDGDFDBGEDEDCBEGEGHCBEBCCDGF,False +299,2.0,2.0,2.0,2.0,1.0,0.0,0.0,1.0,CHCEABDBDA,True +300,21.0,16.0,12.0,20.0,12.0,15.0,16.0,21.0,HFHGDDEFBFBFAGCFAGBGDHEHBHBHAEFBDGACHGHAHFFDFHFHEBBCBDBDBCFCDCACAEDEDHAHBHECABAGCEBHBGEDEGAAHAFAHADCDEGEGADFGAGAHCDAGADAHCHDDGDGDHFBF,False +301,18.0,17.0,21.0,18.0,14.0,17.0,20.0,23.0,BEBFFCAGAGAGHGHFHDHCFDFDEDEBEBEAGFBCCHCDCBCHHGHEACAEFGBGBEDEBCDADHFAADBHBHCHFDFDFHGBGBAEFGFAAEHEHEHCCGHDDDGHCCCCAABCGCGCADACABFEHDBCFHGHGDAHHDFGBGFG,False +302,17.0,9.0,16.0,15.0,18.0,20.0,16.0,20.0,CFEHGDGCGHFADAFGFBFHABACDEDEDGAEHEHCCCBCEFHGHAEAEAHAHEHEHCDFFAHDEAFDFGBGDHHFHFAGGFFBEHEAEAFFFDGBGCGEECAFFHEHEHDACBCFCDDDDCBCBHGAGCG,False +303,17.0,9.0,12.0,14.0,11.0,11.0,11.0,15.0,DFDFAGHHDEDEHEHECGFACAEADDHDEDCHCECFHBBBEGHBACGGGAGAHDHAAADEHEAFADGDBDFHFGBABABHBFCHAHACCFCGCEADFCFG,False +304,32.0,22.0,21.0,20.0,17.0,21.0,22.0,16.0,HABACGCBCGHGHADEGABAFHHGFCCGFFFHFHAHAGACFGEEAHAHABABFBAEAEDGDBDFFFFEGHGDDDCHFAFGECACECECEDFBEAAFBCGAGECECFCFCBGGADADGHACAEBHAHABGGDDADCDADBBBGHEFEDDDGEFBDBDBCBABCBAAAACFGB,False +305,22.0,14.0,10.0,9.0,20.0,15.0,19.0,12.0,GAGABHEFGHGABAEDECGAFABBEFEAECCAAHGHBEEEEEFHFGFGAEAGAGDGHGFAAAHAGAGFBECEFFBBGHGFCBCGCADEDBDBDBDFEECEBEDGAAEAFAHHBFCFCDHGH,False +306,7.0,13.0,6.0,7.0,4.0,5.0,5.0,12.0,BABAFAHDFDGBHHEHBDACHGHGDDBDHFFAFACEBEBEBHBCAHBHDHCGBHBCGCB,False +307,27.0,19.0,23.0,17.0,31.0,29.0,21.0,17.0,FADCDEGEBEGHDAEFEAEBHBCBAFAHAFGEGFBFCAHAHCCBDFHGCEFFCFEFEAEAFCBDADADHDFBFBEBADFCFEFBFBFDFCFGFEAHBBCCCCHHBHAAEGEBECEGDAEFDGECEFEHGAGEFEDGBABABHDHDCDCGHAEACAGFCECGGHEDCFAAAGAGCEHEGEGFGFE,False +308,16.0,23.0,23.0,25.0,22.0,21.0,28.0,27.0,BHGEFEDACAGADADGDGDBBFBCGGHGFCFCEHHDCDCEGFCFBEBEHDHCHCBEDDHBBEBGGFDECHCHCBFDFBGEHEGEDEGAHDBDAHGBGDGBCFCGCGBBAFAFABBBFGFHAHAEAGFFFGDDCABHECEDEBEHDGDEDEGCHCDCACHCAFGGGHFHFHGHGCAEHHHHDDBEF,False +309,11.0,10.0,14.0,4.0,9.0,15.0,8.0,17.0,CECHBGAHBHAHGCACBEFEFDCCCCCBCDCGAFFFFFBCBAFHFHFHDAEAHGHBHBHEHBHCGFBHAAGEFEFEGHAHDFFCAEHG,False +310,7.0,7.0,11.0,8.0,8.0,14.0,8.0,4.0,AFACGFEEDBGHDDADFCFCFCFDBGBHEHFAGDCACFCFEFBDBGBEBFCFCFCADGEGEAHCFGE,False +311,1.0,3.0,3.0,4.0,1.0,4.0,5.0,3.0,DHHBHDGDGCFAFGEBCBCGFGFD,False +312,9.0,6.0,12.0,3.0,7.0,3.0,4.0,5.0,AAEAECGCDFDHACECEAEBHBACCHCHEGCGCHCACBBAFAFCDGEBB,True +313,10.0,20.0,11.0,11.0,10.0,21.0,14.0,10.0,FHEBEBCAHAHBFGFGHGFAFCFDBDFDCHBECCCHEACABDGFBFEFAFAHGBFBDBDBFCCCEBFGGBGFAFABEEAEGBBFFDFBFBDBGBGCGDEDHFHDGGH,False +314,11.0,11.0,19.0,12.0,11.0,7.0,10.0,11.0,GBHBFGDABADADBDCDADHBGCECHCHCGCEAGCGCDCFEAGAEAEHECEFFBECDCGEHCBBBCGDHDBDADCFFEFCACAEBHHCHGHC,False +315,15.0,20.0,19.0,23.0,12.0,16.0,12.0,15.0,CCCCEFDBDHDCDFDCHFHFDEBACECHCGGFGAHDDDBACFFFDFBBABABDBACADAHCHDGCFFBHHDHDHGCCACEDBDECEHEBABHFDDDDGEFBFBGBEBFAGAGBGHEHDFEBABAEADBCGCG,False +316,6.0,8.0,6.0,3.0,8.0,2.0,0.0,9.0,CBCDFDHABAFEHBHBHECEBECHHBEEECEHAHCDAHABAB,True +317,5.0,12.0,12.0,7.0,8.0,8.0,7.0,11.0,CHGBGBFBFDABACAFFFCECHCEGDBBGHCCBGDGFGHEHDHCHBBCCECEBEAEAEHDCDHHBHBDFF,False +318,19.0,29.0,24.0,19.0,24.0,39.0,20.0,15.0,CFEFGHBHFHCEABFCCCFFEFEGBGBAHAHDBABCBGBGBGAGAGABHCCCFFFEHEDGBHEEDHDEDBHFDBCBGBFCFBEDFAFCFGACEFGFGAAFFFFDFEFECCGEGBDAAECECABEFDFCEAEAHFDBABDCHGBGBGBCACBCBEFGFGFCFHDDFAEHDFFEDDFDFBFBEBEBFHFCD,False +319,8.0,5.0,5.0,2.0,5.0,4.0,3.0,7.0,HAAEAHDHCBDEAHCGFGCEABAEAFAFHFHBHBCBCEG,False +320,4.0,0.0,2.0,0.0,3.0,0.0,0.0,1.0,CACAEAHAEE,True +321,19.0,25.0,20.0,14.0,21.0,25.0,19.0,10.0,ECEAHAGAGDCFHAHAHABEGAGBEBFFFFFGFDFDFGCDCBABEBGBFFFAGADFDGHGABAHAGCBABGDGEEACAEDBCBCEEFHGDDCBCEGEFEBEBFGCHBHBEDFHBCGEBCDCFCEBEFEBCBCBCBAGFFAFAFDCGEEFDCBF,False +322,4.0,3.0,7.0,8.0,3.0,3.0,6.0,6.0,AGDFDFDAGECEDDHCHGHCBFDEBCBCHCHCDDAHAGGG,True +323,20.0,23.0,10.0,13.0,14.0,23.0,24.0,21.0,AGAFFGHGEBBCDCEEEGBFAHAEGEGCGFGAAEBGHEBDGAGEBABEFCHAHADFBFDFBHBHBGBEBFBFHCACGCGBFBFAHAHFEFDBGGGBGFGBBEDHGHGHFHDHDGDHBFBFDFHFHFACADAGEFHCAADHBHCADFGA,False +324,6.0,10.0,13.0,15.0,5.0,10.0,12.0,7.0,ABBDDDDGDHDCBBHCHGDGBAEGEGHDBCFGFBEBADGCGCGHFFFFFCFCBDBDGDCAAAFDHCCCECDFDHCGEG,False +325,14.0,17.0,16.0,18.0,24.0,25.0,25.0,12.0,EAGDFBFEHEFGADABCCEGEAEGEGHGBFBDEAEDHDFEFDHCHGBGEECDCDCDCHCDEAEACCBEGAGEBFBFBFCCGFBEBCCDEDFDHHGAGAGEEFFFFFBGHGHBDECEBAFAFDFDGGGAHBEFGFGFHDGDEFGCABFBFGG,False +326,10.0,8.0,13.0,7.0,11.0,10.0,9.0,12.0,HGFCFAFCFAGADEDBHFCFCHHAHACEBECCCCEGEFEFGDBFBHBGBCEEABCECAADDEDHDHBGEGAHCHFHGAGH,False +327,13.0,9.0,7.0,7.0,11.0,9.0,9.0,4.0,EFEGEFABAFHDBFAFGGEBEFECCCEFFDADBDGEGAGABABABFBDDAEAHAHGHEAAGDECCCGCB,False +328,11.0,7.0,14.0,13.0,15.0,16.0,11.0,12.0,HHHHFDGEGFHFHGDGCCHFBFEDBAHGFCDCGGDDACACEDBGEDEHHGHEFEFCFGFAAACADHFAFCFCFCBDBAEEEEGDFBFAEAEDEDEBCCC,False +329,14.0,9.0,16.0,7.0,13.0,4.0,16.0,18.0,GCAEFCFCACAEDGGEGBGBGBHBHAHECAAAAHAHECECHGHADDCBCFCHHGAGEGDGEAECGBHDACECBHDCDGHCHGEBHBHEHCFGEGHHA,False +330,6.0,12.0,18.0,17.0,8.0,10.0,10.0,6.0,GGFCECDCDCAABEBEHEFDDADGDBDHGFBFBEDHDFBHGGCBCBCDCBCHDGCBCBEDCDGDBECADACCCFEFGFGFHDADFCC,False +331,11.0,25.0,21.0,16.0,17.0,27.0,21.0,23.0,FFFCHCBCGHHHGGCEBEDFCHAEFCFHDBDBABFBFEFBFHDHFBGCACHHFBFDFGFBHHDBEFAFAFHFEEEGEGEGEDBHCDCACHHGFGFHHBDBDBHCHGEDBDECECECFGBDBCEGGGGCCBCAAADAHBBBGBGFGHDAEFGFBBGHDCFCF,False +332,31.0,34.0,15.0,23.0,18.0,19.0,14.0,23.0,HBFBAAACBDEABCHDHAHDFEFHAAACDEBHBHBHBCBHBHBGCAFGBGBFFDFGAEAEBDFFADADACADDDHAHAEEBFDFGCCCFCAEGBCBAHCGEEEEEEBFDFEHBBBABAHADBDEDFGHHBHBDDABBHBHDHFCFCGEBAAAEGFDFDGDBBBAGAGABAGHBHCAD,False +333,20.0,17.0,9.0,14.0,13.0,13.0,13.0,14.0,ABGCECACBHDHGEEHEHBDAAAFDEDGDFAFABCCGHBABEBEGADADFDEHEHEGBGAHADDHHGHGCGFFABAFDBDHABEFDCDFFAFBEBHBAFAFABABGCECHGBG,False +334,7.0,5.0,2.0,4.0,6.0,6.0,4.0,9.0,GCGBFBHAHEBEAEDCGEAEHHFHAHABFGFHFHDEDADAFHB,False +335,17.0,13.0,10.0,10.0,9.0,12.0,9.0,20.0,AGHHAHAHCBABFGADADEFEFEDBBBBHHGHDHBCECEHFHFHBHAHDEAEAEBEHACAGADHCHBGGFFFHACBDFDAGHCDGDCFCACFHFBBHGAA,False +336,10.0,13.0,6.0,5.0,11.0,4.0,11.0,9.0,EGEBEBEGEBAHEFBCBEHGDFHFAFCBHBGDABHGGGBGCGBABADHDCEABABADAEEGAGCHCHEH,False +337,17.0,16.0,15.0,8.0,14.0,17.0,17.0,24.0,HBGBABHBHDFFAHAHAGAEAEAFACGCBCECFGDGCCEFEFHHHABGFCHDHGBCBHBDGDHEHGHCFCHGHDHFHFBFDABHBGBAFHEEGEGECBAGEHBHCHEFEADCBFGHCEFGCGFAAAAF,False +338,18.0,20.0,22.0,16.0,18.0,27.0,14.0,22.0,AEAEAEAFHDHAAEFBDHGFGFCAAAGADFFEFBADCHCHEGBBEBGFGFGEHEDCFHAEBHCDCBCGAECGCHCHBFBEBHHHGCBHFDDGHHHCHBDEDECBDFEFBFGFCFBFBCBFBFCDEAFDGABADADBFFFFECECADHHHCHCFCFCG,False +339,24.0,25.0,25.0,23.0,21.0,21.0,28.0,25.0,ABAFDFCFCGHGCDBDGEGEGCAAEBHBHGHGHDADCGCHFECEBDHDABHGCGHDHEEEBFBFBDDCDGEEEHBFFCFBFAFAFGCCCHGGFGCACHEDEHGDDBHEHDACAFHEABGCACABDBEBFDGHGHFHEAEAEADACGGBBBCGCGDGBGBFCHAHAHFBABFCEHBADGDEBACGCGFAFDHD,False +340,14.0,19.0,9.0,8.0,9.0,16.0,11.0,11.0,CAADABAEACBCBGAADHBFFFBDBDEGABHHHAEFHBCFHBEBGFDFBFBDBDBDAEGEGEFCGBFBAEGBGFGFHFHFGFCBCAAGAFEHHHCBC,False +341,2.0,6.0,2.0,4.0,1.0,4.0,1.0,1.0,ECBDBFAFDFDBGBHBCBAFD,True +342,10.0,9.0,6.0,7.0,9.0,12.0,7.0,13.0,AEAHAHFEGEGBGAEBBHFDBGBHHGHAFAFAFHFDDCDHECFCACFHFHCDCDHBEBFAFGFABEEEGBDHH,False +343,12.0,23.0,13.0,17.0,19.0,18.0,25.0,20.0,GCGCGCFABHCGAFCFDFBHBHEECDDBEHEAEABABAHHFFDFGEBEBGCABAGGEGEDEDHBCFDHDGBGDGHAEAGDHAEEECHHFBDGCFCDBDHFHBBBDHHCBEHFHGGGFGFBEBEFEFCFGFGHGDGDBHBGBABDGEG,False +344,8.0,19.0,17.0,14.0,18.0,17.0,16.0,26.0,BFBHCHCACDDFCHEHAFAFEEEDHGHBEEFADGGFGEEDEDEFEFBFBHHGHGHDEFCGCGHDHDBCHDBCFCGEBHBHEHFDEAEBEGCGBHBFBHBCBCBCBGACCHHHGHFDFCFHGDGHEHDCBAAFHBG,False +345,14.0,25.0,9.0,16.0,24.0,29.0,24.0,20.0,BDBDFDFEGEDADGGGGDFAABHGFGFEBHFECHCEDBABFBEDGGCFCEAAHGHFBBHHHHHHEBEBFAEEBEDGDCHEFBFBFBHEGEGEAEBGGCAFFGDGAGAGHFFFFFGCHAHBHDEDEFHBBBFDFHFBFBFBHDEFGBEDEGEGBAFFCACEG,False +346,20.0,21.0,26.0,20.0,28.0,15.0,21.0,20.0,EDEDFHFHEDCCECEHEHCGBBAEFDDHBGBEBGAEHECGCACECGCGCDEHCAFAECHBBDGDFCFBBHBEBEHDGDBDCAGACAHAHDHCEBEHEACDDDFFAGAFAFCGEACACGEEAHAGAGAGEFEFHFBGCHBDBHBCGDGCECHDHFBFDCGCBBEBDAEGEGE,False +347,9.0,10.0,7.0,7.0,9.0,11.0,7.0,1.0,DAFCBCBAFDEGEGEFAADGEGEAEAFGFBFEFCFGFCFHEDCBGBEBAFDDABCBABDBC,False +348,23.0,21.0,22.0,23.0,12.0,21.0,19.0,12.0,DBGBGFCCGCDHGFGFGFDCDEAEAFBFBHGHBCBABAFFFBBAFHFCDBFECCDCACAEADFDEDGCFCHBBBBDFDCGAHFGEADDGHFFDADEGEAEFEDECACACAFADCFCAGBBABEDGDHCGCACACHBDGGAGBGBHAHADDDHB,False +349,24.0,18.0,28.0,33.0,14.0,23.0,32.0,22.0,DBDACACDEGGCFCBGBHFGDGDEDHHADCFBFDFDAAFAGDGCFCECEGDGFBAGHDDCDCDGHCFFAFGDGDHDHFGGBGHDCDCAHFEDBFBFCDDEDGHAHADABHBEAAACADGBGAGAFHCCGFGCGDGAEAGDGHFHFEBAHCFCFGGGEGEGAGHBBBDCCHCHFHCHDFDBDCDEHECBCEAABC,False +350,8.0,4.0,6.0,7.0,7.0,4.0,16.0,7.0,EDGFGACAGBHBEBAGACAGEEEEEGGAGCGCDAFHGDCDHGHCHGBGAFDFDGGGDHH,False +351,14.0,22.0,13.0,15.0,4.0,11.0,14.0,13.0,ABCCHHFHCDBDBDBCCGCGFFDFBFGGBAHADDGDCDCBAHABEFHBBDBDBDBEBEBGDAEABDGFHBHGAGCBFHHHHHACGBGACFBBDGDBFAGAGACACF,False +352,23.0,10.0,18.0,19.0,18.0,25.0,14.0,15.0,GFADHDHFCGCBFFFHHEDFDHAEEFECAGBGEAHAHADAEGCBFBFEGEFHHEGGCFCHHAHAHEBAADAGBEBEDEDGFEFAFADADFGFAFCECECFFAFACACHCDFDADCDGGFDHCCCCDGDAFBFBEADBDAECF,False +353,28.0,26.0,15.0,29.0,24.0,17.0,31.0,29.0,EFGDADGCGBGBGBEAEHGHFDDEDEDEGHGEGEGHGHEHGDGBGFEAEGDCHCHDHFHEHAGDHDFEBEBEBEDCDCACAFGFCABFEGBGAGHHBDBABABHHAHAECEAGBGBHBFEDHCFCDGAFDHBEACFHHGDADHCFCBAAHFFGFDADBBEBHACABAHGDGBEAFABDBGGGGDDDAAHDDDHCHAABE,False +354,2.0,5.0,6.0,7.0,4.0,6.0,4.0,6.0,BHGHAECCCFADBDHDEDBFBHDCDCDFGCGFGFHHEFEB,False +355,6.0,5.0,6.0,6.0,6.0,7.0,2.0,4.0,HFHCGCGBFEAAAHAFBCBDEDEDEDCDFFABBCFCADFEHE,False +356,6.0,7.0,14.0,10.0,18.0,19.0,15.0,16.0,FBEHFGEHFDCDGGGEHCDCDFFFHBABDFDFHCCFEFECEHEFCAAGFGBCBFGFEBCACACDFFGHGBEHEHEHFHCCEGEGEGECAHEDEDGDGEHHHGHFF,False +357,14.0,24.0,11.0,19.0,13.0,13.0,20.0,12.0,CAHGEBBDBFBEGHAEDBDHDGDGECACACEFBDBFFGADBHBCCDCDHDEGEAFAFEGBFBABHFHAEDEDGHGBEBGBGBGFFBCGEGDAFAFAHAEBCGDDAGHHBCBDBDBFBDBDCGGGGH,False +358,14.0,23.0,16.0,16.0,14.0,16.0,6.0,16.0,HBCBHFHFHDBAGAEDCCCBFDFHFHDHDHGHABCFCFAGEGBBBFDADADBEBHFCFDFCBADDBCBCBCAEGEFCBABAFAHBFBEBEBCCEEHEDECBFAEHGADHDHEHBDEFBCDA,False +359,13.0,21.0,20.0,21.0,14.0,16.0,20.0,15.0,GFDBDCACAEBEBEBHBCBCECEGACHCHAHAGGBADADBDFCFHGDGDGEBHBDGGFGFGDBDAGABDGDGEHFDAEFFGFDHEBCCDCHCFCECHGDBCEHEFDFDABEBGDGHACFFBDCEAFGDBCGCBCFHBHBH,False +360,2.0,2.0,1.0,1.0,3.0,6.0,2.0,3.0,GFFFEFEBDBEHGCAHAHFF,True +361,14.0,17.0,14.0,17.0,23.0,22.0,11.0,18.0,DHACABDDDFEFBCAEAEAEFCFEFCFDFHFAFBCBCHGHFHEAEGBHBGCFCHAEBEFECECGFEDEFCCHAFAFAFADGHGBGDHDEDAHBHBHGEEBDHDBEEHGDEDEFBFBFHFGFBDAEBDGCHEEDCHB,False +362,7.0,7.0,14.0,4.0,6.0,6.0,6.0,3.0,CCBCGEGCAFAEADAGFGFCFCBCGHBBDBCGEAHAFCDCACBCHCEEFECBD,False +363,10.0,8.0,17.0,16.0,17.0,20.0,8.0,12.0,FEADABEGEHEBEBECFCDCHBHCAEEGHCFGFGFHHEFEFDFGFDECCACHFFFCDCGADAFGDCDCDCEFFFFAHAHBEECCDADAFFBEDEDEDHCFCDBHGHDB,False +364,8.0,4.0,4.0,12.0,13.0,9.0,10.0,11.0,FFHEHDFFAGEGEHEHFGDDDEDECEDABHFGFGDGAFADAEECGGABDBGHHCDCBGFDHDHAEAEHEHE,False +365,6.0,2.0,5.0,1.0,4.0,5.0,1.0,5.0,FEACAGFEFHCEABABAHFFEHAHCHCDC,True +366,11.0,5.0,9.0,15.0,4.0,9.0,12.0,5.0,CCFDEDFDFEFEHDBDCDHGGGGDFDAACADABFGCBCAGAFDFCGCGAHAGAHDBDHCGEBFDADADGG,True +367,22.0,11.0,14.0,10.0,20.0,19.0,35.0,19.0,DGGGBCECGDADABABHEHBHGAGHGFAFAGBGBGEEACACFEFGGGEFHCDEEBEBAHCEFFFFHAHAHGFECBHGGEGEHAHFGBDFHEEGCGFDAAAGEGAGFEFHFGAGAGDHAACAGHGCGAGDGBFHFGCGCECEHFHDGEGCD,False +368,2.0,3.0,4.0,0.0,3.0,2.0,2.0,2.0,BCECECHFHFAGEGBBCA,False +369,2.0,7.0,10.0,3.0,12.0,8.0,6.0,9.0,HHDHDCCEGEFFFHCBBHDEGEHEFEFEFEFBCBEBHBCCGCHEHBGGACECEFGAC,True +370,17.0,20.0,13.0,14.0,12.0,20.0,18.0,16.0,HEFEBECCHDECGCEBBGCDBDBDGFGFAFHGDDFDHBBBFAGDFAGACEFHGBFDFHFHFHCGBEDHFCFCFGAAEDECEFBFAHABACAGAGACAHABFBFGEGDBFBHBHDHDGBABAGCGEBAHGH,False +371,14.0,16.0,16.0,7.0,13.0,5.0,11.0,14.0,GBGBEHFHFBBBECAABDEABAGAEDEDBCEGECCACAGACACBCHCECEGABDBEBHBHFHCDAEADHCHCHFHCEABBCDHEGFGCHBGGHGHA,False +372,9.0,15.0,11.0,10.0,12.0,17.0,13.0,14.0,BEBEBGFFBFGFDFGCGCGFHDGGCFAFAFBFDHDEAEHEHAFBFEGHHEBGAGCHHHDDCECGCABFBFHFEDEDHBBCBGBCAGACAHBECEDDHBHFF,False +373,14.0,9.0,8.0,14.0,6.0,19.0,18.0,14.0,BHEFAHAHDDDDFBFDFGFEFHGBBFAAAGADHGBFCDGBEFGFCHHGFGHGHFHGEGAGEEAGDDABGGCCCBHBHCHDFAFAFAFGFDFDADADCGCGHF,False +374,13.0,6.0,13.0,5.0,8.0,10.0,12.0,6.0,CBGADAHAHAFAFGCGFGCDEAEADADCBHDFAACCCAFHBBCEGEGECFHAEBEHCGFGFGEGCGCFCGABF,False +375,8.0,5.0,6.0,3.0,11.0,9.0,8.0,4.0,EEEEHFFBFGGCGHGEBABEEFCFCBHGDBHFAFAFDFGAGDGAECECECAAAE,False +376,6.0,8.0,6.0,9.0,8.0,5.0,12.0,5.0,AEGEBACACHCGGHDBDBCEGEBEBHFDDGDCDBDBEGCAFBFGGGEHEAADFDFHGGG,False +377,2.0,3.0,2.0,5.0,6.0,4.0,2.0,2.0,EDEDECEBHBGFGAEADFHBDFEFDC,True +378,18.0,11.0,12.0,20.0,13.0,19.0,14.0,21.0,GAEHGHAADADADBFCECDCFCGDDFCGHAADFFFGHBHFDCDBFHFHGHFAGAGABADDHAEDECFFFAFAFDEDEBABFBGGHBCBAACBHHHFFEDEDADBEHFHGCGEEDHDCDGHGHEHEHCH,False +379,15.0,10.0,10.0,14.0,7.0,13.0,13.0,11.0,FHGHGHBBCDDDDABABGCEDADCHGAAHAFCFBDBDADFCFDDHCHFHAHCHCBCGGAACAHGGGGAGBEDFDFEAGDGFEBEFFAFAEBEF,False +380,20.0,20.0,27.0,28.0,18.0,28.0,19.0,15.0,FAEAEHHHHHHECBHFFFCFCDAGFGDEDCDCBGFFCGBGEGBAEAGFCADGGBEBEFHFDCBAEFDFDEDAHAHGEDAGBGFEBEGFDDDFDFAFCCCCCCBCBCGCGCACDDBFAFBCDADCDEDBCBCGHGFGBBAFDCDHBHDDBDCECACDFDGABFEDEAEFHHAAFFF,False +381,9.0,4.0,8.0,8.0,10.0,3.0,5.0,2.0,DEDECFCECEDAAACHEGDDFDFCACECGAABDGCHBEBGDGBAEAEAE,True +382,28.0,23.0,23.0,25.0,22.0,19.0,22.0,24.0,EBAHHEDEDBDHHGADFEFEHDHDGFFDFDADHDGEACBEHEFGDGAGAGEBCDCBBAFECHGGBHCHCGGGCGAFCHCHBBEBFBFHFCGCGEDEAAADABABADFEFDCDCECDCHCHCBAAAAAAHAFEGEADCCFHFEBEBFHDHFAAAGCBBBCDHDEDFBEGHCBDBGHGCGHDEAGABA,False +383,4.0,5.0,2.0,2.0,4.0,7.0,4.0,2.0,FAFBFGCGAGAGFBDEFEFHABFBDCHEBE,False +384,23.0,10.0,11.0,21.0,17.0,14.0,20.0,15.0,CBEFFDDBFAGHDAGAGAGDDBEGCCCDCBHHEAEFGFEEEHEACACAGAGBDAAHFHFAFADEHCACGDAEEFGGHEHBCDAGAEDEBFGHDHEHDHFHAGAGAGAFAFABBCDGGGDBDGDEDEDFDHD,False +385,16.0,15.0,15.0,12.0,17.0,20.0,20.0,23.0,FGBHBHAHAHBDFEFEBCAEEDEAHBHBHEFDCBAFCFAFAGHGHGACDHBCAEHGHBABFCFDGDFDFHFDBGFGHHACADACHCGBEBEHEACGEGFGFGDGEGEGECEADACBGFHHDFFHFHFGGBHCGCEEHC,False +386,22.0,28.0,19.0,25.0,19.0,24.0,12.0,27.0,BHDGBHDFDFDBABGDHAFAECECBCBCFCBEBHHHEEEBAFDFAFADECBDFDFAEHBHEHEGEADHHHFHFHDBFHAHADADFDFCAHBCGCDCBBBGBFAFCFHAGADDBFEFEAAHCDCECBDFFHFHBHBFEDCACAGEFDHGBEHGBCBHEEGAGHBDBDGHADADCBCB,False +387,16.0,23.0,23.0,12.0,27.0,6.0,20.0,14.0,EDEBGBEBCGGHCACBHBEGAGHGCGEGFCHBDCHGHBHGDADADBBCHCBEBACGEGEGEBABABDEEHECCCCBBBGAGAEAGFGHACCBBABAGFBEEEEEECGDDCDHEEEAEAECDCECGCFHFCBCEADDHEBFH,False +388,29.0,22.0,29.0,26.0,26.0,22.0,19.0,18.0,CECEGHFBFDDCDHGAFBGDFAAHACACAEEBEACFCAEECCGCGCFFFABGBGDCDGDEAEABHBHBFBHAHDCECECHFEFBACDDDEHAGABADFDFDBDBDECECEDHDAAAAEBEGAAADGFBFADACHEAACFGFGCGEHFHFCCCDGGBCEGFAFEBHCDAGBCBCDCEEGDBDBDHFHEBEHH,False +389,6.0,5.0,9.0,6.0,6.0,10.0,3.0,6.0,AFFFACCCEHHHHACDFDEGCBCDEDCFBFBDBFHFHADGCGCEFAFAEBE,False +390,5.0,5.0,8.0,6.0,3.0,4.0,2.0,9.0,CHCGBFDADACBFDFCHHDHDHCGCBFAEAEAECHCHBBDHH,False +391,17.0,18.0,29.0,20.0,13.0,16.0,17.0,22.0,GDCDGHHBEBFCFHGHAAAHBCDCDHFHEHBDDDDDCDCACHEBDBCBFDACBCBHACCDCGGGGCBCFCFBACADHHCFCADHHHGCBBGDGCGEEHEACAGGFGCABABDBEECECECFAFAGHHDHDFBFGFHECEFDFAHBHFGCACE,False +392,4.0,11.0,10.0,5.0,8.0,5.0,3.0,15.0,HHHHEEDDBGHGFABEBECCBHBCBEDECBCHCBEFEHDBDHAHBHFAGCHCHCBCAHFHF,True +393,5.0,6.0,6.0,2.0,4.0,4.0,5.0,6.0,HGFGHHHAGCGEFEBDFDAAHAFCBCBCECBGBEBHCA,False +394,21.0,28.0,17.0,22.0,17.0,15.0,15.0,14.0,DHAAAAFCDBDBDGGABBBCHCACGHFBBBBBBBAAAAFBBBBBEGEABCGFDHEHEDBAADEDEDEHCFEBEGDHFGGECDCHCHBDCEFEHDBDBDBDCECGCBFDGBADHGGFAFAFACEGEFDFBABFFEGDAACACHEHDHDCG,False +395,17.0,17.0,23.0,13.0,25.0,16.0,32.0,27.0,ACFCFGGGEEHEGGDEHBACACECEFEFHDEDFDGEGBGFHCCACEEFDACHGHGHBEEHBACCCCHCEFDAGAGEGCBHBHBGGGDGCFAHGHGHCAEFBBBHBGBHHEHEBGGEGEFHFHFHGHGCFCGHGDEDAAAGCBBBCHAEAHDHDFGGGEGBAHECDFDCAE,False +396,2.0,4.0,1.0,7.0,6.0,10.0,8.0,9.0,GCGFGFGHBFAEGFHFHGBDHEFEDHDEFEFDFEFBGHHAHGDBDHD,True +397,12.0,14.0,13.0,17.0,13.0,20.0,12.0,15.0,CEBHFCBGHGEGEACAHBHBDBGBADFDHDFDADHHEHFHBAAFACECECEDDGDGDCCCHCGBBDGFBECGDGACFFFFFFDHDHAEFEFBBGBFHFHECAFDBEHDFAFAEGFD,False +398,28.0,19.0,7.0,24.0,27.0,19.0,20.0,15.0,DHEAEADDHGAAHAGEHEBDBDHFCFEFEFEGAGHGBFHECAAGDCDADFCHDADADFDHGBGAEHDGFBFAFAFEFEFEHCAAAGGBBABDBCEADADFEGEFHADEGGGEGEGBGBDADEEBDBDHEEEDADEBBFHEEFCFEFAAAGABABDBHBG,False +399,0.0,3.0,1.0,3.0,3.0,3.0,0.0,4.0,DDHFBFEFDHBHCHEBE,True +400,14.0,15.0,8.0,10.0,12.0,16.0,15.0,13.0,BABABGHFHEHEAEBFGHDBCBGDCFFGAGDGFEFEFEFHDCAGAGHHAHACBCBGAGEGEDBDHDEBCACBHAHCFAFEBEDFFFBFGEGFABHGDADFBHG,False +401,11.0,5.0,16.0,15.0,7.0,18.0,6.0,17.0,EGDHHBGCGFFFFECHDAFAFBFDHGHAACFFFAEHBFDFHEHDFDFDABBEAFCCCCCCCFHAGADDDCCEHEHCHDHAHFHCCCFDHDHDADG,True +402,3.0,10.0,24.0,13.0,15.0,13.0,11.0,19.0,CBBEDHAHBDBDBGCECHHDHGHDCGCGEHCHCGCEEEEHFHFECEGBDDFBHEDBDADGFHCHCGCBCDCEAFGFGHGHCECFDECCCCCDHHEBFHFCFCEHFFCF,False +403,1.0,2.0,2.0,2.0,0.0,1.0,2.0,2.0,DGDABGBCHCHF,False +404,5.0,16.0,6.0,12.0,8.0,5.0,12.0,9.0,DGDHBCBCHGEEHEFGFBAGABADDCDBBBBBGAGEEDCDGHGHFHBHGGCEEDBDBDBCBDBGFAEBHFHGD,True +405,21.0,16.0,12.0,16.0,13.0,10.0,25.0,18.0,GFEFBFGGBGBGBHFHEBEBGBGFGFCEAGCDHAABHBEGCGHDHAHDCEGDGDBFGCAAAAEAGADFDGDAACACECEBFDHBAEACHGHAHDEDEFHHHBGEGACDBAGGBCBHHCDGAGDGHGHADAD,False +406,4.0,4.0,3.0,5.0,1.0,0.0,4.0,3.0,GBDDABCBCGDGDCHBHDHAGAEA,True +407,16.0,7.0,6.0,14.0,13.0,6.0,14.0,8.0,BFCAAAAAEFEBDFCFCADGDBDBDAGAHAEDEGHGHGFDBDGAEHEAEAGCEDHAEADGDAFADGGEGHGHDEBEHDGBGCCE,True +408,12.0,15.0,11.0,21.0,18.0,14.0,12.0,11.0,DBDBDBDBCBGGABCEFEFGGDBDAAAEHEFEBGBECCFCBGEEAEHCBFEFHFCEBFBHGADFDACABEBEAECDCGFDDDDDDHGEGFDHDHDHFCDDEDGAAFAFHHGHEE,False +409,20.0,21.0,28.0,22.0,20.0,26.0,20.0,22.0,FCFDFHADGDHDHBBCCHHDHDHDGAABAGCGCDCDFFFAEAFBHHGHCHEFEGBDCDAAHABBCFHFEEGEFFFCHCDBDEDEFEDAFAFABEHCCCEBHBDGDECCAAACDGFFEDHDFBHBAGAEAEFECGGGCHCDAHBGBDBCBEHGFCFCFCFCEGEGHFCBGFGCGCEABBB,False +410,3.0,1.0,3.0,3.0,0.0,0.0,1.0,2.0,DGACBHDHDCACA,True +411,10.0,24.0,18.0,15.0,16.0,10.0,24.0,18.0,HHFBFECHGHAHFGGDCBCBCEGHGBBAAGCCHCBDBGBDHHHBFBDBGGCGHGABABACEHEHCDGDECBAAEFGGDGEADDDHDHBEBEGEFEGEGCGDGDEDBCCCHCEBEDCGFGHGEGFBFBACHBBBBF,False +412,7.0,7.0,14.0,10.0,10.0,6.0,9.0,5.0,GEDFDFBAGCDABADDGAHEDEDFDCDCDFHCBCBCGCHBGCFCAEEEEEGEGCCCHHGCBEBCAGAF,False +413,1.0,1.0,2.0,0.0,2.0,2.0,3.0,2.0,FGCGCHEHEABGF,True +414,3.0,7.0,4.0,3.0,7.0,6.0,6.0,8.0,HCHGEEBABABFBEGFGAGBDFDEHEFCFBHHHFHCHCBEEGGD,False +415,17.0,22.0,23.0,22.0,24.0,17.0,20.0,16.0,BCBGBADDEHEBECCCCDGAGEGEAACEHEHGFABAEHECECFCGCECDBACAHADECGCBBFGFEHEFGDGEGCGFGDHDCBCAFGDGDAEFHFCFBEEHEBDDFHHHBAFAHDEDGDBDEDECFCFHFAGCFFAEGDGDADCBBBBCGHHABBBBBDED,False +416,23.0,23.0,29.0,23.0,28.0,15.0,36.0,18.0,HDFEEHAHFECBCGDFDFBAGABBGGADFDGEGECECGDHCECECEDEDACACGEGCGFBCBCACEEDEGGABHEDCHBGGGHGCGCBDBCCCEHEBGBCDDGGHGEFEGBBBDBAFAFAGBFFHHADEGEDBCCCACGCDCGEAHAEADGGGDGDBFBFCGCGBGBGACAHAHGEFDADEHEHAFGHBHDEAEA,False +417,6.0,3.0,6.0,6.0,13.0,9.0,7.0,12.0,HGCCECEAEHGHGCFAFHDDBDEGBGHHEEDAFGFHEHAAADBCHCGFEEEHEHEFEFDFHF,False +418,7.0,7.0,9.0,13.0,10.0,16.0,6.0,11.0,HEFFFEDECCHHBHFDFACACEDHDBDBDBDFCFDEDEBHGEFFAFADAFHGBGCGCFDEAHDFDHGHFHCGEFEFABC,False +419,6.0,2.0,4.0,3.0,3.0,0.0,2.0,0.0,EEBDBAAAACACEGGCCDAD,True +420,20.0,21.0,13.0,17.0,21.0,27.0,25.0,13.0,HAGAGAECCFDBEADDGAGFFDCBFFCABGBEBAGCGBFBGEGEFDCDEBFBEDCAHBHBDFDFBADGFFEGEGEFEFEFHFBBABAHHDGDGBGAGFGFGEEDEDAFAGDHEACACFFGFGFGEDECBFBFHHHGEAFAEAHFBEBGBCHCHGADC,False +421,9.0,14.0,14.0,8.0,6.0,14.0,12.0,12.0,FHFDFDBBBGBEBCBFDGDHFGABCGABBGEAFAHACACHDDFHCBBFHFHFGCHCHGBBHHGCGCACACHCEFEFADDFEFEGGCGCB,False +422,2.0,4.0,4.0,2.0,2.0,3.0,4.0,6.0,HFCFCECBGGGDGBEHFBAHAHBHDHC,False +423,19.0,10.0,8.0,8.0,6.0,9.0,8.0,8.0,DEABABCFEFDAAABFHFAFAFADACCGBABAGHBABABAGHEHCGDGDCDCGEHEGDAABAEHBAGACDFFCFHH,False +424,22.0,16.0,21.0,30.0,13.0,19.0,17.0,12.0,BCBEBDAEAEAHAHGHCBCAAEADGFGDGDCACFCDEGCDHBCADDDDDEABADADADAEGBGBHCGFAFDCDBDFACDBDBCFEHEHAHGFGFGFGECHFHCCGDGACDFDECFDADEBHFFDFDFBFBEHAGCGDFCBGDACBCFDAD,False +425,12.0,15.0,7.0,11.0,10.0,19.0,9.0,9.0,CADACAFHFDDCDBFBDBEBEDEHFABACFFHHGFDFDGDGHAHACCBEFDFGEGEADFFCEGBABAEHHBHBGBEBABGBEFFFFABGFFF,False +426,10.0,14.0,11.0,11.0,11.0,17.0,18.0,9.0,BFBAAEFEHCHGAFEBCFCGCGBGFHFCGGAFAFBFCFHBBFEFEFEBGCECBGBGCDFDBDBDGAGEFEGHGHAADEGCGHDBAEGDDDDCDFGFGABHH,False +427,37.0,20.0,35.0,16.0,24.0,26.0,23.0,17.0,AGAEEHGHGCCCGBGCHCHCHFGGAAAEAEAFHCHCGCACADEEECBABEFEHDFBFEEBBBCEFAFADACAFFCFDHDGBFFACDGDFDBBBCGCBAAAEAECGCDHFBDBCAAGACACAFAGGBEHECECEABFEGDFDHHAAAACHCHGHCHABEGCGFACCECFFBFBABAGFFDAECEDEFFACGCGAGCDFD,False +428,16.0,17.0,31.0,28.0,15.0,17.0,26.0,26.0,FGFCCACBEDEDBCGCGFDCAAECEAAFFGGGGHCHCAGDGDBHBHFHFHFHDHAGGDDADHDHBACGCGEDHBCDFDGDHDCCCBBBBGCCCCFBDDDBCCCHCFEHHGFBFCCAAGGDADGDHEHAGCGCBDBFBFEGAGEGHCFDHHHHEHEBEHDFDGDHAAECCCEDEDGH,False +429,8.0,4.0,6.0,7.0,12.0,5.0,7.0,6.0,AAHAGBFHFCEAEBECGFGFGEEECBCDCAEHEAEDEDHGHBCFDGEGDHDEDAA,False +430,5.0,7.0,8.0,4.0,4.0,3.0,11.0,4.0,HGDCHCBCBFGAGBGBEDHAEAEGFGCGEGAFCGCGDHDBBBCCGA,True +431,8.0,19.0,9.0,16.0,16.0,15.0,11.0,12.0,FABCEHHCGDGDFDFHFAEDGDFDFBBBBFEDEAGBEEEFEGEBEFDDGBBAAAFHFHEEDCDCGEDBDAEHEHBHBHBFGCDCHEDBFBGHGFBFBCBCGCBAHD,False +432,25.0,23.0,17.0,34.0,27.0,19.0,18.0,34.0,GBHHHFEGGFGFGHBABDBDBHGGEBBDEDHHHHAHFHEHFFFGBDDEAAAAADCDHACAFDBDCGCGDDDHAGBDHGHCHABAFEFEFEFDDBDBABGFAFEEDEDEAEBFDFDHAHABEBEDDDFHCEFEAAAECCBABHDADHCBFGDHEHAGBDHHEHEDEAECEDGCEEHDDGHCHCHEDDHBHCHCACBCG,False +433,11.0,10.0,8.0,8.0,5.0,5.0,7.0,5.0,GEEEBADHCHEBEACABDBDAHABABABCDCGCDABFDCACABGGAGHCHFFDDGFGFB,False +434,8.0,2.0,9.0,3.0,9.0,11.0,9.0,7.0,CECFFFHGHBHCFCFBFHDACEEFCGEDEDAAAGCGCEFFAAGGGHFHFHEGEGECAA,False +435,15.0,9.0,12.0,17.0,12.0,13.0,11.0,8.0,FEFHFAFEDEDBCGGFBHACGCFCHADADAFAEAEADHDBDFHEDEDBBGBDADAGAGEGECCHEAACBCDCEGFGFDADGHHFDFCCCBDGEFADB,False +436,9.0,4.0,4.0,2.0,2.0,7.0,7.0,7.0,HEFBABCEFAFABGGAAACFCFGHBHACGFGAGAGHHDHDHF,True +437,13.0,14.0,15.0,27.0,27.0,6.0,29.0,26.0,DDDEHABAHEHAHDCBGDHFCEGBBHBHADDEAGGEGDGDGCCDCDBDBHBHBAAHGGGGACECEGGGECCDGDGEGADADGFHEEDEGACAGHDDDFDFBEHCHGHFHEEEHEHEHEHEGEFDGDGHBCCEDHBCGDHEEBAGHGEGEGEDHBHCD,True +438,22.0,9.0,13.0,21.0,26.0,17.0,18.0,21.0,GAGEHFHCEGEDAFAHAHEDBDFDABAHEDGDBCAEGDDDGGGGAGEHHHGCCFHHBHBHBHAGECAGDGDGDGEHDFAGCEEFEHEAEAEFFCECFFFBDADFDADADAFEEEEAFAEEBABAHEFDGHEHFCDCDCECHCHFEAH,False +439,24.0,19.0,22.0,19.0,24.0,22.0,19.0,24.0,DCDCAAAAABAFGFDFDHGCGCGBDACCCCEHFACHEDAAEABAHABAEFHFCFCFBBHFHEHEGCGDHFECBBBGBEHEAEAHDGDGHCHFBFEFEBEDFAACDHDFBHADCCEHEHDBFGFHDHDGEGADADEDEBECHFGGAGEFCCBCGFBBAGEHFHGHEHEFECBGA,False +440,23.0,14.0,11.0,16.0,9.0,11.0,13.0,16.0,DCDGBGBAAHECEFGFGAGHHEDGBCFDFGHGEEFADAEGFBAAAABFBFDAACCCEDHHHDDAAEBHCHABCHAHAHABEDGFGBGDDDDDDGAAHACACACABFFHBHBHB,False +441,5.0,9.0,7.0,7.0,5.0,6.0,6.0,2.0,CFDBDGCADBDBDGAAEAEBFBCBFGHBEGDHDECECBCGFGFBFAC,False +442,21.0,17.0,17.0,31.0,26.0,21.0,12.0,20.0,AAAGDEAFCHCBEDDBDBDHCAAHBDBDADHFHFHFHFHFDFEADADHHCHDDCFBFACHDEEEDABADAFEFHCACFFFEFBBEHGDGEGFDDCDGEGECCCCCFCHDEEECGCFDEDGBBDBGGHBFAFEDADFDHEHDHAGDGDBAEEEBEDAHAEBEBEAE,False +443,22.0,20.0,27.0,22.0,26.0,31.0,22.0,17.0,EDEAHFDFEBGFEFHGAFAFEDEAHDFBEDACCCBCBAFADAHFCGHGHDCDCGGHBBGACADFEFEFBFBFBHBHAHAGGGEGAGACECECBAEFFDEECDFECECBCEHDFCABHBCGDHBFBFBFAEDCFFHFCFGFDEDEDGFGFGFBCHEGGCEDGCCHDGFGCCCACEDEAEABABADFDH,False +444,25.0,15.0,17.0,18.0,21.0,13.0,21.0,25.0,GCAFBBBBAFGHBACAFHCECHBEDEHHHEDAHABCGDEAAABDBHAHBEGGDGACDBGGGGHGHGCECEFHFCCGBEEEEEDFCGDGDADADCECBFFCAEAEADGDHAHAHEHDHAHEFEHDGFHFHBDDAHAGAGAGAGEFBHECFCACHDH,False +445,4.0,5.0,1.0,1.0,6.0,3.0,0.0,1.0,FEBBABEBEAFHFEAEAEBDC,True +446,3.0,5.0,3.0,4.0,0.0,2.0,5.0,1.0,DBDAGBGCGCGCBBBAGFDHDFA,True +447,27.0,17.0,19.0,29.0,21.0,26.0,19.0,16.0,AAEEEEFDFHEADAGFGFGAGHFABBBBDADAHFDGCHFDFAFGCCBFFHDHDADEBHGCAHAFCCGCHEEADCBFFDFAFACAEECDCDBHBDCCEDEAGABDBDGGGGHFHFHDEAFDCDAAABAGCGFDFEEEBGAGAHBGDGDFDFDHHACCDCEBEAECEFEFDFDBDB,False +448,12.0,3.0,7.0,7.0,6.0,6.0,10.0,15.0,GCACACAFHFHGHDHAHDDEDCFAHACAHGEFHBHBFGDEHEAAAGAGCDAEGEBHDGFGHHCHGH,False +449,27.0,20.0,31.0,20.0,16.0,31.0,25.0,16.0,CCFCACAHBDGCGCBCGCDCBBEBAGFFFCFCDCBHBEFDFDHGGDCFEDBDFDCDCFFDBAECHADBCHCHCAAAAFAFADDGFCECGCGDDEHGHFFEHGHGFGFGAEFBFEFDBHAFDGGCFAFHHHBHEAGAEAEABGHFAFACACBCACGBBAGACAFFGFGFDBCBCGEEEECFADGBGA,False +450,2.0,7.0,4.0,2.0,6.0,1.0,3.0,3.0,DGCGCBDBHCECHBEGEABFBHEAEBEB,True +451,8.0,7.0,6.0,1.0,2.0,4.0,4.0,3.0,FGFHEABCCCDBABAHCHEAGCGCBAAAABBBFGF,True +452,12.0,16.0,17.0,11.0,29.0,15.0,19.0,16.0,EGDGEGHCFCFDDBECFHFHGEBEBEBEBDBAHAHADCEEEEEEEBECCBBBGDCDCFGHHEACAGBGHFEGEAECFDEGFHCEDFDFDCBHEAEAEFBGCGBAHFHGGEEBFGFGEHAGAGAFCBHHHCCECEG,False +453,4.0,3.0,6.0,2.0,6.0,8.0,4.0,3.0,CCFCEEHCHBDEFAFAFHGDFEGEFBFBFCECGAGA,False +454,17.0,13.0,25.0,22.0,19.0,16.0,28.0,27.0,AGAHHCDEDGGGDHHFEEGEHHCGGHGABCDCDAAFCFCGAGCFFFHEEEHEBGBCFHDAEEBDCDCGCGCBHBFCFHDHGBGDHCHFHBHDHBEAFCCDEDAGCGCDCFFHGHGHGAGADACAEABFCECECEBEHAGAHHDGDGHGHGFDFDEBCHDDCDGBGEA,False +455,3.0,8.0,5.0,6.0,3.0,3.0,1.0,4.0,ADHHHDFFACBCBCHCBDDGDBDBEBEAEFCBB,True +456,17.0,25.0,25.0,21.0,21.0,26.0,24.0,21.0,GEGBFBFBFBGAHAFACDEDCCHFFGBGAACFCHGFCFGHDAEFEFGFGHEBEBDAFGFAFCCBABEHCGFEDEDGBGBFBEHEGGCDCDCBGHDCCCDFAGBHBDEDHCHCHEHCBCDDDDFBEEEEGGBFCFCHAHACGFBBHDHBABGBGDGDFAFAECECEFDFDBGCHBAAHHEH,False +457,12.0,10.0,8.0,8.0,4.0,11.0,8.0,8.0,DBDFDFCCCHBEGFBHEFACBDBGHGBFAFGHAHAHGDDDCCACGCEHGFGFBFBABABDHFAAAEAFA,False +458,20.0,11.0,18.0,22.0,26.0,28.0,20.0,28.0,BFGHCHEAEAFFFFGABCFGFECECECECHCHGHDHAHEEEFHAAFBCGHDHDHCABGHCFDGHGACFDDDBCGDDFGGGGEEABGFAFEHAFEHAFAEAEABAGFDFEEHEFECDADHDHBHEHDHCHFHDHFHGDDDDEDEFEFGDCHCECEFHFAGBFFEFCADGBGBHA,False +459,18.0,25.0,19.0,16.0,13.0,17.0,21.0,14.0,CACACDEDBCBHAAGHBHBCEDEDAGGHDFDEDCHFHECFBFACAHAGGGGGAGDFBABFFGFBHBHBGBHBACABHBGCGBGEFADCDCHAHDHDBACABBBGEGEFCFBGBEFDFABABFCEGECDCBCGDBEGFFCFDGE,False +460,21.0,19.0,19.0,30.0,29.0,19.0,23.0,32.0,FDEDECCDEEHFDFEFEFHAHDCGCGCFDDDCGAGAECDHBEBAHGCGEFEDHDHDGDBHBADCDCHHFECHBGBEHADBDHGHGHGHDHFBGAGHBFBAECGGFEFEFDGDCDAEGEBACHGGDDADFHAEABBGBABDFDFABEDAHBHAHAEDEAEHEHCFCHEHEHBHBHGGCACAHEEEEFDFCGDH,False +461,9.0,19.0,19.0,25.0,19.0,17.0,20.0,16.0,BEGCGDAEHEDBDCEHECACAEAEAFCEGHGHFHGHCEDDDHDEGGFEHEFDFGFDBDBDGDEDCFCFHECBDHACCBCBFGDGCHBHDDBGBGFCBCDDGDACFGGGGFGBEBEGHDBDFCFBFDFDBHHAHAEDFBCBEBEC,False +462,9.0,14.0,11.0,15.0,9.0,10.0,15.0,17.0,CHCHCGCBEBDHEHFBGDGDGDGDBDGEGCHHBDBDACFCHGFEAHFFDCGAGBFHEDEHHAHAEBHBHGAGBFBDBCFCBCBADAGEGHHEFDFDGDAH,False +463,15.0,16.0,16.0,16.0,13.0,12.0,15.0,14.0,EDEGEDHBHDHDACHCBCAHADGDGAEEHFGFGFAEGEDECGGAFAFDBCHCGCEBABABABDEACHCBABAFGEACFDBBCBEGEGCDCDADBDFHHHHHBDCDGBFFGFHCBCFG,False +464,20.0,13.0,10.0,7.0,14.0,12.0,14.0,15.0,HHHBDFFCHCGCGAGDFDGEBFBABAFAFHGHBAGEGEHBACFCEDBACCCABADAGBGAGEEAAFAFACGCFAHEHEDEBAGEHEHEGAGAEFHHHHABEBDBF,False +465,32.0,28.0,23.0,18.0,15.0,22.0,28.0,21.0,CAHHBFBGCACEGFGAAABABAGGCGCGEAAGCGEEDBDGDCDHDBBABAFABAEDBGCEDBDBAHABFHEDEDBFFGAGHHEGAGHEECDCFBHCGBDBDBFGFDFCFAAACACFGHGAGDCFGAGFFBHCHCEABHBFBFHFAFHFEFBABGBGBGHHHAHAGEFCCHBHCAGBCDCECADADAG,False +466,14.0,31.0,26.0,20.0,17.0,27.0,15.0,13.0,BBBBBCGFEFDFDFCCDCHHDAFADACCEAGGCGCACFFEGECEFECCACGEBAGDGHBABDBHBHFCBHFCFCAHDCDHBGFEEDEDFAFHHGBBFAFCCCFAFDFEBBABACHHBDBDBFBCCFFFFFFDBBBBBEBECEGEGDGDGEGCHEBCDFBBBDD,False +467,15.0,12.0,15.0,11.0,17.0,18.0,18.0,13.0,HAGECCBCFHEGGGGBGBDBGBAFACCFCFCBDFAAAAACEEEFECDFDCDCDHBGGGFGDABAGAFFEAEFHBEDEDEFBAHGCGCHFGFGFHHDHECEAEGFAFHHEHEBBGEHFDC,False +468,22.0,12.0,14.0,17.0,19.0,18.0,16.0,15.0,DADADADAHAGABAEHFGFGEGBHBGADHDGGACHEHCHGEFFBCGCAFGDGAEHEAAFCFGAHAHEDDFDCHFEFEDEBECABEFGBGAGCCECFCBBBBHAEBECCADEDHHHEDEDEDFFFFGDAAAFCF,False +469,18.0,26.0,29.0,20.0,29.0,19.0,16.0,15.0,CGCGCHCFCGHHCHCHCHCFAEAFFECEBFGDHDCECECHCFFDBDEDBGGEGAGEHBBCCACABEEEAEBEBACECGADBBHBDBEFEFEFCDDGCCBAHHFCBHBADAGFDBEFEFEAECBFFHABDBAEDECECEDBFBDBDBDACGEGEBADCDGBGDGACFEFBAEH,False +470,6.0,1.0,5.0,5.0,3.0,4.0,4.0,6.0,CBCAGGHDHDHDHFHFEECACADHCAFAFGEADG,False +471,8.0,12.0,3.0,4.0,7.0,8.0,8.0,2.0,GAAFBEGEFDAGEGEFEHGBCFFFFGBBBEBABABDBDBEBDHGCABACAGF,True +472,9.0,4.0,9.0,5.0,3.0,6.0,1.0,7.0,HACGCABHCEAFHBHDAAACFCBEDEDADAHFHFCFAFBCDCHC,True +473,2.0,1.0,5.0,2.0,7.0,3.0,2.0,10.0,CCHCDDGFHAEBEHHFACHHFHEHEHEHECEG,True +474,8.0,7.0,5.0,9.0,9.0,4.0,1.0,12.0,BCDHBCBADCDHHAHDHAHEDEDBHEEDHCHAFAHAHCEGDADEFEFEFABHBEB,True +475,11.0,5.0,2.0,1.0,3.0,2.0,5.0,4.0,AACDCFHAGAGAEBGBHBFEAGBGAAAHAHABE,True +476,25.0,30.0,25.0,21.0,26.0,22.0,25.0,24.0,HGHEDBDBCHEHEDEDEDEDCAHDCGCFDFGEGDGAGAGHGDGDCAAHABAFACBCBCEDEAEDEAGDFEBEBEHGHFHFCBBFGHGFEFBBBFHGBCFCEBABADHBCACGFHFACACDFABHEAEHHDGACHFBFBHBHBABGGDBABGFEFBHGHAHEBGBGCFBEBECGCACEFAGECACFDFEAECCBGHCDD,False +477,15.0,14.0,22.0,19.0,17.0,22.0,25.0,22.0,DFGGGFHHCHEHBGDEEBFBAAHGFGFGACCCGHFHBHCDEEFEFBFAFBFCGCEDEHEHEBFAFAFAFGCGCGDBCBFFCHCDDDEAEAGDEDECGDGABBHDHDFDFDGCGAHEHFHCHAACDDBHHACBGBGAGFFHCCGHHCCGDGDGCGEE,False +478,14.0,12.0,9.0,13.0,13.0,17.0,7.0,13.0,AFAFBFBDAAADFFBFBEHGFEFHAHFGDDFDHAHADABFBFHEHECCACGFBDBGAEHCDCHGHGEAECECEFECADFDBGBHBHEHDDFEFDBEAC,False +479,29.0,20.0,16.0,24.0,27.0,18.0,17.0,26.0,GEHHHAHEGBGCHCBCFGDGBFDHCCBCHFHAEFEGGDHDACEDDDCDFDFDHBAADHFHBEFEHCHCDFAFABAEGBHBABABAEHEAEAEDEAFHEDAGEBEFGCEDEFEDHBFFDFAHHDBDGDHEAEGCBDEDBAGAGAGAEAHACACAEAEBHAHGFGEBEADADBHBHFCC,False +480,11.0,14.0,7.0,9.0,18.0,15.0,6.0,9.0,FAFEGDGBBEFEDEFEFABAGEGEFFFBBCBEDABEGAAAFHFDEHHFBFDFAFCDCDEGHHCHBABCBEHEHEBEBEDEHABEFACDC,False +481,8.0,4.0,7.0,16.0,11.0,8.0,9.0,4.0,EEADADFDEAFBFGEGFGDGCHDDCDEBEGEGCFCHDAGCGDGAECFCEDDFDEABABADDDDEHFH,False +482,11.0,7.0,25.0,5.0,16.0,24.0,10.0,11.0,EAEAEACFCBCEFEGAGAGCCFFEFGBCFFHFCFAHACFCEEHCCFDFEEHBHFHAGFFEFEBDAGCGFAFEFEHECGCGCFCFHFHCCCBCDDBCCCCFDFHAECBHG,True +483,24.0,31.0,31.0,29.0,20.0,23.0,19.0,21.0,HAHEECBBBBGBECEFBFHHCHFHDBGBHEGEADAEAEBBFBCECFCACABHCHCEBFDFCFCFBFHHHEGCDCDCDHDCECGABADDDBAGAGAHEDEBBDGCBCFAFABAHCBCFHGHBDEDGBGEHCDCFCFCAHFBCDCDGDHABGFEBDBDBDGAFAGAFDDCEFABAFDDGAFEFDGCBABHCGDGDCDCAE,False +484,10.0,14.0,9.0,7.0,6.0,9.0,6.0,9.0,HCACBFBFCFCFHAHADACABDCHGHGCBFDHCBGBABFBDBFBEEHADADHBBEBADAGECEFHBGEGF,False +485,10.0,4.0,11.0,5.0,13.0,7.0,15.0,10.0,AEAEHCHCGCGCBEGEGFGBGAGFGEHAFGCHDECCAHADDFDFHFHEGEGACCBHDHAEGEGCGHBEEEGAFAC,False +486,10.0,4.0,4.0,3.0,10.0,7.0,9.0,8.0,HGHCFDHAFAECEFHFHEGECHDDACABAEEEGGAEAGAGAGAHFGFEHEFGBBB,True +487,5.0,6.0,9.0,7.0,10.0,8.0,5.0,12.0,FCFCFHFAFAFGEDCBEHHGGEHEHAGBHCHFEAEDEDBHADCBCDHDHDFBEBCCHCGEHE,False +488,11.0,11.0,11.0,8.0,15.0,8.0,13.0,12.0,CBABEBFHFGEGHCDCAGDGEABBCGGBBHEFBBABGBADEHCHCEAEAEGEFFFCGCEHDHDHECDCAFAGAGAGEHEGFDHCHEHED,False +489,22.0,25.0,26.0,26.0,18.0,25.0,28.0,23.0,BEBEBEBFFHDHDHCHDHCCGCFAGCHCHCDCGCABABAFCHEHBCBCDCGCEHAHAEGGABFDHEBECGCHCHFDADAHHEGFBHAHFDGDCCCHFFGGGGBFAFABGFEFAGGFGDBAHFEGEGEDBBEDDBHBDFDFGGCEFGFBFHGADADHCEGEGDGDFDBBCBCDGBADABAFCFAFADDDBCGAE,False +490,19.0,24.0,22.0,16.0,30.0,19.0,23.0,31.0,FGGAFEFECGHHEGEHEDEFEHAGFBFBFHAEAHAEAEACDEBBHCECACEGBBFBDBCHDHGCFEHHAHAHBEBECGGDGCHBHGFGBDFCGHGHDHBHBACACHBEAABDHEHDHFFBFHFHEBCDEDEDFDGEGAGADBCHFHABDBDCFAEAEBEBECGCGEHHCCBCHCEGEGHFCGEG,False +491,16.0,23.0,19.0,29.0,31.0,20.0,28.0,25.0,DHDBCECECAGFGBBEEEECEDEGHCDGGAFDFGFGCGCEHGHGEDFGCDFGFDDDCDEFEABDEDEBEBHBHBGGHBDBHAFABDGHCECGAEAEAGABHDHDHDHBBBGEHEFEDHBEEEGGCDEFGHGHAHAFCFGFEDCFEABHFHEBEBDHDHACBCFGAGFGHEHBGBCHFGDDADCDADFDECB,False +492,2.0,8.0,8.0,4.0,4.0,4.0,9.0,3.0,GEGFACBGAGECCHCHCBFDGHCCGCGBDBDBEBEFDFBGBG,True +493,21.0,13.0,20.0,26.0,11.0,13.0,10.0,15.0,AACGHHEEDBDBDCDCDBEBFBFEGDCEADDDFAFAEAHHHFAFADEDCHCBCAAGACDDDDDBCAGDCDBEHGHGFGABDHDHCCCCHADAEAEDHDAACAFAFBFEDGBHCCADHBGBDFCFCHCFG,False +494,4.0,3.0,5.0,3.0,3.0,7.0,4.0,3.0,AHFEBAHCHGFGFEFDADBFFCFCGCGCBEAD,False +495,0.0,4.0,1.0,1.0,4.0,0.0,2.0,1.0,BDEEBEGEGHBCB,True +496,6.0,16.0,13.0,12.0,12.0,13.0,12.0,10.0,DHFEEBAFCHCHCEFHABBCBCFGECECEGEBDCDCBBBBFAFEBEGGCGAGFHEDGBGEGCHEBDBHBHCGBHAGDFDFDFDFDHCADFDFGB,False +497,19.0,9.0,12.0,22.0,14.0,24.0,20.0,18.0,DEDAHEBAAGDBHHGABAGCHCDCACFCGCEEACBFAFAGEDDDHHHCHCGFGHBAGAFAHDDDDDGDFDFHFEEDEHFHEBFDFHBAGHGHFHFEDEDFDFDCGBFACAGAFHFEABGEGFGFGFECADAGGDGFFF,False +498,8.0,3.0,6.0,14.0,8.0,17.0,6.0,15.0,GFFDFEGGBEBHAEDGFAFEFDDDAFHCHCDCDGFHAHFHFGDHCEFHCHCFDHDHAFDFEFAFABAEHFHDHDEDH,True +499,0.0,6.0,1.0,2.0,2.0,3.0,3.0,4.0,EDECHDBGBGBHBHFGFBHBF,True +500,9.0,11.0,8.0,10.0,19.0,12.0,9.0,5.0,GCFDBACGFBFAAAAGBFAEGFGCGHEAGHDFFCEDEDEDEDECHBEGDDEAEFDFAFEBEHEHEDEBEBEBCBCBFFEGBCE,False +501,8.0,14.0,12.0,11.0,8.0,12.0,9.0,4.0,DBDBEBDBDFDAGCGFBCBCFFGCDCDEDBBBECECFBFECABDDAFAFAGEFBHAGAFCHCDCGHGHBFBEGEFCAG,False +502,5.0,5.0,5.0,5.0,9.0,6.0,4.0,8.0,FEFEBHHHAHABEBDDFDHDCAFFECEAHCBCEAEBHGHGCGFDEGE,False +503,12.0,12.0,13.0,25.0,16.0,10.0,18.0,21.0,GBGBDECCCFHHBACGDGDGDADCGCBBHDHDHDBDFDFDHEHGCEDEGEFAFHBEFFGCEHFFDDHDHGHGDAACAGBDHGHEDEDGAHCGDGDACEGAHAHDHEHEBEBCBFBEHEADDGDCAHE,False +504,10.0,15.0,9.0,13.0,14.0,7.0,8.0,9.0,CBEEFBBGBGBDBABADFBAAHEBEDEDGFCEBDBHAHBCBCBGGFDFCAGAFDGDHDHGEBEHFHECECEAHCDDEHEAEADCD,False +505,18.0,16.0,17.0,23.0,12.0,18.0,20.0,12.0,FGFABEFDHDHFHGDBDBGBGCACDDDHAHBHFFFBGCGEAEAGABHBGDGCECEDHFAGBDEAAHCEGHDEDEDFGHDDDDEFFAFGDGCFCFDFDACFCEAABGBABCBCFHGGBGEGAACCCCFCGBADADBD,False +506,22.0,16.0,25.0,22.0,25.0,11.0,27.0,18.0,AGCDCDHDBGCGAGDDCDGBGDCBCGFGHCECGHGAEFEDEAEGEFHGBCBCAAAAGGDGEHEAEDEDEBCBGFCFGDDEDECFDHDBEAEDEHGHCCCCABAFABCBAHCHGHCCDCEFAGEHAGAGHEBCHEGBHBHDHFEEEACACDEDEHGGGFBFBGDAAA,False +507,13.0,17.0,22.0,10.0,17.0,14.0,17.0,13.0,GGGCBBBEBHAEAGHDCGCDHFEAEABHCHGFGHGCCFFBCAAHEHEDCGCGCDADEHAHFDFAFCHCFCBDEEAEFHAHFCFABBDBDEGECEBGBGCGCDEEBEBFBEACBCGCGBGCFCF,False +508,17.0,21.0,24.0,12.0,17.0,20.0,19.0,17.0,ECHCHCHCGCFBGAGEBEBEBDCCFHFGCDFFHHBGBGDDDGFCFCGDGFAACACGFHDHGAAHAEBEGCCCFGFADADHBBBBABEBEBCGCHDHBGEHCACECEDDCFFAFEBACAEHEHBGBHEFAFBGHGFBCBEAEAGFFCF,False +509,4.0,0.0,5.0,5.0,1.0,0.0,3.0,4.0,GHDCDCDCDCAEHGCDHHAAAG,True +510,10.0,11.0,3.0,4.0,7.0,2.0,18.0,3.0,HAGGGGAFAGCGEGBGAEBGGEBEBDCEGDBDADEBEGAGAGBBBCGGBGAGHBHAFA,True +511,2.0,4.0,2.0,2.0,1.0,2.0,3.0,1.0,DEDFHGABBBBFAGCGC,False +512,2.0,4.0,2.0,1.0,1.0,1.0,0.0,1.0,HDBABCBCBFEA,True +513,4.0,5.0,8.0,7.0,6.0,8.0,11.0,4.0,GGHGHGDBCECECEGFHDABADEGGCGCECBFEGACFFFFBFCFHBAGGDDDD,False +514,20.0,26.0,19.0,15.0,24.0,22.0,24.0,21.0,FGFEFEFBHGHBEDHHHHEDCDEHEHCBFHGAFAFBFDCACAGGGGGGGHBBABFBFBCHGGBACGCGDFEEEEAEFFFFDECECFCBCBEAHCBADEDAGFDEDBBEBEHACAFAFABHEEDCFGHDAABEBEDGGHGHGDDFEFAHAHBGCGBGCCCABBHBAGCBHBE,False +515,22.0,23.0,26.0,33.0,16.0,30.0,25.0,23.0,GGGGCBEHCBCFEGGFADHDHCGDACCDBDGFCFHBHGAABFBAHAHDGDBDADACGCFDFGFDDHBGGGEBEBEFGFHBEFABEGCGCGHAHFHFHDBDBDCDCDCHFFFHFDFAGEGBABFEDBDCECBCDDHDBGECADEDEFFFFAFDFDECGHDFDFBCGFECHHAHAHGCBCDADAEAFCFCDHDABAHABC,False +516,17.0,13.0,13.0,12.0,15.0,20.0,10.0,20.0,FDFAGABHFHCEEAFCEGGBEBCBCBEBDHFACGHGCACACAHFHDBGFGDAEAEABFDEDHDFAFEBDHHHFHFHFHAHAHAEAFADCCFBBCEHFFFDGDGBEHHHHGCBEFEAEDFC,False +517,26.0,21.0,23.0,17.0,23.0,30.0,24.0,22.0,ABAEAEAEBGGGGGAECECEDFCEBAGHFHAEADCCGGGAGBEBEBEDCDFAFHFHGCCBHAFAFAFHFGBCDDFACGFGHDEEGEFEGBGFGADFCFCFCBAEABCDHHHCHFHFHBHAEFFFCFBECCCFFDFDBCHCADAFHBABDFDBBAHGGEAEHCGEGCDAGAHDGDFHFHFEBABEBH,False +518,7.0,13.0,9.0,12.0,7.0,6.0,7.0,5.0,CGCECBHDEBGBAFCDBDBDACEBDDGDGEGEFAFAFAHCFEHEDBCBDBDCDBBBDCHFBAGAGH,False +519,15.0,23.0,14.0,11.0,17.0,17.0,14.0,16.0,AFGEDCHBBBBBBGGECEFFBACACBCGCBHFAAABCCEEDDDHBBFBFBGEHEFDAEAFFFEHAGABAFHFBDBHHHBEBEACGCGCACDCHEEBEGGDGHGHGDDDCBGAEBEFEFAFHHHFHFB,False +520,18.0,12.0,17.0,12.0,18.0,12.0,16.0,36.0,EGEHCHDHDGDGCADAHAHFCEEBACEEEADAHHBCBEHEHEBAHCEEGCFEFAFABHBHGHDCGCGDHDHFHDHDHAHCHABCGCFBHHAHFHFHFCEHEAAHHBHGEAHHBFCCGBGFHAEAEGCHBHGDGDGAGFHHC,False +521,4.0,11.0,9.0,6.0,9.0,15.0,6.0,12.0,FFFCCHBHCFCBCBFDDGDGBFAGCFEFCHCGFBBBHCHDEDEAEBHBHGAEAFFBEGEHEHEHBHFFFFHD,False +522,17.0,10.0,12.0,14.0,22.0,13.0,17.0,18.0,EEEEDEABAGFEFEHGHBDAAABDBDAEHHAHGHGHDHAEABHHHHHBCGCFCFCDBAGACEEGCGAADGDHAFCFCEBEFDFEEACGHBEFEFEFEDCGFGHGEGDBAEGEDCHAHGDFDGC,False +523,0.0,4.0,3.0,2.0,1.0,0.0,4.0,2.0,DDEBCHCGBGCGBGBH,True +524,25.0,20.0,21.0,11.0,21.0,16.0,21.0,28.0,FGHGHEHEHBHFHFBFBDBEGDCHCGAEAFCDEAAACHEHEHBFFFFAAHCGGHGBGBHCHCDCGAGAGBHHHFDCDAEABBBCECBGGFACHCECEAFAGHFAEHGGEDEDEBHHACCCACBCHDGDGAAABAGFEBHAGBGCFEEDEAEAFBECHHAHBHB,False +525,5.0,5.0,3.0,6.0,5.0,16.0,3.0,8.0,DHFHFEFEADAGEGECBDFCBDDFHCHFAAAFEHHFBBBGDFFFFFFFHFH,True +526,1.0,0.0,1.0,1.0,2.0,0.0,4.0,6.0,HGHCHEHEGGHGDAH,True +527,14.0,26.0,15.0,11.0,16.0,18.0,25.0,17.0,BHFABADGFABCDGGECEBEFEDBDHGFCFDBDBCEFBFHAGBFEFGFHFHCHBHEHFHFHCHCEDBDBEGHGHGCBCBGDEEFCFBGBGBGBCBDBGAEAGBGAGECEAFGGGHGCCAFGGEAEDBHAGABAFAGHHCBBB,False +528,26.0,33.0,22.0,21.0,21.0,26.0,21.0,23.0,HDBFBDGDGHHEBFFCECFBABGGEBEGGAHEHABGBCCCABDFEFGFADACCGABDBFBADADBDAHAHBEGHFHBEGEBCBCBHAHABADCHBGCDEDEDHGGGGGCDBFFFFFAEECHCHCFEBEAADFBFBABDBGEEHEGEFCFCFEAEADCGFADHHFBDBAHAHACABABFBFCFHBHBHCDFGCD,False +529,19.0,28.0,16.0,26.0,16.0,17.0,19.0,17.0,ABADGCGBHDFFFGFGDGFBDGGFAFCGGFHHAAFFFEAAHAHCBCBABADDFFFABDBDBHGDACHCHGBBBBBGEDADAGCBEBHHEDBCBCBDEEGADABABADADCCBCBDFDFCBCHFEEEDEHHHGHBHDEECHGDGDBEEEDEDGDGCBBD,False +530,10.0,4.0,8.0,6.0,5.0,11.0,7.0,6.0,FFBFCDCGAGFEDCDBEGEGFCFCFCBAFDBHAHAHAGACAHAHEGDFCFADEGAFH,False +531,13.0,7.0,11.0,9.0,7.0,13.0,13.0,17.0,GCABEBFBAHHHGHGAAHCHBEBCDAFHFHBCDCDCDFGEGCHAHEHCHDFFFGFGCGAAAHGGGHFCECHHHGAAEADFBFDFDEDAGF,False +532,6.0,4.0,4.0,4.0,4.0,11.0,3.0,7.0,ABCDHFHFECEDADFGHAFCFCFBFBGADEHGBFHEHFHFAFA,False +533,14.0,30.0,24.0,27.0,22.0,23.0,21.0,29.0,CEBEDGCHDGAAABHEHGCGBFBEGDDDCDCHHDEGFHCEFBGBCCFBAEAGABEDFDCDCDHDHGFGHGCGDDFBBBBBDFDADCDGBFEFDBCFCFBDHDGFACAGFDFDEAECFBBHBHCACAHFDEHEHBDBGBHBFBEDCFEEHBHBCBCBHEFEFCHCHEAFHBHBHEHFGCAEGHGHGHGHED,False +534,7.0,14.0,11.0,10.0,12.0,6.0,11.0,7.0,ABADCBEGAGABDBHCECDBEHGCBCBCGCFCFHFHFBBCBGEGHGDGEGEDDDCDEDABAHCFEEAEFEBBGDEHBG,False +535,1.0,8.0,7.0,5.0,5.0,7.0,1.0,7.0,BHBGFHEDDFCBBBBHHHFEFHFCFCACBDBDEHEFECCCD,True +536,5.0,4.0,11.0,11.0,13.0,6.0,6.0,8.0,CDDDEBHHGHDFGCCACEDEDECEGEACACHEBFFEFEFGFGDGDHAEEEABCBHEDCDCHHDC,True +537,28.0,21.0,11.0,18.0,13.0,11.0,21.0,19.0,HGAGAGFDDHGEBDCGAAHGHEDBDFDEGAGHDECCAAAADDGBBCBHBHBHGCGCBBBFBFGABAGCHBGAFHFAACAGDFEFEGGBFHAADADFDADBBBDAEAFHGHEHEHAHAHAHAGEGDCDCHBABABECDGAEBE,False +538,3.0,5.0,4.0,4.0,5.0,2.0,1.0,6.0,HCHGHAFBEBEAEACDCHBEBFCEHBHDDD,False +539,6.0,6.0,7.0,4.0,9.0,4.0,6.0,1.0,CCAGDGDGEFBCACBCGDDBFEFCFEABABCEEEABAEGEGEH,False +540,4.0,1.0,2.0,4.0,0.0,6.0,5.0,0.0,FDDGAGFGCGAGAFFFBCDADF,True +541,9.0,14.0,13.0,6.0,8.0,6.0,10.0,5.0,CBCGEGEFEHAGEDBGEGAGHDCBCGAGAGHDFGAACBBDBDFFCFHFDACACBBEBECCCCHEACBBBBB,False +542,16.0,16.0,8.0,16.0,13.0,11.0,10.0,17.0,EAHAGFDCGCGDEHCHBAAADHDHEHEFBGBABFDAAADBDADADHDGEGCGHGBFAFEBBBBHFDFDEBEFAHEBDGFHCHCHGDFABABDHHHAEBEHEDEBCCF,False +543,21.0,26.0,17.0,27.0,29.0,23.0,26.0,18.0,GDEHHBFFAHDHDCBHBGEDBDGAGDHCEEEBFFACBBEDGFCFBEBECAFDDHBHDEFEFEFEGGCGBHFFCFEHBHEFBHBADAEAGAFBFGEGEGCGDEDEGCGCBDFDFDADABCFEBBBDBGGGFGCDCDCACFEDBGEGEGHABGEGEAAAACCHEBEDEHBABFGFHHEHADGDADADAD,False +544,22.0,22.0,21.0,19.0,23.0,23.0,21.0,20.0,CGDGDBCFDADCCGDBDHAHCHCEDFFGGGECECEAFAHCFDDEDAGCGCBDEDEAEHCHCEEECEFBFHDHGHGEGCHFEAEAEFFCFEDEABHHHGFBAGAGBDEGECECECHBHAHGBBFBGBDFDGAAFAFGBBCBGBFHEHCBDFFFHFBAAHBFBAAAFAGABDB,False +545,23.0,25.0,25.0,15.0,25.0,17.0,21.0,33.0,GAGAGEEHHHFHFHFHEHDCFHABBHBHBEBHFGBCCACACACGHBADHBECECEBABECCHCFEGHDCEBGGEBEBEFHHADCDCDFDHBHCAEEHEHFHGHGHFADCGFHCACACACBCEGDFHCABGDGEGFCDHGHAAAHBHBHBEBHBHAGABEEGEDEGFBFCGEDAGADDBBEAFCF,False +546,3.0,2.0,2.0,4.0,0.0,4.0,0.0,0.0,ADADAFCFDBBFCFD,True +547,13.0,21.0,3.0,11.0,13.0,5.0,12.0,11.0,GHBADHBHBGBEHDHEEFGHDHGFEDDDEGEAEDFAAGBBCBAGAGAEDEHBHBABABAGADBEBECEAEBBBBGBHBDFGCADBFBHG,False +548,25.0,24.0,22.0,17.0,28.0,18.0,39.0,21.0,CDCABDBHBGBGBGBCECBABGBGAHAHBFEEAEBGAGEHFACACDEGEGECHAEGEHFHFABEGHFHAHGHCDCEBEGDBFAFHGEGBGAGDBDBDBEFECHFHEBFGEGEGECAFABEBGBGHGFGEGCCCCHGFACGBHAHAECFGAEDHGHGDDDEAFADGDGDCAEGGACFBFAGEGACCEHDCDGGFG,False +549,3.0,2.0,4.0,4.0,5.0,8.0,5.0,2.0,HFEFGDGFBFDFEEEFEFGBGCCACDCAGAHFD,False +550,1.0,3.0,4.0,3.0,7.0,2.0,2.0,6.0,ECEBHBHGHBECEFDHAHECEDEDGCHF,True +551,16.0,22.0,21.0,26.0,28.0,20.0,19.0,21.0,EGEDEBEAEADDDCFCABGEFFHDBECHBBBBAHAFFCCDDDDDDHGHEFAAAAAGGBGFGBGCCHEHFBFHHDCDFFBFDGEGFCABBEBEBECDGFEECACDDBCFEDEHHDBDFHFHCHCEGGGEGEADCDCEGEFFHHGCCBCBDBEBEAEAEAGDFHCDGDHBHEHEH,False +552,4.0,5.0,6.0,11.0,3.0,11.0,11.0,5.0,GCCDFHFBDDEDECGCGDGHABDDGGGDHAHAFGFGEGFGFABDFHFCFDBDBFFC,True +553,5.0,13.0,12.0,7.0,6.0,1.0,8.0,8.0,BGDACECGDGCCCBCHCGCDBHHGBEAEAEFBCBEBDGCGDGCBABABEDCHHHHHBBDB,True +554,21.0,23.0,19.0,23.0,24.0,21.0,32.0,21.0,FAGAHAHFHGHBEEFGADABCBGBGFAHEDEFGFBHCECEHEHDGDEAAHGGGEGFFDFBCHGAGHCDGGGABDGDADHFEBHBHGGCACBCBCBGBCFADADGDEDACBGHEFDFHFHFBDDDDBHBGGGCDEFEGEGECHCBCBEBEBEFFAGBBFACECECDAEFECGAGEFDGGAADHDH,False +555,11.0,14.0,17.0,9.0,22.0,14.0,9.0,22.0,CGEEDCDADADBDBFFFHCAAEHHHEHEHAHEFFCFBGHHHFHCHDHEBGFGFBEECFCEEECGCGHEEEEADHBHAABCCACFCEDHCHCHBHBDBECGCEFFGFABBEBEGHAHBE,False +556,4.0,3.0,4.0,4.0,4.0,1.0,0.0,1.0,BABHECAAFBDCDEDEDECAC,True +557,11.0,15.0,15.0,16.0,14.0,18.0,14.0,14.0,BCBCBGDGCGEAHHEHGAFFCFHFCGAGACEBEBEBAFGCCDGBCEFDFDAEADDFDCEBFBFBEHDHEHEGEGBGHFHDDDDCCBGBCBHAHDEFFFGGCHBEAAAHFFDFDFDHC,False +558,5.0,2.0,3.0,3.0,1.0,2.0,3.0,2.0,DGDGACBFHFHAEACABACDG,False +559,29.0,26.0,17.0,17.0,20.0,26.0,24.0,23.0,DADCDFFHFAFACAFBDBACAGABFGFBHCHCFFEFEFGHGCBCAEGGGDBDBABFHFAEADDDEDEHAAGGDBHGFFFFCGAHBBGBGECEGEGEGEBEDCFFDFCCEAAFDHAEBFBFAHAGFHCCGBGBGBGAGABEDADHEBEHHAEFHAHABCBCHAEAFAEBHGHBBBAGDHHHHC,False +560,7.0,9.0,14.0,11.0,8.0,12.0,13.0,5.0,FCDCEFEFGHDAABACGCGCGDEBAHHBCCFCFGEGDBDBDBAFECDFDFEGGCAFABCFGFGEGHCDEDGDGFCBCBH,False +561,16.0,32.0,21.0,19.0,21.0,20.0,22.0,22.0,AFBGBGHGEDFAACDCDCEFEBCFCGHGHFDABABAHCCEAHBEDEDBDCCHGHEBEBEBCDEFGDGFBFEDHDHDBBBFFEGBGHEDGDFBGBACDGEBEBHBHCCGHGHGDGDGHGHBCAFHGHGFABAFAHAFCBCBFAHDHBBCBGFEBABCBCFCFEEBCFEDEAHBE,False +562,18.0,21.0,6.0,6.0,14.0,3.0,15.0,20.0,DGAAHCHBAFHBHBGCAEAEAHAEAHHHBCBGGEBDFAHAEAEBGAGAHDEGHAHBEAEGHGHBABHBHEDCGHGBEDGBGEGBGBABDBAEEHFHBCBCBHB,True +563,19.0,18.0,15.0,19.0,14.0,16.0,17.0,24.0,FAFAFABBHDCDCDFDCAABFCEDBBECDCDFFAGADBCHGGFHDHGHEECEGDADABEHHHHCHDHDFAHGFGFBDBCBFHAGABDBGBFDGGFCFCBHBHFHEHEHEGAGAHAGABAGABEECDCHHEBEDEHAGCGHDH,False +564,3.0,3.0,2.0,1.0,0.0,0.0,0.0,2.0,BABCBDAHCHA,True +565,8.0,12.0,12.0,9.0,13.0,13.0,12.0,17.0,BFBFEEHBFAFGGGCHDHDHGCDCGEHAHEEBBAEFGCGCHCFCFDBBBHCEBEHEHFGAGFFHFHABDGDFDFBHAHDHEAABCEGEGEDCHCHC,False +566,24.0,19.0,7.0,22.0,15.0,14.0,18.0,21.0,AEADAHECBGBFHGHDHAGDGHGBGBHFHBDDDHGHDHDADHDHAHDEDADGFEFGFBDBDFAAAAABEFDHHHEGBGAAEDEGEGAFAFHHBEEHCGBEADAEFFBFDFDBDBGBHAGBCBEFDHGCACBCBAAACAGE,False +567,18.0,34.0,25.0,23.0,26.0,29.0,16.0,24.0,CHFDFHBCBDBFBHEEAEABABCGAFDFDADADADBBBCBDBFCEEEFFAFDBDBGHDHBBBFFFDABFHGCABABABAHHHHDFBFEFHBCDCFCFBFEEGECFHEGEGBBDDHDEDHFHDHDFBAECCBHBEBHBCCCBDBEGHGCFCACEFAGEGEGCCFBFEHEHCGFECGFDAGFGHCCCEEEBEHAHDG,False +568,10.0,3.0,8.0,11.0,10.0,4.0,2.0,8.0,EGEDEHEHCDCEAEAEAFFEHCDDDCACHBHBDDDHAAACAEBFAGAHDCCFEDHD,True +569,16.0,11.0,9.0,12.0,15.0,17.0,17.0,12.0,EAEDEACHEAGBHHFFAGGDADADHBHAFFGDEDEHFBFCGBGFFDGHAEAFBCBEAECDADCGCGFGEGEGAGDEDBFFAFAFCBHAEAEGEGFGFDCHCGFBHBHBH,False +570,5.0,3.0,10.0,3.0,5.0,7.0,4.0,6.0,DADCHHGACACECHCFCFHDEGABAFFFFECECFGGHBCBCEH,False +571,19.0,19.0,10.0,25.0,20.0,11.0,12.0,21.0,EGEGEDDDADCBFBFCHCHGAGDHDHDADGHEDDDDHBHBHCADEEEDDHDBCEAABABFEEAEGHGHFEADDDCABHBHBHFHFEEEEFDCEEGCBCHGAEAGABFBHAHEHAFABHBFDDDBDBHAAFBBAGGCD,False +572,9.0,14.0,14.0,11.0,15.0,15.0,19.0,10.0,EFEAEGGGDGDADFHFGFBFBFGDGBBEBEADHGCBCBCGCECGFDCBCBFDFGEDBDHCAFEFEBGCHAFGFGEEHBGCGCEEEBHCHBADCCGGHAHADAGFHFE,False +573,4.0,10.0,13.0,15.0,11.0,8.0,6.0,4.0,AFCCGEEDEBEBAHAHADFBCBCBEFDGHBEGEFFBFDDBCECDCDCECEDDDDDGDCDCEBBGDHFCCGF,True +574,15.0,27.0,18.0,27.0,33.0,20.0,18.0,26.0,FACGCDEDBABABADHDBEFECGDFHHEBCBCGHHAEBHBHGDADGDGDEEEDEBCBDBEAFHFEDGDGDBCHEAADEDEAEDHCHAFDEDHDACHBHBHEHECFBABHDEEEFEGBGDDHGFBFBFCFCEBEBFFCECEGEFEDGDCBGEGHFCECEBGBHBHDHCEFFFBGBHHHEFAAHDG,False +575,16.0,17.0,13.0,14.0,16.0,19.0,22.0,14.0,HBCFCFDFEGAGAHHGEGBGDGFHEHAFBDBDCHCHGFDEDEFHFBEBHBHBEBHBDFDEDEHEGEFFACACGFHADGFADGBAEADAFBCHEFFBEBGBGBACGGFGFAABGGDGFCCACAEAECDGGGC,False +576,21.0,18.0,24.0,12.0,15.0,14.0,8.0,14.0,CDCDFBACHGHECECEDECECHHAHBGFAAHAGFEBCHAGBBBABCBADCFEGABABCGCFAFEBHAHDHECACHHFCBBBEBECFCFAFAHAFCGDFDFDBEBDCACACADBDEHEFEDGCACAC,False +577,11.0,6.0,10.0,4.0,4.0,6.0,15.0,11.0,HHGHAHGDGCEBABABGCHCGCECHCACHDFBABFHFCAHAHFFBFGGGGGGGACAGECDGAADEHG,True +578,13.0,11.0,13.0,13.0,10.0,10.0,11.0,13.0,HDHDFAHCHGEAAAACGBEEHHDEEEDADCDCACACDGDBDBCFEAGHCFCABFBFGCEFBHHHHGBGCGCGEEHAHFBFDDBDBCGDGAFAFB,False +579,16.0,20.0,17.0,10.0,16.0,13.0,17.0,18.0,HBHCDAHECCCCBHGEFCBCGFFAFACBDGDCHBHBCBEBEDGDFEHGHBHECCCEFAGAEHDGDGHBFAFAGAGBGBGBEECCAFAFDBBHFECBGHCHBHDHBHBAEEEAEHEAGAGFGFGDABA,False +580,19.0,23.0,27.0,23.0,24.0,28.0,24.0,26.0,FGFGCHDADGDHFFDCDABFFFFBCEAECEHADCDFDFABAHABDEDBAHCCCHBAAFAEGEGFGHDHGHBHGHDCFCFCADEFEHBAEEFGCDCGGGGGEHFGCGCFFHFHGHBCBDBDCCCGEBEHFBFCFEECFGHGHFHCAEBEBEGHGHFEFDCHCBCBGBDBEAAABCCEAFBHBHDHEEGABDDDED,False +581,14.0,16.0,19.0,20.0,20.0,20.0,13.0,20.0,ACAFBEAHDHEHBHCABBCHFHCEEGCHHFCDCBBEBHFABGDHFHFHBHBHBGDDDCFFHFBFGFECDCEAGAGACCCGCDCDEDEDADADFFFAFAGHCDAGHFEEGHCEEEHECECEGEFDFEEGDDDGDBBFBFBADH,False +582,13.0,15.0,13.0,20.0,21.0,19.0,19.0,16.0,EGGAGAHBFFEFEHECDCFCBGHFFGAGAGEGCGAGBFCFDDDEBEHEHCFBDDDDDDADAFAHHCFDEDBFFFFHAGCBDAFBHBEDGFGCBCBGEGEDCDCDCFHEHGHBDGEHABEGAGHFEDAHEEEEEBHB,False +583,6.0,13.0,10.0,9.0,17.0,8.0,10.0,9.0,FHFGBBBBABCCDHBEDHGFDEHCGCBEBEHCFCFBFBDBACFHGHGEEECECEDEDEHEDGCAEADFDGEAEGGGEBABEH,False +584,18.0,27.0,27.0,16.0,19.0,28.0,14.0,16.0,FHFCFAFHHBEBFBDCHBGEDBAFFCBHBCFGFGCGCEEEDEDBABGEFBGBAFAFHEGCGCDCDBHHCHAHAHGCECAHFHFDEGHBBCACABABFBFBFAFCDCDBABEBECFFGBECCCHCFAFDDDDFDBECEAEDBFCDCEFGFABABCCGEHCABGFEF,False +585,26.0,16.0,22.0,22.0,20.0,21.0,22.0,26.0,FHDHDHFCEBBDBAAAAGFGCBEDHDHGHAEAECDCBEBHCHAHGGFDAEFCFHHHEECCCDCDCDHAHABBECACADAHCDCDFBBEDAAGAFFHCEEEAFAFGFCECEFACAEAFFHEGFHCAGECFFGBGFGDBDBABAGGGGGHHHAHDDDHHHAHDGEGFGBGBFCEDGD,False +586,8.0,5.0,12.0,4.0,4.0,13.0,13.0,7.0,DFDCCCCCCFEBEBDFFAFGCGCBFDFBAAFHGHGCGAAHGFAFGFGCGAGBCHFHCGGHFHEAEG,True +587,4.0,3.0,2.0,3.0,2.0,5.0,3.0,1.0,BGGGDBDHDFCAEAFCFBFEFAA,False +588,7.0,14.0,10.0,16.0,16.0,9.0,9.0,13.0,BCDFHCGFGAEFFFDDBBHBFBHHGAEDDFDEHEGEGEHADFEEHEGEDEDEDEHHBHBDBHBDCDCDBBFBABACACEHECGHEBDGDCCCAG,False +589,41.0,28.0,27.0,20.0,22.0,14.0,25.0,23.0,EDEHHHEACAEAEGECBBHBHBEFAFEBAFHHGHAHACAGBDBEGCDEHAHADACACGEDCCCFBBBBBFAADACAGECDFHGDDBDCDCECDABAFCBEGEDFCGBGDHACABGHECBGGCDCGEFEAGCGDAAABABABDHGEAHBGAEHGBGBFCFCFEFBHGHBAAAAHABABADAGACACGCACHDHDHAFAGEG,False +590,25.0,17.0,16.0,9.0,20.0,24.0,14.0,17.0,HDFDEGEFBBECCBDBABFFAFDFCECBAGAEABGFHCACAFAFAFHEHEHECFCHEHEHECGBDBAFEBCFAFCFAGGCFCABHGABFFEGAHAGAGCHHEHFDFBEBCBEFAFAHAEFEAAHAHBHBGDGDGCEADAGEF,False +591,17.0,13.0,25.0,18.0,20.0,19.0,18.0,19.0,ADCFCHDBAEHEHEFEACAFAFDFEFECEGADHDHEBCCCCEHHGBDBDGCCFBGDDCGABAEAEDEAFAFCGCFHFEGAGDGFHCGCEHEAGCHCBDEDCFEDHCBEBFBAGEGAHCHCBCBAHACDBDCDCHFHEGFGFGDGHGFFH,False +592,4.0,14.0,3.0,5.0,17.0,15.0,9.0,5.0,HGFEEHBHFFEFHFEGBABFBGDFBBEFEDGDEDECEBEFEAEBBBBEBFAHAGFDFEFEBGCGFGBGFECE,True +593,13.0,8.0,10.0,11.0,8.0,10.0,5.0,8.0,EAEADADGFGCDDFBFHHGADABAFHHBAEABHHGBCFCFDFAFDHDCDCBFBCCCBCEEEAEAEFDAHACDG,False +594,16.0,13.0,15.0,7.0,3.0,9.0,20.0,22.0,BGBGCGHHHEHGAAFGCGBDFAFBHCHBDBCCCFDAHHBGBAAABHHHGHGBABABCCCCCDGHGHCHAHGEGDBFGFGCGAHAGFCHGGGAHAHCHFEDHDAAF,True +595,12.0,10.0,9.0,7.0,8.0,10.0,12.0,10.0,AEFDFGFGABHBHBACAHFFEECEFDFGBCAABBCDCGEBEBHHHHFBAEADGDGHGDGDCACGCACAEFHAHGGGBF,False +596,12.0,14.0,7.0,5.0,7.0,8.0,16.0,11.0,DBGBABFCGCGEGBGCHCABEEHGGGHGHFBEBABFBFBGGGGFDFCGABABAFAHHHHBEAAADDHCFEHAHBGACDGE,False +597,12.0,31.0,25.0,23.0,29.0,22.0,19.0,20.0,GBCAEDEGEDHCHGFBEGCCDCGAFBFAFEGBBDBDBDGGCEHEHFHDCDCDEDFHHBGBGCHABGCGCFHFDEBCDHDAABFBGBHDCDCEHEBFBFEFBFHEHEGEBBDBEBABCDGDBHBDFDFDACCEFBCBFHFGCEAEDFCCDCFGGEEEAEAFAFBHBEBCBCHEHCHGEEEBE,False +598,3.0,2.0,2.0,2.0,0.0,4.0,2.0,0.0,DADAGFCFCBGAFBF,True +599,18.0,18.0,17.0,19.0,19.0,25.0,24.0,26.0,EFEFADADEGEGBBHHABBHCCGAFDHDFEHHHHHHGAAADGHFHGGGGDEACHCHCFCGEGEFABEEGEHFCFDFEBGAHCHGFGFGFGFDDHEFCFEBDFEACAFHCHFBADGCGBADGDAFCHCHDDDFDFHCHBHEEEBEBGBABABABCBFFHFDGCGBGD,False +600,18.0,13.0,8.0,18.0,9.0,20.0,11.0,10.0,FAHEFAFAHDGGGGHCBEGABABFEFAAGAGAGAGAGBHBHCFFDHBHDEDEDABCFCEDEBEFADDBFFCFHFAAGDDDDDDFFFFHADFFFBBBCDADCCADHBE,False +601,28.0,16.0,18.0,22.0,25.0,31.0,31.0,28.0,DHDHCHCEGGGGGGHGHGABHGABAGDGEGBACHDHBGADFBHGAGFGDDADGEAEACHBBFFHFEGEFFAFAFGFEFAGADDFAFCFGHBFFEDBACABFHFCCCEEDFDCDAAHFHEHDDEDGHEFCAHFFBCGCGCACABAEAEHDHFHFHFCEDEDGAGAEEEEEFDAGGGHGHFHAGEBHBAEFCFBFCEHBHD,False +602,19.0,22.0,22.0,6.0,18.0,28.0,18.0,32.0,BEHEHCBFBFGAGFFFHEEGEFFGCHCHFABHHCCBFHFABBEBCACAEAFHFABHCHGBBAHEEEEAHAHBHECACAHEHEHCGBFFHFGAGCCBCBEFEGHDDGDHFHCDAHHHHDAFBFAFHFHGHGACCCACBHBGBGBCFGFHFHFGFGFAEBCGCBDEF,False +603,6.0,3.0,3.0,0.0,3.0,1.0,2.0,3.0,AAAAHHHEAEBFCEGAGCBCB,True +604,20.0,12.0,4.0,14.0,4.0,16.0,10.0,13.0,BHADGGGBAFFHAEDBAFGFCFHFHDHBHBGFFHADDEHFFBFGHAHAHABACADFFAAGADAGAGACADDEFEFDADAHBGBABDBDBDCHF,True +605,13.0,12.0,3.0,10.0,9.0,12.0,19.0,5.0,BFBFCDGDBDAGAFCHBBBDHGADCEAABAGFGFGEGEGDGFAFEGBGAGEFFGFGEDADBBGAGAGEFEBBHGHGEDDAFAH,True +606,25.0,22.0,15.0,23.0,20.0,14.0,29.0,17.0,ABABABGDEFEFEHBAAAFDDBDGDGAGEEBHFFCAHAGABACACHEGDGDFDHGGFFHFBEDECFGHCBAGDGCHBGBGCGFDADECEBEAEADAFEBEAEFCBCBCBHBABGBHAHAGAGDDEEEHBCEADGDGDHHFDGABDBDGGCGCADGGHHDHGGEGC,False +607,7.0,12.0,19.0,9.0,3.0,6.0,12.0,7.0,CHGGCADECECGBGCGCEHDAFACDBGGFABCBCBCBCBFBCGCBCBCBFHADACADHDCGGGDFCHGFCHDHDB,True +608,15.0,15.0,12.0,14.0,12.0,4.0,21.0,15.0,BGBEFEGDBCGCGHHEGCFAGEBFGHBCCEGAHACGBDBGBHAHGHGHEHEHACABADADAHACBGDAEHGHBDBDBEBAAAFCGCGDEDCDEDHDAGHGDGBGEGDC,False +609,11.0,19.0,6.0,5.0,9.0,14.0,11.0,10.0,BBBBGBFBFBABDHAHFBBAHEHFCAHGGDGDFCBCFCGAHBDBGBGFGHAHGBEEAFFFBFEFEACACEEGEAEDGFHAHBBBF,False +610,7.0,6.0,1.0,2.0,7.0,8.0,15.0,3.0,GGGGGDGFBAEAEBFHGHDFAGBEFEFGFGBHAGAGBCEAEGBGEGAFF,True +611,9.0,11.0,18.0,12.0,13.0,14.0,18.0,18.0,DABAEGBGEGEGEGFDHCGCHAHFHFCCCCHHGADFBGEHAHEHECFHEHEAGABDGEBCBFFFGDGBGACHHHDHCFCDCHHGDCHCBCDCGCBBDADGGGEDECBFFFFEF,False +612,1.0,6.0,5.0,8.0,3.0,4.0,3.0,4.0,BEBEBGBFBFDDCHBDFCHDGACHFHGDCDCDED,True +613,5.0,7.0,4.0,9.0,3.0,12.0,4.0,8.0,DEEHBFGFCHBHDHFAGDBDHDFCFEBHHHBFBABAGAGDFDCDFFFFCFDA,True +614,5.0,4.0,10.0,9.0,2.0,6.0,6.0,7.0,GCBCBCGGBFHHCFCHHDDDDCBGAEACACFDADCCAFHFHDHDEDGFG,False +615,20.0,20.0,21.0,19.0,32.0,21.0,14.0,26.0,FCCGGEHECEDEDBBECHCHCFGBEHECCCCCHCGCDCDEHAGCECEDDBEBABABEBEAAAAHAHEFAFHFEFBFBFAFGEEEAEHEBGHEHDBCBDAAEFFHCGFHHHGCEAGDBEHEFEGDFBFAHHDBCHFFBEGEGFHECEADADADBHFHAHDDFDFHEAEBDBDGH,False +616,4.0,1.0,4.0,5.0,3.0,3.0,4.0,3.0,AGAHCHBGDFDCHEDEDEFCFCDAGAG,False +617,14.0,17.0,16.0,17.0,18.0,16.0,11.0,15.0,EFEFHFABEBEGEAEBEAECBDHFEEGEGBGDHHHHHBHBHBHAFAHDBFHABDDFDHBGDECECEFEFGDABAFAFABDHFBFCGCGBEFCDCEADDDFACAHDCCGDDCBCGCFCABECGCD,False +618,29.0,30.0,26.0,14.0,18.0,25.0,13.0,17.0,HACCBHBFAFBFBFHFCBAAGAEBEFDDBDAAACACACEEDDAEFGBGFEFCABAGAGAGFGCHCAGFBBDFHAABFCFCFDHEHCFBFBHADBBBBHDDBCFABBEBFBADAEBCBHBHFHCBDDHCHGHCACAGAGDFCFEAEBECECECFCECECGHEBAFAEAGHBCF,False +619,31.0,22.0,24.0,19.0,30.0,25.0,19.0,29.0,CFHEHCGFFACEHBDEEGGACFCACAGAHAEAFDCGBACEFGAECCAGHBHBDBAEAGFBABAGACAHHHAHCHCDCDAGGGAHAEAEDGGCEHFHFHFDGBHBCEHEDEFEFEFEAADACHFBDBDBDBFBFAEHFHBHEHEGEDEDCCEBFBFCFCAHDBFEAEFEACAFADEBEHHDEGEAHBHCHDBGBCDHFGF,False +620,18.0,17.0,15.0,24.0,21.0,15.0,18.0,13.0,ECDGDBDGDGDEAEBEBCFGFGAGAGHCDEHEHBGGGFEAAFBBDFHCDCEEEEGAGAGEDFDHDHAFAFHEHDADADBDECACEDDBHFEGECADDCFHBCBCHCDDFDGBBBEAECEDEFABAHCHGDABFBFGFCBGA,False +621,0.0,2.0,1.0,1.0,4.0,1.0,0.0,1.0,FEEDEBEBHC,True +622,14.0,20.0,14.0,20.0,27.0,29.0,12.0,26.0,CDCACEHFHFHBHEFEDEBBFFFFBFECHHAHEHEDGDEEBFHFHAACEDECCCCEFEHAHBHDHFHFAFABEEEGEGEBDAHEEEEFHDDDGDEDABHBAFGFEHABFBABDBFFFHFCFHFBGCABBGBHFHFDDAHGFEFEDHCHDEBGGGBCDDDCGF,False +623,16.0,25.0,17.0,19.0,21.0,19.0,21.0,15.0,BFDFDFGBGDHBHEDCACFCEHEDEBCFDEDADBDACADDEGEGHAHBHFEBCCCAHEHEBEBAAAAGCFCFGFBEEEHBHEHGBDBDAGAEAGBDBGFEFGBCBCFGEGBGHDHGCCAADCDCBFBAGGFGEHDFBEBFBFDFCFHBGGGEB,False +624,23.0,27.0,21.0,27.0,12.0,19.0,33.0,26.0,DHAGAGFBFCCHHGGBCBFDFACGBGBGHCABACAHFHCDCDGFGFCFGFCAEGHGABABEDEDHFHFDFBGHGEGHAHBHCDAGAGAGBBAEAFGCACBFBDDHGHBHDGDGBGDAAAAEBBGBDBDCACFCHCBDBCCCBGFFHDHDHEGEDEHHDDDHBGBHDFFEBDDEEGGGGAGHCHDBAGD,False +625,17.0,22.0,27.0,7.0,24.0,19.0,26.0,18.0,GHECEGFGAGCBEEGBGHGBEBEAEFGFAFCFHGGGGEEECBFBDGGCGCEDGFBHBCBCBCAGABEGEAEABFFFBFBFHEGFGACAEFDBCBCAGAGAGFFCCBEHCCBCBDHCBEHCHCACEBFBCGDAHFCECEDACAEHHHHHDAFGHCHCEGEH,False +626,21.0,20.0,18.0,14.0,19.0,24.0,20.0,19.0,FGFGDBFGAAHHDABADDECCHFBGCEEHGHGHGAFHCHAHBCBFAFAFABBBABADDGEBBFCFCFCFCBCDCDHFAGGHGHGAGEHBFAFCHHEGEFBHDHAHAEDGAGAGEGCDEHECCCBBBAFFFEFDADBBEDEGCFBFCGAEEEEFEF,False +627,22.0,20.0,15.0,21.0,16.0,16.0,15.0,16.0,GBGEFDACFGFGHBHECCFAAAEEGBCHCBCFADHDHDBDBDFDADABAEDFBADACBCFCFEHGCEFEAEBHDHDFDEEBBHBGAGDGAEAEGGHAHDDDDFDGBBBAAAABDHGHFAFECCCECHBDBCBFEFGAGAHH,False +628,7.0,15.0,8.0,13.0,14.0,12.0,11.0,8.0,DEDBDHFHDCDCBBBCBDBFBFCGHGAGEFAFAEADBFBGBGHGDCFADBDFEFEDECEFHHCBEAGGGDEBECEABBGHGFDHEEFE,False +629,1.0,3.0,3.0,8.0,6.0,2.0,4.0,5.0,HEHDHDHDEFBGBGDDCDHBEDECGCEEFGAD,True +630,11.0,10.0,7.0,6.0,8.0,14.0,8.0,5.0,CAHAHABFCFCACFCAHAGDBCEGHFHEBDFAGAGABBBEBCFEFEFBFAFBDEDEGGDFDABFFEFGG,False +631,14.0,11.0,20.0,21.0,13.0,15.0,14.0,16.0,HCFAAHBFCFAFHFGDHFCFBBBEBEAEAEHEHGDDBHHHFHDCDEGECFHFDFDADACADHGEDADHDHDCDCGADDECEAGBBCECDGGCGCABAHFGCDCGFBHBDCDGAGCCCDCGEFEF,False +632,4.0,8.0,5.0,12.0,1.0,8.0,6.0,3.0,CAHAEDBCCFGDBDFFBFBHDDDDDADCGBGBCFAGDGFGFHDBDBF,True +633,3.0,4.0,7.0,2.0,2.0,6.0,5.0,5.0,CBCECACAFEFDAHBCGFGFBHCHDHCHGGFBFG,True +634,15.0,14.0,8.0,23.0,21.0,16.0,17.0,8.0,GDDDADADACBFGFGFAFACADAEEBEBFCGBFHFHGEDDDFCGABCBDHDHEEFHAHGEFDFEFBFAGAFEGDGDGBGDEDEBHBDCEEEEGEBCDDEAECDDDEGGGAFAEBFBGHEDAB,False +635,16.0,23.0,27.0,12.0,33.0,22.0,20.0,34.0,HEHACECAHFBGBEBHHHHFFCECEHEAEGDGDHAHBFFFFFFFGABCEFEBECECHABGCGFHEEEEEEGBCAHEHCHDFBGBCBCBHHGFBHDHCHEHEHCFCGCGEFHHHCDGDEDECBCAFEFAGHDCABHDAEACCHGHFBBHDEAGBGAFDDGCACEFEFEHEHEBEGCCEGBGBCAHBHB,False +636,18.0,21.0,19.0,22.0,14.0,15.0,21.0,26.0,GHABCDDDAGGFFEFDFHBACHDHDECGBFBFAAGECECDAFBHCDCEBGBAAAGHHEHEHEHEBAFDFCACECECEHHHCHDHAHAHCDBDGGGDHDBCCFCGHHHGDDDBEBFCFDGAFBFBDBDBGBGBABHHCHGHGDBEGAAHDCGAGBGF,False +637,7.0,11.0,15.0,9.0,7.0,9.0,10.0,13.0,DAFBFHGDGAGCDCDGHBCECFCGCDEDHDHBHBFBEGEHDADBBBBGFHHAECHGHGHBFCFAACCCFFHGACHCBCECE,False +638,23.0,18.0,27.0,21.0,18.0,14.0,17.0,30.0,DEDCHCBFEAEAEABAHGDGDADEBEHCFDGGCCCCDCBFGFCCHDHDHFBABDHEHAHFHCAFAEADHDHCHEDACCGCGCGCBAFHHHECDDDBGHHHCHBHAHECFBBGBDBFHAHGHCDGHGCGCBBBGBABFGCGAEEDFDAEHFHDHEEACAEFEACHCAAA,False +639,8.0,5.0,5.0,6.0,7.0,4.0,6.0,5.0,FGEBDBDBGHGDGCAHAHCDAGAFAFBEBEGEFDCHAEECEDACAH,False +640,25.0,30.0,19.0,18.0,18.0,25.0,21.0,28.0,DBGBFBFHFHCAFAFACGCHCHEHEGFGADHHFEAEGEGHGEAEBDADHBABDGGGGHBHDDGAEBDFCGCFFGACDHBHFHCHFAGHEDACAHBDDDAHHEBEBABACAGBDEDGHBHFHFCGCDFBFBFAHGCBDDCBAEAEFCABABACACEFHFBAEHEGBGBHBFFHBEBFBFBFHCBC,False +641,10.0,7.0,19.0,15.0,18.0,26.0,16.0,17.0,EBEBEADCFGFGAADCEFHCAEDEAEFBHEHDGDGDBHCGCFHFHCHFEFGFGCECFCGCEDAFEGDFCAEADCFEFHHHFDFGFGAGDGDFHHGACFBHDHCGFGFCHCHCHCDEECFFFFEBEBFD,False +642,17.0,19.0,31.0,20.0,20.0,27.0,31.0,22.0,EFGFHEBFAHAHFHGCFCFGFHFBFDHDAGAGBECCHCBGBFEABDEGEGFCBDDFEFADADBFEGEBBAEHEHAHAFGCGCGCBCBFGFCACHCECGCBCAGFHDBDCAFGCGCGCGCDDDCDGDGFBHGFFAHCFCFHECDGDBECCCDCEGEFBFEHHGAGCGDHAHGHEFDHAGBGBGHDECE,False +643,10.0,16.0,8.0,13.0,16.0,18.0,19.0,19.0,DBDFCEGABABHBFGAHEGFFDHCFCFBDHHACAFECHHHHGFGBEHEGEGEGFGBBDBFEFHFCEDECFAAGFGFEBAGHEHEHEGDBDFDFBEBDBDFDBGEHCAAGHGHGBGHGHD,False +644,23.0,23.0,24.0,17.0,10.0,17.0,18.0,14.0,BGGGGGEGBACCECHCHCACDBAEFEFHAHACFGGADDCDCDCDGHGCBHBAAFGFGFABBBBFBHGFAAADADCDEACDEACBHEEFCCHCHAFBCHGEGBFDFHEBBHBDBCHDBDBGFCFBDCGFGFACABBBAAAAAFDCDC,False +645,19.0,20.0,19.0,12.0,21.0,19.0,19.0,26.0,BCHEHEABABAHAHDHBEDEAEGECEBECAHDGCFEFCHHAHDHDHFBDACABGCEBHBCFHGCCCAEEDAACABBHGHGHFHBEBHDECEBDBCBFEFHHHGHGHGHFHFBDGEGACEFDFHFEFCGGGAEFDFGCGABFFCFCGBGAGFBAEA,False +646,24.0,19.0,25.0,16.0,26.0,22.0,27.0,28.0,DADGFHCDDBDHDHGGAEECHHHFCAGACFCFEDCCECEGFBFBCBGEHEACBCBGGHGAGFHCGCGEFEDAHAHFHEBBBHHAAEAECBGAAFBGBHBHAAFEEAECEGHGFCDCHHHHBDFGFGFGBEAFHFDAHAHCBCEHGHGFCDGDGCGEFABDBFBAAAHADEDEGCGHECEFEFECECG,False +647,19.0,19.0,11.0,23.0,12.0,13.0,15.0,22.0,FGFAADEGEAEADGDFHAHBHDGGGHDFBHBDDGDCDHBHBHEHECEDBDBEBHHDHEABCCGFAHGGEADAGFDAHEHDHDCDGDHHEHFFFGEGBDCACACDFDHBBBBDCGAAFAHABABACACFDFBBHB,False +648,14.0,18.0,21.0,17.0,4.0,13.0,14.0,14.0,HDCCBGAGBGFGFHCCACHCGCBCBEDEBCBDBHFCFCFGAGACBGFDFBHBADAGHCHBHFCACDFDBABAEGCHHDBDCFBECGCGBDAFFGHDBDBDADADACFDADCHHGH,False +649,18.0,10.0,20.0,21.0,15.0,23.0,20.0,19.0,CDCFFDAABAFGFDBHFHGADADAHGHGBDFCHHHCDCHAHADCDGDGDGCEFGFCECFCFCGCAAAAEAEDBDBFFHHHFECECGGEGAABHECFHDEDGHGAEADFFHGDGDGEEBDCFGEHFCGCECEDDFFFFBFBCBHHAG,False +650,2.0,8.0,12.0,4.0,7.0,2.0,3.0,2.0,BECADGCCCCCBCBCBDGGFECECDBDBHECEFABHBCEE,True +651,23.0,17.0,14.0,13.0,18.0,7.0,9.0,12.0,HGFCACACFCDEEAGBGBADADABCGDAEADGDBACFHBEDAABHBHGHCAAEBECECACEDECEGFGAAHABAEAHDHABABADEBCFCFBEEEHEBFBAEHEHDCDBGBHD,False +652,9.0,5.0,7.0,3.0,3.0,4.0,7.0,7.0,FHAHAGGGGHGCGCEHEAFAFCHDECHBABCFGBHBACDCDAABA,False +653,17.0,14.0,10.0,12.0,16.0,15.0,12.0,13.0,FFDCCCGHBHEFBAEAHDFFFHBBBBGAFABABAEADAEFCBDEEHFDACHCHDAFCFEDGBCBCBEBEGGGCHHDDAGAEAEDEDEBEHDHAHEFGFGFGHGAAEAFG,False +654,18.0,23.0,28.0,27.0,18.0,13.0,30.0,25.0,CGCBCACGBGHACACADFEBGBCAEHBDBCHAEDGDFDCCAEHDGDFDFAFBGBGEDCFBFBFDAHGCCCBGBHEHAHGGGCECEHEAGCGDGDHBBDGCECHAHDFDGEGAGDGEADHCACBGBCHAHAGBGHHCHCHGEBEAEDECHBGBGDGFGEGHCHBDDDCDHDFDHCFEHDBDBF,False +655,15.0,11.0,8.0,7.0,7.0,6.0,7.0,13.0,EFAFACBEEDCAHAHGEAEFFHBHBFBFHGAAHGHGAGDCBHHHABDBEBAGAGDDDADHBCBEACHCACACHB,False +656,23.0,17.0,14.0,15.0,23.0,23.0,21.0,14.0,DBBBEEGCGFABAGAHAHFDEEHECBHBFBEAEADGDACGFGFCFDFGFGFGBEBEDEHHCFEHAHAFAHEBABEDEFGFGBGAAECFCHCEAGDGDCBCAFHFDFDFCFEEEEECFDBGGGAAADBGBHDAGEEBHDAAAHFGCGFAFC,False +657,22.0,13.0,20.0,11.0,19.0,20.0,13.0,19.0,AAAEEECFGGCCCDBDAFHFAFCCBAAHBBBEBFBAGCGEGHCAEACDCEADBDEAFCDGECEGGAGABAHAEBHHHHHCFCFEHCHFHGHCHCFAFDFDFDHBEGEFFFFAEAECEDEDHFGABFEGCHCHAHABF,False +658,13.0,8.0,9.0,8.0,6.0,14.0,16.0,11.0,DFDAACADGHGFECCGBFFFHEAAFACAGFHCGCFAFDFBBHHFGAGABABAGEFEFGDEBFBDBGACHCHCHGDGHGHGEGDGH,False +659,24.0,22.0,11.0,20.0,12.0,19.0,20.0,10.0,ECECBBAAAFHDHDHCBGFGFACABAGGHADBEAFFDFDFDEGCGCBBBFAGABBEDGGAGFDAGHGDDAEABBGBHDGEBFBHDFGCBCBEBFDFDADADBBFEHEFEFDFHFEGDCDCDCGBGAAAAAGAFAHBGA,False +660,9.0,8.0,11.0,8.0,16.0,14.0,26.0,11.0,FEGEHCHBGBGEGHGHGEGHDEBHAFACGDGFGACHHGAFCGGFEHDFDEEGBGBGFGFGCCECFAFDFDHBGDAAHAGEGDGEGFGAGEBCCCCBEEGEFEF,False +661,21.0,16.0,26.0,12.0,16.0,24.0,13.0,16.0,AHBFGAHHBCBABABCCGBEFACECGHGFDAHHCCECFFFDFAHACACBCBGBDFEFEHEDACAEDEDEGEGDGBBBGCGAHACACEFAFDFAFBDACAFFHFCFCAGEGBFDFBFEGCFCBCFHACADDCHFHFCECEHHHCE,False +662,19.0,21.0,19.0,34.0,20.0,23.0,22.0,19.0,AFAFBGBGBABGDDADCFCECGGEAEACHDHDEFCFDFDECHHGDEDEGGFEBBBBBEFEDDFAHCBEDDBACDCDAHAHGHDCFCFDFEFEDHCHDDADBGCABDHEBBFBDCDHDEDEABDHEBFBCEAGGHFHEAGFGFGCGDGFGDGAGAGABFBFDDHDCDHHGHECDCFAF,False +663,30.0,32.0,21.0,26.0,25.0,15.0,23.0,18.0,GBDHGHGHGBGFGABAEEDBCBCAHAEEDFDADEGCCCGHDBBBEDHGGFCBBHEAACDBGAGBGFEAAAAAABADGGBGCDCFCFDFCBHAHBBBHBHGDBDEHBHBHBEAABABDDEAEDFDEBEBECEGEFAFCFCADEGCGBABABFBCEADAEGEGDCDGBFHAEAEFCDDHEHAHFDCDEDCAC,False +664,14.0,12.0,16.0,18.0,20.0,25.0,19.0,23.0,GFFDFGFDEAHBCEEHCFEEEABFGFGHGAGAGCGCFDBDBDEDEABABDBHFCFHDGAGEHEHEGDCDCFAAGAEEHFGFEDCHFHGGEHDDGBADDGHFHEHEHECFCFCDCAEFFFGFGCBHHCCFCFBFHFHEDADHHHHABB,False +665,1.0,1.0,5.0,0.0,2.0,0.0,2.0,0.0,CCCBGGAECEC,True +666,13.0,18.0,8.0,9.0,12.0,13.0,18.0,15.0,FADABCFAFAFGFGFBCBGGGFGDCDCABDHDAEHEDGDGEFFHCGEHHFHBGAGAHEGEGABFCGBGEEBEHFHBHBHBHBFBHCABBHGEEDCDBABABHGGAE,False +667,12.0,9.0,6.0,10.0,3.0,13.0,8.0,9.0,CBCHGHFADHGAGBCFDFAADDFCFHDAAAAAFCFEAAFADCDGDGHFHFHGBFBFBEBHGHGBBDFDEB,False +668,25.0,23.0,24.0,17.0,11.0,21.0,16.0,12.0,GDAFFFFHBBGCACGCECBHAEDBBFFFBCBCACACGBABEBEDDBFAHBHDAGAGBGBGAGBGAGEDBAFCCDCGAGHCDADACAEDFHACBEAACFDDBDBHBDBDFFFCFCFCFCAAAEDHFAFHCHCACHCGAGFFCEEBEBGDH,False +669,3.0,6.0,1.0,5.0,4.0,4.0,3.0,1.0,EABGBEBGBFBGDFDFDADEDBFHEAC,True +670,5.0,9.0,11.0,15.0,8.0,21.0,12.0,11.0,DFDCHCFFDHHAHACGGFBDBDCDCDAHEFFFHBDBDBEECFGDGHGBFCDADABHBHGGEGCCFFFFFDFHEBGCEFDFGFEFEHDGFGFC,False +671,9.0,14.0,11.0,13.0,12.0,14.0,11.0,23.0,HDHCHCFCFCHCFCDADADEHFHBAEGFGHCEDHFCCDEHAHFEBBBADCHHHHDHBHEDDDADHDBGBGBCBFHEBEFGBGHGFFHAHGHBAFAGBEFEBEHEGFG,False +672,3.0,4.0,0.0,0.0,2.0,6.0,4.0,2.0,HFHFAAGEGFGFABBFGFBEB,True +673,17.0,21.0,20.0,5.0,12.0,13.0,17.0,15.0,BCBDBECHCAAADCGGGGFBABABEBCBCACAGHBHDHBFEEEEAABCBCBAAHBGGCGBGHGFGAGFFCHGHGHBABFBFHCHADDFCCCECECHHEAFBFBCHHBCEGGCFAEAEGFF,False +674,14.0,34.0,17.0,24.0,19.0,23.0,30.0,24.0,BBGEGHHHEHEFABDCHCFBDAGBBBBDBFCFCFAHHEHAFGHGEGEDBDBDHCFCHCEDEDEDGCGCDDDGDGAGAGEGBHHCHADFDBBBCDDACGHGEGEHBGBGHFEFGFBBDBHBFBDGGCGCDFGCBBBDADGHFCFADGEHFCFAFGBHFHBGEAEBBBAFGGDGFEFBBHEHEBABF,False +675,22.0,22.0,20.0,24.0,22.0,17.0,36.0,34.0,CHGHGHAHAHCECDBGCADHEEGECDGBFCCHCHFGFGBBHFHFHEGFGAGCGCGDGDCBFBFEFEHEDECCHBGBDADHFHEBDBGFGBAHGHGEACGGAEAHGBDCDGDHFHBHCECBDHGGGGHBBDFDFHAAAAAHADADHGHEHAGFGDGAEDGDEEBHACFGHBHBHCGGGCAHEEAEHEFDDDGDBBBAE,False +676,5.0,3.0,7.0,7.0,6.0,1.0,5.0,6.0,EHCHEBAGEGDGDCCCCABHEGBAEDEDCDFDADAHHCHG,False +677,14.0,12.0,18.0,20.0,14.0,12.0,11.0,15.0,CCADHGFACAHGHDDDDDGFGHBADGBEBCCDDDADADABBHCFCFHBHGAGEEEEEEEGEFHCDFAFCCADBDCDCDCBBBBCHCBDAGAEHDHAHAEEHEHFFCGCDFGECFFH,False +678,20.0,18.0,16.0,16.0,18.0,22.0,18.0,25.0,DFFHFHFGFBADAGHCBCAGBCBFGFACBEFEGABBBEGHHFHFDFHEEGEBECFCEBEGGADEDEAEACHCHABEHAHAFAHAHAFBFAECECHCHGHAHBHCHFHGDCHGHEBDBDGCADEDGGFBFGDBDCFFEHDFDFDGDHCHBGAAA,False +679,13.0,13.0,11.0,11.0,12.0,13.0,13.0,10.0,DADAHACGEBDGEGEDEAACHFGEGEGFGFCFAFEBCBFEFHCCFCHCHEHAFFDBBBHGCEBGBGAAHFHGHBFDEGAGBBBBDDADADEDACFC,False +680,21.0,9.0,11.0,23.0,10.0,11.0,13.0,22.0,BHEFDAEAEGGAGBCHCBAAHAFDFGGGGBHADEDACFCFAEABHBHBAAADFFACDDDHDHCBCFHDHCHGDAHAHDDDCDADEHFFAFDEHHDHECDADAGAGBHHGHEHEHCDGDGD,False +681,29.0,26.0,19.0,24.0,29.0,20.0,27.0,23.0,AAHAECBCBAADACAFFGCEADCBGHGFEFEAEDEDBDHDEBHDHAACAHAEBCBDFFHFBFBFBFGFBEAHBCAEAGAGBEEEEEEEEDCABFGFBDHFAFAGBGHGCGEGDADHDFGBCBHBHACEBDADEDEDGGGGGGGBHBHDHCFGBBEHCCAHHFABDCGGECFBAHGDGDCEAEHECEGHDFDEDGAHA,False +682,12.0,18.0,15.0,23.0,25.0,24.0,20.0,8.0,DADHGFBFDADAEECECBFDHDBCBABAHFFFFEFEFBFBFBEDFDEAFCCHEBBGECCCCFAGBBDBGCEEDHGGEGEAEAEFDDDGDAFEGCGCGCFEDDGDFHEDGGGGGEBEDFDEDHBEBDCCEFFFEFEBABFGAGHGD,False +683,10.0,19.0,7.0,19.0,5.0,6.0,8.0,11.0,CHCGBDFEGADBBBBBEGHAFAHBGFACAGAHDBDBDADHDGDBDCCCEDDHDADADCDBBBHBFBDBDFDADEHHHBHGGEFBB,True +684,10.0,3.0,3.0,5.0,2.0,4.0,6.0,12.0,DBCHHBHEDEGAGAHFGGHFAAAGAGADBCHAHAFDFDACHHHHH,True +685,10.0,19.0,16.0,24.0,9.0,16.0,18.0,17.0,DGDFEBDHDADCDBDHFHFHAGCHCHAGEEBGBGBAFDHCBADCDHAHEEABDDFDFABBCDDADCDFDFBBGBGHECCGCGDECGDBFGGEGECHCGFFBFBDGFHBHBHBCGCGCGBDDDFHFHFHA,False +686,11.0,7.0,14.0,17.0,14.0,20.0,12.0,14.0,HDHABCEFFBEHCGCACACBHBGEGEFFFBGCECDCDEHEDEGFGFDDDDGDGAHDHDADADFFFAHAEDHFBADEDBCCGHAEEECFFEFCFHFGCGAHDFGFHFCFH,False +687,19.0,24.0,19.0,21.0,13.0,20.0,17.0,22.0,GBGCDCDHFCAHAHBFFDCAGBFBABCFFBFACBGHGHBFFGHDDADHFHFHBGGHGAFDFCGAGEDEGEADDFCBABFBABAHEDEGFGFCBCFDDADACECEBEBCHCACFEGCHBBBDDDGHHDHAHAFABDHEHEHEGEDBABCBDBHCHC,False +688,11.0,6.0,12.0,7.0,7.0,10.0,7.0,5.0,CCBGGGGFABECFADHEACFCFGFGEDFCFAFBHBCBHBDCCHCAAAAAEDDDDAFCFCEGEAEH,False +689,1.0,5.0,2.0,2.0,0.0,1.0,2.0,2.0,DHDGFGCBBBBBCHA,True +690,15.0,19.0,20.0,21.0,26.0,23.0,15.0,18.0,GBGBGEFEGECEDHDHDHDHDCGAEACGCFBFECCACGCDEDFDHDFBBBEBDHGHDCBAAAFBHADFBFHFHFHFEDDADEDEFCBBAEEGEACCHCEGACEDECECFFFFHAHEGEBABEDFBHEDEAEADFDCHFHFCGEBHCFFFGBBECGBG,False +691,16.0,20.0,16.0,13.0,21.0,17.0,19.0,17.0,EEBEDECEAEBBBBEHFBFBFDCDCBCBCAFGHGCECGGDHAHCDCFCEHDHDBBFHFGEECBGBFHDHGHEBEBEAEFBAAAAEAGGGFEFCFBABDFGFDFHAEEGHHHGDFHFGCGCGDAAACADEGBBCAHGEGH,False +692,15.0,18.0,25.0,15.0,20.0,16.0,23.0,15.0,DCAGACABGEGHGBBCAEGHHDAAAFGCBCBCGGDGCGCHCDCDAFCFGHGCGCEEEHBGGECACADEDFDFGFDBBFBCDCFCDCEEHEHFDBDBGEGFFBFBFEECHGHBAGABABEHEHGCEHBFDCCGDHEHEGBFAFAECEC,False +693,18.0,15.0,17.0,18.0,19.0,18.0,17.0,13.0,DAEAFACADHDHCFCBBBDFDEGEGEFDGBEFEBGHGHEHGGAFAFAGAEDEBHDADAEAEDEAHGHAHCECEHFHBGFAEAFBCGFDFGCACADFCGCBCBDAHFBCDEBCFCFGECDBDBGBGECECFDDHFG,False +694,7.0,11.0,9.0,10.0,9.0,4.0,5.0,10.0,CDDDBBCGFGDHDHEHBHEHEBEBEAEAFHDEGEDHBAAFHCBFEGCBCBCBAAHACCCGBHDDD,False +695,9.0,7.0,7.0,14.0,15.0,8.0,16.0,16.0,DFDCDCDEAHDDDBHHFHFCDCHCFBAEEDGAEAGGFGHAEECHGHGHEEGDGFEFEDEGBGEDDBHBHGEGFAHAEAHAHGBGHGHGDECB,False +696,24.0,23.0,24.0,22.0,20.0,19.0,26.0,26.0,ADGDAEBHCGCHCEADABGBGBFEEGFAFAFBFGDGDHHACDCHFACHCGGHGHDHCBGDHBACHBHGHGAAEBFAHGGDGHGFGDCDCGCDCAEGGGEEEEEHDFDAAAHADAFADEBBBHEHECACBEEEBABFCFCFCECFCHBHBAGABHHFHBHFCDEBCDGDFDFDCBFBCBEAGDGH,False +697,19.0,24.0,22.0,23.0,29.0,24.0,25.0,34.0,FCFEAEAHCGEDABFEFDHCHCGCGCFHABDGEGFGFGBHBCAEEHGBCBCBCGHDHFHABGHDHCCCAADDFDHDCDHFBEHEHEGFBBHHHADEEEBEBFACHHHHGHGABBBBEDCBBBEDEDFFFFFFHCHDAEFEGDGHFBDGEHHGFBDADECEDEDGFBFEGCGHHCHCHGHEFEAAGAGEGDGCAHAEAEBD,False +698,13.0,19.0,14.0,18.0,18.0,16.0,11.0,16.0,BDBFFDFDFGGHAHBHBHBHFGAGAHDHBEBDBHBFBFHCBEGEGEDCCCCBGHECDCACDBFCEDBDFDFDHDFEFHFHEHEFEBABDEHBCDDHAAADEBAGAEACGEAEFBCEGEDFCCAGE,False +699,20.0,17.0,18.0,13.0,20.0,22.0,16.0,23.0,ADHHHHFDFBFAGADBEFFFEFEGCFBDHCAEABAEAEBHFECCFDFHHHHHFHCHCHEHEAEBGHACABFCFGAGDFDFCBHGCFCBCHDEDHGHAFDFAGECECEFAGCDEGEHEAABCBGBGBGBABGEAHGEAFHFGCECADBDB,False +700,7.0,10.0,13.0,7.0,8.0,14.0,8.0,3.0,FAAEFBFCFBFBEDGHCCCCCEDEDFHECDBDGFGFADGBEFCFCGAAAHEDECACFBFBGGGFCFCBBB,False +701,16.0,27.0,21.0,29.0,23.0,22.0,14.0,18.0,ABAEADACBDBFAFDCGBDEDBBFBFADHHAABHDGABACDBDEAFCHCECHDDACAFDFDFEAEDHDFBFBFCEEBECDCDHABFBGEGFHFHGBDEDEDEDCDHDHFAGDGHGHGHBCBCBFHCEBEHCCDCBFBFBECFDGGGFCECEDHBGBCFEEDGBFBEHEDE,False +702,22.0,31.0,14.0,20.0,15.0,20.0,18.0,12.0,GHADBDAFCHAEBDBDBDFDEAAABADEDCAABBEGEGFGEGFDFBFBAEGBBCBCBEGDCDAHCHBADADGFBFBHBGBDCFGDGHCDCFCBEAGFGFHFEBECAFBFBHBHBFBEGEGEBEDAHABADABBGBCAAGDFBAGHCCFDFHF,False +703,21.0,26.0,13.0,16.0,14.0,14.0,14.0,17.0,CHABCBFGFAABAGAHAHAHACBDFHAHEHGCACDBEHDGBHCECEHFAACABHBABABECGBGAGEFCGDEFHBBFAFHFHAHEBEFEGBGBEBEDDDDDDDAHHCBCDDGEADABGBDBFGFBFBFBGEDCBB,False +704,1.0,0.0,1.0,1.0,3.0,1.0,3.0,0.0,DEECEGFGAG,True +705,7.0,6.0,9.0,6.0,4.0,3.0,8.0,5.0,AGABCBCEHFACGFHHCHEACADDDDGBGBGBCEFHBDEDACGCGCGA,False +706,6.0,5.0,9.0,7.0,4.0,10.0,8.0,4.0,BGHGEDCHCHCGCFFGDGDGCBCBAADFFAFEFGAGADFHBAFCBCEDEFCFD,False +707,10.0,10.0,4.0,9.0,12.0,8.0,9.0,7.0,EECFAEAHAHAEAEBEHFDFDAGCDHBHGGEGEGFDFDEBADDCHFDDBFGEGBGBEBEAHAGBFBABC,False +708,11.0,14.0,22.0,17.0,26.0,26.0,22.0,25.0,ADBFFHCHCHCDGFCFBHBHBAGACHDFEFHCBGECDDGEHEHDHEGEGEGECBHAECDHDCDEEFHFDFDABHGDEHEGDHDGFCCCHCHDHDHBAEEGEHEHGGGBBFEFEDEFHFCFAEHECGCAFFFCFBBCAFBCHEEGEGFFECGCGFGFGFAFAGB,False +709,20.0,25.0,16.0,17.0,13.0,14.0,18.0,22.0,CDEHBHBHAHBHBGDGEGBACAHAHGBGBGBAAAGFDEEBGBABABFGACACHGHDFDADHEFDHHECFDACABGHFHDDDAEAEDGDCDCFCBCFHBCBEBEBEBFCGCHFEGGDDBBBCEHGDACABGHGAFHHHBFAFCFHB,False +710,30.0,23.0,16.0,22.0,21.0,35.0,15.0,23.0,FAFAFAFEFEHAHAEBEFDFDBDHFCEAHHHHBEFDADHEHBCCCADEHFHFHFCGGDECGCBDBGAFAFBCDAHADBECEFHCBCBAAAFAGBFADDFDFHBGAAEABFDEDFHAGAHAGAGEGHFEFCABAFCBEBEBHFDDDFDADEEEFBFDACEGFBDBHBHBFGFBFCFGGHAHAFGFC,False +711,6.0,6.0,12.0,7.0,12.0,9.0,12.0,10.0,HGEDHDGCGCGBHBHGCFAGABCBGGEBCHCHFGDEEEHEHAHFHCGDFEFAFAFDECECDCFABCGEGFCEDE,False +712,23.0,31.0,32.0,27.0,25.0,14.0,31.0,14.0,CGABCFCEHDFDHEHBDBDECCFBDGHGAGBGCHCBAEHEHDFDBDCEFGCGCFBAGGGEFEABFBGEAAAAHAGACACECACBGDGDBHBCFGHGBCAAAFBDDDDDDFGFCECBBEEGDADCBEAEAFDGEGCCBCBCBDGCECGCGCGCECECBFBDBABDBDHDCEHEBECGAABDBGGGDEEGEBBAHGGDH,False +713,4.0,5.0,5.0,9.0,4.0,5.0,6.0,6.0,BEFEACAHDHDHGHBDCHCDEDFDGDBEFGDGDFAFBBGACHCG,False +714,18.0,19.0,22.0,14.0,25.0,27.0,18.0,19.0,GEHFCECFCAEFBFAHBCCEBFFEFECDADEDEAEFEBECECGHGAAADAGHBFGFAFHDEABBDGDEHEFEFDBCHEGCCEFBFEHHHHGHGCAFAFHFHFGEHEHCGDFEAEAGFFBADAFFCFABGBABFBCBGBGCDCDHFHCECECDHDBGBCBCGG,False +715,17.0,8.0,11.0,12.0,13.0,12.0,12.0,14.0,BAGDHBHDHABAEGHFDADFECDCGCGADHDHDHABCBHGAAFBFBEHEAFCFAGHEBCDFDFDCHCHCADAEHEGEAEGCGCFEHAGGFAFEFEAEAG,False +716,16.0,17.0,24.0,24.0,21.0,17.0,16.0,24.0,FCBCBHBCBCECDCDAFFHHHCHDBEFABAEDEDEDECFDGGGAEFEFEHCADAFACEEECFCGAEDEDGHGDGAGFBHDHFHCCGEGBDHGEBHHHEHACAEGFDFDHCECBADECHHHBBBFBFBDADCCFCDCBCDEDHHCGDDAAAHBHGHGDGF,False +717,30.0,23.0,30.0,24.0,12.0,21.0,21.0,16.0,ECEDACAHEHCACECDCGCBHAGDFACBCBAFGFGBACCCCACFGEGFHHAHABGBEFFBFDFCGABCDCBBBBBAADADGDFDFHFDCDCHFBFAAGAGAGAGFCCCHABGDGDBDCDEBHDCDCDBGFFHHGBEAAHAHDFDEDAHAGDCDBHAFGGGBABDFCACACBCFEEAE,False +718,8.0,9.0,11.0,13.0,10.0,18.0,7.0,15.0,BHBGDHDHDEAEFFAGAGABHFFFADHDHDGAFCDCAHBDECFAHDHCCBGHFCECEHEFDBDCDGEGDBHBECFCFCFHBEFFFFFHFHE,False +719,12.0,23.0,32.0,23.0,25.0,25.0,24.0,32.0,ACHDECHBHFHGHGHDADAGHCCEBEBCCGHFFGFCBEGCCDDDBGFDHDHDHGFGBCFCGCDCDCDCFGEDBDBEGGCFEFEHEBEHECBFDCDGBGEGBGEGCFEEECGFGADCFEAEADBBCECEHEBEDFHFCFCAABGHHHHHFAFABCCHCFCAHEHFBFBFHCGFBDGDEBHBHCECGDBAFHHHHHDH,False +720,9.0,6.0,1.0,2.0,6.0,3.0,3.0,2.0,AAABABDBGEHAGABCBGFHEAEDEAEFEFBA,True +721,4.0,4.0,5.0,4.0,1.0,4.0,3.0,0.0,BGBCACGCDDFDFABACECBFAFDG,True +722,16.0,8.0,13.0,19.0,18.0,17.0,9.0,17.0,DFEFCHCGADHDEDAHEDEBFHFEFEAEDEDHAHADCBAFACAHEHDCGCGCDCDHDFECEBEDEDEFGGABFBFGCACFDFAFBDGFHCADHEHEGDAEAHHHBHFHFADCFEBGA,False +723,20.0,21.0,15.0,7.0,15.0,20.0,22.0,15.0,AFCDCFCFGFGAGBCACBHAAFGFBBEEAEGHDEDBHBHEHBCGEGFACEGHGHGCGEGECAFFGEGEGEGBBFAFDCBCFCFADADBHEAEHGBGHGBAFAHCBADFBHBCBFAFHBABABAFABHFGFGEHCG,False +724,22.0,23.0,14.0,13.0,20.0,26.0,11.0,21.0,DEBABADADEGBGBEBHBCCAAEAFFDAAAAFEFAFGFCFCBHBCFFFCFBFDFEHHDHCHCFDEDHBHBGAACEFAHHFABAEEEEGBCHCECACGDHAFDFHFHFEFHAGGGFCHBBDBHBEBFBFHHEHBBBABEEFGFEDGDAHAE,False +725,21.0,25.0,25.0,29.0,21.0,32.0,25.0,20.0,FGGGCGEGDFAHHHCCCGAEABFBEBDBDHDCDEDAFGDGAEFCFCEAEADABCBGGGGGCDCDCFFFEHACBCBCGCFCFDBDFCFAHBDDFDFBEHEADCDFHEHFFEGGDGFHEGEBBBDHEAEAGAGAHBHAAGAHAHDDCBCFFFHFEDGDHDBFBEAHBFBEDFCHGFGDCFEGCHCFBFDEDFDABBFBCB,False +726,16.0,20.0,16.0,17.0,10.0,18.0,13.0,17.0,BBBBGCACACBFBABFBCDHGBCHCBADABFCFCFGAHEGBGEEEFDGDFAGAGCBCEFHFHGHFHAHFDFCHAHAGEBDBDGDCDCHFHBDDADCBFADEEEHHDGFGFHADEDHFHCBCBABADF,False +727,10.0,29.0,22.0,26.0,22.0,17.0,21.0,19.0,BCBCBCBDAFHFCECDCDCBHECFCGAGDGBHFDGDGBGBEDEDEDBCBAFAGHBHDHAADBDCGFGHDBDEGEFBBBCBEBEHECDHEGDADCDHDBBGCEHFGCAEAEBEBFBHADCECFCFEDGHGHBHFHGHBCFGBCEFDHGBGFGEBEHEFFDDBDECGD,False +728,11.0,13.0,13.0,11.0,13.0,20.0,15.0,18.0,EFFFEBCDCHCAAAADFHFHGAFDFHFCFBEBGCGAFBCACAHAHEDBBGEDEDCDGBGFGFGCHCFFDHEBBCGGGGGDFHAHDHBFFCHHDHEHEFBHBHECAGEGEFEFBH,False +729,26.0,25.0,13.0,24.0,26.0,16.0,21.0,19.0,DBDFABGGFGHEHAAAAABFBFBGBDBABAGEGCGFEEGEBEDHAEDCHABCDEFAFAGDHHAHADAFAFGBGAGHBDGCHHHBFFEAEDBDBEHDBBEDDHDHDCBCBEHCACDHFCGAGEGDDBEBEBEAGAEADABAFFFFEHGCGCEEEEBEGDHDGECEABHDCD,False +730,16.0,17.0,13.0,13.0,6.0,15.0,8.0,16.0,CCHDADACCDBABEBHDFBEAGBGFCECHBAAEAEDEGCHCHAFBHGHDBDADAFBDBGBHCHCAGAGHHCDCFFDFBFBADFBFBFHAAADBFCFGFBFHHHH,False +731,16.0,23.0,24.0,23.0,24.0,17.0,32.0,25.0,FFFFFFFDDEDGGHGHGHGFDHBCACGEGEBEBECFFBFBDECCDEHCFGEACHDHDHCFDHEGABHEGBGEAEHBAGCGHGHEEEDEDHFCGDGBAHAGAGDGBACCEAGAGAGAHFBCHCGCDCHCHBDBGBEBGCDFDBCBHEHEHGCGHBCBCGCAADDDGHGBDEDEGBBDFEAEGBCH,False +732,2.0,3.0,2.0,0.0,1.0,3.0,2.0,1.0,FCFGFHCBGBAEAB,True +733,6.0,2.0,3.0,2.0,1.0,4.0,1.0,4.0,BFFCHCHCHAAFADBGFDAHAEA,True +734,5.0,4.0,6.0,8.0,4.0,8.0,3.0,7.0,DGHGDEDEFAFBFBDDEAADFDHCHFAFBDGHHHHCCCCFCFBEA,False +735,11.0,7.0,8.0,6.0,4.0,4.0,8.0,5.0,CHCACAGAEDFDCBHDHFHBCDDHAFGGGCACAGAGBBBGBEBDFAAGAECEA,False +736,20.0,16.0,16.0,26.0,10.0,23.0,15.0,12.0,BDBHCCEBDBACHCDFGFCADHDFDHAECDAGAGCFEFCFEDDDDDDDCFHHADFDABEGGGAGAGADABAFCFAFDBEBEGACADDDHAHBECHDGBGBDDEGEGDBFCFHBADGHGHFFFBFAFAFCFCFBFCFBA,False +737,23.0,11.0,24.0,14.0,10.0,9.0,22.0,11.0,FHADCDEAAAABDBHAFADADFCGGGHGAEAHCGDDCDCDHAHCGGGGCACFCBCBCGCHAAFAHEBADAECGCGCGDGECEDGBFCDBAGACFHAEGCGEGBGCECHGGFHFABABABCCDCE,True +738,26.0,23.0,28.0,29.0,22.0,16.0,18.0,26.0,EHDFFHFHEAFFBBEHDBBBDBDCGEGEGCBCDGHAHDEDEDFAFGCCCACBDAGAEFHFHADAFHCDCDBDHAAAAAHCHCHFHFEFHCHFBAEDHCBCBCBEBDADGDAHAGACACBHEDDDEHCHBDECCGBGBHDCDHDBGCCBGDGCHHGFBAEGEAFACACBCEEEEHEGCGAADAEBGDDD,False +739,8.0,2.0,10.0,6.0,9.0,6.0,10.0,6.0,CGBDCDCHHEEAEACAEEGFHFDDDDFGFEAHCCCCCBFGAGAGEFAGAGHCEGEGH,False +740,11.0,8.0,17.0,13.0,9.0,9.0,18.0,8.0,BGAGBECGDGHFHBHBGDGDGCCCCCCFCFDFAFHBDADGDGBBCACAFEDGDHCECHAEEEBDCGGAGFGCGDAAEDEACHEHCCFGAGDGF,False +741,4.0,2.0,8.0,8.0,5.0,1.0,3.0,4.0,CECEAEHCCADDHDHGGEBHBECFCDDDDCDAGAC,True +742,2.0,9.0,1.0,2.0,5.0,5.0,1.0,4.0,CBHEDBAFFDBABEBEBHFHBHBFBGEFE,True +743,18.0,19.0,21.0,21.0,22.0,11.0,26.0,21.0,EAACDDDHDGEGBHHHHEBEBABHEHBFGCGDGEGCDCDGGCGHFFDFBBGACADADHHADCDGDGBCCCBEDECAGHGHBFCFEDEDEGGCBEFEBEBEHADBHBGGGADADFGFDAEAGBBHGDBHGHCHCACACAEFEGHCECEAFHCHBGEGECA,False +744,31.0,23.0,20.0,24.0,21.0,22.0,28.0,21.0,DADEBEBEDADABCBFGGGGGHGHAFFGBGBGCGDGFGHBCCFDEHEADABAGGBGFCFCAGAHHEDBHBHFFEHAGAGBCDFAEBHDDDDEHHACFBHDGDGACFFBDBAAADAHAHCHCEGAHAGEEEEEBHFFGADABABEBEBCDCBHFHFAADFCGCGBAADDDFCCCHFEFECEAGACAGDGFE,False +745,5.0,11.0,15.0,7.0,10.0,9.0,7.0,16.0,EFHFBCACFCEHBCBABABCECFHHHHFEFHCHCFCBHHGGEGEDDDHAFGEGCBDDDHEEAFBBCHCHEHGHBCBCDCG,False +746,1.0,0.0,6.0,5.0,2.0,2.0,2.0,0.0,GDCDCACECEDFDGCCFD,True +747,14.0,8.0,8.0,12.0,14.0,15.0,12.0,12.0,HCHDFEEGCBCDCAEEEBEFEFCABABFBFDEGFAHEHAHCHGGFCFDEDAHCHDFDGDGABHEAAFAFHFEEGAGDDFBHBHGDGEGAGAFAFD,False +748,23.0,22.0,15.0,27.0,27.0,24.0,31.0,19.0,CFEFAHGBGDEAEBEAEBHBDDGBFAHCGFHFHGEGFAFADBEFHBEBCCFCGEGADBBGGCGBGHHBEGEGABBEEEAHAGEGFGAGFCCBFAGBGFGFGFADDBDBGBFEFGFAAAABHCDDDDDDFDFHFHBGDEAEDDDEDEGEDEDECHDHCFAGAHAEAGADFGHEHDHCCGEGEDBDFCHC,False +749,18.0,23.0,17.0,19.0,17.0,23.0,21.0,21.0,EAADEDBDBFBEECFCDEGFDFHBDAFFBCCCGCHCHAFAFAGGHGECECEBEGAGDGDHEFEHCBAADAFBFBHBABGBGCFCDHFBDEDECFGFBCHHDBBCHDGDFFBFBGDGBHHAHABADADEEGHGHBHFFFFEFGCGCDEHHGHGAAAGBBH,False +750,26.0,15.0,24.0,31.0,22.0,18.0,27.0,36.0,HFCEEEDBCEHFDCDCDGDAHEDGBCCDCGHDEECFHFAFADHFCGEEAEHEHECGABAHFBFBFDACBDBDCDHDHGFBFACAHAHABAHHHCDGHGHGHAABFHFGGHADDDDDADCDEDGDEAGGGGAGBGACCHBHBFDDEEHEDDHCHCHCHGFGAHHHBHFGCGHEEDEDFBAGHGHCECGCAHAGFEADAGA,False +751,2.0,2.0,6.0,6.0,5.0,4.0,2.0,6.0,DCHAHGHCHCEBEGDFCHCDCFEFEDEFHADBD,True +752,12.0,16.0,4.0,9.0,13.0,13.0,11.0,4.0,EBEBDBDBFAHAHADAGBCBFHEEAFAEEBEFGFEFAAAGGGBAFCFCFDGEBBBBBBGAFEEDDDGAGFGCEFEGBDDFHB,False +753,20.0,22.0,13.0,25.0,23.0,25.0,27.0,11.0,DBDAFFDEDEDEFEFDBCFFHDDEEEBEFDFEFEGBGCHCEBEHEHAABAGGGDEAFDFBGGGDFAFAFACHEEBHACBFECCGGGGGGFDFAFCGEGEFHBDBACAHAEFDBDFGABFBEGCGCDHDHDGDBDBDGCFBGCAHGDGBBFAFABEGEGABADADGB,False +754,13.0,24.0,24.0,21.0,25.0,16.0,20.0,11.0,BHBDGCGFGFGFGHGHBFGCEEFEFBAHEHEHEBCDEDEDBBCBCEFECGCDBACAGDGDBBHCCGDAAEAHCEFECABABDGDGCBEDHGFEDEDBGGCACDDBEBCBDFGGGEEHECECEFDFDBBBDCHAFDCBCBCGCFFACAEAEDBFE,False +755,21.0,23.0,12.0,20.0,22.0,23.0,13.0,24.0,FBFBCBFBFECEBHBHDHBBBFBACGBGBDAGFDACHHGCGHFDBHEEEFEAEBEBFGAGAGEDDFDFEFBCAFDFEAEAEDFDBDHECDCFCEAHAFEEHAHGHGHCBDAEGHBDDDBDEHGBAHAFCHGBFHFHEHEADHFHFHFDEBCAAAAHAD,False +756,9.0,16.0,8.0,17.0,8.0,7.0,7.0,4.0,EFEFGFGCCBABHBDDDDGDABBGBFBFEACDBDEDHCGEGBCBCBFDDDEAFABADAHEBADHDCCEDGDBBBAD,False +757,15.0,20.0,18.0,27.0,18.0,16.0,16.0,19.0,GHFBGBCEEAHDBDAHAHEBFFDDDDBFBEEAGBDHDBEGHAHADDEDCFCFBHAHBHDDGDGDECECGHGFGDADEFCFCFDADBGEEBCDEDGABABHBHBHCDCECECEGACCEABFBFBCCHABGHFHFACDDDDDGHECGFGFH,False +758,24.0,10.0,20.0,10.0,13.0,18.0,25.0,18.0,HEHAHAFAHCGCGCHEBGCGHGHGFGCGEABGHGFGHCHEAACABAHACFEAGCECBGGGGGACDFHFAFDFDFDFBEEAEAECFCAADAGFCHHECFHGAGHGEAHFGCCDBDBGACAGADABBDBDCFAFHGEFCF,False +759,5.0,2.0,3.0,3.0,1.0,2.0,7.0,3.0,CFAGGHGHGHBDGDGACEDACAGABF,True +760,23.0,15.0,19.0,10.0,31.0,25.0,21.0,16.0,FGFGHGDGBHACAFAFEFEGEBFGFGFECEDBFEFEHHCFAEACFBBBAFEDCGCEAECFCBBHEGEDEAEFBFGFGADCCCBHAAEEBABAHAHACECFHFEDEABFEDEAEBECACECGFGFEAGAFEFACHGDGAEAEGHHHHGDCBEDEHFHGGCG,False +761,4.0,5.0,6.0,6.0,5.0,5.0,6.0,6.0,EFBFBFGDHCHFEFGGBDAGACHCHDHBAAECCBCDEDEDGHG,False +762,5.0,7.0,14.0,5.0,9.0,9.0,6.0,9.0,EGEFHBHFGFHCEDEBEFACAEAECHCHCHCHBGCFDFCCACBCDHDFGABHBCECDGGEFCFB,False +763,7.0,10.0,9.0,14.0,6.0,13.0,15.0,4.0,FHBHAHAFAEDCDEAEHFDDGFBFBFDGGFGBGBCBFDGDBCGEGECAGAGDGDFDCDCDFGCGEBDGFBACFBFDCG,False +764,18.0,17.0,21.0,10.0,17.0,19.0,30.0,14.0,GFCBGAFBBEFFCGHGEADAHFHEAEAHAHFGGGEGECCFAGAGFFCACBFAFAFGGGAEHGHFHBHCACHFAFDEDHGEGDFBCGCAHGCEBEHCBGBDDCAGBDAGECECACBCBCGGGBBBBBECFCFEFHGDGDGDGEGEGC,False +765,16.0,9.0,24.0,14.0,21.0,12.0,17.0,12.0,FCCCCEGDGDFBEGCBCDDDDCHFGACDHECCCEEAHGHGCCCFEAAADAHGEBEFDDDCDCEAGCGDHEAEAGADAGEFCFCFGFGEAFHEECECEGHGBFCECEBFBCAEBGBGHAHAHAHBE,False +766,2.0,5.0,3.0,5.0,5.0,3.0,5.0,14.0,GCCBCDHEEEFHHEBEHGHBHDHDHAHFGAHDGDGHHHHBFB,True +767,25.0,19.0,25.0,19.0,30.0,21.0,34.0,24.0,AABAGCCCGCDFDAEECGCHBHGHGHDAGCGDFDCEGEBAGFEEEHHAGAGAGFECEHGCECEHFHABEEEBEFEBEFEBCGGGDGABEDEDADGFGFCHHHHDDFBFBAEAEAHGFCFAAAAABAFHECGCDCGFADDBHBGCEHFBBGDHFAFHBHCHFHAGGGGGGAGCGEDEBEDECHFHGBDEDBFGCCCCE,False +768,25.0,18.0,18.0,14.0,17.0,14.0,28.0,21.0,DBBECABABAFFCHGBFEAEHGGEEEHGHGAGADAHGCCFDFDGAFCECECDBBBFBDHHGHEHBHAHGCGFGHHCCFAEAECGAGFHHCEGGGCDCEHEHEDGDHDAGABACCBCBGFFBBHBABADAGGGGHGAGAGAECFBAGAFADAEHDD,False +769,1.0,3.0,1.0,7.0,6.0,6.0,6.0,3.0,EFGFHFCEBGHFBDEDEHEAFDDGDGDGDGBEF,True +770,10.0,20.0,19.0,21.0,15.0,21.0,16.0,16.0,CDHDGGGCGEGECDCDCDABFBDBFBFDFHFHDDBEAEHBGBGCDBGBCHHDGFGCHDHCGCAAHABAFHHBDEFEFCFDFCFCFAHEFBFBGHGDDDCBEGGFEBEAEBDBHCHAEFCDCBFEFEBHCGCBFDFDEA,False +771,4.0,6.0,5.0,4.0,2.0,2.0,2.0,5.0,DBACDGDBBHBHCFDECECACAHAHGBFBH,False +772,20.0,21.0,27.0,26.0,23.0,24.0,13.0,18.0,HHGDAACADHDEDCABDHDFCFDBCFCABDCCCCFFFDFBCBHBGEGHGADACFDGAADDDDDECEHEHDFEBEFCFHFAFCFCFAFCHHHCEBEBEGECECFCHEFDCGBAFADAEAEDEDEFEHEGDAAEBCAEABBFBFBEADGCHDBGBDCDFGGBCBCBEHGHCHBF,False +773,23.0,11.0,12.0,12.0,15.0,10.0,15.0,14.0,HHBEBEDEBGBDFCECGCGEGCHDHGHGBCHAGAGAFAFAHAEEEAEAGBGEGCGAACABBHDABFDFAHADGHFBCDDHAAEAEAEAEACDFDEAAAHFDCCGCHHGDBFF,False +774,17.0,24.0,28.0,15.0,15.0,16.0,18.0,18.0,EFEFEBGCDADCEHBHBHBFBECECBFBFCGCEDEDCCFCGCGFGFACCDFHAHGHBHCHEHECCCGGFCHCADBBBGHHEGCCCGCBHGEGBBBAADCDCDCDADADABFHFAGBDBAHGBBABFEFGBEAHBGCCHFHGDABACAFDEA,False +775,3.0,0.0,2.0,1.0,0.0,2.0,2.0,3.0,AGHGHFDFCHCAA,True +776,17.0,9.0,11.0,6.0,12.0,12.0,17.0,14.0,GCGDABAFGFGCCECFABAEAEBGADHHEHAAAEDEAEABDFCGBADAEHGHFFFGAGFCFDBHBFGHHCGAGHGEGHBHCECEAEAGFCFCBHGHGH,False +777,4.0,6.0,1.0,5.0,7.0,2.0,6.0,4.0,HEFEAEAEDBBGDCDHDFEBAAHEHEDGBBBGGGG,True +778,6.0,7.0,4.0,4.0,5.0,13.0,4.0,5.0,HEHEAFGFAFAFBGBAFFFDEDECBCFGDBEHFAFBFDFHFHGBACCB,False +779,9.0,7.0,5.0,6.0,9.0,8.0,7.0,9.0,DGBEBEDHAFAFHFHFCFCEDEGEDEDGHAFBHBAGAFBCBHFAGADAECCBGEGHHEHA,False +780,19.0,21.0,16.0,16.0,23.0,19.0,26.0,22.0,FFCAGEGEGAHBBEBEGCDFEFCFGHHDHDHDBEFFAGEGAGAGAHEHFAEDBACCCEDGBEACFCFEDEABABABFHFBGBGAGEHHACBCGCHCHGHEABACDBDHEGFGEADHFBDCDCEBBAGHGHEHEHGHDHDGDGFHABECEBDGGFGBGBEFFF,False +781,15.0,24.0,23.0,18.0,23.0,14.0,17.0,21.0,FEAGCCBABABAFAHCDGHFCAEGBGBGHHBBCBFBABAEDEDADHFECGDGAHEBEBECCGCHCHEBCFEDDDCGCGDGDHEFGGCHCBEFECAHDEDFDEHEGEFBBHGGCECECFBDBDBAHAHEHDHECFBFDCECABABHBGBCHFHDHE,False +782,14.0,24.0,23.0,18.0,18.0,17.0,19.0,17.0,GAECGCBBAGAGAGFEEDDFBEEEBBGGEECCCCBEGEGFGDGCHCHCHEADBDBHBHFGADBFGDHHGAGADDDDDCBCDHFBFHDAGFHFHFHCBCFEHHHBFCFHFCGCBCAGFEBDFCECHCACBDBCEAGDBDBEBEBEBABAFC,False +783,17.0,21.0,14.0,26.0,20.0,11.0,14.0,15.0,CHAHEHDHGCCADABAEDBDBFAEABGDDCGADADBBAFCEGDBEBDHGEGFHEHEHEFCFDGHADADBDBDCDCGBABDECEDEDFDCDCDADEDBDHGBGBECDHEHFFBAEAEBEBGHGEBCGGBEFHBHCFAFA,False +784,9.0,13.0,21.0,19.0,11.0,19.0,13.0,15.0,ADHDFGEBBCCDCDCFHAGDBCBCECEAGAHCDEAHBHEFEAHHGDCHCHDHDHFBEADFCGCHDHAFBGBGBEFDFGFECACFEFGFDCDEBGBGCFBFCDGDGCFDFHFHFCFCDCDB,False +785,3.0,4.0,10.0,4.0,5.0,8.0,5.0,7.0,FCFCGCGEAAGFCECECHFFDHCACGCGEBHFEFHBHDFDBDBHHC,False +786,13.0,15.0,20.0,21.0,12.0,14.0,14.0,18.0,BFDGDGDADECHCHCEDGDBDGHCHDGCABEEFEFGGDDBDHDHDGCCEBDFDFBHBHBHFHFAECEBAAAFAEAHBHGHDFEFBHBABECCCCCDEGHGBFFGHCDCBGDCCCFHDCACAFGHADA,False +787,12.0,21.0,22.0,19.0,22.0,24.0,29.0,14.0,CGCGEECEGGBEAGCFFFCDCEEACFBFBGBGDGDHDHCBCGADEHGHBFGFGFDFDBGEGEBFCFCFCFABDBCAFFGDGBFHCHEECDFDFCBEBFHGCGEGAGAFDFCEGEGEAAHHHBGCGCGAGDGDBDFGEDBDFDBCHADEEGEHEHABBFEHBCB,False +788,17.0,13.0,19.0,20.0,16.0,16.0,19.0,15.0,BDCEGHGDAFFHFHDADAHEEEECFCGDHBHGGGAGAEFGBCADGCCCCCCGCDCBEFEFDFECADABAFEBGBGAADGEGHADABHFHFCEDHDGGCDCDFDADGHCFBBCBCEHBHFHDEDEDEGHGAAAFBF,False +789,28.0,17.0,13.0,32.0,28.0,13.0,27.0,17.0,AEADADBGBAFAEADGBAAGDDEGEBEFCFCFHFHAEGEHDHAADEDHDCFCBAEGEGDGCGAGBGBGBFDDDEDGBGBGBDDGGADCDBGAEAGDBCADEDHBABAECHCECAFEHAFACDCDGEHEHFBEHDDDDFEAABDHGHGHDAGECEGEGDHEAEGEGEAFHDHDFAE,False +790,20.0,14.0,14.0,14.0,17.0,15.0,16.0,18.0,FCFDDDHCHCEGHADCBGFEFCFEEEEBEADABHBDEFCABABAGAGEHHBHBDAECGDEAAAFAEADBHCGGBGBGBEFEFEFABAGFHHGACDBDHHGFDACEHDHGHFCFDHCHCHCEFAGAGAG,False +791,18.0,17.0,18.0,19.0,20.0,20.0,6.0,18.0,FHFHFDEAADAFBBACGHDCDFAGGFEFADEDBFBFECEAFAFACCCEFHBHFHBBACHFDGDCDHDHGBAHCDCBHBEEEEAECBABCBCEDHDFDEDEDEAEADACAHFHFHEDCCABEHEBEHCFBFGFBDHC,False +792,14.0,17.0,13.0,12.0,11.0,16.0,16.0,11.0,DDBDBDAFBDBFAFAGBDEGCCECHCHCGFABGBCFEFECHFBABAEECBDHDGDGHGHGFCFHEAEGDHBCBEFHBGAGACAHAFGFGFDEABFBABGFGFGBHCAEDC,False +793,9.0,19.0,17.0,11.0,13.0,16.0,16.0,13.0,DCGHBFFCGEEBEGGAGFDEEBFGHCHCDFDBCBCFCFCGCGBBBCBCBFHFGCAEABHBABGBDBDFDHAHFGFHBBBGHGHECFDECEGHGHDAAGDBCECDAEAEFEFCFH,False +794,18.0,14.0,23.0,18.0,18.0,15.0,28.0,20.0,GBGBGFGAEFECEBGBECECFGDEDGFCFGGHCHCFGDAHHCHCFCFCGCGCEAHAEABACDBDBAGGCGHAHBDFDHEHEGAGEGEHHDCDGFHBHGHFADECACAEABFCAHGHGBDCDFDFBAGACDGGCDBGGADHDBFHEHEAEGDCEC,False +795,2.0,6.0,5.0,6.0,3.0,1.0,4.0,1.0,GDGECBCHDEDECBBFBCBABDGDGACD,True +796,20.0,15.0,22.0,19.0,22.0,17.0,35.0,28.0,EHGHCDCDAEBCBFBACHCGEFEFEFDFHGHDCGAHDCGCDCACBGEEHEHGGGEHEFEGGAAAAHAFFECCAGHGHGHBACACDCFEAGGGGGGGCGAFCBEHHGDGHGADAHGHBDGAGBCDCABAHDDEEFGGEHHHBBBDBDHDHDHFHEHBCDCGFGECEFFGFGEGHFBEDA,False +797,22.0,14.0,14.0,13.0,13.0,14.0,15.0,9.0,HCHGGBDEFAFAGAHDCGCGCHCGFAADEDEABAGABFEFEFEBDFGABHFDAABCHCFCADBBAGDGDGDCDFEFGBDBDFFGCBCBEBGAAAAAAHEHEBEGCAAAFHECEC,False +798,15.0,14.0,14.0,26.0,14.0,22.0,16.0,23.0,DCGAADDDHDHFFDBGGFGEGBBDHAHFFFFAFCFBDDFEAEDHDHGHGDCHCFAGBDFCFEFGAGHECFCEDAHAGEBFBABDEDADCDHAFCFAFHBDFAFADEGEHEHBHGFGCGHGCDCDBBHHHHBCBCHDEDEDEDHH,False +799,27.0,20.0,19.0,24.0,17.0,17.0,26.0,21.0,GFGDGDCDFGBGBEBGBHHFDADAHEHEBBBHFFGGCADACAGHBHAAFACACHBECEFAHADGDAEHECFABCGCAHBHAHDGEEHFDFHFDFCAHDBDBFEGDGDGHBDBGAGEGBGCCECEBEHAGABADADADECGCGCAFHGHBFACACFDEDEBGACAGHGFDDD,False +800,14.0,22.0,27.0,22.0,29.0,27.0,20.0,20.0,BCBCBCACACAHDBFCHEHEFBGGCGCABBHBEEEBECECBDHDEBAACGCGFGFDFGBCDAHHHHFFEDDDDEFFHFDEGGGHEAEDEGBBDFEADFCGCGCHFHGHGEDCHFFFDFDCHFBCBCBCEEEGACAEHEFGFDFCFBAEHECGDEFGHGAFAEBBBBDCEHFCFEFDCDEDE,False +801,5.0,1.0,4.0,0.0,2.0,1.0,0.0,1.0,HCAEACAFBEACAC,True +802,15.0,14.0,17.0,11.0,11.0,11.0,14.0,5.0,DGAEAFAFCFDADEFEFCACGEHEFGCHABACABHBADDFDFCGEGEAAACHCGDGCGBEBFDCABBBBDBABFGGCCCEGFBBBEDAHCGCGCGCED,False +803,19.0,24.0,22.0,27.0,21.0,24.0,25.0,26.0,HFAFEFEFCCCHCHGDDHEHEDEACCFAFBHDEDEBGCGBFAHAHAHFGDBAGAHBHFEFBFEFABCDHDGACACBGDGHAFBDBCFHFHDHDGDADBCFGGBDACGHGCECEGGAGDGDGEGECADHDABGBDDCECEHFHBGGEGEHBFBDHFACAFBBBBHEEEGCDHGFDFDFEFHDHDCBBBC,False +804,14.0,12.0,12.0,16.0,9.0,14.0,9.0,8.0,ABCBAFDEDFDHDCDBAFCBGBDBEAEGEBCDGAACABDECECEHEAGHGDBHFFFCGDADFFFGFDBDFAHCHCHCHCBADADADABFFGGEF,False +805,10.0,5.0,7.0,4.0,17.0,8.0,9.0,3.0,AAGAGAGAGAHECEFEGEHEBEAEFDADFEEEECEDECHGFEFAFBEDFGBEACBCEFBCCGG,True +806,16.0,25.0,13.0,17.0,23.0,16.0,21.0,18.0,CBGEEFEGBBBCHGHBAAAAGAGEGCHCEDBBBBBHHHHDAFFEEDEDAAADFEBHGHDHEGEGHCECEBBDADGGGGGDGHEHEHEBBBFGFAFDFEFEBEBCFFEBHBECDBDFAFAGHDFDGBHDCFCAABCBHEGDGDEBGCCAF,False +807,3.0,8.0,5.0,8.0,9.0,8.0,9.0,9.0,HFFFBHCHEBEBEBGBDCGCECEFDFBFGAGHHDHFACHDHDEFBGDGEHEADGDBEGG,False +808,18.0,19.0,24.0,19.0,15.0,25.0,23.0,17.0,CDGFCFCAGHEAEADCGEGACBGFGDHEEECACECECFAHAFDCDHDFEBEHDFDFHFGBEBGGGBBBHBHFAEAFGFAHAGAFCGCHCHGHBCDDFDFDGDFBEBEBFAFCFGDCCHGHADCBFBGBGHFCGDGBCAHFDFCFCBCBDAEABADGFGHC,False +809,24.0,16.0,20.0,18.0,20.0,16.0,26.0,18.0,HBEFGCGHAHADGCACAFBFAFCEBGBFDGAGAEHHCDDHDFDHDHDEECGABCBFEAEHDGGGGBABGFEBCAEGBCFCHGHBHBABGBHFEFCCCCAHGEGEFHFDGAEBHDADCGHEAEAEAEAEGEDCDADGDGAGAGAEHDGCCFCFCADBGF,False +810,7.0,10.0,7.0,14.0,17.0,13.0,14.0,8.0,DEAEGEFECACABGEGEAHGHGHAEFEFECHDDFDBDBCBDBDFGCGEBECEDDDADBEFEBDFGBDFHGCFFDGGFEHEHFHBGAGEGF,False +811,11.0,12.0,11.0,18.0,16.0,11.0,15.0,16.0,EBEBABDHDHDHEHGHFAAGGCAFEDDGEFAFHDBDBDHEGGGGBCBCFDDDDDEDBHFEBHCHABEFEFGHECECBFGGGEDHCHCGEGACAEAECHABCHDADFDFHG,False +812,7.0,8.0,5.0,1.0,6.0,6.0,5.0,5.0,HHHHAEACACBEBCCAFAGEFCFDBHBFBFEGAGEGBGFABBE,False +813,7.0,6.0,14.0,17.0,20.0,8.0,11.0,16.0,BCHCAFAGAHCEFEDEHEDCHGHAEDGDFCFHGHGHAEGEGFHBBDFEHEDEDHDEDEBGDDFBEHGABCEDECCCADGHEHEHCHCDCDCDCEEGEFD,True +814,27.0,14.0,15.0,25.0,17.0,16.0,12.0,25.0,HFFCACAHFFCBCFFGDDECEFEHCBCBCDAAAGAHAHDECEFHAHAHDEABBEBCFGBGDEAEAEADGHAHACDHHHBCBEDFFAFHFEEGAAAAAHAHEHEDDDDGAGDHDBDFFAHDBACACAGHHDGBGBEDDBDHFHECGDDDHDH,False +815,9.0,8.0,11.0,6.0,5.0,16.0,9.0,7.0,DDGCCHAAADDFEFBHDFFFDFCFCFCFEBEGGGCFCGHGHEAAAFFHBCBGBEBCBFFFCFCAAGAHHGB,False +816,27.0,23.0,14.0,24.0,26.0,27.0,25.0,22.0,DABHHHEHAHAEFDBAGABDBGHDAAGAGFBAHAHEEDABFGGEEADAFBCACGCGCEFEBEBDFDCDGDEFEHEHFAGAGCBCGCBCBEDAGGBABHDFBFBDEHEHGBFEFEBDFHFHFDEECAFGFGFEADHDAGAGADCDCHFHCEADFDGEAFBFCFDBEEDGAGBEFEHDHGAGHGHFBFBF,False +817,1.0,1.0,2.0,2.0,3.0,7.0,3.0,4.0,FFFFADHDHEHEGCFBGECFHFG,True +818,10.0,14.0,17.0,5.0,12.0,5.0,16.0,9.0,CACBHAACABGDCAEAFGBEHEGCGCGEGEDBGAGFHBGCECEFEGEGBHBFGAGHEABDFDBCBCBHEHGHGBDCACBGBECCCCCH,True +819,20.0,12.0,13.0,11.0,16.0,13.0,21.0,6.0,ADCECACDCEGDFFAFBGBGBGBAAAEBEBGFDADEDAACACDCHHBGGGGGGGEGAAHFEFCGDGBCFABAFEGCDHFECEDEHABCDAHFGAGEGAGAEAGBFBCEFEFE,False +820,24.0,22.0,18.0,21.0,20.0,19.0,14.0,22.0,ECFBHAHAHAEAFBFGDGDCBCGAEAHABCBHFEDEDGBCDCDADABAEAEBHDGDHCBAHFDCDHHBHEGAAFAFCHCDDEHBFBFDGDGHBAFCEDEHFCEHEHEHGCGAHABCBEFHFGCDCDFBFBFAFGBDEDAGCHBEBCBADAGEBEAEAFFH,False +821,24.0,21.0,19.0,22.0,19.0,13.0,20.0,29.0,DAHAHAFEGCDEECECAAEHEFDDDGAGAGAGABHBGEHDHFHEHAHAHAFBHBHCAADCEBBGDECHGFGHGAGEDFDFDHHHCGAEABFDGBECECAHACFCHGFBDHGFDHBHDDDDGGHEHAHBGBGBHEABBFBDBFBDAEEBECCCCCACHCBCHAHDGDB,False +822,16.0,25.0,27.0,23.0,14.0,15.0,16.0,28.0,BHCHCDCAGFGAGBFHEHBABGDHBABFBGBDCHCHCHEHAHEHCHDBGBHACADADAFFHAADACBCBEGEFDFDFDFCHEHDDBDEGEDHHHCDEGHCFGFDEDBBGFGCGHAHBDCECHCABHFCCHCDEDCDCGBBEHDHBGBFEFCACHCBBABCBDGC,False +823,19.0,16.0,17.0,19.0,13.0,21.0,12.0,12.0,AAFGBDHDCDFDEHBBFHFCDCABBFDFGEGEBCHDDDBDGDACAGABEGECECECEFEHCHAGDDHCCDAEFFAFBFBGDAEHHBABAHADABGBFCFGDCDFHFHAGAFAFDFBACACFGFEFECBC,False +824,23.0,14.0,24.0,16.0,17.0,21.0,26.0,11.0,EEEECEBHDFDBDCFAABFDEEGGCGEGFHDGAGBCFCHCFAFAGAGFFBGAFAEABCGAEADADAHBBEHCHCBCBCDCECGHBHAFDEDEAAACACFFECEFFGACCDCFGGCGCGFDFHFGCGCGAEAGGHHFBFDADABBCGGGDGDG,False +825,16.0,23.0,19.0,19.0,25.0,21.0,19.0,16.0,BCECEGEHBGBGDACADFFBABGGEBEGCGAGDBCFCEADAEFEDDCHCDEDGBGCFHFGBEBEBEHCHCEBEDEBFBFEFHFHFGDEAEBGBEDDCBHDFGFCACAGAHBDBDBCCFCFAFDDDADHEEEFHAEAGBGCAHHHEHFGFBFGECHABF,False +826,8.0,5.0,4.0,4.0,6.0,3.0,1.0,4.0,CDGDCFEEEEABABADAHBFBHACAFHEAEAHCBD,False +827,24.0,26.0,18.0,19.0,16.0,34.0,27.0,29.0,CFAFCHHGFDHDBDBDCDCHEFBGBGBHBDADCGCGHGFDFBAHDDAFECBFFFHFAGECAHAEBEAAACGEGHGEABAFGCEAGFFHFGACBGHGAFHCHGHGBFAHGHBHBGBGAGCFBEDHBFBHEHEBFGECEADHFHFHFDABFEFHFEFBFBABDBDFDADGDGCAEAFCFCFCDAGGFGFBHHHHB,False +828,2.0,3.0,1.0,7.0,4.0,6.0,1.0,1.0,ADDDFDFEFEDEBFBEGFDADFHCB,True +829,18.0,8.0,19.0,22.0,14.0,21.0,12.0,12.0,EGEGCHAFEECHDBDBDCFAFEFDFEGEAFCFDADADCHFHEADAEHDHCCFCFDFHFDFDACACACEFDFDGBFBCGEGFGCGCAHADACEDDGCCACHBABDBHAHFFFDDHACBDEAEGGGFD,False +830,14.0,17.0,12.0,13.0,7.0,7.0,14.0,9.0,EGEBHBDCDGECBABADDGCABACFCEBDCCADADFGHGHGFGBGBGHGFDDCDAGABACHHDHDFDCBBGBAAFACEHAGAGBEBHBCBEBF,False +831,13.0,21.0,11.0,11.0,12.0,12.0,12.0,8.0,EAEDGBFBDBCHEBEBEBCHCHAFGGBCDDDCDCBADAFAFABADFCBCGEAEDBAFAEHEHADFHBBEHEFBFGEBHFGBCBCBFGGAGAGBGCGFBDB,False +832,14.0,20.0,21.0,16.0,26.0,24.0,30.0,17.0,BGGGEEEBFFFEFCDGGGGGCGABDFGHCAFFFDFEHDHAGAGAEBEBCBCAGBBDBFBFEEEDDFCCGCGEGBBDBHEDCFCHGFEEBGCFAEGEGECFCGCHEDDCBEDDDHHHCGBGEHEHGDDCGCGBGEGEBEHECGGAEABAFAHAFAFHFHCHCFFFHFBA,False +833,0.0,0.0,2.0,1.0,0.0,7.0,1.0,2.0,GFFCFHDHCFFFF,True +834,15.0,17.0,13.0,12.0,21.0,19.0,18.0,23.0,DEFBAGHEHEABHDFGFHFHCHDHECEHBHDGDGFFCGBFBEEHHCDEFECEDEBCBGEGEGACAGHGHAHDFCBHGFFFFDACEHEBFBHBHGAAEADGGADHHHHGHGFAFCFCGEDFFABABGECACABEBEBEB,False +835,9.0,17.0,15.0,12.0,13.0,15.0,12.0,18.0,AEAFDHGHGFDEDBFBABACCCFCHEHCFEDHFGFDHBHBHEFAACHEDECFCGCBCECEGHBHCABDBEGFDFDBDBEGEFFCCGHAHAHGHDFBBGBGDGHBHBCBFHE,False +836,24.0,27.0,17.0,31.0,24.0,22.0,21.0,23.0,DCGBEBCDEDADFBFEDADADBDCDCDEDFDGBGCGBHBHBHEHEDEDAGBGFDAHGHBCECADBDEDBFFAFAFAFEHHGCGFEFDDGDGFBFGEGEBAHAFDDHFABBBDADAHAGAFFFCGGEECHGAGAEECEBFBCBHHGEFDAAECFADHGHCHBBBBDEDHBBBEHHAHCHCAEFEHADGDC,False +837,8.0,2.0,11.0,12.0,11.0,8.0,3.0,11.0,BHCHEDEHFAFHDHCHFDCDFDFDAAHCFDDADHDECECACECAFEHEGDGEHEDEHFCBCGCAEA,True +838,12.0,19.0,12.0,11.0,20.0,17.0,13.0,16.0,DEFEFEHEFBFECEAEAGBGAFEBEDFGFGAHFHFCGBBBBBBHEFEBHBGBGHCHFBCDFHAACCHEHACDBFEGEDFBCBABHHCHEHACACEDDDDFDGHGHCAGFDFBEEEGEGBA,False +839,1.0,4.0,3.0,4.0,6.0,6.0,4.0,1.0,GBEECAGBFBFBEDCDFDFEEHEDGFGFC,True +840,5.0,4.0,4.0,1.0,6.0,4.0,2.0,2.0,GEBEFEHEAADACACFCFBBHCAGEBEF,True +841,15.0,12.0,13.0,8.0,18.0,15.0,11.0,15.0,FHFHFEAAHFEFCGEHEHCHCBCAEBBBCHAHAEGFGABHBEBEFCBCAHDHBEAFGBHAFEFBGCFEFCDADBDEDEDEGEFEFAACHDHAEACGEGHGCGAGFDC,False +842,17.0,27.0,15.0,15.0,25.0,21.0,18.0,18.0,DBEBDBEEGGGBGEHCACBCBABGEDEDGFAFCCBEDCGGFGBHAHDBBHBHECACEDBDHAAFAEBEDCDCHGBEDECHAFAFECECEFHGHGHBEBGBGBFFFFHFEFHFHEBEGEAEFFAFGBBBFHCHADFDFBABCGAEAGFHDADEBHBE,False +843,20.0,14.0,16.0,25.0,17.0,16.0,12.0,24.0,HBHEDGBFBCADADACHHDHDAEAHDDDDDHFFDHDGCGCBHEGABAHEDEABACDCEFGFHAGGBACGHAFFGDCAAGHDEGEGEDABACABHFDEEBEBDBDBDHDADAHCHBEFEDEDCFCFCHCHFHFHFHFCAEHHFCE,False +844,6.0,6.0,6.0,6.0,7.0,4.0,7.0,2.0,GCECFBDBDBEGHDEAEAFFECECACBGBDADGDGHFABGEGCA,False +845,14.0,10.0,13.0,17.0,13.0,16.0,16.0,22.0,DADFGHGHFHCBGAFEFCFCGDGDEDBABABECDCDBBGAFAGAHDDDDFDGDGDCEGGFHFHCHGAGDHHHFFCGCHHEFEAHHHFHGEGDAHECDCHHAHAEAEBCFHFBFCEHBBEEA,False +846,13.0,21.0,15.0,9.0,8.0,13.0,6.0,10.0,AGBCBCBDGCBFGHABCBCBEBABCGHEHBAFAFDFECDBBAAHBHBHCFCFDBABDCDFFCGHAHBHBEBEBCFCACDEHACEBFDFGFAFAED,False +847,8.0,14.0,10.0,15.0,9.0,10.0,9.0,7.0,DECFAHHBGBCEAACBCBADDEBHDHDEDFFFGEAEBGCGBGDGDFDADBDBDCFCGCBCHABFBDEDGDGBHBFFCFEAEH,False +848,10.0,5.0,6.0,10.0,12.0,17.0,10.0,11.0,DHDEDCDFDFAFAHCFGABAGFCFBGGGGAHCFDFAFEEEEBBABHFAFGFEEHDHECEHFHFEAHAHEDFDFHFDGGGEC,False +849,22.0,14.0,13.0,19.0,14.0,18.0,13.0,19.0,AACFCFBBHBGFDADADAHHCGFBCHHFHBHDGDCAHAHABDEDBDAHAGFGEBEBACHCDEGAFFDGBHFCFDDBABAEEDEGEFEAAGAGABADAHFGFCFAAGCFHEHFGFBFEEDEHEDCDCDCDHHH,False +850,12.0,11.0,24.0,25.0,18.0,37.0,27.0,36.0,GEGEAEAEDHDEDECECGGGEFEFEGCBFBFCFCDCHEHDDGEGFGDHFGEGAGCGFDHCHFHDGCCHEBBDACHCFCHGHCHCHGDFFFFDFHGHDFFFGFGHHHGCDFBFCHHFHDDBACHEEFDCAHDHBHFFFHHCHBHFHDGFGFGBEAHFHFHFCAGGDCBGDGDFFAACDCAFDFDFBHHAHE,False +851,8.0,20.0,9.0,10.0,16.0,10.0,11.0,18.0,GAGAGFFHFHCHGHEFEGADABHBHBFEEEBAHCHCEEHEDCAGGBBDBFGFHFHAHFHBABEHEBFBCHEBBBDDDCDBECEGDBCBEBEBHBGCHEDDHG,False +852,8.0,4.0,3.0,3.0,5.0,4.0,5.0,3.0,CEHEHBGFGBABDCGAGHFDCGAAAAEADAFEFEB,False +853,2.0,2.0,4.0,5.0,2.0,8.0,1.0,9.0,BHFHFHFADCCGFDFDBDEFAHHHHHFHECCFD,True +854,0.0,3.0,1.0,7.0,1.0,4.0,3.0,3.0,BGEDFDHDHGFBDBCGHDFDFD,True +855,13.0,9.0,23.0,8.0,13.0,14.0,12.0,14.0,CFCFCGHEACCCEEEGDHHAHBGBCFCDCDCFFGCAFDCABHCHCDFFCECGCGCAABFDEDACCHHAFAEBEBHGHBHFGEGCGCGAEBCBAGEFEFEFDHAHAH,False +856,10.0,14.0,21.0,25.0,13.0,22.0,18.0,15.0,HDAFAFDFBGDDCEEGEDFGBDBGCCCCDDDGDGHFDGHEFECHCHCFEDBDBACGFBFBFDCGEGCABABDEGCGCECEBAFGHHBDDDHHHGGDCDCACAFBEBECFCFAEHHFFFDGDGHGHDDFDFHFCFCBAF,False +857,5.0,7.0,6.0,6.0,3.0,6.0,3.0,6.0,HBHCDAHAFGBACABHBDBDEFGCHCHCBEFEFGFCFDDBDA,False +858,5.0,6.0,10.0,9.0,8.0,7.0,3.0,10.0,BGCHCHCBDDHDGDGABCBABFECECECDCDFHHCEDDFFFHHEHEAEAFHBEDHCAF,False +859,5.0,3.0,3.0,10.0,1.0,2.0,6.0,6.0,DADADBGHEADDDCDGHGHGCDCDBFAHHFHAGDGB,True +860,23.0,20.0,27.0,31.0,27.0,21.0,22.0,20.0,GBHCDCFCFDEDHCHGEFEFECCCCCADABAHFHFHFDGDAEEHACDDGBADFDEECFAFCFEGCGEEHFAFEFBABCDADEDEHBHGHBBAECECGBHAGFHHBGECCDEDBFHCACGCDAGAGADDDDDCDGFCFCEEEDEBHGHGHGCGCBDADHBGDDEDABABAEDEBFCDEBABGBDAFAFGEGH,False +861,7.0,7.0,14.0,4.0,11.0,5.0,11.0,5.0,GCGFGBGCCCGFAAEAECECECGBABHHCAEAHAEFEBEHDCDCGFGFBCGCGCDBEEHDGECB,True +862,12.0,3.0,10.0,5.0,8.0,8.0,5.0,6.0,GFCAHAHAGACCEHDBBAAAHADECEDECGCBCECFCFHFHAGGEDEFFCFAEAFAD,False +863,24.0,14.0,29.0,24.0,18.0,18.0,12.0,25.0,ACACHBEBEDABHBGCDCFCEDFCGCACGFADCCCCBCDEAEBDHEEGAGCDFDFDFGEHAHFEEAEHCCFHFEFCHCHDAAHGDCDAHFHEHDHDHAHADEBEBEGADAHEBFHFHACGFGCGCBCDCDCACFCFABCBADDBCBHHDHGAAHAHFFDHDEDA,False +864,12.0,14.0,8.0,8.0,15.0,8.0,10.0,15.0,EBEBGHCABAFAFDFDADGBHCEBGBGBCFCAEEDHCHGHBHDGDHEHEHEHCFGFBEEHAAAHGHGEGBFCABHFHEEBADCDABEBEA,False +865,3.0,2.0,2.0,3.0,0.0,3.0,0.0,4.0,BHDHBCFDFCAHAHAFD,True +866,5.0,8.0,8.0,6.0,13.0,7.0,15.0,8.0,FHCDEDADBEBGAGCCCEBGGFGEGEGAGAGHDHGBEHEDGAGEBECHCGFEEHEHGGFBFBFCFHEBCD,False +867,15.0,8.0,10.0,4.0,10.0,7.0,12.0,11.0,GCHHEHGBDBCGCBCFEAAHAHADFCFCFGAGAFBGAHAEGFBECEABHCHAEAEHGHGFBDCHGEGEGDACABAEA,False +868,13.0,19.0,24.0,20.0,14.0,16.0,12.0,20.0,HCHAHAGDDCDBGGHGHGCEEAEGFBFDEAEFCFHDHGFAFGEHDBDBDCECDFECHCDCFCHCHBBBBGAFDCACEDBFFAFAFBEHCACDHBCBCBHBCADDDBDHDHCHCBABHHEFGAECGCGCBDBDCFHFEE,False +869,11.0,10.0,12.0,15.0,14.0,12.0,10.0,5.0,CBGECDGDGDADCGAHDBDFFFFEAHFEFDBDGDGECECDDFDADBEACGFEBEBECCCGCBCBEAEAFGBAAAEDEGHHDHCFAFEFB,False +870,8.0,16.0,15.0,5.0,12.0,6.0,10.0,5.0,GEGAAFBCBCEGAAEBEBEFHHCBAAGACBBBBEBCGCGCECECBABCFCGCFEDEHCCDGBGFDFDEHCHBBGBDE,True +871,7.0,10.0,13.0,4.0,10.0,7.0,7.0,8.0,GAAHGCBADEDHDCCCACAFHEBBBBBCBEGEGFCHCBEGEGEHDHCFFABCFCFHGHABFECECE,False +872,5.0,6.0,11.0,4.0,5.0,6.0,7.0,6.0,FCCCACBDAFCCCFGBBHBGAGEGDGCGHGHDHDEBHCCFCBAEFEFEHA,False +873,6.0,3.0,2.0,8.0,3.0,5.0,4.0,1.0,AADDDCDCGGFFEBADADADEDGBGFFEFAHB,True +874,16.0,16.0,9.0,13.0,16.0,16.0,11.0,18.0,DGAGHBHCEFGDAAEAFAFBBDFHEDEDHBHGHGHDDEDFCFCAAADAHFBCBCGEHEBFDFAFCFAFAFBECCBEDHHEHEGBGCDFGFHHHBHBEBEBHAEADBEBAAGEGHF,False +875,10.0,10.0,11.0,9.0,10.0,8.0,13.0,16.0,AFADADEDEFHCHCFGBGEHDFGHCHEGBGHFABHEACHBHBHBHGDGBAAAHAHCHCGGGCGEDEBCDDGBGAECEFFFBCHCHDE,False +876,10.0,18.0,8.0,11.0,7.0,15.0,11.0,9.0,FCHDHBFBGCDHAGCCHDHAGFFHBHEFAFAFDBBBDBDEACGGGBGFECECACHDBABFBDBDGEADADFFFGEGEBBBFBFBGBFAH,False +877,4.0,5.0,14.0,13.0,6.0,8.0,11.0,11.0,ACACGHADGCECGGGDCCCFCFBFDFDHDHDADHDHFFBHGHCHCGCDCDHDEEBGFDEHBHGEEBDFCCGG,True +878,22.0,17.0,15.0,16.0,16.0,19.0,13.0,15.0,CCFCHHDBEGEGDCFHFBAGFEDDFDCECEGBCBABADADBGGDBACAFAEABHHHFHCHDBFBDBDBEHHCHCHEEGFGFHAEAEAEADFEAABCFCEAHFGAAADFDFBFBEGCGCDAFAFAEDGBHBGFA,False +879,11.0,12.0,5.0,10.0,10.0,9.0,11.0,9.0,BCBCEAFGFGHBHBHDDFEFGBGHGFBDCAAGEHDBDGHGHFADAEEFEDEDEAHABABACAGHEDFAGEDBGBCBF,False +880,22.0,23.0,20.0,22.0,17.0,22.0,27.0,22.0,AFEFEHDHDHDBFBGBGEGBGFGFGEHEABABGGGABAHDHEBCGCGCFCDBDFEEAAAFDCBFHGHBCGAEDFDFDBCECFBAGAGAFEHGGCGDBBCCGBDDCDBDCFCAHDBAFFHCHDHFHCEEDHDHBHCCBFBAEAEAFGDCDHAHFHEHADAGAGAFBGCGHGFBEGG,False +881,26.0,17.0,21.0,13.0,20.0,12.0,23.0,19.0,BAEAGCGHGAEADABEEEGAAHHDDBDFGAGACCHHEHEBFBHEEEDFGFEAGHCCACGEFEDCGCHCGFHHBHBGBCCCDCGBGBABABFDDHEAEFEGGGGEHAHACACDGBGBGBEAFACEHFAAAHGHGDCCECFCBCBHDAAAFAD,False +882,1.0,1.0,3.0,2.0,1.0,1.0,0.0,5.0,DHHFADEBCHCHCH,True +883,7.0,3.0,8.0,7.0,4.0,4.0,4.0,4.0,GDEDCFHFHDHDEGEACDCABBGFACACGCFCDADBCAEAH,False +884,21.0,12.0,14.0,11.0,9.0,9.0,15.0,13.0,EHEAEGDDAGGBGFFAGHDHDCDCDCFCGGGGGAAEGCHEDEAEFHFAFGCBHBCCCCADBBAGAGHBCACAHAHBFEDBGBCBEDDHHABAFAHAHFBCAAAA,False +885,16.0,26.0,24.0,20.0,25.0,24.0,19.0,20.0,DFDGGAEAEAEDHGHGCCABBEECFCFGBGBDCGFFDBDECEADADHGHFDBDCEEBCGCGAFBFBCHDFDFEFEFHFHFHBHFEFHCHCBAFDFBFCAGAECBBBBEAEBGCECFHEHDCCEGBGBGFGFHHEHCHBDACECABABDBHAEDDCGGBBEFDFDCBAEHEHECG,False +886,13.0,28.0,17.0,8.0,23.0,25.0,17.0,16.0,GFFBFBHCFBBBCGCGEEBCBABFDEBGBGCACEHFHFHBADDCGEGEBHAAACFCEHBHBDAEFFFFDFDFEFEFECEBBBHFGBBHBEGCBEAEDCHEEEFBGHGECEHFHBABFCFCFCGCEAGDGAGAFBGGAFHHHBEBEBF,False +887,12.0,16.0,10.0,18.0,15.0,11.0,14.0,8.0,EEHEFGDCAFDGDCBFBFGFBEAFBBBAGFGBGCHCHCAGADCFCDBDEHEAEDGDBHBFGEBEBDBDADCDHDEABDDEDFCAGDGAGAFDEAGCGBEBEHEH,False +888,18.0,13.0,17.0,15.0,11.0,10.0,18.0,15.0,DEGEDEFAHAHAHGHGHGCGCFDDDADFCBGDGDCBABCBEACAGAGCEDBABDHFGAGAGDEEHAFCDCBCACBEBHCGBFAHAHCDFHBGBGHFHGHFBACEGEGCHAECFCDAD,False +889,22.0,5.0,11.0,9.0,14.0,19.0,10.0,13.0,HEHFADEFGFCEHEFDFHFAFGGGGAGAFADGDFAEAHBCECEDFCFHFCFDFDAACACABBFGCHEAAABCDHEAEABFHFHEGEFHAAAAACAGDHCHEFE,False +890,27.0,36.0,17.0,27.0,26.0,14.0,25.0,25.0,FHDGFABEECADAEBECEABAGHECDCDADGDADADEHEHGHBFBCBGDEEEEEBABABHBHAGCEDEDEHAHAGGCDCDHBABHBCACAGFCFGHHFDFDGBGHGAGCGFFBHADFCECEHBDBGBABACAHEBBHGHEHBBEDEFEBGBDBCGEDBBBBBEBDHDBAHGFGAEBHAADGHGDABFCFDAGBGDHD,False +891,18.0,15.0,22.0,14.0,25.0,27.0,18.0,19.0,FHFHEHAHCFEDCDHFFFHCCCCCCFAFGEAHAFGGEGEGEGFGFAEHDCDFHGAGEBHFHCHBHBEDHDCFCACGBFCDDEHBCEGAFABEBFDEGAFDCACFEFEDEAAGAGAGCBCDFEHAHEHBCBCBFBEEFEHGGGCEFEFEBEAFFBDADB,False +892,15.0,15.0,17.0,14.0,25.0,21.0,15.0,21.0,EGAHHHDHDFEAEDEGGGGAGFHFAFEEEHHBCBGHGBGDFAAEAECEFEDDBFCFCAGFFHFHFHBCFCDHFHCHADBHFGFGBEBHHEEDDCDGBCEEEBGBHEHEDEAFCBCECEBGAAAEDCDCACABEHHCFEFCFBF,False +893,5.0,2.0,1.0,1.0,3.0,2.0,5.0,2.0,BHAHAEEEGFGFACGBDAGAG,True +894,1.0,2.0,2.0,3.0,4.0,6.0,4.0,3.0,FCFCHHEFEFGGGGHDBEBFAFDDE,True +895,12.0,25.0,10.0,17.0,18.0,19.0,18.0,17.0,CECBHFGFGEBBHFEFDBDBABDGAGAEABCBGAGAHCEEHEHEHDDCDBFHFHEDFCFBFBFAGGGGGFGEHBBBHDHBHDEBEFGDCBBBDBGCAHHEGBGBCDFDEEEDEACAFFGBBHFHFDFAFHGBADED,False +896,16.0,8.0,11.0,13.0,10.0,11.0,7.0,7.0,GEDEHEHBBDADFDADCDCAAAHFHFGFECACAEDCDGAEAEBBCBGEACAHDBDEGFHFBCDCFAADACBCHFAFAFEGGDF,False +897,11.0,6.0,9.0,7.0,10.0,14.0,15.0,10.0,HDBFBGCFCGCGBGDEDGHAHGHAAFHFCGBGCAHHGFCFAFEBGHGBDCHCHDEEFEFEAEAEFEFGDGFAFACGEFDAGA,False +898,17.0,13.0,21.0,30.0,28.0,20.0,12.0,19.0,EDDBGCECEDBCBCDHGFECBGBEHHHEHFHDGDHHAFAHCHDBEFDADCDHEEEHEGDGDGFEDCACEDEAEAEFDFDFDADCCACFEFCFEFCBBHCCFEEDHDFGEGAFCFCACABABCGDEDAHEDDDDGDGFHDHDABFCFDFAHEEBEBEHEAA,False +899,3.0,3.0,2.0,3.0,3.0,3.0,8.0,3.0,BCEFGHGHGAGBGBGDFDCHEGEFAADG,False +900,16.0,24.0,17.0,15.0,11.0,13.0,13.0,18.0,DDCDADAECDHHHCHADDHCHCBCADAECGHGEAHFHGBBHDADAEHHFHGACACFCFBEBEDCGCGBBBBGEFFHFBBGCGBABABAHFEFBBECCHGFDFBFAFAHBBEBEACDGDGCBHBGBDB,False +901,25.0,30.0,29.0,16.0,34.0,19.0,24.0,19.0,FFGCECEBBBCDCBFEEEECGCABAFEFGHBDAACECGHDFCHBFBGGGBGHCHCBCECBGBEFDHBHBHCHAHAGABABGEGFCFBEGEBBCBCDHHHCHCHDBDCFCAEDHGAGEBEGEBEDEFFDBDEFBCEFEAGGFGEGFBFHHACACAEAEAEBEHEBAGAEAECGABADDDAECECFAAEDDAGCECBG,False +902,24.0,23.0,19.0,24.0,26.0,27.0,19.0,14.0,FAAAEACAEEEGEDAHEBADAGGHEDCABGFFDFDFEBEBEDEDGAHFDGBCBFDFGECFBFGFBFEFCFEDADBEFEFACACACAHADBBBEHAHBGBFAGBEEGGFGCGCFAFDFEBHGCAAGDGFHFCFCHCDCBFBGBCBEHFHCHCBEDGDACAEBDBHFHEDDDDDEAED,False +903,29.0,29.0,25.0,18.0,19.0,26.0,26.0,24.0,GABBEDADAGFHBHFHGCBCBDADGBGDGHEDBGBGDAEBEAGFGACEBEDADFFFBBBCFCGAFAHEHEHGBAAAAAAGGCCHBGBABHEEFHFHAHFBGCHDHFEBEGEAEDFGCHBHACADBHGDGCEDFFHFEFBCBABAHAEAGGFFCFAHADGDGCBCBCGCGCBCBCFHEHDFFEFHFCFABCHCDCAC,False +904,6.0,3.0,10.0,6.0,5.0,4.0,4.0,1.0,ACGCFCACDCHCDDDEDCGGEFBCBCBFGFEEAEDCAAA,True +905,3.0,18.0,9.0,11.0,14.0,16.0,4.0,13.0,DCFBBCBEBDBFFEFDCGHBHGDCFBFDEHEFBHBFEFHFHFGCAEHFAFBEHEHEHCACHGFDCBEFEHEBDBDBHBDEDEDBCBFB,True +906,16.0,25.0,37.0,22.0,24.0,10.0,28.0,28.0,DFDCDCEAEHCHEACBHBGBHCCGCECADDDDDDCHHHAHCCCGDECECEBECHCFCFBHBACGCBABCBHGEBBBHGHGBCBCDEEAAGAGDHFCCEDEDGDGDGBGHHDFFGEEBFAGHGFCBBGEHHBCBDBABCEAGACACGBEHEHCFDHAHEGGGHGHGACEDECHCGCGCDHFHBEGEDBCGC,False +907,25.0,18.0,28.0,21.0,19.0,32.0,30.0,20.0,GCGCEBHGCGCEDDHHGCCCCGHGHDHEHACGGGBGFGBEACGHGCFDFDCCCHCFDFAFAEAGABACAGACEBHBFGFBFBDHCFAFGFACAGDEHCDBGHAHBBDFDFCFAEBDCGFAHGHGFGFGBADFEFHBDADABBEAFHDDFDFGBGDEDEFAFEFEFGFAFDFEFCACHFHBEEECGCGCAAEAC,False +908,28.0,27.0,16.0,15.0,23.0,29.0,25.0,24.0,FAFEFGFBABHFFBHDCCGAABEBCACAEFFCFAGAEEGEGFGFDFHFHBAGFGBGDHBHBHBCGEGFAAHAHAHAEGEBEAHABCBDFGFGEGBFBHBDBFBFGFGHGHBEBEBDGHGFAFCHADEEECECFBACCBCDDHGGEHEGCAAFAFBDHHHDHDFDADGFAAEAFABEECGHHDBEACB,False +909,22.0,23.0,20.0,21.0,31.0,23.0,29.0,28.0,EAGGGDCHHHHCDDEDBCHAEDGBGAGADBHAFFHGBGBDEGEGHGAGDBEGAGCCHFHFGEGHHEAEBDDDDADHCBBBCACFCGAGECEAEFEGEDDAAEFEHBHBGBFCFCHGBBDBFBFDEAEAEFCDDEGFGFCECAGHGFGFEHHDAFHFHGHGHFHFEEEHAFBBBEAECGCBCBCEEAHACBFDFEHEH,False +910,35.0,20.0,17.0,22.0,15.0,17.0,23.0,20.0,BABABADGDFFFFFADHEEAEHCBGBGDGEGCACHEFAAHAHAHBHGHBABCBCGCFDFAFCFCEAEHEDGFGBAAADBGADADBDBECGGFCBDBHCAADAHAGADCGFGFGCGCEDAAEAHDEDBAGFGBADDDCDHHHCHAHDEAHGFAEAFBDHAGAEHBBGCGA,False +911,20.0,22.0,16.0,16.0,19.0,34.0,24.0,21.0,HHBBFFAHAHEFAFCDBDBDGCEEBFBDCCBCHDFAFDBDBFCFAHGEDBGFFFDFHACEDGDBFBFCECHCHBFAFADAFFFFFFFGFBHGHGHGHAFABACHCFGGGAFHFHGGGGFAFEEGHGEEEGECDGECBCBHDGDGHEHDBAGEBEAEABABFEGACHEBGFAF,False +912,14.0,22.0,22.0,16.0,10.0,16.0,13.0,11.0,GABHDHAHACDCBFFFECHFHEBEGABCEHEBBFBACHCHCACABEFFDBACDHFADAFBFBGGCGCGCHFBFCGDFAFGBCBCBDHDGDCBCBCGDGCGAGABCBCACEDFDEEFBBDDDEDB,False +913,20.0,27.0,29.0,23.0,22.0,31.0,29.0,18.0,GFGEECFDFAGEFHFACDEGCGCGHGHDHDCGCFDBAGAGAGDGHFDFBFGFGAGHDAGAFABDCFFECECEFFDCDCBCGDBABFFHFDDDGACHHDBEBEBFCEEBEHAHECBABGGAGDHDCEEGFCFBDECACAFHFAFACBEAGGGBGBCBHFCFCFCFCHDFAEBBBHBEBECFCHEEGBGBFCDBDBDBHGC,False +914,12.0,9.0,6.0,2.0,6.0,6.0,2.0,13.0,BFBHEHEHBADCHBAGFHFEBHAAACABHBHAAACECBBACGCHFHAHAHEHEFFD,True +915,10.0,12.0,24.0,13.0,16.0,14.0,13.0,16.0,CEBDBDBDCDCDCDBDAHHBFBFCFGFGEDFHCBCFGECFCEBEBHBCCFCFDFEHAFBHAHAHFCACHCECEHACBCHCFEDEAGACDCHCGAHCDEGGHEEFHAGGGECEGEHDGG,False +916,4.0,4.0,9.0,4.0,6.0,12.0,3.0,4.0,CECDADFBACFCFDFBFGFCFGHCCGBEHEHEHEFFCACBEFFFAD,True +917,15.0,18.0,12.0,11.0,16.0,11.0,18.0,15.0,AEAEAEAEAHAHAGEEFHGHBHBEDABABADHGFGDHBCDDFHGBEFFFAFGGHBDFCBEHECECGFHBHEEGDBEGEBBGDCDHDCACGFGHGCABABHFACCCCBGBGBGDGBE,False +918,14.0,16.0,12.0,30.0,16.0,18.0,12.0,16.0,DHDAEBFADADADADADGDFAFHFHDEFGBGBGBGFHCGEHECEAACACGCDDDFEBEBHBFAFHCDDDDFCFDFGHCFDHEFEFDCHBBBHAEDEDBAAHCEFDCDBDFDBEEDBDHEBDHDGFHDHEGGGCB,False +919,5.0,11.0,3.0,9.0,10.0,8.0,8.0,5.0,BFBHEEEBCBHEHGAGAGDDBDEEEHABFCFBAGDCDGDBDGAFEFEFDBDGGFBFBHE,False +920,5.0,0.0,5.0,4.0,1.0,1.0,4.0,2.0,CGAAFADHDCACGCECGDGDHA,True +921,24.0,17.0,18.0,26.0,23.0,31.0,24.0,25.0,EDEDCDADFGBABAGGFCFDFEGCGBHHECEADGDEDFDFDBEGEFCAGFEFEFDHEADHCHAHFHFHEGEDDDDBGEGEFBCDCEAAHDBAGHDHFGGHEHAHAHAHFHFDFBGBHCGAGFEFEFADACAFEBGCCDBEBADAFBGCFAFCHCHAFEFGCGBGCAFABCDAFBFBHDHFHEGDGHFH,False +922,12.0,3.0,17.0,8.0,6.0,8.0,19.0,16.0,GDFCHCHAADGBHCHAFEHCHCBGBCHFACAFADGGGGGGCGCAADHEHECEAEDDCCEGFGFGAGAHHGHGCDADCCHHGCGFHFHGC,True +923,13.0,7.0,15.0,17.0,15.0,11.0,14.0,5.0,GDDDHCCBCDADAEABADADGHFDCCACAEAGGDEEEDFHFBDGCHBFBFDGGBCDDDFCFCFEEGCFEFADADACAGGGGEGCCAEBEHEGEFECE,False +924,19.0,22.0,14.0,20.0,28.0,12.0,19.0,18.0,CGCDHBFBHGEBEADBDGDGDCBCDCHCEBHGEGEHEGDFFCEAEDGCGEGFDEEEEEBABCBCBCBCBGFDFAEAFDHDHEHFDAAHHHHEAEADAFEFEDBABDHEFEAGCBBFHDHBHBGBADHEEDBDEGBAEAGGCGHBEGGAAAEA,False +925,20.0,23.0,18.0,19.0,19.0,27.0,21.0,22.0,FEHEHEGDGCBDBHBEBCAGACHFEFHAHADAFGBGFFEGECEHDGDAHAHEDCCEAGFDFEGCCBGBFBFHDADCBCBFBCCHBHAHBDCECDFHFGFADCFFFFBFADBGGHADFDBBCBGHHHEHEHBAEAEFGBHBHGAGEFEFGFGFDCDFBFACAGAEADGDB,False +926,8.0,4.0,5.0,5.0,6.0,5.0,4.0,8.0,FGFDECECEADFBFBHEHAHADAHAEACGDADHHHBHFACBEGCG,False +927,4.0,9.0,2.0,4.0,9.0,4.0,11.0,2.0,GHGBGDGBGBEAGFGBBBBDDEBGFGEGEDECEAEAGBFCEHFAE,True +928,19.0,13.0,20.0,26.0,25.0,21.0,11.0,20.0,DDDFAGCFCHADFCCECECFBEHDBEBEDEHEHCFAEAEAEFDFBFADAEAEAEADHDFDFGBGBADEDBHCGCFCBEEAEHECFHAGACCCDDEDHHHHAHDDDACGHBACFCFGDEFEBHFHFCDDDHDACECBDHGHEEFGBGFGFEDHFBA,False +929,31.0,26.0,25.0,22.0,30.0,19.0,16.0,16.0,GADBEEEAEAHACCCCFGFEHBGBGCFCFDDADGBAAAFEFAABEHADFDFACAHBHGEFBAAACFCGABEGFABGFGEGFBFBEBFDEDEHGFEECHAHADADADCHEHEBEDABHBEACADBDBDGDGDCDCACHEHGCEHDCEABCFAEDFDGCEBFBAAEHEDEBCBCBCBCBEEAEBCHC,False +930,5.0,6.0,16.0,9.0,2.0,8.0,6.0,8.0,FCFCBBGDGDBABHCHCGEBEDDGACFCFCFCHCGCABHCCCCHFHCAGFHHCAFDDDDD,True +931,13.0,10.0,13.0,5.0,17.0,8.0,8.0,11.0,AEAEAHAEECBHBHGHAEBFCEEAEBEGCHBFBGEGFACADAEGEDBFCCHHBHBHFHCGEGHDDCDCACAEAFBCGCFEFECEA,False +932,13.0,15.0,7.0,16.0,20.0,10.0,5.0,18.0,AEABBCHEBEHEFEDEAFBHBADFHHDBDEHBABABABACDCFEFHFEGGACEDEHEBBAFGHCEDEDBGCHHDBDBEHCHDADGDEDEDHFEEEAHAHFHFHD,False +933,4.0,6.0,3.0,4.0,2.0,6.0,4.0,5.0,AGAGAHBEEDCGBGBCBDFDFDHHAFBFHFCBHF,False +934,5.0,12.0,3.0,2.0,5.0,4.0,9.0,11.0,CEDBABACFFGFAEAGCGBGHGHBHGHEBBHBHGDFHHHHBEBEAGBBBGH,True +935,8.0,6.0,1.0,11.0,7.0,1.0,14.0,7.0,GEBHGHGDBAEEDAGGEGDGBGBHHHHDDAAAAGDGDGDADABCEGEHEDDFGGB,True +936,12.0,13.0,17.0,16.0,15.0,22.0,16.0,19.0,HHEDDDDGDGAFACACHCFEEECACADBGHGFFFFFFEHEHCAGBDFEFDFEFEHEFFBBABFCHEGFGDHBCBCBEEAHCCECDDBFBHCHFHFHDEDGGGDGBGHCBGAFDGDGCAHBCCHGHFHFAA,False +937,3.0,4.0,1.0,4.0,2.0,0.0,0.0,2.0,ADDEDEHBHBACADBB,True +938,5.0,10.0,7.0,7.0,2.0,7.0,13.0,13.0,FCGGGHHAFEFBFBGBABAEGGGGCFCFHBABHHDHDHFHACDBBGHGDGDHCBDHCHGBGDHC,True +939,0.0,2.0,2.0,0.0,2.0,1.0,2.0,1.0,CGEGEBFBHC,True +940,15.0,12.0,17.0,12.0,18.0,16.0,21.0,10.0,DADACBCEGEGCCAHFCDCDAEACDCFGDAEBEBEACABEGGGABACDFDCGGFDDHCGFGEGBCBDEDGHGFEFBFGGCBCEEFAFGFHFAFHGHGCEFEBHBHGEGEGEFAFAHACBHE,False +941,21.0,9.0,18.0,19.0,23.0,21.0,20.0,26.0,EGEDHBHBHGHGHCEAAGBHBDDDGGGDGFGFEFGFGADHEFEAEAFAHAEAHBFECDCAAGDFAFHEHCCDCEFHFHFAEAHACFCFCHCECEHDDGDHDHDADEBHFEGAAEAFBHCCEGGDEDBCHADAHFBFCFCGGEDECFHGAGHECEHFH,False +942,23.0,23.0,25.0,23.0,16.0,18.0,18.0,24.0,CAHDBDHDEGCADHGHGHGHFCDCHCDFGEDEDHDHBHFDFEEADAEABFFGFGACFBBCFCBBFAHCHCEEDCCFHACACABHBFFFDFECACHHEGDGDEDBHBCBHBHADABHBHBCGHACBCBEBABCGEEFEAEAGGCDDDDAGAGAHBHDGBCFGFDCAGACAB,False +943,9.0,5.0,6.0,3.0,2.0,3.0,4.0,6.0,DBDHCFFHCEAEGBGBGAHCHBBAGFCAHAHACADACA,True +944,1.0,5.0,5.0,2.0,2.0,3.0,5.0,5.0,EGGDGHCBBAEGHGCFCFBHBHBHCFCD,True +945,23.0,12.0,17.0,23.0,21.0,25.0,31.0,23.0,AHAHBHBHCHCEDDFCACDCDFGFBHBCCGFGHGAAHDEEGECFAHAHFHDHEADFGCGCGFGEADBEAEBEDDBCBHAAFAFAFDGDHABAEHDHGEEEHDADGFGHGFEFGFCFAFHFEFADGGEGEGECFDHCHDFGHGDGCAAGAGEGFDBGCEBGBGDEDHFFCFGAGDG,False +946,7.0,6.0,9.0,5.0,3.0,13.0,9.0,7.0,BEBECFHFHAHGCAABCCFGBGFFCFGFBFDFGGAGHGFFFFDBCGHHCHCDDADAEAC,False +947,12.0,14.0,22.0,9.0,8.0,15.0,19.0,16.0,GGGGGADFDBBBCHGACAHBFGHGHGFGCCFDACHGHEFFBCBGEGDGFHHHBHDGDCCCCGBFHACACECDCFGBHBHBCEFECHCBCBCHGFGDAAAADAEEFCFCACFFEHB,False +948,23.0,29.0,24.0,18.0,9.0,25.0,25.0,32.0,BBBHGFAEAEBEBCFCFAFAFCFDFBHBGCHFAEGDACAGBHCHFDBCBGGCCBBHHABDCFGHBDCDBDGFBCAFAHHGHFHEHACEGDABGBGHABABGHHHFBFCFHFABAEAGACBCFHHBABCBCBCACFCHGHCHBGBHDDFGAAFFFEDDDGDHDHGHGHGHDHGHGHDCDCGFGFEA,False +949,7.0,6.0,5.0,7.0,7.0,6.0,6.0,12.0,HHCHADDCGBGFFHDHBBCHCHBFADAEAGAFAEAHBHEEEEHHHBGDGEGCDFDF,False +950,24.0,23.0,22.0,11.0,20.0,30.0,30.0,14.0,EHFBFBFBCCFCAAACEGBFAEEBHCHFHEAEAGBGHGHGCGCFEFAFBEAGAEBGDGCGHGHBBGBGBFBFDFECAGGFEBEGCAEBEDGHAFBHBFBDGDGFGDACCGCECACAGFCECHDFBCGCGFFFGFGCBCGABADFBHGGFGDHDEFBHCAAAAAAFFFFFDEEAE,False +951,16.0,19.0,15.0,15.0,20.0,28.0,15.0,17.0,DGGFECEHGHFHCBCEHGDGCBCGCEEFAFAFAHEHFAABHEGDGAGBGEEBHDHBBCBCHFBDBDBHEDFCAEAFFFDFDFAGBCBDECFFFEFDFBFGFGEECECEFEFEDHGCDAHAEABBDGFBFHHBHDAFHFCFAFABA,False +952,9.0,0.0,6.0,3.0,8.0,5.0,2.0,3.0,EFACCCFAAAAHFFFDGAAEAEHGHECECEDECEAD,True +953,2.0,1.0,1.0,1.0,6.0,2.0,3.0,1.0,ECEHDAAGBGEEEEFGF,True +954,11.0,9.0,7.0,13.0,13.0,4.0,8.0,8.0,CADHDHDFDABBEACAFDBBHFHGAGECBGEGEGEBEHEDEAHBGDADADADFDEBEDDCAABHEHCGEGECC,False +955,17.0,19.0,17.0,18.0,12.0,19.0,16.0,32.0,GFGFAAGFGAHADGGHGEBABFEDBHBDFHHHHBGBHDHDEAACBFBFBEAEHCDDGDFHHEDGHGBGBGADHFHDHCCGAEACDCDCAHAHFHFHFHDBDADHCCCHBACACBHFHFEFECACGEBBFDHCHDHBHEFGCECHFFBHBH,False +956,21.0,23.0,17.0,24.0,20.0,16.0,15.0,22.0,DADEHFHDCBCBCAHGBGFDFDGBAFDFDHHFDBDBACACFEHEAEAHAEEBAGCHCFCFAHAGDGDADADHHGHGECCFCFGFCHAHGDGBCCHADBDEAHGCFBHBHBHEEEEEHEBEAEGDBBFBHHCDCEBBBDBDBAADGFABADFEEGEDDB,False +957,10.0,10.0,8.0,10.0,12.0,10.0,10.0,2.0,FGFBFDFCGGFGABBBDGAAAFHFDGDBDGDEDECECECECGBAEHECGDACEBGBDFCAEAFFEDEBABAE,False +958,23.0,37.0,29.0,27.0,20.0,20.0,23.0,19.0,ADBDBAFABHBADGGCCCHFHGBBDDCACACBBAGDHDHCHFECBHFEGEBEDCCFEDEFBFBCBCBHEHBGDCDGBGAGAFFGCGEGAADACADBGFEDGBGFDBHBCAHEEFFDCDADBDBACDCDCDBHBHFEFHFDBGBGEFHFHBACECEDEBCBCBCGCGBBACAGEFBFBABGDGDHEHEGBCDCBHEAAA,False +959,12.0,18.0,18.0,8.0,12.0,10.0,17.0,15.0,BEBEBGBGBHBCBCECGCGCDCFGGHGBCHEACCCEFGAAAEHBHEHBGBHAEABHGFCFCDCEABACAHEHCGCHFEAEGDBDHDCGFDCDAHBHGFDFGGGHFBBBAF,False +960,6.0,8.0,14.0,11.0,10.0,8.0,6.0,15.0,EADADHGFDEEHFHDHBHBHCECDFDBDECHFFAFGFBEDECBCECHHHHGCGDGDHCCCCCCEEDHHAHABCGFABB,False +961,20.0,29.0,25.0,20.0,25.0,26.0,26.0,18.0,BHBEFEABGFAEGDGDFFBDHDGBGBFFFHEEEEEDFAFADABGGCGCBCBAFCFABCCHEHGDDEDEGFFAAEEEEAGCGAGHGFDCCBCHGACACEDHGHGAFBFBFAHEBEBEDGBHCCEAEADDDHDCBCFHAHCHBHBFBFBGGGBHECGFGECBCBCDHDBBFDCACACBFGFGEGCDEBFBF,False +962,27.0,19.0,27.0,18.0,20.0,32.0,29.0,28.0,GEGECAFAHHHHEAEBDBDCHHGHFEFHDBFAFBFDGDBCBCGHGHFCFCFCFDEGADHHCCADADAGEHEHGACCHGHBHEHCHCHFECGCFAFBFAFGFBCAEFCDHAGFBFHGEGAAHGFGEDEACDCFHDDCDCFCHCGCEDGHBDAAFAGBFBFHEGAFACADEFEBEGGGCGCBBFBFGAGAGAFABAGFBEHF,False +963,18.0,20.0,27.0,19.0,14.0,17.0,15.0,25.0,FFACCGCGCDDHCHCDGGGEHFBCBHFCAAAAHAGFGDGAGDGHFBDEDHCBCACACGCGAFEBBCECEAEHEHBBCHHHHAACDCDBDFCFBFBHCHBHDGCEEEHEDGBBBFEFHFHDCDBDADAHFBCBABDCEAHHDACFCGHBHFHDCFE,False +964,12.0,10.0,8.0,9.0,12.0,10.0,10.0,9.0,FGFAEAEAGADFEECEHBBBAHAEBECECAGGHBAAGEHFHDHAEFDFECDCBFBFBABDDFDGGFGCCCEHAHBHGDGD,False +965,17.0,22.0,24.0,31.0,26.0,22.0,22.0,27.0,CGCEHFCFCEBDBDBEHEHGHGHFABABHEHFBEBGHDHDFCBDBEBGGCHCFDFHEHDHDGDFFBCAHAHGEEFHBHBEBADFFAFAHDHGAGAHEDDHDEBEFEBEFHFHACADDDFDEEEECCCDAGADBGAGFEHBGGHDCCCDEDGHCECDDABFBEBCGEGCGCFCDCAAEDCBGHGDFDGDCDF,False +966,27.0,18.0,26.0,14.0,26.0,27.0,37.0,24.0,AACDCHCFGHAHAGAGACFHEHABFHFAGHBCBDBFBFBABFHHHFHFCEDEFACHCECFGFEFECGDGHGCGFGEHECDCBCBGBECEDFAEECAGGFAFBHEFDGBGEGHFEEGEHCGEGDGDGDFCCCCHBAEACHGHGAGHGAGEHEGEGBCAGGGFABHDADADAGAFHBEDCFAEECFGFGFGCGABEFGABA,False +967,19.0,30.0,23.0,20.0,26.0,19.0,25.0,21.0,BBABCBGGAGFDFGHDHEGBGCGBBAFDCBCEFHDCDFBCBGEFBHBEEEEEBADAHAHBGGGEDBFBHCCCECBGHDHDFGBDCDFBEHECGBGBGFCFAHEHDGEGEFDFDECCCHCHEGEGHGBCEAGABEBABABABADADABAEADCCEFBABFECDFHFHCHFEFCGGEHEHGDADH,False +968,22.0,15.0,29.0,26.0,37.0,20.0,22.0,24.0,AEGBABEFGGEGDHDHAHEFECEFACEEACHBECFBABCDCACAHGHDEEFECECDAAAEHGHGHDHDFGFHCADFDBDEDEAEDEDEDEDGGECEABBGFADADEHGHFECBCAEAEGECECAGDBEGAACCCCCCBHEGECDCDFHFHFHFHFCGEGHBDFEBBBGECHDEFEHHGDADCGHGDDCEFHFCFC,False +969,16.0,6.0,14.0,15.0,9.0,8.0,13.0,13.0,HHHHFEFDDCAHGGEGDGDCBBHCCDADGGHAAADADFDFDGDGDGABEBAFABECDHAAFAFEFGDGCHEHCDCGCEEHHHAEACCCCBCGAA,False +970,21.0,25.0,9.0,17.0,8.0,13.0,18.0,16.0,GBGHGACACAFHFBCADGGGFGFGAGAGBBDBGCHHEHEBFDEABGDGDGBHBCDFFFFHFHAHBDACAHDHCCGAEADBHBDFABABABEBEAECGGBHBHDFBBBBAFDDAGBHHABDDADADBE,False +971,9.0,10.0,11.0,9.0,15.0,9.0,14.0,12.0,EAEDFCFBFBAGHGHGDGBHBGFHEHCFAFAGHECGCHCADAHCEGDGCGBBBBDBDEGFGCCFHEEEHEDEAEDBCGHGCADHEFEAE,False +972,18.0,16.0,12.0,13.0,15.0,19.0,12.0,21.0,BEHFBBABAHGEEAEAFAFCDEHFHAHCGCFBEAAFGCABHHFHFHCHBGADCDHDHCHCEEAGBFDFGADFFFFBFBGDGAGAEADHDHDAEEEBCBCBHBDEEHGFGFBFBDEHCHGHAHFCAD,False +973,27.0,25.0,26.0,28.0,24.0,17.0,20.0,27.0,HCHEFEACGCFDFGCBCHADFCFBADCGHBHCDDDCBAAHAEEDADGDGHGHGHGDAAEBEHAHGDADADEBEHHCEBADAHHHHCHCAAAHBFBDCGBFCHEEFBFBFHAEADDBFBFBDGDEHEHBHGCGAHACECAFBFBEEEBECEFDCCABDBDEDEGAGADEDEDCFBBACHGGFGBGCGDADCHCBC,False +974,2.0,9.0,5.0,14.0,10.0,16.0,13.0,8.0,HBEGFBDBDHEEFHFEGDBFBFBGHFAFDFGFCFDBDBDHDHBGGCFFEGEGECADGFECEHFGDCDHDEDGFGFGD,True +975,7.0,10.0,11.0,8.0,6.0,8.0,11.0,11.0,CECFCDCHGGGGHGAFCECEAECDCGHHBADHDHDBDBFBFDAHGBBBBBBGCFFFAAEHDFCHGAGHCHGE,False +976,22.0,16.0,20.0,24.0,18.0,27.0,21.0,14.0,GDBDHEGEBFHFHDDCFCDAAGEFBFEDBAHGBGBGDFEBBADGHGFABAFAFDCDCBCAHADDDCAHECCDAAFAFGHCCECFGECECEFDHCHAHGBGBGDECECECEAEAEBFBFGHGHAADDFDBDGAFCFBHACAEEFGFAFDFDFGFGDCDGGFFF,False +977,16.0,17.0,23.0,22.0,27.0,15.0,19.0,22.0,EEGGFDFHCHEEAEDEHEHGCEFGBEBEBHBDDCBAHAHDGDAEGEGDHFECBDDDHDCGCFAAAAAFCEHBBEECEFDFDBDBCCCCEFEGAFFCFCFCEBEAHAHAHAGGHGHCHCBGEDBDGEEHCDGHBCBDAHFHBHFGGDHDEDAGECECBCDCG,False +978,5.0,8.0,11.0,18.0,14.0,13.0,11.0,18.0,HFHDBAGHGEFEHCGGEGDAAFHFEFEFDHDGCECHHEHEDEDHGHDFBFCDHHHAHEHBCBCBCDCDGDECEDGDEBFGDCDEBGHFBFDCDFHFDA,False +979,22.0,10.0,19.0,14.0,19.0,26.0,19.0,18.0,HBGDGHGCGBGEFEAEFBDEHEAAHGGGGHDHDHFGEABAFAHEHCACFFDFDFAFECGCDCDCDCFCHCFCHAHFDCBGAGDEHBGEAFAHAHEFAGHEAGACEEEFFFFEFHFBFCFBACGCAFAFCBEFEGEFCGBDDDCAAAH,False +980,9.0,10.0,16.0,13.0,13.0,13.0,17.0,6.0,CDCEBDGFGFACEBDHFCEHACADBDBHBCBGACCECEFEFGFGACHCACDEEGGGEGEGDGCFFFGFDBDFGGAGAHACDDDDGEGFCFCEHBBEB,False +981,19.0,23.0,15.0,12.0,16.0,18.0,17.0,17.0,ECEDHFHFHFAGAHBHDAEFGFBEHGBGBCBHBCEDGDCBHEAGADEGHFHDBBABEBAGAGCCDADHDCGBBBEGAGAGEBBBGFGFCCBFBFEGHAEGHFCFCFCACEDHDAAAAAHDBFFHFEFCBCBEBEFHA,False +982,21.0,16.0,13.0,14.0,20.0,12.0,19.0,12.0,EBEBGBGDGEGECHCHFAAEHBCAEBHBECECACGCDCDCDBABAFABGHGHAAEAHABDEDEFHFGBCDAEAGFGECDHGFGDDDEHAGGGEGBCFDFAFBEGECEHAFDFGABADAGAEBHFAEB,False +983,22.0,16.0,20.0,28.0,16.0,18.0,28.0,14.0,CGCGBDCDCGHACGFDFDGDBDCFEFEFADAECBDDDEAEAEAHAHABGDFAAGFGFGCAAGEDEGFDFDCGBGAGBGHHHGABCBDBDFDFCFDFGCAHAGACABAFEFAGEEDEHBCCHEGBBBDBDHGEDCHCEFAHHGCDHGGFGDGDGDBEGACDCD,False +984,26.0,22.0,19.0,22.0,24.0,27.0,32.0,24.0,ADHHEFAFADABADAFABCGCGAGFGFEDADABEFHFHGHDFGEGADCCFHHHGHGEFCFCEBDGEFEFEGAFBFBFAHGBEBEAGDFAHABAEGHGCECEHBHBDCFFHBAAGAEAGBCCDCDHDHDBDBGBEDDDCBBFBGEDFDHGEGEGEAFAGGBGBHEGBGFGDECHFAFEHHFCGCGEGCCHCHAAFDG,False +985,7.0,9.0,7.0,9.0,13.0,11.0,7.0,5.0,FCBCHEDFAFHEGBGFAEAEAEAFGDGDBDBABAFGEGDCHCHEEBFCEEHEBEDEFFDFGBDBCCFD,False +986,8.0,13.0,17.0,13.0,13.0,11.0,14.0,10.0,HGEDFDFDFDHDHDHDBFEFAGAEBEDGDHHFBBEEABBBFBHGHCCBCEEGECFBACDCDAAGCFCGBGFFEAGDGHCCDGEGCGCGCHCECBCACEB,False +987,20.0,12.0,18.0,25.0,18.0,18.0,21.0,30.0,AAADFHFAADFECBCECEHEHADCDGDGDCFHFHGCGCGFGFCFHDCAHEEGDGCECHCHEBFBHGHGEFHBHFGDADEDHDAFADEHBBBEGEFHADFDBCGDHHGHGHGDGDHDGDFCFEGGFGCAAEAEBHAHADBHEAADHDCECHDADHCHBHFHAB,False +988,20.0,13.0,12.0,16.0,10.0,14.0,25.0,12.0,BBBCHGHGAGFGHGDCACHCHCAAAAAAEHBDBAFDGDGDFCGGEBAFDEDEHEDGDEDADABCBFDGAGAGHGAEDBGGGGDGBFBHAAGBGHDFEFGAEECCGFFBFGFGHCHAFFCACD,False +989,12.0,14.0,12.0,10.0,10.0,5.0,11.0,8.0,AEFEBABAHACGFBABGBGDEDGDEBBCBCHCECBCACDCGHGHGEACFCBBBEFGDDDCDBDADGEHAACHEGAGFBEHAH,False +990,22.0,22.0,18.0,21.0,13.0,23.0,11.0,18.0,AHAHEFFDDCDFGHDFDECHDHABEBCBCEAFBGGGGFCHCBCHHBEDFAFABCHCBCBCBABDDGHHDBFGEEDADFECGBAECEADADADAFFDFBFBFBFAHDFDBHBDEAEFHFGAHAHAHACCBBABGCGCFHFAFDFDEBCA,False +991,10.0,6.0,7.0,9.0,6.0,4.0,5.0,5.0,FDCBCGFHFHBBBABGDFDAGACACEEECAHDDGDEAAADADAECECHDBGH,False +992,9.0,13.0,4.0,15.0,7.0,15.0,17.0,13.0,DEAHFHGHBEGEBBGFFFAFDFDHDGDGHGHFHFDDDCEGBACGDBDGDEHEHGHGBGBGHFBABABFFFAGADHDGGGHFACBFEDDBCAFB,False +993,1.0,1.0,4.0,3.0,4.0,6.0,1.0,3.0,EFEFEFAFCEGDFHHHDFCBCDC,True +994,16.0,14.0,21.0,15.0,11.0,19.0,16.0,24.0,AHACCCDCAAFBFEFBDBAAGAHHCHDHEHAHEHEBGAGAFHFCGCEFEFEDACHCHCGGGFDFCHCDDDHDHAECHGBGBEHCFBDBGGFHFGBAFHFCDADCFCBCBCEHAHFHBCEGGGFAHBHDCDFHFGDB,False +995,7.0,6.0,13.0,6.0,12.0,13.0,4.0,9.0,CEAFHCHFHECCHEACFCFGGAGFCHCHFAFEDHHCECFBDBDGECHDFEEEEEEBABACFCFDFDFBAB,True +996,4.0,9.0,13.0,8.0,5.0,3.0,3.0,5.0,AGAEADDCACBCBCDCDEHECCFHEDBCBCDDDFEBHBHCCCBBFHGCGB,True +997,3.0,1.0,1.0,6.0,4.0,5.0,7.0,3.0,DDDFHEHCGFGFGFGEDAGAEHFDEDBGAG,True +998,18.0,17.0,15.0,15.0,11.0,15.0,12.0,20.0,EBCFCHHAACHCHCHGBCBCBCHDADAFAFEFDFDGHGHCBCFFHCACDFAFAHAEAEAEFEBCHAFBHBFGAEDBDHDHFBCDEAGABBHGADDBDBDHHHEBAGCEEHFHBGGDGFGAGDB,False +999,6.0,13.0,8.0,13.0,6.0,19.0,12.0,12.0,GDGCGCHCAFGFEFBFDEDHFBFBDBGFDADBFBACGBGDGEFBHHHHBDAFGFGBGHCFFECEFEFBAHFDFBFDAHCHDHCHDFDGB,False diff --git a/tests/results/nb_gm_002_2back_240trials.csv b/tests/results/nb_gm_002_2back_240trials.csv new file mode 100644 index 0000000..1c50201 --- /dev/null +++ b/tests/results/nb_gm_002_2back_240trials.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,ralph_skewed +0,30.0,39.0,31.0,30.0,32.0,24.0,27.0,27.0,False +1,33.0,23.0,27.0,32.0,37.0,34.0,25.0,29.0,False +2,31.0,20.0,37.0,28.0,31.0,32.0,26.0,35.0,False +3,27.0,32.0,39.0,24.0,25.0,34.0,35.0,24.0,False +4,34.0,24.0,38.0,28.0,31.0,29.0,28.0,28.0,False +5,29.0,24.0,36.0,31.0,32.0,32.0,31.0,25.0,False +6,25.0,38.0,28.0,30.0,33.0,30.0,26.0,30.0,False +7,27.0,30.0,30.0,29.0,32.0,26.0,33.0,33.0,False +8,24.0,36.0,32.0,23.0,30.0,29.0,35.0,31.0,False +9,35.0,34.0,30.0,29.0,35.0,26.0,23.0,28.0,False +10,30.0,25.0,33.0,31.0,27.0,37.0,30.0,27.0,False +11,28.0,28.0,29.0,26.0,28.0,27.0,34.0,40.0,False +12,35.0,27.0,30.0,29.0,26.0,30.0,36.0,27.0,False +13,38.0,27.0,31.0,27.0,34.0,23.0,27.0,33.0,False +14,29.0,30.0,28.0,35.0,19.0,30.0,37.0,32.0,False 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+996,0.0,3.0,3.0,4.0,1.0,9.0,4.0,0.0,True +997,2.0,2.0,7.0,2.0,1.0,4.0,1.0,5.0,True +998,0.0,1.0,5.0,2.0,3.0,7.0,4.0,2.0,True +999,3.0,4.0,5.0,0.0,6.0,1.0,3.0,2.0,True diff --git a/tests/results/nb_gm_002_3back.csv b/tests/results/nb_gm_002_3back.csv new file mode 100644 index 0000000..08f6266 --- /dev/null +++ b/tests/results/nb_gm_002_3back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,8.0,9.0,10.0,10.0,12.0,10.0,10.0,18.0,BAEBGEFGHBGFBHAAHEAFEAHDFGGGDCGECFECFCCHDCHEBBFGHEEHGBACBFCHFDHCDBADHHGHHEHFDHCHEDADDHE,False +1,9.0,7.0,10.0,4.0,4.0,7.0,8.0,17.0,DBFCHAAFAEBCGAFHCGHCEHCFHCBHCBHFBHCAACBGGAHGDEDDFAHHHHAHEBHGCHGHFG,False +2,9.0,7.0,13.0,9.0,10.0,11.0,15.0,18.0,DHFHHEHHECHCFDEGEACHBBHDGABGACGAEFHEGHCGHDAFDGFDGEEBFGBAGFGGFGHADHDFCBHAGHCECCFFCECCGCDHAHHB,False +3,8.0,10.0,7.0,13.0,4.0,6.0,10.0,10.0,AHBADGDGGAGCAEDACHACHCBDDHHFCBCHBGHBFHBDDGDDADBFDFACHGBHGBEEDDEFBGFG,False +4,15.0,14.0,25.0,14.0,12.0,14.0,11.0,13.0,CCECCDCCDBBGBCFCCDCCDACFECBEGBFGBEABEADADHCDECDAGHHGCHCCHAGFDHFABAHBFBGFEFFDHFEFACHACGACBAGBDEEHFCGABHFDDFEDECCHCABAGH,False +5,11.0,10.0,18.0,13.0,21.0,18.0,16.0,19.0,BHADHEFHGHEFHFCEBEAFEAFDADCAFEFHAFCBHGAHGCGECFFFBEFCFHCBACHEDHGFHGFHDDHDDHCFHCHEAEDDDHBDCBDEGGECGECBEGBEFBEGEGCEGCGAEAHEGCCCFG,False +6,11.0,14.0,16.0,20.0,10.0,15.0,24.0,14.0,BGGBHGBEGAAGHGGBFEHFEHGCGDCGDHDBBDFDDGDDGFFGCADFECFGAFHADEFCFDGFHFHGBHGAHFBHCCEDDHGDEADGCGGDHBDBADGAECEHCBGBBGCBCCDCEACDACFF,False +7,16.0,20.0,19.0,22.0,15.0,27.0,25.0,20.0,HCFHAABBCDDDFGDGCDEDGHAGHEHDAGEABEBBDGDGGFGEAGFCGFCFBEFBEGGHDFFBCFCAFBDFBDFGAFGAGGDCDDBHDHFFFEFAEBDGBHCBDCFGCACHEBHDBHEGCECBFGBHGCHACEAGEAHACFCHFGDFGDFBFEHCDHBFHFAH,False +8,4.0,10.0,2.0,8.0,5.0,8.0,6.0,5.0,HAGFEEABEAHCFBBBBBBBFBHHGHFADDBEDGDDGDDEFCFFGDFG,False +9,11.0,23.0,19.0,24.0,13.0,20.0,28.0,13.0,DFDDFDGFDGCDFFDFEDCCDEGDAHEEDGGGGDAGHFBHFGEDAFGCHGFDBCDBDEBCHDEBGEAFBCHEFEAFBHFCCGEDGADGBCBCDACGCCGFAGBBDCGDBBBEBBECHACFAGFBGABCBBGFHHFHHFGHGGDGGBGBCDB,False +10,10.0,15.0,13.0,9.0,5.0,13.0,10.0,23.0,CAHCFDCFBGFGCFHBHAGHABAAHGFBAFDFBDBHDHCBGEFGDCBDHDEABHHHHGCFCEFCDHCFHBHHGHHGFHGBBABCABCABHEHEFHDCH,False +11,29.0,21.0,32.0,27.0,25.0,25.0,8.0,18.0,HEFAEFGCBEBDCBEADAADADCADABDHHFFEDFBCHACAAFBAFDAFDBCCCFDCEACAACEABFDCFDCFHHFBHDEFDAFCABGAEFDCDCCBCCDCDFAEFDCGCCECCBCBHDEGACBAHBEBEEFDBDHAFHAEAEECEGGHDBHDHCDEADEAHEHFEBFCBAHBHDEGAEFFCFCG,False +12,28.0,27.0,32.0,14.0,15.0,33.0,26.0,13.0,FFFAAFBAHCHHDHGCBBCEBFDGEGBFAACBACBACBAGBGBAGFFGFAHDGHEEFCAAHAHHECFBBFACFACAACDBCAEAHDFHFFCFFEFCAFBEFBFCBCABDBGGFECFGCBCDGGBGFDGDABBCCBEFBEFBAFDACGCCEHGAFCABDGEDFFDCFDGFGGCGGEEGCBGAAGCCCHC,False +13,29.0,16.0,17.0,15.0,16.0,11.0,15.0,11.0,CBECBEFBDDCDCAACAABFAGFEGACCECBEHBEGADFADFBBABCAHCABAABHEEEACEHHAGHABACGDHGDFGCHGCAGDAFAAFCCFEAEBAEDFDDGEABHAGAAGDGBAEDHHGABFEGDCD,False +14,17.0,24.0,25.0,11.0,18.0,20.0,15.0,30.0,DDCDHHAABGECDACBCCFHGEDGAHBABBHFBFFBCFHCHECHECACABHHBHEBHBHDCHCFBAHBFHBEBEDCEDEABCHCHFCHCAFBFBBHGEHGEHGHFCHACHCGGCGCDECFEGHEDFBAFGEFDAAHAHHGFHFABGEBGABGFFEFCEBC,False +15,8.0,6.0,1.0,3.0,4.0,2.0,2.0,6.0,EHBEDEHGEGFABBADBAHCAHAABDAHHABF,True +16,20.0,17.0,20.0,17.0,21.0,21.0,26.0,21.0,DEHCHAEHFEDFDHFCHGCGGCGAFBDDBDCFGEFGEFCEFHDHEFFAGDGDEGAHGFECFACFEEHBEHBGHBGHBGCECEDAHHBGFCCCADHAGHDEDBADGHEBDCHCCFAGEAFAABGABAHBAHBGHCACBEFEGAEFCECBGFDGFDGAGBAGBFG,False +17,12.0,3.0,7.0,9.0,7.0,12.0,9.0,8.0,ADGAGCADCFDFHEFDGHCEHAGGCDAHDCHDAHAFDAFEGFACFECFEBFGBAGAFFAEBDEHGHF,False +18,18.0,19.0,24.0,16.0,21.0,13.0,23.0,20.0,GGEGFBDFGDGEDAHGFBGHAGCDGCAAAHACECDECEBBEDEEDECDFDHBCCDHBHHACBACFHEAEEGHEGDEGAHBAFBEEHCBHCBGGFCGECGECBCAFCGHCBHFHHFHDGGAAEBFCBFDBCBECDCADCACGBHGEHGBFGADHA,False +19,10.0,14.0,15.0,8.0,25.0,14.0,11.0,20.0,EEEEBEEFHEHEEFEEGHEAFFAFHACGDCDDCFDCBDCBFFBCEAHEAHGCGGHGCHEEAEAHEAHEHHCCFGHABHGFGCHGCFDFHEHBBBDFBFBCEAEBHCDGCEEEHBBHB,False +20,16.0,9.0,19.0,17.0,10.0,22.0,10.0,24.0,HFGDDAFEAFEDCGHAADEHDBHAHDCGBAHBECEFFFFFEFEEDHEDCACEGHBGCFGAGGABDHFCHFCHCCDCFHHADFCFFCFFCBFCDHHHHDFFGHHDACDAFDACDCBHCHHAGHABHAB,False +21,6.0,10.0,3.0,4.0,7.0,3.0,3.0,4.0,EABBAEFHEFABAACHDCDDEFBEGHEGBDABHBBCBGEB,True +22,6.0,11.0,12.0,6.0,9.0,6.0,9.0,10.0,AEDBCDECBCHBCBBGFBGFHGEHACHAGAEFBDAECHCFHFDCCECGBCGECGAHGBHBHEBHDFGDE,False +23,11.0,8.0,12.0,13.0,7.0,5.0,13.0,9.0,EAAGACDACDHEEGGGGGBEGEABEAHGCHCCAFCFFGDHGDGCBGBDDEAFAADCDDCDDHBCGBCAFCBDDHHBHH,False +24,36.0,26.0,18.0,26.0,33.0,19.0,21.0,15.0,GBCHFHAAHAFFGBBEFBCFAEFDFGEGEEBECBEBBABBAEBEEAEEABGDBADBACFFBEFCECGACFADABCFDCDBCBBHDHHACGGEHDEGDEGAHAAFAAEDCCHHDDGDDBDGBDBDDCDAGAAFHEDHGDACDACDBGEEACGAEEBEHAFHBGAAAAAAAEEFBEDCDAEEEFGEGGHGFEAFED,False +25,11.0,17.0,16.0,9.0,15.0,15.0,6.0,9.0,CEEFABDBGDBFDFFDGADECBFCBCCACFABEABFABEGBEHBAHEAHEAECCFFCHDCBBBFGBAGCDFHHFBDFDCCHHEHAEBEGCCBFEECEF,False +26,8.0,5.0,15.0,9.0,10.0,7.0,11.0,5.0,ECAGCHDBBDCCDCGHBBEEFDHFEEEHBHGADADGFDEFGAFGAFCCCCCACCDCDGGECGECGEAGFA,False +27,9.0,11.0,8.0,5.0,8.0,4.0,2.0,4.0,FCAFDBEDBABAABAEEAEHDBHCEHCDBCFBABEEGECGBDABFCCAHCB,True +28,6.0,8.0,11.0,7.0,10.0,5.0,9.0,9.0,CFBCBCCBACBEHBEGCADHDGFEGFHGHDAFBAFBEDCDGCHGAACHCHBCEEEEDHEDGEGGH,False +29,24.0,16.0,18.0,25.0,13.0,19.0,26.0,18.0,HEFHCDEGDHFBACGGDEHDGHDGFDEAHFDHGBHEBGEGADFFGCCGDHFBFABDACDABAGFGDAGDAGCAFFAGHHCDHCHACEDDAFDCCDCAECAEDGEDGAFGFCGFAGBBGFBDBBAABAAGADGAFCHBEEGHBGCBFCGFAHHCHDBDDE,False +30,6.0,5.0,2.0,9.0,2.0,4.0,3.0,8.0,DADBAFBDFHDHHBAHEADGFBHFGHEAHDHBDGDCADC,True +31,19.0,18.0,16.0,13.0,19.0,13.0,14.0,15.0,FCHGCAEHAEBDEBABAABHAFEBDCBDCBHCGEAGEFBAFCCECCBCFHEHGEGAEDAECBECEAFEBDHBDEAGFGHDGCDGADFAHGCFCBFDEHEGCEABFADHAFHGBHABHBHDAEBGDFG,False +32,7.0,12.0,12.0,10.0,7.0,5.0,5.0,9.0,EBDGBGBBDCBACGHBDAAHEBGCBFHBFGAFEHFCCCHDCHDCHDAHDCDDEBDEAFECBAHBECC,False +33,1.0,4.0,8.0,1.0,4.0,4.0,5.0,3.0,GAECEGFBHFGHBGCBFCECCECCBCHDGF,True +34,5.0,4.0,6.0,9.0,13.0,13.0,5.0,7.0,CHHEFFDFFDFFDFDGGDFGDHCEAEAHEAFEBFCFEEFEECAECHCHFDEBDBGEGABDEH,True +35,3.0,2.0,3.0,3.0,5.0,4.0,0.0,6.0,CBDEEHHEAHCAEBDFADFHFCHFEH,True +36,13.0,2.0,13.0,8.0,7.0,6.0,16.0,9.0,DEGDECDHGAHGEDGEGACAFCADGACGACHFDACHCCHCEECGHDHBEGGGGCADCAFAGFGGBAGCAHFHFA,True +37,18.0,19.0,17.0,17.0,13.0,17.0,15.0,23.0,HBCABCGHCEEADEDCEDGAGFFFHDFADHHBHHGCHFHHAGHEHEBBBDEFECFEBHCDAADFGDFHDCDCCDCCFACAACHGGBGGBFBCFBFFCFGEDABDBBDAAGAABACBEGBAHAHHFGEDGHDHHEBHBHF,False +38,4.0,6.0,5.0,9.0,6.0,4.0,4.0,6.0,AGDAGHABHCEEFBEFDEHDBHDECDFCDBHDEGBBGCCADFDH,False +39,3.0,5.0,6.0,8.0,8.0,2.0,8.0,6.0,DCEDEEGEEGAAFEHFGHDGDBHDBGBBGECECDGHBGCDDCHCAH,False +40,0.0,0.0,1.0,3.0,1.0,3.0,5.0,1.0,GDGGDCEHFGFDGF,True +41,20.0,19.0,22.0,21.0,30.0,22.0,10.0,26.0,BADBABGCFGFDDDADEFHAAHAAHEAHBBHECFGFDEHDCDBBBHGEDEECCDCCDGCHHBGHCHACFDCFCFEDFEDAHHHBHAECABDABAAEHFEADCFEBFAGFGEABECFEFFECEEFEHFEHEEHDHDCHBBHBDHCEHCDHBDCFAEFAGHEGECBCFEEFE,False +42,3.0,7.0,4.0,4.0,5.0,2.0,5.0,3.0,EBBEAEEHDCHDCGDGGBACBEHBDGBAFBFCG,False +43,21.0,15.0,21.0,27.0,18.0,33.0,14.0,23.0,DDDDDDBCGFEFFABFDHDAGCEFHHACHGBHGBEFEHFEHFCFFCHDGHDFHDAGFECCCAAEAAGHGDFCHFCHBBBFABDEFDFFBBDBAAFDAFAGHACHACEFFEFDHABCAFGDFEDCGACFADFDDFBHFAFFBEHBEHFCHEADEGHEGCDGHDHDEECCFCCD,False +44,27.0,34.0,20.0,19.0,15.0,29.0,27.0,26.0,FGCFGADGADGDDBDBAFGAFDHHHAFBAEEAGGBDBFCEFAHFAHFAECDCBBCGBHAFHABHDCHAHHGBCGECFDCEHCFBCHBGHCABFBCFBEHBECBAHBGDECHFDFBDEAFBBGECGEBBHDBHDBEABEBFCDFHHFGHFAFFGCACFGDGGHGAABCDBHBGGBGGFHGHGGBEADABFABAAFAFF,False +45,15.0,12.0,15.0,7.0,7.0,15.0,11.0,5.0,CAFCDGCFACFCCFACGBBGCAEAEGAHFADBCHACHFCFBEFGEGBDGBDGBEGEHAEFGBFCDFBFBHACAFCAFGABDAFACDB,False +46,12.0,10.0,7.0,5.0,4.0,11.0,11.0,13.0,ECFFHGFGGFCGACGFGGAHFABBHDEDCHABFBHGAHGAHCAHDABDFHDFGCHGBEABAHEHBFHBFCBAA,False +47,15.0,6.0,13.0,11.0,17.0,21.0,13.0,9.0,EDCEFAEFAFFAGHCFCEEAFGFFHFDECECCEGCDGHDGHDGHACFFCFFCDFEHEEFEEGHEDAFBGEAAHAAGCABAEFAFDABGFCFHCDEDBABFGBGGD,False +48,11.0,17.0,17.0,9.0,17.0,17.0,13.0,15.0,GAFGHHGCHBCACCFBCFHHECHBHAFHEEGBAFCAGHGEFGEDGFCBBEBGABCFDCFDCFDBEEEGAAHDAEDFECBGCBHDBFEGHHBFGBFEBFCBCCHEFAEDAEDCEFHB,False +49,13.0,16.0,15.0,12.0,16.0,9.0,12.0,15.0,BGCBAEBCDBEDBECBDCBABDCDFCDBCEGDABDFFEHCEDGECHACHEBDECDGHFFHFHEAHAHHEFFBAGAGHCHCCHGCEEAAAAGEEGDEGBFGBAGBHHBH,False +50,13.0,6.0,16.0,14.0,12.0,13.0,9.0,12.0,DAEAAGAAGCHCCHDFHEFCCBEGFEGFHAHEAGBGCBFCBFCDACDAFDCHECEBFBAFCFFDEHAGHDEFDGCDECEHCHDGADEHHFADCDD,False +51,22.0,27.0,26.0,19.0,24.0,22.0,28.0,20.0,FDCGDAACFACHGCDGEBFCBDCBGBEGBEGAGGFGGCHGDHGDCAACHADHCFHAAEEBBCBCCBAEDAGBFGAFGEGGDGHCEEEDEHCBBCDECEBGEFCCHCFBCFBHFEABEBDEDHABHDBFFFCEFCEDHFFHBFABHAGGECAEADBGGEGAABHAGHAGEFGBFBFHHDHBEGBFCCDD,False +52,19.0,24.0,24.0,17.0,11.0,20.0,12.0,18.0,FBDFCFECGDCFBBFHBFHBAHECHAAHAFCAHCHCFBDFCDHCDBDDBAGAAGAGHFGBDABCFEEAHHGDHBDCCGCCDAEBAEFEBCHBHECHDABFFBHECFDCBDBFDGGDBFABGHBGFCFCBDCBACBFGHEACEACA,False +53,11.0,13.0,7.0,11.0,11.0,7.0,5.0,12.0,HABDABEADFFDABBHBEDAEDACBEHBEGBDDEAAHAHGBHBDEBAEDECCHFDHFGHFGHFDCCEBHEBHGCACF,False +54,11.0,20.0,14.0,17.0,12.0,15.0,15.0,22.0,DFABFDGCDCDDCBHCBECBDHHHBEFBGFEGHGFHEFEAFAHDBHDGDGEDFBAFBGFBGAGGHHCHHEDBDDBCFFCGFCHEEECDDADHBHHCDHCBHFAEGBCBBAHBAGEFGAHABHCBHG,False +55,17.0,24.0,24.0,12.0,23.0,20.0,17.0,26.0,GAECBGBFHAHHEFEGCGFBGBCHHADCACHBGGBHBAHBAEFAFGGFBCCAFCFHCGHCFHCBEFBEFBCHBGFECFGDHBEHCCACGFHEDAEBAEDDEDCEHBEBBEGEEHHACHECBDFFDFADFAEFHCFHCBECDEHDEHCBAGBAGADGBCBHHEH,False +56,17.0,25.0,29.0,22.0,21.0,19.0,27.0,22.0,FFFFFGGHDEHDFGAFGEEAFEGCEADDBBDHDCHECDGCDAAFCDHBGCBGBBECCDCCDAHGBHCBGCHCCEFEGFAABBEHFEHBCGFHGCHBDHCDHCFBDEBEABEDBCDGCHCCFGCFDAGGBGBBCBFABFEGGADGHEGHEDFBBCBCGACDAEEABDADGGEGHEGCCHHAHH,False +57,12.0,11.0,4.0,15.0,9.0,3.0,6.0,8.0,HABCEHAECBEDEDDHBDGAAFHAGCBGBEAAABADEADGHDFBAFBDEBEEBGDCDDGDDHDAHDBH,True +58,9.0,8.0,9.0,9.0,4.0,9.0,12.0,13.0,CAGCGGCBAHDEFDHHGHDFDBFBBFGAFEBFECHABGGDGDEGDHGBHADGFDCACAACHBFHFGHCHHCHA,False +59,15.0,19.0,20.0,23.0,14.0,16.0,21.0,18.0,GDGGBGGCFGABBABFGEFGCDDCFBCDBEBACHABGEBCDCCDFDDFDAACEBCEGGGFHHFDHGGHFGADHFHHGDHDFFGHGGHDEBDCAACGACFADDHDDCBDBBFEBHDDHFCEGBEHCABEAHEAHEFCCHBAEBCEDC,False +60,9.0,8.0,2.0,6.0,8.0,11.0,5.0,10.0,FEBDCDFHFEHFEHEGHBHFBHFEDCHBBBAGEAGEAGHADABFHFFDBFAEFADAAHG,False +61,26.0,25.0,20.0,16.0,13.0,13.0,17.0,12.0,CBACHGCFDHEBHBBEBBFAHCCEAEEABDDBDGEGADGHDAHEABBBEFCFFDEFDAGDADBBHGGCEGBAADABCHGCHGBDBBGCBGCHFAEFCHFBFDDCAACHACFACAACABFEBFAAEGGCGBCGBAGBDDACAA,False +62,9.0,9.0,5.0,7.0,5.0,5.0,11.0,6.0,FAADDAGBGGBGBCHBCAGEADACGAHGACFECDABBFEFDGGDFGHBGHDEHBEHB,False +63,7.0,8.0,8.0,6.0,13.0,12.0,11.0,4.0,GGBDGFEGCEGCECHDCFGFGABGFEHFCGGBHFBHEGEEAEEAFEDBCFBDFDEADACBABFACFEEF,False +64,20.0,11.0,23.0,13.0,16.0,11.0,12.0,18.0,AEDAHACHEFAEFAHCAEDAEDCBAGGCBGFBCHCHFCEACHCEHCFHCEAEAAEAHCAGBDCDHCEHEGBFCHHCGHFBHFAAGEADHBDCADCFDGFDCHDCBGCGAAHCGFGDEBDEBECB,False +65,19.0,12.0,22.0,18.0,18.0,14.0,20.0,17.0,CCDCCAFHAECADDGDGACGADGHDFHEBGEFEAFDHBDGBCGCFHBGHEGAEGBDHFDFDCGDHGDAGDCBHEBHEBGBAFHGCGCCFEEFCDCCDCHECHFCFAAAGECHBBEEBHDAGAAEAAEAHEGHCFCEFGAD,False +66,26.0,13.0,22.0,33.0,10.0,21.0,25.0,20.0,CDFGDFAHFEHDHBBCDECDAHDGGGFBCDBADHHDGADEBDEGDHFFCFFDHDGADHCFHDAGEGCEACGBGGEAGFAGBBDABCABGADGAHADDADCADHAFCFGDGEFBEAHDCGDHDCADFADFGHCCHGFHCFHGDHGHGECCCCCADBFDGAABAFDAFDAFC,False +67,3.0,0.0,0.0,5.0,2.0,3.0,2.0,1.0,FDFEDHDGAFGADEAD,True +68,21.0,30.0,10.0,18.0,20.0,13.0,15.0,10.0,ABBHBEEEHDEHDGFFGDBDBBCABFGDCCDHFHHAAAAABFAEEDBEDBGBBEABEABFBBFBBDDAEEAGCFHEBAFAGDGGBBEDBHDFEFEEBEEBABDHBFBGCBGCGGBGCCGCEGAADAABCDDADEAHF,False +69,23.0,30.0,20.0,17.0,29.0,22.0,24.0,20.0,BHBBFBBEEAEGAEHBCABCBGCGEFHEGHFFBFCBFCHEEDEGCCGBCHFHBAACDGBFBEAEAFEHFEHGHGGACBEDDDBDFBGBAGBAGEDGEHAEDDHGDFEDFEHFACCAEHFBCGBCECFGFFAEGAEAHHBGABGAEGDCGDCHDBBEFAECDHCDHABAFBACBAFBFGEDEEHGB,False +70,16.0,21.0,23.0,21.0,35.0,31.0,21.0,19.0,FEGHEGHEHFBHEBDEGDABDAGFAGCDGCEAEABGGEFEBAEBHDFEFACFEHFHHEBFGGDGBAGBAEEAFBACBCBDFFDGEECFEDFEAFEFFEDFBBFHFFCGFBFCECEHCHFFHGFDGFHECEGCDDBDDEECCBDHADHADEEEECDBCBFHGFHGBCGFCHCCBGDEEAEHAECDCCF,False +71,21.0,21.0,25.0,23.0,34.0,29.0,19.0,27.0,CGCABAFBECCEGAEFEEHEDHEFBAFBFFGFDCBDFHDFDDHCCAEGAEGEECFCDFGDHCDAFDFFHBAEGDECFHHFHHEAABFABAAHCCCCHHGBBCBHGGHEFDFFCGFDGHDAHAGHCEEBBEDBEGEHBEGCHAEHDEHFEBDECFHABHABAAFDDFDDFBEFGHGCEECFDCDCEECEEAHEGHEFBBG,False +72,26.0,9.0,19.0,24.0,24.0,27.0,21.0,27.0,DDGBDCADHEDABHHHAEHAHDCHDBFFEEFAEFAHGACFFEEDHACFCCFGCDACDCCDCEDBADHFEGDHDFHGCHFAEFHDFGFGEFGEGGEHEHHAHFEHCAAEAFCHDCFFFGABAFEAGGBGHCHDFHDAAGAFCADGADHAGHBGBBEEEGEEFAEFAEFCGDCFDHGDH,False +73,24.0,24.0,23.0,19.0,22.0,18.0,26.0,30.0,HGFHGHHBBHDBAGCEDEHDHCDAAGCBCCHCCDGGHAGHGHHFAEFGEGBEBFDFAEAHBBHBDCBDCBCCDECHHFHDDHCGAAAAEAEEDBGDBGCFACGAHGDFGCGHABBACBAHGHHBHGBEDDACFACFEBFGHCAEBGEBGEDGEDHEFFECEEAEFGGHHFBBFCHFBAFGAEHACD,False +74,26.0,17.0,19.0,17.0,28.0,19.0,13.0,23.0,EGCAHEHHEHABADBADECBECEEABEACFACACFFBFGBFBDFCFCCACAHEBHEGHDBHBBAFEADEHBCHEEHEGBFGBFDCGDEFDEADEDHEAAFFEFFHHFACDCCEAHDADDEEEFAFGADBHEBEAGAGDAHBCHCGHCAHGACGEEFAHGHHD,False +75,3.0,1.0,2.0,0.0,2.0,1.0,0.0,4.0,EAHBCHCAHEAHF,True +76,10.0,5.0,4.0,6.0,10.0,5.0,10.0,8.0,HGHHAEEAEDAECGDCAHGFBGAGEFGFBEFAFCGCEAEEBGEBGDDHDBHDAHGAHA,False +77,6.0,2.0,4.0,1.0,4.0,1.0,1.0,0.0,AACCDECAEBAEBAGFECA,True +78,26.0,21.0,24.0,22.0,21.0,23.0,16.0,22.0,AEAFDAFGAFHAHCGFCGFHDCBDCBABADBCDGGFGHEBBDFBFFDCDEAEEGGFHAHDCDDBGEHCEFCHFGEFDADGFHFBDFCCCBCGBCABDFHAEBCHBCHBCDECEGFFAHFAHFCHFDDCAEHAGHBGHBAEECDDDDAABAHECHEBHEAHABGEBAEACEACEAF,False +79,23.0,23.0,29.0,21.0,13.0,23.0,22.0,17.0,CDHBACEAHEFDEGHAGAAGFAHFADFCBBBEFBCDGFBCDBDHGGGGCGFBDBBCFBFDEGEEHEGGBGEHFCCFCBDCEDAEABFDHHBFBBCAGDDCHDCHDAHBACAGCAGCADDBDFHAFCAFCGHDEBGHBCHGCHFBEGBFACFCCACAADACFACFCCFGFDG,False +80,12.0,12.0,23.0,9.0,27.0,13.0,18.0,19.0,EGFECEECHEBEEHHFBDCGCAACFBCGEHEEGCEACEGDEADAGBAGBCDBFBHFHACHCDHCDHCECCEGFHGFBABCGDCBDCEACHBCGGAEEAECFEHHAFFEEFHFCEFCHGGGGDHBEHGGHEEHE,False +81,25.0,15.0,14.0,17.0,20.0,16.0,15.0,15.0,DGDFFBFFCAFHADGAEEAFDABDEGGEBGDGEDEBAHAAEGABAHCACEACAHBAGGECFCDDEDBEFHEBGAFCAFCAHDEHDAFAGFCDBCHCCHCEDBGFGHBADBHGBEAAHAAHAEFECFEDFEDHEBHGB,False +82,23.0,16.0,15.0,28.0,9.0,16.0,15.0,26.0,FAHGHHFHGDHGDHDHCCHFBHEDGDGADGBDFDHFBBEDBADEDDBDHFDACDBFGBFAHCDDDGDBGBBGAAADCHFCHCDGABFHDDHDAEDCEDCGDFEAAEACHHGHDGCFFCHABHAHHAFCFHAAHAACBABBHFEAGEAC,False +83,16.0,17.0,21.0,14.0,11.0,17.0,24.0,19.0,EGHCBBCBBHFAHAAGAFGHBCDFAGFBDABDADEEDBCDBCHBCBGEGFFGFGGCHGCGGHHADHDHCDHAFGACCEHDGHFFCDFEDAHDFFAFFHEGBDGCGCBECECHBGHGGHCGBCHBCEGFGGFCACAABAE,False +84,25.0,24.0,34.0,20.0,21.0,23.0,18.0,22.0,GCCGAFHHFBGFBCFBDFBGFCGDEGCAHEBCAFCBFHEFEDCGFCAFCHCHBCHEAHAFBAFDAHBHBDGAABAFBACACHHCFDAFDGBAHBEBBEDFCFECAEBGFHECCCCCCHHEEHAAFDGFDHBDGBEFBEDDHDDEBHECCECCEBAEBAGACGEDGADCBCCGGCDEAGCADCAFHHD,False +85,14.0,17.0,15.0,14.0,15.0,14.0,16.0,10.0,GGCGDDEBFFHGFBGFBHFHHEDAACAABGFFFCDBGBEHBEDBFDBCDCDGCDEFBCHBEGBEGBEFHGFBAEBCEFAAGGCHCCFCCBCHEHEAACADDEDDAGDAGEAEBAG,False +86,5.0,2.0,1.0,1.0,1.0,1.0,3.0,1.0,ADFAGGAHGBEABCA,True +87,28.0,33.0,23.0,19.0,20.0,25.0,30.0,22.0,FFGDBGHBGEGAADDHGEEDEHBBACDFCGFCGEHFBBFHBFBCCGCCFHDFCGHBECBAAFFDBBCBECGGFEGECCAGABBABHAEHBBHBHDEFDCHDBAFFDDFAAHAAHCDFCAHEAHGAHFAHAGHAGAAGEEDFGBEBECBGCBAFBGCCGAFAAFHAGGFGGBGGBDEEGEGBFGBFHBCHBDDBDDBECCA,False +88,27.0,30.0,28.0,20.0,23.0,12.0,23.0,29.0,EGBCBBCEBCHHGDBECBCDBEDGEHGAGACGEHGCDACFECFCBHBBFDAHCACBACBEFGGAGGADAAEBAHDFHDCDBAHCHHBHABGCBEEDHGHHGFHAHDAEDABDGCDECDBADBHHGHHGFGECBEABDHFDGAHEACFGCAGCABCHBFECHCBFCBFAEABDAGEHEEAECABDHBHHCEBG,False +89,14.0,15.0,7.0,17.0,10.0,11.0,15.0,9.0,CHBADFABGHBGFGGAGGADGDEBHADHGHGFDFDDCDBGAAGHAGFAEEBBEDBEBCEBFAFDAFDFGDEADEGDFACCCGBHBBHABHDEDCBDFE,False +90,5.0,3.0,3.0,1.0,8.0,0.0,6.0,3.0,CCACEGHEGDEGBBAHEHGBAGEAEEAEG,True +91,0.0,0.0,4.0,2.0,4.0,2.0,2.0,1.0,GDCFDCEECGEHFEC,True +92,14.0,4.0,7.0,10.0,8.0,6.0,12.0,5.0,DCDAEFAFCECEEAFEDFEGCCGACBDGHFAHBGEBGAGGAGGDGAEGHHGAADAFDADDCBAHDA,False +93,10.0,8.0,8.0,3.0,8.0,14.0,16.0,15.0,FAGFDGHDHHEHEEGGFFACFHEHACCACHFGHFGHCGCAGCGBCFFEGFGBHABHFDHGBGBHABHAFFAGFEHEEBBAGG,True +94,21.0,25.0,21.0,30.0,27.0,13.0,12.0,17.0,HHBEBCAACEABDGDGBDFBGFCAEHGDCADCHDCEDFEDCEDGDCEDAEGEHAADBBDAADHCDHDFHBEEBEEBCEGAECDEBBCGAHEBBFFHEBHEHDAHDAECFFDFEDFBDABDCCACEDEBDHDDAGFAEABECBHGFDDFEDCCBHCBHGBEGBACBA,False +95,4.0,6.0,6.0,8.0,7.0,6.0,6.0,9.0,EDGEBHEFHACBBCFEGHCHDAHDEHDBHDBDDEHFCGECGFGBFACFAHGD,False +96,8.0,5.0,5.0,6.0,5.0,8.0,12.0,12.0,AFACCAGAGGFBEHEGHECFDFFDGFHGAHGHHFDGAGCAGEFGHBBHEBHDDHDHHGCBA,False +97,20.0,25.0,21.0,20.0,27.0,26.0,25.0,26.0,BFCFGDFBECHDCEBGEFGBABHGDDGAFBEBCEFEEFGDAHFBHEHHCHDDHGEFDFFBGBBAEGCCFDDABEBBEBFHBHHBCCECEDCAFCGFGHFCBGHBEAFCBFDEEAEEAFECEBBGGAGHBDHFHHFHHFHHFHHEEHGCDABGABGACGAFGAGGDDEDDCADCFGAFGDCAHEAHEAEGC,False +98,4.0,3.0,1.0,1.0,6.0,1.0,5.0,3.0,BBAHAEDECGEAGBAGEEGHEGHF,True +99,21.0,17.0,15.0,21.0,17.0,23.0,10.0,21.0,AHDDHEDGFFGCFHDHAGHGHHDDFADFABHDBCCACAAHGDDFDDFGBHEBHBHEEHEFCFFBBDDBAABCEEHDACDHCEEAAEBHBFABFABCABFFFFDFFDFEEFCEHCEBDEBFCAGAGGDGCHBCHAAHEFFECAADH,False +100,21.0,17.0,13.0,22.0,21.0,22.0,21.0,31.0,GCAADDGBDEBDABDGDGGEADEDDFHHHEHDGHFGHFDHGAFAHEHDCHDHFEBGEACDACGABGABGFGGDGBHEEHEFFGHFABDHEDAECBFHAGHAHBAEAAEAFEHFEBGGBCFDFEEAHCHHCFDAFDCFDBFHBAHCHHFFGEHDECCGCBHFHHFBHBE,False +101,3.0,4.0,2.0,2.0,2.0,1.0,2.0,2.0,BCFBEABEABHADGCHGD,False +102,3.0,5.0,4.0,4.0,2.0,1.0,3.0,10.0,BGHBGHCCHCDHEHHABDFHDBHEGCDAHBAH,True +103,22.0,16.0,17.0,17.0,11.0,10.0,13.0,12.0,DECDFCDFEDCCBCCBCADGAGFAEAAHHCGECAAFHAHBAGEFDEFHHGGFBFCBACBABDACDAHDAGDGBDBADHFDBCEHGEHGDHABGBCEDEEHBAABADCGGCFCABDABA,False +104,12.0,15.0,10.0,16.0,25.0,15.0,20.0,17.0,GBFDCFDGDDBHDAADEBGBDEBEEFGHFGHFGHCGHEGDEADHBDHGGBGHEDCFHAAHACHGGEGGEFEBFGADCCEBHEGFEHDEHEEFAGDCHFEEAEEBCEGEDBEDBECBFFBHHCAFAEGAFB,False +105,7.0,10.0,8.0,8.0,6.0,8.0,6.0,10.0,HBEHAGHFGHBGDBAAGCDEHFEBEHBEBCABAACDFHBCHDFGDFGDFHCHCCACBFDBEDF,False +106,17.0,20.0,9.0,15.0,13.0,17.0,14.0,15.0,FBEAGDAGAABAHBGEFFBFFEDHEGHEGHEFHFDBBCBBDBCHCAHGAHCHBEGFDGFAEBAEGADCAHBDFBDFDFBABHEFGBCDAFDBCAGCFBHFBAFAEDHEDCEDHBDGGHGA,False +107,5.0,5.0,1.0,5.0,1.0,5.0,5.0,2.0,FABAAGDGFDFHBFEBAGBAGBFDDHGDC,True +108,17.0,16.0,20.0,15.0,16.0,19.0,21.0,30.0,CBHCHHDDDGADGAFCEHEBHEFEAAEBHFHCBGFAEDHEFEFFCFFAHEHHAHBGCDCHFGHBGFCGFBEABFBHHGHHGCHEAHEADABGHBHHBDHGDHGAGGBGGEFCFFCDBGDFDAECEECGCAGCGDCFDFHHAHHDHBBCCACGAC,False +109,19.0,26.0,19.0,10.0,27.0,23.0,8.0,14.0,EBCAAAGFADFADFEFBBBCBEABEABEAEEHEEHEECEBGACCAFCBHCDCCECFBCAGGAFEAFEFBHHBDFAHEHFEGFHCFBBHCCABCHFFBFFBDGCEGEBAEGCFFEEDHFFBFBADBDBBDBBEHEEFCHACBAHDEE,False +110,19.0,10.0,10.0,17.0,15.0,14.0,13.0,9.0,EACEADEDDGDAEBCFACEAEBFHFFGDFEDBBGBHGCADCFBBBHCAHEAHFAHAAHCDGCDGAEGAEGEDDFGEAEBAGFCGDGDDABDFCDFGFFAAEDFEHAH,False +111,6.0,10.0,13.0,9.0,4.0,7.0,3.0,10.0,CCCAFBAFBEHDFBCCBCHBCBCGHDAHDAGDCDFCHCEHDAFDFHDHHDEEBFBAGBCHBC,True +112,14.0,15.0,18.0,9.0,20.0,11.0,10.0,7.0,DEFDEFBEACFGEFCACCBGGBHAAEBEHCEGGEDEEFEEDBECBABGADFADFADGCHCCHCHACEDHEGAFAEFBFBAEACCAEBBGBBGEBEBHCCDCCFC,False +113,18.0,25.0,13.0,24.0,29.0,22.0,19.0,30.0,HCAHEABDACHBBDDHADBEHEEHCABCFBHFBABBABDHBEHFGAFGFHCHGCAEFHEFHGHCGCEHDDFEBFEFFDDHDEEDGEFCBGBDGAHHCHDCFDEEDGCFHHFEEFGBGGEEHBFAGFDHBEGFEDCEDEBDEFHEAHEAHABBEDBGFBGEHGAHFADBADHADHEDBGGB,False +114,13.0,9.0,15.0,32.0,17.0,18.0,11.0,14.0,HDHDDAGGFDDFHBFBCAEDGEDCEACDDEEDFHFAGFDECDCCDFADECFECHDCHDGAGAHGHDFEDCEDCEHBHDAHDCFDBFHHGDBDAFCGFAHFDCCDAEDGEDEEFADFAGFBBDEBDEBDF,False +115,21.0,18.0,26.0,25.0,21.0,27.0,25.0,34.0,AACCECDFFBBDABHAGHGFHGHAFHBFHFEHCBHFDAGHAGEDBEACHDCAGCDCCDBEDBDDEGGEHGAHFAHDBFGHFGCDCCFCBFCBHCHHFFDFGEEEDHFHHFHDFEDFDCBHAGAAGHBEEDCFFCHEDAEBAGDEGDEDBFBGCBECHCGHCDAGGAHGHCGHCFHBFHCFHDADAEGEGHCGAFFEH,False +116,25.0,15.0,25.0,18.0,19.0,11.0,22.0,30.0,BGGBGDHGBAECHEFABDHBHHBHDADBEEGFGGDGCCGFCHHHAHAFHBFEEGEAHCGEAGDCCHCGDAGBAGBAEADBADHADFCGHEDHCABCHHEHDFHFAHEAHCHCAHBDHBGHFGEFCAGCHGAAACAACHHDHCCGECEDDFCDACDACBCCEEGEE,False +117,28.0,24.0,15.0,28.0,23.0,30.0,14.0,19.0,CHACHAGEBEFDCFAGFADDEDDBDGBDBFEBEDHHDGDECDEBFABFAFFABAAHHAHHDFHFBHDBEDADCBGHEDFFDEDDEBEBAGADDFFFBDFBFFBFFBHACFDBFDFAEBACBACGEGGCFAFEHEAHECHBDGGFCAECFEFHEHHAGACBDCBAHAAEAAEDECDAFGGFB,False +118,0.0,3.0,1.0,0.0,4.0,1.0,0.0,2.0,FHBBEEBEECH,True +119,15.0,14.0,10.0,15.0,7.0,12.0,18.0,9.0,BGDBGBFEBDCFAFFADCGGAGDABAAHHAHHACEBCDDCBDAGDGBBGDGDDACEFCFFCGFHGBEFCGACHAGAGHAGDABBEEFHGFBFDBEDGHDG,False +120,18.0,23.0,21.0,12.0,21.0,14.0,26.0,15.0,GBBHAAEBAEHEEFEGFGCAECABAGCADBEFAAGDABCAGGFGGCHGCHGAHEAHFFCEHCEBBFBBEHBCGECGACGDCGDHGCGGHGGDDGHACBBGDBDECDCFABECFEBFECEBGBBEDDEGFCDFEGBHGBHAHFACEBCHBF,False +121,18.0,17.0,15.0,11.0,14.0,12.0,17.0,17.0,AGGAFDDFCDBBHECHBCHADHCBACFACDDGFACEBCBBGBHAAHEAEEHGFGCFGBHEBAFHAHHADHBEGBHHCEFEEFGHFGFGCBDCADGBDHHEBEBBAADAAFCAGCGGEGGEC,False +122,19.0,12.0,14.0,16.0,13.0,13.0,22.0,12.0,DFAEFDEBHGFEEDAEDFGGCGGFGGFGGAGGAFFDEAGEAGDBBABDHHCHHBDHBDGCGGDHDAGCACCBFCBABHEFHCCHECBCGDDAHDCEEFACFBCAGDAGAAGAEFAGDBEHA,False +123,3.0,8.0,5.0,11.0,9.0,10.0,4.0,11.0,EBFFHHFADFCHFGHEGHFGFACDEDDEGHFAEDHBDEBDECDCDDFHBFEBHHBCEBHDB,True +124,4.0,5.0,6.0,11.0,9.0,6.0,5.0,8.0,ACEACEADEDEHDCFFCDCCEHHEHEBHGBDGHDFDFEGFEDBHDHDBBGFAGD,False +125,11.0,14.0,19.0,12.0,21.0,14.0,17.0,9.0,CCDCBDBEDHEGHAFEECDGCFGCEGCBGEFAEDACCHCDHGFEFFBBEABEAHHAFCCFBFFCFCBEGDACDGCAEBAEGGEDGEDCAGGEDHEBHBBACBHGFEGEGDEGEFCBF,False +126,7.0,15.0,16.0,15.0,17.0,19.0,21.0,17.0,CHHHDBCCEFEEBEGBHFEDGEBFFBGFGHHGHHGEHDHCDHCDFAFFDCABAFBHGBCGBFHBDHCEGAGGHHGDEAFECHDBFGBDBCDECGEFEEBECBDFFDECGGCGADGEDGFGCFGCFAF,False +127,1.0,2.0,2.0,2.0,3.0,3.0,7.0,2.0,BEGGGGACFHCFHEFDGGDEGB,True +128,24.0,27.0,28.0,25.0,25.0,12.0,31.0,20.0,GGGBGGBDBCDHGACGEHDCHDCBDCHHEHBGHADDADDEBGGHGDDEADFAHFAGGEGEEABEHDEHCEBAEBECBACBACGACGADFADBBBBFCCAEGHFBEBCAAHBCHFCEFCDFCDCCBAEGEGCAGCGCCGEHFEHGCCACAACBDDBHGBEBDAFGEFGBBGHHEDGDABCGFHDEGGEDEADB,False +129,8.0,19.0,18.0,15.0,11.0,19.0,15.0,9.0,BEEBFHGAACFBCEBFHFADFCDHCDBCGBGGEGBDAADFDCHECHECEGCFGCFGFBCFGCAGDFGFFHHBDDFCDFBBEDBFDGDBBFBHABCEBCDAEGCBFHBFCGECGD,False +130,19.0,16.0,11.0,13.0,12.0,17.0,19.0,19.0,AGFEGFGGEGDAFDBFDBCGACBHEHHAHHDFADABHAGHBFHDFCDCADEEFEGBDGBEGADBAHFGBDGBAEFAGFBCAECHGBGFBGBBFBHAHHAHDEGEFAHADCACCHCEHGAHFHGFCF,False +131,4.0,4.0,2.0,0.0,2.0,2.0,3.0,2.0,FBECAGHAHCAGBAGBEFB,True +132,21.0,22.0,26.0,22.0,19.0,22.0,19.0,31.0,HHACHAGHDFHCACFECAECGDFFDFCAACEBEDHHAHDCGBCBBCAHCAFCDBGFGDCHBHECHCFACFGCHECBBCFBGHDGHEGHDGFBAADFGBGGFCGHCBHAGHFEEEDAEDAHHABFABHAHHGHBFDAFDGDDFEDGBDFEDHDDHCEHEAHECEECEADBGCBFFHCFBBBBH,False +133,16.0,18.0,20.0,18.0,16.0,13.0,27.0,16.0,DGGBCEDCEFHDGHFBDCHFHHBACBADAAHADEACBGHFGEDGCBCABGAGFCGDCGDGBEGBEGBECEEHGEHGHHDAAGGACBDGBGCBACDEBDBGCFHFEHCEGCEAEFCHFABFEGGCDHFDCDDCDBFGBFGAGHAG,False +134,19.0,21.0,15.0,10.0,12.0,12.0,10.0,11.0,DAGDAGAAHHFHABCBBCEBCFBCGDCGEEACACBACEAFGBDAAFEAFEHBBBFECDEADGFFACGECBBCBBGEBFEBDAACHADHFEFBCHBFGBHDBCGBHADHAH,False +135,13.0,9.0,13.0,6.0,13.0,9.0,17.0,10.0,ACEEHFBHFBGFCHABEADHHCGACGDHBCABEGBEDBGGCGHHAHCEDAEFAEGCEACEAGGFCGCDGBFGAFGAFBEGCEGAFGECHD,False +136,12.0,12.0,9.0,6.0,6.0,6.0,7.0,12.0,DGFDCFBCHHHHHHHBHBBABEAFGBEGCFDFGCCBDABAAEAAHACCAGHADEACGHGEBEFBCDBHAB,False +137,8.0,7.0,7.0,10.0,12.0,16.0,11.0,8.0,EEHEGHGAHFFEFEDBGDBEBBGGFGDCGFCFCGFDDFHDFHAFCFDGAAFFAEHAEDFEGFEDCEGAEFBHBCDBCHA,False +138,16.0,20.0,15.0,26.0,16.0,10.0,21.0,11.0,BCEFDBCDBAHBEFBCAHCAEBDCCDHGHHCHDDDEGBFDFGCACAEEDGADGEDBEGCEHCHBGHBEDDADDGBDGBCGBDHCFGCGGFGGAAEAADAEDGEDBEBADDADGCDGBAGBDGBHGFFBEDAEFBF,False +139,13.0,8.0,3.0,6.0,6.0,4.0,5.0,4.0,EDGABAADGAECAGAAGAACHFFHABGFBABBEDBEHBAHCABDFDEED,True +140,3.0,7.0,9.0,8.0,11.0,8.0,12.0,4.0,FGFCGCCEEDFEBFEBDACHADEBCEDFBDEHEFBEHCEDCGGBGFBEFCGGDGHDGCGGAG,False +141,7.0,6.0,3.0,11.0,10.0,4.0,8.0,7.0,EEAAECEEGHEHDFDCHCGHEAAEHBDFBDBGDBADBEHFEAFGGDHDDGBDGADG,False +142,25.0,23.0,17.0,19.0,29.0,25.0,18.0,29.0,EEBEEBHHHHBCHEFDGCDECDEDBEFHAFGBFBHFBHFCHFEDFBBFEAEGBCBAAAADAHEEFAEFDFACHHCHBEHBHHDGECFEFBEGHEGHAFHCDBCAGHEGHGDHGEGGFAAFAHEEHBFABDACHABDCDAFGFFGCFECFHBFEEDDGDBFCAHAEDDEACEAGDBGAAGAHCBHB,False +143,1.0,2.0,2.0,3.0,4.0,5.0,2.0,3.0,CFDCBDHGEEGAEDFEFFBHFH,True +144,9.0,4.0,7.0,5.0,3.0,7.0,3.0,7.0,EFAFABHACHECHGCBADBADAADGCFFAHGHDFHDCHFCBECAF,False +145,21.0,27.0,26.0,22.0,15.0,22.0,16.0,17.0,FCDFDDECEHCFGCEGDABBGHCGBBFABAEFEEFACHBGFEABEDBHCCFGAFEEFHAFECFHCEBCDBCBAHFAHFCFFCFFBFAGGAECDCCBBDDCDDCABBAGGAGBAGHCHECDACBAFHECGBGGBAGBHBACCADDDDCHHHFHHBDDBDDBDBADBF,False +146,23.0,23.0,27.0,18.0,23.0,27.0,25.0,28.0,DEGHEGFDBFGHDEACECDFDDFDBBBGCEAFHFFHFEBGEBDEBFBBFHFFEFCGFCGCHGAHBCFGAAECGEGDDGCHGAHAAHAADDADCAFBFFBHBHEGCAHCHHBEACCBBABBDBHCBDFAHAEBCEGEGCBHEHFAGCAFCACEFHEFADBCGGCGHAGHGEHEFHCAHCGHDGHCEHCEFCGFDF,False +147,19.0,22.0,21.0,22.0,15.0,18.0,18.0,18.0,ADDADEFBADAHFBBFBBCHGCGBCBHEDCCDHDDACGEGBEACEBCGCFABFHEAHFGDCDDCGFCGHEHHEHBFHDFBFFBAFAABAADACDFCEFHADGADCCECDBHDBCGBAEBAHDHHDHACFCGFGEFHEGGCGEFGBDGBGBBDE,False +148,23.0,18.0,18.0,17.0,20.0,20.0,23.0,19.0,GHBGCBDAFDAFHCBEFGACAECHHGEGFEGDEDDBCAAGFAGCGECAEFBEACEHGEHAEAFEAFBCGCCFCBBGHBAFBFCBFAEHBEHBEGAACFABGEDGHAGBCGCEBDGDDHEAHCADFFGHAHDGHDGHDGBDABHAEDDFHDFCFFHGFE,False +149,11.0,9.0,14.0,14.0,12.0,13.0,8.0,11.0,CCFCGFCDFHHHGGHEDDFHDFEEGCEAHAHCADFEBBBCBFCAHBAHEACDDCDACDADDBDDBEGBDFFCEHEFBEFEAGEGFCGFCAHA,False +150,20.0,17.0,22.0,21.0,18.0,23.0,27.0,26.0,FDDHHBGAEAABAAFAHBGFFHEHCEBEBBEDBGDCGHCGHCFFEGFEDFCDACDAEBFEDAEDHHHFGHGDHGAEFCFGBEDAADCCGFGGAAGCHCDDBDCGGFGGFGGFHGFBGBCGECHFHHACHABDFHDHCAEBBEBGCCFHEHGFHFEHFEHBCACCACGAGHDDDD,False +151,25.0,32.0,23.0,18.0,29.0,30.0,21.0,16.0,CHFAFBDBCEHGEHEEFEACEFCFHHFCAGAEGBCABCAECHDDFDFFEFFGHABFFEHBBDBGABGACGACEDCGDEBDEBCEBFDCHBADBFDAADEFBFHGAACAACHDEADHCBGCAFBFFBFFBEBBGBEEBHDBFDGDAGFEGCABEEBEHBGHBGFBGBAGFGCEGCACFDGAEBEEFCEFAFHBCE,False +152,2.0,5.0,8.0,6.0,3.0,7.0,7.0,3.0,ECBDCEGFFGHCGCGGFBDFDDADDHEBFCBCCBFCGFGAH,True +153,20.0,20.0,31.0,26.0,22.0,23.0,14.0,22.0,GBGFBFFBHCBHCBHGBEFCGFHHHHEHDCHCCDGCFFCDDHFDEDGEGCHHADHCEECFECHECDGCDGADCAGAAHEDHCFBEFEDCHFFAADEADHADCGBCFBCFEEEEBGBCCCCBCDBDHBAHDABCAGCBCFBEHDEBDCFDHFEFDAACAEDADAFGEFABFDCEDAFAB,False +154,14.0,22.0,13.0,6.0,19.0,16.0,15.0,9.0,EEBFEFCBFDAAGAHBCCBGCEEAEEAEEAEEAEGGFHBCHBCBCHBCFACFGDECBAGFFDBHBBHGGFAGBGCBEHGADBFBBGGAFCAFCEGBEGBEFBDFBHEHEFDAFB,False +155,13.0,9.0,8.0,9.0,16.0,11.0,16.0,26.0,HGHDBHECHGCDGAEGFEHDEGGHHFBHFGHBGBEFEAHEAHBFHFDHADHBCHEAHEAHDGHDHHEFFACDCEBFGGEGAEHEGHEGCCGFHGAAAHAFHAHDEBBC,False +156,21.0,23.0,28.0,17.0,32.0,20.0,26.0,33.0,AGBGFFGFGGCEFCBFGBECECGECBECAGHDHEDHCBHEEAEEBFGGHEEHAGFFGFHHCCHADABEGBHGCHGCFBHEHHEHHGFHFFHEFAEHADCEDCHAADBADHEDAFHEDDCCDCFEHBHGGHEFHEBHEBHGBCGCADAAHACBDFBGCBECBCCEHEADEGEEAFCDBHGBCGBCDFAGEAEHAHDCBBCG,False +157,3.0,5.0,10.0,12.0,6.0,7.0,9.0,8.0,CDDCFDCHDGGFGDBGDHFHHEGCCHDCADCAGBFHEGEEGCEDEFDBFDHAHGCBFCBD,False +158,27.0,19.0,22.0,22.0,21.0,22.0,30.0,32.0,AEAADDGDGHBHDGHBGHBHHBCHCAHCABEEBDBDHGFHGHHGBBAHAGFGBAGAGGAGHHCFFBHHGDHAACAGCAHDADGAFHCCHGHHCHGCFGEEDEDBECGAFEDFEDBEGBCACHFCDFGDCDCCBGCFGDFGHFAAEDHFBHFGFFEAEEHEDBECFEABGAFEEEAFDCFDAFDBCGHCGHAEHAG,False +159,6.0,10.0,10.0,5.0,6.0,6.0,5.0,10.0,HCEECDECAFABHBBFADFCGACGABHFEHCBBCBBHFHCDCEDCHGGHEGHFBHABD,False +160,18.0,20.0,20.0,17.0,21.0,19.0,20.0,20.0,FEDBECCGDCDBGDBGDGGDCDFCAHCEHAGAABACFCFFCAACHADAACEGEEGBFBHEHHBGHBACGFDFCHFCHEAEBBEDFFGCFGBEBBEHDDHABGEEEEFABHABHGEHGEHGEHBFDFDHGDHGBEGBECCFCAFHFGCCDAFAHDB,False +161,12.0,21.0,28.0,20.0,19.0,21.0,30.0,23.0,BEBCAAFGAFGBFGEEEFCCHCGHFGHGDDCCHBCGACGEHGHCEHCFCBHCBHDAHDHHDCHEABGHFGBGGCGHCGCEGFDGDDEFGEAHBGEADDCFDGBDGDCFECFCGFCHEGAFCDFCDGDFFEHFBHFCCBECHEBHCBFDBFBBGBDAEDGECGBHEBDABGGGAH,False +162,21.0,14.0,18.0,20.0,18.0,17.0,19.0,20.0,GHBEAFEGBGGHDEEDEABEBBEFECFCCABAAEAAEACBAFBHFHHAEDBCDECDAFBAFBAGEHEHGDAAHGAEDCCDHDDHGAHAFCCECAFCHHCHEGBCDCCBFFEFFGBFDDDDDGGCGDAFDGCGFHHDHHDHGFHGAGG,False +163,7.0,8.0,10.0,9.0,10.0,6.0,9.0,12.0,FBCCDDCAHADHEHHAGCGGHECHECHGBFABFADFGDHBDHDDCDHCEBFHGECEEAEFHECEBGBGGBA,False +164,2.0,1.0,4.0,3.0,2.0,6.0,3.0,7.0,CHCFEGFCGHHEABGAHDFHDFHCFHFD,True +165,27.0,21.0,24.0,26.0,31.0,11.0,22.0,21.0,CAADGACHHEAHDFHCAHCFBCFBEBHGCEFCHCGECDEABEACDDGHDAFCCDCADCAGBDGBEGBCDEHAHHAEFBEGDEFCEABBDBGAHAACAAEACBFBBFGEEHEBDEGDEGDCCDCABHEEEGCDGCDGHEGEEGEHDEGDHDAEFEGBDGADHFDGCDGBAAAAHHEEHDEBABB,False +166,7.0,16.0,7.0,13.0,4.0,10.0,9.0,15.0,BDDEDDGCAHEFHCFHCBHAGFDBDDBDDGFFBAHAHHFGBBDFBDHACHBCEBFEHHGHHBADBCFBHDGABGHBGFBGC,False +167,15.0,15.0,9.0,10.0,9.0,15.0,18.0,14.0,GGABCADCGHHGEHBDHCDHDEGGGFGGAGAABECBCFBEABEBEGAACBBFEAFBHFBHFBGFCAFGHFGHDGCBCEHFFGBFEDFBDAHHAHHGFDDAGDAFA,False +168,21.0,14.0,14.0,15.0,25.0,21.0,7.0,17.0,FDABDAHCHHFDACBGCBGCHFAACGEEBCBFABAEEAEEAFEADDHFAHFEHAHHCEHEFDGFEHFEGFDFHCCAEAAEADBHCFHEBBCFACFDEADFAECAEBBEDBEGFDAFEFDHFDHFEEBCEBGEHD,False +169,11.0,25.0,11.0,15.0,12.0,14.0,16.0,19.0,CDFBBCHGCEBDBACBDCGHFHHFHDFHBEGBEDBFDAFCAHBACFAGGAGEAGBAGBHBBDEBHGHHGHFEABDHFCBECBFDFEGHDFHBFHAEHECHBHBGDBGBCEBABDEGDGGDFDB,False +170,11.0,10.0,15.0,10.0,14.0,10.0,14.0,13.0,EEGCEHAGADCDEADGBDBHDFGDHCDFCDHBAEAHEHCGFCGFCEFDHGHHGHFGCAACHACHAEGEBDCFGCFBBFBBEEBGACGFHEECEBCGA,False +171,15.0,14.0,17.0,21.0,14.0,11.0,20.0,12.0,CBGBFHBCEACEAGAACBDBBDCDDCDDAGGAFGFGDHADEDDEFFAFFCBFCBFCFAHDDBGGGEADHHBHBBDEEGEEGCAGCDCCGCEBHHCGGCDBCHHEAHGAEGHEFADGDGEDGDDA,False +172,6.0,4.0,6.0,6.0,3.0,10.0,5.0,4.0,GBFGHFGDEDFCDAGDHCDACBECDECAHAFFAFBCBHAFFGFF,False +173,2.0,0.0,4.0,3.0,0.0,0.0,1.0,0.0,DDGDCCACCA,True +174,3.0,6.0,8.0,12.0,9.0,8.0,4.0,7.0,FGBDDHHDCFABFABCBCCHDEHEFAEFEBFEDDHDBCDECFHCFGEGGEDDCDDHE,False +175,4.0,4.0,3.0,0.0,0.0,0.0,2.0,1.0,GACGABHBBAABCC,True +176,4.0,2.0,4.0,1.0,2.0,1.0,1.0,1.0,HCDACAAEABCFBCEG,True +177,22.0,20.0,10.0,18.0,13.0,13.0,19.0,20.0,CBHCGHGEHEEADBHGAEGFEGFBAEBCFAFEGHCBABFADFDDCHBCHDHAGGADBAHFEEFHBBHBGDDDHDGHGFHAFAAEGBBDAADHGBEGBAGBADBAHCHHADHDGGDFGDFDCABCABCABEFHEGA,False +178,22.0,19.0,25.0,28.0,26.0,27.0,22.0,13.0,CCCCCCCDCAGHEHCGDGHCADEADBADHFDGGGBDACFHCFHDGBDGDAGDCDDBBCEBFBAABDCDDEDFEFEECDEBAFBDDBFEHEEAEFGEFGEAGBFFBFFBCFCFDGHEFCAFCAHEEGEEBEAHDGEFBFHDFEDCDHCDACGGBGCAGDAFAAFEAFHDFEGECBBGFAEFAG,False +179,3.0,7.0,11.0,8.0,19.0,13.0,15.0,4.0,BEEBAEFHEBGCBCEBFHFDECDCGHGFEGEEBECGFCGFDGDDGFAFFAEGCEFCEFDECEEGDEGCGGFGEBDHCEGF,True +180,23.0,18.0,16.0,19.0,17.0,9.0,16.0,16.0,DACDHCDECEHCBACDAFDAFABCEDHDGHBCFFABCDDFDDHCAHBAEDABHABDGDFCBECAEAAHGEFABFGBGBHABHCEAEGAEGEHGFHEAAEAHGCEGCHGAEGCBGCDGDEGHHADBAGBEDBDBB,False +181,7.0,4.0,3.0,4.0,1.0,4.0,0.0,2.0,CDDAFABHAECADFHCFABFABDAB,True +182,7.0,17.0,14.0,12.0,11.0,8.0,17.0,16.0,ECEECHEGDCFDCFDCEDBBGBGECGBHGFFGCBHEBHABAGBHFBHDGHBECBEHHGCGCCGCFGHABADDDHGDHEBHBCGGFFACHAEADBHDGHBGDB,False +183,18.0,19.0,14.0,22.0,20.0,25.0,20.0,18.0,FBAHCEHGHHGAEDEDDHDHGFACFDBFGCCBHGHHGBHGECBHFDEFBEBHECHFGDFHDEHAGGEGDBGAADFADAADGADGHFFEGCABDGFDBDECDFAFAEFCEFCADGFDFFBFFBHFCECGEBGEBHEADBBDFBCFDCFAAEGBEABE,False +184,9.0,17.0,14.0,14.0,12.0,19.0,15.0,10.0,DBDDHCBBBBGGFEBFEAFGCFDCADCDFEFGHFDHBDCECCFDCAEBEDHFDCBDGBACACGECFEHDBACBFFBFFGGDEGHHGCHFBHFBEFAEAABGFBGEGGFGH,False +185,5.0,15.0,12.0,28.0,11.0,16.0,11.0,13.0,FBEBDDHEDCEGFGGBGEBDBBHCDGDDHBDHECBDFBDEGHEFHEFEDCDHGDADDABHABDCBDBFDHGDFDCGHCGDCHHGDADDEDDAFDFFHFFECDCBBFFCFFC,False +186,3.0,2.0,0.0,4.0,2.0,3.0,6.0,2.0,EGADGADADBGHFGBDGHFGEF,True +187,7.0,12.0,9.0,16.0,4.0,16.0,12.0,10.0,BDFDFFBBBEBBFCHHCHHFFEGDADDFDFHAFDAFBBGDBGDBDDGCDFFDGDGCBCADGEHGDHCCHACABHAHGCFGFFGEFG,False +188,9.0,14.0,12.0,11.0,9.0,6.0,5.0,4.0,DFBEFDCDCBAFBADEFDEGCEBCGFCECHDBADBADBEEBABGHBACBACBECGACBBCADDHFGHECD,False +189,15.0,22.0,16.0,23.0,11.0,18.0,13.0,25.0,CHGBHDEHBEHDGCDFHFHHCHHGHEDDBGHACHECHBHGDHDCHDEAGEABFAEFACBBDDBDBADACDABFAHDABACBHHDHCAHFFBBDBGAFGFFBBABCGEEFEDCCDCBDBFDBFEFGGFHHFHDCADBDGFCGFH,False +190,23.0,11.0,18.0,25.0,19.0,12.0,19.0,38.0,DEHHAGHADHGCHACEDCAGEGFDADHADHDDGEEEEHFHGCAGEDDFHHEHHDHDGBDADHECEEGAFHDBHGBHGBDAHAEHABHBBFDDCDAHHGHHEHFGHCHDDECBFCADCGDCGHCGHGAHGABFHFHHFHHEHHBBAEDAEDFCCECAAGACCACAF,False +191,5.0,6.0,1.0,7.0,12.0,13.0,5.0,13.0,HEEFEHAEHFFHFGDFEDGEGAFGFHGEHDBHAFHFFEAHEBEBDFADBHHHEHBECFDBFD,True +192,14.0,9.0,19.0,16.0,17.0,13.0,14.0,12.0,FBCCBDDFFDHDDHGEFGEFGFHGFBDFCEEHACCAEEDBFDEDCHFCBAEFCGGAHFADGAHEHHAHBACBCEDEEDCCDCGACGCCGCEGDECAECAFGABGBHGDDEAEHA,False +193,13.0,11.0,10.0,13.0,18.0,18.0,16.0,24.0,BFHBGDBGHEFHEGEEGAAFHDFECFEAHEAHDFHCHHEHFAGEGCCHHEDHEDCCDAGGAGGBDCBDAFHFFAFDAFHGCHGCFGHGHHCHDBHBFFADFEDEBHGGFBADHAEEEHEEBFB,False +194,4.0,3.0,4.0,0.0,0.0,3.0,1.0,3.0,HCHBAHBAGFABCAFCFC,True +195,5.0,5.0,1.0,2.0,4.0,4.0,7.0,2.0,EFBGHBGABGADGABHAGDBECGAFGFFEE,True +196,16.0,12.0,12.0,7.0,4.0,7.0,9.0,12.0,ACGACAHFFCEACGGDEADCAGCFHBFBEFDHDBHAAAAGHBBHCBHGBAGBACBDCBHCBACDECHHAGHFHBGADFA,False +197,11.0,6.0,8.0,7.0,7.0,10.0,12.0,14.0,GHFFHACEECGEGGDBGBBFAGFGCHGHDGAEGCCBHCBHAFHAHDAFGAFADCADHAHHBCDFGEAHEHHFDEF,False +198,21.0,16.0,17.0,15.0,22.0,24.0,21.0,20.0,AEFABCDCDABGHHEHDFBBFCAGGAEFCGGCGABGACGHHGDGBDBBCFACBDFHHEHFCHFCECHFCHGEHGBFFECFBHFGHFEDFDCFCEAEEADDGDEGFEGFABFHBFAEHEDDADAAGAACEACBHEBFEDFAAAGGEGGBHEEHFEHF,False +199,3.0,4.0,1.0,2.0,7.0,5.0,9.0,5.0,HFFFEGEEGAHGBHGAHDADCBGGEEGEGBEGBFFH,True +200,27.0,17.0,26.0,18.0,16.0,17.0,15.0,13.0,BDEBEEBCBBCDFCHCCABDEGCGACGACACFGDDGAACBACEEDBDDCCCHCDFAHBGEBCHGGFCGHHHABHBGAEHCBGCDAEDFEFBEAHEAFFGDFHDHHDFDBFEBAAGAAGAGFCBCCEACEACECFAFAAFAADCFDAFDA,False +201,14.0,18.0,22.0,18.0,23.0,25.0,18.0,25.0,EHGEHCBHCHHAEHDEHDEAEBCEBCEGFAHFAHCEHBFHBHHBHEBCFADGHFGCFBAFBDHCHCEHADGBDFBFFBHBGGEFFFDFEBCDFDHCDHBECDEHECBECEFAGFCGCAGEHGEDEFHFCGCCDACAAFDAHDFFDBGDGAFGCBCDFEGFGGE,False +202,6.0,4.0,6.0,6.0,4.0,7.0,2.0,1.0,BADGAEAACFACGEFBACCEFCEFBDHDDFDBFDCF,True +203,4.0,8.0,7.0,5.0,6.0,6.0,6.0,7.0,EHAECAEHBEHBFHBCDBAEFEGGCFGDGHHACBBCGBDHCDFCDFGBF,False +204,6.0,15.0,10.0,9.0,18.0,10.0,16.0,17.0,EHHEDFBDFGDGEDGHFEEDDBGFADFCBHCBHFEEFAECGHHGBCEDCEHFACGHEGHEGCBGHBCHBEFFEHADBAGBGHCHEEBEAGEBGBHGBHCBG,False +205,6.0,8.0,4.0,6.0,11.0,10.0,4.0,7.0,BDFBFFCHFBADBGFCGCCEEAAHFAHFGFEEFBEAHEBDEBDFHDHEGEEBEHDA,False +206,7.0,11.0,7.0,14.0,12.0,11.0,11.0,15.0,DFFHFBABAHBEHBEHDHGCHFDFAGCGHEBADHGDHCEHCEFCEFGFFGHGCDAADGBBGDBGEBFEDHABHDBCDHHEFDEGDEDE,False +207,14.0,19.0,19.0,16.0,15.0,16.0,25.0,15.0,BHBBDBDDGDAHEGEGGECDCCBCDAEBGEDGHDCHFEHACACCEDCGFGFEGDGGAGGAGGHFBEGCEGCEBCAFGHEBHDAEGAFHHCADFBBFBFFDHFCHFBBGBBCBACGFDAFHBCGFCGEDGADEAHFCHBG,False +208,14.0,24.0,23.0,25.0,20.0,23.0,13.0,19.0,CGFHBECCCACGAFFHDFHDAHCCFBDFBCCBGFDAHDABGABGHBFHCDGDDHBHEBCEDEFFEFFEFFCDDGGECDEFDADDHEACEAHEAEEBFBFGBDBBFCBDCFDGFHBBDBCGCDAHDCCDHCEEFEGGECBBABDCBDEFEHHEHHBHBADFA,False +209,5.0,7.0,7.0,12.0,11.0,5.0,6.0,4.0,BEEGAGCAHCFDCAHCEFCAFGGDDEDCBDBEFBEDDADDHDDBBDBEEEGCEGHEF,False +210,21.0,21.0,29.0,26.0,25.0,22.0,25.0,25.0,HGGGCBGCBGFDHCEGCBADBADBDFHCBHDBEBBEHBEFBCABCACCFCEFHAFHGFGDDGDDHHDEDDHCBEDDEDCBGGFAADADGACHAFDBEBEECDECEFGGHECHEFHEBHEDGCDCABCEFGEGHFGHEECDBHDFDFGCAEAGEAHCHFAHDGHACFACGHHGDHGCAAEFAFBCBECGFCFFCA,False +211,25.0,20.0,15.0,18.0,16.0,31.0,22.0,17.0,GDHFDBEDFEFGAHDFFDBECFDAFDBFGBDAEGAEGFDCFDCEACBAFHGHHFBFFBHHEAFBAFDCFBGAGGACBACFCEACEACHHGDHGCGFHGHAGABGBGDFHHFCACEBHEDDAFDAGCADBEGBFGBFEFFEAFGCFBHFEHGABAABAEGAFDFB,False +212,11.0,12.0,15.0,21.0,14.0,13.0,13.0,22.0,FDHBAHAHFDBFDFCHHEFHDFAGBADBADCHDFFDABDHCDHCGAGFHDDHEEHBHHEHBCBGDGCDCDECDEGEBHEHHGHDFBCFDAGCAGCACCEFCDBGEBGEDEFGHCGHEDHEA,False +213,26.0,25.0,22.0,24.0,22.0,21.0,23.0,28.0,DGGABBFFGEFGHFBHBHFAGAHGECGEBAACCADCHDBGDHCDFEDCCCFBFAHDEGGBGECFEABGHDEADGBGGFDEFAABAAHAAHCAHGFHBFABFAEHHCHHCFBEEDEEFEGDEHDHHDHCBEABAGGAFGDFDCBCHBCHBHEBAAGCADCHFCFDBBDBCDECHACHDBEDHEFGADGHDBE,False +214,17.0,18.0,21.0,25.0,26.0,17.0,17.0,17.0,FEFAEAHHABBGBGGCDGDEEDAEBGFHHCADDHDDEDDEAFECGGAGGEBGBACEEDEEDHDDHGBHEBCBHADFEDEGGCDDBDCFCHFEFAHFHDBHDBHAGCFEFFEBEEBEEDGEACFABBCBFDBFHFECGHCGACDCCDCCECFHAACADC,False +215,3.0,8.0,12.0,3.0,11.0,1.0,8.0,8.0,ECHEGGEHEEBCEHGGHBAADGCHBCBBCHBCHBCEDFEGHEDCGCCECEBCGA,True +216,3.0,7.0,2.0,4.0,7.0,5.0,4.0,9.0,EEBACHABHEFDEHHEBHAFHFCHEDGEBBDFBHGBHGFDG,True +217,24.0,19.0,23.0,32.0,19.0,19.0,18.0,19.0,BDFHFFHEAGCGGEHGAHGADAEDAEGACABCBFDEDDEHDGDDEDDGCDGAFBBEBHFBDEADCDDCHBCEAHDBHCBHCACBGCGFCGFCGDHFABCACCABHEEHDGBFFDFFBHADDDCAAHDAEFEEFBDFADGADHADFGDCGCCBECADAHHCFDCGBEFEEDHBA,False +218,15.0,9.0,15.0,14.0,9.0,15.0,10.0,14.0,EDDHBDCEDAHHCDHCDEFECFDDBDEGDCAFCAGCHCFHBFBDFCABCEGEEHHGFHAFCABHABDAFAHBHHGFCGFHGBAAFDAFAAFEDFAGGCCGC,False +219,24.0,26.0,20.0,28.0,17.0,21.0,17.0,23.0,FBGGAGHAGHGGBGGFFDAFDHDCFBFFHFDHDDHFDHFHCFGDHBEFCEACHFEHCBADHDBADCEBCDDAGDAFDAEDEHCAFDAFDFBBAGBGHBCHAFECHDCEBBEABGFHEBHDGCEFCBACBACBCCBHBFGDADAAHAHBGDBDEBGECEDHDAEBAEBAEHADCDBC,False +220,10.0,6.0,12.0,8.0,3.0,8.0,5.0,9.0,DEDDFFBCFCCAGBFHBACAACAHFAHBEGGAGCDCCDFCDFCAHCACDHEHHABGDBHFH,False +221,18.0,20.0,25.0,20.0,16.0,11.0,30.0,25.0,BFFBEGBGFBGHBEFEDHBDCAAHAGHFGDADCBDBBDECAEBAHGHGABBHHBGCGECEECADDDGHDGBBGBCGHHGCHCCHCFHGGHAAHAHGAHGEHGDHBEGFHFAHGADFEGBDHFDGCDGCFGAGCCGACGHEGDCCCABCECGEHDEDDCCECADCB,False +222,19.0,19.0,21.0,28.0,17.0,28.0,23.0,16.0,FFFFGGBAGBFCDFCBFDGDDEDDFDEFCHDCHACAAFFDGFHCFBCDGEGEECCCBBAHHDEHDECFGGGDDGDDGDDCBACBABHCDCFDCEBEGBCHEFHGBHABAGFGFADHAGFAEFHEBBFBEFCGFHAFGADGAFHBCABDEDDCHFEHFEGAEDCGDFADBAG,False +223,23.0,19.0,28.0,13.0,18.0,28.0,23.0,33.0,GHBCHBGHEHEAHDHGDCFBHGCHGCFGCBGBGCDHEFAGHEGAABBHECFCFGDEHCEHAFCADAGDFGDHACBACHACHCHFBEFCFGCHHHHCHBCBEDBFHBEHBAGEACHACFAGGHGDHFFAFEADEAHFAHCCHEFGEFBFCBHDFGFFGAFDACDECECBEBFHBAGCHGCAFFAFF,False +224,3.0,2.0,2.0,3.0,1.0,3.0,0.0,0.0,DAADFBDFBCACFE,True +225,18.0,28.0,26.0,15.0,16.0,22.0,28.0,24.0,CCBGHAGAEGAFGBHGCHGBBBHBBHCBDDBFDFGECEECAGHEBBGBAGBFGCHCCDGCDHEAGCBBFBBFCBGGAGBDGHGGHGHHFHDCEDAFGHBGABHBEAACGCCHCCHBHHFFFFGCFHCFEDACFGEFCAAGDCDDHDBAABFACDABEGCEGFEHFEFCEDBFHBEHF,False +226,0.0,1.0,4.0,5.0,1.0,5.0,5.0,2.0,DBGCFGDHGFCGDHGEFCFDCFD,True +227,9.0,11.0,5.0,9.0,13.0,8.0,7.0,11.0,DGHBGEBGHACBAFHAFHFHDDHCGEAGEDEEBEAGFDFBDFBHFHCDHCEEAFBABBEEBEBDHADHGEEAC,False +228,3.0,5.0,4.0,5.0,8.0,4.0,5.0,8.0,DCEDEHGEHGFCEFGBDHBDCBDHFFHEAHEACGBGHAEHEB,False +229,5.0,2.0,1.0,1.0,0.0,2.0,0.0,0.0,ABABFACFADA,True +230,17.0,15.0,18.0,10.0,25.0,10.0,12.0,11.0,ECCHCABEAEAABAEBGEBCEBGAAGBBDFHDEHDEHCHHCHCEHEEHCGBAFCDEEFGEGGCFDEFBBADBEEFHEAHECGFCDAAAFBBCCCACBGGBAEDDEGDECCEFAEFAEG,False +231,31.0,18.0,29.0,27.0,23.0,14.0,25.0,29.0,DGBAGHGHDGCGACBADBDDEADFCHGDBFEBHEBHEFHFCDFCDACFGHDDDDDCGCEAEEADCBDBGGHCAACAEDACHEHHAHDDFDEHCEHCECEHHEAFEABCGEGABHEDHEFAGCGGCGACDAGDACAAHACBBCDACAACHCDHGAHGFBDAACEACECFEHGGHBGHBCFFGDBGHBEFEHHAHBAG,False +232,9.0,27.0,30.0,27.0,17.0,16.0,18.0,20.0,HDBHDCCCHHCHECBBCGCEDCHCADGDBBEBGEGGFDFDDGDBBFHCEEDFFFHFHHDGCEBCABABDEHDHCDHFDHFDHBDHGGEECBEHBDFDDBCDCCBCCGCAHDBBBBFBEHBEGBEDDGAAHCBECBCCBCFFEDFEDCCGBAGACGDCAFCGFGG,False +233,13.0,14.0,9.0,12.0,10.0,11.0,7.0,12.0,CACBADGHDGHDFHDFHDEEDGEBBEDHACHABBFCFAEHACFDCEAHEABFFBFEAAEBCHDGBDBBGCBFEAFGDCDHHABHABGF,False +234,27.0,12.0,19.0,20.0,14.0,11.0,16.0,19.0,DCEACEBHDGHAGFBGABGABGABCHFEADDADAHDHDGBFAECCBCHHFADFEFAHDAEDCHCHADBFDCGDCHECGAAAAGBAEEHGCCGEAGEFCDFDGGCGACHCEHCEHDEHBCADAADADDFHGAHBAHBAF,False +235,10.0,14.0,16.0,10.0,22.0,13.0,14.0,12.0,BCEFFEFBBGBBGEDGEABFACCDCCDHEGHCBDGHEEEFAGBHGBEEHEEHDEFDEFCECDECHGGAGFFEDGHBECBHCGFEAAEAHGBHGBHEBAFACCEDCACFDCF,False +236,7.0,11.0,9.0,8.0,13.0,11.0,4.0,12.0,AEBEHFHFFGFHBFHFAHBHHBHFEFABBEBAEFCEACHHDGDEGABCCBCEBDEDCEACFHCFDCHDEEDBGDE,False +237,23.0,30.0,14.0,18.0,17.0,26.0,17.0,30.0,DGDDFCEFCGCBBHACAFCEEEEAADADEHFABBADHADHFDBFHHFHDFDAFEADBADCAFAFBEBBEBBCBBCFBEFBGFBHBBFFHFAHABHEFHBFHEGHAAHBAGBGFHAFABEGEGGDCGBHBCHGHFGHGHHCDEFFHCBHBBHGEHGDHFDHCDBDAHGHBEAACFG,False +238,19.0,27.0,27.0,14.0,19.0,23.0,28.0,21.0,CCCACCFBHFGEBABBGFFGBCHBFAAFBAHCAHCBGABGADDABDAFDBCGECFEHBCHGHHGHEGDEBFBBCGBGHBGFBCCBDGDCHACHADFADEHDEHEGADGAFBFGBEGHFHEADFCCGCCGFCEFGHFEFBCDBGHHECGBCFAEBBCDGAGCAGFFEHGEGFEGBECHE,False +239,12.0,6.0,10.0,11.0,16.0,6.0,12.0,10.0,DBDGGDGCDECGHCHEAHGDEFEEFEBBHABCCDACGFEGHECAFAEDAHAGCBGAHGAGFABFDEEDGEHEECEDCEAHDAH,False +240,12.0,11.0,10.0,12.0,15.0,7.0,12.0,8.0,EHCEBGEBCADCDFCEGBEBCEBHDGAAGDGHDCFDEEGBEFEEFGEHGHBEABEAFCFHCGHCBADAADADGAEBBDDHDFGACGA,False +241,24.0,20.0,23.0,18.0,18.0,16.0,33.0,12.0,DCADHACHFFHADCCDEEDCEDCFAAFGBCGACGAGGACHBBDBCCBEFBGCDGHFECABCACGAEFAECBFFFHGCAECAGHEHBFHBAGEFGECGHBABCADDGGDGGDGGCGCFFHGGEAGEGEEBBEGAGFFGDGGBGDBGDCGHAAABGEBEBDDBDAA,False +242,2.0,5.0,2.0,2.0,7.0,2.0,2.0,4.0,EHCHBDECDEGFEAHHABBEBFEBGE,True +243,5.0,8.0,9.0,5.0,11.0,13.0,13.0,9.0,ECEEGBGFFHFBEFHFDBGDBGFHFFHGHCGHEACEABBFEEEEGCGGCFBCDCCEHCDHGAFGABGHFGAFD,False +244,8.0,13.0,8.0,11.0,10.0,14.0,17.0,10.0,EGDHGCEDHEAHFBCGBAABGEDAEDAEGGDDFDCFGCEGCGFADFCFEBBCBFDGFAGFEDFBGFGHBBHEDHGGHBAFBFHCFHGBHGB,False +245,10.0,16.0,19.0,10.0,13.0,11.0,21.0,15.0,BEEBGHAGHCCFEDFGFHBHHDFDDHCFAGFAHABFABGAFAACBECGGGHGCAGCHCEFGEHBEHBGFGEFCHDHHDEBCABDGBGGCGGCBGEBGDCCCCDCBDEBGEBECCH,False +246,9.0,13.0,8.0,9.0,4.0,11.0,15.0,3.0,BDDBDDBAGAEGABGEDFCBCCFCDABHCBGDGGEGCEFAGBAFBGGBGGBDFFAFBCGDHGHFFCFAGFAB,False +247,24.0,29.0,19.0,27.0,21.0,19.0,25.0,36.0,AGGDCEDBEDGADBCBEDBHDFHDBEFHEFEEGEGDEABEFHDBHBHHFFAFBGGHCFFEAFDABEAFCHDCABBBCBEEBFBGAGHBGHCABCAFHDGHCHHCDGADHADGFHGFCGDBHBCHBDAEGHHGHHAHCAHDDBGHBGCEAHGADDHDECGEHHEDEGFEDABHABHABCABDABDACHGCBGDHHFHFFGC,False +248,23.0,15.0,19.0,20.0,20.0,17.0,12.0,20.0,AEDAEDAEFADFAHFAHEEHBBCBBDBCAFAAGCCGACEHEADFHDFCDAHGBEFFEFDAFGACGECEHHGADGBCAFCGCHDDDGCFFDBCHECFEHEABEABDCBHFDHECAFDABDAGEBGHGEHDBADBADCHCHHCFHEEH,False +249,5.0,8.0,8.0,6.0,8.0,12.0,5.0,4.0,DDADDFEDFHACECHGGHCDBBFFBEEBGEBCECCGBEAAGAEBFCFFHFFBFFCF,False +250,9.0,9.0,5.0,9.0,9.0,5.0,9.0,6.0,EBGEGDECAEBBGBFDBACGCBBCBBFDADDACDGEDGHDHDAHEFHFGAEGHFGAAEHAE,False +251,3.0,4.0,6.0,7.0,2.0,6.0,5.0,5.0,FCHFEBDGHDHADFGGFGFFEDBCCBCCHGCHDBDDAA,False +252,23.0,16.0,22.0,22.0,17.0,24.0,15.0,22.0,GDGADAHGFBBFBCHBDHBDCCDHEGADCHBBDFHCGGCEFBECHECEACFDBADEACEDFFDFFDFCEFCGFCHFGAFADGAFHAEABFDEDHHBAAAAHGABGDBFEHFHHFCHDCEAEEAEDCFFAFHCHHADHACHAEDABDCCGGCGFCBFGEHBD,False +253,28.0,21.0,24.0,17.0,16.0,23.0,19.0,22.0,HBGAFCHGAFDHGAHGHGDDGADGECAACFACBDGFCBAHBHDBFDEFABFACAEGFHGBDGBFHDFHCGBAGCABEGHEFHECCEAEHADHFDCCDCCEAFBDDBFHHFGHFCHCDHCFFCBAEFAEFEEAAEBFCBAABAAHEABBAFBGCBGCBDFGAGCCDECAHH,False +254,22.0,21.0,35.0,22.0,18.0,16.0,18.0,17.0,CGFCBBCBBCFBDHEGBFDEHCCAECAHAFDEEDAEHAEBCHFHBFHCHBGEACCCCDCABFABCDBDHCGCCGDCDDADDGGEHFEGCCBCBAFDEFDAADFAGGHECHECHECHAHGCFBBBBAGGEDBFDAFDCEDCEDCADCBHEFCAGCAGCBGFDACAACGGH,False +255,16.0,23.0,16.0,16.0,20.0,17.0,25.0,22.0,FBDCDGFHBEHADAEBABHAGDEEDGEAABDDEEFEEDBCGGDHHDHGDABBCBBCDHCDBGDBGCHGHAGFECEEBEHFGDFACHGHHGBHCEHCECABHADHACFBBAEFCEHAGHGEHGFHGFGGFGBFBFCBGCFGEFGEHBBGFCAFGAB,False +256,4.0,5.0,1.0,1.0,3.0,4.0,5.0,7.0,BHFAGFAFHABDAEHHGHHGEGBEGBCBHF,True +257,15.0,16.0,15.0,21.0,14.0,16.0,23.0,29.0,BBAHCCDBGFHGFGFFCFGCGHCGHDGAGHDCHDEABEBGGFDDFHDHHGHBAHDGCAGBGEBHBCHGEFGEHGEBFECHEDGEHBAHBEHDACDHHHBCHBCHAFHDCHAHGAGGDDBDDEACBAEEAHDDFFHGFHFFDAEDACDFG,False +258,25.0,18.0,28.0,20.0,16.0,20.0,26.0,30.0,GBDGBHAEEAHBAHBCHCCHCEBCECDEAAFHHCGGCFFDFBAGBHGFHDAHBACCADCAECAFFAFFGGEGCEACECCFCBEAAGFCFFGGHCDECBGHBHACAAFDGHDCHDCFDHFEHFDGDGHDCHAEADGGEADCHDHBGBDGAGGFFHHFHAGHCHHCDBGHBEHDEHGABBADBCG,False +259,10.0,4.0,2.0,8.0,6.0,7.0,4.0,6.0,BFAHHADDBDEBDAHFACEADEFDEHDGAGFDGFAEFBGFEAACHAH,False +260,17.0,18.0,20.0,22.0,23.0,26.0,23.0,18.0,CGCHEEDEBDHDGEGFEFFCAHGBHBEHBACAAFAFFDBFDCFAEFADFAEGBBHADAGGHFGCCGCGFBDFEEEEADHGDCEDFGDEBDHBGHBFFCAFCECGEDADDBHGBECFEBFEDFDDEGDHCAHCFFGFFGAHCDHADCBECBHHBHCGFGGABGCEGFE,False +261,27.0,24.0,20.0,19.0,30.0,32.0,21.0,26.0,GEHGECEEBEDACCACGBFGFCDBHEFEEFGEFBFACFACFAFFAGDACBAGDEBABFAEDAGHAHBAECAFDFEEBBBFEBDEFCHFHBFHFEHDGHBGHCCFDDAADEAEECGGHGFECFEDFEAFACHACEFBEFHHBHHFEAFHBFBBFBHFCAGHHFHHGHDCHDCHFGAGDDGCAGDEEAGEBEDAGHADBBB,False +262,24.0,26.0,23.0,23.0,21.0,23.0,28.0,24.0,CFDHHBBHEEHEHHEFHBDAADAFDBCDHDDFGAFCACEADGBEGCGCHEAHGADGABGADCFFBFEDDAFDCFHBBCFBGDGCHECBEBBCABDAECAHAHHAHEBHDHHFAHGEBEHFAAGBAGBGGCAFAFBAFBDCDCCDGGDGBHBBCBGFGEEGECGEHECDFCBFGBDGCACEFGEGGFHGFDGF,False +263,0.0,1.0,9.0,1.0,3.0,4.0,6.0,1.0,CHCCEFCGGBGFDGEGCECCFCFGC,True +264,6.0,5.0,5.0,2.0,0.0,4.0,6.0,0.0,CCAGBBGDBGDBACACGAGGFFFAFBAC,True +265,4.0,10.0,10.0,7.0,1.0,8.0,4.0,4.0,BEFBDFGDFABCABCHFCDGBHBCAFCAFDBDBGGBDFCCBCFHCDHC,True +266,22.0,29.0,31.0,16.0,20.0,28.0,16.0,14.0,EHAHCBHCBECFGBBCHEEBAFBHHAFGBFDBFCBFCBFCBFCGFGECBBGFCEFBEFDEDDGFCFCAGCAFCEGAAGAACDCFGAFGAFHBGABDAGAHCAECABBBCFBCDEAAEBFBBFCCFCCFABFDDFBEHBFGEDBEDEHAECBGCFHCDECACCDEFDADEHCGDBHH,False +267,19.0,18.0,7.0,10.0,13.0,13.0,13.0,11.0,HAHCGEBDCBCBBEGHFGBCGAAGBGGFDGCAEADBAHBFEFFEAGEHCHHBAHAADEFGEAGFFEFAEFCBAABAABEAFGAEGDEDBBABBFBHHDDHDBFD,False +268,17.0,10.0,10.0,7.0,8.0,5.0,14.0,9.0,DCADHDGHAGBAEHECHCGADHCGAEGBEGAEGAEGACAHGHDCBGHBGFBCAAAACBBEEBGBCFCAFDAFDHFGABGA,False +269,1.0,3.0,0.0,1.0,3.0,4.0,3.0,1.0,GHGGEBEFBFABFEDF,True +270,23.0,19.0,18.0,18.0,15.0,13.0,11.0,15.0,AHDAFCAECAFBHBCEFDEFCEFEDAADBADCDDFDAFGEHGEAGHADBBEACFGBDHADGCCABHHGHFBEDGHFEACEFCBAGAAEABEABGABHBEABGABFCBACGDDHFCHBCHBHHCEDCDDCDBC,False +271,7.0,9.0,4.0,6.0,4.0,10.0,14.0,6.0,GDDGADGAHAAHABDGFFFECFBHBEGEGHEGDCABGGFFHFFHFBGABGDBGCBGFGCB,False +272,9.0,5.0,1.0,2.0,6.0,2.0,1.0,1.0,EDAEAFECFGHAABAEDEBBEBAABAA,True +273,6.0,7.0,5.0,6.0,3.0,4.0,5.0,6.0,DBGDAGHAGECGFBHFBGDDFEDFHCBBEHHCAHBACBACAD,False +274,13.0,30.0,20.0,14.0,22.0,14.0,15.0,16.0,HBGBBDCBAHEFEBDBCABCGFGEHGECGCDECDBFDECGHBFHACDCBBHEHGGHFGBBBBHBBHBBGBEABHDBGDEGEFDECCFHEBHEHGEFCFBCFCDABAAHEECEECEDCEDGEBFEBAABGABCBCAAFDAFDHFC,False +275,5.0,8.0,10.0,12.0,2.0,10.0,10.0,5.0,HGDDCDFCDBGFCGDBGEAFACFDBDDBHDBCDCCFGCHGDFGCFDABHGBAGCGFABFEHF,True +276,5.0,1.0,0.0,3.0,1.0,2.0,0.0,3.0,BDDHFAHAAHAFEAD,True +277,24.0,23.0,18.0,24.0,16.0,33.0,19.0,28.0,ADCABCHCAHCAHEADEAHBGBCGFGFFGAFBDFGFBGDEGDGHHGHHACDDGFFAFFBFFEFADHDDADDFFAFGBFBBFHFCHBDADEAHECEDFDGFDFFDCBBHDAHBBHCEGEBHHBFFCCHHHHCHBBHDHAGCAGEDEHDGHDAFAFBBFABFAEAAGABGFEHCCBCHECFEDFGFE,False +278,12.0,29.0,23.0,26.0,19.0,18.0,23.0,13.0,BEBBEHBCAFAHEDDCDBBDBBDAFFAFCADCGGBGGCGHCFECEBDECGEHGEADBFDHFDGCDGCBCCHDBEABDCBDEBEEBDCGECBDHBEHEAGAFGHFHEFBBDBGEBFHGGHFGFDGCDGDDCFFFDFECCGCGGFBDBAACHEDBDDBGCAGBBC,False +279,16.0,11.0,17.0,16.0,19.0,22.0,19.0,14.0,GFAAFDCCEGCHGBEGDABFBDFEFEEBEBGFCGHHHFHAFDADEAHACBFCDFHFGCDACDFCGFEDFEGADGAFCEHCAHBBHEGCDDHDCAFCAFGEEGEEFBEFEHAHFDEFDBGDBGAFCAGCGGCGHE,False +280,10.0,14.0,13.0,11.0,22.0,14.0,17.0,12.0,EHCECEHBFGCGGCAHCDGCGGEDBBBFHCFBFBBFGHGHFABEAEGACGACBFDBCEECDEBFEBDGHDEBEGGECGEHGEDEEHFEHFEGFAADGADEHDAFDHFEEFCBA,False +281,32.0,31.0,18.0,18.0,36.0,28.0,25.0,12.0,GAHFABEGCGAEFADGADFABCADAEBAEFEHFGBGCBHDAHAABBBECFEAEEFEEFEDAEBAECADCDDBBBCBBEDBFAAFHEEGFCGEEGEFGEFAFDABCABDAFGFBGFEGBEACGGHFGAFHBBDEEEGGBHGFFAFFGEFGEBGDCHCHGBBGABEABEFEDADCEEFDCDHCDBGABAACAHCEFCEFBEB,False +282,19.0,24.0,17.0,28.0,20.0,14.0,18.0,11.0,CEGDBCDFGFGCADCEEGFABEDBDBBDEFDEADBGBEGBACDDFDHFBHGGCGAEGHEGHECDDGDFGEFABAEEHDFBDFBEEBHCDCCEHHDCGDBHDFDDADDEEDBBBBABHAHDABAAGADBCFBCBECDAGECGACGACFABFA,False +283,26.0,21.0,30.0,21.0,22.0,23.0,22.0,14.0,ABEAFHABHEFEEFBHDAHFBHFBAFBCBGGHGDHFDHFBEBBACCAECAECACGBCFFEFCEGGACBCDFAAHABGDEGDEGDACFEGDEGAFAACCBEABGAFDCFDFFGACHCEGCFGABCHGAHCDHCDCCDCGABDFBDEDCGFFBFEACCDCHDGGCGEEAEBAGDCDDCEEB,False +284,14.0,18.0,15.0,12.0,15.0,14.0,12.0,12.0,DHBFHFFADGAHCABFABEEFDEAGEAGDDBACBCCBGCBEEBEAHEHCFFCEFCBCGDCGDEGHGGABADBEEBEHCHHDBEGGFFEFDADHAHBBDFBCCBGABCFHCFA,False +285,16.0,15.0,17.0,12.0,11.0,20.0,18.0,11.0,HGHCBHCECFEHFEGDAFFGFEGFEAFGFBGABDBBGBACBGFBECAAFDAHHFGGAGGAEGCBDBBDHEFGGDGEHAHADEADEFCCFCFADDBCCBCABHAFFCFGCFDCFACDBCGH,False +286,11.0,13.0,7.0,7.0,10.0,17.0,12.0,13.0,FDGFDGFHABDDHFAHBHFFGCFHBGAGFFGFHHAGHEGHCGBCECDECDBHBEHBEHCAFGABAFBGFBEFGEABFBFDEFAEAHEABC,False +287,8.0,6.0,3.0,14.0,2.0,6.0,4.0,6.0,BGDFDCCDGAFBADBDHHDHCDHAAFAADBADBFDEFABDGHEGDDFHD,True +288,13.0,9.0,15.0,13.0,19.0,11.0,16.0,13.0,GGEDADGABGCBHAGACCFCHECDDCBAFEEHEBBEABEACFACEDHEAFEGFGDAEAAECDEFEHHEHBFFDCFDCDAGDHEBHCGHGGHCEFCGFEGEDGDCGHBGH,False +289,21.0,24.0,27.0,24.0,13.0,22.0,21.0,28.0,EBFBBCGBDHCAHFAHBBHBDHBDHADECDCAHCGHGFHADHDCHFBBAHBDHECABFBFFCDFGDFECBECBCHEAHFHHEHGGFAGBDCEHCFHCGGBEGFHBFGAFCADDFDDBDFCAFCHFDDACGACGDCGAGGHDEDECDAGHBFABABBEFBCCDEAHGAHGCCGCFAHDGHC,False +290,11.0,5.0,20.0,12.0,8.0,15.0,4.0,7.0,CBCCHDDHADEADEFDAACCCFFDFCAFCADCGDFEDCECCECFFHFFAGFCEDEBFFHCHGCDBHGCFDAFBAEHACCACB,True +291,20.0,16.0,14.0,23.0,25.0,13.0,17.0,18.0,GBEGBEGFEGFBFDBFDBADHAFBDFGDEGDGGECCECAEAADAACHHHHBHEGDADDBHAAAEHEBDEBGEAEHDGHAAHFABCEGDFGFCECDGDABDHBDECCABFBEEDEGFEHFEHGAHBDCDAEHAECDCFDCEDHGHEC,False +292,22.0,21.0,19.0,22.0,30.0,26.0,23.0,31.0,AHGAHGABADGFGGEEAEFDCABCFBCGBCBHCBCFEDFEDHADEFDFBHCBHAHEAHEHHEHEBGEAGEDCEHGACGDCFCEFDEBDEBDFHACEEHBDDGGEBCEBCGHFGEABFAEEBHABGAHGAHDHHDHEABEGBFAEGHEHCADFFDFGAFCDDGFHFFGFFDEBCHFEGFCDFHHCHFBEGHHADH,False +293,16.0,24.0,24.0,18.0,24.0,17.0,14.0,18.0,BDDACEACHABHABHECHGHEGEEFCHFAFAGFBBBGBEECEEHEFDBDDBDDGCGBCEHCEDCBFABFBBCCECCGBEBAABHECEGCEDDECFECFHCFHCGBCFFDDFADFAHHCGBBBCAFEBHGDGADGAHCBEAAFGDBHHEDCEDFEH,False +294,32.0,23.0,12.0,12.0,9.0,21.0,14.0,23.0,BCGBDHDCGGGDAFDFFBCABCABCFGGFAAFBHEBHGBGGDAFAACABHBFFDAFAHHBHHDHGDEADBHGBHBBHBBFACCBECAAAHABHAEAEDFGCCEAFFHEBHFHHEHDABAAGAGHADAAHAACEAHAAFFBFFBFFH,True +295,25.0,28.0,34.0,29.0,21.0,15.0,21.0,21.0,GBBDDFEAEADECDAGBCFBADECDBBDCCGCAGCDBCBBCBDCBGCEHCGACACFBHFDDBCHFCGAGGECFFABDEGDEFDHFHHBBHDAEDBEDCDDCDDCDAADFACEDHHGACGBBGAGAEGFGGHCACCDHGEHGEHGHCEACBHFEAAEACEACHHCHBCBECHHFEBBDCBFCBDDBDABAEFAHG,False +296,10.0,5.0,3.0,10.0,3.0,6.0,4.0,2.0,FCDBCACHBFABDAGEAGDADEBDFDAFGABAADEADHGDFFD,True +297,18.0,24.0,24.0,26.0,29.0,26.0,24.0,26.0,HAEHBEAEEHCACDDCFDHFGCBHCBCDHFDEADBBGCBGABFAFGGHGEAGDBCCGCBDFDDFBEFBEGDEGAADHADHBHADHCDFEFFEGGEBAHBCFGCEGEBGBFGEAAEDHFDAAGHFGEEGEEDHECGEDFEBBDCCDBDECFCBBEFHFCGFEHHEHHAGHCEHCDFCDFCDHCHGGHFEFFBFHBADB,False +298,13.0,9.0,11.0,21.0,12.0,21.0,9.0,8.0,DDADBAGGAGEAGECGEFHFCCFBCABCABHAEFABFDFCHHDDEDDHADHCHABFFFEAEDCFDEGGFDDFCDFEFFEDFEBADFDDFBDFCHBGFCEDDAFG,False +299,9.0,10.0,7.0,5.0,4.0,5.0,9.0,5.0,AEBFBGFGGAGGADCADGDHGHEBHBBGEBGFCHBCHAAFAABCECCFDDBCAB,False +300,9.0,10.0,14.0,12.0,10.0,5.0,22.0,10.0,GBDGFGGEGEHGDGGEGCCGACBDBBDABDAEFABBCEAEHAGCFHDGHGGDGADGHGGBFCDHCDGCGBDAACEHCEGCEGDHCHECHCBF,False +301,23.0,15.0,14.0,8.0,21.0,17.0,19.0,20.0,FGCEGAEGEDHEDBGGECFFHEBBBFDAHHEBAEBHCHEGAAHABEEFEEFGBHGCHCAHDAFGGHGDHGFAGBABFAFHEEGEAAEDAGFAEFACFACBHFDCEHBAHCAHGAHCCGCCGEAGEACFADFHBBHBF,False +302,27.0,23.0,30.0,20.0,17.0,18.0,24.0,20.0,AACCCBGDBFHBAECFFHBHHGHAACGCHDDBFBGGCHGAFGAGGAGGAHGCHGCDGCHBHABFDBDDEEDEEDBCFCCFCHBHFBAFBDFHFBAAAFCCGHCDBADAFCABEACGBFBEEBAEHAEGAHGACBBDACDFCDGCDGHDEEDEBCFFCAACHECGCBGCEGCDAAEEHGD,False +303,30.0,27.0,22.0,22.0,20.0,20.0,25.0,21.0,FCHFDBBDBGCAADEBGFBGABGFEGHAHBADAEDACBECFFCFFGDBGAHHAEHFCAFAACEDCFFBEFAEABHDGAEHDDBGCBGEBGEAEEFBEBDHDAAACCHCCHGDAGDFCFABFHBFHBGBBDHBDHEEHECHDCADAEDGBCCBAGEHGEBGFBGCCACCAGAADAHGHHGFDABGGGD,False +304,29.0,17.0,17.0,22.0,14.0,23.0,28.0,17.0,DABGFCFHAEGAFGFBCCBEDDHFCADEHDEHGHDGADGHGGCCFFFFCCEGHEGBDDDDDFDFGDFGCEABADBCHADBGDCDAHFFBGFGGHAGHAGAEGEGCAAHAAGAAEBAGBGFBHBBHBGDCGFCDFBAEBHCFEAAEAAHGAHGAGFACFDCFEAFDAB,False +305,11.0,12.0,13.0,10.0,10.0,17.0,17.0,13.0,BFDDADEGGFGEFBEAGHAGBACAECAFFBBFHBCHGFHGHGFFGCFCBBAGCDGDDGCGHCBHDGGFHFFHGDECDFCDEAGFAFBAECAECHBHHEHCEBF,False +306,7.0,10.0,4.0,3.0,5.0,2.0,7.0,5.0,BHBHADABBABGABHDGHDBCEFEEFCEBCEHGGCGBAABGAG,True +307,17.0,17.0,13.0,19.0,19.0,19.0,22.0,12.0,FDEAAHFFBFBGFBDFGDFGDBGDBGFBFFHFFABEGGGHAAHEAFEDFCBFCEDCDAGBAFBGHDHCGHGDEGDGCBBDHGABCDHCFHEGGDBCHECEECEADEAEGAGBAEEDDEGCEGCHACBAFBDEDAFGAE,False +308,16.0,19.0,32.0,19.0,25.0,21.0,28.0,24.0,BCGCCBFCFGGDHGDADAACACGGBADDGDDGFBCHHCFECDGGAEBAEGHCDBCHEEHAEHFEFFEGFEHDCCCEGHFHHGBGDEGFHCFBFHBGEGFCGFCBHGBHEBEEBGBAGEEGHEAHEBFEBHCBGGDGDCHCCACCADBAHEDFGCACCHHCHHFBAFAEEDCECCDFCDFCDFEG,False +309,12.0,7.0,7.0,14.0,8.0,9.0,9.0,23.0,HFHHBHGACFAHHHHHDHBGHCEHEHCFHCBHDAHDAHFGDDHEBGFDDHADHBDGEEGDACDAHDAHCGHAADAECBEGEFFAFBDFG,False +310,7.0,9.0,2.0,2.0,5.0,3.0,5.0,9.0,BBABAGEAHBGHFEHBEHBHHAHBEGBGGBDACFCHFDHAAE,True +311,26.0,28.0,24.0,21.0,11.0,21.0,26.0,17.0,BFBEHBHGFHFHDDGADGADGFDCFBCHGFAEAAEAAEAABDDGHDBEDCCGFCFFCBBGGBFHCGGGDBGDBDEBCFBCABGDBGDFGEGCCAAHBGHGGFFBAHBAEGCFBCECHFADGGCECCFCBACBGBBGCCDAEHABFADDADDAFBHFCHAAFAABHHCHBCDBGA,False +312,23.0,13.0,12.0,13.0,21.0,13.0,8.0,13.0,FBAFBAECDHHEEEEAACADHEDAEAEFAEFAEGAEGAEAAEAGGBCDDFHAHHFFHFCCACAEFAHFAECHEAEDDHDGBBCBDFEHEAHBAHBAGCCDDDFGEGEFBBDBBCCB,False +313,3.0,1.0,2.0,0.0,2.0,1.0,1.0,1.0,HACAACEFGEB,True +314,19.0,17.0,14.0,10.0,16.0,21.0,10.0,13.0,AHDAHEEFAEAGCADFEHCEBCGCCGADDADFADFAHAAHFEHFEHFEFFCBFEBAAHEHBEBCCGHEBHCBFCFFGEAHEACBABBABFFGFFGBBBFBGDGCCBEDADAFBFFCHEDG,False +315,3.0,8.0,4.0,7.0,12.0,10.0,4.0,14.0,DHEDBEDBECHEFFFCHDAEBAHHFHFEGFECEEDEGHBGFBAHBHEBEDCFHHFHFDHGBH,True +316,19.0,13.0,26.0,20.0,13.0,13.0,16.0,14.0,AFCBGBFCAFCEECHBBAGCDGCFGHEBHEDCCAHCFEAEDDEDAGCAFCACCADCGDEBFAGDHGDCBACHAGHBFHCGECDCAGCADADFGDCGDGEDFADCADFFDAEDHCCHCBHGBHEBFGBCABHHDE,False +317,16.0,18.0,21.0,25.0,22.0,16.0,21.0,17.0,GDDGDDEDFEGFEDEEDHBDHBCHDHBBBBBBCCBCCHFCHBCHEHADGCDGCBGAFABCEDFFAEBCHBDDEADCGDEFAEGAGCCDCCGFDFBDHCGHGAAFEADAAHEBHEAHFCCDCEAHEAFGBGEBGDGEFGFHGEHFAFDGEDGECEDG,False +318,23.0,22.0,20.0,24.0,12.0,20.0,16.0,25.0,AABCHBFHCDHCGFGHDHHFGAGHBGHBGCEECAEHGBCGDDDHCFHGBHGBHEBHDCCAHCAHAHCAFCDFHHEBDDBGDGEABBAEBCDDFDDFEDFACFABFCHHCHHGBFAEFBCGBDHFDBFDFDAADAFDCEHCBBDFAAAAGECDABDAEFABFG,False +319,9.0,5.0,11.0,3.0,6.0,3.0,10.0,12.0,HABHDEGCCCDFCBHCHHGHAGHCGHCDHCEGCGCEGHEAHFABAECGBBAAFGAEHAG,True +320,31.0,18.0,28.0,29.0,18.0,25.0,23.0,22.0,ADEFDADBAGBEGHEGDCAHAAHCFGCHGFEGFHGCGBFDAFDCFCEBABHDBAFAFFDGDAAHABGGCAFCACCDEBDCCGCCDCCAFGGCHBDHGCHAHBBBBBCCGAADCBDEFDHCAHCHHFHAECDCHDGHDEADEDFADBADEEDGCBGCBGDGEFHAFEAFAAFGEEDCFDHFAHFAFFAEFHEDGD,False +321,11.0,11.0,8.0,16.0,26.0,18.0,18.0,26.0,HFGEAHHHHDBHGEHDFAGGDEFDEFDEFAEFBDFHDEEDEEBGEHEHHEHACGGEBHEGHEFHEHAEGFDGDDGBCEAEGAECDHCGHFEHGAGFCHHEHHFGDFEFFHBFABHDGFFBCEBAECGDABDHBC,False +322,6.0,3.0,4.0,2.0,1.0,1.0,3.0,2.0,CAAFAEHAGBDHCDBCGBAGCA,True +323,10.0,11.0,20.0,18.0,16.0,14.0,16.0,14.0,FCGBEHDGCCHABGBCGACFEFEEFEDCCCBGCFHCDAGDAGDEDFHGBAGEDFECGACGEFGEFEHCDHCDEFHGBHGEFDEFDEADBAEHFCBGCHDCHDCBDCFHBDABGAHDHCD,False +324,14.0,16.0,12.0,17.0,15.0,23.0,16.0,14.0,HDEBDGFAFHDDHDHECHEBHGHEGEGFADHGEFGDFBCEBGAFFAGFHBDHGDCGDCACFECFEHFAFBCEHCFBEFCEADHABCBBCFBAFAGFAEEAGBBECBDGBFGHGBFDDFDDFGAFDAF,False +325,15.0,13.0,7.0,9.0,15.0,10.0,11.0,11.0,BDABDCBEEECAECHCFHBBHDHEAHEAGEDEABEDHEGGFGGFEFBEHEEFBHAAAAAADAADFAEFGHHDFHGAGBBBBCDCGBFGFCG,False +326,18.0,22.0,21.0,20.0,18.0,16.0,22.0,11.0,FAHEBHABFAHGAEGHHBBBCBGCBECAAGDACFBCFEHGDHDDCDDFFCEGHEBHCFCDFCDGCHBAGCEBCBDGBDCBDHGEFADGEFABFGCFCDBCGACGABFACDEDEBDAFAFFABGEBGEGEEDEGDAGAGGEBGCBDCED,False +327,13.0,17.0,20.0,5.0,21.0,19.0,14.0,10.0,CACCAECGEGAFABCCDFAFFHFCEFCHAHBGEECEECGEFDECDECEEABFBEAEEBEDHCAHAADBABFGFFGFGGFBGBHEBHGFGEFBBGCBCCBCBECBCGFEHFHBGHACEFF,False +328,21.0,20.0,17.0,13.0,23.0,15.0,20.0,19.0,HECGCCHADAADGADBEGBEABEHFGFGGFGCBECFHBAAEAHDFHFFBGEBGCBFHAABAABDCBDCAFAAHCGDCGEEGHGDEGCHGHBFHDHCDBCFEAGCAHCEHEEFEFBDHHDEBEEDEBGGAHGAHBEFBECEFABGABEC,False +329,24.0,23.0,29.0,30.0,30.0,21.0,23.0,19.0,HADHFBHFEHCEHDHCDFCBABEEBDEHDACBGDBCDBGDBADCCDABAGCEGBDGBEGCDFAFFGEFGAGEAGEADCGHGBDEDAADEHBAHCAEGBGFBFHBGEBDBBAEEDEEFAEDGCABCEDGFFGECCDACHBDGBDFCHECHECEACEADDDEDFADFAFHCFGCADCEECFCCFCCAEBGGHHCHFDHFEG,False +330,7.0,6.0,9.0,9.0,7.0,8.0,16.0,10.0,HGGAAGEEFBEDHFDAFBAEDFGHFAHGDHEECGHCGCCACGFGHFAHEBHCGGCBGDHGDCGDCGBGDBDF,False +331,15.0,22.0,24.0,18.0,22.0,22.0,16.0,24.0,ABAFBECDEDAHCCGCAAHHCHHGBBGBAGBDGEDEHAECACBBFHHEHHEHHFHDCHDCBGFHFFHAEBFEFGDHAECEECBEFEGCCFBCGBCDEGHBGHFAHFGDBGEAGFADCBCCHCFFDEFEEFBEFHEHDCDDBHDBGFAFFBCCBCFBDADCGDE,False +332,9.0,18.0,16.0,12.0,7.0,14.0,10.0,14.0,AADCABGADACDAEDCHGCBFHBFHBEHGEFGHGECFBCDDGDAECHBCEBCFBCHHFDHDHHFFDFBGFGHBGECCFDFHDBHGBCFFABBACBCBBCB,False +333,24.0,10.0,12.0,14.0,8.0,11.0,24.0,18.0,AHAAHAADADGFHEEGBECBDCEACAHEGHEFHADAADFHGBHGBGBCGAGADGADGAHCAHFHFGEGGBACDCCDGFGBHCFGAFGBGEHACHAGGCDDHDAADGHDGFCGAHBAHBGFF,False +334,17.0,19.0,16.0,21.0,12.0,28.0,7.0,21.0,BCEAFGACAHCFEBBDBBDFFDBCDBFDFFDHFABDGBDFFGFDHFCGFGHCBHAFCEFHHBHHAHFADFBFCBFCBDCHEHDCADFDDEHDECDFCAFAAHABFBDFHFCDGHDHHCHECBEAEHAEFABDEFAFBGHEA,False +335,5.0,1.0,17.0,8.0,5.0,13.0,6.0,9.0,HFEEFACCHDCHDCHFBHDDCACCFCCGCFFDEFAFGCFHAEGFEGFDCCAFCHCGDCGDCHFH,True +336,7.0,5.0,7.0,10.0,4.0,6.0,4.0,9.0,CABCEBDDFADCAFCFGCEGEHDDBFGBFHCHHGHHDFDEHDAACAADHBDH,False +337,17.0,14.0,20.0,15.0,14.0,12.0,26.0,25.0,FEFFADAGDAGFCHHBHHBAFEECECAFCDFDDGGCHGCHFCGDGGBBGDAHDHECHGCBBBHDEHCCHFGHFCHBCHDAHCAGCAGEBHEBAAACEECEGGDHCEBFEHGHCGHCGDABAGHGGBBGFGGDGHHEHDDAAGA,False +338,17.0,17.0,8.0,23.0,13.0,10.0,15.0,13.0,DFFDBGEBEBCDBFDBAEEAFGAHDDDBBDEBGEBGBAGBGBCGEDEAHHADHDDHEDHGGHADDBDHHDCHDAGAECADCHDFBBFABDAFCAGDFFCAEGAEGEFGBDGCHAHA,False +339,18.0,24.0,23.0,25.0,16.0,22.0,30.0,24.0,DGBDGDDCDGCBGFEHEAAFCACGBFEBGCGCABCAFAGEAGEAHDCHBFEGHEBDDBDDBGABGFDGFBHCAEEAGDHEHFEFEHFGHFBFFGCAGCACCDHDDHBDFGDFGEEGBFDHHBCHDFFDCCABGBDGECBEGGGHDCHACHBHHGGHBGABDABHFCHFHHDBABGFCGFCDC,False +340,2.0,2.0,13.0,7.0,3.0,3.0,2.0,4.0,ECCCDCCACCBDCDFCDGAHHFEDFBDCDCCHGCHE,True +341,4.0,3.0,4.0,1.0,4.0,2.0,6.0,4.0,GAEGBCHBCFGAHGAHBACEECEGHGDF,False +342,10.0,14.0,13.0,18.0,10.0,15.0,4.0,7.0,BFBBADBAGACCABFAECCFCCEDEHDABBAFGGBDBCEBFDBFDEHDGHFAEECCDCCFHBFDEDDFDDCDDEHDEFFBDFBDFACHAFH,False +343,2.0,3.0,3.0,5.0,8.0,5.0,2.0,1.0,EAFDCDDCHEBFEFDEFEABECBFGEDGE,True +344,16.0,17.0,10.0,12.0,19.0,14.0,18.0,24.0,DGDFEBGECFCBBGFFEFHEHBEHGCBACBEGFGGHCBHGBHAEFBFFBHHBEHAGAADFAGFAHFAHGACGAEHABFGEGHEHHEHCABDAHEABCDHGEHGAHDDHDDBEFBGDBADGCHECHDHEEE,False +345,12.0,6.0,8.0,11.0,11.0,7.0,6.0,8.0,EEABBCDDGADCAECADHABGABECBECFEFFECDEGHAFHDGHFHAFAABDAHCEHAEHFDCDEGDGD,False +346,14.0,12.0,14.0,18.0,13.0,23.0,16.0,8.0,ECHBFBAFEFGCCDDGFDBFEGFEAFECFEHFEGBDDCHDHAAGAAGFBDBGDADDHGDCFFHEEHCEBGDGCFECFEBFDACDFGDAGDGGCGBABDCBCBAFFAFFAFEAFDHFCG,False +347,13.0,9.0,9.0,6.0,6.0,16.0,14.0,5.0,GEACFCDFGAFGAFCFFDDGGDBGDEGBAAHGAHFFBFFEEFBFFBFCEGBGGCECCAAHAGHAFAAHACGGFBCBBD,False +348,2.0,2.0,2.0,3.0,4.0,6.0,4.0,5.0,EFGDDADHEFBAFECFECFHBFGGHHGH,True +349,25.0,25.0,26.0,14.0,12.0,22.0,23.0,17.0,GCCGCCGEEDFADFDCCEHCBHCBGBBCBFGBAGFGHBGABFAGFBFFACCHHFHABAABCABGHEGBCGBFFAFGACCDDCBFGFAAAAAEACEFCEFCADCAGHAFABFDGADHHGBBCHGEBGCBHCBFDHGHHCEHBBBBEFAFHDDGFDCAGCAGDEDE,False +350,26.0,15.0,7.0,12.0,18.0,16.0,17.0,8.0,GFECAAAAAHFADABEGCECDGDAGEABEGBGBBGBBGCHEFFDFFAAAGEAFBAGDHHFGGAGEADFAEEBEFCGFDDFGDFDBFBEHHAHEAGEABEABEBBADAADAFFCEGCHAE,False +351,19.0,24.0,27.0,20.0,25.0,23.0,28.0,19.0,HHCHFCDGDBGDFGCBGDFGBFEDFBGABHABCABGBGAHGBHGBABCCEEBDFGDHGDBGHFGCFGCBHFBHECGCCBCGBFGACGDCHEEDFBGABFAFFGHDAEAAHDAFDEFDEDEECFEGHECAGCECCFCBABFADCAEGEDDFHFECFEGABGAHDHECBACDGHEEEEHECBECGFC,False +352,11.0,14.0,21.0,19.0,18.0,15.0,12.0,19.0,CGFBDFCAEDFEHEHCEACEAEEFGDAGBACBFCBFABDDGHDEHFGADGHDHCBHCEHCDHBBEFGFBADCGBHEADECDCBDCBACBACBDCHFHHCHFDGCDECGHCEEGHEHFFFFGEHDCHDED,False +353,14.0,12.0,11.0,22.0,22.0,10.0,7.0,14.0,BDEBEHDFDDCDEADEHCFHCAACAABBCDBHHEDHEFBAFDACABGEEDEADFADFBGFAGCGHCFEAEDGDDFDEEBEEBEHHEHHEDEEBHHCADCACHDDGGBFEDDE,False +354,25.0,23.0,25.0,17.0,15.0,24.0,9.0,25.0,FHABBAFCCFBCFBEDDHCHGBAEHCEBDAADFADFHFHHFHBFBCHBHHEHDACDFFAGBGDEGHHGDDCCCAHCEECAEDECFBBHDFCEFBAHAAHAFHAFHBFAAFAGGACEAEDAFDHEGFCFFCDFHGFHACHABBABECCCCACCBBCDBEBBHDB,False +355,17.0,20.0,28.0,20.0,27.0,26.0,18.0,20.0,FCDHEAHEGECAEDAEFCHFEFCCCCBECHEHEDHDHHEGHEDFEHAEDGEDGEFEECECHGCDGCBEDDEDDFDDBGGCGBHHAACABGGBCGBCGDCFHCFBCFBHFAHFEFFCFFBDACFCHBHEEFBGFBHFDGGCECAAFACFBBBABBDBEHCAFFEGCADEADFFBCGA,False +356,11.0,9.0,19.0,9.0,17.0,23.0,24.0,22.0,DCFDCHHGFEAECFFCFFGEFGFFGAHGBHAADAACEFFGGEHCAHCBDFFDGGHHBFHBHHAHFFGGFEGFCGFCHCGGGGEEEFCDHCDECHECEBCFGCHBCHAEHCEGFDGCHBEHBGHBGHFAEAEGGD,False +357,15.0,19.0,23.0,15.0,30.0,8.0,15.0,12.0,EDGEGBEGAEFADGHEFEEDEDDEGGFDAEEAGDAEEADEAEBBCFBCGECBEGGACEFBGDHECHEAHEHGGABCEDDFDDEDBHDBCBACACCGCABEGHCHCCBCCAFCHBEHEHHCCBCEBCEBCEBFBBECA,False +358,8.0,10.0,3.0,16.0,6.0,11.0,10.0,8.0,EADHDFFDBFEGFGCCAFCBHDGEDHDDFBBFEBHHDAHDHEDHGDAGDAEDGDGFBGABGFDGFABBADBF,False +359,20.0,14.0,12.0,8.0,11.0,4.0,10.0,13.0,BAHGAEDBEDCADCAHBABAAFAACGBHGBHABHEHCCHBCGAEACGDCADCHGAECADFAEBDEHFCHEAADHAGHFBEBCEAGEBGBGHB,False +360,26.0,15.0,17.0,18.0,13.0,10.0,21.0,9.0,HCBGGBGGBCCDDCDCCHCHHEGGEAFEDFAGEBDHBGAFGDGAABCADCEGCFGAEABEADHABGAEGFEAFAFCACGADDBEAGAABAHGDCDEADECDBCDBCBHCFDDFAGAEGAHGAGAAFBDB,False +361,15.0,32.0,16.0,34.0,25.0,18.0,29.0,23.0,HDFHFFDABBBBEEBGEBGEDEEGAHGBGBBHDAEGCDACHECHBGDBGDBGDGDDFBGGDEBFAHHHHEHHAHDADDEDBEBBHABHAFGDDBEDHEDHDDHGCHCEFDGGDGGBCFCCFEHFGGFHAEDFDFFCAEGABDFEDGBAGBGDBCFBCHEDADDCDCBBBDEBDEBGHCGBEABFCGGEFCEG,False +362,22.0,28.0,20.0,25.0,21.0,16.0,11.0,16.0,BHCHFBFFBDDBHHBAHBADBAHBAHGCCFCBBDBBECAEFEDHHBCCFDCBBBEBHEBFGBHGDHCFFCFAHHAGAGDBFDGFDBCGEADBFBBAAFEDGEDFDAAGBAGAABEDDACBECBEFDAHCCCCGCEEHAEADEDDEDCEACEAEDDEDDE,False +363,11.0,11.0,7.0,6.0,9.0,8.0,12.0,8.0,FBADHHEHFGGCGAFEAFEGFGGHGHCCHCCBCABAEBAHDDCGFABEABFABABDEBDBHAGGFBGEEGDE,False +364,5.0,2.0,8.0,2.0,1.0,2.0,9.0,6.0,AHGACBAGHCGHGBEFDAFGACHCCGCDGCHGHGC,True +365,33.0,17.0,16.0,24.0,25.0,19.0,21.0,11.0,GDDGDDGBDBAABAFECGEDGEDFAGCACCFHCGHCDAADBACFCHEDAEHABGGHCEEEBAEFEDFDCFDHFDAFAGFBCDAFGEDDEHBEDBDCBHCAGFHFDACAGDABEABGABGAHCAGDAFFGEFDEFGFGEEEAEAAEAAEAEFBBAHBABCEGEDGAA,False +366,24.0,28.0,22.0,9.0,23.0,15.0,15.0,17.0,HEGHECCBBCBBFAEDHBFCBFBBFABGEGCFDCHCCBAAHAADABBBBAECHECEEHEEBAECDDAGDFGDFCDCGBCEBCABEABAAEHGCHEFHEDHFGGAGEHGCBBAFBAHCFEEGAEGABAABAHFHBCCCEHAEBBEGCGFFBHFA,False +367,22.0,19.0,28.0,25.0,31.0,21.0,23.0,26.0,HGHDGHDGEBCDDCAEEADEDEEHAHBDCEEBEFGAHAADGDHBHFCEGEDBFDEFEEBEBCEFCEFCBACBADHADEGDAHCCEDDEDHFAHECDDCBEFBEGBDCHCHAABAACCHCCHCDHAGCAGEBEEAFECHBCHGCGGHFCFAGGEDAFDCBECBEHDEFFGFDGFHGFGGFGFFBFHBCCGAGHAHH,False +368,19.0,23.0,22.0,14.0,18.0,18.0,13.0,20.0,GAHHDGFBGDBFFBHGADABEHCCFDCBDAGDBFBBFBBFBFFEFFAHCAFGAHADHEBFBAFBECCEBCDDAEDGEHBBBBACBAEBDECHEGFCHACFDBGCHHCHGEHCCHCGHCGECEAGACHFCHFCHDEEEEEBDACAAHA,False +369,8.0,9.0,10.0,4.0,11.0,7.0,17.0,8.0,GEHGEBGFGGFCGEHAFBBFCBHCFDCGEHAEGCCGAEGBBCHBHFEAFGBCGADGADEADCGCHGEBAEGHEG,False +370,14.0,14.0,22.0,16.0,19.0,13.0,17.0,12.0,AEAAGFACECCFHBFDEGEAGADCEHCECCADHDEGFGGCCGBHGBHGBAFDGECGECGHBDHBABFACDDEBFECFEFFCAFGEGEEGHGCBACBCBDABCGBDFEDEDDHDFBDHCCHCCHEADE,False +371,24.0,19.0,21.0,13.0,20.0,18.0,17.0,23.0,GEGEADCDGEHBDCBDHAHCEFCEFEEFCDFBEGAGFHGFCCHCCFFCFFAADAFCABBBHGCHDHEAAGCAGDABHHCHHCHGBEFAAFHAFHGHHGDADEABEGBCGCDBADEHHEHACDABGECFEFEEABEBBHBBABCAGCFGEFABHAH,False +372,3.0,3.0,3.0,4.0,0.0,2.0,1.0,2.0,DDFDDBCABHABACFGCH,True +373,11.0,27.0,14.0,16.0,27.0,12.0,14.0,25.0,BGEGGBDBADECHGHHEHADHDGAEAHEFHBFHEEDGEDECBHFEHEBHDDCEABEAHEAHEBEEBEGAHCHHCBBBBBBBCCGDFGEBBEFHFDHFDHFDEFDEDEHGEAEEFBBHBBADBCBCCBGFDGHEFABBGHCCCGCHH,False +374,3.0,9.0,10.0,10.0,8.0,7.0,11.0,11.0,GCGGBBHHCCGFDGFDHDDHFDBFEGEEBECDDAECCBBCHGCHGFHADHACBEFHEBHDBHDGGFGEC,False +375,23.0,33.0,18.0,22.0,30.0,18.0,26.0,23.0,EBDEBDHHGCCGCFGADGBCGHCEHFEHDEHBEGDDGBHGAHDAHDBCBAABCFBCHEFDADCAEBBBBHBAFBAEBAHBHFBCAGCFHDADEAFECEECEFBBGGCCGEHHBBHEDCAFAHEEFFEAGABGCDGBBGBDFBDFGDBEDBHFBGDDGAEBAGAFGEEBEECEABEHGGADGDGFHGFEAEHHE,False +376,26.0,12.0,16.0,23.0,9.0,18.0,21.0,30.0,ADDFFDFFDFFHCFCBFAGFBGHEDHEAHECHCABFAEAAGAAGDDDDCFGCAHABDEGFHBCBCADGHDGADGHEGHDGHFBHGDHCDEABHGEHBDADAACHHHHFHAGHEGHDGHDHHCCCAHDHHGGFAAAAFABFHCFGBHGAACBGCDD,False +377,14.0,10.0,11.0,6.0,8.0,8.0,6.0,11.0,FCEFBBABDCHECFBCGBHGFHECGCFAFAEFDBACADCABCHHEAHGAEBAHAAHAAGFDCBDCBDGAEHHEH,False +378,10.0,13.0,11.0,8.0,10.0,9.0,5.0,12.0,ADCHBEECEEADBACBGBBAHBGHCCHGBHCCACCFHCDBDDFFDFFBFEAEHABHDBDAFHECBAHEGHEGHEFBAF,False +379,26.0,14.0,13.0,28.0,14.0,24.0,18.0,23.0,ACEAFGAGABGAGGEHAFHDCDDFFCGHCDHAAAEFFEGABGAHHADFGDFBCAGCAGBACDDDBDDEADCCHGEAGEABHHFHCCBDABHFEEDGHBGBBHFDFCDFBDADDEDDEDHFDHFDHEDHAAFAHDGDBGEFFABAECAHHFFHFFHDFHFG,False +380,21.0,15.0,24.0,10.0,21.0,16.0,24.0,20.0,GBFFDHFBFGEFHHHHHECHEDEEBCAFAABGACGBCAECBCCBEDFCDGCEEEAEGAGGACDAFDCGBBGBBCAFFDFHBAGGDGGCCHEAFEAFCAFCAHCGGAHCACCAEGHEHEEGEEGDCHDHHGCEGAFHHEHACBCFGHBGBAG,False +381,15.0,21.0,27.0,23.0,28.0,27.0,27.0,20.0,BCBHCAFBBGEBDEDHCDGCGGCGDCFECDECEBCEBFEBFGCGGBGABFAEHCFDCHEGEFFFBGFECCEHCGFFGFHGBECCFCFAEDAGAHDAGEFFFAFDACCHCHBBHFCDAGDHGDEGDBDEHDHHFHFBHDBFDEAGCADBDDBDDEEFEEAGEGGBCGEFEEFDGHHCHFEHCAGGABCE,False +382,0.0,4.0,3.0,2.0,1.0,1.0,2.0,3.0,BCDBHDBHFEHGGCBC,True +383,1.0,2.0,2.0,6.0,6.0,2.0,4.0,2.0,CHDAEDGEDCEGEBGEFDEDGHDFB,True +384,12.0,14.0,12.0,10.0,21.0,16.0,19.0,20.0,GDHEBFGHDHCEABECBDCAHGAEGCEBCEHDEAEBHEBHFHHBBFFAFDCGHAGDCBFHGHCADBAHBGHBGADHFCHFDHCHECEECEGFEGEAGEGGEBFEGAEBAFFFEGFGGDGHFEHF,False +385,9.0,9.0,5.0,9.0,10.0,4.0,7.0,7.0,BCCBABGHBGDEGDACDBEFBHDGADGAEHHCFCEFDEBDBBDAAEEAEHADAGEHGFHE,False +386,15.0,9.0,11.0,11.0,15.0,15.0,12.0,13.0,EGCFFCFGCFHFDHCHCCHACHECAGHFFABEAHEFHEDDEBDHBDHBECDEADGFGFBGFAGFAFAHEEEBDCDGEHGAGGABAAGDFDBEABEHECFAA,False +387,17.0,16.0,9.0,11.0,9.0,4.0,15.0,11.0,DADCFEBAEAGCBBHBEGBDABFBDFDHCAFEGGEAGEACHABHAGHDGHBHHBGDEGHCAAGDAHACEGBBGABAACGACGBDGBDHBDCE,False +388,10.0,3.0,8.0,5.0,5.0,8.0,6.0,3.0,BDDGGCAECAFGAFCACADCEGCAHCADCBFFAFFHHFADEGFEGBEA,False +389,17.0,13.0,28.0,32.0,15.0,31.0,24.0,29.0,HGHCCHGBFDBGAAAAEDAFHHDEGFECFHGFCFFEHFDHGDCCFCHFCFDCFDGEHBEHGHHAACAEDAHDACGEGFEBHDHCFHEFHGFAGFACDACBHCDHCDCCDEFDEFDHFECDHDDCGDGBBCCFDHBDFBDFCGBBHAEHCDGGFHGHAGFBDBDCGFCGFDGDDFDHGHAFFAGDCEDCF,False +390,23.0,24.0,19.0,26.0,25.0,15.0,25.0,27.0,FADECFEGAEGHCFDCBGCBDDHDDHDDAGAHHAEBAGDAHBHGBFGBGGFGDCADCBHBEHDEAEHGEHDBHGBHEBDGBHECAEDADDAEHFFHFHGGCCHHEFECCGDEACEHHAHGAFAADBBDCBGABDACCADABFABEHFEBEEBDDACDEEDGGGGBHGBHCFGCFHFBHCBEGEE,False +391,4.0,5.0,5.0,5.0,10.0,9.0,7.0,10.0,FGGFGCEGEEHHDHGDCEDAHBFHFGDFEBHBHHAHFCCFACFGBFEEHEEDEAB,False +392,2.0,1.0,3.0,2.0,5.0,3.0,4.0,3.0,FBGCCGDCAHEFHFDHAGEEGEE,False +393,32.0,34.0,23.0,23.0,23.0,22.0,17.0,26.0,AABCCBCADCAHAAEFAFBABBHCCFBFGDHDHCAHFGBBCCBHCBHBFCDFBHBEABEAGEDGECBEBHEBAEFHEBEBDHAHHBGCCFDDFDFBDHBGAAACEACDACHADFAGFAGFHGFDFADFAHEAEEBEAGDDHCDEFDBHCGGDGDAHABHEBHEBEEBEHFABAHBGEBHCFDGFGFEDADCACHACBGBB,False +394,10.0,5.0,5.0,10.0,12.0,9.0,5.0,11.0,DCDEADHACFADFADABDHGHHDAHGAGEEBEFFCFAEDAGBAEBCEHDBHFFCEFHEHHEGEEDHF,False +395,9.0,8.0,7.0,6.0,6.0,3.0,2.0,9.0,BAGBECDECDCHEAHAFGBFHBAHDHHAACAACHHFHBDDBEEAEDBCCB,False +396,28.0,25.0,16.0,17.0,19.0,17.0,23.0,14.0,FBGFAAAHBHHGFCGDGGBGGEGGEFCEHCDGBBHEACEGBEADCADGEGHDGAAAAABFABFADFCCBHCADEFGEDDBDACAABAAHHHFACFBDAADBAGBGEHDEDBBFBBFBBCEAGEBHEBHEBEFBCFECFEGDGBAGDACDHCFCFGAGAE,False +397,11.0,7.0,11.0,10.0,5.0,9.0,10.0,7.0,BCHBAHFDBFCHFCDDBHGAGCHGCGGCGGFGEAEECDDFADEBFCHDCHBGABGEFDCFDFAAADAACA,False +398,21.0,30.0,21.0,28.0,27.0,13.0,18.0,24.0,CBDCAGAAEHGBHBHHFHHAHHCGHDBDABFBEHDEBCEDFDCFDCFBCEDCBAEBEDBEBBABEDGFBGFEEAEBGHBGCBACBDCEECBDCDDCAAGDGEAGEAFEGEEBEHFDHDGCEBFEBDGDFHAFHFDHECHGCDGHEGDBDBHEBHGBDAAAAEADDDCABHDCHCEHCHGBBA,False +399,8.0,12.0,5.0,5.0,7.0,5.0,5.0,13.0,HHGHBAEGABBCBBCBBCFBCBHADAAFBAEBEBFHDECEEFHGAHGHHDFHDGHAHHED,False +400,7.0,6.0,11.0,5.0,6.0,14.0,10.0,3.0,AEFAEBCFDCFCFAEFCGGCGECHFGADCBDFGCHCCABCAGGEFHEFGAFBFBGFDGFDBF,True +401,5.0,2.0,3.0,1.0,8.0,3.0,7.0,1.0,BAGCFGEEAEBHEGFAGFDGEEGECAEGAC,True +402,7.0,14.0,22.0,10.0,18.0,10.0,12.0,15.0,GHECCAABBCBBEEBEGBDCEECFGGHCHACHAHFBGGCCCCHCEFCFDCHDCHDFHECHACDBCBAEBDEBDGGEGHDCEGHECEECEEHBEHDFBFBAFHDFGFCG,False +403,14.0,14.0,19.0,22.0,20.0,22.0,14.0,19.0,ECCEDFDGEDEEBCBHDAFBAFAAECCFDCEBBEBDAHCADCFDHEBFEDFEFEGFEAFHAFHGCHEEHDDFEDFDCFDCFCBAHFAHFHHFBDFDDEHCGGBGHBAHCAGCEGAHBHCGCEDEFDFGDHGFCGBBGCHGHDDA,False +404,9.0,11.0,17.0,12.0,11.0,7.0,12.0,10.0,BCBDCEGCECEGCDCCDGGAHGEBGBHCFCAFHAFHADEAHFDHEBCCDCCDCBDHEDHADBAHCHDDGBEGFGGBECFEFEGBAGCAB,False +405,5.0,5.0,3.0,4.0,12.0,4.0,3.0,6.0,DBGAEGEEDAEHAEBBEBEEHFDCBEFGEFCAFCEHHAHEDH,False +406,15.0,17.0,23.0,27.0,15.0,22.0,16.0,20.0,EFCEGEFDBFHCCACBDDHDCFBHFHGFCECAEABGBGDHCDBCABGADFDDFECCACFAEFHDGHDBHDAHDHHDHBFEFDEADFADBDCHDEHFCHFGGFHGHHEAACAFCFBDDCEBCGBDGDEGDBGDHFCCFDEHCBBCBGDFGAFEAGC,False +407,11.0,16.0,12.0,20.0,16.0,15.0,13.0,15.0,HBGBDGBDGFGEFCCHCDHCDHFFCDBCFBEEECEFCEABEHDEDBEFHFDAFDBHBBHDACAHFAFBAEBDDDADDAFDGGGEEGHEGDFHBFHGDBGCBGBACDAHHCEAEEDHGF,False +408,16.0,12.0,20.0,13.0,15.0,13.0,22.0,14.0,HACHAGEAGFHHDDCEDCBFEDFEACBBFHBFHBCGBCACCBDDGDDBEFEGGHDBDDGGFHGAHFEGAEACDACGABAAHEABECECCECGGCAHFAHFGGFEECEHAFDGGGGCFHCGGCGBC,False +409,4.0,7.0,9.0,5.0,9.0,7.0,4.0,6.0,EFCBHCFAFFACFDHHBHCBGBBGBCEHGECBAGDCEFCDFCDEEHEEAED,False +410,12.0,11.0,9.0,6.0,6.0,6.0,2.0,5.0,DDCDHBBABBACFACEBDEHDHBFBAFBAGCAEAEEFHCBCCFHCAAEAABDABGFC,False +411,10.0,13.0,4.0,12.0,8.0,3.0,7.0,11.0,BBHBBDDDDDEEAAHAAHBAHGEHGHHAEDEEDACDBBDGCDBBABHHCGCFGFEGBAGBFDDAEHBH,True +412,2.0,7.0,4.0,0.0,2.0,6.0,5.0,2.0,BGBFGBFGBCGCEACFBHFEABHCBGFF,True +413,28.0,23.0,16.0,19.0,25.0,12.0,17.0,19.0,BHADEAEEHEEAGEFBBCDDAGHHGHAEBDFBAFBAHAEHBECBDCGDGBFGEEAEEDBDDBHDEHGECAACGACABCABFABCADEAHEDBCGFEBFEADEBEGADAAFAFHADBACHABHCCDCDBFABGAEGCGFHACDEGHHGHGDHFBHEBEGC,False +414,4.0,13.0,10.0,10.0,10.0,2.0,11.0,8.0,EEGCECCGBBGBCGDEEAGEDBHCHHADHDBHEHCFBDBGDBDDBDEADEHBCAGCBGEGCBGCBGFH,False +415,13.0,21.0,20.0,13.0,22.0,19.0,15.0,24.0,HFDBGDBHHBCCFHHFBHFBHFBHACEFEHFCBGBBFBHFDGECGFCAABGCFGCHHBHHEGFEABCBECEECGDCHHFEDAHBAEEDECDHDGHFGHFAECAFBAGBDECDCHBHHDCEFCAFEHEEGEAGEAFEDEBACBDCBGG,False +416,21.0,17.0,11.0,9.0,12.0,14.0,19.0,7.0,CGHHGBDBAGBAGBDGACGAHFFBFAGCACDAGAAEAEFCCAEFBCFGCAACGEFFBDAEDABDCEGEFCEBBHFBHEBHEAGGBGFAHFEBFBBDABFAGGAGGDGADE,False +417,6.0,8.0,8.0,1.0,1.0,6.0,7.0,5.0,BADAECHCCHCCHAAFCGFBGBBHBBGFCFHCGGBGGBFFAA,True +418,11.0,22.0,19.0,15.0,20.0,16.0,14.0,28.0,CCEHHDBHECHCGAGDCCABHFHHEHDEGBEGBDDBDEBHBBGFFCFFHBDHBCHBEHBAHFFGFCDHHDCHBEABHDBHCBAAEFDCBCCDFHEFGBDABGFBCADEFDGFAGEHGBHCBCGFAAHEEHEFHEGEEHEEHCGHC,False +419,25.0,19.0,13.0,15.0,18.0,30.0,15.0,15.0,FHCDCFBEHCABEAFAFHEFDGFDCDEHAFGAFBDBBFBBGBAHFAGFBFFBDBDDEGFBDEBHCBFCEFCEFAECAEFECGADBABAEHFDGFGGBGFBGDAAAHAAHDFHGCHFCAFEAEEDECDHBFAGHAGFEEFAFFAFAHCAHG,False +420,5.0,4.0,3.0,9.0,10.0,5.0,4.0,4.0,DEBDADFEFCEHEABEAEEFEDHGDHEDCFGCFDDGBDGBEAAH,False +421,21.0,22.0,19.0,21.0,16.0,23.0,24.0,24.0,BGGDDGBHHHHGHHDAGFAGFBBFGGFGEHBAHECFACAGHEFCEADEAEBAHBGBBACDACDHCDHCHBCDBDDGCFHHFHHAHEEHCGCBGAADFBGEGFCCFCGFDHHDHCBFDAADABBCBFCFGDECBEFDEGDEDFABFADFGBFGFAGFADHHEGABCFBGEE,False +422,5.0,3.0,3.0,1.0,0.0,2.0,1.0,4.0,ABCABCBGAHHHFHAFCAD,True +423,8.0,5.0,10.0,3.0,2.0,6.0,4.0,7.0,CAHCAGAAEDGFCGDCFHCAHCAHBBDFAFFGBFBBCCCHCEHAH,True +424,4.0,2.0,3.0,3.0,3.0,5.0,4.0,1.0,GDFGCGACDACDEBFEGHEFFAAFB,False +425,20.0,29.0,28.0,22.0,37.0,21.0,18.0,23.0,DCDEFDAGCHCHFDAFEFFEHDEDBEABEHBEBFCBEDBCDCCEGCEBCEAHDHHDAHGAHBBBFABFABACBADHEEHEEAEAAEACDCHBCEDEEBEGGEBEFDGCBBBAFDAFCAFCHEDBEDGECHBHGFGECEDGDFECFDCFGHECEEHFEBCABCADEAFEGBBHBFGBEHCCHBCGBEFCHHCHGGGGDF,False +426,3.0,6.0,6.0,5.0,11.0,8.0,8.0,8.0,ECEBAECEDDEBDGBGHDGEBGECGFHGFHACHFGHFCFBEFHHBHEADEFGCFE,False +427,9.0,21.0,17.0,17.0,18.0,17.0,9.0,12.0,BHBBHBBAFBCCHEBDECFECDEFFGHCEFCAFAEHDGHDBHABEEBEEDAECBDCECABDAFDHDGEDBBDBFAFFCCBHCDHDBFDGFGBFCHACDBCGGDGGCBFFBFEEFHECEED,False +428,13.0,9.0,6.0,7.0,7.0,9.0,7.0,6.0,HDAAECHEGFFGFGCFHCBGAADAADAAFABFBEEAFFBBCBBEABECGHDGEDGDABDAFHCH,False +429,8.0,15.0,19.0,18.0,20.0,20.0,16.0,22.0,FGDFDDFHDGAFGFHEBABCDBHFGHFCHACACCECEACEBCFGDBHFEHFBHGHHEHEBGEAFFHCFDEFDADDBDGHFBDFBCFBGAHFBECHECBECHECECCEDCHGEEGEGFDFEDBEHBHCDGDHCHHGGDG,False +430,13.0,25.0,20.0,21.0,26.0,17.0,24.0,16.0,EFFGFCDFCEHCGHDGEECAEBBEGBECFEGHAADDAFCAFCBCEECFFCFCAGDACHBHHBGDCGDGGDEEDBHHGCHEDBEGEECEEBEBBDBAEEFDGBGGBDAEDHEFCGBCGFCGAHGFHDBGGBFBFFHEHBCDBADCEDEBBGAAGHBGHBDBDD,False +431,13.0,21.0,18.0,12.0,10.0,10.0,17.0,15.0,GAFBBBBFHGFAFBGCGGBBCABCAGDHGDHBCHBHBAHGGHEGHDCDBCFBCGECAEDDHBAEBDHBDHBDACECGEGGDHADBEFCDBGACEAHBCFBEHAEHAFGCCGCCFFC,False +432,14.0,11.0,9.0,15.0,14.0,12.0,12.0,18.0,DFAFFAHDHEDFEHHEDHCFHCECBABBDGEFGEDCDCGDHHFCHFCGGCEGABGDBEABAAHAEBDEBHEGHFGHDHEBADGADBAEHCEHDDHBFAGAAFFGH,False +433,16.0,16.0,12.0,20.0,13.0,18.0,9.0,14.0,FDCFDADDBDDAHDCBDCDDCDAEHAFAABADBECFAFBCFADAGCAGCDBAFCFFEHFHBFBEHGCGGDFGDABDEECGGDFEFBHCBHBEHBEABEHBAHGAEFBEHHHFEHFDFD,False +434,15.0,21.0,15.0,6.0,12.0,5.0,12.0,17.0,CBBDBGABGCDGCEADBCCADEFCCAHCHCDHCAHCHHABHBBHABEFCGCBGAFAAHEAFGAEGAHGEEGHEGBFBEECHEBBAHHCHDBHBBHBBABBGEG,False +435,0.0,0.0,3.0,2.0,2.0,2.0,2.0,3.0,CHDCEDEHCGHFGF,True +436,22.0,21.0,21.0,13.0,7.0,14.0,20.0,13.0,BHBGDAADEDFGCFGDHGAGGAFDCCACCHEADBCFBCGBFABEHDCHCEGBGDAGAADCAHGHHGHFFDEHAGAGGABCAFAFFACHACGBDGBDCBDHAGCFEBFACHBCABCGFCAFGBEBBCBBCBB,False +437,18.0,12.0,15.0,15.0,9.0,15.0,19.0,9.0,BEAEFBCFAADCBFGDGGHFCADAADGADHCBHDGDBGDBGDCGAHEFHGFAEBAHBADGCDGCGFCHFDEFEHFCAAAFBAHAEGDEGFEDCCBCGBFGBFGACGCCADFG,False +438,9.0,15.0,11.0,10.0,6.0,5.0,12.0,8.0,CBBCECABBAHBHBCHGGEGGDAEBEDCDFADBGDBGDBGBBCDGABHCFGBFGHFGHFEAAEAABHDDCGCCDCH,False +439,21.0,34.0,13.0,20.0,9.0,14.0,18.0,22.0,DBGDFCCFEAGHBHHCHHCBHBGHBDABCCBAFBAGBDCBDBBGBAFFDHEHGCBACBAEFGHBGAFGCFBAGHAHHAGHGCDEAHABHBDFEDBDDADDHFBHFBEABEABADBHFHDBABBHBAEBGCDCFHGGGBBGFDGDABDABDE,False +440,5.0,7.0,4.0,9.0,2.0,7.0,1.0,7.0,DEBHHHHHHDFAAFGADHABBFFDFFDBEDCCCCFBDDBDAB,True +441,9.0,3.0,11.0,9.0,5.0,3.0,13.0,6.0,GCHGCHBCDDAEAHEAGAGGCGEAEHACDFBDBDGCDGDGGHGCFGCAHCACDGCAEFD,True +442,26.0,15.0,9.0,16.0,20.0,21.0,20.0,20.0,EEHEFAFDDHDDBDEEFFEDFCHFAAGHAEHADBAGHAGBADAAEABCGBCBBFGCFGEFGEFGHDEAEEAFHFGHDGFAGACGCHBCHEAHGABGBGADGFFGEEBCFDHAEBAGBADAABBHFHHCEEFFEDFHAHHAHADDGFG,False +443,5.0,11.0,13.0,10.0,14.0,14.0,10.0,14.0,FCEHCEHCEDGDBBDGEDHEABEFGAFGAFCCFHFFHFBAEEGDFFAHECHGCHDCHBGFEHFHFFBBCBBEHCHHBECDEDBEDCGGGDC,False +444,9.0,3.0,12.0,6.0,9.0,11.0,10.0,6.0,GACGCGACGBHABFCEFCEFCAFGFEGDCFBCHHHHGAAAEADCDGAGEEEEECFFCDFGDFCDFH,False +445,9.0,10.0,13.0,13.0,17.0,11.0,15.0,15.0,DGCDBCDFEFHEHHEDDEGCCFCFFCGDEECEFHHFAHFAEDGGBBGHHGCHGBACAAHEEHEEDGGDGGDGEEFEBGHBCDCAACAHDHBFEFCEDBHBBAG,False +446,4.0,1.0,6.0,9.0,11.0,4.0,5.0,7.0,GACEFGGACGDFDECDEHDEHDEHEEDAHDCDFCDBEHAGFCHEEHE,True +447,26.0,19.0,18.0,11.0,16.0,16.0,12.0,21.0,EEHFFHCBABHABHAEHAEHEFFGFAGHBHAEEAEEAGAAGCCGABDACECFHGHHEDHCBHCBHCBAGDABDCHAHEFHFHHDDFBFFAFCACABEDFEDAGDBFCBDAGFACEACAGHABBFBBEBACCCGHCDBAG,False +448,6.0,5.0,7.0,6.0,1.0,1.0,3.0,5.0,HADHAHCACGDGBDGBAECACBABDCHDBHDCCF,True +449,11.0,2.0,6.0,6.0,9.0,16.0,8.0,5.0,AGAAHAAGFDFEEFBEDGEGEEFEAFCCDEDFFGFFGFFCFAEFAFHDFCBHADHFGHACCAG,True +450,11.0,4.0,8.0,12.0,7.0,9.0,7.0,8.0,FDEFCADCGCEBAHBGECHEFHCDACDABHGBFFDFAEFAEADGADFEDHCAHGDHDFCDAGDAGH,False +451,31.0,20.0,20.0,33.0,22.0,23.0,32.0,17.0,BCCAGAAGFAGCEGDBGDACDHDHGFBGBBDBFGBHBAHECEECDEDHHDFADFEDCEGHAFBCCBFADGCBADDFEFGEHGEFGDHECAEAGEDDEBDEADAADBCBGEDHDDFCEAAHBGBGFAGFDGFDEFEGHBAHFAGFDGDDFDFABCABCAFCAFCAGCAHEGHGDAADAGEFGHDGCDGBGHCFAGDEGA,False +452,6.0,6.0,6.0,10.0,8.0,9.0,9.0,6.0,AFEABEBDGBAFEDHGFHGEDGEHCHAGHECHCCFDADDFEDFEBAGCFGFFGCBGDBDD,False +453,13.0,18.0,14.0,23.0,17.0,19.0,19.0,12.0,DCGDCDDCADEBFFBFFCAACDACDCCABCDDFDFAAEGFHFADCBGCDGEDAFGGEHHEFBFFBFFBGFCDFCGAGDDHDDHFEHGEBGHDGHAEHBGBDEFCBDDEABHAGEBEEBHEDEGBHGBFGBGEEGB,False +454,18.0,22.0,18.0,14.0,25.0,31.0,12.0,21.0,FHADBACFDHAHHDGHBFFFCFGCBGDHFFFGFFGFGGFAHCHEEHFHDFHFFHFAHAHEACEGEEBDEDFAFFBFFBFBEFDCBBEAEHDFDEEEBBGCBFCFCBGBBFEHGCDEHDECDECBADEAEEACEACECCABBECBECBFAFAGHEHHABHAB,False +455,8.0,7.0,7.0,9.0,13.0,7.0,12.0,7.0,AGEBFEADAAGFABFHDEAFFCGFDEHGABGCBHCBGBDHBDFDEGCEGCEDCEHEDHGDAGEHEEGCEG,False +456,26.0,25.0,17.0,12.0,23.0,17.0,8.0,10.0,BCAFCEBDBGCAAFAAFGCBEAEDDBADBADCHEFFEADEAEEFEEGAEGEHBEGAFHAFHDFBBAEACCAECBBBBBFABEABDBBDABDCEDFECACHFHAFHGHDCCAGFEEACEABFABFBEFAEBBGHBCHCC,False +457,17.0,13.0,15.0,8.0,13.0,12.0,8.0,11.0,HFCEBGABGABDAECBBCBBEBEEBFEAADACFHFEHFBACAACDAFHHFAHGAHAAEAHGHCGFCDFDAEEBDECCHCCFFGBEGCDFCBCAEDHG,False +458,4.0,0.0,3.0,1.0,6.0,6.0,4.0,0.0,FEEFEFFGCFAEAGCAGEADEFGC,True +459,21.0,25.0,18.0,16.0,17.0,17.0,23.0,17.0,HDAGCGGBBGBCEDCBBBEGFEGFEGFAFFCGFCBECBFFBEBBGBFABCAFAHEHEDHGDCCEAAGAAGBCGHCBHCAEDHHDFFDABEFECCABHABEDBEGBEGDGDFGAFEAGCDGCBHHDHCAHGABFDEADBADBHGAGAHFHGCHDB,False +460,10.0,14.0,5.0,9.0,15.0,9.0,9.0,8.0,EDEEGEAGEGBEDBDFGDEABFAFDAGEBBABDAGDBGFFHAEHDEABGBHABEACEFBDFBCHGCEBCEBEHHHFHCF,False +461,5.0,3.0,5.0,6.0,2.0,12.0,7.0,4.0,CEAFFGFFGFFDFHDFBDADACCGGCABAHGFBFFDGHDGHEFC,True +462,6.0,6.0,14.0,9.0,5.0,9.0,18.0,19.0,FGCDHCHHGHDGADGECGHCGCGHCEDGEFFHHFHFGBAHEFGBCGHFDHFHHCGHCGHEGBCCBDAHDHGBHACGCGFCDABDAG,True +463,3.0,5.0,4.0,8.0,5.0,3.0,5.0,5.0,DGAFBBFAHGEGGEGBECECCAHHDDDEDDHFDHBDCB,False +464,8.0,5.0,4.0,6.0,7.0,4.0,8.0,3.0,DACBACHAGHBEHDEFEADGGCFEDGEBGEAGBAGFDGFDAAEBC,False +465,13.0,13.0,10.0,12.0,11.0,18.0,10.0,10.0,DFBGFDFFDGBBBEDGEDBECEEDFHAAACAAHHHHHBGGAAAFHACDACEFFHFFHAGCBEFBEBAFGAHGDEGFFBFDBFDECCECCGBCDBFDF,False +466,1.0,7.0,5.0,6.0,4.0,4.0,5.0,8.0,DHBECBCDBGDBHDBHFHECAECFFGHDGBBGHCGHDHFE,False +467,8.0,10.0,7.0,7.0,13.0,10.0,14.0,7.0,GGBEGHAGEGBEDBCAFFBHEEAEFBEGCFGCFHBFEGFEBFHFCHFDGDDGHDGDCHAEGCEGAEDCEBAABABG,False +468,7.0,9.0,14.0,4.0,4.0,10.0,8.0,4.0,FECAECBDFBGFCCFECFDCBGCBGBFDAHGAFGBBEBCHBCAAHGAGCCCFHCFGCDAF,True +469,11.0,8.0,10.0,17.0,9.0,15.0,9.0,16.0,FHDFDDEACFHCFCAHDEHAGHACHDGBAGBEGBAGEHHDGHFEHADHAEFAGGCFECFBCDGDHHDADBCDBEDFFDFFCCBEDHFHAFHDFDB,False +470,1.0,3.0,1.0,1.0,2.0,1.0,2.0,3.0,CHADBEEBGHBGHF,True +471,17.0,15.0,26.0,18.0,19.0,21.0,23.0,27.0,GFFCCCHCDHAGAEGFGCBGCBFCFFHDFBDCHDGHFEAFEAEEAEGDHGHCGABGDCGDGGFFFACHBEAEEDEAHFAHDHHGCHFHHGGHBBECGECEEDAHCACCBBCFBCHGCHACFDCEDAHCAHFFFDABEEBCBAHFCHBHBGDGECGEHDHGDHGDFD,False +472,2.0,5.0,3.0,5.0,4.0,6.0,6.0,2.0,EGHFGBFEBFEDFHGCCFEABDADDBDGBGCFG,False +473,20.0,30.0,26.0,33.0,27.0,26.0,18.0,15.0,CGAHFAGFAFDBCDEGDEHBEGBEBFDGFECFHBFHBEEFEECCEFEFFHCDGAHABDFBAGBADBADBDGFGCDCABGAEGDDDDACFACEAFEBEGDCGCEFDEBEEDFEFFDABDHBDEBCHBHHFDDBCDFGDAGHBDABFBDDDFFBBACBCCBCABCACCHGCBFBDDEEBCGDCGDCEDCHFEHEAHE,False +474,19.0,17.0,14.0,18.0,11.0,17.0,20.0,12.0,GAGCCFFCGFEDEBFFAFCGDHGEHGEHGHGFDFAAFDADDADCACCBFBDGBGGBFEBCABDAGHGBDBBHFGEAGCDGFDCFCHFAGCBBABBABAEBCFCDEDHGHAEHAEDAEDGFDGDAHHAB,False +475,29.0,21.0,29.0,16.0,8.0,11.0,32.0,19.0,GGHBGAGFAHFBGAHFBHGBHGCEACHGBAAAFHHFHHCBGCGAHBDCCDGAAGHHDBDCBDFBDBEACAFCEDCBGABGAFEACGACGCCGBCGHAGADEAHGDCGCBBAFBADCGBEGBEGBAGCGGAGABCCHCDACGHDGEAHAADFCCHACDGCDGCDFC,True +476,1.0,0.0,5.0,0.0,0.0,3.0,1.0,0.0,CCCGCCFFAF,True +477,12.0,12.0,12.0,10.0,3.0,21.0,15.0,7.0,FDFAGACBDCBGCEFEFDGAGGBBDBBAFCADCADCFCGFCFFHFFHBFCCDAGAAGBFDCFCAFHDBBGHDGHFGBFBEFGFFAHGAGGFH,False +478,17.0,16.0,18.0,22.0,16.0,25.0,17.0,21.0,ACEFGEHAECACCHBGAFFBCFECADCEFAEDEFAECBCGBCHFGHGEBAEAADHGDGAFGDDCEHCHAEHDEFGHHHBHABFABFHCFHCFHCFBDFBHBEFFEDFCDBGDAFDGBHFBHAEDCFHBDDGADGDFCDFGDGBDGDFHDFHG,False +479,10.0,7.0,13.0,9.0,7.0,6.0,9.0,3.0,HGCDGCAGAEGAGCCBCCFCEFEAFEACGGCHDABDECHFABFEBEBADBDDBAACGCFDCDDG,False +480,1.0,0.0,4.0,0.0,2.0,0.0,5.0,0.0,GCEGEGGCCGCA,True +481,21.0,16.0,14.0,17.0,11.0,10.0,25.0,16.0,FDGEEGBBDHAHGDHBHGBGCBCCFACEAEGAHHDHBGFDGADAAEAAFHCFHDFABGCBGAGGADCHDCECEDBDACDAHDAGDBHHBAGFAEFGBFGBGHAGAAEDCBCEBHEGHDDBGGGGCAGCFG,False +482,12.0,17.0,21.0,17.0,21.0,22.0,20.0,24.0,HCBHEEHCEHCBHADGBCGBEEHHFGHFDHFCHCGHGGHBGCBCHGDDACDFFFFFGBACFECGCFHFAEDHDDBDDHDEGDECAGCAGHAEHAHFEFDEACCDGGGFGCEBCEDHFCHBHBEHDDABHFFFAFFBFEBEBBGAEGCEGCEBFE,False +483,19.0,21.0,17.0,13.0,22.0,21.0,20.0,24.0,GDGGEGFHAHAEHADHCEHDAACCBEFBEAAFFAFGHHBHDBFDFFACBGDDGDHHBACBFDHFDBFEFFGABDACDFFHGFCCAEBBHGBHBBEBGCDGCHGCHEFHEAHEHHGACCACGAHHEBGECGACFEEEBEFBCFEEGEHGEAGBFHBEB,False +484,14.0,17.0,19.0,19.0,23.0,9.0,30.0,14.0,DBADEECEEGGGCGGCHGAEDCGDCDDHDGGDEBHBBCAHHADGGGEGCECCACHAGHAEDABCHGGHAGDADBEFHHFBCEAGAGGDGGHGGACFFBFGCFGBBDBECBEDBGFEHDEBDEFHEBCEBAEGEECEGBGFCDECD,False +485,23.0,20.0,17.0,18.0,15.0,7.0,16.0,20.0,ADAADBBFAFFAFAAGCDHCHABGABCAGHBGHCAHEECBECGDHHAHDEFBGDGDBGDBAAEABGHBDCECCBGGHCEHBFABFABCACAECBCDDCBEEADEADHHDHDDGEHGEHGEDCBDCHAAGGBHHBHE,False +486,19.0,15.0,16.0,14.0,11.0,13.0,25.0,19.0,GDCGHFGHCBDBAAAAAACAGHBGADDCCHEGBCBDAFDBGDBDEAAGAHBAHADCDDEHHFHEAGCGGCGGBGHCGCBGCBDCGGGFEGBEDFHCFEBFEAFGAEGCFGCFGDEGAHFEHABFFBHHHHHH,False +487,17.0,28.0,19.0,19.0,12.0,13.0,19.0,22.0,DBDEFAHAGFBGHEGHDDBBEBHEBHDCHFEHGEHGBBACBAGAAGEBBHBDFBDFBDCCHCCAEBGDGDCEBCACFAEGAHDFCCBHCEHDEGCBGABGBDFHCFDDFDBFGAGGFHBCHCABDABHAHCAGCHGBBBCBHFDHADHG,False +488,11.0,5.0,10.0,9.0,17.0,10.0,8.0,12.0,HFEBAGAEFADDEHDEHAEHDEHAEDEEDGBCHCFECFBCHGCHGEDBEABGAHFAHFHEEGFHACECCADEDCEFCAFGFG,False +489,15.0,27.0,19.0,19.0,24.0,16.0,18.0,23.0,GDHCDCEEBEBBHABHFBGFEGDDHDFACCAGGADEBDEHABHAFHGBHAFCAFCBFCFHCHDEHDBBFABDEGCECHDDDDGEAGHAFHFEBBEAHCAHFGHABEFEHDHHDCGBEHBEBCCBGDGEBGEBEECEGBECBEBDEBFGHABHFFDGCCGBC,False +490,3.0,2.0,6.0,3.0,7.0,0.0,1.0,4.0,CBCEHEADEACEADEDBCGHHECHEC,True +491,14.0,16.0,16.0,14.0,17.0,13.0,22.0,10.0,FADFCGFCEFCEBCGBCBBCBBAFBGGBGBEEEFDBBDHEEHGHAGHAGDDGBEAAGDFCHADHGDHGHFBDEDDEFECCEGGGGGADGCBEEHDCGCCGABHDBFAFEEECCAGAFGAFCA,False +492,26.0,18.0,20.0,24.0,26.0,19.0,29.0,28.0,DCADFADCEHGDGGFGEAHEHHAHFCCCGHBAHEAECBBGGBHGBHDBAAFECHEBHGFHCAHDAHDAHACHCGHCAAEGGGDBGDGGDEGHHDCGEEGEDAEDCGFCDFEFFADHGBCABHDBEGBGBHCHFGDFEFFEBBEDBEAAEFEBFGBAHAAHECDGDDFDACCAFAEHGEDGEDCEHFGHFA,False +493,1.0,0.0,2.0,1.0,4.0,2.0,0.0,0.0,ECEECEAFFD,True +494,11.0,16.0,14.0,24.0,25.0,15.0,20.0,16.0,HFCEDHDDCEGCFADBEDCEDAFBACGFFGHDDDGBDFEAFCAFHDFHEFBAFBDEBEHCEDBHDGHDFAEFCECCBGGBFDBCDHAHBGEBEEHGGHABDGDGGDHADGAEEBFECEECGEGGEBEEBHGCHGDHGDEDE,False +495,15.0,21.0,13.0,15.0,18.0,25.0,20.0,12.0,GFGGDGBFFFDCCDGCDECAEFFFHCECCEDEEAEEBEFHDHBGGBGGEGHAGEAGBGEAFAHFACFCHGBBGBBCCDEGDFFFFABBBEBDAGDAHFACFAFDABDBBEFDEFAFBBFBBFEHHGHDDHBFGAFHEGC,False +496,14.0,17.0,8.0,12.0,24.0,10.0,23.0,11.0,GBFGBDGAFGBGEBFEHDGAFEBCGGGBABDAEDGEFBAFHEFHBFHEEBGEBAEGGEFGEABAHBGHBCFGEGCAGCEHEGHDDEBAGCAGBECDECDEGDEGDBDHEEHAEHDCAAE,False +497,8.0,11.0,13.0,8.0,7.0,15.0,9.0,16.0,EHBHFAFCAGEGGCCGCAGBAGHDFFCFHBHHDDHFCAECHDBHCBHAFFDFEHCGDFGAFCAFCGFEBBCBBCFHDHEDHFBHEBH,False +498,3.0,6.0,8.0,3.0,3.0,7.0,4.0,5.0,CHECBEABACCGCBGFHFFBGDBFDAFDEFCGBCHFHHC,False +499,7.0,4.0,9.0,5.0,5.0,8.0,3.0,3.0,ECEEFHFFACFAHAABEABDCCGFDGFCCFCCFGDABDCDEBAH,False +500,7.0,8.0,5.0,8.0,4.0,3.0,2.0,4.0,CAEFHGBDDBDDBDDBCGBCFDFDHCAEAEHBEABAAHACB,True +501,22.0,26.0,22.0,26.0,16.0,25.0,21.0,27.0,EBHCGHBFHBFBAEEAHFAHEADFGDFBFHCHCCHGAAAAAHAGBBBDBCHCEHBHHGDDFBEFDECDBFFHFFDDDDDFDAACHBDABDHGCEGCGHFGAFDCFGCFGBBGFACDAGHFGHEEAEEAHHBDDAABBCBCDDCDCGHFGHEBHABGFCGCEGCBCHBCHDGFFBFGEFDEHDBAD,False +502,10.0,11.0,12.0,13.0,8.0,15.0,13.0,13.0,GFHHEHDCHDEFDADGCDGBDFADFHFACFACACBFCGFCAFEECBECBACAFDEHBGGAAFDGHCBDCBHGBHDFHDHGEFGFHGFHDBEBGGB,False +503,5.0,6.0,10.0,4.0,4.0,8.0,9.0,0.0,FEDCEDCGBGGBCFCFEDBEGAACABCGCCGFFGFFDAGGBCABCF,True +504,7.0,14.0,10.0,11.0,12.0,9.0,6.0,15.0,BDBBGBFCEDCHDCHEFFECHGDEEHEDHDBCDHGABFABFBBDBBCEECHEGFAHCGFBHFAHFAHDCEAHBDCBDHGEHAEH,False +505,21.0,9.0,16.0,11.0,15.0,16.0,15.0,15.0,DFAGEAGEAFCCECCECFEGFHGDHAFBCHEDHEHBEAGFCHDHGAHFFCAAGAAGAAGAFEDGCDFHGEHFEDFBDCAHGAHBABEABGABEDFFHGFCEACHADEBCCBGFDCCHA,False +506,17.0,15.0,12.0,11.0,15.0,5.0,18.0,14.0,BHGDHFBGBBABHAEGAEDAEAEDBEDGCGHADCFEHAGHAHHAFADCBBGEGGBDBBDEHHHGGBGADGACHCEGCEHAABFAEHAECAECEECFBCGDCGBCGDG,False +507,23.0,16.0,18.0,17.0,15.0,30.0,19.0,16.0,CAHCHFAHFDGFDGEHAABDAFCAFBAGBHGHCDBAAFGFFGADAHDGDGGFEDFEDCCCCDHGFFGFFCHFAFEAFEFHGBEFEEFEECDBGGHHGHCEHEGCADCEBAFBFDBGBCHBFFBFFBCDBDGAGFABEAEAAFFCBFCADCADHA,False +508,2.0,2.0,6.0,5.0,8.0,2.0,3.0,4.0,AECAHCEDEEGEDCFFCBECDDGGDHECHEBH,True +509,10.0,15.0,13.0,10.0,20.0,25.0,8.0,14.0,BFFFFGHDGHBEECGECGEHFEFAGBHGBEDEGAEAHHFFHCFCFFHEFADFBCEHCEGFAHFHEFECBDCBDABDCBFCBDHBEFCEFCHFEBEBFEAFACFHFBAFEADDDBE,False +510,9.0,6.0,15.0,8.0,8.0,15.0,8.0,4.0,CGFCHFDFCDFADGADECCCFCAFBFFCCFEGFDGFCGCCEBBEAEEAEFGHDGDFCHFEFAGDABBCBCAHA,False +511,1.0,1.0,2.0,5.0,3.0,1.0,4.0,3.0,GDDGCBGCHDEEDHEDFAGH,True +512,16.0,13.0,8.0,20.0,20.0,20.0,19.0,18.0,GEEGAEDHBDFBGBGGHGEEDHEHEGFEGBEGFHGEDBBAHGFDAFDAEDGFFHFFHEEHDEHDGDGADCADFADABFHDFCEFCHFDGAGABHAFHGHCBFCHEHBEAAEAAEBCEDFGABDCHFCBFDFDDG,False +513,2.0,0.0,0.0,0.0,3.0,1.0,1.0,4.0,HHEHHEAGAFE,True +514,16.0,32.0,27.0,32.0,20.0,18.0,31.0,18.0,FFCEHGEAGHCGDDGHDFEDFDDBDCHDAABHAGDEGDEGEFCBDAEABBAGBCGHEEDCCBCCAECAGBDFBCHGHHDHADGGGCCFFAGBGFDGACBHCBDAEDBEDAGDHCDGCEGFGCEGDADDCHBGHBAHBEGBEFBFGBHDHGEBBDBBFCCCDEBDFBDBBGFBGFBGFBGFHDBCCCEBCGDCED,False +515,26.0,15.0,26.0,29.0,17.0,18.0,23.0,22.0,GFHDAEAAEGAEGCEDCDDCAHCABBAEBECGEBHHGAADFECFBCFECEDGDDCDCGDBDFGCGHDAHFADDAHCADDGDFGDEAAGAFDHGCHDCBDCGCBGCBFABGAHHBHDFHDFDDGDCFFAHBEHECCFCBACHACEGCEHHBHFGHCGDAGDAGECBFHAAGFFDEAH,False +516,12.0,12.0,20.0,17.0,22.0,17.0,13.0,11.0,EEBEADDAFDADAHHEEBGEBFFBEBCCDFCEFCEFCEFCABEFHEFCEFGFCGCGHCHDCGFBECACAGDAHDGGDHFDHADEADBFHBFABDHECFDCHCEGGDCDDCGBEAFEBECGECGE,False +517,17.0,18.0,11.0,13.0,13.0,9.0,14.0,20.0,BEFHACHEDBAAHAHHAGBAGCGGHAADEHDEHBBHGEHAEHGEDGEBCEBCHAAHBCHADHCDBGFBGHAABBFFFCCFACBGDBGDBFDCFDCBEHFHHEGBADEDHEGGABD,False +518,20.0,13.0,17.0,15.0,17.0,19.0,27.0,13.0,CFECBCGACDECDHCHAGGAGGAGGAGEAGHBGFFGHHDEHDHDDGAAGDDGDHBEFDAGBABEECEAABAAFAGFGDFCDCEFGECBCGGEGHEGHBGEFHFFDCCAFGAFEAEEFCFACFGBDCBCAHGBEGFDFHBFB,False +519,4.0,10.0,8.0,8.0,7.0,6.0,3.0,5.0,EABADFAHCBFGDFCDCCBACBEFDGBHGBHFEHFECEDHBCCBEDBEDBD,False +520,21.0,21.0,12.0,9.0,4.0,4.0,12.0,8.0,FAACBBBAABGAFADBABBDBBABHACGACBABBHHCECAACAHGDHGABCBDABAGBDGDAEDGCDGCABFEHEAHFBHGADGCCGBCGB,True +521,7.0,6.0,5.0,6.0,9.0,6.0,4.0,9.0,HDFFDAFDAFBFEAGABCHCHHBFHBGEBHEHHEHEDAECEEGACDECDBGA,False +522,7.0,13.0,6.0,12.0,9.0,15.0,17.0,9.0,FEHCDBCDGGDGGDHFBHAEFDEFDFGEAABAFBHCBEFBACDGBDGHHBFGDFEDEEGGBGGBHGFGFEGHCFBFFBGFGHBADCAD,False +523,13.0,18.0,26.0,23.0,24.0,18.0,20.0,22.0,HDCHAFHBBHAEFFCCGDFGAFCFDBHGFGEFBEGCEHDHHEGCEGEDBDDBGAFHCFHCAECHBFHADHFDHECFBCBBEEDGBCGEEEDGHFGECCECDACDGFBCACCDDGDDEBDGBDGAACABCABCFBEFEDHEDHDGHEFHECDECGAHGEHGCCBH,False +524,23.0,26.0,27.0,25.0,18.0,14.0,25.0,20.0,AHEABADDECBHGBEGDCHHCEDCECAFCACEFEEGGDGGDGEDGCFBAEAHFGDFCACHEBDDBADBADBDDACFAFAGCBBHBGGFDBFDGAAGAHGDHFBEEDCCDCBACHHCHECFDDHABAACAAGHHGBGGBGFBGFHDCBDCBHBHHCDFCDEBGHBGACGCCGECBBBEE,False +525,9.0,5.0,7.0,9.0,10.0,14.0,16.0,12.0,GDEGFEHFGFFECEBCBHHAHAGHAGDFCDHBDAFFFGFGGHBDHFDCFDCDGFEGEGCEGAGAAHAGEGHEHFEHFGCDBA,False +526,21.0,20.0,28.0,24.0,24.0,22.0,22.0,28.0,FBFFHFFDFEBCDDDFBEABCGECGECFHFFCFDAACAAHAHCDHGHHFHCBHBDHGDGDHAHCDHGABAABGCGAAFBGFCDFCDFCABEHDEAGHABHEBAEFHCAEABHGHHACFEGEEFEEGDFGDCCDCEDHHGBHGEHGECGDHDDAFCEBDHBGGECBDCBGCAGCEBCECEBCEHCDHEDF,False +527,20.0,11.0,8.0,13.0,17.0,8.0,13.0,14.0,DDHGDHCDHDDHEGFEDECAEHFFHAABEGBEHBCAGADGACFACECDEAHGABBCEAAEAGFABAABAHGFHEEGGDCEBAFGFHGAEDHEDHEABEABDHBG,False +528,9.0,13.0,8.0,10.0,8.0,6.0,9.0,7.0,ECDBCHEGHFFBEDBGDBHDBHDFHFEBBCDFDACACCBEHBAGBAGFDGADGACHABDAEABGGEGCEB,False +529,2.0,5.0,6.0,3.0,4.0,6.0,5.0,4.0,FCBFCBFCDCHDEHBFGFFGAEAHEGBCGCHDEBG,False +530,5.0,3.0,3.0,2.0,4.0,2.0,5.0,5.0,AFBAEGACGFGHCEHEBGEHGHDAHDACB,False +531,14.0,18.0,15.0,23.0,16.0,17.0,15.0,32.0,HBAHEDHGDHCDHDEHDEHDEHDHFAGADFEEHBBDFHDAEDEEHHHBHDFHDFHCFCFECABGGBEGCEBFBBDBDCCHCAACFACFHEEHCHHDHGFHGFHDCDDBEBGHAFFCGBAEBAHBGHAGFBGAHCFFBDGDCBDHGHGDHA,False +532,8.0,6.0,17.0,12.0,9.0,14.0,14.0,11.0,DEGAFHFDCCDGCHHBHCFDCFDCEGGFHHCAGEGBFGBDGDAGHCGCCGDCHDGEDBEFFCFDCGHCEHEGHACCAFAFFDFFAEBAEBC,False +533,15.0,11.0,12.0,12.0,16.0,22.0,21.0,18.0,GAAFFACGGFHDCBDFBAFBAGEAFEBFGGFDDEGFEACHFFBDFGEGDFFAHFHHAHHEHHFHFABECBDHHDCHDGGDGGEFGEHACGACGECEECEEBDBHDHHFHEFGGCABCAFEFCGGGBA,False +534,6.0,6.0,12.0,13.0,5.0,12.0,12.0,8.0,HDGAGHFGHFCHABHFEHFACCCBCEGCGDCDEADCFDHGDGFDGFBGCDCHFFEGFAFDDFDDGADCBECBGB,False +535,22.0,16.0,25.0,15.0,17.0,33.0,16.0,16.0,FBFFEECEEDFEFEEBGGDGFEAAEFCGFDGHDGDEGAAAHACFECDACDCHFCHFAFFAFEGFBDFECHHBACBCCACDAGFGDFEDFCCFHCBCCFACAAGADGHEFFCBFHDFCDHBHGECAFFGBGBFGAAAFBHFHHFEBFCDFCBACBHCBHAB,False +536,20.0,17.0,26.0,15.0,22.0,17.0,17.0,16.0,BHHBAFEEFAEFAEDBBDFEEBCEHHAAHAGBDGBHBECECCBFFAFEACEGCEFEECDDDGBDABEEBEHAAHCFCCEACDAHAGHBGFACFHCGHCFCCBCFGHDHCDHCDGCEAHGAFBADGGFCBFCGDCGCCFADECDGGEGAEB,False +537,13.0,10.0,5.0,5.0,10.0,8.0,9.0,7.0,EADEDEAAGAEEBGGHHBFFBFEBFBBDEAHEABCAHCAEFAGDAEDBFFGFAGAHGCHGHABCGBC,False +538,10.0,10.0,16.0,12.0,12.0,14.0,12.0,13.0,DFCGBCDFCDGBDCFCFFCFDAHDCBECEEBEDBEHECFECGAHGDHEAHAHHGFHGDHFFCGGCEGFGGCGCAAHHAEHCBDFBDEBAFADFAEBCBH,False +539,2.0,2.0,4.0,2.0,0.0,2.0,1.0,0.0,ACCFCAFCBDDBG,True +540,3.0,8.0,6.0,4.0,2.0,10.0,5.0,6.0,FGBFBFDBFDBFHFFGCEAFHCCBFCBECFABGDGHDGHBHHAC,True +541,4.0,4.0,3.0,5.0,9.0,9.0,6.0,7.0,HHFDFBDFAFFAEFEHGEHGEBGEAHFDEBCGHGGFEAFDDHCEBCE,False +542,1.0,6.0,4.0,1.0,3.0,1.0,2.0,0.0,EGEEDACCFCCBBBBBGB,True +543,11.0,8.0,11.0,8.0,8.0,12.0,13.0,10.0,CGFCHFHAFHGCGCCHCGHGACBDDBCDFADFADFBBEDAEGACFAHHGBHGDAEFGEAGEABHBGFBAEEGEHDFCGFCF,False +544,1.0,2.0,1.0,1.0,0.0,0.0,2.0,3.0,GDAHBCHBGH,True +545,20.0,18.0,24.0,26.0,24.0,22.0,18.0,33.0,CBHDDADAHFAEFCEHCEHEBHCBGCHAAHAFHFFEAFDAFBEEGHAGDDDACDHCEECEGDEGDEGBADBEDBAACEECHFBFCHFHHEEDBHHAEFCCHHFDBFDHCHHAHHAHGCHCCGFCGBGGFGDFBHFDGGDCEDADDADCFBCHBCBFHEHBEGAFHCCBEFFHDHGAEGDBGDEHD,False +546,29.0,23.0,21.0,19.0,21.0,27.0,25.0,20.0,BHEADFCDFGBFAFFACEAGFABFACFACFHEBHBFHDFGEGCEHCGDCDFCACAGDEBDEFAEFGEGGHCEHEAFEGECAAGAAEFFFFDFGGGCDGBGEBGHBGEBADFGCAGEADDBDDBACCCBDBBHAAABAHBACGECDDHGHHGBFEACHBFHEDCFDAHEAGCBGBAHFAHFBHFBH,False +547,8.0,14.0,13.0,15.0,21.0,12.0,10.0,20.0,CHCHGGHDDADDEGDBGFHCBECDEFBGHEECEGCFAEHHEHHCHHCHFFAAEDAHDEGBEHAAGBEHDEDBCFFEFCEFCHHEHBEHBEHEDDEGDGABCEBDBBCBFFBDF,False +548,5.0,4.0,1.0,2.0,4.0,2.0,2.0,2.0,ACBADGEEGEEBAFBFHDAHBA,True +549,14.0,13.0,9.0,11.0,17.0,24.0,19.0,14.0,EHAEHGEDBEDCEGGEHFBFBBGBGGFHAFHBFEACBACEADGFEACGFEGFADHGDAGCBGHGCFEBAHBGHAHADDAFDHGGHGFFGFFCFFEAFEGEEFFHFDBBDCBEHFFDFAEFC,False +550,8.0,20.0,16.0,21.0,30.0,20.0,19.0,15.0,FHEAEECEEGBBBBBHBBDDCDDCDBCBFFEGFBCEHEEHEEBEEHFDCEECGBBGAGAHCAFCAFGDEGCEFEHCDBEDHGCGFFGEEGEECBEFEHFHCDHBDFDDGGDHEFHGDECDEHEGACFAFFGFBGBGAFGDDDDDBEFBH,False +551,8.0,3.0,13.0,5.0,6.0,13.0,5.0,7.0,BDFEDFGCFCHFCGCAFFAFFHFGCAGHAEHCBCCEHCHDCADCFFAEFCCDHGEFAEBA,True +552,10.0,10.0,17.0,16.0,16.0,11.0,4.0,13.0,CABEDBDDCCDFHBACBAEEDFGACHECHECEDHDDBDDHAHCBHEFHEFHEDDGACAECHEFBEFDEDDHCBHCHFGBFEBDCFACEGCAACFCEF,False +553,29.0,25.0,19.0,15.0,29.0,33.0,22.0,26.0,EABECBEDDEFBHACGBHHEHFFAFFEDBAGFCHDGEDEHDGDDCADHAFFABHCFEEBAECAECHHHACCAEABEABCCECFECEGCHGCFFBFFBEFDGGAGAECHEHHDHHABDEHAEFFEAFAFFAGFHGEAGFFGFAACAEFFEGBAABFGBEGDFHDFHEFBBHDHHGHBCABABBFBBGBGGEAGBFGCFH,False +554,19.0,13.0,14.0,11.0,11.0,13.0,12.0,8.0,ABGABGBBFEBEDGCDFCEAGEAGHAGFAGHACHCDHADCADFGDCDDAFEGFEDHHAGCGCFDEHBEFCFFCFEABGABFCHEBABBACADEAFBABACC,False +555,4.0,7.0,2.0,2.0,5.0,4.0,2.0,1.0,ABBABDFBHFBEFEGBAGEAEEFDCCB,True +556,33.0,24.0,13.0,22.0,28.0,22.0,18.0,30.0,EEFABBCDBADEGEHHHCAHGEHABDDBDAGAABDGBABBAGBEBHEFDEDCHDAEDBFHEAHFAHFABFCBEHBEHAEHCHHFEHBEHFEFFHAFHAGHEGDDHBCEDGAFGECHHDHFAEFAECAGAGCEGADDAEBABAAHHAHGAHFEEECAACGFCDFDDFAFEBBGHBGBAFBEHDFGDCGDFA,False +557,21.0,20.0,17.0,15.0,9.0,13.0,11.0,17.0,FFFCCBHDBHDBDDBDDHDCGFBAHBHCCDAADHAHHADGADCCHBCFECEACECCFDABDCEHEHHEBHDFFABAABAGBEGAHGACGCGGFBBHBAFBABAGHAFHFGCGDEFBBCABAAE,False +558,17.0,17.0,12.0,11.0,13.0,15.0,10.0,21.0,AACABFAEFAEGCEBAFBFHBDHEAHEBEEHDHHBHCBFGAFGFCACBFBDFADFCDBHHBHDACECHHDABGBBGFGHDACEBCEBCAFHDEBDCAAHHFHHFGHEGAEGHFGHD,False +559,14.0,31.0,29.0,20.0,24.0,28.0,19.0,25.0,CBHCBFCBGABHAFHAGDBEEHABFAEDGEDECFFCBFDFFDEAEHDDCECEHCBACBDFBCEECGGCGFCFHEABDABDGBDAHFHHGADGEFHDGHEFHEBBEBGCBFBBDCEGFFAHGBHAFFGFFHEFHCCHBBHFEHGBDDHCBCFBCFBCADCDBCGCCBBCBECGDCHDFHBGHFGFCEEHEE,False +560,11.0,11.0,9.0,9.0,7.0,8.0,12.0,11.0,FDCFDGECEACDHCFAFGAFAFECFCHECHABHGBHBBHBGEGGAGGAFDBHDCHDBEDGABEAGACHBHDBDABGHG,False +561,17.0,20.0,22.0,24.0,12.0,25.0,33.0,19.0,GFGGFCGFGDHGBCGHGHHGHCGHDGCGCDDCHGCFGFAHCHFDFCDEBDEBGFCEFCFFGAFCCGCHACBFDFGEEBBDDBECAFGAFGADGADGDDGADGFDEBDBBDBGCAGHGGDGGBBDFHCCDCEFABHHBHEEHBDHAFAGEAGDABFAHHAFBFGDCEBCBFFA,False +562,11.0,10.0,11.0,8.0,5.0,15.0,7.0,5.0,GBAGDDBFDHFDGFAACAACBBGFGEBGFFCFFCEFBEFBCBACFFCAHCAHEEDBAHFCFFCDDAGCAHDB,False +563,20.0,11.0,17.0,13.0,14.0,9.0,14.0,23.0,BAGDHGEHCAGCGEFAEFBCCHCCBDADHBDHADHCGHAGAFEAHHAHHACGCEACAHCDHBDGGDFEBFHHDHHCAHGAHFEEDGFDECDHHEHACFGHFECEGBBCAACAABDABEGBE,False +564,25.0,13.0,20.0,11.0,13.0,16.0,8.0,5.0,AAAAFFCFFBBFABDAGEAGAHGACCFEFGEGAEAACACEFCFFCDCHFBBCBCCADFBHFDCCBGABGCBABBDFACAAFGACACDEEDECDBDAEDAHDAECAECEEHF,False +565,28.0,15.0,20.0,25.0,16.0,15.0,18.0,16.0,AADAACACCACGGBEGAEGBEGFHCHCCEBCEBDBBDBCDAEDEBDABDFFHHEAADAHHGHGBDGCAGFADAADADFHEFHFGDEBDFCAFEHFBBFDHCDADDACDHFHAGCGDAGCABADCADEAGEGCHDDBDCAGFHGHCGAEFFECE,False +566,7.0,8.0,2.0,9.0,6.0,8.0,0.0,5.0,HEFHDFDDHDBEDBEFBDBBECBAFBFDAFHAFEDDBCEAAAFHA,True +567,12.0,8.0,8.0,9.0,5.0,12.0,6.0,5.0,DADDAGBGGBCHFGFDAFCACAEFADFGBFABCDDFEDFECHECDBAEAHCAHBACBFFAFFBGH,False +568,27.0,25.0,25.0,24.0,19.0,25.0,34.0,18.0,GGBDADGGGAGEFFECFEBGEADDADDAFHBBHBCFBCGGEGEDHDHBDFBACBGCFACBCGBEGHHGCAGHGBAFAHHBFHAFECHCABFGHCDHEFEFCEDCEGBGGDAGFFGFFGAFBEFEAFEGFDBFCAGCAGCABAHHHCEACBGEBDEAACCFGGFGDBGDCCDBEGBCDFADBAGBADDADHCDHCDGA,False +569,17.0,19.0,19.0,27.0,20.0,24.0,19.0,16.0,DCECCEHDBFDEDGEAGFGFBCHBCAGAHGFDAFDBHAGEADCHDCDGCBHCEFCHFCGFAADABFABFEECGFHHDHBDEBDBCFEEFEEAECGDBFCBDHBDEBDAFDAHCGDEBDEHDFADFDDFGAFEFCAFHDBEBBDGGACDBCHGFFGFGGEGH,False +570,14.0,23.0,26.0,22.0,21.0,32.0,13.0,35.0,DEACHFHFDHEHFCHFCEFBFHBECFECHDGEDFFDEFHFBCCACCHGDFCHFEHCAHCHHCEHEEHCHHCAHDDGFBHCBEAGGDBGFBEHBHFBADBFDAFGGGABHAGHABDFBFHCFDCFDHEHCEAAEGCBGDFCFFEFDBFBBFBCHBHDBEDHDDBAFFCFHAEHCEHCBHDBCDEGFH,False +571,12.0,18.0,32.0,29.0,10.0,22.0,15.0,20.0,DAHAAEGCCHHEBCEBHDDGDDFFCCCCCHCFHDDHDHADBEFBECBCDBCDFEDGHDHCECGACDAEGGDGDBFHCFDGDDGAEFDCFDAADAADHBCBBCGEDBBHCFHCABFDHFBFCBCCBCCHCFFDGCGGCHCBFDFFDFFCFHHBHGFCGD,False +572,19.0,12.0,16.0,19.0,24.0,11.0,17.0,21.0,AEAGEAEEBDEGDECBBDAHDAFECHEFHGFGGDEHDECGGCAEHEHHCBHDDHDEGCEGAHGFEGEEGEECFADFEDEGCCABAGBAHAHHAEHACACHAFHBCBBAEAFBHDDADDGDBFHGCHFCHCCGFDHDDBE,False +573,5.0,2.0,3.0,2.0,1.0,4.0,3.0,2.0,ACEFDDFABGAGGACFAHFCHB,True +574,17.0,18.0,22.0,17.0,4.0,9.0,12.0,14.0,CCBCGGAHDAEDBCFCCHCFACFAEDAHDAHGBGDFDDCACAAFBBDDBDBBFCBECADDACBFCBHCHHABCAHGBBGBADDACHAGHDGHDHBEHBGBGGCFDAGCCCFHC,False +575,13.0,19.0,23.0,32.0,16.0,20.0,25.0,19.0,GGDDGDDCHDBGDFDDHBBHGBHBFHCEAFEHFGFEGEGGDGDFCHFAEFBCFGHDGDEGDBHDAAGHDDADEBCEGCEFCEFEDBACHAHFDEFCGFGHBBBABDCBFCHDCFFCHDDGDDGECGEDAAHAADDAFDCGCHBCGBCEHDEGFFHBDCBDBGCCGCC,False +576,9.0,9.0,12.0,4.0,5.0,6.0,12.0,11.0,BHFCHFGHEGHBGEFHADCDCGGCFGCBDABAEBACGHEGFBGBAHCDHCGHAGEAHHCCFCBGABCA,False +577,6.0,7.0,11.0,9.0,9.0,12.0,13.0,8.0,EDDGBABEGCGACGECECCBCCHGEFDEFGGFGBCGDAGHGCHBFGBFDEFCFFAGFDHBDADFADFHHFHEEHC,False +578,0.0,1.0,2.0,1.0,0.0,2.0,4.0,0.0,GCGDCGFFGB,True +579,5.0,1.0,1.0,3.0,1.0,1.0,1.0,4.0,HGAHAACAAEHDFDDHB,True +580,23.0,6.0,7.0,14.0,17.0,10.0,20.0,6.0,EEAEEHDHGCBEABGFBGEACAADADGADHCGFGGEHGAGGDEAFEAGEDEAAAAAAEGCFGDFGDEGAEAFBAHBAGDFGDFECCECGDBAAGDEGHAFDDF,True +581,26.0,18.0,18.0,18.0,15.0,22.0,19.0,23.0,FFFAFECGECGHCGACGACAFFGHGEHADHFDHBDHCACGABGAFHHGAFGABDABAFBHEBAEAHFAGCAGCGFAEDGHFGAEBAEHDDHBDFAFBHDBFCHEHHGFDDBAEHAECAHGHECDFDDHHBFHBFCBADFFDCCDBCABGEBCEBDEGAC,False +582,21.0,17.0,16.0,25.0,18.0,9.0,13.0,8.0,GAHDCGBCBACDDBDGADCEDBFDAFDADEAEEBEHADFAHEGDBGFHGHCBAAHDEHEEACDACDECFEAHAGGAEGAEFADBGEBGCDDCFDABDCCAGBADBDFFDGDECDBCDCCEEBBEBBA,False +583,3.0,13.0,7.0,7.0,6.0,7.0,7.0,14.0,CGGBGGBGFBHBBHCAEBHEBHFFFDFADCDBFEBGCBCHHHDHHDBHEGDECBAHFDHBEHCH,False +584,19.0,16.0,23.0,16.0,22.0,21.0,12.0,29.0,CGHFFHFFHCFGDFDEECFDCDDABFAEAADFBEAECAEGAECHHCHAEHFECCHGCHGEGGEDHBABFAHEEBGEHHHBHHCDBCDBADCACABCBCCBHBGHDFHBFHCABGDCFCCADHAHHEHHEHFEABEGGAFDFEEFEAFCDDEHFBHCHF,False +585,5.0,14.0,11.0,11.0,4.0,5.0,12.0,10.0,DGDBCBFGBDAEHACCEHCDCCBHFBHFBHCAHGGGCGGBGCBEDBGBAGHFCHDCGDBHABEFBDDBDDHG,False +586,11.0,24.0,18.0,11.0,8.0,6.0,17.0,13.0,GBBGABCCDDEGDFGAHEAHCAEGBEGAEABEAHHCHBBHCBHCBGGGGGGBHCBCCBDDDCGGBEFFADFGBCABGBBDCBDBHABHBBHFBDFCHCBGDHACCCEC,False +587,14.0,18.0,17.0,13.0,15.0,17.0,25.0,21.0,ECCAFEAGBAGCGFCGHADHEBGCGGCBDCGABDHBEGBCGHHGFHGHHGHDGCACAEHBBBABGFHGFDGFDBDGBAHHGGBCEFCFHHFEHFEFFAFFAGFCHCHGABCHEFHCFEBDEBDACGAEGEEHBBDEDDGD,False +588,13.0,15.0,14.0,18.0,15.0,14.0,13.0,9.0,EFAHGBHGDHGDCADGDDEEEECFACDGDGHCCFCEDCBHFBGDBCDBCGFCGBCEDDEAFEAECAFCDFDDBHABHFEEBBHBACBADBGDEABFGFFADGAGFAEFEBH,False +589,12.0,8.0,10.0,3.0,6.0,15.0,8.0,10.0,FDAFCFFHFGHFGBFHAHAADACFCCBBCBBHADHACFAHBBCGGEBECHGAHEAEEAFFFCFFHGFCGAEG,False +590,17.0,15.0,7.0,14.0,11.0,14.0,9.0,6.0,HEAFCADCHBHAFEFFEDAAFBABCGDDFAAGDGDCBEBFEBDEBAEAEBAEBAFBGFBHFCGCHGHDGFAAFCADBDDBDDGFAGFABEDBE,False +591,10.0,3.0,10.0,5.0,10.0,14.0,7.0,11.0,CFGCFEAFHGFCGAHACGFEADCAECAEBEDGFDHFEHFEHBEHFECFAAFHAECDHGDBFHHFAHCCFG,False +592,19.0,16.0,12.0,22.0,13.0,29.0,15.0,13.0,GHBEBBFBGFCCFDDECDGGDFGAFABCHFAFFABBCHBAFGHFBEFDEFGEFGDDGDDACDBCEAFEACEDDFFAHEAEDDHHFFDFBGFHGDBFHECCCFBDEBAHFAEFAGFBGDHADAFDAFDAFHAFGAGCHDB,False +593,7.0,6.0,8.0,6.0,8.0,9.0,6.0,6.0,DCHBFDCFDGACEACBBCBGHAGHFEHFEHDEGAEAACGFBFCHFCAEDFEBEDGF,False +594,30.0,31.0,17.0,16.0,20.0,23.0,18.0,23.0,ECHGCHGBBGFBGABGCDGHFFBFABDADAFEAFEHGBAABEABHABHACFACBEFADDADFBCGHHABFEBEGBCGEHFEFEBGEHGDAFBHDAFBAHBAHFAFACGDCHDCHDGBEBHEFEAFEDHACEBCFBCHBFHBAACFCBAHGHDDEADHAECACGBBABAFBFEBGEHGD,False +595,9.0,14.0,16.0,12.0,7.0,14.0,15.0,6.0,FEGFGGFDBAGEFGEFCCHCBEFBCGACBACFCCBCAFCAGGFFCBHGBHDBADADHADGBDGBDEBCHFCFCCGBDGDHEDADDFEBGGCFB,False +596,26.0,34.0,20.0,24.0,21.0,26.0,22.0,25.0,FEEBEHGEHEFHEFEEACGABBDHDDHGCGFDACBGBHGFHDADCFGCGBDAHHCFHGFEEFEAHEBHGBAABDABFAHFHDDADDFDBGGBFHBAEBAEBAHBAFACFADADDAGGBBGBBCCACFFBDFHDFHDBCBCABAECDFGDGHHEECCAFDBDEFCEFGDBBHBBHGGHFBHEGGEBCABCFBCFCAHBA,False +597,16.0,18.0,17.0,23.0,22.0,17.0,16.0,28.0,EECBEAGEDFCFADAHFCHFCHECDBGDBHDCHAAHDDBDDCDHHFHBAHBEHDEHAFHAHHEEGEEGDEBDEDDHBEBGEHGEHCACFHBDBACHECEBCACCGCGGEHHDHBFGEABFDFFDGFAHCGHCFHBGHGDABDAFGBEGFDFBDEHFA,False +598,14.0,9.0,12.0,11.0,20.0,14.0,7.0,8.0,EEAFAGFHFFBEAGHBCFFFFDFFBAFCEGEEGDCGDCBAADAHFFHAGHACDECBEDBEAACDGCEACHDDADBECBECHEAHFDEEEEEEEBC,False +599,31.0,15.0,28.0,34.0,25.0,28.0,16.0,23.0,EADADBADCDDCGEGGEAFEFGBDDCFACDECFECFBCHAEHABGFCCAECDEDGCDGCDGEAHDBBDBACEAFBFEBEDBEBEEFGAAGADGDFFCEFAFAABDFHDFHDGCDGHDFCDFHEFAEGCFDAFDAFDEFHBCDAFEECHHDDHDCFFAHHHHCHADEADADBADBCGCCHFAFCEHHAFHAHHAEGACCCH,False +600,10.0,11.0,5.0,10.0,8.0,10.0,7.0,10.0,HBFHBHGFGEFGEFAAFAGFGEBBHBDGBHHAHCDHEHBEAFDDBBABDFDCFHEBCECCADGADFADAED,False +601,1.0,4.0,4.0,5.0,1.0,4.0,5.0,0.0,EGCDDCBDCFDFBGBDGCAGFBGF,True +602,4.0,2.0,2.0,6.0,6.0,0.0,2.0,3.0,EDEEBAEDHEAGEABCHDCDDADGH,True +603,22.0,28.0,15.0,26.0,22.0,27.0,16.0,24.0,EADBBCFGEFEAGAFEACAHCDBABGHBHAEDGGDCGFBBFHFCEFCEFEDAEGEHGABFHBFDBGDBABGGCGBCGBABHAFDDFBDFBGFHFCHFCHFHECHDFFDFABFDBHDFDCFDCABHABHEHADCDDCDHFEEDAEDFEBHHAFHGBHBBEEBDHDHEDABDABAEGEEHAF,False +604,21.0,11.0,14.0,19.0,11.0,12.0,18.0,29.0,GHHGHHAHADHAHCGBCGBDGBDHDFAABAEHFCDDAACAFHBHHDEBEGAGGEBGEHDEGFGGCHGDBDHHDAAAACFACFHBHEAAEHADHGCHGHDBCFHEFHEFECDDHFDCGDFGAFHAHHCHBCGDCAD,False +605,9.0,11.0,6.0,10.0,8.0,6.0,9.0,4.0,DCGDAGDABEBBEBGEBGDDGHAHHBCCECAHAFFAEDCEFFEDCBGBBGEGDFGDBAAFDAB,False +606,28.0,22.0,23.0,19.0,24.0,23.0,22.0,23.0,GHDEEDGFDEHCEBCEBAGAAGEGGEGABFHGFAGAHGDCCDHFBADBDDBCDBFHFDGEEGCEHFFHCCHAGHABEACCACDFEEFAFGEFBCGBCBFAFFBFFDGEEGBEHBHHDCACFHCACAABAABAECCDFHHFHBDAEFHEFEECGFBGCDGEHCBGDBAAAHCAHDEHDBHABAAG,False +607,13.0,16.0,14.0,14.0,17.0,12.0,10.0,10.0,BGHBGADGDDGCECBEDBECAECGECGECFACFBEEBEADEDHFAHAAHBFEBHDCFDGDBFFBEGCAFADDHCABDACDABDHGFFGEEBFEBABCEFEHCHHCB,False +608,9.0,17.0,16.0,8.0,12.0,15.0,18.0,16.0,BGGGDCHHBHGBEACEACEGCEHFHCBGBBGFBGFAHCDGCFFCFGCBGBBGBFGBFAHFBGFBABCEGCEADHHEHHCHFEGEDHDDCDABGHECCFCFFGBADEAEHFH,False +609,34.0,28.0,25.0,20.0,27.0,20.0,18.0,15.0,FHGFEGEBBEGBEGHFHDFDAAEAAEDCFDBFEFCDCDDGEAFEADBCCACCDFHHBCHFEDABBABBABHAFGACGEEEACCACDDCBFCDHBFGBAGCGFADEADGABFABAGEEEBHBFDBFEBGEBEBHCCDCAGCAECAECAFCHGEEBFEAGEDECAHHABABBABDFDAHCABCAGHAGA,False +610,27.0,20.0,29.0,19.0,16.0,20.0,23.0,16.0,EDGGDCDCCDCCFAHFACFEEAAGGAHFADGADAEDCEACDAGDAHDCHFAFFHCGHCGDEBAEBAFHADHCBFBBDAECAECACGGGGFFCDGBHGECFBABDABGECGEFBFCBHDBHAHGACBAHEACCACHBHEFCBDCGDBGCBGHGCBFCADEFBFFGABGCEF,False +611,22.0,21.0,24.0,24.0,11.0,17.0,21.0,18.0,CGCHDBGDBABGACGAEAACCDDCDGCDGFDEHBABFCHACHAFGDEBDEBDABHGBCFBCBAHBDFBHFCFECFECGAGEAEBDGCGGCHGDFGDFCFBHFAFGAGHHFBHDAADCAHCAGEABCCBDDEDDHCCAAHFHHDADDBGHCGBFFBEDG,False +612,15.0,15.0,16.0,7.0,8.0,15.0,11.0,10.0,BBGABCABCFCHFCBCAGHHFHFFBFAAFAGBAGDEFFCFECACDACAFCABEEGCEGCAGDBCHBDDFDDFAFHACBGBHGBHCEEEGHCGFBHBA,False +613,1.0,6.0,10.0,13.0,4.0,6.0,8.0,9.0,GCDDCDCAHCHEDFDCCDGGDBHDCHDBHCGGFGCFGHFGFFHHCBBEEBDEDDBDH,True +614,10.0,16.0,11.0,12.0,14.0,10.0,10.0,10.0,DECEGBDAEDAEGGGHGAAEBAEHDGHGEBCHBCHBFEBCBFCBAHEDFEDFGAFDCFBCFBDFBCHCCHDHBDBBABFDGEEEDCEGAHBAF,False +615,1.0,1.0,2.0,4.0,6.0,3.0,0.0,3.0,HDEHFEDCEABEHFEDDECF,True +616,10.0,6.0,9.0,12.0,6.0,14.0,6.0,4.0,DFHDFBBECCFCCFBCDGAFFABDAGEADBDDACECFECGAAGHFHFFHFFDGDAFDEFDEBDAAGC,True +617,6.0,1.0,4.0,3.0,5.0,2.0,0.0,4.0,BDEHDAAFACHECHECDEFHCAAEA,True +618,22.0,16.0,36.0,14.0,21.0,16.0,20.0,16.0,BBGEBEHHHHHACECCGBEDBCDHHAHDCHDCECAFHAFDAFCAECGCCACCGFFDEGACGCCGCEGCGGEGACGACBDGGDEAEBAEGFECAECFBGECAEFFHBCCBCHEFADFDECDBCBFDHDECDGAABHCFGCAGCFGABEABCABCECCFFAHH,False +619,26.0,17.0,24.0,18.0,27.0,15.0,23.0,23.0,ADFABEBGDCGDEAEHBHDBCGECBECEEGAHGCCECGFCAFCHECFACBAHBACBAEBDEHFEDDEHGHHGHHGAHGAHFADAAGEAEDAFAADADHEGHEGHGBHDBCEECGFCHEBHBBFAHDCGAEGEEGECGHCFCFGCDDFDCBCFEAAAFEAHGBGDCDBEFCHAG,False +620,7.0,2.0,1.0,9.0,6.0,2.0,5.0,5.0,GBEGBDDHGCFGDGHEEHDEFAADAAHAAEAHEDDDD,True +621,16.0,26.0,22.0,21.0,29.0,29.0,17.0,19.0,EAFBDDEEGGEGGEGDFBBFADADCGDCBCCHCDDEDFEDFADFEDFGBFHBECAHCDBCGFCFECEEHAFHAFCGFBEHGFHEEHFEBCGBGGHABFGDAGCABFDBFDFFDEFBBBDHBEECFEHEACBFBDFHAHHEHHEHCCHGBAEBDCCEEFBBFAFCBDCBFBAFEACEGHE,False +622,7.0,7.0,8.0,11.0,8.0,4.0,10.0,8.0,DAGDCGDHGDACDBCFHHEGDEDEFHCBHEBHFDHEHBCGGEGBCGDCFDGEDCAABAABEAG,False +623,28.0,16.0,21.0,17.0,19.0,16.0,21.0,15.0,DEHGEHCAACGFGGBEFBEGGGBGFADAEDADDCCHGGACAACEBDGFCBDAAFBCCCCCAEEEECHDCEDAEFAHFABFACFGHHBEGCEFBAHCDHDBCEBCEAHAAHAABEDGECGFAGFABFAHFAHEAHDHBFCBDDAFDAGBGGDGG,False +624,3.0,1.0,2.0,2.0,0.0,4.0,3.0,0.0,GAAFDAFGGFCDFCB,True +625,2.0,3.0,2.0,8.0,3.0,1.0,2.0,1.0,DHDDBDABEGDDGBFAEDCEDC,True +626,25.0,22.0,16.0,18.0,24.0,24.0,24.0,13.0,EBGFHAFDBGEBGEFGEDHADHADAAFCAFCHGEAGACBDGBFBDFEDGEHGEHGDHGCFCEFBEACEBHGFHEBHEGFEBAECFBABCACCABAEDEDGEGCABEEDGEAGAAGCFFDBCGHAGCAFFGFDAFHFFGEBBBHBDAGDABDBDGBAFEDFCAFCEF,False +627,29.0,21.0,28.0,24.0,31.0,21.0,20.0,20.0,FAHFBGFACEAEHGHHCFHGAGFFCCDDBDGBDGBDBHEBHECCEHCAFEGEHGEHGEGGBCABADDACDEEBCHCGAAEAFCABCEBDABEABCAECAEAHHFCFGDFHDFHBCECEDCDFCDACEFBEDBFDBEBEHHECCEDAFDGFDHEEHEGHCDDADAAEGAFADCGCGFEGFEABACFAEBACBGDA,False +628,12.0,14.0,20.0,9.0,14.0,5.0,7.0,10.0,BAHEECEFDEACFADDABAECEHFDHCCCACBAEDHEBHEBHFHCFCCGCDACAADGEGCCGCGBCBBCGBCEBEHBEDCADBEGBCABHH,False +629,5.0,5.0,7.0,3.0,4.0,2.0,2.0,2.0,EFAECAECHGHFCDABDBCDBCBCABCGEA,True +630,23.0,22.0,17.0,29.0,22.0,31.0,12.0,12.0,CCDECDBBHBBHBGFACDAEHBFBGFCCEHGEHEECEFDDFDDBEDBAFEHBDHBFFFFFFFAFFAFHDFAEFACFCCGAFAAFGADGADFFEBHEGEAAFBDGBDADDAGEACECCFBBEEGGEBDBBCAADFEDCADFFDFAEFBHDDDDBCCBFGDAEHEHDDAD,False +631,27.0,22.0,17.0,34.0,24.0,29.0,22.0,24.0,FFDCFDCHHBFADFAGECGECGBFBAFBGGACBFCBACHEFEEFBEFEEFCBAEECEHAEGAEFACFADFDBFBHHDHAFHADDGHHEHDDGEBEEGFFDDGEDGADGBDHFDHFBHFHAABAADHAEHBHGDFGEAADDFDCCDCDDFBAGCFDCGDHBDHEAFDGBEGBADEFGCDBADGADHEHGFHBDHADGACB,False +632,14.0,22.0,9.0,14.0,13.0,13.0,20.0,23.0,BCFBCFAHGDHGAHEDGEBBCBHEGHDDDBAGBAGCECBBGBDABAGHDGHEFFBHEEEEHDEBDEFAAFAHGDGCDAFHAHGADGAGCDDHHFHGFHEBHBGHBFBBFGBFHHFAHCHHBECBGBGG,False +633,24.0,22.0,20.0,25.0,23.0,16.0,19.0,23.0,DBBDHHDHHEFEEFGABGFEGADFACHGEHGEHAFFAHECCEACEBBHBEFADDDDGGHGGHAABCFDCFBGFAECDGBDABEAFECFEHBAHFDBFDBDEFCBCCGDEACAAGBBGBDEAEAAGAAHBGHACCAECGCCDCGDEHAHGBDDEDDHDBHDHHFCHDBHEBCE,False +634,17.0,21.0,22.0,24.0,23.0,23.0,16.0,18.0,CBHDBHCEHCHBGDBECHEHFBCFDFBDFCGFCACCACCGDEAFGADEADFCDFBAHAGHGEBDDBDEBDHBGBDAEDBEDCEFCEFHBHCGDAHAAEDEEGGECBEHDGDBGEHFEFGEFBFFAFFCCFECEDHEGCAGBACFDGFDHFBABHADFBEFHADC,False +635,16.0,6.0,8.0,5.0,5.0,8.0,8.0,4.0,FFABFACAAFAAHAFHCEACEABFCDGCFACABGGDGCABAEBGEAGBAGHACHFEDDDG,False +636,0.0,0.0,0.0,2.0,3.0,1.0,3.0,2.0,EHGEHDEDGFG,True +637,9.0,16.0,10.0,10.0,13.0,11.0,8.0,12.0,FEDBEDBEBBEFBEHBFBFCBEGBAGBHGHDBDDEGBECEFHDDHCFHGBHEBCGBEFAACBDEFCGFAAHAHHFFAADAHDCHGCECC,False +638,12.0,9.0,9.0,12.0,9.0,15.0,8.0,15.0,EFGFDCDAGDHFCBFEAFHACHBGADEEHEFGEDHFDGDDGAECCFHBFHBCACHACHACFAFBGDBGDBHBHHBHDEHDAAAEFFFHF,False +639,14.0,20.0,11.0,14.0,9.0,16.0,14.0,14.0,BFBHEBAEDADCGDAGDAFBHCBACBAEAHHCGBCGFCGAABFCBFGADBFFFDFCDFEAGGDHDDEFFHGHHGHHEFEBHBBGDBCHBEHBEFBCABDGGDCGAFHBFABD,False +640,8.0,6.0,17.0,2.0,13.0,12.0,17.0,7.0,HCFFGFCHCCACAADFGBFCFFCGFCABGBEABGCEGCEGCACCFGDGECGHCAEGBEGEEGHBGEAFEHFEHGHGEECCGF,True +641,14.0,17.0,15.0,14.0,30.0,13.0,21.0,15.0,BBGEDAHDBBEHBCBEHAEGAFGECGACGADAFGFFGFEGDBCCBFCHDHABHEBGEDADDHEGHBBHEGCGCHEEHEEHGEHACACCEGCGGEDGFGAFDBFCAFBAFEEEHGEGFEBEEBHEFDECEEDEBGEDCAD,False +642,26.0,25.0,28.0,26.0,13.0,16.0,19.0,13.0,EBDECDGCAACBAHFACDCCBCDDHDFBDBDAHGAHGBHGBCFDEADGADGHFGBAHBCCDHBDFDFHAEEFDCGGCFCAFGACGCCFADBAEBGBGGBFGDFBFCAACAACECBBHBBGABGFCAHCDFGDCCEBCDACHBCAAEDEEDFEHEDABDACDAGDBB,False +643,14.0,19.0,17.0,9.0,14.0,22.0,18.0,8.0,GCCFBFFBEABEHDEBDGBDFAHFBHCBDEBDGBDHHFFGAFGCGHCACFBGGAGGFEGFCAFCADGGCFECECGFAGFAGACHAFHDCBBCBFABFEBCCBGFEAECDBBFFBAEEEEFG,False +644,15.0,27.0,16.0,22.0,21.0,27.0,27.0,18.0,EDFEFFDFBDGBEGBHCFHCFHFAHFGFFEHGEBGEBGABGCGEBGFFHADEDGEBFABGAEFEGFGGAGFDHFBHCBADAEFBCFCCHDFBEADEDBBBGDBDCACCFCEFDDFBHHAGHGGBGBEGCFCBFEGDAGDEHCEHEBHEBADHDHHDGCDGBAFBDCGAFGDBB,False +645,14.0,11.0,10.0,13.0,16.0,12.0,10.0,15.0,EEHEEHGEFGEDEDBGCBHHFHBFDBEEBEBAHBDGACGADGHEHHECDFHDFDFAEFACFBEBHEHAGDCHDCDGCFAAFAAGCDGCAAAHHFBCDBAFE,False +646,3.0,5.0,2.0,4.0,7.0,6.0,2.0,5.0,EEDEFDFHDFHGFHCBHFBEEEABHABFDBGCEA,True +647,17.0,19.0,20.0,19.0,12.0,18.0,17.0,19.0,HCFBAFBDFDHBCACEAFHCGGCAHBHHBHFECADGBGCDACAECGDCFDFEHBABGADGACGBEFHGFBDBCCBCFBDFADFGGFEGFHGFEBDDBDDADBFGCFGHECHCHHGGBECECCEBDEDHADHADHAFHAHAB,False +648,10.0,10.0,6.0,7.0,5.0,10.0,7.0,10.0,CHGDHGHAECAEAGBCGCEDFBGFCGBCFBHAEAFHDFBEHBGFAFFDDABDABDFBHFHHABHA,False +649,23.0,19.0,18.0,23.0,11.0,22.0,22.0,16.0,DFGDAGAEGAEDABBFDGADBHHAEGECAFDAEDACGBCGDCGHCGBCHEGACCAFDBFHBGGGDBGBFCBEGFHAHHCEDAEDBBAFAFFAFGAHCHCCDCCGBDEFHFFDBFBCFDCDDAAAGDEBDBBHBFHGFHFFHFAHGDGGDACDAF,False +650,4.0,5.0,4.0,4.0,6.0,3.0,2.0,5.0,DDHGDFGEFAECAFCDBCHEEAEEHHBACBHBB,False +651,29.0,15.0,14.0,25.0,15.0,16.0,23.0,19.0,GAFBABHAGGACGAGGAGHABDGFCGDEGEFDFACFBDAHAAHCGECDHFEHCDDEDDECGFDDFEDADAFDBFDBEGHFBAGBADBCDGAFFCEDEHAAHAACGAGDFDDFDAADCAFHBEHGEHGCGEBBHHBCDBCDHEBAEGGHGHHAAHAA,False +652,17.0,19.0,21.0,19.0,20.0,33.0,24.0,19.0,EBHGBHEFHAFCFFEAFEADEBHCBFCEFDEFHBGHGFDGDAHEGFEABBBBFBBFBBFAFEBDHBCBCGFEHACDCFDBGHGEFGACCFFFFDADGFDCFGEGHHGEHFFHEFHCFAGFBGCCGDCDDCGECGHAHEAGEDBCDEHDGHFGFCCDAAFAAFGAFDCGECGD,False +653,4.0,2.0,1.0,5.0,5.0,3.0,4.0,8.0,GBFEDEDGEDEADHGHHGHHDBHAHEFHCFAA,True +654,20.0,23.0,22.0,29.0,18.0,18.0,13.0,18.0,EDEBAEGHHFAHFBDDBGFBGDDABDABDADCCBBCEHGFCGFCDEHDFDGHDCBDHFDCBHBFHECCADGHGGEGBCBACHAEGEEFDEHDCHBEHFDBFCEACFAEDAFBGDBDDBDDBFDCFDCHDAACAABACGFCACDHHAFBAFBHEDCEBEEAC,False +655,7.0,8.0,11.0,11.0,11.0,5.0,11.0,11.0,CHBCHDCHBAHBCGDEGDACDEBAAAFBEFHFBGFEDEEAEEGDGGDGHDAHDHBEEGDECCBHCGCCGHCFHDG,False +656,23.0,22.0,23.0,10.0,19.0,19.0,24.0,14.0,FCGFCGAAEBHECHECHCGABAAFFEHBAHBCBBDEBEFDFADFGDFACFAFAHFBCEACECCDGBFEBFCCCCEGAAHAGEBGABCFBAAGFDFCEABEABECDGCGAHGHCCHBAFBHEEHCGBFGBAHBGGEGGEDBEDBDFGGGGGGACH,False +657,17.0,18.0,13.0,17.0,9.0,17.0,17.0,24.0,BDHBDGBFEBCHBDFBDHBAHBHHAAGABHACFFHHBBDDHHDHGFCFFCGHHBAHADGFDCFHCHCCBDFFGAFGAEEAGEHHBGFFGFAGHADHDCBDEFDECGAGADCAGCHGEHBEHFDABDGBCGAE,False +658,8.0,8.0,5.0,2.0,2.0,4.0,5.0,8.0,CEGBBGBHCFHBHBBABGEBHHGCFAAHADHAHGACFACFAD,True +659,34.0,21.0,21.0,17.0,21.0,20.0,30.0,25.0,HAFHDCDEGEEGAAGBGCBEAGEBGEAHCAHEAHCAHAAHFBHECECABCAHGGFGHHGEHDADFACFACFCGFCGFBBFAAHAAHBFFDAFDGFCAEAGFAEDBGBCEEFFFDEAGGADGCDFHGGHBCABCABCABHDGDGGEGGEGHEAHBDGBHHBCHDFAECGDBHAGHADABBACEFHBDEGC,False +660,14.0,30.0,12.0,19.0,8.0,11.0,20.0,13.0,DEBHHDCGGHGCHBFBFGBFDDFDDGDGBDBBABHDBHACECCACEABBAEBDBBGGGCGDAHCADCABHEFHBFDCDCGGFBGDBDBBGGBCGBEBBEBBHHBHFFHFAADGBBGBGADDFEAAGA,False +661,11.0,26.0,15.0,26.0,16.0,14.0,18.0,26.0,FEBHBBCBDCEDFABGAGEABBHBGCDGFDEBBEBBDBEGBEDDHHDHFBHEBEEGAHHDHHCBHCAHDHCAACEGBEGBDGBHBHDFHDHDFHECHCHEAHBGCFCFHDDHDDFDDAGEGGCCGDFGFAGFGDBBBHBDHFDACDCHFGDE,False +662,5.0,2.0,4.0,1.0,4.0,3.0,0.0,4.0,HCDFCFHCACAEEAEFBHABHAE,True +663,14.0,22.0,18.0,13.0,14.0,22.0,18.0,29.0,DHBHHBGHGDDFFFCBHCBFCHGCGGHHHHABCCBAFAEGBBDBFCFECFADFHBCHADBADGHDGCDACFHBFGFFBFGCFAAEACHAFHEEEEHGEHAEBGBGGBFCBFBGGBGAHDHHBECEHCHBFECFHAFHDCHDEHDEHGFHB,False +664,22.0,13.0,19.0,20.0,21.0,19.0,24.0,26.0,AACFEGGECAHDGHDGDBEHBGDGGCBEAGEFEAGBGGBFFBGGGGDCEEAAFFAHEBFEFACFECEABEFHGFHDAHCBHCFGDFHDAHGEHEAHEAGCCCHDAHFCEFCDCAFCGCHFCHGCHGCBGFBGHHDAHEAHDHHDHEEADEFDHADADDHDBADB,False +665,19.0,16.0,20.0,18.0,23.0,17.0,22.0,24.0,DAACFCEFCEHBFHAEHDBHBHABHABHAHCCGGCGCEDBDHBACCCCCAEDHEACEHEDGECGEFGCGDEFHCAHADFDEEDBECEACDGEDGFHFAEFAGBHHAHHDHAGBBFCGFEGHBHFDEFDHFHHABGABGEDGEDGEGGBCEBGDFGFFGA,False +666,21.0,15.0,10.0,14.0,9.0,13.0,18.0,9.0,ACFGBACCACCADCDGADGADGHBABGDFEDEGAGFADADDBEABDABEABAFBAFBGFGGACGBFEBFEHFHGACGCFEDGBGABCEHFGBAGFEDADBAFHHGHHDH,False +667,8.0,7.0,10.0,12.0,11.0,15.0,18.0,9.0,FAGEGGDGEAGDFCFFHBFDBGDFGBAGHCGFCDBCGBDFHGFHEACECCECAEFGCFGHFEDGHGBHFCHAEDAEDGDFGFGEBEDHAD,False +668,10.0,9.0,8.0,13.0,5.0,7.0,10.0,7.0,GFDGECCECCFHAGBGDBDFADGEDAADAADAADCGBGHBHBDHFGHFAHFACDEHBEBDDCGGCDFBB,False +669,7.0,12.0,7.0,12.0,9.0,2.0,15.0,14.0,HBGHAGHEGBCADABEEHFCCGHGGEGGCDGCHGEDGDBADBHDBGEAGAACEDDFBHBBHBDHBDHGCHGHDEEBHD,True +670,0.0,5.0,2.0,3.0,7.0,4.0,3.0,4.0,FGCFHFEDBHBBHFBGEBEEDEEGEHCD,True +671,5.0,12.0,12.0,3.0,8.0,4.0,5.0,4.0,BBCBBAECHCGHCHFCFCCBDBECBEBFEBCGHCEFGGBAGEAEEACCBDABD,True +672,11.0,18.0,12.0,10.0,18.0,18.0,25.0,17.0,AGBBGFGCFCEFCBHCADEBHCHDEBGGGGGAGGCGFHFBHDBFFAFHAEHFEFFAGBEDHHHHBBCFHAFCGCCBEHBEHGDBFEAGEHGEAGEAGEGDBGDCGDGGDFHEFEBBCBAGBEDHEFGEF,False +673,9.0,13.0,14.0,18.0,14.0,11.0,8.0,15.0,CGDBHCCHGBFGAFEEHEHCEHCACCADCDDCGBCDBHDHCBHEHABHEEGDFHDGACBAGDFEDFEDECDBDHFEHBEFFEBCEBDABAAGFHFDDFDDHB,False +674,8.0,13.0,7.0,9.0,11.0,13.0,8.0,11.0,GHHFHFCGFBEFDEDDBFDBAHFHHFCHEDGEHGCBDBHHAEGAEAAEBAGBAEFCFGCFAHBGEFECBCBBDBBDEFDF,False +675,1.0,9.0,5.0,1.0,4.0,4.0,4.0,4.0,BECBCFDGHHBEBBFBBFBCFBHGAHGCEECG,True +676,7.0,7.0,1.0,4.0,6.0,8.0,6.0,3.0,ECHEDFEAHHDFABGEBEABEDGFAGBAFBAFGFGGFABFDB,False +677,14.0,18.0,19.0,11.0,14.0,16.0,16.0,25.0,EEHFECBGCECHDBHGHHGHHGABBDFBDFBAFHAGDABCABFHHABGAEGDBHHGHFFHDFEDFHFGACBCCGCAAFFAHACDGCDBCHBFGBHEFHAFCCEBBDHCHFAHEGHEGCEHCECCHGEGBECBD,False +678,9.0,12.0,6.0,10.0,11.0,11.0,13.0,11.0,CDEAGGDGGCGBCGBAGBGEBDCAFGHFGBFEHEEACFAGFDEFGBHHFHHEHFCGDADHHDHEDAADFBFBBFBEEHEABBD,False +679,27.0,20.0,25.0,20.0,31.0,18.0,23.0,23.0,EFHEDHDDBECBDAFEEFEEAADGGCGEBGADEECEEFEECAFCGEGGBFCBFABGACDAEHBHCFGCHGCHGCFDCBHHBEABAHBABAHEAHGADGCCFECDHDFAGECHAFBADBGDBCABHADDBHCEHCEHBFHGFEEDCDHCEECGCDBCAHGHBGEAGEAFFAFGAEEAFAHGEHGDACD,False +680,27.0,26.0,27.0,28.0,20.0,19.0,14.0,25.0,GDCFDCFHCBAEGAFACFAGFDBEABDBCAHCGFFFCFBBBADBGFCDACDGDDHCEHAEHBFGBHECDEGAACBHCHEAHEFCGACDBHDACGACHAHHAHDEHFCBBABBABCHBFDCGBCHBCHFDHEEBDEHEEHGEFABHAHCAEDBCDBCDEEDCBDBHAFAGEADDADFADFDDHGDEC,False +681,3.0,1.0,1.0,3.0,4.0,8.0,7.0,1.0,HGFEDDABGFGGFGFFGCGAFDAFEEFE,True +682,15.0,12.0,11.0,14.0,15.0,27.0,23.0,14.0,FHFFHFCHGEDCEDGABGDBGFFGFHGDDFFDGCHECAEGEBCEFCEAAAAGACFAGGGBEGBFBAFBAGGAEHAEHBDGGDFDAHGGEGGHAFHGCEFDBFEHDDBGFBCFAFFEHFCHFHDFCFFDEFB,False +683,3.0,2.0,5.0,6.0,4.0,4.0,5.0,2.0,GGFDFADFADECDCGBCGEDHEDHGCBCAEF,False +684,13.0,18.0,21.0,19.0,20.0,13.0,21.0,11.0,FEEGGCAGBEGFECBEGBDHBDCCGACGFBFEHHEHBCHCCFDCDDCEACEAFHHFCFDEBBGBDCBDBADEDEGCFDHABEDGEGFDCFECDEAHEDGEAGFAEAAGHADABDBGCGGBGFBDCBDGBCGECGHC,False +685,10.0,7.0,12.0,11.0,9.0,18.0,8.0,9.0,HDHAGFAFFAFFAEBDCBDBEAFEACEACDGDDGFCHFCBCCACHGCFFCGDEFDFHEFHDCBEHGEGFFDFAAFBEFCDGHBH,False +686,6.0,12.0,8.0,11.0,9.0,7.0,20.0,10.0,BCEBCDBHAGDAGDHGDEDAGDGHBEHDDFGDGEDAEGGGCEBCBGGGCHECBFHHGGFGGFGGHGAHFBBCBECBHABFDEF,False +687,12.0,20.0,16.0,25.0,15.0,20.0,20.0,33.0,DFDHAGHAEHBHBFCFFDHFDBGGCCBDABHGGHBBCBFCHCEEADDACDFCAFBHBHDBHFBADGHDGHDGFEEBHHGGHGHFGDFCDHEEHCECCHDBDAGDABDCBFHAGEAHEHHEHFDHFDHFDEFDCCGBCHEDHBDGEHGBBGFDHAHHFEFGG,False +688,3.0,9.0,2.0,3.0,7.0,7.0,3.0,4.0,CFEHFBFBBEDBCHAFABFEBEEBDEHFEDFHBGGBGA,True +689,15.0,26.0,20.0,34.0,29.0,23.0,27.0,17.0,GAAGDABHABEGDEBDFFDHFEHFBFCBGCBCCDGFDEHDCFDBHEBEFBEBCGCDGADBDGGGAAFCEDCEDBHGBDDBEDFFGFEHBEFFCAHCHHGFDDBCDBDFEHFGAFHFFDBEABEFBGFAGHGGEECCGABDDBEEBECBEAGCHGDHGDEDHFDHDAECAECDEDGEDEBCEDDGGDEGBCG,False +690,2.0,5.0,5.0,7.0,3.0,8.0,3.0,2.0,GFGFFGFDHHAEBCCBCDFCDEADFDBFDCEDBBF,True +691,11.0,14.0,14.0,3.0,13.0,5.0,13.0,10.0,ABGFGEEGEEGEHAHBCHBDDGHBBABACBCEEGECGECGHCABCABCHBEGAEFCCGBFGCAEFGECBFHACHACHDHBGBA,False +692,17.0,27.0,23.0,13.0,20.0,16.0,15.0,12.0,BCCBCGFCGFADAABEDHEHBEADCFFEFFCABCGBABBEGBADBABBFCACGEDBEBBGFBGHBGHDEHBEHBCHACHFGEECHGFHGCCGECGDBBDGAEADFCGECDEFEFCCFAHFEHEABAFCCECEBDDBADBABBC,False +693,27.0,22.0,19.0,22.0,14.0,28.0,28.0,25.0,FCDFEDBEDFECFBHAAHEACBFDEGDCGFFHHFADGABFAFAAGGBHFECAECAGCGBDGBDHBHCBHFEHBBAFAAFAFFCHFGGFHAADCCGCCGBHGDDGFDGBDGBABHAGFDBFGBHAEFFDGFDGCAACAGGHDGAGCDEHDHBGHEFCEFADHEHABHAFHEHHDBGGBFCBGCHAD,False +694,18.0,13.0,19.0,10.0,11.0,15.0,13.0,6.0,GDGHAABAGDGHFBFGBCGACGAEAFDAFDECHECACBFCBACBEBDGBFACEEBEDCEACEBBDDBGFAFFDCFECDHCACCGBFGHGCEGCAAHAAFCAFCFF,False +695,10.0,11.0,11.0,10.0,20.0,12.0,15.0,5.0,DBDBFDEGDBGEEGEGFAAEGDFCFECEEAEEBHGGHCGHCFACGHEGEEGAEFCEFBAFBAEEACCGFDBFCHACEDFADFGBGCBDEBEGBD,False +696,11.0,15.0,9.0,15.0,19.0,14.0,16.0,14.0,BBEABEBFEDFHBEDCFCEDEFDECCEFGFGBHGBCGHGFHEBDGBFGCFGDGDACDAFBFHBHGECGEHDEHBBFDEEDGEFCAAHEABEHHEAHEAHDAHDGGDBGFAGAD,False +697,4.0,10.0,3.0,4.0,4.0,9.0,13.0,9.0,EFFBHHHHHCADDEGDFGBBGHFGBBBBHBACEHCFBEGDGGFGGFGAFGAGHFGB,True +698,8.0,6.0,6.0,10.0,3.0,3.0,10.0,9.0,CHGBHGEHGAAGHDGDAGDBDHADHBDHDAFACBCFBGEHCEFCGABGAGDCDDH,True +699,23.0,20.0,26.0,25.0,24.0,29.0,20.0,24.0,CDBFFGEGEACCACDGBDCHACHACHBGDBCFBHFHHFHHAGHAGHCHAEEGCEHEEFFCDFDDFDFAAEEFEEFBEDAEDFGDFGDHHDBCBBCEBEABADDAEDGGGCEHAGBEFBCFDHFBEFADFDCEHFEHFHADCFDAFHAFBFCEDDBCAHAACGCBFCDHBFHDAGFEGFGGCCGCBBCAHGE,False +700,29.0,20.0,21.0,24.0,24.0,23.0,13.0,26.0,EBHEBHBADGAHAAEEACGAFAAFBBFCHDBHAGCDEBDCDDAHHBCEAAFHAFCABDDEDEEDFHDFCDFBEGCFGEFAFGCHGDHFFEFHEDDEADBACACEFCBHCEHCAAEAECAEBFDAFHAHGAHGBGCBDHBDABDHBDHADFGEBABHFCFFAHFDECHHCHHCFCGDEGEE,False +701,3.0,7.0,7.0,3.0,6.0,6.0,4.0,11.0,CEFCFHGFHBHEAHECHEBBAHAEECHCDHCFFCHBGFBDDBGHBGH,False +702,9.0,6.0,16.0,15.0,12.0,8.0,10.0,9.0,FDCFDCDAHDGHFAACBCHDEHEGDEDDFDDEGCGCDBCDEAFCBCCBCGACGACHHEEHADDAEDCECFECFAGGBBEHFGHEG,False +703,6.0,1.0,3.0,5.0,2.0,9.0,6.0,6.0,DABEAHCFGGFAGFHHFCFFHDFHDCGFFGDEGDHAAA,True +704,4.0,1.0,0.0,2.0,2.0,1.0,3.0,0.0,BGGAAGEADEFDA,True +705,18.0,19.0,12.0,21.0,25.0,19.0,18.0,24.0,FDAHBFHDCHACHAEAEEBDDDDDGFHHFEHDDBDAAAFHAGGAGDABCHGCEGCFDBGCBEFHFDHFHHEGCFABHEBHCAHBBHEAEEAEGAEDEBGFCDHEEHGEFGEFBDFEGFGHFDHFBHDBGDACBAFBDFEHEECBEGBDGAEGEHBC,False +706,17.0,12.0,10.0,18.0,25.0,13.0,22.0,21.0,AGEHCDCDAEDAEBAGGHGGHDCHEHEFCEABEGBEBHAGABHABFFGGFGAFGDBGAEDAGFAHEEBFFAEFBEHCEFDEFEHDCHDCHDGAEGAHHFHEBEEGABGDHGDHBDHDHGCEDCHFCEEDDEHDGAGGE,False +707,18.0,24.0,22.0,26.0,29.0,18.0,27.0,19.0,HFHHGDEGFHCDHCEGFEGBDCEDEEFFBFCAEBBGABHADAAGABFDCGCBHABAGHDEDEEHBAHDAGDBGCBDHHDBEEGCFGCHCFHBFDEGDHDFHAEDAGDFGEFCEGGEBGCCCCECGECGCHACEGCEFCDFBDFBGBEABECBEBBGAHGDHDDAABGGBEGAEBEDFDDFEDE,False +708,20.0,10.0,10.0,16.0,13.0,13.0,19.0,23.0,FFHDFHCCACGGGHEEHDGGAGEAGHAEBAHDGHGGHBGAGFCBDCDDADDCEHADDDHBAHBAHBGGAFAAGAGGBGFHAHHDHGEHEFHCFHCBACEDBDDFCEFAHFAHEAEFHFABEDHE,False +709,5.0,8.0,2.0,9.0,7.0,8.0,16.0,8.0,CGDAGDFHDGABHDEFFBFFBEDGGAGGCEGHHGADEFDEDHEDGFBGHGGHGGBGBBAHEFB,False +710,2.0,0.0,1.0,2.0,0.0,3.0,1.0,3.0,FGHDDHAFHAFC,True +711,11.0,11.0,7.0,14.0,11.0,15.0,19.0,23.0,DHDDADGHBGFBGHHGDGAHHHGHHGBCEDCHDHDECGGFDDAGBHGBGDAHBFFBFFCHFCFFHBFHEHHGAFGAHGHDCDDAGEHGEHBFHEGBAGFAEFCEABEAEEF,False +712,22.0,16.0,19.0,9.0,22.0,12.0,19.0,16.0,HDGBAGAAGFEEFADBADHGCGCDBCABEACGHGEABEAFGHFEHFGHFGHCGEFGEFHHACDAHFCGECEABEAEEBBABHEFEAGEDGBCEHDEADCBDABCHCCHBCGAGHACEACHFCEEBAEBAGBGFCC,False +713,10.0,16.0,20.0,25.0,19.0,11.0,23.0,14.0,FDCDDBFDGCEFFEBBEBBFDBHCFAAHGDHDBFFGFDACDAEDGEGGDCADCDDGEDGEGCEGDADCGDCBBHEBDECEHCEHGBHACEGGDCGHHGHDGCGGCGCDHHDECCEBEEDABBAGBGEAGEFDHFBHCC,False +714,7.0,8.0,11.0,9.0,14.0,8.0,8.0,14.0,AADAFBHGCCGCDHHFHBCHDCHDEHEEBFBAFHDGHDHHEAFEFCEGDHBEHCCFCHBBEDEEAFEAECGECGEGDBG,False +715,4.0,5.0,2.0,4.0,4.0,2.0,5.0,7.0,BEEHHBHHCDHCGEBGDBDHEFHFAAGAAGBDG,False +716,2.0,4.0,4.0,2.0,5.0,4.0,1.0,3.0,GBACBHFFEFFDHBDHEAEECECCB,True +717,15.0,12.0,19.0,9.0,14.0,21.0,18.0,23.0,DBHAHHEFBFAGHAGHAEHFEAAGCGHBFHBAHDCHCCDAGGHGFDAFEEEGECHCCEBGDAGCAGHGFACDHBDGBAFCFFCDFCFFCEGCBGFBCHBHAGHFHCBHAFHCFGCEGCEHFEBEEFFHDFH,False +718,21.0,29.0,17.0,17.0,19.0,12.0,14.0,21.0,BHBBDDFDBFDBDHADHBCABAHFADGBECCFDBADGEHHBBEGHEDHCHEBHBHHBEEBCABFBBFBFDAFABDGCEGCEGBEACEBBBBCDCHGEDEEGGHGAFGABGABAAHAHHAHGAHGEHCDCFDCFEEDEBHCCCACAAFABE,False +719,15.0,18.0,17.0,14.0,22.0,18.0,20.0,22.0,GGECFCHFHBEHBEDBEFBEHBDHBGAGFAHFAFECFDFHGFBGDEHECDGCAEFHEFBDGHDGDBGBBGBHGCCGCCGCHHEBBBBEEAHHBFEACADDACGCFEHFEHFAGAHGEHFAAFCHDCEGCEFDEGBHGDHEECAADA,False +720,4.0,4.0,3.0,2.0,1.0,3.0,4.0,4.0,BFBBFHBCHAHDAGEAFCADCGGGH,False +721,22.0,14.0,33.0,22.0,22.0,16.0,25.0,18.0,EGACBDEEDAADHAHBABBAEGAEGBHCBADGFBCFBAACFEEFEDHBDCGECHHHAGEAFECFEGFGAFGHCGAFGEFECFGCABEEGGDAGDCCHCCHGDEGBEDBACAHDACCCBHCAHCHDGHAECDDCDHCFCDAHHCECGECGDCGFGECCCFCCDDGDDGDFGBF,False +722,15.0,12.0,9.0,7.0,14.0,11.0,9.0,13.0,HFDHFEHEGDBCFBCAAHFAEFGGDBADEAFEAHEAHFBGFHEAGEDGBBABHGEHGECCABCEHDBADCFEEFAHFGHEAHACCABCBB,False +723,25.0,27.0,19.0,19.0,29.0,24.0,29.0,27.0,CHBDGEDBEGCHBAGECBACBGCEACAGCAGEFHHHGHAGAEDHGCGBBACHDGDAGDAGBFFBGFBDFEAFBABACDEFFEAHHAEHGHHBFABFACHHHEBGBBEABEAHEDGEDBFDCHDBGGEHHEGHFCHFHAFDAFEGGHGECDFGGBGCFEAGECBECBECFEAFEBFEHFEHBDDAEDADDFCBFEBFGHG,False +724,7.0,6.0,4.0,4.0,2.0,2.0,7.0,4.0,BACDABGAGDBGHFGHFCHAEGADGBEGBAADCBHC,False +725,13.0,14.0,14.0,9.0,9.0,11.0,7.0,5.0,ADEDDFDEGBCACCABCADGAFGFGAEGAGBAFCFFHBBHCBDBFEGAEDBDFHCEECEAFBAFHCFCCDBCABCABHBBEC,False +726,6.0,1.0,2.0,1.0,0.0,2.0,3.0,0.0,ADAAGACFACFBGGA,True +727,22.0,23.0,26.0,27.0,23.0,28.0,17.0,22.0,ECCBCCADCDDGGAHBAHFHCGHEGHCAHGHHGBEFCAFBAFHDFAFCCBACDGCBGHGEAGCDECFEBEEDFDFBHGBAGBADFEDAHDACDGEFEEHGEHFAHFAEBDBBEBFEDAEDHDDCFDGDABEGDFHBCBFDFFACFAFHEFHABDCCEABEFFHCFBFFBFCBDCBDCEDGDAHDCHCE,False +728,0.0,0.0,3.0,1.0,3.0,4.0,2.0,2.0,CEHCFCGFHDFEGFE,True +729,17.0,19.0,22.0,26.0,19.0,16.0,18.0,23.0,GFHGAGFACDAEAGFDCBCCBCBBGBDGEGCEHDDADHEDBADHDEFBEDBDGBCGAHHAEAAEBDGDGGDGABBECDEFDEFHCAHBDHBHGGDFFEFDCCDACBAHEABCHEEFCEFHGFHDEBGEBHHHHCFHEAHBAHCDDDDCGFCHFCHCCFCD,False +730,10.0,12.0,10.0,12.0,5.0,3.0,7.0,9.0,GGBHAHCBEBDABDCEDEGDCGDAFAHGAHDADDACHACGECADHABCCGCBBCBBHHBFDEHDBDFB,False +731,8.0,9.0,15.0,9.0,17.0,19.0,15.0,6.0,BHGBCGBCDBCFBCBACFAFEGFECFEGFGCEGCGADEFECHEDEEFFEFFGFFGDFCEGCACBAFADCGEEGDBADFAHHDGHGFEEDCEHFFBGEC,True +732,15.0,25.0,16.0,23.0,8.0,23.0,16.0,19.0,CCGCCHDFHDFABAHDHGDBFDHDDBBDHBGHGFDDFGGHEHABDFCHFAFCACBBDDBDFBDABHABGBEDBEDAFCFBCFGEBBHCBABGABGHBGHFGCFGCFGEBEFADCHFHFFCDDCHAEHBDGADAADGFCFFBFEBH,False +733,26.0,12.0,25.0,16.0,6.0,12.0,11.0,16.0,DDEFFEHBCBCAGCHGBHAAHCAHAHHBHHGGHCFDCADCADABFCCGAFDAGHCCCACFADFADAHBGBCFFDBCHAFAAEDEBAHBAEFAFBADBDDADCCCCCCCACCGCDGADGAEAHGH,True +734,24.0,26.0,16.0,18.0,21.0,14.0,24.0,22.0,HGDGADCHDBBAEBDEBDEBEEDECFBCAGCBCHGDBGEBDEBEEBDGBGHHFCDDHGDAGHADEBDAAHBGBAHAEEGEBGEBAACFHCFACFHFAHFAHFDHCBEAHEHBCHAHAEDGFBGDBGFBHBEGDGGACEACACBACFAGGEGBFBHAGHAGCFGHF,False +735,22.0,22.0,29.0,19.0,27.0,26.0,31.0,18.0,FACFCCFCAHCGBBDADAGDFEEFAEFAHADEGDACBFCBFBHGCGGCFFBGFGFBBHHBCAADGCDECGGCGGCAGCEGEGGDDGAGHAGHFCFCEGDGCFFBDEBDFBFEEEHEHBEAEEAEEAGEFDEGDBBEHGAGFDGEDHBCHGAAAAABCECCECCHCCDFHBFCEGEDGFBFCBFHBFHDHHCGEB,False +736,3.0,2.0,3.0,3.0,1.0,1.0,2.0,0.0,DCBDCBGCAGADEAF,True +737,25.0,20.0,13.0,20.0,9.0,15.0,15.0,17.0,BBCBGDDHBCECEDCBDHGDAGDAEAACDBCDAAHFAEFDCFAFBAGAGBABHABDABFAFFDDHHHHBFHDFGGHDCFGGHHGAAEAABCAGCBGCEGABCADEBBEFBDFHGFHDFHCFHAADEBDGADABH,False +738,15.0,21.0,15.0,20.0,23.0,14.0,16.0,14.0,HBDCBCCDFDDBDABDABDFDHHBEGEFGEFGECGECGECABBEGFEGFGFBABDGBHGBHCAEBBEBEDDDBHDAFCACCEBHGGDEDAEACFBFFBGFGEEHHEHEAHADFCDCAFCDEBDCDEGEHGAHAHEABE,False +739,6.0,4.0,7.0,3.0,11.0,9.0,13.0,4.0,CEEGFEGFDGBBEFGGDEDHCCEAFEAFBAFGACCAGAFEBFEGFGCHGEHGECGHG,True +740,18.0,18.0,17.0,21.0,22.0,23.0,24.0,19.0,CHFCHDGHDGBDCFEEFEDGHDAHDAECAFGFFHFCDEGAHBDBEDHEGAEGAEFBEHAEHABBAHFGECAHBFCDFDEEDEGDACBFHDFBGFGFEEFAEFCFBCHBDFAGGAGGAGBAGBEGEGDDGCDBBDBGEFGDDGHBBECHFCHCCFAGHCFCAH,False +741,9.0,8.0,14.0,9.0,12.0,8.0,10.0,8.0,HHAGBAGCACBHFBHFDEADGBFGCDABDCEDCEFABGECCEBCDGEEEEECECCFACHAEFGGFCGFDGDACDHHBH,False +742,12.0,15.0,13.0,8.0,14.0,16.0,4.0,12.0,AFFFBFFBCEAFAAEBHDAEAHBCHFCHBDHBFHBDEBAHGFHFBEGCFHCEAFEAHABDBEDEEFECHECGECFHCFCCDCCGBDABDBBEFA,False +743,10.0,6.0,7.0,8.0,13.0,10.0,9.0,5.0,AFAAEBGEBEECEEDFCGGHDGDFCFGHFBHEHDDAADEDDECBEFBECHCGAAFFAFEAGEAGFBGC,False +744,4.0,4.0,4.0,5.0,4.0,3.0,5.0,8.0,FHDHHGAHBHDDHGDAFEACEACEGGFHBCHBCGEDB,False +745,5.0,2.0,6.0,1.0,2.0,4.0,4.0,5.0,CHHCFFGFGAAGAHGCHABEACEHCBFCD,True +746,6.0,7.0,9.0,8.0,5.0,5.0,6.0,0.0,GDGGFGCEDBEDACDCCFACFCDABDACAACBEBBCFBFEEGBDGD,False +747,23.0,21.0,27.0,20.0,27.0,21.0,28.0,26.0,DEADBCCGHHGHDBADBADBEEBFEBEBGGCAEDAHDFDGHEAHEAGEDGEFGBAGHFHECBCAEEBEGFFFHHHDHHGACGEEDCADBAFBHGBAFBDFCDCBGHFHAFCCDCGACGAFGCEGCHBBDGCHFDAFGGGBHGBHAAHCAGEDCCGCCHBCHFFHEFCEFAAGACGCEECECHEBHEGEDFEDF,False +748,3.0,5.0,1.0,5.0,3.0,2.0,3.0,3.0,DBGHEAHDADDADECFEGBGHBFBB,False +749,11.0,7.0,13.0,10.0,10.0,9.0,18.0,6.0,AGEGGFDHECGGCGBCGECBCCEFCADCGHCGEGBEBDECGGCAFHDDHGDAGDAEAEFDGADGAFCCFBAFEFDGFAGBAHBH,False +750,19.0,21.0,8.0,26.0,26.0,23.0,18.0,20.0,FEHFHBCHBCHAAHDGEABEDCECBDDAFFAFDGDHCDEGDFADCHDEDEEGHAGDFGCFGDFAEBDFBAGHAEEAEAAFAFBAFBEBBDDBDHEFHEHDEBDEFEBBAAEAEGBEDFHDHGBEGEFBHCHFBHEGGEFGEFGDFHFHGDBGDBFDBHDGA,False +751,10.0,15.0,9.0,6.0,11.0,12.0,12.0,15.0,GDEEDHHBBFGBHHBEHFHFBDCEGGEGCBCCAFCEFBECHEHEBHBAABFABFABFGFEGAEBDHCGHAGHAFCACGAHDHFDHGBBGF,False +752,16.0,16.0,21.0,19.0,22.0,24.0,24.0,17.0,HHEEFGDFCDFCDFGHFHABEGECBCGBCGBFGDFBCBAFFGCAGCAGBAGHGDHDDHGDHGEHAECADCEFFAFFDEGBAGBCEBAHFACCDCBGEHDEGAEFCEDBEHFHAEDBGAGFECFGGAGGEFHDHECHECFECFCBDCGABDBHDFEFFED,False +753,5.0,5.0,9.0,7.0,8.0,5.0,5.0,7.0,DHCDCBFEBACFGCHGCHGEDGDDEDHAGEACFACEAHEFCCFBDHBHBEE,False +754,1.0,1.0,2.0,5.0,0.0,0.0,2.0,1.0,GGBCDDCDDADH,True +755,3.0,4.0,2.0,11.0,7.0,7.0,7.0,3.0,DDGGDGFFEFFGGDECDEDFEDFBBHBGFBHDAGCADHDDEAEE,True +756,13.0,13.0,9.0,10.0,17.0,10.0,13.0,12.0,CGAEDBDFGGHCGBCFAEEAGFBFFBFFBEGEEBEEHEECDEGACGEHAFGADHABHAHHCGHFGHEHEAHGDDCAHFAEBAEDCBBCBBGBDEDDA,False +757,8.0,8.0,4.0,5.0,4.0,3.0,10.0,2.0,BDEBGHGGFDGFDAFCGGCEBBAACEDCADHABGGBGBAABGAE,True +758,26.0,19.0,23.0,17.0,12.0,22.0,20.0,22.0,DDGDEFCHCHHDHHCHGGHDBAFBFGBFEBCAFCAFHFFDCCDCEACACBFEGGHGGDFGDHCBGAFCAFEDBEAEEBDFGDAGBHBHHADGCDFCAHCHFCGFCGHCBHABDABAACHAFAAHCBHBFABFAGFDBFHBEECGAGAAGFAEDABACCEGH,False +759,4.0,1.0,4.0,4.0,4.0,6.0,8.0,4.0,GDFGAFGDGCFGCFCAHAHDFHEEHEEGDGAFGCB,False +760,2.0,2.0,0.0,1.0,4.0,1.0,5.0,1.0,ABEDBHAEGFGGEGGE,True +761,21.0,26.0,28.0,30.0,24.0,24.0,21.0,23.0,FDCHDHHDFHCCGFFAFAAGABBDGBCGBHGEHFHFBCEACEHEHBEABDBBABAGBFFBHDEEDBGFCGFCGFBBCBBDBGGGCDECDCFECFEABGCDAEHEHBEDDADFADGAEEAEFDCFHCFBCHBCHAEDDEBGEDGFHEDCBACDGFFCEGCDACABEGCDGHEECFCFHDFBDHADHADHACGDCDDHH,False +762,24.0,12.0,13.0,17.0,17.0,14.0,9.0,11.0,CEAAEBDEFDBCCBABBACBDBDDADGCGHAEHAEHBEFAEFAFCACHBHFEHADHFEFAGFGCDADDACDEDGEBGECAEBFEBEADGACFAHAACAAEADDFFGAFGCDHDHEFH,False +763,6.0,8.0,13.0,10.0,5.0,9.0,19.0,14.0,HGDFBDFGCHDCBGCEGCEGHGHHGACGFCAEEHBBGDHGCCGFAGHADHBCGDDBEAFDHFBHFDGCAGCGFFGHBGHCGHCD,False +764,27.0,23.0,30.0,22.0,19.0,28.0,33.0,17.0,AACCCCCCFBCDCCGCFBEFDGGDCGFCFFCAECBGBFCBGEHDEFGHFGHACHGFAGEAFFFCHFDGCHGDGCFGCFGCAGDBFFBECEGCGGBGHBDAEDABFABFDBDDBDAADGHHFBAECEBHAHHEFADFADFACAACGECEEAGEABADBDHEGEDGEDBFAHGAHGAGCDFBAGBGFFDCHBHEACGGBGB,False +765,18.0,15.0,16.0,11.0,14.0,19.0,16.0,15.0,CEFGFFADDDDCFAFGAFEEEAEHBEHCECAEBAECABHACHFCFGBGGBDABCFFFGFHGHGDEDABBABBAHFACGDFGDFGCBEEDFHACHGCHGBHFEGFAACECDGCHGBHCBHBAHAF,False +766,2.0,0.0,3.0,2.0,3.0,1.0,2.0,7.0,HHEHHCCHDGHDFCEHAEGA,True +767,17.0,7.0,6.0,11.0,18.0,9.0,7.0,8.0,HEEBEFBEBEEGHEFCEACFABFHBGEAEAACAADAADADDAFABDAGDEDAGDEDHCHFABEGDEFDEAEECEGHHHFGFAC,False +768,7.0,8.0,17.0,12.0,13.0,9.0,9.0,18.0,EBDDBCDHEEEGCEFDAFDABCBBHFGHGGHDCHFEHFAHAEHCFHCAHEHBEGECHEGDECCCCDCBHCGHCBFGECACHAFHDCDDHFDHG,False +769,20.0,21.0,9.0,15.0,21.0,8.0,21.0,20.0,HEDAEDGBFGHEDHEDHEBCGAEAAFAABHDHAEHGGGBEFDFFAAEAEHCHBCHACDBFGBGABHBBEBBAHBHHDABDAGDHEFEGBGGDCGEBGCHECHECHGBEDBEDBAAFGADBAGAHGBGDCGEEGEH,False +770,21.0,9.0,20.0,15.0,18.0,14.0,11.0,20.0,AGHAHEGHACBCDEHDEHEECGABBADBFCHFEABCBDEAGEAFEAFECFDCHDBDFADCAGCADCHDEADAAHFABFEDCEGCHFHHCEACGDDGHFGAFGAHHHECAEHDHHABCEFCHFCGCCEF,False +771,4.0,4.0,4.0,6.0,5.0,8.0,8.0,13.0,HGCHGCEBAEDFEDHAHHGEHDDBGDEGBHGFHGFCFFCHADFFBHGAHFHH,True +772,4.0,7.0,15.0,14.0,7.0,5.0,7.0,12.0,FCECCEHCHDDHEFHDDAEHECCGDDBDDBEDBFCGHHHBHHBCABCHBCDEDGCHFDACDFCDGCGGAGC,True +773,15.0,15.0,19.0,12.0,10.0,13.0,9.0,11.0,CDFCAAHAADAADBHCGEAHFBGCBCCEGCDCCDEAGHAGECHFHFFBFBHFBADCADEHBECBABBHFECAGCDDCFFFHDFHDFAEGAEGBCCBCEDGBBCB,False +774,17.0,15.0,18.0,13.0,14.0,14.0,9.0,11.0,BDADABGFCGHCGAGHAGFFDCCBAGFHDFHCFHCBACEACBAGBACBECFEBGABFBFFBHHBDEEDEAHEAGFDEFAFFBDHBECCCCDCEACEHCEAADDCBAEDDEH,False +775,12.0,10.0,12.0,10.0,14.0,18.0,9.0,17.0,FFDFGDFEBAEBHFHFFBFCBFCBACEGDDCHCHDGBEEAEHAEBACCCCCAHEAFFFFFHGBHDAADAHEFHGFHEDCAHHADHGFGCHGFEEHDEHBEGB,False +776,15.0,9.0,14.0,7.0,14.0,8.0,10.0,14.0,FGGCGFEGFEGEBBABCCDCHEHHCHGFDGAEHCEFCEGCAACEACADHABADBFDCEDAABEACDGCHHCHAFAGHEHBEFEAHBAHBEH,False +777,3.0,5.0,7.0,4.0,6.0,7.0,4.0,2.0,ACHDGDFECAEGAFGEBDFBCFCCFHCEECDBGFBEFB,False +778,13.0,16.0,17.0,23.0,18.0,12.0,11.0,15.0,HGEDGCCFHBDHDDECFEHAEBAEBHDCCDFCDCHGHFGHAABCAFCGHCGCEFFEBAEBABBEHBGHBFFDDGDAEDAEABBHBBHEDFEFCDCEDCEDHHCGDDDDDAGFEBBCDDADCAEEG,False +779,0.0,0.0,2.0,3.0,0.0,5.0,2.0,1.0,DCFGFFCDFHDFG,True +780,4.0,14.0,9.0,15.0,13.0,16.0,18.0,13.0,GFHBCDDGGEFBDFGDFEDHCBBGEFEAFEHBDHGFFECCDHGHCGBBGBEDHDDEDEEDBCFHGDHGFHGFHGFGGFGBFGAFHCDCAECAEBBEDBGFBH,False +781,14.0,11.0,9.0,17.0,16.0,19.0,16.0,13.0,AHAEEAEBDCFCAFEACDFGBGHHFBHDBFDCHDHHEHFDGFAFEABDGEEEFHFABFCGFGGBCHBEGBHACEADGACGCFGBFGAFDAGBAGFDHEDEEDEFDEFDGHDGDDF,False +782,17.0,30.0,15.0,20.0,20.0,24.0,22.0,25.0,GBEGHHGHFDDAEABGCBGDDCCHFEBFGBGDBGDBGCAAFGAFDEFGEFEFAEFACBGEBAEBHBBHBCHEHHEAHDDCBCFDADDHDGHFEHBHFBDBDHAFHFFHGGAFCFGCHEEHEDFAGBCHBFGBCGDCGBHBBCFBDBDEBFEFHHCBHGBEBAEBHEFAAFDAG,False +783,18.0,12.0,19.0,16.0,8.0,23.0,23.0,21.0,CAEAGEACHFBBCABCACFADGBFCCFGDFGFBGHEGHCCHABHGBHFBGEAGCCFDAFDCHBGHCGHDFEGEHGEHFDHBDFAHFAHCGGCGDBFAGFHHFHGFDDHGHFDAGBHFHEDDDDCCGCCGADFAFGAFAAF,False +784,26.0,24.0,29.0,15.0,21.0,16.0,22.0,14.0,GEEGAEGABFAFGEBBHCCCGGBHGBFDAADAAGAFGBEBBCCGCAAHAAHDBEEBGEDADDADDAECAECBEBHEFFADBCGECGCCDCGACBACFDCFHFDHGHBBHDBCECEGCBGEBCEFAECCCHFGECGCBACBFFBGFHCECAFBAHBHHAFDAGDECAG,False +785,1.0,0.0,2.0,2.0,2.0,6.0,1.0,1.0,FFFEFFEDFCDCGAH,True +786,20.0,28.0,18.0,25.0,30.0,17.0,20.0,19.0,ECEDCEBGECGBDDAGEBEEHHADHDECGEDEEFEADEAFEAGDBDFCEFBDHBHAGAAGCAGCHHCHDBDFFEECADBAGFCBBEBDEHHEBHFAHFBCEBFEGEHADBDHBDHCDBGDBHDCGBFEADEADHAEAGBBCBACEACFDCBDHBDGEGGEBGEFGBFCBGHFGFFAB,False +787,5.0,3.0,2.0,6.0,9.0,8.0,2.0,4.0,DAEDAECHGCHBEFFEFEDFEDADHEDAEFBFABFHFEG,True +788,5.0,9.0,7.0,1.0,4.0,3.0,1.0,5.0,EBABAACHBEHFACBBFBBEABCDECHGCHBCHFC,True +789,12.0,4.0,13.0,8.0,13.0,16.0,10.0,11.0,ADAAEBAEGDFGHFGEBGADFAFFAFFEFCECEEFEGFEDFCCECHHAFDCFGHEHBBFAGFGHACECGHCDCCHCCHDFHDGAAEH,False +790,6.0,10.0,8.0,9.0,9.0,8.0,9.0,13.0,CEAHHCFHCFHBEACFACDBGDBEHBGGCGGAFDHFCHFEHBABBHDHGDEAHGBEBEGBEDHEDGCDFHDF,False +791,8.0,14.0,12.0,15.0,11.0,8.0,8.0,8.0,EBHEBDCADCAGCABCGDEADEAEECBEDADFEHECHDBHGEGCFDCFBBBHBBDGHDFFDFFGBGHBACBFCHGCDCDDEBDA,False +792,10.0,22.0,18.0,14.0,21.0,20.0,16.0,23.0,DBGEHGFDGFECFHGFEGFBAECAHFHECBABHGFACEBDGBCGHCECAEGBBCDBEGEEGHEAAECGBFHBFHAFHCFBCDHCDHDBHEAEEBHHBCCBFHBCCBHCEDDEDDEFFHHFHFFHEFDAGBFEBHCBHDBFDGGG,False +793,23.0,21.0,27.0,21.0,31.0,27.0,29.0,18.0,AGFCEBGEFGHCGECBEFEGFCBFDBFHCCHCBEDDAGFBDCCDCCDEGHEGHAFHGGHDGDBADBAGEAEAGFFCDACFACFGCFGHFHEFHEDECBEBHFGDEGCEGDBAFCCFACEEBDDHCECDEADFGBBEABHACFAEFAEHAEHEGBFCAHGEFDEAAHACGDBEFBDBBCBCEHGEFGFGGFAGDAGEG,False +794,24.0,20.0,28.0,18.0,24.0,31.0,23.0,26.0,HHAHBAHDAHGAHECHECDEHEEGEFCECEFDEDDFCDFCHBBHBHFCGGEHCAHCDGAGADGCHGHFGEEGAEBABBAEFDGDHFFEGCBFBGHBGABDBCAGCEFEBFCFAAAGAGBABCAEAAFFBFFBEBDDFFCFFHFFECFHDFGCCACFAFHCFECECCFGHFGBAGBCDHHHCCHDCEDAEDGHFG,False +795,31.0,20.0,15.0,24.0,20.0,24.0,18.0,24.0,DDFDGFDGAGEBGEBGFHEDHBDBGHCFHBDCEACAGHADHGHFGBFHCDHDHEEHGGDGGEGDFGAEAEECGFCBFABFADAADAHGCFFHBFBAFDAFDBEBAAHAAHAAHAAFABCABEBEFDHDHEFHEDABHCDDDHBHCCGDHAECAEBEHAFBACEADFBFFEAFCAFC,False +796,6.0,5.0,4.0,8.0,8.0,11.0,14.0,10.0,AGGGDBHDBEDHHCHFAGFGEECFFAFFAEDAEFEGDBGHHFHDFGCGHAGHGGHGEBCEBDFGDF,False +797,13.0,13.0,14.0,16.0,20.0,20.0,14.0,14.0,FDCFDCDGCDGAFFFFHFBDGAEEFDHFGHGBFDAFHGFHGDEDDEADCHGBHGBACAHBECACHEEEEBBDFCEBBEBFEHAGCEBAEFCEFAGFAHFGHFGCFECADCGEADEHDEBDECHB,False +798,16.0,22.0,7.0,24.0,22.0,17.0,26.0,9.0,EFHFGCFGEDGFBGFBHACDACDAGBBGECEBBBDDADDADHGGGBGGBFEEDEFDEAGEAGEAFEDDBDGCDBBBGHGDHCDBDDEGEAFEADEABABBHFBFDBFDFEEFADGADECHBGEGFFGBBHEGGFDGAGAHGEE,False +799,20.0,13.0,23.0,31.0,20.0,22.0,27.0,27.0,ACCDDCDDCHDEGDBGEBHAHGDDDCDAHDGFAGHAEBFECFBCDECBAHEACGAEGFEFFGHADDGDDACEACECCFFFDFGHBHDBHDCFGCGACFCDHCBHEFDBDGCDCDEFDEFAGHAFHAHHCEGGDBGFEGHEHHAGFEBFGAHCBHCAHDADFGDEHDHHAGHFEHGEGGDGGBF,False +800,7.0,7.0,4.0,8.0,5.0,4.0,9.0,2.0,BFADCAGBDGDDGDDAEDEFBEABEBECGDGHAGHAGFGBABCGFC,True +801,27.0,24.0,11.0,26.0,22.0,20.0,24.0,21.0,FDEFHBBHDBDFECFEGGEGBBBFGBAGBGFBAEHFGHCAACHBBHBDHEABEFBAFGEDECDEGFGGHDGAGGAHCBHEEEFHEDHADFDHGEGFAAACDFDDFBDCEAHEBHEAAEFBDABAABHABDAGDADFAHFGHFGHCGDFGEBCDBDAGDBGHAHDADAGECDACDE,False +802,24.0,16.0,21.0,28.0,24.0,24.0,17.0,24.0,EHGDHECEADBDCGFCGDCFDEFDHFEEBHECAGBDHDDAAAAGEHGCCGBEGCEGEFDEBDAAGEFCAFABFBEAGEAFECCDDCDDHDHFDEFGAACEEEHGHHADHFHADHFCCAHGACGAHECBEBBDFBCFBHADDAGDCDFAHFAHFABFEBFECFHDBHDBHDGHFHFCDF,False +803,20.0,21.0,21.0,27.0,21.0,19.0,21.0,15.0,CHCDAADHHDHFEEFGGDBGABGCBCFAHFHFFGBDEBFEAFEHBEFDEFDAHCGGCDFCGCGECGEAGDBCEBGAADFADFCDAEDBDAHAEHAEGGEGAHGADFCHCCHBDBBGEADDADDBFDBCBBCBEGDDCEEAGDCGDFDEGBEBBFBAHCEHCFCFD,False +804,1.0,2.0,0.0,1.0,3.0,0.0,1.0,2.0,HBEHBEDEAG,True +805,17.0,17.0,12.0,11.0,12.0,11.0,11.0,14.0,CACCACHGBBBBABBDBGEGCAGFBEFAEBAECGBHHHHHHHFDEFGCGGBBBAFFAFFACAACGACDDEFEEDEADHAHCBHDGHABHEBGCFAHBEDDDFEDA,False +806,8.0,5.0,13.0,9.0,8.0,4.0,5.0,7.0,AABDACCACDACDBCBEEHEHCDHEDGEDADGFFCCBCGBEHCHHDGHECCFDCFAEGA,False +807,2.0,3.0,6.0,1.0,2.0,2.0,5.0,2.0,CCGFCGCAGEGGHBBHBDCFECA,True +808,8.0,11.0,13.0,11.0,20.0,5.0,10.0,7.0,EDGEBEBGEBGECCCADEEEBCEGEDBECBCCDAEDHECHAGHGCDDFDBFEBFEBEEGEFHAAGABGDFHDCHACBEDGECAHC,False +809,19.0,18.0,17.0,18.0,21.0,24.0,23.0,21.0,GGGGAGFDDEHDEHAEFAGHHHHCBECAGCEGEBGABGFBDCHDBHEHHGHFAHGCBGFDCFDCFBEFHHDAGFFGCEEDHGDCADAAHEEDEBHHFAFFABFACCBCABHGCGDBEDFEGFCGFBFBBCBBDFEGFECFAHDAEDAEAEEDCBGGFFFHA,False +810,20.0,16.0,11.0,12.0,13.0,19.0,22.0,18.0,AGFCHFDDFBEHGEHGBHGDCGFCHEGAGADFAGGAHAFBABBFBBGGAABAAEADEBDGCHHEBGCAEAHEGCAGFHDFHFEHAGDGFDBFBBFADCGDBGHFGHCCCGCDGBBAAFFAFHHFEHFEHEE,False +811,17.0,22.0,15.0,31.0,25.0,25.0,18.0,24.0,HAFEGGECCHDGGGHDGCDGDEAAEHGEFGBGGHGBEFEEBCHAEHCFHDFHDFGDGDBGDAFBFFBFHEECEDBEDHDBEDBFDBFABDEFCHAEFEDHCDAFDCBDABDABFCBCDHEHFCAFCDBEDACDEHFFHFFEEEBDEHEBHBHHAHGBHDHGDBCABDADDFDAFGAF,False +812,13.0,7.0,5.0,13.0,10.0,18.0,4.0,11.0,FGEADHABHAEHFCHFAAEEAFEAFDAFABEGGHFFBBDBHCAHADHBFADCCHEDFGDFDDBDFEDFEHFDAFDFFEHFC,True +813,30.0,25.0,17.0,27.0,18.0,16.0,23.0,20.0,DGAGBDGFDGFAAACAGCEFHDAHDBHCBACFACFGHFEFBHHBDHBAEDAHCEFDGCAADABGABDEGDGCAGCEGBABEABDFGDFADFABGBHGAFGDDGHDAHDCDDEDGECHEHGFBBFHBEBBCBDGGHHCEHBEGBCGADAADBHEFDEFHEAADCCHEDECAAABABB,False +814,24.0,14.0,14.0,18.0,16.0,18.0,16.0,21.0,ACBABDDGDGCCHAEHAEFDEFGHFGHFGDCGEBFDBGGBFACACFAGEHGBAFBAEAAEFHEGHCAEAADDHCABFHHEDHDHACHAGHACHGCHCHDDHABAAFADDBBABFHCFGCFEDDEDDHFEHFEGFBGEAFEB,False +815,13.0,9.0,13.0,16.0,13.0,6.0,10.0,11.0,EBHEDEGACDDCDGCDACHFCECCHGBHGBHCBEDAEDHFAFEAHEADAAEADDFFEGBDGEHHABGGHGCCADCDDCDHCABEFBEDBAG,False +816,3.0,7.0,5.0,5.0,0.0,0.0,5.0,2.0,DDCDBADBHGBGBBGCCCACBAGBDGH,True +817,5.0,5.0,2.0,2.0,3.0,8.0,12.0,6.0,HCHGCGFHGAEAFGHFGHFGFEADEHDFBGGGGGGFBFABABB,True +818,1.0,11.0,9.0,4.0,7.0,7.0,8.0,7.0,GABGHBHDBHCBECBFGHFGBCBBFEBECCEFCDFCGHCFCDHEFGEGBEBHDG,False +819,2.0,2.0,5.0,5.0,0.0,2.0,1.0,5.0,CDACFHHFAHDBHCCDCHDBGD,True +820,11.0,24.0,12.0,20.0,8.0,10.0,7.0,16.0,DDBDDECFEFFEBFBBABHAFHGGCCADEHHABDDDDCGHFABFABFHDCBDBGDBCDBFEHHCBHADHADBADCHDCBDHBEHBHABCGBEGBCDCGHBDAEFBBBH,False +821,9.0,5.0,8.0,7.0,7.0,2.0,8.0,6.0,DCDGGAGGCHGCHBBEEAGEGEFCEDADAADAAFCABCEHCBHBEHCAHDDG,False +822,4.0,6.0,4.0,6.0,8.0,10.0,6.0,8.0,DGEHGBHAFDDFEAHBFCBFCDFADFCDHGEHGBFCBHEHGEBEEHEFGFFA,False +823,11.0,21.0,15.0,29.0,14.0,28.0,25.0,13.0,GCBACBGFGGFADDGDDHCCBEGFEGBDBBDFFEFECFBCFBFFGFFGDDHHDFHEFDEDDAFAGFDEBEBBDDHDEHGCHFCGCAGCFGDGGHCFBBFBDCGGEGDEBAHFDEADEADFCDGABFDDFGDCGBFADABDGBHGHGFHFDHFEBCB,False +824,9.0,9.0,18.0,17.0,22.0,11.0,12.0,16.0,HDHHDBHCFHEEAEBDEDAEDBEDBHHAFFDDFCHGCHECDDCEEEFEDGADGCDCCHCAHCAHCEHGECGEGGHFDCCEECACBGCEGFGDEBAFFAGCGBEEEFDEFDBHBH,False +825,13.0,14.0,23.0,11.0,13.0,29.0,17.0,16.0,CFBCFDDFBDFBHFHGFAGEAFFBHFCCFCFACFACFDCAEBHFGGBAGDEEHBGFAGFHEDHGFEBFHHFGFDCFCBHEEGGCFGEFBCADHHDBFDBHDHACHCCGCEGAGGFFACCAECFHCGBCEFCEFCAB,False +826,5.0,8.0,5.0,6.0,10.0,4.0,3.0,7.0,DDEDAGAAGAHCDDBBHBGEEFHECEFHEBHEFHECEECBBCHBDFBA,False +827,20.0,17.0,26.0,28.0,18.0,27.0,26.0,26.0,ECFEGFEHFHHFABFABFEHABHAGDBHDBHDBGDGCDGHABHAFCEHDBHGCDCEFEEADECDAFBGFEGFBAAGDGDDEEDHDABDABFAGFDGDDADCBDAHGHHGHHFFFFFGCDEDGGCBCFEDGCCGCCDCEFFHHAHDBHAFCCFDGBCCHACHDEGGEGCCDCCHCBGFAAFEGFGCHHF,False +828,10.0,8.0,14.0,9.0,25.0,17.0,21.0,17.0,ECHGCHBCGEFDEFDECDEGBECBHBHHFFGGFGGHDGHACCAHHBDCFGAFGAGEEHEAHECEEHEEBEEGDECFEBFECFHFFGGGAEGHEGFCFBAGAHEEGDAAHFHCFGEEDFGDC,False +829,3.0,3.0,1.0,2.0,3.0,6.0,4.0,4.0,DHEHHDFHGGBAGAFEACEGFBFFBF,False +830,13.0,14.0,5.0,14.0,12.0,16.0,14.0,22.0,GDABFFCGFEHEGFFBHCBHEDHFGFBBFEDEHDHHGFHAEHAEHCEHABHADGEDGAFGHBCHAGHADHEFHFFGFGBAABAABDGBDCHDGBEAFHHDDBDHBFHDEG,False +831,30.0,21.0,25.0,25.0,16.0,20.0,17.0,32.0,ABDAGCAGBEEEEFEEFGBFGACGBHGBHCAACAACGCHGHADHACEECHDHACHFEGEAGDAHDAHDGBBHBFHGCHEHHAFGFFDDBGHHDHDEHABBACBHCADFDDHBDHBDCDCBDAHFFHDDBFHAGCDBFFEECCECCGHAHCAHBEHDACDAHDFCDAHDBBFFBAFCFFCAHAAGAC,False +832,25.0,27.0,23.0,20.0,26.0,20.0,20.0,27.0,AADBAGBCFACEEGDFBFFBFHCGDBHEFHCFBFBEEBHCCHCHBEBGABDAHDFHDHHFEHGECGFCBHDFHABBDDBDFHDGCGCCGCDGCHBHEEDEHDHBDEEHEGHBBHFBHFBGCEGEDAEGAECCEAAEACBAHDEBAEBFGACGAFAHDABAHDGCDEAHEAFECFGAACBACHAGBFGE,False +833,25.0,13.0,14.0,24.0,17.0,12.0,19.0,18.0,AEBDEBFCFGAEEHEAHBAHDCFDHFBFAGFAGAEGCCDCAAGAHEHHGAHEACFDEGDCFBAGGABGADGCDGFEBFEAAAGAAECBGDFCDBEDHEBCDDHDDHDGHDHHGCHGEBGHCAHDEEDCDDBADAAGABHDDF,False +834,15.0,10.0,18.0,19.0,15.0,14.0,14.0,17.0,GFDGHHGDHFHCFDBEBGADGACECCHHCHFAHCEHCHHDEHAEBADDGDBGDEEDECDFCAFEEFEDDHDCGAHBAGBDEADGHEFDFABCEBFGBCABCFGCFACGDHDEHACACCAFGF,False +835,20.0,10.0,18.0,14.0,16.0,28.0,23.0,12.0,CBFFGFCHEDBFHGFEGFEGFEDCEDAEHAGGGGFGGCCCDGCFGCFHAFBAFBDFCFFHAAGCEGAEGHEGDFAFFCDFADECHEAHGFGEHGEBDDBABFABABECHCFGCDDFFGFAACAAEDHGGHECDBAFCAFAF,False +836,30.0,20.0,19.0,16.0,19.0,13.0,25.0,21.0,GEHGEGBFGFCGFAGHHGFGGFDHAAHECBAGGAGHCGBCABFHBECAAHAFCEBCEACEADDADCGHBDHGFEDBCAEGAHGHCGHCGEBBHGDHEDHDFBEBBFADEAHEACBAEGFDCAABAABAABGAEACHBHDGADHAEBACHDGDAGCEDCEFCBF,False +837,11.0,6.0,11.0,21.0,12.0,11.0,14.0,20.0,CCGFFHDFDCHECHGCEGCGGDDGABGAEHDEHGGHGHDDHDABDHBHFFGEFHDAEDFEDFGFAHHHCFHAEDGEHCHFDADDGDBADAHDAHDCDCCBEHBEAE,False +838,2.0,11.0,5.0,5.0,5.0,11.0,2.0,7.0,HHAFDBFCBFHBFCBHCFEBHEBCFBFEBEHBDDDEDCABBFFGFFGH,True +839,10.0,18.0,12.0,15.0,22.0,22.0,14.0,20.0,GHGGHDGHEHCFHBHHGHGFDFFBHGBDFBCFBFEBAHAACAEBAFCEFHEABGAHCBCCADAEHFDHFEFFEHFEHCECGHFEBFGCFDBBDBDDCEDEEDEEFBFFGDBBEBGEAEHFDCEGEEDHGDHBF,False +840,6.0,5.0,3.0,4.0,8.0,4.0,5.0,6.0,HFAHFAGABEEHFEBBEABCGBGAFGAECDEDHEHHEDGDC,False +841,22.0,25.0,12.0,20.0,30.0,18.0,24.0,19.0,CFDABGGBGGDGGBGDBGDFEHGEHAEDEEDEEAEGABBABHABFEGAAAAFAAGHFEEEAHFBBFBDHEHAGHADHFDHEDHEDCFAHFEHGEHEEHCBBDBBGBGEBCEBFEHDCFAGFECABGDHEFFEBEACCHEGEGCAFDACECDGDBHEFCGFGGBBBDBDDA,False +842,26.0,32.0,18.0,28.0,33.0,16.0,26.0,21.0,BDFEACGAHGEHBEFBDDCDDEBGFBAHCGBBGCEDEHBAFGGFBDFDABCCBFCBHEBEAFGAEGFEGEDGAABBHBDCAAEAEEBEBGDGGDGHDHHCACBEGGDHADHGEFEBDEBDHBDHBEHBHDDCDFCDCGAGGEGGEGFECAEABEAHDAHCFFCDHAAHAACAABFEEEBDEBDGBDBCEEHDBGEBEAHF,False +843,17.0,15.0,21.0,18.0,10.0,19.0,19.0,11.0,GCGCCGCDBAAFCFFCGCCFCBGCBHBGADGFEEEBEDCFDCFBEFAEGDDDDDAGACDEFDBFGCFGEFDDHCGGGGGAFACHACHACGADGHHCHBFAAFDFFDABBEBFHBHEBHCAHBADGABFDC,False +844,28.0,20.0,25.0,32.0,29.0,10.0,34.0,16.0,GCBGCEAHBHHGHCGADBHDGAFGCFEEFDEAABAAFACGACHAGEEEEEBDBDDGEAEBGCFGAFGCGACGAGFEDAGDAGDBGDFEBECDGBDHBDBBDAEHADAAHGDCGDEBAHBEDCGBEGHEDHCCEDDEDCEGCDHDACAABADGEEFCEFGGAHGCCGCBECECBDHDCADAGDGGDGGDECHEBD,False +845,9.0,18.0,18.0,15.0,16.0,16.0,18.0,30.0,FHHFCHBCEBFEBFBHCGHEGFEDEHABHBHCEHCGGEGGCGGDGHDFHBFHAGACEDBBBBBFHEDHAHHBHEGHEHFDHEBHDDHCDCDHCACADBHDAAEGHFCCECCFHHBHGDHCDHFDGFBGFGGECAFBFCEG,False +846,25.0,21.0,20.0,25.0,14.0,20.0,19.0,27.0,DHHAHHGHBEBFFBHACHBCHFEAFHAGEAGEDFFDHACGDCGEBDDBGEAFAAGAAHAAFCFDCAEFBEGHGDCFAEDABDABHGBHGFHFDGDDGDDHFBABCADDACHBCHCGECACDBCGBCFHEHCCBBHHHFHFBHECEDHDAHDFDDFBBFDBEGACGACGADG,False +847,19.0,22.0,26.0,32.0,24.0,20.0,17.0,30.0,FFFFFBEBBCDDHBEHDHHFHCDHCDBCDAFBHDGHDECDEDGEDCBFEFEHAHHAEDBDGHDCHECDEFHHADHCHBCHCDDCHBBHBEECCDFEDFDBGDBDFBEBAEFAHAGFECCACDHCEHCGGCGGCAGABCAGAGCDBADGEDFEGAEGAEHACHCBHABDBEDEDDHADGGFBFFHEFHCAH,False +848,9.0,6.0,11.0,10.0,14.0,15.0,7.0,8.0,EBECBHGDFECFDGFDHFDCEAAGDEFDEFDFFHCAHGBDDHDHFEGEGBAFCEFCAFCACCACBAFHFEHEEFEGAEBC,False +849,4.0,12.0,3.0,4.0,4.0,6.0,9.0,4.0,BADBFBBDBCDAGGEGGAHFBHFECBBGGCGGBBGBDFFHFEHAEB,True +850,11.0,16.0,15.0,13.0,9.0,18.0,8.0,14.0,AHEFHEDHAHCBEFAEABEBBDHGAGCECCECCEDGADFFBFFBFFACACDFCDECHHFDFFHFFGFBAHBCDBGDBGHHGHFBDBHDBCCFHDACABDGBCBF,False +851,14.0,6.0,9.0,8.0,8.0,11.0,8.0,4.0,CADAAFAFGGBDGBECHEGAEGCEGHEAFCGCCAFCAFDBEHBAAAFAFFECEDADGACFBDFHDFBD,False +852,13.0,17.0,14.0,11.0,14.0,23.0,28.0,19.0,AHFBHFEDBHCBHGDHDDBEFGAFBEDCEDCGGCAGCHGCHGCDCEEGFBBFHCGHAGDCFEGABFCBECBAFBAFHHGHEBCFAEGGEGAFBFGGGDGBDBFAEEBGAGHAFHCFHFFAGFHGFHFFHGGBGGHDGFE,False +853,17.0,14.0,15.0,18.0,12.0,25.0,14.0,18.0,FEEDCEDAEDABFABGHCGEGBAFBAFADFDDFBDFGDGEEAEHDGHCFHCHGBHFHFACAEBGHHGHAGAAFFDCCDHCGGCFDCFHCGECADCFDBFEBFBDGHDCHCHDAFFFHFBBEAFADFHBFHFAB,False +854,4.0,8.0,7.0,9.0,7.0,13.0,4.0,5.0,HAHBAEBCEFDHFGBFDDFDDFCGFBBCBFCFFCAFEDFBCGCDGEHEEDFDHFEBA,False +855,8.0,9.0,7.0,8.0,14.0,11.0,8.0,11.0,FCGGHEGHCAHEGDGCDHEBHEGEEFAEFCEAAFAHDEHFEHBGFBFFBFEAHEADCBBCBBCEGDDHFDFBHEAD,False +856,15.0,19.0,19.0,21.0,20.0,23.0,9.0,21.0,EHCABCEDCEDCHDBADEFFEAHGADFHBFEBFEHFEGCHGBBFBDFDCFHCFCGHCDHEHADFFEFHCGHCBABEEBEFBCDBCEHDACDBBDCBACBAEBDDCADFAEFEEHDGHDEEFBFFDHGHFGAFAHFCGFHBHDADAHC,False +857,8.0,14.0,12.0,26.0,12.0,12.0,24.0,18.0,DDGDGFHGDEEDEHGEDDCHGCAGDGBBHHAHDBHDBGACHCCHFCHGGHDGHDBFABCHGHGFDCEAGEADEGDADEGHBCFBGFGDCGBFDFFDCBDCGDGBEGBFGEHHEFHDFGDAEDBDDB,False +858,3.0,12.0,7.0,10.0,7.0,11.0,5.0,6.0,EHBFDFFCEGCEBFAFCCFECFHDGCEHAEFDBFDBAHBGHBGEBCDFDDFBDBDGBHBBD,False +859,15.0,8.0,5.0,5.0,11.0,6.0,8.0,9.0,AFHEGGEGBEDBACAADADGGHGFEGCEHCDAFECBBABHHEHAECFHBAHGABDEBAEFAEFAHAA,False +860,24.0,23.0,16.0,29.0,25.0,13.0,28.0,31.0,ABDBGHHDBEAACAHBDDDDHHGAHBDHDAHCGHCAEGFECFECGHAGBBDBDDBDGBDBAEBACDAHDBGDBCEBGEDDEBDBBABGGGGGEHAEGGGDFHDAHAHFAFDCHDCHEFBEAGECHFCHGGEGGAGFDHADEGHAFHBGHEFBCAGCAEBHEDHEDEEDFEGFHCEHDHHFCHEAGECHA,False +861,19.0,16.0,16.0,18.0,22.0,19.0,15.0,18.0,HBDHADGAFFFCFDCFDHFAEEDEEABBABHHEAEDAHDEHCGFEECHECEFGHFDHFEEGCBDFDGHDGHDCBDCAECAHBACGEFBFFAFBAFBEDHDAHBBDGEGCEGBGDFGAFGAHCHGFECAEGABAHBACBECECD,False +862,23.0,28.0,34.0,23.0,21.0,19.0,19.0,23.0,AADEFDECBCFBFEGCHHCBCAHCAEDAEDFGBAHBGBBGEDGEFBAFBABEABFAHFAHADGBHAAHAAHCFCAECBEHBACDDCDCHDHHDAHDAHCFBCDHCBBGDEDEHFBCCCCCDGEDEEBCBHCDEBEHBCGCDECGCCGBCGBCFAGGACBHBFCAGCFBDHBFHFECFGHEGCEFDDFGDG,False +863,11.0,5.0,11.0,10.0,13.0,17.0,9.0,9.0,HGFAGHEGFFAEFGCHCCHCFACEAFEAFBFFBEEDDDGGDFEBHDFEDFEFCEHCDAAFBAFHCFECHEDDABDAGCCGAHGEF,False +864,8.0,4.0,8.0,5.0,6.0,11.0,2.0,13.0,CGDDADAFHFEHACHFFHAFHAGABEFBHHCHFCFBEHCEHDEFDCFEFHCAHCAHB,True +865,6.0,7.0,13.0,8.0,5.0,5.0,10.0,8.0,EBBEADDABHGBFBHDAHDFCCCCCGDCGACEFCEGCGGCDHHBGHCGCGBFDDFEAHCAHG,False +866,13.0,18.0,13.0,24.0,13.0,21.0,16.0,22.0,CECHEHGAHDBHAACGDDGDDGBGFBACBAFGCFGEBHHBHBBFBBFGDFEBHDBAEEAGEHFEDGEDFFHFADDADFHCHEADCFDBEDCDDFFBFFHFGEFGHCDFBHADHFDHFHCGCAGDACEBDHBDGDHGCHBH,False +867,3.0,4.0,1.0,1.0,0.0,0.0,2.0,1.0,BGHBGBAABACD,True +868,12.0,15.0,8.0,11.0,24.0,11.0,16.0,16.0,GBGAFGAHEABDAHEEHEGHFBEGHCHHCBDFECAADDGHFHFGEAGEBCDGEDBEFEEFGDGGAHGDHEEHBEHGEAGECGEAHECHBBEFBHBBDBBDCBFEFEEFECAAD,False +869,14.0,6.0,19.0,11.0,20.0,15.0,11.0,18.0,AFHAEHAEHGFHACHADFFGGFEGFEGDEDBAFBDECHHGHCCDBCFECHCHFBEDEECHACDGFDCHCEHFHCFACEACEACBCGBGEADECEEGFEHFACEDHEDHAGHFCA,False +870,7.0,10.0,10.0,16.0,6.0,4.0,11.0,16.0,HCBDCBHCBACDCCDHFHAGHCCDECGEDGDAFHGHGBDDFADHGDHBDHBGHFHEAABGBDHEDHEHHEGDDGADGCBB,False +871,6.0,1.0,1.0,3.0,2.0,4.0,9.0,6.0,AHCGEDGAHEAHAFGAGGBHGAHGFGDFGFHD,True +872,3.0,5.0,3.0,3.0,6.0,1.0,1.0,2.0,BBBDCBEGHEFHDBADAECAECEE,True +873,2.0,1.0,1.0,2.0,5.0,1.0,2.0,3.0,HEGAEHAEBCFDEHDEG,True +874,7.0,21.0,14.0,14.0,9.0,12.0,13.0,10.0,FDBFBBDBADBHBAGDHHCGEFDEBGEGGFGBCGEADAGGADHBDFCDECGBCEDFHFGHFEAFGHEDCEDCBFCBCCBHBBHBBDCBFGBCBHDBCAFC,False +875,6.0,6.0,10.0,12.0,5.0,8.0,13.0,6.0,GCGGCGGHBFDDADDBDFBDGCFGAEGAFBBCBHHFDHADHAGCDGEDEFGGCECCHDCEACGDFF,False +876,19.0,14.0,14.0,17.0,5.0,8.0,26.0,9.0,ADBACAGCHGCFGHDADABGEDABDABAFGCFDCADGGGGGGGGGBGGBACCHHAAGAADAGDAGDCGDBFFBCFBEBCEBGBBHEGDDCCCBHHAFGDGADGDDAFCGHHE,True +877,11.0,23.0,26.0,15.0,25.0,13.0,27.0,20.0,DHHEHGFGGCEHCGDGEDHCDHBFEDFEAFHBDGFCBHCEECEECBHCACGACACHGBHGBGGECGBDHCFEEEHCGHCGHCEBEFBGABCDDEGGEGGEGFEDBEBBGBCGBHABGEDCABCFECAHHBBCBDCAGBDGBAGCAHFHEBCEGCDFFDEF,False +878,10.0,21.0,12.0,20.0,16.0,27.0,18.0,16.0,EGCEHFAFAEBBGACGEEDEBDEFDBBDCBDEDFFAFGHBDFBHBGHBEBEGDDGDGBHGBHBFFGDFCFGCFAEGHEDEEDEAFFFFFFCHGGDGAFGAFHDBHEBCAGHBFDFFBHFCHFCHCCDCFDHBDGBDBHFA,False +879,13.0,7.0,15.0,3.0,11.0,11.0,9.0,9.0,CHBCFBFGEFEHCCAFAAFCEECBBHEEGEFBEABAADGAGGFGFCGACEHCHCFECADCACCACFAHFHDGHGAHEB,False +880,18.0,17.0,11.0,7.0,12.0,11.0,12.0,19.0,GACGHHGCCDAEAEBAFGHFGHEHABHBDHGCHGCHBABEEBECDDBABBHFHGCBGCBFAAGDAGHHHCAFCABAABAABHAFDAFBGDCHFEBEEHEFHEFBFHE,False +881,15.0,14.0,12.0,18.0,16.0,16.0,10.0,24.0,EFDEFDHBEHAEFFBHEBGEFABHGEHDFHAFEBCDGDAFDAHAACDACDGCEHDBBBBHDHEAEFAHGDFDABHABHAEHFEHFHHFHBFHAFHAEDCGBGGDDHDEHCBCCHCEFDGGHCDCC,False +882,1.0,3.0,4.0,5.0,7.0,5.0,2.0,5.0,HDHBCGDFACFECFEFBDFDGHEEHEBHEDCE,True +883,10.0,19.0,13.0,15.0,16.0,14.0,11.0,10.0,FDEBDAHCBEFHFHGGHGEBGCHCEECDACEFBAFHCBCEBAGBFGCEGBEHDDHBDHCDAFDEBDFBDEADBADBAECAGDABCGDCFBGFBDFBEFBFGBEHEECF,False +884,4.0,20.0,14.0,12.0,17.0,18.0,12.0,16.0,DHCFHCBHGFHFEDFEDBCDBFHHGCDFADCGHFBDCBDHAGEFBEHBEDCEGCABFHBHCCCCBHCGGFGFFBFBBEGFEBBBCGEGHHHFDAFDEFBEFHEGDEBEEBEEB,False +885,4.0,5.0,7.0,5.0,3.0,5.0,11.0,4.0,GBBEAFCABHGBGEFGDDCBDCFGCAGCDGCGHEGHFCHFGAGD,False +886,4.0,2.0,5.0,6.0,4.0,7.0,8.0,6.0,DEGFEGHBGCGHBGHDFAFFAFDADGCHECDECFFCHADHGG,False +887,7.0,10.0,2.0,12.0,7.0,8.0,10.0,7.0,HDGHAEDCDDBGDBAEBGCBDAEGFGFBGFBDDBFHBEHADFGDFHHFHEDGADGAFEAGEBB,False +888,22.0,21.0,26.0,15.0,24.0,25.0,19.0,23.0,HFHEFEAADAGDBCEBGEBEFHEGHAGEDGADFEBFCBFBBFCEHADFEHGHHFDFCHFCHDBGDHAAHFCFAEBAEGCEGCFFAHHGHHFHHCHCBABGDHHDFABGCFACFECDEAGEAGFBCFGCEGCBBBEBAGHGGCBAFACFDCDDCFCAHCACCBEEBEEBEADCCEF,False +889,14.0,18.0,14.0,7.0,16.0,10.0,10.0,16.0,FHAHHEDDECCCHBCBBFBFCBACDAGHAGHBFHBCHBEGEEGBBGBBGEAEAHHBEFFEAFEDHECEEGABGBDGCABEABAFCHCAACGBHHAHCDHFECFED,False +890,18.0,20.0,25.0,21.0,23.0,27.0,22.0,23.0,ECFEGEBFABFABCDBFHBHABHBDHGFGBFGECGCFHADHDEACCBHFEGFACHECHFBACCCBEBBDFDAEAABDAECCCFCFFCFFCEGCHBEGDEDFBDEGHFCHFCFDCFEGGEGDDGHDHHCGHFDFBDHGHHAAHAEHFGAFGAEADEFCEFBEGBGGHDAEDCEHCDGBDG,False +891,21.0,17.0,16.0,20.0,21.0,17.0,22.0,30.0,GEDGFABBHBBHFAGAEEAEAAECAEHHHBDDCABHGGHGCBAAFABFBFCGEBFEGEHHEHHDDHFGEEHDGHCAHFADBADCCGACHDGHAGHAFHAFBECBEDHGCHGAHGBDCEDCDBFDEGHGADGDHGFHCDGDFHBHHBHAECFECFEGFHFEDCED,False +892,2.0,4.0,1.0,8.0,1.0,2.0,5.0,5.0,HHHHBDABDGBDFFDCAHGGGBDGDDED,True +893,15.0,5.0,9.0,8.0,9.0,2.0,15.0,5.0,GGEGEEDAFGECACCAGFGEEDECDBAEGADGABAACCACCAHGAHADHGDGGHGBACBHBDEGAAGD,True +894,15.0,20.0,23.0,20.0,17.0,18.0,26.0,16.0,FGDFCFCCGBFEBEEDACGECGHCFFEDBBCHBFHBDAFHBGCFCCFAGHDGDGGBFEEGCEGAFGAEAFEDFEDBBDHBHGGGGCFDCEHBEHGCAAAAAGHCHHCHBGDDCDBGBBCABCABADBADBFDGGCCEDEEDGCGGDDGHCFHEFH,False +895,17.0,14.0,14.0,9.0,18.0,14.0,9.0,18.0,BGCDCCFADADBGDGCAEEAGEBEFBHHAEFFEHFEBEBCGCEBCEDAGGAHEABEABDAFDHBHHAAHBAHAHBAHCEHCAHFHBEHFCFFCEFCEHCHHCAEDFEDBGFGF,False +896,10.0,10.0,7.0,13.0,14.0,14.0,10.0,8.0,HCBCDHHGEAFHFCDGHEBDEAFBCFEDFADEADEADABBHCAEDGDDGFDAFHHFDGFGGFABFBCDBCEAGBBGEFGEFEEFEE,False +897,1.0,6.0,2.0,6.0,4.0,12.0,5.0,5.0,FBDGCGGDFEBFEFFEGFBGFHFFDFHBAHFEDFCHBBHDD,True +898,8.0,2.0,6.0,2.0,1.0,5.0,2.0,3.0,CFFCHDCFEHHAADAACCABAACGAFGBF,True +899,13.0,11.0,11.0,13.0,12.0,11.0,12.0,9.0,FCCGCABEBEEFCBGCDGCAECEEHAEGDCFFHDBCABDABEAFCBHABHADHGDFGDFBDFEDGHBGDGDAGAFECHEGDEGHFAHDABAF,False +900,11.0,8.0,16.0,15.0,15.0,12.0,12.0,10.0,HFDECDECFHCHGDEDEEBGHDAHDABCCDDFGDCGBCACCDGGFCGFEHEAGEAGEAFCCHCCAFEAFADEADHGDBFBBFBBFGCEAHFCDEEDHEG,False +901,6.0,5.0,13.0,12.0,14.0,4.0,0.0,2.0,DEEDEFCACAAEHEECDECAHCBDDECCBCFFDBFBCDECEECEDCADEDDEDACB,True +902,5.0,2.0,3.0,0.0,2.0,4.0,3.0,0.0,CFECFBAGAACAAGFFGBE,True +903,1.0,3.0,5.0,2.0,2.0,3.0,3.0,5.0,HEAGEFBCDBCBCFHCFHCDHGHG,False +904,8.0,10.0,8.0,10.0,10.0,10.0,8.0,8.0,HAEHAEDAEDGHFGFFAFFBFFGDABDECDEGGEGHBHBBCCFEDGECBCCBACHDCAFBDDEEDAHGBHBF,False +905,19.0,35.0,22.0,16.0,17.0,18.0,22.0,17.0,BEDEDGGBEBBDBGHBCBBCBHCAEAHBAGBCBHDBHDCHGCBGDAGDCCAGDGCDFCBFCBDBBDHAAEAGEGGEGBAFBHFGFGBFHEACECCGHCFFEFBCFBAFAABBBBBHDBEFBHFAGBEFCDGCFCDEEHBBFBDCGDEGFHGACAACAHHFGHEABE,False +906,6.0,6.0,11.0,1.0,5.0,2.0,8.0,3.0,GGECBACGCCGHCBFEGGAACAACDACBBCHCEFCEHBEGBG,True +907,10.0,11.0,15.0,22.0,12.0,15.0,10.0,11.0,CBDCFAHHHHCHDBDDBEDHCAECDFFDACDGBDABCFBCFBGDCFFCFEEHGGHGADGDFAFACGDCADFBCFGDFEDFDDADGAHEBHFCHDCDEEBEEDEGBE,False +908,4.0,0.0,2.0,5.0,3.0,0.0,2.0,3.0,GHACDADAEDAEDEGDHHC,True +909,1.0,4.0,0.0,5.0,2.0,3.0,1.0,1.0,FDHBDABFEBDDBDEGF,True +910,9.0,19.0,26.0,20.0,13.0,12.0,16.0,22.0,BHDCHGCHBCHDCBGCAEDFEBFBHDBHDGHEGECGCFDCHHGHHBHGFGCCBCCDCHAADFFDFFHEDCFBCEHCEHCDDFAGECGDBDBGFGEECBHCBACBACHCDEFDAHBCHCEGBGGCDDHDEHBAGBADB,False +911,5.0,1.0,2.0,3.0,2.0,3.0,0.0,2.0,HAHAADAFBAFEFCEDCD,True +912,26.0,20.0,25.0,15.0,11.0,21.0,19.0,28.0,BGFDDHABFAGCACFBCDBGDCCAAAHAAHFCHCEGGFFHHFBCABCGGGGBHEAHCAHBAHAHHACHFDHDAHABHCBFEBFADFGDCGFFHCGBCFBDFEDCHBBHBCGECGEHGFHAEHACHADAABHFDECEGBAGDHFDHCCFGAEGAECABFFBHCCHD,False +913,7.0,7.0,5.0,3.0,0.0,6.0,1.0,6.0,CDFCAFHACADCBBHBFHBFHFDGCABBABFHHAA,True +914,20.0,24.0,25.0,24.0,19.0,23.0,23.0,19.0,BDHFDGCHCAHFAHFGGCHBCHDFEDAEHCBFEBCGHCGFEACCAHDFGDFDBFBEFBEBGDBGDBCDECBFHEEEBCGBDDFDECHEHBFCAFADGADAHFCFFGFAGFEGEHGADDHDCHDBDDGEDBHABGGBEGBAHBHBDCFDCACCGEAACCACGAEGBEFBAFCCFGBAG,False +915,6.0,10.0,1.0,9.0,16.0,12.0,5.0,11.0,BFGFHGADDEEEEBEEHEHHEHFEBEGHFDHFBHFBDFDFFEBGDHCEBEEBEAGDADHAFAAFHBBEDF,True +916,19.0,25.0,17.0,15.0,26.0,25.0,27.0,16.0,EBBHBCGEEAEBCECGECHHCGDCECGECDBCDBAGCHGBFDBDBCEBFAAGAAHBGDFGAEGAEHEEHECGFFAFBEEAEEABEHBGHBFHDGCCFEFFCFFGFDHBAHAGFDGFDGHGGEDGEBGHGFFECBAFBHGEFBFGDFHDAADGGBAGBFCBFDEFAFBABE,False +917,1.0,1.0,0.0,2.0,5.0,1.0,1.0,0.0,DABDEEEEGFE,True +918,3.0,4.0,4.0,5.0,6.0,2.0,1.0,2.0,FCHDCBDCDEADEBDEBFBGACAEHEE,True +919,29.0,30.0,27.0,23.0,18.0,16.0,15.0,25.0,CECCDDBFGBEHCFACFCCAAAAABGDBDCBDABFBCEACABCGBHGDCGFBGHCDHCEHCBAFBFGHFHHDHFEHFEHCDBDDACBACGACGACFEDEBDHBDHAAEEGFBHHBHDAHBGBCGDAAHAFEBCCBDBEEAHEHFGHAHAABBABDHBDADDAECGBCEDCDCGEHAEHABBFF,False +920,6.0,8.0,6.0,2.0,10.0,1.0,2.0,2.0,ABABBFGBDGEECCEACECHEHBEABDBEEEACEACB,True +921,9.0,6.0,2.0,9.0,10.0,5.0,13.0,15.0,EBEDHGAHGFHGFBDEDDGCDGDHFAEABEGEGAHGAFEAGHAHHEHDEHDABDBGEGGBGHHACHFHH,True +922,0.0,4.0,4.0,4.0,5.0,3.0,8.0,5.0,BFCBHEBHDBCDFGGEGFEGEHGHCDHGDGGEC,False +923,9.0,18.0,18.0,28.0,20.0,33.0,20.0,19.0,FCFHEFDEBCBBCFACFDCDCAFCAHBDHBFGFHAFEAFEHGCHGDHCDHCFCGDCHBEGFFGDFGBHGDFGDFGFAHDBGGHHABEDFFDFFDFFEBFHDCEDFEFHEHHDGACFFGHBBHBADDDDCDEGDGGCEFCDBEBGEDEEBCEFGFFBEDGEDBFDE,False +924,2.0,5.0,0.0,7.0,6.0,1.0,0.0,3.0,EEDEEHEBAEBDDDADBHDFHBBD,True +925,12.0,20.0,17.0,18.0,18.0,15.0,13.0,21.0,GHHFHBACCFFHHFHHABHGDHFDEBABDDBCAEHABDEDCGDGDDGCDFFDHEBAEBAEBDCBGCEGBEHBFCEFDBGBFGBHBHHFFEEGECGECGECBHGBHDCHDAFDCFDEAHAHEAHACCEEFBBDCC,False +926,4.0,3.0,0.0,1.0,0.0,3.0,0.0,2.0,FHBFBBAAHAFDA,True +927,18.0,22.0,21.0,28.0,13.0,24.0,11.0,19.0,CBHHDCBAGFEDFBGBCGDCEFHFGHFGBFDDDDCDDCFHGFBDEBAFBEDACDAFEGFEDFCHEDADFBEFBABDGCCACBACHDCFDFAACCACBHFBHFBHADDADHACBBCDHCFFBFAEAACDBCHHFHGFHGHBGHBDEDDEDFEAHDBE,False +928,1.0,4.0,0.0,2.0,0.0,5.0,1.0,1.0,HBBFFDFFGFBADB,True +929,3.0,12.0,7.0,6.0,3.0,6.0,4.0,12.0,DHGHFACCACBAFHGDEGDCCBBFEBDEBHHCHHBHBBHBFHFCBFHGDBBDH,True +930,4.0,2.0,2.0,0.0,0.0,4.0,2.0,2.0,HCAACAFFGBFGBHAF,True +931,5.0,1.0,3.0,1.0,0.0,1.0,1.0,3.0,FGAADCACHACHAHB,True +932,6.0,4.0,3.0,4.0,3.0,1.0,3.0,2.0,DGCABBECFGCBGAADHAEHAEDABD,False +933,9.0,5.0,1.0,9.0,8.0,8.0,7.0,8.0,EFBCBAHBDFADADEAFFGGDEHDEHDHAAEABBFEDHEDHGFHGFEGFGGADHA,False +934,4.0,7.0,1.0,3.0,1.0,1.0,4.0,5.0,AEBGGBGBHABDFGDBADBHHCHHBA,True +935,14.0,14.0,13.0,12.0,23.0,12.0,15.0,6.0,EDAGFAGECGAGGACEACGGEHGEHCEBCFBEGECGEDEECFCBFBAFADBBDFBGCEEBEEDCDDFHFHEFDBCEGABGAFDAFDABDAEEEHBEDBEFCEAAGBGHC,False +936,16.0,21.0,7.0,13.0,13.0,15.0,22.0,19.0,GFBGHEGBBAABABEAHHADCEHFAHFACEGBHHBEFGAGEAHADDGDFGDFDAGHCGFFGBFAFEGFHGAHADGBDHCDHEHEGDEGDCGBHGBCGBFEAHCGHEBDBBEBBFBHFBHFBDAGGB,False +937,24.0,12.0,20.0,15.0,16.0,11.0,15.0,24.0,HAECEECEEBBAGGADHAHCGHDDAGBFGAHEHCAABGAHGAFGADHEDGFDHADBBCABGABDDCCDBHBEEBEEHAHHAGHAHHDHCFCAHAACCDCGHCHFCHFCHFADGAHFAFFCCFEDEEBGECCACEHDG,False +938,3.0,5.0,0.0,6.0,7.0,6.0,5.0,5.0,DGBFHAFEFDHBDHBDGGGEEHBEHBFDEGAEFAEFD,False +939,22.0,26.0,26.0,14.0,18.0,22.0,25.0,26.0,ACFACFGFBAFBGBHHBDHBGGEAHFAHFAFEHGECCECCFAEGABGABEAHGBEGFHCHBBDBCHFDEFHEABEFCEBHEBHDBADACDEFBCHDGBBCCBCHBEHFCGFCGCEGCHHCHGAFCADDBHDGFFHBAGCACABCGDGGBFHDCBFGBFEEFHEHAGHGGHCCDAGDAGA,False +940,8.0,10.0,2.0,5.0,4.0,6.0,1.0,9.0,BGDEHABAADAFBAFHHFHHFHBAHDCEABDBBHEDHEBBFBAFC,True +941,29.0,18.0,34.0,25.0,27.0,21.0,24.0,19.0,DEDAEGFBGFBGCBFCHECFEFAGBABDCBEHHEHGADEHDFHFFCEAAEAFEAFCGGDGFEHEECGCCDCCECCDHFAHCACDGDBGFBCFADEABHABDABDHBGHGDADDADFCDAGFAGBBBECFCCECCEDGGDCDEGGAHHFEEAEACBDCDHCHEEAEACFAGDHFEGCAGHABDACHCCBCFGCAGEAC,False +942,22.0,23.0,26.0,28.0,25.0,25.0,28.0,22.0,HHDBFEGFEGCHBDEBHGCHGBDFHDBHFBHBGHCCECADHADGAGGCGCFDCFAFGDFAHGEDEEAEFDBCHBDHGHECFAFFAEFBGFHAFBGFAHFCCGHDBABEGBDBHFACAADAGDGECGEGGHCGFCFFEDFCCACEDDHDDEADECDGBBGBCHAEHEEFCBCCACGFBDFCDEADBGBEGBEGDEADEAD,False +943,10.0,5.0,3.0,10.0,7.0,4.0,2.0,3.0,DEBBHAGEABHDCADAADEEBCEFEDFADAADAGDABDCHDFFE,True +944,12.0,16.0,22.0,10.0,9.0,17.0,15.0,10.0,CBFHFFBDFBAGECGCCHCAHCFECDDFFDECBBCBBCBFCAFCFFEFABFGBEAHAGBGGCCGBADCADHDGBFGCEGCEGCGHFGCFEFBDHADACGABBHHDAHCGCE,False +945,14.0,9.0,10.0,9.0,9.0,9.0,8.0,11.0,GBHGAHFAHFBGGDDGCHFAAFACDEFDACDHCEEAHEAFCBHCBGFBAEBAEBAFCAHDAEGCHDEBAEFGDDCHBCH,False 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For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/src/main/scala/org/xcit/nback/markov/models/State.scala b/src/main/scala/org/xcit/nback/markov/models/State.scala deleted file mode 100644 index fbbd844..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/State.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * A Single state with a label in Markov chain - * @param label A simple string label, representing the state and node - */ -class State(val label: String) { - - /** - * Keep track of transitions from this state to other states. - */ - val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() -} diff --git a/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/src/main/scala/org/xcit/nback/markov/models/Transition.scala deleted file mode 100644 index bc20a9e..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/Transition.scala +++ /dev/null @@ -1,8 +0,0 @@ -package org.xcit.nback.markov.models - -/** - * A Single transition in Markov chain graph. It is stored in "from" node. - * @param to the ending node of the edge - * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). - */ -case class Transition(to: State, probability: Double = 0.0) diff --git a/src/test/scala/ThreeBackBenchmark.scala b/src/test/scala/ThreeBackBenchmark.scala deleted file mode 100644 index 0c7dad9..0000000 --- a/src/test/scala/ThreeBackBenchmark.scala +++ /dev/null @@ -1,7 +0,0 @@ - -/** - * TODO Benchmark 3-back simple sequence generator - */ -class ThreeBackBenchmark { - -} diff --git a/tests/benchmark_diagrams.py b/tests/benchmark_diagrams.py new file mode 100644 index 0000000..8fa448e --- /dev/null +++ b/tests/benchmark_diagrams.py @@ -0,0 +1,159 @@ +import pandas as pd +import numpy as np +from matplotlib import pyplot as plt + +import benchmarks.common as common + + +def tlratio(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2,ignore_index=True) + stats = [] + for trials in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == trials) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == trials) + targets2 = data[alg2].targets if alg2.shape[0] > 0 else np.nan + targets4 = data[alg4].targets if alg4.shape[0] > 0 else np.nan + lures2 = data[alg2].lures if alg2.shape[0] > 0 else np.nan + lures4 = data[alg4].lures if alg4.shape[0] > 0 else np.nan + stats.append([trials, (targets2/lures2).mean(), (targets4/lures4).mean()]) + stats = pd.DataFrame(stats, columns=['trials', 'tl2', 'tl4']) #.dropna(subset=['skewness']) + + plt.style.use('ggplot') + + plt.ylim(bottom=0, top=30) + plt.scatter(stats.trials, stats.tl2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl2[idx], 1)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.tl4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl4[idx], 2)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('T:L Ratio') + plt.ylabel('T:L Ratio') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_tlratio.png', bbox_inches='tight') + plt.show() + + +def time_per_trial(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for t in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == t) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == t) + time2 = data[alg2].time.mean() * 1000 if alg2.shape[0] > 0 else np.nan + time4 = data[alg4].time.mean() * 1000 if alg4.shape[0] > 0 else np.nan + stats.append([t, time2, time4]) + stats = pd.DataFrame(stats, columns=['trials', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.trials, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time2[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time4[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2v4_time_trials.png', bbox_inches='tight') + plt.show() + +def time_profiles(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 8): + alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + time2 = data[alg2].time.mean() * 1000 + time4 = data[alg4].time.mean() * 1000 + stats.append([ni, time2, time4]) + stats = pd.DataFrame(stats, columns=['n', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.n, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.time2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + plt.scatter(stats.n, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.time4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_time_n.png', bbox_inches='tight') + plt.show() + +def skewness(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 9): + all_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + skewed_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) & data.skewed + all_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + skewed_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) & data.skewed + num_of_sequences2 = data[all_alg2].shape[0] + skewed_sequences2 = data[skewed_alg2].shape[0] + num_of_sequences4 = data[all_alg4].shape[0] + skewed_sequences4 = data[skewed_alg4].shape[0] + skewness2 = skewed_sequences2 * 100.0 / num_of_sequences2 if (num_of_sequences2>0) else 0 + skewness4 = skewed_sequences4 * 100.0 / num_of_sequences4 if (num_of_sequences4>0) else 0 + stats.append([ni, skewness2, skewness4]) + stats = pd.DataFrame(stats, columns=['n', 'skewness2', 'skewness4']) #.dropna(subset=['skewness']) + + + plt.style.use('ggplot') + plt.scatter(stats.n, stats.skewness2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.skewness2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + + plt.scatter(stats.n, stats.skewness4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.skewness4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Skewness') + plt.ylabel('Skewed Blocks (%)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_skewness.png', bbox_inches='tight') + plt.show() + +if __name__ == "__main__": + tlratio() + skewness() + time_profiles() + time_per_trial() diff --git a/tests/benchmark_skewness.py b/tests/benchmark_skewness.py new file mode 100644 index 0000000..f468b4d --- /dev/null +++ b/tests/benchmark_skewness.py @@ -0,0 +1,97 @@ +import random +import heapq +import csv + +# Common parameters +alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'] +trials_range = (10, 40) +n = 3 +sample_size = 100 + + +def to_benchmark_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [str(ralph_skewed)] + +def benchmark_nb_gm_001(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_001') + + +def benchmark_nb_gm_002(filename): + import generators.nb_gm_002 as nb_gm_002 + + generator = nb_gm_002.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + # print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_002') + + +def benchmark_nb_gm_003(filename): + import generators.nb_gm_003 as nb_gm_003 + + generator = nb_gm_003.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + print(f"sequence {i}/{sample_size}: {trials} trials") + seq = generator.generate(trials) + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_003') + + +def show_skweness_diagram(filename, choices, title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + print(filename) + data = pd.read_csv(filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) #.dropna(subset=['skewness']) + #print(stats.trials) + #plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'{title}.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + benchmark_nb_gm_003('../benchmarks/nb_gm_003_2back.csv') diff --git a/tests/common.py b/tests/common.py new file mode 100644 index 0000000..e40c0df --- /dev/null +++ b/tests/common.py @@ -0,0 +1,27 @@ + + +# Common benchmark parameters +choices = alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F'] +trials_range = (10, 65) +n = 4 +sample_size = 100 + + +def count_targets_and_lures(seq, n): + mask = 'D'*n + for index in range(n, len(seq)): + if seq[index] == seq[index - n]: + mask += 'T' + elif seq[index] in seq[index - n - 1:index - n + 1]: + mask += 'L' + else: + mask += 'D' + return mask.count('T'), mask.count('L') + + +def skewness(seq, choices): + import heapq + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return ralph_skewed diff --git a/tests/nb_gm_001_bm.py b/tests/nb_gm_001_bm.py new file mode 100644 index 0000000..54f6cb3 --- /dev/null +++ b/tests/nb_gm_001_bm.py @@ -0,0 +1,75 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq) , str(ralph_skewed)] + + +def benchmark(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets / s.trials, axis=1) + plt.scatter(data.trials, data.targets_ratio, alpha=0.2) + plt.show() + +if __name__ == '__main__': + alg = 'nb_gm_001' + fn = f'results/{alg}_{n}back.csv' + benchmark(fn) + # skewness_diagram(fn, alg) + targets_ratio_diagram(fn, alg) diff --git a/tests/nb_gm_002_bm.py b/tests/nb_gm_002_bm.py new file mode 100644 index 0000000..c8af543 --- /dev/null +++ b/tests/nb_gm_002_bm.py @@ -0,0 +1,105 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq), str(ralph_skewed)] + + +def benchmark(filename): + from generators.nb_gm_002 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials, int(trials/3), 0, 0) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +import time +import numpy as np +import pandas as pd + +import benchmarks.common as common + +def profile(): + from generators.nb_gm_002 import SequenceGenerator + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, int(lures/2), int(lures/2)) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('benchmarks/results/nb_gm_002_profile.csv', sep=',', encoding='utf-8') + +if __name__ == '__main__': + alg = 'nb_gm_002' + fn = f'results/{alg}_{n}back.csv' + profile() diff --git a/tests/nb_gm_003_bm.py b/tests/nb_gm_003_bm.py new file mode 100644 index 0000000..fa6c19a --- /dev/null +++ b/tests/nb_gm_003_bm.py @@ -0,0 +1,114 @@ +import heapq +import csv +import random +import time + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq, time_per_block): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [time_per_block, ''.join(seq), str(ralph_skewed)] + + +def benchmark_skewness(filename): + from generators.nb_gm_003 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['time_per_block', 'seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + targets = trials / 3 + t = time.time() + seq = generator.generate(trials, targets) + t = time.time() - t + print(f"sequence {i}/{sample_size}: {trials} trials, took {t}s.") + writer.writerow(to_csv_row(i, seq, t)) + plot_skewness(fn, 'nb_gm_003') + + +def plot_skewness(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def plot_targets_ratio(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +def benchmark_targets_ratio(): + pass + +def benchmark_chunking(): + pass + + +def benchmark_n(): + pass + + +def plot_timing(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['time_per_trial'] = data.apply(lambda s: s.time_per_block / s.trials, axis=1) + plt.style.use('ggplot') + plt.title(f"{figure_title} - average time to generate a trial") + plt.ylabel('time (s)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.time_per_trial, alpha=0.5) + + # draw fitted curve + # import numpy as np + # p = np.poly1d(np.polyfit(data.trials, data.time_per_trial, 3)) + # plt.plot(data.trials, p(data.trials), color='red') + + plt.savefig(f'results/{figure_title}_timing.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + alg = 'nb_gm_003' + fn = f'results/{alg}_{n}back.csv' + benchmark_skewness(fn) diff --git a/tests/nb_gm_004_bm.py b/tests/nb_gm_004_bm.py new file mode 100644 index 0000000..b4ad4a8 --- /dev/null +++ b/tests/nb_gm_004_bm.py @@ -0,0 +1,26 @@ +import time +import numpy as np +import pandas as pd + +import tests.common as common +from generators.nb_gm_004 import SequenceGenerator + +def run(): + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, lures) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('tests/results/nb_gm_004_profile.csv', sep=',', encoding='utf-8') diff --git a/tests/results/2v4_time_trials.png b/tests/results/2v4_time_trials.png new file mode 100644 index 0000000..9be91b4 --- /dev/null +++ b/tests/results/2v4_time_trials.png Binary files differ diff --git a/tests/results/2vs4_skewness.png b/tests/results/2vs4_skewness.png new file mode 100644 index 0000000..a488e1f --- /dev/null +++ b/tests/results/2vs4_skewness.png Binary files differ diff --git a/tests/results/2vs4_time_n.png b/tests/results/2vs4_time_n.png new file mode 100644 index 0000000..d022ed0 --- /dev/null +++ b/tests/results/2vs4_time_n.png Binary files differ diff --git a/tests/results/2vs4_tlratio.png b/tests/results/2vs4_tlratio.png new file mode 100644 index 0000000..b76f296 --- /dev/null +++ b/tests/results/2vs4_tlratio.png Binary files differ diff --git a/tests/results/nb_gm_001_2back.csv b/tests/results/nb_gm_001_2back.csv new file mode 100644 index 0000000..f6ad25e --- /dev/null +++ b/tests/results/nb_gm_001_2back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,0.0,1.0,0.0,55.0,56.0,0.0,0.0,0.0,BEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +1,0.0,94.0,0.0,94.0,0.0,0.0,0.0,1.0,HDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +2,0.0,96.0,95.0,1.0,0.0,0.0,0.0,0.0,DBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +3,0.0,9.0,0.0,1.0,9.0,0.0,0.0,0.0,DBEBEBEBEBEBEBEBEBE,True +4,1.0,80.0,0.0,0.0,80.0,0.0,0.0,0.0,ABEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True +5,0.0,0.0,0.0,66.0,0.0,0.0,65.0,1.0,HDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +6,0.0,0.0,0.0,0.0,0.0,0.0,0.0,57.0,HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +7,1.0,0.0,0.0,0.0,0.0,20.0,0.0,21.0,AHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +8,0.0,21.0,21.0,0.0,0.0,0.0,1.0,0.0,GBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +9,0.0,0.0,0.0,1.0,25.0,0.0,0.0,24.0,DEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +10,0.0,0.0,64.0,0.0,0.0,0.0,1.0,64.0,GCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +11,0.0,0.0,0.0,0.0,0.0,0.0,41.0,41.0,HGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +12,14.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,AAAAAAAAAAAAAA,True +13,0.0,1.0,0.0,0.0,77.0,0.0,78.0,0.0,BGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +14,0.0,1.0,0.0,145.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +15,0.0,0.0,58.0,60.0,0.0,0.0,0.0,0.0,DDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +16,1.0,0.0,0.0,73.0,0.0,0.0,0.0,73.0,ADHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +17,47.0,1.0,0.0,0.0,0.0,0.0,48.0,0.0,BGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +18,92.0,91.0,0.0,1.0,0.0,0.0,0.0,0.0,DABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +19,0.0,0.0,0.0,0.0,44.0,0.0,0.0,0.0,EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True 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+26,0.0,75.0,0.0,0.0,0.0,0.0,75.0,0.0,BGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +27,0.0,0.0,54.0,0.0,0.0,0.0,0.0,53.0,CCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +28,1.0,0.0,0.0,10.0,0.0,10.0,0.0,0.0,ADFDFDFDFDFDFDFDFDFDF,True +29,0.0,1.0,40.0,0.0,0.0,0.0,0.0,41.0,BHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +30,15.0,0.0,16.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACAC,True +31,0.0,0.0,80.0,0.0,0.0,0.0,0.0,81.0,HCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +32,60.0,0.0,0.0,60.0,0.0,0.0,1.0,0.0,GADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +33,0.0,0.0,0.0,0.0,33.0,0.0,0.0,35.0,HHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +34,0.0,0.0,0.0,0.0,89.0,88.0,0.0,0.0,EFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +35,0.0,0.0,0.0,1.0,27.0,27.0,0.0,0.0,DEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +36,0.0,0.0,23.0,0.0,23.0,0.0,1.0,0.0,GECECECECECECECECECECECECECECECECECECECECECECEC,True +37,0.0,1.0,0.0,0.0,85.0,0.0,0.0,86.0,BHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +38,22.0,0.0,0.0,0.0,0.0,0.0,1.0,21.0,GAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +39,0.0,96.0,0.0,0.0,0.0,0.0,1.0,95.0,GBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +40,0.0,10.0,0.0,0.0,0.0,0.0,1.0,10.0,GHBHBHBHBHBHBHBHBHBHB,True +41,0.0,0.0,30.0,31.0,0.0,0.0,1.0,0.0,GDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +42,0.0,0.0,0.0,1.0,48.0,49.0,0.0,0.0,DFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +43,0.0,65.0,0.0,1.0,0.0,65.0,0.0,0.0,DFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +44,11.0,0.0,0.0,11.0,1.0,0.0,0.0,0.0,EDADADADADADADADADADADA,True +45,35.0,0.0,1.0,34.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True 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+64,0.0,0.0,0.0,1.0,0.0,199.0,0.0,0.0,DFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +65,0.0,0.0,0.0,1.0,0.0,13.0,0.0,0.0,DFFFFFFFFFFFFF,True +66,0.0,84.0,0.0,0.0,0.0,84.0,0.0,0.0,FBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +67,48.0,0.0,1.0,0.0,0.0,0.0,0.0,48.0,CAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +68,0.0,0.0,0.0,49.0,0.0,48.0,0.0,0.0,DDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDF,True +69,0.0,48.0,1.0,0.0,47.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True 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+145,0.0,86.0,0.0,0.0,0.0,0.0,85.0,1.0,HBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +146,0.0,0.0,1.0,0.0,0.0,33.0,0.0,32.0,CFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +147,0.0,11.0,0.0,0.0,0.0,0.0,0.0,12.0,HHBHBHBHBHBHBHBHBHBHBHB,True +148,0.0,56.0,0.0,0.0,0.0,0.0,0.0,56.0,BHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +149,0.0,0.0,83.0,0.0,1.0,0.0,83.0,0.0,EGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +150,0.0,78.0,1.0,0.0,0.0,77.0,0.0,0.0,CBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True 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+159,0.0,62.0,0.0,0.0,0.0,0.0,62.0,0.0,GBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +160,0.0,0.0,0.0,1.0,0.0,0.0,0.0,88.0,DHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +161,1.0,7.0,0.0,0.0,8.0,0.0,0.0,0.0,AEBEBEBEBEBEBEBE,True +162,14.0,0.0,0.0,14.0,0.0,0.0,0.0,0.0,DADADADADADADADADADADADADADA,True +163,0.0,0.0,1.0,0.0,51.0,0.0,0.0,50.0,CEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +164,68.0,0.0,0.0,0.0,0.0,68.0,0.0,0.0,FAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +165,0.0,0.0,72.0,0.0,0.0,1.0,72.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +166,0.0,0.0,0.0,1.0,0.0,0.0,29.0,28.0,DGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +167,0.0,0.0,0.0,111.0,0.0,0.0,0.0,0.0,DDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +168,0.0,1.0,0.0,73.0,73.0,0.0,0.0,0.0,BEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +169,0.0,1.0,0.0,0.0,67.0,66.0,0.0,0.0,BEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +170,17.0,0.0,0.0,1.0,0.0,16.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +171,37.0,1.0,0.0,37.0,0.0,0.0,0.0,0.0,BADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +172,0.0,79.0,1.0,79.0,0.0,0.0,0.0,0.0,CBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +173,0.0,0.0,0.0,0.0,35.0,0.0,0.0,0.0,EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +174,0.0,0.0,0.0,0.0,1.0,40.0,0.0,39.0,EFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +175,0.0,0.0,85.0,1.0,0.0,0.0,0.0,85.0,DHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +176,0.0,25.0,1.0,0.0,0.0,0.0,0.0,0.0,CBBBBBBBBBBBBBBBBBBBBBBBBB,True +177,0.0,18.0,17.0,0.0,0.0,0.0,0.0,1.0,HBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +178,0.0,1.0,0.0,0.0,0.0,0.0,0.0,125.0,BHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +179,0.0,0.0,0.0,77.0,76.0,0.0,0.0,0.0,DDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +180,1.0,0.0,0.0,0.0,0.0,19.0,20.0,0.0,AGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFG,True +181,0.0,1.0,92.0,0.0,0.0,0.0,0.0,92.0,BCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +182,0.0,0.0,0.0,0.0,1.0,50.0,50.0,0.0,EGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +183,0.0,0.0,0.0,37.0,0.0,1.0,0.0,0.0,FDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +184,80.0,0.0,1.0,0.0,0.0,81.0,0.0,0.0,CFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +185,0.0,0.0,0.0,16.0,16.0,0.0,0.0,0.0,DEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +186,0.0,16.0,0.0,0.0,0.0,15.0,0.0,1.0,HBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +187,7.0,0.0,0.0,0.0,8.0,1.0,0.0,0.0,FEAEAEAEAEAEAEAE,True +188,0.0,21.0,0.0,0.0,0.0,0.0,1.0,21.0,GHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +189,0.0,0.0,0.0,0.0,29.0,29.0,0.0,0.0,EFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +190,63.0,0.0,0.0,0.0,0.0,63.0,0.0,0.0,FAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +191,8.0,0.0,8.0,0.0,0.0,0.0,1.0,0.0,GACACACACACACACAC,True +192,69.0,1.0,0.0,0.0,0.0,0.0,0.0,70.0,BHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +193,0.0,42.0,0.0,41.0,0.0,0.0,1.0,0.0,GBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +194,91.0,0.0,93.0,0.0,0.0,0.0,0.0,0.0,CCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +195,0.0,16.0,0.0,0.0,0.0,1.0,16.0,0.0,FGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +196,0.0,0.0,1.0,0.0,0.0,72.0,72.0,0.0,CFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFG,True +197,0.0,0.0,0.0,0.0,85.0,0.0,0.0,86.0,HHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +198,0.0,0.0,0.0,0.0,57.0,57.0,1.0,0.0,GFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +199,76.0,0.0,0.0,0.0,0.0,1.0,0.0,76.0,FHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +200,0.0,1.0,0.0,31.0,0.0,0.0,31.0,0.0,BGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +201,0.0,0.0,34.0,1.0,35.0,0.0,0.0,0.0,DECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +202,0.0,0.0,76.0,0.0,1.0,0.0,75.0,0.0,ECGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +203,0.0,88.0,0.0,0.0,0.0,88.0,0.0,1.0,HBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +204,0.0,0.0,0.0,0.0,0.0,0.0,84.0,85.0,HHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +205,0.0,0.0,81.0,0.0,0.0,0.0,81.0,0.0,GCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +206,0.0,0.0,0.0,0.0,70.0,70.0,0.0,1.0,HEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +207,0.0,0.0,0.0,57.0,1.0,0.0,56.0,0.0,EDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +208,0.0,1.0,0.0,53.0,0.0,0.0,52.0,0.0,BDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +209,0.0,0.0,0.0,0.0,12.0,0.0,11.0,1.0,HEGEGEGEGEGEGEGEGEGEGEGE,True +210,87.0,0.0,0.0,88.0,1.0,0.0,0.0,0.0,EDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +211,0.0,0.0,12.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCC,True +212,0.0,0.0,0.0,66.0,0.0,65.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +213,1.0,0.0,0.0,0.0,0.0,21.0,22.0,0.0,AGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFG,True +214,74.0,73.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +215,0.0,5.0,0.0,0.0,6.0,0.0,0.0,1.0,HEBEBEBEBEBE,True +216,0.0,1.0,0.0,0.0,0.0,53.0,0.0,54.0,BHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +217,70.0,0.0,0.0,0.0,0.0,70.0,0.0,0.0,AFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +218,0.0,0.0,0.0,0.0,0.0,0.0,36.0,35.0,GGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +219,0.0,90.0,90.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +220,0.0,0.0,0.0,0.0,0.0,0.0,37.0,38.0,HHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +221,0.0,0.0,44.0,0.0,0.0,1.0,44.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +222,0.0,0.0,0.0,67.0,67.0,0.0,0.0,1.0,HDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +223,6.0,0.0,0.0,0.0,5.0,1.0,0.0,0.0,FAEAEAEAEAEA,True +224,0.0,38.0,0.0,38.0,0.0,0.0,1.0,0.0,GBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +225,0.0,0.0,0.0,128.0,1.0,0.0,0.0,0.0,EDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +226,0.0,90.0,0.0,89.0,1.0,0.0,0.0,0.0,EBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +227,0.0,51.0,0.0,1.0,0.0,0.0,0.0,52.0,DHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +228,0.0,0.0,7.0,0.0,0.0,0.0,8.0,1.0,HGCGCGCGCGCGCGCG,True +229,18.0,0.0,0.0,0.0,0.0,0.0,1.0,18.0,GHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True 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+384,0.0,0.0,28.0,0.0,1.0,0.0,0.0,28.0,ECHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +385,0.0,1.0,119.0,0.0,0.0,0.0,0.0,0.0,BCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +386,0.0,0.0,93.0,0.0,0.0,93.0,1.0,0.0,GCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCF,True +387,92.0,0.0,1.0,0.0,92.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +388,0.0,186.0,0.0,0.0,0.0,0.0,0.0,0.0,BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True 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+396,65.0,0.0,0.0,0.0,0.0,1.0,0.0,65.0,FAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +397,0.0,0.0,0.0,55.0,56.0,0.0,0.0,0.0,EEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +398,26.0,0.0,0.0,25.0,1.0,0.0,0.0,0.0,EADADADADADADADADADADADADADADADADADADADADADADADADADA,True +399,0.0,0.0,60.0,0.0,0.0,0.0,1.0,59.0,GCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +400,1.0,0.0,0.0,0.0,160.0,0.0,0.0,0.0,AEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +401,1.0,0.0,31.0,0.0,0.0,31.0,0.0,0.0,AFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +402,0.0,0.0,0.0,15.0,1.0,0.0,0.0,0.0,EDDDDDDDDDDDDDDD,True +403,0.0,0.0,0.0,54.0,55.0,0.0,0.0,1.0,HEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +404,0.0,0.0,0.0,27.0,0.0,27.0,0.0,1.0,HFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +405,0.0,0.0,0.0,1.0,0.0,15.0,0.0,15.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +406,0.0,95.0,0.0,94.0,0.0,1.0,0.0,0.0,FBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +407,0.0,0.0,15.0,14.0,0.0,0.0,0.0,0.0,CCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +408,78.0,78.0,0.0,0.0,0.0,0.0,1.0,0.0,GBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +409,0.0,0.0,72.0,1.0,0.0,0.0,72.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +410,55.0,0.0,1.0,0.0,0.0,0.0,55.0,0.0,CAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +411,0.0,59.0,0.0,0.0,0.0,60.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +412,61.0,0.0,0.0,61.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +413,0.0,1.0,0.0,75.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +414,0.0,53.0,0.0,0.0,0.0,0.0,52.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +415,0.0,0.0,16.0,0.0,1.0,0.0,0.0,15.0,ECHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +416,0.0,0.0,0.0,39.0,0.0,0.0,0.0,38.0,DHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +417,96.0,0.0,1.0,95.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +418,28.0,0.0,1.0,27.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +419,0.0,1.0,92.0,92.0,0.0,0.0,0.0,0.0,BCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +420,1.0,0.0,20.0,0.0,20.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECE,True +421,0.0,90.0,0.0,0.0,0.0,0.0,89.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +422,10.0,0.0,0.0,0.0,0.0,1.0,11.0,0.0,FGAGAGAGAGAGAGAGAGAGAG,True +423,0.0,0.0,0.0,74.0,73.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +424,0.0,0.0,127.0,0.0,0.0,0.0,1.0,0.0,GCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +425,1.0,9.0,0.0,0.0,0.0,9.0,0.0,0.0,AFBFBFBFBFBFBFBFBFB,True +426,0.0,0.0,84.0,0.0,0.0,0.0,0.0,84.0,HCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +427,33.0,0.0,0.0,34.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +428,1.0,30.0,0.0,30.0,0.0,0.0,0.0,0.0,ABDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +429,0.0,0.0,67.0,0.0,1.0,67.0,0.0,0.0,EFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +430,62.0,0.0,0.0,63.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +431,1.0,9.0,9.0,0.0,0.0,0.0,0.0,0.0,ABCBCBCBCBCBCBCBCBC,True +432,15.0,0.0,0.0,0.0,0.0,0.0,14.0,0.0,AAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +433,0.0,1.0,0.0,65.0,66.0,0.0,0.0,0.0,BEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +434,0.0,160.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +435,0.0,0.0,1.0,0.0,42.0,42.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +436,0.0,0.0,55.0,0.0,55.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +437,0.0,0.0,0.0,1.0,0.0,73.0,0.0,73.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +438,79.0,0.0,0.0,0.0,78.0,0.0,0.0,0.0,AAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +439,0.0,0.0,67.0,0.0,0.0,0.0,66.0,1.0,HCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +440,0.0,0.0,77.0,0.0,0.0,1.0,0.0,76.0,FCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +441,0.0,0.0,0.0,0.0,153.0,0.0,0.0,1.0,HEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +442,0.0,88.0,88.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +443,0.0,0.0,0.0,20.0,22.0,0.0,0.0,0.0,EEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +444,41.0,0.0,42.0,0.0,0.0,0.0,1.0,0.0,GCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +445,0.0,0.0,0.0,47.0,0.0,46.0,0.0,1.0,HDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +446,1.0,0.0,0.0,0.0,86.0,0.0,0.0,87.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +447,56.0,56.0,0.0,0.0,0.0,0.0,0.0,1.0,HABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +448,0.0,0.0,0.0,0.0,11.0,0.0,0.0,10.0,EEHEHEHEHEHEHEHEHEHEH,True +449,0.0,0.0,0.0,0.0,0.0,1.0,92.0,92.0,FGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +450,0.0,0.0,0.0,6.0,5.0,1.0,0.0,0.0,FDEDEDEDEDED,True +451,66.0,1.0,67.0,0.0,0.0,0.0,0.0,0.0,BCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +452,0.0,0.0,0.0,13.0,0.0,1.0,12.0,0.0,FDGDGDGDGDGDGDGDGDGDGDGDGD,True +453,1.0,0.0,0.0,0.0,56.0,0.0,56.0,0.0,AEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +454,15.0,0.0,0.0,0.0,0.0,0.0,0.0,16.0,HAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +455,0.0,21.0,1.0,0.0,21.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True +456,93.0,0.0,1.0,0.0,92.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +457,1.0,0.0,0.0,0.0,35.0,0.0,0.0,35.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +458,13.0,0.0,0.0,0.0,1.0,0.0,13.0,0.0,EAGAGAGAGAGAGAGAGAGAGAGAGAG,True +459,0.0,0.0,65.0,0.0,1.0,0.0,65.0,0.0,ECGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +460,0.0,0.0,95.0,1.0,0.0,95.0,0.0,0.0,DFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +461,15.0,0.0,0.0,0.0,1.0,0.0,0.0,15.0,EHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +462,0.0,0.0,198.0,0.0,1.0,0.0,0.0,0.0,ECCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +463,84.0,84.0,0.0,0.0,1.0,0.0,0.0,0.0,EABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +464,0.0,0.0,0.0,0.0,0.0,60.0,0.0,61.0,HFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +465,0.0,179.0,0.0,1.0,0.0,0.0,0.0,0.0,DBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +466,1.0,0.0,90.0,0.0,89.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +467,0.0,35.0,0.0,0.0,0.0,34.0,0.0,0.0,BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +468,0.0,0.0,0.0,1.0,7.0,0.0,0.0,7.0,DHEHEHEHEHEHEHE,True +469,0.0,0.0,0.0,0.0,92.0,0.0,91.0,0.0,EEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +470,0.0,0.0,46.0,0.0,0.0,1.0,46.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +471,0.0,0.0,0.0,0.0,0.0,1.0,158.0,0.0,FGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +472,1.0,0.0,0.0,0.0,0.0,58.0,0.0,59.0,AHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +473,0.0,0.0,6.0,1.0,0.0,0.0,6.0,0.0,DCGCGCGCGCGCG,True 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+766,56.0,0.0,0.0,0.0,56.0,0.0,0.0,0.0,EAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +767,73.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,BAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +768,0.0,47.0,0.0,0.0,0.0,47.0,0.0,0.0,FBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +769,76.0,0.0,1.0,0.0,0.0,0.0,76.0,0.0,CAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +770,43.0,43.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +771,0.0,0.0,0.0,0.0,1.0,80.0,0.0,0.0,EFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +772,0.0,68.0,0.0,0.0,0.0,0.0,0.0,67.0,BBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +773,60.0,1.0,0.0,0.0,0.0,61.0,0.0,0.0,BFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +774,0.0,1.0,0.0,57.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +775,0.0,78.0,0.0,0.0,1.0,0.0,0.0,0.0,EBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +776,1.0,0.0,0.0,0.0,0.0,96.0,96.0,0.0,AGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +777,43.0,0.0,0.0,0.0,0.0,1.0,44.0,0.0,FGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +778,0.0,0.0,49.0,0.0,50.0,0.0,0.0,1.0,HECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +779,0.0,0.0,0.0,118.0,0.0,0.0,0.0,1.0,HDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +780,0.0,80.0,79.0,0.0,0.0,0.0,0.0,0.0,BCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +781,77.0,0.0,0.0,0.0,0.0,0.0,78.0,1.0,HGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +782,1.0,0.0,0.0,62.0,61.0,0.0,0.0,0.0,ADEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +783,0.0,0.0,0.0,0.0,0.0,10.0,10.0,1.0,HGFGFGFGFGFGFGFGFGFGF,True +784,0.0,0.0,18.0,1.0,17.0,0.0,0.0,0.0,DCECECECECECECECECECECECECECECECECEC,True +785,0.0,1.0,0.0,0.0,67.0,0.0,67.0,0.0,BGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +786,0.0,0.0,0.0,48.0,0.0,0.0,48.0,1.0,HGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +787,0.0,0.0,1.0,0.0,47.0,0.0,0.0,47.0,CEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +788,0.0,28.0,0.0,0.0,1.0,0.0,29.0,0.0,EGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +789,0.0,11.0,0.0,0.0,0.0,11.0,0.0,1.0,HBFBFBFBFBFBFBFBFBFBFBF,True +790,0.0,0.0,0.0,10.0,9.0,0.0,0.0,1.0,HDEDEDEDEDEDEDEDEDED,True +791,0.0,0.0,1.0,0.0,73.0,0.0,0.0,73.0,CHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True 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+798,0.0,0.0,0.0,0.0,0.0,126.0,0.0,0.0,FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +799,1.0,0.0,20.0,20.0,0.0,0.0,0.0,0.0,ADCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +800,1.0,0.0,0.0,0.0,66.0,0.0,0.0,66.0,AEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +801,0.0,0.0,0.0,67.0,0.0,1.0,66.0,0.0,FDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +802,0.0,0.0,0.0,41.0,0.0,0.0,0.0,42.0,HDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +803,1.0,0.0,81.0,0.0,82.0,0.0,0.0,0.0,AECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +804,0.0,1.0,74.0,0.0,0.0,0.0,75.0,0.0,BGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +805,0.0,57.0,58.0,0.0,0.0,0.0,0.0,0.0,CCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +806,45.0,44.0,0.0,0.0,1.0,0.0,0.0,0.0,EABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +807,0.0,0.0,65.0,0.0,0.0,0.0,66.0,0.0,GGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +808,18.0,0.0,0.0,0.0,19.0,1.0,0.0,0.0,FEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +809,0.0,65.0,0.0,64.0,1.0,0.0,0.0,0.0,EBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +810,77.0,0.0,0.0,0.0,77.0,1.0,0.0,0.0,FEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +811,38.0,0.0,38.0,0.0,0.0,0.0,1.0,0.0,GCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +812,0.0,0.0,17.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCCCCCCC,True +813,0.0,0.0,0.0,0.0,191.0,0.0,1.0,0.0,GEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +814,0.0,0.0,0.0,0.0,0.0,0.0,88.0,87.0,GHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +815,78.0,0.0,0.0,0.0,80.0,0.0,0.0,0.0,EEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +816,0.0,34.0,1.0,0.0,0.0,0.0,0.0,0.0,CBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +817,0.0,0.0,71.0,1.0,0.0,0.0,71.0,0.0,DGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +818,0.0,1.0,194.0,0.0,0.0,0.0,0.0,0.0,BCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +819,0.0,0.0,65.0,0.0,1.0,0.0,0.0,0.0,ECCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +820,0.0,0.0,1.0,0.0,0.0,0.0,68.0,68.0,CHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +821,1.0,0.0,0.0,64.0,0.0,65.0,0.0,0.0,AFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDF,True +822,0.0,0.0,0.0,0.0,1.0,0.0,12.0,11.0,EGHGHGHGHGHGHGHGHGHGHGHG,True +823,39.0,0.0,0.0,1.0,39.0,0.0,0.0,0.0,DEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +824,79.0,0.0,0.0,79.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +825,0.0,0.0,0.0,9.0,0.0,0.0,9.0,1.0,HDGDGDGDGDGDGDGDGDG,True +826,1.0,193.0,0.0,0.0,0.0,0.0,0.0,0.0,ABBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +827,0.0,1.0,48.0,0.0,0.0,0.0,48.0,0.0,BGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +828,0.0,31.0,0.0,32.0,0.0,0.0,0.0,0.0,DBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +829,79.0,78.0,0.0,1.0,0.0,0.0,0.0,0.0,DABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +830,0.0,0.0,25.0,0.0,26.0,0.0,0.0,0.0,EECECECECECECECECECECECECECECECECECECECECECECECECEC,True +831,0.0,0.0,163.0,0.0,0.0,1.0,0.0,0.0,FCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +832,0.0,0.0,0.0,67.0,0.0,0.0,0.0,0.0,DDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +833,0.0,0.0,21.0,22.0,0.0,0.0,1.0,0.0,GDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +834,0.0,0.0,0.0,70.0,0.0,0.0,0.0,68.0,DDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +835,0.0,1.0,0.0,76.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +836,0.0,0.0,61.0,0.0,0.0,1.0,60.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +837,0.0,0.0,36.0,0.0,1.0,36.0,0.0,0.0,EFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +838,0.0,1.0,0.0,48.0,0.0,0.0,47.0,0.0,BDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +839,0.0,89.0,0.0,0.0,0.0,0.0,0.0,89.0,BHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +840,10.0,0.0,0.0,0.0,10.0,0.0,1.0,0.0,GEAEAEAEAEAEAEAEAEAEA,True +841,0.0,0.0,0.0,0.0,0.0,90.0,0.0,0.0,FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +842,0.0,0.0,0.0,1.0,0.0,0.0,0.0,183.0,DHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +843,0.0,0.0,0.0,8.0,0.0,1.0,0.0,8.0,FDHDHDHDHDHDHDHDH,True +844,0.0,1.0,0.0,0.0,40.0,40.0,0.0,0.0,BFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +845,1.0,0.0,0.0,11.0,0.0,0.0,0.0,12.0,AHDHDHDHDHDHDHDHDHDHDHDH,True +846,0.0,0.0,23.0,0.0,22.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECEC,True +847,0.0,0.0,31.0,0.0,0.0,1.0,0.0,31.0,FHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +848,0.0,0.0,0.0,0.0,93.0,0.0,1.0,92.0,GEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +849,1.0,0.0,0.0,0.0,0.0,0.0,96.0,96.0,AHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +850,1.0,0.0,0.0,142.0,0.0,0.0,0.0,0.0,ADDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +851,0.0,0.0,0.0,1.0,84.0,0.0,84.0,0.0,DGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True 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+870,0.0,0.0,1.0,0.0,50.0,0.0,51.0,0.0,CGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +871,0.0,0.0,16.0,0.0,0.0,16.0,0.0,1.0,HFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +872,0.0,0.0,0.0,1.0,28.0,28.0,0.0,0.0,DFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +873,0.0,0.0,65.0,65.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +874,0.0,34.0,0.0,0.0,0.0,35.0,0.0,0.0,FBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +875,0.0,0.0,9.0,0.0,8.0,0.0,0.0,1.0,HCECECECECECECECEC,True +876,0.0,0.0,0.0,0.0,94.0,0.0,94.0,1.0,HEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +877,0.0,18.0,0.0,16.0,0.0,0.0,0.0,0.0,BBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True 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+885,0.0,0.0,0.0,93.0,0.0,93.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDF,True +886,0.0,1.0,0.0,89.0,0.0,89.0,0.0,0.0,BFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +887,0.0,1.0,0.0,0.0,42.0,0.0,0.0,42.0,BHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +888,68.0,0.0,0.0,0.0,1.0,0.0,0.0,67.0,EAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +889,55.0,0.0,0.0,0.0,0.0,57.0,0.0,0.0,FFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +890,25.0,1.0,0.0,0.0,0.0,0.0,26.0,0.0,BGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +891,81.0,0.0,0.0,0.0,80.0,0.0,0.0,0.0,AAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +892,0.0,0.0,1.0,0.0,10.0,0.0,10.0,0.0,CGEGEGEGEGEGEGEGEGEGE,True +893,1.0,0.0,43.0,42.0,0.0,0.0,0.0,0.0,ACDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +894,55.0,54.0,0.0,0.0,0.0,0.0,0.0,0.0,AABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +895,43.0,0.0,0.0,0.0,0.0,1.0,0.0,43.0,FAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +896,1.0,0.0,0.0,0.0,97.0,97.0,0.0,0.0,AEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +897,0.0,25.0,0.0,1.0,0.0,25.0,0.0,0.0,DFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +898,0.0,0.0,0.0,0.0,26.0,26.0,1.0,0.0,GEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +899,0.0,0.0,36.0,0.0,36.0,0.0,0.0,0.0,ECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +900,0.0,0.0,0.0,0.0,1.0,0.0,89.0,88.0,EGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +901,0.0,1.0,142.0,0.0,0.0,0.0,0.0,0.0,BCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +902,1.0,83.0,0.0,83.0,0.0,0.0,0.0,0.0,ABDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +903,0.0,0.0,17.0,0.0,17.0,0.0,0.0,1.0,HECECECECECECECECECECECECECECECECEC,True +904,77.0,77.0,0.0,0.0,0.0,0.0,0.0,0.0,BABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +905,0.0,0.0,0.0,0.0,0.0,0.0,164.0,0.0,GGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +906,0.0,0.0,0.0,89.0,0.0,1.0,0.0,90.0,FHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +907,0.0,0.0,41.0,0.0,0.0,0.0,42.0,0.0,GCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +908,28.0,0.0,0.0,0.0,0.0,28.0,1.0,0.0,GAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +909,0.0,0.0,94.0,0.0,1.0,0.0,95.0,0.0,EGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +910,0.0,0.0,27.0,1.0,27.0,0.0,0.0,0.0,DECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +911,0.0,0.0,0.0,100.0,0.0,1.0,0.0,0.0,FDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +912,0.0,1.0,66.0,0.0,0.0,0.0,66.0,0.0,BGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +913,0.0,23.0,23.0,0.0,0.0,1.0,0.0,0.0,FCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +914,0.0,0.0,0.0,0.0,0.0,0.0,150.0,0.0,GGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +915,0.0,0.0,0.0,0.0,0.0,0.0,1.0,42.0,GHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +916,0.0,147.0,0.0,0.0,0.0,0.0,1.0,0.0,GBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +917,0.0,56.0,0.0,1.0,0.0,0.0,0.0,56.0,DHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +918,0.0,0.0,0.0,0.0,0.0,76.0,76.0,1.0,HFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFG,True +919,0.0,53.0,0.0,0.0,0.0,0.0,0.0,52.0,BHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +920,0.0,0.0,147.0,0.0,0.0,1.0,0.0,0.0,FCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +921,0.0,0.0,0.0,40.0,40.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +922,0.0,82.0,0.0,84.0,0.0,0.0,0.0,0.0,DDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +923,1.0,0.0,0.0,0.0,0.0,0.0,0.0,97.0,AHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +924,0.0,29.0,0.0,0.0,0.0,0.0,0.0,30.0,HHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +925,25.0,0.0,0.0,1.0,0.0,0.0,0.0,25.0,DHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +926,0.0,164.0,0.0,0.0,0.0,0.0,1.0,0.0,GBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +927,89.0,0.0,0.0,0.0,1.0,0.0,90.0,0.0,EGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +928,0.0,0.0,1.0,0.0,41.0,41.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +929,0.0,0.0,1.0,19.0,18.0,0.0,0.0,0.0,CDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +930,0.0,0.0,0.0,0.0,1.0,75.0,75.0,0.0,EGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +931,0.0,0.0,21.0,0.0,0.0,22.0,0.0,0.0,FCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCF,True +932,0.0,0.0,81.0,0.0,80.0,1.0,0.0,0.0,FCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +933,20.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAAAAA,True +934,0.0,40.0,0.0,0.0,0.0,40.0,0.0,0.0,BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +935,0.0,72.0,0.0,0.0,72.0,0.0,1.0,0.0,GBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True +936,56.0,1.0,0.0,56.0,0.0,0.0,0.0,0.0,BADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +937,0.0,0.0,0.0,0.0,0.0,96.0,1.0,0.0,GFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +938,0.0,1.0,0.0,88.0,0.0,0.0,0.0,88.0,BHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +939,1.0,0.0,0.0,0.0,0.0,0.0,0.0,175.0,AHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +940,0.0,0.0,84.0,1.0,83.0,0.0,0.0,0.0,DCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +941,0.0,0.0,83.0,0.0,0.0,0.0,0.0,85.0,HHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +942,1.0,5.0,5.0,0.0,0.0,0.0,0.0,0.0,ABCBCBCBCBC,True +943,0.0,0.0,0.0,68.0,0.0,0.0,0.0,69.0,HHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +944,29.0,0.0,0.0,0.0,0.0,29.0,1.0,0.0,GAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +945,0.0,0.0,1.0,0.0,0.0,0.0,81.0,82.0,CHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +946,89.0,0.0,89.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +947,0.0,0.0,0.0,78.0,1.0,0.0,0.0,0.0,EDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +948,90.0,1.0,0.0,0.0,0.0,0.0,91.0,0.0,BGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +949,0.0,0.0,0.0,86.0,1.0,0.0,0.0,86.0,EHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +950,0.0,0.0,0.0,42.0,1.0,0.0,42.0,0.0,EDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +951,85.0,0.0,0.0,84.0,1.0,0.0,0.0,0.0,EADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +952,90.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +953,0.0,0.0,1.0,0.0,0.0,90.0,0.0,0.0,CFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +954,62.0,0.0,0.0,1.0,0.0,62.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +955,0.0,20.0,20.0,0.0,1.0,0.0,0.0,0.0,EBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +956,0.0,0.0,37.0,0.0,0.0,1.0,0.0,38.0,FHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +957,98.0,1.0,0.0,0.0,0.0,98.0,0.0,0.0,BFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +958,0.0,1.0,0.0,0.0,189.0,0.0,0.0,0.0,BEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +959,0.0,0.0,0.0,9.0,0.0,1.0,8.0,0.0,FDGDGDGDGDGDGDGDGD,True +960,0.0,68.0,0.0,0.0,0.0,0.0,0.0,69.0,HHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +961,0.0,0.0,0.0,138.0,0.0,0.0,0.0,0.0,DDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +962,0.0,0.0,0.0,0.0,1.0,30.0,0.0,30.0,EHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +963,0.0,0.0,0.0,80.0,80.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +964,77.0,0.0,0.0,1.0,0.0,0.0,0.0,78.0,DHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +965,0.0,0.0,0.0,58.0,58.0,0.0,1.0,0.0,GEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +966,0.0,0.0,0.0,1.0,35.0,34.0,0.0,0.0,DEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +967,0.0,60.0,0.0,60.0,0.0,1.0,0.0,0.0,FDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +968,0.0,1.0,80.0,0.0,81.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +969,0.0,1.0,0.0,0.0,0.0,0.0,81.0,81.0,BGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +970,16.0,0.0,0.0,16.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADA,True +971,0.0,0.0,0.0,0.0,78.0,77.0,0.0,0.0,EFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +972,0.0,0.0,10.0,1.0,0.0,10.0,0.0,0.0,DFCFCFCFCFCFCFCFCFCFC,True +973,0.0,0.0,0.0,0.0,0.0,44.0,1.0,44.0,GHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +974,0.0,36.0,0.0,0.0,0.0,36.0,1.0,0.0,GFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +975,0.0,87.0,0.0,0.0,0.0,0.0,87.0,0.0,BGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +976,42.0,0.0,42.0,0.0,0.0,0.0,0.0,0.0,CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +977,0.0,0.0,0.0,57.0,0.0,55.0,0.0,0.0,DDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +978,0.0,0.0,0.0,0.0,0.0,0.0,64.0,63.0,GGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +979,0.0,0.0,0.0,0.0,1.0,96.0,0.0,0.0,EFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,True +980,1.0,0.0,0.0,71.0,71.0,0.0,0.0,0.0,ADEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +981,0.0,80.0,1.0,0.0,0.0,0.0,0.0,81.0,CHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +982,0.0,0.0,0.0,0.0,0.0,0.0,27.0,27.0,HGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +983,52.0,51.0,0.0,0.0,0.0,0.0,1.0,0.0,GABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +984,38.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +985,1.0,73.0,0.0,0.0,0.0,0.0,0.0,0.0,ABBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +986,0.0,0.0,0.0,1.0,0.0,0.0,61.0,0.0,DGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +987,82.0,81.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +988,0.0,1.0,0.0,0.0,72.0,0.0,0.0,72.0,BEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +989,93.0,0.0,92.0,0.0,0.0,0.0,0.0,1.0,HACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +990,0.0,1.0,0.0,0.0,60.0,0.0,0.0,61.0,BHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +991,0.0,1.0,0.0,0.0,0.0,0.0,32.0,32.0,BHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +992,0.0,0.0,34.0,35.0,0.0,0.0,1.0,0.0,GDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +993,0.0,0.0,0.0,0.0,54.0,0.0,54.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +994,0.0,0.0,0.0,1.0,0.0,39.0,0.0,38.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +995,0.0,0.0,0.0,0.0,99.0,98.0,0.0,1.0,HEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +996,86.0,1.0,0.0,0.0,0.0,86.0,0.0,0.0,BFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +997,0.0,76.0,77.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +998,0.0,0.0,19.0,0.0,0.0,0.0,0.0,1.0,HCCCCCCCCCCCCCCCCCCC,True +999,0.0,0.0,37.0,1.0,0.0,0.0,38.0,0.0,DGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True diff --git a/tests/results/nb_gm_001_3back.csv b/tests/results/nb_gm_001_3back.csv new file mode 100644 index 0000000..b2f89a4 --- /dev/null +++ b/tests/results/nb_gm_001_3back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,0.0,65.0,132.0,0.0,0.0,0.0,0.0,1.0,HCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCC,True +1,51.0,0.0,52.0,52.0,0.0,0.0,0.0,1.0,HCDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACD,True +2,0.0,61.0,0.0,62.0,0.0,0.0,61.0,1.0,HDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGD,True +3,40.0,0.0,0.0,1.0,0.0,0.0,0.0,80.0,DHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHA,True +4,4.0,0.0,1.0,0.0,0.0,6.0,0.0,0.0,CAFFAFFAFFA,True +5,0.0,123.0,1.0,0.0,0.0,0.0,0.0,0.0,CBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +6,49.0,0.0,49.0,0.0,49.0,0.0,0.0,1.0,HCAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAECAE,True +7,0.0,53.0,53.0,53.0,0.0,1.0,0.0,0.0,FBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCDBCD,True +8,0.0,0.0,54.0,55.0,0.0,55.0,0.0,0.0,FDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFD,True +9,57.0,0.0,57.0,0.0,0.0,0.0,58.0,1.0,HGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAGCAG,True 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+74,25.0,0.0,26.0,0.0,1.0,0.0,0.0,25.0,ECAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHCAHC,True +75,61.0,0.0,0.0,60.0,0.0,60.0,0.0,1.0,HAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDAFDA,True +76,0.0,0.0,0.0,41.0,0.0,0.0,0.0,20.0,DHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDDHDD,True +77,0.0,0.0,1.0,0.0,0.0,15.0,15.0,14.0,CGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGFHGF,True +78,6.0,0.0,1.0,6.0,0.0,0.0,0.0,6.0,CHDAHDAHDAHDAHDAHDA,True +79,0.0,124.0,0.0,62.0,0.0,0.0,0.0,0.0,BBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBDBBD,True +80,0.0,0.0,32.0,0.0,0.0,31.0,31.0,0.0,CGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCF,True +81,0.0,0.0,0.0,64.0,64.0,0.0,64.0,1.0,HGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGEDGED,True +82,0.0,0.0,83.0,0.0,0.0,1.0,41.0,0.0,FCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGCCGC,True +83,0.0,1.0,0.0,48.0,48.0,48.0,0.0,0.0,BFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFEDFED,True +84,1.0,58.0,0.0,0.0,0.0,59.0,0.0,58.0,AFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBFHBF,True +85,31.0,0.0,0.0,1.0,0.0,0.0,61.0,0.0,DAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAGGAG,True 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+92,0.0,0.0,22.0,22.0,22.0,0.0,0.0,0.0,DCEDCEDCEDCEDCEDCEDCEDCEDCEDCEDCEDCEDCEDCEDCEDCEDCEDCEDCEDCEDCEDCE,True +93,0.0,28.0,0.0,1.0,29.0,0.0,28.0,0.0,DEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGEBGE,True +94,1.0,0.0,54.0,0.0,0.0,0.0,54.0,54.0,AHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGCHGC,True +95,0.0,1.0,0.0,49.0,49.0,0.0,0.0,50.0,BHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEHDEH,True +96,15.0,0.0,0.0,0.0,14.0,14.0,0.0,0.0,AEAFEAFEAFEAFEAFEAFEAFEAFEAFEAFEAFEAFEAFEAF,True +97,0.0,50.0,1.0,51.0,51.0,0.0,0.0,0.0,CEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBEDBED,True +98,0.0,54.0,0.0,0.0,0.0,0.0,55.0,53.0,GBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBG,True +99,0.0,0.0,50.0,51.0,49.0,0.0,0.0,0.0,DCDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECD,True +100,0.0,29.0,0.0,0.0,0.0,0.0,29.0,29.0,HBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBG,True +101,0.0,0.0,0.0,33.0,0.0,0.0,1.0,65.0,GHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHDHHD,True +102,1.0,49.0,0.0,0.0,49.0,0.0,0.0,50.0,AHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBHEBH,True +103,22.0,1.0,0.0,0.0,23.0,0.0,0.0,23.0,BEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEH,True +104,114.0,0.0,1.0,0.0,0.0,57.0,0.0,0.0,CFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAAFAA,True +105,0.0,0.0,34.0,0.0,68.0,0.0,0.0,0.0,ECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECEECE,True +106,27.0,1.0,0.0,0.0,27.0,0.0,26.0,0.0,BEAGEAGEAGEAGEAGEAGEAGEAGEAGEAGEAGEAGEAGEAGEAGEAGEAGEAGEAGEAGEAGEAGEAGEAGEAGEAGEA,True +107,59.0,59.0,0.0,0.0,1.0,59.0,0.0,0.0,EABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABFABF,True +108,0.0,0.0,1.0,17.0,16.0,0.0,17.0,0.0,CGDEGDEGDEGDEGDEGDEGDEGDEGDEGDEGDEGDEGDEGDEGDEGDEGD,True +109,9.0,0.0,9.0,0.0,0.0,0.0,11.0,0.0,GGACGACGACGACGACGACGACGACGACG,True +110,64.0,63.0,0.0,0.0,0.0,0.0,0.0,63.0,ABAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAHBAH,True +111,1.0,66.0,0.0,0.0,67.0,66.0,0.0,0.0,AEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFEBFE,True +112,0.0,19.0,0.0,0.0,0.0,0.0,0.0,36.0,BBHHBHHBHHBHHBHHBHHBHHBHHBHHBHHBHHBHHBHHBHHBHHBHHBHHBHH,True +113,0.0,0.0,20.0,1.0,19.0,0.0,0.0,20.0,DHCEHCEHCEHCEHCEHCEHCEHCEHCEHCEHCEHCEHCEHCEHCEHCEHCEHCEHCEHC,True +114,21.0,1.0,21.0,0.0,0.0,21.0,0.0,0.0,BFCAFCAFCAFCAFCAFCAFCAFCAFCAFCAFCAFCAFCAFCAFCAFCAFCAFCAFCAFCAFCA,True +115,0.0,0.0,0.0,44.0,0.0,0.0,43.0,45.0,HDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDHGDH,True +116,0.0,0.0,48.0,0.0,1.0,0.0,0.0,97.0,EHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHHCHH,True +117,1.0,0.0,0.0,0.0,0.0,51.0,0.0,26.0,AFHFFHFFHFFHFFHFFHFFHFFHFFHFFHFFHFFHFFHFFHFFHFFHFFHFFHFFHFFHFFHFFHFFHFFHFFHFFH,True +118,32.0,0.0,0.0,33.0,0.0,0.0,0.0,32.0,DHADHADHADHADHADHADHADHADHADHADHADHADHADHADHADHADHADHADHADHADHADHADHADHADHADHADHADHADHADHADHADHAD,True +119,1.0,0.0,41.0,0.0,0.0,0.0,41.0,40.0,ACGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCGHCG,True +120,0.0,29.0,0.0,30.0,29.0,0.0,0.0,0.0,DEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBDEBD,True +121,0.0,0.0,54.0,1.0,54.0,0.0,54.0,0.0,DEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGCEGC,True +122,1.0,0.0,0.0,18.0,0.0,17.0,17.0,0.0,ADGFDGFDGFDGFDGFDGFDGFDGFDGFDGFDGFDGFDGFDGFDGFDGFDGFD,True +123,13.0,0.0,0.0,14.0,0.0,1.0,14.0,0.0,FGDAGDAGDAGDAGDAGDAGDAGDAGDAGDAGDAGDAGDAGD,True +124,0.0,0.0,62.0,0.0,63.0,0.0,62.0,0.0,ECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGECGE,True +125,0.0,0.0,0.0,0.0,52.0,1.0,0.0,104.0,FHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHEHHE,True +126,39.0,0.0,0.0,39.0,0.0,0.0,1.0,38.0,GDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDAHDA,True +127,0.0,31.0,0.0,63.0,0.0,0.0,0.0,0.0,DDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBDDBD,True +128,0.0,1.0,0.0,56.0,0.0,57.0,0.0,57.0,BFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFHDFH,True +129,1.0,0.0,42.0,42.0,42.0,0.0,0.0,0.0,ACDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDECDE,True +130,0.0,4.0,0.0,4.0,0.0,0.0,4.0,1.0,HBDGBDGBDGBDG,True +131,0.0,0.0,0.0,0.0,1.0,24.0,24.0,25.0,EHFGHFGHFGHFGHFGHFGHFGHFGHFGHFGHFGHFGHFGHFGHFGHFGHFGHFGHFGHFGHFGHFGHFGHFGH,True +132,0.0,0.0,131.0,0.0,0.0,0.0,0.0,64.0,CCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCCHCC,True 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+967,54.0,0.0,54.0,53.0,0.0,0.0,0.0,0.0,ACADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADCADC,True +968,10.0,0.0,10.0,0.0,12.0,0.0,0.0,0.0,EEACEACEACEACEACEACEACEACEACEACE,True +969,0.0,0.0,0.0,0.0,0.0,0.0,125.0,62.0,GGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGHGGH,True +970,0.0,8.0,1.0,9.0,0.0,0.0,8.0,0.0,CDBGDBGDBGDBGDBGDBGDBGDBGD,True +971,0.0,0.0,0.0,66.0,66.0,67.0,1.0,0.0,GFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEFDEF,True +972,63.0,0.0,0.0,0.0,127.0,0.0,1.0,0.0,GEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAE,True +973,0.0,0.0,11.0,0.0,0.0,0.0,21.0,1.0,HCGGCGGCGGCGGCGGCGGCGGCGGCGGCGGCG,True +974,0.0,0.0,39.0,0.0,0.0,40.0,40.0,0.0,FGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFG,True +975,0.0,0.0,1.0,31.0,0.0,0.0,62.0,0.0,CDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGGDGG,True +976,0.0,54.0,0.0,0.0,0.0,1.0,54.0,55.0,FHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBHGBH,True +977,0.0,0.0,18.0,19.0,0.0,18.0,0.0,0.0,DFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCD,True +978,126.0,63.0,0.0,0.0,1.0,0.0,0.0,0.0,EAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAABAAB,True +979,19.0,0.0,0.0,0.0,0.0,1.0,0.0,9.0,FAHAAHAAHAAHAAHAAHAAHAAHAAHAA,True +980,0.0,0.0,32.0,32.0,0.0,33.0,0.0,0.0,FDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFCDFC,True +981,15.0,0.0,15.0,0.0,16.0,0.0,0.0,0.0,ECEACEACEACEACEACEACEACEACEACEACEACEACEACEACEA,True +982,0.0,0.0,55.0,0.0,0.0,56.0,57.0,0.0,GFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFGCFG,True +983,0.0,0.0,32.0,0.0,1.0,32.0,31.0,0.0,EFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFCGFC,True +984,0.0,0.0,0.0,41.0,1.0,40.0,40.0,0.0,EDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGDFGD,True +985,0.0,0.0,0.0,0.0,5.0,6.0,5.0,1.0,HFGEFGEFGEFGEFGEF,True +986,0.0,19.0,17.0,0.0,0.0,0.0,0.0,18.0,BBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBHCBH,True +987,0.0,0.0,0.0,0.0,0.0,0.0,6.0,10.0,GHGHHGHHGHHGHHGH,True +988,0.0,0.0,69.0,0.0,36.0,0.0,0.0,0.0,ECECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCECCE,True +989,1.0,0.0,0.0,0.0,0.0,19.0,0.0,37.0,AHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHFHHF,True +990,67.0,0.0,0.0,0.0,0.0,0.0,0.0,33.0,AHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAA,True +991,0.0,0.0,16.0,18.0,0.0,17.0,0.0,0.0,DFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFDCFD,True +992,1.0,0.0,50.0,50.0,0.0,0.0,49.0,0.0,ACDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCDGCD,True +993,0.0,40.0,39.0,0.0,39.0,0.0,0.0,1.0,HBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEBCEB,True +994,0.0,30.0,1.0,0.0,0.0,0.0,30.0,30.0,CBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGHBGH,True +995,126.0,0.0,1.0,0.0,0.0,0.0,0.0,63.0,CHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAAHAA,True +996,45.0,0.0,45.0,1.0,0.0,0.0,0.0,45.0,DHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHACHAC,True +997,15.0,0.0,0.0,0.0,29.0,0.0,0.0,0.0,AEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEEAEE,True +998,0.0,4.0,1.0,0.0,0.0,4.0,0.0,4.0,CHBFHBFHBFHBF,True +999,0.0,100.0,0.0,0.0,0.0,0.0,0.0,51.0,HBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBHBBH,True diff --git a/tests/results/nb_gm_002_2back.csv b/tests/results/nb_gm_002_2back.csv new file mode 100644 index 0000000..33538c3 --- /dev/null +++ b/tests/results/nb_gm_002_2back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,4.0,2.0,2.0,2.0,2.0,1.0,0.0,5.0,BHCHDHDAEBEHAFAHAC,True +1,0.0,4.0,1.0,2.0,4.0,0.0,0.0,0.0,DBEBDBCEEBE,True +2,5.0,10.0,14.0,6.0,16.0,18.0,12.0,12.0,CFFGHCFCGHEDCCACECBGEGFGAEBGHFDCEEDCCEGEGCBBBHCCECHBHEHBHDEDAFAFAFHFGFGFGHGHEFFFEFEDHFEFEFBBB,False +3,12.0,15.0,11.0,20.0,13.0,17.0,17.0,22.0,AFAHGHGHGBEBCDDDDHHHABCEHEHEBBBAHADADCFHHHHHFEFCBDDFDGDEFCAGGFEFBDGEHECCBCFFFFFFHGEBBHHCBCACHHDDBFGGGGEGEAFDGDADGDGDGBEBAAHDDFH,False +4,4.0,4.0,8.0,8.0,5.0,7.0,4.0,2.0,FGDGECDCECGCDADAHFDFCFCGAFCDDDABEBHBEFEFBC,False +5,15.0,15.0,15.0,16.0,16.0,14.0,9.0,13.0,HGDGBFDHDADHBBBBBHBAAGBCEABCGFAFAFBGBCBFGDDDEAAAHDFACECECHFHFHFCFHEGEFEFDFDAAHDEECDABFCCCCGBEBDAHCECHCHEDEDEDAGEE,False +6,17.0,17.0,9.0,6.0,15.0,13.0,15.0,12.0,BEBEBHAGCFEHHABAHDEDGHFBFGFCAABAGFFFAFGECEBEAEAFBFCEBEGHGDBEFABABEGEHEHBGBGDADACAGHGHGBGBACGCAHFFBHAECDC,False +7,12.0,7.0,7.0,6.0,9.0,8.0,5.0,6.0,CEGBFEFEFEHCCDEBCCHBBBGAHACBGGDBDADACADHDHFEAEAEFGFAAEAHAFAF,False +8,9.0,13.0,10.0,11.0,12.0,15.0,11.0,12.0,CGCFDBDFHHEHFFGCDHEHCFCFAAEGDCEGHGCFCBBBCBGFGHGDFDBDADHBBEGAGABABHBEBEHGHADAFEFCFDBDEFEHEFEFA,False +9,13.0,26.0,23.0,14.0,20.0,18.0,19.0,27.0,HECEBEFFHFDCCFGBCBDBAHGHGCBBABHEFAFEBEBHBHGGCHBGGCCCCCFCBDDDEDHDEEEAAFAFGFDFCGBGHEHDHGHAFABCGGEHEHFBGBADEBEBEAAHBDCCFGGHHHBHBHGHBDBEEAEGCGCBCHCEFFFFCHDHCHDHABCB,False +10,14.0,18.0,15.0,13.0,15.0,19.0,18.0,11.0,AFACABDDFBBBEBECECGHFBFBECDCEEEDGDBHHGCBDDAFCBAAAGHCHCHEAFBFDHAHCFFAAAHBBBFBFBHGFBCBCFGGGHGDGDFEGEFCFEDGDGAGEGCGEGEFEFAFDGC,False +11,21.0,20.0,21.0,13.0,15.0,26.0,21.0,21.0,EECEFFHGCADHGEGEABCCFDEBABEBGGCACHFHFBFBFBAHGBGCGHDCDABHHAGABFHEBCFEGDFDFDFAFBCBCAHACFGFBFBFBFBDACCBCHFHEGEDFDFCAAAGGEBFAAACACHCHFGFBFGHGHAEAGCCEDDFHHHGHGHGDE,False +12,17.0,26.0,17.0,23.0,17.0,11.0,26.0,21.0,ABGCACGDDFHFHBCEHEAGBGBEBAHEBEBFAAHAFBCEGDGBAHGGGGFGDDDBABABHGGGCGDGHGHDACAEDEFECHGEGDABGCHCDDDDCBCBADAHCHGBGBGEHDCDBBFBABHBHBFBACHDEEHGHECDCDHDEFEDECFGHGBFBD,False +13,24.0,21.0,23.0,20.0,15.0,14.0,30.0,24.0,AHHHHAFEDHAFBFGFCFGADADCDGBBBBGDGEGBCBHGGGGCGFBFAGGGGHEEFEGHGHABCBFHGAGACBBDEDHDHDGBCACAHGCACEHECACHBHDCGCECADGDGDABADHFGCGAGAHHBGFDCHBHCAAABEEFDFDBDBEADAHGEGEHECCCBCFCAHD,False +14,1.0,0.0,2.0,1.0,1.0,1.0,2.0,2.0,DECGCGAHFH,True +15,7.0,7.0,10.0,5.0,8.0,4.0,8.0,9.0,HBABHHEEGAGAGEGHCDEECHCHGBCBCDDAEGCBCGEAEFDFBFBFAGCHCHCHAD,False +16,14.0,19.0,14.0,7.0,10.0,15.0,19.0,7.0,CEAFFGHGEGFDFDCACAGBDEAFCEDDFAHHFDFGBEACGCGBGAFECECFGHCEBAFGEGCBABEBHBHBACAGAGDGHBABCBCBGFGFGFGBBBBFBCBGA,False +17,17.0,15.0,14.0,12.0,10.0,9.0,17.0,6.0,EBACADACGBGBAFGHGHADCDGAAFFFADABAHGDGABBCBCACACECHFBFHDCACDGEBADDEGGGEDADFGFGCGFBBABCBEBDBCHGEGEGECE,False +18,14.0,22.0,17.0,9.0,14.0,10.0,25.0,20.0,EHCHAHEHAHCHCGBGCGCGAEBFBFGGCEFGBGHAHCBABABHHGHGCACHDEDBBABGGDGDEBBBHHGCAEGBFHGEGEGBCCGCDFBBGBFBDAEEHHHCFEFECEHGCGCBHDADFDAGAGAGFBB,False +19,13.0,27.0,12.0,18.0,19.0,17.0,20.0,18.0,BFGCGBHAHAHEFEDBABEBEDADGGGGBAFCGEBDFHBHGHGCBBEGEGBHDHDHBCBCACDBFHHCHBGAGAGEDADADCDCACGHEEEEBDFDFDHDCGGBGDEBBBABEHFHGEFFFBADHEFFCFDEBEBFFEBHBFBG,False +20,11.0,10.0,7.0,8.0,8.0,7.0,11.0,4.0,BGBABGHGCGFBFAEBGGEDEFAHEHACDCDADBGGAGAGADFBFBCBCEFBFDHDACCDAGAEEE,False +21,22.0,20.0,18.0,24.0,13.0,11.0,16.0,21.0,DADADHCACFCHEDAAAHGDDHAGCDEDEGBHAHBDBDBGHHHCHCECAAAEFEDECEDBHFABGBCAGDBEGEBABHFCBBABDFDGHGCBFBCCDHDHDGDHDHCHBGADAFACHEHBDCDAFAFAFAGGCGCFHGBDBEBEG,False +22,8.0,10.0,11.0,7.0,8.0,15.0,4.0,11.0,CBAEGDGEHEBGBFBFBDHCHFHBAEHFFGFCFBFCFEEHABECFFFFACAEHHDCDCDHDHAHCFCBCBAADF,False +23,32.0,19.0,21.0,23.0,13.0,27.0,21.0,27.0,GHCABDGDFFFAHHHEAEHGAGAGHEFEGBCFAFBFGCHCHFHBGCAFFDFDBACACHCHCHBFGFEACAFABEBEBHHGHFHAHGGAGAHAFCGDHDHAFGCBCHDAAAAAAFCFHGEFFBEBEDDDFDBCBDDDCGFAFADBDBEBCAGGHDFDFBCDEAGAHCCEHGHAHCDDDDABAFA,False +24,26.0,30.0,18.0,21.0,29.0,16.0,21.0,21.0,GDGDADAGAGDEHCDBDHAHEHFHAHAFBHBHGCEBHBDBHBHBEEABABABAEECEGEGAGADHDBEEGBCAADHGBFBCEAAHDEBEBFBFBFCCGCEFBABAEDBGFGBGCFCGEACDFEFBHDADFHCEAEBDHDCGBEFGCDCACDEBEGAGAEAEFDFBBEHEGEGHCACEFBHDH,False +25,17.0,15.0,10.0,21.0,16.0,11.0,16.0,22.0,BDBDBHHHAAGAEHEHCHCDADEBGHDAGEBHGAABADADEDECEHAHFBGCGBEHCGADFBHECGHHFFFHFBDDDDDFDFDFHFEDEDACAEAEBDCHHBFBABCBGDGEAECHHGHGEGHDAGGG,False +26,12.0,13.0,16.0,11.0,17.0,10.0,17.0,12.0,GEECBGFEEDHCEFGFEAEAHGEGEDDDHDCDCBHBCBCFCECEGAGAGAHECFCEAAFGFGCEHGHBBBGBGBCBDHEAEFHFHGBCDGGACHCGCDADAEBFBADH,False +27,14.0,11.0,17.0,13.0,14.0,21.0,16.0,19.0,AAECGGEGHCACACACHBHADCECBDHDHDFCFGHGDDEDHHHAHDFDACHBHAFBHHAEEECGGFGEGEBEFCFAEAEFFBFBFDGDGDGHFACCDFHFCGBBHBCGGFGEHEFFFFHFCBCAF,False +28,14.0,15.0,12.0,21.0,15.0,9.0,13.0,21.0,GGHGEDHFCFCACBCADAEEEEAHDGAGHGHEHEHBBECEDBBBDBEGDGBAEABCCABBECDDDFDFHGHGHDHGHGHDADHHCHBHCCBAFHFDDDEDHFHAABDFDFEGEAADBDCH,False +29,18.0,19.0,27.0,26.0,29.0,30.0,16.0,16.0,DEFFFAFAGDGEEBFBFGEBADACADFDCEEDEDFDCDEBBGDGHGHGFFFDFBEBEHCHFDCDCEGFGFHFEFCGBBDCHCGCDADEGEGCFAAEHEHFDACGCEABBDECBCBCEFEFBFCFCFEHEHDGACEBAGCEFEBACCCAEDHDHBCFCDEFFHDHDHDCFCAAAEBEBFDHA,False +30,5.0,11.0,5.0,8.0,3.0,2.0,5.0,1.0,BBFGGBABFGCCCDADAHBEDCDBABGEAECBDBDBDBDG,True +31,28.0,17.0,19.0,16.0,18.0,11.0,17.0,33.0,DHAFAHAEAHDHFHFAFADHCGGGDGDGHEBDHCHBHAEBCBCFEGHHHBHCAFDHEHEHCDAGBCBAAAGACCBCAFGBHEHBBEAHAHAFAEACGGEHAFABEDEDFDCGHEBGAGEEAEBBHDEDECHCGABHGHAHAHBHCHCHCHDGACACDFD,False +32,5.0,10.0,12.0,17.0,19.0,17.0,17.0,11.0,EEBHBFFFDDEDCCAGEFEGGDGDFFGEGEAEDEFCFCGCGCGFAEGECDHHCEFDDHDFDABFDECECEHEFDDGDGBBFBFHHGCECEFEHAHDHDGBBFBGHGBG,False +33,4.0,13.0,10.0,7.0,4.0,8.0,11.0,7.0,CGBHBCBCBHFHFECBADGBGBGBDBCFAGDBHGFGECEHBGBCCACFGFGFGDDDFCADHEHB,False +34,22.0,27.0,22.0,21.0,21.0,28.0,21.0,21.0,BABFBCCCCGCDCAGABAHFBAHCBDBDHDCDCDEFFHBHBCBCBEHDAGAEFBBEEEBEGAGHGDGCGEBFBDEAECCFCFGDGDGHBHAEFFFECCADHFFBGHDHEGAAEDEFEFCDCDCDEFCHADAEHFDFHBBEBEBFBFAFGFAAHGHGFFAFGGBABGHGBFBFDFHCHAHEGDA,False +35,24.0,23.0,21.0,17.0,28.0,15.0,20.0,21.0,EGHGAGEGCGDFFCEEEEEAHGEGFGFBCBGBDBACHCAGDDDDEDEHACGCECAFAFEFHCHCEFHDHEHBAEADBDBAFCHCEEEEHBHBECEAEAFGGGGCCHBHAAACABBEHFHBDFHHDHBGCAABEBGAGABBFADADEBBBBCDCACFGFHDCEHEBGADE,False +36,16.0,12.0,18.0,16.0,29.0,20.0,25.0,11.0,EEEBCFFDHDBBGHGHGEFDFACCCFCGAECECEAGFFFCFDAHAEEHGGGBGBGADDGDGEGCCBFEHEGEHACDGDGCCCFCEAFAEGEGBGFGBBBHFGDGFGAAHADADCEEEEDEAEFEAEBFFFHEGECEGEHECAFDDDB,False +37,1.0,6.0,2.0,11.0,2.0,11.0,4.0,7.0,DBFFFHHADFFEFBDBFBGDFFEBHBHFHGDGDGCCDDDDHDHF,True +38,11.0,12.0,15.0,5.0,3.0,15.0,15.0,13.0,HCCCCAEBGFCFBGAHHHHBAFGCGCGCGFGCAABFBABHBFBCAFHFAFGCDBGBGAGFCBBAADHDHDCGEGHGCGFFHFHDEFHFC,False +39,33.0,14.0,21.0,23.0,21.0,18.0,25.0,28.0,DHAHAHADGDAFAFGCHCHEHCHABACEDDDCGBHAEFFGCADADGBGCFFFGGHBAAFGGHFHFHECFCHCHBDEFGADDCGGGHEBEDEBEBEDFHCAAAACFGFBFBFADAEGBDCAGACACAFGEEECDDDDCGGGEEEEEGCADHHHHAHABAHGBBCACHEGGHDADADAHAHEHAH,False +40,9.0,21.0,8.0,6.0,13.0,11.0,9.0,15.0,HEBEGEGAGEBBBHFAFABCBCBEBCBEAFHGGGHEHCHBEDFFAFAHDBFBFBEBDFHHDHBHCHBHBDEFABGBCEDEBCACHHEAGBGF,False +41,13.0,18.0,18.0,16.0,8.0,20.0,16.0,13.0,AGDGBCDHFADAGFFFHHCFCFEBGBGFGFGCGCHHHHCGFBFGDHABCBCGDGECEFBFCACBDBDCFAFBDEDCFFBHGHBEBABDFDFDHDHACABDBAFAFDHEGACACBEECGCBDG,False +42,21.0,15.0,14.0,22.0,14.0,22.0,16.0,21.0,ACFDFDEDFDBAFDCDCDFFFFFACHCHGEDFCFEHADACEHEDEBAFAGGHGEDADFDHDHDHGADAGCCCFHBDBGBDEGEBHGFGHAHFBFBFEAABABACDDAHHGFGBGEGHFEABHBFEHHHGDFDCACABABGECHAH,False +43,17.0,19.0,23.0,19.0,19.0,21.0,20.0,22.0,GDGFGEDDDDDDFDFDFEHBHDGAECBHDEGHGEEDEBEDECGGAADAFAFADECFCDGDGFBHGCBHBACAGACFCGGGBGCHFHEHECECAHFHFGCGHBFCGCBCFEHEGEHBBAAABDHFBCCCCFFFHFCABFBHBHBEDAFEHBHACABECHCH,False +44,2.0,1.0,3.0,4.0,5.0,3.0,6.0,5.0,CHCHFGBGEHFDAGADEDEGGFGEDEHCH,True +45,17.0,20.0,26.0,20.0,18.0,24.0,15.0,12.0,BDEFBBBHHECFCFCBBFEDDADADGECEHEFCGCAFDCGCFFEDDGGHHHHHAFAFEFAFDFDFDEDFAACFCFCDCBBBCGCGDGDFCGCGBDCACBHDHEECBBEBECFCHGBGEGABCDCEFHFGACDFAFAECEBEBDACABAGFBA,False +46,5.0,7.0,11.0,5.0,5.0,3.0,8.0,10.0,CBDHFHCDCEGEHCHCHCHEGCGCGBBBBADAHGDGBACGEAHBHFGFCECAHD,False +47,5.0,4.0,4.0,5.0,0.0,1.0,5.0,3.0,ACABGBHBHBGDCACHCDAGFGAGDDD,True +48,21.0,22.0,13.0,24.0,16.0,18.0,24.0,19.0,DBDGAGBGFHFCABGFECEGBGHHEACDFDGCGBEBGDAFAHADADAHHBHBHAGABADEBFDGDBDGDGCFAFAFDDDDECGFEFEAHAHEHEHCBCDADGBFBFAEBCAHFHEDEGBBFDEHEBDHFGCGHGHGBGCDABCBDGHGBGDCEAFAF,False +49,5.0,12.0,11.0,8.0,8.0,7.0,11.0,9.0,FCFDGDHBEBECFBBHFCFCGDBCCCGCECECBDBGBEHDDBCAGAEHEDFDHGEGAHBHGAGAGFHBHBG,False +50,2.0,7.0,7.0,4.0,6.0,13.0,10.0,11.0,BBFEFEFHAHFDFGHEBABDFHBHEFGFGHEHGGGFDFEHCBGBFDFHFHCCGCGHGCCC,True +51,5.0,7.0,11.0,12.0,13.0,9.0,8.0,13.0,EFFBFDAAECCCHDHBHFEDBHBHDHDGGGGECDGHCFEFEDEDCDCDEDCCHFEFEGCGBHEHBHAHAGDFCEAEHB,False +52,15.0,6.0,11.0,6.0,11.0,16.0,3.0,8.0,BAEGCCEAHBFCCHFABEHEFDCHEBECACECEAFGFEFEFBFBFAFADADACACDFGFAFAFEFDAAHFDCAHHH,True +53,20.0,14.0,19.0,11.0,13.0,12.0,10.0,17.0,CHCECEHEGAHBFGHCHABCBCDCECEDAHACGCADDBBGFGFGFHAAACACFBEGGAGAEHCAAAFDFDCHBDBHGDFDHCBEFEBCBABHHHHDHCHDFEFABEBECAAAEACF,False +54,18.0,14.0,15.0,22.0,24.0,20.0,25.0,23.0,EGGCGCGDEDEBCBFDDDBFHDDGFBFEEEGDBDBEHFDFEACACADABEFDCECGGHBDCDBAGHGFBFECHCFEDEHEHAHEEAGCEEEEFGFHFAAGEEHHHHAHAHDEFGDGDBCGAGHFHFHAHAHDHDBFBFCEGGGGGGGHAADAGCDFFAHCB,False +55,3.0,4.0,2.0,5.0,2.0,5.0,3.0,1.0,EHAABABGBFDFGFGEDDFDCBCDF,True +56,9.0,9.0,8.0,11.0,11.0,13.0,8.0,11.0,ECFFFBCDEDAFEBEAFGFHFHFDEHEBEHEGBFEFHBABCCAGAGBGBDFHAHGHFCFDHDABADEDEDAHGGCDCHCD,False +57,10.0,13.0,10.0,15.0,7.0,9.0,16.0,11.0,HHCFEGEGEDFGABEHEADCHGHBDFDGDGHGCGBBDDCDCDBDBHCDEBAHACCFDGDFAFAFDDAGAGHGCGBGBHACBGBGAHEBFBF,False +58,15.0,15.0,14.0,21.0,27.0,24.0,20.0,28.0,FAFEFAADAGFBFACBCBHHCGFGFAFHCEGEGHHBDBFHFHBEGDGDAEEHEGCGDGHCDGDEHFHGCEEEGEGEDBDEEEEHHHHCHDAGFEBHFHAHFHFDDDCACHFBDDHDGDFDAGGEAEFBHEEEEBEHEFFCFCFDBHAFADCGCGFHDHEBABHB,False +59,11.0,16.0,18.0,17.0,22.0,31.0,15.0,17.0,FCECFCFCFBHCHBGBFHGEDADADEFEFHFDFDADEEADHGAEAECGDGCCFHFGFHFHFHFBFBFCEEEBEFFDEGGBHBEBHFCDDDDGHAFBFBFCACHCAFGCGHHEDCBFEFABCDCEGGGDAEBBBEDEFFFFECGHEHF,False +60,11.0,9.0,7.0,2.0,10.0,10.0,11.0,9.0,HGHCDCHCACBCEGEGEGEBBHCFGABEBFAEHHFBFAAGHGHFHABABCGEGFDEAAABFEFEFGFGA,False +61,23.0,23.0,21.0,24.0,24.0,17.0,27.0,24.0,EDGGCBCFCGCGCFCGCDCBAACHFHFHECACAGAHFHDBDEHAGADHGEGEBCAEAGDHAADDDDCEAEADBGFDBBBBDHDGDBBGCAAEHEGDGBGBFHCGCDBBBEFHFDAGHCDCHFHFGEHEGEGHGBEFACADAFCBGBGBFHDEDEDFBFEGHGHAHAEEEEGEDHAHACEFBHB,False +62,21.0,13.0,9.0,12.0,17.0,15.0,25.0,10.0,HFGFGBGEDEHGHAHFHGAAAFGHBFACGDBEBGAAFEGEFEFBGAHDEDECBCBFBEGAGAFCCBBDBAGABAGGGGGECDADAGAEFEDGACADDCDHDEAFHFHFGGGFGCABAEEEGE,False +63,6.0,6.0,3.0,12.0,7.0,8.0,6.0,13.0,FHEBEBHGHDAGHDCDEDEAFCFCHEEBAAFDDDFDHDAGBGFDHGHAHDHEHFHFHBDBG,False +64,6.0,15.0,15.0,8.0,14.0,13.0,8.0,8.0,CCEDEDBHHGDCBEFEFCCGCEAGFGEGECAHAHGBCFHACEBEBEGEFFFFBDBFBHBDDEDCBCBHBFGFHEAEBCBCFCBCAFD,False +65,6.0,4.0,3.0,4.0,6.0,8.0,5.0,5.0,CGCFEFAFAEEDEHCHBBDAAFAGHEHEBFDHDBAGFGFGF,False +66,17.0,8.0,15.0,6.0,16.0,16.0,11.0,12.0,AFGFGFGHGFECECECHAECCCFAHAFAEHGGCEBAFAEAEFGGHCBFAAEHFHFGBHEHGAFBFHCECEADFDBDBCACACAEAEBEDDACBDFHFHEGC,False +67,24.0,12.0,23.0,14.0,18.0,18.0,15.0,12.0,CCCFCFBHAEEDFDBAADAEAEABDBDGEHEGCCCACECHGEGEDECACFCFCHBFBAGAFFGHADBEBAAAAFAEECEDHDHECGGBHHCHDBGBABAGEFFGFAFADACADAGADCHFECGFGFHFCDCEGFCC,False +68,31.0,17.0,27.0,38.0,29.0,28.0,14.0,16.0,ACACBCFDGBHBDEGEAHDDEFEFEFEFDDHECEBDFDAEAEFECECGCHAHAHCBCDAHBDDDDEDEBEHGDDAFEFCFDDBCGAGACCECAADADABAFEDACGCAFAHDFDBDGCECBGBFFCHCGAEDFFFHADFDADGFAFADEDHABAGAGEHEFBFECEDEDCGEADADFDHBHDFDCBCFCDAFAECFCEHB,False +69,5.0,4.0,3.0,4.0,2.0,3.0,6.0,4.0,DAHAGAHAHAHFGCGEBDFDEDGGCFBBGBC,False +70,5.0,7.0,9.0,5.0,2.0,11.0,6.0,10.0,HAHDHDHBGBFCACDCHFBBHBHGDEACACEGFCDHBGFGFGFCCHBFFHFCFAF,True +71,11.0,10.0,6.0,19.0,14.0,23.0,11.0,9.0,FHFEADABECHFFDFDFHFEDECEFEFEFAFHDADAEADDCAGFGBBHGDGABDDFFFFDDDADEEGFGDABCDGGBHDHFGAGBHBHBEBEGFFFFFCCEDE,False +72,25.0,17.0,20.0,19.0,16.0,13.0,17.0,22.0,GDCDHGBEAEGDGEBDBDHDCDCBHDEAEHDCEFAAABCDCDABAGADADCFAFCGCACAFFBAHGCGCGEGEACHHECACECEHEGGFBDHFHAHAHGGDGFCECHFHFHCHFABABFDGABDEDABABHEACAFDHHGHAHBBBBEH,False +73,15.0,19.0,20.0,23.0,23.0,21.0,22.0,23.0,GFGFECGCEEGHFCBCFDDDHHGBGHGHDCDCFHAHCCCFHAADEBEHEDEDADCDCABEGEFDFHCHGGAHAHFCFCEADFFECGBDBDBDCCACADHGCGEGHFHGHGBFADEBEBEDGDBBACEEEHGBDBFFFFDGEGDGDGFBEHHHHAAEAEFBBBBEFH,False +74,3.0,11.0,6.0,11.0,10.0,12.0,5.0,7.0,ECHFHDHEFFHHDCFGEGFDBEBEFFFDBCBFEDCDCFEBBFADDBDBGBGBGBAHAHFDEDECE,True +75,21.0,13.0,22.0,19.0,30.0,19.0,18.0,19.0,HAHEEEFEDHDFDBHBGCCEEFEGGHGHCCCCCHGECEAHDBDBEFGHCACGBEFEHAFDFACAFEEEHABAGAFDGDADADAGBCBAEADAEFHCDCFGEHFHDEDCDFEFCCCEAEAEGGABFGEDBDBHBCCECEHEAEFGHGHDDAEAEHCFGFGFB,False +76,14.0,30.0,18.0,20.0,25.0,19.0,27.0,30.0,FCFBAEDEGEHEBGHGFEFCGDBDGGCGCGBEBHBHEAAAEECBCBCFHFCFDGAEHHFGGGGGHCHEHBABGBGHHDFAEBDBDBDBCCHAGGEGDGCCBCHFGFGHGHBHEFGHBFBCBHEHBBABCBHBCGEHEADDDBHFHAADEDBFHFEEGEDHDHDEDBDFEFEHCHAEGDHBFBA,False +77,25.0,17.0,30.0,29.0,22.0,22.0,23.0,24.0,CCHEAEHBBCBDADBDBDHGFEECBDFGFEAHDCGCDHHEHEHCGCFHGDGAGAGACACDDDFDFDGECCHDHCCEFAFEBAFGGHDCCGEDBDBDBCHCACDBAHCGCGAHAHAFFFHADCDCFCFHHCDCAEAGAGAGABFHGEGBGDFHEBEFCFAGBEEAABAGDGDFDFEABHCDEDEHEHEFCFCD,False +78,9.0,16.0,9.0,5.0,4.0,15.0,4.0,5.0,BCEADCBBBBABABCCEHFBDHFAAGAGHCFCBCBFDFAGAGBFBDBABFFFFFCEHEBDHFFFBFC,True +79,19.0,17.0,10.0,29.0,13.0,8.0,14.0,14.0,DEDEAEAEDDDDDDDHDGEBEFADAGBFFHDGFBBBBGBABFCHGDFDEACBBBAHADAHCGCAHDHEHABAGCGCGEDAGBDAACAHDBCBGBGBEDDDDDADGDFDHHFDAHAEEEHCDCHG,False +80,9.0,11.0,7.0,9.0,14.0,3.0,11.0,16.0,HEHEACBHBHAGEBEAEBHBHBDEDCFABCGAEABHEHDADABABGGGDGHECEHHDGDHHCHCDGFFHCBEDEGEGHGE,False +81,4.0,9.0,4.0,9.0,3.0,6.0,6.0,5.0,BGBACACHDGDFDFBFEAHFBDDEDEGHGHBBBFBADHDGCGDBFC,False +82,11.0,21.0,22.0,24.0,26.0,28.0,21.0,21.0,EDGDCDCFGEDEFFFFGEEEDEDEDADACHCEBAFAFCHEDBFEDHDCCAHGFDFDGAGEFECEDBHCECDGGGGGBGFGBHCGDGFFDCAGDBCEHEGBBBBHFHADFHCHCHCACHCBBEFAGBGBEBFFFHFBCEDFFEFHDHFHFCCECBHBDBDEDEHBHEHFBFEGAG,False +83,2.0,4.0,1.0,3.0,2.0,4.0,2.0,1.0,CBFHFBBDGDFDFEGEABA,True +84,18.0,13.0,21.0,13.0,16.0,19.0,15.0,8.0,CBCEEADAFGDCFHFHDHFACACEDGACFGGGCBABDCCCCCCBABABABDBDFACGCGCFCAGEFEFBDBCFEFEAGFDBEFEHEHBAEADAFAFGEGECAHFEDGDHHCAEDEFCFGGGBF,False +85,14.0,12.0,10.0,10.0,16.0,19.0,9.0,12.0,FGBGHDEEEGBFAEAEDHGHGFEDEFEGEDEFEFCBAHCHCFBFDGECFFFGAECBBBDGFAFACACBEDABEBFHFHFHAHAHFEDCDCFCAAHBHADAFB,False +86,14.0,13.0,10.0,16.0,18.0,7.0,14.0,15.0,GGGGHADGCGCEEEDEDBAAGBCDAEABAGAFFFDBEFEAHAHBDBDBDBGHAACDHHGHGHDHEFBCDCHCHDEEBEBDADABEFECCGHGHFHDGEEEADBEEHC,False +87,9.0,13.0,17.0,12.0,12.0,23.0,13.0,12.0,EHCHBDDCECFCFCFABABGBFDFDCDHBGDHDGBGCGCGCFCDHEHEFCHGEAFBFBFDFHCEBAFEDEDFFGHCFGBGFGCDCEBGFHFAFBEEEBGFFCFAACAHAHF,False +88,6.0,3.0,0.0,1.0,3.0,3.0,5.0,4.0,GBGAGBHAGAGFEBEFEHHAHAFAD,True +89,11.0,11.0,12.0,15.0,16.0,12.0,7.0,10.0,BHBHDDADCGCAEHHDCEAFAFBFCDEDECBGFCECHAHGCAEDDBDEAFAFHFDCHEBEGEGADBDBHEHDFGFGFDECECECAAEBEBDBFF,False +90,18.0,21.0,18.0,8.0,15.0,18.0,18.0,10.0,BCBDGCBCHGHAAFAFEFAFDFHGGGCCECEHBHFCADAFAFEGBAAAGAFBEBEBEGCBHBFADAECDGHGBGECCBCBABHFFDCEFEHGBGBGBEFGABCBFBDBEEAHACGCGEGFCFCFDA,False +91,21.0,22.0,23.0,29.0,25.0,21.0,20.0,16.0,EDECECBBDBGGGDHDFCFDFAFGBACHDHDADFDHBEAACACACEDECEDGDGEGEGEDEAFCFEGGBEBGFGEDECGFAFAFGHEDFHFCFBFBDEDFDGBHEADHDCCFBABABACGEHAHFHCEGEGHBHDACADFCCHBHDCDCFBHAGDBABEBFBGCDBEBCDDADAEEC,False +92,22.0,26.0,23.0,24.0,20.0,30.0,22.0,18.0,ADAFEGHDHFFFFDFECADDDFHBHDCBFAHCHCACHEGFBFBCDHEFEGABAFAEBGBFFFBFCFGBHBEBAACAHAEDEDEGCDCDCDCGHACFCFHFHGCFCEHEHCGCDCEFGDGBGBGEGBABGBGCCABBBDBAFGDABFBFEFEDADBFEFDBHGHDFEFECBAGGCGADDDGBHAEA,False +93,2.0,2.0,1.0,3.0,0.0,2.0,1.0,2.0,DBDCDGFFAHAHB,True +94,18.0,8.0,12.0,13.0,10.0,9.0,12.0,11.0,HHFAEHCHCHCDDAFACACACGGFEFGCHDEEGCGCGFDDADGDFDEBHCDABGBABDGAGEEBAFABGBDAHAFAFADADEHHCHCBGEAEA,False +95,4.0,5.0,6.0,3.0,5.0,4.0,4.0,3.0,AHBFEADADAGFHFGGCBCBCBCFCEHEBDCEEG,False +96,6.0,10.0,15.0,4.0,14.0,9.0,14.0,11.0,ECECEGHGHEHGDACGHHHFGFGCCCGFEEHEAAACCHCFCFEGEDHFHFDFGEABBBBEBHGCGBEBGCACBEBEGCCDBFG,False +97,3.0,4.0,3.0,4.0,3.0,2.0,2.0,6.0,BGHFHDHDCDBDECAHAHAEGBFBHCE,False +98,14.0,9.0,9.0,12.0,16.0,15.0,11.0,5.0,BGGACFEGEGEAFGFGFGFAADADACBCFDADGEBHBFDFGBBDCGAFAEEFECHCDCBFEAEAEADADCEBDDHDBGEFCHEHEFEAEFF,False +99,24.0,22.0,16.0,19.0,18.0,22.0,22.0,17.0,BABDFDEDEDEHAACABAEAFFGBHFGAHDBCAGADEDCHBBGEGAGAGAGAGFGABEDEDEFCBABDBECECEAGFGEGBGACBFEHEHAHAFBFBCHEFGDADAEEBCBHHHFHFBAGGGFFFFGHDCCHAHBCBCHFGDBCCAFBDGGFDHDFDFDC,False +100,10.0,7.0,6.0,7.0,6.0,11.0,8.0,15.0,GGHGHGFEFDCHAHFHEHEBACCBCHFHFBCBEBFFEFHAHGHDAGADAEGBGHHBAAADCFHFDADFDH,False +101,21.0,23.0,9.0,23.0,25.0,21.0,22.0,21.0,EEEEEACAHEHDDADHFBFBAHGHGBGDGFECGBBBBFBFEFHFGFGFAEHDHAHAHBHGHFBBHGGGGGEHDDDDHEAFBHHDEFEHEDDGBCDCHBGDDFFCAHADEDEGEGEAABBEBDFGEBABCDFEACFDADAGAGEGBAFABHBDGDCEEEAFAFBFC,False +102,1.0,8.0,5.0,3.0,5.0,5.0,6.0,8.0,HCGCHDEBGFEFECBBBFBFGHGHGDGBAHCFCHHHEDEBB,False +103,29.0,22.0,27.0,17.0,23.0,16.0,31.0,26.0,GGHCFGEBEDGCCDEBFFFEFHGCDCBCBCECFCHCHCHGHCEGAGCECABHEEEBEBEGAGBBBABABFBHBHDHGGDADCCFAFEDECEABGBFAFHDAGHGHADEFGBDCHHDEDCHGABABFGDEAAAEBGAAEGGGGFGHAHDBDCCHGHBDGEGHGEAEACCHCACAHGHGHAHDCACAFAGAFA,False +104,7.0,6.0,18.0,7.0,11.0,12.0,24.0,18.0,GDGEHCGGGEFECEBECGCGHGCFHFHFHCDFDFGACHHHGBGHACDCGAGADBCAHECACGHGHBBCFGHEDEFEHGHBHGGCGCGCHCEGGDGEAFFHFCF,True +105,16.0,23.0,21.0,18.0,22.0,17.0,10.0,18.0,ACEGEHEHAFACDCDCHFBFBGBHDFFFCAGHBBBHBHFABABABAHEGCAEEEFGBGBADGEBCDEHEBCFCHBHEFEBDDDDDDDGFEDEFEHAHBCACACBDBDHDCBCEDEHEGCCFEEEDHHAABCFCHAECBCBFFCFG,False +106,9.0,10.0,12.0,6.0,8.0,7.0,13.0,7.0,FABABHCEGEGBGBGCCCHCAAABGEGDGFGFAFCBCGCEHDCCAGHDHCAEHFBFAGBGBGHFDCDBEEDE,False +107,17.0,15.0,17.0,17.0,16.0,26.0,15.0,17.0,EFBHGEAFDGCGFGFGDEEAEGBDEFBGGFAHHCAFAFHBHBDGDGEGEGDFFFDFHHHAHBCDADBCBFGFCBCBGBFEHADAHCECFCECHBFFFFCDEDEDCDEFEFCHHHCACAEBCGAAAAHADAFHFBDBCFDF,False +108,20.0,24.0,27.0,23.0,19.0,28.0,19.0,18.0,AFAEGFGFGAHFCFEHEGDBBBEBEBEBCDDDHDFGFDCDCECFAFAHAGBBBEBFDEBCBAHGFGAGABDBEAGFCCCBEBHCDBDFDFBBHCHGGCDCDFHEHECGCFFFADAHHHDCDAEEBFGAEHCDDGACACACFCBEFFHAGCCCCEFEFCABDBFFFGHCHDHDFDGBGA,False +109,9.0,16.0,17.0,17.0,16.0,16.0,12.0,24.0,EGDDDAHBEAEABDCEBFFHFHFHCDGHAHCCFDFDFDFBBEBFBFEHGHGDCFCGHGHGCBCEDHBCDHFHFBFGDGACCCGAEBHBABCHHEHBDDEHEDEDEGEAHDHCECFCFCBHAHEGBHH,False +110,5.0,7.0,7.0,3.0,11.0,14.0,10.0,14.0,AHEHDHGFEFGCHFGFBBCAEFEFEFECEHFHBHAHFCBGFABHBEDEGCGFDFACGCGBFEFGHHHHEHG,True +111,20.0,16.0,22.0,22.0,11.0,17.0,13.0,10.0,ACAFFCDCDCACBFAFGDAACDCDEDEFFCBHDGDCDGDEABFEAADDCAHHDHEGACEFBCBCACACABBHDHDHEHCAAFAFCDDEDFDFBFCFBFDEDFFGGAGCCBEBCBHBAGGGGGEGACBHBDB,False +112,26.0,22.0,28.0,29.0,20.0,26.0,21.0,19.0,GCDCBAEHEHGGFABGFFFFBDBDBHCHCHAAADGFCBCDCFFFDCHCECEDEAFBFEFEGGCDCDAEAECFCEEACCBABGFDABADAFHBHFEFEAHAEADFCFHHBHAHAGGDHCCCDHBCADABHBDCGHGAGAGDDDFCAGBCBDBCFCFEHEDEBGGFGFDBCGAGDCDEDGDBDBEFEHAFADD,False +113,4.0,0.0,3.0,3.0,1.0,0.0,3.0,3.0,HAHADDGDHAGAECCCG,True +114,15.0,25.0,14.0,19.0,17.0,16.0,17.0,18.0,GDGCHHEBEBHBEFAFEFBFHFBGHEFEFEBAAAGFGDDFDFDFDBDBDBABABDHCBGDHCEBBGBCBEBAGHCHBEBGHEHEHEACACACACBBGGFGHCHDGBCDGEFDFDBEHECDGBCEHAHDHACFGADFDBAGD,False +115,4.0,7.0,3.0,5.0,3.0,0.0,6.0,6.0,HGHBHBDBABACEGDGEAHBHADGEGCHCBDGDB,True +116,18.0,19.0,11.0,27.0,26.0,22.0,18.0,28.0,FDFEHEBGBGBCFDFDFBEGFABHCHEEFAFAFAFBDHEHEABBDCHCDDGEHEADAFAFBHHCHBFBEDHGHGBFDFGECHHABDEGECEDADEHEDCAHAGEBABCDCDAHEDEDEDFFFFFBFHGAFEGEGDHDHGHGHGEDHDGEGDAHABBHHDHBCDADHEGE,False +117,9.0,10.0,11.0,5.0,12.0,11.0,5.0,12.0,HFBFCFBAAEABGHCHAFABBBBCCCHCECECHCGEHEHEHFHAHCEDDFDCEEBFFFFGEBEAFAHDGBGDEHA,False +118,1.0,8.0,6.0,3.0,6.0,11.0,9.0,8.0,BEBFGFGFBFBGBCDFEHBHAGEFHGDEFBFHHCGCDBGFGFGHCHFHCECE,True +119,16.0,21.0,23.0,14.0,8.0,20.0,24.0,21.0,EEGFBBADAFCBHFACCCFCFEFDGAFHFDABHBCGHHHBHGHCHEGCAABBGDHBHBGFGCGCGCGHFEFCFGABAGGCGAGACFCBCBHBFCFADHDHGHGFDEBEGCGCDBHBEAACHDDFDCDCFBFBGGGGCBHDHDHFABA,False +120,23.0,16.0,16.0,25.0,12.0,20.0,24.0,21.0,DFHFBBDGFFEDCHEEGGGEEADAGAGDBDAABFDFCGDGAABABABABACAGGHDHFACECBDDFDHGHGHBCBCAGFGBGCFFFDFDCGHGDEEHBCDCBHBCFGFDFDHAGCHHHHHGAFADDHEHEAGAGAGHCBAEAEDCDADCFGFDHDHF,False +121,19.0,17.0,15.0,20.0,28.0,24.0,23.0,17.0,DCDFFGAAFFFBGAGDGCACHEHDADADFEHEGGFFEFAABBHGGGFHEHACACBEEEHBAGAGFDFEBEGEBECECDCHBHGDGBEFEAEAEAECCGCEHBHCFFGBDBDCDAEEEAEFFFBHAHGEDEBGFGFGHGBGBDFDCDHEHDDDEBAFDFEGCFH,False +122,24.0,21.0,31.0,19.0,20.0,33.0,21.0,17.0,CBDGEGCBFGFHFHFEFBDAECCCBCBGHDCCCAFADHDHDEDACBDBGAHABFDGEGCHEECECDAFBGBGBFFFFHEAECHFHFHGEEBCFCFDGEGFFFFGCDCGBGBGFFBFBFAAAAAFGBAFABECAGEGBGFHFCADDCECHFAFADAHFHEDEHCFBACAEAEFDCCCCCBCHDADCG,False +123,23.0,22.0,33.0,26.0,18.0,14.0,26.0,19.0,DGDGCACABHFCADADGHGEEHGACAHAGACEDEDEDGDFCHDECFCBCGHGECHCHBEEDEDEDEDCBGBGBABCBCBHAGDGECAGDCCCFCDCFHFDABECGBGFHBBFBEBEBACEDBHHCCGCDAGGGFCCCGDDFCBCBGBGHGHGCBADHFFAHDGAAAAABAFDHDHCFCEAD,False +124,14.0,14.0,13.0,14.0,9.0,17.0,19.0,18.0,DCBFBFAFAHBHGFBABECACGGBGCGCFAFHHDGDGEBDADFFHHHHDAABHFFEGAGFDBGHGAGBGHFHFGCHCDGEGEFCGDGDCDCDCECBFAFCFHAHEBEGHBEBHHADAD,False +125,22.0,17.0,18.0,14.0,19.0,23.0,19.0,20.0,AFFEGCACEHAHBHFHECADBDEDHDHDACHCBCBHFDDAGHGHCECEAEAHBHGGCEAFAFBDGFFFFBAGAFAFHHCGDFFAEBBABADADBCGHHHGACACFCFDFBCGHGEGEGBGBCBEEAFHEBBGGECEFECEHGGEAFDFDFAF,False +126,2.0,2.0,5.0,1.0,2.0,0.0,0.0,0.0,CBABCCCECEAD,True +127,9.0,13.0,13.0,20.0,8.0,15.0,15.0,18.0,GGEFDFEHDHDHBAGABBBFFHFCFHGHGHGHGDADHDEDFCEDAGAGCBDFDHDHCBCDFDBHFHGHFBCGDDDDDABGHDHCHAAECFBDBEBCBCEGECCFFHCGAGF,False +128,26.0,16.0,20.0,13.0,15.0,14.0,8.0,14.0,AFAFGCBFDCCGCBCACACAFACECBAFAFDBBABABHECBGAHADEDCBADABABAHEHCHCHGECDHDHBHBAEDEAEAHBGFAHBBCACACAFEDCAHHEADGEGECEFFFCGHDFDEAEFFD,False +129,3.0,2.0,3.0,1.0,2.0,1.0,0.0,1.0,AHABFBEAECCDC,True +130,3.0,10.0,5.0,11.0,10.0,4.0,3.0,9.0,DBGBHBAEDEBCCEBAAFHHDHDCBEDHBHBHBDECECEDDDFDGDFBEGEHEHF,True +131,18.0,19.0,23.0,22.0,20.0,20.0,15.0,23.0,FGBCAABCBCDCDCBBAAADCEGHAFDFEBHBHAHGDAEAEAHGECHCDDFDBEBHHHDBCFCABFHHHABFHHEGEHBAFAFCDCHGEGEFBFEFEDEHCHCHDHDGFAFEBEBGBGFCDCAEDEGFFFHFBEAGACFDDDDHDCCCCDCDGEGBGCEH,False +132,27.0,13.0,16.0,13.0,20.0,12.0,27.0,15.0,HAACDHGHEBFFCDAGADAEABAGHFHDHCCAEHFHBGBECGGGGAGABACDEDCACACFGFGFHBBEBHGGGDABGGGEDECEAEAEAFCEGBBBAGAEAEABHEAEGGGCEHFHDGAGEDEDFDHDEAAGAHAFFGCCCCG,False +133,5.0,7.0,9.0,1.0,6.0,7.0,8.0,7.0,BGCFEBHHHHACABFBFHFCFGGGCCECGCGCHAEBBHFGCGDAEAEBEF,False +134,14.0,15.0,11.0,16.0,21.0,17.0,16.0,20.0,HBHDHFHDDEFEGEFEBGDFDFBBHBAGEGCFHBHDADHHFAFAHECEFADECEDDDBDBDACBEAFHFHGEGCGDECECBAGACHBHGHFHFHGEGFFHEHCHCEGEGEAEGDGEABDBABFFGECABA,False +135,8.0,3.0,1.0,2.0,4.0,6.0,9.0,3.0,GFGEGHGFEFGCGDBAHAFDEAEGBGBAAAFAGAHF,True +136,14.0,29.0,20.0,23.0,25.0,22.0,18.0,18.0,DGDCEBGFHDBFBECHFEFBDEDCACGCGHEFEFEFAFGGGDCFGFHFHAHADEBBCBCEEEFEBABCBEBACACBHHCFCEAEAGBGDCDBDEDGBACECBHEHBDGDFDGCGAFEFDBHBEBEAHGFCFBFBHEDFDGDBBBBACDBDHGBEAEGFCHBHEHDHDFD,False +137,3.0,5.0,1.0,6.0,8.0,6.0,3.0,5.0,FDFDBBBEDEHEHEFEACFFGDHDFGBHAEAEBEGDH,True +138,17.0,19.0,28.0,23.0,19.0,29.0,14.0,27.0,EEHFCDHDHBAADFECECFFFCDGBAHAHFHBCDDFDGDADBCAAHABAEGFHFHDHDEGCGHGHCFDFEFGBHAHBCBABEEECDCDEHFHFBABHCCCACHEACHDGDFHFHBHFGDGDGDFBCDCGABFFDFECHCFFFHFCDGEFCACHCHCHEGACFCFBFEEECEBBBBD,False +139,18.0,10.0,15.0,7.0,19.0,9.0,15.0,15.0,BCDGAGEBBAAFCBEFDFHCAAHABFEADAHGCCCACEDEDEDEDEHCBCFEHCHEACACHGGGGBGEGFGFEHECGFEAHGHEHEHEHACAFBGGABABHGHEAEAC,False +140,12.0,11.0,10.0,15.0,15.0,9.0,10.0,21.0,GGDEDEDHDABGBDCAFADADEEFHFEEBBAHECFCAHGHGHEBBCBABAFHHHHAFADHECEGGBGECECHBHECFCDDDEEHHHHHDHDHDHFACGDABFG,False +141,6.0,7.0,16.0,10.0,19.0,4.0,7.0,3.0,GAGEECEDBGBGFCFCHCFBDBDECEAEDBDCHBEEFAHAEAEGCBCEADDDDEGCCEEEECCCECDCGCEE,True +142,17.0,14.0,17.0,18.0,21.0,18.0,15.0,9.0,BADAGADHDGDGFHFAFDFGEEDDDADCCCGGECCCGEHAHAHEEEEAECFCDHDFABABFBGBCACEFFDADAEEHBHFDFCBEBGHGCFCDAGFDBEFFGFGEGCBAEDEBCBAACDCBEBEFEFEG,False +143,1.0,3.0,4.0,4.0,2.0,3.0,3.0,3.0,DHDCCGCGAGHBBFEFCFDHDEB,False +144,3.0,1.0,7.0,1.0,1.0,3.0,7.0,2.0,CDCFHGGFBCCCCGAGAGAEHFGCG,True +145,3.0,5.0,7.0,4.0,3.0,11.0,6.0,3.0,DHGEGBGBGCCFDFAFHCBEBEBDFCFCFGFCCAHFFFDGAF,True +146,4.0,13.0,6.0,8.0,6.0,15.0,9.0,3.0,FABGBGFGFDBBBCGEEEEBFGCBFBDBCFDFGFGFAFECCDDADAFBDGHGBFBFHFEFHCBD,True +147,16.0,16.0,22.0,23.0,21.0,20.0,35.0,29.0,FBFEECGAGFGFGHDHDFAGEGEHFHFHFEGHGCEEAHDGDEHEGEFHFCFHGHBECDBDBHHGGGGGGCBHAHACAHAGEBDCEAGGHGHGEGEBDAHHHCHADGCFBFHGBGCHDFDFDGHCBCHHAGBEBDACHCFFGGGDADEEAGCEDEDCCCGDFDBDGFBFBGBDEACACDCDCH,False +148,16.0,20.0,20.0,23.0,21.0,16.0,31.0,18.0,EBEHGGGHCACFDDDDDAFCHEGCACFCFDFAGADEGGGAGEECEGEGEGAFFDCBHBHDHEGCDCGBGBGCCCCCBDGEBCGFHCHGHAHBBCEGEGEBFBGAHABDBDAGAGFGBEEEFEDGDAFCHBABGBADADEGFFDHDCFGGDHBFBDEDEDGHHHBH,False +149,3.0,7.0,4.0,6.0,10.0,7.0,3.0,5.0,EBEHEBEDCFCBBADCHFHFGBGBDEEEECHBDADADEFFFGFHE,False +150,6.0,2.0,7.0,6.0,2.0,3.0,8.0,0.0,DDDCGCADFDFGGGACACAGBECGGDGABACFCE,True +151,5.0,2.0,2.0,0.0,5.0,4.0,2.0,3.0,GAGAFBFEFECEFHABAEHEACH,True +152,14.0,12.0,9.0,7.0,12.0,11.0,10.0,17.0,FDHDFEHDHCFCBCDGHGCFFFBFHACCHBGAGAHEHEBEAADAHBGBFBFBABABAHAHEEAFHEHBHEHABGGECDCECEAGDHAHEFGG,False +153,19.0,24.0,27.0,19.0,23.0,23.0,26.0,24.0,CDCGGGFAAGACHFHDHDHBBCCHCGFAHABGBEDHBGBGBABADECFFFFAGGCHDDGDGCGHGHGDCFHDHAFEFEFEHDCCGGBGEGAAFCEEDFDFGBEAFHFCGEBCBHBFBDCDGBCBEHADABCHCHEHEHBHDGFGAGEGBBEBHDEEHAHAEAECCFFFCCCECECEFBFBDECBA,False +154,13.0,10.0,11.0,9.0,11.0,8.0,12.0,4.0,GEAEAFAGADADAEFCGCGCGCAFBFBEECEGADADACBGBCHHBFEECACBEHEFBFBDADEDBCGGGBDFHCAGGD,False +155,23.0,15.0,20.0,21.0,22.0,13.0,16.0,23.0,FEBEBEBFDHDHCCDDBCBEGFDFGBHCHFDAEBCBFHAHGHDADCBGDHDHDFCAHHHDBCEHDFDAAECDCDCBCAFEEEEEAEAGACHCEGEAEGGGGAEABAFAFHHGEAAACHFHAHFGEAEDEDEDADHDBCGAGACBCHHBGGCHC,False +156,1.0,2.0,8.0,2.0,1.0,1.0,0.0,3.0,CCCCCHCHBACDCBHEDF,True +157,11.0,6.0,5.0,14.0,10.0,10.0,2.0,6.0,EFAHAHFBFGGABADFCBEDEDADAHAFAHBFEDEDCDEDEDEDFFCBEDFDFBACDDAEHCHA,True +158,15.0,22.0,16.0,16.0,9.0,21.0,17.0,9.0,CFCFCAEBDGDHBBFBHCAAGFFFAGGGGFGHCHDBDBECECECFHBBCBAFHFDFBCACHCAAAEFDBDBCFGAADADAGGBBBGCGBGCFBEEGHGFGFDFDFABABDFHFDBDCEFEBGDDB,False +159,3.0,6.0,10.0,6.0,2.0,3.0,4.0,5.0,GGGFDFDBCBHBHBCCHCBCEHHFCACDCBEDDDACGCA,True +160,7.0,12.0,7.0,6.0,6.0,8.0,8.0,5.0,AEFEFEBCBADCEFHHCHGBBECAABFBFBDBGBHECGDADADGBGAHFFCFCGDGBGB,False +161,25.0,18.0,13.0,27.0,15.0,21.0,17.0,28.0,HFHGDDBDFDGHGADHGFBHGCFDAECCHHEFEFEDDBEBAHAHFHFBFHAHDFDFAEDFBBCEHADGFGAHDGDGDGDFCBCEAEBCBHDHDHAHAEADHHFHFHEGBHEDABABACDCAEFDDGFGAGABAHDHDGDGDBHBFAABAGAECECHCACBFAFH,False +162,18.0,23.0,16.0,12.0,17.0,23.0,24.0,31.0,AEABABCBCHCHCFFFBHHEGBABDDDDDHHFHEECFCFCBEDDBHBHBCGHDFAFHCHFGCHHHHHHHCFGFGEHDBAAEGGHEBBHGDAHFHBHBECGFAFBGCAHEHGBBFBDCHHGEAEHGFFFADGEGBGBGCGFFCHGEGEGAGAFABABAEAEGFGF,False +163,24.0,23.0,17.0,16.0,25.0,31.0,34.0,30.0,FHFHFEFGFBAEHHHDHDHFGGDGDGFGDHACAFGDGDECECHCGAHAHBBBBBFFFCGBGEFFHFEAECGGBBAGABABAFHFHECGDECFCHDBACDEHBFBHBFEFDDGCHBHGHGHBEAGFGCEHFBAHACEHEACFCFEAEGEGAGACFEAEBGGFDBDBGEGECEAHHHAGBGHAFDFAFDFGBGHGFGAGHEE,False +164,16.0,17.0,19.0,27.0,19.0,29.0,35.0,19.0,GDGBCCGCAFBFGFDHGHBFAFGFGDDECECDGDCDFHFGFCFHFEABACFHFBFHEEECEDFDEDGGGDGCCBBDBFBABFBGDEDEGBHBDDDGGGGCFHFGFGFHFEABBDCDCHCGGGDGFGEDADHDECEAGAFAHEHADAFFGGGCABEGHCAEFGFGAGDDHDHBCEHGAEHFH,False +165,10.0,7.0,7.0,12.0,6.0,6.0,5.0,8.0,DGFFDCDCDAEGDBDCEBGACECHCECDBABDEAHDHGAAHHHFHFBFBGBHDADADAFAE,False +166,17.0,18.0,17.0,16.0,20.0,19.0,17.0,15.0,CACAHAFBDAAADADHBGFAFDGDGDGHHFHFGFGFHHCAAEBFBFCFAHEBABEEGEGEGEBAHGDCDGEBCHEGDGCFCEEFECBCFHBHBHBADDFBFBGDCBCFFEGCAEGEFBACDCECECFDDADEEEGHBHB,False +167,15.0,4.0,11.0,15.0,21.0,12.0,17.0,17.0,HHAHDEDGHFHEHCHGFGFCECEGEACFGDGDCDCHADCEHEGGAEEBEBFHHHCHCHCFDAHAGDGFGDDHEEGCAEDEABAEGEGHGDDFAAEFGAGAEAFAFDFEEBED,False +168,8.0,4.0,9.0,2.0,9.0,7.0,3.0,7.0,ECECBCHFHCGFGFEEEHEHECAAHAFFBAEAFHBGAEAHDBDACCCFC,True +169,16.0,14.0,9.0,11.0,11.0,11.0,12.0,11.0,DFDFDGAGAGAGFGHHACBHBHGFFDFGBCEAHBDAEADACCECAAEABBHEAEAEDEDCABABCBGGGGFFACHHBDBFFDFEEGBCDHEHBHB,False +170,4.0,2.0,1.0,1.0,6.0,4.0,5.0,2.0,GGDBEEEEBEAGFFCFGFHAHAEAG,True +171,28.0,14.0,20.0,10.0,8.0,25.0,20.0,36.0,HCHCDCGCDAGAGHGBABAFAFCFAFDFGFGEGHFEFHBHGFGCHEHABFGFHHHCFDACHEFBHHHCHAHGBAADCHBHBFAAAHHHFEGCGDAHAGFBFAADAEACFFGAEAGABFCHCBFDEAGAHBHBAAHHHFHFHCCACGHGHDHDHCHCFCBGF,True +172,3.0,11.0,4.0,4.0,5.0,7.0,5.0,5.0,BBBEBHHCCFEFGFGHGBBBGBDFAFACEHFGFHDBDBABCDEE,False +173,8.0,13.0,6.0,15.0,4.0,10.0,15.0,7.0,ACDCGBGFFFGEGBGFHBHDADHDFGBGBGHCDAGGGCHDHGADDDDDDEBBHBFBFGFAEADGCCBDBDGAAEFBFB,True +174,10.0,11.0,8.0,10.0,13.0,7.0,14.0,11.0,GCGCGCGFGEBCAAEEHEAEHDHDGAADADADFBEDECHCGGGHGEEHBHAHABFBEBHFADGDHEECHBBFBGEGBGDCFBFD,False +175,23.0,12.0,12.0,24.0,26.0,34.0,26.0,24.0,CDBFHAHBGAAFEGHAFGCAFGFGBGBEBEAFGDGDFDADCFGEGBFCHABFCGADHFFEFHFEFEFEDHFGCGEGEAABEGAGHGEAFAFAFCFAEDEDEDHDHDHFFFGFHACEFHHHDHDAGFDFGEGBGDHDBABAFEEEHEBGFGEEAEAHHFDDDGHGHDFCFCACHDDEDEFHC,False +176,18.0,8.0,20.0,16.0,15.0,17.0,11.0,11.0,FCFBECGAFAFABAEEEEDCDAECEDGAAADFHBDBECEHEABABCDCHBGEHAHAGAECHHHADCCCCFCDCDAGCFFEEAFAFGDDFHFHFHDBGGDGDADFGCECFCGCDCFF,False +177,13.0,12.0,13.0,12.0,6.0,11.0,5.0,9.0,DABFHGHCBDBDCFFGABAFEBACAHECGDFFHFHFDFEFCHCBCBAECGCGCHEAEADDDBDADAHHBACABACDCDBFB,False +178,7.0,14.0,10.0,12.0,19.0,22.0,10.0,9.0,FDECFBFDFDFHFGCEDEDEFHGBACCEGGAEBEGABFDFDFCHGHFFEDBFBFBFEGEHADAEFEFEFEABCFHDHDAECFCGBFBGBFBEECECDBEBHGH,False +179,2.0,2.0,2.0,1.0,5.0,4.0,1.0,6.0,HGFEHEHEFEDAFHFEABBCHCH,True +180,2.0,5.0,1.0,3.0,3.0,4.0,0.0,0.0,FAADBBBBEBEFEFDDCF,True +181,6.0,7.0,5.0,2.0,1.0,4.0,3.0,6.0,BHBDBAAGAHCHFHACAHEHBBBFCFCACGGDBF,True +182,2.0,3.0,10.0,6.0,8.0,6.0,4.0,4.0,BCBCECEAEDEDHCCCCHEHEGDGCFFFAHGBFFFECDDECGD,True +183,27.0,20.0,35.0,20.0,19.0,18.0,17.0,19.0,CHCHCFCBDEHBHEHCCCCBDBAADFFECCGCAEAFAHCFGDGAGACABFEAHCBDBDBDACGDEDEDEHEBGDGDCAGABEBEAECEGAGFGCABFGFCEAEAGACFCDCFFGFEHBDBDECACAFHBHCHBHBFAHDBCADHEHACAGDDDGCEBFBFCCCCGAHCFCACAHH,False +184,21.0,29.0,29.0,14.0,13.0,23.0,22.0,20.0,HBBEFAHAHDHCHCGCBCAFABDDHDFAAADBDBEBCBCBEACGCGFFBFAFHGHFCFEHCHDADFCFCEDBGBCCFCFGFHCHCACBEAFBECFCDAGGCGFGHGFGEGACCDCBHBACGFGFHFBFGEGBCHCBCDEBBCHGGBGBDDFAAAEBEBABHBABHGEGBHA,False +185,16.0,21.0,7.0,5.0,16.0,12.0,3.0,15.0,BBBHGHBACDBEAAAFDHEHAGAGAEEEHHCAEAFBBABFBCECAFAFBFHFEDABBBFBEBEBEBACHFHFHDHBFEAEBHAFCHEDECEHBHB,True +186,26.0,34.0,20.0,22.0,24.0,21.0,26.0,17.0,HFACACHCBBBBHBGBEHFHFEAHAEAEFDBHECAHAHDDBGEDCBEGGFGECAAADBEBGCGCFCFCFBFBFBAGCBBABEHGCGCGFGBBCHCEDAHBCEAEHDBAHGGDDDDHEADDDDDFFGBGAGBGBEBABDBDGDGBFBDBDBDHEFEFCFEAAFGEBCGEGBFFGCGAABAGCHEEEAFAEA,False +187,3.0,5.0,0.0,1.0,1.0,2.0,2.0,4.0,DEBGHGAFBFHHBHBABA,True +188,8.0,11.0,10.0,11.0,8.0,19.0,14.0,12.0,HGFBFHFBFGGAHDDEBAHFHFHFCEGFGFGFGBGEGBCEEAFDBBBHFHDBDBGACHCHFGCGFGCGFBCDCDFFAEAHAEFDFDHAECDCD,False +189,24.0,32.0,23.0,32.0,21.0,21.0,20.0,22.0,BBBABAEECDDDEDEHEBECEDEDHHHFHFDFHCDAHAHDBGBGEGFGFGFGFBAGCGDFBFHDHBBCHGHGFAEBEDCAAGFDDADADBDCFGHBABDHECBDBAAHADAGCDCBABABGBHDCGCBCGFEBDCHAHCCCFCFEBABHDDBGBHHCCCGBABDBCEEGHAFEFEDDBAFFFDFDCEAEAEGDBD,False +190,13.0,10.0,11.0,9.0,7.0,16.0,9.0,11.0,AGCHAGCBAHCBGBEBEACADADHDBFBDDAGEFCFCBHDEFEFHFHGHDFGFACAEFHAEAGGBGFCFCFHFDFCFCBBFDAHAH,False +191,14.0,3.0,6.0,9.0,14.0,7.0,4.0,6.0,EAEFDGEEFCCCFCFEAAAEADCDAEAEGGAFHHHHEAAADADEFEBDBAEGECEADFDHDHB,True +192,6.0,4.0,7.0,3.0,3.0,3.0,1.0,4.0,CFGEHCCFCBCEAEHCHDADADABBBACAFH,True +193,29.0,36.0,21.0,12.0,18.0,14.0,23.0,24.0,BBHFFFCEHEGEHDHBGBHBHDEBHBHBEAEBDBFHFHEHABADACGGGADBBHHFBBBAAAAABECDCACHCAGACFCFAEAFAFAGGDAEBDBHBEBGACBHFAFGFGBBCAGGBGHDCBBDGEHEGEACACACEBEBCACAEGDGHCBDGHGHBBABCCHCHCHGBAEAGBFBG,False +194,6.0,3.0,5.0,1.0,2.0,4.0,8.0,5.0,HBHGGFCFCACAEABGEACDCHBGGHGAGAFHFG,True +195,3.0,6.0,4.0,7.0,9.0,15.0,5.0,10.0,HAHEHFGFHHGHGFFCFCEDEFEDBGBDEDACBDFHEBFHFHFEFDFCFDFABEBGHFE,True +196,2.0,2.0,8.0,2.0,3.0,5.0,4.0,4.0,CCECHCDCDCEBHCGEHBHGAAFFFFGFGC,True +197,0.0,3.0,4.0,2.0,1.0,2.0,3.0,2.0,DBHBDFCCCGCGBGEFH,True +198,9.0,8.0,9.0,4.0,11.0,7.0,12.0,11.0,AAAFADHGGGFGCBCBCHEGEFEHDCABDHGEGEGDACBFHFBEBGBECEHAHAHGBECFCGEGAHEHCHF,False +199,9.0,8.0,10.0,11.0,7.0,10.0,5.0,6.0,ACADDFDHDABGCDEBEHAFFBECECDBBABAFAFAEAFHDDDHCCDCGCGHGDGHFCBCBFFEFE,False +200,15.0,9.0,5.0,13.0,12.0,23.0,15.0,22.0,CHGFEHBDGDHEHAHDFDFAEBDAHEFEFEGGGGAAAGEDAHGHGHECEGFGFGAGBFEFAFBFBGBDFAFHDHBHFHFHGDEDHFFCFEDBDHFFFAAHBHAHFCFDHHCHAA,False +201,8.0,4.0,6.0,6.0,2.0,3.0,2.0,2.0,AGCFBBCBCDAHABACEHDADADCDADAEFGFC,True +202,15.0,30.0,30.0,30.0,15.0,29.0,25.0,23.0,DFBBDGHBCEDBFBHBHBCBHEGGGEBEBHHEHCFFHFGBHEGBDFDFGBGDFDFHCEFHCGCFDHDFDEHADADEBCFEFDFEFECDAAHFGDDDCACACACACDBABGGEDAABBBGCACABFBGDCDAGGGGDCDFFFGFCBBBDBDHECGHGDGCGCHCHFBFHHHDHCEBFDFDFCFCGCBCBCFCDABHCG,False +203,14.0,19.0,19.0,3.0,12.0,14.0,16.0,22.0,CHAEADAHBHBHBHBGGDBHFHEAAABCBGEFCCHFEBHCHABABFHCCCHBHAGAFCFBFAAAHCFCGEGEHEHEHFHBHEGFGHBEGGGCCFGFGCDAECGCBBGBFBCHCHCGBFE,False +204,9.0,15.0,19.0,11.0,9.0,19.0,20.0,15.0,FAAACCHEGCGDGBHDCCCEBAHDGDFDBDBHCFGFCFCBCBFGFGHGBFBHHHFHEGBGBCAEBCCCFCFCHGAEFEAGCDHGHGFGFGCGBGBGFDACEBFDFDEHEDGHABFHF,False +205,20.0,16.0,16.0,34.0,30.0,20.0,29.0,29.0,CDCFGDGDEFHGHEHEGGBGBGBHBGEFECDCEBGDAHGCBDDGDHDHEBEDDDDHAFAFDEGCHEGFHFADBEEGAGDGDHFHBDEAEAHAHDDDECGBADEHEFEFDACAGEGFGBDEDECHHHEAEFFBADDDDAEAHHDHDCCFCAAAHCFCFEGHHHHGBGBDCHCHDFDGGEGBFBGHFAFEGEGEAE,False +206,20.0,18.0,16.0,14.0,21.0,4.0,6.0,11.0,ABABAFADEDBAECHGDDAAHEBBDBACECGAAAACHEFEBCDHGBCECECEBEFEAECBCEHEDGAHACADAHACECGDDEEECEHHHFECBCBEBHBDBDBDBAGDBA,True +207,1.0,3.0,2.0,6.0,1.0,4.0,1.0,1.0,FCADBDBGBFEFDFHCDDD,True +208,5.0,3.0,5.0,6.0,4.0,0.0,1.0,2.0,DCCBCDCDCAAAAHDHBGAEEDBDEE,True +209,9.0,6.0,7.0,6.0,5.0,8.0,3.0,2.0,FCFEAEGDADABCBCFGAGCFAFABABCBDHCFDFEFEACBDHEAD,False +210,21.0,21.0,15.0,16.0,11.0,15.0,20.0,12.0,CACFFACCCEHFDBGBGBFHFAGDGDADACGGDGBAACABBECECEGEDHDHCABDFDFDAGHGHGBGBFBGEGBFDFAGAEHFDAHEGABABFGAGEBCCGCHBDEDGBCACFBFAFHDBEBHBABADAH,False +211,10.0,24.0,13.0,13.0,14.0,11.0,16.0,23.0,EDEABACHGHAEGGBBBBECECEBBBAHGHGHCBCECDCBFBHBHFHFHFBBDAGFEBHAHDHGCFAGABCDDBEBEDHGHBCCACFDDBAHHHGBGBGEGEGHGFEFHHHDDBBCDEFGFHDH,False +212,19.0,7.0,17.0,13.0,17.0,11.0,21.0,24.0,FGCAHAHFGEHAAAAAHGDGHGFEEGDHHAEAEDCDFGBGDHDGFECECGGEEHGHGHCFBBHBFEEHGHGHDHFHDHDAAAHDECAAACBCECACAHFDFCCCCCCGGGGGEEEDHBHEFCGDHAHAB,False +213,10.0,20.0,7.0,7.0,13.0,11.0,10.0,5.0,HACBEBEBAGEEHEDAFABBFEEEBGBGBGBAAEBBDDFDFDFHCHDDAFECHBBAFAGGGFAFCGBEBEBEGGBFFCBCBCB,False +214,6.0,9.0,11.0,6.0,13.0,4.0,11.0,19.0,ECECBCFDGEGBHEDDHGEBHHGCGCBHHHHHEHEGACABADHFFGCGBGHDDCEEEEBEFHAECBCHGHGHBHAHAHC,True +215,3.0,0.0,0.0,3.0,3.0,2.0,6.0,5.0,HDFDHEHGGGGHAHAEGEAFDG,True +216,1.0,8.0,11.0,12.0,14.0,8.0,9.0,12.0,GEBDBDCCADDBGFGFEEGEGCDCEFEGEBEDCCFBHCEDDGEHEHDDFCHHHBHBHBCDFDEGEGCHCHEHFHF,False +217,10.0,10.0,22.0,13.0,14.0,8.0,15.0,10.0,DCHGECECEAGHEFGACFBGBECGCAEBEHHAGEGFDFDFHEDDCDBFBABACDDHDBDGCCCGHGACFCFDGCGCBCBGAGACECACBCECGDHEHEHECD,False +218,7.0,10.0,14.0,5.0,9.0,7.0,7.0,16.0,CFCECECDHHHHHHHHBBBHEFCCEBDBABAGDFDHCHGACCHCHEFEGHGDACFBGBCEEEFGHGFCBCHAAAB,False +219,15.0,20.0,16.0,12.0,13.0,12.0,14.0,14.0,AGAEAEAHGHFBFEHBHFGGEEHCFCDADACBDBFBCBFGFBBBCCAEGDGFAACAHBCBCDAFHFHECAFFEGEBCBGGCDCDCDEBBDBDBHHHHHDGAGDCHCAGEGABBEBE,False +220,0.0,1.0,1.0,0.0,3.0,3.0,1.0,3.0,HEHEHFFFGCBE,True +221,4.0,7.0,18.0,11.0,9.0,20.0,14.0,16.0,GGGBFCCCFBFDGCFCFDFHFHCDCDHHHGHFDCAGHCBAEEFEFEFHAEFCHCGEFCCCHCHEHCDCDAGBGBGCDDFDFGFHEHDHFGEGFHFGFBB,True +222,19.0,32.0,14.0,24.0,24.0,23.0,30.0,29.0,EAEAGFDFDCBHFAFADGBHBDAGCDEABDFGEEFFFEEAECHDHBHDGAHHGBGBGBGHCDFDBDBDEDADHFFAFEFGBHBGDCHEDABGBEBCDCHCBFAFBGBAHFHFGEDFHHHBBBBDBDBDBGEGBHEACCHEGEGEDEHECGHGFBHGHCBGAGHGHGEGEGEHAHAHFCCEFHFAGBGBGDADFBB,False +223,6.0,4.0,7.0,6.0,14.0,14.0,8.0,15.0,CEEFAGEBDFAHHDHFAFAHBFFHFCFEHHHHFDEGEGEDEDGAGHDFGBGBEFGFHHCHCHEHECFCACEEFE,True +224,11.0,10.0,13.0,13.0,21.0,14.0,25.0,19.0,CGBAEGEGEHHCGGHGCCBCAEBEGHCHDFDFDFEGBDFDFEFAGDGAGEGCGBHEEGCGBEEGEADACECABEDCDFFFDCAGAGHFHAHGEGEGEGBGBGHHHHHHDABCEDHHFFDHEHEGFF,False +225,6.0,19.0,5.0,11.0,12.0,6.0,9.0,5.0,GBHBDBABHBCBDEDBGBGBEBEBCCFDHDFEBBDDEAEAEAECFGFGEGABCFGBBDHDEFBGBGEEABHDD,True +226,11.0,18.0,23.0,14.0,12.0,26.0,20.0,26.0,EFEFEFGDCDFBHBHADECHHEHEFGFGHCBGACBGACFDFGFCFGFCCCHHHBHFHFHDADFFEBGFFFFFDBCCFCFHFCDGEHDFDBDCAGGHHHHHHBACGCGAGBGHAAAFFCHGBGCADGBBBCGDHEBEBEBEBHCHDHCCCG,False +227,23.0,20.0,28.0,18.0,25.0,23.0,23.0,21.0,FCCBCEFEDAGGBEHCHCHAFCCADFFHFEFAHCHDGCCHAEDEDFDGAGAGAGEFEBEBHHEFEFHFCGDFBGBDHAHBGAHFFFBFCDDADCDEEAGABHBHGHCHCABADABCHCHCDFGHGHBAFFEGECBGADCECGCGCBFEFDFCGCGDEECAGAEAGAGBBBBBCEEAEDECE,False +228,5.0,3.0,9.0,5.0,8.0,2.0,3.0,5.0,DDDACEHGFBCEAECCCCCFCEHEHEHEBCDAEBDHAGAG,True +229,15.0,19.0,18.0,23.0,23.0,15.0,10.0,23.0,HHFHGHEBFHHBCBDEEHCBGBAHAEDEDCGCGEBBDDDDEDBDHDFDEDACCEEDFCEEECBCBCBCDAFEHCFAHBEDACAGHHHHHHHAHGFACACAFBEBEFFFFFDEBEAEGCBEEDADACBHGCGBGDHDHDFDHDEABF,False +230,15.0,10.0,14.0,14.0,7.0,9.0,3.0,6.0,EDADBFADCDCDEBFBFAFEFEDCBADFBFBAHACCBCGEHEHBCCAGDCFFBAAABAGACHCHDDCCCEDHDADADA,True +231,21.0,19.0,19.0,16.0,21.0,13.0,13.0,23.0,EHBFBHBCDAEACABABEHCAAAAAEBDHDCECACAHGFCFBFBDCCBDBDECHCGCAAHHDDCDCDEEHHHADAFBFGFGDGFGHGAGEEFEHBBDBGHAHGHEBCCACACGEDEAABDBCEDEFEHBHEEEHGHFHEHFFGHB,False +232,10.0,11.0,13.0,7.0,8.0,12.0,12.0,9.0,EFGGGHCHBAEHFDFEADAHBBFBCGFGBCBCBCFHFAFAGCGCEBEDCCCHCHDGGGCGCADFEBEBDAFAFAHEFGBHDA,False +233,16.0,18.0,26.0,21.0,12.0,11.0,22.0,9.0,GBGCHBGDHEHDGAFCFCGCBBDDDHHGCEDEDCDBGBEBCCCCDBGBCACBGGEHEDGGAGACFCFCHCGGDGABDCCCGDBDEDEBBCHCDCDBDAGECECAFEFBFEAGAFAGBGAGDDDACAFAFAFCHBA,False +234,8.0,5.0,2.0,10.0,3.0,5.0,9.0,5.0,GAGBBEDFDFDBDGDAEADHGAGHBDGDFDFCGAGACABAGHHHFED,True +235,28.0,16.0,21.0,19.0,24.0,21.0,12.0,20.0,EDHFBEAFADABHFHFCFHFACCBBBHAHDHBADGDBCBDFEFDHHADACBHBEAEDDDGAGACAEHECFCECHHHEABFCFEEHGAFFFADADCDGEEEGEBECEBBCACAHAHADADFFAFAFHGDEEFEBCGCGCGCDCAHBGEEFGADECECAFAHA,False +236,13.0,6.0,14.0,8.0,9.0,13.0,7.0,14.0,FCFAFAFAHAHCDCDGFFEFECEDBCECDCFHEEFAFACHCHCEBGDHEHFHAHBHDHFCGGAGDHHACCBHDCGFGBAAEABA,False +237,4.0,7.0,4.0,12.0,6.0,4.0,7.0,10.0,DGGHBHDDDGDGCGCGADBHEDEDAGFCFEBDHDEBAHAFEHEHCHDBDBHFHB,False +238,25.0,27.0,17.0,20.0,11.0,20.0,27.0,24.0,BGGGHACECEFEAEDBDBHCGDGDHDHBHBHAHAHFBFGCGCAHFHABABEFFDDAAFHFHDAGADFDGBACCCHGHDAACHCHGBEBCCCBDAFAEGHAHGHGEDBDBCBHBGFEAGAGBGBABDHDGAGADFBFGFGCAEBGFFEHBBGDGBBBFFHFBFCDAGCGHDA,False +239,27.0,19.0,14.0,12.0,26.0,20.0,17.0,18.0,CACHFHBABHBABAHEGBDDEBFAFAEACABAFAHAHGHDFEGEFEBEBEAFCDCHABAGEGEDFBGBACAFDCDCAEHEHFHFEEEFABABCGEEEGHDHAHBHDFGEGBAAAFDHECEAGCGEBEDCDHFAFAGAGBGFFCGCEHGFEBEF,False +240,13.0,5.0,13.0,8.0,10.0,9.0,13.0,11.0,HCHAGAEFGBGAGFGCDCAGAECGCGEFEDHGFADADACHDFDGBCBCFEDEFEFBAHHHHHHAAFGCECACBCGEHEADCG,False +241,15.0,13.0,22.0,21.0,14.0,24.0,13.0,15.0,CECEBACABEFHFGBEFDCDBABGDAEADCDHGFGFDDDFDFDFGFEFGCGEAHGHGHCFCDABFEHHABCECBCHFHCACFBFBHBADFEFEFDFDHDHCHCDEDAGGECHAFDHCABFCFDFDGBGCFCACDCEA,False +242,10.0,3.0,9.0,4.0,10.0,22.0,6.0,6.0,CBAAFFFFGBDAFFFFFFFDGAGEHFGECEFEFHCHCEEEDCFAFAHAFBDEHGHCFEFCFCFEAAFAGC,True +243,16.0,18.0,13.0,25.0,8.0,14.0,16.0,17.0,CFHGHAFGFCFEDAGEBBFDGBGHDHAHBGBGBDCHHEBDBDBDCDHDHFAGGHGHABADDCDFBHAGDDDBCACECAGEGDDHDFDFHFHCGCGCDBAFAFDBDEFEACADADADBCFAHBHGEBB,False +244,14.0,10.0,26.0,18.0,17.0,28.0,19.0,21.0,HEHEHDFDFEGEGFGDCBBDAFHFHFDCEGBBDHFAGBHFHCECHCGAFCCDDADGHGCGAGBDCDHDHDACFCFGACEHEGDGFCFCFCAEFHHHFBFDFDCBCFEFCDGAGDEEFEFHFHFEECCCAAABECFHACECFAFGFCBCGHGHG,False +245,30.0,27.0,23.0,25.0,28.0,19.0,14.0,26.0,AAACACBCAEDEBEFCCHCAEGEDEFGAGCEAEADFEBBBEFAGBBBFDAEAEHHHHCFCHCHADFDEBHFACBFBGBFBCHHAHAEEGHHEAEGHGHGHGCAHADADAEAEAGDGBECHDDDDEFFDCDCACAFBFHCHEHEADFBFBGBDBCGABHBHDACCECDDBDBDFDBEEEEHCBAFHHDBBADF,False +246,9.0,17.0,16.0,9.0,17.0,6.0,11.0,16.0,HGEGACAHDHDCDEGFHBHDHECEDEDFDEEHCFCFHBEGGFABEHHHHGAABCCDBEBECHCHFBAHGCGABCBEBECCCCCEGEBBBBDBABEBHGEGA,False +247,10.0,6.0,15.0,20.0,23.0,16.0,16.0,6.0,AFDGEGEFEDCDFHEGEGFGBCACECEAEHEDDHEGEDEFGDDDCCCCGAGEDBABEFEFDGDHDGDCBHBGFFCFCEEEEFCHEFGDGFCDADCFCAEGFGBEFDADADAE,True +248,1.0,1.0,5.0,2.0,5.0,7.0,7.0,2.0,EFCFDAGFCFGFCHEHECEGGCGDGFGFBE,True +249,20.0,25.0,23.0,25.0,18.0,22.0,28.0,20.0,DGDBDAABACHGHEBDCCABFBAHGGBGEAAGDDFGFAHADADEDFHFHGGGFGFDHDEDBACDGDGBFACABBGBGEGEGECFFFEABDEDHFAFGBCBCACHHFHFBFBFHCHCHCECDGDCEHEGCGBBFBGEFEFHCGCBHGDGFHFEABCCEBDBHGDGDGBHCEDADCDCBAEAC,False +250,27.0,24.0,20.0,16.0,26.0,17.0,25.0,11.0,CHCBCACHBABAGHFEEBEGECEBEBEACDGDHHGAAFGEGABEGAGEGADADABAECFGBGAGAEBEADFGFECACGGFGEGDGFBFGCGBFBFEAEBEFAFAFEDEAAAAGBBBCDCDGECCCBCFADABHDEDEGEAHHBDEDFDFGCCCDBBHAHGBCBEHF,False +251,23.0,19.0,20.0,25.0,22.0,22.0,28.0,26.0,ACACGEBFHHCAGAGHGHGCGCGBEHFHFCAGFGCGHEHAHADDDDAEEEECCFBGHAHAHGBDECFADGCECEGEGDGAADBEAEFHFDGDGAEAFDECBGECCHDEEBGBABEHHAFFFFEFDADHBHBDDGGCGCBAGAHABDBDEFEBCBDHGHGFDFDFDFHBAFCBDBDFFGGCHHHDH,False +252,22.0,23.0,23.0,11.0,21.0,24.0,27.0,23.0,CGGAGEGECECECDBFFFHAHGEGCGAGACEDBBBFGFGHGHFCBGHFHBHGEAHAHABDHABABDBECHAHFCFEFAAGGGBGFCDCBEADADHFHDHCEABCGGGFGAHEEAECCCCGBBEHEHBHBHDCDFFAFBFCEBAGAGCCBCAGFDHHEHFFFCFEFBBEBFGEGA,False +253,21.0,15.0,11.0,10.0,10.0,18.0,15.0,19.0,CFCEEFHBGDEEFEFDAGAHAHGHFHFHGHAHAHGFFFGBDBGAAAABABGBFBFBEACGCEDHFACCFFFGECBAECDGGAFAHDHDHBCCGHAHAFAEDHDHGBBABDFCAGABHBH,False +254,16.0,7.0,14.0,11.0,13.0,17.0,11.0,13.0,CDFHFHECACEDEAECCHFHFHGHGCAHAGAGDEDFDCHCFDADFEGAAEAFFDEDCCEDBFCGCGEBEBHGAGFBABAGFHDHAHAEFFFFFBEBCGHACA,False +255,14.0,24.0,17.0,17.0,23.0,22.0,12.0,11.0,EDGFFFGBBBCACDDDBDCFCFCEEAFGFGFGFDBBBFBDCFEFADAHEDBDFHAAGHCHFGACABEDEDEAECEFEFDAABHHAHCECBFBCBFFDBDGHGHFBCDCECEDEAAGEGFBEBCBEEGEBEBEBHCEFBBH,False +256,15.0,18.0,13.0,27.0,17.0,28.0,20.0,24.0,FBDBCHCGDEDCGAGAGDDFBBBFFFFEDACGCHAGGGEGEBABFHFEDHFHFCBDGHGBGDHBCBGAEHFAFHHHDBDCHBFGFGFHFHEGEBDFFFHAHGHCHAHDHEBEFEDGDGAFABDBEHACFCFCEDADEFBDDEAEADFDFHFHFDGHEDDDDC,False +257,6.0,7.0,12.0,13.0,9.0,11.0,8.0,10.0,DDACHGHGHDHEFCCEGEGACCDCDCDADHBFEFEDEGCFBFDFBFEHCHDAGEDECBCBHFGFDFHAHCGABDBF,False +258,17.0,20.0,27.0,16.0,18.0,18.0,19.0,20.0,AGEHCDAGCGFGDCDCHCACDFEAGFGAAAADADCCHGHGHCCEEEGCADACAHECEGDGFBFBFCHCHCBBDBDBDEFCGCBBBEHFHACAGBCHFFBCBCGGGGHDBECEHEHGHBCAGEDEBFCEEBEBDFCFAFHBADDHFHFHFHECFBB,False +259,1.0,5.0,4.0,1.0,1.0,0.0,6.0,2.0,GGGGBGAHBHCGDBECCBCB,True +260,2.0,3.0,4.0,1.0,3.0,5.0,1.0,3.0,BFBCBFHEEGEHCACACHFFDF,True +261,2.0,4.0,3.0,2.0,3.0,2.0,6.0,2.0,CDCABEHHGFGFGEBABCBGDGEG,False +262,17.0,17.0,32.0,25.0,20.0,22.0,15.0,15.0,DHDCDCDGEHCBGBEBACGDFDCBCFCBCEAEAFCDEBAAEADHCEAEHECDDDBDCDBBFFEFGFBCBHAHFCCECGHDHFHAHACDEHECFCDEAAHABBCHGEGDGFHDDCDGDCCCGCACACFCFDADFGFBFBFEGEGEHDACGDFCFCFGBEBEFCF,False +263,7.0,4.0,7.0,4.0,5.0,5.0,7.0,12.0,GCACAHGHECGCHFGFEDHDHDHGHBAEAHBHFHGCCBCHEGEBHAFADAF,False +264,6.0,6.0,13.0,6.0,11.0,2.0,9.0,8.0,DCFBDBEEEEEEADAHGHGCGDHCHGEACBCGCAHEHGGAFAGCCCCCBEBHDCBCEGEHD,True +265,20.0,25.0,22.0,32.0,26.0,23.0,23.0,27.0,DCHBHBCEHHGHDCGCAHHGHDEEHEHBBECDCGBBACACADDDDDFCGEABGBABEBEBEACFHFBEGHFBABCGHGEGDDDEGAHAEFBFDGDHBFGFCDCDCDFGFHEBEHEHBDEAEACBDADHFBDDDDAFEFBGGGGHGHCHEHFCFGFGADDDDBDADHFEBEBECEADACBCFAFHFDFGFAEGHHCCFE,False +266,7.0,6.0,7.0,3.0,4.0,2.0,13.0,8.0,BGHCABHHCHGGBDBABAFCGEGDGAHCEEGEGBGCAHAHACGCGHGFGD,True +267,8.0,8.0,22.0,12.0,15.0,14.0,10.0,10.0,DCBAAGBEBEHECCCCFEDDDFGHGDEDCBCGEGEGEBFFAEHECFCHCHFHDCDCBHGGCCBCFCHHFAFGHGDFCEADCDCDCEBFAFACECAFEFE,False +268,20.0,11.0,17.0,15.0,11.0,11.0,19.0,11.0,FACAFGDHCEFHAECBCBEBEAEGBGBGFHCCBCAHDCFCDGDAEEEFBACADABACECHGGDBDGGGFHEHADAFGFGFGHGHGCFCDCDEGAAAABDDDGHBACACDGDHAGA,False +269,6.0,1.0,7.0,4.0,8.0,4.0,3.0,3.0,DBGECEAEAEAEAGDGFCHCECFAAHHFEFCCDEDC,True +270,18.0,16.0,20.0,26.0,19.0,21.0,22.0,23.0,BFBCDDGAGACDBDGDGDADHCAEACGCGDEBGDFDCDBDGHEHCFFFFFHFBFAFHDDGBHHHHFEFABGGDGDEFCDGHCHEFCFHBADHHCFCBGBFEEEEEFEDEDAFGHGDGCACDEAEACDEDHBHGHBHBHCDGAEACCEHGHAHACAGACBEBGFDF,False +271,0.0,3.0,1.0,4.0,2.0,4.0,2.0,3.0,HFHFEFDBEBHFDDBDGCG,True +272,16.0,16.0,17.0,14.0,11.0,14.0,8.0,16.0,FCHEHAFAFBFBDHGAFABBCDCDHBHEFABCHCHDAGABEBAHDHDFCEBGDFECECECEHECACDBDBDCGAGAGACAGBFBGDDACCDDBHEHBACFBFHHHFHFCFAE,False +273,13.0,11.0,14.0,14.0,11.0,17.0,18.0,16.0,CDFDGBHBFGFGFGEDABABCHHDDEDCHCGAGFBFDADHDCDCECAGEFEBEAFAEHEHGGEFBHCHFHFAFDFACGGFGHHDHGHAHCFAFGEBCBGBGCACDCDEHGFBAG,False +274,30.0,26.0,12.0,16.0,14.0,36.0,17.0,16.0,GGHCBABACFGFHFBBHAEAEACADADABABFFDABBFFEFBAGFHFBFCFBAHHHHGGDGFGBHBFEECEFDCHCHBHGEAHADDGAFAFDDBDGFGBEFFFFFGFACABGFFFAABAFACAGAGHDABABGDACFEAEADBBFBEDEAFFBFBFCFCDBHEHEDF,False +275,6.0,13.0,13.0,9.0,7.0,9.0,12.0,6.0,CEFBGCCCCHDBDBCAFDFDFGFHHCCGCGBGDGDBCBCBHFGAAEGBGBFBGBGECHCDAEGEFADAHEDEBBF,False +276,7.0,5.0,3.0,5.0,6.0,7.0,3.0,5.0,BCCDFEFEFEBADABCFDDHDHAAEAGFGFHFBAEAGHBHE,False +277,6.0,5.0,1.0,2.0,3.0,3.0,6.0,7.0,HBBFBFDHCGEGAHAHGHGFEBHBGGAEAHADA,True +278,4.0,8.0,15.0,16.0,12.0,11.0,10.0,10.0,DHCHAEEEHEHEFEHGFBHEDEGEGFCDCFCGCDCBFFFCEGDBHFDDADGGCGDEDEDGACDCFCFBGBHBDBCFCHCDDDHCAB,False +279,15.0,15.0,14.0,9.0,20.0,30.0,10.0,19.0,EAFFEFEFHBHBHBHCHCFAAACFCAHGBGBFEEBECEGEFDCEFEGCBFHFBEAFDBBGDDCGFDCBBHBHFEFEHCHFBFDGCHFHFHFGFGAAAAEECEFDBEFECEHDFCFHDHFFEAAAAAFGFHFH,False +280,20.0,27.0,17.0,23.0,26.0,20.0,26.0,25.0,AEDGCEBACABABGBGFDCEBHBCBCGHBAEACBHHHCDDEGFHAAFABCEHDBDBDFFGFCBGGGFGEEFEDEAEDEDHHHFHEEEGEGCBCBHBEBGBGECEAEHGHABBBFHEAFGBGDGFFEFDGDGDGHGDAFAGDHDECEHHHAHDDGHGCGEBEFABCBDBFCFCFHBADADFDAHH,False +281,10.0,6.0,6.0,8.0,8.0,11.0,10.0,7.0,GBFFDHAEAECDDBEGDGAEECGGGDHDAFADAEAHBHDEFFFFBCBCECAFABAHGFGFGFGHCH,False +282,21.0,33.0,19.0,20.0,21.0,12.0,19.0,26.0,CAADABABCEABHBABDCHEAEGHBBCCCCCHCBGGGGHHDHGHGDGDGDBDAAGCBHDFEEEEEEBEBAHHGHEHCCGHFBFBFBFGHBDBHAFAGACCHAHFBCCFDEDEHCHABDBEGADBBCBHEHEDDDDBDEDBBHAHBEEEDBBBBHGGGCEFBFAFBGAHAFA,False +283,12.0,9.0,6.0,10.0,12.0,16.0,15.0,10.0,CFCEDFGCGFHFBGCGFGABEGAGAGAGAFADBHGHDEFHHDGCADEGBBCHDAAAGEBEBABFDFEFEFHFHFHFHGBFEGEDDDEFEA,False +284,0.0,7.0,2.0,2.0,5.0,4.0,3.0,5.0,FBBHBHECBFDFGEHCHEHEBEBDGFGB,True +285,18.0,10.0,10.0,8.0,8.0,13.0,19.0,13.0,HHHFGFAHCCBCHCBFAGCGBABDBDGAFDCDAEAEHDADBHBAGFGFGHEFFGHGHBHAFFBFCFCAAABEEEAGGGAGCGFGAGADAGEHAHCDGEG,False +286,17.0,19.0,13.0,13.0,17.0,16.0,12.0,9.0,DBDADABCGDAFEFEFEDABCBEBGDGFEBEBEBEADBDGHCADABFDADADABGFGFCBCDCFBGGEEFCFAFEFBAGGEFHCGAFAHBHBFFEBACECACBCHAHEHEHCGBEH,False +287,11.0,13.0,8.0,14.0,5.0,10.0,1.0,11.0,ADDCHBHFDEACFDBDBABCBCDDDBAAADHFBFBABEHEHBHBCCHFDABAHCDDDCDAFHFEFEFHFHGAB,True +288,21.0,32.0,21.0,22.0,23.0,17.0,23.0,21.0,CFCBBDADEDEDBDHDADCCCEHEHBFBHADADBGBGDCBBHFAEBDHDFDFBEBHDEDBCECEGABCFGFHDHGHEHAAGHGEDEAEABGFCCBEBCFDFAEGGAGADECFFGFBBHCGEBEGAFABDBHFFAHAHAHBHBEBEBCBABDEGCGCHCHBHBGEGEGCAAGGBBFCCGDG,False +289,10.0,13.0,5.0,12.0,9.0,19.0,21.0,12.0,GBFAEDDDGGFEFDHHGHGFGFGDGFGHHHHEGDBHFGGHECBAGAEACFBBDBCADFGEGDBBBBCBHHFFBFBFDAAAEFGFAFAFDFDFHGGGGGECE,False +290,10.0,11.0,9.0,13.0,3.0,16.0,8.0,5.0,DBDBDCFFGFGABEBEDEFFGFGFAFABHCAFABCDHDADAHBGBDDDADFHCBCDCAAGHBFGFGFCCBFFCFD,False +291,22.0,19.0,25.0,28.0,18.0,24.0,23.0,17.0,FCFEFEFAGEGCGEAAAEGEHFHEGFGDGDEDBDEEECBBBEDFHFAGHCAGAFAHABFBFDDGECEBGFDFCFCDBEFABGEDACACDHDHDFFCDCACHCDBBGCDBHBHCFCDHHHBHBGFGFADDGDCDCHCDCACAGAGCDDABCEGHDHFGGDDEAFBFACACABGBGFD,False +292,22.0,21.0,17.0,19.0,16.0,16.0,15.0,29.0,EFHHAHDCDEBEHEHEHEHEHCFDBCBDHCAFEGGHDDBDFGFGHCFDDDDAFADCGCFDFBFBHGAFCCBBEEAAGAGDEDAHAHAHBHBHBHEHCABABHBCCCHCBBBDAHGFDEAEAFHGBGEHAFBGHAFAFAHABCDDECGCHHGHGAB,False +293,14.0,10.0,22.0,19.0,17.0,10.0,11.0,13.0,FDGGCACGCDCACBCDCDGHHDHBHFGGCCFBFBCBDFDAGEHAHEFECBHGDDDCEBBADCDFDADEEEEDEBHAHAGCGCBDGECEHEHAACADAHFHFEFCCECEDECCDAEA,False +294,21.0,23.0,11.0,16.0,19.0,13.0,19.0,13.0,ECDFDEAGAEAGHBFEFGHBBGBABABGDGCCAGHBHFEFGGCBDGDGDGHFHABAECEAGHFDFEFBFECECEFDHGFGABAEHEGEBBBBEBADFEHEHBDBDADADGBHADADHGAEBBBDCACECBCAAGA,False +295,16.0,21.0,15.0,23.0,14.0,18.0,17.0,12.0,DDBBHFDFGBGBHBFFFFFFFGEBCFCGHABBEHDDDDBBBBDGFHFAEDHDHCFCHCECBAHACDCDHAAADDECACAGABAGEFEBCAEACGDGFEFBGBDBCBGGDDAEFEDGCGEGEDEDGDBABADFHCHG,False +296,2.0,5.0,5.0,3.0,8.0,3.0,7.0,5.0,GHDHFBBGGCGBHEHBCACHCGCGEEEEFDADBEGEFE,False +297,8.0,7.0,6.0,6.0,3.0,4.0,7.0,7.0,GDGFBFEFAAEBDBDBAGAEHBDBHCHDGBGCGHGHAAACHCHAFCCD,False +298,10.0,8.0,9.0,8.0,12.0,10.0,12.0,8.0,AAAAAADGHGAEEEHFHEHEFFAGAFHCDCGEBCBCBFBFAFHFGGCGHEDGDFDBGEDEDCBEGEGHCBEBCCDGF,False +299,2.0,2.0,2.0,2.0,1.0,0.0,0.0,1.0,CHCEABDBDA,True +300,21.0,16.0,12.0,20.0,12.0,15.0,16.0,21.0,HFHGDDEFBFBFAGCFAGBGDHEHBHBHAEFBDGACHGHAHFFDFHFHEBBCBDBDBCFCDCACAEDEDHAHBHECABAGCEBHBGEDEGAAHAFAHADCDEGEGADFGAGAHCDAGADAHCHDDGDGDHFBF,False +301,18.0,17.0,21.0,18.0,14.0,17.0,20.0,23.0,BEBFFCAGAGAGHGHFHDHCFDFDEDEBEBEAGFBCCHCDCBCHHGHEACAEFGBGBEDEBCDADHFAADBHBHCHFDFDFHGBGBAEFGFAAEHEHEHCCGHDDDGHCCCCAABCGCGCADACABFEHDBCFHGHGDAHHDFGBGFG,False +302,17.0,9.0,16.0,15.0,18.0,20.0,16.0,20.0,CFEHGDGCGHFADAFGFBFHABACDEDEDGAEHEHCCCBCEFHGHAEAEAHAHEHEHCDFFAHDEAFDFGBGDHHFHFAGGFFBEHEAEAFFFDGBGCGEECAFFHEHEHDACBCFCDDDDCBCBHGAGCG,False +303,17.0,9.0,12.0,14.0,11.0,11.0,11.0,15.0,DFDFAGHHDEDEHEHECGFACAEADDHDEDCHCECFHBBBEGHBACGGGAGAHDHAAADEHEAFADGDBDFHFGBABABHBFCHAHACCFCGCEADFCFG,False +304,32.0,22.0,21.0,20.0,17.0,21.0,22.0,16.0,HABACGCBCGHGHADEGABAFHHGFCCGFFFHFHAHAGACFGEEAHAHABABFBAEAEDGDBDFFFFEGHGDDDCHFAFGECACECECEDFBEAAFBCGAGECECFCFCBGGADADGHACAEBHAHABGGDDADCDADBBBGHEFEDDDGEFBDBDBCBABCBAAAACFGB,False +305,22.0,14.0,10.0,9.0,20.0,15.0,19.0,12.0,GAGABHEFGHGABAEDECGAFABBEFEAECCAAHGHBEEEEEFHFGFGAEAGAGDGHGFAAAHAGAGFBECEFFBBGHGFCBCGCADEDBDBDBDFEECEBEDGAAEAFAHHBFCFCDHGH,False +306,7.0,13.0,6.0,7.0,4.0,5.0,5.0,12.0,BABAFAHDFDGBHHEHBDACHGHGDDBDHFFAFACEBEBEBHBCAHBHDHCGBHBCGCB,False +307,27.0,19.0,23.0,17.0,31.0,29.0,21.0,17.0,FADCDEGEBEGHDAEFEAEBHBCBAFAHAFGEGFBFCAHAHCCBDFHGCEFFCFEFEAEAFCBDADADHDFBFBEBADFCFEFBFBFDFCFGFEAHBBCCCCHHBHAAEGEBECEGDAEFDGECEFEHGAGEFEDGBABABHDHDCDCGHAEACAGFCECGGHEDCFAAAGAGCEHEGEGFGFE,False +308,16.0,23.0,23.0,25.0,22.0,21.0,28.0,27.0,BHGEFEDACAGADADGDGDBBFBCGGHGFCFCEHHDCDCEGFCFBEBEHDHCHCBEDDHBBEBGGFDECHCHCBFDFBGEHEGEDEGAHDBDAHGBGDGBCFCGCGBBAFAFABBBFGFHAHAEAGFFFGDDCABHECEDEBEHDGDEDEGCHCDCACHCAFGGGHFHFHGHGCAEHHHHDDBEF,False +309,11.0,10.0,14.0,4.0,9.0,15.0,8.0,17.0,CECHBGAHBHAHGCACBEFEFDCCCCCBCDCGAFFFFFBCBAFHFHFHDAEAHGHBHBHEHBHCGFBHAAGEFEFEGHAHDFFCAEHG,False +310,7.0,7.0,11.0,8.0,8.0,14.0,8.0,4.0,AFACGFEEDBGHDDADFCFCFCFDBGBHEHFAGDCACFCFEFBDBGBEBFCFCFCADGEGEAHCFGE,False +311,1.0,3.0,3.0,4.0,1.0,4.0,5.0,3.0,DHHBHDGDGCFAFGEBCBCGFGFD,False +312,9.0,6.0,12.0,3.0,7.0,3.0,4.0,5.0,AAEAECGCDFDHACECEAEBHBACCHCHEGCGCHCACBBAFAFCDGEBB,True +313,10.0,20.0,11.0,11.0,10.0,21.0,14.0,10.0,FHEBEBCAHAHBFGFGHGFAFCFDBDFDCHBECCCHEACABDGFBFEFAFAHGBFBDBDBFCCCEBFGGBGFAFABEEAEGBBFFDFBFBDBGBGCGDEDHFHDGGH,False +314,11.0,11.0,19.0,12.0,11.0,7.0,10.0,11.0,GBHBFGDABADADBDCDADHBGCECHCHCGCEAGCGCDCFEAGAEAEHECEFFBECDCGEHCBBBCGDHDBDADCFFEFCACAEBHHCHGHC,False +315,15.0,20.0,19.0,23.0,12.0,16.0,12.0,15.0,CCCCEFDBDHDCDFDCHFHFDEBACECHCGGFGAHDDDBACFFFDFBBABABDBACADAHCHDGCFFBHHDHDHGCCACEDBDECEHEBABHFDDDDGEFBFBGBEBFAGAGBGHEHDFEBABAEADBCGCG,False +316,6.0,8.0,6.0,3.0,8.0,2.0,0.0,9.0,CBCDFDHABAFEHBHBHECEBECHHBEEECEHAHCDAHABAB,True +317,5.0,12.0,12.0,7.0,8.0,8.0,7.0,11.0,CHGBGBFBFDABACAFFFCECHCEGDBBGHCCBGDGFGHEHDHCHBBCCECEBEAEAEHDCDHHBHBDFF,False +318,19.0,29.0,24.0,19.0,24.0,39.0,20.0,15.0,CFEFGHBHFHCEABFCCCFFEFEGBGBAHAHDBABCBGBGBGAGAGABHCCCFFFEHEDGBHEEDHDEDBHFDBCBGBFCFBEDFAFCFGACEFGFGAAFFFFDFEFECCGEGBDAAECECABEFDFCEAEAHFDBABDCHGBGBGBCACBCBEFGFGFCFHDDFAEHDFFEDDFDFBFBEBEBFHFCD,False +319,8.0,5.0,5.0,2.0,5.0,4.0,3.0,7.0,HAAEAHDHCBDEAHCGFGCEABAEAFAFHFHBHBCBCEG,False +320,4.0,0.0,2.0,0.0,3.0,0.0,0.0,1.0,CACAEAHAEE,True +321,19.0,25.0,20.0,14.0,21.0,25.0,19.0,10.0,ECEAHAGAGDCFHAHAHABEGAGBEBFFFFFGFDFDFGCDCBABEBGBFFFAGADFDGHGABAHAGCBABGDGEEACAEDBCBCEEFHGDDCBCEGEFEBEBFGCHBHBEDFHBCGEBCDCFCEBEFEBCBCBCBAGFFAFAFDCGEEFDCBF,False +322,4.0,3.0,7.0,8.0,3.0,3.0,6.0,6.0,AGDFDFDAGECEDDHCHGHCBFDEBCBCHCHCDDAHAGGG,True +323,20.0,23.0,10.0,13.0,14.0,23.0,24.0,21.0,AGAFFGHGEBBCDCEEEGBFAHAEGEGCGFGAAEBGHEBDGAGEBABEFCHAHADFBFDFBHBHBGBEBFBFHCACGCGBFBFAHAHFEFDBGGGBGFGBBEDHGHGHFHDHDGDHBFBFDFHFHFACADAGEFHCAADHBHCADFGA,False +324,6.0,10.0,13.0,15.0,5.0,10.0,12.0,7.0,ABBDDDDGDHDCBBHCHGDGBAEGEGHDBCFGFBEBADGCGCGHFFFFFCFCBDBDGDCAAAFDHCCCECDFDHCGEG,False +325,14.0,17.0,16.0,18.0,24.0,25.0,25.0,12.0,EAGDFBFEHEFGADABCCEGEAEGEGHGBFBDEAEDHDFEFDHCHGBGEECDCDCDCHCDEAEACCBEGAGEBFBFBFCCGFBEBCCDEDFDHHGAGAGEEFFFFFBGHGHBDECEBAFAFDFDGGGAHBEFGFGFHDGDEFGCABFBFGG,False +326,10.0,8.0,13.0,7.0,11.0,10.0,9.0,12.0,HGFCFAFCFAGADEDBHFCFCHHAHACEBECCCCEGEFEFGDBFBHBGBCEEABCECAADDEDHDHBGEGAHCHFHGAGH,False +327,13.0,9.0,7.0,7.0,11.0,9.0,9.0,4.0,EFEGEFABAFHDBFAFGGEBEFECCCEFFDADBDGEGAGABABABFBDDAEAHAHGHEAAGDECCCGCB,False +328,11.0,7.0,14.0,13.0,15.0,16.0,11.0,12.0,HHHHFDGEGFHFHGDGCCHFBFEDBAHGFCDCGGDDACACEDBGEDEHHGHEFEFCFGFAAACADHFAFCFCFCBDBAEEEEGDFBFAEAEDEDEBCCC,False +329,14.0,9.0,16.0,7.0,13.0,4.0,16.0,18.0,GCAEFCFCACAEDGGEGBGBGBHBHAHECAAAAHAHECECHGHADDCBCFCHHGAGEGDGEAECGBHDACECBHDCDGHCHGEBHBHEHCFGEGHHA,False +330,6.0,12.0,18.0,17.0,8.0,10.0,10.0,6.0,GGFCECDCDCAABEBEHEFDDADGDBDHGFBFBEDHDFBHGGCBCBCDCBCHDGCBCBEDCDGDBECADACCCFEFGFGFHDADFCC,False +331,11.0,25.0,21.0,16.0,17.0,27.0,21.0,23.0,FFFCHCBCGHHHGGCEBEDFCHAEFCFHDBDBABFBFEFBFHDHFBGCACHHFBFDFGFBHHDBEFAFAFHFEEEGEGEGEDBHCDCACHHGFGFHHBDBDBHCHGEDBDECECECFGBDBCEGGGGCCBCAAADAHBBBGBGFGHDAEFGFBBGHDCFCF,False +332,31.0,34.0,15.0,23.0,18.0,19.0,14.0,23.0,HBFBAAACBDEABCHDHAHDFEFHAAACDEBHBHBHBCBHBHBGCAFGBGBFFDFGAEAEBDFFADADACADDDHAHAEEBFDFGCCCFCAEGBCBAHCGEEEEEEBFDFEHBBBABAHADBDEDFGHHBHBDDABBHBHDHFCFCGEBAAAEGFDFDGDBBBAGAGABAGHBHCAD,False +333,20.0,17.0,9.0,14.0,13.0,13.0,13.0,14.0,ABGCECACBHDHGEEHEHBDAAAFDEDGDFAFABCCGHBABEBEGADADFDEHEHEGBGAHADDHHGHGCGFFABAFDBDHABEFDCDFFAFBEBHBAFAFABABGCECHGBG,False +334,7.0,5.0,2.0,4.0,6.0,6.0,4.0,9.0,GCGBFBHAHEBEAEDCGEAEHHFHAHABFGFHFHDEDADAFHB,False +335,17.0,13.0,10.0,10.0,9.0,12.0,9.0,20.0,AGHHAHAHCBABFGADADEFEFEDBBBBHHGHDHBCECEHFHFHBHAHDEAEAEBEHACAGADHCHBGGFFFHACBDFDAGHCDGDCFCACFHFBBHGAA,False +336,10.0,13.0,6.0,5.0,11.0,4.0,11.0,9.0,EGEBEBEGEBAHEFBCBEHGDFHFAFCBHBGDABHGGGBGCGBABADHDCEABABADAEEGAGCHCHEH,False +337,17.0,16.0,15.0,8.0,14.0,17.0,17.0,24.0,HBGBABHBHDFFAHAHAGAEAEAFACGCBCECFGDGCCEFEFHHHABGFCHDHGBCBHBDGDHEHGHCFCHGHDHFHFBFDABHBGBAFHEEGEGECBAGEHBHCHEFEADCBFGHCEFGCGFAAAAF,False +338,18.0,20.0,22.0,16.0,18.0,27.0,14.0,22.0,AEAEAEAFHDHAAEFBDHGFGFCAAAGADFFEFBADCHCHEGBBEBGFGFGEHEDCFHAEBHCDCBCGAECGCHCHBFBEBHHHGCBHFDDGHHHCHBDEDECBDFEFBFGFCFBFBCBFBFCDEAFDGABADADBFFFFECECADHHHCHCFCFCG,False +339,24.0,25.0,25.0,23.0,21.0,21.0,28.0,25.0,ABAFDFCFCGHGCDBDGEGEGCAAEBHBHGHGHDADCGCHFECEBDHDABHGCGHDHEEEBFBFBDDCDGEEEHBFFCFBFAFAFGCCCHGGFGCACHEDEHGDDBHEHDACAFHEABGCACABDBEBFDGHGHFHEAEAEADACGGBBBCGCGDGBGBFCHAHAHFBABFCEHBADGDEBACGCGFAFDHD,False +340,14.0,19.0,9.0,8.0,9.0,16.0,11.0,11.0,CAADABAEACBCBGAADHBFFFBDBDEGABHHHAEFHBCFHBEBGFDFBFBDBDBDAEGEGEFCGBFBAEGBGFGFHFHFGFCBCAAGAFEHHHCBC,False +341,2.0,6.0,2.0,4.0,1.0,4.0,1.0,1.0,ECBDBFAFDFDBGBHBCBAFD,True +342,10.0,9.0,6.0,7.0,9.0,12.0,7.0,13.0,AEAHAHFEGEGBGAEBBHFDBGBHHGHAFAFAFHFDDCDHECFCACFHFHCDCDHBEBFAFGFABEEEGBDHH,False +343,12.0,23.0,13.0,17.0,19.0,18.0,25.0,20.0,GCGCGCFABHCGAFCFDFBHBHEECDDBEHEAEABABAHHFFDFGEBEBGCABAGGEGEDEDHBCFDHDGBGDGHAEAGDHAEEECHHFBDGCFCDBDHFHBBBDHHCBEHFHGGGFGFBEBEFEFCFGFGHGDGDBHBGBABDGEG,False +344,8.0,19.0,17.0,14.0,18.0,17.0,16.0,26.0,BFBHCHCACDDFCHEHAFAFEEEDHGHBEEFADGGFGEEDEDEFEFBFBHHGHGHDEFCGCGHDHDBCHDBCFCGEBHBHEHFDEAEBEGCGBHBFBHBCBCBCBGACCHHHGHFDFCFHGDGHEHDCBAAFHBG,False +345,14.0,25.0,9.0,16.0,24.0,29.0,24.0,20.0,BDBDFDFEGEDADGGGGDFAABHGFGFEBHFECHCEDBABFBEDGGCFCEAAHGHFBBHHHHHHEBEBFAEEBEDGDCHEFBFBFBHEGEGEAEBGGCAFFGDGAGAGHFFFFFGCHAHBHDEDEFHBBBFDFHFBFBFBHDEFGBEDEGEGBAFFCACEG,False +346,20.0,21.0,26.0,20.0,28.0,15.0,21.0,20.0,EDEDFHFHEDCCECEHEHCGBBAEFDDHBGBEBGAEHECGCACECGCGCDEHCAFAECHBBDGDFCFBBHBEBEHDGDBDCAGACAHAHDHCEBEHEACDDDFFAGAFAFCGEACACGEEAHAGAGAGEFEFHFBGCHBDBHBCGDGCECHDHFBFDCGCBBEBDAEGEGE,False +347,9.0,10.0,7.0,7.0,9.0,11.0,7.0,1.0,DAFCBCBAFDEGEGEFAADGEGEAEAFGFBFEFCFGFCFHEDCBGBEBAFDDABCBABDBC,False +348,23.0,21.0,22.0,23.0,12.0,21.0,19.0,12.0,DBGBGFCCGCDHGFGFGFDCDEAEAFBFBHGHBCBABAFFFBBAFHFCDBFECCDCACAEADFDEDGCFCHBBBBDFDCGAHFGEADDGHFFDADEGEAEFEDECACACAFADCFCAGBBABEDGDHCGCACACHBDGGAGBGBHAHADDDHB,False +349,24.0,18.0,28.0,33.0,14.0,23.0,32.0,22.0,DBDACACDEGGCFCBGBHFGDGDEDHHADCFBFDFDAAFAGDGCFCECEGDGFBAGHDDCDCDGHCFFAFGDGDHDHFGGBGHDCDCAHFEDBFBFCDDEDGHAHADABHBEAAACADGBGAGAFHCCGFGCGDGAEAGDGHFHFEBAHCFCFGGGEGEGAGHBBBDCCHCHFHCHDFDBDCDEHECBCEAABC,False +350,8.0,4.0,6.0,7.0,7.0,4.0,16.0,7.0,EDGFGACAGBHBEBAGACAGEEEEEGGAGCGCDAFHGDCDHGHCHGBGAFDFDGGGDHH,False +351,14.0,22.0,13.0,15.0,4.0,11.0,14.0,13.0,ABCCHHFHCDBDBDBCCGCGFFDFBFGGBAHADDGDCDCBAHABEFHBBDBDBDBEBEBGDAEABDGFHBHGAGCBFHHHHHACGBGACFBBDGDBFAGAGACACF,False +352,23.0,10.0,18.0,19.0,18.0,25.0,14.0,15.0,GFADHDHFCGCBFFFHHEDFDHAEEFECAGBGEAHAHADAEGCBFBFEGEFHHEGGCFCHHAHAHEBAADAGBEBEDEDGFEFAFADADFGFAFCECECFFAFACACHCDFDADCDGGFDHCCCCDGDAFBFBEADBDAECF,False +353,28.0,26.0,15.0,29.0,24.0,17.0,31.0,29.0,EFGDADGCGBGBGBEAEHGHFDDEDEDEGHGEGEGHGHEHGDGBGFEAEGDCHCHDHFHEHAGDHDFEBEBEBEDCDCACAFGFCABFEGBGAGHHBDBABABHHAHAECEAGBGBHBFEDHCFCDGAFDHBEACFHHGDADHCFCBAAHFFGFDADBBEBHACABAHGDGBEAFABDBGGGGDDDAAHDDDHCHAABE,False +354,2.0,5.0,6.0,7.0,4.0,6.0,4.0,6.0,BHGHAECCCFADBDHDEDBFBHDCDCDFGCGFGFHHEFEB,False +355,6.0,5.0,6.0,6.0,6.0,7.0,2.0,4.0,HFHCGCGBFEAAAHAFBCBDEDEDEDCDFFABBCFCADFEHE,False +356,6.0,7.0,14.0,10.0,18.0,19.0,15.0,16.0,FBEHFGEHFDCDGGGEHCDCDFFFHBABDFDFHCCFEFECEHEFCAAGFGBCBFGFEBCACACDFFGHGBEHEHEHFHCCEGEGEGECAHEDEDGDGEHHHGHFF,False +357,14.0,24.0,11.0,19.0,13.0,13.0,20.0,12.0,CAHGEBBDBFBEGHAEDBDHDGDGECACACEFBDBFFGADBHBCCDCDHDEGEAFAFEGBFBABHFHAEDEDGHGBEBGBGBGFFBCGEGDAFAFAHAEBCGDDAGHHBCBDBDBFBDBDCGGGGH,False +358,14.0,23.0,16.0,16.0,14.0,16.0,6.0,16.0,HBCBHFHFHDBAGAEDCCCBFDFHFHDHDHGHABCFCFAGEGBBBFDADADBEBHFCFDFCBADDBCBCBCAEGEFCBABAFAHBFBEBEBCCEEHEDECBFAEHGADHDHEHBDEFBCDA,False +359,13.0,21.0,20.0,21.0,14.0,16.0,20.0,15.0,GFDBDCACAEBEBEBHBCBCECEGACHCHAHAGGBADADBDFCFHGDGDGEBHBDGGFGFGDBDAGABDGDGEHFDAEFFGFDHEBCCDCHCFCECHGDBCEHEFDFDABEBGDGHACFFBDCEAFGDBCGCBCFHBHBH,False +360,2.0,2.0,1.0,1.0,3.0,6.0,2.0,3.0,GFFFEFEBDBEHGCAHAHFF,True +361,14.0,17.0,14.0,17.0,23.0,22.0,11.0,18.0,DHACABDDDFEFBCAEAEAEFCFEFCFDFHFAFBCBCHGHFHEAEGBHBGCFCHAEBEFECECGFEDEFCCHAFAFAFADGHGBGDHDEDAHBHBHGEEBDHDBEEHGDEDEFBFBFHFGFBDAEBDGCHEEDCHB,False +362,7.0,7.0,14.0,4.0,6.0,6.0,6.0,3.0,CCBCGEGCAFAEADAGFGFCFCBCGHBBDBCGEAHAFCDCACBCHCEEFECBD,False +363,10.0,8.0,17.0,16.0,17.0,20.0,8.0,12.0,FEADABEGEHEBEBECFCDCHBHCAEEGHCFGFGFHHEFEFDFGFDECCACHFFFCDCGADAFGDCDCDCEFFFFAHAHBEECCDADAFFBEDEDEDHCFCDBHGHDB,False +364,8.0,4.0,4.0,12.0,13.0,9.0,10.0,11.0,FFHEHDFFAGEGEHEHFGDDDEDECEDABHFGFGDGAFADAEECGGABDBGHHCDCBGFDHDHAEAEHEHE,False +365,6.0,2.0,5.0,1.0,4.0,5.0,1.0,5.0,FEACAGFEFHCEABABAHFFEHAHCHCDC,True +366,11.0,5.0,9.0,15.0,4.0,9.0,12.0,5.0,CCFDEDFDFEFEHDBDCDHGGGGDFDAACADABFGCBCAGAFDFCGCGAHAGAHDBDHCGEBFDADADGG,True +367,22.0,11.0,14.0,10.0,20.0,19.0,35.0,19.0,DGGGBCECGDADABABHEHBHGAGHGFAFAGBGBGEEACACFEFGGGEFHCDEEBEBAHCEFFFFHAHAHGFECBHGGEGEHAHFGBDFHEEGCGFDAAAGEGAGFEFHFGAGAGDHAACAGHGCGAGDGBFHFGCGCECEHFHDGEGCD,False +368,2.0,3.0,4.0,0.0,3.0,2.0,2.0,2.0,BCECECHFHFAGEGBBCA,False +369,2.0,7.0,10.0,3.0,12.0,8.0,6.0,9.0,HHDHDCCEGEFFFHCBBHDEGEHEFEFEFEFBCBEBHBCCGCHEHBGGACECEFGAC,True +370,17.0,20.0,13.0,14.0,12.0,20.0,18.0,16.0,HEFEBECCHDECGCEBBGCDBDBDGFGFAFHGDDFDHBBBFAGDFAGACEFHGBFDFHFHFHCGBEDHFCFCFGAAEDECEFBFAHABACAGAGACAHABFBFGEGDBFBHBHDHDGBABAGCGEBAHGH,False +371,14.0,16.0,16.0,7.0,13.0,5.0,11.0,14.0,GBGBEHFHFBBBECAABDEABAGAEDEDBCEGECCACAGACACBCHCECEGABDBEBHBHFHCDAEADHCHCHFHCEABBCDHEGFGCHBGGHGHA,False +372,9.0,15.0,11.0,10.0,12.0,17.0,13.0,14.0,BEBEBGFFBFGFDFGCGCGFHDGGCFAFAFBFDHDEAEHEHAFBFEGHHEBGAGCHHHDDCECGCABFBFHFEDEDHBBCBGBCAGACAHBECEDDHBHFF,False +373,14.0,9.0,8.0,14.0,6.0,19.0,18.0,14.0,BHEFAHAHDDDDFBFDFGFEFHGBBFAAAGADHGBFCDGBEFGFCHHGFGHGHFHGEGAGEEAGDDABGGCCCBHBHCHDFAFAFAFGFDFDADADCGCGHF,False +374,13.0,6.0,13.0,5.0,8.0,10.0,12.0,6.0,CBGADAHAHAFAFGCGFGCDEAEADADCBHDFAACCCAFHBBCEGEGECFHAEBEHCGFGFGEGCGCFCGABF,False +375,8.0,5.0,6.0,3.0,11.0,9.0,8.0,4.0,EEEEHFFBFGGCGHGEBABEEFCFCBHGDBHFAFAFDFGAGDGAECECECAAAE,False +376,6.0,8.0,6.0,9.0,8.0,5.0,12.0,5.0,AEGEBACACHCGGHDBDBCEGEBEBHFDDGDCDBDBEGCAFBFGGGEHEAADFDFHGGG,False +377,2.0,3.0,2.0,5.0,6.0,4.0,2.0,2.0,EDEDECEBHBGFGAEADFHBDFEFDC,True +378,18.0,11.0,12.0,20.0,13.0,19.0,14.0,21.0,GAEHGHAADADADBFCECDCFCGDDFCGHAADFFFGHBHFDCDBFHFHGHFAGAGABADDHAEDECFFFAFAFDEDEBABFBGGHBCBAACBHHHFFEDEDADBEHFHGCGEEDHDCDGHGHEHEHCH,False +379,15.0,10.0,10.0,14.0,7.0,13.0,13.0,11.0,FHGHGHBBCDDDDABABGCEDADCHGAAHAFCFBDBDADFCFDDHCHFHAHCHCBCGGAACAHGGGGAGBEDFDFEAGDGFEBEFFAFAEBEF,False +380,20.0,20.0,27.0,28.0,18.0,28.0,19.0,15.0,FAEAEHHHHHHECBHFFFCFCDAGFGDEDCDCBGFFCGBGEGBAEAGFCADGGBEBEFHFDCBAEFDFDEDAHAHGEDAGBGFEBEGFDDDFDFAFCCCCCCBCBCGCGCACDDBFAFBCDADCDEDBCBCGHGFGBBAFDCDHBHDDBDCECACDFDGABFEDEAEFHHAAFFF,False +381,9.0,4.0,8.0,8.0,10.0,3.0,5.0,2.0,DEDECFCECEDAAACHEGDDFDFCACECGAABDGCHBEBGDGBAEAEAE,True +382,28.0,23.0,23.0,25.0,22.0,19.0,22.0,24.0,EBAHHEDEDBDHHGADFEFEHDHDGFFDFDADHDGEACBEHEFGDGAGAGEBCDCBBAFECHGGBHCHCGGGCGAFCHCHBBEBFBFHFCGCGEDEAAADABABADFEFDCDCECDCHCHCBAAAAAAHAFEGEADCCFHFEBEBFHDHFAAAGCBBBCDHDEDFBEGHCBDBGHGCGHDEAGABA,False +383,4.0,5.0,2.0,2.0,4.0,7.0,4.0,2.0,FAFBFGCGAGAGFBDEFEFHABFBDCHEBE,False +384,23.0,10.0,11.0,21.0,17.0,14.0,20.0,15.0,CBEFFDDBFAGHDAGAGAGDDBEGCCCDCBHHEAEFGFEEEHEACACAGAGBDAAHFHFAFADEHCACGDAEEFGGHEHBCDAGAEDEBFGHDHEHDHFHAGAGAGAFAFABBCDGGGDBDGDEDEDFDHD,False +385,16.0,15.0,15.0,12.0,17.0,20.0,20.0,23.0,FGBHBHAHAHBDFEFEBCAEEDEAHBHBHEFDCBAFCFAFAGHGHGACDHBCAEHGHBABFCFDGDFDFHFDBGFGHHACADACHCGBEBEHEACGEGFGFGDGEGEGECEADACBGFHHDFFHFHFGGBHCGCEEHC,False +386,22.0,28.0,19.0,25.0,19.0,24.0,12.0,27.0,BHDGBHDFDFDBABGDHAFAECECBCBCFCBEBHHHEEEBAFDFAFADECBDFDFAEHBHEHEGEADHHHFHFHDBFHAHADADFDFCAHBCGCDCBBBGBFAFCFHAGADDBFEFEAAHCDCECBDFFHFHBHBFEDCACAGEFDHGBEHGBCBHEEGAGHBDBDGHADADCBCB,False +387,16.0,23.0,23.0,12.0,27.0,6.0,20.0,14.0,EDEBGBEBCGGHCACBHBEGAGHGCGEGFCHBDCHGHBHGDADADBBCHCBEBACGEGEGEBABABDEEHECCCCBBBGAGAEAGFGHACCBBABAGFBEEEEEECGDDCDHEEEAEAECDCECGCFHFCBCEADDHEBFH,False +388,29.0,22.0,29.0,26.0,26.0,22.0,19.0,18.0,CECEGHFBFDDCDHGAFBGDFAAHACACAEEBEACFCAEECCGCGCFFFABGBGDCDGDEAEABHBHBFBHAHDCECECHFEFBACDDDEHAGABADFDFDBDBDECECEDHDAAAAEBEGAAADGFBFADACHEAACFGFGCGEHFHFCCCDGGBCEGFAFEBHCDAGBCBCDCEEGDBDBDHFHEBEHH,False +389,6.0,5.0,9.0,6.0,6.0,10.0,3.0,6.0,AFFFACCCEHHHHACDFDEGCBCDEDCFBFBDBFHFHADGCGCEFAFAEBE,False +390,5.0,5.0,8.0,6.0,3.0,4.0,2.0,9.0,CHCGBFDADACBFDFCHHDHDHCGCBFAEAEAECHCHBBDHH,False +391,17.0,18.0,29.0,20.0,13.0,16.0,17.0,22.0,GDCDGHHBEBFCFHGHAAAHBCDCDHFHEHBDDDDDCDCACHEBDBCBFDACBCBHACCDCGGGGCBCFCFBACADHHCFCADHHHGCBBGDGCGEEHEACAGGFGCABABDBEECECECFAFAGHHDHDFBFGFHECEFDFAHBHFGCACE,False +392,4.0,11.0,10.0,5.0,8.0,5.0,3.0,15.0,HHHHEEDDBGHGFABEBECCBHBCBEDECBCHCBEFEHDBDHAHBHFAGCHCHCBCAHFHF,True +393,5.0,6.0,6.0,2.0,4.0,4.0,5.0,6.0,HGFGHHHAGCGEFEBDFDAAHAFCBCBCECBGBEBHCA,False +394,21.0,28.0,17.0,22.0,17.0,15.0,15.0,14.0,DHAAAAFCDBDBDGGABBBCHCACGHFBBBBBBBAAAAFBBBBBEGEABCGFDHEHEDBAADEDEDEHCFEBEGDHFGGECDCHCHBDCEFEHDBDBDBDCECGCBFDGBADHGGFAFAFACEGEFDFBABFFEGDAACACHEHDHDCG,False +395,17.0,17.0,23.0,13.0,25.0,16.0,32.0,27.0,ACFCFGGGEEHEGGDEHBACACECEFEFHDEDFDGEGBGFHCCACEEFDACHGHGHBEEHBACCCCHCEFDAGAGEGCBHBHBGGGDGCFAHGHGHCAEFBBBHBGBHHEHEBGGEGEFHFHFHGHGCFCGHGDEDAAAGCBBBCHAEAHDHDFGGGEGBAHECDFDCAE,False +396,2.0,4.0,1.0,7.0,6.0,10.0,8.0,9.0,GCGFGFGHBFAEGFHFHGBDHEFEDHDEFEFDFEFBGHHAHGDBDHD,True +397,12.0,14.0,13.0,17.0,13.0,20.0,12.0,15.0,CEBHFCBGHGEGEACAHBHBDBGBADFDHDFDADHHEHFHBAAFACECECEDDGDGDCCCHCGBBDGFBECGDGACFFFFFFDHDHAEFEFBBGBFHFHECAFDBEHDFAFAEGFD,False +398,28.0,19.0,7.0,24.0,27.0,19.0,20.0,15.0,DHEAEADDHGAAHAGEHEBDBDHFCFEFEFEGAGHGBFHECAAGDCDADFCHDADADFDHGBGAEHDGFBFAFAFEFEFEHCAAAGGBBABDBCEADADFEGEFHADEGGGEGEGBGBDADEEBDBDHEEEDADEBBFHEEFCFEFAAAGABABDBHBG,False +399,0.0,3.0,1.0,3.0,3.0,3.0,0.0,4.0,DDHFBFEFDHBHCHEBE,True +400,14.0,15.0,8.0,10.0,12.0,16.0,15.0,13.0,BABABGHFHEHEAEBFGHDBCBGDCFFGAGDGFEFEFEFHDCAGAGHHAHACBCBGAGEGEDBDHDEBCACBHAHCFAFEBEDFFFBFGEGFABHGDADFBHG,False +401,11.0,5.0,16.0,15.0,7.0,18.0,6.0,17.0,EGDHHBGCGFFFFECHDAFAFBFDHGHAACFFFAEHBFDFHEHDFDFDABBEAFCCCCCCCFHAGADDDCCEHEHCHDHAHFHCCCFDHDHDADG,True +402,3.0,10.0,24.0,13.0,15.0,13.0,11.0,19.0,CBBEDHAHBDBDBGCECHHDHGHDCGCGEHCHCGCEEEEHFHFECEGBDDFBHEDBDADGFHCHCGCBCDCEAFGFGHGHCECFDECCCCCDHHEBFHFCFCEHFFCF,False +403,1.0,2.0,2.0,2.0,0.0,1.0,2.0,2.0,DGDABGBCHCHF,False +404,5.0,16.0,6.0,12.0,8.0,5.0,12.0,9.0,DGDHBCBCHGEEHEFGFBAGABADDCDBBBBBGAGEEDCDGHGHFHBHGGCEEDBDBDBCBDBGFAEBHFHGD,True +405,21.0,16.0,12.0,16.0,13.0,10.0,25.0,18.0,GFEFBFGGBGBGBHFHEBEBGBGFGFCEAGCDHAABHBEGCGHDHAHDCEGDGDBFGCAAAAEAGADFDGDAACACECEBFDHBAEACHGHAHDEDEFHHHBGEGACDBAGGBCBHHCDGAGDGHGHADAD,False +406,4.0,4.0,3.0,5.0,1.0,0.0,4.0,3.0,GBDDABCBCGDGDCHBHDHAGAEA,True +407,16.0,7.0,6.0,14.0,13.0,6.0,14.0,8.0,BFCAAAAAEFEBDFCFCADGDBDBDAGAHAEDEGHGHGFDBDGAEHEAEAGCEDHAEADGDAFADGGEGHGHDEBEHDGBGCCE,True +408,12.0,15.0,11.0,21.0,18.0,14.0,12.0,11.0,DBDBDBDBCBGGABCEFEFGGDBDAAAEHEFEBGBECCFCBGEEAEHCBFEFHFCEBFBHGADFDACABEBEAECDCGFDDDDDDHGEGFDHDHDHFCDDEDGAAFAFHHGHEE,False +409,20.0,21.0,28.0,22.0,20.0,26.0,20.0,22.0,FCFDFHADGDHDHBBCCHHDHDHDGAABAGCGCDCDFFFAEAFBHHGHCHEFEGBDCDAAHABBCFHFEEGEFFFCHCDBDEDEFEDAFAFABEHCCCEBHBDGDECCAAACDGFFEDHDFBHBAGAEAEFECGGGCHCDAHBGBDBCBEHGFCFCFCFCEGEGHFCBGFGCGCEABBB,False +410,3.0,1.0,3.0,3.0,0.0,0.0,1.0,2.0,DGACBHDHDCACA,True +411,10.0,24.0,18.0,15.0,16.0,10.0,24.0,18.0,HHFBFECHGHAHFGGDCBCBCEGHGBBAAGCCHCBDBGBDHHHBFBDBGGCGHGABABACEHEHCDGDECBAAEFGGDGEADDDHDHBEBEGEFEGEGCGDGDEDBCCCHCEBEDCGFGHGEGFBFBACHBBBBF,False +412,7.0,7.0,14.0,10.0,10.0,6.0,9.0,5.0,GEDFDFBAGCDABADDGAHEDEDFDCDCDFHCBCBCGCHBGCFCAEEEEEGEGCCCHHGCBEBCAGAF,False +413,1.0,1.0,2.0,0.0,2.0,2.0,3.0,2.0,FGCGCHEHEABGF,True +414,3.0,7.0,4.0,3.0,7.0,6.0,6.0,8.0,HCHGEEBABABFBEGFGAGBDFDEHEFCFBHHHFHCHCBEEGGD,False +415,17.0,22.0,23.0,22.0,24.0,17.0,20.0,16.0,BCBGBADDEHEBECCCCDGAGEGEAACEHEHGFABAEHECECFCGCECDBACAHADECGCBBFGFEHEFGDGEGCGFGDHDCBCAFGDGDAEFHFCFBEEHEBDDFHHHBAFAHDEDGDBDEDECFCFHFAGCFFAEGDGDADCBBBBCGHHABBBBBDED,False +416,23.0,23.0,29.0,23.0,28.0,15.0,36.0,18.0,HDFEEHAHFECBCGDFDFBAGABBGGADFDGEGECECGDHCECECEDEDACACGEGCGFBCBCACEEDEGGABHEDCHBGGGHGCGCBDBCCCEHEBGBCDDGGHGEFEGBBBDBAFAFAGBFFHHADEGEDBCCCACGCDCGEAHAEADGGGDGDBFBFCGCGBGBGACAHAHGEFDADEHEHAFGHBHDEAEA,False +417,6.0,3.0,6.0,6.0,13.0,9.0,7.0,12.0,HGCCECEAEHGHGCFAFHDDBDEGBGHHEEDAFGFHEHAAADBCHCGFEEEHEHEFEFDFHF,False +418,7.0,7.0,9.0,13.0,10.0,16.0,6.0,11.0,HEFFFEDECCHHBHFDFACACEDHDBDBDBDFCFDEDEBHGEFFAFADAFHGBGCGCFDEAHDFDHGHFHCGEFEFABC,False +419,6.0,2.0,4.0,3.0,3.0,0.0,2.0,0.0,EEBDBAAAACACEGGCCDAD,True +420,20.0,21.0,13.0,17.0,21.0,27.0,25.0,13.0,HAGAGAECCFDBEADDGAGFFDCBFFCABGBEBAGCGBFBGEGEFDCDEBFBEDCAHBHBDFDFBADGFFEGEGEFEFEFHFBBABAHHDGDGBGAGFGFGEEDEDAFAGDHEACACFFGFGFGEDECBFBFHHHGEAFAEAHFBEBGBCHCHGADC,False +421,9.0,14.0,14.0,8.0,6.0,14.0,12.0,12.0,FHFDFDBBBGBEBCBFDGDHFGABCGABBGEAFAHACACHDDFHCBBFHFHFGCHCHGBBHHGCGCACACHCEFEFADDFEFEGGCGCB,False +422,2.0,4.0,4.0,2.0,2.0,3.0,4.0,6.0,HFCFCECBGGGDGBEHFBAHAHBHDHC,False +423,19.0,10.0,8.0,8.0,6.0,9.0,8.0,8.0,DEABABCFEFDAAABFHFAFAFADACCGBABAGHBABABAGHEHCGDGDCDCGEHEGDAABAEHBAGACDFFCFHH,False +424,22.0,16.0,21.0,30.0,13.0,19.0,17.0,12.0,BCBEBDAEAEAHAHGHCBCAAEADGFGDGDCACFCDEGCDHBCADDDDDEABADADADAEGBGBHCGFAFDCDBDFACDBDBCFEHEHAHGFGFGFGECHFHCCGDGACDFDECFDADEBHFFDFDFBFBEHAGCGDFCBGDACBCFDAD,False +425,12.0,15.0,7.0,11.0,10.0,19.0,9.0,9.0,CADACAFHFDDCDBFBDBEBEDEHFABACFFHHGFDFDGDGHAHACCBEFDFGEGEADFFCEGBABAEHHBHBGBEBABGBEFFFFABGFFF,False +426,10.0,14.0,11.0,11.0,11.0,17.0,18.0,9.0,BFBAAEFEHCHGAFEBCFCGCGBGFHFCGGAFAFBFCFHBBFEFEFEBGCECBGBGCDFDBDBDGAGEFEGHGHAADEGCGHDBAEGDDDDCDFGFGABHH,False +427,37.0,20.0,35.0,16.0,24.0,26.0,23.0,17.0,AGAEEHGHGCCCGBGCHCHCHFGGAAAEAEAFHCHCGCACADEEECBABEFEHDFBFEEBBBCEFAFADACAFFCFDHDGBFFACDGDFDBBBCGCBAAAEAECGCDHFBDBCAAGACACAFAGGBEHECECEABFEGDFDHHAAAACHCHGHCHABEGCGFACCECFFBFBABAGFFDAECEDEFFACGCGAGCDFD,False +428,16.0,17.0,31.0,28.0,15.0,17.0,26.0,26.0,FGFCCACBEDEDBCGCGFDCAAECEAAFFGGGGHCHCAGDGDBHBHFHFHFHDHAGGDDADHDHBACGCGEDHBCDFDGDHDCCCBBBBGCCCCFBDDDBCCCHCFEHHGFBFCCAAGGDADGDHEHAGCGCBDBFBFEGAGEGHCFDHHHHEHEBEHDFDGDHAAECCCEDEDGH,False +429,8.0,4.0,6.0,7.0,12.0,5.0,7.0,6.0,AAHAGBFHFCEAEBECGFGFGEEECBCDCAEHEAEDEDHGHBCFDGEGDHDEDAA,False +430,5.0,7.0,8.0,4.0,4.0,3.0,11.0,4.0,HGDCHCBCBFGAGBGBEDHAEAEGFGCGEGAFCGCGDHDBBBCCGA,True +431,8.0,19.0,9.0,16.0,16.0,15.0,11.0,12.0,FABCEHHCGDGDFDFHFAEDGDFDFBBBBFEDEAGBEEEFEGEBEFDDGBBAAAFHFHEEDCDCGEDBDAEHEHBHBHBFGCDCHEDBFBGHGFBFBCBCGCBAHD,False +432,25.0,23.0,17.0,34.0,27.0,19.0,18.0,34.0,GBHHHFEGGFGFGHBABDBDBHGGEBBDEDHHHHAHFHEHFFFGBDDEAAAAADCDHACAFDBDCGCGDDDHAGBDHGHCHABAFEFEFEFDDBDBABGFAFEEDEDEAEBFDFDHAHABEBEDDDFHCEFEAAAECCBABHDADHCBFGDHEHAGBDHHEHEDEAECEDGCEEHDDGHCHCHEDDHBHCHCACBCG,False +433,11.0,10.0,8.0,8.0,5.0,5.0,7.0,5.0,GEEEBADHCHEBEACABDBDAHABABABCDCGCDABFDCACABGGAGHCHFFDDGFGFB,False +434,8.0,2.0,9.0,3.0,9.0,11.0,9.0,7.0,CECFFFHGHBHCFCFBFHDACEEFCGEDEDAAAGCGCEFFAAGGGHFHFHEGEGECAA,False +435,15.0,9.0,12.0,17.0,12.0,13.0,11.0,8.0,FEFHFAFEDEDBCGGFBHACGCFCHADADAFAEAEADHDBDFHEDEDBBGBDADAGAGEGECCHEAACBCDCEGFGFDADGHHFDFCCCBDGEFADB,False +436,9.0,4.0,4.0,2.0,2.0,7.0,7.0,7.0,HEFBABCEFAFABGGAAACFCFGHBHACGFGAGAGHHDHDHF,True +437,13.0,14.0,15.0,27.0,27.0,6.0,29.0,26.0,DDDEHABAHEHAHDCBGDHFCEGBBHBHADDEAGGEGDGDGCCDCDBDBHBHBAAHGGGGACECEGGGECCDGDGEGADADGFHEEDEGACAGHDDDFDFBEHCHGHFHEEEHEHEHEHEGEFDGDGHBCCEDHBCGDHEEBAGHGEGEGEDHBHCD,True +438,22.0,9.0,13.0,21.0,26.0,17.0,18.0,21.0,GAGEHFHCEGEDAFAHAHEDBDFDABAHEDGDBCAEGDDDGGGGAGEHHHGCCFHHBHBHBHAGECAGDGDGDGEHDFAGCEEFEHEAEAEFFCECFFFBDADFDADADAFEEEEAFAEEBABAHEFDGHEHFCDCDCECHCHFEAH,False +439,24.0,19.0,22.0,19.0,24.0,22.0,19.0,24.0,DCDCAAAAABAFGFDFDHGCGCGBDACCCCEHFACHEDAAEABAHABAEFHFCFCFBBHFHEHEGCGDHFECBBBGBEHEAEAHDGDGHCHFBFEFEBEDFAACDHDFBHADCCEHEHDBFGFHDHDGEGADADEDEBECHFGGAGEFCCBCGFBBAGEHFHGHEHEFECBGA,False +440,23.0,14.0,11.0,16.0,9.0,11.0,13.0,16.0,DCDGBGBAAHECEFGFGAGHHEDGBCFDFGHGEEFADAEGFBAAAABFBFDAACCCEDHHHDDAAEBHCHABCHAHAHABEDGFGBGDDDDDDGAAHACACACABFFHBHBHB,False +441,5.0,9.0,7.0,7.0,5.0,6.0,6.0,2.0,CFDBDGCADBDBDGAAEAEBFBCBFGHBEGDHDECECBCGFGFBFAC,False +442,21.0,17.0,17.0,31.0,26.0,21.0,12.0,20.0,AAAGDEAFCHCBEDDBDBDHCAAHBDBDADHFHFHFHFHFDFEADADHHCHDDCFBFACHDEEEDABADAFEFHCACFFFEFBBEHGDGEGFDDCDGEGECCCCCFCHDEEECGCFDEDGBBDBGGHBFAFEDADFDHEHDHAGDGDBAEEEBEDAHAEBEBEAE,False +443,22.0,20.0,27.0,22.0,26.0,31.0,22.0,17.0,EDEAHFDFEBGFEFHGAFAFEDEAHDFBEDACCCBCBAFADAHFCGHGHDCDCGGHBBGACADFEFEFBFBFBHBHAHAGGGEGAGACECECBAEFFDEECDFECECBCEHDFCABHBCGDHBFBFBFAEDCFFHFCFGFDEDEDGFGFGFBCHEGGCEDGCCHDGFGCCCACEDEAEABABADFDH,False +444,25.0,15.0,17.0,18.0,21.0,13.0,21.0,25.0,GCAFBBBBAFGHBACAFHCECHBEDEHHHEDAHABCGDEAAABDBHAHBEGGDGACDBGGGGHGHGCECEFHFCCGBEEEEEDFCGDGDADADCECBFFCAEAEADGDHAHAHEHDHAHEFEHDGFHFHBDDAHAGAGAGAGEFBHECFCACHDH,False +445,4.0,5.0,1.0,1.0,6.0,3.0,0.0,1.0,FEBBABEBEAFHFEAEAEBDC,True +446,3.0,5.0,3.0,4.0,0.0,2.0,5.0,1.0,DBDAGBGCGCGCBBBAGFDHDFA,True +447,27.0,17.0,19.0,29.0,21.0,26.0,19.0,16.0,AAEEEEFDFHEADAGFGFGAGHFABBBBDADAHFDGCHFDFAFGCCBFFHDHDADEBHGCAHAFCCGCHEEADCBFFDFAFACAEECDCDBHBDCCEDEAGABDBDGGGGHFHFHDEAFDCDAAABAGCGFDFEEEBGAGAHBGDGDFDFDHHACCDCEBEAECEFEFDFDBDB,False +448,12.0,3.0,7.0,7.0,6.0,6.0,10.0,15.0,GCACACAFHFHGHDHAHDDEDCFAHACAHGEFHBHBFGDEHEAAAGAGCDAEGEBHDGFGHHCHGH,False +449,27.0,20.0,31.0,20.0,16.0,31.0,25.0,16.0,CCFCACAHBDGCGCBCGCDCBBEBAGFFFCFCDCBHBEFDFDHGGDCFEDBDFDCDCFFDBAECHADBCHCHCAAAAFAFADDGFCECGCGDDEHGHFFEHGHGFGFGAEFBFEFDBHAFDGGCFAFHHHBHEAGAEAEABGHFAFACACBCACGBBAGACAFFGFGFDBCBCGEEEECFADGBGA,False +450,2.0,7.0,4.0,2.0,6.0,1.0,3.0,3.0,DGCGCBDBHCECHBEGEABFBHEAEBEB,True +451,8.0,7.0,6.0,1.0,2.0,4.0,4.0,3.0,FGFHEABCCCDBABAHCHEAGCGCBAAAABBBFGF,True +452,12.0,16.0,17.0,11.0,29.0,15.0,19.0,16.0,EGDGEGHCFCFDDBECFHFHGEBEBEBEBDBAHAHADCEEEEEEEBECCBBBGDCDCFGHHEACAGBGHFEGEAECFDEGFHCEDFDFDCBHEAEAEFBGCGBAHFHGGEEBFGFGEHAGAGAFCBHHHCCECEG,False +453,4.0,3.0,6.0,2.0,6.0,8.0,4.0,3.0,CCFCEEHCHBDEFAFAFHGDFEGEFBFBFCECGAGA,False +454,17.0,13.0,25.0,22.0,19.0,16.0,28.0,27.0,AGAHHCDEDGGGDHHFEEGEHHCGGHGABCDCDAAFCFCGAGCFFFHEEEHEBGBCFHDAEEBDCDCGCGCBHBFCFHDHGBGDHCHFHBHDHBEAFCCDEDAGCGCDCFFHGHGHGAGADACAEABFCECECEBEHAGAHHDGDGHGHGFDFDEBCHDDCDGBGEA,False +455,3.0,8.0,5.0,6.0,3.0,3.0,1.0,4.0,ADHHHDFFACBCBCHCBDDGDBDBEBEAEFCBB,True +456,17.0,25.0,25.0,21.0,21.0,26.0,24.0,21.0,GEGBFBFBFBGAHAFACDEDCCHFFGBGAACFCHGFCFGHDAEFEFGFGHEBEBDAFGFAFCCBABEHCGFEDEDGBGBFBEHEGGCDCDCBGHDCCCDFAGBHBDEDHCHCHEHCBCDDDDFBEEEEGGBFCFCHAHACGFBBHDHBABGBGDGDFAFAECECEFDFDBGCHBAAHHEH,False +457,12.0,10.0,8.0,8.0,4.0,11.0,8.0,8.0,DBDFDFCCCHBEGFBHEFACBDBGHGBFAFGHAHAHGDDDCCACGCEHGFGFBFBABABDHFAAAEAFA,False +458,20.0,11.0,18.0,22.0,26.0,28.0,20.0,28.0,BFGHCHEAEAFFFFGABCFGFECECECECHCHGHDHAHEEEFHAAFBCGHDHDHCABGHCFDGHGACFDDDBCGDDFGGGGEEABGFAFEHAFEHAFAEAEABAGFDFEEHEFECDADHDHBHEHDHCHFHDHFHGDDDDEDEFEFGDCHCECEFHFAGBFFEFCADGBGBHA,False +459,18.0,25.0,19.0,16.0,13.0,17.0,21.0,14.0,CACACDEDBCBHAAGHBHBCEDEDAGGHDFDEDCHFHECFBFACAHAGGGGGAGDFBABFFGFBHBHBGBHBACABHBGCGBGEFADCDCHAHDHDBACABBBGEGEFCFBGBEFDFABABFCEGECDCBCGDBEGFFCFDGE,False +460,21.0,19.0,19.0,30.0,29.0,19.0,23.0,32.0,FDEDECCDEEHFDFEFEFHAHDCGCGCFDDDCGAGAECDHBEBAHGCGEFEDHDHDGDBHBADCDCHHFECHBGBEHADBDHGHGHGHDHFBGAGHBFBAECGGFEFEFDGDCDAEGEBACHGGDDADFHAEABBGBABDFDFABEDAHBHAHAEDEAEHEHCFCHEHEHBHBHGGCACAHEEEEFDFCGDH,False +461,9.0,19.0,19.0,25.0,19.0,17.0,20.0,16.0,BEGCGDAEHEDBDCEHECACAEAEAFCEGHGHFHGHCEDDDHDEGGFEHEFDFGFDBDBDGDEDCFCFHECBDHACCBCBFGDGCHBHDDBGBGFCBCDDGDACFGGGGFGBEBEGHDBDFCFBFDFDBHHAHAEDFBCBEBEC,False +462,9.0,14.0,11.0,15.0,9.0,10.0,15.0,17.0,CHCHCGCBEBDHEHFBGDGDGDGDBDGEGCHHBDBDACFCHGFEAHFFDCGAGBFHEDEHHAHAEBHBHGAGBFBDBCFCBCBADAGEGHHEFDFDGDAH,False +463,15.0,16.0,16.0,16.0,13.0,12.0,15.0,14.0,EDEGEDHBHDHDACHCBCAHADGDGAEEHFGFGFAEGEDECGGAFAFDBCHCGCEBABABABDEACHCBABAFGEACFDBBCBEGEGCDCDADBDFHHHHHBDCDGBFFGFHCBCFG,False +464,20.0,13.0,10.0,7.0,14.0,12.0,14.0,15.0,HHHBDFFCHCGCGAGDFDGEBFBABAFAFHGHBAGEGEHBACFCEDBACCCABADAGBGAGEEAAFAFACGCFAHEHEDEBAGEHEHEGAGAEFHHHHABEBDBF,False +465,32.0,28.0,23.0,18.0,15.0,22.0,28.0,21.0,CAHHBFBGCACEGFGAAABABAGGCGCGEAAGCGEEDBDGDCDHDBBABAFABAEDBGCEDBDBAHABFHEDEDBFFGAGHHEGAGHEECDCFBHCGBDBDBFGFDFCFAAACACFGHGAGDCFGAGFFBHCHCEABHBFBFHFAFHFEFBABGBGBGHHHAHAGEFCCHBHCAGBCDCECADADAG,False +466,14.0,31.0,26.0,20.0,17.0,27.0,15.0,13.0,BBBBBCGFEFDFDFCCDCHHDAFADACCEAGGCGCACFFEGECEFECCACGEBAGDGHBABDBHBHFCBHFCFCAHDCDHBGFEEDEDFAFHHGBBFAFCCCFAFDFEBBABACHHBDBDBFBCCFFFFFFDBBBBBEBECEGEGDGDGEGCHEBCDFBBBDD,False +467,15.0,12.0,15.0,11.0,17.0,18.0,18.0,13.0,HAGECCBCFHEGGGGBGBDBGBAFACCFCFCBDFAAAAACEEEFECDFDCDCDHBGGGFGDABAGAFFEAEFHBEDEDEFBAHGCGCHFGFGFHHDHECEAEGFAFHHEHEBBGEHFDC,False +468,22.0,12.0,14.0,17.0,19.0,18.0,16.0,15.0,DADADADAHAGABAEHFGFGEGBHBGADHDGGACHEHCHGEFFBCGCAFGDGAEHEAAFCFGAHAHEDDFDCHFEFEDEBECABEFGBGAGCCECFCBBBBHAEBECCADEDHHHEDEDEDFFFFGDAAAFCF,False +469,18.0,26.0,29.0,20.0,29.0,19.0,16.0,15.0,CGCGCHCFCGHHCHCHCHCFAEAFFECEBFGDHDCECECHCFFDBDEDBGGEGAGEHBBCCACABEEEAEBEBACECGADBBHBDBEFEFEFCDDGCCBAHHFCBHBADAGFDBEFEFEAECBFFHABDBAEDECECEDBFBDBDBDACGEGEBADCDGBGDGACFEFBAEH,False +470,6.0,1.0,5.0,5.0,3.0,4.0,4.0,6.0,CBCAGGHDHDHDHFHFEECACADHCAFAFGEADG,False +471,8.0,12.0,3.0,4.0,7.0,8.0,8.0,2.0,GAAFBEGEFDAGEGEFEHGBCFFFFGBBBEBABABDBDBEBDHGCABACAGF,True +472,9.0,4.0,9.0,5.0,3.0,6.0,1.0,7.0,HACGCABHCEAFHBHDAAACFCBEDEDADAHFHFCFAFBCDCHC,True +473,2.0,1.0,5.0,2.0,7.0,3.0,2.0,10.0,CCHCDDGFHAEBEHHFACHHFHEHEHEHECEG,True +474,8.0,7.0,5.0,9.0,9.0,4.0,1.0,12.0,BCDHBCBADCDHHAHDHAHEDEDBHEEDHCHAFAHAHCEGDADEFEFEFABHBEB,True +475,11.0,5.0,2.0,1.0,3.0,2.0,5.0,4.0,AACDCFHAGAGAEBGBHBFEAGBGAAAHAHABE,True +476,25.0,30.0,25.0,21.0,26.0,22.0,25.0,24.0,HGHEDBDBCHEHEDEDEDEDCAHDCGCFDFGEGDGAGAGHGDGDCAAHABAFACBCBCEDEAEDEAGDFEBEBEHGHFHFCBBFGHGFEFBBBFHGBCFCEBABADHBCACGFHFACACDFABHEAEHHDGACHFBFBHBHBABGGDBABGFEFBHGHAHEBGBGCFBEBECGCACEFAGECACFDFEAECCBGHCDD,False +477,15.0,14.0,22.0,19.0,17.0,22.0,25.0,22.0,DFGGGFHHCHEHBGDEEBFBAAHGFGFGACCCGHFHBHCDEEFEFBFAFBFCGCEDEHEHEBFAFAFAFGCGCGDBCBFFCHCDDDEAEAGDEDECGDGABBHDHDFDFDGCGAHEHFHCHAACDDBHHACBGBGAGFFHCCGHHCCGDGDGCGEE,False +478,14.0,12.0,9.0,13.0,13.0,17.0,7.0,13.0,AFAFBFBDAAADFFBFBEHGFEFHAHFGDDFDHAHADABFBFHEHECCACGFBDBGAEHCDCHGHGEAECECEFECADFDBGBHBHEHDDFEFDBEAC,False +479,29.0,20.0,16.0,24.0,27.0,18.0,17.0,26.0,GEHHHAHEGBGCHCBCFGDGBFDHCCBCHFHAEFEGGDHDACEDDDCDFDFDHBAADHFHBEFEHCHCDFAFABAEGBHBABABAEHEAEAEDEAFHEDAGEBEFGCEDEFEDHBFFDFAHHDBDGDHEAEGCBDEDBAGAGAGAEAHACACAEAEBHAHGFGEBEADADBHBHFCC,False +480,11.0,14.0,7.0,9.0,18.0,15.0,6.0,9.0,FAFEGDGBBEFEDEFEFABAGEGEFFFBBCBEDABEGAAAFHFDEHHFBFDFAFCDCDEGHHCHBABCBEHEHEBEBEDEHABEFACDC,False +481,8.0,4.0,7.0,16.0,11.0,8.0,9.0,4.0,EEADADFDEAFBFGEGFGDGCHDDCDEBEGEGCFCHDAGCGDGAECFCEDDFDEABABADDDDEHFH,False +482,11.0,7.0,25.0,5.0,16.0,24.0,10.0,11.0,EAEAEACFCBCEFEGAGAGCCFFEFGBCFFHFCFAHACFCEEHCCFDFEEHBHFHAGFFEFEBDAGCGFAFEFEHECGCGCFCFHFHCCCBCDDBCCCCFDFHAECBHG,True +483,24.0,31.0,31.0,29.0,20.0,23.0,19.0,21.0,HAHEECBBBBGBECEFBFHHCHFHDBGBHEGEADAEAEBBFBCECFCACABHCHCEBFDFCFCFBFHHHEGCDCDCDHDCECGABADDDBAGAGAHEDEBBDGCBCFAFABAHCBCFHGHBDEDGBGEHCDCFCFCAHFBCDCDGDHABGFEBDBDBDGAFAGAFDDCEFABAFDDGAFEFDGCBABHCGDGDCDCAE,False +484,10.0,14.0,9.0,7.0,6.0,9.0,6.0,9.0,HCACBFBFCFCFHAHADACABDCHGHGCBFDHCBGBABFBDBFBEEHADADHBBEBADAGECEFHBGEGF,False +485,10.0,4.0,11.0,5.0,13.0,7.0,15.0,10.0,AEAEHCHCGCGCBEGEGFGBGAGFGEHAFGCHDECCAHADDFDFHFHEGEGACCBHDHAEGEGCGHBEEEGAFAC,False +486,10.0,4.0,4.0,3.0,10.0,7.0,9.0,8.0,HGHCFDHAFAECEFHFHEGECHDDACABAEEEGGAEAGAGAGAHFGFEHEFGBBB,True +487,5.0,6.0,9.0,7.0,10.0,8.0,5.0,12.0,FCFCFHFAFAFGEDCBEHHGGEHEHAGBHCHFEAEDEDBHADCBCDHDHDFBEBCCHCGEHE,False +488,11.0,11.0,11.0,8.0,15.0,8.0,13.0,12.0,CBABEBFHFGEGHCDCAGDGEABBCGGBBHEFBBABGBADEHCHCEAEAEGEFFFCGCEHDHDHECDCAFAGAGAGEHEGFDHCHEHED,False +489,22.0,25.0,26.0,26.0,18.0,25.0,28.0,23.0,BEBEBEBFFHDHDHCHDHCCGCFAGCHCHCDCGCABABAFCHEHBCBCDCGCEHAHAEGGABFDHEBECGCHCHFDADAHHEGFBHAHFDGDCCCHFFGGGGBFAFABGFEFAGGFGDBAHFEGEGEDBBEDDBHBDFDFGGCEFGFBFHGADADHCEGEGDGDFDBBCBCDGBADABAFCFAFADDDBCGAE,False +490,19.0,24.0,22.0,16.0,30.0,19.0,23.0,31.0,FGGAFEFECGHHEGEHEDEFEHAGFBFBFHAEAHAEAEACDEBBHCECACEGBBFBDBCHDHGCFEHHAHAHBEBECGGDGCHBHGFGBDFCGHGHDHBHBACACHBEAABDHEHDHFFBFHFHEBCDEDEDFDGEGAGADBCHFHABDBDCFAEAEBEBECGCGEHHCCBCHCEGEGHFCGEG,False +491,16.0,23.0,19.0,29.0,31.0,20.0,28.0,25.0,DHDBCECECAGFGBBEEEECEDEGHCDGGAFDFGFGCGCEHGHGEDFGCDFGFDDDCDEFEABDEDEBEBHBHBGGHBDBHAFABDGHCECGAEAEAGABHDHDHDHBBBGEHEFEDHBEEEGGCDEFGHGHAHAFCFGFEDCFEABHFHEBEBDHDHACBCFGAGFGHEHBGBCHFGDDADCDADFDECB,False +492,2.0,8.0,8.0,4.0,4.0,4.0,9.0,3.0,GEGFACBGAGECCHCHCBFDGHCCGCGBDBDBEBEFDFBGBG,True +493,21.0,13.0,20.0,26.0,11.0,13.0,10.0,15.0,AACGHHEEDBDBDCDCDBEBFBFEGDCEADDDFAFAEAHHHFAFADEDCHCBCAAGACDDDDDBCAGDCDBEHGHGFGABDHDHCCCCHADAEAEDHDAACAFAFBFEDGBHCCADHBGBDFCFCHCFG,False +494,4.0,3.0,5.0,3.0,3.0,7.0,4.0,3.0,AHFEBAHCHGFGFEFDADBFFCFCGCGCBEAD,False +495,0.0,4.0,1.0,1.0,4.0,0.0,2.0,1.0,BDEEBEGEGHBCB,True +496,6.0,16.0,13.0,12.0,12.0,13.0,12.0,10.0,DHFEEBAFCHCHCEFHABBCBCFGECECEGEBDCDCBBBBFAFEBEGGCGAGFHEDGBGEGCHEBDBHBHCGBHAGDFDFDFDFDHCADFDFGB,False +497,19.0,9.0,12.0,22.0,14.0,24.0,20.0,18.0,DEDAHEBAAGDBHHGABAGCHCDCACFCGCEEACBFAFAGEDDDHHHCHCGFGHBAGAFAHDDDDDGDFDFHFEEDEHFHEBFDFHBAGHGHFHFEDEDFDFDCGBFACAGAFHFEABGEGFGFGFECADAGGDGFFF,False +498,8.0,3.0,6.0,14.0,8.0,17.0,6.0,15.0,GFFDFEGGBEBHAEDGFAFEFDDDAFHCHCDCDGFHAHFHFGDHCEFHCHCFDHDHAFDFEFAFABAEHFHDHDEDH,True +499,0.0,6.0,1.0,2.0,2.0,3.0,3.0,4.0,EDECHDBGBGBHBHFGFBHBF,True +500,9.0,11.0,8.0,10.0,19.0,12.0,9.0,5.0,GCFDBACGFBFAAAAGBFAEGFGCGHEAGHDFFCEDEDEDEDECHBEGDDEAEFDFAFEBEHEHEDEBEBEBCBCBFFEGBCE,False +501,8.0,14.0,12.0,11.0,8.0,12.0,9.0,4.0,DBDBEBDBDFDAGCGFBCBCFFGCDCDEDBBBECECFBFECABDDAFAFAGEFBHAGAFCHCDCGHGHBFBEGEFCAG,False +502,5.0,5.0,5.0,5.0,9.0,6.0,4.0,8.0,FEFEBHHHAHABEBDDFDHDCAFFECEAHCBCEAEBHGHGCGFDEGE,False +503,12.0,12.0,13.0,25.0,16.0,10.0,18.0,21.0,GBGBDECCCFHHBACGDGDGDADCGCBBHDHDHDBDFDFDHEHGCEDEGEFAFHBEFFGCEHFFDDHDHGHGDAACAGBDHGHEDEDGAHCGDGDACEGAHAHDHEHEBEBCBFBEHEADDGDCAHE,False +504,10.0,15.0,9.0,13.0,14.0,7.0,8.0,9.0,CBEEFBBGBGBDBABADFBAAHEBEDEDGFCEBDBHAHBCBCBGGFDFCAGAFDGDHDHGEBEHFHECECEAHCDDEHEAEADCD,False +505,18.0,16.0,17.0,23.0,12.0,18.0,20.0,12.0,FGFABEFDHDHFHGDBDBGBGCACDDDHAHBHFFFBGCGEAEAGABHBGDGCECEDHFAGBDEAAHCEGHDEDEDFGHDDDDEFFAFGDGCFCFDFDACFCEAABGBABCBCFHGGBGEGAACCCCFCGBADADBD,False +506,22.0,16.0,25.0,22.0,25.0,11.0,27.0,18.0,AGCDCDHDBGCGAGDDCDGBGDCBCGFGHCECGHGAEFEDEAEGEFHGBCBCAAAAGGDGEHEAEDEDEBCBGFCFGDDEDECFDHDBEAEDEHGHCCCCABAFABCBAHCHGHCCDCEFAGEHAGAGHEBCHEGBHBHDHFEEEACACDEDEHGGGFBFBGDAAA,False +507,13.0,17.0,22.0,10.0,17.0,14.0,17.0,13.0,GGGCBBBEBHAEAGHDCGCDHFEAEABHCHGFGHGCCFFBCAAHEHEDCGCGCDADEHAHFDFAFCHCFCBDEEAEFHAHFCFABBDBDEGECEBGBGCGCDEEBEBFBEACBCGCGBGCFCF,False +508,17.0,21.0,24.0,12.0,17.0,20.0,19.0,17.0,ECHCHCHCGCFBGAGEBEBEBDCCFHFGCDFFHHBGBGDDDGFCFCGDGFAACACGFHDHGAAHAEBEGCCCFGFADADHBBBBABEBEBCGCHDHBGEHCACECEDDCFFAFEBACAEHEHBGBHEFAFBGHGFBCBEAEAGFFCF,False +509,4.0,0.0,5.0,5.0,1.0,0.0,3.0,4.0,GHDCDCDCDCAEHGCDHHAAAG,True +510,10.0,11.0,3.0,4.0,7.0,2.0,18.0,3.0,HAGGGGAFAGCGEGBGAEBGGEBEBDCEGDBDADEBEGAGAGBBBCGGBGAGHBHAFA,True +511,2.0,4.0,2.0,2.0,1.0,2.0,3.0,1.0,DEDFHGABBBBFAGCGC,False +512,2.0,4.0,2.0,1.0,1.0,1.0,0.0,1.0,HDBABCBCBFEA,True +513,4.0,5.0,8.0,7.0,6.0,8.0,11.0,4.0,GGHGHGDBCECECEGFHDABADEGGCGCECBFEGACFFFFBFCFHBAGGDDDD,False +514,20.0,26.0,19.0,15.0,24.0,22.0,24.0,21.0,FGFEFEFBHGHBEDHHHHEDCDEHEHCBFHGAFAFBFDCACAGGGGGGGHBBABFBFBCHGGBACGCGDFEEEEAEFFFFDECECFCBCBEAHCBADEDAGFDEDBBEBEHACAFAFABHEEDCFGHDAABEBEDGGHGHGDDFEFAHAHBGCGBGCCCABBHBAGCBHBE,False +515,22.0,23.0,26.0,33.0,16.0,30.0,25.0,23.0,GGGGCBEHCBCFEGGFADHDHCGDACCDBDGFCFHBHGAABFBAHAHDGDBDADACGCFDFGFDDHBGGGEBEBEFGFHBEFABEGCGCGHAHFHFHDBDBDCDCDCHFFFHFDFAGEGBABFEDBDCECBCDDHDBGECADEDEFFFFAFDFDECGHDFDFBCGFECHHAHAHGCBCDADAEAFCFCDHDABAHABC,False +516,17.0,13.0,13.0,12.0,15.0,20.0,10.0,20.0,FDFAGABHFHCEEAFCEGGBEBCBCBEBDHFACGHGCACACAHFHDBGFGDAEAEABFDEDHDFAFEBDHHHFHFHFHAHAHAEAFADCCFBBCEHFFFDGDGBEHHHHGCBEFEAEDFC,False +517,26.0,21.0,23.0,17.0,23.0,30.0,24.0,22.0,ABAEAEAEBGGGGGAECECEDFCEBAGHFHAEADCCGGGAGBEBEBEDCDFAFHFHGCCBHAFAFAFHFGBCDDFACGFGHDEEGEFEGBGFGADFCFCFCBAEABCDHHHCHFHFHBHAEFFFCFBECCCFFDFDBCHCADAFHBABDFDBBAHGGEAEHCGEGCDAGAHDGDFHFHFEBABEBH,False +518,7.0,13.0,9.0,12.0,7.0,6.0,7.0,5.0,CGCECBHDEBGBAFCDBDBDACEBDDGDGEGEFAFAFAHCFEHEDBCBDBDCDBBBDCHFBAGAGH,False +519,15.0,23.0,14.0,11.0,17.0,17.0,14.0,16.0,AFGEDCHBBBBBBGGECEFFBACACBCGCBHFAAABCCEEDDDHBBFBFBGEHEFDAEAFFFEHAGABAFHFBDBHHHBEBEACGCGCACDCHEEBEGGDGHGHGDDDCBGAEBEFEFAFHHHFHFB,False +520,18.0,12.0,17.0,12.0,18.0,12.0,16.0,36.0,EGEHCHDHDGDGCADAHAHFCEEBACEEEADAHHBCBEHEHEBAHCEEGCFEFAFABHBHGHDCGCGDHDHFHDHDHAHCHABCGCFBHHAHFHFHFCEHEAAHHBHGEAHHBFCCGBGFHAEAEGCHBHGDGDGAGFHHC,False +521,4.0,11.0,9.0,6.0,9.0,15.0,6.0,12.0,FFFCCHBHCFCBCBFDDGDGBFAGCFEFCHCGFBBBHCHDEDEAEBHBHGAEAFFBEGEHEHEHBHFFFFHD,False +522,17.0,10.0,12.0,14.0,22.0,13.0,17.0,18.0,EEEEDEABAGFEFEHGHBDAAABDBDAEHHAHGHGHDHAEABHHHHHBCGCFCFCDBAGACEEGCGAADGDHAFCFCEBEFDFEEACGHBEFEFEFEDCGFGHGEGDBAEGEDCHAHGDFDGC,False +523,0.0,4.0,3.0,2.0,1.0,0.0,4.0,2.0,DDEBCHCGBGCGBGBH,True +524,25.0,20.0,21.0,11.0,21.0,16.0,21.0,28.0,FGHGHEHEHBHFHFBFBDBEGDCHCGAEAFCDEAAACHEHEHBFFFFAAHCGGHGBGBHCHCDCGAGAGBHHHFDCDAEABBBCECBGGFACHCECEAFAGHFAEHGGEDEDEBHHACCCACBCHDGDGAAABAGFEBHAGBGCFEEDEAEAFBECHHAHBHB,False +525,5.0,5.0,3.0,6.0,5.0,16.0,3.0,8.0,DHFHFEFEADAGEGECBDFCBDDFHCHFAAAFEHHFBBBGDFFFFFFFHFH,True +526,1.0,0.0,1.0,1.0,2.0,0.0,4.0,6.0,HGHCHEHEGGHGDAH,True +527,14.0,26.0,15.0,11.0,16.0,18.0,25.0,17.0,BHFABADGFABCDGGECEBEFEDBDHGFCFDBDBCEFBFHAGBFEFGFHFHCHBHEHFHFHCHCEDBDBEGHGHGCBCBGDEEFCFBGBGBGBCBDBGAEAGBGAGECEAFGGGHGCCAFGGEAEDBHAGABAFAGHHCBBB,False +528,26.0,33.0,22.0,21.0,21.0,26.0,21.0,23.0,HDBFBDGDGHHEBFFCECFBABGGEBEGGAHEHABGBCCCABDFEFGFADACCGABDBFBADADBDAHAHBEGHFHBEGEBCBCBHAHABADCHBGCDEDEDHGGGGGCDBFFFFFAEECHCHCFEBEAADFBFBABDBGEEHEGEFCFCFEAEADCGFADHHFBDBAHAHACABABFBFCFHBHBHCDFGCD,False +529,19.0,28.0,16.0,26.0,16.0,17.0,19.0,17.0,ABADGCGBHDFFFGFGDGFBDGGFAFCGGFHHAAFFFEAAHAHCBCBABADDFFFABDBDBHGDACHCHGBBBBBGEDADAGCBEBHHEDBCBCBDEEGADABABADADCCBCBDFDFCBCHFEEEDEHHHGHBHDEECHGDGDBEEEDEDGDGCBBD,False +530,10.0,4.0,8.0,6.0,5.0,11.0,7.0,6.0,FFBFCDCGAGFEDCDBEGEGFCFCFCBAFDBHAHAHAGACAHAHEGDFCFADEGAFH,False +531,13.0,7.0,11.0,9.0,7.0,13.0,13.0,17.0,GCABEBFBAHHHGHGAAHCHBEBCDAFHFHBCDCDCDFGEGCHAHEHCHDFFFGFGCGAAAHGGGHFCECHHHGAAEADFBFDFDEDAGF,False +532,6.0,4.0,4.0,4.0,4.0,11.0,3.0,7.0,ABCDHFHFECEDADFGHAFCFCFBFBGADEHGBFHEHFHFAFA,False +533,14.0,30.0,24.0,27.0,22.0,23.0,21.0,29.0,CEBEDGCHDGAAABHEHGCGBFBEGDDDCDCHHDEGFHCEFBGBCCFBAEAGABEDFDCDCDHDHGFGHGCGDDFBBBBBDFDADCDGBFEFDBCFCFBDHDGFACAGFDFDEAECFBBHBHCACAHFDEHEHBDBGBHBFBEDCFEEHBHBCBCBHEFEFCHCHEAFHBHBHEHFGCAEGHGHGHGHED,False +534,7.0,14.0,11.0,10.0,12.0,6.0,11.0,7.0,ABADCBEGAGABDBHCECDBEHGCBCBCGCFCFHFHFBBCBGEGHGDGEGEDDDCDEDABAHCFEEAEFEBBGDEHBG,False +535,1.0,8.0,7.0,5.0,5.0,7.0,1.0,7.0,BHBGFHEDDFCBBBBHHHFEFHFCFCACBDBDEHEFECCCD,True +536,5.0,4.0,11.0,11.0,13.0,6.0,6.0,8.0,CDDDEBHHGHDFGCCACEDEDECEGEACACHEBFFEFEFGFGDGDHAEEEABCBHEDCDCHHDC,True +537,28.0,21.0,11.0,18.0,13.0,11.0,21.0,19.0,HGAGAGFDDHGEBDCGAAHGHEDBDFDEGAGHDECCAAAADDGBBCBHBHBHGCGCBBBFBFGABAGCHBGAFHFAACAGDFEFEGGBFHAADADFDADBBBDAEAFHGHEHEHAHAHAHAGEGDCDCHBABABECDGAEBE,False +538,3.0,5.0,4.0,4.0,5.0,2.0,1.0,6.0,HCHGHAFBEBEAEACDCHBEBFCEHBHDDD,False +539,6.0,6.0,7.0,4.0,9.0,4.0,6.0,1.0,CCAGDGDGEFBCACBCGDDBFEFCFEABABCEEEABAEGEGEH,False +540,4.0,1.0,2.0,4.0,0.0,6.0,5.0,0.0,FDDGAGFGCGAGAFFFBCDADF,True +541,9.0,14.0,13.0,6.0,8.0,6.0,10.0,5.0,CBCGEGEFEHAGEDBGEGAGHDCBCGAGAGHDFGAACBBDBDFFCFHFDACACBBEBECCCCHEACBBBBB,False +542,16.0,16.0,8.0,16.0,13.0,11.0,10.0,17.0,EAHAGFDCGCGDEHCHBAAADHDHEHEFBGBABFDAAADBDADADHDGEGCGHGBFAFEBBBBHFDFDEBEFAHEBDGFHCHCHGDFABABDHHHAEBEHEDEBCCF,False +543,21.0,26.0,17.0,27.0,29.0,23.0,26.0,18.0,GDEHHBFFAHDHDCBHBGEDBDGAGDHCEEEBFFACBBEDGFCFBEBECAFDDHBHDEFEFEFEGGCGBHFFCFEHBHEFBHBADAEAGAFBFGEGEGCGDEDEGCGCBDFDFDADABCFEBBBDBGGGFGCDCDCACFEDBGEGEGHABGEGEAAAACCHEBEDEHBABFGFHHEHADGDADADAD,False +544,22.0,22.0,21.0,19.0,23.0,23.0,21.0,20.0,CGDGDBCFDADCCGDBDHAHCHCEDFFGGGECECEAFAHCFDDEDAGCGCBDEDEAEHCHCEEECEFBFHDHGHGEGCHFEAEAEFFCFEDEABHHHGFBAGAGBDEGECECECHBHAHGBBFBGBDFDGAAFAFGBBCBGBFHEHCBDFFFHFBAAHBFBAAAFAGABDB,False +545,23.0,25.0,25.0,15.0,25.0,17.0,21.0,33.0,GAGAGEEHHHFHFHFHEHDCFHABBHBHBEBHFGBCCACACACGHBADHBECECEBABECCHCFEGHDCEBGGEBEBEFHHADCDCDFDHBHCAEEHEHFHGHGHFADCGFHCACACACBCEGDFHCABGDGEGFCDHGHAAAHBHBHBEBHBHAGABEEGEDEGFBFCGEDAGADDBBEAFCF,False +546,3.0,2.0,2.0,4.0,0.0,4.0,0.0,0.0,ADADAFCFDBBFCFD,True +547,13.0,21.0,3.0,11.0,13.0,5.0,12.0,11.0,GHBADHBHBGBEHDHEEFGHDHGFEDDDEGEAEDFAAGBBCBAGAGAEDEHBHBABABAGADBEBECEAEBBBBGBHBDFGCADBFBHG,False +548,25.0,24.0,22.0,17.0,28.0,18.0,39.0,21.0,CDCABDBHBGBGBGBCECBABGBGAHAHBFEEAEBGAGEHFACACDEGEGECHAEGEHFHFABEGHFHAHGHCDCEBEGDBFAFHGEGBGAGDBDBDBEFECHFHEBFGEGEGECAFABEBGBGHGFGEGCCCCHGFACGBHAHAECFGAEDHGHGDDDEAFADGDGDCAEGGACFBFAGEGACCEHDCDGGFG,False +549,3.0,2.0,4.0,4.0,5.0,8.0,5.0,2.0,HFEFGDGFBFDFEEEFEFGBGCCACDCAGAHFD,False +550,1.0,3.0,4.0,3.0,7.0,2.0,2.0,6.0,ECEBHBHGHBECEFDHAHECEDEDGCHF,True +551,16.0,22.0,21.0,26.0,28.0,20.0,19.0,21.0,EGEDEBEAEADDDCFCABGEFFHDBECHBBBBAHAFFCCDDDDDDHGHEFAAAAAGGBGFGBGCCHEHFBFHHDCDFFBFDGEGFCABBEBEBECDGFEECACDDBCFEDEHHDBDFHFHCHCEGGGEGEADCDCEGEFFHHGCCBCBDBEBEAEAEAGDFHCDGDHBHEHEH,False +552,4.0,5.0,6.0,11.0,3.0,11.0,11.0,5.0,GCCDFHFBDDEDECGCGDGHABDDGGGDHAHAFGFGEGFGFABDFHFCFDBDBFFC,True +553,5.0,13.0,12.0,7.0,6.0,1.0,8.0,8.0,BGDACECGDGCCCBCHCGCDBHHGBEAEAEFBCBEBDGCGDGCBABABEDCHHHHHBBDB,True +554,21.0,23.0,19.0,23.0,24.0,21.0,32.0,21.0,FAGAHAHFHGHBEEFGADABCBGBGFAHEDEFGFBHCECEHEHDGDEAAHGGGEGFFDFBCHGAGHCDGGGABDGDADHFEBHBHGGCACBCBCBGBCFADADGDEDACBGHEFDFHFHFBDDDDBHBGGGCDEFEGEGECHCBCBEBEBEFFAGBBFACECECDAEFECGAGEFDGGAADHDH,False +555,11.0,14.0,17.0,9.0,22.0,14.0,9.0,22.0,CGEEDCDADADBDBFFFHCAAEHHHEHEHAHEFFCFBGHHHFHCHDHEBGFGFBEECFCEEECGCGHEEEEADHBHAABCCACFCEDHCHCHBHBDBECGCEFFGFABBEBEGHAHBE,False +556,4.0,3.0,4.0,4.0,4.0,1.0,0.0,1.0,BABHECAAFBDCDEDEDECAC,True +557,11.0,15.0,15.0,16.0,14.0,18.0,14.0,14.0,BCBCBGDGCGEAHHEHGAFFCFHFCGAGACEBEBEBAFGCCDGBCEFDFDAEADDFDCEBFBFBEHDHEHEGEGBGHFHDDDDCCBGBCBHAHDEFFFGGCHBEAAAHFFDFDFDHC,False +558,5.0,2.0,3.0,3.0,1.0,2.0,3.0,2.0,DGDGACBFHFHAEACABACDG,False +559,29.0,26.0,17.0,17.0,20.0,26.0,24.0,23.0,DADCDFFHFAFACAFBDBACAGABFGFBHCHCFFEFEFGHGCBCAEGGGDBDBABFHFAEADDDEDEHAAGGDBHGFFFFCGAHBBGBGECEGEGEGEBEDCFFDFCCEAAFDHAEBFBFAHAGFHCCGBGBGBGAGABEDADHEBEHHAEFHAHABCBCHAEAFAEBHGHBBBAGDHHHHC,False +560,7.0,9.0,14.0,11.0,8.0,12.0,13.0,5.0,FCDCEFEFGHDAABACGCGCGDEBAHHBCCFCFGEGDBDBDBAFECDFDFEGGCAFABCFGFGEGHCDEDGDGFCBCBH,False +561,16.0,32.0,21.0,19.0,21.0,20.0,22.0,22.0,AFBGBGHGEDFAACDCDCEFEBCFCGHGHFDABABAHCCEAHBEDEDBDCCHGHEBEBEBCDEFGDGFBFEDHDHDBBBFFEGBGHEDGDFBGBACDGEBEBHBHCCGHGHGDGDGHGHBCAFHGHGFABAFAHAFCBCBFAHDHBBCBGFEBABCBCFCFEEBCFEDEAHBE,False +562,18.0,21.0,6.0,6.0,14.0,3.0,15.0,20.0,DGAAHCHBAFHBHBGCAEAEAHAEAHHHBCBGGEBDFAHAEAEBGAGAHDEGHAHBEAEGHGHBABHBHEDCGHGBEDGBGEGBGBABDBAEEHFHBCBCBHB,True +563,19.0,18.0,15.0,19.0,14.0,16.0,17.0,24.0,FAFAFABBHDCDCDFDCAABFCEDBBECDCDFFAGADBCHGGFHDHGHEECEGDADABEHHHHCHDHDFAHGFGFBDBCBFHAGABDBGBFDGGFCFCBHBHFHEHEHEGAGAHAGABAGABEECDCHHEBEDEHAGCGHDH,False +564,3.0,3.0,2.0,1.0,0.0,0.0,0.0,2.0,BABCBDAHCHA,True +565,8.0,12.0,12.0,9.0,13.0,13.0,12.0,17.0,BFBFEEHBFAFGGGCHDHDHGCDCGEHAHEEBBAEFGCGCHCFCFDBBBHCEBEHEHFGAGFFHFHABDGDFDFBHAHDHEAABCEGEGEDCHCHC,False +566,24.0,19.0,7.0,22.0,15.0,14.0,18.0,21.0,AEADAHECBGBFHGHDHAGDGHGBGBHFHBDDDHGHDHDADHDHAHDEDADGFEFGFBDBDFAAAAABEFDHHHEGBGAAEDEGEGAFAFHHBEEHCGBEADAEFFBFDFDBDBGBHAGBCBEFDHGCACBCBAAACAGE,False +567,18.0,34.0,25.0,23.0,26.0,29.0,16.0,24.0,CHFDFHBCBDBFBHEEAEABABCGAFDFDADADADBBBCBDBFCEEEFFAFDBDBGHDHBBBFFFDABFHGCABABABAHHHHDFBFEFHBCDCFCFBFEEGECFHEGEGBBDDHDEDHFHDHDFBAECCBHBEBHBCCCBDBEGHGCFCACEFAGEGEGCCFBFEHEHCGFECGFDAGFGHCCCEEEBEHAHDG,False +568,10.0,3.0,8.0,11.0,10.0,4.0,2.0,8.0,EGEDEHEHCDCEAEAEAFFEHCDDDCACHBHBDDDHAAACAEBFAGAHDCCFEDHD,True +569,16.0,11.0,9.0,12.0,15.0,17.0,17.0,12.0,EAEDEACHEAGBHHFFAGGDADADHBHAFFGDEDEHFBFCGBGFFDGHAEAFBCBEAECDADCGCGFGEGEGAGDEDBFFAFAFCBHAEAEGEGFGFDCHCGFBHBHBH,False +570,5.0,3.0,10.0,3.0,5.0,7.0,4.0,6.0,DADCHHGACACECHCFCFHDEGABAFFFFECECFGGHBCBCEH,False +571,19.0,19.0,10.0,25.0,20.0,11.0,12.0,21.0,EGEGEDDDADCBFBFCHCHGAGDHDHDADGHEDDDDHBHBHCADEEEDDHDBCEAABABFEEAEGHGHFEADDDCABHBHBHFHFEEEEFDCEEGCBCHGAEAGABFBHAHEHAFABHBFDDDBDBHAAFBBAGGCD,False +572,9.0,14.0,14.0,11.0,15.0,15.0,19.0,10.0,EFEAEGGGDGDADFHFGFBFBFGDGBBEBEADHGCBCBCGCECGFDCBCBFDFGEDBDHCAFEFEBGCHAFGFGEEHBGCGCEEEBHCHBADCCGGHAHADAGFHFE,False +573,4.0,10.0,13.0,15.0,11.0,8.0,6.0,4.0,AFCCGEEDEBEBAHAHADFBCBCBEFDGHBEGEFFBFDDBCECDCDCECEDDDDDGDCDCEBBGDHFCCGF,True +574,15.0,27.0,18.0,27.0,33.0,20.0,18.0,26.0,FACGCDEDBABABADHDBEFECGDFHHEBCBCGHHAEBHBHGDADGDGDEEEDEBCBDBEAFHFEDGDGDBCHEAADEDEAEDHCHAFDEDHDACHBHBHEHECFBABHDEEEFEGBGDDHGFBFBFCFCEBEBFFCECEGEFEDGDCBGEGHFCECEBGBHBHDHCEFFFBGBHHHEFAAHDG,False +575,16.0,17.0,13.0,14.0,16.0,19.0,22.0,14.0,HBCFCFDFEGAGAHHGEGBGDGFHEHAFBDBDCHCHGFDEDEFHFBEBHBHBEBHBDFDEDEHEGEFFACACGFHADGFADGBAEADAFBCHEFFBEBGBGBACGGFGFAABGGDGFCCACAEAECDGGGC,False +576,21.0,18.0,24.0,12.0,15.0,14.0,8.0,14.0,CDCDFBACHGHECECEDECECHHAHBGFAAHAGFEBCHAGBBBABCBADCFEGABABCGCFAFEBHAHDHECACHHFCBBBEBECFCFAFAHAFCGDFDFDBEBDCACACADBDEHEFEDGCACAC,False +577,11.0,6.0,10.0,4.0,4.0,6.0,15.0,11.0,HHGHAHGDGCEBABABGCHCGCECHCACHDFBABFHFCAHAHFFBFGGGGGGGACAGECDGAADEHG,True +578,13.0,11.0,13.0,13.0,10.0,10.0,11.0,13.0,HDHDFAHCHGEAAAACGBEEHHDEEEDADCDCACACDGDBDBCFEAGHCFCABFBFGCEFBHHHHGBGCGCGEEHAHFBFDDBDBCGDGAFAFB,False +579,16.0,20.0,17.0,10.0,16.0,13.0,17.0,18.0,HBHCDAHECCCCBHGEFCBCGFFAFACBDGDCHBHBCBEBEDGDFEHGHBHECCCEFAGAEHDGDGHBFAFAGAGBGBGBEECCAFAFDBBHFECBGHCHBHDHBHBAEEEAEHEAGAGFGFGDABA,False +580,19.0,23.0,27.0,23.0,24.0,28.0,24.0,26.0,FGFGCHDADGDHFFDCDABFFFFBCEAECEHADCDFDFABAHABDEDBAHCCCHBAAFAEGEGFGHDHGHBHGHDCFCFCADEFEHBAEEFGCDCGGGGGEHFGCGCFFHFHGHBCBDBDCCCGEBEHFBFCFEECFGHGHFHCAEBEBEGHGHFEFDCHCBCBGBDBEAAABCCEAFBHBHDHEEGABDDDED,False +581,14.0,16.0,19.0,20.0,20.0,20.0,13.0,20.0,ACAFBEAHDHEHBHCABBCHFHCEEGCHHFCDCBBEBHFABGDHFHFHBHBHBGDDDCFFHFBFGFECDCEAGAGACCCGCDCDEDEDADADFFFAFAGHCDAGHFEEGHCEEEHECECEGEFDFEEGDDDGDBBFBFBADH,False +582,13.0,15.0,13.0,20.0,21.0,19.0,19.0,16.0,EGGAGAHBFFEFEHECDCFCBGHFFGAGAGEGCGAGBFCFDDDEBEHEHCFBDDDDDDADAFAHHCFDEDBFFFFHAGCBDAFBHBEDGFGCBCBGEGEDCDCDCFHEHGHBDGEHABEGAGHFEDAHEEEEEBHB,False +583,6.0,13.0,10.0,9.0,17.0,8.0,10.0,9.0,FHFGBBBBABCCDHBEDHGFDEHCGCBEBEHCFCFBFBDBACFHGHGEEECECEDEDEHEDGCAEADFDGEAEGGGEBABEH,False +584,18.0,27.0,27.0,16.0,19.0,28.0,14.0,16.0,FHFCFAFHHBEBFBDCHBGEDBAFFCBHBCFGFGCGCEEEDEDBABGEFBGBAFAFHEGCGCDCDBHHCHAHAHGCECAHFHFDEGHBBCACABABFBFBFAFCDCDBABEBECFFGBECCCHCFAFDDDDFDBECEAEDBFCDCEFGFABABCCGEHCABGFEF,False +585,26.0,16.0,22.0,22.0,20.0,21.0,22.0,26.0,FHDHDHFCEBBDBAAAAGFGCBEDHDHGHAEAECDCBEBHCHAHGGFDAEFCFHHHEECCCDCDCDHAHABBECACADAHCDCDFBBEDAAGAFFHCEEEAFAFGFCECEFACAEAFFHEGFHCAGECFFGBGFGDBDBABAGGGGGHHHAHDDDHHHAHDGEGFGBGBFCEDGD,False +586,8.0,5.0,12.0,4.0,4.0,13.0,13.0,7.0,DFDCCCCCCFEBEBDFFAFGCGCBFDFBAAFHGHGCGAAHGFAFGFGCGAGBCHFHCGGHFHEAEG,True +587,4.0,3.0,2.0,3.0,2.0,5.0,3.0,1.0,BGGGDBDHDFCAEAFCFBFEFAA,False +588,7.0,14.0,10.0,16.0,16.0,9.0,9.0,13.0,BCDFHCGFGAEFFFDDBBHBFBHHGAEDDFDEHEGEGEHADFEEHEGEDEDEDEHHBHBDBHBDCDCDBBFBABACACEHECGHEBDGDCCCAG,False +589,41.0,28.0,27.0,20.0,22.0,14.0,25.0,23.0,EDEHHHEACAEAEGECBBHBHBEFAFEBAFHHGHAHACAGBDBEGCDEHAHADACACGEDCCCFBBBBBFAADACAGECDFHGDDBDCDCECDABAFCBEGEDFCGBGDHACABGHECBGGCDCGEFEAGCGDAAABABABDHGEAHBGAEHGBGBFCFCFEFBHGHBAAAAHABABADAGACACGCACHDHDHAFAGEG,False +590,25.0,17.0,16.0,9.0,20.0,24.0,14.0,17.0,HDFDEGEFBBECCBDBABFFAFDFCECBAGAEABGFHCACAFAFAFHEHEHECFCHEHEHECGBDBAFEBCFAFCFAGGCFCABHGABFFEGAHAGAGCHHEHFDFBEBCBEFAFAHAEFEAAHAHBHBGDGDGCEADAGEF,False +591,17.0,13.0,25.0,18.0,20.0,19.0,18.0,19.0,ADCFCHDBAEHEHEFEACAFAFDFEFECEGADHDHEBCCCCEHHGBDBDGCCFBGDDCGABAEAEDEAFAFCGCFHFEGAGDGFHCGCEHEAGCHCBDEDCFEDHCBEBFBAGEGAHCHCBCBAHACDBDCDCHFHEGFGFGDGHGFFH,False +592,4.0,14.0,3.0,5.0,17.0,15.0,9.0,5.0,HGFEEHBHFFEFHFEGBABFBGDFBBEFEDGDEDECEBEFEAEBBBBEBFAHAGFDFEFEBGCGFGBGFECE,True +593,13.0,8.0,10.0,11.0,8.0,10.0,5.0,8.0,EAEADADGFGCDDFBFHHGADABAFHHBAEABHHGBCFCFDFAFDHDCDCBFBCCCBCEEEAEAEFDAHACDG,False +594,16.0,13.0,15.0,7.0,3.0,9.0,20.0,22.0,BGBGCGHHHEHGAAFGCGBDFAFBHCHBDBCCCFDAHHBGBAAABHHHGHGBABABCCCCCDGHGHCHAHGEGDBFGFGCGAHAGFCHGGGAHAHCHFEDHDAAF,True +595,12.0,10.0,9.0,7.0,8.0,10.0,12.0,10.0,AEFDFGFGABHBHBACAHFFEECEFDFGBCAABBCDCGEBEBHHHHFBAEADGDGHGDGDCACGCACAEFHAHGGGBF,False +596,12.0,14.0,7.0,5.0,7.0,8.0,16.0,11.0,DBGBABFCGCGEGBGCHCABEEHGGGHGHFBEBABFBFBGGGGFDFCGABABAFAHHHHBEAAADDHCFEHAHBGACDGE,False +597,12.0,31.0,25.0,23.0,29.0,22.0,19.0,20.0,GBCAEDEGEDHCHGFBEGCCDCGAFBFAFEGBBDBDBDGGCEHEHFHDCDCDEDFHHBGBGCHABGCGCFHFDEBCDHDAABFBGBHDCDCEHEBFBFEFBFHEHEGEBBDBEBABCDGDBHBDFDFDACCEFBCBFHFGCEAEDFCCDCFGGEEEAEAFAFBHBEBCBCHEHCHGEEEBE,False +598,3.0,2.0,2.0,2.0,0.0,4.0,2.0,0.0,DADAGFCFCBGAFBF,True +599,18.0,18.0,17.0,19.0,19.0,25.0,24.0,26.0,EFEFADADEGEGBBHHABBHCCGAFDHDFEHHHHHHGAAADGHFHGGGGDEACHCHCFCGEGEFABEEGEHFCFDFEBGAHCHGFGFGFGFDDHEFCFEBDFEACAFHCHFBADGCGBADGDAFCHCHDDDFDFHCHBHEEEBEBGBABABABCBFFHFDGCGBGD,False +600,18.0,13.0,8.0,18.0,9.0,20.0,11.0,10.0,FAHEFAFAHDGGGGHCBEGABABFEFAAGAGAGAGAGBHBHCFFDHBHDEDEDABCFCEDEBEFADDBFFCFHFAAGDDDDDDFFFFHADFFFBBBCDADCCADHBE,False +601,28.0,16.0,18.0,22.0,25.0,31.0,31.0,28.0,DHDHCHCEGGGGGGHGHGABHGABAGDGEGBACHDHBGADFBHGAGFGDDADGEAEACHBBFFHFEGEFFAFAFGFEFAGADDFAFCFGHBFFEDBACABFHFCCCEEDFDCDAAHFHEHDDEDGHEFCAHFFBCGCGCACABAEAEHDHFHFHFCEDEDGAGAEEEEEFDAGGGHGHFHAGEBHBAEFCFBFCEHBHD,False +602,19.0,22.0,22.0,6.0,18.0,28.0,18.0,32.0,BEHEHCBFBFGAGFFFHEEGEFFGCHCHFABHHCCBFHFABBEBCACAEAFHFABHCHGBBAHEEEEAHAHBHECACAHEHEHCGBFFHFGAGCCBCBEFEGHDDGDHFHCDAHHHHDAFBFAFHFHGHGACCCACBHBGBGBCFGFHFHFGFGFAEBCGCBDEF,False +603,6.0,3.0,3.0,0.0,3.0,1.0,2.0,3.0,AAAAHHHEAEBFCEGAGCBCB,True +604,20.0,12.0,4.0,14.0,4.0,16.0,10.0,13.0,BHADGGGBAFFHAEDBAFGFCFHFHDHBHBGFFHADDEHFFBFGHAHAHABACADFFAAGADAGAGACADDEFEFDADAHBGBABDBDBDCHF,True +605,13.0,12.0,3.0,10.0,9.0,12.0,19.0,5.0,BFBFCDGDBDAGAFCHBBBDHGADCEAABAGFGFGEGEGDGFAFEGBGAGEFFGFGEDADBBGAGAGEFEBBHGHGEDDAFAH,True +606,25.0,22.0,15.0,23.0,20.0,14.0,29.0,17.0,ABABABGDEFEFEHBAAAFDDBDGDGAGEEBHFFCAHAGABACACHEGDGDFDHGGFFHFBEDECFGHCBAGDGCHBGBGCGFDADECEBEAEADAFEBEAEFCBCBCBHBABGBHAHAGAGDDEEEHBCEADGDGDHHFDGABDBDGGCGCADGGHHDHGGEGC,False +607,7.0,12.0,19.0,9.0,3.0,6.0,12.0,7.0,CHGGCADECECGBGCGCEHDAFACDBGGFABCBCBCBCBFBCGCBCBCBFHADACADHDCGGGDFCHGFCHDHDB,True +608,15.0,15.0,12.0,14.0,12.0,4.0,21.0,15.0,BGBEFEGDBCGCGHHEGCFAGEBFGHBCCEGAHACGBDBGBHAHGHGHEHEHACABADADAHACBGDAEHGHBDBDBEBAAAFCGCGDEDCDEDHDAGHGDGBGEGDC,False +609,11.0,19.0,6.0,5.0,9.0,14.0,11.0,10.0,BBBBGBFBFBABDHAHFBBAHEHFCAHGGDGDFCBCFCGAHBDBGBGFGHAHGBEEAFFFBFEFEACACEEGEAEDGFHAHBBBF,False +610,7.0,6.0,1.0,2.0,7.0,8.0,15.0,3.0,GGGGGDGFBAEAEBFHGHDFAGBEFEFGFGBHAGAGBCEAEGBGEGAFF,True +611,9.0,11.0,18.0,12.0,13.0,14.0,18.0,18.0,DABAEGBGEGEGEGFDHCGCHAHFHFCCCCHHGADFBGEHAHEHECFHEHEAGABDGEBCBFFFGDGBGACHHHDHCFCDCHHGDCHCBCDCGCBBDADGGGEDECBFFFFEF,False +612,1.0,6.0,5.0,8.0,3.0,4.0,3.0,4.0,BEBEBGBFBFDDCHBDFCHDGACHFHGDCDCDED,True +613,5.0,7.0,4.0,9.0,3.0,12.0,4.0,8.0,DEEHBFGFCHBHDHFAGDBDHDFCFEBHHHBFBABAGAGDFDCDFFFFCFDA,True +614,5.0,4.0,10.0,9.0,2.0,6.0,6.0,7.0,GCBCBCGGBFHHCFCHHDDDDCBGAEACACFDADCCAFHFHDHDEDGFG,False +615,20.0,20.0,21.0,19.0,32.0,21.0,14.0,26.0,FCCGGEHECEDEDBBECHCHCFGBEHECCCCCHCGCDCDEHAGCECEDDBEBABABEBEAAAAHAHEFAFHFEFBFBFAFGEEEAEHEBGHEHDBCBDAAEFFHCGFHHHGCEAGDBEHEFEGDFBFAHHDBCHFFBEGEGFHECEADADADBHFHAHDDFDFHEAEBDBDGH,False +616,4.0,1.0,4.0,5.0,3.0,3.0,4.0,3.0,AGAHCHBGDFDCHEDEDEFCFCDAGAG,False +617,14.0,17.0,16.0,17.0,18.0,16.0,11.0,15.0,EFEFHFABEBEGEAEBEAECBDHFEEGEGBGDHHHHHBHBHBHAFAHDBFHABDDFDHBGDECECEFEFGDABAFAFABDHFBFCGCGBEFCDCEADDDFACAHDCCGDDCBCGCFCABECGCD,False +618,29.0,30.0,26.0,14.0,18.0,25.0,13.0,17.0,HACCBHBFAFBFBFHFCBAAGAEBEFDDBDAAACACACEEDDAEFGBGFEFCABAGAGAGFGCHCAGFBBDFHAABFCFCFDHEHCFBFBHADBBBBHDDBCFABBEBFBADAEBCBHBHFHCBDDHCHGHCACAGAGDFCFEAEBECECECFCECECGHEBAFAEAGHBCF,False +619,31.0,22.0,24.0,19.0,30.0,25.0,19.0,29.0,CFHEHCGFFACEHBDEEGGACFCACAGAHAEAFDCGBACEFGAECCAGHBHBDBAEAGFBABAGACAHHHAHCHCDCDAGGGAHAEAEDGGCEHFHFHFDGBHBCEHEDEFEFEFEAADACHFBDBDBDBFBFAEHFHBHEHEGEDEDCCEBFBFCFCAHDBFEAEFEACAFADEBEHHDEGEAHBHCHDBGBCDHFGF,False +620,18.0,17.0,15.0,24.0,21.0,15.0,18.0,13.0,ECDGDBDGDGDEAEBEBCFGFGAGAGHCDEHEHBGGGFEAAFBBDFHCDCEEEEGAGAGEDFDHDHAFAFHEHDADADBDECACEDDBHFEGECADDCFHBCBCHCDDFDGBBBEAECEDEFABAHCHGDABFBFGFCBGA,False +621,0.0,2.0,1.0,1.0,4.0,1.0,0.0,1.0,FEEDEBEBHC,True +622,14.0,20.0,14.0,20.0,27.0,29.0,12.0,26.0,CDCACEHFHFHBHEFEDEBBFFFFBFECHHAHEHEDGDEEBFHFHAACEDECCCCEFEHAHBHDHFHFAFABEEEGEGEBDAHEEEEFHDDDGDEDABHBAFGFEHABFBABDBFFFHFCFHFBGCABBGBHFHFDDAHGFEFEDHCHDEBGGGBCDDDCGF,False +623,16.0,25.0,17.0,19.0,21.0,19.0,21.0,15.0,BFDFDFGBGDHBHEDCACFCEHEDEBCFDEDADBDACADDEGEGHAHBHFEBCCCAHEHEBEBAAAAGCFCFGFBEEEHBHEHGBDBDAGAEAGBDBGFEFGBCBCFGEGBGHDHGCCAADCDCBFBAGGFGEHDFBEBFBFDFCFHBGGGEB,False +624,23.0,27.0,21.0,27.0,12.0,19.0,33.0,26.0,DHAGAGFBFCCHHGGBCBFDFACGBGBGHCABACAHFHCDCDGFGFCFGFCAEGHGABABEDEDHFHFDFBGHGEGHAHBHCDAGAGAGBBAEAFGCACBFBDDHGHBHDGDGBGDAAAAEBBGBDBDCACFCHCBDBCCCBGFFHDHDHEGEDEHHDDDHBGBHDFFEBDDEEGGGGAGHCHDBAGD,False +625,17.0,22.0,27.0,7.0,24.0,19.0,26.0,18.0,GHECEGFGAGCBEEGBGHGBEBEAEFGFAFCFHGGGGEEECBFBDGGCGCEDGFBHBCBCBCAGABEGEAEABFFFBFBFHEGFGACAEFDBCBCAGAGAGFFCCBEHCCBCBDHCBEHCHCACEBFBCGDAHFCECEDACAEHHHHHDAFGHCHCEGEH,False +626,21.0,20.0,18.0,14.0,19.0,24.0,20.0,19.0,FGFGDBFGAAHHDABADDECCHFBGCEEHGHGHGAFHCHAHBCBFAFAFABBBABADDGEBBFCFCFCFCBCDCDHFAGGHGHGAGEHBFAFCHHEGEFBHDHAHAEDGAGAGEGCDEHECCCBBBAFFFEFDADBBEDEGCFBFCGAEEEEFEF,False +627,22.0,20.0,15.0,21.0,16.0,16.0,15.0,16.0,GBGEFDACFGFGHBHECCFAAAEEGBCHCBCFADHDHDBDBDFDADABAEDFBADACBCFCFEHGCEFEAEBHDHDFDEEBBHBGAGDGAEAEGGHAHDDDDFDGBBBAAAABDHGHFAFECCCECHBDBCBFEFGAGAHH,False +628,7.0,15.0,8.0,13.0,14.0,12.0,11.0,8.0,DEDBDHFHDCDCBBBCBDBFBFCGHGAGEFAFAEADBFBGBGHGDCFADBDFEFEDECEFHHCBEAGGGDEBECEABBGHGFDHEEFE,False +629,1.0,3.0,3.0,8.0,6.0,2.0,4.0,5.0,HEHDHDHDEFBGBGDDCDHBEDECGCEEFGAD,True +630,11.0,10.0,7.0,6.0,8.0,14.0,8.0,5.0,CAHAHABFCFCACFCAHAGDBCEGHFHEBDFAGAGABBBEBCFEFEFBFAFBDEDEGGDFDABFFEFGG,False +631,14.0,11.0,20.0,21.0,13.0,15.0,14.0,16.0,HCFAAHBFCFAFHFGDHFCFBBBEBEAEAEHEHGDDBHHHFHDCDEGECFHFDFDADACADHGEDADHDHDCDCGADDECEAGBBCECDGGCGCABAHFGCDCGFBHBDCDGAGCCCDCGEFEF,False +632,4.0,8.0,5.0,12.0,1.0,8.0,6.0,3.0,CAHAEDBCCFGDBDFFBFBHDDDDDADCGBGBCFAGDGFGFHDBDBF,True +633,3.0,4.0,7.0,2.0,2.0,6.0,5.0,5.0,CBCECACAFEFDAHBCGFGFBHCHDHCHGGFBFG,True +634,15.0,14.0,8.0,23.0,21.0,16.0,17.0,8.0,GDDDADADACBFGFGFAFACADAEEBEBFCGBFHFHGEDDDFCGABCBDHDHEEFHAHGEFDFEFBFAGAFEGDGDGBGDEDEBHBDCEEEEGEBCDDEAECDDDEGGGAFAEBFBGHEDAB,False +635,16.0,23.0,27.0,12.0,33.0,22.0,20.0,34.0,HEHACECAHFBGBEBHHHHFFCECEHEAEGDGDHAHBFFFFFFFGABCEFEBECECHABGCGFHEEEEEEGBCAHEHCHDFBGBCBCBHHGFBHDHCHEHEHCFCGCGEFHHHCDGDEDECBCAFEFAGHDCABHDAEACCHGHFBBHDEAGBGAFDDGCACEFEFEHEHEBEGCCEGBGBCAHBHB,False +636,18.0,21.0,19.0,22.0,14.0,15.0,21.0,26.0,GHABCDDDAGGFFEFDFHBACHDHDECGBFBFAAGECECDAFBHCDCEBGBAAAGHHEHEHEHEBAFDFCACECECEHHHCHDHAHAHCDBDGGGDHDBCCFCGHHHGDDDBEBFCFDGAFBFBDBDBGBGBABHHCHGHGDBEGAAHDCGAGBGF,False +637,7.0,11.0,15.0,9.0,7.0,9.0,10.0,13.0,DAFBFHGDGAGCDCDGHBCECFCGCDEDHDHBHBFBEGEHDADBBBBGFHHAECHGHGHBFCFAACCCFFHGACHCBCECE,False +638,23.0,18.0,27.0,21.0,18.0,14.0,17.0,30.0,DEDCHCBFEAEAEABAHGDGDADEBEHCFDGGCCCCDCBFGFCCHDHDHFBABDHEHAHFHCAFAEADHDHCHEDACCGCGCGCBAFHHHECDDDBGHHHCHBHAHECFBBGBDBFHAHGHCDGHGCGCBBBGBABFGCGAEEDFDAEHFHDHEEACAEFEACHCAAA,False +639,8.0,5.0,5.0,6.0,7.0,4.0,6.0,5.0,FGEBDBDBGHGDGCAHAHCDAGAFAFBEBEGEFDCHAEECEDACAH,False +640,25.0,30.0,19.0,18.0,18.0,25.0,21.0,28.0,DBGBFBFHFHCAFAFACGCHCHEHEGFGADHHFEAEGEGHGEAEBDADHBABDGGGGHBHDDGAEBDFCGCFFGACDHBHFHCHFAGHEDACAHBDDDAHHEBEBABACAGBDEDGHBHFHFCGCDFBFBFAHGCBDDCBAEAEFCABABACACEFHFBAEHEGBGBHBFFHBEBFBFBFHCBC,False +641,10.0,7.0,19.0,15.0,18.0,26.0,16.0,17.0,EBEBEADCFGFGAADCEFHCAEDEAEFBHEHDGDGDBHCGCFHFHCHFEFGFGCECFCGCEDAFEGDFCAEADCFEFHHHFDFGFGAGDGDFHHGACFBHDHCGFGFCHCHCHCDEECFFFFEBEBFD,False +642,17.0,19.0,31.0,20.0,20.0,27.0,31.0,22.0,EFGFHEBFAHAHFHGCFCFGFHFBFDHDAGAGBECCHCBGBFEABDEGEGFCBDDFEFADADBFEGEBBAEHEHAHAFGCGCGCBCBFGFCACHCECGCBCAGFHDBDCAFGCGCGCGCDDDCDGDGFBHGFFAHCFCFHECDGDBECCCDCEGEFBFEHHGAGCGDHAHGHEFDHAGBGBGHDECE,False +643,10.0,16.0,8.0,13.0,16.0,18.0,19.0,19.0,DBDFCEGABABHBFGAHEGFFDHCFCFBDHHACAFECHHHHGFGBEHEGEGEGFGBBDBFEFHFCEDECFAAGFGFEBAGHEHEHEGDBDFDFBEBDBDFDBGEHCAAGHGHGBGHGHD,False +644,23.0,23.0,24.0,17.0,10.0,17.0,18.0,14.0,BGGGGGEGBACCECHCHCACDBAEFEFHAHACFGGADDCDCDCDGHGCBHBAAFGFGFABBBBFBHGFAAADADCDEACDEACBHEEFCCHCHAFBCHGEGBFDFHEBBHBDBCHDBDBGFCFBDCGFGFACABBBAAAAAFDCDC,False +645,19.0,20.0,19.0,12.0,21.0,19.0,19.0,26.0,BCHEHEABABAHAHDHBEDEAEGECEBECAHDGCFEFCHHAHDHDHFBDACABGCEBHBCFHGCCCAEEDAACABBHGHGHFHBEBHDECEBDBCBFEFHHHGHGHGHFHFBDGEGACEFDFHFEFCGGGAEFDFGCGABFFCFCGBGAGFBAEA,False +646,24.0,19.0,25.0,16.0,26.0,22.0,27.0,28.0,DADGFHCDDBDHDHGGAEECHHHFCAGACFCFEDCCECEGFBFBCBGEHEACBCBGGHGAGFHCGCGEFEDAHAHFHEBBBHHAAEAECBGAAFBGBHBHAAFEEAECEGHGFCDCHHHHBDFGFGFGBEAFHFDAHAHCBCEHGHGFCDGDGCGEFABDBFBAAAHADEDEGCGHECEFEFECECG,False +647,19.0,19.0,11.0,23.0,12.0,13.0,15.0,22.0,FGFAADEGEAEADGDFHAHBHDGGGHDFBHBDDGDCDHBHBHEHECEDBDBEBHHDHEABCCGFAHGGEADAGFDAHEHDHDCDGDHHEHFFFGEGBDCACACDFDHBBBBDCGAAFAHABABACACFDFBBHB,False +648,14.0,18.0,21.0,17.0,4.0,13.0,14.0,14.0,HDCCBGAGBGFGFHCCACHCGCBCBEDEBCBDBHFCFCFGAGACBGFDFBHBADAGHCHBHFCACDFDBABAEGCHHDBDCFBECGCGBDAFFGHDBDBDADADACFDADCHHGH,False +649,18.0,10.0,20.0,21.0,15.0,23.0,20.0,19.0,CDCFFDAABAFGFDBHFHGADADAHGHGBDFCHHHCDCHAHADCDGDGDGCEFGFCECFCFCGCAAAAEAEDBDBFFHHHFECECGGEGAABHECFHDEDGHGAEADFFHGDGDGEEBDCFGEHFCGCECEDDFFFFBFBCBHHAG,False +650,2.0,8.0,12.0,4.0,7.0,2.0,3.0,2.0,BECADGCCCCCBCBCBDGGFECECDBDBHECEFABHBCEE,True +651,23.0,17.0,14.0,13.0,18.0,7.0,9.0,12.0,HGFCACACFCDEEAGBGBADADABCGDAEADGDBACFHBEDAABHBHGHCAAEBECECACEDECEGFGAAHABAEAHDHABABADEBCFCFBEEEHEBFBAEHEHDCDBGBHD,False +652,9.0,5.0,7.0,3.0,3.0,4.0,7.0,7.0,FHAHAGGGGHGCGCEHEAFAFCHDECHBABCFGBHBACDCDAABA,False +653,17.0,14.0,10.0,12.0,16.0,15.0,12.0,13.0,FFDCCCGHBHEFBAEAHDFFFHBBBBGAFABABAEADAEFCBDEEHFDACHCHDAFCFEDGBCBCBEBEGGGCHHDDAGAEAEDEDEBEHDHAHEFGFGFGHGAAEAFG,False +654,18.0,23.0,28.0,27.0,18.0,13.0,30.0,25.0,CGCBCACGBGHACACADFEBGBCAEHBDBCHAEDGDFDCCAEHDGDFDFAFBGBGEDCFBFBFDAHGCCCBGBHEHAHGGGCECEHEAGCGDGDHBBDGCECHAHDFDGEGAGDGEADHCACBGBCHAHAGBGHHCHCHGEBEAEDECHBGBGDGFGEGHCHBDDDCDHDFDHCFEHDBDBF,False +655,15.0,11.0,8.0,7.0,7.0,6.0,7.0,13.0,EFAFACBEEDCAHAHGEAEFFHBHBFBFHGAAHGHGAGDCBHHHABDBEBAGAGDDDADHBCBEACHCACACHB,False +656,23.0,17.0,14.0,15.0,23.0,23.0,21.0,14.0,DBBBEEGCGFABAGAHAHFDEEHECBHBFBEAEADGDACGFGFCFDFGFGFGBEBEDEHHCFEHAHAFAHEBABEDEFGFGBGAAECFCHCEAGDGDCBCAFHFDFDFCFEEEEECFDBGGGAAADBGBHDAGEEBHDAAAHFGCGFAFC,False +657,22.0,13.0,20.0,11.0,19.0,20.0,13.0,19.0,AAAEEECFGGCCCDBDAFHFAFCCBAAHBBBEBFBAGCGEGHCAEACDCEADBDEAFCDGECEGGAGABAHAEBHHHHHCFCFEHCHFHGHCHCFAFDFDFDHBEGEFFFFAEAECEDEDHFGABFEGCHCHAHABF,False +658,13.0,8.0,9.0,8.0,6.0,14.0,16.0,11.0,DFDAACADGHGFECCGBFFFHEAAFACAGFHCGCFAFDFBBHHFGAGABABAGEFEFGDEBFBDBGACHCHCHGDGHGHGEGDGH,False +659,24.0,22.0,11.0,20.0,12.0,19.0,20.0,10.0,ECECBBAAAFHDHDHCBGFGFACABAGGHADBEAFFDFDFDEGCGCBBBFAGABBEDGGAGFDAGHGDDAEABBGBHDGEBFBHDFGCBCBEBFDFDADADBBFEHEFEFDFHFEGDCDCDCGBGAAAAAGAFAHBGA,False +660,9.0,8.0,11.0,8.0,16.0,14.0,26.0,11.0,FEGEHCHBGBGEGHGHGEGHDEBHAFACGDGFGACHHGAFCGGFEHDFDEEGBGBGFGFGCCECFAFDFDHBGDAAHAGEGDGEGFGAGEBCCCCBEEGEFEF,False +661,21.0,16.0,26.0,12.0,16.0,24.0,13.0,16.0,AHBFGAHHBCBABABCCGBEFACECGHGFDAHHCCECFFFDFAHACACBCBGBDFEFEHEDACAEDEDEGEGDGBBBGCGAHACACEFAFDFAFBDACAFFHFCFCAGEGBFDFBFEGCFCBCFHACADDCHFHFCECEHHHCE,False +662,19.0,21.0,19.0,34.0,20.0,23.0,22.0,19.0,AFAFBGBGBABGDDADCFCECGGEAEACHDHDEFCFDFDECHHGDEDEGGFEBBBBBEFEDDFAHCBEDDBACDCDAHAHGHDCFCFDFEFEDHCHDDADBGCABDHEBBFBDCDHDEDEABDHEBFBCEAGGHFHEAGFGFGCGDGFGDGAGAGABFBFDDHDCDHHGHECDCFAF,False +663,30.0,32.0,21.0,26.0,25.0,15.0,23.0,18.0,GBDHGHGHGBGFGABAEEDBCBCAHAEEDFDADEGCCCGHDBBBEDHGGFCBBHEAACDBGAGBGFEAAAAAABADGGBGCDCFCFDFCBHAHBBBHBHGDBDEHBHBHBEAABABDDEAEDFDEBEBECEGEFAFCFCADEGCGBABABFBCEADAEGEGDCDGBFHAEAEFCDDHEHAHFDCDEDCAC,False +664,14.0,12.0,16.0,18.0,20.0,25.0,19.0,23.0,GFFDFGFDEAHBCEEHCFEEEABFGFGHGAGAGCGCFDBDBDEDEABABDBHFCFHDGAGEHEHEGDCDCFAAGAEEHFGFEDCHFHGGEHDDGBADDGHFHEHEHECFCFCDCAEFFFGFGCBHHCCFCFBFHFHEDADHHHHABB,False +665,1.0,1.0,5.0,0.0,2.0,0.0,2.0,0.0,CCCBGGAECEC,True +666,13.0,18.0,8.0,9.0,12.0,13.0,18.0,15.0,FADABCFAFAFGFGFBCBGGGFGDCDCABDHDAEHEDGDGEFFHCGEHHFHBGAGAHEGEGABFCGBGEEBEHFHBHBHBHBFBHCABBHGEEDCDBABABHGGAE,False +667,12.0,9.0,6.0,10.0,3.0,13.0,8.0,9.0,CBCHGHFADHGAGBCFDFAADDFCFHDAAAAAFCFEAAFADCDGDGHFHFHGBFBFBEBHGHGBBDFDEB,False +668,25.0,23.0,24.0,17.0,11.0,21.0,16.0,12.0,GDAFFFFHBBGCACGCECBHAEDBBFFFBCBCACACGBABEBEDDBFAHBHDAGAGBGBGAGBGAGEDBAFCCDCGAGHCDADACAEDFHACBEAACFDDBDBHBDBDFFFCFCFCFCAAAEDHFAFHCHCACHCGAGFFCEEBEBGDH,False +669,3.0,6.0,1.0,5.0,4.0,4.0,3.0,1.0,EABGBEBGBFBGDFDFDADEDBFHEAC,True +670,5.0,9.0,11.0,15.0,8.0,21.0,12.0,11.0,DFDCHCFFDHHAHACGGFBDBDCDCDAHEFFFHBDBDBEECFGDGHGBFCDADABHBHGGEGCCFFFFFDFHEBGCEFDFGFEFEHDGFGFC,False +671,9.0,14.0,11.0,13.0,12.0,14.0,11.0,23.0,HDHCHCFCFCHCFCDADADEHFHBAEGFGHCEDHFCCDEHAHFEBBBADCHHHHDHBHEDDDADHDBGBGBCBFHEBEFGBGHGFFHAHGHBAFAGBEFEBEHEGFG,False +672,3.0,4.0,0.0,0.0,2.0,6.0,4.0,2.0,HFHFAAGEGFGFABBFGFBEB,True +673,17.0,21.0,20.0,5.0,12.0,13.0,17.0,15.0,BCBDBECHCAAADCGGGGFBABABEBCBCACAGHBHDHBFEEEEAABCBCBAAHBGGCGBGHGFGAGFFCHGHGHBABFBFHCHADDFCCCECECHHEAFBFBCHHBCEGGCFAEAEGFF,False +674,14.0,34.0,17.0,24.0,19.0,23.0,30.0,24.0,BBGEGHHHEHEFABDCHCFBDAGBBBBDBFCFCFAHHEHAFGHGEGEDBDBDHCFCHCEDEDEDGCGCDDDGDGAGAGEGBHHCHADFDBBBCDDACGHGEGEHBGBGHFEFGFBBDBHBFBDGGCGCDFGCBBBDADGHFCFADGEHFCFAFGBHFHBGEAEBBBAFGGDGFEFBBHEHEBABF,False +675,22.0,22.0,20.0,24.0,22.0,17.0,36.0,34.0,CHGHGHAHAHCECDBGCADHEEGECDGBFCCHCHFGFGBBHFHFHEGFGAGCGCGDGDCBFBFEFEHEDECCHBGBDADHFHEBDBGFGBAHGHGEACGGAEAHGBDCDGDHFHBHCECBDHGGGGHBBDFDFHAAAAAHADADHGHEHAGFGDGAEDGDEEBHACFGHBHBHCGGGCAHEEAEHEFDDDGDBBBAE,False +676,5.0,3.0,7.0,7.0,6.0,1.0,5.0,6.0,EHCHEBAGEGDGDCCCCABHEGBAEDEDCDFDADAHHCHG,False +677,14.0,12.0,18.0,20.0,14.0,12.0,11.0,15.0,CCADHGFACAHGHDDDDDGFGHBADGBEBCCDDDADADABBHCFCFHBHGAGEEEEEEEGEFHCDFAFCCADBDCDCDCBBBBCHCBDAGAEHDHAHAEEHEHFFCGCDFGECFFH,False +678,20.0,18.0,16.0,16.0,18.0,22.0,18.0,25.0,DFFHFHFGFBADAGHCBCAGBCBFGFACBEFEGABBBEGHHFHFDFHEEGEBECFCEBEGGADEDEAEACHCHABEHAHAFAHAHAFBFAECECHCHGHAHBHCHFHGDCHGHEBDBDGCADEDGGFBFGDBDCFFEHDFDFDGDHCHBGAAA,False +679,13.0,13.0,11.0,11.0,12.0,13.0,13.0,10.0,DADAHACGEBDGEGEDEAACHFGEGEGFGFCFAFEBCBFEFHCCFCHCHEHAFFDBBBHGCEBGBGAAHFHGHBFDEGAGBBBBDDADADEDACFC,False +680,21.0,9.0,11.0,23.0,10.0,11.0,13.0,22.0,BHEFDAEAEGGAGBCHCBAAHAFDFGGGGBHADEDACFCFAEABHBHBAAADFFACDDDHDHCBCFHDHCHGDAHAHDDDCDADEHFFAFDEHHDHECDADAGAGBHHGHEHEHCDGDGD,False +681,29.0,26.0,19.0,24.0,29.0,20.0,27.0,23.0,AAHAECBCBAADACAFFGCEADCBGHGFEFEAEDEDBDHDEBHDHAACAHAEBCBDFFHFBFBFBFGFBEAHBCAEAGAGBEEEEEEEEDCABFGFBDHFAFAGBGHGCGEGDADHDFGBCBHBHACEBDADEDEDGGGGGGGBHBHDHCFGBBEHCCAHHFABDCGGECFBAHGDGDCEAEHECEGHDFDEDGAHA,False +682,12.0,18.0,15.0,23.0,25.0,24.0,20.0,8.0,DADHGFBFDADAEECECBFDHDBCBABAHFFFFEFEFBFBFBEDFDEAFCCHEBBGECCCCFAGBBDBGCEEDHGGEGEAEAEFDDDGDAFEGCGCGCFEDDGDFHEDGGGGGEBEDFDEDHBEBDCCEFFFEFEBABFGAGHGD,False +683,10.0,19.0,7.0,19.0,5.0,6.0,8.0,11.0,CHCGBDFEGADBBBBBEGHAFAHBGFACAGAHDBDBDADHDGDBDCCCEDDHDADADCDBBBHBFBDBDFDADEHHHBHGGEFBB,True +684,10.0,3.0,3.0,5.0,2.0,4.0,6.0,12.0,DBCHHBHEDEGAGAHFGGHFAAAGAGADBCHAHAFDFDACHHHHH,True +685,10.0,19.0,16.0,24.0,9.0,16.0,18.0,17.0,DGDFEBDHDADCDBDHFHFHAGCHCHAGEEBGBGBAFDHCBADCDHAHEEABDDFDFABBCDDADCDFDFBBGBGHECCGCGDECGDBFGGEGECHCGFFBFBDGFHBHBHBCGCGCGBDDDFHFHFHA,False +686,11.0,7.0,14.0,17.0,14.0,20.0,12.0,14.0,HDHABCEFFBEHCGCACACBHBGEGEFFFBGCECDCDEHEDEGFGFDDDDGDGAHDHDADADFFFAHAEDHFBADEDBCCGHAEEECFFEFCFHFGCGAHDFGFHFCFH,False +687,19.0,24.0,19.0,21.0,13.0,20.0,17.0,22.0,GBGCDCDHFCAHAHBFFDCAGBFBABCFFBFACBGHGHBFFGHDDADHFHFHBGGHGAFDFCGAGEDEGEADDFCBABFBABAHEDEGFGFCBCFDDADACECEBEBCHCACFEGCHBBBDDDGHHDHAHAFABDHEHEHEGEDBABCBDBHCHC,False +688,11.0,6.0,12.0,7.0,7.0,10.0,7.0,5.0,CCBGGGGFABECFADHEACFCFGFGEDFCFAFBHBCBHBDCCHCAAAAAEDDDDAFCFCEGEAEH,False +689,1.0,5.0,2.0,2.0,0.0,1.0,2.0,2.0,DHDGFGCBBBBBCHA,True +690,15.0,19.0,20.0,21.0,26.0,23.0,15.0,18.0,GBGBGEFEGECEDHDHDHDHDCGAEACGCFBFECCACGCDEDFDHDFBBBEBDHGHDCBAAAFBHADFBFHFHFHFEDDADEDEFCBBAEEGEACCHCEGACEDECECFFFFHAHEGEBABEDFBHEDEAEADFDCHFHFCGEBHCFFFGBBECGBG,False +691,16.0,20.0,16.0,13.0,21.0,17.0,19.0,17.0,EEBEDECEAEBBBBEHFBFBFDCDCBCBCAFGHGCECGGDHAHCDCFCEHDHDBBFHFGEECBGBFHDHGHEBEBEAEFBAAAAEAGGGFEFCFBABDFGFDFHAEEGHHHGDFHFGCGCGDAAACADEGBBCAHGEGH,False +692,15.0,18.0,25.0,15.0,20.0,16.0,23.0,15.0,DCAGACABGEGHGBBCAEGHHDAAAFGCBCBCGGDGCGCHCDCDAFCFGHGCGCEEEHBGGECACADEDFDFGFDBBFBCDCFCDCEEHEHFDBDBGEGFFBFBFEECHGHBAGABABEHEHGCEHBFDCCGDHEHEGBFAFAECEC,False +693,18.0,15.0,17.0,18.0,19.0,18.0,17.0,13.0,DAEAFACADHDHCFCBBBDFDEGEGEFDGBEFEBGHGHEHGGAFAFAGAEDEBHDADAEAEDEAHGHAHCECEHFHBGFAEAFBCGFDFGCACADFCGCBCBDAHFBCDEBCFCFGECDBDBGBGECECFDDHFG,False +694,7.0,11.0,9.0,10.0,9.0,4.0,5.0,10.0,CDDDBBCGFGDHDHEHBHEHEBEBEAEAFHDEGEDHBAAFHCBFEGCBCBCBAAHACCCGBHDDD,False +695,9.0,7.0,7.0,14.0,15.0,8.0,16.0,16.0,DFDCDCDEAHDDDBHHFHFCDCHCFBAEEDGAEAGGFGHAEECHGHGHEEGDGFEFEDEGBGEDDBHBHGEGFAHAEAHAHGBGHGHGDECB,False +696,24.0,23.0,24.0,22.0,20.0,19.0,26.0,26.0,ADGDAEBHCGCHCEADABGBGBFEEGFAFAFBFGDGDHHACDCHFACHCGGHGHDHCBGDHBACHBHGHGAAEBFAHGGDGHGFGDCDCGCDCAEGGGEEEEEHDFDAAAHADAFADEBBBHEHECACBEEEBABFCFCFCECFCHBHBAGABHHFHBHFCDEBCDGDFDFDCBFBCBEAGDGH,False +697,19.0,24.0,22.0,23.0,29.0,24.0,25.0,34.0,FCFEAEAHCGEDABFEFDHCHCGCGCFHABDGEGFGFGBHBCAEEHGBCBCBCGHDHFHABGHDHCCCAADDFDHDCDHFBEHEHEGFBBHHHADEEEBEBFACHHHHGHGABBBBEDCBBBEDEDFFFFFFHCHDAEFEGDGHFBDGEHHGFBDADECEDEDGFBFEGCGHHCHCHGHEFEAAGAGEGDGCAHAEAEBD,False +698,13.0,19.0,14.0,18.0,18.0,16.0,11.0,16.0,BDBFFDFDFGGHAHBHBHBHFGAGAHDHBEBDBHBFBFHCBEGEGEDCCCCBGHECDCACDBFCEDBDFDFDHDFEFHFHEHEFEBABDEHBCDDHAAADEBAGAEACGEAEFBCEGEDFCCAGE,False +699,20.0,17.0,18.0,13.0,20.0,22.0,16.0,23.0,ADHHHHFDFBFAGADBEFFFEFEGCFBDHCAEABAEAEBHFECCFDFHHHHHFHCHCHEHEAEBGHACABFCFGAGDFDFCBHGCFCBCHDEDHGHAFDFAGECECEFAGCDEGEHEAABCBGBGBGBABGEAHGEAFHFGCECADBDB,False +700,7.0,10.0,13.0,7.0,8.0,14.0,8.0,3.0,FAAEFBFCFBFBEDGHCCCCCEDEDFHECDBDGFGFADGBEFCFCGAAAHEDECACFBFBGGGFCFCBBB,False +701,16.0,27.0,21.0,29.0,23.0,22.0,14.0,18.0,ABAEADACBDBFAFDCGBDEDBBFBFADHHAABHDGABACDBDEAFCHCECHDDACAFDFDFEAEDHDFBFBFCEEBECDCDHABFBGEGFHFHGBDEDEDEDCDHDHFAGDGHGHGHBCBCBFHCEBEHCCDCBFBFBECFDGGGFCECEDHBGBCFEEDGBFBEHEDE,False +702,22.0,31.0,14.0,20.0,15.0,20.0,18.0,12.0,GHADBDAFCHAEBDBDBDFDEAAABADEDCAABBEGEGFGEGFDFBFBAEGBBCBCBEGDCDAHCHBADADGFBFBHBGBDCFGDGHCDCFCBEAGFGFHFEBECAFBFBHBHBFBEGEGEBEDAHABADABBGBCAAGDFBAGHCCFDFHF,False +703,21.0,26.0,13.0,16.0,14.0,14.0,14.0,17.0,CHABCBFGFAABAGAHAHAHACBDFHAHEHGCACDBEHDGBHCECEHFAACABHBABABECGBGAGEFCGDEFHBBFAFHFHAHEBEFEGBGBEBEDDDDDDDAHHCBCDDGEADABGBDBFGFBFBFBGEDCBB,False +704,1.0,0.0,1.0,1.0,3.0,1.0,3.0,0.0,DEECEGFGAG,True +705,7.0,6.0,9.0,6.0,4.0,3.0,8.0,5.0,AGABCBCEHFACGFHHCHEACADDDDGBGBGBCEFHBDEDACGCGCGA,False +706,6.0,5.0,9.0,7.0,4.0,10.0,8.0,4.0,BGHGEDCHCHCGCFFGDGDGCBCBAADFFAFEFGAGADFHBAFCBCEDEFCFD,False +707,10.0,10.0,4.0,9.0,12.0,8.0,9.0,7.0,EECFAEAHAHAEAEBEHFDFDAGCDHBHGGEGEGFDFDEBADDCHFDDBFGEGBGBEBEAHAGBFBABC,False +708,11.0,14.0,22.0,17.0,26.0,26.0,22.0,25.0,ADBFFHCHCHCDGFCFBHBHBAGACHDFEFHCBGECDDGEHEHDHEGEGEGECBHAECDHDCDEEFHFDFDABHGDEHEGDHDGFCCCHCHDHDHBAEEGEHEHGGGBBFEFEDEFHFCFAEHECGCAFFFCFBBCAFBCHEEGEGFFECGCGFGFGFAFAGB,False +709,20.0,25.0,16.0,17.0,13.0,14.0,18.0,22.0,CDEHBHBHAHBHBGDGEGBACAHAHGBGBGBAAAGFDEEBGBABABFGACACHGHDFDADHEFDHHECFDACABGHFHDDDAEAEDGDCDCFCBCFHBCBEBEBEBFCGCHFEGGDDBBBCEHGDACABGHGAFHHHBFAFCFHB,False +710,30.0,23.0,16.0,22.0,21.0,35.0,15.0,23.0,FAFAFAFEFEHAHAEBEFDFDBDHFCEAHHHHBEFDADHEHBCCCADEHFHFHFCGGDECGCBDBGAFAFBCDAHADBECEFHCBCBAAAFAGBFADDFDFHBGAAEABFDEDFHAGAHAGAGEGHFEFCABAFCBEBEBHFDDDFDADEEEFBFDACEGFBDBHBHBFGFBFCFGGHAHAFGFC,False +711,6.0,6.0,12.0,7.0,12.0,9.0,12.0,10.0,HGEDHDGCGCGBHBHGCFAGABCBGGEBCHCHFGDEEEHEHAHFHCGDFEFAFAFDECECDCFABCGEGFCEDE,False +712,23.0,31.0,32.0,27.0,25.0,14.0,31.0,14.0,CGABCFCEHDFDHEHBDBDECCFBDGHGAGBGCHCBAEHEHDFDBDCEFGCGCFBAGGGEFEABFBGEAAAAHAGACACECACBGDGDBHBCFGHGBCAAAFBDDDDDDFGFCECBBEEGDADCBEAEAFDGEGCCBCBCBDGCECGCGCGCECECBFBDBABDBDHDCEHEBECGAABDBGGGDEEGEBBAHGGDH,False +713,4.0,5.0,5.0,9.0,4.0,5.0,6.0,6.0,BEFEACAHDHDHGHBDCHCDEDFDGDBEFGDGDFAFBBGACHCG,False +714,18.0,19.0,22.0,14.0,25.0,27.0,18.0,19.0,GEHFCECFCAEFBFAHBCCEBFFEFECDADEDEAEFEBECECGHGAAADAGHBFGFAFHDEABBDGDEHEFEFDBCHEGCCEFBFEHHHHGHGCAFAFHFHFGEHEHCGDFEAEAGFFBADAFFCFABGBABFBCBGBGCDCDHFHCECECDHDBGBCBCGG,False +715,17.0,8.0,11.0,12.0,13.0,12.0,12.0,14.0,BAGDHBHDHABAEGHFDADFECDCGCGADHDHDHABCBHGAAFBFBEHEAFCFAGHEBCDFDFDCHCHCADAEHEGEAEGCGCFEHAGGFAFEFEAEAG,False +716,16.0,17.0,24.0,24.0,21.0,17.0,16.0,24.0,FCBCBHBCBCECDCDAFFHHHCHDBEFABAEDEDEDECFDGGGAEFEFEHCADAFACEEECFCGAEDEDGHGDGAGFBHDHFHCCGEGBDHGEBHHHEHACAEGFDFDHCECBADECHHHBBBFBFBDADCCFCDCBCDEDHHCGDDAAAHBHGHGDGF,False +717,30.0,23.0,30.0,24.0,12.0,21.0,21.0,16.0,ECEDACAHEHCACECDCGCBHAGDFACBCBAFGFGBACCCCACFGEGFHHAHABGBEFFBFDFCGABCDCBBBBBAADADGDFDFHFDCDCHFBFAAGAGAGAGFCCCHABGDGDBDCDEBHDCDCDBGFFHHGBEAAHAHDFDEDAHAGDCDBHAFGGGBABDFCACACBCFEEAE,False +718,8.0,9.0,11.0,13.0,10.0,18.0,7.0,15.0,BHBGDHDHDEAEFFAGAGABHFFFADHDHDGAFCDCAHBDECFAHDHCCBGHFCECEHEFDBDCDGEGDBHBECFCFCFHBEFFFFFHFHE,False +719,12.0,23.0,32.0,23.0,25.0,25.0,24.0,32.0,ACHDECHBHFHGHGHDADAGHCCEBEBCCGHFFGFCBEGCCDDDBGFDHDHDHGFGBCFCGCDCDCDCFGEDBDBEGGCFEFEHEBEHECBFDCDGBGEGBGEGCFEEECGFGADCFEAEADBBCECEHEBEDFHFCFCAABGHHHHHFAFABCCHCFCAHEHFBFBFHCGFBDGDEBHBHCECGDBAFHHHHHDH,False +720,9.0,6.0,1.0,2.0,6.0,3.0,3.0,2.0,AAABABDBGEHAGABCBGFHEAEDEAEFEFBA,True +721,4.0,4.0,5.0,4.0,1.0,4.0,3.0,0.0,BGBCACGCDDFDFABACECBFAFDG,True +722,16.0,8.0,13.0,19.0,18.0,17.0,9.0,17.0,DFEFCHCGADHDEDAHEDEBFHFEFEAEDEDHAHADCBAFACAHEHDCGCGCDCDHDFECEBEDEDEFGGABFBFGCACFDFAFBDGFHCADHEHEGDAEAHHHBHFHFADCFEBGA,False +723,20.0,21.0,15.0,7.0,15.0,20.0,22.0,15.0,AFCDCFCFGFGAGBCACBHAAFGFBBEEAEGHDEDBHBHEHBCGEGFACEGHGHGCGEGECAFFGEGEGEGBBFAFDCBCFCFADADBHEAEHGBGHGBAFAHCBADFBHBCBFAFHBABABAFABHFGFGEHCG,False +724,22.0,23.0,14.0,13.0,20.0,26.0,11.0,21.0,DEBABADADEGBGBEBHBCCAAEAFFDAAAAFEFAFGFCFCBHBCFFFCFBFDFEHHDHCHCFDEDHBHBGAACEFAHHFABAEEEEGBCHCECACGDHAFDFHFHFEFHAGGGFCHBBDBHBEBFBFHHEHBBBABEEFGFEDGDAHAE,False +725,21.0,25.0,25.0,29.0,21.0,32.0,25.0,20.0,FGGGCGEGDFAHHHCCCGAEABFBEBDBDHDCDEDAFGDGAEFCFCEAEADABCBGGGGGCDCDCFFFEHACBCBCGCFCFDBDFCFAHBDDFDFBEHEADCDFHEHFFEGGDGFHEGEBBBDHEAEAGAGAHBHAAGAHAHDDCBCFFFHFEDGDHDBFBEAHBFBEDFCHGFGDCFEGCHCFBFDEDFDABBFBCB,False +726,16.0,20.0,16.0,17.0,10.0,18.0,13.0,17.0,BBBBGCACACBFBABFBCDHGBCHCBADABFCFCFGAHEGBGEEEFDGDFAGAGCBCEFHFHGHFHAHFDFCHAHAGEBDBDGDCDCHFHBDDADCBFADEEEHHDGFGFHADEDHFHCBCBABADF,False +727,10.0,29.0,22.0,26.0,22.0,17.0,21.0,19.0,BCBCBCBDAFHFCECDCDCBHECFCGAGDGBHFDGDGBGBEDEDEDBCBAFAGHBHDHAADBDCGFGHDBDEGEFBBBCBEBEHECDHEGDADCDHDBBGCEHFGCAEAEBEBFBHADCECFCFEDGHGHBHFHGHBCFGBCEFDHGBGFGEBEHEFFDDBDECGD,False +728,11.0,13.0,13.0,11.0,13.0,20.0,15.0,18.0,EFFFEBCDCHCAAAADFHFHGAFDFHFCFBEBGCGAFBCACAHAHEDBBGEDEDCDGBGFGFGCHCFFDHEBBCGGGGGDFHAHDHBFFCHHDHEHEFBHBHECAGEGEFEFBH,False +729,26.0,25.0,13.0,24.0,26.0,16.0,21.0,19.0,DBDFABGGFGHEHAAAAABFBFBGBDBABAGEGCGFEEGEBEDHAEDCHABCDEFAFAGDHHAHADAFAFGBGAGHBDGCHHHBFFEAEDBDBEHDBBEDDHDHDCBCBEHCACDHFCGAGEGDDBEBEBEAGAEADABAFFFFEHGCGCEEEEBEGDHDGECEABHDCD,False +730,16.0,17.0,13.0,13.0,6.0,15.0,8.0,16.0,CCHDADACCDBABEBHDFBEAGBGFCECHBAAEAEDEGCHCHAFBHGHDBDADAFBDBGBHCHCAGAGHHCDCFFDFBFBADFBFBFHAAADBFCFGFBFHHHH,False +731,16.0,23.0,24.0,23.0,24.0,17.0,32.0,25.0,FFFFFFFDDEDGGHGHGHGFDHBCACGEGEBEBECFFBFBDECCDEHCFGEACHDHDHCFDHEGABHEGBGEAEHBAGCGHGHEEEDEDHFCGDGBAHAGAGDGBACCEAGAGAGAHFBCHCGCDCHCHBDBGBEBGCDFDBCBHEHEHGCGHBCBCGCAADDDGHGBDEDEGBBDFEAEGBCH,False +732,2.0,3.0,2.0,0.0,1.0,3.0,2.0,1.0,FCFGFHCBGBAEAB,True +733,6.0,2.0,3.0,2.0,1.0,4.0,1.0,4.0,BFFCHCHCHAAFADBGFDAHAEA,True +734,5.0,4.0,6.0,8.0,4.0,8.0,3.0,7.0,DGHGDEDEFAFBFBDDEAADFDHCHFAFBDGHHHHCCCCFCFBEA,False +735,11.0,7.0,8.0,6.0,4.0,4.0,8.0,5.0,CHCACAGAEDFDCBHDHFHBCDDHAFGGGCACAGAGBBBGBEBDFAAGAECEA,False +736,20.0,16.0,16.0,26.0,10.0,23.0,15.0,12.0,BDBHCCEBDBACHCDFGFCADHDFDHAECDAGAGCFEFCFEDDDDDDDCFHHADFDABEGGGAGAGADABAFCFAFDBEBEGACADDDHAHBECHDGBGBDDEGEGDBFCFHBADGHGHFFFBFAFAFCFCFBFCFBA,False +737,23.0,11.0,24.0,14.0,10.0,9.0,22.0,11.0,FHADCDEAAAABDBHAFADADFCGGGHGAEAHCGDDCDCDHAHCGGGGCACFCBCBCGCHAAFAHEBADAECGCGCGDGECEDGBFCDBAGACFHAEGCGEGBGCECHGGFHFABABABCCDCE,True +738,26.0,23.0,28.0,29.0,22.0,16.0,18.0,26.0,EHDFFHFHEAFFBBEHDBBBDBDCGEGEGCBCDGHAHDEDEDFAFGCCCACBDAGAEFHFHADAFHCDCDBDHAAAAAHCHCHFHFEFHCHFBAEDHCBCBCBEBDADGDAHAGACACBHEDDDEHCHBDECCGBGBHDCDHDBGCCBGDGCHHGFBAEGEAFACACBCEEEEHEGCGAADAEBGDDD,False +739,8.0,2.0,10.0,6.0,9.0,6.0,10.0,6.0,CGBDCDCHHEEAEACAEEGFHFDDDDFGFEAHCCCCCBFGAGAGEFAGAGHCEGEGH,False +740,11.0,8.0,17.0,13.0,9.0,9.0,18.0,8.0,BGAGBECGDGHFHBHBGDGDGCCCCCCFCFDFAFHBDADGDGBBCACAFEDGDHCECHAEEEBDCGGAGFGCGDAAEDEACHEHCCFGAGDGF,False +741,4.0,2.0,8.0,8.0,5.0,1.0,3.0,4.0,CECEAEHCCADDHDHGGEBHBECFCDDDDCDAGAC,True +742,2.0,9.0,1.0,2.0,5.0,5.0,1.0,4.0,CBHEDBAFFDBABEBEBHFHBHBFBGEFE,True +743,18.0,19.0,21.0,21.0,22.0,11.0,26.0,21.0,EAACDDDHDGEGBHHHHEBEBABHEHBFGCGDGEGCDCDGGCGHFFDFBBGACADADHHADCDGDGBCCCBEDECAGHGHBFCFEDEDEGGCBEFEBEBEHADBHBGGGADADFGFDAEAGBBHGDBHGHCHCACACAEFEGHCECEAFHCHBGEGECA,False +744,31.0,23.0,20.0,24.0,21.0,22.0,28.0,21.0,DADEBEBEDADABCBFGGGGGHGHAFFGBGBGCGDGFGHBCCFDEHEADABAGGBGFCFCAGAHHEDBHBHFFEHAGAGBCDFAEBHDDDDEHHACFBHDGDGACFFBDBAAADAHAHCHCEGAHAGEEEEEBHFFGADABABEBEBCDCBHFHFAADFCGCGBAADDDFCCCHFEFECEAGACAGDGFE,False +745,5.0,11.0,15.0,7.0,10.0,9.0,7.0,16.0,EFHFBCACFCEHBCBABABCECFHHHHFEFHCHCFCBHHGGEGEDDDHAFGEGCBDDDHEEAFBBCHCHEHGHBCBCDCG,False +746,1.0,0.0,6.0,5.0,2.0,2.0,2.0,0.0,GDCDCACECEDFDGCCFD,True +747,14.0,8.0,8.0,12.0,14.0,15.0,12.0,12.0,HCHDFEEGCBCDCAEEEBEFEFCABABFBFDEGFAHEHAHCHGGFCFDEDAHCHDFDGDGABHEAAFAFHFEEGAGDDFBHBHGDGEGAGAFAFD,False +748,23.0,22.0,15.0,27.0,27.0,24.0,31.0,19.0,CFEFAHGBGDEAEBEAEBHBDDGBFAHCGFHFHGEGFAFADBEFHBEBCCFCGEGADBBGGCGBGHHBEGEGABBEEEAHAGEGFGAGFCCBFAGBGFGFGFADDBDBGBFEFGFAAAABHCDDDDDDFDFHFHBGDEAEDDDEDEGEDEDECHDHCFAGAHAEAGADFGHEHDHCCGEGEDBDFCHC,False +749,18.0,23.0,17.0,19.0,17.0,23.0,21.0,21.0,EAADEDBDBFBEECFCDEGFDFHBDAFFBCCCGCHCHAFAFAGGHGECECEBEGAGDGDHEFEHCBAADAFBFBHBABGBGCFCDHFBDEDECFGFBCHHDBBCHDGDFFBFBGDGBHHAHABADADEEGHGHBHFFFFEFGCGCDEHHGHGAAAGBBH,False +750,26.0,15.0,24.0,31.0,22.0,18.0,27.0,36.0,HFCEEEDBCEHFDCDCDGDAHEDGBCCDCGHDEECFHFAFADHFCGEEAEHEHECGABAHFBFBFDACBDBDCDHDHGFBFACAHAHABAHHHCDGHGHGHAABFHFGGHADDDDDADCDEDGDEAGGGGAGBGACCHBHBFDDEEHEDDHCHCHCHGFGAHHHBHFGCGHEEDEDFBAGHGHCECGCAHAGFEADAGA,False +751,2.0,2.0,6.0,6.0,5.0,4.0,2.0,6.0,DCHAHGHCHCEBEGDFCHCDCFEFEDEFHADBD,True +752,12.0,16.0,4.0,9.0,13.0,13.0,11.0,4.0,EBEBDBDBFAHAHADAGBCBFHEEAFAEEBEFGFEFAAAGGGBAFCFCFDGEBBBBBBGAFEEDDDGAGFGCEFEGBDDFHB,False +753,20.0,22.0,13.0,25.0,23.0,25.0,27.0,11.0,DBDAFFDEDEDEFEFDBCFFHDDEEEBEFDFEFEGBGCHCEBEHEHAABAGGGDEAFDFBGGGDFAFAFACHEEBHACBFECCGGGGGGFDFAFCGEGEFHBDBACAHAEFDBDFGABFBEGCGCDHDHDGDBDBDGCFBGCAHGDGBBFAFABEGEGABADADGB,False +754,13.0,24.0,24.0,21.0,25.0,16.0,20.0,11.0,BHBDGCGFGFGFGHGHBFGCEEFEFBAHEHEHEBCDEDEDBBCBCEFECGCDBACAGDGDBBHCCGDAAEAHCEFECABABDGDGCBEDHGFEDEDBGGCACDDBEBCBDFGGGEEHECECEFDFDBBBDCHAFDCBCBCGCFFACAEAEDBFE,False +755,21.0,23.0,12.0,20.0,22.0,23.0,13.0,24.0,FBFBCBFBFECEBHBHDHBBBFBACGBGBDAGFDACHHGCGHFDBHEEEFEAEBEBFGAGAGEDDFDFEFBCAFDFEAEAEDFDBDHECDCFCEAHAFEEHAHGHGHCBDAEGHBDDDBDEHGBAHAFCHGBFHFHEHEADHFHFHFDEBCAAAAHAD,False +756,9.0,16.0,8.0,17.0,8.0,7.0,7.0,4.0,EFEFGFGCCBABHBDDDDGDABBGBFBFEACDBDEDHCGEGBCBCBFDDDEAFABADAHEBADHDCCEDGDBBBAD,False +757,15.0,20.0,18.0,27.0,18.0,16.0,16.0,19.0,GHFBGBCEEAHDBDAHAHEBFFDDDDBFBEEAGBDHDBEGHAHADDEDCFCFBHAHBHDDGDGDECECGHGFGDADEFCFCFDADBGEEBCDEDGABABHBHBHCDCECECEGACCEABFBFBCCHABGHFHFACDDDDDGHECGFGFH,False +758,24.0,10.0,20.0,10.0,13.0,18.0,25.0,18.0,HEHAHAFAHCGCGCHEBGCGHGHGFGCGEABGHGFGHCHEAACABAHACFEAGCECBGGGGGACDFHFAFDFDFDFBEEAEAECFCAADAGFCHHECFHGAGHGEAHFGCCDBDBGACAGADABBDBDCFAFHGEFCF,False +759,5.0,2.0,3.0,3.0,1.0,2.0,7.0,3.0,CFAGGHGHGHBDGDGACEDACAGABF,True +760,23.0,15.0,19.0,10.0,31.0,25.0,21.0,16.0,FGFGHGDGBHACAFAFEFEGEBFGFGFECEDBFEFEHHCFAEACFBBBAFEDCGCEAECFCBBHEGEDEAEFBFGFGADCCCBHAAEEBABAHAHACECFHFEDEABFEDEAEBECACECGFGFEAGAFEFACHGDGAEAEGHHHHGDCBEDEHFHGGCG,False +761,4.0,5.0,6.0,6.0,5.0,5.0,6.0,6.0,EFBFBFGDHCHFEFGGBDAGACHCHDHBAAECCBCDEDEDGHG,False +762,5.0,7.0,14.0,5.0,9.0,9.0,6.0,9.0,EGEFHBHFGFHCEDEBEFACAEAECHCHCHCHBGCFDFCCACBCDHDFGABHBCECDGGEFCFB,False +763,7.0,10.0,9.0,14.0,6.0,13.0,15.0,4.0,FHBHAHAFAEDCDEAEHFDDGFBFBFDGGFGBGBCBFDGDBCGEGECAGAGDGDFDCDCDFGCGEBDGFBACFBFDCG,False +764,18.0,17.0,21.0,10.0,17.0,19.0,30.0,14.0,GFCBGAFBBEFFCGHGEADAHFHEAEAHAHFGGGEGECCFAGAGFFCACBFAFAFGGGAEHGHFHBHCACHFAFDEDHGEGDFBCGCAHGCEBEHCBGBDDCAGBDAGECECACBCBCGGGBBBBBECFCFEFHGDGDGDGEGEGC,False +765,16.0,9.0,24.0,14.0,21.0,12.0,17.0,12.0,FCCCCEGDGDFBEGCBCDDDDCHFGACDHECCCEEAHGHGCCCFEAAADAHGEBEFDDDCDCEAGCGDHEAEAGADAGEFCFCFGFGEAFHEECECEGHGBFCECEBFBCAEBGBGHAHAHAHBE,False +766,2.0,5.0,3.0,5.0,5.0,3.0,5.0,14.0,GCCBCDHEEEFHHEBEHGHBHDHDHAHFGAHDGDGHHHHBFB,True +767,25.0,19.0,25.0,19.0,30.0,21.0,34.0,24.0,AABAGCCCGCDFDAEECGCHBHGHGHDAGCGDFDCEGEBAGFEEEHHAGAGAGFECEHGCECEHFHABEEEBEFEBEFEBCGGGDGABEDEDADGFGFCHHHHDDFBFBAEAEAHGFCFAAAAABAFHECGCDCGFADDBHBGCEHFBBGDHFAFHBHCHFHAGGGGGGAGCGEDEBEDECHFHGBDEDBFGCCCCE,False +768,25.0,18.0,18.0,14.0,17.0,14.0,28.0,21.0,DBBECABABAFFCHGBFEAEHGGEEEHGHGAGADAHGCCFDFDGAFCECECDBBBFBDHHGHEHBHAHGCGFGHHCCFAEAECGAGFHHCEGGGCDCEHEHEDGDHDAGABACCBCBGFFBBHBABADAGGGGHGAGAGAECFBAGAFADAEHDD,False +769,1.0,3.0,1.0,7.0,6.0,6.0,6.0,3.0,EFGFHFCEBGHFBDEDEHEAFDDGDGDGDGBEF,True +770,10.0,20.0,19.0,21.0,15.0,21.0,16.0,16.0,CDHDGGGCGEGECDCDCDABFBDBFBFDFHFHDDBEAEHBGBGCDBGBCHHDGFGCHDHCGCAAHABAFHHBDEFEFCFDFCFCFAHEFBFBGHGDDDCBEGGFEBEAEBDBHCHAEFCDCBFEFEBHCGCBFDFDEA,False +771,4.0,6.0,5.0,4.0,2.0,2.0,2.0,5.0,DBACDGDBBHBHCFDECECACAHAHGBFBH,False +772,20.0,21.0,27.0,26.0,23.0,24.0,13.0,18.0,HHGDAACADHDEDCABDHDFCFDBCFCABDCCCCFFFDFBCBHBGEGHGADACFDGAADDDDDECEHEHDFEBEFCFHFAFCFCFAFCHHHCEBEBEGECECFCHEFDCGBAFADAEAEDEDEFEHEGDAAEBCAEABBFBFBEADGCHDBGBDCDFGGBCBCBEHGHCHBF,False +773,23.0,11.0,12.0,12.0,15.0,10.0,15.0,14.0,HHBEBEDEBGBDFCECGCGEGCHDHGHGBCHAGAGAFAFAHAEEEAEAGBGEGCGAACABBHDABFDFAHADGHFBCDDHAAEAEAEAEACDFDEAAAHFDCCGCHHGDBFF,False +774,17.0,24.0,28.0,15.0,15.0,16.0,18.0,18.0,EFEFEBGCDADCEHBHBHBFBECECBFBFCGCEDEDCCFCGCGFGFACCDFHAHGHBHCHEHECCCGGFCHCADBBBGHHEGCCCGCBHGEGBBBAADCDCDCDADADABFHFAGBDBAHGBBABFEFGBEAHBGCCHFHGDABACAFDEA,False +775,3.0,0.0,2.0,1.0,0.0,2.0,2.0,3.0,AGHGHFDFCHCAA,True +776,17.0,9.0,11.0,6.0,12.0,12.0,17.0,14.0,GCGDABAFGFGCCECFABAEAEBGADHHEHAAAEDEAEABDFCGBADAEHGHFFFGAGFCFDBHBFGHHCGAGHGEGHBHCECEAEAGFCFCBHGHGH,False +777,4.0,6.0,1.0,5.0,7.0,2.0,6.0,4.0,HEFEAEAEDBBGDCDHDFEBAAHEHEDGBBBGGGG,True +778,6.0,7.0,4.0,4.0,5.0,13.0,4.0,5.0,HEHEAFGFAFAFBGBAFFFDEDECBCFGDBEHFAFBFDFHFHGBACCB,False +779,9.0,7.0,5.0,6.0,9.0,8.0,7.0,9.0,DGBEBEDHAFAFHFHFCFCEDEGEDEDGHAFBHBAGAFBCBHFAGADAECCBGEGHHEHA,False +780,19.0,21.0,16.0,16.0,23.0,19.0,26.0,22.0,FFCAGEGEGAHBBEBEGCDFEFCFGHHDHDHDBEFFAGEGAGAGAHEHFAEDBACCCEDGBEACFCFEDEABABABFHFBGBGAGEHHACBCGCHCHGHEABACDBDHEGFGEADHFBDCDCEBBAGHGHEHEHGHDHDGDGFHABECEBDGGFGBGBEFFF,False +781,15.0,24.0,23.0,18.0,23.0,14.0,17.0,21.0,FEAGCCBABABAFAHCDGHFCAEGBGBGHHBBCBFBABAEDEDADHFECGDGAHEBEBECCGCHCHEBCFEDDDCGCGDGDHEFGGCHCBEFECAHDEDFDEHEGEFBBHGGCECECFBDBDBAHAHEHDHECFBFDCECABABHBGBCHFHDHE,False +782,14.0,24.0,23.0,18.0,18.0,17.0,19.0,17.0,GAECGCBBAGAGAGFEEDDFBEEEBBGGEECCCCBEGEGFGDGCHCHCHEADBDBHBHFGADBFGDHHGAGADDDDDCBCDHFBFHDAGFHFHFHCBCFEHHHBFCFHFCGCBCAGFEBDFCECHCACBDBCEAGDBDBEBEBEBABAFC,False +783,17.0,21.0,14.0,26.0,20.0,11.0,14.0,15.0,CHAHEHDHGCCADABAEDBDBFAEABGDDCGADADBBAFCEGDBEBDHGEGFHEHEHEFCFDGHADADBDBDCDCGBABDECEDEDFDCDCDADEDBDHGBGBECDHEHFFBAEAEBEBGHGEBCGGBEFHBHCFAFA,False +784,9.0,13.0,21.0,19.0,11.0,19.0,13.0,15.0,ADHDFGEBBCCDCDCFHAGDBCBCECEAGAHCDEAHBHEFEAHHGDCHCHDHDHFBEADFCGCHDHAFBGBGBEFDFGFECACFEFGFDCDEBGBGCFBFCDGDGCFDFHFHFCFCDCDB,False +785,3.0,4.0,10.0,4.0,5.0,8.0,5.0,7.0,FCFCGCGEAAGFCECECHFFDHCACGCGEBHFEFHBHDFDBDBHHC,False +786,13.0,15.0,20.0,21.0,12.0,14.0,14.0,18.0,BFDGDGDADECHCHCEDGDBDGHCHDGCABEEFEFGGDDBDHDHDGCCEBDFDFBHBHBHFHFAECEBAAAFAEAHBHGHDFEFBHBABECCCCCDEGHGBFFGHCDCBGDCCCFHDCACAFGHADA,False +787,12.0,21.0,22.0,19.0,22.0,24.0,29.0,14.0,CGCGEECEGGBEAGCFFFCDCEEACFBFBGBGDGDHDHCBCGADEHGHBFGFGFDFDBGEGEBFCFCFCFABDBCAFFGDGBFHCHEECDFDFCBEBFHGCGEGAGAFDFCEGEGEAAHHHBGCGCGAGDGDBDFGEDBDFDBCHADEEGEHEHABBFEHBCB,False +788,17.0,13.0,19.0,20.0,16.0,16.0,19.0,15.0,BDCEGHGDAFFHFHDADAHEEEECFCGDHBHGGGAGAEFGBCADGCCCCCCGCDCBEFEFDFECADABAFEBGBGAADGEGHADABHFHFCEDHDGGCDCDFDADGHCFBBCBCEHBHFHDEDEDEGHGAAAFBF,False +789,28.0,17.0,13.0,32.0,28.0,13.0,27.0,17.0,AEADADBGBAFAEADGBAAGDDEGEBEFCFCFHFHAEGEHDHAADEDHDCFCBAEGEGDGCGAGBGBGBFDDDEDGBGBGBDDGGADCDBGAEAGDBCADEDHBABAECHCECAFEHAFACDCDGEHEHFBEHDDDDFEAABDHGHGHDAGECEGEGDHEAEGEGEAFHDHDFAE,False +790,20.0,14.0,14.0,14.0,17.0,15.0,16.0,18.0,FCFDDDHCHCEGHADCBGFEFCFEEEEBEADABHBDEFCABABAGAGEHHBHBDAECGDEAAAFAEADBHCGGBGBGBEFEFEFABAGFHHGACDBDHHGFDACEHDHGHFCFDHCHCHCEFAGAGAG,False +791,18.0,17.0,18.0,19.0,20.0,20.0,6.0,18.0,FHFHFDEAADAFBBACGHDCDFAGGFEFADEDBFBFECEAFAFACCCEFHBHFHBBACHFDGDCDHDHGBAHCDCBHBEEEEAECBABCBCEDHDFDEDEDEAEADACAHFHFHEDCCABEHEBEHCFBFGFBDHC,False +792,14.0,17.0,13.0,12.0,11.0,16.0,16.0,11.0,DDBDBDAFBDBFAFAGBDEGCCECHCHCGFABGBCFEFECHFBABAEECBDHDGDGHGHGFCFHEAEGDHBCBEFHBGAGACAHAFGFGFDEABFBABGFGFGBHCAEDC,False +793,9.0,19.0,17.0,11.0,13.0,16.0,16.0,13.0,DCGHBFFCGEEBEGGAGFDEEBFGHCHCDFDBCBCFCFCGCGBBBCBCBFHFGCAEABHBABGBDBDFDHAHFGFHBBBGHGHECFDECEGHGHDAAGDBCECDAEAEFEFCFH,False +794,18.0,14.0,23.0,18.0,18.0,15.0,28.0,20.0,GBGBGFGAEFECEBGBECECFGDEDGFCFGGHCHCFGDAHHCHCFCFCGCGCEAHAEABACDBDBAGGCGHAHBDFDHEHEGAGEGEHHDCDGFHBHGHFADECACAEABFCAHGHGBDCDFDFBAGACDGGCDBGGADHDBFHEHEAEGDCEC,False +795,2.0,6.0,5.0,6.0,3.0,1.0,4.0,1.0,GDGECBCHDEDECBBFBCBABDGDGACD,True +796,20.0,15.0,22.0,19.0,22.0,17.0,35.0,28.0,EHGHCDCDAEBCBFBACHCGEFEFEFDFHGHDCGAHDCGCDCACBGEEHEHGGGEHEFEGGAAAAHAFFECCAGHGHGHBACACDCFEAGGGGGGGCGAFCBEHHGDGHGADAHGHBDGAGBCDCABAHDDEEFGGEHHHBBBDBDHDHDHFHEHBCDCGFGECEFFGFGEGHFBEDA,False +797,22.0,14.0,14.0,13.0,13.0,14.0,15.0,9.0,HCHGGBDEFAFAGAHDCGCGCHCGFAADEDEABAGABFEFEFEBDFGABHFDAABCHCFCADBBAGDGDGDCDFEFGBDBDFFGCBCBEBGAAAAAAHEHEBEGCAAAFHECEC,False +798,15.0,14.0,14.0,26.0,14.0,22.0,16.0,23.0,DCGAADDDHDHFFDBGGFGEGBBDHAHFFFFAFCFBDDFEAEDHDHGHGDCHCFAGBDFCFEFGAGHECFCEDAHAGEBFBABDEDADCDHAFCFAFHBDFAFADEGEHEHBHGFGCGHGCDCDBBHHHHBCBCHDEDEDEDHH,False +799,27.0,20.0,19.0,24.0,17.0,17.0,26.0,21.0,GFGDGDCDFGBGBEBGBHHFDADAHEHEBBBHFFGGCADACAGHBHAAFACACHBECEFAHADGDAEHECFABCGCAHBHAHDGEEHFDFHFDFCAHDBDBFEGDGDGHBDBGAGEGBGCCECEBEHAGABADADADECGCGCAFHGHBFACACFDEDEBGACAGHGFDDD,False +800,14.0,22.0,27.0,22.0,29.0,27.0,20.0,20.0,BCBCBCACACAHDBFCHEHEFBGGCGCABBHBEEEBECECBDHDEBAACGCGFGFDFGBCDAHHHHFFEDDDDEFFHFDEGGGHEAEDEGBBDFEADFCGCGCHFHGHGEDCHFFFDFDCHFBCBCBCEEEGACAEHEFGFDFCFBAEHECGDEFGHGAFAEBBBBDCEHFCFEFDCDEDE,False +801,5.0,1.0,4.0,0.0,2.0,1.0,0.0,1.0,HCAEACAFBEACAC,True +802,15.0,14.0,17.0,11.0,11.0,11.0,14.0,5.0,DGAEAFAFCFDADEFEFCACGEHEFGCHABACABHBADDFDFCGEGEAAACHCGDGCGBEBFDCABBBBDBABFGGCCCEGFBBBEDAHCGCGCGCED,False +803,19.0,24.0,22.0,27.0,21.0,24.0,25.0,26.0,HFAFEFEFCCCHCHGDDHEHEDEACCFAFBHDEDEBGCGBFAHAHAHFGDBAGAHBHFEFBFEFABCDHDGACACBGDGHAFBDBCFHFHDHDGDADBCFGGBDACGHGCECEGGAGDGDGEGECADHDABGBDDCECEHFHBGGEGEHBFBDHFACAFBBBBHEEEGCDHGFDFDFEFHDHDCBBBC,False +804,14.0,12.0,12.0,16.0,9.0,14.0,9.0,8.0,ABCBAFDEDFDHDCDBAFCBGBDBEAEGEBCDGAACABDECECEHEAGHGDBHFFFCGDADFFFGFDBDFAHCHCHCHCBADADADABFFGGEF,False +805,10.0,5.0,7.0,4.0,17.0,8.0,9.0,3.0,AAGAGAGAGAHECEFEGEHEBEAEFDADFEEEECEDECHGFEFAFBEDFGBEACBCEFBCCGG,True +806,16.0,25.0,13.0,17.0,23.0,16.0,21.0,18.0,CBGEEFEGBBBCHGHBAAAAGAGEGCHCEDBBBBBHHHHDAFFEEDEDAAADFEBHGHDHEGEGHCECEBBDADGGGGGDGHEHEHEBBBFGFAFDFEFEBEBCFFEBHBECDBDFAFAGHDFDGBHDCFCAABCBHEGDGDEBGCCAF,False +807,3.0,8.0,5.0,8.0,9.0,8.0,9.0,9.0,HFFFBHCHEBEBEBGBDCGCECEFDFBFGAGHHDHFACHDHDEFBGDGEHEADGDBEGG,False +808,18.0,19.0,24.0,19.0,15.0,25.0,23.0,17.0,CDGFCFCAGHEAEADCGEGACBGFGDHEEECACECECFAHAFDCDHDFEBEHDFDFHFGBEBGGGBBBHBHFAEAFGFAHAGAFCGCHCHGHBCDDFDFDGDFBEBEBFAFCFGDCCHGHADCBFBGBGHFCGDGBCAHFDFCFCBCBDAEABADGFGHC,False +809,24.0,16.0,20.0,18.0,20.0,16.0,26.0,18.0,HBEFGCGHAHADGCACAFBFAFCEBGBFDGAGAEHHCDDHDFDHDHDEECGABCBFEAEHDGGGGBABGFEBCAEGBCFCHGHBHBABGBHFEFCCCCAHGEGEFHFDGAEBHDADCGHEAEAEAEAEGEDCDADGDGAGAGAEHDGCCFCFCADBGF,False +810,7.0,10.0,7.0,14.0,17.0,13.0,14.0,8.0,DEAEGEFECACABGEGEAHGHGHAEFEFECHDDFDBDBCBDBDFGCGEBECEDDDADBEFEBDFGBDFHGCFFDGGFEHEHFHBGAGEGF,False +811,11.0,12.0,11.0,18.0,16.0,11.0,15.0,16.0,EBEBABDHDHDHEHGHFAAGGCAFEDDGEFAFHDBDBDHEGGGGBCBCFDDDDDEDBHFEBHCHABEFEFGHECECBFGGGEDHCHCGEGACAEAECHABCHDADFDFHG,False +812,7.0,8.0,5.0,1.0,6.0,6.0,5.0,5.0,HHHHAEACACBEBCCAFAGEFCFDBHBFBFEGAGEGBGFABBE,False +813,7.0,6.0,14.0,17.0,20.0,8.0,11.0,16.0,BCHCAFAGAHCEFEDEHEDCHGHAEDGDFCFHGHGHAEGEGFHBBDFEHEDEDHDEDEBGDDFBEHGABCEDECCCADGHEHEHCHCDCDCDCEEGEFD,True +814,27.0,14.0,15.0,25.0,17.0,16.0,12.0,25.0,HFFCACAHFFCBCFFGDDECEFEHCBCBCDAAAGAHAHDECEFHAHAHDEABBEBCFGBGDEAEAEADGHAHACDHHHBCBEDFFAFHFEEGAAAAAHAHEHEDDDDGAGDHDBDFFAHDBACACAGHHDGBGBEDDBDHFHECGDDDHDH,False +815,9.0,8.0,11.0,6.0,5.0,16.0,9.0,7.0,DDGCCHAAADDFEFBHDFFFDFCFCFCFEBEGGGCFCGHGHEAAAFFHBCBGBEBCBFFFCFCAAGAHHGB,False +816,27.0,23.0,14.0,24.0,26.0,27.0,25.0,22.0,DABHHHEHAHAEFDBAGABDBGHDAAGAGFBAHAHEEDABFGGEEADAFBCACGCGCEFEBEBDFDCDGDEFEHEHFAGAGCBCGCBCBEDAGGBABHDFBFBDEHEHGBFEFEBDFHFHFDEECAFGFGFEADHDAGAGADCDCHFHCEADFDGEAFBFCFDBEEDGAGBEFEHDHGAGHGHFBFBF,False +817,1.0,1.0,2.0,2.0,3.0,7.0,3.0,4.0,FFFFADHDHEHEGCFBGECFHFG,True +818,10.0,14.0,17.0,5.0,12.0,5.0,16.0,9.0,CACBHAACABGDCAEAFGBEHEGCGCGEGEDBGAGFHBGCECEFEGEGBHBFGAGHEABDFDBCBCBHEHGHGBDCACBGBECCCCCH,True +819,20.0,12.0,13.0,11.0,16.0,13.0,21.0,6.0,ADCECACDCEGDFFAFBGBGBGBAAAEBEBGFDADEDAACACDCHHBGGGGGGGEGAAHFEFCGDGBCFABAFEGCDHFECEDEHABCDAHFGAGEGAGAEAGBFBCEFEFE,False +820,24.0,22.0,18.0,21.0,20.0,19.0,14.0,22.0,ECFBHAHAHAEAFBFGDGDCBCGAEAHABCBHFEDEDGBCDCDADABAEAEBHDGDHCBAHFDCDHHBHEGAAFAFCHCDDEHBFBFDGDGHBAFCEDEHFCEHEHEHGCGAHABCBEFHFGCDCDFBFBFAFGBDEDAGCHBEBCBADAGEBEAEAFFH,False +821,24.0,21.0,19.0,22.0,19.0,13.0,20.0,29.0,DAHAHAFEGCDEECECAAEHEFDDDGAGAGAGABHBGEHDHFHEHAHAHAFBHBHCAADCEBBGDECHGFGHGAGEDFDFDHHHCGAEABFDGBECECAHACFCHGFBDHGFDHBHDDDDGGHEHAHBGBGBHEABBFBDBFBDAEEBECCCCCACHCBCHAHDGDB,False +822,16.0,25.0,27.0,23.0,14.0,15.0,16.0,28.0,BHCHCDCAGFGAGBFHEHBABGDHBABFBGBDCHCHCHEHAHEHCHDBGBHACADADAFFHAADACBCBEGEFDFDFDFCHEHDDBDEGEDHHHCDEGHCFGFDEDBBGFGCGHAHBDCECHCABHFCCHCDEDCDCGBBEHDHBGBFEFCACHCBBABCBDGC,False +823,19.0,16.0,17.0,19.0,13.0,21.0,12.0,12.0,AAFGBDHDCDFDEHBBFHFCDCABBFDFGEGEBCHDDDBDGDACAGABEGECECECEFEHCHAGDDHCCDAEFFAFBFBGDAEHHBABAHADABGBFCFGDCDFHFHAGAFAFDFBACACFGFEFECBC,False +824,23.0,14.0,24.0,16.0,17.0,21.0,26.0,11.0,EEEECEBHDFDBDCFAABFDEEGGCGEGFHDGAGBCFCHCFAFAGAGFFBGAFAEABCGAEADADAHBBEHCHCBCBCDCECGHBHAFDEDEAAACACFFECEFFGACCDCFGGCGCGFDFHFGCGCGAEAGGHHFBFDADABBCGGGDGDG,False +825,16.0,23.0,19.0,19.0,25.0,21.0,19.0,16.0,BCECEGEHBGBGDACADFFBABGGEBEGCGAGDBCFCEADAEFEDDCHCDEDGBGCFHFGBEBEBEHCHCEBEDEBFBFEFHFHFGDEAEBGBEDDCBHDFGFCACAGAHBDBDBCCFCFAFDDDADHEEEFHAEAGBGCAHHHEHFGFBFGECHABF,False +826,8.0,5.0,4.0,4.0,6.0,3.0,1.0,4.0,CDGDCFEEEEABABADAHBFBHACAFHEAEAHCBD,False +827,24.0,26.0,18.0,19.0,16.0,34.0,27.0,29.0,CFAFCHHGFDHDBDBDCDCHEFBGBGBHBDADCGCGHGFDFBAHDDAFECBFFFHFAGECAHAEBEAAACGEGHGEABAFGCEAGFFHFGACBGHGAFHCHGHGBFAHGHBHBGBGAGCFBEDHBFBHEHEBFGECEADHFHFHFDABFEFHFEFBFBABDBDFDADGDGCAEAFCFCFCDAGGFGFBHHHHB,False +828,2.0,3.0,1.0,7.0,4.0,6.0,1.0,1.0,ADDDFDFEFEDEBFBEGFDADFHCB,True +829,18.0,8.0,19.0,22.0,14.0,21.0,12.0,12.0,EGEGCHAFEECHDBDBDCFAFEFDFEGEAFCFDADADCHFHEADAEHDHCCFCFDFHFDFDACACACEFDFDGBFBCGEGFGCGCAHADACEDDGCCACHBABDBHAHFFFDDHACBDEAEGGGFD,False +830,14.0,17.0,12.0,13.0,7.0,7.0,14.0,9.0,EGEBHBDCDGECBABADDGCABACFCEBDCCADADFGHGHGFGBGBGHGFDDCDAGABACHHDHDFDCBBGBAAFACEHAGAGBEBHBCBEBF,False +831,13.0,21.0,11.0,11.0,12.0,12.0,12.0,8.0,EAEDGBFBDBCHEBEBEBCHCHAFGGBCDDDCDCBADAFAFABADFCBCGEAEDBAFAEHEHADFHBBEHEFBFGEBHFGBCBCBFGGAGAGBGCGFBDB,False +832,14.0,20.0,21.0,16.0,26.0,24.0,30.0,17.0,BGGGEEEBFFFEFCDGGGGGCGABDFGHCAFFFDFEHDHAGAGAEBEBCBCAGBBDBFBFEEEDDFCCGCGEGBBDBHEDCFCHGFEEBGCFAEGEGECFCGCHEDDCBEDDDHHHCGBGEHEHGDDCGCGBGEGEBEHECGGAEABAFAHAFAFHFHCHCFFFHFBA,False +833,0.0,0.0,2.0,1.0,0.0,7.0,1.0,2.0,GFFCFHDHCFFFF,True +834,15.0,17.0,13.0,12.0,21.0,19.0,18.0,23.0,DEFBAGHEHEABHDFGFHFHCHDHECEHBHDGDGFFCGBFBEEHHCDEFECEDEBCBGEGEGACAGHGHAHDFCBHGFFFFDACEHEBFBHBHGAAEADGGADHHHHGHGFAFCFCGEDFFABABGECACABEBEBEB,False +835,9.0,17.0,15.0,12.0,13.0,15.0,12.0,18.0,AEAFDHGHGFDEDBFBABACCCFCHEHCFEDHFGFDHBHBHEFAACHEDECFCGCBCECEGHBHCABDBEGFDFDBDBEGEFFCCGHAHAHGHDFBBGBGDGHBHBCBFHE,False +836,24.0,27.0,17.0,31.0,24.0,22.0,21.0,23.0,DCGBEBCDEDADFBFEDADADBDCDCDEDFDGBGCGBHBHBHEHEDEDAGBGFDAHGHBCECADBDEDBFFAFAFAFEHHGCGFEFDDGDGFBFGEGEBAHAFDDHFABBBDADAHAGAFFFCGGEECHGAGAEECEBFBCBHHGEFDAAECFADHGHCHBBBBDEDHBBBEHHAHCHCAEFEHADGDC,False +837,8.0,2.0,11.0,12.0,11.0,8.0,3.0,11.0,BHCHEDEHFAFHDHCHFDCDFDFDAAHCFDDADHDECECACECAFEHEGDGEHEDEHFCBCGCAEA,True +838,12.0,19.0,12.0,11.0,20.0,17.0,13.0,16.0,DEFEFEHEFBFECEAEAGBGAFEBEDFGFGAHFHFCGBBBBBBHEFEBHBGBGHCHFBCDFHAACCHEHACDBFEGEDFBCBABHHCHEHACACEDDDDFDGHGHCAGFDFBEEEGEGBA,False +839,1.0,4.0,3.0,4.0,6.0,6.0,4.0,1.0,GBEECAGBFBFBEDCDFDFEEHEDGFGFC,True +840,5.0,4.0,4.0,1.0,6.0,4.0,2.0,2.0,GEBEFEHEAADACACFCFBBHCAGEBEF,True +841,15.0,12.0,13.0,8.0,18.0,15.0,11.0,15.0,FHFHFEAAHFEFCGEHEHCHCBCAEBBBCHAHAEGFGABHBEBEFCBCAHDHBEAFGBHAFEFBGCFEFCDADBDEDEDEGEFEFAACHDHAEACGEGHGCGAGFDC,False +842,17.0,27.0,15.0,15.0,25.0,21.0,18.0,18.0,DBEBDBEEGGGBGEHCACBCBABGEDEDGFAFCCBEDCGGFGBHAHDBBHBHECACEDBDHAAFAEBEDCDCHGBEDECHAFAFECECEFHGHGHBEBGBGBFFFFHFEFHFHEBEGEAEFFAFGBBBFHCHADFDFBABCGAEAGFHDADEBHBE,False +843,20.0,14.0,16.0,25.0,17.0,16.0,12.0,24.0,HBHEDGBFBCADADACHHDHDAEAHDDDDDHFFDHDGCGCBHEGABAHEDEABACDCEFGFHAGGBACGHAFFGDCAAGHDEGEGEDABACABHFDEEBEBDBDBDHDADAHCHBEFEDEDCFCFCHCHFHFHFHFCAEHHFCE,False +844,6.0,6.0,6.0,6.0,7.0,4.0,7.0,2.0,GCECFBDBDBEGHDEAEAFFECECACBGBDADGDGHFABGEGCA,False +845,14.0,10.0,13.0,17.0,13.0,16.0,16.0,22.0,DADFGHGHFHCBGAFEFCFCGDGDEDBABABECDCDBBGAFAGAHDDDDFDGDGDCEGGFHFHCHGAGDHHHFFCGCHHEFEAHHHFHGEGDAHECDCHHAHAEAEBCFHFBFCEHBBEEA,False +846,13.0,21.0,15.0,9.0,8.0,13.0,6.0,10.0,AGBCBCBDGCBFGHABCBCBEBABCGHEHBAFAFDFECDBBAAHBHBHCFCFDBABDCDFFCGHAHBHBEBEBCFCACDEHACEBFDFGFAFAED,False +847,8.0,14.0,10.0,15.0,9.0,10.0,9.0,7.0,DECFAHHBGBCEAACBCBADDEBHDHDEDFFFGEAEBGCGBGDGDFDADBDBDCFCGCBCHABFBDEDGDGBHBFFCFEAEH,False +848,10.0,5.0,6.0,10.0,12.0,17.0,10.0,11.0,DHDEDCDFDFAFAHCFGABAGFCFBGGGGAHCFDFAFEEEEBBABHFAFGFEEHDHECEHFHFEAHAHEDFDFHFDGGGEC,False +849,22.0,14.0,13.0,19.0,14.0,18.0,13.0,19.0,AACFCFBBHBGFDADADAHHCGFBCHHFHBHDGDCAHAHABDEDBDAHAGFGEBEBACHCDEGAFFDGBHFCFDDBABAEEDEGEFEAAGAGABADAHFGFCFAAGCFHEHFGFBFEEDEHEDCDCDCDHHH,False +850,12.0,11.0,24.0,25.0,18.0,37.0,27.0,36.0,GEGEAEAEDHDEDECECGGGEFEFEGCBFBFCFCDCHEHDDGEGFGDHFGEGAGCGFDHCHFHDGCCHEBBDACHCFCHGHCHCHGDFFFFDFHGHDFFFGFGHHHGCDFBFCHHFHDDBACHEEFDCAHDHBHFFFHHCHBHFHDGFGFGBEAHFHFHFCAGGDCBGDGDFFAACDCAFDFDFBHHAHE,False +851,8.0,20.0,9.0,10.0,16.0,10.0,11.0,18.0,GAGAGFFHFHCHGHEFEGADABHBHBFEEEBAHCHCEEHEDCAGGBBDBFGFHFHAHFHBABEHEBFBCHEBBBDDDCDBECEGDBCBEBEBHBGCHEDDHG,False +852,8.0,4.0,3.0,3.0,5.0,4.0,5.0,3.0,CEHEHBGFGBABDCGAGHFDCGAAAAEADAFEFEB,False +853,2.0,2.0,4.0,5.0,2.0,8.0,1.0,9.0,BHFHFHFADCCGFDFDBDEFAHHHHHFHECCFD,True +854,0.0,3.0,1.0,7.0,1.0,4.0,3.0,3.0,BGEDFDHDHGFBDBCGHDFDFD,True +855,13.0,9.0,23.0,8.0,13.0,14.0,12.0,14.0,CFCFCGHEACCCEEEGDHHAHBGBCFCDCDCFFGCAFDCABHCHCDFFCECGCGCAABFDEDACCHHAFAEBEBHGHBHFGEGCGCGAEBCBAGEFEFEFDHAHAH,False +856,10.0,14.0,21.0,25.0,13.0,22.0,18.0,15.0,HDAFAFDFBGDDCEEGEDFGBDBGCCCCDDDGDGHFDGHEFECHCHCFEDBDBACGFBFBFDCGEGCABABDEGCGCECEBAFGHHBDDDHHHGGDCDCACAFBEBECFCFAEHHFFFDGDGHGHDDFDFHFCFCBAF,False +857,5.0,7.0,6.0,6.0,3.0,6.0,3.0,6.0,HBHCDAHAFGBACABHBDBDEFGCHCHCBEFEFGFCFDDBDA,False +858,5.0,6.0,10.0,9.0,8.0,7.0,3.0,10.0,BGCHCHCBDDHDGDGABCBABFECECECDCDFHHCEDDFFFHHEHEAEAFHBEDHCAF,False +859,5.0,3.0,3.0,10.0,1.0,2.0,6.0,6.0,DADADBGHEADDDCDGHGHGCDCDBFAHHFHAGDGB,True +860,23.0,20.0,27.0,31.0,27.0,21.0,22.0,20.0,GBHCDCFCFDEDHCHGEFEFECCCCCADABAHFHFHFDGDAEEHACDDGBADFDEECFAFCFEGCGEEHFAFEFBABCDADEDEHBHGHBBAECECGBHAGFHHBGECCDEDBFHCACGCDAGAGADDDDDCDGFCFCEEEDEBHGHGHGCGCBDADHBGDDEDABABAEDEBFCDEBABGBDAFAFGEGH,False +861,7.0,7.0,14.0,4.0,11.0,5.0,11.0,5.0,GCGFGBGCCCGFAAEAECECECGBABHHCAEAHAEFEBEHDCDCGFGFBCGCGCDBEEHDGECB,True +862,12.0,3.0,10.0,5.0,8.0,8.0,5.0,6.0,GFCAHAHAGACCEHDBBAAAHADECEDECGCBCECFCFHFHAGGEDEFFCFAEAFAD,False +863,24.0,14.0,29.0,24.0,18.0,18.0,12.0,25.0,ACACHBEBEDABHBGCDCFCEDFCGCACGFADCCCCBCDEAEBDHEEGAGCDFDFDFGEHAHFEEAEHCCFHFEFCHCHDAAHGDCDAHFHEHDHDHAHADEBEBEGADAHEBFHFHACGFGCGCBCDCDCACFCFABCBADDBCBHHDHGAAHAHFFDHDEDA,False +864,12.0,14.0,8.0,8.0,15.0,8.0,10.0,15.0,EBEBGHCABAFAFDFDADGBHCEBGBGBCFCAEEDHCHGHBHDGDHEHEHEHCFGFBEEHAAAHGHGEGBFCABHFHEEBADCDABEBEA,False +865,3.0,2.0,2.0,3.0,0.0,3.0,0.0,4.0,BHDHBCFDFCAHAHAFD,True +866,5.0,8.0,8.0,6.0,13.0,7.0,15.0,8.0,FHCDEDADBEBGAGCCCEBGGFGEGEGAGAGHDHGBEHEDGAGEBECHCGFEEHEHGGFBFBFCFHEBCD,False +867,15.0,8.0,10.0,4.0,10.0,7.0,12.0,11.0,GCHHEHGBDBCGCBCFEAAHAHADFCFCFGAGAFBGAHAEGFBECEABHCHAEAEHGHGFBDCHGEGEGDACABAEA,False +868,13.0,19.0,24.0,20.0,14.0,16.0,12.0,20.0,HCHAHAGDDCDBGGHGHGCEEAEGFBFDEAEFCFHDHGFAFGEHDBDBDCECDFECHCDCFCHCHBBBBGAFDCACEDBFFAFAFBEHCACDHBCBCBHBCADDDBDHDHCHCBABHHEFGAECGCGCBDBDCFHFEE,False +869,11.0,10.0,12.0,15.0,14.0,12.0,10.0,5.0,CBGECDGDGDADCGAHDBDFFFFEAHFEFDBDGDGECECDDFDADBEACGFEBEBECCCGCBCBEAEAFGBAAAEDEGHHDHCFAFEFB,False +870,8.0,16.0,15.0,5.0,12.0,6.0,10.0,5.0,GEGAAFBCBCEGAAEBEBEFHHCBAAGACBBBBEBCGCGCECECBABCFCGCFEDEHCCDGBGFDFDEHCHBBGBDE,True +871,7.0,10.0,13.0,4.0,10.0,7.0,7.0,8.0,GAAHGCBADEDHDCCCACAFHEBBBBBCBEGEGFCHCBEGEGEHDHCFFABCFCFHGHABFECECE,False +872,5.0,6.0,11.0,4.0,5.0,6.0,7.0,6.0,FCCCACBDAFCCCFGBBHBGAGEGDGCGHGHDHDEBHCCFCBAEFEFEHA,False +873,6.0,3.0,2.0,8.0,3.0,5.0,4.0,1.0,AADDDCDCGGFFEBADADADEDGBGFFEFAHB,True +874,16.0,16.0,9.0,13.0,16.0,16.0,11.0,18.0,DGAGHBHCEFGDAAEAFAFBBDFHEDEDHBHGHGHDDEDFCFCAAADAHFBCBCGEHEBFDFAFCFAFAFBECCBEDHHEHEGBGCDFGFHHHBHBEBEBHAEADBEBAAGEGHF,False +875,10.0,10.0,11.0,9.0,10.0,8.0,13.0,16.0,AFADADEDEFHCHCFGBGEHDFGHCHEGBGHFABHEACHBHBHBHGDGBAAAHAHCHCGGGCGEDEBCDDGBGAECEFFFBCHCHDE,False +876,10.0,18.0,8.0,11.0,7.0,15.0,11.0,9.0,FCHDHBFBGCDHAGCCHDHAGFFHBHEFAFAFDBBBDBDEACGGGBGFECECACHDBABFBDBDGEADADFFFGEGEBBBFBFBGBFAH,False +877,4.0,5.0,14.0,13.0,6.0,8.0,11.0,11.0,ACACGHADGCECGGGDCCCFCFBFDFDHDHDADHDHFFBHGHCHCGCDCDHDEEBGFDEHBHGEEBDFCCGG,True +878,22.0,17.0,15.0,16.0,16.0,19.0,13.0,15.0,CCFCHHDBEGEGDCFHFBAGFEDDFDCECEGBCBABADADBGGDBACAFAEABHHHFHCHDBFBDBDBEHHCHCHEEGFGFHAEAEAEADFEAABCFCEAHFGAAADFDFBFBEGCGCDAFAFAEDGBHBGFA,False +879,11.0,12.0,5.0,10.0,10.0,9.0,11.0,9.0,BCBCEAFGFGHBHBHDDFEFGBGHGFBDCAAGEHDBDGHGHFADAEEFEDEDEAHABABACAGHEDFAGEDBGBCBF,False +880,22.0,23.0,20.0,22.0,17.0,22.0,27.0,22.0,AFEFEHDHDHDBFBGBGEGBGFGFGEHEABABGGGABAHDHEBCGCGCFCDBDFEEAAAFDCBFHGHBCGAEDFDFDBCECFBAGAGAFEHGGCGDBBCCGBDDCDBDCFCAHDBAFFHCHDHFHCEEDHDHBHCCBFBAEAEAFGDCDHAHFHEHADAGAGAFBGCGHGFBEGG,False +881,26.0,17.0,21.0,13.0,20.0,12.0,23.0,19.0,BAEAGCGHGAEADABEEEGAAHHDDBDFGAGACCHHEHEBFBHEEEDFGFEAGHCCACGEFEDCGCHCGFHHBHBGBCCCDCGBGBABABFDDHEAEFEGGGGEHAHACACDGBGBGBEAFACEHFAAAHGHGDCCECFCBCBHDAAAFAD,False +882,1.0,1.0,3.0,2.0,1.0,1.0,0.0,5.0,DHHFADEBCHCHCH,True +883,7.0,3.0,8.0,7.0,4.0,4.0,4.0,4.0,GDEDCFHFHDHDEGEACDCABBGFACACGCFCDADBCAEAH,False +884,21.0,12.0,14.0,11.0,9.0,9.0,15.0,13.0,EHEAEGDDAGGBGFFAGHDHDCDCDCFCGGGGGAAEGCHEDEAEFHFAFGCBHBCCCCADBBAGAGHBCACAHAHBFEDBGBCBEDDHHABAFAHAHFBCAAAA,False +885,16.0,26.0,24.0,20.0,25.0,24.0,19.0,20.0,DFDGGAEAEAEDHGHGCCABBEECFCFGBGBDCGFFDBDECEADADHGHFDBDCEEBCGCGAFBFBCHDFDFEFEFHFHFHBHFEFHCHCBAFDFBFCAGAECBBBBEAEBGCECFHEHDCCEGBGBGFGFHHEHCHBDACECABABDBHAEDDCGGBBEFDFDCBAEHEHECG,False +886,13.0,28.0,17.0,8.0,23.0,25.0,17.0,16.0,GFFBFBHCFBBBCGCGEEBCBABFDEBGBGCACEHFHFHBADDCGEGEBHAAACFCEHBHBDAEFFFFDFDFEFEFECEBBBHFGBBHBEGCBEAEDCHEEEFBGHGECEHFHBABFCFCFCGCEAGDGAGAFBGGAFHHHBEBEBF,False +887,12.0,16.0,10.0,18.0,15.0,11.0,14.0,8.0,EEHEFGDCAFDGDCBFBFGFBEAFBBBAGFGBGCHCHCAGADCFCDBDEHEAEDGDBHBFGEBEBDBDADCDHDEABDDEDFCAGDGAGAFDEAGCGBEBEHEH,False +888,18.0,13.0,17.0,15.0,11.0,10.0,18.0,15.0,DEGEDEFAHAHAHGHGHGCGCFDDDADFCBGDGDCBABCBEACAGAGCEDBABDHFGAGAGDEEHAFCDCBCACBEBHCGBFAHAHCDFHBGBGHFHGHFBACEGEGCHAECFCDAD,False +889,22.0,5.0,11.0,9.0,14.0,19.0,10.0,13.0,HEHFADEFGFCEHEFDFHFAFGGGGAGAFADGDFAEAHBCECEDFCFHFCFDFDAACACABBFGCHEAAABCDHEAEABFHFHEGEFHAAAAACAGDHCHEFE,False +890,27.0,36.0,17.0,27.0,26.0,14.0,25.0,25.0,FHDGFABEECADAEBECEABAGHECDCDADGDADADEHEHGHBFBCBGDEEEEEBABABHBHAGCEDEDEHAHAGGCDCDHBABHBCACAGFCFGHHFDFDGBGHGAGCGFFBHADFCECEHBDBGBABACAHEBBHGHEHBBEDEFEBGBDBCGEDBBBBBEBDHDBAHGFGAEBHAADGHGDABFCFDAGBGDHD,False +891,18.0,15.0,22.0,14.0,25.0,27.0,18.0,19.0,FHFHEHAHCFEDCDHFFFHCCCCCCFAFGEAHAFGGEGEGEGFGFAEHDCDFHGAGEBHFHCHBHBEDHDCFCACGBFCDDEHBCEGAFABEBFDEGAFDCACFEFEDEAAGAGAGCBCDFEHAHEHBCBCBFBEEFEHGGGCEFEFEBEAFFBDADB,False +892,15.0,15.0,17.0,14.0,25.0,21.0,15.0,21.0,EGAHHHDHDFEAEDEGGGGAGFHFAFEEEHHBCBGHGBGDFAAEAECEFEDDBFCFCAGFFHFHFHBCFCDHFHCHADBHFGFGBEBHHEEDDCDGBCEEEBGBHEHEDEAFCBCECEBGAAAEDCDCACABEHHCFEFCFBF,False +893,5.0,2.0,1.0,1.0,3.0,2.0,5.0,2.0,BHAHAEEEGFGFACGBDAGAG,True +894,1.0,2.0,2.0,3.0,4.0,6.0,4.0,3.0,FCFCHHEFEFGGGGHDBEBFAFDDE,True +895,12.0,25.0,10.0,17.0,18.0,19.0,18.0,17.0,CECBHFGFGEBBHFEFDBDBABDGAGAEABCBGAGAHCEEHEHEHDDCDBFHFHEDFCFBFBFAGGGGGFGEHBBBHDHBHDEBEFGDCBBBDBGCAHHEGBGBCDFDEEEDEACAFFGBBHFHFDFAFHGBADED,False +896,16.0,8.0,11.0,13.0,10.0,11.0,7.0,7.0,GEDEHEHBBDADFDADCDCAAAHFHFGFECACAEDCDGAEAEBBCBGEACAHDBDEGFHFBCDCFAADACBCHFAFAFEGGDF,False +897,11.0,6.0,9.0,7.0,10.0,14.0,15.0,10.0,HDBFBGCFCGCGBGDEDGHAHGHAAFHFCGBGCAHHGFCFAFEBGHGBDCHCHDEEFEFEAEAEFEFGDGFAFACGEFDAGA,False +898,17.0,13.0,21.0,30.0,28.0,20.0,12.0,19.0,EDDBGCECEDBCBCDHGFECBGBEHHHEHFHDGDHHAFAHCHDBEFDADCDHEEEHEGDGDGFEDCACEDEAEAEFDFDFDADCCACFEFCFEFCBBHCCFEEDHDFGEGAFCFCACABABCGDEDAHEDDDDGDGFHDHDABFCFDFAHEEBEBEHEAA,False +899,3.0,3.0,2.0,3.0,3.0,3.0,8.0,3.0,BCEFGHGHGAGBGBGDFDCHEGEFAADG,False +900,16.0,24.0,17.0,15.0,11.0,13.0,13.0,18.0,DDCDADAECDHHHCHADDHCHCBCADAECGHGEAHFHGBBHDADAEHHFHGACACFCFBEBEDCGCGBBBBGEFFHFBBGCGBABABAHFEFBBECCHGFDFBFAFAHBBEBEACDGDGCBHBGBDB,False +901,25.0,30.0,29.0,16.0,34.0,19.0,24.0,19.0,FFGCECEBBBCDCBFEEEECGCABAFEFGHBDAACECGHDFCHBFBGGGBGHCHCBCECBGBEFDHBHBHCHAHAGABABGEGFCFBEGEBBCBCDHHHCHCHDBDCFCAEDHGAGEBEGEBEDEFFDBDEFBCEFEAGGFGEGFBFHHACACAEAEAEBEHEBAGAEAECGABADDDAECECFAAEDDAGCECBG,False +902,24.0,23.0,19.0,24.0,26.0,27.0,19.0,14.0,FAAAEACAEEEGEDAHEBADAGGHEDCABGFFDFDFEBEBEDEDGAHFDGBCBFDFGECFBFGFBFEFCFEDADBEFEFACACACAHADBBBEHAHBGBFAGBEEGGFGCGCFAFDFEBHGCAAGDGFHFCFCHCDCBFBGBCBEHFHCHCBEDGDACAEBDBHFHEDDDDDEAED,False +903,29.0,29.0,25.0,18.0,19.0,26.0,26.0,24.0,GABBEDADAGFHBHFHGCBCBDADGBGDGHEDBGBGDAEBEAGFGACEBEDADFFFBBBCFCGAFAHEHEHGBAAAAAAGGCCHBGBABHEEFHFHAHFBGCHDHFEBEGEAEDFGCHBHACADBHGDGCEDFFHFEFBCBABAHAEAGGFFCFAHADGDGCBCBCGCGCBCBCFHEHDFFEFHFCFABCHCDCAC,False +904,6.0,3.0,10.0,6.0,5.0,4.0,4.0,1.0,ACGCFCACDCHCDDDEDCGGEFBCBCBFGFEEAEDCAAA,True +905,3.0,18.0,9.0,11.0,14.0,16.0,4.0,13.0,DCFBBCBEBDBFFEFDCGHBHGDCFBFDEHEFBHBFEFHFHFGCAEHFAFBEHEHEHCACHGFDCBEFEHEBDBDBHBDEDEDBCBFB,True +906,16.0,25.0,37.0,22.0,24.0,10.0,28.0,28.0,DFDCDCEAEHCHEACBHBGBHCCGCECADDDDDDCHHHAHCCCGDECECEBECHCFCFBHBACGCBABCBHGEBBBHGHGBCBCDEEAAGAGDHFCCEDEDGDGDGBGHHDFFGEEBFAGHGFCBBGEHHBCBDBABCEAGACACGBEHEHCFDHAHEGGGHGHGACEDECHCGCGCDHFHBEGEDBCGC,False +907,25.0,18.0,28.0,21.0,19.0,32.0,30.0,20.0,GCGCEBHGCGCEDDHHGCCCCGHGHDHEHACGGGBGFGBEACGHGCFDFDCCCHCFDFAFAEAGABACAGACEBHBFGFBFBDHCFAFGFACAGDEHCDBGHAHBBDFDFCFAEBDCGFAHGHGFGFGBADFEFHBDADABBEAFHDDFDFGBGDEDEFAFEFEFGFAFDFEFCACHFHBEEECGCGCAAEAC,False +908,28.0,27.0,16.0,15.0,23.0,29.0,25.0,24.0,FAFEFGFBABHFFBHDCCGAABEBCACAEFFCFAGAEEGEGFGFDFHFHBAGFGBGDHBHBHBCGEGFAAHAHAHAEGEBEAHABCBDFGFGEGBFBHBDBFBFGFGHGHBEBEBDGHGFAFCHADEEECECFBACCBCDDHGGEHEGCAAFAFBDHHHDHDFDADGFAAEAFABEECGHHDBEACB,False +909,22.0,23.0,20.0,21.0,31.0,23.0,29.0,28.0,EAGGGDCHHHHCDDEDBCHAEDGBGAGADBHAFFHGBGBDEGEGHGAGDBEGAGCCHFHFGEGHHEAEBDDDDADHCBBBCACFCGAGECEAEFEGEDDAAEFEHBHBGBFCFCHGBBDBFBFDEAEAEFCDDEGFGFCECAGHGFGFEHHDAFHFHGHGHFHFEEEHAFBBBEAECGCBCBCEEAHACBFDFEHEH,False +910,35.0,20.0,17.0,22.0,15.0,17.0,23.0,20.0,BABABADGDFFFFFADHEEAEHCBGBGDGEGCACHEFAAHAHAHBHGHBABCBCGCFDFAFCFCEAEHEDGFGBAAADBGADADBDBECGGFCBDBHCAADAHAGADCGFGFGCGCEDAAEAHDEDBAGFGBADDDCDHHHCHAHDEAHGFAEAFBDHAGAEHBBGCGA,False +911,20.0,22.0,16.0,16.0,19.0,34.0,24.0,21.0,HHBBFFAHAHEFAFCDBDBDGCEEBFBDCCBCHDFAFDBDBFCFAHGEDBGFFFDFHACEDGDBFBFCECHCHBFAFADAFFFFFFFGFBHGHGHGHAFABACHCFGGGAFHFHGGGGFAFEEGHGEEEGECDGECBCBHDGDGHEHDBAGEBEAEABABFEGACHEBGFAF,False +912,14.0,22.0,22.0,16.0,10.0,16.0,13.0,11.0,GABHDHAHACDCBFFFECHFHEBEGABCEHEBBFBACHCHCACABEFFDBACDHFADAFBFBGGCGCGCHFBFCGDFAFGBCBCBDHDGDCBCBCGDGCGAGABCBCACEDFDEEFBBDDDEDB,False +913,20.0,27.0,29.0,23.0,22.0,31.0,29.0,18.0,GFGEECFDFAGEFHFACDEGCGCGHGHDHDCGCFDBAGAGAGDGHFDFBFGFGAGHDAGAFABDCFFECECEFFDCDCBCGDBABFFHFDDDGACHHDBEBEBFCEEBEHAHECBABGGAGDHDCEEGFCFBDECACAFHFAFACBEAGGGBGBCBHFCFCFCFCHDFAEBBBHBEBECFCHEEGBGBFCDBDBDBHGC,False +914,12.0,9.0,6.0,2.0,6.0,6.0,2.0,13.0,BFBHEHEHBADCHBAGFHFEBHAAACABHBHAAACECBBACGCHFHAHAHEHEFFD,True +915,10.0,12.0,24.0,13.0,16.0,14.0,13.0,16.0,CEBDBDBDCDCDCDBDAHHBFBFCFGFGEDFHCBCFGECFCEBEBHBCCFCFDFEHAFBHAHAHFCACHCECEHACBCHCFEDEAGACDCHCGAHCDEGGHEEFHAGGGECEGEHDGG,False +916,4.0,4.0,9.0,4.0,6.0,12.0,3.0,4.0,CECDADFBACFCFDFBFGFCFGHCCGBEHEHEHEFFCACBEFFFAD,True +917,15.0,18.0,12.0,11.0,16.0,11.0,18.0,15.0,AEAEAEAEAHAHAGEEFHGHBHBEDABABADHGFGDHBCDDFHGBEFFFAFGGHBDFCBEHECECGFHBHEEGDBEGEBBGDCDHDCACGFGHGCABABHFACCCCBGBGBGDGBE,False +918,14.0,16.0,12.0,30.0,16.0,18.0,12.0,16.0,DHDAEBFADADADADADGDFAFHFHDEFGBGBGBGFHCGEHECEAACACGCDDDFEBEBHBFAFHCDDDDFCFDFGHCFDHEFEFDCHBBBHAEDEDBAAHCEFDCDBDFDBEEDBDHEBDHDGFHDHEGGGCB,False +919,5.0,11.0,3.0,9.0,10.0,8.0,8.0,5.0,BFBHEEEBCBHEHGAGAGDDBDEEEHABFCFBAGDCDGDBDGAFEFEFDBDGGFBFBHE,False +920,5.0,0.0,5.0,4.0,1.0,1.0,4.0,2.0,CGAAFADHDCACGCECGDGDHA,True +921,24.0,17.0,18.0,26.0,23.0,31.0,24.0,25.0,EDEDCDADFGBABAGGFCFDFEGCGBHHECEADGDEDFDFDBEGEFCAGFEFEFDHEADHCHAHFHFHEGEDDDDBGEGEFBCDCEAAHDBAGHDHFGGHEHAHAHAHFHFDFBGBHCGAGFEFEFADACAFEBGCCDBEBADAFBGCFAFCHCHAFEFGCGBGCAFABCDAFBFBHDHFHEGDGHFH,False +922,12.0,3.0,17.0,8.0,6.0,8.0,19.0,16.0,GDFCHCHAADGBHCHAFEHCHCBGBCHFACAFADGGGGGGCGCAADHEHECEAEDDCCEGFGFGAGAHHGHGCDADCCHHGCGFHFHGC,True +923,13.0,7.0,15.0,17.0,15.0,11.0,14.0,5.0,GDDDHCCBCDADAEABADADGHFDCCACAEAGGDEEEDFHFBDGCHBFBFDGGBCDDDFCFCFEEGCFEFADADACAGGGGEGCCAEBEHEGEFECE,False +924,19.0,22.0,14.0,20.0,28.0,12.0,19.0,18.0,CGCDHBFBHGEBEADBDGDGDCBCDCHCEBHGEGEHEGDFFCEAEDGCGEGFDEEEEEBABCBCBCBCBGFDFAEAFDHDHEHFDAAHHHHEAEADAFEFEDBABDHEFEAGCBBFHDHBHBGBADHEEDBDEGBAEAGGCGHBEGGAAAEA,False +925,20.0,23.0,18.0,19.0,19.0,27.0,21.0,22.0,FEHEHEGDGCBDBHBEBCAGACHFEFHAHADAFGBGFFEGECEHDGDAHAHEDCCEAGFDFEGCCBGBFBFHDADCBCBFBCCHBHAHBDCECDFHFGFADCFFFFBFADBGGHADFDBBCBGHHHEHEHBAEAEFGBHBHGAGEFEFGFGFDCDFBFACAGAEADGDB,False +926,8.0,4.0,5.0,5.0,6.0,5.0,4.0,8.0,FGFDECECEADFBFBHEHAHADAHAEACGDADHHHBHFACBEGCG,False +927,4.0,9.0,2.0,4.0,9.0,4.0,11.0,2.0,GHGBGDGBGBEAGFGBBBBDDEBGFGEGEDECEAEAGBFCEHFAE,True +928,19.0,13.0,20.0,26.0,25.0,21.0,11.0,20.0,DDDFAGCFCHADFCCECECFBEHDBEBEDEHEHCFAEAEAEFDFBFADAEAEAEADHDFDFGBGBADEDBHCGCFCBEEAEHECFHAGACCCDDEDHHHHAHDDDACGHBACFCFGDEFEBHFHFCDDDHDACECBDHGHEEFGBGFGFEDHFBA,False +929,31.0,26.0,25.0,22.0,30.0,19.0,16.0,16.0,GADBEEEAEAHACCCCFGFEHBGBGCFCFDDADGBAAAFEFAABEHADFDFACAHBHGEFBAAACFCGABEGFABGFGEGFBFBEBFDEDEHGFEECHAHADADADCHEHEBEDABHBEACADBDBDGDGDCDCACHEHGCEHDCEABCFAEDFDGCEBFBAAEHEDEBCBCBCBCBEEAEBCHC,False +930,5.0,6.0,16.0,9.0,2.0,8.0,6.0,8.0,FCFCBBGDGDBABHCHCGEBEDDGACFCFCFCHCGCABHCCCCHFHCAGFHHCAFDDDDD,True +931,13.0,10.0,13.0,5.0,17.0,8.0,8.0,11.0,AEAEAHAEECBHBHGHAEBFCEEAEBEGCHBFBGEGFACADAEGEDBFCCHHBHBHFHCGEGHDDCDCACAEAFBCGCFEFECEA,False +932,13.0,15.0,7.0,16.0,20.0,10.0,5.0,18.0,AEABBCHEBEHEFEDEAFBHBADFHHDBDEHBABABABACDCFEFHFEGGACEDEHEBBAFGHCEDEDBGCHHDBDBEHCHDADGDEDEDHFEEEAHAHFHFHD,False +933,4.0,6.0,3.0,4.0,2.0,6.0,4.0,5.0,AGAGAHBEEDCGBGBCBDFDFDHHAFBFHFCBHF,False +934,5.0,12.0,3.0,2.0,5.0,4.0,9.0,11.0,CEDBABACFFGFAEAGCGBGHGHBHGHEBBHBHGDFHHHHBEBEAGBBBGH,True +935,8.0,6.0,1.0,11.0,7.0,1.0,14.0,7.0,GEBHGHGDBAEEDAGGEGDGBGBHHHHDDAAAAGDGDGDADABCEGEHEDDFGGB,True +936,12.0,13.0,17.0,16.0,15.0,22.0,16.0,19.0,HHEDDDDGDGAFACACHCFEEECACADBGHGFFFFFFEHEHCAGBDFEFDFEFEHEFFBBABFCHEGFGDHBCBCBEEAHCCECDDBFBHCHFHFHDEDGGGDGBGHCBGAFDGDGCAHBCCHGHFHFAA,False +937,3.0,4.0,1.0,4.0,2.0,0.0,0.0,2.0,ADDEDEHBHBACADBB,True +938,5.0,10.0,7.0,7.0,2.0,7.0,13.0,13.0,FCGGGHHAFEFBFBGBABAEGGGGCFCFHBABHHDHDHFHACDBBGHGDGDHCBDHCHGBGDHC,True +939,0.0,2.0,2.0,0.0,2.0,1.0,2.0,1.0,CGEGEBFBHC,True +940,15.0,12.0,17.0,12.0,18.0,16.0,21.0,10.0,DADACBCEGEGCCAHFCDCDAEACDCFGDAEBEBEACABEGGGABACDFDCGGFDDHCGFGEGBCBDEDGHGFEFBFGGCBCEEFAFGFHFAFHGHGCEFEBHBHGEGEGEFAFAHACBHE,False +941,21.0,9.0,18.0,19.0,23.0,21.0,20.0,26.0,EGEDHBHBHGHGHCEAAGBHBDDDGGGDGFGFEFGFGADHEFEAEAFAHAEAHBFECDCAAGDFAFHEHCCDCEFHFHFAEAHACFCFCHCECEHDDGDHDHDADEBHFEGAAEAFBHCCEGGDEDBCHADAHFBFCFCGGEDECFHGAGHECEHFH,False +942,23.0,23.0,25.0,23.0,16.0,18.0,18.0,24.0,CAHDBDHDEGCADHGHGHGHFCDCHCDFGEDEDHDHBHFDFEEADAEABFFGFGACFBBCFCBBFAHCHCEEDCCFHACACABHBFFFDFECACHHEGDGDEDBHBCBHBHADABHBHBCGHACBCBEBABCGEEFEAEAGGCDDDDAGAGAHBHDGBCFGFDCAGACAB,False +943,9.0,5.0,6.0,3.0,2.0,3.0,4.0,6.0,DBDHCFFHCEAEGBGBGAHCHBBAGFCAHAHACADACA,True +944,1.0,5.0,5.0,2.0,2.0,3.0,5.0,5.0,EGGDGHCBBAEGHGCFCFBHBHBHCFCD,True +945,23.0,12.0,17.0,23.0,21.0,25.0,31.0,23.0,AHAHBHBHCHCEDDFCACDCDFGFBHBCCGFGHGAAHDEEGECFAHAHFHDHEADFGCGCGFGEADBEAEBEDDBCBHAAFAFAFDGDHABAEHDHGEEEHDADGFGHGFEFGFCFAFHFEFADGGEGEGECFDHCHDFGHGDGCAAGAGEGFDBGCEBGBGDEDHFFCFGAGDG,False +946,7.0,6.0,9.0,5.0,3.0,13.0,9.0,7.0,BEBECFHFHAHGCAABCCFGBGFFCFGFBFDFGGAGHGFFFFDBCGHHCHCDDADAEAC,False +947,12.0,14.0,22.0,9.0,8.0,15.0,19.0,16.0,GGGGGADFDBBBCHGACAHBFGHGHGFGCCFDACHGHEFFBCBGEGDGFHHHBHDGDCCCCGBFHACACECDCFGBHBHBCEFECHCBCBCHGFGDAAAADAEEFCFCACFFEHB,False +948,23.0,29.0,24.0,18.0,9.0,25.0,25.0,32.0,BBBHGFAEAEBEBCFCFAFAFCFDFBHBGCHFAEGDACAGBHCHFDBCBGGCCBBHHABDCFGHBDCDBDGFBCAFAHHGHFHEHACEGDABGBGHABABGHHHFBFCFHFABAEAGACBCFHHBABCBCBCACFCHGHCHBGBHDDFGAAFFFEDDDGDHDHGHGHGHDHGHGHDCDCGFGFEA,False +949,7.0,6.0,5.0,7.0,7.0,6.0,6.0,12.0,HHCHADDCGBGFFHDHBBCHCHBFADAEAGAFAEAHBHEEEEHHHBGDGEGCDFDF,False +950,24.0,23.0,22.0,11.0,20.0,30.0,30.0,14.0,EHFBFBFBCCFCAAACEGBFAEEBHCHFHEAEAGBGHGHGCGCFEFAFBEAGAEBGDGCGHGHBBGBGBFBFDFECAGGFEBEGCAEBEDGHAFBHBFBDGDGFGDACCGCECACAGFCECHDFBCGCGFFFGFGCBCGABADFBHGGFGDHDEFBHCAAAAAAFFFFFDEEAE,False +951,16.0,19.0,15.0,15.0,20.0,28.0,15.0,17.0,DGGFECEHGHFHCBCEHGDGCBCGCEEFAFAFAHEHFAABHEGDGAGBGEEBHDHBBCBCHFBDBDBHEDFCAEAFFFDFDFAGBCBDECFFFEFDFBFGFGEECECEFEFEDHGCDAHAEABBDGFBFHHBHDAFHFCFAFABA,False +952,9.0,0.0,6.0,3.0,8.0,5.0,2.0,3.0,EFACCCFAAAAHFFFDGAAEAEHGHECECEDECEAD,True +953,2.0,1.0,1.0,1.0,6.0,2.0,3.0,1.0,ECEHDAAGBGEEEEFGF,True +954,11.0,9.0,7.0,13.0,13.0,4.0,8.0,8.0,CADHDHDFDABBEACAFDBBHFHGAGECBGEGEGEBEHEDEAHBGDADADADFDEBEDDCAABHEHCGEGECC,False +955,17.0,19.0,17.0,18.0,12.0,19.0,16.0,32.0,GFGFAAGFGAHADGGHGEBABFEDBHBDFHHHHBGBHDHDEAACBFBFBEAEHCDDGDFHHEDGHGBGBGADHFHDHCCGAEACDCDCAHAHFHFHFHDBDADHCCCHBACACBHFHFEFECACGEBBFDHCHDHBHEFGCECHFFBHBH,False +956,21.0,23.0,17.0,24.0,20.0,16.0,15.0,22.0,DADEHFHDCBCBCAHGBGFDFDGBAFDFDHHFDBDBACACFEHEAEAHAEEBAGCHCFCFAHAGDGDADADHHGHGECCFCFGFCHAHGDGBCCHADBDEAHGCFBHBHBHEEEEEHEBEAEGDBBFBHHCDCEBBBDBDBAADGFABADFEEGEDDB,False +957,10.0,10.0,8.0,10.0,12.0,10.0,10.0,2.0,FGFBFDFCGGFGABBBDGAAAFHFDGDBDGDEDECECECECGBAEHECGDACEBGBDFCAEAFFEDEBABAE,False +958,23.0,37.0,29.0,27.0,20.0,20.0,23.0,19.0,ADBDBAFABHBADGGCCCHFHGBBDDCACACBBAGDHDHCHFECBHFEGEBEDCCFEDEFBFBCBCBHEHBGDCDGBGAGAFFGCGEGAADACADBGFEDGBGFDBHBCAHEEFFDCDADBDBACDCDCDBHBHFEFHFDBGBGEFHFHBACECEDEBCBCBCGCGBBACAGEFBFBABGDGDHEHEGBCDCBHEAAA,False +959,12.0,18.0,18.0,8.0,12.0,10.0,17.0,15.0,BEBEBGBGBHBCBCECGCGCDCFGGHGBCHEACCCEFGAAAEHBHEHBGBHAEABHGFCFCDCEABACAHEHCGCHFEAEGDBDHDCGFDCDAHBHGFDFGGGHFBBBAF,False +960,6.0,8.0,14.0,11.0,10.0,8.0,6.0,15.0,EADADHGFDEEHFHDHBHBHCECDFDBDECHFFAFGFBEDECBCECHHHHGCGDGDHCCCCCCEEDHHAHABCGFABB,False +961,20.0,29.0,25.0,20.0,25.0,26.0,26.0,18.0,BHBEFEABGFAEGDGDFFBDHDGBGBFFFHEEEEEDFAFADABGGCGCBCBAFCFABCCHEHGDDEDEGFFAAEEEEAGCGAGHGFDCCBCHGACACEDHGHGAFBFBFAHEBEBEDGBHCCEAEADDDHDCBCFHAHCHBHBFBFBGGGBHECGFGECBCBCDHDBBFDCACACBFGFGEGCDEBFBF,False +962,27.0,19.0,27.0,18.0,20.0,32.0,29.0,28.0,GEGECAFAHHHHEAEBDBDCHHGHFEFHDBFAFBFDGDBCBCGHGHFCFCFCFDEGADHHCCADADAGEHEHGACCHGHBHEHCHCHFECGCFAFBFAFGFBCAEFCDHAGFBFHGEGAAHGFGEDEACDCFHDDCDCFCHCGCEDGHBDAAFAGBFBFHEGAFACADEFEBEGGGCGCBBFBFGAGAGAFABAGFBEHF,False +963,18.0,20.0,27.0,19.0,14.0,17.0,15.0,25.0,FFACCGCGCDDHCHCDGGGEHFBCBHFCAAAAHAGFGDGAGDGHFBDEDHCBCACACGCGAFEBBCECEAEHEHBBCHHHHAACDCDBDFCFBFBHCHBHDGCEEEHEDGBBBFEFHFHDCDBDADAHFBCBABDCEAHHDACFCGHBHFHDCFE,False +964,12.0,10.0,8.0,9.0,12.0,10.0,10.0,9.0,FGFAEAEAGADFEECEHBBBAHAEBECECAGGHBAAGEHFHDHAEFDFECDCBFBFBABDDFDGGFGCCCEHAHBHGDGD,False +965,17.0,22.0,24.0,31.0,26.0,22.0,22.0,27.0,CGCEHFCFCEBDBDBEHEHGHGHFABABHEHFBEBGHDHDFCBDBEBGGCHCFDFHEHDHDGDFFBCAHAHGEEFHBHBEBADFFAFAHDHGAGAHEDDHDEBEFEBEFHFHACADDDFDEEEECCCDAGADBGAGFEHBGGHDCCCDEDGHCECDDABFBEBCGEGCGCFCDCAAEDCBGHGDFDGDCDF,False +966,27.0,18.0,26.0,14.0,26.0,27.0,37.0,24.0,AACDCHCFGHAHAGAGACFHEHABFHFAGHBCBDBFBFBABFHHHFHFCEDEFACHCECFGFEFECGDGHGCGFGEHECDCBCBGBECEDFAEECAGGFAFBHEFDGBGEGHFEEGEHCGEGDGDGDFCCCCHBAEACHGHGAGHGAGEHEGEGBCAGGGFABHDADADAGAFHBEDCFAEECFGFGFGCGABEFGABA,False +967,19.0,30.0,23.0,20.0,26.0,19.0,25.0,21.0,BBABCBGGAGFDFGHDHEGBGCGBBAFDCBCEFHDCDFBCBGEFBHBEEEEEBADAHAHBGGGEDBFBHCCCECBGHDHDFGBDCDFBEHECGBGBGFCFAHEHDGEGEFDFDECCCHCHEGEGHGBCEAGABEBABABABADADABAEADCCEFBABFECDFHFHCHFEFCGGEHEHGDADH,False +968,22.0,15.0,29.0,26.0,37.0,20.0,22.0,24.0,AEGBABEFGGEGDHDHAHEFECEFACEEACHBECFBABCDCACAHGHDEEFECECDAAAEHGHGHDHDFGFHCADFDBDEDEAEDEDEDEDGGECEABBGFADADEHGHFECBCAEAEGECECAGDBEGAACCCCCCBHEGECDCDFHFHFHFHFCGEGHBDFEBBBGECHDEFEHHGDADCGHGDDCEFHFCFC,False +969,16.0,6.0,14.0,15.0,9.0,8.0,13.0,13.0,HHHHFEFDDCAHGGEGDGDCBBHCCDADGGHAAADADFDFDGDGDGABEBAFABECDHAAFAFEFGDGCHEHCDCGCEEHHHAEACCCCBCGAA,False +970,21.0,25.0,9.0,17.0,8.0,13.0,18.0,16.0,GBGHGACACAFHFBCADGGGFGFGAGAGBBDBGCHHEHEBFDEABGDGDGBHBCDFFFFHFHAHBDACAHDHCCGAEADBHBDFABABABEBEAECGGBHBHDFBBBBAFDDAGBHHABDDADADBE,False +971,9.0,10.0,11.0,9.0,15.0,9.0,14.0,12.0,EAEDFCFBFBAGHGHGDGBHBGFHEHCFAFAGHECGCHCADAHCEGDGCGBBBBDBDEGFGCCFHEEEHEDEAEDBCGHGCADHEFEAE,False +972,18.0,16.0,12.0,13.0,15.0,19.0,12.0,21.0,BEHFBBABAHGEEAEAFAFCDEHFHAHCGCFBEAAFGCABHHFHFHCHBGADCDHDHCHCEEAGBFDFGADFFFFBFBGDGAGAEADHDHDAEEEBCBCBHBDEEHGFGFBFBDEHCHGHAHFCAD,False +973,27.0,25.0,26.0,28.0,24.0,17.0,20.0,27.0,HCHEFEACGCFDFGCBCHADFCFBADCGHBHCDDDCBAAHAEEDADGDGHGHGHGDAAEBEHAHGDADADEBEHHCEBADAHHHHCHCAAAHBFBDCGBFCHEEFBFBFHAEADDBFBFBDGDEHEHBHGCGAHACECAFBFBEEEBECEFDCCABDBDEDEGAGADEDEDCFBBACHGGFGBGCGDADCHCBC,False +974,2.0,9.0,5.0,14.0,10.0,16.0,13.0,8.0,HBEGFBDBDHEEFHFEGDBFBFBGHFAFDFGFCFDBDBDHDHBGGCFFEGEGECADGFECEHFGDCDHDEDGFGFGD,True +975,7.0,10.0,11.0,8.0,6.0,8.0,11.0,11.0,CECFCDCHGGGGHGAFCECEAECDCGHHBADHDHDBDBFBFDAHGBBBBBBGCFFFAAEHDFCHGAGHCHGE,False +976,22.0,16.0,20.0,24.0,18.0,27.0,21.0,14.0,GDBDHEGEBFHFHDDCFCDAAGEFBFEDBAHGBGBGDFEBBADGHGFABAFAFDCDCBCAHADDDCAHECCDAAFAFGHCCECFGECECEFDHCHAHGBGBGDECECECEAEAEBFBFGHGHAADDFDBDGAFCFBHACAEEFGFAFDFDFGFGDCDGGFFF,False +977,16.0,17.0,23.0,22.0,27.0,15.0,19.0,22.0,EEGGFDFHCHEEAEDEHEHGCEFGBEBEBHBDDCBAHAHDGDAEGEGDHFECBDDDHDCGCFAAAAAFCEHBBEECEFDFDBDBCCCCEFEGAFFCFCFCEBEAHAHAHAGGHGHCHCBGEDBDGEEHCDGHBCBDAHFHBHFGGDHDEDAGECECBCDCG,False +978,5.0,8.0,11.0,18.0,14.0,13.0,11.0,18.0,HFHDBAGHGEFEHCGGEGDAAFHFEFEFDHDGCECHHEHEDEDHGHDFBFCDHHHAHEHBCBCBCDCDGDECEDGDEBFGDCDEBGHFBFDCDFHFDA,False +979,22.0,10.0,19.0,14.0,19.0,26.0,19.0,18.0,HBGDGHGCGBGEFEAEFBDEHEAAHGGGGHDHDHFGEABAFAHEHCACFFDFDFAFECGCDCDCDCFCHCFCHAHFDCBGAGDEHBGEAFAHAHEFAGHEAGACEEEFFFFEFHFBFCFBACGCAFAFCBEFEGEFCGBDDDCAAAH,False +980,9.0,10.0,16.0,13.0,13.0,13.0,17.0,6.0,CDCEBDGFGFACEBDHFCEHACADBDBHBCBGACCECEFEFGFGACHCACDEEGGGEGEGDGCFFFGFDBDFGGAGAHACDDDDGEGFCFCEHBBEB,False +981,19.0,23.0,15.0,12.0,16.0,18.0,17.0,17.0,ECEDHFHFHFAGAHBHDAEFGFBEHGBGBCBHBCEDGDCBHEAGADEGHFHDBBABEBAGAGCCDADHDCGBBBEGAGAGEBBBGFGFCCBFBFEGHAEGHFCFCFCACEDHDAAAAAHDBFFHFEFCBCBEBEFHA,False +982,21.0,16.0,13.0,14.0,20.0,12.0,19.0,12.0,EBEBGBGDGEGECHCHFAAEHBCAEBHBECECACGCDCDCDBABAFABGHGHAAEAHABDEDEFHFGBCDAEAGFGECDHGFGDDDEHAGGGEGBCFDFAFBEGECEHAFDFGABADAGAEBHFAEB,False +983,22.0,16.0,20.0,28.0,16.0,18.0,28.0,14.0,CGCGBDCDCGHACGFDFDGDBDCFEFEFADAECBDDDEAEAEAHAHABGDFAAGFGFGCAAGEDEGFDFDCGBGAGBGHHHGABCBDBDFDFCFDFGCAHAGACABAFEFAGEEDEHBCCHEGBBBDBDHGEDCHCEFAHHGCDHGGFGDGDGDBEGACDCD,False +984,26.0,22.0,19.0,22.0,24.0,27.0,32.0,24.0,ADHHEFAFADABADAFABCGCGAGFGFEDADABEFHFHGHDFGEGADCCFHHHGHGEFCFCEBDGEFEFEGAFBFBFAHGBEBEAGDFAHABAEGHGCECEHBHBDCFFHBAAGAEAGBCCDCDHDHDBDBGBEDDDCBBFBGEDFDHGEGEGEAFAGGBGBHEGBGFGDECHFAFEHHFCGCGEGCCHCHAAFDG,False +985,7.0,9.0,7.0,9.0,13.0,11.0,7.0,5.0,FCBCHEDFAFHEGBGFAEAEAEAFGDGDBDBABAFGEGDCHCHEEBFCEEHEBEDEFFDFGBDBCCFD,False +986,8.0,13.0,17.0,13.0,13.0,11.0,14.0,10.0,HGEDFDFDFDHDHDHDBFEFAGAEBEDGDHHFBBEEABBBFBHGHCCBCEEGECFBACDCDAAGCFCGBGFFEAGDGHCCDGEGCGCGCHCECBCACEB,False +987,20.0,12.0,18.0,25.0,18.0,18.0,21.0,30.0,AAADFHFAADFECBCECEHEHADCDGDGDCFHFHGCGCGFGFCFHDCAHEEGDGCECHCHEBFBHGHGEFHBHFGDADEDHDAFADEHBBBEGEFHADFDBCGDHHGHGHGDGDHDGDFCFEGGFGCAAEAEBHAHADBHEAADHDCECHDADHCHBHFHAB,False +988,20.0,13.0,12.0,16.0,10.0,14.0,25.0,12.0,BBBCHGHGAGFGHGDCACHCHCAAAAAAEHBDBAFDGDGDFCGGEBAFDEDEHEDGDEDADABCBFDGAGAGHGAEDBGGGGDGBFBHAAGBGHDFEFGAEECCGFFBFGFGHCHAFFCACD,False +989,12.0,14.0,12.0,10.0,10.0,5.0,11.0,8.0,AEFEBABAHACGFBABGBGDEDGDEBBCBCHCECBCACDCGHGHGEACFCBBBEFGDDDCDBDADGEHAACHEGAGFBEHAH,False +990,22.0,22.0,18.0,21.0,13.0,23.0,11.0,18.0,AHAHEFFDDCDFGHDFDECHDHABEBCBCEAFBGGGGFCHCBCHHBEDFAFABCHCBCBCBABDDGHHDBFGEEDADFECGBAECEADADADAFFDFBFBFBFAHDFDBHBDEAEFHFGAHAHAHACCBBABGCGCFHFAFDFDEBCA,False +991,10.0,6.0,7.0,9.0,6.0,4.0,5.0,5.0,FDCBCGFHFHBBBABGDFDAGACACEEECAHDDGDEAAADADAECECHDBGH,False +992,9.0,13.0,4.0,15.0,7.0,15.0,17.0,13.0,DEAHFHGHBEGEBBGFFFAFDFDHDGDGHGHFHFDDDCEGBACGDBDGDEHEHGHGBGBGHFBABABFFFAGADHDGGGHFACBFEDDBCAFB,False +993,1.0,1.0,4.0,3.0,4.0,6.0,1.0,3.0,EFEFEFAFCEGDFHHHDFCBCDC,True +994,16.0,14.0,21.0,15.0,11.0,19.0,16.0,24.0,AHACCCDCAAFBFEFBDBAAGAHHCHDHEHAHEHEBGAGAFHFCGCEFEFEDACHCHCGGGFDFCHCDDDHDHAECHGBGBEHCFBDBGGFHFGBAFHFCDADCFCBCBCEHAHFHBCEGGGFAHBHDCDFHFGDB,False +995,7.0,6.0,13.0,6.0,12.0,13.0,4.0,9.0,CEAFHCHFHECCHEACFCFGGAGFCHCHFAFEDHHCECFBDBDGECHDFEEEEEEBABACFCFDFDFBAB,True +996,4.0,9.0,13.0,8.0,5.0,3.0,3.0,5.0,AGAEADDCACBCBCDCDEHECCFHEDBCBCDDDFEBHBHCCCBBFHGCGB,True +997,3.0,1.0,1.0,6.0,4.0,5.0,7.0,3.0,DDDFHEHCGFGFGFGEDAGAEHFDEDBGAG,True +998,18.0,17.0,15.0,15.0,11.0,15.0,12.0,20.0,EBCFCHHAACHCHCHGBCBCBCHDADAFAFEFDFDGHGHCBCFFHCACDFAFAHAEAEAEFEBCHAFBHBFGAEDBDHDHFBCDEAGABBHGADDBDBDHHHEBAGCEEHFHBGGDGFGAGDB,False +999,6.0,13.0,8.0,13.0,6.0,19.0,12.0,12.0,GDGCGCHCAFGFEFBFDEDHFBFBDBGFDADBFBACGBGDGEFBHHHHBDAFGFGBGHCFFECEFEFBAHFDFBFDAHCHDHCHDFDGB,False diff --git a/tests/results/nb_gm_002_2back_240trials.csv b/tests/results/nb_gm_002_2back_240trials.csv new file mode 100644 index 0000000..1c50201 --- /dev/null +++ b/tests/results/nb_gm_002_2back_240trials.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,ralph_skewed +0,30.0,39.0,31.0,30.0,32.0,24.0,27.0,27.0,False +1,33.0,23.0,27.0,32.0,37.0,34.0,25.0,29.0,False +2,31.0,20.0,37.0,28.0,31.0,32.0,26.0,35.0,False +3,27.0,32.0,39.0,24.0,25.0,34.0,35.0,24.0,False +4,34.0,24.0,38.0,28.0,31.0,29.0,28.0,28.0,False +5,29.0,24.0,36.0,31.0,32.0,32.0,31.0,25.0,False +6,25.0,38.0,28.0,30.0,33.0,30.0,26.0,30.0,False +7,27.0,30.0,30.0,29.0,32.0,26.0,33.0,33.0,False +8,24.0,36.0,32.0,23.0,30.0,29.0,35.0,31.0,False +9,35.0,34.0,30.0,29.0,35.0,26.0,23.0,28.0,False +10,30.0,25.0,33.0,31.0,27.0,37.0,30.0,27.0,False +11,28.0,28.0,29.0,26.0,28.0,27.0,34.0,40.0,False +12,35.0,27.0,30.0,29.0,26.0,30.0,36.0,27.0,False +13,38.0,27.0,31.0,27.0,34.0,23.0,27.0,33.0,False +14,29.0,30.0,28.0,35.0,19.0,30.0,37.0,32.0,False 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+996,0.0,3.0,3.0,4.0,1.0,9.0,4.0,0.0,True +997,2.0,2.0,7.0,2.0,1.0,4.0,1.0,5.0,True +998,0.0,1.0,5.0,2.0,3.0,7.0,4.0,2.0,True +999,3.0,4.0,5.0,0.0,6.0,1.0,3.0,2.0,True diff --git a/tests/results/nb_gm_002_3back.csv b/tests/results/nb_gm_002_3back.csv new file mode 100644 index 0000000..08f6266 --- /dev/null +++ b/tests/results/nb_gm_002_3back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,8.0,9.0,10.0,10.0,12.0,10.0,10.0,18.0,BAEBGEFGHBGFBHAAHEAFEAHDFGGGDCGECFECFCCHDCHEBBFGHEEHGBACBFCHFDHCDBADHHGHHEHFDHCHEDADDHE,False +1,9.0,7.0,10.0,4.0,4.0,7.0,8.0,17.0,DBFCHAAFAEBCGAFHCGHCEHCFHCBHCBHFBHCAACBGGAHGDEDDFAHHHHAHEBHGCHGHFG,False +2,9.0,7.0,13.0,9.0,10.0,11.0,15.0,18.0,DHFHHEHHECHCFDEGEACHBBHDGABGACGAEFHEGHCGHDAFDGFDGEEBFGBAGFGGFGHADHDFCBHAGHCECCFFCECCGCDHAHHB,False +3,8.0,10.0,7.0,13.0,4.0,6.0,10.0,10.0,AHBADGDGGAGCAEDACHACHCBDDHHFCBCHBGHBFHBDDGDDADBFDFACHGBHGBEEDDEFBGFG,False +4,15.0,14.0,25.0,14.0,12.0,14.0,11.0,13.0,CCECCDCCDBBGBCFCCDCCDACFECBEGBFGBEABEADADHCDECDAGHHGCHCCHAGFDHFABAHBFBGFEFFDHFEFACHACGACBAGBDEEHFCGABHFDDFEDECCHCABAGH,False +5,11.0,10.0,18.0,13.0,21.0,18.0,16.0,19.0,BHADHEFHGHEFHFCEBEAFEAFDADCAFEFHAFCBHGAHGCGECFFFBEFCFHCBACHEDHGFHGFHDDHDDHCFHCHEAEDDDHBDCBDEGGECGECBEGBEFBEGEGCEGCGAEAHEGCCCFG,False +6,11.0,14.0,16.0,20.0,10.0,15.0,24.0,14.0,BGGBHGBEGAAGHGGBFEHFEHGCGDCGDHDBBDFDDGDDGFFGCADFECFGAFHADEFCFDGFHFHGBHGAHFBHCCEDDHGDEADGCGGDHBDBADGAECEHCBGBBGCBCCDCEACDACFF,False +7,16.0,20.0,19.0,22.0,15.0,27.0,25.0,20.0,HCFHAABBCDDDFGDGCDEDGHAGHEHDAGEABEBBDGDGGFGEAGFCGFCFBEFBEGGHDFFBCFCAFBDFBDFGAFGAGGDCDDBHDHFFFEFAEBDGBHCBDCFGCACHEBHDBHEGCECBFGBHGCHACEAGEAHACFCHFGDFGDFBFEHCDHBFHFAH,False +8,4.0,10.0,2.0,8.0,5.0,8.0,6.0,5.0,HAGFEEABEAHCFBBBBBBBFBHHGHFADDBEDGDDGDDEFCFFGDFG,False +9,11.0,23.0,19.0,24.0,13.0,20.0,28.0,13.0,DFDDFDGFDGCDFFDFEDCCDEGDAHEEDGGGGDAGHFBHFGEDAFGCHGFDBCDBDEBCHDEBGEAFBCHEFEAFBHFCCGEDGADGBCBCDACGCCGFAGBBDCGDBBBEBBECHACFAGFBGABCBBGFHHFHHFGHGGDGGBGBCDB,False +10,10.0,15.0,13.0,9.0,5.0,13.0,10.0,23.0,CAHCFDCFBGFGCFHBHAGHABAAHGFBAFDFBDBHDHCBGEFGDCBDHDEABHHHHGCFCEFCDHCFHBHHGHHGFHGBBABCABCABHEHEFHDCH,False +11,29.0,21.0,32.0,27.0,25.0,25.0,8.0,18.0,HEFAEFGCBEBDCBEADAADADCADABDHHFFEDFBCHACAAFBAFDAFDBCCCFDCEACAACEABFDCFDCFHHFBHDEFDAFCABGAEFDCDCCBCCDCDFAEFDCGCCECCBCBHDEGACBAHBEBEEFDBDHAFHAEAEECEGGHDBHDHCDEADEAHEHFEBFCBAHBHDEGAEFFCFCG,False +12,28.0,27.0,32.0,14.0,15.0,33.0,26.0,13.0,FFFAAFBAHCHHDHGCBBCEBFDGEGBFAACBACBACBAGBGBAGFFGFAHDGHEEFCAAHAHHECFBBFACFACAACDBCAEAHDFHFFCFFEFCAFBEFBFCBCABDBGGFECFGCBCDGGBGFDGDABBCCBEFBEFBAFDACGCCEHGAFCABDGEDFFDCFDGFGGCGGEEGCBGAAGCCCHC,False +13,29.0,16.0,17.0,15.0,16.0,11.0,15.0,11.0,CBECBEFBDDCDCAACAABFAGFEGACCECBEHBEGADFADFBBABCAHCABAABHEEEACEHHAGHABACGDHGDFGCHGCAGDAFAAFCCFEAEBAEDFDDGEABHAGAAGDGBAEDHHGABFEGDCD,False +14,17.0,24.0,25.0,11.0,18.0,20.0,15.0,30.0,DDCDHHAABGECDACBCCFHGEDGAHBABBHFBFFBCFHCHECHECACABHHBHEBHBHDCHCFBAHBFHBEBEDCEDEABCHCHFCHCAFBFBBHGEHGEHGHFCHACHCGGCGCDECFEGHEDFBAFGEFDAAHAHHGFHFABGEBGABGFFEFCEBC,False +15,8.0,6.0,1.0,3.0,4.0,2.0,2.0,6.0,EHBEDEHGEGFABBADBAHCAHAABDAHHABF,True +16,20.0,17.0,20.0,17.0,21.0,21.0,26.0,21.0,DEHCHAEHFEDFDHFCHGCGGCGAFBDDBDCFGEFGEFCEFHDHEFFAGDGDEGAHGFECFACFEEHBEHBGHBGHBGCECEDAHHBGFCCCADHAGHDEDBADGHEBDCHCCFAGEAFAABGABAHBAHBGHCACBEFEGAEFCECBGFDGFDGAGBAGBFG,False +17,12.0,3.0,7.0,9.0,7.0,12.0,9.0,8.0,ADGAGCADCFDFHEFDGHCEHAGGCDAHDCHDAHAFDAFEGFACFECFEBFGBAGAFFAEBDEHGHF,False +18,18.0,19.0,24.0,16.0,21.0,13.0,23.0,20.0,GGEGFBDFGDGEDAHGFBGHAGCDGCAAAHACECDECEBBEDEEDECDFDHBCCDHBHHACBACFHEAEEGHEGDEGAHBAFBEEHCBHCBGGFCGECGECBCAFCGHCBHFHHFHDGGAAEBFCBFDBCBECDCADCACGBHGEHGBFGADHA,False +19,10.0,14.0,15.0,8.0,25.0,14.0,11.0,20.0,EEEEBEEFHEHEEFEEGHEAFFAFHACGDCDDCFDCBDCBFFBCEAHEAHGCGGHGCHEEAEAHEAHEHHCCFGHABHGFGCHGCFDFHEHBBBDFBFBCEAEBHCDGCEEEHBBHB,False +20,16.0,9.0,19.0,17.0,10.0,22.0,10.0,24.0,HFGDDAFEAFEDCGHAADEHDBHAHDCGBAHBECEFFFFFEFEEDHEDCACEGHBGCFGAGGABDHFCHFCHCCDCFHHADFCFFCFFCBFCDHHHHDFFGHHDACDAFDACDCBHCHHAGHABHAB,False +21,6.0,10.0,3.0,4.0,7.0,3.0,3.0,4.0,EABBAEFHEFABAACHDCDDEFBEGHEGBDABHBBCBGEB,True +22,6.0,11.0,12.0,6.0,9.0,6.0,9.0,10.0,AEDBCDECBCHBCBBGFBGFHGEHACHAGAEFBDAECHCFHFDCCECGBCGECGAHGBHBHEBHDFGDE,False +23,11.0,8.0,12.0,13.0,7.0,5.0,13.0,9.0,EAAGACDACDHEEGGGGGBEGEABEAHGCHCCAFCFFGDHGDGCBGBDDEAFAADCDDCDDHBCGBCAFCBDDHHBHH,False +24,36.0,26.0,18.0,26.0,33.0,19.0,21.0,15.0,GBCHFHAAHAFFGBBEFBCFAEFDFGEGEEBECBEBBABBAEBEEAEEABGDBADBACFFBEFCECGACFADABCFDCDBCBBHDHHACGGEHDEGDEGAHAAFAAEDCCHHDDGDDBDGBDBDDCDAGAAFHEDHGDACDACDBGEEACGAEEBEHAFHBGAAAAAAAEEFBEDCDAEEEFGEGGHGFEAFED,False +25,11.0,17.0,16.0,9.0,15.0,15.0,6.0,9.0,CEEFABDBGDBFDFFDGADECBFCBCCACFABEABFABEGBEHBAHEAHEAECCFFCHDCBBBFGBAGCDFHHFBDFDCCHHEHAEBEGCCBFEECEF,False +26,8.0,5.0,15.0,9.0,10.0,7.0,11.0,5.0,ECAGCHDBBDCCDCGHBBEEFDHFEEEHBHGADADGFDEFGAFGAFCCCCCACCDCDGGECGECGEAGFA,False +27,9.0,11.0,8.0,5.0,8.0,4.0,2.0,4.0,FCAFDBEDBABAABAEEAEHDBHCEHCDBCFBABEEGECGBDABFCCAHCB,True +28,6.0,8.0,11.0,7.0,10.0,5.0,9.0,9.0,CFBCBCCBACBEHBEGCADHDGFEGFHGHDAFBAFBEDCDGCHGAACHCHBCEEEEDHEDGEGGH,False +29,24.0,16.0,18.0,25.0,13.0,19.0,26.0,18.0,HEFHCDEGDHFBACGGDEHDGHDGFDEAHFDHGBHEBGEGADFFGCCGDHFBFABDACDABAGFGDAGDAGCAFFAGHHCDHCHACEDDAFDCCDCAECAEDGEDGAFGFCGFAGBBGFBDBBAABAAGADGAFCHBEEGHBGCBFCGFAHHCHDBDDE,False +30,6.0,5.0,2.0,9.0,2.0,4.0,3.0,8.0,DADBAFBDFHDHHBAHEADGFBHFGHEAHDHBDGDCADC,True +31,19.0,18.0,16.0,13.0,19.0,13.0,14.0,15.0,FCHGCAEHAEBDEBABAABHAFEBDCBDCBHCGEAGEFBAFCCECCBCFHEHGEGAEDAECBECEAFEBDHBDEAGFGHDGCDGADFAHGCFCBFDEHEGCEABFADHAFHGBHABHBHDAEBGDFG,False +32,7.0,12.0,12.0,10.0,7.0,5.0,5.0,9.0,EBDGBGBBDCBACGHBDAAHEBGCBFHBFGAFEHFCCCHDCHDCHDAHDCDDEBDEAFECBAHBECC,False +33,1.0,4.0,8.0,1.0,4.0,4.0,5.0,3.0,GAECEGFBHFGHBGCBFCECCECCBCHDGF,True +34,5.0,4.0,6.0,9.0,13.0,13.0,5.0,7.0,CHHEFFDFFDFFDFDGGDFGDHCEAEAHEAFEBFCFEEFEECAECHCHFDEBDBGEGABDEH,True +35,3.0,2.0,3.0,3.0,5.0,4.0,0.0,6.0,CBDEEHHEAHCAEBDFADFHFCHFEH,True +36,13.0,2.0,13.0,8.0,7.0,6.0,16.0,9.0,DEGDECDHGAHGEDGEGACAFCADGACGACHFDACHCCHCEECGHDHBEGGGGCADCAFAGFGGBAGCAHFHFA,True +37,18.0,19.0,17.0,17.0,13.0,17.0,15.0,23.0,HBCABCGHCEEADEDCEDGAGFFFHDFADHHBHHGCHFHHAGHEHEBBBDEFECFEBHCDAADFGDFHDCDCCDCCFACAACHGGBGGBFBCFBFFCFGEDABDBBDAAGAABACBEGBAHAHHFGEDGHDHHEBHBHF,False +38,4.0,6.0,5.0,9.0,6.0,4.0,4.0,6.0,AGDAGHABHCEEFBEFDEHDBHDECDFCDBHDEGBBGCCADFDH,False +39,3.0,5.0,6.0,8.0,8.0,2.0,8.0,6.0,DCEDEEGEEGAAFEHFGHDGDBHDBGBBGECECDGHBGCDDCHCAH,False +40,0.0,0.0,1.0,3.0,1.0,3.0,5.0,1.0,GDGGDCEHFGFDGF,True +41,20.0,19.0,22.0,21.0,30.0,22.0,10.0,26.0,BADBABGCFGFDDDADEFHAAHAAHEAHBBHECFGFDEHDCDBBBHGEDEECCDCCDGCHHBGHCHACFDCFCFEDFEDAHHHBHAECABDABAAEHFEADCFEBFAGFGEABECFEFFECEEFEHFEHEEHDHDCHBBHBDHCEHCDHBDCFAEFAGHEGECBCFEEFE,False +42,3.0,7.0,4.0,4.0,5.0,2.0,5.0,3.0,EBBEAEEHDCHDCGDGGBACBEHBDGBAFBFCG,False +43,21.0,15.0,21.0,27.0,18.0,33.0,14.0,23.0,DDDDDDBCGFEFFABFDHDAGCEFHHACHGBHGBEFEHFEHFCFFCHDGHDFHDAGFECCCAAEAAGHGDFCHFCHBBBFABDEFDFFBBDBAAFDAFAGHACHACEFFEFDHABCAFGDFEDCGACFADFDDFBHFAFFBEHBEHFCHEADEGHEGCDGHDHDEECCFCCD,False +44,27.0,34.0,20.0,19.0,15.0,29.0,27.0,26.0,FGCFGADGADGDDBDBAFGAFDHHHAFBAEEAGGBDBFCEFAHFAHFAECDCBBCGBHAFHABHDCHAHHGBCGECFDCEHCFBCHBGHCABFBCFBEHBECBAHBGDECHFDFBDEAFBBGECGEBBHDBHDBEABEBFCDFHHFGHFAFFGCACFGDGGHGAABCDBHBGGBGGFHGHGGBEADABFABAAFAFF,False +45,15.0,12.0,15.0,7.0,7.0,15.0,11.0,5.0,CAFCDGCFACFCCFACGBBGCAEAEGAHFADBCHACHFCFBEFGEGBDGBDGBEGEHAEFGBFCDFBFBHACAFCAFGABDAFACDB,False +46,12.0,10.0,7.0,5.0,4.0,11.0,11.0,13.0,ECFFHGFGGFCGACGFGGAHFABBHDEDCHABFBHGAHGAHCAHDABDFHDFGCHGBEABAHEHBFHBFCBAA,False +47,15.0,6.0,13.0,11.0,17.0,21.0,13.0,9.0,EDCEFAEFAFFAGHCFCEEAFGFFHFDECECCEGCDGHDGHDGHACFFCFFCDFEHEEFEEGHEDAFBGEAAHAAGCABAEFAFDABGFCFHCDEDBABFGBGGD,False +48,11.0,17.0,17.0,9.0,17.0,17.0,13.0,15.0,GAFGHHGCHBCACCFBCFHHECHBHAFHEEGBAFCAGHGEFGEDGFCBBEBGABCFDCFDCFDBEEEGAAHDAEDFECBGCBHDBFEGHHBFGBFEBFCBCCHEFAEDAEDCEFHB,False +49,13.0,16.0,15.0,12.0,16.0,9.0,12.0,15.0,BGCBAEBCDBEDBECBDCBABDCDFCDBCEGDABDFFEHCEDGECHACHEBDECDGHFFHFHEAHAHHEFFBAGAGHCHCCHGCEEAAAAGEEGDEGBFGBAGBHHBH,False +50,13.0,6.0,16.0,14.0,12.0,13.0,9.0,12.0,DAEAAGAAGCHCCHDFHEFCCBEGFEGFHAHEAGBGCBFCBFCDACDAFDCHECEBFBAFCFFDEHAGHDEFDGCDECEHCHDGADEHHFADCDD,False +51,22.0,27.0,26.0,19.0,24.0,22.0,28.0,20.0,FDCGDAACFACHGCDGEBFCBDCBGBEGBEGAGGFGGCHGDHGDCAACHADHCFHAAEEBBCBCCBAEDAGBFGAFGEGGDGHCEEEDEHCBBCDECEBGEFCCHCFBCFBHFEABEBDEDHABHDBFFFCEFCEDHFFHBFABHAGGECAEADBGGEGAABHAGHAGEFGBFBFHHDHBEGBFCCDD,False +52,19.0,24.0,24.0,17.0,11.0,20.0,12.0,18.0,FBDFCFECGDCFBBFHBFHBAHECHAAHAFCAHCHCFBDFCDHCDBDDBAGAAGAGHFGBDABCFEEAHHGDHBDCCGCCDAEBAEFEBCHBHECHDABFFBHECFDCBDBFDGGDBFABGHBGFCFCBDCBACBFGHEACEACA,False +53,11.0,13.0,7.0,11.0,11.0,7.0,5.0,12.0,HABDABEADFFDABBHBEDAEDACBEHBEGBDDEAAHAHGBHBDEBAEDECCHFDHFGHFGHFDCCEBHEBHGCACF,False +54,11.0,20.0,14.0,17.0,12.0,15.0,15.0,22.0,DFABFDGCDCDDCBHCBECBDHHHBEFBGFEGHGFHEFEAFAHDBHDGDGEDFBAFBGFBGAGGHHCHHEDBDDBCFFCGFCHEEECDDADHBHHCDHCBHFAEGBCBBAHBAGEFGAHABHCBHG,False +55,17.0,24.0,24.0,12.0,23.0,20.0,17.0,26.0,GAECBGBFHAHHEFEGCGFBGBCHHADCACHBGGBHBAHBAEFAFGGFBCCAFCFHCGHCFHCBEFBEFBCHBGFECFGDHBEHCCACGFHEDAEBAEDDEDCEHBEBBEGEEHHACHECBDFFDFADFAEFHCFHCBECDEHDEHCBAGBAGADGBCBHHEH,False +56,17.0,25.0,29.0,22.0,21.0,19.0,27.0,22.0,FFFFFGGHDEHDFGAFGEEAFEGCEADDBBDHDCHECDGCDAAFCDHBGCBGBBECCDCCDAHGBHCBGCHCCEFEGFAABBEHFEHBCGFHGCHBDHCDHCFBDEBEABEDBCDGCHCCFGCFDAGGBGBBCBFABFEGGADGHEGHEDFBBCBCGACDAEEABDADGGEGHEGCCHHAHH,False +57,12.0,11.0,4.0,15.0,9.0,3.0,6.0,8.0,HABCEHAECBEDEDDHBDGAAFHAGCBGBEAAABADEADGHDFBAFBDEBEEBGDCDDGDDHDAHDBH,True +58,9.0,8.0,9.0,9.0,4.0,9.0,12.0,13.0,CAGCGGCBAHDEFDHHGHDFDBFBBFGAFEBFECHABGGDGDEGDHGBHADGFDCACAACHBFHFGHCHHCHA,False +59,15.0,19.0,20.0,23.0,14.0,16.0,21.0,18.0,GDGGBGGCFGABBABFGEFGCDDCFBCDBEBACHABGEBCDCCDFDDFDAACEBCEGGGFHHFDHGGHFGADHFHHGDHDFFGHGGHDEBDCAACGACFADDHDDCBDBBFEBHDDHFCEGBEHCABEAHEAHEFCCHBAEBCEDC,False +60,9.0,8.0,2.0,6.0,8.0,11.0,5.0,10.0,FEBDCDFHFEHFEHEGHBHFBHFEDCHBBBAGEAGEAGHADABFHFFDBFAEFADAAHG,False +61,26.0,25.0,20.0,16.0,13.0,13.0,17.0,12.0,CBACHGCFDHEBHBBEBBFAHCCEAEEABDDBDGEGADGHDAHEABBBEFCFFDEFDAGDADBBHGGCEGBAADABCHGCHGBDBBGCBGCHFAEFCHFBFDDCAACHACFACAACABFEBFAAEGGCGBCGBAGBDDACAA,False +62,9.0,9.0,5.0,7.0,5.0,5.0,11.0,6.0,FAADDAGBGGBGBCHBCAGEADACGAHGACFECDABBFEFDGGDFGHBGHDEHBEHB,False +63,7.0,8.0,8.0,6.0,13.0,12.0,11.0,4.0,GGBDGFEGCEGCECHDCFGFGABGFEHFCGGBHFBHEGEEAEEAFEDBCFBDFDEADACBABFACFEEF,False +64,20.0,11.0,23.0,13.0,16.0,11.0,12.0,18.0,AEDAHACHEFAEFAHCAEDAEDCBAGGCBGFBCHCHFCEACHCEHCFHCEAEAAEAHCAGBDCDHCEHEGBFCHHCGHFBHFAAGEADHBDCADCFDGFDCHDCBGCGAAHCGFGDEBDEBECB,False +65,19.0,12.0,22.0,18.0,18.0,14.0,20.0,17.0,CCDCCAFHAECADDGDGACGADGHDFHEBGEFEAFDHBDGBCGCFHBGHEGAEGBDHFDFDCGDHGDAGDCBHEBHEBGBAFHGCGCCFEEFCDCCDCHECHFCFAAAGECHBBEEBHDAGAAEAAEAHEGHCFCEFGAD,False +66,26.0,13.0,22.0,33.0,10.0,21.0,25.0,20.0,CDFGDFAHFEHDHBBCDECDAHDGGGFBCDBADHHDGADEBDEGDHFFCFFDHDGADHCFHDAGEGCEACGBGGEAGFAGBBDABCABGADGAHADDADCADHAFCFGDGEFBEAHDCGDHDCADFADFGHCCHGFHCFHGDHGHGECCCCCADBFDGAABAFDAFDAFC,False +67,3.0,0.0,0.0,5.0,2.0,3.0,2.0,1.0,FDFEDHDGAFGADEAD,True +68,21.0,30.0,10.0,18.0,20.0,13.0,15.0,10.0,ABBHBEEEHDEHDGFFGDBDBBCABFGDCCDHFHHAAAAABFAEEDBEDBGBBEABEABFBBFBBDDAEEAGCFHEBAFAGDGGBBEDBHDFEFEEBEEBABDHBFBGCBGCGGBGCCGCEGAADAABCDDADEAHF,False +69,23.0,30.0,20.0,17.0,29.0,22.0,24.0,20.0,BHBBFBBEEAEGAEHBCABCBGCGEFHEGHFFBFCBFCHEEDEGCCGBCHFHBAACDGBFBEAEAFEHFEHGHGGACBEDDDBDFBGBAGBAGEDGEHAEDDHGDFEDFEHFACCAEHFBCGBCECFGFFAEGAEAHHBGABGAEGDCGDCHDBBEFAECDHCDHABAFBACBAFBFGEDEEHGB,False +70,16.0,21.0,23.0,21.0,35.0,31.0,21.0,19.0,FEGHEGHEHFBHEBDEGDABDAGFAGCDGCEAEABGGEFEBAEBHDFEFACFEHFHHEBFGGDGBAGBAEEAFBACBCBDFFDGEECFEDFEAFEFFEDFBBFHFFCGFBFCECEHCHFFHGFDGFHECEGCDDBDDEECCBDHADHADEEEECDBCBFHGFHGBCGFCHCCBGDEEAEHAECDCCF,False +71,21.0,21.0,25.0,23.0,34.0,29.0,19.0,27.0,CGCABAFBECCEGAEFEEHEDHEFBAFBFFGFDCBDFHDFDDHCCAEGAEGEECFCDFGDHCDAFDFFHBAEGDECFHHFHHEAABFABAAHCCCCHHGBBCBHGGHEFDFFCGFDGHDAHAGHCEEBBEDBEGEHBEGCHAEHDEHFEBDECFHABHABAAFDDFDDFBEFGHGCEECFDCDCEECEEAHEGHEFBBG,False +72,26.0,9.0,19.0,24.0,24.0,27.0,21.0,27.0,DDGBDCADHEDABHHHAEHAHDCHDBFFEEFAEFAHGACFFEEDHACFCCFGCDACDCCDCEDBADHFEGDHDFHGCHFAEFHDFGFGEFGEGGEHEHHAHFEHCAAEAFCHDCFFFGABAFEAGGBGHCHDFHDAAGAFCADGADHAGHBGBBEEEGEEFAEFAEFCGDCFDHGDH,False +73,24.0,24.0,23.0,19.0,22.0,18.0,26.0,30.0,HGFHGHHBBHDBAGCEDEHDHCDAAGCBCCHCCDGGHAGHGHHFAEFGEGBEBFDFAEAHBBHBDCBDCBCCDECHHFHDDHCGAAAAEAEEDBGDBGCFACGAHGDFGCGHABBACBAHGHHBHGBEDDACFACFEBFGHCAEBGEBGEDGEDHEFFECEEAEFGGHHFBBFCHFBAFGAEHACD,False +74,26.0,17.0,19.0,17.0,28.0,19.0,13.0,23.0,EGCAHEHHEHABADBADECBECEEABEACFACACFFBFGBFBDFCFCCACAHEBHEGHDBHBBAFEADEHBCHEEHEGBFGBFDCGDEFDEADEDHEAAFFEFFHHFACDCCEAHDADDEEEFAFGADBHEBEAGAGDAHBCHCGHCAHGACGEEFAHGHHD,False +75,3.0,1.0,2.0,0.0,2.0,1.0,0.0,4.0,EAHBCHCAHEAHF,True +76,10.0,5.0,4.0,6.0,10.0,5.0,10.0,8.0,HGHHAEEAEDAECGDCAHGFBGAGEFGFBEFAFCGCEAEEBGEBGDDHDBHDAHGAHA,False +77,6.0,2.0,4.0,1.0,4.0,1.0,1.0,0.0,AACCDECAEBAEBAGFECA,True +78,26.0,21.0,24.0,22.0,21.0,23.0,16.0,22.0,AEAFDAFGAFHAHCGFCGFHDCBDCBABADBCDGGFGHEBBDFBFFDCDEAEEGGFHAHDCDDBGEHCEFCHFGEFDADGFHFBDFCCCBCGBCABDFHAEBCHBCHBCDECEGFFAHFAHFCHFDDCAEHAGHBGHBAEECDDDDAABAHECHEBHEAHABGEBAEACEACEAF,False +79,23.0,23.0,29.0,21.0,13.0,23.0,22.0,17.0,CDHBACEAHEFDEGHAGAAGFAHFADFCBBBEFBCDGFBCDBDHGGGGCGFBDBBCFBFDEGEEHEGGBGEHFCCFCBDCEDAEABFDHHBFBBCAGDDCHDCHDAHBACAGCAGCADDBDFHAFCAFCGHDEBGHBCHGCHFBEGBFACFCCACAADACFACFCCFGFDG,False +80,12.0,12.0,23.0,9.0,27.0,13.0,18.0,19.0,EGFECEECHEBEEHHFBDCGCAACFBCGEHEEGCEACEGDEADAGBAGBCDBFBHFHACHCDHCDHCECCEGFHGFBABCGDCBDCEACHBCGGAEEAECFEHHAFFEEFHFCEFCHGGGGDHBEHGGHEEHE,False +81,25.0,15.0,14.0,17.0,20.0,16.0,15.0,15.0,DGDFFBFFCAFHADGAEEAFDABDEGGEBGDGEDEBAHAAEGABAHCACEACAHBAGGECFCDDEDBEFHEBGAFCAFCAHDEHDAFAGFCDBCHCCHCEDBGFGHBADBHGBEAAHAAHAEFECFEDFEDHEBHGB,False +82,23.0,16.0,15.0,28.0,9.0,16.0,15.0,26.0,FAHGHHFHGDHGDHDHCCHFBHEDGDGADGBDFDHFBBEDBADEDDBDHFDACDBFGBFAHCDDDGDBGBBGAAADCHFCHCDGABFHDDHDAEDCEDCGDFEAAEACHHGHDGCFFCHABHAHHAFCFHAAHAACBABBHFEAGEAC,False +83,16.0,17.0,21.0,14.0,11.0,17.0,24.0,19.0,EGHCBBCBBHFAHAAGAFGHBCDFAGFBDABDADEEDBCDBCHBCBGEGFFGFGGCHGCGGHHADHDHCDHAFGACCEHDGHFFCDFEDAHDFFAFFHEGBDGCGCBECECHBGHGGHCGBCHBCEGFGGFCACAABAE,False +84,25.0,24.0,34.0,20.0,21.0,23.0,18.0,22.0,GCCGAFHHFBGFBCFBDFBGFCGDEGCAHEBCAFCBFHEFEDCGFCAFCHCHBCHEAHAFBAFDAHBHBDGAABAFBACACHHCFDAFDGBAHBEBBEDFCFECAEBGFHECCCCCCHHEEHAAFDGFDHBDGBEFBEDDHDDEBHECCECCEBAEBAGACGEDGADCBCCGGCDEAGCADCAFHHD,False +85,14.0,17.0,15.0,14.0,15.0,14.0,16.0,10.0,GGCGDDEBFFHGFBGFBHFHHEDAACAABGFFFCDBGBEHBEDBFDBCDCDGCDEFBCHBEGBEGBEFHGFBAEBCEFAAGGCHCCFCCBCHEHEAACADDEDDAGDAGEAEBAG,False +86,5.0,2.0,1.0,1.0,1.0,1.0,3.0,1.0,ADFAGGAHGBEABCA,True +87,28.0,33.0,23.0,19.0,20.0,25.0,30.0,22.0,FFGDBGHBGEGAADDHGEEDEHBBACDFCGFCGEHFBBFHBFBCCGCCFHDFCGHBECBAAFFDBBCBECGGFEGECCAGABBABHAEHBBHBHDEFDCHDBAFFDDFAAHAAHCDFCAHEAHGAHFAHAGHAGAAGEEDFGBEBECBGCBAFBGCCGAFAAFHAGGFGGBGGBDEEGEGBFGBFHBCHBDDBDDBECCA,False +88,27.0,30.0,28.0,20.0,23.0,12.0,23.0,29.0,EGBCBBCEBCHHGDBECBCDBEDGEHGAGACGEHGCDACFECFCBHBBFDAHCACBACBEFGGAGGADAAEBAHDFHDCDBAHCHHBHABGCBEEDHGHHGFHAHDAEDABDGCDECDBADBHHGHHGFGECBEABDHFDGAHEACFGCAGCABCHBFECHCBFCBFAEABDAGEHEEAECABDHBHHCEBG,False +89,14.0,15.0,7.0,17.0,10.0,11.0,15.0,9.0,CHBADFABGHBGFGGAGGADGDEBHADHGHGFDFDDCDBGAAGHAGFAEEBBEDBEBCEBFAFDAFDFGDEADEGDFACCCGBHBBHABHDEDCBDFE,False +90,5.0,3.0,3.0,1.0,8.0,0.0,6.0,3.0,CCACEGHEGDEGBBAHEHGBAGEAEEAEG,True +91,0.0,0.0,4.0,2.0,4.0,2.0,2.0,1.0,GDCFDCEECGEHFEC,True +92,14.0,4.0,7.0,10.0,8.0,6.0,12.0,5.0,DCDAEFAFCECEEAFEDFEGCCGACBDGHFAHBGEBGAGGAGGDGAEGHHGAADAFDADDCBAHDA,False +93,10.0,8.0,8.0,3.0,8.0,14.0,16.0,15.0,FAGFDGHDHHEHEEGGFFACFHEHACCACHFGHFGHCGCAGCGBCFFEGFGBHABHFDHGBGBHABHAFFAGFEHEEBBAGG,True +94,21.0,25.0,21.0,30.0,27.0,13.0,12.0,17.0,HHBEBCAACEABDGDGBDFBGFCAEHGDCADCHDCEDFEDCEDGDCEDAEGEHAADBBDAADHCDHDFHBEEBEEBCEGAECDEBBCGAHEBBFFHEBHEHDAHDAECFFDFEDFBDABDCCACEDEBDHDDAGFAEABECBHGFDDFEDCCBHCBHGBEGBACBA,False +95,4.0,6.0,6.0,8.0,7.0,6.0,6.0,9.0,EDGEBHEFHACBBCFEGHCHDAHDEHDBHDBDDEHFCGECGFGBFACFAHGD,False +96,8.0,5.0,5.0,6.0,5.0,8.0,12.0,12.0,AFACCAGAGGFBEHEGHECFDFFDGFHGAHGHHFDGAGCAGEFGHBBHEBHDDHDHHGCBA,False +97,20.0,25.0,21.0,20.0,27.0,26.0,25.0,26.0,BFCFGDFBECHDCEBGEFGBABHGDDGAFBEBCEFEEFGDAHFBHEHHCHDDHGEFDFFBGBBAEGCCFDDABEBBEBFHBHHBCCECEDCAFCGFGHFCBGHBEAFCBFDEEAEEAFECEBBGGAGHBDHFHHFHHFHHFHHEEHGCDABGABGACGAFGAGGDDEDDCADCFGAFGDCAHEAHEAEGC,False +98,4.0,3.0,1.0,1.0,6.0,1.0,5.0,3.0,BBAHAEDECGEAGBAGEEGHEGHF,True +99,21.0,17.0,15.0,21.0,17.0,23.0,10.0,21.0,AHDDHEDGFFGCFHDHAGHGHHDDFADFABHDBCCACAAHGDDFDDFGBHEBHBHEEHEFCFFBBDDBAABCEEHDACDHCEEAAEBHBFABFABCABFFFFDFFDFEEFCEHCEBDEBFCAGAGGDGCHBCHAAHEFFECAADH,False +100,21.0,17.0,13.0,22.0,21.0,22.0,21.0,31.0,GCAADDGBDEBDABDGDGGEADEDDFHHHEHDGHFGHFDHGAFAHEHDCHDHFEBGEACDACGABGABGFGGDGBHEEHEFFGHFABDHEDAECBFHAGHAHBAEAAEAFEHFEBGGBCFDFEEAHCHHCFDAFDCFDBFHBAHCHHFFGEHDECCGCBHFHHFBHBE,False +101,3.0,4.0,2.0,2.0,2.0,1.0,2.0,2.0,BCFBEABEABHADGCHGD,False +102,3.0,5.0,4.0,4.0,2.0,1.0,3.0,10.0,BGHBGHCCHCDHEHHABDFHDBHEGCDAHBAH,True +103,22.0,16.0,17.0,17.0,11.0,10.0,13.0,12.0,DECDFCDFEDCCBCCBCADGAGFAEAAHHCGECAAFHAHBAGEFDEFHHGGFBFCBACBABDACDAHDAGDGBDBADHFDBCEHGEHGDHABGBCEDEEHBAABADCGGCFCABDABA,False +104,12.0,15.0,10.0,16.0,25.0,15.0,20.0,17.0,GBFDCFDGDDBHDAADEBGBDEBEEFGHFGHFGHCGHEGDEADHBDHGGBGHEDCFHAAHACHGGEGGEFEBFGADCCEBHEGFEHDEHEEFAGDCHFEEAEEBCEGEDBEDBECBFFBHHCAFAEGAFB,False +105,7.0,10.0,8.0,8.0,6.0,8.0,6.0,10.0,HBEHAGHFGHBGDBAAGCDEHFEBEHBEBCABAACDFHBCHDFGDFGDFHCHCCACBFDBEDF,False +106,17.0,20.0,9.0,15.0,13.0,17.0,14.0,15.0,FBEAGDAGAABAHBGEFFBFFEDHEGHEGHEFHFDBBCBBDBCHCAHGAHCHBEGFDGFAEBAEGADCAHBDFBDFDFBABHEFGBCDAFDBCAGCFBHFBAFAEDHEDCEDHBDGGHGA,False +107,5.0,5.0,1.0,5.0,1.0,5.0,5.0,2.0,FABAAGDGFDFHBFEBAGBAGBFDDHGDC,True +108,17.0,16.0,20.0,15.0,16.0,19.0,21.0,30.0,CBHCHHDDDGADGAFCEHEBHEFEAAEBHFHCBGFAEDHEFEFFCFFAHEHHAHBGCDCHFGHBGFCGFBEABFBHHGHHGCHEAHEADABGHBHHBDHGDHGAGGBGGEFCFFCDBGDFDAECEECGCAGCGDCFDFHHAHHDHBBCCACGAC,False +109,19.0,26.0,19.0,10.0,27.0,23.0,8.0,14.0,EBCAAAGFADFADFEFBBBCBEABEABEAEEHEEHEECEBGACCAFCBHCDCCECFBCAGGAFEAFEFBHHBDFAHEHFEGFHCFBBHCCABCHFFBFFBDGCEGEBAEGCFFEEDHFFBFBADBDBBDBBEHEEFCHACBAHDEE,False +110,19.0,10.0,10.0,17.0,15.0,14.0,13.0,9.0,EACEADEDDGDAEBCFACEAEBFHFFGDFEDBBGBHGCADCFBBBHCAHEAHFAHAAHCDGCDGAEGAEGEDDFGEAEBAGFCGDGDDABDFCDFGFFAAEDFEHAH,False +111,6.0,10.0,13.0,9.0,4.0,7.0,3.0,10.0,CCCAFBAFBEHDFBCCBCHBCBCGHDAHDAGDCDFCHCEHDAFDFHDHHDEEBFBAGBCHBC,True +112,14.0,15.0,18.0,9.0,20.0,11.0,10.0,7.0,DEFDEFBEACFGEFCACCBGGBHAAEBEHCEGGEDEEFEEDBECBABGADFADFADGCHCCHCHACEDHEGAFAEFBFBAEACCAEBBGBBGEBEBHCCDCCFC,False +113,18.0,25.0,13.0,24.0,29.0,22.0,19.0,30.0,HCAHEABDACHBBDDHADBEHEEHCABCFBHFBABBABDHBEHFGAFGFHCHGCAEFHEFHGHCGCEHDDFEBFEFFDDHDEEDGEFCBGBDGAHHCHDCFDEEDGCFHHFEEFGBGGEEHBFAGFDHBEGFEDCEDEBDEFHEAHEAHABBEDBGFBGEHGAHFADBADHADHEDBGGB,False +114,13.0,9.0,15.0,32.0,17.0,18.0,11.0,14.0,HDHDDAGGFDDFHBFBCAEDGEDCEACDDEEDFHFAGFDECDCCDFADECFECHDCHDGAGAHGHDFEDCEDCEHBHDAHDCFDBFHHGDBDAFCGFAHFDCCDAEDGEDEEFADFAGFBBDEBDEBDF,False +115,21.0,18.0,26.0,25.0,21.0,27.0,25.0,34.0,AACCECDFFBBDABHAGHGFHGHAFHBFHFEHCBHFDAGHAGEDBEACHDCAGCDCCDBEDBDDEGGEHGAHFAHDBFGHFGCDCCFCBFCBHCHHFFDFGEEEDHFHHFHDFEDFDCBHAGAAGHBEEDCFFCHEDAEBAGDEGDEDBFBGCBECHCGHCDAGGAHGHCGHCFHBFHCFHDADAEGEGHCGAFFEH,False +116,25.0,15.0,25.0,18.0,19.0,11.0,22.0,30.0,BGGBGDHGBAECHEFABDHBHHBHDADBEEGFGGDGCCGFCHHHAHAFHBFEEGEAHCGEAGDCCHCGDAGBAGBAEADBADHADFCGHEDHCABCHHEHDFHFAHEAHCHCAHBDHBGHFGEFCAGCHGAAACAACHHDHCCGECEDDFCDACDACBCCEEGEE,False +117,28.0,24.0,15.0,28.0,23.0,30.0,14.0,19.0,CHACHAGEBEFDCFAGFADDEDDBDGBDBFEBEDHHDGDECDEBFABFAFFABAAHHAHHDFHFBHDBEDADCBGHEDFFDEDDEBEBAGADDFFFBDFBFFBFFBHACFDBFDFAEBACBACGEGGCFAFEHEAHECHBDGGFCAECFEFHEHHAGACBDCBAHAAEAAEDECDAFGGFB,False +118,0.0,3.0,1.0,0.0,4.0,1.0,0.0,2.0,FHBBEEBEECH,True +119,15.0,14.0,10.0,15.0,7.0,12.0,18.0,9.0,BGDBGBFEBDCFAFFADCGGAGDABAAHHAHHACEBCDDCBDAGDGBBGDGDDACEFCFFCGFHGBEFCGACHAGAGHAGDABBEEFHGFBFDBEDGHDG,False +120,18.0,23.0,21.0,12.0,21.0,14.0,26.0,15.0,GBBHAAEBAEHEEFEGFGCAECABAGCADBEFAAGDABCAGGFGGCHGCHGAHEAHFFCEHCEBBFBBEHBCGECGACGDCGDHGCGGHGGDDGHACBBGDBDECDCFABECFEBFECEBGBBEDDEGFCDFEGBHGBHAHFACEBCHBF,False +121,18.0,17.0,15.0,11.0,14.0,12.0,17.0,17.0,AGGAFDDFCDBBHECHBCHADHCBACFACDDGFACEBCBBGBHAAHEAEEHGFGCFGBHEBAFHAHHADHBEGBHHCEFEEFGHFGFGCBDCADGBDHHEBEBBAADAAFCAGCGGEGGEC,False +122,19.0,12.0,14.0,16.0,13.0,13.0,22.0,12.0,DFAEFDEBHGFEEDAEDFGGCGGFGGFGGAGGAFFDEAGEAGDBBABDHHCHHBDHBDGCGGDHDAGCACCBFCBABHEFHCCHECBCGDDAHDCEEFACFBCAGDAGAAGAEFAGDBEHA,False +123,3.0,8.0,5.0,11.0,9.0,10.0,4.0,11.0,EBFFHHFADFCHFGHEGHFGFACDEDDEGHFAEDHBDEBDECDCDDFHBFEBHHBCEBHDB,True +124,4.0,5.0,6.0,11.0,9.0,6.0,5.0,8.0,ACEACEADEDEHDCFFCDCCEHHEHEBHGBDGHDFDFEGFEDBHDHDBBGFAGD,False +125,11.0,14.0,19.0,12.0,21.0,14.0,17.0,9.0,CCDCBDBEDHEGHAFEECDGCFGCEGCBGEFAEDACCHCDHGFEFFBBEABEAHHAFCCFBFFCFCBEGDACDGCAEBAEGGEDGEDCAGGEDHEBHBBACBHGFEGEGDEGEFCBF,False +126,7.0,15.0,16.0,15.0,17.0,19.0,21.0,17.0,CHHHDBCCEFEEBEGBHFEDGEBFFBGFGHHGHHGEHDHCDHCDFAFFDCABAFBHGBCGBFHBDHCEGAGGHHGDEAFECHDBFGBDBCDECGEFEEBECBDFFDECGGCGADGEDGFGCFGCFAF,False +127,1.0,2.0,2.0,2.0,3.0,3.0,7.0,2.0,BEGGGGACFHCFHEFDGGDEGB,True +128,24.0,27.0,28.0,25.0,25.0,12.0,31.0,20.0,GGGBGGBDBCDHGACGEHDCHDCBDCHHEHBGHADDADDEBGGHGDDEADFAHFAGGEGEEABEHDEHCEBAEBECBACBACGACGADFADBBBBFCCAEGHFBEBCAAHBCHFCEFCDFCDCCBAEGEGCAGCGCCGEHFEHGCCACAACBDDBHGBEBDAFGEFGBBGHHEDGDABCGFHDEGGEDEADB,False +129,8.0,19.0,18.0,15.0,11.0,19.0,15.0,9.0,BEEBFHGAACFBCEBFHFADFCDHCDBCGBGGEGBDAADFDCHECHECEGCFGCFGFBCFGCAGDFGFFHHBDDFCDFBBEDBFDGDBBFBHABCEBCDAEGCBFHBFCGECGD,False +130,19.0,16.0,11.0,13.0,12.0,17.0,19.0,19.0,AGFEGFGGEGDAFDBFDBCGACBHEHHAHHDFADABHAGHBFHDFCDCADEEFEGBDGBEGADBAHFGBDGBAEFAGFBCAECHGBGFBGBBFBHAHHAHDEGEFAHADCACCHCEHGAHFHGFCF,False +131,4.0,4.0,2.0,0.0,2.0,2.0,3.0,2.0,FBECAGHAHCAGBAGBEFB,True +132,21.0,22.0,26.0,22.0,19.0,22.0,19.0,31.0,HHACHAGHDFHCACFECAECGDFFDFCAACEBEDHHAHDCGBCBBCAHCAFCDBGFGDCHBHECHCFACFGCHECBBCFBGHDGHEGHDGFBAADFGBGGFCGHCBHAGHFEEEDAEDAHHABFABHAHHGHBFDAFDGDDFEDGBDFEDHDDHCEHEAHECEECEADBGCBFFHCFBBBBH,False +133,16.0,18.0,20.0,18.0,16.0,13.0,27.0,16.0,DGGBCEDCEFHDGHFBDCHFHHBACBADAAHADEACBGHFGEDGCBCABGAGFCGDCGDGBEGBEGBECEEHGEHGHHDAAGGACBDGBGCBACDEBDBGCFHFEHCEGCEAEFCHFABFEGGCDHFDCDDCDBFGBFGAGHAG,False +134,19.0,21.0,15.0,10.0,12.0,12.0,10.0,11.0,DAGDAGAAHHFHABCBBCEBCFBCGDCGEEACACBACEAFGBDAAFEAFEHBBBFECDEADGFFACGECBBCBBGEBFEBDAACHADHFEFBCHBFGBHDBCGBHADHAH,False +135,13.0,9.0,13.0,6.0,13.0,9.0,17.0,10.0,ACEEHFBHFBGFCHABEADHHCGACGDHBCABEGBEDBGGCGHHAHCEDAEFAEGCEACEAGGFCGCDGBFGAFGAFBEGCEGAFGECHD,False +136,12.0,12.0,9.0,6.0,6.0,6.0,7.0,12.0,DGFDCFBCHHHHHHHBHBBABEAFGBEGCFDFGCCBDABAAEAAHACCAGHADEACGHGEBEFBCDBHAB,False +137,8.0,7.0,7.0,10.0,12.0,16.0,11.0,8.0,EEHEGHGAHFFEFEDBGDBEBBGGFGDCGFCFCGFDDFHDFHAFCFDGAAFFAEHAEDFEGFEDCEGAEFBHBCDBCHA,False +138,16.0,20.0,15.0,26.0,16.0,10.0,21.0,11.0,BCEFDBCDBAHBEFBCAHCAEBDCCDHGHHCHDDDEGBFDFGCACAEEDGADGEDBEGCEHCHBGHBEDDADDGBDGBCGBDHCFGCGGFGGAAEAADAEDGEDBEBADDADGCDGBAGBDGBHGFFBEDAEFBF,False +139,13.0,8.0,3.0,6.0,6.0,4.0,5.0,4.0,EDGABAADGAECAGAAGAACHFFHABGFBABBEDBEHBAHCABDFDEED,True +140,3.0,7.0,9.0,8.0,11.0,8.0,12.0,4.0,FGFCGCCEEDFEBFEBDACHADEBCEDFBDEHEFBEHCEDCGGBGFBEFCGGDGHDGCGGAG,False +141,7.0,6.0,3.0,11.0,10.0,4.0,8.0,7.0,EEAAECEEGHEHDFDCHCGHEAAEHBDFBDBGDBADBEHFEAFGGDHDDGBDGADG,False +142,25.0,23.0,17.0,19.0,29.0,25.0,18.0,29.0,EEBEEBHHHHBCHEFDGCDECDEDBEFHAFGBFBHFBHFCHFEDFBBFEAEGBCBAAAADAHEEFAEFDFACHHCHBEHBHHDGECFEFBEGHEGHAFHCDBCAGHEGHGDHGEGGFAAFAHEEHBFABDACHABDCDAFGFFGCFECFHBFEEDDGDBFCAHAEDDEACEAGDBGAAGAHCBHB,False +143,1.0,2.0,2.0,3.0,4.0,5.0,2.0,3.0,CFDCBDHGEEGAEDFEFFBHFH,True +144,9.0,4.0,7.0,5.0,3.0,7.0,3.0,7.0,EFAFABHACHECHGCBADBADAADGCFFAHGHDFHDCHFCBECAF,False +145,21.0,27.0,26.0,22.0,15.0,22.0,16.0,17.0,FCDFDDECEHCFGCEGDABBGHCGBBFABAEFEEFACHBGFEABEDBHCCFGAFEEFHAFECFHCEBCDBCBAHFAHFCFFCFFBFAGGAECDCCBBDDCDDCABBAGGAGBAGHCHECDACBAFHECGBGGBAGBHBACCADDDDCHHHFHHBDDBDDBDBADBF,False +146,23.0,23.0,27.0,18.0,23.0,27.0,25.0,28.0,DEGHEGFDBFGHDEACECDFDDFDBBBGCEAFHFFHFEBGEBDEBFBBFHFFEFCGFCGCHGAHBCFGAAECGEGDDGCHGAHAAHAADDADCAFBFFBHBHEGCAHCHHBEACCBBABBDBHCBDFAHAEBCEGEGCBHEHFAGCAFCACEFHEFADBCGGCGHAGHGEHEFHCAHCGHDGHCEHCEFCGFDF,False +147,19.0,22.0,21.0,22.0,15.0,18.0,18.0,18.0,ADDADEFBADAHFBBFBBCHGCGBCBHEDCCDHDDACGEGBEACEBCGCFABFHEAHFGDCDDCGFCGHEHHEHBFHDFBFFBAFAABAADACDFCEFHADGADCCECDBHDBCGBAEBAHDHHDHACFCGFGEFHEGGCGEFGBDGBGBBDE,False +148,23.0,18.0,18.0,17.0,20.0,20.0,23.0,19.0,GHBGCBDAFDAFHCBEFGACAECHHGEGFEGDEDDBCAAGFAGCGECAEFBEACEHGEHAEAFEAFBCGCCFCBBGHBAFBFCBFAEHBEHBEGAACFABGEDGHAGBCGCEBDGDDHEAHCADFFGHAHDGHDGHDGBDABHAEDDFHDFCFFHGFE,False +149,11.0,9.0,14.0,14.0,12.0,13.0,8.0,11.0,CCFCGFCDFHHHGGHEDDFHDFEEGCEAHAHCADFEBBBCBFCAHBAHEACDDCDACDADDBDDBEGBDFFCEHEFBEFEAGEGFCGFCAHA,False +150,20.0,17.0,22.0,21.0,18.0,23.0,27.0,26.0,FDDHHBGAEAABAAFAHBGFFHEHCEBEBBEDBGDCGHCGHCFFEGFEDFCDACDAEBFEDAEDHHHFGHGDHGAEFCFGBEDAADCCGFGGAAGCHCDDBDCGGFGGFGGFHGFBGBCGECHFHHACHABDFHDHCAEBBEBGCCFHEHGFHFEHFEHBCACCACGAGHDDDD,False +151,25.0,32.0,23.0,18.0,29.0,30.0,21.0,16.0,CHFAFBDBCEHGEHEEFEACEFCFHHFCAGAEGBCABCAECHDDFDFFEFFGHABFFEHBBDBGABGACGACEDCGDEBDEBCEBFDCHBADBFDAADEFBFHGAACAACHDEADHCBGCAFBFFBFFBEBBGBEEBHDBFDGDAGFEGCABEEBEHBGHBGFBGBAGFGCEGCACFDGAEBEEFCEFAFHBCE,False +152,2.0,5.0,8.0,6.0,3.0,7.0,7.0,3.0,ECBDCEGFFGHCGCGGFBDFDDADDHEBFCBCCBFCGFGAH,True +153,20.0,20.0,31.0,26.0,22.0,23.0,14.0,22.0,GBGFBFFBHCBHCBHGBEFCGFHHHHEHDCHCCDGCFFCDDHFDEDGEGCHHADHCEECFECHECDGCDGADCAGAAHEDHCFBEFEDCHFFAADEADHADCGBCFBCFEEEEBGBCCCCBCDBDHBAHDABCAGCBCFBEHDEBDCFDHFEFDAACAEDADAFGEFABFDCEDAFAB,False +154,14.0,22.0,13.0,6.0,19.0,16.0,15.0,9.0,EEBFEFCBFDAAGAHBCCBGCEEAEEAEEAEEAEGGFHBCHBCBCHBCFACFGDECBAGFFDBHBBHGGFAGBGCBEHGADBFBBGGAFCAFCEGBEGBEFBDFBHEHEFDAFB,False +155,13.0,9.0,8.0,9.0,16.0,11.0,16.0,26.0,HGHDBHECHGCDGAEGFEHDEGGHHFBHFGHBGBEFEAHEAHBFHFDHADHBCHEAHEAHDGHDHHEFFACDCEBFGGEGAEHEGHEGCCGFHGAAAHAFHAHDEBBC,False +156,21.0,23.0,28.0,17.0,32.0,20.0,26.0,33.0,AGBGFFGFGGCEFCBFGBECECGECBECAGHDHEDHCBHEEAEEBFGGHEEHAGFFGFHHCCHADABEGBHGCHGCFBHEHHEHHGFHFFHEFAEHADCEDCHAADBADHEDAFHEDDCCDCFEHBHGGHEFHEBHEBHGBCGCADAAHACBDFBGCBECBCCEHEADEGEEAFCDBHGBCGBCDFAGEAEHAHDCBBCG,False +157,3.0,5.0,10.0,12.0,6.0,7.0,9.0,8.0,CDDCFDCHDGGFGDBGDHFHHEGCCHDCADCAGBFHEGEEGCEDEFDBFDHAHGCBFCBD,False +158,27.0,19.0,22.0,22.0,21.0,22.0,30.0,32.0,AEAADDGDGHBHDGHBGHBHHBCHCAHCABEEBDBDHGFHGHHGBBAHAGFGBAGAGGAGHHCFFBHHGDHAACAGCAHDADGAFHCCHGHHCHGCFGEEDEDBECGAFEDFEDBEGBCACHFCDFGDCDCCBGCFGDFGHFAAEDHFBHFGFFEAEEHEDBECFEABGAFEEEAFDCFDAFDBCGHCGHAEHAG,False +159,6.0,10.0,10.0,5.0,6.0,6.0,5.0,10.0,HCEECDECAFABHBBFADFCGACGABHFEHCBBCBBHFHCDCEDCHGGHEGHFBHABD,False +160,18.0,20.0,20.0,17.0,21.0,19.0,20.0,20.0,FEDBECCGDCDBGDBGDGGDCDFCAHCEHAGAABACFCFFCAACHADAACEGEEGBFBHEHHBGHBACGFDFCHFCHEAEBBEDFFGCFGBEBBEHDDHABGEEEEFABHABHGEHGEHGEHBFDFDHGDHGBEGBECCFCAFHFGCCDAFAHDB,False +161,12.0,21.0,28.0,20.0,19.0,21.0,30.0,23.0,BEBCAAFGAFGBFGEEEFCCHCGHFGHGDDCCHBCGACGEHGHCEHCFCBHCBHDAHDHHDCHEABGHFGBGGCGHCGCEGFDGDDEFGEAHBGEADDCFDGBDGDCFECFCGFCHEGAFCDFCDGDFFEHFBHFCCBECHEBHCBFDBFBBGBDAEDGECGBHEBDABGGGAH,False +162,21.0,14.0,18.0,20.0,18.0,17.0,19.0,20.0,GHBEAFEGBGGHDEEDEABEBBEFECFCCABAAEAAEACBAFBHFHHAEDBCDECDAFBAFBAGEHEHGDAAHGAEDCCDHDDHGAHAFCCECAFCHHCHEGBCDCCBFFEFFGBFDDDDDGGCGDAFDGCGFHHDHHDHGFHGAGG,False +163,7.0,8.0,10.0,9.0,10.0,6.0,9.0,12.0,FBCCDDCAHADHEHHAGCGGHECHECHGBFABFADFGDHBDHDDCDHCEBFHGECEEAEFHECEBGBGGBA,False +164,2.0,1.0,4.0,3.0,2.0,6.0,3.0,7.0,CHCFEGFCGHHEABGAHDFHDFHCFHFD,True +165,27.0,21.0,24.0,26.0,31.0,11.0,22.0,21.0,CAADGACHHEAHDFHCAHCFBCFBEBHGCEFCHCGECDEABEACDDGHDAFCCDCADCAGBDGBEGBCDEHAHHAEFBEGDEFCEABBDBGAHAACAAEACBFBBFGEEHEBDEGDEGDCCDCABHEEEGCDGCDGHEGEEGEHDEGDHDAEFEGBDGADHFDGCDGBAAAAHHEEHDEBABB,False +166,7.0,16.0,7.0,13.0,4.0,10.0,9.0,15.0,BDDEDDGCAHEFHCFHCBHAGFDBDDBDDGFFBAHAHHFGBBDFBDHACHBCEBFEHHGHHBADBCFBHDGABGHBGFBGC,False +167,15.0,15.0,9.0,10.0,9.0,15.0,18.0,14.0,GGABCADCGHHGEHBDHCDHDEGGGFGGAGAABECBCFBEABEBEGAACBBFEAFBHFBHFBGFCAFGHFGHDGCBCEHFFGBFEDFBDAHHAHHGFDDAGDAFA,False +168,21.0,14.0,14.0,15.0,25.0,21.0,7.0,17.0,FDABDAHCHHFDACBGCBGCHFAACGEEBCBFABAEEAEEAFEADDHFAHFEHAHHCEHEFDGFEHFEGFDFHCCAEAAEADBHCFHEBBCFACFDEADFAECAEBBEDBEGFDAFEFDHFDHFEEBCEBGEHD,False +169,11.0,25.0,11.0,15.0,12.0,14.0,16.0,19.0,CDFBBCHGCEBDBACBDCGHFHHFHDFHBEGBEDBFDAFCAHBACFAGGAGEAGBAGBHBBDEBHGHHGHFEABDHFCBECBFDFEGHDFHBFHAEHECHBHBGDBGBCEBABDEGDGGDFDB,False +170,11.0,10.0,15.0,10.0,14.0,10.0,14.0,13.0,EEGCEHAGADCDEADGBDBHDFGDHCDFCDHBAEAHEHCGFCGFCEFDHGHHGHFGCAACHACHAEGEBDCFGCFBBFBBEEBGACGFHEECEBCGA,False +171,15.0,14.0,17.0,21.0,14.0,11.0,20.0,12.0,CBGBFHBCEACEAGAACBDBBDCDDCDDAGGAFGFGDHADEDDEFFAFFCBFCBFCFAHDDBGGGEADHHBHBBDEEGEEGCAGCDCCGCEBHHCGGCDBCHHEAHGAEGHEFADGDGEDGDDA,False +172,6.0,4.0,6.0,6.0,3.0,10.0,5.0,4.0,GBFGHFGDEDFCDAGDHCDACBECDECAHAFFAFBCBHAFFGFF,False +173,2.0,0.0,4.0,3.0,0.0,0.0,1.0,0.0,DDGDCCACCA,True +174,3.0,6.0,8.0,12.0,9.0,8.0,4.0,7.0,FGBDDHHDCFABFABCBCCHDEHEFAEFEBFEDDHDBCDECFHCFGEGGEDDCDDHE,False +175,4.0,4.0,3.0,0.0,0.0,0.0,2.0,1.0,GACGABHBBAABCC,True +176,4.0,2.0,4.0,1.0,2.0,1.0,1.0,1.0,HCDACAAEABCFBCEG,True +177,22.0,20.0,10.0,18.0,13.0,13.0,19.0,20.0,CBHCGHGEHEEADBHGAEGFEGFBAEBCFAFEGHCBABFADFDDCHBCHDHAGGADBAHFEEFHBBHBGDDDHDGHGFHAFAAEGBBDAADHGBEGBAGBADBAHCHHADHDGGDFGDFDCABCABCABEFHEGA,False +178,22.0,19.0,25.0,28.0,26.0,27.0,22.0,13.0,CCCCCCCDCAGHEHCGDGHCADEADBADHFDGGGBDACFHCFHDGBDGDAGDCDDBBCEBFBAABDCDDEDFEFEECDEBAFBDDBFEHEEAEFGEFGEAGBFFBFFBCFCFDGHEFCAFCAHEEGEEBEAHDGEFBFHDFEDCDHCDACGGBGCAGDAFAAFEAFHDFEGECBBGFAEFAG,False +179,3.0,7.0,11.0,8.0,19.0,13.0,15.0,4.0,BEEBAEFHEBGCBCEBFHFDECDCGHGFEGEEBECGFCGFDGDDGFAFFAEGCEFCEFDECEEGDEGCGGFGEBDHCEGF,True +180,23.0,18.0,16.0,19.0,17.0,9.0,16.0,16.0,DACDHCDECEHCBACDAFDAFABCEDHDGHBCFFABCDDFDDHCAHBAEDABHABDGDFCBECAEAAHGEFABFGBGBHABHCEAEGAEGEHGFHEAAEAHGCEGCHGAEGCBGCDGDEGHHADBAGBEDBDBB,False +181,7.0,4.0,3.0,4.0,1.0,4.0,0.0,2.0,CDDAFABHAECADFHCFABFABDAB,True +182,7.0,17.0,14.0,12.0,11.0,8.0,17.0,16.0,ECEECHEGDCFDCFDCEDBBGBGECGBHGFFGCBHEBHABAGBHFBHDGHBECBEHHGCGCCGCFGHABADDDHGDHEBHBCGGFFACHAEADBHDGHBGDB,False +183,18.0,19.0,14.0,22.0,20.0,25.0,20.0,18.0,FBAHCEHGHHGAEDEDDHDHGFACFDBFGCCBHGHHGBHGECBHFDEFBEBHECHFGDFHDEHAGGEGDBGAADFADAADGADGHFFEGCABDGFDBDECDFAFAEFCEFCADGFDFFBFFBHFCECGEBGEBHEADBBDFBCFDCFAAEGBEABE,False +184,9.0,17.0,14.0,14.0,12.0,19.0,15.0,10.0,DBDDHCBBBBGGFEBFEAFGCFDCADCDFEFGHFDHBDCECCFDCAEBEDHFDCBDGBACACGECFEHDBACBFFBFFGGDEGHHGCHFBHFBEFAEAABGFBGEGGFGH,False +185,5.0,15.0,12.0,28.0,11.0,16.0,11.0,13.0,FBEBDDHEDCEGFGGBGEBDBBHCDGDDHBDHECBDFBDEGHEFHEFEDCDHGDADDABHABDCBDBFDHGDFDCGHCGDCHHGDADDEDDAFDFFHFFECDCBBFFCFFC,False +186,3.0,2.0,0.0,4.0,2.0,3.0,6.0,2.0,EGADGADADBGHFGBDGHFGEF,True +187,7.0,12.0,9.0,16.0,4.0,16.0,12.0,10.0,BDFDFFBBBEBBFCHHCHHFFEGDADDFDFHAFDAFBBGDBGDBDDGCDFFDGDGCBCADGEHGDHCCHACABHAHGCFGFFGEFG,False +188,9.0,14.0,12.0,11.0,9.0,6.0,5.0,4.0,DFBEFDCDCBAFBADEFDEGCEBCGFCECHDBADBADBEEBABGHBACBACBECGACBBCADDHFGHECD,False +189,15.0,22.0,16.0,23.0,11.0,18.0,13.0,25.0,CHGBHDEHBEHDGCDFHFHHCHHGHEDDBGHACHECHBHGDHDCHDEAGEABFAEFACBBDDBDBADACDABFAHDABACBHHDHCAHFFBBDBGAFGFFBBABCGEEFEDCCDCBDBFDBFEFGGFHHFHDCADBDGFCGFH,False +190,23.0,11.0,18.0,25.0,19.0,12.0,19.0,38.0,DEHHAGHADHGCHACEDCAGEGFDADHADHDDGEEEEHFHGCAGEDDFHHEHHDHDGBDADHECEEGAFHDBHGBHGBDAHAEHABHBBFDDCDAHHGHHEHFGHCHDDECBFCADCGDCGHCGHGAHGABFHFHHFHHEHHBBAEDAEDFCCECAAGACCACAF,False +191,5.0,6.0,1.0,7.0,12.0,13.0,5.0,13.0,HEEFEHAEHFFHFGDFEDGEGAFGFHGEHDBHAFHFFEAHEBEBDFADBHHHEHBECFDBFD,True +192,14.0,9.0,19.0,16.0,17.0,13.0,14.0,12.0,FBCCBDDFFDHDDHGEFGEFGFHGFBDFCEEHACCAEEDBFDEDCHFCBAEFCGGAHFADGAHEHHAHBACBCEDEEDCCDCGACGCCGCEGDECAECAFGABGBHGDDEAEHA,False +193,13.0,11.0,10.0,13.0,18.0,18.0,16.0,24.0,BFHBGDBGHEFHEGEEGAAFHDFECFEAHEAHDFHCHHEHFAGEGCCHHEDHEDCCDAGGAGGBDCBDAFHFFAFDAFHGCHGCFGHGHHCHDBHBFFADFEDEBHGGFBADHAEEEHEEBFB,False +194,4.0,3.0,4.0,0.0,0.0,3.0,1.0,3.0,HCHBAHBAGFABCAFCFC,True +195,5.0,5.0,1.0,2.0,4.0,4.0,7.0,2.0,EFBGHBGABGADGABHAGDBECGAFGFFEE,True +196,16.0,12.0,12.0,7.0,4.0,7.0,9.0,12.0,ACGACAHFFCEACGGDEADCAGCFHBFBEFDHDBHAAAAGHBBHCBHGBAGBACBDCBHCBACDECHHAGHFHBGADFA,False +197,11.0,6.0,8.0,7.0,7.0,10.0,12.0,14.0,GHFFHACEECGEGGDBGBBFAGFGCHGHDGAEGCCBHCBHAFHAHDAFGAFADCADHAHHBCDFGEAHEHHFDEF,False +198,21.0,16.0,17.0,15.0,22.0,24.0,21.0,20.0,AEFABCDCDABGHHEHDFBBFCAGGAEFCGGCGABGACGHHGDGBDBBCFACBDFHHEHFCHFCECHFCHGEHGBFFECFBHFGHFEDFDCFCEAEEADDGDEGFEGFABFHBFAEHEDDADAAGAACEACBHEBFEDFAAAGGEGGBHEEHFEHF,False +199,3.0,4.0,1.0,2.0,7.0,5.0,9.0,5.0,HFFFEGEEGAHGBHGAHDADCBGGEEGEGBEGBFFH,True +200,27.0,17.0,26.0,18.0,16.0,17.0,15.0,13.0,BDEBEEBCBBCDFCHCCABDEGCGACGACACFGDDGAACBACEEDBDDCCCHCDFAHBGEBCHGGFCGHHHABHBGAEHCBGCDAEDFEFBEAHEAFFGDFHDHHDFDBFEBAAGAAGAGFCBCCEACEACECFAFAAFAADCFDAFDA,False +201,14.0,18.0,22.0,18.0,23.0,25.0,18.0,25.0,EHGEHCBHCHHAEHDEHDEAEBCEBCEGFAHFAHCEHBFHBHHBHEBCFADGHFGCFBAFBDHCHCEHADGBDFBFFBHBGGEFFFDFEBCDFDHCDHBECDEHECBECEFAGFCGCAGEHGEDEFHFCGCCDACAAFDAHDFFDBGDGAFGCBCDFEGFGGE,False +202,6.0,4.0,6.0,6.0,4.0,7.0,2.0,1.0,BADGAEAACFACGEFBACCEFCEFBDHDDFDBFDCF,True +203,4.0,8.0,7.0,5.0,6.0,6.0,6.0,7.0,EHAECAEHBEHBFHBCDBAEFEGGCFGDGHHACBBCGBDHCDFCDFGBF,False +204,6.0,15.0,10.0,9.0,18.0,10.0,16.0,17.0,EHHEDFBDFGDGEDGHFEEDDBGFADFCBHCBHFEEFAECGHHGBCEDCEHFACGHEGHEGCBGHBCHBEFFEHADBAGBGHCHEEBEAGEBGBHGBHCBG,False +205,6.0,8.0,4.0,6.0,11.0,10.0,4.0,7.0,BDFBFFCHFBADBGFCGCCEEAAHFAHFGFEEFBEAHEBDEBDFHDHEGEEBEHDA,False +206,7.0,11.0,7.0,14.0,12.0,11.0,11.0,15.0,DFFHFBABAHBEHBEHDHGCHFDFAGCGHEBADHGDHCEHCEFCEFGFFGHGCDAADGBBGDBGEBFEDHABHDBCDHHEFDEGDEDE,False +207,14.0,19.0,19.0,16.0,15.0,16.0,25.0,15.0,BHBBDBDDGDAHEGEGGECDCCBCDAEBGEDGHDCHFEHACACCEDCGFGFEGDGGAGGAGGHFBEGCEGCEBCAFGHEBHDAEGAFHHCADFBBFBFFDHFCHFBBGBBCBACGFDAFHBCGFCGEDGADEAHFCHBG,False +208,14.0,24.0,23.0,25.0,20.0,23.0,13.0,19.0,CGFHBECCCACGAFFHDFHDAHCCFBDFBCCBGFDAHDABGABGHBFHCDGDDHBHEBCEDEFFEFFEFFCDDGGECDEFDADDHEACEAHEAEEBFBFGBDBBFCBDCFDGFHBBDBCGCDAHDCCDHCEEFEGGECBBABDCBDEFEHHEHHBHBADFA,False +209,5.0,7.0,7.0,12.0,11.0,5.0,6.0,4.0,BEEGAGCAHCFDCAHCEFCAFGGDDEDCBDBEFBEDDADDHDDBBDBEEEGCEGHEF,False +210,21.0,21.0,29.0,26.0,25.0,22.0,25.0,25.0,HGGGCBGCBGFDHCEGCBADBADBDFHCBHDBEBBEHBEFBCABCACCFCEFHAFHGFGDDGDDHHDEDDHCBEDDEDCBGGFAADADGACHAFDBEBEECDECEFGGHECHEFHEBHEDGCDCABCEFGEGHFGHEECDBHDFDFGCAEAGEAHCHFAHDGHACFACGHHGDHGCAAEFAFBCBECGFCFFCA,False +211,25.0,20.0,15.0,18.0,16.0,31.0,22.0,17.0,GDHFDBEDFEFGAHDFFDBECFDAFDBFGBDAEGAEGFDCFDCEACBAFHGHHFBFFBHHEAFBAFDCFBGAGGACBACFCEACEACHHGDHGCGFHGHAGABGBGDFHHFCACEBHEDDAFDAGCADBEGBFGBFEFFEAFGCFBHFEHGABAABAEGAFDFB,False +212,11.0,12.0,15.0,21.0,14.0,13.0,13.0,22.0,FDHBAHAHFDBFDFCHHEFHDFAGBADBADCHDFFDABDHCDHCGAGFHDDHEEHBHHEHBCBGDGCDCDECDEGEBHEHHGHDFBCFDAGCAGCACCEFCDBGEBGEDEFGHCGHEDHEA,False +213,26.0,25.0,22.0,24.0,22.0,21.0,23.0,28.0,DGGABBFFGEFGHFBHBHFAGAHGECGEBAACCADCHDBGDHCDFEDCCCFBFAHDEGGBGECFEABGHDEADGBGGFDEFAABAAHAAHCAHGFHBFABFAEHHCHHCFBEEDEEFEGDEHDHHDHCBEABAGGAFGDFDCBCHBCHBHEBAAGCADCHFCFDBBDBCDECHACHDBEDHEFGADGHDBE,False +214,17.0,18.0,21.0,25.0,26.0,17.0,17.0,17.0,FEFAEAHHABBGBGGCDGDEEDAEBGFHHCADDHDDEDDEAFECGGAGGEBGBACEEDEEDHDDHGBHEBCBHADFEDEGGCDDBDCFCHFEFAHFHDBHDBHAGCFEFFEBEEBEEDGEACFABBCBFDBFHFECGHCGACDCCDCCECFHAACADC,False +215,3.0,8.0,12.0,3.0,11.0,1.0,8.0,8.0,ECHEGGEHEEBCEHGGHBAADGCHBCBBCHBCHBCEDFEGHEDCGCCECEBCGA,True +216,3.0,7.0,2.0,4.0,7.0,5.0,4.0,9.0,EEBACHABHEFDEHHEBHAFHFCHEDGEBBDFBHGBHGFDG,True +217,24.0,19.0,23.0,32.0,19.0,19.0,18.0,19.0,BDFHFFHEAGCGGEHGAHGADAEDAEGACABCBFDEDDEHDGDDEDDGCDGAFBBEBHFBDEADCDDCHBCEAHDBHCBHCACBGCGFCGFCGDHFABCACCABHEEHDGBFFDFFBHADDDCAAHDAEFEEFBDFADGADHADFGDCGCCBECADAHHCFDCGBEFEEDHBA,False +218,15.0,9.0,15.0,14.0,9.0,15.0,10.0,14.0,EDDHBDCEDAHHCDHCDEFECFDDBDEGDCAFCAGCHCFHBFBDFCABCEGEEHHGFHAFCABHABDAFAHBHHGFCGFHGBAAFDAFAAFEDFAGGCCGC,False +219,24.0,26.0,20.0,28.0,17.0,21.0,17.0,23.0,FBGGAGHAGHGGBGGFFDAFDHDCFBFFHFDHDDHFDHFHCFGDHBEFCEACHFEHCBADHDBADCEBCDDAGDAFDAEDEHCAFDAFDFBBAGBGHBCHAFECHDCEBBEABGFHEBHDGCEFCBACBACBCCBHBFGDADAAHAHBGDBDEBGECEDHDAEBAEBAEHADCDBC,False +220,10.0,6.0,12.0,8.0,3.0,8.0,5.0,9.0,DEDDFFBCFCCAGBFHBACAACAHFAHBEGGAGCDCCDFCDFCAHCACDHEHHABGDBHFH,False +221,18.0,20.0,25.0,20.0,16.0,11.0,30.0,25.0,BFFBEGBGFBGHBEFEDHBDCAAHAGHFGDADCBDBBDECAEBAHGHGABBHHBGCGECEECADDDGHDGBBGBCGHHGCHCCHCFHGGHAAHAHGAHGEHGDHBEGFHFAHGADFEGBDHFDGCDGCFGAGCCGACGHEGDCCCABCECGEHDEDDCCECADCB,False +222,19.0,19.0,21.0,28.0,17.0,28.0,23.0,16.0,FFFFGGBAGBFCDFCBFDGDDEDDFDEFCHDCHACAAFFDGFHCFBCDGEGEECCCBBAHHDEHDECFGGGDDGDDGDDCBACBABHCDCFDCEBEGBCHEFHGBHABAGFGFADHAGFAEFHEBBFBEFCGFHAFGADGAFHBCABDEDDCHFEHFEGAEDCGDFADBAG,False +223,23.0,19.0,28.0,13.0,18.0,28.0,23.0,33.0,GHBCHBGHEHEAHDHGDCFBHGCHGCFGCBGBGCDHEFAGHEGAABBHECFCFGDEHCEHAFCADAGDFGDHACBACHACHCHFBEFCFGCHHHHCHBCBEDBFHBEHBAGEACHACFAGGHGDHFFAFEADEAHFAHCCHEFGEFBFCBHDFGFFGAFDACDECECBEBFHBAGCHGCAFFAFF,False +224,3.0,2.0,2.0,3.0,1.0,3.0,0.0,0.0,DAADFBDFBCACFE,True +225,18.0,28.0,26.0,15.0,16.0,22.0,28.0,24.0,CCBGHAGAEGAFGBHGCHGBBBHBBHCBDDBFDFGECEECAGHEBBGBAGBFGCHCCDGCDHEAGCBBFBBFCBGGAGBDGHGGHGHHFHDCEDAFGHBGABHBEAACGCCHCCHBHHFFFFGCFHCFEDACFGEFCAAGDCDDHDBAABFACDABEGCEGFEHFEFCEDBFHBEHF,False +226,0.0,1.0,4.0,5.0,1.0,5.0,5.0,2.0,DBGCFGDHGFCGDHGEFCFDCFD,True +227,9.0,11.0,5.0,9.0,13.0,8.0,7.0,11.0,DGHBGEBGHACBAFHAFHFHDDHCGEAGEDEEBEAGFDFBDFBHFHCDHCEEAFBABBEEBEBDHADHGEEAC,False +228,3.0,5.0,4.0,5.0,8.0,4.0,5.0,8.0,DCEDEHGEHGFCEFGBDHBDCBDHFFHEAHEACGBGHAEHEB,False +229,5.0,2.0,1.0,1.0,0.0,2.0,0.0,0.0,ABABFACFADA,True +230,17.0,15.0,18.0,10.0,25.0,10.0,12.0,11.0,ECCHCABEAEAABAEBGEBCEBGAAGBBDFHDEHDEHCHHCHCEHEEHCGBAFCDEEFGEGGCFDEFBBADBEEFHEAHECGFCDAAAFBBCCCACBGGBAEDDEGDECCEFAEFAEG,False +231,31.0,18.0,29.0,27.0,23.0,14.0,25.0,29.0,DGBAGHGHDGCGACBADBDDEADFCHGDBFEBHEBHEFHFCDFCDACFGHDDDDDCGCEAEEADCBDBGGHCAACAEDACHEHHAHDDFDEHCEHCECEHHEAFEABCGEGABHEDHEFAGCGGCGACDAGDACAAHACBBCDACAACHCDHGAHGFBDAACEACECFEHGGHBGHBCFFGDBGHBEFEHHAHBAG,False +232,9.0,27.0,30.0,27.0,17.0,16.0,18.0,20.0,HDBHDCCCHHCHECBBCGCEDCHCADGDBBEBGEGGFDFDDGDBBFHCEEDFFFHFHHDGCEBCABABDEHDHCDHFDHFDHBDHGGEECBEHBDFDDBCDCCBCCGCAHDBBBBFBEHBEGBEDDGAAHCBECBCCBCFFEDFEDCCGBAGACGDCAFCGFGG,False +233,13.0,14.0,9.0,12.0,10.0,11.0,7.0,12.0,CACBADGHDGHDFHDFHDEEDGEBBEDHACHABBFCFAEHACFDCEAHEABFFBFEAAEBCHDGBDBBGCBFEAFGDCDHHABHABGF,False +234,27.0,12.0,19.0,20.0,14.0,11.0,16.0,19.0,DCEACEBHDGHAGFBGABGABGABCHFEADDADAHDHDGBFAECCBCHHFADFEFAHDAEDCHCHADBFDCGDCHECGAAAAGBAEEHGCCGEAGEFCDFDGGCGACHCEHCEHDEHBCADAADADDFHGAHBAHBAF,False +235,10.0,14.0,16.0,10.0,22.0,13.0,14.0,12.0,BCEFFEFBBGBBGEDGEABFACCDCCDHEGHCBDGHEEEFAGBHGBEEHEEHDEFDEFCECDECHGGAGFFEDGHBECBHCGFEAAEAHGBHGBHEBAFACCEDCACFDCF,False +236,7.0,11.0,9.0,8.0,13.0,11.0,4.0,12.0,AEBEHFHFFGFHBFHFAHBHHBHFEFABBEBAEFCEACHHDGDEGABCCBCEBDEDCEACFHCFDCHDEEDBGDE,False +237,23.0,30.0,14.0,18.0,17.0,26.0,17.0,30.0,DGDDFCEFCGCBBHACAFCEEEEAADADEHFABBADHADHFDBFHHFHDFDAFEADBADCAFAFBEBBEBBCBBCFBEFBGFBHBBFFHFAHABHEFHBFHEGHAAHBAGBGFHAFABEGEGGDCGBHBCHGHFGHGHHCDEFFHCBHBBHGEHGDHFDHCDBDAHGHBEAACFG,False +238,19.0,27.0,27.0,14.0,19.0,23.0,28.0,21.0,CCCACCFBHFGEBABBGFFGBCHBFAAFBAHCAHCBGABGADDABDAFDBCGECFEHBCHGHHGHEGDEBFBBCGBGHBGFBCCBDGDCHACHADFADEHDEHEGADGAFBFGBEGHFHEADFCCGCCGFCEFGHFEFBCDBGHHECGBCFAEBBCDGAGCAGFFEHGEGFEGBECHE,False +239,12.0,6.0,10.0,11.0,16.0,6.0,12.0,10.0,DBDGGDGCDECGHCHEAHGDEFEEFEBBHABCCDACGFEGHECAFAEDAHAGCBGAHGAGFABFDEEDGEHEECEDCEAHDAH,False +240,12.0,11.0,10.0,12.0,15.0,7.0,12.0,8.0,EHCEBGEBCADCDFCEGBEBCEBHDGAAGDGHDCFDEEGBEFEEFGEHGHBEABEAFCFHCGHCBADAADADGAEBBDDHDFGACGA,False +241,24.0,20.0,23.0,18.0,18.0,16.0,33.0,12.0,DCADHACHFFHADCCDEEDCEDCFAAFGBCGACGAGGACHBBDBCCBEFBGCDGHFECABCACGAEFAECBFFFHGCAECAGHEHBFHBAGEFGECGHBABCADDGGDGGDGGCGCFFHGGEAGEGEEBBEGAGFFGDGGBGDBGDCGHAAABGEBEBDDBDAA,False +242,2.0,5.0,2.0,2.0,7.0,2.0,2.0,4.0,EHCHBDECDEGFEAHHABBEBFEBGE,True +243,5.0,8.0,9.0,5.0,11.0,13.0,13.0,9.0,ECEEGBGFFHFBEFHFDBGDBGFHFFHGHCGHEACEABBFEEEEGCGGCFBCDCCEHCDHGAFGABGHFGAFD,False +244,8.0,13.0,8.0,11.0,10.0,14.0,17.0,10.0,EGDHGCEDHEAHFBCGBAABGEDAEDAEGGDDFDCFGCEGCGFADFCFEBBCBFDGFAGFEDFBGFGHBBHEDHGGHBAFBFHCFHGBHGB,False +245,10.0,16.0,19.0,10.0,13.0,11.0,21.0,15.0,BEEBGHAGHCCFEDFGFHBHHDFDDHCFAGFAHABFABGAFAACBECGGGHGCAGCHCEFGEHBEHBGFGEFCHDHHDEBCABDGBGGCGGCBGEBGDCCCCDCBDEBGEBECCH,False +246,9.0,13.0,8.0,9.0,4.0,11.0,15.0,3.0,BDDBDDBAGAEGABGEDFCBCCFCDABHCBGDGGEGCEFAGBAFBGGBGGBDFFAFBCGDHGHFFCFAGFAB,False +247,24.0,29.0,19.0,27.0,21.0,19.0,25.0,36.0,AGGDCEDBEDGADBCBEDBHDFHDBEFHEFEEGEGDEABEFHDBHBHHFFAFBGGHCFFEAFDABEAFCHDCABBBCBEEBFBGAGHBGHCABCAFHDGHCHHCDGADHADGFHGFCGDBHBCHBDAEGHHGHHAHCAHDDBGHBGCEAHGADDHDECGEHHEDEGFEDABHABHABCABDABDACHGCBGDHHFHFFGC,False +248,23.0,15.0,19.0,20.0,20.0,17.0,12.0,20.0,AEDAEDAEFADFAHFAHEEHBBCBBDBCAFAAGCCGACEHEADFHDFCDAHGBEFFEFDAFGACGECEHHGADGBCAFCGCHDDDGCFFDBCHECFEHEABEABDCBHFDHECAFDABDAGEBGHGEHDBADBADCHCHHCFHEEH,False +249,5.0,8.0,8.0,6.0,8.0,12.0,5.0,4.0,DDADDFEDFHACECHGGHCDBBFFBEEBGEBCECCGBEAAGAEBFCFFHFFBFFCF,False +250,9.0,9.0,5.0,9.0,9.0,5.0,9.0,6.0,EBGEGDECAEBBGBFDBACGCBBCBBFDADDACDGEDGHDHDAHEFHFGAEGHFGAAEHAE,False +251,3.0,4.0,6.0,7.0,2.0,6.0,5.0,5.0,FCHFEBDGHDHADFGGFGFFEDBCCBCCHGCHDBDDAA,False +252,23.0,16.0,22.0,22.0,17.0,24.0,15.0,22.0,GDGADAHGFBBFBCHBDHBDCCDHEGADCHBBDFHCGGCEFBECHECEACFDBADEACEDFFDFFDFCEFCGFCHFGAFADGAFHAEABFDEDHHBAAAAHGABGDBFEHFHHFCHDCEAEEAEDCFFAFHCHHADHACHAEDABDCCGGCGFCBFGEHBD,False +253,28.0,21.0,24.0,17.0,16.0,23.0,19.0,22.0,HBGAFCHGAFDHGAHGHGDDGADGECAACFACBDGFCBAHBHDBFDEFABFACAEGFHGBDGBFHDFHCGBAGCABEGHEFHECCEAEHADHFDCCDCCEAFBDDBFHHFGHFCHCDHCFFCBAEFAEFEEAAEBFCBAABAAHEABBAFBGCBGCBDFGAGCCDECAHH,False +254,22.0,21.0,35.0,22.0,18.0,16.0,18.0,17.0,CGFCBBCBBCFBDHEGBFDEHCCAECAHAFDEEDAEHAEBCHFHBFHCHBGEACCCCDCABFABCDBDHCGCCGDCDDADDGGEHFEGCCBCBAFDEFDAADFAGGHECHECHECHAHGCFBBBBAGGEDBFDAFDCEDCEDCADCBHEFCAGCAGCBGFDACAACGGH,False +255,16.0,23.0,16.0,16.0,20.0,17.0,25.0,22.0,FBDCDGFHBEHADAEBABHAGDEEDGEAABDDEEFEEDBCGGDHHDHGDABBCBBCDHCDBGDBGCHGHAGFECEEBEHFGDFACHGHHGBHCEHCECABHADHACFBBAEFCEHAGHGEHGFHGFGGFGBFBFCBGCFGEFGEHBBGFCAFGAB,False +256,4.0,5.0,1.0,1.0,3.0,4.0,5.0,7.0,BHFAGFAFHABDAEHHGHHGEGBEGBCBHF,True +257,15.0,16.0,15.0,21.0,14.0,16.0,23.0,29.0,BBAHCCDBGFHGFGFFCFGCGHCGHDGAGHDCHDEABEBGGFDDFHDHHGHBAHDGCAGBGEBHBCHGEFGEHGEBFECHEDGEHBAHBEHDACDHHHBCHBCHAFHDCHAHGAGGDDBDDEACBAEEAHDDFFHGFHFFDAEDACDFG,False +258,25.0,18.0,28.0,20.0,16.0,20.0,26.0,30.0,GBDGBHAEEAHBAHBCHCCHCEBCECDEAAFHHCGGCFFDFBAGBHGFHDAHBACCADCAECAFFAFFGGEGCEACECCFCBEAAGFCFFGGHCDECBGHBHACAAFDGHDCHDCFDHFEHFDGDGHDCHAEADGGEADCHDHBGBDGAGGFFHHFHAGHCHHCDBGHBEHDEHGABBADBCG,False +259,10.0,4.0,2.0,8.0,6.0,7.0,4.0,6.0,BFAHHADDBDEBDAHFACEADEFDEHDGAGFDGFAEFBGFEAACHAH,False +260,17.0,18.0,20.0,22.0,23.0,26.0,23.0,18.0,CGCHEEDEBDHDGEGFEFFCAHGBHBEHBACAAFAFFDBFDCFAEFADFAEGBBHADAGGHFGCCGCGFBDFEEEEADHGDCEDFGDEBDHBGHBFFCAFCECGEDADDBHGBECFEBFEDFDDEGDHCAHCFFGFFGAHCDHADCBECBHHBHCGFGGABGCEGFE,False +261,27.0,24.0,20.0,19.0,30.0,32.0,21.0,26.0,GEHGECEEBEDACCACGBFGFCDBHEFEEFGEFBFACFACFAFFAGDACBAGDEBABFAEDAGHAHBAECAFDFEEBBBFEBDEFCHFHBFHFEHDGHBGHCCFDDAADEAEECGGHGFECFEDFEAFACHACEFBEFHHBHHFEAFHBFBBFBHFCAGHHFHHGHDCHDCHFGAGDDGCAGDEEAGEBEDAGHADBBB,False +262,24.0,26.0,23.0,23.0,21.0,23.0,28.0,24.0,CFDHHBBHEEHEHHEFHBDAADAFDBCDHDDFGAFCACEADGBEGCGCHEAHGADGABGADCFFBFEDDAFDCFHBBCFBGDGCHECBEBBCABDAECAHAHHAHEBHDHHFAHGEBEHFAAGBAGBGGCAFAFBAFBDCDCCDGGDGBHBBCBGFGEEGECGEHECDFCBFGBDGCACEFGEGGFHGFDGF,False +263,0.0,1.0,9.0,1.0,3.0,4.0,6.0,1.0,CHCCEFCGGBGFDGEGCECCFCFGC,True +264,6.0,5.0,5.0,2.0,0.0,4.0,6.0,0.0,CCAGBBGDBGDBACACGAGGFFFAFBAC,True +265,4.0,10.0,10.0,7.0,1.0,8.0,4.0,4.0,BEFBDFGDFABCABCHFCDGBHBCAFCAFDBDBGGBDFCCBCFHCDHC,True +266,22.0,29.0,31.0,16.0,20.0,28.0,16.0,14.0,EHAHCBHCBECFGBBCHEEBAFBHHAFGBFDBFCBFCBFCBFCGFGECBBGFCEFBEFDEDDGFCFCAGCAFCEGAAGAACDCFGAFGAFHBGABDAGAHCAECABBBCFBCDEAAEBFBBFCCFCCFABFDDFBEHBFGEDBEDEHAECBGCFHCDECACCDEFDADEHCGDBHH,False +267,19.0,18.0,7.0,10.0,13.0,13.0,13.0,11.0,HAHCGEBDCBCBBEGHFGBCGAAGBGGFDGCAEADBAHBFEFFEAGEHCHHBAHAADEFGEAGFFEFAEFCBAABAABEAFGAEGDEDBBABBFBHHDDHDBFD,False +268,17.0,10.0,10.0,7.0,8.0,5.0,14.0,9.0,DCADHDGHAGBAEHECHCGADHCGAEGBEGAEGAEGACAHGHDCBGHBGFBCAAAACBBEEBGBCFCAFDAFDHFGABGA,False +269,1.0,3.0,0.0,1.0,3.0,4.0,3.0,1.0,GHGGEBEFBFABFEDF,True +270,23.0,19.0,18.0,18.0,15.0,13.0,11.0,15.0,AHDAFCAECAFBHBCEFDEFCEFEDAADBADCDDFDAFGEHGEAGHADBBEACFGBDHADGCCABHHGHFBEDGHFEACEFCBAGAAEABEABGABHBEABGABFCBACGDDHFCHBCHBHHCEDCDDCDBC,False +271,7.0,9.0,4.0,6.0,4.0,10.0,14.0,6.0,GDDGADGAHAAHABDGFFFECFBHBEGEGHEGDCABGGFFHFFHFBGABGDBGCBGFGCB,False +272,9.0,5.0,1.0,2.0,6.0,2.0,1.0,1.0,EDAEAFECFGHAABAEDEBBEBAABAA,True +273,6.0,7.0,5.0,6.0,3.0,4.0,5.0,6.0,DBGDAGHAGECGFBHFBGDDFEDFHCBBEHHCAHBACBACAD,False +274,13.0,30.0,20.0,14.0,22.0,14.0,15.0,16.0,HBGBBDCBAHEFEBDBCABCGFGEHGECGCDECDBFDECGHBFHACDCBBHEHGGHFGBBBBHBBHBBGBEABHDBGDEGEFDECCFHEBHEHGEFCFBCFCDABAAHEECEECEDCEDGEBFEBAABGABCBCAAFDAFDHFC,False +275,5.0,8.0,10.0,12.0,2.0,10.0,10.0,5.0,HGDDCDFCDBGFCGDBGEAFACFDBDDBHDBCDCCFGCHGDFGCFDABHGBAGCGFABFEHF,True +276,5.0,1.0,0.0,3.0,1.0,2.0,0.0,3.0,BDDHFAHAAHAFEAD,True +277,24.0,23.0,18.0,24.0,16.0,33.0,19.0,28.0,ADCABCHCAHCAHEADEAHBGBCGFGFFGAFBDFGFBGDEGDGHHGHHACDDGFFAFFBFFEFADHDDADDFFAFGBFBBFHFCHBDADEAHECEDFDGFDFFDCBBHDAHBBHCEGEBHHBFFCCHHHHCHBBHDHAGCAGEDEHDGHDAFAFBBFABFAEAAGABGFEHCCBCHECFEDFGFE,False +278,12.0,29.0,23.0,26.0,19.0,18.0,23.0,13.0,BEBBEHBCAFAHEDDCDBBDBBDAFFAFCADCGGBGGCGHCFECEBDECGEHGEADBFDHFDGCDGCBCCHDBEABDCBDEBEEBDCGECBDHBEHEAGAFGHFHEFBBDBGEBFHGGHFGFDGCDGDDCFFFDFECCGCGGFBDBAACHEDBDDBGCAGBBC,False +279,16.0,11.0,17.0,16.0,19.0,22.0,19.0,14.0,GFAAFDCCEGCHGBEGDABFBDFEFEEBEBGFCGHHHFHAFDADEAHACBFCDFHFGCDACDFCGFEDFEGADGAFCEHCAHBBHEGCDDHDCAFCAFGEEGEEFBEFEHAHFDEFDBGDBGAFCAGCGGCGHE,False +280,10.0,14.0,13.0,11.0,22.0,14.0,17.0,12.0,EHCECEHBFGCGGCAHCDGCGGEDBBBFHCFBFBBFGHGHFABEAEGACGACBFDBCEECDEBFEBDGHDEBEGGECGEHGEDEEHFEHFEGFAADGADEHDAFDHFEEFCBA,False +281,32.0,31.0,18.0,18.0,36.0,28.0,25.0,12.0,GAHFABEGCGAEFADGADFABCADAEBAEFEHFGBGCBHDAHAABBBECFEAEEFEEFEDAEBAECADCDDBBBCBBEDBFAAFHEEGFCGEEGEFGEFAFDABCABDAFGFBGFEGBEACGGHFGAFHBBDEEEGGBHGFFAFFGEFGEBGDCHCHGBBGABEABEFEDADCEEFDCDHCDBGABAACAHCEFCEFBEB,False +282,19.0,24.0,17.0,28.0,20.0,14.0,18.0,11.0,CEGDBCDFGFGCADCEEGFABEDBDBBDEFDEADBGBEGBACDDFDHFBHGGCGAEGHEGHECDDGDFGEFABAEEHDFBDFBEEBHCDCCEHHDCGDBHDFDDADDEEDBBBBABHAHDABAAGADBCFBCBECDAGECGACGACFABFA,False +283,26.0,21.0,30.0,21.0,22.0,23.0,22.0,14.0,ABEAFHABHEFEEFBHDAHFBHFBAFBCBGGHGDHFDHFBEBBACCAECAECACGBCFFEFCEGGACBCDFAAHABGDEGDEGDACFEGDEGAFAACCBEABGAFDCFDFFGACHCEGCFGABCHGAHCDHCDCCDCGABDFBDEDCGFFBFEACCDCHDGGCGEEAEBAGDCDDCEEB,False +284,14.0,18.0,15.0,12.0,15.0,14.0,12.0,12.0,DHBFHFFADGAHCABFABEEFDEAGEAGDDBACBCCBGCBEEBEAHEHCFFCEFCBCGDCGDEGHGGABADBEEBEHCHHDBEGGFFEFDADHAHBBDFBCCBGABCFHCFA,False +285,16.0,15.0,17.0,12.0,11.0,20.0,18.0,11.0,HGHCBHCECFEHFEGDAFFGFEGFEAFGFBGABDBBGBACBGFBECAAFDAHHFGGAGGAEGCBDBBDHEFGGDGEHAHADEADEFCCFCFADDBCCBCABHAFFCFGCFDCFACDBCGH,False +286,11.0,13.0,7.0,7.0,10.0,17.0,12.0,13.0,FDGFDGFHABDDHFAHBHFFGCFHBGAGFFGFHHAGHEGHCGBCECDECDBHBEHBEHCAFGABAFBGFBEFGEABFBFDEFAEAHEABC,False +287,8.0,6.0,3.0,14.0,2.0,6.0,4.0,6.0,BGDFDCCDGAFBADBDHHDHCDHAAFAADBADBFDEFABDGHEGDDFHD,True +288,13.0,9.0,15.0,13.0,19.0,11.0,16.0,13.0,GGEDADGABGCBHAGACCFCHECDDCBAFEEHEBBEABEACFACEDHEAFEGFGDAEAAECDEFEHHEHBFFDCFDCDAGDHEBHCGHGGHCEFCGFEGEDGDCGHBGH,False +289,21.0,24.0,27.0,24.0,13.0,22.0,21.0,28.0,EBFBBCGBDHCAHFAHBBHBDHBDHADECDCAHCGHGFHADHDCHFBBAHBDHECABFBFFCDFGDFECBECBCHEAHFHHEHGGFAGBDCEHCFHCGGBEGFHBFGAFCADDFDDBDFCAFCHFDDACGACGDCGAGGHDEDECDAGHBFABABBEFBCCDEAHGAHGCCGCFAHDGHC,False +290,11.0,5.0,20.0,12.0,8.0,15.0,4.0,7.0,CBCCHDDHADEADEFDAACCCFFDFCAFCADCGDFEDCECCECFFHFFAGFCEDEBFFHCHGCDBHGCFDAFBAEHACCACB,True +291,20.0,16.0,14.0,23.0,25.0,13.0,17.0,18.0,GBEGBEGFEGFBFDBFDBADHAFBDFGDEGDGGECCECAEAADAACHHHHBHEGDADDBHAAAEHEBDEBGEAEHDGHAAHFABCEGDFGFCECDGDABDHBDECCABFBEEDEGFEHFEHGAHBDCDAEHAECDCFDCEDHGHEC,False +292,22.0,21.0,19.0,22.0,30.0,26.0,23.0,31.0,AHGAHGABADGFGGEEAEFDCABCFBCGBCBHCBCFEDFEDHADEFDFBHCBHAHEAHEHHEHEBGEAGEDCEHGACGDCFCEFDEBDEBDFHACEEHBDDGGEBCEBCGHFGEABFAEEBHABGAHGAHDHHDHEABEGBFAEGHEHCADFFDFGAFCDDGFHFFGFFDEBCHFEGFCDFHHCHFBEGHHADH,False +293,16.0,24.0,24.0,18.0,24.0,17.0,14.0,18.0,BDDACEACHABHABHECHGHEGEEFCHFAFAGFBBBGBEECEEHEFDBDDBDDGCGBCEHCEDCBFABFBBCCECCGBEBAABHECEGCEDDECFECFHCFHCGBCFFDDFADFAHHCGBBBCAFEBHGDGADGAHCBEAAFGDBHHEDCEDFEH,False +294,32.0,23.0,12.0,12.0,9.0,21.0,14.0,23.0,BCGBDHDCGGGDAFDFFBCABCABCFGGFAAFBHEBHGBGGDAFAACABHBFFDAFAHHBHHDHGDEADBHGBHBBHBBFACCBECAAAHABHAEAEDFGCCEAFFHEBHFHHEHDABAAGAGHADAAHAACEAHAAFFBFFBFFH,True +295,25.0,28.0,34.0,29.0,21.0,15.0,21.0,21.0,GBBDDFEAEADECDAGBCFBADECDBBDCCGCAGCDBCBBCBDCBGCEHCGACACFBHFDDBCHFCGAGGECFFABDEGDEFDHFHHBBHDAEDBEDCDDCDDCDAADFACEDHHGACGBBGAGAEGFGGHCACCDHGEHGEHGHCEACBHFEAAEACEACHHCHBCBECHHFEBBDCBFCBDDBDABAEFAHG,False +296,10.0,5.0,3.0,10.0,3.0,6.0,4.0,2.0,FCDBCACHBFABDAGEAGDADEBDFDAFGABAADEADHGDFFD,True +297,18.0,24.0,24.0,26.0,29.0,26.0,24.0,26.0,HAEHBEAEEHCACDDCFDHFGCBHCBCDHFDEADBBGCBGABFAFGGHGEAGDBCCGCBDFDDFBEFBEGDEGAADHADHBHADHCDFEFFEGGEBAHBCFGCEGEBGBFGEAAEDHFDAAGHFGEEGEEDHECGEDFEBBDCCDBDECFCBBEFHFCGFEHHEHHAGHCEHCDFCDFCDHCHGGHFEFFBFHBADB,False +298,13.0,9.0,11.0,21.0,12.0,21.0,9.0,8.0,DDADBAGGAGEAGECGEFHFCCFBCABCABHAEFABFDFCHHDDEDDHADHCHABFFFEAEDCFDEGGFDDFCDFEFFEDFEBADFDDFBDFCHBGFCEDDAFG,False +299,9.0,10.0,7.0,5.0,4.0,5.0,9.0,5.0,AEBFBGFGGAGGADCADGDHGHEBHBBGEBGFCHBCHAAFAABCECCFDDBCAB,False +300,9.0,10.0,14.0,12.0,10.0,5.0,22.0,10.0,GBDGFGGEGEHGDGGEGCCGACBDBBDABDAEFABBCEAEHAGCFHDGHGGDGADGHGGBFCDHCDGCGBDAACEHCEGCEGDHCHECHCBF,False +301,23.0,15.0,14.0,8.0,21.0,17.0,19.0,20.0,FGCEGAEGEDHEDBGGECFFHEBBBFDAHHEBAEBHCHEGAAHABEEFEEFGBHGCHCAHDAFGGHGDHGFAGBABFAFHEEGEAAEDAGFAEFACFACBHFDCEHBAHCAHGAHCCGCCGEAGEACFADFHBBHBF,False +302,27.0,23.0,30.0,20.0,17.0,18.0,24.0,20.0,AACCCBGDBFHBAECFFHBHHGHAACGCHDDBFBGGCHGAFGAGGAGGAHGCHGCDGCHBHABFDBDDEEDEEDBCFCCFCHBHFBAFBDFHFBAAAFCCGHCDBADAFCABEACGBFBEEBAEHAEGAHGACBBDACDFCDGCDGHDEEDEBCFFCAACHECGCBGCEGCDAAEEHGD,False +303,30.0,27.0,22.0,22.0,20.0,20.0,25.0,21.0,FCHFDBBDBGCAADEBGFBGABGFEGHAHBADAEDACBECFFCFFGDBGAHHAEHFCAFAACEDCFFBEFAEABHDGAEHDDBGCBGEBGEAEEFBEBDHDAAACCHCCHGDAGDFCFABFHBFHBGBBDHBDHEEHECHDCADAEDGBCCBAGEHGEBGFBGCCACCAGAADAHGHHGFDABGGGD,False +304,29.0,17.0,17.0,22.0,14.0,23.0,28.0,17.0,DABGFCFHAEGAFGFBCCBEDDHFCADEHDEHGHDGADGHGGCCFFFFCCEGHEGBDDDDDFDFGDFGCEABADBCHADBGDCDAHFFBGFGGHAGHAGAEGEGCAAHAAGAAEBAGBGFBHBBHBGDCGFCDFBAEBHCFEAAEAAHGAHGAGFACFDCFEAFDAB,False +305,11.0,12.0,13.0,10.0,10.0,17.0,17.0,13.0,BFDDADEGGFGEFBEAGHAGBACAECAFFBBFHBCHGFHGHGFFGCFCBBAGCDGDDGCGHCBHDGGFHFFHGDECDFCDEAGFAFBAECAECHBHHEHCEBF,False +306,7.0,10.0,4.0,3.0,5.0,2.0,7.0,5.0,BHBHADABBABGABHDGHDBCEFEEFCEBCEHGGCGBAABGAG,True +307,17.0,17.0,13.0,19.0,19.0,19.0,22.0,12.0,FDEAAHFFBFBGFBDFGDFGDBGDBGFBFFHFFABEGGGHAAHEAFEDFCBFCEDCDAGBAFBGHDHCGHGDEGDGCBBDHGABCDHCFHEGGDBCHECEECEADEAEGAGBAEEDDEGCEGCHACBAFBDEDAFGAE,False +308,16.0,19.0,32.0,19.0,25.0,21.0,28.0,24.0,BCGCCBFCFGGDHGDADAACACGGBADDGDDGFBCHHCFECDGGAEBAEGHCDBCHEEHAEHFEFFEGFEHDCCCEGHFHHGBGDEGFHCFBFHBGEGFCGFCBHGBHEBEEBGBAGEEGHEAHEBFEBHCBGGDGDCHCCACCADBAHEDFGCACCHHCHHFBAFAEEDCECCDFCDFCDFEG,False +309,12.0,7.0,7.0,14.0,8.0,9.0,9.0,23.0,HFHHBHGACFAHHHHHDHBGHCEHEHCFHCBHDAHDAHFGDDHEBGFDDHADHBDGEEGDACDAHDAHCGHAADAECBEGEFFAFBDFG,False +310,7.0,9.0,2.0,2.0,5.0,3.0,5.0,9.0,BBABAGEAHBGHFEHBEHBHHAHBEGBGGBDACFCHFDHAAE,True +311,26.0,28.0,24.0,21.0,11.0,21.0,26.0,17.0,BFBEHBHGFHFHDDGADGADGFDCFBCHGFAEAAEAAEAABDDGHDBEDCCGFCFFCBBGGBFHCGGGDBGDBDEBCFBCABGDBGDFGEGCCAAHBGHGGFFBAHBAEGCFBCECHFADGGCECCFCBACBGBBGCCDAEHABFADDADDAFBHFCHAAFAABHHCHBCDBGA,False +312,23.0,13.0,12.0,13.0,21.0,13.0,8.0,13.0,FBAFBAECDHHEEEEAACADHEDAEAEFAEFAEGAEGAEAAEAGGBCDDFHAHHFFHFCCACAEFAHFAECHEAEDDHDGBBCBDFEHEAHBAHBAGCCDDDFGEGEFBBDBBCCB,False +313,3.0,1.0,2.0,0.0,2.0,1.0,1.0,1.0,HACAACEFGEB,True +314,19.0,17.0,14.0,10.0,16.0,21.0,10.0,13.0,AHDAHEEFAEAGCADFEHCEBCGCCGADDADFADFAHAAHFEHFEHFEFFCBFEBAAHEHBEBCCGHEBHCBFCFFGEAHEACBABBABFFGFFGBBBFBGDGCCBEDADAFBFFCHEDG,False +315,3.0,8.0,4.0,7.0,12.0,10.0,4.0,14.0,DHEDBEDBECHEFFFCHDAEBAHHFHFEGFECEEDEGHBGFBAHBHEBEDCFHHFHFDHGBH,True +316,19.0,13.0,26.0,20.0,13.0,13.0,16.0,14.0,AFCBGBFCAFCEECHBBAGCDGCFGHEBHEDCCAHCFEAEDDEDAGCAFCACCADCGDEBFAGDHGDCBACHAGHBFHCGECDCAGCADADFGDCGDGEDFADCADFFDAEDHCCHCBHGBHEBFGBCABHHDE,False +317,16.0,18.0,21.0,25.0,22.0,16.0,21.0,17.0,GDDGDDEDFEGFEDEEDHBDHBCHDHBBBBBBCCBCCHFCHBCHEHADGCDGCBGAFABCEDFFAEBCHBDDEADCGDEFAEGAGCCDCCGFDFBDHCGHGAAFEADAAHEBHEAHFCCDCEAHEAFGBGEBGDGEFGFHGEHFAFDGEDGECEDG,False +318,23.0,22.0,20.0,24.0,12.0,20.0,16.0,25.0,AABCHBFHCDHCGFGHDHHFGAGHBGHBGCEECAEHGBCGDDDHCFHGBHGBHEBHDCCAHCAHAHCAFCDFHHEBDDBGDGEABBAEBCDDFDDFEDFACFABFCHHCHHGBFAEFBCGBDHFDBFDFDAADAFDCEHCBBDFAAAAGECDABDAEFABFG,False +319,9.0,5.0,11.0,3.0,6.0,3.0,10.0,12.0,HABHDEGCCCDFCBHCHHGHAGHCGHCDHCEGCGCEGHEAHFABAECGBBAAFGAEHAG,True +320,31.0,18.0,28.0,29.0,18.0,25.0,23.0,22.0,ADEFDADBAGBEGHEGDCAHAAHCFGCHGFEGFHGCGBFDAFDCFCEBABHDBAFAFFDGDAAHABGGCAFCACCDEBDCCGCCDCCAFGGCHBDHGCHAHBBBBBCCGAADCBDEFDHCAHCHHFHAECDCHDGHDEADEDFADBADEEDGCBGCBGDGEFHAFEAFAAFGEEDCFDHFAHFAFFAEFHEDGD,False +321,11.0,11.0,8.0,16.0,26.0,18.0,18.0,26.0,HFGEAHHHHDBHGEHDFAGGDEFDEFDEFAEFBDFHDEEDEEBGEHEHHEHACGGEBHEGHEFHEHAEGFDGDDGBCEAEGAECDHCGHFEHGAGFCHHEHHFGDFEFFHBFABHDGFFBCEBAECGDABDHBC,False +322,6.0,3.0,4.0,2.0,1.0,1.0,3.0,2.0,CAAFAEHAGBDHCDBCGBAGCA,True +323,10.0,11.0,20.0,18.0,16.0,14.0,16.0,14.0,FCGBEHDGCCHABGBCGACFEFEEFEDCCCBGCFHCDAGDAGDEDFHGBAGEDFECGACGEFGEFEHCDHCDEFHGBHGEFDEFDEADBAEHFCBGCHDCHDCBDCFHBDABGAHDHCD,False +324,14.0,16.0,12.0,17.0,15.0,23.0,16.0,14.0,HDEBDGFAFHDDHDHECHEBHGHEGEGFADHGEFGDFBCEBGAFFAGFHBDHGDCGDCACFECFEHFAFBCEHCFBEFCEADHABCBBCFBAFAGFAEEAGBBECBDGBFGHGBFDDFDDFGAFDAF,False +325,15.0,13.0,7.0,9.0,15.0,10.0,11.0,11.0,BDABDCBEEECAECHCFHBBHDHEAHEAGEDEABEDHEGGFGGFEFBEHEEFBHAAAAAADAADFAEFGHHDFHGAGBBBBCDCGBFGFCG,False +326,18.0,22.0,21.0,20.0,18.0,16.0,22.0,11.0,FAHEBHABFAHGAEGHHBBBCBGCBECAAGDACFBCFEHGDHDDCDDFFCEGHEBHCFCDFCDGCHBAGCEBCBDGBDCBDHGEFADGEFABFGCFCDBCGACGABFACDEDEBDAFAFFABGEBGEGEEDEGDAGAGGEBGCBDCED,False +327,13.0,17.0,20.0,5.0,21.0,19.0,14.0,10.0,CACCAECGEGAFABCCDFAFFHFCEFCHAHBGEECEECGEFDECDECEEABFBEAEEBEDHCAHAADBABFGFFGFGGFBGBHEBHGFGEFBBGCBCCBCBECBCGFEHFHBGHACEFF,False +328,21.0,20.0,17.0,13.0,23.0,15.0,20.0,19.0,HECGCCHADAADGADBEGBEABEHFGFGGFGCBECFHBAAEAHDFHFFBGEBGCBFHAABAABDCBDCAFAAHCGDCGEEGHGDEGCHGHBFHDHCDBCFEAGCAHCEHEEFEFBDHHDEBEEDEBGGAHGAHBEFBECEFABGABEC,False +329,24.0,23.0,29.0,30.0,30.0,21.0,23.0,19.0,HADHFBHFEHCEHDHCDFCBABEEBDEHDACBGDBCDBGDBADCCDABAGCEGBDGBEGCDFAFFGEFGAGEAGEADCGHGBDEDAADEHBAHCAEGBGFBFHBGEBDBBAEEDEEFAEDGCABCEDGFFGECCDACHBDGBDFCHECHECEACEADDDEDFADFAFHCFGCADCEECFCCFCCAEBGGHHCHFDHFEG,False +330,7.0,6.0,9.0,9.0,7.0,8.0,16.0,10.0,HGGAAGEEFBEDHFDAFBAEDFGHFAHGDHEECGHCGCCACGFGHFAHEBHCGGCBGDHGDCGDCGBGDBDF,False +331,15.0,22.0,24.0,18.0,22.0,22.0,16.0,24.0,ABAFBECDEDAHCCGCAAHHCHHGBBGBAGBDGEDEHAECACBBFHHEHHEHHFHDCHDCBGFHFFHAEBFEFGDHAECEECBEFEGCCFBCGBCDEGHBGHFAHFGDBGEAGFADCBCCHCFFDEFEEFBEFHEHDCDDBHDBGFAFFBCCBCFBDADCGDE,False +332,9.0,18.0,16.0,12.0,7.0,14.0,10.0,14.0,AADCABGADACDAEDCHGCBFHBFHBEHGEFGHGECFBCDDGDAECHBCEBCFBCHHFDHDHHFFDFBGFGHBGECCFDFHDBHGBCFFABBACBCBBCB,False +333,24.0,10.0,12.0,14.0,8.0,11.0,24.0,18.0,AHAAHAADADGFHEEGBECBDCEACAHEGHEFHADAADFHGBHGBGBCGAGADGADGAHCAHFHFGEGGBACDCCDGFGBHCFGAFGBGEHACHAGGCDDHDAADGHDGFCGAHBAHBGFF,False +334,17.0,19.0,16.0,21.0,12.0,28.0,7.0,21.0,BCEAFGACAHCFEBBDBBDFFDBCDBFDFFDHFABDGBDFFGFDHFCGFGHCBHAFCEFHHBHHAHFADFBFCBFCBDCHEHDCADFDDEHDECDFCAFAAHABFBDFHFCDGHDHHCHECBEAEHAEFABDEFAFBGHEA,False +335,5.0,1.0,17.0,8.0,5.0,13.0,6.0,9.0,HFEEFACCHDCHDCHFBHDDCACCFCCGCFFDEFAFGCFHAEGFEGFDCCAFCHCGDCGDCHFH,True +336,7.0,5.0,7.0,10.0,4.0,6.0,4.0,9.0,CABCEBDDFADCAFCFGCEGEHDDBFGBFHCHHGHHDFDEHDAACAADHBDH,False +337,17.0,14.0,20.0,15.0,14.0,12.0,26.0,25.0,FEFFADAGDAGFCHHBHHBAFEECECAFCDFDDGGCHGCHFCGDGGBBGDAHDHECHGCBBBHDEHCCHFGHFCHBCHDAHCAGCAGEBHEBAAACEECEGGDHCEBFEHGHCGHCGDABAGHGGBBGFGGDGHHEHDDAAGA,False +338,17.0,17.0,8.0,23.0,13.0,10.0,15.0,13.0,DFFDBGEBEBCDBFDBAEEAFGAHDDDBBDEBGEBGBAGBGBCGEDEAHHADHDDHEDHGGHADDBDHHDCHDAGAECADCHDFBBFABDAFCAGDFFCAEGAEGEFGBDGCHAHA,False +339,18.0,24.0,23.0,25.0,16.0,22.0,30.0,24.0,DGBDGDDCDGCBGFEHEAAFCACGBFEBGCGCABCAFAGEAGEAHDCHBFEGHEBDDBDDBGABGFDGFBHCAEEAGDHEHFEFEHFGHFBFFGCAGCACCDHDDHBDFGDFGEEGBFDHHBCHDFFDCCABGBDGECBEGGGHDCHACHBHHGGHBGABDABHFCHFHHDBABGFCGFCDC,False +340,2.0,2.0,13.0,7.0,3.0,3.0,2.0,4.0,ECCCDCCACCBDCDFCDGAHHFEDFBDCDCCHGCHE,True +341,4.0,3.0,4.0,1.0,4.0,2.0,6.0,4.0,GAEGBCHBCFGAHGAHBACEECEGHGDF,False +342,10.0,14.0,13.0,18.0,10.0,15.0,4.0,7.0,BFBBADBAGACCABFAECCFCCEDEHDABBAFGGBDBCEBFDBFDEHDGHFAEECCDCCFHBFDEDDFDDCDDEHDEFFBDFBDFACHAFH,False +343,2.0,3.0,3.0,5.0,8.0,5.0,2.0,1.0,EAFDCDDCHEBFEFDEFEABECBFGEDGE,True +344,16.0,17.0,10.0,12.0,19.0,14.0,18.0,24.0,DGDFEBGECFCBBGFFEFHEHBEHGCBACBEGFGGHCBHGBHAEFBFFBHHBEHAGAADFAGFAHFAHGACGAEHABFGEGHEHHEHCABDAHEABCDHGEHGAHDDHDDBEFBGDBADGCHECHDHEEE,False +345,12.0,6.0,8.0,11.0,11.0,7.0,6.0,8.0,EEABBCDDGADCAECADHABGABECBECFEFFECDEGHAFHDGHFHAFAABDAHCEHAEHFDCDEGDGD,False +346,14.0,12.0,14.0,18.0,13.0,23.0,16.0,8.0,ECHBFBAFEFGCCDDGFDBFEGFEAFECFEHFEGBDDCHDHAAGAAGFBDBGDADDHGDCFFHEEHCEBGDGCFECFEBFDACDFGDAGDGGCGBABDCBCBAFFAFFAFEAFDHFCG,False +347,13.0,9.0,9.0,6.0,6.0,16.0,14.0,5.0,GEACFCDFGAFGAFCFFDDGGDBGDEGBAAHGAHFFBFFEEFBFFBFCEGBGGCECCAAHAGHAFAAHACGGFBCBBD,False +348,2.0,2.0,2.0,3.0,4.0,6.0,4.0,5.0,EFGDDADHEFBAFECFECFHBFGGHHGH,True +349,25.0,25.0,26.0,14.0,12.0,22.0,23.0,17.0,GCCGCCGEEDFADFDCCEHCBHCBGBBCBFGBAGFGHBGABFAGFBFFACCHHFHABAABCABGHEGBCGBFFAFGACCDDCBFGFAAAAAEACEFCEFCADCAGHAFABFDGADHHGBBCHGEBGCBHCBFDHGHHCEHBBBBEFAFHDDGFDCAGCAGDEDE,False +350,26.0,15.0,7.0,12.0,18.0,16.0,17.0,8.0,GFECAAAAAHFADABEGCECDGDAGEABEGBGBBGBBGCHEFFDFFAAAGEAFBAGDHHFGGAGEADFAEEBEFCGFDDFGDFDBFBEHHAHEAGEABEABEBBADAADAFFCEGCHAE,False +351,19.0,24.0,27.0,20.0,25.0,23.0,28.0,19.0,HHCHFCDGDBGDFGCBGDFGBFEDFBGABHABCABGBGAHGBHGBABCCEEBDFGDHGDBGHFGCFGCBHFBHECGCCBCGBFGACGDCHEEDFBGABFAFFGHDAEAAHDAFDEFDEDEECFEGHECAGCECCFCBABFADCAEGEDDFHFECFEGABGAHDHECBACDGHEEEEHECBECGFC,False +352,11.0,14.0,21.0,19.0,18.0,15.0,12.0,19.0,CGFBDFCAEDFEHEHCEACEAEEFGDAGBACBFCBFABDDGHDEHFGADGHDHCBHCEHCDHBBEFGFBADCGBHEADECDCBDCBACBACBDCHFHHCHFDGCDECGHCEEGHEHFFFFGEHDCHDED,False +353,14.0,12.0,11.0,22.0,22.0,10.0,7.0,14.0,BDEBEHDFDDCDEADEHCFHCAACAABBCDBHHEDHEFBAFDACABGEEDEADFADFBGFAGCGHCFEAEDGDDFDEEBEEBEHHEHHEDEEBHHCADCACHDDGGBFEDDE,False +354,25.0,23.0,25.0,17.0,15.0,24.0,9.0,25.0,FHABBAFCCFBCFBEDDHCHGBAEHCEBDAADFADFHFHHFHBFBCHBHHEHDACDFFAGBGDEGHHGDDCCCAHCEECAEDECFBBHDFCEFBAHAAHAFHAFHBFAAFAGGACEAEDAFDHEGFCFFCDFHGFHACHABBABECCCCACCBBCDBEBBHDB,False +355,17.0,20.0,28.0,20.0,27.0,26.0,18.0,20.0,FCDHEAHEGECAEDAEFCHFEFCCCCBECHEHEDHDHHEGHEDFEHAEDGEDGEFEECECHGCDGCBEDDEDDFDDBGGCGBHHAACABGGBCGBCGDCFHCFBCFBHFAHFEFFCFFBDACFCHBHEEFBGFBHFDGGCECAAFACFBBBABBDBEHCAFFEGCADEADFFBCGA,False +356,11.0,9.0,19.0,9.0,17.0,23.0,24.0,22.0,DCFDCHHGFEAECFFCFFGEFGFFGAHGBHAADAACEFFGGEHCAHCBDFFDGGHHBFHBHHAHFFGGFEGFCGFCHCGGGGEEEFCDHCDECHECEBCFGCHBCHAEHCEGFDGCHBEHBGHBGHFAEAEGGD,False +357,15.0,19.0,23.0,15.0,30.0,8.0,15.0,12.0,EDGEGBEGAEFADGHEFEEDEDDEGGFDAEEAGDAEEADEAEBBCFBCGECBEGGACEFBGDHECHEAHEHGGABCEDDFDDEDBHDBCBACACCGCABEGHCHCCBCCAFCHBEHEHHCCBCEBCEBCEBFBBECA,False +358,8.0,10.0,3.0,16.0,6.0,11.0,10.0,8.0,EADHDFFDBFEGFGCCAFCBHDGEDHDDFBBFEBHHDAHDHEDHGDAGDAEDGDGFBGABGFDGFABBADBF,False +359,20.0,14.0,12.0,8.0,11.0,4.0,10.0,13.0,BAHGAEDBEDCADCAHBABAAFAACGBHGBHABHEHCCHBCGAEACGDCADCHGAECADFAEBDEHFCHEAADHAGHFBEBCEAGEBGBGHB,False +360,26.0,15.0,17.0,18.0,13.0,10.0,21.0,9.0,HCBGGBGGBCCDDCDCCHCHHEGGEAFEDFAGEBDHBGAFGDGAABCADCEGCFGAEABEADHABGAEGFEAFAFCACGADDBEAGAABAHGDCDEADECDBCDBCBHCFDDFAGAEGAHGAGAAFBDB,False +361,15.0,32.0,16.0,34.0,25.0,18.0,29.0,23.0,HDFHFFDABBBBEEBGEBGEDEEGAHGBGBBHDAEGCDACHECHBGDBGDBGDGDDFBGGDEBFAHHHHEHHAHDADDEDBEBBHABHAFGDDBEDHEDHDDHGCHCEFDGGDGGBCFCCFEHFGGFHAEDFDFFCAEGABDFEDGBAGBGDBCFBCHEDADDCDCBBBDEBDEBGHCGBEABFCGGEFCEG,False +362,22.0,28.0,20.0,25.0,21.0,16.0,11.0,16.0,BHCHFBFFBDDBHHBAHBADBAHBAHGCCFCBBDBBECAEFEDHHBCCFDCBBBEBHEBFGBHGDHCFFCFAHHAGAGDBFDGFDBCGEADBFBBAAFEDGEDFDAAGBAGAABEDDACBECBEFDAHCCCCGCEEHAEADEDDEDCEACEAEDDEDDE,False +363,11.0,11.0,7.0,6.0,9.0,8.0,12.0,8.0,FBADHHEHFGGCGAFEAFEGFGGHGHCCHCCBCABAEBAHDDCGFABEABFABABDEBDBHAGGFBGEEGDE,False +364,5.0,2.0,8.0,2.0,1.0,2.0,9.0,6.0,AHGACBAGHCGHGBEFDAFGACHCCGCDGCHGHGC,True +365,33.0,17.0,16.0,24.0,25.0,19.0,21.0,11.0,GDDGDDGBDBAABAFECGEDGEDFAGCACCFHCGHCDAADBACFCHEDAEHABGGHCEEEBAEFEDFDCFDHFDAFAGFBCDAFGEDDEHBEDBDCBHCAGFHFDACAGDABEABGABGAHCAGDAFFGEFDEFGFGEEEAEAAEAAEAEFBBAHBABCEGEDGAA,False +366,24.0,28.0,22.0,9.0,23.0,15.0,15.0,17.0,HEGHECCBBCBBFAEDHBFCBFBBFABGEGCFDCHCCBAAHAADABBBBAECHECEEHEEBAECDDAGDFGDFCDCGBCEBCABEABAAEHGCHEFHEDHFGGAGEHGCBBAFBAHCFEEGAEGABAABAHFHBCCCEHAEBBEGCGFFBHFA,False +367,22.0,19.0,28.0,25.0,31.0,21.0,23.0,26.0,HGHDGHDGEBCDDCAEEADEDEEHAHBDCEEBEFGAHAADGDHBHFCEGEDBFDEFEEBEBCEFCEFCBACBADHADEGDAHCCEDDEDHFAHECDDCBEFBEGBDCHCHAABAACCHCCHCDHAGCAGEBEEAFECHBCHGCGGHFCFAGGEDAFDCBECBEHDEFFGFDGFHGFGGFGFFBFHBCCGAGHAHH,False +368,19.0,23.0,22.0,14.0,18.0,18.0,13.0,20.0,GAHHDGFBGDBFFBHGADABEHCCFDCBDAGDBFBBFBBFBFFEFFAHCAFGAHADHEBFBAFBECCEBCDDAEDGEHBBBBACBAEBDECHEGFCHACFDBGCHHCHGEHCCHCGHCGECEAGACHFCHFCHDEEEEEBDACAAHA,False +369,8.0,9.0,10.0,4.0,11.0,7.0,17.0,8.0,GEHGEBGFGGFCGEHAFBBFCBHCFDCGEHAEGCCGAEGBBCHBHFEAFGBCGADGADEADCGCHGEBAEGHEG,False +370,14.0,14.0,22.0,16.0,19.0,13.0,17.0,12.0,AEAAGFACECCFHBFDEGEAGADCEHCECCADHDEGFGGCCGBHGBHGBAFDGECGECGHBDHBABFACDDEBFECFEFFCAFGEGEEGHGCBACBCBDABCGBDFEDEDDHDFBDHCCHCCHEADE,False +371,24.0,19.0,21.0,13.0,20.0,18.0,17.0,23.0,GEGEADCDGEHBDCBDHAHCEFCEFEEFCDFBEGAGFHGFCCHCCFFCFFAADAFCABBBHGCHDHEAAGCAGDABHHCHHCHGBEFAAFHAFHGHHGDADEABEGBCGCDBADEHHEHACDABGECFEFEEABEBBHBBABCAGCFGEFABHAH,False +372,3.0,3.0,3.0,4.0,0.0,2.0,1.0,2.0,DDFDDBCABHABACFGCH,True +373,11.0,27.0,14.0,16.0,27.0,12.0,14.0,25.0,BGEGGBDBADECHGHHEHADHDGAEAHEFHBFHEEDGEDECBHFEHEBHDDCEABEAHEAHEBEEBEGAHCHHCBBBBBBBCCGDFGEBBEFHFDHFDHFDEFDEDEHGEAEEFBBHBBADBCBCCBGFDGHEFABBGHCCCGCHH,False +374,3.0,9.0,10.0,10.0,8.0,7.0,11.0,11.0,GCGGBBHHCCGFDGFDHDDHFDBFEGEEBECDDAECCBBCHGCHGFHADHACBEFHEBHDBHDGGFGEC,False +375,23.0,33.0,18.0,22.0,30.0,18.0,26.0,23.0,EBDEBDHHGCCGCFGADGBCGHCEHFEHDEHBEGDDGBHGAHDAHDBCBAABCFBCHEFDADCAEBBBBHBAFBAEBAHBHFBCAGCFHDADEAFECEECEFBBGGCCGEHHBBHEDCAFAHEEFFEAGABGCDGBBGBDFBDFGDBEDBHFBGDDGAEBAGAFGEEBEECEABEHGGADGDGFHGFEAEHHE,False +376,26.0,12.0,16.0,23.0,9.0,18.0,21.0,30.0,ADDFFDFFDFFHCFCBFAGFBGHEDHEAHECHCABFAEAAGAAGDDDDCFGCAHABDEGFHBCBCADGHDGADGHEGHDGHFBHGDHCDEABHGEHBDADAACHHHHFHAGHEGHDGHDHHCCCAHDHHGGFAAAAFABFHCFGBHGAACBGCDD,False +377,14.0,10.0,11.0,6.0,8.0,8.0,6.0,11.0,FCEFBBABDCHECFBCGBHGFHECGCFAFAEFDBACADCABCHHEAHGAEBAHAAHAAGFDCBDCBDGAEHHEH,False +378,10.0,13.0,11.0,8.0,10.0,9.0,5.0,12.0,ADCHBEECEEADBACBGBBAHBGHCCHGBHCCACCFHCDBDDFFDFFBFEAEHABHDBDAFHECBAHEGHEGHEFBAF,False +379,26.0,14.0,13.0,28.0,14.0,24.0,18.0,23.0,ACEAFGAGABGAGGEHAFHDCDDFFCGHCDHAAAEFFEGABGAHHADFGDFBCAGCAGBACDDDBDDEADCCHGEAGEABHHFHCCBDABHFEEDGHBGBBHFDFCDFBDADDEDDEDHFDHFDHEDHAAFAHDGDBGEFFABAECAHHFFHFFHDFHFG,False +380,21.0,15.0,24.0,10.0,21.0,16.0,24.0,20.0,GBFFDHFBFGEFHHHHHECHEDEEBCAFAABGACGBCAECBCCBEDFCDGCEEEAEGAGGACDAFDCGBBGBBCAFFDFHBAGGDGGCCHEAFEAFCAFCAHCGGAHCACCAEGHEHEEGEEGDCHDHHGCEGAFHHEHACBCFGHBGBAG,False +381,15.0,21.0,27.0,23.0,28.0,27.0,27.0,20.0,BCBHCAFBBGEBDEDHCDGCGGCGDCFECDECEBCEBFEBFGCGGBGABFAEHCFDCHEGEFFFBGFECCEHCGFFGFHGBECCFCFAEDAGAHDAGEFFFAFDACCHCHBBHFCDAGDHGDEGDBDEHDHHFHFBHDBFDEAGCADBDDBDDEEFEEAGEGGBCGEFEEFDGHHCHFEHCAGGABCE,False +382,0.0,4.0,3.0,2.0,1.0,1.0,2.0,3.0,BCDBHDBHFEHGGCBC,True +383,1.0,2.0,2.0,6.0,6.0,2.0,4.0,2.0,CHDAEDGEDCEGEBGEFDEDGHDFB,True +384,12.0,14.0,12.0,10.0,21.0,16.0,19.0,20.0,GDHEBFGHDHCEABECBDCAHGAEGCEBCEHDEAEBHEBHFHHBBFFAFDCGHAGDCBFHGHCADBAHBGHBGADHFCHFDHCHECEECEGFEGEAGEGGEBFEGAEBAFFFEGFGGDGHFEHF,False +385,9.0,9.0,5.0,9.0,10.0,4.0,7.0,7.0,BCCBABGHBGDEGDACDBEFBHDGADGAEHHCFCEFDEBDBBDAAEEAEHADAGEHGFHE,False +386,15.0,9.0,11.0,11.0,15.0,15.0,12.0,13.0,EGCFFCFGCFHFDHCHCCHACHECAGHFFABEAHEFHEDDEBDHBDHBECDEADGFGFBGFAGFAFAHEEEBDCDGEHGAGGABAAGDFDBEABEHECFAA,False +387,17.0,16.0,9.0,11.0,9.0,4.0,15.0,11.0,DADCFEBAEAGCBBHBEGBDABFBDFDHCAFEGGEAGEACHABHAGHDGHBHHBGDEGHCAAGDAHACEGBBGABAACGACGBDGBDHBDCE,False +388,10.0,3.0,8.0,5.0,5.0,8.0,6.0,3.0,BDDGGCAECAFGAFCACADCEGCAHCADCBFFAFFHHFADEGFEGBEA,False +389,17.0,13.0,28.0,32.0,15.0,31.0,24.0,29.0,HGHCCHGBFDBGAAAAEDAFHHDEGFECFHGFCFFEHFDHGDCCFCHFCFDCFDGEHBEHGHHAACAEDAHDACGEGFEBHDHCFHEFHGFAGFACDACBHCDHCDCCDEFDEFDHFECDHDDCGDGBBCCFDHBDFBDFCGBBHAEHCDGGFHGHAGFBDBDCGFCGFDGDDFDHGHAFFAGDCEDCF,False +390,23.0,24.0,19.0,26.0,25.0,15.0,25.0,27.0,FADECFEGAEGHCFDCBGCBDDHDDHDDAGAHHAEBAGDAHBHGBFGBGGFGDCADCBHBEHDEAEHGEHDBHGBHEBDGBHECAEDADDAEHFFHFHGGCCHHEFECCGDEACEHHAHGAFAADBBDCBGABDACCADABFABEHFEBEEBDDACDEEDGGGGBHGBHCFGCFHFBHCBEGEE,False +391,4.0,5.0,5.0,5.0,10.0,9.0,7.0,10.0,FGGFGCEGEEHHDHGDCEDAHBFHFGDFEBHBHHAHFCCFACFGBFEEHEEDEAB,False +392,2.0,1.0,3.0,2.0,5.0,3.0,4.0,3.0,FBGCCGDCAHEFHFDHAGEEGEE,False +393,32.0,34.0,23.0,23.0,23.0,22.0,17.0,26.0,AABCCBCADCAHAAEFAFBABBHCCFBFGDHDHCAHFGBBCCBHCBHBFCDFBHBEABEAGEDGECBEBHEBAEFHEBEBDHAHHBGCCFDDFDFBDHBGAAACEACDACHADFAGFAGFHGFDFADFAHEAEEBEAGDDHCDEFDBHCGGDGDAHABHEBHEBEEBEHFABAHBGEBHCFDGFGFEDADCACHACBGBB,False +394,10.0,5.0,5.0,10.0,12.0,9.0,5.0,11.0,DCDEADHACFADFADABDHGHHDAHGAGEEBEFFCFAEDAGBAEBCEHDBHFFCEFHEHHEGEEDHF,False +395,9.0,8.0,7.0,6.0,6.0,3.0,2.0,9.0,BAGBECDECDCHEAHAFGBFHBAHDHHAACAACHHFHBDDBEEAEDBCCB,False +396,28.0,25.0,16.0,17.0,19.0,17.0,23.0,14.0,FBGFAAAHBHHGFCGDGGBGGEGGEFCEHCDGBBHEACEGBEADCADGEGHDGAAAAABFABFADFCCBHCADEFGEDDBDACAABAAHHHFACFBDAADBAGBGEHDEDBBFBBFBBCEAGEBHEBHEBEFBCFECFEGDGBAGDACDHCFCFGAGAE,False +397,11.0,7.0,11.0,10.0,5.0,9.0,10.0,7.0,BCHBAHFDBFCHFCDDBHGAGCHGCGGCGGFGEAEECDDFADEBFCHDCHBGABGEFDCFDFAAADAACA,False +398,21.0,30.0,21.0,28.0,27.0,13.0,18.0,24.0,CBDCAGAAEHGBHBHHFHHAHHCGHDBDABFBEHDEBCEDFDCFDCFBCEDCBAEBEDBEBBABEDGFBGFEEAEBGHBGCBACBDCEECBDCDDCAAGDGEAGEAFEGEEBEHFDHDGCEBFEBDGDFHAFHFDHECHGCDGHEGDBDBHEBHGBDAAAAEADDDCABHDCHCEHCHGBBA,False +399,8.0,12.0,5.0,5.0,7.0,5.0,5.0,13.0,HHGHBAEGABBCBBCBBCFBCBHADAAFBAEBEBFHDECEEFHGAHGHHDFHDGHAHHED,False +400,7.0,6.0,11.0,5.0,6.0,14.0,10.0,3.0,AEFAEBCFDCFCFAEFCGGCGECHFGADCBDFGCHCCABCAGGEFHEFGAFBFBGFDGFDBF,True +401,5.0,2.0,3.0,1.0,8.0,3.0,7.0,1.0,BAGCFGEEAEBHEGFAGFDGEEGECAEGAC,True +402,7.0,14.0,22.0,10.0,18.0,10.0,12.0,15.0,GHECCAABBCBBEEBEGBDCEECFGGHCHACHAHFBGGCCCCHCEFCFDCHDCHDFHECHACDBCBAEBDEBDGGEGHDCEGHECEECEEHBEHDFBFBAFHDFGFCG,False +403,14.0,14.0,19.0,22.0,20.0,22.0,14.0,19.0,ECCEDFDGEDEEBCBHDAFBAFAAECCFDCEBBEBDAHCADCFDHEBFEDFEFEGFEAFHAFHGCHEEHDDFEDFDCFDCFCBAHFAHFHHFBDFDDEHCGGBGHBAHCAGCEGAHBHCGCEDEFDFGDHGFCGBBGCHGHDDA,False +404,9.0,11.0,17.0,12.0,11.0,7.0,12.0,10.0,BCBDCEGCECEGCDCCDGGAHGEBGBHCFCAFHAFHADEAHFDHEBCCDCCDCBDHEDHADBAHCHDDGBEGFGGBECFEFEGBAGCAB,False +405,5.0,5.0,3.0,4.0,12.0,4.0,3.0,6.0,DBGAEGEEDAEHAEBBEBEEHFDCBEFGEFCAFCEHHAHEDH,False +406,15.0,17.0,23.0,27.0,15.0,22.0,16.0,20.0,EFCEGEFDBFHCCACBDDHDCFBHFHGFCECAEABGBGDHCDBCABGADFDDFECCACFAEFHDGHDBHDAHDHHDHBFEFDEADFADBDCHDEHFCHFGGFHGHHEAACAFCFBDDCEBCGBDGDEGDBGDHFCCFDEHCBBCBGDFGAFEAGC,False +407,11.0,16.0,12.0,20.0,16.0,15.0,13.0,15.0,HBGBDGBDGFGEFCCHCDHCDHFFCDBCFBEEECEFCEABEHDEDBEFHFDAFDBHBBHDACAHFAFBAEBDDDADDAFDGGGEEGHEGDFHBFHGDBGCBGBACDAHHCEAEEDHGF,False +408,16.0,12.0,20.0,13.0,15.0,13.0,22.0,14.0,HACHAGEAGFHHDDCEDCBFEDFEACBBFHBFHBCGBCACCBDDGDDBEFEGGHDBDDGGFHGAHFEGAEACDACGABAAHEABECECCECGGCAHFAHFGGFEECEHAFDGGGGCFHCGGCGBC,False +409,4.0,7.0,9.0,5.0,9.0,7.0,4.0,6.0,EFCBHCFAFFACFDHHBHCBGBBGBCEHGECBAGDCEFCDFCDEEHEEAED,False +410,12.0,11.0,9.0,6.0,6.0,6.0,2.0,5.0,DDCDHBBABBACFACEBDEHDHBFBAFBAGCAEAEEFHCBCCFHCAAEAABDABGFC,False +411,10.0,13.0,4.0,12.0,8.0,3.0,7.0,11.0,BBHBBDDDDDEEAAHAAHBAHGEHGHHAEDEEDACDBBDGCDBBABHHCGCFGFEGBAGBFDDAEHBH,True +412,2.0,7.0,4.0,0.0,2.0,6.0,5.0,2.0,BGBFGBFGBCGCEACFBHFEABHCBGFF,True +413,28.0,23.0,16.0,19.0,25.0,12.0,17.0,19.0,BHADEAEEHEEAGEFBBCDDAGHHGHAEBDFBAFBAHAEHBECBDCGDGBFGEEAEEDBDDBHDEHGECAACGACABCABFABCADEAHEDBCGFEBFEADEBEGADAAFAFHADBACHABHCCDCDBFABGAEGCGFHACDEGHHGHGDHFBHEBEGC,False +414,4.0,13.0,10.0,10.0,10.0,2.0,11.0,8.0,EEGCECCGBBGBCGDEEAGEDBHCHHADHDBHEHCFBDBGDBDDBDEADEHBCAGCBGEGCBGCBGFH,False +415,13.0,21.0,20.0,13.0,22.0,19.0,15.0,24.0,HFDBGDBHHBCCFHHFBHFBHFBHACEFEHFCBGBBFBHFDGECGFCAABGCFGCHHBHHEGFEABCBECEECGDCHHFEDAHBAEEDECDHDGHFGHFAECAFBAGBDECDCHBHHDCEFCAFEHEEGEAGEAFEDEBACBDCBGG,False +416,21.0,17.0,11.0,9.0,12.0,14.0,19.0,7.0,CGHHGBDBAGBAGBDGACGAHFFBFAGCACDAGAAEAEFCCAEFBCFGCAACGEFFBDAEDABDCEGEFCEBBHFBHEBHEAGGBGFAHFEBFBBDABFAGGAGGDGADE,False +417,6.0,8.0,8.0,1.0,1.0,6.0,7.0,5.0,BADAECHCCHCCHAAFCGFBGBBHBBGFCFHCGGBGGBFFAA,True +418,11.0,22.0,19.0,15.0,20.0,16.0,14.0,28.0,CCEHHDBHECHCGAGDCCABHFHHEHDEGBEGBDDBDEBHBBGFFCFFHBDHBCHBEHBAHFFGFCDHHDCHBEABHDBHCBAAEFDCBCCDFHEFGBDABGFBCADEFDGFAGEHGBHCBCGFAAHEEHEFHEGEEHEEHCGHC,False +419,25.0,19.0,13.0,15.0,18.0,30.0,15.0,15.0,FHCDCFBEHCABEAFAFHEFDGFDCDEHAFGAFBDBBFBBGBAHFAGFBFFBDBDDEGFBDEBHCBFCEFCEFAECAEFECGADBABAEHFDGFGGBGFBGDAAAHAAHDFHGCHFCAFEAEEDECDHBFAGHAGFEEFAFFAFAHCAHG,False +420,5.0,4.0,3.0,9.0,10.0,5.0,4.0,4.0,DEBDADFEFCEHEABEAEEFEDHGDHEDCFGCFDDGBDGBEAAH,False +421,21.0,22.0,19.0,21.0,16.0,23.0,24.0,24.0,BGGDDGBHHHHGHHDAGFAGFBBFGGFGEHBAHECFACAGHEFCEADEAEBAHBGBBACDACDHCDHCHBCDBDDGCFHHFHHAHEEHCGCBGAADFBGEGFCCFCGFDHHDHCBFDAADABBCBFCFGDECBEFDEGDEDFABFADFGBFGFAGFADHHEGABCFBGEE,False +422,5.0,3.0,3.0,1.0,0.0,2.0,1.0,4.0,ABCABCBGAHHHFHAFCAD,True +423,8.0,5.0,10.0,3.0,2.0,6.0,4.0,7.0,CAHCAGAAEDGFCGDCFHCAHCAHBBDFAFFGBFBBCCCHCEHAH,True +424,4.0,2.0,3.0,3.0,3.0,5.0,4.0,1.0,GDFGCGACDACDEBFEGHEFFAAFB,False +425,20.0,29.0,28.0,22.0,37.0,21.0,18.0,23.0,DCDEFDAGCHCHFDAFEFFEHDEDBEABEHBEBFCBEDBCDCCEGCEBCEAHDHHDAHGAHBBBFABFABACBADHEEHEEAEAAEACDCHBCEDEEBEGGEBEFDGCBBBAFDAFCAFCHEDBEDGECHBHGFGECEDGDFECFDCFGHECEEHFEBCABCADEAFEGBBHBFGBEHCCHBCGBEFCHHCHGGGGDF,False +426,3.0,6.0,6.0,5.0,11.0,8.0,8.0,8.0,ECEBAECEDDEBDGBGHDGEBGECGFHGFHACHFGHFCFBEFHHBHEADEFGCFE,False +427,9.0,21.0,17.0,17.0,18.0,17.0,9.0,12.0,BHBBHBBAFBCCHEBDECFECDEFFGHCEFCAFAEHDGHDBHABEEBEEDAECBDCECABDAFDHDGEDBBDBFAFFCCBHCDHDBFDGFGBFCHACDBCGGDGGCBFFBFEEFHECEED,False +428,13.0,9.0,6.0,7.0,7.0,9.0,7.0,6.0,HDAAECHEGFFGFGCFHCBGAADAADAAFABFBEEAFFBBCBBEABECGHDGEDGDABDAFHCH,False +429,8.0,15.0,19.0,18.0,20.0,20.0,16.0,22.0,FGDFDDFHDGAFGFHEBABCDBHFGHFCHACACCECEACEBCFGDBHFEHFBHGHHEHEBGEAFFHCFDEFDADDBDGHFBDFBCFBGAHFBECHECBECHECECCEDCHGEEGEGFDFEDBEHBHCDGDHCHHGGDG,False +430,13.0,25.0,20.0,21.0,26.0,17.0,24.0,16.0,EFFGFCDFCEHCGHDGEECAEBBEGBECFEGHAADDAFCAFCBCEECFFCFCAGDACHBHHBGDCGDGGDEEDBHHGCHEDBEGEECEEBEBBDBAEEFDGBGGBDAEDHEFCGBCGFCGAHGFHDBGGBFBFFHEHBCDBADCEDEBBGAAGHBGHBDBDD,False +431,13.0,21.0,18.0,12.0,10.0,10.0,17.0,15.0,GAFBBBBFHGFAFBGCGGBBCABCAGDHGDHBCHBHBAHGGHEGHDCDBCFBCGECAEDDHBAEBDHBDHBDACECGEGGDHADBEFCDBGACEAHBCFBEHAEHAFGCCGCCFFC,False +432,14.0,11.0,9.0,15.0,14.0,12.0,12.0,18.0,DFAFFAHDHEDFEHHEDHCFHCECBABBDGEFGEDCDCGDHHFCHFCGGCEGABGDBEABAAHAEBDEBHEGHFGHDHEBADGADBAEHCEHDDHBFAGAAFFGH,False +433,16.0,16.0,12.0,20.0,13.0,18.0,9.0,14.0,FDCFDADDBDDAHDCBDCDDCDAEHAFAABADBECFAFBCFADAGCAGCDBAFCFFEHFHBFBEHGCGGDFGDABDEECGGDFEFBHCBHBEHBEABEHBAHGAEFBEHHHFEHFDFD,False +434,15.0,21.0,15.0,6.0,12.0,5.0,12.0,17.0,CBBDBGABGCDGCEADBCCADEFCCAHCHCDHCAHCHHABHBBHABEFCGCBGAFAAHEAFGAEGAHGEEGHEGBFBEECHEBBAHHCHDBHBBHBBABBGEG,False +435,0.0,0.0,3.0,2.0,2.0,2.0,2.0,3.0,CHDCEDEHCGHFGF,True +436,22.0,21.0,21.0,13.0,7.0,14.0,20.0,13.0,BHBGDAADEDFGCFGDHGAGGAFDCCACCHEADBCFBCGBFABEHDCHCEGBGDAGAADCAHGHHGHFFDEHAGAGGABCAFAFFACHACGBDGBDCBDHAGCFEBFACHBCABCGFCAFGBEBBCBBCBB,False +437,18.0,12.0,15.0,15.0,9.0,15.0,19.0,9.0,BEAEFBCFAADCBFGDGGHFCADAADGADHCBHDGDBGDBGDCGAHEFHGFAEBAHBADGCDGCGFCHFDEFEHFCAAAFBAHAEGDEGFEDCCBCGBFGBFGACGCCADFG,False +438,9.0,15.0,11.0,10.0,6.0,5.0,12.0,8.0,CBBCECABBAHBHBCHGGEGGDAEBEDCDFADBGDBGDBGBBCDGABHCFGBFGHFGHFEAAEAABHDDCGCCDCH,False +439,21.0,34.0,13.0,20.0,9.0,14.0,18.0,22.0,DBGDFCCFEAGHBHHCHHCBHBGHBDABCCBAFBAGBDCBDBBGBAFFDHEHGCBACBAEFGHBGAFGCFBAGHAHHAGHGCDEAHABHBDFEDBDDADDHFBHFBEABEABADBHFHDBABBHBAEBGCDCFHGGGBBGFDGDABDABDE,False +440,5.0,7.0,4.0,9.0,2.0,7.0,1.0,7.0,DEBHHHHHHDFAAFGADHABBFFDFFDBEDCCCCFBDDBDAB,True +441,9.0,3.0,11.0,9.0,5.0,3.0,13.0,6.0,GCHGCHBCDDAEAHEAGAGGCGEAEHACDFBDBDGCDGDGGHGCFGCAHCACDGCAEFD,True +442,26.0,15.0,9.0,16.0,20.0,21.0,20.0,20.0,EEHEFAFDDHDDBDEEFFEDFCHFAAGHAEHADBAGHAGBADAAEABCGBCBBFGCFGEFGEFGHDEAEEAFHFGHDGFAGACGCHBCHEAHGABGBGADGFFGEEBCFDHAEBAGBADAABBHFHHCEEFFEDFHAHHAHADDGFG,False +443,5.0,11.0,13.0,10.0,14.0,14.0,10.0,14.0,FCEHCEHCEDGDBBDGEDHEABEFGAFGAFCCFHFFHFBAEEGDFFAHECHGCHDCHBGFEHFHFFBBCBBEHCHHBECDEDBEDCGGGDC,False +444,9.0,3.0,12.0,6.0,9.0,11.0,10.0,6.0,GACGCGACGBHABFCEFCEFCAFGFEGDCFBCHHHHGAAAEADCDGAGEEEEECFFCDFGDFCDFH,False +445,9.0,10.0,13.0,13.0,17.0,11.0,15.0,15.0,DGCDBCDFEFHEHHEDDEGCCFCFFCGDEECEFHHFAHFAEDGGBBGHHGCHGBACAAHEEHEEDGGDGGDGEEFEBGHBCDCAACAHDHBFEFCEDBHBBAG,False +446,4.0,1.0,6.0,9.0,11.0,4.0,5.0,7.0,GACEFGGACGDFDECDEHDEHDEHEEDAHDCDFCDBEHAGFCHEEHE,True +447,26.0,19.0,18.0,11.0,16.0,16.0,12.0,21.0,EEHFFHCBABHABHAEHAEHEFFGFAGHBHAEEAEEAGAAGCCGABDACECFHGHHEDHCBHCBHCBAGDABDCHAHEFHFHHDDFBFFAFCACABEDFEDAGDBFCBDAGFACEACAGHABBFBBEBACCCGHCDBAG,False +448,6.0,5.0,7.0,6.0,1.0,1.0,3.0,5.0,HADHAHCACGDGBDGBAECACBABDCHDBHDCCF,True +449,11.0,2.0,6.0,6.0,9.0,16.0,8.0,5.0,AGAAHAAGFDFEEFBEDGEGEEFEAFCCDEDFFGFFGFFCFAEFAFHDFCBHADHFGHACCAG,True +450,11.0,4.0,8.0,12.0,7.0,9.0,7.0,8.0,FDEFCADCGCEBAHBGECHEFHCDACDABHGBFFDFAEFAEADGADFEDHCAHGDHDFCDAGDAGH,False +451,31.0,20.0,20.0,33.0,22.0,23.0,32.0,17.0,BCCAGAAGFAGCEGDBGDACDHDHGFBGBBDBFGBHBAHECEECDEDHHDFADFEDCEGHAFBCCBFADGCBADDFEFGEHGEFGDHECAEAGEDDEBDEADAADBCBGEDHDDFCEAAHBGBGFAGFDGFDEFEGHBAHFAGFDGDDFDFABCABCAFCAFCAGCAHEGHGDAADAGEFGHDGCDGBGHCFAGDEGA,False +452,6.0,6.0,6.0,10.0,8.0,9.0,9.0,6.0,AFEABEBDGBAFEDHGFHGEDGEHCHAGHECHCCFDADDFEDFEBAGCFGFFGCBGDBDD,False +453,13.0,18.0,14.0,23.0,17.0,19.0,19.0,12.0,DCGDCDDCADEBFFBFFCAACDACDCCABCDDFDFAAEGFHFADCBGCDGEDAFGGEHHEFBFFBFFBGFCDFCGAGDDHDDHFEHGEBGHDGHAEHBGBDEFCBDDEABHAGEBEEBHEDEGBHGBFGBGEEGB,False +454,18.0,22.0,18.0,14.0,25.0,31.0,12.0,21.0,FHADBACFDHAHHDGHBFFFCFGCBGDHFFFGFFGFGGFAHCHEEHFHDFHFFHFAHAHEACEGEEBDEDFAFFBFFBFBEFDCBBEAEHDFDEEEBBGCBFCFCBGBBFEHGCDEHDECDECBADEAEEACEACECCABBECBECBFAFAGHEHHABHAB,False +455,8.0,7.0,7.0,9.0,13.0,7.0,12.0,7.0,AGEBFEADAAGFABFHDEAFFCGFDEHGABGCBHCBGBDHBDFDEGCEGCEDCEHEDHGDAGEHEEGCEG,False +456,26.0,25.0,17.0,12.0,23.0,17.0,8.0,10.0,BCAFCEBDBGCAAFAAFGCBEAEDDBADBADCHEFFEADEAEEFEEGAEGEHBEGAFHAFHDFBBAEACCAECBBBBBFABEABDBBDABDCEDFECACHFHAFHGHDCCAGFEEACEABFABFBEFAEBBGHBCHCC,False +457,17.0,13.0,15.0,8.0,13.0,12.0,8.0,11.0,HFCEBGABGABDAECBBCBBEBEEBFEAADACFHFEHFBACAACDAFHHFAHGAHAAEAHGHCGFCDFDAEEBDECCHCCFFGBEGCDFCBCAEDHG,False +458,4.0,0.0,3.0,1.0,6.0,6.0,4.0,0.0,FEEFEFFGCFAEAGCAGEADEFGC,True +459,21.0,25.0,18.0,16.0,17.0,17.0,23.0,17.0,HDAGCGGBBGBCEDCBBBEGFEGFEGFAFFCGFCBECBFFBEBBGBFABCAFAHEHEDHGDCCEAAGAAGBCGHCBHCAEDHHDFFDABEFECCABHABEDBEGBEGDGDFGAFEAGCDGCBHHDHCAHGABFDEADBADBHGAGAHFHGCHDB,False +460,10.0,14.0,5.0,9.0,15.0,9.0,9.0,8.0,EDEEGEAGEGBEDBDFGDEABFAFDAGEBBABDAGDBGFFHAEHDEABGBHABEACEFBDFBCHGCEBCEBEHHHFHCF,False +461,5.0,3.0,5.0,6.0,2.0,12.0,7.0,4.0,CEAFFGFFGFFDFHDFBDADACCGGCABAHGFBFFDGHDGHEFC,True +462,6.0,6.0,14.0,9.0,5.0,9.0,18.0,19.0,FGCDHCHHGHDGADGECGHCGCGHCEDGEFFHHFHFGBAHEFGBCGHFDHFHHCGHCGHEGBCCBDAHDHGBHACGCGFCDABDAG,True +463,3.0,5.0,4.0,8.0,5.0,3.0,5.0,5.0,DGAFBBFAHGEGGEGBECECCAHHDDDEDDHFDHBDCB,False +464,8.0,5.0,4.0,6.0,7.0,4.0,8.0,3.0,DACBACHAGHBEHDEFEADGGCFEDGEBGEAGBAGFDGFDAAEBC,False +465,13.0,13.0,10.0,12.0,11.0,18.0,10.0,10.0,DFBGFDFFDGBBBEDGEDBECEEDFHAAACAAHHHHHBGGAAAFHACDACEFFHFFHAGCBEFBEBAFGAHGDEGFFBFDBFDECCECCGBCDBFDF,False +466,1.0,7.0,5.0,6.0,4.0,4.0,5.0,8.0,DHBECBCDBGDBHDBHFHECAECFFGHDGBBGHCGHDHFE,False +467,8.0,10.0,7.0,7.0,13.0,10.0,14.0,7.0,GGBEGHAGEGBEDBCAFFBHEEAEFBEGCFGCFHBFEGFEBFHFCHFDGDDGHDGDCHAEGCEGAEDCEBAABABG,False +468,7.0,9.0,14.0,4.0,4.0,10.0,8.0,4.0,FECAECBDFBGFCCFECFDCBGCBGBFDAHGAFGBBEBCHBCAAHGAGCCCFHCFGCDAF,True +469,11.0,8.0,10.0,17.0,9.0,15.0,9.0,16.0,FHDFDDEACFHCFCAHDEHAGHACHDGBAGBEGBAGEHHDGHFEHADHAEFAGGCFECFBCDGDHHDADBCDBEDFFDFFCCBEDHFHAFHDFDB,False +470,1.0,3.0,1.0,1.0,2.0,1.0,2.0,3.0,CHADBEEBGHBGHF,True +471,17.0,15.0,26.0,18.0,19.0,21.0,23.0,27.0,GFFCCCHCDHAGAEGFGCBGCBFCFFHDFBDCHDGHFEAFEAEEAEGDHGHCGABGDCGDGGFFFACHBEAEEDEAHFAHDHHGCHFHHGGHBBECGECEEDAHCACCBBCFBCHGCHACFDCEDAHCAHFFFDABEEBCBAHFCHBHBGDGECGEHDHGDHGDFD,False +472,2.0,5.0,3.0,5.0,4.0,6.0,6.0,2.0,EGHFGBFEBFEDFHGCCFEABDADDBDGBGCFG,False +473,20.0,30.0,26.0,33.0,27.0,26.0,18.0,15.0,CGAHFAGFAFDBCDEGDEHBEGBEBFDGFECFHBFHBEEFEECCEFEFFHCDGAHABDFBAGBADBADBDGFGCDCABGAEGDDDDACFACEAFEBEGDCGCEFDEBEEDFEFFDABDHBDEBCHBHHFDDBCDFGDAGHBDABFBDDDFFBBACBCCBCABCACCHGCBFBDDEEBCGDCGDCEDCHFEHEAHE,False +474,19.0,17.0,14.0,18.0,11.0,17.0,20.0,12.0,GAGCCFFCGFEDEBFFAFCGDHGEHGEHGHGFDFAAFDADDADCACCBFBDGBGGBFEBCABDAGHGBDBBHFGEAGCDGFDCFCHFAGCBBABBABAEBCFCDEDHGHAEHAEDAEDGFDGDAHHAB,False +475,29.0,21.0,29.0,16.0,8.0,11.0,32.0,19.0,GGHBGAGFAHFBGAHFBHGBHGCEACHGBAAAFHHFHHCBGCGAHBDCCDGAAGHHDBDCBDFBDBEACAFCEDCBGABGAFEACGACGCCGBCGHAGADEAHGDCGCBBAFBADCGBEGBEGBAGCGGAGABCCHCDACGHDGEAHAADFCCHACDGCDGCDFC,True +476,1.0,0.0,5.0,0.0,0.0,3.0,1.0,0.0,CCCGCCFFAF,True +477,12.0,12.0,12.0,10.0,3.0,21.0,15.0,7.0,FDFAGACBDCBGCEFEFDGAGGBBDBBAFCADCADCFCGFCFFHFFHBFCCDAGAAGBFDCFCAFHDBBGHDGHFGBFBEFGFFAHGAGGFH,False +478,17.0,16.0,18.0,22.0,16.0,25.0,17.0,21.0,ACEFGEHAECACCHBGAFFBCFECADCEFAEDEFAECBCGBCHFGHGEBAEAADHGDGAFGDDCEHCHAEHDEFGHHHBHABFABFHCFHCFHCFBDFBHBEFFEDFCDBGDAFDGBHFBHAEDCFHBDDGADGDFCDFGDGBDGDFHDFHG,False +479,10.0,7.0,13.0,9.0,7.0,6.0,9.0,3.0,HGCDGCAGAEGAGCCBCCFCEFEAFEACGGCHDABDECHFABFEBEBADBDDBAACGCFDCDDG,False +480,1.0,0.0,4.0,0.0,2.0,0.0,5.0,0.0,GCEGEGGCCGCA,True +481,21.0,16.0,14.0,17.0,11.0,10.0,25.0,16.0,FDGEEGBBDHAHGDHBHGBGCBCCFACEAEGAHHDHBGFDGADAAEAAFHCFHDFABGCBGAGGADCHDCECEDBDACDAHDAGDBHHBAGFAEFGBFGBGHAGAAEDCBCEBHEGHDDBGGGGCAGCFG,False +482,12.0,17.0,21.0,17.0,21.0,22.0,20.0,24.0,HCBHEEHCEHCBHADGBCGBEEHHFGHFDHFCHCGHGGHBGCBCHGDDACDFFFFFGBACFECGCFHFAEDHDDBDDHDEGDECAGCAGHAEHAHFEFDEACCDGGGFGCEBCEDHFCHBHBEHDDABHFFFAFFBFEBEBBGAEGCEGCEBFE,False +483,19.0,21.0,17.0,13.0,22.0,21.0,20.0,24.0,GDGGEGFHAHAEHADHCEHDAACCBEFBEAAFFAFGHHBHDBFDFFACBGDDGDHHBACBFDHFDBFEFFGABDACDFFHGFCCAEBBHGBHBBEBGCDGCHGCHEFHEAHEHHGACCACGAHHEBGECGACFEEEBEFBCFEEGEHGEAGBFHBEB,False +484,14.0,17.0,19.0,19.0,23.0,9.0,30.0,14.0,DBADEECEEGGGCGGCHGAEDCGDCDDHDGGDEBHBBCAHHADGGGEGCECCACHAGHAEDABCHGGHAGDADBEFHHFBCEAGAGGDGGHGGACFFBFGCFGBBDBECBEDBGFEHDEBDEFHEBCEBAEGEECEGBGFCDECD,False +485,23.0,20.0,17.0,18.0,15.0,7.0,16.0,20.0,ADAADBBFAFFAFAAGCDHCHABGABCAGHBGHCAHEECBECGDHHAHDEFBGDGDBGDBAAEABGHBDCECCBGGHCEHBFABFABCACAECBCDDCBEEADEADHHDHDDGEHGEHGEDCBDCHAAGGBHHBHE,False +486,19.0,15.0,16.0,14.0,11.0,13.0,25.0,19.0,GDCGHFGHCBDBAAAAAACAGHBGADDCCHEGBCBDAFDBGDBDEAAGAHBAHADCDDEHHFHEAGCGGCGGBGHCGCBGCBDCGGGFEGBEDFHCFEBFEAFGAEGCFGCFGDEGAHFEHABFFBHHHHHH,False +487,17.0,28.0,19.0,19.0,12.0,13.0,19.0,22.0,DBDEFAHAGFBGHEGHDDBBEBHEBHDCHFEHGEHGBBACBAGAAGEBBHBDFBDFBDCCHCCAEBGDGDCEBCACFAEGAHDFCCBHCEHDEGCBGABGBDFHCFDDFDBFGAGGFHBCHCABDABHAHCAGCHGBBBCBHFDHADHG,False +488,11.0,5.0,10.0,9.0,17.0,10.0,8.0,12.0,HFEBAGAEFADDEHDEHAEHDEHAEDEEDGBCHCFECFBCHGCHGEDBEABGAHFAHFHEEGFHACECCADEDCEFCAFGFG,False +489,15.0,27.0,19.0,19.0,24.0,16.0,18.0,23.0,GDHCDCEEBEBBHABHFBGFEGDDHDFACCAGGADEBDEHABHAFHGBHAFCAFCBFCFHCHDEHDBBFABDEGCECHDDDDGEAGHAFHFEBBEAHCAHFGHABEFEHDHHDCGBEHBEBCCBGDGEBGEBEECEGBECBEBDEBFGHABHFFDGCCGBC,False +490,3.0,2.0,6.0,3.0,7.0,0.0,1.0,4.0,CBCEHEADEACEADEDBCGHHECHEC,True +491,14.0,16.0,16.0,14.0,17.0,13.0,22.0,10.0,FADFCGFCEFCEBCGBCBBCBBAFBGGBGBEEEFDBBDHEEHGHAGHAGDDGBEAAGDFCHADHGDHGHFBDEDDEFECCEGGGGGADGCBEEHDCGCCGABHDBFAFEEECCAGAFGAFCA,False +492,26.0,18.0,20.0,24.0,26.0,19.0,29.0,28.0,DCADFADCEHGDGGFGEAHEHHAHFCCCGHBAHEAECBBGGBHGBHDBAAFECHEBHGFHCAHDAHDAHACHCGHCAAEGGGDBGDGGDEGHHDCGEEGEDAEDCGFCDFEFFADHGBCABHDBEGBGBHCHFGDFEFFEBBEDBEAAEFEBFGBAHAAHECDGDDFDACCAFAEHGEDGEDCEHFGHFA,False +493,1.0,0.0,2.0,1.0,4.0,2.0,0.0,0.0,ECEECEAFFD,True +494,11.0,16.0,14.0,24.0,25.0,15.0,20.0,16.0,HFCEDHDDCEGCFADBEDCEDAFBACGFFGHDDDGBDFEAFCAFHDFHEFBAFBDEBEHCEDBHDGHDFAEFCECCBGGBFDBCDHAHBGEBEEHGGHABDGDGGDHADGAEEBFECEECGEGGEBEEBHGCHGDHGDEDE,False +495,15.0,21.0,13.0,15.0,18.0,25.0,20.0,12.0,GFGGDGBFFFDCCDGCDECAEFFFHCECCEDEEAEEBEFHDHBGGBGGEGHAGEAGBGEAFAHFACFCHGBBGBBCCDEGDFFFFABBBEBDAGDAHFACFAFDABDBBEFDEFAFBBFBBFEHHGHDDHBFGAFHEGC,False +496,14.0,17.0,8.0,12.0,24.0,10.0,23.0,11.0,GBFGBDGAFGBGEBFEHDGAFEBCGGGBABDAEDGEFBAFHEFHBFHEEBGEBAEGGEFGEABAHBGHBCFGEGCAGCEHEGHDDEBAGCAGBECDECDEGDEGDBDHEEHAEHDCAAE,False +497,8.0,11.0,13.0,8.0,7.0,15.0,9.0,16.0,EHBHFAFCAGEGGCCGCAGBAGHDFFCFHBHHDDHFCAECHDBHCBHAFFDFEHCGDFGAFCAFCGFEBBCBBCFHDHEDHFBHEBH,False +498,3.0,6.0,8.0,3.0,3.0,7.0,4.0,5.0,CHECBEABACCGCBGFHFFBGDBFDAFDEFCGBCHFHHC,False +499,7.0,4.0,9.0,5.0,5.0,8.0,3.0,3.0,ECEEFHFFACFAHAABEABDCCGFDGFCCFCCFGDABDCDEBAH,False +500,7.0,8.0,5.0,8.0,4.0,3.0,2.0,4.0,CAEFHGBDDBDDBDDBCGBCFDFDHCAEAEHBEABAAHACB,True +501,22.0,26.0,22.0,26.0,16.0,25.0,21.0,27.0,EBHCGHBFHBFBAEEAHFAHEADFGDFBFHCHCCHGAAAAAHAGBBBDBCHCEHBHHGDDFBEFDECDBFFHFFDDDDDFDAACHBDABDHGCEGCGHFGAFDCFGCFGBBGFACDAGHFGHEEAEEAHHBDDAABBCBCDDCDCGHFGHEBHABGFCGCEGCBCHBCHDGFFBFGEFDEHDBAD,False +502,10.0,11.0,12.0,13.0,8.0,15.0,13.0,13.0,GFHHEHDCHDEFDADGCDGBDFADFHFACFACACBFCGFCAFEECBECBACAFDEHBGGAAFDGHCBDCBHGBHDFHDHGEFGFHGFHDBEBGGB,False +503,5.0,6.0,10.0,4.0,4.0,8.0,9.0,0.0,FEDCEDCGBGGBCFCFEDBEGAACABCGCCGFFGFFDAGGBCABCF,True +504,7.0,14.0,10.0,11.0,12.0,9.0,6.0,15.0,BDBBGBFCEDCHDCHEFFECHGDEEHEDHDBCDHGABFABFBBDBBCEECHEGFAHCGFBHFAHFAHDCEAHBDCBDHGEHAEH,False +505,21.0,9.0,16.0,11.0,15.0,16.0,15.0,15.0,DFAGEAGEAFCCECCECFEGFHGDHAFBCHEDHEHBEAGFCHDHGAHFFCAAGAAGAAGAFEDGCDFHGEHFEDFBDCAHGAHBABEABGABEDFFHGFCEACHADEBCCBGFDCCHA,False +506,17.0,15.0,12.0,11.0,15.0,5.0,18.0,14.0,BHGDHFBGBBABHAEGAEDAEAEDBEDGCGHADCFEHAGHAHHAFADCBBGEGGBDBBDEHHHGGBGADGACHCEGCEHAABFAEHAECAECEECFBCGDCGBCGDG,False +507,23.0,16.0,18.0,17.0,15.0,30.0,19.0,16.0,CAHCHFAHFDGFDGEHAABDAFCAFBAGBHGHCDBAAFGFFGADAHDGDGGFEDFEDCCCCDHGFFGFFCHFAFEAFEFHGBEFEEFEECDBGGHHGHCEHEGCADCEBAFBFDBGBCHBFFBFFBCDBDGAGFABEAEAAFFCBFCADCADHA,False +508,2.0,2.0,6.0,5.0,8.0,2.0,3.0,4.0,AECAHCEDEEGEDCFFCBECDDGGDHECHEBH,True +509,10.0,15.0,13.0,10.0,20.0,25.0,8.0,14.0,BFFFFGHDGHBEECGECGEHFEFAGBHGBEDEGAEAHHFFHCFCFFHEFADFBCEHCEGFAHFHEFECBDCBDABDCBFCBDHBEFCEFCHFEBEBFEAFACFHFBAFEADDDBE,False +510,9.0,6.0,15.0,8.0,8.0,15.0,8.0,4.0,CGFCHFDFCDFADGADECCCFCAFBFFCCFEGFDGFCGCCEBBEAEEAEFGHDGDFCHFEFAGDABBCBCAHA,False +511,1.0,1.0,2.0,5.0,3.0,1.0,4.0,3.0,GDDGCBGCHDEEDHEDFAGH,True +512,16.0,13.0,8.0,20.0,20.0,20.0,19.0,18.0,GEEGAEDHBDFBGBGGHGEEDHEHEGFEGBEGFHGEDBBAHGFDAFDAEDGFFHFFHEEHDEHDGDGADCADFADABFHDFCEFCHFDGAGABHAFHGHCBFCHEHBEAAEAAEBCEDFGABDCHFCBFDFDDG,False +513,2.0,0.0,0.0,0.0,3.0,1.0,1.0,4.0,HHEHHEAGAFE,True +514,16.0,32.0,27.0,32.0,20.0,18.0,31.0,18.0,FFCEHGEAGHCGDDGHDFEDFDDBDCHDAABHAGDEGDEGEFCBDAEABBAGBCGHEEDCCBCCAECAGBDFBCHGHHDHADGGGCCFFAGBGFDGACBHCBDAEDBEDAGDHCDGCEGFGCEGDADDCHBGHBAHBEGBEFBFGBHDHGEBBDBBFCCCDEBDFBDBBGFBGFBGFBGFHDBCCCEBCGDCED,False +515,26.0,15.0,26.0,29.0,17.0,18.0,23.0,22.0,GFHDAEAAEGAEGCEDCDDCAHCABBAEBECGEBHHGAADFECFBCFECEDGDDCDCGDBDFGCGHDAHFADDAHCADDGDFGDEAAGAFDHGCHDCBDCGCBGCBFABGAHHBHDFHDFDDGDCFFAHBEHECCFCBACHACEGCEHHBHFGHCGDAGDAGECBFHAAGFFDEAH,False +516,12.0,12.0,20.0,17.0,22.0,17.0,13.0,11.0,EEBEADDAFDADAHHEEBGEBFFBEBCCDFCEFCEFCEFCABEFHEFCEFGFCGCGHCHDCGFBECACAGDAHDGGDHFDHADEADBFHBFABDHECFDCHCEGGDCDDCGBEAFEBECGECGE,False +517,17.0,18.0,11.0,13.0,13.0,9.0,14.0,20.0,BEFHACHEDBAAHAHHAGBAGCGGHAADEHDEHBBHGEHAEHGEDGEBCEBCHAAHBCHADHCDBGFBGHAABBFFFCCFACBGDBGDBFDCFDCBEHFHHEGBADEDHEGGABD,False +518,20.0,13.0,17.0,15.0,17.0,19.0,27.0,13.0,CFECBCGACDECDHCHAGGAGGAGGAGEAGHBGFFGHHDEHDHDDGAAGDDGDHBEFDAGBABEECEAABAAFAGFGDFCDCEFGECBCGGEGHEGHBGEFHFFDCCAFGAFEAEEFCFACFGBDCBCAHGBEGFDFHBFB,False +519,4.0,10.0,8.0,8.0,7.0,6.0,3.0,5.0,EABADFAHCBFGDFCDCCBACBEFDGBHGBHFEHFECEDHBCCBEDBEDBD,False +520,21.0,21.0,12.0,9.0,4.0,4.0,12.0,8.0,FAACBBBAABGAFADBABBDBBABHACGACBABBHHCECAACAHGDHGABCBDABAGBDGDAEDGCDGCABFEHEAHFBHGADGCCGBCGB,True +521,7.0,6.0,5.0,6.0,9.0,6.0,4.0,9.0,HDFFDAFDAFBFEAGABCHCHHBFHBGEBHEHHEHEDAECEEGACDECDBGA,False +522,7.0,13.0,6.0,12.0,9.0,15.0,17.0,9.0,FEHCDBCDGGDGGDHFBHAEFDEFDFGEAABAFBHCBEFBACDGBDGHHBFGDFEDEEGGBGGBHGFGFEGHCFBFFBGFGHBADCAD,False +523,13.0,18.0,26.0,23.0,24.0,18.0,20.0,22.0,HDCHAFHBBHAEFFCCGDFGAFCFDBHGFGEFBEGCEHDHHEGCEGEDBDDBGAFHCFHCAECHBFHADHFDHECFBCBBEEDGBCGEEEDGHFGECCECDACDGFBCACCDDGDDEBDGBDGAACABCABCFBEFEDHEDHDGHEFHECDECGAHGEHGCCBH,False +524,23.0,26.0,27.0,25.0,18.0,14.0,25.0,20.0,AHEABADDECBHGBEGDCHHCEDCECAFCACEFEEGGDGGDGEDGCFBAEAHFGDFCACHEBDDBADBADBDDACFAFAGCBBHBGGFDBFDGAAGAHGDHFBEEDCCDCBACHHCHECFDDHABAACAAGHHGBGGBGFBGFHDCBDCBHBHHCDFCDEBGHBGACGCCGECBBBEE,False +525,9.0,5.0,7.0,9.0,10.0,14.0,16.0,12.0,GDEGFEHFGFFECEBCBHHAHAGHAGDFCDHBDAFFFGFGGHBDHFDCFDCDGFEGEGCEGAGAAHAGEGHEHFEHFGCDBA,False +526,21.0,20.0,28.0,24.0,24.0,22.0,22.0,28.0,FBFFHFFDFEBCDDDFBEABCGECGECFHFFCFDAACAAHAHCDHGHHFHCBHBDHGDGDHAHCDHGABAABGCGAAFBGFCDFCDFCABEHDEAGHABHEBAEFHCAEABHGHHACFEGEEFEEGDFGDCCDCEDHHGBHGEHGECGDHDDAFCEBDHBGGECBDCBGCAGCEBCECEBCEHCDHEDF,False +527,20.0,11.0,8.0,13.0,17.0,8.0,13.0,14.0,DDHGDHCDHDDHEGFEDECAEHFFHAABEGBEHBCAGADGACFACECDEAHGABBCEAAEAGFABAABAHGFHEEGGDCEBAFGFHGAEDHEDHEABEABDHBG,False +528,9.0,13.0,8.0,10.0,8.0,6.0,9.0,7.0,ECDBCHEGHFFBEDBGDBHDBHDFHFEBBCDFDACACCBEHBAGBAGFDGADGACHABDAEABGGEGCEB,False +529,2.0,5.0,6.0,3.0,4.0,6.0,5.0,4.0,FCBFCBFCDCHDEHBFGFFGAEAHEGBCGCHDEBG,False +530,5.0,3.0,3.0,2.0,4.0,2.0,5.0,5.0,AFBAEGACGFGHCEHEBGEHGHDAHDACB,False +531,14.0,18.0,15.0,23.0,16.0,17.0,15.0,32.0,HBAHEDHGDHCDHDEHDEHDEHDHFAGADFEEHBBDFHDAEDEEHHHBHDFHDFHCFCFECABGGBEGCEBFBBDBDCCHCAACFACFHEEHCHHDHGFHGFHDCDDBEBGHAFFCGBAEBAHBGHAGFBGAHCFFBDGDCBDHGHGDHA,False +532,8.0,6.0,17.0,12.0,9.0,14.0,14.0,11.0,DEGAFHFDCCDGCHHBHCFDCFDCEGGFHHCAGEGBFGBDGDAGHCGCCGDCHDGEDBEFFCFDCGHCEHEGHACCAFAFFDFFAEBAEBC,False +533,15.0,11.0,12.0,12.0,16.0,22.0,21.0,18.0,GAAFFACGGFHDCBDFBAFBAGEAFEBFGGFDDEGFEACHFFBDFGEGDFFAHFHHAHHEHHFHFABECBDHHDCHDGGDGGEFGEHACGACGECEECEEBDBHDHHFHEFGGCABCAFEFCGGGBA,False +534,6.0,6.0,12.0,13.0,5.0,12.0,12.0,8.0,HDGAGHFGHFCHABHFEHFACCCBCEGCGDCDEADCFDHGDGFDGFBGCDCHFFEGFAFDDFDDGADCBECBGB,False +535,22.0,16.0,25.0,15.0,17.0,33.0,16.0,16.0,FBFFEECEEDFEFEEBGGDGFEAAEFCGFDGHDGDEGAAAHACFECDACDCHFCHFAFFAFEGFBDFECHHBACBCCACDAGFGDFEDFCCFHCBCCFACAAGADGHEFFCBFHDFCDHBHGECAFFGBGBFGAAAFBHFHHFEBFCDFCBACBHCBHAB,False +536,20.0,17.0,26.0,15.0,22.0,17.0,17.0,16.0,BHHBAFEEFAEFAEDBBDFEEBCEHHAAHAGBDGBHBECECCBFFAFEACEGCEFEECDDDGBDABEEBEHAAHCFCCEACDAHAGHBGFACFHCGHCFCCBCFGHDHCDHCDGCEAHGAFBADGGFCBFCGDCGCCFADECDGGEGAEB,False +537,13.0,10.0,5.0,5.0,10.0,8.0,9.0,7.0,EADEDEAAGAEEBGGHHBFFBFEBFBBDEAHEABCAHCAEFAGDAEDBFFGFAGAHGCHGHABCGBC,False +538,10.0,10.0,16.0,12.0,12.0,14.0,12.0,13.0,DFCGBCDFCDGBDCFCFFCFDAHDCBECEEBEDBEHECFECGAHGDHEAHAHHGFHGDHFFCGGCEGFGGCGCAAHHAEHCBDFBDEBAFADFAEBCBH,False +539,2.0,2.0,4.0,2.0,0.0,2.0,1.0,0.0,ACCFCAFCBDDBG,True +540,3.0,8.0,6.0,4.0,2.0,10.0,5.0,6.0,FGBFBFDBFDBFHFFGCEAFHCCBFCBECFABGDGHDGHBHHAC,True +541,4.0,4.0,3.0,5.0,9.0,9.0,6.0,7.0,HHFDFBDFAFFAEFEHGEHGEBGEAHFDEBCGHGGFEAFDDHCEBCE,False +542,1.0,6.0,4.0,1.0,3.0,1.0,2.0,0.0,EGEEDACCFCCBBBBBGB,True +543,11.0,8.0,11.0,8.0,8.0,12.0,13.0,10.0,CGFCHFHAFHGCGCCHCGHGACBDDBCDFADFADFBBEDAEGACFAHHGBHGDAEFGEAGEABHBGFBAEEGEHDFCGFCF,False +544,1.0,2.0,1.0,1.0,0.0,0.0,2.0,3.0,GDAHBCHBGH,True +545,20.0,18.0,24.0,26.0,24.0,22.0,18.0,33.0,CBHDDADAHFAEFCEHCEHEBHCBGCHAAHAFHFFEAFDAFBEEGHAGDDDACDHCEECEGDEGDEGBADBEDBAACEECHFBFCHFHHEEDBHHAEFCCHHFDBFDHCHHAHHAHGCHCCGFCGBGGFGDFBHFDGGDCEDADDADCFBCHBCBFHEHBEGAFHCCBEFFHDHGAEGDBGDEHD,False +546,29.0,23.0,21.0,19.0,21.0,27.0,25.0,20.0,BHEADFCDFGBFAFFACEAGFABFACFACFHEBHBFHDFGEGCEHCGDCDFCACAGDEBDEFAEFGEGGHCEHEAFEGECAAGAAEFFFFDFGGGCDGBGEBGHBGEBADFGCAGEADDBDDBACCCBDBBHAAABAHBACGECDDHGHHGBFEACHBFHEDCFDAHEAGCBGBAHFAHFBHFBH,False +547,8.0,14.0,13.0,15.0,21.0,12.0,10.0,20.0,CHCHGGHDDADDEGDBGFHCBECDEFBGHEECEGCFAEHHEHHCHHCHFFAAEDAHDEGBEHAAGBEHDEDBCFFEFCEFCHHEHBEHBEHEDDEGDGABCEBDBBCBFFBDF,False +548,5.0,4.0,1.0,2.0,4.0,2.0,2.0,2.0,ACBADGEEGEEBAFBFHDAHBA,True +549,14.0,13.0,9.0,11.0,17.0,24.0,19.0,14.0,EHAEHGEDBEDCEGGEHFBFBBGBGGFHAFHBFEACBACEADGFEACGFEGFADHGDAGCBGHGCFEBAHBGHAHADDAFDHGGHGFFGFFCFFEAFEGEEFFHFDBBDCBEHFFDFAEFC,False +550,8.0,20.0,16.0,21.0,30.0,20.0,19.0,15.0,FHEAEECEEGBBBBBHBBDDCDDCDBCBFFEGFBCEHEEHEEBEEHFDCEECGBBGAGAHCAFCAFGDEGCEFEHCDBEDHGCGFFGEEGEECBEFEHFHCDHBDFDDGGDHEFHGDECDEHEGACFAFFGFBGBGAFGDDDDDBEFBH,False +551,8.0,3.0,13.0,5.0,6.0,13.0,5.0,7.0,BDFEDFGCFCHFCGCAFFAFFHFGCAGHAEHCBCCEHCHDCADCFFAEFCCDHGEFAEBA,True +552,10.0,10.0,17.0,16.0,16.0,11.0,4.0,13.0,CABEDBDDCCDFHBACBAEEDFGACHECHECEDHDDBDDHAHCBHEFHEFHEDDGACAECHEFBEFDEDDHCBHCHFGBFEBDCFACEGCAACFCEF,False +553,29.0,25.0,19.0,15.0,29.0,33.0,22.0,26.0,EABECBEDDEFBHACGBHHEHFFAFFEDBAGFCHDGEDEHDGDDCADHAFFABHCFEEBAECAECHHHACCAEABEABCCECFECEGCHGCFFBFFBEFDGGAGAECHEHHDHHABDEHAEFFEAFAFFAGFHGEAGFFGFAACAEFFEGBAABFGBEGDFHDFHEFBBHDHHGHBCABABBFBBGBGGEAGBFGCFH,False +554,19.0,13.0,14.0,11.0,11.0,13.0,12.0,8.0,ABGABGBBFEBEDGCDFCEAGEAGHAGFAGHACHCDHADCADFGDCDDAFEGFEDHHAGCGCFDEHBEFCFFCFEABGABFCHEBABBACADEAFBABACC,False +555,4.0,7.0,2.0,2.0,5.0,4.0,2.0,1.0,ABBABDFBHFBEFEGBAGEAEEFDCCB,True +556,33.0,24.0,13.0,22.0,28.0,22.0,18.0,30.0,EEFABBCDBADEGEHHHCAHGEHABDDBDAGAABDGBABBAGBEBHEFDEDCHDAEDBFHEAHFAHFABFCBEHBEHAEHCHHFEHBEHFEFFHAFHAGHEGDDHBCEDGAFGECHHDHFAEFAECAGAGCEGADDAEBABAAHHAHGAHFEEECAACGFCDFDDFAFEBBGHBGBAFBEHDFGDCGDFA,False +557,21.0,20.0,17.0,15.0,9.0,13.0,11.0,17.0,FFFCCBHDBHDBDDBDDHDCGFBAHBHCCDAADHAHHADGADCCHBCFECEACECCFDABDCEHEHHEBHDFFABAABAGBEGAHGACGCGGFBBHBAFBABAGHAFHFGCGDEFBBCABAAE,False +558,17.0,17.0,12.0,11.0,13.0,15.0,10.0,21.0,AACABFAEFAEGCEBAFBFHBDHEAHEBEEHDHHBHCBFGAFGFCACBFBDFADFCDBHHBHDACECHHDABGBBGFGHDACEBCEBCAFHDEBDCAAHHFHHFGHEGAEGHFGHD,False +559,14.0,31.0,29.0,20.0,24.0,28.0,19.0,25.0,CBHCBFCBGABHAFHAGDBEEHABFAEDGEDECFFCBFDFFDEAEHDDCECEHCBACBDFBCEECGGCGFCFHEABDABDGBDAHFHHGADGEFHDGHEFHEBBEBGCBFBBDCEGFFAHGBHAFFGFFHEFHCCHBBHFEHGBDDHCBCFBCFBCADCDBCGCCBBCBECGDCHDFHBGHFGFCEEHEE,False +560,11.0,11.0,9.0,9.0,7.0,8.0,12.0,11.0,FDCFDGECEACDHCFAFGAFAFECFCHECHABHGBHBBHBGEGGAGGAFDBHDCHDBEDGABEAGACHBHDBDABGHG,False +561,17.0,20.0,22.0,24.0,12.0,25.0,33.0,19.0,GFGGFCGFGDHGBCGHGHHGHCGHDGCGCDDCHGCFGFAHCHFDFCDEBDEBGFCEFCFFGAFCCGCHACBFDFGEEBBDDBECAFGAFGADGADGDDGADGFDEBDBBDBGCAGHGGDGGBBDFHCCDCEFABHHBHEEHBDHAFAGEAGDABFAHHAFBFGDCEBCBFFA,False +562,11.0,10.0,11.0,8.0,5.0,15.0,7.0,5.0,GBAGDDBFDHFDGFAACAACBBGFGEBGFFCFFCEFBEFBCBACFFCAHCAHEEDBAHFCFFCDDAGCAHDB,False +563,20.0,11.0,17.0,13.0,14.0,9.0,14.0,23.0,BAGDHGEHCAGCGEFAEFBCCHCCBDADHBDHADHCGHAGAFEAHHAHHACGCEACAHCDHBDGGDFEBFHHDHHCAHGAHFEEDGFDECDHHEHACFGHFECEGBBCAACAABDABEGBE,False +564,25.0,13.0,20.0,11.0,13.0,16.0,8.0,5.0,AAAAFFCFFBBFABDAGEAGAHGACCFEFGEGAEAACACEFCFFCDCHFBBCBCCADFBHFDCCBGABGCBABBDFACAAFGACACDEEDECDBDAEDAHDAECAECEEHF,False +565,28.0,15.0,20.0,25.0,16.0,15.0,18.0,16.0,AADAACACCACGGBEGAEGBEGFHCHCCEBCEBDBBDBCDAEDEBDABDFFHHEAADAHHGHGBDGCAGFADAADADFHEFHFGDEBDFCAFEHFBBFDHCDADDACDHFHAGCGDAGCABADCADEAGEGCHDDBDCAGFHGHCGAEFFECE,False +566,7.0,8.0,2.0,9.0,6.0,8.0,0.0,5.0,HEFHDFDDHDBEDBEFBDBBECBAFBFDAFHAFEDDBCEAAAFHA,True +567,12.0,8.0,8.0,9.0,5.0,12.0,6.0,5.0,DADDAGBGGBCHFGFDAFCACAEFADFGBFABCDDFEDFECHECDBAEAHCAHBACBFFAFFBGH,False +568,27.0,25.0,25.0,24.0,19.0,25.0,34.0,18.0,GGBDADGGGAGEFFECFEBGEADDADDAFHBBHBCFBCGGEGEDHDHBDFBACBGCFACBCGBEGHHGCAGHGBAFAHHBFHAFECHCABFGHCDHEFEFCEDCEGBGGDAGFFGFFGAFBEFEAFEGFDBFCAGCAGCABAHHHCEACBGEBDEAACCFGGFGDBGDCCDBEGBCDFADBAGBADDADHCDHCDGA,False +569,17.0,19.0,19.0,27.0,20.0,24.0,19.0,16.0,DCECCEHDBFDEDGEAGFGFBCHBCAGAHGFDAFDBHAGEADCHDCDGCBHCEFCHFCGFAADABFABFEECGFHHDHBDEBDBCFEEFEEAECGDBFCBDHBDEBDAFDAHCGDEBDEHDFADFDDFGAFEFCAFHDBEBBDGGACDBCHGFFGFGGEGH,False +570,14.0,23.0,26.0,22.0,21.0,32.0,13.0,35.0,DEACHFHFDHEHFCHFCEFBFHBECFECHDGEDFFDEFHFBCCACCHGDFCHFEHCAHCHHCEHEEHCHHCAHDDGFBHCBEAGGDBGFBEHBHFBADBFDAFGGGABHAGHABDFBFHCFDCFDHEHCEAAEGCBGDFCFFEFDBFBBFBCHBHDBEDHDDBAFFCFHAEHCEHCBHDBCDEGFH,False +571,12.0,18.0,32.0,29.0,10.0,22.0,15.0,20.0,DAHAAEGCCHHEBCEBHDDGDDFFCCCCCHCFHDDHDHADBEFBECBCDBCDFEDGHDHCECGACDAEGGDGDBFHCFDGDDGAEFDCFDAADAADHBCBBCGEDBBHCFHCABFDHFBFCBCCBCCHCFFDGCGGCHCBFDFFDFFCFHHBHGFCGD,False +572,19.0,12.0,16.0,19.0,24.0,11.0,17.0,21.0,AEAGEAEEBDEGDECBBDAHDAFECHEFHGFGGDEHDECGGCAEHEHHCBHDDHDEGCEGAHGFEGEEGEECFADFEDEGCCABAGBAHAHHAEHACACHAFHBCBBAEAFBHDDADDGDBFHGCHFCHCCGFDHDDBE,False +573,5.0,2.0,3.0,2.0,1.0,4.0,3.0,2.0,ACEFDDFABGAGGACFAHFCHB,True +574,17.0,18.0,22.0,17.0,4.0,9.0,12.0,14.0,CCBCGGAHDAEDBCFCCHCFACFAEDAHDAHGBGDFDDCACAAFBBDDBDBBFCBECADDACBFCBHCHHABCAHGBBGBADDACHAGHDGHDHBEHBGBGGCFDAGCCCFHC,False +575,13.0,19.0,23.0,32.0,16.0,20.0,25.0,19.0,GGDDGDDCHDBGDFDDHBBHGBHBFHCEAFEHFGFEGEGGDGDFCHFAEFBCFGHDGDEGDBHDAAGHDDADEBCEGCEFCEFEDBACHAHFDEFCGFGHBBBABDCBFCHDCFFCHDDGDDGECGEDAAHAADDAFDCGCHBCGBCEHDEGFFHBDCBDBGCCGCC,False +576,9.0,9.0,12.0,4.0,5.0,6.0,12.0,11.0,BHFCHFGHEGHBGEFHADCDCGGCFGCBDABAEBACGHEGFBGBAHCDHCGHAGEAHHCCFCBGABCA,False +577,6.0,7.0,11.0,9.0,9.0,12.0,13.0,8.0,EDDGBABEGCGACGECECCBCCHGEFDEFGGFGBCGDAGHGCHBFGBFDEFCFFAGFDHBDADFADFHHFHEEHC,False +578,0.0,1.0,2.0,1.0,0.0,2.0,4.0,0.0,GCGDCGFFGB,True +579,5.0,1.0,1.0,3.0,1.0,1.0,1.0,4.0,HGAHAACAAEHDFDDHB,True +580,23.0,6.0,7.0,14.0,17.0,10.0,20.0,6.0,EEAEEHDHGCBEABGFBGEACAADADGADHCGFGGEHGAGGDEAFEAGEDEAAAAAAEGCFGDFGDEGAEAFBAHBAGDFGDFECCECGDBAAGDEGHAFDDF,True +581,26.0,18.0,18.0,18.0,15.0,22.0,19.0,23.0,FFFAFECGECGHCGACGACAFFGHGEHADHFDHBDHCACGABGAFHHGAFGABDABAFBHEBAEAHFAGCAGCGFAEDGHFGAEBAEHDDHBDFAFBHDBFCHEHHGFDDBAEHAECAHGHECDFDDHHBFHBFCBADFFDCCDBCABGEBCEBDEGAC,False +582,21.0,17.0,16.0,25.0,18.0,9.0,13.0,8.0,GAHDCGBCBACDDBDGADCEDBFDAFDADEAEEBEHADFAHEGDBGFHGHCBAAHDEHEEACDACDECFEAHAGGAEGAEFADBGEBGCDDCFDABDCCAGBADBDFFDGDECDBCDCCEEBBEBBA,False +583,3.0,13.0,7.0,7.0,6.0,7.0,7.0,14.0,CGGBGGBGFBHBBHCAEBHEBHFFFDFADCDBFEBGCBCHHHDHHDBHEGDECBAHFDHBEHCH,False +584,19.0,16.0,23.0,16.0,22.0,21.0,12.0,29.0,CGHFFHFFHCFGDFDEECFDCDDABFAEAADFBEAECAEGAECHHCHAEHFECCHGCHGEGGEDHBABFAHEEBGEHHHBHHCDBCDBADCACABCBCCBHBGHDFHBFHCABGDCFCCADHAHHEHHEHFEABEGGAFDFEEFEAFCDDEHFBHCHF,False +585,5.0,14.0,11.0,11.0,4.0,5.0,12.0,10.0,DGDBCBFGBDAEHACCEHCDCCBHFBHFBHCAHGGGCGGBGCBEDBGBAGHFCHDCGDBHABEFBDDBDDHG,False +586,11.0,24.0,18.0,11.0,8.0,6.0,17.0,13.0,GBBGABCCDDEGDFGAHEAHCAEGBEGAEABEAHHCHBBHCBHCBGGGGGGBHCBCCBDDDCGGBEFFADFGBCABGBBDCBDBHABHBBHFBDFCHCBGDHACCCEC,False +587,14.0,18.0,17.0,13.0,15.0,17.0,25.0,21.0,ECCAFEAGBAGCGFCGHADHEBGCGGCBDCGABDHBEGBCGHHGFHGHHGHDGCACAEHBBBABGFHGFDGFDBDGBAHHGGBCEFCFHHFEHFEFFAFFAGFCHCHGABCHEFHCFEBDEBDACGAEGEEHBBDEDDGD,False +588,13.0,15.0,14.0,18.0,15.0,14.0,13.0,9.0,EFAHGBHGDHGDCADGDDEEEECFACDGDGHCCFCEDCBHFBGDBCDBCGFCGBCEDDEAFEAECAFCDFDDBHABHFEEBBHBACBADBGDEABFGFFADGAGFAEFEBH,False +589,12.0,8.0,10.0,3.0,6.0,15.0,8.0,10.0,FDAFCFFHFGHFGBFHAHAADACFCCBBCBBHADHACFAHBBCGGEBECHGAHEAEEAFFFCFFHGFCGAEG,False +590,17.0,15.0,7.0,14.0,11.0,14.0,9.0,6.0,HEAFCADCHBHAFEFFEDAAFBABCGDDFAAGDGDCBEBFEBDEBAEAEBAEBAFBGFBHFCGCHGHDGFAAFCADBDDBDDGFAGFABEDBE,False +591,10.0,3.0,10.0,5.0,10.0,14.0,7.0,11.0,CFGCFEAFHGFCGAHACGFEADCAECAEBEDGFDHFEHFEHBEHFECFAAFHAECDHGDBFHHFAHCCFG,False +592,19.0,16.0,12.0,22.0,13.0,29.0,15.0,13.0,GHBEBBFBGFCCFDDECDGGDFGAFABCHFAFFABBCHBAFGHFBEFDEFGEFGDDGDDACDBCEAFEACEDDFFAHEAEDDHHFFDFBGFHGDBFHECCCFBDEBAHFAEFAGFBGDHADAFDAFDAFHAFGAGCHDB,False +593,7.0,6.0,8.0,6.0,8.0,9.0,6.0,6.0,DCHBFDCFDGACEACBBCBGHAGHFEHFEHDEGAEAACGFBFCHFCAEDFEBEDGF,False +594,30.0,31.0,17.0,16.0,20.0,23.0,18.0,23.0,ECHGCHGBBGFBGABGCDGHFFBFABDADAFEAFEHGBAABEABHABHACFACBEFADDADFBCGHHABFEBEGBCGEHFEFEBGEHGDAFBHDAFBAHBAHFAFACGDCHDCHDGBEBHEFEAFEDHACEBCFBCHBFHBAACFCBAHGHDDEADHAECACGBBABAFBFEBGEHGD,False +595,9.0,14.0,16.0,12.0,7.0,14.0,15.0,6.0,FEGFGGFDBAGEFGEFCCHCBEFBCGACBACFCCBCAFCAGGFFCBHGBHDBADADHADGBDGBDEBCHFCFCCGBDGDHEDADDFEBGGCFB,False +596,26.0,34.0,20.0,24.0,21.0,26.0,22.0,25.0,FEEBEHGEHEFHEFEEACGABBDHDDHGCGFDACBGBHGFHDADCFGCGBDAHHCFHGFEEFEAHEBHGBAABDABFAHFHDDADDFDBGGBFHBAEBAEBAHBAFACFADADDAGGBBGBBCCACFFBDFHDFHDBCBCABAECDFGDGHHEECCAFDBDEFCEFGDBBHBBHGGHFBHEGGEBCABCFBCFCAHBA,False +597,16.0,18.0,17.0,23.0,22.0,17.0,16.0,28.0,EECBEAGEDFCFADAHFCHFCHECDBGDBHDCHAAHDDBDDCDHHFHBAHBEHDEHAFHAHHEEGEEGDEBDEDDHBEBGEHGEHCACFHBDBACHECEBCACCGCGGEHHDHBFGEABFDFFDGFAHCGHCFHBGHGDABDAFGBEGFDFBDEHFA,False +598,14.0,9.0,12.0,11.0,20.0,14.0,7.0,8.0,EEAFAGFHFFBEAGHBCFFFFDFFBAFCEGEEGDCGDCBAADAHFFHAGHACDECBEDBEAACDGCEACHDDADBECBECHEAHFDEEEEEEEBC,False +599,31.0,15.0,28.0,34.0,25.0,28.0,16.0,23.0,EADADBADCDDCGEGGEAFEFGBDDCFACDECFECFBCHAEHABGFCCAECDEDGCDGCDGEAHDBBDBACEAFBFEBEDBEBEEFGAAGADGDFFCEFAFAABDFHDFHDGCDGHDFCDFHEFAEGCFDAFDAFDEFHBCDAFEECHHDDHDCFFAHHHHCHADEADADBADBCGCCHFAFCEHHAFHAHHAEGACCCH,False +600,10.0,11.0,5.0,10.0,8.0,10.0,7.0,10.0,HBFHBHGFGEFGEFAAFAGFGEBBHBDGBHHAHCDHEHBEAFDDBBABDFDCFHEBCECCADGADFADAED,False +601,1.0,4.0,4.0,5.0,1.0,4.0,5.0,0.0,EGCDDCBDCFDFBGBDGCAGFBGF,True +602,4.0,2.0,2.0,6.0,6.0,0.0,2.0,3.0,EDEEBAEDHEAGEABCHDCDDADGH,True +603,22.0,28.0,15.0,26.0,22.0,27.0,16.0,24.0,EADBBCFGEFEAGAFEACAHCDBABGHBHAEDGGDCGFBBFHFCEFCEFEDAEGEHGABFHBFDBGDBABGGCGBCGBABHAFDDFBDFBGFHFCHFCHFHECHDFFDFABFDBHDFDCFDCABHABHEHADCDDCDHFEEDAEDFEBHHAFHGBHBBEEBDHDHEDABDABAEGEEHAF,False +604,21.0,11.0,14.0,19.0,11.0,12.0,18.0,29.0,GHHGHHAHADHAHCGBCGBDGBDHDFAABAEHFCDDAACAFHBHHDEBEGAGGEBGEHDEGFGGCHGDBDHHDAAAACFACFHBHEAAEHADHGCHGHDBCFHEFHEFECDDHFDCGDFGAFHAHHCHBCGDCAD,False +605,9.0,11.0,6.0,10.0,8.0,6.0,9.0,4.0,DCGDAGDABEBBEBGEBGDDGHAHHBCCECAHAFFAEDCEFFEDCBGBBGEGDFGDBAAFDAB,False +606,28.0,22.0,23.0,19.0,24.0,23.0,22.0,23.0,GHDEEDGFDEHCEBCEBAGAAGEGGEGABFHGFAGAHGDCCDHFBADBDDBCDBFHFDGEEGCEHFFHCCHAGHABEACCACDFEEFAFGEFBCGBCBFAFFBFFDGEEGBEHBHHDCACFHCACAABAABAECCDFHHFHBDAEFHEFEECGFBGCDGEHCBGDBAAAHCAHDEHDBHABAAG,False +607,13.0,16.0,14.0,14.0,17.0,12.0,10.0,10.0,BGHBGADGDDGCECBEDBECAECGECGECFACFBEEBEADEDHFAHAAHBFEBHDCFDGDBFFBEGCAFADDHCABDACDABDHGFFGEEBFEBABCEFEHCHHCB,False +608,9.0,17.0,16.0,8.0,12.0,15.0,18.0,16.0,BGGGDCHHBHGBEACEACEGCEHFHCBGBBGFBGFAHCDGCFFCFGCBGBBGBFGBFAHFBGFBABCEGCEADHHEHHCHFEGEDHDDCDABGHECCFCFFGBADEAEHFH,False +609,34.0,28.0,25.0,20.0,27.0,20.0,18.0,15.0,FHGFEGEBBEGBEGHFHDFDAAEAAEDCFDBFEFCDCDDGEAFEADBCCACCDFHHBCHFEDABBABBABHAFGACGEEEACCACDDCBFCDHBFGBAGCGFADEADGABFABAGEEEBHBFDBFEBGEBEBHCCDCAGCAECAECAFCHGEEBFEAGEDECAHHABABBABDFDAHCABCAGHAGA,False +610,27.0,20.0,29.0,19.0,16.0,20.0,23.0,16.0,EDGGDCDCCDCCFAHFACFEEAAGGAHFADGADAEDCEACDAGDAHDCHFAFFHCGHCGDEBAEBAFHADHCBFBBDAECAECACGGGGFFCDGBHGECFBABDABGECGEFBFCBHDBHAHGACBAHEACCACHBHEFCBDCGDBGCBGHGCBFCADEFBFFGABGCEF,False +611,22.0,21.0,24.0,24.0,11.0,17.0,21.0,18.0,CGCHDBGDBABGACGAEAACCDDCDGCDGFDEHBABFCHACHAFGDEBDEBDABHGBCFBCBAHBDFBHFCFECFECGAGEAEBDGCGGCHGDFGDFCFBHFAFGAGHHFBHDAADCAHCAGEABCCBDDEDDHCCAAHFHHDADDBGHCGBFFBEDG,False +612,15.0,15.0,16.0,7.0,8.0,15.0,11.0,10.0,BBGABCABCFCHFCBCAGHHFHFFBFAAFAGBAGDEFFCFECACDACAFCABEEGCEGCAGDBCHBDDFDDFAFHACBGBHGBHCEEEGHCGFBHBA,False +613,1.0,6.0,10.0,13.0,4.0,6.0,8.0,9.0,GCDDCDCAHCHEDFDCCDGGDBHDCHDBHCGGFGCFGHFGFFHHCBBEEBDEDDBDH,True +614,10.0,16.0,11.0,12.0,14.0,10.0,10.0,10.0,DECEGBDAEDAEGGGHGAAEBAEHDGHGEBCHBCHBFEBCBFCBAHEDFEDFGAFDCFBCFBDFBCHCCHDHBDBBABFDGEEEDCEGAHBAF,False +615,1.0,1.0,2.0,4.0,6.0,3.0,0.0,3.0,HDEHFEDCEABEHFEDDECF,True +616,10.0,6.0,9.0,12.0,6.0,14.0,6.0,4.0,DFHDFBBECCFCCFBCDGAFFABDAGEADBDDACECFECGAAGHFHFFHFFDGDAFDEFDEBDAAGC,True +617,6.0,1.0,4.0,3.0,5.0,2.0,0.0,4.0,BDEHDAAFACHECHECDEFHCAAEA,True +618,22.0,16.0,36.0,14.0,21.0,16.0,20.0,16.0,BBGEBEHHHHHACECCGBEDBCDHHAHDCHDCECAFHAFDAFCAECGCCACCGFFDEGACGCCGCEGCGGEGACGACBDGGDEAEBAEGFECAECFBGECAEFFHBCCBCHEFADFDECDBCBFDHDECDGAABHCFGCAGCFGABEABCABCECCFFAHH,False +619,26.0,17.0,24.0,18.0,27.0,15.0,23.0,23.0,ADFABEBGDCGDEAEHBHDBCGECBECEEGAHGCCECGFCAFCHECFACBAHBACBAEBDEHFEDDEHGHHGHHGAHGAHFADAAGEAEDAFAADADHEGHEGHGBHDBCEECGFCHEBHBBFAHDCGAEGEEGECGHCFCFGCDDFDCBCFEAAAFEAHGBGDCDBEFCHAG,False +620,7.0,2.0,1.0,9.0,6.0,2.0,5.0,5.0,GBEGBDDHGCFGDGHEEHDEFAADAAHAAEAHEDDDD,True +621,16.0,26.0,22.0,21.0,29.0,29.0,17.0,19.0,EAFBDDEEGGEGGEGDFBBFADADCGDCBCCHCDDEDFEDFADFEDFGBFHBECAHCDBCGFCFECEEHAFHAFCGFBEHGFHEEHFEBCGBGGHABFGDAGCABFDBFDFFDEFBBBDHBEECFEHEACBFBDFHAHHEHHEHCCHGBAEBDCCEEFBBFAFCBDCBFBAFEACEGHE,False +622,7.0,7.0,8.0,11.0,8.0,4.0,10.0,8.0,DAGDCGDHGDACDBCFHHEGDEDEFHCBHEBHFDHEHBCGGEGBCGDCFDGEDCAABAABEAG,False +623,28.0,16.0,21.0,17.0,19.0,16.0,21.0,15.0,DEHGEHCAACGFGGBEFBEGGGBGFADAEDADDCCHGGACAACEBDGFCBDAAFBCCCCCAEEEECHDCEDAEFAHFABFACFGHHBEGCEFBAHCDHDBCEBCEAHAAHAABEDGECGFAGFABFAHFAHEAHDHBFCBDDAFDAGBGGDGG,False +624,3.0,1.0,2.0,2.0,0.0,4.0,3.0,0.0,GAAFDAFGGFCDFCB,True +625,2.0,3.0,2.0,8.0,3.0,1.0,2.0,1.0,DHDDBDABEGDDGBFAEDCEDC,True +626,25.0,22.0,16.0,18.0,24.0,24.0,24.0,13.0,EBGFHAFDBGEBGEFGEDHADHADAAFCAFCHGEAGACBDGBFBDFEDGEHGEHGDHGCFCEFBEACEBHGFHEBHEGFEBAECFBABCACCABAEDEDGEGCABEEDGEAGAAGCFFDBCGHAGCAFFGFDAFHFFGEBBBHBDAGDABDBDGBAFEDFCAFCEF,False +627,29.0,21.0,28.0,24.0,31.0,21.0,20.0,20.0,FAHFBGFACEAEHGHHCFHGAGFFCCDDBDGBDGBDBHEBHECCEHCAFEGEHGEHGEGGBCABADDACDEEBCHCGAAEAFCABCEBDABEABCAECAEAHHFCFGDFHDFHBCECEDCDFCDACEFBEDBFDBEBEHHECCEDAFDGFDHEEHEGHCDDADAAEGAFADCGCGFEGFEABACFAEBACBGDA,False +628,12.0,14.0,20.0,9.0,14.0,5.0,7.0,10.0,BAHEECEFDEACFADDABAECEHFDHCCCACBAEDHEBHEBHFHCFCCGCDACAADGEGCCGCGBCBBCGBCEBEHBEDCADBEGBCABHH,False +629,5.0,5.0,7.0,3.0,4.0,2.0,2.0,2.0,EFAECAECHGHFCDABDBCDBCBCABCGEA,True +630,23.0,22.0,17.0,29.0,22.0,31.0,12.0,12.0,CCDECDBBHBBHBGFACDAEHBFBGFCCEHGEHEECEFDDFDDBEDBAFEHBDHBFFFFFFFAFFAFHDFAEFACFCCGAFAAFGADGADFFEBHEGEAAFBDGBDADDAGEACECCFBBEEGGEBDBBCAADFEDCADFFDFAEFBHDDDDBCCBFGDAEHEHDDAD,False +631,27.0,22.0,17.0,34.0,24.0,29.0,22.0,24.0,FFDCFDCHHBFADFAGECGECGBFBAFBGGACBFCBACHEFEEFBEFEEFCBAEECEHAEGAEFACFADFDBFBHHDHAFHADDGHHEHDDGEBEEGFFDDGEDGADGBDHFDHFBHFHAABAADHAEHBHGDFGEAADDFDCCDCDDFBAGCFDCGDHBDHEAFDGBEGBADEFGCDBADGADHEHGFHBDHADGACB,False +632,14.0,22.0,9.0,14.0,13.0,13.0,20.0,23.0,BCFBCFAHGDHGAHEDGEBBCBHEGHDDDBAGBAGCECBBGBDABAGHDGHEFFBHEEEEHDEBDEFAAFAHGDGCDAFHAHGADGAGCDDHHFHGFHEBHBGHBFBBFGBFHHFAHCHHBECBGBGG,False +633,24.0,22.0,20.0,25.0,23.0,16.0,19.0,23.0,DBBDHHDHHEFEEFGABGFEGADFACHGEHGEHAFFAHECCEACEBBHBEFADDDDGGHGGHAABCFDCFBGFAECDGBDABEAFECFEHBAHFDBFDBDEFCBCCGDEACAAGBBGBDEAEAAGAAHBGHACCAECGCCDCGDEHAHGBDDEDDHDBHDHHFCHDBHEBCE,False +634,17.0,21.0,22.0,24.0,23.0,23.0,16.0,18.0,CBHDBHCEHCHBGDBECHEHFBCFDFBDFCGFCACCACCGDEAFGADEADFCDFBAHAGHGEBDDBDEBDHBGBDAEDBEDCEFCEFHBHCGDAHAAEDEEGGECBEHDGDBGEHFEFGEFBFFAFFCCFECEDHEGCAGBACFDGFDHFBABHADFBEFHADC,False +635,16.0,6.0,8.0,5.0,5.0,8.0,8.0,4.0,FFABFACAAFAAHAFHCEACEABFCDGCFACABGGDGCABAEBGEAGBAGHACHFEDDDG,False +636,0.0,0.0,0.0,2.0,3.0,1.0,3.0,2.0,EHGEHDEDGFG,True +637,9.0,16.0,10.0,10.0,13.0,11.0,8.0,12.0,FEDBEDBEBBEFBEHBFBFCBEGBAGBHGHDBDDEGBECEFHDDHCFHGBHEBCGBEFAACBDEFCGFAAHAHHFFAADAHDCHGCECC,False +638,12.0,9.0,9.0,12.0,9.0,15.0,8.0,15.0,EFGFDCDAGDHFCBFEAFHACHBGADEEHEFGEDHFDGDDGAECCFHBFHBCACHACHACFAFBGDBGDBHBHHBHDEHDAAAEFFFHF,False +639,14.0,20.0,11.0,14.0,9.0,16.0,14.0,14.0,BFBHEBAEDADCGDAGDAFBHCBACBAEAHHCGBCGFCGAABFCBFGADBFFFDFCDFEAGGDHDDEFFHGHHGHHEFEBHBBGDBCHBEHBEFBCABDGGDCGAFHBFABD,False +640,8.0,6.0,17.0,2.0,13.0,12.0,17.0,7.0,HCFFGFCHCCACAADFGBFCFFCGFCABGBEABGCEGCEGCACCFGDGECGHCAEGBEGEEGHBGEAFEHFEHGHGEECCGF,True +641,14.0,17.0,15.0,14.0,30.0,13.0,21.0,15.0,BBGEDAHDBBEHBCBEHAEGAFGECGACGADAFGFFGFEGDBCCBFCHDHABHEBGEDADDHEGHBBHEGCGCHEEHEEHGEHACACCEGCGGEDGFGAFDBFCAFBAFEEEHGEGFEBEEBHEFDECEEDEBGEDCAD,False +642,26.0,25.0,28.0,26.0,13.0,16.0,19.0,13.0,EBDECDGCAACBAHFACDCCBCDDHDFBDBDAHGAHGBHGBCFDEADGADGHFGBAHBCCDHBDFDFHAEEFDCGGCFCAFGACGCCFADBAEBGBGGBFGDFBFCAACAACECBBHBBGABGFCAHCDFGDCCEBCDACHBCAAEDEEDFEHEDABDACDAGDBB,False +643,14.0,19.0,17.0,9.0,14.0,22.0,18.0,8.0,GCCFBFFBEABEHDEBDGBDFAHFBHCBDEBDGBDHHFFGAFGCGHCACFBGGAGGFEGFCAFCADGGCFECECGFAGFAGACHAFHDCBBCBFABFEBCCBGFEAECDBBFFBAEEEEFG,False +644,15.0,27.0,16.0,22.0,21.0,27.0,27.0,18.0,EDFEFFDFBDGBEGBHCFHCFHFAHFGFFEHGEBGEBGABGCGEBGFFHADEDGEBFABGAEFEGFGGAGFDHFBHCBADAEFBCFCCHDFBEADEDBBBGDBDCACCFCEFDDFBHHAGHGGBGBEGCFCBFEGDAGDEHCEHEBHEBADHDHHDGCDGBAFBDCGAFGDBB,False +645,14.0,11.0,10.0,13.0,16.0,12.0,10.0,15.0,EEHEEHGEFGEDEDBGCBHHFHBFDBEEBEBAHBDGACGADGHEHHECDFHDFDFAEFACFBEBHEHAGDCHDCDGCFAAFAAGCDGCAAAHHFBCDBAFE,False +646,3.0,5.0,2.0,4.0,7.0,6.0,2.0,5.0,EEDEFDFHDFHGFHCBHFBEEEABHABFDBGCEA,True +647,17.0,19.0,20.0,19.0,12.0,18.0,17.0,19.0,HCFBAFBDFDHBCACEAFHCGGCAHBHHBHFECADGBGCDACAECGDCFDFEHBABGADGACGBEFHGFBDBCCBCFBDFADFGGFEGFHGFEBDDBDDADBFGCFGHECHCHHGGBECECCEBDEDHADHADHAFHAHAB,False +648,10.0,10.0,6.0,7.0,5.0,10.0,7.0,10.0,CHGDHGHAECAEAGBCGCEDFBGFCGBCFBHAEAFHDFBEHBGFAFFDDABDABDFBHFHHABHA,False +649,23.0,19.0,18.0,23.0,11.0,22.0,22.0,16.0,DFGDAGAEGAEDABBFDGADBHHAEGECAFDAEDACGBCGDCGHCGBCHEGACCAFDBFHBGGGDBGBFCBEGFHAHHCEDAEDBBAFAFFAFGAHCHCCDCCGBDEFHFFDBFBCFDCDDAAAGDEBDBBHBFHGFHFFHFAHGDGGDACDAF,False +650,4.0,5.0,4.0,4.0,6.0,3.0,2.0,5.0,DDHGDFGEFAECAFCDBCHEEAEEHHBACBHBB,False +651,29.0,15.0,14.0,25.0,15.0,16.0,23.0,19.0,GAFBABHAGGACGAGGAGHABDGFCGDEGEFDFACFBDAHAAHCGECDHFEHCDDEDDECGFDDFEDADAFDBFDBEGHFBAGBADBCDGAFFCEDEHAAHAACGAGDFDDFDAADCAFHBEHGEHGCGEBBHHBCDBCDHEBAEGGHGHHAAHAA,False +652,17.0,19.0,21.0,19.0,20.0,33.0,24.0,19.0,EBHGBHEFHAFCFFEAFEADEBHCBFCEFDEFHBGHGFDGDAHEGFEABBBBFBBFBBFAFEBDHBCBCGFEHACDCFDBGHGEFGACCFFFFDADGFDCFGEGHHGEHFFHEFHCFAGFBGCCGDCDDCGECGHAHEAGEDBCDEHDGHFGFCCDAAFAAFGAFDCGECGD,False +653,4.0,2.0,1.0,5.0,5.0,3.0,4.0,8.0,GBFEDEDGEDEADHGHHGHHDBHAHEFHCFAA,True +654,20.0,23.0,22.0,29.0,18.0,18.0,13.0,18.0,EDEBAEGHHFAHFBDDBGFBGDDABDABDADCCBBCEHGFCGFCDEHDFDGHDCBDHFDCBHBFHECCADGHGGEGBCBACHAEGEEFDEHDCHBEHFDBFCEACFAEDAFBGDBDDBDDBFDCFDCHDAACAABACGFCACDHHAFBAFBHEDCEBEEAC,False +655,7.0,8.0,11.0,11.0,11.0,5.0,11.0,11.0,CHBCHDCHBAHBCGDEGDACDEBAAAFBEFHFBGFEDEEAEEGDGGDGHDAHDHBEEGDECCBHCGCCGHCFHDG,False +656,23.0,22.0,23.0,10.0,19.0,19.0,24.0,14.0,FCGFCGAAEBHECHECHCGABAAFFEHBAHBCBBDEBEFDFADFGDFACFAFAHFBCEACECCDGBFEBFCCCCEGAAHAGEBGABCFBAAGFDFCEABEABECDGCGAHGHCCHBAFBHEEHCGBFGBAHBGGEGGEDBEDBDFGGGGGGACH,False +657,17.0,18.0,13.0,17.0,9.0,17.0,17.0,24.0,BDHBDGBFEBCHBDFBDHBAHBHHAAGABHACFFHHBBDDHHDHGFCFFCGHHBAHADGFDCFHCHCCBDFFGAFGAEEAGEHHBGFFGFAGHADHDCBDEFDECGAGADCAGCHGEHBEHFDABDGBCGAE,False +658,8.0,8.0,5.0,2.0,2.0,4.0,5.0,8.0,CEGBBGBHCFHBHBBABGEBHHGCFAAHADHAHGACFACFAD,True +659,34.0,21.0,21.0,17.0,21.0,20.0,30.0,25.0,HAFHDCDEGEEGAAGBGCBEAGEBGEAHCAHEAHCAHAAHFBHECECABCAHGGFGHHGEHDADFACFACFCGFCGFBBFAAHAAHBFFDAFDGFCAEAGFAEDBGBCEEFFFDEAGGADGCDFHGGHBCABCABCABHDGDGGEGGEGHEAHBDGBHHBCHDFAECGDBHAGHADABBACEFHBDEGC,False +660,14.0,30.0,12.0,19.0,8.0,11.0,20.0,13.0,DEBHHDCGGHGCHBFBFGBFDDFDDGDGBDBBABHDBHACECCACEABBAEBDBBGGGCGDAHCADCABHEFHBFDCDCGGFBGDBDBBGGBCGBEBBEBBHHBHFFHFAADGBBGBGADDFEAAGA,False +661,11.0,26.0,15.0,26.0,16.0,14.0,18.0,26.0,FEBHBBCBDCEDFABGAGEABBHBGCDGFDEBBEBBDBEGBEDDHHDHFBHEBEEGAHHDHHCBHCAHDHCAACEGBEGBDGBHBHDFHDHDFHECHCHEAHBGCFCFHDDHDDFDDAGEGGCCGDFGFAGFGDBBBHBDHFDACDCHFGDE,False +662,5.0,2.0,4.0,1.0,4.0,3.0,0.0,4.0,HCDFCFHCACAEEAEFBHABHAE,True +663,14.0,22.0,18.0,13.0,14.0,22.0,18.0,29.0,DHBHHBGHGDDFFFCBHCBFCHGCGGHHHHABCCBAFAEGBBDBFCFECFADFHBCHADBADGHDGCDACFHBFGFFBFGCFAAEACHAFHEEEEHGEHAEBGBGGBFCBFBGGBGAHDHHBECEHCHBFECFHAFHDCHDEHDEHGFHB,False +664,22.0,13.0,19.0,20.0,21.0,19.0,24.0,26.0,AACFEGGECAHDGHDGDBEHBGDGGCBEAGEFEAGBGGBFFBGGGGDCEEAAFFAHEBFEFACFECEABEFHGFHDAHCBHCFGDFHDAHGEHEAHEAGCCCHDAHFCEFCDCAFCGCHFCHGCHGCBGFBGHHDAHEAHDHHDHEEADEFDHADADDHDBADB,False +665,19.0,16.0,20.0,18.0,23.0,17.0,22.0,24.0,DAACFCEFCEHBFHAEHDBHBHABHABHAHCCGGCGCEDBDHBACCCCCAEDHEACEHEDGECGEFGCGDEFHCAHADFDEEDBECEACDGEDGFHFAEFAGBHHAHHDHAGBBFCGFEGHBHFDEFDHFHHABGABGEDGEDGEGGBCEBGDFGFFGA,False +666,21.0,15.0,10.0,14.0,9.0,13.0,18.0,9.0,ACFGBACCACCADCDGADGADGHBABGDFEDEGAGFADADDBEABDABEABAFBAFBGFGGACGBFEBFEHFHGACGCFEDGBGABCEHFGBAGFEDADBAFHHGHHDH,False +667,8.0,7.0,10.0,12.0,11.0,15.0,18.0,9.0,FAGEGGDGEAGDFCFFHBFDBGDFGBAGHCGFCDBCGBDFHGFHEACECCECAEFGCFGHFEDGHGBHFCHAEDAEDGDFGFGEBEDHAD,False +668,10.0,9.0,8.0,13.0,5.0,7.0,10.0,7.0,GFDGECCECCFHAGBGDBDFADGEDAADAADAADCGBGHBHBDHFGHFAHFACDEHBEBDDCGGCDFBB,False +669,7.0,12.0,7.0,12.0,9.0,2.0,15.0,14.0,HBGHAGHEGBCADABEEHFCCGHGGEGGCDGCHGEDGDBADBHDBGEAGAACEDDFBHBBHBDHBDHGCHGHDEEBHD,True +670,0.0,5.0,2.0,3.0,7.0,4.0,3.0,4.0,FGCFHFEDBHBBHFBGEBEEDEEGEHCD,True +671,5.0,12.0,12.0,3.0,8.0,4.0,5.0,4.0,BBCBBAECHCGHCHFCFCCBDBECBEBFEBCGHCEFGGBAGEAEEACCBDABD,True +672,11.0,18.0,12.0,10.0,18.0,18.0,25.0,17.0,AGBBGFGCFCEFCBHCADEBHCHDEBGGGGGAGGCGFHFBHDBFFAFHAEHFEFFAGBEDHHHHBBCFHAFCGCCBEHBEHGDBFEAGEHGEAGEAGEGDBGDCGDGGDFHEFEBBCBAGBEDHEFGEF,False +673,9.0,13.0,14.0,18.0,14.0,11.0,8.0,15.0,CGDBHCCHGBFGAFEEHEHCEHCACCADCDDCGBCDBHDHCBHEHABHEEGDFHDGACBAGDFEDFEDECDBDHFEHBEFFEBCEBDABAAGFHFDDFDDHB,False +674,8.0,13.0,7.0,9.0,11.0,13.0,8.0,11.0,GHHFHFCGFBEFDEDDBFDBAHFHHFCHEDGEHGCBDBHHAEGAEAAEBAGBAEFCFGCFAHBGEFECBCBBDBBDEFDF,False +675,1.0,9.0,5.0,1.0,4.0,4.0,4.0,4.0,BECBCFDGHHBEBBFBBFBCFBHGAHGCEECG,True +676,7.0,7.0,1.0,4.0,6.0,8.0,6.0,3.0,ECHEDFEAHHDFABGEBEABEDGFAGBAFBAFGFGGFABFDB,False +677,14.0,18.0,19.0,11.0,14.0,16.0,16.0,25.0,EEHFECBGCECHDBHGHHGHHGABBDFBDFBAFHAGDABCABFHHABGAEGDBHHGHFFHDFEDFHFGACBCCGCAAFFAHACDGCDBCHBFGBHEFHAFCCEBBDHCHFAHEGHEGCEHCECCHGEGBECBD,False +678,9.0,12.0,6.0,10.0,11.0,11.0,13.0,11.0,CDEAGGDGGCGBCGBAGBGEBDCAFGHFGBFEHEEACFAGFDEFGBHHFHHEHFCGDADHHDHEDAADFBFBBFBEEHEABBD,False +679,27.0,20.0,25.0,20.0,31.0,18.0,23.0,23.0,EFHEDHDDBECBDAFEEFEEAADGGCGEBGADEECEEFEECAFCGEGGBFCBFABGACDAEHBHCFGCHGCHGCFDCBHHBEABAHBABAHEAHGADGCCFECDHDFAGECHAFBADBGDBCABHADDBHCEHCEHBFHGFEEDCDHCEECGCDBCAHGHBGEAGEAFFAFGAEEAFAHGEHGDACD,False +680,27.0,26.0,27.0,28.0,20.0,19.0,14.0,25.0,GDCFDCFHCBAEGAFACFAGFDBEABDBCAHCGFFFCFBBBADBGFCDACDGDDHCEHAEHBFGBHECDEGAACBHCHEAHEFCGACDBHDACGACHAHHAHDEHFCBBABBABCHBFDCGBCHBCHFDHEEBDEHEEHGEFABHAHCAEDBCDBCDEEDCBDBHAFAGEADDADFADFDDHGDEC,False +681,3.0,1.0,1.0,3.0,4.0,8.0,7.0,1.0,HGFEDDABGFGGFGFFGCGAFDAFEEFE,True +682,15.0,12.0,11.0,14.0,15.0,27.0,23.0,14.0,FHFFHFCHGEDCEDGABGDBGFFGFHGDDFFDGCHECAEGEBCEFCEAAAAGACFAGGGBEGBFBAFBAGGAEHAEHBDGGDFDAHGGEGGHAFHGCEFDBFEHDDBGFBCFAFFEHFCHFHDFCFFDEFB,False +683,3.0,2.0,5.0,6.0,4.0,4.0,5.0,2.0,GGFDFADFADECDCGBCGEDHEDHGCBCAEF,False +684,13.0,18.0,21.0,19.0,20.0,13.0,21.0,11.0,FEEGGCAGBEGFECBEGBDHBDCCGACGFBFEHHEHBCHCCFDCDDCEACEAFHHFCFDEBBGBDCBDBADEDEGCFDHABEDGEGFDCFECDEAHEDGEAGFAEAAGHADABDBGCGGBGFBDCBDGBCGECGHC,False +685,10.0,7.0,12.0,11.0,9.0,18.0,8.0,9.0,HDHAGFAFFAFFAEBDCBDBEAFEACEACDGDDGFCHFCBCCACHGCFFCGDEFDFHEFHDCBEHGEGFFDFAAFBEFCDGHBH,False +686,6.0,12.0,8.0,11.0,9.0,7.0,20.0,10.0,BCEBCDBHAGDAGDHGDEDAGDGHBEHDDFGDGEDAEGGGCEBCBGGGCHECBFHHGGFGGFGGHGAHFBBCBECBHABFDEF,False +687,12.0,20.0,16.0,25.0,15.0,20.0,20.0,33.0,DFDHAGHAEHBHBFCFFDHFDBGGCCBDABHGGHBBCBFCHCEEADDACDFCAFBHBHDBHFBADGHDGHDGFEEBHHGGHGHFGDFCDHEEHCECCHDBDAGDABDCBFHAGEAHEHHEHFDHFDHFDEFDCCGBCHEDHBDGEHGBBGFDHAHHFEFGG,False +688,3.0,9.0,2.0,3.0,7.0,7.0,3.0,4.0,CFEHFBFBBEDBCHAFABFEBEEBDEHFEDFHBGGBGA,True +689,15.0,26.0,20.0,34.0,29.0,23.0,27.0,17.0,GAAGDABHABEGDEBDFFDHFEHFBFCBGCBCCDGFDEHDCFDBHEBEFBEBCGCDGADBDGGGAAFCEDCEDBHGBDDBEDFFGFEHBEFFCAHCHHGFDDBCDBDFEHFGAFHFFDBEABEFBGFAGHGGEECCGABDDBEEBECBEAGCHGDHGDEDHFDHDAECAECDEDGEDEBCEDDGGDEGBCG,False +690,2.0,5.0,5.0,7.0,3.0,8.0,3.0,2.0,GFGFFGFDHHAEBCCBCDFCDEADFDBFDCEDBBF,True +691,11.0,14.0,14.0,3.0,13.0,5.0,13.0,10.0,ABGFGEEGEEGEHAHBCHBDDGHBBABACBCEEGECGECGHCABCABCHBEGAEFCCGBFGCAEFGECBFHACHACHDHBGBA,False +692,17.0,27.0,23.0,13.0,20.0,16.0,15.0,12.0,BCCBCGFCGFADAABEDHEHBEADCFFEFFCABCGBABBEGBADBABBFCACGEDBEBBGFBGHBGHDEHBEHBCHACHFGEECHGFHGCCGECGDBBDGAEADFCGECDEFEFCCFAHFEHEABAFCCECEBDDBADBABBC,False +693,27.0,22.0,19.0,22.0,14.0,28.0,28.0,25.0,FCDFEDBEDFECFBHAAHEACBFDEGDCGFFHHFADGABFAFAAGGBHFECAECAGCGBDGBDHBHCBHFEHBBAFAAFAFFCHFGGFHAADCCGCCGBHGDDGFDGBDGBABHAGFDBFGBHAEFFDGFDGCAACAGGHDGAGCDEHDHBGHEFCEFADHEHABHAFHEHHDBGGBFCBGCHAD,False +694,18.0,13.0,19.0,10.0,11.0,15.0,13.0,6.0,GDGHAABAGDGHFBFGBCGACGAEAFDAFDECHECACBFCBACBEBDGBFACEEBEDCEACEBBDDBGFAFFDCFECDHCACCGBFGHGCEGCAAHAAFCAFCFF,False +695,10.0,11.0,11.0,10.0,20.0,12.0,15.0,5.0,DBDBFDEGDBGEEGEGFAAEGDFCFECEEAEEBHGGHCGHCFACGHEGEEGAEFCEFBAFBAEEACCGFDBFCHACEDFADFGBGCBDEBEGBD,False +696,11.0,15.0,9.0,15.0,19.0,14.0,16.0,14.0,BBEABEBFEDFHBEDCFCEDEFDECCEFGFGBHGBCGHGFHEBDGBFGCFGDGDACDAFBFHBHGECGEHDEHBBFDEEDGEFCAAHEABEHHEAHEAHDAHDGGDBGFAGAD,False +697,4.0,10.0,3.0,4.0,4.0,9.0,13.0,9.0,EFFBHHHHHCADDEGDFGBBGHFGBBBBHBACEHCFBEGDGGFGGFGAFGAGHFGB,True +698,8.0,6.0,6.0,10.0,3.0,3.0,10.0,9.0,CHGBHGEHGAAGHDGDAGDBDHADHBDHDAFACBCFBGEHCEFCGABGAGDCDDH,True +699,23.0,20.0,26.0,25.0,24.0,29.0,20.0,24.0,CDBFFGEGEACCACDGBDCHACHACHBGDBCFBHFHHFHHAGHAGHCHAEEGCEHEEFFCDFDDFDFAAEEFEEFBEDAEDFGDFGDHHDBCBBCEBEABADDAEDGGGCEHAGBEFBCFDHFBEFADFDCEHFEHFHADCFDAFHAFBFCEDDBCAHAACGCBFCDHBFHDAGFEGFGGCCGCBBCAHGE,False +700,29.0,20.0,21.0,24.0,24.0,23.0,13.0,26.0,EBHEBHBADGAHAAEEACGAFAAFBBFCHDBHAGCDEBDCDDAHHBCEAAFHAFCABDDEDEEDFHDFCDFBEGCFGEFAFGCHGDHFFEFHEDDEADBACACEFCBHCEHCAAEAECAEBFDAFHAHGAHGBGCBDHBDABDHBDHADFGEBABHFCFFAHFDECHHCHHCFCGDEGEE,False +701,3.0,7.0,7.0,3.0,6.0,6.0,4.0,11.0,CEFCFHGFHBHEAHECHEBBAHAEECHCDHCFFCHBGFBDDBGHBGH,False +702,9.0,6.0,16.0,15.0,12.0,8.0,10.0,9.0,FDCFDCDAHDGHFAACBCHDEHEGDEDDFDDEGCGCDBCDEAFCBCCBCGACGACHHEEHADDAEDCECFECFAGGBBEHFGHEG,False +703,6.0,1.0,3.0,5.0,2.0,9.0,6.0,6.0,DABEAHCFGGFAGFHHFCFFHDFHDCGFFGDEGDHAAA,True +704,4.0,1.0,0.0,2.0,2.0,1.0,3.0,0.0,BGGAAGEADEFDA,True +705,18.0,19.0,12.0,21.0,25.0,19.0,18.0,24.0,FDAHBFHDCHACHAEAEEBDDDDDGFHHFEHDDBDAAAFHAGGAGDABCHGCEGCFDBGCBEFHFDHFHHEGCFABHEBHCAHBBHEAEEAEGAEDEBGFCDHEEHGEFGEFBDFEGFGHFDHFBHDBGDACBAFBDFEHEECBEGBDGAEGEHBC,False +706,17.0,12.0,10.0,18.0,25.0,13.0,22.0,21.0,AGEHCDCDAEDAEBAGGHGGHDCHEHEFCEABEGBEBHAGABHABFFGGFGAFGDBGAEDAGFAHEEBFFAEFBEHCEFDEFEHDCHDCHDGAEGAHHFHEBEEGABGDHGDHBDHDHGCEDCHFCEEDDEHDGAGGE,False +707,18.0,24.0,22.0,26.0,29.0,18.0,27.0,19.0,HFHHGDEGFHCDHCEGFEGBDCEDEEFFBFCAEBBGABHADAAGABFDCGCBHABAGHDEDEEHBAHDAGDBGCBDHHDBEEGCFGCHCFHBFDEGDHDFHAEDAGDFGEFCEGGEBGCCCCECGECGCHACEGCEFCDFBDFBGBEABECBEBBGAHGDHDDAABGGBEGAEBEDFDDFEDE,False +708,20.0,10.0,10.0,16.0,13.0,13.0,19.0,23.0,FFHDFHCCACGGGHEEHDGGAGEAGHAEBAHDGHGGHBGAGFCBDCDDADDCEHADDDHBAHBAHBGGAFAAGAGGBGFHAHHDHGEHEFHCFHCBACEDBDDFCEFAHFAHEAEFHFABEDHE,False +709,5.0,8.0,2.0,9.0,7.0,8.0,16.0,8.0,CGDAGDFHDGABHDEFFBFFBEDGGAGGCEGHHGADEFDEDHEDGFBGHGGHGGBGBBAHEFB,False +710,2.0,0.0,1.0,2.0,0.0,3.0,1.0,3.0,FGHDDHAFHAFC,True +711,11.0,11.0,7.0,14.0,11.0,15.0,19.0,23.0,DHDDADGHBGFBGHHGDGAHHHGHHGBCEDCHDHDECGGFDDAGBHGBGDAHBFFBFFCHFCFFHBFHEHHGAFGAHGHDCDDAGEHGEHBFHEGBAGFAEFCEABEAEEF,False +712,22.0,16.0,19.0,9.0,22.0,12.0,19.0,16.0,HDGBAGAAGFEEFADBADHGCGCDBCABEACGHGEABEAFGHFEHFGHFGHCGEFGEFHHACDAHFCGECEABEAEEBBABHEFEAGEDGBCEHDEADCBDABCHCCHBCGAGHACEACHFCEEBAEBAGBGFCC,False +713,10.0,16.0,20.0,25.0,19.0,11.0,23.0,14.0,FDCDDBFDGCEFFEBBEBBFDBHCFAAHGDHDBFFGFDACDAEDGEGGDCADCDDGEDGEGCEGDADCGDCBBHEBDECEHCEHGBHACEGGDCGHHGHDGCGGCGCDHHDECCEBEEDABBAGBGEAGEFDHFBHCC,False +714,7.0,8.0,11.0,9.0,14.0,8.0,8.0,14.0,AADAFBHGCCGCDHHFHBCHDCHDEHEEBFBAFHDGHDHHEAFEFCEGDHBEHCCFCHBBEDEEAFEAECGECGEGDBG,False +715,4.0,5.0,2.0,4.0,4.0,2.0,5.0,7.0,BEEHHBHHCDHCGEBGDBDHEFHFAAGAAGBDG,False +716,2.0,4.0,4.0,2.0,5.0,4.0,1.0,3.0,GBACBHFFEFFDHBDHEAEECECCB,True +717,15.0,12.0,19.0,9.0,14.0,21.0,18.0,23.0,DBHAHHEFBFAGHAGHAEHFEAAGCGHBFHBAHDCHCCDAGGHGFDAFEEEGECHCCEBGDAGCAGHGFACDHBDGBAFCFFCDFCFFCEGCBGFBCHBHAGHFHCBHAFHCFGCEGCEHFEBEEFFHDFH,False +718,21.0,29.0,17.0,17.0,19.0,12.0,14.0,21.0,BHBBDDFDBFDBDHADHBCABAHFADGBECCFDBADGEHHBBEGHEDHCHEBHBHHBEEBCABFBBFBFDAFABDGCEGCEGBEACEBBBBCDCHGEDEEGGHGAFGABGABAAHAHHAHGAHGEHCDCFDCFEEDEBHCCCACAAFABE,False +719,15.0,18.0,17.0,14.0,22.0,18.0,20.0,22.0,GGECFCHFHBEHBEDBEFBEHBDHBGAGFAHFAFECFDFHGFBGDEHECDGCAEFHEFBDGHDGDBGBBGBHGCCGCCGCHHEBBBBEEAHHBFEACADDACGCFEHFEHFAGAHGEHFAAFCHDCEGCEFDEGBHGDHEECAADA,False +720,4.0,4.0,3.0,2.0,1.0,3.0,4.0,4.0,BFBBFHBCHAHDAGEAFCADCGGGH,False +721,22.0,14.0,33.0,22.0,22.0,16.0,25.0,18.0,EGACBDEEDAADHAHBABBAEGAEGBHCBADGFBCFBAACFEEFEDHBDCGECHHHAGEAFECFEGFGAFGHCGAFGEFECFGCABEEGGDAGDCCHCCHGDEGBEDBACAHDACCCBHCAHCHDGHAECDDCDHCFCDAHHCECGECGDCGFGECCCFCCDDGDDGDFGBF,False +722,15.0,12.0,9.0,7.0,14.0,11.0,9.0,13.0,HFDHFEHEGDBCFBCAAHFAEFGGDBADEAFEAHEAHFBGFHEAGEDGBBABHGEHGECCABCEHDBADCFEEFAHFGHEAHACCABCBB,False +723,25.0,27.0,19.0,19.0,29.0,24.0,29.0,27.0,CHBDGEDBEGCHBAGECBACBGCEACAGCAGEFHHHGHAGAEDHGCGBBACHDGDAGDAGBFFBGFBDFEAFBABACDEFFEAHHAEHGHHBFABFACHHHEBGBBEABEAHEDGEDBFDCHDBGGEHHEGHFCHFHAFDAFEGGHGECDFGGBGCFEAGECBECBECFEAFEBFEHFEHBDDAEDADDFCBFEBFGHG,False +724,7.0,6.0,4.0,4.0,2.0,2.0,7.0,4.0,BACDABGAGDBGHFGHFCHAEGADGBEGBAADCBHC,False +725,13.0,14.0,14.0,9.0,9.0,11.0,7.0,5.0,ADEDDFDEGBCACCABCADGAFGFGAEGAGBAFCFFHBBHCBDBFEGAEDBDFHCEECEAFBAFHCFCCDBCABCABHBBEC,False +726,6.0,1.0,2.0,1.0,0.0,2.0,3.0,0.0,ADAAGACFACFBGGA,True +727,22.0,23.0,26.0,27.0,23.0,28.0,17.0,22.0,ECCBCCADCDDGGAHBAHFHCGHEGHCAHGHHGBEFCAFBAFHDFAFCCBACDGCBGHGEAGCDECFEBEEDFDFBHGBAGBADFEDAHDACDGEFEEHGEHFAHFAEBDBBEBFEDAEDHDDCFDGDABEGDFHBCBFDFFACFAFHEFHABDCCEABEFFHCFBFFBFCBDCBDCEDGDAHDCHCE,False +728,0.0,0.0,3.0,1.0,3.0,4.0,2.0,2.0,CEHCFCGFHDFEGFE,True +729,17.0,19.0,22.0,26.0,19.0,16.0,18.0,23.0,GFHGAGFACDAEAGFDCBCCBCBBGBDGEGCEHDDADHEDBADHDEFBEDBDGBCGAHHAEAAEBDGDGGDGABBECDEFDEFHCAHBDHBHGGDFFEFDCCDACBAHEABCHEEFCEFHGFHDEBGEBHHHHCFHEAHBAHCDDDDCGFCHFCHCCFCD,False +730,10.0,12.0,10.0,12.0,5.0,3.0,7.0,9.0,GGBHAHCBEBDABDCEDEGDCGDAFAHGAHDADDACHACGECADHABCCGCBBCBBHHBFDEHDBDFB,False +731,8.0,9.0,15.0,9.0,17.0,19.0,15.0,6.0,BHGBCGBCDBCFBCBACFAFEGFECFEGFGCEGCGADEFECHEDEEFFEFFGFFGDFCEGCACBAFADCGEEGDBADFAHHDGHGFEEDCEHFFBGEC,True +732,15.0,25.0,16.0,23.0,8.0,23.0,16.0,19.0,CCGCCHDFHDFABAHDHGDBFDHDDBBDHBGHGFDDFGGHEHABDFCHFAFCACBBDDBDFBDABHABGBEDBEDAFCFBCFGEBBHCBABGABGHBGHFGCFGCFGEBEFADCHFHFFCDDCHAEHBDGADAADGFCFFBFEBH,False +733,26.0,12.0,25.0,16.0,6.0,12.0,11.0,16.0,DDEFFEHBCBCAGCHGBHAAHCAHAHHBHHGGHCFDCADCADABFCCGAFDAGHCCCACFADFADAHBGBCFFDBCHAFAAEDEBAHBAEFAFBADBDDADCCCCCCCACCGCDGADGAEAHGH,True +734,24.0,26.0,16.0,18.0,21.0,14.0,24.0,22.0,HGDGADCHDBBAEBDEBDEBEEDECFBCAGCBCHGDBGEBDEBEEBDGBGHHFCDDHGDAGHADEBDAAHBGBAHAEEGEBGEBAACFHCFACFHFAHFAHFDHCBEAHEHBCHAHAEDGFBGDBGFBHBEGDGGACEACACBACFAGGEGBFBHAGHAGCFGHF,False +735,22.0,22.0,29.0,19.0,27.0,26.0,31.0,18.0,FACFCCFCAHCGBBDADAGDFEEFAEFAHADEGDACBFCBFBHGCGGCFFBGFGFBBHHBCAADGCDECGGCGGCAGCEGEGGDDGAGHAGHFCFCEGDGCFFBDEBDFBFEEEHEHBEAEEAEEAGEFDEGDBBEHGAGFDGEDHBCHGAAAAABCECCECCHCCDFHBFCEGEDGFBFCBFHBFHDHHCGEB,False +736,3.0,2.0,3.0,3.0,1.0,1.0,2.0,0.0,DCBDCBGCAGADEAF,True +737,25.0,20.0,13.0,20.0,9.0,15.0,15.0,17.0,BBCBGDDHBCECEDCBDHGDAGDAEAACDBCDAAHFAEFDCFAFBAGAGBABHABDABFAFFDDHHHHBFHDFGGHDCFGGHHGAAEAABCAGCBGCEGABCADEBBEFBDFHGFHDFHCFHAADEBDGADABH,False +738,15.0,21.0,15.0,20.0,23.0,14.0,16.0,14.0,HBDCBCCDFDDBDABDABDFDHHBEGEFGEFGECGECGECABBEGFEGFGFBABDGBHGBHCAEBBEBEDDDBHDAFCACCEBHGGDEDAEACFBFFBGFGEEHHEHEAHADFCDCAFCDEBDCDEGEHGAHAHEABE,False +739,6.0,4.0,7.0,3.0,11.0,9.0,13.0,4.0,CEEGFEGFDGBBEFGGDEDHCCEAFEAFBAFGACCAGAFEBFEGFGCHGEHGECGHG,True +740,18.0,18.0,17.0,21.0,22.0,23.0,24.0,19.0,CHFCHDGHDGBDCFEEFEDGHDAHDAECAFGFFHFCDEGAHBDBEDHEGAEGAEFBEHAEHABBAHFGECAHBFCDFDEEDEGDACBFHDFBGFGFEEFAEFCFBCHBDFAGGAGGAGBAGBEGEGDDGCDBBDBGEFGDDGHBBECHFCHCCFAGHCFCAH,False +741,9.0,8.0,14.0,9.0,12.0,8.0,10.0,8.0,HHAGBAGCACBHFBHFDEADGBFGCDABDCEDCEFABGECCEBCDGEEEEECECCFACHAEFGGFCGFDGDACDHHBH,False +742,12.0,15.0,13.0,8.0,14.0,16.0,4.0,12.0,AFFFBFFBCEAFAAEBHDAEAHBCHFCHBDHBFHBDEBAHGFHFBEGCFHCEAFEAHABDBEDEEFECHECGECFHCFCCDCCGBDABDBBEFA,False +743,10.0,6.0,7.0,8.0,13.0,10.0,9.0,5.0,AFAAEBGEBEECEEDFCGGHDGDFCFGHFBHEHDDAADEDDECBEFBECHCGAAFFAFEAGEAGFBGC,False +744,4.0,4.0,4.0,5.0,4.0,3.0,5.0,8.0,FHDHHGAHBHDDHGDAFEACEACEGGFHBCHBCGEDB,False +745,5.0,2.0,6.0,1.0,2.0,4.0,4.0,5.0,CHHCFFGFGAAGAHGCHABEACEHCBFCD,True +746,6.0,7.0,9.0,8.0,5.0,5.0,6.0,0.0,GDGGFGCEDBEDACDCCFACFCDABDACAACBEBBCFBFEEGBDGD,False +747,23.0,21.0,27.0,20.0,27.0,21.0,28.0,26.0,DEADBCCGHHGHDBADBADBEEBFEBEBGGCAEDAHDFDGHEAHEAGEDGEFGBAGHFHECBCAEEBEGFFFHHHDHHGACGEEDCADBAFBHGBAFBDFCDCBGHFHAFCCDCGACGAFGCEGCHBBDGCHFDAFGGGBHGBHAAHCAGEDCCGCCHBCHFFHEFCEFAAGACGCEECECHEBHEGEDFEDF,False +748,3.0,5.0,1.0,5.0,3.0,2.0,3.0,3.0,DBGHEAHDADDADECFEGBGHBFBB,False +749,11.0,7.0,13.0,10.0,10.0,9.0,18.0,6.0,AGEGGFDHECGGCGBCGECBCCEFCADCGHCGEGBEBDECGGCAFHDDHGDAGDAEAEFDGADGAFCCFBAFEFDGFAGBAHBH,False +750,19.0,21.0,8.0,26.0,26.0,23.0,18.0,20.0,FEHFHBCHBCHAAHDGEABEDCECBDDAFFAFDGDHCDEGDFADCHDEDEEGHAGDFGCFGDFAEBDFBAGHAEEAEAAFAFBAFBEBBDDBDHEFHEHDEBDEFEBBAAEAEGBEDFHDHGBEGEFBHCHFBHEGGEFGEFGDFHFHGDBGDBFDBHDGA,False +751,10.0,15.0,9.0,6.0,11.0,12.0,12.0,15.0,GDEEDHHBBFGBHHBEHFHFBDCEGGEGCBCCAFCEFBECHEHEBHBAABFABFABFGFEGAEBDHCGHAGHAFCACGAHDHFDHGBBGF,False +752,16.0,16.0,21.0,19.0,22.0,24.0,24.0,17.0,HHEEFGDFCDFCDFGHFHABEGECBCGBCGBFGDFBCBAFFGCAGCAGBAGHGDHDDHGDHGEHAECADCEFFAFFDEGBAGBCEBAHFACCDCBGEHDEGAEFCEDBEHFHAEDBGAGFECFGGAGGEFHDHECHECFECFCBDCGABDBHDFEFFED,False +753,5.0,5.0,9.0,7.0,8.0,5.0,5.0,7.0,DHCDCBFEBACFGCHGCHGEDGDDEDHAGEACFACEAHEFCCFBDHBHBEE,False +754,1.0,1.0,2.0,5.0,0.0,0.0,2.0,1.0,GGBCDDCDDADH,True +755,3.0,4.0,2.0,11.0,7.0,7.0,7.0,3.0,DDGGDGFFEFFGGDECDEDFEDFBBHBGFBHDAGCADHDDEAEE,True +756,13.0,13.0,9.0,10.0,17.0,10.0,13.0,12.0,CGAEDBDFGGHCGBCFAEEAGFBFFBFFBEGEEBEEHEECDEGACGEHAFGADHABHAHHCGHFGHEHEAHGDDCAHFAEBAEDCBBCBBGBDEDDA,False +757,8.0,8.0,4.0,5.0,4.0,3.0,10.0,2.0,BDEBGHGGFDGFDAFCGGCEBBAACEDCADHABGGBGBAABGAE,True +758,26.0,19.0,23.0,17.0,12.0,22.0,20.0,22.0,DDGDEFCHCHHDHHCHGGHDBAFBFGBFEBCAFCAFHFFDCCDCEACACBFEGGHGGDFGDHCBGAFCAFEDBEAEEBDFGDAGBHBHHADGCDFCAHCHFCGFCGHCBHABDABAACHAFAAHCBHBFABFAGFDBFHBEECGAGAAGFAEDABACCEGH,False +759,4.0,1.0,4.0,4.0,4.0,6.0,8.0,4.0,GDFGAFGDGCFGCFCAHAHDFHEEHEEGDGAFGCB,False +760,2.0,2.0,0.0,1.0,4.0,1.0,5.0,1.0,ABEDBHAEGFGGEGGE,True +761,21.0,26.0,28.0,30.0,24.0,24.0,21.0,23.0,FDCHDHHDFHCCGFFAFAAGABBDGBCGBHGEHFHFBCEACEHEHBEABDBBABAGBFFBHDEEDBGFCGFCGFBBCBBDBGGGCDECDCFECFEABGCDAEHEHBEDDADFADGAEEAEFDCFHCFBCHBCHAEDDEBGEDGFHEDCBACDGFFCEGCDACABEGCDGHEECFCFHDFBDHADHADHACGDCDDHH,False +762,24.0,12.0,13.0,17.0,17.0,14.0,9.0,11.0,CEAAEBDEFDBCCBABBACBDBDDADGCGHAEHAEHBEFAEFAFCACHBHFEHADHFEFAGFGCDADDACDEDGEBGECAEBFEBEADGACFAHAACAAEADDFFGAFGCDHDHEFH,False +763,6.0,8.0,13.0,10.0,5.0,9.0,19.0,14.0,HGDFBDFGCHDCBGCEGCEGHGHHGACGFCAEEHBBGDHGCCGFAGHADHBCGDDBEAFDHFBHFDGCAGCGFFGHBGHCGHCD,False +764,27.0,23.0,30.0,22.0,19.0,28.0,33.0,17.0,AACCCCCCFBCDCCGCFBEFDGGDCGFCFFCAECBGBFCBGEHDEFGHFGHACHGFAGEAFFFCHFDGCHGDGCFGCFGCAGDBFFBECEGCGGBGHBDAEDABFABFDBDDBDAADGHHFBAECEBHAHHEFADFADFACAACGECEEAGEABADBDHEGEDGEDBFAHGAHGAGCDFBAGBGFFDCHBHEACGGBGB,False +765,18.0,15.0,16.0,11.0,14.0,19.0,16.0,15.0,CEFGFFADDDDCFAFGAFEEEAEHBEHCECAEBAECABHACHFCFGBGGBDABCFFFGFHGHGDEDABBABBAHFACGDFGDFGCBEEDFHACHGCHGBHFEGFAACECDGCHGBHCBHBAHAF,False +766,2.0,0.0,3.0,2.0,3.0,1.0,2.0,7.0,HHEHHCCHDGHDFCEHAEGA,True +767,17.0,7.0,6.0,11.0,18.0,9.0,7.0,8.0,HEEBEFBEBEEGHEFCEACFABFHBGEAEAACAADAADADDAFABDAGDEDAGDEDHCHFABEGDEFDEAEECEGHHHFGFAC,False +768,7.0,8.0,17.0,12.0,13.0,9.0,9.0,18.0,EBDDBCDHEEEGCEFDAFDABCBBHFGHGGHDCHFEHFAHAEHCFHCAHEHBEGECHEGDECCCCDCBHCGHCBFGECACHAFHDCDDHFDHG,False +769,20.0,21.0,9.0,15.0,21.0,8.0,21.0,20.0,HEDAEDGBFGHEDHEDHEBCGAEAAFAABHDHAEHGGGBEFDFFAAEAEHCHBCHACDBFGBGABHBBEBBAHBHHDABDAGDHEFEGBGGDCGEBGCHECHECHGBEDBEDBAAFGADBAGAHGBGDCGEEGEH,False +770,21.0,9.0,20.0,15.0,18.0,14.0,11.0,20.0,AGHAHEGHACBCDEHDEHEECGABBADBFCHFEABCBDEAGEAFEAFECFDCHDBDFADCAGCADCHDEADAAHFABFEDCEGCHFHHCEACGDDGHFGAFGAHHHECAEHDHHABCEFCHFCGCCEF,False +771,4.0,4.0,4.0,6.0,5.0,8.0,8.0,13.0,HGCHGCEBAEDFEDHAHHGEHDDBGDEGBHGFHGFCFFCHADFFBHGAHFHH,True +772,4.0,7.0,15.0,14.0,7.0,5.0,7.0,12.0,FCECCEHCHDDHEFHDDAEHECCGDDBDDBEDBFCGHHHBHHBCABCHBCDEDGCHFDACDFCDGCGGAGC,True +773,15.0,15.0,19.0,12.0,10.0,13.0,9.0,11.0,CDFCAAHAADAADBHCGEAHFBGCBCCEGCDCCDEAGHAGECHFHFFBFBHFBADCADEHBECBABBHFECAGCDDCFFFHDFHDFAEGAEGBCCBCEDGBBCB,False +774,17.0,15.0,18.0,13.0,14.0,14.0,9.0,11.0,BDADABGFCGHCGAGHAGFFDCCBAGFHDFHCFHCBACEACBAGBACBECFEBGABFBFFBHHBDEEDEAHEAGFDEFAFFBDHBECCCCDCEACEHCEAADDCBAEDDEH,False +775,12.0,10.0,12.0,10.0,14.0,18.0,9.0,17.0,FFDFGDFEBAEBHFHFFBFCBFCBACEGDDCHCHDGBEEAEHAEBACCCCCAHEAFFFFFHGBHDAADAHEFHGFHEDCAHHADHGFGCHGFEEHDEHBEGB,False +776,15.0,9.0,14.0,7.0,14.0,8.0,10.0,14.0,FGGCGFEGFEGEBBABCCDCHEHHCHGFDGAEHCEFCEGCAACEACADHABADBFDCEDAABEACDGCHHCHAFAGHEHBEFEAHBAHBEH,False +777,3.0,5.0,7.0,4.0,6.0,7.0,4.0,2.0,ACHDGDFECAEGAFGEBDFBCFCCFHCEECDBGFBEFB,False +778,13.0,16.0,17.0,23.0,18.0,12.0,11.0,15.0,HGEDGCCFHBDHDDECFEHAEBAEBHDCCDFCDCHGHFGHAABCAFCGHCGCEFFEBAEBABBEHBGHBFFDDGDAEDAEABBHBBHEDFEFCDCEDCEDHHCGDDDDDAGFEBBCDDADCAEEG,False +779,0.0,0.0,2.0,3.0,0.0,5.0,2.0,1.0,DCFGFFCDFHDFG,True +780,4.0,14.0,9.0,15.0,13.0,16.0,18.0,13.0,GFHBCDDGGEFBDFGDFEDHCBBGEFEAFEHBDHGFFECCDHGHCGBBGBEDHDDEDEEDBCFHGDHGFHGFHGFGGFGBFGAFHCDCAECAEBBEDBGFBH,False +781,14.0,11.0,9.0,17.0,16.0,19.0,16.0,13.0,AHAEEAEBDCFCAFEACDFGBGHHFBHDBFDCHDHHEHFDGFAFEABDGEEEFHFABFCGFGGBCHBEGBHACEADGACGCFGBFGAFDAGBAGFDHEDEEDEFDEFDGHDGDDF,False +782,17.0,30.0,15.0,20.0,20.0,24.0,22.0,25.0,GBEGHHGHFDDAEABGCBGDDCCHFEBFGBGDBGDBGCAAFGAFDEFGEFEFAEFACBGEBAEBHBBHBCHEHHEAHDDCBCFDADDHDGHFEHBHFBDBDHAFHFFHGGAFCFGCHEEHEDFAGBCHBFGBCGDCGBHBBCFBDBDEBFEFHHCBHGBEBAEBHEFAAFDAG,False +783,18.0,12.0,19.0,16.0,8.0,23.0,23.0,21.0,CAEAGEACHFBBCABCACFADGBFCCFGDFGFBGHEGHCCHABHGBHFBGEAGCCFDAFDCHBGHCGHDFEGEHGEHFDHBDFAHFAHCGGCGDBFAGFHHFHGFDDHGHFDAGBHFHEDDDDCCGCCGADFAFGAFAAF,False +784,26.0,24.0,29.0,15.0,21.0,16.0,22.0,14.0,GEEGAEGABFAFGEBBHCCCGGBHGBFDAADAAGAFGBEBBCCGCAAHAAHDBEEBGEDADDADDAECAECBEBHEFFADBCGECGCCDCGACBACFDCFHFDHGHBBHDBCECEGCBGEBCEFAECCCHFGECGCBACBFFBGFHCECAFBAHBHHAFDAGDECAG,False +785,1.0,0.0,2.0,2.0,2.0,6.0,1.0,1.0,FFFEFFEDFCDCGAH,True +786,20.0,28.0,18.0,25.0,30.0,17.0,20.0,19.0,ECEDCEBGECGBDDAGEBEEHHADHDECGEDEEFEADEAFEAGDBDFCEFBDHBHAGAAGCAGCHHCHDBDFFEECADBAGFCBBEBDEHHEBHFAHFBCEBFEGEHADBDHBDHCDBGDBHDCGBFEADEADHAEAGBBCBACEACFDCBDHBDGEGGEBGEFGBFCBGHFGFFAB,False +787,5.0,3.0,2.0,6.0,9.0,8.0,2.0,4.0,DAEDAECHGCHBEFFEFEDFEDADHEDAEFBFABFHFEG,True +788,5.0,9.0,7.0,1.0,4.0,3.0,1.0,5.0,EBABAACHBEHFACBBFBBEABCDECHGCHBCHFC,True +789,12.0,4.0,13.0,8.0,13.0,16.0,10.0,11.0,ADAAEBAEGDFGHFGEBGADFAFFAFFEFCECEEFEGFEDFCCECHHAFDCFGHEHBBFAGFGHACECGHCDCCHCCHDFHDGAAEH,False +790,6.0,10.0,8.0,9.0,9.0,8.0,9.0,13.0,CEAHHCFHCFHBEACFACDBGDBEHBGGCGGAFDHFCHFEHBABBHDHGDEAHGBEBEGBEDHEDGCDFHDF,False +791,8.0,14.0,12.0,15.0,11.0,8.0,8.0,8.0,EBHEBDCADCAGCABCGDEADEAEECBEDADFEHECHDBHGEGCFDCFBBBHBBDGHDFFDFFGBGHBACBFCHGCDCDDEBDA,False +792,10.0,22.0,18.0,14.0,21.0,20.0,16.0,23.0,DBGEHGFDGFECFHGFEGFBAECAHFHECBABHGFACEBDGBCGHCECAEGBBCDBEGEEGHEAAECGBFHBFHAFHCFBCDHCDHDBHEAEEBHHBCCBFHBCCBHCEDDEDDEFFHHFHFFHEFDAGBFEBHCBHDBFDGGG,False +793,23.0,21.0,27.0,21.0,31.0,27.0,29.0,18.0,AGFCEBGEFGHCGECBEFEGFCBFDBFHCCHCBEDDAGFBDCCDCCDEGHEGHAFHGGHDGDBADBAGEAEAGFFCDACFACFGCFGHFHEFHEDECBEBHFGDEGCEGDBAFCCFACEEBDDHCECDEADFGBBEABHACFAEFAEHAEHEGBFCAHGEFDEAAHACGDBEFBDBBCBCEHGEFGFGGFAGDAGEG,False +794,24.0,20.0,28.0,18.0,24.0,31.0,23.0,26.0,HHAHBAHDAHGAHECHECDEHEEGEFCECEFDEDDFCDFCHBBHBHFCGGEHCAHCDGAGADGCHGHFGEEGAEBABBAEFDGDHFFEGCBFBGHBGABDBCAGCEFEBFCFAAAGAGBABCAEAAFFBFFBEBDDFFCFFHFFECFHDFGCCACFAFHCFECECCFGHFGBAGBCDHHHCCHDCEDAEDGHFG,False +795,31.0,20.0,15.0,24.0,20.0,24.0,18.0,24.0,DDFDGFDGAGEBGEBGFHEDHBDBGHCFHBDCEACAGHADHGHFGBFHCDHDHEEHGGDGGEGDFGAEAEECGFCBFABFADAADAHGCFFHBFBAFDAFDBEBAAHAAHAAHAAFABCABEBEFDHDHEFHEDABHCDDDHBHCCGDHAECAEBEHAFBACEADFBFFEAFCAFC,False +796,6.0,5.0,4.0,8.0,8.0,11.0,14.0,10.0,AGGGDBHDBEDHHCHFAGFGEECFFAFFAEDAEFEGDBGHHFHDFGCGHAGHGGHGEBCEBDFGDF,False +797,13.0,13.0,14.0,16.0,20.0,20.0,14.0,14.0,FDCFDCDGCDGAFFFFHFBDGAEEFDHFGHGBFDAFHGFHGDEDDEADCHGBHGBACAHBECACHEEEEBBDFCEBBEBFEHAGCEBAEFCEFAGFAHFGHFGCFECADCGEADEHDEBDECHB,False +798,16.0,22.0,7.0,24.0,22.0,17.0,26.0,9.0,EFHFGCFGEDGFBGFBHACDACDAGBBGECEBBBDDADDADHGGGBGGBFEEDEFDEAGEAGEAFEDDBDGCDBBBGHGDHCDBDDEGEAFEADEABABBHFBFDBFDFEEFADGADECHBGEGFFGBBHEGGFDGAGAHGEE,False +799,20.0,13.0,23.0,31.0,20.0,22.0,27.0,27.0,ACCDDCDDCHDEGDBGEBHAHGDDDCDAHDGFAGHAEBFECFBCDECBAHEACGAEGFEFFGHADDGDDACEACECCFFFDFGHBHDBHDCFGCGACFCDHCBHEFDBDGCDCDEFDEFAGHAFHAHHCEGGDBGFEGHEHHAGFEBFGAHCBHCAHDADFGDEHDHHAGHFEHGEGGDGGBF,False +800,7.0,7.0,4.0,8.0,5.0,4.0,9.0,2.0,BFADCAGBDGDDGDDAEDEFBEABEBECGDGHAGHAGFGBABCGFC,True +801,27.0,24.0,11.0,26.0,22.0,20.0,24.0,21.0,FDEFHBBHDBDFECFEGGEGBBBFGBAGBGFBAEHFGHCAACHBBHBDHEABEFBAFGEDECDEGFGGHDGAGGAHCBHEEEFHEDHADFDHGEGFAAACDFDDFBDCEAHEBHEAAEFBDABAABHABDAGDADFAHFGHFGHCGDFGEBCDBDAGDBGHAHDADAGECDACDE,False +802,24.0,16.0,21.0,28.0,24.0,24.0,17.0,24.0,EHGDHECEADBDCGFCGDCFDEFDHFEEBHECAGBDHDDAAAAGEHGCCGBEGCEGEFDEBDAAGEFCAFABFBEAGEAFECCDDCDDHDHFDEFGAACEEEHGHHADHFHADHFCCAHGACGAHECBEBBDFBCFBHADDAGDCDFAHFAHFABFEBFECFHDBHDBHDGHFHFCDF,False +803,20.0,21.0,21.0,27.0,21.0,19.0,21.0,15.0,CHCDAADHHDHFEEFGGDBGABGCBCFAHFHFFGBDEBFEAFEHBEFDEFDAHCGGCDFCGCGECGEAGDBCEBGAADFADFCDAEDBDAHAEHAEGGEGAHGADFCHCCHBDBBGEADDADDBFDBCBBCBEGDDCEEAGDCGDFDEGBEBBFBAHCEHCFCFD,False +804,1.0,2.0,0.0,1.0,3.0,0.0,1.0,2.0,HBEHBEDEAG,True +805,17.0,17.0,12.0,11.0,12.0,11.0,11.0,14.0,CACCACHGBBBBABBDBGEGCAGFBEFAEBAECGBHHHHHHHFDEFGCGGBBBAFFAFFACAACGACDDEFEEDEADHAHCBHDGHABHEBGCFAHBEDDDFEDA,False +806,8.0,5.0,13.0,9.0,8.0,4.0,5.0,7.0,AABDACCACDACDBCBEEHEHCDHEDGEDADGFFCCBCGBEHCHHDGHECCFDCFAEGA,False +807,2.0,3.0,6.0,1.0,2.0,2.0,5.0,2.0,CCGFCGCAGEGGHBBHBDCFECA,True +808,8.0,11.0,13.0,11.0,20.0,5.0,10.0,7.0,EDGEBEBGEBGECCCADEEEBCEGEDBECBCCDAEDHECHAGHGCDDFDBFEBFEBEEGEFHAAGABGDFHDCHACBEDGECAHC,False +809,19.0,18.0,17.0,18.0,21.0,24.0,23.0,21.0,GGGGAGFDDEHDEHAEFAGHHHHCBECAGCEGEBGABGFBDCHDBHEHHGHFAHGCBGFDCFDCFBEFHHDAGFFGCEEDHGDCADAAHEEDEBHHFAFFABFACCBCABHGCGDBEDFEGFCGFBFBBCBBDFEGFECFAHDAEDAEAEEDCBGGFFFHA,False +810,20.0,16.0,11.0,12.0,13.0,19.0,22.0,18.0,AGFCHFDDFBEHGEHGBHGDCGFCHEGAGADFAGGAHAFBABBFBBGGAABAAEADEBDGCHHEBGCAEAHEGCAGFHDFHFEHAGDGFDBFBBFADCGDBGHFGHCCCGCDGBBAAFFAFHHFEHFEHEE,False +811,17.0,22.0,15.0,31.0,25.0,25.0,18.0,24.0,HAFEGGECCHDGGGHDGCDGDEAAEHGEFGBGGHGBEFEEBCHAEHCFHDFHDFGDGDBGDAFBFFBFHEECEDBEDHDBEDBFDBFABDEFCHAEFEDHCDAFDCBDABDABFCBCDHEHFCAFCDBEDACDEHFFHFFEEEBDEHEBHBHHAHGBHDHGDBCABDADDFDAFGAF,False +812,13.0,7.0,5.0,13.0,10.0,18.0,4.0,11.0,FGEADHABHAEHFCHFAAEEAFEAFDAFABEGGHFFBBDBHCAHADHBFADCCHEDFGDFDDBDFEDFEHFDAFDFFEHFC,True +813,30.0,25.0,17.0,27.0,18.0,16.0,23.0,20.0,DGAGBDGFDGFAAACAGCEFHDAHDBHCBACFACFGHFEFBHHBDHBAEDAHCEFDGCAADABGABDEGDGCAGCEGBABEABDFGDFADFABGBHGAFGDDGHDAHDCDDEDGECHEHGFBBFHBEBBCBDGGHHCEHBEGBCGADAADBHEFDEFHEAADCCHEDECAAABABB,False +814,24.0,14.0,14.0,18.0,16.0,18.0,16.0,21.0,ACBABDDGDGCCHAEHAEFDEFGHFGHFGDCGEBFDBGGBFACACFAGEHGBAFBAEAAEFHEGHCAEAADDHCABFHHEDHDHACHAGHACHGCHCHDDHABAAFADDBBABFHCFGCFEDDEDDHFEHFEGFBGEAFEB,False +815,13.0,9.0,13.0,16.0,13.0,6.0,10.0,11.0,EBHEDEGACDDCDGCDACHFCECCHGBHGBHCBEDAEDHFAFEAHEADAAEADDFFEGBDGEHHABGGHGCCADCDDCDHCABEFBEDBAG,False +816,3.0,7.0,5.0,5.0,0.0,0.0,5.0,2.0,DDCDBADBHGBGBBGCCCACBAGBDGH,True +817,5.0,5.0,2.0,2.0,3.0,8.0,12.0,6.0,HCHGCGFHGAEAFGHFGHFGFEADEHDFBGGGGGGFBFABABB,True +818,1.0,11.0,9.0,4.0,7.0,7.0,8.0,7.0,GABGHBHDBHCBECBFGHFGBCBBFEBECCEFCDFCGHCFCDHEFGEGBEBHDG,False +819,2.0,2.0,5.0,5.0,0.0,2.0,1.0,5.0,CDACFHHFAHDBHCCDCHDBGD,True +820,11.0,24.0,12.0,20.0,8.0,10.0,7.0,16.0,DDBDDECFEFFEBFBBABHAFHGGCCADEHHABDDDDCGHFABFABFHDCBDBGDBCDBFEHHCBHADHADBADCHDCBDHBEHBHABCGBEGBCDCGHBDAEFBBBH,False +821,9.0,5.0,8.0,7.0,7.0,2.0,8.0,6.0,DCDGGAGGCHGCHBBEEAGEGEFCEDADAADAAFCABCEHCBHBEHCAHDDG,False +822,4.0,6.0,4.0,6.0,8.0,10.0,6.0,8.0,DGEHGBHAFDDFEAHBFCBFCDFADFCDHGEHGBFCBHEHGEBEEHEFGFFA,False +823,11.0,21.0,15.0,29.0,14.0,28.0,25.0,13.0,GCBACBGFGGFADDGDDHCCBEGFEGBDBBDFFEFECFBCFBFFGFFGDDHHDFHEFDEDDAFAGFDEBEBBDDHDEHGCHFCGCAGCFGDGGHCFBBFBDCGGEGDEBAHFDEADEADFCDGABFDDFGDCGBFADABDGBHGHGFHFDHFEBCB,False +824,9.0,9.0,18.0,17.0,22.0,11.0,12.0,16.0,HDHHDBHCFHEEAEBDEDAEDBEDBHHAFFDDFCHGCHECDDCEEEFEDGADGCDCCHCAHCAHCEHGECGEGGHFDCCEECACBGCEGFGDEBAFFAGCGBEEEFDEFDBHBH,False +825,13.0,14.0,23.0,11.0,13.0,29.0,17.0,16.0,CFBCFDDFBDFBHFHGFAGEAFFBHFCCFCFACFACFDCAEBHFGGBAGDEEHBGFAGFHEDHGFEBFHHFGFDCFCBHEEGGCFGEFBCADHHDBFDBHDHACHCCGCEGAGGFFACCAECFHCGBCEFCEFCAB,False +826,5.0,8.0,5.0,6.0,10.0,4.0,3.0,7.0,DDEDAGAAGAHCDDBBHBGEEFHECEFHEBHEFHECEECBBCHBDFBA,False +827,20.0,17.0,26.0,28.0,18.0,27.0,26.0,26.0,ECFEGFEHFHHFABFABFEHABHAGDBHDBHDBGDGCDGHABHAFCEHDBHGCDCEFEEADECDAFBGFEGFBAAGDGDDEEDHDABDABFAGFDGDDADCBDAHGHHGHHFFFFFGCDEDGGCBCFEDGCCGCCDCEFFHHAHDBHAFCCFDGBCCHACHDEGGEGCCDCCHCBGFAAFEGFGCHHF,False +828,10.0,8.0,14.0,9.0,25.0,17.0,21.0,17.0,ECHGCHBCGEFDEFDECDEGBECBHBHHFFGGFGGHDGHACCAHHBDCFGAFGAGEEHEAHECEEHEEBEEGDECFEBFECFHFFGGGAEGHEGFCFBAGAHEEGDAAHFHCFGEEDFGDC,False +829,3.0,3.0,1.0,2.0,3.0,6.0,4.0,4.0,DHEHHDFHGGBAGAFEACEGFBFFBF,False +830,13.0,14.0,5.0,14.0,12.0,16.0,14.0,22.0,GDABFFCGFEHEGFFBHCBHEDHFGFBBFEDEHDHHGFHAEHAEHCEHABHADGEDGAFGHBCHAGHADHEFHFFGFGBAABAABDGBDCHDGBEAFHHDDBDHBFHDEG,False +831,30.0,21.0,25.0,25.0,16.0,20.0,17.0,32.0,ABDAGCAGBEEEEFEEFGBFGACGBHGBHCAACAACGCHGHADHACEECHDHACHFEGEAGDAHDAHDGBBHBFHGCHEHHAFGFFDDBGHHDHDEHABBACBHCADFDDHBDHBDCDCBDAHFFHDDBFHAGCDBFFEECCECCGHAHCAHBEHDACDAHDFCDAHDBBFFBAFCFFCAHAAGAC,False +832,25.0,27.0,23.0,20.0,26.0,20.0,20.0,27.0,AADBAGBCFACEEGDFBFFBFHCGDBHEFHCFBFBEEBHCCHCHBEBGABDAHDFHDHHFEHGECGFCBHDFHABBDDBDFHDGCGCCGCDGCHBHEEDEHDHBDEEHEGHBBHFBHFBGCEGEDAEGAECCEAAEACBAHDEBAEBFGACGAFAHDABAHDGCDEAHEAFECFGAACBACHAGBFGE,False +833,25.0,13.0,14.0,24.0,17.0,12.0,19.0,18.0,AEBDEBFCFGAEEHEAHBAHDCFDHFBFAGFAGAEGCCDCAAGAHEHHGAHEACFDEGDCFBAGGABGADGCDGFEBFEAAAGAAECBGDFCDBEDHEBCDDHDDHDGHDHHGCHGEBGHCAHDEEDCDDBADAAGABHDDF,False +834,15.0,10.0,18.0,19.0,15.0,14.0,14.0,17.0,GFDGHHGDHFHCFDBEBGADGACECCHHCHFAHCEHCHHDEHAEBADDGDBGDEEDECDFCAFEEFEDDHDCGAHBAGBDEADGHEFDFABCEBFGBCABCFGCFACGDHDEHACACCAFGF,False +835,20.0,10.0,18.0,14.0,16.0,28.0,23.0,12.0,CBFFGFCHEDBFHGFEGFEGFEDCEDAEHAGGGGFGGCCCDGCFGCFHAFBAFBDFCFFHAAGCEGAEGHEGDFAFFCDFADECHEAHGFGEHGEBDDBABFABABECHCFGCDDFFGFAACAAEDHGGHECDBAFCAFAF,False +836,30.0,20.0,19.0,16.0,19.0,13.0,25.0,21.0,GEHGEGBFGFCGFAGHHGFGGFDHAAHECBAGGAGHCGBCABFHBECAAHAFCEBCEACEADDADCGHBDHGFEDBCAEGAHGHCGHCGEBBHGDHEDHDFBEBBFADEAHEACBAEGFDCAABAABAABGAEACHBHDGADHAEBACHDGDAGCEDCEFCBF,False +837,11.0,6.0,11.0,21.0,12.0,11.0,14.0,20.0,CCGFFHDFDCHECHGCEGCGGDDGABGAEHDEHGGHGHDDHDABDHBHFFGEFHDAEDFEDFGFAHHHCFHAEDGEHCHFDADDGDBADAHDAHDCDCCBEHBEAE,False +838,2.0,11.0,5.0,5.0,5.0,11.0,2.0,7.0,HHAFDBFCBFHBFCBHCFEBHEBCFBFEBEHBDDDEDCABBFFGFFGH,True +839,10.0,18.0,12.0,15.0,22.0,22.0,14.0,20.0,GHGGHDGHEHCFHBHHGHGFDFFBHGBDFBCFBFEBAHAACAEBAFCEFHEABGAHCBCCADAEHFDHFEFFEHFEHCECGHFEBFGCFDBBDBDDCEDEEDEEFBFFGDBBEBGEAEHFDCEGEEDHGDHBF,False +840,6.0,5.0,3.0,4.0,8.0,4.0,5.0,6.0,HFAHFAGABEEHFEBBEABCGBGAFGAECDEDHEHHEDGDC,False +841,22.0,25.0,12.0,20.0,30.0,18.0,24.0,19.0,CFDABGGBGGDGGBGDBGDFEHGEHAEDEEDEEAEGABBABHABFEGAAAAFAAGHFEEEAHFBBFBDHEHAGHADHFDHEDHEDCFAHFEHGEHEEHCBBDBBGBGEBCEBFEHDCFAGFECABGDHEFFEBEACCHEGEGCAFDACECDGDBHEFCGFGGBBBDBDDA,False +842,26.0,32.0,18.0,28.0,33.0,16.0,26.0,21.0,BDFEACGAHGEHBEFBDDCDDEBGFBAHCGBBGCEDEHBAFGGFBDFDABCCBFCBHEBEAFGAEGFEGEDGAABBHBDCAAEAEEBEBGDGGDGHDHHCACBEGGDHADHGEFEBDEBDHBDHBEHBHDDCDFCDCGAGGEGGEGFECAEABEAHDAHCFFCDHAAHAACAABFEEEBDEBDGBDBCEEHDBGEBEAHF,False +843,17.0,15.0,21.0,18.0,10.0,19.0,19.0,11.0,GCGCCGCDBAAFCFFCGCCFCBGCBHBGADGFEEEBEDCFDCFBEFAEGDDDDDAGACDEFDBFGCFGEFDDHCGGGGGAFACHACHACGADGHHCHBFAAFDFFDABBEBFHBHEBHCAHBADGABFDC,False +844,28.0,20.0,25.0,32.0,29.0,10.0,34.0,16.0,GCBGCEAHBHHGHCGADBHDGAFGCFEEFDEAABAAFACGACHAGEEEEEBDBDDGEAEBGCFGAFGCGACGAGFEDAGDAGDBGDFEBECDGBDHBDBBDAEHADAAHGDCGDEBAHBEDCGBEGHEDHCCEDDEDCEGCDHDACAABADGEEFCEFGGAHGCCGCBECECBDHDCADAGDGGDGGDECHEBD,False +845,9.0,18.0,18.0,15.0,16.0,16.0,18.0,30.0,FHHFCHBCEBFEBFBHCGHEGFEDEHABHBHCEHCGGEGGCGGDGHDFHBFHAGACEDBBBBBFHEDHAHHBHEGHEHFDHEBHDDHCDCDHCACADBHDAAEGHFCCECCFHHBHGDHCDHFDGFBGFGGECAFBFCEG,False +846,25.0,21.0,20.0,25.0,14.0,20.0,19.0,27.0,DHHAHHGHBEBFFBHACHBCHFEAFHAGEAGEDFFDHACGDCGEBDDBGEAFAAGAAHAAFCFDCAEFBEGHGDCFAEDABDABHGBHGFHFDGDDGDDHFBABCADDACHBCHCGECACDBCGBCFHEHCCBBHHHFHFBHECEDHDAHDFDDFBBFDBEGACGACGADG,False +847,19.0,22.0,26.0,32.0,24.0,20.0,17.0,30.0,FFFFFBEBBCDDHBEHDHHFHCDHCDBCDAFBHDGHDECDEDGEDCBFEFEHAHHAEDBDGHDCHECDEFHHADHCHBCHCDDCHBBHBEECCDFEDFDBGDBDFBEBAEFAHAGFECCACDHCEHCGGCGGCAGABCAGAGCDBADGEDFEGAEGAEHACHCBHABDBEDEDDHADGGFBFFHEFHCAH,False +848,9.0,6.0,11.0,10.0,14.0,15.0,7.0,8.0,EBECBHGDFECFDGFDHFDCEAAGDEFDEFDFFHCAHGBDDHDHFEGEGBAFCEFCAFCACCACBAFHFEHEEFEGAEBC,False +849,4.0,12.0,3.0,4.0,4.0,6.0,9.0,4.0,BADBFBBDBCDAGGEGGAHFBHFECBBGGCGGBBGBDFFHFEHAEB,True +850,11.0,16.0,15.0,13.0,9.0,18.0,8.0,14.0,AHEFHEDHAHCBEFAEABEBBDHGAGCECCECCEDGADFFBFFBFFACACDFCDECHHFDFFHFFGFBAHBCDBGDBGHHGHFBDBHDBCCFHDACABDGBCBF,False +851,14.0,6.0,9.0,8.0,8.0,11.0,8.0,4.0,CADAAFAFGGBDGBECHEGAEGCEGHEAFCGCCAFCAFDBEHBAAAFAFFECEDADGACFBDFHDFBD,False +852,13.0,17.0,14.0,11.0,14.0,23.0,28.0,19.0,AHFBHFEDBHCBHGDHDDBEFGAFBEDCEDCGGCAGCHGCHGCDCEEGFBBFHCGHAGDCFEGABFCBECBAFBAFHHGHEBCFAEGGEGAFBFGGGDGBDBFAEEBGAGHAFHCFHFFAGFHGFHFFHGGBGGHDGFE,False +853,17.0,14.0,15.0,18.0,12.0,25.0,14.0,18.0,FEEDCEDAEDABFABGHCGEGBAFBAFADFDDFBDFGDGEEAEHDGHCFHCHGBHFHFACAEBGHHGHAGAAFFDCCDHCGGCFDCFHCGECADCFDBFEBFBDGHDCHCHDAFFFHFBBEAFADFHBFHFAB,False +854,4.0,8.0,7.0,9.0,7.0,13.0,4.0,5.0,HAHBAEBCEFDHFGBFDDFDDFCGFBBCBFCFFCAFEDFBCGCDGEHEEDFDHFEBA,False +855,8.0,9.0,7.0,8.0,14.0,11.0,8.0,11.0,FCGGHEGHCAHEGDGCDHEBHEGEEFAEFCEAAFAHDEHFEHBGFBFFBFEAHEADCBBCBBCEGDDHFDFBHEAD,False +856,15.0,19.0,19.0,21.0,20.0,23.0,9.0,21.0,EHCABCEDCEDCHDBADEFFEAHGADFHBFEBFEHFEGCHGBBFBDFDCFHCFCGHCDHEHADFFEFHCGHCBABEEBEFBCDBCEHDACDBBDCBACBAEBDDCADFAEFEEHDGHDEEFBFFDHGHFGAFAHFCGFHBHDADAHC,False +857,8.0,14.0,12.0,26.0,12.0,12.0,24.0,18.0,DDGDGFHGDEEDEHGEDDCHGCAGDGBBHHAHDBHDBGACHCCHFCHGGHDGHDBFABCHGHGFDCEAGEADEGDADEGHBCFBGFGDCGBFDFFDCBDCGDGBEGBFGEHHEFHDFGDAEDBDDB,False +858,3.0,12.0,7.0,10.0,7.0,11.0,5.0,6.0,EHBFDFFCEGCEBFAFCCFECFHDGCEHAEFDBFDBAHBGHBGEBCDFDDFBDBDGBHBBD,False +859,15.0,8.0,5.0,5.0,11.0,6.0,8.0,9.0,AFHEGGEGBEDBACAADADGGHGFEGCEHCDAFECBBABHHEHAECFHBAHGABDEBAEFAEFAHAA,False +860,24.0,23.0,16.0,29.0,25.0,13.0,28.0,31.0,ABDBGHHDBEAACAHBDDDDHHGAHBDHDAHCGHCAEGFECFECGHAGBBDBDDBDGBDBAEBACDAHDBGDBCEBGEDDEBDBBABGGGGGEHAEGGGDFHDAHAHFAFDCHDCHEFBEAGECHFCHGGEGGAGFDHADEGHAFHBGHEFBCAGCAEBHEDHEDEEDFEGFHCEHDHHFCHEAGECHA,False +861,19.0,16.0,16.0,18.0,22.0,19.0,15.0,18.0,HBDHADGAFFFCFDCFDHFAEEDEEABBABHHEAEDAHDEHCGFEECHECEFGHFDHFEEGCBDFDGHDGHDCBDCAECAHBACGEFBFFAFBAFBEDHDAHBBDGEGCEGBGDFGAFGAHCHGFECAEGABAHBACBECECD,False +862,23.0,28.0,34.0,23.0,21.0,19.0,19.0,23.0,AADEFDECBCFBFEGCHHCBCAHCAEDAEDFGBAHBGBBGEDGEFBAFBABEABFAHFAHADGBHAAHAAHCFCAECBEHBACDDCDCHDHHDAHDAHCFBCDHCBBGDEDEHFBCCCCCDGEDEEBCBHCDEBEHBCGCDECGCCGBCGBCFAGGACBHBFCAGCFBDHBFHFECFGHEGCEFDDFGDG,False +863,11.0,5.0,11.0,10.0,13.0,17.0,9.0,9.0,HGFAGHEGFFAEFGCHCCHCFACEAFEAFBFFBEEDDDGGDFEBHDFEDFEFCEHCDAAFBAFHCFECHEDDABDAGCCGAHGEF,False +864,8.0,4.0,8.0,5.0,6.0,11.0,2.0,13.0,CGDDADAFHFEHACHFFHAFHAGABEFBHHCHFCFBEHCEHDEFDCFEFHCAHCAHB,True +865,6.0,7.0,13.0,8.0,5.0,5.0,10.0,8.0,EBBEADDABHGBFBHDAHDFCCCCCGDCGACEFCEGCGGCDHHBGHCGCGBFDDFEAHCAHG,False +866,13.0,18.0,13.0,24.0,13.0,21.0,16.0,22.0,CECHEHGAHDBHAACGDDGDDGBGFBACBAFGCFGEBHHBHBBFBBFGDFEBHDBAEEAGEHFEDGEDFFHFADDADFHCHEADCFDBEDCDDFFBFFHFGEFGHCDFBHADHFDHFHCGCAGDACEBDHBDGDHGCHBH,False +867,3.0,4.0,1.0,1.0,0.0,0.0,2.0,1.0,BGHBGBAABACD,True +868,12.0,15.0,8.0,11.0,24.0,11.0,16.0,16.0,GBGAFGAHEABDAHEEHEGHFBEGHCHHCBDFECAADDGHFHFGEAGEBCDGEDBEFEEFGDGGAHGDHEEHBEHGEAGECGEAHECHBBEFBHBBDBBDCBFEFEEFECAAD,False +869,14.0,6.0,19.0,11.0,20.0,15.0,11.0,18.0,AFHAEHAEHGFHACHADFFGGFEGFEGDEDBAFBDECHHGHCCDBCFECHCHFBEDEECHACDGFDCHCEHFHCFACEACEACBCGBGEADECEEGFEHFACEDHEDHAGHFCA,False +870,7.0,10.0,10.0,16.0,6.0,4.0,11.0,16.0,HCBDCBHCBACDCCDHFHAGHCCDECGEDGDAFHGHGBDDFADHGDHBDHBGHFHEAABGBDHEDHEHHEGDDGADGCBB,False +871,6.0,1.0,1.0,3.0,2.0,4.0,9.0,6.0,AHCGEDGAHEAHAFGAGGBHGAHGFGDFGFHD,True +872,3.0,5.0,3.0,3.0,6.0,1.0,1.0,2.0,BBBDCBEGHEFHDBADAECAECEE,True +873,2.0,1.0,1.0,2.0,5.0,1.0,2.0,3.0,HEGAEHAEBCFDEHDEG,True +874,7.0,21.0,14.0,14.0,9.0,12.0,13.0,10.0,FDBFBBDBADBHBAGDHHCGEFDEBGEGGFGBCGEADAGGADHBDFCDECGBCEDFHFGHFEAFGHEDCEDCBFCBCCBHBBHBBDCBFGBCBHDBCAFC,False +875,6.0,6.0,10.0,12.0,5.0,8.0,13.0,6.0,GCGGCGGHBFDDADDBDFBDGCFGAEGAFBBCBHHFDHADHAGCDGEDEFGGCECCHDCEACGDFF,False +876,19.0,14.0,14.0,17.0,5.0,8.0,26.0,9.0,ADBACAGCHGCFGHDADABGEDABDABAFGCFDCADGGGGGGGGGBGGBACCHHAAGAADAGDAGDCGDBFFBCFBEBCEBGBBHEGDDCCCBHHAFGDGADGDDAFCGHHE,True +877,11.0,23.0,26.0,15.0,25.0,13.0,27.0,20.0,DHHEHGFGGCEHCGDGEDHCDHBFEDFEAFHBDGFCBHCEECEECBHCACGACACHGBHGBGGECGBDHCFEEEHCGHCGHCEBEFBGABCDDEGGEGGEGFEDBEBBGBCGBHABGEDCABCFECAHHBBCBDCAGBDGBAGCAHFHEBCEGCDFFDEF,False +878,10.0,21.0,12.0,20.0,16.0,27.0,18.0,16.0,EGCEHFAFAEBBGACGEEDEBDEFDBBDCBDEDFFAFGHBDFBHBGHBEBEGDDGDGBHGBHBFFGDFCFGCFAEGHEDEEDEAFFFFFFCHGGDGAFGAFHDBHEBCAGHBFDFFBHFCHFCHCCDCFDHBDGBDBHFA,False +879,13.0,7.0,15.0,3.0,11.0,11.0,9.0,9.0,CHBCFBFGEFEHCCAFAAFCEECBBHEEGEFBEABAADGAGGFGFCGACEHCHCFECADCACCACFAHFHDGHGAHEB,False +880,18.0,17.0,11.0,7.0,12.0,11.0,12.0,19.0,GACGHHGCCDAEAEBAFGHFGHEHABHBDHGCHGCHBABEEBECDDBABBHFHGCBGCBFAAGDAGHHHCAFCABAABAABHAFDAFBGDCHFEBEEHEFHEFBFHE,False +881,15.0,14.0,12.0,18.0,16.0,16.0,10.0,24.0,EFDEFDHBEHAEFFBHEBGEFABHGEHDFHAFEBCDGDAFDAHAACDACDGCEHDBBBBHDHEAEFAHGDFDABHABHAEHFEHFHHFHBFHAFHAEDCGBGGDDHDEHCBCCHCEFDGGHCDCC,False +882,1.0,3.0,4.0,5.0,7.0,5.0,2.0,5.0,HDHBCGDFACFECFEFBDFDGHEEHEBHEDCE,True +883,10.0,19.0,13.0,15.0,16.0,14.0,11.0,10.0,FDEBDAHCBEFHFHGGHGEBGCHCEECDACEFBAFHCBCEBAGBFGCEGBEHDDHBDHCDAFDEBDFBDEADBADBAECAGDABCGDCFBGFBDFBEFBFGBEHEECF,False +884,4.0,20.0,14.0,12.0,17.0,18.0,12.0,16.0,DHCFHCBHGFHFEDFEDBCDBFHHGCDFADCGHFBDCBDHAGEFBEHBEDCEGCABFHBHCCCCBHCGGFGFFBFBBEGFEBBBCGEGHHHFDAFDEFBEFHEGDEBEEBEEB,False +885,4.0,5.0,7.0,5.0,3.0,5.0,11.0,4.0,GBBEAFCABHGBGEFGDDCBDCFGCAGCDGCGHEGHFCHFGAGD,False +886,4.0,2.0,5.0,6.0,4.0,7.0,8.0,6.0,DEGFEGHBGCGHBGHDFAFFAFDADGCHECDECFFCHADHGG,False +887,7.0,10.0,2.0,12.0,7.0,8.0,10.0,7.0,HDGHAEDCDDBGDBAEBGCBDAEGFGFBGFBDDBFHBEHADFGDFHHFHEDGADGAFEAGEBB,False +888,22.0,21.0,26.0,15.0,24.0,25.0,19.0,23.0,HFHEFEAADAGDBCEBGEBEFHEGHAGEDGADFEBFCBFBBFCEHADFEHGHHFDFCHFCHDBGDHAAHFCFAEBAEGCEGCFFAHHGHHFHHCHCBABGDHHDFABGCFACFECDEAGEAGFBCFGCEGCBBBEBAGHGGCBAFACFDCDDCFCAHCACCBEEBEEBEADCCEF,False +889,14.0,18.0,14.0,7.0,16.0,10.0,10.0,16.0,FHAHHEDDECCCHBCBBFBFCBACDAGHAGHBFHBCHBEGEEGBBGBBGEAEAHHBEFFEAFEDHECEEGABGBDGCABEABAFCHCAACGBHHAHCDHFECFED,False +890,18.0,20.0,25.0,21.0,23.0,27.0,22.0,23.0,ECFEGEBFABFABCDBFHBHABHBDHGFGBFGECGCFHADHDEACCBHFEGFACHECHFBACCCBEBBDFDAEAABDAECCCFCFFCFFCEGCHBEGDEDFBDEGHFCHFCFDCFEGGEGDDGHDHHCGHFDFBDHGHHAAHAEHFGAFGAEADEFCEFBEGBGGHDAEDCEHCDGBDG,False +891,21.0,17.0,16.0,20.0,21.0,17.0,22.0,30.0,GEDGFABBHBBHFAGAEEAEAAECAEHHHBDDCABHGGHGCBAAFABFBFCGEBFEGEHHEHHDDHFGEEHDGHCAHFADBADCCGACHDGHAGHAFHAFBECBEDHGCHGAHGBDCEDCDBFDEGHGADGDHGFHCDGDFHBHHBHAECFECFEGFHFEDCED,False +892,2.0,4.0,1.0,8.0,1.0,2.0,5.0,5.0,HHHHBDABDGBDFFDCAHGGGBDGDDED,True +893,15.0,5.0,9.0,8.0,9.0,2.0,15.0,5.0,GGEGEEDAFGECACCAGFGEEDECDBAEGADGABAACCACCAHGAHADHGDGGHGBACBHBDEGAAGD,True +894,15.0,20.0,23.0,20.0,17.0,18.0,26.0,16.0,FGDFCFCCGBFEBEEDACGECGHCFFEDBBCHBFHBDAFHBGCFCCFAGHDGDGGBFEEGCEGAFGAEAFEDFEDBBDHBHGGGGCFDCEHBEHGCAAAAAGHCHHCHBGDDCDBGBBCABCABADBADBFDGGCCEDEEDGCGGDDGHCFHEFH,False +895,17.0,14.0,14.0,9.0,18.0,14.0,9.0,18.0,BGCDCCFADADBGDGCAEEAGEBEFBHHAEFFEHFEBEBCGCEBCEDAGGAHEABEABDAFDHBHHAAHBAHAHBAHCEHCAHFHBEHFCFFCEFCEHCHHCAEDFEDBGFGF,False +896,10.0,10.0,7.0,13.0,14.0,14.0,10.0,8.0,HCBCDHHGEAFHFCDGHEBDEAFBCFEDFADEADEADABBHCAEDGDDGFDAFHHFDGFGGFABFBCDBCEAGBBGEFGEFEEFEE,False +897,1.0,6.0,2.0,6.0,4.0,12.0,5.0,5.0,FBDGCGGDFEBFEFFEGFBGFHFFDFHBAHFEDFCHBBHDD,True +898,8.0,2.0,6.0,2.0,1.0,5.0,2.0,3.0,CFFCHDCFEHHAADAACCABAACGAFGBF,True +899,13.0,11.0,11.0,13.0,12.0,11.0,12.0,9.0,FCCGCABEBEEFCBGCDGCAECEEHAEGDCFFHDBCABDABEAFCBHABHADHGDFGDFBDFEDGHBGDGDAGAFECHEGDEGHFAHDABAF,False +900,11.0,8.0,16.0,15.0,15.0,12.0,12.0,10.0,HFDECDECFHCHGDEDEEBGHDAHDABCCDDFGDCGBCACCDGGFCGFEHEAGEAGEAFCCHCCAFEAFADEADHGDBFBBFBBFGCEAHFCDEEDHEG,False +901,6.0,5.0,13.0,12.0,14.0,4.0,0.0,2.0,DEEDEFCACAAEHEECDECAHCBDDECCBCFFDBFBCDECEECEDCADEDDEDACB,True +902,5.0,2.0,3.0,0.0,2.0,4.0,3.0,0.0,CFECFBAGAACAAGFFGBE,True +903,1.0,3.0,5.0,2.0,2.0,3.0,3.0,5.0,HEAGEFBCDBCBCFHCFHCDHGHG,False +904,8.0,10.0,8.0,10.0,10.0,10.0,8.0,8.0,HAEHAEDAEDGHFGFFAFFBFFGDABDECDEGGEGHBHBBCCFEDGECBCCBACHDCAFBDDEEDAHGBHBF,False +905,19.0,35.0,22.0,16.0,17.0,18.0,22.0,17.0,BEDEDGGBEBBDBGHBCBBCBHCAEAHBAGBCBHDBHDCHGCBGDAGDCCAGDGCDFCBFCBDBBDHAAEAGEGGEGBAFBHFGFGBFHEACECCGHCFFEFBCFBAFAABBBBBHDBEFBHFAGBEFCDGCFCDEEHBBFBDCGDEGFHGACAACAHHFGHEABE,False +906,6.0,6.0,11.0,1.0,5.0,2.0,8.0,3.0,GGECBACGCCGHCBFEGGAACAACDACBBCHCEFCEHBEGBG,True +907,10.0,11.0,15.0,22.0,12.0,15.0,10.0,11.0,CBDCFAHHHHCHDBDDBEDHCAECDFFDACDGBDABCFBCFBGDCFFCFEEHGGHGADGDFAFACGDCADFBCFGDFEDFDDADGAHEBHFCHDCDEEBEEDEGBE,False +908,4.0,0.0,2.0,5.0,3.0,0.0,2.0,3.0,GHACDADAEDAEDEGDHHC,True +909,1.0,4.0,0.0,5.0,2.0,3.0,1.0,1.0,FDHBDABFEBDDBDEGF,True +910,9.0,19.0,26.0,20.0,13.0,12.0,16.0,22.0,BHDCHGCHBCHDCBGCAEDFEBFBHDBHDGHEGECGCFDCHHGHHBHGFGCCBCCDCHAADFFDFFHEDCFBCEHCEHCDDFAGECGDBDBGFGEECBHCBACBACHCDEFDAHBCHCEGBGGCDDHDEHBAGBADB,False +911,5.0,1.0,2.0,3.0,2.0,3.0,0.0,2.0,HAHAADAFBAFEFCEDCD,True +912,26.0,20.0,25.0,15.0,11.0,21.0,19.0,28.0,BGFDDHABFAGCACFBCDBGDCCAAAHAAHFCHCEGGFFHHFBCABCGGGGBHEAHCAHBAHAHHACHFDHDAHABHCBFEBFADFGDCGFFHCGBCFBDFEDCHBBHBCGECGEHGFHAEHACHADAABHFDECEGBAGDHFDHCCFGAEGAECABFFBHCCHD,False +913,7.0,7.0,5.0,3.0,0.0,6.0,1.0,6.0,CDFCAFHACADCBBHBFHBFHFDGCABBABFHHAA,True +914,20.0,24.0,25.0,24.0,19.0,23.0,23.0,19.0,BDHFDGCHCAHFAHFGGCHBCHDFEDAEHCBFEBCGHCGFEACCAHDFGDFDBFBEFBEBGDBGDBCDECBFHEEEBCGBDDFDECHEHBFCAFADGADAHFCFFGFAGFEGEHGADDHDCHDBDDGEDBHABGGBEGBAHBHBDCFDCACCGEAACCACGAEGBEFBAFCCFGBAG,False +915,6.0,10.0,1.0,9.0,16.0,12.0,5.0,11.0,BFGFHGADDEEEEBEEHEHHEHFEBEGHFDHFBHFBDFDFFEBGDHCEBEEBEAGDADHAFAAFHBBEDF,True +916,19.0,25.0,17.0,15.0,26.0,25.0,27.0,16.0,EBBHBCGEEAEBCECGECHHCGDCECGECDBCDBAGCHGBFDBDBCEBFAAGAAHBGDFGAEGAEHEEHECGFFAFBEEAEEABEHBGHBFHDGCCFEFFCFFGFDHBAHAGFDGFDGHGGEDGEBGHGFFECBAFBHGEFBFGDFHDAADGGBAGBFCBFDEFAFBABE,False +917,1.0,1.0,0.0,2.0,5.0,1.0,1.0,0.0,DABDEEEEGFE,True +918,3.0,4.0,4.0,5.0,6.0,2.0,1.0,2.0,FCHDCBDCDEADEBDEBFBGACAEHEE,True +919,29.0,30.0,27.0,23.0,18.0,16.0,15.0,25.0,CECCDDBFGBEHCFACFCCAAAAABGDBDCBDABFBCEACABCGBHGDCGFBGHCDHCEHCBAFBFGHFHHDHFEHFEHCDBDDACBACGACGACFEDEBDHBDHAAEEGFBHHBHDAHBGBCGDAAHAFEBCCBDBEEAHEHFGHAHAABBABDHBDADDAECGBCEDCDCGEHAEHABBFF,False +920,6.0,8.0,6.0,2.0,10.0,1.0,2.0,2.0,ABABBFGBDGEECCEACECHEHBEABDBEEEACEACB,True +921,9.0,6.0,2.0,9.0,10.0,5.0,13.0,15.0,EBEDHGAHGFHGFBDEDDGCDGDHFAEABEGEGAHGAFEAGHAHHEHDEHDABDBGEGGBGHHACHFHH,True +922,0.0,4.0,4.0,4.0,5.0,3.0,8.0,5.0,BFCBHEBHDBCDFGGEGFEGEHGHCDHGDGGEC,False +923,9.0,18.0,18.0,28.0,20.0,33.0,20.0,19.0,FCFHEFDEBCBBCFACFDCDCAFCAHBDHBFGFHAFEAFEHGCHGDHCDHCFCGDCHBEGFFGDFGBHGDFGDFGFAHDBGGHHABEDFFDFFDFFEBFHDCEDFEFHEHHDGACFFGHBBHBADDDDCDEGDGGCEFCDBEBGEDEEBCEFGFFBEDGEDBFDE,False +924,2.0,5.0,0.0,7.0,6.0,1.0,0.0,3.0,EEDEEHEBAEBDDDADBHDFHBBD,True +925,12.0,20.0,17.0,18.0,18.0,15.0,13.0,21.0,GHHFHBACCFFHHFHHABHGDHFDEBABDDBCAEHABDEDCGDGDDGCDFFDHEBAEBAEBDCBGCEGBEHBFCEFDBGBFGBHBHHFFEEGECGECGECBHGBHDCHDAFDCFDEAHAHEAHACCEEFBBDCC,False +926,4.0,3.0,0.0,1.0,0.0,3.0,0.0,2.0,FHBFBBAAHAFDA,True +927,18.0,22.0,21.0,28.0,13.0,24.0,11.0,19.0,CBHHDCBAGFEDFBGBCGDCEFHFGHFGBFDDDDCDDCFHGFBDEBAFBEDACDAFEGFEDFCHEDADFBEFBABDGCCACBACHDCFDFAACCACBHFBHFBHADDADHACBBCDHCFFBFAEAACDBCHHFHGFHGHBGHBDEDDEDFEAHDBE,False +928,1.0,4.0,0.0,2.0,0.0,5.0,1.0,1.0,HBBFFDFFGFBADB,True +929,3.0,12.0,7.0,6.0,3.0,6.0,4.0,12.0,DHGHFACCACBAFHGDEGDCCBBFEBDEBHHCHHBHBBHBFHFCBFHGDBBDH,True +930,4.0,2.0,2.0,0.0,0.0,4.0,2.0,2.0,HCAACAFFGBFGBHAF,True +931,5.0,1.0,3.0,1.0,0.0,1.0,1.0,3.0,FGAADCACHACHAHB,True +932,6.0,4.0,3.0,4.0,3.0,1.0,3.0,2.0,DGCABBECFGCBGAADHAEHAEDABD,False +933,9.0,5.0,1.0,9.0,8.0,8.0,7.0,8.0,EFBCBAHBDFADADEAFFGGDEHDEHDHAAEABBFEDHEDHGFHGFEGFGGADHA,False +934,4.0,7.0,1.0,3.0,1.0,1.0,4.0,5.0,AEBGGBGBHABDFGDBADBHHCHHBA,True +935,14.0,14.0,13.0,12.0,23.0,12.0,15.0,6.0,EDAGFAGECGAGGACEACGGEHGEHCEBCFBEGECGEDEECFCBFBAFADBBDFBGCEEBEEDCDDFHFHEFDBCEGABGAFDAFDABDAEEEHBEDBEFCEAAGBGHC,False +936,16.0,21.0,7.0,13.0,13.0,15.0,22.0,19.0,GFBGHEGBBAABABEAHHADCEHFAHFACEGBHHBEFGAGEAHADDGDFGDFDAGHCGFFGBFAFEGFHGAHADGBDHCDHEHEGDEGDCGBHGBCGBFEAHCGHEBDBBEBBFBHFBHFBDAGGB,False +937,24.0,12.0,20.0,15.0,16.0,11.0,15.0,24.0,HAECEECEEBBAGGADHAHCGHDDAGBFGAHEHCAABGAHGAFGADHEDGFDHADBBCABGABDDCCDBHBEEBEEHAHHAGHAHHDHCFCAHAACCDCGHCHFCHFCHFADGAHFAFFCCFEDEEBGECCACEHDG,False +938,3.0,5.0,0.0,6.0,7.0,6.0,5.0,5.0,DGBFHAFEFDHBDHBDGGGEEHBEHBFDEGAEFAEFD,False +939,22.0,26.0,26.0,14.0,18.0,22.0,25.0,26.0,ACFACFGFBAFBGBHHBDHBGGEAHFAHFAFEHGECCECCFAEGABGABEAHGBEGFHCHBBDBCHFDEFHEABEFCEBHEBHDBADACDEFBCHDGBBCCBCHBEHFCGFCGCEGCHHCHGAFCADDBHDGFFHBAGCACABCGDGGBFHDCBFGBFEEFHEHAGHGGHCCDAGDAGA,False +940,8.0,10.0,2.0,5.0,4.0,6.0,1.0,9.0,BGDEHABAADAFBAFHHFHHFHBAHDCEABDBBHEDHEBBFBAFC,True +941,29.0,18.0,34.0,25.0,27.0,21.0,24.0,19.0,DEDAEGFBGFBGCBFCHECFEFAGBABDCBEHHEHGADEHDFHFFCEAAEAFEAFCGGDGFEHEECGCCDCCECCDHFAHCACDGDBGFBCFADEABHABDABDHBGHGDADDADFCDAGFAGBBBECFCCECCEDGGDCDEGGAHHFEEAEACBDCDHCHEEAEACFAGDHFEGCAGHABDACHCCBCFGCAGEAC,False +942,22.0,23.0,26.0,28.0,25.0,25.0,28.0,22.0,HHDBFEGFEGCHBDEBHGCHGBDFHDBHFBHBGHCCECADHADGAGGCGCFDCFAFGDFAHGEDEEAEFDBCHBDHGHECFAFFAEFBGFHAFBGFAHFCCGHDBABEGBDBHFACAADAGDGECGEGGHCGFCFFEDFCCACEDDHDDEADECDGBBGBCHAEHEEFCBCCACGFBDFCDEADBGBEGBEGDEADEAD,False +943,10.0,5.0,3.0,10.0,7.0,4.0,2.0,3.0,DEBBHAGEABHDCADAADEEBCEFEDFADAADAGDABDCHDFFE,True +944,12.0,16.0,22.0,10.0,9.0,17.0,15.0,10.0,CBFHFFBDFBAGECGCCHCAHCFECDDFFDECBBCBBCBFCAFCFFEFABFGBEAHAGBGGCCGBADCADHDGBFGCEGCEGCGHFGCFEFBDHADACGABBHHDAHCGCE,False +945,14.0,9.0,10.0,9.0,9.0,9.0,8.0,11.0,GBHGAHFAHFBGGDDGCHFAAFACDEFDACDHCEEAHEAFCBHCBGFBAEBAEBAFCAHDAEGCHDEBAEFGDDCHBCH,False 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], + "markers": "python_version >= '3.7' and implementation_name == 'cpython'", + "version": "==1.3.1" + }, + "wrapt": { + "hashes": [ + "sha256:4aea003270831cceb8a90ff27c4031da6ead7ec1886023b80ce0dfe0adf61533" + ], + "version": "==1.11.1" + } + } +} diff --git a/README.md b/README.md index a24051a..1e7491b 100644 --- a/README.md +++ b/README.md @@ -1,36 +1,10 @@ -# N-Back Sequence Generator with [Hidden] Markov Chain +# N-Back Sequence Generators -**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/src/main/scala/org/xcit/nback/markov/models/State.scala b/src/main/scala/org/xcit/nback/markov/models/State.scala deleted file mode 100644 index fbbd844..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/State.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * A Single state with a label in Markov chain - * @param label A simple string label, representing the state and node - */ -class State(val label: String) { - - /** - * Keep track of transitions from this state to other states. - */ - val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() -} diff --git a/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/src/main/scala/org/xcit/nback/markov/models/Transition.scala deleted file mode 100644 index bc20a9e..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/Transition.scala +++ /dev/null @@ -1,8 +0,0 @@ -package org.xcit.nback.markov.models - -/** - * A Single transition in Markov chain graph. It is stored in "from" node. - * @param to the ending node of the edge - * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). - */ -case class Transition(to: State, probability: Double = 0.0) diff --git a/src/test/scala/ThreeBackBenchmark.scala b/src/test/scala/ThreeBackBenchmark.scala deleted file mode 100644 index 0c7dad9..0000000 --- a/src/test/scala/ThreeBackBenchmark.scala +++ /dev/null @@ -1,7 +0,0 @@ - -/** - * TODO Benchmark 3-back simple sequence generator - */ -class ThreeBackBenchmark { - -} diff --git a/tests/benchmark_diagrams.py b/tests/benchmark_diagrams.py new file mode 100644 index 0000000..8fa448e --- /dev/null +++ b/tests/benchmark_diagrams.py @@ -0,0 +1,159 @@ +import pandas as pd +import numpy as np +from matplotlib import pyplot as plt + +import benchmarks.common as common + + +def tlratio(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2,ignore_index=True) + stats = [] + for trials in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == trials) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == trials) + targets2 = data[alg2].targets if alg2.shape[0] > 0 else np.nan + targets4 = data[alg4].targets if alg4.shape[0] > 0 else np.nan + lures2 = data[alg2].lures if alg2.shape[0] > 0 else np.nan + lures4 = data[alg4].lures if alg4.shape[0] > 0 else np.nan + stats.append([trials, (targets2/lures2).mean(), (targets4/lures4).mean()]) + stats = pd.DataFrame(stats, columns=['trials', 'tl2', 'tl4']) #.dropna(subset=['skewness']) + + plt.style.use('ggplot') + + plt.ylim(bottom=0, top=30) + plt.scatter(stats.trials, stats.tl2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl2[idx], 1)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.tl4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl4[idx], 2)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('T:L Ratio') + plt.ylabel('T:L Ratio') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_tlratio.png', bbox_inches='tight') + plt.show() + + +def time_per_trial(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for t in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == t) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == t) + time2 = data[alg2].time.mean() * 1000 if alg2.shape[0] > 0 else np.nan + time4 = data[alg4].time.mean() * 1000 if alg4.shape[0] > 0 else np.nan + stats.append([t, time2, time4]) + stats = pd.DataFrame(stats, columns=['trials', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.trials, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time2[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time4[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2v4_time_trials.png', bbox_inches='tight') + plt.show() + +def time_profiles(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 8): + alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + time2 = data[alg2].time.mean() * 1000 + time4 = data[alg4].time.mean() * 1000 + stats.append([ni, time2, time4]) + stats = pd.DataFrame(stats, columns=['n', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.n, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.time2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + plt.scatter(stats.n, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.time4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_time_n.png', bbox_inches='tight') + plt.show() + +def skewness(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 9): + all_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + skewed_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) & data.skewed + all_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + skewed_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) & data.skewed + num_of_sequences2 = data[all_alg2].shape[0] + skewed_sequences2 = data[skewed_alg2].shape[0] + num_of_sequences4 = data[all_alg4].shape[0] + skewed_sequences4 = data[skewed_alg4].shape[0] + skewness2 = skewed_sequences2 * 100.0 / num_of_sequences2 if (num_of_sequences2>0) else 0 + skewness4 = skewed_sequences4 * 100.0 / num_of_sequences4 if (num_of_sequences4>0) else 0 + stats.append([ni, skewness2, skewness4]) + stats = pd.DataFrame(stats, columns=['n', 'skewness2', 'skewness4']) #.dropna(subset=['skewness']) + + + plt.style.use('ggplot') + plt.scatter(stats.n, stats.skewness2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.skewness2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + + plt.scatter(stats.n, stats.skewness4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.skewness4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Skewness') + plt.ylabel('Skewed Blocks (%)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_skewness.png', bbox_inches='tight') + plt.show() + +if __name__ == "__main__": + tlratio() + skewness() + time_profiles() + time_per_trial() diff --git a/tests/benchmark_skewness.py b/tests/benchmark_skewness.py new file mode 100644 index 0000000..f468b4d --- /dev/null +++ b/tests/benchmark_skewness.py @@ -0,0 +1,97 @@ +import random +import heapq +import csv + +# Common parameters +alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'] +trials_range = (10, 40) +n = 3 +sample_size = 100 + + +def to_benchmark_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [str(ralph_skewed)] + +def benchmark_nb_gm_001(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_001') + + +def benchmark_nb_gm_002(filename): + import generators.nb_gm_002 as nb_gm_002 + + generator = nb_gm_002.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + # print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_002') + + +def benchmark_nb_gm_003(filename): + import generators.nb_gm_003 as nb_gm_003 + + generator = nb_gm_003.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + print(f"sequence {i}/{sample_size}: {trials} trials") + seq = generator.generate(trials) + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_003') + + +def show_skweness_diagram(filename, choices, title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + print(filename) + data = pd.read_csv(filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) #.dropna(subset=['skewness']) + #print(stats.trials) + #plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'{title}.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + benchmark_nb_gm_003('../benchmarks/nb_gm_003_2back.csv') diff --git a/tests/common.py b/tests/common.py new file mode 100644 index 0000000..e40c0df --- /dev/null +++ b/tests/common.py @@ -0,0 +1,27 @@ + + +# Common benchmark parameters +choices = alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F'] +trials_range = (10, 65) +n = 4 +sample_size = 100 + + +def count_targets_and_lures(seq, n): + mask = 'D'*n + for index in range(n, len(seq)): + if seq[index] == seq[index - n]: + mask += 'T' + elif seq[index] in seq[index - n - 1:index - n + 1]: + mask += 'L' + else: + mask += 'D' + return mask.count('T'), mask.count('L') + + +def skewness(seq, choices): + import heapq + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return ralph_skewed diff --git a/tests/nb_gm_001_bm.py b/tests/nb_gm_001_bm.py new file mode 100644 index 0000000..54f6cb3 --- /dev/null +++ b/tests/nb_gm_001_bm.py @@ -0,0 +1,75 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq) , str(ralph_skewed)] + + +def benchmark(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets / s.trials, axis=1) + plt.scatter(data.trials, data.targets_ratio, alpha=0.2) + plt.show() + +if __name__ == '__main__': + alg = 'nb_gm_001' + fn = f'results/{alg}_{n}back.csv' + benchmark(fn) + # skewness_diagram(fn, alg) + targets_ratio_diagram(fn, alg) diff --git a/tests/nb_gm_002_bm.py b/tests/nb_gm_002_bm.py new file mode 100644 index 0000000..c8af543 --- /dev/null +++ b/tests/nb_gm_002_bm.py @@ -0,0 +1,105 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq), str(ralph_skewed)] + + +def benchmark(filename): + from generators.nb_gm_002 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials, int(trials/3), 0, 0) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +import time +import numpy as np +import pandas as pd + +import benchmarks.common as common + +def profile(): + from generators.nb_gm_002 import SequenceGenerator + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, int(lures/2), int(lures/2)) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('benchmarks/results/nb_gm_002_profile.csv', sep=',', encoding='utf-8') + +if __name__ == '__main__': + alg = 'nb_gm_002' + fn = f'results/{alg}_{n}back.csv' + profile() diff --git a/tests/nb_gm_003_bm.py b/tests/nb_gm_003_bm.py new file mode 100644 index 0000000..fa6c19a --- /dev/null +++ b/tests/nb_gm_003_bm.py @@ -0,0 +1,114 @@ +import heapq +import csv +import random +import time + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq, time_per_block): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [time_per_block, ''.join(seq), str(ralph_skewed)] + + +def benchmark_skewness(filename): + from generators.nb_gm_003 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['time_per_block', 'seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + targets = trials / 3 + t = time.time() + seq = generator.generate(trials, targets) + t = time.time() - t + print(f"sequence {i}/{sample_size}: {trials} trials, took {t}s.") + writer.writerow(to_csv_row(i, seq, t)) + plot_skewness(fn, 'nb_gm_003') + + +def plot_skewness(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def plot_targets_ratio(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +def benchmark_targets_ratio(): + pass + +def benchmark_chunking(): + pass + + +def benchmark_n(): + pass + + +def plot_timing(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['time_per_trial'] = data.apply(lambda s: s.time_per_block / s.trials, axis=1) + plt.style.use('ggplot') + plt.title(f"{figure_title} - average time to generate a trial") + plt.ylabel('time (s)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.time_per_trial, alpha=0.5) + + # draw fitted curve + # import numpy as np + # p = np.poly1d(np.polyfit(data.trials, data.time_per_trial, 3)) + # plt.plot(data.trials, p(data.trials), color='red') + + plt.savefig(f'results/{figure_title}_timing.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + alg = 'nb_gm_003' + fn = f'results/{alg}_{n}back.csv' + benchmark_skewness(fn) diff --git a/tests/nb_gm_004_bm.py b/tests/nb_gm_004_bm.py new file mode 100644 index 0000000..b4ad4a8 --- /dev/null +++ b/tests/nb_gm_004_bm.py @@ -0,0 +1,26 @@ +import time +import numpy as np +import pandas as pd + +import tests.common as common +from generators.nb_gm_004 import SequenceGenerator + +def run(): + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, lures) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('tests/results/nb_gm_004_profile.csv', sep=',', encoding='utf-8') diff --git a/tests/results/2v4_time_trials.png b/tests/results/2v4_time_trials.png new file mode 100644 index 0000000..9be91b4 --- /dev/null +++ b/tests/results/2v4_time_trials.png Binary files differ diff --git a/tests/results/2vs4_skewness.png b/tests/results/2vs4_skewness.png new file mode 100644 index 0000000..a488e1f --- /dev/null +++ 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+210,87.0,0.0,0.0,88.0,1.0,0.0,0.0,0.0,EDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +211,0.0,0.0,12.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCC,True +212,0.0,0.0,0.0,66.0,0.0,65.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +213,1.0,0.0,0.0,0.0,0.0,21.0,22.0,0.0,AGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFG,True +214,74.0,73.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +215,0.0,5.0,0.0,0.0,6.0,0.0,0.0,1.0,HEBEBEBEBEBE,True +216,0.0,1.0,0.0,0.0,0.0,53.0,0.0,54.0,BHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +217,70.0,0.0,0.0,0.0,0.0,70.0,0.0,0.0,AFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +218,0.0,0.0,0.0,0.0,0.0,0.0,36.0,35.0,GGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +219,0.0,90.0,90.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +220,0.0,0.0,0.0,0.0,0.0,0.0,37.0,38.0,HHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +221,0.0,0.0,44.0,0.0,0.0,1.0,44.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +222,0.0,0.0,0.0,67.0,67.0,0.0,0.0,1.0,HDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True 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+409,0.0,0.0,72.0,1.0,0.0,0.0,72.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +410,55.0,0.0,1.0,0.0,0.0,0.0,55.0,0.0,CAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +411,0.0,59.0,0.0,0.0,0.0,60.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +412,61.0,0.0,0.0,61.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +413,0.0,1.0,0.0,75.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +414,0.0,53.0,0.0,0.0,0.0,0.0,52.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +415,0.0,0.0,16.0,0.0,1.0,0.0,0.0,15.0,ECHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +416,0.0,0.0,0.0,39.0,0.0,0.0,0.0,38.0,DHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +417,96.0,0.0,1.0,95.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +418,28.0,0.0,1.0,27.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +419,0.0,1.0,92.0,92.0,0.0,0.0,0.0,0.0,BCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +420,1.0,0.0,20.0,0.0,20.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECE,True +421,0.0,90.0,0.0,0.0,0.0,0.0,89.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +422,10.0,0.0,0.0,0.0,0.0,1.0,11.0,0.0,FGAGAGAGAGAGAGAGAGAGAG,True +423,0.0,0.0,0.0,74.0,73.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +424,0.0,0.0,127.0,0.0,0.0,0.0,1.0,0.0,GCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +425,1.0,9.0,0.0,0.0,0.0,9.0,0.0,0.0,AFBFBFBFBFBFBFBFBFB,True +426,0.0,0.0,84.0,0.0,0.0,0.0,0.0,84.0,HCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +427,33.0,0.0,0.0,34.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +428,1.0,30.0,0.0,30.0,0.0,0.0,0.0,0.0,ABDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +429,0.0,0.0,67.0,0.0,1.0,67.0,0.0,0.0,EFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +430,62.0,0.0,0.0,63.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +431,1.0,9.0,9.0,0.0,0.0,0.0,0.0,0.0,ABCBCBCBCBCBCBCBCBC,True +432,15.0,0.0,0.0,0.0,0.0,0.0,14.0,0.0,AAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +433,0.0,1.0,0.0,65.0,66.0,0.0,0.0,0.0,BEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +434,0.0,160.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +435,0.0,0.0,1.0,0.0,42.0,42.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +436,0.0,0.0,55.0,0.0,55.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +437,0.0,0.0,0.0,1.0,0.0,73.0,0.0,73.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +438,79.0,0.0,0.0,0.0,78.0,0.0,0.0,0.0,AAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +439,0.0,0.0,67.0,0.0,0.0,0.0,66.0,1.0,HCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +440,0.0,0.0,77.0,0.0,0.0,1.0,0.0,76.0,FCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +441,0.0,0.0,0.0,0.0,153.0,0.0,0.0,1.0,HEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +442,0.0,88.0,88.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +443,0.0,0.0,0.0,20.0,22.0,0.0,0.0,0.0,EEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +444,41.0,0.0,42.0,0.0,0.0,0.0,1.0,0.0,GCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +445,0.0,0.0,0.0,47.0,0.0,46.0,0.0,1.0,HDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +446,1.0,0.0,0.0,0.0,86.0,0.0,0.0,87.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +447,56.0,56.0,0.0,0.0,0.0,0.0,0.0,1.0,HABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +448,0.0,0.0,0.0,0.0,11.0,0.0,0.0,10.0,EEHEHEHEHEHEHEHEHEHEH,True +449,0.0,0.0,0.0,0.0,0.0,1.0,92.0,92.0,FGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +450,0.0,0.0,0.0,6.0,5.0,1.0,0.0,0.0,FDEDEDEDEDED,True +451,66.0,1.0,67.0,0.0,0.0,0.0,0.0,0.0,BCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +452,0.0,0.0,0.0,13.0,0.0,1.0,12.0,0.0,FDGDGDGDGDGDGDGDGDGDGDGDGD,True +453,1.0,0.0,0.0,0.0,56.0,0.0,56.0,0.0,AEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +454,15.0,0.0,0.0,0.0,0.0,0.0,0.0,16.0,HAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +455,0.0,21.0,1.0,0.0,21.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True +456,93.0,0.0,1.0,0.0,92.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +457,1.0,0.0,0.0,0.0,35.0,0.0,0.0,35.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +458,13.0,0.0,0.0,0.0,1.0,0.0,13.0,0.0,EAGAGAGAGAGAGAGAGAGAGAGAGAG,True +459,0.0,0.0,65.0,0.0,1.0,0.0,65.0,0.0,ECGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +460,0.0,0.0,95.0,1.0,0.0,95.0,0.0,0.0,DFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +461,15.0,0.0,0.0,0.0,1.0,0.0,0.0,15.0,EHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +462,0.0,0.0,198.0,0.0,1.0,0.0,0.0,0.0,ECCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +463,84.0,84.0,0.0,0.0,1.0,0.0,0.0,0.0,EABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +464,0.0,0.0,0.0,0.0,0.0,60.0,0.0,61.0,HFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +465,0.0,179.0,0.0,1.0,0.0,0.0,0.0,0.0,DBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +466,1.0,0.0,90.0,0.0,89.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +467,0.0,35.0,0.0,0.0,0.0,34.0,0.0,0.0,BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +468,0.0,0.0,0.0,1.0,7.0,0.0,0.0,7.0,DHEHEHEHEHEHEHE,True +469,0.0,0.0,0.0,0.0,92.0,0.0,91.0,0.0,EEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +470,0.0,0.0,46.0,0.0,0.0,1.0,46.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +471,0.0,0.0,0.0,0.0,0.0,1.0,158.0,0.0,FGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +472,1.0,0.0,0.0,0.0,0.0,58.0,0.0,59.0,AHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +473,0.0,0.0,6.0,1.0,0.0,0.0,6.0,0.0,DCGCGCGCGCGCG,True +474,0.0,0.0,0.0,0.0,0.0,98.0,0.0,97.0,FFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +475,0.0,87.0,0.0,0.0,0.0,0.0,0.0,85.0,BBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +476,0.0,0.0,33.0,0.0,0.0,0.0,1.0,33.0,GHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +477,45.0,0.0,0.0,0.0,46.0,0.0,0.0,0.0,EAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +478,0.0,0.0,0.0,77.0,0.0,0.0,75.0,0.0,DDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +479,73.0,1.0,73.0,0.0,0.0,0.0,0.0,0.0,BACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +480,0.0,1.0,0.0,0.0,37.0,37.0,0.0,0.0,BEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +481,0.0,92.0,93.0,0.0,0.0,1.0,0.0,0.0,FCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +482,0.0,0.0,0.0,1.0,0.0,0.0,0.0,24.0,DHHHHHHHHHHHHHHHHHHHHHHHH,True +483,25.0,0.0,0.0,1.0,0.0,25.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +484,0.0,0.0,0.0,0.0,0.0,37.0,0.0,36.0,FHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +485,21.0,0.0,0.0,1.0,0.0,20.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +486,0.0,35.0,0.0,36.0,0.0,0.0,0.0,1.0,HDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +487,0.0,0.0,1.0,0.0,97.0,98.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +488,0.0,93.0,0.0,0.0,0.0,1.0,0.0,94.0,FHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +489,0.0,1.0,0.0,93.0,0.0,0.0,93.0,0.0,BGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +490,0.0,0.0,0.0,70.0,0.0,0.0,72.0,0.0,GGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +491,86.0,0.0,0.0,0.0,1.0,86.0,0.0,0.0,EFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +492,0.0,65.0,1.0,0.0,0.0,65.0,0.0,0.0,CBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +493,0.0,0.0,0.0,69.0,0.0,0.0,0.0,1.0,HDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +494,0.0,0.0,144.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +495,0.0,45.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True 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+599,16.0,0.0,16.0,0.0,0.0,0.0,0.0,0.0,ACACACACACACACACACACACACACACACAC,True +600,0.0,21.0,0.0,22.0,0.0,0.0,0.0,0.0,DBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +601,70.0,71.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +602,0.0,0.0,0.0,1.0,0.0,0.0,53.0,0.0,DGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +603,45.0,0.0,0.0,0.0,0.0,45.0,0.0,0.0,FAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +604,0.0,1.0,56.0,0.0,0.0,0.0,56.0,0.0,BGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +605,0.0,1.0,0.0,0.0,0.0,0.0,0.0,195.0,BHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True 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+611,0.0,0.0,86.0,0.0,88.0,0.0,0.0,0.0,EECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +612,1.0,0.0,0.0,0.0,14.0,0.0,0.0,14.0,AEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +613,0.0,0.0,35.0,0.0,0.0,35.0,1.0,0.0,GCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCF,True +614,0.0,0.0,1.0,0.0,43.0,43.0,0.0,0.0,CEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +615,0.0,0.0,0.0,0.0,0.0,1.0,67.0,66.0,FGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +616,0.0,27.0,0.0,0.0,26.0,0.0,1.0,0.0,GBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +617,0.0,88.0,1.0,87.0,0.0,0.0,0.0,0.0,CBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +618,0.0,41.0,0.0,0.0,0.0,41.0,1.0,0.0,GFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +619,0.0,27.0,27.0,0.0,0.0,0.0,0.0,0.0,CBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +620,1.0,0.0,20.0,20.0,0.0,0.0,0.0,0.0,ADCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +621,0.0,0.0,1.0,24.0,24.0,0.0,0.0,0.0,CEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +622,1.0,0.0,0.0,0.0,55.0,55.0,0.0,0.0,AEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +623,1.0,0.0,0.0,0.0,26.0,0.0,26.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +624,0.0,0.0,15.0,0.0,0.0,0.0,0.0,13.0,CCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +625,0.0,0.0,1.0,67.0,67.0,0.0,0.0,0.0,CDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +626,0.0,0.0,65.0,0.0,0.0,1.0,0.0,64.0,FCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +627,0.0,0.0,0.0,0.0,89.0,1.0,90.0,0.0,FGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +628,0.0,0.0,0.0,0.0,1.0,0.0,51.0,0.0,EGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +629,0.0,0.0,41.0,0.0,0.0,40.0,0.0,0.0,CFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +630,0.0,0.0,93.0,0.0,0.0,0.0,1.0,0.0,GCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +631,0.0,53.0,1.0,0.0,0.0,53.0,0.0,0.0,CBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +632,0.0,0.0,0.0,14.0,0.0,0.0,0.0,15.0,HHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +633,0.0,29.0,0.0,0.0,0.0,0.0,28.0,0.0,BGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +634,0.0,66.0,0.0,0.0,0.0,1.0,66.0,0.0,FGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +635,0.0,0.0,62.0,62.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +636,0.0,31.0,32.0,0.0,1.0,0.0,0.0,0.0,ECBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +637,0.0,0.0,0.0,0.0,0.0,0.0,48.0,49.0,HGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +638,1.0,0.0,0.0,0.0,0.0,0.0,54.0,53.0,AGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +639,59.0,0.0,1.0,0.0,59.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +640,0.0,0.0,0.0,0.0,1.0,0.0,27.0,27.0,EGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +641,0.0,0.0,0.0,23.0,24.0,0.0,0.0,0.0,EDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +642,0.0,0.0,0.0,91.0,0.0,0.0,91.0,0.0,DGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +643,0.0,0.0,0.0,0.0,48.0,49.0,0.0,1.0,HFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +644,14.0,0.0,0.0,0.0,0.0,14.0,1.0,0.0,GAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +645,0.0,96.0,0.0,0.0,1.0,0.0,0.0,96.0,EHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +646,0.0,0.0,0.0,50.0,48.0,0.0,0.0,0.0,DDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +647,0.0,0.0,0.0,99.0,0.0,99.0,0.0,0.0,FDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +648,49.0,0.0,1.0,0.0,0.0,0.0,0.0,48.0,CAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +649,0.0,0.0,52.0,0.0,1.0,0.0,53.0,0.0,EGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True 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+667,1.0,147.0,0.0,0.0,0.0,0.0,0.0,0.0,ABBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +668,0.0,0.0,97.0,0.0,97.0,0.0,0.0,1.0,HCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +669,0.0,0.0,1.0,0.0,0.0,0.0,53.0,52.0,CGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +670,0.0,0.0,94.0,0.0,96.0,0.0,0.0,0.0,EECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +671,99.0,0.0,1.0,0.0,98.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +672,68.0,0.0,0.0,0.0,0.0,0.0,67.0,1.0,HAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGA,True +673,0.0,0.0,0.0,26.0,27.0,0.0,1.0,0.0,GEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +674,31.0,0.0,0.0,0.0,32.0,0.0,0.0,1.0,HEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +675,0.0,0.0,0.0,0.0,42.0,0.0,41.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +676,0.0,0.0,50.0,0.0,0.0,0.0,1.0,50.0,GCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +677,0.0,25.0,0.0,24.0,0.0,0.0,0.0,0.0,BBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +678,0.0,0.0,0.0,0.0,1.0,10.0,9.0,0.0,EFGFGFGFGFGFGFGFGFGF,True +679,65.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,DAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +680,0.0,23.0,0.0,0.0,0.0,0.0,23.0,1.0,HGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +681,0.0,1.0,58.0,0.0,0.0,0.0,57.0,0.0,BCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +682,0.0,0.0,0.0,0.0,0.0,68.0,1.0,68.0,GFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +683,0.0,0.0,0.0,0.0,96.0,0.0,96.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +684,1.0,0.0,0.0,0.0,66.0,0.0,66.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +685,0.0,0.0,0.0,0.0,0.0,1.0,0.0,21.0,FHHHHHHHHHHHHHHHHHHHHH,True +686,0.0,88.0,0.0,87.0,0.0,0.0,0.0,0.0,BDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +687,0.0,0.0,19.0,19.0,0.0,0.0,1.0,0.0,GDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +688,0.0,42.0,1.0,0.0,41.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +689,0.0,0.0,0.0,0.0,0.0,60.0,61.0,0.0,GGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +690,0.0,23.0,23.0,0.0,0.0,0.0,1.0,0.0,GBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +691,86.0,86.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +692,35.0,35.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +693,57.0,0.0,0.0,0.0,0.0,58.0,1.0,0.0,GFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +694,0.0,0.0,30.0,30.0,1.0,0.0,0.0,0.0,EDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +695,19.0,18.0,0.0,1.0,0.0,0.0,0.0,0.0,DABABABABABABABABABABABABABABABABABABA,True +696,0.0,0.0,0.0,1.0,0.0,56.0,0.0,57.0,DHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +697,10.0,0.0,1.0,0.0,0.0,0.0,0.0,11.0,CHAHAHAHAHAHAHAHAHAHAH,True +698,0.0,0.0,89.0,0.0,88.0,0.0,1.0,0.0,GCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +699,0.0,0.0,87.0,0.0,86.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +700,17.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAA,True +701,0.0,0.0,66.0,65.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +702,0.0,0.0,1.0,0.0,0.0,0.0,123.0,0.0,CGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +703,0.0,118.0,0.0,0.0,1.0,0.0,0.0,0.0,EBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +704,0.0,0.0,0.0,0.0,0.0,0.0,0.0,132.0,HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +705,0.0,0.0,0.0,0.0,0.0,23.0,1.0,23.0,GHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +706,0.0,0.0,0.0,0.0,6.0,5.0,0.0,0.0,EFEFEFEFEFE,True +707,18.0,0.0,0.0,16.0,0.0,0.0,0.0,0.0,AADADADADADADADADADADADADADADADADA,True +708,0.0,72.0,0.0,0.0,0.0,71.0,0.0,1.0,HBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +709,0.0,0.0,54.0,0.0,0.0,1.0,0.0,55.0,FHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +710,0.0,1.0,87.0,0.0,87.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +711,0.0,0.0,1.0,63.0,0.0,0.0,0.0,64.0,CHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +712,78.0,0.0,78.0,0.0,0.0,1.0,0.0,0.0,FCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +713,0.0,80.0,0.0,0.0,0.0,81.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +714,0.0,1.0,0.0,0.0,0.0,0.0,40.0,39.0,BGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +715,0.0,0.0,7.0,0.0,6.0,0.0,0.0,0.0,CCECECECECECE,True +716,35.0,0.0,0.0,0.0,0.0,0.0,0.0,33.0,AAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +717,0.0,0.0,0.0,1.0,73.0,0.0,0.0,72.0,DEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +718,0.0,0.0,90.0,0.0,0.0,1.0,89.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +719,1.0,0.0,0.0,67.0,0.0,0.0,0.0,66.0,ADHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +720,56.0,0.0,0.0,0.0,56.0,0.0,1.0,0.0,GAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +721,0.0,0.0,0.0,1.0,0.0,0.0,49.0,49.0,DHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +722,0.0,0.0,0.0,117.0,0.0,1.0,0.0,0.0,FDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +723,0.0,0.0,86.0,1.0,0.0,0.0,85.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +724,0.0,0.0,31.0,0.0,0.0,0.0,0.0,30.0,CCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +725,1.0,0.0,0.0,0.0,98.0,0.0,98.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +726,1.0,84.0,84.0,0.0,0.0,0.0,0.0,0.0,ACBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +727,0.0,56.0,56.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +728,0.0,1.0,0.0,24.0,24.0,0.0,0.0,0.0,BDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +729,37.0,0.0,0.0,0.0,0.0,37.0,0.0,0.0,FAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +730,0.0,0.0,91.0,0.0,0.0,0.0,91.0,0.0,GCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True 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+772,0.0,68.0,0.0,0.0,0.0,0.0,0.0,67.0,BBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +773,60.0,1.0,0.0,0.0,0.0,61.0,0.0,0.0,BFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +774,0.0,1.0,0.0,57.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +775,0.0,78.0,0.0,0.0,1.0,0.0,0.0,0.0,EBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +776,1.0,0.0,0.0,0.0,0.0,96.0,96.0,0.0,AGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +777,43.0,0.0,0.0,0.0,0.0,1.0,44.0,0.0,FGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True 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+989,93.0,0.0,92.0,0.0,0.0,0.0,0.0,1.0,HACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +990,0.0,1.0,0.0,0.0,60.0,0.0,0.0,61.0,BHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +991,0.0,1.0,0.0,0.0,0.0,0.0,32.0,32.0,BHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +992,0.0,0.0,34.0,35.0,0.0,0.0,1.0,0.0,GDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +993,0.0,0.0,0.0,0.0,54.0,0.0,54.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +994,0.0,0.0,0.0,1.0,0.0,39.0,0.0,38.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +995,0.0,0.0,0.0,0.0,99.0,98.0,0.0,1.0,HEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +996,86.0,1.0,0.0,0.0,0.0,86.0,0.0,0.0,BFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +997,0.0,76.0,77.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +998,0.0,0.0,19.0,0.0,0.0,0.0,0.0,1.0,HCCCCCCCCCCCCCCCCCCC,True +999,0.0,0.0,37.0,1.0,0.0,0.0,38.0,0.0,DGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True diff --git a/tests/results/nb_gm_001_3back.csv b/tests/results/nb_gm_001_3back.csv new file mode 100644 index 0000000..b2f89a4 --- /dev/null +++ b/tests/results/nb_gm_001_3back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,0.0,65.0,132.0,0.0,0.0,0.0,0.0,1.0,HCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCC,True +1,51.0,0.0,52.0,52.0,0.0,0.0,0.0,1.0,HCDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACD,True +2,0.0,61.0,0.0,62.0,0.0,0.0,61.0,1.0,HDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGD,True +3,40.0,0.0,0.0,1.0,0.0,0.0,0.0,80.0,DHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHA,True +4,4.0,0.0,1.0,0.0,0.0,6.0,0.0,0.0,CAFFAFFAFFA,True 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+401,0.0,55.0,55.0,0.0,0.0,1.0,54.0,0.0,FCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCB,True +402,47.0,0.0,0.0,0.0,1.0,47.0,0.0,47.0,EAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFH,True +403,56.0,0.0,0.0,0.0,58.0,0.0,0.0,56.0,EEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAE,True +404,0.0,39.0,0.0,0.0,39.0,1.0,40.0,0.0,FGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEG,True 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+3,12.0,15.0,11.0,20.0,13.0,17.0,17.0,22.0,AFAHGHGHGBEBCDDDDHHHABCEHEHEBBBAHADADCFHHHHHFEFCBDDFDGDEFCAGGFEFBDGEHECCBCFFFFFFHGEBBHHCBCACHHDDBFGGGGEGEAFDGDADGDGDGBEBAAHDDFH,False +4,4.0,4.0,8.0,8.0,5.0,7.0,4.0,2.0,FGDGECDCECGCDADAHFDFCFCGAFCDDDABEBHBEFEFBC,False +5,15.0,15.0,15.0,16.0,16.0,14.0,9.0,13.0,HGDGBFDHDADHBBBBBHBAAGBCEABCGFAFAFBGBCBFGDDDEAAAHDFACECECHFHFHFCFHEGEFEFDFDAAHDEECDABFCCCCGBEBDAHCECHCHEDEDEDAGEE,False +6,17.0,17.0,9.0,6.0,15.0,13.0,15.0,12.0,BEBEBHAGCFEHHABAHDEDGHFBFGFCAABAGFFFAFGECEBEAEAFBFCEBEGHGDBEFABABEGEHEHBGBGDADACAGHGHGBGBACGCAHFFBHAECDC,False +7,12.0,7.0,7.0,6.0,9.0,8.0,5.0,6.0,CEGBFEFEFEHCCDEBCCHBBBGAHACBGGDBDADACADHDHFEAEAEFGFAAEAHAFAF,False +8,9.0,13.0,10.0,11.0,12.0,15.0,11.0,12.0,CGCFDBDFHHEHFFGCDHEHCFCFAAEGDCEGHGCFCBBBCBGFGHGDFDBDADHBBEGAGABABHBEBEHGHADAFEFCFDBDEFEHEFEFA,False +9,13.0,26.0,23.0,14.0,20.0,18.0,19.0,27.0,HECEBEFFHFDCCFGBCBDBAHGHGCBBABHEFAFEBEBHBHGGCHBGGCCCCCFCBDDDEDHDEEEAAFAFGFDFCGBGHEHDHGHAFABCGGEHEHFBGBADEBEBEAAHBDCCFGGHHHBHBHGHBDBEEAEGCGCBCHCEFFFFCHDHCHDHABCB,False +10,14.0,18.0,15.0,13.0,15.0,19.0,18.0,11.0,AFACABDDFBBBEBECECGHFBFBECDCEEEDGDBHHGCBDDAFCBAAAGHCHCHEAFBFDHAHCFFAAAHBBBFBFBHGFBCBCFGGGHGDGDFEGEFCFEDGDGAGEGCGEGEFEFAFDGC,False +11,21.0,20.0,21.0,13.0,15.0,26.0,21.0,21.0,EECEFFHGCADHGEGEABCCFDEBABEBGGCACHFHFBFBFBAHGBGCGHDCDABHHAGABFHEBCFEGDFDFDFAFBCBCAHACFGFBFBFBFBDACCBCHFHEGEDFDFCAAAGGEBFAAACACHCHFGFBFGHGHAEAGCCEDDFHHHGHGHGDE,False +12,17.0,26.0,17.0,23.0,17.0,11.0,26.0,21.0,ABGCACGDDFHFHBCEHEAGBGBEBAHEBEBFAAHAFBCEGDGBAHGGGGFGDDDBABABHGGGCGDGHGHDACAEDEFECHGEGDABGCHCDDDDCBCBADAHCHGBGBGEHDCDBBFBABHBHBFBACHDEEHGHECDCDHDEFEDECFGHGBFBD,False +13,24.0,21.0,23.0,20.0,15.0,14.0,30.0,24.0,AHHHHAFEDHAFBFGFCFGADADCDGBBBBGDGEGBCBHGGGGCGFBFAGGGGHEEFEGHGHABCBFHGAGACBBDEDHDHDGBCACAHGCACEHECACHBHDCGCECADGDGDABADHFGCGAGAHHBGFDCHBHCAAABEEFDFDBDBEADAHGEGEHECCCBCFCAHD,False +14,1.0,0.0,2.0,1.0,1.0,1.0,2.0,2.0,DECGCGAHFH,True +15,7.0,7.0,10.0,5.0,8.0,4.0,8.0,9.0,HBABHHEEGAGAGEGHCDEECHCHGBCBCDDAEGCBCGEAEFDFBFBFAGCHCHCHAD,False +16,14.0,19.0,14.0,7.0,10.0,15.0,19.0,7.0,CEAFFGHGEGFDFDCACAGBDEAFCEDDFAHHFDFGBEACGCGBGAFECECFGHCEBAFGEGCBABEBHBHBACAGAGDGHBABCBCBGFGFGFGBBBBFBCBGA,False +17,17.0,15.0,14.0,12.0,10.0,9.0,17.0,6.0,EBACADACGBGBAFGHGHADCDGAAFFFADABAHGDGABBCBCACACECHFBFHDCACDGEBADDEGGGEDADFGFGCGFBBABCBEBDBCHGEGEGECE,False +18,14.0,22.0,17.0,9.0,14.0,10.0,25.0,20.0,EHCHAHEHAHCHCGBGCGCGAEBFBFGGCEFGBGHAHCBABABHHGHGCACHDEDBBABGGDGDEBBBHHGCAEGBFHGEGEGBCCGCDFBBGBFBDAEEHHHCFEFECEHGCGCBHDADFDAGAGAGFBB,False +19,13.0,27.0,12.0,18.0,19.0,17.0,20.0,18.0,BFGCGBHAHAHEFEDBABEBEDADGGGGBAFCGEBDFHBHGHGCBBEGEGBHDHDHBCBCACDBFHHCHBGAGAGEDADADCDCACGHEEEEBDFDFDHDCGGBGDEBBBABEHFHGEFFFBADHEFFCFDEBEBFFEBHBFBG,False +20,11.0,10.0,7.0,8.0,8.0,7.0,11.0,4.0,BGBABGHGCGFBFAEBGGEDEFAHEHACDCDADBGGAGAGADFBFBCBCEFBFDHDACCDAGAEEE,False +21,22.0,20.0,18.0,24.0,13.0,11.0,16.0,21.0,DADADHCACFCHEDAAAHGDDHAGCDEDEGBHAHBDBDBGHHHCHCECAAAEFEDECEDBHFABGBCAGDBEGEBABHFCBBABDFDGHGCBFBCCDHDHDGDHDHCHBGADAFACHEHBDCDAFAFAFAGGCGCFHGBDBEBEG,False +22,8.0,10.0,11.0,7.0,8.0,15.0,4.0,11.0,CBAEGDGEHEBGBFBFBDHCHFHBAEHFFGFCFBFCFEEHABECFFFFACAEHHDCDCDHDHAHCFCBCBAADF,False +23,32.0,19.0,21.0,23.0,13.0,27.0,21.0,27.0,GHCABDGDFFFAHHHEAEHGAGAGHEFEGBCFAFBFGCHCHFHBGCAFFDFDBACACHCHCHBFGFEACAFABEBEBHHGHFHAHGGAGAHAFCGDHDHAFGCBCHDAAAAAAFCFHGEFFBEBEDDDFDBCBDDDCGFAFADBDBEBCAGGHDFDFBCDEAGAHCCEHGHAHCDDDDABAFA,False +24,26.0,30.0,18.0,21.0,29.0,16.0,21.0,21.0,GDGDADAGAGDEHCDBDHAHEHFHAHAFBHBHGCEBHBDBHBHBEEABABABAEECEGEGAGADHDBEEGBCAADHGBFBCEAAHDEBEBFBFBFCCGCEFBABAEDBGFGBGCFCGEACDFEFBHDADFHCEAEBDHDCGBEFGCDCACDEBEGAGAEAEFDFBBEHEGEGHCACEFBHDH,False +25,17.0,15.0,10.0,21.0,16.0,11.0,16.0,22.0,BDBDBHHHAAGAEHEHCHCDADEBGHDAGEBHGAABADADEDECEHAHFBGCGBEHCGADFBHECGHHFFFHFBDDDDDFDFDFHFEDEDACAEAEBDCHHBFBABCBGDGEAECHHGHGEGHDAGGG,False +26,12.0,13.0,16.0,11.0,17.0,10.0,17.0,12.0,GEECBGFEEDHCEFGFEAEAHGEGEDDDHDCDCBHBCBCFCECEGAGAGAHECFCEAAFGFGCEHGHBBBGBGBCBDHEAEFHFHGBCDGGACHCGCDADAEBFBADH,False +27,14.0,11.0,17.0,13.0,14.0,21.0,16.0,19.0,AAECGGEGHCACACACHBHADCECBDHDHDFCFGHGDDEDHHHAHDFDACHBHAFBHHAEEECGGFGEGEBEFCFAEAEFFBFBFDGDGDGHFACCDFHFCGBBHBCGGFGEHEFFFFHFCBCAF,False +28,14.0,15.0,12.0,21.0,15.0,9.0,13.0,21.0,GGHGEDHFCFCACBCADAEEEEAHDGAGHGHEHEHBBECEDBBBDBEGDGBAEABCCABBECDDDFDFHGHGHDHGHGHDADHHCHBHCCBAFHFDDDEDHFHAABDFDFEGEAADBDCH,False +29,18.0,19.0,27.0,26.0,29.0,30.0,16.0,16.0,DEFFFAFAGDGEEBFBFGEBADACADFDCEEDEDFDCDEBBGDGHGHGFFFDFBEBEHCHFDCDCEGFGFHFEFCGBBDCHCGCDADEGEGCFAAEHEHFDACGCEABBDECBCBCEFEFBFCFCFEHEHDGACEBAGCEFEBACCCAEDHDHBCFCDEFFHDHDHDCFCAAAEBEBFDHA,False +30,5.0,11.0,5.0,8.0,3.0,2.0,5.0,1.0,BBFGGBABFGCCCDADAHBEDCDBABGEAECBDBDBDBDG,True +31,28.0,17.0,19.0,16.0,18.0,11.0,17.0,33.0,DHAFAHAEAHDHFHFAFADHCGGGDGDGHEBDHCHBHAEBCBCFEGHHHBHCAFDHEHEHCDAGBCBAAAGACCBCAFGBHEHBBEAHAHAFAEACGGEHAFABEDEDFDCGHEBGAGEEAEBBHDEDECHCGABHGHAHAHBHCHCHCHDGACACDFD,False +32,5.0,10.0,12.0,17.0,19.0,17.0,17.0,11.0,EEBHBFFFDDEDCCAGEFEGGDGDFFGEGEAEDEFCFCGCGCGFAEGECDHHCEFDDHDFDABFDECECEHEFDDGDGBBFBFHHGCECEFEHAHDHDGBBFBGHGBG,False +33,4.0,13.0,10.0,7.0,4.0,8.0,11.0,7.0,CGBHBCBCBHFHFECBADGBGBGBDBCFAGDBHGFGECEHBGBCCACFGFGFGDDDFCADHEHB,False +34,22.0,27.0,22.0,21.0,21.0,28.0,21.0,21.0,BABFBCCCCGCDCAGABAHFBAHCBDBDHDCDCDEFFHBHBCBCBEHDAGAEFBBEEEBEGAGHGDGCGEBFBDEAECCFCFGDGDGHBHAEFFFECCADHFFBGHDHEGAAEDEFEFCDCDCDEFCHADAEHFDFHBBEBEBFBFAFGFAAHGHGFFAFGGBABGHGBFBFDFHCHAHEGDA,False +35,24.0,23.0,21.0,17.0,28.0,15.0,20.0,21.0,EGHGAGEGCGDFFCEEEEEAHGEGFGFBCBGBDBACHCAGDDDDEDEHACGCECAFAFEFHCHCEFHDHEHBAEADBDBAFCHCEEEEHBHBECEAEAFGGGGCCHBHAAACABBEHFHBDFHHDHBGCAABEBGAGABBFADADEBBBBCDCACFGFHDCEHEBGADE,False +36,16.0,12.0,18.0,16.0,29.0,20.0,25.0,11.0,EEEBCFFDHDBBGHGHGEFDFACCCFCGAECECEAGFFFCFDAHAEEHGGGBGBGADDGDGEGCCBFEHEGEHACDGDGCCCFCEAFAEGEGBGFGBBBHFGDGFGAAHADADCEEEEDEAEFEAEBFFFHEGECEGEHECAFDDDB,False +37,1.0,6.0,2.0,11.0,2.0,11.0,4.0,7.0,DBFFFHHADFFEFBDBFBGDFFEBHBHFHGDGDGCCDDDDHDHF,True +38,11.0,12.0,15.0,5.0,3.0,15.0,15.0,13.0,HCCCCAEBGFCFBGAHHHHBAFGCGCGCGFGCAABFBABHBFBCAFHFAFGCDBGBGAGFCBBAADHDHDCGEGHGCGFFHFHDEFHFC,False +39,33.0,14.0,21.0,23.0,21.0,18.0,25.0,28.0,DHAHAHADGDAFAFGCHCHEHCHABACEDDDCGBHAEFFGCADADGBGCFFFGGHBAAFGGHFHFHECFCHCHBDEFGADDCGGGHEBEDEBEBEDFHCAAAACFGFBFBFADAEGBDCAGACACAFGEEECDDDDCGGGEEEEEGCADHHHHAHABAHGBBCACHEGGHDADADAHAHEHAH,False +40,9.0,21.0,8.0,6.0,13.0,11.0,9.0,15.0,HEBEGEGAGEBBBHFAFABCBCBEBCBEAFHGGGHEHCHBEDFFAFAHDBFBFBEBDFHHDHBHCHBHBDEFABGBCEDEBCACHHEAGBGF,False +41,13.0,18.0,18.0,16.0,8.0,20.0,16.0,13.0,AGDGBCDHFADAGFFFHHCFCFEBGBGFGFGCGCHHHHCGFBFGDHABCBCGDGECEFBFCACBDBDCFAFBDEDCFFBHGHBEBABDFDFDHDHACABDBAFAFDHEGACACBEECGCBDG,False +42,21.0,15.0,14.0,22.0,14.0,22.0,16.0,21.0,ACFDFDEDFDBAFDCDCDFFFFFACHCHGEDFCFEHADACEHEDEBAFAGGHGEDADFDHDHDHGADAGCCCFHBDBGBDEGEBHGFGHAHFBFBFEAABABACDDAHHGFGBGEGHFEABHBFEHHHGDFDCACABABGECHAH,False +43,17.0,19.0,23.0,19.0,19.0,21.0,20.0,22.0,GDGFGEDDDDDDFDFDFEHBHDGAECBHDEGHGEEDEBEDECGGAADAFAFADECFCDGDGFBHGCBHBACAGACFCGGGBGCHFHEHECECAHFHFGCGHBFCGCBCFEHEGEHBBAAABDHFBCCCCFFFHFCABFBHBHBEDAFEHBHACABECHCH,False +44,2.0,1.0,3.0,4.0,5.0,3.0,6.0,5.0,CHCHFGBGEHFDAGADEDEGGFGEDEHCH,True +45,17.0,20.0,26.0,20.0,18.0,24.0,15.0,12.0,BDEFBBBHHECFCFCBBFEDDADADGECEHEFCGCAFDCGCFFEDDGGHHHHHAFAFEFAFDFDFDEDFAACFCFCDCBBBCGCGDGDFCGCGBDCACBHDHEECBBEBECFCHGBGEGABCDCEFHFGACDFAFAECEBEBDACABAGFBA,False +46,5.0,7.0,11.0,5.0,5.0,3.0,8.0,10.0,CBDHFHCDCEGEHCHCHCHEGCGCGBBBBADAHGDGBACGEAHBHFGFCECAHD,False +47,5.0,4.0,4.0,5.0,0.0,1.0,5.0,3.0,ACABGBHBHBGDCACHCDAGFGAGDDD,True +48,21.0,22.0,13.0,24.0,16.0,18.0,24.0,19.0,DBDGAGBGFHFCABGFECEGBGHHEACDFDGCGBEBGDAFAHADADAHHBHBHAGABADEBFDGDBDGDGCFAFAFDDDDECGFEFEAHAHEHEHCBCDADGBFBFAEBCAHFHEDEGBBFDEHEBDHFGCGHGHGBGCDABCBDGHGBGDCEAFAF,False +49,5.0,12.0,11.0,8.0,8.0,7.0,11.0,9.0,FCFDGDHBEBECFBBHFCFCGDBCCCGCECECBDBGBEHDDBCAGAEHEDFDHGEGAHBHGAGAGFHBHBG,False +50,2.0,7.0,7.0,4.0,6.0,13.0,10.0,11.0,BBFEFEFHAHFDFGHEBABDFHBHEFGFGHEHGGGFDFEHCBGBFDFHFHCCGCGHGCCC,True +51,5.0,7.0,11.0,12.0,13.0,9.0,8.0,13.0,EFFBFDAAECCCHDHBHFEDBHBHDHDGGGGECDGHCFEFEDEDCDCDEDCCHFEFEGCGBHEHBHAHAGDFCEAEHB,False +52,15.0,6.0,11.0,6.0,11.0,16.0,3.0,8.0,BAEGCCEAHBFCCHFABEHEFDCHEBECACECEAFGFEFEFBFBFAFADADACACDFGFAFAFEFDAAHFDCAHHH,True +53,20.0,14.0,19.0,11.0,13.0,12.0,10.0,17.0,CHCECEHEGAHBFGHCHABCBCDCECEDAHACGCADDBBGFGFGFHAAACACFBEGGAGAEHCAAAFDFDCHBDBHGDFDHCBEFEBCBABHHHHDHCHDFEFABEBECAAAEACF,False +54,18.0,14.0,15.0,22.0,24.0,20.0,25.0,23.0,EGGCGCGDEDEBCBFDDDBFHDDGFBFEEEGDBDBEHFDFEACACADABEFDCECGGHBDCDBAGHGFBFECHCFEDEHEHAHEEAGCEEEEFGFHFAAGEEHHHHAHAHDEFGDGDBCGAGHFHFHAHAHDHDBFBFCEGGGGGGGHAADAGCDFFAHCB,False +55,3.0,4.0,2.0,5.0,2.0,5.0,3.0,1.0,EHAABABGBFDFGFGEDDFDCBCDF,True +56,9.0,9.0,8.0,11.0,11.0,13.0,8.0,11.0,ECFFFBCDEDAFEBEAFGFHFHFDEHEBEHEGBFEFHBABCCAGAGBGBDFHAHGHFCFDHDABADEDEDAHGGCDCHCD,False +57,10.0,13.0,10.0,15.0,7.0,9.0,16.0,11.0,HHCFEGEGEDFGABEHEADCHGHBDFDGDGHGCGBBDDCDCDBDBHCDEBAHACCFDGDFAFAFDDAGAGHGCGBGBHACBGBGAHEBFBF,False +58,15.0,15.0,14.0,21.0,27.0,24.0,20.0,28.0,FAFEFAADAGFBFACBCBHHCGFGFAFHCEGEGHHBDBFHFHBEGDGDAEEHEGCGDGHCDGDEHFHGCEEEGEGEDBDEEEEHHHHCHDAGFEBHFHAHFHFDDDCACHFBDDHDGDFDAGGEAEFBHEEEEBEHEFFCFCFDBHAFADCGCGFHDHEBABHB,False +59,11.0,16.0,18.0,17.0,22.0,31.0,15.0,17.0,FCECFCFCFBHCHBGBFHGEDADADEFEFHFDFDADEEADHGAEAECGDGCCFHFGFHFHFHFBFBFCEEEBEFFDEGGBHBEBHFCDDDDGHAFBFBFCACHCAFGCGHHEDCBFEFABCDCEGGGDAEBBBEDEFFFFECGHEHF,False +60,11.0,9.0,7.0,2.0,10.0,10.0,11.0,9.0,HGHCDCHCACBCEGEGEGEBBHCFGABEBFAEHHFBFAAGHGHFHABABCGEGFDEAAABFEFEFGFGA,False +61,23.0,23.0,21.0,24.0,24.0,17.0,27.0,24.0,EDGGCBCFCGCGCFCGCDCBAACHFHFHECACAGAHFHDBDEHAGADHGEGEBCAEAGDHAADDDDCEAEADBGFDBBBBDHDGDBBGCAAEHEGDGBGBFHCGCDBBBEFHFDAGHCDCHFHFGEHEGEGHGBEFACADAFCBGBGBFHDEDEDFBFEGHGHAHAEEEEGEDHAHACEFBHB,False +62,21.0,13.0,9.0,12.0,17.0,15.0,25.0,10.0,HFGFGBGEDEHGHAHFHGAAAFGHBFACGDBEBGAAFEGEFEFBGAHDEDECBCBFBEGAGAFCCBBDBAGABAGGGGGECDADAGAEFEDGACADDCDHDEAFHFHFGGGFGCABAEEEGE,False +63,6.0,6.0,3.0,12.0,7.0,8.0,6.0,13.0,FHEBEBHGHDAGHDCDEDEAFCFCHEEBAAFDDDFDHDAGBGFDHGHAHDHEHFHFHBDBG,False +64,6.0,15.0,15.0,8.0,14.0,13.0,8.0,8.0,CCEDEDBHHGDCBEFEFCCGCEAGFGEGECAHAHGBCFHACEBEBEGEFFFFBDBFBHBDDEDCBCBHBFGFHEAEBCBCFCBCAFD,False +65,6.0,4.0,3.0,4.0,6.0,8.0,5.0,5.0,CGCFEFAFAEEDEHCHBBDAAFAGHEHEBFDHDBAGFGFGF,False +66,17.0,8.0,15.0,6.0,16.0,16.0,11.0,12.0,AFGFGFGHGFECECECHAECCCFAHAFAEHGGCEBAFAEAEFGGHCBFAAEHFHFGBHEHGAFBFHCECEADFDBDBCACACAEAEBEDDACBDFHFHEGC,False +67,24.0,12.0,23.0,14.0,18.0,18.0,15.0,12.0,CCCFCFBHAEEDFDBAADAEAEABDBDGEHEGCCCACECHGEGEDECACFCFCHBFBAGAFFGHADBEBAAAAFAEECEDHDHECGGBHHCHDBGBABAGEFFGFAFADACADAGADCHFECGFGFHFCDCEGFCC,False +68,31.0,17.0,27.0,38.0,29.0,28.0,14.0,16.0,ACACBCFDGBHBDEGEAHDDEFEFEFEFDDHECEBDFDAEAEFECECGCHAHAHCBCDAHBDDDDEDEBEHGDDAFEFCFDDBCGAGACCECAADADABAFEDACGCAFAHDFDBDGCECBGBFFCHCGAEDFFFHADFDADGFAFADEDHABAGAGEHEFBFECEDEDCGEADADFDHBHDFDCBCFCDAFAECFCEHB,False +69,5.0,4.0,3.0,4.0,2.0,3.0,6.0,4.0,DAHAGAHAHAHFGCGEBDFDEDGGCFBBGBC,False +70,5.0,7.0,9.0,5.0,2.0,11.0,6.0,10.0,HAHDHDHBGBFCACDCHFBBHBHGDEACACEGFCDHBGFGFGFCCHBFFHFCFAF,True +71,11.0,10.0,6.0,19.0,14.0,23.0,11.0,9.0,FHFEADABECHFFDFDFHFEDECEFEFEFAFHDADAEADDCAGFGBBHGDGABDDFFFFDDDADEEGFGDABCDGGBHDHFGAGBHBHBEBEGFFFFFCCEDE,False +72,25.0,17.0,20.0,19.0,16.0,13.0,17.0,22.0,GDCDHGBEAEGDGEBDBDHDCDCBHDEAEHDCEFAAABCDCDABAGADADCFAFCGCACAFFBAHGCGCGEGEACHHECACECEHEGGFBDHFHAHAHGGDGFCECHFHFHCHFABABFDGABDEDABABHEACAFDHHGHAHBBBBEH,False +73,15.0,19.0,20.0,23.0,23.0,21.0,22.0,23.0,GFGFECGCEEGHFCBCFDDDHHGBGHGHDCDCFHAHCCCFHAADEBEHEDEDADCDCABEGEFDFHCHGGAHAHFCFCEADFFECGBDBDBDCCACADHGCGEGHFHGHGBFADEBEBEDGDBBACEEEHGBDBFFFFDGEGDGDGFBEHHHHAAEAEFBBBBEFH,False +74,3.0,11.0,6.0,11.0,10.0,12.0,5.0,7.0,ECHFHDHEFFHHDCFGEGFDBEBEFFFDBCBFEDCDCFEBBFADDBDBGBGBGBAHAHFDEDECE,True +75,21.0,13.0,22.0,19.0,30.0,19.0,18.0,19.0,HAHEEEFEDHDFDBHBGCCEEFEGGHGHCCCCCHGECEAHDBDBEFGHCACGBEFEHAFDFACAFEEEHABAGAFDGDADADAGBCBAEADAEFHCDCFGEHFHDEDCDFEFCCCEAEAEGGABFGEDBDBHBCCECEHEAEFGHGHDDAEAEHCFGFGFB,False +76,14.0,30.0,18.0,20.0,25.0,19.0,27.0,30.0,FCFBAEDEGEHEBGHGFEFCGDBDGGCGCGBEBHBHEAAAEECBCBCFHFCFDGAEHHFGGGGGHCHEHBABGBGHHDFAEBDBDBDBCCHAGGEGDGCCBCHFGFGHGHBHEFGHBFBCBHEHBBABCBHBCGEHEADDDBHFHAADEDBFHFEEGEDHDHDEDBDFEFEHCHAEGDHBFBA,False +77,25.0,17.0,30.0,29.0,22.0,22.0,23.0,24.0,CCHEAEHBBCBDADBDBDHGFEECBDFGFEAHDCGCDHHEHEHCGCFHGDGAGAGACACDDDFDFDGECCHDHCCEFAFEBAFGGHDCCGEDBDBDBCHCACDBAHCGCGAHAHAFFFHADCDCFCFHHCDCAEAGAGAGABFHGEGBGDFHEBEFCFAGBEEAABAGDGDFDFEABHCDEDEHEHEFCFCD,False +78,9.0,16.0,9.0,5.0,4.0,15.0,4.0,5.0,BCEADCBBBBABABCCEHFBDHFAAGAGHCFCBCBFDFAGAGBFBDBABFFFFFCEHEBDHFFFBFC,True +79,19.0,17.0,10.0,29.0,13.0,8.0,14.0,14.0,DEDEAEAEDDDDDDDHDGEBEFADAGBFFHDGFBBBBGBABFCHGDFDEACBBBAHADAHCGCAHDHEHABAGCGCGEDAGBDAACAHDBCBGBGBEDDDDDADGDFDHHFDAHAEEEHCDCHG,False +80,9.0,11.0,7.0,9.0,14.0,3.0,11.0,16.0,HEHEACBHBHAGEBEAEBHBHBDEDCFABCGAEABHEHDADABABGGGDGHECEHHDGDHHCHCDGFFHCBEDEGEGHGE,False +81,4.0,9.0,4.0,9.0,3.0,6.0,6.0,5.0,BGBACACHDGDFDFBFEAHFBDDEDEGHGHBBBFBADHDGCGDBFC,False +82,11.0,21.0,22.0,24.0,26.0,28.0,21.0,21.0,EDGDCDCFGEDEFFFFGEEEDEDEDADACHCEBAFAFCHEDBFEDHDCCAHGFDFDGAGEFECEDBHCECDGGGGGBGFGBHCGDGFFDCAGDBCEHEGBBBBHFHADFHCHCHCACHCBBEFAGBGBEBFFFHFBCEDFFEFHDHFHFCCECBHBDBDEDEHBHEHFBFEGAG,False +83,2.0,4.0,1.0,3.0,2.0,4.0,2.0,1.0,CBFHFBBDGDFDFEGEABA,True +84,18.0,13.0,21.0,13.0,16.0,19.0,15.0,8.0,CBCEEADAFGDCFHFHDHFACACEDGACFGGGCBABDCCCCCCBABABABDBDFACGCGCFCAGEFEFBDBCFEFEAGFDBEFEHEHBAEADAFAFGEGECAHFEDGDHHCAEDEFCFGGGBF,False +85,14.0,12.0,10.0,10.0,16.0,19.0,9.0,12.0,FGBGHDEEEGBFAEAEDHGHGFEDEFEGEDEFEFCBAHCHCFBFDGECFFFGAECBBBDGFAFACACBEDABEBFHFHFHAHAHFEDCDCFCAAHBHADAFB,False +86,14.0,13.0,10.0,16.0,18.0,7.0,14.0,15.0,GGGGHADGCGCEEEDEDBAAGBCDAEABAGAFFFDBEFEAHAHBDBDBDBGHAACDHHGHGHDHEFBCDCHCHDEEBEBDADABEFECCGHGHFHDGEEEADBEEHC,False +87,9.0,13.0,17.0,12.0,12.0,23.0,13.0,12.0,EHCHBDDCECFCFCFABABGBFDFDCDHBGDHDGBGCGCGCFCDHEHEFCHGEAFBFBFDFHCEBAFEDEDFFGHCFGBGFGCDCEBGFHFAFBEEEBGFFCFAACAHAHF,False +88,6.0,3.0,0.0,1.0,3.0,3.0,5.0,4.0,GBGAGBHAGAGFEBEFEHHAHAFAD,True +89,11.0,11.0,12.0,15.0,16.0,12.0,7.0,10.0,BHBHDDADCGCAEHHDCEAFAFBFCDEDECBGFCECHAHGCAEDDBDEAFAFHFDCHEBEGEGADBDBHEHDFGFGFDECECECAAEBEBDBFF,False +90,18.0,21.0,18.0,8.0,15.0,18.0,18.0,10.0,BCBDGCBCHGHAAFAFEFAFDFHGGGCCECEHBHFCADAFAFEGBAAAGAFBEBEBEGCBHBFADAECDGHGBGECCBCBABHFFDCEFEHGBGBGBEFGABCBFBDBEEAHACGCGEGFCFCFDA,False +91,21.0,22.0,23.0,29.0,25.0,21.0,20.0,16.0,EDECECBBDBGGGDHDFCFDFAFGBACHDHDADFDHBEAACACACEDECEDGDGEGEGEDEAFCFEGGBEBGFGEDECGFAFAFGHEDFHFCFBFBDEDFDGBHEADHDCCFBABABACGEHAHFHCEGEGHBHDACADFCCHBHDCDCFBHAGDBABEBFBGCDBEBCDDADAEEC,False +92,22.0,26.0,23.0,24.0,20.0,30.0,22.0,18.0,ADAFEGHDHFFFFDFECADDDFHBHDCBFAHCHCACHEGFBFBCDHEFEGABAFAEBGBFFFBFCFGBHBEBAACAHAEDEDEGCDCDCDCGHACFCFHFHGCFCEHEHCGCDCEFGDGBGBGEGBABGBGCCABBBDBAFGDABFBFEFEDADBFEFDBHGHDFEFECBAGGCGADDDGBHAEA,False +93,2.0,2.0,1.0,3.0,0.0,2.0,1.0,2.0,DBDCDGFFAHAHB,True +94,18.0,8.0,12.0,13.0,10.0,9.0,12.0,11.0,HHFAEHCHCHCDDAFACACACGGFEFGCHDEEGCGCGFDDADGDFDEBHCDABGBABDGAGEEBAFABGBDAHAFAFADADEHHCHCBGEAEA,False +95,4.0,5.0,6.0,3.0,5.0,4.0,4.0,3.0,AHBFEADADAGFHFGGCBCBCBCFCEHEBDCEEG,False +96,6.0,10.0,15.0,4.0,14.0,9.0,14.0,11.0,ECECEGHGHEHGDACGHHHFGFGCCCGFEEHEAAACCHCFCFEGEDHFHFDFGEABBBBEBHGCGBEBGCACBEBEGCCDBFG,False +97,3.0,4.0,3.0,4.0,3.0,2.0,2.0,6.0,BGHFHDHDCDBDECAHAHAEGBFBHCE,False +98,14.0,9.0,9.0,12.0,16.0,15.0,11.0,5.0,BGGACFEGEGEAFGFGFGFAADADACBCFDADGEBHBFDFGBBDCGAFAEEFECHCDCBFEAEAEADADCEBDDHDBGEFCHEHEFEAEFF,False +99,24.0,22.0,16.0,19.0,18.0,22.0,22.0,17.0,BABDFDEDEDEHAACABAEAFFGBHFGAHDBCAGADEDCHBBGEGAGAGAGAGFGABEDEDEFCBABDBECECEAGFGEGBGACBFEHEHAHAFBFBCHEFGDADAEEBCBHHHFHFBAGGGFFFFGHDCCHAHBCBCHFGDBCCAFBDGGFDHDFDFDC,False +100,10.0,7.0,6.0,7.0,6.0,11.0,8.0,15.0,GGHGHGFEFDCHAHFHEHEBACCBCHFHFBCBEBFFEFHAHGHDAGADAEGBGHHBAAADCFHFDADFDH,False +101,21.0,23.0,9.0,23.0,25.0,21.0,22.0,21.0,EEEEEACAHEHDDADHFBFBAHGHGBGDGFECGBBBBFBFEFHFGFGFAEHDHAHAHBHGHFBBHGGGGGEHDDDDHEAFBHHDEFEHEDDGBCDCHBGDDFFCAHADEDEGEGEAABBEBDFGEBABCDFEACFDADAGAGEGBAFABHBDGDCEEEAFAFBFC,False +102,1.0,8.0,5.0,3.0,5.0,5.0,6.0,8.0,HCGCHDEBGFEFECBBBFBFGHGHGDGBAHCFCHHHEDEBB,False +103,29.0,22.0,27.0,17.0,23.0,16.0,31.0,26.0,GGHCFGEBEDGCCDEBFFFEFHGCDCBCBCECFCHCHCHGHCEGAGCECABHEEEBEBEGAGBBBABABFBHBHDHGGDADCCFAFEDECEABGBFAFHDAGHGHADEFGBDCHHDEDCHGABABFGDEAAAEBGAAEGGGGFGHAHDBDCCHGHBDGEGHGEAEACCHCACAHGHGHAHDCACAFAGAFA,False +104,7.0,6.0,18.0,7.0,11.0,12.0,24.0,18.0,GDGEHCGGGEFECEBECGCGHGCFHFHFHCDFDFGACHHHGBGHACDCGAGADBCAHECACGHGHBBCFGHEDEFEHGHBHGGCGCGCHCEGGDGEAFFHFCF,True +105,16.0,23.0,21.0,18.0,22.0,17.0,10.0,18.0,ACEGEHEHAFACDCDCHFBFBGBHDFFFCAGHBBBHBHFABABABAHEGCAEEEFGBGBADGEBCDEHEBCFCHBHEFEBDDDDDDDGFEDEFEHAHBCACACBDBDHDCBCEDEHEGCCFEEEDHHAABCFCHAECBCBFFCFG,False +106,9.0,10.0,12.0,6.0,8.0,7.0,13.0,7.0,FABABHCEGEGBGBGCCCHCAAABGEGDGFGFAFCBCGCEHDCCAGHDHCAEHFBFAGBGBGHFDCDBEEDE,False +107,17.0,15.0,17.0,17.0,16.0,26.0,15.0,17.0,EFBHGEAFDGCGFGFGDEEAEGBDEFBGGFAHHCAFAFHBHBDGDGEGEGDFFFDFHHHAHBCDADBCBFGFCBCBGBFEHADAHCECFCECHBFFFFCDEDEDCDEFEFCHHHCACAEBCGAAAAHADAFHFBDBCFDF,False +108,20.0,24.0,27.0,23.0,19.0,28.0,19.0,18.0,AFAEGFGFGAHFCFEHEGDBBBEBEBEBCDDDHDFGFDCDCECFAFAHAGBBBEBFDEBCBAHGFGAGABDBEAGFCCCBEBHCDBDFDFBBHCHGGCDCDFHEHECGCFFFADAHHHDCDAEEBFGAEHCDDGACACACFCBEFFHAGCCCCEFEFCABDBFFFGHCHDHDFDGBGA,False +109,9.0,16.0,17.0,17.0,16.0,16.0,12.0,24.0,EGDDDAHBEAEABDCEBFFHFHFHCDGHAHCCFDFDFDFBBEBFBFEHGHGDCFCGHGHGCBCEDHBCDHFHFBFGDGACCCGAEBHBABCHHEHBDDEHEDEDEGEAHDHCECFCFCBHAHEGBHH,False +110,5.0,7.0,7.0,3.0,11.0,14.0,10.0,14.0,AHEHDHGFEFGCHFGFBBCAEFEFEFECEHFHBHAHFCBGFABHBEDEGCGFDFACGCGBFEFGHHHHEHG,True +111,20.0,16.0,22.0,22.0,11.0,17.0,13.0,10.0,ACAFFCDCDCACBFAFGDAACDCDEDEFFCBHDGDCDGDEABFEAADDCAHHDHEGACEFBCBCACACABBHDHDHEHCAAFAFCDDEDFDFBFCFBFDEDFFGGAGCCBEBCBHBAGGGGGEGACBHBDB,False +112,26.0,22.0,28.0,29.0,20.0,26.0,21.0,19.0,GCDCBAEHEHGGFABGFFFFBDBDBHCHCHAAADGFCBCDCFFFDCHCECEDEAFBFEFEGGCDCDAEAECFCEEACCBABGFDABADAFHBHFEFEAHAEADFCFHHBHAHAGGDHCCCDHBCADABHBDCGHGAGAGDDDFCAGBCBDBCFCFEHEDEBGGFGFDBCGAGDCDEDGDBDBEFEHAFADD,False +113,4.0,0.0,3.0,3.0,1.0,0.0,3.0,3.0,HAHADDGDHAGAECCCG,True +114,15.0,25.0,14.0,19.0,17.0,16.0,17.0,18.0,GDGCHHEBEBHBEFAFEFBFHFBGHEFEFEBAAAGFGDDFDFDFDBDBDBABABDHCBGDHCEBBGBCBEBAGHCHBEBGHEHEHEACACACACBBGGFGHCHDGBCDGEFDFDBEHECDGBCEHAHDHACFGADFDBAGD,False +115,4.0,7.0,3.0,5.0,3.0,0.0,6.0,6.0,HGHBHBDBABACEGDGEAHBHADGEGCHCBDGDB,True +116,18.0,19.0,11.0,27.0,26.0,22.0,18.0,28.0,FDFEHEBGBGBCFDFDFBEGFABHCHEEFAFAFAFBDHEHEABBDCHCDDGEHEADAFAFBHHCHBFBEDHGHGBFDFGECHHABDEGECEDADEHEDCAHAGEBABCDCDAHEDEDEDFFFFFBFHGAFEGEGDHDHGHGHGEDHDGEGDAHABBHHDHBCDADHEGE,False +117,9.0,10.0,11.0,5.0,12.0,11.0,5.0,12.0,HFBFCFBAAEABGHCHAFABBBBCCCHCECECHCGEHEHEHFHAHCEDDFDCEEBFFFFGEBEAFAHDGBGDEHA,False +118,1.0,8.0,6.0,3.0,6.0,11.0,9.0,8.0,BEBFGFGFBFBGBCDFEHBHAGEFHGDEFBFHHCGCDBGFGFGHCHFHCECE,True +119,16.0,21.0,23.0,14.0,8.0,20.0,24.0,21.0,EEGFBBADAFCBHFACCCFCFEFDGAFHFDABHBCGHHHBHGHCHEGCAABBGDHBHBGFGCGCGCGHFEFCFGABAGGCGAGACFCBCBHBFCFADHDHGHGFDEBEGCGCDBHBEAACHDDFDCDCFBFBGGGGCBHDHDHFABA,False +120,23.0,16.0,16.0,25.0,12.0,20.0,24.0,21.0,DFHFBBDGFFEDCHEEGGGEEADAGAGDBDAABFDFCGDGAABABABABACAGGHDHFACECBDDFDHGHGHBCBCAGFGBGCFFFDFDCGHGDEEHBCDCBHBCFGFDFDHAGCHHHHHGAFADDHEHEAGAGAGHCBAEAEDCDADCFGFDHDHF,False +121,19.0,17.0,15.0,20.0,28.0,24.0,23.0,17.0,DCDFFGAAFFFBGAGDGCACHEHDADADFEHEGGFFEFAABBHGGGFHEHACACBEEEHBAGAGFDFEBEGEBECECDCHBHGDGBEFEAEAEAECCGCEHBHCFFGBDBDCDAEEEAEFFFBHAHGEDEBGFGFGHGBGBDFDCDHEHDDDEBAFDFEGCFH,False +122,24.0,21.0,31.0,19.0,20.0,33.0,21.0,17.0,CBDGEGCBFGFHFHFEFBDAECCCBCBGHDCCCAFADHDHDEDACBDBGAHABFDGEGCHEECECDAFBGBGBFFFFHEAECHFHFHGEEBCFCFDGEGFFFFGCDCGBGBGFFBFBFAAAAAFGBAFABECAGEGBGFHFCADDCECHFAFADAHFHEDEHCFBACAEAEFDCCCCCBCHDADCG,False +123,23.0,22.0,33.0,26.0,18.0,14.0,26.0,19.0,DGDGCACABHFCADADGHGEEHGACAHAGACEDEDEDGDFCHDECFCBCGHGECHCHBEEDEDEDEDCBGBGBABCBCBHAGDGECAGDCCCFCDCFHFDABECGBGFHBBFBEBEBACEDBHHCCGCDAGGGFCCCGDDFCBCBGBGHGHGCBADHFFAHDGAAAAABAFDHDHCFCEAD,False +124,14.0,14.0,13.0,14.0,9.0,17.0,19.0,18.0,DCBFBFAFAHBHGFBABECACGGBGCGCFAFHHDGDGEBDADFFHHHHDAABHFFEGAGFDBGHGAGBGHFHFGCHCDGEGEFCGDGDCDCDCECBFAFCFHAHEBEGHBEBHHADAD,False +125,22.0,17.0,18.0,14.0,19.0,23.0,19.0,20.0,AFFEGCACEHAHBHFHECADBDEDHDHDACHCBCBHFDDAGHGHCECEAEAHBHGGCEAFAFBDGFFFFBAGAFAFHHCGDFFAEBBABADADBCGHHHGACACFCFDFBCGHGEGEGBGBCBEEAFHEBBGGECEFECEHGGEAFDFDFAF,False +126,2.0,2.0,5.0,1.0,2.0,0.0,0.0,0.0,CBABCCCECEAD,True +127,9.0,13.0,13.0,20.0,8.0,15.0,15.0,18.0,GGEFDFEHDHDHBAGABBBFFHFCFHGHGHGHGDADHDEDFCEDAGAGCBDFDHDHCBCDFDBHFHGHFBCGDDDDDABGHDHCHAAECFBDBEBCBCEGECCFFHCGAGF,False +128,26.0,16.0,20.0,13.0,15.0,14.0,8.0,14.0,AFAFGCBFDCCGCBCACACAFACECBAFAFDBBABABHECBGAHADEDCBADABABAHEHCHCHGECDHDHBHBAEDEAEAHBGFAHBBCACACAFEDCAHHEADGEGECEFFFCGHDFDEAEFFD,False +129,3.0,2.0,3.0,1.0,2.0,1.0,0.0,1.0,AHABFBEAECCDC,True +130,3.0,10.0,5.0,11.0,10.0,4.0,3.0,9.0,DBGBHBAEDEBCCEBAAFHHDHDCBEDHBHBHBDECECEDDDFDGDFBEGEHEHF,True +131,18.0,19.0,23.0,22.0,20.0,20.0,15.0,23.0,FGBCAABCBCDCDCBBAAADCEGHAFDFEBHBHAHGDAEAEAHGECHCDDFDBEBHHHDBCFCABFHHHABFHHEGEHBAFAFCDCHGEGEFBFEFEDEHCHCHDHDGFAFEBEBGBGFCDCAEDEGFFFHFBEAGACFDDDDHDCCCCDCDGEGBGCEH,False +132,27.0,13.0,16.0,13.0,20.0,12.0,27.0,15.0,HAACDHGHEBFFCDAGADAEABAGHFHDHCCAEHFHBGBECGGGGAGABACDEDCACACFGFGFHBBEBHGGGDABGGGEDECEAEAEAFCEGBBBAGAEAEABHEAEGGGCEHFHDGAGEDEDFDHDEAAGAHAFFGCCCCG,False +133,5.0,7.0,9.0,1.0,6.0,7.0,8.0,7.0,BGCFEBHHHHACABFBFHFCFGGGCCECGCGCHAEBBHFGCGDAEAEBEF,False +134,14.0,15.0,11.0,16.0,21.0,17.0,16.0,20.0,HBHDHFHDDEFEGEFEBGDFDFBBHBAGEGCFHBHDADHHFAFAHECEFADECEDDDBDBDACBEAFHFHGEGCGDECECBAGACHBHGHFHFHGEGFFHEHCHCEGEGEAEGDGEABDBABFFGECABA,False +135,8.0,3.0,1.0,2.0,4.0,6.0,9.0,3.0,GFGEGHGFEFGCGDBAHAFDEAEGBGBAAAFAGAHF,True +136,14.0,29.0,20.0,23.0,25.0,22.0,18.0,18.0,DGDCEBGFHDBFBECHFEFBDEDCACGCGHEFEFEFAFGGGDCFGFHFHAHADEBBCBCEEEFEBABCBEBACACBHHCFCEAEAGBGDCDBDEDGBACECBHEHBDGDFDGCGAFEFDBHBEBEAHGFCFBFBHEDFDGDBBBBACDBDHGBEAEGFCHBHEHDHDFD,False +137,3.0,5.0,1.0,6.0,8.0,6.0,3.0,5.0,FDFDBBBEDEHEHEFEACFFGDHDFGBHAEAEBEGDH,True +138,17.0,19.0,28.0,23.0,19.0,29.0,14.0,27.0,EEHFCDHDHBAADFECECFFFCDGBAHAHFHBCDDFDGDADBCAAHABAEGFHFHDHDEGCGHGHCFDFEFGBHAHBCBABEEECDCDEHFHFBABHCCCACHEACHDGDFHFHBHFGDGDGDFBCDCGABFFDFECHCFFFHFCDGEFCACHCHCHEGACFCFBFEEECEBBBBD,False +139,18.0,10.0,15.0,7.0,19.0,9.0,15.0,15.0,BCDGAGEBBAAFCBEFDFHCAAHABFEADAHGCCCACEDEDEDEDEHCBCFEHCHEACACHGGGGBGEGFGFEHECGFEAHGHEHEHEHACAFBGGABABHGHEAEAC,False +140,12.0,11.0,10.0,15.0,15.0,9.0,10.0,21.0,GGDEDEDHDABGBDCAFADADEEFHFEEBBAHECFCAHGHGHEBBCBABAFHHHHAFADHECEGGBGECECHBHECFCDDDEEHHHHHDHDHDHFACGDABFG,False +141,6.0,7.0,16.0,10.0,19.0,4.0,7.0,3.0,GAGEECEDBGBGFCFCHCFBDBDECEAEDBDCHBEEFAHAEAEGCBCEADDDDEGCCEEEECCCECDCGCEE,True +142,17.0,14.0,17.0,18.0,21.0,18.0,15.0,9.0,BADAGADHDGDGFHFAFDFGEEDDDADCCCGGECCCGEHAHAHEEEEAECFCDHDFABABFBGBCACEFFDADAEEHBHFDFCBEBGHGCFCDAGFDBEFFGFGEGCBAEDEBCBAACDCBEBEFEFEG,False +143,1.0,3.0,4.0,4.0,2.0,3.0,3.0,3.0,DHDCCGCGAGHBBFEFCFDHDEB,False +144,3.0,1.0,7.0,1.0,1.0,3.0,7.0,2.0,CDCFHGGFBCCCCGAGAGAEHFGCG,True +145,3.0,5.0,7.0,4.0,3.0,11.0,6.0,3.0,DHGEGBGBGCCFDFAFHCBEBEBDFCFCFGFCCAHFFFDGAF,True +146,4.0,13.0,6.0,8.0,6.0,15.0,9.0,3.0,FABGBGFGFDBBBCGEEEEBFGCBFBDBCFDFGFGFAFECCDDADAFBDGHGBFBFHFEFHCBD,True +147,16.0,16.0,22.0,23.0,21.0,20.0,35.0,29.0,FBFEECGAGFGFGHDHDFAGEGEHFHFHFEGHGCEEAHDGDEHEGEFHFCFHGHBECDBDBHHGGGGGGCBHAHACAHAGEBDCEAGGHGHGEGEBDAHHHCHADGCFBFHGBGCHDFDFDGHCBCHHAGBEBDACHCFFGGGDADEEAGCEDEDCCCGDFDBDGFBFBGBDEACACDCDCH,False +148,16.0,20.0,20.0,23.0,21.0,16.0,31.0,18.0,EBEHGGGHCACFDDDDDAFCHEGCACFCFDFAGADEGGGAGEECEGEGEGAFFDCBHBHDHEGCDCGBGBGCCCCCBDGEBCGFHCHGHAHBBCEGEGEBFBGAHABDBDAGAGFGBEEEFEDGDAFCHBABGBADADEGFFDHDCFGGDHBFBDEDEDGHHHBH,False +149,3.0,7.0,4.0,6.0,10.0,7.0,3.0,5.0,EBEHEBEDCFCBBADCHFHFGBGBDEEEECHBDADADEFFFGFHE,False +150,6.0,2.0,7.0,6.0,2.0,3.0,8.0,0.0,DDDCGCADFDFGGGACACAGBECGGDGABACFCE,True +151,5.0,2.0,2.0,0.0,5.0,4.0,2.0,3.0,GAGAFBFEFECEFHABAEHEACH,True +152,14.0,12.0,9.0,7.0,12.0,11.0,10.0,17.0,FDHDFEHDHCFCBCDGHGCFFFBFHACCHBGAGAHEHEBEAADAHBGBFBFBABABAHAHEEAFHEHBHEHABGGECDCECEAGDHAHEFGG,False +153,19.0,24.0,27.0,19.0,23.0,23.0,26.0,24.0,CDCGGGFAAGACHFHDHDHBBCCHCGFAHABGBEDHBGBGBABADECFFFFAGGCHDDGDGCGHGHGDCFHDHAFEFEFEHDCCGGBGEGAAFCEEDFDFGBEAFHFCGEBCBHBFBDCDGBCBEHADABCHCHEHEHBHDGFGAGEGBBEBHDEEHAHAEAECCFFFCCCECECEFBFBDECBA,False +154,13.0,10.0,11.0,9.0,11.0,8.0,12.0,4.0,GEAEAFAGADADAEFCGCGCGCAFBFBEECEGADADACBGBCHHBFEECACBEHEFBFBDADEDBCGGGBDFHCAGGD,False +155,23.0,15.0,20.0,21.0,22.0,13.0,16.0,23.0,FEBEBEBFDHDHCCDDBCBEGFDFGBHCHFDAEBCBFHAHGHDADCBGDHDHDFCAHHHDBCEHDFDAAECDCDCBCAFEEEEEAEAGACHCEGEAEGGGGAEABAFAFHHGEAAACHFHAHFGEAEDEDEDADHDBCGAGACBCHHBGGCHC,False +156,1.0,2.0,8.0,2.0,1.0,1.0,0.0,3.0,CCCCCHCHBACDCBHEDF,True +157,11.0,6.0,5.0,14.0,10.0,10.0,2.0,6.0,EFAHAHFBFGGABADFCBEDEDADAHAFAHBFEDEDCDEDEDEDFFCBEDFDFBACDDAEHCHA,True +158,15.0,22.0,16.0,16.0,9.0,21.0,17.0,9.0,CFCFCAEBDGDHBBFBHCAAGFFFAGGGGFGHCHDBDBECECECFHBBCBAFHFDFBCACHCAAAEFDBDBCFGAADADAGGBBBGCGBGCFBEEGHGFGFDFDFABABDFHFDBDCEFEBGDDB,False +159,3.0,6.0,10.0,6.0,2.0,3.0,4.0,5.0,GGGFDFDBCBHBHBCCHCBCEHHFCACDCBEDDDACGCA,True +160,7.0,12.0,7.0,6.0,6.0,8.0,8.0,5.0,AEFEFEBCBADCEFHHCHGBBECAABFBFBDBGBHECGDADADGBGAHFFCFCGDGBGB,False +161,25.0,18.0,13.0,27.0,15.0,21.0,17.0,28.0,HFHGDDBDFDGHGADHGFBHGCFDAECCHHEFEFEDDBEBAHAHFHFBFHAHDFDFAEDFBBCEHADGFGAHDGDGDGDFCBCEAEBCBHDHDHAHAEADHHFHFHEGBHEDABABACDCAEFDDGFGAGABAHDHDGDGDBHBFAABAGAECECHCACBFAFH,False +162,18.0,23.0,16.0,12.0,17.0,23.0,24.0,31.0,AEABABCBCHCHCFFFBHHEGBABDDDDDHHFHEECFCFCBEDDBHBHBCGHDFAFHCHFGCHHHHHHHCFGFGEHDBAAEGGHEBBHGDAHFHBHBECGFAFBGCAHEHGBBFBDCHHGEAEHGFFFADGEGBGBGCGFFCHGEGEGAGAFABABAEAEGFGF,False +163,24.0,23.0,17.0,16.0,25.0,31.0,34.0,30.0,FHFHFEFGFBAEHHHDHDHFGGDGDGFGDHACAFGDGDECECHCGAHAHBBBBBFFFCGBGEFFHFEAECGGBBAGABABAFHFHECGDECFCHDBACDEHBFBHBFEFDDGCHBHGHGHBEAGFGCEHFBAHACEHEACFCFEAEGEGAGACFEAEBGGFDBDBGEGECEAHHHAGBGHAFDFAFDFGBGHGFGAGHEE,False +164,16.0,17.0,19.0,27.0,19.0,29.0,35.0,19.0,GDGBCCGCAFBFGFDHGHBFAFGFGDDECECDGDCDFHFGFCFHFEABACFHFBFHEEECEDFDEDGGGDGCCBBDBFBABFBGDEDEGBHBDDDGGGGCFHFGFGFHFEABBDCDCHCGGGDGFGEDADHDECEAGAFAHEHADAFFGGGCABEGHCAEFGFGAGDDHDHBCEHGAEHFH,False +165,10.0,7.0,7.0,12.0,6.0,6.0,5.0,8.0,DGFFDCDCDAEGDBDCEBGACECHCECDBABDEAHDHGAAHHHFHFBFBGBHDADADAFAE,False +166,17.0,18.0,17.0,16.0,20.0,19.0,17.0,15.0,CACAHAFBDAAADADHBGFAFDGDGDGHHFHFGFGFHHCAAEBFBFCFAHEBABEEGEGEGEBAHGDCDGEBCHEGDGCFCEEFECBCFHBHBHBADDFBFBGDCBCFFEGCAEGEFBACDCECECFDDADEEEGHBHB,False +167,15.0,4.0,11.0,15.0,21.0,12.0,17.0,17.0,HHAHDEDGHFHEHCHGFGFCECEGEACFGDGDCDCHADCEHEGGAEEBEBFHHHCHCHCFDAHAGDGFGDDHEEGCAEDEABAEGEGHGDDFAAEFGAGAEAFAFDFEEBED,False +168,8.0,4.0,9.0,2.0,9.0,7.0,3.0,7.0,ECECBCHFHCGFGFEEEHEHECAAHAFFBAEAFHBGAEAHDBDACCCFC,True +169,16.0,14.0,9.0,11.0,11.0,11.0,12.0,11.0,DFDFDGAGAGAGFGHHACBHBHGFFDFGBCEAHBDAEADACCECAAEABBHEAEAEDEDCABABCBGGGGFFACHHBDBFFDFEEGBCDHEHBHB,False +170,4.0,2.0,1.0,1.0,6.0,4.0,5.0,2.0,GGDBEEEEBEAGFFCFGFHAHAEAG,True +171,28.0,14.0,20.0,10.0,8.0,25.0,20.0,36.0,HCHCDCGCDAGAGHGBABAFAFCFAFDFGFGEGHFEFHBHGFGCHEHABFGFHHHCFDACHEFBHHHCHAHGBAADCHBHBFAAAHHHFEGCGDAHAGFBFAADAEACFFGAEAGABFCHCBFDEAGAHBHBAAHHHFHFHCCACGHGHDHDHCHCFCBGF,True +172,3.0,11.0,4.0,4.0,5.0,7.0,5.0,5.0,BBBEBHHCCFEFGFGHGBBBGBDFAFACEHFGFHDBDBABCDEE,False +173,8.0,13.0,6.0,15.0,4.0,10.0,15.0,7.0,ACDCGBGFFFGEGBGFHBHDADHDFGBGBGHCDAGGGCHDHGADDDDDDEBBHBFBFGFAEADGCCBDBDGAAEFBFB,True +174,10.0,11.0,8.0,10.0,13.0,7.0,14.0,11.0,GCGCGCGFGEBCAAEEHEAEHDHDGAADADADFBEDECHCGGGHGEEHBHAHABFBEBHFADGDHEECHBBFBGEGBGDCFBFD,False +175,23.0,12.0,12.0,24.0,26.0,34.0,26.0,24.0,CDBFHAHBGAAFEGHAFGCAFGFGBGBEBEAFGDGDFDADCFGEGBFCHABFCGADHFFEFHFEFEFEDHFGCGEGEAABEGAGHGEAFAFAFCFAEDEDEDHDHDHFFFGFHACEFHHHDHDAGFDFGEGBGDHDBABAFEEEHEBGFGEEAEAHHFDDDGHGHDFCFCACHDDEDEFHC,False +176,18.0,8.0,20.0,16.0,15.0,17.0,11.0,11.0,FCFBECGAFAFABAEEEEDCDAECEDGAAADFHBDBECEHEABABCDCHBGEHAHAGAECHHHADCCCCFCDCDAGCFFEEAFAFGDDFHFHFHDBGGDGDADFGCECFCGCDCFF,False +177,13.0,12.0,13.0,12.0,6.0,11.0,5.0,9.0,DABFHGHCBDBDCFFGABAFEBACAHECGDFFHFHFDFEFCHCBCBAECGCGCHEAEADDDBDADAHHBACABACDCDBFB,False +178,7.0,14.0,10.0,12.0,19.0,22.0,10.0,9.0,FDECFBFDFDFHFGCEDEDEFHGBACCEGGAEBEGABFDFDFCHGHFFEDBFBFBFEGEHADAEFEFEFEABCFHDHDAECFCGBFBGBFBEECECDBEBHGH,False +179,2.0,2.0,2.0,1.0,5.0,4.0,1.0,6.0,HGFEHEHEFEDAFHFEABBCHCH,True +180,2.0,5.0,1.0,3.0,3.0,4.0,0.0,0.0,FAADBBBBEBEFEFDDCF,True +181,6.0,7.0,5.0,2.0,1.0,4.0,3.0,6.0,BHBDBAAGAHCHFHACAHEHBBBFCFCACGGDBF,True +182,2.0,3.0,10.0,6.0,8.0,6.0,4.0,4.0,BCBCECEAEDEDHCCCCHEHEGDGCFFFAHGBFFFECDDECGD,True +183,27.0,20.0,35.0,20.0,19.0,18.0,17.0,19.0,CHCHCFCBDEHBHEHCCCCBDBAADFFECCGCAEAFAHCFGDGAGACABFEAHCBDBDBDACGDEDEDEHEBGDGDCAGABEBEAECEGAGFGCABFGFCEAEAGACFCDCFFGFEHBDBDECACAFHBHCHBHBFAHDBCADHEHACAGDDDGCEBFBFCCCCGAHCFCACAHH,False +184,21.0,29.0,29.0,14.0,13.0,23.0,22.0,20.0,HBBEFAHAHDHCHCGCBCAFABDDHDFAAADBDBEBCBCBEACGCGFFBFAFHGHFCFEHCHDADFCFCEDBGBCCFCFGFHCHCACBEAFBECFCDAGGCGFGHGFGEGACCDCBHBACGFGFHFBFGEGBCHCBCDEBBCHGGBGBDDFAAAEBEBABHBABHGEGBHA,False +185,16.0,21.0,7.0,5.0,16.0,12.0,3.0,15.0,BBBHGHBACDBEAAAFDHEHAGAGAEEEHHCAEAFBBABFBCECAFAFBFHFEDABBBFBEBEBEBACHFHFHDHBFEAEBHAFCHEDECEHBHB,True +186,26.0,34.0,20.0,22.0,24.0,21.0,26.0,17.0,HFACACHCBBBBHBGBEHFHFEAHAEAEFDBHECAHAHDDBGEDCBEGGFGECAAADBEBGCGCFCFCFBFBFBAGCBBABEHGCGCGFGBBCHCEDAHBCEAEHDBAHGGDDDDHEADDDDDFFGBGAGBGBEBABDBDGDGBFBDBDBDHEFEFCFEAAFGEBCGEGBFFGCGAABAGCHEEEAFAEA,False +187,3.0,5.0,0.0,1.0,1.0,2.0,2.0,4.0,DEBGHGAFBFHHBHBABA,True +188,8.0,11.0,10.0,11.0,8.0,19.0,14.0,12.0,HGFBFHFBFGGAHDDEBAHFHFHFCEGFGFGFGBGEGBCEEAFDBBBHFHDBDBGACHCHFGCGFGCGFBCDCDFFAEAHAEFDFDHAECDCD,False +189,24.0,32.0,23.0,32.0,21.0,21.0,20.0,22.0,BBBABAEECDDDEDEHEBECEDEDHHHFHFDFHCDAHAHDBGBGEGFGFGFGFBAGCGDFBFHDHBBCHGHGFAEBEDCAAGFDDADADBDCFGHBABDHECBDBAAHADAGCDCBABABGBHDCGCBCGFEBDCHAHCCCFCFEBABHDDBGBHHCCCGBABDBCEEGHAFEFEDDBAFFFDFDCEAEAEGDBD,False +190,13.0,10.0,11.0,9.0,7.0,16.0,9.0,11.0,AGCHAGCBAHCBGBEBEACADADHDBFBDDAGEFCFCBHDEFEFHFHGHDFGFACAEFHAEAGGBGFCFCFHFDFCFCBBFDAHAH,False +191,14.0,3.0,6.0,9.0,14.0,7.0,4.0,6.0,EAEFDGEEFCCCFCFEAAAEADCDAEAEGGAFHHHHEAAADADEFEBDBAEGECEADFDHDHB,True +192,6.0,4.0,7.0,3.0,3.0,3.0,1.0,4.0,CFGEHCCFCBCEAEHCHDADADABBBACAFH,True +193,29.0,36.0,21.0,12.0,18.0,14.0,23.0,24.0,BBHFFFCEHEGEHDHBGBHBHDEBHBHBEAEBDBFHFHEHABADACGGGADBBHHFBBBAAAAABECDCACHCAGACFCFAEAFAFAGGDAEBDBHBEBGACBHFAFGFGBBCAGGBGHDCBBDGEHEGEACACACEBEBCACAEGDGHCBDGHGHBBABCCHCHCHGBAEAGBFBG,False +194,6.0,3.0,5.0,1.0,2.0,4.0,8.0,5.0,HBHGGFCFCACAEABGEACDCHBGGHGAGAFHFG,True +195,3.0,6.0,4.0,7.0,9.0,15.0,5.0,10.0,HAHEHFGFHHGHGFFCFCEDEFEDBGBDEDACBDFHEBFHFHFEFDFCFDFABEBGHFE,True +196,2.0,2.0,8.0,2.0,3.0,5.0,4.0,4.0,CCECHCDCDCEBHCGEHBHGAAFFFFGFGC,True +197,0.0,3.0,4.0,2.0,1.0,2.0,3.0,2.0,DBHBDFCCCGCGBGEFH,True +198,9.0,8.0,9.0,4.0,11.0,7.0,12.0,11.0,AAAFADHGGGFGCBCBCHEGEFEHDCABDHGEGEGDACBFHFBEBGBECEHAHAHGBECFCGEGAHEHCHF,False +199,9.0,8.0,10.0,11.0,7.0,10.0,5.0,6.0,ACADDFDHDABGCDEBEHAFFBECECDBBABAFAFAEAFHDDDHCCDCGCGHGDGHFCBCBFFEFE,False +200,15.0,9.0,5.0,13.0,12.0,23.0,15.0,22.0,CHGFEHBDGDHEHAHDFDFAEBDAHEFEFEGGGGAAAGEDAHGHGHECEGFGFGAGBFEFAFBFBGBDFAFHDHBHFHFHGDEDHFFCFEDBDHFFFAAHBHAHFCFDHHCHAA,False +201,8.0,4.0,6.0,6.0,2.0,3.0,2.0,2.0,AGCFBBCBCDAHABACEHDADADCDADAEFGFC,True +202,15.0,30.0,30.0,30.0,15.0,29.0,25.0,23.0,DFBBDGHBCEDBFBHBHBCBHEGGGEBEBHHEHCFFHFGBHEGBDFDFGBGDFDFHCEFHCGCFDHDFDEHADADEBCFEFDFEFECDAAHFGDDDCACACACACDBABGGEDAABBBGCACABFBGDCDAGGGGDCDFFFGFCBBBDBDHECGHGDGCGCHCHFBFHHHDHCEBFDFDFCFCGCBCBCFCDABHCG,False +203,14.0,19.0,19.0,3.0,12.0,14.0,16.0,22.0,CHAEADAHBHBHBHBGGDBHFHEAAABCBGEFCCHFEBHCHABABFHCCCHBHAGAFCFBFAAAHCFCGEGEHEHEHFHBHEGFGHBEGGGCCFGFGCDAECGCBBGBFBCHCHCGBFE,False +204,9.0,15.0,19.0,11.0,9.0,19.0,20.0,15.0,FAAACCHEGCGDGBHDCCCEBAHDGDFDBDBHCFGFCFCBCBFGFGHGBFBHHHFHEGBGBCAEBCCCFCFCHGAEFEAGCDHGHGFGFGCGBGBGFDACEBFDFDEHEDGHABFHF,False +205,20.0,16.0,16.0,34.0,30.0,20.0,29.0,29.0,CDCFGDGDEFHGHEHEGGBGBGBHBGEFECDCEBGDAHGCBDDGDHDHEBEDDDDHAFAFDEGCHEGFHFADBEEGAGDGDHFHBDEAEAHAHDDDECGBADEHEFEFDACAGEGFGBDEDECHHHEAEFFBADDDDAEAHHDHDCCFCAAAHCFCFEGHHHHGBGBDCHCHDFDGGEGBFBGHFAFEGEGEAE,False +206,20.0,18.0,16.0,14.0,21.0,4.0,6.0,11.0,ABABAFADEDBAECHGDDAAHEBBDBACECGAAAACHEFEBCDHGBCECECEBEFEAECBCEHEDGAHACADAHACECGDDEEECEHHHFECBCBEBHBDBDBDBAGDBA,True +207,1.0,3.0,2.0,6.0,1.0,4.0,1.0,1.0,FCADBDBGBFEFDFHCDDD,True +208,5.0,3.0,5.0,6.0,4.0,0.0,1.0,2.0,DCCBCDCDCAAAAHDHBGAEEDBDEE,True +209,9.0,6.0,7.0,6.0,5.0,8.0,3.0,2.0,FCFEAEGDADABCBCFGAGCFAFABABCBDHCFDFEFEACBDHEAD,False +210,21.0,21.0,15.0,16.0,11.0,15.0,20.0,12.0,CACFFACCCEHFDBGBGBFHFAGDGDADACGGDGBAACABBECECEGEDHDHCABDFDFDAGHGHGBGBFBGEGBFDFAGAEHFDAHEGABABFGAGEBCCGCHBDEDGBCACFBFAFHDBEBHBABADAH,False +211,10.0,24.0,13.0,13.0,14.0,11.0,16.0,23.0,EDEABACHGHAEGGBBBBECECEBBBAHGHGHCBCECDCBFBHBHFHFHFBBDAGFEBHAHDHGCFAGABCDDBEBEDHGHBCCACFDDBAHHHGBGBGEGEGHGFEFHHHDDBBCDEFGFHDH,False +212,19.0,7.0,17.0,13.0,17.0,11.0,21.0,24.0,FGCAHAHFGEHAAAAAHGDGHGFEEGDHHAEAEDCDFGBGDHDGFECECGGEEHGHGHCFBBHBFEEHGHGHDHFHDHDAAAHDECAAACBCECACAHFDFCCCCCCGGGGGEEEDHBHEFCGDHAHAB,False +213,10.0,20.0,7.0,7.0,13.0,11.0,10.0,5.0,HACBEBEBAGEEHEDAFABBFEEEBGBGBGBAAEBBDDFDFDFHCHDDAFECHBBAFAGGGFAFCGBEBEBEGGBFFCBCBCB,False +214,6.0,9.0,11.0,6.0,13.0,4.0,11.0,19.0,ECECBCFDGEGBHEDDHGEBHHGCGCBHHHHHEHEGACABADHFFGCGBGHDDCEEEEBEFHAECBCHGHGHBHAHAHC,True +215,3.0,0.0,0.0,3.0,3.0,2.0,6.0,5.0,HDFDHEHGGGGHAHAEGEAFDG,True +216,1.0,8.0,11.0,12.0,14.0,8.0,9.0,12.0,GEBDBDCCADDBGFGFEEGEGCDCEFEGEBEDCCFBHCEDDGEHEHDDFCHHHBHBHBCDFDEGEGCHCHEHFHF,False +217,10.0,10.0,22.0,13.0,14.0,8.0,15.0,10.0,DCHGECECEAGHEFGACFBGBECGCAEBEHHAGEGFDFDFHEDDCDBFBABACDDHDBDGCCCGHGACFCFDGCGCBCBGAGACECACBCECGDHEHEHECD,False +218,7.0,10.0,14.0,5.0,9.0,7.0,7.0,16.0,CFCECECDHHHHHHHHBBBHEFCCEBDBABAGDFDHCHGACCHCHEFEGHGDACFBGBCEEEFGHGFCBCHAAAB,False +219,15.0,20.0,16.0,12.0,13.0,12.0,14.0,14.0,AGAEAEAHGHFBFEHBHFGGEEHCFCDADACBDBFBCBFGFBBBCCAEGDGFAACAHBCBCDAFHFHECAFFEGEBCBGGCDCDCDEBBDBDBHHHHHDGAGDCHCAGEGABBEBE,False +220,0.0,1.0,1.0,0.0,3.0,3.0,1.0,3.0,HEHEHFFFGCBE,True +221,4.0,7.0,18.0,11.0,9.0,20.0,14.0,16.0,GGGBFCCCFBFDGCFCFDFHFHCDCDHHHGHFDCAGHCBAEEFEFEFHAEFCHCGEFCCCHCHEHCDCDAGBGBGCDDFDFGFHEHDHFGEGFHFGFBB,True +222,19.0,32.0,14.0,24.0,24.0,23.0,30.0,29.0,EAEAGFDFDCBHFAFADGBHBDAGCDEABDFGEEFFFEEAECHDHBHDGAHHGBGBGBGHCDFDBDBDEDADHFFAFEFGBHBGDCHEDABGBEBCDCHCBFAFBGBAHFHFGEDFHHHBBBBDBDBDBGEGBHEACCHEGEGEDEHECGHGFBHGHCBGAGHGHGEGEGEHAHAHFCCEFHFAGBGBGDADFBB,False +223,6.0,4.0,7.0,6.0,14.0,14.0,8.0,15.0,CEEFAGEBDFAHHDHFAFAHBFFHFCFEHHHHFDEGEGEDEDGAGHDFGBGBEFGFHHCHCHEHECFCACEEFE,True +224,11.0,10.0,13.0,13.0,21.0,14.0,25.0,19.0,CGBAEGEGEHHCGGHGCCBCAEBEGHCHDFDFDFEGBDFDFEFAGDGAGEGCGBHEEGCGBEEGEADACECABEDCDFFFDCAGAGHFHAHGEGEGEGBGBGHHHHHHDABCEDHHFFDHEHEGFF,False +225,6.0,19.0,5.0,11.0,12.0,6.0,9.0,5.0,GBHBDBABHBCBDEDBGBGBEBEBCCFDHDFEBBDDEAEAEAECFGFGEGABCFGBBDHDEFBGBGEEABHDD,True +226,11.0,18.0,23.0,14.0,12.0,26.0,20.0,26.0,EFEFEFGDCDFBHBHADECHHEHEFGFGHCBGACBGACFDFGFCFGFCCCHHHBHFHFHDADFFEBGFFFFFDBCCFCFHFCDGEHDFDBDCAGGHHHHHHBACGCGAGBGHAAAFFCHGBGCADGBBBCGDHEBEBEBEBHCHDHCCCG,False +227,23.0,20.0,28.0,18.0,25.0,23.0,23.0,21.0,FCCBCEFEDAGGBEHCHCHAFCCADFFHFEFAHCHDGCCHAEDEDFDGAGAGAGEFEBEBHHEFEFHFCGDFBGBDHAHBGAHFFFBFCDDADCDEEAGABHBHGHCHCABADABCHCHCDFGHGHBAFFEGECBGADCECGCGCBFEFDFCGCGDEECAGAEAGAGBBBBBCEEAEDECE,False +228,5.0,3.0,9.0,5.0,8.0,2.0,3.0,5.0,DDDACEHGFBCEAECCCCCFCEHEHEHEBCDAEBDHAGAG,True +229,15.0,19.0,18.0,23.0,23.0,15.0,10.0,23.0,HHFHGHEBFHHBCBDEEHCBGBAHAEDEDCGCGEBBDDDDEDBDHDFDEDACCEEDFCEEECBCBCBCDAFEHCFAHBEDACAGHHHHHHHAHGFACACAFBEBEFFFFFDEBEAEGCBEEDADACBHGCGBGDHDHDFDHDEABF,False +230,15.0,10.0,14.0,14.0,7.0,9.0,3.0,6.0,EDADBFADCDCDEBFBFAFEFEDCBADFBFBAHACCBCGEHEHBCCAGDCFFBAAABAGACHCHDDCCCEDHDADADA,True +231,21.0,19.0,19.0,16.0,21.0,13.0,13.0,23.0,EHBFBHBCDAEACABABEHCAAAAAEBDHDCECACAHGFCFBFBDCCBDBDECHCGCAAHHDDCDCDEEHHHADAFBFGFGDGFGHGAGEEFEHBBDBGHAHGHEBCCACACGEDEAABDBCEDEFEHBHEEEHGHFHEHFFGHB,False +232,10.0,11.0,13.0,7.0,8.0,12.0,12.0,9.0,EFGGGHCHBAEHFDFEADAHBBFBCGFGBCBCBCFHFAFAGCGCEBEDCCCHCHDGGGCGCADFEBEBDAFAFAHEFGBHDA,False +233,16.0,18.0,26.0,21.0,12.0,11.0,22.0,9.0,GBGCHBGDHEHDGAFCFCGCBBDDDHHGCEDEDCDBGBEBCCCCDBGBCACBGGEHEDGGAGACFCFCHCGGDGABDCCCGDBDEDEBBCHCDCDBDAGECECAFEFBFEAGAFAGBGAGDDDACAFAFAFCHBA,False +234,8.0,5.0,2.0,10.0,3.0,5.0,9.0,5.0,GAGBBEDFDFDBDGDAEADHGAGHBDGDFDFCGAGACABAGHHHFED,True +235,28.0,16.0,21.0,19.0,24.0,21.0,12.0,20.0,EDHFBEAFADABHFHFCFHFACCBBBHAHDHBADGDBCBDFEFDHHADACBHBEAEDDDGAGACAEHECFCECHHHEABFCFEEHGAFFFADADCDGEEEGEBECEBBCACAHAHADADFFAFAFHGDEEFEBCGCGCGCDCAHBGEEFGADECECAFAHA,False +236,13.0,6.0,14.0,8.0,9.0,13.0,7.0,14.0,FCFAFAFAHAHCDCDGFFEFECEDBCECDCFHEEFAFACHCHCEBGDHEHFHAHBHDHFCGGAGDHHACCBHDCGFGBAAEABA,False +237,4.0,7.0,4.0,12.0,6.0,4.0,7.0,10.0,DGGHBHDDDGDGCGCGADBHEDEDAGFCFEBDHDEBAHAFEHEHCHDBDBHFHB,False +238,25.0,27.0,17.0,20.0,11.0,20.0,27.0,24.0,BGGGHACECEFEAEDBDBHCGDGDHDHBHBHAHAHFBFGCGCAHFHABABEFFDDAAFHFHDAGADFDGBACCCHGHDAACHCHGBEBCCCBDAFAEGHAHGHGEDBDBCBHBGFEAGAGBGBABDHDGAGADFBFGFGCAEBGFFEHBBGDGBBBFFHFBFCDAGCGHDA,False +239,27.0,19.0,14.0,12.0,26.0,20.0,17.0,18.0,CACHFHBABHBABAHEGBDDEBFAFAEACABAFAHAHGHDFEGEFEBEBEAFCDCHABAGEGEDFBGBACAFDCDCAEHEHFHFEEEFABABCGEEEGHDHAHBHDFGEGBAAAFDHECEAGCGEBEDCDHFAFAGAGBGFFCGCEHGFEBEF,False +240,13.0,5.0,13.0,8.0,10.0,9.0,13.0,11.0,HCHAGAEFGBGAGFGCDCAGAECGCGEFEDHGFADADACHDFDGBCBCFEDEFEFBAHHHHHHAAFGCECACBCGEHEADCG,False +241,15.0,13.0,22.0,21.0,14.0,24.0,13.0,15.0,CECEBACABEFHFGBEFDCDBABGDAEADCDHGFGFDDDFDFDFGFEFGCGEAHGHGHCFCDABFEHHABCECBCHFHCACFBFBHBADFEFEFDFDHDHCHCDEDAGGECHAFDHCABFCFDFDGBGCFCACDCEA,False +242,10.0,3.0,9.0,4.0,10.0,22.0,6.0,6.0,CBAAFFFFGBDAFFFFFFFDGAGEHFGECEFEFHCHCEEEDCFAFAHAFBDEHGHCFEFCFCFEAAFAGC,True +243,16.0,18.0,13.0,25.0,8.0,14.0,16.0,17.0,CFHGHAFGFCFEDAGEBBFDGBGHDHAHBGBGBDCHHEBDBDBDCDHDHFAGGHGHABADDCDFBHAGDDDBCACECAGEGDDHDFDFHFHCGCGCDBAFAFDBDEFEACADADADBCFAHBHGEBB,False +244,14.0,10.0,26.0,18.0,17.0,28.0,19.0,21.0,HEHEHDFDFEGEGFGDCBBDAFHFHFDCEGBBDHFAGBHFHCECHCGAFCCDDADGHGCGAGBDCDHDHDACFCFGACEHEGDGFCFCFCAEFHHHFBFDFDCBCFEFCDGAGDEEFEFHFHFEECCCAAABECFHACECFAFGFCBCGHGHG,False +245,30.0,27.0,23.0,25.0,28.0,19.0,14.0,26.0,AAACACBCAEDEBEFCCHCAEGEDEFGAGCEAEADFEBBBEFAGBBBFDAEAEHHHHCFCHCHADFDEBHFACBFBGBFBCHHAHAEEGHHEAEGHGHGHGCAHADADAEAEAGDGBECHDDDDEFFDCDCACAFBFHCHEHEADFBFBGBDBCGABHBHDACCECDDBDBDFDBEEEEHCBAFHHDBBADF,False +246,9.0,17.0,16.0,9.0,17.0,6.0,11.0,16.0,HGEGACAHDHDCDEGFHBHDHECEDEDFDEEHCFCFHBEGGFABEHHHHGAABCCDBEBECHCHFBAHGCGABCBEBECCCCCEGEBBBBDBABEBHGEGA,False +247,10.0,6.0,15.0,20.0,23.0,16.0,16.0,6.0,AFDGEGEFEDCDFHEGEGFGBCACECEAEHEDDHEGEDEFGDDDCCCCGAGEDBABEFEFDGDHDGDCBHBGFFCFCEEEEFCHEFGDGFCDADCFCAEGFGBEFDADADAE,True +248,1.0,1.0,5.0,2.0,5.0,7.0,7.0,2.0,EFCFDAGFCFGFCHEHECEGGCGDGFGFBE,True +249,20.0,25.0,23.0,25.0,18.0,22.0,28.0,20.0,DGDBDAABACHGHEBDCCABFBAHGGBGEAAGDDFGFAHADADEDFHFHGGGFGFDHDEDBACDGDGBFACABBGBGEGEGECFFFEABDEDHFAFGBCBCACHHFHFBFBFHCHCHCECDGDCEHEGCGBBFBGEFEFHCGCBHGDGFHFEABCCEBDBHGDGDGBHCEDADCDCBAEAC,False +250,27.0,24.0,20.0,16.0,26.0,17.0,25.0,11.0,CHCBCACHBABAGHFEEBEGECEBEBEACDGDHHGAAFGEGABEGAGEGADADABAECFGBGAGAEBEADFGFECACGGFGEGDGFBFGCGBFBFEAEBEFAFAFEDEAAAAGBBBCDCDGECCCBCFADABHDEDEGEAHHBDEDFDFGCCCDBBHAHGBCBEHF,False +251,23.0,19.0,20.0,25.0,22.0,22.0,28.0,26.0,ACACGEBFHHCAGAGHGHGCGCGBEHFHFCAGFGCGHEHAHADDDDAEEEECCFBGHAHAHGBDECFADGCECEGEGDGAADBEAEFHFDGDGAEAFDECBGECCHDEEBGBABEHHAFFFFEFDADHBHBDDGGCGCBAGAHABDBDEFEBCBDHGHGFDFDFDFHBAFCBDBDFFGGCHHHDH,False +252,22.0,23.0,23.0,11.0,21.0,24.0,27.0,23.0,CGGAGEGECECECDBFFFHAHGEGCGAGACEDBBBFGFGHGHFCBGHFHBHGEAHAHABDHABABDBECHAHFCFEFAAGGGBGFCDCBEADADHFHDHCEABCGGGFGAHEEAECCCCGBBEHEHBHBHDCDFFAFBFCEBAGAGCCBCAGFDHHEHFFFCFEFBBEBFGEGA,False +253,21.0,15.0,11.0,10.0,10.0,18.0,15.0,19.0,CFCEEFHBGDEEFEFDAGAHAHGHFHFHGHAHAHGFFFGBDBGAAAABABGBFBFBEACGCEDHFACCFFFGECBAECDGGAFAHDHDHBCCGHAHAFAEDHDHGBBABDFCAGABHBH,False +254,16.0,7.0,14.0,11.0,13.0,17.0,11.0,13.0,CDFHFHECACEDEAECCHFHFHGHGCAHAGAGDEDFDCHCFDADFEGAAEAFFDEDCCEDBFCGCGEBEBHGAGFBABAGFHDHAHAEFFFFFBEBCGHACA,False +255,14.0,24.0,17.0,17.0,23.0,22.0,12.0,11.0,EDGFFFGBBBCACDDDBDCFCFCEEAFGFGFGFDBBBFBDCFEFADAHEDBDFHAAGHCHFGACABEDEDEAECEFEFDAABHHAHCECBFBCBFFDBDGHGHFBCDCECEDEAAGEGFBEBCBEEGEBEBEBHCEFBBH,False +256,15.0,18.0,13.0,27.0,17.0,28.0,20.0,24.0,FBDBCHCGDEDCGAGAGDDFBBBFFFFEDACGCHAGGGEGEBABFHFEDHFHFCBDGHGBGDHBCBGAEHFAFHHHDBDCHBFGFGFHFHEGEBDFFFHAHGHCHAHDHEBEFEDGDGAFABDBEHACFCFCEDADEFBDDEAEADFDFHFHFDGHEDDDDC,False +257,6.0,7.0,12.0,13.0,9.0,11.0,8.0,10.0,DDACHGHGHDHEFCCEGEGACCDCDCDADHBFEFEDEGCFBFDFBFEHCHDAGEDECBCBHFGFDFHAHCGABDBF,False +258,17.0,20.0,27.0,16.0,18.0,18.0,19.0,20.0,AGEHCDAGCGFGDCDCHCACDFEAGFGAAAADADCCHGHGHCCEEEGCADACAHECEGDGFBFBFCHCHCBBDBDBDEFCGCBBBEHFHACAGBCHFFBCBCGGGGHDBECEHEHGHBCAGEDEBFCEEBEBDFCFAFHBADDHFHFHFHECFBB,False +259,1.0,5.0,4.0,1.0,1.0,0.0,6.0,2.0,GGGGBGAHBHCGDBECCBCB,True +260,2.0,3.0,4.0,1.0,3.0,5.0,1.0,3.0,BFBCBFHEEGEHCACACHFFDF,True +261,2.0,4.0,3.0,2.0,3.0,2.0,6.0,2.0,CDCABEHHGFGFGEBABCBGDGEG,False +262,17.0,17.0,32.0,25.0,20.0,22.0,15.0,15.0,DHDCDCDGEHCBGBEBACGDFDCBCFCBCEAEAFCDEBAAEADHCEAEHECDDDBDCDBBFFEFGFBCBHAHFCCECGHDHFHAHACDEHECFCDEAAHABBCHGEGDGFHDDCDGDCCCGCACACFCFDADFGFBFBFEGEGEHDACGDFCFCFGBEBEFCF,False +263,7.0,4.0,7.0,4.0,5.0,5.0,7.0,12.0,GCACAHGHECGCHFGFEDHDHDHGHBAEAHBHFHGCCBCHEGEBHAFADAF,False +264,6.0,6.0,13.0,6.0,11.0,2.0,9.0,8.0,DCFBDBEEEEEEADAHGHGCGDHCHGEACBCGCAHEHGGAFAGCCCCCBEBHDCBCEGEHD,True +265,20.0,25.0,22.0,32.0,26.0,23.0,23.0,27.0,DCHBHBCEHHGHDCGCAHHGHDEEHEHBBECDCGBBACACADDDDDFCGEABGBABEBEBEACFHFBEGHFBABCGHGEGDDDEGAHAEFBFDGDHBFGFCDCDCDFGFHEBEHEHBDEAEACBDADHFBDDDDAFEFBGGGGHGHCHEHFCFGFGADDDDBDADHFEBEBECEADACBCFAFHFDFGFAEGHHCCFE,False +266,7.0,6.0,7.0,3.0,4.0,2.0,13.0,8.0,BGHCABHHCHGGBDBABAFCGEGDGAHCEEGEGBGCAHAHACGCGHGFGD,True +267,8.0,8.0,22.0,12.0,15.0,14.0,10.0,10.0,DCBAAGBEBEHECCCCFEDDDFGHGDEDCBCGEGEGEBFFAEHECFCHCHFHDCDCBHGGCCBCFCHHFAFGHGDFCEADCDCDCEBFAFACECAFEFE,False +268,20.0,11.0,17.0,15.0,11.0,11.0,19.0,11.0,FACAFGDHCEFHAECBCBEBEAEGBGBGFHCCBCAHDCFCDGDAEEEFBACADABACECHGGDBDGGGFHEHADAFGFGFGHGHGCFCDCDEGAAAABDDDGHBACACDGDHAGA,False +269,6.0,1.0,7.0,4.0,8.0,4.0,3.0,3.0,DBGECEAEAEAEAGDGFCHCECFAAHHFEFCCDEDC,True +270,18.0,16.0,20.0,26.0,19.0,21.0,22.0,23.0,BFBCDDGAGACDBDGDGDADHCAEACGCGDEBGDFDCDBDGHEHCFFFFFHFBFAFHDDGBHHHHFEFABGGDGDEFCDGHCHEFCFHBADHHCFCBGBFEEEEEFEDEDAFGHGDGCACDEAEACDEDHBHGHBHBHCDGAEACCEHGHAHACAGACBEBGFDF,False +271,0.0,3.0,1.0,4.0,2.0,4.0,2.0,3.0,HFHFEFDBEBHFDDBDGCG,True +272,16.0,16.0,17.0,14.0,11.0,14.0,8.0,16.0,FCHEHAFAFBFBDHGAFABBCDCDHBHEFABCHCHDAGABEBAHDHDFCEBGDFECECECEHECACDBDBDCGAGAGACAGBFBGDDACCDDBHEHBACFBFHHHFHFCFAE,False +273,13.0,11.0,14.0,14.0,11.0,17.0,18.0,16.0,CDFDGBHBFGFGFGEDABABCHHDDEDCHCGAGFBFDADHDCDCECAGEFEBEAFAEHEHGGEFBHCHFHFAFDFACGGFGHHDHGHAHCFAFGEBCBGBGCACDCDEHGFBAG,False +274,30.0,26.0,12.0,16.0,14.0,36.0,17.0,16.0,GGHCBABACFGFHFBBHAEAEACADADABABFFDABBFFEFBAGFHFBFCFBAHHHHGGDGFGBHBFEECEFDCHCHBHGEAHADDGAFAFDDBDGFGBEFFFFFGFACABGFFFAABAFACAGAGHDABABGDACFEAEADBBFBEDEAFFBFBFCFCDBHEHEDF,False +275,6.0,13.0,13.0,9.0,7.0,9.0,12.0,6.0,CEFBGCCCCHDBDBCAFDFDFGFHHCCGCGBGDGDBCBCBHFGAAEGBGBFBGBGECHCDAEGEFADAHEDEBBF,False +276,7.0,5.0,3.0,5.0,6.0,7.0,3.0,5.0,BCCDFEFEFEBADABCFDDHDHAAEAGFGFHFBAEAGHBHE,False +277,6.0,5.0,1.0,2.0,3.0,3.0,6.0,7.0,HBBFBFDHCGEGAHAHGHGFEBHBGGAEAHADA,True +278,4.0,8.0,15.0,16.0,12.0,11.0,10.0,10.0,DHCHAEEEHEHEFEHGFBHEDEGEGFCDCFCGCDCBFFFCEGDBHFDDADGGCGDEDEDGACDCFCFBGBHBDBCFCHCDDDHCAB,False +279,15.0,15.0,14.0,9.0,20.0,30.0,10.0,19.0,EAFFEFEFHBHBHBHCHCFAAACFCAHGBGBFEEBECEGEFDCEFEGCBFHFBEAFDBBGDDCGFDCBBHBHFEFEHCHFBFDGCHFHFHFGFGAAAAEECEFDBEFECEHDFCFHDHFFEAAAAAFGFHFH,False +280,20.0,27.0,17.0,23.0,26.0,20.0,26.0,25.0,AEDGCEBACABABGBGFDCEBHBCBCGHBAEACBHHHCDDEGFHAAFABCEHDBDBDFFGFCBGGGFGEEFEDEAEDEDHHHFHEEEGEGCBCBHBEBGBGECEAEHGHABBBFHEAFGBGDGFFEFDGDGDGHGDAFAGDHDECEHHHAHDDGHGCGEBEFABCBDBFCFCFHBADADFDAHH,False +281,10.0,6.0,6.0,8.0,8.0,11.0,10.0,7.0,GBFFDHAEAECDDBEGDGAEECGGGDHDAFADAEAHBHDEFFFFBCBCECAFABAHGFGFGFGHCH,False +282,21.0,33.0,19.0,20.0,21.0,12.0,19.0,26.0,CAADABABCEABHBABDCHEAEGHBBCCCCCHCBGGGGHHDHGHGDGDGDBDAAGCBHDFEEEEEEBEBAHHGHEHCCGHFBFBFBFGHBDBHAFAGACCHAHFBCCFDEDEHCHABDBEGADBBCBHEHEDDDDBDEDBBHAHBEEEDBBBBHGGGCEFBFAFBGAHAFA,False +283,12.0,9.0,6.0,10.0,12.0,16.0,15.0,10.0,CFCEDFGCGFHFBGCGFGABEGAGAGAGAFADBHGHDEFHHDGCADEGBBCHDAAAGEBEBABFDFEFEFHFHFHFHGBFEGEDDDEFEA,False +284,0.0,7.0,2.0,2.0,5.0,4.0,3.0,5.0,FBBHBHECBFDFGEHCHEHEBEBDGFGB,True +285,18.0,10.0,10.0,8.0,8.0,13.0,19.0,13.0,HHHFGFAHCCBCHCBFAGCGBABDBDGAFDCDAEAEHDADBHBAGFGFGHEFFGHGHBHAFFBFCFCAAABEEEAGGGAGCGFGAGADAGEHAHCDGEG,False +286,17.0,19.0,13.0,13.0,17.0,16.0,12.0,9.0,DBDADABCGDAFEFEFEDABCBEBGDGFEBEBEBEADBDGHCADABFDADADABGFGFCBCDCFBGGEEFCFAFEFBAGGEFHCGAFAHBHBFFEBACECACBCHAHEHEHCGBEH,False +287,11.0,13.0,8.0,14.0,5.0,10.0,1.0,11.0,ADDCHBHFDEACFDBDBABCBCDDDBAAADHFBFBABEHEHBHBCCHFDABAHCDDDCDAFHFEFEFHFHGAB,True +288,21.0,32.0,21.0,22.0,23.0,17.0,23.0,21.0,CFCBBDADEDEDBDHDADCCCEHEHBFBHADADBGBGDCBBHFAEBDHDFDFBEBHDEDBCECEGABCFGFHDHGHEHAAGHGEDEAEABGFCCBEBCFDFAEGGAGADECFFGFBBHCGEBEGAFABDBHFFAHAHAHBHBEBEBCBABDEGCGCHCHBHBGEGEGCAAGGBBFCCGDG,False +289,10.0,13.0,5.0,12.0,9.0,19.0,21.0,12.0,GBFAEDDDGGFEFDHHGHGFGFGDGFGHHHHEGDBHFGGHECBAGAEACFBBDBCADFGEGDBBBBCBHHFFBFBFDAAAEFGFAFAFDFDFHGGGGGECE,False +290,10.0,11.0,9.0,13.0,3.0,16.0,8.0,5.0,DBDBDCFFGFGABEBEDEFFGFGFAFABHCAFABCDHDADAHBGBDDDADFHCBCDCAAGHBFGFGFCCBFFCFD,False +291,22.0,19.0,25.0,28.0,18.0,24.0,23.0,17.0,FCFEFEFAGEGCGEAAAEGEHFHEGFGDGDEDBDEEECBBBEDFHFAGHCAGAFAHABFBFDDGECEBGFDFCFCDBEFABGEDACACDHDHDFFCDCACHCDBBGCDBHBHCFCDHHHBHBGFGFADDGDCDCHCDCACAGAGCDDABCEGHDHFGGDDEAFBFACACABGBGFD,False +292,22.0,21.0,17.0,19.0,16.0,16.0,15.0,29.0,EFHHAHDCDEBEHEHEHEHEHCFDBCBDHCAFEGGHDDBDFGFGHCFDDDDAFADCGCFDFBFBHGAFCCBBEEAAGAGDEDAHAHAHBHBHBHEHCABABHBCCCHCBBBDAHGFDEAEAFHGBGEHAFBGHAFAFAHABCDDECGCHHGHGAB,False +293,14.0,10.0,22.0,19.0,17.0,10.0,11.0,13.0,FDGGCACGCDCACBCDCDGHHDHBHFGGCCFBFBCBDFDAGEHAHEFECBHGDDDCEBBADCDFDADEEEEDEBHAHAGCGCBDGECEHEHAACADAHFHFEFCCECEDECCDAEA,False +294,21.0,23.0,11.0,16.0,19.0,13.0,19.0,13.0,ECDFDEAGAEAGHBFEFGHBBGBABABGDGCCAGHBHFEFGGCBDGDGDGHFHABAECEAGHFDFEFBFECECEFDHGFGABAEHEGEBBBBEBADFEHEHBDBDADADGBHADADHGAEBBBDCACECBCAAGA,False +295,16.0,21.0,15.0,23.0,14.0,18.0,17.0,12.0,DDBBHFDFGBGBHBFFFFFFFGEBCFCGHABBEHDDDDBBBBDGFHFAEDHDHCFCHCECBAHACDCDHAAADDECACAGABAGEFEBCAEACGDGFEFBGBDBCBGGDDAEFEDGCGEGEDEDGDBABADFHCHG,False +296,2.0,5.0,5.0,3.0,8.0,3.0,7.0,5.0,GHDHFBBGGCGBHEHBCACHCGCGEEEEFDADBEGEFE,False +297,8.0,7.0,6.0,6.0,3.0,4.0,7.0,7.0,GDGFBFEFAAEBDBDBAGAEHBDBHCHDGBGCGHGHAAACHCHAFCCD,False +298,10.0,8.0,9.0,8.0,12.0,10.0,12.0,8.0,AAAAAADGHGAEEEHFHEHEFFAGAFHCDCGEBCBCBFBFAFHFGGCGHEDGDFDBGEDEDCBEGEGHCBEBCCDGF,False +299,2.0,2.0,2.0,2.0,1.0,0.0,0.0,1.0,CHCEABDBDA,True +300,21.0,16.0,12.0,20.0,12.0,15.0,16.0,21.0,HFHGDDEFBFBFAGCFAGBGDHEHBHBHAEFBDGACHGHAHFFDFHFHEBBCBDBDBCFCDCACAEDEDHAHBHECABAGCEBHBGEDEGAAHAFAHADCDEGEGADFGAGAHCDAGADAHCHDDGDGDHFBF,False +301,18.0,17.0,21.0,18.0,14.0,17.0,20.0,23.0,BEBFFCAGAGAGHGHFHDHCFDFDEDEBEBEAGFBCCHCDCBCHHGHEACAEFGBGBEDEBCDADHFAADBHBHCHFDFDFHGBGBAEFGFAAEHEHEHCCGHDDDGHCCCCAABCGCGCADACABFEHDBCFHGHGDAHHDFGBGFG,False +302,17.0,9.0,16.0,15.0,18.0,20.0,16.0,20.0,CFEHGDGCGHFADAFGFBFHABACDEDEDGAEHEHCCCBCEFHGHAEAEAHAHEHEHCDFFAHDEAFDFGBGDHHFHFAGGFFBEHEAEAFFFDGBGCGEECAFFHEHEHDACBCFCDDDDCBCBHGAGCG,False +303,17.0,9.0,12.0,14.0,11.0,11.0,11.0,15.0,DFDFAGHHDEDEHEHECGFACAEADDHDEDCHCECFHBBBEGHBACGGGAGAHDHAAADEHEAFADGDBDFHFGBABABHBFCHAHACCFCGCEADFCFG,False +304,32.0,22.0,21.0,20.0,17.0,21.0,22.0,16.0,HABACGCBCGHGHADEGABAFHHGFCCGFFFHFHAHAGACFGEEAHAHABABFBAEAEDGDBDFFFFEGHGDDDCHFAFGECACECECEDFBEAAFBCGAGECECFCFCBGGADADGHACAEBHAHABGGDDADCDADBBBGHEFEDDDGEFBDBDBCBABCBAAAACFGB,False +305,22.0,14.0,10.0,9.0,20.0,15.0,19.0,12.0,GAGABHEFGHGABAEDECGAFABBEFEAECCAAHGHBEEEEEFHFGFGAEAGAGDGHGFAAAHAGAGFBECEFFBBGHGFCBCGCADEDBDBDBDFEECEBEDGAAEAFAHHBFCFCDHGH,False +306,7.0,13.0,6.0,7.0,4.0,5.0,5.0,12.0,BABAFAHDFDGBHHEHBDACHGHGDDBDHFFAFACEBEBEBHBCAHBHDHCGBHBCGCB,False +307,27.0,19.0,23.0,17.0,31.0,29.0,21.0,17.0,FADCDEGEBEGHDAEFEAEBHBCBAFAHAFGEGFBFCAHAHCCBDFHGCEFFCFEFEAEAFCBDADADHDFBFBEBADFCFEFBFBFDFCFGFEAHBBCCCCHHBHAAEGEBECEGDAEFDGECEFEHGAGEFEDGBABABHDHDCDCGHAEACAGFCECGGHEDCFAAAGAGCEHEGEGFGFE,False +308,16.0,23.0,23.0,25.0,22.0,21.0,28.0,27.0,BHGEFEDACAGADADGDGDBBFBCGGHGFCFCEHHDCDCEGFCFBEBEHDHCHCBEDDHBBEBGGFDECHCHCBFDFBGEHEGEDEGAHDBDAHGBGDGBCFCGCGBBAFAFABBBFGFHAHAEAGFFFGDDCABHECEDEBEHDGDEDEGCHCDCACHCAFGGGHFHFHGHGCAEHHHHDDBEF,False +309,11.0,10.0,14.0,4.0,9.0,15.0,8.0,17.0,CECHBGAHBHAHGCACBEFEFDCCCCCBCDCGAFFFFFBCBAFHFHFHDAEAHGHBHBHEHBHCGFBHAAGEFEFEGHAHDFFCAEHG,False +310,7.0,7.0,11.0,8.0,8.0,14.0,8.0,4.0,AFACGFEEDBGHDDADFCFCFCFDBGBHEHFAGDCACFCFEFBDBGBEBFCFCFCADGEGEAHCFGE,False +311,1.0,3.0,3.0,4.0,1.0,4.0,5.0,3.0,DHHBHDGDGCFAFGEBCBCGFGFD,False +312,9.0,6.0,12.0,3.0,7.0,3.0,4.0,5.0,AAEAECGCDFDHACECEAEBHBACCHCHEGCGCHCACBBAFAFCDGEBB,True +313,10.0,20.0,11.0,11.0,10.0,21.0,14.0,10.0,FHEBEBCAHAHBFGFGHGFAFCFDBDFDCHBECCCHEACABDGFBFEFAFAHGBFBDBDBFCCCEBFGGBGFAFABEEAEGBBFFDFBFBDBGBGCGDEDHFHDGGH,False +314,11.0,11.0,19.0,12.0,11.0,7.0,10.0,11.0,GBHBFGDABADADBDCDADHBGCECHCHCGCEAGCGCDCFEAGAEAEHECEFFBECDCGEHCBBBCGDHDBDADCFFEFCACAEBHHCHGHC,False +315,15.0,20.0,19.0,23.0,12.0,16.0,12.0,15.0,CCCCEFDBDHDCDFDCHFHFDEBACECHCGGFGAHDDDBACFFFDFBBABABDBACADAHCHDGCFFBHHDHDHGCCACEDBDECEHEBABHFDDDDGEFBFBGBEBFAGAGBGHEHDFEBABAEADBCGCG,False +316,6.0,8.0,6.0,3.0,8.0,2.0,0.0,9.0,CBCDFDHABAFEHBHBHECEBECHHBEEECEHAHCDAHABAB,True +317,5.0,12.0,12.0,7.0,8.0,8.0,7.0,11.0,CHGBGBFBFDABACAFFFCECHCEGDBBGHCCBGDGFGHEHDHCHBBCCECEBEAEAEHDCDHHBHBDFF,False +318,19.0,29.0,24.0,19.0,24.0,39.0,20.0,15.0,CFEFGHBHFHCEABFCCCFFEFEGBGBAHAHDBABCBGBGBGAGAGABHCCCFFFEHEDGBHEEDHDEDBHFDBCBGBFCFBEDFAFCFGACEFGFGAAFFFFDFEFECCGEGBDAAECECABEFDFCEAEAHFDBABDCHGBGBGBCACBCBEFGFGFCFHDDFAEHDFFEDDFDFBFBEBEBFHFCD,False +319,8.0,5.0,5.0,2.0,5.0,4.0,3.0,7.0,HAAEAHDHCBDEAHCGFGCEABAEAFAFHFHBHBCBCEG,False +320,4.0,0.0,2.0,0.0,3.0,0.0,0.0,1.0,CACAEAHAEE,True +321,19.0,25.0,20.0,14.0,21.0,25.0,19.0,10.0,ECEAHAGAGDCFHAHAHABEGAGBEBFFFFFGFDFDFGCDCBABEBGBFFFAGADFDGHGABAHAGCBABGDGEEACAEDBCBCEEFHGDDCBCEGEFEBEBFGCHBHBEDFHBCGEBCDCFCEBEFEBCBCBCBAGFFAFAFDCGEEFDCBF,False +322,4.0,3.0,7.0,8.0,3.0,3.0,6.0,6.0,AGDFDFDAGECEDDHCHGHCBFDEBCBCHCHCDDAHAGGG,True +323,20.0,23.0,10.0,13.0,14.0,23.0,24.0,21.0,AGAFFGHGEBBCDCEEEGBFAHAEGEGCGFGAAEBGHEBDGAGEBABEFCHAHADFBFDFBHBHBGBEBFBFHCACGCGBFBFAHAHFEFDBGGGBGFGBBEDHGHGHFHDHDGDHBFBFDFHFHFACADAGEFHCAADHBHCADFGA,False +324,6.0,10.0,13.0,15.0,5.0,10.0,12.0,7.0,ABBDDDDGDHDCBBHCHGDGBAEGEGHDBCFGFBEBADGCGCGHFFFFFCFCBDBDGDCAAAFDHCCCECDFDHCGEG,False +325,14.0,17.0,16.0,18.0,24.0,25.0,25.0,12.0,EAGDFBFEHEFGADABCCEGEAEGEGHGBFBDEAEDHDFEFDHCHGBGEECDCDCDCHCDEAEACCBEGAGEBFBFBFCCGFBEBCCDEDFDHHGAGAGEEFFFFFBGHGHBDECEBAFAFDFDGGGAHBEFGFGFHDGDEFGCABFBFGG,False +326,10.0,8.0,13.0,7.0,11.0,10.0,9.0,12.0,HGFCFAFCFAGADEDBHFCFCHHAHACEBECCCCEGEFEFGDBFBHBGBCEEABCECAADDEDHDHBGEGAHCHFHGAGH,False +327,13.0,9.0,7.0,7.0,11.0,9.0,9.0,4.0,EFEGEFABAFHDBFAFGGEBEFECCCEFFDADBDGEGAGABABABFBDDAEAHAHGHEAAGDECCCGCB,False +328,11.0,7.0,14.0,13.0,15.0,16.0,11.0,12.0,HHHHFDGEGFHFHGDGCCHFBFEDBAHGFCDCGGDDACACEDBGEDEHHGHEFEFCFGFAAACADHFAFCFCFCBDBAEEEEGDFBFAEAEDEDEBCCC,False +329,14.0,9.0,16.0,7.0,13.0,4.0,16.0,18.0,GCAEFCFCACAEDGGEGBGBGBHBHAHECAAAAHAHECECHGHADDCBCFCHHGAGEGDGEAECGBHDACECBHDCDGHCHGEBHBHEHCFGEGHHA,False +330,6.0,12.0,18.0,17.0,8.0,10.0,10.0,6.0,GGFCECDCDCAABEBEHEFDDADGDBDHGFBFBEDHDFBHGGCBCBCDCBCHDGCBCBEDCDGDBECADACCCFEFGFGFHDADFCC,False +331,11.0,25.0,21.0,16.0,17.0,27.0,21.0,23.0,FFFCHCBCGHHHGGCEBEDFCHAEFCFHDBDBABFBFEFBFHDHFBGCACHHFBFDFGFBHHDBEFAFAFHFEEEGEGEGEDBHCDCACHHGFGFHHBDBDBHCHGEDBDECECECFGBDBCEGGGGCCBCAAADAHBBBGBGFGHDAEFGFBBGHDCFCF,False +332,31.0,34.0,15.0,23.0,18.0,19.0,14.0,23.0,HBFBAAACBDEABCHDHAHDFEFHAAACDEBHBHBHBCBHBHBGCAFGBGBFFDFGAEAEBDFFADADACADDDHAHAEEBFDFGCCCFCAEGBCBAHCGEEEEEEBFDFEHBBBABAHADBDEDFGHHBHBDDABBHBHDHFCFCGEBAAAEGFDFDGDBBBAGAGABAGHBHCAD,False +333,20.0,17.0,9.0,14.0,13.0,13.0,13.0,14.0,ABGCECACBHDHGEEHEHBDAAAFDEDGDFAFABCCGHBABEBEGADADFDEHEHEGBGAHADDHHGHGCGFFABAFDBDHABEFDCDFFAFBEBHBAFAFABABGCECHGBG,False +334,7.0,5.0,2.0,4.0,6.0,6.0,4.0,9.0,GCGBFBHAHEBEAEDCGEAEHHFHAHABFGFHFHDEDADAFHB,False +335,17.0,13.0,10.0,10.0,9.0,12.0,9.0,20.0,AGHHAHAHCBABFGADADEFEFEDBBBBHHGHDHBCECEHFHFHBHAHDEAEAEBEHACAGADHCHBGGFFFHACBDFDAGHCDGDCFCACFHFBBHGAA,False +336,10.0,13.0,6.0,5.0,11.0,4.0,11.0,9.0,EGEBEBEGEBAHEFBCBEHGDFHFAFCBHBGDABHGGGBGCGBABADHDCEABABADAEEGAGCHCHEH,False +337,17.0,16.0,15.0,8.0,14.0,17.0,17.0,24.0,HBGBABHBHDFFAHAHAGAEAEAFACGCBCECFGDGCCEFEFHHHABGFCHDHGBCBHBDGDHEHGHCFCHGHDHFHFBFDABHBGBAFHEEGEGECBAGEHBHCHEFEADCBFGHCEFGCGFAAAAF,False +338,18.0,20.0,22.0,16.0,18.0,27.0,14.0,22.0,AEAEAEAFHDHAAEFBDHGFGFCAAAGADFFEFBADCHCHEGBBEBGFGFGEHEDCFHAEBHCDCBCGAECGCHCHBFBEBHHHGCBHFDDGHHHCHBDEDECBDFEFBFGFCFBFBCBFBFCDEAFDGABADADBFFFFECECADHHHCHCFCFCG,False +339,24.0,25.0,25.0,23.0,21.0,21.0,28.0,25.0,ABAFDFCFCGHGCDBDGEGEGCAAEBHBHGHGHDADCGCHFECEBDHDABHGCGHDHEEEBFBFBDDCDGEEEHBFFCFBFAFAFGCCCHGGFGCACHEDEHGDDBHEHDACAFHEABGCACABDBEBFDGHGHFHEAEAEADACGGBBBCGCGDGBGBFCHAHAHFBABFCEHBADGDEBACGCGFAFDHD,False +340,14.0,19.0,9.0,8.0,9.0,16.0,11.0,11.0,CAADABAEACBCBGAADHBFFFBDBDEGABHHHAEFHBCFHBEBGFDFBFBDBDBDAEGEGEFCGBFBAEGBGFGFHFHFGFCBCAAGAFEHHHCBC,False +341,2.0,6.0,2.0,4.0,1.0,4.0,1.0,1.0,ECBDBFAFDFDBGBHBCBAFD,True +342,10.0,9.0,6.0,7.0,9.0,12.0,7.0,13.0,AEAHAHFEGEGBGAEBBHFDBGBHHGHAFAFAFHFDDCDHECFCACFHFHCDCDHBEBFAFGFABEEEGBDHH,False +343,12.0,23.0,13.0,17.0,19.0,18.0,25.0,20.0,GCGCGCFABHCGAFCFDFBHBHEECDDBEHEAEABABAHHFFDFGEBEBGCABAGGEGEDEDHBCFDHDGBGDGHAEAGDHAEEECHHFBDGCFCDBDHFHBBBDHHCBEHFHGGGFGFBEBEFEFCFGFGHGDGDBHBGBABDGEG,False +344,8.0,19.0,17.0,14.0,18.0,17.0,16.0,26.0,BFBHCHCACDDFCHEHAFAFEEEDHGHBEEFADGGFGEEDEDEFEFBFBHHGHGHDEFCGCGHDHDBCHDBCFCGEBHBHEHFDEAEBEGCGBHBFBHBCBCBCBGACCHHHGHFDFCFHGDGHEHDCBAAFHBG,False +345,14.0,25.0,9.0,16.0,24.0,29.0,24.0,20.0,BDBDFDFEGEDADGGGGDFAABHGFGFEBHFECHCEDBABFBEDGGCFCEAAHGHFBBHHHHHHEBEBFAEEBEDGDCHEFBFBFBHEGEGEAEBGGCAFFGDGAGAGHFFFFFGCHAHBHDEDEFHBBBFDFHFBFBFBHDEFGBEDEGEGBAFFCACEG,False +346,20.0,21.0,26.0,20.0,28.0,15.0,21.0,20.0,EDEDFHFHEDCCECEHEHCGBBAEFDDHBGBEBGAEHECGCACECGCGCDEHCAFAECHBBDGDFCFBBHBEBEHDGDBDCAGACAHAHDHCEBEHEACDDDFFAGAFAFCGEACACGEEAHAGAGAGEFEFHFBGCHBDBHBCGDGCECHDHFBFDCGCBBEBDAEGEGE,False +347,9.0,10.0,7.0,7.0,9.0,11.0,7.0,1.0,DAFCBCBAFDEGEGEFAADGEGEAEAFGFBFEFCFGFCFHEDCBGBEBAFDDABCBABDBC,False +348,23.0,21.0,22.0,23.0,12.0,21.0,19.0,12.0,DBGBGFCCGCDHGFGFGFDCDEAEAFBFBHGHBCBABAFFFBBAFHFCDBFECCDCACAEADFDEDGCFCHBBBBDFDCGAHFGEADDGHFFDADEGEAEFEDECACACAFADCFCAGBBABEDGDHCGCACACHBDGGAGBGBHAHADDDHB,False +349,24.0,18.0,28.0,33.0,14.0,23.0,32.0,22.0,DBDACACDEGGCFCBGBHFGDGDEDHHADCFBFDFDAAFAGDGCFCECEGDGFBAGHDDCDCDGHCFFAFGDGDHDHFGGBGHDCDCAHFEDBFBFCDDEDGHAHADABHBEAAACADGBGAGAFHCCGFGCGDGAEAGDGHFHFEBAHCFCFGGGEGEGAGHBBBDCCHCHFHCHDFDBDCDEHECBCEAABC,False +350,8.0,4.0,6.0,7.0,7.0,4.0,16.0,7.0,EDGFGACAGBHBEBAGACAGEEEEEGGAGCGCDAFHGDCDHGHCHGBGAFDFDGGGDHH,False +351,14.0,22.0,13.0,15.0,4.0,11.0,14.0,13.0,ABCCHHFHCDBDBDBCCGCGFFDFBFGGBAHADDGDCDCBAHABEFHBBDBDBDBEBEBGDAEABDGFHBHGAGCBFHHHHHACGBGACFBBDGDBFAGAGACACF,False +352,23.0,10.0,18.0,19.0,18.0,25.0,14.0,15.0,GFADHDHFCGCBFFFHHEDFDHAEEFECAGBGEAHAHADAEGCBFBFEGEFHHEGGCFCHHAHAHEBAADAGBEBEDEDGFEFAFADADFGFAFCECECFFAFACACHCDFDADCDGGFDHCCCCDGDAFBFBEADBDAECF,False +353,28.0,26.0,15.0,29.0,24.0,17.0,31.0,29.0,EFGDADGCGBGBGBEAEHGHFDDEDEDEGHGEGEGHGHEHGDGBGFEAEGDCHCHDHFHEHAGDHDFEBEBEBEDCDCACAFGFCABFEGBGAGHHBDBABABHHAHAECEAGBGBHBFEDHCFCDGAFDHBEACFHHGDADHCFCBAAHFFGFDADBBEBHACABAHGDGBEAFABDBGGGGDDDAAHDDDHCHAABE,False +354,2.0,5.0,6.0,7.0,4.0,6.0,4.0,6.0,BHGHAECCCFADBDHDEDBFBHDCDCDFGCGFGFHHEFEB,False +355,6.0,5.0,6.0,6.0,6.0,7.0,2.0,4.0,HFHCGCGBFEAAAHAFBCBDEDEDEDCDFFABBCFCADFEHE,False +356,6.0,7.0,14.0,10.0,18.0,19.0,15.0,16.0,FBEHFGEHFDCDGGGEHCDCDFFFHBABDFDFHCCFEFECEHEFCAAGFGBCBFGFEBCACACDFFGHGBEHEHEHFHCCEGEGEGECAHEDEDGDGEHHHGHFF,False +357,14.0,24.0,11.0,19.0,13.0,13.0,20.0,12.0,CAHGEBBDBFBEGHAEDBDHDGDGECACACEFBDBFFGADBHBCCDCDHDEGEAFAFEGBFBABHFHAEDEDGHGBEBGBGBGFFBCGEGDAFAFAHAEBCGDDAGHHBCBDBDBFBDBDCGGGGH,False +358,14.0,23.0,16.0,16.0,14.0,16.0,6.0,16.0,HBCBHFHFHDBAGAEDCCCBFDFHFHDHDHGHABCFCFAGEGBBBFDADADBEBHFCFDFCBADDBCBCBCAEGEFCBABAFAHBFBEBEBCCEEHEDECBFAEHGADHDHEHBDEFBCDA,False +359,13.0,21.0,20.0,21.0,14.0,16.0,20.0,15.0,GFDBDCACAEBEBEBHBCBCECEGACHCHAHAGGBADADBDFCFHGDGDGEBHBDGGFGFGDBDAGABDGDGEHFDAEFFGFDHEBCCDCHCFCECHGDBCEHEFDFDABEBGDGHACFFBDCEAFGDBCGCBCFHBHBH,False +360,2.0,2.0,1.0,1.0,3.0,6.0,2.0,3.0,GFFFEFEBDBEHGCAHAHFF,True +361,14.0,17.0,14.0,17.0,23.0,22.0,11.0,18.0,DHACABDDDFEFBCAEAEAEFCFEFCFDFHFAFBCBCHGHFHEAEGBHBGCFCHAEBEFECECGFEDEFCCHAFAFAFADGHGBGDHDEDAHBHBHGEEBDHDBEEHGDEDEFBFBFHFGFBDAEBDGCHEEDCHB,False +362,7.0,7.0,14.0,4.0,6.0,6.0,6.0,3.0,CCBCGEGCAFAEADAGFGFCFCBCGHBBDBCGEAHAFCDCACBCHCEEFECBD,False +363,10.0,8.0,17.0,16.0,17.0,20.0,8.0,12.0,FEADABEGEHEBEBECFCDCHBHCAEEGHCFGFGFHHEFEFDFGFDECCACHFFFCDCGADAFGDCDCDCEFFFFAHAHBEECCDADAFFBEDEDEDHCFCDBHGHDB,False +364,8.0,4.0,4.0,12.0,13.0,9.0,10.0,11.0,FFHEHDFFAGEGEHEHFGDDDEDECEDABHFGFGDGAFADAEECGGABDBGHHCDCBGFDHDHAEAEHEHE,False +365,6.0,2.0,5.0,1.0,4.0,5.0,1.0,5.0,FEACAGFEFHCEABABAHFFEHAHCHCDC,True +366,11.0,5.0,9.0,15.0,4.0,9.0,12.0,5.0,CCFDEDFDFEFEHDBDCDHGGGGDFDAACADABFGCBCAGAFDFCGCGAHAGAHDBDHCGEBFDADADGG,True +367,22.0,11.0,14.0,10.0,20.0,19.0,35.0,19.0,DGGGBCECGDADABABHEHBHGAGHGFAFAGBGBGEEACACFEFGGGEFHCDEEBEBAHCEFFFFHAHAHGFECBHGGEGEHAHFGBDFHEEGCGFDAAAGEGAGFEFHFGAGAGDHAACAGHGCGAGDGBFHFGCGCECEHFHDGEGCD,False +368,2.0,3.0,4.0,0.0,3.0,2.0,2.0,2.0,BCECECHFHFAGEGBBCA,False +369,2.0,7.0,10.0,3.0,12.0,8.0,6.0,9.0,HHDHDCCEGEFFFHCBBHDEGEHEFEFEFEFBCBEBHBCCGCHEHBGGACECEFGAC,True +370,17.0,20.0,13.0,14.0,12.0,20.0,18.0,16.0,HEFEBECCHDECGCEBBGCDBDBDGFGFAFHGDDFDHBBBFAGDFAGACEFHGBFDFHFHFHCGBEDHFCFCFGAAEDECEFBFAHABACAGAGACAHABFBFGEGDBFBHBHDHDGBABAGCGEBAHGH,False +371,14.0,16.0,16.0,7.0,13.0,5.0,11.0,14.0,GBGBEHFHFBBBECAABDEABAGAEDEDBCEGECCACAGACACBCHCECEGABDBEBHBHFHCDAEADHCHCHFHCEABBCDHEGFGCHBGGHGHA,False +372,9.0,15.0,11.0,10.0,12.0,17.0,13.0,14.0,BEBEBGFFBFGFDFGCGCGFHDGGCFAFAFBFDHDEAEHEHAFBFEGHHEBGAGCHHHDDCECGCABFBFHFEDEDHBBCBGBCAGACAHBECEDDHBHFF,False +373,14.0,9.0,8.0,14.0,6.0,19.0,18.0,14.0,BHEFAHAHDDDDFBFDFGFEFHGBBFAAAGADHGBFCDGBEFGFCHHGFGHGHFHGEGAGEEAGDDABGGCCCBHBHCHDFAFAFAFGFDFDADADCGCGHF,False +374,13.0,6.0,13.0,5.0,8.0,10.0,12.0,6.0,CBGADAHAHAFAFGCGFGCDEAEADADCBHDFAACCCAFHBBCEGEGECFHAEBEHCGFGFGEGCGCFCGABF,False +375,8.0,5.0,6.0,3.0,11.0,9.0,8.0,4.0,EEEEHFFBFGGCGHGEBABEEFCFCBHGDBHFAFAFDFGAGDGAECECECAAAE,False +376,6.0,8.0,6.0,9.0,8.0,5.0,12.0,5.0,AEGEBACACHCGGHDBDBCEGEBEBHFDDGDCDBDBEGCAFBFGGGEHEAADFDFHGGG,False +377,2.0,3.0,2.0,5.0,6.0,4.0,2.0,2.0,EDEDECEBHBGFGAEADFHBDFEFDC,True +378,18.0,11.0,12.0,20.0,13.0,19.0,14.0,21.0,GAEHGHAADADADBFCECDCFCGDDFCGHAADFFFGHBHFDCDBFHFHGHFAGAGABADDHAEDECFFFAFAFDEDEBABFBGGHBCBAACBHHHFFEDEDADBEHFHGCGEEDHDCDGHGHEHEHCH,False +379,15.0,10.0,10.0,14.0,7.0,13.0,13.0,11.0,FHGHGHBBCDDDDABABGCEDADCHGAAHAFCFBDBDADFCFDDHCHFHAHCHCBCGGAACAHGGGGAGBEDFDFEAGDGFEBEFFAFAEBEF,False +380,20.0,20.0,27.0,28.0,18.0,28.0,19.0,15.0,FAEAEHHHHHHECBHFFFCFCDAGFGDEDCDCBGFFCGBGEGBAEAGFCADGGBEBEFHFDCBAEFDFDEDAHAHGEDAGBGFEBEGFDDDFDFAFCCCCCCBCBCGCGCACDDBFAFBCDADCDEDBCBCGHGFGBBAFDCDHBHDDBDCECACDFDGABFEDEAEFHHAAFFF,False +381,9.0,4.0,8.0,8.0,10.0,3.0,5.0,2.0,DEDECFCECEDAAACHEGDDFDFCACECGAABDGCHBEBGDGBAEAEAE,True +382,28.0,23.0,23.0,25.0,22.0,19.0,22.0,24.0,EBAHHEDEDBDHHGADFEFEHDHDGFFDFDADHDGEACBEHEFGDGAGAGEBCDCBBAFECHGGBHCHCGGGCGAFCHCHBBEBFBFHFCGCGEDEAAADABABADFEFDCDCECDCHCHCBAAAAAAHAFEGEADCCFHFEBEBFHDHFAAAGCBBBCDHDEDFBEGHCBDBGHGCGHDEAGABA,False +383,4.0,5.0,2.0,2.0,4.0,7.0,4.0,2.0,FAFBFGCGAGAGFBDEFEFHABFBDCHEBE,False +384,23.0,10.0,11.0,21.0,17.0,14.0,20.0,15.0,CBEFFDDBFAGHDAGAGAGDDBEGCCCDCBHHEAEFGFEEEHEACACAGAGBDAAHFHFAFADEHCACGDAEEFGGHEHBCDAGAEDEBFGHDHEHDHFHAGAGAGAFAFABBCDGGGDBDGDEDEDFDHD,False +385,16.0,15.0,15.0,12.0,17.0,20.0,20.0,23.0,FGBHBHAHAHBDFEFEBCAEEDEAHBHBHEFDCBAFCFAFAGHGHGACDHBCAEHGHBABFCFDGDFDFHFDBGFGHHACADACHCGBEBEHEACGEGFGFGDGEGEGECEADACBGFHHDFFHFHFGGBHCGCEEHC,False +386,22.0,28.0,19.0,25.0,19.0,24.0,12.0,27.0,BHDGBHDFDFDBABGDHAFAECECBCBCFCBEBHHHEEEBAFDFAFADECBDFDFAEHBHEHEGEADHHHFHFHDBFHAHADADFDFCAHBCGCDCBBBGBFAFCFHAGADDBFEFEAAHCDCECBDFFHFHBHBFEDCACAGEFDHGBEHGBCBHEEGAGHBDBDGHADADCBCB,False +387,16.0,23.0,23.0,12.0,27.0,6.0,20.0,14.0,EDEBGBEBCGGHCACBHBEGAGHGCGEGFCHBDCHGHBHGDADADBBCHCBEBACGEGEGEBABABDEEHECCCCBBBGAGAEAGFGHACCBBABAGFBEEEEEECGDDCDHEEEAEAECDCECGCFHFCBCEADDHEBFH,False +388,29.0,22.0,29.0,26.0,26.0,22.0,19.0,18.0,CECEGHFBFDDCDHGAFBGDFAAHACACAEEBEACFCAEECCGCGCFFFABGBGDCDGDEAEABHBHBFBHAHDCECECHFEFBACDDDEHAGABADFDFDBDBDECECEDHDAAAAEBEGAAADGFBFADACHEAACFGFGCGEHFHFCCCDGGBCEGFAFEBHCDAGBCBCDCEEGDBDBDHFHEBEHH,False +389,6.0,5.0,9.0,6.0,6.0,10.0,3.0,6.0,AFFFACCCEHHHHACDFDEGCBCDEDCFBFBDBFHFHADGCGCEFAFAEBE,False +390,5.0,5.0,8.0,6.0,3.0,4.0,2.0,9.0,CHCGBFDADACBFDFCHHDHDHCGCBFAEAEAECHCHBBDHH,False +391,17.0,18.0,29.0,20.0,13.0,16.0,17.0,22.0,GDCDGHHBEBFCFHGHAAAHBCDCDHFHEHBDDDDDCDCACHEBDBCBFDACBCBHACCDCGGGGCBCFCFBACADHHCFCADHHHGCBBGDGCGEEHEACAGGFGCABABDBEECECECFAFAGHHDHDFBFGFHECEFDFAHBHFGCACE,False +392,4.0,11.0,10.0,5.0,8.0,5.0,3.0,15.0,HHHHEEDDBGHGFABEBECCBHBCBEDECBCHCBEFEHDBDHAHBHFAGCHCHCBCAHFHF,True +393,5.0,6.0,6.0,2.0,4.0,4.0,5.0,6.0,HGFGHHHAGCGEFEBDFDAAHAFCBCBCECBGBEBHCA,False +394,21.0,28.0,17.0,22.0,17.0,15.0,15.0,14.0,DHAAAAFCDBDBDGGABBBCHCACGHFBBBBBBBAAAAFBBBBBEGEABCGFDHEHEDBAADEDEDEHCFEBEGDHFGGECDCHCHBDCEFEHDBDBDBDCECGCBFDGBADHGGFAFAFACEGEFDFBABFFEGDAACACHEHDHDCG,False +395,17.0,17.0,23.0,13.0,25.0,16.0,32.0,27.0,ACFCFGGGEEHEGGDEHBACACECEFEFHDEDFDGEGBGFHCCACEEFDACHGHGHBEEHBACCCCHCEFDAGAGEGCBHBHBGGGDGCFAHGHGHCAEFBBBHBGBHHEHEBGGEGEFHFHFHGHGCFCGHGDEDAAAGCBBBCHAEAHDHDFGGGEGBAHECDFDCAE,False +396,2.0,4.0,1.0,7.0,6.0,10.0,8.0,9.0,GCGFGFGHBFAEGFHFHGBDHEFEDHDEFEFDFEFBGHHAHGDBDHD,True +397,12.0,14.0,13.0,17.0,13.0,20.0,12.0,15.0,CEBHFCBGHGEGEACAHBHBDBGBADFDHDFDADHHEHFHBAAFACECECEDDGDGDCCCHCGBBDGFBECGDGACFFFFFFDHDHAEFEFBBGBFHFHECAFDBEHDFAFAEGFD,False +398,28.0,19.0,7.0,24.0,27.0,19.0,20.0,15.0,DHEAEADDHGAAHAGEHEBDBDHFCFEFEFEGAGHGBFHECAAGDCDADFCHDADADFDHGBGAEHDGFBFAFAFEFEFEHCAAAGGBBABDBCEADADFEGEFHADEGGGEGEGBGBDADEEBDBDHEEEDADEBBFHEEFCFEFAAAGABABDBHBG,False +399,0.0,3.0,1.0,3.0,3.0,3.0,0.0,4.0,DDHFBFEFDHBHCHEBE,True +400,14.0,15.0,8.0,10.0,12.0,16.0,15.0,13.0,BABABGHFHEHEAEBFGHDBCBGDCFFGAGDGFEFEFEFHDCAGAGHHAHACBCBGAGEGEDBDHDEBCACBHAHCFAFEBEDFFFBFGEGFABHGDADFBHG,False +401,11.0,5.0,16.0,15.0,7.0,18.0,6.0,17.0,EGDHHBGCGFFFFECHDAFAFBFDHGHAACFFFAEHBFDFHEHDFDFDABBEAFCCCCCCCFHAGADDDCCEHEHCHDHAHFHCCCFDHDHDADG,True +402,3.0,10.0,24.0,13.0,15.0,13.0,11.0,19.0,CBBEDHAHBDBDBGCECHHDHGHDCGCGEHCHCGCEEEEHFHFECEGBDDFBHEDBDADGFHCHCGCBCDCEAFGFGHGHCECFDECCCCCDHHEBFHFCFCEHFFCF,False +403,1.0,2.0,2.0,2.0,0.0,1.0,2.0,2.0,DGDABGBCHCHF,False +404,5.0,16.0,6.0,12.0,8.0,5.0,12.0,9.0,DGDHBCBCHGEEHEFGFBAGABADDCDBBBBBGAGEEDCDGHGHFHBHGGCEEDBDBDBCBDBGFAEBHFHGD,True +405,21.0,16.0,12.0,16.0,13.0,10.0,25.0,18.0,GFEFBFGGBGBGBHFHEBEBGBGFGFCEAGCDHAABHBEGCGHDHAHDCEGDGDBFGCAAAAEAGADFDGDAACACECEBFDHBAEACHGHAHDEDEFHHHBGEGACDBAGGBCBHHCDGAGDGHGHADAD,False +406,4.0,4.0,3.0,5.0,1.0,0.0,4.0,3.0,GBDDABCBCGDGDCHBHDHAGAEA,True +407,16.0,7.0,6.0,14.0,13.0,6.0,14.0,8.0,BFCAAAAAEFEBDFCFCADGDBDBDAGAHAEDEGHGHGFDBDGAEHEAEAGCEDHAEADGDAFADGGEGHGHDEBEHDGBGCCE,True +408,12.0,15.0,11.0,21.0,18.0,14.0,12.0,11.0,DBDBDBDBCBGGABCEFEFGGDBDAAAEHEFEBGBECCFCBGEEAEHCBFEFHFCEBFBHGADFDACABEBEAECDCGFDDDDDDHGEGFDHDHDHFCDDEDGAAFAFHHGHEE,False +409,20.0,21.0,28.0,22.0,20.0,26.0,20.0,22.0,FCFDFHADGDHDHBBCCHHDHDHDGAABAGCGCDCDFFFAEAFBHHGHCHEFEGBDCDAAHABBCFHFEEGEFFFCHCDBDEDEFEDAFAFABEHCCCEBHBDGDECCAAACDGFFEDHDFBHBAGAEAEFECGGGCHCDAHBGBDBCBEHGFCFCFCFCEGEGHFCBGFGCGCEABBB,False +410,3.0,1.0,3.0,3.0,0.0,0.0,1.0,2.0,DGACBHDHDCACA,True +411,10.0,24.0,18.0,15.0,16.0,10.0,24.0,18.0,HHFBFECHGHAHFGGDCBCBCEGHGBBAAGCCHCBDBGBDHHHBFBDBGGCGHGABABACEHEHCDGDECBAAEFGGDGEADDDHDHBEBEGEFEGEGCGDGDEDBCCCHCEBEDCGFGHGEGFBFBACHBBBBF,False +412,7.0,7.0,14.0,10.0,10.0,6.0,9.0,5.0,GEDFDFBAGCDABADDGAHEDEDFDCDCDFHCBCBCGCHBGCFCAEEEEEGEGCCCHHGCBEBCAGAF,False +413,1.0,1.0,2.0,0.0,2.0,2.0,3.0,2.0,FGCGCHEHEABGF,True +414,3.0,7.0,4.0,3.0,7.0,6.0,6.0,8.0,HCHGEEBABABFBEGFGAGBDFDEHEFCFBHHHFHCHCBEEGGD,False +415,17.0,22.0,23.0,22.0,24.0,17.0,20.0,16.0,BCBGBADDEHEBECCCCDGAGEGEAACEHEHGFABAEHECECFCGCECDBACAHADECGCBBFGFEHEFGDGEGCGFGDHDCBCAFGDGDAEFHFCFBEEHEBDDFHHHBAFAHDEDGDBDEDECFCFHFAGCFFAEGDGDADCBBBBCGHHABBBBBDED,False +416,23.0,23.0,29.0,23.0,28.0,15.0,36.0,18.0,HDFEEHAHFECBCGDFDFBAGABBGGADFDGEGECECGDHCECECEDEDACACGEGCGFBCBCACEEDEGGABHEDCHBGGGHGCGCBDBCCCEHEBGBCDDGGHGEFEGBBBDBAFAFAGBFFHHADEGEDBCCCACGCDCGEAHAEADGGGDGDBFBFCGCGBGBGACAHAHGEFDADEHEHAFGHBHDEAEA,False +417,6.0,3.0,6.0,6.0,13.0,9.0,7.0,12.0,HGCCECEAEHGHGCFAFHDDBDEGBGHHEEDAFGFHEHAAADBCHCGFEEEHEHEFEFDFHF,False +418,7.0,7.0,9.0,13.0,10.0,16.0,6.0,11.0,HEFFFEDECCHHBHFDFACACEDHDBDBDBDFCFDEDEBHGEFFAFADAFHGBGCGCFDEAHDFDHGHFHCGEFEFABC,False +419,6.0,2.0,4.0,3.0,3.0,0.0,2.0,0.0,EEBDBAAAACACEGGCCDAD,True +420,20.0,21.0,13.0,17.0,21.0,27.0,25.0,13.0,HAGAGAECCFDBEADDGAGFFDCBFFCABGBEBAGCGBFBGEGEFDCDEBFBEDCAHBHBDFDFBADGFFEGEGEFEFEFHFBBABAHHDGDGBGAGFGFGEEDEDAFAGDHEACACFFGFGFGEDECBFBFHHHGEAFAEAHFBEBGBCHCHGADC,False +421,9.0,14.0,14.0,8.0,6.0,14.0,12.0,12.0,FHFDFDBBBGBEBCBFDGDHFGABCGABBGEAFAHACACHDDFHCBBFHFHFGCHCHGBBHHGCGCACACHCEFEFADDFEFEGGCGCB,False +422,2.0,4.0,4.0,2.0,2.0,3.0,4.0,6.0,HFCFCECBGGGDGBEHFBAHAHBHDHC,False +423,19.0,10.0,8.0,8.0,6.0,9.0,8.0,8.0,DEABABCFEFDAAABFHFAFAFADACCGBABAGHBABABAGHEHCGDGDCDCGEHEGDAABAEHBAGACDFFCFHH,False +424,22.0,16.0,21.0,30.0,13.0,19.0,17.0,12.0,BCBEBDAEAEAHAHGHCBCAAEADGFGDGDCACFCDEGCDHBCADDDDDEABADADADAEGBGBHCGFAFDCDBDFACDBDBCFEHEHAHGFGFGFGECHFHCCGDGACDFDECFDADEBHFFDFDFBFBEHAGCGDFCBGDACBCFDAD,False +425,12.0,15.0,7.0,11.0,10.0,19.0,9.0,9.0,CADACAFHFDDCDBFBDBEBEDEHFABACFFHHGFDFDGDGHAHACCBEFDFGEGEADFFCEGBABAEHHBHBGBEBABGBEFFFFABGFFF,False +426,10.0,14.0,11.0,11.0,11.0,17.0,18.0,9.0,BFBAAEFEHCHGAFEBCFCGCGBGFHFCGGAFAFBFCFHBBFEFEFEBGCECBGBGCDFDBDBDGAGEFEGHGHAADEGCGHDBAEGDDDDCDFGFGABHH,False +427,37.0,20.0,35.0,16.0,24.0,26.0,23.0,17.0,AGAEEHGHGCCCGBGCHCHCHFGGAAAEAEAFHCHCGCACADEEECBABEFEHDFBFEEBBBCEFAFADACAFFCFDHDGBFFACDGDFDBBBCGCBAAAEAECGCDHFBDBCAAGACACAFAGGBEHECECEABFEGDFDHHAAAACHCHGHCHABEGCGFACCECFFBFBABAGFFDAECEDEFFACGCGAGCDFD,False +428,16.0,17.0,31.0,28.0,15.0,17.0,26.0,26.0,FGFCCACBEDEDBCGCGFDCAAECEAAFFGGGGHCHCAGDGDBHBHFHFHFHDHAGGDDADHDHBACGCGEDHBCDFDGDHDCCCBBBBGCCCCFBDDDBCCCHCFEHHGFBFCCAAGGDADGDHEHAGCGCBDBFBFEGAGEGHCFDHHHHEHEBEHDFDGDHAAECCCEDEDGH,False +429,8.0,4.0,6.0,7.0,12.0,5.0,7.0,6.0,AAHAGBFHFCEAEBECGFGFGEEECBCDCAEHEAEDEDHGHBCFDGEGDHDEDAA,False +430,5.0,7.0,8.0,4.0,4.0,3.0,11.0,4.0,HGDCHCBCBFGAGBGBEDHAEAEGFGCGEGAFCGCGDHDBBBCCGA,True +431,8.0,19.0,9.0,16.0,16.0,15.0,11.0,12.0,FABCEHHCGDGDFDFHFAEDGDFDFBBBBFEDEAGBEEEFEGEBEFDDGBBAAAFHFHEEDCDCGEDBDAEHEHBHBHBFGCDCHEDBFBGHGFBFBCBCGCBAHD,False +432,25.0,23.0,17.0,34.0,27.0,19.0,18.0,34.0,GBHHHFEGGFGFGHBABDBDBHGGEBBDEDHHHHAHFHEHFFFGBDDEAAAAADCDHACAFDBDCGCGDDDHAGBDHGHCHABAFEFEFEFDDBDBABGFAFEEDEDEAEBFDFDHAHABEBEDDDFHCEFEAAAECCBABHDADHCBFGDHEHAGBDHHEHEDEAECEDGCEEHDDGHCHCHEDDHBHCHCACBCG,False +433,11.0,10.0,8.0,8.0,5.0,5.0,7.0,5.0,GEEEBADHCHEBEACABDBDAHABABABCDCGCDABFDCACABGGAGHCHFFDDGFGFB,False +434,8.0,2.0,9.0,3.0,9.0,11.0,9.0,7.0,CECFFFHGHBHCFCFBFHDACEEFCGEDEDAAAGCGCEFFAAGGGHFHFHEGEGECAA,False +435,15.0,9.0,12.0,17.0,12.0,13.0,11.0,8.0,FEFHFAFEDEDBCGGFBHACGCFCHADADAFAEAEADHDBDFHEDEDBBGBDADAGAGEGECCHEAACBCDCEGFGFDADGHHFDFCCCBDGEFADB,False +436,9.0,4.0,4.0,2.0,2.0,7.0,7.0,7.0,HEFBABCEFAFABGGAAACFCFGHBHACGFGAGAGHHDHDHF,True +437,13.0,14.0,15.0,27.0,27.0,6.0,29.0,26.0,DDDEHABAHEHAHDCBGDHFCEGBBHBHADDEAGGEGDGDGCCDCDBDBHBHBAAHGGGGACECEGGGECCDGDGEGADADGFHEEDEGACAGHDDDFDFBEHCHGHFHEEEHEHEHEHEGEFDGDGHBCCEDHBCGDHEEBAGHGEGEGEDHBHCD,True +438,22.0,9.0,13.0,21.0,26.0,17.0,18.0,21.0,GAGEHFHCEGEDAFAHAHEDBDFDABAHEDGDBCAEGDDDGGGGAGEHHHGCCFHHBHBHBHAGECAGDGDGDGEHDFAGCEEFEHEAEAEFFCECFFFBDADFDADADAFEEEEAFAEEBABAHEFDGHEHFCDCDCECHCHFEAH,False +439,24.0,19.0,22.0,19.0,24.0,22.0,19.0,24.0,DCDCAAAAABAFGFDFDHGCGCGBDACCCCEHFACHEDAAEABAHABAEFHFCFCFBBHFHEHEGCGDHFECBBBGBEHEAEAHDGDGHCHFBFEFEBEDFAACDHDFBHADCCEHEHDBFGFHDHDGEGADADEDEBECHFGGAGEFCCBCGFBBAGEHFHGHEHEFECBGA,False +440,23.0,14.0,11.0,16.0,9.0,11.0,13.0,16.0,DCDGBGBAAHECEFGFGAGHHEDGBCFDFGHGEEFADAEGFBAAAABFBFDAACCCEDHHHDDAAEBHCHABCHAHAHABEDGFGBGDDDDDDGAAHACACACABFFHBHBHB,False +441,5.0,9.0,7.0,7.0,5.0,6.0,6.0,2.0,CFDBDGCADBDBDGAAEAEBFBCBFGHBEGDHDECECBCGFGFBFAC,False +442,21.0,17.0,17.0,31.0,26.0,21.0,12.0,20.0,AAAGDEAFCHCBEDDBDBDHCAAHBDBDADHFHFHFHFHFDFEADADHHCHDDCFBFACHDEEEDABADAFEFHCACFFFEFBBEHGDGEGFDDCDGEGECCCCCFCHDEEECGCFDEDGBBDBGGHBFAFEDADFDHEHDHAGDGDBAEEEBEDAHAEBEBEAE,False +443,22.0,20.0,27.0,22.0,26.0,31.0,22.0,17.0,EDEAHFDFEBGFEFHGAFAFEDEAHDFBEDACCCBCBAFADAHFCGHGHDCDCGGHBBGACADFEFEFBFBFBHBHAHAGGGEGAGACECECBAEFFDEECDFECECBCEHDFCABHBCGDHBFBFBFAEDCFFHFCFGFDEDEDGFGFGFBCHEGGCEDGCCHDGFGCCCACEDEAEABABADFDH,False +444,25.0,15.0,17.0,18.0,21.0,13.0,21.0,25.0,GCAFBBBBAFGHBACAFHCECHBEDEHHHEDAHABCGDEAAABDBHAHBEGGDGACDBGGGGHGHGCECEFHFCCGBEEEEEDFCGDGDADADCECBFFCAEAEADGDHAHAHEHDHAHEFEHDGFHFHBDDAHAGAGAGAGEFBHECFCACHDH,False +445,4.0,5.0,1.0,1.0,6.0,3.0,0.0,1.0,FEBBABEBEAFHFEAEAEBDC,True +446,3.0,5.0,3.0,4.0,0.0,2.0,5.0,1.0,DBDAGBGCGCGCBBBAGFDHDFA,True +447,27.0,17.0,19.0,29.0,21.0,26.0,19.0,16.0,AAEEEEFDFHEADAGFGFGAGHFABBBBDADAHFDGCHFDFAFGCCBFFHDHDADEBHGCAHAFCCGCHEEADCBFFDFAFACAEECDCDBHBDCCEDEAGABDBDGGGGHFHFHDEAFDCDAAABAGCGFDFEEEBGAGAHBGDGDFDFDHHACCDCEBEAECEFEFDFDBDB,False +448,12.0,3.0,7.0,7.0,6.0,6.0,10.0,15.0,GCACACAFHFHGHDHAHDDEDCFAHACAHGEFHBHBFGDEHEAAAGAGCDAEGEBHDGFGHHCHGH,False +449,27.0,20.0,31.0,20.0,16.0,31.0,25.0,16.0,CCFCACAHBDGCGCBCGCDCBBEBAGFFFCFCDCBHBEFDFDHGGDCFEDBDFDCDCFFDBAECHADBCHCHCAAAAFAFADDGFCECGCGDDEHGHFFEHGHGFGFGAEFBFEFDBHAFDGGCFAFHHHBHEAGAEAEABGHFAFACACBCACGBBAGACAFFGFGFDBCBCGEEEECFADGBGA,False +450,2.0,7.0,4.0,2.0,6.0,1.0,3.0,3.0,DGCGCBDBHCECHBEGEABFBHEAEBEB,True +451,8.0,7.0,6.0,1.0,2.0,4.0,4.0,3.0,FGFHEABCCCDBABAHCHEAGCGCBAAAABBBFGF,True +452,12.0,16.0,17.0,11.0,29.0,15.0,19.0,16.0,EGDGEGHCFCFDDBECFHFHGEBEBEBEBDBAHAHADCEEEEEEEBECCBBBGDCDCFGHHEACAGBGHFEGEAECFDEGFHCEDFDFDCBHEAEAEFBGCGBAHFHGGEEBFGFGEHAGAGAFCBHHHCCECEG,False +453,4.0,3.0,6.0,2.0,6.0,8.0,4.0,3.0,CCFCEEHCHBDEFAFAFHGDFEGEFBFBFCECGAGA,False +454,17.0,13.0,25.0,22.0,19.0,16.0,28.0,27.0,AGAHHCDEDGGGDHHFEEGEHHCGGHGABCDCDAAFCFCGAGCFFFHEEEHEBGBCFHDAEEBDCDCGCGCBHBFCFHDHGBGDHCHFHBHDHBEAFCCDEDAGCGCDCFFHGHGHGAGADACAEABFCECECEBEHAGAHHDGDGHGHGFDFDEBCHDDCDGBGEA,False +455,3.0,8.0,5.0,6.0,3.0,3.0,1.0,4.0,ADHHHDFFACBCBCHCBDDGDBDBEBEAEFCBB,True +456,17.0,25.0,25.0,21.0,21.0,26.0,24.0,21.0,GEGBFBFBFBGAHAFACDEDCCHFFGBGAACFCHGFCFGHDAEFEFGFGHEBEBDAFGFAFCCBABEHCGFEDEDGBGBFBEHEGGCDCDCBGHDCCCDFAGBHBDEDHCHCHEHCBCDDDDFBEEEEGGBFCFCHAHACGFBBHDHBABGBGDGDFAFAECECEFDFDBGCHBAAHHEH,False +457,12.0,10.0,8.0,8.0,4.0,11.0,8.0,8.0,DBDFDFCCCHBEGFBHEFACBDBGHGBFAFGHAHAHGDDDCCACGCEHGFGFBFBABABDHFAAAEAFA,False +458,20.0,11.0,18.0,22.0,26.0,28.0,20.0,28.0,BFGHCHEAEAFFFFGABCFGFECECECECHCHGHDHAHEEEFHAAFBCGHDHDHCABGHCFDGHGACFDDDBCGDDFGGGGEEABGFAFEHAFEHAFAEAEABAGFDFEEHEFECDADHDHBHEHDHCHFHDHFHGDDDDEDEFEFGDCHCECEFHFAGBFFEFCADGBGBHA,False +459,18.0,25.0,19.0,16.0,13.0,17.0,21.0,14.0,CACACDEDBCBHAAGHBHBCEDEDAGGHDFDEDCHFHECFBFACAHAGGGGGAGDFBABFFGFBHBHBGBHBACABHBGCGBGEFADCDCHAHDHDBACABBBGEGEFCFBGBEFDFABABFCEGECDCBCGDBEGFFCFDGE,False +460,21.0,19.0,19.0,30.0,29.0,19.0,23.0,32.0,FDEDECCDEEHFDFEFEFHAHDCGCGCFDDDCGAGAECDHBEBAHGCGEFEDHDHDGDBHBADCDCHHFECHBGBEHADBDHGHGHGHDHFBGAGHBFBAECGGFEFEFDGDCDAEGEBACHGGDDADFHAEABBGBABDFDFABEDAHBHAHAEDEAEHEHCFCHEHEHBHBHGGCACAHEEEEFDFCGDH,False +461,9.0,19.0,19.0,25.0,19.0,17.0,20.0,16.0,BEGCGDAEHEDBDCEHECACAEAEAFCEGHGHFHGHCEDDDHDEGGFEHEFDFGFDBDBDGDEDCFCFHECBDHACCBCBFGDGCHBHDDBGBGFCBCDDGDACFGGGGFGBEBEGHDBDFCFBFDFDBHHAHAEDFBCBEBEC,False +462,9.0,14.0,11.0,15.0,9.0,10.0,15.0,17.0,CHCHCGCBEBDHEHFBGDGDGDGDBDGEGCHHBDBDACFCHGFEAHFFDCGAGBFHEDEHHAHAEBHBHGAGBFBDBCFCBCBADAGEGHHEFDFDGDAH,False +463,15.0,16.0,16.0,16.0,13.0,12.0,15.0,14.0,EDEGEDHBHDHDACHCBCAHADGDGAEEHFGFGFAEGEDECGGAFAFDBCHCGCEBABABABDEACHCBABAFGEACFDBBCBEGEGCDCDADBDFHHHHHBDCDGBFFGFHCBCFG,False +464,20.0,13.0,10.0,7.0,14.0,12.0,14.0,15.0,HHHBDFFCHCGCGAGDFDGEBFBABAFAFHGHBAGEGEHBACFCEDBACCCABADAGBGAGEEAAFAFACGCFAHEHEDEBAGEHEHEGAGAEFHHHHABEBDBF,False +465,32.0,28.0,23.0,18.0,15.0,22.0,28.0,21.0,CAHHBFBGCACEGFGAAABABAGGCGCGEAAGCGEEDBDGDCDHDBBABAFABAEDBGCEDBDBAHABFHEDEDBFFGAGHHEGAGHEECDCFBHCGBDBDBFGFDFCFAAACACFGHGAGDCFGAGFFBHCHCEABHBFBFHFAFHFEFBABGBGBGHHHAHAGEFCCHBHCAGBCDCECADADAG,False +466,14.0,31.0,26.0,20.0,17.0,27.0,15.0,13.0,BBBBBCGFEFDFDFCCDCHHDAFADACCEAGGCGCACFFEGECEFECCACGEBAGDGHBABDBHBHFCBHFCFCAHDCDHBGFEEDEDFAFHHGBBFAFCCCFAFDFEBBABACHHBDBDBFBCCFFFFFFDBBBBBEBECEGEGDGDGEGCHEBCDFBBBDD,False +467,15.0,12.0,15.0,11.0,17.0,18.0,18.0,13.0,HAGECCBCFHEGGGGBGBDBGBAFACCFCFCBDFAAAAACEEEFECDFDCDCDHBGGGFGDABAGAFFEAEFHBEDEDEFBAHGCGCHFGFGFHHDHECEAEGFAFHHEHEBBGEHFDC,False +468,22.0,12.0,14.0,17.0,19.0,18.0,16.0,15.0,DADADADAHAGABAEHFGFGEGBHBGADHDGGACHEHCHGEFFBCGCAFGDGAEHEAAFCFGAHAHEDDFDCHFEFEDEBECABEFGBGAGCCECFCBBBBHAEBECCADEDHHHEDEDEDFFFFGDAAAFCF,False +469,18.0,26.0,29.0,20.0,29.0,19.0,16.0,15.0,CGCGCHCFCGHHCHCHCHCFAEAFFECEBFGDHDCECECHCFFDBDEDBGGEGAGEHBBCCACABEEEAEBEBACECGADBBHBDBEFEFEFCDDGCCBAHHFCBHBADAGFDBEFEFEAECBFFHABDBAEDECECEDBFBDBDBDACGEGEBADCDGBGDGACFEFBAEH,False +470,6.0,1.0,5.0,5.0,3.0,4.0,4.0,6.0,CBCAGGHDHDHDHFHFEECACADHCAFAFGEADG,False +471,8.0,12.0,3.0,4.0,7.0,8.0,8.0,2.0,GAAFBEGEFDAGEGEFEHGBCFFFFGBBBEBABABDBDBEBDHGCABACAGF,True +472,9.0,4.0,9.0,5.0,3.0,6.0,1.0,7.0,HACGCABHCEAFHBHDAAACFCBEDEDADAHFHFCFAFBCDCHC,True +473,2.0,1.0,5.0,2.0,7.0,3.0,2.0,10.0,CCHCDDGFHAEBEHHFACHHFHEHEHEHECEG,True +474,8.0,7.0,5.0,9.0,9.0,4.0,1.0,12.0,BCDHBCBADCDHHAHDHAHEDEDBHEEDHCHAFAHAHCEGDADEFEFEFABHBEB,True +475,11.0,5.0,2.0,1.0,3.0,2.0,5.0,4.0,AACDCFHAGAGAEBGBHBFEAGBGAAAHAHABE,True +476,25.0,30.0,25.0,21.0,26.0,22.0,25.0,24.0,HGHEDBDBCHEHEDEDEDEDCAHDCGCFDFGEGDGAGAGHGDGDCAAHABAFACBCBCEDEAEDEAGDFEBEBEHGHFHFCBBFGHGFEFBBBFHGBCFCEBABADHBCACGFHFACACDFABHEAEHHDGACHFBFBHBHBABGGDBABGFEFBHGHAHEBGBGCFBEBECGCACEFAGECACFDFEAECCBGHCDD,False +477,15.0,14.0,22.0,19.0,17.0,22.0,25.0,22.0,DFGGGFHHCHEHBGDEEBFBAAHGFGFGACCCGHFHBHCDEEFEFBFAFBFCGCEDEHEHEBFAFAFAFGCGCGDBCBFFCHCDDDEAEAGDEDECGDGABBHDHDFDFDGCGAHEHFHCHAACDDBHHACBGBGAGFFHCCGHHCCGDGDGCGEE,False +478,14.0,12.0,9.0,13.0,13.0,17.0,7.0,13.0,AFAFBFBDAAADFFBFBEHGFEFHAHFGDDFDHAHADABFBFHEHECCACGFBDBGAEHCDCHGHGEAECECEFECADFDBGBHBHEHDDFEFDBEAC,False +479,29.0,20.0,16.0,24.0,27.0,18.0,17.0,26.0,GEHHHAHEGBGCHCBCFGDGBFDHCCBCHFHAEFEGGDHDACEDDDCDFDFDHBAADHFHBEFEHCHCDFAFABAEGBHBABABAEHEAEAEDEAFHEDAGEBEFGCEDEFEDHBFFDFAHHDBDGDHEAEGCBDEDBAGAGAGAEAHACACAEAEBHAHGFGEBEADADBHBHFCC,False +480,11.0,14.0,7.0,9.0,18.0,15.0,6.0,9.0,FAFEGDGBBEFEDEFEFABAGEGEFFFBBCBEDABEGAAAFHFDEHHFBFDFAFCDCDEGHHCHBABCBEHEHEBEBEDEHABEFACDC,False +481,8.0,4.0,7.0,16.0,11.0,8.0,9.0,4.0,EEADADFDEAFBFGEGFGDGCHDDCDEBEGEGCFCHDAGCGDGAECFCEDDFDEABABADDDDEHFH,False +482,11.0,7.0,25.0,5.0,16.0,24.0,10.0,11.0,EAEAEACFCBCEFEGAGAGCCFFEFGBCFFHFCFAHACFCEEHCCFDFEEHBHFHAGFFEFEBDAGCGFAFEFEHECGCGCFCFHFHCCCBCDDBCCCCFDFHAECBHG,True +483,24.0,31.0,31.0,29.0,20.0,23.0,19.0,21.0,HAHEECBBBBGBECEFBFHHCHFHDBGBHEGEADAEAEBBFBCECFCACABHCHCEBFDFCFCFBFHHHEGCDCDCDHDCECGABADDDBAGAGAHEDEBBDGCBCFAFABAHCBCFHGHBDEDGBGEHCDCFCFCAHFBCDCDGDHABGFEBDBDBDGAFAGAFDDCEFABAFDDGAFEFDGCBABHCGDGDCDCAE,False +484,10.0,14.0,9.0,7.0,6.0,9.0,6.0,9.0,HCACBFBFCFCFHAHADACABDCHGHGCBFDHCBGBABFBDBFBEEHADADHBBEBADAGECEFHBGEGF,False +485,10.0,4.0,11.0,5.0,13.0,7.0,15.0,10.0,AEAEHCHCGCGCBEGEGFGBGAGFGEHAFGCHDECCAHADDFDFHFHEGEGACCBHDHAEGEGCGHBEEEGAFAC,False +486,10.0,4.0,4.0,3.0,10.0,7.0,9.0,8.0,HGHCFDHAFAECEFHFHEGECHDDACABAEEEGGAEAGAGAGAHFGFEHEFGBBB,True +487,5.0,6.0,9.0,7.0,10.0,8.0,5.0,12.0,FCFCFHFAFAFGEDCBEHHGGEHEHAGBHCHFEAEDEDBHADCBCDHDHDFBEBCCHCGEHE,False +488,11.0,11.0,11.0,8.0,15.0,8.0,13.0,12.0,CBABEBFHFGEGHCDCAGDGEABBCGGBBHEFBBABGBADEHCHCEAEAEGEFFFCGCEHDHDHECDCAFAGAGAGEHEGFDHCHEHED,False +489,22.0,25.0,26.0,26.0,18.0,25.0,28.0,23.0,BEBEBEBFFHDHDHCHDHCCGCFAGCHCHCDCGCABABAFCHEHBCBCDCGCEHAHAEGGABFDHEBECGCHCHFDADAHHEGFBHAHFDGDCCCHFFGGGGBFAFABGFEFAGGFGDBAHFEGEGEDBBEDDBHBDFDFGGCEFGFBFHGADADHCEGEGDGDFDBBCBCDGBADABAFCFAFADDDBCGAE,False +490,19.0,24.0,22.0,16.0,30.0,19.0,23.0,31.0,FGGAFEFECGHHEGEHEDEFEHAGFBFBFHAEAHAEAEACDEBBHCECACEGBBFBDBCHDHGCFEHHAHAHBEBECGGDGCHBHGFGBDFCGHGHDHBHBACACHBEAABDHEHDHFFBFHFHEBCDEDEDFDGEGAGADBCHFHABDBDCFAEAEBEBECGCGEHHCCBCHCEGEGHFCGEG,False +491,16.0,23.0,19.0,29.0,31.0,20.0,28.0,25.0,DHDBCECECAGFGBBEEEECEDEGHCDGGAFDFGFGCGCEHGHGEDFGCDFGFDDDCDEFEABDEDEBEBHBHBGGHBDBHAFABDGHCECGAEAEAGABHDHDHDHBBBGEHEFEDHBEEEGGCDEFGHGHAHAFCFGFEDCFEABHFHEBEBDHDHACBCFGAGFGHEHBGBCHFGDDADCDADFDECB,False +492,2.0,8.0,8.0,4.0,4.0,4.0,9.0,3.0,GEGFACBGAGECCHCHCBFDGHCCGCGBDBDBEBEFDFBGBG,True +493,21.0,13.0,20.0,26.0,11.0,13.0,10.0,15.0,AACGHHEEDBDBDCDCDBEBFBFEGDCEADDDFAFAEAHHHFAFADEDCHCBCAAGACDDDDDBCAGDCDBEHGHGFGABDHDHCCCCHADAEAEDHDAACAFAFBFEDGBHCCADHBGBDFCFCHCFG,False +494,4.0,3.0,5.0,3.0,3.0,7.0,4.0,3.0,AHFEBAHCHGFGFEFDADBFFCFCGCGCBEAD,False +495,0.0,4.0,1.0,1.0,4.0,0.0,2.0,1.0,BDEEBEGEGHBCB,True +496,6.0,16.0,13.0,12.0,12.0,13.0,12.0,10.0,DHFEEBAFCHCHCEFHABBCBCFGECECEGEBDCDCBBBBFAFEBEGGCGAGFHEDGBGEGCHEBDBHBHCGBHAGDFDFDFDFDHCADFDFGB,False +497,19.0,9.0,12.0,22.0,14.0,24.0,20.0,18.0,DEDAHEBAAGDBHHGABAGCHCDCACFCGCEEACBFAFAGEDDDHHHCHCGFGHBAGAFAHDDDDDGDFDFHFEEDEHFHEBFDFHBAGHGHFHFEDEDFDFDCGBFACAGAFHFEABGEGFGFGFECADAGGDGFFF,False +498,8.0,3.0,6.0,14.0,8.0,17.0,6.0,15.0,GFFDFEGGBEBHAEDGFAFEFDDDAFHCHCDCDGFHAHFHFGDHCEFHCHCFDHDHAFDFEFAFABAEHFHDHDEDH,True +499,0.0,6.0,1.0,2.0,2.0,3.0,3.0,4.0,EDECHDBGBGBHBHFGFBHBF,True +500,9.0,11.0,8.0,10.0,19.0,12.0,9.0,5.0,GCFDBACGFBFAAAAGBFAEGFGCGHEAGHDFFCEDEDEDEDECHBEGDDEAEFDFAFEBEHEHEDEBEBEBCBCBFFEGBCE,False +501,8.0,14.0,12.0,11.0,8.0,12.0,9.0,4.0,DBDBEBDBDFDAGCGFBCBCFFGCDCDEDBBBECECFBFECABDDAFAFAGEFBHAGAFCHCDCGHGHBFBEGEFCAG,False +502,5.0,5.0,5.0,5.0,9.0,6.0,4.0,8.0,FEFEBHHHAHABEBDDFDHDCAFFECEAHCBCEAEBHGHGCGFDEGE,False +503,12.0,12.0,13.0,25.0,16.0,10.0,18.0,21.0,GBGBDECCCFHHBACGDGDGDADCGCBBHDHDHDBDFDFDHEHGCEDEGEFAFHBEFFGCEHFFDDHDHGHGDAACAGBDHGHEDEDGAHCGDGDACEGAHAHDHEHEBEBCBFBEHEADDGDCAHE,False +504,10.0,15.0,9.0,13.0,14.0,7.0,8.0,9.0,CBEEFBBGBGBDBABADFBAAHEBEDEDGFCEBDBHAHBCBCBGGFDFCAGAFDGDHDHGEBEHFHECECEAHCDDEHEAEADCD,False +505,18.0,16.0,17.0,23.0,12.0,18.0,20.0,12.0,FGFABEFDHDHFHGDBDBGBGCACDDDHAHBHFFFBGCGEAEAGABHBGDGCECEDHFAGBDEAAHCEGHDEDEDFGHDDDDEFFAFGDGCFCFDFDACFCEAABGBABCBCFHGGBGEGAACCCCFCGBADADBD,False +506,22.0,16.0,25.0,22.0,25.0,11.0,27.0,18.0,AGCDCDHDBGCGAGDDCDGBGDCBCGFGHCECGHGAEFEDEAEGEFHGBCBCAAAAGGDGEHEAEDEDEBCBGFCFGDDEDECFDHDBEAEDEHGHCCCCABAFABCBAHCHGHCCDCEFAGEHAGAGHEBCHEGBHBHDHFEEEACACDEDEHGGGFBFBGDAAA,False +507,13.0,17.0,22.0,10.0,17.0,14.0,17.0,13.0,GGGCBBBEBHAEAGHDCGCDHFEAEABHCHGFGHGCCFFBCAAHEHEDCGCGCDADEHAHFDFAFCHCFCBDEEAEFHAHFCFABBDBDEGECEBGBGCGCDEEBEBFBEACBCGCGBGCFCF,False +508,17.0,21.0,24.0,12.0,17.0,20.0,19.0,17.0,ECHCHCHCGCFBGAGEBEBEBDCCFHFGCDFFHHBGBGDDDGFCFCGDGFAACACGFHDHGAAHAEBEGCCCFGFADADHBBBBABEBEBCGCHDHBGEHCACECEDDCFFAFEBACAEHEHBGBHEFAFBGHGFBCBEAEAGFFCF,False +509,4.0,0.0,5.0,5.0,1.0,0.0,3.0,4.0,GHDCDCDCDCAEHGCDHHAAAG,True +510,10.0,11.0,3.0,4.0,7.0,2.0,18.0,3.0,HAGGGGAFAGCGEGBGAEBGGEBEBDCEGDBDADEBEGAGAGBBBCGGBGAGHBHAFA,True +511,2.0,4.0,2.0,2.0,1.0,2.0,3.0,1.0,DEDFHGABBBBFAGCGC,False +512,2.0,4.0,2.0,1.0,1.0,1.0,0.0,1.0,HDBABCBCBFEA,True +513,4.0,5.0,8.0,7.0,6.0,8.0,11.0,4.0,GGHGHGDBCECECEGFHDABADEGGCGCECBFEGACFFFFBFCFHBAGGDDDD,False +514,20.0,26.0,19.0,15.0,24.0,22.0,24.0,21.0,FGFEFEFBHGHBEDHHHHEDCDEHEHCBFHGAFAFBFDCACAGGGGGGGHBBABFBFBCHGGBACGCGDFEEEEAEFFFFDECECFCBCBEAHCBADEDAGFDEDBBEBEHACAFAFABHEEDCFGHDAABEBEDGGHGHGDDFEFAHAHBGCGBGCCCABBHBAGCBHBE,False +515,22.0,23.0,26.0,33.0,16.0,30.0,25.0,23.0,GGGGCBEHCBCFEGGFADHDHCGDACCDBDGFCFHBHGAABFBAHAHDGDBDADACGCFDFGFDDHBGGGEBEBEFGFHBEFABEGCGCGHAHFHFHDBDBDCDCDCHFFFHFDFAGEGBABFEDBDCECBCDDHDBGECADEDEFFFFAFDFDECGHDFDFBCGFECHHAHAHGCBCDADAEAFCFCDHDABAHABC,False +516,17.0,13.0,13.0,12.0,15.0,20.0,10.0,20.0,FDFAGABHFHCEEAFCEGGBEBCBCBEBDHFACGHGCACACAHFHDBGFGDAEAEABFDEDHDFAFEBDHHHFHFHFHAHAHAEAFADCCFBBCEHFFFDGDGBEHHHHGCBEFEAEDFC,False +517,26.0,21.0,23.0,17.0,23.0,30.0,24.0,22.0,ABAEAEAEBGGGGGAECECEDFCEBAGHFHAEADCCGGGAGBEBEBEDCDFAFHFHGCCBHAFAFAFHFGBCDDFACGFGHDEEGEFEGBGFGADFCFCFCBAEABCDHHHCHFHFHBHAEFFFCFBECCCFFDFDBCHCADAFHBABDFDBBAHGGEAEHCGEGCDAGAHDGDFHFHFEBABEBH,False +518,7.0,13.0,9.0,12.0,7.0,6.0,7.0,5.0,CGCECBHDEBGBAFCDBDBDACEBDDGDGEGEFAFAFAHCFEHEDBCBDBDCDBBBDCHFBAGAGH,False +519,15.0,23.0,14.0,11.0,17.0,17.0,14.0,16.0,AFGEDCHBBBBBBGGECEFFBACACBCGCBHFAAABCCEEDDDHBBFBFBGEHEFDAEAFFFEHAGABAFHFBDBHHHBEBEACGCGCACDCHEEBEGGDGHGHGDDDCBGAEBEFEFAFHHHFHFB,False +520,18.0,12.0,17.0,12.0,18.0,12.0,16.0,36.0,EGEHCHDHDGDGCADAHAHFCEEBACEEEADAHHBCBEHEHEBAHCEEGCFEFAFABHBHGHDCGCGDHDHFHDHDHAHCHABCGCFBHHAHFHFHFCEHEAAHHBHGEAHHBFCCGBGFHAEAEGCHBHGDGDGAGFHHC,False +521,4.0,11.0,9.0,6.0,9.0,15.0,6.0,12.0,FFFCCHBHCFCBCBFDDGDGBFAGCFEFCHCGFBBBHCHDEDEAEBHBHGAEAFFBEGEHEHEHBHFFFFHD,False +522,17.0,10.0,12.0,14.0,22.0,13.0,17.0,18.0,EEEEDEABAGFEFEHGHBDAAABDBDAEHHAHGHGHDHAEABHHHHHBCGCFCFCDBAGACEEGCGAADGDHAFCFCEBEFDFEEACGHBEFEFEFEDCGFGHGEGDBAEGEDCHAHGDFDGC,False +523,0.0,4.0,3.0,2.0,1.0,0.0,4.0,2.0,DDEBCHCGBGCGBGBH,True +524,25.0,20.0,21.0,11.0,21.0,16.0,21.0,28.0,FGHGHEHEHBHFHFBFBDBEGDCHCGAEAFCDEAAACHEHEHBFFFFAAHCGGHGBGBHCHCDCGAGAGBHHHFDCDAEABBBCECBGGFACHCECEAFAGHFAEHGGEDEDEBHHACCCACBCHDGDGAAABAGFEBHAGBGCFEEDEAEAFBECHHAHBHB,False +525,5.0,5.0,3.0,6.0,5.0,16.0,3.0,8.0,DHFHFEFEADAGEGECBDFCBDDFHCHFAAAFEHHFBBBGDFFFFFFFHFH,True +526,1.0,0.0,1.0,1.0,2.0,0.0,4.0,6.0,HGHCHEHEGGHGDAH,True +527,14.0,26.0,15.0,11.0,16.0,18.0,25.0,17.0,BHFABADGFABCDGGECEBEFEDBDHGFCFDBDBCEFBFHAGBFEFGFHFHCHBHEHFHFHCHCEDBDBEGHGHGCBCBGDEEFCFBGBGBGBCBDBGAEAGBGAGECEAFGGGHGCCAFGGEAEDBHAGABAFAGHHCBBB,False +528,26.0,33.0,22.0,21.0,21.0,26.0,21.0,23.0,HDBFBDGDGHHEBFFCECFBABGGEBEGGAHEHABGBCCCABDFEFGFADACCGABDBFBADADBDAHAHBEGHFHBEGEBCBCBHAHABADCHBGCDEDEDHGGGGGCDBFFFFFAEECHCHCFEBEAADFBFBABDBGEEHEGEFCFCFEAEADCGFADHHFBDBAHAHACABABFBFCFHBHBHCDFGCD,False +529,19.0,28.0,16.0,26.0,16.0,17.0,19.0,17.0,ABADGCGBHDFFFGFGDGFBDGGFAFCGGFHHAAFFFEAAHAHCBCBABADDFFFABDBDBHGDACHCHGBBBBBGEDADAGCBEBHHEDBCBCBDEEGADABABADADCCBCBDFDFCBCHFEEEDEHHHGHBHDEECHGDGDBEEEDEDGDGCBBD,False +530,10.0,4.0,8.0,6.0,5.0,11.0,7.0,6.0,FFBFCDCGAGFEDCDBEGEGFCFCFCBAFDBHAHAHAGACAHAHEGDFCFADEGAFH,False +531,13.0,7.0,11.0,9.0,7.0,13.0,13.0,17.0,GCABEBFBAHHHGHGAAHCHBEBCDAFHFHBCDCDCDFGEGCHAHEHCHDFFFGFGCGAAAHGGGHFCECHHHGAAEADFBFDFDEDAGF,False +532,6.0,4.0,4.0,4.0,4.0,11.0,3.0,7.0,ABCDHFHFECEDADFGHAFCFCFBFBGADEHGBFHEHFHFAFA,False +533,14.0,30.0,24.0,27.0,22.0,23.0,21.0,29.0,CEBEDGCHDGAAABHEHGCGBFBEGDDDCDCHHDEGFHCEFBGBCCFBAEAGABEDFDCDCDHDHGFGHGCGDDFBBBBBDFDADCDGBFEFDBCFCFBDHDGFACAGFDFDEAECFBBHBHCACAHFDEHEHBDBGBHBFBEDCFEEHBHBCBCBHEFEFCHCHEAFHBHBHEHFGCAEGHGHGHGHED,False +534,7.0,14.0,11.0,10.0,12.0,6.0,11.0,7.0,ABADCBEGAGABDBHCECDBEHGCBCBCGCFCFHFHFBBCBGEGHGDGEGEDDDCDEDABAHCFEEAEFEBBGDEHBG,False +535,1.0,8.0,7.0,5.0,5.0,7.0,1.0,7.0,BHBGFHEDDFCBBBBHHHFEFHFCFCACBDBDEHEFECCCD,True +536,5.0,4.0,11.0,11.0,13.0,6.0,6.0,8.0,CDDDEBHHGHDFGCCACEDEDECEGEACACHEBFFEFEFGFGDGDHAEEEABCBHEDCDCHHDC,True +537,28.0,21.0,11.0,18.0,13.0,11.0,21.0,19.0,HGAGAGFDDHGEBDCGAAHGHEDBDFDEGAGHDECCAAAADDGBBCBHBHBHGCGCBBBFBFGABAGCHBGAFHFAACAGDFEFEGGBFHAADADFDADBBBDAEAFHGHEHEHAHAHAHAGEGDCDCHBABABECDGAEBE,False +538,3.0,5.0,4.0,4.0,5.0,2.0,1.0,6.0,HCHGHAFBEBEAEACDCHBEBFCEHBHDDD,False +539,6.0,6.0,7.0,4.0,9.0,4.0,6.0,1.0,CCAGDGDGEFBCACBCGDDBFEFCFEABABCEEEABAEGEGEH,False +540,4.0,1.0,2.0,4.0,0.0,6.0,5.0,0.0,FDDGAGFGCGAGAFFFBCDADF,True +541,9.0,14.0,13.0,6.0,8.0,6.0,10.0,5.0,CBCGEGEFEHAGEDBGEGAGHDCBCGAGAGHDFGAACBBDBDFFCFHFDACACBBEBECCCCHEACBBBBB,False +542,16.0,16.0,8.0,16.0,13.0,11.0,10.0,17.0,EAHAGFDCGCGDEHCHBAAADHDHEHEFBGBABFDAAADBDADADHDGEGCGHGBFAFEBBBBHFDFDEBEFAHEBDGFHCHCHGDFABABDHHHAEBEHEDEBCCF,False +543,21.0,26.0,17.0,27.0,29.0,23.0,26.0,18.0,GDEHHBFFAHDHDCBHBGEDBDGAGDHCEEEBFFACBBEDGFCFBEBECAFDDHBHDEFEFEFEGGCGBHFFCFEHBHEFBHBADAEAGAFBFGEGEGCGDEDEGCGCBDFDFDADABCFEBBBDBGGGFGCDCDCACFEDBGEGEGHABGEGEAAAACCHEBEDEHBABFGFHHEHADGDADADAD,False +544,22.0,22.0,21.0,19.0,23.0,23.0,21.0,20.0,CGDGDBCFDADCCGDBDHAHCHCEDFFGGGECECEAFAHCFDDEDAGCGCBDEDEAEHCHCEEECEFBFHDHGHGEGCHFEAEAEFFCFEDEABHHHGFBAGAGBDEGECECECHBHAHGBBFBGBDFDGAAFAFGBBCBGBFHEHCBDFFFHFBAAHBFBAAAFAGABDB,False +545,23.0,25.0,25.0,15.0,25.0,17.0,21.0,33.0,GAGAGEEHHHFHFHFHEHDCFHABBHBHBEBHFGBCCACACACGHBADHBECECEBABECCHCFEGHDCEBGGEBEBEFHHADCDCDFDHBHCAEEHEHFHGHGHFADCGFHCACACACBCEGDFHCABGDGEGFCDHGHAAAHBHBHBEBHBHAGABEEGEDEGFBFCGEDAGADDBBEAFCF,False +546,3.0,2.0,2.0,4.0,0.0,4.0,0.0,0.0,ADADAFCFDBBFCFD,True +547,13.0,21.0,3.0,11.0,13.0,5.0,12.0,11.0,GHBADHBHBGBEHDHEEFGHDHGFEDDDEGEAEDFAAGBBCBAGAGAEDEHBHBABABAGADBEBECEAEBBBBGBHBDFGCADBFBHG,False +548,25.0,24.0,22.0,17.0,28.0,18.0,39.0,21.0,CDCABDBHBGBGBGBCECBABGBGAHAHBFEEAEBGAGEHFACACDEGEGECHAEGEHFHFABEGHFHAHGHCDCEBEGDBFAFHGEGBGAGDBDBDBEFECHFHEBFGEGEGECAFABEBGBGHGFGEGCCCCHGFACGBHAHAECFGAEDHGHGDDDEAFADGDGDCAEGGACFBFAGEGACCEHDCDGGFG,False +549,3.0,2.0,4.0,4.0,5.0,8.0,5.0,2.0,HFEFGDGFBFDFEEEFEFGBGCCACDCAGAHFD,False +550,1.0,3.0,4.0,3.0,7.0,2.0,2.0,6.0,ECEBHBHGHBECEFDHAHECEDEDGCHF,True +551,16.0,22.0,21.0,26.0,28.0,20.0,19.0,21.0,EGEDEBEAEADDDCFCABGEFFHDBECHBBBBAHAFFCCDDDDDDHGHEFAAAAAGGBGFGBGCCHEHFBFHHDCDFFBFDGEGFCABBEBEBECDGFEECACDDBCFEDEHHDBDFHFHCHCEGGGEGEADCDCEGEFFHHGCCBCBDBEBEAEAEAGDFHCDGDHBHEHEH,False +552,4.0,5.0,6.0,11.0,3.0,11.0,11.0,5.0,GCCDFHFBDDEDECGCGDGHABDDGGGDHAHAFGFGEGFGFABDFHFCFDBDBFFC,True +553,5.0,13.0,12.0,7.0,6.0,1.0,8.0,8.0,BGDACECGDGCCCBCHCGCDBHHGBEAEAEFBCBEBDGCGDGCBABABEDCHHHHHBBDB,True +554,21.0,23.0,19.0,23.0,24.0,21.0,32.0,21.0,FAGAHAHFHGHBEEFGADABCBGBGFAHEDEFGFBHCECEHEHDGDEAAHGGGEGFFDFBCHGAGHCDGGGABDGDADHFEBHBHGGCACBCBCBGBCFADADGDEDACBGHEFDFHFHFBDDDDBHBGGGCDEFEGEGECHCBCBEBEBEFFAGBBFACECECDAEFECGAGEFDGGAADHDH,False +555,11.0,14.0,17.0,9.0,22.0,14.0,9.0,22.0,CGEEDCDADADBDBFFFHCAAEHHHEHEHAHEFFCFBGHHHFHCHDHEBGFGFBEECFCEEECGCGHEEEEADHBHAABCCACFCEDHCHCHBHBDBECGCEFFGFABBEBEGHAHBE,False +556,4.0,3.0,4.0,4.0,4.0,1.0,0.0,1.0,BABHECAAFBDCDEDEDECAC,True +557,11.0,15.0,15.0,16.0,14.0,18.0,14.0,14.0,BCBCBGDGCGEAHHEHGAFFCFHFCGAGACEBEBEBAFGCCDGBCEFDFDAEADDFDCEBFBFBEHDHEHEGEGBGHFHDDDDCCBGBCBHAHDEFFFGGCHBEAAAHFFDFDFDHC,False +558,5.0,2.0,3.0,3.0,1.0,2.0,3.0,2.0,DGDGACBFHFHAEACABACDG,False +559,29.0,26.0,17.0,17.0,20.0,26.0,24.0,23.0,DADCDFFHFAFACAFBDBACAGABFGFBHCHCFFEFEFGHGCBCAEGGGDBDBABFHFAEADDDEDEHAAGGDBHGFFFFCGAHBBGBGECEGEGEGEBEDCFFDFCCEAAFDHAEBFBFAHAGFHCCGBGBGBGAGABEDADHEBEHHAEFHAHABCBCHAEAFAEBHGHBBBAGDHHHHC,False +560,7.0,9.0,14.0,11.0,8.0,12.0,13.0,5.0,FCDCEFEFGHDAABACGCGCGDEBAHHBCCFCFGEGDBDBDBAFECDFDFEGGCAFABCFGFGEGHCDEDGDGFCBCBH,False +561,16.0,32.0,21.0,19.0,21.0,20.0,22.0,22.0,AFBGBGHGEDFAACDCDCEFEBCFCGHGHFDABABAHCCEAHBEDEDBDCCHGHEBEBEBCDEFGDGFBFEDHDHDBBBFFEGBGHEDGDFBGBACDGEBEBHBHCCGHGHGDGDGHGHBCAFHGHGFABAFAHAFCBCBFAHDHBBCBGFEBABCBCFCFEEBCFEDEAHBE,False +562,18.0,21.0,6.0,6.0,14.0,3.0,15.0,20.0,DGAAHCHBAFHBHBGCAEAEAHAEAHHHBCBGGEBDFAHAEAEBGAGAHDEGHAHBEAEGHGHBABHBHEDCGHGBEDGBGEGBGBABDBAEEHFHBCBCBHB,True +563,19.0,18.0,15.0,19.0,14.0,16.0,17.0,24.0,FAFAFABBHDCDCDFDCAABFCEDBBECDCDFFAGADBCHGGFHDHGHEECEGDADABEHHHHCHDHDFAHGFGFBDBCBFHAGABDBGBFDGGFCFCBHBHFHEHEHEGAGAHAGABAGABEECDCHHEBEDEHAGCGHDH,False +564,3.0,3.0,2.0,1.0,0.0,0.0,0.0,2.0,BABCBDAHCHA,True +565,8.0,12.0,12.0,9.0,13.0,13.0,12.0,17.0,BFBFEEHBFAFGGGCHDHDHGCDCGEHAHEEBBAEFGCGCHCFCFDBBBHCEBEHEHFGAGFFHFHABDGDFDFBHAHDHEAABCEGEGEDCHCHC,False +566,24.0,19.0,7.0,22.0,15.0,14.0,18.0,21.0,AEADAHECBGBFHGHDHAGDGHGBGBHFHBDDDHGHDHDADHDHAHDEDADGFEFGFBDBDFAAAAABEFDHHHEGBGAAEDEGEGAFAFHHBEEHCGBEADAEFFBFDFDBDBGBHAGBCBEFDHGCACBCBAAACAGE,False +567,18.0,34.0,25.0,23.0,26.0,29.0,16.0,24.0,CHFDFHBCBDBFBHEEAEABABCGAFDFDADADADBBBCBDBFCEEEFFAFDBDBGHDHBBBFFFDABFHGCABABABAHHHHDFBFEFHBCDCFCFBFEEGECFHEGEGBBDDHDEDHFHDHDFBAECCBHBEBHBCCCBDBEGHGCFCACEFAGEGEGCCFBFEHEHCGFECGFDAGFGHCCCEEEBEHAHDG,False +568,10.0,3.0,8.0,11.0,10.0,4.0,2.0,8.0,EGEDEHEHCDCEAEAEAFFEHCDDDCACHBHBDDDHAAACAEBFAGAHDCCFEDHD,True +569,16.0,11.0,9.0,12.0,15.0,17.0,17.0,12.0,EAEDEACHEAGBHHFFAGGDADADHBHAFFGDEDEHFBFCGBGFFDGHAEAFBCBEAECDADCGCGFGEGEGAGDEDBFFAFAFCBHAEAEGEGFGFDCHCGFBHBHBH,False +570,5.0,3.0,10.0,3.0,5.0,7.0,4.0,6.0,DADCHHGACACECHCFCFHDEGABAFFFFECECFGGHBCBCEH,False +571,19.0,19.0,10.0,25.0,20.0,11.0,12.0,21.0,EGEGEDDDADCBFBFCHCHGAGDHDHDADGHEDDDDHBHBHCADEEEDDHDBCEAABABFEEAEGHGHFEADDDCABHBHBHFHFEEEEFDCEEGCBCHGAEAGABFBHAHEHAFABHBFDDDBDBHAAFBBAGGCD,False +572,9.0,14.0,14.0,11.0,15.0,15.0,19.0,10.0,EFEAEGGGDGDADFHFGFBFBFGDGBBEBEADHGCBCBCGCECGFDCBCBFDFGEDBDHCAFEFEBGCHAFGFGEEHBGCGCEEEBHCHBADCCGGHAHADAGFHFE,False +573,4.0,10.0,13.0,15.0,11.0,8.0,6.0,4.0,AFCCGEEDEBEBAHAHADFBCBCBEFDGHBEGEFFBFDDBCECDCDCECEDDDDDGDCDCEBBGDHFCCGF,True +574,15.0,27.0,18.0,27.0,33.0,20.0,18.0,26.0,FACGCDEDBABABADHDBEFECGDFHHEBCBCGHHAEBHBHGDADGDGDEEEDEBCBDBEAFHFEDGDGDBCHEAADEDEAEDHCHAFDEDHDACHBHBHEHECFBABHDEEEFEGBGDDHGFBFBFCFCEBEBFFCECEGEFEDGDCBGEGHFCECEBGBHBHDHCEFFFBGBHHHEFAAHDG,False +575,16.0,17.0,13.0,14.0,16.0,19.0,22.0,14.0,HBCFCFDFEGAGAHHGEGBGDGFHEHAFBDBDCHCHGFDEDEFHFBEBHBHBEBHBDFDEDEHEGEFFACACGFHADGFADGBAEADAFBCHEFFBEBGBGBACGGFGFAABGGDGFCCACAEAECDGGGC,False +576,21.0,18.0,24.0,12.0,15.0,14.0,8.0,14.0,CDCDFBACHGHECECEDECECHHAHBGFAAHAGFEBCHAGBBBABCBADCFEGABABCGCFAFEBHAHDHECACHHFCBBBEBECFCFAFAHAFCGDFDFDBEBDCACACADBDEHEFEDGCACAC,False +577,11.0,6.0,10.0,4.0,4.0,6.0,15.0,11.0,HHGHAHGDGCEBABABGCHCGCECHCACHDFBABFHFCAHAHFFBFGGGGGGGACAGECDGAADEHG,True +578,13.0,11.0,13.0,13.0,10.0,10.0,11.0,13.0,HDHDFAHCHGEAAAACGBEEHHDEEEDADCDCACACDGDBDBCFEAGHCFCABFBFGCEFBHHHHGBGCGCGEEHAHFBFDDBDBCGDGAFAFB,False +579,16.0,20.0,17.0,10.0,16.0,13.0,17.0,18.0,HBHCDAHECCCCBHGEFCBCGFFAFACBDGDCHBHBCBEBEDGDFEHGHBHECCCEFAGAEHDGDGHBFAFAGAGBGBGBEECCAFAFDBBHFECBGHCHBHDHBHBAEEEAEHEAGAGFGFGDABA,False +580,19.0,23.0,27.0,23.0,24.0,28.0,24.0,26.0,FGFGCHDADGDHFFDCDABFFFFBCEAECEHADCDFDFABAHABDEDBAHCCCHBAAFAEGEGFGHDHGHBHGHDCFCFCADEFEHBAEEFGCDCGGGGGEHFGCGCFFHFHGHBCBDBDCCCGEBEHFBFCFEECFGHGHFHCAEBEBEGHGHFEFDCHCBCBGBDBEAAABCCEAFBHBHDHEEGABDDDED,False +581,14.0,16.0,19.0,20.0,20.0,20.0,13.0,20.0,ACAFBEAHDHEHBHCABBCHFHCEEGCHHFCDCBBEBHFABGDHFHFHBHBHBGDDDCFFHFBFGFECDCEAGAGACCCGCDCDEDEDADADFFFAFAGHCDAGHFEEGHCEEEHECECEGEFDFEEGDDDGDBBFBFBADH,False +582,13.0,15.0,13.0,20.0,21.0,19.0,19.0,16.0,EGGAGAHBFFEFEHECDCFCBGHFFGAGAGEGCGAGBFCFDDDEBEHEHCFBDDDDDDADAFAHHCFDEDBFFFFHAGCBDAFBHBEDGFGCBCBGEGEDCDCDCFHEHGHBDGEHABEGAGHFEDAHEEEEEBHB,False +583,6.0,13.0,10.0,9.0,17.0,8.0,10.0,9.0,FHFGBBBBABCCDHBEDHGFDEHCGCBEBEHCFCFBFBDBACFHGHGEEECECEDEDEHEDGCAEADFDGEAEGGGEBABEH,False +584,18.0,27.0,27.0,16.0,19.0,28.0,14.0,16.0,FHFCFAFHHBEBFBDCHBGEDBAFFCBHBCFGFGCGCEEEDEDBABGEFBGBAFAFHEGCGCDCDBHHCHAHAHGCECAHFHFDEGHBBCACABABFBFBFAFCDCDBABEBECFFGBECCCHCFAFDDDDFDBECEAEDBFCDCEFGFABABCCGEHCABGFEF,False +585,26.0,16.0,22.0,22.0,20.0,21.0,22.0,26.0,FHDHDHFCEBBDBAAAAGFGCBEDHDHGHAEAECDCBEBHCHAHGGFDAEFCFHHHEECCCDCDCDHAHABBECACADAHCDCDFBBEDAAGAFFHCEEEAFAFGFCECEFACAEAFFHEGFHCAGECFFGBGFGDBDBABAGGGGGHHHAHDDDHHHAHDGEGFGBGBFCEDGD,False +586,8.0,5.0,12.0,4.0,4.0,13.0,13.0,7.0,DFDCCCCCCFEBEBDFFAFGCGCBFDFBAAFHGHGCGAAHGFAFGFGCGAGBCHFHCGGHFHEAEG,True +587,4.0,3.0,2.0,3.0,2.0,5.0,3.0,1.0,BGGGDBDHDFCAEAFCFBFEFAA,False +588,7.0,14.0,10.0,16.0,16.0,9.0,9.0,13.0,BCDFHCGFGAEFFFDDBBHBFBHHGAEDDFDEHEGEGEHADFEEHEGEDEDEDEHHBHBDBHBDCDCDBBFBABACACEHECGHEBDGDCCCAG,False +589,41.0,28.0,27.0,20.0,22.0,14.0,25.0,23.0,EDEHHHEACAEAEGECBBHBHBEFAFEBAFHHGHAHACAGBDBEGCDEHAHADACACGEDCCCFBBBBBFAADACAGECDFHGDDBDCDCECDABAFCBEGEDFCGBGDHACABGHECBGGCDCGEFEAGCGDAAABABABDHGEAHBGAEHGBGBFCFCFEFBHGHBAAAAHABABADAGACACGCACHDHDHAFAGEG,False +590,25.0,17.0,16.0,9.0,20.0,24.0,14.0,17.0,HDFDEGEFBBECCBDBABFFAFDFCECBAGAEABGFHCACAFAFAFHEHEHECFCHEHEHECGBDBAFEBCFAFCFAGGCFCABHGABFFEGAHAGAGCHHEHFDFBEBCBEFAFAHAEFEAAHAHBHBGDGDGCEADAGEF,False +591,17.0,13.0,25.0,18.0,20.0,19.0,18.0,19.0,ADCFCHDBAEHEHEFEACAFAFDFEFECEGADHDHEBCCCCEHHGBDBDGCCFBGDDCGABAEAEDEAFAFCGCFHFEGAGDGFHCGCEHEAGCHCBDEDCFEDHCBEBFBAGEGAHCHCBCBAHACDBDCDCHFHEGFGFGDGHGFFH,False +592,4.0,14.0,3.0,5.0,17.0,15.0,9.0,5.0,HGFEEHBHFFEFHFEGBABFBGDFBBEFEDGDEDECEBEFEAEBBBBEBFAHAGFDFEFEBGCGFGBGFECE,True +593,13.0,8.0,10.0,11.0,8.0,10.0,5.0,8.0,EAEADADGFGCDDFBFHHGADABAFHHBAEABHHGBCFCFDFAFDHDCDCBFBCCCBCEEEAEAEFDAHACDG,False +594,16.0,13.0,15.0,7.0,3.0,9.0,20.0,22.0,BGBGCGHHHEHGAAFGCGBDFAFBHCHBDBCCCFDAHHBGBAAABHHHGHGBABABCCCCCDGHGHCHAHGEGDBFGFGCGAHAGFCHGGGAHAHCHFEDHDAAF,True +595,12.0,10.0,9.0,7.0,8.0,10.0,12.0,10.0,AEFDFGFGABHBHBACAHFFEECEFDFGBCAABBCDCGEBEBHHHHFBAEADGDGHGDGDCACGCACAEFHAHGGGBF,False +596,12.0,14.0,7.0,5.0,7.0,8.0,16.0,11.0,DBGBABFCGCGEGBGCHCABEEHGGGHGHFBEBABFBFBGGGGFDFCGABABAFAHHHHBEAAADDHCFEHAHBGACDGE,False +597,12.0,31.0,25.0,23.0,29.0,22.0,19.0,20.0,GBCAEDEGEDHCHGFBEGCCDCGAFBFAFEGBBDBDBDGGCEHEHFHDCDCDEDFHHBGBGCHABGCGCFHFDEBCDHDAABFBGBHDCDCEHEBFBFEFBFHEHEGEBBDBEBABCDGDBHBDFDFDACCEFBCBFHFGCEAEDFCCDCFGGEEEAEAFAFBHBEBCBCHEHCHGEEEBE,False +598,3.0,2.0,2.0,2.0,0.0,4.0,2.0,0.0,DADAGFCFCBGAFBF,True +599,18.0,18.0,17.0,19.0,19.0,25.0,24.0,26.0,EFEFADADEGEGBBHHABBHCCGAFDHDFEHHHHHHGAAADGHFHGGGGDEACHCHCFCGEGEFABEEGEHFCFDFEBGAHCHGFGFGFGFDDHEFCFEBDFEACAFHCHFBADGCGBADGDAFCHCHDDDFDFHCHBHEEEBEBGBABABABCBFFHFDGCGBGD,False +600,18.0,13.0,8.0,18.0,9.0,20.0,11.0,10.0,FAHEFAFAHDGGGGHCBEGABABFEFAAGAGAGAGAGBHBHCFFDHBHDEDEDABCFCEDEBEFADDBFFCFHFAAGDDDDDDFFFFHADFFFBBBCDADCCADHBE,False +601,28.0,16.0,18.0,22.0,25.0,31.0,31.0,28.0,DHDHCHCEGGGGGGHGHGABHGABAGDGEGBACHDHBGADFBHGAGFGDDADGEAEACHBBFFHFEGEFFAFAFGFEFAGADDFAFCFGHBFFEDBACABFHFCCCEEDFDCDAAHFHEHDDEDGHEFCAHFFBCGCGCACABAEAEHDHFHFHFCEDEDGAGAEEEEEFDAGGGHGHFHAGEBHBAEFCFBFCEHBHD,False +602,19.0,22.0,22.0,6.0,18.0,28.0,18.0,32.0,BEHEHCBFBFGAGFFFHEEGEFFGCHCHFABHHCCBFHFABBEBCACAEAFHFABHCHGBBAHEEEEAHAHBHECACAHEHEHCGBFFHFGAGCCBCBEFEGHDDGDHFHCDAHHHHDAFBFAFHFHGHGACCCACBHBGBGBCFGFHFHFGFGFAEBCGCBDEF,False +603,6.0,3.0,3.0,0.0,3.0,1.0,2.0,3.0,AAAAHHHEAEBFCEGAGCBCB,True +604,20.0,12.0,4.0,14.0,4.0,16.0,10.0,13.0,BHADGGGBAFFHAEDBAFGFCFHFHDHBHBGFFHADDEHFFBFGHAHAHABACADFFAAGADAGAGACADDEFEFDADAHBGBABDBDBDCHF,True +605,13.0,12.0,3.0,10.0,9.0,12.0,19.0,5.0,BFBFCDGDBDAGAFCHBBBDHGADCEAABAGFGFGEGEGDGFAFEGBGAGEFFGFGEDADBBGAGAGEFEBBHGHGEDDAFAH,True +606,25.0,22.0,15.0,23.0,20.0,14.0,29.0,17.0,ABABABGDEFEFEHBAAAFDDBDGDGAGEEBHFFCAHAGABACACHEGDGDFDHGGFFHFBEDECFGHCBAGDGCHBGBGCGFDADECEBEAEADAFEBEAEFCBCBCBHBABGBHAHAGAGDDEEEHBCEADGDGDHHFDGABDBDGGCGCADGGHHDHGGEGC,False +607,7.0,12.0,19.0,9.0,3.0,6.0,12.0,7.0,CHGGCADECECGBGCGCEHDAFACDBGGFABCBCBCBCBFBCGCBCBCBFHADACADHDCGGGDFCHGFCHDHDB,True +608,15.0,15.0,12.0,14.0,12.0,4.0,21.0,15.0,BGBEFEGDBCGCGHHEGCFAGEBFGHBCCEGAHACGBDBGBHAHGHGHEHEHACABADADAHACBGDAEHGHBDBDBEBAAAFCGCGDEDCDEDHDAGHGDGBGEGDC,False +609,11.0,19.0,6.0,5.0,9.0,14.0,11.0,10.0,BBBBGBFBFBABDHAHFBBAHEHFCAHGGDGDFCBCFCGAHBDBGBGFGHAHGBEEAFFFBFEFEACACEEGEAEDGFHAHBBBF,False +610,7.0,6.0,1.0,2.0,7.0,8.0,15.0,3.0,GGGGGDGFBAEAEBFHGHDFAGBEFEFGFGBHAGAGBCEAEGBGEGAFF,True +611,9.0,11.0,18.0,12.0,13.0,14.0,18.0,18.0,DABAEGBGEGEGEGFDHCGCHAHFHFCCCCHHGADFBGEHAHEHECFHEHEAGABDGEBCBFFFGDGBGACHHHDHCFCDCHHGDCHCBCDCGCBBDADGGGEDECBFFFFEF,False +612,1.0,6.0,5.0,8.0,3.0,4.0,3.0,4.0,BEBEBGBFBFDDCHBDFCHDGACHFHGDCDCDED,True +613,5.0,7.0,4.0,9.0,3.0,12.0,4.0,8.0,DEEHBFGFCHBHDHFAGDBDHDFCFEBHHHBFBABAGAGDFDCDFFFFCFDA,True +614,5.0,4.0,10.0,9.0,2.0,6.0,6.0,7.0,GCBCBCGGBFHHCFCHHDDDDCBGAEACACFDADCCAFHFHDHDEDGFG,False +615,20.0,20.0,21.0,19.0,32.0,21.0,14.0,26.0,FCCGGEHECEDEDBBECHCHCFGBEHECCCCCHCGCDCDEHAGCECEDDBEBABABEBEAAAAHAHEFAFHFEFBFBFAFGEEEAEHEBGHEHDBCBDAAEFFHCGFHHHGCEAGDBEHEFEGDFBFAHHDBCHFFBEGEGFHECEADADADBHFHAHDDFDFHEAEBDBDGH,False +616,4.0,1.0,4.0,5.0,3.0,3.0,4.0,3.0,AGAHCHBGDFDCHEDEDEFCFCDAGAG,False +617,14.0,17.0,16.0,17.0,18.0,16.0,11.0,15.0,EFEFHFABEBEGEAEBEAECBDHFEEGEGBGDHHHHHBHBHBHAFAHDBFHABDDFDHBGDECECEFEFGDABAFAFABDHFBFCGCGBEFCDCEADDDFACAHDCCGDDCBCGCFCABECGCD,False +618,29.0,30.0,26.0,14.0,18.0,25.0,13.0,17.0,HACCBHBFAFBFBFHFCBAAGAEBEFDDBDAAACACACEEDDAEFGBGFEFCABAGAGAGFGCHCAGFBBDFHAABFCFCFDHEHCFBFBHADBBBBHDDBCFABBEBFBADAEBCBHBHFHCBDDHCHGHCACAGAGDFCFEAEBECECECFCECECGHEBAFAEAGHBCF,False +619,31.0,22.0,24.0,19.0,30.0,25.0,19.0,29.0,CFHEHCGFFACEHBDEEGGACFCACAGAHAEAFDCGBACEFGAECCAGHBHBDBAEAGFBABAGACAHHHAHCHCDCDAGGGAHAEAEDGGCEHFHFHFDGBHBCEHEDEFEFEFEAADACHFBDBDBDBFBFAEHFHBHEHEGEDEDCCEBFBFCFCAHDBFEAEFEACAFADEBEHHDEGEAHBHCHDBGBCDHFGF,False +620,18.0,17.0,15.0,24.0,21.0,15.0,18.0,13.0,ECDGDBDGDGDEAEBEBCFGFGAGAGHCDEHEHBGGGFEAAFBBDFHCDCEEEEGAGAGEDFDHDHAFAFHEHDADADBDECACEDDBHFEGECADDCFHBCBCHCDDFDGBBBEAECEDEFABAHCHGDABFBFGFCBGA,False +621,0.0,2.0,1.0,1.0,4.0,1.0,0.0,1.0,FEEDEBEBHC,True +622,14.0,20.0,14.0,20.0,27.0,29.0,12.0,26.0,CDCACEHFHFHBHEFEDEBBFFFFBFECHHAHEHEDGDEEBFHFHAACEDECCCCEFEHAHBHDHFHFAFABEEEGEGEBDAHEEEEFHDDDGDEDABHBAFGFEHABFBABDBFFFHFCFHFBGCABBGBHFHFDDAHGFEFEDHCHDEBGGGBCDDDCGF,False +623,16.0,25.0,17.0,19.0,21.0,19.0,21.0,15.0,BFDFDFGBGDHBHEDCACFCEHEDEBCFDEDADBDACADDEGEGHAHBHFEBCCCAHEHEBEBAAAAGCFCFGFBEEEHBHEHGBDBDAGAEAGBDBGFEFGBCBCFGEGBGHDHGCCAADCDCBFBAGGFGEHDFBEBFBFDFCFHBGGGEB,False +624,23.0,27.0,21.0,27.0,12.0,19.0,33.0,26.0,DHAGAGFBFCCHHGGBCBFDFACGBGBGHCABACAHFHCDCDGFGFCFGFCAEGHGABABEDEDHFHFDFBGHGEGHAHBHCDAGAGAGBBAEAFGCACBFBDDHGHBHDGDGBGDAAAAEBBGBDBDCACFCHCBDBCCCBGFFHDHDHEGEDEHHDDDHBGBHDFFEBDDEEGGGGAGHCHDBAGD,False +625,17.0,22.0,27.0,7.0,24.0,19.0,26.0,18.0,GHECEGFGAGCBEEGBGHGBEBEAEFGFAFCFHGGGGEEECBFBDGGCGCEDGFBHBCBCBCAGABEGEAEABFFFBFBFHEGFGACAEFDBCBCAGAGAGFFCCBEHCCBCBDHCBEHCHCACEBFBCGDAHFCECEDACAEHHHHHDAFGHCHCEGEH,False +626,21.0,20.0,18.0,14.0,19.0,24.0,20.0,19.0,FGFGDBFGAAHHDABADDECCHFBGCEEHGHGHGAFHCHAHBCBFAFAFABBBABADDGEBBFCFCFCFCBCDCDHFAGGHGHGAGEHBFAFCHHEGEFBHDHAHAEDGAGAGEGCDEHECCCBBBAFFFEFDADBBEDEGCFBFCGAEEEEFEF,False +627,22.0,20.0,15.0,21.0,16.0,16.0,15.0,16.0,GBGEFDACFGFGHBHECCFAAAEEGBCHCBCFADHDHDBDBDFDADABAEDFBADACBCFCFEHGCEFEAEBHDHDFDEEBBHBGAGDGAEAEGGHAHDDDDFDGBBBAAAABDHGHFAFECCCECHBDBCBFEFGAGAHH,False +628,7.0,15.0,8.0,13.0,14.0,12.0,11.0,8.0,DEDBDHFHDCDCBBBCBDBFBFCGHGAGEFAFAEADBFBGBGHGDCFADBDFEFEDECEFHHCBEAGGGDEBECEABBGHGFDHEEFE,False +629,1.0,3.0,3.0,8.0,6.0,2.0,4.0,5.0,HEHDHDHDEFBGBGDDCDHBEDECGCEEFGAD,True +630,11.0,10.0,7.0,6.0,8.0,14.0,8.0,5.0,CAHAHABFCFCACFCAHAGDBCEGHFHEBDFAGAGABBBEBCFEFEFBFAFBDEDEGGDFDABFFEFGG,False +631,14.0,11.0,20.0,21.0,13.0,15.0,14.0,16.0,HCFAAHBFCFAFHFGDHFCFBBBEBEAEAEHEHGDDBHHHFHDCDEGECFHFDFDADACADHGEDADHDHDCDCGADDECEAGBBCECDGGCGCABAHFGCDCGFBHBDCDGAGCCCDCGEFEF,False +632,4.0,8.0,5.0,12.0,1.0,8.0,6.0,3.0,CAHAEDBCCFGDBDFFBFBHDDDDDADCGBGBCFAGDGFGFHDBDBF,True +633,3.0,4.0,7.0,2.0,2.0,6.0,5.0,5.0,CBCECACAFEFDAHBCGFGFBHCHDHCHGGFBFG,True +634,15.0,14.0,8.0,23.0,21.0,16.0,17.0,8.0,GDDDADADACBFGFGFAFACADAEEBEBFCGBFHFHGEDDDFCGABCBDHDHEEFHAHGEFDFEFBFAGAFEGDGDGBGDEDEBHBDCEEEEGEBCDDEAECDDDEGGGAFAEBFBGHEDAB,False +635,16.0,23.0,27.0,12.0,33.0,22.0,20.0,34.0,HEHACECAHFBGBEBHHHHFFCECEHEAEGDGDHAHBFFFFFFFGABCEFEBECECHABGCGFHEEEEEEGBCAHEHCHDFBGBCBCBHHGFBHDHCHEHEHCFCGCGEFHHHCDGDEDECBCAFEFAGHDCABHDAEACCHGHFBBHDEAGBGAFDDGCACEFEFEHEHEBEGCCEGBGBCAHBHB,False +636,18.0,21.0,19.0,22.0,14.0,15.0,21.0,26.0,GHABCDDDAGGFFEFDFHBACHDHDECGBFBFAAGECECDAFBHCDCEBGBAAAGHHEHEHEHEBAFDFCACECECEHHHCHDHAHAHCDBDGGGDHDBCCFCGHHHGDDDBEBFCFDGAFBFBDBDBGBGBABHHCHGHGDBEGAAHDCGAGBGF,False +637,7.0,11.0,15.0,9.0,7.0,9.0,10.0,13.0,DAFBFHGDGAGCDCDGHBCECFCGCDEDHDHBHBFBEGEHDADBBBBGFHHAECHGHGHBFCFAACCCFFHGACHCBCECE,False +638,23.0,18.0,27.0,21.0,18.0,14.0,17.0,30.0,DEDCHCBFEAEAEABAHGDGDADEBEHCFDGGCCCCDCBFGFCCHDHDHFBABDHEHAHFHCAFAEADHDHCHEDACCGCGCGCBAFHHHECDDDBGHHHCHBHAHECFBBGBDBFHAHGHCDGHGCGCBBBGBABFGCGAEEDFDAEHFHDHEEACAEFEACHCAAA,False +639,8.0,5.0,5.0,6.0,7.0,4.0,6.0,5.0,FGEBDBDBGHGDGCAHAHCDAGAFAFBEBEGEFDCHAEECEDACAH,False +640,25.0,30.0,19.0,18.0,18.0,25.0,21.0,28.0,DBGBFBFHFHCAFAFACGCHCHEHEGFGADHHFEAEGEGHGEAEBDADHBABDGGGGHBHDDGAEBDFCGCFFGACDHBHFHCHFAGHEDACAHBDDDAHHEBEBABACAGBDEDGHBHFHFCGCDFBFBFAHGCBDDCBAEAEFCABABACACEFHFBAEHEGBGBHBFFHBEBFBFBFHCBC,False +641,10.0,7.0,19.0,15.0,18.0,26.0,16.0,17.0,EBEBEADCFGFGAADCEFHCAEDEAEFBHEHDGDGDBHCGCFHFHCHFEFGFGCECFCGCEDAFEGDFCAEADCFEFHHHFDFGFGAGDGDFHHGACFBHDHCGFGFCHCHCHCDEECFFFFEBEBFD,False +642,17.0,19.0,31.0,20.0,20.0,27.0,31.0,22.0,EFGFHEBFAHAHFHGCFCFGFHFBFDHDAGAGBECCHCBGBFEABDEGEGFCBDDFEFADADBFEGEBBAEHEHAHAFGCGCGCBCBFGFCACHCECGCBCAGFHDBDCAFGCGCGCGCDDDCDGDGFBHGFFAHCFCFHECDGDBECCCDCEGEFBFEHHGAGCGDHAHGHEFDHAGBGBGHDECE,False +643,10.0,16.0,8.0,13.0,16.0,18.0,19.0,19.0,DBDFCEGABABHBFGAHEGFFDHCFCFBDHHACAFECHHHHGFGBEHEGEGEGFGBBDBFEFHFCEDECFAAGFGFEBAGHEHEHEGDBDFDFBEBDBDFDBGEHCAAGHGHGBGHGHD,False +644,23.0,23.0,24.0,17.0,10.0,17.0,18.0,14.0,BGGGGGEGBACCECHCHCACDBAEFEFHAHACFGGADDCDCDCDGHGCBHBAAFGFGFABBBBFBHGFAAADADCDEACDEACBHEEFCCHCHAFBCHGEGBFDFHEBBHBDBCHDBDBGFCFBDCGFGFACABBBAAAAAFDCDC,False +645,19.0,20.0,19.0,12.0,21.0,19.0,19.0,26.0,BCHEHEABABAHAHDHBEDEAEGECEBECAHDGCFEFCHHAHDHDHFBDACABGCEBHBCFHGCCCAEEDAACABBHGHGHFHBEBHDECEBDBCBFEFHHHGHGHGHFHFBDGEGACEFDFHFEFCGGGAEFDFGCGABFFCFCGBGAGFBAEA,False +646,24.0,19.0,25.0,16.0,26.0,22.0,27.0,28.0,DADGFHCDDBDHDHGGAEECHHHFCAGACFCFEDCCECEGFBFBCBGEHEACBCBGGHGAGFHCGCGEFEDAHAHFHEBBBHHAAEAECBGAAFBGBHBHAAFEEAECEGHGFCDCHHHHBDFGFGFGBEAFHFDAHAHCBCEHGHGFCDGDGCGEFABDBFBAAAHADEDEGCGHECEFEFECECG,False +647,19.0,19.0,11.0,23.0,12.0,13.0,15.0,22.0,FGFAADEGEAEADGDFHAHBHDGGGHDFBHBDDGDCDHBHBHEHECEDBDBEBHHDHEABCCGFAHGGEADAGFDAHEHDHDCDGDHHEHFFFGEGBDCACACDFDHBBBBDCGAAFAHABABACACFDFBBHB,False +648,14.0,18.0,21.0,17.0,4.0,13.0,14.0,14.0,HDCCBGAGBGFGFHCCACHCGCBCBEDEBCBDBHFCFCFGAGACBGFDFBHBADAGHCHBHFCACDFDBABAEGCHHDBDCFBECGCGBDAFFGHDBDBDADADACFDADCHHGH,False +649,18.0,10.0,20.0,21.0,15.0,23.0,20.0,19.0,CDCFFDAABAFGFDBHFHGADADAHGHGBDFCHHHCDCHAHADCDGDGDGCEFGFCECFCFCGCAAAAEAEDBDBFFHHHFECECGGEGAABHECFHDEDGHGAEADFFHGDGDGEEBDCFGEHFCGCECEDDFFFFBFBCBHHAG,False +650,2.0,8.0,12.0,4.0,7.0,2.0,3.0,2.0,BECADGCCCCCBCBCBDGGFECECDBDBHECEFABHBCEE,True +651,23.0,17.0,14.0,13.0,18.0,7.0,9.0,12.0,HGFCACACFCDEEAGBGBADADABCGDAEADGDBACFHBEDAABHBHGHCAAEBECECACEDECEGFGAAHABAEAHDHABABADEBCFCFBEEEHEBFBAEHEHDCDBGBHD,False +652,9.0,5.0,7.0,3.0,3.0,4.0,7.0,7.0,FHAHAGGGGHGCGCEHEAFAFCHDECHBABCFGBHBACDCDAABA,False +653,17.0,14.0,10.0,12.0,16.0,15.0,12.0,13.0,FFDCCCGHBHEFBAEAHDFFFHBBBBGAFABABAEADAEFCBDEEHFDACHCHDAFCFEDGBCBCBEBEGGGCHHDDAGAEAEDEDEBEHDHAHEFGFGFGHGAAEAFG,False +654,18.0,23.0,28.0,27.0,18.0,13.0,30.0,25.0,CGCBCACGBGHACACADFEBGBCAEHBDBCHAEDGDFDCCAEHDGDFDFAFBGBGEDCFBFBFDAHGCCCBGBHEHAHGGGCECEHEAGCGDGDHBBDGCECHAHDFDGEGAGDGEADHCACBGBCHAHAGBGHHCHCHGEBEAEDECHBGBGDGFGEGHCHBDDDCDHDFDHCFEHDBDBF,False +655,15.0,11.0,8.0,7.0,7.0,6.0,7.0,13.0,EFAFACBEEDCAHAHGEAEFFHBHBFBFHGAAHGHGAGDCBHHHABDBEBAGAGDDDADHBCBEACHCACACHB,False +656,23.0,17.0,14.0,15.0,23.0,23.0,21.0,14.0,DBBBEEGCGFABAGAHAHFDEEHECBHBFBEAEADGDACGFGFCFDFGFGFGBEBEDEHHCFEHAHAFAHEBABEDEFGFGBGAAECFCHCEAGDGDCBCAFHFDFDFCFEEEEECFDBGGGAAADBGBHDAGEEBHDAAAHFGCGFAFC,False +657,22.0,13.0,20.0,11.0,19.0,20.0,13.0,19.0,AAAEEECFGGCCCDBDAFHFAFCCBAAHBBBEBFBAGCGEGHCAEACDCEADBDEAFCDGECEGGAGABAHAEBHHHHHCFCFEHCHFHGHCHCFAFDFDFDHBEGEFFFFAEAECEDEDHFGABFEGCHCHAHABF,False +658,13.0,8.0,9.0,8.0,6.0,14.0,16.0,11.0,DFDAACADGHGFECCGBFFFHEAAFACAGFHCGCFAFDFBBHHFGAGABABAGEFEFGDEBFBDBGACHCHCHGDGHGHGEGDGH,False +659,24.0,22.0,11.0,20.0,12.0,19.0,20.0,10.0,ECECBBAAAFHDHDHCBGFGFACABAGGHADBEAFFDFDFDEGCGCBBBFAGABBEDGGAGFDAGHGDDAEABBGBHDGEBFBHDFGCBCBEBFDFDADADBBFEHEFEFDFHFEGDCDCDCGBGAAAAAGAFAHBGA,False +660,9.0,8.0,11.0,8.0,16.0,14.0,26.0,11.0,FEGEHCHBGBGEGHGHGEGHDEBHAFACGDGFGACHHGAFCGGFEHDFDEEGBGBGFGFGCCECFAFDFDHBGDAAHAGEGDGEGFGAGEBCCCCBEEGEFEF,False +661,21.0,16.0,26.0,12.0,16.0,24.0,13.0,16.0,AHBFGAHHBCBABABCCGBEFACECGHGFDAHHCCECFFFDFAHACACBCBGBDFEFEHEDACAEDEDEGEGDGBBBGCGAHACACEFAFDFAFBDACAFFHFCFCAGEGBFDFBFEGCFCBCFHACADDCHFHFCECEHHHCE,False +662,19.0,21.0,19.0,34.0,20.0,23.0,22.0,19.0,AFAFBGBGBABGDDADCFCECGGEAEACHDHDEFCFDFDECHHGDEDEGGFEBBBBBEFEDDFAHCBEDDBACDCDAHAHGHDCFCFDFEFEDHCHDDADBGCABDHEBBFBDCDHDEDEABDHEBFBCEAGGHFHEAGFGFGCGDGFGDGAGAGABFBFDDHDCDHHGHECDCFAF,False +663,30.0,32.0,21.0,26.0,25.0,15.0,23.0,18.0,GBDHGHGHGBGFGABAEEDBCBCAHAEEDFDADEGCCCGHDBBBEDHGGFCBBHEAACDBGAGBGFEAAAAAABADGGBGCDCFCFDFCBHAHBBBHBHGDBDEHBHBHBEAABABDDEAEDFDEBEBECEGEFAFCFCADEGCGBABABFBCEADAEGEGDCDGBFHAEAEFCDDHEHAHFDCDEDCAC,False +664,14.0,12.0,16.0,18.0,20.0,25.0,19.0,23.0,GFFDFGFDEAHBCEEHCFEEEABFGFGHGAGAGCGCFDBDBDEDEABABDBHFCFHDGAGEHEHEGDCDCFAAGAEEHFGFEDCHFHGGEHDDGBADDGHFHEHEHECFCFCDCAEFFFGFGCBHHCCFCFBFHFHEDADHHHHABB,False +665,1.0,1.0,5.0,0.0,2.0,0.0,2.0,0.0,CCCBGGAECEC,True +666,13.0,18.0,8.0,9.0,12.0,13.0,18.0,15.0,FADABCFAFAFGFGFBCBGGGFGDCDCABDHDAEHEDGDGEFFHCGEHHFHBGAGAHEGEGABFCGBGEEBEHFHBHBHBHBFBHCABBHGEEDCDBABABHGGAE,False +667,12.0,9.0,6.0,10.0,3.0,13.0,8.0,9.0,CBCHGHFADHGAGBCFDFAADDFCFHDAAAAAFCFEAAFADCDGDGHFHFHGBFBFBEBHGHGBBDFDEB,False +668,25.0,23.0,24.0,17.0,11.0,21.0,16.0,12.0,GDAFFFFHBBGCACGCECBHAEDBBFFFBCBCACACGBABEBEDDBFAHBHDAGAGBGBGAGBGAGEDBAFCCDCGAGHCDADACAEDFHACBEAACFDDBDBHBDBDFFFCFCFCFCAAAEDHFAFHCHCACHCGAGFFCEEBEBGDH,False +669,3.0,6.0,1.0,5.0,4.0,4.0,3.0,1.0,EABGBEBGBFBGDFDFDADEDBFHEAC,True +670,5.0,9.0,11.0,15.0,8.0,21.0,12.0,11.0,DFDCHCFFDHHAHACGGFBDBDCDCDAHEFFFHBDBDBEECFGDGHGBFCDADABHBHGGEGCCFFFFFDFHEBGCEFDFGFEFEHDGFGFC,False +671,9.0,14.0,11.0,13.0,12.0,14.0,11.0,23.0,HDHCHCFCFCHCFCDADADEHFHBAEGFGHCEDHFCCDEHAHFEBBBADCHHHHDHBHEDDDADHDBGBGBCBFHEBEFGBGHGFFHAHGHBAFAGBEFEBEHEGFG,False +672,3.0,4.0,0.0,0.0,2.0,6.0,4.0,2.0,HFHFAAGEGFGFABBFGFBEB,True +673,17.0,21.0,20.0,5.0,12.0,13.0,17.0,15.0,BCBDBECHCAAADCGGGGFBABABEBCBCACAGHBHDHBFEEEEAABCBCBAAHBGGCGBGHGFGAGFFCHGHGHBABFBFHCHADDFCCCECECHHEAFBFBCHHBCEGGCFAEAEGFF,False +674,14.0,34.0,17.0,24.0,19.0,23.0,30.0,24.0,BBGEGHHHEHEFABDCHCFBDAGBBBBDBFCFCFAHHEHAFGHGEGEDBDBDHCFCHCEDEDEDGCGCDDDGDGAGAGEGBHHCHADFDBBBCDDACGHGEGEHBGBGHFEFGFBBDBHBFBDGGCGCDFGCBBBDADGHFCFADGEHFCFAFGBHFHBGEAEBBBAFGGDGFEFBBHEHEBABF,False +675,22.0,22.0,20.0,24.0,22.0,17.0,36.0,34.0,CHGHGHAHAHCECDBGCADHEEGECDGBFCCHCHFGFGBBHFHFHEGFGAGCGCGDGDCBFBFEFEHEDECCHBGBDADHFHEBDBGFGBAHGHGEACGGAEAHGBDCDGDHFHBHCECBDHGGGGHBBDFDFHAAAAAHADADHGHEHAGFGDGAEDGDEEBHACFGHBHBHCGGGCAHEEAEHEFDDDGDBBBAE,False +676,5.0,3.0,7.0,7.0,6.0,1.0,5.0,6.0,EHCHEBAGEGDGDCCCCABHEGBAEDEDCDFDADAHHCHG,False +677,14.0,12.0,18.0,20.0,14.0,12.0,11.0,15.0,CCADHGFACAHGHDDDDDGFGHBADGBEBCCDDDADADABBHCFCFHBHGAGEEEEEEEGEFHCDFAFCCADBDCDCDCBBBBCHCBDAGAEHDHAHAEEHEHFFCGCDFGECFFH,False +678,20.0,18.0,16.0,16.0,18.0,22.0,18.0,25.0,DFFHFHFGFBADAGHCBCAGBCBFGFACBEFEGABBBEGHHFHFDFHEEGEBECFCEBEGGADEDEAEACHCHABEHAHAFAHAHAFBFAECECHCHGHAHBHCHFHGDCHGHEBDBDGCADEDGGFBFGDBDCFFEHDFDFDGDHCHBGAAA,False +679,13.0,13.0,11.0,11.0,12.0,13.0,13.0,10.0,DADAHACGEBDGEGEDEAACHFGEGEGFGFCFAFEBCBFEFHCCFCHCHEHAFFDBBBHGCEBGBGAAHFHGHBFDEGAGBBBBDDADADEDACFC,False +680,21.0,9.0,11.0,23.0,10.0,11.0,13.0,22.0,BHEFDAEAEGGAGBCHCBAAHAFDFGGGGBHADEDACFCFAEABHBHBAAADFFACDDDHDHCBCFHDHCHGDAHAHDDDCDADEHFFAFDEHHDHECDADAGAGBHHGHEHEHCDGDGD,False +681,29.0,26.0,19.0,24.0,29.0,20.0,27.0,23.0,AAHAECBCBAADACAFFGCEADCBGHGFEFEAEDEDBDHDEBHDHAACAHAEBCBDFFHFBFBFBFGFBEAHBCAEAGAGBEEEEEEEEDCABFGFBDHFAFAGBGHGCGEGDADHDFGBCBHBHACEBDADEDEDGGGGGGGBHBHDHCFGBBEHCCAHHFABDCGGECFBAHGDGDCEAEHECEGHDFDEDGAHA,False +682,12.0,18.0,15.0,23.0,25.0,24.0,20.0,8.0,DADHGFBFDADAEECECBFDHDBCBABAHFFFFEFEFBFBFBEDFDEAFCCHEBBGECCCCFAGBBDBGCEEDHGGEGEAEAEFDDDGDAFEGCGCGCFEDDGDFHEDGGGGGEBEDFDEDHBEBDCCEFFFEFEBABFGAGHGD,False +683,10.0,19.0,7.0,19.0,5.0,6.0,8.0,11.0,CHCGBDFEGADBBBBBEGHAFAHBGFACAGAHDBDBDADHDGDBDCCCEDDHDADADCDBBBHBFBDBDFDADEHHHBHGGEFBB,True +684,10.0,3.0,3.0,5.0,2.0,4.0,6.0,12.0,DBCHHBHEDEGAGAHFGGHFAAAGAGADBCHAHAFDFDACHHHHH,True +685,10.0,19.0,16.0,24.0,9.0,16.0,18.0,17.0,DGDFEBDHDADCDBDHFHFHAGCHCHAGEEBGBGBAFDHCBADCDHAHEEABDDFDFABBCDDADCDFDFBBGBGHECCGCGDECGDBFGGEGECHCGFFBFBDGFHBHBHBCGCGCGBDDDFHFHFHA,False +686,11.0,7.0,14.0,17.0,14.0,20.0,12.0,14.0,HDHABCEFFBEHCGCACACBHBGEGEFFFBGCECDCDEHEDEGFGFDDDDGDGAHDHDADADFFFAHAEDHFBADEDBCCGHAEEECFFEFCFHFGCGAHDFGFHFCFH,False +687,19.0,24.0,19.0,21.0,13.0,20.0,17.0,22.0,GBGCDCDHFCAHAHBFFDCAGBFBABCFFBFACBGHGHBFFGHDDADHFHFHBGGHGAFDFCGAGEDEGEADDFCBABFBABAHEDEGFGFCBCFDDADACECEBEBCHCACFEGCHBBBDDDGHHDHAHAFABDHEHEHEGEDBABCBDBHCHC,False +688,11.0,6.0,12.0,7.0,7.0,10.0,7.0,5.0,CCBGGGGFABECFADHEACFCFGFGEDFCFAFBHBCBHBDCCHCAAAAAEDDDDAFCFCEGEAEH,False +689,1.0,5.0,2.0,2.0,0.0,1.0,2.0,2.0,DHDGFGCBBBBBCHA,True +690,15.0,19.0,20.0,21.0,26.0,23.0,15.0,18.0,GBGBGEFEGECEDHDHDHDHDCGAEACGCFBFECCACGCDEDFDHDFBBBEBDHGHDCBAAAFBHADFBFHFHFHFEDDADEDEFCBBAEEGEACCHCEGACEDECECFFFFHAHEGEBABEDFBHEDEAEADFDCHFHFCGEBHCFFFGBBECGBG,False +691,16.0,20.0,16.0,13.0,21.0,17.0,19.0,17.0,EEBEDECEAEBBBBEHFBFBFDCDCBCBCAFGHGCECGGDHAHCDCFCEHDHDBBFHFGEECBGBFHDHGHEBEBEAEFBAAAAEAGGGFEFCFBABDFGFDFHAEEGHHHGDFHFGCGCGDAAACADEGBBCAHGEGH,False +692,15.0,18.0,25.0,15.0,20.0,16.0,23.0,15.0,DCAGACABGEGHGBBCAEGHHDAAAFGCBCBCGGDGCGCHCDCDAFCFGHGCGCEEEHBGGECACADEDFDFGFDBBFBCDCFCDCEEHEHFDBDBGEGFFBFBFEECHGHBAGABABEHEHGCEHBFDCCGDHEHEGBFAFAECEC,False +693,18.0,15.0,17.0,18.0,19.0,18.0,17.0,13.0,DAEAFACADHDHCFCBBBDFDEGEGEFDGBEFEBGHGHEHGGAFAFAGAEDEBHDADAEAEDEAHGHAHCECEHFHBGFAEAFBCGFDFGCACADFCGCBCBDAHFBCDEBCFCFGECDBDBGBGECECFDDHFG,False +694,7.0,11.0,9.0,10.0,9.0,4.0,5.0,10.0,CDDDBBCGFGDHDHEHBHEHEBEBEAEAFHDEGEDHBAAFHCBFEGCBCBCBAAHACCCGBHDDD,False +695,9.0,7.0,7.0,14.0,15.0,8.0,16.0,16.0,DFDCDCDEAHDDDBHHFHFCDCHCFBAEEDGAEAGGFGHAEECHGHGHEEGDGFEFEDEGBGEDDBHBHGEGFAHAEAHAHGBGHGHGDECB,False +696,24.0,23.0,24.0,22.0,20.0,19.0,26.0,26.0,ADGDAEBHCGCHCEADABGBGBFEEGFAFAFBFGDGDHHACDCHFACHCGGHGHDHCBGDHBACHBHGHGAAEBFAHGGDGHGFGDCDCGCDCAEGGGEEEEEHDFDAAAHADAFADEBBBHEHECACBEEEBABFCFCFCECFCHBHBAGABHHFHBHFCDEBCDGDFDFDCBFBCBEAGDGH,False +697,19.0,24.0,22.0,23.0,29.0,24.0,25.0,34.0,FCFEAEAHCGEDABFEFDHCHCGCGCFHABDGEGFGFGBHBCAEEHGBCBCBCGHDHFHABGHDHCCCAADDFDHDCDHFBEHEHEGFBBHHHADEEEBEBFACHHHHGHGABBBBEDCBBBEDEDFFFFFFHCHDAEFEGDGHFBDGEHHGFBDADECEDEDGFBFEGCGHHCHCHGHEFEAAGAGEGDGCAHAEAEBD,False +698,13.0,19.0,14.0,18.0,18.0,16.0,11.0,16.0,BDBFFDFDFGGHAHBHBHBHFGAGAHDHBEBDBHBFBFHCBEGEGEDCCCCBGHECDCACDBFCEDBDFDFDHDFEFHFHEHEFEBABDEHBCDDHAAADEBAGAEACGEAEFBCEGEDFCCAGE,False +699,20.0,17.0,18.0,13.0,20.0,22.0,16.0,23.0,ADHHHHFDFBFAGADBEFFFEFEGCFBDHCAEABAEAEBHFECCFDFHHHHHFHCHCHEHEAEBGHACABFCFGAGDFDFCBHGCFCBCHDEDHGHAFDFAGECECEFAGCDEGEHEAABCBGBGBGBABGEAHGEAFHFGCECADBDB,False +700,7.0,10.0,13.0,7.0,8.0,14.0,8.0,3.0,FAAEFBFCFBFBEDGHCCCCCEDEDFHECDBDGFGFADGBEFCFCGAAAHEDECACFBFBGGGFCFCBBB,False +701,16.0,27.0,21.0,29.0,23.0,22.0,14.0,18.0,ABAEADACBDBFAFDCGBDEDBBFBFADHHAABHDGABACDBDEAFCHCECHDDACAFDFDFEAEDHDFBFBFCEEBECDCDHABFBGEGFHFHGBDEDEDEDCDHDHFAGDGHGHGHBCBCBFHCEBEHCCDCBFBFBECFDGGGFCECEDHBGBCFEEDGBFBEHEDE,False +702,22.0,31.0,14.0,20.0,15.0,20.0,18.0,12.0,GHADBDAFCHAEBDBDBDFDEAAABADEDCAABBEGEGFGEGFDFBFBAEGBBCBCBEGDCDAHCHBADADGFBFBHBGBDCFGDGHCDCFCBEAGFGFHFEBECAFBFBHBHBFBEGEGEBEDAHABADABBGBCAAGDFBAGHCCFDFHF,False +703,21.0,26.0,13.0,16.0,14.0,14.0,14.0,17.0,CHABCBFGFAABAGAHAHAHACBDFHAHEHGCACDBEHDGBHCECEHFAACABHBABABECGBGAGEFCGDEFHBBFAFHFHAHEBEFEGBGBEBEDDDDDDDAHHCBCDDGEADABGBDBFGFBFBFBGEDCBB,False +704,1.0,0.0,1.0,1.0,3.0,1.0,3.0,0.0,DEECEGFGAG,True +705,7.0,6.0,9.0,6.0,4.0,3.0,8.0,5.0,AGABCBCEHFACGFHHCHEACADDDDGBGBGBCEFHBDEDACGCGCGA,False +706,6.0,5.0,9.0,7.0,4.0,10.0,8.0,4.0,BGHGEDCHCHCGCFFGDGDGCBCBAADFFAFEFGAGADFHBAFCBCEDEFCFD,False +707,10.0,10.0,4.0,9.0,12.0,8.0,9.0,7.0,EECFAEAHAHAEAEBEHFDFDAGCDHBHGGEGEGFDFDEBADDCHFDDBFGEGBGBEBEAHAGBFBABC,False +708,11.0,14.0,22.0,17.0,26.0,26.0,22.0,25.0,ADBFFHCHCHCDGFCFBHBHBAGACHDFEFHCBGECDDGEHEHDHEGEGEGECBHAECDHDCDEEFHFDFDABHGDEHEGDHDGFCCCHCHDHDHBAEEGEHEHGGGBBFEFEDEFHFCFAEHECGCAFFFCFBBCAFBCHEEGEGFFECGCGFGFGFAFAGB,False +709,20.0,25.0,16.0,17.0,13.0,14.0,18.0,22.0,CDEHBHBHAHBHBGDGEGBACAHAHGBGBGBAAAGFDEEBGBABABFGACACHGHDFDADHEFDHHECFDACABGHFHDDDAEAEDGDCDCFCBCFHBCBEBEBEBFCGCHFEGGDDBBBCEHGDACABGHGAFHHHBFAFCFHB,False +710,30.0,23.0,16.0,22.0,21.0,35.0,15.0,23.0,FAFAFAFEFEHAHAEBEFDFDBDHFCEAHHHHBEFDADHEHBCCCADEHFHFHFCGGDECGCBDBGAFAFBCDAHADBECEFHCBCBAAAFAGBFADDFDFHBGAAEABFDEDFHAGAHAGAGEGHFEFCABAFCBEBEBHFDDDFDADEEEFBFDACEGFBDBHBHBFGFBFCFGGHAHAFGFC,False +711,6.0,6.0,12.0,7.0,12.0,9.0,12.0,10.0,HGEDHDGCGCGBHBHGCFAGABCBGGEBCHCHFGDEEEHEHAHFHCGDFEFAFAFDECECDCFABCGEGFCEDE,False +712,23.0,31.0,32.0,27.0,25.0,14.0,31.0,14.0,CGABCFCEHDFDHEHBDBDECCFBDGHGAGBGCHCBAEHEHDFDBDCEFGCGCFBAGGGEFEABFBGEAAAAHAGACACECACBGDGDBHBCFGHGBCAAAFBDDDDDDFGFCECBBEEGDADCBEAEAFDGEGCCBCBCBDGCECGCGCGCECECBFBDBABDBDHDCEHEBECGAABDBGGGDEEGEBBAHGGDH,False +713,4.0,5.0,5.0,9.0,4.0,5.0,6.0,6.0,BEFEACAHDHDHGHBDCHCDEDFDGDBEFGDGDFAFBBGACHCG,False +714,18.0,19.0,22.0,14.0,25.0,27.0,18.0,19.0,GEHFCECFCAEFBFAHBCCEBFFEFECDADEDEAEFEBECECGHGAAADAGHBFGFAFHDEABBDGDEHEFEFDBCHEGCCEFBFEHHHHGHGCAFAFHFHFGEHEHCGDFEAEAGFFBADAFFCFABGBABFBCBGBGCDCDHFHCECECDHDBGBCBCGG,False +715,17.0,8.0,11.0,12.0,13.0,12.0,12.0,14.0,BAGDHBHDHABAEGHFDADFECDCGCGADHDHDHABCBHGAAFBFBEHEAFCFAGHEBCDFDFDCHCHCADAEHEGEAEGCGCFEHAGGFAFEFEAEAG,False +716,16.0,17.0,24.0,24.0,21.0,17.0,16.0,24.0,FCBCBHBCBCECDCDAFFHHHCHDBEFABAEDEDEDECFDGGGAEFEFEHCADAFACEEECFCGAEDEDGHGDGAGFBHDHFHCCGEGBDHGEBHHHEHACAEGFDFDHCECBADECHHHBBBFBFBDADCCFCDCBCDEDHHCGDDAAAHBHGHGDGF,False +717,30.0,23.0,30.0,24.0,12.0,21.0,21.0,16.0,ECEDACAHEHCACECDCGCBHAGDFACBCBAFGFGBACCCCACFGEGFHHAHABGBEFFBFDFCGABCDCBBBBBAADADGDFDFHFDCDCHFBFAAGAGAGAGFCCCHABGDGDBDCDEBHDCDCDBGFFHHGBEAAHAHDFDEDAHAGDCDBHAFGGGBABDFCACACBCFEEAE,False +718,8.0,9.0,11.0,13.0,10.0,18.0,7.0,15.0,BHBGDHDHDEAEFFAGAGABHFFFADHDHDGAFCDCAHBDECFAHDHCCBGHFCECEHEFDBDCDGEGDBHBECFCFCFHBEFFFFFHFHE,False +719,12.0,23.0,32.0,23.0,25.0,25.0,24.0,32.0,ACHDECHBHFHGHGHDADAGHCCEBEBCCGHFFGFCBEGCCDDDBGFDHDHDHGFGBCFCGCDCDCDCFGEDBDBEGGCFEFEHEBEHECBFDCDGBGEGBGEGCFEEECGFGADCFEAEADBBCECEHEBEDFHFCFCAABGHHHHHFAFABCCHCFCAHEHFBFBFHCGFBDGDEBHBHCECGDBAFHHHHHDH,False +720,9.0,6.0,1.0,2.0,6.0,3.0,3.0,2.0,AAABABDBGEHAGABCBGFHEAEDEAEFEFBA,True +721,4.0,4.0,5.0,4.0,1.0,4.0,3.0,0.0,BGBCACGCDDFDFABACECBFAFDG,True +722,16.0,8.0,13.0,19.0,18.0,17.0,9.0,17.0,DFEFCHCGADHDEDAHEDEBFHFEFEAEDEDHAHADCBAFACAHEHDCGCGCDCDHDFECEBEDEDEFGGABFBFGCACFDFAFBDGFHCADHEHEGDAEAHHHBHFHFADCFEBGA,False +723,20.0,21.0,15.0,7.0,15.0,20.0,22.0,15.0,AFCDCFCFGFGAGBCACBHAAFGFBBEEAEGHDEDBHBHEHBCGEGFACEGHGHGCGEGECAFFGEGEGEGBBFAFDCBCFCFADADBHEAEHGBGHGBAFAHCBADFBHBCBFAFHBABABAFABHFGFGEHCG,False +724,22.0,23.0,14.0,13.0,20.0,26.0,11.0,21.0,DEBABADADEGBGBEBHBCCAAEAFFDAAAAFEFAFGFCFCBHBCFFFCFBFDFEHHDHCHCFDEDHBHBGAACEFAHHFABAEEEEGBCHCECACGDHAFDFHFHFEFHAGGGFCHBBDBHBEBFBFHHEHBBBABEEFGFEDGDAHAE,False +725,21.0,25.0,25.0,29.0,21.0,32.0,25.0,20.0,FGGGCGEGDFAHHHCCCGAEABFBEBDBDHDCDEDAFGDGAEFCFCEAEADABCBGGGGGCDCDCFFFEHACBCBCGCFCFDBDFCFAHBDDFDFBEHEADCDFHEHFFEGGDGFHEGEBBBDHEAEAGAGAHBHAAGAHAHDDCBCFFFHFEDGDHDBFBEAHBFBEDFCHGFGDCFEGCHCFBFDEDFDABBFBCB,False +726,16.0,20.0,16.0,17.0,10.0,18.0,13.0,17.0,BBBBGCACACBFBABFBCDHGBCHCBADABFCFCFGAHEGBGEEEFDGDFAGAGCBCEFHFHGHFHAHFDFCHAHAGEBDBDGDCDCHFHBDDADCBFADEEEHHDGFGFHADEDHFHCBCBABADF,False +727,10.0,29.0,22.0,26.0,22.0,17.0,21.0,19.0,BCBCBCBDAFHFCECDCDCBHECFCGAGDGBHFDGDGBGBEDEDEDBCBAFAGHBHDHAADBDCGFGHDBDEGEFBBBCBEBEHECDHEGDADCDHDBBGCEHFGCAEAEBEBFBHADCECFCFEDGHGHBHFHGHBCFGBCEFDHGBGFGEBEHEFFDDBDECGD,False +728,11.0,13.0,13.0,11.0,13.0,20.0,15.0,18.0,EFFFEBCDCHCAAAADFHFHGAFDFHFCFBEBGCGAFBCACAHAHEDBBGEDEDCDGBGFGFGCHCFFDHEBBCGGGGGDFHAHDHBFFCHHDHEHEFBHBHECAGEGEFEFBH,False +729,26.0,25.0,13.0,24.0,26.0,16.0,21.0,19.0,DBDFABGGFGHEHAAAAABFBFBGBDBABAGEGCGFEEGEBEDHAEDCHABCDEFAFAGDHHAHADAFAFGBGAGHBDGCHHHBFFEAEDBDBEHDBBEDDHDHDCBCBEHCACDHFCGAGEGDDBEBEBEAGAEADABAFFFFEHGCGCEEEEBEGDHDGECEABHDCD,False +730,16.0,17.0,13.0,13.0,6.0,15.0,8.0,16.0,CCHDADACCDBABEBHDFBEAGBGFCECHBAAEAEDEGCHCHAFBHGHDBDADAFBDBGBHCHCAGAGHHCDCFFDFBFBADFBFBFHAAADBFCFGFBFHHHH,False +731,16.0,23.0,24.0,23.0,24.0,17.0,32.0,25.0,FFFFFFFDDEDGGHGHGHGFDHBCACGEGEBEBECFFBFBDECCDEHCFGEACHDHDHCFDHEGABHEGBGEAEHBAGCGHGHEEEDEDHFCGDGBAHAGAGDGBACCEAGAGAGAHFBCHCGCDCHCHBDBGBEBGCDFDBCBHEHEHGCGHBCBCGCAADDDGHGBDEDEGBBDFEAEGBCH,False +732,2.0,3.0,2.0,0.0,1.0,3.0,2.0,1.0,FCFGFHCBGBAEAB,True +733,6.0,2.0,3.0,2.0,1.0,4.0,1.0,4.0,BFFCHCHCHAAFADBGFDAHAEA,True +734,5.0,4.0,6.0,8.0,4.0,8.0,3.0,7.0,DGHGDEDEFAFBFBDDEAADFDHCHFAFBDGHHHHCCCCFCFBEA,False +735,11.0,7.0,8.0,6.0,4.0,4.0,8.0,5.0,CHCACAGAEDFDCBHDHFHBCDDHAFGGGCACAGAGBBBGBEBDFAAGAECEA,False +736,20.0,16.0,16.0,26.0,10.0,23.0,15.0,12.0,BDBHCCEBDBACHCDFGFCADHDFDHAECDAGAGCFEFCFEDDDDDDDCFHHADFDABEGGGAGAGADABAFCFAFDBEBEGACADDDHAHBECHDGBGBDDEGEGDBFCFHBADGHGHFFFBFAFAFCFCFBFCFBA,False +737,23.0,11.0,24.0,14.0,10.0,9.0,22.0,11.0,FHADCDEAAAABDBHAFADADFCGGGHGAEAHCGDDCDCDHAHCGGGGCACFCBCBCGCHAAFAHEBADAECGCGCGDGECEDGBFCDBAGACFHAEGCGEGBGCECHGGFHFABABABCCDCE,True +738,26.0,23.0,28.0,29.0,22.0,16.0,18.0,26.0,EHDFFHFHEAFFBBEHDBBBDBDCGEGEGCBCDGHAHDEDEDFAFGCCCACBDAGAEFHFHADAFHCDCDBDHAAAAAHCHCHFHFEFHCHFBAEDHCBCBCBEBDADGDAHAGACACBHEDDDEHCHBDECCGBGBHDCDHDBGCCBGDGCHHGFBAEGEAFACACBCEEEEHEGCGAADAEBGDDD,False +739,8.0,2.0,10.0,6.0,9.0,6.0,10.0,6.0,CGBDCDCHHEEAEACAEEGFHFDDDDFGFEAHCCCCCBFGAGAGEFAGAGHCEGEGH,False +740,11.0,8.0,17.0,13.0,9.0,9.0,18.0,8.0,BGAGBECGDGHFHBHBGDGDGCCCCCCFCFDFAFHBDADGDGBBCACAFEDGDHCECHAEEEBDCGGAGFGCGDAAEDEACHEHCCFGAGDGF,False +741,4.0,2.0,8.0,8.0,5.0,1.0,3.0,4.0,CECEAEHCCADDHDHGGEBHBECFCDDDDCDAGAC,True +742,2.0,9.0,1.0,2.0,5.0,5.0,1.0,4.0,CBHEDBAFFDBABEBEBHFHBHBFBGEFE,True +743,18.0,19.0,21.0,21.0,22.0,11.0,26.0,21.0,EAACDDDHDGEGBHHHHEBEBABHEHBFGCGDGEGCDCDGGCGHFFDFBBGACADADHHADCDGDGBCCCBEDECAGHGHBFCFEDEDEGGCBEFEBEBEHADBHBGGGADADFGFDAEAGBBHGDBHGHCHCACACAEFEGHCECEAFHCHBGEGECA,False +744,31.0,23.0,20.0,24.0,21.0,22.0,28.0,21.0,DADEBEBEDADABCBFGGGGGHGHAFFGBGBGCGDGFGHBCCFDEHEADABAGGBGFCFCAGAHHEDBHBHFFEHAGAGBCDFAEBHDDDDEHHACFBHDGDGACFFBDBAAADAHAHCHCEGAHAGEEEEEBHFFGADABABEBEBCDCBHFHFAADFCGCGBAADDDFCCCHFEFECEAGACAGDGFE,False +745,5.0,11.0,15.0,7.0,10.0,9.0,7.0,16.0,EFHFBCACFCEHBCBABABCECFHHHHFEFHCHCFCBHHGGEGEDDDHAFGEGCBDDDHEEAFBBCHCHEHGHBCBCDCG,False +746,1.0,0.0,6.0,5.0,2.0,2.0,2.0,0.0,GDCDCACECEDFDGCCFD,True +747,14.0,8.0,8.0,12.0,14.0,15.0,12.0,12.0,HCHDFEEGCBCDCAEEEBEFEFCABABFBFDEGFAHEHAHCHGGFCFDEDAHCHDFDGDGABHEAAFAFHFEEGAGDDFBHBHGDGEGAGAFAFD,False +748,23.0,22.0,15.0,27.0,27.0,24.0,31.0,19.0,CFEFAHGBGDEAEBEAEBHBDDGBFAHCGFHFHGEGFAFADBEFHBEBCCFCGEGADBBGGCGBGHHBEGEGABBEEEAHAGEGFGAGFCCBFAGBGFGFGFADDBDBGBFEFGFAAAABHCDDDDDDFDFHFHBGDEAEDDDEDEGEDEDECHDHCFAGAHAEAGADFGHEHDHCCGEGEDBDFCHC,False +749,18.0,23.0,17.0,19.0,17.0,23.0,21.0,21.0,EAADEDBDBFBEECFCDEGFDFHBDAFFBCCCGCHCHAFAFAGGHGECECEBEGAGDGDHEFEHCBAADAFBFBHBABGBGCFCDHFBDEDECFGFBCHHDBBCHDGDFFBFBGDGBHHAHABADADEEGHGHBHFFFFEFGCGCDEHHGHGAAAGBBH,False +750,26.0,15.0,24.0,31.0,22.0,18.0,27.0,36.0,HFCEEEDBCEHFDCDCDGDAHEDGBCCDCGHDEECFHFAFADHFCGEEAEHEHECGABAHFBFBFDACBDBDCDHDHGFBFACAHAHABAHHHCDGHGHGHAABFHFGGHADDDDDADCDEDGDEAGGGGAGBGACCHBHBFDDEEHEDDHCHCHCHGFGAHHHBHFGCGHEEDEDFBAGHGHCECGCAHAGFEADAGA,False +751,2.0,2.0,6.0,6.0,5.0,4.0,2.0,6.0,DCHAHGHCHCEBEGDFCHCDCFEFEDEFHADBD,True +752,12.0,16.0,4.0,9.0,13.0,13.0,11.0,4.0,EBEBDBDBFAHAHADAGBCBFHEEAFAEEBEFGFEFAAAGGGBAFCFCFDGEBBBBBBGAFEEDDDGAGFGCEFEGBDDFHB,False +753,20.0,22.0,13.0,25.0,23.0,25.0,27.0,11.0,DBDAFFDEDEDEFEFDBCFFHDDEEEBEFDFEFEGBGCHCEBEHEHAABAGGGDEAFDFBGGGDFAFAFACHEEBHACBFECCGGGGGGFDFAFCGEGEFHBDBACAHAEFDBDFGABFBEGCGCDHDHDGDBDBDGCFBGCAHGDGBBFAFABEGEGABADADGB,False +754,13.0,24.0,24.0,21.0,25.0,16.0,20.0,11.0,BHBDGCGFGFGFGHGHBFGCEEFEFBAHEHEHEBCDEDEDBBCBCEFECGCDBACAGDGDBBHCCGDAAEAHCEFECABABDGDGCBEDHGFEDEDBGGCACDDBEBCBDFGGGEEHECECEFDFDBBBDCHAFDCBCBCGCFFACAEAEDBFE,False +755,21.0,23.0,12.0,20.0,22.0,23.0,13.0,24.0,FBFBCBFBFECEBHBHDHBBBFBACGBGBDAGFDACHHGCGHFDBHEEEFEAEBEBFGAGAGEDDFDFEFBCAFDFEAEAEDFDBDHECDCFCEAHAFEEHAHGHGHCBDAEGHBDDDBDEHGBAHAFCHGBFHFHEHEADHFHFHFDEBCAAAAHAD,False +756,9.0,16.0,8.0,17.0,8.0,7.0,7.0,4.0,EFEFGFGCCBABHBDDDDGDABBGBFBFEACDBDEDHCGEGBCBCBFDDDEAFABADAHEBADHDCCEDGDBBBAD,False +757,15.0,20.0,18.0,27.0,18.0,16.0,16.0,19.0,GHFBGBCEEAHDBDAHAHEBFFDDDDBFBEEAGBDHDBEGHAHADDEDCFCFBHAHBHDDGDGDECECGHGFGDADEFCFCFDADBGEEBCDEDGABABHBHBHCDCECECEGACCEABFBFBCCHABGHFHFACDDDDDGHECGFGFH,False +758,24.0,10.0,20.0,10.0,13.0,18.0,25.0,18.0,HEHAHAFAHCGCGCHEBGCGHGHGFGCGEABGHGFGHCHEAACABAHACFEAGCECBGGGGGACDFHFAFDFDFDFBEEAEAECFCAADAGFCHHECFHGAGHGEAHFGCCDBDBGACAGADABBDBDCFAFHGEFCF,False +759,5.0,2.0,3.0,3.0,1.0,2.0,7.0,3.0,CFAGGHGHGHBDGDGACEDACAGABF,True +760,23.0,15.0,19.0,10.0,31.0,25.0,21.0,16.0,FGFGHGDGBHACAFAFEFEGEBFGFGFECEDBFEFEHHCFAEACFBBBAFEDCGCEAECFCBBHEGEDEAEFBFGFGADCCCBHAAEEBABAHAHACECFHFEDEABFEDEAEBECACECGFGFEAGAFEFACHGDGAEAEGHHHHGDCBEDEHFHGGCG,False +761,4.0,5.0,6.0,6.0,5.0,5.0,6.0,6.0,EFBFBFGDHCHFEFGGBDAGACHCHDHBAAECCBCDEDEDGHG,False +762,5.0,7.0,14.0,5.0,9.0,9.0,6.0,9.0,EGEFHBHFGFHCEDEBEFACAEAECHCHCHCHBGCFDFCCACBCDHDFGABHBCECDGGEFCFB,False +763,7.0,10.0,9.0,14.0,6.0,13.0,15.0,4.0,FHBHAHAFAEDCDEAEHFDDGFBFBFDGGFGBGBCBFDGDBCGEGECAGAGDGDFDCDCDFGCGEBDGFBACFBFDCG,False +764,18.0,17.0,21.0,10.0,17.0,19.0,30.0,14.0,GFCBGAFBBEFFCGHGEADAHFHEAEAHAHFGGGEGECCFAGAGFFCACBFAFAFGGGAEHGHFHBHCACHFAFDEDHGEGDFBCGCAHGCEBEHCBGBDDCAGBDAGECECACBCBCGGGBBBBBECFCFEFHGDGDGDGEGEGC,False +765,16.0,9.0,24.0,14.0,21.0,12.0,17.0,12.0,FCCCCEGDGDFBEGCBCDDDDCHFGACDHECCCEEAHGHGCCCFEAAADAHGEBEFDDDCDCEAGCGDHEAEAGADAGEFCFCFGFGEAFHEECECEGHGBFCECEBFBCAEBGBGHAHAHAHBE,False +766,2.0,5.0,3.0,5.0,5.0,3.0,5.0,14.0,GCCBCDHEEEFHHEBEHGHBHDHDHAHFGAHDGDGHHHHBFB,True +767,25.0,19.0,25.0,19.0,30.0,21.0,34.0,24.0,AABAGCCCGCDFDAEECGCHBHGHGHDAGCGDFDCEGEBAGFEEEHHAGAGAGFECEHGCECEHFHABEEEBEFEBEFEBCGGGDGABEDEDADGFGFCHHHHDDFBFBAEAEAHGFCFAAAAABAFHECGCDCGFADDBHBGCEHFBBGDHFAFHBHCHFHAGGGGGGAGCGEDEBEDECHFHGBDEDBFGCCCCE,False +768,25.0,18.0,18.0,14.0,17.0,14.0,28.0,21.0,DBBECABABAFFCHGBFEAEHGGEEEHGHGAGADAHGCCFDFDGAFCECECDBBBFBDHHGHEHBHAHGCGFGHHCCFAEAECGAGFHHCEGGGCDCEHEHEDGDHDAGABACCBCBGFFBBHBABADAGGGGHGAGAGAECFBAGAFADAEHDD,False +769,1.0,3.0,1.0,7.0,6.0,6.0,6.0,3.0,EFGFHFCEBGHFBDEDEHEAFDDGDGDGDGBEF,True +770,10.0,20.0,19.0,21.0,15.0,21.0,16.0,16.0,CDHDGGGCGEGECDCDCDABFBDBFBFDFHFHDDBEAEHBGBGCDBGBCHHDGFGCHDHCGCAAHABAFHHBDEFEFCFDFCFCFAHEFBFBGHGDDDCBEGGFEBEAEBDBHCHAEFCDCBFEFEBHCGCBFDFDEA,False +771,4.0,6.0,5.0,4.0,2.0,2.0,2.0,5.0,DBACDGDBBHBHCFDECECACAHAHGBFBH,False +772,20.0,21.0,27.0,26.0,23.0,24.0,13.0,18.0,HHGDAACADHDEDCABDHDFCFDBCFCABDCCCCFFFDFBCBHBGEGHGADACFDGAADDDDDECEHEHDFEBEFCFHFAFCFCFAFCHHHCEBEBEGECECFCHEFDCGBAFADAEAEDEDEFEHEGDAAEBCAEABBFBFBEADGCHDBGBDCDFGGBCBCBEHGHCHBF,False +773,23.0,11.0,12.0,12.0,15.0,10.0,15.0,14.0,HHBEBEDEBGBDFCECGCGEGCHDHGHGBCHAGAGAFAFAHAEEEAEAGBGEGCGAACABBHDABFDFAHADGHFBCDDHAAEAEAEAEACDFDEAAAHFDCCGCHHGDBFF,False +774,17.0,24.0,28.0,15.0,15.0,16.0,18.0,18.0,EFEFEBGCDADCEHBHBHBFBECECBFBFCGCEDEDCCFCGCGFGFACCDFHAHGHBHCHEHECCCGGFCHCADBBBGHHEGCCCGCBHGEGBBBAADCDCDCDADADABFHFAGBDBAHGBBABFEFGBEAHBGCCHFHGDABACAFDEA,False +775,3.0,0.0,2.0,1.0,0.0,2.0,2.0,3.0,AGHGHFDFCHCAA,True +776,17.0,9.0,11.0,6.0,12.0,12.0,17.0,14.0,GCGDABAFGFGCCECFABAEAEBGADHHEHAAAEDEAEABDFCGBADAEHGHFFFGAGFCFDBHBFGHHCGAGHGEGHBHCECEAEAGFCFCBHGHGH,False +777,4.0,6.0,1.0,5.0,7.0,2.0,6.0,4.0,HEFEAEAEDBBGDCDHDFEBAAHEHEDGBBBGGGG,True +778,6.0,7.0,4.0,4.0,5.0,13.0,4.0,5.0,HEHEAFGFAFAFBGBAFFFDEDECBCFGDBEHFAFBFDFHFHGBACCB,False +779,9.0,7.0,5.0,6.0,9.0,8.0,7.0,9.0,DGBEBEDHAFAFHFHFCFCEDEGEDEDGHAFBHBAGAFBCBHFAGADAECCBGEGHHEHA,False +780,19.0,21.0,16.0,16.0,23.0,19.0,26.0,22.0,FFCAGEGEGAHBBEBEGCDFEFCFGHHDHDHDBEFFAGEGAGAGAHEHFAEDBACCCEDGBEACFCFEDEABABABFHFBGBGAGEHHACBCGCHCHGHEABACDBDHEGFGEADHFBDCDCEBBAGHGHEHEHGHDHDGDGFHABECEBDGGFGBGBEFFF,False +781,15.0,24.0,23.0,18.0,23.0,14.0,17.0,21.0,FEAGCCBABABAFAHCDGHFCAEGBGBGHHBBCBFBABAEDEDADHFECGDGAHEBEBECCGCHCHEBCFEDDDCGCGDGDHEFGGCHCBEFECAHDEDFDEHEGEFBBHGGCECECFBDBDBAHAHEHDHECFBFDCECABABHBGBCHFHDHE,False +782,14.0,24.0,23.0,18.0,18.0,17.0,19.0,17.0,GAECGCBBAGAGAGFEEDDFBEEEBBGGEECCCCBEGEGFGDGCHCHCHEADBDBHBHFGADBFGDHHGAGADDDDDCBCDHFBFHDAGFHFHFHCBCFEHHHBFCFHFCGCBCAGFEBDFCECHCACBDBCEAGDBDBEBEBEBABAFC,False +783,17.0,21.0,14.0,26.0,20.0,11.0,14.0,15.0,CHAHEHDHGCCADABAEDBDBFAEABGDDCGADADBBAFCEGDBEBDHGEGFHEHEHEFCFDGHADADBDBDCDCGBABDECEDEDFDCDCDADEDBDHGBGBECDHEHFFBAEAEBEBGHGEBCGGBEFHBHCFAFA,False +784,9.0,13.0,21.0,19.0,11.0,19.0,13.0,15.0,ADHDFGEBBCCDCDCFHAGDBCBCECEAGAHCDEAHBHEFEAHHGDCHCHDHDHFBEADFCGCHDHAFBGBGBEFDFGFECACFEFGFDCDEBGBGCFBFCDGDGCFDFHFHFCFCDCDB,False +785,3.0,4.0,10.0,4.0,5.0,8.0,5.0,7.0,FCFCGCGEAAGFCECECHFFDHCACGCGEBHFEFHBHDFDBDBHHC,False +786,13.0,15.0,20.0,21.0,12.0,14.0,14.0,18.0,BFDGDGDADECHCHCEDGDBDGHCHDGCABEEFEFGGDDBDHDHDGCCEBDFDFBHBHBHFHFAECEBAAAFAEAHBHGHDFEFBHBABECCCCCDEGHGBFFGHCDCBGDCCCFHDCACAFGHADA,False +787,12.0,21.0,22.0,19.0,22.0,24.0,29.0,14.0,CGCGEECEGGBEAGCFFFCDCEEACFBFBGBGDGDHDHCBCGADEHGHBFGFGFDFDBGEGEBFCFCFCFABDBCAFFGDGBFHCHEECDFDFCBEBFHGCGEGAGAFDFCEGEGEAAHHHBGCGCGAGDGDBDFGEDBDFDBCHADEEGEHEHABBFEHBCB,False +788,17.0,13.0,19.0,20.0,16.0,16.0,19.0,15.0,BDCEGHGDAFFHFHDADAHEEEECFCGDHBHGGGAGAEFGBCADGCCCCCCGCDCBEFEFDFECADABAFEBGBGAADGEGHADABHFHFCEDHDGGCDCDFDADGHCFBBCBCEHBHFHDEDEDEGHGAAAFBF,False +789,28.0,17.0,13.0,32.0,28.0,13.0,27.0,17.0,AEADADBGBAFAEADGBAAGDDEGEBEFCFCFHFHAEGEHDHAADEDHDCFCBAEGEGDGCGAGBGBGBFDDDEDGBGBGBDDGGADCDBGAEAGDBCADEDHBABAECHCECAFEHAFACDCDGEHEHFBEHDDDDFEAABDHGHGHDAGECEGEGDHEAEGEGEAFHDHDFAE,False +790,20.0,14.0,14.0,14.0,17.0,15.0,16.0,18.0,FCFDDDHCHCEGHADCBGFEFCFEEEEBEADABHBDEFCABABAGAGEHHBHBDAECGDEAAAFAEADBHCGGBGBGBEFEFEFABAGFHHGACDBDHHGFDACEHDHGHFCFDHCHCHCEFAGAGAG,False +791,18.0,17.0,18.0,19.0,20.0,20.0,6.0,18.0,FHFHFDEAADAFBBACGHDCDFAGGFEFADEDBFBFECEAFAFACCCEFHBHFHBBACHFDGDCDHDHGBAHCDCBHBEEEEAECBABCBCEDHDFDEDEDEAEADACAHFHFHEDCCABEHEBEHCFBFGFBDHC,False +792,14.0,17.0,13.0,12.0,11.0,16.0,16.0,11.0,DDBDBDAFBDBFAFAGBDEGCCECHCHCGFABGBCFEFECHFBABAEECBDHDGDGHGHGFCFHEAEGDHBCBEFHBGAGACAHAFGFGFDEABFBABGFGFGBHCAEDC,False +793,9.0,19.0,17.0,11.0,13.0,16.0,16.0,13.0,DCGHBFFCGEEBEGGAGFDEEBFGHCHCDFDBCBCFCFCGCGBBBCBCBFHFGCAEABHBABGBDBDFDHAHFGFHBBBGHGHECFDECEGHGHDAAGDBCECDAEAEFEFCFH,False +794,18.0,14.0,23.0,18.0,18.0,15.0,28.0,20.0,GBGBGFGAEFECEBGBECECFGDEDGFCFGGHCHCFGDAHHCHCFCFCGCGCEAHAEABACDBDBAGGCGHAHBDFDHEHEGAGEGEHHDCDGFHBHGHFADECACAEABFCAHGHGBDCDFDFBAGACDGGCDBGGADHDBFHEHEAEGDCEC,False +795,2.0,6.0,5.0,6.0,3.0,1.0,4.0,1.0,GDGECBCHDEDECBBFBCBABDGDGACD,True +796,20.0,15.0,22.0,19.0,22.0,17.0,35.0,28.0,EHGHCDCDAEBCBFBACHCGEFEFEFDFHGHDCGAHDCGCDCACBGEEHEHGGGEHEFEGGAAAAHAFFECCAGHGHGHBACACDCFEAGGGGGGGCGAFCBEHHGDGHGADAHGHBDGAGBCDCABAHDDEEFGGEHHHBBBDBDHDHDHFHEHBCDCGFGECEFFGFGEGHFBEDA,False +797,22.0,14.0,14.0,13.0,13.0,14.0,15.0,9.0,HCHGGBDEFAFAGAHDCGCGCHCGFAADEDEABAGABFEFEFEBDFGABHFDAABCHCFCADBBAGDGDGDCDFEFGBDBDFFGCBCBEBGAAAAAAHEHEBEGCAAAFHECEC,False +798,15.0,14.0,14.0,26.0,14.0,22.0,16.0,23.0,DCGAADDDHDHFFDBGGFGEGBBDHAHFFFFAFCFBDDFEAEDHDHGHGDCHCFAGBDFCFEFGAGHECFCEDAHAGEBFBABDEDADCDHAFCFAFHBDFAFADEGEHEHBHGFGCGHGCDCDBBHHHHBCBCHDEDEDEDHH,False +799,27.0,20.0,19.0,24.0,17.0,17.0,26.0,21.0,GFGDGDCDFGBGBEBGBHHFDADAHEHEBBBHFFGGCADACAGHBHAAFACACHBECEFAHADGDAEHECFABCGCAHBHAHDGEEHFDFHFDFCAHDBDBFEGDGDGHBDBGAGEGBGCCECEBEHAGABADADADECGCGCAFHGHBFACACFDEDEBGACAGHGFDDD,False +800,14.0,22.0,27.0,22.0,29.0,27.0,20.0,20.0,BCBCBCACACAHDBFCHEHEFBGGCGCABBHBEEEBECECBDHDEBAACGCGFGFDFGBCDAHHHHFFEDDDDEFFHFDEGGGHEAEDEGBBDFEADFCGCGCHFHGHGEDCHFFFDFDCHFBCBCBCEEEGACAEHEFGFDFCFBAEHECGDEFGHGAFAEBBBBDCEHFCFEFDCDEDE,False +801,5.0,1.0,4.0,0.0,2.0,1.0,0.0,1.0,HCAEACAFBEACAC,True +802,15.0,14.0,17.0,11.0,11.0,11.0,14.0,5.0,DGAEAFAFCFDADEFEFCACGEHEFGCHABACABHBADDFDFCGEGEAAACHCGDGCGBEBFDCABBBBDBABFGGCCCEGFBBBEDAHCGCGCGCED,False +803,19.0,24.0,22.0,27.0,21.0,24.0,25.0,26.0,HFAFEFEFCCCHCHGDDHEHEDEACCFAFBHDEDEBGCGBFAHAHAHFGDBAGAHBHFEFBFEFABCDHDGACACBGDGHAFBDBCFHFHDHDGDADBCFGGBDACGHGCECEGGAGDGDGEGECADHDABGBDDCECEHFHBGGEGEHBFBDHFACAFBBBBHEEEGCDHGFDFDFEFHDHDCBBBC,False +804,14.0,12.0,12.0,16.0,9.0,14.0,9.0,8.0,ABCBAFDEDFDHDCDBAFCBGBDBEAEGEBCDGAACABDECECEHEAGHGDBHFFFCGDADFFFGFDBDFAHCHCHCHCBADADADABFFGGEF,False +805,10.0,5.0,7.0,4.0,17.0,8.0,9.0,3.0,AAGAGAGAGAHECEFEGEHEBEAEFDADFEEEECEDECHGFEFAFBEDFGBEACBCEFBCCGG,True +806,16.0,25.0,13.0,17.0,23.0,16.0,21.0,18.0,CBGEEFEGBBBCHGHBAAAAGAGEGCHCEDBBBBBHHHHDAFFEEDEDAAADFEBHGHDHEGEGHCECEBBDADGGGGGDGHEHEHEBBBFGFAFDFEFEBEBCFFEBHBECDBDFAFAGHDFDGBHDCFCAABCBHEGDGDEBGCCAF,False +807,3.0,8.0,5.0,8.0,9.0,8.0,9.0,9.0,HFFFBHCHEBEBEBGBDCGCECEFDFBFGAGHHDHFACHDHDEFBGDGEHEADGDBEGG,False +808,18.0,19.0,24.0,19.0,15.0,25.0,23.0,17.0,CDGFCFCAGHEAEADCGEGACBGFGDHEEECACECECFAHAFDCDHDFEBEHDFDFHFGBEBGGGBBBHBHFAEAFGFAHAGAFCGCHCHGHBCDDFDFDGDFBEBEBFAFCFGDCCHGHADCBFBGBGHFCGDGBCAHFDFCFCBCBDAEABADGFGHC,False +809,24.0,16.0,20.0,18.0,20.0,16.0,26.0,18.0,HBEFGCGHAHADGCACAFBFAFCEBGBFDGAGAEHHCDDHDFDHDHDEECGABCBFEAEHDGGGGBABGFEBCAEGBCFCHGHBHBABGBHFEFCCCCAHGEGEFHFDGAEBHDADCGHEAEAEAEAEGEDCDADGDGAGAGAEHDGCCFCFCADBGF,False +810,7.0,10.0,7.0,14.0,17.0,13.0,14.0,8.0,DEAEGEFECACABGEGEAHGHGHAEFEFECHDDFDBDBCBDBDFGCGEBECEDDDADBEFEBDFGBDFHGCFFDGGFEHEHFHBGAGEGF,False +811,11.0,12.0,11.0,18.0,16.0,11.0,15.0,16.0,EBEBABDHDHDHEHGHFAAGGCAFEDDGEFAFHDBDBDHEGGGGBCBCFDDDDDEDBHFEBHCHABEFEFGHECECBFGGGEDHCHCGEGACAEAECHABCHDADFDFHG,False +812,7.0,8.0,5.0,1.0,6.0,6.0,5.0,5.0,HHHHAEACACBEBCCAFAGEFCFDBHBFBFEGAGEGBGFABBE,False +813,7.0,6.0,14.0,17.0,20.0,8.0,11.0,16.0,BCHCAFAGAHCEFEDEHEDCHGHAEDGDFCFHGHGHAEGEGFHBBDFEHEDEDHDEDEBGDDFBEHGABCEDECCCADGHEHEHCHCDCDCDCEEGEFD,True +814,27.0,14.0,15.0,25.0,17.0,16.0,12.0,25.0,HFFCACAHFFCBCFFGDDECEFEHCBCBCDAAAGAHAHDECEFHAHAHDEABBEBCFGBGDEAEAEADGHAHACDHHHBCBEDFFAFHFEEGAAAAAHAHEHEDDDDGAGDHDBDFFAHDBACACAGHHDGBGBEDDBDHFHECGDDDHDH,False +815,9.0,8.0,11.0,6.0,5.0,16.0,9.0,7.0,DDGCCHAAADDFEFBHDFFFDFCFCFCFEBEGGGCFCGHGHEAAAFFHBCBGBEBCBFFFCFCAAGAHHGB,False +816,27.0,23.0,14.0,24.0,26.0,27.0,25.0,22.0,DABHHHEHAHAEFDBAGABDBGHDAAGAGFBAHAHEEDABFGGEEADAFBCACGCGCEFEBEBDFDCDGDEFEHEHFAGAGCBCGCBCBEDAGGBABHDFBFBDEHEHGBFEFEBDFHFHFDEECAFGFGFEADHDAGAGADCDCHFHCEADFDGEAFBFCFDBEEDGAGBEFEHDHGAGHGHFBFBF,False +817,1.0,1.0,2.0,2.0,3.0,7.0,3.0,4.0,FFFFADHDHEHEGCFBGECFHFG,True +818,10.0,14.0,17.0,5.0,12.0,5.0,16.0,9.0,CACBHAACABGDCAEAFGBEHEGCGCGEGEDBGAGFHBGCECEFEGEGBHBFGAGHEABDFDBCBCBHEHGHGBDCACBGBECCCCCH,True +819,20.0,12.0,13.0,11.0,16.0,13.0,21.0,6.0,ADCECACDCEGDFFAFBGBGBGBAAAEBEBGFDADEDAACACDCHHBGGGGGGGEGAAHFEFCGDGBCFABAFEGCDHFECEDEHABCDAHFGAGEGAGAEAGBFBCEFEFE,False +820,24.0,22.0,18.0,21.0,20.0,19.0,14.0,22.0,ECFBHAHAHAEAFBFGDGDCBCGAEAHABCBHFEDEDGBCDCDADABAEAEBHDGDHCBAHFDCDHHBHEGAAFAFCHCDDEHBFBFDGDGHBAFCEDEHFCEHEHEHGCGAHABCBEFHFGCDCDFBFBFAFGBDEDAGCHBEBCBADAGEBEAEAFFH,False +821,24.0,21.0,19.0,22.0,19.0,13.0,20.0,29.0,DAHAHAFEGCDEECECAAEHEFDDDGAGAGAGABHBGEHDHFHEHAHAHAFBHBHCAADCEBBGDECHGFGHGAGEDFDFDHHHCGAEABFDGBECECAHACFCHGFBDHGFDHBHDDDDGGHEHAHBGBGBHEABBFBDBFBDAEEBECCCCCACHCBCHAHDGDB,False +822,16.0,25.0,27.0,23.0,14.0,15.0,16.0,28.0,BHCHCDCAGFGAGBFHEHBABGDHBABFBGBDCHCHCHEHAHEHCHDBGBHACADADAFFHAADACBCBEGEFDFDFDFCHEHDDBDEGEDHHHCDEGHCFGFDEDBBGFGCGHAHBDCECHCABHFCCHCDEDCDCGBBEHDHBGBFEFCACHCBBABCBDGC,False +823,19.0,16.0,17.0,19.0,13.0,21.0,12.0,12.0,AAFGBDHDCDFDEHBBFHFCDCABBFDFGEGEBCHDDDBDGDACAGABEGECECECEFEHCHAGDDHCCDAEFFAFBFBGDAEHHBABAHADABGBFCFGDCDFHFHAGAFAFDFBACACFGFEFECBC,False +824,23.0,14.0,24.0,16.0,17.0,21.0,26.0,11.0,EEEECEBHDFDBDCFAABFDEEGGCGEGFHDGAGBCFCHCFAFAGAGFFBGAFAEABCGAEADADAHBBEHCHCBCBCDCECGHBHAFDEDEAAACACFFECEFFGACCDCFGGCGCGFDFHFGCGCGAEAGGHHFBFDADABBCGGGDGDG,False +825,16.0,23.0,19.0,19.0,25.0,21.0,19.0,16.0,BCECEGEHBGBGDACADFFBABGGEBEGCGAGDBCFCEADAEFEDDCHCDEDGBGCFHFGBEBEBEHCHCEBEDEBFBFEFHFHFGDEAEBGBEDDCBHDFGFCACAGAHBDBDBCCFCFAFDDDADHEEEFHAEAGBGCAHHHEHFGFBFGECHABF,False +826,8.0,5.0,4.0,4.0,6.0,3.0,1.0,4.0,CDGDCFEEEEABABADAHBFBHACAFHEAEAHCBD,False +827,24.0,26.0,18.0,19.0,16.0,34.0,27.0,29.0,CFAFCHHGFDHDBDBDCDCHEFBGBGBHBDADCGCGHGFDFBAHDDAFECBFFFHFAGECAHAEBEAAACGEGHGEABAFGCEAGFFHFGACBGHGAFHCHGHGBFAHGHBHBGBGAGCFBEDHBFBHEHEBFGECEADHFHFHFDABFEFHFEFBFBABDBDFDADGDGCAEAFCFCFCDAGGFGFBHHHHB,False +828,2.0,3.0,1.0,7.0,4.0,6.0,1.0,1.0,ADDDFDFEFEDEBFBEGFDADFHCB,True +829,18.0,8.0,19.0,22.0,14.0,21.0,12.0,12.0,EGEGCHAFEECHDBDBDCFAFEFDFEGEAFCFDADADCHFHEADAEHDHCCFCFDFHFDFDACACACEFDFDGBFBCGEGFGCGCAHADACEDDGCCACHBABDBHAHFFFDDHACBDEAEGGGFD,False +830,14.0,17.0,12.0,13.0,7.0,7.0,14.0,9.0,EGEBHBDCDGECBABADDGCABACFCEBDCCADADFGHGHGFGBGBGHGFDDCDAGABACHHDHDFDCBBGBAAFACEHAGAGBEBHBCBEBF,False +831,13.0,21.0,11.0,11.0,12.0,12.0,12.0,8.0,EAEDGBFBDBCHEBEBEBCHCHAFGGBCDDDCDCBADAFAFABADFCBCGEAEDBAFAEHEHADFHBBEHEFBFGEBHFGBCBCBFGGAGAGBGCGFBDB,False +832,14.0,20.0,21.0,16.0,26.0,24.0,30.0,17.0,BGGGEEEBFFFEFCDGGGGGCGABDFGHCAFFFDFEHDHAGAGAEBEBCBCAGBBDBFBFEEEDDFCCGCGEGBBDBHEDCFCHGFEEBGCFAEGEGECFCGCHEDDCBEDDDHHHCGBGEHEHGDDCGCGBGEGEBEHECGGAEABAFAHAFAFHFHCHCFFFHFBA,False +833,0.0,0.0,2.0,1.0,0.0,7.0,1.0,2.0,GFFCFHDHCFFFF,True +834,15.0,17.0,13.0,12.0,21.0,19.0,18.0,23.0,DEFBAGHEHEABHDFGFHFHCHDHECEHBHDGDGFFCGBFBEEHHCDEFECEDEBCBGEGEGACAGHGHAHDFCBHGFFFFDACEHEBFBHBHGAAEADGGADHHHHGHGFAFCFCGEDFFABABGECACABEBEBEB,False +835,9.0,17.0,15.0,12.0,13.0,15.0,12.0,18.0,AEAFDHGHGFDEDBFBABACCCFCHEHCFEDHFGFDHBHBHEFAACHEDECFCGCBCECEGHBHCABDBEGFDFDBDBEGEFFCCGHAHAHGHDFBBGBGDGHBHBCBFHE,False +836,24.0,27.0,17.0,31.0,24.0,22.0,21.0,23.0,DCGBEBCDEDADFBFEDADADBDCDCDEDFDGBGCGBHBHBHEHEDEDAGBGFDAHGHBCECADBDEDBFFAFAFAFEHHGCGFEFDDGDGFBFGEGEBAHAFDDHFABBBDADAHAGAFFFCGGEECHGAGAEECEBFBCBHHGEFDAAECFADHGHCHBBBBDEDHBBBEHHAHCHCAEFEHADGDC,False +837,8.0,2.0,11.0,12.0,11.0,8.0,3.0,11.0,BHCHEDEHFAFHDHCHFDCDFDFDAAHCFDDADHDECECACECAFEHEGDGEHEDEHFCBCGCAEA,True +838,12.0,19.0,12.0,11.0,20.0,17.0,13.0,16.0,DEFEFEHEFBFECEAEAGBGAFEBEDFGFGAHFHFCGBBBBBBHEFEBHBGBGHCHFBCDFHAACCHEHACDBFEGEDFBCBABHHCHEHACACEDDDDFDGHGHCAGFDFBEEEGEGBA,False +839,1.0,4.0,3.0,4.0,6.0,6.0,4.0,1.0,GBEECAGBFBFBEDCDFDFEEHEDGFGFC,True +840,5.0,4.0,4.0,1.0,6.0,4.0,2.0,2.0,GEBEFEHEAADACACFCFBBHCAGEBEF,True +841,15.0,12.0,13.0,8.0,18.0,15.0,11.0,15.0,FHFHFEAAHFEFCGEHEHCHCBCAEBBBCHAHAEGFGABHBEBEFCBCAHDHBEAFGBHAFEFBGCFEFCDADBDEDEDEGEFEFAACHDHAEACGEGHGCGAGFDC,False +842,17.0,27.0,15.0,15.0,25.0,21.0,18.0,18.0,DBEBDBEEGGGBGEHCACBCBABGEDEDGFAFCCBEDCGGFGBHAHDBBHBHECACEDBDHAAFAEBEDCDCHGBEDECHAFAFECECEFHGHGHBEBGBGBFFFFHFEFHFHEBEGEAEFFAFGBBBFHCHADFDFBABCGAEAGFHDADEBHBE,False +843,20.0,14.0,16.0,25.0,17.0,16.0,12.0,24.0,HBHEDGBFBCADADACHHDHDAEAHDDDDDHFFDHDGCGCBHEGABAHEDEABACDCEFGFHAGGBACGHAFFGDCAAGHDEGEGEDABACABHFDEEBEBDBDBDHDADAHCHBEFEDEDCFCFCHCHFHFHFHFCAEHHFCE,False +844,6.0,6.0,6.0,6.0,7.0,4.0,7.0,2.0,GCECFBDBDBEGHDEAEAFFECECACBGBDADGDGHFABGEGCA,False +845,14.0,10.0,13.0,17.0,13.0,16.0,16.0,22.0,DADFGHGHFHCBGAFEFCFCGDGDEDBABABECDCDBBGAFAGAHDDDDFDGDGDCEGGFHFHCHGAGDHHHFFCGCHHEFEAHHHFHGEGDAHECDCHHAHAEAEBCFHFBFCEHBBEEA,False +846,13.0,21.0,15.0,9.0,8.0,13.0,6.0,10.0,AGBCBCBDGCBFGHABCBCBEBABCGHEHBAFAFDFECDBBAAHBHBHCFCFDBABDCDFFCGHAHBHBEBEBCFCACDEHACEBFDFGFAFAED,False +847,8.0,14.0,10.0,15.0,9.0,10.0,9.0,7.0,DECFAHHBGBCEAACBCBADDEBHDHDEDFFFGEAEBGCGBGDGDFDADBDBDCFCGCBCHABFBDEDGDGBHBFFCFEAEH,False +848,10.0,5.0,6.0,10.0,12.0,17.0,10.0,11.0,DHDEDCDFDFAFAHCFGABAGFCFBGGGGAHCFDFAFEEEEBBABHFAFGFEEHDHECEHFHFEAHAHEDFDFHFDGGGEC,False +849,22.0,14.0,13.0,19.0,14.0,18.0,13.0,19.0,AACFCFBBHBGFDADADAHHCGFBCHHFHBHDGDCAHAHABDEDBDAHAGFGEBEBACHCDEGAFFDGBHFCFDDBABAEEDEGEFEAAGAGABADAHFGFCFAAGCFHEHFGFBFEEDEHEDCDCDCDHHH,False +850,12.0,11.0,24.0,25.0,18.0,37.0,27.0,36.0,GEGEAEAEDHDEDECECGGGEFEFEGCBFBFCFCDCHEHDDGEGFGDHFGEGAGCGFDHCHFHDGCCHEBBDACHCFCHGHCHCHGDFFFFDFHGHDFFFGFGHHHGCDFBFCHHFHDDBACHEEFDCAHDHBHFFFHHCHBHFHDGFGFGBEAHFHFHFCAGGDCBGDGDFFAACDCAFDFDFBHHAHE,False +851,8.0,20.0,9.0,10.0,16.0,10.0,11.0,18.0,GAGAGFFHFHCHGHEFEGADABHBHBFEEEBAHCHCEEHEDCAGGBBDBFGFHFHAHFHBABEHEBFBCHEBBBDDDCDBECEGDBCBEBEBHBGCHEDDHG,False +852,8.0,4.0,3.0,3.0,5.0,4.0,5.0,3.0,CEHEHBGFGBABDCGAGHFDCGAAAAEADAFEFEB,False +853,2.0,2.0,4.0,5.0,2.0,8.0,1.0,9.0,BHFHFHFADCCGFDFDBDEFAHHHHHFHECCFD,True +854,0.0,3.0,1.0,7.0,1.0,4.0,3.0,3.0,BGEDFDHDHGFBDBCGHDFDFD,True +855,13.0,9.0,23.0,8.0,13.0,14.0,12.0,14.0,CFCFCGHEACCCEEEGDHHAHBGBCFCDCDCFFGCAFDCABHCHCDFFCECGCGCAABFDEDACCHHAFAEBEBHGHBHFGEGCGCGAEBCBAGEFEFEFDHAHAH,False +856,10.0,14.0,21.0,25.0,13.0,22.0,18.0,15.0,HDAFAFDFBGDDCEEGEDFGBDBGCCCCDDDGDGHFDGHEFECHCHCFEDBDBACGFBFBFDCGEGCABABDEGCGCECEBAFGHHBDDDHHHGGDCDCACAFBEBECFCFAEHHFFFDGDGHGHDDFDFHFCFCBAF,False +857,5.0,7.0,6.0,6.0,3.0,6.0,3.0,6.0,HBHCDAHAFGBACABHBDBDEFGCHCHCBEFEFGFCFDDBDA,False +858,5.0,6.0,10.0,9.0,8.0,7.0,3.0,10.0,BGCHCHCBDDHDGDGABCBABFECECECDCDFHHCEDDFFFHHEHEAEAFHBEDHCAF,False +859,5.0,3.0,3.0,10.0,1.0,2.0,6.0,6.0,DADADBGHEADDDCDGHGHGCDCDBFAHHFHAGDGB,True +860,23.0,20.0,27.0,31.0,27.0,21.0,22.0,20.0,GBHCDCFCFDEDHCHGEFEFECCCCCADABAHFHFHFDGDAEEHACDDGBADFDEECFAFCFEGCGEEHFAFEFBABCDADEDEHBHGHBBAECECGBHAGFHHBGECCDEDBFHCACGCDAGAGADDDDDCDGFCFCEEEDEBHGHGHGCGCBDADHBGDDEDABABAEDEBFCDEBABGBDAFAFGEGH,False +861,7.0,7.0,14.0,4.0,11.0,5.0,11.0,5.0,GCGFGBGCCCGFAAEAECECECGBABHHCAEAHAEFEBEHDCDCGFGFBCGCGCDBEEHDGECB,True +862,12.0,3.0,10.0,5.0,8.0,8.0,5.0,6.0,GFCAHAHAGACCEHDBBAAAHADECEDECGCBCECFCFHFHAGGEDEFFCFAEAFAD,False +863,24.0,14.0,29.0,24.0,18.0,18.0,12.0,25.0,ACACHBEBEDABHBGCDCFCEDFCGCACGFADCCCCBCDEAEBDHEEGAGCDFDFDFGEHAHFEEAEHCCFHFEFCHCHDAAHGDCDAHFHEHDHDHAHADEBEBEGADAHEBFHFHACGFGCGCBCDCDCACFCFABCBADDBCBHHDHGAAHAHFFDHDEDA,False +864,12.0,14.0,8.0,8.0,15.0,8.0,10.0,15.0,EBEBGHCABAFAFDFDADGBHCEBGBGBCFCAEEDHCHGHBHDGDHEHEHEHCFGFBEEHAAAHGHGEGBFCABHFHEEBADCDABEBEA,False +865,3.0,2.0,2.0,3.0,0.0,3.0,0.0,4.0,BHDHBCFDFCAHAHAFD,True +866,5.0,8.0,8.0,6.0,13.0,7.0,15.0,8.0,FHCDEDADBEBGAGCCCEBGGFGEGEGAGAGHDHGBEHEDGAGEBECHCGFEEHEHGGFBFBFCFHEBCD,False +867,15.0,8.0,10.0,4.0,10.0,7.0,12.0,11.0,GCHHEHGBDBCGCBCFEAAHAHADFCFCFGAGAFBGAHAEGFBECEABHCHAEAEHGHGFBDCHGEGEGDACABAEA,False +868,13.0,19.0,24.0,20.0,14.0,16.0,12.0,20.0,HCHAHAGDDCDBGGHGHGCEEAEGFBFDEAEFCFHDHGFAFGEHDBDBDCECDFECHCDCFCHCHBBBBGAFDCACEDBFFAFAFBEHCACDHBCBCBHBCADDDBDHDHCHCBABHHEFGAECGCGCBDBDCFHFEE,False +869,11.0,10.0,12.0,15.0,14.0,12.0,10.0,5.0,CBGECDGDGDADCGAHDBDFFFFEAHFEFDBDGDGECECDDFDADBEACGFEBEBECCCGCBCBEAEAFGBAAAEDEGHHDHCFAFEFB,False +870,8.0,16.0,15.0,5.0,12.0,6.0,10.0,5.0,GEGAAFBCBCEGAAEBEBEFHHCBAAGACBBBBEBCGCGCECECBABCFCGCFEDEHCCDGBGFDFDEHCHBBGBDE,True +871,7.0,10.0,13.0,4.0,10.0,7.0,7.0,8.0,GAAHGCBADEDHDCCCACAFHEBBBBBCBEGEGFCHCBEGEGEHDHCFFABCFCFHGHABFECECE,False +872,5.0,6.0,11.0,4.0,5.0,6.0,7.0,6.0,FCCCACBDAFCCCFGBBHBGAGEGDGCGHGHDHDEBHCCFCBAEFEFEHA,False +873,6.0,3.0,2.0,8.0,3.0,5.0,4.0,1.0,AADDDCDCGGFFEBADADADEDGBGFFEFAHB,True +874,16.0,16.0,9.0,13.0,16.0,16.0,11.0,18.0,DGAGHBHCEFGDAAEAFAFBBDFHEDEDHBHGHGHDDEDFCFCAAADAHFBCBCGEHEBFDFAFCFAFAFBECCBEDHHEHEGBGCDFGFHHHBHBEBEBHAEADBEBAAGEGHF,False +875,10.0,10.0,11.0,9.0,10.0,8.0,13.0,16.0,AFADADEDEFHCHCFGBGEHDFGHCHEGBGHFABHEACHBHBHBHGDGBAAAHAHCHCGGGCGEDEBCDDGBGAECEFFFBCHCHDE,False +876,10.0,18.0,8.0,11.0,7.0,15.0,11.0,9.0,FCHDHBFBGCDHAGCCHDHAGFFHBHEFAFAFDBBBDBDEACGGGBGFECECACHDBABFBDBDGEADADFFFGEGEBBBFBFBGBFAH,False +877,4.0,5.0,14.0,13.0,6.0,8.0,11.0,11.0,ACACGHADGCECGGGDCCCFCFBFDFDHDHDADHDHFFBHGHCHCGCDCDHDEEBGFDEHBHGEEBDFCCGG,True +878,22.0,17.0,15.0,16.0,16.0,19.0,13.0,15.0,CCFCHHDBEGEGDCFHFBAGFEDDFDCECEGBCBABADADBGGDBACAFAEABHHHFHCHDBFBDBDBEHHCHCHEEGFGFHAEAEAEADFEAABCFCEAHFGAAADFDFBFBEGCGCDAFAFAEDGBHBGFA,False +879,11.0,12.0,5.0,10.0,10.0,9.0,11.0,9.0,BCBCEAFGFGHBHBHDDFEFGBGHGFBDCAAGEHDBDGHGHFADAEEFEDEDEAHABABACAGHEDFAGEDBGBCBF,False +880,22.0,23.0,20.0,22.0,17.0,22.0,27.0,22.0,AFEFEHDHDHDBFBGBGEGBGFGFGEHEABABGGGABAHDHEBCGCGCFCDBDFEEAAAFDCBFHGHBCGAEDFDFDBCECFBAGAGAFEHGGCGDBBCCGBDDCDBDCFCAHDBAFFHCHDHFHCEEDHDHBHCCBFBAEAEAFGDCDHAHFHEHADAGAGAFBGCGHGFBEGG,False +881,26.0,17.0,21.0,13.0,20.0,12.0,23.0,19.0,BAEAGCGHGAEADABEEEGAAHHDDBDFGAGACCHHEHEBFBHEEEDFGFEAGHCCACGEFEDCGCHCGFHHBHBGBCCCDCGBGBABABFDDHEAEFEGGGGEHAHACACDGBGBGBEAFACEHFAAAHGHGDCCECFCBCBHDAAAFAD,False +882,1.0,1.0,3.0,2.0,1.0,1.0,0.0,5.0,DHHFADEBCHCHCH,True +883,7.0,3.0,8.0,7.0,4.0,4.0,4.0,4.0,GDEDCFHFHDHDEGEACDCABBGFACACGCFCDADBCAEAH,False +884,21.0,12.0,14.0,11.0,9.0,9.0,15.0,13.0,EHEAEGDDAGGBGFFAGHDHDCDCDCFCGGGGGAAEGCHEDEAEFHFAFGCBHBCCCCADBBAGAGHBCACAHAHBFEDBGBCBEDDHHABAFAHAHFBCAAAA,False +885,16.0,26.0,24.0,20.0,25.0,24.0,19.0,20.0,DFDGGAEAEAEDHGHGCCABBEECFCFGBGBDCGFFDBDECEADADHGHFDBDCEEBCGCGAFBFBCHDFDFEFEFHFHFHBHFEFHCHCBAFDFBFCAGAECBBBBEAEBGCECFHEHDCCEGBGBGFGFHHEHCHBDACECABABDBHAEDDCGGBBEFDFDCBAEHEHECG,False +886,13.0,28.0,17.0,8.0,23.0,25.0,17.0,16.0,GFFBFBHCFBBBCGCGEEBCBABFDEBGBGCACEHFHFHBADDCGEGEBHAAACFCEHBHBDAEFFFFDFDFEFEFECEBBBHFGBBHBEGCBEAEDCHEEEFBGHGECEHFHBABFCFCFCGCEAGDGAGAFBGGAFHHHBEBEBF,False +887,12.0,16.0,10.0,18.0,15.0,11.0,14.0,8.0,EEHEFGDCAFDGDCBFBFGFBEAFBBBAGFGBGCHCHCAGADCFCDBDEHEAEDGDBHBFGEBEBDBDADCDHDEABDDEDFCAGDGAGAFDEAGCGBEBEHEH,False +888,18.0,13.0,17.0,15.0,11.0,10.0,18.0,15.0,DEGEDEFAHAHAHGHGHGCGCFDDDADFCBGDGDCBABCBEACAGAGCEDBABDHFGAGAGDEEHAFCDCBCACBEBHCGBFAHAHCDFHBGBGHFHGHFBACEGEGCHAECFCDAD,False +889,22.0,5.0,11.0,9.0,14.0,19.0,10.0,13.0,HEHFADEFGFCEHEFDFHFAFGGGGAGAFADGDFAEAHBCECEDFCFHFCFDFDAACACABBFGCHEAAABCDHEAEABFHFHEGEFHAAAAACAGDHCHEFE,False +890,27.0,36.0,17.0,27.0,26.0,14.0,25.0,25.0,FHDGFABEECADAEBECEABAGHECDCDADGDADADEHEHGHBFBCBGDEEEEEBABABHBHAGCEDEDEHAHAGGCDCDHBABHBCACAGFCFGHHFDFDGBGHGAGCGFFBHADFCECEHBDBGBABACAHEBBHGHEHBBEDEFEBGBDBCGEDBBBBBEBDHDBAHGFGAEBHAADGHGDABFCFDAGBGDHD,False +891,18.0,15.0,22.0,14.0,25.0,27.0,18.0,19.0,FHFHEHAHCFEDCDHFFFHCCCCCCFAFGEAHAFGGEGEGEGFGFAEHDCDFHGAGEBHFHCHBHBEDHDCFCACGBFCDDEHBCEGAFABEBFDEGAFDCACFEFEDEAAGAGAGCBCDFEHAHEHBCBCBFBEEFEHGGGCEFEFEBEAFFBDADB,False +892,15.0,15.0,17.0,14.0,25.0,21.0,15.0,21.0,EGAHHHDHDFEAEDEGGGGAGFHFAFEEEHHBCBGHGBGDFAAEAECEFEDDBFCFCAGFFHFHFHBCFCDHFHCHADBHFGFGBEBHHEEDDCDGBCEEEBGBHEHEDEAFCBCECEBGAAAEDCDCACABEHHCFEFCFBF,False +893,5.0,2.0,1.0,1.0,3.0,2.0,5.0,2.0,BHAHAEEEGFGFACGBDAGAG,True +894,1.0,2.0,2.0,3.0,4.0,6.0,4.0,3.0,FCFCHHEFEFGGGGHDBEBFAFDDE,True +895,12.0,25.0,10.0,17.0,18.0,19.0,18.0,17.0,CECBHFGFGEBBHFEFDBDBABDGAGAEABCBGAGAHCEEHEHEHDDCDBFHFHEDFCFBFBFAGGGGGFGEHBBBHDHBHDEBEFGDCBBBDBGCAHHEGBGBCDFDEEEDEACAFFGBBHFHFDFAFHGBADED,False +896,16.0,8.0,11.0,13.0,10.0,11.0,7.0,7.0,GEDEHEHBBDADFDADCDCAAAHFHFGFECACAEDCDGAEAEBBCBGEACAHDBDEGFHFBCDCFAADACBCHFAFAFEGGDF,False +897,11.0,6.0,9.0,7.0,10.0,14.0,15.0,10.0,HDBFBGCFCGCGBGDEDGHAHGHAAFHFCGBGCAHHGFCFAFEBGHGBDCHCHDEEFEFEAEAEFEFGDGFAFACGEFDAGA,False +898,17.0,13.0,21.0,30.0,28.0,20.0,12.0,19.0,EDDBGCECEDBCBCDHGFECBGBEHHHEHFHDGDHHAFAHCHDBEFDADCDHEEEHEGDGDGFEDCACEDEAEAEFDFDFDADCCACFEFCFEFCBBHCCFEEDHDFGEGAFCFCACABABCGDEDAHEDDDDGDGFHDHDABFCFDFAHEEBEBEHEAA,False +899,3.0,3.0,2.0,3.0,3.0,3.0,8.0,3.0,BCEFGHGHGAGBGBGDFDCHEGEFAADG,False +900,16.0,24.0,17.0,15.0,11.0,13.0,13.0,18.0,DDCDADAECDHHHCHADDHCHCBCADAECGHGEAHFHGBBHDADAEHHFHGACACFCFBEBEDCGCGBBBBGEFFHFBBGCGBABABAHFEFBBECCHGFDFBFAFAHBBEBEACDGDGCBHBGBDB,False +901,25.0,30.0,29.0,16.0,34.0,19.0,24.0,19.0,FFGCECEBBBCDCBFEEEECGCABAFEFGHBDAACECGHDFCHBFBGGGBGHCHCBCECBGBEFDHBHBHCHAHAGABABGEGFCFBEGEBBCBCDHHHCHCHDBDCFCAEDHGAGEBEGEBEDEFFDBDEFBCEFEAGGFGEGFBFHHACACAEAEAEBEHEBAGAEAECGABADDDAECECFAAEDDAGCECBG,False +902,24.0,23.0,19.0,24.0,26.0,27.0,19.0,14.0,FAAAEACAEEEGEDAHEBADAGGHEDCABGFFDFDFEBEBEDEDGAHFDGBCBFDFGECFBFGFBFEFCFEDADBEFEFACACACAHADBBBEHAHBGBFAGBEEGGFGCGCFAFDFEBHGCAAGDGFHFCFCHCDCBFBGBCBEHFHCHCBEDGDACAEBDBHFHEDDDDDEAED,False +903,29.0,29.0,25.0,18.0,19.0,26.0,26.0,24.0,GABBEDADAGFHBHFHGCBCBDADGBGDGHEDBGBGDAEBEAGFGACEBEDADFFFBBBCFCGAFAHEHEHGBAAAAAAGGCCHBGBABHEEFHFHAHFBGCHDHFEBEGEAEDFGCHBHACADBHGDGCEDFFHFEFBCBABAHAEAGGFFCFAHADGDGCBCBCGCGCBCBCFHEHDFFEFHFCFABCHCDCAC,False +904,6.0,3.0,10.0,6.0,5.0,4.0,4.0,1.0,ACGCFCACDCHCDDDEDCGGEFBCBCBFGFEEAEDCAAA,True +905,3.0,18.0,9.0,11.0,14.0,16.0,4.0,13.0,DCFBBCBEBDBFFEFDCGHBHGDCFBFDEHEFBHBFEFHFHFGCAEHFAFBEHEHEHCACHGFDCBEFEHEBDBDBHBDEDEDBCBFB,True +906,16.0,25.0,37.0,22.0,24.0,10.0,28.0,28.0,DFDCDCEAEHCHEACBHBGBHCCGCECADDDDDDCHHHAHCCCGDECECEBECHCFCFBHBACGCBABCBHGEBBBHGHGBCBCDEEAAGAGDHFCCEDEDGDGDGBGHHDFFGEEBFAGHGFCBBGEHHBCBDBABCEAGACACGBEHEHCFDHAHEGGGHGHGACEDECHCGCGCDHFHBEGEDBCGC,False +907,25.0,18.0,28.0,21.0,19.0,32.0,30.0,20.0,GCGCEBHGCGCEDDHHGCCCCGHGHDHEHACGGGBGFGBEACGHGCFDFDCCCHCFDFAFAEAGABACAGACEBHBFGFBFBDHCFAFGFACAGDEHCDBGHAHBBDFDFCFAEBDCGFAHGHGFGFGBADFEFHBDADABBEAFHDDFDFGBGDEDEFAFEFEFGFAFDFEFCACHFHBEEECGCGCAAEAC,False +908,28.0,27.0,16.0,15.0,23.0,29.0,25.0,24.0,FAFEFGFBABHFFBHDCCGAABEBCACAEFFCFAGAEEGEGFGFDFHFHBAGFGBGDHBHBHBCGEGFAAHAHAHAEGEBEAHABCBDFGFGEGBFBHBDBFBFGFGHGHBEBEBDGHGFAFCHADEEECECFBACCBCDDHGGEHEGCAAFAFBDHHHDHDFDADGFAAEAFABEECGHHDBEACB,False +909,22.0,23.0,20.0,21.0,31.0,23.0,29.0,28.0,EAGGGDCHHHHCDDEDBCHAEDGBGAGADBHAFFHGBGBDEGEGHGAGDBEGAGCCHFHFGEGHHEAEBDDDDADHCBBBCACFCGAGECEAEFEGEDDAAEFEHBHBGBFCFCHGBBDBFBFDEAEAEFCDDEGFGFCECAGHGFGFEHHDAFHFHGHGHFHFEEEHAFBBBEAECGCBCBCEEAHACBFDFEHEH,False +910,35.0,20.0,17.0,22.0,15.0,17.0,23.0,20.0,BABABADGDFFFFFADHEEAEHCBGBGDGEGCACHEFAAHAHAHBHGHBABCBCGCFDFAFCFCEAEHEDGFGBAAADBGADADBDBECGGFCBDBHCAADAHAGADCGFGFGCGCEDAAEAHDEDBAGFGBADDDCDHHHCHAHDEAHGFAEAFBDHAGAEHBBGCGA,False +911,20.0,22.0,16.0,16.0,19.0,34.0,24.0,21.0,HHBBFFAHAHEFAFCDBDBDGCEEBFBDCCBCHDFAFDBDBFCFAHGEDBGFFFDFHACEDGDBFBFCECHCHBFAFADAFFFFFFFGFBHGHGHGHAFABACHCFGGGAFHFHGGGGFAFEEGHGEEEGECDGECBCBHDGDGHEHDBAGEBEAEABABFEGACHEBGFAF,False +912,14.0,22.0,22.0,16.0,10.0,16.0,13.0,11.0,GABHDHAHACDCBFFFECHFHEBEGABCEHEBBFBACHCHCACABEFFDBACDHFADAFBFBGGCGCGCHFBFCGDFAFGBCBCBDHDGDCBCBCGDGCGAGABCBCACEDFDEEFBBDDDEDB,False +913,20.0,27.0,29.0,23.0,22.0,31.0,29.0,18.0,GFGEECFDFAGEFHFACDEGCGCGHGHDHDCGCFDBAGAGAGDGHFDFBFGFGAGHDAGAFABDCFFECECEFFDCDCBCGDBABFFHFDDDGACHHDBEBEBFCEEBEHAHECBABGGAGDHDCEEGFCFBDECACAFHFAFACBEAGGGBGBCBHFCFCFCFCHDFAEBBBHBEBECFCHEEGBGBFCDBDBDBHGC,False +914,12.0,9.0,6.0,2.0,6.0,6.0,2.0,13.0,BFBHEHEHBADCHBAGFHFEBHAAACABHBHAAACECBBACGCHFHAHAHEHEFFD,True +915,10.0,12.0,24.0,13.0,16.0,14.0,13.0,16.0,CEBDBDBDCDCDCDBDAHHBFBFCFGFGEDFHCBCFGECFCEBEBHBCCFCFDFEHAFBHAHAHFCACHCECEHACBCHCFEDEAGACDCHCGAHCDEGGHEEFHAGGGECEGEHDGG,False +916,4.0,4.0,9.0,4.0,6.0,12.0,3.0,4.0,CECDADFBACFCFDFBFGFCFGHCCGBEHEHEHEFFCACBEFFFAD,True +917,15.0,18.0,12.0,11.0,16.0,11.0,18.0,15.0,AEAEAEAEAHAHAGEEFHGHBHBEDABABADHGFGDHBCDDFHGBEFFFAFGGHBDFCBEHECECGFHBHEEGDBEGEBBGDCDHDCACGFGHGCABABHFACCCCBGBGBGDGBE,False +918,14.0,16.0,12.0,30.0,16.0,18.0,12.0,16.0,DHDAEBFADADADADADGDFAFHFHDEFGBGBGBGFHCGEHECEAACACGCDDDFEBEBHBFAFHCDDDDFCFDFGHCFDHEFEFDCHBBBHAEDEDBAAHCEFDCDBDFDBEEDBDHEBDHDGFHDHEGGGCB,False +919,5.0,11.0,3.0,9.0,10.0,8.0,8.0,5.0,BFBHEEEBCBHEHGAGAGDDBDEEEHABFCFBAGDCDGDBDGAFEFEFDBDGGFBFBHE,False +920,5.0,0.0,5.0,4.0,1.0,1.0,4.0,2.0,CGAAFADHDCACGCECGDGDHA,True +921,24.0,17.0,18.0,26.0,23.0,31.0,24.0,25.0,EDEDCDADFGBABAGGFCFDFEGCGBHHECEADGDEDFDFDBEGEFCAGFEFEFDHEADHCHAHFHFHEGEDDDDBGEGEFBCDCEAAHDBAGHDHFGGHEHAHAHAHFHFDFBGBHCGAGFEFEFADACAFEBGCCDBEBADAFBGCFAFCHCHAFEFGCGBGCAFABCDAFBFBHDHFHEGDGHFH,False +922,12.0,3.0,17.0,8.0,6.0,8.0,19.0,16.0,GDFCHCHAADGBHCHAFEHCHCBGBCHFACAFADGGGGGGCGCAADHEHECEAEDDCCEGFGFGAGAHHGHGCDADCCHHGCGFHFHGC,True +923,13.0,7.0,15.0,17.0,15.0,11.0,14.0,5.0,GDDDHCCBCDADAEABADADGHFDCCACAEAGGDEEEDFHFBDGCHBFBFDGGBCDDDFCFCFEEGCFEFADADACAGGGGEGCCAEBEHEGEFECE,False +924,19.0,22.0,14.0,20.0,28.0,12.0,19.0,18.0,CGCDHBFBHGEBEADBDGDGDCBCDCHCEBHGEGEHEGDFFCEAEDGCGEGFDEEEEEBABCBCBCBCBGFDFAEAFDHDHEHFDAAHHHHEAEADAFEFEDBABDHEFEAGCBBFHDHBHBGBADHEEDBDEGBAEAGGCGHBEGGAAAEA,False +925,20.0,23.0,18.0,19.0,19.0,27.0,21.0,22.0,FEHEHEGDGCBDBHBEBCAGACHFEFHAHADAFGBGFFEGECEHDGDAHAHEDCCEAGFDFEGCCBGBFBFHDADCBCBFBCCHBHAHBDCECDFHFGFADCFFFFBFADBGGHADFDBBCBGHHHEHEHBAEAEFGBHBHGAGEFEFGFGFDCDFBFACAGAEADGDB,False +926,8.0,4.0,5.0,5.0,6.0,5.0,4.0,8.0,FGFDECECEADFBFBHEHAHADAHAEACGDADHHHBHFACBEGCG,False +927,4.0,9.0,2.0,4.0,9.0,4.0,11.0,2.0,GHGBGDGBGBEAGFGBBBBDDEBGFGEGEDECEAEAGBFCEHFAE,True +928,19.0,13.0,20.0,26.0,25.0,21.0,11.0,20.0,DDDFAGCFCHADFCCECECFBEHDBEBEDEHEHCFAEAEAEFDFBFADAEAEAEADHDFDFGBGBADEDBHCGCFCBEEAEHECFHAGACCCDDEDHHHHAHDDDACGHBACFCFGDEFEBHFHFCDDDHDACECBDHGHEEFGBGFGFEDHFBA,False +929,31.0,26.0,25.0,22.0,30.0,19.0,16.0,16.0,GADBEEEAEAHACCCCFGFEHBGBGCFCFDDADGBAAAFEFAABEHADFDFACAHBHGEFBAAACFCGABEGFABGFGEGFBFBEBFDEDEHGFEECHAHADADADCHEHEBEDABHBEACADBDBDGDGDCDCACHEHGCEHDCEABCFAEDFDGCEBFBAAEHEDEBCBCBCBCBEEAEBCHC,False +930,5.0,6.0,16.0,9.0,2.0,8.0,6.0,8.0,FCFCBBGDGDBABHCHCGEBEDDGACFCFCFCHCGCABHCCCCHFHCAGFHHCAFDDDDD,True +931,13.0,10.0,13.0,5.0,17.0,8.0,8.0,11.0,AEAEAHAEECBHBHGHAEBFCEEAEBEGCHBFBGEGFACADAEGEDBFCCHHBHBHFHCGEGHDDCDCACAEAFBCGCFEFECEA,False +932,13.0,15.0,7.0,16.0,20.0,10.0,5.0,18.0,AEABBCHEBEHEFEDEAFBHBADFHHDBDEHBABABABACDCFEFHFEGGACEDEHEBBAFGHCEDEDBGCHHDBDBEHCHDADGDEDEDHFEEEAHAHFHFHD,False +933,4.0,6.0,3.0,4.0,2.0,6.0,4.0,5.0,AGAGAHBEEDCGBGBCBDFDFDHHAFBFHFCBHF,False +934,5.0,12.0,3.0,2.0,5.0,4.0,9.0,11.0,CEDBABACFFGFAEAGCGBGHGHBHGHEBBHBHGDFHHHHBEBEAGBBBGH,True +935,8.0,6.0,1.0,11.0,7.0,1.0,14.0,7.0,GEBHGHGDBAEEDAGGEGDGBGBHHHHDDAAAAGDGDGDADABCEGEHEDDFGGB,True +936,12.0,13.0,17.0,16.0,15.0,22.0,16.0,19.0,HHEDDDDGDGAFACACHCFEEECACADBGHGFFFFFFEHEHCAGBDFEFDFEFEHEFFBBABFCHEGFGDHBCBCBEEAHCCECDDBFBHCHFHFHDEDGGGDGBGHCBGAFDGDGCAHBCCHGHFHFAA,False +937,3.0,4.0,1.0,4.0,2.0,0.0,0.0,2.0,ADDEDEHBHBACADBB,True +938,5.0,10.0,7.0,7.0,2.0,7.0,13.0,13.0,FCGGGHHAFEFBFBGBABAEGGGGCFCFHBABHHDHDHFHACDBBGHGDGDHCBDHCHGBGDHC,True +939,0.0,2.0,2.0,0.0,2.0,1.0,2.0,1.0,CGEGEBFBHC,True +940,15.0,12.0,17.0,12.0,18.0,16.0,21.0,10.0,DADACBCEGEGCCAHFCDCDAEACDCFGDAEBEBEACABEGGGABACDFDCGGFDDHCGFGEGBCBDEDGHGFEFBFGGCBCEEFAFGFHFAFHGHGCEFEBHBHGEGEGEFAFAHACBHE,False +941,21.0,9.0,18.0,19.0,23.0,21.0,20.0,26.0,EGEDHBHBHGHGHCEAAGBHBDDDGGGDGFGFEFGFGADHEFEAEAFAHAEAHBFECDCAAGDFAFHEHCCDCEFHFHFAEAHACFCFCHCECEHDDGDHDHDADEBHFEGAAEAFBHCCEGGDEDBCHADAHFBFCFCGGEDECFHGAGHECEHFH,False +942,23.0,23.0,25.0,23.0,16.0,18.0,18.0,24.0,CAHDBDHDEGCADHGHGHGHFCDCHCDFGEDEDHDHBHFDFEEADAEABFFGFGACFBBCFCBBFAHCHCEEDCCFHACACABHBFFFDFECACHHEGDGDEDBHBCBHBHADABHBHBCGHACBCBEBABCGEEFEAEAGGCDDDDAGAGAHBHDGBCFGFDCAGACAB,False +943,9.0,5.0,6.0,3.0,2.0,3.0,4.0,6.0,DBDHCFFHCEAEGBGBGAHCHBBAGFCAHAHACADACA,True +944,1.0,5.0,5.0,2.0,2.0,3.0,5.0,5.0,EGGDGHCBBAEGHGCFCFBHBHBHCFCD,True +945,23.0,12.0,17.0,23.0,21.0,25.0,31.0,23.0,AHAHBHBHCHCEDDFCACDCDFGFBHBCCGFGHGAAHDEEGECFAHAHFHDHEADFGCGCGFGEADBEAEBEDDBCBHAAFAFAFDGDHABAEHDHGEEEHDADGFGHGFEFGFCFAFHFEFADGGEGEGECFDHCHDFGHGDGCAAGAGEGFDBGCEBGBGDEDHFFCFGAGDG,False +946,7.0,6.0,9.0,5.0,3.0,13.0,9.0,7.0,BEBECFHFHAHGCAABCCFGBGFFCFGFBFDFGGAGHGFFFFDBCGHHCHCDDADAEAC,False +947,12.0,14.0,22.0,9.0,8.0,15.0,19.0,16.0,GGGGGADFDBBBCHGACAHBFGHGHGFGCCFDACHGHEFFBCBGEGDGFHHHBHDGDCCCCGBFHACACECDCFGBHBHBCEFECHCBCBCHGFGDAAAADAEEFCFCACFFEHB,False +948,23.0,29.0,24.0,18.0,9.0,25.0,25.0,32.0,BBBHGFAEAEBEBCFCFAFAFCFDFBHBGCHFAEGDACAGBHCHFDBCBGGCCBBHHABDCFGHBDCDBDGFBCAFAHHGHFHEHACEGDABGBGHABABGHHHFBFCFHFABAEAGACBCFHHBABCBCBCACFCHGHCHBGBHDDFGAAFFFEDDDGDHDHGHGHGHDHGHGHDCDCGFGFEA,False +949,7.0,6.0,5.0,7.0,7.0,6.0,6.0,12.0,HHCHADDCGBGFFHDHBBCHCHBFADAEAGAFAEAHBHEEEEHHHBGDGEGCDFDF,False +950,24.0,23.0,22.0,11.0,20.0,30.0,30.0,14.0,EHFBFBFBCCFCAAACEGBFAEEBHCHFHEAEAGBGHGHGCGCFEFAFBEAGAEBGDGCGHGHBBGBGBFBFDFECAGGFEBEGCAEBEDGHAFBHBFBDGDGFGDACCGCECACAGFCECHDFBCGCGFFFGFGCBCGABADFBHGGFGDHDEFBHCAAAAAAFFFFFDEEAE,False +951,16.0,19.0,15.0,15.0,20.0,28.0,15.0,17.0,DGGFECEHGHFHCBCEHGDGCBCGCEEFAFAFAHEHFAABHEGDGAGBGEEBHDHBBCBCHFBDBDBHEDFCAEAFFFDFDFAGBCBDECFFFEFDFBFGFGEECECEFEFEDHGCDAHAEABBDGFBFHHBHDAFHFCFAFABA,False +952,9.0,0.0,6.0,3.0,8.0,5.0,2.0,3.0,EFACCCFAAAAHFFFDGAAEAEHGHECECEDECEAD,True +953,2.0,1.0,1.0,1.0,6.0,2.0,3.0,1.0,ECEHDAAGBGEEEEFGF,True +954,11.0,9.0,7.0,13.0,13.0,4.0,8.0,8.0,CADHDHDFDABBEACAFDBBHFHGAGECBGEGEGEBEHEDEAHBGDADADADFDEBEDDCAABHEHCGEGECC,False +955,17.0,19.0,17.0,18.0,12.0,19.0,16.0,32.0,GFGFAAGFGAHADGGHGEBABFEDBHBDFHHHHBGBHDHDEAACBFBFBEAEHCDDGDFHHEDGHGBGBGADHFHDHCCGAEACDCDCAHAHFHFHFHDBDADHCCCHBACACBHFHFEFECACGEBBFDHCHDHBHEFGCECHFFBHBH,False +956,21.0,23.0,17.0,24.0,20.0,16.0,15.0,22.0,DADEHFHDCBCBCAHGBGFDFDGBAFDFDHHFDBDBACACFEHEAEAHAEEBAGCHCFCFAHAGDGDADADHHGHGECCFCFGFCHAHGDGBCCHADBDEAHGCFBHBHBHEEEEEHEBEAEGDBBFBHHCDCEBBBDBDBAADGFABADFEEGEDDB,False +957,10.0,10.0,8.0,10.0,12.0,10.0,10.0,2.0,FGFBFDFCGGFGABBBDGAAAFHFDGDBDGDEDECECECECGBAEHECGDACEBGBDFCAEAFFEDEBABAE,False +958,23.0,37.0,29.0,27.0,20.0,20.0,23.0,19.0,ADBDBAFABHBADGGCCCHFHGBBDDCACACBBAGDHDHCHFECBHFEGEBEDCCFEDEFBFBCBCBHEHBGDCDGBGAGAFFGCGEGAADACADBGFEDGBGFDBHBCAHEEFFDCDADBDBACDCDCDBHBHFEFHFDBGBGEFHFHBACECEDEBCBCBCGCGBBACAGEFBFBABGDGDHEHEGBCDCBHEAAA,False +959,12.0,18.0,18.0,8.0,12.0,10.0,17.0,15.0,BEBEBGBGBHBCBCECGCGCDCFGGHGBCHEACCCEFGAAAEHBHEHBGBHAEABHGFCFCDCEABACAHEHCGCHFEAEGDBDHDCGFDCDAHBHGFDFGGGHFBBBAF,False +960,6.0,8.0,14.0,11.0,10.0,8.0,6.0,15.0,EADADHGFDEEHFHDHBHBHCECDFDBDECHFFAFGFBEDECBCECHHHHGCGDGDHCCCCCCEEDHHAHABCGFABB,False +961,20.0,29.0,25.0,20.0,25.0,26.0,26.0,18.0,BHBEFEABGFAEGDGDFFBDHDGBGBFFFHEEEEEDFAFADABGGCGCBCBAFCFABCCHEHGDDEDEGFFAAEEEEAGCGAGHGFDCCBCHGACACEDHGHGAFBFBFAHEBEBEDGBHCCEAEADDDHDCBCFHAHCHBHBFBFBGGGBHECGFGECBCBCDHDBBFDCACACBFGFGEGCDEBFBF,False +962,27.0,19.0,27.0,18.0,20.0,32.0,29.0,28.0,GEGECAFAHHHHEAEBDBDCHHGHFEFHDBFAFBFDGDBCBCGHGHFCFCFCFDEGADHHCCADADAGEHEHGACCHGHBHEHCHCHFECGCFAFBFAFGFBCAEFCDHAGFBFHGEGAAHGFGEDEACDCFHDDCDCFCHCGCEDGHBDAAFAGBFBFHEGAFACADEFEBEGGGCGCBBFBFGAGAGAFABAGFBEHF,False +963,18.0,20.0,27.0,19.0,14.0,17.0,15.0,25.0,FFACCGCGCDDHCHCDGGGEHFBCBHFCAAAAHAGFGDGAGDGHFBDEDHCBCACACGCGAFEBBCECEAEHEHBBCHHHHAACDCDBDFCFBFBHCHBHDGCEEEHEDGBBBFEFHFHDCDBDADAHFBCBABDCEAHHDACFCGHBHFHDCFE,False +964,12.0,10.0,8.0,9.0,12.0,10.0,10.0,9.0,FGFAEAEAGADFEECEHBBBAHAEBECECAGGHBAAGEHFHDHAEFDFECDCBFBFBABDDFDGGFGCCCEHAHBHGDGD,False +965,17.0,22.0,24.0,31.0,26.0,22.0,22.0,27.0,CGCEHFCFCEBDBDBEHEHGHGHFABABHEHFBEBGHDHDFCBDBEBGGCHCFDFHEHDHDGDFFBCAHAHGEEFHBHBEBADFFAFAHDHGAGAHEDDHDEBEFEBEFHFHACADDDFDEEEECCCDAGADBGAGFEHBGGHDCCCDEDGHCECDDABFBEBCGEGCGCFCDCAAEDCBGHGDFDGDCDF,False +966,27.0,18.0,26.0,14.0,26.0,27.0,37.0,24.0,AACDCHCFGHAHAGAGACFHEHABFHFAGHBCBDBFBFBABFHHHFHFCEDEFACHCECFGFEFECGDGHGCGFGEHECDCBCBGBECEDFAEECAGGFAFBHEFDGBGEGHFEEGEHCGEGDGDGDFCCCCHBAEACHGHGAGHGAGEHEGEGBCAGGGFABHDADADAGAFHBEDCFAEECFGFGFGCGABEFGABA,False +967,19.0,30.0,23.0,20.0,26.0,19.0,25.0,21.0,BBABCBGGAGFDFGHDHEGBGCGBBAFDCBCEFHDCDFBCBGEFBHBEEEEEBADAHAHBGGGEDBFBHCCCECBGHDHDFGBDCDFBEHECGBGBGFCFAHEHDGEGEFDFDECCCHCHEGEGHGBCEAGABEBABABABADADABAEADCCEFBABFECDFHFHCHFEFCGGEHEHGDADH,False +968,22.0,15.0,29.0,26.0,37.0,20.0,22.0,24.0,AEGBABEFGGEGDHDHAHEFECEFACEEACHBECFBABCDCACAHGHDEEFECECDAAAEHGHGHDHDFGFHCADFDBDEDEAEDEDEDEDGGECEABBGFADADEHGHFECBCAEAEGECECAGDBEGAACCCCCCBHEGECDCDFHFHFHFHFCGEGHBDFEBBBGECHDEFEHHGDADCGHGDDCEFHFCFC,False +969,16.0,6.0,14.0,15.0,9.0,8.0,13.0,13.0,HHHHFEFDDCAHGGEGDGDCBBHCCDADGGHAAADADFDFDGDGDGABEBAFABECDHAAFAFEFGDGCHEHCDCGCEEHHHAEACCCCBCGAA,False +970,21.0,25.0,9.0,17.0,8.0,13.0,18.0,16.0,GBGHGACACAFHFBCADGGGFGFGAGAGBBDBGCHHEHEBFDEABGDGDGBHBCDFFFFHFHAHBDACAHDHCCGAEADBHBDFABABABEBEAECGGBHBHDFBBBBAFDDAGBHHABDDADADBE,False +971,9.0,10.0,11.0,9.0,15.0,9.0,14.0,12.0,EAEDFCFBFBAGHGHGDGBHBGFHEHCFAFAGHECGCHCADAHCEGDGCGBBBBDBDEGFGCCFHEEEHEDEAEDBCGHGCADHEFEAE,False +972,18.0,16.0,12.0,13.0,15.0,19.0,12.0,21.0,BEHFBBABAHGEEAEAFAFCDEHFHAHCGCFBEAAFGCABHHFHFHCHBGADCDHDHCHCEEAGBFDFGADFFFFBFBGDGAGAEADHDHDAEEEBCBCBHBDEEHGFGFBFBDEHCHGHAHFCAD,False +973,27.0,25.0,26.0,28.0,24.0,17.0,20.0,27.0,HCHEFEACGCFDFGCBCHADFCFBADCGHBHCDDDCBAAHAEEDADGDGHGHGHGDAAEBEHAHGDADADEBEHHCEBADAHHHHCHCAAAHBFBDCGBFCHEEFBFBFHAEADDBFBFBDGDEHEHBHGCGAHACECAFBFBEEEBECEFDCCABDBDEDEGAGADEDEDCFBBACHGGFGBGCGDADCHCBC,False +974,2.0,9.0,5.0,14.0,10.0,16.0,13.0,8.0,HBEGFBDBDHEEFHFEGDBFBFBGHFAFDFGFCFDBDBDHDHBGGCFFEGEGECADGFECEHFGDCDHDEDGFGFGD,True +975,7.0,10.0,11.0,8.0,6.0,8.0,11.0,11.0,CECFCDCHGGGGHGAFCECEAECDCGHHBADHDHDBDBFBFDAHGBBBBBBGCFFFAAEHDFCHGAGHCHGE,False +976,22.0,16.0,20.0,24.0,18.0,27.0,21.0,14.0,GDBDHEGEBFHFHDDCFCDAAGEFBFEDBAHGBGBGDFEBBADGHGFABAFAFDCDCBCAHADDDCAHECCDAAFAFGHCCECFGECECEFDHCHAHGBGBGDECECECEAEAEBFBFGHGHAADDFDBDGAFCFBHACAEEFGFAFDFDFGFGDCDGGFFF,False +977,16.0,17.0,23.0,22.0,27.0,15.0,19.0,22.0,EEGGFDFHCHEEAEDEHEHGCEFGBEBEBHBDDCBAHAHDGDAEGEGDHFECBDDDHDCGCFAAAAAFCEHBBEECEFDFDBDBCCCCEFEGAFFCFCFCEBEAHAHAHAGGHGHCHCBGEDBDGEEHCDGHBCBDAHFHBHFGGDHDEDAGECECBCDCG,False +978,5.0,8.0,11.0,18.0,14.0,13.0,11.0,18.0,HFHDBAGHGEFEHCGGEGDAAFHFEFEFDHDGCECHHEHEDEDHGHDFBFCDHHHAHEHBCBCBCDCDGDECEDGDEBFGDCDEBGHFBFDCDFHFDA,False +979,22.0,10.0,19.0,14.0,19.0,26.0,19.0,18.0,HBGDGHGCGBGEFEAEFBDEHEAAHGGGGHDHDHFGEABAFAHEHCACFFDFDFAFECGCDCDCDCFCHCFCHAHFDCBGAGDEHBGEAFAHAHEFAGHEAGACEEEFFFFEFHFBFCFBACGCAFAFCBEFEGEFCGBDDDCAAAH,False +980,9.0,10.0,16.0,13.0,13.0,13.0,17.0,6.0,CDCEBDGFGFACEBDHFCEHACADBDBHBCBGACCECEFEFGFGACHCACDEEGGGEGEGDGCFFFGFDBDFGGAGAHACDDDDGEGFCFCEHBBEB,False +981,19.0,23.0,15.0,12.0,16.0,18.0,17.0,17.0,ECEDHFHFHFAGAHBHDAEFGFBEHGBGBCBHBCEDGDCBHEAGADEGHFHDBBABEBAGAGCCDADHDCGBBBEGAGAGEBBBGFGFCCBFBFEGHAEGHFCFCFCACEDHDAAAAAHDBFFHFEFCBCBEBEFHA,False +982,21.0,16.0,13.0,14.0,20.0,12.0,19.0,12.0,EBEBGBGDGEGECHCHFAAEHBCAEBHBECECACGCDCDCDBABAFABGHGHAAEAHABDEDEFHFGBCDAEAGFGECDHGFGDDDEHAGGGEGBCFDFAFBEGECEHAFDFGABADAGAEBHFAEB,False +983,22.0,16.0,20.0,28.0,16.0,18.0,28.0,14.0,CGCGBDCDCGHACGFDFDGDBDCFEFEFADAECBDDDEAEAEAHAHABGDFAAGFGFGCAAGEDEGFDFDCGBGAGBGHHHGABCBDBDFDFCFDFGCAHAGACABAFEFAGEEDEHBCCHEGBBBDBDHGEDCHCEFAHHGCDHGGFGDGDGDBEGACDCD,False +984,26.0,22.0,19.0,22.0,24.0,27.0,32.0,24.0,ADHHEFAFADABADAFABCGCGAGFGFEDADABEFHFHGHDFGEGADCCFHHHGHGEFCFCEBDGEFEFEGAFBFBFAHGBEBEAGDFAHABAEGHGCECEHBHBDCFFHBAAGAEAGBCCDCDHDHDBDBGBEDDDCBBFBGEDFDHGEGEGEAFAGGBGBHEGBGFGDECHFAFEHHFCGCGEGCCHCHAAFDG,False +985,7.0,9.0,7.0,9.0,13.0,11.0,7.0,5.0,FCBCHEDFAFHEGBGFAEAEAEAFGDGDBDBABAFGEGDCHCHEEBFCEEHEBEDEFFDFGBDBCCFD,False +986,8.0,13.0,17.0,13.0,13.0,11.0,14.0,10.0,HGEDFDFDFDHDHDHDBFEFAGAEBEDGDHHFBBEEABBBFBHGHCCBCEEGECFBACDCDAAGCFCGBGFFEAGDGHCCDGEGCGCGCHCECBCACEB,False +987,20.0,12.0,18.0,25.0,18.0,18.0,21.0,30.0,AAADFHFAADFECBCECEHEHADCDGDGDCFHFHGCGCGFGFCFHDCAHEEGDGCECHCHEBFBHGHGEFHBHFGDADEDHDAFADEHBBBEGEFHADFDBCGDHHGHGHGDGDHDGDFCFEGGFGCAAEAEBHAHADBHEAADHDCECHDADHCHBHFHAB,False +988,20.0,13.0,12.0,16.0,10.0,14.0,25.0,12.0,BBBCHGHGAGFGHGDCACHCHCAAAAAAEHBDBAFDGDGDFCGGEBAFDEDEHEDGDEDADABCBFDGAGAGHGAEDBGGGGDGBFBHAAGBGHDFEFGAEECCGFFBFGFGHCHAFFCACD,False +989,12.0,14.0,12.0,10.0,10.0,5.0,11.0,8.0,AEFEBABAHACGFBABGBGDEDGDEBBCBCHCECBCACDCGHGHGEACFCBBBEFGDDDCDBDADGEHAACHEGAGFBEHAH,False +990,22.0,22.0,18.0,21.0,13.0,23.0,11.0,18.0,AHAHEFFDDCDFGHDFDECHDHABEBCBCEAFBGGGGFCHCBCHHBEDFAFABCHCBCBCBABDDGHHDBFGEEDADFECGBAECEADADADAFFDFBFBFBFAHDFDBHBDEAEFHFGAHAHAHACCBBABGCGCFHFAFDFDEBCA,False +991,10.0,6.0,7.0,9.0,6.0,4.0,5.0,5.0,FDCBCGFHFHBBBABGDFDAGACACEEECAHDDGDEAAADADAECECHDBGH,False +992,9.0,13.0,4.0,15.0,7.0,15.0,17.0,13.0,DEAHFHGHBEGEBBGFFFAFDFDHDGDGHGHFHFDDDCEGBACGDBDGDEHEHGHGBGBGHFBABABFFFAGADHDGGGHFACBFEDDBCAFB,False +993,1.0,1.0,4.0,3.0,4.0,6.0,1.0,3.0,EFEFEFAFCEGDFHHHDFCBCDC,True +994,16.0,14.0,21.0,15.0,11.0,19.0,16.0,24.0,AHACCCDCAAFBFEFBDBAAGAHHCHDHEHAHEHEBGAGAFHFCGCEFEFEDACHCHCGGGFDFCHCDDDHDHAECHGBGBEHCFBDBGGFHFGBAFHFCDADCFCBCBCEHAHFHBCEGGGFAHBHDCDFHFGDB,False +995,7.0,6.0,13.0,6.0,12.0,13.0,4.0,9.0,CEAFHCHFHECCHEACFCFGGAGFCHCHFAFEDHHCECFBDBDGECHDFEEEEEEBABACFCFDFDFBAB,True +996,4.0,9.0,13.0,8.0,5.0,3.0,3.0,5.0,AGAEADDCACBCBCDCDEHECCFHEDBCBCDDDFEBHBHCCCBBFHGCGB,True +997,3.0,1.0,1.0,6.0,4.0,5.0,7.0,3.0,DDDFHEHCGFGFGFGEDAGAEHFDEDBGAG,True +998,18.0,17.0,15.0,15.0,11.0,15.0,12.0,20.0,EBCFCHHAACHCHCHGBCBCBCHDADAFAFEFDFDGHGHCBCFFHCACDFAFAHAEAEAEFEBCHAFBHBFGAEDBDHDHFBCDEAGABBHGADDBDBDHHHEBAGCEEHFHBGGDGFGAGDB,False +999,6.0,13.0,8.0,13.0,6.0,19.0,12.0,12.0,GDGCGCHCAFGFEFBFDEDHFBFBDBGFDADBFBACGBGDGEFBHHHHBDAFGFGBGHCFFECEFEFBAHFDFBFDAHCHDHCHDFDGB,False diff --git a/tests/results/nb_gm_002_2back_240trials.csv b/tests/results/nb_gm_002_2back_240trials.csv new file mode 100644 index 0000000..1c50201 --- /dev/null +++ b/tests/results/nb_gm_002_2back_240trials.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,ralph_skewed +0,30.0,39.0,31.0,30.0,32.0,24.0,27.0,27.0,False +1,33.0,23.0,27.0,32.0,37.0,34.0,25.0,29.0,False +2,31.0,20.0,37.0,28.0,31.0,32.0,26.0,35.0,False +3,27.0,32.0,39.0,24.0,25.0,34.0,35.0,24.0,False +4,34.0,24.0,38.0,28.0,31.0,29.0,28.0,28.0,False +5,29.0,24.0,36.0,31.0,32.0,32.0,31.0,25.0,False +6,25.0,38.0,28.0,30.0,33.0,30.0,26.0,30.0,False +7,27.0,30.0,30.0,29.0,32.0,26.0,33.0,33.0,False +8,24.0,36.0,32.0,23.0,30.0,29.0,35.0,31.0,False +9,35.0,34.0,30.0,29.0,35.0,26.0,23.0,28.0,False +10,30.0,25.0,33.0,31.0,27.0,37.0,30.0,27.0,False +11,28.0,28.0,29.0,26.0,28.0,27.0,34.0,40.0,False +12,35.0,27.0,30.0,29.0,26.0,30.0,36.0,27.0,False +13,38.0,27.0,31.0,27.0,34.0,23.0,27.0,33.0,False +14,29.0,30.0,28.0,35.0,19.0,30.0,37.0,32.0,False 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+9,11.0,23.0,19.0,24.0,13.0,20.0,28.0,13.0,DFDDFDGFDGCDFFDFEDCCDEGDAHEEDGGGGDAGHFBHFGEDAFGCHGFDBCDBDEBCHDEBGEAFBCHEFEAFBHFCCGEDGADGBCBCDACGCCGFAGBBDCGDBBBEBBECHACFAGFBGABCBBGFHHFHHFGHGGDGGBGBCDB,False +10,10.0,15.0,13.0,9.0,5.0,13.0,10.0,23.0,CAHCFDCFBGFGCFHBHAGHABAAHGFBAFDFBDBHDHCBGEFGDCBDHDEABHHHHGCFCEFCDHCFHBHHGHHGFHGBBABCABCABHEHEFHDCH,False +11,29.0,21.0,32.0,27.0,25.0,25.0,8.0,18.0,HEFAEFGCBEBDCBEADAADADCADABDHHFFEDFBCHACAAFBAFDAFDBCCCFDCEACAACEABFDCFDCFHHFBHDEFDAFCABGAEFDCDCCBCCDCDFAEFDCGCCECCBCBHDEGACBAHBEBEEFDBDHAFHAEAEECEGGHDBHDHCDEADEAHEHFEBFCBAHBHDEGAEFFCFCG,False +12,28.0,27.0,32.0,14.0,15.0,33.0,26.0,13.0,FFFAAFBAHCHHDHGCBBCEBFDGEGBFAACBACBACBAGBGBAGFFGFAHDGHEEFCAAHAHHECFBBFACFACAACDBCAEAHDFHFFCFFEFCAFBEFBFCBCABDBGGFECFGCBCDGGBGFDGDABBCCBEFBEFBAFDACGCCEHGAFCABDGEDFFDCFDGFGGCGGEEGCBGAAGCCCHC,False +13,29.0,16.0,17.0,15.0,16.0,11.0,15.0,11.0,CBECBEFBDDCDCAACAABFAGFEGACCECBEHBEGADFADFBBABCAHCABAABHEEEACEHHAGHABACGDHGDFGCHGCAGDAFAAFCCFEAEBAEDFDDGEABHAGAAGDGBAEDHHGABFEGDCD,False +14,17.0,24.0,25.0,11.0,18.0,20.0,15.0,30.0,DDCDHHAABGECDACBCCFHGEDGAHBABBHFBFFBCFHCHECHECACABHHBHEBHBHDCHCFBAHBFHBEBEDCEDEABCHCHFCHCAFBFBBHGEHGEHGHFCHACHCGGCGCDECFEGHEDFBAFGEFDAAHAHHGFHFABGEBGABGFFEFCEBC,False +15,8.0,6.0,1.0,3.0,4.0,2.0,2.0,6.0,EHBEDEHGEGFABBADBAHCAHAABDAHHABF,True +16,20.0,17.0,20.0,17.0,21.0,21.0,26.0,21.0,DEHCHAEHFEDFDHFCHGCGGCGAFBDDBDCFGEFGEFCEFHDHEFFAGDGDEGAHGFECFACFEEHBEHBGHBGHBGCECEDAHHBGFCCCADHAGHDEDBADGHEBDCHCCFAGEAFAABGABAHBAHBGHCACBEFEGAEFCECBGFDGFDGAGBAGBFG,False +17,12.0,3.0,7.0,9.0,7.0,12.0,9.0,8.0,ADGAGCADCFDFHEFDGHCEHAGGCDAHDCHDAHAFDAFEGFACFECFEBFGBAGAFFAEBDEHGHF,False +18,18.0,19.0,24.0,16.0,21.0,13.0,23.0,20.0,GGEGFBDFGDGEDAHGFBGHAGCDGCAAAHACECDECEBBEDEEDECDFDHBCCDHBHHACBACFHEAEEGHEGDEGAHBAFBEEHCBHCBGGFCGECGECBCAFCGHCBHFHHFHDGGAAEBFCBFDBCBECDCADCACGBHGEHGBFGADHA,False +19,10.0,14.0,15.0,8.0,25.0,14.0,11.0,20.0,EEEEBEEFHEHEEFEEGHEAFFAFHACGDCDDCFDCBDCBFFBCEAHEAHGCGGHGCHEEAEAHEAHEHHCCFGHABHGFGCHGCFDFHEHBBBDFBFBCEAEBHCDGCEEEHBBHB,False +20,16.0,9.0,19.0,17.0,10.0,22.0,10.0,24.0,HFGDDAFEAFEDCGHAADEHDBHAHDCGBAHBECEFFFFFEFEEDHEDCACEGHBGCFGAGGABDHFCHFCHCCDCFHHADFCFFCFFCBFCDHHHHDFFGHHDACDAFDACDCBHCHHAGHABHAB,False +21,6.0,10.0,3.0,4.0,7.0,3.0,3.0,4.0,EABBAEFHEFABAACHDCDDEFBEGHEGBDABHBBCBGEB,True +22,6.0,11.0,12.0,6.0,9.0,6.0,9.0,10.0,AEDBCDECBCHBCBBGFBGFHGEHACHAGAEFBDAECHCFHFDCCECGBCGECGAHGBHBHEBHDFGDE,False +23,11.0,8.0,12.0,13.0,7.0,5.0,13.0,9.0,EAAGACDACDHEEGGGGGBEGEABEAHGCHCCAFCFFGDHGDGCBGBDDEAFAADCDDCDDHBCGBCAFCBDDHHBHH,False +24,36.0,26.0,18.0,26.0,33.0,19.0,21.0,15.0,GBCHFHAAHAFFGBBEFBCFAEFDFGEGEEBECBEBBABBAEBEEAEEABGDBADBACFFBEFCECGACFADABCFDCDBCBBHDHHACGGEHDEGDEGAHAAFAAEDCCHHDDGDDBDGBDBDDCDAGAAFHEDHGDACDACDBGEEACGAEEBEHAFHBGAAAAAAAEEFBEDCDAEEEFGEGGHGFEAFED,False +25,11.0,17.0,16.0,9.0,15.0,15.0,6.0,9.0,CEEFABDBGDBFDFFDGADECBFCBCCACFABEABFABEGBEHBAHEAHEAECCFFCHDCBBBFGBAGCDFHHFBDFDCCHHEHAEBEGCCBFEECEF,False +26,8.0,5.0,15.0,9.0,10.0,7.0,11.0,5.0,ECAGCHDBBDCCDCGHBBEEFDHFEEEHBHGADADGFDEFGAFGAFCCCCCACCDCDGGECGECGEAGFA,False +27,9.0,11.0,8.0,5.0,8.0,4.0,2.0,4.0,FCAFDBEDBABAABAEEAEHDBHCEHCDBCFBABEEGECGBDABFCCAHCB,True +28,6.0,8.0,11.0,7.0,10.0,5.0,9.0,9.0,CFBCBCCBACBEHBEGCADHDGFEGFHGHDAFBAFBEDCDGCHGAACHCHBCEEEEDHEDGEGGH,False +29,24.0,16.0,18.0,25.0,13.0,19.0,26.0,18.0,HEFHCDEGDHFBACGGDEHDGHDGFDEAHFDHGBHEBGEGADFFGCCGDHFBFABDACDABAGFGDAGDAGCAFFAGHHCDHCHACEDDAFDCCDCAECAEDGEDGAFGFCGFAGBBGFBDBBAABAAGADGAFCHBEEGHBGCBFCGFAHHCHDBDDE,False +30,6.0,5.0,2.0,9.0,2.0,4.0,3.0,8.0,DADBAFBDFHDHHBAHEADGFBHFGHEAHDHBDGDCADC,True +31,19.0,18.0,16.0,13.0,19.0,13.0,14.0,15.0,FCHGCAEHAEBDEBABAABHAFEBDCBDCBHCGEAGEFBAFCCECCBCFHEHGEGAEDAECBECEAFEBDHBDEAGFGHDGCDGADFAHGCFCBFDEHEGCEABFADHAFHGBHABHBHDAEBGDFG,False +32,7.0,12.0,12.0,10.0,7.0,5.0,5.0,9.0,EBDGBGBBDCBACGHBDAAHEBGCBFHBFGAFEHFCCCHDCHDCHDAHDCDDEBDEAFECBAHBECC,False +33,1.0,4.0,8.0,1.0,4.0,4.0,5.0,3.0,GAECEGFBHFGHBGCBFCECCECCBCHDGF,True +34,5.0,4.0,6.0,9.0,13.0,13.0,5.0,7.0,CHHEFFDFFDFFDFDGGDFGDHCEAEAHEAFEBFCFEEFEECAECHCHFDEBDBGEGABDEH,True +35,3.0,2.0,3.0,3.0,5.0,4.0,0.0,6.0,CBDEEHHEAHCAEBDFADFHFCHFEH,True +36,13.0,2.0,13.0,8.0,7.0,6.0,16.0,9.0,DEGDECDHGAHGEDGEGACAFCADGACGACHFDACHCCHCEECGHDHBEGGGGCADCAFAGFGGBAGCAHFHFA,True +37,18.0,19.0,17.0,17.0,13.0,17.0,15.0,23.0,HBCABCGHCEEADEDCEDGAGFFFHDFADHHBHHGCHFHHAGHEHEBBBDEFECFEBHCDAADFGDFHDCDCCDCCFACAACHGGBGGBFBCFBFFCFGEDABDBBDAAGAABACBEGBAHAHHFGEDGHDHHEBHBHF,False +38,4.0,6.0,5.0,9.0,6.0,4.0,4.0,6.0,AGDAGHABHCEEFBEFDEHDBHDECDFCDBHDEGBBGCCADFDH,False +39,3.0,5.0,6.0,8.0,8.0,2.0,8.0,6.0,DCEDEEGEEGAAFEHFGHDGDBHDBGBBGECECDGHBGCDDCHCAH,False +40,0.0,0.0,1.0,3.0,1.0,3.0,5.0,1.0,GDGGDCEHFGFDGF,True +41,20.0,19.0,22.0,21.0,30.0,22.0,10.0,26.0,BADBABGCFGFDDDADEFHAAHAAHEAHBBHECFGFDEHDCDBBBHGEDEECCDCCDGCHHBGHCHACFDCFCFEDFEDAHHHBHAECABDABAAEHFEADCFEBFAGFGEABECFEFFECEEFEHFEHEEHDHDCHBBHBDHCEHCDHBDCFAEFAGHEGECBCFEEFE,False +42,3.0,7.0,4.0,4.0,5.0,2.0,5.0,3.0,EBBEAEEHDCHDCGDGGBACBEHBDGBAFBFCG,False +43,21.0,15.0,21.0,27.0,18.0,33.0,14.0,23.0,DDDDDDBCGFEFFABFDHDAGCEFHHACHGBHGBEFEHFEHFCFFCHDGHDFHDAGFECCCAAEAAGHGDFCHFCHBBBFABDEFDFFBBDBAAFDAFAGHACHACEFFEFDHABCAFGDFEDCGACFADFDDFBHFAFFBEHBEHFCHEADEGHEGCDGHDHDEECCFCCD,False +44,27.0,34.0,20.0,19.0,15.0,29.0,27.0,26.0,FGCFGADGADGDDBDBAFGAFDHHHAFBAEEAGGBDBFCEFAHFAHFAECDCBBCGBHAFHABHDCHAHHGBCGECFDCEHCFBCHBGHCABFBCFBEHBECBAHBGDECHFDFBDEAFBBGECGEBBHDBHDBEABEBFCDFHHFGHFAFFGCACFGDGGHGAABCDBHBGGBGGFHGHGGBEADABFABAAFAFF,False +45,15.0,12.0,15.0,7.0,7.0,15.0,11.0,5.0,CAFCDGCFACFCCFACGBBGCAEAEGAHFADBCHACHFCFBEFGEGBDGBDGBEGEHAEFGBFCDFBFBHACAFCAFGABDAFACDB,False +46,12.0,10.0,7.0,5.0,4.0,11.0,11.0,13.0,ECFFHGFGGFCGACGFGGAHFABBHDEDCHABFBHGAHGAHCAHDABDFHDFGCHGBEABAHEHBFHBFCBAA,False +47,15.0,6.0,13.0,11.0,17.0,21.0,13.0,9.0,EDCEFAEFAFFAGHCFCEEAFGFFHFDECECCEGCDGHDGHDGHACFFCFFCDFEHEEFEEGHEDAFBGEAAHAAGCABAEFAFDABGFCFHCDEDBABFGBGGD,False +48,11.0,17.0,17.0,9.0,17.0,17.0,13.0,15.0,GAFGHHGCHBCACCFBCFHHECHBHAFHEEGBAFCAGHGEFGEDGFCBBEBGABCFDCFDCFDBEEEGAAHDAEDFECBGCBHDBFEGHHBFGBFEBFCBCCHEFAEDAEDCEFHB,False +49,13.0,16.0,15.0,12.0,16.0,9.0,12.0,15.0,BGCBAEBCDBEDBECBDCBABDCDFCDBCEGDABDFFEHCEDGECHACHEBDECDGHFFHFHEAHAHHEFFBAGAGHCHCCHGCEEAAAAGEEGDEGBFGBAGBHHBH,False +50,13.0,6.0,16.0,14.0,12.0,13.0,9.0,12.0,DAEAAGAAGCHCCHDFHEFCCBEGFEGFHAHEAGBGCBFCBFCDACDAFDCHECEBFBAFCFFDEHAGHDEFDGCDECEHCHDGADEHHFADCDD,False +51,22.0,27.0,26.0,19.0,24.0,22.0,28.0,20.0,FDCGDAACFACHGCDGEBFCBDCBGBEGBEGAGGFGGCHGDHGDCAACHADHCFHAAEEBBCBCCBAEDAGBFGAFGEGGDGHCEEEDEHCBBCDECEBGEFCCHCFBCFBHFEABEBDEDHABHDBFFFCEFCEDHFFHBFABHAGGECAEADBGGEGAABHAGHAGEFGBFBFHHDHBEGBFCCDD,False +52,19.0,24.0,24.0,17.0,11.0,20.0,12.0,18.0,FBDFCFECGDCFBBFHBFHBAHECHAAHAFCAHCHCFBDFCDHCDBDDBAGAAGAGHFGBDABCFEEAHHGDHBDCCGCCDAEBAEFEBCHBHECHDABFFBHECFDCBDBFDGGDBFABGHBGFCFCBDCBACBFGHEACEACA,False +53,11.0,13.0,7.0,11.0,11.0,7.0,5.0,12.0,HABDABEADFFDABBHBEDAEDACBEHBEGBDDEAAHAHGBHBDEBAEDECCHFDHFGHFGHFDCCEBHEBHGCACF,False +54,11.0,20.0,14.0,17.0,12.0,15.0,15.0,22.0,DFABFDGCDCDDCBHCBECBDHHHBEFBGFEGHGFHEFEAFAHDBHDGDGEDFBAFBGFBGAGGHHCHHEDBDDBCFFCGFCHEEECDDADHBHHCDHCBHFAEGBCBBAHBAGEFGAHABHCBHG,False +55,17.0,24.0,24.0,12.0,23.0,20.0,17.0,26.0,GAECBGBFHAHHEFEGCGFBGBCHHADCACHBGGBHBAHBAEFAFGGFBCCAFCFHCGHCFHCBEFBEFBCHBGFECFGDHBEHCCACGFHEDAEBAEDDEDCEHBEBBEGEEHHACHECBDFFDFADFAEFHCFHCBECDEHDEHCBAGBAGADGBCBHHEH,False +56,17.0,25.0,29.0,22.0,21.0,19.0,27.0,22.0,FFFFFGGHDEHDFGAFGEEAFEGCEADDBBDHDCHECDGCDAAFCDHBGCBGBBECCDCCDAHGBHCBGCHCCEFEGFAABBEHFEHBCGFHGCHBDHCDHCFBDEBEABEDBCDGCHCCFGCFDAGGBGBBCBFABFEGGADGHEGHEDFBBCBCGACDAEEABDADGGEGHEGCCHHAHH,False +57,12.0,11.0,4.0,15.0,9.0,3.0,6.0,8.0,HABCEHAECBEDEDDHBDGAAFHAGCBGBEAAABADEADGHDFBAFBDEBEEBGDCDDGDDHDAHDBH,True +58,9.0,8.0,9.0,9.0,4.0,9.0,12.0,13.0,CAGCGGCBAHDEFDHHGHDFDBFBBFGAFEBFECHABGGDGDEGDHGBHADGFDCACAACHBFHFGHCHHCHA,False +59,15.0,19.0,20.0,23.0,14.0,16.0,21.0,18.0,GDGGBGGCFGABBABFGEFGCDDCFBCDBEBACHABGEBCDCCDFDDFDAACEBCEGGGFHHFDHGGHFGADHFHHGDHDFFGHGGHDEBDCAACGACFADDHDDCBDBBFEBHDDHFCEGBEHCABEAHEAHEFCCHBAEBCEDC,False +60,9.0,8.0,2.0,6.0,8.0,11.0,5.0,10.0,FEBDCDFHFEHFEHEGHBHFBHFEDCHBBBAGEAGEAGHADABFHFFDBFAEFADAAHG,False +61,26.0,25.0,20.0,16.0,13.0,13.0,17.0,12.0,CBACHGCFDHEBHBBEBBFAHCCEAEEABDDBDGEGADGHDAHEABBBEFCFFDEFDAGDADBBHGGCEGBAADABCHGCHGBDBBGCBGCHFAEFCHFBFDDCAACHACFACAACABFEBFAAEGGCGBCGBAGBDDACAA,False +62,9.0,9.0,5.0,7.0,5.0,5.0,11.0,6.0,FAADDAGBGGBGBCHBCAGEADACGAHGACFECDABBFEFDGGDFGHBGHDEHBEHB,False +63,7.0,8.0,8.0,6.0,13.0,12.0,11.0,4.0,GGBDGFEGCEGCECHDCFGFGABGFEHFCGGBHFBHEGEEAEEAFEDBCFBDFDEADACBABFACFEEF,False +64,20.0,11.0,23.0,13.0,16.0,11.0,12.0,18.0,AEDAHACHEFAEFAHCAEDAEDCBAGGCBGFBCHCHFCEACHCEHCFHCEAEAAEAHCAGBDCDHCEHEGBFCHHCGHFBHFAAGEADHBDCADCFDGFDCHDCBGCGAAHCGFGDEBDEBECB,False +65,19.0,12.0,22.0,18.0,18.0,14.0,20.0,17.0,CCDCCAFHAECADDGDGACGADGHDFHEBGEFEAFDHBDGBCGCFHBGHEGAEGBDHFDFDCGDHGDAGDCBHEBHEBGBAFHGCGCCFEEFCDCCDCHECHFCFAAAGECHBBEEBHDAGAAEAAEAHEGHCFCEFGAD,False +66,26.0,13.0,22.0,33.0,10.0,21.0,25.0,20.0,CDFGDFAHFEHDHBBCDECDAHDGGGFBCDBADHHDGADEBDEGDHFFCFFDHDGADHCFHDAGEGCEACGBGGEAGFAGBBDABCABGADGAHADDADCADHAFCFGDGEFBEAHDCGDHDCADFADFGHCCHGFHCFHGDHGHGECCCCCADBFDGAABAFDAFDAFC,False +67,3.0,0.0,0.0,5.0,2.0,3.0,2.0,1.0,FDFEDHDGAFGADEAD,True +68,21.0,30.0,10.0,18.0,20.0,13.0,15.0,10.0,ABBHBEEEHDEHDGFFGDBDBBCABFGDCCDHFHHAAAAABFAEEDBEDBGBBEABEABFBBFBBDDAEEAGCFHEBAFAGDGGBBEDBHDFEFEEBEEBABDHBFBGCBGCGGBGCCGCEGAADAABCDDADEAHF,False +69,23.0,30.0,20.0,17.0,29.0,22.0,24.0,20.0,BHBBFBBEEAEGAEHBCABCBGCGEFHEGHFFBFCBFCHEEDEGCCGBCHFHBAACDGBFBEAEAFEHFEHGHGGACBEDDDBDFBGBAGBAGEDGEHAEDDHGDFEDFEHFACCAEHFBCGBCECFGFFAEGAEAHHBGABGAEGDCGDCHDBBEFAECDHCDHABAFBACBAFBFGEDEEHGB,False +70,16.0,21.0,23.0,21.0,35.0,31.0,21.0,19.0,FEGHEGHEHFBHEBDEGDABDAGFAGCDGCEAEABGGEFEBAEBHDFEFACFEHFHHEBFGGDGBAGBAEEAFBACBCBDFFDGEECFEDFEAFEFFEDFBBFHFFCGFBFCECEHCHFFHGFDGFHECEGCDDBDDEECCBDHADHADEEEECDBCBFHGFHGBCGFCHCCBGDEEAEHAECDCCF,False +71,21.0,21.0,25.0,23.0,34.0,29.0,19.0,27.0,CGCABAFBECCEGAEFEEHEDHEFBAFBFFGFDCBDFHDFDDHCCAEGAEGEECFCDFGDHCDAFDFFHBAEGDECFHHFHHEAABFABAAHCCCCHHGBBCBHGGHEFDFFCGFDGHDAHAGHCEEBBEDBEGEHBEGCHAEHDEHFEBDECFHABHABAAFDDFDDFBEFGHGCEECFDCDCEECEEAHEGHEFBBG,False +72,26.0,9.0,19.0,24.0,24.0,27.0,21.0,27.0,DDGBDCADHEDABHHHAEHAHDCHDBFFEEFAEFAHGACFFEEDHACFCCFGCDACDCCDCEDBADHFEGDHDFHGCHFAEFHDFGFGEFGEGGEHEHHAHFEHCAAEAFCHDCFFFGABAFEAGGBGHCHDFHDAAGAFCADGADHAGHBGBBEEEGEEFAEFAEFCGDCFDHGDH,False +73,24.0,24.0,23.0,19.0,22.0,18.0,26.0,30.0,HGFHGHHBBHDBAGCEDEHDHCDAAGCBCCHCCDGGHAGHGHHFAEFGEGBEBFDFAEAHBBHBDCBDCBCCDECHHFHDDHCGAAAAEAEEDBGDBGCFACGAHGDFGCGHABBACBAHGHHBHGBEDDACFACFEBFGHCAEBGEBGEDGEDHEFFECEEAEFGGHHFBBFCHFBAFGAEHACD,False +74,26.0,17.0,19.0,17.0,28.0,19.0,13.0,23.0,EGCAHEHHEHABADBADECBECEEABEACFACACFFBFGBFBDFCFCCACAHEBHEGHDBHBBAFEADEHBCHEEHEGBFGBFDCGDEFDEADEDHEAAFFEFFHHFACDCCEAHDADDEEEFAFGADBHEBEAGAGDAHBCHCGHCAHGACGEEFAHGHHD,False +75,3.0,1.0,2.0,0.0,2.0,1.0,0.0,4.0,EAHBCHCAHEAHF,True +76,10.0,5.0,4.0,6.0,10.0,5.0,10.0,8.0,HGHHAEEAEDAECGDCAHGFBGAGEFGFBEFAFCGCEAEEBGEBGDDHDBHDAHGAHA,False +77,6.0,2.0,4.0,1.0,4.0,1.0,1.0,0.0,AACCDECAEBAEBAGFECA,True +78,26.0,21.0,24.0,22.0,21.0,23.0,16.0,22.0,AEAFDAFGAFHAHCGFCGFHDCBDCBABADBCDGGFGHEBBDFBFFDCDEAEEGGFHAHDCDDBGEHCEFCHFGEFDADGFHFBDFCCCBCGBCABDFHAEBCHBCHBCDECEGFFAHFAHFCHFDDCAEHAGHBGHBAEECDDDDAABAHECHEBHEAHABGEBAEACEACEAF,False +79,23.0,23.0,29.0,21.0,13.0,23.0,22.0,17.0,CDHBACEAHEFDEGHAGAAGFAHFADFCBBBEFBCDGFBCDBDHGGGGCGFBDBBCFBFDEGEEHEGGBGEHFCCFCBDCEDAEABFDHHBFBBCAGDDCHDCHDAHBACAGCAGCADDBDFHAFCAFCGHDEBGHBCHGCHFBEGBFACFCCACAADACFACFCCFGFDG,False +80,12.0,12.0,23.0,9.0,27.0,13.0,18.0,19.0,EGFECEECHEBEEHHFBDCGCAACFBCGEHEEGCEACEGDEADAGBAGBCDBFBHFHACHCDHCDHCECCEGFHGFBABCGDCBDCEACHBCGGAEEAECFEHHAFFEEFHFCEFCHGGGGDHBEHGGHEEHE,False +81,25.0,15.0,14.0,17.0,20.0,16.0,15.0,15.0,DGDFFBFFCAFHADGAEEAFDABDEGGEBGDGEDEBAHAAEGABAHCACEACAHBAGGECFCDDEDBEFHEBGAFCAFCAHDEHDAFAGFCDBCHCCHCEDBGFGHBADBHGBEAAHAAHAEFECFEDFEDHEBHGB,False +82,23.0,16.0,15.0,28.0,9.0,16.0,15.0,26.0,FAHGHHFHGDHGDHDHCCHFBHEDGDGADGBDFDHFBBEDBADEDDBDHFDACDBFGBFAHCDDDGDBGBBGAAADCHFCHCDGABFHDDHDAEDCEDCGDFEAAEACHHGHDGCFFCHABHAHHAFCFHAAHAACBABBHFEAGEAC,False +83,16.0,17.0,21.0,14.0,11.0,17.0,24.0,19.0,EGHCBBCBBHFAHAAGAFGHBCDFAGFBDABDADEEDBCDBCHBCBGEGFFGFGGCHGCGGHHADHDHCDHAFGACCEHDGHFFCDFEDAHDFFAFFHEGBDGCGCBECECHBGHGGHCGBCHBCEGFGGFCACAABAE,False +84,25.0,24.0,34.0,20.0,21.0,23.0,18.0,22.0,GCCGAFHHFBGFBCFBDFBGFCGDEGCAHEBCAFCBFHEFEDCGFCAFCHCHBCHEAHAFBAFDAHBHBDGAABAFBACACHHCFDAFDGBAHBEBBEDFCFECAEBGFHECCCCCCHHEEHAAFDGFDHBDGBEFBEDDHDDEBHECCECCEBAEBAGACGEDGADCBCCGGCDEAGCADCAFHHD,False +85,14.0,17.0,15.0,14.0,15.0,14.0,16.0,10.0,GGCGDDEBFFHGFBGFBHFHHEDAACAABGFFFCDBGBEHBEDBFDBCDCDGCDEFBCHBEGBEGBEFHGFBAEBCEFAAGGCHCCFCCBCHEHEAACADDEDDAGDAGEAEBAG,False +86,5.0,2.0,1.0,1.0,1.0,1.0,3.0,1.0,ADFAGGAHGBEABCA,True +87,28.0,33.0,23.0,19.0,20.0,25.0,30.0,22.0,FFGDBGHBGEGAADDHGEEDEHBBACDFCGFCGEHFBBFHBFBCCGCCFHDFCGHBECBAAFFDBBCBECGGFEGECCAGABBABHAEHBBHBHDEFDCHDBAFFDDFAAHAAHCDFCAHEAHGAHFAHAGHAGAAGEEDFGBEBECBGCBAFBGCCGAFAAFHAGGFGGBGGBDEEGEGBFGBFHBCHBDDBDDBECCA,False +88,27.0,30.0,28.0,20.0,23.0,12.0,23.0,29.0,EGBCBBCEBCHHGDBECBCDBEDGEHGAGACGEHGCDACFECFCBHBBFDAHCACBACBEFGGAGGADAAEBAHDFHDCDBAHCHHBHABGCBEEDHGHHGFHAHDAEDABDGCDECDBADBHHGHHGFGECBEABDHFDGAHEACFGCAGCABCHBFECHCBFCBFAEABDAGEHEEAECABDHBHHCEBG,False +89,14.0,15.0,7.0,17.0,10.0,11.0,15.0,9.0,CHBADFABGHBGFGGAGGADGDEBHADHGHGFDFDDCDBGAAGHAGFAEEBBEDBEBCEBFAFDAFDFGDEADEGDFACCCGBHBBHABHDEDCBDFE,False +90,5.0,3.0,3.0,1.0,8.0,0.0,6.0,3.0,CCACEGHEGDEGBBAHEHGBAGEAEEAEG,True +91,0.0,0.0,4.0,2.0,4.0,2.0,2.0,1.0,GDCFDCEECGEHFEC,True +92,14.0,4.0,7.0,10.0,8.0,6.0,12.0,5.0,DCDAEFAFCECEEAFEDFEGCCGACBDGHFAHBGEBGAGGAGGDGAEGHHGAADAFDADDCBAHDA,False +93,10.0,8.0,8.0,3.0,8.0,14.0,16.0,15.0,FAGFDGHDHHEHEEGGFFACFHEHACCACHFGHFGHCGCAGCGBCFFEGFGBHABHFDHGBGBHABHAFFAGFEHEEBBAGG,True +94,21.0,25.0,21.0,30.0,27.0,13.0,12.0,17.0,HHBEBCAACEABDGDGBDFBGFCAEHGDCADCHDCEDFEDCEDGDCEDAEGEHAADBBDAADHCDHDFHBEEBEEBCEGAECDEBBCGAHEBBFFHEBHEHDAHDAECFFDFEDFBDABDCCACEDEBDHDDAGFAEABECBHGFDDFEDCCBHCBHGBEGBACBA,False +95,4.0,6.0,6.0,8.0,7.0,6.0,6.0,9.0,EDGEBHEFHACBBCFEGHCHDAHDEHDBHDBDDEHFCGECGFGBFACFAHGD,False +96,8.0,5.0,5.0,6.0,5.0,8.0,12.0,12.0,AFACCAGAGGFBEHEGHECFDFFDGFHGAHGHHFDGAGCAGEFGHBBHEBHDDHDHHGCBA,False +97,20.0,25.0,21.0,20.0,27.0,26.0,25.0,26.0,BFCFGDFBECHDCEBGEFGBABHGDDGAFBEBCEFEEFGDAHFBHEHHCHDDHGEFDFFBGBBAEGCCFDDABEBBEBFHBHHBCCECEDCAFCGFGHFCBGHBEAFCBFDEEAEEAFECEBBGGAGHBDHFHHFHHFHHFHHEEHGCDABGABGACGAFGAGGDDEDDCADCFGAFGDCAHEAHEAEGC,False +98,4.0,3.0,1.0,1.0,6.0,1.0,5.0,3.0,BBAHAEDECGEAGBAGEEGHEGHF,True +99,21.0,17.0,15.0,21.0,17.0,23.0,10.0,21.0,AHDDHEDGFFGCFHDHAGHGHHDDFADFABHDBCCACAAHGDDFDDFGBHEBHBHEEHEFCFFBBDDBAABCEEHDACDHCEEAAEBHBFABFABCABFFFFDFFDFEEFCEHCEBDEBFCAGAGGDGCHBCHAAHEFFECAADH,False +100,21.0,17.0,13.0,22.0,21.0,22.0,21.0,31.0,GCAADDGBDEBDABDGDGGEADEDDFHHHEHDGHFGHFDHGAFAHEHDCHDHFEBGEACDACGABGABGFGGDGBHEEHEFFGHFABDHEDAECBFHAGHAHBAEAAEAFEHFEBGGBCFDFEEAHCHHCFDAFDCFDBFHBAHCHHFFGEHDECCGCBHFHHFBHBE,False +101,3.0,4.0,2.0,2.0,2.0,1.0,2.0,2.0,BCFBEABEABHADGCHGD,False +102,3.0,5.0,4.0,4.0,2.0,1.0,3.0,10.0,BGHBGHCCHCDHEHHABDFHDBHEGCDAHBAH,True +103,22.0,16.0,17.0,17.0,11.0,10.0,13.0,12.0,DECDFCDFEDCCBCCBCADGAGFAEAAHHCGECAAFHAHBAGEFDEFHHGGFBFCBACBABDACDAHDAGDGBDBADHFDBCEHGEHGDHABGBCEDEEHBAABADCGGCFCABDABA,False +104,12.0,15.0,10.0,16.0,25.0,15.0,20.0,17.0,GBFDCFDGDDBHDAADEBGBDEBEEFGHFGHFGHCGHEGDEADHBDHGGBGHEDCFHAAHACHGGEGGEFEBFGADCCEBHEGFEHDEHEEFAGDCHFEEAEEBCEGEDBEDBECBFFBHHCAFAEGAFB,False +105,7.0,10.0,8.0,8.0,6.0,8.0,6.0,10.0,HBEHAGHFGHBGDBAAGCDEHFEBEHBEBCABAACDFHBCHDFGDFGDFHCHCCACBFDBEDF,False +106,17.0,20.0,9.0,15.0,13.0,17.0,14.0,15.0,FBEAGDAGAABAHBGEFFBFFEDHEGHEGHEFHFDBBCBBDBCHCAHGAHCHBEGFDGFAEBAEGADCAHBDFBDFDFBABHEFGBCDAFDBCAGCFBHFBAFAEDHEDCEDHBDGGHGA,False +107,5.0,5.0,1.0,5.0,1.0,5.0,5.0,2.0,FABAAGDGFDFHBFEBAGBAGBFDDHGDC,True +108,17.0,16.0,20.0,15.0,16.0,19.0,21.0,30.0,CBHCHHDDDGADGAFCEHEBHEFEAAEBHFHCBGFAEDHEFEFFCFFAHEHHAHBGCDCHFGHBGFCGFBEABFBHHGHHGCHEAHEADABGHBHHBDHGDHGAGGBGGEFCFFCDBGDFDAECEECGCAGCGDCFDFHHAHHDHBBCCACGAC,False +109,19.0,26.0,19.0,10.0,27.0,23.0,8.0,14.0,EBCAAAGFADFADFEFBBBCBEABEABEAEEHEEHEECEBGACCAFCBHCDCCECFBCAGGAFEAFEFBHHBDFAHEHFEGFHCFBBHCCABCHFFBFFBDGCEGEBAEGCFFEEDHFFBFBADBDBBDBBEHEEFCHACBAHDEE,False +110,19.0,10.0,10.0,17.0,15.0,14.0,13.0,9.0,EACEADEDDGDAEBCFACEAEBFHFFGDFEDBBGBHGCADCFBBBHCAHEAHFAHAAHCDGCDGAEGAEGEDDFGEAEBAGFCGDGDDABDFCDFGFFAAEDFEHAH,False +111,6.0,10.0,13.0,9.0,4.0,7.0,3.0,10.0,CCCAFBAFBEHDFBCCBCHBCBCGHDAHDAGDCDFCHCEHDAFDFHDHHDEEBFBAGBCHBC,True +112,14.0,15.0,18.0,9.0,20.0,11.0,10.0,7.0,DEFDEFBEACFGEFCACCBGGBHAAEBEHCEGGEDEEFEEDBECBABGADFADFADGCHCCHCHACEDHEGAFAEFBFBAEACCAEBBGBBGEBEBHCCDCCFC,False +113,18.0,25.0,13.0,24.0,29.0,22.0,19.0,30.0,HCAHEABDACHBBDDHADBEHEEHCABCFBHFBABBABDHBEHFGAFGFHCHGCAEFHEFHGHCGCEHDDFEBFEFFDDHDEEDGEFCBGBDGAHHCHDCFDEEDGCFHHFEEFGBGGEEHBFAGFDHBEGFEDCEDEBDEFHEAHEAHABBEDBGFBGEHGAHFADBADHADHEDBGGB,False +114,13.0,9.0,15.0,32.0,17.0,18.0,11.0,14.0,HDHDDAGGFDDFHBFBCAEDGEDCEACDDEEDFHFAGFDECDCCDFADECFECHDCHDGAGAHGHDFEDCEDCEHBHDAHDCFDBFHHGDBDAFCGFAHFDCCDAEDGEDEEFADFAGFBBDEBDEBDF,False +115,21.0,18.0,26.0,25.0,21.0,27.0,25.0,34.0,AACCECDFFBBDABHAGHGFHGHAFHBFHFEHCBHFDAGHAGEDBEACHDCAGCDCCDBEDBDDEGGEHGAHFAHDBFGHFGCDCCFCBFCBHCHHFFDFGEEEDHFHHFHDFEDFDCBHAGAAGHBEEDCFFCHEDAEBAGDEGDEDBFBGCBECHCGHCDAGGAHGHCGHCFHBFHCFHDADAEGEGHCGAFFEH,False +116,25.0,15.0,25.0,18.0,19.0,11.0,22.0,30.0,BGGBGDHGBAECHEFABDHBHHBHDADBEEGFGGDGCCGFCHHHAHAFHBFEEGEAHCGEAGDCCHCGDAGBAGBAEADBADHADFCGHEDHCABCHHEHDFHFAHEAHCHCAHBDHBGHFGEFCAGCHGAAACAACHHDHCCGECEDDFCDACDACBCCEEGEE,False +117,28.0,24.0,15.0,28.0,23.0,30.0,14.0,19.0,CHACHAGEBEFDCFAGFADDEDDBDGBDBFEBEDHHDGDECDEBFABFAFFABAAHHAHHDFHFBHDBEDADCBGHEDFFDEDDEBEBAGADDFFFBDFBFFBFFBHACFDBFDFAEBACBACGEGGCFAFEHEAHECHBDGGFCAECFEFHEHHAGACBDCBAHAAEAAEDECDAFGGFB,False +118,0.0,3.0,1.0,0.0,4.0,1.0,0.0,2.0,FHBBEEBEECH,True +119,15.0,14.0,10.0,15.0,7.0,12.0,18.0,9.0,BGDBGBFEBDCFAFFADCGGAGDABAAHHAHHACEBCDDCBDAGDGBBGDGDDACEFCFFCGFHGBEFCGACHAGAGHAGDABBEEFHGFBFDBEDGHDG,False +120,18.0,23.0,21.0,12.0,21.0,14.0,26.0,15.0,GBBHAAEBAEHEEFEGFGCAECABAGCADBEFAAGDABCAGGFGGCHGCHGAHEAHFFCEHCEBBFBBEHBCGECGACGDCGDHGCGGHGGDDGHACBBGDBDECDCFABECFEBFECEBGBBEDDEGFCDFEGBHGBHAHFACEBCHBF,False +121,18.0,17.0,15.0,11.0,14.0,12.0,17.0,17.0,AGGAFDDFCDBBHECHBCHADHCBACFACDDGFACEBCBBGBHAAHEAEEHGFGCFGBHEBAFHAHHADHBEGBHHCEFEEFGHFGFGCBDCADGBDHHEBEBBAADAAFCAGCGGEGGEC,False +122,19.0,12.0,14.0,16.0,13.0,13.0,22.0,12.0,DFAEFDEBHGFEEDAEDFGGCGGFGGFGGAGGAFFDEAGEAGDBBABDHHCHHBDHBDGCGGDHDAGCACCBFCBABHEFHCCHECBCGDDAHDCEEFACFBCAGDAGAAGAEFAGDBEHA,False +123,3.0,8.0,5.0,11.0,9.0,10.0,4.0,11.0,EBFFHHFADFCHFGHEGHFGFACDEDDEGHFAEDHBDEBDECDCDDFHBFEBHHBCEBHDB,True +124,4.0,5.0,6.0,11.0,9.0,6.0,5.0,8.0,ACEACEADEDEHDCFFCDCCEHHEHEBHGBDGHDFDFEGFEDBHDHDBBGFAGD,False +125,11.0,14.0,19.0,12.0,21.0,14.0,17.0,9.0,CCDCBDBEDHEGHAFEECDGCFGCEGCBGEFAEDACCHCDHGFEFFBBEABEAHHAFCCFBFFCFCBEGDACDGCAEBAEGGEDGEDCAGGEDHEBHBBACBHGFEGEGDEGEFCBF,False +126,7.0,15.0,16.0,15.0,17.0,19.0,21.0,17.0,CHHHDBCCEFEEBEGBHFEDGEBFFBGFGHHGHHGEHDHCDHCDFAFFDCABAFBHGBCGBFHBDHCEGAGGHHGDEAFECHDBFGBDBCDECGEFEEBECBDFFDECGGCGADGEDGFGCFGCFAF,False +127,1.0,2.0,2.0,2.0,3.0,3.0,7.0,2.0,BEGGGGACFHCFHEFDGGDEGB,True +128,24.0,27.0,28.0,25.0,25.0,12.0,31.0,20.0,GGGBGGBDBCDHGACGEHDCHDCBDCHHEHBGHADDADDEBGGHGDDEADFAHFAGGEGEEABEHDEHCEBAEBECBACBACGACGADFADBBBBFCCAEGHFBEBCAAHBCHFCEFCDFCDCCBAEGEGCAGCGCCGEHFEHGCCACAACBDDBHGBEBDAFGEFGBBGHHEDGDABCGFHDEGGEDEADB,False +129,8.0,19.0,18.0,15.0,11.0,19.0,15.0,9.0,BEEBFHGAACFBCEBFHFADFCDHCDBCGBGGEGBDAADFDCHECHECEGCFGCFGFBCFGCAGDFGFFHHBDDFCDFBBEDBFDGDBBFBHABCEBCDAEGCBFHBFCGECGD,False +130,19.0,16.0,11.0,13.0,12.0,17.0,19.0,19.0,AGFEGFGGEGDAFDBFDBCGACBHEHHAHHDFADABHAGHBFHDFCDCADEEFEGBDGBEGADBAHFGBDGBAEFAGFBCAECHGBGFBGBBFBHAHHAHDEGEFAHADCACCHCEHGAHFHGFCF,False +131,4.0,4.0,2.0,0.0,2.0,2.0,3.0,2.0,FBECAGHAHCAGBAGBEFB,True +132,21.0,22.0,26.0,22.0,19.0,22.0,19.0,31.0,HHACHAGHDFHCACFECAECGDFFDFCAACEBEDHHAHDCGBCBBCAHCAFCDBGFGDCHBHECHCFACFGCHECBBCFBGHDGHEGHDGFBAADFGBGGFCGHCBHAGHFEEEDAEDAHHABFABHAHHGHBFDAFDGDDFEDGBDFEDHDDHCEHEAHECEECEADBGCBFFHCFBBBBH,False +133,16.0,18.0,20.0,18.0,16.0,13.0,27.0,16.0,DGGBCEDCEFHDGHFBDCHFHHBACBADAAHADEACBGHFGEDGCBCABGAGFCGDCGDGBEGBEGBECEEHGEHGHHDAAGGACBDGBGCBACDEBDBGCFHFEHCEGCEAEFCHFABFEGGCDHFDCDDCDBFGBFGAGHAG,False +134,19.0,21.0,15.0,10.0,12.0,12.0,10.0,11.0,DAGDAGAAHHFHABCBBCEBCFBCGDCGEEACACBACEAFGBDAAFEAFEHBBBFECDEADGFFACGECBBCBBGEBFEBDAACHADHFEFBCHBFGBHDBCGBHADHAH,False +135,13.0,9.0,13.0,6.0,13.0,9.0,17.0,10.0,ACEEHFBHFBGFCHABEADHHCGACGDHBCABEGBEDBGGCGHHAHCEDAEFAEGCEACEAGGFCGCDGBFGAFGAFBEGCEGAFGECHD,False +136,12.0,12.0,9.0,6.0,6.0,6.0,7.0,12.0,DGFDCFBCHHHHHHHBHBBABEAFGBEGCFDFGCCBDABAAEAAHACCAGHADEACGHGEBEFBCDBHAB,False +137,8.0,7.0,7.0,10.0,12.0,16.0,11.0,8.0,EEHEGHGAHFFEFEDBGDBEBBGGFGDCGFCFCGFDDFHDFHAFCFDGAAFFAEHAEDFEGFEDCEGAEFBHBCDBCHA,False +138,16.0,20.0,15.0,26.0,16.0,10.0,21.0,11.0,BCEFDBCDBAHBEFBCAHCAEBDCCDHGHHCHDDDEGBFDFGCACAEEDGADGEDBEGCEHCHBGHBEDDADDGBDGBCGBDHCFGCGGFGGAAEAADAEDGEDBEBADDADGCDGBAGBDGBHGFFBEDAEFBF,False +139,13.0,8.0,3.0,6.0,6.0,4.0,5.0,4.0,EDGABAADGAECAGAAGAACHFFHABGFBABBEDBEHBAHCABDFDEED,True +140,3.0,7.0,9.0,8.0,11.0,8.0,12.0,4.0,FGFCGCCEEDFEBFEBDACHADEBCEDFBDEHEFBEHCEDCGGBGFBEFCGGDGHDGCGGAG,False +141,7.0,6.0,3.0,11.0,10.0,4.0,8.0,7.0,EEAAECEEGHEHDFDCHCGHEAAEHBDFBDBGDBADBEHFEAFGGDHDDGBDGADG,False +142,25.0,23.0,17.0,19.0,29.0,25.0,18.0,29.0,EEBEEBHHHHBCHEFDGCDECDEDBEFHAFGBFBHFBHFCHFEDFBBFEAEGBCBAAAADAHEEFAEFDFACHHCHBEHBHHDGECFEFBEGHEGHAFHCDBCAGHEGHGDHGEGGFAAFAHEEHBFABDACHABDCDAFGFFGCFECFHBFEEDDGDBFCAHAEDDEACEAGDBGAAGAHCBHB,False +143,1.0,2.0,2.0,3.0,4.0,5.0,2.0,3.0,CFDCBDHGEEGAEDFEFFBHFH,True +144,9.0,4.0,7.0,5.0,3.0,7.0,3.0,7.0,EFAFABHACHECHGCBADBADAADGCFFAHGHDFHDCHFCBECAF,False +145,21.0,27.0,26.0,22.0,15.0,22.0,16.0,17.0,FCDFDDECEHCFGCEGDABBGHCGBBFABAEFEEFACHBGFEABEDBHCCFGAFEEFHAFECFHCEBCDBCBAHFAHFCFFCFFBFAGGAECDCCBBDDCDDCABBAGGAGBAGHCHECDACBAFHECGBGGBAGBHBACCADDDDCHHHFHHBDDBDDBDBADBF,False +146,23.0,23.0,27.0,18.0,23.0,27.0,25.0,28.0,DEGHEGFDBFGHDEACECDFDDFDBBBGCEAFHFFHFEBGEBDEBFBBFHFFEFCGFCGCHGAHBCFGAAECGEGDDGCHGAHAAHAADDADCAFBFFBHBHEGCAHCHHBEACCBBABBDBHCBDFAHAEBCEGEGCBHEHFAGCAFCACEFHEFADBCGGCGHAGHGEHEFHCAHCGHDGHCEHCEFCGFDF,False +147,19.0,22.0,21.0,22.0,15.0,18.0,18.0,18.0,ADDADEFBADAHFBBFBBCHGCGBCBHEDCCDHDDACGEGBEACEBCGCFABFHEAHFGDCDDCGFCGHEHHEHBFHDFBFFBAFAABAADACDFCEFHADGADCCECDBHDBCGBAEBAHDHHDHACFCGFGEFHEGGCGEFGBDGBGBBDE,False +148,23.0,18.0,18.0,17.0,20.0,20.0,23.0,19.0,GHBGCBDAFDAFHCBEFGACAECHHGEGFEGDEDDBCAAGFAGCGECAEFBEACEHGEHAEAFEAFBCGCCFCBBGHBAFBFCBFAEHBEHBEGAACFABGEDGHAGBCGCEBDGDDHEAHCADFFGHAHDGHDGHDGBDABHAEDDFHDFCFFHGFE,False +149,11.0,9.0,14.0,14.0,12.0,13.0,8.0,11.0,CCFCGFCDFHHHGGHEDDFHDFEEGCEAHAHCADFEBBBCBFCAHBAHEACDDCDACDADDBDDBEGBDFFCEHEFBEFEAGEGFCGFCAHA,False +150,20.0,17.0,22.0,21.0,18.0,23.0,27.0,26.0,FDDHHBGAEAABAAFAHBGFFHEHCEBEBBEDBGDCGHCGHCFFEGFEDFCDACDAEBFEDAEDHHHFGHGDHGAEFCFGBEDAADCCGFGGAAGCHCDDBDCGGFGGFGGFHGFBGBCGECHFHHACHABDFHDHCAEBBEBGCCFHEHGFHFEHFEHBCACCACGAGHDDDD,False +151,25.0,32.0,23.0,18.0,29.0,30.0,21.0,16.0,CHFAFBDBCEHGEHEEFEACEFCFHHFCAGAEGBCABCAECHDDFDFFEFFGHABFFEHBBDBGABGACGACEDCGDEBDEBCEBFDCHBADBFDAADEFBFHGAACAACHDEADHCBGCAFBFFBFFBEBBGBEEBHDBFDGDAGFEGCABEEBEHBGHBGFBGBAGFGCEGCACFDGAEBEEFCEFAFHBCE,False +152,2.0,5.0,8.0,6.0,3.0,7.0,7.0,3.0,ECBDCEGFFGHCGCGGFBDFDDADDHEBFCBCCBFCGFGAH,True +153,20.0,20.0,31.0,26.0,22.0,23.0,14.0,22.0,GBGFBFFBHCBHCBHGBEFCGFHHHHEHDCHCCDGCFFCDDHFDEDGEGCHHADHCEECFECHECDGCDGADCAGAAHEDHCFBEFEDCHFFAADEADHADCGBCFBCFEEEEBGBCCCCBCDBDHBAHDABCAGCBCFBEHDEBDCFDHFEFDAACAEDADAFGEFABFDCEDAFAB,False +154,14.0,22.0,13.0,6.0,19.0,16.0,15.0,9.0,EEBFEFCBFDAAGAHBCCBGCEEAEEAEEAEEAEGGFHBCHBCBCHBCFACFGDECBAGFFDBHBBHGGFAGBGCBEHGADBFBBGGAFCAFCEGBEGBEFBDFBHEHEFDAFB,False +155,13.0,9.0,8.0,9.0,16.0,11.0,16.0,26.0,HGHDBHECHGCDGAEGFEHDEGGHHFBHFGHBGBEFEAHEAHBFHFDHADHBCHEAHEAHDGHDHHEFFACDCEBFGGEGAEHEGHEGCCGFHGAAAHAFHAHDEBBC,False +156,21.0,23.0,28.0,17.0,32.0,20.0,26.0,33.0,AGBGFFGFGGCEFCBFGBECECGECBECAGHDHEDHCBHEEAEEBFGGHEEHAGFFGFHHCCHADABEGBHGCHGCFBHEHHEHHGFHFFHEFAEHADCEDCHAADBADHEDAFHEDDCCDCFEHBHGGHEFHEBHEBHGBCGCADAAHACBDFBGCBECBCCEHEADEGEEAFCDBHGBCGBCDFAGEAEHAHDCBBCG,False +157,3.0,5.0,10.0,12.0,6.0,7.0,9.0,8.0,CDDCFDCHDGGFGDBGDHFHHEGCCHDCADCAGBFHEGEEGCEDEFDBFDHAHGCBFCBD,False +158,27.0,19.0,22.0,22.0,21.0,22.0,30.0,32.0,AEAADDGDGHBHDGHBGHBHHBCHCAHCABEEBDBDHGFHGHHGBBAHAGFGBAGAGGAGHHCFFBHHGDHAACAGCAHDADGAFHCCHGHHCHGCFGEEDEDBECGAFEDFEDBEGBCACHFCDFGDCDCCBGCFGDFGHFAAEDHFBHFGFFEAEEHEDBECFEABGAFEEEAFDCFDAFDBCGHCGHAEHAG,False +159,6.0,10.0,10.0,5.0,6.0,6.0,5.0,10.0,HCEECDECAFABHBBFADFCGACGABHFEHCBBCBBHFHCDCEDCHGGHEGHFBHABD,False +160,18.0,20.0,20.0,17.0,21.0,19.0,20.0,20.0,FEDBECCGDCDBGDBGDGGDCDFCAHCEHAGAABACFCFFCAACHADAACEGEEGBFBHEHHBGHBACGFDFCHFCHEAEBBEDFFGCFGBEBBEHDDHABGEEEEFABHABHGEHGEHGEHBFDFDHGDHGBEGBECCFCAFHFGCCDAFAHDB,False +161,12.0,21.0,28.0,20.0,19.0,21.0,30.0,23.0,BEBCAAFGAFGBFGEEEFCCHCGHFGHGDDCCHBCGACGEHGHCEHCFCBHCBHDAHDHHDCHEABGHFGBGGCGHCGCEGFDGDDEFGEAHBGEADDCFDGBDGDCFECFCGFCHEGAFCDFCDGDFFEHFBHFCCBECHEBHCBFDBFBBGBDAEDGECGBHEBDABGGGAH,False +162,21.0,14.0,18.0,20.0,18.0,17.0,19.0,20.0,GHBEAFEGBGGHDEEDEABEBBEFECFCCABAAEAAEACBAFBHFHHAEDBCDECDAFBAFBAGEHEHGDAAHGAEDCCDHDDHGAHAFCCECAFCHHCHEGBCDCCBFFEFFGBFDDDDDGGCGDAFDGCGFHHDHHDHGFHGAGG,False +163,7.0,8.0,10.0,9.0,10.0,6.0,9.0,12.0,FBCCDDCAHADHEHHAGCGGHECHECHGBFABFADFGDHBDHDDCDHCEBFHGECEEAEFHECEBGBGGBA,False +164,2.0,1.0,4.0,3.0,2.0,6.0,3.0,7.0,CHCFEGFCGHHEABGAHDFHDFHCFHFD,True +165,27.0,21.0,24.0,26.0,31.0,11.0,22.0,21.0,CAADGACHHEAHDFHCAHCFBCFBEBHGCEFCHCGECDEABEACDDGHDAFCCDCADCAGBDGBEGBCDEHAHHAEFBEGDEFCEABBDBGAHAACAAEACBFBBFGEEHEBDEGDEGDCCDCABHEEEGCDGCDGHEGEEGEHDEGDHDAEFEGBDGADHFDGCDGBAAAAHHEEHDEBABB,False +166,7.0,16.0,7.0,13.0,4.0,10.0,9.0,15.0,BDDEDDGCAHEFHCFHCBHAGFDBDDBDDGFFBAHAHHFGBBDFBDHACHBCEBFEHHGHHBADBCFBHDGABGHBGFBGC,False +167,15.0,15.0,9.0,10.0,9.0,15.0,18.0,14.0,GGABCADCGHHGEHBDHCDHDEGGGFGGAGAABECBCFBEABEBEGAACBBFEAFBHFBHFBGFCAFGHFGHDGCBCEHFFGBFEDFBDAHHAHHGFDDAGDAFA,False +168,21.0,14.0,14.0,15.0,25.0,21.0,7.0,17.0,FDABDAHCHHFDACBGCBGCHFAACGEEBCBFABAEEAEEAFEADDHFAHFEHAHHCEHEFDGFEHFEGFDFHCCAEAAEADBHCFHEBBCFACFDEADFAECAEBBEDBEGFDAFEFDHFDHFEEBCEBGEHD,False +169,11.0,25.0,11.0,15.0,12.0,14.0,16.0,19.0,CDFBBCHGCEBDBACBDCGHFHHFHDFHBEGBEDBFDAFCAHBACFAGGAGEAGBAGBHBBDEBHGHHGHFEABDHFCBECBFDFEGHDFHBFHAEHECHBHBGDBGBCEBABDEGDGGDFDB,False +170,11.0,10.0,15.0,10.0,14.0,10.0,14.0,13.0,EEGCEHAGADCDEADGBDBHDFGDHCDFCDHBAEAHEHCGFCGFCEFDHGHHGHFGCAACHACHAEGEBDCFGCFBBFBBEEBGACGFHEECEBCGA,False +171,15.0,14.0,17.0,21.0,14.0,11.0,20.0,12.0,CBGBFHBCEACEAGAACBDBBDCDDCDDAGGAFGFGDHADEDDEFFAFFCBFCBFCFAHDDBGGGEADHHBHBBDEEGEEGCAGCDCCGCEBHHCGGCDBCHHEAHGAEGHEFADGDGEDGDDA,False +172,6.0,4.0,6.0,6.0,3.0,10.0,5.0,4.0,GBFGHFGDEDFCDAGDHCDACBECDECAHAFFAFBCBHAFFGFF,False +173,2.0,0.0,4.0,3.0,0.0,0.0,1.0,0.0,DDGDCCACCA,True +174,3.0,6.0,8.0,12.0,9.0,8.0,4.0,7.0,FGBDDHHDCFABFABCBCCHDEHEFAEFEBFEDDHDBCDECFHCFGEGGEDDCDDHE,False +175,4.0,4.0,3.0,0.0,0.0,0.0,2.0,1.0,GACGABHBBAABCC,True +176,4.0,2.0,4.0,1.0,2.0,1.0,1.0,1.0,HCDACAAEABCFBCEG,True +177,22.0,20.0,10.0,18.0,13.0,13.0,19.0,20.0,CBHCGHGEHEEADBHGAEGFEGFBAEBCFAFEGHCBABFADFDDCHBCHDHAGGADBAHFEEFHBBHBGDDDHDGHGFHAFAAEGBBDAADHGBEGBAGBADBAHCHHADHDGGDFGDFDCABCABCABEFHEGA,False +178,22.0,19.0,25.0,28.0,26.0,27.0,22.0,13.0,CCCCCCCDCAGHEHCGDGHCADEADBADHFDGGGBDACFHCFHDGBDGDAGDCDDBBCEBFBAABDCDDEDFEFEECDEBAFBDDBFEHEEAEFGEFGEAGBFFBFFBCFCFDGHEFCAFCAHEEGEEBEAHDGEFBFHDFEDCDHCDACGGBGCAGDAFAAFEAFHDFEGECBBGFAEFAG,False +179,3.0,7.0,11.0,8.0,19.0,13.0,15.0,4.0,BEEBAEFHEBGCBCEBFHFDECDCGHGFEGEEBECGFCGFDGDDGFAFFAEGCEFCEFDECEEGDEGCGGFGEBDHCEGF,True +180,23.0,18.0,16.0,19.0,17.0,9.0,16.0,16.0,DACDHCDECEHCBACDAFDAFABCEDHDGHBCFFABCDDFDDHCAHBAEDABHABDGDFCBECAEAAHGEFABFGBGBHABHCEAEGAEGEHGFHEAAEAHGCEGCHGAEGCBGCDGDEGHHADBAGBEDBDBB,False +181,7.0,4.0,3.0,4.0,1.0,4.0,0.0,2.0,CDDAFABHAECADFHCFABFABDAB,True +182,7.0,17.0,14.0,12.0,11.0,8.0,17.0,16.0,ECEECHEGDCFDCFDCEDBBGBGECGBHGFFGCBHEBHABAGBHFBHDGHBECBEHHGCGCCGCFGHABADDDHGDHEBHBCGGFFACHAEADBHDGHBGDB,False +183,18.0,19.0,14.0,22.0,20.0,25.0,20.0,18.0,FBAHCEHGHHGAEDEDDHDHGFACFDBFGCCBHGHHGBHGECBHFDEFBEBHECHFGDFHDEHAGGEGDBGAADFADAADGADGHFFEGCABDGFDBDECDFAFAEFCEFCADGFDFFBFFBHFCECGEBGEBHEADBBDFBCFDCFAAEGBEABE,False +184,9.0,17.0,14.0,14.0,12.0,19.0,15.0,10.0,DBDDHCBBBBGGFEBFEAFGCFDCADCDFEFGHFDHBDCECCFDCAEBEDHFDCBDGBACACGECFEHDBACBFFBFFGGDEGHHGCHFBHFBEFAEAABGFBGEGGFGH,False +185,5.0,15.0,12.0,28.0,11.0,16.0,11.0,13.0,FBEBDDHEDCEGFGGBGEBDBBHCDGDDHBDHECBDFBDEGHEFHEFEDCDHGDADDABHABDCBDBFDHGDFDCGHCGDCHHGDADDEDDAFDFFHFFECDCBBFFCFFC,False +186,3.0,2.0,0.0,4.0,2.0,3.0,6.0,2.0,EGADGADADBGHFGBDGHFGEF,True +187,7.0,12.0,9.0,16.0,4.0,16.0,12.0,10.0,BDFDFFBBBEBBFCHHCHHFFEGDADDFDFHAFDAFBBGDBGDBDDGCDFFDGDGCBCADGEHGDHCCHACABHAHGCFGFFGEFG,False +188,9.0,14.0,12.0,11.0,9.0,6.0,5.0,4.0,DFBEFDCDCBAFBADEFDEGCEBCGFCECHDBADBADBEEBABGHBACBACBECGACBBCADDHFGHECD,False +189,15.0,22.0,16.0,23.0,11.0,18.0,13.0,25.0,CHGBHDEHBEHDGCDFHFHHCHHGHEDDBGHACHECHBHGDHDCHDEAGEABFAEFACBBDDBDBADACDABFAHDABACBHHDHCAHFFBBDBGAFGFFBBABCGEEFEDCCDCBDBFDBFEFGGFHHFHDCADBDGFCGFH,False +190,23.0,11.0,18.0,25.0,19.0,12.0,19.0,38.0,DEHHAGHADHGCHACEDCAGEGFDADHADHDDGEEEEHFHGCAGEDDFHHEHHDHDGBDADHECEEGAFHDBHGBHGBDAHAEHABHBBFDDCDAHHGHHEHFGHCHDDECBFCADCGDCGHCGHGAHGABFHFHHFHHEHHBBAEDAEDFCCECAAGACCACAF,False +191,5.0,6.0,1.0,7.0,12.0,13.0,5.0,13.0,HEEFEHAEHFFHFGDFEDGEGAFGFHGEHDBHAFHFFEAHEBEBDFADBHHHEHBECFDBFD,True +192,14.0,9.0,19.0,16.0,17.0,13.0,14.0,12.0,FBCCBDDFFDHDDHGEFGEFGFHGFBDFCEEHACCAEEDBFDEDCHFCBAEFCGGAHFADGAHEHHAHBACBCEDEEDCCDCGACGCCGCEGDECAECAFGABGBHGDDEAEHA,False +193,13.0,11.0,10.0,13.0,18.0,18.0,16.0,24.0,BFHBGDBGHEFHEGEEGAAFHDFECFEAHEAHDFHCHHEHFAGEGCCHHEDHEDCCDAGGAGGBDCBDAFHFFAFDAFHGCHGCFGHGHHCHDBHBFFADFEDEBHGGFBADHAEEEHEEBFB,False +194,4.0,3.0,4.0,0.0,0.0,3.0,1.0,3.0,HCHBAHBAGFABCAFCFC,True +195,5.0,5.0,1.0,2.0,4.0,4.0,7.0,2.0,EFBGHBGABGADGABHAGDBECGAFGFFEE,True +196,16.0,12.0,12.0,7.0,4.0,7.0,9.0,12.0,ACGACAHFFCEACGGDEADCAGCFHBFBEFDHDBHAAAAGHBBHCBHGBAGBACBDCBHCBACDECHHAGHFHBGADFA,False +197,11.0,6.0,8.0,7.0,7.0,10.0,12.0,14.0,GHFFHACEECGEGGDBGBBFAGFGCHGHDGAEGCCBHCBHAFHAHDAFGAFADCADHAHHBCDFGEAHEHHFDEF,False +198,21.0,16.0,17.0,15.0,22.0,24.0,21.0,20.0,AEFABCDCDABGHHEHDFBBFCAGGAEFCGGCGABGACGHHGDGBDBBCFACBDFHHEHFCHFCECHFCHGEHGBFFECFBHFGHFEDFDCFCEAEEADDGDEGFEGFABFHBFAEHEDDADAAGAACEACBHEBFEDFAAAGGEGGBHEEHFEHF,False +199,3.0,4.0,1.0,2.0,7.0,5.0,9.0,5.0,HFFFEGEEGAHGBHGAHDADCBGGEEGEGBEGBFFH,True +200,27.0,17.0,26.0,18.0,16.0,17.0,15.0,13.0,BDEBEEBCBBCDFCHCCABDEGCGACGACACFGDDGAACBACEEDBDDCCCHCDFAHBGEBCHGGFCGHHHABHBGAEHCBGCDAEDFEFBEAHEAFFGDFHDHHDFDBFEBAAGAAGAGFCBCCEACEACECFAFAAFAADCFDAFDA,False +201,14.0,18.0,22.0,18.0,23.0,25.0,18.0,25.0,EHGEHCBHCHHAEHDEHDEAEBCEBCEGFAHFAHCEHBFHBHHBHEBCFADGHFGCFBAFBDHCHCEHADGBDFBFFBHBGGEFFFDFEBCDFDHCDHBECDEHECBECEFAGFCGCAGEHGEDEFHFCGCCDACAAFDAHDFFDBGDGAFGCBCDFEGFGGE,False +202,6.0,4.0,6.0,6.0,4.0,7.0,2.0,1.0,BADGAEAACFACGEFBACCEFCEFBDHDDFDBFDCF,True +203,4.0,8.0,7.0,5.0,6.0,6.0,6.0,7.0,EHAECAEHBEHBFHBCDBAEFEGGCFGDGHHACBBCGBDHCDFCDFGBF,False +204,6.0,15.0,10.0,9.0,18.0,10.0,16.0,17.0,EHHEDFBDFGDGEDGHFEEDDBGFADFCBHCBHFEEFAECGHHGBCEDCEHFACGHEGHEGCBGHBCHBEFFEHADBAGBGHCHEEBEAGEBGBHGBHCBG,False +205,6.0,8.0,4.0,6.0,11.0,10.0,4.0,7.0,BDFBFFCHFBADBGFCGCCEEAAHFAHFGFEEFBEAHEBDEBDFHDHEGEEBEHDA,False +206,7.0,11.0,7.0,14.0,12.0,11.0,11.0,15.0,DFFHFBABAHBEHBEHDHGCHFDFAGCGHEBADHGDHCEHCEFCEFGFFGHGCDAADGBBGDBGEBFEDHABHDBCDHHEFDEGDEDE,False +207,14.0,19.0,19.0,16.0,15.0,16.0,25.0,15.0,BHBBDBDDGDAHEGEGGECDCCBCDAEBGEDGHDCHFEHACACCEDCGFGFEGDGGAGGAGGHFBEGCEGCEBCAFGHEBHDAEGAFHHCADFBBFBFFDHFCHFBBGBBCBACGFDAFHBCGFCGEDGADEAHFCHBG,False +208,14.0,24.0,23.0,25.0,20.0,23.0,13.0,19.0,CGFHBECCCACGAFFHDFHDAHCCFBDFBCCBGFDAHDABGABGHBFHCDGDDHBHEBCEDEFFEFFEFFCDDGGECDEFDADDHEACEAHEAEEBFBFGBDBBFCBDCFDGFHBBDBCGCDAHDCCDHCEEFEGGECBBABDCBDEFEHHEHHBHBADFA,False +209,5.0,7.0,7.0,12.0,11.0,5.0,6.0,4.0,BEEGAGCAHCFDCAHCEFCAFGGDDEDCBDBEFBEDDADDHDDBBDBEEEGCEGHEF,False +210,21.0,21.0,29.0,26.0,25.0,22.0,25.0,25.0,HGGGCBGCBGFDHCEGCBADBADBDFHCBHDBEBBEHBEFBCABCACCFCEFHAFHGFGDDGDDHHDEDDHCBEDDEDCBGGFAADADGACHAFDBEBEECDECEFGGHECHEFHEBHEDGCDCABCEFGEGHFGHEECDBHDFDFGCAEAGEAHCHFAHDGHACFACGHHGDHGCAAEFAFBCBECGFCFFCA,False +211,25.0,20.0,15.0,18.0,16.0,31.0,22.0,17.0,GDHFDBEDFEFGAHDFFDBECFDAFDBFGBDAEGAEGFDCFDCEACBAFHGHHFBFFBHHEAFBAFDCFBGAGGACBACFCEACEACHHGDHGCGFHGHAGABGBGDFHHFCACEBHEDDAFDAGCADBEGBFGBFEFFEAFGCFBHFEHGABAABAEGAFDFB,False +212,11.0,12.0,15.0,21.0,14.0,13.0,13.0,22.0,FDHBAHAHFDBFDFCHHEFHDFAGBADBADCHDFFDABDHCDHCGAGFHDDHEEHBHHEHBCBGDGCDCDECDEGEBHEHHGHDFBCFDAGCAGCACCEFCDBGEBGEDEFGHCGHEDHEA,False +213,26.0,25.0,22.0,24.0,22.0,21.0,23.0,28.0,DGGABBFFGEFGHFBHBHFAGAHGECGEBAACCADCHDBGDHCDFEDCCCFBFAHDEGGBGECFEABGHDEADGBGGFDEFAABAAHAAHCAHGFHBFABFAEHHCHHCFBEEDEEFEGDEHDHHDHCBEABAGGAFGDFDCBCHBCHBHEBAAGCADCHFCFDBBDBCDECHACHDBEDHEFGADGHDBE,False +214,17.0,18.0,21.0,25.0,26.0,17.0,17.0,17.0,FEFAEAHHABBGBGGCDGDEEDAEBGFHHCADDHDDEDDEAFECGGAGGEBGBACEEDEEDHDDHGBHEBCBHADFEDEGGCDDBDCFCHFEFAHFHDBHDBHAGCFEFFEBEEBEEDGEACFABBCBFDBFHFECGHCGACDCCDCCECFHAACADC,False +215,3.0,8.0,12.0,3.0,11.0,1.0,8.0,8.0,ECHEGGEHEEBCEHGGHBAADGCHBCBBCHBCHBCEDFEGHEDCGCCECEBCGA,True +216,3.0,7.0,2.0,4.0,7.0,5.0,4.0,9.0,EEBACHABHEFDEHHEBHAFHFCHEDGEBBDFBHGBHGFDG,True +217,24.0,19.0,23.0,32.0,19.0,19.0,18.0,19.0,BDFHFFHEAGCGGEHGAHGADAEDAEGACABCBFDEDDEHDGDDEDDGCDGAFBBEBHFBDEADCDDCHBCEAHDBHCBHCACBGCGFCGFCGDHFABCACCABHEEHDGBFFDFFBHADDDCAAHDAEFEEFBDFADGADHADFGDCGCCBECADAHHCFDCGBEFEEDHBA,False +218,15.0,9.0,15.0,14.0,9.0,15.0,10.0,14.0,EDDHBDCEDAHHCDHCDEFECFDDBDEGDCAFCAGCHCFHBFBDFCABCEGEEHHGFHAFCABHABDAFAHBHHGFCGFHGBAAFDAFAAFEDFAGGCCGC,False +219,24.0,26.0,20.0,28.0,17.0,21.0,17.0,23.0,FBGGAGHAGHGGBGGFFDAFDHDCFBFFHFDHDDHFDHFHCFGDHBEFCEACHFEHCBADHDBADCEBCDDAGDAFDAEDEHCAFDAFDFBBAGBGHBCHAFECHDCEBBEABGFHEBHDGCEFCBACBACBCCBHBFGDADAAHAHBGDBDEBGECEDHDAEBAEBAEHADCDBC,False +220,10.0,6.0,12.0,8.0,3.0,8.0,5.0,9.0,DEDDFFBCFCCAGBFHBACAACAHFAHBEGGAGCDCCDFCDFCAHCACDHEHHABGDBHFH,False +221,18.0,20.0,25.0,20.0,16.0,11.0,30.0,25.0,BFFBEGBGFBGHBEFEDHBDCAAHAGHFGDADCBDBBDECAEBAHGHGABBHHBGCGECEECADDDGHDGBBGBCGHHGCHCCHCFHGGHAAHAHGAHGEHGDHBEGFHFAHGADFEGBDHFDGCDGCFGAGCCGACGHEGDCCCABCECGEHDEDDCCECADCB,False +222,19.0,19.0,21.0,28.0,17.0,28.0,23.0,16.0,FFFFGGBAGBFCDFCBFDGDDEDDFDEFCHDCHACAAFFDGFHCFBCDGEGEECCCBBAHHDEHDECFGGGDDGDDGDDCBACBABHCDCFDCEBEGBCHEFHGBHABAGFGFADHAGFAEFHEBBFBEFCGFHAFGADGAFHBCABDEDDCHFEHFEGAEDCGDFADBAG,False +223,23.0,19.0,28.0,13.0,18.0,28.0,23.0,33.0,GHBCHBGHEHEAHDHGDCFBHGCHGCFGCBGBGCDHEFAGHEGAABBHECFCFGDEHCEHAFCADAGDFGDHACBACHACHCHFBEFCFGCHHHHCHBCBEDBFHBEHBAGEACHACFAGGHGDHFFAFEADEAHFAHCCHEFGEFBFCBHDFGFFGAFDACDECECBEBFHBAGCHGCAFFAFF,False +224,3.0,2.0,2.0,3.0,1.0,3.0,0.0,0.0,DAADFBDFBCACFE,True +225,18.0,28.0,26.0,15.0,16.0,22.0,28.0,24.0,CCBGHAGAEGAFGBHGCHGBBBHBBHCBDDBFDFGECEECAGHEBBGBAGBFGCHCCDGCDHEAGCBBFBBFCBGGAGBDGHGGHGHHFHDCEDAFGHBGABHBEAACGCCHCCHBHHFFFFGCFHCFEDACFGEFCAAGDCDDHDBAABFACDABEGCEGFEHFEFCEDBFHBEHF,False +226,0.0,1.0,4.0,5.0,1.0,5.0,5.0,2.0,DBGCFGDHGFCGDHGEFCFDCFD,True +227,9.0,11.0,5.0,9.0,13.0,8.0,7.0,11.0,DGHBGEBGHACBAFHAFHFHDDHCGEAGEDEEBEAGFDFBDFBHFHCDHCEEAFBABBEEBEBDHADHGEEAC,False +228,3.0,5.0,4.0,5.0,8.0,4.0,5.0,8.0,DCEDEHGEHGFCEFGBDHBDCBDHFFHEAHEACGBGHAEHEB,False +229,5.0,2.0,1.0,1.0,0.0,2.0,0.0,0.0,ABABFACFADA,True +230,17.0,15.0,18.0,10.0,25.0,10.0,12.0,11.0,ECCHCABEAEAABAEBGEBCEBGAAGBBDFHDEHDEHCHHCHCEHEEHCGBAFCDEEFGEGGCFDEFBBADBEEFHEAHECGFCDAAAFBBCCCACBGGBAEDDEGDECCEFAEFAEG,False +231,31.0,18.0,29.0,27.0,23.0,14.0,25.0,29.0,DGBAGHGHDGCGACBADBDDEADFCHGDBFEBHEBHEFHFCDFCDACFGHDDDDDCGCEAEEADCBDBGGHCAACAEDACHEHHAHDDFDEHCEHCECEHHEAFEABCGEGABHEDHEFAGCGGCGACDAGDACAAHACBBCDACAACHCDHGAHGFBDAACEACECFEHGGHBGHBCFFGDBGHBEFEHHAHBAG,False +232,9.0,27.0,30.0,27.0,17.0,16.0,18.0,20.0,HDBHDCCCHHCHECBBCGCEDCHCADGDBBEBGEGGFDFDDGDBBFHCEEDFFFHFHHDGCEBCABABDEHDHCDHFDHFDHBDHGGEECBEHBDFDDBCDCCBCCGCAHDBBBBFBEHBEGBEDDGAAHCBECBCCBCFFEDFEDCCGBAGACGDCAFCGFGG,False +233,13.0,14.0,9.0,12.0,10.0,11.0,7.0,12.0,CACBADGHDGHDFHDFHDEEDGEBBEDHACHABBFCFAEHACFDCEAHEABFFBFEAAEBCHDGBDBBGCBFEAFGDCDHHABHABGF,False +234,27.0,12.0,19.0,20.0,14.0,11.0,16.0,19.0,DCEACEBHDGHAGFBGABGABGABCHFEADDADAHDHDGBFAECCBCHHFADFEFAHDAEDCHCHADBFDCGDCHECGAAAAGBAEEHGCCGEAGEFCDFDGGCGACHCEHCEHDEHBCADAADADDFHGAHBAHBAF,False +235,10.0,14.0,16.0,10.0,22.0,13.0,14.0,12.0,BCEFFEFBBGBBGEDGEABFACCDCCDHEGHCBDGHEEEFAGBHGBEEHEEHDEFDEFCECDECHGGAGFFEDGHBECBHCGFEAAEAHGBHGBHEBAFACCEDCACFDCF,False +236,7.0,11.0,9.0,8.0,13.0,11.0,4.0,12.0,AEBEHFHFFGFHBFHFAHBHHBHFEFABBEBAEFCEACHHDGDEGABCCBCEBDEDCEACFHCFDCHDEEDBGDE,False +237,23.0,30.0,14.0,18.0,17.0,26.0,17.0,30.0,DGDDFCEFCGCBBHACAFCEEEEAADADEHFABBADHADHFDBFHHFHDFDAFEADBADCAFAFBEBBEBBCBBCFBEFBGFBHBBFFHFAHABHEFHBFHEGHAAHBAGBGFHAFABEGEGGDCGBHBCHGHFGHGHHCDEFFHCBHBBHGEHGDHFDHCDBDAHGHBEAACFG,False +238,19.0,27.0,27.0,14.0,19.0,23.0,28.0,21.0,CCCACCFBHFGEBABBGFFGBCHBFAAFBAHCAHCBGABGADDABDAFDBCGECFEHBCHGHHGHEGDEBFBBCGBGHBGFBCCBDGDCHACHADFADEHDEHEGADGAFBFGBEGHFHEADFCCGCCGFCEFGHFEFBCDBGHHECGBCFAEBBCDGAGCAGFFEHGEGFEGBECHE,False +239,12.0,6.0,10.0,11.0,16.0,6.0,12.0,10.0,DBDGGDGCDECGHCHEAHGDEFEEFEBBHABCCDACGFEGHECAFAEDAHAGCBGAHGAGFABFDEEDGEHEECEDCEAHDAH,False +240,12.0,11.0,10.0,12.0,15.0,7.0,12.0,8.0,EHCEBGEBCADCDFCEGBEBCEBHDGAAGDGHDCFDEEGBEFEEFGEHGHBEABEAFCFHCGHCBADAADADGAEBBDDHDFGACGA,False +241,24.0,20.0,23.0,18.0,18.0,16.0,33.0,12.0,DCADHACHFFHADCCDEEDCEDCFAAFGBCGACGAGGACHBBDBCCBEFBGCDGHFECABCACGAEFAECBFFFHGCAECAGHEHBFHBAGEFGECGHBABCADDGGDGGDGGCGCFFHGGEAGEGEEBBEGAGFFGDGGBGDBGDCGHAAABGEBEBDDBDAA,False +242,2.0,5.0,2.0,2.0,7.0,2.0,2.0,4.0,EHCHBDECDEGFEAHHABBEBFEBGE,True +243,5.0,8.0,9.0,5.0,11.0,13.0,13.0,9.0,ECEEGBGFFHFBEFHFDBGDBGFHFFHGHCGHEACEABBFEEEEGCGGCFBCDCCEHCDHGAFGABGHFGAFD,False +244,8.0,13.0,8.0,11.0,10.0,14.0,17.0,10.0,EGDHGCEDHEAHFBCGBAABGEDAEDAEGGDDFDCFGCEGCGFADFCFEBBCBFDGFAGFEDFBGFGHBBHEDHGGHBAFBFHCFHGBHGB,False +245,10.0,16.0,19.0,10.0,13.0,11.0,21.0,15.0,BEEBGHAGHCCFEDFGFHBHHDFDDHCFAGFAHABFABGAFAACBECGGGHGCAGCHCEFGEHBEHBGFGEFCHDHHDEBCABDGBGGCGGCBGEBGDCCCCDCBDEBGEBECCH,False +246,9.0,13.0,8.0,9.0,4.0,11.0,15.0,3.0,BDDBDDBAGAEGABGEDFCBCCFCDABHCBGDGGEGCEFAGBAFBGGBGGBDFFAFBCGDHGHFFCFAGFAB,False +247,24.0,29.0,19.0,27.0,21.0,19.0,25.0,36.0,AGGDCEDBEDGADBCBEDBHDFHDBEFHEFEEGEGDEABEFHDBHBHHFFAFBGGHCFFEAFDABEAFCHDCABBBCBEEBFBGAGHBGHCABCAFHDGHCHHCDGADHADGFHGFCGDBHBCHBDAEGHHGHHAHCAHDDBGHBGCEAHGADDHDECGEHHEDEGFEDABHABHABCABDABDACHGCBGDHHFHFFGC,False +248,23.0,15.0,19.0,20.0,20.0,17.0,12.0,20.0,AEDAEDAEFADFAHFAHEEHBBCBBDBCAFAAGCCGACEHEADFHDFCDAHGBEFFEFDAFGACGECEHHGADGBCAFCGCHDDDGCFFDBCHECFEHEABEABDCBHFDHECAFDABDAGEBGHGEHDBADBADCHCHHCFHEEH,False +249,5.0,8.0,8.0,6.0,8.0,12.0,5.0,4.0,DDADDFEDFHACECHGGHCDBBFFBEEBGEBCECCGBEAAGAEBFCFFHFFBFFCF,False +250,9.0,9.0,5.0,9.0,9.0,5.0,9.0,6.0,EBGEGDECAEBBGBFDBACGCBBCBBFDADDACDGEDGHDHDAHEFHFGAEGHFGAAEHAE,False +251,3.0,4.0,6.0,7.0,2.0,6.0,5.0,5.0,FCHFEBDGHDHADFGGFGFFEDBCCBCCHGCHDBDDAA,False +252,23.0,16.0,22.0,22.0,17.0,24.0,15.0,22.0,GDGADAHGFBBFBCHBDHBDCCDHEGADCHBBDFHCGGCEFBECHECEACFDBADEACEDFFDFFDFCEFCGFCHFGAFADGAFHAEABFDEDHHBAAAAHGABGDBFEHFHHFCHDCEAEEAEDCFFAFHCHHADHACHAEDABDCCGGCGFCBFGEHBD,False +253,28.0,21.0,24.0,17.0,16.0,23.0,19.0,22.0,HBGAFCHGAFDHGAHGHGDDGADGECAACFACBDGFCBAHBHDBFDEFABFACAEGFHGBDGBFHDFHCGBAGCABEGHEFHECCEAEHADHFDCCDCCEAFBDDBFHHFGHFCHCDHCFFCBAEFAEFEEAAEBFCBAABAAHEABBAFBGCBGCBDFGAGCCDECAHH,False +254,22.0,21.0,35.0,22.0,18.0,16.0,18.0,17.0,CGFCBBCBBCFBDHEGBFDEHCCAECAHAFDEEDAEHAEBCHFHBFHCHBGEACCCCDCABFABCDBDHCGCCGDCDDADDGGEHFEGCCBCBAFDEFDAADFAGGHECHECHECHAHGCFBBBBAGGEDBFDAFDCEDCEDCADCBHEFCAGCAGCBGFDACAACGGH,False +255,16.0,23.0,16.0,16.0,20.0,17.0,25.0,22.0,FBDCDGFHBEHADAEBABHAGDEEDGEAABDDEEFEEDBCGGDHHDHGDABBCBBCDHCDBGDBGCHGHAGFECEEBEHFGDFACHGHHGBHCEHCECABHADHACFBBAEFCEHAGHGEHGFHGFGGFGBFBFCBGCFGEFGEHBBGFCAFGAB,False +256,4.0,5.0,1.0,1.0,3.0,4.0,5.0,7.0,BHFAGFAFHABDAEHHGHHGEGBEGBCBHF,True +257,15.0,16.0,15.0,21.0,14.0,16.0,23.0,29.0,BBAHCCDBGFHGFGFFCFGCGHCGHDGAGHDCHDEABEBGGFDDFHDHHGHBAHDGCAGBGEBHBCHGEFGEHGEBFECHEDGEHBAHBEHDACDHHHBCHBCHAFHDCHAHGAGGDDBDDEACBAEEAHDDFFHGFHFFDAEDACDFG,False +258,25.0,18.0,28.0,20.0,16.0,20.0,26.0,30.0,GBDGBHAEEAHBAHBCHCCHCEBCECDEAAFHHCGGCFFDFBAGBHGFHDAHBACCADCAECAFFAFFGGEGCEACECCFCBEAAGFCFFGGHCDECBGHBHACAAFDGHDCHDCFDHFEHFDGDGHDCHAEADGGEADCHDHBGBDGAGGFFHHFHAGHCHHCDBGHBEHDEHGABBADBCG,False +259,10.0,4.0,2.0,8.0,6.0,7.0,4.0,6.0,BFAHHADDBDEBDAHFACEADEFDEHDGAGFDGFAEFBGFEAACHAH,False +260,17.0,18.0,20.0,22.0,23.0,26.0,23.0,18.0,CGCHEEDEBDHDGEGFEFFCAHGBHBEHBACAAFAFFDBFDCFAEFADFAEGBBHADAGGHFGCCGCGFBDFEEEEADHGDCEDFGDEBDHBGHBFFCAFCECGEDADDBHGBECFEBFEDFDDEGDHCAHCFFGFFGAHCDHADCBECBHHBHCGFGGABGCEGFE,False +261,27.0,24.0,20.0,19.0,30.0,32.0,21.0,26.0,GEHGECEEBEDACCACGBFGFCDBHEFEEFGEFBFACFACFAFFAGDACBAGDEBABFAEDAGHAHBAECAFDFEEBBBFEBDEFCHFHBFHFEHDGHBGHCCFDDAADEAEECGGHGFECFEDFEAFACHACEFBEFHHBHHFEAFHBFBBFBHFCAGHHFHHGHDCHDCHFGAGDDGCAGDEEAGEBEDAGHADBBB,False +262,24.0,26.0,23.0,23.0,21.0,23.0,28.0,24.0,CFDHHBBHEEHEHHEFHBDAADAFDBCDHDDFGAFCACEADGBEGCGCHEAHGADGABGADCFFBFEDDAFDCFHBBCFBGDGCHECBEBBCABDAECAHAHHAHEBHDHHFAHGEBEHFAAGBAGBGGCAFAFBAFBDCDCCDGGDGBHBBCBGFGEEGECGEHECDFCBFGBDGCACEFGEGGFHGFDGF,False +263,0.0,1.0,9.0,1.0,3.0,4.0,6.0,1.0,CHCCEFCGGBGFDGEGCECCFCFGC,True +264,6.0,5.0,5.0,2.0,0.0,4.0,6.0,0.0,CCAGBBGDBGDBACACGAGGFFFAFBAC,True +265,4.0,10.0,10.0,7.0,1.0,8.0,4.0,4.0,BEFBDFGDFABCABCHFCDGBHBCAFCAFDBDBGGBDFCCBCFHCDHC,True +266,22.0,29.0,31.0,16.0,20.0,28.0,16.0,14.0,EHAHCBHCBECFGBBCHEEBAFBHHAFGBFDBFCBFCBFCBFCGFGECBBGFCEFBEFDEDDGFCFCAGCAFCEGAAGAACDCFGAFGAFHBGABDAGAHCAECABBBCFBCDEAAEBFBBFCCFCCFABFDDFBEHBFGEDBEDEHAECBGCFHCDECACCDEFDADEHCGDBHH,False +267,19.0,18.0,7.0,10.0,13.0,13.0,13.0,11.0,HAHCGEBDCBCBBEGHFGBCGAAGBGGFDGCAEADBAHBFEFFEAGEHCHHBAHAADEFGEAGFFEFAEFCBAABAABEAFGAEGDEDBBABBFBHHDDHDBFD,False +268,17.0,10.0,10.0,7.0,8.0,5.0,14.0,9.0,DCADHDGHAGBAEHECHCGADHCGAEGBEGAEGAEGACAHGHDCBGHBGFBCAAAACBBEEBGBCFCAFDAFDHFGABGA,False +269,1.0,3.0,0.0,1.0,3.0,4.0,3.0,1.0,GHGGEBEFBFABFEDF,True +270,23.0,19.0,18.0,18.0,15.0,13.0,11.0,15.0,AHDAFCAECAFBHBCEFDEFCEFEDAADBADCDDFDAFGEHGEAGHADBBEACFGBDHADGCCABHHGHFBEDGHFEACEFCBAGAAEABEABGABHBEABGABFCBACGDDHFCHBCHBHHCEDCDDCDBC,False +271,7.0,9.0,4.0,6.0,4.0,10.0,14.0,6.0,GDDGADGAHAAHABDGFFFECFBHBEGEGHEGDCABGGFFHFFHFBGABGDBGCBGFGCB,False +272,9.0,5.0,1.0,2.0,6.0,2.0,1.0,1.0,EDAEAFECFGHAABAEDEBBEBAABAA,True +273,6.0,7.0,5.0,6.0,3.0,4.0,5.0,6.0,DBGDAGHAGECGFBHFBGDDFEDFHCBBEHHCAHBACBACAD,False +274,13.0,30.0,20.0,14.0,22.0,14.0,15.0,16.0,HBGBBDCBAHEFEBDBCABCGFGEHGECGCDECDBFDECGHBFHACDCBBHEHGGHFGBBBBHBBHBBGBEABHDBGDEGEFDECCFHEBHEHGEFCFBCFCDABAAHEECEECEDCEDGEBFEBAABGABCBCAAFDAFDHFC,False +275,5.0,8.0,10.0,12.0,2.0,10.0,10.0,5.0,HGDDCDFCDBGFCGDBGEAFACFDBDDBHDBCDCCFGCHGDFGCFDABHGBAGCGFABFEHF,True +276,5.0,1.0,0.0,3.0,1.0,2.0,0.0,3.0,BDDHFAHAAHAFEAD,True +277,24.0,23.0,18.0,24.0,16.0,33.0,19.0,28.0,ADCABCHCAHCAHEADEAHBGBCGFGFFGAFBDFGFBGDEGDGHHGHHACDDGFFAFFBFFEFADHDDADDFFAFGBFBBFHFCHBDADEAHECEDFDGFDFFDCBBHDAHBBHCEGEBHHBFFCCHHHHCHBBHDHAGCAGEDEHDGHDAFAFBBFABFAEAAGABGFEHCCBCHECFEDFGFE,False +278,12.0,29.0,23.0,26.0,19.0,18.0,23.0,13.0,BEBBEHBCAFAHEDDCDBBDBBDAFFAFCADCGGBGGCGHCFECEBDECGEHGEADBFDHFDGCDGCBCCHDBEABDCBDEBEEBDCGECBDHBEHEAGAFGHFHEFBBDBGEBFHGGHFGFDGCDGDDCFFFDFECCGCGGFBDBAACHEDBDDBGCAGBBC,False +279,16.0,11.0,17.0,16.0,19.0,22.0,19.0,14.0,GFAAFDCCEGCHGBEGDABFBDFEFEEBEBGFCGHHHFHAFDADEAHACBFCDFHFGCDACDFCGFEDFEGADGAFCEHCAHBBHEGCDDHDCAFCAFGEEGEEFBEFEHAHFDEFDBGDBGAFCAGCGGCGHE,False +280,10.0,14.0,13.0,11.0,22.0,14.0,17.0,12.0,EHCECEHBFGCGGCAHCDGCGGEDBBBFHCFBFBBFGHGHFABEAEGACGACBFDBCEECDEBFEBDGHDEBEGGECGEHGEDEEHFEHFEGFAADGADEHDAFDHFEEFCBA,False +281,32.0,31.0,18.0,18.0,36.0,28.0,25.0,12.0,GAHFABEGCGAEFADGADFABCADAEBAEFEHFGBGCBHDAHAABBBECFEAEEFEEFEDAEBAECADCDDBBBCBBEDBFAAFHEEGFCGEEGEFGEFAFDABCABDAFGFBGFEGBEACGGHFGAFHBBDEEEGGBHGFFAFFGEFGEBGDCHCHGBBGABEABEFEDADCEEFDCDHCDBGABAACAHCEFCEFBEB,False +282,19.0,24.0,17.0,28.0,20.0,14.0,18.0,11.0,CEGDBCDFGFGCADCEEGFABEDBDBBDEFDEADBGBEGBACDDFDHFBHGGCGAEGHEGHECDDGDFGEFABAEEHDFBDFBEEBHCDCCEHHDCGDBHDFDDADDEEDBBBBABHAHDABAAGADBCFBCBECDAGECGACGACFABFA,False +283,26.0,21.0,30.0,21.0,22.0,23.0,22.0,14.0,ABEAFHABHEFEEFBHDAHFBHFBAFBCBGGHGDHFDHFBEBBACCAECAECACGBCFFEFCEGGACBCDFAAHABGDEGDEGDACFEGDEGAFAACCBEABGAFDCFDFFGACHCEGCFGABCHGAHCDHCDCCDCGABDFBDEDCGFFBFEACCDCHDGGCGEEAEBAGDCDDCEEB,False +284,14.0,18.0,15.0,12.0,15.0,14.0,12.0,12.0,DHBFHFFADGAHCABFABEEFDEAGEAGDDBACBCCBGCBEEBEAHEHCFFCEFCBCGDCGDEGHGGABADBEEBEHCHHDBEGGFFEFDADHAHBBDFBCCBGABCFHCFA,False +285,16.0,15.0,17.0,12.0,11.0,20.0,18.0,11.0,HGHCBHCECFEHFEGDAFFGFEGFEAFGFBGABDBBGBACBGFBECAAFDAHHFGGAGGAEGCBDBBDHEFGGDGEHAHADEADEFCCFCFADDBCCBCABHAFFCFGCFDCFACDBCGH,False +286,11.0,13.0,7.0,7.0,10.0,17.0,12.0,13.0,FDGFDGFHABDDHFAHBHFFGCFHBGAGFFGFHHAGHEGHCGBCECDECDBHBEHBEHCAFGABAFBGFBEFGEABFBFDEFAEAHEABC,False +287,8.0,6.0,3.0,14.0,2.0,6.0,4.0,6.0,BGDFDCCDGAFBADBDHHDHCDHAAFAADBADBFDEFABDGHEGDDFHD,True +288,13.0,9.0,15.0,13.0,19.0,11.0,16.0,13.0,GGEDADGABGCBHAGACCFCHECDDCBAFEEHEBBEABEACFACEDHEAFEGFGDAEAAECDEFEHHEHBFFDCFDCDAGDHEBHCGHGGHCEFCGFEGEDGDCGHBGH,False +289,21.0,24.0,27.0,24.0,13.0,22.0,21.0,28.0,EBFBBCGBDHCAHFAHBBHBDHBDHADECDCAHCGHGFHADHDCHFBBAHBDHECABFBFFCDFGDFECBECBCHEAHFHHEHGGFAGBDCEHCFHCGGBEGFHBFGAFCADDFDDBDFCAFCHFDDACGACGDCGAGGHDEDECDAGHBFABABBEFBCCDEAHGAHGCCGCFAHDGHC,False +290,11.0,5.0,20.0,12.0,8.0,15.0,4.0,7.0,CBCCHDDHADEADEFDAACCCFFDFCAFCADCGDFEDCECCECFFHFFAGFCEDEBFFHCHGCDBHGCFDAFBAEHACCACB,True +291,20.0,16.0,14.0,23.0,25.0,13.0,17.0,18.0,GBEGBEGFEGFBFDBFDBADHAFBDFGDEGDGGECCECAEAADAACHHHHBHEGDADDBHAAAEHEBDEBGEAEHDGHAAHFABCEGDFGFCECDGDABDHBDECCABFBEEDEGFEHFEHGAHBDCDAEHAECDCFDCEDHGHEC,False +292,22.0,21.0,19.0,22.0,30.0,26.0,23.0,31.0,AHGAHGABADGFGGEEAEFDCABCFBCGBCBHCBCFEDFEDHADEFDFBHCBHAHEAHEHHEHEBGEAGEDCEHGACGDCFCEFDEBDEBDFHACEEHBDDGGEBCEBCGHFGEABFAEEBHABGAHGAHDHHDHEABEGBFAEGHEHCADFFDFGAFCDDGFHFFGFFDEBCHFEGFCDFHHCHFBEGHHADH,False +293,16.0,24.0,24.0,18.0,24.0,17.0,14.0,18.0,BDDACEACHABHABHECHGHEGEEFCHFAFAGFBBBGBEECEEHEFDBDDBDDGCGBCEHCEDCBFABFBBCCECCGBEBAABHECEGCEDDECFECFHCFHCGBCFFDDFADFAHHCGBBBCAFEBHGDGADGAHCBEAAFGDBHHEDCEDFEH,False +294,32.0,23.0,12.0,12.0,9.0,21.0,14.0,23.0,BCGBDHDCGGGDAFDFFBCABCABCFGGFAAFBHEBHGBGGDAFAACABHBFFDAFAHHBHHDHGDEADBHGBHBBHBBFACCBECAAAHABHAEAEDFGCCEAFFHEBHFHHEHDABAAGAGHADAAHAACEAHAAFFBFFBFFH,True +295,25.0,28.0,34.0,29.0,21.0,15.0,21.0,21.0,GBBDDFEAEADECDAGBCFBADECDBBDCCGCAGCDBCBBCBDCBGCEHCGACACFBHFDDBCHFCGAGGECFFABDEGDEFDHFHHBBHDAEDBEDCDDCDDCDAADFACEDHHGACGBBGAGAEGFGGHCACCDHGEHGEHGHCEACBHFEAAEACEACHHCHBCBECHHFEBBDCBFCBDDBDABAEFAHG,False +296,10.0,5.0,3.0,10.0,3.0,6.0,4.0,2.0,FCDBCACHBFABDAGEAGDADEBDFDAFGABAADEADHGDFFD,True +297,18.0,24.0,24.0,26.0,29.0,26.0,24.0,26.0,HAEHBEAEEHCACDDCFDHFGCBHCBCDHFDEADBBGCBGABFAFGGHGEAGDBCCGCBDFDDFBEFBEGDEGAADHADHBHADHCDFEFFEGGEBAHBCFGCEGEBGBFGEAAEDHFDAAGHFGEEGEEDHECGEDFEBBDCCDBDECFCBBEFHFCGFEHHEHHAGHCEHCDFCDFCDHCHGGHFEFFBFHBADB,False +298,13.0,9.0,11.0,21.0,12.0,21.0,9.0,8.0,DDADBAGGAGEAGECGEFHFCCFBCABCABHAEFABFDFCHHDDEDDHADHCHABFFFEAEDCFDEGGFDDFCDFEFFEDFEBADFDDFBDFCHBGFCEDDAFG,False +299,9.0,10.0,7.0,5.0,4.0,5.0,9.0,5.0,AEBFBGFGGAGGADCADGDHGHEBHBBGEBGFCHBCHAAFAABCECCFDDBCAB,False +300,9.0,10.0,14.0,12.0,10.0,5.0,22.0,10.0,GBDGFGGEGEHGDGGEGCCGACBDBBDABDAEFABBCEAEHAGCFHDGHGGDGADGHGGBFCDHCDGCGBDAACEHCEGCEGDHCHECHCBF,False +301,23.0,15.0,14.0,8.0,21.0,17.0,19.0,20.0,FGCEGAEGEDHEDBGGECFFHEBBBFDAHHEBAEBHCHEGAAHABEEFEEFGBHGCHCAHDAFGGHGDHGFAGBABFAFHEEGEAAEDAGFAEFACFACBHFDCEHBAHCAHGAHCCGCCGEAGEACFADFHBBHBF,False +302,27.0,23.0,30.0,20.0,17.0,18.0,24.0,20.0,AACCCBGDBFHBAECFFHBHHGHAACGCHDDBFBGGCHGAFGAGGAGGAHGCHGCDGCHBHABFDBDDEEDEEDBCFCCFCHBHFBAFBDFHFBAAAFCCGHCDBADAFCABEACGBFBEEBAEHAEGAHGACBBDACDFCDGCDGHDEEDEBCFFCAACHECGCBGCEGCDAAEEHGD,False +303,30.0,27.0,22.0,22.0,20.0,20.0,25.0,21.0,FCHFDBBDBGCAADEBGFBGABGFEGHAHBADAEDACBECFFCFFGDBGAHHAEHFCAFAACEDCFFBEFAEABHDGAEHDDBGCBGEBGEAEEFBEBDHDAAACCHCCHGDAGDFCFABFHBFHBGBBDHBDHEEHECHDCADAEDGBCCBAGEHGEBGFBGCCACCAGAADAHGHHGFDABGGGD,False +304,29.0,17.0,17.0,22.0,14.0,23.0,28.0,17.0,DABGFCFHAEGAFGFBCCBEDDHFCADEHDEHGHDGADGHGGCCFFFFCCEGHEGBDDDDDFDFGDFGCEABADBCHADBGDCDAHFFBGFGGHAGHAGAEGEGCAAHAAGAAEBAGBGFBHBBHBGDCGFCDFBAEBHCFEAAEAAHGAHGAGFACFDCFEAFDAB,False +305,11.0,12.0,13.0,10.0,10.0,17.0,17.0,13.0,BFDDADEGGFGEFBEAGHAGBACAECAFFBBFHBCHGFHGHGFFGCFCBBAGCDGDDGCGHCBHDGGFHFFHGDECDFCDEAGFAFBAECAECHBHHEHCEBF,False +306,7.0,10.0,4.0,3.0,5.0,2.0,7.0,5.0,BHBHADABBABGABHDGHDBCEFEEFCEBCEHGGCGBAABGAG,True +307,17.0,17.0,13.0,19.0,19.0,19.0,22.0,12.0,FDEAAHFFBFBGFBDFGDFGDBGDBGFBFFHFFABEGGGHAAHEAFEDFCBFCEDCDAGBAFBGHDHCGHGDEGDGCBBDHGABCDHCFHEGGDBCHECEECEADEAEGAGBAEEDDEGCEGCHACBAFBDEDAFGAE,False +308,16.0,19.0,32.0,19.0,25.0,21.0,28.0,24.0,BCGCCBFCFGGDHGDADAACACGGBADDGDDGFBCHHCFECDGGAEBAEGHCDBCHEEHAEHFEFFEGFEHDCCCEGHFHHGBGDEGFHCFBFHBGEGFCGFCBHGBHEBEEBGBAGEEGHEAHEBFEBHCBGGDGDCHCCACCADBAHEDFGCACCHHCHHFBAFAEEDCECCDFCDFCDFEG,False +309,12.0,7.0,7.0,14.0,8.0,9.0,9.0,23.0,HFHHBHGACFAHHHHHDHBGHCEHEHCFHCBHDAHDAHFGDDHEBGFDDHADHBDGEEGDACDAHDAHCGHAADAECBEGEFFAFBDFG,False +310,7.0,9.0,2.0,2.0,5.0,3.0,5.0,9.0,BBABAGEAHBGHFEHBEHBHHAHBEGBGGBDACFCHFDHAAE,True +311,26.0,28.0,24.0,21.0,11.0,21.0,26.0,17.0,BFBEHBHGFHFHDDGADGADGFDCFBCHGFAEAAEAAEAABDDGHDBEDCCGFCFFCBBGGBFHCGGGDBGDBDEBCFBCABGDBGDFGEGCCAAHBGHGGFFBAHBAEGCFBCECHFADGGCECCFCBACBGBBGCCDAEHABFADDADDAFBHFCHAAFAABHHCHBCDBGA,False +312,23.0,13.0,12.0,13.0,21.0,13.0,8.0,13.0,FBAFBAECDHHEEEEAACADHEDAEAEFAEFAEGAEGAEAAEAGGBCDDFHAHHFFHFCCACAEFAHFAECHEAEDDHDGBBCBDFEHEAHBAHBAGCCDDDFGEGEFBBDBBCCB,False +313,3.0,1.0,2.0,0.0,2.0,1.0,1.0,1.0,HACAACEFGEB,True +314,19.0,17.0,14.0,10.0,16.0,21.0,10.0,13.0,AHDAHEEFAEAGCADFEHCEBCGCCGADDADFADFAHAAHFEHFEHFEFFCBFEBAAHEHBEBCCGHEBHCBFCFFGEAHEACBABBABFFGFFGBBBFBGDGCCBEDADAFBFFCHEDG,False +315,3.0,8.0,4.0,7.0,12.0,10.0,4.0,14.0,DHEDBEDBECHEFFFCHDAEBAHHFHFEGFECEEDEGHBGFBAHBHEBEDCFHHFHFDHGBH,True +316,19.0,13.0,26.0,20.0,13.0,13.0,16.0,14.0,AFCBGBFCAFCEECHBBAGCDGCFGHEBHEDCCAHCFEAEDDEDAGCAFCACCADCGDEBFAGDHGDCBACHAGHBFHCGECDCAGCADADFGDCGDGEDFADCADFFDAEDHCCHCBHGBHEBFGBCABHHDE,False +317,16.0,18.0,21.0,25.0,22.0,16.0,21.0,17.0,GDDGDDEDFEGFEDEEDHBDHBCHDHBBBBBBCCBCCHFCHBCHEHADGCDGCBGAFABCEDFFAEBCHBDDEADCGDEFAEGAGCCDCCGFDFBDHCGHGAAFEADAAHEBHEAHFCCDCEAHEAFGBGEBGDGEFGFHGEHFAFDGEDGECEDG,False +318,23.0,22.0,20.0,24.0,12.0,20.0,16.0,25.0,AABCHBFHCDHCGFGHDHHFGAGHBGHBGCEECAEHGBCGDDDHCFHGBHGBHEBHDCCAHCAHAHCAFCDFHHEBDDBGDGEABBAEBCDDFDDFEDFACFABFCHHCHHGBFAEFBCGBDHFDBFDFDAADAFDCEHCBBDFAAAAGECDABDAEFABFG,False +319,9.0,5.0,11.0,3.0,6.0,3.0,10.0,12.0,HABHDEGCCCDFCBHCHHGHAGHCGHCDHCEGCGCEGHEAHFABAECGBBAAFGAEHAG,True +320,31.0,18.0,28.0,29.0,18.0,25.0,23.0,22.0,ADEFDADBAGBEGHEGDCAHAAHCFGCHGFEGFHGCGBFDAFDCFCEBABHDBAFAFFDGDAAHABGGCAFCACCDEBDCCGCCDCCAFGGCHBDHGCHAHBBBBBCCGAADCBDEFDHCAHCHHFHAECDCHDGHDEADEDFADBADEEDGCBGCBGDGEFHAFEAFAAFGEEDCFDHFAHFAFFAEFHEDGD,False +321,11.0,11.0,8.0,16.0,26.0,18.0,18.0,26.0,HFGEAHHHHDBHGEHDFAGGDEFDEFDEFAEFBDFHDEEDEEBGEHEHHEHACGGEBHEGHEFHEHAEGFDGDDGBCEAEGAECDHCGHFEHGAGFCHHEHHFGDFEFFHBFABHDGFFBCEBAECGDABDHBC,False +322,6.0,3.0,4.0,2.0,1.0,1.0,3.0,2.0,CAAFAEHAGBDHCDBCGBAGCA,True +323,10.0,11.0,20.0,18.0,16.0,14.0,16.0,14.0,FCGBEHDGCCHABGBCGACFEFEEFEDCCCBGCFHCDAGDAGDEDFHGBAGEDFECGACGEFGEFEHCDHCDEFHGBHGEFDEFDEADBAEHFCBGCHDCHDCBDCFHBDABGAHDHCD,False +324,14.0,16.0,12.0,17.0,15.0,23.0,16.0,14.0,HDEBDGFAFHDDHDHECHEBHGHEGEGFADHGEFGDFBCEBGAFFAGFHBDHGDCGDCACFECFEHFAFBCEHCFBEFCEADHABCBBCFBAFAGFAEEAGBBECBDGBFGHGBFDDFDDFGAFDAF,False +325,15.0,13.0,7.0,9.0,15.0,10.0,11.0,11.0,BDABDCBEEECAECHCFHBBHDHEAHEAGEDEABEDHEGGFGGFEFBEHEEFBHAAAAAADAADFAEFGHHDFHGAGBBBBCDCGBFGFCG,False +326,18.0,22.0,21.0,20.0,18.0,16.0,22.0,11.0,FAHEBHABFAHGAEGHHBBBCBGCBECAAGDACFBCFEHGDHDDCDDFFCEGHEBHCFCDFCDGCHBAGCEBCBDGBDCBDHGEFADGEFABFGCFCDBCGACGABFACDEDEBDAFAFFABGEBGEGEEDEGDAGAGGEBGCBDCED,False +327,13.0,17.0,20.0,5.0,21.0,19.0,14.0,10.0,CACCAECGEGAFABCCDFAFFHFCEFCHAHBGEECEECGEFDECDECEEABFBEAEEBEDHCAHAADBABFGFFGFGGFBGBHEBHGFGEFBBGCBCCBCBECBCGFEHFHBGHACEFF,False +328,21.0,20.0,17.0,13.0,23.0,15.0,20.0,19.0,HECGCCHADAADGADBEGBEABEHFGFGGFGCBECFHBAAEAHDFHFFBGEBGCBFHAABAABDCBDCAFAAHCGDCGEEGHGDEGCHGHBFHDHCDBCFEAGCAHCEHEEFEFBDHHDEBEEDEBGGAHGAHBEFBECEFABGABEC,False +329,24.0,23.0,29.0,30.0,30.0,21.0,23.0,19.0,HADHFBHFEHCEHDHCDFCBABEEBDEHDACBGDBCDBGDBADCCDABAGCEGBDGBEGCDFAFFGEFGAGEAGEADCGHGBDEDAADEHBAHCAEGBGFBFHBGEBDBBAEEDEEFAEDGCABCEDGFFGECCDACHBDGBDFCHECHECEACEADDDEDFADFAFHCFGCADCEECFCCFCCAEBGGHHCHFDHFEG,False +330,7.0,6.0,9.0,9.0,7.0,8.0,16.0,10.0,HGGAAGEEFBEDHFDAFBAEDFGHFAHGDHEECGHCGCCACGFGHFAHEBHCGGCBGDHGDCGDCGBGDBDF,False +331,15.0,22.0,24.0,18.0,22.0,22.0,16.0,24.0,ABAFBECDEDAHCCGCAAHHCHHGBBGBAGBDGEDEHAECACBBFHHEHHEHHFHDCHDCBGFHFFHAEBFEFGDHAECEECBEFEGCCFBCGBCDEGHBGHFAHFGDBGEAGFADCBCCHCFFDEFEEFBEFHEHDCDDBHDBGFAFFBCCBCFBDADCGDE,False +332,9.0,18.0,16.0,12.0,7.0,14.0,10.0,14.0,AADCABGADACDAEDCHGCBFHBFHBEHGEFGHGECFBCDDGDAECHBCEBCFBCHHFDHDHHFFDFBGFGHBGECCFDFHDBHGBCFFABBACBCBBCB,False +333,24.0,10.0,12.0,14.0,8.0,11.0,24.0,18.0,AHAAHAADADGFHEEGBECBDCEACAHEGHEFHADAADFHGBHGBGBCGAGADGADGAHCAHFHFGEGGBACDCCDGFGBHCFGAFGBGEHACHAGGCDDHDAADGHDGFCGAHBAHBGFF,False +334,17.0,19.0,16.0,21.0,12.0,28.0,7.0,21.0,BCEAFGACAHCFEBBDBBDFFDBCDBFDFFDHFABDGBDFFGFDHFCGFGHCBHAFCEFHHBHHAHFADFBFCBFCBDCHEHDCADFDDEHDECDFCAFAAHABFBDFHFCDGHDHHCHECBEAEHAEFABDEFAFBGHEA,False +335,5.0,1.0,17.0,8.0,5.0,13.0,6.0,9.0,HFEEFACCHDCHDCHFBHDDCACCFCCGCFFDEFAFGCFHAEGFEGFDCCAFCHCGDCGDCHFH,True +336,7.0,5.0,7.0,10.0,4.0,6.0,4.0,9.0,CABCEBDDFADCAFCFGCEGEHDDBFGBFHCHHGHHDFDEHDAACAADHBDH,False +337,17.0,14.0,20.0,15.0,14.0,12.0,26.0,25.0,FEFFADAGDAGFCHHBHHBAFEECECAFCDFDDGGCHGCHFCGDGGBBGDAHDHECHGCBBBHDEHCCHFGHFCHBCHDAHCAGCAGEBHEBAAACEECEGGDHCEBFEHGHCGHCGDABAGHGGBBGFGGDGHHEHDDAAGA,False +338,17.0,17.0,8.0,23.0,13.0,10.0,15.0,13.0,DFFDBGEBEBCDBFDBAEEAFGAHDDDBBDEBGEBGBAGBGBCGEDEAHHADHDDHEDHGGHADDBDHHDCHDAGAECADCHDFBBFABDAFCAGDFFCAEGAEGEFGBDGCHAHA,False +339,18.0,24.0,23.0,25.0,16.0,22.0,30.0,24.0,DGBDGDDCDGCBGFEHEAAFCACGBFEBGCGCABCAFAGEAGEAHDCHBFEGHEBDDBDDBGABGFDGFBHCAEEAGDHEHFEFEHFGHFBFFGCAGCACCDHDDHBDFGDFGEEGBFDHHBCHDFFDCCABGBDGECBEGGGHDCHACHBHHGGHBGABDABHFCHFHHDBABGFCGFCDC,False +340,2.0,2.0,13.0,7.0,3.0,3.0,2.0,4.0,ECCCDCCACCBDCDFCDGAHHFEDFBDCDCCHGCHE,True +341,4.0,3.0,4.0,1.0,4.0,2.0,6.0,4.0,GAEGBCHBCFGAHGAHBACEECEGHGDF,False +342,10.0,14.0,13.0,18.0,10.0,15.0,4.0,7.0,BFBBADBAGACCABFAECCFCCEDEHDABBAFGGBDBCEBFDBFDEHDGHFAEECCDCCFHBFDEDDFDDCDDEHDEFFBDFBDFACHAFH,False +343,2.0,3.0,3.0,5.0,8.0,5.0,2.0,1.0,EAFDCDDCHEBFEFDEFEABECBFGEDGE,True +344,16.0,17.0,10.0,12.0,19.0,14.0,18.0,24.0,DGDFEBGECFCBBGFFEFHEHBEHGCBACBEGFGGHCBHGBHAEFBFFBHHBEHAGAADFAGFAHFAHGACGAEHABFGEGHEHHEHCABDAHEABCDHGEHGAHDDHDDBEFBGDBADGCHECHDHEEE,False +345,12.0,6.0,8.0,11.0,11.0,7.0,6.0,8.0,EEABBCDDGADCAECADHABGABECBECFEFFECDEGHAFHDGHFHAFAABDAHCEHAEHFDCDEGDGD,False +346,14.0,12.0,14.0,18.0,13.0,23.0,16.0,8.0,ECHBFBAFEFGCCDDGFDBFEGFEAFECFEHFEGBDDCHDHAAGAAGFBDBGDADDHGDCFFHEEHCEBGDGCFECFEBFDACDFGDAGDGGCGBABDCBCBAFFAFFAFEAFDHFCG,False +347,13.0,9.0,9.0,6.0,6.0,16.0,14.0,5.0,GEACFCDFGAFGAFCFFDDGGDBGDEGBAAHGAHFFBFFEEFBFFBFCEGBGGCECCAAHAGHAFAAHACGGFBCBBD,False +348,2.0,2.0,2.0,3.0,4.0,6.0,4.0,5.0,EFGDDADHEFBAFECFECFHBFGGHHGH,True +349,25.0,25.0,26.0,14.0,12.0,22.0,23.0,17.0,GCCGCCGEEDFADFDCCEHCBHCBGBBCBFGBAGFGHBGABFAGFBFFACCHHFHABAABCABGHEGBCGBFFAFGACCDDCBFGFAAAAAEACEFCEFCADCAGHAFABFDGADHHGBBCHGEBGCBHCBFDHGHHCEHBBBBEFAFHDDGFDCAGCAGDEDE,False +350,26.0,15.0,7.0,12.0,18.0,16.0,17.0,8.0,GFECAAAAAHFADABEGCECDGDAGEABEGBGBBGBBGCHEFFDFFAAAGEAFBAGDHHFGGAGEADFAEEBEFCGFDDFGDFDBFBEHHAHEAGEABEABEBBADAADAFFCEGCHAE,False +351,19.0,24.0,27.0,20.0,25.0,23.0,28.0,19.0,HHCHFCDGDBGDFGCBGDFGBFEDFBGABHABCABGBGAHGBHGBABCCEEBDFGDHGDBGHFGCFGCBHFBHECGCCBCGBFGACGDCHEEDFBGABFAFFGHDAEAAHDAFDEFDEDEECFEGHECAGCECCFCBABFADCAEGEDDFHFECFEGABGAHDHECBACDGHEEEEHECBECGFC,False +352,11.0,14.0,21.0,19.0,18.0,15.0,12.0,19.0,CGFBDFCAEDFEHEHCEACEAEEFGDAGBACBFCBFABDDGHDEHFGADGHDHCBHCEHCDHBBEFGFBADCGBHEADECDCBDCBACBACBDCHFHHCHFDGCDECGHCEEGHEHFFFFGEHDCHDED,False +353,14.0,12.0,11.0,22.0,22.0,10.0,7.0,14.0,BDEBEHDFDDCDEADEHCFHCAACAABBCDBHHEDHEFBAFDACABGEEDEADFADFBGFAGCGHCFEAEDGDDFDEEBEEBEHHEHHEDEEBHHCADCACHDDGGBFEDDE,False +354,25.0,23.0,25.0,17.0,15.0,24.0,9.0,25.0,FHABBAFCCFBCFBEDDHCHGBAEHCEBDAADFADFHFHHFHBFBCHBHHEHDACDFFAGBGDEGHHGDDCCCAHCEECAEDECFBBHDFCEFBAHAAHAFHAFHBFAAFAGGACEAEDAFDHEGFCFFCDFHGFHACHABBABECCCCACCBBCDBEBBHDB,False +355,17.0,20.0,28.0,20.0,27.0,26.0,18.0,20.0,FCDHEAHEGECAEDAEFCHFEFCCCCBECHEHEDHDHHEGHEDFEHAEDGEDGEFEECECHGCDGCBEDDEDDFDDBGGCGBHHAACABGGBCGBCGDCFHCFBCFBHFAHFEFFCFFBDACFCHBHEEFBGFBHFDGGCECAAFACFBBBABBDBEHCAFFEGCADEADFFBCGA,False +356,11.0,9.0,19.0,9.0,17.0,23.0,24.0,22.0,DCFDCHHGFEAECFFCFFGEFGFFGAHGBHAADAACEFFGGEHCAHCBDFFDGGHHBFHBHHAHFFGGFEGFCGFCHCGGGGEEEFCDHCDECHECEBCFGCHBCHAEHCEGFDGCHBEHBGHBGHFAEAEGGD,False +357,15.0,19.0,23.0,15.0,30.0,8.0,15.0,12.0,EDGEGBEGAEFADGHEFEEDEDDEGGFDAEEAGDAEEADEAEBBCFBCGECBEGGACEFBGDHECHEAHEHGGABCEDDFDDEDBHDBCBACACCGCABEGHCHCCBCCAFCHBEHEHHCCBCEBCEBCEBFBBECA,False +358,8.0,10.0,3.0,16.0,6.0,11.0,10.0,8.0,EADHDFFDBFEGFGCCAFCBHDGEDHDDFBBFEBHHDAHDHEDHGDAGDAEDGDGFBGABGFDGFABBADBF,False +359,20.0,14.0,12.0,8.0,11.0,4.0,10.0,13.0,BAHGAEDBEDCADCAHBABAAFAACGBHGBHABHEHCCHBCGAEACGDCADCHGAECADFAEBDEHFCHEAADHAGHFBEBCEAGEBGBGHB,False +360,26.0,15.0,17.0,18.0,13.0,10.0,21.0,9.0,HCBGGBGGBCCDDCDCCHCHHEGGEAFEDFAGEBDHBGAFGDGAABCADCEGCFGAEABEADHABGAEGFEAFAFCACGADDBEAGAABAHGDCDEADECDBCDBCBHCFDDFAGAEGAHGAGAAFBDB,False +361,15.0,32.0,16.0,34.0,25.0,18.0,29.0,23.0,HDFHFFDABBBBEEBGEBGEDEEGAHGBGBBHDAEGCDACHECHBGDBGDBGDGDDFBGGDEBFAHHHHEHHAHDADDEDBEBBHABHAFGDDBEDHEDHDDHGCHCEFDGGDGGBCFCCFEHFGGFHAEDFDFFCAEGABDFEDGBAGBGDBCFBCHEDADDCDCBBBDEBDEBGHCGBEABFCGGEFCEG,False +362,22.0,28.0,20.0,25.0,21.0,16.0,11.0,16.0,BHCHFBFFBDDBHHBAHBADBAHBAHGCCFCBBDBBECAEFEDHHBCCFDCBBBEBHEBFGBHGDHCFFCFAHHAGAGDBFDGFDBCGEADBFBBAAFEDGEDFDAAGBAGAABEDDACBECBEFDAHCCCCGCEEHAEADEDDEDCEACEAEDDEDDE,False +363,11.0,11.0,7.0,6.0,9.0,8.0,12.0,8.0,FBADHHEHFGGCGAFEAFEGFGGHGHCCHCCBCABAEBAHDDCGFABEABFABABDEBDBHAGGFBGEEGDE,False +364,5.0,2.0,8.0,2.0,1.0,2.0,9.0,6.0,AHGACBAGHCGHGBEFDAFGACHCCGCDGCHGHGC,True +365,33.0,17.0,16.0,24.0,25.0,19.0,21.0,11.0,GDDGDDGBDBAABAFECGEDGEDFAGCACCFHCGHCDAADBACFCHEDAEHABGGHCEEEBAEFEDFDCFDHFDAFAGFBCDAFGEDDEHBEDBDCBHCAGFHFDACAGDABEABGABGAHCAGDAFFGEFDEFGFGEEEAEAAEAAEAEFBBAHBABCEGEDGAA,False +366,24.0,28.0,22.0,9.0,23.0,15.0,15.0,17.0,HEGHECCBBCBBFAEDHBFCBFBBFABGEGCFDCHCCBAAHAADABBBBAECHECEEHEEBAECDDAGDFGDFCDCGBCEBCABEABAAEHGCHEFHEDHFGGAGEHGCBBAFBAHCFEEGAEGABAABAHFHBCCCEHAEBBEGCGFFBHFA,False +367,22.0,19.0,28.0,25.0,31.0,21.0,23.0,26.0,HGHDGHDGEBCDDCAEEADEDEEHAHBDCEEBEFGAHAADGDHBHFCEGEDBFDEFEEBEBCEFCEFCBACBADHADEGDAHCCEDDEDHFAHECDDCBEFBEGBDCHCHAABAACCHCCHCDHAGCAGEBEEAFECHBCHGCGGHFCFAGGEDAFDCBECBEHDEFFGFDGFHGFGGFGFFBFHBCCGAGHAHH,False +368,19.0,23.0,22.0,14.0,18.0,18.0,13.0,20.0,GAHHDGFBGDBFFBHGADABEHCCFDCBDAGDBFBBFBBFBFFEFFAHCAFGAHADHEBFBAFBECCEBCDDAEDGEHBBBBACBAEBDECHEGFCHACFDBGCHHCHGEHCCHCGHCGECEAGACHFCHFCHDEEEEEBDACAAHA,False +369,8.0,9.0,10.0,4.0,11.0,7.0,17.0,8.0,GEHGEBGFGGFCGEHAFBBFCBHCFDCGEHAEGCCGAEGBBCHBHFEAFGBCGADGADEADCGCHGEBAEGHEG,False +370,14.0,14.0,22.0,16.0,19.0,13.0,17.0,12.0,AEAAGFACECCFHBFDEGEAGADCEHCECCADHDEGFGGCCGBHGBHGBAFDGECGECGHBDHBABFACDDEBFECFEFFCAFGEGEEGHGCBACBCBDABCGBDFEDEDDHDFBDHCCHCCHEADE,False +371,24.0,19.0,21.0,13.0,20.0,18.0,17.0,23.0,GEGEADCDGEHBDCBDHAHCEFCEFEEFCDFBEGAGFHGFCCHCCFFCFFAADAFCABBBHGCHDHEAAGCAGDABHHCHHCHGBEFAAFHAFHGHHGDADEABEGBCGCDBADEHHEHACDABGECFEFEEABEBBHBBABCAGCFGEFABHAH,False +372,3.0,3.0,3.0,4.0,0.0,2.0,1.0,2.0,DDFDDBCABHABACFGCH,True +373,11.0,27.0,14.0,16.0,27.0,12.0,14.0,25.0,BGEGGBDBADECHGHHEHADHDGAEAHEFHBFHEEDGEDECBHFEHEBHDDCEABEAHEAHEBEEBEGAHCHHCBBBBBBBCCGDFGEBBEFHFDHFDHFDEFDEDEHGEAEEFBBHBBADBCBCCBGFDGHEFABBGHCCCGCHH,False +374,3.0,9.0,10.0,10.0,8.0,7.0,11.0,11.0,GCGGBBHHCCGFDGFDHDDHFDBFEGEEBECDDAECCBBCHGCHGFHADHACBEFHEBHDBHDGGFGEC,False +375,23.0,33.0,18.0,22.0,30.0,18.0,26.0,23.0,EBDEBDHHGCCGCFGADGBCGHCEHFEHDEHBEGDDGBHGAHDAHDBCBAABCFBCHEFDADCAEBBBBHBAFBAEBAHBHFBCAGCFHDADEAFECEECEFBBGGCCGEHHBBHEDCAFAHEEFFEAGABGCDGBBGBDFBDFGDBEDBHFBGDDGAEBAGAFGEEBEECEABEHGGADGDGFHGFEAEHHE,False +376,26.0,12.0,16.0,23.0,9.0,18.0,21.0,30.0,ADDFFDFFDFFHCFCBFAGFBGHEDHEAHECHCABFAEAAGAAGDDDDCFGCAHABDEGFHBCBCADGHDGADGHEGHDGHFBHGDHCDEABHGEHBDADAACHHHHFHAGHEGHDGHDHHCCCAHDHHGGFAAAAFABFHCFGBHGAACBGCDD,False +377,14.0,10.0,11.0,6.0,8.0,8.0,6.0,11.0,FCEFBBABDCHECFBCGBHGFHECGCFAFAEFDBACADCABCHHEAHGAEBAHAAHAAGFDCBDCBDGAEHHEH,False +378,10.0,13.0,11.0,8.0,10.0,9.0,5.0,12.0,ADCHBEECEEADBACBGBBAHBGHCCHGBHCCACCFHCDBDDFFDFFBFEAEHABHDBDAFHECBAHEGHEGHEFBAF,False +379,26.0,14.0,13.0,28.0,14.0,24.0,18.0,23.0,ACEAFGAGABGAGGEHAFHDCDDFFCGHCDHAAAEFFEGABGAHHADFGDFBCAGCAGBACDDDBDDEADCCHGEAGEABHHFHCCBDABHFEEDGHBGBBHFDFCDFBDADDEDDEDHFDHFDHEDHAAFAHDGDBGEFFABAECAHHFFHFFHDFHFG,False +380,21.0,15.0,24.0,10.0,21.0,16.0,24.0,20.0,GBFFDHFBFGEFHHHHHECHEDEEBCAFAABGACGBCAECBCCBEDFCDGCEEEAEGAGGACDAFDCGBBGBBCAFFDFHBAGGDGGCCHEAFEAFCAFCAHCGGAHCACCAEGHEHEEGEEGDCHDHHGCEGAFHHEHACBCFGHBGBAG,False +381,15.0,21.0,27.0,23.0,28.0,27.0,27.0,20.0,BCBHCAFBBGEBDEDHCDGCGGCGDCFECDECEBCEBFEBFGCGGBGABFAEHCFDCHEGEFFFBGFECCEHCGFFGFHGBECCFCFAEDAGAHDAGEFFFAFDACCHCHBBHFCDAGDHGDEGDBDEHDHHFHFBHDBFDEAGCADBDDBDDEEFEEAGEGGBCGEFEEFDGHHCHFEHCAGGABCE,False +382,0.0,4.0,3.0,2.0,1.0,1.0,2.0,3.0,BCDBHDBHFEHGGCBC,True +383,1.0,2.0,2.0,6.0,6.0,2.0,4.0,2.0,CHDAEDGEDCEGEBGEFDEDGHDFB,True +384,12.0,14.0,12.0,10.0,21.0,16.0,19.0,20.0,GDHEBFGHDHCEABECBDCAHGAEGCEBCEHDEAEBHEBHFHHBBFFAFDCGHAGDCBFHGHCADBAHBGHBGADHFCHFDHCHECEECEGFEGEAGEGGEBFEGAEBAFFFEGFGGDGHFEHF,False +385,9.0,9.0,5.0,9.0,10.0,4.0,7.0,7.0,BCCBABGHBGDEGDACDBEFBHDGADGAEHHCFCEFDEBDBBDAAEEAEHADAGEHGFHE,False +386,15.0,9.0,11.0,11.0,15.0,15.0,12.0,13.0,EGCFFCFGCFHFDHCHCCHACHECAGHFFABEAHEFHEDDEBDHBDHBECDEADGFGFBGFAGFAFAHEEEBDCDGEHGAGGABAAGDFDBEABEHECFAA,False +387,17.0,16.0,9.0,11.0,9.0,4.0,15.0,11.0,DADCFEBAEAGCBBHBEGBDABFBDFDHCAFEGGEAGEACHABHAGHDGHBHHBGDEGHCAAGDAHACEGBBGABAACGACGBDGBDHBDCE,False +388,10.0,3.0,8.0,5.0,5.0,8.0,6.0,3.0,BDDGGCAECAFGAFCACADCEGCAHCADCBFFAFFHHFADEGFEGBEA,False +389,17.0,13.0,28.0,32.0,15.0,31.0,24.0,29.0,HGHCCHGBFDBGAAAAEDAFHHDEGFECFHGFCFFEHFDHGDCCFCHFCFDCFDGEHBEHGHHAACAEDAHDACGEGFEBHDHCFHEFHGFAGFACDACBHCDHCDCCDEFDEFDHFECDHDDCGDGBBCCFDHBDFBDFCGBBHAEHCDGGFHGHAGFBDBDCGFCGFDGDDFDHGHAFFAGDCEDCF,False +390,23.0,24.0,19.0,26.0,25.0,15.0,25.0,27.0,FADECFEGAEGHCFDCBGCBDDHDDHDDAGAHHAEBAGDAHBHGBFGBGGFGDCADCBHBEHDEAEHGEHDBHGBHEBDGBHECAEDADDAEHFFHFHGGCCHHEFECCGDEACEHHAHGAFAADBBDCBGABDACCADABFABEHFEBEEBDDACDEEDGGGGBHGBHCFGCFHFBHCBEGEE,False +391,4.0,5.0,5.0,5.0,10.0,9.0,7.0,10.0,FGGFGCEGEEHHDHGDCEDAHBFHFGDFEBHBHHAHFCCFACFGBFEEHEEDEAB,False +392,2.0,1.0,3.0,2.0,5.0,3.0,4.0,3.0,FBGCCGDCAHEFHFDHAGEEGEE,False +393,32.0,34.0,23.0,23.0,23.0,22.0,17.0,26.0,AABCCBCADCAHAAEFAFBABBHCCFBFGDHDHCAHFGBBCCBHCBHBFCDFBHBEABEAGEDGECBEBHEBAEFHEBEBDHAHHBGCCFDDFDFBDHBGAAACEACDACHADFAGFAGFHGFDFADFAHEAEEBEAGDDHCDEFDBHCGGDGDAHABHEBHEBEEBEHFABAHBGEBHCFDGFGFEDADCACHACBGBB,False +394,10.0,5.0,5.0,10.0,12.0,9.0,5.0,11.0,DCDEADHACFADFADABDHGHHDAHGAGEEBEFFCFAEDAGBAEBCEHDBHFFCEFHEHHEGEEDHF,False +395,9.0,8.0,7.0,6.0,6.0,3.0,2.0,9.0,BAGBECDECDCHEAHAFGBFHBAHDHHAACAACHHFHBDDBEEAEDBCCB,False +396,28.0,25.0,16.0,17.0,19.0,17.0,23.0,14.0,FBGFAAAHBHHGFCGDGGBGGEGGEFCEHCDGBBHEACEGBEADCADGEGHDGAAAAABFABFADFCCBHCADEFGEDDBDACAABAAHHHFACFBDAADBAGBGEHDEDBBFBBFBBCEAGEBHEBHEBEFBCFECFEGDGBAGDACDHCFCFGAGAE,False +397,11.0,7.0,11.0,10.0,5.0,9.0,10.0,7.0,BCHBAHFDBFCHFCDDBHGAGCHGCGGCGGFGEAEECDDFADEBFCHDCHBGABGEFDCFDFAAADAACA,False +398,21.0,30.0,21.0,28.0,27.0,13.0,18.0,24.0,CBDCAGAAEHGBHBHHFHHAHHCGHDBDABFBEHDEBCEDFDCFDCFBCEDCBAEBEDBEBBABEDGFBGFEEAEBGHBGCBACBDCEECBDCDDCAAGDGEAGEAFEGEEBEHFDHDGCEBFEBDGDFHAFHFDHECHGCDGHEGDBDBHEBHGBDAAAAEADDDCABHDCHCEHCHGBBA,False +399,8.0,12.0,5.0,5.0,7.0,5.0,5.0,13.0,HHGHBAEGABBCBBCBBCFBCBHADAAFBAEBEBFHDECEEFHGAHGHHDFHDGHAHHED,False +400,7.0,6.0,11.0,5.0,6.0,14.0,10.0,3.0,AEFAEBCFDCFCFAEFCGGCGECHFGADCBDFGCHCCABCAGGEFHEFGAFBFBGFDGFDBF,True +401,5.0,2.0,3.0,1.0,8.0,3.0,7.0,1.0,BAGCFGEEAEBHEGFAGFDGEEGECAEGAC,True +402,7.0,14.0,22.0,10.0,18.0,10.0,12.0,15.0,GHECCAABBCBBEEBEGBDCEECFGGHCHACHAHFBGGCCCCHCEFCFDCHDCHDFHECHACDBCBAEBDEBDGGEGHDCEGHECEECEEHBEHDFBFBAFHDFGFCG,False +403,14.0,14.0,19.0,22.0,20.0,22.0,14.0,19.0,ECCEDFDGEDEEBCBHDAFBAFAAECCFDCEBBEBDAHCADCFDHEBFEDFEFEGFEAFHAFHGCHEEHDDFEDFDCFDCFCBAHFAHFHHFBDFDDEHCGGBGHBAHCAGCEGAHBHCGCEDEFDFGDHGFCGBBGCHGHDDA,False +404,9.0,11.0,17.0,12.0,11.0,7.0,12.0,10.0,BCBDCEGCECEGCDCCDGGAHGEBGBHCFCAFHAFHADEAHFDHEBCCDCCDCBDHEDHADBAHCHDDGBEGFGGBECFEFEGBAGCAB,False +405,5.0,5.0,3.0,4.0,12.0,4.0,3.0,6.0,DBGAEGEEDAEHAEBBEBEEHFDCBEFGEFCAFCEHHAHEDH,False +406,15.0,17.0,23.0,27.0,15.0,22.0,16.0,20.0,EFCEGEFDBFHCCACBDDHDCFBHFHGFCECAEABGBGDHCDBCABGADFDDFECCACFAEFHDGHDBHDAHDHHDHBFEFDEADFADBDCHDEHFCHFGGFHGHHEAACAFCFBDDCEBCGBDGDEGDBGDHFCCFDEHCBBCBGDFGAFEAGC,False +407,11.0,16.0,12.0,20.0,16.0,15.0,13.0,15.0,HBGBDGBDGFGEFCCHCDHCDHFFCDBCFBEEECEFCEABEHDEDBEFHFDAFDBHBBHDACAHFAFBAEBDDDADDAFDGGGEEGHEGDFHBFHGDBGCBGBACDAHHCEAEEDHGF,False +408,16.0,12.0,20.0,13.0,15.0,13.0,22.0,14.0,HACHAGEAGFHHDDCEDCBFEDFEACBBFHBFHBCGBCACCBDDGDDBEFEGGHDBDDGGFHGAHFEGAEACDACGABAAHEABECECCECGGCAHFAHFGGFEECEHAFDGGGGCFHCGGCGBC,False +409,4.0,7.0,9.0,5.0,9.0,7.0,4.0,6.0,EFCBHCFAFFACFDHHBHCBGBBGBCEHGECBAGDCEFCDFCDEEHEEAED,False +410,12.0,11.0,9.0,6.0,6.0,6.0,2.0,5.0,DDCDHBBABBACFACEBDEHDHBFBAFBAGCAEAEEFHCBCCFHCAAEAABDABGFC,False +411,10.0,13.0,4.0,12.0,8.0,3.0,7.0,11.0,BBHBBDDDDDEEAAHAAHBAHGEHGHHAEDEEDACDBBDGCDBBABHHCGCFGFEGBAGBFDDAEHBH,True +412,2.0,7.0,4.0,0.0,2.0,6.0,5.0,2.0,BGBFGBFGBCGCEACFBHFEABHCBGFF,True +413,28.0,23.0,16.0,19.0,25.0,12.0,17.0,19.0,BHADEAEEHEEAGEFBBCDDAGHHGHAEBDFBAFBAHAEHBECBDCGDGBFGEEAEEDBDDBHDEHGECAACGACABCABFABCADEAHEDBCGFEBFEADEBEGADAAFAFHADBACHABHCCDCDBFABGAEGCGFHACDEGHHGHGDHFBHEBEGC,False +414,4.0,13.0,10.0,10.0,10.0,2.0,11.0,8.0,EEGCECCGBBGBCGDEEAGEDBHCHHADHDBHEHCFBDBGDBDDBDEADEHBCAGCBGEGCBGCBGFH,False +415,13.0,21.0,20.0,13.0,22.0,19.0,15.0,24.0,HFDBGDBHHBCCFHHFBHFBHFBHACEFEHFCBGBBFBHFDGECGFCAABGCFGCHHBHHEGFEABCBECEECGDCHHFEDAHBAEEDECDHDGHFGHFAECAFBAGBDECDCHBHHDCEFCAFEHEEGEAGEAFEDEBACBDCBGG,False +416,21.0,17.0,11.0,9.0,12.0,14.0,19.0,7.0,CGHHGBDBAGBAGBDGACGAHFFBFAGCACDAGAAEAEFCCAEFBCFGCAACGEFFBDAEDABDCEGEFCEBBHFBHEBHEAGGBGFAHFEBFBBDABFAGGAGGDGADE,False +417,6.0,8.0,8.0,1.0,1.0,6.0,7.0,5.0,BADAECHCCHCCHAAFCGFBGBBHBBGFCFHCGGBGGBFFAA,True +418,11.0,22.0,19.0,15.0,20.0,16.0,14.0,28.0,CCEHHDBHECHCGAGDCCABHFHHEHDEGBEGBDDBDEBHBBGFFCFFHBDHBCHBEHBAHFFGFCDHHDCHBEABHDBHCBAAEFDCBCCDFHEFGBDABGFBCADEFDGFAGEHGBHCBCGFAAHEEHEFHEGEEHEEHCGHC,False +419,25.0,19.0,13.0,15.0,18.0,30.0,15.0,15.0,FHCDCFBEHCABEAFAFHEFDGFDCDEHAFGAFBDBBFBBGBAHFAGFBFFBDBDDEGFBDEBHCBFCEFCEFAECAEFECGADBABAEHFDGFGGBGFBGDAAAHAAHDFHGCHFCAFEAEEDECDHBFAGHAGFEEFAFFAFAHCAHG,False +420,5.0,4.0,3.0,9.0,10.0,5.0,4.0,4.0,DEBDADFEFCEHEABEAEEFEDHGDHEDCFGCFDDGBDGBEAAH,False +421,21.0,22.0,19.0,21.0,16.0,23.0,24.0,24.0,BGGDDGBHHHHGHHDAGFAGFBBFGGFGEHBAHECFACAGHEFCEADEAEBAHBGBBACDACDHCDHCHBCDBDDGCFHHFHHAHEEHCGCBGAADFBGEGFCCFCGFDHHDHCBFDAADABBCBFCFGDECBEFDEGDEDFABFADFGBFGFAGFADHHEGABCFBGEE,False +422,5.0,3.0,3.0,1.0,0.0,2.0,1.0,4.0,ABCABCBGAHHHFHAFCAD,True +423,8.0,5.0,10.0,3.0,2.0,6.0,4.0,7.0,CAHCAGAAEDGFCGDCFHCAHCAHBBDFAFFGBFBBCCCHCEHAH,True +424,4.0,2.0,3.0,3.0,3.0,5.0,4.0,1.0,GDFGCGACDACDEBFEGHEFFAAFB,False +425,20.0,29.0,28.0,22.0,37.0,21.0,18.0,23.0,DCDEFDAGCHCHFDAFEFFEHDEDBEABEHBEBFCBEDBCDCCEGCEBCEAHDHHDAHGAHBBBFABFABACBADHEEHEEAEAAEACDCHBCEDEEBEGGEBEFDGCBBBAFDAFCAFCHEDBEDGECHBHGFGECEDGDFECFDCFGHECEEHFEBCABCADEAFEGBBHBFGBEHCCHBCGBEFCHHCHGGGGDF,False +426,3.0,6.0,6.0,5.0,11.0,8.0,8.0,8.0,ECEBAECEDDEBDGBGHDGEBGECGFHGFHACHFGHFCFBEFHHBHEADEFGCFE,False +427,9.0,21.0,17.0,17.0,18.0,17.0,9.0,12.0,BHBBHBBAFBCCHEBDECFECDEFFGHCEFCAFAEHDGHDBHABEEBEEDAECBDCECABDAFDHDGEDBBDBFAFFCCBHCDHDBFDGFGBFCHACDBCGGDGGCBFFBFEEFHECEED,False +428,13.0,9.0,6.0,7.0,7.0,9.0,7.0,6.0,HDAAECHEGFFGFGCFHCBGAADAADAAFABFBEEAFFBBCBBEABECGHDGEDGDABDAFHCH,False +429,8.0,15.0,19.0,18.0,20.0,20.0,16.0,22.0,FGDFDDFHDGAFGFHEBABCDBHFGHFCHACACCECEACEBCFGDBHFEHFBHGHHEHEBGEAFFHCFDEFDADDBDGHFBDFBCFBGAHFBECHECBECHECECCEDCHGEEGEGFDFEDBEHBHCDGDHCHHGGDG,False +430,13.0,25.0,20.0,21.0,26.0,17.0,24.0,16.0,EFFGFCDFCEHCGHDGEECAEBBEGBECFEGHAADDAFCAFCBCEECFFCFCAGDACHBHHBGDCGDGGDEEDBHHGCHEDBEGEECEEBEBBDBAEEFDGBGGBDAEDHEFCGBCGFCGAHGFHDBGGBFBFFHEHBCDBADCEDEBBGAAGHBGHBDBDD,False +431,13.0,21.0,18.0,12.0,10.0,10.0,17.0,15.0,GAFBBBBFHGFAFBGCGGBBCABCAGDHGDHBCHBHBAHGGHEGHDCDBCFBCGECAEDDHBAEBDHBDHBDACECGEGGDHADBEFCDBGACEAHBCFBEHAEHAFGCCGCCFFC,False +432,14.0,11.0,9.0,15.0,14.0,12.0,12.0,18.0,DFAFFAHDHEDFEHHEDHCFHCECBABBDGEFGEDCDCGDHHFCHFCGGCEGABGDBEABAAHAEBDEBHEGHFGHDHEBADGADBAEHCEHDDHBFAGAAFFGH,False +433,16.0,16.0,12.0,20.0,13.0,18.0,9.0,14.0,FDCFDADDBDDAHDCBDCDDCDAEHAFAABADBECFAFBCFADAGCAGCDBAFCFFEHFHBFBEHGCGGDFGDABDEECGGDFEFBHCBHBEHBEABEHBAHGAEFBEHHHFEHFDFD,False +434,15.0,21.0,15.0,6.0,12.0,5.0,12.0,17.0,CBBDBGABGCDGCEADBCCADEFCCAHCHCDHCAHCHHABHBBHABEFCGCBGAFAAHEAFGAEGAHGEEGHEGBFBEECHEBBAHHCHDBHBBHBBABBGEG,False +435,0.0,0.0,3.0,2.0,2.0,2.0,2.0,3.0,CHDCEDEHCGHFGF,True +436,22.0,21.0,21.0,13.0,7.0,14.0,20.0,13.0,BHBGDAADEDFGCFGDHGAGGAFDCCACCHEADBCFBCGBFABEHDCHCEGBGDAGAADCAHGHHGHFFDEHAGAGGABCAFAFFACHACGBDGBDCBDHAGCFEBFACHBCABCGFCAFGBEBBCBBCBB,False +437,18.0,12.0,15.0,15.0,9.0,15.0,19.0,9.0,BEAEFBCFAADCBFGDGGHFCADAADGADHCBHDGDBGDBGDCGAHEFHGFAEBAHBADGCDGCGFCHFDEFEHFCAAAFBAHAEGDEGFEDCCBCGBFGBFGACGCCADFG,False +438,9.0,15.0,11.0,10.0,6.0,5.0,12.0,8.0,CBBCECABBAHBHBCHGGEGGDAEBEDCDFADBGDBGDBGBBCDGABHCFGBFGHFGHFEAAEAABHDDCGCCDCH,False +439,21.0,34.0,13.0,20.0,9.0,14.0,18.0,22.0,DBGDFCCFEAGHBHHCHHCBHBGHBDABCCBAFBAGBDCBDBBGBAFFDHEHGCBACBAEFGHBGAFGCFBAGHAHHAGHGCDEAHABHBDFEDBDDADDHFBHFBEABEABADBHFHDBABBHBAEBGCDCFHGGGBBGFDGDABDABDE,False +440,5.0,7.0,4.0,9.0,2.0,7.0,1.0,7.0,DEBHHHHHHDFAAFGADHABBFFDFFDBEDCCCCFBDDBDAB,True +441,9.0,3.0,11.0,9.0,5.0,3.0,13.0,6.0,GCHGCHBCDDAEAHEAGAGGCGEAEHACDFBDBDGCDGDGGHGCFGCAHCACDGCAEFD,True +442,26.0,15.0,9.0,16.0,20.0,21.0,20.0,20.0,EEHEFAFDDHDDBDEEFFEDFCHFAAGHAEHADBAGHAGBADAAEABCGBCBBFGCFGEFGEFGHDEAEEAFHFGHDGFAGACGCHBCHEAHGABGBGADGFFGEEBCFDHAEBAGBADAABBHFHHCEEFFEDFHAHHAHADDGFG,False +443,5.0,11.0,13.0,10.0,14.0,14.0,10.0,14.0,FCEHCEHCEDGDBBDGEDHEABEFGAFGAFCCFHFFHFBAEEGDFFAHECHGCHDCHBGFEHFHFFBBCBBEHCHHBECDEDBEDCGGGDC,False +444,9.0,3.0,12.0,6.0,9.0,11.0,10.0,6.0,GACGCGACGBHABFCEFCEFCAFGFEGDCFBCHHHHGAAAEADCDGAGEEEEECFFCDFGDFCDFH,False +445,9.0,10.0,13.0,13.0,17.0,11.0,15.0,15.0,DGCDBCDFEFHEHHEDDEGCCFCFFCGDEECEFHHFAHFAEDGGBBGHHGCHGBACAAHEEHEEDGGDGGDGEEFEBGHBCDCAACAHDHBFEFCEDBHBBAG,False +446,4.0,1.0,6.0,9.0,11.0,4.0,5.0,7.0,GACEFGGACGDFDECDEHDEHDEHEEDAHDCDFCDBEHAGFCHEEHE,True +447,26.0,19.0,18.0,11.0,16.0,16.0,12.0,21.0,EEHFFHCBABHABHAEHAEHEFFGFAGHBHAEEAEEAGAAGCCGABDACECFHGHHEDHCBHCBHCBAGDABDCHAHEFHFHHDDFBFFAFCACABEDFEDAGDBFCBDAGFACEACAGHABBFBBEBACCCGHCDBAG,False +448,6.0,5.0,7.0,6.0,1.0,1.0,3.0,5.0,HADHAHCACGDGBDGBAECACBABDCHDBHDCCF,True +449,11.0,2.0,6.0,6.0,9.0,16.0,8.0,5.0,AGAAHAAGFDFEEFBEDGEGEEFEAFCCDEDFFGFFGFFCFAEFAFHDFCBHADHFGHACCAG,True +450,11.0,4.0,8.0,12.0,7.0,9.0,7.0,8.0,FDEFCADCGCEBAHBGECHEFHCDACDABHGBFFDFAEFAEADGADFEDHCAHGDHDFCDAGDAGH,False +451,31.0,20.0,20.0,33.0,22.0,23.0,32.0,17.0,BCCAGAAGFAGCEGDBGDACDHDHGFBGBBDBFGBHBAHECEECDEDHHDFADFEDCEGHAFBCCBFADGCBADDFEFGEHGEFGDHECAEAGEDDEBDEADAADBCBGEDHDDFCEAAHBGBGFAGFDGFDEFEGHBAHFAGFDGDDFDFABCABCAFCAFCAGCAHEGHGDAADAGEFGHDGCDGBGHCFAGDEGA,False +452,6.0,6.0,6.0,10.0,8.0,9.0,9.0,6.0,AFEABEBDGBAFEDHGFHGEDGEHCHAGHECHCCFDADDFEDFEBAGCFGFFGCBGDBDD,False +453,13.0,18.0,14.0,23.0,17.0,19.0,19.0,12.0,DCGDCDDCADEBFFBFFCAACDACDCCABCDDFDFAAEGFHFADCBGCDGEDAFGGEHHEFBFFBFFBGFCDFCGAGDDHDDHFEHGEBGHDGHAEHBGBDEFCBDDEABHAGEBEEBHEDEGBHGBFGBGEEGB,False +454,18.0,22.0,18.0,14.0,25.0,31.0,12.0,21.0,FHADBACFDHAHHDGHBFFFCFGCBGDHFFFGFFGFGGFAHCHEEHFHDFHFFHFAHAHEACEGEEBDEDFAFFBFFBFBEFDCBBEAEHDFDEEEBBGCBFCFCBGBBFEHGCDEHDECDECBADEAEEACEACECCABBECBECBFAFAGHEHHABHAB,False +455,8.0,7.0,7.0,9.0,13.0,7.0,12.0,7.0,AGEBFEADAAGFABFHDEAFFCGFDEHGABGCBHCBGBDHBDFDEGCEGCEDCEHEDHGDAGEHEEGCEG,False +456,26.0,25.0,17.0,12.0,23.0,17.0,8.0,10.0,BCAFCEBDBGCAAFAAFGCBEAEDDBADBADCHEFFEADEAEEFEEGAEGEHBEGAFHAFHDFBBAEACCAECBBBBBFABEABDBBDABDCEDFECACHFHAFHGHDCCAGFEEACEABFABFBEFAEBBGHBCHCC,False +457,17.0,13.0,15.0,8.0,13.0,12.0,8.0,11.0,HFCEBGABGABDAECBBCBBEBEEBFEAADACFHFEHFBACAACDAFHHFAHGAHAAEAHGHCGFCDFDAEEBDECCHCCFFGBEGCDFCBCAEDHG,False +458,4.0,0.0,3.0,1.0,6.0,6.0,4.0,0.0,FEEFEFFGCFAEAGCAGEADEFGC,True +459,21.0,25.0,18.0,16.0,17.0,17.0,23.0,17.0,HDAGCGGBBGBCEDCBBBEGFEGFEGFAFFCGFCBECBFFBEBBGBFABCAFAHEHEDHGDCCEAAGAAGBCGHCBHCAEDHHDFFDABEFECCABHABEDBEGBEGDGDFGAFEAGCDGCBHHDHCAHGABFDEADBADBHGAGAHFHGCHDB,False +460,10.0,14.0,5.0,9.0,15.0,9.0,9.0,8.0,EDEEGEAGEGBEDBDFGDEABFAFDAGEBBABDAGDBGFFHAEHDEABGBHABEACEFBDFBCHGCEBCEBEHHHFHCF,False +461,5.0,3.0,5.0,6.0,2.0,12.0,7.0,4.0,CEAFFGFFGFFDFHDFBDADACCGGCABAHGFBFFDGHDGHEFC,True +462,6.0,6.0,14.0,9.0,5.0,9.0,18.0,19.0,FGCDHCHHGHDGADGECGHCGCGHCEDGEFFHHFHFGBAHEFGBCGHFDHFHHCGHCGHEGBCCBDAHDHGBHACGCGFCDABDAG,True +463,3.0,5.0,4.0,8.0,5.0,3.0,5.0,5.0,DGAFBBFAHGEGGEGBECECCAHHDDDEDDHFDHBDCB,False +464,8.0,5.0,4.0,6.0,7.0,4.0,8.0,3.0,DACBACHAGHBEHDEFEADGGCFEDGEBGEAGBAGFDGFDAAEBC,False +465,13.0,13.0,10.0,12.0,11.0,18.0,10.0,10.0,DFBGFDFFDGBBBEDGEDBECEEDFHAAACAAHHHHHBGGAAAFHACDACEFFHFFHAGCBEFBEBAFGAHGDEGFFBFDBFDECCECCGBCDBFDF,False +466,1.0,7.0,5.0,6.0,4.0,4.0,5.0,8.0,DHBECBCDBGDBHDBHFHECAECFFGHDGBBGHCGHDHFE,False +467,8.0,10.0,7.0,7.0,13.0,10.0,14.0,7.0,GGBEGHAGEGBEDBCAFFBHEEAEFBEGCFGCFHBFEGFEBFHFCHFDGDDGHDGDCHAEGCEGAEDCEBAABABG,False +468,7.0,9.0,14.0,4.0,4.0,10.0,8.0,4.0,FECAECBDFBGFCCFECFDCBGCBGBFDAHGAFGBBEBCHBCAAHGAGCCCFHCFGCDAF,True +469,11.0,8.0,10.0,17.0,9.0,15.0,9.0,16.0,FHDFDDEACFHCFCAHDEHAGHACHDGBAGBEGBAGEHHDGHFEHADHAEFAGGCFECFBCDGDHHDADBCDBEDFFDFFCCBEDHFHAFHDFDB,False +470,1.0,3.0,1.0,1.0,2.0,1.0,2.0,3.0,CHADBEEBGHBGHF,True +471,17.0,15.0,26.0,18.0,19.0,21.0,23.0,27.0,GFFCCCHCDHAGAEGFGCBGCBFCFFHDFBDCHDGHFEAFEAEEAEGDHGHCGABGDCGDGGFFFACHBEAEEDEAHFAHDHHGCHFHHGGHBBECGECEEDAHCACCBBCFBCHGCHACFDCEDAHCAHFFFDABEEBCBAHFCHBHBGDGECGEHDHGDHGDFD,False +472,2.0,5.0,3.0,5.0,4.0,6.0,6.0,2.0,EGHFGBFEBFEDFHGCCFEABDADDBDGBGCFG,False +473,20.0,30.0,26.0,33.0,27.0,26.0,18.0,15.0,CGAHFAGFAFDBCDEGDEHBEGBEBFDGFECFHBFHBEEFEECCEFEFFHCDGAHABDFBAGBADBADBDGFGCDCABGAEGDDDDACFACEAFEBEGDCGCEFDEBEEDFEFFDABDHBDEBCHBHHFDDBCDFGDAGHBDABFBDDDFFBBACBCCBCABCACCHGCBFBDDEEBCGDCGDCEDCHFEHEAHE,False +474,19.0,17.0,14.0,18.0,11.0,17.0,20.0,12.0,GAGCCFFCGFEDEBFFAFCGDHGEHGEHGHGFDFAAFDADDADCACCBFBDGBGGBFEBCABDAGHGBDBBHFGEAGCDGFDCFCHFAGCBBABBABAEBCFCDEDHGHAEHAEDAEDGFDGDAHHAB,False +475,29.0,21.0,29.0,16.0,8.0,11.0,32.0,19.0,GGHBGAGFAHFBGAHFBHGBHGCEACHGBAAAFHHFHHCBGCGAHBDCCDGAAGHHDBDCBDFBDBEACAFCEDCBGABGAFEACGACGCCGBCGHAGADEAHGDCGCBBAFBADCGBEGBEGBAGCGGAGABCCHCDACGHDGEAHAADFCCHACDGCDGCDFC,True +476,1.0,0.0,5.0,0.0,0.0,3.0,1.0,0.0,CCCGCCFFAF,True +477,12.0,12.0,12.0,10.0,3.0,21.0,15.0,7.0,FDFAGACBDCBGCEFEFDGAGGBBDBBAFCADCADCFCGFCFFHFFHBFCCDAGAAGBFDCFCAFHDBBGHDGHFGBFBEFGFFAHGAGGFH,False +478,17.0,16.0,18.0,22.0,16.0,25.0,17.0,21.0,ACEFGEHAECACCHBGAFFBCFECADCEFAEDEFAECBCGBCHFGHGEBAEAADHGDGAFGDDCEHCHAEHDEFGHHHBHABFABFHCFHCFHCFBDFBHBEFFEDFCDBGDAFDGBHFBHAEDCFHBDDGADGDFCDFGDGBDGDFHDFHG,False +479,10.0,7.0,13.0,9.0,7.0,6.0,9.0,3.0,HGCDGCAGAEGAGCCBCCFCEFEAFEACGGCHDABDECHFABFEBEBADBDDBAACGCFDCDDG,False +480,1.0,0.0,4.0,0.0,2.0,0.0,5.0,0.0,GCEGEGGCCGCA,True +481,21.0,16.0,14.0,17.0,11.0,10.0,25.0,16.0,FDGEEGBBDHAHGDHBHGBGCBCCFACEAEGAHHDHBGFDGADAAEAAFHCFHDFABGCBGAGGADCHDCECEDBDACDAHDAGDBHHBAGFAEFGBFGBGHAGAAEDCBCEBHEGHDDBGGGGCAGCFG,False +482,12.0,17.0,21.0,17.0,21.0,22.0,20.0,24.0,HCBHEEHCEHCBHADGBCGBEEHHFGHFDHFCHCGHGGHBGCBCHGDDACDFFFFFGBACFECGCFHFAEDHDDBDDHDEGDECAGCAGHAEHAHFEFDEACCDGGGFGCEBCEDHFCHBHBEHDDABHFFFAFFBFEBEBBGAEGCEGCEBFE,False +483,19.0,21.0,17.0,13.0,22.0,21.0,20.0,24.0,GDGGEGFHAHAEHADHCEHDAACCBEFBEAAFFAFGHHBHDBFDFFACBGDDGDHHBACBFDHFDBFEFFGABDACDFFHGFCCAEBBHGBHBBEBGCDGCHGCHEFHEAHEHHGACCACGAHHEBGECGACFEEEBEFBCFEEGEHGEAGBFHBEB,False +484,14.0,17.0,19.0,19.0,23.0,9.0,30.0,14.0,DBADEECEEGGGCGGCHGAEDCGDCDDHDGGDEBHBBCAHHADGGGEGCECCACHAGHAEDABCHGGHAGDADBEFHHFBCEAGAGGDGGHGGACFFBFGCFGBBDBECBEDBGFEHDEBDEFHEBCEBAEGEECEGBGFCDECD,False +485,23.0,20.0,17.0,18.0,15.0,7.0,16.0,20.0,ADAADBBFAFFAFAAGCDHCHABGABCAGHBGHCAHEECBECGDHHAHDEFBGDGDBGDBAAEABGHBDCECCBGGHCEHBFABFABCACAECBCDDCBEEADEADHHDHDDGEHGEHGEDCBDCHAAGGBHHBHE,False +486,19.0,15.0,16.0,14.0,11.0,13.0,25.0,19.0,GDCGHFGHCBDBAAAAAACAGHBGADDCCHEGBCBDAFDBGDBDEAAGAHBAHADCDDEHHFHEAGCGGCGGBGHCGCBGCBDCGGGFEGBEDFHCFEBFEAFGAEGCFGCFGDEGAHFEHABFFBHHHHHH,False +487,17.0,28.0,19.0,19.0,12.0,13.0,19.0,22.0,DBDEFAHAGFBGHEGHDDBBEBHEBHDCHFEHGEHGBBACBAGAAGEBBHBDFBDFBDCCHCCAEBGDGDCEBCACFAEGAHDFCCBHCEHDEGCBGABGBDFHCFDDFDBFGAGGFHBCHCABDABHAHCAGCHGBBBCBHFDHADHG,False +488,11.0,5.0,10.0,9.0,17.0,10.0,8.0,12.0,HFEBAGAEFADDEHDEHAEHDEHAEDEEDGBCHCFECFBCHGCHGEDBEABGAHFAHFHEEGFHACECCADEDCEFCAFGFG,False +489,15.0,27.0,19.0,19.0,24.0,16.0,18.0,23.0,GDHCDCEEBEBBHABHFBGFEGDDHDFACCAGGADEBDEHABHAFHGBHAFCAFCBFCFHCHDEHDBBFABDEGCECHDDDDGEAGHAFHFEBBEAHCAHFGHABEFEHDHHDCGBEHBEBCCBGDGEBGEBEECEGBECBEBDEBFGHABHFFDGCCGBC,False +490,3.0,2.0,6.0,3.0,7.0,0.0,1.0,4.0,CBCEHEADEACEADEDBCGHHECHEC,True +491,14.0,16.0,16.0,14.0,17.0,13.0,22.0,10.0,FADFCGFCEFCEBCGBCBBCBBAFBGGBGBEEEFDBBDHEEHGHAGHAGDDGBEAAGDFCHADHGDHGHFBDEDDEFECCEGGGGGADGCBEEHDCGCCGABHDBFAFEEECCAGAFGAFCA,False +492,26.0,18.0,20.0,24.0,26.0,19.0,29.0,28.0,DCADFADCEHGDGGFGEAHEHHAHFCCCGHBAHEAECBBGGBHGBHDBAAFECHEBHGFHCAHDAHDAHACHCGHCAAEGGGDBGDGGDEGHHDCGEEGEDAEDCGFCDFEFFADHGBCABHDBEGBGBHCHFGDFEFFEBBEDBEAAEFEBFGBAHAAHECDGDDFDACCAFAEHGEDGEDCEHFGHFA,False +493,1.0,0.0,2.0,1.0,4.0,2.0,0.0,0.0,ECEECEAFFD,True +494,11.0,16.0,14.0,24.0,25.0,15.0,20.0,16.0,HFCEDHDDCEGCFADBEDCEDAFBACGFFGHDDDGBDFEAFCAFHDFHEFBAFBDEBEHCEDBHDGHDFAEFCECCBGGBFDBCDHAHBGEBEEHGGHABDGDGGDHADGAEEBFECEECGEGGEBEEBHGCHGDHGDEDE,False +495,15.0,21.0,13.0,15.0,18.0,25.0,20.0,12.0,GFGGDGBFFFDCCDGCDECAEFFFHCECCEDEEAEEBEFHDHBGGBGGEGHAGEAGBGEAFAHFACFCHGBBGBBCCDEGDFFFFABBBEBDAGDAHFACFAFDABDBBEFDEFAFBBFBBFEHHGHDDHBFGAFHEGC,False +496,14.0,17.0,8.0,12.0,24.0,10.0,23.0,11.0,GBFGBDGAFGBGEBFEHDGAFEBCGGGBABDAEDGEFBAFHEFHBFHEEBGEBAEGGEFGEABAHBGHBCFGEGCAGCEHEGHDDEBAGCAGBECDECDEGDEGDBDHEEHAEHDCAAE,False +497,8.0,11.0,13.0,8.0,7.0,15.0,9.0,16.0,EHBHFAFCAGEGGCCGCAGBAGHDFFCFHBHHDDHFCAECHDBHCBHAFFDFEHCGDFGAFCAFCGFEBBCBBCFHDHEDHFBHEBH,False +498,3.0,6.0,8.0,3.0,3.0,7.0,4.0,5.0,CHECBEABACCGCBGFHFFBGDBFDAFDEFCGBCHFHHC,False +499,7.0,4.0,9.0,5.0,5.0,8.0,3.0,3.0,ECEEFHFFACFAHAABEABDCCGFDGFCCFCCFGDABDCDEBAH,False +500,7.0,8.0,5.0,8.0,4.0,3.0,2.0,4.0,CAEFHGBDDBDDBDDBCGBCFDFDHCAEAEHBEABAAHACB,True +501,22.0,26.0,22.0,26.0,16.0,25.0,21.0,27.0,EBHCGHBFHBFBAEEAHFAHEADFGDFBFHCHCCHGAAAAAHAGBBBDBCHCEHBHHGDDFBEFDECDBFFHFFDDDDDFDAACHBDABDHGCEGCGHFGAFDCFGCFGBBGFACDAGHFGHEEAEEAHHBDDAABBCBCDDCDCGHFGHEBHABGFCGCEGCBCHBCHDGFFBFGEFDEHDBAD,False +502,10.0,11.0,12.0,13.0,8.0,15.0,13.0,13.0,GFHHEHDCHDEFDADGCDGBDFADFHFACFACACBFCGFCAFEECBECBACAFDEHBGGAAFDGHCBDCBHGBHDFHDHGEFGFHGFHDBEBGGB,False +503,5.0,6.0,10.0,4.0,4.0,8.0,9.0,0.0,FEDCEDCGBGGBCFCFEDBEGAACABCGCCGFFGFFDAGGBCABCF,True +504,7.0,14.0,10.0,11.0,12.0,9.0,6.0,15.0,BDBBGBFCEDCHDCHEFFECHGDEEHEDHDBCDHGABFABFBBDBBCEECHEGFAHCGFBHFAHFAHDCEAHBDCBDHGEHAEH,False +505,21.0,9.0,16.0,11.0,15.0,16.0,15.0,15.0,DFAGEAGEAFCCECCECFEGFHGDHAFBCHEDHEHBEAGFCHDHGAHFFCAAGAAGAAGAFEDGCDFHGEHFEDFBDCAHGAHBABEABGABEDFFHGFCEACHADEBCCBGFDCCHA,False +506,17.0,15.0,12.0,11.0,15.0,5.0,18.0,14.0,BHGDHFBGBBABHAEGAEDAEAEDBEDGCGHADCFEHAGHAHHAFADCBBGEGGBDBBDEHHHGGBGADGACHCEGCEHAABFAEHAECAECEECFBCGDCGBCGDG,False +507,23.0,16.0,18.0,17.0,15.0,30.0,19.0,16.0,CAHCHFAHFDGFDGEHAABDAFCAFBAGBHGHCDBAAFGFFGADAHDGDGGFEDFEDCCCCDHGFFGFFCHFAFEAFEFHGBEFEEFEECDBGGHHGHCEHEGCADCEBAFBFDBGBCHBFFBFFBCDBDGAGFABEAEAAFFCBFCADCADHA,False +508,2.0,2.0,6.0,5.0,8.0,2.0,3.0,4.0,AECAHCEDEEGEDCFFCBECDDGGDHECHEBH,True +509,10.0,15.0,13.0,10.0,20.0,25.0,8.0,14.0,BFFFFGHDGHBEECGECGEHFEFAGBHGBEDEGAEAHHFFHCFCFFHEFADFBCEHCEGFAHFHEFECBDCBDABDCBFCBDHBEFCEFCHFEBEBFEAFACFHFBAFEADDDBE,False +510,9.0,6.0,15.0,8.0,8.0,15.0,8.0,4.0,CGFCHFDFCDFADGADECCCFCAFBFFCCFEGFDGFCGCCEBBEAEEAEFGHDGDFCHFEFAGDABBCBCAHA,False +511,1.0,1.0,2.0,5.0,3.0,1.0,4.0,3.0,GDDGCBGCHDEEDHEDFAGH,True +512,16.0,13.0,8.0,20.0,20.0,20.0,19.0,18.0,GEEGAEDHBDFBGBGGHGEEDHEHEGFEGBEGFHGEDBBAHGFDAFDAEDGFFHFFHEEHDEHDGDGADCADFADABFHDFCEFCHFDGAGABHAFHGHCBFCHEHBEAAEAAEBCEDFGABDCHFCBFDFDDG,False +513,2.0,0.0,0.0,0.0,3.0,1.0,1.0,4.0,HHEHHEAGAFE,True +514,16.0,32.0,27.0,32.0,20.0,18.0,31.0,18.0,FFCEHGEAGHCGDDGHDFEDFDDBDCHDAABHAGDEGDEGEFCBDAEABBAGBCGHEEDCCBCCAECAGBDFBCHGHHDHADGGGCCFFAGBGFDGACBHCBDAEDBEDAGDHCDGCEGFGCEGDADDCHBGHBAHBEGBEFBFGBHDHGEBBDBBFCCCDEBDFBDBBGFBGFBGFBGFHDBCCCEBCGDCED,False +515,26.0,15.0,26.0,29.0,17.0,18.0,23.0,22.0,GFHDAEAAEGAEGCEDCDDCAHCABBAEBECGEBHHGAADFECFBCFECEDGDDCDCGDBDFGCGHDAHFADDAHCADDGDFGDEAAGAFDHGCHDCBDCGCBGCBFABGAHHBHDFHDFDDGDCFFAHBEHECCFCBACHACEGCEHHBHFGHCGDAGDAGECBFHAAGFFDEAH,False +516,12.0,12.0,20.0,17.0,22.0,17.0,13.0,11.0,EEBEADDAFDADAHHEEBGEBFFBEBCCDFCEFCEFCEFCABEFHEFCEFGFCGCGHCHDCGFBECACAGDAHDGGDHFDHADEADBFHBFABDHECFDCHCEGGDCDDCGBEAFEBECGECGE,False +517,17.0,18.0,11.0,13.0,13.0,9.0,14.0,20.0,BEFHACHEDBAAHAHHAGBAGCGGHAADEHDEHBBHGEHAEHGEDGEBCEBCHAAHBCHADHCDBGFBGHAABBFFFCCFACBGDBGDBFDCFDCBEHFHHEGBADEDHEGGABD,False +518,20.0,13.0,17.0,15.0,17.0,19.0,27.0,13.0,CFECBCGACDECDHCHAGGAGGAGGAGEAGHBGFFGHHDEHDHDDGAAGDDGDHBEFDAGBABEECEAABAAFAGFGDFCDCEFGECBCGGEGHEGHBGEFHFFDCCAFGAFEAEEFCFACFGBDCBCAHGBEGFDFHBFB,False +519,4.0,10.0,8.0,8.0,7.0,6.0,3.0,5.0,EABADFAHCBFGDFCDCCBACBEFDGBHGBHFEHFECEDHBCCBEDBEDBD,False +520,21.0,21.0,12.0,9.0,4.0,4.0,12.0,8.0,FAACBBBAABGAFADBABBDBBABHACGACBABBHHCECAACAHGDHGABCBDABAGBDGDAEDGCDGCABFEHEAHFBHGADGCCGBCGB,True +521,7.0,6.0,5.0,6.0,9.0,6.0,4.0,9.0,HDFFDAFDAFBFEAGABCHCHHBFHBGEBHEHHEHEDAECEEGACDECDBGA,False +522,7.0,13.0,6.0,12.0,9.0,15.0,17.0,9.0,FEHCDBCDGGDGGDHFBHAEFDEFDFGEAABAFBHCBEFBACDGBDGHHBFGDFEDEEGGBGGBHGFGFEGHCFBFFBGFGHBADCAD,False +523,13.0,18.0,26.0,23.0,24.0,18.0,20.0,22.0,HDCHAFHBBHAEFFCCGDFGAFCFDBHGFGEFBEGCEHDHHEGCEGEDBDDBGAFHCFHCAECHBFHADHFDHECFBCBBEEDGBCGEEEDGHFGECCECDACDGFBCACCDDGDDEBDGBDGAACABCABCFBEFEDHEDHDGHEFHECDECGAHGEHGCCBH,False +524,23.0,26.0,27.0,25.0,18.0,14.0,25.0,20.0,AHEABADDECBHGBEGDCHHCEDCECAFCACEFEEGGDGGDGEDGCFBAEAHFGDFCACHEBDDBADBADBDDACFAFAGCBBHBGGFDBFDGAAGAHGDHFBEEDCCDCBACHHCHECFDDHABAACAAGHHGBGGBGFBGFHDCBDCBHBHHCDFCDEBGHBGACGCCGECBBBEE,False +525,9.0,5.0,7.0,9.0,10.0,14.0,16.0,12.0,GDEGFEHFGFFECEBCBHHAHAGHAGDFCDHBDAFFFGFGGHBDHFDCFDCDGFEGEGCEGAGAAHAGEGHEHFEHFGCDBA,False +526,21.0,20.0,28.0,24.0,24.0,22.0,22.0,28.0,FBFFHFFDFEBCDDDFBEABCGECGECFHFFCFDAACAAHAHCDHGHHFHCBHBDHGDGDHAHCDHGABAABGCGAAFBGFCDFCDFCABEHDEAGHABHEBAEFHCAEABHGHHACFEGEEFEEGDFGDCCDCEDHHGBHGEHGECGDHDDAFCEBDHBGGECBDCBGCAGCEBCECEBCEHCDHEDF,False +527,20.0,11.0,8.0,13.0,17.0,8.0,13.0,14.0,DDHGDHCDHDDHEGFEDECAEHFFHAABEGBEHBCAGADGACFACECDEAHGABBCEAAEAGFABAABAHGFHEEGGDCEBAFGFHGAEDHEDHEABEABDHBG,False +528,9.0,13.0,8.0,10.0,8.0,6.0,9.0,7.0,ECDBCHEGHFFBEDBGDBHDBHDFHFEBBCDFDACACCBEHBAGBAGFDGADGACHABDAEABGGEGCEB,False +529,2.0,5.0,6.0,3.0,4.0,6.0,5.0,4.0,FCBFCBFCDCHDEHBFGFFGAEAHEGBCGCHDEBG,False +530,5.0,3.0,3.0,2.0,4.0,2.0,5.0,5.0,AFBAEGACGFGHCEHEBGEHGHDAHDACB,False +531,14.0,18.0,15.0,23.0,16.0,17.0,15.0,32.0,HBAHEDHGDHCDHDEHDEHDEHDHFAGADFEEHBBDFHDAEDEEHHHBHDFHDFHCFCFECABGGBEGCEBFBBDBDCCHCAACFACFHEEHCHHDHGFHGFHDCDDBEBGHAFFCGBAEBAHBGHAGFBGAHCFFBDGDCBDHGHGDHA,False +532,8.0,6.0,17.0,12.0,9.0,14.0,14.0,11.0,DEGAFHFDCCDGCHHBHCFDCFDCEGGFHHCAGEGBFGBDGDAGHCGCCGDCHDGEDBEFFCFDCGHCEHEGHACCAFAFFDFFAEBAEBC,False +533,15.0,11.0,12.0,12.0,16.0,22.0,21.0,18.0,GAAFFACGGFHDCBDFBAFBAGEAFEBFGGFDDEGFEACHFFBDFGEGDFFAHFHHAHHEHHFHFABECBDHHDCHDGGDGGEFGEHACGACGECEECEEBDBHDHHFHEFGGCABCAFEFCGGGBA,False +534,6.0,6.0,12.0,13.0,5.0,12.0,12.0,8.0,HDGAGHFGHFCHABHFEHFACCCBCEGCGDCDEADCFDHGDGFDGFBGCDCHFFEGFAFDDFDDGADCBECBGB,False +535,22.0,16.0,25.0,15.0,17.0,33.0,16.0,16.0,FBFFEECEEDFEFEEBGGDGFEAAEFCGFDGHDGDEGAAAHACFECDACDCHFCHFAFFAFEGFBDFECHHBACBCCACDAGFGDFEDFCCFHCBCCFACAAGADGHEFFCBFHDFCDHBHGECAFFGBGBFGAAAFBHFHHFEBFCDFCBACBHCBHAB,False +536,20.0,17.0,26.0,15.0,22.0,17.0,17.0,16.0,BHHBAFEEFAEFAEDBBDFEEBCEHHAAHAGBDGBHBECECCBFFAFEACEGCEFEECDDDGBDABEEBEHAAHCFCCEACDAHAGHBGFACFHCGHCFCCBCFGHDHCDHCDGCEAHGAFBADGGFCBFCGDCGCCFADECDGGEGAEB,False +537,13.0,10.0,5.0,5.0,10.0,8.0,9.0,7.0,EADEDEAAGAEEBGGHHBFFBFEBFBBDEAHEABCAHCAEFAGDAEDBFFGFAGAHGCHGHABCGBC,False +538,10.0,10.0,16.0,12.0,12.0,14.0,12.0,13.0,DFCGBCDFCDGBDCFCFFCFDAHDCBECEEBEDBEHECFECGAHGDHEAHAHHGFHGDHFFCGGCEGFGGCGCAAHHAEHCBDFBDEBAFADFAEBCBH,False +539,2.0,2.0,4.0,2.0,0.0,2.0,1.0,0.0,ACCFCAFCBDDBG,True +540,3.0,8.0,6.0,4.0,2.0,10.0,5.0,6.0,FGBFBFDBFDBFHFFGCEAFHCCBFCBECFABGDGHDGHBHHAC,True +541,4.0,4.0,3.0,5.0,9.0,9.0,6.0,7.0,HHFDFBDFAFFAEFEHGEHGEBGEAHFDEBCGHGGFEAFDDHCEBCE,False +542,1.0,6.0,4.0,1.0,3.0,1.0,2.0,0.0,EGEEDACCFCCBBBBBGB,True +543,11.0,8.0,11.0,8.0,8.0,12.0,13.0,10.0,CGFCHFHAFHGCGCCHCGHGACBDDBCDFADFADFBBEDAEGACFAHHGBHGDAEFGEAGEABHBGFBAEEGEHDFCGFCF,False +544,1.0,2.0,1.0,1.0,0.0,0.0,2.0,3.0,GDAHBCHBGH,True +545,20.0,18.0,24.0,26.0,24.0,22.0,18.0,33.0,CBHDDADAHFAEFCEHCEHEBHCBGCHAAHAFHFFEAFDAFBEEGHAGDDDACDHCEECEGDEGDEGBADBEDBAACEECHFBFCHFHHEEDBHHAEFCCHHFDBFDHCHHAHHAHGCHCCGFCGBGGFGDFBHFDGGDCEDADDADCFBCHBCBFHEHBEGAFHCCBEFFHDHGAEGDBGDEHD,False +546,29.0,23.0,21.0,19.0,21.0,27.0,25.0,20.0,BHEADFCDFGBFAFFACEAGFABFACFACFHEBHBFHDFGEGCEHCGDCDFCACAGDEBDEFAEFGEGGHCEHEAFEGECAAGAAEFFFFDFGGGCDGBGEBGHBGEBADFGCAGEADDBDDBACCCBDBBHAAABAHBACGECDDHGHHGBFEACHBFHEDCFDAHEAGCBGBAHFAHFBHFBH,False +547,8.0,14.0,13.0,15.0,21.0,12.0,10.0,20.0,CHCHGGHDDADDEGDBGFHCBECDEFBGHEECEGCFAEHHEHHCHHCHFFAAEDAHDEGBEHAAGBEHDEDBCFFEFCEFCHHEHBEHBEHEDDEGDGABCEBDBBCBFFBDF,False +548,5.0,4.0,1.0,2.0,4.0,2.0,2.0,2.0,ACBADGEEGEEBAFBFHDAHBA,True +549,14.0,13.0,9.0,11.0,17.0,24.0,19.0,14.0,EHAEHGEDBEDCEGGEHFBFBBGBGGFHAFHBFEACBACEADGFEACGFEGFADHGDAGCBGHGCFEBAHBGHAHADDAFDHGGHGFFGFFCFFEAFEGEEFFHFDBBDCBEHFFDFAEFC,False +550,8.0,20.0,16.0,21.0,30.0,20.0,19.0,15.0,FHEAEECEEGBBBBBHBBDDCDDCDBCBFFEGFBCEHEEHEEBEEHFDCEECGBBGAGAHCAFCAFGDEGCEFEHCDBEDHGCGFFGEEGEECBEFEHFHCDHBDFDDGGDHEFHGDECDEHEGACFAFFGFBGBGAFGDDDDDBEFBH,False +551,8.0,3.0,13.0,5.0,6.0,13.0,5.0,7.0,BDFEDFGCFCHFCGCAFFAFFHFGCAGHAEHCBCCEHCHDCADCFFAEFCCDHGEFAEBA,True +552,10.0,10.0,17.0,16.0,16.0,11.0,4.0,13.0,CABEDBDDCCDFHBACBAEEDFGACHECHECEDHDDBDDHAHCBHEFHEFHEDDGACAECHEFBEFDEDDHCBHCHFGBFEBDCFACEGCAACFCEF,False +553,29.0,25.0,19.0,15.0,29.0,33.0,22.0,26.0,EABECBEDDEFBHACGBHHEHFFAFFEDBAGFCHDGEDEHDGDDCADHAFFABHCFEEBAECAECHHHACCAEABEABCCECFECEGCHGCFFBFFBEFDGGAGAECHEHHDHHABDEHAEFFEAFAFFAGFHGEAGFFGFAACAEFFEGBAABFGBEGDFHDFHEFBBHDHHGHBCABABBFBBGBGGEAGBFGCFH,False +554,19.0,13.0,14.0,11.0,11.0,13.0,12.0,8.0,ABGABGBBFEBEDGCDFCEAGEAGHAGFAGHACHCDHADCADFGDCDDAFEGFEDHHAGCGCFDEHBEFCFFCFEABGABFCHEBABBACADEAFBABACC,False +555,4.0,7.0,2.0,2.0,5.0,4.0,2.0,1.0,ABBABDFBHFBEFEGBAGEAEEFDCCB,True +556,33.0,24.0,13.0,22.0,28.0,22.0,18.0,30.0,EEFABBCDBADEGEHHHCAHGEHABDDBDAGAABDGBABBAGBEBHEFDEDCHDAEDBFHEAHFAHFABFCBEHBEHAEHCHHFEHBEHFEFFHAFHAGHEGDDHBCEDGAFGECHHDHFAEFAECAGAGCEGADDAEBABAAHHAHGAHFEEECAACGFCDFDDFAFEBBGHBGBAFBEHDFGDCGDFA,False +557,21.0,20.0,17.0,15.0,9.0,13.0,11.0,17.0,FFFCCBHDBHDBDDBDDHDCGFBAHBHCCDAADHAHHADGADCCHBCFECEACECCFDABDCEHEHHEBHDFFABAABAGBEGAHGACGCGGFBBHBAFBABAGHAFHFGCGDEFBBCABAAE,False +558,17.0,17.0,12.0,11.0,13.0,15.0,10.0,21.0,AACABFAEFAEGCEBAFBFHBDHEAHEBEEHDHHBHCBFGAFGFCACBFBDFADFCDBHHBHDACECHHDABGBBGFGHDACEBCEBCAFHDEBDCAAHHFHHFGHEGAEGHFGHD,False +559,14.0,31.0,29.0,20.0,24.0,28.0,19.0,25.0,CBHCBFCBGABHAFHAGDBEEHABFAEDGEDECFFCBFDFFDEAEHDDCECEHCBACBDFBCEECGGCGFCFHEABDABDGBDAHFHHGADGEFHDGHEFHEBBEBGCBFBBDCEGFFAHGBHAFFGFFHEFHCCHBBHFEHGBDDHCBCFBCFBCADCDBCGCCBBCBECGDCHDFHBGHFGFCEEHEE,False +560,11.0,11.0,9.0,9.0,7.0,8.0,12.0,11.0,FDCFDGECEACDHCFAFGAFAFECFCHECHABHGBHBBHBGEGGAGGAFDBHDCHDBEDGABEAGACHBHDBDABGHG,False +561,17.0,20.0,22.0,24.0,12.0,25.0,33.0,19.0,GFGGFCGFGDHGBCGHGHHGHCGHDGCGCDDCHGCFGFAHCHFDFCDEBDEBGFCEFCFFGAFCCGCHACBFDFGEEBBDDBECAFGAFGADGADGDDGADGFDEBDBBDBGCAGHGGDGGBBDFHCCDCEFABHHBHEEHBDHAFAGEAGDABFAHHAFBFGDCEBCBFFA,False +562,11.0,10.0,11.0,8.0,5.0,15.0,7.0,5.0,GBAGDDBFDHFDGFAACAACBBGFGEBGFFCFFCEFBEFBCBACFFCAHCAHEEDBAHFCFFCDDAGCAHDB,False +563,20.0,11.0,17.0,13.0,14.0,9.0,14.0,23.0,BAGDHGEHCAGCGEFAEFBCCHCCBDADHBDHADHCGHAGAFEAHHAHHACGCEACAHCDHBDGGDFEBFHHDHHCAHGAHFEEDGFDECDHHEHACFGHFECEGBBCAACAABDABEGBE,False +564,25.0,13.0,20.0,11.0,13.0,16.0,8.0,5.0,AAAAFFCFFBBFABDAGEAGAHGACCFEFGEGAEAACACEFCFFCDCHFBBCBCCADFBHFDCCBGABGCBABBDFACAAFGACACDEEDECDBDAEDAHDAECAECEEHF,False +565,28.0,15.0,20.0,25.0,16.0,15.0,18.0,16.0,AADAACACCACGGBEGAEGBEGFHCHCCEBCEBDBBDBCDAEDEBDABDFFHHEAADAHHGHGBDGCAGFADAADADFHEFHFGDEBDFCAFEHFBBFDHCDADDACDHFHAGCGDAGCABADCADEAGEGCHDDBDCAGFHGHCGAEFFECE,False +566,7.0,8.0,2.0,9.0,6.0,8.0,0.0,5.0,HEFHDFDDHDBEDBEFBDBBECBAFBFDAFHAFEDDBCEAAAFHA,True +567,12.0,8.0,8.0,9.0,5.0,12.0,6.0,5.0,DADDAGBGGBCHFGFDAFCACAEFADFGBFABCDDFEDFECHECDBAEAHCAHBACBFFAFFBGH,False +568,27.0,25.0,25.0,24.0,19.0,25.0,34.0,18.0,GGBDADGGGAGEFFECFEBGEADDADDAFHBBHBCFBCGGEGEDHDHBDFBACBGCFACBCGBEGHHGCAGHGBAFAHHBFHAFECHCABFGHCDHEFEFCEDCEGBGGDAGFFGFFGAFBEFEAFEGFDBFCAGCAGCABAHHHCEACBGEBDEAACCFGGFGDBGDCCDBEGBCDFADBAGBADDADHCDHCDGA,False +569,17.0,19.0,19.0,27.0,20.0,24.0,19.0,16.0,DCECCEHDBFDEDGEAGFGFBCHBCAGAHGFDAFDBHAGEADCHDCDGCBHCEFCHFCGFAADABFABFEECGFHHDHBDEBDBCFEEFEEAECGDBFCBDHBDEBDAFDAHCGDEBDEHDFADFDDFGAFEFCAFHDBEBBDGGACDBCHGFFGFGGEGH,False +570,14.0,23.0,26.0,22.0,21.0,32.0,13.0,35.0,DEACHFHFDHEHFCHFCEFBFHBECFECHDGEDFFDEFHFBCCACCHGDFCHFEHCAHCHHCEHEEHCHHCAHDDGFBHCBEAGGDBGFBEHBHFBADBFDAFGGGABHAGHABDFBFHCFDCFDHEHCEAAEGCBGDFCFFEFDBFBBFBCHBHDBEDHDDBAFFCFHAEHCEHCBHDBCDEGFH,False +571,12.0,18.0,32.0,29.0,10.0,22.0,15.0,20.0,DAHAAEGCCHHEBCEBHDDGDDFFCCCCCHCFHDDHDHADBEFBECBCDBCDFEDGHDHCECGACDAEGGDGDBFHCFDGDDGAEFDCFDAADAADHBCBBCGEDBBHCFHCABFDHFBFCBCCBCCHCFFDGCGGCHCBFDFFDFFCFHHBHGFCGD,False +572,19.0,12.0,16.0,19.0,24.0,11.0,17.0,21.0,AEAGEAEEBDEGDECBBDAHDAFECHEFHGFGGDEHDECGGCAEHEHHCBHDDHDEGCEGAHGFEGEEGEECFADFEDEGCCABAGBAHAHHAEHACACHAFHBCBBAEAFBHDDADDGDBFHGCHFCHCCGFDHDDBE,False +573,5.0,2.0,3.0,2.0,1.0,4.0,3.0,2.0,ACEFDDFABGAGGACFAHFCHB,True +574,17.0,18.0,22.0,17.0,4.0,9.0,12.0,14.0,CCBCGGAHDAEDBCFCCHCFACFAEDAHDAHGBGDFDDCACAAFBBDDBDBBFCBECADDACBFCBHCHHABCAHGBBGBADDACHAGHDGHDHBEHBGBGGCFDAGCCCFHC,False +575,13.0,19.0,23.0,32.0,16.0,20.0,25.0,19.0,GGDDGDDCHDBGDFDDHBBHGBHBFHCEAFEHFGFEGEGGDGDFCHFAEFBCFGHDGDEGDBHDAAGHDDADEBCEGCEFCEFEDBACHAHFDEFCGFGHBBBABDCBFCHDCFFCHDDGDDGECGEDAAHAADDAFDCGCHBCGBCEHDEGFFHBDCBDBGCCGCC,False +576,9.0,9.0,12.0,4.0,5.0,6.0,12.0,11.0,BHFCHFGHEGHBGEFHADCDCGGCFGCBDABAEBACGHEGFBGBAHCDHCGHAGEAHHCCFCBGABCA,False +577,6.0,7.0,11.0,9.0,9.0,12.0,13.0,8.0,EDDGBABEGCGACGECECCBCCHGEFDEFGGFGBCGDAGHGCHBFGBFDEFCFFAGFDHBDADFADFHHFHEEHC,False +578,0.0,1.0,2.0,1.0,0.0,2.0,4.0,0.0,GCGDCGFFGB,True +579,5.0,1.0,1.0,3.0,1.0,1.0,1.0,4.0,HGAHAACAAEHDFDDHB,True +580,23.0,6.0,7.0,14.0,17.0,10.0,20.0,6.0,EEAEEHDHGCBEABGFBGEACAADADGADHCGFGGEHGAGGDEAFEAGEDEAAAAAAEGCFGDFGDEGAEAFBAHBAGDFGDFECCECGDBAAGDEGHAFDDF,True +581,26.0,18.0,18.0,18.0,15.0,22.0,19.0,23.0,FFFAFECGECGHCGACGACAFFGHGEHADHFDHBDHCACGABGAFHHGAFGABDABAFBHEBAEAHFAGCAGCGFAEDGHFGAEBAEHDDHBDFAFBHDBFCHEHHGFDDBAEHAECAHGHECDFDDHHBFHBFCBADFFDCCDBCABGEBCEBDEGAC,False +582,21.0,17.0,16.0,25.0,18.0,9.0,13.0,8.0,GAHDCGBCBACDDBDGADCEDBFDAFDADEAEEBEHADFAHEGDBGFHGHCBAAHDEHEEACDACDECFEAHAGGAEGAEFADBGEBGCDDCFDABDCCAGBADBDFFDGDECDBCDCCEEBBEBBA,False +583,3.0,13.0,7.0,7.0,6.0,7.0,7.0,14.0,CGGBGGBGFBHBBHCAEBHEBHFFFDFADCDBFEBGCBCHHHDHHDBHEGDECBAHFDHBEHCH,False +584,19.0,16.0,23.0,16.0,22.0,21.0,12.0,29.0,CGHFFHFFHCFGDFDEECFDCDDABFAEAADFBEAECAEGAECHHCHAEHFECCHGCHGEGGEDHBABFAHEEBGEHHHBHHCDBCDBADCACABCBCCBHBGHDFHBFHCABGDCFCCADHAHHEHHEHFEABEGGAFDFEEFEAFCDDEHFBHCHF,False +585,5.0,14.0,11.0,11.0,4.0,5.0,12.0,10.0,DGDBCBFGBDAEHACCEHCDCCBHFBHFBHCAHGGGCGGBGCBEDBGBAGHFCHDCGDBHABEFBDDBDDHG,False +586,11.0,24.0,18.0,11.0,8.0,6.0,17.0,13.0,GBBGABCCDDEGDFGAHEAHCAEGBEGAEABEAHHCHBBHCBHCBGGGGGGBHCBCCBDDDCGGBEFFADFGBCABGBBDCBDBHABHBBHFBDFCHCBGDHACCCEC,False +587,14.0,18.0,17.0,13.0,15.0,17.0,25.0,21.0,ECCAFEAGBAGCGFCGHADHEBGCGGCBDCGABDHBEGBCGHHGFHGHHGHDGCACAEHBBBABGFHGFDGFDBDGBAHHGGBCEFCFHHFEHFEFFAFFAGFCHCHGABCHEFHCFEBDEBDACGAEGEEHBBDEDDGD,False +588,13.0,15.0,14.0,18.0,15.0,14.0,13.0,9.0,EFAHGBHGDHGDCADGDDEEEECFACDGDGHCCFCEDCBHFBGDBCDBCGFCGBCEDDEAFEAECAFCDFDDBHABHFEEBBHBACBADBGDEABFGFFADGAGFAEFEBH,False +589,12.0,8.0,10.0,3.0,6.0,15.0,8.0,10.0,FDAFCFFHFGHFGBFHAHAADACFCCBBCBBHADHACFAHBBCGGEBECHGAHEAEEAFFFCFFHGFCGAEG,False +590,17.0,15.0,7.0,14.0,11.0,14.0,9.0,6.0,HEAFCADCHBHAFEFFEDAAFBABCGDDFAAGDGDCBEBFEBDEBAEAEBAEBAFBGFBHFCGCHGHDGFAAFCADBDDBDDGFAGFABEDBE,False +591,10.0,3.0,10.0,5.0,10.0,14.0,7.0,11.0,CFGCFEAFHGFCGAHACGFEADCAECAEBEDGFDHFEHFEHBEHFECFAAFHAECDHGDBFHHFAHCCFG,False +592,19.0,16.0,12.0,22.0,13.0,29.0,15.0,13.0,GHBEBBFBGFCCFDDECDGGDFGAFABCHFAFFABBCHBAFGHFBEFDEFGEFGDDGDDACDBCEAFEACEDDFFAHEAEDDHHFFDFBGFHGDBFHECCCFBDEBAHFAEFAGFBGDHADAFDAFDAFHAFGAGCHDB,False +593,7.0,6.0,8.0,6.0,8.0,9.0,6.0,6.0,DCHBFDCFDGACEACBBCBGHAGHFEHFEHDEGAEAACGFBFCHFCAEDFEBEDGF,False +594,30.0,31.0,17.0,16.0,20.0,23.0,18.0,23.0,ECHGCHGBBGFBGABGCDGHFFBFABDADAFEAFEHGBAABEABHABHACFACBEFADDADFBCGHHABFEBEGBCGEHFEFEBGEHGDAFBHDAFBAHBAHFAFACGDCHDCHDGBEBHEFEAFEDHACEBCFBCHBFHBAACFCBAHGHDDEADHAECACGBBABAFBFEBGEHGD,False +595,9.0,14.0,16.0,12.0,7.0,14.0,15.0,6.0,FEGFGGFDBAGEFGEFCCHCBEFBCGACBACFCCBCAFCAGGFFCBHGBHDBADADHADGBDGBDEBCHFCFCCGBDGDHEDADDFEBGGCFB,False +596,26.0,34.0,20.0,24.0,21.0,26.0,22.0,25.0,FEEBEHGEHEFHEFEEACGABBDHDDHGCGFDACBGBHGFHDADCFGCGBDAHHCFHGFEEFEAHEBHGBAABDABFAHFHDDADDFDBGGBFHBAEBAEBAHBAFACFADADDAGGBBGBBCCACFFBDFHDFHDBCBCABAECDFGDGHHEECCAFDBDEFCEFGDBBHBBHGGHFBHEGGEBCABCFBCFCAHBA,False +597,16.0,18.0,17.0,23.0,22.0,17.0,16.0,28.0,EECBEAGEDFCFADAHFCHFCHECDBGDBHDCHAAHDDBDDCDHHFHBAHBEHDEHAFHAHHEEGEEGDEBDEDDHBEBGEHGEHCACFHBDBACHECEBCACCGCGGEHHDHBFGEABFDFFDGFAHCGHCFHBGHGDABDAFGBEGFDFBDEHFA,False +598,14.0,9.0,12.0,11.0,20.0,14.0,7.0,8.0,EEAFAGFHFFBEAGHBCFFFFDFFBAFCEGEEGDCGDCBAADAHFFHAGHACDECBEDBEAACDGCEACHDDADBECBECHEAHFDEEEEEEEBC,False +599,31.0,15.0,28.0,34.0,25.0,28.0,16.0,23.0,EADADBADCDDCGEGGEAFEFGBDDCFACDECFECFBCHAEHABGFCCAECDEDGCDGCDGEAHDBBDBACEAFBFEBEDBEBEEFGAAGADGDFFCEFAFAABDFHDFHDGCDGHDFCDFHEFAEGCFDAFDAFDEFHBCDAFEECHHDDHDCFFAHHHHCHADEADADBADBCGCCHFAFCEHHAFHAHHAEGACCCH,False +600,10.0,11.0,5.0,10.0,8.0,10.0,7.0,10.0,HBFHBHGFGEFGEFAAFAGFGEBBHBDGBHHAHCDHEHBEAFDDBBABDFDCFHEBCECCADGADFADAED,False +601,1.0,4.0,4.0,5.0,1.0,4.0,5.0,0.0,EGCDDCBDCFDFBGBDGCAGFBGF,True +602,4.0,2.0,2.0,6.0,6.0,0.0,2.0,3.0,EDEEBAEDHEAGEABCHDCDDADGH,True +603,22.0,28.0,15.0,26.0,22.0,27.0,16.0,24.0,EADBBCFGEFEAGAFEACAHCDBABGHBHAEDGGDCGFBBFHFCEFCEFEDAEGEHGABFHBFDBGDBABGGCGBCGBABHAFDDFBDFBGFHFCHFCHFHECHDFFDFABFDBHDFDCFDCABHABHEHADCDDCDHFEEDAEDFEBHHAFHGBHBBEEBDHDHEDABDABAEGEEHAF,False +604,21.0,11.0,14.0,19.0,11.0,12.0,18.0,29.0,GHHGHHAHADHAHCGBCGBDGBDHDFAABAEHFCDDAACAFHBHHDEBEGAGGEBGEHDEGFGGCHGDBDHHDAAAACFACFHBHEAAEHADHGCHGHDBCFHEFHEFECDDHFDCGDFGAFHAHHCHBCGDCAD,False +605,9.0,11.0,6.0,10.0,8.0,6.0,9.0,4.0,DCGDAGDABEBBEBGEBGDDGHAHHBCCECAHAFFAEDCEFFEDCBGBBGEGDFGDBAAFDAB,False +606,28.0,22.0,23.0,19.0,24.0,23.0,22.0,23.0,GHDEEDGFDEHCEBCEBAGAAGEGGEGABFHGFAGAHGDCCDHFBADBDDBCDBFHFDGEEGCEHFFHCCHAGHABEACCACDFEEFAFGEFBCGBCBFAFFBFFDGEEGBEHBHHDCACFHCACAABAABAECCDFHHFHBDAEFHEFEECGFBGCDGEHCBGDBAAAHCAHDEHDBHABAAG,False +607,13.0,16.0,14.0,14.0,17.0,12.0,10.0,10.0,BGHBGADGDDGCECBEDBECAECGECGECFACFBEEBEADEDHFAHAAHBFEBHDCFDGDBFFBEGCAFADDHCABDACDABDHGFFGEEBFEBABCEFEHCHHCB,False +608,9.0,17.0,16.0,8.0,12.0,15.0,18.0,16.0,BGGGDCHHBHGBEACEACEGCEHFHCBGBBGFBGFAHCDGCFFCFGCBGBBGBFGBFAHFBGFBABCEGCEADHHEHHCHFEGEDHDDCDABGHECCFCFFGBADEAEHFH,False +609,34.0,28.0,25.0,20.0,27.0,20.0,18.0,15.0,FHGFEGEBBEGBEGHFHDFDAAEAAEDCFDBFEFCDCDDGEAFEADBCCACCDFHHBCHFEDABBABBABHAFGACGEEEACCACDDCBFCDHBFGBAGCGFADEADGABFABAGEEEBHBFDBFEBGEBEBHCCDCAGCAECAECAFCHGEEBFEAGEDECAHHABABBABDFDAHCABCAGHAGA,False +610,27.0,20.0,29.0,19.0,16.0,20.0,23.0,16.0,EDGGDCDCCDCCFAHFACFEEAAGGAHFADGADAEDCEACDAGDAHDCHFAFFHCGHCGDEBAEBAFHADHCBFBBDAECAECACGGGGFFCDGBHGECFBABDABGECGEFBFCBHDBHAHGACBAHEACCACHBHEFCBDCGDBGCBGHGCBFCADEFBFFGABGCEF,False +611,22.0,21.0,24.0,24.0,11.0,17.0,21.0,18.0,CGCHDBGDBABGACGAEAACCDDCDGCDGFDEHBABFCHACHAFGDEBDEBDABHGBCFBCBAHBDFBHFCFECFECGAGEAEBDGCGGCHGDFGDFCFBHFAFGAGHHFBHDAADCAHCAGEABCCBDDEDDHCCAAHFHHDADDBGHCGBFFBEDG,False +612,15.0,15.0,16.0,7.0,8.0,15.0,11.0,10.0,BBGABCABCFCHFCBCAGHHFHFFBFAAFAGBAGDEFFCFECACDACAFCABEEGCEGCAGDBCHBDDFDDFAFHACBGBHGBHCEEEGHCGFBHBA,False +613,1.0,6.0,10.0,13.0,4.0,6.0,8.0,9.0,GCDDCDCAHCHEDFDCCDGGDBHDCHDBHCGGFGCFGHFGFFHHCBBEEBDEDDBDH,True +614,10.0,16.0,11.0,12.0,14.0,10.0,10.0,10.0,DECEGBDAEDAEGGGHGAAEBAEHDGHGEBCHBCHBFEBCBFCBAHEDFEDFGAFDCFBCFBDFBCHCCHDHBDBBABFDGEEEDCEGAHBAF,False +615,1.0,1.0,2.0,4.0,6.0,3.0,0.0,3.0,HDEHFEDCEABEHFEDDECF,True +616,10.0,6.0,9.0,12.0,6.0,14.0,6.0,4.0,DFHDFBBECCFCCFBCDGAFFABDAGEADBDDACECFECGAAGHFHFFHFFDGDAFDEFDEBDAAGC,True +617,6.0,1.0,4.0,3.0,5.0,2.0,0.0,4.0,BDEHDAAFACHECHECDEFHCAAEA,True +618,22.0,16.0,36.0,14.0,21.0,16.0,20.0,16.0,BBGEBEHHHHHACECCGBEDBCDHHAHDCHDCECAFHAFDAFCAECGCCACCGFFDEGACGCCGCEGCGGEGACGACBDGGDEAEBAEGFECAECFBGECAEFFHBCCBCHEFADFDECDBCBFDHDECDGAABHCFGCAGCFGABEABCABCECCFFAHH,False +619,26.0,17.0,24.0,18.0,27.0,15.0,23.0,23.0,ADFABEBGDCGDEAEHBHDBCGECBECEEGAHGCCECGFCAFCHECFACBAHBACBAEBDEHFEDDEHGHHGHHGAHGAHFADAAGEAEDAFAADADHEGHEGHGBHDBCEECGFCHEBHBBFAHDCGAEGEEGECGHCFCFGCDDFDCBCFEAAAFEAHGBGDCDBEFCHAG,False +620,7.0,2.0,1.0,9.0,6.0,2.0,5.0,5.0,GBEGBDDHGCFGDGHEEHDEFAADAAHAAEAHEDDDD,True +621,16.0,26.0,22.0,21.0,29.0,29.0,17.0,19.0,EAFBDDEEGGEGGEGDFBBFADADCGDCBCCHCDDEDFEDFADFEDFGBFHBECAHCDBCGFCFECEEHAFHAFCGFBEHGFHEEHFEBCGBGGHABFGDAGCABFDBFDFFDEFBBBDHBEECFEHEACBFBDFHAHHEHHEHCCHGBAEBDCCEEFBBFAFCBDCBFBAFEACEGHE,False +622,7.0,7.0,8.0,11.0,8.0,4.0,10.0,8.0,DAGDCGDHGDACDBCFHHEGDEDEFHCBHEBHFDHEHBCGGEGBCGDCFDGEDCAABAABEAG,False +623,28.0,16.0,21.0,17.0,19.0,16.0,21.0,15.0,DEHGEHCAACGFGGBEFBEGGGBGFADAEDADDCCHGGACAACEBDGFCBDAAFBCCCCCAEEEECHDCEDAEFAHFABFACFGHHBEGCEFBAHCDHDBCEBCEAHAAHAABEDGECGFAGFABFAHFAHEAHDHBFCBDDAFDAGBGGDGG,False +624,3.0,1.0,2.0,2.0,0.0,4.0,3.0,0.0,GAAFDAFGGFCDFCB,True +625,2.0,3.0,2.0,8.0,3.0,1.0,2.0,1.0,DHDDBDABEGDDGBFAEDCEDC,True +626,25.0,22.0,16.0,18.0,24.0,24.0,24.0,13.0,EBGFHAFDBGEBGEFGEDHADHADAAFCAFCHGEAGACBDGBFBDFEDGEHGEHGDHGCFCEFBEACEBHGFHEBHEGFEBAECFBABCACCABAEDEDGEGCABEEDGEAGAAGCFFDBCGHAGCAFFGFDAFHFFGEBBBHBDAGDABDBDGBAFEDFCAFCEF,False +627,29.0,21.0,28.0,24.0,31.0,21.0,20.0,20.0,FAHFBGFACEAEHGHHCFHGAGFFCCDDBDGBDGBDBHEBHECCEHCAFEGEHGEHGEGGBCABADDACDEEBCHCGAAEAFCABCEBDABEABCAECAEAHHFCFGDFHDFHBCECEDCDFCDACEFBEDBFDBEBEHHECCEDAFDGFDHEEHEGHCDDADAAEGAFADCGCGFEGFEABACFAEBACBGDA,False +628,12.0,14.0,20.0,9.0,14.0,5.0,7.0,10.0,BAHEECEFDEACFADDABAECEHFDHCCCACBAEDHEBHEBHFHCFCCGCDACAADGEGCCGCGBCBBCGBCEBEHBEDCADBEGBCABHH,False +629,5.0,5.0,7.0,3.0,4.0,2.0,2.0,2.0,EFAECAECHGHFCDABDBCDBCBCABCGEA,True +630,23.0,22.0,17.0,29.0,22.0,31.0,12.0,12.0,CCDECDBBHBBHBGFACDAEHBFBGFCCEHGEHEECEFDDFDDBEDBAFEHBDHBFFFFFFFAFFAFHDFAEFACFCCGAFAAFGADGADFFEBHEGEAAFBDGBDADDAGEACECCFBBEEGGEBDBBCAADFEDCADFFDFAEFBHDDDDBCCBFGDAEHEHDDAD,False +631,27.0,22.0,17.0,34.0,24.0,29.0,22.0,24.0,FFDCFDCHHBFADFAGECGECGBFBAFBGGACBFCBACHEFEEFBEFEEFCBAEECEHAEGAEFACFADFDBFBHHDHAFHADDGHHEHDDGEBEEGFFDDGEDGADGBDHFDHFBHFHAABAADHAEHBHGDFGEAADDFDCCDCDDFBAGCFDCGDHBDHEAFDGBEGBADEFGCDBADGADHEHGFHBDHADGACB,False +632,14.0,22.0,9.0,14.0,13.0,13.0,20.0,23.0,BCFBCFAHGDHGAHEDGEBBCBHEGHDDDBAGBAGCECBBGBDABAGHDGHEFFBHEEEEHDEBDEFAAFAHGDGCDAFHAHGADGAGCDDHHFHGFHEBHBGHBFBBFGBFHHFAHCHHBECBGBGG,False +633,24.0,22.0,20.0,25.0,23.0,16.0,19.0,23.0,DBBDHHDHHEFEEFGABGFEGADFACHGEHGEHAFFAHECCEACEBBHBEFADDDDGGHGGHAABCFDCFBGFAECDGBDABEAFECFEHBAHFDBFDBDEFCBCCGDEACAAGBBGBDEAEAAGAAHBGHACCAECGCCDCGDEHAHGBDDEDDHDBHDHHFCHDBHEBCE,False +634,17.0,21.0,22.0,24.0,23.0,23.0,16.0,18.0,CBHDBHCEHCHBGDBECHEHFBCFDFBDFCGFCACCACCGDEAFGADEADFCDFBAHAGHGEBDDBDEBDHBGBDAEDBEDCEFCEFHBHCGDAHAAEDEEGGECBEHDGDBGEHFEFGEFBFFAFFCCFECEDHEGCAGBACFDGFDHFBABHADFBEFHADC,False +635,16.0,6.0,8.0,5.0,5.0,8.0,8.0,4.0,FFABFACAAFAAHAFHCEACEABFCDGCFACABGGDGCABAEBGEAGBAGHACHFEDDDG,False +636,0.0,0.0,0.0,2.0,3.0,1.0,3.0,2.0,EHGEHDEDGFG,True +637,9.0,16.0,10.0,10.0,13.0,11.0,8.0,12.0,FEDBEDBEBBEFBEHBFBFCBEGBAGBHGHDBDDEGBECEFHDDHCFHGBHEBCGBEFAACBDEFCGFAAHAHHFFAADAHDCHGCECC,False +638,12.0,9.0,9.0,12.0,9.0,15.0,8.0,15.0,EFGFDCDAGDHFCBFEAFHACHBGADEEHEFGEDHFDGDDGAECCFHBFHBCACHACHACFAFBGDBGDBHBHHBHDEHDAAAEFFFHF,False +639,14.0,20.0,11.0,14.0,9.0,16.0,14.0,14.0,BFBHEBAEDADCGDAGDAFBHCBACBAEAHHCGBCGFCGAABFCBFGADBFFFDFCDFEAGGDHDDEFFHGHHGHHEFEBHBBGDBCHBEHBEFBCABDGGDCGAFHBFABD,False +640,8.0,6.0,17.0,2.0,13.0,12.0,17.0,7.0,HCFFGFCHCCACAADFGBFCFFCGFCABGBEABGCEGCEGCACCFGDGECGHCAEGBEGEEGHBGEAFEHFEHGHGEECCGF,True +641,14.0,17.0,15.0,14.0,30.0,13.0,21.0,15.0,BBGEDAHDBBEHBCBEHAEGAFGECGACGADAFGFFGFEGDBCCBFCHDHABHEBGEDADDHEGHBBHEGCGCHEEHEEHGEHACACCEGCGGEDGFGAFDBFCAFBAFEEEHGEGFEBEEBHEFDECEEDEBGEDCAD,False +642,26.0,25.0,28.0,26.0,13.0,16.0,19.0,13.0,EBDECDGCAACBAHFACDCCBCDDHDFBDBDAHGAHGBHGBCFDEADGADGHFGBAHBCCDHBDFDFHAEEFDCGGCFCAFGACGCCFADBAEBGBGGBFGDFBFCAACAACECBBHBBGABGFCAHCDFGDCCEBCDACHBCAAEDEEDFEHEDABDACDAGDBB,False +643,14.0,19.0,17.0,9.0,14.0,22.0,18.0,8.0,GCCFBFFBEABEHDEBDGBDFAHFBHCBDEBDGBDHHFFGAFGCGHCACFBGGAGGFEGFCAFCADGGCFECECGFAGFAGACHAFHDCBBCBFABFEBCCBGFEAECDBBFFBAEEEEFG,False +644,15.0,27.0,16.0,22.0,21.0,27.0,27.0,18.0,EDFEFFDFBDGBEGBHCFHCFHFAHFGFFEHGEBGEBGABGCGEBGFFHADEDGEBFABGAEFEGFGGAGFDHFBHCBADAEFBCFCCHDFBEADEDBBBGDBDCACCFCEFDDFBHHAGHGGBGBEGCFCBFEGDAGDEHCEHEBHEBADHDHHDGCDGBAFBDCGAFGDBB,False +645,14.0,11.0,10.0,13.0,16.0,12.0,10.0,15.0,EEHEEHGEFGEDEDBGCBHHFHBFDBEEBEBAHBDGACGADGHEHHECDFHDFDFAEFACFBEBHEHAGDCHDCDGCFAAFAAGCDGCAAAHHFBCDBAFE,False +646,3.0,5.0,2.0,4.0,7.0,6.0,2.0,5.0,EEDEFDFHDFHGFHCBHFBEEEABHABFDBGCEA,True +647,17.0,19.0,20.0,19.0,12.0,18.0,17.0,19.0,HCFBAFBDFDHBCACEAFHCGGCAHBHHBHFECADGBGCDACAECGDCFDFEHBABGADGACGBEFHGFBDBCCBCFBDFADFGGFEGFHGFEBDDBDDADBFGCFGHECHCHHGGBECECCEBDEDHADHADHAFHAHAB,False +648,10.0,10.0,6.0,7.0,5.0,10.0,7.0,10.0,CHGDHGHAECAEAGBCGCEDFBGFCGBCFBHAEAFHDFBEHBGFAFFDDABDABDFBHFHHABHA,False +649,23.0,19.0,18.0,23.0,11.0,22.0,22.0,16.0,DFGDAGAEGAEDABBFDGADBHHAEGECAFDAEDACGBCGDCGHCGBCHEGACCAFDBFHBGGGDBGBFCBEGFHAHHCEDAEDBBAFAFFAFGAHCHCCDCCGBDEFHFFDBFBCFDCDDAAAGDEBDBBHBFHGFHFFHFAHGDGGDACDAF,False +650,4.0,5.0,4.0,4.0,6.0,3.0,2.0,5.0,DDHGDFGEFAECAFCDBCHEEAEEHHBACBHBB,False +651,29.0,15.0,14.0,25.0,15.0,16.0,23.0,19.0,GAFBABHAGGACGAGGAGHABDGFCGDEGEFDFACFBDAHAAHCGECDHFEHCDDEDDECGFDDFEDADAFDBFDBEGHFBAGBADBCDGAFFCEDEHAAHAACGAGDFDDFDAADCAFHBEHGEHGCGEBBHHBCDBCDHEBAEGGHGHHAAHAA,False +652,17.0,19.0,21.0,19.0,20.0,33.0,24.0,19.0,EBHGBHEFHAFCFFEAFEADEBHCBFCEFDEFHBGHGFDGDAHEGFEABBBBFBBFBBFAFEBDHBCBCGFEHACDCFDBGHGEFGACCFFFFDADGFDCFGEGHHGEHFFHEFHCFAGFBGCCGDCDDCGECGHAHEAGEDBCDEHDGHFGFCCDAAFAAFGAFDCGECGD,False +653,4.0,2.0,1.0,5.0,5.0,3.0,4.0,8.0,GBFEDEDGEDEADHGHHGHHDBHAHEFHCFAA,True +654,20.0,23.0,22.0,29.0,18.0,18.0,13.0,18.0,EDEBAEGHHFAHFBDDBGFBGDDABDABDADCCBBCEHGFCGFCDEHDFDGHDCBDHFDCBHBFHECCADGHGGEGBCBACHAEGEEFDEHDCHBEHFDBFCEACFAEDAFBGDBDDBDDBFDCFDCHDAACAABACGFCACDHHAFBAFBHEDCEBEEAC,False +655,7.0,8.0,11.0,11.0,11.0,5.0,11.0,11.0,CHBCHDCHBAHBCGDEGDACDEBAAAFBEFHFBGFEDEEAEEGDGGDGHDAHDHBEEGDECCBHCGCCGHCFHDG,False +656,23.0,22.0,23.0,10.0,19.0,19.0,24.0,14.0,FCGFCGAAEBHECHECHCGABAAFFEHBAHBCBBDEBEFDFADFGDFACFAFAHFBCEACECCDGBFEBFCCCCEGAAHAGEBGABCFBAAGFDFCEABEABECDGCGAHGHCCHBAFBHEEHCGBFGBAHBGGEGGEDBEDBDFGGGGGGACH,False +657,17.0,18.0,13.0,17.0,9.0,17.0,17.0,24.0,BDHBDGBFEBCHBDFBDHBAHBHHAAGABHACFFHHBBDDHHDHGFCFFCGHHBAHADGFDCFHCHCCBDFFGAFGAEEAGEHHBGFFGFAGHADHDCBDEFDECGAGADCAGCHGEHBEHFDABDGBCGAE,False +658,8.0,8.0,5.0,2.0,2.0,4.0,5.0,8.0,CEGBBGBHCFHBHBBABGEBHHGCFAAHADHAHGACFACFAD,True +659,34.0,21.0,21.0,17.0,21.0,20.0,30.0,25.0,HAFHDCDEGEEGAAGBGCBEAGEBGEAHCAHEAHCAHAAHFBHECECABCAHGGFGHHGEHDADFACFACFCGFCGFBBFAAHAAHBFFDAFDGFCAEAGFAEDBGBCEEFFFDEAGGADGCDFHGGHBCABCABCABHDGDGGEGGEGHEAHBDGBHHBCHDFAECGDBHAGHADABBACEFHBDEGC,False +660,14.0,30.0,12.0,19.0,8.0,11.0,20.0,13.0,DEBHHDCGGHGCHBFBFGBFDDFDDGDGBDBBABHDBHACECCACEABBAEBDBBGGGCGDAHCADCABHEFHBFDCDCGGFBGDBDBBGGBCGBEBBEBBHHBHFFHFAADGBBGBGADDFEAAGA,False +661,11.0,26.0,15.0,26.0,16.0,14.0,18.0,26.0,FEBHBBCBDCEDFABGAGEABBHBGCDGFDEBBEBBDBEGBEDDHHDHFBHEBEEGAHHDHHCBHCAHDHCAACEGBEGBDGBHBHDFHDHDFHECHCHEAHBGCFCFHDDHDDFDDAGEGGCCGDFGFAGFGDBBBHBDHFDACDCHFGDE,False +662,5.0,2.0,4.0,1.0,4.0,3.0,0.0,4.0,HCDFCFHCACAEEAEFBHABHAE,True +663,14.0,22.0,18.0,13.0,14.0,22.0,18.0,29.0,DHBHHBGHGDDFFFCBHCBFCHGCGGHHHHABCCBAFAEGBBDBFCFECFADFHBCHADBADGHDGCDACFHBFGFFBFGCFAAEACHAFHEEEEHGEHAEBGBGGBFCBFBGGBGAHDHHBECEHCHBFECFHAFHDCHDEHDEHGFHB,False +664,22.0,13.0,19.0,20.0,21.0,19.0,24.0,26.0,AACFEGGECAHDGHDGDBEHBGDGGCBEAGEFEAGBGGBFFBGGGGDCEEAAFFAHEBFEFACFECEABEFHGFHDAHCBHCFGDFHDAHGEHEAHEAGCCCHDAHFCEFCDCAFCGCHFCHGCHGCBGFBGHHDAHEAHDHHDHEEADEFDHADADDHDBADB,False +665,19.0,16.0,20.0,18.0,23.0,17.0,22.0,24.0,DAACFCEFCEHBFHAEHDBHBHABHABHAHCCGGCGCEDBDHBACCCCCAEDHEACEHEDGECGEFGCGDEFHCAHADFDEEDBECEACDGEDGFHFAEFAGBHHAHHDHAGBBFCGFEGHBHFDEFDHFHHABGABGEDGEDGEGGBCEBGDFGFFGA,False +666,21.0,15.0,10.0,14.0,9.0,13.0,18.0,9.0,ACFGBACCACCADCDGADGADGHBABGDFEDEGAGFADADDBEABDABEABAFBAFBGFGGACGBFEBFEHFHGACGCFEDGBGABCEHFGBAGFEDADBAFHHGHHDH,False +667,8.0,7.0,10.0,12.0,11.0,15.0,18.0,9.0,FAGEGGDGEAGDFCFFHBFDBGDFGBAGHCGFCDBCGBDFHGFHEACECCECAEFGCFGHFEDGHGBHFCHAEDAEDGDFGFGEBEDHAD,False +668,10.0,9.0,8.0,13.0,5.0,7.0,10.0,7.0,GFDGECCECCFHAGBGDBDFADGEDAADAADAADCGBGHBHBDHFGHFAHFACDEHBEBDDCGGCDFBB,False +669,7.0,12.0,7.0,12.0,9.0,2.0,15.0,14.0,HBGHAGHEGBCADABEEHFCCGHGGEGGCDGCHGEDGDBADBHDBGEAGAACEDDFBHBBHBDHBDHGCHGHDEEBHD,True +670,0.0,5.0,2.0,3.0,7.0,4.0,3.0,4.0,FGCFHFEDBHBBHFBGEBEEDEEGEHCD,True +671,5.0,12.0,12.0,3.0,8.0,4.0,5.0,4.0,BBCBBAECHCGHCHFCFCCBDBECBEBFEBCGHCEFGGBAGEAEEACCBDABD,True +672,11.0,18.0,12.0,10.0,18.0,18.0,25.0,17.0,AGBBGFGCFCEFCBHCADEBHCHDEBGGGGGAGGCGFHFBHDBFFAFHAEHFEFFAGBEDHHHHBBCFHAFCGCCBEHBEHGDBFEAGEHGEAGEAGEGDBGDCGDGGDFHEFEBBCBAGBEDHEFGEF,False +673,9.0,13.0,14.0,18.0,14.0,11.0,8.0,15.0,CGDBHCCHGBFGAFEEHEHCEHCACCADCDDCGBCDBHDHCBHEHABHEEGDFHDGACBAGDFEDFEDECDBDHFEHBEFFEBCEBDABAAGFHFDDFDDHB,False +674,8.0,13.0,7.0,9.0,11.0,13.0,8.0,11.0,GHHFHFCGFBEFDEDDBFDBAHFHHFCHEDGEHGCBDBHHAEGAEAAEBAGBAEFCFGCFAHBGEFECBCBBDBBDEFDF,False +675,1.0,9.0,5.0,1.0,4.0,4.0,4.0,4.0,BECBCFDGHHBEBBFBBFBCFBHGAHGCEECG,True +676,7.0,7.0,1.0,4.0,6.0,8.0,6.0,3.0,ECHEDFEAHHDFABGEBEABEDGFAGBAFBAFGFGGFABFDB,False +677,14.0,18.0,19.0,11.0,14.0,16.0,16.0,25.0,EEHFECBGCECHDBHGHHGHHGABBDFBDFBAFHAGDABCABFHHABGAEGDBHHGHFFHDFEDFHFGACBCCGCAAFFAHACDGCDBCHBFGBHEFHAFCCEBBDHCHFAHEGHEGCEHCECCHGEGBECBD,False +678,9.0,12.0,6.0,10.0,11.0,11.0,13.0,11.0,CDEAGGDGGCGBCGBAGBGEBDCAFGHFGBFEHEEACFAGFDEFGBHHFHHEHFCGDADHHDHEDAADFBFBBFBEEHEABBD,False +679,27.0,20.0,25.0,20.0,31.0,18.0,23.0,23.0,EFHEDHDDBECBDAFEEFEEAADGGCGEBGADEECEEFEECAFCGEGGBFCBFABGACDAEHBHCFGCHGCHGCFDCBHHBEABAHBABAHEAHGADGCCFECDHDFAGECHAFBADBGDBCABHADDBHCEHCEHBFHGFEEDCDHCEECGCDBCAHGHBGEAGEAFFAFGAEEAFAHGEHGDACD,False +680,27.0,26.0,27.0,28.0,20.0,19.0,14.0,25.0,GDCFDCFHCBAEGAFACFAGFDBEABDBCAHCGFFFCFBBBADBGFCDACDGDDHCEHAEHBFGBHECDEGAACBHCHEAHEFCGACDBHDACGACHAHHAHDEHFCBBABBABCHBFDCGBCHBCHFDHEEBDEHEEHGEFABHAHCAEDBCDBCDEEDCBDBHAFAGEADDADFADFDDHGDEC,False +681,3.0,1.0,1.0,3.0,4.0,8.0,7.0,1.0,HGFEDDABGFGGFGFFGCGAFDAFEEFE,True +682,15.0,12.0,11.0,14.0,15.0,27.0,23.0,14.0,FHFFHFCHGEDCEDGABGDBGFFGFHGDDFFDGCHECAEGEBCEFCEAAAAGACFAGGGBEGBFBAFBAGGAEHAEHBDGGDFDAHGGEGGHAFHGCEFDBFEHDDBGFBCFAFFEHFCHFHDFCFFDEFB,False +683,3.0,2.0,5.0,6.0,4.0,4.0,5.0,2.0,GGFDFADFADECDCGBCGEDHEDHGCBCAEF,False +684,13.0,18.0,21.0,19.0,20.0,13.0,21.0,11.0,FEEGGCAGBEGFECBEGBDHBDCCGACGFBFEHHEHBCHCCFDCDDCEACEAFHHFCFDEBBGBDCBDBADEDEGCFDHABEDGEGFDCFECDEAHEDGEAGFAEAAGHADABDBGCGGBGFBDCBDGBCGECGHC,False +685,10.0,7.0,12.0,11.0,9.0,18.0,8.0,9.0,HDHAGFAFFAFFAEBDCBDBEAFEACEACDGDDGFCHFCBCCACHGCFFCGDEFDFHEFHDCBEHGEGFFDFAAFBEFCDGHBH,False +686,6.0,12.0,8.0,11.0,9.0,7.0,20.0,10.0,BCEBCDBHAGDAGDHGDEDAGDGHBEHDDFGDGEDAEGGGCEBCBGGGCHECBFHHGGFGGFGGHGAHFBBCBECBHABFDEF,False +687,12.0,20.0,16.0,25.0,15.0,20.0,20.0,33.0,DFDHAGHAEHBHBFCFFDHFDBGGCCBDABHGGHBBCBFCHCEEADDACDFCAFBHBHDBHFBADGHDGHDGFEEBHHGGHGHFGDFCDHEEHCECCHDBDAGDABDCBFHAGEAHEHHEHFDHFDHFDEFDCCGBCHEDHBDGEHGBBGFDHAHHFEFGG,False +688,3.0,9.0,2.0,3.0,7.0,7.0,3.0,4.0,CFEHFBFBBEDBCHAFABFEBEEBDEHFEDFHBGGBGA,True +689,15.0,26.0,20.0,34.0,29.0,23.0,27.0,17.0,GAAGDABHABEGDEBDFFDHFEHFBFCBGCBCCDGFDEHDCFDBHEBEFBEBCGCDGADBDGGGAAFCEDCEDBHGBDDBEDFFGFEHBEFFCAHCHHGFDDBCDBDFEHFGAFHFFDBEABEFBGFAGHGGEECCGABDDBEEBECBEAGCHGDHGDEDHFDHDAECAECDEDGEDEBCEDDGGDEGBCG,False +690,2.0,5.0,5.0,7.0,3.0,8.0,3.0,2.0,GFGFFGFDHHAEBCCBCDFCDEADFDBFDCEDBBF,True +691,11.0,14.0,14.0,3.0,13.0,5.0,13.0,10.0,ABGFGEEGEEGEHAHBCHBDDGHBBABACBCEEGECGECGHCABCABCHBEGAEFCCGBFGCAEFGECBFHACHACHDHBGBA,False +692,17.0,27.0,23.0,13.0,20.0,16.0,15.0,12.0,BCCBCGFCGFADAABEDHEHBEADCFFEFFCABCGBABBEGBADBABBFCACGEDBEBBGFBGHBGHDEHBEHBCHACHFGEECHGFHGCCGECGDBBDGAEADFCGECDEFEFCCFAHFEHEABAFCCECEBDDBADBABBC,False +693,27.0,22.0,19.0,22.0,14.0,28.0,28.0,25.0,FCDFEDBEDFECFBHAAHEACBFDEGDCGFFHHFADGABFAFAAGGBHFECAECAGCGBDGBDHBHCBHFEHBBAFAAFAFFCHFGGFHAADCCGCCGBHGDDGFDGBDGBABHAGFDBFGBHAEFFDGFDGCAACAGGHDGAGCDEHDHBGHEFCEFADHEHABHAFHEHHDBGGBFCBGCHAD,False +694,18.0,13.0,19.0,10.0,11.0,15.0,13.0,6.0,GDGHAABAGDGHFBFGBCGACGAEAFDAFDECHECACBFCBACBEBDGBFACEEBEDCEACEBBDDBGFAFFDCFECDHCACCGBFGHGCEGCAAHAAFCAFCFF,False +695,10.0,11.0,11.0,10.0,20.0,12.0,15.0,5.0,DBDBFDEGDBGEEGEGFAAEGDFCFECEEAEEBHGGHCGHCFACGHEGEEGAEFCEFBAFBAEEACCGFDBFCHACEDFADFGBGCBDEBEGBD,False +696,11.0,15.0,9.0,15.0,19.0,14.0,16.0,14.0,BBEABEBFEDFHBEDCFCEDEFDECCEFGFGBHGBCGHGFHEBDGBFGCFGDGDACDAFBFHBHGECGEHDEHBBFDEEDGEFCAAHEABEHHEAHEAHDAHDGGDBGFAGAD,False +697,4.0,10.0,3.0,4.0,4.0,9.0,13.0,9.0,EFFBHHHHHCADDEGDFGBBGHFGBBBBHBACEHCFBEGDGGFGGFGAFGAGHFGB,True +698,8.0,6.0,6.0,10.0,3.0,3.0,10.0,9.0,CHGBHGEHGAAGHDGDAGDBDHADHBDHDAFACBCFBGEHCEFCGABGAGDCDDH,True +699,23.0,20.0,26.0,25.0,24.0,29.0,20.0,24.0,CDBFFGEGEACCACDGBDCHACHACHBGDBCFBHFHHFHHAGHAGHCHAEEGCEHEEFFCDFDDFDFAAEEFEEFBEDAEDFGDFGDHHDBCBBCEBEABADDAEDGGGCEHAGBEFBCFDHFBEFADFDCEHFEHFHADCFDAFHAFBFCEDDBCAHAACGCBFCDHBFHDAGFEGFGGCCGCBBCAHGE,False +700,29.0,20.0,21.0,24.0,24.0,23.0,13.0,26.0,EBHEBHBADGAHAAEEACGAFAAFBBFCHDBHAGCDEBDCDDAHHBCEAAFHAFCABDDEDEEDFHDFCDFBEGCFGEFAFGCHGDHFFEFHEDDEADBACACEFCBHCEHCAAEAECAEBFDAFHAHGAHGBGCBDHBDABDHBDHADFGEBABHFCFFAHFDECHHCHHCFCGDEGEE,False +701,3.0,7.0,7.0,3.0,6.0,6.0,4.0,11.0,CEFCFHGFHBHEAHECHEBBAHAEECHCDHCFFCHBGFBDDBGHBGH,False +702,9.0,6.0,16.0,15.0,12.0,8.0,10.0,9.0,FDCFDCDAHDGHFAACBCHDEHEGDEDDFDDEGCGCDBCDEAFCBCCBCGACGACHHEEHADDAEDCECFECFAGGBBEHFGHEG,False +703,6.0,1.0,3.0,5.0,2.0,9.0,6.0,6.0,DABEAHCFGGFAGFHHFCFFHDFHDCGFFGDEGDHAAA,True +704,4.0,1.0,0.0,2.0,2.0,1.0,3.0,0.0,BGGAAGEADEFDA,True +705,18.0,19.0,12.0,21.0,25.0,19.0,18.0,24.0,FDAHBFHDCHACHAEAEEBDDDDDGFHHFEHDDBDAAAFHAGGAGDABCHGCEGCFDBGCBEFHFDHFHHEGCFABHEBHCAHBBHEAEEAEGAEDEBGFCDHEEHGEFGEFBDFEGFGHFDHFBHDBGDACBAFBDFEHEECBEGBDGAEGEHBC,False +706,17.0,12.0,10.0,18.0,25.0,13.0,22.0,21.0,AGEHCDCDAEDAEBAGGHGGHDCHEHEFCEABEGBEBHAGABHABFFGGFGAFGDBGAEDAGFAHEEBFFAEFBEHCEFDEFEHDCHDCHDGAEGAHHFHEBEEGABGDHGDHBDHDHGCEDCHFCEEDDEHDGAGGE,False +707,18.0,24.0,22.0,26.0,29.0,18.0,27.0,19.0,HFHHGDEGFHCDHCEGFEGBDCEDEEFFBFCAEBBGABHADAAGABFDCGCBHABAGHDEDEEHBAHDAGDBGCBDHHDBEEGCFGCHCFHBFDEGDHDFHAEDAGDFGEFCEGGEBGCCCCECGECGCHACEGCEFCDFBDFBGBEABECBEBBGAHGDHDDAABGGBEGAEBEDFDDFEDE,False +708,20.0,10.0,10.0,16.0,13.0,13.0,19.0,23.0,FFHDFHCCACGGGHEEHDGGAGEAGHAEBAHDGHGGHBGAGFCBDCDDADDCEHADDDHBAHBAHBGGAFAAGAGGBGFHAHHDHGEHEFHCFHCBACEDBDDFCEFAHFAHEAEFHFABEDHE,False +709,5.0,8.0,2.0,9.0,7.0,8.0,16.0,8.0,CGDAGDFHDGABHDEFFBFFBEDGGAGGCEGHHGADEFDEDHEDGFBGHGGHGGBGBBAHEFB,False +710,2.0,0.0,1.0,2.0,0.0,3.0,1.0,3.0,FGHDDHAFHAFC,True +711,11.0,11.0,7.0,14.0,11.0,15.0,19.0,23.0,DHDDADGHBGFBGHHGDGAHHHGHHGBCEDCHDHDECGGFDDAGBHGBGDAHBFFBFFCHFCFFHBFHEHHGAFGAHGHDCDDAGEHGEHBFHEGBAGFAEFCEABEAEEF,False +712,22.0,16.0,19.0,9.0,22.0,12.0,19.0,16.0,HDGBAGAAGFEEFADBADHGCGCDBCABEACGHGEABEAFGHFEHFGHFGHCGEFGEFHHACDAHFCGECEABEAEEBBABHEFEAGEDGBCEHDEADCBDABCHCCHBCGAGHACEACHFCEEBAEBAGBGFCC,False +713,10.0,16.0,20.0,25.0,19.0,11.0,23.0,14.0,FDCDDBFDGCEFFEBBEBBFDBHCFAAHGDHDBFFGFDACDAEDGEGGDCADCDDGEDGEGCEGDADCGDCBBHEBDECEHCEHGBHACEGGDCGHHGHDGCGGCGCDHHDECCEBEEDABBAGBGEAGEFDHFBHCC,False +714,7.0,8.0,11.0,9.0,14.0,8.0,8.0,14.0,AADAFBHGCCGCDHHFHBCHDCHDEHEEBFBAFHDGHDHHEAFEFCEGDHBEHCCFCHBBEDEEAFEAECGECGEGDBG,False +715,4.0,5.0,2.0,4.0,4.0,2.0,5.0,7.0,BEEHHBHHCDHCGEBGDBDHEFHFAAGAAGBDG,False +716,2.0,4.0,4.0,2.0,5.0,4.0,1.0,3.0,GBACBHFFEFFDHBDHEAEECECCB,True +717,15.0,12.0,19.0,9.0,14.0,21.0,18.0,23.0,DBHAHHEFBFAGHAGHAEHFEAAGCGHBFHBAHDCHCCDAGGHGFDAFEEEGECHCCEBGDAGCAGHGFACDHBDGBAFCFFCDFCFFCEGCBGFBCHBHAGHFHCBHAFHCFGCEGCEHFEBEEFFHDFH,False +718,21.0,29.0,17.0,17.0,19.0,12.0,14.0,21.0,BHBBDDFDBFDBDHADHBCABAHFADGBECCFDBADGEHHBBEGHEDHCHEBHBHHBEEBCABFBBFBFDAFABDGCEGCEGBEACEBBBBCDCHGEDEEGGHGAFGABGABAAHAHHAHGAHGEHCDCFDCFEEDEBHCCCACAAFABE,False +719,15.0,18.0,17.0,14.0,22.0,18.0,20.0,22.0,GGECFCHFHBEHBEDBEFBEHBDHBGAGFAHFAFECFDFHGFBGDEHECDGCAEFHEFBDGHDGDBGBBGBHGCCGCCGCHHEBBBBEEAHHBFEACADDACGCFEHFEHFAGAHGEHFAAFCHDCEGCEFDEGBHGDHEECAADA,False +720,4.0,4.0,3.0,2.0,1.0,3.0,4.0,4.0,BFBBFHBCHAHDAGEAFCADCGGGH,False +721,22.0,14.0,33.0,22.0,22.0,16.0,25.0,18.0,EGACBDEEDAADHAHBABBAEGAEGBHCBADGFBCFBAACFEEFEDHBDCGECHHHAGEAFECFEGFGAFGHCGAFGEFECFGCABEEGGDAGDCCHCCHGDEGBEDBACAHDACCCBHCAHCHDGHAECDDCDHCFCDAHHCECGECGDCGFGECCCFCCDDGDDGDFGBF,False +722,15.0,12.0,9.0,7.0,14.0,11.0,9.0,13.0,HFDHFEHEGDBCFBCAAHFAEFGGDBADEAFEAHEAHFBGFHEAGEDGBBABHGEHGECCABCEHDBADCFEEFAHFGHEAHACCABCBB,False +723,25.0,27.0,19.0,19.0,29.0,24.0,29.0,27.0,CHBDGEDBEGCHBAGECBACBGCEACAGCAGEFHHHGHAGAEDHGCGBBACHDGDAGDAGBFFBGFBDFEAFBABACDEFFEAHHAEHGHHBFABFACHHHEBGBBEABEAHEDGEDBFDCHDBGGEHHEGHFCHFHAFDAFEGGHGECDFGGBGCFEAGECBECBECFEAFEBFEHFEHBDDAEDADDFCBFEBFGHG,False +724,7.0,6.0,4.0,4.0,2.0,2.0,7.0,4.0,BACDABGAGDBGHFGHFCHAEGADGBEGBAADCBHC,False +725,13.0,14.0,14.0,9.0,9.0,11.0,7.0,5.0,ADEDDFDEGBCACCABCADGAFGFGAEGAGBAFCFFHBBHCBDBFEGAEDBDFHCEECEAFBAFHCFCCDBCABCABHBBEC,False +726,6.0,1.0,2.0,1.0,0.0,2.0,3.0,0.0,ADAAGACFACFBGGA,True +727,22.0,23.0,26.0,27.0,23.0,28.0,17.0,22.0,ECCBCCADCDDGGAHBAHFHCGHEGHCAHGHHGBEFCAFBAFHDFAFCCBACDGCBGHGEAGCDECFEBEEDFDFBHGBAGBADFEDAHDACDGEFEEHGEHFAHFAEBDBBEBFEDAEDHDDCFDGDABEGDFHBCBFDFFACFAFHEFHABDCCEABEFFHCFBFFBFCBDCBDCEDGDAHDCHCE,False +728,0.0,0.0,3.0,1.0,3.0,4.0,2.0,2.0,CEHCFCGFHDFEGFE,True +729,17.0,19.0,22.0,26.0,19.0,16.0,18.0,23.0,GFHGAGFACDAEAGFDCBCCBCBBGBDGEGCEHDDADHEDBADHDEFBEDBDGBCGAHHAEAAEBDGDGGDGABBECDEFDEFHCAHBDHBHGGDFFEFDCCDACBAHEABCHEEFCEFHGFHDEBGEBHHHHCFHEAHBAHCDDDDCGFCHFCHCCFCD,False +730,10.0,12.0,10.0,12.0,5.0,3.0,7.0,9.0,GGBHAHCBEBDABDCEDEGDCGDAFAHGAHDADDACHACGECADHABCCGCBBCBBHHBFDEHDBDFB,False +731,8.0,9.0,15.0,9.0,17.0,19.0,15.0,6.0,BHGBCGBCDBCFBCBACFAFEGFECFEGFGCEGCGADEFECHEDEEFFEFFGFFGDFCEGCACBAFADCGEEGDBADFAHHDGHGFEEDCEHFFBGEC,True +732,15.0,25.0,16.0,23.0,8.0,23.0,16.0,19.0,CCGCCHDFHDFABAHDHGDBFDHDDBBDHBGHGFDDFGGHEHABDFCHFAFCACBBDDBDFBDABHABGBEDBEDAFCFBCFGEBBHCBABGABGHBGHFGCFGCFGEBEFADCHFHFFCDDCHAEHBDGADAADGFCFFBFEBH,False +733,26.0,12.0,25.0,16.0,6.0,12.0,11.0,16.0,DDEFFEHBCBCAGCHGBHAAHCAHAHHBHHGGHCFDCADCADABFCCGAFDAGHCCCACFADFADAHBGBCFFDBCHAFAAEDEBAHBAEFAFBADBDDADCCCCCCCACCGCDGADGAEAHGH,True +734,24.0,26.0,16.0,18.0,21.0,14.0,24.0,22.0,HGDGADCHDBBAEBDEBDEBEEDECFBCAGCBCHGDBGEBDEBEEBDGBGHHFCDDHGDAGHADEBDAAHBGBAHAEEGEBGEBAACFHCFACFHFAHFAHFDHCBEAHEHBCHAHAEDGFBGDBGFBHBEGDGGACEACACBACFAGGEGBFBHAGHAGCFGHF,False +735,22.0,22.0,29.0,19.0,27.0,26.0,31.0,18.0,FACFCCFCAHCGBBDADAGDFEEFAEFAHADEGDACBFCBFBHGCGGCFFBGFGFBBHHBCAADGCDECGGCGGCAGCEGEGGDDGAGHAGHFCFCEGDGCFFBDEBDFBFEEEHEHBEAEEAEEAGEFDEGDBBEHGAGFDGEDHBCHGAAAAABCECCECCHCCDFHBFCEGEDGFBFCBFHBFHDHHCGEB,False +736,3.0,2.0,3.0,3.0,1.0,1.0,2.0,0.0,DCBDCBGCAGADEAF,True +737,25.0,20.0,13.0,20.0,9.0,15.0,15.0,17.0,BBCBGDDHBCECEDCBDHGDAGDAEAACDBCDAAHFAEFDCFAFBAGAGBABHABDABFAFFDDHHHHBFHDFGGHDCFGGHHGAAEAABCAGCBGCEGABCADEBBEFBDFHGFHDFHCFHAADEBDGADABH,False +738,15.0,21.0,15.0,20.0,23.0,14.0,16.0,14.0,HBDCBCCDFDDBDABDABDFDHHBEGEFGEFGECGECGECABBEGFEGFGFBABDGBHGBHCAEBBEBEDDDBHDAFCACCEBHGGDEDAEACFBFFBGFGEEHHEHEAHADFCDCAFCDEBDCDEGEHGAHAHEABE,False +739,6.0,4.0,7.0,3.0,11.0,9.0,13.0,4.0,CEEGFEGFDGBBEFGGDEDHCCEAFEAFBAFGACCAGAFEBFEGFGCHGEHGECGHG,True +740,18.0,18.0,17.0,21.0,22.0,23.0,24.0,19.0,CHFCHDGHDGBDCFEEFEDGHDAHDAECAFGFFHFCDEGAHBDBEDHEGAEGAEFBEHAEHABBAHFGECAHBFCDFDEEDEGDACBFHDFBGFGFEEFAEFCFBCHBDFAGGAGGAGBAGBEGEGDDGCDBBDBGEFGDDGHBBECHFCHCCFAGHCFCAH,False +741,9.0,8.0,14.0,9.0,12.0,8.0,10.0,8.0,HHAGBAGCACBHFBHFDEADGBFGCDABDCEDCEFABGECCEBCDGEEEEECECCFACHAEFGGFCGFDGDACDHHBH,False +742,12.0,15.0,13.0,8.0,14.0,16.0,4.0,12.0,AFFFBFFBCEAFAAEBHDAEAHBCHFCHBDHBFHBDEBAHGFHFBEGCFHCEAFEAHABDBEDEEFECHECGECFHCFCCDCCGBDABDBBEFA,False +743,10.0,6.0,7.0,8.0,13.0,10.0,9.0,5.0,AFAAEBGEBEECEEDFCGGHDGDFCFGHFBHEHDDAADEDDECBEFBECHCGAAFFAFEAGEAGFBGC,False +744,4.0,4.0,4.0,5.0,4.0,3.0,5.0,8.0,FHDHHGAHBHDDHGDAFEACEACEGGFHBCHBCGEDB,False +745,5.0,2.0,6.0,1.0,2.0,4.0,4.0,5.0,CHHCFFGFGAAGAHGCHABEACEHCBFCD,True +746,6.0,7.0,9.0,8.0,5.0,5.0,6.0,0.0,GDGGFGCEDBEDACDCCFACFCDABDACAACBEBBCFBFEEGBDGD,False +747,23.0,21.0,27.0,20.0,27.0,21.0,28.0,26.0,DEADBCCGHHGHDBADBADBEEBFEBEBGGCAEDAHDFDGHEAHEAGEDGEFGBAGHFHECBCAEEBEGFFFHHHDHHGACGEEDCADBAFBHGBAFBDFCDCBGHFHAFCCDCGACGAFGCEGCHBBDGCHFDAFGGGBHGBHAAHCAGEDCCGCCHBCHFFHEFCEFAAGACGCEECECHEBHEGEDFEDF,False +748,3.0,5.0,1.0,5.0,3.0,2.0,3.0,3.0,DBGHEAHDADDADECFEGBGHBFBB,False +749,11.0,7.0,13.0,10.0,10.0,9.0,18.0,6.0,AGEGGFDHECGGCGBCGECBCCEFCADCGHCGEGBEBDECGGCAFHDDHGDAGDAEAEFDGADGAFCCFBAFEFDGFAGBAHBH,False +750,19.0,21.0,8.0,26.0,26.0,23.0,18.0,20.0,FEHFHBCHBCHAAHDGEABEDCECBDDAFFAFDGDHCDEGDFADCHDEDEEGHAGDFGCFGDFAEBDFBAGHAEEAEAAFAFBAFBEBBDDBDHEFHEHDEBDEFEBBAAEAEGBEDFHDHGBEGEFBHCHFBHEGGEFGEFGDFHFHGDBGDBFDBHDGA,False +751,10.0,15.0,9.0,6.0,11.0,12.0,12.0,15.0,GDEEDHHBBFGBHHBEHFHFBDCEGGEGCBCCAFCEFBECHEHEBHBAABFABFABFGFEGAEBDHCGHAGHAFCACGAHDHFDHGBBGF,False +752,16.0,16.0,21.0,19.0,22.0,24.0,24.0,17.0,HHEEFGDFCDFCDFGHFHABEGECBCGBCGBFGDFBCBAFFGCAGCAGBAGHGDHDDHGDHGEHAECADCEFFAFFDEGBAGBCEBAHFACCDCBGEHDEGAEFCEDBEHFHAEDBGAGFECFGGAGGEFHDHECHECFECFCBDCGABDBHDFEFFED,False +753,5.0,5.0,9.0,7.0,8.0,5.0,5.0,7.0,DHCDCBFEBACFGCHGCHGEDGDDEDHAGEACFACEAHEFCCFBDHBHBEE,False +754,1.0,1.0,2.0,5.0,0.0,0.0,2.0,1.0,GGBCDDCDDADH,True +755,3.0,4.0,2.0,11.0,7.0,7.0,7.0,3.0,DDGGDGFFEFFGGDECDEDFEDFBBHBGFBHDAGCADHDDEAEE,True +756,13.0,13.0,9.0,10.0,17.0,10.0,13.0,12.0,CGAEDBDFGGHCGBCFAEEAGFBFFBFFBEGEEBEEHEECDEGACGEHAFGADHABHAHHCGHFGHEHEAHGDDCAHFAEBAEDCBBCBBGBDEDDA,False +757,8.0,8.0,4.0,5.0,4.0,3.0,10.0,2.0,BDEBGHGGFDGFDAFCGGCEBBAACEDCADHABGGBGBAABGAE,True +758,26.0,19.0,23.0,17.0,12.0,22.0,20.0,22.0,DDGDEFCHCHHDHHCHGGHDBAFBFGBFEBCAFCAFHFFDCCDCEACACBFEGGHGGDFGDHCBGAFCAFEDBEAEEBDFGDAGBHBHHADGCDFCAHCHFCGFCGHCBHABDABAACHAFAAHCBHBFABFAGFDBFHBEECGAGAAGFAEDABACCEGH,False +759,4.0,1.0,4.0,4.0,4.0,6.0,8.0,4.0,GDFGAFGDGCFGCFCAHAHDFHEEHEEGDGAFGCB,False +760,2.0,2.0,0.0,1.0,4.0,1.0,5.0,1.0,ABEDBHAEGFGGEGGE,True +761,21.0,26.0,28.0,30.0,24.0,24.0,21.0,23.0,FDCHDHHDFHCCGFFAFAAGABBDGBCGBHGEHFHFBCEACEHEHBEABDBBABAGBFFBHDEEDBGFCGFCGFBBCBBDBGGGCDECDCFECFEABGCDAEHEHBEDDADFADGAEEAEFDCFHCFBCHBCHAEDDEBGEDGFHEDCBACDGFFCEGCDACABEGCDGHEECFCFHDFBDHADHADHACGDCDDHH,False +762,24.0,12.0,13.0,17.0,17.0,14.0,9.0,11.0,CEAAEBDEFDBCCBABBACBDBDDADGCGHAEHAEHBEFAEFAFCACHBHFEHADHFEFAGFGCDADDACDEDGEBGECAEBFEBEADGACFAHAACAAEADDFFGAFGCDHDHEFH,False +763,6.0,8.0,13.0,10.0,5.0,9.0,19.0,14.0,HGDFBDFGCHDCBGCEGCEGHGHHGACGFCAEEHBBGDHGCCGFAGHADHBCGDDBEAFDHFBHFDGCAGCGFFGHBGHCGHCD,False +764,27.0,23.0,30.0,22.0,19.0,28.0,33.0,17.0,AACCCCCCFBCDCCGCFBEFDGGDCGFCFFCAECBGBFCBGEHDEFGHFGHACHGFAGEAFFFCHFDGCHGDGCFGCFGCAGDBFFBECEGCGGBGHBDAEDABFABFDBDDBDAADGHHFBAECEBHAHHEFADFADFACAACGECEEAGEABADBDHEGEDGEDBFAHGAHGAGCDFBAGBGFFDCHBHEACGGBGB,False +765,18.0,15.0,16.0,11.0,14.0,19.0,16.0,15.0,CEFGFFADDDDCFAFGAFEEEAEHBEHCECAEBAECABHACHFCFGBGGBDABCFFFGFHGHGDEDABBABBAHFACGDFGDFGCBEEDFHACHGCHGBHFEGFAACECDGCHGBHCBHBAHAF,False +766,2.0,0.0,3.0,2.0,3.0,1.0,2.0,7.0,HHEHHCCHDGHDFCEHAEGA,True +767,17.0,7.0,6.0,11.0,18.0,9.0,7.0,8.0,HEEBEFBEBEEGHEFCEACFABFHBGEAEAACAADAADADDAFABDAGDEDAGDEDHCHFABEGDEFDEAEECEGHHHFGFAC,False +768,7.0,8.0,17.0,12.0,13.0,9.0,9.0,18.0,EBDDBCDHEEEGCEFDAFDABCBBHFGHGGHDCHFEHFAHAEHCFHCAHEHBEGECHEGDECCCCDCBHCGHCBFGECACHAFHDCDDHFDHG,False +769,20.0,21.0,9.0,15.0,21.0,8.0,21.0,20.0,HEDAEDGBFGHEDHEDHEBCGAEAAFAABHDHAEHGGGBEFDFFAAEAEHCHBCHACDBFGBGABHBBEBBAHBHHDABDAGDHEFEGBGGDCGEBGCHECHECHGBEDBEDBAAFGADBAGAHGBGDCGEEGEH,False +770,21.0,9.0,20.0,15.0,18.0,14.0,11.0,20.0,AGHAHEGHACBCDEHDEHEECGABBADBFCHFEABCBDEAGEAFEAFECFDCHDBDFADCAGCADCHDEADAAHFABFEDCEGCHFHHCEACGDDGHFGAFGAHHHECAEHDHHABCEFCHFCGCCEF,False +771,4.0,4.0,4.0,6.0,5.0,8.0,8.0,13.0,HGCHGCEBAEDFEDHAHHGEHDDBGDEGBHGFHGFCFFCHADFFBHGAHFHH,True +772,4.0,7.0,15.0,14.0,7.0,5.0,7.0,12.0,FCECCEHCHDDHEFHDDAEHECCGDDBDDBEDBFCGHHHBHHBCABCHBCDEDGCHFDACDFCDGCGGAGC,True +773,15.0,15.0,19.0,12.0,10.0,13.0,9.0,11.0,CDFCAAHAADAADBHCGEAHFBGCBCCEGCDCCDEAGHAGECHFHFFBFBHFBADCADEHBECBABBHFECAGCDDCFFFHDFHDFAEGAEGBCCBCEDGBBCB,False +774,17.0,15.0,18.0,13.0,14.0,14.0,9.0,11.0,BDADABGFCGHCGAGHAGFFDCCBAGFHDFHCFHCBACEACBAGBACBECFEBGABFBFFBHHBDEEDEAHEAGFDEFAFFBDHBECCCCDCEACEHCEAADDCBAEDDEH,False +775,12.0,10.0,12.0,10.0,14.0,18.0,9.0,17.0,FFDFGDFEBAEBHFHFFBFCBFCBACEGDDCHCHDGBEEAEHAEBACCCCCAHEAFFFFFHGBHDAADAHEFHGFHEDCAHHADHGFGCHGFEEHDEHBEGB,False +776,15.0,9.0,14.0,7.0,14.0,8.0,10.0,14.0,FGGCGFEGFEGEBBABCCDCHEHHCHGFDGAEHCEFCEGCAACEACADHABADBFDCEDAABEACDGCHHCHAFAGHEHBEFEAHBAHBEH,False +777,3.0,5.0,7.0,4.0,6.0,7.0,4.0,2.0,ACHDGDFECAEGAFGEBDFBCFCCFHCEECDBGFBEFB,False +778,13.0,16.0,17.0,23.0,18.0,12.0,11.0,15.0,HGEDGCCFHBDHDDECFEHAEBAEBHDCCDFCDCHGHFGHAABCAFCGHCGCEFFEBAEBABBEHBGHBFFDDGDAEDAEABBHBBHEDFEFCDCEDCEDHHCGDDDDDAGFEBBCDDADCAEEG,False +779,0.0,0.0,2.0,3.0,0.0,5.0,2.0,1.0,DCFGFFCDFHDFG,True +780,4.0,14.0,9.0,15.0,13.0,16.0,18.0,13.0,GFHBCDDGGEFBDFGDFEDHCBBGEFEAFEHBDHGFFECCDHGHCGBBGBEDHDDEDEEDBCFHGDHGFHGFHGFGGFGBFGAFHCDCAECAEBBEDBGFBH,False +781,14.0,11.0,9.0,17.0,16.0,19.0,16.0,13.0,AHAEEAEBDCFCAFEACDFGBGHHFBHDBFDCHDHHEHFDGFAFEABDGEEEFHFABFCGFGGBCHBEGBHACEADGACGCFGBFGAFDAGBAGFDHEDEEDEFDEFDGHDGDDF,False +782,17.0,30.0,15.0,20.0,20.0,24.0,22.0,25.0,GBEGHHGHFDDAEABGCBGDDCCHFEBFGBGDBGDBGCAAFGAFDEFGEFEFAEFACBGEBAEBHBBHBCHEHHEAHDDCBCFDADDHDGHFEHBHFBDBDHAFHFFHGGAFCFGCHEEHEDFAGBCHBFGBCGDCGBHBBCFBDBDEBFEFHHCBHGBEBAEBHEFAAFDAG,False +783,18.0,12.0,19.0,16.0,8.0,23.0,23.0,21.0,CAEAGEACHFBBCABCACFADGBFCCFGDFGFBGHEGHCCHABHGBHFBGEAGCCFDAFDCHBGHCGHDFEGEHGEHFDHBDFAHFAHCGGCGDBFAGFHHFHGFDDHGHFDAGBHFHEDDDDCCGCCGADFAFGAFAAF,False +784,26.0,24.0,29.0,15.0,21.0,16.0,22.0,14.0,GEEGAEGABFAFGEBBHCCCGGBHGBFDAADAAGAFGBEBBCCGCAAHAAHDBEEBGEDADDADDAECAECBEBHEFFADBCGECGCCDCGACBACFDCFHFDHGHBBHDBCECEGCBGEBCEFAECCCHFGECGCBACBFFBGFHCECAFBAHBHHAFDAGDECAG,False +785,1.0,0.0,2.0,2.0,2.0,6.0,1.0,1.0,FFFEFFEDFCDCGAH,True +786,20.0,28.0,18.0,25.0,30.0,17.0,20.0,19.0,ECEDCEBGECGBDDAGEBEEHHADHDECGEDEEFEADEAFEAGDBDFCEFBDHBHAGAAGCAGCHHCHDBDFFEECADBAGFCBBEBDEHHEBHFAHFBCEBFEGEHADBDHBDHCDBGDBHDCGBFEADEADHAEAGBBCBACEACFDCBDHBDGEGGEBGEFGBFCBGHFGFFAB,False +787,5.0,3.0,2.0,6.0,9.0,8.0,2.0,4.0,DAEDAECHGCHBEFFEFEDFEDADHEDAEFBFABFHFEG,True +788,5.0,9.0,7.0,1.0,4.0,3.0,1.0,5.0,EBABAACHBEHFACBBFBBEABCDECHGCHBCHFC,True +789,12.0,4.0,13.0,8.0,13.0,16.0,10.0,11.0,ADAAEBAEGDFGHFGEBGADFAFFAFFEFCECEEFEGFEDFCCECHHAFDCFGHEHBBFAGFGHACECGHCDCCHCCHDFHDGAAEH,False +790,6.0,10.0,8.0,9.0,9.0,8.0,9.0,13.0,CEAHHCFHCFHBEACFACDBGDBEHBGGCGGAFDHFCHFEHBABBHDHGDEAHGBEBEGBEDHEDGCDFHDF,False +791,8.0,14.0,12.0,15.0,11.0,8.0,8.0,8.0,EBHEBDCADCAGCABCGDEADEAEECBEDADFEHECHDBHGEGCFDCFBBBHBBDGHDFFDFFGBGHBACBFCHGCDCDDEBDA,False +792,10.0,22.0,18.0,14.0,21.0,20.0,16.0,23.0,DBGEHGFDGFECFHGFEGFBAECAHFHECBABHGFACEBDGBCGHCECAEGBBCDBEGEEGHEAAECGBFHBFHAFHCFBCDHCDHDBHEAEEBHHBCCBFHBCCBHCEDDEDDEFFHHFHFFHEFDAGBFEBHCBHDBFDGGG,False +793,23.0,21.0,27.0,21.0,31.0,27.0,29.0,18.0,AGFCEBGEFGHCGECBEFEGFCBFDBFHCCHCBEDDAGFBDCCDCCDEGHEGHAFHGGHDGDBADBAGEAEAGFFCDACFACFGCFGHFHEFHEDECBEBHFGDEGCEGDBAFCCFACEEBDDHCECDEADFGBBEABHACFAEFAEHAEHEGBFCAHGEFDEAAHACGDBEFBDBBCBCEHGEFGFGGFAGDAGEG,False +794,24.0,20.0,28.0,18.0,24.0,31.0,23.0,26.0,HHAHBAHDAHGAHECHECDEHEEGEFCECEFDEDDFCDFCHBBHBHFCGGEHCAHCDGAGADGCHGHFGEEGAEBABBAEFDGDHFFEGCBFBGHBGABDBCAGCEFEBFCFAAAGAGBABCAEAAFFBFFBEBDDFFCFFHFFECFHDFGCCACFAFHCFECECCFGHFGBAGBCDHHHCCHDCEDAEDGHFG,False +795,31.0,20.0,15.0,24.0,20.0,24.0,18.0,24.0,DDFDGFDGAGEBGEBGFHEDHBDBGHCFHBDCEACAGHADHGHFGBFHCDHDHEEHGGDGGEGDFGAEAEECGFCBFABFADAADAHGCFFHBFBAFDAFDBEBAAHAAHAAHAAFABCABEBEFDHDHEFHEDABHCDDDHBHCCGDHAECAEBEHAFBACEADFBFFEAFCAFC,False +796,6.0,5.0,4.0,8.0,8.0,11.0,14.0,10.0,AGGGDBHDBEDHHCHFAGFGEECFFAFFAEDAEFEGDBGHHFHDFGCGHAGHGGHGEBCEBDFGDF,False +797,13.0,13.0,14.0,16.0,20.0,20.0,14.0,14.0,FDCFDCDGCDGAFFFFHFBDGAEEFDHFGHGBFDAFHGFHGDEDDEADCHGBHGBACAHBECACHEEEEBBDFCEBBEBFEHAGCEBAEFCEFAGFAHFGHFGCFECADCGEADEHDEBDECHB,False +798,16.0,22.0,7.0,24.0,22.0,17.0,26.0,9.0,EFHFGCFGEDGFBGFBHACDACDAGBBGECEBBBDDADDADHGGGBGGBFEEDEFDEAGEAGEAFEDDBDGCDBBBGHGDHCDBDDEGEAFEADEABABBHFBFDBFDFEEFADGADECHBGEGFFGBBHEGGFDGAGAHGEE,False +799,20.0,13.0,23.0,31.0,20.0,22.0,27.0,27.0,ACCDDCDDCHDEGDBGEBHAHGDDDCDAHDGFAGHAEBFECFBCDECBAHEACGAEGFEFFGHADDGDDACEACECCFFFDFGHBHDBHDCFGCGACFCDHCBHEFDBDGCDCDEFDEFAGHAFHAHHCEGGDBGFEGHEHHAGFEBFGAHCBHCAHDADFGDEHDHHAGHFEHGEGGDGGBF,False +800,7.0,7.0,4.0,8.0,5.0,4.0,9.0,2.0,BFADCAGBDGDDGDDAEDEFBEABEBECGDGHAGHAGFGBABCGFC,True +801,27.0,24.0,11.0,26.0,22.0,20.0,24.0,21.0,FDEFHBBHDBDFECFEGGEGBBBFGBAGBGFBAEHFGHCAACHBBHBDHEABEFBAFGEDECDEGFGGHDGAGGAHCBHEEEFHEDHADFDHGEGFAAACDFDDFBDCEAHEBHEAAEFBDABAABHABDAGDADFAHFGHFGHCGDFGEBCDBDAGDBGHAHDADAGECDACDE,False +802,24.0,16.0,21.0,28.0,24.0,24.0,17.0,24.0,EHGDHECEADBDCGFCGDCFDEFDHFEEBHECAGBDHDDAAAAGEHGCCGBEGCEGEFDEBDAAGEFCAFABFBEAGEAFECCDDCDDHDHFDEFGAACEEEHGHHADHFHADHFCCAHGACGAHECBEBBDFBCFBHADDAGDCDFAHFAHFABFEBFECFHDBHDBHDGHFHFCDF,False +803,20.0,21.0,21.0,27.0,21.0,19.0,21.0,15.0,CHCDAADHHDHFEEFGGDBGABGCBCFAHFHFFGBDEBFEAFEHBEFDEFDAHCGGCDFCGCGECGEAGDBCEBGAADFADFCDAEDBDAHAEHAEGGEGAHGADFCHCCHBDBBGEADDADDBFDBCBBCBEGDDCEEAGDCGDFDEGBEBBFBAHCEHCFCFD,False +804,1.0,2.0,0.0,1.0,3.0,0.0,1.0,2.0,HBEHBEDEAG,True +805,17.0,17.0,12.0,11.0,12.0,11.0,11.0,14.0,CACCACHGBBBBABBDBGEGCAGFBEFAEBAECGBHHHHHHHFDEFGCGGBBBAFFAFFACAACGACDDEFEEDEADHAHCBHDGHABHEBGCFAHBEDDDFEDA,False +806,8.0,5.0,13.0,9.0,8.0,4.0,5.0,7.0,AABDACCACDACDBCBEEHEHCDHEDGEDADGFFCCBCGBEHCHHDGHECCFDCFAEGA,False +807,2.0,3.0,6.0,1.0,2.0,2.0,5.0,2.0,CCGFCGCAGEGGHBBHBDCFECA,True +808,8.0,11.0,13.0,11.0,20.0,5.0,10.0,7.0,EDGEBEBGEBGECCCADEEEBCEGEDBECBCCDAEDHECHAGHGCDDFDBFEBFEBEEGEFHAAGABGDFHDCHACBEDGECAHC,False +809,19.0,18.0,17.0,18.0,21.0,24.0,23.0,21.0,GGGGAGFDDEHDEHAEFAGHHHHCBECAGCEGEBGABGFBDCHDBHEHHGHFAHGCBGFDCFDCFBEFHHDAGFFGCEEDHGDCADAAHEEDEBHHFAFFABFACCBCABHGCGDBEDFEGFCGFBFBBCBBDFEGFECFAHDAEDAEAEEDCBGGFFFHA,False +810,20.0,16.0,11.0,12.0,13.0,19.0,22.0,18.0,AGFCHFDDFBEHGEHGBHGDCGFCHEGAGADFAGGAHAFBABBFBBGGAABAAEADEBDGCHHEBGCAEAHEGCAGFHDFHFEHAGDGFDBFBBFADCGDBGHFGHCCCGCDGBBAAFFAFHHFEHFEHEE,False +811,17.0,22.0,15.0,31.0,25.0,25.0,18.0,24.0,HAFEGGECCHDGGGHDGCDGDEAAEHGEFGBGGHGBEFEEBCHAEHCFHDFHDFGDGDBGDAFBFFBFHEECEDBEDHDBEDBFDBFABDEFCHAEFEDHCDAFDCBDABDABFCBCDHEHFCAFCDBEDACDEHFFHFFEEEBDEHEBHBHHAHGBHDHGDBCABDADDFDAFGAF,False +812,13.0,7.0,5.0,13.0,10.0,18.0,4.0,11.0,FGEADHABHAEHFCHFAAEEAFEAFDAFABEGGHFFBBDBHCAHADHBFADCCHEDFGDFDDBDFEDFEHFDAFDFFEHFC,True +813,30.0,25.0,17.0,27.0,18.0,16.0,23.0,20.0,DGAGBDGFDGFAAACAGCEFHDAHDBHCBACFACFGHFEFBHHBDHBAEDAHCEFDGCAADABGABDEGDGCAGCEGBABEABDFGDFADFABGBHGAFGDDGHDAHDCDDEDGECHEHGFBBFHBEBBCBDGGHHCEHBEGBCGADAADBHEFDEFHEAADCCHEDECAAABABB,False +814,24.0,14.0,14.0,18.0,16.0,18.0,16.0,21.0,ACBABDDGDGCCHAEHAEFDEFGHFGHFGDCGEBFDBGGBFACACFAGEHGBAFBAEAAEFHEGHCAEAADDHCABFHHEDHDHACHAGHACHGCHCHDDHABAAFADDBBABFHCFGCFEDDEDDHFEHFEGFBGEAFEB,False +815,13.0,9.0,13.0,16.0,13.0,6.0,10.0,11.0,EBHEDEGACDDCDGCDACHFCECCHGBHGBHCBEDAEDHFAFEAHEADAAEADDFFEGBDGEHHABGGHGCCADCDDCDHCABEFBEDBAG,False +816,3.0,7.0,5.0,5.0,0.0,0.0,5.0,2.0,DDCDBADBHGBGBBGCCCACBAGBDGH,True +817,5.0,5.0,2.0,2.0,3.0,8.0,12.0,6.0,HCHGCGFHGAEAFGHFGHFGFEADEHDFBGGGGGGFBFABABB,True +818,1.0,11.0,9.0,4.0,7.0,7.0,8.0,7.0,GABGHBHDBHCBECBFGHFGBCBBFEBECCEFCDFCGHCFCDHEFGEGBEBHDG,False +819,2.0,2.0,5.0,5.0,0.0,2.0,1.0,5.0,CDACFHHFAHDBHCCDCHDBGD,True +820,11.0,24.0,12.0,20.0,8.0,10.0,7.0,16.0,DDBDDECFEFFEBFBBABHAFHGGCCADEHHABDDDDCGHFABFABFHDCBDBGDBCDBFEHHCBHADHADBADCHDCBDHBEHBHABCGBEGBCDCGHBDAEFBBBH,False +821,9.0,5.0,8.0,7.0,7.0,2.0,8.0,6.0,DCDGGAGGCHGCHBBEEAGEGEFCEDADAADAAFCABCEHCBHBEHCAHDDG,False +822,4.0,6.0,4.0,6.0,8.0,10.0,6.0,8.0,DGEHGBHAFDDFEAHBFCBFCDFADFCDHGEHGBFCBHEHGEBEEHEFGFFA,False +823,11.0,21.0,15.0,29.0,14.0,28.0,25.0,13.0,GCBACBGFGGFADDGDDHCCBEGFEGBDBBDFFEFECFBCFBFFGFFGDDHHDFHEFDEDDAFAGFDEBEBBDDHDEHGCHFCGCAGCFGDGGHCFBBFBDCGGEGDEBAHFDEADEADFCDGABFDDFGDCGBFADABDGBHGHGFHFDHFEBCB,False +824,9.0,9.0,18.0,17.0,22.0,11.0,12.0,16.0,HDHHDBHCFHEEAEBDEDAEDBEDBHHAFFDDFCHGCHECDDCEEEFEDGADGCDCCHCAHCAHCEHGECGEGGHFDCCEECACBGCEGFGDEBAFFAGCGBEEEFDEFDBHBH,False +825,13.0,14.0,23.0,11.0,13.0,29.0,17.0,16.0,CFBCFDDFBDFBHFHGFAGEAFFBHFCCFCFACFACFDCAEBHFGGBAGDEEHBGFAGFHEDHGFEBFHHFGFDCFCBHEEGGCFGEFBCADHHDBFDBHDHACHCCGCEGAGGFFACCAECFHCGBCEFCEFCAB,False +826,5.0,8.0,5.0,6.0,10.0,4.0,3.0,7.0,DDEDAGAAGAHCDDBBHBGEEFHECEFHEBHEFHECEECBBCHBDFBA,False +827,20.0,17.0,26.0,28.0,18.0,27.0,26.0,26.0,ECFEGFEHFHHFABFABFEHABHAGDBHDBHDBGDGCDGHABHAFCEHDBHGCDCEFEEADECDAFBGFEGFBAAGDGDDEEDHDABDABFAGFDGDDADCBDAHGHHGHHFFFFFGCDEDGGCBCFEDGCCGCCDCEFFHHAHDBHAFCCFDGBCCHACHDEGGEGCCDCCHCBGFAAFEGFGCHHF,False +828,10.0,8.0,14.0,9.0,25.0,17.0,21.0,17.0,ECHGCHBCGEFDEFDECDEGBECBHBHHFFGGFGGHDGHACCAHHBDCFGAFGAGEEHEAHECEEHEEBEEGDECFEBFECFHFFGGGAEGHEGFCFBAGAHEEGDAAHFHCFGEEDFGDC,False +829,3.0,3.0,1.0,2.0,3.0,6.0,4.0,4.0,DHEHHDFHGGBAGAFEACEGFBFFBF,False +830,13.0,14.0,5.0,14.0,12.0,16.0,14.0,22.0,GDABFFCGFEHEGFFBHCBHEDHFGFBBFEDEHDHHGFHAEHAEHCEHABHADGEDGAFGHBCHAGHADHEFHFFGFGBAABAABDGBDCHDGBEAFHHDDBDHBFHDEG,False +831,30.0,21.0,25.0,25.0,16.0,20.0,17.0,32.0,ABDAGCAGBEEEEFEEFGBFGACGBHGBHCAACAACGCHGHADHACEECHDHACHFEGEAGDAHDAHDGBBHBFHGCHEHHAFGFFDDBGHHDHDEHABBACBHCADFDDHBDHBDCDCBDAHFFHDDBFHAGCDBFFEECCECCGHAHCAHBEHDACDAHDFCDAHDBBFFBAFCFFCAHAAGAC,False +832,25.0,27.0,23.0,20.0,26.0,20.0,20.0,27.0,AADBAGBCFACEEGDFBFFBFHCGDBHEFHCFBFBEEBHCCHCHBEBGABDAHDFHDHHFEHGECGFCBHDFHABBDDBDFHDGCGCCGCDGCHBHEEDEHDHBDEEHEGHBBHFBHFBGCEGEDAEGAECCEAAEACBAHDEBAEBFGACGAFAHDABAHDGCDEAHEAFECFGAACBACHAGBFGE,False +833,25.0,13.0,14.0,24.0,17.0,12.0,19.0,18.0,AEBDEBFCFGAEEHEAHBAHDCFDHFBFAGFAGAEGCCDCAAGAHEHHGAHEACFDEGDCFBAGGABGADGCDGFEBFEAAAGAAECBGDFCDBEDHEBCDDHDDHDGHDHHGCHGEBGHCAHDEEDCDDBADAAGABHDDF,False +834,15.0,10.0,18.0,19.0,15.0,14.0,14.0,17.0,GFDGHHGDHFHCFDBEBGADGACECCHHCHFAHCEHCHHDEHAEBADDGDBGDEEDECDFCAFEEFEDDHDCGAHBAGBDEADGHEFDFABCEBFGBCABCFGCFACGDHDEHACACCAFGF,False +835,20.0,10.0,18.0,14.0,16.0,28.0,23.0,12.0,CBFFGFCHEDBFHGFEGFEGFEDCEDAEHAGGGGFGGCCCDGCFGCFHAFBAFBDFCFFHAAGCEGAEGHEGDFAFFCDFADECHEAHGFGEHGEBDDBABFABABECHCFGCDDFFGFAACAAEDHGGHECDBAFCAFAF,False +836,30.0,20.0,19.0,16.0,19.0,13.0,25.0,21.0,GEHGEGBFGFCGFAGHHGFGGFDHAAHECBAGGAGHCGBCABFHBECAAHAFCEBCEACEADDADCGHBDHGFEDBCAEGAHGHCGHCGEBBHGDHEDHDFBEBBFADEAHEACBAEGFDCAABAABAABGAEACHBHDGADHAEBACHDGDAGCEDCEFCBF,False +837,11.0,6.0,11.0,21.0,12.0,11.0,14.0,20.0,CCGFFHDFDCHECHGCEGCGGDDGABGAEHDEHGGHGHDDHDABDHBHFFGEFHDAEDFEDFGFAHHHCFHAEDGEHCHFDADDGDBADAHDAHDCDCCBEHBEAE,False +838,2.0,11.0,5.0,5.0,5.0,11.0,2.0,7.0,HHAFDBFCBFHBFCBHCFEBHEBCFBFEBEHBDDDEDCABBFFGFFGH,True +839,10.0,18.0,12.0,15.0,22.0,22.0,14.0,20.0,GHGGHDGHEHCFHBHHGHGFDFFBHGBDFBCFBFEBAHAACAEBAFCEFHEABGAHCBCCADAEHFDHFEFFEHFEHCECGHFEBFGCFDBBDBDDCEDEEDEEFBFFGDBBEBGEAEHFDCEGEEDHGDHBF,False +840,6.0,5.0,3.0,4.0,8.0,4.0,5.0,6.0,HFAHFAGABEEHFEBBEABCGBGAFGAECDEDHEHHEDGDC,False +841,22.0,25.0,12.0,20.0,30.0,18.0,24.0,19.0,CFDABGGBGGDGGBGDBGDFEHGEHAEDEEDEEAEGABBABHABFEGAAAAFAAGHFEEEAHFBBFBDHEHAGHADHFDHEDHEDCFAHFEHGEHEEHCBBDBBGBGEBCEBFEHDCFAGFECABGDHEFFEBEACCHEGEGCAFDACECDGDBHEFCGFGGBBBDBDDA,False +842,26.0,32.0,18.0,28.0,33.0,16.0,26.0,21.0,BDFEACGAHGEHBEFBDDCDDEBGFBAHCGBBGCEDEHBAFGGFBDFDABCCBFCBHEBEAFGAEGFEGEDGAABBHBDCAAEAEEBEBGDGGDGHDHHCACBEGGDHADHGEFEBDEBDHBDHBEHBHDDCDFCDCGAGGEGGEGFECAEABEAHDAHCFFCDHAAHAACAABFEEEBDEBDGBDBCEEHDBGEBEAHF,False +843,17.0,15.0,21.0,18.0,10.0,19.0,19.0,11.0,GCGCCGCDBAAFCFFCGCCFCBGCBHBGADGFEEEBEDCFDCFBEFAEGDDDDDAGACDEFDBFGCFGEFDDHCGGGGGAFACHACHACGADGHHCHBFAAFDFFDABBEBFHBHEBHCAHBADGABFDC,False +844,28.0,20.0,25.0,32.0,29.0,10.0,34.0,16.0,GCBGCEAHBHHGHCGADBHDGAFGCFEEFDEAABAAFACGACHAGEEEEEBDBDDGEAEBGCFGAFGCGACGAGFEDAGDAGDBGDFEBECDGBDHBDBBDAEHADAAHGDCGDEBAHBEDCGBEGHEDHCCEDDEDCEGCDHDACAABADGEEFCEFGGAHGCCGCBECECBDHDCADAGDGGDGGDECHEBD,False +845,9.0,18.0,18.0,15.0,16.0,16.0,18.0,30.0,FHHFCHBCEBFEBFBHCGHEGFEDEHABHBHCEHCGGEGGCGGDGHDFHBFHAGACEDBBBBBFHEDHAHHBHEGHEHFDHEBHDDHCDCDHCACADBHDAAEGHFCCECCFHHBHGDHCDHFDGFBGFGGECAFBFCEG,False +846,25.0,21.0,20.0,25.0,14.0,20.0,19.0,27.0,DHHAHHGHBEBFFBHACHBCHFEAFHAGEAGEDFFDHACGDCGEBDDBGEAFAAGAAHAAFCFDCAEFBEGHGDCFAEDABDABHGBHGFHFDGDDGDDHFBABCADDACHBCHCGECACDBCGBCFHEHCCBBHHHFHFBHECEDHDAHDFDDFBBFDBEGACGACGADG,False +847,19.0,22.0,26.0,32.0,24.0,20.0,17.0,30.0,FFFFFBEBBCDDHBEHDHHFHCDHCDBCDAFBHDGHDECDEDGEDCBFEFEHAHHAEDBDGHDCHECDEFHHADHCHBCHCDDCHBBHBEECCDFEDFDBGDBDFBEBAEFAHAGFECCACDHCEHCGGCGGCAGABCAGAGCDBADGEDFEGAEGAEHACHCBHABDBEDEDDHADGGFBFFHEFHCAH,False +848,9.0,6.0,11.0,10.0,14.0,15.0,7.0,8.0,EBECBHGDFECFDGFDHFDCEAAGDEFDEFDFFHCAHGBDDHDHFEGEGBAFCEFCAFCACCACBAFHFEHEEFEGAEBC,False +849,4.0,12.0,3.0,4.0,4.0,6.0,9.0,4.0,BADBFBBDBCDAGGEGGAHFBHFECBBGGCGGBBGBDFFHFEHAEB,True +850,11.0,16.0,15.0,13.0,9.0,18.0,8.0,14.0,AHEFHEDHAHCBEFAEABEBBDHGAGCECCECCEDGADFFBFFBFFACACDFCDECHHFDFFHFFGFBAHBCDBGDBGHHGHFBDBHDBCCFHDACABDGBCBF,False +851,14.0,6.0,9.0,8.0,8.0,11.0,8.0,4.0,CADAAFAFGGBDGBECHEGAEGCEGHEAFCGCCAFCAFDBEHBAAAFAFFECEDADGACFBDFHDFBD,False +852,13.0,17.0,14.0,11.0,14.0,23.0,28.0,19.0,AHFBHFEDBHCBHGDHDDBEFGAFBEDCEDCGGCAGCHGCHGCDCEEGFBBFHCGHAGDCFEGABFCBECBAFBAFHHGHEBCFAEGGEGAFBFGGGDGBDBFAEEBGAGHAFHCFHFFAGFHGFHFFHGGBGGHDGFE,False +853,17.0,14.0,15.0,18.0,12.0,25.0,14.0,18.0,FEEDCEDAEDABFABGHCGEGBAFBAFADFDDFBDFGDGEEAEHDGHCFHCHGBHFHFACAEBGHHGHAGAAFFDCCDHCGGCFDCFHCGECADCFDBFEBFBDGHDCHCHDAFFFHFBBEAFADFHBFHFAB,False +854,4.0,8.0,7.0,9.0,7.0,13.0,4.0,5.0,HAHBAEBCEFDHFGBFDDFDDFCGFBBCBFCFFCAFEDFBCGCDGEHEEDFDHFEBA,False +855,8.0,9.0,7.0,8.0,14.0,11.0,8.0,11.0,FCGGHEGHCAHEGDGCDHEBHEGEEFAEFCEAAFAHDEHFEHBGFBFFBFEAHEADCBBCBBCEGDDHFDFBHEAD,False +856,15.0,19.0,19.0,21.0,20.0,23.0,9.0,21.0,EHCABCEDCEDCHDBADEFFEAHGADFHBFEBFEHFEGCHGBBFBDFDCFHCFCGHCDHEHADFFEFHCGHCBABEEBEFBCDBCEHDACDBBDCBACBAEBDDCADFAEFEEHDGHDEEFBFFDHGHFGAFAHFCGFHBHDADAHC,False +857,8.0,14.0,12.0,26.0,12.0,12.0,24.0,18.0,DDGDGFHGDEEDEHGEDDCHGCAGDGBBHHAHDBHDBGACHCCHFCHGGHDGHDBFABCHGHGFDCEAGEADEGDADEGHBCFBGFGDCGBFDFFDCBDCGDGBEGBFGEHHEFHDFGDAEDBDDB,False +858,3.0,12.0,7.0,10.0,7.0,11.0,5.0,6.0,EHBFDFFCEGCEBFAFCCFECFHDGCEHAEFDBFDBAHBGHBGEBCDFDDFBDBDGBHBBD,False +859,15.0,8.0,5.0,5.0,11.0,6.0,8.0,9.0,AFHEGGEGBEDBACAADADGGHGFEGCEHCDAFECBBABHHEHAECFHBAHGABDEBAEFAEFAHAA,False +860,24.0,23.0,16.0,29.0,25.0,13.0,28.0,31.0,ABDBGHHDBEAACAHBDDDDHHGAHBDHDAHCGHCAEGFECFECGHAGBBDBDDBDGBDBAEBACDAHDBGDBCEBGEDDEBDBBABGGGGGEHAEGGGDFHDAHAHFAFDCHDCHEFBEAGECHFCHGGEGGAGFDHADEGHAFHBGHEFBCAGCAEBHEDHEDEEDFEGFHCEHDHHFCHEAGECHA,False +861,19.0,16.0,16.0,18.0,22.0,19.0,15.0,18.0,HBDHADGAFFFCFDCFDHFAEEDEEABBABHHEAEDAHDEHCGFEECHECEFGHFDHFEEGCBDFDGHDGHDCBDCAECAHBACGEFBFFAFBAFBEDHDAHBBDGEGCEGBGDFGAFGAHCHGFECAEGABAHBACBECECD,False +862,23.0,28.0,34.0,23.0,21.0,19.0,19.0,23.0,AADEFDECBCFBFEGCHHCBCAHCAEDAEDFGBAHBGBBGEDGEFBAFBABEABFAHFAHADGBHAAHAAHCFCAECBEHBACDDCDCHDHHDAHDAHCFBCDHCBBGDEDEHFBCCCCCDGEDEEBCBHCDEBEHBCGCDECGCCGBCGBCFAGGACBHBFCAGCFBDHBFHFECFGHEGCEFDDFGDG,False +863,11.0,5.0,11.0,10.0,13.0,17.0,9.0,9.0,HGFAGHEGFFAEFGCHCCHCFACEAFEAFBFFBEEDDDGGDFEBHDFEDFEFCEHCDAAFBAFHCFECHEDDABDAGCCGAHGEF,False +864,8.0,4.0,8.0,5.0,6.0,11.0,2.0,13.0,CGDDADAFHFEHACHFFHAFHAGABEFBHHCHFCFBEHCEHDEFDCFEFHCAHCAHB,True +865,6.0,7.0,13.0,8.0,5.0,5.0,10.0,8.0,EBBEADDABHGBFBHDAHDFCCCCCGDCGACEFCEGCGGCDHHBGHCGCGBFDDFEAHCAHG,False +866,13.0,18.0,13.0,24.0,13.0,21.0,16.0,22.0,CECHEHGAHDBHAACGDDGDDGBGFBACBAFGCFGEBHHBHBBFBBFGDFEBHDBAEEAGEHFEDGEDFFHFADDADFHCHEADCFDBEDCDDFFBFFHFGEFGHCDFBHADHFDHFHCGCAGDACEBDHBDGDHGCHBH,False +867,3.0,4.0,1.0,1.0,0.0,0.0,2.0,1.0,BGHBGBAABACD,True +868,12.0,15.0,8.0,11.0,24.0,11.0,16.0,16.0,GBGAFGAHEABDAHEEHEGHFBEGHCHHCBDFECAADDGHFHFGEAGEBCDGEDBEFEEFGDGGAHGDHEEHBEHGEAGECGEAHECHBBEFBHBBDBBDCBFEFEEFECAAD,False +869,14.0,6.0,19.0,11.0,20.0,15.0,11.0,18.0,AFHAEHAEHGFHACHADFFGGFEGFEGDEDBAFBDECHHGHCCDBCFECHCHFBEDEECHACDGFDCHCEHFHCFACEACEACBCGBGEADECEEGFEHFACEDHEDHAGHFCA,False +870,7.0,10.0,10.0,16.0,6.0,4.0,11.0,16.0,HCBDCBHCBACDCCDHFHAGHCCDECGEDGDAFHGHGBDDFADHGDHBDHBGHFHEAABGBDHEDHEHHEGDDGADGCBB,False +871,6.0,1.0,1.0,3.0,2.0,4.0,9.0,6.0,AHCGEDGAHEAHAFGAGGBHGAHGFGDFGFHD,True +872,3.0,5.0,3.0,3.0,6.0,1.0,1.0,2.0,BBBDCBEGHEFHDBADAECAECEE,True +873,2.0,1.0,1.0,2.0,5.0,1.0,2.0,3.0,HEGAEHAEBCFDEHDEG,True +874,7.0,21.0,14.0,14.0,9.0,12.0,13.0,10.0,FDBFBBDBADBHBAGDHHCGEFDEBGEGGFGBCGEADAGGADHBDFCDECGBCEDFHFGHFEAFGHEDCEDCBFCBCCBHBBHBBDCBFGBCBHDBCAFC,False +875,6.0,6.0,10.0,12.0,5.0,8.0,13.0,6.0,GCGGCGGHBFDDADDBDFBDGCFGAEGAFBBCBHHFDHADHAGCDGEDEFGGCECCHDCEACGDFF,False +876,19.0,14.0,14.0,17.0,5.0,8.0,26.0,9.0,ADBACAGCHGCFGHDADABGEDABDABAFGCFDCADGGGGGGGGGBGGBACCHHAAGAADAGDAGDCGDBFFBCFBEBCEBGBBHEGDDCCCBHHAFGDGADGDDAFCGHHE,True +877,11.0,23.0,26.0,15.0,25.0,13.0,27.0,20.0,DHHEHGFGGCEHCGDGEDHCDHBFEDFEAFHBDGFCBHCEECEECBHCACGACACHGBHGBGGECGBDHCFEEEHCGHCGHCEBEFBGABCDDEGGEGGEGFEDBEBBGBCGBHABGEDCABCFECAHHBBCBDCAGBDGBAGCAHFHEBCEGCDFFDEF,False +878,10.0,21.0,12.0,20.0,16.0,27.0,18.0,16.0,EGCEHFAFAEBBGACGEEDEBDEFDBBDCBDEDFFAFGHBDFBHBGHBEBEGDDGDGBHGBHBFFGDFCFGCFAEGHEDEEDEAFFFFFFCHGGDGAFGAFHDBHEBCAGHBFDFFBHFCHFCHCCDCFDHBDGBDBHFA,False +879,13.0,7.0,15.0,3.0,11.0,11.0,9.0,9.0,CHBCFBFGEFEHCCAFAAFCEECBBHEEGEFBEABAADGAGGFGFCGACEHCHCFECADCACCACFAHFHDGHGAHEB,False +880,18.0,17.0,11.0,7.0,12.0,11.0,12.0,19.0,GACGHHGCCDAEAEBAFGHFGHEHABHBDHGCHGCHBABEEBECDDBABBHFHGCBGCBFAAGDAGHHHCAFCABAABAABHAFDAFBGDCHFEBEEHEFHEFBFHE,False +881,15.0,14.0,12.0,18.0,16.0,16.0,10.0,24.0,EFDEFDHBEHAEFFBHEBGEFABHGEHDFHAFEBCDGDAFDAHAACDACDGCEHDBBBBHDHEAEFAHGDFDABHABHAEHFEHFHHFHBFHAFHAEDCGBGGDDHDEHCBCCHCEFDGGHCDCC,False +882,1.0,3.0,4.0,5.0,7.0,5.0,2.0,5.0,HDHBCGDFACFECFEFBDFDGHEEHEBHEDCE,True +883,10.0,19.0,13.0,15.0,16.0,14.0,11.0,10.0,FDEBDAHCBEFHFHGGHGEBGCHCEECDACEFBAFHCBCEBAGBFGCEGBEHDDHBDHCDAFDEBDFBDEADBADBAECAGDABCGDCFBGFBDFBEFBFGBEHEECF,False +884,4.0,20.0,14.0,12.0,17.0,18.0,12.0,16.0,DHCFHCBHGFHFEDFEDBCDBFHHGCDFADCGHFBDCBDHAGEFBEHBEDCEGCABFHBHCCCCBHCGGFGFFBFBBEGFEBBBCGEGHHHFDAFDEFBEFHEGDEBEEBEEB,False +885,4.0,5.0,7.0,5.0,3.0,5.0,11.0,4.0,GBBEAFCABHGBGEFGDDCBDCFGCAGCDGCGHEGHFCHFGAGD,False +886,4.0,2.0,5.0,6.0,4.0,7.0,8.0,6.0,DEGFEGHBGCGHBGHDFAFFAFDADGCHECDECFFCHADHGG,False +887,7.0,10.0,2.0,12.0,7.0,8.0,10.0,7.0,HDGHAEDCDDBGDBAEBGCBDAEGFGFBGFBDDBFHBEHADFGDFHHFHEDGADGAFEAGEBB,False +888,22.0,21.0,26.0,15.0,24.0,25.0,19.0,23.0,HFHEFEAADAGDBCEBGEBEFHEGHAGEDGADFEBFCBFBBFCEHADFEHGHHFDFCHFCHDBGDHAAHFCFAEBAEGCEGCFFAHHGHHFHHCHCBABGDHHDFABGCFACFECDEAGEAGFBCFGCEGCBBBEBAGHGGCBAFACFDCDDCFCAHCACCBEEBEEBEADCCEF,False +889,14.0,18.0,14.0,7.0,16.0,10.0,10.0,16.0,FHAHHEDDECCCHBCBBFBFCBACDAGHAGHBFHBCHBEGEEGBBGBBGEAEAHHBEFFEAFEDHECEEGABGBDGCABEABAFCHCAACGBHHAHCDHFECFED,False +890,18.0,20.0,25.0,21.0,23.0,27.0,22.0,23.0,ECFEGEBFABFABCDBFHBHABHBDHGFGBFGECGCFHADHDEACCBHFEGFACHECHFBACCCBEBBDFDAEAABDAECCCFCFFCFFCEGCHBEGDEDFBDEGHFCHFCFDCFEGGEGDDGHDHHCGHFDFBDHGHHAAHAEHFGAFGAEADEFCEFBEGBGGHDAEDCEHCDGBDG,False +891,21.0,17.0,16.0,20.0,21.0,17.0,22.0,30.0,GEDGFABBHBBHFAGAEEAEAAECAEHHHBDDCABHGGHGCBAAFABFBFCGEBFEGEHHEHHDDHFGEEHDGHCAHFADBADCCGACHDGHAGHAFHAFBECBEDHGCHGAHGBDCEDCDBFDEGHGADGDHGFHCDGDFHBHHBHAECFECFEGFHFEDCED,False +892,2.0,4.0,1.0,8.0,1.0,2.0,5.0,5.0,HHHHBDABDGBDFFDCAHGGGBDGDDED,True +893,15.0,5.0,9.0,8.0,9.0,2.0,15.0,5.0,GGEGEEDAFGECACCAGFGEEDECDBAEGADGABAACCACCAHGAHADHGDGGHGBACBHBDEGAAGD,True +894,15.0,20.0,23.0,20.0,17.0,18.0,26.0,16.0,FGDFCFCCGBFEBEEDACGECGHCFFEDBBCHBFHBDAFHBGCFCCFAGHDGDGGBFEEGCEGAFGAEAFEDFEDBBDHBHGGGGCFDCEHBEHGCAAAAAGHCHHCHBGDDCDBGBBCABCABADBADBFDGGCCEDEEDGCGGDDGHCFHEFH,False +895,17.0,14.0,14.0,9.0,18.0,14.0,9.0,18.0,BGCDCCFADADBGDGCAEEAGEBEFBHHAEFFEHFEBEBCGCEBCEDAGGAHEABEABDAFDHBHHAAHBAHAHBAHCEHCAHFHBEHFCFFCEFCEHCHHCAEDFEDBGFGF,False +896,10.0,10.0,7.0,13.0,14.0,14.0,10.0,8.0,HCBCDHHGEAFHFCDGHEBDEAFBCFEDFADEADEADABBHCAEDGDDGFDAFHHFDGFGGFABFBCDBCEAGBBGEFGEFEEFEE,False +897,1.0,6.0,2.0,6.0,4.0,12.0,5.0,5.0,FBDGCGGDFEBFEFFEGFBGFHFFDFHBAHFEDFCHBBHDD,True +898,8.0,2.0,6.0,2.0,1.0,5.0,2.0,3.0,CFFCHDCFEHHAADAACCABAACGAFGBF,True +899,13.0,11.0,11.0,13.0,12.0,11.0,12.0,9.0,FCCGCABEBEEFCBGCDGCAECEEHAEGDCFFHDBCABDABEAFCBHABHADHGDFGDFBDFEDGHBGDGDAGAFECHEGDEGHFAHDABAF,False +900,11.0,8.0,16.0,15.0,15.0,12.0,12.0,10.0,HFDECDECFHCHGDEDEEBGHDAHDABCCDDFGDCGBCACCDGGFCGFEHEAGEAGEAFCCHCCAFEAFADEADHGDBFBBFBBFGCEAHFCDEEDHEG,False +901,6.0,5.0,13.0,12.0,14.0,4.0,0.0,2.0,DEEDEFCACAAEHEECDECAHCBDDECCBCFFDBFBCDECEECEDCADEDDEDACB,True +902,5.0,2.0,3.0,0.0,2.0,4.0,3.0,0.0,CFECFBAGAACAAGFFGBE,True +903,1.0,3.0,5.0,2.0,2.0,3.0,3.0,5.0,HEAGEFBCDBCBCFHCFHCDHGHG,False +904,8.0,10.0,8.0,10.0,10.0,10.0,8.0,8.0,HAEHAEDAEDGHFGFFAFFBFFGDABDECDEGGEGHBHBBCCFEDGECBCCBACHDCAFBDDEEDAHGBHBF,False +905,19.0,35.0,22.0,16.0,17.0,18.0,22.0,17.0,BEDEDGGBEBBDBGHBCBBCBHCAEAHBAGBCBHDBHDCHGCBGDAGDCCAGDGCDFCBFCBDBBDHAAEAGEGGEGBAFBHFGFGBFHEACECCGHCFFEFBCFBAFAABBBBBHDBEFBHFAGBEFCDGCFCDEEHBBFBDCGDEGFHGACAACAHHFGHEABE,False +906,6.0,6.0,11.0,1.0,5.0,2.0,8.0,3.0,GGECBACGCCGHCBFEGGAACAACDACBBCHCEFCEHBEGBG,True +907,10.0,11.0,15.0,22.0,12.0,15.0,10.0,11.0,CBDCFAHHHHCHDBDDBEDHCAECDFFDACDGBDABCFBCFBGDCFFCFEEHGGHGADGDFAFACGDCADFBCFGDFEDFDDADGAHEBHFCHDCDEEBEEDEGBE,False +908,4.0,0.0,2.0,5.0,3.0,0.0,2.0,3.0,GHACDADAEDAEDEGDHHC,True +909,1.0,4.0,0.0,5.0,2.0,3.0,1.0,1.0,FDHBDABFEBDDBDEGF,True +910,9.0,19.0,26.0,20.0,13.0,12.0,16.0,22.0,BHDCHGCHBCHDCBGCAEDFEBFBHDBHDGHEGECGCFDCHHGHHBHGFGCCBCCDCHAADFFDFFHEDCFBCEHCEHCDDFAGECGDBDBGFGEECBHCBACBACHCDEFDAHBCHCEGBGGCDDHDEHBAGBADB,False +911,5.0,1.0,2.0,3.0,2.0,3.0,0.0,2.0,HAHAADAFBAFEFCEDCD,True +912,26.0,20.0,25.0,15.0,11.0,21.0,19.0,28.0,BGFDDHABFAGCACFBCDBGDCCAAAHAAHFCHCEGGFFHHFBCABCGGGGBHEAHCAHBAHAHHACHFDHDAHABHCBFEBFADFGDCGFFHCGBCFBDFEDCHBBHBCGECGEHGFHAEHACHADAABHFDECEGBAGDHFDHCCFGAEGAECABFFBHCCHD,False +913,7.0,7.0,5.0,3.0,0.0,6.0,1.0,6.0,CDFCAFHACADCBBHBFHBFHFDGCABBABFHHAA,True +914,20.0,24.0,25.0,24.0,19.0,23.0,23.0,19.0,BDHFDGCHCAHFAHFGGCHBCHDFEDAEHCBFEBCGHCGFEACCAHDFGDFDBFBEFBEBGDBGDBCDECBFHEEEBCGBDDFDECHEHBFCAFADGADAHFCFFGFAGFEGEHGADDHDCHDBDDGEDBHABGGBEGBAHBHBDCFDCACCGEAACCACGAEGBEFBAFCCFGBAG,False +915,6.0,10.0,1.0,9.0,16.0,12.0,5.0,11.0,BFGFHGADDEEEEBEEHEHHEHFEBEGHFDHFBHFBDFDFFEBGDHCEBEEBEAGDADHAFAAFHBBEDF,True +916,19.0,25.0,17.0,15.0,26.0,25.0,27.0,16.0,EBBHBCGEEAEBCECGECHHCGDCECGECDBCDBAGCHGBFDBDBCEBFAAGAAHBGDFGAEGAEHEEHECGFFAFBEEAEEABEHBGHBFHDGCCFEFFCFFGFDHBAHAGFDGFDGHGGEDGEBGHGFFECBAFBHGEFBFGDFHDAADGGBAGBFCBFDEFAFBABE,False +917,1.0,1.0,0.0,2.0,5.0,1.0,1.0,0.0,DABDEEEEGFE,True +918,3.0,4.0,4.0,5.0,6.0,2.0,1.0,2.0,FCHDCBDCDEADEBDEBFBGACAEHEE,True +919,29.0,30.0,27.0,23.0,18.0,16.0,15.0,25.0,CECCDDBFGBEHCFACFCCAAAAABGDBDCBDABFBCEACABCGBHGDCGFBGHCDHCEHCBAFBFGHFHHDHFEHFEHCDBDDACBACGACGACFEDEBDHBDHAAEEGFBHHBHDAHBGBCGDAAHAFEBCCBDBEEAHEHFGHAHAABBABDHBDADDAECGBCEDCDCGEHAEHABBFF,False +920,6.0,8.0,6.0,2.0,10.0,1.0,2.0,2.0,ABABBFGBDGEECCEACECHEHBEABDBEEEACEACB,True +921,9.0,6.0,2.0,9.0,10.0,5.0,13.0,15.0,EBEDHGAHGFHGFBDEDDGCDGDHFAEABEGEGAHGAFEAGHAHHEHDEHDABDBGEGGBGHHACHFHH,True +922,0.0,4.0,4.0,4.0,5.0,3.0,8.0,5.0,BFCBHEBHDBCDFGGEGFEGEHGHCDHGDGGEC,False +923,9.0,18.0,18.0,28.0,20.0,33.0,20.0,19.0,FCFHEFDEBCBBCFACFDCDCAFCAHBDHBFGFHAFEAFEHGCHGDHCDHCFCGDCHBEGFFGDFGBHGDFGDFGFAHDBGGHHABEDFFDFFDFFEBFHDCEDFEFHEHHDGACFFGHBBHBADDDDCDEGDGGCEFCDBEBGEDEEBCEFGFFBEDGEDBFDE,False +924,2.0,5.0,0.0,7.0,6.0,1.0,0.0,3.0,EEDEEHEBAEBDDDADBHDFHBBD,True +925,12.0,20.0,17.0,18.0,18.0,15.0,13.0,21.0,GHHFHBACCFFHHFHHABHGDHFDEBABDDBCAEHABDEDCGDGDDGCDFFDHEBAEBAEBDCBGCEGBEHBFCEFDBGBFGBHBHHFFEEGECGECGECBHGBHDCHDAFDCFDEAHAHEAHACCEEFBBDCC,False 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+976,27.0,32.0,25.0,20.0,17.0,19.0,24.0,36.0,HCFABFDBGEFGFDCBDCAEBHEDADCADCGBCDACDBBHBBDAHAHHFFGEFHHBBHEFAEDHEHHBHHDAHCACCDDDAHCEECBBHBHHBGDBGBBGHCAHCFHFHGCHGAEGFFBBHCBHAAABACEGCGGCGACFACGHBDCBHCGGEHEBGAFFAEHHDFHDFEGFABDABGBBECBEBGAAFAACGHGHHGDH,False +977,21.0,23.0,33.0,29.0,26.0,21.0,26.0,19.0,BFCBCBEGFEGDEGFEBDACFGCDGADCDDCBBCGCDDCGCCGDDGBFBEEBAABAACFCCFHDDHDEBDEFCEBBGBEEDAEAHFCHFHHEBEEFFEFHEADEGEGGCGGADDFBCADDDCCGCCGCDGEDFADGDFGFFBCAAHAHEFHECAGFGDCEDCADBAHHHHEHHEFHBCCCCBBAABCAHHDGBEGCGG,False +978,7.0,8.0,10.0,5.0,10.0,5.0,5.0,1.0,DECDEBFCGFADFEBAECABABEGGECDFCGBEGCEHCBDCBCABCAEAFE,True +979,1.0,2.0,1.0,6.0,0.0,1.0,0.0,1.0,DCADFBDHDDBD,True +980,24.0,21.0,18.0,12.0,17.0,7.0,12.0,18.0,BBAHBHDDHBHFAHACBEBBCBAEEACHAHHEGBBGBCDCCAECAHCAGGAFFACFAHHEEAEHFGCACEACHFCHDDEDDEDDCBCCHEBHBAHEABBGBBADBGBBEAAGAADHEGEGGEGAFDACC,False +981,22.0,33.0,18.0,23.0,27.0,28.0,28.0,13.0,EAEDGBCFBAFBGFDAFAAGHAEBFHFFHFFGACDBDFCDFGDBEBBDHCFBEEGGDAGECGEFABFGBEDAEAHEGDDBEGCDABHBBGBDFBDHBGBBEBBHABAABDCEFGAFGAFBFCEFBGGHAGAFEDGEDCHFHBFGDHCFHCAGFDGCGECFECBECBECECABCAEFBEFEEGDBGDEGDBGD,False +982,22.0,20.0,15.0,16.0,27.0,17.0,27.0,21.0,GDFGHEGBEHCEBCHBEHBAHGCGGEGBBFDEADFFHADHEBHGDACDACDEBEEGEHBEGBEGHEBFAAFGFFGDFGDFABGHFHCEECHDGBDCBFFBGCBDDHDCGBCFAFHGGHEGACHECAEAAHCABAACAHEEDEADEFEGBGGEGAAGEBGFAHHAE,False +983,6.0,5.0,6.0,11.0,8.0,8.0,5.0,7.0,HBFHDFCEABBADECDEGDFCDFHBFEDECCFGHFAHGHHADEADFCDGDDGEBAE,False +984,9.0,13.0,13.0,13.0,32.0,25.0,15.0,18.0,EEAEEGEABEGHGFDADEEFAHHCBFGDCBBCHBCFDCFDCFDEFDEFCHFEFECFEHFHGFHGFHEBBCGECBDHHEEDEFCEGAADEFEHGEDFEHFEDFEGBHHFHGEEGEGAACFABFGFDGBEECEEFHBFHB,False +985,14.0,10.0,10.0,7.0,7.0,11.0,13.0,6.0,FAFAHGABAACAAGAFCDDCGCEFDBGBGACHECAECAEBAHDDFDBFDBFGBAGCHBEHBAGBECFFCEFGGGGGFH,False 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#1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/src/main/scala/org/xcit/nback/markov/models/State.scala b/src/main/scala/org/xcit/nback/markov/models/State.scala deleted file mode 100644 index fbbd844..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/State.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * A Single state with a label in Markov chain - * @param label A simple string label, representing the state and node - */ -class State(val label: String) { - - /** - * Keep track of transitions from this state to other states. - */ - val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() -} diff --git a/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/src/main/scala/org/xcit/nback/markov/models/Transition.scala deleted file mode 100644 index bc20a9e..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/Transition.scala +++ /dev/null @@ -1,8 +0,0 @@ -package org.xcit.nback.markov.models - -/** - * A Single transition in Markov chain graph. It is stored in "from" node. - * @param to the ending node of the edge - * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). - */ -case class Transition(to: State, probability: Double = 0.0) diff --git a/src/test/scala/ThreeBackBenchmark.scala b/src/test/scala/ThreeBackBenchmark.scala deleted file mode 100644 index 0c7dad9..0000000 --- a/src/test/scala/ThreeBackBenchmark.scala +++ /dev/null @@ -1,7 +0,0 @@ - -/** - * TODO Benchmark 3-back simple sequence generator - */ -class ThreeBackBenchmark { - -} diff --git a/tests/benchmark_diagrams.py b/tests/benchmark_diagrams.py new file mode 100644 index 0000000..8fa448e --- /dev/null +++ b/tests/benchmark_diagrams.py @@ -0,0 +1,159 @@ +import pandas as pd +import numpy as np +from matplotlib import pyplot as plt + +import benchmarks.common as common + + +def tlratio(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2,ignore_index=True) + stats = [] + for trials in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == trials) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == trials) + targets2 = data[alg2].targets if alg2.shape[0] > 0 else np.nan + targets4 = data[alg4].targets if alg4.shape[0] > 0 else np.nan + lures2 = data[alg2].lures if alg2.shape[0] > 0 else np.nan + lures4 = data[alg4].lures if alg4.shape[0] > 0 else np.nan + stats.append([trials, (targets2/lures2).mean(), (targets4/lures4).mean()]) + stats = pd.DataFrame(stats, columns=['trials', 'tl2', 'tl4']) #.dropna(subset=['skewness']) + + plt.style.use('ggplot') + + plt.ylim(bottom=0, top=30) + plt.scatter(stats.trials, stats.tl2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl2[idx], 1)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.tl4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl4[idx], 2)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('T:L Ratio') + plt.ylabel('T:L Ratio') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_tlratio.png', bbox_inches='tight') + plt.show() + + +def time_per_trial(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for t in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == t) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == t) + time2 = data[alg2].time.mean() * 1000 if alg2.shape[0] > 0 else np.nan + time4 = data[alg4].time.mean() * 1000 if alg4.shape[0] > 0 else np.nan + stats.append([t, time2, time4]) + stats = pd.DataFrame(stats, columns=['trials', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.trials, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time2[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time4[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2v4_time_trials.png', bbox_inches='tight') + plt.show() + +def time_profiles(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 8): + alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + time2 = data[alg2].time.mean() * 1000 + time4 = data[alg4].time.mean() * 1000 + stats.append([ni, time2, time4]) + stats = pd.DataFrame(stats, columns=['n', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.n, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.time2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + plt.scatter(stats.n, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.time4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_time_n.png', bbox_inches='tight') + plt.show() + +def skewness(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 9): + all_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + skewed_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) & data.skewed + all_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + skewed_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) & data.skewed + num_of_sequences2 = data[all_alg2].shape[0] + skewed_sequences2 = data[skewed_alg2].shape[0] + num_of_sequences4 = data[all_alg4].shape[0] + skewed_sequences4 = data[skewed_alg4].shape[0] + skewness2 = skewed_sequences2 * 100.0 / num_of_sequences2 if (num_of_sequences2>0) else 0 + skewness4 = skewed_sequences4 * 100.0 / num_of_sequences4 if (num_of_sequences4>0) else 0 + stats.append([ni, skewness2, skewness4]) + stats = pd.DataFrame(stats, columns=['n', 'skewness2', 'skewness4']) #.dropna(subset=['skewness']) + + + plt.style.use('ggplot') + plt.scatter(stats.n, stats.skewness2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.skewness2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + + plt.scatter(stats.n, stats.skewness4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.skewness4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Skewness') + plt.ylabel('Skewed Blocks (%)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_skewness.png', bbox_inches='tight') + plt.show() + +if __name__ == "__main__": + tlratio() + skewness() + time_profiles() + time_per_trial() diff --git a/tests/benchmark_skewness.py b/tests/benchmark_skewness.py new file mode 100644 index 0000000..f468b4d --- /dev/null +++ b/tests/benchmark_skewness.py @@ -0,0 +1,97 @@ +import random +import heapq +import csv + +# Common parameters +alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'] +trials_range = (10, 40) +n = 3 +sample_size = 100 + + +def to_benchmark_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [str(ralph_skewed)] + +def benchmark_nb_gm_001(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_001') + + +def benchmark_nb_gm_002(filename): + import generators.nb_gm_002 as nb_gm_002 + + generator = nb_gm_002.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + # print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_002') + + +def benchmark_nb_gm_003(filename): + import generators.nb_gm_003 as nb_gm_003 + + generator = nb_gm_003.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + print(f"sequence {i}/{sample_size}: {trials} trials") + seq = generator.generate(trials) + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_003') + + +def show_skweness_diagram(filename, choices, title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + print(filename) + data = pd.read_csv(filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) #.dropna(subset=['skewness']) + #print(stats.trials) + #plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'{title}.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + benchmark_nb_gm_003('../benchmarks/nb_gm_003_2back.csv') diff --git a/tests/common.py b/tests/common.py new file mode 100644 index 0000000..e40c0df --- /dev/null +++ b/tests/common.py @@ -0,0 +1,27 @@ + + +# Common benchmark parameters +choices = alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F'] +trials_range = (10, 65) +n = 4 +sample_size = 100 + + +def count_targets_and_lures(seq, n): + mask = 'D'*n + for index in range(n, len(seq)): + if seq[index] == seq[index - n]: + mask += 'T' + elif seq[index] in seq[index - n - 1:index - n + 1]: + mask += 'L' + else: + mask += 'D' + return mask.count('T'), mask.count('L') + + +def skewness(seq, choices): + import heapq + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return ralph_skewed diff --git a/tests/nb_gm_001_bm.py b/tests/nb_gm_001_bm.py new file mode 100644 index 0000000..54f6cb3 --- /dev/null +++ b/tests/nb_gm_001_bm.py @@ -0,0 +1,75 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq) , str(ralph_skewed)] + + +def benchmark(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets / s.trials, axis=1) + plt.scatter(data.trials, data.targets_ratio, alpha=0.2) + plt.show() + +if __name__ == '__main__': + alg = 'nb_gm_001' + fn = f'results/{alg}_{n}back.csv' + benchmark(fn) + # skewness_diagram(fn, alg) + targets_ratio_diagram(fn, alg) diff --git a/tests/nb_gm_002_bm.py b/tests/nb_gm_002_bm.py new file mode 100644 index 0000000..c8af543 --- /dev/null +++ b/tests/nb_gm_002_bm.py @@ -0,0 +1,105 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq), str(ralph_skewed)] + + +def benchmark(filename): + from generators.nb_gm_002 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials, int(trials/3), 0, 0) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +import time +import numpy as np +import pandas as pd + +import benchmarks.common as common + +def profile(): + from generators.nb_gm_002 import SequenceGenerator + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, int(lures/2), int(lures/2)) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('benchmarks/results/nb_gm_002_profile.csv', sep=',', encoding='utf-8') + +if __name__ == '__main__': + alg = 'nb_gm_002' + fn = f'results/{alg}_{n}back.csv' + profile() diff --git a/tests/nb_gm_003_bm.py b/tests/nb_gm_003_bm.py new file mode 100644 index 0000000..fa6c19a --- /dev/null +++ b/tests/nb_gm_003_bm.py @@ -0,0 +1,114 @@ +import heapq +import csv +import random +import time + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq, time_per_block): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [time_per_block, ''.join(seq), str(ralph_skewed)] + + +def benchmark_skewness(filename): + from generators.nb_gm_003 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['time_per_block', 'seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + targets = trials / 3 + t = time.time() + seq = generator.generate(trials, targets) + t = time.time() - t + print(f"sequence {i}/{sample_size}: {trials} trials, took {t}s.") + writer.writerow(to_csv_row(i, seq, t)) + plot_skewness(fn, 'nb_gm_003') + + +def plot_skewness(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def plot_targets_ratio(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +def benchmark_targets_ratio(): + pass + +def benchmark_chunking(): + pass + + +def benchmark_n(): + pass + + +def plot_timing(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['time_per_trial'] = data.apply(lambda s: s.time_per_block / s.trials, axis=1) + plt.style.use('ggplot') + plt.title(f"{figure_title} - average time to generate a trial") + plt.ylabel('time (s)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.time_per_trial, alpha=0.5) + + # draw fitted curve + # import numpy as np + # p = np.poly1d(np.polyfit(data.trials, data.time_per_trial, 3)) + # plt.plot(data.trials, p(data.trials), color='red') + + plt.savefig(f'results/{figure_title}_timing.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + alg = 'nb_gm_003' + fn = f'results/{alg}_{n}back.csv' + benchmark_skewness(fn) diff --git a/tests/nb_gm_004_bm.py b/tests/nb_gm_004_bm.py new file mode 100644 index 0000000..b4ad4a8 --- /dev/null +++ b/tests/nb_gm_004_bm.py @@ -0,0 +1,26 @@ +import time +import numpy as np +import pandas as pd + +import tests.common as common +from generators.nb_gm_004 import SequenceGenerator + +def run(): + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, lures) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('tests/results/nb_gm_004_profile.csv', sep=',', encoding='utf-8') diff --git a/tests/results/2v4_time_trials.png b/tests/results/2v4_time_trials.png new file mode 100644 index 0000000..9be91b4 --- /dev/null +++ b/tests/results/2v4_time_trials.png Binary files differ diff --git a/tests/results/2vs4_skewness.png b/tests/results/2vs4_skewness.png new file mode 100644 index 0000000..a488e1f --- /dev/null +++ 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+210,87.0,0.0,0.0,88.0,1.0,0.0,0.0,0.0,EDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +211,0.0,0.0,12.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCC,True +212,0.0,0.0,0.0,66.0,0.0,65.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +213,1.0,0.0,0.0,0.0,0.0,21.0,22.0,0.0,AGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFG,True +214,74.0,73.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +215,0.0,5.0,0.0,0.0,6.0,0.0,0.0,1.0,HEBEBEBEBEBE,True +216,0.0,1.0,0.0,0.0,0.0,53.0,0.0,54.0,BHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +217,70.0,0.0,0.0,0.0,0.0,70.0,0.0,0.0,AFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +218,0.0,0.0,0.0,0.0,0.0,0.0,36.0,35.0,GGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +219,0.0,90.0,90.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +220,0.0,0.0,0.0,0.0,0.0,0.0,37.0,38.0,HHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +221,0.0,0.0,44.0,0.0,0.0,1.0,44.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +222,0.0,0.0,0.0,67.0,67.0,0.0,0.0,1.0,HDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True 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+409,0.0,0.0,72.0,1.0,0.0,0.0,72.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +410,55.0,0.0,1.0,0.0,0.0,0.0,55.0,0.0,CAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +411,0.0,59.0,0.0,0.0,0.0,60.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +412,61.0,0.0,0.0,61.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +413,0.0,1.0,0.0,75.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +414,0.0,53.0,0.0,0.0,0.0,0.0,52.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +415,0.0,0.0,16.0,0.0,1.0,0.0,0.0,15.0,ECHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +416,0.0,0.0,0.0,39.0,0.0,0.0,0.0,38.0,DHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +417,96.0,0.0,1.0,95.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +418,28.0,0.0,1.0,27.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +419,0.0,1.0,92.0,92.0,0.0,0.0,0.0,0.0,BCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +420,1.0,0.0,20.0,0.0,20.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECE,True +421,0.0,90.0,0.0,0.0,0.0,0.0,89.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +422,10.0,0.0,0.0,0.0,0.0,1.0,11.0,0.0,FGAGAGAGAGAGAGAGAGAGAG,True +423,0.0,0.0,0.0,74.0,73.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +424,0.0,0.0,127.0,0.0,0.0,0.0,1.0,0.0,GCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +425,1.0,9.0,0.0,0.0,0.0,9.0,0.0,0.0,AFBFBFBFBFBFBFBFBFB,True +426,0.0,0.0,84.0,0.0,0.0,0.0,0.0,84.0,HCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +427,33.0,0.0,0.0,34.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +428,1.0,30.0,0.0,30.0,0.0,0.0,0.0,0.0,ABDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +429,0.0,0.0,67.0,0.0,1.0,67.0,0.0,0.0,EFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +430,62.0,0.0,0.0,63.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +431,1.0,9.0,9.0,0.0,0.0,0.0,0.0,0.0,ABCBCBCBCBCBCBCBCBC,True +432,15.0,0.0,0.0,0.0,0.0,0.0,14.0,0.0,AAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +433,0.0,1.0,0.0,65.0,66.0,0.0,0.0,0.0,BEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +434,0.0,160.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +435,0.0,0.0,1.0,0.0,42.0,42.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +436,0.0,0.0,55.0,0.0,55.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +437,0.0,0.0,0.0,1.0,0.0,73.0,0.0,73.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +438,79.0,0.0,0.0,0.0,78.0,0.0,0.0,0.0,AAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +439,0.0,0.0,67.0,0.0,0.0,0.0,66.0,1.0,HCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +440,0.0,0.0,77.0,0.0,0.0,1.0,0.0,76.0,FCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +441,0.0,0.0,0.0,0.0,153.0,0.0,0.0,1.0,HEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +442,0.0,88.0,88.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +443,0.0,0.0,0.0,20.0,22.0,0.0,0.0,0.0,EEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +444,41.0,0.0,42.0,0.0,0.0,0.0,1.0,0.0,GCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +445,0.0,0.0,0.0,47.0,0.0,46.0,0.0,1.0,HDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +446,1.0,0.0,0.0,0.0,86.0,0.0,0.0,87.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +447,56.0,56.0,0.0,0.0,0.0,0.0,0.0,1.0,HABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +448,0.0,0.0,0.0,0.0,11.0,0.0,0.0,10.0,EEHEHEHEHEHEHEHEHEHEH,True +449,0.0,0.0,0.0,0.0,0.0,1.0,92.0,92.0,FGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +450,0.0,0.0,0.0,6.0,5.0,1.0,0.0,0.0,FDEDEDEDEDED,True +451,66.0,1.0,67.0,0.0,0.0,0.0,0.0,0.0,BCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +452,0.0,0.0,0.0,13.0,0.0,1.0,12.0,0.0,FDGDGDGDGDGDGDGDGDGDGDGDGD,True +453,1.0,0.0,0.0,0.0,56.0,0.0,56.0,0.0,AEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +454,15.0,0.0,0.0,0.0,0.0,0.0,0.0,16.0,HAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +455,0.0,21.0,1.0,0.0,21.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True +456,93.0,0.0,1.0,0.0,92.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +457,1.0,0.0,0.0,0.0,35.0,0.0,0.0,35.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +458,13.0,0.0,0.0,0.0,1.0,0.0,13.0,0.0,EAGAGAGAGAGAGAGAGAGAGAGAGAG,True +459,0.0,0.0,65.0,0.0,1.0,0.0,65.0,0.0,ECGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +460,0.0,0.0,95.0,1.0,0.0,95.0,0.0,0.0,DFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +461,15.0,0.0,0.0,0.0,1.0,0.0,0.0,15.0,EHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +462,0.0,0.0,198.0,0.0,1.0,0.0,0.0,0.0,ECCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +463,84.0,84.0,0.0,0.0,1.0,0.0,0.0,0.0,EABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +464,0.0,0.0,0.0,0.0,0.0,60.0,0.0,61.0,HFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +465,0.0,179.0,0.0,1.0,0.0,0.0,0.0,0.0,DBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +466,1.0,0.0,90.0,0.0,89.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +467,0.0,35.0,0.0,0.0,0.0,34.0,0.0,0.0,BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +468,0.0,0.0,0.0,1.0,7.0,0.0,0.0,7.0,DHEHEHEHEHEHEHE,True +469,0.0,0.0,0.0,0.0,92.0,0.0,91.0,0.0,EEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +470,0.0,0.0,46.0,0.0,0.0,1.0,46.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +471,0.0,0.0,0.0,0.0,0.0,1.0,158.0,0.0,FGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +472,1.0,0.0,0.0,0.0,0.0,58.0,0.0,59.0,AHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +473,0.0,0.0,6.0,1.0,0.0,0.0,6.0,0.0,DCGCGCGCGCGCG,True +474,0.0,0.0,0.0,0.0,0.0,98.0,0.0,97.0,FFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +475,0.0,87.0,0.0,0.0,0.0,0.0,0.0,85.0,BBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +476,0.0,0.0,33.0,0.0,0.0,0.0,1.0,33.0,GHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +477,45.0,0.0,0.0,0.0,46.0,0.0,0.0,0.0,EAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +478,0.0,0.0,0.0,77.0,0.0,0.0,75.0,0.0,DDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +479,73.0,1.0,73.0,0.0,0.0,0.0,0.0,0.0,BACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +480,0.0,1.0,0.0,0.0,37.0,37.0,0.0,0.0,BEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +481,0.0,92.0,93.0,0.0,0.0,1.0,0.0,0.0,FCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +482,0.0,0.0,0.0,1.0,0.0,0.0,0.0,24.0,DHHHHHHHHHHHHHHHHHHHHHHHH,True +483,25.0,0.0,0.0,1.0,0.0,25.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +484,0.0,0.0,0.0,0.0,0.0,37.0,0.0,36.0,FHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +485,21.0,0.0,0.0,1.0,0.0,20.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +486,0.0,35.0,0.0,36.0,0.0,0.0,0.0,1.0,HDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +487,0.0,0.0,1.0,0.0,97.0,98.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +488,0.0,93.0,0.0,0.0,0.0,1.0,0.0,94.0,FHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +489,0.0,1.0,0.0,93.0,0.0,0.0,93.0,0.0,BGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +490,0.0,0.0,0.0,70.0,0.0,0.0,72.0,0.0,GGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +491,86.0,0.0,0.0,0.0,1.0,86.0,0.0,0.0,EFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +492,0.0,65.0,1.0,0.0,0.0,65.0,0.0,0.0,CBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +493,0.0,0.0,0.0,69.0,0.0,0.0,0.0,1.0,HDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +494,0.0,0.0,144.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +495,0.0,45.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True 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+599,16.0,0.0,16.0,0.0,0.0,0.0,0.0,0.0,ACACACACACACACACACACACACACACACAC,True +600,0.0,21.0,0.0,22.0,0.0,0.0,0.0,0.0,DBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +601,70.0,71.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +602,0.0,0.0,0.0,1.0,0.0,0.0,53.0,0.0,DGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +603,45.0,0.0,0.0,0.0,0.0,45.0,0.0,0.0,FAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +604,0.0,1.0,56.0,0.0,0.0,0.0,56.0,0.0,BGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +605,0.0,1.0,0.0,0.0,0.0,0.0,0.0,195.0,BHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True 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+611,0.0,0.0,86.0,0.0,88.0,0.0,0.0,0.0,EECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +612,1.0,0.0,0.0,0.0,14.0,0.0,0.0,14.0,AEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +613,0.0,0.0,35.0,0.0,0.0,35.0,1.0,0.0,GCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCF,True +614,0.0,0.0,1.0,0.0,43.0,43.0,0.0,0.0,CEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +615,0.0,0.0,0.0,0.0,0.0,1.0,67.0,66.0,FGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +616,0.0,27.0,0.0,0.0,26.0,0.0,1.0,0.0,GBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +617,0.0,88.0,1.0,87.0,0.0,0.0,0.0,0.0,CBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +618,0.0,41.0,0.0,0.0,0.0,41.0,1.0,0.0,GFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +619,0.0,27.0,27.0,0.0,0.0,0.0,0.0,0.0,CBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +620,1.0,0.0,20.0,20.0,0.0,0.0,0.0,0.0,ADCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +621,0.0,0.0,1.0,24.0,24.0,0.0,0.0,0.0,CEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +622,1.0,0.0,0.0,0.0,55.0,55.0,0.0,0.0,AEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +623,1.0,0.0,0.0,0.0,26.0,0.0,26.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +624,0.0,0.0,15.0,0.0,0.0,0.0,0.0,13.0,CCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +625,0.0,0.0,1.0,67.0,67.0,0.0,0.0,0.0,CDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +626,0.0,0.0,65.0,0.0,0.0,1.0,0.0,64.0,FCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +627,0.0,0.0,0.0,0.0,89.0,1.0,90.0,0.0,FGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +628,0.0,0.0,0.0,0.0,1.0,0.0,51.0,0.0,EGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +629,0.0,0.0,41.0,0.0,0.0,40.0,0.0,0.0,CFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +630,0.0,0.0,93.0,0.0,0.0,0.0,1.0,0.0,GCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +631,0.0,53.0,1.0,0.0,0.0,53.0,0.0,0.0,CBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +632,0.0,0.0,0.0,14.0,0.0,0.0,0.0,15.0,HHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +633,0.0,29.0,0.0,0.0,0.0,0.0,28.0,0.0,BGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +634,0.0,66.0,0.0,0.0,0.0,1.0,66.0,0.0,FGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +635,0.0,0.0,62.0,62.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +636,0.0,31.0,32.0,0.0,1.0,0.0,0.0,0.0,ECBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +637,0.0,0.0,0.0,0.0,0.0,0.0,48.0,49.0,HGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +638,1.0,0.0,0.0,0.0,0.0,0.0,54.0,53.0,AGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +639,59.0,0.0,1.0,0.0,59.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +640,0.0,0.0,0.0,0.0,1.0,0.0,27.0,27.0,EGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +641,0.0,0.0,0.0,23.0,24.0,0.0,0.0,0.0,EDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +642,0.0,0.0,0.0,91.0,0.0,0.0,91.0,0.0,DGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +643,0.0,0.0,0.0,0.0,48.0,49.0,0.0,1.0,HFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +644,14.0,0.0,0.0,0.0,0.0,14.0,1.0,0.0,GAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +645,0.0,96.0,0.0,0.0,1.0,0.0,0.0,96.0,EHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +646,0.0,0.0,0.0,50.0,48.0,0.0,0.0,0.0,DDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +647,0.0,0.0,0.0,99.0,0.0,99.0,0.0,0.0,FDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +648,49.0,0.0,1.0,0.0,0.0,0.0,0.0,48.0,CAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +649,0.0,0.0,52.0,0.0,1.0,0.0,53.0,0.0,EGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True 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+667,1.0,147.0,0.0,0.0,0.0,0.0,0.0,0.0,ABBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +668,0.0,0.0,97.0,0.0,97.0,0.0,0.0,1.0,HCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +669,0.0,0.0,1.0,0.0,0.0,0.0,53.0,52.0,CGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +670,0.0,0.0,94.0,0.0,96.0,0.0,0.0,0.0,EECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +671,99.0,0.0,1.0,0.0,98.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +672,68.0,0.0,0.0,0.0,0.0,0.0,67.0,1.0,HAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGA,True +673,0.0,0.0,0.0,26.0,27.0,0.0,1.0,0.0,GEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +674,31.0,0.0,0.0,0.0,32.0,0.0,0.0,1.0,HEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +675,0.0,0.0,0.0,0.0,42.0,0.0,41.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +676,0.0,0.0,50.0,0.0,0.0,0.0,1.0,50.0,GCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +677,0.0,25.0,0.0,24.0,0.0,0.0,0.0,0.0,BBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +678,0.0,0.0,0.0,0.0,1.0,10.0,9.0,0.0,EFGFGFGFGFGFGFGFGFGF,True +679,65.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,DAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +680,0.0,23.0,0.0,0.0,0.0,0.0,23.0,1.0,HGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +681,0.0,1.0,58.0,0.0,0.0,0.0,57.0,0.0,BCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +682,0.0,0.0,0.0,0.0,0.0,68.0,1.0,68.0,GFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +683,0.0,0.0,0.0,0.0,96.0,0.0,96.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +684,1.0,0.0,0.0,0.0,66.0,0.0,66.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +685,0.0,0.0,0.0,0.0,0.0,1.0,0.0,21.0,FHHHHHHHHHHHHHHHHHHHHH,True +686,0.0,88.0,0.0,87.0,0.0,0.0,0.0,0.0,BDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +687,0.0,0.0,19.0,19.0,0.0,0.0,1.0,0.0,GDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +688,0.0,42.0,1.0,0.0,41.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +689,0.0,0.0,0.0,0.0,0.0,60.0,61.0,0.0,GGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +690,0.0,23.0,23.0,0.0,0.0,0.0,1.0,0.0,GBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +691,86.0,86.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +692,35.0,35.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +693,57.0,0.0,0.0,0.0,0.0,58.0,1.0,0.0,GFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +694,0.0,0.0,30.0,30.0,1.0,0.0,0.0,0.0,EDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +695,19.0,18.0,0.0,1.0,0.0,0.0,0.0,0.0,DABABABABABABABABABABABABABABABABABABA,True +696,0.0,0.0,0.0,1.0,0.0,56.0,0.0,57.0,DHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +697,10.0,0.0,1.0,0.0,0.0,0.0,0.0,11.0,CHAHAHAHAHAHAHAHAHAHAH,True +698,0.0,0.0,89.0,0.0,88.0,0.0,1.0,0.0,GCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +699,0.0,0.0,87.0,0.0,86.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +700,17.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAA,True +701,0.0,0.0,66.0,65.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +702,0.0,0.0,1.0,0.0,0.0,0.0,123.0,0.0,CGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +703,0.0,118.0,0.0,0.0,1.0,0.0,0.0,0.0,EBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +704,0.0,0.0,0.0,0.0,0.0,0.0,0.0,132.0,HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +705,0.0,0.0,0.0,0.0,0.0,23.0,1.0,23.0,GHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +706,0.0,0.0,0.0,0.0,6.0,5.0,0.0,0.0,EFEFEFEFEFE,True +707,18.0,0.0,0.0,16.0,0.0,0.0,0.0,0.0,AADADADADADADADADADADADADADADADADA,True +708,0.0,72.0,0.0,0.0,0.0,71.0,0.0,1.0,HBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +709,0.0,0.0,54.0,0.0,0.0,1.0,0.0,55.0,FHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +710,0.0,1.0,87.0,0.0,87.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +711,0.0,0.0,1.0,63.0,0.0,0.0,0.0,64.0,CHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +712,78.0,0.0,78.0,0.0,0.0,1.0,0.0,0.0,FCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +713,0.0,80.0,0.0,0.0,0.0,81.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +714,0.0,1.0,0.0,0.0,0.0,0.0,40.0,39.0,BGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +715,0.0,0.0,7.0,0.0,6.0,0.0,0.0,0.0,CCECECECECECE,True +716,35.0,0.0,0.0,0.0,0.0,0.0,0.0,33.0,AAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +717,0.0,0.0,0.0,1.0,73.0,0.0,0.0,72.0,DEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +718,0.0,0.0,90.0,0.0,0.0,1.0,89.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +719,1.0,0.0,0.0,67.0,0.0,0.0,0.0,66.0,ADHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +720,56.0,0.0,0.0,0.0,56.0,0.0,1.0,0.0,GAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +721,0.0,0.0,0.0,1.0,0.0,0.0,49.0,49.0,DHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +722,0.0,0.0,0.0,117.0,0.0,1.0,0.0,0.0,FDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +723,0.0,0.0,86.0,1.0,0.0,0.0,85.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +724,0.0,0.0,31.0,0.0,0.0,0.0,0.0,30.0,CCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +725,1.0,0.0,0.0,0.0,98.0,0.0,98.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +726,1.0,84.0,84.0,0.0,0.0,0.0,0.0,0.0,ACBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +727,0.0,56.0,56.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +728,0.0,1.0,0.0,24.0,24.0,0.0,0.0,0.0,BDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +729,37.0,0.0,0.0,0.0,0.0,37.0,0.0,0.0,FAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +730,0.0,0.0,91.0,0.0,0.0,0.0,91.0,0.0,GCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True 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+772,0.0,68.0,0.0,0.0,0.0,0.0,0.0,67.0,BBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +773,60.0,1.0,0.0,0.0,0.0,61.0,0.0,0.0,BFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +774,0.0,1.0,0.0,57.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +775,0.0,78.0,0.0,0.0,1.0,0.0,0.0,0.0,EBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +776,1.0,0.0,0.0,0.0,0.0,96.0,96.0,0.0,AGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +777,43.0,0.0,0.0,0.0,0.0,1.0,44.0,0.0,FGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True 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+989,93.0,0.0,92.0,0.0,0.0,0.0,0.0,1.0,HACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +990,0.0,1.0,0.0,0.0,60.0,0.0,0.0,61.0,BHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +991,0.0,1.0,0.0,0.0,0.0,0.0,32.0,32.0,BHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +992,0.0,0.0,34.0,35.0,0.0,0.0,1.0,0.0,GDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +993,0.0,0.0,0.0,0.0,54.0,0.0,54.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +994,0.0,0.0,0.0,1.0,0.0,39.0,0.0,38.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +995,0.0,0.0,0.0,0.0,99.0,98.0,0.0,1.0,HEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +996,86.0,1.0,0.0,0.0,0.0,86.0,0.0,0.0,BFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +997,0.0,76.0,77.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +998,0.0,0.0,19.0,0.0,0.0,0.0,0.0,1.0,HCCCCCCCCCCCCCCCCCCC,True +999,0.0,0.0,37.0,1.0,0.0,0.0,38.0,0.0,DGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True diff --git a/tests/results/nb_gm_001_3back.csv b/tests/results/nb_gm_001_3back.csv new file mode 100644 index 0000000..b2f89a4 --- /dev/null +++ b/tests/results/nb_gm_001_3back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,0.0,65.0,132.0,0.0,0.0,0.0,0.0,1.0,HCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCC,True +1,51.0,0.0,52.0,52.0,0.0,0.0,0.0,1.0,HCDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACD,True +2,0.0,61.0,0.0,62.0,0.0,0.0,61.0,1.0,HDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGD,True +3,40.0,0.0,0.0,1.0,0.0,0.0,0.0,80.0,DHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHA,True +4,4.0,0.0,1.0,0.0,0.0,6.0,0.0,0.0,CAFFAFFAFFA,True 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+401,0.0,55.0,55.0,0.0,0.0,1.0,54.0,0.0,FCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCB,True +402,47.0,0.0,0.0,0.0,1.0,47.0,0.0,47.0,EAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFH,True +403,56.0,0.0,0.0,0.0,58.0,0.0,0.0,56.0,EEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAE,True +404,0.0,39.0,0.0,0.0,39.0,1.0,40.0,0.0,FGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEG,True 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+3,12.0,15.0,11.0,20.0,13.0,17.0,17.0,22.0,AFAHGHGHGBEBCDDDDHHHABCEHEHEBBBAHADADCFHHHHHFEFCBDDFDGDEFCAGGFEFBDGEHECCBCFFFFFFHGEBBHHCBCACHHDDBFGGGGEGEAFDGDADGDGDGBEBAAHDDFH,False +4,4.0,4.0,8.0,8.0,5.0,7.0,4.0,2.0,FGDGECDCECGCDADAHFDFCFCGAFCDDDABEBHBEFEFBC,False +5,15.0,15.0,15.0,16.0,16.0,14.0,9.0,13.0,HGDGBFDHDADHBBBBBHBAAGBCEABCGFAFAFBGBCBFGDDDEAAAHDFACECECHFHFHFCFHEGEFEFDFDAAHDEECDABFCCCCGBEBDAHCECHCHEDEDEDAGEE,False +6,17.0,17.0,9.0,6.0,15.0,13.0,15.0,12.0,BEBEBHAGCFEHHABAHDEDGHFBFGFCAABAGFFFAFGECEBEAEAFBFCEBEGHGDBEFABABEGEHEHBGBGDADACAGHGHGBGBACGCAHFFBHAECDC,False +7,12.0,7.0,7.0,6.0,9.0,8.0,5.0,6.0,CEGBFEFEFEHCCDEBCCHBBBGAHACBGGDBDADACADHDHFEAEAEFGFAAEAHAFAF,False +8,9.0,13.0,10.0,11.0,12.0,15.0,11.0,12.0,CGCFDBDFHHEHFFGCDHEHCFCFAAEGDCEGHGCFCBBBCBGFGHGDFDBDADHBBEGAGABABHBEBEHGHADAFEFCFDBDEFEHEFEFA,False +9,13.0,26.0,23.0,14.0,20.0,18.0,19.0,27.0,HECEBEFFHFDCCFGBCBDBAHGHGCBBABHEFAFEBEBHBHGGCHBGGCCCCCFCBDDDEDHDEEEAAFAFGFDFCGBGHEHDHGHAFABCGGEHEHFBGBADEBEBEAAHBDCCFGGHHHBHBHGHBDBEEAEGCGCBCHCEFFFFCHDHCHDHABCB,False +10,14.0,18.0,15.0,13.0,15.0,19.0,18.0,11.0,AFACABDDFBBBEBECECGHFBFBECDCEEEDGDBHHGCBDDAFCBAAAGHCHCHEAFBFDHAHCFFAAAHBBBFBFBHGFBCBCFGGGHGDGDFEGEFCFEDGDGAGEGCGEGEFEFAFDGC,False +11,21.0,20.0,21.0,13.0,15.0,26.0,21.0,21.0,EECEFFHGCADHGEGEABCCFDEBABEBGGCACHFHFBFBFBAHGBGCGHDCDABHHAGABFHEBCFEGDFDFDFAFBCBCAHACFGFBFBFBFBDACCBCHFHEGEDFDFCAAAGGEBFAAACACHCHFGFBFGHGHAEAGCCEDDFHHHGHGHGDE,False +12,17.0,26.0,17.0,23.0,17.0,11.0,26.0,21.0,ABGCACGDDFHFHBCEHEAGBGBEBAHEBEBFAAHAFBCEGDGBAHGGGGFGDDDBABABHGGGCGDGHGHDACAEDEFECHGEGDABGCHCDDDDCBCBADAHCHGBGBGEHDCDBBFBABHBHBFBACHDEEHGHECDCDHDEFEDECFGHGBFBD,False +13,24.0,21.0,23.0,20.0,15.0,14.0,30.0,24.0,AHHHHAFEDHAFBFGFCFGADADCDGBBBBGDGEGBCBHGGGGCGFBFAGGGGHEEFEGHGHABCBFHGAGACBBDEDHDHDGBCACAHGCACEHECACHBHDCGCECADGDGDABADHFGCGAGAHHBGFDCHBHCAAABEEFDFDBDBEADAHGEGEHECCCBCFCAHD,False +14,1.0,0.0,2.0,1.0,1.0,1.0,2.0,2.0,DECGCGAHFH,True +15,7.0,7.0,10.0,5.0,8.0,4.0,8.0,9.0,HBABHHEEGAGAGEGHCDEECHCHGBCBCDDAEGCBCGEAEFDFBFBFAGCHCHCHAD,False +16,14.0,19.0,14.0,7.0,10.0,15.0,19.0,7.0,CEAFFGHGEGFDFDCACAGBDEAFCEDDFAHHFDFGBEACGCGBGAFECECFGHCEBAFGEGCBABEBHBHBACAGAGDGHBABCBCBGFGFGFGBBBBFBCBGA,False +17,17.0,15.0,14.0,12.0,10.0,9.0,17.0,6.0,EBACADACGBGBAFGHGHADCDGAAFFFADABAHGDGABBCBCACACECHFBFHDCACDGEBADDEGGGEDADFGFGCGFBBABCBEBDBCHGEGEGECE,False +18,14.0,22.0,17.0,9.0,14.0,10.0,25.0,20.0,EHCHAHEHAHCHCGBGCGCGAEBFBFGGCEFGBGHAHCBABABHHGHGCACHDEDBBABGGDGDEBBBHHGCAEGBFHGEGEGBCCGCDFBBGBFBDAEEHHHCFEFECEHGCGCBHDADFDAGAGAGFBB,False +19,13.0,27.0,12.0,18.0,19.0,17.0,20.0,18.0,BFGCGBHAHAHEFEDBABEBEDADGGGGBAFCGEBDFHBHGHGCBBEGEGBHDHDHBCBCACDBFHHCHBGAGAGEDADADCDCACGHEEEEBDFDFDHDCGGBGDEBBBABEHFHGEFFFBADHEFFCFDEBEBFFEBHBFBG,False +20,11.0,10.0,7.0,8.0,8.0,7.0,11.0,4.0,BGBABGHGCGFBFAEBGGEDEFAHEHACDCDADBGGAGAGADFBFBCBCEFBFDHDACCDAGAEEE,False +21,22.0,20.0,18.0,24.0,13.0,11.0,16.0,21.0,DADADHCACFCHEDAAAHGDDHAGCDEDEGBHAHBDBDBGHHHCHCECAAAEFEDECEDBHFABGBCAGDBEGEBABHFCBBABDFDGHGCBFBCCDHDHDGDHDHCHBGADAFACHEHBDCDAFAFAFAGGCGCFHGBDBEBEG,False +22,8.0,10.0,11.0,7.0,8.0,15.0,4.0,11.0,CBAEGDGEHEBGBFBFBDHCHFHBAEHFFGFCFBFCFEEHABECFFFFACAEHHDCDCDHDHAHCFCBCBAADF,False +23,32.0,19.0,21.0,23.0,13.0,27.0,21.0,27.0,GHCABDGDFFFAHHHEAEHGAGAGHEFEGBCFAFBFGCHCHFHBGCAFFDFDBACACHCHCHBFGFEACAFABEBEBHHGHFHAHGGAGAHAFCGDHDHAFGCBCHDAAAAAAFCFHGEFFBEBEDDDFDBCBDDDCGFAFADBDBEBCAGGHDFDFBCDEAGAHCCEHGHAHCDDDDABAFA,False +24,26.0,30.0,18.0,21.0,29.0,16.0,21.0,21.0,GDGDADAGAGDEHCDBDHAHEHFHAHAFBHBHGCEBHBDBHBHBEEABABABAEECEGEGAGADHDBEEGBCAADHGBFBCEAAHDEBEBFBFBFCCGCEFBABAEDBGFGBGCFCGEACDFEFBHDADFHCEAEBDHDCGBEFGCDCACDEBEGAGAEAEFDFBBEHEGEGHCACEFBHDH,False +25,17.0,15.0,10.0,21.0,16.0,11.0,16.0,22.0,BDBDBHHHAAGAEHEHCHCDADEBGHDAGEBHGAABADADEDECEHAHFBGCGBEHCGADFBHECGHHFFFHFBDDDDDFDFDFHFEDEDACAEAEBDCHHBFBABCBGDGEAECHHGHGEGHDAGGG,False +26,12.0,13.0,16.0,11.0,17.0,10.0,17.0,12.0,GEECBGFEEDHCEFGFEAEAHGEGEDDDHDCDCBHBCBCFCECEGAGAGAHECFCEAAFGFGCEHGHBBBGBGBCBDHEAEFHFHGBCDGGACHCGCDADAEBFBADH,False +27,14.0,11.0,17.0,13.0,14.0,21.0,16.0,19.0,AAECGGEGHCACACACHBHADCECBDHDHDFCFGHGDDEDHHHAHDFDACHBHAFBHHAEEECGGFGEGEBEFCFAEAEFFBFBFDGDGDGHFACCDFHFCGBBHBCGGFGEHEFFFFHFCBCAF,False +28,14.0,15.0,12.0,21.0,15.0,9.0,13.0,21.0,GGHGEDHFCFCACBCADAEEEEAHDGAGHGHEHEHBBECEDBBBDBEGDGBAEABCCABBECDDDFDFHGHGHDHGHGHDADHHCHBHCCBAFHFDDDEDHFHAABDFDFEGEAADBDCH,False +29,18.0,19.0,27.0,26.0,29.0,30.0,16.0,16.0,DEFFFAFAGDGEEBFBFGEBADACADFDCEEDEDFDCDEBBGDGHGHGFFFDFBEBEHCHFDCDCEGFGFHFEFCGBBDCHCGCDADEGEGCFAAEHEHFDACGCEABBDECBCBCEFEFBFCFCFEHEHDGACEBAGCEFEBACCCAEDHDHBCFCDEFFHDHDHDCFCAAAEBEBFDHA,False +30,5.0,11.0,5.0,8.0,3.0,2.0,5.0,1.0,BBFGGBABFGCCCDADAHBEDCDBABGEAECBDBDBDBDG,True +31,28.0,17.0,19.0,16.0,18.0,11.0,17.0,33.0,DHAFAHAEAHDHFHFAFADHCGGGDGDGHEBDHCHBHAEBCBCFEGHHHBHCAFDHEHEHCDAGBCBAAAGACCBCAFGBHEHBBEAHAHAFAEACGGEHAFABEDEDFDCGHEBGAGEEAEBBHDEDECHCGABHGHAHAHBHCHCHCHDGACACDFD,False +32,5.0,10.0,12.0,17.0,19.0,17.0,17.0,11.0,EEBHBFFFDDEDCCAGEFEGGDGDFFGEGEAEDEFCFCGCGCGFAEGECDHHCEFDDHDFDABFDECECEHEFDDGDGBBFBFHHGCECEFEHAHDHDGBBFBGHGBG,False +33,4.0,13.0,10.0,7.0,4.0,8.0,11.0,7.0,CGBHBCBCBHFHFECBADGBGBGBDBCFAGDBHGFGECEHBGBCCACFGFGFGDDDFCADHEHB,False +34,22.0,27.0,22.0,21.0,21.0,28.0,21.0,21.0,BABFBCCCCGCDCAGABAHFBAHCBDBDHDCDCDEFFHBHBCBCBEHDAGAEFBBEEEBEGAGHGDGCGEBFBDEAECCFCFGDGDGHBHAEFFFECCADHFFBGHDHEGAAEDEFEFCDCDCDEFCHADAEHFDFHBBEBEBFBFAFGFAAHGHGFFAFGGBABGHGBFBFDFHCHAHEGDA,False +35,24.0,23.0,21.0,17.0,28.0,15.0,20.0,21.0,EGHGAGEGCGDFFCEEEEEAHGEGFGFBCBGBDBACHCAGDDDDEDEHACGCECAFAFEFHCHCEFHDHEHBAEADBDBAFCHCEEEEHBHBECEAEAFGGGGCCHBHAAACABBEHFHBDFHHDHBGCAABEBGAGABBFADADEBBBBCDCACFGFHDCEHEBGADE,False +36,16.0,12.0,18.0,16.0,29.0,20.0,25.0,11.0,EEEBCFFDHDBBGHGHGEFDFACCCFCGAECECEAGFFFCFDAHAEEHGGGBGBGADDGDGEGCCBFEHEGEHACDGDGCCCFCEAFAEGEGBGFGBBBHFGDGFGAAHADADCEEEEDEAEFEAEBFFFHEGECEGEHECAFDDDB,False +37,1.0,6.0,2.0,11.0,2.0,11.0,4.0,7.0,DBFFFHHADFFEFBDBFBGDFFEBHBHFHGDGDGCCDDDDHDHF,True +38,11.0,12.0,15.0,5.0,3.0,15.0,15.0,13.0,HCCCCAEBGFCFBGAHHHHBAFGCGCGCGFGCAABFBABHBFBCAFHFAFGCDBGBGAGFCBBAADHDHDCGEGHGCGFFHFHDEFHFC,False +39,33.0,14.0,21.0,23.0,21.0,18.0,25.0,28.0,DHAHAHADGDAFAFGCHCHEHCHABACEDDDCGBHAEFFGCADADGBGCFFFGGHBAAFGGHFHFHECFCHCHBDEFGADDCGGGHEBEDEBEBEDFHCAAAACFGFBFBFADAEGBDCAGACACAFGEEECDDDDCGGGEEEEEGCADHHHHAHABAHGBBCACHEGGHDADADAHAHEHAH,False +40,9.0,21.0,8.0,6.0,13.0,11.0,9.0,15.0,HEBEGEGAGEBBBHFAFABCBCBEBCBEAFHGGGHEHCHBEDFFAFAHDBFBFBEBDFHHDHBHCHBHBDEFABGBCEDEBCACHHEAGBGF,False +41,13.0,18.0,18.0,16.0,8.0,20.0,16.0,13.0,AGDGBCDHFADAGFFFHHCFCFEBGBGFGFGCGCHHHHCGFBFGDHABCBCGDGECEFBFCACBDBDCFAFBDEDCFFBHGHBEBABDFDFDHDHACABDBAFAFDHEGACACBEECGCBDG,False +42,21.0,15.0,14.0,22.0,14.0,22.0,16.0,21.0,ACFDFDEDFDBAFDCDCDFFFFFACHCHGEDFCFEHADACEHEDEBAFAGGHGEDADFDHDHDHGADAGCCCFHBDBGBDEGEBHGFGHAHFBFBFEAABABACDDAHHGFGBGEGHFEABHBFEHHHGDFDCACABABGECHAH,False +43,17.0,19.0,23.0,19.0,19.0,21.0,20.0,22.0,GDGFGEDDDDDDFDFDFEHBHDGAECBHDEGHGEEDEBEDECGGAADAFAFADECFCDGDGFBHGCBHBACAGACFCGGGBGCHFHEHECECAHFHFGCGHBFCGCBCFEHEGEHBBAAABDHFBCCCCFFFHFCABFBHBHBEDAFEHBHACABECHCH,False +44,2.0,1.0,3.0,4.0,5.0,3.0,6.0,5.0,CHCHFGBGEHFDAGADEDEGGFGEDEHCH,True +45,17.0,20.0,26.0,20.0,18.0,24.0,15.0,12.0,BDEFBBBHHECFCFCBBFEDDADADGECEHEFCGCAFDCGCFFEDDGGHHHHHAFAFEFAFDFDFDEDFAACFCFCDCBBBCGCGDGDFCGCGBDCACBHDHEECBBEBECFCHGBGEGABCDCEFHFGACDFAFAECEBEBDACABAGFBA,False +46,5.0,7.0,11.0,5.0,5.0,3.0,8.0,10.0,CBDHFHCDCEGEHCHCHCHEGCGCGBBBBADAHGDGBACGEAHBHFGFCECAHD,False +47,5.0,4.0,4.0,5.0,0.0,1.0,5.0,3.0,ACABGBHBHBGDCACHCDAGFGAGDDD,True +48,21.0,22.0,13.0,24.0,16.0,18.0,24.0,19.0,DBDGAGBGFHFCABGFECEGBGHHEACDFDGCGBEBGDAFAHADADAHHBHBHAGABADEBFDGDBDGDGCFAFAFDDDDECGFEFEAHAHEHEHCBCDADGBFBFAEBCAHFHEDEGBBFDEHEBDHFGCGHGHGBGCDABCBDGHGBGDCEAFAF,False +49,5.0,12.0,11.0,8.0,8.0,7.0,11.0,9.0,FCFDGDHBEBECFBBHFCFCGDBCCCGCECECBDBGBEHDDBCAGAEHEDFDHGEGAHBHGAGAGFHBHBG,False +50,2.0,7.0,7.0,4.0,6.0,13.0,10.0,11.0,BBFEFEFHAHFDFGHEBABDFHBHEFGFGHEHGGGFDFEHCBGBFDFHFHCCGCGHGCCC,True +51,5.0,7.0,11.0,12.0,13.0,9.0,8.0,13.0,EFFBFDAAECCCHDHBHFEDBHBHDHDGGGGECDGHCFEFEDEDCDCDEDCCHFEFEGCGBHEHBHAHAGDFCEAEHB,False +52,15.0,6.0,11.0,6.0,11.0,16.0,3.0,8.0,BAEGCCEAHBFCCHFABEHEFDCHEBECACECEAFGFEFEFBFBFAFADADACACDFGFAFAFEFDAAHFDCAHHH,True +53,20.0,14.0,19.0,11.0,13.0,12.0,10.0,17.0,CHCECEHEGAHBFGHCHABCBCDCECEDAHACGCADDBBGFGFGFHAAACACFBEGGAGAEHCAAAFDFDCHBDBHGDFDHCBEFEBCBABHHHHDHCHDFEFABEBECAAAEACF,False +54,18.0,14.0,15.0,22.0,24.0,20.0,25.0,23.0,EGGCGCGDEDEBCBFDDDBFHDDGFBFEEEGDBDBEHFDFEACACADABEFDCECGGHBDCDBAGHGFBFECHCFEDEHEHAHEEAGCEEEEFGFHFAAGEEHHHHAHAHDEFGDGDBCGAGHFHFHAHAHDHDBFBFCEGGGGGGGHAADAGCDFFAHCB,False +55,3.0,4.0,2.0,5.0,2.0,5.0,3.0,1.0,EHAABABGBFDFGFGEDDFDCBCDF,True +56,9.0,9.0,8.0,11.0,11.0,13.0,8.0,11.0,ECFFFBCDEDAFEBEAFGFHFHFDEHEBEHEGBFEFHBABCCAGAGBGBDFHAHGHFCFDHDABADEDEDAHGGCDCHCD,False +57,10.0,13.0,10.0,15.0,7.0,9.0,16.0,11.0,HHCFEGEGEDFGABEHEADCHGHBDFDGDGHGCGBBDDCDCDBDBHCDEBAHACCFDGDFAFAFDDAGAGHGCGBGBHACBGBGAHEBFBF,False +58,15.0,15.0,14.0,21.0,27.0,24.0,20.0,28.0,FAFEFAADAGFBFACBCBHHCGFGFAFHCEGEGHHBDBFHFHBEGDGDAEEHEGCGDGHCDGDEHFHGCEEEGEGEDBDEEEEHHHHCHDAGFEBHFHAHFHFDDDCACHFBDDHDGDFDAGGEAEFBHEEEEBEHEFFCFCFDBHAFADCGCGFHDHEBABHB,False +59,11.0,16.0,18.0,17.0,22.0,31.0,15.0,17.0,FCECFCFCFBHCHBGBFHGEDADADEFEFHFDFDADEEADHGAEAECGDGCCFHFGFHFHFHFBFBFCEEEBEFFDEGGBHBEBHFCDDDDGHAFBFBFCACHCAFGCGHHEDCBFEFABCDCEGGGDAEBBBEDEFFFFECGHEHF,False +60,11.0,9.0,7.0,2.0,10.0,10.0,11.0,9.0,HGHCDCHCACBCEGEGEGEBBHCFGABEBFAEHHFBFAAGHGHFHABABCGEGFDEAAABFEFEFGFGA,False +61,23.0,23.0,21.0,24.0,24.0,17.0,27.0,24.0,EDGGCBCFCGCGCFCGCDCBAACHFHFHECACAGAHFHDBDEHAGADHGEGEBCAEAGDHAADDDDCEAEADBGFDBBBBDHDGDBBGCAAEHEGDGBGBFHCGCDBBBEFHFDAGHCDCHFHFGEHEGEGHGBEFACADAFCBGBGBFHDEDEDFBFEGHGHAHAEEEEGEDHAHACEFBHB,False +62,21.0,13.0,9.0,12.0,17.0,15.0,25.0,10.0,HFGFGBGEDEHGHAHFHGAAAFGHBFACGDBEBGAAFEGEFEFBGAHDEDECBCBFBEGAGAFCCBBDBAGABAGGGGGECDADAGAEFEDGACADDCDHDEAFHFHFGGGFGCABAEEEGE,False +63,6.0,6.0,3.0,12.0,7.0,8.0,6.0,13.0,FHEBEBHGHDAGHDCDEDEAFCFCHEEBAAFDDDFDHDAGBGFDHGHAHDHEHFHFHBDBG,False +64,6.0,15.0,15.0,8.0,14.0,13.0,8.0,8.0,CCEDEDBHHGDCBEFEFCCGCEAGFGEGECAHAHGBCFHACEBEBEGEFFFFBDBFBHBDDEDCBCBHBFGFHEAEBCBCFCBCAFD,False +65,6.0,4.0,3.0,4.0,6.0,8.0,5.0,5.0,CGCFEFAFAEEDEHCHBBDAAFAGHEHEBFDHDBAGFGFGF,False +66,17.0,8.0,15.0,6.0,16.0,16.0,11.0,12.0,AFGFGFGHGFECECECHAECCCFAHAFAEHGGCEBAFAEAEFGGHCBFAAEHFHFGBHEHGAFBFHCECEADFDBDBCACACAEAEBEDDACBDFHFHEGC,False +67,24.0,12.0,23.0,14.0,18.0,18.0,15.0,12.0,CCCFCFBHAEEDFDBAADAEAEABDBDGEHEGCCCACECHGEGEDECACFCFCHBFBAGAFFGHADBEBAAAAFAEECEDHDHECGGBHHCHDBGBABAGEFFGFAFADACADAGADCHFECGFGFHFCDCEGFCC,False +68,31.0,17.0,27.0,38.0,29.0,28.0,14.0,16.0,ACACBCFDGBHBDEGEAHDDEFEFEFEFDDHECEBDFDAEAEFECECGCHAHAHCBCDAHBDDDDEDEBEHGDDAFEFCFDDBCGAGACCECAADADABAFEDACGCAFAHDFDBDGCECBGBFFCHCGAEDFFFHADFDADGFAFADEDHABAGAGEHEFBFECEDEDCGEADADFDHBHDFDCBCFCDAFAECFCEHB,False +69,5.0,4.0,3.0,4.0,2.0,3.0,6.0,4.0,DAHAGAHAHAHFGCGEBDFDEDGGCFBBGBC,False +70,5.0,7.0,9.0,5.0,2.0,11.0,6.0,10.0,HAHDHDHBGBFCACDCHFBBHBHGDEACACEGFCDHBGFGFGFCCHBFFHFCFAF,True +71,11.0,10.0,6.0,19.0,14.0,23.0,11.0,9.0,FHFEADABECHFFDFDFHFEDECEFEFEFAFHDADAEADDCAGFGBBHGDGABDDFFFFDDDADEEGFGDABCDGGBHDHFGAGBHBHBEBEGFFFFFCCEDE,False +72,25.0,17.0,20.0,19.0,16.0,13.0,17.0,22.0,GDCDHGBEAEGDGEBDBDHDCDCBHDEAEHDCEFAAABCDCDABAGADADCFAFCGCACAFFBAHGCGCGEGEACHHECACECEHEGGFBDHFHAHAHGGDGFCECHFHFHCHFABABFDGABDEDABABHEACAFDHHGHAHBBBBEH,False +73,15.0,19.0,20.0,23.0,23.0,21.0,22.0,23.0,GFGFECGCEEGHFCBCFDDDHHGBGHGHDCDCFHAHCCCFHAADEBEHEDEDADCDCABEGEFDFHCHGGAHAHFCFCEADFFECGBDBDBDCCACADHGCGEGHFHGHGBFADEBEBEDGDBBACEEEHGBDBFFFFDGEGDGDGFBEHHHHAAEAEFBBBBEFH,False +74,3.0,11.0,6.0,11.0,10.0,12.0,5.0,7.0,ECHFHDHEFFHHDCFGEGFDBEBEFFFDBCBFEDCDCFEBBFADDBDBGBGBGBAHAHFDEDECE,True +75,21.0,13.0,22.0,19.0,30.0,19.0,18.0,19.0,HAHEEEFEDHDFDBHBGCCEEFEGGHGHCCCCCHGECEAHDBDBEFGHCACGBEFEHAFDFACAFEEEHABAGAFDGDADADAGBCBAEADAEFHCDCFGEHFHDEDCDFEFCCCEAEAEGGABFGEDBDBHBCCECEHEAEFGHGHDDAEAEHCFGFGFB,False +76,14.0,30.0,18.0,20.0,25.0,19.0,27.0,30.0,FCFBAEDEGEHEBGHGFEFCGDBDGGCGCGBEBHBHEAAAEECBCBCFHFCFDGAEHHFGGGGGHCHEHBABGBGHHDFAEBDBDBDBCCHAGGEGDGCCBCHFGFGHGHBHEFGHBFBCBHEHBBABCBHBCGEHEADDDBHFHAADEDBFHFEEGEDHDHDEDBDFEFEHCHAEGDHBFBA,False +77,25.0,17.0,30.0,29.0,22.0,22.0,23.0,24.0,CCHEAEHBBCBDADBDBDHGFEECBDFGFEAHDCGCDHHEHEHCGCFHGDGAGAGACACDDDFDFDGECCHDHCCEFAFEBAFGGHDCCGEDBDBDBCHCACDBAHCGCGAHAHAFFFHADCDCFCFHHCDCAEAGAGAGABFHGEGBGDFHEBEFCFAGBEEAABAGDGDFDFEABHCDEDEHEHEFCFCD,False +78,9.0,16.0,9.0,5.0,4.0,15.0,4.0,5.0,BCEADCBBBBABABCCEHFBDHFAAGAGHCFCBCBFDFAGAGBFBDBABFFFFFCEHEBDHFFFBFC,True +79,19.0,17.0,10.0,29.0,13.0,8.0,14.0,14.0,DEDEAEAEDDDDDDDHDGEBEFADAGBFFHDGFBBBBGBABFCHGDFDEACBBBAHADAHCGCAHDHEHABAGCGCGEDAGBDAACAHDBCBGBGBEDDDDDADGDFDHHFDAHAEEEHCDCHG,False +80,9.0,11.0,7.0,9.0,14.0,3.0,11.0,16.0,HEHEACBHBHAGEBEAEBHBHBDEDCFABCGAEABHEHDADABABGGGDGHECEHHDGDHHCHCDGFFHCBEDEGEGHGE,False +81,4.0,9.0,4.0,9.0,3.0,6.0,6.0,5.0,BGBACACHDGDFDFBFEAHFBDDEDEGHGHBBBFBADHDGCGDBFC,False +82,11.0,21.0,22.0,24.0,26.0,28.0,21.0,21.0,EDGDCDCFGEDEFFFFGEEEDEDEDADACHCEBAFAFCHEDBFEDHDCCAHGFDFDGAGEFECEDBHCECDGGGGGBGFGBHCGDGFFDCAGDBCEHEGBBBBHFHADFHCHCHCACHCBBEFAGBGBEBFFFHFBCEDFFEFHDHFHFCCECBHBDBDEDEHBHEHFBFEGAG,False +83,2.0,4.0,1.0,3.0,2.0,4.0,2.0,1.0,CBFHFBBDGDFDFEGEABA,True +84,18.0,13.0,21.0,13.0,16.0,19.0,15.0,8.0,CBCEEADAFGDCFHFHDHFACACEDGACFGGGCBABDCCCCCCBABABABDBDFACGCGCFCAGEFEFBDBCFEFEAGFDBEFEHEHBAEADAFAFGEGECAHFEDGDHHCAEDEFCFGGGBF,False +85,14.0,12.0,10.0,10.0,16.0,19.0,9.0,12.0,FGBGHDEEEGBFAEAEDHGHGFEDEFEGEDEFEFCBAHCHCFBFDGECFFFGAECBBBDGFAFACACBEDABEBFHFHFHAHAHFEDCDCFCAAHBHADAFB,False +86,14.0,13.0,10.0,16.0,18.0,7.0,14.0,15.0,GGGGHADGCGCEEEDEDBAAGBCDAEABAGAFFFDBEFEAHAHBDBDBDBGHAACDHHGHGHDHEFBCDCHCHDEEBEBDADABEFECCGHGHFHDGEEEADBEEHC,False +87,9.0,13.0,17.0,12.0,12.0,23.0,13.0,12.0,EHCHBDDCECFCFCFABABGBFDFDCDHBGDHDGBGCGCGCFCDHEHEFCHGEAFBFBFDFHCEBAFEDEDFFGHCFGBGFGCDCEBGFHFAFBEEEBGFFCFAACAHAHF,False +88,6.0,3.0,0.0,1.0,3.0,3.0,5.0,4.0,GBGAGBHAGAGFEBEFEHHAHAFAD,True +89,11.0,11.0,12.0,15.0,16.0,12.0,7.0,10.0,BHBHDDADCGCAEHHDCEAFAFBFCDEDECBGFCECHAHGCAEDDBDEAFAFHFDCHEBEGEGADBDBHEHDFGFGFDECECECAAEBEBDBFF,False +90,18.0,21.0,18.0,8.0,15.0,18.0,18.0,10.0,BCBDGCBCHGHAAFAFEFAFDFHGGGCCECEHBHFCADAFAFEGBAAAGAFBEBEBEGCBHBFADAECDGHGBGECCBCBABHFFDCEFEHGBGBGBEFGABCBFBDBEEAHACGCGEGFCFCFDA,False +91,21.0,22.0,23.0,29.0,25.0,21.0,20.0,16.0,EDECECBBDBGGGDHDFCFDFAFGBACHDHDADFDHBEAACACACEDECEDGDGEGEGEDEAFCFEGGBEBGFGEDECGFAFAFGHEDFHFCFBFBDEDFDGBHEADHDCCFBABABACGEHAHFHCEGEGHBHDACADFCCHBHDCDCFBHAGDBABEBFBGCDBEBCDDADAEEC,False +92,22.0,26.0,23.0,24.0,20.0,30.0,22.0,18.0,ADAFEGHDHFFFFDFECADDDFHBHDCBFAHCHCACHEGFBFBCDHEFEGABAFAEBGBFFFBFCFGBHBEBAACAHAEDEDEGCDCDCDCGHACFCFHFHGCFCEHEHCGCDCEFGDGBGBGEGBABGBGCCABBBDBAFGDABFBFEFEDADBFEFDBHGHDFEFECBAGGCGADDDGBHAEA,False +93,2.0,2.0,1.0,3.0,0.0,2.0,1.0,2.0,DBDCDGFFAHAHB,True +94,18.0,8.0,12.0,13.0,10.0,9.0,12.0,11.0,HHFAEHCHCHCDDAFACACACGGFEFGCHDEEGCGCGFDDADGDFDEBHCDABGBABDGAGEEBAFABGBDAHAFAFADADEHHCHCBGEAEA,False +95,4.0,5.0,6.0,3.0,5.0,4.0,4.0,3.0,AHBFEADADAGFHFGGCBCBCBCFCEHEBDCEEG,False +96,6.0,10.0,15.0,4.0,14.0,9.0,14.0,11.0,ECECEGHGHEHGDACGHHHFGFGCCCGFEEHEAAACCHCFCFEGEDHFHFDFGEABBBBEBHGCGBEBGCACBEBEGCCDBFG,False +97,3.0,4.0,3.0,4.0,3.0,2.0,2.0,6.0,BGHFHDHDCDBDECAHAHAEGBFBHCE,False +98,14.0,9.0,9.0,12.0,16.0,15.0,11.0,5.0,BGGACFEGEGEAFGFGFGFAADADACBCFDADGEBHBFDFGBBDCGAFAEEFECHCDCBFEAEAEADADCEBDDHDBGEFCHEHEFEAEFF,False +99,24.0,22.0,16.0,19.0,18.0,22.0,22.0,17.0,BABDFDEDEDEHAACABAEAFFGBHFGAHDBCAGADEDCHBBGEGAGAGAGAGFGABEDEDEFCBABDBECECEAGFGEGBGACBFEHEHAHAFBFBCHEFGDADAEEBCBHHHFHFBAGGGFFFFGHDCCHAHBCBCHFGDBCCAFBDGGFDHDFDFDC,False +100,10.0,7.0,6.0,7.0,6.0,11.0,8.0,15.0,GGHGHGFEFDCHAHFHEHEBACCBCHFHFBCBEBFFEFHAHGHDAGADAEGBGHHBAAADCFHFDADFDH,False +101,21.0,23.0,9.0,23.0,25.0,21.0,22.0,21.0,EEEEEACAHEHDDADHFBFBAHGHGBGDGFECGBBBBFBFEFHFGFGFAEHDHAHAHBHGHFBBHGGGGGEHDDDDHEAFBHHDEFEHEDDGBCDCHBGDDFFCAHADEDEGEGEAABBEBDFGEBABCDFEACFDADAGAGEGBAFABHBDGDCEEEAFAFBFC,False +102,1.0,8.0,5.0,3.0,5.0,5.0,6.0,8.0,HCGCHDEBGFEFECBBBFBFGHGHGDGBAHCFCHHHEDEBB,False +103,29.0,22.0,27.0,17.0,23.0,16.0,31.0,26.0,GGHCFGEBEDGCCDEBFFFEFHGCDCBCBCECFCHCHCHGHCEGAGCECABHEEEBEBEGAGBBBABABFBHBHDHGGDADCCFAFEDECEABGBFAFHDAGHGHADEFGBDCHHDEDCHGABABFGDEAAAEBGAAEGGGGFGHAHDBDCCHGHBDGEGHGEAEACCHCACAHGHGHAHDCACAFAGAFA,False +104,7.0,6.0,18.0,7.0,11.0,12.0,24.0,18.0,GDGEHCGGGEFECEBECGCGHGCFHFHFHCDFDFGACHHHGBGHACDCGAGADBCAHECACGHGHBBCFGHEDEFEHGHBHGGCGCGCHCEGGDGEAFFHFCF,True +105,16.0,23.0,21.0,18.0,22.0,17.0,10.0,18.0,ACEGEHEHAFACDCDCHFBFBGBHDFFFCAGHBBBHBHFABABABAHEGCAEEEFGBGBADGEBCDEHEBCFCHBHEFEBDDDDDDDGFEDEFEHAHBCACACBDBDHDCBCEDEHEGCCFEEEDHHAABCFCHAECBCBFFCFG,False +106,9.0,10.0,12.0,6.0,8.0,7.0,13.0,7.0,FABABHCEGEGBGBGCCCHCAAABGEGDGFGFAFCBCGCEHDCCAGHDHCAEHFBFAGBGBGHFDCDBEEDE,False +107,17.0,15.0,17.0,17.0,16.0,26.0,15.0,17.0,EFBHGEAFDGCGFGFGDEEAEGBDEFBGGFAHHCAFAFHBHBDGDGEGEGDFFFDFHHHAHBCDADBCBFGFCBCBGBFEHADAHCECFCECHBFFFFCDEDEDCDEFEFCHHHCACAEBCGAAAAHADAFHFBDBCFDF,False +108,20.0,24.0,27.0,23.0,19.0,28.0,19.0,18.0,AFAEGFGFGAHFCFEHEGDBBBEBEBEBCDDDHDFGFDCDCECFAFAHAGBBBEBFDEBCBAHGFGAGABDBEAGFCCCBEBHCDBDFDFBBHCHGGCDCDFHEHECGCFFFADAHHHDCDAEEBFGAEHCDDGACACACFCBEFFHAGCCCCEFEFCABDBFFFGHCHDHDFDGBGA,False +109,9.0,16.0,17.0,17.0,16.0,16.0,12.0,24.0,EGDDDAHBEAEABDCEBFFHFHFHCDGHAHCCFDFDFDFBBEBFBFEHGHGDCFCGHGHGCBCEDHBCDHFHFBFGDGACCCGAEBHBABCHHEHBDDEHEDEDEGEAHDHCECFCFCBHAHEGBHH,False +110,5.0,7.0,7.0,3.0,11.0,14.0,10.0,14.0,AHEHDHGFEFGCHFGFBBCAEFEFEFECEHFHBHAHFCBGFABHBEDEGCGFDFACGCGBFEFGHHHHEHG,True +111,20.0,16.0,22.0,22.0,11.0,17.0,13.0,10.0,ACAFFCDCDCACBFAFGDAACDCDEDEFFCBHDGDCDGDEABFEAADDCAHHDHEGACEFBCBCACACABBHDHDHEHCAAFAFCDDEDFDFBFCFBFDEDFFGGAGCCBEBCBHBAGGGGGEGACBHBDB,False +112,26.0,22.0,28.0,29.0,20.0,26.0,21.0,19.0,GCDCBAEHEHGGFABGFFFFBDBDBHCHCHAAADGFCBCDCFFFDCHCECEDEAFBFEFEGGCDCDAEAECFCEEACCBABGFDABADAFHBHFEFEAHAEADFCFHHBHAHAGGDHCCCDHBCADABHBDCGHGAGAGDDDFCAGBCBDBCFCFEHEDEBGGFGFDBCGAGDCDEDGDBDBEFEHAFADD,False +113,4.0,0.0,3.0,3.0,1.0,0.0,3.0,3.0,HAHADDGDHAGAECCCG,True +114,15.0,25.0,14.0,19.0,17.0,16.0,17.0,18.0,GDGCHHEBEBHBEFAFEFBFHFBGHEFEFEBAAAGFGDDFDFDFDBDBDBABABDHCBGDHCEBBGBCBEBAGHCHBEBGHEHEHEACACACACBBGGFGHCHDGBCDGEFDFDBEHECDGBCEHAHDHACFGADFDBAGD,False +115,4.0,7.0,3.0,5.0,3.0,0.0,6.0,6.0,HGHBHBDBABACEGDGEAHBHADGEGCHCBDGDB,True +116,18.0,19.0,11.0,27.0,26.0,22.0,18.0,28.0,FDFEHEBGBGBCFDFDFBEGFABHCHEEFAFAFAFBDHEHEABBDCHCDDGEHEADAFAFBHHCHBFBEDHGHGBFDFGECHHABDEGECEDADEHEDCAHAGEBABCDCDAHEDEDEDFFFFFBFHGAFEGEGDHDHGHGHGEDHDGEGDAHABBHHDHBCDADHEGE,False +117,9.0,10.0,11.0,5.0,12.0,11.0,5.0,12.0,HFBFCFBAAEABGHCHAFABBBBCCCHCECECHCGEHEHEHFHAHCEDDFDCEEBFFFFGEBEAFAHDGBGDEHA,False +118,1.0,8.0,6.0,3.0,6.0,11.0,9.0,8.0,BEBFGFGFBFBGBCDFEHBHAGEFHGDEFBFHHCGCDBGFGFGHCHFHCECE,True +119,16.0,21.0,23.0,14.0,8.0,20.0,24.0,21.0,EEGFBBADAFCBHFACCCFCFEFDGAFHFDABHBCGHHHBHGHCHEGCAABBGDHBHBGFGCGCGCGHFEFCFGABAGGCGAGACFCBCBHBFCFADHDHGHGFDEBEGCGCDBHBEAACHDDFDCDCFBFBGGGGCBHDHDHFABA,False +120,23.0,16.0,16.0,25.0,12.0,20.0,24.0,21.0,DFHFBBDGFFEDCHEEGGGEEADAGAGDBDAABFDFCGDGAABABABABACAGGHDHFACECBDDFDHGHGHBCBCAGFGBGCFFFDFDCGHGDEEHBCDCBHBCFGFDFDHAGCHHHHHGAFADDHEHEAGAGAGHCBAEAEDCDADCFGFDHDHF,False +121,19.0,17.0,15.0,20.0,28.0,24.0,23.0,17.0,DCDFFGAAFFFBGAGDGCACHEHDADADFEHEGGFFEFAABBHGGGFHEHACACBEEEHBAGAGFDFEBEGEBECECDCHBHGDGBEFEAEAEAECCGCEHBHCFFGBDBDCDAEEEAEFFFBHAHGEDEBGFGFGHGBGBDFDCDHEHDDDEBAFDFEGCFH,False +122,24.0,21.0,31.0,19.0,20.0,33.0,21.0,17.0,CBDGEGCBFGFHFHFEFBDAECCCBCBGHDCCCAFADHDHDEDACBDBGAHABFDGEGCHEECECDAFBGBGBFFFFHEAECHFHFHGEEBCFCFDGEGFFFFGCDCGBGBGFFBFBFAAAAAFGBAFABECAGEGBGFHFCADDCECHFAFADAHFHEDEHCFBACAEAEFDCCCCCBCHDADCG,False +123,23.0,22.0,33.0,26.0,18.0,14.0,26.0,19.0,DGDGCACABHFCADADGHGEEHGACAHAGACEDEDEDGDFCHDECFCBCGHGECHCHBEEDEDEDEDCBGBGBABCBCBHAGDGECAGDCCCFCDCFHFDABECGBGFHBBFBEBEBACEDBHHCCGCDAGGGFCCCGDDFCBCBGBGHGHGCBADHFFAHDGAAAAABAFDHDHCFCEAD,False +124,14.0,14.0,13.0,14.0,9.0,17.0,19.0,18.0,DCBFBFAFAHBHGFBABECACGGBGCGCFAFHHDGDGEBDADFFHHHHDAABHFFEGAGFDBGHGAGBGHFHFGCHCDGEGEFCGDGDCDCDCECBFAFCFHAHEBEGHBEBHHADAD,False +125,22.0,17.0,18.0,14.0,19.0,23.0,19.0,20.0,AFFEGCACEHAHBHFHECADBDEDHDHDACHCBCBHFDDAGHGHCECEAEAHBHGGCEAFAFBDGFFFFBAGAFAFHHCGDFFAEBBABADADBCGHHHGACACFCFDFBCGHGEGEGBGBCBEEAFHEBBGGECEFECEHGGEAFDFDFAF,False +126,2.0,2.0,5.0,1.0,2.0,0.0,0.0,0.0,CBABCCCECEAD,True +127,9.0,13.0,13.0,20.0,8.0,15.0,15.0,18.0,GGEFDFEHDHDHBAGABBBFFHFCFHGHGHGHGDADHDEDFCEDAGAGCBDFDHDHCBCDFDBHFHGHFBCGDDDDDABGHDHCHAAECFBDBEBCBCEGECCFFHCGAGF,False +128,26.0,16.0,20.0,13.0,15.0,14.0,8.0,14.0,AFAFGCBFDCCGCBCACACAFACECBAFAFDBBABABHECBGAHADEDCBADABABAHEHCHCHGECDHDHBHBAEDEAEAHBGFAHBBCACACAFEDCAHHEADGEGECEFFFCGHDFDEAEFFD,False +129,3.0,2.0,3.0,1.0,2.0,1.0,0.0,1.0,AHABFBEAECCDC,True +130,3.0,10.0,5.0,11.0,10.0,4.0,3.0,9.0,DBGBHBAEDEBCCEBAAFHHDHDCBEDHBHBHBDECECEDDDFDGDFBEGEHEHF,True +131,18.0,19.0,23.0,22.0,20.0,20.0,15.0,23.0,FGBCAABCBCDCDCBBAAADCEGHAFDFEBHBHAHGDAEAEAHGECHCDDFDBEBHHHDBCFCABFHHHABFHHEGEHBAFAFCDCHGEGEFBFEFEDEHCHCHDHDGFAFEBEBGBGFCDCAEDEGFFFHFBEAGACFDDDDHDCCCCDCDGEGBGCEH,False +132,27.0,13.0,16.0,13.0,20.0,12.0,27.0,15.0,HAACDHGHEBFFCDAGADAEABAGHFHDHCCAEHFHBGBECGGGGAGABACDEDCACACFGFGFHBBEBHGGGDABGGGEDECEAEAEAFCEGBBBAGAEAEABHEAEGGGCEHFHDGAGEDEDFDHDEAAGAHAFFGCCCCG,False +133,5.0,7.0,9.0,1.0,6.0,7.0,8.0,7.0,BGCFEBHHHHACABFBFHFCFGGGCCECGCGCHAEBBHFGCGDAEAEBEF,False +134,14.0,15.0,11.0,16.0,21.0,17.0,16.0,20.0,HBHDHFHDDEFEGEFEBGDFDFBBHBAGEGCFHBHDADHHFAFAHECEFADECEDDDBDBDACBEAFHFHGEGCGDECECBAGACHBHGHFHFHGEGFFHEHCHCEGEGEAEGDGEABDBABFFGECABA,False +135,8.0,3.0,1.0,2.0,4.0,6.0,9.0,3.0,GFGEGHGFEFGCGDBAHAFDEAEGBGBAAAFAGAHF,True +136,14.0,29.0,20.0,23.0,25.0,22.0,18.0,18.0,DGDCEBGFHDBFBECHFEFBDEDCACGCGHEFEFEFAFGGGDCFGFHFHAHADEBBCBCEEEFEBABCBEBACACBHHCFCEAEAGBGDCDBDEDGBACECBHEHBDGDFDGCGAFEFDBHBEBEAHGFCFBFBHEDFDGDBBBBACDBDHGBEAEGFCHBHEHDHDFD,False +137,3.0,5.0,1.0,6.0,8.0,6.0,3.0,5.0,FDFDBBBEDEHEHEFEACFFGDHDFGBHAEAEBEGDH,True +138,17.0,19.0,28.0,23.0,19.0,29.0,14.0,27.0,EEHFCDHDHBAADFECECFFFCDGBAHAHFHBCDDFDGDADBCAAHABAEGFHFHDHDEGCGHGHCFDFEFGBHAHBCBABEEECDCDEHFHFBABHCCCACHEACHDGDFHFHBHFGDGDGDFBCDCGABFFDFECHCFFFHFCDGEFCACHCHCHEGACFCFBFEEECEBBBBD,False +139,18.0,10.0,15.0,7.0,19.0,9.0,15.0,15.0,BCDGAGEBBAAFCBEFDFHCAAHABFEADAHGCCCACEDEDEDEDEHCBCFEHCHEACACHGGGGBGEGFGFEHECGFEAHGHEHEHEHACAFBGGABABHGHEAEAC,False +140,12.0,11.0,10.0,15.0,15.0,9.0,10.0,21.0,GGDEDEDHDABGBDCAFADADEEFHFEEBBAHECFCAHGHGHEBBCBABAFHHHHAFADHECEGGBGECECHBHECFCDDDEEHHHHHDHDHDHFACGDABFG,False +141,6.0,7.0,16.0,10.0,19.0,4.0,7.0,3.0,GAGEECEDBGBGFCFCHCFBDBDECEAEDBDCHBEEFAHAEAEGCBCEADDDDEGCCEEEECCCECDCGCEE,True +142,17.0,14.0,17.0,18.0,21.0,18.0,15.0,9.0,BADAGADHDGDGFHFAFDFGEEDDDADCCCGGECCCGEHAHAHEEEEAECFCDHDFABABFBGBCACEFFDADAEEHBHFDFCBEBGHGCFCDAGFDBEFFGFGEGCBAEDEBCBAACDCBEBEFEFEG,False +143,1.0,3.0,4.0,4.0,2.0,3.0,3.0,3.0,DHDCCGCGAGHBBFEFCFDHDEB,False +144,3.0,1.0,7.0,1.0,1.0,3.0,7.0,2.0,CDCFHGGFBCCCCGAGAGAEHFGCG,True +145,3.0,5.0,7.0,4.0,3.0,11.0,6.0,3.0,DHGEGBGBGCCFDFAFHCBEBEBDFCFCFGFCCAHFFFDGAF,True +146,4.0,13.0,6.0,8.0,6.0,15.0,9.0,3.0,FABGBGFGFDBBBCGEEEEBFGCBFBDBCFDFGFGFAFECCDDADAFBDGHGBFBFHFEFHCBD,True +147,16.0,16.0,22.0,23.0,21.0,20.0,35.0,29.0,FBFEECGAGFGFGHDHDFAGEGEHFHFHFEGHGCEEAHDGDEHEGEFHFCFHGHBECDBDBHHGGGGGGCBHAHACAHAGEBDCEAGGHGHGEGEBDAHHHCHADGCFBFHGBGCHDFDFDGHCBCHHAGBEBDACHCFFGGGDADEEAGCEDEDCCCGDFDBDGFBFBGBDEACACDCDCH,False +148,16.0,20.0,20.0,23.0,21.0,16.0,31.0,18.0,EBEHGGGHCACFDDDDDAFCHEGCACFCFDFAGADEGGGAGEECEGEGEGAFFDCBHBHDHEGCDCGBGBGCCCCCBDGEBCGFHCHGHAHBBCEGEGEBFBGAHABDBDAGAGFGBEEEFEDGDAFCHBABGBADADEGFFDHDCFGGDHBFBDEDEDGHHHBH,False +149,3.0,7.0,4.0,6.0,10.0,7.0,3.0,5.0,EBEHEBEDCFCBBADCHFHFGBGBDEEEECHBDADADEFFFGFHE,False +150,6.0,2.0,7.0,6.0,2.0,3.0,8.0,0.0,DDDCGCADFDFGGGACACAGBECGGDGABACFCE,True +151,5.0,2.0,2.0,0.0,5.0,4.0,2.0,3.0,GAGAFBFEFECEFHABAEHEACH,True +152,14.0,12.0,9.0,7.0,12.0,11.0,10.0,17.0,FDHDFEHDHCFCBCDGHGCFFFBFHACCHBGAGAHEHEBEAADAHBGBFBFBABABAHAHEEAFHEHBHEHABGGECDCECEAGDHAHEFGG,False +153,19.0,24.0,27.0,19.0,23.0,23.0,26.0,24.0,CDCGGGFAAGACHFHDHDHBBCCHCGFAHABGBEDHBGBGBABADECFFFFAGGCHDDGDGCGHGHGDCFHDHAFEFEFEHDCCGGBGEGAAFCEEDFDFGBEAFHFCGEBCBHBFBDCDGBCBEHADABCHCHEHEHBHDGFGAGEGBBEBHDEEHAHAEAECCFFFCCCECECEFBFBDECBA,False +154,13.0,10.0,11.0,9.0,11.0,8.0,12.0,4.0,GEAEAFAGADADAEFCGCGCGCAFBFBEECEGADADACBGBCHHBFEECACBEHEFBFBDADEDBCGGGBDFHCAGGD,False +155,23.0,15.0,20.0,21.0,22.0,13.0,16.0,23.0,FEBEBEBFDHDHCCDDBCBEGFDFGBHCHFDAEBCBFHAHGHDADCBGDHDHDFCAHHHDBCEHDFDAAECDCDCBCAFEEEEEAEAGACHCEGEAEGGGGAEABAFAFHHGEAAACHFHAHFGEAEDEDEDADHDBCGAGACBCHHBGGCHC,False +156,1.0,2.0,8.0,2.0,1.0,1.0,0.0,3.0,CCCCCHCHBACDCBHEDF,True +157,11.0,6.0,5.0,14.0,10.0,10.0,2.0,6.0,EFAHAHFBFGGABADFCBEDEDADAHAFAHBFEDEDCDEDEDEDFFCBEDFDFBACDDAEHCHA,True +158,15.0,22.0,16.0,16.0,9.0,21.0,17.0,9.0,CFCFCAEBDGDHBBFBHCAAGFFFAGGGGFGHCHDBDBECECECFHBBCBAFHFDFBCACHCAAAEFDBDBCFGAADADAGGBBBGCGBGCFBEEGHGFGFDFDFABABDFHFDBDCEFEBGDDB,False +159,3.0,6.0,10.0,6.0,2.0,3.0,4.0,5.0,GGGFDFDBCBHBHBCCHCBCEHHFCACDCBEDDDACGCA,True +160,7.0,12.0,7.0,6.0,6.0,8.0,8.0,5.0,AEFEFEBCBADCEFHHCHGBBECAABFBFBDBGBHECGDADADGBGAHFFCFCGDGBGB,False +161,25.0,18.0,13.0,27.0,15.0,21.0,17.0,28.0,HFHGDDBDFDGHGADHGFBHGCFDAECCHHEFEFEDDBEBAHAHFHFBFHAHDFDFAEDFBBCEHADGFGAHDGDGDGDFCBCEAEBCBHDHDHAHAEADHHFHFHEGBHEDABABACDCAEFDDGFGAGABAHDHDGDGDBHBFAABAGAECECHCACBFAFH,False +162,18.0,23.0,16.0,12.0,17.0,23.0,24.0,31.0,AEABABCBCHCHCFFFBHHEGBABDDDDDHHFHEECFCFCBEDDBHBHBCGHDFAFHCHFGCHHHHHHHCFGFGEHDBAAEGGHEBBHGDAHFHBHBECGFAFBGCAHEHGBBFBDCHHGEAEHGFFFADGEGBGBGCGFFCHGEGEGAGAFABABAEAEGFGF,False +163,24.0,23.0,17.0,16.0,25.0,31.0,34.0,30.0,FHFHFEFGFBAEHHHDHDHFGGDGDGFGDHACAFGDGDECECHCGAHAHBBBBBFFFCGBGEFFHFEAECGGBBAGABABAFHFHECGDECFCHDBACDEHBFBHBFEFDDGCHBHGHGHBEAGFGCEHFBAHACEHEACFCFEAEGEGAGACFEAEBGGFDBDBGEGECEAHHHAGBGHAFDFAFDFGBGHGFGAGHEE,False +164,16.0,17.0,19.0,27.0,19.0,29.0,35.0,19.0,GDGBCCGCAFBFGFDHGHBFAFGFGDDECECDGDCDFHFGFCFHFEABACFHFBFHEEECEDFDEDGGGDGCCBBDBFBABFBGDEDEGBHBDDDGGGGCFHFGFGFHFEABBDCDCHCGGGDGFGEDADHDECEAGAFAHEHADAFFGGGCABEGHCAEFGFGAGDDHDHBCEHGAEHFH,False +165,10.0,7.0,7.0,12.0,6.0,6.0,5.0,8.0,DGFFDCDCDAEGDBDCEBGACECHCECDBABDEAHDHGAAHHHFHFBFBGBHDADADAFAE,False +166,17.0,18.0,17.0,16.0,20.0,19.0,17.0,15.0,CACAHAFBDAAADADHBGFAFDGDGDGHHFHFGFGFHHCAAEBFBFCFAHEBABEEGEGEGEBAHGDCDGEBCHEGDGCFCEEFECBCFHBHBHBADDFBFBGDCBCFFEGCAEGEFBACDCECECFDDADEEEGHBHB,False +167,15.0,4.0,11.0,15.0,21.0,12.0,17.0,17.0,HHAHDEDGHFHEHCHGFGFCECEGEACFGDGDCDCHADCEHEGGAEEBEBFHHHCHCHCFDAHAGDGFGDDHEEGCAEDEABAEGEGHGDDFAAEFGAGAEAFAFDFEEBED,False +168,8.0,4.0,9.0,2.0,9.0,7.0,3.0,7.0,ECECBCHFHCGFGFEEEHEHECAAHAFFBAEAFHBGAEAHDBDACCCFC,True +169,16.0,14.0,9.0,11.0,11.0,11.0,12.0,11.0,DFDFDGAGAGAGFGHHACBHBHGFFDFGBCEAHBDAEADACCECAAEABBHEAEAEDEDCABABCBGGGGFFACHHBDBFFDFEEGBCDHEHBHB,False +170,4.0,2.0,1.0,1.0,6.0,4.0,5.0,2.0,GGDBEEEEBEAGFFCFGFHAHAEAG,True +171,28.0,14.0,20.0,10.0,8.0,25.0,20.0,36.0,HCHCDCGCDAGAGHGBABAFAFCFAFDFGFGEGHFEFHBHGFGCHEHABFGFHHHCFDACHEFBHHHCHAHGBAADCHBHBFAAAHHHFEGCGDAHAGFBFAADAEACFFGAEAGABFCHCBFDEAGAHBHBAAHHHFHFHCCACGHGHDHDHCHCFCBGF,True +172,3.0,11.0,4.0,4.0,5.0,7.0,5.0,5.0,BBBEBHHCCFEFGFGHGBBBGBDFAFACEHFGFHDBDBABCDEE,False +173,8.0,13.0,6.0,15.0,4.0,10.0,15.0,7.0,ACDCGBGFFFGEGBGFHBHDADHDFGBGBGHCDAGGGCHDHGADDDDDDEBBHBFBFGFAEADGCCBDBDGAAEFBFB,True +174,10.0,11.0,8.0,10.0,13.0,7.0,14.0,11.0,GCGCGCGFGEBCAAEEHEAEHDHDGAADADADFBEDECHCGGGHGEEHBHAHABFBEBHFADGDHEECHBBFBGEGBGDCFBFD,False +175,23.0,12.0,12.0,24.0,26.0,34.0,26.0,24.0,CDBFHAHBGAAFEGHAFGCAFGFGBGBEBEAFGDGDFDADCFGEGBFCHABFCGADHFFEFHFEFEFEDHFGCGEGEAABEGAGHGEAFAFAFCFAEDEDEDHDHDHFFFGFHACEFHHHDHDAGFDFGEGBGDHDBABAFEEEHEBGFGEEAEAHHFDDDGHGHDFCFCACHDDEDEFHC,False +176,18.0,8.0,20.0,16.0,15.0,17.0,11.0,11.0,FCFBECGAFAFABAEEEEDCDAECEDGAAADFHBDBECEHEABABCDCHBGEHAHAGAECHHHADCCCCFCDCDAGCFFEEAFAFGDDFHFHFHDBGGDGDADFGCECFCGCDCFF,False +177,13.0,12.0,13.0,12.0,6.0,11.0,5.0,9.0,DABFHGHCBDBDCFFGABAFEBACAHECGDFFHFHFDFEFCHCBCBAECGCGCHEAEADDDBDADAHHBACABACDCDBFB,False +178,7.0,14.0,10.0,12.0,19.0,22.0,10.0,9.0,FDECFBFDFDFHFGCEDEDEFHGBACCEGGAEBEGABFDFDFCHGHFFEDBFBFBFEGEHADAEFEFEFEABCFHDHDAECFCGBFBGBFBEECECDBEBHGH,False +179,2.0,2.0,2.0,1.0,5.0,4.0,1.0,6.0,HGFEHEHEFEDAFHFEABBCHCH,True +180,2.0,5.0,1.0,3.0,3.0,4.0,0.0,0.0,FAADBBBBEBEFEFDDCF,True +181,6.0,7.0,5.0,2.0,1.0,4.0,3.0,6.0,BHBDBAAGAHCHFHACAHEHBBBFCFCACGGDBF,True +182,2.0,3.0,10.0,6.0,8.0,6.0,4.0,4.0,BCBCECEAEDEDHCCCCHEHEGDGCFFFAHGBFFFECDDECGD,True +183,27.0,20.0,35.0,20.0,19.0,18.0,17.0,19.0,CHCHCFCBDEHBHEHCCCCBDBAADFFECCGCAEAFAHCFGDGAGACABFEAHCBDBDBDACGDEDEDEHEBGDGDCAGABEBEAECEGAGFGCABFGFCEAEAGACFCDCFFGFEHBDBDECACAFHBHCHBHBFAHDBCADHEHACAGDDDGCEBFBFCCCCGAHCFCACAHH,False +184,21.0,29.0,29.0,14.0,13.0,23.0,22.0,20.0,HBBEFAHAHDHCHCGCBCAFABDDHDFAAADBDBEBCBCBEACGCGFFBFAFHGHFCFEHCHDADFCFCEDBGBCCFCFGFHCHCACBEAFBECFCDAGGCGFGHGFGEGACCDCBHBACGFGFHFBFGEGBCHCBCDEBBCHGGBGBDDFAAAEBEBABHBABHGEGBHA,False +185,16.0,21.0,7.0,5.0,16.0,12.0,3.0,15.0,BBBHGHBACDBEAAAFDHEHAGAGAEEEHHCAEAFBBABFBCECAFAFBFHFEDABBBFBEBEBEBACHFHFHDHBFEAEBHAFCHEDECEHBHB,True +186,26.0,34.0,20.0,22.0,24.0,21.0,26.0,17.0,HFACACHCBBBBHBGBEHFHFEAHAEAEFDBHECAHAHDDBGEDCBEGGFGECAAADBEBGCGCFCFCFBFBFBAGCBBABEHGCGCGFGBBCHCEDAHBCEAEHDBAHGGDDDDHEADDDDDFFGBGAGBGBEBABDBDGDGBFBDBDBDHEFEFCFEAAFGEBCGEGBFFGCGAABAGCHEEEAFAEA,False +187,3.0,5.0,0.0,1.0,1.0,2.0,2.0,4.0,DEBGHGAFBFHHBHBABA,True +188,8.0,11.0,10.0,11.0,8.0,19.0,14.0,12.0,HGFBFHFBFGGAHDDEBAHFHFHFCEGFGFGFGBGEGBCEEAFDBBBHFHDBDBGACHCHFGCGFGCGFBCDCDFFAEAHAEFDFDHAECDCD,False +189,24.0,32.0,23.0,32.0,21.0,21.0,20.0,22.0,BBBABAEECDDDEDEHEBECEDEDHHHFHFDFHCDAHAHDBGBGEGFGFGFGFBAGCGDFBFHDHBBCHGHGFAEBEDCAAGFDDADADBDCFGHBABDHECBDBAAHADAGCDCBABABGBHDCGCBCGFEBDCHAHCCCFCFEBABHDDBGBHHCCCGBABDBCEEGHAFEFEDDBAFFFDFDCEAEAEGDBD,False +190,13.0,10.0,11.0,9.0,7.0,16.0,9.0,11.0,AGCHAGCBAHCBGBEBEACADADHDBFBDDAGEFCFCBHDEFEFHFHGHDFGFACAEFHAEAGGBGFCFCFHFDFCFCBBFDAHAH,False +191,14.0,3.0,6.0,9.0,14.0,7.0,4.0,6.0,EAEFDGEEFCCCFCFEAAAEADCDAEAEGGAFHHHHEAAADADEFEBDBAEGECEADFDHDHB,True +192,6.0,4.0,7.0,3.0,3.0,3.0,1.0,4.0,CFGEHCCFCBCEAEHCHDADADABBBACAFH,True +193,29.0,36.0,21.0,12.0,18.0,14.0,23.0,24.0,BBHFFFCEHEGEHDHBGBHBHDEBHBHBEAEBDBFHFHEHABADACGGGADBBHHFBBBAAAAABECDCACHCAGACFCFAEAFAFAGGDAEBDBHBEBGACBHFAFGFGBBCAGGBGHDCBBDGEHEGEACACACEBEBCACAEGDGHCBDGHGHBBABCCHCHCHGBAEAGBFBG,False +194,6.0,3.0,5.0,1.0,2.0,4.0,8.0,5.0,HBHGGFCFCACAEABGEACDCHBGGHGAGAFHFG,True +195,3.0,6.0,4.0,7.0,9.0,15.0,5.0,10.0,HAHEHFGFHHGHGFFCFCEDEFEDBGBDEDACBDFHEBFHFHFEFDFCFDFABEBGHFE,True +196,2.0,2.0,8.0,2.0,3.0,5.0,4.0,4.0,CCECHCDCDCEBHCGEHBHGAAFFFFGFGC,True +197,0.0,3.0,4.0,2.0,1.0,2.0,3.0,2.0,DBHBDFCCCGCGBGEFH,True +198,9.0,8.0,9.0,4.0,11.0,7.0,12.0,11.0,AAAFADHGGGFGCBCBCHEGEFEHDCABDHGEGEGDACBFHFBEBGBECEHAHAHGBECFCGEGAHEHCHF,False +199,9.0,8.0,10.0,11.0,7.0,10.0,5.0,6.0,ACADDFDHDABGCDEBEHAFFBECECDBBABAFAFAEAFHDDDHCCDCGCGHGDGHFCBCBFFEFE,False +200,15.0,9.0,5.0,13.0,12.0,23.0,15.0,22.0,CHGFEHBDGDHEHAHDFDFAEBDAHEFEFEGGGGAAAGEDAHGHGHECEGFGFGAGBFEFAFBFBGBDFAFHDHBHFHFHGDEDHFFCFEDBDHFFFAAHBHAHFCFDHHCHAA,False +201,8.0,4.0,6.0,6.0,2.0,3.0,2.0,2.0,AGCFBBCBCDAHABACEHDADADCDADAEFGFC,True +202,15.0,30.0,30.0,30.0,15.0,29.0,25.0,23.0,DFBBDGHBCEDBFBHBHBCBHEGGGEBEBHHEHCFFHFGBHEGBDFDFGBGDFDFHCEFHCGCFDHDFDEHADADEBCFEFDFEFECDAAHFGDDDCACACACACDBABGGEDAABBBGCACABFBGDCDAGGGGDCDFFFGFCBBBDBDHECGHGDGCGCHCHFBFHHHDHCEBFDFDFCFCGCBCBCFCDABHCG,False +203,14.0,19.0,19.0,3.0,12.0,14.0,16.0,22.0,CHAEADAHBHBHBHBGGDBHFHEAAABCBGEFCCHFEBHCHABABFHCCCHBHAGAFCFBFAAAHCFCGEGEHEHEHFHBHEGFGHBEGGGCCFGFGCDAECGCBBGBFBCHCHCGBFE,False +204,9.0,15.0,19.0,11.0,9.0,19.0,20.0,15.0,FAAACCHEGCGDGBHDCCCEBAHDGDFDBDBHCFGFCFCBCBFGFGHGBFBHHHFHEGBGBCAEBCCCFCFCHGAEFEAGCDHGHGFGFGCGBGBGFDACEBFDFDEHEDGHABFHF,False +205,20.0,16.0,16.0,34.0,30.0,20.0,29.0,29.0,CDCFGDGDEFHGHEHEGGBGBGBHBGEFECDCEBGDAHGCBDDGDHDHEBEDDDDHAFAFDEGCHEGFHFADBEEGAGDGDHFHBDEAEAHAHDDDECGBADEHEFEFDACAGEGFGBDEDECHHHEAEFFBADDDDAEAHHDHDCCFCAAAHCFCFEGHHHHGBGBDCHCHDFDGGEGBFBGHFAFEGEGEAE,False +206,20.0,18.0,16.0,14.0,21.0,4.0,6.0,11.0,ABABAFADEDBAECHGDDAAHEBBDBACECGAAAACHEFEBCDHGBCECECEBEFEAECBCEHEDGAHACADAHACECGDDEEECEHHHFECBCBEBHBDBDBDBAGDBA,True +207,1.0,3.0,2.0,6.0,1.0,4.0,1.0,1.0,FCADBDBGBFEFDFHCDDD,True +208,5.0,3.0,5.0,6.0,4.0,0.0,1.0,2.0,DCCBCDCDCAAAAHDHBGAEEDBDEE,True +209,9.0,6.0,7.0,6.0,5.0,8.0,3.0,2.0,FCFEAEGDADABCBCFGAGCFAFABABCBDHCFDFEFEACBDHEAD,False +210,21.0,21.0,15.0,16.0,11.0,15.0,20.0,12.0,CACFFACCCEHFDBGBGBFHFAGDGDADACGGDGBAACABBECECEGEDHDHCABDFDFDAGHGHGBGBFBGEGBFDFAGAEHFDAHEGABABFGAGEBCCGCHBDEDGBCACFBFAFHDBEBHBABADAH,False +211,10.0,24.0,13.0,13.0,14.0,11.0,16.0,23.0,EDEABACHGHAEGGBBBBECECEBBBAHGHGHCBCECDCBFBHBHFHFHFBBDAGFEBHAHDHGCFAGABCDDBEBEDHGHBCCACFDDBAHHHGBGBGEGEGHGFEFHHHDDBBCDEFGFHDH,False +212,19.0,7.0,17.0,13.0,17.0,11.0,21.0,24.0,FGCAHAHFGEHAAAAAHGDGHGFEEGDHHAEAEDCDFGBGDHDGFECECGGEEHGHGHCFBBHBFEEHGHGHDHFHDHDAAAHDECAAACBCECACAHFDFCCCCCCGGGGGEEEDHBHEFCGDHAHAB,False +213,10.0,20.0,7.0,7.0,13.0,11.0,10.0,5.0,HACBEBEBAGEEHEDAFABBFEEEBGBGBGBAAEBBDDFDFDFHCHDDAFECHBBAFAGGGFAFCGBEBEBEGGBFFCBCBCB,False +214,6.0,9.0,11.0,6.0,13.0,4.0,11.0,19.0,ECECBCFDGEGBHEDDHGEBHHGCGCBHHHHHEHEGACABADHFFGCGBGHDDCEEEEBEFHAECBCHGHGHBHAHAHC,True +215,3.0,0.0,0.0,3.0,3.0,2.0,6.0,5.0,HDFDHEHGGGGHAHAEGEAFDG,True +216,1.0,8.0,11.0,12.0,14.0,8.0,9.0,12.0,GEBDBDCCADDBGFGFEEGEGCDCEFEGEBEDCCFBHCEDDGEHEHDDFCHHHBHBHBCDFDEGEGCHCHEHFHF,False +217,10.0,10.0,22.0,13.0,14.0,8.0,15.0,10.0,DCHGECECEAGHEFGACFBGBECGCAEBEHHAGEGFDFDFHEDDCDBFBABACDDHDBDGCCCGHGACFCFDGCGCBCBGAGACECACBCECGDHEHEHECD,False +218,7.0,10.0,14.0,5.0,9.0,7.0,7.0,16.0,CFCECECDHHHHHHHHBBBHEFCCEBDBABAGDFDHCHGACCHCHEFEGHGDACFBGBCEEEFGHGFCBCHAAAB,False +219,15.0,20.0,16.0,12.0,13.0,12.0,14.0,14.0,AGAEAEAHGHFBFEHBHFGGEEHCFCDADACBDBFBCBFGFBBBCCAEGDGFAACAHBCBCDAFHFHECAFFEGEBCBGGCDCDCDEBBDBDBHHHHHDGAGDCHCAGEGABBEBE,False +220,0.0,1.0,1.0,0.0,3.0,3.0,1.0,3.0,HEHEHFFFGCBE,True +221,4.0,7.0,18.0,11.0,9.0,20.0,14.0,16.0,GGGBFCCCFBFDGCFCFDFHFHCDCDHHHGHFDCAGHCBAEEFEFEFHAEFCHCGEFCCCHCHEHCDCDAGBGBGCDDFDFGFHEHDHFGEGFHFGFBB,True +222,19.0,32.0,14.0,24.0,24.0,23.0,30.0,29.0,EAEAGFDFDCBHFAFADGBHBDAGCDEABDFGEEFFFEEAECHDHBHDGAHHGBGBGBGHCDFDBDBDEDADHFFAFEFGBHBGDCHEDABGBEBCDCHCBFAFBGBAHFHFGEDFHHHBBBBDBDBDBGEGBHEACCHEGEGEDEHECGHGFBHGHCBGAGHGHGEGEGEHAHAHFCCEFHFAGBGBGDADFBB,False +223,6.0,4.0,7.0,6.0,14.0,14.0,8.0,15.0,CEEFAGEBDFAHHDHFAFAHBFFHFCFEHHHHFDEGEGEDEDGAGHDFGBGBEFGFHHCHCHEHECFCACEEFE,True +224,11.0,10.0,13.0,13.0,21.0,14.0,25.0,19.0,CGBAEGEGEHHCGGHGCCBCAEBEGHCHDFDFDFEGBDFDFEFAGDGAGEGCGBHEEGCGBEEGEADACECABEDCDFFFDCAGAGHFHAHGEGEGEGBGBGHHHHHHDABCEDHHFFDHEHEGFF,False +225,6.0,19.0,5.0,11.0,12.0,6.0,9.0,5.0,GBHBDBABHBCBDEDBGBGBEBEBCCFDHDFEBBDDEAEAEAECFGFGEGABCFGBBDHDEFBGBGEEABHDD,True +226,11.0,18.0,23.0,14.0,12.0,26.0,20.0,26.0,EFEFEFGDCDFBHBHADECHHEHEFGFGHCBGACBGACFDFGFCFGFCCCHHHBHFHFHDADFFEBGFFFFFDBCCFCFHFCDGEHDFDBDCAGGHHHHHHBACGCGAGBGHAAAFFCHGBGCADGBBBCGDHEBEBEBEBHCHDHCCCG,False +227,23.0,20.0,28.0,18.0,25.0,23.0,23.0,21.0,FCCBCEFEDAGGBEHCHCHAFCCADFFHFEFAHCHDGCCHAEDEDFDGAGAGAGEFEBEBHHEFEFHFCGDFBGBDHAHBGAHFFFBFCDDADCDEEAGABHBHGHCHCABADABCHCHCDFGHGHBAFFEGECBGADCECGCGCBFEFDFCGCGDEECAGAEAGAGBBBBBCEEAEDECE,False +228,5.0,3.0,9.0,5.0,8.0,2.0,3.0,5.0,DDDACEHGFBCEAECCCCCFCEHEHEHEBCDAEBDHAGAG,True +229,15.0,19.0,18.0,23.0,23.0,15.0,10.0,23.0,HHFHGHEBFHHBCBDEEHCBGBAHAEDEDCGCGEBBDDDDEDBDHDFDEDACCEEDFCEEECBCBCBCDAFEHCFAHBEDACAGHHHHHHHAHGFACACAFBEBEFFFFFDEBEAEGCBEEDADACBHGCGBGDHDHDFDHDEABF,False +230,15.0,10.0,14.0,14.0,7.0,9.0,3.0,6.0,EDADBFADCDCDEBFBFAFEFEDCBADFBFBAHACCBCGEHEHBCCAGDCFFBAAABAGACHCHDDCCCEDHDADADA,True +231,21.0,19.0,19.0,16.0,21.0,13.0,13.0,23.0,EHBFBHBCDAEACABABEHCAAAAAEBDHDCECACAHGFCFBFBDCCBDBDECHCGCAAHHDDCDCDEEHHHADAFBFGFGDGFGHGAGEEFEHBBDBGHAHGHEBCCACACGEDEAABDBCEDEFEHBHEEEHGHFHEHFFGHB,False +232,10.0,11.0,13.0,7.0,8.0,12.0,12.0,9.0,EFGGGHCHBAEHFDFEADAHBBFBCGFGBCBCBCFHFAFAGCGCEBEDCCCHCHDGGGCGCADFEBEBDAFAFAHEFGBHDA,False +233,16.0,18.0,26.0,21.0,12.0,11.0,22.0,9.0,GBGCHBGDHEHDGAFCFCGCBBDDDHHGCEDEDCDBGBEBCCCCDBGBCACBGGEHEDGGAGACFCFCHCGGDGABDCCCGDBDEDEBBCHCDCDBDAGECECAFEFBFEAGAFAGBGAGDDDACAFAFAFCHBA,False +234,8.0,5.0,2.0,10.0,3.0,5.0,9.0,5.0,GAGBBEDFDFDBDGDAEADHGAGHBDGDFDFCGAGACABAGHHHFED,True +235,28.0,16.0,21.0,19.0,24.0,21.0,12.0,20.0,EDHFBEAFADABHFHFCFHFACCBBBHAHDHBADGDBCBDFEFDHHADACBHBEAEDDDGAGACAEHECFCECHHHEABFCFEEHGAFFFADADCDGEEEGEBECEBBCACAHAHADADFFAFAFHGDEEFEBCGCGCGCDCAHBGEEFGADECECAFAHA,False +236,13.0,6.0,14.0,8.0,9.0,13.0,7.0,14.0,FCFAFAFAHAHCDCDGFFEFECEDBCECDCFHEEFAFACHCHCEBGDHEHFHAHBHDHFCGGAGDHHACCBHDCGFGBAAEABA,False +237,4.0,7.0,4.0,12.0,6.0,4.0,7.0,10.0,DGGHBHDDDGDGCGCGADBHEDEDAGFCFEBDHDEBAHAFEHEHCHDBDBHFHB,False +238,25.0,27.0,17.0,20.0,11.0,20.0,27.0,24.0,BGGGHACECEFEAEDBDBHCGDGDHDHBHBHAHAHFBFGCGCAHFHABABEFFDDAAFHFHDAGADFDGBACCCHGHDAACHCHGBEBCCCBDAFAEGHAHGHGEDBDBCBHBGFEAGAGBGBABDHDGAGADFBFGFGCAEBGFFEHBBGDGBBBFFHFBFCDAGCGHDA,False +239,27.0,19.0,14.0,12.0,26.0,20.0,17.0,18.0,CACHFHBABHBABAHEGBDDEBFAFAEACABAFAHAHGHDFEGEFEBEBEAFCDCHABAGEGEDFBGBACAFDCDCAEHEHFHFEEEFABABCGEEEGHDHAHBHDFGEGBAAAFDHECEAGCGEBEDCDHFAFAGAGBGFFCGCEHGFEBEF,False +240,13.0,5.0,13.0,8.0,10.0,9.0,13.0,11.0,HCHAGAEFGBGAGFGCDCAGAECGCGEFEDHGFADADACHDFDGBCBCFEDEFEFBAHHHHHHAAFGCECACBCGEHEADCG,False +241,15.0,13.0,22.0,21.0,14.0,24.0,13.0,15.0,CECEBACABEFHFGBEFDCDBABGDAEADCDHGFGFDDDFDFDFGFEFGCGEAHGHGHCFCDABFEHHABCECBCHFHCACFBFBHBADFEFEFDFDHDHCHCDEDAGGECHAFDHCABFCFDFDGBGCFCACDCEA,False +242,10.0,3.0,9.0,4.0,10.0,22.0,6.0,6.0,CBAAFFFFGBDAFFFFFFFDGAGEHFGECEFEFHCHCEEEDCFAFAHAFBDEHGHCFEFCFCFEAAFAGC,True +243,16.0,18.0,13.0,25.0,8.0,14.0,16.0,17.0,CFHGHAFGFCFEDAGEBBFDGBGHDHAHBGBGBDCHHEBDBDBDCDHDHFAGGHGHABADDCDFBHAGDDDBCACECAGEGDDHDFDFHFHCGCGCDBAFAFDBDEFEACADADADBCFAHBHGEBB,False +244,14.0,10.0,26.0,18.0,17.0,28.0,19.0,21.0,HEHEHDFDFEGEGFGDCBBDAFHFHFDCEGBBDHFAGBHFHCECHCGAFCCDDADGHGCGAGBDCDHDHDACFCFGACEHEGDGFCFCFCAEFHHHFBFDFDCBCFEFCDGAGDEEFEFHFHFEECCCAAABECFHACECFAFGFCBCGHGHG,False +245,30.0,27.0,23.0,25.0,28.0,19.0,14.0,26.0,AAACACBCAEDEBEFCCHCAEGEDEFGAGCEAEADFEBBBEFAGBBBFDAEAEHHHHCFCHCHADFDEBHFACBFBGBFBCHHAHAEEGHHEAEGHGHGHGCAHADADAEAEAGDGBECHDDDDEFFDCDCACAFBFHCHEHEADFBFBGBDBCGABHBHDACCECDDBDBDFDBEEEEHCBAFHHDBBADF,False +246,9.0,17.0,16.0,9.0,17.0,6.0,11.0,16.0,HGEGACAHDHDCDEGFHBHDHECEDEDFDEEHCFCFHBEGGFABEHHHHGAABCCDBEBECHCHFBAHGCGABCBEBECCCCCEGEBBBBDBABEBHGEGA,False +247,10.0,6.0,15.0,20.0,23.0,16.0,16.0,6.0,AFDGEGEFEDCDFHEGEGFGBCACECEAEHEDDHEGEDEFGDDDCCCCGAGEDBABEFEFDGDHDGDCBHBGFFCFCEEEEFCHEFGDGFCDADCFCAEGFGBEFDADADAE,True +248,1.0,1.0,5.0,2.0,5.0,7.0,7.0,2.0,EFCFDAGFCFGFCHEHECEGGCGDGFGFBE,True +249,20.0,25.0,23.0,25.0,18.0,22.0,28.0,20.0,DGDBDAABACHGHEBDCCABFBAHGGBGEAAGDDFGFAHADADEDFHFHGGGFGFDHDEDBACDGDGBFACABBGBGEGEGECFFFEABDEDHFAFGBCBCACHHFHFBFBFHCHCHCECDGDCEHEGCGBBFBGEFEFHCGCBHGDGFHFEABCCEBDBHGDGDGBHCEDADCDCBAEAC,False +250,27.0,24.0,20.0,16.0,26.0,17.0,25.0,11.0,CHCBCACHBABAGHFEEBEGECEBEBEACDGDHHGAAFGEGABEGAGEGADADABAECFGBGAGAEBEADFGFECACGGFGEGDGFBFGCGBFBFEAEBEFAFAFEDEAAAAGBBBCDCDGECCCBCFADABHDEDEGEAHHBDEDFDFGCCCDBBHAHGBCBEHF,False +251,23.0,19.0,20.0,25.0,22.0,22.0,28.0,26.0,ACACGEBFHHCAGAGHGHGCGCGBEHFHFCAGFGCGHEHAHADDDDAEEEECCFBGHAHAHGBDECFADGCECEGEGDGAADBEAEFHFDGDGAEAFDECBGECCHDEEBGBABEHHAFFFFEFDADHBHBDDGGCGCBAGAHABDBDEFEBCBDHGHGFDFDFDFHBAFCBDBDFFGGCHHHDH,False +252,22.0,23.0,23.0,11.0,21.0,24.0,27.0,23.0,CGGAGEGECECECDBFFFHAHGEGCGAGACEDBBBFGFGHGHFCBGHFHBHGEAHAHABDHABABDBECHAHFCFEFAAGGGBGFCDCBEADADHFHDHCEABCGGGFGAHEEAECCCCGBBEHEHBHBHDCDFFAFBFCEBAGAGCCBCAGFDHHEHFFFCFEFBBEBFGEGA,False +253,21.0,15.0,11.0,10.0,10.0,18.0,15.0,19.0,CFCEEFHBGDEEFEFDAGAHAHGHFHFHGHAHAHGFFFGBDBGAAAABABGBFBFBEACGCEDHFACCFFFGECBAECDGGAFAHDHDHBCCGHAHAFAEDHDHGBBABDFCAGABHBH,False +254,16.0,7.0,14.0,11.0,13.0,17.0,11.0,13.0,CDFHFHECACEDEAECCHFHFHGHGCAHAGAGDEDFDCHCFDADFEGAAEAFFDEDCCEDBFCGCGEBEBHGAGFBABAGFHDHAHAEFFFFFBEBCGHACA,False +255,14.0,24.0,17.0,17.0,23.0,22.0,12.0,11.0,EDGFFFGBBBCACDDDBDCFCFCEEAFGFGFGFDBBBFBDCFEFADAHEDBDFHAAGHCHFGACABEDEDEAECEFEFDAABHHAHCECBFBCBFFDBDGHGHFBCDCECEDEAAGEGFBEBCBEEGEBEBEBHCEFBBH,False +256,15.0,18.0,13.0,27.0,17.0,28.0,20.0,24.0,FBDBCHCGDEDCGAGAGDDFBBBFFFFEDACGCHAGGGEGEBABFHFEDHFHFCBDGHGBGDHBCBGAEHFAFHHHDBDCHBFGFGFHFHEGEBDFFFHAHGHCHAHDHEBEFEDGDGAFABDBEHACFCFCEDADEFBDDEAEADFDFHFHFDGHEDDDDC,False +257,6.0,7.0,12.0,13.0,9.0,11.0,8.0,10.0,DDACHGHGHDHEFCCEGEGACCDCDCDADHBFEFEDEGCFBFDFBFEHCHDAGEDECBCBHFGFDFHAHCGABDBF,False +258,17.0,20.0,27.0,16.0,18.0,18.0,19.0,20.0,AGEHCDAGCGFGDCDCHCACDFEAGFGAAAADADCCHGHGHCCEEEGCADACAHECEGDGFBFBFCHCHCBBDBDBDEFCGCBBBEHFHACAGBCHFFBCBCGGGGHDBECEHEHGHBCAGEDEBFCEEBEBDFCFAFHBADDHFHFHFHECFBB,False +259,1.0,5.0,4.0,1.0,1.0,0.0,6.0,2.0,GGGGBGAHBHCGDBECCBCB,True +260,2.0,3.0,4.0,1.0,3.0,5.0,1.0,3.0,BFBCBFHEEGEHCACACHFFDF,True +261,2.0,4.0,3.0,2.0,3.0,2.0,6.0,2.0,CDCABEHHGFGFGEBABCBGDGEG,False +262,17.0,17.0,32.0,25.0,20.0,22.0,15.0,15.0,DHDCDCDGEHCBGBEBACGDFDCBCFCBCEAEAFCDEBAAEADHCEAEHECDDDBDCDBBFFEFGFBCBHAHFCCECGHDHFHAHACDEHECFCDEAAHABBCHGEGDGFHDDCDGDCCCGCACACFCFDADFGFBFBFEGEGEHDACGDFCFCFGBEBEFCF,False +263,7.0,4.0,7.0,4.0,5.0,5.0,7.0,12.0,GCACAHGHECGCHFGFEDHDHDHGHBAEAHBHFHGCCBCHEGEBHAFADAF,False +264,6.0,6.0,13.0,6.0,11.0,2.0,9.0,8.0,DCFBDBEEEEEEADAHGHGCGDHCHGEACBCGCAHEHGGAFAGCCCCCBEBHDCBCEGEHD,True +265,20.0,25.0,22.0,32.0,26.0,23.0,23.0,27.0,DCHBHBCEHHGHDCGCAHHGHDEEHEHBBECDCGBBACACADDDDDFCGEABGBABEBEBEACFHFBEGHFBABCGHGEGDDDEGAHAEFBFDGDHBFGFCDCDCDFGFHEBEHEHBDEAEACBDADHFBDDDDAFEFBGGGGHGHCHEHFCFGFGADDDDBDADHFEBEBECEADACBCFAFHFDFGFAEGHHCCFE,False +266,7.0,6.0,7.0,3.0,4.0,2.0,13.0,8.0,BGHCABHHCHGGBDBABAFCGEGDGAHCEEGEGBGCAHAHACGCGHGFGD,True +267,8.0,8.0,22.0,12.0,15.0,14.0,10.0,10.0,DCBAAGBEBEHECCCCFEDDDFGHGDEDCBCGEGEGEBFFAEHECFCHCHFHDCDCBHGGCCBCFCHHFAFGHGDFCEADCDCDCEBFAFACECAFEFE,False +268,20.0,11.0,17.0,15.0,11.0,11.0,19.0,11.0,FACAFGDHCEFHAECBCBEBEAEGBGBGFHCCBCAHDCFCDGDAEEEFBACADABACECHGGDBDGGGFHEHADAFGFGFGHGHGCFCDCDEGAAAABDDDGHBACACDGDHAGA,False +269,6.0,1.0,7.0,4.0,8.0,4.0,3.0,3.0,DBGECEAEAEAEAGDGFCHCECFAAHHFEFCCDEDC,True +270,18.0,16.0,20.0,26.0,19.0,21.0,22.0,23.0,BFBCDDGAGACDBDGDGDADHCAEACGCGDEBGDFDCDBDGHEHCFFFFFHFBFAFHDDGBHHHHFEFABGGDGDEFCDGHCHEFCFHBADHHCFCBGBFEEEEEFEDEDAFGHGDGCACDEAEACDEDHBHGHBHBHCDGAEACCEHGHAHACAGACBEBGFDF,False +271,0.0,3.0,1.0,4.0,2.0,4.0,2.0,3.0,HFHFEFDBEBHFDDBDGCG,True +272,16.0,16.0,17.0,14.0,11.0,14.0,8.0,16.0,FCHEHAFAFBFBDHGAFABBCDCDHBHEFABCHCHDAGABEBAHDHDFCEBGDFECECECEHECACDBDBDCGAGAGACAGBFBGDDACCDDBHEHBACFBFHHHFHFCFAE,False +273,13.0,11.0,14.0,14.0,11.0,17.0,18.0,16.0,CDFDGBHBFGFGFGEDABABCHHDDEDCHCGAGFBFDADHDCDCECAGEFEBEAFAEHEHGGEFBHCHFHFAFDFACGGFGHHDHGHAHCFAFGEBCBGBGCACDCDEHGFBAG,False +274,30.0,26.0,12.0,16.0,14.0,36.0,17.0,16.0,GGHCBABACFGFHFBBHAEAEACADADABABFFDABBFFEFBAGFHFBFCFBAHHHHGGDGFGBHBFEECEFDCHCHBHGEAHADDGAFAFDDBDGFGBEFFFFFGFACABGFFFAABAFACAGAGHDABABGDACFEAEADBBFBEDEAFFBFBFCFCDBHEHEDF,False +275,6.0,13.0,13.0,9.0,7.0,9.0,12.0,6.0,CEFBGCCCCHDBDBCAFDFDFGFHHCCGCGBGDGDBCBCBHFGAAEGBGBFBGBGECHCDAEGEFADAHEDEBBF,False +276,7.0,5.0,3.0,5.0,6.0,7.0,3.0,5.0,BCCDFEFEFEBADABCFDDHDHAAEAGFGFHFBAEAGHBHE,False +277,6.0,5.0,1.0,2.0,3.0,3.0,6.0,7.0,HBBFBFDHCGEGAHAHGHGFEBHBGGAEAHADA,True +278,4.0,8.0,15.0,16.0,12.0,11.0,10.0,10.0,DHCHAEEEHEHEFEHGFBHEDEGEGFCDCFCGCDCBFFFCEGDBHFDDADGGCGDEDEDGACDCFCFBGBHBDBCFCHCDDDHCAB,False +279,15.0,15.0,14.0,9.0,20.0,30.0,10.0,19.0,EAFFEFEFHBHBHBHCHCFAAACFCAHGBGBFEEBECEGEFDCEFEGCBFHFBEAFDBBGDDCGFDCBBHBHFEFEHCHFBFDGCHFHFHFGFGAAAAEECEFDBEFECEHDFCFHDHFFEAAAAAFGFHFH,False +280,20.0,27.0,17.0,23.0,26.0,20.0,26.0,25.0,AEDGCEBACABABGBGFDCEBHBCBCGHBAEACBHHHCDDEGFHAAFABCEHDBDBDFFGFCBGGGFGEEFEDEAEDEDHHHFHEEEGEGCBCBHBEBGBGECEAEHGHABBBFHEAFGBGDGFFEFDGDGDGHGDAFAGDHDECEHHHAHDDGHGCGEBEFABCBDBFCFCFHBADADFDAHH,False +281,10.0,6.0,6.0,8.0,8.0,11.0,10.0,7.0,GBFFDHAEAECDDBEGDGAEECGGGDHDAFADAEAHBHDEFFFFBCBCECAFABAHGFGFGFGHCH,False +282,21.0,33.0,19.0,20.0,21.0,12.0,19.0,26.0,CAADABABCEABHBABDCHEAEGHBBCCCCCHCBGGGGHHDHGHGDGDGDBDAAGCBHDFEEEEEEBEBAHHGHEHCCGHFBFBFBFGHBDBHAFAGACCHAHFBCCFDEDEHCHABDBEGADBBCBHEHEDDDDBDEDBBHAHBEEEDBBBBHGGGCEFBFAFBGAHAFA,False +283,12.0,9.0,6.0,10.0,12.0,16.0,15.0,10.0,CFCEDFGCGFHFBGCGFGABEGAGAGAGAFADBHGHDEFHHDGCADEGBBCHDAAAGEBEBABFDFEFEFHFHFHFHGBFEGEDDDEFEA,False +284,0.0,7.0,2.0,2.0,5.0,4.0,3.0,5.0,FBBHBHECBFDFGEHCHEHEBEBDGFGB,True +285,18.0,10.0,10.0,8.0,8.0,13.0,19.0,13.0,HHHFGFAHCCBCHCBFAGCGBABDBDGAFDCDAEAEHDADBHBAGFGFGHEFFGHGHBHAFFBFCFCAAABEEEAGGGAGCGFGAGADAGEHAHCDGEG,False +286,17.0,19.0,13.0,13.0,17.0,16.0,12.0,9.0,DBDADABCGDAFEFEFEDABCBEBGDGFEBEBEBEADBDGHCADABFDADADABGFGFCBCDCFBGGEEFCFAFEFBAGGEFHCGAFAHBHBFFEBACECACBCHAHEHEHCGBEH,False +287,11.0,13.0,8.0,14.0,5.0,10.0,1.0,11.0,ADDCHBHFDEACFDBDBABCBCDDDBAAADHFBFBABEHEHBHBCCHFDABAHCDDDCDAFHFEFEFHFHGAB,True +288,21.0,32.0,21.0,22.0,23.0,17.0,23.0,21.0,CFCBBDADEDEDBDHDADCCCEHEHBFBHADADBGBGDCBBHFAEBDHDFDFBEBHDEDBCECEGABCFGFHDHGHEHAAGHGEDEAEABGFCCBEBCFDFAEGGAGADECFFGFBBHCGEBEGAFABDBHFFAHAHAHBHBEBEBCBABDEGCGCHCHBHBGEGEGCAAGGBBFCCGDG,False +289,10.0,13.0,5.0,12.0,9.0,19.0,21.0,12.0,GBFAEDDDGGFEFDHHGHGFGFGDGFGHHHHEGDBHFGGHECBAGAEACFBBDBCADFGEGDBBBBCBHHFFBFBFDAAAEFGFAFAFDFDFHGGGGGECE,False +290,10.0,11.0,9.0,13.0,3.0,16.0,8.0,5.0,DBDBDCFFGFGABEBEDEFFGFGFAFABHCAFABCDHDADAHBGBDDDADFHCBCDCAAGHBFGFGFCCBFFCFD,False +291,22.0,19.0,25.0,28.0,18.0,24.0,23.0,17.0,FCFEFEFAGEGCGEAAAEGEHFHEGFGDGDEDBDEEECBBBEDFHFAGHCAGAFAHABFBFDDGECEBGFDFCFCDBEFABGEDACACDHDHDFFCDCACHCDBBGCDBHBHCFCDHHHBHBGFGFADDGDCDCHCDCACAGAGCDDABCEGHDHFGGDDEAFBFACACABGBGFD,False +292,22.0,21.0,17.0,19.0,16.0,16.0,15.0,29.0,EFHHAHDCDEBEHEHEHEHEHCFDBCBDHCAFEGGHDDBDFGFGHCFDDDDAFADCGCFDFBFBHGAFCCBBEEAAGAGDEDAHAHAHBHBHBHEHCABABHBCCCHCBBBDAHGFDEAEAFHGBGEHAFBGHAFAFAHABCDDECGCHHGHGAB,False +293,14.0,10.0,22.0,19.0,17.0,10.0,11.0,13.0,FDGGCACGCDCACBCDCDGHHDHBHFGGCCFBFBCBDFDAGEHAHEFECBHGDDDCEBBADCDFDADEEEEDEBHAHAGCGCBDGECEHEHAACADAHFHFEFCCECEDECCDAEA,False +294,21.0,23.0,11.0,16.0,19.0,13.0,19.0,13.0,ECDFDEAGAEAGHBFEFGHBBGBABABGDGCCAGHBHFEFGGCBDGDGDGHFHABAECEAGHFDFEFBFECECEFDHGFGABAEHEGEBBBBEBADFEHEHBDBDADADGBHADADHGAEBBBDCACECBCAAGA,False +295,16.0,21.0,15.0,23.0,14.0,18.0,17.0,12.0,DDBBHFDFGBGBHBFFFFFFFGEBCFCGHABBEHDDDDBBBBDGFHFAEDHDHCFCHCECBAHACDCDHAAADDECACAGABAGEFEBCAEACGDGFEFBGBDBCBGGDDAEFEDGCGEGEDEDGDBABADFHCHG,False +296,2.0,5.0,5.0,3.0,8.0,3.0,7.0,5.0,GHDHFBBGGCGBHEHBCACHCGCGEEEEFDADBEGEFE,False +297,8.0,7.0,6.0,6.0,3.0,4.0,7.0,7.0,GDGFBFEFAAEBDBDBAGAEHBDBHCHDGBGCGHGHAAACHCHAFCCD,False +298,10.0,8.0,9.0,8.0,12.0,10.0,12.0,8.0,AAAAAADGHGAEEEHFHEHEFFAGAFHCDCGEBCBCBFBFAFHFGGCGHEDGDFDBGEDEDCBEGEGHCBEBCCDGF,False +299,2.0,2.0,2.0,2.0,1.0,0.0,0.0,1.0,CHCEABDBDA,True +300,21.0,16.0,12.0,20.0,12.0,15.0,16.0,21.0,HFHGDDEFBFBFAGCFAGBGDHEHBHBHAEFBDGACHGHAHFFDFHFHEBBCBDBDBCFCDCACAEDEDHAHBHECABAGCEBHBGEDEGAAHAFAHADCDEGEGADFGAGAHCDAGADAHCHDDGDGDHFBF,False +301,18.0,17.0,21.0,18.0,14.0,17.0,20.0,23.0,BEBFFCAGAGAGHGHFHDHCFDFDEDEBEBEAGFBCCHCDCBCHHGHEACAEFGBGBEDEBCDADHFAADBHBHCHFDFDFHGBGBAEFGFAAEHEHEHCCGHDDDGHCCCCAABCGCGCADACABFEHDBCFHGHGDAHHDFGBGFG,False +302,17.0,9.0,16.0,15.0,18.0,20.0,16.0,20.0,CFEHGDGCGHFADAFGFBFHABACDEDEDGAEHEHCCCBCEFHGHAEAEAHAHEHEHCDFFAHDEAFDFGBGDHHFHFAGGFFBEHEAEAFFFDGBGCGEECAFFHEHEHDACBCFCDDDDCBCBHGAGCG,False +303,17.0,9.0,12.0,14.0,11.0,11.0,11.0,15.0,DFDFAGHHDEDEHEHECGFACAEADDHDEDCHCECFHBBBEGHBACGGGAGAHDHAAADEHEAFADGDBDFHFGBABABHBFCHAHACCFCGCEADFCFG,False +304,32.0,22.0,21.0,20.0,17.0,21.0,22.0,16.0,HABACGCBCGHGHADEGABAFHHGFCCGFFFHFHAHAGACFGEEAHAHABABFBAEAEDGDBDFFFFEGHGDDDCHFAFGECACECECEDFBEAAFBCGAGECECFCFCBGGADADGHACAEBHAHABGGDDADCDADBBBGHEFEDDDGEFBDBDBCBABCBAAAACFGB,False +305,22.0,14.0,10.0,9.0,20.0,15.0,19.0,12.0,GAGABHEFGHGABAEDECGAFABBEFEAECCAAHGHBEEEEEFHFGFGAEAGAGDGHGFAAAHAGAGFBECEFFBBGHGFCBCGCADEDBDBDBDFEECEBEDGAAEAFAHHBFCFCDHGH,False +306,7.0,13.0,6.0,7.0,4.0,5.0,5.0,12.0,BABAFAHDFDGBHHEHBDACHGHGDDBDHFFAFACEBEBEBHBCAHBHDHCGBHBCGCB,False +307,27.0,19.0,23.0,17.0,31.0,29.0,21.0,17.0,FADCDEGEBEGHDAEFEAEBHBCBAFAHAFGEGFBFCAHAHCCBDFHGCEFFCFEFEAEAFCBDADADHDFBFBEBADFCFEFBFBFDFCFGFEAHBBCCCCHHBHAAEGEBECEGDAEFDGECEFEHGAGEFEDGBABABHDHDCDCGHAEACAGFCECGGHEDCFAAAGAGCEHEGEGFGFE,False +308,16.0,23.0,23.0,25.0,22.0,21.0,28.0,27.0,BHGEFEDACAGADADGDGDBBFBCGGHGFCFCEHHDCDCEGFCFBEBEHDHCHCBEDDHBBEBGGFDECHCHCBFDFBGEHEGEDEGAHDBDAHGBGDGBCFCGCGBBAFAFABBBFGFHAHAEAGFFFGDDCABHECEDEBEHDGDEDEGCHCDCACHCAFGGGHFHFHGHGCAEHHHHDDBEF,False +309,11.0,10.0,14.0,4.0,9.0,15.0,8.0,17.0,CECHBGAHBHAHGCACBEFEFDCCCCCBCDCGAFFFFFBCBAFHFHFHDAEAHGHBHBHEHBHCGFBHAAGEFEFEGHAHDFFCAEHG,False +310,7.0,7.0,11.0,8.0,8.0,14.0,8.0,4.0,AFACGFEEDBGHDDADFCFCFCFDBGBHEHFAGDCACFCFEFBDBGBEBFCFCFCADGEGEAHCFGE,False +311,1.0,3.0,3.0,4.0,1.0,4.0,5.0,3.0,DHHBHDGDGCFAFGEBCBCGFGFD,False +312,9.0,6.0,12.0,3.0,7.0,3.0,4.0,5.0,AAEAECGCDFDHACECEAEBHBACCHCHEGCGCHCACBBAFAFCDGEBB,True +313,10.0,20.0,11.0,11.0,10.0,21.0,14.0,10.0,FHEBEBCAHAHBFGFGHGFAFCFDBDFDCHBECCCHEACABDGFBFEFAFAHGBFBDBDBFCCCEBFGGBGFAFABEEAEGBBFFDFBFBDBGBGCGDEDHFHDGGH,False +314,11.0,11.0,19.0,12.0,11.0,7.0,10.0,11.0,GBHBFGDABADADBDCDADHBGCECHCHCGCEAGCGCDCFEAGAEAEHECEFFBECDCGEHCBBBCGDHDBDADCFFEFCACAEBHHCHGHC,False +315,15.0,20.0,19.0,23.0,12.0,16.0,12.0,15.0,CCCCEFDBDHDCDFDCHFHFDEBACECHCGGFGAHDDDBACFFFDFBBABABDBACADAHCHDGCFFBHHDHDHGCCACEDBDECEHEBABHFDDDDGEFBFBGBEBFAGAGBGHEHDFEBABAEADBCGCG,False +316,6.0,8.0,6.0,3.0,8.0,2.0,0.0,9.0,CBCDFDHABAFEHBHBHECEBECHHBEEECEHAHCDAHABAB,True +317,5.0,12.0,12.0,7.0,8.0,8.0,7.0,11.0,CHGBGBFBFDABACAFFFCECHCEGDBBGHCCBGDGFGHEHDHCHBBCCECEBEAEAEHDCDHHBHBDFF,False +318,19.0,29.0,24.0,19.0,24.0,39.0,20.0,15.0,CFEFGHBHFHCEABFCCCFFEFEGBGBAHAHDBABCBGBGBGAGAGABHCCCFFFEHEDGBHEEDHDEDBHFDBCBGBFCFBEDFAFCFGACEFGFGAAFFFFDFEFECCGEGBDAAECECABEFDFCEAEAHFDBABDCHGBGBGBCACBCBEFGFGFCFHDDFAEHDFFEDDFDFBFBEBEBFHFCD,False +319,8.0,5.0,5.0,2.0,5.0,4.0,3.0,7.0,HAAEAHDHCBDEAHCGFGCEABAEAFAFHFHBHBCBCEG,False +320,4.0,0.0,2.0,0.0,3.0,0.0,0.0,1.0,CACAEAHAEE,True +321,19.0,25.0,20.0,14.0,21.0,25.0,19.0,10.0,ECEAHAGAGDCFHAHAHABEGAGBEBFFFFFGFDFDFGCDCBABEBGBFFFAGADFDGHGABAHAGCBABGDGEEACAEDBCBCEEFHGDDCBCEGEFEBEBFGCHBHBEDFHBCGEBCDCFCEBEFEBCBCBCBAGFFAFAFDCGEEFDCBF,False +322,4.0,3.0,7.0,8.0,3.0,3.0,6.0,6.0,AGDFDFDAGECEDDHCHGHCBFDEBCBCHCHCDDAHAGGG,True +323,20.0,23.0,10.0,13.0,14.0,23.0,24.0,21.0,AGAFFGHGEBBCDCEEEGBFAHAEGEGCGFGAAEBGHEBDGAGEBABEFCHAHADFBFDFBHBHBGBEBFBFHCACGCGBFBFAHAHFEFDBGGGBGFGBBEDHGHGHFHDHDGDHBFBFDFHFHFACADAGEFHCAADHBHCADFGA,False +324,6.0,10.0,13.0,15.0,5.0,10.0,12.0,7.0,ABBDDDDGDHDCBBHCHGDGBAEGEGHDBCFGFBEBADGCGCGHFFFFFCFCBDBDGDCAAAFDHCCCECDFDHCGEG,False +325,14.0,17.0,16.0,18.0,24.0,25.0,25.0,12.0,EAGDFBFEHEFGADABCCEGEAEGEGHGBFBDEAEDHDFEFDHCHGBGEECDCDCDCHCDEAEACCBEGAGEBFBFBFCCGFBEBCCDEDFDHHGAGAGEEFFFFFBGHGHBDECEBAFAFDFDGGGAHBEFGFGFHDGDEFGCABFBFGG,False +326,10.0,8.0,13.0,7.0,11.0,10.0,9.0,12.0,HGFCFAFCFAGADEDBHFCFCHHAHACEBECCCCEGEFEFGDBFBHBGBCEEABCECAADDEDHDHBGEGAHCHFHGAGH,False +327,13.0,9.0,7.0,7.0,11.0,9.0,9.0,4.0,EFEGEFABAFHDBFAFGGEBEFECCCEFFDADBDGEGAGABABABFBDDAEAHAHGHEAAGDECCCGCB,False +328,11.0,7.0,14.0,13.0,15.0,16.0,11.0,12.0,HHHHFDGEGFHFHGDGCCHFBFEDBAHGFCDCGGDDACACEDBGEDEHHGHEFEFCFGFAAACADHFAFCFCFCBDBAEEEEGDFBFAEAEDEDEBCCC,False +329,14.0,9.0,16.0,7.0,13.0,4.0,16.0,18.0,GCAEFCFCACAEDGGEGBGBGBHBHAHECAAAAHAHECECHGHADDCBCFCHHGAGEGDGEAECGBHDACECBHDCDGHCHGEBHBHEHCFGEGHHA,False +330,6.0,12.0,18.0,17.0,8.0,10.0,10.0,6.0,GGFCECDCDCAABEBEHEFDDADGDBDHGFBFBEDHDFBHGGCBCBCDCBCHDGCBCBEDCDGDBECADACCCFEFGFGFHDADFCC,False +331,11.0,25.0,21.0,16.0,17.0,27.0,21.0,23.0,FFFCHCBCGHHHGGCEBEDFCHAEFCFHDBDBABFBFEFBFHDHFBGCACHHFBFDFGFBHHDBEFAFAFHFEEEGEGEGEDBHCDCACHHGFGFHHBDBDBHCHGEDBDECECECFGBDBCEGGGGCCBCAAADAHBBBGBGFGHDAEFGFBBGHDCFCF,False +332,31.0,34.0,15.0,23.0,18.0,19.0,14.0,23.0,HBFBAAACBDEABCHDHAHDFEFHAAACDEBHBHBHBCBHBHBGCAFGBGBFFDFGAEAEBDFFADADACADDDHAHAEEBFDFGCCCFCAEGBCBAHCGEEEEEEBFDFEHBBBABAHADBDEDFGHHBHBDDABBHBHDHFCFCGEBAAAEGFDFDGDBBBAGAGABAGHBHCAD,False +333,20.0,17.0,9.0,14.0,13.0,13.0,13.0,14.0,ABGCECACBHDHGEEHEHBDAAAFDEDGDFAFABCCGHBABEBEGADADFDEHEHEGBGAHADDHHGHGCGFFABAFDBDHABEFDCDFFAFBEBHBAFAFABABGCECHGBG,False +334,7.0,5.0,2.0,4.0,6.0,6.0,4.0,9.0,GCGBFBHAHEBEAEDCGEAEHHFHAHABFGFHFHDEDADAFHB,False +335,17.0,13.0,10.0,10.0,9.0,12.0,9.0,20.0,AGHHAHAHCBABFGADADEFEFEDBBBBHHGHDHBCECEHFHFHBHAHDEAEAEBEHACAGADHCHBGGFFFHACBDFDAGHCDGDCFCACFHFBBHGAA,False +336,10.0,13.0,6.0,5.0,11.0,4.0,11.0,9.0,EGEBEBEGEBAHEFBCBEHGDFHFAFCBHBGDABHGGGBGCGBABADHDCEABABADAEEGAGCHCHEH,False +337,17.0,16.0,15.0,8.0,14.0,17.0,17.0,24.0,HBGBABHBHDFFAHAHAGAEAEAFACGCBCECFGDGCCEFEFHHHABGFCHDHGBCBHBDGDHEHGHCFCHGHDHFHFBFDABHBGBAFHEEGEGECBAGEHBHCHEFEADCBFGHCEFGCGFAAAAF,False +338,18.0,20.0,22.0,16.0,18.0,27.0,14.0,22.0,AEAEAEAFHDHAAEFBDHGFGFCAAAGADFFEFBADCHCHEGBBEBGFGFGEHEDCFHAEBHCDCBCGAECGCHCHBFBEBHHHGCBHFDDGHHHCHBDEDECBDFEFBFGFCFBFBCBFBFCDEAFDGABADADBFFFFECECADHHHCHCFCFCG,False +339,24.0,25.0,25.0,23.0,21.0,21.0,28.0,25.0,ABAFDFCFCGHGCDBDGEGEGCAAEBHBHGHGHDADCGCHFECEBDHDABHGCGHDHEEEBFBFBDDCDGEEEHBFFCFBFAFAFGCCCHGGFGCACHEDEHGDDBHEHDACAFHEABGCACABDBEBFDGHGHFHEAEAEADACGGBBBCGCGDGBGBFCHAHAHFBABFCEHBADGDEBACGCGFAFDHD,False +340,14.0,19.0,9.0,8.0,9.0,16.0,11.0,11.0,CAADABAEACBCBGAADHBFFFBDBDEGABHHHAEFHBCFHBEBGFDFBFBDBDBDAEGEGEFCGBFBAEGBGFGFHFHFGFCBCAAGAFEHHHCBC,False +341,2.0,6.0,2.0,4.0,1.0,4.0,1.0,1.0,ECBDBFAFDFDBGBHBCBAFD,True +342,10.0,9.0,6.0,7.0,9.0,12.0,7.0,13.0,AEAHAHFEGEGBGAEBBHFDBGBHHGHAFAFAFHFDDCDHECFCACFHFHCDCDHBEBFAFGFABEEEGBDHH,False +343,12.0,23.0,13.0,17.0,19.0,18.0,25.0,20.0,GCGCGCFABHCGAFCFDFBHBHEECDDBEHEAEABABAHHFFDFGEBEBGCABAGGEGEDEDHBCFDHDGBGDGHAEAGDHAEEECHHFBDGCFCDBDHFHBBBDHHCBEHFHGGGFGFBEBEFEFCFGFGHGDGDBHBGBABDGEG,False +344,8.0,19.0,17.0,14.0,18.0,17.0,16.0,26.0,BFBHCHCACDDFCHEHAFAFEEEDHGHBEEFADGGFGEEDEDEFEFBFBHHGHGHDEFCGCGHDHDBCHDBCFCGEBHBHEHFDEAEBEGCGBHBFBHBCBCBCBGACCHHHGHFDFCFHGDGHEHDCBAAFHBG,False +345,14.0,25.0,9.0,16.0,24.0,29.0,24.0,20.0,BDBDFDFEGEDADGGGGDFAABHGFGFEBHFECHCEDBABFBEDGGCFCEAAHGHFBBHHHHHHEBEBFAEEBEDGDCHEFBFBFBHEGEGEAEBGGCAFFGDGAGAGHFFFFFGCHAHBHDEDEFHBBBFDFHFBFBFBHDEFGBEDEGEGBAFFCACEG,False +346,20.0,21.0,26.0,20.0,28.0,15.0,21.0,20.0,EDEDFHFHEDCCECEHEHCGBBAEFDDHBGBEBGAEHECGCACECGCGCDEHCAFAECHBBDGDFCFBBHBEBEHDGDBDCAGACAHAHDHCEBEHEACDDDFFAGAFAFCGEACACGEEAHAGAGAGEFEFHFBGCHBDBHBCGDGCECHDHFBFDCGCBBEBDAEGEGE,False +347,9.0,10.0,7.0,7.0,9.0,11.0,7.0,1.0,DAFCBCBAFDEGEGEFAADGEGEAEAFGFBFEFCFGFCFHEDCBGBEBAFDDABCBABDBC,False +348,23.0,21.0,22.0,23.0,12.0,21.0,19.0,12.0,DBGBGFCCGCDHGFGFGFDCDEAEAFBFBHGHBCBABAFFFBBAFHFCDBFECCDCACAEADFDEDGCFCHBBBBDFDCGAHFGEADDGHFFDADEGEAEFEDECACACAFADCFCAGBBABEDGDHCGCACACHBDGGAGBGBHAHADDDHB,False +349,24.0,18.0,28.0,33.0,14.0,23.0,32.0,22.0,DBDACACDEGGCFCBGBHFGDGDEDHHADCFBFDFDAAFAGDGCFCECEGDGFBAGHDDCDCDGHCFFAFGDGDHDHFGGBGHDCDCAHFEDBFBFCDDEDGHAHADABHBEAAACADGBGAGAFHCCGFGCGDGAEAGDGHFHFEBAHCFCFGGGEGEGAGHBBBDCCHCHFHCHDFDBDCDEHECBCEAABC,False +350,8.0,4.0,6.0,7.0,7.0,4.0,16.0,7.0,EDGFGACAGBHBEBAGACAGEEEEEGGAGCGCDAFHGDCDHGHCHGBGAFDFDGGGDHH,False +351,14.0,22.0,13.0,15.0,4.0,11.0,14.0,13.0,ABCCHHFHCDBDBDBCCGCGFFDFBFGGBAHADDGDCDCBAHABEFHBBDBDBDBEBEBGDAEABDGFHBHGAGCBFHHHHHACGBGACFBBDGDBFAGAGACACF,False +352,23.0,10.0,18.0,19.0,18.0,25.0,14.0,15.0,GFADHDHFCGCBFFFHHEDFDHAEEFECAGBGEAHAHADAEGCBFBFEGEFHHEGGCFCHHAHAHEBAADAGBEBEDEDGFEFAFADADFGFAFCECECFFAFACACHCDFDADCDGGFDHCCCCDGDAFBFBEADBDAECF,False +353,28.0,26.0,15.0,29.0,24.0,17.0,31.0,29.0,EFGDADGCGBGBGBEAEHGHFDDEDEDEGHGEGEGHGHEHGDGBGFEAEGDCHCHDHFHEHAGDHDFEBEBEBEDCDCACAFGFCABFEGBGAGHHBDBABABHHAHAECEAGBGBHBFEDHCFCDGAFDHBEACFHHGDADHCFCBAAHFFGFDADBBEBHACABAHGDGBEAFABDBGGGGDDDAAHDDDHCHAABE,False +354,2.0,5.0,6.0,7.0,4.0,6.0,4.0,6.0,BHGHAECCCFADBDHDEDBFBHDCDCDFGCGFGFHHEFEB,False +355,6.0,5.0,6.0,6.0,6.0,7.0,2.0,4.0,HFHCGCGBFEAAAHAFBCBDEDEDEDCDFFABBCFCADFEHE,False +356,6.0,7.0,14.0,10.0,18.0,19.0,15.0,16.0,FBEHFGEHFDCDGGGEHCDCDFFFHBABDFDFHCCFEFECEHEFCAAGFGBCBFGFEBCACACDFFGHGBEHEHEHFHCCEGEGEGECAHEDEDGDGEHHHGHFF,False +357,14.0,24.0,11.0,19.0,13.0,13.0,20.0,12.0,CAHGEBBDBFBEGHAEDBDHDGDGECACACEFBDBFFGADBHBCCDCDHDEGEAFAFEGBFBABHFHAEDEDGHGBEBGBGBGFFBCGEGDAFAFAHAEBCGDDAGHHBCBDBDBFBDBDCGGGGH,False +358,14.0,23.0,16.0,16.0,14.0,16.0,6.0,16.0,HBCBHFHFHDBAGAEDCCCBFDFHFHDHDHGHABCFCFAGEGBBBFDADADBEBHFCFDFCBADDBCBCBCAEGEFCBABAFAHBFBEBEBCCEEHEDECBFAEHGADHDHEHBDEFBCDA,False +359,13.0,21.0,20.0,21.0,14.0,16.0,20.0,15.0,GFDBDCACAEBEBEBHBCBCECEGACHCHAHAGGBADADBDFCFHGDGDGEBHBDGGFGFGDBDAGABDGDGEHFDAEFFGFDHEBCCDCHCFCECHGDBCEHEFDFDABEBGDGHACFFBDCEAFGDBCGCBCFHBHBH,False +360,2.0,2.0,1.0,1.0,3.0,6.0,2.0,3.0,GFFFEFEBDBEHGCAHAHFF,True +361,14.0,17.0,14.0,17.0,23.0,22.0,11.0,18.0,DHACABDDDFEFBCAEAEAEFCFEFCFDFHFAFBCBCHGHFHEAEGBHBGCFCHAEBEFECECGFEDEFCCHAFAFAFADGHGBGDHDEDAHBHBHGEEBDHDBEEHGDEDEFBFBFHFGFBDAEBDGCHEEDCHB,False +362,7.0,7.0,14.0,4.0,6.0,6.0,6.0,3.0,CCBCGEGCAFAEADAGFGFCFCBCGHBBDBCGEAHAFCDCACBCHCEEFECBD,False +363,10.0,8.0,17.0,16.0,17.0,20.0,8.0,12.0,FEADABEGEHEBEBECFCDCHBHCAEEGHCFGFGFHHEFEFDFGFDECCACHFFFCDCGADAFGDCDCDCEFFFFAHAHBEECCDADAFFBEDEDEDHCFCDBHGHDB,False +364,8.0,4.0,4.0,12.0,13.0,9.0,10.0,11.0,FFHEHDFFAGEGEHEHFGDDDEDECEDABHFGFGDGAFADAEECGGABDBGHHCDCBGFDHDHAEAEHEHE,False +365,6.0,2.0,5.0,1.0,4.0,5.0,1.0,5.0,FEACAGFEFHCEABABAHFFEHAHCHCDC,True +366,11.0,5.0,9.0,15.0,4.0,9.0,12.0,5.0,CCFDEDFDFEFEHDBDCDHGGGGDFDAACADABFGCBCAGAFDFCGCGAHAGAHDBDHCGEBFDADADGG,True +367,22.0,11.0,14.0,10.0,20.0,19.0,35.0,19.0,DGGGBCECGDADABABHEHBHGAGHGFAFAGBGBGEEACACFEFGGGEFHCDEEBEBAHCEFFFFHAHAHGFECBHGGEGEHAHFGBDFHEEGCGFDAAAGEGAGFEFHFGAGAGDHAACAGHGCGAGDGBFHFGCGCECEHFHDGEGCD,False +368,2.0,3.0,4.0,0.0,3.0,2.0,2.0,2.0,BCECECHFHFAGEGBBCA,False +369,2.0,7.0,10.0,3.0,12.0,8.0,6.0,9.0,HHDHDCCEGEFFFHCBBHDEGEHEFEFEFEFBCBEBHBCCGCHEHBGGACECEFGAC,True +370,17.0,20.0,13.0,14.0,12.0,20.0,18.0,16.0,HEFEBECCHDECGCEBBGCDBDBDGFGFAFHGDDFDHBBBFAGDFAGACEFHGBFDFHFHFHCGBEDHFCFCFGAAEDECEFBFAHABACAGAGACAHABFBFGEGDBFBHBHDHDGBABAGCGEBAHGH,False +371,14.0,16.0,16.0,7.0,13.0,5.0,11.0,14.0,GBGBEHFHFBBBECAABDEABAGAEDEDBCEGECCACAGACACBCHCECEGABDBEBHBHFHCDAEADHCHCHFHCEABBCDHEGFGCHBGGHGHA,False +372,9.0,15.0,11.0,10.0,12.0,17.0,13.0,14.0,BEBEBGFFBFGFDFGCGCGFHDGGCFAFAFBFDHDEAEHEHAFBFEGHHEBGAGCHHHDDCECGCABFBFHFEDEDHBBCBGBCAGACAHBECEDDHBHFF,False +373,14.0,9.0,8.0,14.0,6.0,19.0,18.0,14.0,BHEFAHAHDDDDFBFDFGFEFHGBBFAAAGADHGBFCDGBEFGFCHHGFGHGHFHGEGAGEEAGDDABGGCCCBHBHCHDFAFAFAFGFDFDADADCGCGHF,False +374,13.0,6.0,13.0,5.0,8.0,10.0,12.0,6.0,CBGADAHAHAFAFGCGFGCDEAEADADCBHDFAACCCAFHBBCEGEGECFHAEBEHCGFGFGEGCGCFCGABF,False +375,8.0,5.0,6.0,3.0,11.0,9.0,8.0,4.0,EEEEHFFBFGGCGHGEBABEEFCFCBHGDBHFAFAFDFGAGDGAECECECAAAE,False +376,6.0,8.0,6.0,9.0,8.0,5.0,12.0,5.0,AEGEBACACHCGGHDBDBCEGEBEBHFDDGDCDBDBEGCAFBFGGGEHEAADFDFHGGG,False +377,2.0,3.0,2.0,5.0,6.0,4.0,2.0,2.0,EDEDECEBHBGFGAEADFHBDFEFDC,True +378,18.0,11.0,12.0,20.0,13.0,19.0,14.0,21.0,GAEHGHAADADADBFCECDCFCGDDFCGHAADFFFGHBHFDCDBFHFHGHFAGAGABADDHAEDECFFFAFAFDEDEBABFBGGHBCBAACBHHHFFEDEDADBEHFHGCGEEDHDCDGHGHEHEHCH,False +379,15.0,10.0,10.0,14.0,7.0,13.0,13.0,11.0,FHGHGHBBCDDDDABABGCEDADCHGAAHAFCFBDBDADFCFDDHCHFHAHCHCBCGGAACAHGGGGAGBEDFDFEAGDGFEBEFFAFAEBEF,False +380,20.0,20.0,27.0,28.0,18.0,28.0,19.0,15.0,FAEAEHHHHHHECBHFFFCFCDAGFGDEDCDCBGFFCGBGEGBAEAGFCADGGBEBEFHFDCBAEFDFDEDAHAHGEDAGBGFEBEGFDDDFDFAFCCCCCCBCBCGCGCACDDBFAFBCDADCDEDBCBCGHGFGBBAFDCDHBHDDBDCECACDFDGABFEDEAEFHHAAFFF,False +381,9.0,4.0,8.0,8.0,10.0,3.0,5.0,2.0,DEDECFCECEDAAACHEGDDFDFCACECGAABDGCHBEBGDGBAEAEAE,True +382,28.0,23.0,23.0,25.0,22.0,19.0,22.0,24.0,EBAHHEDEDBDHHGADFEFEHDHDGFFDFDADHDGEACBEHEFGDGAGAGEBCDCBBAFECHGGBHCHCGGGCGAFCHCHBBEBFBFHFCGCGEDEAAADABABADFEFDCDCECDCHCHCBAAAAAAHAFEGEADCCFHFEBEBFHDHFAAAGCBBBCDHDEDFBEGHCBDBGHGCGHDEAGABA,False +383,4.0,5.0,2.0,2.0,4.0,7.0,4.0,2.0,FAFBFGCGAGAGFBDEFEFHABFBDCHEBE,False +384,23.0,10.0,11.0,21.0,17.0,14.0,20.0,15.0,CBEFFDDBFAGHDAGAGAGDDBEGCCCDCBHHEAEFGFEEEHEACACAGAGBDAAHFHFAFADEHCACGDAEEFGGHEHBCDAGAEDEBFGHDHEHDHFHAGAGAGAFAFABBCDGGGDBDGDEDEDFDHD,False +385,16.0,15.0,15.0,12.0,17.0,20.0,20.0,23.0,FGBHBHAHAHBDFEFEBCAEEDEAHBHBHEFDCBAFCFAFAGHGHGACDHBCAEHGHBABFCFDGDFDFHFDBGFGHHACADACHCGBEBEHEACGEGFGFGDGEGEGECEADACBGFHHDFFHFHFGGBHCGCEEHC,False +386,22.0,28.0,19.0,25.0,19.0,24.0,12.0,27.0,BHDGBHDFDFDBABGDHAFAECECBCBCFCBEBHHHEEEBAFDFAFADECBDFDFAEHBHEHEGEADHHHFHFHDBFHAHADADFDFCAHBCGCDCBBBGBFAFCFHAGADDBFEFEAAHCDCECBDFFHFHBHBFEDCACAGEFDHGBEHGBCBHEEGAGHBDBDGHADADCBCB,False +387,16.0,23.0,23.0,12.0,27.0,6.0,20.0,14.0,EDEBGBEBCGGHCACBHBEGAGHGCGEGFCHBDCHGHBHGDADADBBCHCBEBACGEGEGEBABABDEEHECCCCBBBGAGAEAGFGHACCBBABAGFBEEEEEECGDDCDHEEEAEAECDCECGCFHFCBCEADDHEBFH,False +388,29.0,22.0,29.0,26.0,26.0,22.0,19.0,18.0,CECEGHFBFDDCDHGAFBGDFAAHACACAEEBEACFCAEECCGCGCFFFABGBGDCDGDEAEABHBHBFBHAHDCECECHFEFBACDDDEHAGABADFDFDBDBDECECEDHDAAAAEBEGAAADGFBFADACHEAACFGFGCGEHFHFCCCDGGBCEGFAFEBHCDAGBCBCDCEEGDBDBDHFHEBEHH,False +389,6.0,5.0,9.0,6.0,6.0,10.0,3.0,6.0,AFFFACCCEHHHHACDFDEGCBCDEDCFBFBDBFHFHADGCGCEFAFAEBE,False +390,5.0,5.0,8.0,6.0,3.0,4.0,2.0,9.0,CHCGBFDADACBFDFCHHDHDHCGCBFAEAEAECHCHBBDHH,False +391,17.0,18.0,29.0,20.0,13.0,16.0,17.0,22.0,GDCDGHHBEBFCFHGHAAAHBCDCDHFHEHBDDDDDCDCACHEBDBCBFDACBCBHACCDCGGGGCBCFCFBACADHHCFCADHHHGCBBGDGCGEEHEACAGGFGCABABDBEECECECFAFAGHHDHDFBFGFHECEFDFAHBHFGCACE,False +392,4.0,11.0,10.0,5.0,8.0,5.0,3.0,15.0,HHHHEEDDBGHGFABEBECCBHBCBEDECBCHCBEFEHDBDHAHBHFAGCHCHCBCAHFHF,True +393,5.0,6.0,6.0,2.0,4.0,4.0,5.0,6.0,HGFGHHHAGCGEFEBDFDAAHAFCBCBCECBGBEBHCA,False +394,21.0,28.0,17.0,22.0,17.0,15.0,15.0,14.0,DHAAAAFCDBDBDGGABBBCHCACGHFBBBBBBBAAAAFBBBBBEGEABCGFDHEHEDBAADEDEDEHCFEBEGDHFGGECDCHCHBDCEFEHDBDBDBDCECGCBFDGBADHGGFAFAFACEGEFDFBABFFEGDAACACHEHDHDCG,False +395,17.0,17.0,23.0,13.0,25.0,16.0,32.0,27.0,ACFCFGGGEEHEGGDEHBACACECEFEFHDEDFDGEGBGFHCCACEEFDACHGHGHBEEHBACCCCHCEFDAGAGEGCBHBHBGGGDGCFAHGHGHCAEFBBBHBGBHHEHEBGGEGEFHFHFHGHGCFCGHGDEDAAAGCBBBCHAEAHDHDFGGGEGBAHECDFDCAE,False +396,2.0,4.0,1.0,7.0,6.0,10.0,8.0,9.0,GCGFGFGHBFAEGFHFHGBDHEFEDHDEFEFDFEFBGHHAHGDBDHD,True +397,12.0,14.0,13.0,17.0,13.0,20.0,12.0,15.0,CEBHFCBGHGEGEACAHBHBDBGBADFDHDFDADHHEHFHBAAFACECECEDDGDGDCCCHCGBBDGFBECGDGACFFFFFFDHDHAEFEFBBGBFHFHECAFDBEHDFAFAEGFD,False +398,28.0,19.0,7.0,24.0,27.0,19.0,20.0,15.0,DHEAEADDHGAAHAGEHEBDBDHFCFEFEFEGAGHGBFHECAAGDCDADFCHDADADFDHGBGAEHDGFBFAFAFEFEFEHCAAAGGBBABDBCEADADFEGEFHADEGGGEGEGBGBDADEEBDBDHEEEDADEBBFHEEFCFEFAAAGABABDBHBG,False +399,0.0,3.0,1.0,3.0,3.0,3.0,0.0,4.0,DDHFBFEFDHBHCHEBE,True +400,14.0,15.0,8.0,10.0,12.0,16.0,15.0,13.0,BABABGHFHEHEAEBFGHDBCBGDCFFGAGDGFEFEFEFHDCAGAGHHAHACBCBGAGEGEDBDHDEBCACBHAHCFAFEBEDFFFBFGEGFABHGDADFBHG,False +401,11.0,5.0,16.0,15.0,7.0,18.0,6.0,17.0,EGDHHBGCGFFFFECHDAFAFBFDHGHAACFFFAEHBFDFHEHDFDFDABBEAFCCCCCCCFHAGADDDCCEHEHCHDHAHFHCCCFDHDHDADG,True +402,3.0,10.0,24.0,13.0,15.0,13.0,11.0,19.0,CBBEDHAHBDBDBGCECHHDHGHDCGCGEHCHCGCEEEEHFHFECEGBDDFBHEDBDADGFHCHCGCBCDCEAFGFGHGHCECFDECCCCCDHHEBFHFCFCEHFFCF,False +403,1.0,2.0,2.0,2.0,0.0,1.0,2.0,2.0,DGDABGBCHCHF,False +404,5.0,16.0,6.0,12.0,8.0,5.0,12.0,9.0,DGDHBCBCHGEEHEFGFBAGABADDCDBBBBBGAGEEDCDGHGHFHBHGGCEEDBDBDBCBDBGFAEBHFHGD,True +405,21.0,16.0,12.0,16.0,13.0,10.0,25.0,18.0,GFEFBFGGBGBGBHFHEBEBGBGFGFCEAGCDHAABHBEGCGHDHAHDCEGDGDBFGCAAAAEAGADFDGDAACACECEBFDHBAEACHGHAHDEDEFHHHBGEGACDBAGGBCBHHCDGAGDGHGHADAD,False +406,4.0,4.0,3.0,5.0,1.0,0.0,4.0,3.0,GBDDABCBCGDGDCHBHDHAGAEA,True +407,16.0,7.0,6.0,14.0,13.0,6.0,14.0,8.0,BFCAAAAAEFEBDFCFCADGDBDBDAGAHAEDEGHGHGFDBDGAEHEAEAGCEDHAEADGDAFADGGEGHGHDEBEHDGBGCCE,True +408,12.0,15.0,11.0,21.0,18.0,14.0,12.0,11.0,DBDBDBDBCBGGABCEFEFGGDBDAAAEHEFEBGBECCFCBGEEAEHCBFEFHFCEBFBHGADFDACABEBEAECDCGFDDDDDDHGEGFDHDHDHFCDDEDGAAFAFHHGHEE,False +409,20.0,21.0,28.0,22.0,20.0,26.0,20.0,22.0,FCFDFHADGDHDHBBCCHHDHDHDGAABAGCGCDCDFFFAEAFBHHGHCHEFEGBDCDAAHABBCFHFEEGEFFFCHCDBDEDEFEDAFAFABEHCCCEBHBDGDECCAAACDGFFEDHDFBHBAGAEAEFECGGGCHCDAHBGBDBCBEHGFCFCFCFCEGEGHFCBGFGCGCEABBB,False +410,3.0,1.0,3.0,3.0,0.0,0.0,1.0,2.0,DGACBHDHDCACA,True +411,10.0,24.0,18.0,15.0,16.0,10.0,24.0,18.0,HHFBFECHGHAHFGGDCBCBCEGHGBBAAGCCHCBDBGBDHHHBFBDBGGCGHGABABACEHEHCDGDECBAAEFGGDGEADDDHDHBEBEGEFEGEGCGDGDEDBCCCHCEBEDCGFGHGEGFBFBACHBBBBF,False +412,7.0,7.0,14.0,10.0,10.0,6.0,9.0,5.0,GEDFDFBAGCDABADDGAHEDEDFDCDCDFHCBCBCGCHBGCFCAEEEEEGEGCCCHHGCBEBCAGAF,False +413,1.0,1.0,2.0,0.0,2.0,2.0,3.0,2.0,FGCGCHEHEABGF,True +414,3.0,7.0,4.0,3.0,7.0,6.0,6.0,8.0,HCHGEEBABABFBEGFGAGBDFDEHEFCFBHHHFHCHCBEEGGD,False +415,17.0,22.0,23.0,22.0,24.0,17.0,20.0,16.0,BCBGBADDEHEBECCCCDGAGEGEAACEHEHGFABAEHECECFCGCECDBACAHADECGCBBFGFEHEFGDGEGCGFGDHDCBCAFGDGDAEFHFCFBEEHEBDDFHHHBAFAHDEDGDBDEDECFCFHFAGCFFAEGDGDADCBBBBCGHHABBBBBDED,False +416,23.0,23.0,29.0,23.0,28.0,15.0,36.0,18.0,HDFEEHAHFECBCGDFDFBAGABBGGADFDGEGECECGDHCECECEDEDACACGEGCGFBCBCACEEDEGGABHEDCHBGGGHGCGCBDBCCCEHEBGBCDDGGHGEFEGBBBDBAFAFAGBFFHHADEGEDBCCCACGCDCGEAHAEADGGGDGDBFBFCGCGBGBGACAHAHGEFDADEHEHAFGHBHDEAEA,False +417,6.0,3.0,6.0,6.0,13.0,9.0,7.0,12.0,HGCCECEAEHGHGCFAFHDDBDEGBGHHEEDAFGFHEHAAADBCHCGFEEEHEHEFEFDFHF,False +418,7.0,7.0,9.0,13.0,10.0,16.0,6.0,11.0,HEFFFEDECCHHBHFDFACACEDHDBDBDBDFCFDEDEBHGEFFAFADAFHGBGCGCFDEAHDFDHGHFHCGEFEFABC,False +419,6.0,2.0,4.0,3.0,3.0,0.0,2.0,0.0,EEBDBAAAACACEGGCCDAD,True +420,20.0,21.0,13.0,17.0,21.0,27.0,25.0,13.0,HAGAGAECCFDBEADDGAGFFDCBFFCABGBEBAGCGBFBGEGEFDCDEBFBEDCAHBHBDFDFBADGFFEGEGEFEFEFHFBBABAHHDGDGBGAGFGFGEEDEDAFAGDHEACACFFGFGFGEDECBFBFHHHGEAFAEAHFBEBGBCHCHGADC,False +421,9.0,14.0,14.0,8.0,6.0,14.0,12.0,12.0,FHFDFDBBBGBEBCBFDGDHFGABCGABBGEAFAHACACHDDFHCBBFHFHFGCHCHGBBHHGCGCACACHCEFEFADDFEFEGGCGCB,False +422,2.0,4.0,4.0,2.0,2.0,3.0,4.0,6.0,HFCFCECBGGGDGBEHFBAHAHBHDHC,False +423,19.0,10.0,8.0,8.0,6.0,9.0,8.0,8.0,DEABABCFEFDAAABFHFAFAFADACCGBABAGHBABABAGHEHCGDGDCDCGEHEGDAABAEHBAGACDFFCFHH,False +424,22.0,16.0,21.0,30.0,13.0,19.0,17.0,12.0,BCBEBDAEAEAHAHGHCBCAAEADGFGDGDCACFCDEGCDHBCADDDDDEABADADADAEGBGBHCGFAFDCDBDFACDBDBCFEHEHAHGFGFGFGECHFHCCGDGACDFDECFDADEBHFFDFDFBFBEHAGCGDFCBGDACBCFDAD,False +425,12.0,15.0,7.0,11.0,10.0,19.0,9.0,9.0,CADACAFHFDDCDBFBDBEBEDEHFABACFFHHGFDFDGDGHAHACCBEFDFGEGEADFFCEGBABAEHHBHBGBEBABGBEFFFFABGFFF,False +426,10.0,14.0,11.0,11.0,11.0,17.0,18.0,9.0,BFBAAEFEHCHGAFEBCFCGCGBGFHFCGGAFAFBFCFHBBFEFEFEBGCECBGBGCDFDBDBDGAGEFEGHGHAADEGCGHDBAEGDDDDCDFGFGABHH,False +427,37.0,20.0,35.0,16.0,24.0,26.0,23.0,17.0,AGAEEHGHGCCCGBGCHCHCHFGGAAAEAEAFHCHCGCACADEEECBABEFEHDFBFEEBBBCEFAFADACAFFCFDHDGBFFACDGDFDBBBCGCBAAAEAECGCDHFBDBCAAGACACAFAGGBEHECECEABFEGDFDHHAAAACHCHGHCHABEGCGFACCECFFBFBABAGFFDAECEDEFFACGCGAGCDFD,False +428,16.0,17.0,31.0,28.0,15.0,17.0,26.0,26.0,FGFCCACBEDEDBCGCGFDCAAECEAAFFGGGGHCHCAGDGDBHBHFHFHFHDHAGGDDADHDHBACGCGEDHBCDFDGDHDCCCBBBBGCCCCFBDDDBCCCHCFEHHGFBFCCAAGGDADGDHEHAGCGCBDBFBFEGAGEGHCFDHHHHEHEBEHDFDGDHAAECCCEDEDGH,False +429,8.0,4.0,6.0,7.0,12.0,5.0,7.0,6.0,AAHAGBFHFCEAEBECGFGFGEEECBCDCAEHEAEDEDHGHBCFDGEGDHDEDAA,False +430,5.0,7.0,8.0,4.0,4.0,3.0,11.0,4.0,HGDCHCBCBFGAGBGBEDHAEAEGFGCGEGAFCGCGDHDBBBCCGA,True +431,8.0,19.0,9.0,16.0,16.0,15.0,11.0,12.0,FABCEHHCGDGDFDFHFAEDGDFDFBBBBFEDEAGBEEEFEGEBEFDDGBBAAAFHFHEEDCDCGEDBDAEHEHBHBHBFGCDCHEDBFBGHGFBFBCBCGCBAHD,False +432,25.0,23.0,17.0,34.0,27.0,19.0,18.0,34.0,GBHHHFEGGFGFGHBABDBDBHGGEBBDEDHHHHAHFHEHFFFGBDDEAAAAADCDHACAFDBDCGCGDDDHAGBDHGHCHABAFEFEFEFDDBDBABGFAFEEDEDEAEBFDFDHAHABEBEDDDFHCEFEAAAECCBABHDADHCBFGDHEHAGBDHHEHEDEAECEDGCEEHDDGHCHCHEDDHBHCHCACBCG,False +433,11.0,10.0,8.0,8.0,5.0,5.0,7.0,5.0,GEEEBADHCHEBEACABDBDAHABABABCDCGCDABFDCACABGGAGHCHFFDDGFGFB,False +434,8.0,2.0,9.0,3.0,9.0,11.0,9.0,7.0,CECFFFHGHBHCFCFBFHDACEEFCGEDEDAAAGCGCEFFAAGGGHFHFHEGEGECAA,False +435,15.0,9.0,12.0,17.0,12.0,13.0,11.0,8.0,FEFHFAFEDEDBCGGFBHACGCFCHADADAFAEAEADHDBDFHEDEDBBGBDADAGAGEGECCHEAACBCDCEGFGFDADGHHFDFCCCBDGEFADB,False +436,9.0,4.0,4.0,2.0,2.0,7.0,7.0,7.0,HEFBABCEFAFABGGAAACFCFGHBHACGFGAGAGHHDHDHF,True +437,13.0,14.0,15.0,27.0,27.0,6.0,29.0,26.0,DDDEHABAHEHAHDCBGDHFCEGBBHBHADDEAGGEGDGDGCCDCDBDBHBHBAAHGGGGACECEGGGECCDGDGEGADADGFHEEDEGACAGHDDDFDFBEHCHGHFHEEEHEHEHEHEGEFDGDGHBCCEDHBCGDHEEBAGHGEGEGEDHBHCD,True +438,22.0,9.0,13.0,21.0,26.0,17.0,18.0,21.0,GAGEHFHCEGEDAFAHAHEDBDFDABAHEDGDBCAEGDDDGGGGAGEHHHGCCFHHBHBHBHAGECAGDGDGDGEHDFAGCEEFEHEAEAEFFCECFFFBDADFDADADAFEEEEAFAEEBABAHEFDGHEHFCDCDCECHCHFEAH,False +439,24.0,19.0,22.0,19.0,24.0,22.0,19.0,24.0,DCDCAAAAABAFGFDFDHGCGCGBDACCCCEHFACHEDAAEABAHABAEFHFCFCFBBHFHEHEGCGDHFECBBBGBEHEAEAHDGDGHCHFBFEFEBEDFAACDHDFBHADCCEHEHDBFGFHDHDGEGADADEDEBECHFGGAGEFCCBCGFBBAGEHFHGHEHEFECBGA,False +440,23.0,14.0,11.0,16.0,9.0,11.0,13.0,16.0,DCDGBGBAAHECEFGFGAGHHEDGBCFDFGHGEEFADAEGFBAAAABFBFDAACCCEDHHHDDAAEBHCHABCHAHAHABEDGFGBGDDDDDDGAAHACACACABFFHBHBHB,False +441,5.0,9.0,7.0,7.0,5.0,6.0,6.0,2.0,CFDBDGCADBDBDGAAEAEBFBCBFGHBEGDHDECECBCGFGFBFAC,False +442,21.0,17.0,17.0,31.0,26.0,21.0,12.0,20.0,AAAGDEAFCHCBEDDBDBDHCAAHBDBDADHFHFHFHFHFDFEADADHHCHDDCFBFACHDEEEDABADAFEFHCACFFFEFBBEHGDGEGFDDCDGEGECCCCCFCHDEEECGCFDEDGBBDBGGHBFAFEDADFDHEHDHAGDGDBAEEEBEDAHAEBEBEAE,False +443,22.0,20.0,27.0,22.0,26.0,31.0,22.0,17.0,EDEAHFDFEBGFEFHGAFAFEDEAHDFBEDACCCBCBAFADAHFCGHGHDCDCGGHBBGACADFEFEFBFBFBHBHAHAGGGEGAGACECECBAEFFDEECDFECECBCEHDFCABHBCGDHBFBFBFAEDCFFHFCFGFDEDEDGFGFGFBCHEGGCEDGCCHDGFGCCCACEDEAEABABADFDH,False +444,25.0,15.0,17.0,18.0,21.0,13.0,21.0,25.0,GCAFBBBBAFGHBACAFHCECHBEDEHHHEDAHABCGDEAAABDBHAHBEGGDGACDBGGGGHGHGCECEFHFCCGBEEEEEDFCGDGDADADCECBFFCAEAEADGDHAHAHEHDHAHEFEHDGFHFHBDDAHAGAGAGAGEFBHECFCACHDH,False +445,4.0,5.0,1.0,1.0,6.0,3.0,0.0,1.0,FEBBABEBEAFHFEAEAEBDC,True +446,3.0,5.0,3.0,4.0,0.0,2.0,5.0,1.0,DBDAGBGCGCGCBBBAGFDHDFA,True +447,27.0,17.0,19.0,29.0,21.0,26.0,19.0,16.0,AAEEEEFDFHEADAGFGFGAGHFABBBBDADAHFDGCHFDFAFGCCBFFHDHDADEBHGCAHAFCCGCHEEADCBFFDFAFACAEECDCDBHBDCCEDEAGABDBDGGGGHFHFHDEAFDCDAAABAGCGFDFEEEBGAGAHBGDGDFDFDHHACCDCEBEAECEFEFDFDBDB,False +448,12.0,3.0,7.0,7.0,6.0,6.0,10.0,15.0,GCACACAFHFHGHDHAHDDEDCFAHACAHGEFHBHBFGDEHEAAAGAGCDAEGEBHDGFGHHCHGH,False +449,27.0,20.0,31.0,20.0,16.0,31.0,25.0,16.0,CCFCACAHBDGCGCBCGCDCBBEBAGFFFCFCDCBHBEFDFDHGGDCFEDBDFDCDCFFDBAECHADBCHCHCAAAAFAFADDGFCECGCGDDEHGHFFEHGHGFGFGAEFBFEFDBHAFDGGCFAFHHHBHEAGAEAEABGHFAFACACBCACGBBAGACAFFGFGFDBCBCGEEEECFADGBGA,False +450,2.0,7.0,4.0,2.0,6.0,1.0,3.0,3.0,DGCGCBDBHCECHBEGEABFBHEAEBEB,True +451,8.0,7.0,6.0,1.0,2.0,4.0,4.0,3.0,FGFHEABCCCDBABAHCHEAGCGCBAAAABBBFGF,True +452,12.0,16.0,17.0,11.0,29.0,15.0,19.0,16.0,EGDGEGHCFCFDDBECFHFHGEBEBEBEBDBAHAHADCEEEEEEEBECCBBBGDCDCFGHHEACAGBGHFEGEAECFDEGFHCEDFDFDCBHEAEAEFBGCGBAHFHGGEEBFGFGEHAGAGAFCBHHHCCECEG,False +453,4.0,3.0,6.0,2.0,6.0,8.0,4.0,3.0,CCFCEEHCHBDEFAFAFHGDFEGEFBFBFCECGAGA,False +454,17.0,13.0,25.0,22.0,19.0,16.0,28.0,27.0,AGAHHCDEDGGGDHHFEEGEHHCGGHGABCDCDAAFCFCGAGCFFFHEEEHEBGBCFHDAEEBDCDCGCGCBHBFCFHDHGBGDHCHFHBHDHBEAFCCDEDAGCGCDCFFHGHGHGAGADACAEABFCECECEBEHAGAHHDGDGHGHGFDFDEBCHDDCDGBGEA,False +455,3.0,8.0,5.0,6.0,3.0,3.0,1.0,4.0,ADHHHDFFACBCBCHCBDDGDBDBEBEAEFCBB,True +456,17.0,25.0,25.0,21.0,21.0,26.0,24.0,21.0,GEGBFBFBFBGAHAFACDEDCCHFFGBGAACFCHGFCFGHDAEFEFGFGHEBEBDAFGFAFCCBABEHCGFEDEDGBGBFBEHEGGCDCDCBGHDCCCDFAGBHBDEDHCHCHEHCBCDDDDFBEEEEGGBFCFCHAHACGFBBHDHBABGBGDGDFAFAECECEFDFDBGCHBAAHHEH,False +457,12.0,10.0,8.0,8.0,4.0,11.0,8.0,8.0,DBDFDFCCCHBEGFBHEFACBDBGHGBFAFGHAHAHGDDDCCACGCEHGFGFBFBABABDHFAAAEAFA,False +458,20.0,11.0,18.0,22.0,26.0,28.0,20.0,28.0,BFGHCHEAEAFFFFGABCFGFECECECECHCHGHDHAHEEEFHAAFBCGHDHDHCABGHCFDGHGACFDDDBCGDDFGGGGEEABGFAFEHAFEHAFAEAEABAGFDFEEHEFECDADHDHBHEHDHCHFHDHFHGDDDDEDEFEFGDCHCECEFHFAGBFFEFCADGBGBHA,False +459,18.0,25.0,19.0,16.0,13.0,17.0,21.0,14.0,CACACDEDBCBHAAGHBHBCEDEDAGGHDFDEDCHFHECFBFACAHAGGGGGAGDFBABFFGFBHBHBGBHBACABHBGCGBGEFADCDCHAHDHDBACABBBGEGEFCFBGBEFDFABABFCEGECDCBCGDBEGFFCFDGE,False +460,21.0,19.0,19.0,30.0,29.0,19.0,23.0,32.0,FDEDECCDEEHFDFEFEFHAHDCGCGCFDDDCGAGAECDHBEBAHGCGEFEDHDHDGDBHBADCDCHHFECHBGBEHADBDHGHGHGHDHFBGAGHBFBAECGGFEFEFDGDCDAEGEBACHGGDDADFHAEABBGBABDFDFABEDAHBHAHAEDEAEHEHCFCHEHEHBHBHGGCACAHEEEEFDFCGDH,False +461,9.0,19.0,19.0,25.0,19.0,17.0,20.0,16.0,BEGCGDAEHEDBDCEHECACAEAEAFCEGHGHFHGHCEDDDHDEGGFEHEFDFGFDBDBDGDEDCFCFHECBDHACCBCBFGDGCHBHDDBGBGFCBCDDGDACFGGGGFGBEBEGHDBDFCFBFDFDBHHAHAEDFBCBEBEC,False +462,9.0,14.0,11.0,15.0,9.0,10.0,15.0,17.0,CHCHCGCBEBDHEHFBGDGDGDGDBDGEGCHHBDBDACFCHGFEAHFFDCGAGBFHEDEHHAHAEBHBHGAGBFBDBCFCBCBADAGEGHHEFDFDGDAH,False +463,15.0,16.0,16.0,16.0,13.0,12.0,15.0,14.0,EDEGEDHBHDHDACHCBCAHADGDGAEEHFGFGFAEGEDECGGAFAFDBCHCGCEBABABABDEACHCBABAFGEACFDBBCBEGEGCDCDADBDFHHHHHBDCDGBFFGFHCBCFG,False +464,20.0,13.0,10.0,7.0,14.0,12.0,14.0,15.0,HHHBDFFCHCGCGAGDFDGEBFBABAFAFHGHBAGEGEHBACFCEDBACCCABADAGBGAGEEAAFAFACGCFAHEHEDEBAGEHEHEGAGAEFHHHHABEBDBF,False +465,32.0,28.0,23.0,18.0,15.0,22.0,28.0,21.0,CAHHBFBGCACEGFGAAABABAGGCGCGEAAGCGEEDBDGDCDHDBBABAFABAEDBGCEDBDBAHABFHEDEDBFFGAGHHEGAGHEECDCFBHCGBDBDBFGFDFCFAAACACFGHGAGDCFGAGFFBHCHCEABHBFBFHFAFHFEFBABGBGBGHHHAHAGEFCCHBHCAGBCDCECADADAG,False +466,14.0,31.0,26.0,20.0,17.0,27.0,15.0,13.0,BBBBBCGFEFDFDFCCDCHHDAFADACCEAGGCGCACFFEGECEFECCACGEBAGDGHBABDBHBHFCBHFCFCAHDCDHBGFEEDEDFAFHHGBBFAFCCCFAFDFEBBABACHHBDBDBFBCCFFFFFFDBBBBBEBECEGEGDGDGEGCHEBCDFBBBDD,False +467,15.0,12.0,15.0,11.0,17.0,18.0,18.0,13.0,HAGECCBCFHEGGGGBGBDBGBAFACCFCFCBDFAAAAACEEEFECDFDCDCDHBGGGFGDABAGAFFEAEFHBEDEDEFBAHGCGCHFGFGFHHDHECEAEGFAFHHEHEBBGEHFDC,False +468,22.0,12.0,14.0,17.0,19.0,18.0,16.0,15.0,DADADADAHAGABAEHFGFGEGBHBGADHDGGACHEHCHGEFFBCGCAFGDGAEHEAAFCFGAHAHEDDFDCHFEFEDEBECABEFGBGAGCCECFCBBBBHAEBECCADEDHHHEDEDEDFFFFGDAAAFCF,False +469,18.0,26.0,29.0,20.0,29.0,19.0,16.0,15.0,CGCGCHCFCGHHCHCHCHCFAEAFFECEBFGDHDCECECHCFFDBDEDBGGEGAGEHBBCCACABEEEAEBEBACECGADBBHBDBEFEFEFCDDGCCBAHHFCBHBADAGFDBEFEFEAECBFFHABDBAEDECECEDBFBDBDBDACGEGEBADCDGBGDGACFEFBAEH,False +470,6.0,1.0,5.0,5.0,3.0,4.0,4.0,6.0,CBCAGGHDHDHDHFHFEECACADHCAFAFGEADG,False +471,8.0,12.0,3.0,4.0,7.0,8.0,8.0,2.0,GAAFBEGEFDAGEGEFEHGBCFFFFGBBBEBABABDBDBEBDHGCABACAGF,True +472,9.0,4.0,9.0,5.0,3.0,6.0,1.0,7.0,HACGCABHCEAFHBHDAAACFCBEDEDADAHFHFCFAFBCDCHC,True +473,2.0,1.0,5.0,2.0,7.0,3.0,2.0,10.0,CCHCDDGFHAEBEHHFACHHFHEHEHEHECEG,True +474,8.0,7.0,5.0,9.0,9.0,4.0,1.0,12.0,BCDHBCBADCDHHAHDHAHEDEDBHEEDHCHAFAHAHCEGDADEFEFEFABHBEB,True +475,11.0,5.0,2.0,1.0,3.0,2.0,5.0,4.0,AACDCFHAGAGAEBGBHBFEAGBGAAAHAHABE,True +476,25.0,30.0,25.0,21.0,26.0,22.0,25.0,24.0,HGHEDBDBCHEHEDEDEDEDCAHDCGCFDFGEGDGAGAGHGDGDCAAHABAFACBCBCEDEAEDEAGDFEBEBEHGHFHFCBBFGHGFEFBBBFHGBCFCEBABADHBCACGFHFACACDFABHEAEHHDGACHFBFBHBHBABGGDBABGFEFBHGHAHEBGBGCFBEBECGCACEFAGECACFDFEAECCBGHCDD,False +477,15.0,14.0,22.0,19.0,17.0,22.0,25.0,22.0,DFGGGFHHCHEHBGDEEBFBAAHGFGFGACCCGHFHBHCDEEFEFBFAFBFCGCEDEHEHEBFAFAFAFGCGCGDBCBFFCHCDDDEAEAGDEDECGDGABBHDHDFDFDGCGAHEHFHCHAACDDBHHACBGBGAGFFHCCGHHCCGDGDGCGEE,False +478,14.0,12.0,9.0,13.0,13.0,17.0,7.0,13.0,AFAFBFBDAAADFFBFBEHGFEFHAHFGDDFDHAHADABFBFHEHECCACGFBDBGAEHCDCHGHGEAECECEFECADFDBGBHBHEHDDFEFDBEAC,False +479,29.0,20.0,16.0,24.0,27.0,18.0,17.0,26.0,GEHHHAHEGBGCHCBCFGDGBFDHCCBCHFHAEFEGGDHDACEDDDCDFDFDHBAADHFHBEFEHCHCDFAFABAEGBHBABABAEHEAEAEDEAFHEDAGEBEFGCEDEFEDHBFFDFAHHDBDGDHEAEGCBDEDBAGAGAGAEAHACACAEAEBHAHGFGEBEADADBHBHFCC,False +480,11.0,14.0,7.0,9.0,18.0,15.0,6.0,9.0,FAFEGDGBBEFEDEFEFABAGEGEFFFBBCBEDABEGAAAFHFDEHHFBFDFAFCDCDEGHHCHBABCBEHEHEBEBEDEHABEFACDC,False +481,8.0,4.0,7.0,16.0,11.0,8.0,9.0,4.0,EEADADFDEAFBFGEGFGDGCHDDCDEBEGEGCFCHDAGCGDGAECFCEDDFDEABABADDDDEHFH,False +482,11.0,7.0,25.0,5.0,16.0,24.0,10.0,11.0,EAEAEACFCBCEFEGAGAGCCFFEFGBCFFHFCFAHACFCEEHCCFDFEEHBHFHAGFFEFEBDAGCGFAFEFEHECGCGCFCFHFHCCCBCDDBCCCCFDFHAECBHG,True +483,24.0,31.0,31.0,29.0,20.0,23.0,19.0,21.0,HAHEECBBBBGBECEFBFHHCHFHDBGBHEGEADAEAEBBFBCECFCACABHCHCEBFDFCFCFBFHHHEGCDCDCDHDCECGABADDDBAGAGAHEDEBBDGCBCFAFABAHCBCFHGHBDEDGBGEHCDCFCFCAHFBCDCDGDHABGFEBDBDBDGAFAGAFDDCEFABAFDDGAFEFDGCBABHCGDGDCDCAE,False +484,10.0,14.0,9.0,7.0,6.0,9.0,6.0,9.0,HCACBFBFCFCFHAHADACABDCHGHGCBFDHCBGBABFBDBFBEEHADADHBBEBADAGECEFHBGEGF,False +485,10.0,4.0,11.0,5.0,13.0,7.0,15.0,10.0,AEAEHCHCGCGCBEGEGFGBGAGFGEHAFGCHDECCAHADDFDFHFHEGEGACCBHDHAEGEGCGHBEEEGAFAC,False +486,10.0,4.0,4.0,3.0,10.0,7.0,9.0,8.0,HGHCFDHAFAECEFHFHEGECHDDACABAEEEGGAEAGAGAGAHFGFEHEFGBBB,True +487,5.0,6.0,9.0,7.0,10.0,8.0,5.0,12.0,FCFCFHFAFAFGEDCBEHHGGEHEHAGBHCHFEAEDEDBHADCBCDHDHDFBEBCCHCGEHE,False +488,11.0,11.0,11.0,8.0,15.0,8.0,13.0,12.0,CBABEBFHFGEGHCDCAGDGEABBCGGBBHEFBBABGBADEHCHCEAEAEGEFFFCGCEHDHDHECDCAFAGAGAGEHEGFDHCHEHED,False +489,22.0,25.0,26.0,26.0,18.0,25.0,28.0,23.0,BEBEBEBFFHDHDHCHDHCCGCFAGCHCHCDCGCABABAFCHEHBCBCDCGCEHAHAEGGABFDHEBECGCHCHFDADAHHEGFBHAHFDGDCCCHFFGGGGBFAFABGFEFAGGFGDBAHFEGEGEDBBEDDBHBDFDFGGCEFGFBFHGADADHCEGEGDGDFDBBCBCDGBADABAFCFAFADDDBCGAE,False +490,19.0,24.0,22.0,16.0,30.0,19.0,23.0,31.0,FGGAFEFECGHHEGEHEDEFEHAGFBFBFHAEAHAEAEACDEBBHCECACEGBBFBDBCHDHGCFEHHAHAHBEBECGGDGCHBHGFGBDFCGHGHDHBHBACACHBEAABDHEHDHFFBFHFHEBCDEDEDFDGEGAGADBCHFHABDBDCFAEAEBEBECGCGEHHCCBCHCEGEGHFCGEG,False +491,16.0,23.0,19.0,29.0,31.0,20.0,28.0,25.0,DHDBCECECAGFGBBEEEECEDEGHCDGGAFDFGFGCGCEHGHGEDFGCDFGFDDDCDEFEABDEDEBEBHBHBGGHBDBHAFABDGHCECGAEAEAGABHDHDHDHBBBGEHEFEDHBEEEGGCDEFGHGHAHAFCFGFEDCFEABHFHEBEBDHDHACBCFGAGFGHEHBGBCHFGDDADCDADFDECB,False +492,2.0,8.0,8.0,4.0,4.0,4.0,9.0,3.0,GEGFACBGAGECCHCHCBFDGHCCGCGBDBDBEBEFDFBGBG,True +493,21.0,13.0,20.0,26.0,11.0,13.0,10.0,15.0,AACGHHEEDBDBDCDCDBEBFBFEGDCEADDDFAFAEAHHHFAFADEDCHCBCAAGACDDDDDBCAGDCDBEHGHGFGABDHDHCCCCHADAEAEDHDAACAFAFBFEDGBHCCADHBGBDFCFCHCFG,False +494,4.0,3.0,5.0,3.0,3.0,7.0,4.0,3.0,AHFEBAHCHGFGFEFDADBFFCFCGCGCBEAD,False +495,0.0,4.0,1.0,1.0,4.0,0.0,2.0,1.0,BDEEBEGEGHBCB,True +496,6.0,16.0,13.0,12.0,12.0,13.0,12.0,10.0,DHFEEBAFCHCHCEFHABBCBCFGECECEGEBDCDCBBBBFAFEBEGGCGAGFHEDGBGEGCHEBDBHBHCGBHAGDFDFDFDFDHCADFDFGB,False +497,19.0,9.0,12.0,22.0,14.0,24.0,20.0,18.0,DEDAHEBAAGDBHHGABAGCHCDCACFCGCEEACBFAFAGEDDDHHHCHCGFGHBAGAFAHDDDDDGDFDFHFEEDEHFHEBFDFHBAGHGHFHFEDEDFDFDCGBFACAGAFHFEABGEGFGFGFECADAGGDGFFF,False +498,8.0,3.0,6.0,14.0,8.0,17.0,6.0,15.0,GFFDFEGGBEBHAEDGFAFEFDDDAFHCHCDCDGFHAHFHFGDHCEFHCHCFDHDHAFDFEFAFABAEHFHDHDEDH,True +499,0.0,6.0,1.0,2.0,2.0,3.0,3.0,4.0,EDECHDBGBGBHBHFGFBHBF,True +500,9.0,11.0,8.0,10.0,19.0,12.0,9.0,5.0,GCFDBACGFBFAAAAGBFAEGFGCGHEAGHDFFCEDEDEDEDECHBEGDDEAEFDFAFEBEHEHEDEBEBEBCBCBFFEGBCE,False +501,8.0,14.0,12.0,11.0,8.0,12.0,9.0,4.0,DBDBEBDBDFDAGCGFBCBCFFGCDCDEDBBBECECFBFECABDDAFAFAGEFBHAGAFCHCDCGHGHBFBEGEFCAG,False +502,5.0,5.0,5.0,5.0,9.0,6.0,4.0,8.0,FEFEBHHHAHABEBDDFDHDCAFFECEAHCBCEAEBHGHGCGFDEGE,False +503,12.0,12.0,13.0,25.0,16.0,10.0,18.0,21.0,GBGBDECCCFHHBACGDGDGDADCGCBBHDHDHDBDFDFDHEHGCEDEGEFAFHBEFFGCEHFFDDHDHGHGDAACAGBDHGHEDEDGAHCGDGDACEGAHAHDHEHEBEBCBFBEHEADDGDCAHE,False +504,10.0,15.0,9.0,13.0,14.0,7.0,8.0,9.0,CBEEFBBGBGBDBABADFBAAHEBEDEDGFCEBDBHAHBCBCBGGFDFCAGAFDGDHDHGEBEHFHECECEAHCDDEHEAEADCD,False +505,18.0,16.0,17.0,23.0,12.0,18.0,20.0,12.0,FGFABEFDHDHFHGDBDBGBGCACDDDHAHBHFFFBGCGEAEAGABHBGDGCECEDHFAGBDEAAHCEGHDEDEDFGHDDDDEFFAFGDGCFCFDFDACFCEAABGBABCBCFHGGBGEGAACCCCFCGBADADBD,False +506,22.0,16.0,25.0,22.0,25.0,11.0,27.0,18.0,AGCDCDHDBGCGAGDDCDGBGDCBCGFGHCECGHGAEFEDEAEGEFHGBCBCAAAAGGDGEHEAEDEDEBCBGFCFGDDEDECFDHDBEAEDEHGHCCCCABAFABCBAHCHGHCCDCEFAGEHAGAGHEBCHEGBHBHDHFEEEACACDEDEHGGGFBFBGDAAA,False +507,13.0,17.0,22.0,10.0,17.0,14.0,17.0,13.0,GGGCBBBEBHAEAGHDCGCDHFEAEABHCHGFGHGCCFFBCAAHEHEDCGCGCDADEHAHFDFAFCHCFCBDEEAEFHAHFCFABBDBDEGECEBGBGCGCDEEBEBFBEACBCGCGBGCFCF,False +508,17.0,21.0,24.0,12.0,17.0,20.0,19.0,17.0,ECHCHCHCGCFBGAGEBEBEBDCCFHFGCDFFHHBGBGDDDGFCFCGDGFAACACGFHDHGAAHAEBEGCCCFGFADADHBBBBABEBEBCGCHDHBGEHCACECEDDCFFAFEBACAEHEHBGBHEFAFBGHGFBCBEAEAGFFCF,False +509,4.0,0.0,5.0,5.0,1.0,0.0,3.0,4.0,GHDCDCDCDCAEHGCDHHAAAG,True +510,10.0,11.0,3.0,4.0,7.0,2.0,18.0,3.0,HAGGGGAFAGCGEGBGAEBGGEBEBDCEGDBDADEBEGAGAGBBBCGGBGAGHBHAFA,True +511,2.0,4.0,2.0,2.0,1.0,2.0,3.0,1.0,DEDFHGABBBBFAGCGC,False +512,2.0,4.0,2.0,1.0,1.0,1.0,0.0,1.0,HDBABCBCBFEA,True +513,4.0,5.0,8.0,7.0,6.0,8.0,11.0,4.0,GGHGHGDBCECECEGFHDABADEGGCGCECBFEGACFFFFBFCFHBAGGDDDD,False +514,20.0,26.0,19.0,15.0,24.0,22.0,24.0,21.0,FGFEFEFBHGHBEDHHHHEDCDEHEHCBFHGAFAFBFDCACAGGGGGGGHBBABFBFBCHGGBACGCGDFEEEEAEFFFFDECECFCBCBEAHCBADEDAGFDEDBBEBEHACAFAFABHEEDCFGHDAABEBEDGGHGHGDDFEFAHAHBGCGBGCCCABBHBAGCBHBE,False +515,22.0,23.0,26.0,33.0,16.0,30.0,25.0,23.0,GGGGCBEHCBCFEGGFADHDHCGDACCDBDGFCFHBHGAABFBAHAHDGDBDADACGCFDFGFDDHBGGGEBEBEFGFHBEFABEGCGCGHAHFHFHDBDBDCDCDCHFFFHFDFAGEGBABFEDBDCECBCDDHDBGECADEDEFFFFAFDFDECGHDFDFBCGFECHHAHAHGCBCDADAEAFCFCDHDABAHABC,False +516,17.0,13.0,13.0,12.0,15.0,20.0,10.0,20.0,FDFAGABHFHCEEAFCEGGBEBCBCBEBDHFACGHGCACACAHFHDBGFGDAEAEABFDEDHDFAFEBDHHHFHFHFHAHAHAEAFADCCFBBCEHFFFDGDGBEHHHHGCBEFEAEDFC,False +517,26.0,21.0,23.0,17.0,23.0,30.0,24.0,22.0,ABAEAEAEBGGGGGAECECEDFCEBAGHFHAEADCCGGGAGBEBEBEDCDFAFHFHGCCBHAFAFAFHFGBCDDFACGFGHDEEGEFEGBGFGADFCFCFCBAEABCDHHHCHFHFHBHAEFFFCFBECCCFFDFDBCHCADAFHBABDFDBBAHGGEAEHCGEGCDAGAHDGDFHFHFEBABEBH,False +518,7.0,13.0,9.0,12.0,7.0,6.0,7.0,5.0,CGCECBHDEBGBAFCDBDBDACEBDDGDGEGEFAFAFAHCFEHEDBCBDBDCDBBBDCHFBAGAGH,False +519,15.0,23.0,14.0,11.0,17.0,17.0,14.0,16.0,AFGEDCHBBBBBBGGECEFFBACACBCGCBHFAAABCCEEDDDHBBFBFBGEHEFDAEAFFFEHAGABAFHFBDBHHHBEBEACGCGCACDCHEEBEGGDGHGHGDDDCBGAEBEFEFAFHHHFHFB,False +520,18.0,12.0,17.0,12.0,18.0,12.0,16.0,36.0,EGEHCHDHDGDGCADAHAHFCEEBACEEEADAHHBCBEHEHEBAHCEEGCFEFAFABHBHGHDCGCGDHDHFHDHDHAHCHABCGCFBHHAHFHFHFCEHEAAHHBHGEAHHBFCCGBGFHAEAEGCHBHGDGDGAGFHHC,False +521,4.0,11.0,9.0,6.0,9.0,15.0,6.0,12.0,FFFCCHBHCFCBCBFDDGDGBFAGCFEFCHCGFBBBHCHDEDEAEBHBHGAEAFFBEGEHEHEHBHFFFFHD,False +522,17.0,10.0,12.0,14.0,22.0,13.0,17.0,18.0,EEEEDEABAGFEFEHGHBDAAABDBDAEHHAHGHGHDHAEABHHHHHBCGCFCFCDBAGACEEGCGAADGDHAFCFCEBEFDFEEACGHBEFEFEFEDCGFGHGEGDBAEGEDCHAHGDFDGC,False +523,0.0,4.0,3.0,2.0,1.0,0.0,4.0,2.0,DDEBCHCGBGCGBGBH,True +524,25.0,20.0,21.0,11.0,21.0,16.0,21.0,28.0,FGHGHEHEHBHFHFBFBDBEGDCHCGAEAFCDEAAACHEHEHBFFFFAAHCGGHGBGBHCHCDCGAGAGBHHHFDCDAEABBBCECBGGFACHCECEAFAGHFAEHGGEDEDEBHHACCCACBCHDGDGAAABAGFEBHAGBGCFEEDEAEAFBECHHAHBHB,False +525,5.0,5.0,3.0,6.0,5.0,16.0,3.0,8.0,DHFHFEFEADAGEGECBDFCBDDFHCHFAAAFEHHFBBBGDFFFFFFFHFH,True +526,1.0,0.0,1.0,1.0,2.0,0.0,4.0,6.0,HGHCHEHEGGHGDAH,True +527,14.0,26.0,15.0,11.0,16.0,18.0,25.0,17.0,BHFABADGFABCDGGECEBEFEDBDHGFCFDBDBCEFBFHAGBFEFGFHFHCHBHEHFHFHCHCEDBDBEGHGHGCBCBGDEEFCFBGBGBGBCBDBGAEAGBGAGECEAFGGGHGCCAFGGEAEDBHAGABAFAGHHCBBB,False +528,26.0,33.0,22.0,21.0,21.0,26.0,21.0,23.0,HDBFBDGDGHHEBFFCECFBABGGEBEGGAHEHABGBCCCABDFEFGFADACCGABDBFBADADBDAHAHBEGHFHBEGEBCBCBHAHABADCHBGCDEDEDHGGGGGCDBFFFFFAEECHCHCFEBEAADFBFBABDBGEEHEGEFCFCFEAEADCGFADHHFBDBAHAHACABABFBFCFHBHBHCDFGCD,False +529,19.0,28.0,16.0,26.0,16.0,17.0,19.0,17.0,ABADGCGBHDFFFGFGDGFBDGGFAFCGGFHHAAFFFEAAHAHCBCBABADDFFFABDBDBHGDACHCHGBBBBBGEDADAGCBEBHHEDBCBCBDEEGADABABADADCCBCBDFDFCBCHFEEEDEHHHGHBHDEECHGDGDBEEEDEDGDGCBBD,False +530,10.0,4.0,8.0,6.0,5.0,11.0,7.0,6.0,FFBFCDCGAGFEDCDBEGEGFCFCFCBAFDBHAHAHAGACAHAHEGDFCFADEGAFH,False +531,13.0,7.0,11.0,9.0,7.0,13.0,13.0,17.0,GCABEBFBAHHHGHGAAHCHBEBCDAFHFHBCDCDCDFGEGCHAHEHCHDFFFGFGCGAAAHGGGHFCECHHHGAAEADFBFDFDEDAGF,False +532,6.0,4.0,4.0,4.0,4.0,11.0,3.0,7.0,ABCDHFHFECEDADFGHAFCFCFBFBGADEHGBFHEHFHFAFA,False +533,14.0,30.0,24.0,27.0,22.0,23.0,21.0,29.0,CEBEDGCHDGAAABHEHGCGBFBEGDDDCDCHHDEGFHCEFBGBCCFBAEAGABEDFDCDCDHDHGFGHGCGDDFBBBBBDFDADCDGBFEFDBCFCFBDHDGFACAGFDFDEAECFBBHBHCACAHFDEHEHBDBGBHBFBEDCFEEHBHBCBCBHEFEFCHCHEAFHBHBHEHFGCAEGHGHGHGHED,False +534,7.0,14.0,11.0,10.0,12.0,6.0,11.0,7.0,ABADCBEGAGABDBHCECDBEHGCBCBCGCFCFHFHFBBCBGEGHGDGEGEDDDCDEDABAHCFEEAEFEBBGDEHBG,False +535,1.0,8.0,7.0,5.0,5.0,7.0,1.0,7.0,BHBGFHEDDFCBBBBHHHFEFHFCFCACBDBDEHEFECCCD,True +536,5.0,4.0,11.0,11.0,13.0,6.0,6.0,8.0,CDDDEBHHGHDFGCCACEDEDECEGEACACHEBFFEFEFGFGDGDHAEEEABCBHEDCDCHHDC,True +537,28.0,21.0,11.0,18.0,13.0,11.0,21.0,19.0,HGAGAGFDDHGEBDCGAAHGHEDBDFDEGAGHDECCAAAADDGBBCBHBHBHGCGCBBBFBFGABAGCHBGAFHFAACAGDFEFEGGBFHAADADFDADBBBDAEAFHGHEHEHAHAHAHAGEGDCDCHBABABECDGAEBE,False +538,3.0,5.0,4.0,4.0,5.0,2.0,1.0,6.0,HCHGHAFBEBEAEACDCHBEBFCEHBHDDD,False +539,6.0,6.0,7.0,4.0,9.0,4.0,6.0,1.0,CCAGDGDGEFBCACBCGDDBFEFCFEABABCEEEABAEGEGEH,False +540,4.0,1.0,2.0,4.0,0.0,6.0,5.0,0.0,FDDGAGFGCGAGAFFFBCDADF,True +541,9.0,14.0,13.0,6.0,8.0,6.0,10.0,5.0,CBCGEGEFEHAGEDBGEGAGHDCBCGAGAGHDFGAACBBDBDFFCFHFDACACBBEBECCCCHEACBBBBB,False +542,16.0,16.0,8.0,16.0,13.0,11.0,10.0,17.0,EAHAGFDCGCGDEHCHBAAADHDHEHEFBGBABFDAAADBDADADHDGEGCGHGBFAFEBBBBHFDFDEBEFAHEBDGFHCHCHGDFABABDHHHAEBEHEDEBCCF,False +543,21.0,26.0,17.0,27.0,29.0,23.0,26.0,18.0,GDEHHBFFAHDHDCBHBGEDBDGAGDHCEEEBFFACBBEDGFCFBEBECAFDDHBHDEFEFEFEGGCGBHFFCFEHBHEFBHBADAEAGAFBFGEGEGCGDEDEGCGCBDFDFDADABCFEBBBDBGGGFGCDCDCACFEDBGEGEGHABGEGEAAAACCHEBEDEHBABFGFHHEHADGDADADAD,False +544,22.0,22.0,21.0,19.0,23.0,23.0,21.0,20.0,CGDGDBCFDADCCGDBDHAHCHCEDFFGGGECECEAFAHCFDDEDAGCGCBDEDEAEHCHCEEECEFBFHDHGHGEGCHFEAEAEFFCFEDEABHHHGFBAGAGBDEGECECECHBHAHGBBFBGBDFDGAAFAFGBBCBGBFHEHCBDFFFHFBAAHBFBAAAFAGABDB,False +545,23.0,25.0,25.0,15.0,25.0,17.0,21.0,33.0,GAGAGEEHHHFHFHFHEHDCFHABBHBHBEBHFGBCCACACACGHBADHBECECEBABECCHCFEGHDCEBGGEBEBEFHHADCDCDFDHBHCAEEHEHFHGHGHFADCGFHCACACACBCEGDFHCABGDGEGFCDHGHAAAHBHBHBEBHBHAGABEEGEDEGFBFCGEDAGADDBBEAFCF,False +546,3.0,2.0,2.0,4.0,0.0,4.0,0.0,0.0,ADADAFCFDBBFCFD,True +547,13.0,21.0,3.0,11.0,13.0,5.0,12.0,11.0,GHBADHBHBGBEHDHEEFGHDHGFEDDDEGEAEDFAAGBBCBAGAGAEDEHBHBABABAGADBEBECEAEBBBBGBHBDFGCADBFBHG,False +548,25.0,24.0,22.0,17.0,28.0,18.0,39.0,21.0,CDCABDBHBGBGBGBCECBABGBGAHAHBFEEAEBGAGEHFACACDEGEGECHAEGEHFHFABEGHFHAHGHCDCEBEGDBFAFHGEGBGAGDBDBDBEFECHFHEBFGEGEGECAFABEBGBGHGFGEGCCCCHGFACGBHAHAECFGAEDHGHGDDDEAFADGDGDCAEGGACFBFAGEGACCEHDCDGGFG,False +549,3.0,2.0,4.0,4.0,5.0,8.0,5.0,2.0,HFEFGDGFBFDFEEEFEFGBGCCACDCAGAHFD,False +550,1.0,3.0,4.0,3.0,7.0,2.0,2.0,6.0,ECEBHBHGHBECEFDHAHECEDEDGCHF,True +551,16.0,22.0,21.0,26.0,28.0,20.0,19.0,21.0,EGEDEBEAEADDDCFCABGEFFHDBECHBBBBAHAFFCCDDDDDDHGHEFAAAAAGGBGFGBGCCHEHFBFHHDCDFFBFDGEGFCABBEBEBECDGFEECACDDBCFEDEHHDBDFHFHCHCEGGGEGEADCDCEGEFFHHGCCBCBDBEBEAEAEAGDFHCDGDHBHEHEH,False +552,4.0,5.0,6.0,11.0,3.0,11.0,11.0,5.0,GCCDFHFBDDEDECGCGDGHABDDGGGDHAHAFGFGEGFGFABDFHFCFDBDBFFC,True +553,5.0,13.0,12.0,7.0,6.0,1.0,8.0,8.0,BGDACECGDGCCCBCHCGCDBHHGBEAEAEFBCBEBDGCGDGCBABABEDCHHHHHBBDB,True +554,21.0,23.0,19.0,23.0,24.0,21.0,32.0,21.0,FAGAHAHFHGHBEEFGADABCBGBGFAHEDEFGFBHCECEHEHDGDEAAHGGGEGFFDFBCHGAGHCDGGGABDGDADHFEBHBHGGCACBCBCBGBCFADADGDEDACBGHEFDFHFHFBDDDDBHBGGGCDEFEGEGECHCBCBEBEBEFFAGBBFACECECDAEFECGAGEFDGGAADHDH,False +555,11.0,14.0,17.0,9.0,22.0,14.0,9.0,22.0,CGEEDCDADADBDBFFFHCAAEHHHEHEHAHEFFCFBGHHHFHCHDHEBGFGFBEECFCEEECGCGHEEEEADHBHAABCCACFCEDHCHCHBHBDBECGCEFFGFABBEBEGHAHBE,False +556,4.0,3.0,4.0,4.0,4.0,1.0,0.0,1.0,BABHECAAFBDCDEDEDECAC,True +557,11.0,15.0,15.0,16.0,14.0,18.0,14.0,14.0,BCBCBGDGCGEAHHEHGAFFCFHFCGAGACEBEBEBAFGCCDGBCEFDFDAEADDFDCEBFBFBEHDHEHEGEGBGHFHDDDDCCBGBCBHAHDEFFFGGCHBEAAAHFFDFDFDHC,False +558,5.0,2.0,3.0,3.0,1.0,2.0,3.0,2.0,DGDGACBFHFHAEACABACDG,False +559,29.0,26.0,17.0,17.0,20.0,26.0,24.0,23.0,DADCDFFHFAFACAFBDBACAGABFGFBHCHCFFEFEFGHGCBCAEGGGDBDBABFHFAEADDDEDEHAAGGDBHGFFFFCGAHBBGBGECEGEGEGEBEDCFFDFCCEAAFDHAEBFBFAHAGFHCCGBGBGBGAGABEDADHEBEHHAEFHAHABCBCHAEAFAEBHGHBBBAGDHHHHC,False +560,7.0,9.0,14.0,11.0,8.0,12.0,13.0,5.0,FCDCEFEFGHDAABACGCGCGDEBAHHBCCFCFGEGDBDBDBAFECDFDFEGGCAFABCFGFGEGHCDEDGDGFCBCBH,False +561,16.0,32.0,21.0,19.0,21.0,20.0,22.0,22.0,AFBGBGHGEDFAACDCDCEFEBCFCGHGHFDABABAHCCEAHBEDEDBDCCHGHEBEBEBCDEFGDGFBFEDHDHDBBBFFEGBGHEDGDFBGBACDGEBEBHBHCCGHGHGDGDGHGHBCAFHGHGFABAFAHAFCBCBFAHDHBBCBGFEBABCBCFCFEEBCFEDEAHBE,False +562,18.0,21.0,6.0,6.0,14.0,3.0,15.0,20.0,DGAAHCHBAFHBHBGCAEAEAHAEAHHHBCBGGEBDFAHAEAEBGAGAHDEGHAHBEAEGHGHBABHBHEDCGHGBEDGBGEGBGBABDBAEEHFHBCBCBHB,True +563,19.0,18.0,15.0,19.0,14.0,16.0,17.0,24.0,FAFAFABBHDCDCDFDCAABFCEDBBECDCDFFAGADBCHGGFHDHGHEECEGDADABEHHHHCHDHDFAHGFGFBDBCBFHAGABDBGBFDGGFCFCBHBHFHEHEHEGAGAHAGABAGABEECDCHHEBEDEHAGCGHDH,False +564,3.0,3.0,2.0,1.0,0.0,0.0,0.0,2.0,BABCBDAHCHA,True +565,8.0,12.0,12.0,9.0,13.0,13.0,12.0,17.0,BFBFEEHBFAFGGGCHDHDHGCDCGEHAHEEBBAEFGCGCHCFCFDBBBHCEBEHEHFGAGFFHFHABDGDFDFBHAHDHEAABCEGEGEDCHCHC,False +566,24.0,19.0,7.0,22.0,15.0,14.0,18.0,21.0,AEADAHECBGBFHGHDHAGDGHGBGBHFHBDDDHGHDHDADHDHAHDEDADGFEFGFBDBDFAAAAABEFDHHHEGBGAAEDEGEGAFAFHHBEEHCGBEADAEFFBFDFDBDBGBHAGBCBEFDHGCACBCBAAACAGE,False +567,18.0,34.0,25.0,23.0,26.0,29.0,16.0,24.0,CHFDFHBCBDBFBHEEAEABABCGAFDFDADADADBBBCBDBFCEEEFFAFDBDBGHDHBBBFFFDABFHGCABABABAHHHHDFBFEFHBCDCFCFBFEEGECFHEGEGBBDDHDEDHFHDHDFBAECCBHBEBHBCCCBDBEGHGCFCACEFAGEGEGCCFBFEHEHCGFECGFDAGFGHCCCEEEBEHAHDG,False +568,10.0,3.0,8.0,11.0,10.0,4.0,2.0,8.0,EGEDEHEHCDCEAEAEAFFEHCDDDCACHBHBDDDHAAACAEBFAGAHDCCFEDHD,True +569,16.0,11.0,9.0,12.0,15.0,17.0,17.0,12.0,EAEDEACHEAGBHHFFAGGDADADHBHAFFGDEDEHFBFCGBGFFDGHAEAFBCBEAECDADCGCGFGEGEGAGDEDBFFAFAFCBHAEAEGEGFGFDCHCGFBHBHBH,False +570,5.0,3.0,10.0,3.0,5.0,7.0,4.0,6.0,DADCHHGACACECHCFCFHDEGABAFFFFECECFGGHBCBCEH,False +571,19.0,19.0,10.0,25.0,20.0,11.0,12.0,21.0,EGEGEDDDADCBFBFCHCHGAGDHDHDADGHEDDDDHBHBHCADEEEDDHDBCEAABABFEEAEGHGHFEADDDCABHBHBHFHFEEEEFDCEEGCBCHGAEAGABFBHAHEHAFABHBFDDDBDBHAAFBBAGGCD,False +572,9.0,14.0,14.0,11.0,15.0,15.0,19.0,10.0,EFEAEGGGDGDADFHFGFBFBFGDGBBEBEADHGCBCBCGCECGFDCBCBFDFGEDBDHCAFEFEBGCHAFGFGEEHBGCGCEEEBHCHBADCCGGHAHADAGFHFE,False +573,4.0,10.0,13.0,15.0,11.0,8.0,6.0,4.0,AFCCGEEDEBEBAHAHADFBCBCBEFDGHBEGEFFBFDDBCECDCDCECEDDDDDGDCDCEBBGDHFCCGF,True +574,15.0,27.0,18.0,27.0,33.0,20.0,18.0,26.0,FACGCDEDBABABADHDBEFECGDFHHEBCBCGHHAEBHBHGDADGDGDEEEDEBCBDBEAFHFEDGDGDBCHEAADEDEAEDHCHAFDEDHDACHBHBHEHECFBABHDEEEFEGBGDDHGFBFBFCFCEBEBFFCECEGEFEDGDCBGEGHFCECEBGBHBHDHCEFFFBGBHHHEFAAHDG,False +575,16.0,17.0,13.0,14.0,16.0,19.0,22.0,14.0,HBCFCFDFEGAGAHHGEGBGDGFHEHAFBDBDCHCHGFDEDEFHFBEBHBHBEBHBDFDEDEHEGEFFACACGFHADGFADGBAEADAFBCHEFFBEBGBGBACGGFGFAABGGDGFCCACAEAECDGGGC,False +576,21.0,18.0,24.0,12.0,15.0,14.0,8.0,14.0,CDCDFBACHGHECECEDECECHHAHBGFAAHAGFEBCHAGBBBABCBADCFEGABABCGCFAFEBHAHDHECACHHFCBBBEBECFCFAFAHAFCGDFDFDBEBDCACACADBDEHEFEDGCACAC,False +577,11.0,6.0,10.0,4.0,4.0,6.0,15.0,11.0,HHGHAHGDGCEBABABGCHCGCECHCACHDFBABFHFCAHAHFFBFGGGGGGGACAGECDGAADEHG,True +578,13.0,11.0,13.0,13.0,10.0,10.0,11.0,13.0,HDHDFAHCHGEAAAACGBEEHHDEEEDADCDCACACDGDBDBCFEAGHCFCABFBFGCEFBHHHHGBGCGCGEEHAHFBFDDBDBCGDGAFAFB,False +579,16.0,20.0,17.0,10.0,16.0,13.0,17.0,18.0,HBHCDAHECCCCBHGEFCBCGFFAFACBDGDCHBHBCBEBEDGDFEHGHBHECCCEFAGAEHDGDGHBFAFAGAGBGBGBEECCAFAFDBBHFECBGHCHBHDHBHBAEEEAEHEAGAGFGFGDABA,False +580,19.0,23.0,27.0,23.0,24.0,28.0,24.0,26.0,FGFGCHDADGDHFFDCDABFFFFBCEAECEHADCDFDFABAHABDEDBAHCCCHBAAFAEGEGFGHDHGHBHGHDCFCFCADEFEHBAEEFGCDCGGGGGEHFGCGCFFHFHGHBCBDBDCCCGEBEHFBFCFEECFGHGHFHCAEBEBEGHGHFEFDCHCBCBGBDBEAAABCCEAFBHBHDHEEGABDDDED,False +581,14.0,16.0,19.0,20.0,20.0,20.0,13.0,20.0,ACAFBEAHDHEHBHCABBCHFHCEEGCHHFCDCBBEBHFABGDHFHFHBHBHBGDDDCFFHFBFGFECDCEAGAGACCCGCDCDEDEDADADFFFAFAGHCDAGHFEEGHCEEEHECECEGEFDFEEGDDDGDBBFBFBADH,False +582,13.0,15.0,13.0,20.0,21.0,19.0,19.0,16.0,EGGAGAHBFFEFEHECDCFCBGHFFGAGAGEGCGAGBFCFDDDEBEHEHCFBDDDDDDADAFAHHCFDEDBFFFFHAGCBDAFBHBEDGFGCBCBGEGEDCDCDCFHEHGHBDGEHABEGAGHFEDAHEEEEEBHB,False +583,6.0,13.0,10.0,9.0,17.0,8.0,10.0,9.0,FHFGBBBBABCCDHBEDHGFDEHCGCBEBEHCFCFBFBDBACFHGHGEEECECEDEDEHEDGCAEADFDGEAEGGGEBABEH,False +584,18.0,27.0,27.0,16.0,19.0,28.0,14.0,16.0,FHFCFAFHHBEBFBDCHBGEDBAFFCBHBCFGFGCGCEEEDEDBABGEFBGBAFAFHEGCGCDCDBHHCHAHAHGCECAHFHFDEGHBBCACABABFBFBFAFCDCDBABEBECFFGBECCCHCFAFDDDDFDBECEAEDBFCDCEFGFABABCCGEHCABGFEF,False +585,26.0,16.0,22.0,22.0,20.0,21.0,22.0,26.0,FHDHDHFCEBBDBAAAAGFGCBEDHDHGHAEAECDCBEBHCHAHGGFDAEFCFHHHEECCCDCDCDHAHABBECACADAHCDCDFBBEDAAGAFFHCEEEAFAFGFCECEFACAEAFFHEGFHCAGECFFGBGFGDBDBABAGGGGGHHHAHDDDHHHAHDGEGFGBGBFCEDGD,False +586,8.0,5.0,12.0,4.0,4.0,13.0,13.0,7.0,DFDCCCCCCFEBEBDFFAFGCGCBFDFBAAFHGHGCGAAHGFAFGFGCGAGBCHFHCGGHFHEAEG,True +587,4.0,3.0,2.0,3.0,2.0,5.0,3.0,1.0,BGGGDBDHDFCAEAFCFBFEFAA,False +588,7.0,14.0,10.0,16.0,16.0,9.0,9.0,13.0,BCDFHCGFGAEFFFDDBBHBFBHHGAEDDFDEHEGEGEHADFEEHEGEDEDEDEHHBHBDBHBDCDCDBBFBABACACEHECGHEBDGDCCCAG,False +589,41.0,28.0,27.0,20.0,22.0,14.0,25.0,23.0,EDEHHHEACAEAEGECBBHBHBEFAFEBAFHHGHAHACAGBDBEGCDEHAHADACACGEDCCCFBBBBBFAADACAGECDFHGDDBDCDCECDABAFCBEGEDFCGBGDHACABGHECBGGCDCGEFEAGCGDAAABABABDHGEAHBGAEHGBGBFCFCFEFBHGHBAAAAHABABADAGACACGCACHDHDHAFAGEG,False +590,25.0,17.0,16.0,9.0,20.0,24.0,14.0,17.0,HDFDEGEFBBECCBDBABFFAFDFCECBAGAEABGFHCACAFAFAFHEHEHECFCHEHEHECGBDBAFEBCFAFCFAGGCFCABHGABFFEGAHAGAGCHHEHFDFBEBCBEFAFAHAEFEAAHAHBHBGDGDGCEADAGEF,False +591,17.0,13.0,25.0,18.0,20.0,19.0,18.0,19.0,ADCFCHDBAEHEHEFEACAFAFDFEFECEGADHDHEBCCCCEHHGBDBDGCCFBGDDCGABAEAEDEAFAFCGCFHFEGAGDGFHCGCEHEAGCHCBDEDCFEDHCBEBFBAGEGAHCHCBCBAHACDBDCDCHFHEGFGFGDGHGFFH,False +592,4.0,14.0,3.0,5.0,17.0,15.0,9.0,5.0,HGFEEHBHFFEFHFEGBABFBGDFBBEFEDGDEDECEBEFEAEBBBBEBFAHAGFDFEFEBGCGFGBGFECE,True +593,13.0,8.0,10.0,11.0,8.0,10.0,5.0,8.0,EAEADADGFGCDDFBFHHGADABAFHHBAEABHHGBCFCFDFAFDHDCDCBFBCCCBCEEEAEAEFDAHACDG,False +594,16.0,13.0,15.0,7.0,3.0,9.0,20.0,22.0,BGBGCGHHHEHGAAFGCGBDFAFBHCHBDBCCCFDAHHBGBAAABHHHGHGBABABCCCCCDGHGHCHAHGEGDBFGFGCGAHAGFCHGGGAHAHCHFEDHDAAF,True +595,12.0,10.0,9.0,7.0,8.0,10.0,12.0,10.0,AEFDFGFGABHBHBACAHFFEECEFDFGBCAABBCDCGEBEBHHHHFBAEADGDGHGDGDCACGCACAEFHAHGGGBF,False +596,12.0,14.0,7.0,5.0,7.0,8.0,16.0,11.0,DBGBABFCGCGEGBGCHCABEEHGGGHGHFBEBABFBFBGGGGFDFCGABABAFAHHHHBEAAADDHCFEHAHBGACDGE,False +597,12.0,31.0,25.0,23.0,29.0,22.0,19.0,20.0,GBCAEDEGEDHCHGFBEGCCDCGAFBFAFEGBBDBDBDGGCEHEHFHDCDCDEDFHHBGBGCHABGCGCFHFDEBCDHDAABFBGBHDCDCEHEBFBFEFBFHEHEGEBBDBEBABCDGDBHBDFDFDACCEFBCBFHFGCEAEDFCCDCFGGEEEAEAFAFBHBEBCBCHEHCHGEEEBE,False +598,3.0,2.0,2.0,2.0,0.0,4.0,2.0,0.0,DADAGFCFCBGAFBF,True +599,18.0,18.0,17.0,19.0,19.0,25.0,24.0,26.0,EFEFADADEGEGBBHHABBHCCGAFDHDFEHHHHHHGAAADGHFHGGGGDEACHCHCFCGEGEFABEEGEHFCFDFEBGAHCHGFGFGFGFDDHEFCFEBDFEACAFHCHFBADGCGBADGDAFCHCHDDDFDFHCHBHEEEBEBGBABABABCBFFHFDGCGBGD,False +600,18.0,13.0,8.0,18.0,9.0,20.0,11.0,10.0,FAHEFAFAHDGGGGHCBEGABABFEFAAGAGAGAGAGBHBHCFFDHBHDEDEDABCFCEDEBEFADDBFFCFHFAAGDDDDDDFFFFHADFFFBBBCDADCCADHBE,False +601,28.0,16.0,18.0,22.0,25.0,31.0,31.0,28.0,DHDHCHCEGGGGGGHGHGABHGABAGDGEGBACHDHBGADFBHGAGFGDDADGEAEACHBBFFHFEGEFFAFAFGFEFAGADDFAFCFGHBFFEDBACABFHFCCCEEDFDCDAAHFHEHDDEDGHEFCAHFFBCGCGCACABAEAEHDHFHFHFCEDEDGAGAEEEEEFDAGGGHGHFHAGEBHBAEFCFBFCEHBHD,False +602,19.0,22.0,22.0,6.0,18.0,28.0,18.0,32.0,BEHEHCBFBFGAGFFFHEEGEFFGCHCHFABHHCCBFHFABBEBCACAEAFHFABHCHGBBAHEEEEAHAHBHECACAHEHEHCGBFFHFGAGCCBCBEFEGHDDGDHFHCDAHHHHDAFBFAFHFHGHGACCCACBHBGBGBCFGFHFHFGFGFAEBCGCBDEF,False +603,6.0,3.0,3.0,0.0,3.0,1.0,2.0,3.0,AAAAHHHEAEBFCEGAGCBCB,True +604,20.0,12.0,4.0,14.0,4.0,16.0,10.0,13.0,BHADGGGBAFFHAEDBAFGFCFHFHDHBHBGFFHADDEHFFBFGHAHAHABACADFFAAGADAGAGACADDEFEFDADAHBGBABDBDBDCHF,True +605,13.0,12.0,3.0,10.0,9.0,12.0,19.0,5.0,BFBFCDGDBDAGAFCHBBBDHGADCEAABAGFGFGEGEGDGFAFEGBGAGEFFGFGEDADBBGAGAGEFEBBHGHGEDDAFAH,True +606,25.0,22.0,15.0,23.0,20.0,14.0,29.0,17.0,ABABABGDEFEFEHBAAAFDDBDGDGAGEEBHFFCAHAGABACACHEGDGDFDHGGFFHFBEDECFGHCBAGDGCHBGBGCGFDADECEBEAEADAFEBEAEFCBCBCBHBABGBHAHAGAGDDEEEHBCEADGDGDHHFDGABDBDGGCGCADGGHHDHGGEGC,False +607,7.0,12.0,19.0,9.0,3.0,6.0,12.0,7.0,CHGGCADECECGBGCGCEHDAFACDBGGFABCBCBCBCBFBCGCBCBCBFHADACADHDCGGGDFCHGFCHDHDB,True +608,15.0,15.0,12.0,14.0,12.0,4.0,21.0,15.0,BGBEFEGDBCGCGHHEGCFAGEBFGHBCCEGAHACGBDBGBHAHGHGHEHEHACABADADAHACBGDAEHGHBDBDBEBAAAFCGCGDEDCDEDHDAGHGDGBGEGDC,False +609,11.0,19.0,6.0,5.0,9.0,14.0,11.0,10.0,BBBBGBFBFBABDHAHFBBAHEHFCAHGGDGDFCBCFCGAHBDBGBGFGHAHGBEEAFFFBFEFEACACEEGEAEDGFHAHBBBF,False +610,7.0,6.0,1.0,2.0,7.0,8.0,15.0,3.0,GGGGGDGFBAEAEBFHGHDFAGBEFEFGFGBHAGAGBCEAEGBGEGAFF,True +611,9.0,11.0,18.0,12.0,13.0,14.0,18.0,18.0,DABAEGBGEGEGEGFDHCGCHAHFHFCCCCHHGADFBGEHAHEHECFHEHEAGABDGEBCBFFFGDGBGACHHHDHCFCDCHHGDCHCBCDCGCBBDADGGGEDECBFFFFEF,False +612,1.0,6.0,5.0,8.0,3.0,4.0,3.0,4.0,BEBEBGBFBFDDCHBDFCHDGACHFHGDCDCDED,True +613,5.0,7.0,4.0,9.0,3.0,12.0,4.0,8.0,DEEHBFGFCHBHDHFAGDBDHDFCFEBHHHBFBABAGAGDFDCDFFFFCFDA,True +614,5.0,4.0,10.0,9.0,2.0,6.0,6.0,7.0,GCBCBCGGBFHHCFCHHDDDDCBGAEACACFDADCCAFHFHDHDEDGFG,False +615,20.0,20.0,21.0,19.0,32.0,21.0,14.0,26.0,FCCGGEHECEDEDBBECHCHCFGBEHECCCCCHCGCDCDEHAGCECEDDBEBABABEBEAAAAHAHEFAFHFEFBFBFAFGEEEAEHEBGHEHDBCBDAAEFFHCGFHHHGCEAGDBEHEFEGDFBFAHHDBCHFFBEGEGFHECEADADADBHFHAHDDFDFHEAEBDBDGH,False +616,4.0,1.0,4.0,5.0,3.0,3.0,4.0,3.0,AGAHCHBGDFDCHEDEDEFCFCDAGAG,False +617,14.0,17.0,16.0,17.0,18.0,16.0,11.0,15.0,EFEFHFABEBEGEAEBEAECBDHFEEGEGBGDHHHHHBHBHBHAFAHDBFHABDDFDHBGDECECEFEFGDABAFAFABDHFBFCGCGBEFCDCEADDDFACAHDCCGDDCBCGCFCABECGCD,False +618,29.0,30.0,26.0,14.0,18.0,25.0,13.0,17.0,HACCBHBFAFBFBFHFCBAAGAEBEFDDBDAAACACACEEDDAEFGBGFEFCABAGAGAGFGCHCAGFBBDFHAABFCFCFDHEHCFBFBHADBBBBHDDBCFABBEBFBADAEBCBHBHFHCBDDHCHGHCACAGAGDFCFEAEBECECECFCECECGHEBAFAEAGHBCF,False +619,31.0,22.0,24.0,19.0,30.0,25.0,19.0,29.0,CFHEHCGFFACEHBDEEGGACFCACAGAHAEAFDCGBACEFGAECCAGHBHBDBAEAGFBABAGACAHHHAHCHCDCDAGGGAHAEAEDGGCEHFHFHFDGBHBCEHEDEFEFEFEAADACHFBDBDBDBFBFAEHFHBHEHEGEDEDCCEBFBFCFCAHDBFEAEFEACAFADEBEHHDEGEAHBHCHDBGBCDHFGF,False +620,18.0,17.0,15.0,24.0,21.0,15.0,18.0,13.0,ECDGDBDGDGDEAEBEBCFGFGAGAGHCDEHEHBGGGFEAAFBBDFHCDCEEEEGAGAGEDFDHDHAFAFHEHDADADBDECACEDDBHFEGECADDCFHBCBCHCDDFDGBBBEAECEDEFABAHCHGDABFBFGFCBGA,False +621,0.0,2.0,1.0,1.0,4.0,1.0,0.0,1.0,FEEDEBEBHC,True +622,14.0,20.0,14.0,20.0,27.0,29.0,12.0,26.0,CDCACEHFHFHBHEFEDEBBFFFFBFECHHAHEHEDGDEEBFHFHAACEDECCCCEFEHAHBHDHFHFAFABEEEGEGEBDAHEEEEFHDDDGDEDABHBAFGFEHABFBABDBFFFHFCFHFBGCABBGBHFHFDDAHGFEFEDHCHDEBGGGBCDDDCGF,False +623,16.0,25.0,17.0,19.0,21.0,19.0,21.0,15.0,BFDFDFGBGDHBHEDCACFCEHEDEBCFDEDADBDACADDEGEGHAHBHFEBCCCAHEHEBEBAAAAGCFCFGFBEEEHBHEHGBDBDAGAEAGBDBGFEFGBCBCFGEGBGHDHGCCAADCDCBFBAGGFGEHDFBEBFBFDFCFHBGGGEB,False +624,23.0,27.0,21.0,27.0,12.0,19.0,33.0,26.0,DHAGAGFBFCCHHGGBCBFDFACGBGBGHCABACAHFHCDCDGFGFCFGFCAEGHGABABEDEDHFHFDFBGHGEGHAHBHCDAGAGAGBBAEAFGCACBFBDDHGHBHDGDGBGDAAAAEBBGBDBDCACFCHCBDBCCCBGFFHDHDHEGEDEHHDDDHBGBHDFFEBDDEEGGGGAGHCHDBAGD,False +625,17.0,22.0,27.0,7.0,24.0,19.0,26.0,18.0,GHECEGFGAGCBEEGBGHGBEBEAEFGFAFCFHGGGGEEECBFBDGGCGCEDGFBHBCBCBCAGABEGEAEABFFFBFBFHEGFGACAEFDBCBCAGAGAGFFCCBEHCCBCBDHCBEHCHCACEBFBCGDAHFCECEDACAEHHHHHDAFGHCHCEGEH,False +626,21.0,20.0,18.0,14.0,19.0,24.0,20.0,19.0,FGFGDBFGAAHHDABADDECCHFBGCEEHGHGHGAFHCHAHBCBFAFAFABBBABADDGEBBFCFCFCFCBCDCDHFAGGHGHGAGEHBFAFCHHEGEFBHDHAHAEDGAGAGEGCDEHECCCBBBAFFFEFDADBBEDEGCFBFCGAEEEEFEF,False +627,22.0,20.0,15.0,21.0,16.0,16.0,15.0,16.0,GBGEFDACFGFGHBHECCFAAAEEGBCHCBCFADHDHDBDBDFDADABAEDFBADACBCFCFEHGCEFEAEBHDHDFDEEBBHBGAGDGAEAEGGHAHDDDDFDGBBBAAAABDHGHFAFECCCECHBDBCBFEFGAGAHH,False +628,7.0,15.0,8.0,13.0,14.0,12.0,11.0,8.0,DEDBDHFHDCDCBBBCBDBFBFCGHGAGEFAFAEADBFBGBGHGDCFADBDFEFEDECEFHHCBEAGGGDEBECEABBGHGFDHEEFE,False +629,1.0,3.0,3.0,8.0,6.0,2.0,4.0,5.0,HEHDHDHDEFBGBGDDCDHBEDECGCEEFGAD,True +630,11.0,10.0,7.0,6.0,8.0,14.0,8.0,5.0,CAHAHABFCFCACFCAHAGDBCEGHFHEBDFAGAGABBBEBCFEFEFBFAFBDEDEGGDFDABFFEFGG,False +631,14.0,11.0,20.0,21.0,13.0,15.0,14.0,16.0,HCFAAHBFCFAFHFGDHFCFBBBEBEAEAEHEHGDDBHHHFHDCDEGECFHFDFDADACADHGEDADHDHDCDCGADDECEAGBBCECDGGCGCABAHFGCDCGFBHBDCDGAGCCCDCGEFEF,False +632,4.0,8.0,5.0,12.0,1.0,8.0,6.0,3.0,CAHAEDBCCFGDBDFFBFBHDDDDDADCGBGBCFAGDGFGFHDBDBF,True +633,3.0,4.0,7.0,2.0,2.0,6.0,5.0,5.0,CBCECACAFEFDAHBCGFGFBHCHDHCHGGFBFG,True +634,15.0,14.0,8.0,23.0,21.0,16.0,17.0,8.0,GDDDADADACBFGFGFAFACADAEEBEBFCGBFHFHGEDDDFCGABCBDHDHEEFHAHGEFDFEFBFAGAFEGDGDGBGDEDEBHBDCEEEEGEBCDDEAECDDDEGGGAFAEBFBGHEDAB,False +635,16.0,23.0,27.0,12.0,33.0,22.0,20.0,34.0,HEHACECAHFBGBEBHHHHFFCECEHEAEGDGDHAHBFFFFFFFGABCEFEBECECHABGCGFHEEEEEEGBCAHEHCHDFBGBCBCBHHGFBHDHCHEHEHCFCGCGEFHHHCDGDEDECBCAFEFAGHDCABHDAEACCHGHFBBHDEAGBGAFDDGCACEFEFEHEHEBEGCCEGBGBCAHBHB,False +636,18.0,21.0,19.0,22.0,14.0,15.0,21.0,26.0,GHABCDDDAGGFFEFDFHBACHDHDECGBFBFAAGECECDAFBHCDCEBGBAAAGHHEHEHEHEBAFDFCACECECEHHHCHDHAHAHCDBDGGGDHDBCCFCGHHHGDDDBEBFCFDGAFBFBDBDBGBGBABHHCHGHGDBEGAAHDCGAGBGF,False +637,7.0,11.0,15.0,9.0,7.0,9.0,10.0,13.0,DAFBFHGDGAGCDCDGHBCECFCGCDEDHDHBHBFBEGEHDADBBBBGFHHAECHGHGHBFCFAACCCFFHGACHCBCECE,False +638,23.0,18.0,27.0,21.0,18.0,14.0,17.0,30.0,DEDCHCBFEAEAEABAHGDGDADEBEHCFDGGCCCCDCBFGFCCHDHDHFBABDHEHAHFHCAFAEADHDHCHEDACCGCGCGCBAFHHHECDDDBGHHHCHBHAHECFBBGBDBFHAHGHCDGHGCGCBBBGBABFGCGAEEDFDAEHFHDHEEACAEFEACHCAAA,False +639,8.0,5.0,5.0,6.0,7.0,4.0,6.0,5.0,FGEBDBDBGHGDGCAHAHCDAGAFAFBEBEGEFDCHAEECEDACAH,False +640,25.0,30.0,19.0,18.0,18.0,25.0,21.0,28.0,DBGBFBFHFHCAFAFACGCHCHEHEGFGADHHFEAEGEGHGEAEBDADHBABDGGGGHBHDDGAEBDFCGCFFGACDHBHFHCHFAGHEDACAHBDDDAHHEBEBABACAGBDEDGHBHFHFCGCDFBFBFAHGCBDDCBAEAEFCABABACACEFHFBAEHEGBGBHBFFHBEBFBFBFHCBC,False +641,10.0,7.0,19.0,15.0,18.0,26.0,16.0,17.0,EBEBEADCFGFGAADCEFHCAEDEAEFBHEHDGDGDBHCGCFHFHCHFEFGFGCECFCGCEDAFEGDFCAEADCFEFHHHFDFGFGAGDGDFHHGACFBHDHCGFGFCHCHCHCDEECFFFFEBEBFD,False +642,17.0,19.0,31.0,20.0,20.0,27.0,31.0,22.0,EFGFHEBFAHAHFHGCFCFGFHFBFDHDAGAGBECCHCBGBFEABDEGEGFCBDDFEFADADBFEGEBBAEHEHAHAFGCGCGCBCBFGFCACHCECGCBCAGFHDBDCAFGCGCGCGCDDDCDGDGFBHGFFAHCFCFHECDGDBECCCDCEGEFBFEHHGAGCGDHAHGHEFDHAGBGBGHDECE,False +643,10.0,16.0,8.0,13.0,16.0,18.0,19.0,19.0,DBDFCEGABABHBFGAHEGFFDHCFCFBDHHACAFECHHHHGFGBEHEGEGEGFGBBDBFEFHFCEDECFAAGFGFEBAGHEHEHEGDBDFDFBEBDBDFDBGEHCAAGHGHGBGHGHD,False +644,23.0,23.0,24.0,17.0,10.0,17.0,18.0,14.0,BGGGGGEGBACCECHCHCACDBAEFEFHAHACFGGADDCDCDCDGHGCBHBAAFGFGFABBBBFBHGFAAADADCDEACDEACBHEEFCCHCHAFBCHGEGBFDFHEBBHBDBCHDBDBGFCFBDCGFGFACABBBAAAAAFDCDC,False +645,19.0,20.0,19.0,12.0,21.0,19.0,19.0,26.0,BCHEHEABABAHAHDHBEDEAEGECEBECAHDGCFEFCHHAHDHDHFBDACABGCEBHBCFHGCCCAEEDAACABBHGHGHFHBEBHDECEBDBCBFEFHHHGHGHGHFHFBDGEGACEFDFHFEFCGGGAEFDFGCGABFFCFCGBGAGFBAEA,False +646,24.0,19.0,25.0,16.0,26.0,22.0,27.0,28.0,DADGFHCDDBDHDHGGAEECHHHFCAGACFCFEDCCECEGFBFBCBGEHEACBCBGGHGAGFHCGCGEFEDAHAHFHEBBBHHAAEAECBGAAFBGBHBHAAFEEAECEGHGFCDCHHHHBDFGFGFGBEAFHFDAHAHCBCEHGHGFCDGDGCGEFABDBFBAAAHADEDEGCGHECEFEFECECG,False +647,19.0,19.0,11.0,23.0,12.0,13.0,15.0,22.0,FGFAADEGEAEADGDFHAHBHDGGGHDFBHBDDGDCDHBHBHEHECEDBDBEBHHDHEABCCGFAHGGEADAGFDAHEHDHDCDGDHHEHFFFGEGBDCACACDFDHBBBBDCGAAFAHABABACACFDFBBHB,False +648,14.0,18.0,21.0,17.0,4.0,13.0,14.0,14.0,HDCCBGAGBGFGFHCCACHCGCBCBEDEBCBDBHFCFCFGAGACBGFDFBHBADAGHCHBHFCACDFDBABAEGCHHDBDCFBECGCGBDAFFGHDBDBDADADACFDADCHHGH,False +649,18.0,10.0,20.0,21.0,15.0,23.0,20.0,19.0,CDCFFDAABAFGFDBHFHGADADAHGHGBDFCHHHCDCHAHADCDGDGDGCEFGFCECFCFCGCAAAAEAEDBDBFFHHHFECECGGEGAABHECFHDEDGHGAEADFFHGDGDGEEBDCFGEHFCGCECEDDFFFFBFBCBHHAG,False +650,2.0,8.0,12.0,4.0,7.0,2.0,3.0,2.0,BECADGCCCCCBCBCBDGGFECECDBDBHECEFABHBCEE,True +651,23.0,17.0,14.0,13.0,18.0,7.0,9.0,12.0,HGFCACACFCDEEAGBGBADADABCGDAEADGDBACFHBEDAABHBHGHCAAEBECECACEDECEGFGAAHABAEAHDHABABADEBCFCFBEEEHEBFBAEHEHDCDBGBHD,False +652,9.0,5.0,7.0,3.0,3.0,4.0,7.0,7.0,FHAHAGGGGHGCGCEHEAFAFCHDECHBABCFGBHBACDCDAABA,False +653,17.0,14.0,10.0,12.0,16.0,15.0,12.0,13.0,FFDCCCGHBHEFBAEAHDFFFHBBBBGAFABABAEADAEFCBDEEHFDACHCHDAFCFEDGBCBCBEBEGGGCHHDDAGAEAEDEDEBEHDHAHEFGFGFGHGAAEAFG,False +654,18.0,23.0,28.0,27.0,18.0,13.0,30.0,25.0,CGCBCACGBGHACACADFEBGBCAEHBDBCHAEDGDFDCCAEHDGDFDFAFBGBGEDCFBFBFDAHGCCCBGBHEHAHGGGCECEHEAGCGDGDHBBDGCECHAHDFDGEGAGDGEADHCACBGBCHAHAGBGHHCHCHGEBEAEDECHBGBGDGFGEGHCHBDDDCDHDFDHCFEHDBDBF,False +655,15.0,11.0,8.0,7.0,7.0,6.0,7.0,13.0,EFAFACBEEDCAHAHGEAEFFHBHBFBFHGAAHGHGAGDCBHHHABDBEBAGAGDDDADHBCBEACHCACACHB,False +656,23.0,17.0,14.0,15.0,23.0,23.0,21.0,14.0,DBBBEEGCGFABAGAHAHFDEEHECBHBFBEAEADGDACGFGFCFDFGFGFGBEBEDEHHCFEHAHAFAHEBABEDEFGFGBGAAECFCHCEAGDGDCBCAFHFDFDFCFEEEEECFDBGGGAAADBGBHDAGEEBHDAAAHFGCGFAFC,False +657,22.0,13.0,20.0,11.0,19.0,20.0,13.0,19.0,AAAEEECFGGCCCDBDAFHFAFCCBAAHBBBEBFBAGCGEGHCAEACDCEADBDEAFCDGECEGGAGABAHAEBHHHHHCFCFEHCHFHGHCHCFAFDFDFDHBEGEFFFFAEAECEDEDHFGABFEGCHCHAHABF,False +658,13.0,8.0,9.0,8.0,6.0,14.0,16.0,11.0,DFDAACADGHGFECCGBFFFHEAAFACAGFHCGCFAFDFBBHHFGAGABABAGEFEFGDEBFBDBGACHCHCHGDGHGHGEGDGH,False +659,24.0,22.0,11.0,20.0,12.0,19.0,20.0,10.0,ECECBBAAAFHDHDHCBGFGFACABAGGHADBEAFFDFDFDEGCGCBBBFAGABBEDGGAGFDAGHGDDAEABBGBHDGEBFBHDFGCBCBEBFDFDADADBBFEHEFEFDFHFEGDCDCDCGBGAAAAAGAFAHBGA,False +660,9.0,8.0,11.0,8.0,16.0,14.0,26.0,11.0,FEGEHCHBGBGEGHGHGEGHDEBHAFACGDGFGACHHGAFCGGFEHDFDEEGBGBGFGFGCCECFAFDFDHBGDAAHAGEGDGEGFGAGEBCCCCBEEGEFEF,False +661,21.0,16.0,26.0,12.0,16.0,24.0,13.0,16.0,AHBFGAHHBCBABABCCGBEFACECGHGFDAHHCCECFFFDFAHACACBCBGBDFEFEHEDACAEDEDEGEGDGBBBGCGAHACACEFAFDFAFBDACAFFHFCFCAGEGBFDFBFEGCFCBCFHACADDCHFHFCECEHHHCE,False +662,19.0,21.0,19.0,34.0,20.0,23.0,22.0,19.0,AFAFBGBGBABGDDADCFCECGGEAEACHDHDEFCFDFDECHHGDEDEGGFEBBBBBEFEDDFAHCBEDDBACDCDAHAHGHDCFCFDFEFEDHCHDDADBGCABDHEBBFBDCDHDEDEABDHEBFBCEAGGHFHEAGFGFGCGDGFGDGAGAGABFBFDDHDCDHHGHECDCFAF,False +663,30.0,32.0,21.0,26.0,25.0,15.0,23.0,18.0,GBDHGHGHGBGFGABAEEDBCBCAHAEEDFDADEGCCCGHDBBBEDHGGFCBBHEAACDBGAGBGFEAAAAAABADGGBGCDCFCFDFCBHAHBBBHBHGDBDEHBHBHBEAABABDDEAEDFDEBEBECEGEFAFCFCADEGCGBABABFBCEADAEGEGDCDGBFHAEAEFCDDHEHAHFDCDEDCAC,False +664,14.0,12.0,16.0,18.0,20.0,25.0,19.0,23.0,GFFDFGFDEAHBCEEHCFEEEABFGFGHGAGAGCGCFDBDBDEDEABABDBHFCFHDGAGEHEHEGDCDCFAAGAEEHFGFEDCHFHGGEHDDGBADDGHFHEHEHECFCFCDCAEFFFGFGCBHHCCFCFBFHFHEDADHHHHABB,False +665,1.0,1.0,5.0,0.0,2.0,0.0,2.0,0.0,CCCBGGAECEC,True +666,13.0,18.0,8.0,9.0,12.0,13.0,18.0,15.0,FADABCFAFAFGFGFBCBGGGFGDCDCABDHDAEHEDGDGEFFHCGEHHFHBGAGAHEGEGABFCGBGEEBEHFHBHBHBHBFBHCABBHGEEDCDBABABHGGAE,False +667,12.0,9.0,6.0,10.0,3.0,13.0,8.0,9.0,CBCHGHFADHGAGBCFDFAADDFCFHDAAAAAFCFEAAFADCDGDGHFHFHGBFBFBEBHGHGBBDFDEB,False +668,25.0,23.0,24.0,17.0,11.0,21.0,16.0,12.0,GDAFFFFHBBGCACGCECBHAEDBBFFFBCBCACACGBABEBEDDBFAHBHDAGAGBGBGAGBGAGEDBAFCCDCGAGHCDADACAEDFHACBEAACFDDBDBHBDBDFFFCFCFCFCAAAEDHFAFHCHCACHCGAGFFCEEBEBGDH,False +669,3.0,6.0,1.0,5.0,4.0,4.0,3.0,1.0,EABGBEBGBFBGDFDFDADEDBFHEAC,True +670,5.0,9.0,11.0,15.0,8.0,21.0,12.0,11.0,DFDCHCFFDHHAHACGGFBDBDCDCDAHEFFFHBDBDBEECFGDGHGBFCDADABHBHGGEGCCFFFFFDFHEBGCEFDFGFEFEHDGFGFC,False +671,9.0,14.0,11.0,13.0,12.0,14.0,11.0,23.0,HDHCHCFCFCHCFCDADADEHFHBAEGFGHCEDHFCCDEHAHFEBBBADCHHHHDHBHEDDDADHDBGBGBCBFHEBEFGBGHGFFHAHGHBAFAGBEFEBEHEGFG,False +672,3.0,4.0,0.0,0.0,2.0,6.0,4.0,2.0,HFHFAAGEGFGFABBFGFBEB,True +673,17.0,21.0,20.0,5.0,12.0,13.0,17.0,15.0,BCBDBECHCAAADCGGGGFBABABEBCBCACAGHBHDHBFEEEEAABCBCBAAHBGGCGBGHGFGAGFFCHGHGHBABFBFHCHADDFCCCECECHHEAFBFBCHHBCEGGCFAEAEGFF,False +674,14.0,34.0,17.0,24.0,19.0,23.0,30.0,24.0,BBGEGHHHEHEFABDCHCFBDAGBBBBDBFCFCFAHHEHAFGHGEGEDBDBDHCFCHCEDEDEDGCGCDDDGDGAGAGEGBHHCHADFDBBBCDDACGHGEGEHBGBGHFEFGFBBDBHBFBDGGCGCDFGCBBBDADGHFCFADGEHFCFAFGBHFHBGEAEBBBAFGGDGFEFBBHEHEBABF,False +675,22.0,22.0,20.0,24.0,22.0,17.0,36.0,34.0,CHGHGHAHAHCECDBGCADHEEGECDGBFCCHCHFGFGBBHFHFHEGFGAGCGCGDGDCBFBFEFEHEDECCHBGBDADHFHEBDBGFGBAHGHGEACGGAEAHGBDCDGDHFHBHCECBDHGGGGHBBDFDFHAAAAAHADADHGHEHAGFGDGAEDGDEEBHACFGHBHBHCGGGCAHEEAEHEFDDDGDBBBAE,False +676,5.0,3.0,7.0,7.0,6.0,1.0,5.0,6.0,EHCHEBAGEGDGDCCCCABHEGBAEDEDCDFDADAHHCHG,False +677,14.0,12.0,18.0,20.0,14.0,12.0,11.0,15.0,CCADHGFACAHGHDDDDDGFGHBADGBEBCCDDDADADABBHCFCFHBHGAGEEEEEEEGEFHCDFAFCCADBDCDCDCBBBBCHCBDAGAEHDHAHAEEHEHFFCGCDFGECFFH,False +678,20.0,18.0,16.0,16.0,18.0,22.0,18.0,25.0,DFFHFHFGFBADAGHCBCAGBCBFGFACBEFEGABBBEGHHFHFDFHEEGEBECFCEBEGGADEDEAEACHCHABEHAHAFAHAHAFBFAECECHCHGHAHBHCHFHGDCHGHEBDBDGCADEDGGFBFGDBDCFFEHDFDFDGDHCHBGAAA,False +679,13.0,13.0,11.0,11.0,12.0,13.0,13.0,10.0,DADAHACGEBDGEGEDEAACHFGEGEGFGFCFAFEBCBFEFHCCFCHCHEHAFFDBBBHGCEBGBGAAHFHGHBFDEGAGBBBBDDADADEDACFC,False +680,21.0,9.0,11.0,23.0,10.0,11.0,13.0,22.0,BHEFDAEAEGGAGBCHCBAAHAFDFGGGGBHADEDACFCFAEABHBHBAAADFFACDDDHDHCBCFHDHCHGDAHAHDDDCDADEHFFAFDEHHDHECDADAGAGBHHGHEHEHCDGDGD,False +681,29.0,26.0,19.0,24.0,29.0,20.0,27.0,23.0,AAHAECBCBAADACAFFGCEADCBGHGFEFEAEDEDBDHDEBHDHAACAHAEBCBDFFHFBFBFBFGFBEAHBCAEAGAGBEEEEEEEEDCABFGFBDHFAFAGBGHGCGEGDADHDFGBCBHBHACEBDADEDEDGGGGGGGBHBHDHCFGBBEHCCAHHFABDCGGECFBAHGDGDCEAEHECEGHDFDEDGAHA,False +682,12.0,18.0,15.0,23.0,25.0,24.0,20.0,8.0,DADHGFBFDADAEECECBFDHDBCBABAHFFFFEFEFBFBFBEDFDEAFCCHEBBGECCCCFAGBBDBGCEEDHGGEGEAEAEFDDDGDAFEGCGCGCFEDDGDFHEDGGGGGEBEDFDEDHBEBDCCEFFFEFEBABFGAGHGD,False +683,10.0,19.0,7.0,19.0,5.0,6.0,8.0,11.0,CHCGBDFEGADBBBBBEGHAFAHBGFACAGAHDBDBDADHDGDBDCCCEDDHDADADCDBBBHBFBDBDFDADEHHHBHGGEFBB,True +684,10.0,3.0,3.0,5.0,2.0,4.0,6.0,12.0,DBCHHBHEDEGAGAHFGGHFAAAGAGADBCHAHAFDFDACHHHHH,True +685,10.0,19.0,16.0,24.0,9.0,16.0,18.0,17.0,DGDFEBDHDADCDBDHFHFHAGCHCHAGEEBGBGBAFDHCBADCDHAHEEABDDFDFABBCDDADCDFDFBBGBGHECCGCGDECGDBFGGEGECHCGFFBFBDGFHBHBHBCGCGCGBDDDFHFHFHA,False +686,11.0,7.0,14.0,17.0,14.0,20.0,12.0,14.0,HDHABCEFFBEHCGCACACBHBGEGEFFFBGCECDCDEHEDEGFGFDDDDGDGAHDHDADADFFFAHAEDHFBADEDBCCGHAEEECFFEFCFHFGCGAHDFGFHFCFH,False +687,19.0,24.0,19.0,21.0,13.0,20.0,17.0,22.0,GBGCDCDHFCAHAHBFFDCAGBFBABCFFBFACBGHGHBFFGHDDADHFHFHBGGHGAFDFCGAGEDEGEADDFCBABFBABAHEDEGFGFCBCFDDADACECEBEBCHCACFEGCHBBBDDDGHHDHAHAFABDHEHEHEGEDBABCBDBHCHC,False +688,11.0,6.0,12.0,7.0,7.0,10.0,7.0,5.0,CCBGGGGFABECFADHEACFCFGFGEDFCFAFBHBCBHBDCCHCAAAAAEDDDDAFCFCEGEAEH,False +689,1.0,5.0,2.0,2.0,0.0,1.0,2.0,2.0,DHDGFGCBBBBBCHA,True +690,15.0,19.0,20.0,21.0,26.0,23.0,15.0,18.0,GBGBGEFEGECEDHDHDHDHDCGAEACGCFBFECCACGCDEDFDHDFBBBEBDHGHDCBAAAFBHADFBFHFHFHFEDDADEDEFCBBAEEGEACCHCEGACEDECECFFFFHAHEGEBABEDFBHEDEAEADFDCHFHFCGEBHCFFFGBBECGBG,False +691,16.0,20.0,16.0,13.0,21.0,17.0,19.0,17.0,EEBEDECEAEBBBBEHFBFBFDCDCBCBCAFGHGCECGGDHAHCDCFCEHDHDBBFHFGEECBGBFHDHGHEBEBEAEFBAAAAEAGGGFEFCFBABDFGFDFHAEEGHHHGDFHFGCGCGDAAACADEGBBCAHGEGH,False +692,15.0,18.0,25.0,15.0,20.0,16.0,23.0,15.0,DCAGACABGEGHGBBCAEGHHDAAAFGCBCBCGGDGCGCHCDCDAFCFGHGCGCEEEHBGGECACADEDFDFGFDBBFBCDCFCDCEEHEHFDBDBGEGFFBFBFEECHGHBAGABABEHEHGCEHBFDCCGDHEHEGBFAFAECEC,False +693,18.0,15.0,17.0,18.0,19.0,18.0,17.0,13.0,DAEAFACADHDHCFCBBBDFDEGEGEFDGBEFEBGHGHEHGGAFAFAGAEDEBHDADAEAEDEAHGHAHCECEHFHBGFAEAFBCGFDFGCACADFCGCBCBDAHFBCDEBCFCFGECDBDBGBGECECFDDHFG,False +694,7.0,11.0,9.0,10.0,9.0,4.0,5.0,10.0,CDDDBBCGFGDHDHEHBHEHEBEBEAEAFHDEGEDHBAAFHCBFEGCBCBCBAAHACCCGBHDDD,False +695,9.0,7.0,7.0,14.0,15.0,8.0,16.0,16.0,DFDCDCDEAHDDDBHHFHFCDCHCFBAEEDGAEAGGFGHAEECHGHGHEEGDGFEFEDEGBGEDDBHBHGEGFAHAEAHAHGBGHGHGDECB,False +696,24.0,23.0,24.0,22.0,20.0,19.0,26.0,26.0,ADGDAEBHCGCHCEADABGBGBFEEGFAFAFBFGDGDHHACDCHFACHCGGHGHDHCBGDHBACHBHGHGAAEBFAHGGDGHGFGDCDCGCDCAEGGGEEEEEHDFDAAAHADAFADEBBBHEHECACBEEEBABFCFCFCECFCHBHBAGABHHFHBHFCDEBCDGDFDFDCBFBCBEAGDGH,False +697,19.0,24.0,22.0,23.0,29.0,24.0,25.0,34.0,FCFEAEAHCGEDABFEFDHCHCGCGCFHABDGEGFGFGBHBCAEEHGBCBCBCGHDHFHABGHDHCCCAADDFDHDCDHFBEHEHEGFBBHHHADEEEBEBFACHHHHGHGABBBBEDCBBBEDEDFFFFFFHCHDAEFEGDGHFBDGEHHGFBDADECEDEDGFBFEGCGHHCHCHGHEFEAAGAGEGDGCAHAEAEBD,False +698,13.0,19.0,14.0,18.0,18.0,16.0,11.0,16.0,BDBFFDFDFGGHAHBHBHBHFGAGAHDHBEBDBHBFBFHCBEGEGEDCCCCBGHECDCACDBFCEDBDFDFDHDFEFHFHEHEFEBABDEHBCDDHAAADEBAGAEACGEAEFBCEGEDFCCAGE,False +699,20.0,17.0,18.0,13.0,20.0,22.0,16.0,23.0,ADHHHHFDFBFAGADBEFFFEFEGCFBDHCAEABAEAEBHFECCFDFHHHHHFHCHCHEHEAEBGHACABFCFGAGDFDFCBHGCFCBCHDEDHGHAFDFAGECECEFAGCDEGEHEAABCBGBGBGBABGEAHGEAFHFGCECADBDB,False +700,7.0,10.0,13.0,7.0,8.0,14.0,8.0,3.0,FAAEFBFCFBFBEDGHCCCCCEDEDFHECDBDGFGFADGBEFCFCGAAAHEDECACFBFBGGGFCFCBBB,False +701,16.0,27.0,21.0,29.0,23.0,22.0,14.0,18.0,ABAEADACBDBFAFDCGBDEDBBFBFADHHAABHDGABACDBDEAFCHCECHDDACAFDFDFEAEDHDFBFBFCEEBECDCDHABFBGEGFHFHGBDEDEDEDCDHDHFAGDGHGHGHBCBCBFHCEBEHCCDCBFBFBECFDGGGFCECEDHBGBCFEEDGBFBEHEDE,False +702,22.0,31.0,14.0,20.0,15.0,20.0,18.0,12.0,GHADBDAFCHAEBDBDBDFDEAAABADEDCAABBEGEGFGEGFDFBFBAEGBBCBCBEGDCDAHCHBADADGFBFBHBGBDCFGDGHCDCFCBEAGFGFHFEBECAFBFBHBHBFBEGEGEBEDAHABADABBGBCAAGDFBAGHCCFDFHF,False +703,21.0,26.0,13.0,16.0,14.0,14.0,14.0,17.0,CHABCBFGFAABAGAHAHAHACBDFHAHEHGCACDBEHDGBHCECEHFAACABHBABABECGBGAGEFCGDEFHBBFAFHFHAHEBEFEGBGBEBEDDDDDDDAHHCBCDDGEADABGBDBFGFBFBFBGEDCBB,False +704,1.0,0.0,1.0,1.0,3.0,1.0,3.0,0.0,DEECEGFGAG,True +705,7.0,6.0,9.0,6.0,4.0,3.0,8.0,5.0,AGABCBCEHFACGFHHCHEACADDDDGBGBGBCEFHBDEDACGCGCGA,False +706,6.0,5.0,9.0,7.0,4.0,10.0,8.0,4.0,BGHGEDCHCHCGCFFGDGDGCBCBAADFFAFEFGAGADFHBAFCBCEDEFCFD,False +707,10.0,10.0,4.0,9.0,12.0,8.0,9.0,7.0,EECFAEAHAHAEAEBEHFDFDAGCDHBHGGEGEGFDFDEBADDCHFDDBFGEGBGBEBEAHAGBFBABC,False +708,11.0,14.0,22.0,17.0,26.0,26.0,22.0,25.0,ADBFFHCHCHCDGFCFBHBHBAGACHDFEFHCBGECDDGEHEHDHEGEGEGECBHAECDHDCDEEFHFDFDABHGDEHEGDHDGFCCCHCHDHDHBAEEGEHEHGGGBBFEFEDEFHFCFAEHECGCAFFFCFBBCAFBCHEEGEGFFECGCGFGFGFAFAGB,False +709,20.0,25.0,16.0,17.0,13.0,14.0,18.0,22.0,CDEHBHBHAHBHBGDGEGBACAHAHGBGBGBAAAGFDEEBGBABABFGACACHGHDFDADHEFDHHECFDACABGHFHDDDAEAEDGDCDCFCBCFHBCBEBEBEBFCGCHFEGGDDBBBCEHGDACABGHGAFHHHBFAFCFHB,False +710,30.0,23.0,16.0,22.0,21.0,35.0,15.0,23.0,FAFAFAFEFEHAHAEBEFDFDBDHFCEAHHHHBEFDADHEHBCCCADEHFHFHFCGGDECGCBDBGAFAFBCDAHADBECEFHCBCBAAAFAGBFADDFDFHBGAAEABFDEDFHAGAHAGAGEGHFEFCABAFCBEBEBHFDDDFDADEEEFBFDACEGFBDBHBHBFGFBFCFGGHAHAFGFC,False +711,6.0,6.0,12.0,7.0,12.0,9.0,12.0,10.0,HGEDHDGCGCGBHBHGCFAGABCBGGEBCHCHFGDEEEHEHAHFHCGDFEFAFAFDECECDCFABCGEGFCEDE,False +712,23.0,31.0,32.0,27.0,25.0,14.0,31.0,14.0,CGABCFCEHDFDHEHBDBDECCFBDGHGAGBGCHCBAEHEHDFDBDCEFGCGCFBAGGGEFEABFBGEAAAAHAGACACECACBGDGDBHBCFGHGBCAAAFBDDDDDDFGFCECBBEEGDADCBEAEAFDGEGCCBCBCBDGCECGCGCGCECECBFBDBABDBDHDCEHEBECGAABDBGGGDEEGEBBAHGGDH,False +713,4.0,5.0,5.0,9.0,4.0,5.0,6.0,6.0,BEFEACAHDHDHGHBDCHCDEDFDGDBEFGDGDFAFBBGACHCG,False +714,18.0,19.0,22.0,14.0,25.0,27.0,18.0,19.0,GEHFCECFCAEFBFAHBCCEBFFEFECDADEDEAEFEBECECGHGAAADAGHBFGFAFHDEABBDGDEHEFEFDBCHEGCCEFBFEHHHHGHGCAFAFHFHFGEHEHCGDFEAEAGFFBADAFFCFABGBABFBCBGBGCDCDHFHCECECDHDBGBCBCGG,False +715,17.0,8.0,11.0,12.0,13.0,12.0,12.0,14.0,BAGDHBHDHABAEGHFDADFECDCGCGADHDHDHABCBHGAAFBFBEHEAFCFAGHEBCDFDFDCHCHCADAEHEGEAEGCGCFEHAGGFAFEFEAEAG,False +716,16.0,17.0,24.0,24.0,21.0,17.0,16.0,24.0,FCBCBHBCBCECDCDAFFHHHCHDBEFABAEDEDEDECFDGGGAEFEFEHCADAFACEEECFCGAEDEDGHGDGAGFBHDHFHCCGEGBDHGEBHHHEHACAEGFDFDHCECBADECHHHBBBFBFBDADCCFCDCBCDEDHHCGDDAAAHBHGHGDGF,False +717,30.0,23.0,30.0,24.0,12.0,21.0,21.0,16.0,ECEDACAHEHCACECDCGCBHAGDFACBCBAFGFGBACCCCACFGEGFHHAHABGBEFFBFDFCGABCDCBBBBBAADADGDFDFHFDCDCHFBFAAGAGAGAGFCCCHABGDGDBDCDEBHDCDCDBGFFHHGBEAAHAHDFDEDAHAGDCDBHAFGGGBABDFCACACBCFEEAE,False +718,8.0,9.0,11.0,13.0,10.0,18.0,7.0,15.0,BHBGDHDHDEAEFFAGAGABHFFFADHDHDGAFCDCAHBDECFAHDHCCBGHFCECEHEFDBDCDGEGDBHBECFCFCFHBEFFFFFHFHE,False +719,12.0,23.0,32.0,23.0,25.0,25.0,24.0,32.0,ACHDECHBHFHGHGHDADAGHCCEBEBCCGHFFGFCBEGCCDDDBGFDHDHDHGFGBCFCGCDCDCDCFGEDBDBEGGCFEFEHEBEHECBFDCDGBGEGBGEGCFEEECGFGADCFEAEADBBCECEHEBEDFHFCFCAABGHHHHHFAFABCCHCFCAHEHFBFBFHCGFBDGDEBHBHCECGDBAFHHHHHDH,False +720,9.0,6.0,1.0,2.0,6.0,3.0,3.0,2.0,AAABABDBGEHAGABCBGFHEAEDEAEFEFBA,True +721,4.0,4.0,5.0,4.0,1.0,4.0,3.0,0.0,BGBCACGCDDFDFABACECBFAFDG,True +722,16.0,8.0,13.0,19.0,18.0,17.0,9.0,17.0,DFEFCHCGADHDEDAHEDEBFHFEFEAEDEDHAHADCBAFACAHEHDCGCGCDCDHDFECEBEDEDEFGGABFBFGCACFDFAFBDGFHCADHEHEGDAEAHHHBHFHFADCFEBGA,False +723,20.0,21.0,15.0,7.0,15.0,20.0,22.0,15.0,AFCDCFCFGFGAGBCACBHAAFGFBBEEAEGHDEDBHBHEHBCGEGFACEGHGHGCGEGECAFFGEGEGEGBBFAFDCBCFCFADADBHEAEHGBGHGBAFAHCBADFBHBCBFAFHBABABAFABHFGFGEHCG,False +724,22.0,23.0,14.0,13.0,20.0,26.0,11.0,21.0,DEBABADADEGBGBEBHBCCAAEAFFDAAAAFEFAFGFCFCBHBCFFFCFBFDFEHHDHCHCFDEDHBHBGAACEFAHHFABAEEEEGBCHCECACGDHAFDFHFHFEFHAGGGFCHBBDBHBEBFBFHHEHBBBABEEFGFEDGDAHAE,False +725,21.0,25.0,25.0,29.0,21.0,32.0,25.0,20.0,FGGGCGEGDFAHHHCCCGAEABFBEBDBDHDCDEDAFGDGAEFCFCEAEADABCBGGGGGCDCDCFFFEHACBCBCGCFCFDBDFCFAHBDDFDFBEHEADCDFHEHFFEGGDGFHEGEBBBDHEAEAGAGAHBHAAGAHAHDDCBCFFFHFEDGDHDBFBEAHBFBEDFCHGFGDCFEGCHCFBFDEDFDABBFBCB,False +726,16.0,20.0,16.0,17.0,10.0,18.0,13.0,17.0,BBBBGCACACBFBABFBCDHGBCHCBADABFCFCFGAHEGBGEEEFDGDFAGAGCBCEFHFHGHFHAHFDFCHAHAGEBDBDGDCDCHFHBDDADCBFADEEEHHDGFGFHADEDHFHCBCBABADF,False +727,10.0,29.0,22.0,26.0,22.0,17.0,21.0,19.0,BCBCBCBDAFHFCECDCDCBHECFCGAGDGBHFDGDGBGBEDEDEDBCBAFAGHBHDHAADBDCGFGHDBDEGEFBBBCBEBEHECDHEGDADCDHDBBGCEHFGCAEAEBEBFBHADCECFCFEDGHGHBHFHGHBCFGBCEFDHGBGFGEBEHEFFDDBDECGD,False +728,11.0,13.0,13.0,11.0,13.0,20.0,15.0,18.0,EFFFEBCDCHCAAAADFHFHGAFDFHFCFBEBGCGAFBCACAHAHEDBBGEDEDCDGBGFGFGCHCFFDHEBBCGGGGGDFHAHDHBFFCHHDHEHEFBHBHECAGEGEFEFBH,False +729,26.0,25.0,13.0,24.0,26.0,16.0,21.0,19.0,DBDFABGGFGHEHAAAAABFBFBGBDBABAGEGCGFEEGEBEDHAEDCHABCDEFAFAGDHHAHADAFAFGBGAGHBDGCHHHBFFEAEDBDBEHDBBEDDHDHDCBCBEHCACDHFCGAGEGDDBEBEBEAGAEADABAFFFFEHGCGCEEEEBEGDHDGECEABHDCD,False +730,16.0,17.0,13.0,13.0,6.0,15.0,8.0,16.0,CCHDADACCDBABEBHDFBEAGBGFCECHBAAEAEDEGCHCHAFBHGHDBDADAFBDBGBHCHCAGAGHHCDCFFDFBFBADFBFBFHAAADBFCFGFBFHHHH,False +731,16.0,23.0,24.0,23.0,24.0,17.0,32.0,25.0,FFFFFFFDDEDGGHGHGHGFDHBCACGEGEBEBECFFBFBDECCDEHCFGEACHDHDHCFDHEGABHEGBGEAEHBAGCGHGHEEEDEDHFCGDGBAHAGAGDGBACCEAGAGAGAHFBCHCGCDCHCHBDBGBEBGCDFDBCBHEHEHGCGHBCBCGCAADDDGHGBDEDEGBBDFEAEGBCH,False +732,2.0,3.0,2.0,0.0,1.0,3.0,2.0,1.0,FCFGFHCBGBAEAB,True +733,6.0,2.0,3.0,2.0,1.0,4.0,1.0,4.0,BFFCHCHCHAAFADBGFDAHAEA,True +734,5.0,4.0,6.0,8.0,4.0,8.0,3.0,7.0,DGHGDEDEFAFBFBDDEAADFDHCHFAFBDGHHHHCCCCFCFBEA,False +735,11.0,7.0,8.0,6.0,4.0,4.0,8.0,5.0,CHCACAGAEDFDCBHDHFHBCDDHAFGGGCACAGAGBBBGBEBDFAAGAECEA,False +736,20.0,16.0,16.0,26.0,10.0,23.0,15.0,12.0,BDBHCCEBDBACHCDFGFCADHDFDHAECDAGAGCFEFCFEDDDDDDDCFHHADFDABEGGGAGAGADABAFCFAFDBEBEGACADDDHAHBECHDGBGBDDEGEGDBFCFHBADGHGHFFFBFAFAFCFCFBFCFBA,False +737,23.0,11.0,24.0,14.0,10.0,9.0,22.0,11.0,FHADCDEAAAABDBHAFADADFCGGGHGAEAHCGDDCDCDHAHCGGGGCACFCBCBCGCHAAFAHEBADAECGCGCGDGECEDGBFCDBAGACFHAEGCGEGBGCECHGGFHFABABABCCDCE,True +738,26.0,23.0,28.0,29.0,22.0,16.0,18.0,26.0,EHDFFHFHEAFFBBEHDBBBDBDCGEGEGCBCDGHAHDEDEDFAFGCCCACBDAGAEFHFHADAFHCDCDBDHAAAAAHCHCHFHFEFHCHFBAEDHCBCBCBEBDADGDAHAGACACBHEDDDEHCHBDECCGBGBHDCDHDBGCCBGDGCHHGFBAEGEAFACACBCEEEEHEGCGAADAEBGDDD,False +739,8.0,2.0,10.0,6.0,9.0,6.0,10.0,6.0,CGBDCDCHHEEAEACAEEGFHFDDDDFGFEAHCCCCCBFGAGAGEFAGAGHCEGEGH,False +740,11.0,8.0,17.0,13.0,9.0,9.0,18.0,8.0,BGAGBECGDGHFHBHBGDGDGCCCCCCFCFDFAFHBDADGDGBBCACAFEDGDHCECHAEEEBDCGGAGFGCGDAAEDEACHEHCCFGAGDGF,False +741,4.0,2.0,8.0,8.0,5.0,1.0,3.0,4.0,CECEAEHCCADDHDHGGEBHBECFCDDDDCDAGAC,True +742,2.0,9.0,1.0,2.0,5.0,5.0,1.0,4.0,CBHEDBAFFDBABEBEBHFHBHBFBGEFE,True +743,18.0,19.0,21.0,21.0,22.0,11.0,26.0,21.0,EAACDDDHDGEGBHHHHEBEBABHEHBFGCGDGEGCDCDGGCGHFFDFBBGACADADHHADCDGDGBCCCBEDECAGHGHBFCFEDEDEGGCBEFEBEBEHADBHBGGGADADFGFDAEAGBBHGDBHGHCHCACACAEFEGHCECEAFHCHBGEGECA,False +744,31.0,23.0,20.0,24.0,21.0,22.0,28.0,21.0,DADEBEBEDADABCBFGGGGGHGHAFFGBGBGCGDGFGHBCCFDEHEADABAGGBGFCFCAGAHHEDBHBHFFEHAGAGBCDFAEBHDDDDEHHACFBHDGDGACFFBDBAAADAHAHCHCEGAHAGEEEEEBHFFGADABABEBEBCDCBHFHFAADFCGCGBAADDDFCCCHFEFECEAGACAGDGFE,False +745,5.0,11.0,15.0,7.0,10.0,9.0,7.0,16.0,EFHFBCACFCEHBCBABABCECFHHHHFEFHCHCFCBHHGGEGEDDDHAFGEGCBDDDHEEAFBBCHCHEHGHBCBCDCG,False +746,1.0,0.0,6.0,5.0,2.0,2.0,2.0,0.0,GDCDCACECEDFDGCCFD,True +747,14.0,8.0,8.0,12.0,14.0,15.0,12.0,12.0,HCHDFEEGCBCDCAEEEBEFEFCABABFBFDEGFAHEHAHCHGGFCFDEDAHCHDFDGDGABHEAAFAFHFEEGAGDDFBHBHGDGEGAGAFAFD,False +748,23.0,22.0,15.0,27.0,27.0,24.0,31.0,19.0,CFEFAHGBGDEAEBEAEBHBDDGBFAHCGFHFHGEGFAFADBEFHBEBCCFCGEGADBBGGCGBGHHBEGEGABBEEEAHAGEGFGAGFCCBFAGBGFGFGFADDBDBGBFEFGFAAAABHCDDDDDDFDFHFHBGDEAEDDDEDEGEDEDECHDHCFAGAHAEAGADFGHEHDHCCGEGEDBDFCHC,False +749,18.0,23.0,17.0,19.0,17.0,23.0,21.0,21.0,EAADEDBDBFBEECFCDEGFDFHBDAFFBCCCGCHCHAFAFAGGHGECECEBEGAGDGDHEFEHCBAADAFBFBHBABGBGCFCDHFBDEDECFGFBCHHDBBCHDGDFFBFBGDGBHHAHABADADEEGHGHBHFFFFEFGCGCDEHHGHGAAAGBBH,False +750,26.0,15.0,24.0,31.0,22.0,18.0,27.0,36.0,HFCEEEDBCEHFDCDCDGDAHEDGBCCDCGHDEECFHFAFADHFCGEEAEHEHECGABAHFBFBFDACBDBDCDHDHGFBFACAHAHABAHHHCDGHGHGHAABFHFGGHADDDDDADCDEDGDEAGGGGAGBGACCHBHBFDDEEHEDDHCHCHCHGFGAHHHBHFGCGHEEDEDFBAGHGHCECGCAHAGFEADAGA,False +751,2.0,2.0,6.0,6.0,5.0,4.0,2.0,6.0,DCHAHGHCHCEBEGDFCHCDCFEFEDEFHADBD,True +752,12.0,16.0,4.0,9.0,13.0,13.0,11.0,4.0,EBEBDBDBFAHAHADAGBCBFHEEAFAEEBEFGFEFAAAGGGBAFCFCFDGEBBBBBBGAFEEDDDGAGFGCEFEGBDDFHB,False +753,20.0,22.0,13.0,25.0,23.0,25.0,27.0,11.0,DBDAFFDEDEDEFEFDBCFFHDDEEEBEFDFEFEGBGCHCEBEHEHAABAGGGDEAFDFBGGGDFAFAFACHEEBHACBFECCGGGGGGFDFAFCGEGEFHBDBACAHAEFDBDFGABFBEGCGCDHDHDGDBDBDGCFBGCAHGDGBBFAFABEGEGABADADGB,False +754,13.0,24.0,24.0,21.0,25.0,16.0,20.0,11.0,BHBDGCGFGFGFGHGHBFGCEEFEFBAHEHEHEBCDEDEDBBCBCEFECGCDBACAGDGDBBHCCGDAAEAHCEFECABABDGDGCBEDHGFEDEDBGGCACDDBEBCBDFGGGEEHECECEFDFDBBBDCHAFDCBCBCGCFFACAEAEDBFE,False +755,21.0,23.0,12.0,20.0,22.0,23.0,13.0,24.0,FBFBCBFBFECEBHBHDHBBBFBACGBGBDAGFDACHHGCGHFDBHEEEFEAEBEBFGAGAGEDDFDFEFBCAFDFEAEAEDFDBDHECDCFCEAHAFEEHAHGHGHCBDAEGHBDDDBDEHGBAHAFCHGBFHFHEHEADHFHFHFDEBCAAAAHAD,False +756,9.0,16.0,8.0,17.0,8.0,7.0,7.0,4.0,EFEFGFGCCBABHBDDDDGDABBGBFBFEACDBDEDHCGEGBCBCBFDDDEAFABADAHEBADHDCCEDGDBBBAD,False +757,15.0,20.0,18.0,27.0,18.0,16.0,16.0,19.0,GHFBGBCEEAHDBDAHAHEBFFDDDDBFBEEAGBDHDBEGHAHADDEDCFCFBHAHBHDDGDGDECECGHGFGDADEFCFCFDADBGEEBCDEDGABABHBHBHCDCECECEGACCEABFBFBCCHABGHFHFACDDDDDGHECGFGFH,False +758,24.0,10.0,20.0,10.0,13.0,18.0,25.0,18.0,HEHAHAFAHCGCGCHEBGCGHGHGFGCGEABGHGFGHCHEAACABAHACFEAGCECBGGGGGACDFHFAFDFDFDFBEEAEAECFCAADAGFCHHECFHGAGHGEAHFGCCDBDBGACAGADABBDBDCFAFHGEFCF,False +759,5.0,2.0,3.0,3.0,1.0,2.0,7.0,3.0,CFAGGHGHGHBDGDGACEDACAGABF,True +760,23.0,15.0,19.0,10.0,31.0,25.0,21.0,16.0,FGFGHGDGBHACAFAFEFEGEBFGFGFECEDBFEFEHHCFAEACFBBBAFEDCGCEAECFCBBHEGEDEAEFBFGFGADCCCBHAAEEBABAHAHACECFHFEDEABFEDEAEBECACECGFGFEAGAFEFACHGDGAEAEGHHHHGDCBEDEHFHGGCG,False +761,4.0,5.0,6.0,6.0,5.0,5.0,6.0,6.0,EFBFBFGDHCHFEFGGBDAGACHCHDHBAAECCBCDEDEDGHG,False +762,5.0,7.0,14.0,5.0,9.0,9.0,6.0,9.0,EGEFHBHFGFHCEDEBEFACAEAECHCHCHCHBGCFDFCCACBCDHDFGABHBCECDGGEFCFB,False +763,7.0,10.0,9.0,14.0,6.0,13.0,15.0,4.0,FHBHAHAFAEDCDEAEHFDDGFBFBFDGGFGBGBCBFDGDBCGEGECAGAGDGDFDCDCDFGCGEBDGFBACFBFDCG,False +764,18.0,17.0,21.0,10.0,17.0,19.0,30.0,14.0,GFCBGAFBBEFFCGHGEADAHFHEAEAHAHFGGGEGECCFAGAGFFCACBFAFAFGGGAEHGHFHBHCACHFAFDEDHGEGDFBCGCAHGCEBEHCBGBDDCAGBDAGECECACBCBCGGGBBBBBECFCFEFHGDGDGDGEGEGC,False +765,16.0,9.0,24.0,14.0,21.0,12.0,17.0,12.0,FCCCCEGDGDFBEGCBCDDDDCHFGACDHECCCEEAHGHGCCCFEAAADAHGEBEFDDDCDCEAGCGDHEAEAGADAGEFCFCFGFGEAFHEECECEGHGBFCECEBFBCAEBGBGHAHAHAHBE,False +766,2.0,5.0,3.0,5.0,5.0,3.0,5.0,14.0,GCCBCDHEEEFHHEBEHGHBHDHDHAHFGAHDGDGHHHHBFB,True +767,25.0,19.0,25.0,19.0,30.0,21.0,34.0,24.0,AABAGCCCGCDFDAEECGCHBHGHGHDAGCGDFDCEGEBAGFEEEHHAGAGAGFECEHGCECEHFHABEEEBEFEBEFEBCGGGDGABEDEDADGFGFCHHHHDDFBFBAEAEAHGFCFAAAAABAFHECGCDCGFADDBHBGCEHFBBGDHFAFHBHCHFHAGGGGGGAGCGEDEBEDECHFHGBDEDBFGCCCCE,False +768,25.0,18.0,18.0,14.0,17.0,14.0,28.0,21.0,DBBECABABAFFCHGBFEAEHGGEEEHGHGAGADAHGCCFDFDGAFCECECDBBBFBDHHGHEHBHAHGCGFGHHCCFAEAECGAGFHHCEGGGCDCEHEHEDGDHDAGABACCBCBGFFBBHBABADAGGGGHGAGAGAECFBAGAFADAEHDD,False +769,1.0,3.0,1.0,7.0,6.0,6.0,6.0,3.0,EFGFHFCEBGHFBDEDEHEAFDDGDGDGDGBEF,True +770,10.0,20.0,19.0,21.0,15.0,21.0,16.0,16.0,CDHDGGGCGEGECDCDCDABFBDBFBFDFHFHDDBEAEHBGBGCDBGBCHHDGFGCHDHCGCAAHABAFHHBDEFEFCFDFCFCFAHEFBFBGHGDDDCBEGGFEBEAEBDBHCHAEFCDCBFEFEBHCGCBFDFDEA,False +771,4.0,6.0,5.0,4.0,2.0,2.0,2.0,5.0,DBACDGDBBHBHCFDECECACAHAHGBFBH,False +772,20.0,21.0,27.0,26.0,23.0,24.0,13.0,18.0,HHGDAACADHDEDCABDHDFCFDBCFCABDCCCCFFFDFBCBHBGEGHGADACFDGAADDDDDECEHEHDFEBEFCFHFAFCFCFAFCHHHCEBEBEGECECFCHEFDCGBAFADAEAEDEDEFEHEGDAAEBCAEABBFBFBEADGCHDBGBDCDFGGBCBCBEHGHCHBF,False +773,23.0,11.0,12.0,12.0,15.0,10.0,15.0,14.0,HHBEBEDEBGBDFCECGCGEGCHDHGHGBCHAGAGAFAFAHAEEEAEAGBGEGCGAACABBHDABFDFAHADGHFBCDDHAAEAEAEAEACDFDEAAAHFDCCGCHHGDBFF,False +774,17.0,24.0,28.0,15.0,15.0,16.0,18.0,18.0,EFEFEBGCDADCEHBHBHBFBECECBFBFCGCEDEDCCFCGCGFGFACCDFHAHGHBHCHEHECCCGGFCHCADBBBGHHEGCCCGCBHGEGBBBAADCDCDCDADADABFHFAGBDBAHGBBABFEFGBEAHBGCCHFHGDABACAFDEA,False +775,3.0,0.0,2.0,1.0,0.0,2.0,2.0,3.0,AGHGHFDFCHCAA,True +776,17.0,9.0,11.0,6.0,12.0,12.0,17.0,14.0,GCGDABAFGFGCCECFABAEAEBGADHHEHAAAEDEAEABDFCGBADAEHGHFFFGAGFCFDBHBFGHHCGAGHGEGHBHCECEAEAGFCFCBHGHGH,False +777,4.0,6.0,1.0,5.0,7.0,2.0,6.0,4.0,HEFEAEAEDBBGDCDHDFEBAAHEHEDGBBBGGGG,True +778,6.0,7.0,4.0,4.0,5.0,13.0,4.0,5.0,HEHEAFGFAFAFBGBAFFFDEDECBCFGDBEHFAFBFDFHFHGBACCB,False +779,9.0,7.0,5.0,6.0,9.0,8.0,7.0,9.0,DGBEBEDHAFAFHFHFCFCEDEGEDEDGHAFBHBAGAFBCBHFAGADAECCBGEGHHEHA,False +780,19.0,21.0,16.0,16.0,23.0,19.0,26.0,22.0,FFCAGEGEGAHBBEBEGCDFEFCFGHHDHDHDBEFFAGEGAGAGAHEHFAEDBACCCEDGBEACFCFEDEABABABFHFBGBGAGEHHACBCGCHCHGHEABACDBDHEGFGEADHFBDCDCEBBAGHGHEHEHGHDHDGDGFHABECEBDGGFGBGBEFFF,False +781,15.0,24.0,23.0,18.0,23.0,14.0,17.0,21.0,FEAGCCBABABAFAHCDGHFCAEGBGBGHHBBCBFBABAEDEDADHFECGDGAHEBEBECCGCHCHEBCFEDDDCGCGDGDHEFGGCHCBEFECAHDEDFDEHEGEFBBHGGCECECFBDBDBAHAHEHDHECFBFDCECABABHBGBCHFHDHE,False +782,14.0,24.0,23.0,18.0,18.0,17.0,19.0,17.0,GAECGCBBAGAGAGFEEDDFBEEEBBGGEECCCCBEGEGFGDGCHCHCHEADBDBHBHFGADBFGDHHGAGADDDDDCBCDHFBFHDAGFHFHFHCBCFEHHHBFCFHFCGCBCAGFEBDFCECHCACBDBCEAGDBDBEBEBEBABAFC,False +783,17.0,21.0,14.0,26.0,20.0,11.0,14.0,15.0,CHAHEHDHGCCADABAEDBDBFAEABGDDCGADADBBAFCEGDBEBDHGEGFHEHEHEFCFDGHADADBDBDCDCGBABDECEDEDFDCDCDADEDBDHGBGBECDHEHFFBAEAEBEBGHGEBCGGBEFHBHCFAFA,False +784,9.0,13.0,21.0,19.0,11.0,19.0,13.0,15.0,ADHDFGEBBCCDCDCFHAGDBCBCECEAGAHCDEAHBHEFEAHHGDCHCHDHDHFBEADFCGCHDHAFBGBGBEFDFGFECACFEFGFDCDEBGBGCFBFCDGDGCFDFHFHFCFCDCDB,False +785,3.0,4.0,10.0,4.0,5.0,8.0,5.0,7.0,FCFCGCGEAAGFCECECHFFDHCACGCGEBHFEFHBHDFDBDBHHC,False +786,13.0,15.0,20.0,21.0,12.0,14.0,14.0,18.0,BFDGDGDADECHCHCEDGDBDGHCHDGCABEEFEFGGDDBDHDHDGCCEBDFDFBHBHBHFHFAECEBAAAFAEAHBHGHDFEFBHBABECCCCCDEGHGBFFGHCDCBGDCCCFHDCACAFGHADA,False +787,12.0,21.0,22.0,19.0,22.0,24.0,29.0,14.0,CGCGEECEGGBEAGCFFFCDCEEACFBFBGBGDGDHDHCBCGADEHGHBFGFGFDFDBGEGEBFCFCFCFABDBCAFFGDGBFHCHEECDFDFCBEBFHGCGEGAGAFDFCEGEGEAAHHHBGCGCGAGDGDBDFGEDBDFDBCHADEEGEHEHABBFEHBCB,False +788,17.0,13.0,19.0,20.0,16.0,16.0,19.0,15.0,BDCEGHGDAFFHFHDADAHEEEECFCGDHBHGGGAGAEFGBCADGCCCCCCGCDCBEFEFDFECADABAFEBGBGAADGEGHADABHFHFCEDHDGGCDCDFDADGHCFBBCBCEHBHFHDEDEDEGHGAAAFBF,False +789,28.0,17.0,13.0,32.0,28.0,13.0,27.0,17.0,AEADADBGBAFAEADGBAAGDDEGEBEFCFCFHFHAEGEHDHAADEDHDCFCBAEGEGDGCGAGBGBGBFDDDEDGBGBGBDDGGADCDBGAEAGDBCADEDHBABAECHCECAFEHAFACDCDGEHEHFBEHDDDDFEAABDHGHGHDAGECEGEGDHEAEGEGEAFHDHDFAE,False +790,20.0,14.0,14.0,14.0,17.0,15.0,16.0,18.0,FCFDDDHCHCEGHADCBGFEFCFEEEEBEADABHBDEFCABABAGAGEHHBHBDAECGDEAAAFAEADBHCGGBGBGBEFEFEFABAGFHHGACDBDHHGFDACEHDHGHFCFDHCHCHCEFAGAGAG,False +791,18.0,17.0,18.0,19.0,20.0,20.0,6.0,18.0,FHFHFDEAADAFBBACGHDCDFAGGFEFADEDBFBFECEAFAFACCCEFHBHFHBBACHFDGDCDHDHGBAHCDCBHBEEEEAECBABCBCEDHDFDEDEDEAEADACAHFHFHEDCCABEHEBEHCFBFGFBDHC,False +792,14.0,17.0,13.0,12.0,11.0,16.0,16.0,11.0,DDBDBDAFBDBFAFAGBDEGCCECHCHCGFABGBCFEFECHFBABAEECBDHDGDGHGHGFCFHEAEGDHBCBEFHBGAGACAHAFGFGFDEABFBABGFGFGBHCAEDC,False +793,9.0,19.0,17.0,11.0,13.0,16.0,16.0,13.0,DCGHBFFCGEEBEGGAGFDEEBFGHCHCDFDBCBCFCFCGCGBBBCBCBFHFGCAEABHBABGBDBDFDHAHFGFHBBBGHGHECFDECEGHGHDAAGDBCECDAEAEFEFCFH,False +794,18.0,14.0,23.0,18.0,18.0,15.0,28.0,20.0,GBGBGFGAEFECEBGBECECFGDEDGFCFGGHCHCFGDAHHCHCFCFCGCGCEAHAEABACDBDBAGGCGHAHBDFDHEHEGAGEGEHHDCDGFHBHGHFADECACAEABFCAHGHGBDCDFDFBAGACDGGCDBGGADHDBFHEHEAEGDCEC,False +795,2.0,6.0,5.0,6.0,3.0,1.0,4.0,1.0,GDGECBCHDEDECBBFBCBABDGDGACD,True +796,20.0,15.0,22.0,19.0,22.0,17.0,35.0,28.0,EHGHCDCDAEBCBFBACHCGEFEFEFDFHGHDCGAHDCGCDCACBGEEHEHGGGEHEFEGGAAAAHAFFECCAGHGHGHBACACDCFEAGGGGGGGCGAFCBEHHGDGHGADAHGHBDGAGBCDCABAHDDEEFGGEHHHBBBDBDHDHDHFHEHBCDCGFGECEFFGFGEGHFBEDA,False +797,22.0,14.0,14.0,13.0,13.0,14.0,15.0,9.0,HCHGGBDEFAFAGAHDCGCGCHCGFAADEDEABAGABFEFEFEBDFGABHFDAABCHCFCADBBAGDGDGDCDFEFGBDBDFFGCBCBEBGAAAAAAHEHEBEGCAAAFHECEC,False +798,15.0,14.0,14.0,26.0,14.0,22.0,16.0,23.0,DCGAADDDHDHFFDBGGFGEGBBDHAHFFFFAFCFBDDFEAEDHDHGHGDCHCFAGBDFCFEFGAGHECFCEDAHAGEBFBABDEDADCDHAFCFAFHBDFAFADEGEHEHBHGFGCGHGCDCDBBHHHHBCBCHDEDEDEDHH,False +799,27.0,20.0,19.0,24.0,17.0,17.0,26.0,21.0,GFGDGDCDFGBGBEBGBHHFDADAHEHEBBBHFFGGCADACAGHBHAAFACACHBECEFAHADGDAEHECFABCGCAHBHAHDGEEHFDFHFDFCAHDBDBFEGDGDGHBDBGAGEGBGCCECEBEHAGABADADADECGCGCAFHGHBFACACFDEDEBGACAGHGFDDD,False +800,14.0,22.0,27.0,22.0,29.0,27.0,20.0,20.0,BCBCBCACACAHDBFCHEHEFBGGCGCABBHBEEEBECECBDHDEBAACGCGFGFDFGBCDAHHHHFFEDDDDEFFHFDEGGGHEAEDEGBBDFEADFCGCGCHFHGHGEDCHFFFDFDCHFBCBCBCEEEGACAEHEFGFDFCFBAEHECGDEFGHGAFAEBBBBDCEHFCFEFDCDEDE,False +801,5.0,1.0,4.0,0.0,2.0,1.0,0.0,1.0,HCAEACAFBEACAC,True +802,15.0,14.0,17.0,11.0,11.0,11.0,14.0,5.0,DGAEAFAFCFDADEFEFCACGEHEFGCHABACABHBADDFDFCGEGEAAACHCGDGCGBEBFDCABBBBDBABFGGCCCEGFBBBEDAHCGCGCGCED,False +803,19.0,24.0,22.0,27.0,21.0,24.0,25.0,26.0,HFAFEFEFCCCHCHGDDHEHEDEACCFAFBHDEDEBGCGBFAHAHAHFGDBAGAHBHFEFBFEFABCDHDGACACBGDGHAFBDBCFHFHDHDGDADBCFGGBDACGHGCECEGGAGDGDGEGECADHDABGBDDCECEHFHBGGEGEHBFBDHFACAFBBBBHEEEGCDHGFDFDFEFHDHDCBBBC,False +804,14.0,12.0,12.0,16.0,9.0,14.0,9.0,8.0,ABCBAFDEDFDHDCDBAFCBGBDBEAEGEBCDGAACABDECECEHEAGHGDBHFFFCGDADFFFGFDBDFAHCHCHCHCBADADADABFFGGEF,False +805,10.0,5.0,7.0,4.0,17.0,8.0,9.0,3.0,AAGAGAGAGAHECEFEGEHEBEAEFDADFEEEECEDECHGFEFAFBEDFGBEACBCEFBCCGG,True +806,16.0,25.0,13.0,17.0,23.0,16.0,21.0,18.0,CBGEEFEGBBBCHGHBAAAAGAGEGCHCEDBBBBBHHHHDAFFEEDEDAAADFEBHGHDHEGEGHCECEBBDADGGGGGDGHEHEHEBBBFGFAFDFEFEBEBCFFEBHBECDBDFAFAGHDFDGBHDCFCAABCBHEGDGDEBGCCAF,False +807,3.0,8.0,5.0,8.0,9.0,8.0,9.0,9.0,HFFFBHCHEBEBEBGBDCGCECEFDFBFGAGHHDHFACHDHDEFBGDGEHEADGDBEGG,False +808,18.0,19.0,24.0,19.0,15.0,25.0,23.0,17.0,CDGFCFCAGHEAEADCGEGACBGFGDHEEECACECECFAHAFDCDHDFEBEHDFDFHFGBEBGGGBBBHBHFAEAFGFAHAGAFCGCHCHGHBCDDFDFDGDFBEBEBFAFCFGDCCHGHADCBFBGBGHFCGDGBCAHFDFCFCBCBDAEABADGFGHC,False +809,24.0,16.0,20.0,18.0,20.0,16.0,26.0,18.0,HBEFGCGHAHADGCACAFBFAFCEBGBFDGAGAEHHCDDHDFDHDHDEECGABCBFEAEHDGGGGBABGFEBCAEGBCFCHGHBHBABGBHFEFCCCCAHGEGEFHFDGAEBHDADCGHEAEAEAEAEGEDCDADGDGAGAGAEHDGCCFCFCADBGF,False +810,7.0,10.0,7.0,14.0,17.0,13.0,14.0,8.0,DEAEGEFECACABGEGEAHGHGHAEFEFECHDDFDBDBCBDBDFGCGEBECEDDDADBEFEBDFGBDFHGCFFDGGFEHEHFHBGAGEGF,False +811,11.0,12.0,11.0,18.0,16.0,11.0,15.0,16.0,EBEBABDHDHDHEHGHFAAGGCAFEDDGEFAFHDBDBDHEGGGGBCBCFDDDDDEDBHFEBHCHABEFEFGHECECBFGGGEDHCHCGEGACAEAECHABCHDADFDFHG,False +812,7.0,8.0,5.0,1.0,6.0,6.0,5.0,5.0,HHHHAEACACBEBCCAFAGEFCFDBHBFBFEGAGEGBGFABBE,False +813,7.0,6.0,14.0,17.0,20.0,8.0,11.0,16.0,BCHCAFAGAHCEFEDEHEDCHGHAEDGDFCFHGHGHAEGEGFHBBDFEHEDEDHDEDEBGDDFBEHGABCEDECCCADGHEHEHCHCDCDCDCEEGEFD,True +814,27.0,14.0,15.0,25.0,17.0,16.0,12.0,25.0,HFFCACAHFFCBCFFGDDECEFEHCBCBCDAAAGAHAHDECEFHAHAHDEABBEBCFGBGDEAEAEADGHAHACDHHHBCBEDFFAFHFEEGAAAAAHAHEHEDDDDGAGDHDBDFFAHDBACACAGHHDGBGBEDDBDHFHECGDDDHDH,False +815,9.0,8.0,11.0,6.0,5.0,16.0,9.0,7.0,DDGCCHAAADDFEFBHDFFFDFCFCFCFEBEGGGCFCGHGHEAAAFFHBCBGBEBCBFFFCFCAAGAHHGB,False +816,27.0,23.0,14.0,24.0,26.0,27.0,25.0,22.0,DABHHHEHAHAEFDBAGABDBGHDAAGAGFBAHAHEEDABFGGEEADAFBCACGCGCEFEBEBDFDCDGDEFEHEHFAGAGCBCGCBCBEDAGGBABHDFBFBDEHEHGBFEFEBDFHFHFDEECAFGFGFEADHDAGAGADCDCHFHCEADFDGEAFBFCFDBEEDGAGBEFEHDHGAGHGHFBFBF,False +817,1.0,1.0,2.0,2.0,3.0,7.0,3.0,4.0,FFFFADHDHEHEGCFBGECFHFG,True +818,10.0,14.0,17.0,5.0,12.0,5.0,16.0,9.0,CACBHAACABGDCAEAFGBEHEGCGCGEGEDBGAGFHBGCECEFEGEGBHBFGAGHEABDFDBCBCBHEHGHGBDCACBGBECCCCCH,True +819,20.0,12.0,13.0,11.0,16.0,13.0,21.0,6.0,ADCECACDCEGDFFAFBGBGBGBAAAEBEBGFDADEDAACACDCHHBGGGGGGGEGAAHFEFCGDGBCFABAFEGCDHFECEDEHABCDAHFGAGEGAGAEAGBFBCEFEFE,False +820,24.0,22.0,18.0,21.0,20.0,19.0,14.0,22.0,ECFBHAHAHAEAFBFGDGDCBCGAEAHABCBHFEDEDGBCDCDADABAEAEBHDGDHCBAHFDCDHHBHEGAAFAFCHCDDEHBFBFDGDGHBAFCEDEHFCEHEHEHGCGAHABCBEFHFGCDCDFBFBFAFGBDEDAGCHBEBCBADAGEBEAEAFFH,False +821,24.0,21.0,19.0,22.0,19.0,13.0,20.0,29.0,DAHAHAFEGCDEECECAAEHEFDDDGAGAGAGABHBGEHDHFHEHAHAHAFBHBHCAADCEBBGDECHGFGHGAGEDFDFDHHHCGAEABFDGBECECAHACFCHGFBDHGFDHBHDDDDGGHEHAHBGBGBHEABBFBDBFBDAEEBECCCCCACHCBCHAHDGDB,False +822,16.0,25.0,27.0,23.0,14.0,15.0,16.0,28.0,BHCHCDCAGFGAGBFHEHBABGDHBABFBGBDCHCHCHEHAHEHCHDBGBHACADADAFFHAADACBCBEGEFDFDFDFCHEHDDBDEGEDHHHCDEGHCFGFDEDBBGFGCGHAHBDCECHCABHFCCHCDEDCDCGBBEHDHBGBFEFCACHCBBABCBDGC,False +823,19.0,16.0,17.0,19.0,13.0,21.0,12.0,12.0,AAFGBDHDCDFDEHBBFHFCDCABBFDFGEGEBCHDDDBDGDACAGABEGECECECEFEHCHAGDDHCCDAEFFAFBFBGDAEHHBABAHADABGBFCFGDCDFHFHAGAFAFDFBACACFGFEFECBC,False +824,23.0,14.0,24.0,16.0,17.0,21.0,26.0,11.0,EEEECEBHDFDBDCFAABFDEEGGCGEGFHDGAGBCFCHCFAFAGAGFFBGAFAEABCGAEADADAHBBEHCHCBCBCDCECGHBHAFDEDEAAACACFFECEFFGACCDCFGGCGCGFDFHFGCGCGAEAGGHHFBFDADABBCGGGDGDG,False +825,16.0,23.0,19.0,19.0,25.0,21.0,19.0,16.0,BCECEGEHBGBGDACADFFBABGGEBEGCGAGDBCFCEADAEFEDDCHCDEDGBGCFHFGBEBEBEHCHCEBEDEBFBFEFHFHFGDEAEBGBEDDCBHDFGFCACAGAHBDBDBCCFCFAFDDDADHEEEFHAEAGBGCAHHHEHFGFBFGECHABF,False +826,8.0,5.0,4.0,4.0,6.0,3.0,1.0,4.0,CDGDCFEEEEABABADAHBFBHACAFHEAEAHCBD,False +827,24.0,26.0,18.0,19.0,16.0,34.0,27.0,29.0,CFAFCHHGFDHDBDBDCDCHEFBGBGBHBDADCGCGHGFDFBAHDDAFECBFFFHFAGECAHAEBEAAACGEGHGEABAFGCEAGFFHFGACBGHGAFHCHGHGBFAHGHBHBGBGAGCFBEDHBFBHEHEBFGECEADHFHFHFDABFEFHFEFBFBABDBDFDADGDGCAEAFCFCFCDAGGFGFBHHHHB,False +828,2.0,3.0,1.0,7.0,4.0,6.0,1.0,1.0,ADDDFDFEFEDEBFBEGFDADFHCB,True +829,18.0,8.0,19.0,22.0,14.0,21.0,12.0,12.0,EGEGCHAFEECHDBDBDCFAFEFDFEGEAFCFDADADCHFHEADAEHDHCCFCFDFHFDFDACACACEFDFDGBFBCGEGFGCGCAHADACEDDGCCACHBABDBHAHFFFDDHACBDEAEGGGFD,False +830,14.0,17.0,12.0,13.0,7.0,7.0,14.0,9.0,EGEBHBDCDGECBABADDGCABACFCEBDCCADADFGHGHGFGBGBGHGFDDCDAGABACHHDHDFDCBBGBAAFACEHAGAGBEBHBCBEBF,False +831,13.0,21.0,11.0,11.0,12.0,12.0,12.0,8.0,EAEDGBFBDBCHEBEBEBCHCHAFGGBCDDDCDCBADAFAFABADFCBCGEAEDBAFAEHEHADFHBBEHEFBFGEBHFGBCBCBFGGAGAGBGCGFBDB,False +832,14.0,20.0,21.0,16.0,26.0,24.0,30.0,17.0,BGGGEEEBFFFEFCDGGGGGCGABDFGHCAFFFDFEHDHAGAGAEBEBCBCAGBBDBFBFEEEDDFCCGCGEGBBDBHEDCFCHGFEEBGCFAEGEGECFCGCHEDDCBEDDDHHHCGBGEHEHGDDCGCGBGEGEBEHECGGAEABAFAHAFAFHFHCHCFFFHFBA,False +833,0.0,0.0,2.0,1.0,0.0,7.0,1.0,2.0,GFFCFHDHCFFFF,True +834,15.0,17.0,13.0,12.0,21.0,19.0,18.0,23.0,DEFBAGHEHEABHDFGFHFHCHDHECEHBHDGDGFFCGBFBEEHHCDEFECEDEBCBGEGEGACAGHGHAHDFCBHGFFFFDACEHEBFBHBHGAAEADGGADHHHHGHGFAFCFCGEDFFABABGECACABEBEBEB,False +835,9.0,17.0,15.0,12.0,13.0,15.0,12.0,18.0,AEAFDHGHGFDEDBFBABACCCFCHEHCFEDHFGFDHBHBHEFAACHEDECFCGCBCECEGHBHCABDBEGFDFDBDBEGEFFCCGHAHAHGHDFBBGBGDGHBHBCBFHE,False +836,24.0,27.0,17.0,31.0,24.0,22.0,21.0,23.0,DCGBEBCDEDADFBFEDADADBDCDCDEDFDGBGCGBHBHBHEHEDEDAGBGFDAHGHBCECADBDEDBFFAFAFAFEHHGCGFEFDDGDGFBFGEGEBAHAFDDHFABBBDADAHAGAFFFCGGEECHGAGAEECEBFBCBHHGEFDAAECFADHGHCHBBBBDEDHBBBEHHAHCHCAEFEHADGDC,False +837,8.0,2.0,11.0,12.0,11.0,8.0,3.0,11.0,BHCHEDEHFAFHDHCHFDCDFDFDAAHCFDDADHDECECACECAFEHEGDGEHEDEHFCBCGCAEA,True +838,12.0,19.0,12.0,11.0,20.0,17.0,13.0,16.0,DEFEFEHEFBFECEAEAGBGAFEBEDFGFGAHFHFCGBBBBBBHEFEBHBGBGHCHFBCDFHAACCHEHACDBFEGEDFBCBABHHCHEHACACEDDDDFDGHGHCAGFDFBEEEGEGBA,False +839,1.0,4.0,3.0,4.0,6.0,6.0,4.0,1.0,GBEECAGBFBFBEDCDFDFEEHEDGFGFC,True +840,5.0,4.0,4.0,1.0,6.0,4.0,2.0,2.0,GEBEFEHEAADACACFCFBBHCAGEBEF,True +841,15.0,12.0,13.0,8.0,18.0,15.0,11.0,15.0,FHFHFEAAHFEFCGEHEHCHCBCAEBBBCHAHAEGFGABHBEBEFCBCAHDHBEAFGBHAFEFBGCFEFCDADBDEDEDEGEFEFAACHDHAEACGEGHGCGAGFDC,False +842,17.0,27.0,15.0,15.0,25.0,21.0,18.0,18.0,DBEBDBEEGGGBGEHCACBCBABGEDEDGFAFCCBEDCGGFGBHAHDBBHBHECACEDBDHAAFAEBEDCDCHGBEDECHAFAFECECEFHGHGHBEBGBGBFFFFHFEFHFHEBEGEAEFFAFGBBBFHCHADFDFBABCGAEAGFHDADEBHBE,False +843,20.0,14.0,16.0,25.0,17.0,16.0,12.0,24.0,HBHEDGBFBCADADACHHDHDAEAHDDDDDHFFDHDGCGCBHEGABAHEDEABACDCEFGFHAGGBACGHAFFGDCAAGHDEGEGEDABACABHFDEEBEBDBDBDHDADAHCHBEFEDEDCFCFCHCHFHFHFHFCAEHHFCE,False +844,6.0,6.0,6.0,6.0,7.0,4.0,7.0,2.0,GCECFBDBDBEGHDEAEAFFECECACBGBDADGDGHFABGEGCA,False +845,14.0,10.0,13.0,17.0,13.0,16.0,16.0,22.0,DADFGHGHFHCBGAFEFCFCGDGDEDBABABECDCDBBGAFAGAHDDDDFDGDGDCEGGFHFHCHGAGDHHHFFCGCHHEFEAHHHFHGEGDAHECDCHHAHAEAEBCFHFBFCEHBBEEA,False +846,13.0,21.0,15.0,9.0,8.0,13.0,6.0,10.0,AGBCBCBDGCBFGHABCBCBEBABCGHEHBAFAFDFECDBBAAHBHBHCFCFDBABDCDFFCGHAHBHBEBEBCFCACDEHACEBFDFGFAFAED,False +847,8.0,14.0,10.0,15.0,9.0,10.0,9.0,7.0,DECFAHHBGBCEAACBCBADDEBHDHDEDFFFGEAEBGCGBGDGDFDADBDBDCFCGCBCHABFBDEDGDGBHBFFCFEAEH,False +848,10.0,5.0,6.0,10.0,12.0,17.0,10.0,11.0,DHDEDCDFDFAFAHCFGABAGFCFBGGGGAHCFDFAFEEEEBBABHFAFGFEEHDHECEHFHFEAHAHEDFDFHFDGGGEC,False +849,22.0,14.0,13.0,19.0,14.0,18.0,13.0,19.0,AACFCFBBHBGFDADADAHHCGFBCHHFHBHDGDCAHAHABDEDBDAHAGFGEBEBACHCDEGAFFDGBHFCFDDBABAEEDEGEFEAAGAGABADAHFGFCFAAGCFHEHFGFBFEEDEHEDCDCDCDHHH,False +850,12.0,11.0,24.0,25.0,18.0,37.0,27.0,36.0,GEGEAEAEDHDEDECECGGGEFEFEGCBFBFCFCDCHEHDDGEGFGDHFGEGAGCGFDHCHFHDGCCHEBBDACHCFCHGHCHCHGDFFFFDFHGHDFFFGFGHHHGCDFBFCHHFHDDBACHEEFDCAHDHBHFFFHHCHBHFHDGFGFGBEAHFHFHFCAGGDCBGDGDFFAACDCAFDFDFBHHAHE,False +851,8.0,20.0,9.0,10.0,16.0,10.0,11.0,18.0,GAGAGFFHFHCHGHEFEGADABHBHBFEEEBAHCHCEEHEDCAGGBBDBFGFHFHAHFHBABEHEBFBCHEBBBDDDCDBECEGDBCBEBEBHBGCHEDDHG,False +852,8.0,4.0,3.0,3.0,5.0,4.0,5.0,3.0,CEHEHBGFGBABDCGAGHFDCGAAAAEADAFEFEB,False +853,2.0,2.0,4.0,5.0,2.0,8.0,1.0,9.0,BHFHFHFADCCGFDFDBDEFAHHHHHFHECCFD,True +854,0.0,3.0,1.0,7.0,1.0,4.0,3.0,3.0,BGEDFDHDHGFBDBCGHDFDFD,True +855,13.0,9.0,23.0,8.0,13.0,14.0,12.0,14.0,CFCFCGHEACCCEEEGDHHAHBGBCFCDCDCFFGCAFDCABHCHCDFFCECGCGCAABFDEDACCHHAFAEBEBHGHBHFGEGCGCGAEBCBAGEFEFEFDHAHAH,False +856,10.0,14.0,21.0,25.0,13.0,22.0,18.0,15.0,HDAFAFDFBGDDCEEGEDFGBDBGCCCCDDDGDGHFDGHEFECHCHCFEDBDBACGFBFBFDCGEGCABABDEGCGCECEBAFGHHBDDDHHHGGDCDCACAFBEBECFCFAEHHFFFDGDGHGHDDFDFHFCFCBAF,False +857,5.0,7.0,6.0,6.0,3.0,6.0,3.0,6.0,HBHCDAHAFGBACABHBDBDEFGCHCHCBEFEFGFCFDDBDA,False +858,5.0,6.0,10.0,9.0,8.0,7.0,3.0,10.0,BGCHCHCBDDHDGDGABCBABFECECECDCDFHHCEDDFFFHHEHEAEAFHBEDHCAF,False +859,5.0,3.0,3.0,10.0,1.0,2.0,6.0,6.0,DADADBGHEADDDCDGHGHGCDCDBFAHHFHAGDGB,True +860,23.0,20.0,27.0,31.0,27.0,21.0,22.0,20.0,GBHCDCFCFDEDHCHGEFEFECCCCCADABAHFHFHFDGDAEEHACDDGBADFDEECFAFCFEGCGEEHFAFEFBABCDADEDEHBHGHBBAECECGBHAGFHHBGECCDEDBFHCACGCDAGAGADDDDDCDGFCFCEEEDEBHGHGHGCGCBDADHBGDDEDABABAEDEBFCDEBABGBDAFAFGEGH,False +861,7.0,7.0,14.0,4.0,11.0,5.0,11.0,5.0,GCGFGBGCCCGFAAEAECECECGBABHHCAEAHAEFEBEHDCDCGFGFBCGCGCDBEEHDGECB,True +862,12.0,3.0,10.0,5.0,8.0,8.0,5.0,6.0,GFCAHAHAGACCEHDBBAAAHADECEDECGCBCECFCFHFHAGGEDEFFCFAEAFAD,False +863,24.0,14.0,29.0,24.0,18.0,18.0,12.0,25.0,ACACHBEBEDABHBGCDCFCEDFCGCACGFADCCCCBCDEAEBDHEEGAGCDFDFDFGEHAHFEEAEHCCFHFEFCHCHDAAHGDCDAHFHEHDHDHAHADEBEBEGADAHEBFHFHACGFGCGCBCDCDCACFCFABCBADDBCBHHDHGAAHAHFFDHDEDA,False +864,12.0,14.0,8.0,8.0,15.0,8.0,10.0,15.0,EBEBGHCABAFAFDFDADGBHCEBGBGBCFCAEEDHCHGHBHDGDHEHEHEHCFGFBEEHAAAHGHGEGBFCABHFHEEBADCDABEBEA,False +865,3.0,2.0,2.0,3.0,0.0,3.0,0.0,4.0,BHDHBCFDFCAHAHAFD,True +866,5.0,8.0,8.0,6.0,13.0,7.0,15.0,8.0,FHCDEDADBEBGAGCCCEBGGFGEGEGAGAGHDHGBEHEDGAGEBECHCGFEEHEHGGFBFBFCFHEBCD,False +867,15.0,8.0,10.0,4.0,10.0,7.0,12.0,11.0,GCHHEHGBDBCGCBCFEAAHAHADFCFCFGAGAFBGAHAEGFBECEABHCHAEAEHGHGFBDCHGEGEGDACABAEA,False +868,13.0,19.0,24.0,20.0,14.0,16.0,12.0,20.0,HCHAHAGDDCDBGGHGHGCEEAEGFBFDEAEFCFHDHGFAFGEHDBDBDCECDFECHCDCFCHCHBBBBGAFDCACEDBFFAFAFBEHCACDHBCBCBHBCADDDBDHDHCHCBABHHEFGAECGCGCBDBDCFHFEE,False +869,11.0,10.0,12.0,15.0,14.0,12.0,10.0,5.0,CBGECDGDGDADCGAHDBDFFFFEAHFEFDBDGDGECECDDFDADBEACGFEBEBECCCGCBCBEAEAFGBAAAEDEGHHDHCFAFEFB,False +870,8.0,16.0,15.0,5.0,12.0,6.0,10.0,5.0,GEGAAFBCBCEGAAEBEBEFHHCBAAGACBBBBEBCGCGCECECBABCFCGCFEDEHCCDGBGFDFDEHCHBBGBDE,True +871,7.0,10.0,13.0,4.0,10.0,7.0,7.0,8.0,GAAHGCBADEDHDCCCACAFHEBBBBBCBEGEGFCHCBEGEGEHDHCFFABCFCFHGHABFECECE,False +872,5.0,6.0,11.0,4.0,5.0,6.0,7.0,6.0,FCCCACBDAFCCCFGBBHBGAGEGDGCGHGHDHDEBHCCFCBAEFEFEHA,False +873,6.0,3.0,2.0,8.0,3.0,5.0,4.0,1.0,AADDDCDCGGFFEBADADADEDGBGFFEFAHB,True +874,16.0,16.0,9.0,13.0,16.0,16.0,11.0,18.0,DGAGHBHCEFGDAAEAFAFBBDFHEDEDHBHGHGHDDEDFCFCAAADAHFBCBCGEHEBFDFAFCFAFAFBECCBEDHHEHEGBGCDFGFHHHBHBEBEBHAEADBEBAAGEGHF,False +875,10.0,10.0,11.0,9.0,10.0,8.0,13.0,16.0,AFADADEDEFHCHCFGBGEHDFGHCHEGBGHFABHEACHBHBHBHGDGBAAAHAHCHCGGGCGEDEBCDDGBGAECEFFFBCHCHDE,False +876,10.0,18.0,8.0,11.0,7.0,15.0,11.0,9.0,FCHDHBFBGCDHAGCCHDHAGFFHBHEFAFAFDBBBDBDEACGGGBGFECECACHDBABFBDBDGEADADFFFGEGEBBBFBFBGBFAH,False +877,4.0,5.0,14.0,13.0,6.0,8.0,11.0,11.0,ACACGHADGCECGGGDCCCFCFBFDFDHDHDADHDHFFBHGHCHCGCDCDHDEEBGFDEHBHGEEBDFCCGG,True +878,22.0,17.0,15.0,16.0,16.0,19.0,13.0,15.0,CCFCHHDBEGEGDCFHFBAGFEDDFDCECEGBCBABADADBGGDBACAFAEABHHHFHCHDBFBDBDBEHHCHCHEEGFGFHAEAEAEADFEAABCFCEAHFGAAADFDFBFBEGCGCDAFAFAEDGBHBGFA,False +879,11.0,12.0,5.0,10.0,10.0,9.0,11.0,9.0,BCBCEAFGFGHBHBHDDFEFGBGHGFBDCAAGEHDBDGHGHFADAEEFEDEDEAHABABACAGHEDFAGEDBGBCBF,False +880,22.0,23.0,20.0,22.0,17.0,22.0,27.0,22.0,AFEFEHDHDHDBFBGBGEGBGFGFGEHEABABGGGABAHDHEBCGCGCFCDBDFEEAAAFDCBFHGHBCGAEDFDFDBCECFBAGAGAFEHGGCGDBBCCGBDDCDBDCFCAHDBAFFHCHDHFHCEEDHDHBHCCBFBAEAEAFGDCDHAHFHEHADAGAGAFBGCGHGFBEGG,False +881,26.0,17.0,21.0,13.0,20.0,12.0,23.0,19.0,BAEAGCGHGAEADABEEEGAAHHDDBDFGAGACCHHEHEBFBHEEEDFGFEAGHCCACGEFEDCGCHCGFHHBHBGBCCCDCGBGBABABFDDHEAEFEGGGGEHAHACACDGBGBGBEAFACEHFAAAHGHGDCCECFCBCBHDAAAFAD,False +882,1.0,1.0,3.0,2.0,1.0,1.0,0.0,5.0,DHHFADEBCHCHCH,True +883,7.0,3.0,8.0,7.0,4.0,4.0,4.0,4.0,GDEDCFHFHDHDEGEACDCABBGFACACGCFCDADBCAEAH,False +884,21.0,12.0,14.0,11.0,9.0,9.0,15.0,13.0,EHEAEGDDAGGBGFFAGHDHDCDCDCFCGGGGGAAEGCHEDEAEFHFAFGCBHBCCCCADBBAGAGHBCACAHAHBFEDBGBCBEDDHHABAFAHAHFBCAAAA,False +885,16.0,26.0,24.0,20.0,25.0,24.0,19.0,20.0,DFDGGAEAEAEDHGHGCCABBEECFCFGBGBDCGFFDBDECEADADHGHFDBDCEEBCGCGAFBFBCHDFDFEFEFHFHFHBHFEFHCHCBAFDFBFCAGAECBBBBEAEBGCECFHEHDCCEGBGBGFGFHHEHCHBDACECABABDBHAEDDCGGBBEFDFDCBAEHEHECG,False +886,13.0,28.0,17.0,8.0,23.0,25.0,17.0,16.0,GFFBFBHCFBBBCGCGEEBCBABFDEBGBGCACEHFHFHBADDCGEGEBHAAACFCEHBHBDAEFFFFDFDFEFEFECEBBBHFGBBHBEGCBEAEDCHEEEFBGHGECEHFHBABFCFCFCGCEAGDGAGAFBGGAFHHHBEBEBF,False +887,12.0,16.0,10.0,18.0,15.0,11.0,14.0,8.0,EEHEFGDCAFDGDCBFBFGFBEAFBBBAGFGBGCHCHCAGADCFCDBDEHEAEDGDBHBFGEBEBDBDADCDHDEABDDEDFCAGDGAGAFDEAGCGBEBEHEH,False +888,18.0,13.0,17.0,15.0,11.0,10.0,18.0,15.0,DEGEDEFAHAHAHGHGHGCGCFDDDADFCBGDGDCBABCBEACAGAGCEDBABDHFGAGAGDEEHAFCDCBCACBEBHCGBFAHAHCDFHBGBGHFHGHFBACEGEGCHAECFCDAD,False +889,22.0,5.0,11.0,9.0,14.0,19.0,10.0,13.0,HEHFADEFGFCEHEFDFHFAFGGGGAGAFADGDFAEAHBCECEDFCFHFCFDFDAACACABBFGCHEAAABCDHEAEABFHFHEGEFHAAAAACAGDHCHEFE,False +890,27.0,36.0,17.0,27.0,26.0,14.0,25.0,25.0,FHDGFABEECADAEBECEABAGHECDCDADGDADADEHEHGHBFBCBGDEEEEEBABABHBHAGCEDEDEHAHAGGCDCDHBABHBCACAGFCFGHHFDFDGBGHGAGCGFFBHADFCECEHBDBGBABACAHEBBHGHEHBBEDEFEBGBDBCGEDBBBBBEBDHDBAHGFGAEBHAADGHGDABFCFDAGBGDHD,False +891,18.0,15.0,22.0,14.0,25.0,27.0,18.0,19.0,FHFHEHAHCFEDCDHFFFHCCCCCCFAFGEAHAFGGEGEGEGFGFAEHDCDFHGAGEBHFHCHBHBEDHDCFCACGBFCDDEHBCEGAFABEBFDEGAFDCACFEFEDEAAGAGAGCBCDFEHAHEHBCBCBFBEEFEHGGGCEFEFEBEAFFBDADB,False +892,15.0,15.0,17.0,14.0,25.0,21.0,15.0,21.0,EGAHHHDHDFEAEDEGGGGAGFHFAFEEEHHBCBGHGBGDFAAEAECEFEDDBFCFCAGFFHFHFHBCFCDHFHCHADBHFGFGBEBHHEEDDCDGBCEEEBGBHEHEDEAFCBCECEBGAAAEDCDCACABEHHCFEFCFBF,False +893,5.0,2.0,1.0,1.0,3.0,2.0,5.0,2.0,BHAHAEEEGFGFACGBDAGAG,True +894,1.0,2.0,2.0,3.0,4.0,6.0,4.0,3.0,FCFCHHEFEFGGGGHDBEBFAFDDE,True +895,12.0,25.0,10.0,17.0,18.0,19.0,18.0,17.0,CECBHFGFGEBBHFEFDBDBABDGAGAEABCBGAGAHCEEHEHEHDDCDBFHFHEDFCFBFBFAGGGGGFGEHBBBHDHBHDEBEFGDCBBBDBGCAHHEGBGBCDFDEEEDEACAFFGBBHFHFDFAFHGBADED,False +896,16.0,8.0,11.0,13.0,10.0,11.0,7.0,7.0,GEDEHEHBBDADFDADCDCAAAHFHFGFECACAEDCDGAEAEBBCBGEACAHDBDEGFHFBCDCFAADACBCHFAFAFEGGDF,False +897,11.0,6.0,9.0,7.0,10.0,14.0,15.0,10.0,HDBFBGCFCGCGBGDEDGHAHGHAAFHFCGBGCAHHGFCFAFEBGHGBDCHCHDEEFEFEAEAEFEFGDGFAFACGEFDAGA,False +898,17.0,13.0,21.0,30.0,28.0,20.0,12.0,19.0,EDDBGCECEDBCBCDHGFECBGBEHHHEHFHDGDHHAFAHCHDBEFDADCDHEEEHEGDGDGFEDCACEDEAEAEFDFDFDADCCACFEFCFEFCBBHCCFEEDHDFGEGAFCFCACABABCGDEDAHEDDDDGDGFHDHDABFCFDFAHEEBEBEHEAA,False +899,3.0,3.0,2.0,3.0,3.0,3.0,8.0,3.0,BCEFGHGHGAGBGBGDFDCHEGEFAADG,False +900,16.0,24.0,17.0,15.0,11.0,13.0,13.0,18.0,DDCDADAECDHHHCHADDHCHCBCADAECGHGEAHFHGBBHDADAEHHFHGACACFCFBEBEDCGCGBBBBGEFFHFBBGCGBABABAHFEFBBECCHGFDFBFAFAHBBEBEACDGDGCBHBGBDB,False +901,25.0,30.0,29.0,16.0,34.0,19.0,24.0,19.0,FFGCECEBBBCDCBFEEEECGCABAFEFGHBDAACECGHDFCHBFBGGGBGHCHCBCECBGBEFDHBHBHCHAHAGABABGEGFCFBEGEBBCBCDHHHCHCHDBDCFCAEDHGAGEBEGEBEDEFFDBDEFBCEFEAGGFGEGFBFHHACACAEAEAEBEHEBAGAEAECGABADDDAECECFAAEDDAGCECBG,False +902,24.0,23.0,19.0,24.0,26.0,27.0,19.0,14.0,FAAAEACAEEEGEDAHEBADAGGHEDCABGFFDFDFEBEBEDEDGAHFDGBCBFDFGECFBFGFBFEFCFEDADBEFEFACACACAHADBBBEHAHBGBFAGBEEGGFGCGCFAFDFEBHGCAAGDGFHFCFCHCDCBFBGBCBEHFHCHCBEDGDACAEBDBHFHEDDDDDEAED,False +903,29.0,29.0,25.0,18.0,19.0,26.0,26.0,24.0,GABBEDADAGFHBHFHGCBCBDADGBGDGHEDBGBGDAEBEAGFGACEBEDADFFFBBBCFCGAFAHEHEHGBAAAAAAGGCCHBGBABHEEFHFHAHFBGCHDHFEBEGEAEDFGCHBHACADBHGDGCEDFFHFEFBCBABAHAEAGGFFCFAHADGDGCBCBCGCGCBCBCFHEHDFFEFHFCFABCHCDCAC,False +904,6.0,3.0,10.0,6.0,5.0,4.0,4.0,1.0,ACGCFCACDCHCDDDEDCGGEFBCBCBFGFEEAEDCAAA,True +905,3.0,18.0,9.0,11.0,14.0,16.0,4.0,13.0,DCFBBCBEBDBFFEFDCGHBHGDCFBFDEHEFBHBFEFHFHFGCAEHFAFBEHEHEHCACHGFDCBEFEHEBDBDBHBDEDEDBCBFB,True +906,16.0,25.0,37.0,22.0,24.0,10.0,28.0,28.0,DFDCDCEAEHCHEACBHBGBHCCGCECADDDDDDCHHHAHCCCGDECECEBECHCFCFBHBACGCBABCBHGEBBBHGHGBCBCDEEAAGAGDHFCCEDEDGDGDGBGHHDFFGEEBFAGHGFCBBGEHHBCBDBABCEAGACACGBEHEHCFDHAHEGGGHGHGACEDECHCGCGCDHFHBEGEDBCGC,False +907,25.0,18.0,28.0,21.0,19.0,32.0,30.0,20.0,GCGCEBHGCGCEDDHHGCCCCGHGHDHEHACGGGBGFGBEACGHGCFDFDCCCHCFDFAFAEAGABACAGACEBHBFGFBFBDHCFAFGFACAGDEHCDBGHAHBBDFDFCFAEBDCGFAHGHGFGFGBADFEFHBDADABBEAFHDDFDFGBGDEDEFAFEFEFGFAFDFEFCACHFHBEEECGCGCAAEAC,False +908,28.0,27.0,16.0,15.0,23.0,29.0,25.0,24.0,FAFEFGFBABHFFBHDCCGAABEBCACAEFFCFAGAEEGEGFGFDFHFHBAGFGBGDHBHBHBCGEGFAAHAHAHAEGEBEAHABCBDFGFGEGBFBHBDBFBFGFGHGHBEBEBDGHGFAFCHADEEECECFBACCBCDDHGGEHEGCAAFAFBDHHHDHDFDADGFAAEAFABEECGHHDBEACB,False +909,22.0,23.0,20.0,21.0,31.0,23.0,29.0,28.0,EAGGGDCHHHHCDDEDBCHAEDGBGAGADBHAFFHGBGBDEGEGHGAGDBEGAGCCHFHFGEGHHEAEBDDDDADHCBBBCACFCGAGECEAEFEGEDDAAEFEHBHBGBFCFCHGBBDBFBFDEAEAEFCDDEGFGFCECAGHGFGFEHHDAFHFHGHGHFHFEEEHAFBBBEAECGCBCBCEEAHACBFDFEHEH,False +910,35.0,20.0,17.0,22.0,15.0,17.0,23.0,20.0,BABABADGDFFFFFADHEEAEHCBGBGDGEGCACHEFAAHAHAHBHGHBABCBCGCFDFAFCFCEAEHEDGFGBAAADBGADADBDBECGGFCBDBHCAADAHAGADCGFGFGCGCEDAAEAHDEDBAGFGBADDDCDHHHCHAHDEAHGFAEAFBDHAGAEHBBGCGA,False +911,20.0,22.0,16.0,16.0,19.0,34.0,24.0,21.0,HHBBFFAHAHEFAFCDBDBDGCEEBFBDCCBCHDFAFDBDBFCFAHGEDBGFFFDFHACEDGDBFBFCECHCHBFAFADAFFFFFFFGFBHGHGHGHAFABACHCFGGGAFHFHGGGGFAFEEGHGEEEGECDGECBCBHDGDGHEHDBAGEBEAEABABFEGACHEBGFAF,False +912,14.0,22.0,22.0,16.0,10.0,16.0,13.0,11.0,GABHDHAHACDCBFFFECHFHEBEGABCEHEBBFBACHCHCACABEFFDBACDHFADAFBFBGGCGCGCHFBFCGDFAFGBCBCBDHDGDCBCBCGDGCGAGABCBCACEDFDEEFBBDDDEDB,False +913,20.0,27.0,29.0,23.0,22.0,31.0,29.0,18.0,GFGEECFDFAGEFHFACDEGCGCGHGHDHDCGCFDBAGAGAGDGHFDFBFGFGAGHDAGAFABDCFFECECEFFDCDCBCGDBABFFHFDDDGACHHDBEBEBFCEEBEHAHECBABGGAGDHDCEEGFCFBDECACAFHFAFACBEAGGGBGBCBHFCFCFCFCHDFAEBBBHBEBECFCHEEGBGBFCDBDBDBHGC,False +914,12.0,9.0,6.0,2.0,6.0,6.0,2.0,13.0,BFBHEHEHBADCHBAGFHFEBHAAACABHBHAAACECBBACGCHFHAHAHEHEFFD,True +915,10.0,12.0,24.0,13.0,16.0,14.0,13.0,16.0,CEBDBDBDCDCDCDBDAHHBFBFCFGFGEDFHCBCFGECFCEBEBHBCCFCFDFEHAFBHAHAHFCACHCECEHACBCHCFEDEAGACDCHCGAHCDEGGHEEFHAGGGECEGEHDGG,False +916,4.0,4.0,9.0,4.0,6.0,12.0,3.0,4.0,CECDADFBACFCFDFBFGFCFGHCCGBEHEHEHEFFCACBEFFFAD,True +917,15.0,18.0,12.0,11.0,16.0,11.0,18.0,15.0,AEAEAEAEAHAHAGEEFHGHBHBEDABABADHGFGDHBCDDFHGBEFFFAFGGHBDFCBEHECECGFHBHEEGDBEGEBBGDCDHDCACGFGHGCABABHFACCCCBGBGBGDGBE,False +918,14.0,16.0,12.0,30.0,16.0,18.0,12.0,16.0,DHDAEBFADADADADADGDFAFHFHDEFGBGBGBGFHCGEHECEAACACGCDDDFEBEBHBFAFHCDDDDFCFDFGHCFDHEFEFDCHBBBHAEDEDBAAHCEFDCDBDFDBEEDBDHEBDHDGFHDHEGGGCB,False +919,5.0,11.0,3.0,9.0,10.0,8.0,8.0,5.0,BFBHEEEBCBHEHGAGAGDDBDEEEHABFCFBAGDCDGDBDGAFEFEFDBDGGFBFBHE,False +920,5.0,0.0,5.0,4.0,1.0,1.0,4.0,2.0,CGAAFADHDCACGCECGDGDHA,True +921,24.0,17.0,18.0,26.0,23.0,31.0,24.0,25.0,EDEDCDADFGBABAGGFCFDFEGCGBHHECEADGDEDFDFDBEGEFCAGFEFEFDHEADHCHAHFHFHEGEDDDDBGEGEFBCDCEAAHDBAGHDHFGGHEHAHAHAHFHFDFBGBHCGAGFEFEFADACAFEBGCCDBEBADAFBGCFAFCHCHAFEFGCGBGCAFABCDAFBFBHDHFHEGDGHFH,False +922,12.0,3.0,17.0,8.0,6.0,8.0,19.0,16.0,GDFCHCHAADGBHCHAFEHCHCBGBCHFACAFADGGGGGGCGCAADHEHECEAEDDCCEGFGFGAGAHHGHGCDADCCHHGCGFHFHGC,True +923,13.0,7.0,15.0,17.0,15.0,11.0,14.0,5.0,GDDDHCCBCDADAEABADADGHFDCCACAEAGGDEEEDFHFBDGCHBFBFDGGBCDDDFCFCFEEGCFEFADADACAGGGGEGCCAEBEHEGEFECE,False +924,19.0,22.0,14.0,20.0,28.0,12.0,19.0,18.0,CGCDHBFBHGEBEADBDGDGDCBCDCHCEBHGEGEHEGDFFCEAEDGCGEGFDEEEEEBABCBCBCBCBGFDFAEAFDHDHEHFDAAHHHHEAEADAFEFEDBABDHEFEAGCBBFHDHBHBGBADHEEDBDEGBAEAGGCGHBEGGAAAEA,False +925,20.0,23.0,18.0,19.0,19.0,27.0,21.0,22.0,FEHEHEGDGCBDBHBEBCAGACHFEFHAHADAFGBGFFEGECEHDGDAHAHEDCCEAGFDFEGCCBGBFBFHDADCBCBFBCCHBHAHBDCECDFHFGFADCFFFFBFADBGGHADFDBBCBGHHHEHEHBAEAEFGBHBHGAGEFEFGFGFDCDFBFACAGAEADGDB,False +926,8.0,4.0,5.0,5.0,6.0,5.0,4.0,8.0,FGFDECECEADFBFBHEHAHADAHAEACGDADHHHBHFACBEGCG,False +927,4.0,9.0,2.0,4.0,9.0,4.0,11.0,2.0,GHGBGDGBGBEAGFGBBBBDDEBGFGEGEDECEAEAGBFCEHFAE,True +928,19.0,13.0,20.0,26.0,25.0,21.0,11.0,20.0,DDDFAGCFCHADFCCECECFBEHDBEBEDEHEHCFAEAEAEFDFBFADAEAEAEADHDFDFGBGBADEDBHCGCFCBEEAEHECFHAGACCCDDEDHHHHAHDDDACGHBACFCFGDEFEBHFHFCDDDHDACECBDHGHEEFGBGFGFEDHFBA,False +929,31.0,26.0,25.0,22.0,30.0,19.0,16.0,16.0,GADBEEEAEAHACCCCFGFEHBGBGCFCFDDADGBAAAFEFAABEHADFDFACAHBHGEFBAAACFCGABEGFABGFGEGFBFBEBFDEDEHGFEECHAHADADADCHEHEBEDABHBEACADBDBDGDGDCDCACHEHGCEHDCEABCFAEDFDGCEBFBAAEHEDEBCBCBCBCBEEAEBCHC,False +930,5.0,6.0,16.0,9.0,2.0,8.0,6.0,8.0,FCFCBBGDGDBABHCHCGEBEDDGACFCFCFCHCGCABHCCCCHFHCAGFHHCAFDDDDD,True +931,13.0,10.0,13.0,5.0,17.0,8.0,8.0,11.0,AEAEAHAEECBHBHGHAEBFCEEAEBEGCHBFBGEGFACADAEGEDBFCCHHBHBHFHCGEGHDDCDCACAEAFBCGCFEFECEA,False +932,13.0,15.0,7.0,16.0,20.0,10.0,5.0,18.0,AEABBCHEBEHEFEDEAFBHBADFHHDBDEHBABABABACDCFEFHFEGGACEDEHEBBAFGHCEDEDBGCHHDBDBEHCHDADGDEDEDHFEEEAHAHFHFHD,False +933,4.0,6.0,3.0,4.0,2.0,6.0,4.0,5.0,AGAGAHBEEDCGBGBCBDFDFDHHAFBFHFCBHF,False +934,5.0,12.0,3.0,2.0,5.0,4.0,9.0,11.0,CEDBABACFFGFAEAGCGBGHGHBHGHEBBHBHGDFHHHHBEBEAGBBBGH,True +935,8.0,6.0,1.0,11.0,7.0,1.0,14.0,7.0,GEBHGHGDBAEEDAGGEGDGBGBHHHHDDAAAAGDGDGDADABCEGEHEDDFGGB,True +936,12.0,13.0,17.0,16.0,15.0,22.0,16.0,19.0,HHEDDDDGDGAFACACHCFEEECACADBGHGFFFFFFEHEHCAGBDFEFDFEFEHEFFBBABFCHEGFGDHBCBCBEEAHCCECDDBFBHCHFHFHDEDGGGDGBGHCBGAFDGDGCAHBCCHGHFHFAA,False +937,3.0,4.0,1.0,4.0,2.0,0.0,0.0,2.0,ADDEDEHBHBACADBB,True +938,5.0,10.0,7.0,7.0,2.0,7.0,13.0,13.0,FCGGGHHAFEFBFBGBABAEGGGGCFCFHBABHHDHDHFHACDBBGHGDGDHCBDHCHGBGDHC,True +939,0.0,2.0,2.0,0.0,2.0,1.0,2.0,1.0,CGEGEBFBHC,True +940,15.0,12.0,17.0,12.0,18.0,16.0,21.0,10.0,DADACBCEGEGCCAHFCDCDAEACDCFGDAEBEBEACABEGGGABACDFDCGGFDDHCGFGEGBCBDEDGHGFEFBFGGCBCEEFAFGFHFAFHGHGCEFEBHBHGEGEGEFAFAHACBHE,False +941,21.0,9.0,18.0,19.0,23.0,21.0,20.0,26.0,EGEDHBHBHGHGHCEAAGBHBDDDGGGDGFGFEFGFGADHEFEAEAFAHAEAHBFECDCAAGDFAFHEHCCDCEFHFHFAEAHACFCFCHCECEHDDGDHDHDADEBHFEGAAEAFBHCCEGGDEDBCHADAHFBFCFCGGEDECFHGAGHECEHFH,False +942,23.0,23.0,25.0,23.0,16.0,18.0,18.0,24.0,CAHDBDHDEGCADHGHGHGHFCDCHCDFGEDEDHDHBHFDFEEADAEABFFGFGACFBBCFCBBFAHCHCEEDCCFHACACABHBFFFDFECACHHEGDGDEDBHBCBHBHADABHBHBCGHACBCBEBABCGEEFEAEAGGCDDDDAGAGAHBHDGBCFGFDCAGACAB,False +943,9.0,5.0,6.0,3.0,2.0,3.0,4.0,6.0,DBDHCFFHCEAEGBGBGAHCHBBAGFCAHAHACADACA,True +944,1.0,5.0,5.0,2.0,2.0,3.0,5.0,5.0,EGGDGHCBBAEGHGCFCFBHBHBHCFCD,True +945,23.0,12.0,17.0,23.0,21.0,25.0,31.0,23.0,AHAHBHBHCHCEDDFCACDCDFGFBHBCCGFGHGAAHDEEGECFAHAHFHDHEADFGCGCGFGEADBEAEBEDDBCBHAAFAFAFDGDHABAEHDHGEEEHDADGFGHGFEFGFCFAFHFEFADGGEGEGECFDHCHDFGHGDGCAAGAGEGFDBGCEBGBGDEDHFFCFGAGDG,False +946,7.0,6.0,9.0,5.0,3.0,13.0,9.0,7.0,BEBECFHFHAHGCAABCCFGBGFFCFGFBFDFGGAGHGFFFFDBCGHHCHCDDADAEAC,False +947,12.0,14.0,22.0,9.0,8.0,15.0,19.0,16.0,GGGGGADFDBBBCHGACAHBFGHGHGFGCCFDACHGHEFFBCBGEGDGFHHHBHDGDCCCCGBFHACACECDCFGBHBHBCEFECHCBCBCHGFGDAAAADAEEFCFCACFFEHB,False +948,23.0,29.0,24.0,18.0,9.0,25.0,25.0,32.0,BBBHGFAEAEBEBCFCFAFAFCFDFBHBGCHFAEGDACAGBHCHFDBCBGGCCBBHHABDCFGHBDCDBDGFBCAFAHHGHFHEHACEGDABGBGHABABGHHHFBFCFHFABAEAGACBCFHHBABCBCBCACFCHGHCHBGBHDDFGAAFFFEDDDGDHDHGHGHGHDHGHGHDCDCGFGFEA,False +949,7.0,6.0,5.0,7.0,7.0,6.0,6.0,12.0,HHCHADDCGBGFFHDHBBCHCHBFADAEAGAFAEAHBHEEEEHHHBGDGEGCDFDF,False +950,24.0,23.0,22.0,11.0,20.0,30.0,30.0,14.0,EHFBFBFBCCFCAAACEGBFAEEBHCHFHEAEAGBGHGHGCGCFEFAFBEAGAEBGDGCGHGHBBGBGBFBFDFECAGGFEBEGCAEBEDGHAFBHBFBDGDGFGDACCGCECACAGFCECHDFBCGCGFFFGFGCBCGABADFBHGGFGDHDEFBHCAAAAAAFFFFFDEEAE,False +951,16.0,19.0,15.0,15.0,20.0,28.0,15.0,17.0,DGGFECEHGHFHCBCEHGDGCBCGCEEFAFAFAHEHFAABHEGDGAGBGEEBHDHBBCBCHFBDBDBHEDFCAEAFFFDFDFAGBCBDECFFFEFDFBFGFGEECECEFEFEDHGCDAHAEABBDGFBFHHBHDAFHFCFAFABA,False +952,9.0,0.0,6.0,3.0,8.0,5.0,2.0,3.0,EFACCCFAAAAHFFFDGAAEAEHGHECECEDECEAD,True +953,2.0,1.0,1.0,1.0,6.0,2.0,3.0,1.0,ECEHDAAGBGEEEEFGF,True +954,11.0,9.0,7.0,13.0,13.0,4.0,8.0,8.0,CADHDHDFDABBEACAFDBBHFHGAGECBGEGEGEBEHEDEAHBGDADADADFDEBEDDCAABHEHCGEGECC,False +955,17.0,19.0,17.0,18.0,12.0,19.0,16.0,32.0,GFGFAAGFGAHADGGHGEBABFEDBHBDFHHHHBGBHDHDEAACBFBFBEAEHCDDGDFHHEDGHGBGBGADHFHDHCCGAEACDCDCAHAHFHFHFHDBDADHCCCHBACACBHFHFEFECACGEBBFDHCHDHBHEFGCECHFFBHBH,False +956,21.0,23.0,17.0,24.0,20.0,16.0,15.0,22.0,DADEHFHDCBCBCAHGBGFDFDGBAFDFDHHFDBDBACACFEHEAEAHAEEBAGCHCFCFAHAGDGDADADHHGHGECCFCFGFCHAHGDGBCCHADBDEAHGCFBHBHBHEEEEEHEBEAEGDBBFBHHCDCEBBBDBDBAADGFABADFEEGEDDB,False +957,10.0,10.0,8.0,10.0,12.0,10.0,10.0,2.0,FGFBFDFCGGFGABBBDGAAAFHFDGDBDGDEDECECECECGBAEHECGDACEBGBDFCAEAFFEDEBABAE,False +958,23.0,37.0,29.0,27.0,20.0,20.0,23.0,19.0,ADBDBAFABHBADGGCCCHFHGBBDDCACACBBAGDHDHCHFECBHFEGEBEDCCFEDEFBFBCBCBHEHBGDCDGBGAGAFFGCGEGAADACADBGFEDGBGFDBHBCAHEEFFDCDADBDBACDCDCDBHBHFEFHFDBGBGEFHFHBACECEDEBCBCBCGCGBBACAGEFBFBABGDGDHEHEGBCDCBHEAAA,False +959,12.0,18.0,18.0,8.0,12.0,10.0,17.0,15.0,BEBEBGBGBHBCBCECGCGCDCFGGHGBCHEACCCEFGAAAEHBHEHBGBHAEABHGFCFCDCEABACAHEHCGCHFEAEGDBDHDCGFDCDAHBHGFDFGGGHFBBBAF,False +960,6.0,8.0,14.0,11.0,10.0,8.0,6.0,15.0,EADADHGFDEEHFHDHBHBHCECDFDBDECHFFAFGFBEDECBCECHHHHGCGDGDHCCCCCCEEDHHAHABCGFABB,False +961,20.0,29.0,25.0,20.0,25.0,26.0,26.0,18.0,BHBEFEABGFAEGDGDFFBDHDGBGBFFFHEEEEEDFAFADABGGCGCBCBAFCFABCCHEHGDDEDEGFFAAEEEEAGCGAGHGFDCCBCHGACACEDHGHGAFBFBFAHEBEBEDGBHCCEAEADDDHDCBCFHAHCHBHBFBFBGGGBHECGFGECBCBCDHDBBFDCACACBFGFGEGCDEBFBF,False +962,27.0,19.0,27.0,18.0,20.0,32.0,29.0,28.0,GEGECAFAHHHHEAEBDBDCHHGHFEFHDBFAFBFDGDBCBCGHGHFCFCFCFDEGADHHCCADADAGEHEHGACCHGHBHEHCHCHFECGCFAFBFAFGFBCAEFCDHAGFBFHGEGAAHGFGEDEACDCFHDDCDCFCHCGCEDGHBDAAFAGBFBFHEGAFACADEFEBEGGGCGCBBFBFGAGAGAFABAGFBEHF,False +963,18.0,20.0,27.0,19.0,14.0,17.0,15.0,25.0,FFACCGCGCDDHCHCDGGGEHFBCBHFCAAAAHAGFGDGAGDGHFBDEDHCBCACACGCGAFEBBCECEAEHEHBBCHHHHAACDCDBDFCFBFBHCHBHDGCEEEHEDGBBBFEFHFHDCDBDADAHFBCBABDCEAHHDACFCGHBHFHDCFE,False +964,12.0,10.0,8.0,9.0,12.0,10.0,10.0,9.0,FGFAEAEAGADFEECEHBBBAHAEBECECAGGHBAAGEHFHDHAEFDFECDCBFBFBABDDFDGGFGCCCEHAHBHGDGD,False +965,17.0,22.0,24.0,31.0,26.0,22.0,22.0,27.0,CGCEHFCFCEBDBDBEHEHGHGHFABABHEHFBEBGHDHDFCBDBEBGGCHCFDFHEHDHDGDFFBCAHAHGEEFHBHBEBADFFAFAHDHGAGAHEDDHDEBEFEBEFHFHACADDDFDEEEECCCDAGADBGAGFEHBGGHDCCCDEDGHCECDDABFBEBCGEGCGCFCDCAAEDCBGHGDFDGDCDF,False +966,27.0,18.0,26.0,14.0,26.0,27.0,37.0,24.0,AACDCHCFGHAHAGAGACFHEHABFHFAGHBCBDBFBFBABFHHHFHFCEDEFACHCECFGFEFECGDGHGCGFGEHECDCBCBGBECEDFAEECAGGFAFBHEFDGBGEGHFEEGEHCGEGDGDGDFCCCCHBAEACHGHGAGHGAGEHEGEGBCAGGGFABHDADADAGAFHBEDCFAEECFGFGFGCGABEFGABA,False +967,19.0,30.0,23.0,20.0,26.0,19.0,25.0,21.0,BBABCBGGAGFDFGHDHEGBGCGBBAFDCBCEFHDCDFBCBGEFBHBEEEEEBADAHAHBGGGEDBFBHCCCECBGHDHDFGBDCDFBEHECGBGBGFCFAHEHDGEGEFDFDECCCHCHEGEGHGBCEAGABEBABABABADADABAEADCCEFBABFECDFHFHCHFEFCGGEHEHGDADH,False +968,22.0,15.0,29.0,26.0,37.0,20.0,22.0,24.0,AEGBABEFGGEGDHDHAHEFECEFACEEACHBECFBABCDCACAHGHDEEFECECDAAAEHGHGHDHDFGFHCADFDBDEDEAEDEDEDEDGGECEABBGFADADEHGHFECBCAEAEGECECAGDBEGAACCCCCCBHEGECDCDFHFHFHFHFCGEGHBDFEBBBGECHDEFEHHGDADCGHGDDCEFHFCFC,False +969,16.0,6.0,14.0,15.0,9.0,8.0,13.0,13.0,HHHHFEFDDCAHGGEGDGDCBBHCCDADGGHAAADADFDFDGDGDGABEBAFABECDHAAFAFEFGDGCHEHCDCGCEEHHHAEACCCCBCGAA,False +970,21.0,25.0,9.0,17.0,8.0,13.0,18.0,16.0,GBGHGACACAFHFBCADGGGFGFGAGAGBBDBGCHHEHEBFDEABGDGDGBHBCDFFFFHFHAHBDACAHDHCCGAEADBHBDFABABABEBEAECGGBHBHDFBBBBAFDDAGBHHABDDADADBE,False +971,9.0,10.0,11.0,9.0,15.0,9.0,14.0,12.0,EAEDFCFBFBAGHGHGDGBHBGFHEHCFAFAGHECGCHCADAHCEGDGCGBBBBDBDEGFGCCFHEEEHEDEAEDBCGHGCADHEFEAE,False +972,18.0,16.0,12.0,13.0,15.0,19.0,12.0,21.0,BEHFBBABAHGEEAEAFAFCDEHFHAHCGCFBEAAFGCABHHFHFHCHBGADCDHDHCHCEEAGBFDFGADFFFFBFBGDGAGAEADHDHDAEEEBCBCBHBDEEHGFGFBFBDEHCHGHAHFCAD,False +973,27.0,25.0,26.0,28.0,24.0,17.0,20.0,27.0,HCHEFEACGCFDFGCBCHADFCFBADCGHBHCDDDCBAAHAEEDADGDGHGHGHGDAAEBEHAHGDADADEBEHHCEBADAHHHHCHCAAAHBFBDCGBFCHEEFBFBFHAEADDBFBFBDGDEHEHBHGCGAHACECAFBFBEEEBECEFDCCABDBDEDEGAGADEDEDCFBBACHGGFGBGCGDADCHCBC,False +974,2.0,9.0,5.0,14.0,10.0,16.0,13.0,8.0,HBEGFBDBDHEEFHFEGDBFBFBGHFAFDFGFCFDBDBDHDHBGGCFFEGEGECADGFECEHFGDCDHDEDGFGFGD,True +975,7.0,10.0,11.0,8.0,6.0,8.0,11.0,11.0,CECFCDCHGGGGHGAFCECEAECDCGHHBADHDHDBDBFBFDAHGBBBBBBGCFFFAAEHDFCHGAGHCHGE,False +976,22.0,16.0,20.0,24.0,18.0,27.0,21.0,14.0,GDBDHEGEBFHFHDDCFCDAAGEFBFEDBAHGBGBGDFEBBADGHGFABAFAFDCDCBCAHADDDCAHECCDAAFAFGHCCECFGECECEFDHCHAHGBGBGDECECECEAEAEBFBFGHGHAADDFDBDGAFCFBHACAEEFGFAFDFDFGFGDCDGGFFF,False +977,16.0,17.0,23.0,22.0,27.0,15.0,19.0,22.0,EEGGFDFHCHEEAEDEHEHGCEFGBEBEBHBDDCBAHAHDGDAEGEGDHFECBDDDHDCGCFAAAAAFCEHBBEECEFDFDBDBCCCCEFEGAFFCFCFCEBEAHAHAHAGGHGHCHCBGEDBDGEEHCDGHBCBDAHFHBHFGGDHDEDAGECECBCDCG,False +978,5.0,8.0,11.0,18.0,14.0,13.0,11.0,18.0,HFHDBAGHGEFEHCGGEGDAAFHFEFEFDHDGCECHHEHEDEDHGHDFBFCDHHHAHEHBCBCBCDCDGDECEDGDEBFGDCDEBGHFBFDCDFHFDA,False +979,22.0,10.0,19.0,14.0,19.0,26.0,19.0,18.0,HBGDGHGCGBGEFEAEFBDEHEAAHGGGGHDHDHFGEABAFAHEHCACFFDFDFAFECGCDCDCDCFCHCFCHAHFDCBGAGDEHBGEAFAHAHEFAGHEAGACEEEFFFFEFHFBFCFBACGCAFAFCBEFEGEFCGBDDDCAAAH,False +980,9.0,10.0,16.0,13.0,13.0,13.0,17.0,6.0,CDCEBDGFGFACEBDHFCEHACADBDBHBCBGACCECEFEFGFGACHCACDEEGGGEGEGDGCFFFGFDBDFGGAGAHACDDDDGEGFCFCEHBBEB,False +981,19.0,23.0,15.0,12.0,16.0,18.0,17.0,17.0,ECEDHFHFHFAGAHBHDAEFGFBEHGBGBCBHBCEDGDCBHEAGADEGHFHDBBABEBAGAGCCDADHDCGBBBEGAGAGEBBBGFGFCCBFBFEGHAEGHFCFCFCACEDHDAAAAAHDBFFHFEFCBCBEBEFHA,False +982,21.0,16.0,13.0,14.0,20.0,12.0,19.0,12.0,EBEBGBGDGEGECHCHFAAEHBCAEBHBECECACGCDCDCDBABAFABGHGHAAEAHABDEDEFHFGBCDAEAGFGECDHGFGDDDEHAGGGEGBCFDFAFBEGECEHAFDFGABADAGAEBHFAEB,False +983,22.0,16.0,20.0,28.0,16.0,18.0,28.0,14.0,CGCGBDCDCGHACGFDFDGDBDCFEFEFADAECBDDDEAEAEAHAHABGDFAAGFGFGCAAGEDEGFDFDCGBGAGBGHHHGABCBDBDFDFCFDFGCAHAGACABAFEFAGEEDEHBCCHEGBBBDBDHGEDCHCEFAHHGCDHGGFGDGDGDBEGACDCD,False +984,26.0,22.0,19.0,22.0,24.0,27.0,32.0,24.0,ADHHEFAFADABADAFABCGCGAGFGFEDADABEFHFHGHDFGEGADCCFHHHGHGEFCFCEBDGEFEFEGAFBFBFAHGBEBEAGDFAHABAEGHGCECEHBHBDCFFHBAAGAEAGBCCDCDHDHDBDBGBEDDDCBBFBGEDFDHGEGEGEAFAGGBGBHEGBGFGDECHFAFEHHFCGCGEGCCHCHAAFDG,False +985,7.0,9.0,7.0,9.0,13.0,11.0,7.0,5.0,FCBCHEDFAFHEGBGFAEAEAEAFGDGDBDBABAFGEGDCHCHEEBFCEEHEBEDEFFDFGBDBCCFD,False +986,8.0,13.0,17.0,13.0,13.0,11.0,14.0,10.0,HGEDFDFDFDHDHDHDBFEFAGAEBEDGDHHFBBEEABBBFBHGHCCBCEEGECFBACDCDAAGCFCGBGFFEAGDGHCCDGEGCGCGCHCECBCACEB,False +987,20.0,12.0,18.0,25.0,18.0,18.0,21.0,30.0,AAADFHFAADFECBCECEHEHADCDGDGDCFHFHGCGCGFGFCFHDCAHEEGDGCECHCHEBFBHGHGEFHBHFGDADEDHDAFADEHBBBEGEFHADFDBCGDHHGHGHGDGDHDGDFCFEGGFGCAAEAEBHAHADBHEAADHDCECHDADHCHBHFHAB,False +988,20.0,13.0,12.0,16.0,10.0,14.0,25.0,12.0,BBBCHGHGAGFGHGDCACHCHCAAAAAAEHBDBAFDGDGDFCGGEBAFDEDEHEDGDEDADABCBFDGAGAGHGAEDBGGGGDGBFBHAAGBGHDFEFGAEECCGFFBFGFGHCHAFFCACD,False +989,12.0,14.0,12.0,10.0,10.0,5.0,11.0,8.0,AEFEBABAHACGFBABGBGDEDGDEBBCBCHCECBCACDCGHGHGEACFCBBBEFGDDDCDBDADGEHAACHEGAGFBEHAH,False +990,22.0,22.0,18.0,21.0,13.0,23.0,11.0,18.0,AHAHEFFDDCDFGHDFDECHDHABEBCBCEAFBGGGGFCHCBCHHBEDFAFABCHCBCBCBABDDGHHDBFGEEDADFECGBAECEADADADAFFDFBFBFBFAHDFDBHBDEAEFHFGAHAHAHACCBBABGCGCFHFAFDFDEBCA,False +991,10.0,6.0,7.0,9.0,6.0,4.0,5.0,5.0,FDCBCGFHFHBBBABGDFDAGACACEEECAHDDGDEAAADADAECECHDBGH,False +992,9.0,13.0,4.0,15.0,7.0,15.0,17.0,13.0,DEAHFHGHBEGEBBGFFFAFDFDHDGDGHGHFHFDDDCEGBACGDBDGDEHEHGHGBGBGHFBABABFFFAGADHDGGGHFACBFEDDBCAFB,False +993,1.0,1.0,4.0,3.0,4.0,6.0,1.0,3.0,EFEFEFAFCEGDFHHHDFCBCDC,True +994,16.0,14.0,21.0,15.0,11.0,19.0,16.0,24.0,AHACCCDCAAFBFEFBDBAAGAHHCHDHEHAHEHEBGAGAFHFCGCEFEFEDACHCHCGGGFDFCHCDDDHDHAECHGBGBEHCFBDBGGFHFGBAFHFCDADCFCBCBCEHAHFHBCEGGGFAHBHDCDFHFGDB,False +995,7.0,6.0,13.0,6.0,12.0,13.0,4.0,9.0,CEAFHCHFHECCHEACFCFGGAGFCHCHFAFEDHHCECFBDBDGECHDFEEEEEEBABACFCFDFDFBAB,True +996,4.0,9.0,13.0,8.0,5.0,3.0,3.0,5.0,AGAEADDCACBCBCDCDEHECCFHEDBCBCDDDFEBHBHCCCBBFHGCGB,True +997,3.0,1.0,1.0,6.0,4.0,5.0,7.0,3.0,DDDFHEHCGFGFGFGEDAGAEHFDEDBGAG,True +998,18.0,17.0,15.0,15.0,11.0,15.0,12.0,20.0,EBCFCHHAACHCHCHGBCBCBCHDADAFAFEFDFDGHGHCBCFFHCACDFAFAHAEAEAEFEBCHAFBHBFGAEDBDHDHFBCDEAGABBHGADDBDBDHHHEBAGCEEHFHBGGDGFGAGDB,False +999,6.0,13.0,8.0,13.0,6.0,19.0,12.0,12.0,GDGCGCHCAFGFEFBFDEDHFBFBDBGFDADBFBACGBGDGEFBHHHHBDAFGFGBGHCFFECEFEFBAHFDFBFDAHCHDHCHDFDGB,False diff --git a/tests/results/nb_gm_002_2back_240trials.csv b/tests/results/nb_gm_002_2back_240trials.csv new file mode 100644 index 0000000..1c50201 --- /dev/null +++ b/tests/results/nb_gm_002_2back_240trials.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,ralph_skewed +0,30.0,39.0,31.0,30.0,32.0,24.0,27.0,27.0,False +1,33.0,23.0,27.0,32.0,37.0,34.0,25.0,29.0,False +2,31.0,20.0,37.0,28.0,31.0,32.0,26.0,35.0,False +3,27.0,32.0,39.0,24.0,25.0,34.0,35.0,24.0,False +4,34.0,24.0,38.0,28.0,31.0,29.0,28.0,28.0,False +5,29.0,24.0,36.0,31.0,32.0,32.0,31.0,25.0,False +6,25.0,38.0,28.0,30.0,33.0,30.0,26.0,30.0,False +7,27.0,30.0,30.0,29.0,32.0,26.0,33.0,33.0,False +8,24.0,36.0,32.0,23.0,30.0,29.0,35.0,31.0,False +9,35.0,34.0,30.0,29.0,35.0,26.0,23.0,28.0,False +10,30.0,25.0,33.0,31.0,27.0,37.0,30.0,27.0,False +11,28.0,28.0,29.0,26.0,28.0,27.0,34.0,40.0,False +12,35.0,27.0,30.0,29.0,26.0,30.0,36.0,27.0,False +13,38.0,27.0,31.0,27.0,34.0,23.0,27.0,33.0,False +14,29.0,30.0,28.0,35.0,19.0,30.0,37.0,32.0,False 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+9,11.0,23.0,19.0,24.0,13.0,20.0,28.0,13.0,DFDDFDGFDGCDFFDFEDCCDEGDAHEEDGGGGDAGHFBHFGEDAFGCHGFDBCDBDEBCHDEBGEAFBCHEFEAFBHFCCGEDGADGBCBCDACGCCGFAGBBDCGDBBBEBBECHACFAGFBGABCBBGFHHFHHFGHGGDGGBGBCDB,False +10,10.0,15.0,13.0,9.0,5.0,13.0,10.0,23.0,CAHCFDCFBGFGCFHBHAGHABAAHGFBAFDFBDBHDHCBGEFGDCBDHDEABHHHHGCFCEFCDHCFHBHHGHHGFHGBBABCABCABHEHEFHDCH,False +11,29.0,21.0,32.0,27.0,25.0,25.0,8.0,18.0,HEFAEFGCBEBDCBEADAADADCADABDHHFFEDFBCHACAAFBAFDAFDBCCCFDCEACAACEABFDCFDCFHHFBHDEFDAFCABGAEFDCDCCBCCDCDFAEFDCGCCECCBCBHDEGACBAHBEBEEFDBDHAFHAEAEECEGGHDBHDHCDEADEAHEHFEBFCBAHBHDEGAEFFCFCG,False +12,28.0,27.0,32.0,14.0,15.0,33.0,26.0,13.0,FFFAAFBAHCHHDHGCBBCEBFDGEGBFAACBACBACBAGBGBAGFFGFAHDGHEEFCAAHAHHECFBBFACFACAACDBCAEAHDFHFFCFFEFCAFBEFBFCBCABDBGGFECFGCBCDGGBGFDGDABBCCBEFBEFBAFDACGCCEHGAFCABDGEDFFDCFDGFGGCGGEEGCBGAAGCCCHC,False +13,29.0,16.0,17.0,15.0,16.0,11.0,15.0,11.0,CBECBEFBDDCDCAACAABFAGFEGACCECBEHBEGADFADFBBABCAHCABAABHEEEACEHHAGHABACGDHGDFGCHGCAGDAFAAFCCFEAEBAEDFDDGEABHAGAAGDGBAEDHHGABFEGDCD,False +14,17.0,24.0,25.0,11.0,18.0,20.0,15.0,30.0,DDCDHHAABGECDACBCCFHGEDGAHBABBHFBFFBCFHCHECHECACABHHBHEBHBHDCHCFBAHBFHBEBEDCEDEABCHCHFCHCAFBFBBHGEHGEHGHFCHACHCGGCGCDECFEGHEDFBAFGEFDAAHAHHGFHFABGEBGABGFFEFCEBC,False +15,8.0,6.0,1.0,3.0,4.0,2.0,2.0,6.0,EHBEDEHGEGFABBADBAHCAHAABDAHHABF,True +16,20.0,17.0,20.0,17.0,21.0,21.0,26.0,21.0,DEHCHAEHFEDFDHFCHGCGGCGAFBDDBDCFGEFGEFCEFHDHEFFAGDGDEGAHGFECFACFEEHBEHBGHBGHBGCECEDAHHBGFCCCADHAGHDEDBADGHEBDCHCCFAGEAFAABGABAHBAHBGHCACBEFEGAEFCECBGFDGFDGAGBAGBFG,False +17,12.0,3.0,7.0,9.0,7.0,12.0,9.0,8.0,ADGAGCADCFDFHEFDGHCEHAGGCDAHDCHDAHAFDAFEGFACFECFEBFGBAGAFFAEBDEHGHF,False +18,18.0,19.0,24.0,16.0,21.0,13.0,23.0,20.0,GGEGFBDFGDGEDAHGFBGHAGCDGCAAAHACECDECEBBEDEEDECDFDHBCCDHBHHACBACFHEAEEGHEGDEGAHBAFBEEHCBHCBGGFCGECGECBCAFCGHCBHFHHFHDGGAAEBFCBFDBCBECDCADCACGBHGEHGBFGADHA,False +19,10.0,14.0,15.0,8.0,25.0,14.0,11.0,20.0,EEEEBEEFHEHEEFEEGHEAFFAFHACGDCDDCFDCBDCBFFBCEAHEAHGCGGHGCHEEAEAHEAHEHHCCFGHABHGFGCHGCFDFHEHBBBDFBFBCEAEBHCDGCEEEHBBHB,False +20,16.0,9.0,19.0,17.0,10.0,22.0,10.0,24.0,HFGDDAFEAFEDCGHAADEHDBHAHDCGBAHBECEFFFFFEFEEDHEDCACEGHBGCFGAGGABDHFCHFCHCCDCFHHADFCFFCFFCBFCDHHHHDFFGHHDACDAFDACDCBHCHHAGHABHAB,False +21,6.0,10.0,3.0,4.0,7.0,3.0,3.0,4.0,EABBAEFHEFABAACHDCDDEFBEGHEGBDABHBBCBGEB,True +22,6.0,11.0,12.0,6.0,9.0,6.0,9.0,10.0,AEDBCDECBCHBCBBGFBGFHGEHACHAGAEFBDAECHCFHFDCCECGBCGECGAHGBHBHEBHDFGDE,False +23,11.0,8.0,12.0,13.0,7.0,5.0,13.0,9.0,EAAGACDACDHEEGGGGGBEGEABEAHGCHCCAFCFFGDHGDGCBGBDDEAFAADCDDCDDHBCGBCAFCBDDHHBHH,False +24,36.0,26.0,18.0,26.0,33.0,19.0,21.0,15.0,GBCHFHAAHAFFGBBEFBCFAEFDFGEGEEBECBEBBABBAEBEEAEEABGDBADBACFFBEFCECGACFADABCFDCDBCBBHDHHACGGEHDEGDEGAHAAFAAEDCCHHDDGDDBDGBDBDDCDAGAAFHEDHGDACDACDBGEEACGAEEBEHAFHBGAAAAAAAEEFBEDCDAEEEFGEGGHGFEAFED,False +25,11.0,17.0,16.0,9.0,15.0,15.0,6.0,9.0,CEEFABDBGDBFDFFDGADECBFCBCCACFABEABFABEGBEHBAHEAHEAECCFFCHDCBBBFGBAGCDFHHFBDFDCCHHEHAEBEGCCBFEECEF,False +26,8.0,5.0,15.0,9.0,10.0,7.0,11.0,5.0,ECAGCHDBBDCCDCGHBBEEFDHFEEEHBHGADADGFDEFGAFGAFCCCCCACCDCDGGECGECGEAGFA,False +27,9.0,11.0,8.0,5.0,8.0,4.0,2.0,4.0,FCAFDBEDBABAABAEEAEHDBHCEHCDBCFBABEEGECGBDABFCCAHCB,True +28,6.0,8.0,11.0,7.0,10.0,5.0,9.0,9.0,CFBCBCCBACBEHBEGCADHDGFEGFHGHDAFBAFBEDCDGCHGAACHCHBCEEEEDHEDGEGGH,False +29,24.0,16.0,18.0,25.0,13.0,19.0,26.0,18.0,HEFHCDEGDHFBACGGDEHDGHDGFDEAHFDHGBHEBGEGADFFGCCGDHFBFABDACDABAGFGDAGDAGCAFFAGHHCDHCHACEDDAFDCCDCAECAEDGEDGAFGFCGFAGBBGFBDBBAABAAGADGAFCHBEEGHBGCBFCGFAHHCHDBDDE,False +30,6.0,5.0,2.0,9.0,2.0,4.0,3.0,8.0,DADBAFBDFHDHHBAHEADGFBHFGHEAHDHBDGDCADC,True +31,19.0,18.0,16.0,13.0,19.0,13.0,14.0,15.0,FCHGCAEHAEBDEBABAABHAFEBDCBDCBHCGEAGEFBAFCCECCBCFHEHGEGAEDAECBECEAFEBDHBDEAGFGHDGCDGADFAHGCFCBFDEHEGCEABFADHAFHGBHABHBHDAEBGDFG,False +32,7.0,12.0,12.0,10.0,7.0,5.0,5.0,9.0,EBDGBGBBDCBACGHBDAAHEBGCBFHBFGAFEHFCCCHDCHDCHDAHDCDDEBDEAFECBAHBECC,False +33,1.0,4.0,8.0,1.0,4.0,4.0,5.0,3.0,GAECEGFBHFGHBGCBFCECCECCBCHDGF,True +34,5.0,4.0,6.0,9.0,13.0,13.0,5.0,7.0,CHHEFFDFFDFFDFDGGDFGDHCEAEAHEAFEBFCFEEFEECAECHCHFDEBDBGEGABDEH,True +35,3.0,2.0,3.0,3.0,5.0,4.0,0.0,6.0,CBDEEHHEAHCAEBDFADFHFCHFEH,True +36,13.0,2.0,13.0,8.0,7.0,6.0,16.0,9.0,DEGDECDHGAHGEDGEGACAFCADGACGACHFDACHCCHCEECGHDHBEGGGGCADCAFAGFGGBAGCAHFHFA,True +37,18.0,19.0,17.0,17.0,13.0,17.0,15.0,23.0,HBCABCGHCEEADEDCEDGAGFFFHDFADHHBHHGCHFHHAGHEHEBBBDEFECFEBHCDAADFGDFHDCDCCDCCFACAACHGGBGGBFBCFBFFCFGEDABDBBDAAGAABACBEGBAHAHHFGEDGHDHHEBHBHF,False +38,4.0,6.0,5.0,9.0,6.0,4.0,4.0,6.0,AGDAGHABHCEEFBEFDEHDBHDECDFCDBHDEGBBGCCADFDH,False +39,3.0,5.0,6.0,8.0,8.0,2.0,8.0,6.0,DCEDEEGEEGAAFEHFGHDGDBHDBGBBGECECDGHBGCDDCHCAH,False +40,0.0,0.0,1.0,3.0,1.0,3.0,5.0,1.0,GDGGDCEHFGFDGF,True +41,20.0,19.0,22.0,21.0,30.0,22.0,10.0,26.0,BADBABGCFGFDDDADEFHAAHAAHEAHBBHECFGFDEHDCDBBBHGEDEECCDCCDGCHHBGHCHACFDCFCFEDFEDAHHHBHAECABDABAAEHFEADCFEBFAGFGEABECFEFFECEEFEHFEHEEHDHDCHBBHBDHCEHCDHBDCFAEFAGHEGECBCFEEFE,False +42,3.0,7.0,4.0,4.0,5.0,2.0,5.0,3.0,EBBEAEEHDCHDCGDGGBACBEHBDGBAFBFCG,False +43,21.0,15.0,21.0,27.0,18.0,33.0,14.0,23.0,DDDDDDBCGFEFFABFDHDAGCEFHHACHGBHGBEFEHFEHFCFFCHDGHDFHDAGFECCCAAEAAGHGDFCHFCHBBBFABDEFDFFBBDBAAFDAFAGHACHACEFFEFDHABCAFGDFEDCGACFADFDDFBHFAFFBEHBEHFCHEADEGHEGCDGHDHDEECCFCCD,False +44,27.0,34.0,20.0,19.0,15.0,29.0,27.0,26.0,FGCFGADGADGDDBDBAFGAFDHHHAFBAEEAGGBDBFCEFAHFAHFAECDCBBCGBHAFHABHDCHAHHGBCGECFDCEHCFBCHBGHCABFBCFBEHBECBAHBGDECHFDFBDEAFBBGECGEBBHDBHDBEABEBFCDFHHFGHFAFFGCACFGDGGHGAABCDBHBGGBGGFHGHGGBEADABFABAAFAFF,False +45,15.0,12.0,15.0,7.0,7.0,15.0,11.0,5.0,CAFCDGCFACFCCFACGBBGCAEAEGAHFADBCHACHFCFBEFGEGBDGBDGBEGEHAEFGBFCDFBFBHACAFCAFGABDAFACDB,False +46,12.0,10.0,7.0,5.0,4.0,11.0,11.0,13.0,ECFFHGFGGFCGACGFGGAHFABBHDEDCHABFBHGAHGAHCAHDABDFHDFGCHGBEABAHEHBFHBFCBAA,False +47,15.0,6.0,13.0,11.0,17.0,21.0,13.0,9.0,EDCEFAEFAFFAGHCFCEEAFGFFHFDECECCEGCDGHDGHDGHACFFCFFCDFEHEEFEEGHEDAFBGEAAHAAGCABAEFAFDABGFCFHCDEDBABFGBGGD,False +48,11.0,17.0,17.0,9.0,17.0,17.0,13.0,15.0,GAFGHHGCHBCACCFBCFHHECHBHAFHEEGBAFCAGHGEFGEDGFCBBEBGABCFDCFDCFDBEEEGAAHDAEDFECBGCBHDBFEGHHBFGBFEBFCBCCHEFAEDAEDCEFHB,False +49,13.0,16.0,15.0,12.0,16.0,9.0,12.0,15.0,BGCBAEBCDBEDBECBDCBABDCDFCDBCEGDABDFFEHCEDGECHACHEBDECDGHFFHFHEAHAHHEFFBAGAGHCHCCHGCEEAAAAGEEGDEGBFGBAGBHHBH,False +50,13.0,6.0,16.0,14.0,12.0,13.0,9.0,12.0,DAEAAGAAGCHCCHDFHEFCCBEGFEGFHAHEAGBGCBFCBFCDACDAFDCHECEBFBAFCFFDEHAGHDEFDGCDECEHCHDGADEHHFADCDD,False +51,22.0,27.0,26.0,19.0,24.0,22.0,28.0,20.0,FDCGDAACFACHGCDGEBFCBDCBGBEGBEGAGGFGGCHGDHGDCAACHADHCFHAAEEBBCBCCBAEDAGBFGAFGEGGDGHCEEEDEHCBBCDECEBGEFCCHCFBCFBHFEABEBDEDHABHDBFFFCEFCEDHFFHBFABHAGGECAEADBGGEGAABHAGHAGEFGBFBFHHDHBEGBFCCDD,False +52,19.0,24.0,24.0,17.0,11.0,20.0,12.0,18.0,FBDFCFECGDCFBBFHBFHBAHECHAAHAFCAHCHCFBDFCDHCDBDDBAGAAGAGHFGBDABCFEEAHHGDHBDCCGCCDAEBAEFEBCHBHECHDABFFBHECFDCBDBFDGGDBFABGHBGFCFCBDCBACBFGHEACEACA,False +53,11.0,13.0,7.0,11.0,11.0,7.0,5.0,12.0,HABDABEADFFDABBHBEDAEDACBEHBEGBDDEAAHAHGBHBDEBAEDECCHFDHFGHFGHFDCCEBHEBHGCACF,False +54,11.0,20.0,14.0,17.0,12.0,15.0,15.0,22.0,DFABFDGCDCDDCBHCBECBDHHHBEFBGFEGHGFHEFEAFAHDBHDGDGEDFBAFBGFBGAGGHHCHHEDBDDBCFFCGFCHEEECDDADHBHHCDHCBHFAEGBCBBAHBAGEFGAHABHCBHG,False +55,17.0,24.0,24.0,12.0,23.0,20.0,17.0,26.0,GAECBGBFHAHHEFEGCGFBGBCHHADCACHBGGBHBAHBAEFAFGGFBCCAFCFHCGHCFHCBEFBEFBCHBGFECFGDHBEHCCACGFHEDAEBAEDDEDCEHBEBBEGEEHHACHECBDFFDFADFAEFHCFHCBECDEHDEHCBAGBAGADGBCBHHEH,False +56,17.0,25.0,29.0,22.0,21.0,19.0,27.0,22.0,FFFFFGGHDEHDFGAFGEEAFEGCEADDBBDHDCHECDGCDAAFCDHBGCBGBBECCDCCDAHGBHCBGCHCCEFEGFAABBEHFEHBCGFHGCHBDHCDHCFBDEBEABEDBCDGCHCCFGCFDAGGBGBBCBFABFEGGADGHEGHEDFBBCBCGACDAEEABDADGGEGHEGCCHHAHH,False +57,12.0,11.0,4.0,15.0,9.0,3.0,6.0,8.0,HABCEHAECBEDEDDHBDGAAFHAGCBGBEAAABADEADGHDFBAFBDEBEEBGDCDDGDDHDAHDBH,True +58,9.0,8.0,9.0,9.0,4.0,9.0,12.0,13.0,CAGCGGCBAHDEFDHHGHDFDBFBBFGAFEBFECHABGGDGDEGDHGBHADGFDCACAACHBFHFGHCHHCHA,False +59,15.0,19.0,20.0,23.0,14.0,16.0,21.0,18.0,GDGGBGGCFGABBABFGEFGCDDCFBCDBEBACHABGEBCDCCDFDDFDAACEBCEGGGFHHFDHGGHFGADHFHHGDHDFFGHGGHDEBDCAACGACFADDHDDCBDBBFEBHDDHFCEGBEHCABEAHEAHEFCCHBAEBCEDC,False +60,9.0,8.0,2.0,6.0,8.0,11.0,5.0,10.0,FEBDCDFHFEHFEHEGHBHFBHFEDCHBBBAGEAGEAGHADABFHFFDBFAEFADAAHG,False +61,26.0,25.0,20.0,16.0,13.0,13.0,17.0,12.0,CBACHGCFDHEBHBBEBBFAHCCEAEEABDDBDGEGADGHDAHEABBBEFCFFDEFDAGDADBBHGGCEGBAADABCHGCHGBDBBGCBGCHFAEFCHFBFDDCAACHACFACAACABFEBFAAEGGCGBCGBAGBDDACAA,False +62,9.0,9.0,5.0,7.0,5.0,5.0,11.0,6.0,FAADDAGBGGBGBCHBCAGEADACGAHGACFECDABBFEFDGGDFGHBGHDEHBEHB,False +63,7.0,8.0,8.0,6.0,13.0,12.0,11.0,4.0,GGBDGFEGCEGCECHDCFGFGABGFEHFCGGBHFBHEGEEAEEAFEDBCFBDFDEADACBABFACFEEF,False +64,20.0,11.0,23.0,13.0,16.0,11.0,12.0,18.0,AEDAHACHEFAEFAHCAEDAEDCBAGGCBGFBCHCHFCEACHCEHCFHCEAEAAEAHCAGBDCDHCEHEGBFCHHCGHFBHFAAGEADHBDCADCFDGFDCHDCBGCGAAHCGFGDEBDEBECB,False +65,19.0,12.0,22.0,18.0,18.0,14.0,20.0,17.0,CCDCCAFHAECADDGDGACGADGHDFHEBGEFEAFDHBDGBCGCFHBGHEGAEGBDHFDFDCGDHGDAGDCBHEBHEBGBAFHGCGCCFEEFCDCCDCHECHFCFAAAGECHBBEEBHDAGAAEAAEAHEGHCFCEFGAD,False +66,26.0,13.0,22.0,33.0,10.0,21.0,25.0,20.0,CDFGDFAHFEHDHBBCDECDAHDGGGFBCDBADHHDGADEBDEGDHFFCFFDHDGADHCFHDAGEGCEACGBGGEAGFAGBBDABCABGADGAHADDADCADHAFCFGDGEFBEAHDCGDHDCADFADFGHCCHGFHCFHGDHGHGECCCCCADBFDGAABAFDAFDAFC,False +67,3.0,0.0,0.0,5.0,2.0,3.0,2.0,1.0,FDFEDHDGAFGADEAD,True +68,21.0,30.0,10.0,18.0,20.0,13.0,15.0,10.0,ABBHBEEEHDEHDGFFGDBDBBCABFGDCCDHFHHAAAAABFAEEDBEDBGBBEABEABFBBFBBDDAEEAGCFHEBAFAGDGGBBEDBHDFEFEEBEEBABDHBFBGCBGCGGBGCCGCEGAADAABCDDADEAHF,False +69,23.0,30.0,20.0,17.0,29.0,22.0,24.0,20.0,BHBBFBBEEAEGAEHBCABCBGCGEFHEGHFFBFCBFCHEEDEGCCGBCHFHBAACDGBFBEAEAFEHFEHGHGGACBEDDDBDFBGBAGBAGEDGEHAEDDHGDFEDFEHFACCAEHFBCGBCECFGFFAEGAEAHHBGABGAEGDCGDCHDBBEFAECDHCDHABAFBACBAFBFGEDEEHGB,False +70,16.0,21.0,23.0,21.0,35.0,31.0,21.0,19.0,FEGHEGHEHFBHEBDEGDABDAGFAGCDGCEAEABGGEFEBAEBHDFEFACFEHFHHEBFGGDGBAGBAEEAFBACBCBDFFDGEECFEDFEAFEFFEDFBBFHFFCGFBFCECEHCHFFHGFDGFHECEGCDDBDDEECCBDHADHADEEEECDBCBFHGFHGBCGFCHCCBGDEEAEHAECDCCF,False +71,21.0,21.0,25.0,23.0,34.0,29.0,19.0,27.0,CGCABAFBECCEGAEFEEHEDHEFBAFBFFGFDCBDFHDFDDHCCAEGAEGEECFCDFGDHCDAFDFFHBAEGDECFHHFHHEAABFABAAHCCCCHHGBBCBHGGHEFDFFCGFDGHDAHAGHCEEBBEDBEGEHBEGCHAEHDEHFEBDECFHABHABAAFDDFDDFBEFGHGCEECFDCDCEECEEAHEGHEFBBG,False +72,26.0,9.0,19.0,24.0,24.0,27.0,21.0,27.0,DDGBDCADHEDABHHHAEHAHDCHDBFFEEFAEFAHGACFFEEDHACFCCFGCDACDCCDCEDBADHFEGDHDFHGCHFAEFHDFGFGEFGEGGEHEHHAHFEHCAAEAFCHDCFFFGABAFEAGGBGHCHDFHDAAGAFCADGADHAGHBGBBEEEGEEFAEFAEFCGDCFDHGDH,False +73,24.0,24.0,23.0,19.0,22.0,18.0,26.0,30.0,HGFHGHHBBHDBAGCEDEHDHCDAAGCBCCHCCDGGHAGHGHHFAEFGEGBEBFDFAEAHBBHBDCBDCBCCDECHHFHDDHCGAAAAEAEEDBGDBGCFACGAHGDFGCGHABBACBAHGHHBHGBEDDACFACFEBFGHCAEBGEBGEDGEDHEFFECEEAEFGGHHFBBFCHFBAFGAEHACD,False +74,26.0,17.0,19.0,17.0,28.0,19.0,13.0,23.0,EGCAHEHHEHABADBADECBECEEABEACFACACFFBFGBFBDFCFCCACAHEBHEGHDBHBBAFEADEHBCHEEHEGBFGBFDCGDEFDEADEDHEAAFFEFFHHFACDCCEAHDADDEEEFAFGADBHEBEAGAGDAHBCHCGHCAHGACGEEFAHGHHD,False +75,3.0,1.0,2.0,0.0,2.0,1.0,0.0,4.0,EAHBCHCAHEAHF,True +76,10.0,5.0,4.0,6.0,10.0,5.0,10.0,8.0,HGHHAEEAEDAECGDCAHGFBGAGEFGFBEFAFCGCEAEEBGEBGDDHDBHDAHGAHA,False +77,6.0,2.0,4.0,1.0,4.0,1.0,1.0,0.0,AACCDECAEBAEBAGFECA,True +78,26.0,21.0,24.0,22.0,21.0,23.0,16.0,22.0,AEAFDAFGAFHAHCGFCGFHDCBDCBABADBCDGGFGHEBBDFBFFDCDEAEEGGFHAHDCDDBGEHCEFCHFGEFDADGFHFBDFCCCBCGBCABDFHAEBCHBCHBCDECEGFFAHFAHFCHFDDCAEHAGHBGHBAEECDDDDAABAHECHEBHEAHABGEBAEACEACEAF,False +79,23.0,23.0,29.0,21.0,13.0,23.0,22.0,17.0,CDHBACEAHEFDEGHAGAAGFAHFADFCBBBEFBCDGFBCDBDHGGGGCGFBDBBCFBFDEGEEHEGGBGEHFCCFCBDCEDAEABFDHHBFBBCAGDDCHDCHDAHBACAGCAGCADDBDFHAFCAFCGHDEBGHBCHGCHFBEGBFACFCCACAADACFACFCCFGFDG,False +80,12.0,12.0,23.0,9.0,27.0,13.0,18.0,19.0,EGFECEECHEBEEHHFBDCGCAACFBCGEHEEGCEACEGDEADAGBAGBCDBFBHFHACHCDHCDHCECCEGFHGFBABCGDCBDCEACHBCGGAEEAECFEHHAFFEEFHFCEFCHGGGGDHBEHGGHEEHE,False +81,25.0,15.0,14.0,17.0,20.0,16.0,15.0,15.0,DGDFFBFFCAFHADGAEEAFDABDEGGEBGDGEDEBAHAAEGABAHCACEACAHBAGGECFCDDEDBEFHEBGAFCAFCAHDEHDAFAGFCDBCHCCHCEDBGFGHBADBHGBEAAHAAHAEFECFEDFEDHEBHGB,False +82,23.0,16.0,15.0,28.0,9.0,16.0,15.0,26.0,FAHGHHFHGDHGDHDHCCHFBHEDGDGADGBDFDHFBBEDBADEDDBDHFDACDBFGBFAHCDDDGDBGBBGAAADCHFCHCDGABFHDDHDAEDCEDCGDFEAAEACHHGHDGCFFCHABHAHHAFCFHAAHAACBABBHFEAGEAC,False +83,16.0,17.0,21.0,14.0,11.0,17.0,24.0,19.0,EGHCBBCBBHFAHAAGAFGHBCDFAGFBDABDADEEDBCDBCHBCBGEGFFGFGGCHGCGGHHADHDHCDHAFGACCEHDGHFFCDFEDAHDFFAFFHEGBDGCGCBECECHBGHGGHCGBCHBCEGFGGFCACAABAE,False +84,25.0,24.0,34.0,20.0,21.0,23.0,18.0,22.0,GCCGAFHHFBGFBCFBDFBGFCGDEGCAHEBCAFCBFHEFEDCGFCAFCHCHBCHEAHAFBAFDAHBHBDGAABAFBACACHHCFDAFDGBAHBEBBEDFCFECAEBGFHECCCCCCHHEEHAAFDGFDHBDGBEFBEDDHDDEBHECCECCEBAEBAGACGEDGADCBCCGGCDEAGCADCAFHHD,False +85,14.0,17.0,15.0,14.0,15.0,14.0,16.0,10.0,GGCGDDEBFFHGFBGFBHFHHEDAACAABGFFFCDBGBEHBEDBFDBCDCDGCDEFBCHBEGBEGBEFHGFBAEBCEFAAGGCHCCFCCBCHEHEAACADDEDDAGDAGEAEBAG,False +86,5.0,2.0,1.0,1.0,1.0,1.0,3.0,1.0,ADFAGGAHGBEABCA,True +87,28.0,33.0,23.0,19.0,20.0,25.0,30.0,22.0,FFGDBGHBGEGAADDHGEEDEHBBACDFCGFCGEHFBBFHBFBCCGCCFHDFCGHBECBAAFFDBBCBECGGFEGECCAGABBABHAEHBBHBHDEFDCHDBAFFDDFAAHAAHCDFCAHEAHGAHFAHAGHAGAAGEEDFGBEBECBGCBAFBGCCGAFAAFHAGGFGGBGGBDEEGEGBFGBFHBCHBDDBDDBECCA,False +88,27.0,30.0,28.0,20.0,23.0,12.0,23.0,29.0,EGBCBBCEBCHHGDBECBCDBEDGEHGAGACGEHGCDACFECFCBHBBFDAHCACBACBEFGGAGGADAAEBAHDFHDCDBAHCHHBHABGCBEEDHGHHGFHAHDAEDABDGCDECDBADBHHGHHGFGECBEABDHFDGAHEACFGCAGCABCHBFECHCBFCBFAEABDAGEHEEAECABDHBHHCEBG,False +89,14.0,15.0,7.0,17.0,10.0,11.0,15.0,9.0,CHBADFABGHBGFGGAGGADGDEBHADHGHGFDFDDCDBGAAGHAGFAEEBBEDBEBCEBFAFDAFDFGDEADEGDFACCCGBHBBHABHDEDCBDFE,False +90,5.0,3.0,3.0,1.0,8.0,0.0,6.0,3.0,CCACEGHEGDEGBBAHEHGBAGEAEEAEG,True +91,0.0,0.0,4.0,2.0,4.0,2.0,2.0,1.0,GDCFDCEECGEHFEC,True +92,14.0,4.0,7.0,10.0,8.0,6.0,12.0,5.0,DCDAEFAFCECEEAFEDFEGCCGACBDGHFAHBGEBGAGGAGGDGAEGHHGAADAFDADDCBAHDA,False +93,10.0,8.0,8.0,3.0,8.0,14.0,16.0,15.0,FAGFDGHDHHEHEEGGFFACFHEHACCACHFGHFGHCGCAGCGBCFFEGFGBHABHFDHGBGBHABHAFFAGFEHEEBBAGG,True +94,21.0,25.0,21.0,30.0,27.0,13.0,12.0,17.0,HHBEBCAACEABDGDGBDFBGFCAEHGDCADCHDCEDFEDCEDGDCEDAEGEHAADBBDAADHCDHDFHBEEBEEBCEGAECDEBBCGAHEBBFFHEBHEHDAHDAECFFDFEDFBDABDCCACEDEBDHDDAGFAEABECBHGFDDFEDCCBHCBHGBEGBACBA,False +95,4.0,6.0,6.0,8.0,7.0,6.0,6.0,9.0,EDGEBHEFHACBBCFEGHCHDAHDEHDBHDBDDEHFCGECGFGBFACFAHGD,False +96,8.0,5.0,5.0,6.0,5.0,8.0,12.0,12.0,AFACCAGAGGFBEHEGHECFDFFDGFHGAHGHHFDGAGCAGEFGHBBHEBHDDHDHHGCBA,False +97,20.0,25.0,21.0,20.0,27.0,26.0,25.0,26.0,BFCFGDFBECHDCEBGEFGBABHGDDGAFBEBCEFEEFGDAHFBHEHHCHDDHGEFDFFBGBBAEGCCFDDABEBBEBFHBHHBCCECEDCAFCGFGHFCBGHBEAFCBFDEEAEEAFECEBBGGAGHBDHFHHFHHFHHFHHEEHGCDABGABGACGAFGAGGDDEDDCADCFGAFGDCAHEAHEAEGC,False +98,4.0,3.0,1.0,1.0,6.0,1.0,5.0,3.0,BBAHAEDECGEAGBAGEEGHEGHF,True +99,21.0,17.0,15.0,21.0,17.0,23.0,10.0,21.0,AHDDHEDGFFGCFHDHAGHGHHDDFADFABHDBCCACAAHGDDFDDFGBHEBHBHEEHEFCFFBBDDBAABCEEHDACDHCEEAAEBHBFABFABCABFFFFDFFDFEEFCEHCEBDEBFCAGAGGDGCHBCHAAHEFFECAADH,False +100,21.0,17.0,13.0,22.0,21.0,22.0,21.0,31.0,GCAADDGBDEBDABDGDGGEADEDDFHHHEHDGHFGHFDHGAFAHEHDCHDHFEBGEACDACGABGABGFGGDGBHEEHEFFGHFABDHEDAECBFHAGHAHBAEAAEAFEHFEBGGBCFDFEEAHCHHCFDAFDCFDBFHBAHCHHFFGEHDECCGCBHFHHFBHBE,False +101,3.0,4.0,2.0,2.0,2.0,1.0,2.0,2.0,BCFBEABEABHADGCHGD,False +102,3.0,5.0,4.0,4.0,2.0,1.0,3.0,10.0,BGHBGHCCHCDHEHHABDFHDBHEGCDAHBAH,True +103,22.0,16.0,17.0,17.0,11.0,10.0,13.0,12.0,DECDFCDFEDCCBCCBCADGAGFAEAAHHCGECAAFHAHBAGEFDEFHHGGFBFCBACBABDACDAHDAGDGBDBADHFDBCEHGEHGDHABGBCEDEEHBAABADCGGCFCABDABA,False +104,12.0,15.0,10.0,16.0,25.0,15.0,20.0,17.0,GBFDCFDGDDBHDAADEBGBDEBEEFGHFGHFGHCGHEGDEADHBDHGGBGHEDCFHAAHACHGGEGGEFEBFGADCCEBHEGFEHDEHEEFAGDCHFEEAEEBCEGEDBEDBECBFFBHHCAFAEGAFB,False +105,7.0,10.0,8.0,8.0,6.0,8.0,6.0,10.0,HBEHAGHFGHBGDBAAGCDEHFEBEHBEBCABAACDFHBCHDFGDFGDFHCHCCACBFDBEDF,False +106,17.0,20.0,9.0,15.0,13.0,17.0,14.0,15.0,FBEAGDAGAABAHBGEFFBFFEDHEGHEGHEFHFDBBCBBDBCHCAHGAHCHBEGFDGFAEBAEGADCAHBDFBDFDFBABHEFGBCDAFDBCAGCFBHFBAFAEDHEDCEDHBDGGHGA,False +107,5.0,5.0,1.0,5.0,1.0,5.0,5.0,2.0,FABAAGDGFDFHBFEBAGBAGBFDDHGDC,True +108,17.0,16.0,20.0,15.0,16.0,19.0,21.0,30.0,CBHCHHDDDGADGAFCEHEBHEFEAAEBHFHCBGFAEDHEFEFFCFFAHEHHAHBGCDCHFGHBGFCGFBEABFBHHGHHGCHEAHEADABGHBHHBDHGDHGAGGBGGEFCFFCDBGDFDAECEECGCAGCGDCFDFHHAHHDHBBCCACGAC,False +109,19.0,26.0,19.0,10.0,27.0,23.0,8.0,14.0,EBCAAAGFADFADFEFBBBCBEABEABEAEEHEEHEECEBGACCAFCBHCDCCECFBCAGGAFEAFEFBHHBDFAHEHFEGFHCFBBHCCABCHFFBFFBDGCEGEBAEGCFFEEDHFFBFBADBDBBDBBEHEEFCHACBAHDEE,False +110,19.0,10.0,10.0,17.0,15.0,14.0,13.0,9.0,EACEADEDDGDAEBCFACEAEBFHFFGDFEDBBGBHGCADCFBBBHCAHEAHFAHAAHCDGCDGAEGAEGEDDFGEAEBAGFCGDGDDABDFCDFGFFAAEDFEHAH,False +111,6.0,10.0,13.0,9.0,4.0,7.0,3.0,10.0,CCCAFBAFBEHDFBCCBCHBCBCGHDAHDAGDCDFCHCEHDAFDFHDHHDEEBFBAGBCHBC,True +112,14.0,15.0,18.0,9.0,20.0,11.0,10.0,7.0,DEFDEFBEACFGEFCACCBGGBHAAEBEHCEGGEDEEFEEDBECBABGADFADFADGCHCCHCHACEDHEGAFAEFBFBAEACCAEBBGBBGEBEBHCCDCCFC,False +113,18.0,25.0,13.0,24.0,29.0,22.0,19.0,30.0,HCAHEABDACHBBDDHADBEHEEHCABCFBHFBABBABDHBEHFGAFGFHCHGCAEFHEFHGHCGCEHDDFEBFEFFDDHDEEDGEFCBGBDGAHHCHDCFDEEDGCFHHFEEFGBGGEEHBFAGFDHBEGFEDCEDEBDEFHEAHEAHABBEDBGFBGEHGAHFADBADHADHEDBGGB,False +114,13.0,9.0,15.0,32.0,17.0,18.0,11.0,14.0,HDHDDAGGFDDFHBFBCAEDGEDCEACDDEEDFHFAGFDECDCCDFADECFECHDCHDGAGAHGHDFEDCEDCEHBHDAHDCFDBFHHGDBDAFCGFAHFDCCDAEDGEDEEFADFAGFBBDEBDEBDF,False +115,21.0,18.0,26.0,25.0,21.0,27.0,25.0,34.0,AACCECDFFBBDABHAGHGFHGHAFHBFHFEHCBHFDAGHAGEDBEACHDCAGCDCCDBEDBDDEGGEHGAHFAHDBFGHFGCDCCFCBFCBHCHHFFDFGEEEDHFHHFHDFEDFDCBHAGAAGHBEEDCFFCHEDAEBAGDEGDEDBFBGCBECHCGHCDAGGAHGHCGHCFHBFHCFHDADAEGEGHCGAFFEH,False +116,25.0,15.0,25.0,18.0,19.0,11.0,22.0,30.0,BGGBGDHGBAECHEFABDHBHHBHDADBEEGFGGDGCCGFCHHHAHAFHBFEEGEAHCGEAGDCCHCGDAGBAGBAEADBADHADFCGHEDHCABCHHEHDFHFAHEAHCHCAHBDHBGHFGEFCAGCHGAAACAACHHDHCCGECEDDFCDACDACBCCEEGEE,False +117,28.0,24.0,15.0,28.0,23.0,30.0,14.0,19.0,CHACHAGEBEFDCFAGFADDEDDBDGBDBFEBEDHHDGDECDEBFABFAFFABAAHHAHHDFHFBHDBEDADCBGHEDFFDEDDEBEBAGADDFFFBDFBFFBFFBHACFDBFDFAEBACBACGEGGCFAFEHEAHECHBDGGFCAECFEFHEHHAGACBDCBAHAAEAAEDECDAFGGFB,False +118,0.0,3.0,1.0,0.0,4.0,1.0,0.0,2.0,FHBBEEBEECH,True +119,15.0,14.0,10.0,15.0,7.0,12.0,18.0,9.0,BGDBGBFEBDCFAFFADCGGAGDABAAHHAHHACEBCDDCBDAGDGBBGDGDDACEFCFFCGFHGBEFCGACHAGAGHAGDABBEEFHGFBFDBEDGHDG,False +120,18.0,23.0,21.0,12.0,21.0,14.0,26.0,15.0,GBBHAAEBAEHEEFEGFGCAECABAGCADBEFAAGDABCAGGFGGCHGCHGAHEAHFFCEHCEBBFBBEHBCGECGACGDCGDHGCGGHGGDDGHACBBGDBDECDCFABECFEBFECEBGBBEDDEGFCDFEGBHGBHAHFACEBCHBF,False +121,18.0,17.0,15.0,11.0,14.0,12.0,17.0,17.0,AGGAFDDFCDBBHECHBCHADHCBACFACDDGFACEBCBBGBHAAHEAEEHGFGCFGBHEBAFHAHHADHBEGBHHCEFEEFGHFGFGCBDCADGBDHHEBEBBAADAAFCAGCGGEGGEC,False +122,19.0,12.0,14.0,16.0,13.0,13.0,22.0,12.0,DFAEFDEBHGFEEDAEDFGGCGGFGGFGGAGGAFFDEAGEAGDBBABDHHCHHBDHBDGCGGDHDAGCACCBFCBABHEFHCCHECBCGDDAHDCEEFACFBCAGDAGAAGAEFAGDBEHA,False +123,3.0,8.0,5.0,11.0,9.0,10.0,4.0,11.0,EBFFHHFADFCHFGHEGHFGFACDEDDEGHFAEDHBDEBDECDCDDFHBFEBHHBCEBHDB,True +124,4.0,5.0,6.0,11.0,9.0,6.0,5.0,8.0,ACEACEADEDEHDCFFCDCCEHHEHEBHGBDGHDFDFEGFEDBHDHDBBGFAGD,False +125,11.0,14.0,19.0,12.0,21.0,14.0,17.0,9.0,CCDCBDBEDHEGHAFEECDGCFGCEGCBGEFAEDACCHCDHGFEFFBBEABEAHHAFCCFBFFCFCBEGDACDGCAEBAEGGEDGEDCAGGEDHEBHBBACBHGFEGEGDEGEFCBF,False +126,7.0,15.0,16.0,15.0,17.0,19.0,21.0,17.0,CHHHDBCCEFEEBEGBHFEDGEBFFBGFGHHGHHGEHDHCDHCDFAFFDCABAFBHGBCGBFHBDHCEGAGGHHGDEAFECHDBFGBDBCDECGEFEEBECBDFFDECGGCGADGEDGFGCFGCFAF,False +127,1.0,2.0,2.0,2.0,3.0,3.0,7.0,2.0,BEGGGGACFHCFHEFDGGDEGB,True +128,24.0,27.0,28.0,25.0,25.0,12.0,31.0,20.0,GGGBGGBDBCDHGACGEHDCHDCBDCHHEHBGHADDADDEBGGHGDDEADFAHFAGGEGEEABEHDEHCEBAEBECBACBACGACGADFADBBBBFCCAEGHFBEBCAAHBCHFCEFCDFCDCCBAEGEGCAGCGCCGEHFEHGCCACAACBDDBHGBEBDAFGEFGBBGHHEDGDABCGFHDEGGEDEADB,False +129,8.0,19.0,18.0,15.0,11.0,19.0,15.0,9.0,BEEBFHGAACFBCEBFHFADFCDHCDBCGBGGEGBDAADFDCHECHECEGCFGCFGFBCFGCAGDFGFFHHBDDFCDFBBEDBFDGDBBFBHABCEBCDAEGCBFHBFCGECGD,False +130,19.0,16.0,11.0,13.0,12.0,17.0,19.0,19.0,AGFEGFGGEGDAFDBFDBCGACBHEHHAHHDFADABHAGHBFHDFCDCADEEFEGBDGBEGADBAHFGBDGBAEFAGFBCAECHGBGFBGBBFBHAHHAHDEGEFAHADCACCHCEHGAHFHGFCF,False +131,4.0,4.0,2.0,0.0,2.0,2.0,3.0,2.0,FBECAGHAHCAGBAGBEFB,True +132,21.0,22.0,26.0,22.0,19.0,22.0,19.0,31.0,HHACHAGHDFHCACFECAECGDFFDFCAACEBEDHHAHDCGBCBBCAHCAFCDBGFGDCHBHECHCFACFGCHECBBCFBGHDGHEGHDGFBAADFGBGGFCGHCBHAGHFEEEDAEDAHHABFABHAHHGHBFDAFDGDDFEDGBDFEDHDDHCEHEAHECEECEADBGCBFFHCFBBBBH,False +133,16.0,18.0,20.0,18.0,16.0,13.0,27.0,16.0,DGGBCEDCEFHDGHFBDCHFHHBACBADAAHADEACBGHFGEDGCBCABGAGFCGDCGDGBEGBEGBECEEHGEHGHHDAAGGACBDGBGCBACDEBDBGCFHFEHCEGCEAEFCHFABFEGGCDHFDCDDCDBFGBFGAGHAG,False +134,19.0,21.0,15.0,10.0,12.0,12.0,10.0,11.0,DAGDAGAAHHFHABCBBCEBCFBCGDCGEEACACBACEAFGBDAAFEAFEHBBBFECDEADGFFACGECBBCBBGEBFEBDAACHADHFEFBCHBFGBHDBCGBHADHAH,False +135,13.0,9.0,13.0,6.0,13.0,9.0,17.0,10.0,ACEEHFBHFBGFCHABEADHHCGACGDHBCABEGBEDBGGCGHHAHCEDAEFAEGCEACEAGGFCGCDGBFGAFGAFBEGCEGAFGECHD,False +136,12.0,12.0,9.0,6.0,6.0,6.0,7.0,12.0,DGFDCFBCHHHHHHHBHBBABEAFGBEGCFDFGCCBDABAAEAAHACCAGHADEACGHGEBEFBCDBHAB,False +137,8.0,7.0,7.0,10.0,12.0,16.0,11.0,8.0,EEHEGHGAHFFEFEDBGDBEBBGGFGDCGFCFCGFDDFHDFHAFCFDGAAFFAEHAEDFEGFEDCEGAEFBHBCDBCHA,False +138,16.0,20.0,15.0,26.0,16.0,10.0,21.0,11.0,BCEFDBCDBAHBEFBCAHCAEBDCCDHGHHCHDDDEGBFDFGCACAEEDGADGEDBEGCEHCHBGHBEDDADDGBDGBCGBDHCFGCGGFGGAAEAADAEDGEDBEBADDADGCDGBAGBDGBHGFFBEDAEFBF,False +139,13.0,8.0,3.0,6.0,6.0,4.0,5.0,4.0,EDGABAADGAECAGAAGAACHFFHABGFBABBEDBEHBAHCABDFDEED,True +140,3.0,7.0,9.0,8.0,11.0,8.0,12.0,4.0,FGFCGCCEEDFEBFEBDACHADEBCEDFBDEHEFBEHCEDCGGBGFBEFCGGDGHDGCGGAG,False +141,7.0,6.0,3.0,11.0,10.0,4.0,8.0,7.0,EEAAECEEGHEHDFDCHCGHEAAEHBDFBDBGDBADBEHFEAFGGDHDDGBDGADG,False +142,25.0,23.0,17.0,19.0,29.0,25.0,18.0,29.0,EEBEEBHHHHBCHEFDGCDECDEDBEFHAFGBFBHFBHFCHFEDFBBFEAEGBCBAAAADAHEEFAEFDFACHHCHBEHBHHDGECFEFBEGHEGHAFHCDBCAGHEGHGDHGEGGFAAFAHEEHBFABDACHABDCDAFGFFGCFECFHBFEEDDGDBFCAHAEDDEACEAGDBGAAGAHCBHB,False +143,1.0,2.0,2.0,3.0,4.0,5.0,2.0,3.0,CFDCBDHGEEGAEDFEFFBHFH,True +144,9.0,4.0,7.0,5.0,3.0,7.0,3.0,7.0,EFAFABHACHECHGCBADBADAADGCFFAHGHDFHDCHFCBECAF,False +145,21.0,27.0,26.0,22.0,15.0,22.0,16.0,17.0,FCDFDDECEHCFGCEGDABBGHCGBBFABAEFEEFACHBGFEABEDBHCCFGAFEEFHAFECFHCEBCDBCBAHFAHFCFFCFFBFAGGAECDCCBBDDCDDCABBAGGAGBAGHCHECDACBAFHECGBGGBAGBHBACCADDDDCHHHFHHBDDBDDBDBADBF,False +146,23.0,23.0,27.0,18.0,23.0,27.0,25.0,28.0,DEGHEGFDBFGHDEACECDFDDFDBBBGCEAFHFFHFEBGEBDEBFBBFHFFEFCGFCGCHGAHBCFGAAECGEGDDGCHGAHAAHAADDADCAFBFFBHBHEGCAHCHHBEACCBBABBDBHCBDFAHAEBCEGEGCBHEHFAGCAFCACEFHEFADBCGGCGHAGHGEHEFHCAHCGHDGHCEHCEFCGFDF,False +147,19.0,22.0,21.0,22.0,15.0,18.0,18.0,18.0,ADDADEFBADAHFBBFBBCHGCGBCBHEDCCDHDDACGEGBEACEBCGCFABFHEAHFGDCDDCGFCGHEHHEHBFHDFBFFBAFAABAADACDFCEFHADGADCCECDBHDBCGBAEBAHDHHDHACFCGFGEFHEGGCGEFGBDGBGBBDE,False +148,23.0,18.0,18.0,17.0,20.0,20.0,23.0,19.0,GHBGCBDAFDAFHCBEFGACAECHHGEGFEGDEDDBCAAGFAGCGECAEFBEACEHGEHAEAFEAFBCGCCFCBBGHBAFBFCBFAEHBEHBEGAACFABGEDGHAGBCGCEBDGDDHEAHCADFFGHAHDGHDGHDGBDABHAEDDFHDFCFFHGFE,False +149,11.0,9.0,14.0,14.0,12.0,13.0,8.0,11.0,CCFCGFCDFHHHGGHEDDFHDFEEGCEAHAHCADFEBBBCBFCAHBAHEACDDCDACDADDBDDBEGBDFFCEHEFBEFEAGEGFCGFCAHA,False +150,20.0,17.0,22.0,21.0,18.0,23.0,27.0,26.0,FDDHHBGAEAABAAFAHBGFFHEHCEBEBBEDBGDCGHCGHCFFEGFEDFCDACDAEBFEDAEDHHHFGHGDHGAEFCFGBEDAADCCGFGGAAGCHCDDBDCGGFGGFGGFHGFBGBCGECHFHHACHABDFHDHCAEBBEBGCCFHEHGFHFEHFEHBCACCACGAGHDDDD,False +151,25.0,32.0,23.0,18.0,29.0,30.0,21.0,16.0,CHFAFBDBCEHGEHEEFEACEFCFHHFCAGAEGBCABCAECHDDFDFFEFFGHABFFEHBBDBGABGACGACEDCGDEBDEBCEBFDCHBADBFDAADEFBFHGAACAACHDEADHCBGCAFBFFBFFBEBBGBEEBHDBFDGDAGFEGCABEEBEHBGHBGFBGBAGFGCEGCACFDGAEBEEFCEFAFHBCE,False +152,2.0,5.0,8.0,6.0,3.0,7.0,7.0,3.0,ECBDCEGFFGHCGCGGFBDFDDADDHEBFCBCCBFCGFGAH,True +153,20.0,20.0,31.0,26.0,22.0,23.0,14.0,22.0,GBGFBFFBHCBHCBHGBEFCGFHHHHEHDCHCCDGCFFCDDHFDEDGEGCHHADHCEECFECHECDGCDGADCAGAAHEDHCFBEFEDCHFFAADEADHADCGBCFBCFEEEEBGBCCCCBCDBDHBAHDABCAGCBCFBEHDEBDCFDHFEFDAACAEDADAFGEFABFDCEDAFAB,False +154,14.0,22.0,13.0,6.0,19.0,16.0,15.0,9.0,EEBFEFCBFDAAGAHBCCBGCEEAEEAEEAEEAEGGFHBCHBCBCHBCFACFGDECBAGFFDBHBBHGGFAGBGCBEHGADBFBBGGAFCAFCEGBEGBEFBDFBHEHEFDAFB,False +155,13.0,9.0,8.0,9.0,16.0,11.0,16.0,26.0,HGHDBHECHGCDGAEGFEHDEGGHHFBHFGHBGBEFEAHEAHBFHFDHADHBCHEAHEAHDGHDHHEFFACDCEBFGGEGAEHEGHEGCCGFHGAAAHAFHAHDEBBC,False +156,21.0,23.0,28.0,17.0,32.0,20.0,26.0,33.0,AGBGFFGFGGCEFCBFGBECECGECBECAGHDHEDHCBHEEAEEBFGGHEEHAGFFGFHHCCHADABEGBHGCHGCFBHEHHEHHGFHFFHEFAEHADCEDCHAADBADHEDAFHEDDCCDCFEHBHGGHEFHEBHEBHGBCGCADAAHACBDFBGCBECBCCEHEADEGEEAFCDBHGBCGBCDFAGEAEHAHDCBBCG,False +157,3.0,5.0,10.0,12.0,6.0,7.0,9.0,8.0,CDDCFDCHDGGFGDBGDHFHHEGCCHDCADCAGBFHEGEEGCEDEFDBFDHAHGCBFCBD,False +158,27.0,19.0,22.0,22.0,21.0,22.0,30.0,32.0,AEAADDGDGHBHDGHBGHBHHBCHCAHCABEEBDBDHGFHGHHGBBAHAGFGBAGAGGAGHHCFFBHHGDHAACAGCAHDADGAFHCCHGHHCHGCFGEEDEDBECGAFEDFEDBEGBCACHFCDFGDCDCCBGCFGDFGHFAAEDHFBHFGFFEAEEHEDBECFEABGAFEEEAFDCFDAFDBCGHCGHAEHAG,False +159,6.0,10.0,10.0,5.0,6.0,6.0,5.0,10.0,HCEECDECAFABHBBFADFCGACGABHFEHCBBCBBHFHCDCEDCHGGHEGHFBHABD,False +160,18.0,20.0,20.0,17.0,21.0,19.0,20.0,20.0,FEDBECCGDCDBGDBGDGGDCDFCAHCEHAGAABACFCFFCAACHADAACEGEEGBFBHEHHBGHBACGFDFCHFCHEAEBBEDFFGCFGBEBBEHDDHABGEEEEFABHABHGEHGEHGEHBFDFDHGDHGBEGBECCFCAFHFGCCDAFAHDB,False +161,12.0,21.0,28.0,20.0,19.0,21.0,30.0,23.0,BEBCAAFGAFGBFGEEEFCCHCGHFGHGDDCCHBCGACGEHGHCEHCFCBHCBHDAHDHHDCHEABGHFGBGGCGHCGCEGFDGDDEFGEAHBGEADDCFDGBDGDCFECFCGFCHEGAFCDFCDGDFFEHFBHFCCBECHEBHCBFDBFBBGBDAEDGECGBHEBDABGGGAH,False +162,21.0,14.0,18.0,20.0,18.0,17.0,19.0,20.0,GHBEAFEGBGGHDEEDEABEBBEFECFCCABAAEAAEACBAFBHFHHAEDBCDECDAFBAFBAGEHEHGDAAHGAEDCCDHDDHGAHAFCCECAFCHHCHEGBCDCCBFFEFFGBFDDDDDGGCGDAFDGCGFHHDHHDHGFHGAGG,False +163,7.0,8.0,10.0,9.0,10.0,6.0,9.0,12.0,FBCCDDCAHADHEHHAGCGGHECHECHGBFABFADFGDHBDHDDCDHCEBFHGECEEAEFHECEBGBGGBA,False +164,2.0,1.0,4.0,3.0,2.0,6.0,3.0,7.0,CHCFEGFCGHHEABGAHDFHDFHCFHFD,True +165,27.0,21.0,24.0,26.0,31.0,11.0,22.0,21.0,CAADGACHHEAHDFHCAHCFBCFBEBHGCEFCHCGECDEABEACDDGHDAFCCDCADCAGBDGBEGBCDEHAHHAEFBEGDEFCEABBDBGAHAACAAEACBFBBFGEEHEBDEGDEGDCCDCABHEEEGCDGCDGHEGEEGEHDEGDHDAEFEGBDGADHFDGCDGBAAAAHHEEHDEBABB,False +166,7.0,16.0,7.0,13.0,4.0,10.0,9.0,15.0,BDDEDDGCAHEFHCFHCBHAGFDBDDBDDGFFBAHAHHFGBBDFBDHACHBCEBFEHHGHHBADBCFBHDGABGHBGFBGC,False +167,15.0,15.0,9.0,10.0,9.0,15.0,18.0,14.0,GGABCADCGHHGEHBDHCDHDEGGGFGGAGAABECBCFBEABEBEGAACBBFEAFBHFBHFBGFCAFGHFGHDGCBCEHFFGBFEDFBDAHHAHHGFDDAGDAFA,False +168,21.0,14.0,14.0,15.0,25.0,21.0,7.0,17.0,FDABDAHCHHFDACBGCBGCHFAACGEEBCBFABAEEAEEAFEADDHFAHFEHAHHCEHEFDGFEHFEGFDFHCCAEAAEADBHCFHEBBCFACFDEADFAECAEBBEDBEGFDAFEFDHFDHFEEBCEBGEHD,False +169,11.0,25.0,11.0,15.0,12.0,14.0,16.0,19.0,CDFBBCHGCEBDBACBDCGHFHHFHDFHBEGBEDBFDAFCAHBACFAGGAGEAGBAGBHBBDEBHGHHGHFEABDHFCBECBFDFEGHDFHBFHAEHECHBHBGDBGBCEBABDEGDGGDFDB,False +170,11.0,10.0,15.0,10.0,14.0,10.0,14.0,13.0,EEGCEHAGADCDEADGBDBHDFGDHCDFCDHBAEAHEHCGFCGFCEFDHGHHGHFGCAACHACHAEGEBDCFGCFBBFBBEEBGACGFHEECEBCGA,False +171,15.0,14.0,17.0,21.0,14.0,11.0,20.0,12.0,CBGBFHBCEACEAGAACBDBBDCDDCDDAGGAFGFGDHADEDDEFFAFFCBFCBFCFAHDDBGGGEADHHBHBBDEEGEEGCAGCDCCGCEBHHCGGCDBCHHEAHGAEGHEFADGDGEDGDDA,False +172,6.0,4.0,6.0,6.0,3.0,10.0,5.0,4.0,GBFGHFGDEDFCDAGDHCDACBECDECAHAFFAFBCBHAFFGFF,False +173,2.0,0.0,4.0,3.0,0.0,0.0,1.0,0.0,DDGDCCACCA,True +174,3.0,6.0,8.0,12.0,9.0,8.0,4.0,7.0,FGBDDHHDCFABFABCBCCHDEHEFAEFEBFEDDHDBCDECFHCFGEGGEDDCDDHE,False +175,4.0,4.0,3.0,0.0,0.0,0.0,2.0,1.0,GACGABHBBAABCC,True +176,4.0,2.0,4.0,1.0,2.0,1.0,1.0,1.0,HCDACAAEABCFBCEG,True +177,22.0,20.0,10.0,18.0,13.0,13.0,19.0,20.0,CBHCGHGEHEEADBHGAEGFEGFBAEBCFAFEGHCBABFADFDDCHBCHDHAGGADBAHFEEFHBBHBGDDDHDGHGFHAFAAEGBBDAADHGBEGBAGBADBAHCHHADHDGGDFGDFDCABCABCABEFHEGA,False +178,22.0,19.0,25.0,28.0,26.0,27.0,22.0,13.0,CCCCCCCDCAGHEHCGDGHCADEADBADHFDGGGBDACFHCFHDGBDGDAGDCDDBBCEBFBAABDCDDEDFEFEECDEBAFBDDBFEHEEAEFGEFGEAGBFFBFFBCFCFDGHEFCAFCAHEEGEEBEAHDGEFBFHDFEDCDHCDACGGBGCAGDAFAAFEAFHDFEGECBBGFAEFAG,False +179,3.0,7.0,11.0,8.0,19.0,13.0,15.0,4.0,BEEBAEFHEBGCBCEBFHFDECDCGHGFEGEEBECGFCGFDGDDGFAFFAEGCEFCEFDECEEGDEGCGGFGEBDHCEGF,True +180,23.0,18.0,16.0,19.0,17.0,9.0,16.0,16.0,DACDHCDECEHCBACDAFDAFABCEDHDGHBCFFABCDDFDDHCAHBAEDABHABDGDFCBECAEAAHGEFABFGBGBHABHCEAEGAEGEHGFHEAAEAHGCEGCHGAEGCBGCDGDEGHHADBAGBEDBDBB,False +181,7.0,4.0,3.0,4.0,1.0,4.0,0.0,2.0,CDDAFABHAECADFHCFABFABDAB,True +182,7.0,17.0,14.0,12.0,11.0,8.0,17.0,16.0,ECEECHEGDCFDCFDCEDBBGBGECGBHGFFGCBHEBHABAGBHFBHDGHBECBEHHGCGCCGCFGHABADDDHGDHEBHBCGGFFACHAEADBHDGHBGDB,False +183,18.0,19.0,14.0,22.0,20.0,25.0,20.0,18.0,FBAHCEHGHHGAEDEDDHDHGFACFDBFGCCBHGHHGBHGECBHFDEFBEBHECHFGDFHDEHAGGEGDBGAADFADAADGADGHFFEGCABDGFDBDECDFAFAEFCEFCADGFDFFBFFBHFCECGEBGEBHEADBBDFBCFDCFAAEGBEABE,False +184,9.0,17.0,14.0,14.0,12.0,19.0,15.0,10.0,DBDDHCBBBBGGFEBFEAFGCFDCADCDFEFGHFDHBDCECCFDCAEBEDHFDCBDGBACACGECFEHDBACBFFBFFGGDEGHHGCHFBHFBEFAEAABGFBGEGGFGH,False +185,5.0,15.0,12.0,28.0,11.0,16.0,11.0,13.0,FBEBDDHEDCEGFGGBGEBDBBHCDGDDHBDHECBDFBDEGHEFHEFEDCDHGDADDABHABDCBDBFDHGDFDCGHCGDCHHGDADDEDDAFDFFHFFECDCBBFFCFFC,False +186,3.0,2.0,0.0,4.0,2.0,3.0,6.0,2.0,EGADGADADBGHFGBDGHFGEF,True +187,7.0,12.0,9.0,16.0,4.0,16.0,12.0,10.0,BDFDFFBBBEBBFCHHCHHFFEGDADDFDFHAFDAFBBGDBGDBDDGCDFFDGDGCBCADGEHGDHCCHACABHAHGCFGFFGEFG,False +188,9.0,14.0,12.0,11.0,9.0,6.0,5.0,4.0,DFBEFDCDCBAFBADEFDEGCEBCGFCECHDBADBADBEEBABGHBACBACBECGACBBCADDHFGHECD,False +189,15.0,22.0,16.0,23.0,11.0,18.0,13.0,25.0,CHGBHDEHBEHDGCDFHFHHCHHGHEDDBGHACHECHBHGDHDCHDEAGEABFAEFACBBDDBDBADACDABFAHDABACBHHDHCAHFFBBDBGAFGFFBBABCGEEFEDCCDCBDBFDBFEFGGFHHFHDCADBDGFCGFH,False +190,23.0,11.0,18.0,25.0,19.0,12.0,19.0,38.0,DEHHAGHADHGCHACEDCAGEGFDADHADHDDGEEEEHFHGCAGEDDFHHEHHDHDGBDADHECEEGAFHDBHGBHGBDAHAEHABHBBFDDCDAHHGHHEHFGHCHDDECBFCADCGDCGHCGHGAHGABFHFHHFHHEHHBBAEDAEDFCCECAAGACCACAF,False +191,5.0,6.0,1.0,7.0,12.0,13.0,5.0,13.0,HEEFEHAEHFFHFGDFEDGEGAFGFHGEHDBHAFHFFEAHEBEBDFADBHHHEHBECFDBFD,True +192,14.0,9.0,19.0,16.0,17.0,13.0,14.0,12.0,FBCCBDDFFDHDDHGEFGEFGFHGFBDFCEEHACCAEEDBFDEDCHFCBAEFCGGAHFADGAHEHHAHBACBCEDEEDCCDCGACGCCGCEGDECAECAFGABGBHGDDEAEHA,False +193,13.0,11.0,10.0,13.0,18.0,18.0,16.0,24.0,BFHBGDBGHEFHEGEEGAAFHDFECFEAHEAHDFHCHHEHFAGEGCCHHEDHEDCCDAGGAGGBDCBDAFHFFAFDAFHGCHGCFGHGHHCHDBHBFFADFEDEBHGGFBADHAEEEHEEBFB,False +194,4.0,3.0,4.0,0.0,0.0,3.0,1.0,3.0,HCHBAHBAGFABCAFCFC,True +195,5.0,5.0,1.0,2.0,4.0,4.0,7.0,2.0,EFBGHBGABGADGABHAGDBECGAFGFFEE,True +196,16.0,12.0,12.0,7.0,4.0,7.0,9.0,12.0,ACGACAHFFCEACGGDEADCAGCFHBFBEFDHDBHAAAAGHBBHCBHGBAGBACBDCBHCBACDECHHAGHFHBGADFA,False +197,11.0,6.0,8.0,7.0,7.0,10.0,12.0,14.0,GHFFHACEECGEGGDBGBBFAGFGCHGHDGAEGCCBHCBHAFHAHDAFGAFADCADHAHHBCDFGEAHEHHFDEF,False +198,21.0,16.0,17.0,15.0,22.0,24.0,21.0,20.0,AEFABCDCDABGHHEHDFBBFCAGGAEFCGGCGABGACGHHGDGBDBBCFACBDFHHEHFCHFCECHFCHGEHGBFFECFBHFGHFEDFDCFCEAEEADDGDEGFEGFABFHBFAEHEDDADAAGAACEACBHEBFEDFAAAGGEGGBHEEHFEHF,False +199,3.0,4.0,1.0,2.0,7.0,5.0,9.0,5.0,HFFFEGEEGAHGBHGAHDADCBGGEEGEGBEGBFFH,True +200,27.0,17.0,26.0,18.0,16.0,17.0,15.0,13.0,BDEBEEBCBBCDFCHCCABDEGCGACGACACFGDDGAACBACEEDBDDCCCHCDFAHBGEBCHGGFCGHHHABHBGAEHCBGCDAEDFEFBEAHEAFFGDFHDHHDFDBFEBAAGAAGAGFCBCCEACEACECFAFAAFAADCFDAFDA,False +201,14.0,18.0,22.0,18.0,23.0,25.0,18.0,25.0,EHGEHCBHCHHAEHDEHDEAEBCEBCEGFAHFAHCEHBFHBHHBHEBCFADGHFGCFBAFBDHCHCEHADGBDFBFFBHBGGEFFFDFEBCDFDHCDHBECDEHECBECEFAGFCGCAGEHGEDEFHFCGCCDACAAFDAHDFFDBGDGAFGCBCDFEGFGGE,False +202,6.0,4.0,6.0,6.0,4.0,7.0,2.0,1.0,BADGAEAACFACGEFBACCEFCEFBDHDDFDBFDCF,True +203,4.0,8.0,7.0,5.0,6.0,6.0,6.0,7.0,EHAECAEHBEHBFHBCDBAEFEGGCFGDGHHACBBCGBDHCDFCDFGBF,False +204,6.0,15.0,10.0,9.0,18.0,10.0,16.0,17.0,EHHEDFBDFGDGEDGHFEEDDBGFADFCBHCBHFEEFAECGHHGBCEDCEHFACGHEGHEGCBGHBCHBEFFEHADBAGBGHCHEEBEAGEBGBHGBHCBG,False +205,6.0,8.0,4.0,6.0,11.0,10.0,4.0,7.0,BDFBFFCHFBADBGFCGCCEEAAHFAHFGFEEFBEAHEBDEBDFHDHEGEEBEHDA,False +206,7.0,11.0,7.0,14.0,12.0,11.0,11.0,15.0,DFFHFBABAHBEHBEHDHGCHFDFAGCGHEBADHGDHCEHCEFCEFGFFGHGCDAADGBBGDBGEBFEDHABHDBCDHHEFDEGDEDE,False +207,14.0,19.0,19.0,16.0,15.0,16.0,25.0,15.0,BHBBDBDDGDAHEGEGGECDCCBCDAEBGEDGHDCHFEHACACCEDCGFGFEGDGGAGGAGGHFBEGCEGCEBCAFGHEBHDAEGAFHHCADFBBFBFFDHFCHFBBGBBCBACGFDAFHBCGFCGEDGADEAHFCHBG,False +208,14.0,24.0,23.0,25.0,20.0,23.0,13.0,19.0,CGFHBECCCACGAFFHDFHDAHCCFBDFBCCBGFDAHDABGABGHBFHCDGDDHBHEBCEDEFFEFFEFFCDDGGECDEFDADDHEACEAHEAEEBFBFGBDBBFCBDCFDGFHBBDBCGCDAHDCCDHCEEFEGGECBBABDCBDEFEHHEHHBHBADFA,False +209,5.0,7.0,7.0,12.0,11.0,5.0,6.0,4.0,BEEGAGCAHCFDCAHCEFCAFGGDDEDCBDBEFBEDDADDHDDBBDBEEEGCEGHEF,False +210,21.0,21.0,29.0,26.0,25.0,22.0,25.0,25.0,HGGGCBGCBGFDHCEGCBADBADBDFHCBHDBEBBEHBEFBCABCACCFCEFHAFHGFGDDGDDHHDEDDHCBEDDEDCBGGFAADADGACHAFDBEBEECDECEFGGHECHEFHEBHEDGCDCABCEFGEGHFGHEECDBHDFDFGCAEAGEAHCHFAHDGHACFACGHHGDHGCAAEFAFBCBECGFCFFCA,False +211,25.0,20.0,15.0,18.0,16.0,31.0,22.0,17.0,GDHFDBEDFEFGAHDFFDBECFDAFDBFGBDAEGAEGFDCFDCEACBAFHGHHFBFFBHHEAFBAFDCFBGAGGACBACFCEACEACHHGDHGCGFHGHAGABGBGDFHHFCACEBHEDDAFDAGCADBEGBFGBFEFFEAFGCFBHFEHGABAABAEGAFDFB,False +212,11.0,12.0,15.0,21.0,14.0,13.0,13.0,22.0,FDHBAHAHFDBFDFCHHEFHDFAGBADBADCHDFFDABDHCDHCGAGFHDDHEEHBHHEHBCBGDGCDCDECDEGEBHEHHGHDFBCFDAGCAGCACCEFCDBGEBGEDEFGHCGHEDHEA,False +213,26.0,25.0,22.0,24.0,22.0,21.0,23.0,28.0,DGGABBFFGEFGHFBHBHFAGAHGECGEBAACCADCHDBGDHCDFEDCCCFBFAHDEGGBGECFEABGHDEADGBGGFDEFAABAAHAAHCAHGFHBFABFAEHHCHHCFBEEDEEFEGDEHDHHDHCBEABAGGAFGDFDCBCHBCHBHEBAAGCADCHFCFDBBDBCDECHACHDBEDHEFGADGHDBE,False +214,17.0,18.0,21.0,25.0,26.0,17.0,17.0,17.0,FEFAEAHHABBGBGGCDGDEEDAEBGFHHCADDHDDEDDEAFECGGAGGEBGBACEEDEEDHDDHGBHEBCBHADFEDEGGCDDBDCFCHFEFAHFHDBHDBHAGCFEFFEBEEBEEDGEACFABBCBFDBFHFECGHCGACDCCDCCECFHAACADC,False +215,3.0,8.0,12.0,3.0,11.0,1.0,8.0,8.0,ECHEGGEHEEBCEHGGHBAADGCHBCBBCHBCHBCEDFEGHEDCGCCECEBCGA,True +216,3.0,7.0,2.0,4.0,7.0,5.0,4.0,9.0,EEBACHABHEFDEHHEBHAFHFCHEDGEBBDFBHGBHGFDG,True +217,24.0,19.0,23.0,32.0,19.0,19.0,18.0,19.0,BDFHFFHEAGCGGEHGAHGADAEDAEGACABCBFDEDDEHDGDDEDDGCDGAFBBEBHFBDEADCDDCHBCEAHDBHCBHCACBGCGFCGFCGDHFABCACCABHEEHDGBFFDFFBHADDDCAAHDAEFEEFBDFADGADHADFGDCGCCBECADAHHCFDCGBEFEEDHBA,False +218,15.0,9.0,15.0,14.0,9.0,15.0,10.0,14.0,EDDHBDCEDAHHCDHCDEFECFDDBDEGDCAFCAGCHCFHBFBDFCABCEGEEHHGFHAFCABHABDAFAHBHHGFCGFHGBAAFDAFAAFEDFAGGCCGC,False +219,24.0,26.0,20.0,28.0,17.0,21.0,17.0,23.0,FBGGAGHAGHGGBGGFFDAFDHDCFBFFHFDHDDHFDHFHCFGDHBEFCEACHFEHCBADHDBADCEBCDDAGDAFDAEDEHCAFDAFDFBBAGBGHBCHAFECHDCEBBEABGFHEBHDGCEFCBACBACBCCBHBFGDADAAHAHBGDBDEBGECEDHDAEBAEBAEHADCDBC,False +220,10.0,6.0,12.0,8.0,3.0,8.0,5.0,9.0,DEDDFFBCFCCAGBFHBACAACAHFAHBEGGAGCDCCDFCDFCAHCACDHEHHABGDBHFH,False +221,18.0,20.0,25.0,20.0,16.0,11.0,30.0,25.0,BFFBEGBGFBGHBEFEDHBDCAAHAGHFGDADCBDBBDECAEBAHGHGABBHHBGCGECEECADDDGHDGBBGBCGHHGCHCCHCFHGGHAAHAHGAHGEHGDHBEGFHFAHGADFEGBDHFDGCDGCFGAGCCGACGHEGDCCCABCECGEHDEDDCCECADCB,False +222,19.0,19.0,21.0,28.0,17.0,28.0,23.0,16.0,FFFFGGBAGBFCDFCBFDGDDEDDFDEFCHDCHACAAFFDGFHCFBCDGEGEECCCBBAHHDEHDECFGGGDDGDDGDDCBACBABHCDCFDCEBEGBCHEFHGBHABAGFGFADHAGFAEFHEBBFBEFCGFHAFGADGAFHBCABDEDDCHFEHFEGAEDCGDFADBAG,False +223,23.0,19.0,28.0,13.0,18.0,28.0,23.0,33.0,GHBCHBGHEHEAHDHGDCFBHGCHGCFGCBGBGCDHEFAGHEGAABBHECFCFGDEHCEHAFCADAGDFGDHACBACHACHCHFBEFCFGCHHHHCHBCBEDBFHBEHBAGEACHACFAGGHGDHFFAFEADEAHFAHCCHEFGEFBFCBHDFGFFGAFDACDECECBEBFHBAGCHGCAFFAFF,False +224,3.0,2.0,2.0,3.0,1.0,3.0,0.0,0.0,DAADFBDFBCACFE,True +225,18.0,28.0,26.0,15.0,16.0,22.0,28.0,24.0,CCBGHAGAEGAFGBHGCHGBBBHBBHCBDDBFDFGECEECAGHEBBGBAGBFGCHCCDGCDHEAGCBBFBBFCBGGAGBDGHGGHGHHFHDCEDAFGHBGABHBEAACGCCHCCHBHHFFFFGCFHCFEDACFGEFCAAGDCDDHDBAABFACDABEGCEGFEHFEFCEDBFHBEHF,False +226,0.0,1.0,4.0,5.0,1.0,5.0,5.0,2.0,DBGCFGDHGFCGDHGEFCFDCFD,True +227,9.0,11.0,5.0,9.0,13.0,8.0,7.0,11.0,DGHBGEBGHACBAFHAFHFHDDHCGEAGEDEEBEAGFDFBDFBHFHCDHCEEAFBABBEEBEBDHADHGEEAC,False +228,3.0,5.0,4.0,5.0,8.0,4.0,5.0,8.0,DCEDEHGEHGFCEFGBDHBDCBDHFFHEAHEACGBGHAEHEB,False +229,5.0,2.0,1.0,1.0,0.0,2.0,0.0,0.0,ABABFACFADA,True +230,17.0,15.0,18.0,10.0,25.0,10.0,12.0,11.0,ECCHCABEAEAABAEBGEBCEBGAAGBBDFHDEHDEHCHHCHCEHEEHCGBAFCDEEFGEGGCFDEFBBADBEEFHEAHECGFCDAAAFBBCCCACBGGBAEDDEGDECCEFAEFAEG,False +231,31.0,18.0,29.0,27.0,23.0,14.0,25.0,29.0,DGBAGHGHDGCGACBADBDDEADFCHGDBFEBHEBHEFHFCDFCDACFGHDDDDDCGCEAEEADCBDBGGHCAACAEDACHEHHAHDDFDEHCEHCECEHHEAFEABCGEGABHEDHEFAGCGGCGACDAGDACAAHACBBCDACAACHCDHGAHGFBDAACEACECFEHGGHBGHBCFFGDBGHBEFEHHAHBAG,False +232,9.0,27.0,30.0,27.0,17.0,16.0,18.0,20.0,HDBHDCCCHHCHECBBCGCEDCHCADGDBBEBGEGGFDFDDGDBBFHCEEDFFFHFHHDGCEBCABABDEHDHCDHFDHFDHBDHGGEECBEHBDFDDBCDCCBCCGCAHDBBBBFBEHBEGBEDDGAAHCBECBCCBCFFEDFEDCCGBAGACGDCAFCGFGG,False +233,13.0,14.0,9.0,12.0,10.0,11.0,7.0,12.0,CACBADGHDGHDFHDFHDEEDGEBBEDHACHABBFCFAEHACFDCEAHEABFFBFEAAEBCHDGBDBBGCBFEAFGDCDHHABHABGF,False +234,27.0,12.0,19.0,20.0,14.0,11.0,16.0,19.0,DCEACEBHDGHAGFBGABGABGABCHFEADDADAHDHDGBFAECCBCHHFADFEFAHDAEDCHCHADBFDCGDCHECGAAAAGBAEEHGCCGEAGEFCDFDGGCGACHCEHCEHDEHBCADAADADDFHGAHBAHBAF,False +235,10.0,14.0,16.0,10.0,22.0,13.0,14.0,12.0,BCEFFEFBBGBBGEDGEABFACCDCCDHEGHCBDGHEEEFAGBHGBEEHEEHDEFDEFCECDECHGGAGFFEDGHBECBHCGFEAAEAHGBHGBHEBAFACCEDCACFDCF,False +236,7.0,11.0,9.0,8.0,13.0,11.0,4.0,12.0,AEBEHFHFFGFHBFHFAHBHHBHFEFABBEBAEFCEACHHDGDEGABCCBCEBDEDCEACFHCFDCHDEEDBGDE,False +237,23.0,30.0,14.0,18.0,17.0,26.0,17.0,30.0,DGDDFCEFCGCBBHACAFCEEEEAADADEHFABBADHADHFDBFHHFHDFDAFEADBADCAFAFBEBBEBBCBBCFBEFBGFBHBBFFHFAHABHEFHBFHEGHAAHBAGBGFHAFABEGEGGDCGBHBCHGHFGHGHHCDEFFHCBHBBHGEHGDHFDHCDBDAHGHBEAACFG,False +238,19.0,27.0,27.0,14.0,19.0,23.0,28.0,21.0,CCCACCFBHFGEBABBGFFGBCHBFAAFBAHCAHCBGABGADDABDAFDBCGECFEHBCHGHHGHEGDEBFBBCGBGHBGFBCCBDGDCHACHADFADEHDEHEGADGAFBFGBEGHFHEADFCCGCCGFCEFGHFEFBCDBGHHECGBCFAEBBCDGAGCAGFFEHGEGFEGBECHE,False +239,12.0,6.0,10.0,11.0,16.0,6.0,12.0,10.0,DBDGGDGCDECGHCHEAHGDEFEEFEBBHABCCDACGFEGHECAFAEDAHAGCBGAHGAGFABFDEEDGEHEECEDCEAHDAH,False +240,12.0,11.0,10.0,12.0,15.0,7.0,12.0,8.0,EHCEBGEBCADCDFCEGBEBCEBHDGAAGDGHDCFDEEGBEFEEFGEHGHBEABEAFCFHCGHCBADAADADGAEBBDDHDFGACGA,False +241,24.0,20.0,23.0,18.0,18.0,16.0,33.0,12.0,DCADHACHFFHADCCDEEDCEDCFAAFGBCGACGAGGACHBBDBCCBEFBGCDGHFECABCACGAEFAECBFFFHGCAECAGHEHBFHBAGEFGECGHBABCADDGGDGGDGGCGCFFHGGEAGEGEEBBEGAGFFGDGGBGDBGDCGHAAABGEBEBDDBDAA,False +242,2.0,5.0,2.0,2.0,7.0,2.0,2.0,4.0,EHCHBDECDEGFEAHHABBEBFEBGE,True +243,5.0,8.0,9.0,5.0,11.0,13.0,13.0,9.0,ECEEGBGFFHFBEFHFDBGDBGFHFFHGHCGHEACEABBFEEEEGCGGCFBCDCCEHCDHGAFGABGHFGAFD,False +244,8.0,13.0,8.0,11.0,10.0,14.0,17.0,10.0,EGDHGCEDHEAHFBCGBAABGEDAEDAEGGDDFDCFGCEGCGFADFCFEBBCBFDGFAGFEDFBGFGHBBHEDHGGHBAFBFHCFHGBHGB,False +245,10.0,16.0,19.0,10.0,13.0,11.0,21.0,15.0,BEEBGHAGHCCFEDFGFHBHHDFDDHCFAGFAHABFABGAFAACBECGGGHGCAGCHCEFGEHBEHBGFGEFCHDHHDEBCABDGBGGCGGCBGEBGDCCCCDCBDEBGEBECCH,False +246,9.0,13.0,8.0,9.0,4.0,11.0,15.0,3.0,BDDBDDBAGAEGABGEDFCBCCFCDABHCBGDGGEGCEFAGBAFBGGBGGBDFFAFBCGDHGHFFCFAGFAB,False +247,24.0,29.0,19.0,27.0,21.0,19.0,25.0,36.0,AGGDCEDBEDGADBCBEDBHDFHDBEFHEFEEGEGDEABEFHDBHBHHFFAFBGGHCFFEAFDABEAFCHDCABBBCBEEBFBGAGHBGHCABCAFHDGHCHHCDGADHADGFHGFCGDBHBCHBDAEGHHGHHAHCAHDDBGHBGCEAHGADDHDECGEHHEDEGFEDABHABHABCABDABDACHGCBGDHHFHFFGC,False +248,23.0,15.0,19.0,20.0,20.0,17.0,12.0,20.0,AEDAEDAEFADFAHFAHEEHBBCBBDBCAFAAGCCGACEHEADFHDFCDAHGBEFFEFDAFGACGECEHHGADGBCAFCGCHDDDGCFFDBCHECFEHEABEABDCBHFDHECAFDABDAGEBGHGEHDBADBADCHCHHCFHEEH,False +249,5.0,8.0,8.0,6.0,8.0,12.0,5.0,4.0,DDADDFEDFHACECHGGHCDBBFFBEEBGEBCECCGBEAAGAEBFCFFHFFBFFCF,False +250,9.0,9.0,5.0,9.0,9.0,5.0,9.0,6.0,EBGEGDECAEBBGBFDBACGCBBCBBFDADDACDGEDGHDHDAHEFHFGAEGHFGAAEHAE,False +251,3.0,4.0,6.0,7.0,2.0,6.0,5.0,5.0,FCHFEBDGHDHADFGGFGFFEDBCCBCCHGCHDBDDAA,False +252,23.0,16.0,22.0,22.0,17.0,24.0,15.0,22.0,GDGADAHGFBBFBCHBDHBDCCDHEGADCHBBDFHCGGCEFBECHECEACFDBADEACEDFFDFFDFCEFCGFCHFGAFADGAFHAEABFDEDHHBAAAAHGABGDBFEHFHHFCHDCEAEEAEDCFFAFHCHHADHACHAEDABDCCGGCGFCBFGEHBD,False +253,28.0,21.0,24.0,17.0,16.0,23.0,19.0,22.0,HBGAFCHGAFDHGAHGHGDDGADGECAACFACBDGFCBAHBHDBFDEFABFACAEGFHGBDGBFHDFHCGBAGCABEGHEFHECCEAEHADHFDCCDCCEAFBDDBFHHFGHFCHCDHCFFCBAEFAEFEEAAEBFCBAABAAHEABBAFBGCBGCBDFGAGCCDECAHH,False +254,22.0,21.0,35.0,22.0,18.0,16.0,18.0,17.0,CGFCBBCBBCFBDHEGBFDEHCCAECAHAFDEEDAEHAEBCHFHBFHCHBGEACCCCDCABFABCDBDHCGCCGDCDDADDGGEHFEGCCBCBAFDEFDAADFAGGHECHECHECHAHGCFBBBBAGGEDBFDAFDCEDCEDCADCBHEFCAGCAGCBGFDACAACGGH,False +255,16.0,23.0,16.0,16.0,20.0,17.0,25.0,22.0,FBDCDGFHBEHADAEBABHAGDEEDGEAABDDEEFEEDBCGGDHHDHGDABBCBBCDHCDBGDBGCHGHAGFECEEBEHFGDFACHGHHGBHCEHCECABHADHACFBBAEFCEHAGHGEHGFHGFGGFGBFBFCBGCFGEFGEHBBGFCAFGAB,False +256,4.0,5.0,1.0,1.0,3.0,4.0,5.0,7.0,BHFAGFAFHABDAEHHGHHGEGBEGBCBHF,True +257,15.0,16.0,15.0,21.0,14.0,16.0,23.0,29.0,BBAHCCDBGFHGFGFFCFGCGHCGHDGAGHDCHDEABEBGGFDDFHDHHGHBAHDGCAGBGEBHBCHGEFGEHGEBFECHEDGEHBAHBEHDACDHHHBCHBCHAFHDCHAHGAGGDDBDDEACBAEEAHDDFFHGFHFFDAEDACDFG,False +258,25.0,18.0,28.0,20.0,16.0,20.0,26.0,30.0,GBDGBHAEEAHBAHBCHCCHCEBCECDEAAFHHCGGCFFDFBAGBHGFHDAHBACCADCAECAFFAFFGGEGCEACECCFCBEAAGFCFFGGHCDECBGHBHACAAFDGHDCHDCFDHFEHFDGDGHDCHAEADGGEADCHDHBGBDGAGGFFHHFHAGHCHHCDBGHBEHDEHGABBADBCG,False +259,10.0,4.0,2.0,8.0,6.0,7.0,4.0,6.0,BFAHHADDBDEBDAHFACEADEFDEHDGAGFDGFAEFBGFEAACHAH,False +260,17.0,18.0,20.0,22.0,23.0,26.0,23.0,18.0,CGCHEEDEBDHDGEGFEFFCAHGBHBEHBACAAFAFFDBFDCFAEFADFAEGBBHADAGGHFGCCGCGFBDFEEEEADHGDCEDFGDEBDHBGHBFFCAFCECGEDADDBHGBECFEBFEDFDDEGDHCAHCFFGFFGAHCDHADCBECBHHBHCGFGGABGCEGFE,False +261,27.0,24.0,20.0,19.0,30.0,32.0,21.0,26.0,GEHGECEEBEDACCACGBFGFCDBHEFEEFGEFBFACFACFAFFAGDACBAGDEBABFAEDAGHAHBAECAFDFEEBBBFEBDEFCHFHBFHFEHDGHBGHCCFDDAADEAEECGGHGFECFEDFEAFACHACEFBEFHHBHHFEAFHBFBBFBHFCAGHHFHHGHDCHDCHFGAGDDGCAGDEEAGEBEDAGHADBBB,False +262,24.0,26.0,23.0,23.0,21.0,23.0,28.0,24.0,CFDHHBBHEEHEHHEFHBDAADAFDBCDHDDFGAFCACEADGBEGCGCHEAHGADGABGADCFFBFEDDAFDCFHBBCFBGDGCHECBEBBCABDAECAHAHHAHEBHDHHFAHGEBEHFAAGBAGBGGCAFAFBAFBDCDCCDGGDGBHBBCBGFGEEGECGEHECDFCBFGBDGCACEFGEGGFHGFDGF,False +263,0.0,1.0,9.0,1.0,3.0,4.0,6.0,1.0,CHCCEFCGGBGFDGEGCECCFCFGC,True +264,6.0,5.0,5.0,2.0,0.0,4.0,6.0,0.0,CCAGBBGDBGDBACACGAGGFFFAFBAC,True +265,4.0,10.0,10.0,7.0,1.0,8.0,4.0,4.0,BEFBDFGDFABCABCHFCDGBHBCAFCAFDBDBGGBDFCCBCFHCDHC,True +266,22.0,29.0,31.0,16.0,20.0,28.0,16.0,14.0,EHAHCBHCBECFGBBCHEEBAFBHHAFGBFDBFCBFCBFCBFCGFGECBBGFCEFBEFDEDDGFCFCAGCAFCEGAAGAACDCFGAFGAFHBGABDAGAHCAECABBBCFBCDEAAEBFBBFCCFCCFABFDDFBEHBFGEDBEDEHAECBGCFHCDECACCDEFDADEHCGDBHH,False +267,19.0,18.0,7.0,10.0,13.0,13.0,13.0,11.0,HAHCGEBDCBCBBEGHFGBCGAAGBGGFDGCAEADBAHBFEFFEAGEHCHHBAHAADEFGEAGFFEFAEFCBAABAABEAFGAEGDEDBBABBFBHHDDHDBFD,False +268,17.0,10.0,10.0,7.0,8.0,5.0,14.0,9.0,DCADHDGHAGBAEHECHCGADHCGAEGBEGAEGAEGACAHGHDCBGHBGFBCAAAACBBEEBGBCFCAFDAFDHFGABGA,False +269,1.0,3.0,0.0,1.0,3.0,4.0,3.0,1.0,GHGGEBEFBFABFEDF,True +270,23.0,19.0,18.0,18.0,15.0,13.0,11.0,15.0,AHDAFCAECAFBHBCEFDEFCEFEDAADBADCDDFDAFGEHGEAGHADBBEACFGBDHADGCCABHHGHFBEDGHFEACEFCBAGAAEABEABGABHBEABGABFCBACGDDHFCHBCHBHHCEDCDDCDBC,False +271,7.0,9.0,4.0,6.0,4.0,10.0,14.0,6.0,GDDGADGAHAAHABDGFFFECFBHBEGEGHEGDCABGGFFHFFHFBGABGDBGCBGFGCB,False +272,9.0,5.0,1.0,2.0,6.0,2.0,1.0,1.0,EDAEAFECFGHAABAEDEBBEBAABAA,True +273,6.0,7.0,5.0,6.0,3.0,4.0,5.0,6.0,DBGDAGHAGECGFBHFBGDDFEDFHCBBEHHCAHBACBACAD,False +274,13.0,30.0,20.0,14.0,22.0,14.0,15.0,16.0,HBGBBDCBAHEFEBDBCABCGFGEHGECGCDECDBFDECGHBFHACDCBBHEHGGHFGBBBBHBBHBBGBEABHDBGDEGEFDECCFHEBHEHGEFCFBCFCDABAAHEECEECEDCEDGEBFEBAABGABCBCAAFDAFDHFC,False +275,5.0,8.0,10.0,12.0,2.0,10.0,10.0,5.0,HGDDCDFCDBGFCGDBGEAFACFDBDDBHDBCDCCFGCHGDFGCFDABHGBAGCGFABFEHF,True +276,5.0,1.0,0.0,3.0,1.0,2.0,0.0,3.0,BDDHFAHAAHAFEAD,True +277,24.0,23.0,18.0,24.0,16.0,33.0,19.0,28.0,ADCABCHCAHCAHEADEAHBGBCGFGFFGAFBDFGFBGDEGDGHHGHHACDDGFFAFFBFFEFADHDDADDFFAFGBFBBFHFCHBDADEAHECEDFDGFDFFDCBBHDAHBBHCEGEBHHBFFCCHHHHCHBBHDHAGCAGEDEHDGHDAFAFBBFABFAEAAGABGFEHCCBCHECFEDFGFE,False +278,12.0,29.0,23.0,26.0,19.0,18.0,23.0,13.0,BEBBEHBCAFAHEDDCDBBDBBDAFFAFCADCGGBGGCGHCFECEBDECGEHGEADBFDHFDGCDGCBCCHDBEABDCBDEBEEBDCGECBDHBEHEAGAFGHFHEFBBDBGEBFHGGHFGFDGCDGDDCFFFDFECCGCGGFBDBAACHEDBDDBGCAGBBC,False +279,16.0,11.0,17.0,16.0,19.0,22.0,19.0,14.0,GFAAFDCCEGCHGBEGDABFBDFEFEEBEBGFCGHHHFHAFDADEAHACBFCDFHFGCDACDFCGFEDFEGADGAFCEHCAHBBHEGCDDHDCAFCAFGEEGEEFBEFEHAHFDEFDBGDBGAFCAGCGGCGHE,False +280,10.0,14.0,13.0,11.0,22.0,14.0,17.0,12.0,EHCECEHBFGCGGCAHCDGCGGEDBBBFHCFBFBBFGHGHFABEAEGACGACBFDBCEECDEBFEBDGHDEBEGGECGEHGEDEEHFEHFEGFAADGADEHDAFDHFEEFCBA,False +281,32.0,31.0,18.0,18.0,36.0,28.0,25.0,12.0,GAHFABEGCGAEFADGADFABCADAEBAEFEHFGBGCBHDAHAABBBECFEAEEFEEFEDAEBAECADCDDBBBCBBEDBFAAFHEEGFCGEEGEFGEFAFDABCABDAFGFBGFEGBEACGGHFGAFHBBDEEEGGBHGFFAFFGEFGEBGDCHCHGBBGABEABEFEDADCEEFDCDHCDBGABAACAHCEFCEFBEB,False +282,19.0,24.0,17.0,28.0,20.0,14.0,18.0,11.0,CEGDBCDFGFGCADCEEGFABEDBDBBDEFDEADBGBEGBACDDFDHFBHGGCGAEGHEGHECDDGDFGEFABAEEHDFBDFBEEBHCDCCEHHDCGDBHDFDDADDEEDBBBBABHAHDABAAGADBCFBCBECDAGECGACGACFABFA,False +283,26.0,21.0,30.0,21.0,22.0,23.0,22.0,14.0,ABEAFHABHEFEEFBHDAHFBHFBAFBCBGGHGDHFDHFBEBBACCAECAECACGBCFFEFCEGGACBCDFAAHABGDEGDEGDACFEGDEGAFAACCBEABGAFDCFDFFGACHCEGCFGABCHGAHCDHCDCCDCGABDFBDEDCGFFBFEACCDCHDGGCGEEAEBAGDCDDCEEB,False +284,14.0,18.0,15.0,12.0,15.0,14.0,12.0,12.0,DHBFHFFADGAHCABFABEEFDEAGEAGDDBACBCCBGCBEEBEAHEHCFFCEFCBCGDCGDEGHGGABADBEEBEHCHHDBEGGFFEFDADHAHBBDFBCCBGABCFHCFA,False +285,16.0,15.0,17.0,12.0,11.0,20.0,18.0,11.0,HGHCBHCECFEHFEGDAFFGFEGFEAFGFBGABDBBGBACBGFBECAAFDAHHFGGAGGAEGCBDBBDHEFGGDGEHAHADEADEFCCFCFADDBCCBCABHAFFCFGCFDCFACDBCGH,False +286,11.0,13.0,7.0,7.0,10.0,17.0,12.0,13.0,FDGFDGFHABDDHFAHBHFFGCFHBGAGFFGFHHAGHEGHCGBCECDECDBHBEHBEHCAFGABAFBGFBEFGEABFBFDEFAEAHEABC,False +287,8.0,6.0,3.0,14.0,2.0,6.0,4.0,6.0,BGDFDCCDGAFBADBDHHDHCDHAAFAADBADBFDEFABDGHEGDDFHD,True +288,13.0,9.0,15.0,13.0,19.0,11.0,16.0,13.0,GGEDADGABGCBHAGACCFCHECDDCBAFEEHEBBEABEACFACEDHEAFEGFGDAEAAECDEFEHHEHBFFDCFDCDAGDHEBHCGHGGHCEFCGFEGEDGDCGHBGH,False +289,21.0,24.0,27.0,24.0,13.0,22.0,21.0,28.0,EBFBBCGBDHCAHFAHBBHBDHBDHADECDCAHCGHGFHADHDCHFBBAHBDHECABFBFFCDFGDFECBECBCHEAHFHHEHGGFAGBDCEHCFHCGGBEGFHBFGAFCADDFDDBDFCAFCHFDDACGACGDCGAGGHDEDECDAGHBFABABBEFBCCDEAHGAHGCCGCFAHDGHC,False +290,11.0,5.0,20.0,12.0,8.0,15.0,4.0,7.0,CBCCHDDHADEADEFDAACCCFFDFCAFCADCGDFEDCECCECFFHFFAGFCEDEBFFHCHGCDBHGCFDAFBAEHACCACB,True +291,20.0,16.0,14.0,23.0,25.0,13.0,17.0,18.0,GBEGBEGFEGFBFDBFDBADHAFBDFGDEGDGGECCECAEAADAACHHHHBHEGDADDBHAAAEHEBDEBGEAEHDGHAAHFABCEGDFGFCECDGDABDHBDECCABFBEEDEGFEHFEHGAHBDCDAEHAECDCFDCEDHGHEC,False +292,22.0,21.0,19.0,22.0,30.0,26.0,23.0,31.0,AHGAHGABADGFGGEEAEFDCABCFBCGBCBHCBCFEDFEDHADEFDFBHCBHAHEAHEHHEHEBGEAGEDCEHGACGDCFCEFDEBDEBDFHACEEHBDDGGEBCEBCGHFGEABFAEEBHABGAHGAHDHHDHEABEGBFAEGHEHCADFFDFGAFCDDGFHFFGFFDEBCHFEGFCDFHHCHFBEGHHADH,False +293,16.0,24.0,24.0,18.0,24.0,17.0,14.0,18.0,BDDACEACHABHABHECHGHEGEEFCHFAFAGFBBBGBEECEEHEFDBDDBDDGCGBCEHCEDCBFABFBBCCECCGBEBAABHECEGCEDDECFECFHCFHCGBCFFDDFADFAHHCGBBBCAFEBHGDGADGAHCBEAAFGDBHHEDCEDFEH,False +294,32.0,23.0,12.0,12.0,9.0,21.0,14.0,23.0,BCGBDHDCGGGDAFDFFBCABCABCFGGFAAFBHEBHGBGGDAFAACABHBFFDAFAHHBHHDHGDEADBHGBHBBHBBFACCBECAAAHABHAEAEDFGCCEAFFHEBHFHHEHDABAAGAGHADAAHAACEAHAAFFBFFBFFH,True +295,25.0,28.0,34.0,29.0,21.0,15.0,21.0,21.0,GBBDDFEAEADECDAGBCFBADECDBBDCCGCAGCDBCBBCBDCBGCEHCGACACFBHFDDBCHFCGAGGECFFABDEGDEFDHFHHBBHDAEDBEDCDDCDDCDAADFACEDHHGACGBBGAGAEGFGGHCACCDHGEHGEHGHCEACBHFEAAEACEACHHCHBCBECHHFEBBDCBFCBDDBDABAEFAHG,False +296,10.0,5.0,3.0,10.0,3.0,6.0,4.0,2.0,FCDBCACHBFABDAGEAGDADEBDFDAFGABAADEADHGDFFD,True +297,18.0,24.0,24.0,26.0,29.0,26.0,24.0,26.0,HAEHBEAEEHCACDDCFDHFGCBHCBCDHFDEADBBGCBGABFAFGGHGEAGDBCCGCBDFDDFBEFBEGDEGAADHADHBHADHCDFEFFEGGEBAHBCFGCEGEBGBFGEAAEDHFDAAGHFGEEGEEDHECGEDFEBBDCCDBDECFCBBEFHFCGFEHHEHHAGHCEHCDFCDFCDHCHGGHFEFFBFHBADB,False +298,13.0,9.0,11.0,21.0,12.0,21.0,9.0,8.0,DDADBAGGAGEAGECGEFHFCCFBCABCABHAEFABFDFCHHDDEDDHADHCHABFFFEAEDCFDEGGFDDFCDFEFFEDFEBADFDDFBDFCHBGFCEDDAFG,False +299,9.0,10.0,7.0,5.0,4.0,5.0,9.0,5.0,AEBFBGFGGAGGADCADGDHGHEBHBBGEBGFCHBCHAAFAABCECCFDDBCAB,False +300,9.0,10.0,14.0,12.0,10.0,5.0,22.0,10.0,GBDGFGGEGEHGDGGEGCCGACBDBBDABDAEFABBCEAEHAGCFHDGHGGDGADGHGGBFCDHCDGCGBDAACEHCEGCEGDHCHECHCBF,False +301,23.0,15.0,14.0,8.0,21.0,17.0,19.0,20.0,FGCEGAEGEDHEDBGGECFFHEBBBFDAHHEBAEBHCHEGAAHABEEFEEFGBHGCHCAHDAFGGHGDHGFAGBABFAFHEEGEAAEDAGFAEFACFACBHFDCEHBAHCAHGAHCCGCCGEAGEACFADFHBBHBF,False +302,27.0,23.0,30.0,20.0,17.0,18.0,24.0,20.0,AACCCBGDBFHBAECFFHBHHGHAACGCHDDBFBGGCHGAFGAGGAGGAHGCHGCDGCHBHABFDBDDEEDEEDBCFCCFCHBHFBAFBDFHFBAAAFCCGHCDBADAFCABEACGBFBEEBAEHAEGAHGACBBDACDFCDGCDGHDEEDEBCFFCAACHECGCBGCEGCDAAEEHGD,False +303,30.0,27.0,22.0,22.0,20.0,20.0,25.0,21.0,FCHFDBBDBGCAADEBGFBGABGFEGHAHBADAEDACBECFFCFFGDBGAHHAEHFCAFAACEDCFFBEFAEABHDGAEHDDBGCBGEBGEAEEFBEBDHDAAACCHCCHGDAGDFCFABFHBFHBGBBDHBDHEEHECHDCADAEDGBCCBAGEHGEBGFBGCCACCAGAADAHGHHGFDABGGGD,False +304,29.0,17.0,17.0,22.0,14.0,23.0,28.0,17.0,DABGFCFHAEGAFGFBCCBEDDHFCADEHDEHGHDGADGHGGCCFFFFCCEGHEGBDDDDDFDFGDFGCEABADBCHADBGDCDAHFFBGFGGHAGHAGAEGEGCAAHAAGAAEBAGBGFBHBBHBGDCGFCDFBAEBHCFEAAEAAHGAHGAGFACFDCFEAFDAB,False +305,11.0,12.0,13.0,10.0,10.0,17.0,17.0,13.0,BFDDADEGGFGEFBEAGHAGBACAECAFFBBFHBCHGFHGHGFFGCFCBBAGCDGDDGCGHCBHDGGFHFFHGDECDFCDEAGFAFBAECAECHBHHEHCEBF,False +306,7.0,10.0,4.0,3.0,5.0,2.0,7.0,5.0,BHBHADABBABGABHDGHDBCEFEEFCEBCEHGGCGBAABGAG,True +307,17.0,17.0,13.0,19.0,19.0,19.0,22.0,12.0,FDEAAHFFBFBGFBDFGDFGDBGDBGFBFFHFFABEGGGHAAHEAFEDFCBFCEDCDAGBAFBGHDHCGHGDEGDGCBBDHGABCDHCFHEGGDBCHECEECEADEAEGAGBAEEDDEGCEGCHACBAFBDEDAFGAE,False +308,16.0,19.0,32.0,19.0,25.0,21.0,28.0,24.0,BCGCCBFCFGGDHGDADAACACGGBADDGDDGFBCHHCFECDGGAEBAEGHCDBCHEEHAEHFEFFEGFEHDCCCEGHFHHGBGDEGFHCFBFHBGEGFCGFCBHGBHEBEEBGBAGEEGHEAHEBFEBHCBGGDGDCHCCACCADBAHEDFGCACCHHCHHFBAFAEEDCECCDFCDFCDFEG,False +309,12.0,7.0,7.0,14.0,8.0,9.0,9.0,23.0,HFHHBHGACFAHHHHHDHBGHCEHEHCFHCBHDAHDAHFGDDHEBGFDDHADHBDGEEGDACDAHDAHCGHAADAECBEGEFFAFBDFG,False +310,7.0,9.0,2.0,2.0,5.0,3.0,5.0,9.0,BBABAGEAHBGHFEHBEHBHHAHBEGBGGBDACFCHFDHAAE,True +311,26.0,28.0,24.0,21.0,11.0,21.0,26.0,17.0,BFBEHBHGFHFHDDGADGADGFDCFBCHGFAEAAEAAEAABDDGHDBEDCCGFCFFCBBGGBFHCGGGDBGDBDEBCFBCABGDBGDFGEGCCAAHBGHGGFFBAHBAEGCFBCECHFADGGCECCFCBACBGBBGCCDAEHABFADDADDAFBHFCHAAFAABHHCHBCDBGA,False +312,23.0,13.0,12.0,13.0,21.0,13.0,8.0,13.0,FBAFBAECDHHEEEEAACADHEDAEAEFAEFAEGAEGAEAAEAGGBCDDFHAHHFFHFCCACAEFAHFAECHEAEDDHDGBBCBDFEHEAHBAHBAGCCDDDFGEGEFBBDBBCCB,False +313,3.0,1.0,2.0,0.0,2.0,1.0,1.0,1.0,HACAACEFGEB,True +314,19.0,17.0,14.0,10.0,16.0,21.0,10.0,13.0,AHDAHEEFAEAGCADFEHCEBCGCCGADDADFADFAHAAHFEHFEHFEFFCBFEBAAHEHBEBCCGHEBHCBFCFFGEAHEACBABBABFFGFFGBBBFBGDGCCBEDADAFBFFCHEDG,False +315,3.0,8.0,4.0,7.0,12.0,10.0,4.0,14.0,DHEDBEDBECHEFFFCHDAEBAHHFHFEGFECEEDEGHBGFBAHBHEBEDCFHHFHFDHGBH,True +316,19.0,13.0,26.0,20.0,13.0,13.0,16.0,14.0,AFCBGBFCAFCEECHBBAGCDGCFGHEBHEDCCAHCFEAEDDEDAGCAFCACCADCGDEBFAGDHGDCBACHAGHBFHCGECDCAGCADADFGDCGDGEDFADCADFFDAEDHCCHCBHGBHEBFGBCABHHDE,False +317,16.0,18.0,21.0,25.0,22.0,16.0,21.0,17.0,GDDGDDEDFEGFEDEEDHBDHBCHDHBBBBBBCCBCCHFCHBCHEHADGCDGCBGAFABCEDFFAEBCHBDDEADCGDEFAEGAGCCDCCGFDFBDHCGHGAAFEADAAHEBHEAHFCCDCEAHEAFGBGEBGDGEFGFHGEHFAFDGEDGECEDG,False +318,23.0,22.0,20.0,24.0,12.0,20.0,16.0,25.0,AABCHBFHCDHCGFGHDHHFGAGHBGHBGCEECAEHGBCGDDDHCFHGBHGBHEBHDCCAHCAHAHCAFCDFHHEBDDBGDGEABBAEBCDDFDDFEDFACFABFCHHCHHGBFAEFBCGBDHFDBFDFDAADAFDCEHCBBDFAAAAGECDABDAEFABFG,False +319,9.0,5.0,11.0,3.0,6.0,3.0,10.0,12.0,HABHDEGCCCDFCBHCHHGHAGHCGHCDHCEGCGCEGHEAHFABAECGBBAAFGAEHAG,True +320,31.0,18.0,28.0,29.0,18.0,25.0,23.0,22.0,ADEFDADBAGBEGHEGDCAHAAHCFGCHGFEGFHGCGBFDAFDCFCEBABHDBAFAFFDGDAAHABGGCAFCACCDEBDCCGCCDCCAFGGCHBDHGCHAHBBBBBCCGAADCBDEFDHCAHCHHFHAECDCHDGHDEADEDFADBADEEDGCBGCBGDGEFHAFEAFAAFGEEDCFDHFAHFAFFAEFHEDGD,False +321,11.0,11.0,8.0,16.0,26.0,18.0,18.0,26.0,HFGEAHHHHDBHGEHDFAGGDEFDEFDEFAEFBDFHDEEDEEBGEHEHHEHACGGEBHEGHEFHEHAEGFDGDDGBCEAEGAECDHCGHFEHGAGFCHHEHHFGDFEFFHBFABHDGFFBCEBAECGDABDHBC,False +322,6.0,3.0,4.0,2.0,1.0,1.0,3.0,2.0,CAAFAEHAGBDHCDBCGBAGCA,True +323,10.0,11.0,20.0,18.0,16.0,14.0,16.0,14.0,FCGBEHDGCCHABGBCGACFEFEEFEDCCCBGCFHCDAGDAGDEDFHGBAGEDFECGACGEFGEFEHCDHCDEFHGBHGEFDEFDEADBAEHFCBGCHDCHDCBDCFHBDABGAHDHCD,False +324,14.0,16.0,12.0,17.0,15.0,23.0,16.0,14.0,HDEBDGFAFHDDHDHECHEBHGHEGEGFADHGEFGDFBCEBGAFFAGFHBDHGDCGDCACFECFEHFAFBCEHCFBEFCEADHABCBBCFBAFAGFAEEAGBBECBDGBFGHGBFDDFDDFGAFDAF,False +325,15.0,13.0,7.0,9.0,15.0,10.0,11.0,11.0,BDABDCBEEECAECHCFHBBHDHEAHEAGEDEABEDHEGGFGGFEFBEHEEFBHAAAAAADAADFAEFGHHDFHGAGBBBBCDCGBFGFCG,False +326,18.0,22.0,21.0,20.0,18.0,16.0,22.0,11.0,FAHEBHABFAHGAEGHHBBBCBGCBECAAGDACFBCFEHGDHDDCDDFFCEGHEBHCFCDFCDGCHBAGCEBCBDGBDCBDHGEFADGEFABFGCFCDBCGACGABFACDEDEBDAFAFFABGEBGEGEEDEGDAGAGGEBGCBDCED,False +327,13.0,17.0,20.0,5.0,21.0,19.0,14.0,10.0,CACCAECGEGAFABCCDFAFFHFCEFCHAHBGEECEECGEFDECDECEEABFBEAEEBEDHCAHAADBABFGFFGFGGFBGBHEBHGFGEFBBGCBCCBCBECBCGFEHFHBGHACEFF,False +328,21.0,20.0,17.0,13.0,23.0,15.0,20.0,19.0,HECGCCHADAADGADBEGBEABEHFGFGGFGCBECFHBAAEAHDFHFFBGEBGCBFHAABAABDCBDCAFAAHCGDCGEEGHGDEGCHGHBFHDHCDBCFEAGCAHCEHEEFEFBDHHDEBEEDEBGGAHGAHBEFBECEFABGABEC,False +329,24.0,23.0,29.0,30.0,30.0,21.0,23.0,19.0,HADHFBHFEHCEHDHCDFCBABEEBDEHDACBGDBCDBGDBADCCDABAGCEGBDGBEGCDFAFFGEFGAGEAGEADCGHGBDEDAADEHBAHCAEGBGFBFHBGEBDBBAEEDEEFAEDGCABCEDGFFGECCDACHBDGBDFCHECHECEACEADDDEDFADFAFHCFGCADCEECFCCFCCAEBGGHHCHFDHFEG,False +330,7.0,6.0,9.0,9.0,7.0,8.0,16.0,10.0,HGGAAGEEFBEDHFDAFBAEDFGHFAHGDHEECGHCGCCACGFGHFAHEBHCGGCBGDHGDCGDCGBGDBDF,False +331,15.0,22.0,24.0,18.0,22.0,22.0,16.0,24.0,ABAFBECDEDAHCCGCAAHHCHHGBBGBAGBDGEDEHAECACBBFHHEHHEHHFHDCHDCBGFHFFHAEBFEFGDHAECEECBEFEGCCFBCGBCDEGHBGHFAHFGDBGEAGFADCBCCHCFFDEFEEFBEFHEHDCDDBHDBGFAFFBCCBCFBDADCGDE,False +332,9.0,18.0,16.0,12.0,7.0,14.0,10.0,14.0,AADCABGADACDAEDCHGCBFHBFHBEHGEFGHGECFBCDDGDAECHBCEBCFBCHHFDHDHHFFDFBGFGHBGECCFDFHDBHGBCFFABBACBCBBCB,False +333,24.0,10.0,12.0,14.0,8.0,11.0,24.0,18.0,AHAAHAADADGFHEEGBECBDCEACAHEGHEFHADAADFHGBHGBGBCGAGADGADGAHCAHFHFGEGGBACDCCDGFGBHCFGAFGBGEHACHAGGCDDHDAADGHDGFCGAHBAHBGFF,False +334,17.0,19.0,16.0,21.0,12.0,28.0,7.0,21.0,BCEAFGACAHCFEBBDBBDFFDBCDBFDFFDHFABDGBDFFGFDHFCGFGHCBHAFCEFHHBHHAHFADFBFCBFCBDCHEHDCADFDDEHDECDFCAFAAHABFBDFHFCDGHDHHCHECBEAEHAEFABDEFAFBGHEA,False +335,5.0,1.0,17.0,8.0,5.0,13.0,6.0,9.0,HFEEFACCHDCHDCHFBHDDCACCFCCGCFFDEFAFGCFHAEGFEGFDCCAFCHCGDCGDCHFH,True +336,7.0,5.0,7.0,10.0,4.0,6.0,4.0,9.0,CABCEBDDFADCAFCFGCEGEHDDBFGBFHCHHGHHDFDEHDAACAADHBDH,False +337,17.0,14.0,20.0,15.0,14.0,12.0,26.0,25.0,FEFFADAGDAGFCHHBHHBAFEECECAFCDFDDGGCHGCHFCGDGGBBGDAHDHECHGCBBBHDEHCCHFGHFCHBCHDAHCAGCAGEBHEBAAACEECEGGDHCEBFEHGHCGHCGDABAGHGGBBGFGGDGHHEHDDAAGA,False +338,17.0,17.0,8.0,23.0,13.0,10.0,15.0,13.0,DFFDBGEBEBCDBFDBAEEAFGAHDDDBBDEBGEBGBAGBGBCGEDEAHHADHDDHEDHGGHADDBDHHDCHDAGAECADCHDFBBFABDAFCAGDFFCAEGAEGEFGBDGCHAHA,False +339,18.0,24.0,23.0,25.0,16.0,22.0,30.0,24.0,DGBDGDDCDGCBGFEHEAAFCACGBFEBGCGCABCAFAGEAGEAHDCHBFEGHEBDDBDDBGABGFDGFBHCAEEAGDHEHFEFEHFGHFBFFGCAGCACCDHDDHBDFGDFGEEGBFDHHBCHDFFDCCABGBDGECBEGGGHDCHACHBHHGGHBGABDABHFCHFHHDBABGFCGFCDC,False +340,2.0,2.0,13.0,7.0,3.0,3.0,2.0,4.0,ECCCDCCACCBDCDFCDGAHHFEDFBDCDCCHGCHE,True +341,4.0,3.0,4.0,1.0,4.0,2.0,6.0,4.0,GAEGBCHBCFGAHGAHBACEECEGHGDF,False +342,10.0,14.0,13.0,18.0,10.0,15.0,4.0,7.0,BFBBADBAGACCABFAECCFCCEDEHDABBAFGGBDBCEBFDBFDEHDGHFAEECCDCCFHBFDEDDFDDCDDEHDEFFBDFBDFACHAFH,False +343,2.0,3.0,3.0,5.0,8.0,5.0,2.0,1.0,EAFDCDDCHEBFEFDEFEABECBFGEDGE,True +344,16.0,17.0,10.0,12.0,19.0,14.0,18.0,24.0,DGDFEBGECFCBBGFFEFHEHBEHGCBACBEGFGGHCBHGBHAEFBFFBHHBEHAGAADFAGFAHFAHGACGAEHABFGEGHEHHEHCABDAHEABCDHGEHGAHDDHDDBEFBGDBADGCHECHDHEEE,False +345,12.0,6.0,8.0,11.0,11.0,7.0,6.0,8.0,EEABBCDDGADCAECADHABGABECBECFEFFECDEGHAFHDGHFHAFAABDAHCEHAEHFDCDEGDGD,False +346,14.0,12.0,14.0,18.0,13.0,23.0,16.0,8.0,ECHBFBAFEFGCCDDGFDBFEGFEAFECFEHFEGBDDCHDHAAGAAGFBDBGDADDHGDCFFHEEHCEBGDGCFECFEBFDACDFGDAGDGGCGBABDCBCBAFFAFFAFEAFDHFCG,False +347,13.0,9.0,9.0,6.0,6.0,16.0,14.0,5.0,GEACFCDFGAFGAFCFFDDGGDBGDEGBAAHGAHFFBFFEEFBFFBFCEGBGGCECCAAHAGHAFAAHACGGFBCBBD,False +348,2.0,2.0,2.0,3.0,4.0,6.0,4.0,5.0,EFGDDADHEFBAFECFECFHBFGGHHGH,True +349,25.0,25.0,26.0,14.0,12.0,22.0,23.0,17.0,GCCGCCGEEDFADFDCCEHCBHCBGBBCBFGBAGFGHBGABFAGFBFFACCHHFHABAABCABGHEGBCGBFFAFGACCDDCBFGFAAAAAEACEFCEFCADCAGHAFABFDGADHHGBBCHGEBGCBHCBFDHGHHCEHBBBBEFAFHDDGFDCAGCAGDEDE,False +350,26.0,15.0,7.0,12.0,18.0,16.0,17.0,8.0,GFECAAAAAHFADABEGCECDGDAGEABEGBGBBGBBGCHEFFDFFAAAGEAFBAGDHHFGGAGEADFAEEBEFCGFDDFGDFDBFBEHHAHEAGEABEABEBBADAADAFFCEGCHAE,False +351,19.0,24.0,27.0,20.0,25.0,23.0,28.0,19.0,HHCHFCDGDBGDFGCBGDFGBFEDFBGABHABCABGBGAHGBHGBABCCEEBDFGDHGDBGHFGCFGCBHFBHECGCCBCGBFGACGDCHEEDFBGABFAFFGHDAEAAHDAFDEFDEDEECFEGHECAGCECCFCBABFADCAEGEDDFHFECFEGABGAHDHECBACDGHEEEEHECBECGFC,False +352,11.0,14.0,21.0,19.0,18.0,15.0,12.0,19.0,CGFBDFCAEDFEHEHCEACEAEEFGDAGBACBFCBFABDDGHDEHFGADGHDHCBHCEHCDHBBEFGFBADCGBHEADECDCBDCBACBACBDCHFHHCHFDGCDECGHCEEGHEHFFFFGEHDCHDED,False +353,14.0,12.0,11.0,22.0,22.0,10.0,7.0,14.0,BDEBEHDFDDCDEADEHCFHCAACAABBCDBHHEDHEFBAFDACABGEEDEADFADFBGFAGCGHCFEAEDGDDFDEEBEEBEHHEHHEDEEBHHCADCACHDDGGBFEDDE,False +354,25.0,23.0,25.0,17.0,15.0,24.0,9.0,25.0,FHABBAFCCFBCFBEDDHCHGBAEHCEBDAADFADFHFHHFHBFBCHBHHEHDACDFFAGBGDEGHHGDDCCCAHCEECAEDECFBBHDFCEFBAHAAHAFHAFHBFAAFAGGACEAEDAFDHEGFCFFCDFHGFHACHABBABECCCCACCBBCDBEBBHDB,False +355,17.0,20.0,28.0,20.0,27.0,26.0,18.0,20.0,FCDHEAHEGECAEDAEFCHFEFCCCCBECHEHEDHDHHEGHEDFEHAEDGEDGEFEECECHGCDGCBEDDEDDFDDBGGCGBHHAACABGGBCGBCGDCFHCFBCFBHFAHFEFFCFFBDACFCHBHEEFBGFBHFDGGCECAAFACFBBBABBDBEHCAFFEGCADEADFFBCGA,False +356,11.0,9.0,19.0,9.0,17.0,23.0,24.0,22.0,DCFDCHHGFEAECFFCFFGEFGFFGAHGBHAADAACEFFGGEHCAHCBDFFDGGHHBFHBHHAHFFGGFEGFCGFCHCGGGGEEEFCDHCDECHECEBCFGCHBCHAEHCEGFDGCHBEHBGHBGHFAEAEGGD,False +357,15.0,19.0,23.0,15.0,30.0,8.0,15.0,12.0,EDGEGBEGAEFADGHEFEEDEDDEGGFDAEEAGDAEEADEAEBBCFBCGECBEGGACEFBGDHECHEAHEHGGABCEDDFDDEDBHDBCBACACCGCABEGHCHCCBCCAFCHBEHEHHCCBCEBCEBCEBFBBECA,False +358,8.0,10.0,3.0,16.0,6.0,11.0,10.0,8.0,EADHDFFDBFEGFGCCAFCBHDGEDHDDFBBFEBHHDAHDHEDHGDAGDAEDGDGFBGABGFDGFABBADBF,False +359,20.0,14.0,12.0,8.0,11.0,4.0,10.0,13.0,BAHGAEDBEDCADCAHBABAAFAACGBHGBHABHEHCCHBCGAEACGDCADCHGAECADFAEBDEHFCHEAADHAGHFBEBCEAGEBGBGHB,False +360,26.0,15.0,17.0,18.0,13.0,10.0,21.0,9.0,HCBGGBGGBCCDDCDCCHCHHEGGEAFEDFAGEBDHBGAFGDGAABCADCEGCFGAEABEADHABGAEGFEAFAFCACGADDBEAGAABAHGDCDEADECDBCDBCBHCFDDFAGAEGAHGAGAAFBDB,False +361,15.0,32.0,16.0,34.0,25.0,18.0,29.0,23.0,HDFHFFDABBBBEEBGEBGEDEEGAHGBGBBHDAEGCDACHECHBGDBGDBGDGDDFBGGDEBFAHHHHEHHAHDADDEDBEBBHABHAFGDDBEDHEDHDDHGCHCEFDGGDGGBCFCCFEHFGGFHAEDFDFFCAEGABDFEDGBAGBGDBCFBCHEDADDCDCBBBDEBDEBGHCGBEABFCGGEFCEG,False +362,22.0,28.0,20.0,25.0,21.0,16.0,11.0,16.0,BHCHFBFFBDDBHHBAHBADBAHBAHGCCFCBBDBBECAEFEDHHBCCFDCBBBEBHEBFGBHGDHCFFCFAHHAGAGDBFDGFDBCGEADBFBBAAFEDGEDFDAAGBAGAABEDDACBECBEFDAHCCCCGCEEHAEADEDDEDCEACEAEDDEDDE,False +363,11.0,11.0,7.0,6.0,9.0,8.0,12.0,8.0,FBADHHEHFGGCGAFEAFEGFGGHGHCCHCCBCABAEBAHDDCGFABEABFABABDEBDBHAGGFBGEEGDE,False +364,5.0,2.0,8.0,2.0,1.0,2.0,9.0,6.0,AHGACBAGHCGHGBEFDAFGACHCCGCDGCHGHGC,True +365,33.0,17.0,16.0,24.0,25.0,19.0,21.0,11.0,GDDGDDGBDBAABAFECGEDGEDFAGCACCFHCGHCDAADBACFCHEDAEHABGGHCEEEBAEFEDFDCFDHFDAFAGFBCDAFGEDDEHBEDBDCBHCAGFHFDACAGDABEABGABGAHCAGDAFFGEFDEFGFGEEEAEAAEAAEAEFBBAHBABCEGEDGAA,False +366,24.0,28.0,22.0,9.0,23.0,15.0,15.0,17.0,HEGHECCBBCBBFAEDHBFCBFBBFABGEGCFDCHCCBAAHAADABBBBAECHECEEHEEBAECDDAGDFGDFCDCGBCEBCABEABAAEHGCHEFHEDHFGGAGEHGCBBAFBAHCFEEGAEGABAABAHFHBCCCEHAEBBEGCGFFBHFA,False +367,22.0,19.0,28.0,25.0,31.0,21.0,23.0,26.0,HGHDGHDGEBCDDCAEEADEDEEHAHBDCEEBEFGAHAADGDHBHFCEGEDBFDEFEEBEBCEFCEFCBACBADHADEGDAHCCEDDEDHFAHECDDCBEFBEGBDCHCHAABAACCHCCHCDHAGCAGEBEEAFECHBCHGCGGHFCFAGGEDAFDCBECBEHDEFFGFDGFHGFGGFGFFBFHBCCGAGHAHH,False +368,19.0,23.0,22.0,14.0,18.0,18.0,13.0,20.0,GAHHDGFBGDBFFBHGADABEHCCFDCBDAGDBFBBFBBFBFFEFFAHCAFGAHADHEBFBAFBECCEBCDDAEDGEHBBBBACBAEBDECHEGFCHACFDBGCHHCHGEHCCHCGHCGECEAGACHFCHFCHDEEEEEBDACAAHA,False +369,8.0,9.0,10.0,4.0,11.0,7.0,17.0,8.0,GEHGEBGFGGFCGEHAFBBFCBHCFDCGEHAEGCCGAEGBBCHBHFEAFGBCGADGADEADCGCHGEBAEGHEG,False +370,14.0,14.0,22.0,16.0,19.0,13.0,17.0,12.0,AEAAGFACECCFHBFDEGEAGADCEHCECCADHDEGFGGCCGBHGBHGBAFDGECGECGHBDHBABFACDDEBFECFEFFCAFGEGEEGHGCBACBCBDABCGBDFEDEDDHDFBDHCCHCCHEADE,False +371,24.0,19.0,21.0,13.0,20.0,18.0,17.0,23.0,GEGEADCDGEHBDCBDHAHCEFCEFEEFCDFBEGAGFHGFCCHCCFFCFFAADAFCABBBHGCHDHEAAGCAGDABHHCHHCHGBEFAAFHAFHGHHGDADEABEGBCGCDBADEHHEHACDABGECFEFEEABEBBHBBABCAGCFGEFABHAH,False +372,3.0,3.0,3.0,4.0,0.0,2.0,1.0,2.0,DDFDDBCABHABACFGCH,True +373,11.0,27.0,14.0,16.0,27.0,12.0,14.0,25.0,BGEGGBDBADECHGHHEHADHDGAEAHEFHBFHEEDGEDECBHFEHEBHDDCEABEAHEAHEBEEBEGAHCHHCBBBBBBBCCGDFGEBBEFHFDHFDHFDEFDEDEHGEAEEFBBHBBADBCBCCBGFDGHEFABBGHCCCGCHH,False +374,3.0,9.0,10.0,10.0,8.0,7.0,11.0,11.0,GCGGBBHHCCGFDGFDHDDHFDBFEGEEBECDDAECCBBCHGCHGFHADHACBEFHEBHDBHDGGFGEC,False +375,23.0,33.0,18.0,22.0,30.0,18.0,26.0,23.0,EBDEBDHHGCCGCFGADGBCGHCEHFEHDEHBEGDDGBHGAHDAHDBCBAABCFBCHEFDADCAEBBBBHBAFBAEBAHBHFBCAGCFHDADEAFECEECEFBBGGCCGEHHBBHEDCAFAHEEFFEAGABGCDGBBGBDFBDFGDBEDBHFBGDDGAEBAGAFGEEBEECEABEHGGADGDGFHGFEAEHHE,False +376,26.0,12.0,16.0,23.0,9.0,18.0,21.0,30.0,ADDFFDFFDFFHCFCBFAGFBGHEDHEAHECHCABFAEAAGAAGDDDDCFGCAHABDEGFHBCBCADGHDGADGHEGHDGHFBHGDHCDEABHGEHBDADAACHHHHFHAGHEGHDGHDHHCCCAHDHHGGFAAAAFABFHCFGBHGAACBGCDD,False +377,14.0,10.0,11.0,6.0,8.0,8.0,6.0,11.0,FCEFBBABDCHECFBCGBHGFHECGCFAFAEFDBACADCABCHHEAHGAEBAHAAHAAGFDCBDCBDGAEHHEH,False +378,10.0,13.0,11.0,8.0,10.0,9.0,5.0,12.0,ADCHBEECEEADBACBGBBAHBGHCCHGBHCCACCFHCDBDDFFDFFBFEAEHABHDBDAFHECBAHEGHEGHEFBAF,False +379,26.0,14.0,13.0,28.0,14.0,24.0,18.0,23.0,ACEAFGAGABGAGGEHAFHDCDDFFCGHCDHAAAEFFEGABGAHHADFGDFBCAGCAGBACDDDBDDEADCCHGEAGEABHHFHCCBDABHFEEDGHBGBBHFDFCDFBDADDEDDEDHFDHFDHEDHAAFAHDGDBGEFFABAECAHHFFHFFHDFHFG,False +380,21.0,15.0,24.0,10.0,21.0,16.0,24.0,20.0,GBFFDHFBFGEFHHHHHECHEDEEBCAFAABGACGBCAECBCCBEDFCDGCEEEAEGAGGACDAFDCGBBGBBCAFFDFHBAGGDGGCCHEAFEAFCAFCAHCGGAHCACCAEGHEHEEGEEGDCHDHHGCEGAFHHEHACBCFGHBGBAG,False +381,15.0,21.0,27.0,23.0,28.0,27.0,27.0,20.0,BCBHCAFBBGEBDEDHCDGCGGCGDCFECDECEBCEBFEBFGCGGBGABFAEHCFDCHEGEFFFBGFECCEHCGFFGFHGBECCFCFAEDAGAHDAGEFFFAFDACCHCHBBHFCDAGDHGDEGDBDEHDHHFHFBHDBFDEAGCADBDDBDDEEFEEAGEGGBCGEFEEFDGHHCHFEHCAGGABCE,False +382,0.0,4.0,3.0,2.0,1.0,1.0,2.0,3.0,BCDBHDBHFEHGGCBC,True +383,1.0,2.0,2.0,6.0,6.0,2.0,4.0,2.0,CHDAEDGEDCEGEBGEFDEDGHDFB,True +384,12.0,14.0,12.0,10.0,21.0,16.0,19.0,20.0,GDHEBFGHDHCEABECBDCAHGAEGCEBCEHDEAEBHEBHFHHBBFFAFDCGHAGDCBFHGHCADBAHBGHBGADHFCHFDHCHECEECEGFEGEAGEGGEBFEGAEBAFFFEGFGGDGHFEHF,False +385,9.0,9.0,5.0,9.0,10.0,4.0,7.0,7.0,BCCBABGHBGDEGDACDBEFBHDGADGAEHHCFCEFDEBDBBDAAEEAEHADAGEHGFHE,False +386,15.0,9.0,11.0,11.0,15.0,15.0,12.0,13.0,EGCFFCFGCFHFDHCHCCHACHECAGHFFABEAHEFHEDDEBDHBDHBECDEADGFGFBGFAGFAFAHEEEBDCDGEHGAGGABAAGDFDBEABEHECFAA,False +387,17.0,16.0,9.0,11.0,9.0,4.0,15.0,11.0,DADCFEBAEAGCBBHBEGBDABFBDFDHCAFEGGEAGEACHABHAGHDGHBHHBGDEGHCAAGDAHACEGBBGABAACGACGBDGBDHBDCE,False +388,10.0,3.0,8.0,5.0,5.0,8.0,6.0,3.0,BDDGGCAECAFGAFCACADCEGCAHCADCBFFAFFHHFADEGFEGBEA,False +389,17.0,13.0,28.0,32.0,15.0,31.0,24.0,29.0,HGHCCHGBFDBGAAAAEDAFHHDEGFECFHGFCFFEHFDHGDCCFCHFCFDCFDGEHBEHGHHAACAEDAHDACGEGFEBHDHCFHEFHGFAGFACDACBHCDHCDCCDEFDEFDHFECDHDDCGDGBBCCFDHBDFBDFCGBBHAEHCDGGFHGHAGFBDBDCGFCGFDGDDFDHGHAFFAGDCEDCF,False +390,23.0,24.0,19.0,26.0,25.0,15.0,25.0,27.0,FADECFEGAEGHCFDCBGCBDDHDDHDDAGAHHAEBAGDAHBHGBFGBGGFGDCADCBHBEHDEAEHGEHDBHGBHEBDGBHECAEDADDAEHFFHFHGGCCHHEFECCGDEACEHHAHGAFAADBBDCBGABDACCADABFABEHFEBEEBDDACDEEDGGGGBHGBHCFGCFHFBHCBEGEE,False +391,4.0,5.0,5.0,5.0,10.0,9.0,7.0,10.0,FGGFGCEGEEHHDHGDCEDAHBFHFGDFEBHBHHAHFCCFACFGBFEEHEEDEAB,False +392,2.0,1.0,3.0,2.0,5.0,3.0,4.0,3.0,FBGCCGDCAHEFHFDHAGEEGEE,False +393,32.0,34.0,23.0,23.0,23.0,22.0,17.0,26.0,AABCCBCADCAHAAEFAFBABBHCCFBFGDHDHCAHFGBBCCBHCBHBFCDFBHBEABEAGEDGECBEBHEBAEFHEBEBDHAHHBGCCFDDFDFBDHBGAAACEACDACHADFAGFAGFHGFDFADFAHEAEEBEAGDDHCDEFDBHCGGDGDAHABHEBHEBEEBEHFABAHBGEBHCFDGFGFEDADCACHACBGBB,False +394,10.0,5.0,5.0,10.0,12.0,9.0,5.0,11.0,DCDEADHACFADFADABDHGHHDAHGAGEEBEFFCFAEDAGBAEBCEHDBHFFCEFHEHHEGEEDHF,False +395,9.0,8.0,7.0,6.0,6.0,3.0,2.0,9.0,BAGBECDECDCHEAHAFGBFHBAHDHHAACAACHHFHBDDBEEAEDBCCB,False +396,28.0,25.0,16.0,17.0,19.0,17.0,23.0,14.0,FBGFAAAHBHHGFCGDGGBGGEGGEFCEHCDGBBHEACEGBEADCADGEGHDGAAAAABFABFADFCCBHCADEFGEDDBDACAABAAHHHFACFBDAADBAGBGEHDEDBBFBBFBBCEAGEBHEBHEBEFBCFECFEGDGBAGDACDHCFCFGAGAE,False +397,11.0,7.0,11.0,10.0,5.0,9.0,10.0,7.0,BCHBAHFDBFCHFCDDBHGAGCHGCGGCGGFGEAEECDDFADEBFCHDCHBGABGEFDCFDFAAADAACA,False +398,21.0,30.0,21.0,28.0,27.0,13.0,18.0,24.0,CBDCAGAAEHGBHBHHFHHAHHCGHDBDABFBEHDEBCEDFDCFDCFBCEDCBAEBEDBEBBABEDGFBGFEEAEBGHBGCBACBDCEECBDCDDCAAGDGEAGEAFEGEEBEHFDHDGCEBFEBDGDFHAFHFDHECHGCDGHEGDBDBHEBHGBDAAAAEADDDCABHDCHCEHCHGBBA,False +399,8.0,12.0,5.0,5.0,7.0,5.0,5.0,13.0,HHGHBAEGABBCBBCBBCFBCBHADAAFBAEBEBFHDECEEFHGAHGHHDFHDGHAHHED,False +400,7.0,6.0,11.0,5.0,6.0,14.0,10.0,3.0,AEFAEBCFDCFCFAEFCGGCGECHFGADCBDFGCHCCABCAGGEFHEFGAFBFBGFDGFDBF,True +401,5.0,2.0,3.0,1.0,8.0,3.0,7.0,1.0,BAGCFGEEAEBHEGFAGFDGEEGECAEGAC,True +402,7.0,14.0,22.0,10.0,18.0,10.0,12.0,15.0,GHECCAABBCBBEEBEGBDCEECFGGHCHACHAHFBGGCCCCHCEFCFDCHDCHDFHECHACDBCBAEBDEBDGGEGHDCEGHECEECEEHBEHDFBFBAFHDFGFCG,False +403,14.0,14.0,19.0,22.0,20.0,22.0,14.0,19.0,ECCEDFDGEDEEBCBHDAFBAFAAECCFDCEBBEBDAHCADCFDHEBFEDFEFEGFEAFHAFHGCHEEHDDFEDFDCFDCFCBAHFAHFHHFBDFDDEHCGGBGHBAHCAGCEGAHBHCGCEDEFDFGDHGFCGBBGCHGHDDA,False +404,9.0,11.0,17.0,12.0,11.0,7.0,12.0,10.0,BCBDCEGCECEGCDCCDGGAHGEBGBHCFCAFHAFHADEAHFDHEBCCDCCDCBDHEDHADBAHCHDDGBEGFGGBECFEFEGBAGCAB,False +405,5.0,5.0,3.0,4.0,12.0,4.0,3.0,6.0,DBGAEGEEDAEHAEBBEBEEHFDCBEFGEFCAFCEHHAHEDH,False +406,15.0,17.0,23.0,27.0,15.0,22.0,16.0,20.0,EFCEGEFDBFHCCACBDDHDCFBHFHGFCECAEABGBGDHCDBCABGADFDDFECCACFAEFHDGHDBHDAHDHHDHBFEFDEADFADBDCHDEHFCHFGGFHGHHEAACAFCFBDDCEBCGBDGDEGDBGDHFCCFDEHCBBCBGDFGAFEAGC,False +407,11.0,16.0,12.0,20.0,16.0,15.0,13.0,15.0,HBGBDGBDGFGEFCCHCDHCDHFFCDBCFBEEECEFCEABEHDEDBEFHFDAFDBHBBHDACAHFAFBAEBDDDADDAFDGGGEEGHEGDFHBFHGDBGCBGBACDAHHCEAEEDHGF,False +408,16.0,12.0,20.0,13.0,15.0,13.0,22.0,14.0,HACHAGEAGFHHDDCEDCBFEDFEACBBFHBFHBCGBCACCBDDGDDBEFEGGHDBDDGGFHGAHFEGAEACDACGABAAHEABECECCECGGCAHFAHFGGFEECEHAFDGGGGCFHCGGCGBC,False +409,4.0,7.0,9.0,5.0,9.0,7.0,4.0,6.0,EFCBHCFAFFACFDHHBHCBGBBGBCEHGECBAGDCEFCDFCDEEHEEAED,False +410,12.0,11.0,9.0,6.0,6.0,6.0,2.0,5.0,DDCDHBBABBACFACEBDEHDHBFBAFBAGCAEAEEFHCBCCFHCAAEAABDABGFC,False +411,10.0,13.0,4.0,12.0,8.0,3.0,7.0,11.0,BBHBBDDDDDEEAAHAAHBAHGEHGHHAEDEEDACDBBDGCDBBABHHCGCFGFEGBAGBFDDAEHBH,True +412,2.0,7.0,4.0,0.0,2.0,6.0,5.0,2.0,BGBFGBFGBCGCEACFBHFEABHCBGFF,True +413,28.0,23.0,16.0,19.0,25.0,12.0,17.0,19.0,BHADEAEEHEEAGEFBBCDDAGHHGHAEBDFBAFBAHAEHBECBDCGDGBFGEEAEEDBDDBHDEHGECAACGACABCABFABCADEAHEDBCGFEBFEADEBEGADAAFAFHADBACHABHCCDCDBFABGAEGCGFHACDEGHHGHGDHFBHEBEGC,False +414,4.0,13.0,10.0,10.0,10.0,2.0,11.0,8.0,EEGCECCGBBGBCGDEEAGEDBHCHHADHDBHEHCFBDBGDBDDBDEADEHBCAGCBGEGCBGCBGFH,False +415,13.0,21.0,20.0,13.0,22.0,19.0,15.0,24.0,HFDBGDBHHBCCFHHFBHFBHFBHACEFEHFCBGBBFBHFDGECGFCAABGCFGCHHBHHEGFEABCBECEECGDCHHFEDAHBAEEDECDHDGHFGHFAECAFBAGBDECDCHBHHDCEFCAFEHEEGEAGEAFEDEBACBDCBGG,False +416,21.0,17.0,11.0,9.0,12.0,14.0,19.0,7.0,CGHHGBDBAGBAGBDGACGAHFFBFAGCACDAGAAEAEFCCAEFBCFGCAACGEFFBDAEDABDCEGEFCEBBHFBHEBHEAGGBGFAHFEBFBBDABFAGGAGGDGADE,False +417,6.0,8.0,8.0,1.0,1.0,6.0,7.0,5.0,BADAECHCCHCCHAAFCGFBGBBHBBGFCFHCGGBGGBFFAA,True +418,11.0,22.0,19.0,15.0,20.0,16.0,14.0,28.0,CCEHHDBHECHCGAGDCCABHFHHEHDEGBEGBDDBDEBHBBGFFCFFHBDHBCHBEHBAHFFGFCDHHDCHBEABHDBHCBAAEFDCBCCDFHEFGBDABGFBCADEFDGFAGEHGBHCBCGFAAHEEHEFHEGEEHEEHCGHC,False +419,25.0,19.0,13.0,15.0,18.0,30.0,15.0,15.0,FHCDCFBEHCABEAFAFHEFDGFDCDEHAFGAFBDBBFBBGBAHFAGFBFFBDBDDEGFBDEBHCBFCEFCEFAECAEFECGADBABAEHFDGFGGBGFBGDAAAHAAHDFHGCHFCAFEAEEDECDHBFAGHAGFEEFAFFAFAHCAHG,False +420,5.0,4.0,3.0,9.0,10.0,5.0,4.0,4.0,DEBDADFEFCEHEABEAEEFEDHGDHEDCFGCFDDGBDGBEAAH,False +421,21.0,22.0,19.0,21.0,16.0,23.0,24.0,24.0,BGGDDGBHHHHGHHDAGFAGFBBFGGFGEHBAHECFACAGHEFCEADEAEBAHBGBBACDACDHCDHCHBCDBDDGCFHHFHHAHEEHCGCBGAADFBGEGFCCFCGFDHHDHCBFDAADABBCBFCFGDECBEFDEGDEDFABFADFGBFGFAGFADHHEGABCFBGEE,False +422,5.0,3.0,3.0,1.0,0.0,2.0,1.0,4.0,ABCABCBGAHHHFHAFCAD,True +423,8.0,5.0,10.0,3.0,2.0,6.0,4.0,7.0,CAHCAGAAEDGFCGDCFHCAHCAHBBDFAFFGBFBBCCCHCEHAH,True +424,4.0,2.0,3.0,3.0,3.0,5.0,4.0,1.0,GDFGCGACDACDEBFEGHEFFAAFB,False +425,20.0,29.0,28.0,22.0,37.0,21.0,18.0,23.0,DCDEFDAGCHCHFDAFEFFEHDEDBEABEHBEBFCBEDBCDCCEGCEBCEAHDHHDAHGAHBBBFABFABACBADHEEHEEAEAAEACDCHBCEDEEBEGGEBEFDGCBBBAFDAFCAFCHEDBEDGECHBHGFGECEDGDFECFDCFGHECEEHFEBCABCADEAFEGBBHBFGBEHCCHBCGBEFCHHCHGGGGDF,False +426,3.0,6.0,6.0,5.0,11.0,8.0,8.0,8.0,ECEBAECEDDEBDGBGHDGEBGECGFHGFHACHFGHFCFBEFHHBHEADEFGCFE,False +427,9.0,21.0,17.0,17.0,18.0,17.0,9.0,12.0,BHBBHBBAFBCCHEBDECFECDEFFGHCEFCAFAEHDGHDBHABEEBEEDAECBDCECABDAFDHDGEDBBDBFAFFCCBHCDHDBFDGFGBFCHACDBCGGDGGCBFFBFEEFHECEED,False +428,13.0,9.0,6.0,7.0,7.0,9.0,7.0,6.0,HDAAECHEGFFGFGCFHCBGAADAADAAFABFBEEAFFBBCBBEABECGHDGEDGDABDAFHCH,False +429,8.0,15.0,19.0,18.0,20.0,20.0,16.0,22.0,FGDFDDFHDGAFGFHEBABCDBHFGHFCHACACCECEACEBCFGDBHFEHFBHGHHEHEBGEAFFHCFDEFDADDBDGHFBDFBCFBGAHFBECHECBECHECECCEDCHGEEGEGFDFEDBEHBHCDGDHCHHGGDG,False +430,13.0,25.0,20.0,21.0,26.0,17.0,24.0,16.0,EFFGFCDFCEHCGHDGEECAEBBEGBECFEGHAADDAFCAFCBCEECFFCFCAGDACHBHHBGDCGDGGDEEDBHHGCHEDBEGEECEEBEBBDBAEEFDGBGGBDAEDHEFCGBCGFCGAHGFHDBGGBFBFFHEHBCDBADCEDEBBGAAGHBGHBDBDD,False +431,13.0,21.0,18.0,12.0,10.0,10.0,17.0,15.0,GAFBBBBFHGFAFBGCGGBBCABCAGDHGDHBCHBHBAHGGHEGHDCDBCFBCGECAEDDHBAEBDHBDHBDACECGEGGDHADBEFCDBGACEAHBCFBEHAEHAFGCCGCCFFC,False +432,14.0,11.0,9.0,15.0,14.0,12.0,12.0,18.0,DFAFFAHDHEDFEHHEDHCFHCECBABBDGEFGEDCDCGDHHFCHFCGGCEGABGDBEABAAHAEBDEBHEGHFGHDHEBADGADBAEHCEHDDHBFAGAAFFGH,False +433,16.0,16.0,12.0,20.0,13.0,18.0,9.0,14.0,FDCFDADDBDDAHDCBDCDDCDAEHAFAABADBECFAFBCFADAGCAGCDBAFCFFEHFHBFBEHGCGGDFGDABDEECGGDFEFBHCBHBEHBEABEHBAHGAEFBEHHHFEHFDFD,False +434,15.0,21.0,15.0,6.0,12.0,5.0,12.0,17.0,CBBDBGABGCDGCEADBCCADEFCCAHCHCDHCAHCHHABHBBHABEFCGCBGAFAAHEAFGAEGAHGEEGHEGBFBEECHEBBAHHCHDBHBBHBBABBGEG,False +435,0.0,0.0,3.0,2.0,2.0,2.0,2.0,3.0,CHDCEDEHCGHFGF,True +436,22.0,21.0,21.0,13.0,7.0,14.0,20.0,13.0,BHBGDAADEDFGCFGDHGAGGAFDCCACCHEADBCFBCGBFABEHDCHCEGBGDAGAADCAHGHHGHFFDEHAGAGGABCAFAFFACHACGBDGBDCBDHAGCFEBFACHBCABCGFCAFGBEBBCBBCBB,False +437,18.0,12.0,15.0,15.0,9.0,15.0,19.0,9.0,BEAEFBCFAADCBFGDGGHFCADAADGADHCBHDGDBGDBGDCGAHEFHGFAEBAHBADGCDGCGFCHFDEFEHFCAAAFBAHAEGDEGFEDCCBCGBFGBFGACGCCADFG,False +438,9.0,15.0,11.0,10.0,6.0,5.0,12.0,8.0,CBBCECABBAHBHBCHGGEGGDAEBEDCDFADBGDBGDBGBBCDGABHCFGBFGHFGHFEAAEAABHDDCGCCDCH,False +439,21.0,34.0,13.0,20.0,9.0,14.0,18.0,22.0,DBGDFCCFEAGHBHHCHHCBHBGHBDABCCBAFBAGBDCBDBBGBAFFDHEHGCBACBAEFGHBGAFGCFBAGHAHHAGHGCDEAHABHBDFEDBDDADDHFBHFBEABEABADBHFHDBABBHBAEBGCDCFHGGGBBGFDGDABDABDE,False +440,5.0,7.0,4.0,9.0,2.0,7.0,1.0,7.0,DEBHHHHHHDFAAFGADHABBFFDFFDBEDCCCCFBDDBDAB,True +441,9.0,3.0,11.0,9.0,5.0,3.0,13.0,6.0,GCHGCHBCDDAEAHEAGAGGCGEAEHACDFBDBDGCDGDGGHGCFGCAHCACDGCAEFD,True +442,26.0,15.0,9.0,16.0,20.0,21.0,20.0,20.0,EEHEFAFDDHDDBDEEFFEDFCHFAAGHAEHADBAGHAGBADAAEABCGBCBBFGCFGEFGEFGHDEAEEAFHFGHDGFAGACGCHBCHEAHGABGBGADGFFGEEBCFDHAEBAGBADAABBHFHHCEEFFEDFHAHHAHADDGFG,False +443,5.0,11.0,13.0,10.0,14.0,14.0,10.0,14.0,FCEHCEHCEDGDBBDGEDHEABEFGAFGAFCCFHFFHFBAEEGDFFAHECHGCHDCHBGFEHFHFFBBCBBEHCHHBECDEDBEDCGGGDC,False +444,9.0,3.0,12.0,6.0,9.0,11.0,10.0,6.0,GACGCGACGBHABFCEFCEFCAFGFEGDCFBCHHHHGAAAEADCDGAGEEEEECFFCDFGDFCDFH,False +445,9.0,10.0,13.0,13.0,17.0,11.0,15.0,15.0,DGCDBCDFEFHEHHEDDEGCCFCFFCGDEECEFHHFAHFAEDGGBBGHHGCHGBACAAHEEHEEDGGDGGDGEEFEBGHBCDCAACAHDHBFEFCEDBHBBAG,False +446,4.0,1.0,6.0,9.0,11.0,4.0,5.0,7.0,GACEFGGACGDFDECDEHDEHDEHEEDAHDCDFCDBEHAGFCHEEHE,True +447,26.0,19.0,18.0,11.0,16.0,16.0,12.0,21.0,EEHFFHCBABHABHAEHAEHEFFGFAGHBHAEEAEEAGAAGCCGABDACECFHGHHEDHCBHCBHCBAGDABDCHAHEFHFHHDDFBFFAFCACABEDFEDAGDBFCBDAGFACEACAGHABBFBBEBACCCGHCDBAG,False +448,6.0,5.0,7.0,6.0,1.0,1.0,3.0,5.0,HADHAHCACGDGBDGBAECACBABDCHDBHDCCF,True +449,11.0,2.0,6.0,6.0,9.0,16.0,8.0,5.0,AGAAHAAGFDFEEFBEDGEGEEFEAFCCDEDFFGFFGFFCFAEFAFHDFCBHADHFGHACCAG,True +450,11.0,4.0,8.0,12.0,7.0,9.0,7.0,8.0,FDEFCADCGCEBAHBGECHEFHCDACDABHGBFFDFAEFAEADGADFEDHCAHGDHDFCDAGDAGH,False +451,31.0,20.0,20.0,33.0,22.0,23.0,32.0,17.0,BCCAGAAGFAGCEGDBGDACDHDHGFBGBBDBFGBHBAHECEECDEDHHDFADFEDCEGHAFBCCBFADGCBADDFEFGEHGEFGDHECAEAGEDDEBDEADAADBCBGEDHDDFCEAAHBGBGFAGFDGFDEFEGHBAHFAGFDGDDFDFABCABCAFCAFCAGCAHEGHGDAADAGEFGHDGCDGBGHCFAGDEGA,False +452,6.0,6.0,6.0,10.0,8.0,9.0,9.0,6.0,AFEABEBDGBAFEDHGFHGEDGEHCHAGHECHCCFDADDFEDFEBAGCFGFFGCBGDBDD,False +453,13.0,18.0,14.0,23.0,17.0,19.0,19.0,12.0,DCGDCDDCADEBFFBFFCAACDACDCCABCDDFDFAAEGFHFADCBGCDGEDAFGGEHHEFBFFBFFBGFCDFCGAGDDHDDHFEHGEBGHDGHAEHBGBDEFCBDDEABHAGEBEEBHEDEGBHGBFGBGEEGB,False +454,18.0,22.0,18.0,14.0,25.0,31.0,12.0,21.0,FHADBACFDHAHHDGHBFFFCFGCBGDHFFFGFFGFGGFAHCHEEHFHDFHFFHFAHAHEACEGEEBDEDFAFFBFFBFBEFDCBBEAEHDFDEEEBBGCBFCFCBGBBFEHGCDEHDECDECBADEAEEACEACECCABBECBECBFAFAGHEHHABHAB,False +455,8.0,7.0,7.0,9.0,13.0,7.0,12.0,7.0,AGEBFEADAAGFABFHDEAFFCGFDEHGABGCBHCBGBDHBDFDEGCEGCEDCEHEDHGDAGEHEEGCEG,False +456,26.0,25.0,17.0,12.0,23.0,17.0,8.0,10.0,BCAFCEBDBGCAAFAAFGCBEAEDDBADBADCHEFFEADEAEEFEEGAEGEHBEGAFHAFHDFBBAEACCAECBBBBBFABEABDBBDABDCEDFECACHFHAFHGHDCCAGFEEACEABFABFBEFAEBBGHBCHCC,False +457,17.0,13.0,15.0,8.0,13.0,12.0,8.0,11.0,HFCEBGABGABDAECBBCBBEBEEBFEAADACFHFEHFBACAACDAFHHFAHGAHAAEAHGHCGFCDFDAEEBDECCHCCFFGBEGCDFCBCAEDHG,False +458,4.0,0.0,3.0,1.0,6.0,6.0,4.0,0.0,FEEFEFFGCFAEAGCAGEADEFGC,True +459,21.0,25.0,18.0,16.0,17.0,17.0,23.0,17.0,HDAGCGGBBGBCEDCBBBEGFEGFEGFAFFCGFCBECBFFBEBBGBFABCAFAHEHEDHGDCCEAAGAAGBCGHCBHCAEDHHDFFDABEFECCABHABEDBEGBEGDGDFGAFEAGCDGCBHHDHCAHGABFDEADBADBHGAGAHFHGCHDB,False +460,10.0,14.0,5.0,9.0,15.0,9.0,9.0,8.0,EDEEGEAGEGBEDBDFGDEABFAFDAGEBBABDAGDBGFFHAEHDEABGBHABEACEFBDFBCHGCEBCEBEHHHFHCF,False +461,5.0,3.0,5.0,6.0,2.0,12.0,7.0,4.0,CEAFFGFFGFFDFHDFBDADACCGGCABAHGFBFFDGHDGHEFC,True +462,6.0,6.0,14.0,9.0,5.0,9.0,18.0,19.0,FGCDHCHHGHDGADGECGHCGCGHCEDGEFFHHFHFGBAHEFGBCGHFDHFHHCGHCGHEGBCCBDAHDHGBHACGCGFCDABDAG,True +463,3.0,5.0,4.0,8.0,5.0,3.0,5.0,5.0,DGAFBBFAHGEGGEGBECECCAHHDDDEDDHFDHBDCB,False +464,8.0,5.0,4.0,6.0,7.0,4.0,8.0,3.0,DACBACHAGHBEHDEFEADGGCFEDGEBGEAGBAGFDGFDAAEBC,False +465,13.0,13.0,10.0,12.0,11.0,18.0,10.0,10.0,DFBGFDFFDGBBBEDGEDBECEEDFHAAACAAHHHHHBGGAAAFHACDACEFFHFFHAGCBEFBEBAFGAHGDEGFFBFDBFDECCECCGBCDBFDF,False +466,1.0,7.0,5.0,6.0,4.0,4.0,5.0,8.0,DHBECBCDBGDBHDBHFHECAECFFGHDGBBGHCGHDHFE,False +467,8.0,10.0,7.0,7.0,13.0,10.0,14.0,7.0,GGBEGHAGEGBEDBCAFFBHEEAEFBEGCFGCFHBFEGFEBFHFCHFDGDDGHDGDCHAEGCEGAEDCEBAABABG,False +468,7.0,9.0,14.0,4.0,4.0,10.0,8.0,4.0,FECAECBDFBGFCCFECFDCBGCBGBFDAHGAFGBBEBCHBCAAHGAGCCCFHCFGCDAF,True +469,11.0,8.0,10.0,17.0,9.0,15.0,9.0,16.0,FHDFDDEACFHCFCAHDEHAGHACHDGBAGBEGBAGEHHDGHFEHADHAEFAGGCFECFBCDGDHHDADBCDBEDFFDFFCCBEDHFHAFHDFDB,False +470,1.0,3.0,1.0,1.0,2.0,1.0,2.0,3.0,CHADBEEBGHBGHF,True +471,17.0,15.0,26.0,18.0,19.0,21.0,23.0,27.0,GFFCCCHCDHAGAEGFGCBGCBFCFFHDFBDCHDGHFEAFEAEEAEGDHGHCGABGDCGDGGFFFACHBEAEEDEAHFAHDHHGCHFHHGGHBBECGECEEDAHCACCBBCFBCHGCHACFDCEDAHCAHFFFDABEEBCBAHFCHBHBGDGECGEHDHGDHGDFD,False +472,2.0,5.0,3.0,5.0,4.0,6.0,6.0,2.0,EGHFGBFEBFEDFHGCCFEABDADDBDGBGCFG,False +473,20.0,30.0,26.0,33.0,27.0,26.0,18.0,15.0,CGAHFAGFAFDBCDEGDEHBEGBEBFDGFECFHBFHBEEFEECCEFEFFHCDGAHABDFBAGBADBADBDGFGCDCABGAEGDDDDACFACEAFEBEGDCGCEFDEBEEDFEFFDABDHBDEBCHBHHFDDBCDFGDAGHBDABFBDDDFFBBACBCCBCABCACCHGCBFBDDEEBCGDCGDCEDCHFEHEAHE,False +474,19.0,17.0,14.0,18.0,11.0,17.0,20.0,12.0,GAGCCFFCGFEDEBFFAFCGDHGEHGEHGHGFDFAAFDADDADCACCBFBDGBGGBFEBCABDAGHGBDBBHFGEAGCDGFDCFCHFAGCBBABBABAEBCFCDEDHGHAEHAEDAEDGFDGDAHHAB,False +475,29.0,21.0,29.0,16.0,8.0,11.0,32.0,19.0,GGHBGAGFAHFBGAHFBHGBHGCEACHGBAAAFHHFHHCBGCGAHBDCCDGAAGHHDBDCBDFBDBEACAFCEDCBGABGAFEACGACGCCGBCGHAGADEAHGDCGCBBAFBADCGBEGBEGBAGCGGAGABCCHCDACGHDGEAHAADFCCHACDGCDGCDFC,True +476,1.0,0.0,5.0,0.0,0.0,3.0,1.0,0.0,CCCGCCFFAF,True +477,12.0,12.0,12.0,10.0,3.0,21.0,15.0,7.0,FDFAGACBDCBGCEFEFDGAGGBBDBBAFCADCADCFCGFCFFHFFHBFCCDAGAAGBFDCFCAFHDBBGHDGHFGBFBEFGFFAHGAGGFH,False +478,17.0,16.0,18.0,22.0,16.0,25.0,17.0,21.0,ACEFGEHAECACCHBGAFFBCFECADCEFAEDEFAECBCGBCHFGHGEBAEAADHGDGAFGDDCEHCHAEHDEFGHHHBHABFABFHCFHCFHCFBDFBHBEFFEDFCDBGDAFDGBHFBHAEDCFHBDDGADGDFCDFGDGBDGDFHDFHG,False +479,10.0,7.0,13.0,9.0,7.0,6.0,9.0,3.0,HGCDGCAGAEGAGCCBCCFCEFEAFEACGGCHDABDECHFABFEBEBADBDDBAACGCFDCDDG,False +480,1.0,0.0,4.0,0.0,2.0,0.0,5.0,0.0,GCEGEGGCCGCA,True +481,21.0,16.0,14.0,17.0,11.0,10.0,25.0,16.0,FDGEEGBBDHAHGDHBHGBGCBCCFACEAEGAHHDHBGFDGADAAEAAFHCFHDFABGCBGAGGADCHDCECEDBDACDAHDAGDBHHBAGFAEFGBFGBGHAGAAEDCBCEBHEGHDDBGGGGCAGCFG,False +482,12.0,17.0,21.0,17.0,21.0,22.0,20.0,24.0,HCBHEEHCEHCBHADGBCGBEEHHFGHFDHFCHCGHGGHBGCBCHGDDACDFFFFFGBACFECGCFHFAEDHDDBDDHDEGDECAGCAGHAEHAHFEFDEACCDGGGFGCEBCEDHFCHBHBEHDDABHFFFAFFBFEBEBBGAEGCEGCEBFE,False +483,19.0,21.0,17.0,13.0,22.0,21.0,20.0,24.0,GDGGEGFHAHAEHADHCEHDAACCBEFBEAAFFAFGHHBHDBFDFFACBGDDGDHHBACBFDHFDBFEFFGABDACDFFHGFCCAEBBHGBHBBEBGCDGCHGCHEFHEAHEHHGACCACGAHHEBGECGACFEEEBEFBCFEEGEHGEAGBFHBEB,False +484,14.0,17.0,19.0,19.0,23.0,9.0,30.0,14.0,DBADEECEEGGGCGGCHGAEDCGDCDDHDGGDEBHBBCAHHADGGGEGCECCACHAGHAEDABCHGGHAGDADBEFHHFBCEAGAGGDGGHGGACFFBFGCFGBBDBECBEDBGFEHDEBDEFHEBCEBAEGEECEGBGFCDECD,False +485,23.0,20.0,17.0,18.0,15.0,7.0,16.0,20.0,ADAADBBFAFFAFAAGCDHCHABGABCAGHBGHCAHEECBECGDHHAHDEFBGDGDBGDBAAEABGHBDCECCBGGHCEHBFABFABCACAECBCDDCBEEADEADHHDHDDGEHGEHGEDCBDCHAAGGBHHBHE,False +486,19.0,15.0,16.0,14.0,11.0,13.0,25.0,19.0,GDCGHFGHCBDBAAAAAACAGHBGADDCCHEGBCBDAFDBGDBDEAAGAHBAHADCDDEHHFHEAGCGGCGGBGHCGCBGCBDCGGGFEGBEDFHCFEBFEAFGAEGCFGCFGDEGAHFEHABFFBHHHHHH,False +487,17.0,28.0,19.0,19.0,12.0,13.0,19.0,22.0,DBDEFAHAGFBGHEGHDDBBEBHEBHDCHFEHGEHGBBACBAGAAGEBBHBDFBDFBDCCHCCAEBGDGDCEBCACFAEGAHDFCCBHCEHDEGCBGABGBDFHCFDDFDBFGAGGFHBCHCABDABHAHCAGCHGBBBCBHFDHADHG,False +488,11.0,5.0,10.0,9.0,17.0,10.0,8.0,12.0,HFEBAGAEFADDEHDEHAEHDEHAEDEEDGBCHCFECFBCHGCHGEDBEABGAHFAHFHEEGFHACECCADEDCEFCAFGFG,False +489,15.0,27.0,19.0,19.0,24.0,16.0,18.0,23.0,GDHCDCEEBEBBHABHFBGFEGDDHDFACCAGGADEBDEHABHAFHGBHAFCAFCBFCFHCHDEHDBBFABDEGCECHDDDDGEAGHAFHFEBBEAHCAHFGHABEFEHDHHDCGBEHBEBCCBGDGEBGEBEECEGBECBEBDEBFGHABHFFDGCCGBC,False +490,3.0,2.0,6.0,3.0,7.0,0.0,1.0,4.0,CBCEHEADEACEADEDBCGHHECHEC,True +491,14.0,16.0,16.0,14.0,17.0,13.0,22.0,10.0,FADFCGFCEFCEBCGBCBBCBBAFBGGBGBEEEFDBBDHEEHGHAGHAGDDGBEAAGDFCHADHGDHGHFBDEDDEFECCEGGGGGADGCBEEHDCGCCGABHDBFAFEEECCAGAFGAFCA,False +492,26.0,18.0,20.0,24.0,26.0,19.0,29.0,28.0,DCADFADCEHGDGGFGEAHEHHAHFCCCGHBAHEAECBBGGBHGBHDBAAFECHEBHGFHCAHDAHDAHACHCGHCAAEGGGDBGDGGDEGHHDCGEEGEDAEDCGFCDFEFFADHGBCABHDBEGBGBHCHFGDFEFFEBBEDBEAAEFEBFGBAHAAHECDGDDFDACCAFAEHGEDGEDCEHFGHFA,False +493,1.0,0.0,2.0,1.0,4.0,2.0,0.0,0.0,ECEECEAFFD,True +494,11.0,16.0,14.0,24.0,25.0,15.0,20.0,16.0,HFCEDHDDCEGCFADBEDCEDAFBACGFFGHDDDGBDFEAFCAFHDFHEFBAFBDEBEHCEDBHDGHDFAEFCECCBGGBFDBCDHAHBGEBEEHGGHABDGDGGDHADGAEEBFECEECGEGGEBEEBHGCHGDHGDEDE,False +495,15.0,21.0,13.0,15.0,18.0,25.0,20.0,12.0,GFGGDGBFFFDCCDGCDECAEFFFHCECCEDEEAEEBEFHDHBGGBGGEGHAGEAGBGEAFAHFACFCHGBBGBBCCDEGDFFFFABBBEBDAGDAHFACFAFDABDBBEFDEFAFBBFBBFEHHGHDDHBFGAFHEGC,False +496,14.0,17.0,8.0,12.0,24.0,10.0,23.0,11.0,GBFGBDGAFGBGEBFEHDGAFEBCGGGBABDAEDGEFBAFHEFHBFHEEBGEBAEGGEFGEABAHBGHBCFGEGCAGCEHEGHDDEBAGCAGBECDECDEGDEGDBDHEEHAEHDCAAE,False +497,8.0,11.0,13.0,8.0,7.0,15.0,9.0,16.0,EHBHFAFCAGEGGCCGCAGBAGHDFFCFHBHHDDHFCAECHDBHCBHAFFDFEHCGDFGAFCAFCGFEBBCBBCFHDHEDHFBHEBH,False +498,3.0,6.0,8.0,3.0,3.0,7.0,4.0,5.0,CHECBEABACCGCBGFHFFBGDBFDAFDEFCGBCHFHHC,False +499,7.0,4.0,9.0,5.0,5.0,8.0,3.0,3.0,ECEEFHFFACFAHAABEABDCCGFDGFCCFCCFGDABDCDEBAH,False +500,7.0,8.0,5.0,8.0,4.0,3.0,2.0,4.0,CAEFHGBDDBDDBDDBCGBCFDFDHCAEAEHBEABAAHACB,True +501,22.0,26.0,22.0,26.0,16.0,25.0,21.0,27.0,EBHCGHBFHBFBAEEAHFAHEADFGDFBFHCHCCHGAAAAAHAGBBBDBCHCEHBHHGDDFBEFDECDBFFHFFDDDDDFDAACHBDABDHGCEGCGHFGAFDCFGCFGBBGFACDAGHFGHEEAEEAHHBDDAABBCBCDDCDCGHFGHEBHABGFCGCEGCBCHBCHDGFFBFGEFDEHDBAD,False +502,10.0,11.0,12.0,13.0,8.0,15.0,13.0,13.0,GFHHEHDCHDEFDADGCDGBDFADFHFACFACACBFCGFCAFEECBECBACAFDEHBGGAAFDGHCBDCBHGBHDFHDHGEFGFHGFHDBEBGGB,False +503,5.0,6.0,10.0,4.0,4.0,8.0,9.0,0.0,FEDCEDCGBGGBCFCFEDBEGAACABCGCCGFFGFFDAGGBCABCF,True +504,7.0,14.0,10.0,11.0,12.0,9.0,6.0,15.0,BDBBGBFCEDCHDCHEFFECHGDEEHEDHDBCDHGABFABFBBDBBCEECHEGFAHCGFBHFAHFAHDCEAHBDCBDHGEHAEH,False +505,21.0,9.0,16.0,11.0,15.0,16.0,15.0,15.0,DFAGEAGEAFCCECCECFEGFHGDHAFBCHEDHEHBEAGFCHDHGAHFFCAAGAAGAAGAFEDGCDFHGEHFEDFBDCAHGAHBABEABGABEDFFHGFCEACHADEBCCBGFDCCHA,False +506,17.0,15.0,12.0,11.0,15.0,5.0,18.0,14.0,BHGDHFBGBBABHAEGAEDAEAEDBEDGCGHADCFEHAGHAHHAFADCBBGEGGBDBBDEHHHGGBGADGACHCEGCEHAABFAEHAECAECEECFBCGDCGBCGDG,False +507,23.0,16.0,18.0,17.0,15.0,30.0,19.0,16.0,CAHCHFAHFDGFDGEHAABDAFCAFBAGBHGHCDBAAFGFFGADAHDGDGGFEDFEDCCCCDHGFFGFFCHFAFEAFEFHGBEFEEFEECDBGGHHGHCEHEGCADCEBAFBFDBGBCHBFFBFFBCDBDGAGFABEAEAAFFCBFCADCADHA,False +508,2.0,2.0,6.0,5.0,8.0,2.0,3.0,4.0,AECAHCEDEEGEDCFFCBECDDGGDHECHEBH,True +509,10.0,15.0,13.0,10.0,20.0,25.0,8.0,14.0,BFFFFGHDGHBEECGECGEHFEFAGBHGBEDEGAEAHHFFHCFCFFHEFADFBCEHCEGFAHFHEFECBDCBDABDCBFCBDHBEFCEFCHFEBEBFEAFACFHFBAFEADDDBE,False +510,9.0,6.0,15.0,8.0,8.0,15.0,8.0,4.0,CGFCHFDFCDFADGADECCCFCAFBFFCCFEGFDGFCGCCEBBEAEEAEFGHDGDFCHFEFAGDABBCBCAHA,False +511,1.0,1.0,2.0,5.0,3.0,1.0,4.0,3.0,GDDGCBGCHDEEDHEDFAGH,True +512,16.0,13.0,8.0,20.0,20.0,20.0,19.0,18.0,GEEGAEDHBDFBGBGGHGEEDHEHEGFEGBEGFHGEDBBAHGFDAFDAEDGFFHFFHEEHDEHDGDGADCADFADABFHDFCEFCHFDGAGABHAFHGHCBFCHEHBEAAEAAEBCEDFGABDCHFCBFDFDDG,False +513,2.0,0.0,0.0,0.0,3.0,1.0,1.0,4.0,HHEHHEAGAFE,True +514,16.0,32.0,27.0,32.0,20.0,18.0,31.0,18.0,FFCEHGEAGHCGDDGHDFEDFDDBDCHDAABHAGDEGDEGEFCBDAEABBAGBCGHEEDCCBCCAECAGBDFBCHGHHDHADGGGCCFFAGBGFDGACBHCBDAEDBEDAGDHCDGCEGFGCEGDADDCHBGHBAHBEGBEFBFGBHDHGEBBDBBFCCCDEBDFBDBBGFBGFBGFBGFHDBCCCEBCGDCED,False +515,26.0,15.0,26.0,29.0,17.0,18.0,23.0,22.0,GFHDAEAAEGAEGCEDCDDCAHCABBAEBECGEBHHGAADFECFBCFECEDGDDCDCGDBDFGCGHDAHFADDAHCADDGDFGDEAAGAFDHGCHDCBDCGCBGCBFABGAHHBHDFHDFDDGDCFFAHBEHECCFCBACHACEGCEHHBHFGHCGDAGDAGECBFHAAGFFDEAH,False +516,12.0,12.0,20.0,17.0,22.0,17.0,13.0,11.0,EEBEADDAFDADAHHEEBGEBFFBEBCCDFCEFCEFCEFCABEFHEFCEFGFCGCGHCHDCGFBECACAGDAHDGGDHFDHADEADBFHBFABDHECFDCHCEGGDCDDCGBEAFEBECGECGE,False +517,17.0,18.0,11.0,13.0,13.0,9.0,14.0,20.0,BEFHACHEDBAAHAHHAGBAGCGGHAADEHDEHBBHGEHAEHGEDGEBCEBCHAAHBCHADHCDBGFBGHAABBFFFCCFACBGDBGDBFDCFDCBEHFHHEGBADEDHEGGABD,False +518,20.0,13.0,17.0,15.0,17.0,19.0,27.0,13.0,CFECBCGACDECDHCHAGGAGGAGGAGEAGHBGFFGHHDEHDHDDGAAGDDGDHBEFDAGBABEECEAABAAFAGFGDFCDCEFGECBCGGEGHEGHBGEFHFFDCCAFGAFEAEEFCFACFGBDCBCAHGBEGFDFHBFB,False +519,4.0,10.0,8.0,8.0,7.0,6.0,3.0,5.0,EABADFAHCBFGDFCDCCBACBEFDGBHGBHFEHFECEDHBCCBEDBEDBD,False +520,21.0,21.0,12.0,9.0,4.0,4.0,12.0,8.0,FAACBBBAABGAFADBABBDBBABHACGACBABBHHCECAACAHGDHGABCBDABAGBDGDAEDGCDGCABFEHEAHFBHGADGCCGBCGB,True +521,7.0,6.0,5.0,6.0,9.0,6.0,4.0,9.0,HDFFDAFDAFBFEAGABCHCHHBFHBGEBHEHHEHEDAECEEGACDECDBGA,False +522,7.0,13.0,6.0,12.0,9.0,15.0,17.0,9.0,FEHCDBCDGGDGGDHFBHAEFDEFDFGEAABAFBHCBEFBACDGBDGHHBFGDFEDEEGGBGGBHGFGFEGHCFBFFBGFGHBADCAD,False +523,13.0,18.0,26.0,23.0,24.0,18.0,20.0,22.0,HDCHAFHBBHAEFFCCGDFGAFCFDBHGFGEFBEGCEHDHHEGCEGEDBDDBGAFHCFHCAECHBFHADHFDHECFBCBBEEDGBCGEEEDGHFGECCECDACDGFBCACCDDGDDEBDGBDGAACABCABCFBEFEDHEDHDGHEFHECDECGAHGEHGCCBH,False +524,23.0,26.0,27.0,25.0,18.0,14.0,25.0,20.0,AHEABADDECBHGBEGDCHHCEDCECAFCACEFEEGGDGGDGEDGCFBAEAHFGDFCACHEBDDBADBADBDDACFAFAGCBBHBGGFDBFDGAAGAHGDHFBEEDCCDCBACHHCHECFDDHABAACAAGHHGBGGBGFBGFHDCBDCBHBHHCDFCDEBGHBGACGCCGECBBBEE,False +525,9.0,5.0,7.0,9.0,10.0,14.0,16.0,12.0,GDEGFEHFGFFECEBCBHHAHAGHAGDFCDHBDAFFFGFGGHBDHFDCFDCDGFEGEGCEGAGAAHAGEGHEHFEHFGCDBA,False +526,21.0,20.0,28.0,24.0,24.0,22.0,22.0,28.0,FBFFHFFDFEBCDDDFBEABCGECGECFHFFCFDAACAAHAHCDHGHHFHCBHBDHGDGDHAHCDHGABAABGCGAAFBGFCDFCDFCABEHDEAGHABHEBAEFHCAEABHGHHACFEGEEFEEGDFGDCCDCEDHHGBHGEHGECGDHDDAFCEBDHBGGECBDCBGCAGCEBCECEBCEHCDHEDF,False +527,20.0,11.0,8.0,13.0,17.0,8.0,13.0,14.0,DDHGDHCDHDDHEGFEDECAEHFFHAABEGBEHBCAGADGACFACECDEAHGABBCEAAEAGFABAABAHGFHEEGGDCEBAFGFHGAEDHEDHEABEABDHBG,False +528,9.0,13.0,8.0,10.0,8.0,6.0,9.0,7.0,ECDBCHEGHFFBEDBGDBHDBHDFHFEBBCDFDACACCBEHBAGBAGFDGADGACHABDAEABGGEGCEB,False +529,2.0,5.0,6.0,3.0,4.0,6.0,5.0,4.0,FCBFCBFCDCHDEHBFGFFGAEAHEGBCGCHDEBG,False +530,5.0,3.0,3.0,2.0,4.0,2.0,5.0,5.0,AFBAEGACGFGHCEHEBGEHGHDAHDACB,False +531,14.0,18.0,15.0,23.0,16.0,17.0,15.0,32.0,HBAHEDHGDHCDHDEHDEHDEHDHFAGADFEEHBBDFHDAEDEEHHHBHDFHDFHCFCFECABGGBEGCEBFBBDBDCCHCAACFACFHEEHCHHDHGFHGFHDCDDBEBGHAFFCGBAEBAHBGHAGFBGAHCFFBDGDCBDHGHGDHA,False +532,8.0,6.0,17.0,12.0,9.0,14.0,14.0,11.0,DEGAFHFDCCDGCHHBHCFDCFDCEGGFHHCAGEGBFGBDGDAGHCGCCGDCHDGEDBEFFCFDCGHCEHEGHACCAFAFFDFFAEBAEBC,False +533,15.0,11.0,12.0,12.0,16.0,22.0,21.0,18.0,GAAFFACGGFHDCBDFBAFBAGEAFEBFGGFDDEGFEACHFFBDFGEGDFFAHFHHAHHEHHFHFABECBDHHDCHDGGDGGEFGEHACGACGECEECEEBDBHDHHFHEFGGCABCAFEFCGGGBA,False +534,6.0,6.0,12.0,13.0,5.0,12.0,12.0,8.0,HDGAGHFGHFCHABHFEHFACCCBCEGCGDCDEADCFDHGDGFDGFBGCDCHFFEGFAFDDFDDGADCBECBGB,False +535,22.0,16.0,25.0,15.0,17.0,33.0,16.0,16.0,FBFFEECEEDFEFEEBGGDGFEAAEFCGFDGHDGDEGAAAHACFECDACDCHFCHFAFFAFEGFBDFECHHBACBCCACDAGFGDFEDFCCFHCBCCFACAAGADGHEFFCBFHDFCDHBHGECAFFGBGBFGAAAFBHFHHFEBFCDFCBACBHCBHAB,False +536,20.0,17.0,26.0,15.0,22.0,17.0,17.0,16.0,BHHBAFEEFAEFAEDBBDFEEBCEHHAAHAGBDGBHBECECCBFFAFEACEGCEFEECDDDGBDABEEBEHAAHCFCCEACDAHAGHBGFACFHCGHCFCCBCFGHDHCDHCDGCEAHGAFBADGGFCBFCGDCGCCFADECDGGEGAEB,False +537,13.0,10.0,5.0,5.0,10.0,8.0,9.0,7.0,EADEDEAAGAEEBGGHHBFFBFEBFBBDEAHEABCAHCAEFAGDAEDBFFGFAGAHGCHGHABCGBC,False +538,10.0,10.0,16.0,12.0,12.0,14.0,12.0,13.0,DFCGBCDFCDGBDCFCFFCFDAHDCBECEEBEDBEHECFECGAHGDHEAHAHHGFHGDHFFCGGCEGFGGCGCAAHHAEHCBDFBDEBAFADFAEBCBH,False +539,2.0,2.0,4.0,2.0,0.0,2.0,1.0,0.0,ACCFCAFCBDDBG,True +540,3.0,8.0,6.0,4.0,2.0,10.0,5.0,6.0,FGBFBFDBFDBFHFFGCEAFHCCBFCBECFABGDGHDGHBHHAC,True +541,4.0,4.0,3.0,5.0,9.0,9.0,6.0,7.0,HHFDFBDFAFFAEFEHGEHGEBGEAHFDEBCGHGGFEAFDDHCEBCE,False +542,1.0,6.0,4.0,1.0,3.0,1.0,2.0,0.0,EGEEDACCFCCBBBBBGB,True +543,11.0,8.0,11.0,8.0,8.0,12.0,13.0,10.0,CGFCHFHAFHGCGCCHCGHGACBDDBCDFADFADFBBEDAEGACFAHHGBHGDAEFGEAGEABHBGFBAEEGEHDFCGFCF,False +544,1.0,2.0,1.0,1.0,0.0,0.0,2.0,3.0,GDAHBCHBGH,True +545,20.0,18.0,24.0,26.0,24.0,22.0,18.0,33.0,CBHDDADAHFAEFCEHCEHEBHCBGCHAAHAFHFFEAFDAFBEEGHAGDDDACDHCEECEGDEGDEGBADBEDBAACEECHFBFCHFHHEEDBHHAEFCCHHFDBFDHCHHAHHAHGCHCCGFCGBGGFGDFBHFDGGDCEDADDADCFBCHBCBFHEHBEGAFHCCBEFFHDHGAEGDBGDEHD,False +546,29.0,23.0,21.0,19.0,21.0,27.0,25.0,20.0,BHEADFCDFGBFAFFACEAGFABFACFACFHEBHBFHDFGEGCEHCGDCDFCACAGDEBDEFAEFGEGGHCEHEAFEGECAAGAAEFFFFDFGGGCDGBGEBGHBGEBADFGCAGEADDBDDBACCCBDBBHAAABAHBACGECDDHGHHGBFEACHBFHEDCFDAHEAGCBGBAHFAHFBHFBH,False +547,8.0,14.0,13.0,15.0,21.0,12.0,10.0,20.0,CHCHGGHDDADDEGDBGFHCBECDEFBGHEECEGCFAEHHEHHCHHCHFFAAEDAHDEGBEHAAGBEHDEDBCFFEFCEFCHHEHBEHBEHEDDEGDGABCEBDBBCBFFBDF,False +548,5.0,4.0,1.0,2.0,4.0,2.0,2.0,2.0,ACBADGEEGEEBAFBFHDAHBA,True +549,14.0,13.0,9.0,11.0,17.0,24.0,19.0,14.0,EHAEHGEDBEDCEGGEHFBFBBGBGGFHAFHBFEACBACEADGFEACGFEGFADHGDAGCBGHGCFEBAHBGHAHADDAFDHGGHGFFGFFCFFEAFEGEEFFHFDBBDCBEHFFDFAEFC,False +550,8.0,20.0,16.0,21.0,30.0,20.0,19.0,15.0,FHEAEECEEGBBBBBHBBDDCDDCDBCBFFEGFBCEHEEHEEBEEHFDCEECGBBGAGAHCAFCAFGDEGCEFEHCDBEDHGCGFFGEEGEECBEFEHFHCDHBDFDDGGDHEFHGDECDEHEGACFAFFGFBGBGAFGDDDDDBEFBH,False +551,8.0,3.0,13.0,5.0,6.0,13.0,5.0,7.0,BDFEDFGCFCHFCGCAFFAFFHFGCAGHAEHCBCCEHCHDCADCFFAEFCCDHGEFAEBA,True +552,10.0,10.0,17.0,16.0,16.0,11.0,4.0,13.0,CABEDBDDCCDFHBACBAEEDFGACHECHECEDHDDBDDHAHCBHEFHEFHEDDGACAECHEFBEFDEDDHCBHCHFGBFEBDCFACEGCAACFCEF,False +553,29.0,25.0,19.0,15.0,29.0,33.0,22.0,26.0,EABECBEDDEFBHACGBHHEHFFAFFEDBAGFCHDGEDEHDGDDCADHAFFABHCFEEBAECAECHHHACCAEABEABCCECFECEGCHGCFFBFFBEFDGGAGAECHEHHDHHABDEHAEFFEAFAFFAGFHGEAGFFGFAACAEFFEGBAABFGBEGDFHDFHEFBBHDHHGHBCABABBFBBGBGGEAGBFGCFH,False +554,19.0,13.0,14.0,11.0,11.0,13.0,12.0,8.0,ABGABGBBFEBEDGCDFCEAGEAGHAGFAGHACHCDHADCADFGDCDDAFEGFEDHHAGCGCFDEHBEFCFFCFEABGABFCHEBABBACADEAFBABACC,False +555,4.0,7.0,2.0,2.0,5.0,4.0,2.0,1.0,ABBABDFBHFBEFEGBAGEAEEFDCCB,True +556,33.0,24.0,13.0,22.0,28.0,22.0,18.0,30.0,EEFABBCDBADEGEHHHCAHGEHABDDBDAGAABDGBABBAGBEBHEFDEDCHDAEDBFHEAHFAHFABFCBEHBEHAEHCHHFEHBEHFEFFHAFHAGHEGDDHBCEDGAFGECHHDHFAEFAECAGAGCEGADDAEBABAAHHAHGAHFEEECAACGFCDFDDFAFEBBGHBGBAFBEHDFGDCGDFA,False +557,21.0,20.0,17.0,15.0,9.0,13.0,11.0,17.0,FFFCCBHDBHDBDDBDDHDCGFBAHBHCCDAADHAHHADGADCCHBCFECEACECCFDABDCEHEHHEBHDFFABAABAGBEGAHGACGCGGFBBHBAFBABAGHAFHFGCGDEFBBCABAAE,False +558,17.0,17.0,12.0,11.0,13.0,15.0,10.0,21.0,AACABFAEFAEGCEBAFBFHBDHEAHEBEEHDHHBHCBFGAFGFCACBFBDFADFCDBHHBHDACECHHDABGBBGFGHDACEBCEBCAFHDEBDCAAHHFHHFGHEGAEGHFGHD,False +559,14.0,31.0,29.0,20.0,24.0,28.0,19.0,25.0,CBHCBFCBGABHAFHAGDBEEHABFAEDGEDECFFCBFDFFDEAEHDDCECEHCBACBDFBCEECGGCGFCFHEABDABDGBDAHFHHGADGEFHDGHEFHEBBEBGCBFBBDCEGFFAHGBHAFFGFFHEFHCCHBBHFEHGBDDHCBCFBCFBCADCDBCGCCBBCBECGDCHDFHBGHFGFCEEHEE,False +560,11.0,11.0,9.0,9.0,7.0,8.0,12.0,11.0,FDCFDGECEACDHCFAFGAFAFECFCHECHABHGBHBBHBGEGGAGGAFDBHDCHDBEDGABEAGACHBHDBDABGHG,False +561,17.0,20.0,22.0,24.0,12.0,25.0,33.0,19.0,GFGGFCGFGDHGBCGHGHHGHCGHDGCGCDDCHGCFGFAHCHFDFCDEBDEBGFCEFCFFGAFCCGCHACBFDFGEEBBDDBECAFGAFGADGADGDDGADGFDEBDBBDBGCAGHGGDGGBBDFHCCDCEFABHHBHEEHBDHAFAGEAGDABFAHHAFBFGDCEBCBFFA,False +562,11.0,10.0,11.0,8.0,5.0,15.0,7.0,5.0,GBAGDDBFDHFDGFAACAACBBGFGEBGFFCFFCEFBEFBCBACFFCAHCAHEEDBAHFCFFCDDAGCAHDB,False +563,20.0,11.0,17.0,13.0,14.0,9.0,14.0,23.0,BAGDHGEHCAGCGEFAEFBCCHCCBDADHBDHADHCGHAGAFEAHHAHHACGCEACAHCDHBDGGDFEBFHHDHHCAHGAHFEEDGFDECDHHEHACFGHFECEGBBCAACAABDABEGBE,False +564,25.0,13.0,20.0,11.0,13.0,16.0,8.0,5.0,AAAAFFCFFBBFABDAGEAGAHGACCFEFGEGAEAACACEFCFFCDCHFBBCBCCADFBHFDCCBGABGCBABBDFACAAFGACACDEEDECDBDAEDAHDAECAECEEHF,False +565,28.0,15.0,20.0,25.0,16.0,15.0,18.0,16.0,AADAACACCACGGBEGAEGBEGFHCHCCEBCEBDBBDBCDAEDEBDABDFFHHEAADAHHGHGBDGCAGFADAADADFHEFHFGDEBDFCAFEHFBBFDHCDADDACDHFHAGCGDAGCABADCADEAGEGCHDDBDCAGFHGHCGAEFFECE,False +566,7.0,8.0,2.0,9.0,6.0,8.0,0.0,5.0,HEFHDFDDHDBEDBEFBDBBECBAFBFDAFHAFEDDBCEAAAFHA,True +567,12.0,8.0,8.0,9.0,5.0,12.0,6.0,5.0,DADDAGBGGBCHFGFDAFCACAEFADFGBFABCDDFEDFECHECDBAEAHCAHBACBFFAFFBGH,False +568,27.0,25.0,25.0,24.0,19.0,25.0,34.0,18.0,GGBDADGGGAGEFFECFEBGEADDADDAFHBBHBCFBCGGEGEDHDHBDFBACBGCFACBCGBEGHHGCAGHGBAFAHHBFHAFECHCABFGHCDHEFEFCEDCEGBGGDAGFFGFFGAFBEFEAFEGFDBFCAGCAGCABAHHHCEACBGEBDEAACCFGGFGDBGDCCDBEGBCDFADBAGBADDADHCDHCDGA,False +569,17.0,19.0,19.0,27.0,20.0,24.0,19.0,16.0,DCECCEHDBFDEDGEAGFGFBCHBCAGAHGFDAFDBHAGEADCHDCDGCBHCEFCHFCGFAADABFABFEECGFHHDHBDEBDBCFEEFEEAECGDBFCBDHBDEBDAFDAHCGDEBDEHDFADFDDFGAFEFCAFHDBEBBDGGACDBCHGFFGFGGEGH,False +570,14.0,23.0,26.0,22.0,21.0,32.0,13.0,35.0,DEACHFHFDHEHFCHFCEFBFHBECFECHDGEDFFDEFHFBCCACCHGDFCHFEHCAHCHHCEHEEHCHHCAHDDGFBHCBEAGGDBGFBEHBHFBADBFDAFGGGABHAGHABDFBFHCFDCFDHEHCEAAEGCBGDFCFFEFDBFBBFBCHBHDBEDHDDBAFFCFHAEHCEHCBHDBCDEGFH,False +571,12.0,18.0,32.0,29.0,10.0,22.0,15.0,20.0,DAHAAEGCCHHEBCEBHDDGDDFFCCCCCHCFHDDHDHADBEFBECBCDBCDFEDGHDHCECGACDAEGGDGDBFHCFDGDDGAEFDCFDAADAADHBCBBCGEDBBHCFHCABFDHFBFCBCCBCCHCFFDGCGGCHCBFDFFDFFCFHHBHGFCGD,False +572,19.0,12.0,16.0,19.0,24.0,11.0,17.0,21.0,AEAGEAEEBDEGDECBBDAHDAFECHEFHGFGGDEHDECGGCAEHEHHCBHDDHDEGCEGAHGFEGEEGEECFADFEDEGCCABAGBAHAHHAEHACACHAFHBCBBAEAFBHDDADDGDBFHGCHFCHCCGFDHDDBE,False +573,5.0,2.0,3.0,2.0,1.0,4.0,3.0,2.0,ACEFDDFABGAGGACFAHFCHB,True +574,17.0,18.0,22.0,17.0,4.0,9.0,12.0,14.0,CCBCGGAHDAEDBCFCCHCFACFAEDAHDAHGBGDFDDCACAAFBBDDBDBBFCBECADDACBFCBHCHHABCAHGBBGBADDACHAGHDGHDHBEHBGBGGCFDAGCCCFHC,False +575,13.0,19.0,23.0,32.0,16.0,20.0,25.0,19.0,GGDDGDDCHDBGDFDDHBBHGBHBFHCEAFEHFGFEGEGGDGDFCHFAEFBCFGHDGDEGDBHDAAGHDDADEBCEGCEFCEFEDBACHAHFDEFCGFGHBBBABDCBFCHDCFFCHDDGDDGECGEDAAHAADDAFDCGCHBCGBCEHDEGFFHBDCBDBGCCGCC,False +576,9.0,9.0,12.0,4.0,5.0,6.0,12.0,11.0,BHFCHFGHEGHBGEFHADCDCGGCFGCBDABAEBACGHEGFBGBAHCDHCGHAGEAHHCCFCBGABCA,False +577,6.0,7.0,11.0,9.0,9.0,12.0,13.0,8.0,EDDGBABEGCGACGECECCBCCHGEFDEFGGFGBCGDAGHGCHBFGBFDEFCFFAGFDHBDADFADFHHFHEEHC,False +578,0.0,1.0,2.0,1.0,0.0,2.0,4.0,0.0,GCGDCGFFGB,True +579,5.0,1.0,1.0,3.0,1.0,1.0,1.0,4.0,HGAHAACAAEHDFDDHB,True +580,23.0,6.0,7.0,14.0,17.0,10.0,20.0,6.0,EEAEEHDHGCBEABGFBGEACAADADGADHCGFGGEHGAGGDEAFEAGEDEAAAAAAEGCFGDFGDEGAEAFBAHBAGDFGDFECCECGDBAAGDEGHAFDDF,True +581,26.0,18.0,18.0,18.0,15.0,22.0,19.0,23.0,FFFAFECGECGHCGACGACAFFGHGEHADHFDHBDHCACGABGAFHHGAFGABDABAFBHEBAEAHFAGCAGCGFAEDGHFGAEBAEHDDHBDFAFBHDBFCHEHHGFDDBAEHAECAHGHECDFDDHHBFHBFCBADFFDCCDBCABGEBCEBDEGAC,False +582,21.0,17.0,16.0,25.0,18.0,9.0,13.0,8.0,GAHDCGBCBACDDBDGADCEDBFDAFDADEAEEBEHADFAHEGDBGFHGHCBAAHDEHEEACDACDECFEAHAGGAEGAEFADBGEBGCDDCFDABDCCAGBADBDFFDGDECDBCDCCEEBBEBBA,False +583,3.0,13.0,7.0,7.0,6.0,7.0,7.0,14.0,CGGBGGBGFBHBBHCAEBHEBHFFFDFADCDBFEBGCBCHHHDHHDBHEGDECBAHFDHBEHCH,False +584,19.0,16.0,23.0,16.0,22.0,21.0,12.0,29.0,CGHFFHFFHCFGDFDEECFDCDDABFAEAADFBEAECAEGAECHHCHAEHFECCHGCHGEGGEDHBABFAHEEBGEHHHBHHCDBCDBADCACABCBCCBHBGHDFHBFHCABGDCFCCADHAHHEHHEHFEABEGGAFDFEEFEAFCDDEHFBHCHF,False +585,5.0,14.0,11.0,11.0,4.0,5.0,12.0,10.0,DGDBCBFGBDAEHACCEHCDCCBHFBHFBHCAHGGGCGGBGCBEDBGBAGHFCHDCGDBHABEFBDDBDDHG,False +586,11.0,24.0,18.0,11.0,8.0,6.0,17.0,13.0,GBBGABCCDDEGDFGAHEAHCAEGBEGAEABEAHHCHBBHCBHCBGGGGGGBHCBCCBDDDCGGBEFFADFGBCABGBBDCBDBHABHBBHFBDFCHCBGDHACCCEC,False +587,14.0,18.0,17.0,13.0,15.0,17.0,25.0,21.0,ECCAFEAGBAGCGFCGHADHEBGCGGCBDCGABDHBEGBCGHHGFHGHHGHDGCACAEHBBBABGFHGFDGFDBDGBAHHGGBCEFCFHHFEHFEFFAFFAGFCHCHGABCHEFHCFEBDEBDACGAEGEEHBBDEDDGD,False +588,13.0,15.0,14.0,18.0,15.0,14.0,13.0,9.0,EFAHGBHGDHGDCADGDDEEEECFACDGDGHCCFCEDCBHFBGDBCDBCGFCGBCEDDEAFEAECAFCDFDDBHABHFEEBBHBACBADBGDEABFGFFADGAGFAEFEBH,False +589,12.0,8.0,10.0,3.0,6.0,15.0,8.0,10.0,FDAFCFFHFGHFGBFHAHAADACFCCBBCBBHADHACFAHBBCGGEBECHGAHEAEEAFFFCFFHGFCGAEG,False +590,17.0,15.0,7.0,14.0,11.0,14.0,9.0,6.0,HEAFCADCHBHAFEFFEDAAFBABCGDDFAAGDGDCBEBFEBDEBAEAEBAEBAFBGFBHFCGCHGHDGFAAFCADBDDBDDGFAGFABEDBE,False +591,10.0,3.0,10.0,5.0,10.0,14.0,7.0,11.0,CFGCFEAFHGFCGAHACGFEADCAECAEBEDGFDHFEHFEHBEHFECFAAFHAECDHGDBFHHFAHCCFG,False +592,19.0,16.0,12.0,22.0,13.0,29.0,15.0,13.0,GHBEBBFBGFCCFDDECDGGDFGAFABCHFAFFABBCHBAFGHFBEFDEFGEFGDDGDDACDBCEAFEACEDDFFAHEAEDDHHFFDFBGFHGDBFHECCCFBDEBAHFAEFAGFBGDHADAFDAFDAFHAFGAGCHDB,False +593,7.0,6.0,8.0,6.0,8.0,9.0,6.0,6.0,DCHBFDCFDGACEACBBCBGHAGHFEHFEHDEGAEAACGFBFCHFCAEDFEBEDGF,False +594,30.0,31.0,17.0,16.0,20.0,23.0,18.0,23.0,ECHGCHGBBGFBGABGCDGHFFBFABDADAFEAFEHGBAABEABHABHACFACBEFADDADFBCGHHABFEBEGBCGEHFEFEBGEHGDAFBHDAFBAHBAHFAFACGDCHDCHDGBEBHEFEAFEDHACEBCFBCHBFHBAACFCBAHGHDDEADHAECACGBBABAFBFEBGEHGD,False +595,9.0,14.0,16.0,12.0,7.0,14.0,15.0,6.0,FEGFGGFDBAGEFGEFCCHCBEFBCGACBACFCCBCAFCAGGFFCBHGBHDBADADHADGBDGBDEBCHFCFCCGBDGDHEDADDFEBGGCFB,False +596,26.0,34.0,20.0,24.0,21.0,26.0,22.0,25.0,FEEBEHGEHEFHEFEEACGABBDHDDHGCGFDACBGBHGFHDADCFGCGBDAHHCFHGFEEFEAHEBHGBAABDABFAHFHDDADDFDBGGBFHBAEBAEBAHBAFACFADADDAGGBBGBBCCACFFBDFHDFHDBCBCABAECDFGDGHHEECCAFDBDEFCEFGDBBHBBHGGHFBHEGGEBCABCFBCFCAHBA,False +597,16.0,18.0,17.0,23.0,22.0,17.0,16.0,28.0,EECBEAGEDFCFADAHFCHFCHECDBGDBHDCHAAHDDBDDCDHHFHBAHBEHDEHAFHAHHEEGEEGDEBDEDDHBEBGEHGEHCACFHBDBACHECEBCACCGCGGEHHDHBFGEABFDFFDGFAHCGHCFHBGHGDABDAFGBEGFDFBDEHFA,False +598,14.0,9.0,12.0,11.0,20.0,14.0,7.0,8.0,EEAFAGFHFFBEAGHBCFFFFDFFBAFCEGEEGDCGDCBAADAHFFHAGHACDECBEDBEAACDGCEACHDDADBECBECHEAHFDEEEEEEEBC,False +599,31.0,15.0,28.0,34.0,25.0,28.0,16.0,23.0,EADADBADCDDCGEGGEAFEFGBDDCFACDECFECFBCHAEHABGFCCAECDEDGCDGCDGEAHDBBDBACEAFBFEBEDBEBEEFGAAGADGDFFCEFAFAABDFHDFHDGCDGHDFCDFHEFAEGCFDAFDAFDEFHBCDAFEECHHDDHDCFFAHHHHCHADEADADBADBCGCCHFAFCEHHAFHAHHAEGACCCH,False +600,10.0,11.0,5.0,10.0,8.0,10.0,7.0,10.0,HBFHBHGFGEFGEFAAFAGFGEBBHBDGBHHAHCDHEHBEAFDDBBABDFDCFHEBCECCADGADFADAED,False +601,1.0,4.0,4.0,5.0,1.0,4.0,5.0,0.0,EGCDDCBDCFDFBGBDGCAGFBGF,True +602,4.0,2.0,2.0,6.0,6.0,0.0,2.0,3.0,EDEEBAEDHEAGEABCHDCDDADGH,True +603,22.0,28.0,15.0,26.0,22.0,27.0,16.0,24.0,EADBBCFGEFEAGAFEACAHCDBABGHBHAEDGGDCGFBBFHFCEFCEFEDAEGEHGABFHBFDBGDBABGGCGBCGBABHAFDDFBDFBGFHFCHFCHFHECHDFFDFABFDBHDFDCFDCABHABHEHADCDDCDHFEEDAEDFEBHHAFHGBHBBEEBDHDHEDABDABAEGEEHAF,False +604,21.0,11.0,14.0,19.0,11.0,12.0,18.0,29.0,GHHGHHAHADHAHCGBCGBDGBDHDFAABAEHFCDDAACAFHBHHDEBEGAGGEBGEHDEGFGGCHGDBDHHDAAAACFACFHBHEAAEHADHGCHGHDBCFHEFHEFECDDHFDCGDFGAFHAHHCHBCGDCAD,False +605,9.0,11.0,6.0,10.0,8.0,6.0,9.0,4.0,DCGDAGDABEBBEBGEBGDDGHAHHBCCECAHAFFAEDCEFFEDCBGBBGEGDFGDBAAFDAB,False +606,28.0,22.0,23.0,19.0,24.0,23.0,22.0,23.0,GHDEEDGFDEHCEBCEBAGAAGEGGEGABFHGFAGAHGDCCDHFBADBDDBCDBFHFDGEEGCEHFFHCCHAGHABEACCACDFEEFAFGEFBCGBCBFAFFBFFDGEEGBEHBHHDCACFHCACAABAABAECCDFHHFHBDAEFHEFEECGFBGCDGEHCBGDBAAAHCAHDEHDBHABAAG,False +607,13.0,16.0,14.0,14.0,17.0,12.0,10.0,10.0,BGHBGADGDDGCECBEDBECAECGECGECFACFBEEBEADEDHFAHAAHBFEBHDCFDGDBFFBEGCAFADDHCABDACDABDHGFFGEEBFEBABCEFEHCHHCB,False +608,9.0,17.0,16.0,8.0,12.0,15.0,18.0,16.0,BGGGDCHHBHGBEACEACEGCEHFHCBGBBGFBGFAHCDGCFFCFGCBGBBGBFGBFAHFBGFBABCEGCEADHHEHHCHFEGEDHDDCDABGHECCFCFFGBADEAEHFH,False +609,34.0,28.0,25.0,20.0,27.0,20.0,18.0,15.0,FHGFEGEBBEGBEGHFHDFDAAEAAEDCFDBFEFCDCDDGEAFEADBCCACCDFHHBCHFEDABBABBABHAFGACGEEEACCACDDCBFCDHBFGBAGCGFADEADGABFABAGEEEBHBFDBFEBGEBEBHCCDCAGCAECAECAFCHGEEBFEAGEDECAHHABABBABDFDAHCABCAGHAGA,False +610,27.0,20.0,29.0,19.0,16.0,20.0,23.0,16.0,EDGGDCDCCDCCFAHFACFEEAAGGAHFADGADAEDCEACDAGDAHDCHFAFFHCGHCGDEBAEBAFHADHCBFBBDAECAECACGGGGFFCDGBHGECFBABDABGECGEFBFCBHDBHAHGACBAHEACCACHBHEFCBDCGDBGCBGHGCBFCADEFBFFGABGCEF,False +611,22.0,21.0,24.0,24.0,11.0,17.0,21.0,18.0,CGCHDBGDBABGACGAEAACCDDCDGCDGFDEHBABFCHACHAFGDEBDEBDABHGBCFBCBAHBDFBHFCFECFECGAGEAEBDGCGGCHGDFGDFCFBHFAFGAGHHFBHDAADCAHCAGEABCCBDDEDDHCCAAHFHHDADDBGHCGBFFBEDG,False +612,15.0,15.0,16.0,7.0,8.0,15.0,11.0,10.0,BBGABCABCFCHFCBCAGHHFHFFBFAAFAGBAGDEFFCFECACDACAFCABEEGCEGCAGDBCHBDDFDDFAFHACBGBHGBHCEEEGHCGFBHBA,False +613,1.0,6.0,10.0,13.0,4.0,6.0,8.0,9.0,GCDDCDCAHCHEDFDCCDGGDBHDCHDBHCGGFGCFGHFGFFHHCBBEEBDEDDBDH,True +614,10.0,16.0,11.0,12.0,14.0,10.0,10.0,10.0,DECEGBDAEDAEGGGHGAAEBAEHDGHGEBCHBCHBFEBCBFCBAHEDFEDFGAFDCFBCFBDFBCHCCHDHBDBBABFDGEEEDCEGAHBAF,False +615,1.0,1.0,2.0,4.0,6.0,3.0,0.0,3.0,HDEHFEDCEABEHFEDDECF,True +616,10.0,6.0,9.0,12.0,6.0,14.0,6.0,4.0,DFHDFBBECCFCCFBCDGAFFABDAGEADBDDACECFECGAAGHFHFFHFFDGDAFDEFDEBDAAGC,True +617,6.0,1.0,4.0,3.0,5.0,2.0,0.0,4.0,BDEHDAAFACHECHECDEFHCAAEA,True +618,22.0,16.0,36.0,14.0,21.0,16.0,20.0,16.0,BBGEBEHHHHHACECCGBEDBCDHHAHDCHDCECAFHAFDAFCAECGCCACCGFFDEGACGCCGCEGCGGEGACGACBDGGDEAEBAEGFECAECFBGECAEFFHBCCBCHEFADFDECDBCBFDHDECDGAABHCFGCAGCFGABEABCABCECCFFAHH,False +619,26.0,17.0,24.0,18.0,27.0,15.0,23.0,23.0,ADFABEBGDCGDEAEHBHDBCGECBECEEGAHGCCECGFCAFCHECFACBAHBACBAEBDEHFEDDEHGHHGHHGAHGAHFADAAGEAEDAFAADADHEGHEGHGBHDBCEECGFCHEBHBBFAHDCGAEGEEGECGHCFCFGCDDFDCBCFEAAAFEAHGBGDCDBEFCHAG,False +620,7.0,2.0,1.0,9.0,6.0,2.0,5.0,5.0,GBEGBDDHGCFGDGHEEHDEFAADAAHAAEAHEDDDD,True +621,16.0,26.0,22.0,21.0,29.0,29.0,17.0,19.0,EAFBDDEEGGEGGEGDFBBFADADCGDCBCCHCDDEDFEDFADFEDFGBFHBECAHCDBCGFCFECEEHAFHAFCGFBEHGFHEEHFEBCGBGGHABFGDAGCABFDBFDFFDEFBBBDHBEECFEHEACBFBDFHAHHEHHEHCCHGBAEBDCCEEFBBFAFCBDCBFBAFEACEGHE,False +622,7.0,7.0,8.0,11.0,8.0,4.0,10.0,8.0,DAGDCGDHGDACDBCFHHEGDEDEFHCBHEBHFDHEHBCGGEGBCGDCFDGEDCAABAABEAG,False +623,28.0,16.0,21.0,17.0,19.0,16.0,21.0,15.0,DEHGEHCAACGFGGBEFBEGGGBGFADAEDADDCCHGGACAACEBDGFCBDAAFBCCCCCAEEEECHDCEDAEFAHFABFACFGHHBEGCEFBAHCDHDBCEBCEAHAAHAABEDGECGFAGFABFAHFAHEAHDHBFCBDDAFDAGBGGDGG,False +624,3.0,1.0,2.0,2.0,0.0,4.0,3.0,0.0,GAAFDAFGGFCDFCB,True +625,2.0,3.0,2.0,8.0,3.0,1.0,2.0,1.0,DHDDBDABEGDDGBFAEDCEDC,True +626,25.0,22.0,16.0,18.0,24.0,24.0,24.0,13.0,EBGFHAFDBGEBGEFGEDHADHADAAFCAFCHGEAGACBDGBFBDFEDGEHGEHGDHGCFCEFBEACEBHGFHEBHEGFEBAECFBABCACCABAEDEDGEGCABEEDGEAGAAGCFFDBCGHAGCAFFGFDAFHFFGEBBBHBDAGDABDBDGBAFEDFCAFCEF,False +627,29.0,21.0,28.0,24.0,31.0,21.0,20.0,20.0,FAHFBGFACEAEHGHHCFHGAGFFCCDDBDGBDGBDBHEBHECCEHCAFEGEHGEHGEGGBCABADDACDEEBCHCGAAEAFCABCEBDABEABCAECAEAHHFCFGDFHDFHBCECEDCDFCDACEFBEDBFDBEBEHHECCEDAFDGFDHEEHEGHCDDADAAEGAFADCGCGFEGFEABACFAEBACBGDA,False +628,12.0,14.0,20.0,9.0,14.0,5.0,7.0,10.0,BAHEECEFDEACFADDABAECEHFDHCCCACBAEDHEBHEBHFHCFCCGCDACAADGEGCCGCGBCBBCGBCEBEHBEDCADBEGBCABHH,False +629,5.0,5.0,7.0,3.0,4.0,2.0,2.0,2.0,EFAECAECHGHFCDABDBCDBCBCABCGEA,True +630,23.0,22.0,17.0,29.0,22.0,31.0,12.0,12.0,CCDECDBBHBBHBGFACDAEHBFBGFCCEHGEHEECEFDDFDDBEDBAFEHBDHBFFFFFFFAFFAFHDFAEFACFCCGAFAAFGADGADFFEBHEGEAAFBDGBDADDAGEACECCFBBEEGGEBDBBCAADFEDCADFFDFAEFBHDDDDBCCBFGDAEHEHDDAD,False +631,27.0,22.0,17.0,34.0,24.0,29.0,22.0,24.0,FFDCFDCHHBFADFAGECGECGBFBAFBGGACBFCBACHEFEEFBEFEEFCBAEECEHAEGAEFACFADFDBFBHHDHAFHADDGHHEHDDGEBEEGFFDDGEDGADGBDHFDHFBHFHAABAADHAEHBHGDFGEAADDFDCCDCDDFBAGCFDCGDHBDHEAFDGBEGBADEFGCDBADGADHEHGFHBDHADGACB,False +632,14.0,22.0,9.0,14.0,13.0,13.0,20.0,23.0,BCFBCFAHGDHGAHEDGEBBCBHEGHDDDBAGBAGCECBBGBDABAGHDGHEFFBHEEEEHDEBDEFAAFAHGDGCDAFHAHGADGAGCDDHHFHGFHEBHBGHBFBBFGBFHHFAHCHHBECBGBGG,False +633,24.0,22.0,20.0,25.0,23.0,16.0,19.0,23.0,DBBDHHDHHEFEEFGABGFEGADFACHGEHGEHAFFAHECCEACEBBHBEFADDDDGGHGGHAABCFDCFBGFAECDGBDABEAFECFEHBAHFDBFDBDEFCBCCGDEACAAGBBGBDEAEAAGAAHBGHACCAECGCCDCGDEHAHGBDDEDDHDBHDHHFCHDBHEBCE,False +634,17.0,21.0,22.0,24.0,23.0,23.0,16.0,18.0,CBHDBHCEHCHBGDBECHEHFBCFDFBDFCGFCACCACCGDEAFGADEADFCDFBAHAGHGEBDDBDEBDHBGBDAEDBEDCEFCEFHBHCGDAHAAEDEEGGECBEHDGDBGEHFEFGEFBFFAFFCCFECEDHEGCAGBACFDGFDHFBABHADFBEFHADC,False +635,16.0,6.0,8.0,5.0,5.0,8.0,8.0,4.0,FFABFACAAFAAHAFHCEACEABFCDGCFACABGGDGCABAEBGEAGBAGHACHFEDDDG,False +636,0.0,0.0,0.0,2.0,3.0,1.0,3.0,2.0,EHGEHDEDGFG,True +637,9.0,16.0,10.0,10.0,13.0,11.0,8.0,12.0,FEDBEDBEBBEFBEHBFBFCBEGBAGBHGHDBDDEGBECEFHDDHCFHGBHEBCGBEFAACBDEFCGFAAHAHHFFAADAHDCHGCECC,False +638,12.0,9.0,9.0,12.0,9.0,15.0,8.0,15.0,EFGFDCDAGDHFCBFEAFHACHBGADEEHEFGEDHFDGDDGAECCFHBFHBCACHACHACFAFBGDBGDBHBHHBHDEHDAAAEFFFHF,False +639,14.0,20.0,11.0,14.0,9.0,16.0,14.0,14.0,BFBHEBAEDADCGDAGDAFBHCBACBAEAHHCGBCGFCGAABFCBFGADBFFFDFCDFEAGGDHDDEFFHGHHGHHEFEBHBBGDBCHBEHBEFBCABDGGDCGAFHBFABD,False +640,8.0,6.0,17.0,2.0,13.0,12.0,17.0,7.0,HCFFGFCHCCACAADFGBFCFFCGFCABGBEABGCEGCEGCACCFGDGECGHCAEGBEGEEGHBGEAFEHFEHGHGEECCGF,True +641,14.0,17.0,15.0,14.0,30.0,13.0,21.0,15.0,BBGEDAHDBBEHBCBEHAEGAFGECGACGADAFGFFGFEGDBCCBFCHDHABHEBGEDADDHEGHBBHEGCGCHEEHEEHGEHACACCEGCGGEDGFGAFDBFCAFBAFEEEHGEGFEBEEBHEFDECEEDEBGEDCAD,False +642,26.0,25.0,28.0,26.0,13.0,16.0,19.0,13.0,EBDECDGCAACBAHFACDCCBCDDHDFBDBDAHGAHGBHGBCFDEADGADGHFGBAHBCCDHBDFDFHAEEFDCGGCFCAFGACGCCFADBAEBGBGGBFGDFBFCAACAACECBBHBBGABGFCAHCDFGDCCEBCDACHBCAAEDEEDFEHEDABDACDAGDBB,False +643,14.0,19.0,17.0,9.0,14.0,22.0,18.0,8.0,GCCFBFFBEABEHDEBDGBDFAHFBHCBDEBDGBDHHFFGAFGCGHCACFBGGAGGFEGFCAFCADGGCFECECGFAGFAGACHAFHDCBBCBFABFEBCCBGFEAECDBBFFBAEEEEFG,False +644,15.0,27.0,16.0,22.0,21.0,27.0,27.0,18.0,EDFEFFDFBDGBEGBHCFHCFHFAHFGFFEHGEBGEBGABGCGEBGFFHADEDGEBFABGAEFEGFGGAGFDHFBHCBADAEFBCFCCHDFBEADEDBBBGDBDCACCFCEFDDFBHHAGHGGBGBEGCFCBFEGDAGDEHCEHEBHEBADHDHHDGCDGBAFBDCGAFGDBB,False +645,14.0,11.0,10.0,13.0,16.0,12.0,10.0,15.0,EEHEEHGEFGEDEDBGCBHHFHBFDBEEBEBAHBDGACGADGHEHHECDFHDFDFAEFACFBEBHEHAGDCHDCDGCFAAFAAGCDGCAAAHHFBCDBAFE,False +646,3.0,5.0,2.0,4.0,7.0,6.0,2.0,5.0,EEDEFDFHDFHGFHCBHFBEEEABHABFDBGCEA,True +647,17.0,19.0,20.0,19.0,12.0,18.0,17.0,19.0,HCFBAFBDFDHBCACEAFHCGGCAHBHHBHFECADGBGCDACAECGDCFDFEHBABGADGACGBEFHGFBDBCCBCFBDFADFGGFEGFHGFEBDDBDDADBFGCFGHECHCHHGGBECECCEBDEDHADHADHAFHAHAB,False +648,10.0,10.0,6.0,7.0,5.0,10.0,7.0,10.0,CHGDHGHAECAEAGBCGCEDFBGFCGBCFBHAEAFHDFBEHBGFAFFDDABDABDFBHFHHABHA,False +649,23.0,19.0,18.0,23.0,11.0,22.0,22.0,16.0,DFGDAGAEGAEDABBFDGADBHHAEGECAFDAEDACGBCGDCGHCGBCHEGACCAFDBFHBGGGDBGBFCBEGFHAHHCEDAEDBBAFAFFAFGAHCHCCDCCGBDEFHFFDBFBCFDCDDAAAGDEBDBBHBFHGFHFFHFAHGDGGDACDAF,False +650,4.0,5.0,4.0,4.0,6.0,3.0,2.0,5.0,DDHGDFGEFAECAFCDBCHEEAEEHHBACBHBB,False +651,29.0,15.0,14.0,25.0,15.0,16.0,23.0,19.0,GAFBABHAGGACGAGGAGHABDGFCGDEGEFDFACFBDAHAAHCGECDHFEHCDDEDDECGFDDFEDADAFDBFDBEGHFBAGBADBCDGAFFCEDEHAAHAACGAGDFDDFDAADCAFHBEHGEHGCGEBBHHBCDBCDHEBAEGGHGHHAAHAA,False +652,17.0,19.0,21.0,19.0,20.0,33.0,24.0,19.0,EBHGBHEFHAFCFFEAFEADEBHCBFCEFDEFHBGHGFDGDAHEGFEABBBBFBBFBBFAFEBDHBCBCGFEHACDCFDBGHGEFGACCFFFFDADGFDCFGEGHHGEHFFHEFHCFAGFBGCCGDCDDCGECGHAHEAGEDBCDEHDGHFGFCCDAAFAAFGAFDCGECGD,False +653,4.0,2.0,1.0,5.0,5.0,3.0,4.0,8.0,GBFEDEDGEDEADHGHHGHHDBHAHEFHCFAA,True +654,20.0,23.0,22.0,29.0,18.0,18.0,13.0,18.0,EDEBAEGHHFAHFBDDBGFBGDDABDABDADCCBBCEHGFCGFCDEHDFDGHDCBDHFDCBHBFHECCADGHGGEGBCBACHAEGEEFDEHDCHBEHFDBFCEACFAEDAFBGDBDDBDDBFDCFDCHDAACAABACGFCACDHHAFBAFBHEDCEBEEAC,False +655,7.0,8.0,11.0,11.0,11.0,5.0,11.0,11.0,CHBCHDCHBAHBCGDEGDACDEBAAAFBEFHFBGFEDEEAEEGDGGDGHDAHDHBEEGDECCBHCGCCGHCFHDG,False +656,23.0,22.0,23.0,10.0,19.0,19.0,24.0,14.0,FCGFCGAAEBHECHECHCGABAAFFEHBAHBCBBDEBEFDFADFGDFACFAFAHFBCEACECCDGBFEBFCCCCEGAAHAGEBGABCFBAAGFDFCEABEABECDGCGAHGHCCHBAFBHEEHCGBFGBAHBGGEGGEDBEDBDFGGGGGGACH,False +657,17.0,18.0,13.0,17.0,9.0,17.0,17.0,24.0,BDHBDGBFEBCHBDFBDHBAHBHHAAGABHACFFHHBBDDHHDHGFCFFCGHHBAHADGFDCFHCHCCBDFFGAFGAEEAGEHHBGFFGFAGHADHDCBDEFDECGAGADCAGCHGEHBEHFDABDGBCGAE,False +658,8.0,8.0,5.0,2.0,2.0,4.0,5.0,8.0,CEGBBGBHCFHBHBBABGEBHHGCFAAHADHAHGACFACFAD,True +659,34.0,21.0,21.0,17.0,21.0,20.0,30.0,25.0,HAFHDCDEGEEGAAGBGCBEAGEBGEAHCAHEAHCAHAAHFBHECECABCAHGGFGHHGEHDADFACFACFCGFCGFBBFAAHAAHBFFDAFDGFCAEAGFAEDBGBCEEFFFDEAGGADGCDFHGGHBCABCABCABHDGDGGEGGEGHEAHBDGBHHBCHDFAECGDBHAGHADABBACEFHBDEGC,False +660,14.0,30.0,12.0,19.0,8.0,11.0,20.0,13.0,DEBHHDCGGHGCHBFBFGBFDDFDDGDGBDBBABHDBHACECCACEABBAEBDBBGGGCGDAHCADCABHEFHBFDCDCGGFBGDBDBBGGBCGBEBBEBBHHBHFFHFAADGBBGBGADDFEAAGA,False +661,11.0,26.0,15.0,26.0,16.0,14.0,18.0,26.0,FEBHBBCBDCEDFABGAGEABBHBGCDGFDEBBEBBDBEGBEDDHHDHFBHEBEEGAHHDHHCBHCAHDHCAACEGBEGBDGBHBHDFHDHDFHECHCHEAHBGCFCFHDDHDDFDDAGEGGCCGDFGFAGFGDBBBHBDHFDACDCHFGDE,False +662,5.0,2.0,4.0,1.0,4.0,3.0,0.0,4.0,HCDFCFHCACAEEAEFBHABHAE,True +663,14.0,22.0,18.0,13.0,14.0,22.0,18.0,29.0,DHBHHBGHGDDFFFCBHCBFCHGCGGHHHHABCCBAFAEGBBDBFCFECFADFHBCHADBADGHDGCDACFHBFGFFBFGCFAAEACHAFHEEEEHGEHAEBGBGGBFCBFBGGBGAHDHHBECEHCHBFECFHAFHDCHDEHDEHGFHB,False +664,22.0,13.0,19.0,20.0,21.0,19.0,24.0,26.0,AACFEGGECAHDGHDGDBEHBGDGGCBEAGEFEAGBGGBFFBGGGGDCEEAAFFAHEBFEFACFECEABEFHGFHDAHCBHCFGDFHDAHGEHEAHEAGCCCHDAHFCEFCDCAFCGCHFCHGCHGCBGFBGHHDAHEAHDHHDHEEADEFDHADADDHDBADB,False +665,19.0,16.0,20.0,18.0,23.0,17.0,22.0,24.0,DAACFCEFCEHBFHAEHDBHBHABHABHAHCCGGCGCEDBDHBACCCCCAEDHEACEHEDGECGEFGCGDEFHCAHADFDEEDBECEACDGEDGFHFAEFAGBHHAHHDHAGBBFCGFEGHBHFDEFDHFHHABGABGEDGEDGEGGBCEBGDFGFFGA,False +666,21.0,15.0,10.0,14.0,9.0,13.0,18.0,9.0,ACFGBACCACCADCDGADGADGHBABGDFEDEGAGFADADDBEABDABEABAFBAFBGFGGACGBFEBFEHFHGACGCFEDGBGABCEHFGBAGFEDADBAFHHGHHDH,False +667,8.0,7.0,10.0,12.0,11.0,15.0,18.0,9.0,FAGEGGDGEAGDFCFFHBFDBGDFGBAGHCGFCDBCGBDFHGFHEACECCECAEFGCFGHFEDGHGBHFCHAEDAEDGDFGFGEBEDHAD,False +668,10.0,9.0,8.0,13.0,5.0,7.0,10.0,7.0,GFDGECCECCFHAGBGDBDFADGEDAADAADAADCGBGHBHBDHFGHFAHFACDEHBEBDDCGGCDFBB,False +669,7.0,12.0,7.0,12.0,9.0,2.0,15.0,14.0,HBGHAGHEGBCADABEEHFCCGHGGEGGCDGCHGEDGDBADBHDBGEAGAACEDDFBHBBHBDHBDHGCHGHDEEBHD,True +670,0.0,5.0,2.0,3.0,7.0,4.0,3.0,4.0,FGCFHFEDBHBBHFBGEBEEDEEGEHCD,True +671,5.0,12.0,12.0,3.0,8.0,4.0,5.0,4.0,BBCBBAECHCGHCHFCFCCBDBECBEBFEBCGHCEFGGBAGEAEEACCBDABD,True +672,11.0,18.0,12.0,10.0,18.0,18.0,25.0,17.0,AGBBGFGCFCEFCBHCADEBHCHDEBGGGGGAGGCGFHFBHDBFFAFHAEHFEFFAGBEDHHHHBBCFHAFCGCCBEHBEHGDBFEAGEHGEAGEAGEGDBGDCGDGGDFHEFEBBCBAGBEDHEFGEF,False +673,9.0,13.0,14.0,18.0,14.0,11.0,8.0,15.0,CGDBHCCHGBFGAFEEHEHCEHCACCADCDDCGBCDBHDHCBHEHABHEEGDFHDGACBAGDFEDFEDECDBDHFEHBEFFEBCEBDABAAGFHFDDFDDHB,False +674,8.0,13.0,7.0,9.0,11.0,13.0,8.0,11.0,GHHFHFCGFBEFDEDDBFDBAHFHHFCHEDGEHGCBDBHHAEGAEAAEBAGBAEFCFGCFAHBGEFECBCBBDBBDEFDF,False +675,1.0,9.0,5.0,1.0,4.0,4.0,4.0,4.0,BECBCFDGHHBEBBFBBFBCFBHGAHGCEECG,True +676,7.0,7.0,1.0,4.0,6.0,8.0,6.0,3.0,ECHEDFEAHHDFABGEBEABEDGFAGBAFBAFGFGGFABFDB,False +677,14.0,18.0,19.0,11.0,14.0,16.0,16.0,25.0,EEHFECBGCECHDBHGHHGHHGABBDFBDFBAFHAGDABCABFHHABGAEGDBHHGHFFHDFEDFHFGACBCCGCAAFFAHACDGCDBCHBFGBHEFHAFCCEBBDHCHFAHEGHEGCEHCECCHGEGBECBD,False +678,9.0,12.0,6.0,10.0,11.0,11.0,13.0,11.0,CDEAGGDGGCGBCGBAGBGEBDCAFGHFGBFEHEEACFAGFDEFGBHHFHHEHFCGDADHHDHEDAADFBFBBFBEEHEABBD,False +679,27.0,20.0,25.0,20.0,31.0,18.0,23.0,23.0,EFHEDHDDBECBDAFEEFEEAADGGCGEBGADEECEEFEECAFCGEGGBFCBFABGACDAEHBHCFGCHGCHGCFDCBHHBEABAHBABAHEAHGADGCCFECDHDFAGECHAFBADBGDBCABHADDBHCEHCEHBFHGFEEDCDHCEECGCDBCAHGHBGEAGEAFFAFGAEEAFAHGEHGDACD,False +680,27.0,26.0,27.0,28.0,20.0,19.0,14.0,25.0,GDCFDCFHCBAEGAFACFAGFDBEABDBCAHCGFFFCFBBBADBGFCDACDGDDHCEHAEHBFGBHECDEGAACBHCHEAHEFCGACDBHDACGACHAHHAHDEHFCBBABBABCHBFDCGBCHBCHFDHEEBDEHEEHGEFABHAHCAEDBCDBCDEEDCBDBHAFAGEADDADFADFDDHGDEC,False +681,3.0,1.0,1.0,3.0,4.0,8.0,7.0,1.0,HGFEDDABGFGGFGFFGCGAFDAFEEFE,True +682,15.0,12.0,11.0,14.0,15.0,27.0,23.0,14.0,FHFFHFCHGEDCEDGABGDBGFFGFHGDDFFDGCHECAEGEBCEFCEAAAAGACFAGGGBEGBFBAFBAGGAEHAEHBDGGDFDAHGGEGGHAFHGCEFDBFEHDDBGFBCFAFFEHFCHFHDFCFFDEFB,False +683,3.0,2.0,5.0,6.0,4.0,4.0,5.0,2.0,GGFDFADFADECDCGBCGEDHEDHGCBCAEF,False +684,13.0,18.0,21.0,19.0,20.0,13.0,21.0,11.0,FEEGGCAGBEGFECBEGBDHBDCCGACGFBFEHHEHBCHCCFDCDDCEACEAFHHFCFDEBBGBDCBDBADEDEGCFDHABEDGEGFDCFECDEAHEDGEAGFAEAAGHADABDBGCGGBGFBDCBDGBCGECGHC,False +685,10.0,7.0,12.0,11.0,9.0,18.0,8.0,9.0,HDHAGFAFFAFFAEBDCBDBEAFEACEACDGDDGFCHFCBCCACHGCFFCGDEFDFHEFHDCBEHGEGFFDFAAFBEFCDGHBH,False +686,6.0,12.0,8.0,11.0,9.0,7.0,20.0,10.0,BCEBCDBHAGDAGDHGDEDAGDGHBEHDDFGDGEDAEGGGCEBCBGGGCHECBFHHGGFGGFGGHGAHFBBCBECBHABFDEF,False +687,12.0,20.0,16.0,25.0,15.0,20.0,20.0,33.0,DFDHAGHAEHBHBFCFFDHFDBGGCCBDABHGGHBBCBFCHCEEADDACDFCAFBHBHDBHFBADGHDGHDGFEEBHHGGHGHFGDFCDHEEHCECCHDBDAGDABDCBFHAGEAHEHHEHFDHFDHFDEFDCCGBCHEDHBDGEHGBBGFDHAHHFEFGG,False +688,3.0,9.0,2.0,3.0,7.0,7.0,3.0,4.0,CFEHFBFBBEDBCHAFABFEBEEBDEHFEDFHBGGBGA,True +689,15.0,26.0,20.0,34.0,29.0,23.0,27.0,17.0,GAAGDABHABEGDEBDFFDHFEHFBFCBGCBCCDGFDEHDCFDBHEBEFBEBCGCDGADBDGGGAAFCEDCEDBHGBDDBEDFFGFEHBEFFCAHCHHGFDDBCDBDFEHFGAFHFFDBEABEFBGFAGHGGEECCGABDDBEEBECBEAGCHGDHGDEDHFDHDAECAECDEDGEDEBCEDDGGDEGBCG,False +690,2.0,5.0,5.0,7.0,3.0,8.0,3.0,2.0,GFGFFGFDHHAEBCCBCDFCDEADFDBFDCEDBBF,True +691,11.0,14.0,14.0,3.0,13.0,5.0,13.0,10.0,ABGFGEEGEEGEHAHBCHBDDGHBBABACBCEEGECGECGHCABCABCHBEGAEFCCGBFGCAEFGECBFHACHACHDHBGBA,False +692,17.0,27.0,23.0,13.0,20.0,16.0,15.0,12.0,BCCBCGFCGFADAABEDHEHBEADCFFEFFCABCGBABBEGBADBABBFCACGEDBEBBGFBGHBGHDEHBEHBCHACHFGEECHGFHGCCGECGDBBDGAEADFCGECDEFEFCCFAHFEHEABAFCCECEBDDBADBABBC,False +693,27.0,22.0,19.0,22.0,14.0,28.0,28.0,25.0,FCDFEDBEDFECFBHAAHEACBFDEGDCGFFHHFADGABFAFAAGGBHFECAECAGCGBDGBDHBHCBHFEHBBAFAAFAFFCHFGGFHAADCCGCCGBHGDDGFDGBDGBABHAGFDBFGBHAEFFDGFDGCAACAGGHDGAGCDEHDHBGHEFCEFADHEHABHAFHEHHDBGGBFCBGCHAD,False +694,18.0,13.0,19.0,10.0,11.0,15.0,13.0,6.0,GDGHAABAGDGHFBFGBCGACGAEAFDAFDECHECACBFCBACBEBDGBFACEEBEDCEACEBBDDBGFAFFDCFECDHCACCGBFGHGCEGCAAHAAFCAFCFF,False +695,10.0,11.0,11.0,10.0,20.0,12.0,15.0,5.0,DBDBFDEGDBGEEGEGFAAEGDFCFECEEAEEBHGGHCGHCFACGHEGEEGAEFCEFBAFBAEEACCGFDBFCHACEDFADFGBGCBDEBEGBD,False +696,11.0,15.0,9.0,15.0,19.0,14.0,16.0,14.0,BBEABEBFEDFHBEDCFCEDEFDECCEFGFGBHGBCGHGFHEBDGBFGCFGDGDACDAFBFHBHGECGEHDEHBBFDEEDGEFCAAHEABEHHEAHEAHDAHDGGDBGFAGAD,False +697,4.0,10.0,3.0,4.0,4.0,9.0,13.0,9.0,EFFBHHHHHCADDEGDFGBBGHFGBBBBHBACEHCFBEGDGGFGGFGAFGAGHFGB,True +698,8.0,6.0,6.0,10.0,3.0,3.0,10.0,9.0,CHGBHGEHGAAGHDGDAGDBDHADHBDHDAFACBCFBGEHCEFCGABGAGDCDDH,True +699,23.0,20.0,26.0,25.0,24.0,29.0,20.0,24.0,CDBFFGEGEACCACDGBDCHACHACHBGDBCFBHFHHFHHAGHAGHCHAEEGCEHEEFFCDFDDFDFAAEEFEEFBEDAEDFGDFGDHHDBCBBCEBEABADDAEDGGGCEHAGBEFBCFDHFBEFADFDCEHFEHFHADCFDAFHAFBFCEDDBCAHAACGCBFCDHBFHDAGFEGFGGCCGCBBCAHGE,False +700,29.0,20.0,21.0,24.0,24.0,23.0,13.0,26.0,EBHEBHBADGAHAAEEACGAFAAFBBFCHDBHAGCDEBDCDDAHHBCEAAFHAFCABDDEDEEDFHDFCDFBEGCFGEFAFGCHGDHFFEFHEDDEADBACACEFCBHCEHCAAEAECAEBFDAFHAHGAHGBGCBDHBDABDHBDHADFGEBABHFCFFAHFDECHHCHHCFCGDEGEE,False +701,3.0,7.0,7.0,3.0,6.0,6.0,4.0,11.0,CEFCFHGFHBHEAHECHEBBAHAEECHCDHCFFCHBGFBDDBGHBGH,False +702,9.0,6.0,16.0,15.0,12.0,8.0,10.0,9.0,FDCFDCDAHDGHFAACBCHDEHEGDEDDFDDEGCGCDBCDEAFCBCCBCGACGACHHEEHADDAEDCECFECFAGGBBEHFGHEG,False +703,6.0,1.0,3.0,5.0,2.0,9.0,6.0,6.0,DABEAHCFGGFAGFHHFCFFHDFHDCGFFGDEGDHAAA,True +704,4.0,1.0,0.0,2.0,2.0,1.0,3.0,0.0,BGGAAGEADEFDA,True +705,18.0,19.0,12.0,21.0,25.0,19.0,18.0,24.0,FDAHBFHDCHACHAEAEEBDDDDDGFHHFEHDDBDAAAFHAGGAGDABCHGCEGCFDBGCBEFHFDHFHHEGCFABHEBHCAHBBHEAEEAEGAEDEBGFCDHEEHGEFGEFBDFEGFGHFDHFBHDBGDACBAFBDFEHEECBEGBDGAEGEHBC,False +706,17.0,12.0,10.0,18.0,25.0,13.0,22.0,21.0,AGEHCDCDAEDAEBAGGHGGHDCHEHEFCEABEGBEBHAGABHABFFGGFGAFGDBGAEDAGFAHEEBFFAEFBEHCEFDEFEHDCHDCHDGAEGAHHFHEBEEGABGDHGDHBDHDHGCEDCHFCEEDDEHDGAGGE,False +707,18.0,24.0,22.0,26.0,29.0,18.0,27.0,19.0,HFHHGDEGFHCDHCEGFEGBDCEDEEFFBFCAEBBGABHADAAGABFDCGCBHABAGHDEDEEHBAHDAGDBGCBDHHDBEEGCFGCHCFHBFDEGDHDFHAEDAGDFGEFCEGGEBGCCCCECGECGCHACEGCEFCDFBDFBGBEABECBEBBGAHGDHDDAABGGBEGAEBEDFDDFEDE,False +708,20.0,10.0,10.0,16.0,13.0,13.0,19.0,23.0,FFHDFHCCACGGGHEEHDGGAGEAGHAEBAHDGHGGHBGAGFCBDCDDADDCEHADDDHBAHBAHBGGAFAAGAGGBGFHAHHDHGEHEFHCFHCBACEDBDDFCEFAHFAHEAEFHFABEDHE,False +709,5.0,8.0,2.0,9.0,7.0,8.0,16.0,8.0,CGDAGDFHDGABHDEFFBFFBEDGGAGGCEGHHGADEFDEDHEDGFBGHGGHGGBGBBAHEFB,False +710,2.0,0.0,1.0,2.0,0.0,3.0,1.0,3.0,FGHDDHAFHAFC,True +711,11.0,11.0,7.0,14.0,11.0,15.0,19.0,23.0,DHDDADGHBGFBGHHGDGAHHHGHHGBCEDCHDHDECGGFDDAGBHGBGDAHBFFBFFCHFCFFHBFHEHHGAFGAHGHDCDDAGEHGEHBFHEGBAGFAEFCEABEAEEF,False +712,22.0,16.0,19.0,9.0,22.0,12.0,19.0,16.0,HDGBAGAAGFEEFADBADHGCGCDBCABEACGHGEABEAFGHFEHFGHFGHCGEFGEFHHACDAHFCGECEABEAEEBBABHEFEAGEDGBCEHDEADCBDABCHCCHBCGAGHACEACHFCEEBAEBAGBGFCC,False +713,10.0,16.0,20.0,25.0,19.0,11.0,23.0,14.0,FDCDDBFDGCEFFEBBEBBFDBHCFAAHGDHDBFFGFDACDAEDGEGGDCADCDDGEDGEGCEGDADCGDCBBHEBDECEHCEHGBHACEGGDCGHHGHDGCGGCGCDHHDECCEBEEDABBAGBGEAGEFDHFBHCC,False +714,7.0,8.0,11.0,9.0,14.0,8.0,8.0,14.0,AADAFBHGCCGCDHHFHBCHDCHDEHEEBFBAFHDGHDHHEAFEFCEGDHBEHCCFCHBBEDEEAFEAECGECGEGDBG,False +715,4.0,5.0,2.0,4.0,4.0,2.0,5.0,7.0,BEEHHBHHCDHCGEBGDBDHEFHFAAGAAGBDG,False +716,2.0,4.0,4.0,2.0,5.0,4.0,1.0,3.0,GBACBHFFEFFDHBDHEAEECECCB,True +717,15.0,12.0,19.0,9.0,14.0,21.0,18.0,23.0,DBHAHHEFBFAGHAGHAEHFEAAGCGHBFHBAHDCHCCDAGGHGFDAFEEEGECHCCEBGDAGCAGHGFACDHBDGBAFCFFCDFCFFCEGCBGFBCHBHAGHFHCBHAFHCFGCEGCEHFEBEEFFHDFH,False +718,21.0,29.0,17.0,17.0,19.0,12.0,14.0,21.0,BHBBDDFDBFDBDHADHBCABAHFADGBECCFDBADGEHHBBEGHEDHCHEBHBHHBEEBCABFBBFBFDAFABDGCEGCEGBEACEBBBBCDCHGEDEEGGHGAFGABGABAAHAHHAHGAHGEHCDCFDCFEEDEBHCCCACAAFABE,False +719,15.0,18.0,17.0,14.0,22.0,18.0,20.0,22.0,GGECFCHFHBEHBEDBEFBEHBDHBGAGFAHFAFECFDFHGFBGDEHECDGCAEFHEFBDGHDGDBGBBGBHGCCGCCGCHHEBBBBEEAHHBFEACADDACGCFEHFEHFAGAHGEHFAAFCHDCEGCEFDEGBHGDHEECAADA,False +720,4.0,4.0,3.0,2.0,1.0,3.0,4.0,4.0,BFBBFHBCHAHDAGEAFCADCGGGH,False +721,22.0,14.0,33.0,22.0,22.0,16.0,25.0,18.0,EGACBDEEDAADHAHBABBAEGAEGBHCBADGFBCFBAACFEEFEDHBDCGECHHHAGEAFECFEGFGAFGHCGAFGEFECFGCABEEGGDAGDCCHCCHGDEGBEDBACAHDACCCBHCAHCHDGHAECDDCDHCFCDAHHCECGECGDCGFGECCCFCCDDGDDGDFGBF,False +722,15.0,12.0,9.0,7.0,14.0,11.0,9.0,13.0,HFDHFEHEGDBCFBCAAHFAEFGGDBADEAFEAHEAHFBGFHEAGEDGBBABHGEHGECCABCEHDBADCFEEFAHFGHEAHACCABCBB,False +723,25.0,27.0,19.0,19.0,29.0,24.0,29.0,27.0,CHBDGEDBEGCHBAGECBACBGCEACAGCAGEFHHHGHAGAEDHGCGBBACHDGDAGDAGBFFBGFBDFEAFBABACDEFFEAHHAEHGHHBFABFACHHHEBGBBEABEAHEDGEDBFDCHDBGGEHHEGHFCHFHAFDAFEGGHGECDFGGBGCFEAGECBECBECFEAFEBFEHFEHBDDAEDADDFCBFEBFGHG,False +724,7.0,6.0,4.0,4.0,2.0,2.0,7.0,4.0,BACDABGAGDBGHFGHFCHAEGADGBEGBAADCBHC,False +725,13.0,14.0,14.0,9.0,9.0,11.0,7.0,5.0,ADEDDFDEGBCACCABCADGAFGFGAEGAGBAFCFFHBBHCBDBFEGAEDBDFHCEECEAFBAFHCFCCDBCABCABHBBEC,False +726,6.0,1.0,2.0,1.0,0.0,2.0,3.0,0.0,ADAAGACFACFBGGA,True +727,22.0,23.0,26.0,27.0,23.0,28.0,17.0,22.0,ECCBCCADCDDGGAHBAHFHCGHEGHCAHGHHGBEFCAFBAFHDFAFCCBACDGCBGHGEAGCDECFEBEEDFDFBHGBAGBADFEDAHDACDGEFEEHGEHFAHFAEBDBBEBFEDAEDHDDCFDGDABEGDFHBCBFDFFACFAFHEFHABDCCEABEFFHCFBFFBFCBDCBDCEDGDAHDCHCE,False +728,0.0,0.0,3.0,1.0,3.0,4.0,2.0,2.0,CEHCFCGFHDFEGFE,True +729,17.0,19.0,22.0,26.0,19.0,16.0,18.0,23.0,GFHGAGFACDAEAGFDCBCCBCBBGBDGEGCEHDDADHEDBADHDEFBEDBDGBCGAHHAEAAEBDGDGGDGABBECDEFDEFHCAHBDHBHGGDFFEFDCCDACBAHEABCHEEFCEFHGFHDEBGEBHHHHCFHEAHBAHCDDDDCGFCHFCHCCFCD,False +730,10.0,12.0,10.0,12.0,5.0,3.0,7.0,9.0,GGBHAHCBEBDABDCEDEGDCGDAFAHGAHDADDACHACGECADHABCCGCBBCBBHHBFDEHDBDFB,False +731,8.0,9.0,15.0,9.0,17.0,19.0,15.0,6.0,BHGBCGBCDBCFBCBACFAFEGFECFEGFGCEGCGADEFECHEDEEFFEFFGFFGDFCEGCACBAFADCGEEGDBADFAHHDGHGFEEDCEHFFBGEC,True +732,15.0,25.0,16.0,23.0,8.0,23.0,16.0,19.0,CCGCCHDFHDFABAHDHGDBFDHDDBBDHBGHGFDDFGGHEHABDFCHFAFCACBBDDBDFBDABHABGBEDBEDAFCFBCFGEBBHCBABGABGHBGHFGCFGCFGEBEFADCHFHFFCDDCHAEHBDGADAADGFCFFBFEBH,False +733,26.0,12.0,25.0,16.0,6.0,12.0,11.0,16.0,DDEFFEHBCBCAGCHGBHAAHCAHAHHBHHGGHCFDCADCADABFCCGAFDAGHCCCACFADFADAHBGBCFFDBCHAFAAEDEBAHBAEFAFBADBDDADCCCCCCCACCGCDGADGAEAHGH,True +734,24.0,26.0,16.0,18.0,21.0,14.0,24.0,22.0,HGDGADCHDBBAEBDEBDEBEEDECFBCAGCBCHGDBGEBDEBEEBDGBGHHFCDDHGDAGHADEBDAAHBGBAHAEEGEBGEBAACFHCFACFHFAHFAHFDHCBEAHEHBCHAHAEDGFBGDBGFBHBEGDGGACEACACBACFAGGEGBFBHAGHAGCFGHF,False +735,22.0,22.0,29.0,19.0,27.0,26.0,31.0,18.0,FACFCCFCAHCGBBDADAGDFEEFAEFAHADEGDACBFCBFBHGCGGCFFBGFGFBBHHBCAADGCDECGGCGGCAGCEGEGGDDGAGHAGHFCFCEGDGCFFBDEBDFBFEEEHEHBEAEEAEEAGEFDEGDBBEHGAGFDGEDHBCHGAAAAABCECCECCHCCDFHBFCEGEDGFBFCBFHBFHDHHCGEB,False +736,3.0,2.0,3.0,3.0,1.0,1.0,2.0,0.0,DCBDCBGCAGADEAF,True +737,25.0,20.0,13.0,20.0,9.0,15.0,15.0,17.0,BBCBGDDHBCECEDCBDHGDAGDAEAACDBCDAAHFAEFDCFAFBAGAGBABHABDABFAFFDDHHHHBFHDFGGHDCFGGHHGAAEAABCAGCBGCEGABCADEBBEFBDFHGFHDFHCFHAADEBDGADABH,False +738,15.0,21.0,15.0,20.0,23.0,14.0,16.0,14.0,HBDCBCCDFDDBDABDABDFDHHBEGEFGEFGECGECGECABBEGFEGFGFBABDGBHGBHCAEBBEBEDDDBHDAFCACCEBHGGDEDAEACFBFFBGFGEEHHEHEAHADFCDCAFCDEBDCDEGEHGAHAHEABE,False +739,6.0,4.0,7.0,3.0,11.0,9.0,13.0,4.0,CEEGFEGFDGBBEFGGDEDHCCEAFEAFBAFGACCAGAFEBFEGFGCHGEHGECGHG,True +740,18.0,18.0,17.0,21.0,22.0,23.0,24.0,19.0,CHFCHDGHDGBDCFEEFEDGHDAHDAECAFGFFHFCDEGAHBDBEDHEGAEGAEFBEHAEHABBAHFGECAHBFCDFDEEDEGDACBFHDFBGFGFEEFAEFCFBCHBDFAGGAGGAGBAGBEGEGDDGCDBBDBGEFGDDGHBBECHFCHCCFAGHCFCAH,False +741,9.0,8.0,14.0,9.0,12.0,8.0,10.0,8.0,HHAGBAGCACBHFBHFDEADGBFGCDABDCEDCEFABGECCEBCDGEEEEECECCFACHAEFGGFCGFDGDACDHHBH,False +742,12.0,15.0,13.0,8.0,14.0,16.0,4.0,12.0,AFFFBFFBCEAFAAEBHDAEAHBCHFCHBDHBFHBDEBAHGFHFBEGCFHCEAFEAHABDBEDEEFECHECGECFHCFCCDCCGBDABDBBEFA,False +743,10.0,6.0,7.0,8.0,13.0,10.0,9.0,5.0,AFAAEBGEBEECEEDFCGGHDGDFCFGHFBHEHDDAADEDDECBEFBECHCGAAFFAFEAGEAGFBGC,False +744,4.0,4.0,4.0,5.0,4.0,3.0,5.0,8.0,FHDHHGAHBHDDHGDAFEACEACEGGFHBCHBCGEDB,False +745,5.0,2.0,6.0,1.0,2.0,4.0,4.0,5.0,CHHCFFGFGAAGAHGCHABEACEHCBFCD,True +746,6.0,7.0,9.0,8.0,5.0,5.0,6.0,0.0,GDGGFGCEDBEDACDCCFACFCDABDACAACBEBBCFBFEEGBDGD,False +747,23.0,21.0,27.0,20.0,27.0,21.0,28.0,26.0,DEADBCCGHHGHDBADBADBEEBFEBEBGGCAEDAHDFDGHEAHEAGEDGEFGBAGHFHECBCAEEBEGFFFHHHDHHGACGEEDCADBAFBHGBAFBDFCDCBGHFHAFCCDCGACGAFGCEGCHBBDGCHFDAFGGGBHGBHAAHCAGEDCCGCCHBCHFFHEFCEFAAGACGCEECECHEBHEGEDFEDF,False +748,3.0,5.0,1.0,5.0,3.0,2.0,3.0,3.0,DBGHEAHDADDADECFEGBGHBFBB,False +749,11.0,7.0,13.0,10.0,10.0,9.0,18.0,6.0,AGEGGFDHECGGCGBCGECBCCEFCADCGHCGEGBEBDECGGCAFHDDHGDAGDAEAEFDGADGAFCCFBAFEFDGFAGBAHBH,False +750,19.0,21.0,8.0,26.0,26.0,23.0,18.0,20.0,FEHFHBCHBCHAAHDGEABEDCECBDDAFFAFDGDHCDEGDFADCHDEDEEGHAGDFGCFGDFAEBDFBAGHAEEAEAAFAFBAFBEBBDDBDHEFHEHDEBDEFEBBAAEAEGBEDFHDHGBEGEFBHCHFBHEGGEFGEFGDFHFHGDBGDBFDBHDGA,False +751,10.0,15.0,9.0,6.0,11.0,12.0,12.0,15.0,GDEEDHHBBFGBHHBEHFHFBDCEGGEGCBCCAFCEFBECHEHEBHBAABFABFABFGFEGAEBDHCGHAGHAFCACGAHDHFDHGBBGF,False +752,16.0,16.0,21.0,19.0,22.0,24.0,24.0,17.0,HHEEFGDFCDFCDFGHFHABEGECBCGBCGBFGDFBCBAFFGCAGCAGBAGHGDHDDHGDHGEHAECADCEFFAFFDEGBAGBCEBAHFACCDCBGEHDEGAEFCEDBEHFHAEDBGAGFECFGGAGGEFHDHECHECFECFCBDCGABDBHDFEFFED,False +753,5.0,5.0,9.0,7.0,8.0,5.0,5.0,7.0,DHCDCBFEBACFGCHGCHGEDGDDEDHAGEACFACEAHEFCCFBDHBHBEE,False +754,1.0,1.0,2.0,5.0,0.0,0.0,2.0,1.0,GGBCDDCDDADH,True +755,3.0,4.0,2.0,11.0,7.0,7.0,7.0,3.0,DDGGDGFFEFFGGDECDEDFEDFBBHBGFBHDAGCADHDDEAEE,True +756,13.0,13.0,9.0,10.0,17.0,10.0,13.0,12.0,CGAEDBDFGGHCGBCFAEEAGFBFFBFFBEGEEBEEHEECDEGACGEHAFGADHABHAHHCGHFGHEHEAHGDDCAHFAEBAEDCBBCBBGBDEDDA,False +757,8.0,8.0,4.0,5.0,4.0,3.0,10.0,2.0,BDEBGHGGFDGFDAFCGGCEBBAACEDCADHABGGBGBAABGAE,True +758,26.0,19.0,23.0,17.0,12.0,22.0,20.0,22.0,DDGDEFCHCHHDHHCHGGHDBAFBFGBFEBCAFCAFHFFDCCDCEACACBFEGGHGGDFGDHCBGAFCAFEDBEAEEBDFGDAGBHBHHADGCDFCAHCHFCGFCGHCBHABDABAACHAFAAHCBHBFABFAGFDBFHBEECGAGAAGFAEDABACCEGH,False +759,4.0,1.0,4.0,4.0,4.0,6.0,8.0,4.0,GDFGAFGDGCFGCFCAHAHDFHEEHEEGDGAFGCB,False +760,2.0,2.0,0.0,1.0,4.0,1.0,5.0,1.0,ABEDBHAEGFGGEGGE,True +761,21.0,26.0,28.0,30.0,24.0,24.0,21.0,23.0,FDCHDHHDFHCCGFFAFAAGABBDGBCGBHGEHFHFBCEACEHEHBEABDBBABAGBFFBHDEEDBGFCGFCGFBBCBBDBGGGCDECDCFECFEABGCDAEHEHBEDDADFADGAEEAEFDCFHCFBCHBCHAEDDEBGEDGFHEDCBACDGFFCEGCDACABEGCDGHEECFCFHDFBDHADHADHACGDCDDHH,False +762,24.0,12.0,13.0,17.0,17.0,14.0,9.0,11.0,CEAAEBDEFDBCCBABBACBDBDDADGCGHAEHAEHBEFAEFAFCACHBHFEHADHFEFAGFGCDADDACDEDGEBGECAEBFEBEADGACFAHAACAAEADDFFGAFGCDHDHEFH,False +763,6.0,8.0,13.0,10.0,5.0,9.0,19.0,14.0,HGDFBDFGCHDCBGCEGCEGHGHHGACGFCAEEHBBGDHGCCGFAGHADHBCGDDBEAFDHFBHFDGCAGCGFFGHBGHCGHCD,False +764,27.0,23.0,30.0,22.0,19.0,28.0,33.0,17.0,AACCCCCCFBCDCCGCFBEFDGGDCGFCFFCAECBGBFCBGEHDEFGHFGHACHGFAGEAFFFCHFDGCHGDGCFGCFGCAGDBFFBECEGCGGBGHBDAEDABFABFDBDDBDAADGHHFBAECEBHAHHEFADFADFACAACGECEEAGEABADBDHEGEDGEDBFAHGAHGAGCDFBAGBGFFDCHBHEACGGBGB,False +765,18.0,15.0,16.0,11.0,14.0,19.0,16.0,15.0,CEFGFFADDDDCFAFGAFEEEAEHBEHCECAEBAECABHACHFCFGBGGBDABCFFFGFHGHGDEDABBABBAHFACGDFGDFGCBEEDFHACHGCHGBHFEGFAACECDGCHGBHCBHBAHAF,False +766,2.0,0.0,3.0,2.0,3.0,1.0,2.0,7.0,HHEHHCCHDGHDFCEHAEGA,True +767,17.0,7.0,6.0,11.0,18.0,9.0,7.0,8.0,HEEBEFBEBEEGHEFCEACFABFHBGEAEAACAADAADADDAFABDAGDEDAGDEDHCHFABEGDEFDEAEECEGHHHFGFAC,False +768,7.0,8.0,17.0,12.0,13.0,9.0,9.0,18.0,EBDDBCDHEEEGCEFDAFDABCBBHFGHGGHDCHFEHFAHAEHCFHCAHEHBEGECHEGDECCCCDCBHCGHCBFGECACHAFHDCDDHFDHG,False +769,20.0,21.0,9.0,15.0,21.0,8.0,21.0,20.0,HEDAEDGBFGHEDHEDHEBCGAEAAFAABHDHAEHGGGBEFDFFAAEAEHCHBCHACDBFGBGABHBBEBBAHBHHDABDAGDHEFEGBGGDCGEBGCHECHECHGBEDBEDBAAFGADBAGAHGBGDCGEEGEH,False +770,21.0,9.0,20.0,15.0,18.0,14.0,11.0,20.0,AGHAHEGHACBCDEHDEHEECGABBADBFCHFEABCBDEAGEAFEAFECFDCHDBDFADCAGCADCHDEADAAHFABFEDCEGCHFHHCEACGDDGHFGAFGAHHHECAEHDHHABCEFCHFCGCCEF,False +771,4.0,4.0,4.0,6.0,5.0,8.0,8.0,13.0,HGCHGCEBAEDFEDHAHHGEHDDBGDEGBHGFHGFCFFCHADFFBHGAHFHH,True +772,4.0,7.0,15.0,14.0,7.0,5.0,7.0,12.0,FCECCEHCHDDHEFHDDAEHECCGDDBDDBEDBFCGHHHBHHBCABCHBCDEDGCHFDACDFCDGCGGAGC,True +773,15.0,15.0,19.0,12.0,10.0,13.0,9.0,11.0,CDFCAAHAADAADBHCGEAHFBGCBCCEGCDCCDEAGHAGECHFHFFBFBHFBADCADEHBECBABBHFECAGCDDCFFFHDFHDFAEGAEGBCCBCEDGBBCB,False +774,17.0,15.0,18.0,13.0,14.0,14.0,9.0,11.0,BDADABGFCGHCGAGHAGFFDCCBAGFHDFHCFHCBACEACBAGBACBECFEBGABFBFFBHHBDEEDEAHEAGFDEFAFFBDHBECCCCDCEACEHCEAADDCBAEDDEH,False +775,12.0,10.0,12.0,10.0,14.0,18.0,9.0,17.0,FFDFGDFEBAEBHFHFFBFCBFCBACEGDDCHCHDGBEEAEHAEBACCCCCAHEAFFFFFHGBHDAADAHEFHGFHEDCAHHADHGFGCHGFEEHDEHBEGB,False +776,15.0,9.0,14.0,7.0,14.0,8.0,10.0,14.0,FGGCGFEGFEGEBBABCCDCHEHHCHGFDGAEHCEFCEGCAACEACADHABADBFDCEDAABEACDGCHHCHAFAGHEHBEFEAHBAHBEH,False +777,3.0,5.0,7.0,4.0,6.0,7.0,4.0,2.0,ACHDGDFECAEGAFGEBDFBCFCCFHCEECDBGFBEFB,False +778,13.0,16.0,17.0,23.0,18.0,12.0,11.0,15.0,HGEDGCCFHBDHDDECFEHAEBAEBHDCCDFCDCHGHFGHAABCAFCGHCGCEFFEBAEBABBEHBGHBFFDDGDAEDAEABBHBBHEDFEFCDCEDCEDHHCGDDDDDAGFEBBCDDADCAEEG,False +779,0.0,0.0,2.0,3.0,0.0,5.0,2.0,1.0,DCFGFFCDFHDFG,True +780,4.0,14.0,9.0,15.0,13.0,16.0,18.0,13.0,GFHBCDDGGEFBDFGDFEDHCBBGEFEAFEHBDHGFFECCDHGHCGBBGBEDHDDEDEEDBCFHGDHGFHGFHGFGGFGBFGAFHCDCAECAEBBEDBGFBH,False +781,14.0,11.0,9.0,17.0,16.0,19.0,16.0,13.0,AHAEEAEBDCFCAFEACDFGBGHHFBHDBFDCHDHHEHFDGFAFEABDGEEEFHFABFCGFGGBCHBEGBHACEADGACGCFGBFGAFDAGBAGFDHEDEEDEFDEFDGHDGDDF,False +782,17.0,30.0,15.0,20.0,20.0,24.0,22.0,25.0,GBEGHHGHFDDAEABGCBGDDCCHFEBFGBGDBGDBGCAAFGAFDEFGEFEFAEFACBGEBAEBHBBHBCHEHHEAHDDCBCFDADDHDGHFEHBHFBDBDHAFHFFHGGAFCFGCHEEHEDFAGBCHBFGBCGDCGBHBBCFBDBDEBFEFHHCBHGBEBAEBHEFAAFDAG,False +783,18.0,12.0,19.0,16.0,8.0,23.0,23.0,21.0,CAEAGEACHFBBCABCACFADGBFCCFGDFGFBGHEGHCCHABHGBHFBGEAGCCFDAFDCHBGHCGHDFEGEHGEHFDHBDFAHFAHCGGCGDBFAGFHHFHGFDDHGHFDAGBHFHEDDDDCCGCCGADFAFGAFAAF,False +784,26.0,24.0,29.0,15.0,21.0,16.0,22.0,14.0,GEEGAEGABFAFGEBBHCCCGGBHGBFDAADAAGAFGBEBBCCGCAAHAAHDBEEBGEDADDADDAECAECBEBHEFFADBCGECGCCDCGACBACFDCFHFDHGHBBHDBCECEGCBGEBCEFAECCCHFGECGCBACBFFBGFHCECAFBAHBHHAFDAGDECAG,False +785,1.0,0.0,2.0,2.0,2.0,6.0,1.0,1.0,FFFEFFEDFCDCGAH,True +786,20.0,28.0,18.0,25.0,30.0,17.0,20.0,19.0,ECEDCEBGECGBDDAGEBEEHHADHDECGEDEEFEADEAFEAGDBDFCEFBDHBHAGAAGCAGCHHCHDBDFFEECADBAGFCBBEBDEHHEBHFAHFBCEBFEGEHADBDHBDHCDBGDBHDCGBFEADEADHAEAGBBCBACEACFDCBDHBDGEGGEBGEFGBFCBGHFGFFAB,False +787,5.0,3.0,2.0,6.0,9.0,8.0,2.0,4.0,DAEDAECHGCHBEFFEFEDFEDADHEDAEFBFABFHFEG,True +788,5.0,9.0,7.0,1.0,4.0,3.0,1.0,5.0,EBABAACHBEHFACBBFBBEABCDECHGCHBCHFC,True +789,12.0,4.0,13.0,8.0,13.0,16.0,10.0,11.0,ADAAEBAEGDFGHFGEBGADFAFFAFFEFCECEEFEGFEDFCCECHHAFDCFGHEHBBFAGFGHACECGHCDCCHCCHDFHDGAAEH,False +790,6.0,10.0,8.0,9.0,9.0,8.0,9.0,13.0,CEAHHCFHCFHBEACFACDBGDBEHBGGCGGAFDHFCHFEHBABBHDHGDEAHGBEBEGBEDHEDGCDFHDF,False +791,8.0,14.0,12.0,15.0,11.0,8.0,8.0,8.0,EBHEBDCADCAGCABCGDEADEAEECBEDADFEHECHDBHGEGCFDCFBBBHBBDGHDFFDFFGBGHBACBFCHGCDCDDEBDA,False +792,10.0,22.0,18.0,14.0,21.0,20.0,16.0,23.0,DBGEHGFDGFECFHGFEGFBAECAHFHECBABHGFACEBDGBCGHCECAEGBBCDBEGEEGHEAAECGBFHBFHAFHCFBCDHCDHDBHEAEEBHHBCCBFHBCCBHCEDDEDDEFFHHFHFFHEFDAGBFEBHCBHDBFDGGG,False +793,23.0,21.0,27.0,21.0,31.0,27.0,29.0,18.0,AGFCEBGEFGHCGECBEFEGFCBFDBFHCCHCBEDDAGFBDCCDCCDEGHEGHAFHGGHDGDBADBAGEAEAGFFCDACFACFGCFGHFHEFHEDECBEBHFGDEGCEGDBAFCCFACEEBDDHCECDEADFGBBEABHACFAEFAEHAEHEGBFCAHGEFDEAAHACGDBEFBDBBCBCEHGEFGFGGFAGDAGEG,False +794,24.0,20.0,28.0,18.0,24.0,31.0,23.0,26.0,HHAHBAHDAHGAHECHECDEHEEGEFCECEFDEDDFCDFCHBBHBHFCGGEHCAHCDGAGADGCHGHFGEEGAEBABBAEFDGDHFFEGCBFBGHBGABDBCAGCEFEBFCFAAAGAGBABCAEAAFFBFFBEBDDFFCFFHFFECFHDFGCCACFAFHCFECECCFGHFGBAGBCDHHHCCHDCEDAEDGHFG,False +795,31.0,20.0,15.0,24.0,20.0,24.0,18.0,24.0,DDFDGFDGAGEBGEBGFHEDHBDBGHCFHBDCEACAGHADHGHFGBFHCDHDHEEHGGDGGEGDFGAEAEECGFCBFABFADAADAHGCFFHBFBAFDAFDBEBAAHAAHAAHAAFABCABEBEFDHDHEFHEDABHCDDDHBHCCGDHAECAEBEHAFBACEADFBFFEAFCAFC,False +796,6.0,5.0,4.0,8.0,8.0,11.0,14.0,10.0,AGGGDBHDBEDHHCHFAGFGEECFFAFFAEDAEFEGDBGHHFHDFGCGHAGHGGHGEBCEBDFGDF,False +797,13.0,13.0,14.0,16.0,20.0,20.0,14.0,14.0,FDCFDCDGCDGAFFFFHFBDGAEEFDHFGHGBFDAFHGFHGDEDDEADCHGBHGBACAHBECACHEEEEBBDFCEBBEBFEHAGCEBAEFCEFAGFAHFGHFGCFECADCGEADEHDEBDECHB,False +798,16.0,22.0,7.0,24.0,22.0,17.0,26.0,9.0,EFHFGCFGEDGFBGFBHACDACDAGBBGECEBBBDDADDADHGGGBGGBFEEDEFDEAGEAGEAFEDDBDGCDBBBGHGDHCDBDDEGEAFEADEABABBHFBFDBFDFEEFADGADECHBGEGFFGBBHEGGFDGAGAHGEE,False +799,20.0,13.0,23.0,31.0,20.0,22.0,27.0,27.0,ACCDDCDDCHDEGDBGEBHAHGDDDCDAHDGFAGHAEBFECFBCDECBAHEACGAEGFEFFGHADDGDDACEACECCFFFDFGHBHDBHDCFGCGACFCDHCBHEFDBDGCDCDEFDEFAGHAFHAHHCEGGDBGFEGHEHHAGFEBFGAHCBHCAHDADFGDEHDHHAGHFEHGEGGDGGBF,False +800,7.0,7.0,4.0,8.0,5.0,4.0,9.0,2.0,BFADCAGBDGDDGDDAEDEFBEABEBECGDGHAGHAGFGBABCGFC,True +801,27.0,24.0,11.0,26.0,22.0,20.0,24.0,21.0,FDEFHBBHDBDFECFEGGEGBBBFGBAGBGFBAEHFGHCAACHBBHBDHEABEFBAFGEDECDEGFGGHDGAGGAHCBHEEEFHEDHADFDHGEGFAAACDFDDFBDCEAHEBHEAAEFBDABAABHABDAGDADFAHFGHFGHCGDFGEBCDBDAGDBGHAHDADAGECDACDE,False +802,24.0,16.0,21.0,28.0,24.0,24.0,17.0,24.0,EHGDHECEADBDCGFCGDCFDEFDHFEEBHECAGBDHDDAAAAGEHGCCGBEGCEGEFDEBDAAGEFCAFABFBEAGEAFECCDDCDDHDHFDEFGAACEEEHGHHADHFHADHFCCAHGACGAHECBEBBDFBCFBHADDAGDCDFAHFAHFABFEBFECFHDBHDBHDGHFHFCDF,False +803,20.0,21.0,21.0,27.0,21.0,19.0,21.0,15.0,CHCDAADHHDHFEEFGGDBGABGCBCFAHFHFFGBDEBFEAFEHBEFDEFDAHCGGCDFCGCGECGEAGDBCEBGAADFADFCDAEDBDAHAEHAEGGEGAHGADFCHCCHBDBBGEADDADDBFDBCBBCBEGDDCEEAGDCGDFDEGBEBBFBAHCEHCFCFD,False +804,1.0,2.0,0.0,1.0,3.0,0.0,1.0,2.0,HBEHBEDEAG,True +805,17.0,17.0,12.0,11.0,12.0,11.0,11.0,14.0,CACCACHGBBBBABBDBGEGCAGFBEFAEBAECGBHHHHHHHFDEFGCGGBBBAFFAFFACAACGACDDEFEEDEADHAHCBHDGHABHEBGCFAHBEDDDFEDA,False +806,8.0,5.0,13.0,9.0,8.0,4.0,5.0,7.0,AABDACCACDACDBCBEEHEHCDHEDGEDADGFFCCBCGBEHCHHDGHECCFDCFAEGA,False +807,2.0,3.0,6.0,1.0,2.0,2.0,5.0,2.0,CCGFCGCAGEGGHBBHBDCFECA,True +808,8.0,11.0,13.0,11.0,20.0,5.0,10.0,7.0,EDGEBEBGEBGECCCADEEEBCEGEDBECBCCDAEDHECHAGHGCDDFDBFEBFEBEEGEFHAAGABGDFHDCHACBEDGECAHC,False +809,19.0,18.0,17.0,18.0,21.0,24.0,23.0,21.0,GGGGAGFDDEHDEHAEFAGHHHHCBECAGCEGEBGABGFBDCHDBHEHHGHFAHGCBGFDCFDCFBEFHHDAGFFGCEEDHGDCADAAHEEDEBHHFAFFABFACCBCABHGCGDBEDFEGFCGFBFBBCBBDFEGFECFAHDAEDAEAEEDCBGGFFFHA,False +810,20.0,16.0,11.0,12.0,13.0,19.0,22.0,18.0,AGFCHFDDFBEHGEHGBHGDCGFCHEGAGADFAGGAHAFBABBFBBGGAABAAEADEBDGCHHEBGCAEAHEGCAGFHDFHFEHAGDGFDBFBBFADCGDBGHFGHCCCGCDGBBAAFFAFHHFEHFEHEE,False +811,17.0,22.0,15.0,31.0,25.0,25.0,18.0,24.0,HAFEGGECCHDGGGHDGCDGDEAAEHGEFGBGGHGBEFEEBCHAEHCFHDFHDFGDGDBGDAFBFFBFHEECEDBEDHDBEDBFDBFABDEFCHAEFEDHCDAFDCBDABDABFCBCDHEHFCAFCDBEDACDEHFFHFFEEEBDEHEBHBHHAHGBHDHGDBCABDADDFDAFGAF,False +812,13.0,7.0,5.0,13.0,10.0,18.0,4.0,11.0,FGEADHABHAEHFCHFAAEEAFEAFDAFABEGGHFFBBDBHCAHADHBFADCCHEDFGDFDDBDFEDFEHFDAFDFFEHFC,True +813,30.0,25.0,17.0,27.0,18.0,16.0,23.0,20.0,DGAGBDGFDGFAAACAGCEFHDAHDBHCBACFACFGHFEFBHHBDHBAEDAHCEFDGCAADABGABDEGDGCAGCEGBABEABDFGDFADFABGBHGAFGDDGHDAHDCDDEDGECHEHGFBBFHBEBBCBDGGHHCEHBEGBCGADAADBHEFDEFHEAADCCHEDECAAABABB,False +814,24.0,14.0,14.0,18.0,16.0,18.0,16.0,21.0,ACBABDDGDGCCHAEHAEFDEFGHFGHFGDCGEBFDBGGBFACACFAGEHGBAFBAEAAEFHEGHCAEAADDHCABFHHEDHDHACHAGHACHGCHCHDDHABAAFADDBBABFHCFGCFEDDEDDHFEHFEGFBGEAFEB,False +815,13.0,9.0,13.0,16.0,13.0,6.0,10.0,11.0,EBHEDEGACDDCDGCDACHFCECCHGBHGBHCBEDAEDHFAFEAHEADAAEADDFFEGBDGEHHABGGHGCCADCDDCDHCABEFBEDBAG,False +816,3.0,7.0,5.0,5.0,0.0,0.0,5.0,2.0,DDCDBADBHGBGBBGCCCACBAGBDGH,True +817,5.0,5.0,2.0,2.0,3.0,8.0,12.0,6.0,HCHGCGFHGAEAFGHFGHFGFEADEHDFBGGGGGGFBFABABB,True +818,1.0,11.0,9.0,4.0,7.0,7.0,8.0,7.0,GABGHBHDBHCBECBFGHFGBCBBFEBECCEFCDFCGHCFCDHEFGEGBEBHDG,False +819,2.0,2.0,5.0,5.0,0.0,2.0,1.0,5.0,CDACFHHFAHDBHCCDCHDBGD,True +820,11.0,24.0,12.0,20.0,8.0,10.0,7.0,16.0,DDBDDECFEFFEBFBBABHAFHGGCCADEHHABDDDDCGHFABFABFHDCBDBGDBCDBFEHHCBHADHADBADCHDCBDHBEHBHABCGBEGBCDCGHBDAEFBBBH,False +821,9.0,5.0,8.0,7.0,7.0,2.0,8.0,6.0,DCDGGAGGCHGCHBBEEAGEGEFCEDADAADAAFCABCEHCBHBEHCAHDDG,False +822,4.0,6.0,4.0,6.0,8.0,10.0,6.0,8.0,DGEHGBHAFDDFEAHBFCBFCDFADFCDHGEHGBFCBHEHGEBEEHEFGFFA,False +823,11.0,21.0,15.0,29.0,14.0,28.0,25.0,13.0,GCBACBGFGGFADDGDDHCCBEGFEGBDBBDFFEFECFBCFBFFGFFGDDHHDFHEFDEDDAFAGFDEBEBBDDHDEHGCHFCGCAGCFGDGGHCFBBFBDCGGEGDEBAHFDEADEADFCDGABFDDFGDCGBFADABDGBHGHGFHFDHFEBCB,False +824,9.0,9.0,18.0,17.0,22.0,11.0,12.0,16.0,HDHHDBHCFHEEAEBDEDAEDBEDBHHAFFDDFCHGCHECDDCEEEFEDGADGCDCCHCAHCAHCEHGECGEGGHFDCCEECACBGCEGFGDEBAFFAGCGBEEEFDEFDBHBH,False +825,13.0,14.0,23.0,11.0,13.0,29.0,17.0,16.0,CFBCFDDFBDFBHFHGFAGEAFFBHFCCFCFACFACFDCAEBHFGGBAGDEEHBGFAGFHEDHGFEBFHHFGFDCFCBHEEGGCFGEFBCADHHDBFDBHDHACHCCGCEGAGGFFACCAECFHCGBCEFCEFCAB,False +826,5.0,8.0,5.0,6.0,10.0,4.0,3.0,7.0,DDEDAGAAGAHCDDBBHBGEEFHECEFHEBHEFHECEECBBCHBDFBA,False +827,20.0,17.0,26.0,28.0,18.0,27.0,26.0,26.0,ECFEGFEHFHHFABFABFEHABHAGDBHDBHDBGDGCDGHABHAFCEHDBHGCDCEFEEADECDAFBGFEGFBAAGDGDDEEDHDABDABFAGFDGDDADCBDAHGHHGHHFFFFFGCDEDGGCBCFEDGCCGCCDCEFFHHAHDBHAFCCFDGBCCHACHDEGGEGCCDCCHCBGFAAFEGFGCHHF,False +828,10.0,8.0,14.0,9.0,25.0,17.0,21.0,17.0,ECHGCHBCGEFDEFDECDEGBECBHBHHFFGGFGGHDGHACCAHHBDCFGAFGAGEEHEAHECEEHEEBEEGDECFEBFECFHFFGGGAEGHEGFCFBAGAHEEGDAAHFHCFGEEDFGDC,False +829,3.0,3.0,1.0,2.0,3.0,6.0,4.0,4.0,DHEHHDFHGGBAGAFEACEGFBFFBF,False +830,13.0,14.0,5.0,14.0,12.0,16.0,14.0,22.0,GDABFFCGFEHEGFFBHCBHEDHFGFBBFEDEHDHHGFHAEHAEHCEHABHADGEDGAFGHBCHAGHADHEFHFFGFGBAABAABDGBDCHDGBEAFHHDDBDHBFHDEG,False +831,30.0,21.0,25.0,25.0,16.0,20.0,17.0,32.0,ABDAGCAGBEEEEFEEFGBFGACGBHGBHCAACAACGCHGHADHACEECHDHACHFEGEAGDAHDAHDGBBHBFHGCHEHHAFGFFDDBGHHDHDEHABBACBHCADFDDHBDHBDCDCBDAHFFHDDBFHAGCDBFFEECCECCGHAHCAHBEHDACDAHDFCDAHDBBFFBAFCFFCAHAAGAC,False +832,25.0,27.0,23.0,20.0,26.0,20.0,20.0,27.0,AADBAGBCFACEEGDFBFFBFHCGDBHEFHCFBFBEEBHCCHCHBEBGABDAHDFHDHHFEHGECGFCBHDFHABBDDBDFHDGCGCCGCDGCHBHEEDEHDHBDEEHEGHBBHFBHFBGCEGEDAEGAECCEAAEACBAHDEBAEBFGACGAFAHDABAHDGCDEAHEAFECFGAACBACHAGBFGE,False +833,25.0,13.0,14.0,24.0,17.0,12.0,19.0,18.0,AEBDEBFCFGAEEHEAHBAHDCFDHFBFAGFAGAEGCCDCAAGAHEHHGAHEACFDEGDCFBAGGABGADGCDGFEBFEAAAGAAECBGDFCDBEDHEBCDDHDDHDGHDHHGCHGEBGHCAHDEEDCDDBADAAGABHDDF,False +834,15.0,10.0,18.0,19.0,15.0,14.0,14.0,17.0,GFDGHHGDHFHCFDBEBGADGACECCHHCHFAHCEHCHHDEHAEBADDGDBGDEEDECDFCAFEEFEDDHDCGAHBAGBDEADGHEFDFABCEBFGBCABCFGCFACGDHDEHACACCAFGF,False +835,20.0,10.0,18.0,14.0,16.0,28.0,23.0,12.0,CBFFGFCHEDBFHGFEGFEGFEDCEDAEHAGGGGFGGCCCDGCFGCFHAFBAFBDFCFFHAAGCEGAEGHEGDFAFFCDFADECHEAHGFGEHGEBDDBABFABABECHCFGCDDFFGFAACAAEDHGGHECDBAFCAFAF,False +836,30.0,20.0,19.0,16.0,19.0,13.0,25.0,21.0,GEHGEGBFGFCGFAGHHGFGGFDHAAHECBAGGAGHCGBCABFHBECAAHAFCEBCEACEADDADCGHBDHGFEDBCAEGAHGHCGHCGEBBHGDHEDHDFBEBBFADEAHEACBAEGFDCAABAABAABGAEACHBHDGADHAEBACHDGDAGCEDCEFCBF,False +837,11.0,6.0,11.0,21.0,12.0,11.0,14.0,20.0,CCGFFHDFDCHECHGCEGCGGDDGABGAEHDEHGGHGHDDHDABDHBHFFGEFHDAEDFEDFGFAHHHCFHAEDGEHCHFDADDGDBADAHDAHDCDCCBEHBEAE,False +838,2.0,11.0,5.0,5.0,5.0,11.0,2.0,7.0,HHAFDBFCBFHBFCBHCFEBHEBCFBFEBEHBDDDEDCABBFFGFFGH,True +839,10.0,18.0,12.0,15.0,22.0,22.0,14.0,20.0,GHGGHDGHEHCFHBHHGHGFDFFBHGBDFBCFBFEBAHAACAEBAFCEFHEABGAHCBCCADAEHFDHFEFFEHFEHCECGHFEBFGCFDBBDBDDCEDEEDEEFBFFGDBBEBGEAEHFDCEGEEDHGDHBF,False +840,6.0,5.0,3.0,4.0,8.0,4.0,5.0,6.0,HFAHFAGABEEHFEBBEABCGBGAFGAECDEDHEHHEDGDC,False +841,22.0,25.0,12.0,20.0,30.0,18.0,24.0,19.0,CFDABGGBGGDGGBGDBGDFEHGEHAEDEEDEEAEGABBABHABFEGAAAAFAAGHFEEEAHFBBFBDHEHAGHADHFDHEDHEDCFAHFEHGEHEEHCBBDBBGBGEBCEBFEHDCFAGFECABGDHEFFEBEACCHEGEGCAFDACECDGDBHEFCGFGGBBBDBDDA,False +842,26.0,32.0,18.0,28.0,33.0,16.0,26.0,21.0,BDFEACGAHGEHBEFBDDCDDEBGFBAHCGBBGCEDEHBAFGGFBDFDABCCBFCBHEBEAFGAEGFEGEDGAABBHBDCAAEAEEBEBGDGGDGHDHHCACBEGGDHADHGEFEBDEBDHBDHBEHBHDDCDFCDCGAGGEGGEGFECAEABEAHDAHCFFCDHAAHAACAABFEEEBDEBDGBDBCEEHDBGEBEAHF,False +843,17.0,15.0,21.0,18.0,10.0,19.0,19.0,11.0,GCGCCGCDBAAFCFFCGCCFCBGCBHBGADGFEEEBEDCFDCFBEFAEGDDDDDAGACDEFDBFGCFGEFDDHCGGGGGAFACHACHACGADGHHCHBFAAFDFFDABBEBFHBHEBHCAHBADGABFDC,False +844,28.0,20.0,25.0,32.0,29.0,10.0,34.0,16.0,GCBGCEAHBHHGHCGADBHDGAFGCFEEFDEAABAAFACGACHAGEEEEEBDBDDGEAEBGCFGAFGCGACGAGFEDAGDAGDBGDFEBECDGBDHBDBBDAEHADAAHGDCGDEBAHBEDCGBEGHEDHCCEDDEDCEGCDHDACAABADGEEFCEFGGAHGCCGCBECECBDHDCADAGDGGDGGDECHEBD,False +845,9.0,18.0,18.0,15.0,16.0,16.0,18.0,30.0,FHHFCHBCEBFEBFBHCGHEGFEDEHABHBHCEHCGGEGGCGGDGHDFHBFHAGACEDBBBBBFHEDHAHHBHEGHEHFDHEBHDDHCDCDHCACADBHDAAEGHFCCECCFHHBHGDHCDHFDGFBGFGGECAFBFCEG,False +846,25.0,21.0,20.0,25.0,14.0,20.0,19.0,27.0,DHHAHHGHBEBFFBHACHBCHFEAFHAGEAGEDFFDHACGDCGEBDDBGEAFAAGAAHAAFCFDCAEFBEGHGDCFAEDABDABHGBHGFHFDGDDGDDHFBABCADDACHBCHCGECACDBCGBCFHEHCCBBHHHFHFBHECEDHDAHDFDDFBBFDBEGACGACGADG,False +847,19.0,22.0,26.0,32.0,24.0,20.0,17.0,30.0,FFFFFBEBBCDDHBEHDHHFHCDHCDBCDAFBHDGHDECDEDGEDCBFEFEHAHHAEDBDGHDCHECDEFHHADHCHBCHCDDCHBBHBEECCDFEDFDBGDBDFBEBAEFAHAGFECCACDHCEHCGGCGGCAGABCAGAGCDBADGEDFEGAEGAEHACHCBHABDBEDEDDHADGGFBFFHEFHCAH,False +848,9.0,6.0,11.0,10.0,14.0,15.0,7.0,8.0,EBECBHGDFECFDGFDHFDCEAAGDEFDEFDFFHCAHGBDDHDHFEGEGBAFCEFCAFCACCACBAFHFEHEEFEGAEBC,False +849,4.0,12.0,3.0,4.0,4.0,6.0,9.0,4.0,BADBFBBDBCDAGGEGGAHFBHFECBBGGCGGBBGBDFFHFEHAEB,True +850,11.0,16.0,15.0,13.0,9.0,18.0,8.0,14.0,AHEFHEDHAHCBEFAEABEBBDHGAGCECCECCEDGADFFBFFBFFACACDFCDECHHFDFFHFFGFBAHBCDBGDBGHHGHFBDBHDBCCFHDACABDGBCBF,False +851,14.0,6.0,9.0,8.0,8.0,11.0,8.0,4.0,CADAAFAFGGBDGBECHEGAEGCEGHEAFCGCCAFCAFDBEHBAAAFAFFECEDADGACFBDFHDFBD,False +852,13.0,17.0,14.0,11.0,14.0,23.0,28.0,19.0,AHFBHFEDBHCBHGDHDDBEFGAFBEDCEDCGGCAGCHGCHGCDCEEGFBBFHCGHAGDCFEGABFCBECBAFBAFHHGHEBCFAEGGEGAFBFGGGDGBDBFAEEBGAGHAFHCFHFFAGFHGFHFFHGGBGGHDGFE,False +853,17.0,14.0,15.0,18.0,12.0,25.0,14.0,18.0,FEEDCEDAEDABFABGHCGEGBAFBAFADFDDFBDFGDGEEAEHDGHCFHCHGBHFHFACAEBGHHGHAGAAFFDCCDHCGGCFDCFHCGECADCFDBFEBFBDGHDCHCHDAFFFHFBBEAFADFHBFHFAB,False +854,4.0,8.0,7.0,9.0,7.0,13.0,4.0,5.0,HAHBAEBCEFDHFGBFDDFDDFCGFBBCBFCFFCAFEDFBCGCDGEHEEDFDHFEBA,False +855,8.0,9.0,7.0,8.0,14.0,11.0,8.0,11.0,FCGGHEGHCAHEGDGCDHEBHEGEEFAEFCEAAFAHDEHFEHBGFBFFBFEAHEADCBBCBBCEGDDHFDFBHEAD,False +856,15.0,19.0,19.0,21.0,20.0,23.0,9.0,21.0,EHCABCEDCEDCHDBADEFFEAHGADFHBFEBFEHFEGCHGBBFBDFDCFHCFCGHCDHEHADFFEFHCGHCBABEEBEFBCDBCEHDACDBBDCBACBAEBDDCADFAEFEEHDGHDEEFBFFDHGHFGAFAHFCGFHBHDADAHC,False +857,8.0,14.0,12.0,26.0,12.0,12.0,24.0,18.0,DDGDGFHGDEEDEHGEDDCHGCAGDGBBHHAHDBHDBGACHCCHFCHGGHDGHDBFABCHGHGFDCEAGEADEGDADEGHBCFBGFGDCGBFDFFDCBDCGDGBEGBFGEHHEFHDFGDAEDBDDB,False +858,3.0,12.0,7.0,10.0,7.0,11.0,5.0,6.0,EHBFDFFCEGCEBFAFCCFECFHDGCEHAEFDBFDBAHBGHBGEBCDFDDFBDBDGBHBBD,False +859,15.0,8.0,5.0,5.0,11.0,6.0,8.0,9.0,AFHEGGEGBEDBACAADADGGHGFEGCEHCDAFECBBABHHEHAECFHBAHGABDEBAEFAEFAHAA,False +860,24.0,23.0,16.0,29.0,25.0,13.0,28.0,31.0,ABDBGHHDBEAACAHBDDDDHHGAHBDHDAHCGHCAEGFECFECGHAGBBDBDDBDGBDBAEBACDAHDBGDBCEBGEDDEBDBBABGGGGGEHAEGGGDFHDAHAHFAFDCHDCHEFBEAGECHFCHGGEGGAGFDHADEGHAFHBGHEFBCAGCAEBHEDHEDEEDFEGFHCEHDHHFCHEAGECHA,False +861,19.0,16.0,16.0,18.0,22.0,19.0,15.0,18.0,HBDHADGAFFFCFDCFDHFAEEDEEABBABHHEAEDAHDEHCGFEECHECEFGHFDHFEEGCBDFDGHDGHDCBDCAECAHBACGEFBFFAFBAFBEDHDAHBBDGEGCEGBGDFGAFGAHCHGFECAEGABAHBACBECECD,False +862,23.0,28.0,34.0,23.0,21.0,19.0,19.0,23.0,AADEFDECBCFBFEGCHHCBCAHCAEDAEDFGBAHBGBBGEDGEFBAFBABEABFAHFAHADGBHAAHAAHCFCAECBEHBACDDCDCHDHHDAHDAHCFBCDHCBBGDEDEHFBCCCCCDGEDEEBCBHCDEBEHBCGCDECGCCGBCGBCFAGGACBHBFCAGCFBDHBFHFECFGHEGCEFDDFGDG,False +863,11.0,5.0,11.0,10.0,13.0,17.0,9.0,9.0,HGFAGHEGFFAEFGCHCCHCFACEAFEAFBFFBEEDDDGGDFEBHDFEDFEFCEHCDAAFBAFHCFECHEDDABDAGCCGAHGEF,False +864,8.0,4.0,8.0,5.0,6.0,11.0,2.0,13.0,CGDDADAFHFEHACHFFHAFHAGABEFBHHCHFCFBEHCEHDEFDCFEFHCAHCAHB,True +865,6.0,7.0,13.0,8.0,5.0,5.0,10.0,8.0,EBBEADDABHGBFBHDAHDFCCCCCGDCGACEFCEGCGGCDHHBGHCGCGBFDDFEAHCAHG,False +866,13.0,18.0,13.0,24.0,13.0,21.0,16.0,22.0,CECHEHGAHDBHAACGDDGDDGBGFBACBAFGCFGEBHHBHBBFBBFGDFEBHDBAEEAGEHFEDGEDFFHFADDADFHCHEADCFDBEDCDDFFBFFHFGEFGHCDFBHADHFDHFHCGCAGDACEBDHBDGDHGCHBH,False +867,3.0,4.0,1.0,1.0,0.0,0.0,2.0,1.0,BGHBGBAABACD,True +868,12.0,15.0,8.0,11.0,24.0,11.0,16.0,16.0,GBGAFGAHEABDAHEEHEGHFBEGHCHHCBDFECAADDGHFHFGEAGEBCDGEDBEFEEFGDGGAHGDHEEHBEHGEAGECGEAHECHBBEFBHBBDBBDCBFEFEEFECAAD,False +869,14.0,6.0,19.0,11.0,20.0,15.0,11.0,18.0,AFHAEHAEHGFHACHADFFGGFEGFEGDEDBAFBDECHHGHCCDBCFECHCHFBEDEECHACDGFDCHCEHFHCFACEACEACBCGBGEADECEEGFEHFACEDHEDHAGHFCA,False +870,7.0,10.0,10.0,16.0,6.0,4.0,11.0,16.0,HCBDCBHCBACDCCDHFHAGHCCDECGEDGDAFHGHGBDDFADHGDHBDHBGHFHEAABGBDHEDHEHHEGDDGADGCBB,False +871,6.0,1.0,1.0,3.0,2.0,4.0,9.0,6.0,AHCGEDGAHEAHAFGAGGBHGAHGFGDFGFHD,True +872,3.0,5.0,3.0,3.0,6.0,1.0,1.0,2.0,BBBDCBEGHEFHDBADAECAECEE,True +873,2.0,1.0,1.0,2.0,5.0,1.0,2.0,3.0,HEGAEHAEBCFDEHDEG,True +874,7.0,21.0,14.0,14.0,9.0,12.0,13.0,10.0,FDBFBBDBADBHBAGDHHCGEFDEBGEGGFGBCGEADAGGADHBDFCDECGBCEDFHFGHFEAFGHEDCEDCBFCBCCBHBBHBBDCBFGBCBHDBCAFC,False +875,6.0,6.0,10.0,12.0,5.0,8.0,13.0,6.0,GCGGCGGHBFDDADDBDFBDGCFGAEGAFBBCBHHFDHADHAGCDGEDEFGGCECCHDCEACGDFF,False +876,19.0,14.0,14.0,17.0,5.0,8.0,26.0,9.0,ADBACAGCHGCFGHDADABGEDABDABAFGCFDCADGGGGGGGGGBGGBACCHHAAGAADAGDAGDCGDBFFBCFBEBCEBGBBHEGDDCCCBHHAFGDGADGDDAFCGHHE,True +877,11.0,23.0,26.0,15.0,25.0,13.0,27.0,20.0,DHHEHGFGGCEHCGDGEDHCDHBFEDFEAFHBDGFCBHCEECEECBHCACGACACHGBHGBGGECGBDHCFEEEHCGHCGHCEBEFBGABCDDEGGEGGEGFEDBEBBGBCGBHABGEDCABCFECAHHBBCBDCAGBDGBAGCAHFHEBCEGCDFFDEF,False +878,10.0,21.0,12.0,20.0,16.0,27.0,18.0,16.0,EGCEHFAFAEBBGACGEEDEBDEFDBBDCBDEDFFAFGHBDFBHBGHBEBEGDDGDGBHGBHBFFGDFCFGCFAEGHEDEEDEAFFFFFFCHGGDGAFGAFHDBHEBCAGHBFDFFBHFCHFCHCCDCFDHBDGBDBHFA,False +879,13.0,7.0,15.0,3.0,11.0,11.0,9.0,9.0,CHBCFBFGEFEHCCAFAAFCEECBBHEEGEFBEABAADGAGGFGFCGACEHCHCFECADCACCACFAHFHDGHGAHEB,False +880,18.0,17.0,11.0,7.0,12.0,11.0,12.0,19.0,GACGHHGCCDAEAEBAFGHFGHEHABHBDHGCHGCHBABEEBECDDBABBHFHGCBGCBFAAGDAGHHHCAFCABAABAABHAFDAFBGDCHFEBEEHEFHEFBFHE,False +881,15.0,14.0,12.0,18.0,16.0,16.0,10.0,24.0,EFDEFDHBEHAEFFBHEBGEFABHGEHDFHAFEBCDGDAFDAHAACDACDGCEHDBBBBHDHEAEFAHGDFDABHABHAEHFEHFHHFHBFHAFHAEDCGBGGDDHDEHCBCCHCEFDGGHCDCC,False +882,1.0,3.0,4.0,5.0,7.0,5.0,2.0,5.0,HDHBCGDFACFECFEFBDFDGHEEHEBHEDCE,True +883,10.0,19.0,13.0,15.0,16.0,14.0,11.0,10.0,FDEBDAHCBEFHFHGGHGEBGCHCEECDACEFBAFHCBCEBAGBFGCEGBEHDDHBDHCDAFDEBDFBDEADBADBAECAGDABCGDCFBGFBDFBEFBFGBEHEECF,False +884,4.0,20.0,14.0,12.0,17.0,18.0,12.0,16.0,DHCFHCBHGFHFEDFEDBCDBFHHGCDFADCGHFBDCBDHAGEFBEHBEDCEGCABFHBHCCCCBHCGGFGFFBFBBEGFEBBBCGEGHHHFDAFDEFBEFHEGDEBEEBEEB,False +885,4.0,5.0,7.0,5.0,3.0,5.0,11.0,4.0,GBBEAFCABHGBGEFGDDCBDCFGCAGCDGCGHEGHFCHFGAGD,False +886,4.0,2.0,5.0,6.0,4.0,7.0,8.0,6.0,DEGFEGHBGCGHBGHDFAFFAFDADGCHECDECFFCHADHGG,False +887,7.0,10.0,2.0,12.0,7.0,8.0,10.0,7.0,HDGHAEDCDDBGDBAEBGCBDAEGFGFBGFBDDBFHBEHADFGDFHHFHEDGADGAFEAGEBB,False +888,22.0,21.0,26.0,15.0,24.0,25.0,19.0,23.0,HFHEFEAADAGDBCEBGEBEFHEGHAGEDGADFEBFCBFBBFCEHADFEHGHHFDFCHFCHDBGDHAAHFCFAEBAEGCEGCFFAHHGHHFHHCHCBABGDHHDFABGCFACFECDEAGEAGFBCFGCEGCBBBEBAGHGGCBAFACFDCDDCFCAHCACCBEEBEEBEADCCEF,False +889,14.0,18.0,14.0,7.0,16.0,10.0,10.0,16.0,FHAHHEDDECCCHBCBBFBFCBACDAGHAGHBFHBCHBEGEEGBBGBBGEAEAHHBEFFEAFEDHECEEGABGBDGCABEABAFCHCAACGBHHAHCDHFECFED,False +890,18.0,20.0,25.0,21.0,23.0,27.0,22.0,23.0,ECFEGEBFABFABCDBFHBHABHBDHGFGBFGECGCFHADHDEACCBHFEGFACHECHFBACCCBEBBDFDAEAABDAECCCFCFFCFFCEGCHBEGDEDFBDEGHFCHFCFDCFEGGEGDDGHDHHCGHFDFBDHGHHAAHAEHFGAFGAEADEFCEFBEGBGGHDAEDCEHCDGBDG,False +891,21.0,17.0,16.0,20.0,21.0,17.0,22.0,30.0,GEDGFABBHBBHFAGAEEAEAAECAEHHHBDDCABHGGHGCBAAFABFBFCGEBFEGEHHEHHDDHFGEEHDGHCAHFADBADCCGACHDGHAGHAFHAFBECBEDHGCHGAHGBDCEDCDBFDEGHGADGDHGFHCDGDFHBHHBHAECFECFEGFHFEDCED,False +892,2.0,4.0,1.0,8.0,1.0,2.0,5.0,5.0,HHHHBDABDGBDFFDCAHGGGBDGDDED,True +893,15.0,5.0,9.0,8.0,9.0,2.0,15.0,5.0,GGEGEEDAFGECACCAGFGEEDECDBAEGADGABAACCACCAHGAHADHGDGGHGBACBHBDEGAAGD,True +894,15.0,20.0,23.0,20.0,17.0,18.0,26.0,16.0,FGDFCFCCGBFEBEEDACGECGHCFFEDBBCHBFHBDAFHBGCFCCFAGHDGDGGBFEEGCEGAFGAEAFEDFEDBBDHBHGGGGCFDCEHBEHGCAAAAAGHCHHCHBGDDCDBGBBCABCABADBADBFDGGCCEDEEDGCGGDDGHCFHEFH,False +895,17.0,14.0,14.0,9.0,18.0,14.0,9.0,18.0,BGCDCCFADADBGDGCAEEAGEBEFBHHAEFFEHFEBEBCGCEBCEDAGGAHEABEABDAFDHBHHAAHBAHAHBAHCEHCAHFHBEHFCFFCEFCEHCHHCAEDFEDBGFGF,False +896,10.0,10.0,7.0,13.0,14.0,14.0,10.0,8.0,HCBCDHHGEAFHFCDGHEBDEAFBCFEDFADEADEADABBHCAEDGDDGFDAFHHFDGFGGFABFBCDBCEAGBBGEFGEFEEFEE,False +897,1.0,6.0,2.0,6.0,4.0,12.0,5.0,5.0,FBDGCGGDFEBFEFFEGFBGFHFFDFHBAHFEDFCHBBHDD,True +898,8.0,2.0,6.0,2.0,1.0,5.0,2.0,3.0,CFFCHDCFEHHAADAACCABAACGAFGBF,True +899,13.0,11.0,11.0,13.0,12.0,11.0,12.0,9.0,FCCGCABEBEEFCBGCDGCAECEEHAEGDCFFHDBCABDABEAFCBHABHADHGDFGDFBDFEDGHBGDGDAGAFECHEGDEGHFAHDABAF,False +900,11.0,8.0,16.0,15.0,15.0,12.0,12.0,10.0,HFDECDECFHCHGDEDEEBGHDAHDABCCDDFGDCGBCACCDGGFCGFEHEAGEAGEAFCCHCCAFEAFADEADHGDBFBBFBBFGCEAHFCDEEDHEG,False +901,6.0,5.0,13.0,12.0,14.0,4.0,0.0,2.0,DEEDEFCACAAEHEECDECAHCBDDECCBCFFDBFBCDECEECEDCADEDDEDACB,True +902,5.0,2.0,3.0,0.0,2.0,4.0,3.0,0.0,CFECFBAGAACAAGFFGBE,True +903,1.0,3.0,5.0,2.0,2.0,3.0,3.0,5.0,HEAGEFBCDBCBCFHCFHCDHGHG,False +904,8.0,10.0,8.0,10.0,10.0,10.0,8.0,8.0,HAEHAEDAEDGHFGFFAFFBFFGDABDECDEGGEGHBHBBCCFEDGECBCCBACHDCAFBDDEEDAHGBHBF,False +905,19.0,35.0,22.0,16.0,17.0,18.0,22.0,17.0,BEDEDGGBEBBDBGHBCBBCBHCAEAHBAGBCBHDBHDCHGCBGDAGDCCAGDGCDFCBFCBDBBDHAAEAGEGGEGBAFBHFGFGBFHEACECCGHCFFEFBCFBAFAABBBBBHDBEFBHFAGBEFCDGCFCDEEHBBFBDCGDEGFHGACAACAHHFGHEABE,False +906,6.0,6.0,11.0,1.0,5.0,2.0,8.0,3.0,GGECBACGCCGHCBFEGGAACAACDACBBCHCEFCEHBEGBG,True +907,10.0,11.0,15.0,22.0,12.0,15.0,10.0,11.0,CBDCFAHHHHCHDBDDBEDHCAECDFFDACDGBDABCFBCFBGDCFFCFEEHGGHGADGDFAFACGDCADFBCFGDFEDFDDADGAHEBHFCHDCDEEBEEDEGBE,False +908,4.0,0.0,2.0,5.0,3.0,0.0,2.0,3.0,GHACDADAEDAEDEGDHHC,True +909,1.0,4.0,0.0,5.0,2.0,3.0,1.0,1.0,FDHBDABFEBDDBDEGF,True +910,9.0,19.0,26.0,20.0,13.0,12.0,16.0,22.0,BHDCHGCHBCHDCBGCAEDFEBFBHDBHDGHEGECGCFDCHHGHHBHGFGCCBCCDCHAADFFDFFHEDCFBCEHCEHCDDFAGECGDBDBGFGEECBHCBACBACHCDEFDAHBCHCEGBGGCDDHDEHBAGBADB,False +911,5.0,1.0,2.0,3.0,2.0,3.0,0.0,2.0,HAHAADAFBAFEFCEDCD,True +912,26.0,20.0,25.0,15.0,11.0,21.0,19.0,28.0,BGFDDHABFAGCACFBCDBGDCCAAAHAAHFCHCEGGFFHHFBCABCGGGGBHEAHCAHBAHAHHACHFDHDAHABHCBFEBFADFGDCGFFHCGBCFBDFEDCHBBHBCGECGEHGFHAEHACHADAABHFDECEGBAGDHFDHCCFGAEGAECABFFBHCCHD,False +913,7.0,7.0,5.0,3.0,0.0,6.0,1.0,6.0,CDFCAFHACADCBBHBFHBFHFDGCABBABFHHAA,True +914,20.0,24.0,25.0,24.0,19.0,23.0,23.0,19.0,BDHFDGCHCAHFAHFGGCHBCHDFEDAEHCBFEBCGHCGFEACCAHDFGDFDBFBEFBEBGDBGDBCDECBFHEEEBCGBDDFDECHEHBFCAFADGADAHFCFFGFAGFEGEHGADDHDCHDBDDGEDBHABGGBEGBAHBHBDCFDCACCGEAACCACGAEGBEFBAFCCFGBAG,False +915,6.0,10.0,1.0,9.0,16.0,12.0,5.0,11.0,BFGFHGADDEEEEBEEHEHHEHFEBEGHFDHFBHFBDFDFFEBGDHCEBEEBEAGDADHAFAAFHBBEDF,True +916,19.0,25.0,17.0,15.0,26.0,25.0,27.0,16.0,EBBHBCGEEAEBCECGECHHCGDCECGECDBCDBAGCHGBFDBDBCEBFAAGAAHBGDFGAEGAEHEEHECGFFAFBEEAEEABEHBGHBFHDGCCFEFFCFFGFDHBAHAGFDGFDGHGGEDGEBGHGFFECBAFBHGEFBFGDFHDAADGGBAGBFCBFDEFAFBABE,False +917,1.0,1.0,0.0,2.0,5.0,1.0,1.0,0.0,DABDEEEEGFE,True +918,3.0,4.0,4.0,5.0,6.0,2.0,1.0,2.0,FCHDCBDCDEADEBDEBFBGACAEHEE,True +919,29.0,30.0,27.0,23.0,18.0,16.0,15.0,25.0,CECCDDBFGBEHCFACFCCAAAAABGDBDCBDABFBCEACABCGBHGDCGFBGHCDHCEHCBAFBFGHFHHDHFEHFEHCDBDDACBACGACGACFEDEBDHBDHAAEEGFBHHBHDAHBGBCGDAAHAFEBCCBDBEEAHEHFGHAHAABBABDHBDADDAECGBCEDCDCGEHAEHABBFF,False +920,6.0,8.0,6.0,2.0,10.0,1.0,2.0,2.0,ABABBFGBDGEECCEACECHEHBEABDBEEEACEACB,True +921,9.0,6.0,2.0,9.0,10.0,5.0,13.0,15.0,EBEDHGAHGFHGFBDEDDGCDGDHFAEABEGEGAHGAFEAGHAHHEHDEHDABDBGEGGBGHHACHFHH,True +922,0.0,4.0,4.0,4.0,5.0,3.0,8.0,5.0,BFCBHEBHDBCDFGGEGFEGEHGHCDHGDGGEC,False +923,9.0,18.0,18.0,28.0,20.0,33.0,20.0,19.0,FCFHEFDEBCBBCFACFDCDCAFCAHBDHBFGFHAFEAFEHGCHGDHCDHCFCGDCHBEGFFGDFGBHGDFGDFGFAHDBGGHHABEDFFDFFDFFEBFHDCEDFEFHEHHDGACFFGHBBHBADDDDCDEGDGGCEFCDBEBGEDEEBCEFGFFBEDGEDBFDE,False +924,2.0,5.0,0.0,7.0,6.0,1.0,0.0,3.0,EEDEEHEBAEBDDDADBHDFHBBD,True +925,12.0,20.0,17.0,18.0,18.0,15.0,13.0,21.0,GHHFHBACCFFHHFHHABHGDHFDEBABDDBCAEHABDEDCGDGDDGCDFFDHEBAEBAEBDCBGCEGBEHBFCEFDBGBFGBHBHHFFEEGECGECGECBHGBHDCHDAFDCFDEAHAHEAHACCEEFBBDCC,False 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+976,27.0,32.0,25.0,20.0,17.0,19.0,24.0,36.0,HCFABFDBGEFGFDCBDCAEBHEDADCADCGBCDACDBBHBBDAHAHHFFGEFHHBBHEFAEDHEHHBHHDAHCACCDDDAHCEECBBHBHHBGDBGBBGHCAHCFHFHGCHGAEGFFBBHCBHAAABACEGCGGCGACFACGHBDCBHCGGEHEBGAFFAEHHDFHDFEGFABDABGBBECBEBGAAFAACGHGHHGDH,False +977,21.0,23.0,33.0,29.0,26.0,21.0,26.0,19.0,BFCBCBEGFEGDEGFEBDACFGCDGADCDDCBBCGCDDCGCCGDDGBFBEEBAABAACFCCFHDDHDEBDEFCEBBGBEEDAEAHFCHFHHEBEEFFEFHEADEGEGGCGGADDFBCADDDCCGCCGCDGEDFADGDFGFFBCAAHAHEFHECAGFGDCEDCADBAHHHHEHHEFHBCCCCBBAABCAHHDGBEGCGG,False +978,7.0,8.0,10.0,5.0,10.0,5.0,5.0,1.0,DECDEBFCGFADFEBAECABABEGGECDFCGBEGCEHCBDCBCABCAEAFE,True +979,1.0,2.0,1.0,6.0,0.0,1.0,0.0,1.0,DCADFBDHDDBD,True +980,24.0,21.0,18.0,12.0,17.0,7.0,12.0,18.0,BBAHBHDDHBHFAHACBEBBCBAEEACHAHHEGBBGBCDCCAECAHCAGGAFFACFAHHEEAEHFGCACEACHFCHDDEDDEDDCBCCHEBHBAHEABBGBBADBGBBEAAGAADHEGEGGEGAFDACC,False +981,22.0,33.0,18.0,23.0,27.0,28.0,28.0,13.0,EAEDGBCFBAFBGFDAFAAGHAEBFHFFHFFGACDBDFCDFGDBEBBDHCFBEEGGDAGECGEFABFGBEDAEAHEGDDBEGCDABHBBGBDFBDHBGBBEBBHABAABDCEFGAFGAFBFCEFBGGHAGAFEDGEDCHFHBFGDHCFHCAGFDGCGECFECBECBECECABCAEFBEFEEGDBGDEGDBGD,False +982,22.0,20.0,15.0,16.0,27.0,17.0,27.0,21.0,GDFGHEGBEHCEBCHBEHBAHGCGGEGBBFDEADFFHADHEBHGDACDACDEBEEGEHBEGBEGHEBFAAFGFFGDFGDFABGHFHCEECHDGBDCBFFBGCBDDHDCGBCFAFHGGHEGACHECAEAAHCABAACAHEEDEADEFEGBGGEGAAGEBGFAHHAE,False +983,6.0,5.0,6.0,11.0,8.0,8.0,5.0,7.0,HBFHDFCEABBADECDEGDFCDFHBFEDECCFGHFAHGHHADEADFCDGDDGEBAE,False +984,9.0,13.0,13.0,13.0,32.0,25.0,15.0,18.0,EEAEEGEABEGHGFDADEEFAHHCBFGDCBBCHBCFDCFDCFDEFDEFCHFEFECFEHFHGFHGFHEBBCGECBDHHEEDEFCEGAADEFEHGEDFEHFEDFEGBHHFHGEEGEGAACFABFGFDGBEECEEFHBFHB,False +985,14.0,10.0,10.0,7.0,7.0,11.0,13.0,6.0,FAFAHGABAACAAGAFCDDCGCEFDBGBGACHECAECAEBAHDDFDBFDBFGBAGCHBEHBAGBECFFCEFGGGGGFH,False 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100644 --- a/README.md +++ b/README.md @@ -1,36 +1,10 @@ -# N-Back Sequence Generator with [Hidden] Markov Chain +# N-Back Sequence Generators -**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! +This project contains Python implementations of various sequence generators for the n-back task. -**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/src/main/scala/org/xcit/nback/markov/models/State.scala b/src/main/scala/org/xcit/nback/markov/models/State.scala deleted file mode 100644 index fbbd844..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/State.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * A Single state with a label in Markov chain - * @param label A simple string label, representing the state and node - */ -class State(val label: String) { - - /** - * Keep track of transitions from this state to other states. - */ - val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() -} diff --git a/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/src/main/scala/org/xcit/nback/markov/models/Transition.scala deleted file mode 100644 index bc20a9e..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/Transition.scala +++ /dev/null @@ -1,8 +0,0 @@ -package org.xcit.nback.markov.models - -/** - * A Single transition in Markov chain graph. It is stored in "from" node. - * @param to the ending node of the edge - * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). - */ -case class Transition(to: State, probability: Double = 0.0) diff --git a/src/test/scala/ThreeBackBenchmark.scala b/src/test/scala/ThreeBackBenchmark.scala deleted file mode 100644 index 0c7dad9..0000000 --- a/src/test/scala/ThreeBackBenchmark.scala +++ /dev/null @@ -1,7 +0,0 @@ - -/** - * TODO Benchmark 3-back simple sequence generator - */ -class ThreeBackBenchmark { - -} diff --git a/tests/benchmark_diagrams.py b/tests/benchmark_diagrams.py new file mode 100644 index 0000000..8fa448e --- /dev/null +++ b/tests/benchmark_diagrams.py @@ -0,0 +1,159 @@ +import pandas as pd +import numpy as np +from matplotlib import pyplot as plt + +import benchmarks.common as common + + +def tlratio(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2,ignore_index=True) + stats = [] + for trials in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == trials) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == trials) + targets2 = data[alg2].targets if alg2.shape[0] > 0 else np.nan + targets4 = data[alg4].targets if alg4.shape[0] > 0 else np.nan + lures2 = data[alg2].lures if alg2.shape[0] > 0 else np.nan + lures4 = data[alg4].lures if alg4.shape[0] > 0 else np.nan + stats.append([trials, (targets2/lures2).mean(), (targets4/lures4).mean()]) + stats = pd.DataFrame(stats, columns=['trials', 'tl2', 'tl4']) #.dropna(subset=['skewness']) + + plt.style.use('ggplot') + + plt.ylim(bottom=0, top=30) + plt.scatter(stats.trials, stats.tl2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl2[idx], 1)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.tl4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl4[idx], 2)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('T:L Ratio') + plt.ylabel('T:L Ratio') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_tlratio.png', bbox_inches='tight') + plt.show() + + +def time_per_trial(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for t in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == t) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == t) + time2 = data[alg2].time.mean() * 1000 if alg2.shape[0] > 0 else np.nan + time4 = data[alg4].time.mean() * 1000 if alg4.shape[0] > 0 else np.nan + stats.append([t, time2, time4]) + stats = pd.DataFrame(stats, columns=['trials', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.trials, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time2[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time4[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2v4_time_trials.png', bbox_inches='tight') + plt.show() + +def time_profiles(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 8): + alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + time2 = data[alg2].time.mean() * 1000 + time4 = data[alg4].time.mean() * 1000 + stats.append([ni, time2, time4]) + stats = pd.DataFrame(stats, columns=['n', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.n, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.time2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + plt.scatter(stats.n, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.time4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_time_n.png', bbox_inches='tight') + plt.show() + +def skewness(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 9): + all_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + skewed_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) & data.skewed + all_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + skewed_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) & data.skewed + num_of_sequences2 = data[all_alg2].shape[0] + skewed_sequences2 = data[skewed_alg2].shape[0] + num_of_sequences4 = data[all_alg4].shape[0] + skewed_sequences4 = data[skewed_alg4].shape[0] + skewness2 = skewed_sequences2 * 100.0 / num_of_sequences2 if (num_of_sequences2>0) else 0 + skewness4 = skewed_sequences4 * 100.0 / num_of_sequences4 if (num_of_sequences4>0) else 0 + stats.append([ni, skewness2, skewness4]) + stats = pd.DataFrame(stats, columns=['n', 'skewness2', 'skewness4']) #.dropna(subset=['skewness']) + + + plt.style.use('ggplot') + plt.scatter(stats.n, stats.skewness2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.skewness2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + + plt.scatter(stats.n, stats.skewness4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.skewness4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Skewness') + plt.ylabel('Skewed Blocks (%)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_skewness.png', bbox_inches='tight') + plt.show() + +if __name__ == "__main__": + tlratio() + skewness() + time_profiles() + time_per_trial() diff --git a/tests/benchmark_skewness.py b/tests/benchmark_skewness.py new file mode 100644 index 0000000..f468b4d --- /dev/null +++ b/tests/benchmark_skewness.py @@ -0,0 +1,97 @@ +import random +import heapq +import csv + +# Common parameters +alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'] +trials_range = (10, 40) +n = 3 +sample_size = 100 + + +def to_benchmark_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [str(ralph_skewed)] + +def benchmark_nb_gm_001(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_001') + + +def benchmark_nb_gm_002(filename): + import generators.nb_gm_002 as nb_gm_002 + + generator = nb_gm_002.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + # print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_002') + + +def benchmark_nb_gm_003(filename): + import generators.nb_gm_003 as nb_gm_003 + + generator = nb_gm_003.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + print(f"sequence {i}/{sample_size}: {trials} trials") + seq = generator.generate(trials) + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_003') + + +def show_skweness_diagram(filename, choices, title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + print(filename) + data = pd.read_csv(filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) #.dropna(subset=['skewness']) + #print(stats.trials) + #plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'{title}.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + benchmark_nb_gm_003('../benchmarks/nb_gm_003_2back.csv') diff --git a/tests/common.py b/tests/common.py new file mode 100644 index 0000000..e40c0df --- /dev/null +++ b/tests/common.py @@ -0,0 +1,27 @@ + + +# Common benchmark parameters +choices = alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F'] +trials_range = (10, 65) +n = 4 +sample_size = 100 + + +def count_targets_and_lures(seq, n): + mask = 'D'*n + for index in range(n, len(seq)): + if seq[index] == seq[index - n]: + mask += 'T' + elif seq[index] in seq[index - n - 1:index - n + 1]: + mask += 'L' + else: + mask += 'D' + return mask.count('T'), mask.count('L') + + +def skewness(seq, choices): + import heapq + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return ralph_skewed diff --git a/tests/nb_gm_001_bm.py b/tests/nb_gm_001_bm.py new file mode 100644 index 0000000..54f6cb3 --- /dev/null +++ b/tests/nb_gm_001_bm.py @@ -0,0 +1,75 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq) , str(ralph_skewed)] + + +def benchmark(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets / s.trials, axis=1) + plt.scatter(data.trials, data.targets_ratio, alpha=0.2) + plt.show() + +if __name__ == '__main__': + alg = 'nb_gm_001' + fn = f'results/{alg}_{n}back.csv' + benchmark(fn) + # skewness_diagram(fn, alg) + targets_ratio_diagram(fn, alg) diff --git a/tests/nb_gm_002_bm.py b/tests/nb_gm_002_bm.py new file mode 100644 index 0000000..c8af543 --- /dev/null +++ b/tests/nb_gm_002_bm.py @@ -0,0 +1,105 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq), str(ralph_skewed)] + + +def benchmark(filename): + from generators.nb_gm_002 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials, int(trials/3), 0, 0) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +import time +import numpy as np +import pandas as pd + +import benchmarks.common as common + +def profile(): + from generators.nb_gm_002 import SequenceGenerator + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, int(lures/2), int(lures/2)) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('benchmarks/results/nb_gm_002_profile.csv', sep=',', encoding='utf-8') + +if __name__ == '__main__': + alg = 'nb_gm_002' + fn = f'results/{alg}_{n}back.csv' + profile() diff --git a/tests/nb_gm_003_bm.py b/tests/nb_gm_003_bm.py new file mode 100644 index 0000000..fa6c19a --- /dev/null +++ b/tests/nb_gm_003_bm.py @@ -0,0 +1,114 @@ +import heapq +import csv +import random +import time + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq, time_per_block): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [time_per_block, ''.join(seq), str(ralph_skewed)] + + +def benchmark_skewness(filename): + from generators.nb_gm_003 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['time_per_block', 'seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + targets = trials / 3 + t = time.time() + seq = generator.generate(trials, targets) + t = time.time() - t + print(f"sequence {i}/{sample_size}: {trials} trials, took {t}s.") + writer.writerow(to_csv_row(i, seq, t)) + plot_skewness(fn, 'nb_gm_003') + + +def plot_skewness(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def plot_targets_ratio(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +def benchmark_targets_ratio(): + pass + +def benchmark_chunking(): + pass + + +def benchmark_n(): + pass + + +def plot_timing(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['time_per_trial'] = data.apply(lambda s: s.time_per_block / s.trials, axis=1) + plt.style.use('ggplot') + plt.title(f"{figure_title} - average time to generate a trial") + plt.ylabel('time (s)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.time_per_trial, alpha=0.5) + + # draw fitted curve + # import numpy as np + # p = np.poly1d(np.polyfit(data.trials, data.time_per_trial, 3)) + # plt.plot(data.trials, p(data.trials), color='red') + + plt.savefig(f'results/{figure_title}_timing.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + alg = 'nb_gm_003' + fn = f'results/{alg}_{n}back.csv' + benchmark_skewness(fn) diff --git a/tests/nb_gm_004_bm.py b/tests/nb_gm_004_bm.py new file mode 100644 index 0000000..b4ad4a8 --- /dev/null +++ b/tests/nb_gm_004_bm.py @@ -0,0 +1,26 @@ +import time +import numpy as np +import pandas as pd + +import tests.common as common +from generators.nb_gm_004 import SequenceGenerator + +def run(): + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, lures) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('tests/results/nb_gm_004_profile.csv', sep=',', encoding='utf-8') diff --git a/tests/results/2v4_time_trials.png b/tests/results/2v4_time_trials.png new file mode 100644 index 0000000..9be91b4 --- /dev/null +++ b/tests/results/2v4_time_trials.png Binary files differ diff --git a/tests/results/2vs4_skewness.png b/tests/results/2vs4_skewness.png new file mode 100644 index 0000000..a488e1f --- /dev/null +++ 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+210,87.0,0.0,0.0,88.0,1.0,0.0,0.0,0.0,EDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +211,0.0,0.0,12.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCC,True +212,0.0,0.0,0.0,66.0,0.0,65.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +213,1.0,0.0,0.0,0.0,0.0,21.0,22.0,0.0,AGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFG,True +214,74.0,73.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +215,0.0,5.0,0.0,0.0,6.0,0.0,0.0,1.0,HEBEBEBEBEBE,True +216,0.0,1.0,0.0,0.0,0.0,53.0,0.0,54.0,BHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +217,70.0,0.0,0.0,0.0,0.0,70.0,0.0,0.0,AFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +218,0.0,0.0,0.0,0.0,0.0,0.0,36.0,35.0,GGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +219,0.0,90.0,90.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +220,0.0,0.0,0.0,0.0,0.0,0.0,37.0,38.0,HHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +221,0.0,0.0,44.0,0.0,0.0,1.0,44.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +222,0.0,0.0,0.0,67.0,67.0,0.0,0.0,1.0,HDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True 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+409,0.0,0.0,72.0,1.0,0.0,0.0,72.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +410,55.0,0.0,1.0,0.0,0.0,0.0,55.0,0.0,CAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +411,0.0,59.0,0.0,0.0,0.0,60.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +412,61.0,0.0,0.0,61.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +413,0.0,1.0,0.0,75.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +414,0.0,53.0,0.0,0.0,0.0,0.0,52.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +415,0.0,0.0,16.0,0.0,1.0,0.0,0.0,15.0,ECHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +416,0.0,0.0,0.0,39.0,0.0,0.0,0.0,38.0,DHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +417,96.0,0.0,1.0,95.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +418,28.0,0.0,1.0,27.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +419,0.0,1.0,92.0,92.0,0.0,0.0,0.0,0.0,BCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +420,1.0,0.0,20.0,0.0,20.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECE,True +421,0.0,90.0,0.0,0.0,0.0,0.0,89.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +422,10.0,0.0,0.0,0.0,0.0,1.0,11.0,0.0,FGAGAGAGAGAGAGAGAGAGAG,True +423,0.0,0.0,0.0,74.0,73.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +424,0.0,0.0,127.0,0.0,0.0,0.0,1.0,0.0,GCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +425,1.0,9.0,0.0,0.0,0.0,9.0,0.0,0.0,AFBFBFBFBFBFBFBFBFB,True +426,0.0,0.0,84.0,0.0,0.0,0.0,0.0,84.0,HCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +427,33.0,0.0,0.0,34.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +428,1.0,30.0,0.0,30.0,0.0,0.0,0.0,0.0,ABDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +429,0.0,0.0,67.0,0.0,1.0,67.0,0.0,0.0,EFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +430,62.0,0.0,0.0,63.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +431,1.0,9.0,9.0,0.0,0.0,0.0,0.0,0.0,ABCBCBCBCBCBCBCBCBC,True +432,15.0,0.0,0.0,0.0,0.0,0.0,14.0,0.0,AAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +433,0.0,1.0,0.0,65.0,66.0,0.0,0.0,0.0,BEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +434,0.0,160.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +435,0.0,0.0,1.0,0.0,42.0,42.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +436,0.0,0.0,55.0,0.0,55.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +437,0.0,0.0,0.0,1.0,0.0,73.0,0.0,73.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +438,79.0,0.0,0.0,0.0,78.0,0.0,0.0,0.0,AAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +439,0.0,0.0,67.0,0.0,0.0,0.0,66.0,1.0,HCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +440,0.0,0.0,77.0,0.0,0.0,1.0,0.0,76.0,FCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +441,0.0,0.0,0.0,0.0,153.0,0.0,0.0,1.0,HEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +442,0.0,88.0,88.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +443,0.0,0.0,0.0,20.0,22.0,0.0,0.0,0.0,EEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +444,41.0,0.0,42.0,0.0,0.0,0.0,1.0,0.0,GCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +445,0.0,0.0,0.0,47.0,0.0,46.0,0.0,1.0,HDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +446,1.0,0.0,0.0,0.0,86.0,0.0,0.0,87.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +447,56.0,56.0,0.0,0.0,0.0,0.0,0.0,1.0,HABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +448,0.0,0.0,0.0,0.0,11.0,0.0,0.0,10.0,EEHEHEHEHEHEHEHEHEHEH,True +449,0.0,0.0,0.0,0.0,0.0,1.0,92.0,92.0,FGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +450,0.0,0.0,0.0,6.0,5.0,1.0,0.0,0.0,FDEDEDEDEDED,True +451,66.0,1.0,67.0,0.0,0.0,0.0,0.0,0.0,BCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +452,0.0,0.0,0.0,13.0,0.0,1.0,12.0,0.0,FDGDGDGDGDGDGDGDGDGDGDGDGD,True +453,1.0,0.0,0.0,0.0,56.0,0.0,56.0,0.0,AEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +454,15.0,0.0,0.0,0.0,0.0,0.0,0.0,16.0,HAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +455,0.0,21.0,1.0,0.0,21.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True +456,93.0,0.0,1.0,0.0,92.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +457,1.0,0.0,0.0,0.0,35.0,0.0,0.0,35.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +458,13.0,0.0,0.0,0.0,1.0,0.0,13.0,0.0,EAGAGAGAGAGAGAGAGAGAGAGAGAG,True +459,0.0,0.0,65.0,0.0,1.0,0.0,65.0,0.0,ECGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +460,0.0,0.0,95.0,1.0,0.0,95.0,0.0,0.0,DFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +461,15.0,0.0,0.0,0.0,1.0,0.0,0.0,15.0,EHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +462,0.0,0.0,198.0,0.0,1.0,0.0,0.0,0.0,ECCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +463,84.0,84.0,0.0,0.0,1.0,0.0,0.0,0.0,EABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +464,0.0,0.0,0.0,0.0,0.0,60.0,0.0,61.0,HFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +465,0.0,179.0,0.0,1.0,0.0,0.0,0.0,0.0,DBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +466,1.0,0.0,90.0,0.0,89.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +467,0.0,35.0,0.0,0.0,0.0,34.0,0.0,0.0,BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +468,0.0,0.0,0.0,1.0,7.0,0.0,0.0,7.0,DHEHEHEHEHEHEHE,True +469,0.0,0.0,0.0,0.0,92.0,0.0,91.0,0.0,EEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +470,0.0,0.0,46.0,0.0,0.0,1.0,46.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +471,0.0,0.0,0.0,0.0,0.0,1.0,158.0,0.0,FGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +472,1.0,0.0,0.0,0.0,0.0,58.0,0.0,59.0,AHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +473,0.0,0.0,6.0,1.0,0.0,0.0,6.0,0.0,DCGCGCGCGCGCG,True +474,0.0,0.0,0.0,0.0,0.0,98.0,0.0,97.0,FFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +475,0.0,87.0,0.0,0.0,0.0,0.0,0.0,85.0,BBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +476,0.0,0.0,33.0,0.0,0.0,0.0,1.0,33.0,GHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +477,45.0,0.0,0.0,0.0,46.0,0.0,0.0,0.0,EAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +478,0.0,0.0,0.0,77.0,0.0,0.0,75.0,0.0,DDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +479,73.0,1.0,73.0,0.0,0.0,0.0,0.0,0.0,BACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +480,0.0,1.0,0.0,0.0,37.0,37.0,0.0,0.0,BEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +481,0.0,92.0,93.0,0.0,0.0,1.0,0.0,0.0,FCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +482,0.0,0.0,0.0,1.0,0.0,0.0,0.0,24.0,DHHHHHHHHHHHHHHHHHHHHHHHH,True +483,25.0,0.0,0.0,1.0,0.0,25.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +484,0.0,0.0,0.0,0.0,0.0,37.0,0.0,36.0,FHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +485,21.0,0.0,0.0,1.0,0.0,20.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +486,0.0,35.0,0.0,36.0,0.0,0.0,0.0,1.0,HDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +487,0.0,0.0,1.0,0.0,97.0,98.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +488,0.0,93.0,0.0,0.0,0.0,1.0,0.0,94.0,FHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +489,0.0,1.0,0.0,93.0,0.0,0.0,93.0,0.0,BGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +490,0.0,0.0,0.0,70.0,0.0,0.0,72.0,0.0,GGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +491,86.0,0.0,0.0,0.0,1.0,86.0,0.0,0.0,EFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +492,0.0,65.0,1.0,0.0,0.0,65.0,0.0,0.0,CBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +493,0.0,0.0,0.0,69.0,0.0,0.0,0.0,1.0,HDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +494,0.0,0.0,144.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +495,0.0,45.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True 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+599,16.0,0.0,16.0,0.0,0.0,0.0,0.0,0.0,ACACACACACACACACACACACACACACACAC,True +600,0.0,21.0,0.0,22.0,0.0,0.0,0.0,0.0,DBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +601,70.0,71.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +602,0.0,0.0,0.0,1.0,0.0,0.0,53.0,0.0,DGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +603,45.0,0.0,0.0,0.0,0.0,45.0,0.0,0.0,FAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +604,0.0,1.0,56.0,0.0,0.0,0.0,56.0,0.0,BGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +605,0.0,1.0,0.0,0.0,0.0,0.0,0.0,195.0,BHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True 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+611,0.0,0.0,86.0,0.0,88.0,0.0,0.0,0.0,EECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +612,1.0,0.0,0.0,0.0,14.0,0.0,0.0,14.0,AEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +613,0.0,0.0,35.0,0.0,0.0,35.0,1.0,0.0,GCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCF,True +614,0.0,0.0,1.0,0.0,43.0,43.0,0.0,0.0,CEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +615,0.0,0.0,0.0,0.0,0.0,1.0,67.0,66.0,FGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +616,0.0,27.0,0.0,0.0,26.0,0.0,1.0,0.0,GBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +617,0.0,88.0,1.0,87.0,0.0,0.0,0.0,0.0,CBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +618,0.0,41.0,0.0,0.0,0.0,41.0,1.0,0.0,GFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +619,0.0,27.0,27.0,0.0,0.0,0.0,0.0,0.0,CBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +620,1.0,0.0,20.0,20.0,0.0,0.0,0.0,0.0,ADCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +621,0.0,0.0,1.0,24.0,24.0,0.0,0.0,0.0,CEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +622,1.0,0.0,0.0,0.0,55.0,55.0,0.0,0.0,AEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +623,1.0,0.0,0.0,0.0,26.0,0.0,26.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +624,0.0,0.0,15.0,0.0,0.0,0.0,0.0,13.0,CCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +625,0.0,0.0,1.0,67.0,67.0,0.0,0.0,0.0,CDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +626,0.0,0.0,65.0,0.0,0.0,1.0,0.0,64.0,FCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +627,0.0,0.0,0.0,0.0,89.0,1.0,90.0,0.0,FGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +628,0.0,0.0,0.0,0.0,1.0,0.0,51.0,0.0,EGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +629,0.0,0.0,41.0,0.0,0.0,40.0,0.0,0.0,CFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +630,0.0,0.0,93.0,0.0,0.0,0.0,1.0,0.0,GCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +631,0.0,53.0,1.0,0.0,0.0,53.0,0.0,0.0,CBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +632,0.0,0.0,0.0,14.0,0.0,0.0,0.0,15.0,HHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +633,0.0,29.0,0.0,0.0,0.0,0.0,28.0,0.0,BGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +634,0.0,66.0,0.0,0.0,0.0,1.0,66.0,0.0,FGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +635,0.0,0.0,62.0,62.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +636,0.0,31.0,32.0,0.0,1.0,0.0,0.0,0.0,ECBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +637,0.0,0.0,0.0,0.0,0.0,0.0,48.0,49.0,HGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +638,1.0,0.0,0.0,0.0,0.0,0.0,54.0,53.0,AGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +639,59.0,0.0,1.0,0.0,59.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +640,0.0,0.0,0.0,0.0,1.0,0.0,27.0,27.0,EGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +641,0.0,0.0,0.0,23.0,24.0,0.0,0.0,0.0,EDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +642,0.0,0.0,0.0,91.0,0.0,0.0,91.0,0.0,DGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +643,0.0,0.0,0.0,0.0,48.0,49.0,0.0,1.0,HFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +644,14.0,0.0,0.0,0.0,0.0,14.0,1.0,0.0,GAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +645,0.0,96.0,0.0,0.0,1.0,0.0,0.0,96.0,EHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +646,0.0,0.0,0.0,50.0,48.0,0.0,0.0,0.0,DDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +647,0.0,0.0,0.0,99.0,0.0,99.0,0.0,0.0,FDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +648,49.0,0.0,1.0,0.0,0.0,0.0,0.0,48.0,CAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +649,0.0,0.0,52.0,0.0,1.0,0.0,53.0,0.0,EGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True 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+667,1.0,147.0,0.0,0.0,0.0,0.0,0.0,0.0,ABBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +668,0.0,0.0,97.0,0.0,97.0,0.0,0.0,1.0,HCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +669,0.0,0.0,1.0,0.0,0.0,0.0,53.0,52.0,CGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +670,0.0,0.0,94.0,0.0,96.0,0.0,0.0,0.0,EECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +671,99.0,0.0,1.0,0.0,98.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +672,68.0,0.0,0.0,0.0,0.0,0.0,67.0,1.0,HAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGA,True +673,0.0,0.0,0.0,26.0,27.0,0.0,1.0,0.0,GEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +674,31.0,0.0,0.0,0.0,32.0,0.0,0.0,1.0,HEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +675,0.0,0.0,0.0,0.0,42.0,0.0,41.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +676,0.0,0.0,50.0,0.0,0.0,0.0,1.0,50.0,GCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +677,0.0,25.0,0.0,24.0,0.0,0.0,0.0,0.0,BBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +678,0.0,0.0,0.0,0.0,1.0,10.0,9.0,0.0,EFGFGFGFGFGFGFGFGFGF,True +679,65.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,DAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +680,0.0,23.0,0.0,0.0,0.0,0.0,23.0,1.0,HGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +681,0.0,1.0,58.0,0.0,0.0,0.0,57.0,0.0,BCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +682,0.0,0.0,0.0,0.0,0.0,68.0,1.0,68.0,GFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +683,0.0,0.0,0.0,0.0,96.0,0.0,96.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +684,1.0,0.0,0.0,0.0,66.0,0.0,66.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +685,0.0,0.0,0.0,0.0,0.0,1.0,0.0,21.0,FHHHHHHHHHHHHHHHHHHHHH,True +686,0.0,88.0,0.0,87.0,0.0,0.0,0.0,0.0,BDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +687,0.0,0.0,19.0,19.0,0.0,0.0,1.0,0.0,GDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +688,0.0,42.0,1.0,0.0,41.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +689,0.0,0.0,0.0,0.0,0.0,60.0,61.0,0.0,GGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +690,0.0,23.0,23.0,0.0,0.0,0.0,1.0,0.0,GBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +691,86.0,86.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +692,35.0,35.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +693,57.0,0.0,0.0,0.0,0.0,58.0,1.0,0.0,GFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +694,0.0,0.0,30.0,30.0,1.0,0.0,0.0,0.0,EDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +695,19.0,18.0,0.0,1.0,0.0,0.0,0.0,0.0,DABABABABABABABABABABABABABABABABABABA,True +696,0.0,0.0,0.0,1.0,0.0,56.0,0.0,57.0,DHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +697,10.0,0.0,1.0,0.0,0.0,0.0,0.0,11.0,CHAHAHAHAHAHAHAHAHAHAH,True +698,0.0,0.0,89.0,0.0,88.0,0.0,1.0,0.0,GCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +699,0.0,0.0,87.0,0.0,86.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +700,17.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAA,True +701,0.0,0.0,66.0,65.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +702,0.0,0.0,1.0,0.0,0.0,0.0,123.0,0.0,CGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +703,0.0,118.0,0.0,0.0,1.0,0.0,0.0,0.0,EBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +704,0.0,0.0,0.0,0.0,0.0,0.0,0.0,132.0,HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +705,0.0,0.0,0.0,0.0,0.0,23.0,1.0,23.0,GHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +706,0.0,0.0,0.0,0.0,6.0,5.0,0.0,0.0,EFEFEFEFEFE,True +707,18.0,0.0,0.0,16.0,0.0,0.0,0.0,0.0,AADADADADADADADADADADADADADADADADA,True +708,0.0,72.0,0.0,0.0,0.0,71.0,0.0,1.0,HBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +709,0.0,0.0,54.0,0.0,0.0,1.0,0.0,55.0,FHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +710,0.0,1.0,87.0,0.0,87.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +711,0.0,0.0,1.0,63.0,0.0,0.0,0.0,64.0,CHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +712,78.0,0.0,78.0,0.0,0.0,1.0,0.0,0.0,FCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +713,0.0,80.0,0.0,0.0,0.0,81.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +714,0.0,1.0,0.0,0.0,0.0,0.0,40.0,39.0,BGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +715,0.0,0.0,7.0,0.0,6.0,0.0,0.0,0.0,CCECECECECECE,True +716,35.0,0.0,0.0,0.0,0.0,0.0,0.0,33.0,AAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +717,0.0,0.0,0.0,1.0,73.0,0.0,0.0,72.0,DEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +718,0.0,0.0,90.0,0.0,0.0,1.0,89.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +719,1.0,0.0,0.0,67.0,0.0,0.0,0.0,66.0,ADHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +720,56.0,0.0,0.0,0.0,56.0,0.0,1.0,0.0,GAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +721,0.0,0.0,0.0,1.0,0.0,0.0,49.0,49.0,DHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +722,0.0,0.0,0.0,117.0,0.0,1.0,0.0,0.0,FDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +723,0.0,0.0,86.0,1.0,0.0,0.0,85.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +724,0.0,0.0,31.0,0.0,0.0,0.0,0.0,30.0,CCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +725,1.0,0.0,0.0,0.0,98.0,0.0,98.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +726,1.0,84.0,84.0,0.0,0.0,0.0,0.0,0.0,ACBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +727,0.0,56.0,56.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +728,0.0,1.0,0.0,24.0,24.0,0.0,0.0,0.0,BDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +729,37.0,0.0,0.0,0.0,0.0,37.0,0.0,0.0,FAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +730,0.0,0.0,91.0,0.0,0.0,0.0,91.0,0.0,GCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True 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+772,0.0,68.0,0.0,0.0,0.0,0.0,0.0,67.0,BBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +773,60.0,1.0,0.0,0.0,0.0,61.0,0.0,0.0,BFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +774,0.0,1.0,0.0,57.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +775,0.0,78.0,0.0,0.0,1.0,0.0,0.0,0.0,EBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +776,1.0,0.0,0.0,0.0,0.0,96.0,96.0,0.0,AGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +777,43.0,0.0,0.0,0.0,0.0,1.0,44.0,0.0,FGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True 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+989,93.0,0.0,92.0,0.0,0.0,0.0,0.0,1.0,HACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +990,0.0,1.0,0.0,0.0,60.0,0.0,0.0,61.0,BHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +991,0.0,1.0,0.0,0.0,0.0,0.0,32.0,32.0,BHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +992,0.0,0.0,34.0,35.0,0.0,0.0,1.0,0.0,GDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +993,0.0,0.0,0.0,0.0,54.0,0.0,54.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +994,0.0,0.0,0.0,1.0,0.0,39.0,0.0,38.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +995,0.0,0.0,0.0,0.0,99.0,98.0,0.0,1.0,HEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +996,86.0,1.0,0.0,0.0,0.0,86.0,0.0,0.0,BFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +997,0.0,76.0,77.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +998,0.0,0.0,19.0,0.0,0.0,0.0,0.0,1.0,HCCCCCCCCCCCCCCCCCCC,True +999,0.0,0.0,37.0,1.0,0.0,0.0,38.0,0.0,DGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True diff --git a/tests/results/nb_gm_001_3back.csv b/tests/results/nb_gm_001_3back.csv new file mode 100644 index 0000000..b2f89a4 --- /dev/null +++ b/tests/results/nb_gm_001_3back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,0.0,65.0,132.0,0.0,0.0,0.0,0.0,1.0,HCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCC,True +1,51.0,0.0,52.0,52.0,0.0,0.0,0.0,1.0,HCDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACD,True +2,0.0,61.0,0.0,62.0,0.0,0.0,61.0,1.0,HDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGD,True +3,40.0,0.0,0.0,1.0,0.0,0.0,0.0,80.0,DHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHA,True +4,4.0,0.0,1.0,0.0,0.0,6.0,0.0,0.0,CAFFAFFAFFA,True 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+401,0.0,55.0,55.0,0.0,0.0,1.0,54.0,0.0,FCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCB,True +402,47.0,0.0,0.0,0.0,1.0,47.0,0.0,47.0,EAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFH,True +403,56.0,0.0,0.0,0.0,58.0,0.0,0.0,56.0,EEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAE,True +404,0.0,39.0,0.0,0.0,39.0,1.0,40.0,0.0,FGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEG,True 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+3,12.0,15.0,11.0,20.0,13.0,17.0,17.0,22.0,AFAHGHGHGBEBCDDDDHHHABCEHEHEBBBAHADADCFHHHHHFEFCBDDFDGDEFCAGGFEFBDGEHECCBCFFFFFFHGEBBHHCBCACHHDDBFGGGGEGEAFDGDADGDGDGBEBAAHDDFH,False +4,4.0,4.0,8.0,8.0,5.0,7.0,4.0,2.0,FGDGECDCECGCDADAHFDFCFCGAFCDDDABEBHBEFEFBC,False +5,15.0,15.0,15.0,16.0,16.0,14.0,9.0,13.0,HGDGBFDHDADHBBBBBHBAAGBCEABCGFAFAFBGBCBFGDDDEAAAHDFACECECHFHFHFCFHEGEFEFDFDAAHDEECDABFCCCCGBEBDAHCECHCHEDEDEDAGEE,False +6,17.0,17.0,9.0,6.0,15.0,13.0,15.0,12.0,BEBEBHAGCFEHHABAHDEDGHFBFGFCAABAGFFFAFGECEBEAEAFBFCEBEGHGDBEFABABEGEHEHBGBGDADACAGHGHGBGBACGCAHFFBHAECDC,False +7,12.0,7.0,7.0,6.0,9.0,8.0,5.0,6.0,CEGBFEFEFEHCCDEBCCHBBBGAHACBGGDBDADACADHDHFEAEAEFGFAAEAHAFAF,False +8,9.0,13.0,10.0,11.0,12.0,15.0,11.0,12.0,CGCFDBDFHHEHFFGCDHEHCFCFAAEGDCEGHGCFCBBBCBGFGHGDFDBDADHBBEGAGABABHBEBEHGHADAFEFCFDBDEFEHEFEFA,False +9,13.0,26.0,23.0,14.0,20.0,18.0,19.0,27.0,HECEBEFFHFDCCFGBCBDBAHGHGCBBABHEFAFEBEBHBHGGCHBGGCCCCCFCBDDDEDHDEEEAAFAFGFDFCGBGHEHDHGHAFABCGGEHEHFBGBADEBEBEAAHBDCCFGGHHHBHBHGHBDBEEAEGCGCBCHCEFFFFCHDHCHDHABCB,False +10,14.0,18.0,15.0,13.0,15.0,19.0,18.0,11.0,AFACABDDFBBBEBECECGHFBFBECDCEEEDGDBHHGCBDDAFCBAAAGHCHCHEAFBFDHAHCFFAAAHBBBFBFBHGFBCBCFGGGHGDGDFEGEFCFEDGDGAGEGCGEGEFEFAFDGC,False +11,21.0,20.0,21.0,13.0,15.0,26.0,21.0,21.0,EECEFFHGCADHGEGEABCCFDEBABEBGGCACHFHFBFBFBAHGBGCGHDCDABHHAGABFHEBCFEGDFDFDFAFBCBCAHACFGFBFBFBFBDACCBCHFHEGEDFDFCAAAGGEBFAAACACHCHFGFBFGHGHAEAGCCEDDFHHHGHGHGDE,False +12,17.0,26.0,17.0,23.0,17.0,11.0,26.0,21.0,ABGCACGDDFHFHBCEHEAGBGBEBAHEBEBFAAHAFBCEGDGBAHGGGGFGDDDBABABHGGGCGDGHGHDACAEDEFECHGEGDABGCHCDDDDCBCBADAHCHGBGBGEHDCDBBFBABHBHBFBACHDEEHGHECDCDHDEFEDECFGHGBFBD,False +13,24.0,21.0,23.0,20.0,15.0,14.0,30.0,24.0,AHHHHAFEDHAFBFGFCFGADADCDGBBBBGDGEGBCBHGGGGCGFBFAGGGGHEEFEGHGHABCBFHGAGACBBDEDHDHDGBCACAHGCACEHECACHBHDCGCECADGDGDABADHFGCGAGAHHBGFDCHBHCAAABEEFDFDBDBEADAHGEGEHECCCBCFCAHD,False +14,1.0,0.0,2.0,1.0,1.0,1.0,2.0,2.0,DECGCGAHFH,True +15,7.0,7.0,10.0,5.0,8.0,4.0,8.0,9.0,HBABHHEEGAGAGEGHCDEECHCHGBCBCDDAEGCBCGEAEFDFBFBFAGCHCHCHAD,False +16,14.0,19.0,14.0,7.0,10.0,15.0,19.0,7.0,CEAFFGHGEGFDFDCACAGBDEAFCEDDFAHHFDFGBEACGCGBGAFECECFGHCEBAFGEGCBABEBHBHBACAGAGDGHBABCBCBGFGFGFGBBBBFBCBGA,False +17,17.0,15.0,14.0,12.0,10.0,9.0,17.0,6.0,EBACADACGBGBAFGHGHADCDGAAFFFADABAHGDGABBCBCACACECHFBFHDCACDGEBADDEGGGEDADFGFGCGFBBABCBEBDBCHGEGEGECE,False +18,14.0,22.0,17.0,9.0,14.0,10.0,25.0,20.0,EHCHAHEHAHCHCGBGCGCGAEBFBFGGCEFGBGHAHCBABABHHGHGCACHDEDBBABGGDGDEBBBHHGCAEGBFHGEGEGBCCGCDFBBGBFBDAEEHHHCFEFECEHGCGCBHDADFDAGAGAGFBB,False +19,13.0,27.0,12.0,18.0,19.0,17.0,20.0,18.0,BFGCGBHAHAHEFEDBABEBEDADGGGGBAFCGEBDFHBHGHGCBBEGEGBHDHDHBCBCACDBFHHCHBGAGAGEDADADCDCACGHEEEEBDFDFDHDCGGBGDEBBBABEHFHGEFFFBADHEFFCFDEBEBFFEBHBFBG,False +20,11.0,10.0,7.0,8.0,8.0,7.0,11.0,4.0,BGBABGHGCGFBFAEBGGEDEFAHEHACDCDADBGGAGAGADFBFBCBCEFBFDHDACCDAGAEEE,False +21,22.0,20.0,18.0,24.0,13.0,11.0,16.0,21.0,DADADHCACFCHEDAAAHGDDHAGCDEDEGBHAHBDBDBGHHHCHCECAAAEFEDECEDBHFABGBCAGDBEGEBABHFCBBABDFDGHGCBFBCCDHDHDGDHDHCHBGADAFACHEHBDCDAFAFAFAGGCGCFHGBDBEBEG,False +22,8.0,10.0,11.0,7.0,8.0,15.0,4.0,11.0,CBAEGDGEHEBGBFBFBDHCHFHBAEHFFGFCFBFCFEEHABECFFFFACAEHHDCDCDHDHAHCFCBCBAADF,False +23,32.0,19.0,21.0,23.0,13.0,27.0,21.0,27.0,GHCABDGDFFFAHHHEAEHGAGAGHEFEGBCFAFBFGCHCHFHBGCAFFDFDBACACHCHCHBFGFEACAFABEBEBHHGHFHAHGGAGAHAFCGDHDHAFGCBCHDAAAAAAFCFHGEFFBEBEDDDFDBCBDDDCGFAFADBDBEBCAGGHDFDFBCDEAGAHCCEHGHAHCDDDDABAFA,False +24,26.0,30.0,18.0,21.0,29.0,16.0,21.0,21.0,GDGDADAGAGDEHCDBDHAHEHFHAHAFBHBHGCEBHBDBHBHBEEABABABAEECEGEGAGADHDBEEGBCAADHGBFBCEAAHDEBEBFBFBFCCGCEFBABAEDBGFGBGCFCGEACDFEFBHDADFHCEAEBDHDCGBEFGCDCACDEBEGAGAEAEFDFBBEHEGEGHCACEFBHDH,False +25,17.0,15.0,10.0,21.0,16.0,11.0,16.0,22.0,BDBDBHHHAAGAEHEHCHCDADEBGHDAGEBHGAABADADEDECEHAHFBGCGBEHCGADFBHECGHHFFFHFBDDDDDFDFDFHFEDEDACAEAEBDCHHBFBABCBGDGEAECHHGHGEGHDAGGG,False +26,12.0,13.0,16.0,11.0,17.0,10.0,17.0,12.0,GEECBGFEEDHCEFGFEAEAHGEGEDDDHDCDCBHBCBCFCECEGAGAGAHECFCEAAFGFGCEHGHBBBGBGBCBDHEAEFHFHGBCDGGACHCGCDADAEBFBADH,False +27,14.0,11.0,17.0,13.0,14.0,21.0,16.0,19.0,AAECGGEGHCACACACHBHADCECBDHDHDFCFGHGDDEDHHHAHDFDACHBHAFBHHAEEECGGFGEGEBEFCFAEAEFFBFBFDGDGDGHFACCDFHFCGBBHBCGGFGEHEFFFFHFCBCAF,False +28,14.0,15.0,12.0,21.0,15.0,9.0,13.0,21.0,GGHGEDHFCFCACBCADAEEEEAHDGAGHGHEHEHBBECEDBBBDBEGDGBAEABCCABBECDDDFDFHGHGHDHGHGHDADHHCHBHCCBAFHFDDDEDHFHAABDFDFEGEAADBDCH,False +29,18.0,19.0,27.0,26.0,29.0,30.0,16.0,16.0,DEFFFAFAGDGEEBFBFGEBADACADFDCEEDEDFDCDEBBGDGHGHGFFFDFBEBEHCHFDCDCEGFGFHFEFCGBBDCHCGCDADEGEGCFAAEHEHFDACGCEABBDECBCBCEFEFBFCFCFEHEHDGACEBAGCEFEBACCCAEDHDHBCFCDEFFHDHDHDCFCAAAEBEBFDHA,False +30,5.0,11.0,5.0,8.0,3.0,2.0,5.0,1.0,BBFGGBABFGCCCDADAHBEDCDBABGEAECBDBDBDBDG,True +31,28.0,17.0,19.0,16.0,18.0,11.0,17.0,33.0,DHAFAHAEAHDHFHFAFADHCGGGDGDGHEBDHCHBHAEBCBCFEGHHHBHCAFDHEHEHCDAGBCBAAAGACCBCAFGBHEHBBEAHAHAFAEACGGEHAFABEDEDFDCGHEBGAGEEAEBBHDEDECHCGABHGHAHAHBHCHCHCHDGACACDFD,False +32,5.0,10.0,12.0,17.0,19.0,17.0,17.0,11.0,EEBHBFFFDDEDCCAGEFEGGDGDFFGEGEAEDEFCFCGCGCGFAEGECDHHCEFDDHDFDABFDECECEHEFDDGDGBBFBFHHGCECEFEHAHDHDGBBFBGHGBG,False +33,4.0,13.0,10.0,7.0,4.0,8.0,11.0,7.0,CGBHBCBCBHFHFECBADGBGBGBDBCFAGDBHGFGECEHBGBCCACFGFGFGDDDFCADHEHB,False +34,22.0,27.0,22.0,21.0,21.0,28.0,21.0,21.0,BABFBCCCCGCDCAGABAHFBAHCBDBDHDCDCDEFFHBHBCBCBEHDAGAEFBBEEEBEGAGHGDGCGEBFBDEAECCFCFGDGDGHBHAEFFFECCADHFFBGHDHEGAAEDEFEFCDCDCDEFCHADAEHFDFHBBEBEBFBFAFGFAAHGHGFFAFGGBABGHGBFBFDFHCHAHEGDA,False +35,24.0,23.0,21.0,17.0,28.0,15.0,20.0,21.0,EGHGAGEGCGDFFCEEEEEAHGEGFGFBCBGBDBACHCAGDDDDEDEHACGCECAFAFEFHCHCEFHDHEHBAEADBDBAFCHCEEEEHBHBECEAEAFGGGGCCHBHAAACABBEHFHBDFHHDHBGCAABEBGAGABBFADADEBBBBCDCACFGFHDCEHEBGADE,False +36,16.0,12.0,18.0,16.0,29.0,20.0,25.0,11.0,EEEBCFFDHDBBGHGHGEFDFACCCFCGAECECEAGFFFCFDAHAEEHGGGBGBGADDGDGEGCCBFEHEGEHACDGDGCCCFCEAFAEGEGBGFGBBBHFGDGFGAAHADADCEEEEDEAEFEAEBFFFHEGECEGEHECAFDDDB,False +37,1.0,6.0,2.0,11.0,2.0,11.0,4.0,7.0,DBFFFHHADFFEFBDBFBGDFFEBHBHFHGDGDGCCDDDDHDHF,True +38,11.0,12.0,15.0,5.0,3.0,15.0,15.0,13.0,HCCCCAEBGFCFBGAHHHHBAFGCGCGCGFGCAABFBABHBFBCAFHFAFGCDBGBGAGFCBBAADHDHDCGEGHGCGFFHFHDEFHFC,False +39,33.0,14.0,21.0,23.0,21.0,18.0,25.0,28.0,DHAHAHADGDAFAFGCHCHEHCHABACEDDDCGBHAEFFGCADADGBGCFFFGGHBAAFGGHFHFHECFCHCHBDEFGADDCGGGHEBEDEBEBEDFHCAAAACFGFBFBFADAEGBDCAGACACAFGEEECDDDDCGGGEEEEEGCADHHHHAHABAHGBBCACHEGGHDADADAHAHEHAH,False +40,9.0,21.0,8.0,6.0,13.0,11.0,9.0,15.0,HEBEGEGAGEBBBHFAFABCBCBEBCBEAFHGGGHEHCHBEDFFAFAHDBFBFBEBDFHHDHBHCHBHBDEFABGBCEDEBCACHHEAGBGF,False +41,13.0,18.0,18.0,16.0,8.0,20.0,16.0,13.0,AGDGBCDHFADAGFFFHHCFCFEBGBGFGFGCGCHHHHCGFBFGDHABCBCGDGECEFBFCACBDBDCFAFBDEDCFFBHGHBEBABDFDFDHDHACABDBAFAFDHEGACACBEECGCBDG,False +42,21.0,15.0,14.0,22.0,14.0,22.0,16.0,21.0,ACFDFDEDFDBAFDCDCDFFFFFACHCHGEDFCFEHADACEHEDEBAFAGGHGEDADFDHDHDHGADAGCCCFHBDBGBDEGEBHGFGHAHFBFBFEAABABACDDAHHGFGBGEGHFEABHBFEHHHGDFDCACABABGECHAH,False +43,17.0,19.0,23.0,19.0,19.0,21.0,20.0,22.0,GDGFGEDDDDDDFDFDFEHBHDGAECBHDEGHGEEDEBEDECGGAADAFAFADECFCDGDGFBHGCBHBACAGACFCGGGBGCHFHEHECECAHFHFGCGHBFCGCBCFEHEGEHBBAAABDHFBCCCCFFFHFCABFBHBHBEDAFEHBHACABECHCH,False +44,2.0,1.0,3.0,4.0,5.0,3.0,6.0,5.0,CHCHFGBGEHFDAGADEDEGGFGEDEHCH,True +45,17.0,20.0,26.0,20.0,18.0,24.0,15.0,12.0,BDEFBBBHHECFCFCBBFEDDADADGECEHEFCGCAFDCGCFFEDDGGHHHHHAFAFEFAFDFDFDEDFAACFCFCDCBBBCGCGDGDFCGCGBDCACBHDHEECBBEBECFCHGBGEGABCDCEFHFGACDFAFAECEBEBDACABAGFBA,False +46,5.0,7.0,11.0,5.0,5.0,3.0,8.0,10.0,CBDHFHCDCEGEHCHCHCHEGCGCGBBBBADAHGDGBACGEAHBHFGFCECAHD,False +47,5.0,4.0,4.0,5.0,0.0,1.0,5.0,3.0,ACABGBHBHBGDCACHCDAGFGAGDDD,True +48,21.0,22.0,13.0,24.0,16.0,18.0,24.0,19.0,DBDGAGBGFHFCABGFECEGBGHHEACDFDGCGBEBGDAFAHADADAHHBHBHAGABADEBFDGDBDGDGCFAFAFDDDDECGFEFEAHAHEHEHCBCDADGBFBFAEBCAHFHEDEGBBFDEHEBDHFGCGHGHGBGCDABCBDGHGBGDCEAFAF,False +49,5.0,12.0,11.0,8.0,8.0,7.0,11.0,9.0,FCFDGDHBEBECFBBHFCFCGDBCCCGCECECBDBGBEHDDBCAGAEHEDFDHGEGAHBHGAGAGFHBHBG,False +50,2.0,7.0,7.0,4.0,6.0,13.0,10.0,11.0,BBFEFEFHAHFDFGHEBABDFHBHEFGFGHEHGGGFDFEHCBGBFDFHFHCCGCGHGCCC,True +51,5.0,7.0,11.0,12.0,13.0,9.0,8.0,13.0,EFFBFDAAECCCHDHBHFEDBHBHDHDGGGGECDGHCFEFEDEDCDCDEDCCHFEFEGCGBHEHBHAHAGDFCEAEHB,False +52,15.0,6.0,11.0,6.0,11.0,16.0,3.0,8.0,BAEGCCEAHBFCCHFABEHEFDCHEBECACECEAFGFEFEFBFBFAFADADACACDFGFAFAFEFDAAHFDCAHHH,True +53,20.0,14.0,19.0,11.0,13.0,12.0,10.0,17.0,CHCECEHEGAHBFGHCHABCBCDCECEDAHACGCADDBBGFGFGFHAAACACFBEGGAGAEHCAAAFDFDCHBDBHGDFDHCBEFEBCBABHHHHDHCHDFEFABEBECAAAEACF,False +54,18.0,14.0,15.0,22.0,24.0,20.0,25.0,23.0,EGGCGCGDEDEBCBFDDDBFHDDGFBFEEEGDBDBEHFDFEACACADABEFDCECGGHBDCDBAGHGFBFECHCFEDEHEHAHEEAGCEEEEFGFHFAAGEEHHHHAHAHDEFGDGDBCGAGHFHFHAHAHDHDBFBFCEGGGGGGGHAADAGCDFFAHCB,False +55,3.0,4.0,2.0,5.0,2.0,5.0,3.0,1.0,EHAABABGBFDFGFGEDDFDCBCDF,True +56,9.0,9.0,8.0,11.0,11.0,13.0,8.0,11.0,ECFFFBCDEDAFEBEAFGFHFHFDEHEBEHEGBFEFHBABCCAGAGBGBDFHAHGHFCFDHDABADEDEDAHGGCDCHCD,False +57,10.0,13.0,10.0,15.0,7.0,9.0,16.0,11.0,HHCFEGEGEDFGABEHEADCHGHBDFDGDGHGCGBBDDCDCDBDBHCDEBAHACCFDGDFAFAFDDAGAGHGCGBGBHACBGBGAHEBFBF,False +58,15.0,15.0,14.0,21.0,27.0,24.0,20.0,28.0,FAFEFAADAGFBFACBCBHHCGFGFAFHCEGEGHHBDBFHFHBEGDGDAEEHEGCGDGHCDGDEHFHGCEEEGEGEDBDEEEEHHHHCHDAGFEBHFHAHFHFDDDCACHFBDDHDGDFDAGGEAEFBHEEEEBEHEFFCFCFDBHAFADCGCGFHDHEBABHB,False +59,11.0,16.0,18.0,17.0,22.0,31.0,15.0,17.0,FCECFCFCFBHCHBGBFHGEDADADEFEFHFDFDADEEADHGAEAECGDGCCFHFGFHFHFHFBFBFCEEEBEFFDEGGBHBEBHFCDDDDGHAFBFBFCACHCAFGCGHHEDCBFEFABCDCEGGGDAEBBBEDEFFFFECGHEHF,False +60,11.0,9.0,7.0,2.0,10.0,10.0,11.0,9.0,HGHCDCHCACBCEGEGEGEBBHCFGABEBFAEHHFBFAAGHGHFHABABCGEGFDEAAABFEFEFGFGA,False +61,23.0,23.0,21.0,24.0,24.0,17.0,27.0,24.0,EDGGCBCFCGCGCFCGCDCBAACHFHFHECACAGAHFHDBDEHAGADHGEGEBCAEAGDHAADDDDCEAEADBGFDBBBBDHDGDBBGCAAEHEGDGBGBFHCGCDBBBEFHFDAGHCDCHFHFGEHEGEGHGBEFACADAFCBGBGBFHDEDEDFBFEGHGHAHAEEEEGEDHAHACEFBHB,False +62,21.0,13.0,9.0,12.0,17.0,15.0,25.0,10.0,HFGFGBGEDEHGHAHFHGAAAFGHBFACGDBEBGAAFEGEFEFBGAHDEDECBCBFBEGAGAFCCBBDBAGABAGGGGGECDADAGAEFEDGACADDCDHDEAFHFHFGGGFGCABAEEEGE,False +63,6.0,6.0,3.0,12.0,7.0,8.0,6.0,13.0,FHEBEBHGHDAGHDCDEDEAFCFCHEEBAAFDDDFDHDAGBGFDHGHAHDHEHFHFHBDBG,False +64,6.0,15.0,15.0,8.0,14.0,13.0,8.0,8.0,CCEDEDBHHGDCBEFEFCCGCEAGFGEGECAHAHGBCFHACEBEBEGEFFFFBDBFBHBDDEDCBCBHBFGFHEAEBCBCFCBCAFD,False +65,6.0,4.0,3.0,4.0,6.0,8.0,5.0,5.0,CGCFEFAFAEEDEHCHBBDAAFAGHEHEBFDHDBAGFGFGF,False +66,17.0,8.0,15.0,6.0,16.0,16.0,11.0,12.0,AFGFGFGHGFECECECHAECCCFAHAFAEHGGCEBAFAEAEFGGHCBFAAEHFHFGBHEHGAFBFHCECEADFDBDBCACACAEAEBEDDACBDFHFHEGC,False +67,24.0,12.0,23.0,14.0,18.0,18.0,15.0,12.0,CCCFCFBHAEEDFDBAADAEAEABDBDGEHEGCCCACECHGEGEDECACFCFCHBFBAGAFFGHADBEBAAAAFAEECEDHDHECGGBHHCHDBGBABAGEFFGFAFADACADAGADCHFECGFGFHFCDCEGFCC,False +68,31.0,17.0,27.0,38.0,29.0,28.0,14.0,16.0,ACACBCFDGBHBDEGEAHDDEFEFEFEFDDHECEBDFDAEAEFECECGCHAHAHCBCDAHBDDDDEDEBEHGDDAFEFCFDDBCGAGACCECAADADABAFEDACGCAFAHDFDBDGCECBGBFFCHCGAEDFFFHADFDADGFAFADEDHABAGAGEHEFBFECEDEDCGEADADFDHBHDFDCBCFCDAFAECFCEHB,False +69,5.0,4.0,3.0,4.0,2.0,3.0,6.0,4.0,DAHAGAHAHAHFGCGEBDFDEDGGCFBBGBC,False +70,5.0,7.0,9.0,5.0,2.0,11.0,6.0,10.0,HAHDHDHBGBFCACDCHFBBHBHGDEACACEGFCDHBGFGFGFCCHBFFHFCFAF,True +71,11.0,10.0,6.0,19.0,14.0,23.0,11.0,9.0,FHFEADABECHFFDFDFHFEDECEFEFEFAFHDADAEADDCAGFGBBHGDGABDDFFFFDDDADEEGFGDABCDGGBHDHFGAGBHBHBEBEGFFFFFCCEDE,False +72,25.0,17.0,20.0,19.0,16.0,13.0,17.0,22.0,GDCDHGBEAEGDGEBDBDHDCDCBHDEAEHDCEFAAABCDCDABAGADADCFAFCGCACAFFBAHGCGCGEGEACHHECACECEHEGGFBDHFHAHAHGGDGFCECHFHFHCHFABABFDGABDEDABABHEACAFDHHGHAHBBBBEH,False +73,15.0,19.0,20.0,23.0,23.0,21.0,22.0,23.0,GFGFECGCEEGHFCBCFDDDHHGBGHGHDCDCFHAHCCCFHAADEBEHEDEDADCDCABEGEFDFHCHGGAHAHFCFCEADFFECGBDBDBDCCACADHGCGEGHFHGHGBFADEBEBEDGDBBACEEEHGBDBFFFFDGEGDGDGFBEHHHHAAEAEFBBBBEFH,False +74,3.0,11.0,6.0,11.0,10.0,12.0,5.0,7.0,ECHFHDHEFFHHDCFGEGFDBEBEFFFDBCBFEDCDCFEBBFADDBDBGBGBGBAHAHFDEDECE,True +75,21.0,13.0,22.0,19.0,30.0,19.0,18.0,19.0,HAHEEEFEDHDFDBHBGCCEEFEGGHGHCCCCCHGECEAHDBDBEFGHCACGBEFEHAFDFACAFEEEHABAGAFDGDADADAGBCBAEADAEFHCDCFGEHFHDEDCDFEFCCCEAEAEGGABFGEDBDBHBCCECEHEAEFGHGHDDAEAEHCFGFGFB,False +76,14.0,30.0,18.0,20.0,25.0,19.0,27.0,30.0,FCFBAEDEGEHEBGHGFEFCGDBDGGCGCGBEBHBHEAAAEECBCBCFHFCFDGAEHHFGGGGGHCHEHBABGBGHHDFAEBDBDBDBCCHAGGEGDGCCBCHFGFGHGHBHEFGHBFBCBHEHBBABCBHBCGEHEADDDBHFHAADEDBFHFEEGEDHDHDEDBDFEFEHCHAEGDHBFBA,False +77,25.0,17.0,30.0,29.0,22.0,22.0,23.0,24.0,CCHEAEHBBCBDADBDBDHGFEECBDFGFEAHDCGCDHHEHEHCGCFHGDGAGAGACACDDDFDFDGECCHDHCCEFAFEBAFGGHDCCGEDBDBDBCHCACDBAHCGCGAHAHAFFFHADCDCFCFHHCDCAEAGAGAGABFHGEGBGDFHEBEFCFAGBEEAABAGDGDFDFEABHCDEDEHEHEFCFCD,False +78,9.0,16.0,9.0,5.0,4.0,15.0,4.0,5.0,BCEADCBBBBABABCCEHFBDHFAAGAGHCFCBCBFDFAGAGBFBDBABFFFFFCEHEBDHFFFBFC,True +79,19.0,17.0,10.0,29.0,13.0,8.0,14.0,14.0,DEDEAEAEDDDDDDDHDGEBEFADAGBFFHDGFBBBBGBABFCHGDFDEACBBBAHADAHCGCAHDHEHABAGCGCGEDAGBDAACAHDBCBGBGBEDDDDDADGDFDHHFDAHAEEEHCDCHG,False +80,9.0,11.0,7.0,9.0,14.0,3.0,11.0,16.0,HEHEACBHBHAGEBEAEBHBHBDEDCFABCGAEABHEHDADABABGGGDGHECEHHDGDHHCHCDGFFHCBEDEGEGHGE,False +81,4.0,9.0,4.0,9.0,3.0,6.0,6.0,5.0,BGBACACHDGDFDFBFEAHFBDDEDEGHGHBBBFBADHDGCGDBFC,False +82,11.0,21.0,22.0,24.0,26.0,28.0,21.0,21.0,EDGDCDCFGEDEFFFFGEEEDEDEDADACHCEBAFAFCHEDBFEDHDCCAHGFDFDGAGEFECEDBHCECDGGGGGBGFGBHCGDGFFDCAGDBCEHEGBBBBHFHADFHCHCHCACHCBBEFAGBGBEBFFFHFBCEDFFEFHDHFHFCCECBHBDBDEDEHBHEHFBFEGAG,False +83,2.0,4.0,1.0,3.0,2.0,4.0,2.0,1.0,CBFHFBBDGDFDFEGEABA,True +84,18.0,13.0,21.0,13.0,16.0,19.0,15.0,8.0,CBCEEADAFGDCFHFHDHFACACEDGACFGGGCBABDCCCCCCBABABABDBDFACGCGCFCAGEFEFBDBCFEFEAGFDBEFEHEHBAEADAFAFGEGECAHFEDGDHHCAEDEFCFGGGBF,False +85,14.0,12.0,10.0,10.0,16.0,19.0,9.0,12.0,FGBGHDEEEGBFAEAEDHGHGFEDEFEGEDEFEFCBAHCHCFBFDGECFFFGAECBBBDGFAFACACBEDABEBFHFHFHAHAHFEDCDCFCAAHBHADAFB,False +86,14.0,13.0,10.0,16.0,18.0,7.0,14.0,15.0,GGGGHADGCGCEEEDEDBAAGBCDAEABAGAFFFDBEFEAHAHBDBDBDBGHAACDHHGHGHDHEFBCDCHCHDEEBEBDADABEFECCGHGHFHDGEEEADBEEHC,False +87,9.0,13.0,17.0,12.0,12.0,23.0,13.0,12.0,EHCHBDDCECFCFCFABABGBFDFDCDHBGDHDGBGCGCGCFCDHEHEFCHGEAFBFBFDFHCEBAFEDEDFFGHCFGBGFGCDCEBGFHFAFBEEEBGFFCFAACAHAHF,False +88,6.0,3.0,0.0,1.0,3.0,3.0,5.0,4.0,GBGAGBHAGAGFEBEFEHHAHAFAD,True +89,11.0,11.0,12.0,15.0,16.0,12.0,7.0,10.0,BHBHDDADCGCAEHHDCEAFAFBFCDEDECBGFCECHAHGCAEDDBDEAFAFHFDCHEBEGEGADBDBHEHDFGFGFDECECECAAEBEBDBFF,False +90,18.0,21.0,18.0,8.0,15.0,18.0,18.0,10.0,BCBDGCBCHGHAAFAFEFAFDFHGGGCCECEHBHFCADAFAFEGBAAAGAFBEBEBEGCBHBFADAECDGHGBGECCBCBABHFFDCEFEHGBGBGBEFGABCBFBDBEEAHACGCGEGFCFCFDA,False +91,21.0,22.0,23.0,29.0,25.0,21.0,20.0,16.0,EDECECBBDBGGGDHDFCFDFAFGBACHDHDADFDHBEAACACACEDECEDGDGEGEGEDEAFCFEGGBEBGFGEDECGFAFAFGHEDFHFCFBFBDEDFDGBHEADHDCCFBABABACGEHAHFHCEGEGHBHDACADFCCHBHDCDCFBHAGDBABEBFBGCDBEBCDDADAEEC,False +92,22.0,26.0,23.0,24.0,20.0,30.0,22.0,18.0,ADAFEGHDHFFFFDFECADDDFHBHDCBFAHCHCACHEGFBFBCDHEFEGABAFAEBGBFFFBFCFGBHBEBAACAHAEDEDEGCDCDCDCGHACFCFHFHGCFCEHEHCGCDCEFGDGBGBGEGBABGBGCCABBBDBAFGDABFBFEFEDADBFEFDBHGHDFEFECBAGGCGADDDGBHAEA,False +93,2.0,2.0,1.0,3.0,0.0,2.0,1.0,2.0,DBDCDGFFAHAHB,True +94,18.0,8.0,12.0,13.0,10.0,9.0,12.0,11.0,HHFAEHCHCHCDDAFACACACGGFEFGCHDEEGCGCGFDDADGDFDEBHCDABGBABDGAGEEBAFABGBDAHAFAFADADEHHCHCBGEAEA,False +95,4.0,5.0,6.0,3.0,5.0,4.0,4.0,3.0,AHBFEADADAGFHFGGCBCBCBCFCEHEBDCEEG,False +96,6.0,10.0,15.0,4.0,14.0,9.0,14.0,11.0,ECECEGHGHEHGDACGHHHFGFGCCCGFEEHEAAACCHCFCFEGEDHFHFDFGEABBBBEBHGCGBEBGCACBEBEGCCDBFG,False +97,3.0,4.0,3.0,4.0,3.0,2.0,2.0,6.0,BGHFHDHDCDBDECAHAHAEGBFBHCE,False +98,14.0,9.0,9.0,12.0,16.0,15.0,11.0,5.0,BGGACFEGEGEAFGFGFGFAADADACBCFDADGEBHBFDFGBBDCGAFAEEFECHCDCBFEAEAEADADCEBDDHDBGEFCHEHEFEAEFF,False +99,24.0,22.0,16.0,19.0,18.0,22.0,22.0,17.0,BABDFDEDEDEHAACABAEAFFGBHFGAHDBCAGADEDCHBBGEGAGAGAGAGFGABEDEDEFCBABDBECECEAGFGEGBGACBFEHEHAHAFBFBCHEFGDADAEEBCBHHHFHFBAGGGFFFFGHDCCHAHBCBCHFGDBCCAFBDGGFDHDFDFDC,False +100,10.0,7.0,6.0,7.0,6.0,11.0,8.0,15.0,GGHGHGFEFDCHAHFHEHEBACCBCHFHFBCBEBFFEFHAHGHDAGADAEGBGHHBAAADCFHFDADFDH,False +101,21.0,23.0,9.0,23.0,25.0,21.0,22.0,21.0,EEEEEACAHEHDDADHFBFBAHGHGBGDGFECGBBBBFBFEFHFGFGFAEHDHAHAHBHGHFBBHGGGGGEHDDDDHEAFBHHDEFEHEDDGBCDCHBGDDFFCAHADEDEGEGEAABBEBDFGEBABCDFEACFDADAGAGEGBAFABHBDGDCEEEAFAFBFC,False +102,1.0,8.0,5.0,3.0,5.0,5.0,6.0,8.0,HCGCHDEBGFEFECBBBFBFGHGHGDGBAHCFCHHHEDEBB,False +103,29.0,22.0,27.0,17.0,23.0,16.0,31.0,26.0,GGHCFGEBEDGCCDEBFFFEFHGCDCBCBCECFCHCHCHGHCEGAGCECABHEEEBEBEGAGBBBABABFBHBHDHGGDADCCFAFEDECEABGBFAFHDAGHGHADEFGBDCHHDEDCHGABABFGDEAAAEBGAAEGGGGFGHAHDBDCCHGHBDGEGHGEAEACCHCACAHGHGHAHDCACAFAGAFA,False +104,7.0,6.0,18.0,7.0,11.0,12.0,24.0,18.0,GDGEHCGGGEFECEBECGCGHGCFHFHFHCDFDFGACHHHGBGHACDCGAGADBCAHECACGHGHBBCFGHEDEFEHGHBHGGCGCGCHCEGGDGEAFFHFCF,True +105,16.0,23.0,21.0,18.0,22.0,17.0,10.0,18.0,ACEGEHEHAFACDCDCHFBFBGBHDFFFCAGHBBBHBHFABABABAHEGCAEEEFGBGBADGEBCDEHEBCFCHBHEFEBDDDDDDDGFEDEFEHAHBCACACBDBDHDCBCEDEHEGCCFEEEDHHAABCFCHAECBCBFFCFG,False +106,9.0,10.0,12.0,6.0,8.0,7.0,13.0,7.0,FABABHCEGEGBGBGCCCHCAAABGEGDGFGFAFCBCGCEHDCCAGHDHCAEHFBFAGBGBGHFDCDBEEDE,False +107,17.0,15.0,17.0,17.0,16.0,26.0,15.0,17.0,EFBHGEAFDGCGFGFGDEEAEGBDEFBGGFAHHCAFAFHBHBDGDGEGEGDFFFDFHHHAHBCDADBCBFGFCBCBGBFEHADAHCECFCECHBFFFFCDEDEDCDEFEFCHHHCACAEBCGAAAAHADAFHFBDBCFDF,False +108,20.0,24.0,27.0,23.0,19.0,28.0,19.0,18.0,AFAEGFGFGAHFCFEHEGDBBBEBEBEBCDDDHDFGFDCDCECFAFAHAGBBBEBFDEBCBAHGFGAGABDBEAGFCCCBEBHCDBDFDFBBHCHGGCDCDFHEHECGCFFFADAHHHDCDAEEBFGAEHCDDGACACACFCBEFFHAGCCCCEFEFCABDBFFFGHCHDHDFDGBGA,False +109,9.0,16.0,17.0,17.0,16.0,16.0,12.0,24.0,EGDDDAHBEAEABDCEBFFHFHFHCDGHAHCCFDFDFDFBBEBFBFEHGHGDCFCGHGHGCBCEDHBCDHFHFBFGDGACCCGAEBHBABCHHEHBDDEHEDEDEGEAHDHCECFCFCBHAHEGBHH,False +110,5.0,7.0,7.0,3.0,11.0,14.0,10.0,14.0,AHEHDHGFEFGCHFGFBBCAEFEFEFECEHFHBHAHFCBGFABHBEDEGCGFDFACGCGBFEFGHHHHEHG,True +111,20.0,16.0,22.0,22.0,11.0,17.0,13.0,10.0,ACAFFCDCDCACBFAFGDAACDCDEDEFFCBHDGDCDGDEABFEAADDCAHHDHEGACEFBCBCACACABBHDHDHEHCAAFAFCDDEDFDFBFCFBFDEDFFGGAGCCBEBCBHBAGGGGGEGACBHBDB,False +112,26.0,22.0,28.0,29.0,20.0,26.0,21.0,19.0,GCDCBAEHEHGGFABGFFFFBDBDBHCHCHAAADGFCBCDCFFFDCHCECEDEAFBFEFEGGCDCDAEAECFCEEACCBABGFDABADAFHBHFEFEAHAEADFCFHHBHAHAGGDHCCCDHBCADABHBDCGHGAGAGDDDFCAGBCBDBCFCFEHEDEBGGFGFDBCGAGDCDEDGDBDBEFEHAFADD,False +113,4.0,0.0,3.0,3.0,1.0,0.0,3.0,3.0,HAHADDGDHAGAECCCG,True +114,15.0,25.0,14.0,19.0,17.0,16.0,17.0,18.0,GDGCHHEBEBHBEFAFEFBFHFBGHEFEFEBAAAGFGDDFDFDFDBDBDBABABDHCBGDHCEBBGBCBEBAGHCHBEBGHEHEHEACACACACBBGGFGHCHDGBCDGEFDFDBEHECDGBCEHAHDHACFGADFDBAGD,False +115,4.0,7.0,3.0,5.0,3.0,0.0,6.0,6.0,HGHBHBDBABACEGDGEAHBHADGEGCHCBDGDB,True +116,18.0,19.0,11.0,27.0,26.0,22.0,18.0,28.0,FDFEHEBGBGBCFDFDFBEGFABHCHEEFAFAFAFBDHEHEABBDCHCDDGEHEADAFAFBHHCHBFBEDHGHGBFDFGECHHABDEGECEDADEHEDCAHAGEBABCDCDAHEDEDEDFFFFFBFHGAFEGEGDHDHGHGHGEDHDGEGDAHABBHHDHBCDADHEGE,False +117,9.0,10.0,11.0,5.0,12.0,11.0,5.0,12.0,HFBFCFBAAEABGHCHAFABBBBCCCHCECECHCGEHEHEHFHAHCEDDFDCEEBFFFFGEBEAFAHDGBGDEHA,False +118,1.0,8.0,6.0,3.0,6.0,11.0,9.0,8.0,BEBFGFGFBFBGBCDFEHBHAGEFHGDEFBFHHCGCDBGFGFGHCHFHCECE,True +119,16.0,21.0,23.0,14.0,8.0,20.0,24.0,21.0,EEGFBBADAFCBHFACCCFCFEFDGAFHFDABHBCGHHHBHGHCHEGCAABBGDHBHBGFGCGCGCGHFEFCFGABAGGCGAGACFCBCBHBFCFADHDHGHGFDEBEGCGCDBHBEAACHDDFDCDCFBFBGGGGCBHDHDHFABA,False +120,23.0,16.0,16.0,25.0,12.0,20.0,24.0,21.0,DFHFBBDGFFEDCHEEGGGEEADAGAGDBDAABFDFCGDGAABABABABACAGGHDHFACECBDDFDHGHGHBCBCAGFGBGCFFFDFDCGHGDEEHBCDCBHBCFGFDFDHAGCHHHHHGAFADDHEHEAGAGAGHCBAEAEDCDADCFGFDHDHF,False +121,19.0,17.0,15.0,20.0,28.0,24.0,23.0,17.0,DCDFFGAAFFFBGAGDGCACHEHDADADFEHEGGFFEFAABBHGGGFHEHACACBEEEHBAGAGFDFEBEGEBECECDCHBHGDGBEFEAEAEAECCGCEHBHCFFGBDBDCDAEEEAEFFFBHAHGEDEBGFGFGHGBGBDFDCDHEHDDDEBAFDFEGCFH,False +122,24.0,21.0,31.0,19.0,20.0,33.0,21.0,17.0,CBDGEGCBFGFHFHFEFBDAECCCBCBGHDCCCAFADHDHDEDACBDBGAHABFDGEGCHEECECDAFBGBGBFFFFHEAECHFHFHGEEBCFCFDGEGFFFFGCDCGBGBGFFBFBFAAAAAFGBAFABECAGEGBGFHFCADDCECHFAFADAHFHEDEHCFBACAEAEFDCCCCCBCHDADCG,False +123,23.0,22.0,33.0,26.0,18.0,14.0,26.0,19.0,DGDGCACABHFCADADGHGEEHGACAHAGACEDEDEDGDFCHDECFCBCGHGECHCHBEEDEDEDEDCBGBGBABCBCBHAGDGECAGDCCCFCDCFHFDABECGBGFHBBFBEBEBACEDBHHCCGCDAGGGFCCCGDDFCBCBGBGHGHGCBADHFFAHDGAAAAABAFDHDHCFCEAD,False +124,14.0,14.0,13.0,14.0,9.0,17.0,19.0,18.0,DCBFBFAFAHBHGFBABECACGGBGCGCFAFHHDGDGEBDADFFHHHHDAABHFFEGAGFDBGHGAGBGHFHFGCHCDGEGEFCGDGDCDCDCECBFAFCFHAHEBEGHBEBHHADAD,False +125,22.0,17.0,18.0,14.0,19.0,23.0,19.0,20.0,AFFEGCACEHAHBHFHECADBDEDHDHDACHCBCBHFDDAGHGHCECEAEAHBHGGCEAFAFBDGFFFFBAGAFAFHHCGDFFAEBBABADADBCGHHHGACACFCFDFBCGHGEGEGBGBCBEEAFHEBBGGECEFECEHGGEAFDFDFAF,False +126,2.0,2.0,5.0,1.0,2.0,0.0,0.0,0.0,CBABCCCECEAD,True +127,9.0,13.0,13.0,20.0,8.0,15.0,15.0,18.0,GGEFDFEHDHDHBAGABBBFFHFCFHGHGHGHGDADHDEDFCEDAGAGCBDFDHDHCBCDFDBHFHGHFBCGDDDDDABGHDHCHAAECFBDBEBCBCEGECCFFHCGAGF,False +128,26.0,16.0,20.0,13.0,15.0,14.0,8.0,14.0,AFAFGCBFDCCGCBCACACAFACECBAFAFDBBABABHECBGAHADEDCBADABABAHEHCHCHGECDHDHBHBAEDEAEAHBGFAHBBCACACAFEDCAHHEADGEGECEFFFCGHDFDEAEFFD,False +129,3.0,2.0,3.0,1.0,2.0,1.0,0.0,1.0,AHABFBEAECCDC,True +130,3.0,10.0,5.0,11.0,10.0,4.0,3.0,9.0,DBGBHBAEDEBCCEBAAFHHDHDCBEDHBHBHBDECECEDDDFDGDFBEGEHEHF,True +131,18.0,19.0,23.0,22.0,20.0,20.0,15.0,23.0,FGBCAABCBCDCDCBBAAADCEGHAFDFEBHBHAHGDAEAEAHGECHCDDFDBEBHHHDBCFCABFHHHABFHHEGEHBAFAFCDCHGEGEFBFEFEDEHCHCHDHDGFAFEBEBGBGFCDCAEDEGFFFHFBEAGACFDDDDHDCCCCDCDGEGBGCEH,False +132,27.0,13.0,16.0,13.0,20.0,12.0,27.0,15.0,HAACDHGHEBFFCDAGADAEABAGHFHDHCCAEHFHBGBECGGGGAGABACDEDCACACFGFGFHBBEBHGGGDABGGGEDECEAEAEAFCEGBBBAGAEAEABHEAEGGGCEHFHDGAGEDEDFDHDEAAGAHAFFGCCCCG,False +133,5.0,7.0,9.0,1.0,6.0,7.0,8.0,7.0,BGCFEBHHHHACABFBFHFCFGGGCCECGCGCHAEBBHFGCGDAEAEBEF,False +134,14.0,15.0,11.0,16.0,21.0,17.0,16.0,20.0,HBHDHFHDDEFEGEFEBGDFDFBBHBAGEGCFHBHDADHHFAFAHECEFADECEDDDBDBDACBEAFHFHGEGCGDECECBAGACHBHGHFHFHGEGFFHEHCHCEGEGEAEGDGEABDBABFFGECABA,False +135,8.0,3.0,1.0,2.0,4.0,6.0,9.0,3.0,GFGEGHGFEFGCGDBAHAFDEAEGBGBAAAFAGAHF,True +136,14.0,29.0,20.0,23.0,25.0,22.0,18.0,18.0,DGDCEBGFHDBFBECHFEFBDEDCACGCGHEFEFEFAFGGGDCFGFHFHAHADEBBCBCEEEFEBABCBEBACACBHHCFCEAEAGBGDCDBDEDGBACECBHEHBDGDFDGCGAFEFDBHBEBEAHGFCFBFBHEDFDGDBBBBACDBDHGBEAEGFCHBHEHDHDFD,False +137,3.0,5.0,1.0,6.0,8.0,6.0,3.0,5.0,FDFDBBBEDEHEHEFEACFFGDHDFGBHAEAEBEGDH,True +138,17.0,19.0,28.0,23.0,19.0,29.0,14.0,27.0,EEHFCDHDHBAADFECECFFFCDGBAHAHFHBCDDFDGDADBCAAHABAEGFHFHDHDEGCGHGHCFDFEFGBHAHBCBABEEECDCDEHFHFBABHCCCACHEACHDGDFHFHBHFGDGDGDFBCDCGABFFDFECHCFFFHFCDGEFCACHCHCHEGACFCFBFEEECEBBBBD,False +139,18.0,10.0,15.0,7.0,19.0,9.0,15.0,15.0,BCDGAGEBBAAFCBEFDFHCAAHABFEADAHGCCCACEDEDEDEDEHCBCFEHCHEACACHGGGGBGEGFGFEHECGFEAHGHEHEHEHACAFBGGABABHGHEAEAC,False +140,12.0,11.0,10.0,15.0,15.0,9.0,10.0,21.0,GGDEDEDHDABGBDCAFADADEEFHFEEBBAHECFCAHGHGHEBBCBABAFHHHHAFADHECEGGBGECECHBHECFCDDDEEHHHHHDHDHDHFACGDABFG,False +141,6.0,7.0,16.0,10.0,19.0,4.0,7.0,3.0,GAGEECEDBGBGFCFCHCFBDBDECEAEDBDCHBEEFAHAEAEGCBCEADDDDEGCCEEEECCCECDCGCEE,True +142,17.0,14.0,17.0,18.0,21.0,18.0,15.0,9.0,BADAGADHDGDGFHFAFDFGEEDDDADCCCGGECCCGEHAHAHEEEEAECFCDHDFABABFBGBCACEFFDADAEEHBHFDFCBEBGHGCFCDAGFDBEFFGFGEGCBAEDEBCBAACDCBEBEFEFEG,False +143,1.0,3.0,4.0,4.0,2.0,3.0,3.0,3.0,DHDCCGCGAGHBBFEFCFDHDEB,False +144,3.0,1.0,7.0,1.0,1.0,3.0,7.0,2.0,CDCFHGGFBCCCCGAGAGAEHFGCG,True +145,3.0,5.0,7.0,4.0,3.0,11.0,6.0,3.0,DHGEGBGBGCCFDFAFHCBEBEBDFCFCFGFCCAHFFFDGAF,True +146,4.0,13.0,6.0,8.0,6.0,15.0,9.0,3.0,FABGBGFGFDBBBCGEEEEBFGCBFBDBCFDFGFGFAFECCDDADAFBDGHGBFBFHFEFHCBD,True +147,16.0,16.0,22.0,23.0,21.0,20.0,35.0,29.0,FBFEECGAGFGFGHDHDFAGEGEHFHFHFEGHGCEEAHDGDEHEGEFHFCFHGHBECDBDBHHGGGGGGCBHAHACAHAGEBDCEAGGHGHGEGEBDAHHHCHADGCFBFHGBGCHDFDFDGHCBCHHAGBEBDACHCFFGGGDADEEAGCEDEDCCCGDFDBDGFBFBGBDEACACDCDCH,False +148,16.0,20.0,20.0,23.0,21.0,16.0,31.0,18.0,EBEHGGGHCACFDDDDDAFCHEGCACFCFDFAGADEGGGAGEECEGEGEGAFFDCBHBHDHEGCDCGBGBGCCCCCBDGEBCGFHCHGHAHBBCEGEGEBFBGAHABDBDAGAGFGBEEEFEDGDAFCHBABGBADADEGFFDHDCFGGDHBFBDEDEDGHHHBH,False +149,3.0,7.0,4.0,6.0,10.0,7.0,3.0,5.0,EBEHEBEDCFCBBADCHFHFGBGBDEEEECHBDADADEFFFGFHE,False +150,6.0,2.0,7.0,6.0,2.0,3.0,8.0,0.0,DDDCGCADFDFGGGACACAGBECGGDGABACFCE,True +151,5.0,2.0,2.0,0.0,5.0,4.0,2.0,3.0,GAGAFBFEFECEFHABAEHEACH,True +152,14.0,12.0,9.0,7.0,12.0,11.0,10.0,17.0,FDHDFEHDHCFCBCDGHGCFFFBFHACCHBGAGAHEHEBEAADAHBGBFBFBABABAHAHEEAFHEHBHEHABGGECDCECEAGDHAHEFGG,False +153,19.0,24.0,27.0,19.0,23.0,23.0,26.0,24.0,CDCGGGFAAGACHFHDHDHBBCCHCGFAHABGBEDHBGBGBABADECFFFFAGGCHDDGDGCGHGHGDCFHDHAFEFEFEHDCCGGBGEGAAFCEEDFDFGBEAFHFCGEBCBHBFBDCDGBCBEHADABCHCHEHEHBHDGFGAGEGBBEBHDEEHAHAEAECCFFFCCCECECEFBFBDECBA,False +154,13.0,10.0,11.0,9.0,11.0,8.0,12.0,4.0,GEAEAFAGADADAEFCGCGCGCAFBFBEECEGADADACBGBCHHBFEECACBEHEFBFBDADEDBCGGGBDFHCAGGD,False +155,23.0,15.0,20.0,21.0,22.0,13.0,16.0,23.0,FEBEBEBFDHDHCCDDBCBEGFDFGBHCHFDAEBCBFHAHGHDADCBGDHDHDFCAHHHDBCEHDFDAAECDCDCBCAFEEEEEAEAGACHCEGEAEGGGGAEABAFAFHHGEAAACHFHAHFGEAEDEDEDADHDBCGAGACBCHHBGGCHC,False +156,1.0,2.0,8.0,2.0,1.0,1.0,0.0,3.0,CCCCCHCHBACDCBHEDF,True +157,11.0,6.0,5.0,14.0,10.0,10.0,2.0,6.0,EFAHAHFBFGGABADFCBEDEDADAHAFAHBFEDEDCDEDEDEDFFCBEDFDFBACDDAEHCHA,True +158,15.0,22.0,16.0,16.0,9.0,21.0,17.0,9.0,CFCFCAEBDGDHBBFBHCAAGFFFAGGGGFGHCHDBDBECECECFHBBCBAFHFDFBCACHCAAAEFDBDBCFGAADADAGGBBBGCGBGCFBEEGHGFGFDFDFABABDFHFDBDCEFEBGDDB,False +159,3.0,6.0,10.0,6.0,2.0,3.0,4.0,5.0,GGGFDFDBCBHBHBCCHCBCEHHFCACDCBEDDDACGCA,True +160,7.0,12.0,7.0,6.0,6.0,8.0,8.0,5.0,AEFEFEBCBADCEFHHCHGBBECAABFBFBDBGBHECGDADADGBGAHFFCFCGDGBGB,False +161,25.0,18.0,13.0,27.0,15.0,21.0,17.0,28.0,HFHGDDBDFDGHGADHGFBHGCFDAECCHHEFEFEDDBEBAHAHFHFBFHAHDFDFAEDFBBCEHADGFGAHDGDGDGDFCBCEAEBCBHDHDHAHAEADHHFHFHEGBHEDABABACDCAEFDDGFGAGABAHDHDGDGDBHBFAABAGAECECHCACBFAFH,False +162,18.0,23.0,16.0,12.0,17.0,23.0,24.0,31.0,AEABABCBCHCHCFFFBHHEGBABDDDDDHHFHEECFCFCBEDDBHBHBCGHDFAFHCHFGCHHHHHHHCFGFGEHDBAAEGGHEBBHGDAHFHBHBECGFAFBGCAHEHGBBFBDCHHGEAEHGFFFADGEGBGBGCGFFCHGEGEGAGAFABABAEAEGFGF,False +163,24.0,23.0,17.0,16.0,25.0,31.0,34.0,30.0,FHFHFEFGFBAEHHHDHDHFGGDGDGFGDHACAFGDGDECECHCGAHAHBBBBBFFFCGBGEFFHFEAECGGBBAGABABAFHFHECGDECFCHDBACDEHBFBHBFEFDDGCHBHGHGHBEAGFGCEHFBAHACEHEACFCFEAEGEGAGACFEAEBGGFDBDBGEGECEAHHHAGBGHAFDFAFDFGBGHGFGAGHEE,False +164,16.0,17.0,19.0,27.0,19.0,29.0,35.0,19.0,GDGBCCGCAFBFGFDHGHBFAFGFGDDECECDGDCDFHFGFCFHFEABACFHFBFHEEECEDFDEDGGGDGCCBBDBFBABFBGDEDEGBHBDDDGGGGCFHFGFGFHFEABBDCDCHCGGGDGFGEDADHDECEAGAFAHEHADAFFGGGCABEGHCAEFGFGAGDDHDHBCEHGAEHFH,False +165,10.0,7.0,7.0,12.0,6.0,6.0,5.0,8.0,DGFFDCDCDAEGDBDCEBGACECHCECDBABDEAHDHGAAHHHFHFBFBGBHDADADAFAE,False +166,17.0,18.0,17.0,16.0,20.0,19.0,17.0,15.0,CACAHAFBDAAADADHBGFAFDGDGDGHHFHFGFGFHHCAAEBFBFCFAHEBABEEGEGEGEBAHGDCDGEBCHEGDGCFCEEFECBCFHBHBHBADDFBFBGDCBCFFEGCAEGEFBACDCECECFDDADEEEGHBHB,False +167,15.0,4.0,11.0,15.0,21.0,12.0,17.0,17.0,HHAHDEDGHFHEHCHGFGFCECEGEACFGDGDCDCHADCEHEGGAEEBEBFHHHCHCHCFDAHAGDGFGDDHEEGCAEDEABAEGEGHGDDFAAEFGAGAEAFAFDFEEBED,False +168,8.0,4.0,9.0,2.0,9.0,7.0,3.0,7.0,ECECBCHFHCGFGFEEEHEHECAAHAFFBAEAFHBGAEAHDBDACCCFC,True +169,16.0,14.0,9.0,11.0,11.0,11.0,12.0,11.0,DFDFDGAGAGAGFGHHACBHBHGFFDFGBCEAHBDAEADACCECAAEABBHEAEAEDEDCABABCBGGGGFFACHHBDBFFDFEEGBCDHEHBHB,False +170,4.0,2.0,1.0,1.0,6.0,4.0,5.0,2.0,GGDBEEEEBEAGFFCFGFHAHAEAG,True +171,28.0,14.0,20.0,10.0,8.0,25.0,20.0,36.0,HCHCDCGCDAGAGHGBABAFAFCFAFDFGFGEGHFEFHBHGFGCHEHABFGFHHHCFDACHEFBHHHCHAHGBAADCHBHBFAAAHHHFEGCGDAHAGFBFAADAEACFFGAEAGABFCHCBFDEAGAHBHBAAHHHFHFHCCACGHGHDHDHCHCFCBGF,True +172,3.0,11.0,4.0,4.0,5.0,7.0,5.0,5.0,BBBEBHHCCFEFGFGHGBBBGBDFAFACEHFGFHDBDBABCDEE,False +173,8.0,13.0,6.0,15.0,4.0,10.0,15.0,7.0,ACDCGBGFFFGEGBGFHBHDADHDFGBGBGHCDAGGGCHDHGADDDDDDEBBHBFBFGFAEADGCCBDBDGAAEFBFB,True +174,10.0,11.0,8.0,10.0,13.0,7.0,14.0,11.0,GCGCGCGFGEBCAAEEHEAEHDHDGAADADADFBEDECHCGGGHGEEHBHAHABFBEBHFADGDHEECHBBFBGEGBGDCFBFD,False +175,23.0,12.0,12.0,24.0,26.0,34.0,26.0,24.0,CDBFHAHBGAAFEGHAFGCAFGFGBGBEBEAFGDGDFDADCFGEGBFCHABFCGADHFFEFHFEFEFEDHFGCGEGEAABEGAGHGEAFAFAFCFAEDEDEDHDHDHFFFGFHACEFHHHDHDAGFDFGEGBGDHDBABAFEEEHEBGFGEEAEAHHFDDDGHGHDFCFCACHDDEDEFHC,False +176,18.0,8.0,20.0,16.0,15.0,17.0,11.0,11.0,FCFBECGAFAFABAEEEEDCDAECEDGAAADFHBDBECEHEABABCDCHBGEHAHAGAECHHHADCCCCFCDCDAGCFFEEAFAFGDDFHFHFHDBGGDGDADFGCECFCGCDCFF,False +177,13.0,12.0,13.0,12.0,6.0,11.0,5.0,9.0,DABFHGHCBDBDCFFGABAFEBACAHECGDFFHFHFDFEFCHCBCBAECGCGCHEAEADDDBDADAHHBACABACDCDBFB,False +178,7.0,14.0,10.0,12.0,19.0,22.0,10.0,9.0,FDECFBFDFDFHFGCEDEDEFHGBACCEGGAEBEGABFDFDFCHGHFFEDBFBFBFEGEHADAEFEFEFEABCFHDHDAECFCGBFBGBFBEECECDBEBHGH,False +179,2.0,2.0,2.0,1.0,5.0,4.0,1.0,6.0,HGFEHEHEFEDAFHFEABBCHCH,True +180,2.0,5.0,1.0,3.0,3.0,4.0,0.0,0.0,FAADBBBBEBEFEFDDCF,True +181,6.0,7.0,5.0,2.0,1.0,4.0,3.0,6.0,BHBDBAAGAHCHFHACAHEHBBBFCFCACGGDBF,True +182,2.0,3.0,10.0,6.0,8.0,6.0,4.0,4.0,BCBCECEAEDEDHCCCCHEHEGDGCFFFAHGBFFFECDDECGD,True +183,27.0,20.0,35.0,20.0,19.0,18.0,17.0,19.0,CHCHCFCBDEHBHEHCCCCBDBAADFFECCGCAEAFAHCFGDGAGACABFEAHCBDBDBDACGDEDEDEHEBGDGDCAGABEBEAECEGAGFGCABFGFCEAEAGACFCDCFFGFEHBDBDECACAFHBHCHBHBFAHDBCADHEHACAGDDDGCEBFBFCCCCGAHCFCACAHH,False +184,21.0,29.0,29.0,14.0,13.0,23.0,22.0,20.0,HBBEFAHAHDHCHCGCBCAFABDDHDFAAADBDBEBCBCBEACGCGFFBFAFHGHFCFEHCHDADFCFCEDBGBCCFCFGFHCHCACBEAFBECFCDAGGCGFGHGFGEGACCDCBHBACGFGFHFBFGEGBCHCBCDEBBCHGGBGBDDFAAAEBEBABHBABHGEGBHA,False +185,16.0,21.0,7.0,5.0,16.0,12.0,3.0,15.0,BBBHGHBACDBEAAAFDHEHAGAGAEEEHHCAEAFBBABFBCECAFAFBFHFEDABBBFBEBEBEBACHFHFHDHBFEAEBHAFCHEDECEHBHB,True +186,26.0,34.0,20.0,22.0,24.0,21.0,26.0,17.0,HFACACHCBBBBHBGBEHFHFEAHAEAEFDBHECAHAHDDBGEDCBEGGFGECAAADBEBGCGCFCFCFBFBFBAGCBBABEHGCGCGFGBBCHCEDAHBCEAEHDBAHGGDDDDHEADDDDDFFGBGAGBGBEBABDBDGDGBFBDBDBDHEFEFCFEAAFGEBCGEGBFFGCGAABAGCHEEEAFAEA,False +187,3.0,5.0,0.0,1.0,1.0,2.0,2.0,4.0,DEBGHGAFBFHHBHBABA,True +188,8.0,11.0,10.0,11.0,8.0,19.0,14.0,12.0,HGFBFHFBFGGAHDDEBAHFHFHFCEGFGFGFGBGEGBCEEAFDBBBHFHDBDBGACHCHFGCGFGCGFBCDCDFFAEAHAEFDFDHAECDCD,False +189,24.0,32.0,23.0,32.0,21.0,21.0,20.0,22.0,BBBABAEECDDDEDEHEBECEDEDHHHFHFDFHCDAHAHDBGBGEGFGFGFGFBAGCGDFBFHDHBBCHGHGFAEBEDCAAGFDDADADBDCFGHBABDHECBDBAAHADAGCDCBABABGBHDCGCBCGFEBDCHAHCCCFCFEBABHDDBGBHHCCCGBABDBCEEGHAFEFEDDBAFFFDFDCEAEAEGDBD,False +190,13.0,10.0,11.0,9.0,7.0,16.0,9.0,11.0,AGCHAGCBAHCBGBEBEACADADHDBFBDDAGEFCFCBHDEFEFHFHGHDFGFACAEFHAEAGGBGFCFCFHFDFCFCBBFDAHAH,False +191,14.0,3.0,6.0,9.0,14.0,7.0,4.0,6.0,EAEFDGEEFCCCFCFEAAAEADCDAEAEGGAFHHHHEAAADADEFEBDBAEGECEADFDHDHB,True +192,6.0,4.0,7.0,3.0,3.0,3.0,1.0,4.0,CFGEHCCFCBCEAEHCHDADADABBBACAFH,True +193,29.0,36.0,21.0,12.0,18.0,14.0,23.0,24.0,BBHFFFCEHEGEHDHBGBHBHDEBHBHBEAEBDBFHFHEHABADACGGGADBBHHFBBBAAAAABECDCACHCAGACFCFAEAFAFAGGDAEBDBHBEBGACBHFAFGFGBBCAGGBGHDCBBDGEHEGEACACACEBEBCACAEGDGHCBDGHGHBBABCCHCHCHGBAEAGBFBG,False +194,6.0,3.0,5.0,1.0,2.0,4.0,8.0,5.0,HBHGGFCFCACAEABGEACDCHBGGHGAGAFHFG,True +195,3.0,6.0,4.0,7.0,9.0,15.0,5.0,10.0,HAHEHFGFHHGHGFFCFCEDEFEDBGBDEDACBDFHEBFHFHFEFDFCFDFABEBGHFE,True +196,2.0,2.0,8.0,2.0,3.0,5.0,4.0,4.0,CCECHCDCDCEBHCGEHBHGAAFFFFGFGC,True +197,0.0,3.0,4.0,2.0,1.0,2.0,3.0,2.0,DBHBDFCCCGCGBGEFH,True +198,9.0,8.0,9.0,4.0,11.0,7.0,12.0,11.0,AAAFADHGGGFGCBCBCHEGEFEHDCABDHGEGEGDACBFHFBEBGBECEHAHAHGBECFCGEGAHEHCHF,False +199,9.0,8.0,10.0,11.0,7.0,10.0,5.0,6.0,ACADDFDHDABGCDEBEHAFFBECECDBBABAFAFAEAFHDDDHCCDCGCGHGDGHFCBCBFFEFE,False +200,15.0,9.0,5.0,13.0,12.0,23.0,15.0,22.0,CHGFEHBDGDHEHAHDFDFAEBDAHEFEFEGGGGAAAGEDAHGHGHECEGFGFGAGBFEFAFBFBGBDFAFHDHBHFHFHGDEDHFFCFEDBDHFFFAAHBHAHFCFDHHCHAA,False +201,8.0,4.0,6.0,6.0,2.0,3.0,2.0,2.0,AGCFBBCBCDAHABACEHDADADCDADAEFGFC,True +202,15.0,30.0,30.0,30.0,15.0,29.0,25.0,23.0,DFBBDGHBCEDBFBHBHBCBHEGGGEBEBHHEHCFFHFGBHEGBDFDFGBGDFDFHCEFHCGCFDHDFDEHADADEBCFEFDFEFECDAAHFGDDDCACACACACDBABGGEDAABBBGCACABFBGDCDAGGGGDCDFFFGFCBBBDBDHECGHGDGCGCHCHFBFHHHDHCEBFDFDFCFCGCBCBCFCDABHCG,False +203,14.0,19.0,19.0,3.0,12.0,14.0,16.0,22.0,CHAEADAHBHBHBHBGGDBHFHEAAABCBGEFCCHFEBHCHABABFHCCCHBHAGAFCFBFAAAHCFCGEGEHEHEHFHBHEGFGHBEGGGCCFGFGCDAECGCBBGBFBCHCHCGBFE,False +204,9.0,15.0,19.0,11.0,9.0,19.0,20.0,15.0,FAAACCHEGCGDGBHDCCCEBAHDGDFDBDBHCFGFCFCBCBFGFGHGBFBHHHFHEGBGBCAEBCCCFCFCHGAEFEAGCDHGHGFGFGCGBGBGFDACEBFDFDEHEDGHABFHF,False +205,20.0,16.0,16.0,34.0,30.0,20.0,29.0,29.0,CDCFGDGDEFHGHEHEGGBGBGBHBGEFECDCEBGDAHGCBDDGDHDHEBEDDDDHAFAFDEGCHEGFHFADBEEGAGDGDHFHBDEAEAHAHDDDECGBADEHEFEFDACAGEGFGBDEDECHHHEAEFFBADDDDAEAHHDHDCCFCAAAHCFCFEGHHHHGBGBDCHCHDFDGGEGBFBGHFAFEGEGEAE,False +206,20.0,18.0,16.0,14.0,21.0,4.0,6.0,11.0,ABABAFADEDBAECHGDDAAHEBBDBACECGAAAACHEFEBCDHGBCECECEBEFEAECBCEHEDGAHACADAHACECGDDEEECEHHHFECBCBEBHBDBDBDBAGDBA,True +207,1.0,3.0,2.0,6.0,1.0,4.0,1.0,1.0,FCADBDBGBFEFDFHCDDD,True +208,5.0,3.0,5.0,6.0,4.0,0.0,1.0,2.0,DCCBCDCDCAAAAHDHBGAEEDBDEE,True +209,9.0,6.0,7.0,6.0,5.0,8.0,3.0,2.0,FCFEAEGDADABCBCFGAGCFAFABABCBDHCFDFEFEACBDHEAD,False +210,21.0,21.0,15.0,16.0,11.0,15.0,20.0,12.0,CACFFACCCEHFDBGBGBFHFAGDGDADACGGDGBAACABBECECEGEDHDHCABDFDFDAGHGHGBGBFBGEGBFDFAGAEHFDAHEGABABFGAGEBCCGCHBDEDGBCACFBFAFHDBEBHBABADAH,False +211,10.0,24.0,13.0,13.0,14.0,11.0,16.0,23.0,EDEABACHGHAEGGBBBBECECEBBBAHGHGHCBCECDCBFBHBHFHFHFBBDAGFEBHAHDHGCFAGABCDDBEBEDHGHBCCACFDDBAHHHGBGBGEGEGHGFEFHHHDDBBCDEFGFHDH,False +212,19.0,7.0,17.0,13.0,17.0,11.0,21.0,24.0,FGCAHAHFGEHAAAAAHGDGHGFEEGDHHAEAEDCDFGBGDHDGFECECGGEEHGHGHCFBBHBFEEHGHGHDHFHDHDAAAHDECAAACBCECACAHFDFCCCCCCGGGGGEEEDHBHEFCGDHAHAB,False +213,10.0,20.0,7.0,7.0,13.0,11.0,10.0,5.0,HACBEBEBAGEEHEDAFABBFEEEBGBGBGBAAEBBDDFDFDFHCHDDAFECHBBAFAGGGFAFCGBEBEBEGGBFFCBCBCB,False +214,6.0,9.0,11.0,6.0,13.0,4.0,11.0,19.0,ECECBCFDGEGBHEDDHGEBHHGCGCBHHHHHEHEGACABADHFFGCGBGHDDCEEEEBEFHAECBCHGHGHBHAHAHC,True +215,3.0,0.0,0.0,3.0,3.0,2.0,6.0,5.0,HDFDHEHGGGGHAHAEGEAFDG,True +216,1.0,8.0,11.0,12.0,14.0,8.0,9.0,12.0,GEBDBDCCADDBGFGFEEGEGCDCEFEGEBEDCCFBHCEDDGEHEHDDFCHHHBHBHBCDFDEGEGCHCHEHFHF,False +217,10.0,10.0,22.0,13.0,14.0,8.0,15.0,10.0,DCHGECECEAGHEFGACFBGBECGCAEBEHHAGEGFDFDFHEDDCDBFBABACDDHDBDGCCCGHGACFCFDGCGCBCBGAGACECACBCECGDHEHEHECD,False +218,7.0,10.0,14.0,5.0,9.0,7.0,7.0,16.0,CFCECECDHHHHHHHHBBBHEFCCEBDBABAGDFDHCHGACCHCHEFEGHGDACFBGBCEEEFGHGFCBCHAAAB,False +219,15.0,20.0,16.0,12.0,13.0,12.0,14.0,14.0,AGAEAEAHGHFBFEHBHFGGEEHCFCDADACBDBFBCBFGFBBBCCAEGDGFAACAHBCBCDAFHFHECAFFEGEBCBGGCDCDCDEBBDBDBHHHHHDGAGDCHCAGEGABBEBE,False +220,0.0,1.0,1.0,0.0,3.0,3.0,1.0,3.0,HEHEHFFFGCBE,True +221,4.0,7.0,18.0,11.0,9.0,20.0,14.0,16.0,GGGBFCCCFBFDGCFCFDFHFHCDCDHHHGHFDCAGHCBAEEFEFEFHAEFCHCGEFCCCHCHEHCDCDAGBGBGCDDFDFGFHEHDHFGEGFHFGFBB,True +222,19.0,32.0,14.0,24.0,24.0,23.0,30.0,29.0,EAEAGFDFDCBHFAFADGBHBDAGCDEABDFGEEFFFEEAECHDHBHDGAHHGBGBGBGHCDFDBDBDEDADHFFAFEFGBHBGDCHEDABGBEBCDCHCBFAFBGBAHFHFGEDFHHHBBBBDBDBDBGEGBHEACCHEGEGEDEHECGHGFBHGHCBGAGHGHGEGEGEHAHAHFCCEFHFAGBGBGDADFBB,False +223,6.0,4.0,7.0,6.0,14.0,14.0,8.0,15.0,CEEFAGEBDFAHHDHFAFAHBFFHFCFEHHHHFDEGEGEDEDGAGHDFGBGBEFGFHHCHCHEHECFCACEEFE,True +224,11.0,10.0,13.0,13.0,21.0,14.0,25.0,19.0,CGBAEGEGEHHCGGHGCCBCAEBEGHCHDFDFDFEGBDFDFEFAGDGAGEGCGBHEEGCGBEEGEADACECABEDCDFFFDCAGAGHFHAHGEGEGEGBGBGHHHHHHDABCEDHHFFDHEHEGFF,False +225,6.0,19.0,5.0,11.0,12.0,6.0,9.0,5.0,GBHBDBABHBCBDEDBGBGBEBEBCCFDHDFEBBDDEAEAEAECFGFGEGABCFGBBDHDEFBGBGEEABHDD,True +226,11.0,18.0,23.0,14.0,12.0,26.0,20.0,26.0,EFEFEFGDCDFBHBHADECHHEHEFGFGHCBGACBGACFDFGFCFGFCCCHHHBHFHFHDADFFEBGFFFFFDBCCFCFHFCDGEHDFDBDCAGGHHHHHHBACGCGAGBGHAAAFFCHGBGCADGBBBCGDHEBEBEBEBHCHDHCCCG,False +227,23.0,20.0,28.0,18.0,25.0,23.0,23.0,21.0,FCCBCEFEDAGGBEHCHCHAFCCADFFHFEFAHCHDGCCHAEDEDFDGAGAGAGEFEBEBHHEFEFHFCGDFBGBDHAHBGAHFFFBFCDDADCDEEAGABHBHGHCHCABADABCHCHCDFGHGHBAFFEGECBGADCECGCGCBFEFDFCGCGDEECAGAEAGAGBBBBBCEEAEDECE,False +228,5.0,3.0,9.0,5.0,8.0,2.0,3.0,5.0,DDDACEHGFBCEAECCCCCFCEHEHEHEBCDAEBDHAGAG,True +229,15.0,19.0,18.0,23.0,23.0,15.0,10.0,23.0,HHFHGHEBFHHBCBDEEHCBGBAHAEDEDCGCGEBBDDDDEDBDHDFDEDACCEEDFCEEECBCBCBCDAFEHCFAHBEDACAGHHHHHHHAHGFACACAFBEBEFFFFFDEBEAEGCBEEDADACBHGCGBGDHDHDFDHDEABF,False +230,15.0,10.0,14.0,14.0,7.0,9.0,3.0,6.0,EDADBFADCDCDEBFBFAFEFEDCBADFBFBAHACCBCGEHEHBCCAGDCFFBAAABAGACHCHDDCCCEDHDADADA,True +231,21.0,19.0,19.0,16.0,21.0,13.0,13.0,23.0,EHBFBHBCDAEACABABEHCAAAAAEBDHDCECACAHGFCFBFBDCCBDBDECHCGCAAHHDDCDCDEEHHHADAFBFGFGDGFGHGAGEEFEHBBDBGHAHGHEBCCACACGEDEAABDBCEDEFEHBHEEEHGHFHEHFFGHB,False +232,10.0,11.0,13.0,7.0,8.0,12.0,12.0,9.0,EFGGGHCHBAEHFDFEADAHBBFBCGFGBCBCBCFHFAFAGCGCEBEDCCCHCHDGGGCGCADFEBEBDAFAFAHEFGBHDA,False +233,16.0,18.0,26.0,21.0,12.0,11.0,22.0,9.0,GBGCHBGDHEHDGAFCFCGCBBDDDHHGCEDEDCDBGBEBCCCCDBGBCACBGGEHEDGGAGACFCFCHCGGDGABDCCCGDBDEDEBBCHCDCDBDAGECECAFEFBFEAGAFAGBGAGDDDACAFAFAFCHBA,False +234,8.0,5.0,2.0,10.0,3.0,5.0,9.0,5.0,GAGBBEDFDFDBDGDAEADHGAGHBDGDFDFCGAGACABAGHHHFED,True +235,28.0,16.0,21.0,19.0,24.0,21.0,12.0,20.0,EDHFBEAFADABHFHFCFHFACCBBBHAHDHBADGDBCBDFEFDHHADACBHBEAEDDDGAGACAEHECFCECHHHEABFCFEEHGAFFFADADCDGEEEGEBECEBBCACAHAHADADFFAFAFHGDEEFEBCGCGCGCDCAHBGEEFGADECECAFAHA,False +236,13.0,6.0,14.0,8.0,9.0,13.0,7.0,14.0,FCFAFAFAHAHCDCDGFFEFECEDBCECDCFHEEFAFACHCHCEBGDHEHFHAHBHDHFCGGAGDHHACCBHDCGFGBAAEABA,False +237,4.0,7.0,4.0,12.0,6.0,4.0,7.0,10.0,DGGHBHDDDGDGCGCGADBHEDEDAGFCFEBDHDEBAHAFEHEHCHDBDBHFHB,False +238,25.0,27.0,17.0,20.0,11.0,20.0,27.0,24.0,BGGGHACECEFEAEDBDBHCGDGDHDHBHBHAHAHFBFGCGCAHFHABABEFFDDAAFHFHDAGADFDGBACCCHGHDAACHCHGBEBCCCBDAFAEGHAHGHGEDBDBCBHBGFEAGAGBGBABDHDGAGADFBFGFGCAEBGFFEHBBGDGBBBFFHFBFCDAGCGHDA,False +239,27.0,19.0,14.0,12.0,26.0,20.0,17.0,18.0,CACHFHBABHBABAHEGBDDEBFAFAEACABAFAHAHGHDFEGEFEBEBEAFCDCHABAGEGEDFBGBACAFDCDCAEHEHFHFEEEFABABCGEEEGHDHAHBHDFGEGBAAAFDHECEAGCGEBEDCDHFAFAGAGBGFFCGCEHGFEBEF,False +240,13.0,5.0,13.0,8.0,10.0,9.0,13.0,11.0,HCHAGAEFGBGAGFGCDCAGAECGCGEFEDHGFADADACHDFDGBCBCFEDEFEFBAHHHHHHAAFGCECACBCGEHEADCG,False +241,15.0,13.0,22.0,21.0,14.0,24.0,13.0,15.0,CECEBACABEFHFGBEFDCDBABGDAEADCDHGFGFDDDFDFDFGFEFGCGEAHGHGHCFCDABFEHHABCECBCHFHCACFBFBHBADFEFEFDFDHDHCHCDEDAGGECHAFDHCABFCFDFDGBGCFCACDCEA,False +242,10.0,3.0,9.0,4.0,10.0,22.0,6.0,6.0,CBAAFFFFGBDAFFFFFFFDGAGEHFGECEFEFHCHCEEEDCFAFAHAFBDEHGHCFEFCFCFEAAFAGC,True +243,16.0,18.0,13.0,25.0,8.0,14.0,16.0,17.0,CFHGHAFGFCFEDAGEBBFDGBGHDHAHBGBGBDCHHEBDBDBDCDHDHFAGGHGHABADDCDFBHAGDDDBCACECAGEGDDHDFDFHFHCGCGCDBAFAFDBDEFEACADADADBCFAHBHGEBB,False +244,14.0,10.0,26.0,18.0,17.0,28.0,19.0,21.0,HEHEHDFDFEGEGFGDCBBDAFHFHFDCEGBBDHFAGBHFHCECHCGAFCCDDADGHGCGAGBDCDHDHDACFCFGACEHEGDGFCFCFCAEFHHHFBFDFDCBCFEFCDGAGDEEFEFHFHFEECCCAAABECFHACECFAFGFCBCGHGHG,False +245,30.0,27.0,23.0,25.0,28.0,19.0,14.0,26.0,AAACACBCAEDEBEFCCHCAEGEDEFGAGCEAEADFEBBBEFAGBBBFDAEAEHHHHCFCHCHADFDEBHFACBFBGBFBCHHAHAEEGHHEAEGHGHGHGCAHADADAEAEAGDGBECHDDDDEFFDCDCACAFBFHCHEHEADFBFBGBDBCGABHBHDACCECDDBDBDFDBEEEEHCBAFHHDBBADF,False +246,9.0,17.0,16.0,9.0,17.0,6.0,11.0,16.0,HGEGACAHDHDCDEGFHBHDHECEDEDFDEEHCFCFHBEGGFABEHHHHGAABCCDBEBECHCHFBAHGCGABCBEBECCCCCEGEBBBBDBABEBHGEGA,False +247,10.0,6.0,15.0,20.0,23.0,16.0,16.0,6.0,AFDGEGEFEDCDFHEGEGFGBCACECEAEHEDDHEGEDEFGDDDCCCCGAGEDBABEFEFDGDHDGDCBHBGFFCFCEEEEFCHEFGDGFCDADCFCAEGFGBEFDADADAE,True +248,1.0,1.0,5.0,2.0,5.0,7.0,7.0,2.0,EFCFDAGFCFGFCHEHECEGGCGDGFGFBE,True +249,20.0,25.0,23.0,25.0,18.0,22.0,28.0,20.0,DGDBDAABACHGHEBDCCABFBAHGGBGEAAGDDFGFAHADADEDFHFHGGGFGFDHDEDBACDGDGBFACABBGBGEGEGECFFFEABDEDHFAFGBCBCACHHFHFBFBFHCHCHCECDGDCEHEGCGBBFBGEFEFHCGCBHGDGFHFEABCCEBDBHGDGDGBHCEDADCDCBAEAC,False +250,27.0,24.0,20.0,16.0,26.0,17.0,25.0,11.0,CHCBCACHBABAGHFEEBEGECEBEBEACDGDHHGAAFGEGABEGAGEGADADABAECFGBGAGAEBEADFGFECACGGFGEGDGFBFGCGBFBFEAEBEFAFAFEDEAAAAGBBBCDCDGECCCBCFADABHDEDEGEAHHBDEDFDFGCCCDBBHAHGBCBEHF,False +251,23.0,19.0,20.0,25.0,22.0,22.0,28.0,26.0,ACACGEBFHHCAGAGHGHGCGCGBEHFHFCAGFGCGHEHAHADDDDAEEEECCFBGHAHAHGBDECFADGCECEGEGDGAADBEAEFHFDGDGAEAFDECBGECCHDEEBGBABEHHAFFFFEFDADHBHBDDGGCGCBAGAHABDBDEFEBCBDHGHGFDFDFDFHBAFCBDBDFFGGCHHHDH,False +252,22.0,23.0,23.0,11.0,21.0,24.0,27.0,23.0,CGGAGEGECECECDBFFFHAHGEGCGAGACEDBBBFGFGHGHFCBGHFHBHGEAHAHABDHABABDBECHAHFCFEFAAGGGBGFCDCBEADADHFHDHCEABCGGGFGAHEEAECCCCGBBEHEHBHBHDCDFFAFBFCEBAGAGCCBCAGFDHHEHFFFCFEFBBEBFGEGA,False +253,21.0,15.0,11.0,10.0,10.0,18.0,15.0,19.0,CFCEEFHBGDEEFEFDAGAHAHGHFHFHGHAHAHGFFFGBDBGAAAABABGBFBFBEACGCEDHFACCFFFGECBAECDGGAFAHDHDHBCCGHAHAFAEDHDHGBBABDFCAGABHBH,False +254,16.0,7.0,14.0,11.0,13.0,17.0,11.0,13.0,CDFHFHECACEDEAECCHFHFHGHGCAHAGAGDEDFDCHCFDADFEGAAEAFFDEDCCEDBFCGCGEBEBHGAGFBABAGFHDHAHAEFFFFFBEBCGHACA,False +255,14.0,24.0,17.0,17.0,23.0,22.0,12.0,11.0,EDGFFFGBBBCACDDDBDCFCFCEEAFGFGFGFDBBBFBDCFEFADAHEDBDFHAAGHCHFGACABEDEDEAECEFEFDAABHHAHCECBFBCBFFDBDGHGHFBCDCECEDEAAGEGFBEBCBEEGEBEBEBHCEFBBH,False +256,15.0,18.0,13.0,27.0,17.0,28.0,20.0,24.0,FBDBCHCGDEDCGAGAGDDFBBBFFFFEDACGCHAGGGEGEBABFHFEDHFHFCBDGHGBGDHBCBGAEHFAFHHHDBDCHBFGFGFHFHEGEBDFFFHAHGHCHAHDHEBEFEDGDGAFABDBEHACFCFCEDADEFBDDEAEADFDFHFHFDGHEDDDDC,False +257,6.0,7.0,12.0,13.0,9.0,11.0,8.0,10.0,DDACHGHGHDHEFCCEGEGACCDCDCDADHBFEFEDEGCFBFDFBFEHCHDAGEDECBCBHFGFDFHAHCGABDBF,False +258,17.0,20.0,27.0,16.0,18.0,18.0,19.0,20.0,AGEHCDAGCGFGDCDCHCACDFEAGFGAAAADADCCHGHGHCCEEEGCADACAHECEGDGFBFBFCHCHCBBDBDBDEFCGCBBBEHFHACAGBCHFFBCBCGGGGHDBECEHEHGHBCAGEDEBFCEEBEBDFCFAFHBADDHFHFHFHECFBB,False +259,1.0,5.0,4.0,1.0,1.0,0.0,6.0,2.0,GGGGBGAHBHCGDBECCBCB,True +260,2.0,3.0,4.0,1.0,3.0,5.0,1.0,3.0,BFBCBFHEEGEHCACACHFFDF,True +261,2.0,4.0,3.0,2.0,3.0,2.0,6.0,2.0,CDCABEHHGFGFGEBABCBGDGEG,False +262,17.0,17.0,32.0,25.0,20.0,22.0,15.0,15.0,DHDCDCDGEHCBGBEBACGDFDCBCFCBCEAEAFCDEBAAEADHCEAEHECDDDBDCDBBFFEFGFBCBHAHFCCECGHDHFHAHACDEHECFCDEAAHABBCHGEGDGFHDDCDGDCCCGCACACFCFDADFGFBFBFEGEGEHDACGDFCFCFGBEBEFCF,False +263,7.0,4.0,7.0,4.0,5.0,5.0,7.0,12.0,GCACAHGHECGCHFGFEDHDHDHGHBAEAHBHFHGCCBCHEGEBHAFADAF,False +264,6.0,6.0,13.0,6.0,11.0,2.0,9.0,8.0,DCFBDBEEEEEEADAHGHGCGDHCHGEACBCGCAHEHGGAFAGCCCCCBEBHDCBCEGEHD,True +265,20.0,25.0,22.0,32.0,26.0,23.0,23.0,27.0,DCHBHBCEHHGHDCGCAHHGHDEEHEHBBECDCGBBACACADDDDDFCGEABGBABEBEBEACFHFBEGHFBABCGHGEGDDDEGAHAEFBFDGDHBFGFCDCDCDFGFHEBEHEHBDEAEACBDADHFBDDDDAFEFBGGGGHGHCHEHFCFGFGADDDDBDADHFEBEBECEADACBCFAFHFDFGFAEGHHCCFE,False +266,7.0,6.0,7.0,3.0,4.0,2.0,13.0,8.0,BGHCABHHCHGGBDBABAFCGEGDGAHCEEGEGBGCAHAHACGCGHGFGD,True +267,8.0,8.0,22.0,12.0,15.0,14.0,10.0,10.0,DCBAAGBEBEHECCCCFEDDDFGHGDEDCBCGEGEGEBFFAEHECFCHCHFHDCDCBHGGCCBCFCHHFAFGHGDFCEADCDCDCEBFAFACECAFEFE,False +268,20.0,11.0,17.0,15.0,11.0,11.0,19.0,11.0,FACAFGDHCEFHAECBCBEBEAEGBGBGFHCCBCAHDCFCDGDAEEEFBACADABACECHGGDBDGGGFHEHADAFGFGFGHGHGCFCDCDEGAAAABDDDGHBACACDGDHAGA,False +269,6.0,1.0,7.0,4.0,8.0,4.0,3.0,3.0,DBGECEAEAEAEAGDGFCHCECFAAHHFEFCCDEDC,True +270,18.0,16.0,20.0,26.0,19.0,21.0,22.0,23.0,BFBCDDGAGACDBDGDGDADHCAEACGCGDEBGDFDCDBDGHEHCFFFFFHFBFAFHDDGBHHHHFEFABGGDGDEFCDGHCHEFCFHBADHHCFCBGBFEEEEEFEDEDAFGHGDGCACDEAEACDEDHBHGHBHBHCDGAEACCEHGHAHACAGACBEBGFDF,False +271,0.0,3.0,1.0,4.0,2.0,4.0,2.0,3.0,HFHFEFDBEBHFDDBDGCG,True +272,16.0,16.0,17.0,14.0,11.0,14.0,8.0,16.0,FCHEHAFAFBFBDHGAFABBCDCDHBHEFABCHCHDAGABEBAHDHDFCEBGDFECECECEHECACDBDBDCGAGAGACAGBFBGDDACCDDBHEHBACFBFHHHFHFCFAE,False +273,13.0,11.0,14.0,14.0,11.0,17.0,18.0,16.0,CDFDGBHBFGFGFGEDABABCHHDDEDCHCGAGFBFDADHDCDCECAGEFEBEAFAEHEHGGEFBHCHFHFAFDFACGGFGHHDHGHAHCFAFGEBCBGBGCACDCDEHGFBAG,False +274,30.0,26.0,12.0,16.0,14.0,36.0,17.0,16.0,GGHCBABACFGFHFBBHAEAEACADADABABFFDABBFFEFBAGFHFBFCFBAHHHHGGDGFGBHBFEECEFDCHCHBHGEAHADDGAFAFDDBDGFGBEFFFFFGFACABGFFFAABAFACAGAGHDABABGDACFEAEADBBFBEDEAFFBFBFCFCDBHEHEDF,False +275,6.0,13.0,13.0,9.0,7.0,9.0,12.0,6.0,CEFBGCCCCHDBDBCAFDFDFGFHHCCGCGBGDGDBCBCBHFGAAEGBGBFBGBGECHCDAEGEFADAHEDEBBF,False +276,7.0,5.0,3.0,5.0,6.0,7.0,3.0,5.0,BCCDFEFEFEBADABCFDDHDHAAEAGFGFHFBAEAGHBHE,False +277,6.0,5.0,1.0,2.0,3.0,3.0,6.0,7.0,HBBFBFDHCGEGAHAHGHGFEBHBGGAEAHADA,True +278,4.0,8.0,15.0,16.0,12.0,11.0,10.0,10.0,DHCHAEEEHEHEFEHGFBHEDEGEGFCDCFCGCDCBFFFCEGDBHFDDADGGCGDEDEDGACDCFCFBGBHBDBCFCHCDDDHCAB,False +279,15.0,15.0,14.0,9.0,20.0,30.0,10.0,19.0,EAFFEFEFHBHBHBHCHCFAAACFCAHGBGBFEEBECEGEFDCEFEGCBFHFBEAFDBBGDDCGFDCBBHBHFEFEHCHFBFDGCHFHFHFGFGAAAAEECEFDBEFECEHDFCFHDHFFEAAAAAFGFHFH,False +280,20.0,27.0,17.0,23.0,26.0,20.0,26.0,25.0,AEDGCEBACABABGBGFDCEBHBCBCGHBAEACBHHHCDDEGFHAAFABCEHDBDBDFFGFCBGGGFGEEFEDEAEDEDHHHFHEEEGEGCBCBHBEBGBGECEAEHGHABBBFHEAFGBGDGFFEFDGDGDGHGDAFAGDHDECEHHHAHDDGHGCGEBEFABCBDBFCFCFHBADADFDAHH,False +281,10.0,6.0,6.0,8.0,8.0,11.0,10.0,7.0,GBFFDHAEAECDDBEGDGAEECGGGDHDAFADAEAHBHDEFFFFBCBCECAFABAHGFGFGFGHCH,False +282,21.0,33.0,19.0,20.0,21.0,12.0,19.0,26.0,CAADABABCEABHBABDCHEAEGHBBCCCCCHCBGGGGHHDHGHGDGDGDBDAAGCBHDFEEEEEEBEBAHHGHEHCCGHFBFBFBFGHBDBHAFAGACCHAHFBCCFDEDEHCHABDBEGADBBCBHEHEDDDDBDEDBBHAHBEEEDBBBBHGGGCEFBFAFBGAHAFA,False +283,12.0,9.0,6.0,10.0,12.0,16.0,15.0,10.0,CFCEDFGCGFHFBGCGFGABEGAGAGAGAFADBHGHDEFHHDGCADEGBBCHDAAAGEBEBABFDFEFEFHFHFHFHGBFEGEDDDEFEA,False +284,0.0,7.0,2.0,2.0,5.0,4.0,3.0,5.0,FBBHBHECBFDFGEHCHEHEBEBDGFGB,True +285,18.0,10.0,10.0,8.0,8.0,13.0,19.0,13.0,HHHFGFAHCCBCHCBFAGCGBABDBDGAFDCDAEAEHDADBHBAGFGFGHEFFGHGHBHAFFBFCFCAAABEEEAGGGAGCGFGAGADAGEHAHCDGEG,False +286,17.0,19.0,13.0,13.0,17.0,16.0,12.0,9.0,DBDADABCGDAFEFEFEDABCBEBGDGFEBEBEBEADBDGHCADABFDADADABGFGFCBCDCFBGGEEFCFAFEFBAGGEFHCGAFAHBHBFFEBACECACBCHAHEHEHCGBEH,False +287,11.0,13.0,8.0,14.0,5.0,10.0,1.0,11.0,ADDCHBHFDEACFDBDBABCBCDDDBAAADHFBFBABEHEHBHBCCHFDABAHCDDDCDAFHFEFEFHFHGAB,True +288,21.0,32.0,21.0,22.0,23.0,17.0,23.0,21.0,CFCBBDADEDEDBDHDADCCCEHEHBFBHADADBGBGDCBBHFAEBDHDFDFBEBHDEDBCECEGABCFGFHDHGHEHAAGHGEDEAEABGFCCBEBCFDFAEGGAGADECFFGFBBHCGEBEGAFABDBHFFAHAHAHBHBEBEBCBABDEGCGCHCHBHBGEGEGCAAGGBBFCCGDG,False +289,10.0,13.0,5.0,12.0,9.0,19.0,21.0,12.0,GBFAEDDDGGFEFDHHGHGFGFGDGFGHHHHEGDBHFGGHECBAGAEACFBBDBCADFGEGDBBBBCBHHFFBFBFDAAAEFGFAFAFDFDFHGGGGGECE,False +290,10.0,11.0,9.0,13.0,3.0,16.0,8.0,5.0,DBDBDCFFGFGABEBEDEFFGFGFAFABHCAFABCDHDADAHBGBDDDADFHCBCDCAAGHBFGFGFCCBFFCFD,False +291,22.0,19.0,25.0,28.0,18.0,24.0,23.0,17.0,FCFEFEFAGEGCGEAAAEGEHFHEGFGDGDEDBDEEECBBBEDFHFAGHCAGAFAHABFBFDDGECEBGFDFCFCDBEFABGEDACACDHDHDFFCDCACHCDBBGCDBHBHCFCDHHHBHBGFGFADDGDCDCHCDCACAGAGCDDABCEGHDHFGGDDEAFBFACACABGBGFD,False +292,22.0,21.0,17.0,19.0,16.0,16.0,15.0,29.0,EFHHAHDCDEBEHEHEHEHEHCFDBCBDHCAFEGGHDDBDFGFGHCFDDDDAFADCGCFDFBFBHGAFCCBBEEAAGAGDEDAHAHAHBHBHBHEHCABABHBCCCHCBBBDAHGFDEAEAFHGBGEHAFBGHAFAFAHABCDDECGCHHGHGAB,False +293,14.0,10.0,22.0,19.0,17.0,10.0,11.0,13.0,FDGGCACGCDCACBCDCDGHHDHBHFGGCCFBFBCBDFDAGEHAHEFECBHGDDDCEBBADCDFDADEEEEDEBHAHAGCGCBDGECEHEHAACADAHFHFEFCCECEDECCDAEA,False +294,21.0,23.0,11.0,16.0,19.0,13.0,19.0,13.0,ECDFDEAGAEAGHBFEFGHBBGBABABGDGCCAGHBHFEFGGCBDGDGDGHFHABAECEAGHFDFEFBFECECEFDHGFGABAEHEGEBBBBEBADFEHEHBDBDADADGBHADADHGAEBBBDCACECBCAAGA,False +295,16.0,21.0,15.0,23.0,14.0,18.0,17.0,12.0,DDBBHFDFGBGBHBFFFFFFFGEBCFCGHABBEHDDDDBBBBDGFHFAEDHDHCFCHCECBAHACDCDHAAADDECACAGABAGEFEBCAEACGDGFEFBGBDBCBGGDDAEFEDGCGEGEDEDGDBABADFHCHG,False +296,2.0,5.0,5.0,3.0,8.0,3.0,7.0,5.0,GHDHFBBGGCGBHEHBCACHCGCGEEEEFDADBEGEFE,False +297,8.0,7.0,6.0,6.0,3.0,4.0,7.0,7.0,GDGFBFEFAAEBDBDBAGAEHBDBHCHDGBGCGHGHAAACHCHAFCCD,False +298,10.0,8.0,9.0,8.0,12.0,10.0,12.0,8.0,AAAAAADGHGAEEEHFHEHEFFAGAFHCDCGEBCBCBFBFAFHFGGCGHEDGDFDBGEDEDCBEGEGHCBEBCCDGF,False +299,2.0,2.0,2.0,2.0,1.0,0.0,0.0,1.0,CHCEABDBDA,True +300,21.0,16.0,12.0,20.0,12.0,15.0,16.0,21.0,HFHGDDEFBFBFAGCFAGBGDHEHBHBHAEFBDGACHGHAHFFDFHFHEBBCBDBDBCFCDCACAEDEDHAHBHECABAGCEBHBGEDEGAAHAFAHADCDEGEGADFGAGAHCDAGADAHCHDDGDGDHFBF,False +301,18.0,17.0,21.0,18.0,14.0,17.0,20.0,23.0,BEBFFCAGAGAGHGHFHDHCFDFDEDEBEBEAGFBCCHCDCBCHHGHEACAEFGBGBEDEBCDADHFAADBHBHCHFDFDFHGBGBAEFGFAAEHEHEHCCGHDDDGHCCCCAABCGCGCADACABFEHDBCFHGHGDAHHDFGBGFG,False +302,17.0,9.0,16.0,15.0,18.0,20.0,16.0,20.0,CFEHGDGCGHFADAFGFBFHABACDEDEDGAEHEHCCCBCEFHGHAEAEAHAHEHEHCDFFAHDEAFDFGBGDHHFHFAGGFFBEHEAEAFFFDGBGCGEECAFFHEHEHDACBCFCDDDDCBCBHGAGCG,False +303,17.0,9.0,12.0,14.0,11.0,11.0,11.0,15.0,DFDFAGHHDEDEHEHECGFACAEADDHDEDCHCECFHBBBEGHBACGGGAGAHDHAAADEHEAFADGDBDFHFGBABABHBFCHAHACCFCGCEADFCFG,False +304,32.0,22.0,21.0,20.0,17.0,21.0,22.0,16.0,HABACGCBCGHGHADEGABAFHHGFCCGFFFHFHAHAGACFGEEAHAHABABFBAEAEDGDBDFFFFEGHGDDDCHFAFGECACECECEDFBEAAFBCGAGECECFCFCBGGADADGHACAEBHAHABGGDDADCDADBBBGHEFEDDDGEFBDBDBCBABCBAAAACFGB,False +305,22.0,14.0,10.0,9.0,20.0,15.0,19.0,12.0,GAGABHEFGHGABAEDECGAFABBEFEAECCAAHGHBEEEEEFHFGFGAEAGAGDGHGFAAAHAGAGFBECEFFBBGHGFCBCGCADEDBDBDBDFEECEBEDGAAEAFAHHBFCFCDHGH,False +306,7.0,13.0,6.0,7.0,4.0,5.0,5.0,12.0,BABAFAHDFDGBHHEHBDACHGHGDDBDHFFAFACEBEBEBHBCAHBHDHCGBHBCGCB,False +307,27.0,19.0,23.0,17.0,31.0,29.0,21.0,17.0,FADCDEGEBEGHDAEFEAEBHBCBAFAHAFGEGFBFCAHAHCCBDFHGCEFFCFEFEAEAFCBDADADHDFBFBEBADFCFEFBFBFDFCFGFEAHBBCCCCHHBHAAEGEBECEGDAEFDGECEFEHGAGEFEDGBABABHDHDCDCGHAEACAGFCECGGHEDCFAAAGAGCEHEGEGFGFE,False +308,16.0,23.0,23.0,25.0,22.0,21.0,28.0,27.0,BHGEFEDACAGADADGDGDBBFBCGGHGFCFCEHHDCDCEGFCFBEBEHDHCHCBEDDHBBEBGGFDECHCHCBFDFBGEHEGEDEGAHDBDAHGBGDGBCFCGCGBBAFAFABBBFGFHAHAEAGFFFGDDCABHECEDEBEHDGDEDEGCHCDCACHCAFGGGHFHFHGHGCAEHHHHDDBEF,False +309,11.0,10.0,14.0,4.0,9.0,15.0,8.0,17.0,CECHBGAHBHAHGCACBEFEFDCCCCCBCDCGAFFFFFBCBAFHFHFHDAEAHGHBHBHEHBHCGFBHAAGEFEFEGHAHDFFCAEHG,False +310,7.0,7.0,11.0,8.0,8.0,14.0,8.0,4.0,AFACGFEEDBGHDDADFCFCFCFDBGBHEHFAGDCACFCFEFBDBGBEBFCFCFCADGEGEAHCFGE,False +311,1.0,3.0,3.0,4.0,1.0,4.0,5.0,3.0,DHHBHDGDGCFAFGEBCBCGFGFD,False +312,9.0,6.0,12.0,3.0,7.0,3.0,4.0,5.0,AAEAECGCDFDHACECEAEBHBACCHCHEGCGCHCACBBAFAFCDGEBB,True +313,10.0,20.0,11.0,11.0,10.0,21.0,14.0,10.0,FHEBEBCAHAHBFGFGHGFAFCFDBDFDCHBECCCHEACABDGFBFEFAFAHGBFBDBDBFCCCEBFGGBGFAFABEEAEGBBFFDFBFBDBGBGCGDEDHFHDGGH,False +314,11.0,11.0,19.0,12.0,11.0,7.0,10.0,11.0,GBHBFGDABADADBDCDADHBGCECHCHCGCEAGCGCDCFEAGAEAEHECEFFBECDCGEHCBBBCGDHDBDADCFFEFCACAEBHHCHGHC,False +315,15.0,20.0,19.0,23.0,12.0,16.0,12.0,15.0,CCCCEFDBDHDCDFDCHFHFDEBACECHCGGFGAHDDDBACFFFDFBBABABDBACADAHCHDGCFFBHHDHDHGCCACEDBDECEHEBABHFDDDDGEFBFBGBEBFAGAGBGHEHDFEBABAEADBCGCG,False +316,6.0,8.0,6.0,3.0,8.0,2.0,0.0,9.0,CBCDFDHABAFEHBHBHECEBECHHBEEECEHAHCDAHABAB,True +317,5.0,12.0,12.0,7.0,8.0,8.0,7.0,11.0,CHGBGBFBFDABACAFFFCECHCEGDBBGHCCBGDGFGHEHDHCHBBCCECEBEAEAEHDCDHHBHBDFF,False +318,19.0,29.0,24.0,19.0,24.0,39.0,20.0,15.0,CFEFGHBHFHCEABFCCCFFEFEGBGBAHAHDBABCBGBGBGAGAGABHCCCFFFEHEDGBHEEDHDEDBHFDBCBGBFCFBEDFAFCFGACEFGFGAAFFFFDFEFECCGEGBDAAECECABEFDFCEAEAHFDBABDCHGBGBGBCACBCBEFGFGFCFHDDFAEHDFFEDDFDFBFBEBEBFHFCD,False +319,8.0,5.0,5.0,2.0,5.0,4.0,3.0,7.0,HAAEAHDHCBDEAHCGFGCEABAEAFAFHFHBHBCBCEG,False +320,4.0,0.0,2.0,0.0,3.0,0.0,0.0,1.0,CACAEAHAEE,True +321,19.0,25.0,20.0,14.0,21.0,25.0,19.0,10.0,ECEAHAGAGDCFHAHAHABEGAGBEBFFFFFGFDFDFGCDCBABEBGBFFFAGADFDGHGABAHAGCBABGDGEEACAEDBCBCEEFHGDDCBCEGEFEBEBFGCHBHBEDFHBCGEBCDCFCEBEFEBCBCBCBAGFFAFAFDCGEEFDCBF,False +322,4.0,3.0,7.0,8.0,3.0,3.0,6.0,6.0,AGDFDFDAGECEDDHCHGHCBFDEBCBCHCHCDDAHAGGG,True +323,20.0,23.0,10.0,13.0,14.0,23.0,24.0,21.0,AGAFFGHGEBBCDCEEEGBFAHAEGEGCGFGAAEBGHEBDGAGEBABEFCHAHADFBFDFBHBHBGBEBFBFHCACGCGBFBFAHAHFEFDBGGGBGFGBBEDHGHGHFHDHDGDHBFBFDFHFHFACADAGEFHCAADHBHCADFGA,False +324,6.0,10.0,13.0,15.0,5.0,10.0,12.0,7.0,ABBDDDDGDHDCBBHCHGDGBAEGEGHDBCFGFBEBADGCGCGHFFFFFCFCBDBDGDCAAAFDHCCCECDFDHCGEG,False +325,14.0,17.0,16.0,18.0,24.0,25.0,25.0,12.0,EAGDFBFEHEFGADABCCEGEAEGEGHGBFBDEAEDHDFEFDHCHGBGEECDCDCDCHCDEAEACCBEGAGEBFBFBFCCGFBEBCCDEDFDHHGAGAGEEFFFFFBGHGHBDECEBAFAFDFDGGGAHBEFGFGFHDGDEFGCABFBFGG,False +326,10.0,8.0,13.0,7.0,11.0,10.0,9.0,12.0,HGFCFAFCFAGADEDBHFCFCHHAHACEBECCCCEGEFEFGDBFBHBGBCEEABCECAADDEDHDHBGEGAHCHFHGAGH,False +327,13.0,9.0,7.0,7.0,11.0,9.0,9.0,4.0,EFEGEFABAFHDBFAFGGEBEFECCCEFFDADBDGEGAGABABABFBDDAEAHAHGHEAAGDECCCGCB,False +328,11.0,7.0,14.0,13.0,15.0,16.0,11.0,12.0,HHHHFDGEGFHFHGDGCCHFBFEDBAHGFCDCGGDDACACEDBGEDEHHGHEFEFCFGFAAACADHFAFCFCFCBDBAEEEEGDFBFAEAEDEDEBCCC,False +329,14.0,9.0,16.0,7.0,13.0,4.0,16.0,18.0,GCAEFCFCACAEDGGEGBGBGBHBHAHECAAAAHAHECECHGHADDCBCFCHHGAGEGDGEAECGBHDACECBHDCDGHCHGEBHBHEHCFGEGHHA,False +330,6.0,12.0,18.0,17.0,8.0,10.0,10.0,6.0,GGFCECDCDCAABEBEHEFDDADGDBDHGFBFBEDHDFBHGGCBCBCDCBCHDGCBCBEDCDGDBECADACCCFEFGFGFHDADFCC,False +331,11.0,25.0,21.0,16.0,17.0,27.0,21.0,23.0,FFFCHCBCGHHHGGCEBEDFCHAEFCFHDBDBABFBFEFBFHDHFBGCACHHFBFDFGFBHHDBEFAFAFHFEEEGEGEGEDBHCDCACHHGFGFHHBDBDBHCHGEDBDECECECFGBDBCEGGGGCCBCAAADAHBBBGBGFGHDAEFGFBBGHDCFCF,False +332,31.0,34.0,15.0,23.0,18.0,19.0,14.0,23.0,HBFBAAACBDEABCHDHAHDFEFHAAACDEBHBHBHBCBHBHBGCAFGBGBFFDFGAEAEBDFFADADACADDDHAHAEEBFDFGCCCFCAEGBCBAHCGEEEEEEBFDFEHBBBABAHADBDEDFGHHBHBDDABBHBHDHFCFCGEBAAAEGFDFDGDBBBAGAGABAGHBHCAD,False +333,20.0,17.0,9.0,14.0,13.0,13.0,13.0,14.0,ABGCECACBHDHGEEHEHBDAAAFDEDGDFAFABCCGHBABEBEGADADFDEHEHEGBGAHADDHHGHGCGFFABAFDBDHABEFDCDFFAFBEBHBAFAFABABGCECHGBG,False +334,7.0,5.0,2.0,4.0,6.0,6.0,4.0,9.0,GCGBFBHAHEBEAEDCGEAEHHFHAHABFGFHFHDEDADAFHB,False +335,17.0,13.0,10.0,10.0,9.0,12.0,9.0,20.0,AGHHAHAHCBABFGADADEFEFEDBBBBHHGHDHBCECEHFHFHBHAHDEAEAEBEHACAGADHCHBGGFFFHACBDFDAGHCDGDCFCACFHFBBHGAA,False +336,10.0,13.0,6.0,5.0,11.0,4.0,11.0,9.0,EGEBEBEGEBAHEFBCBEHGDFHFAFCBHBGDABHGGGBGCGBABADHDCEABABADAEEGAGCHCHEH,False +337,17.0,16.0,15.0,8.0,14.0,17.0,17.0,24.0,HBGBABHBHDFFAHAHAGAEAEAFACGCBCECFGDGCCEFEFHHHABGFCHDHGBCBHBDGDHEHGHCFCHGHDHFHFBFDABHBGBAFHEEGEGECBAGEHBHCHEFEADCBFGHCEFGCGFAAAAF,False +338,18.0,20.0,22.0,16.0,18.0,27.0,14.0,22.0,AEAEAEAFHDHAAEFBDHGFGFCAAAGADFFEFBADCHCHEGBBEBGFGFGEHEDCFHAEBHCDCBCGAECGCHCHBFBEBHHHGCBHFDDGHHHCHBDEDECBDFEFBFGFCFBFBCBFBFCDEAFDGABADADBFFFFECECADHHHCHCFCFCG,False +339,24.0,25.0,25.0,23.0,21.0,21.0,28.0,25.0,ABAFDFCFCGHGCDBDGEGEGCAAEBHBHGHGHDADCGCHFECEBDHDABHGCGHDHEEEBFBFBDDCDGEEEHBFFCFBFAFAFGCCCHGGFGCACHEDEHGDDBHEHDACAFHEABGCACABDBEBFDGHGHFHEAEAEADACGGBBBCGCGDGBGBFCHAHAHFBABFCEHBADGDEBACGCGFAFDHD,False +340,14.0,19.0,9.0,8.0,9.0,16.0,11.0,11.0,CAADABAEACBCBGAADHBFFFBDBDEGABHHHAEFHBCFHBEBGFDFBFBDBDBDAEGEGEFCGBFBAEGBGFGFHFHFGFCBCAAGAFEHHHCBC,False +341,2.0,6.0,2.0,4.0,1.0,4.0,1.0,1.0,ECBDBFAFDFDBGBHBCBAFD,True +342,10.0,9.0,6.0,7.0,9.0,12.0,7.0,13.0,AEAHAHFEGEGBGAEBBHFDBGBHHGHAFAFAFHFDDCDHECFCACFHFHCDCDHBEBFAFGFABEEEGBDHH,False +343,12.0,23.0,13.0,17.0,19.0,18.0,25.0,20.0,GCGCGCFABHCGAFCFDFBHBHEECDDBEHEAEABABAHHFFDFGEBEBGCABAGGEGEDEDHBCFDHDGBGDGHAEAGDHAEEECHHFBDGCFCDBDHFHBBBDHHCBEHFHGGGFGFBEBEFEFCFGFGHGDGDBHBGBABDGEG,False +344,8.0,19.0,17.0,14.0,18.0,17.0,16.0,26.0,BFBHCHCACDDFCHEHAFAFEEEDHGHBEEFADGGFGEEDEDEFEFBFBHHGHGHDEFCGCGHDHDBCHDBCFCGEBHBHEHFDEAEBEGCGBHBFBHBCBCBCBGACCHHHGHFDFCFHGDGHEHDCBAAFHBG,False +345,14.0,25.0,9.0,16.0,24.0,29.0,24.0,20.0,BDBDFDFEGEDADGGGGDFAABHGFGFEBHFECHCEDBABFBEDGGCFCEAAHGHFBBHHHHHHEBEBFAEEBEDGDCHEFBFBFBHEGEGEAEBGGCAFFGDGAGAGHFFFFFGCHAHBHDEDEFHBBBFDFHFBFBFBHDEFGBEDEGEGBAFFCACEG,False +346,20.0,21.0,26.0,20.0,28.0,15.0,21.0,20.0,EDEDFHFHEDCCECEHEHCGBBAEFDDHBGBEBGAEHECGCACECGCGCDEHCAFAECHBBDGDFCFBBHBEBEHDGDBDCAGACAHAHDHCEBEHEACDDDFFAGAFAFCGEACACGEEAHAGAGAGEFEFHFBGCHBDBHBCGDGCECHDHFBFDCGCBBEBDAEGEGE,False +347,9.0,10.0,7.0,7.0,9.0,11.0,7.0,1.0,DAFCBCBAFDEGEGEFAADGEGEAEAFGFBFEFCFGFCFHEDCBGBEBAFDDABCBABDBC,False +348,23.0,21.0,22.0,23.0,12.0,21.0,19.0,12.0,DBGBGFCCGCDHGFGFGFDCDEAEAFBFBHGHBCBABAFFFBBAFHFCDBFECCDCACAEADFDEDGCFCHBBBBDFDCGAHFGEADDGHFFDADEGEAEFEDECACACAFADCFCAGBBABEDGDHCGCACACHBDGGAGBGBHAHADDDHB,False +349,24.0,18.0,28.0,33.0,14.0,23.0,32.0,22.0,DBDACACDEGGCFCBGBHFGDGDEDHHADCFBFDFDAAFAGDGCFCECEGDGFBAGHDDCDCDGHCFFAFGDGDHDHFGGBGHDCDCAHFEDBFBFCDDEDGHAHADABHBEAAACADGBGAGAFHCCGFGCGDGAEAGDGHFHFEBAHCFCFGGGEGEGAGHBBBDCCHCHFHCHDFDBDCDEHECBCEAABC,False +350,8.0,4.0,6.0,7.0,7.0,4.0,16.0,7.0,EDGFGACAGBHBEBAGACAGEEEEEGGAGCGCDAFHGDCDHGHCHGBGAFDFDGGGDHH,False +351,14.0,22.0,13.0,15.0,4.0,11.0,14.0,13.0,ABCCHHFHCDBDBDBCCGCGFFDFBFGGBAHADDGDCDCBAHABEFHBBDBDBDBEBEBGDAEABDGFHBHGAGCBFHHHHHACGBGACFBBDGDBFAGAGACACF,False +352,23.0,10.0,18.0,19.0,18.0,25.0,14.0,15.0,GFADHDHFCGCBFFFHHEDFDHAEEFECAGBGEAHAHADAEGCBFBFEGEFHHEGGCFCHHAHAHEBAADAGBEBEDEDGFEFAFADADFGFAFCECECFFAFACACHCDFDADCDGGFDHCCCCDGDAFBFBEADBDAECF,False +353,28.0,26.0,15.0,29.0,24.0,17.0,31.0,29.0,EFGDADGCGBGBGBEAEHGHFDDEDEDEGHGEGEGHGHEHGDGBGFEAEGDCHCHDHFHEHAGDHDFEBEBEBEDCDCACAFGFCABFEGBGAGHHBDBABABHHAHAECEAGBGBHBFEDHCFCDGAFDHBEACFHHGDADHCFCBAAHFFGFDADBBEBHACABAHGDGBEAFABDBGGGGDDDAAHDDDHCHAABE,False +354,2.0,5.0,6.0,7.0,4.0,6.0,4.0,6.0,BHGHAECCCFADBDHDEDBFBHDCDCDFGCGFGFHHEFEB,False +355,6.0,5.0,6.0,6.0,6.0,7.0,2.0,4.0,HFHCGCGBFEAAAHAFBCBDEDEDEDCDFFABBCFCADFEHE,False +356,6.0,7.0,14.0,10.0,18.0,19.0,15.0,16.0,FBEHFGEHFDCDGGGEHCDCDFFFHBABDFDFHCCFEFECEHEFCAAGFGBCBFGFEBCACACDFFGHGBEHEHEHFHCCEGEGEGECAHEDEDGDGEHHHGHFF,False +357,14.0,24.0,11.0,19.0,13.0,13.0,20.0,12.0,CAHGEBBDBFBEGHAEDBDHDGDGECACACEFBDBFFGADBHBCCDCDHDEGEAFAFEGBFBABHFHAEDEDGHGBEBGBGBGFFBCGEGDAFAFAHAEBCGDDAGHHBCBDBDBFBDBDCGGGGH,False +358,14.0,23.0,16.0,16.0,14.0,16.0,6.0,16.0,HBCBHFHFHDBAGAEDCCCBFDFHFHDHDHGHABCFCFAGEGBBBFDADADBEBHFCFDFCBADDBCBCBCAEGEFCBABAFAHBFBEBEBCCEEHEDECBFAEHGADHDHEHBDEFBCDA,False +359,13.0,21.0,20.0,21.0,14.0,16.0,20.0,15.0,GFDBDCACAEBEBEBHBCBCECEGACHCHAHAGGBADADBDFCFHGDGDGEBHBDGGFGFGDBDAGABDGDGEHFDAEFFGFDHEBCCDCHCFCECHGDBCEHEFDFDABEBGDGHACFFBDCEAFGDBCGCBCFHBHBH,False +360,2.0,2.0,1.0,1.0,3.0,6.0,2.0,3.0,GFFFEFEBDBEHGCAHAHFF,True +361,14.0,17.0,14.0,17.0,23.0,22.0,11.0,18.0,DHACABDDDFEFBCAEAEAEFCFEFCFDFHFAFBCBCHGHFHEAEGBHBGCFCHAEBEFECECGFEDEFCCHAFAFAFADGHGBGDHDEDAHBHBHGEEBDHDBEEHGDEDEFBFBFHFGFBDAEBDGCHEEDCHB,False +362,7.0,7.0,14.0,4.0,6.0,6.0,6.0,3.0,CCBCGEGCAFAEADAGFGFCFCBCGHBBDBCGEAHAFCDCACBCHCEEFECBD,False +363,10.0,8.0,17.0,16.0,17.0,20.0,8.0,12.0,FEADABEGEHEBEBECFCDCHBHCAEEGHCFGFGFHHEFEFDFGFDECCACHFFFCDCGADAFGDCDCDCEFFFFAHAHBEECCDADAFFBEDEDEDHCFCDBHGHDB,False +364,8.0,4.0,4.0,12.0,13.0,9.0,10.0,11.0,FFHEHDFFAGEGEHEHFGDDDEDECEDABHFGFGDGAFADAEECGGABDBGHHCDCBGFDHDHAEAEHEHE,False +365,6.0,2.0,5.0,1.0,4.0,5.0,1.0,5.0,FEACAGFEFHCEABABAHFFEHAHCHCDC,True +366,11.0,5.0,9.0,15.0,4.0,9.0,12.0,5.0,CCFDEDFDFEFEHDBDCDHGGGGDFDAACADABFGCBCAGAFDFCGCGAHAGAHDBDHCGEBFDADADGG,True +367,22.0,11.0,14.0,10.0,20.0,19.0,35.0,19.0,DGGGBCECGDADABABHEHBHGAGHGFAFAGBGBGEEACACFEFGGGEFHCDEEBEBAHCEFFFFHAHAHGFECBHGGEGEHAHFGBDFHEEGCGFDAAAGEGAGFEFHFGAGAGDHAACAGHGCGAGDGBFHFGCGCECEHFHDGEGCD,False +368,2.0,3.0,4.0,0.0,3.0,2.0,2.0,2.0,BCECECHFHFAGEGBBCA,False +369,2.0,7.0,10.0,3.0,12.0,8.0,6.0,9.0,HHDHDCCEGEFFFHCBBHDEGEHEFEFEFEFBCBEBHBCCGCHEHBGGACECEFGAC,True +370,17.0,20.0,13.0,14.0,12.0,20.0,18.0,16.0,HEFEBECCHDECGCEBBGCDBDBDGFGFAFHGDDFDHBBBFAGDFAGACEFHGBFDFHFHFHCGBEDHFCFCFGAAEDECEFBFAHABACAGAGACAHABFBFGEGDBFBHBHDHDGBABAGCGEBAHGH,False +371,14.0,16.0,16.0,7.0,13.0,5.0,11.0,14.0,GBGBEHFHFBBBECAABDEABAGAEDEDBCEGECCACAGACACBCHCECEGABDBEBHBHFHCDAEADHCHCHFHCEABBCDHEGFGCHBGGHGHA,False +372,9.0,15.0,11.0,10.0,12.0,17.0,13.0,14.0,BEBEBGFFBFGFDFGCGCGFHDGGCFAFAFBFDHDEAEHEHAFBFEGHHEBGAGCHHHDDCECGCABFBFHFEDEDHBBCBGBCAGACAHBECEDDHBHFF,False +373,14.0,9.0,8.0,14.0,6.0,19.0,18.0,14.0,BHEFAHAHDDDDFBFDFGFEFHGBBFAAAGADHGBFCDGBEFGFCHHGFGHGHFHGEGAGEEAGDDABGGCCCBHBHCHDFAFAFAFGFDFDADADCGCGHF,False +374,13.0,6.0,13.0,5.0,8.0,10.0,12.0,6.0,CBGADAHAHAFAFGCGFGCDEAEADADCBHDFAACCCAFHBBCEGEGECFHAEBEHCGFGFGEGCGCFCGABF,False +375,8.0,5.0,6.0,3.0,11.0,9.0,8.0,4.0,EEEEHFFBFGGCGHGEBABEEFCFCBHGDBHFAFAFDFGAGDGAECECECAAAE,False +376,6.0,8.0,6.0,9.0,8.0,5.0,12.0,5.0,AEGEBACACHCGGHDBDBCEGEBEBHFDDGDCDBDBEGCAFBFGGGEHEAADFDFHGGG,False +377,2.0,3.0,2.0,5.0,6.0,4.0,2.0,2.0,EDEDECEBHBGFGAEADFHBDFEFDC,True +378,18.0,11.0,12.0,20.0,13.0,19.0,14.0,21.0,GAEHGHAADADADBFCECDCFCGDDFCGHAADFFFGHBHFDCDBFHFHGHFAGAGABADDHAEDECFFFAFAFDEDEBABFBGGHBCBAACBHHHFFEDEDADBEHFHGCGEEDHDCDGHGHEHEHCH,False +379,15.0,10.0,10.0,14.0,7.0,13.0,13.0,11.0,FHGHGHBBCDDDDABABGCEDADCHGAAHAFCFBDBDADFCFDDHCHFHAHCHCBCGGAACAHGGGGAGBEDFDFEAGDGFEBEFFAFAEBEF,False +380,20.0,20.0,27.0,28.0,18.0,28.0,19.0,15.0,FAEAEHHHHHHECBHFFFCFCDAGFGDEDCDCBGFFCGBGEGBAEAGFCADGGBEBEFHFDCBAEFDFDEDAHAHGEDAGBGFEBEGFDDDFDFAFCCCCCCBCBCGCGCACDDBFAFBCDADCDEDBCBCGHGFGBBAFDCDHBHDDBDCECACDFDGABFEDEAEFHHAAFFF,False +381,9.0,4.0,8.0,8.0,10.0,3.0,5.0,2.0,DEDECFCECEDAAACHEGDDFDFCACECGAABDGCHBEBGDGBAEAEAE,True +382,28.0,23.0,23.0,25.0,22.0,19.0,22.0,24.0,EBAHHEDEDBDHHGADFEFEHDHDGFFDFDADHDGEACBEHEFGDGAGAGEBCDCBBAFECHGGBHCHCGGGCGAFCHCHBBEBFBFHFCGCGEDEAAADABABADFEFDCDCECDCHCHCBAAAAAAHAFEGEADCCFHFEBEBFHDHFAAAGCBBBCDHDEDFBEGHCBDBGHGCGHDEAGABA,False +383,4.0,5.0,2.0,2.0,4.0,7.0,4.0,2.0,FAFBFGCGAGAGFBDEFEFHABFBDCHEBE,False +384,23.0,10.0,11.0,21.0,17.0,14.0,20.0,15.0,CBEFFDDBFAGHDAGAGAGDDBEGCCCDCBHHEAEFGFEEEHEACACAGAGBDAAHFHFAFADEHCACGDAEEFGGHEHBCDAGAEDEBFGHDHEHDHFHAGAGAGAFAFABBCDGGGDBDGDEDEDFDHD,False +385,16.0,15.0,15.0,12.0,17.0,20.0,20.0,23.0,FGBHBHAHAHBDFEFEBCAEEDEAHBHBHEFDCBAFCFAFAGHGHGACDHBCAEHGHBABFCFDGDFDFHFDBGFGHHACADACHCGBEBEHEACGEGFGFGDGEGEGECEADACBGFHHDFFHFHFGGBHCGCEEHC,False +386,22.0,28.0,19.0,25.0,19.0,24.0,12.0,27.0,BHDGBHDFDFDBABGDHAFAECECBCBCFCBEBHHHEEEBAFDFAFADECBDFDFAEHBHEHEGEADHHHFHFHDBFHAHADADFDFCAHBCGCDCBBBGBFAFCFHAGADDBFEFEAAHCDCECBDFFHFHBHBFEDCACAGEFDHGBEHGBCBHEEGAGHBDBDGHADADCBCB,False +387,16.0,23.0,23.0,12.0,27.0,6.0,20.0,14.0,EDEBGBEBCGGHCACBHBEGAGHGCGEGFCHBDCHGHBHGDADADBBCHCBEBACGEGEGEBABABDEEHECCCCBBBGAGAEAGFGHACCBBABAGFBEEEEEECGDDCDHEEEAEAECDCECGCFHFCBCEADDHEBFH,False +388,29.0,22.0,29.0,26.0,26.0,22.0,19.0,18.0,CECEGHFBFDDCDHGAFBGDFAAHACACAEEBEACFCAEECCGCGCFFFABGBGDCDGDEAEABHBHBFBHAHDCECECHFEFBACDDDEHAGABADFDFDBDBDECECEDHDAAAAEBEGAAADGFBFADACHEAACFGFGCGEHFHFCCCDGGBCEGFAFEBHCDAGBCBCDCEEGDBDBDHFHEBEHH,False +389,6.0,5.0,9.0,6.0,6.0,10.0,3.0,6.0,AFFFACCCEHHHHACDFDEGCBCDEDCFBFBDBFHFHADGCGCEFAFAEBE,False +390,5.0,5.0,8.0,6.0,3.0,4.0,2.0,9.0,CHCGBFDADACBFDFCHHDHDHCGCBFAEAEAECHCHBBDHH,False +391,17.0,18.0,29.0,20.0,13.0,16.0,17.0,22.0,GDCDGHHBEBFCFHGHAAAHBCDCDHFHEHBDDDDDCDCACHEBDBCBFDACBCBHACCDCGGGGCBCFCFBACADHHCFCADHHHGCBBGDGCGEEHEACAGGFGCABABDBEECECECFAFAGHHDHDFBFGFHECEFDFAHBHFGCACE,False +392,4.0,11.0,10.0,5.0,8.0,5.0,3.0,15.0,HHHHEEDDBGHGFABEBECCBHBCBEDECBCHCBEFEHDBDHAHBHFAGCHCHCBCAHFHF,True +393,5.0,6.0,6.0,2.0,4.0,4.0,5.0,6.0,HGFGHHHAGCGEFEBDFDAAHAFCBCBCECBGBEBHCA,False +394,21.0,28.0,17.0,22.0,17.0,15.0,15.0,14.0,DHAAAAFCDBDBDGGABBBCHCACGHFBBBBBBBAAAAFBBBBBEGEABCGFDHEHEDBAADEDEDEHCFEBEGDHFGGECDCHCHBDCEFEHDBDBDBDCECGCBFDGBADHGGFAFAFACEGEFDFBABFFEGDAACACHEHDHDCG,False +395,17.0,17.0,23.0,13.0,25.0,16.0,32.0,27.0,ACFCFGGGEEHEGGDEHBACACECEFEFHDEDFDGEGBGFHCCACEEFDACHGHGHBEEHBACCCCHCEFDAGAGEGCBHBHBGGGDGCFAHGHGHCAEFBBBHBGBHHEHEBGGEGEFHFHFHGHGCFCGHGDEDAAAGCBBBCHAEAHDHDFGGGEGBAHECDFDCAE,False +396,2.0,4.0,1.0,7.0,6.0,10.0,8.0,9.0,GCGFGFGHBFAEGFHFHGBDHEFEDHDEFEFDFEFBGHHAHGDBDHD,True +397,12.0,14.0,13.0,17.0,13.0,20.0,12.0,15.0,CEBHFCBGHGEGEACAHBHBDBGBADFDHDFDADHHEHFHBAAFACECECEDDGDGDCCCHCGBBDGFBECGDGACFFFFFFDHDHAEFEFBBGBFHFHECAFDBEHDFAFAEGFD,False +398,28.0,19.0,7.0,24.0,27.0,19.0,20.0,15.0,DHEAEADDHGAAHAGEHEBDBDHFCFEFEFEGAGHGBFHECAAGDCDADFCHDADADFDHGBGAEHDGFBFAFAFEFEFEHCAAAGGBBABDBCEADADFEGEFHADEGGGEGEGBGBDADEEBDBDHEEEDADEBBFHEEFCFEFAAAGABABDBHBG,False +399,0.0,3.0,1.0,3.0,3.0,3.0,0.0,4.0,DDHFBFEFDHBHCHEBE,True +400,14.0,15.0,8.0,10.0,12.0,16.0,15.0,13.0,BABABGHFHEHEAEBFGHDBCBGDCFFGAGDGFEFEFEFHDCAGAGHHAHACBCBGAGEGEDBDHDEBCACBHAHCFAFEBEDFFFBFGEGFABHGDADFBHG,False +401,11.0,5.0,16.0,15.0,7.0,18.0,6.0,17.0,EGDHHBGCGFFFFECHDAFAFBFDHGHAACFFFAEHBFDFHEHDFDFDABBEAFCCCCCCCFHAGADDDCCEHEHCHDHAHFHCCCFDHDHDADG,True +402,3.0,10.0,24.0,13.0,15.0,13.0,11.0,19.0,CBBEDHAHBDBDBGCECHHDHGHDCGCGEHCHCGCEEEEHFHFECEGBDDFBHEDBDADGFHCHCGCBCDCEAFGFGHGHCECFDECCCCCDHHEBFHFCFCEHFFCF,False +403,1.0,2.0,2.0,2.0,0.0,1.0,2.0,2.0,DGDABGBCHCHF,False +404,5.0,16.0,6.0,12.0,8.0,5.0,12.0,9.0,DGDHBCBCHGEEHEFGFBAGABADDCDBBBBBGAGEEDCDGHGHFHBHGGCEEDBDBDBCBDBGFAEBHFHGD,True +405,21.0,16.0,12.0,16.0,13.0,10.0,25.0,18.0,GFEFBFGGBGBGBHFHEBEBGBGFGFCEAGCDHAABHBEGCGHDHAHDCEGDGDBFGCAAAAEAGADFDGDAACACECEBFDHBAEACHGHAHDEDEFHHHBGEGACDBAGGBCBHHCDGAGDGHGHADAD,False +406,4.0,4.0,3.0,5.0,1.0,0.0,4.0,3.0,GBDDABCBCGDGDCHBHDHAGAEA,True +407,16.0,7.0,6.0,14.0,13.0,6.0,14.0,8.0,BFCAAAAAEFEBDFCFCADGDBDBDAGAHAEDEGHGHGFDBDGAEHEAEAGCEDHAEADGDAFADGGEGHGHDEBEHDGBGCCE,True +408,12.0,15.0,11.0,21.0,18.0,14.0,12.0,11.0,DBDBDBDBCBGGABCEFEFGGDBDAAAEHEFEBGBECCFCBGEEAEHCBFEFHFCEBFBHGADFDACABEBEAECDCGFDDDDDDHGEGFDHDHDHFCDDEDGAAFAFHHGHEE,False +409,20.0,21.0,28.0,22.0,20.0,26.0,20.0,22.0,FCFDFHADGDHDHBBCCHHDHDHDGAABAGCGCDCDFFFAEAFBHHGHCHEFEGBDCDAAHABBCFHFEEGEFFFCHCDBDEDEFEDAFAFABEHCCCEBHBDGDECCAAACDGFFEDHDFBHBAGAEAEFECGGGCHCDAHBGBDBCBEHGFCFCFCFCEGEGHFCBGFGCGCEABBB,False +410,3.0,1.0,3.0,3.0,0.0,0.0,1.0,2.0,DGACBHDHDCACA,True +411,10.0,24.0,18.0,15.0,16.0,10.0,24.0,18.0,HHFBFECHGHAHFGGDCBCBCEGHGBBAAGCCHCBDBGBDHHHBFBDBGGCGHGABABACEHEHCDGDECBAAEFGGDGEADDDHDHBEBEGEFEGEGCGDGDEDBCCCHCEBEDCGFGHGEGFBFBACHBBBBF,False +412,7.0,7.0,14.0,10.0,10.0,6.0,9.0,5.0,GEDFDFBAGCDABADDGAHEDEDFDCDCDFHCBCBCGCHBGCFCAEEEEEGEGCCCHHGCBEBCAGAF,False +413,1.0,1.0,2.0,0.0,2.0,2.0,3.0,2.0,FGCGCHEHEABGF,True +414,3.0,7.0,4.0,3.0,7.0,6.0,6.0,8.0,HCHGEEBABABFBEGFGAGBDFDEHEFCFBHHHFHCHCBEEGGD,False +415,17.0,22.0,23.0,22.0,24.0,17.0,20.0,16.0,BCBGBADDEHEBECCCCDGAGEGEAACEHEHGFABAEHECECFCGCECDBACAHADECGCBBFGFEHEFGDGEGCGFGDHDCBCAFGDGDAEFHFCFBEEHEBDDFHHHBAFAHDEDGDBDEDECFCFHFAGCFFAEGDGDADCBBBBCGHHABBBBBDED,False +416,23.0,23.0,29.0,23.0,28.0,15.0,36.0,18.0,HDFEEHAHFECBCGDFDFBAGABBGGADFDGEGECECGDHCECECEDEDACACGEGCGFBCBCACEEDEGGABHEDCHBGGGHGCGCBDBCCCEHEBGBCDDGGHGEFEGBBBDBAFAFAGBFFHHADEGEDBCCCACGCDCGEAHAEADGGGDGDBFBFCGCGBGBGACAHAHGEFDADEHEHAFGHBHDEAEA,False +417,6.0,3.0,6.0,6.0,13.0,9.0,7.0,12.0,HGCCECEAEHGHGCFAFHDDBDEGBGHHEEDAFGFHEHAAADBCHCGFEEEHEHEFEFDFHF,False +418,7.0,7.0,9.0,13.0,10.0,16.0,6.0,11.0,HEFFFEDECCHHBHFDFACACEDHDBDBDBDFCFDEDEBHGEFFAFADAFHGBGCGCFDEAHDFDHGHFHCGEFEFABC,False +419,6.0,2.0,4.0,3.0,3.0,0.0,2.0,0.0,EEBDBAAAACACEGGCCDAD,True +420,20.0,21.0,13.0,17.0,21.0,27.0,25.0,13.0,HAGAGAECCFDBEADDGAGFFDCBFFCABGBEBAGCGBFBGEGEFDCDEBFBEDCAHBHBDFDFBADGFFEGEGEFEFEFHFBBABAHHDGDGBGAGFGFGEEDEDAFAGDHEACACFFGFGFGEDECBFBFHHHGEAFAEAHFBEBGBCHCHGADC,False +421,9.0,14.0,14.0,8.0,6.0,14.0,12.0,12.0,FHFDFDBBBGBEBCBFDGDHFGABCGABBGEAFAHACACHDDFHCBBFHFHFGCHCHGBBHHGCGCACACHCEFEFADDFEFEGGCGCB,False +422,2.0,4.0,4.0,2.0,2.0,3.0,4.0,6.0,HFCFCECBGGGDGBEHFBAHAHBHDHC,False +423,19.0,10.0,8.0,8.0,6.0,9.0,8.0,8.0,DEABABCFEFDAAABFHFAFAFADACCGBABAGHBABABAGHEHCGDGDCDCGEHEGDAABAEHBAGACDFFCFHH,False +424,22.0,16.0,21.0,30.0,13.0,19.0,17.0,12.0,BCBEBDAEAEAHAHGHCBCAAEADGFGDGDCACFCDEGCDHBCADDDDDEABADADADAEGBGBHCGFAFDCDBDFACDBDBCFEHEHAHGFGFGFGECHFHCCGDGACDFDECFDADEBHFFDFDFBFBEHAGCGDFCBGDACBCFDAD,False +425,12.0,15.0,7.0,11.0,10.0,19.0,9.0,9.0,CADACAFHFDDCDBFBDBEBEDEHFABACFFHHGFDFDGDGHAHACCBEFDFGEGEADFFCEGBABAEHHBHBGBEBABGBEFFFFABGFFF,False +426,10.0,14.0,11.0,11.0,11.0,17.0,18.0,9.0,BFBAAEFEHCHGAFEBCFCGCGBGFHFCGGAFAFBFCFHBBFEFEFEBGCECBGBGCDFDBDBDGAGEFEGHGHAADEGCGHDBAEGDDDDCDFGFGABHH,False +427,37.0,20.0,35.0,16.0,24.0,26.0,23.0,17.0,AGAEEHGHGCCCGBGCHCHCHFGGAAAEAEAFHCHCGCACADEEECBABEFEHDFBFEEBBBCEFAFADACAFFCFDHDGBFFACDGDFDBBBCGCBAAAEAECGCDHFBDBCAAGACACAFAGGBEHECECEABFEGDFDHHAAAACHCHGHCHABEGCGFACCECFFBFBABAGFFDAECEDEFFACGCGAGCDFD,False +428,16.0,17.0,31.0,28.0,15.0,17.0,26.0,26.0,FGFCCACBEDEDBCGCGFDCAAECEAAFFGGGGHCHCAGDGDBHBHFHFHFHDHAGGDDADHDHBACGCGEDHBCDFDGDHDCCCBBBBGCCCCFBDDDBCCCHCFEHHGFBFCCAAGGDADGDHEHAGCGCBDBFBFEGAGEGHCFDHHHHEHEBEHDFDGDHAAECCCEDEDGH,False +429,8.0,4.0,6.0,7.0,12.0,5.0,7.0,6.0,AAHAGBFHFCEAEBECGFGFGEEECBCDCAEHEAEDEDHGHBCFDGEGDHDEDAA,False +430,5.0,7.0,8.0,4.0,4.0,3.0,11.0,4.0,HGDCHCBCBFGAGBGBEDHAEAEGFGCGEGAFCGCGDHDBBBCCGA,True +431,8.0,19.0,9.0,16.0,16.0,15.0,11.0,12.0,FABCEHHCGDGDFDFHFAEDGDFDFBBBBFEDEAGBEEEFEGEBEFDDGBBAAAFHFHEEDCDCGEDBDAEHEHBHBHBFGCDCHEDBFBGHGFBFBCBCGCBAHD,False +432,25.0,23.0,17.0,34.0,27.0,19.0,18.0,34.0,GBHHHFEGGFGFGHBABDBDBHGGEBBDEDHHHHAHFHEHFFFGBDDEAAAAADCDHACAFDBDCGCGDDDHAGBDHGHCHABAFEFEFEFDDBDBABGFAFEEDEDEAEBFDFDHAHABEBEDDDFHCEFEAAAECCBABHDADHCBFGDHEHAGBDHHEHEDEAECEDGCEEHDDGHCHCHEDDHBHCHCACBCG,False +433,11.0,10.0,8.0,8.0,5.0,5.0,7.0,5.0,GEEEBADHCHEBEACABDBDAHABABABCDCGCDABFDCACABGGAGHCHFFDDGFGFB,False +434,8.0,2.0,9.0,3.0,9.0,11.0,9.0,7.0,CECFFFHGHBHCFCFBFHDACEEFCGEDEDAAAGCGCEFFAAGGGHFHFHEGEGECAA,False +435,15.0,9.0,12.0,17.0,12.0,13.0,11.0,8.0,FEFHFAFEDEDBCGGFBHACGCFCHADADAFAEAEADHDBDFHEDEDBBGBDADAGAGEGECCHEAACBCDCEGFGFDADGHHFDFCCCBDGEFADB,False +436,9.0,4.0,4.0,2.0,2.0,7.0,7.0,7.0,HEFBABCEFAFABGGAAACFCFGHBHACGFGAGAGHHDHDHF,True +437,13.0,14.0,15.0,27.0,27.0,6.0,29.0,26.0,DDDEHABAHEHAHDCBGDHFCEGBBHBHADDEAGGEGDGDGCCDCDBDBHBHBAAHGGGGACECEGGGECCDGDGEGADADGFHEEDEGACAGHDDDFDFBEHCHGHFHEEEHEHEHEHEGEFDGDGHBCCEDHBCGDHEEBAGHGEGEGEDHBHCD,True +438,22.0,9.0,13.0,21.0,26.0,17.0,18.0,21.0,GAGEHFHCEGEDAFAHAHEDBDFDABAHEDGDBCAEGDDDGGGGAGEHHHGCCFHHBHBHBHAGECAGDGDGDGEHDFAGCEEFEHEAEAEFFCECFFFBDADFDADADAFEEEEAFAEEBABAHEFDGHEHFCDCDCECHCHFEAH,False +439,24.0,19.0,22.0,19.0,24.0,22.0,19.0,24.0,DCDCAAAAABAFGFDFDHGCGCGBDACCCCEHFACHEDAAEABAHABAEFHFCFCFBBHFHEHEGCGDHFECBBBGBEHEAEAHDGDGHCHFBFEFEBEDFAACDHDFBHADCCEHEHDBFGFHDHDGEGADADEDEBECHFGGAGEFCCBCGFBBAGEHFHGHEHEFECBGA,False +440,23.0,14.0,11.0,16.0,9.0,11.0,13.0,16.0,DCDGBGBAAHECEFGFGAGHHEDGBCFDFGHGEEFADAEGFBAAAABFBFDAACCCEDHHHDDAAEBHCHABCHAHAHABEDGFGBGDDDDDDGAAHACACACABFFHBHBHB,False +441,5.0,9.0,7.0,7.0,5.0,6.0,6.0,2.0,CFDBDGCADBDBDGAAEAEBFBCBFGHBEGDHDECECBCGFGFBFAC,False +442,21.0,17.0,17.0,31.0,26.0,21.0,12.0,20.0,AAAGDEAFCHCBEDDBDBDHCAAHBDBDADHFHFHFHFHFDFEADADHHCHDDCFBFACHDEEEDABADAFEFHCACFFFEFBBEHGDGEGFDDCDGEGECCCCCFCHDEEECGCFDEDGBBDBGGHBFAFEDADFDHEHDHAGDGDBAEEEBEDAHAEBEBEAE,False +443,22.0,20.0,27.0,22.0,26.0,31.0,22.0,17.0,EDEAHFDFEBGFEFHGAFAFEDEAHDFBEDACCCBCBAFADAHFCGHGHDCDCGGHBBGACADFEFEFBFBFBHBHAHAGGGEGAGACECECBAEFFDEECDFECECBCEHDFCABHBCGDHBFBFBFAEDCFFHFCFGFDEDEDGFGFGFBCHEGGCEDGCCHDGFGCCCACEDEAEABABADFDH,False +444,25.0,15.0,17.0,18.0,21.0,13.0,21.0,25.0,GCAFBBBBAFGHBACAFHCECHBEDEHHHEDAHABCGDEAAABDBHAHBEGGDGACDBGGGGHGHGCECEFHFCCGBEEEEEDFCGDGDADADCECBFFCAEAEADGDHAHAHEHDHAHEFEHDGFHFHBDDAHAGAGAGAGEFBHECFCACHDH,False +445,4.0,5.0,1.0,1.0,6.0,3.0,0.0,1.0,FEBBABEBEAFHFEAEAEBDC,True +446,3.0,5.0,3.0,4.0,0.0,2.0,5.0,1.0,DBDAGBGCGCGCBBBAGFDHDFA,True +447,27.0,17.0,19.0,29.0,21.0,26.0,19.0,16.0,AAEEEEFDFHEADAGFGFGAGHFABBBBDADAHFDGCHFDFAFGCCBFFHDHDADEBHGCAHAFCCGCHEEADCBFFDFAFACAEECDCDBHBDCCEDEAGABDBDGGGGHFHFHDEAFDCDAAABAGCGFDFEEEBGAGAHBGDGDFDFDHHACCDCEBEAECEFEFDFDBDB,False +448,12.0,3.0,7.0,7.0,6.0,6.0,10.0,15.0,GCACACAFHFHGHDHAHDDEDCFAHACAHGEFHBHBFGDEHEAAAGAGCDAEGEBHDGFGHHCHGH,False +449,27.0,20.0,31.0,20.0,16.0,31.0,25.0,16.0,CCFCACAHBDGCGCBCGCDCBBEBAGFFFCFCDCBHBEFDFDHGGDCFEDBDFDCDCFFDBAECHADBCHCHCAAAAFAFADDGFCECGCGDDEHGHFFEHGHGFGFGAEFBFEFDBHAFDGGCFAFHHHBHEAGAEAEABGHFAFACACBCACGBBAGACAFFGFGFDBCBCGEEEECFADGBGA,False +450,2.0,7.0,4.0,2.0,6.0,1.0,3.0,3.0,DGCGCBDBHCECHBEGEABFBHEAEBEB,True +451,8.0,7.0,6.0,1.0,2.0,4.0,4.0,3.0,FGFHEABCCCDBABAHCHEAGCGCBAAAABBBFGF,True +452,12.0,16.0,17.0,11.0,29.0,15.0,19.0,16.0,EGDGEGHCFCFDDBECFHFHGEBEBEBEBDBAHAHADCEEEEEEEBECCBBBGDCDCFGHHEACAGBGHFEGEAECFDEGFHCEDFDFDCBHEAEAEFBGCGBAHFHGGEEBFGFGEHAGAGAFCBHHHCCECEG,False +453,4.0,3.0,6.0,2.0,6.0,8.0,4.0,3.0,CCFCEEHCHBDEFAFAFHGDFEGEFBFBFCECGAGA,False +454,17.0,13.0,25.0,22.0,19.0,16.0,28.0,27.0,AGAHHCDEDGGGDHHFEEGEHHCGGHGABCDCDAAFCFCGAGCFFFHEEEHEBGBCFHDAEEBDCDCGCGCBHBFCFHDHGBGDHCHFHBHDHBEAFCCDEDAGCGCDCFFHGHGHGAGADACAEABFCECECEBEHAGAHHDGDGHGHGFDFDEBCHDDCDGBGEA,False +455,3.0,8.0,5.0,6.0,3.0,3.0,1.0,4.0,ADHHHDFFACBCBCHCBDDGDBDBEBEAEFCBB,True +456,17.0,25.0,25.0,21.0,21.0,26.0,24.0,21.0,GEGBFBFBFBGAHAFACDEDCCHFFGBGAACFCHGFCFGHDAEFEFGFGHEBEBDAFGFAFCCBABEHCGFEDEDGBGBFBEHEGGCDCDCBGHDCCCDFAGBHBDEDHCHCHEHCBCDDDDFBEEEEGGBFCFCHAHACGFBBHDHBABGBGDGDFAFAECECEFDFDBGCHBAAHHEH,False +457,12.0,10.0,8.0,8.0,4.0,11.0,8.0,8.0,DBDFDFCCCHBEGFBHEFACBDBGHGBFAFGHAHAHGDDDCCACGCEHGFGFBFBABABDHFAAAEAFA,False +458,20.0,11.0,18.0,22.0,26.0,28.0,20.0,28.0,BFGHCHEAEAFFFFGABCFGFECECECECHCHGHDHAHEEEFHAAFBCGHDHDHCABGHCFDGHGACFDDDBCGDDFGGGGEEABGFAFEHAFEHAFAEAEABAGFDFEEHEFECDADHDHBHEHDHCHFHDHFHGDDDDEDEFEFGDCHCECEFHFAGBFFEFCADGBGBHA,False +459,18.0,25.0,19.0,16.0,13.0,17.0,21.0,14.0,CACACDEDBCBHAAGHBHBCEDEDAGGHDFDEDCHFHECFBFACAHAGGGGGAGDFBABFFGFBHBHBGBHBACABHBGCGBGEFADCDCHAHDHDBACABBBGEGEFCFBGBEFDFABABFCEGECDCBCGDBEGFFCFDGE,False +460,21.0,19.0,19.0,30.0,29.0,19.0,23.0,32.0,FDEDECCDEEHFDFEFEFHAHDCGCGCFDDDCGAGAECDHBEBAHGCGEFEDHDHDGDBHBADCDCHHFECHBGBEHADBDHGHGHGHDHFBGAGHBFBAECGGFEFEFDGDCDAEGEBACHGGDDADFHAEABBGBABDFDFABEDAHBHAHAEDEAEHEHCFCHEHEHBHBHGGCACAHEEEEFDFCGDH,False +461,9.0,19.0,19.0,25.0,19.0,17.0,20.0,16.0,BEGCGDAEHEDBDCEHECACAEAEAFCEGHGHFHGHCEDDDHDEGGFEHEFDFGFDBDBDGDEDCFCFHECBDHACCBCBFGDGCHBHDDBGBGFCBCDDGDACFGGGGFGBEBEGHDBDFCFBFDFDBHHAHAEDFBCBEBEC,False +462,9.0,14.0,11.0,15.0,9.0,10.0,15.0,17.0,CHCHCGCBEBDHEHFBGDGDGDGDBDGEGCHHBDBDACFCHGFEAHFFDCGAGBFHEDEHHAHAEBHBHGAGBFBDBCFCBCBADAGEGHHEFDFDGDAH,False +463,15.0,16.0,16.0,16.0,13.0,12.0,15.0,14.0,EDEGEDHBHDHDACHCBCAHADGDGAEEHFGFGFAEGEDECGGAFAFDBCHCGCEBABABABDEACHCBABAFGEACFDBBCBEGEGCDCDADBDFHHHHHBDCDGBFFGFHCBCFG,False +464,20.0,13.0,10.0,7.0,14.0,12.0,14.0,15.0,HHHBDFFCHCGCGAGDFDGEBFBABAFAFHGHBAGEGEHBACFCEDBACCCABADAGBGAGEEAAFAFACGCFAHEHEDEBAGEHEHEGAGAEFHHHHABEBDBF,False +465,32.0,28.0,23.0,18.0,15.0,22.0,28.0,21.0,CAHHBFBGCACEGFGAAABABAGGCGCGEAAGCGEEDBDGDCDHDBBABAFABAEDBGCEDBDBAHABFHEDEDBFFGAGHHEGAGHEECDCFBHCGBDBDBFGFDFCFAAACACFGHGAGDCFGAGFFBHCHCEABHBFBFHFAFHFEFBABGBGBGHHHAHAGEFCCHBHCAGBCDCECADADAG,False +466,14.0,31.0,26.0,20.0,17.0,27.0,15.0,13.0,BBBBBCGFEFDFDFCCDCHHDAFADACCEAGGCGCACFFEGECEFECCACGEBAGDGHBABDBHBHFCBHFCFCAHDCDHBGFEEDEDFAFHHGBBFAFCCCFAFDFEBBABACHHBDBDBFBCCFFFFFFDBBBBBEBECEGEGDGDGEGCHEBCDFBBBDD,False +467,15.0,12.0,15.0,11.0,17.0,18.0,18.0,13.0,HAGECCBCFHEGGGGBGBDBGBAFACCFCFCBDFAAAAACEEEFECDFDCDCDHBGGGFGDABAGAFFEAEFHBEDEDEFBAHGCGCHFGFGFHHDHECEAEGFAFHHEHEBBGEHFDC,False +468,22.0,12.0,14.0,17.0,19.0,18.0,16.0,15.0,DADADADAHAGABAEHFGFGEGBHBGADHDGGACHEHCHGEFFBCGCAFGDGAEHEAAFCFGAHAHEDDFDCHFEFEDEBECABEFGBGAGCCECFCBBBBHAEBECCADEDHHHEDEDEDFFFFGDAAAFCF,False +469,18.0,26.0,29.0,20.0,29.0,19.0,16.0,15.0,CGCGCHCFCGHHCHCHCHCFAEAFFECEBFGDHDCECECHCFFDBDEDBGGEGAGEHBBCCACABEEEAEBEBACECGADBBHBDBEFEFEFCDDGCCBAHHFCBHBADAGFDBEFEFEAECBFFHABDBAEDECECEDBFBDBDBDACGEGEBADCDGBGDGACFEFBAEH,False +470,6.0,1.0,5.0,5.0,3.0,4.0,4.0,6.0,CBCAGGHDHDHDHFHFEECACADHCAFAFGEADG,False +471,8.0,12.0,3.0,4.0,7.0,8.0,8.0,2.0,GAAFBEGEFDAGEGEFEHGBCFFFFGBBBEBABABDBDBEBDHGCABACAGF,True +472,9.0,4.0,9.0,5.0,3.0,6.0,1.0,7.0,HACGCABHCEAFHBHDAAACFCBEDEDADAHFHFCFAFBCDCHC,True +473,2.0,1.0,5.0,2.0,7.0,3.0,2.0,10.0,CCHCDDGFHAEBEHHFACHHFHEHEHEHECEG,True +474,8.0,7.0,5.0,9.0,9.0,4.0,1.0,12.0,BCDHBCBADCDHHAHDHAHEDEDBHEEDHCHAFAHAHCEGDADEFEFEFABHBEB,True +475,11.0,5.0,2.0,1.0,3.0,2.0,5.0,4.0,AACDCFHAGAGAEBGBHBFEAGBGAAAHAHABE,True +476,25.0,30.0,25.0,21.0,26.0,22.0,25.0,24.0,HGHEDBDBCHEHEDEDEDEDCAHDCGCFDFGEGDGAGAGHGDGDCAAHABAFACBCBCEDEAEDEAGDFEBEBEHGHFHFCBBFGHGFEFBBBFHGBCFCEBABADHBCACGFHFACACDFABHEAEHHDGACHFBFBHBHBABGGDBABGFEFBHGHAHEBGBGCFBEBECGCACEFAGECACFDFEAECCBGHCDD,False +477,15.0,14.0,22.0,19.0,17.0,22.0,25.0,22.0,DFGGGFHHCHEHBGDEEBFBAAHGFGFGACCCGHFHBHCDEEFEFBFAFBFCGCEDEHEHEBFAFAFAFGCGCGDBCBFFCHCDDDEAEAGDEDECGDGABBHDHDFDFDGCGAHEHFHCHAACDDBHHACBGBGAGFFHCCGHHCCGDGDGCGEE,False +478,14.0,12.0,9.0,13.0,13.0,17.0,7.0,13.0,AFAFBFBDAAADFFBFBEHGFEFHAHFGDDFDHAHADABFBFHEHECCACGFBDBGAEHCDCHGHGEAECECEFECADFDBGBHBHEHDDFEFDBEAC,False +479,29.0,20.0,16.0,24.0,27.0,18.0,17.0,26.0,GEHHHAHEGBGCHCBCFGDGBFDHCCBCHFHAEFEGGDHDACEDDDCDFDFDHBAADHFHBEFEHCHCDFAFABAEGBHBABABAEHEAEAEDEAFHEDAGEBEFGCEDEFEDHBFFDFAHHDBDGDHEAEGCBDEDBAGAGAGAEAHACACAEAEBHAHGFGEBEADADBHBHFCC,False +480,11.0,14.0,7.0,9.0,18.0,15.0,6.0,9.0,FAFEGDGBBEFEDEFEFABAGEGEFFFBBCBEDABEGAAAFHFDEHHFBFDFAFCDCDEGHHCHBABCBEHEHEBEBEDEHABEFACDC,False +481,8.0,4.0,7.0,16.0,11.0,8.0,9.0,4.0,EEADADFDEAFBFGEGFGDGCHDDCDEBEGEGCFCHDAGCGDGAECFCEDDFDEABABADDDDEHFH,False +482,11.0,7.0,25.0,5.0,16.0,24.0,10.0,11.0,EAEAEACFCBCEFEGAGAGCCFFEFGBCFFHFCFAHACFCEEHCCFDFEEHBHFHAGFFEFEBDAGCGFAFEFEHECGCGCFCFHFHCCCBCDDBCCCCFDFHAECBHG,True +483,24.0,31.0,31.0,29.0,20.0,23.0,19.0,21.0,HAHEECBBBBGBECEFBFHHCHFHDBGBHEGEADAEAEBBFBCECFCACABHCHCEBFDFCFCFBFHHHEGCDCDCDHDCECGABADDDBAGAGAHEDEBBDGCBCFAFABAHCBCFHGHBDEDGBGEHCDCFCFCAHFBCDCDGDHABGFEBDBDBDGAFAGAFDDCEFABAFDDGAFEFDGCBABHCGDGDCDCAE,False +484,10.0,14.0,9.0,7.0,6.0,9.0,6.0,9.0,HCACBFBFCFCFHAHADACABDCHGHGCBFDHCBGBABFBDBFBEEHADADHBBEBADAGECEFHBGEGF,False +485,10.0,4.0,11.0,5.0,13.0,7.0,15.0,10.0,AEAEHCHCGCGCBEGEGFGBGAGFGEHAFGCHDECCAHADDFDFHFHEGEGACCBHDHAEGEGCGHBEEEGAFAC,False +486,10.0,4.0,4.0,3.0,10.0,7.0,9.0,8.0,HGHCFDHAFAECEFHFHEGECHDDACABAEEEGGAEAGAGAGAHFGFEHEFGBBB,True +487,5.0,6.0,9.0,7.0,10.0,8.0,5.0,12.0,FCFCFHFAFAFGEDCBEHHGGEHEHAGBHCHFEAEDEDBHADCBCDHDHDFBEBCCHCGEHE,False +488,11.0,11.0,11.0,8.0,15.0,8.0,13.0,12.0,CBABEBFHFGEGHCDCAGDGEABBCGGBBHEFBBABGBADEHCHCEAEAEGEFFFCGCEHDHDHECDCAFAGAGAGEHEGFDHCHEHED,False +489,22.0,25.0,26.0,26.0,18.0,25.0,28.0,23.0,BEBEBEBFFHDHDHCHDHCCGCFAGCHCHCDCGCABABAFCHEHBCBCDCGCEHAHAEGGABFDHEBECGCHCHFDADAHHEGFBHAHFDGDCCCHFFGGGGBFAFABGFEFAGGFGDBAHFEGEGEDBBEDDBHBDFDFGGCEFGFBFHGADADHCEGEGDGDFDBBCBCDGBADABAFCFAFADDDBCGAE,False +490,19.0,24.0,22.0,16.0,30.0,19.0,23.0,31.0,FGGAFEFECGHHEGEHEDEFEHAGFBFBFHAEAHAEAEACDEBBHCECACEGBBFBDBCHDHGCFEHHAHAHBEBECGGDGCHBHGFGBDFCGHGHDHBHBACACHBEAABDHEHDHFFBFHFHEBCDEDEDFDGEGAGADBCHFHABDBDCFAEAEBEBECGCGEHHCCBCHCEGEGHFCGEG,False +491,16.0,23.0,19.0,29.0,31.0,20.0,28.0,25.0,DHDBCECECAGFGBBEEEECEDEGHCDGGAFDFGFGCGCEHGHGEDFGCDFGFDDDCDEFEABDEDEBEBHBHBGGHBDBHAFABDGHCECGAEAEAGABHDHDHDHBBBGEHEFEDHBEEEGGCDEFGHGHAHAFCFGFEDCFEABHFHEBEBDHDHACBCFGAGFGHEHBGBCHFGDDADCDADFDECB,False +492,2.0,8.0,8.0,4.0,4.0,4.0,9.0,3.0,GEGFACBGAGECCHCHCBFDGHCCGCGBDBDBEBEFDFBGBG,True +493,21.0,13.0,20.0,26.0,11.0,13.0,10.0,15.0,AACGHHEEDBDBDCDCDBEBFBFEGDCEADDDFAFAEAHHHFAFADEDCHCBCAAGACDDDDDBCAGDCDBEHGHGFGABDHDHCCCCHADAEAEDHDAACAFAFBFEDGBHCCADHBGBDFCFCHCFG,False +494,4.0,3.0,5.0,3.0,3.0,7.0,4.0,3.0,AHFEBAHCHGFGFEFDADBFFCFCGCGCBEAD,False +495,0.0,4.0,1.0,1.0,4.0,0.0,2.0,1.0,BDEEBEGEGHBCB,True +496,6.0,16.0,13.0,12.0,12.0,13.0,12.0,10.0,DHFEEBAFCHCHCEFHABBCBCFGECECEGEBDCDCBBBBFAFEBEGGCGAGFHEDGBGEGCHEBDBHBHCGBHAGDFDFDFDFDHCADFDFGB,False +497,19.0,9.0,12.0,22.0,14.0,24.0,20.0,18.0,DEDAHEBAAGDBHHGABAGCHCDCACFCGCEEACBFAFAGEDDDHHHCHCGFGHBAGAFAHDDDDDGDFDFHFEEDEHFHEBFDFHBAGHGHFHFEDEDFDFDCGBFACAGAFHFEABGEGFGFGFECADAGGDGFFF,False +498,8.0,3.0,6.0,14.0,8.0,17.0,6.0,15.0,GFFDFEGGBEBHAEDGFAFEFDDDAFHCHCDCDGFHAHFHFGDHCEFHCHCFDHDHAFDFEFAFABAEHFHDHDEDH,True +499,0.0,6.0,1.0,2.0,2.0,3.0,3.0,4.0,EDECHDBGBGBHBHFGFBHBF,True +500,9.0,11.0,8.0,10.0,19.0,12.0,9.0,5.0,GCFDBACGFBFAAAAGBFAEGFGCGHEAGHDFFCEDEDEDEDECHBEGDDEAEFDFAFEBEHEHEDEBEBEBCBCBFFEGBCE,False +501,8.0,14.0,12.0,11.0,8.0,12.0,9.0,4.0,DBDBEBDBDFDAGCGFBCBCFFGCDCDEDBBBECECFBFECABDDAFAFAGEFBHAGAFCHCDCGHGHBFBEGEFCAG,False +502,5.0,5.0,5.0,5.0,9.0,6.0,4.0,8.0,FEFEBHHHAHABEBDDFDHDCAFFECEAHCBCEAEBHGHGCGFDEGE,False +503,12.0,12.0,13.0,25.0,16.0,10.0,18.0,21.0,GBGBDECCCFHHBACGDGDGDADCGCBBHDHDHDBDFDFDHEHGCEDEGEFAFHBEFFGCEHFFDDHDHGHGDAACAGBDHGHEDEDGAHCGDGDACEGAHAHDHEHEBEBCBFBEHEADDGDCAHE,False +504,10.0,15.0,9.0,13.0,14.0,7.0,8.0,9.0,CBEEFBBGBGBDBABADFBAAHEBEDEDGFCEBDBHAHBCBCBGGFDFCAGAFDGDHDHGEBEHFHECECEAHCDDEHEAEADCD,False +505,18.0,16.0,17.0,23.0,12.0,18.0,20.0,12.0,FGFABEFDHDHFHGDBDBGBGCACDDDHAHBHFFFBGCGEAEAGABHBGDGCECEDHFAGBDEAAHCEGHDEDEDFGHDDDDEFFAFGDGCFCFDFDACFCEAABGBABCBCFHGGBGEGAACCCCFCGBADADBD,False +506,22.0,16.0,25.0,22.0,25.0,11.0,27.0,18.0,AGCDCDHDBGCGAGDDCDGBGDCBCGFGHCECGHGAEFEDEAEGEFHGBCBCAAAAGGDGEHEAEDEDEBCBGFCFGDDEDECFDHDBEAEDEHGHCCCCABAFABCBAHCHGHCCDCEFAGEHAGAGHEBCHEGBHBHDHFEEEACACDEDEHGGGFBFBGDAAA,False +507,13.0,17.0,22.0,10.0,17.0,14.0,17.0,13.0,GGGCBBBEBHAEAGHDCGCDHFEAEABHCHGFGHGCCFFBCAAHEHEDCGCGCDADEHAHFDFAFCHCFCBDEEAEFHAHFCFABBDBDEGECEBGBGCGCDEEBEBFBEACBCGCGBGCFCF,False +508,17.0,21.0,24.0,12.0,17.0,20.0,19.0,17.0,ECHCHCHCGCFBGAGEBEBEBDCCFHFGCDFFHHBGBGDDDGFCFCGDGFAACACGFHDHGAAHAEBEGCCCFGFADADHBBBBABEBEBCGCHDHBGEHCACECEDDCFFAFEBACAEHEHBGBHEFAFBGHGFBCBEAEAGFFCF,False +509,4.0,0.0,5.0,5.0,1.0,0.0,3.0,4.0,GHDCDCDCDCAEHGCDHHAAAG,True +510,10.0,11.0,3.0,4.0,7.0,2.0,18.0,3.0,HAGGGGAFAGCGEGBGAEBGGEBEBDCEGDBDADEBEGAGAGBBBCGGBGAGHBHAFA,True +511,2.0,4.0,2.0,2.0,1.0,2.0,3.0,1.0,DEDFHGABBBBFAGCGC,False +512,2.0,4.0,2.0,1.0,1.0,1.0,0.0,1.0,HDBABCBCBFEA,True +513,4.0,5.0,8.0,7.0,6.0,8.0,11.0,4.0,GGHGHGDBCECECEGFHDABADEGGCGCECBFEGACFFFFBFCFHBAGGDDDD,False +514,20.0,26.0,19.0,15.0,24.0,22.0,24.0,21.0,FGFEFEFBHGHBEDHHHHEDCDEHEHCBFHGAFAFBFDCACAGGGGGGGHBBABFBFBCHGGBACGCGDFEEEEAEFFFFDECECFCBCBEAHCBADEDAGFDEDBBEBEHACAFAFABHEEDCFGHDAABEBEDGGHGHGDDFEFAHAHBGCGBGCCCABBHBAGCBHBE,False +515,22.0,23.0,26.0,33.0,16.0,30.0,25.0,23.0,GGGGCBEHCBCFEGGFADHDHCGDACCDBDGFCFHBHGAABFBAHAHDGDBDADACGCFDFGFDDHBGGGEBEBEFGFHBEFABEGCGCGHAHFHFHDBDBDCDCDCHFFFHFDFAGEGBABFEDBDCECBCDDHDBGECADEDEFFFFAFDFDECGHDFDFBCGFECHHAHAHGCBCDADAEAFCFCDHDABAHABC,False +516,17.0,13.0,13.0,12.0,15.0,20.0,10.0,20.0,FDFAGABHFHCEEAFCEGGBEBCBCBEBDHFACGHGCACACAHFHDBGFGDAEAEABFDEDHDFAFEBDHHHFHFHFHAHAHAEAFADCCFBBCEHFFFDGDGBEHHHHGCBEFEAEDFC,False +517,26.0,21.0,23.0,17.0,23.0,30.0,24.0,22.0,ABAEAEAEBGGGGGAECECEDFCEBAGHFHAEADCCGGGAGBEBEBEDCDFAFHFHGCCBHAFAFAFHFGBCDDFACGFGHDEEGEFEGBGFGADFCFCFCBAEABCDHHHCHFHFHBHAEFFFCFBECCCFFDFDBCHCADAFHBABDFDBBAHGGEAEHCGEGCDAGAHDGDFHFHFEBABEBH,False +518,7.0,13.0,9.0,12.0,7.0,6.0,7.0,5.0,CGCECBHDEBGBAFCDBDBDACEBDDGDGEGEFAFAFAHCFEHEDBCBDBDCDBBBDCHFBAGAGH,False +519,15.0,23.0,14.0,11.0,17.0,17.0,14.0,16.0,AFGEDCHBBBBBBGGECEFFBACACBCGCBHFAAABCCEEDDDHBBFBFBGEHEFDAEAFFFEHAGABAFHFBDBHHHBEBEACGCGCACDCHEEBEGGDGHGHGDDDCBGAEBEFEFAFHHHFHFB,False +520,18.0,12.0,17.0,12.0,18.0,12.0,16.0,36.0,EGEHCHDHDGDGCADAHAHFCEEBACEEEADAHHBCBEHEHEBAHCEEGCFEFAFABHBHGHDCGCGDHDHFHDHDHAHCHABCGCFBHHAHFHFHFCEHEAAHHBHGEAHHBFCCGBGFHAEAEGCHBHGDGDGAGFHHC,False +521,4.0,11.0,9.0,6.0,9.0,15.0,6.0,12.0,FFFCCHBHCFCBCBFDDGDGBFAGCFEFCHCGFBBBHCHDEDEAEBHBHGAEAFFBEGEHEHEHBHFFFFHD,False +522,17.0,10.0,12.0,14.0,22.0,13.0,17.0,18.0,EEEEDEABAGFEFEHGHBDAAABDBDAEHHAHGHGHDHAEABHHHHHBCGCFCFCDBAGACEEGCGAADGDHAFCFCEBEFDFEEACGHBEFEFEFEDCGFGHGEGDBAEGEDCHAHGDFDGC,False +523,0.0,4.0,3.0,2.0,1.0,0.0,4.0,2.0,DDEBCHCGBGCGBGBH,True +524,25.0,20.0,21.0,11.0,21.0,16.0,21.0,28.0,FGHGHEHEHBHFHFBFBDBEGDCHCGAEAFCDEAAACHEHEHBFFFFAAHCGGHGBGBHCHCDCGAGAGBHHHFDCDAEABBBCECBGGFACHCECEAFAGHFAEHGGEDEDEBHHACCCACBCHDGDGAAABAGFEBHAGBGCFEEDEAEAFBECHHAHBHB,False +525,5.0,5.0,3.0,6.0,5.0,16.0,3.0,8.0,DHFHFEFEADAGEGECBDFCBDDFHCHFAAAFEHHFBBBGDFFFFFFFHFH,True +526,1.0,0.0,1.0,1.0,2.0,0.0,4.0,6.0,HGHCHEHEGGHGDAH,True +527,14.0,26.0,15.0,11.0,16.0,18.0,25.0,17.0,BHFABADGFABCDGGECEBEFEDBDHGFCFDBDBCEFBFHAGBFEFGFHFHCHBHEHFHFHCHCEDBDBEGHGHGCBCBGDEEFCFBGBGBGBCBDBGAEAGBGAGECEAFGGGHGCCAFGGEAEDBHAGABAFAGHHCBBB,False +528,26.0,33.0,22.0,21.0,21.0,26.0,21.0,23.0,HDBFBDGDGHHEBFFCECFBABGGEBEGGAHEHABGBCCCABDFEFGFADACCGABDBFBADADBDAHAHBEGHFHBEGEBCBCBHAHABADCHBGCDEDEDHGGGGGCDBFFFFFAEECHCHCFEBEAADFBFBABDBGEEHEGEFCFCFEAEADCGFADHHFBDBAHAHACABABFBFCFHBHBHCDFGCD,False +529,19.0,28.0,16.0,26.0,16.0,17.0,19.0,17.0,ABADGCGBHDFFFGFGDGFBDGGFAFCGGFHHAAFFFEAAHAHCBCBABADDFFFABDBDBHGDACHCHGBBBBBGEDADAGCBEBHHEDBCBCBDEEGADABABADADCCBCBDFDFCBCHFEEEDEHHHGHBHDEECHGDGDBEEEDEDGDGCBBD,False +530,10.0,4.0,8.0,6.0,5.0,11.0,7.0,6.0,FFBFCDCGAGFEDCDBEGEGFCFCFCBAFDBHAHAHAGACAHAHEGDFCFADEGAFH,False +531,13.0,7.0,11.0,9.0,7.0,13.0,13.0,17.0,GCABEBFBAHHHGHGAAHCHBEBCDAFHFHBCDCDCDFGEGCHAHEHCHDFFFGFGCGAAAHGGGHFCECHHHGAAEADFBFDFDEDAGF,False +532,6.0,4.0,4.0,4.0,4.0,11.0,3.0,7.0,ABCDHFHFECEDADFGHAFCFCFBFBGADEHGBFHEHFHFAFA,False +533,14.0,30.0,24.0,27.0,22.0,23.0,21.0,29.0,CEBEDGCHDGAAABHEHGCGBFBEGDDDCDCHHDEGFHCEFBGBCCFBAEAGABEDFDCDCDHDHGFGHGCGDDFBBBBBDFDADCDGBFEFDBCFCFBDHDGFACAGFDFDEAECFBBHBHCACAHFDEHEHBDBGBHBFBEDCFEEHBHBCBCBHEFEFCHCHEAFHBHBHEHFGCAEGHGHGHGHED,False +534,7.0,14.0,11.0,10.0,12.0,6.0,11.0,7.0,ABADCBEGAGABDBHCECDBEHGCBCBCGCFCFHFHFBBCBGEGHGDGEGEDDDCDEDABAHCFEEAEFEBBGDEHBG,False +535,1.0,8.0,7.0,5.0,5.0,7.0,1.0,7.0,BHBGFHEDDFCBBBBHHHFEFHFCFCACBDBDEHEFECCCD,True +536,5.0,4.0,11.0,11.0,13.0,6.0,6.0,8.0,CDDDEBHHGHDFGCCACEDEDECEGEACACHEBFFEFEFGFGDGDHAEEEABCBHEDCDCHHDC,True +537,28.0,21.0,11.0,18.0,13.0,11.0,21.0,19.0,HGAGAGFDDHGEBDCGAAHGHEDBDFDEGAGHDECCAAAADDGBBCBHBHBHGCGCBBBFBFGABAGCHBGAFHFAACAGDFEFEGGBFHAADADFDADBBBDAEAFHGHEHEHAHAHAHAGEGDCDCHBABABECDGAEBE,False +538,3.0,5.0,4.0,4.0,5.0,2.0,1.0,6.0,HCHGHAFBEBEAEACDCHBEBFCEHBHDDD,False +539,6.0,6.0,7.0,4.0,9.0,4.0,6.0,1.0,CCAGDGDGEFBCACBCGDDBFEFCFEABABCEEEABAEGEGEH,False +540,4.0,1.0,2.0,4.0,0.0,6.0,5.0,0.0,FDDGAGFGCGAGAFFFBCDADF,True +541,9.0,14.0,13.0,6.0,8.0,6.0,10.0,5.0,CBCGEGEFEHAGEDBGEGAGHDCBCGAGAGHDFGAACBBDBDFFCFHFDACACBBEBECCCCHEACBBBBB,False +542,16.0,16.0,8.0,16.0,13.0,11.0,10.0,17.0,EAHAGFDCGCGDEHCHBAAADHDHEHEFBGBABFDAAADBDADADHDGEGCGHGBFAFEBBBBHFDFDEBEFAHEBDGFHCHCHGDFABABDHHHAEBEHEDEBCCF,False +543,21.0,26.0,17.0,27.0,29.0,23.0,26.0,18.0,GDEHHBFFAHDHDCBHBGEDBDGAGDHCEEEBFFACBBEDGFCFBEBECAFDDHBHDEFEFEFEGGCGBHFFCFEHBHEFBHBADAEAGAFBFGEGEGCGDEDEGCGCBDFDFDADABCFEBBBDBGGGFGCDCDCACFEDBGEGEGHABGEGEAAAACCHEBEDEHBABFGFHHEHADGDADADAD,False +544,22.0,22.0,21.0,19.0,23.0,23.0,21.0,20.0,CGDGDBCFDADCCGDBDHAHCHCEDFFGGGECECEAFAHCFDDEDAGCGCBDEDEAEHCHCEEECEFBFHDHGHGEGCHFEAEAEFFCFEDEABHHHGFBAGAGBDEGECECECHBHAHGBBFBGBDFDGAAFAFGBBCBGBFHEHCBDFFFHFBAAHBFBAAAFAGABDB,False +545,23.0,25.0,25.0,15.0,25.0,17.0,21.0,33.0,GAGAGEEHHHFHFHFHEHDCFHABBHBHBEBHFGBCCACACACGHBADHBECECEBABECCHCFEGHDCEBGGEBEBEFHHADCDCDFDHBHCAEEHEHFHGHGHFADCGFHCACACACBCEGDFHCABGDGEGFCDHGHAAAHBHBHBEBHBHAGABEEGEDEGFBFCGEDAGADDBBEAFCF,False +546,3.0,2.0,2.0,4.0,0.0,4.0,0.0,0.0,ADADAFCFDBBFCFD,True +547,13.0,21.0,3.0,11.0,13.0,5.0,12.0,11.0,GHBADHBHBGBEHDHEEFGHDHGFEDDDEGEAEDFAAGBBCBAGAGAEDEHBHBABABAGADBEBECEAEBBBBGBHBDFGCADBFBHG,False +548,25.0,24.0,22.0,17.0,28.0,18.0,39.0,21.0,CDCABDBHBGBGBGBCECBABGBGAHAHBFEEAEBGAGEHFACACDEGEGECHAEGEHFHFABEGHFHAHGHCDCEBEGDBFAFHGEGBGAGDBDBDBEFECHFHEBFGEGEGECAFABEBGBGHGFGEGCCCCHGFACGBHAHAECFGAEDHGHGDDDEAFADGDGDCAEGGACFBFAGEGACCEHDCDGGFG,False +549,3.0,2.0,4.0,4.0,5.0,8.0,5.0,2.0,HFEFGDGFBFDFEEEFEFGBGCCACDCAGAHFD,False +550,1.0,3.0,4.0,3.0,7.0,2.0,2.0,6.0,ECEBHBHGHBECEFDHAHECEDEDGCHF,True +551,16.0,22.0,21.0,26.0,28.0,20.0,19.0,21.0,EGEDEBEAEADDDCFCABGEFFHDBECHBBBBAHAFFCCDDDDDDHGHEFAAAAAGGBGFGBGCCHEHFBFHHDCDFFBFDGEGFCABBEBEBECDGFEECACDDBCFEDEHHDBDFHFHCHCEGGGEGEADCDCEGEFFHHGCCBCBDBEBEAEAEAGDFHCDGDHBHEHEH,False +552,4.0,5.0,6.0,11.0,3.0,11.0,11.0,5.0,GCCDFHFBDDEDECGCGDGHABDDGGGDHAHAFGFGEGFGFABDFHFCFDBDBFFC,True +553,5.0,13.0,12.0,7.0,6.0,1.0,8.0,8.0,BGDACECGDGCCCBCHCGCDBHHGBEAEAEFBCBEBDGCGDGCBABABEDCHHHHHBBDB,True +554,21.0,23.0,19.0,23.0,24.0,21.0,32.0,21.0,FAGAHAHFHGHBEEFGADABCBGBGFAHEDEFGFBHCECEHEHDGDEAAHGGGEGFFDFBCHGAGHCDGGGABDGDADHFEBHBHGGCACBCBCBGBCFADADGDEDACBGHEFDFHFHFBDDDDBHBGGGCDEFEGEGECHCBCBEBEBEFFAGBBFACECECDAEFECGAGEFDGGAADHDH,False +555,11.0,14.0,17.0,9.0,22.0,14.0,9.0,22.0,CGEEDCDADADBDBFFFHCAAEHHHEHEHAHEFFCFBGHHHFHCHDHEBGFGFBEECFCEEECGCGHEEEEADHBHAABCCACFCEDHCHCHBHBDBECGCEFFGFABBEBEGHAHBE,False +556,4.0,3.0,4.0,4.0,4.0,1.0,0.0,1.0,BABHECAAFBDCDEDEDECAC,True +557,11.0,15.0,15.0,16.0,14.0,18.0,14.0,14.0,BCBCBGDGCGEAHHEHGAFFCFHFCGAGACEBEBEBAFGCCDGBCEFDFDAEADDFDCEBFBFBEHDHEHEGEGBGHFHDDDDCCBGBCBHAHDEFFFGGCHBEAAAHFFDFDFDHC,False +558,5.0,2.0,3.0,3.0,1.0,2.0,3.0,2.0,DGDGACBFHFHAEACABACDG,False +559,29.0,26.0,17.0,17.0,20.0,26.0,24.0,23.0,DADCDFFHFAFACAFBDBACAGABFGFBHCHCFFEFEFGHGCBCAEGGGDBDBABFHFAEADDDEDEHAAGGDBHGFFFFCGAHBBGBGECEGEGEGEBEDCFFDFCCEAAFDHAEBFBFAHAGFHCCGBGBGBGAGABEDADHEBEHHAEFHAHABCBCHAEAFAEBHGHBBBAGDHHHHC,False +560,7.0,9.0,14.0,11.0,8.0,12.0,13.0,5.0,FCDCEFEFGHDAABACGCGCGDEBAHHBCCFCFGEGDBDBDBAFECDFDFEGGCAFABCFGFGEGHCDEDGDGFCBCBH,False +561,16.0,32.0,21.0,19.0,21.0,20.0,22.0,22.0,AFBGBGHGEDFAACDCDCEFEBCFCGHGHFDABABAHCCEAHBEDEDBDCCHGHEBEBEBCDEFGDGFBFEDHDHDBBBFFEGBGHEDGDFBGBACDGEBEBHBHCCGHGHGDGDGHGHBCAFHGHGFABAFAHAFCBCBFAHDHBBCBGFEBABCBCFCFEEBCFEDEAHBE,False +562,18.0,21.0,6.0,6.0,14.0,3.0,15.0,20.0,DGAAHCHBAFHBHBGCAEAEAHAEAHHHBCBGGEBDFAHAEAEBGAGAHDEGHAHBEAEGHGHBABHBHEDCGHGBEDGBGEGBGBABDBAEEHFHBCBCBHB,True +563,19.0,18.0,15.0,19.0,14.0,16.0,17.0,24.0,FAFAFABBHDCDCDFDCAABFCEDBBECDCDFFAGADBCHGGFHDHGHEECEGDADABEHHHHCHDHDFAHGFGFBDBCBFHAGABDBGBFDGGFCFCBHBHFHEHEHEGAGAHAGABAGABEECDCHHEBEDEHAGCGHDH,False +564,3.0,3.0,2.0,1.0,0.0,0.0,0.0,2.0,BABCBDAHCHA,True +565,8.0,12.0,12.0,9.0,13.0,13.0,12.0,17.0,BFBFEEHBFAFGGGCHDHDHGCDCGEHAHEEBBAEFGCGCHCFCFDBBBHCEBEHEHFGAGFFHFHABDGDFDFBHAHDHEAABCEGEGEDCHCHC,False +566,24.0,19.0,7.0,22.0,15.0,14.0,18.0,21.0,AEADAHECBGBFHGHDHAGDGHGBGBHFHBDDDHGHDHDADHDHAHDEDADGFEFGFBDBDFAAAAABEFDHHHEGBGAAEDEGEGAFAFHHBEEHCGBEADAEFFBFDFDBDBGBHAGBCBEFDHGCACBCBAAACAGE,False +567,18.0,34.0,25.0,23.0,26.0,29.0,16.0,24.0,CHFDFHBCBDBFBHEEAEABABCGAFDFDADADADBBBCBDBFCEEEFFAFDBDBGHDHBBBFFFDABFHGCABABABAHHHHDFBFEFHBCDCFCFBFEEGECFHEGEGBBDDHDEDHFHDHDFBAECCBHBEBHBCCCBDBEGHGCFCACEFAGEGEGCCFBFEHEHCGFECGFDAGFGHCCCEEEBEHAHDG,False +568,10.0,3.0,8.0,11.0,10.0,4.0,2.0,8.0,EGEDEHEHCDCEAEAEAFFEHCDDDCACHBHBDDDHAAACAEBFAGAHDCCFEDHD,True +569,16.0,11.0,9.0,12.0,15.0,17.0,17.0,12.0,EAEDEACHEAGBHHFFAGGDADADHBHAFFGDEDEHFBFCGBGFFDGHAEAFBCBEAECDADCGCGFGEGEGAGDEDBFFAFAFCBHAEAEGEGFGFDCHCGFBHBHBH,False +570,5.0,3.0,10.0,3.0,5.0,7.0,4.0,6.0,DADCHHGACACECHCFCFHDEGABAFFFFECECFGGHBCBCEH,False +571,19.0,19.0,10.0,25.0,20.0,11.0,12.0,21.0,EGEGEDDDADCBFBFCHCHGAGDHDHDADGHEDDDDHBHBHCADEEEDDHDBCEAABABFEEAEGHGHFEADDDCABHBHBHFHFEEEEFDCEEGCBCHGAEAGABFBHAHEHAFABHBFDDDBDBHAAFBBAGGCD,False +572,9.0,14.0,14.0,11.0,15.0,15.0,19.0,10.0,EFEAEGGGDGDADFHFGFBFBFGDGBBEBEADHGCBCBCGCECGFDCBCBFDFGEDBDHCAFEFEBGCHAFGFGEEHBGCGCEEEBHCHBADCCGGHAHADAGFHFE,False +573,4.0,10.0,13.0,15.0,11.0,8.0,6.0,4.0,AFCCGEEDEBEBAHAHADFBCBCBEFDGHBEGEFFBFDDBCECDCDCECEDDDDDGDCDCEBBGDHFCCGF,True +574,15.0,27.0,18.0,27.0,33.0,20.0,18.0,26.0,FACGCDEDBABABADHDBEFECGDFHHEBCBCGHHAEBHBHGDADGDGDEEEDEBCBDBEAFHFEDGDGDBCHEAADEDEAEDHCHAFDEDHDACHBHBHEHECFBABHDEEEFEGBGDDHGFBFBFCFCEBEBFFCECEGEFEDGDCBGEGHFCECEBGBHBHDHCEFFFBGBHHHEFAAHDG,False +575,16.0,17.0,13.0,14.0,16.0,19.0,22.0,14.0,HBCFCFDFEGAGAHHGEGBGDGFHEHAFBDBDCHCHGFDEDEFHFBEBHBHBEBHBDFDEDEHEGEFFACACGFHADGFADGBAEADAFBCHEFFBEBGBGBACGGFGFAABGGDGFCCACAEAECDGGGC,False +576,21.0,18.0,24.0,12.0,15.0,14.0,8.0,14.0,CDCDFBACHGHECECEDECECHHAHBGFAAHAGFEBCHAGBBBABCBADCFEGABABCGCFAFEBHAHDHECACHHFCBBBEBECFCFAFAHAFCGDFDFDBEBDCACACADBDEHEFEDGCACAC,False +577,11.0,6.0,10.0,4.0,4.0,6.0,15.0,11.0,HHGHAHGDGCEBABABGCHCGCECHCACHDFBABFHFCAHAHFFBFGGGGGGGACAGECDGAADEHG,True +578,13.0,11.0,13.0,13.0,10.0,10.0,11.0,13.0,HDHDFAHCHGEAAAACGBEEHHDEEEDADCDCACACDGDBDBCFEAGHCFCABFBFGCEFBHHHHGBGCGCGEEHAHFBFDDBDBCGDGAFAFB,False +579,16.0,20.0,17.0,10.0,16.0,13.0,17.0,18.0,HBHCDAHECCCCBHGEFCBCGFFAFACBDGDCHBHBCBEBEDGDFEHGHBHECCCEFAGAEHDGDGHBFAFAGAGBGBGBEECCAFAFDBBHFECBGHCHBHDHBHBAEEEAEHEAGAGFGFGDABA,False +580,19.0,23.0,27.0,23.0,24.0,28.0,24.0,26.0,FGFGCHDADGDHFFDCDABFFFFBCEAECEHADCDFDFABAHABDEDBAHCCCHBAAFAEGEGFGHDHGHBHGHDCFCFCADEFEHBAEEFGCDCGGGGGEHFGCGCFFHFHGHBCBDBDCCCGEBEHFBFCFEECFGHGHFHCAEBEBEGHGHFEFDCHCBCBGBDBEAAABCCEAFBHBHDHEEGABDDDED,False +581,14.0,16.0,19.0,20.0,20.0,20.0,13.0,20.0,ACAFBEAHDHEHBHCABBCHFHCEEGCHHFCDCBBEBHFABGDHFHFHBHBHBGDDDCFFHFBFGFECDCEAGAGACCCGCDCDEDEDADADFFFAFAGHCDAGHFEEGHCEEEHECECEGEFDFEEGDDDGDBBFBFBADH,False +582,13.0,15.0,13.0,20.0,21.0,19.0,19.0,16.0,EGGAGAHBFFEFEHECDCFCBGHFFGAGAGEGCGAGBFCFDDDEBEHEHCFBDDDDDDADAFAHHCFDEDBFFFFHAGCBDAFBHBEDGFGCBCBGEGEDCDCDCFHEHGHBDGEHABEGAGHFEDAHEEEEEBHB,False +583,6.0,13.0,10.0,9.0,17.0,8.0,10.0,9.0,FHFGBBBBABCCDHBEDHGFDEHCGCBEBEHCFCFBFBDBACFHGHGEEECECEDEDEHEDGCAEADFDGEAEGGGEBABEH,False +584,18.0,27.0,27.0,16.0,19.0,28.0,14.0,16.0,FHFCFAFHHBEBFBDCHBGEDBAFFCBHBCFGFGCGCEEEDEDBABGEFBGBAFAFHEGCGCDCDBHHCHAHAHGCECAHFHFDEGHBBCACABABFBFBFAFCDCDBABEBECFFGBECCCHCFAFDDDDFDBECEAEDBFCDCEFGFABABCCGEHCABGFEF,False +585,26.0,16.0,22.0,22.0,20.0,21.0,22.0,26.0,FHDHDHFCEBBDBAAAAGFGCBEDHDHGHAEAECDCBEBHCHAHGGFDAEFCFHHHEECCCDCDCDHAHABBECACADAHCDCDFBBEDAAGAFFHCEEEAFAFGFCECEFACAEAFFHEGFHCAGECFFGBGFGDBDBABAGGGGGHHHAHDDDHHHAHDGEGFGBGBFCEDGD,False +586,8.0,5.0,12.0,4.0,4.0,13.0,13.0,7.0,DFDCCCCCCFEBEBDFFAFGCGCBFDFBAAFHGHGCGAAHGFAFGFGCGAGBCHFHCGGHFHEAEG,True +587,4.0,3.0,2.0,3.0,2.0,5.0,3.0,1.0,BGGGDBDHDFCAEAFCFBFEFAA,False +588,7.0,14.0,10.0,16.0,16.0,9.0,9.0,13.0,BCDFHCGFGAEFFFDDBBHBFBHHGAEDDFDEHEGEGEHADFEEHEGEDEDEDEHHBHBDBHBDCDCDBBFBABACACEHECGHEBDGDCCCAG,False +589,41.0,28.0,27.0,20.0,22.0,14.0,25.0,23.0,EDEHHHEACAEAEGECBBHBHBEFAFEBAFHHGHAHACAGBDBEGCDEHAHADACACGEDCCCFBBBBBFAADACAGECDFHGDDBDCDCECDABAFCBEGEDFCGBGDHACABGHECBGGCDCGEFEAGCGDAAABABABDHGEAHBGAEHGBGBFCFCFEFBHGHBAAAAHABABADAGACACGCACHDHDHAFAGEG,False +590,25.0,17.0,16.0,9.0,20.0,24.0,14.0,17.0,HDFDEGEFBBECCBDBABFFAFDFCECBAGAEABGFHCACAFAFAFHEHEHECFCHEHEHECGBDBAFEBCFAFCFAGGCFCABHGABFFEGAHAGAGCHHEHFDFBEBCBEFAFAHAEFEAAHAHBHBGDGDGCEADAGEF,False +591,17.0,13.0,25.0,18.0,20.0,19.0,18.0,19.0,ADCFCHDBAEHEHEFEACAFAFDFEFECEGADHDHEBCCCCEHHGBDBDGCCFBGDDCGABAEAEDEAFAFCGCFHFEGAGDGFHCGCEHEAGCHCBDEDCFEDHCBEBFBAGEGAHCHCBCBAHACDBDCDCHFHEGFGFGDGHGFFH,False +592,4.0,14.0,3.0,5.0,17.0,15.0,9.0,5.0,HGFEEHBHFFEFHFEGBABFBGDFBBEFEDGDEDECEBEFEAEBBBBEBFAHAGFDFEFEBGCGFGBGFECE,True +593,13.0,8.0,10.0,11.0,8.0,10.0,5.0,8.0,EAEADADGFGCDDFBFHHGADABAFHHBAEABHHGBCFCFDFAFDHDCDCBFBCCCBCEEEAEAEFDAHACDG,False +594,16.0,13.0,15.0,7.0,3.0,9.0,20.0,22.0,BGBGCGHHHEHGAAFGCGBDFAFBHCHBDBCCCFDAHHBGBAAABHHHGHGBABABCCCCCDGHGHCHAHGEGDBFGFGCGAHAGFCHGGGAHAHCHFEDHDAAF,True +595,12.0,10.0,9.0,7.0,8.0,10.0,12.0,10.0,AEFDFGFGABHBHBACAHFFEECEFDFGBCAABBCDCGEBEBHHHHFBAEADGDGHGDGDCACGCACAEFHAHGGGBF,False +596,12.0,14.0,7.0,5.0,7.0,8.0,16.0,11.0,DBGBABFCGCGEGBGCHCABEEHGGGHGHFBEBABFBFBGGGGFDFCGABABAFAHHHHBEAAADDHCFEHAHBGACDGE,False +597,12.0,31.0,25.0,23.0,29.0,22.0,19.0,20.0,GBCAEDEGEDHCHGFBEGCCDCGAFBFAFEGBBDBDBDGGCEHEHFHDCDCDEDFHHBGBGCHABGCGCFHFDEBCDHDAABFBGBHDCDCEHEBFBFEFBFHEHEGEBBDBEBABCDGDBHBDFDFDACCEFBCBFHFGCEAEDFCCDCFGGEEEAEAFAFBHBEBCBCHEHCHGEEEBE,False +598,3.0,2.0,2.0,2.0,0.0,4.0,2.0,0.0,DADAGFCFCBGAFBF,True +599,18.0,18.0,17.0,19.0,19.0,25.0,24.0,26.0,EFEFADADEGEGBBHHABBHCCGAFDHDFEHHHHHHGAAADGHFHGGGGDEACHCHCFCGEGEFABEEGEHFCFDFEBGAHCHGFGFGFGFDDHEFCFEBDFEACAFHCHFBADGCGBADGDAFCHCHDDDFDFHCHBHEEEBEBGBABABABCBFFHFDGCGBGD,False +600,18.0,13.0,8.0,18.0,9.0,20.0,11.0,10.0,FAHEFAFAHDGGGGHCBEGABABFEFAAGAGAGAGAGBHBHCFFDHBHDEDEDABCFCEDEBEFADDBFFCFHFAAGDDDDDDFFFFHADFFFBBBCDADCCADHBE,False +601,28.0,16.0,18.0,22.0,25.0,31.0,31.0,28.0,DHDHCHCEGGGGGGHGHGABHGABAGDGEGBACHDHBGADFBHGAGFGDDADGEAEACHBBFFHFEGEFFAFAFGFEFAGADDFAFCFGHBFFEDBACABFHFCCCEEDFDCDAAHFHEHDDEDGHEFCAHFFBCGCGCACABAEAEHDHFHFHFCEDEDGAGAEEEEEFDAGGGHGHFHAGEBHBAEFCFBFCEHBHD,False +602,19.0,22.0,22.0,6.0,18.0,28.0,18.0,32.0,BEHEHCBFBFGAGFFFHEEGEFFGCHCHFABHHCCBFHFABBEBCACAEAFHFABHCHGBBAHEEEEAHAHBHECACAHEHEHCGBFFHFGAGCCBCBEFEGHDDGDHFHCDAHHHHDAFBFAFHFHGHGACCCACBHBGBGBCFGFHFHFGFGFAEBCGCBDEF,False +603,6.0,3.0,3.0,0.0,3.0,1.0,2.0,3.0,AAAAHHHEAEBFCEGAGCBCB,True +604,20.0,12.0,4.0,14.0,4.0,16.0,10.0,13.0,BHADGGGBAFFHAEDBAFGFCFHFHDHBHBGFFHADDEHFFBFGHAHAHABACADFFAAGADAGAGACADDEFEFDADAHBGBABDBDBDCHF,True +605,13.0,12.0,3.0,10.0,9.0,12.0,19.0,5.0,BFBFCDGDBDAGAFCHBBBDHGADCEAABAGFGFGEGEGDGFAFEGBGAGEFFGFGEDADBBGAGAGEFEBBHGHGEDDAFAH,True +606,25.0,22.0,15.0,23.0,20.0,14.0,29.0,17.0,ABABABGDEFEFEHBAAAFDDBDGDGAGEEBHFFCAHAGABACACHEGDGDFDHGGFFHFBEDECFGHCBAGDGCHBGBGCGFDADECEBEAEADAFEBEAEFCBCBCBHBABGBHAHAGAGDDEEEHBCEADGDGDHHFDGABDBDGGCGCADGGHHDHGGEGC,False +607,7.0,12.0,19.0,9.0,3.0,6.0,12.0,7.0,CHGGCADECECGBGCGCEHDAFACDBGGFABCBCBCBCBFBCGCBCBCBFHADACADHDCGGGDFCHGFCHDHDB,True +608,15.0,15.0,12.0,14.0,12.0,4.0,21.0,15.0,BGBEFEGDBCGCGHHEGCFAGEBFGHBCCEGAHACGBDBGBHAHGHGHEHEHACABADADAHACBGDAEHGHBDBDBEBAAAFCGCGDEDCDEDHDAGHGDGBGEGDC,False +609,11.0,19.0,6.0,5.0,9.0,14.0,11.0,10.0,BBBBGBFBFBABDHAHFBBAHEHFCAHGGDGDFCBCFCGAHBDBGBGFGHAHGBEEAFFFBFEFEACACEEGEAEDGFHAHBBBF,False +610,7.0,6.0,1.0,2.0,7.0,8.0,15.0,3.0,GGGGGDGFBAEAEBFHGHDFAGBEFEFGFGBHAGAGBCEAEGBGEGAFF,True +611,9.0,11.0,18.0,12.0,13.0,14.0,18.0,18.0,DABAEGBGEGEGEGFDHCGCHAHFHFCCCCHHGADFBGEHAHEHECFHEHEAGABDGEBCBFFFGDGBGACHHHDHCFCDCHHGDCHCBCDCGCBBDADGGGEDECBFFFFEF,False +612,1.0,6.0,5.0,8.0,3.0,4.0,3.0,4.0,BEBEBGBFBFDDCHBDFCHDGACHFHGDCDCDED,True +613,5.0,7.0,4.0,9.0,3.0,12.0,4.0,8.0,DEEHBFGFCHBHDHFAGDBDHDFCFEBHHHBFBABAGAGDFDCDFFFFCFDA,True +614,5.0,4.0,10.0,9.0,2.0,6.0,6.0,7.0,GCBCBCGGBFHHCFCHHDDDDCBGAEACACFDADCCAFHFHDHDEDGFG,False +615,20.0,20.0,21.0,19.0,32.0,21.0,14.0,26.0,FCCGGEHECEDEDBBECHCHCFGBEHECCCCCHCGCDCDEHAGCECEDDBEBABABEBEAAAAHAHEFAFHFEFBFBFAFGEEEAEHEBGHEHDBCBDAAEFFHCGFHHHGCEAGDBEHEFEGDFBFAHHDBCHFFBEGEGFHECEADADADBHFHAHDDFDFHEAEBDBDGH,False +616,4.0,1.0,4.0,5.0,3.0,3.0,4.0,3.0,AGAHCHBGDFDCHEDEDEFCFCDAGAG,False +617,14.0,17.0,16.0,17.0,18.0,16.0,11.0,15.0,EFEFHFABEBEGEAEBEAECBDHFEEGEGBGDHHHHHBHBHBHAFAHDBFHABDDFDHBGDECECEFEFGDABAFAFABDHFBFCGCGBEFCDCEADDDFACAHDCCGDDCBCGCFCABECGCD,False +618,29.0,30.0,26.0,14.0,18.0,25.0,13.0,17.0,HACCBHBFAFBFBFHFCBAAGAEBEFDDBDAAACACACEEDDAEFGBGFEFCABAGAGAGFGCHCAGFBBDFHAABFCFCFDHEHCFBFBHADBBBBHDDBCFABBEBFBADAEBCBHBHFHCBDDHCHGHCACAGAGDFCFEAEBECECECFCECECGHEBAFAEAGHBCF,False +619,31.0,22.0,24.0,19.0,30.0,25.0,19.0,29.0,CFHEHCGFFACEHBDEEGGACFCACAGAHAEAFDCGBACEFGAECCAGHBHBDBAEAGFBABAGACAHHHAHCHCDCDAGGGAHAEAEDGGCEHFHFHFDGBHBCEHEDEFEFEFEAADACHFBDBDBDBFBFAEHFHBHEHEGEDEDCCEBFBFCFCAHDBFEAEFEACAFADEBEHHDEGEAHBHCHDBGBCDHFGF,False +620,18.0,17.0,15.0,24.0,21.0,15.0,18.0,13.0,ECDGDBDGDGDEAEBEBCFGFGAGAGHCDEHEHBGGGFEAAFBBDFHCDCEEEEGAGAGEDFDHDHAFAFHEHDADADBDECACEDDBHFEGECADDCFHBCBCHCDDFDGBBBEAECEDEFABAHCHGDABFBFGFCBGA,False +621,0.0,2.0,1.0,1.0,4.0,1.0,0.0,1.0,FEEDEBEBHC,True +622,14.0,20.0,14.0,20.0,27.0,29.0,12.0,26.0,CDCACEHFHFHBHEFEDEBBFFFFBFECHHAHEHEDGDEEBFHFHAACEDECCCCEFEHAHBHDHFHFAFABEEEGEGEBDAHEEEEFHDDDGDEDABHBAFGFEHABFBABDBFFFHFCFHFBGCABBGBHFHFDDAHGFEFEDHCHDEBGGGBCDDDCGF,False +623,16.0,25.0,17.0,19.0,21.0,19.0,21.0,15.0,BFDFDFGBGDHBHEDCACFCEHEDEBCFDEDADBDACADDEGEGHAHBHFEBCCCAHEHEBEBAAAAGCFCFGFBEEEHBHEHGBDBDAGAEAGBDBGFEFGBCBCFGEGBGHDHGCCAADCDCBFBAGGFGEHDFBEBFBFDFCFHBGGGEB,False +624,23.0,27.0,21.0,27.0,12.0,19.0,33.0,26.0,DHAGAGFBFCCHHGGBCBFDFACGBGBGHCABACAHFHCDCDGFGFCFGFCAEGHGABABEDEDHFHFDFBGHGEGHAHBHCDAGAGAGBBAEAFGCACBFBDDHGHBHDGDGBGDAAAAEBBGBDBDCACFCHCBDBCCCBGFFHDHDHEGEDEHHDDDHBGBHDFFEBDDEEGGGGAGHCHDBAGD,False +625,17.0,22.0,27.0,7.0,24.0,19.0,26.0,18.0,GHECEGFGAGCBEEGBGHGBEBEAEFGFAFCFHGGGGEEECBFBDGGCGCEDGFBHBCBCBCAGABEGEAEABFFFBFBFHEGFGACAEFDBCBCAGAGAGFFCCBEHCCBCBDHCBEHCHCACEBFBCGDAHFCECEDACAEHHHHHDAFGHCHCEGEH,False +626,21.0,20.0,18.0,14.0,19.0,24.0,20.0,19.0,FGFGDBFGAAHHDABADDECCHFBGCEEHGHGHGAFHCHAHBCBFAFAFABBBABADDGEBBFCFCFCFCBCDCDHFAGGHGHGAGEHBFAFCHHEGEFBHDHAHAEDGAGAGEGCDEHECCCBBBAFFFEFDADBBEDEGCFBFCGAEEEEFEF,False +627,22.0,20.0,15.0,21.0,16.0,16.0,15.0,16.0,GBGEFDACFGFGHBHECCFAAAEEGBCHCBCFADHDHDBDBDFDADABAEDFBADACBCFCFEHGCEFEAEBHDHDFDEEBBHBGAGDGAEAEGGHAHDDDDFDGBBBAAAABDHGHFAFECCCECHBDBCBFEFGAGAHH,False +628,7.0,15.0,8.0,13.0,14.0,12.0,11.0,8.0,DEDBDHFHDCDCBBBCBDBFBFCGHGAGEFAFAEADBFBGBGHGDCFADBDFEFEDECEFHHCBEAGGGDEBECEABBGHGFDHEEFE,False +629,1.0,3.0,3.0,8.0,6.0,2.0,4.0,5.0,HEHDHDHDEFBGBGDDCDHBEDECGCEEFGAD,True +630,11.0,10.0,7.0,6.0,8.0,14.0,8.0,5.0,CAHAHABFCFCACFCAHAGDBCEGHFHEBDFAGAGABBBEBCFEFEFBFAFBDEDEGGDFDABFFEFGG,False +631,14.0,11.0,20.0,21.0,13.0,15.0,14.0,16.0,HCFAAHBFCFAFHFGDHFCFBBBEBEAEAEHEHGDDBHHHFHDCDEGECFHFDFDADACADHGEDADHDHDCDCGADDECEAGBBCECDGGCGCABAHFGCDCGFBHBDCDGAGCCCDCGEFEF,False +632,4.0,8.0,5.0,12.0,1.0,8.0,6.0,3.0,CAHAEDBCCFGDBDFFBFBHDDDDDADCGBGBCFAGDGFGFHDBDBF,True +633,3.0,4.0,7.0,2.0,2.0,6.0,5.0,5.0,CBCECACAFEFDAHBCGFGFBHCHDHCHGGFBFG,True +634,15.0,14.0,8.0,23.0,21.0,16.0,17.0,8.0,GDDDADADACBFGFGFAFACADAEEBEBFCGBFHFHGEDDDFCGABCBDHDHEEFHAHGEFDFEFBFAGAFEGDGDGBGDEDEBHBDCEEEEGEBCDDEAECDDDEGGGAFAEBFBGHEDAB,False +635,16.0,23.0,27.0,12.0,33.0,22.0,20.0,34.0,HEHACECAHFBGBEBHHHHFFCECEHEAEGDGDHAHBFFFFFFFGABCEFEBECECHABGCGFHEEEEEEGBCAHEHCHDFBGBCBCBHHGFBHDHCHEHEHCFCGCGEFHHHCDGDEDECBCAFEFAGHDCABHDAEACCHGHFBBHDEAGBGAFDDGCACEFEFEHEHEBEGCCEGBGBCAHBHB,False +636,18.0,21.0,19.0,22.0,14.0,15.0,21.0,26.0,GHABCDDDAGGFFEFDFHBACHDHDECGBFBFAAGECECDAFBHCDCEBGBAAAGHHEHEHEHEBAFDFCACECECEHHHCHDHAHAHCDBDGGGDHDBCCFCGHHHGDDDBEBFCFDGAFBFBDBDBGBGBABHHCHGHGDBEGAAHDCGAGBGF,False +637,7.0,11.0,15.0,9.0,7.0,9.0,10.0,13.0,DAFBFHGDGAGCDCDGHBCECFCGCDEDHDHBHBFBEGEHDADBBBBGFHHAECHGHGHBFCFAACCCFFHGACHCBCECE,False +638,23.0,18.0,27.0,21.0,18.0,14.0,17.0,30.0,DEDCHCBFEAEAEABAHGDGDADEBEHCFDGGCCCCDCBFGFCCHDHDHFBABDHEHAHFHCAFAEADHDHCHEDACCGCGCGCBAFHHHECDDDBGHHHCHBHAHECFBBGBDBFHAHGHCDGHGCGCBBBGBABFGCGAEEDFDAEHFHDHEEACAEFEACHCAAA,False +639,8.0,5.0,5.0,6.0,7.0,4.0,6.0,5.0,FGEBDBDBGHGDGCAHAHCDAGAFAFBEBEGEFDCHAEECEDACAH,False +640,25.0,30.0,19.0,18.0,18.0,25.0,21.0,28.0,DBGBFBFHFHCAFAFACGCHCHEHEGFGADHHFEAEGEGHGEAEBDADHBABDGGGGHBHDDGAEBDFCGCFFGACDHBHFHCHFAGHEDACAHBDDDAHHEBEBABACAGBDEDGHBHFHFCGCDFBFBFAHGCBDDCBAEAEFCABABACACEFHFBAEHEGBGBHBFFHBEBFBFBFHCBC,False +641,10.0,7.0,19.0,15.0,18.0,26.0,16.0,17.0,EBEBEADCFGFGAADCEFHCAEDEAEFBHEHDGDGDBHCGCFHFHCHFEFGFGCECFCGCEDAFEGDFCAEADCFEFHHHFDFGFGAGDGDFHHGACFBHDHCGFGFCHCHCHCDEECFFFFEBEBFD,False +642,17.0,19.0,31.0,20.0,20.0,27.0,31.0,22.0,EFGFHEBFAHAHFHGCFCFGFHFBFDHDAGAGBECCHCBGBFEABDEGEGFCBDDFEFADADBFEGEBBAEHEHAHAFGCGCGCBCBFGFCACHCECGCBCAGFHDBDCAFGCGCGCGCDDDCDGDGFBHGFFAHCFCFHECDGDBECCCDCEGEFBFEHHGAGCGDHAHGHEFDHAGBGBGHDECE,False +643,10.0,16.0,8.0,13.0,16.0,18.0,19.0,19.0,DBDFCEGABABHBFGAHEGFFDHCFCFBDHHACAFECHHHHGFGBEHEGEGEGFGBBDBFEFHFCEDECFAAGFGFEBAGHEHEHEGDBDFDFBEBDBDFDBGEHCAAGHGHGBGHGHD,False +644,23.0,23.0,24.0,17.0,10.0,17.0,18.0,14.0,BGGGGGEGBACCECHCHCACDBAEFEFHAHACFGGADDCDCDCDGHGCBHBAAFGFGFABBBBFBHGFAAADADCDEACDEACBHEEFCCHCHAFBCHGEGBFDFHEBBHBDBCHDBDBGFCFBDCGFGFACABBBAAAAAFDCDC,False +645,19.0,20.0,19.0,12.0,21.0,19.0,19.0,26.0,BCHEHEABABAHAHDHBEDEAEGECEBECAHDGCFEFCHHAHDHDHFBDACABGCEBHBCFHGCCCAEEDAACABBHGHGHFHBEBHDECEBDBCBFEFHHHGHGHGHFHFBDGEGACEFDFHFEFCGGGAEFDFGCGABFFCFCGBGAGFBAEA,False +646,24.0,19.0,25.0,16.0,26.0,22.0,27.0,28.0,DADGFHCDDBDHDHGGAEECHHHFCAGACFCFEDCCECEGFBFBCBGEHEACBCBGGHGAGFHCGCGEFEDAHAHFHEBBBHHAAEAECBGAAFBGBHBHAAFEEAECEGHGFCDCHHHHBDFGFGFGBEAFHFDAHAHCBCEHGHGFCDGDGCGEFABDBFBAAAHADEDEGCGHECEFEFECECG,False +647,19.0,19.0,11.0,23.0,12.0,13.0,15.0,22.0,FGFAADEGEAEADGDFHAHBHDGGGHDFBHBDDGDCDHBHBHEHECEDBDBEBHHDHEABCCGFAHGGEADAGFDAHEHDHDCDGDHHEHFFFGEGBDCACACDFDHBBBBDCGAAFAHABABACACFDFBBHB,False +648,14.0,18.0,21.0,17.0,4.0,13.0,14.0,14.0,HDCCBGAGBGFGFHCCACHCGCBCBEDEBCBDBHFCFCFGAGACBGFDFBHBADAGHCHBHFCACDFDBABAEGCHHDBDCFBECGCGBDAFFGHDBDBDADADACFDADCHHGH,False +649,18.0,10.0,20.0,21.0,15.0,23.0,20.0,19.0,CDCFFDAABAFGFDBHFHGADADAHGHGBDFCHHHCDCHAHADCDGDGDGCEFGFCECFCFCGCAAAAEAEDBDBFFHHHFECECGGEGAABHECFHDEDGHGAEADFFHGDGDGEEBDCFGEHFCGCECEDDFFFFBFBCBHHAG,False +650,2.0,8.0,12.0,4.0,7.0,2.0,3.0,2.0,BECADGCCCCCBCBCBDGGFECECDBDBHECEFABHBCEE,True +651,23.0,17.0,14.0,13.0,18.0,7.0,9.0,12.0,HGFCACACFCDEEAGBGBADADABCGDAEADGDBACFHBEDAABHBHGHCAAEBECECACEDECEGFGAAHABAEAHDHABABADEBCFCFBEEEHEBFBAEHEHDCDBGBHD,False +652,9.0,5.0,7.0,3.0,3.0,4.0,7.0,7.0,FHAHAGGGGHGCGCEHEAFAFCHDECHBABCFGBHBACDCDAABA,False +653,17.0,14.0,10.0,12.0,16.0,15.0,12.0,13.0,FFDCCCGHBHEFBAEAHDFFFHBBBBGAFABABAEADAEFCBDEEHFDACHCHDAFCFEDGBCBCBEBEGGGCHHDDAGAEAEDEDEBEHDHAHEFGFGFGHGAAEAFG,False +654,18.0,23.0,28.0,27.0,18.0,13.0,30.0,25.0,CGCBCACGBGHACACADFEBGBCAEHBDBCHAEDGDFDCCAEHDGDFDFAFBGBGEDCFBFBFDAHGCCCBGBHEHAHGGGCECEHEAGCGDGDHBBDGCECHAHDFDGEGAGDGEADHCACBGBCHAHAGBGHHCHCHGEBEAEDECHBGBGDGFGEGHCHBDDDCDHDFDHCFEHDBDBF,False +655,15.0,11.0,8.0,7.0,7.0,6.0,7.0,13.0,EFAFACBEEDCAHAHGEAEFFHBHBFBFHGAAHGHGAGDCBHHHABDBEBAGAGDDDADHBCBEACHCACACHB,False +656,23.0,17.0,14.0,15.0,23.0,23.0,21.0,14.0,DBBBEEGCGFABAGAHAHFDEEHECBHBFBEAEADGDACGFGFCFDFGFGFGBEBEDEHHCFEHAHAFAHEBABEDEFGFGBGAAECFCHCEAGDGDCBCAFHFDFDFCFEEEEECFDBGGGAAADBGBHDAGEEBHDAAAHFGCGFAFC,False +657,22.0,13.0,20.0,11.0,19.0,20.0,13.0,19.0,AAAEEECFGGCCCDBDAFHFAFCCBAAHBBBEBFBAGCGEGHCAEACDCEADBDEAFCDGECEGGAGABAHAEBHHHHHCFCFEHCHFHGHCHCFAFDFDFDHBEGEFFFFAEAECEDEDHFGABFEGCHCHAHABF,False +658,13.0,8.0,9.0,8.0,6.0,14.0,16.0,11.0,DFDAACADGHGFECCGBFFFHEAAFACAGFHCGCFAFDFBBHHFGAGABABAGEFEFGDEBFBDBGACHCHCHGDGHGHGEGDGH,False +659,24.0,22.0,11.0,20.0,12.0,19.0,20.0,10.0,ECECBBAAAFHDHDHCBGFGFACABAGGHADBEAFFDFDFDEGCGCBBBFAGABBEDGGAGFDAGHGDDAEABBGBHDGEBFBHDFGCBCBEBFDFDADADBBFEHEFEFDFHFEGDCDCDCGBGAAAAAGAFAHBGA,False +660,9.0,8.0,11.0,8.0,16.0,14.0,26.0,11.0,FEGEHCHBGBGEGHGHGEGHDEBHAFACGDGFGACHHGAFCGGFEHDFDEEGBGBGFGFGCCECFAFDFDHBGDAAHAGEGDGEGFGAGEBCCCCBEEGEFEF,False +661,21.0,16.0,26.0,12.0,16.0,24.0,13.0,16.0,AHBFGAHHBCBABABCCGBEFACECGHGFDAHHCCECFFFDFAHACACBCBGBDFEFEHEDACAEDEDEGEGDGBBBGCGAHACACEFAFDFAFBDACAFFHFCFCAGEGBFDFBFEGCFCBCFHACADDCHFHFCECEHHHCE,False +662,19.0,21.0,19.0,34.0,20.0,23.0,22.0,19.0,AFAFBGBGBABGDDADCFCECGGEAEACHDHDEFCFDFDECHHGDEDEGGFEBBBBBEFEDDFAHCBEDDBACDCDAHAHGHDCFCFDFEFEDHCHDDADBGCABDHEBBFBDCDHDEDEABDHEBFBCEAGGHFHEAGFGFGCGDGFGDGAGAGABFBFDDHDCDHHGHECDCFAF,False +663,30.0,32.0,21.0,26.0,25.0,15.0,23.0,18.0,GBDHGHGHGBGFGABAEEDBCBCAHAEEDFDADEGCCCGHDBBBEDHGGFCBBHEAACDBGAGBGFEAAAAAABADGGBGCDCFCFDFCBHAHBBBHBHGDBDEHBHBHBEAABABDDEAEDFDEBEBECEGEFAFCFCADEGCGBABABFBCEADAEGEGDCDGBFHAEAEFCDDHEHAHFDCDEDCAC,False +664,14.0,12.0,16.0,18.0,20.0,25.0,19.0,23.0,GFFDFGFDEAHBCEEHCFEEEABFGFGHGAGAGCGCFDBDBDEDEABABDBHFCFHDGAGEHEHEGDCDCFAAGAEEHFGFEDCHFHGGEHDDGBADDGHFHEHEHECFCFCDCAEFFFGFGCBHHCCFCFBFHFHEDADHHHHABB,False +665,1.0,1.0,5.0,0.0,2.0,0.0,2.0,0.0,CCCBGGAECEC,True +666,13.0,18.0,8.0,9.0,12.0,13.0,18.0,15.0,FADABCFAFAFGFGFBCBGGGFGDCDCABDHDAEHEDGDGEFFHCGEHHFHBGAGAHEGEGABFCGBGEEBEHFHBHBHBHBFBHCABBHGEEDCDBABABHGGAE,False +667,12.0,9.0,6.0,10.0,3.0,13.0,8.0,9.0,CBCHGHFADHGAGBCFDFAADDFCFHDAAAAAFCFEAAFADCDGDGHFHFHGBFBFBEBHGHGBBDFDEB,False +668,25.0,23.0,24.0,17.0,11.0,21.0,16.0,12.0,GDAFFFFHBBGCACGCECBHAEDBBFFFBCBCACACGBABEBEDDBFAHBHDAGAGBGBGAGBGAGEDBAFCCDCGAGHCDADACAEDFHACBEAACFDDBDBHBDBDFFFCFCFCFCAAAEDHFAFHCHCACHCGAGFFCEEBEBGDH,False +669,3.0,6.0,1.0,5.0,4.0,4.0,3.0,1.0,EABGBEBGBFBGDFDFDADEDBFHEAC,True +670,5.0,9.0,11.0,15.0,8.0,21.0,12.0,11.0,DFDCHCFFDHHAHACGGFBDBDCDCDAHEFFFHBDBDBEECFGDGHGBFCDADABHBHGGEGCCFFFFFDFHEBGCEFDFGFEFEHDGFGFC,False +671,9.0,14.0,11.0,13.0,12.0,14.0,11.0,23.0,HDHCHCFCFCHCFCDADADEHFHBAEGFGHCEDHFCCDEHAHFEBBBADCHHHHDHBHEDDDADHDBGBGBCBFHEBEFGBGHGFFHAHGHBAFAGBEFEBEHEGFG,False +672,3.0,4.0,0.0,0.0,2.0,6.0,4.0,2.0,HFHFAAGEGFGFABBFGFBEB,True +673,17.0,21.0,20.0,5.0,12.0,13.0,17.0,15.0,BCBDBECHCAAADCGGGGFBABABEBCBCACAGHBHDHBFEEEEAABCBCBAAHBGGCGBGHGFGAGFFCHGHGHBABFBFHCHADDFCCCECECHHEAFBFBCHHBCEGGCFAEAEGFF,False +674,14.0,34.0,17.0,24.0,19.0,23.0,30.0,24.0,BBGEGHHHEHEFABDCHCFBDAGBBBBDBFCFCFAHHEHAFGHGEGEDBDBDHCFCHCEDEDEDGCGCDDDGDGAGAGEGBHHCHADFDBBBCDDACGHGEGEHBGBGHFEFGFBBDBHBFBDGGCGCDFGCBBBDADGHFCFADGEHFCFAFGBHFHBGEAEBBBAFGGDGFEFBBHEHEBABF,False +675,22.0,22.0,20.0,24.0,22.0,17.0,36.0,34.0,CHGHGHAHAHCECDBGCADHEEGECDGBFCCHCHFGFGBBHFHFHEGFGAGCGCGDGDCBFBFEFEHEDECCHBGBDADHFHEBDBGFGBAHGHGEACGGAEAHGBDCDGDHFHBHCECBDHGGGGHBBDFDFHAAAAAHADADHGHEHAGFGDGAEDGDEEBHACFGHBHBHCGGGCAHEEAEHEFDDDGDBBBAE,False +676,5.0,3.0,7.0,7.0,6.0,1.0,5.0,6.0,EHCHEBAGEGDGDCCCCABHEGBAEDEDCDFDADAHHCHG,False +677,14.0,12.0,18.0,20.0,14.0,12.0,11.0,15.0,CCADHGFACAHGHDDDDDGFGHBADGBEBCCDDDADADABBHCFCFHBHGAGEEEEEEEGEFHCDFAFCCADBDCDCDCBBBBCHCBDAGAEHDHAHAEEHEHFFCGCDFGECFFH,False +678,20.0,18.0,16.0,16.0,18.0,22.0,18.0,25.0,DFFHFHFGFBADAGHCBCAGBCBFGFACBEFEGABBBEGHHFHFDFHEEGEBECFCEBEGGADEDEAEACHCHABEHAHAFAHAHAFBFAECECHCHGHAHBHCHFHGDCHGHEBDBDGCADEDGGFBFGDBDCFFEHDFDFDGDHCHBGAAA,False +679,13.0,13.0,11.0,11.0,12.0,13.0,13.0,10.0,DADAHACGEBDGEGEDEAACHFGEGEGFGFCFAFEBCBFEFHCCFCHCHEHAFFDBBBHGCEBGBGAAHFHGHBFDEGAGBBBBDDADADEDACFC,False +680,21.0,9.0,11.0,23.0,10.0,11.0,13.0,22.0,BHEFDAEAEGGAGBCHCBAAHAFDFGGGGBHADEDACFCFAEABHBHBAAADFFACDDDHDHCBCFHDHCHGDAHAHDDDCDADEHFFAFDEHHDHECDADAGAGBHHGHEHEHCDGDGD,False +681,29.0,26.0,19.0,24.0,29.0,20.0,27.0,23.0,AAHAECBCBAADACAFFGCEADCBGHGFEFEAEDEDBDHDEBHDHAACAHAEBCBDFFHFBFBFBFGFBEAHBCAEAGAGBEEEEEEEEDCABFGFBDHFAFAGBGHGCGEGDADHDFGBCBHBHACEBDADEDEDGGGGGGGBHBHDHCFGBBEHCCAHHFABDCGGECFBAHGDGDCEAEHECEGHDFDEDGAHA,False +682,12.0,18.0,15.0,23.0,25.0,24.0,20.0,8.0,DADHGFBFDADAEECECBFDHDBCBABAHFFFFEFEFBFBFBEDFDEAFCCHEBBGECCCCFAGBBDBGCEEDHGGEGEAEAEFDDDGDAFEGCGCGCFEDDGDFHEDGGGGGEBEDFDEDHBEBDCCEFFFEFEBABFGAGHGD,False +683,10.0,19.0,7.0,19.0,5.0,6.0,8.0,11.0,CHCGBDFEGADBBBBBEGHAFAHBGFACAGAHDBDBDADHDGDBDCCCEDDHDADADCDBBBHBFBDBDFDADEHHHBHGGEFBB,True +684,10.0,3.0,3.0,5.0,2.0,4.0,6.0,12.0,DBCHHBHEDEGAGAHFGGHFAAAGAGADBCHAHAFDFDACHHHHH,True +685,10.0,19.0,16.0,24.0,9.0,16.0,18.0,17.0,DGDFEBDHDADCDBDHFHFHAGCHCHAGEEBGBGBAFDHCBADCDHAHEEABDDFDFABBCDDADCDFDFBBGBGHECCGCGDECGDBFGGEGECHCGFFBFBDGFHBHBHBCGCGCGBDDDFHFHFHA,False +686,11.0,7.0,14.0,17.0,14.0,20.0,12.0,14.0,HDHABCEFFBEHCGCACACBHBGEGEFFFBGCECDCDEHEDEGFGFDDDDGDGAHDHDADADFFFAHAEDHFBADEDBCCGHAEEECFFEFCFHFGCGAHDFGFHFCFH,False +687,19.0,24.0,19.0,21.0,13.0,20.0,17.0,22.0,GBGCDCDHFCAHAHBFFDCAGBFBABCFFBFACBGHGHBFFGHDDADHFHFHBGGHGAFDFCGAGEDEGEADDFCBABFBABAHEDEGFGFCBCFDDADACECEBEBCHCACFEGCHBBBDDDGHHDHAHAFABDHEHEHEGEDBABCBDBHCHC,False +688,11.0,6.0,12.0,7.0,7.0,10.0,7.0,5.0,CCBGGGGFABECFADHEACFCFGFGEDFCFAFBHBCBHBDCCHCAAAAAEDDDDAFCFCEGEAEH,False +689,1.0,5.0,2.0,2.0,0.0,1.0,2.0,2.0,DHDGFGCBBBBBCHA,True +690,15.0,19.0,20.0,21.0,26.0,23.0,15.0,18.0,GBGBGEFEGECEDHDHDHDHDCGAEACGCFBFECCACGCDEDFDHDFBBBEBDHGHDCBAAAFBHADFBFHFHFHFEDDADEDEFCBBAEEGEACCHCEGACEDECECFFFFHAHEGEBABEDFBHEDEAEADFDCHFHFCGEBHCFFFGBBECGBG,False +691,16.0,20.0,16.0,13.0,21.0,17.0,19.0,17.0,EEBEDECEAEBBBBEHFBFBFDCDCBCBCAFGHGCECGGDHAHCDCFCEHDHDBBFHFGEECBGBFHDHGHEBEBEAEFBAAAAEAGGGFEFCFBABDFGFDFHAEEGHHHGDFHFGCGCGDAAACADEGBBCAHGEGH,False +692,15.0,18.0,25.0,15.0,20.0,16.0,23.0,15.0,DCAGACABGEGHGBBCAEGHHDAAAFGCBCBCGGDGCGCHCDCDAFCFGHGCGCEEEHBGGECACADEDFDFGFDBBFBCDCFCDCEEHEHFDBDBGEGFFBFBFEECHGHBAGABABEHEHGCEHBFDCCGDHEHEGBFAFAECEC,False +693,18.0,15.0,17.0,18.0,19.0,18.0,17.0,13.0,DAEAFACADHDHCFCBBBDFDEGEGEFDGBEFEBGHGHEHGGAFAFAGAEDEBHDADAEAEDEAHGHAHCECEHFHBGFAEAFBCGFDFGCACADFCGCBCBDAHFBCDEBCFCFGECDBDBGBGECECFDDHFG,False +694,7.0,11.0,9.0,10.0,9.0,4.0,5.0,10.0,CDDDBBCGFGDHDHEHBHEHEBEBEAEAFHDEGEDHBAAFHCBFEGCBCBCBAAHACCCGBHDDD,False +695,9.0,7.0,7.0,14.0,15.0,8.0,16.0,16.0,DFDCDCDEAHDDDBHHFHFCDCHCFBAEEDGAEAGGFGHAEECHGHGHEEGDGFEFEDEGBGEDDBHBHGEGFAHAEAHAHGBGHGHGDECB,False +696,24.0,23.0,24.0,22.0,20.0,19.0,26.0,26.0,ADGDAEBHCGCHCEADABGBGBFEEGFAFAFBFGDGDHHACDCHFACHCGGHGHDHCBGDHBACHBHGHGAAEBFAHGGDGHGFGDCDCGCDCAEGGGEEEEEHDFDAAAHADAFADEBBBHEHECACBEEEBABFCFCFCECFCHBHBAGABHHFHBHFCDEBCDGDFDFDCBFBCBEAGDGH,False +697,19.0,24.0,22.0,23.0,29.0,24.0,25.0,34.0,FCFEAEAHCGEDABFEFDHCHCGCGCFHABDGEGFGFGBHBCAEEHGBCBCBCGHDHFHABGHDHCCCAADDFDHDCDHFBEHEHEGFBBHHHADEEEBEBFACHHHHGHGABBBBEDCBBBEDEDFFFFFFHCHDAEFEGDGHFBDGEHHGFBDADECEDEDGFBFEGCGHHCHCHGHEFEAAGAGEGDGCAHAEAEBD,False +698,13.0,19.0,14.0,18.0,18.0,16.0,11.0,16.0,BDBFFDFDFGGHAHBHBHBHFGAGAHDHBEBDBHBFBFHCBEGEGEDCCCCBGHECDCACDBFCEDBDFDFDHDFEFHFHEHEFEBABDEHBCDDHAAADEBAGAEACGEAEFBCEGEDFCCAGE,False +699,20.0,17.0,18.0,13.0,20.0,22.0,16.0,23.0,ADHHHHFDFBFAGADBEFFFEFEGCFBDHCAEABAEAEBHFECCFDFHHHHHFHCHCHEHEAEBGHACABFCFGAGDFDFCBHGCFCBCHDEDHGHAFDFAGECECEFAGCDEGEHEAABCBGBGBGBABGEAHGEAFHFGCECADBDB,False +700,7.0,10.0,13.0,7.0,8.0,14.0,8.0,3.0,FAAEFBFCFBFBEDGHCCCCCEDEDFHECDBDGFGFADGBEFCFCGAAAHEDECACFBFBGGGFCFCBBB,False +701,16.0,27.0,21.0,29.0,23.0,22.0,14.0,18.0,ABAEADACBDBFAFDCGBDEDBBFBFADHHAABHDGABACDBDEAFCHCECHDDACAFDFDFEAEDHDFBFBFCEEBECDCDHABFBGEGFHFHGBDEDEDEDCDHDHFAGDGHGHGHBCBCBFHCEBEHCCDCBFBFBECFDGGGFCECEDHBGBCFEEDGBFBEHEDE,False +702,22.0,31.0,14.0,20.0,15.0,20.0,18.0,12.0,GHADBDAFCHAEBDBDBDFDEAAABADEDCAABBEGEGFGEGFDFBFBAEGBBCBCBEGDCDAHCHBADADGFBFBHBGBDCFGDGHCDCFCBEAGFGFHFEBECAFBFBHBHBFBEGEGEBEDAHABADABBGBCAAGDFBAGHCCFDFHF,False +703,21.0,26.0,13.0,16.0,14.0,14.0,14.0,17.0,CHABCBFGFAABAGAHAHAHACBDFHAHEHGCACDBEHDGBHCECEHFAACABHBABABECGBGAGEFCGDEFHBBFAFHFHAHEBEFEGBGBEBEDDDDDDDAHHCBCDDGEADABGBDBFGFBFBFBGEDCBB,False +704,1.0,0.0,1.0,1.0,3.0,1.0,3.0,0.0,DEECEGFGAG,True +705,7.0,6.0,9.0,6.0,4.0,3.0,8.0,5.0,AGABCBCEHFACGFHHCHEACADDDDGBGBGBCEFHBDEDACGCGCGA,False +706,6.0,5.0,9.0,7.0,4.0,10.0,8.0,4.0,BGHGEDCHCHCGCFFGDGDGCBCBAADFFAFEFGAGADFHBAFCBCEDEFCFD,False +707,10.0,10.0,4.0,9.0,12.0,8.0,9.0,7.0,EECFAEAHAHAEAEBEHFDFDAGCDHBHGGEGEGFDFDEBADDCHFDDBFGEGBGBEBEAHAGBFBABC,False +708,11.0,14.0,22.0,17.0,26.0,26.0,22.0,25.0,ADBFFHCHCHCDGFCFBHBHBAGACHDFEFHCBGECDDGEHEHDHEGEGEGECBHAECDHDCDEEFHFDFDABHGDEHEGDHDGFCCCHCHDHDHBAEEGEHEHGGGBBFEFEDEFHFCFAEHECGCAFFFCFBBCAFBCHEEGEGFFECGCGFGFGFAFAGB,False +709,20.0,25.0,16.0,17.0,13.0,14.0,18.0,22.0,CDEHBHBHAHBHBGDGEGBACAHAHGBGBGBAAAGFDEEBGBABABFGACACHGHDFDADHEFDHHECFDACABGHFHDDDAEAEDGDCDCFCBCFHBCBEBEBEBFCGCHFEGGDDBBBCEHGDACABGHGAFHHHBFAFCFHB,False +710,30.0,23.0,16.0,22.0,21.0,35.0,15.0,23.0,FAFAFAFEFEHAHAEBEFDFDBDHFCEAHHHHBEFDADHEHBCCCADEHFHFHFCGGDECGCBDBGAFAFBCDAHADBECEFHCBCBAAAFAGBFADDFDFHBGAAEABFDEDFHAGAHAGAGEGHFEFCABAFCBEBEBHFDDDFDADEEEFBFDACEGFBDBHBHBFGFBFCFGGHAHAFGFC,False +711,6.0,6.0,12.0,7.0,12.0,9.0,12.0,10.0,HGEDHDGCGCGBHBHGCFAGABCBGGEBCHCHFGDEEEHEHAHFHCGDFEFAFAFDECECDCFABCGEGFCEDE,False +712,23.0,31.0,32.0,27.0,25.0,14.0,31.0,14.0,CGABCFCEHDFDHEHBDBDECCFBDGHGAGBGCHCBAEHEHDFDBDCEFGCGCFBAGGGEFEABFBGEAAAAHAGACACECACBGDGDBHBCFGHGBCAAAFBDDDDDDFGFCECBBEEGDADCBEAEAFDGEGCCBCBCBDGCECGCGCGCECECBFBDBABDBDHDCEHEBECGAABDBGGGDEEGEBBAHGGDH,False +713,4.0,5.0,5.0,9.0,4.0,5.0,6.0,6.0,BEFEACAHDHDHGHBDCHCDEDFDGDBEFGDGDFAFBBGACHCG,False +714,18.0,19.0,22.0,14.0,25.0,27.0,18.0,19.0,GEHFCECFCAEFBFAHBCCEBFFEFECDADEDEAEFEBECECGHGAAADAGHBFGFAFHDEABBDGDEHEFEFDBCHEGCCEFBFEHHHHGHGCAFAFHFHFGEHEHCGDFEAEAGFFBADAFFCFABGBABFBCBGBGCDCDHFHCECECDHDBGBCBCGG,False +715,17.0,8.0,11.0,12.0,13.0,12.0,12.0,14.0,BAGDHBHDHABAEGHFDADFECDCGCGADHDHDHABCBHGAAFBFBEHEAFCFAGHEBCDFDFDCHCHCADAEHEGEAEGCGCFEHAGGFAFEFEAEAG,False +716,16.0,17.0,24.0,24.0,21.0,17.0,16.0,24.0,FCBCBHBCBCECDCDAFFHHHCHDBEFABAEDEDEDECFDGGGAEFEFEHCADAFACEEECFCGAEDEDGHGDGAGFBHDHFHCCGEGBDHGEBHHHEHACAEGFDFDHCECBADECHHHBBBFBFBDADCCFCDCBCDEDHHCGDDAAAHBHGHGDGF,False +717,30.0,23.0,30.0,24.0,12.0,21.0,21.0,16.0,ECEDACAHEHCACECDCGCBHAGDFACBCBAFGFGBACCCCACFGEGFHHAHABGBEFFBFDFCGABCDCBBBBBAADADGDFDFHFDCDCHFBFAAGAGAGAGFCCCHABGDGDBDCDEBHDCDCDBGFFHHGBEAAHAHDFDEDAHAGDCDBHAFGGGBABDFCACACBCFEEAE,False +718,8.0,9.0,11.0,13.0,10.0,18.0,7.0,15.0,BHBGDHDHDEAEFFAGAGABHFFFADHDHDGAFCDCAHBDECFAHDHCCBGHFCECEHEFDBDCDGEGDBHBECFCFCFHBEFFFFFHFHE,False +719,12.0,23.0,32.0,23.0,25.0,25.0,24.0,32.0,ACHDECHBHFHGHGHDADAGHCCEBEBCCGHFFGFCBEGCCDDDBGFDHDHDHGFGBCFCGCDCDCDCFGEDBDBEGGCFEFEHEBEHECBFDCDGBGEGBGEGCFEEECGFGADCFEAEADBBCECEHEBEDFHFCFCAABGHHHHHFAFABCCHCFCAHEHFBFBFHCGFBDGDEBHBHCECGDBAFHHHHHDH,False +720,9.0,6.0,1.0,2.0,6.0,3.0,3.0,2.0,AAABABDBGEHAGABCBGFHEAEDEAEFEFBA,True +721,4.0,4.0,5.0,4.0,1.0,4.0,3.0,0.0,BGBCACGCDDFDFABACECBFAFDG,True +722,16.0,8.0,13.0,19.0,18.0,17.0,9.0,17.0,DFEFCHCGADHDEDAHEDEBFHFEFEAEDEDHAHADCBAFACAHEHDCGCGCDCDHDFECEBEDEDEFGGABFBFGCACFDFAFBDGFHCADHEHEGDAEAHHHBHFHFADCFEBGA,False +723,20.0,21.0,15.0,7.0,15.0,20.0,22.0,15.0,AFCDCFCFGFGAGBCACBHAAFGFBBEEAEGHDEDBHBHEHBCGEGFACEGHGHGCGEGECAFFGEGEGEGBBFAFDCBCFCFADADBHEAEHGBGHGBAFAHCBADFBHBCBFAFHBABABAFABHFGFGEHCG,False +724,22.0,23.0,14.0,13.0,20.0,26.0,11.0,21.0,DEBABADADEGBGBEBHBCCAAEAFFDAAAAFEFAFGFCFCBHBCFFFCFBFDFEHHDHCHCFDEDHBHBGAACEFAHHFABAEEEEGBCHCECACGDHAFDFHFHFEFHAGGGFCHBBDBHBEBFBFHHEHBBBABEEFGFEDGDAHAE,False +725,21.0,25.0,25.0,29.0,21.0,32.0,25.0,20.0,FGGGCGEGDFAHHHCCCGAEABFBEBDBDHDCDEDAFGDGAEFCFCEAEADABCBGGGGGCDCDCFFFEHACBCBCGCFCFDBDFCFAHBDDFDFBEHEADCDFHEHFFEGGDGFHEGEBBBDHEAEAGAGAHBHAAGAHAHDDCBCFFFHFEDGDHDBFBEAHBFBEDFCHGFGDCFEGCHCFBFDEDFDABBFBCB,False +726,16.0,20.0,16.0,17.0,10.0,18.0,13.0,17.0,BBBBGCACACBFBABFBCDHGBCHCBADABFCFCFGAHEGBGEEEFDGDFAGAGCBCEFHFHGHFHAHFDFCHAHAGEBDBDGDCDCHFHBDDADCBFADEEEHHDGFGFHADEDHFHCBCBABADF,False +727,10.0,29.0,22.0,26.0,22.0,17.0,21.0,19.0,BCBCBCBDAFHFCECDCDCBHECFCGAGDGBHFDGDGBGBEDEDEDBCBAFAGHBHDHAADBDCGFGHDBDEGEFBBBCBEBEHECDHEGDADCDHDBBGCEHFGCAEAEBEBFBHADCECFCFEDGHGHBHFHGHBCFGBCEFDHGBGFGEBEHEFFDDBDECGD,False +728,11.0,13.0,13.0,11.0,13.0,20.0,15.0,18.0,EFFFEBCDCHCAAAADFHFHGAFDFHFCFBEBGCGAFBCACAHAHEDBBGEDEDCDGBGFGFGCHCFFDHEBBCGGGGGDFHAHDHBFFCHHDHEHEFBHBHECAGEGEFEFBH,False +729,26.0,25.0,13.0,24.0,26.0,16.0,21.0,19.0,DBDFABGGFGHEHAAAAABFBFBGBDBABAGEGCGFEEGEBEDHAEDCHABCDEFAFAGDHHAHADAFAFGBGAGHBDGCHHHBFFEAEDBDBEHDBBEDDHDHDCBCBEHCACDHFCGAGEGDDBEBEBEAGAEADABAFFFFEHGCGCEEEEBEGDHDGECEABHDCD,False +730,16.0,17.0,13.0,13.0,6.0,15.0,8.0,16.0,CCHDADACCDBABEBHDFBEAGBGFCECHBAAEAEDEGCHCHAFBHGHDBDADAFBDBGBHCHCAGAGHHCDCFFDFBFBADFBFBFHAAADBFCFGFBFHHHH,False +731,16.0,23.0,24.0,23.0,24.0,17.0,32.0,25.0,FFFFFFFDDEDGGHGHGHGFDHBCACGEGEBEBECFFBFBDECCDEHCFGEACHDHDHCFDHEGABHEGBGEAEHBAGCGHGHEEEDEDHFCGDGBAHAGAGDGBACCEAGAGAGAHFBCHCGCDCHCHBDBGBEBGCDFDBCBHEHEHGCGHBCBCGCAADDDGHGBDEDEGBBDFEAEGBCH,False +732,2.0,3.0,2.0,0.0,1.0,3.0,2.0,1.0,FCFGFHCBGBAEAB,True +733,6.0,2.0,3.0,2.0,1.0,4.0,1.0,4.0,BFFCHCHCHAAFADBGFDAHAEA,True +734,5.0,4.0,6.0,8.0,4.0,8.0,3.0,7.0,DGHGDEDEFAFBFBDDEAADFDHCHFAFBDGHHHHCCCCFCFBEA,False +735,11.0,7.0,8.0,6.0,4.0,4.0,8.0,5.0,CHCACAGAEDFDCBHDHFHBCDDHAFGGGCACAGAGBBBGBEBDFAAGAECEA,False +736,20.0,16.0,16.0,26.0,10.0,23.0,15.0,12.0,BDBHCCEBDBACHCDFGFCADHDFDHAECDAGAGCFEFCFEDDDDDDDCFHHADFDABEGGGAGAGADABAFCFAFDBEBEGACADDDHAHBECHDGBGBDDEGEGDBFCFHBADGHGHFFFBFAFAFCFCFBFCFBA,False +737,23.0,11.0,24.0,14.0,10.0,9.0,22.0,11.0,FHADCDEAAAABDBHAFADADFCGGGHGAEAHCGDDCDCDHAHCGGGGCACFCBCBCGCHAAFAHEBADAECGCGCGDGECEDGBFCDBAGACFHAEGCGEGBGCECHGGFHFABABABCCDCE,True +738,26.0,23.0,28.0,29.0,22.0,16.0,18.0,26.0,EHDFFHFHEAFFBBEHDBBBDBDCGEGEGCBCDGHAHDEDEDFAFGCCCACBDAGAEFHFHADAFHCDCDBDHAAAAAHCHCHFHFEFHCHFBAEDHCBCBCBEBDADGDAHAGACACBHEDDDEHCHBDECCGBGBHDCDHDBGCCBGDGCHHGFBAEGEAFACACBCEEEEHEGCGAADAEBGDDD,False +739,8.0,2.0,10.0,6.0,9.0,6.0,10.0,6.0,CGBDCDCHHEEAEACAEEGFHFDDDDFGFEAHCCCCCBFGAGAGEFAGAGHCEGEGH,False +740,11.0,8.0,17.0,13.0,9.0,9.0,18.0,8.0,BGAGBECGDGHFHBHBGDGDGCCCCCCFCFDFAFHBDADGDGBBCACAFEDGDHCECHAEEEBDCGGAGFGCGDAAEDEACHEHCCFGAGDGF,False +741,4.0,2.0,8.0,8.0,5.0,1.0,3.0,4.0,CECEAEHCCADDHDHGGEBHBECFCDDDDCDAGAC,True +742,2.0,9.0,1.0,2.0,5.0,5.0,1.0,4.0,CBHEDBAFFDBABEBEBHFHBHBFBGEFE,True +743,18.0,19.0,21.0,21.0,22.0,11.0,26.0,21.0,EAACDDDHDGEGBHHHHEBEBABHEHBFGCGDGEGCDCDGGCGHFFDFBBGACADADHHADCDGDGBCCCBEDECAGHGHBFCFEDEDEGGCBEFEBEBEHADBHBGGGADADFGFDAEAGBBHGDBHGHCHCACACAEFEGHCECEAFHCHBGEGECA,False +744,31.0,23.0,20.0,24.0,21.0,22.0,28.0,21.0,DADEBEBEDADABCBFGGGGGHGHAFFGBGBGCGDGFGHBCCFDEHEADABAGGBGFCFCAGAHHEDBHBHFFEHAGAGBCDFAEBHDDDDEHHACFBHDGDGACFFBDBAAADAHAHCHCEGAHAGEEEEEBHFFGADABABEBEBCDCBHFHFAADFCGCGBAADDDFCCCHFEFECEAGACAGDGFE,False +745,5.0,11.0,15.0,7.0,10.0,9.0,7.0,16.0,EFHFBCACFCEHBCBABABCECFHHHHFEFHCHCFCBHHGGEGEDDDHAFGEGCBDDDHEEAFBBCHCHEHGHBCBCDCG,False +746,1.0,0.0,6.0,5.0,2.0,2.0,2.0,0.0,GDCDCACECEDFDGCCFD,True +747,14.0,8.0,8.0,12.0,14.0,15.0,12.0,12.0,HCHDFEEGCBCDCAEEEBEFEFCABABFBFDEGFAHEHAHCHGGFCFDEDAHCHDFDGDGABHEAAFAFHFEEGAGDDFBHBHGDGEGAGAFAFD,False +748,23.0,22.0,15.0,27.0,27.0,24.0,31.0,19.0,CFEFAHGBGDEAEBEAEBHBDDGBFAHCGFHFHGEGFAFADBEFHBEBCCFCGEGADBBGGCGBGHHBEGEGABBEEEAHAGEGFGAGFCCBFAGBGFGFGFADDBDBGBFEFGFAAAABHCDDDDDDFDFHFHBGDEAEDDDEDEGEDEDECHDHCFAGAHAEAGADFGHEHDHCCGEGEDBDFCHC,False +749,18.0,23.0,17.0,19.0,17.0,23.0,21.0,21.0,EAADEDBDBFBEECFCDEGFDFHBDAFFBCCCGCHCHAFAFAGGHGECECEBEGAGDGDHEFEHCBAADAFBFBHBABGBGCFCDHFBDEDECFGFBCHHDBBCHDGDFFBFBGDGBHHAHABADADEEGHGHBHFFFFEFGCGCDEHHGHGAAAGBBH,False +750,26.0,15.0,24.0,31.0,22.0,18.0,27.0,36.0,HFCEEEDBCEHFDCDCDGDAHEDGBCCDCGHDEECFHFAFADHFCGEEAEHEHECGABAHFBFBFDACBDBDCDHDHGFBFACAHAHABAHHHCDGHGHGHAABFHFGGHADDDDDADCDEDGDEAGGGGAGBGACCHBHBFDDEEHEDDHCHCHCHGFGAHHHBHFGCGHEEDEDFBAGHGHCECGCAHAGFEADAGA,False +751,2.0,2.0,6.0,6.0,5.0,4.0,2.0,6.0,DCHAHGHCHCEBEGDFCHCDCFEFEDEFHADBD,True +752,12.0,16.0,4.0,9.0,13.0,13.0,11.0,4.0,EBEBDBDBFAHAHADAGBCBFHEEAFAEEBEFGFEFAAAGGGBAFCFCFDGEBBBBBBGAFEEDDDGAGFGCEFEGBDDFHB,False +753,20.0,22.0,13.0,25.0,23.0,25.0,27.0,11.0,DBDAFFDEDEDEFEFDBCFFHDDEEEBEFDFEFEGBGCHCEBEHEHAABAGGGDEAFDFBGGGDFAFAFACHEEBHACBFECCGGGGGGFDFAFCGEGEFHBDBACAHAEFDBDFGABFBEGCGCDHDHDGDBDBDGCFBGCAHGDGBBFAFABEGEGABADADGB,False +754,13.0,24.0,24.0,21.0,25.0,16.0,20.0,11.0,BHBDGCGFGFGFGHGHBFGCEEFEFBAHEHEHEBCDEDEDBBCBCEFECGCDBACAGDGDBBHCCGDAAEAHCEFECABABDGDGCBEDHGFEDEDBGGCACDDBEBCBDFGGGEEHECECEFDFDBBBDCHAFDCBCBCGCFFACAEAEDBFE,False +755,21.0,23.0,12.0,20.0,22.0,23.0,13.0,24.0,FBFBCBFBFECEBHBHDHBBBFBACGBGBDAGFDACHHGCGHFDBHEEEFEAEBEBFGAGAGEDDFDFEFBCAFDFEAEAEDFDBDHECDCFCEAHAFEEHAHGHGHCBDAEGHBDDDBDEHGBAHAFCHGBFHFHEHEADHFHFHFDEBCAAAAHAD,False +756,9.0,16.0,8.0,17.0,8.0,7.0,7.0,4.0,EFEFGFGCCBABHBDDDDGDABBGBFBFEACDBDEDHCGEGBCBCBFDDDEAFABADAHEBADHDCCEDGDBBBAD,False +757,15.0,20.0,18.0,27.0,18.0,16.0,16.0,19.0,GHFBGBCEEAHDBDAHAHEBFFDDDDBFBEEAGBDHDBEGHAHADDEDCFCFBHAHBHDDGDGDECECGHGFGDADEFCFCFDADBGEEBCDEDGABABHBHBHCDCECECEGACCEABFBFBCCHABGHFHFACDDDDDGHECGFGFH,False +758,24.0,10.0,20.0,10.0,13.0,18.0,25.0,18.0,HEHAHAFAHCGCGCHEBGCGHGHGFGCGEABGHGFGHCHEAACABAHACFEAGCECBGGGGGACDFHFAFDFDFDFBEEAEAECFCAADAGFCHHECFHGAGHGEAHFGCCDBDBGACAGADABBDBDCFAFHGEFCF,False +759,5.0,2.0,3.0,3.0,1.0,2.0,7.0,3.0,CFAGGHGHGHBDGDGACEDACAGABF,True +760,23.0,15.0,19.0,10.0,31.0,25.0,21.0,16.0,FGFGHGDGBHACAFAFEFEGEBFGFGFECEDBFEFEHHCFAEACFBBBAFEDCGCEAECFCBBHEGEDEAEFBFGFGADCCCBHAAEEBABAHAHACECFHFEDEABFEDEAEBECACECGFGFEAGAFEFACHGDGAEAEGHHHHGDCBEDEHFHGGCG,False +761,4.0,5.0,6.0,6.0,5.0,5.0,6.0,6.0,EFBFBFGDHCHFEFGGBDAGACHCHDHBAAECCBCDEDEDGHG,False +762,5.0,7.0,14.0,5.0,9.0,9.0,6.0,9.0,EGEFHBHFGFHCEDEBEFACAEAECHCHCHCHBGCFDFCCACBCDHDFGABHBCECDGGEFCFB,False +763,7.0,10.0,9.0,14.0,6.0,13.0,15.0,4.0,FHBHAHAFAEDCDEAEHFDDGFBFBFDGGFGBGBCBFDGDBCGEGECAGAGDGDFDCDCDFGCGEBDGFBACFBFDCG,False +764,18.0,17.0,21.0,10.0,17.0,19.0,30.0,14.0,GFCBGAFBBEFFCGHGEADAHFHEAEAHAHFGGGEGECCFAGAGFFCACBFAFAFGGGAEHGHFHBHCACHFAFDEDHGEGDFBCGCAHGCEBEHCBGBDDCAGBDAGECECACBCBCGGGBBBBBECFCFEFHGDGDGDGEGEGC,False +765,16.0,9.0,24.0,14.0,21.0,12.0,17.0,12.0,FCCCCEGDGDFBEGCBCDDDDCHFGACDHECCCEEAHGHGCCCFEAAADAHGEBEFDDDCDCEAGCGDHEAEAGADAGEFCFCFGFGEAFHEECECEGHGBFCECEBFBCAEBGBGHAHAHAHBE,False +766,2.0,5.0,3.0,5.0,5.0,3.0,5.0,14.0,GCCBCDHEEEFHHEBEHGHBHDHDHAHFGAHDGDGHHHHBFB,True +767,25.0,19.0,25.0,19.0,30.0,21.0,34.0,24.0,AABAGCCCGCDFDAEECGCHBHGHGHDAGCGDFDCEGEBAGFEEEHHAGAGAGFECEHGCECEHFHABEEEBEFEBEFEBCGGGDGABEDEDADGFGFCHHHHDDFBFBAEAEAHGFCFAAAAABAFHECGCDCGFADDBHBGCEHFBBGDHFAFHBHCHFHAGGGGGGAGCGEDEBEDECHFHGBDEDBFGCCCCE,False +768,25.0,18.0,18.0,14.0,17.0,14.0,28.0,21.0,DBBECABABAFFCHGBFEAEHGGEEEHGHGAGADAHGCCFDFDGAFCECECDBBBFBDHHGHEHBHAHGCGFGHHCCFAEAECGAGFHHCEGGGCDCEHEHEDGDHDAGABACCBCBGFFBBHBABADAGGGGHGAGAGAECFBAGAFADAEHDD,False +769,1.0,3.0,1.0,7.0,6.0,6.0,6.0,3.0,EFGFHFCEBGHFBDEDEHEAFDDGDGDGDGBEF,True +770,10.0,20.0,19.0,21.0,15.0,21.0,16.0,16.0,CDHDGGGCGEGECDCDCDABFBDBFBFDFHFHDDBEAEHBGBGCDBGBCHHDGFGCHDHCGCAAHABAFHHBDEFEFCFDFCFCFAHEFBFBGHGDDDCBEGGFEBEAEBDBHCHAEFCDCBFEFEBHCGCBFDFDEA,False +771,4.0,6.0,5.0,4.0,2.0,2.0,2.0,5.0,DBACDGDBBHBHCFDECECACAHAHGBFBH,False +772,20.0,21.0,27.0,26.0,23.0,24.0,13.0,18.0,HHGDAACADHDEDCABDHDFCFDBCFCABDCCCCFFFDFBCBHBGEGHGADACFDGAADDDDDECEHEHDFEBEFCFHFAFCFCFAFCHHHCEBEBEGECECFCHEFDCGBAFADAEAEDEDEFEHEGDAAEBCAEABBFBFBEADGCHDBGBDCDFGGBCBCBEHGHCHBF,False +773,23.0,11.0,12.0,12.0,15.0,10.0,15.0,14.0,HHBEBEDEBGBDFCECGCGEGCHDHGHGBCHAGAGAFAFAHAEEEAEAGBGEGCGAACABBHDABFDFAHADGHFBCDDHAAEAEAEAEACDFDEAAAHFDCCGCHHGDBFF,False +774,17.0,24.0,28.0,15.0,15.0,16.0,18.0,18.0,EFEFEBGCDADCEHBHBHBFBECECBFBFCGCEDEDCCFCGCGFGFACCDFHAHGHBHCHEHECCCGGFCHCADBBBGHHEGCCCGCBHGEGBBBAADCDCDCDADADABFHFAGBDBAHGBBABFEFGBEAHBGCCHFHGDABACAFDEA,False +775,3.0,0.0,2.0,1.0,0.0,2.0,2.0,3.0,AGHGHFDFCHCAA,True +776,17.0,9.0,11.0,6.0,12.0,12.0,17.0,14.0,GCGDABAFGFGCCECFABAEAEBGADHHEHAAAEDEAEABDFCGBADAEHGHFFFGAGFCFDBHBFGHHCGAGHGEGHBHCECEAEAGFCFCBHGHGH,False +777,4.0,6.0,1.0,5.0,7.0,2.0,6.0,4.0,HEFEAEAEDBBGDCDHDFEBAAHEHEDGBBBGGGG,True +778,6.0,7.0,4.0,4.0,5.0,13.0,4.0,5.0,HEHEAFGFAFAFBGBAFFFDEDECBCFGDBEHFAFBFDFHFHGBACCB,False +779,9.0,7.0,5.0,6.0,9.0,8.0,7.0,9.0,DGBEBEDHAFAFHFHFCFCEDEGEDEDGHAFBHBAGAFBCBHFAGADAECCBGEGHHEHA,False +780,19.0,21.0,16.0,16.0,23.0,19.0,26.0,22.0,FFCAGEGEGAHBBEBEGCDFEFCFGHHDHDHDBEFFAGEGAGAGAHEHFAEDBACCCEDGBEACFCFEDEABABABFHFBGBGAGEHHACBCGCHCHGHEABACDBDHEGFGEADHFBDCDCEBBAGHGHEHEHGHDHDGDGFHABECEBDGGFGBGBEFFF,False +781,15.0,24.0,23.0,18.0,23.0,14.0,17.0,21.0,FEAGCCBABABAFAHCDGHFCAEGBGBGHHBBCBFBABAEDEDADHFECGDGAHEBEBECCGCHCHEBCFEDDDCGCGDGDHEFGGCHCBEFECAHDEDFDEHEGEFBBHGGCECECFBDBDBAHAHEHDHECFBFDCECABABHBGBCHFHDHE,False +782,14.0,24.0,23.0,18.0,18.0,17.0,19.0,17.0,GAECGCBBAGAGAGFEEDDFBEEEBBGGEECCCCBEGEGFGDGCHCHCHEADBDBHBHFGADBFGDHHGAGADDDDDCBCDHFBFHDAGFHFHFHCBCFEHHHBFCFHFCGCBCAGFEBDFCECHCACBDBCEAGDBDBEBEBEBABAFC,False +783,17.0,21.0,14.0,26.0,20.0,11.0,14.0,15.0,CHAHEHDHGCCADABAEDBDBFAEABGDDCGADADBBAFCEGDBEBDHGEGFHEHEHEFCFDGHADADBDBDCDCGBABDECEDEDFDCDCDADEDBDHGBGBECDHEHFFBAEAEBEBGHGEBCGGBEFHBHCFAFA,False +784,9.0,13.0,21.0,19.0,11.0,19.0,13.0,15.0,ADHDFGEBBCCDCDCFHAGDBCBCECEAGAHCDEAHBHEFEAHHGDCHCHDHDHFBEADFCGCHDHAFBGBGBEFDFGFECACFEFGFDCDEBGBGCFBFCDGDGCFDFHFHFCFCDCDB,False +785,3.0,4.0,10.0,4.0,5.0,8.0,5.0,7.0,FCFCGCGEAAGFCECECHFFDHCACGCGEBHFEFHBHDFDBDBHHC,False +786,13.0,15.0,20.0,21.0,12.0,14.0,14.0,18.0,BFDGDGDADECHCHCEDGDBDGHCHDGCABEEFEFGGDDBDHDHDGCCEBDFDFBHBHBHFHFAECEBAAAFAEAHBHGHDFEFBHBABECCCCCDEGHGBFFGHCDCBGDCCCFHDCACAFGHADA,False +787,12.0,21.0,22.0,19.0,22.0,24.0,29.0,14.0,CGCGEECEGGBEAGCFFFCDCEEACFBFBGBGDGDHDHCBCGADEHGHBFGFGFDFDBGEGEBFCFCFCFABDBCAFFGDGBFHCHEECDFDFCBEBFHGCGEGAGAFDFCEGEGEAAHHHBGCGCGAGDGDBDFGEDBDFDBCHADEEGEHEHABBFEHBCB,False +788,17.0,13.0,19.0,20.0,16.0,16.0,19.0,15.0,BDCEGHGDAFFHFHDADAHEEEECFCGDHBHGGGAGAEFGBCADGCCCCCCGCDCBEFEFDFECADABAFEBGBGAADGEGHADABHFHFCEDHDGGCDCDFDADGHCFBBCBCEHBHFHDEDEDEGHGAAAFBF,False +789,28.0,17.0,13.0,32.0,28.0,13.0,27.0,17.0,AEADADBGBAFAEADGBAAGDDEGEBEFCFCFHFHAEGEHDHAADEDHDCFCBAEGEGDGCGAGBGBGBFDDDEDGBGBGBDDGGADCDBGAEAGDBCADEDHBABAECHCECAFEHAFACDCDGEHEHFBEHDDDDFEAABDHGHGHDAGECEGEGDHEAEGEGEAFHDHDFAE,False +790,20.0,14.0,14.0,14.0,17.0,15.0,16.0,18.0,FCFDDDHCHCEGHADCBGFEFCFEEEEBEADABHBDEFCABABAGAGEHHBHBDAECGDEAAAFAEADBHCGGBGBGBEFEFEFABAGFHHGACDBDHHGFDACEHDHGHFCFDHCHCHCEFAGAGAG,False +791,18.0,17.0,18.0,19.0,20.0,20.0,6.0,18.0,FHFHFDEAADAFBBACGHDCDFAGGFEFADEDBFBFECEAFAFACCCEFHBHFHBBACHFDGDCDHDHGBAHCDCBHBEEEEAECBABCBCEDHDFDEDEDEAEADACAHFHFHEDCCABEHEBEHCFBFGFBDHC,False +792,14.0,17.0,13.0,12.0,11.0,16.0,16.0,11.0,DDBDBDAFBDBFAFAGBDEGCCECHCHCGFABGBCFEFECHFBABAEECBDHDGDGHGHGFCFHEAEGDHBCBEFHBGAGACAHAFGFGFDEABFBABGFGFGBHCAEDC,False +793,9.0,19.0,17.0,11.0,13.0,16.0,16.0,13.0,DCGHBFFCGEEBEGGAGFDEEBFGHCHCDFDBCBCFCFCGCGBBBCBCBFHFGCAEABHBABGBDBDFDHAHFGFHBBBGHGHECFDECEGHGHDAAGDBCECDAEAEFEFCFH,False +794,18.0,14.0,23.0,18.0,18.0,15.0,28.0,20.0,GBGBGFGAEFECEBGBECECFGDEDGFCFGGHCHCFGDAHHCHCFCFCGCGCEAHAEABACDBDBAGGCGHAHBDFDHEHEGAGEGEHHDCDGFHBHGHFADECACAEABFCAHGHGBDCDFDFBAGACDGGCDBGGADHDBFHEHEAEGDCEC,False +795,2.0,6.0,5.0,6.0,3.0,1.0,4.0,1.0,GDGECBCHDEDECBBFBCBABDGDGACD,True +796,20.0,15.0,22.0,19.0,22.0,17.0,35.0,28.0,EHGHCDCDAEBCBFBACHCGEFEFEFDFHGHDCGAHDCGCDCACBGEEHEHGGGEHEFEGGAAAAHAFFECCAGHGHGHBACACDCFEAGGGGGGGCGAFCBEHHGDGHGADAHGHBDGAGBCDCABAHDDEEFGGEHHHBBBDBDHDHDHFHEHBCDCGFGECEFFGFGEGHFBEDA,False +797,22.0,14.0,14.0,13.0,13.0,14.0,15.0,9.0,HCHGGBDEFAFAGAHDCGCGCHCGFAADEDEABAGABFEFEFEBDFGABHFDAABCHCFCADBBAGDGDGDCDFEFGBDBDFFGCBCBEBGAAAAAAHEHEBEGCAAAFHECEC,False +798,15.0,14.0,14.0,26.0,14.0,22.0,16.0,23.0,DCGAADDDHDHFFDBGGFGEGBBDHAHFFFFAFCFBDDFEAEDHDHGHGDCHCFAGBDFCFEFGAGHECFCEDAHAGEBFBABDEDADCDHAFCFAFHBDFAFADEGEHEHBHGFGCGHGCDCDBBHHHHBCBCHDEDEDEDHH,False +799,27.0,20.0,19.0,24.0,17.0,17.0,26.0,21.0,GFGDGDCDFGBGBEBGBHHFDADAHEHEBBBHFFGGCADACAGHBHAAFACACHBECEFAHADGDAEHECFABCGCAHBHAHDGEEHFDFHFDFCAHDBDBFEGDGDGHBDBGAGEGBGCCECEBEHAGABADADADECGCGCAFHGHBFACACFDEDEBGACAGHGFDDD,False +800,14.0,22.0,27.0,22.0,29.0,27.0,20.0,20.0,BCBCBCACACAHDBFCHEHEFBGGCGCABBHBEEEBECECBDHDEBAACGCGFGFDFGBCDAHHHHFFEDDDDEFFHFDEGGGHEAEDEGBBDFEADFCGCGCHFHGHGEDCHFFFDFDCHFBCBCBCEEEGACAEHEFGFDFCFBAEHECGDEFGHGAFAEBBBBDCEHFCFEFDCDEDE,False +801,5.0,1.0,4.0,0.0,2.0,1.0,0.0,1.0,HCAEACAFBEACAC,True +802,15.0,14.0,17.0,11.0,11.0,11.0,14.0,5.0,DGAEAFAFCFDADEFEFCACGEHEFGCHABACABHBADDFDFCGEGEAAACHCGDGCGBEBFDCABBBBDBABFGGCCCEGFBBBEDAHCGCGCGCED,False +803,19.0,24.0,22.0,27.0,21.0,24.0,25.0,26.0,HFAFEFEFCCCHCHGDDHEHEDEACCFAFBHDEDEBGCGBFAHAHAHFGDBAGAHBHFEFBFEFABCDHDGACACBGDGHAFBDBCFHFHDHDGDADBCFGGBDACGHGCECEGGAGDGDGEGECADHDABGBDDCECEHFHBGGEGEHBFBDHFACAFBBBBHEEEGCDHGFDFDFEFHDHDCBBBC,False +804,14.0,12.0,12.0,16.0,9.0,14.0,9.0,8.0,ABCBAFDEDFDHDCDBAFCBGBDBEAEGEBCDGAACABDECECEHEAGHGDBHFFFCGDADFFFGFDBDFAHCHCHCHCBADADADABFFGGEF,False +805,10.0,5.0,7.0,4.0,17.0,8.0,9.0,3.0,AAGAGAGAGAHECEFEGEHEBEAEFDADFEEEECEDECHGFEFAFBEDFGBEACBCEFBCCGG,True +806,16.0,25.0,13.0,17.0,23.0,16.0,21.0,18.0,CBGEEFEGBBBCHGHBAAAAGAGEGCHCEDBBBBBHHHHDAFFEEDEDAAADFEBHGHDHEGEGHCECEBBDADGGGGGDGHEHEHEBBBFGFAFDFEFEBEBCFFEBHBECDBDFAFAGHDFDGBHDCFCAABCBHEGDGDEBGCCAF,False +807,3.0,8.0,5.0,8.0,9.0,8.0,9.0,9.0,HFFFBHCHEBEBEBGBDCGCECEFDFBFGAGHHDHFACHDHDEFBGDGEHEADGDBEGG,False +808,18.0,19.0,24.0,19.0,15.0,25.0,23.0,17.0,CDGFCFCAGHEAEADCGEGACBGFGDHEEECACECECFAHAFDCDHDFEBEHDFDFHFGBEBGGGBBBHBHFAEAFGFAHAGAFCGCHCHGHBCDDFDFDGDFBEBEBFAFCFGDCCHGHADCBFBGBGHFCGDGBCAHFDFCFCBCBDAEABADGFGHC,False +809,24.0,16.0,20.0,18.0,20.0,16.0,26.0,18.0,HBEFGCGHAHADGCACAFBFAFCEBGBFDGAGAEHHCDDHDFDHDHDEECGABCBFEAEHDGGGGBABGFEBCAEGBCFCHGHBHBABGBHFEFCCCCAHGEGEFHFDGAEBHDADCGHEAEAEAEAEGEDCDADGDGAGAGAEHDGCCFCFCADBGF,False +810,7.0,10.0,7.0,14.0,17.0,13.0,14.0,8.0,DEAEGEFECACABGEGEAHGHGHAEFEFECHDDFDBDBCBDBDFGCGEBECEDDDADBEFEBDFGBDFHGCFFDGGFEHEHFHBGAGEGF,False +811,11.0,12.0,11.0,18.0,16.0,11.0,15.0,16.0,EBEBABDHDHDHEHGHFAAGGCAFEDDGEFAFHDBDBDHEGGGGBCBCFDDDDDEDBHFEBHCHABEFEFGHECECBFGGGEDHCHCGEGACAEAECHABCHDADFDFHG,False +812,7.0,8.0,5.0,1.0,6.0,6.0,5.0,5.0,HHHHAEACACBEBCCAFAGEFCFDBHBFBFEGAGEGBGFABBE,False +813,7.0,6.0,14.0,17.0,20.0,8.0,11.0,16.0,BCHCAFAGAHCEFEDEHEDCHGHAEDGDFCFHGHGHAEGEGFHBBDFEHEDEDHDEDEBGDDFBEHGABCEDECCCADGHEHEHCHCDCDCDCEEGEFD,True +814,27.0,14.0,15.0,25.0,17.0,16.0,12.0,25.0,HFFCACAHFFCBCFFGDDECEFEHCBCBCDAAAGAHAHDECEFHAHAHDEABBEBCFGBGDEAEAEADGHAHACDHHHBCBEDFFAFHFEEGAAAAAHAHEHEDDDDGAGDHDBDFFAHDBACACAGHHDGBGBEDDBDHFHECGDDDHDH,False +815,9.0,8.0,11.0,6.0,5.0,16.0,9.0,7.0,DDGCCHAAADDFEFBHDFFFDFCFCFCFEBEGGGCFCGHGHEAAAFFHBCBGBEBCBFFFCFCAAGAHHGB,False +816,27.0,23.0,14.0,24.0,26.0,27.0,25.0,22.0,DABHHHEHAHAEFDBAGABDBGHDAAGAGFBAHAHEEDABFGGEEADAFBCACGCGCEFEBEBDFDCDGDEFEHEHFAGAGCBCGCBCBEDAGGBABHDFBFBDEHEHGBFEFEBDFHFHFDEECAFGFGFEADHDAGAGADCDCHFHCEADFDGEAFBFCFDBEEDGAGBEFEHDHGAGHGHFBFBF,False +817,1.0,1.0,2.0,2.0,3.0,7.0,3.0,4.0,FFFFADHDHEHEGCFBGECFHFG,True +818,10.0,14.0,17.0,5.0,12.0,5.0,16.0,9.0,CACBHAACABGDCAEAFGBEHEGCGCGEGEDBGAGFHBGCECEFEGEGBHBFGAGHEABDFDBCBCBHEHGHGBDCACBGBECCCCCH,True +819,20.0,12.0,13.0,11.0,16.0,13.0,21.0,6.0,ADCECACDCEGDFFAFBGBGBGBAAAEBEBGFDADEDAACACDCHHBGGGGGGGEGAAHFEFCGDGBCFABAFEGCDHFECEDEHABCDAHFGAGEGAGAEAGBFBCEFEFE,False +820,24.0,22.0,18.0,21.0,20.0,19.0,14.0,22.0,ECFBHAHAHAEAFBFGDGDCBCGAEAHABCBHFEDEDGBCDCDADABAEAEBHDGDHCBAHFDCDHHBHEGAAFAFCHCDDEHBFBFDGDGHBAFCEDEHFCEHEHEHGCGAHABCBEFHFGCDCDFBFBFAFGBDEDAGCHBEBCBADAGEBEAEAFFH,False +821,24.0,21.0,19.0,22.0,19.0,13.0,20.0,29.0,DAHAHAFEGCDEECECAAEHEFDDDGAGAGAGABHBGEHDHFHEHAHAHAFBHBHCAADCEBBGDECHGFGHGAGEDFDFDHHHCGAEABFDGBECECAHACFCHGFBDHGFDHBHDDDDGGHEHAHBGBGBHEABBFBDBFBDAEEBECCCCCACHCBCHAHDGDB,False +822,16.0,25.0,27.0,23.0,14.0,15.0,16.0,28.0,BHCHCDCAGFGAGBFHEHBABGDHBABFBGBDCHCHCHEHAHEHCHDBGBHACADADAFFHAADACBCBEGEFDFDFDFCHEHDDBDEGEDHHHCDEGHCFGFDEDBBGFGCGHAHBDCECHCABHFCCHCDEDCDCGBBEHDHBGBFEFCACHCBBABCBDGC,False +823,19.0,16.0,17.0,19.0,13.0,21.0,12.0,12.0,AAFGBDHDCDFDEHBBFHFCDCABBFDFGEGEBCHDDDBDGDACAGABEGECECECEFEHCHAGDDHCCDAEFFAFBFBGDAEHHBABAHADABGBFCFGDCDFHFHAGAFAFDFBACACFGFEFECBC,False +824,23.0,14.0,24.0,16.0,17.0,21.0,26.0,11.0,EEEECEBHDFDBDCFAABFDEEGGCGEGFHDGAGBCFCHCFAFAGAGFFBGAFAEABCGAEADADAHBBEHCHCBCBCDCECGHBHAFDEDEAAACACFFECEFFGACCDCFGGCGCGFDFHFGCGCGAEAGGHHFBFDADABBCGGGDGDG,False +825,16.0,23.0,19.0,19.0,25.0,21.0,19.0,16.0,BCECEGEHBGBGDACADFFBABGGEBEGCGAGDBCFCEADAEFEDDCHCDEDGBGCFHFGBEBEBEHCHCEBEDEBFBFEFHFHFGDEAEBGBEDDCBHDFGFCACAGAHBDBDBCCFCFAFDDDADHEEEFHAEAGBGCAHHHEHFGFBFGECHABF,False +826,8.0,5.0,4.0,4.0,6.0,3.0,1.0,4.0,CDGDCFEEEEABABADAHBFBHACAFHEAEAHCBD,False +827,24.0,26.0,18.0,19.0,16.0,34.0,27.0,29.0,CFAFCHHGFDHDBDBDCDCHEFBGBGBHBDADCGCGHGFDFBAHDDAFECBFFFHFAGECAHAEBEAAACGEGHGEABAFGCEAGFFHFGACBGHGAFHCHGHGBFAHGHBHBGBGAGCFBEDHBFBHEHEBFGECEADHFHFHFDABFEFHFEFBFBABDBDFDADGDGCAEAFCFCFCDAGGFGFBHHHHB,False +828,2.0,3.0,1.0,7.0,4.0,6.0,1.0,1.0,ADDDFDFEFEDEBFBEGFDADFHCB,True +829,18.0,8.0,19.0,22.0,14.0,21.0,12.0,12.0,EGEGCHAFEECHDBDBDCFAFEFDFEGEAFCFDADADCHFHEADAEHDHCCFCFDFHFDFDACACACEFDFDGBFBCGEGFGCGCAHADACEDDGCCACHBABDBHAHFFFDDHACBDEAEGGGFD,False +830,14.0,17.0,12.0,13.0,7.0,7.0,14.0,9.0,EGEBHBDCDGECBABADDGCABACFCEBDCCADADFGHGHGFGBGBGHGFDDCDAGABACHHDHDFDCBBGBAAFACEHAGAGBEBHBCBEBF,False +831,13.0,21.0,11.0,11.0,12.0,12.0,12.0,8.0,EAEDGBFBDBCHEBEBEBCHCHAFGGBCDDDCDCBADAFAFABADFCBCGEAEDBAFAEHEHADFHBBEHEFBFGEBHFGBCBCBFGGAGAGBGCGFBDB,False +832,14.0,20.0,21.0,16.0,26.0,24.0,30.0,17.0,BGGGEEEBFFFEFCDGGGGGCGABDFGHCAFFFDFEHDHAGAGAEBEBCBCAGBBDBFBFEEEDDFCCGCGEGBBDBHEDCFCHGFEEBGCFAEGEGECFCGCHEDDCBEDDDHHHCGBGEHEHGDDCGCGBGEGEBEHECGGAEABAFAHAFAFHFHCHCFFFHFBA,False +833,0.0,0.0,2.0,1.0,0.0,7.0,1.0,2.0,GFFCFHDHCFFFF,True +834,15.0,17.0,13.0,12.0,21.0,19.0,18.0,23.0,DEFBAGHEHEABHDFGFHFHCHDHECEHBHDGDGFFCGBFBEEHHCDEFECEDEBCBGEGEGACAGHGHAHDFCBHGFFFFDACEHEBFBHBHGAAEADGGADHHHHGHGFAFCFCGEDFFABABGECACABEBEBEB,False +835,9.0,17.0,15.0,12.0,13.0,15.0,12.0,18.0,AEAFDHGHGFDEDBFBABACCCFCHEHCFEDHFGFDHBHBHEFAACHEDECFCGCBCECEGHBHCABDBEGFDFDBDBEGEFFCCGHAHAHGHDFBBGBGDGHBHBCBFHE,False +836,24.0,27.0,17.0,31.0,24.0,22.0,21.0,23.0,DCGBEBCDEDADFBFEDADADBDCDCDEDFDGBGCGBHBHBHEHEDEDAGBGFDAHGHBCECADBDEDBFFAFAFAFEHHGCGFEFDDGDGFBFGEGEBAHAFDDHFABBBDADAHAGAFFFCGGEECHGAGAEECEBFBCBHHGEFDAAECFADHGHCHBBBBDEDHBBBEHHAHCHCAEFEHADGDC,False +837,8.0,2.0,11.0,12.0,11.0,8.0,3.0,11.0,BHCHEDEHFAFHDHCHFDCDFDFDAAHCFDDADHDECECACECAFEHEGDGEHEDEHFCBCGCAEA,True +838,12.0,19.0,12.0,11.0,20.0,17.0,13.0,16.0,DEFEFEHEFBFECEAEAGBGAFEBEDFGFGAHFHFCGBBBBBBHEFEBHBGBGHCHFBCDFHAACCHEHACDBFEGEDFBCBABHHCHEHACACEDDDDFDGHGHCAGFDFBEEEGEGBA,False +839,1.0,4.0,3.0,4.0,6.0,6.0,4.0,1.0,GBEECAGBFBFBEDCDFDFEEHEDGFGFC,True +840,5.0,4.0,4.0,1.0,6.0,4.0,2.0,2.0,GEBEFEHEAADACACFCFBBHCAGEBEF,True +841,15.0,12.0,13.0,8.0,18.0,15.0,11.0,15.0,FHFHFEAAHFEFCGEHEHCHCBCAEBBBCHAHAEGFGABHBEBEFCBCAHDHBEAFGBHAFEFBGCFEFCDADBDEDEDEGEFEFAACHDHAEACGEGHGCGAGFDC,False +842,17.0,27.0,15.0,15.0,25.0,21.0,18.0,18.0,DBEBDBEEGGGBGEHCACBCBABGEDEDGFAFCCBEDCGGFGBHAHDBBHBHECACEDBDHAAFAEBEDCDCHGBEDECHAFAFECECEFHGHGHBEBGBGBFFFFHFEFHFHEBEGEAEFFAFGBBBFHCHADFDFBABCGAEAGFHDADEBHBE,False +843,20.0,14.0,16.0,25.0,17.0,16.0,12.0,24.0,HBHEDGBFBCADADACHHDHDAEAHDDDDDHFFDHDGCGCBHEGABAHEDEABACDCEFGFHAGGBACGHAFFGDCAAGHDEGEGEDABACABHFDEEBEBDBDBDHDADAHCHBEFEDEDCFCFCHCHFHFHFHFCAEHHFCE,False +844,6.0,6.0,6.0,6.0,7.0,4.0,7.0,2.0,GCECFBDBDBEGHDEAEAFFECECACBGBDADGDGHFABGEGCA,False +845,14.0,10.0,13.0,17.0,13.0,16.0,16.0,22.0,DADFGHGHFHCBGAFEFCFCGDGDEDBABABECDCDBBGAFAGAHDDDDFDGDGDCEGGFHFHCHGAGDHHHFFCGCHHEFEAHHHFHGEGDAHECDCHHAHAEAEBCFHFBFCEHBBEEA,False +846,13.0,21.0,15.0,9.0,8.0,13.0,6.0,10.0,AGBCBCBDGCBFGHABCBCBEBABCGHEHBAFAFDFECDBBAAHBHBHCFCFDBABDCDFFCGHAHBHBEBEBCFCACDEHACEBFDFGFAFAED,False +847,8.0,14.0,10.0,15.0,9.0,10.0,9.0,7.0,DECFAHHBGBCEAACBCBADDEBHDHDEDFFFGEAEBGCGBGDGDFDADBDBDCFCGCBCHABFBDEDGDGBHBFFCFEAEH,False +848,10.0,5.0,6.0,10.0,12.0,17.0,10.0,11.0,DHDEDCDFDFAFAHCFGABAGFCFBGGGGAHCFDFAFEEEEBBABHFAFGFEEHDHECEHFHFEAHAHEDFDFHFDGGGEC,False +849,22.0,14.0,13.0,19.0,14.0,18.0,13.0,19.0,AACFCFBBHBGFDADADAHHCGFBCHHFHBHDGDCAHAHABDEDBDAHAGFGEBEBACHCDEGAFFDGBHFCFDDBABAEEDEGEFEAAGAGABADAHFGFCFAAGCFHEHFGFBFEEDEHEDCDCDCDHHH,False +850,12.0,11.0,24.0,25.0,18.0,37.0,27.0,36.0,GEGEAEAEDHDEDECECGGGEFEFEGCBFBFCFCDCHEHDDGEGFGDHFGEGAGCGFDHCHFHDGCCHEBBDACHCFCHGHCHCHGDFFFFDFHGHDFFFGFGHHHGCDFBFCHHFHDDBACHEEFDCAHDHBHFFFHHCHBHFHDGFGFGBEAHFHFHFCAGGDCBGDGDFFAACDCAFDFDFBHHAHE,False +851,8.0,20.0,9.0,10.0,16.0,10.0,11.0,18.0,GAGAGFFHFHCHGHEFEGADABHBHBFEEEBAHCHCEEHEDCAGGBBDBFGFHFHAHFHBABEHEBFBCHEBBBDDDCDBECEGDBCBEBEBHBGCHEDDHG,False +852,8.0,4.0,3.0,3.0,5.0,4.0,5.0,3.0,CEHEHBGFGBABDCGAGHFDCGAAAAEADAFEFEB,False +853,2.0,2.0,4.0,5.0,2.0,8.0,1.0,9.0,BHFHFHFADCCGFDFDBDEFAHHHHHFHECCFD,True +854,0.0,3.0,1.0,7.0,1.0,4.0,3.0,3.0,BGEDFDHDHGFBDBCGHDFDFD,True +855,13.0,9.0,23.0,8.0,13.0,14.0,12.0,14.0,CFCFCGHEACCCEEEGDHHAHBGBCFCDCDCFFGCAFDCABHCHCDFFCECGCGCAABFDEDACCHHAFAEBEBHGHBHFGEGCGCGAEBCBAGEFEFEFDHAHAH,False +856,10.0,14.0,21.0,25.0,13.0,22.0,18.0,15.0,HDAFAFDFBGDDCEEGEDFGBDBGCCCCDDDGDGHFDGHEFECHCHCFEDBDBACGFBFBFDCGEGCABABDEGCGCECEBAFGHHBDDDHHHGGDCDCACAFBEBECFCFAEHHFFFDGDGHGHDDFDFHFCFCBAF,False +857,5.0,7.0,6.0,6.0,3.0,6.0,3.0,6.0,HBHCDAHAFGBACABHBDBDEFGCHCHCBEFEFGFCFDDBDA,False +858,5.0,6.0,10.0,9.0,8.0,7.0,3.0,10.0,BGCHCHCBDDHDGDGABCBABFECECECDCDFHHCEDDFFFHHEHEAEAFHBEDHCAF,False +859,5.0,3.0,3.0,10.0,1.0,2.0,6.0,6.0,DADADBGHEADDDCDGHGHGCDCDBFAHHFHAGDGB,True +860,23.0,20.0,27.0,31.0,27.0,21.0,22.0,20.0,GBHCDCFCFDEDHCHGEFEFECCCCCADABAHFHFHFDGDAEEHACDDGBADFDEECFAFCFEGCGEEHFAFEFBABCDADEDEHBHGHBBAECECGBHAGFHHBGECCDEDBFHCACGCDAGAGADDDDDCDGFCFCEEEDEBHGHGHGCGCBDADHBGDDEDABABAEDEBFCDEBABGBDAFAFGEGH,False +861,7.0,7.0,14.0,4.0,11.0,5.0,11.0,5.0,GCGFGBGCCCGFAAEAECECECGBABHHCAEAHAEFEBEHDCDCGFGFBCGCGCDBEEHDGECB,True +862,12.0,3.0,10.0,5.0,8.0,8.0,5.0,6.0,GFCAHAHAGACCEHDBBAAAHADECEDECGCBCECFCFHFHAGGEDEFFCFAEAFAD,False +863,24.0,14.0,29.0,24.0,18.0,18.0,12.0,25.0,ACACHBEBEDABHBGCDCFCEDFCGCACGFADCCCCBCDEAEBDHEEGAGCDFDFDFGEHAHFEEAEHCCFHFEFCHCHDAAHGDCDAHFHEHDHDHAHADEBEBEGADAHEBFHFHACGFGCGCBCDCDCACFCFABCBADDBCBHHDHGAAHAHFFDHDEDA,False +864,12.0,14.0,8.0,8.0,15.0,8.0,10.0,15.0,EBEBGHCABAFAFDFDADGBHCEBGBGBCFCAEEDHCHGHBHDGDHEHEHEHCFGFBEEHAAAHGHGEGBFCABHFHEEBADCDABEBEA,False +865,3.0,2.0,2.0,3.0,0.0,3.0,0.0,4.0,BHDHBCFDFCAHAHAFD,True +866,5.0,8.0,8.0,6.0,13.0,7.0,15.0,8.0,FHCDEDADBEBGAGCCCEBGGFGEGEGAGAGHDHGBEHEDGAGEBECHCGFEEHEHGGFBFBFCFHEBCD,False +867,15.0,8.0,10.0,4.0,10.0,7.0,12.0,11.0,GCHHEHGBDBCGCBCFEAAHAHADFCFCFGAGAFBGAHAEGFBECEABHCHAEAEHGHGFBDCHGEGEGDACABAEA,False +868,13.0,19.0,24.0,20.0,14.0,16.0,12.0,20.0,HCHAHAGDDCDBGGHGHGCEEAEGFBFDEAEFCFHDHGFAFGEHDBDBDCECDFECHCDCFCHCHBBBBGAFDCACEDBFFAFAFBEHCACDHBCBCBHBCADDDBDHDHCHCBABHHEFGAECGCGCBDBDCFHFEE,False +869,11.0,10.0,12.0,15.0,14.0,12.0,10.0,5.0,CBGECDGDGDADCGAHDBDFFFFEAHFEFDBDGDGECECDDFDADBEACGFEBEBECCCGCBCBEAEAFGBAAAEDEGHHDHCFAFEFB,False +870,8.0,16.0,15.0,5.0,12.0,6.0,10.0,5.0,GEGAAFBCBCEGAAEBEBEFHHCBAAGACBBBBEBCGCGCECECBABCFCGCFEDEHCCDGBGFDFDEHCHBBGBDE,True +871,7.0,10.0,13.0,4.0,10.0,7.0,7.0,8.0,GAAHGCBADEDHDCCCACAFHEBBBBBCBEGEGFCHCBEGEGEHDHCFFABCFCFHGHABFECECE,False +872,5.0,6.0,11.0,4.0,5.0,6.0,7.0,6.0,FCCCACBDAFCCCFGBBHBGAGEGDGCGHGHDHDEBHCCFCBAEFEFEHA,False +873,6.0,3.0,2.0,8.0,3.0,5.0,4.0,1.0,AADDDCDCGGFFEBADADADEDGBGFFEFAHB,True +874,16.0,16.0,9.0,13.0,16.0,16.0,11.0,18.0,DGAGHBHCEFGDAAEAFAFBBDFHEDEDHBHGHGHDDEDFCFCAAADAHFBCBCGEHEBFDFAFCFAFAFBECCBEDHHEHEGBGCDFGFHHHBHBEBEBHAEADBEBAAGEGHF,False +875,10.0,10.0,11.0,9.0,10.0,8.0,13.0,16.0,AFADADEDEFHCHCFGBGEHDFGHCHEGBGHFABHEACHBHBHBHGDGBAAAHAHCHCGGGCGEDEBCDDGBGAECEFFFBCHCHDE,False +876,10.0,18.0,8.0,11.0,7.0,15.0,11.0,9.0,FCHDHBFBGCDHAGCCHDHAGFFHBHEFAFAFDBBBDBDEACGGGBGFECECACHDBABFBDBDGEADADFFFGEGEBBBFBFBGBFAH,False +877,4.0,5.0,14.0,13.0,6.0,8.0,11.0,11.0,ACACGHADGCECGGGDCCCFCFBFDFDHDHDADHDHFFBHGHCHCGCDCDHDEEBGFDEHBHGEEBDFCCGG,True +878,22.0,17.0,15.0,16.0,16.0,19.0,13.0,15.0,CCFCHHDBEGEGDCFHFBAGFEDDFDCECEGBCBABADADBGGDBACAFAEABHHHFHCHDBFBDBDBEHHCHCHEEGFGFHAEAEAEADFEAABCFCEAHFGAAADFDFBFBEGCGCDAFAFAEDGBHBGFA,False +879,11.0,12.0,5.0,10.0,10.0,9.0,11.0,9.0,BCBCEAFGFGHBHBHDDFEFGBGHGFBDCAAGEHDBDGHGHFADAEEFEDEDEAHABABACAGHEDFAGEDBGBCBF,False +880,22.0,23.0,20.0,22.0,17.0,22.0,27.0,22.0,AFEFEHDHDHDBFBGBGEGBGFGFGEHEABABGGGABAHDHEBCGCGCFCDBDFEEAAAFDCBFHGHBCGAEDFDFDBCECFBAGAGAFEHGGCGDBBCCGBDDCDBDCFCAHDBAFFHCHDHFHCEEDHDHBHCCBFBAEAEAFGDCDHAHFHEHADAGAGAFBGCGHGFBEGG,False +881,26.0,17.0,21.0,13.0,20.0,12.0,23.0,19.0,BAEAGCGHGAEADABEEEGAAHHDDBDFGAGACCHHEHEBFBHEEEDFGFEAGHCCACGEFEDCGCHCGFHHBHBGBCCCDCGBGBABABFDDHEAEFEGGGGEHAHACACDGBGBGBEAFACEHFAAAHGHGDCCECFCBCBHDAAAFAD,False +882,1.0,1.0,3.0,2.0,1.0,1.0,0.0,5.0,DHHFADEBCHCHCH,True +883,7.0,3.0,8.0,7.0,4.0,4.0,4.0,4.0,GDEDCFHFHDHDEGEACDCABBGFACACGCFCDADBCAEAH,False +884,21.0,12.0,14.0,11.0,9.0,9.0,15.0,13.0,EHEAEGDDAGGBGFFAGHDHDCDCDCFCGGGGGAAEGCHEDEAEFHFAFGCBHBCCCCADBBAGAGHBCACAHAHBFEDBGBCBEDDHHABAFAHAHFBCAAAA,False +885,16.0,26.0,24.0,20.0,25.0,24.0,19.0,20.0,DFDGGAEAEAEDHGHGCCABBEECFCFGBGBDCGFFDBDECEADADHGHFDBDCEEBCGCGAFBFBCHDFDFEFEFHFHFHBHFEFHCHCBAFDFBFCAGAECBBBBEAEBGCECFHEHDCCEGBGBGFGFHHEHCHBDACECABABDBHAEDDCGGBBEFDFDCBAEHEHECG,False +886,13.0,28.0,17.0,8.0,23.0,25.0,17.0,16.0,GFFBFBHCFBBBCGCGEEBCBABFDEBGBGCACEHFHFHBADDCGEGEBHAAACFCEHBHBDAEFFFFDFDFEFEFECEBBBHFGBBHBEGCBEAEDCHEEEFBGHGECEHFHBABFCFCFCGCEAGDGAGAFBGGAFHHHBEBEBF,False +887,12.0,16.0,10.0,18.0,15.0,11.0,14.0,8.0,EEHEFGDCAFDGDCBFBFGFBEAFBBBAGFGBGCHCHCAGADCFCDBDEHEAEDGDBHBFGEBEBDBDADCDHDEABDDEDFCAGDGAGAFDEAGCGBEBEHEH,False +888,18.0,13.0,17.0,15.0,11.0,10.0,18.0,15.0,DEGEDEFAHAHAHGHGHGCGCFDDDADFCBGDGDCBABCBEACAGAGCEDBABDHFGAGAGDEEHAFCDCBCACBEBHCGBFAHAHCDFHBGBGHFHGHFBACEGEGCHAECFCDAD,False +889,22.0,5.0,11.0,9.0,14.0,19.0,10.0,13.0,HEHFADEFGFCEHEFDFHFAFGGGGAGAFADGDFAEAHBCECEDFCFHFCFDFDAACACABBFGCHEAAABCDHEAEABFHFHEGEFHAAAAACAGDHCHEFE,False +890,27.0,36.0,17.0,27.0,26.0,14.0,25.0,25.0,FHDGFABEECADAEBECEABAGHECDCDADGDADADEHEHGHBFBCBGDEEEEEBABABHBHAGCEDEDEHAHAGGCDCDHBABHBCACAGFCFGHHFDFDGBGHGAGCGFFBHADFCECEHBDBGBABACAHEBBHGHEHBBEDEFEBGBDBCGEDBBBBBEBDHDBAHGFGAEBHAADGHGDABFCFDAGBGDHD,False +891,18.0,15.0,22.0,14.0,25.0,27.0,18.0,19.0,FHFHEHAHCFEDCDHFFFHCCCCCCFAFGEAHAFGGEGEGEGFGFAEHDCDFHGAGEBHFHCHBHBEDHDCFCACGBFCDDEHBCEGAFABEBFDEGAFDCACFEFEDEAAGAGAGCBCDFEHAHEHBCBCBFBEEFEHGGGCEFEFEBEAFFBDADB,False +892,15.0,15.0,17.0,14.0,25.0,21.0,15.0,21.0,EGAHHHDHDFEAEDEGGGGAGFHFAFEEEHHBCBGHGBGDFAAEAECEFEDDBFCFCAGFFHFHFHBCFCDHFHCHADBHFGFGBEBHHEEDDCDGBCEEEBGBHEHEDEAFCBCECEBGAAAEDCDCACABEHHCFEFCFBF,False +893,5.0,2.0,1.0,1.0,3.0,2.0,5.0,2.0,BHAHAEEEGFGFACGBDAGAG,True +894,1.0,2.0,2.0,3.0,4.0,6.0,4.0,3.0,FCFCHHEFEFGGGGHDBEBFAFDDE,True +895,12.0,25.0,10.0,17.0,18.0,19.0,18.0,17.0,CECBHFGFGEBBHFEFDBDBABDGAGAEABCBGAGAHCEEHEHEHDDCDBFHFHEDFCFBFBFAGGGGGFGEHBBBHDHBHDEBEFGDCBBBDBGCAHHEGBGBCDFDEEEDEACAFFGBBHFHFDFAFHGBADED,False +896,16.0,8.0,11.0,13.0,10.0,11.0,7.0,7.0,GEDEHEHBBDADFDADCDCAAAHFHFGFECACAEDCDGAEAEBBCBGEACAHDBDEGFHFBCDCFAADACBCHFAFAFEGGDF,False +897,11.0,6.0,9.0,7.0,10.0,14.0,15.0,10.0,HDBFBGCFCGCGBGDEDGHAHGHAAFHFCGBGCAHHGFCFAFEBGHGBDCHCHDEEFEFEAEAEFEFGDGFAFACGEFDAGA,False +898,17.0,13.0,21.0,30.0,28.0,20.0,12.0,19.0,EDDBGCECEDBCBCDHGFECBGBEHHHEHFHDGDHHAFAHCHDBEFDADCDHEEEHEGDGDGFEDCACEDEAEAEFDFDFDADCCACFEFCFEFCBBHCCFEEDHDFGEGAFCFCACABABCGDEDAHEDDDDGDGFHDHDABFCFDFAHEEBEBEHEAA,False +899,3.0,3.0,2.0,3.0,3.0,3.0,8.0,3.0,BCEFGHGHGAGBGBGDFDCHEGEFAADG,False +900,16.0,24.0,17.0,15.0,11.0,13.0,13.0,18.0,DDCDADAECDHHHCHADDHCHCBCADAECGHGEAHFHGBBHDADAEHHFHGACACFCFBEBEDCGCGBBBBGEFFHFBBGCGBABABAHFEFBBECCHGFDFBFAFAHBBEBEACDGDGCBHBGBDB,False +901,25.0,30.0,29.0,16.0,34.0,19.0,24.0,19.0,FFGCECEBBBCDCBFEEEECGCABAFEFGHBDAACECGHDFCHBFBGGGBGHCHCBCECBGBEFDHBHBHCHAHAGABABGEGFCFBEGEBBCBCDHHHCHCHDBDCFCAEDHGAGEBEGEBEDEFFDBDEFBCEFEAGGFGEGFBFHHACACAEAEAEBEHEBAGAEAECGABADDDAECECFAAEDDAGCECBG,False +902,24.0,23.0,19.0,24.0,26.0,27.0,19.0,14.0,FAAAEACAEEEGEDAHEBADAGGHEDCABGFFDFDFEBEBEDEDGAHFDGBCBFDFGECFBFGFBFEFCFEDADBEFEFACACACAHADBBBEHAHBGBFAGBEEGGFGCGCFAFDFEBHGCAAGDGFHFCFCHCDCBFBGBCBEHFHCHCBEDGDACAEBDBHFHEDDDDDEAED,False +903,29.0,29.0,25.0,18.0,19.0,26.0,26.0,24.0,GABBEDADAGFHBHFHGCBCBDADGBGDGHEDBGBGDAEBEAGFGACEBEDADFFFBBBCFCGAFAHEHEHGBAAAAAAGGCCHBGBABHEEFHFHAHFBGCHDHFEBEGEAEDFGCHBHACADBHGDGCEDFFHFEFBCBABAHAEAGGFFCFAHADGDGCBCBCGCGCBCBCFHEHDFFEFHFCFABCHCDCAC,False +904,6.0,3.0,10.0,6.0,5.0,4.0,4.0,1.0,ACGCFCACDCHCDDDEDCGGEFBCBCBFGFEEAEDCAAA,True +905,3.0,18.0,9.0,11.0,14.0,16.0,4.0,13.0,DCFBBCBEBDBFFEFDCGHBHGDCFBFDEHEFBHBFEFHFHFGCAEHFAFBEHEHEHCACHGFDCBEFEHEBDBDBHBDEDEDBCBFB,True +906,16.0,25.0,37.0,22.0,24.0,10.0,28.0,28.0,DFDCDCEAEHCHEACBHBGBHCCGCECADDDDDDCHHHAHCCCGDECECEBECHCFCFBHBACGCBABCBHGEBBBHGHGBCBCDEEAAGAGDHFCCEDEDGDGDGBGHHDFFGEEBFAGHGFCBBGEHHBCBDBABCEAGACACGBEHEHCFDHAHEGGGHGHGACEDECHCGCGCDHFHBEGEDBCGC,False +907,25.0,18.0,28.0,21.0,19.0,32.0,30.0,20.0,GCGCEBHGCGCEDDHHGCCCCGHGHDHEHACGGGBGFGBEACGHGCFDFDCCCHCFDFAFAEAGABACAGACEBHBFGFBFBDHCFAFGFACAGDEHCDBGHAHBBDFDFCFAEBDCGFAHGHGFGFGBADFEFHBDADABBEAFHDDFDFGBGDEDEFAFEFEFGFAFDFEFCACHFHBEEECGCGCAAEAC,False +908,28.0,27.0,16.0,15.0,23.0,29.0,25.0,24.0,FAFEFGFBABHFFBHDCCGAABEBCACAEFFCFAGAEEGEGFGFDFHFHBAGFGBGDHBHBHBCGEGFAAHAHAHAEGEBEAHABCBDFGFGEGBFBHBDBFBFGFGHGHBEBEBDGHGFAFCHADEEECECFBACCBCDDHGGEHEGCAAFAFBDHHHDHDFDADGFAAEAFABEECGHHDBEACB,False +909,22.0,23.0,20.0,21.0,31.0,23.0,29.0,28.0,EAGGGDCHHHHCDDEDBCHAEDGBGAGADBHAFFHGBGBDEGEGHGAGDBEGAGCCHFHFGEGHHEAEBDDDDADHCBBBCACFCGAGECEAEFEGEDDAAEFEHBHBGBFCFCHGBBDBFBFDEAEAEFCDDEGFGFCECAGHGFGFEHHDAFHFHGHGHFHFEEEHAFBBBEAECGCBCBCEEAHACBFDFEHEH,False +910,35.0,20.0,17.0,22.0,15.0,17.0,23.0,20.0,BABABADGDFFFFFADHEEAEHCBGBGDGEGCACHEFAAHAHAHBHGHBABCBCGCFDFAFCFCEAEHEDGFGBAAADBGADADBDBECGGFCBDBHCAADAHAGADCGFGFGCGCEDAAEAHDEDBAGFGBADDDCDHHHCHAHDEAHGFAEAFBDHAGAEHBBGCGA,False +911,20.0,22.0,16.0,16.0,19.0,34.0,24.0,21.0,HHBBFFAHAHEFAFCDBDBDGCEEBFBDCCBCHDFAFDBDBFCFAHGEDBGFFFDFHACEDGDBFBFCECHCHBFAFADAFFFFFFFGFBHGHGHGHAFABACHCFGGGAFHFHGGGGFAFEEGHGEEEGECDGECBCBHDGDGHEHDBAGEBEAEABABFEGACHEBGFAF,False +912,14.0,22.0,22.0,16.0,10.0,16.0,13.0,11.0,GABHDHAHACDCBFFFECHFHEBEGABCEHEBBFBACHCHCACABEFFDBACDHFADAFBFBGGCGCGCHFBFCGDFAFGBCBCBDHDGDCBCBCGDGCGAGABCBCACEDFDEEFBBDDDEDB,False +913,20.0,27.0,29.0,23.0,22.0,31.0,29.0,18.0,GFGEECFDFAGEFHFACDEGCGCGHGHDHDCGCFDBAGAGAGDGHFDFBFGFGAGHDAGAFABDCFFECECEFFDCDCBCGDBABFFHFDDDGACHHDBEBEBFCEEBEHAHECBABGGAGDHDCEEGFCFBDECACAFHFAFACBEAGGGBGBCBHFCFCFCFCHDFAEBBBHBEBECFCHEEGBGBFCDBDBDBHGC,False +914,12.0,9.0,6.0,2.0,6.0,6.0,2.0,13.0,BFBHEHEHBADCHBAGFHFEBHAAACABHBHAAACECBBACGCHFHAHAHEHEFFD,True +915,10.0,12.0,24.0,13.0,16.0,14.0,13.0,16.0,CEBDBDBDCDCDCDBDAHHBFBFCFGFGEDFHCBCFGECFCEBEBHBCCFCFDFEHAFBHAHAHFCACHCECEHACBCHCFEDEAGACDCHCGAHCDEGGHEEFHAGGGECEGEHDGG,False +916,4.0,4.0,9.0,4.0,6.0,12.0,3.0,4.0,CECDADFBACFCFDFBFGFCFGHCCGBEHEHEHEFFCACBEFFFAD,True +917,15.0,18.0,12.0,11.0,16.0,11.0,18.0,15.0,AEAEAEAEAHAHAGEEFHGHBHBEDABABADHGFGDHBCDDFHGBEFFFAFGGHBDFCBEHECECGFHBHEEGDBEGEBBGDCDHDCACGFGHGCABABHFACCCCBGBGBGDGBE,False +918,14.0,16.0,12.0,30.0,16.0,18.0,12.0,16.0,DHDAEBFADADADADADGDFAFHFHDEFGBGBGBGFHCGEHECEAACACGCDDDFEBEBHBFAFHCDDDDFCFDFGHCFDHEFEFDCHBBBHAEDEDBAAHCEFDCDBDFDBEEDBDHEBDHDGFHDHEGGGCB,False +919,5.0,11.0,3.0,9.0,10.0,8.0,8.0,5.0,BFBHEEEBCBHEHGAGAGDDBDEEEHABFCFBAGDCDGDBDGAFEFEFDBDGGFBFBHE,False +920,5.0,0.0,5.0,4.0,1.0,1.0,4.0,2.0,CGAAFADHDCACGCECGDGDHA,True +921,24.0,17.0,18.0,26.0,23.0,31.0,24.0,25.0,EDEDCDADFGBABAGGFCFDFEGCGBHHECEADGDEDFDFDBEGEFCAGFEFEFDHEADHCHAHFHFHEGEDDDDBGEGEFBCDCEAAHDBAGHDHFGGHEHAHAHAHFHFDFBGBHCGAGFEFEFADACAFEBGCCDBEBADAFBGCFAFCHCHAFEFGCGBGCAFABCDAFBFBHDHFHEGDGHFH,False +922,12.0,3.0,17.0,8.0,6.0,8.0,19.0,16.0,GDFCHCHAADGBHCHAFEHCHCBGBCHFACAFADGGGGGGCGCAADHEHECEAEDDCCEGFGFGAGAHHGHGCDADCCHHGCGFHFHGC,True +923,13.0,7.0,15.0,17.0,15.0,11.0,14.0,5.0,GDDDHCCBCDADAEABADADGHFDCCACAEAGGDEEEDFHFBDGCHBFBFDGGBCDDDFCFCFEEGCFEFADADACAGGGGEGCCAEBEHEGEFECE,False +924,19.0,22.0,14.0,20.0,28.0,12.0,19.0,18.0,CGCDHBFBHGEBEADBDGDGDCBCDCHCEBHGEGEHEGDFFCEAEDGCGEGFDEEEEEBABCBCBCBCBGFDFAEAFDHDHEHFDAAHHHHEAEADAFEFEDBABDHEFEAGCBBFHDHBHBGBADHEEDBDEGBAEAGGCGHBEGGAAAEA,False +925,20.0,23.0,18.0,19.0,19.0,27.0,21.0,22.0,FEHEHEGDGCBDBHBEBCAGACHFEFHAHADAFGBGFFEGECEHDGDAHAHEDCCEAGFDFEGCCBGBFBFHDADCBCBFBCCHBHAHBDCECDFHFGFADCFFFFBFADBGGHADFDBBCBGHHHEHEHBAEAEFGBHBHGAGEFEFGFGFDCDFBFACAGAEADGDB,False +926,8.0,4.0,5.0,5.0,6.0,5.0,4.0,8.0,FGFDECECEADFBFBHEHAHADAHAEACGDADHHHBHFACBEGCG,False +927,4.0,9.0,2.0,4.0,9.0,4.0,11.0,2.0,GHGBGDGBGBEAGFGBBBBDDEBGFGEGEDECEAEAGBFCEHFAE,True +928,19.0,13.0,20.0,26.0,25.0,21.0,11.0,20.0,DDDFAGCFCHADFCCECECFBEHDBEBEDEHEHCFAEAEAEFDFBFADAEAEAEADHDFDFGBGBADEDBHCGCFCBEEAEHECFHAGACCCDDEDHHHHAHDDDACGHBACFCFGDEFEBHFHFCDDDHDACECBDHGHEEFGBGFGFEDHFBA,False +929,31.0,26.0,25.0,22.0,30.0,19.0,16.0,16.0,GADBEEEAEAHACCCCFGFEHBGBGCFCFDDADGBAAAFEFAABEHADFDFACAHBHGEFBAAACFCGABEGFABGFGEGFBFBEBFDEDEHGFEECHAHADADADCHEHEBEDABHBEACADBDBDGDGDCDCACHEHGCEHDCEABCFAEDFDGCEBFBAAEHEDEBCBCBCBCBEEAEBCHC,False +930,5.0,6.0,16.0,9.0,2.0,8.0,6.0,8.0,FCFCBBGDGDBABHCHCGEBEDDGACFCFCFCHCGCABHCCCCHFHCAGFHHCAFDDDDD,True +931,13.0,10.0,13.0,5.0,17.0,8.0,8.0,11.0,AEAEAHAEECBHBHGHAEBFCEEAEBEGCHBFBGEGFACADAEGEDBFCCHHBHBHFHCGEGHDDCDCACAEAFBCGCFEFECEA,False +932,13.0,15.0,7.0,16.0,20.0,10.0,5.0,18.0,AEABBCHEBEHEFEDEAFBHBADFHHDBDEHBABABABACDCFEFHFEGGACEDEHEBBAFGHCEDEDBGCHHDBDBEHCHDADGDEDEDHFEEEAHAHFHFHD,False +933,4.0,6.0,3.0,4.0,2.0,6.0,4.0,5.0,AGAGAHBEEDCGBGBCBDFDFDHHAFBFHFCBHF,False +934,5.0,12.0,3.0,2.0,5.0,4.0,9.0,11.0,CEDBABACFFGFAEAGCGBGHGHBHGHEBBHBHGDFHHHHBEBEAGBBBGH,True +935,8.0,6.0,1.0,11.0,7.0,1.0,14.0,7.0,GEBHGHGDBAEEDAGGEGDGBGBHHHHDDAAAAGDGDGDADABCEGEHEDDFGGB,True +936,12.0,13.0,17.0,16.0,15.0,22.0,16.0,19.0,HHEDDDDGDGAFACACHCFEEECACADBGHGFFFFFFEHEHCAGBDFEFDFEFEHEFFBBABFCHEGFGDHBCBCBEEAHCCECDDBFBHCHFHFHDEDGGGDGBGHCBGAFDGDGCAHBCCHGHFHFAA,False +937,3.0,4.0,1.0,4.0,2.0,0.0,0.0,2.0,ADDEDEHBHBACADBB,True +938,5.0,10.0,7.0,7.0,2.0,7.0,13.0,13.0,FCGGGHHAFEFBFBGBABAEGGGGCFCFHBABHHDHDHFHACDBBGHGDGDHCBDHCHGBGDHC,True +939,0.0,2.0,2.0,0.0,2.0,1.0,2.0,1.0,CGEGEBFBHC,True +940,15.0,12.0,17.0,12.0,18.0,16.0,21.0,10.0,DADACBCEGEGCCAHFCDCDAEACDCFGDAEBEBEACABEGGGABACDFDCGGFDDHCGFGEGBCBDEDGHGFEFBFGGCBCEEFAFGFHFAFHGHGCEFEBHBHGEGEGEFAFAHACBHE,False +941,21.0,9.0,18.0,19.0,23.0,21.0,20.0,26.0,EGEDHBHBHGHGHCEAAGBHBDDDGGGDGFGFEFGFGADHEFEAEAFAHAEAHBFECDCAAGDFAFHEHCCDCEFHFHFAEAHACFCFCHCECEHDDGDHDHDADEBHFEGAAEAFBHCCEGGDEDBCHADAHFBFCFCGGEDECFHGAGHECEHFH,False +942,23.0,23.0,25.0,23.0,16.0,18.0,18.0,24.0,CAHDBDHDEGCADHGHGHGHFCDCHCDFGEDEDHDHBHFDFEEADAEABFFGFGACFBBCFCBBFAHCHCEEDCCFHACACABHBFFFDFECACHHEGDGDEDBHBCBHBHADABHBHBCGHACBCBEBABCGEEFEAEAGGCDDDDAGAGAHBHDGBCFGFDCAGACAB,False +943,9.0,5.0,6.0,3.0,2.0,3.0,4.0,6.0,DBDHCFFHCEAEGBGBGAHCHBBAGFCAHAHACADACA,True +944,1.0,5.0,5.0,2.0,2.0,3.0,5.0,5.0,EGGDGHCBBAEGHGCFCFBHBHBHCFCD,True +945,23.0,12.0,17.0,23.0,21.0,25.0,31.0,23.0,AHAHBHBHCHCEDDFCACDCDFGFBHBCCGFGHGAAHDEEGECFAHAHFHDHEADFGCGCGFGEADBEAEBEDDBCBHAAFAFAFDGDHABAEHDHGEEEHDADGFGHGFEFGFCFAFHFEFADGGEGEGECFDHCHDFGHGDGCAAGAGEGFDBGCEBGBGDEDHFFCFGAGDG,False +946,7.0,6.0,9.0,5.0,3.0,13.0,9.0,7.0,BEBECFHFHAHGCAABCCFGBGFFCFGFBFDFGGAGHGFFFFDBCGHHCHCDDADAEAC,False +947,12.0,14.0,22.0,9.0,8.0,15.0,19.0,16.0,GGGGGADFDBBBCHGACAHBFGHGHGFGCCFDACHGHEFFBCBGEGDGFHHHBHDGDCCCCGBFHACACECDCFGBHBHBCEFECHCBCBCHGFGDAAAADAEEFCFCACFFEHB,False +948,23.0,29.0,24.0,18.0,9.0,25.0,25.0,32.0,BBBHGFAEAEBEBCFCFAFAFCFDFBHBGCHFAEGDACAGBHCHFDBCBGGCCBBHHABDCFGHBDCDBDGFBCAFAHHGHFHEHACEGDABGBGHABABGHHHFBFCFHFABAEAGACBCFHHBABCBCBCACFCHGHCHBGBHDDFGAAFFFEDDDGDHDHGHGHGHDHGHGHDCDCGFGFEA,False +949,7.0,6.0,5.0,7.0,7.0,6.0,6.0,12.0,HHCHADDCGBGFFHDHBBCHCHBFADAEAGAFAEAHBHEEEEHHHBGDGEGCDFDF,False +950,24.0,23.0,22.0,11.0,20.0,30.0,30.0,14.0,EHFBFBFBCCFCAAACEGBFAEEBHCHFHEAEAGBGHGHGCGCFEFAFBEAGAEBGDGCGHGHBBGBGBFBFDFECAGGFEBEGCAEBEDGHAFBHBFBDGDGFGDACCGCECACAGFCECHDFBCGCGFFFGFGCBCGABADFBHGGFGDHDEFBHCAAAAAAFFFFFDEEAE,False +951,16.0,19.0,15.0,15.0,20.0,28.0,15.0,17.0,DGGFECEHGHFHCBCEHGDGCBCGCEEFAFAFAHEHFAABHEGDGAGBGEEBHDHBBCBCHFBDBDBHEDFCAEAFFFDFDFAGBCBDECFFFEFDFBFGFGEECECEFEFEDHGCDAHAEABBDGFBFHHBHDAFHFCFAFABA,False +952,9.0,0.0,6.0,3.0,8.0,5.0,2.0,3.0,EFACCCFAAAAHFFFDGAAEAEHGHECECEDECEAD,True +953,2.0,1.0,1.0,1.0,6.0,2.0,3.0,1.0,ECEHDAAGBGEEEEFGF,True +954,11.0,9.0,7.0,13.0,13.0,4.0,8.0,8.0,CADHDHDFDABBEACAFDBBHFHGAGECBGEGEGEBEHEDEAHBGDADADADFDEBEDDCAABHEHCGEGECC,False +955,17.0,19.0,17.0,18.0,12.0,19.0,16.0,32.0,GFGFAAGFGAHADGGHGEBABFEDBHBDFHHHHBGBHDHDEAACBFBFBEAEHCDDGDFHHEDGHGBGBGADHFHDHCCGAEACDCDCAHAHFHFHFHDBDADHCCCHBACACBHFHFEFECACGEBBFDHCHDHBHEFGCECHFFBHBH,False +956,21.0,23.0,17.0,24.0,20.0,16.0,15.0,22.0,DADEHFHDCBCBCAHGBGFDFDGBAFDFDHHFDBDBACACFEHEAEAHAEEBAGCHCFCFAHAGDGDADADHHGHGECCFCFGFCHAHGDGBCCHADBDEAHGCFBHBHBHEEEEEHEBEAEGDBBFBHHCDCEBBBDBDBAADGFABADFEEGEDDB,False +957,10.0,10.0,8.0,10.0,12.0,10.0,10.0,2.0,FGFBFDFCGGFGABBBDGAAAFHFDGDBDGDEDECECECECGBAEHECGDACEBGBDFCAEAFFEDEBABAE,False +958,23.0,37.0,29.0,27.0,20.0,20.0,23.0,19.0,ADBDBAFABHBADGGCCCHFHGBBDDCACACBBAGDHDHCHFECBHFEGEBEDCCFEDEFBFBCBCBHEHBGDCDGBGAGAFFGCGEGAADACADBGFEDGBGFDBHBCAHEEFFDCDADBDBACDCDCDBHBHFEFHFDBGBGEFHFHBACECEDEBCBCBCGCGBBACAGEFBFBABGDGDHEHEGBCDCBHEAAA,False +959,12.0,18.0,18.0,8.0,12.0,10.0,17.0,15.0,BEBEBGBGBHBCBCECGCGCDCFGGHGBCHEACCCEFGAAAEHBHEHBGBHAEABHGFCFCDCEABACAHEHCGCHFEAEGDBDHDCGFDCDAHBHGFDFGGGHFBBBAF,False +960,6.0,8.0,14.0,11.0,10.0,8.0,6.0,15.0,EADADHGFDEEHFHDHBHBHCECDFDBDECHFFAFGFBEDECBCECHHHHGCGDGDHCCCCCCEEDHHAHABCGFABB,False +961,20.0,29.0,25.0,20.0,25.0,26.0,26.0,18.0,BHBEFEABGFAEGDGDFFBDHDGBGBFFFHEEEEEDFAFADABGGCGCBCBAFCFABCCHEHGDDEDEGFFAAEEEEAGCGAGHGFDCCBCHGACACEDHGHGAFBFBFAHEBEBEDGBHCCEAEADDDHDCBCFHAHCHBHBFBFBGGGBHECGFGECBCBCDHDBBFDCACACBFGFGEGCDEBFBF,False +962,27.0,19.0,27.0,18.0,20.0,32.0,29.0,28.0,GEGECAFAHHHHEAEBDBDCHHGHFEFHDBFAFBFDGDBCBCGHGHFCFCFCFDEGADHHCCADADAGEHEHGACCHGHBHEHCHCHFECGCFAFBFAFGFBCAEFCDHAGFBFHGEGAAHGFGEDEACDCFHDDCDCFCHCGCEDGHBDAAFAGBFBFHEGAFACADEFEBEGGGCGCBBFBFGAGAGAFABAGFBEHF,False +963,18.0,20.0,27.0,19.0,14.0,17.0,15.0,25.0,FFACCGCGCDDHCHCDGGGEHFBCBHFCAAAAHAGFGDGAGDGHFBDEDHCBCACACGCGAFEBBCECEAEHEHBBCHHHHAACDCDBDFCFBFBHCHBHDGCEEEHEDGBBBFEFHFHDCDBDADAHFBCBABDCEAHHDACFCGHBHFHDCFE,False +964,12.0,10.0,8.0,9.0,12.0,10.0,10.0,9.0,FGFAEAEAGADFEECEHBBBAHAEBECECAGGHBAAGEHFHDHAEFDFECDCBFBFBABDDFDGGFGCCCEHAHBHGDGD,False +965,17.0,22.0,24.0,31.0,26.0,22.0,22.0,27.0,CGCEHFCFCEBDBDBEHEHGHGHFABABHEHFBEBGHDHDFCBDBEBGGCHCFDFHEHDHDGDFFBCAHAHGEEFHBHBEBADFFAFAHDHGAGAHEDDHDEBEFEBEFHFHACADDDFDEEEECCCDAGADBGAGFEHBGGHDCCCDEDGHCECDDABFBEBCGEGCGCFCDCAAEDCBGHGDFDGDCDF,False +966,27.0,18.0,26.0,14.0,26.0,27.0,37.0,24.0,AACDCHCFGHAHAGAGACFHEHABFHFAGHBCBDBFBFBABFHHHFHFCEDEFACHCECFGFEFECGDGHGCGFGEHECDCBCBGBECEDFAEECAGGFAFBHEFDGBGEGHFEEGEHCGEGDGDGDFCCCCHBAEACHGHGAGHGAGEHEGEGBCAGGGFABHDADADAGAFHBEDCFAEECFGFGFGCGABEFGABA,False +967,19.0,30.0,23.0,20.0,26.0,19.0,25.0,21.0,BBABCBGGAGFDFGHDHEGBGCGBBAFDCBCEFHDCDFBCBGEFBHBEEEEEBADAHAHBGGGEDBFBHCCCECBGHDHDFGBDCDFBEHECGBGBGFCFAHEHDGEGEFDFDECCCHCHEGEGHGBCEAGABEBABABABADADABAEADCCEFBABFECDFHFHCHFEFCGGEHEHGDADH,False +968,22.0,15.0,29.0,26.0,37.0,20.0,22.0,24.0,AEGBABEFGGEGDHDHAHEFECEFACEEACHBECFBABCDCACAHGHDEEFECECDAAAEHGHGHDHDFGFHCADFDBDEDEAEDEDEDEDGGECEABBGFADADEHGHFECBCAEAEGECECAGDBEGAACCCCCCBHEGECDCDFHFHFHFHFCGEGHBDFEBBBGECHDEFEHHGDADCGHGDDCEFHFCFC,False +969,16.0,6.0,14.0,15.0,9.0,8.0,13.0,13.0,HHHHFEFDDCAHGGEGDGDCBBHCCDADGGHAAADADFDFDGDGDGABEBAFABECDHAAFAFEFGDGCHEHCDCGCEEHHHAEACCCCBCGAA,False +970,21.0,25.0,9.0,17.0,8.0,13.0,18.0,16.0,GBGHGACACAFHFBCADGGGFGFGAGAGBBDBGCHHEHEBFDEABGDGDGBHBCDFFFFHFHAHBDACAHDHCCGAEADBHBDFABABABEBEAECGGBHBHDFBBBBAFDDAGBHHABDDADADBE,False +971,9.0,10.0,11.0,9.0,15.0,9.0,14.0,12.0,EAEDFCFBFBAGHGHGDGBHBGFHEHCFAFAGHECGCHCADAHCEGDGCGBBBBDBDEGFGCCFHEEEHEDEAEDBCGHGCADHEFEAE,False +972,18.0,16.0,12.0,13.0,15.0,19.0,12.0,21.0,BEHFBBABAHGEEAEAFAFCDEHFHAHCGCFBEAAFGCABHHFHFHCHBGADCDHDHCHCEEAGBFDFGADFFFFBFBGDGAGAEADHDHDAEEEBCBCBHBDEEHGFGFBFBDEHCHGHAHFCAD,False +973,27.0,25.0,26.0,28.0,24.0,17.0,20.0,27.0,HCHEFEACGCFDFGCBCHADFCFBADCGHBHCDDDCBAAHAEEDADGDGHGHGHGDAAEBEHAHGDADADEBEHHCEBADAHHHHCHCAAAHBFBDCGBFCHEEFBFBFHAEADDBFBFBDGDEHEHBHGCGAHACECAFBFBEEEBECEFDCCABDBDEDEGAGADEDEDCFBBACHGGFGBGCGDADCHCBC,False +974,2.0,9.0,5.0,14.0,10.0,16.0,13.0,8.0,HBEGFBDBDHEEFHFEGDBFBFBGHFAFDFGFCFDBDBDHDHBGGCFFEGEGECADGFECEHFGDCDHDEDGFGFGD,True +975,7.0,10.0,11.0,8.0,6.0,8.0,11.0,11.0,CECFCDCHGGGGHGAFCECEAECDCGHHBADHDHDBDBFBFDAHGBBBBBBGCFFFAAEHDFCHGAGHCHGE,False +976,22.0,16.0,20.0,24.0,18.0,27.0,21.0,14.0,GDBDHEGEBFHFHDDCFCDAAGEFBFEDBAHGBGBGDFEBBADGHGFABAFAFDCDCBCAHADDDCAHECCDAAFAFGHCCECFGECECEFDHCHAHGBGBGDECECECEAEAEBFBFGHGHAADDFDBDGAFCFBHACAEEFGFAFDFDFGFGDCDGGFFF,False +977,16.0,17.0,23.0,22.0,27.0,15.0,19.0,22.0,EEGGFDFHCHEEAEDEHEHGCEFGBEBEBHBDDCBAHAHDGDAEGEGDHFECBDDDHDCGCFAAAAAFCEHBBEECEFDFDBDBCCCCEFEGAFFCFCFCEBEAHAHAHAGGHGHCHCBGEDBDGEEHCDGHBCBDAHFHBHFGGDHDEDAGECECBCDCG,False +978,5.0,8.0,11.0,18.0,14.0,13.0,11.0,18.0,HFHDBAGHGEFEHCGGEGDAAFHFEFEFDHDGCECHHEHEDEDHGHDFBFCDHHHAHEHBCBCBCDCDGDECEDGDEBFGDCDEBGHFBFDCDFHFDA,False +979,22.0,10.0,19.0,14.0,19.0,26.0,19.0,18.0,HBGDGHGCGBGEFEAEFBDEHEAAHGGGGHDHDHFGEABAFAHEHCACFFDFDFAFECGCDCDCDCFCHCFCHAHFDCBGAGDEHBGEAFAHAHEFAGHEAGACEEEFFFFEFHFBFCFBACGCAFAFCBEFEGEFCGBDDDCAAAH,False +980,9.0,10.0,16.0,13.0,13.0,13.0,17.0,6.0,CDCEBDGFGFACEBDHFCEHACADBDBHBCBGACCECEFEFGFGACHCACDEEGGGEGEGDGCFFFGFDBDFGGAGAHACDDDDGEGFCFCEHBBEB,False +981,19.0,23.0,15.0,12.0,16.0,18.0,17.0,17.0,ECEDHFHFHFAGAHBHDAEFGFBEHGBGBCBHBCEDGDCBHEAGADEGHFHDBBABEBAGAGCCDADHDCGBBBEGAGAGEBBBGFGFCCBFBFEGHAEGHFCFCFCACEDHDAAAAAHDBFFHFEFCBCBEBEFHA,False +982,21.0,16.0,13.0,14.0,20.0,12.0,19.0,12.0,EBEBGBGDGEGECHCHFAAEHBCAEBHBECECACGCDCDCDBABAFABGHGHAAEAHABDEDEFHFGBCDAEAGFGECDHGFGDDDEHAGGGEGBCFDFAFBEGECEHAFDFGABADAGAEBHFAEB,False +983,22.0,16.0,20.0,28.0,16.0,18.0,28.0,14.0,CGCGBDCDCGHACGFDFDGDBDCFEFEFADAECBDDDEAEAEAHAHABGDFAAGFGFGCAAGEDEGFDFDCGBGAGBGHHHGABCBDBDFDFCFDFGCAHAGACABAFEFAGEEDEHBCCHEGBBBDBDHGEDCHCEFAHHGCDHGGFGDGDGDBEGACDCD,False +984,26.0,22.0,19.0,22.0,24.0,27.0,32.0,24.0,ADHHEFAFADABADAFABCGCGAGFGFEDADABEFHFHGHDFGEGADCCFHHHGHGEFCFCEBDGEFEFEGAFBFBFAHGBEBEAGDFAHABAEGHGCECEHBHBDCFFHBAAGAEAGBCCDCDHDHDBDBGBEDDDCBBFBGEDFDHGEGEGEAFAGGBGBHEGBGFGDECHFAFEHHFCGCGEGCCHCHAAFDG,False +985,7.0,9.0,7.0,9.0,13.0,11.0,7.0,5.0,FCBCHEDFAFHEGBGFAEAEAEAFGDGDBDBABAFGEGDCHCHEEBFCEEHEBEDEFFDFGBDBCCFD,False +986,8.0,13.0,17.0,13.0,13.0,11.0,14.0,10.0,HGEDFDFDFDHDHDHDBFEFAGAEBEDGDHHFBBEEABBBFBHGHCCBCEEGECFBACDCDAAGCFCGBGFFEAGDGHCCDGEGCGCGCHCECBCACEB,False +987,20.0,12.0,18.0,25.0,18.0,18.0,21.0,30.0,AAADFHFAADFECBCECEHEHADCDGDGDCFHFHGCGCGFGFCFHDCAHEEGDGCECHCHEBFBHGHGEFHBHFGDADEDHDAFADEHBBBEGEFHADFDBCGDHHGHGHGDGDHDGDFCFEGGFGCAAEAEBHAHADBHEAADHDCECHDADHCHBHFHAB,False +988,20.0,13.0,12.0,16.0,10.0,14.0,25.0,12.0,BBBCHGHGAGFGHGDCACHCHCAAAAAAEHBDBAFDGDGDFCGGEBAFDEDEHEDGDEDADABCBFDGAGAGHGAEDBGGGGDGBFBHAAGBGHDFEFGAEECCGFFBFGFGHCHAFFCACD,False +989,12.0,14.0,12.0,10.0,10.0,5.0,11.0,8.0,AEFEBABAHACGFBABGBGDEDGDEBBCBCHCECBCACDCGHGHGEACFCBBBEFGDDDCDBDADGEHAACHEGAGFBEHAH,False +990,22.0,22.0,18.0,21.0,13.0,23.0,11.0,18.0,AHAHEFFDDCDFGHDFDECHDHABEBCBCEAFBGGGGFCHCBCHHBEDFAFABCHCBCBCBABDDGHHDBFGEEDADFECGBAECEADADADAFFDFBFBFBFAHDFDBHBDEAEFHFGAHAHAHACCBBABGCGCFHFAFDFDEBCA,False +991,10.0,6.0,7.0,9.0,6.0,4.0,5.0,5.0,FDCBCGFHFHBBBABGDFDAGACACEEECAHDDGDEAAADADAECECHDBGH,False +992,9.0,13.0,4.0,15.0,7.0,15.0,17.0,13.0,DEAHFHGHBEGEBBGFFFAFDFDHDGDGHGHFHFDDDCEGBACGDBDGDEHEHGHGBGBGHFBABABFFFAGADHDGGGHFACBFEDDBCAFB,False +993,1.0,1.0,4.0,3.0,4.0,6.0,1.0,3.0,EFEFEFAFCEGDFHHHDFCBCDC,True +994,16.0,14.0,21.0,15.0,11.0,19.0,16.0,24.0,AHACCCDCAAFBFEFBDBAAGAHHCHDHEHAHEHEBGAGAFHFCGCEFEFEDACHCHCGGGFDFCHCDDDHDHAECHGBGBEHCFBDBGGFHFGBAFHFCDADCFCBCBCEHAHFHBCEGGGFAHBHDCDFHFGDB,False +995,7.0,6.0,13.0,6.0,12.0,13.0,4.0,9.0,CEAFHCHFHECCHEACFCFGGAGFCHCHFAFEDHHCECFBDBDGECHDFEEEEEEBABACFCFDFDFBAB,True +996,4.0,9.0,13.0,8.0,5.0,3.0,3.0,5.0,AGAEADDCACBCBCDCDEHECCFHEDBCBCDDDFEBHBHCCCBBFHGCGB,True +997,3.0,1.0,1.0,6.0,4.0,5.0,7.0,3.0,DDDFHEHCGFGFGFGEDAGAEHFDEDBGAG,True +998,18.0,17.0,15.0,15.0,11.0,15.0,12.0,20.0,EBCFCHHAACHCHCHGBCBCBCHDADAFAFEFDFDGHGHCBCFFHCACDFAFAHAEAEAEFEBCHAFBHBFGAEDBDHDHFBCDEAGABBHGADDBDBDHHHEBAGCEEHFHBGGDGFGAGDB,False +999,6.0,13.0,8.0,13.0,6.0,19.0,12.0,12.0,GDGCGCHCAFGFEFBFDEDHFBFBDBGFDADBFBACGBGDGEFBHHHHBDAFGFGBGHCFFECEFEFBAHFDFBFDAHCHDHCHDFDGB,False diff --git a/tests/results/nb_gm_002_2back_240trials.csv b/tests/results/nb_gm_002_2back_240trials.csv new file mode 100644 index 0000000..1c50201 --- /dev/null +++ b/tests/results/nb_gm_002_2back_240trials.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,ralph_skewed +0,30.0,39.0,31.0,30.0,32.0,24.0,27.0,27.0,False +1,33.0,23.0,27.0,32.0,37.0,34.0,25.0,29.0,False +2,31.0,20.0,37.0,28.0,31.0,32.0,26.0,35.0,False +3,27.0,32.0,39.0,24.0,25.0,34.0,35.0,24.0,False +4,34.0,24.0,38.0,28.0,31.0,29.0,28.0,28.0,False +5,29.0,24.0,36.0,31.0,32.0,32.0,31.0,25.0,False +6,25.0,38.0,28.0,30.0,33.0,30.0,26.0,30.0,False +7,27.0,30.0,30.0,29.0,32.0,26.0,33.0,33.0,False +8,24.0,36.0,32.0,23.0,30.0,29.0,35.0,31.0,False +9,35.0,34.0,30.0,29.0,35.0,26.0,23.0,28.0,False +10,30.0,25.0,33.0,31.0,27.0,37.0,30.0,27.0,False +11,28.0,28.0,29.0,26.0,28.0,27.0,34.0,40.0,False +12,35.0,27.0,30.0,29.0,26.0,30.0,36.0,27.0,False +13,38.0,27.0,31.0,27.0,34.0,23.0,27.0,33.0,False +14,29.0,30.0,28.0,35.0,19.0,30.0,37.0,32.0,False 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+9,11.0,23.0,19.0,24.0,13.0,20.0,28.0,13.0,DFDDFDGFDGCDFFDFEDCCDEGDAHEEDGGGGDAGHFBHFGEDAFGCHGFDBCDBDEBCHDEBGEAFBCHEFEAFBHFCCGEDGADGBCBCDACGCCGFAGBBDCGDBBBEBBECHACFAGFBGABCBBGFHHFHHFGHGGDGGBGBCDB,False +10,10.0,15.0,13.0,9.0,5.0,13.0,10.0,23.0,CAHCFDCFBGFGCFHBHAGHABAAHGFBAFDFBDBHDHCBGEFGDCBDHDEABHHHHGCFCEFCDHCFHBHHGHHGFHGBBABCABCABHEHEFHDCH,False +11,29.0,21.0,32.0,27.0,25.0,25.0,8.0,18.0,HEFAEFGCBEBDCBEADAADADCADABDHHFFEDFBCHACAAFBAFDAFDBCCCFDCEACAACEABFDCFDCFHHFBHDEFDAFCABGAEFDCDCCBCCDCDFAEFDCGCCECCBCBHDEGACBAHBEBEEFDBDHAFHAEAEECEGGHDBHDHCDEADEAHEHFEBFCBAHBHDEGAEFFCFCG,False +12,28.0,27.0,32.0,14.0,15.0,33.0,26.0,13.0,FFFAAFBAHCHHDHGCBBCEBFDGEGBFAACBACBACBAGBGBAGFFGFAHDGHEEFCAAHAHHECFBBFACFACAACDBCAEAHDFHFFCFFEFCAFBEFBFCBCABDBGGFECFGCBCDGGBGFDGDABBCCBEFBEFBAFDACGCCEHGAFCABDGEDFFDCFDGFGGCGGEEGCBGAAGCCCHC,False +13,29.0,16.0,17.0,15.0,16.0,11.0,15.0,11.0,CBECBEFBDDCDCAACAABFAGFEGACCECBEHBEGADFADFBBABCAHCABAABHEEEACEHHAGHABACGDHGDFGCHGCAGDAFAAFCCFEAEBAEDFDDGEABHAGAAGDGBAEDHHGABFEGDCD,False +14,17.0,24.0,25.0,11.0,18.0,20.0,15.0,30.0,DDCDHHAABGECDACBCCFHGEDGAHBABBHFBFFBCFHCHECHECACABHHBHEBHBHDCHCFBAHBFHBEBEDCEDEABCHCHFCHCAFBFBBHGEHGEHGHFCHACHCGGCGCDECFEGHEDFBAFGEFDAAHAHHGFHFABGEBGABGFFEFCEBC,False +15,8.0,6.0,1.0,3.0,4.0,2.0,2.0,6.0,EHBEDEHGEGFABBADBAHCAHAABDAHHABF,True +16,20.0,17.0,20.0,17.0,21.0,21.0,26.0,21.0,DEHCHAEHFEDFDHFCHGCGGCGAFBDDBDCFGEFGEFCEFHDHEFFAGDGDEGAHGFECFACFEEHBEHBGHBGHBGCECEDAHHBGFCCCADHAGHDEDBADGHEBDCHCCFAGEAFAABGABAHBAHBGHCACBEFEGAEFCECBGFDGFDGAGBAGBFG,False +17,12.0,3.0,7.0,9.0,7.0,12.0,9.0,8.0,ADGAGCADCFDFHEFDGHCEHAGGCDAHDCHDAHAFDAFEGFACFECFEBFGBAGAFFAEBDEHGHF,False +18,18.0,19.0,24.0,16.0,21.0,13.0,23.0,20.0,GGEGFBDFGDGEDAHGFBGHAGCDGCAAAHACECDECEBBEDEEDECDFDHBCCDHBHHACBACFHEAEEGHEGDEGAHBAFBEEHCBHCBGGFCGECGECBCAFCGHCBHFHHFHDGGAAEBFCBFDBCBECDCADCACGBHGEHGBFGADHA,False +19,10.0,14.0,15.0,8.0,25.0,14.0,11.0,20.0,EEEEBEEFHEHEEFEEGHEAFFAFHACGDCDDCFDCBDCBFFBCEAHEAHGCGGHGCHEEAEAHEAHEHHCCFGHABHGFGCHGCFDFHEHBBBDFBFBCEAEBHCDGCEEEHBBHB,False +20,16.0,9.0,19.0,17.0,10.0,22.0,10.0,24.0,HFGDDAFEAFEDCGHAADEHDBHAHDCGBAHBECEFFFFFEFEEDHEDCACEGHBGCFGAGGABDHFCHFCHCCDCFHHADFCFFCFFCBFCDHHHHDFFGHHDACDAFDACDCBHCHHAGHABHAB,False +21,6.0,10.0,3.0,4.0,7.0,3.0,3.0,4.0,EABBAEFHEFABAACHDCDDEFBEGHEGBDABHBBCBGEB,True +22,6.0,11.0,12.0,6.0,9.0,6.0,9.0,10.0,AEDBCDECBCHBCBBGFBGFHGEHACHAGAEFBDAECHCFHFDCCECGBCGECGAHGBHBHEBHDFGDE,False +23,11.0,8.0,12.0,13.0,7.0,5.0,13.0,9.0,EAAGACDACDHEEGGGGGBEGEABEAHGCHCCAFCFFGDHGDGCBGBDDEAFAADCDDCDDHBCGBCAFCBDDHHBHH,False +24,36.0,26.0,18.0,26.0,33.0,19.0,21.0,15.0,GBCHFHAAHAFFGBBEFBCFAEFDFGEGEEBECBEBBABBAEBEEAEEABGDBADBACFFBEFCECGACFADABCFDCDBCBBHDHHACGGEHDEGDEGAHAAFAAEDCCHHDDGDDBDGBDBDDCDAGAAFHEDHGDACDACDBGEEACGAEEBEHAFHBGAAAAAAAEEFBEDCDAEEEFGEGGHGFEAFED,False +25,11.0,17.0,16.0,9.0,15.0,15.0,6.0,9.0,CEEFABDBGDBFDFFDGADECBFCBCCACFABEABFABEGBEHBAHEAHEAECCFFCHDCBBBFGBAGCDFHHFBDFDCCHHEHAEBEGCCBFEECEF,False +26,8.0,5.0,15.0,9.0,10.0,7.0,11.0,5.0,ECAGCHDBBDCCDCGHBBEEFDHFEEEHBHGADADGFDEFGAFGAFCCCCCACCDCDGGECGECGEAGFA,False +27,9.0,11.0,8.0,5.0,8.0,4.0,2.0,4.0,FCAFDBEDBABAABAEEAEHDBHCEHCDBCFBABEEGECGBDABFCCAHCB,True +28,6.0,8.0,11.0,7.0,10.0,5.0,9.0,9.0,CFBCBCCBACBEHBEGCADHDGFEGFHGHDAFBAFBEDCDGCHGAACHCHBCEEEEDHEDGEGGH,False +29,24.0,16.0,18.0,25.0,13.0,19.0,26.0,18.0,HEFHCDEGDHFBACGGDEHDGHDGFDEAHFDHGBHEBGEGADFFGCCGDHFBFABDACDABAGFGDAGDAGCAFFAGHHCDHCHACEDDAFDCCDCAECAEDGEDGAFGFCGFAGBBGFBDBBAABAAGADGAFCHBEEGHBGCBFCGFAHHCHDBDDE,False +30,6.0,5.0,2.0,9.0,2.0,4.0,3.0,8.0,DADBAFBDFHDHHBAHEADGFBHFGHEAHDHBDGDCADC,True +31,19.0,18.0,16.0,13.0,19.0,13.0,14.0,15.0,FCHGCAEHAEBDEBABAABHAFEBDCBDCBHCGEAGEFBAFCCECCBCFHEHGEGAEDAECBECEAFEBDHBDEAGFGHDGCDGADFAHGCFCBFDEHEGCEABFADHAFHGBHABHBHDAEBGDFG,False +32,7.0,12.0,12.0,10.0,7.0,5.0,5.0,9.0,EBDGBGBBDCBACGHBDAAHEBGCBFHBFGAFEHFCCCHDCHDCHDAHDCDDEBDEAFECBAHBECC,False +33,1.0,4.0,8.0,1.0,4.0,4.0,5.0,3.0,GAECEGFBHFGHBGCBFCECCECCBCHDGF,True +34,5.0,4.0,6.0,9.0,13.0,13.0,5.0,7.0,CHHEFFDFFDFFDFDGGDFGDHCEAEAHEAFEBFCFEEFEECAECHCHFDEBDBGEGABDEH,True +35,3.0,2.0,3.0,3.0,5.0,4.0,0.0,6.0,CBDEEHHEAHCAEBDFADFHFCHFEH,True +36,13.0,2.0,13.0,8.0,7.0,6.0,16.0,9.0,DEGDECDHGAHGEDGEGACAFCADGACGACHFDACHCCHCEECGHDHBEGGGGCADCAFAGFGGBAGCAHFHFA,True +37,18.0,19.0,17.0,17.0,13.0,17.0,15.0,23.0,HBCABCGHCEEADEDCEDGAGFFFHDFADHHBHHGCHFHHAGHEHEBBBDEFECFEBHCDAADFGDFHDCDCCDCCFACAACHGGBGGBFBCFBFFCFGEDABDBBDAAGAABACBEGBAHAHHFGEDGHDHHEBHBHF,False +38,4.0,6.0,5.0,9.0,6.0,4.0,4.0,6.0,AGDAGHABHCEEFBEFDEHDBHDECDFCDBHDEGBBGCCADFDH,False +39,3.0,5.0,6.0,8.0,8.0,2.0,8.0,6.0,DCEDEEGEEGAAFEHFGHDGDBHDBGBBGECECDGHBGCDDCHCAH,False +40,0.0,0.0,1.0,3.0,1.0,3.0,5.0,1.0,GDGGDCEHFGFDGF,True +41,20.0,19.0,22.0,21.0,30.0,22.0,10.0,26.0,BADBABGCFGFDDDADEFHAAHAAHEAHBBHECFGFDEHDCDBBBHGEDEECCDCCDGCHHBGHCHACFDCFCFEDFEDAHHHBHAECABDABAAEHFEADCFEBFAGFGEABECFEFFECEEFEHFEHEEHDHDCHBBHBDHCEHCDHBDCFAEFAGHEGECBCFEEFE,False +42,3.0,7.0,4.0,4.0,5.0,2.0,5.0,3.0,EBBEAEEHDCHDCGDGGBACBEHBDGBAFBFCG,False +43,21.0,15.0,21.0,27.0,18.0,33.0,14.0,23.0,DDDDDDBCGFEFFABFDHDAGCEFHHACHGBHGBEFEHFEHFCFFCHDGHDFHDAGFECCCAAEAAGHGDFCHFCHBBBFABDEFDFFBBDBAAFDAFAGHACHACEFFEFDHABCAFGDFEDCGACFADFDDFBHFAFFBEHBEHFCHEADEGHEGCDGHDHDEECCFCCD,False +44,27.0,34.0,20.0,19.0,15.0,29.0,27.0,26.0,FGCFGADGADGDDBDBAFGAFDHHHAFBAEEAGGBDBFCEFAHFAHFAECDCBBCGBHAFHABHDCHAHHGBCGECFDCEHCFBCHBGHCABFBCFBEHBECBAHBGDECHFDFBDEAFBBGECGEBBHDBHDBEABEBFCDFHHFGHFAFFGCACFGDGGHGAABCDBHBGGBGGFHGHGGBEADABFABAAFAFF,False +45,15.0,12.0,15.0,7.0,7.0,15.0,11.0,5.0,CAFCDGCFACFCCFACGBBGCAEAEGAHFADBCHACHFCFBEFGEGBDGBDGBEGEHAEFGBFCDFBFBHACAFCAFGABDAFACDB,False +46,12.0,10.0,7.0,5.0,4.0,11.0,11.0,13.0,ECFFHGFGGFCGACGFGGAHFABBHDEDCHABFBHGAHGAHCAHDABDFHDFGCHGBEABAHEHBFHBFCBAA,False +47,15.0,6.0,13.0,11.0,17.0,21.0,13.0,9.0,EDCEFAEFAFFAGHCFCEEAFGFFHFDECECCEGCDGHDGHDGHACFFCFFCDFEHEEFEEGHEDAFBGEAAHAAGCABAEFAFDABGFCFHCDEDBABFGBGGD,False +48,11.0,17.0,17.0,9.0,17.0,17.0,13.0,15.0,GAFGHHGCHBCACCFBCFHHECHBHAFHEEGBAFCAGHGEFGEDGFCBBEBGABCFDCFDCFDBEEEGAAHDAEDFECBGCBHDBFEGHHBFGBFEBFCBCCHEFAEDAEDCEFHB,False +49,13.0,16.0,15.0,12.0,16.0,9.0,12.0,15.0,BGCBAEBCDBEDBECBDCBABDCDFCDBCEGDABDFFEHCEDGECHACHEBDECDGHFFHFHEAHAHHEFFBAGAGHCHCCHGCEEAAAAGEEGDEGBFGBAGBHHBH,False +50,13.0,6.0,16.0,14.0,12.0,13.0,9.0,12.0,DAEAAGAAGCHCCHDFHEFCCBEGFEGFHAHEAGBGCBFCBFCDACDAFDCHECEBFBAFCFFDEHAGHDEFDGCDECEHCHDGADEHHFADCDD,False +51,22.0,27.0,26.0,19.0,24.0,22.0,28.0,20.0,FDCGDAACFACHGCDGEBFCBDCBGBEGBEGAGGFGGCHGDHGDCAACHADHCFHAAEEBBCBCCBAEDAGBFGAFGEGGDGHCEEEDEHCBBCDECEBGEFCCHCFBCFBHFEABEBDEDHABHDBFFFCEFCEDHFFHBFABHAGGECAEADBGGEGAABHAGHAGEFGBFBFHHDHBEGBFCCDD,False +52,19.0,24.0,24.0,17.0,11.0,20.0,12.0,18.0,FBDFCFECGDCFBBFHBFHBAHECHAAHAFCAHCHCFBDFCDHCDBDDBAGAAGAGHFGBDABCFEEAHHGDHBDCCGCCDAEBAEFEBCHBHECHDABFFBHECFDCBDBFDGGDBFABGHBGFCFCBDCBACBFGHEACEACA,False +53,11.0,13.0,7.0,11.0,11.0,7.0,5.0,12.0,HABDABEADFFDABBHBEDAEDACBEHBEGBDDEAAHAHGBHBDEBAEDECCHFDHFGHFGHFDCCEBHEBHGCACF,False +54,11.0,20.0,14.0,17.0,12.0,15.0,15.0,22.0,DFABFDGCDCDDCBHCBECBDHHHBEFBGFEGHGFHEFEAFAHDBHDGDGEDFBAFBGFBGAGGHHCHHEDBDDBCFFCGFCHEEECDDADHBHHCDHCBHFAEGBCBBAHBAGEFGAHABHCBHG,False +55,17.0,24.0,24.0,12.0,23.0,20.0,17.0,26.0,GAECBGBFHAHHEFEGCGFBGBCHHADCACHBGGBHBAHBAEFAFGGFBCCAFCFHCGHCFHCBEFBEFBCHBGFECFGDHBEHCCACGFHEDAEBAEDDEDCEHBEBBEGEEHHACHECBDFFDFADFAEFHCFHCBECDEHDEHCBAGBAGADGBCBHHEH,False +56,17.0,25.0,29.0,22.0,21.0,19.0,27.0,22.0,FFFFFGGHDEHDFGAFGEEAFEGCEADDBBDHDCHECDGCDAAFCDHBGCBGBBECCDCCDAHGBHCBGCHCCEFEGFAABBEHFEHBCGFHGCHBDHCDHCFBDEBEABEDBCDGCHCCFGCFDAGGBGBBCBFABFEGGADGHEGHEDFBBCBCGACDAEEABDADGGEGHEGCCHHAHH,False +57,12.0,11.0,4.0,15.0,9.0,3.0,6.0,8.0,HABCEHAECBEDEDDHBDGAAFHAGCBGBEAAABADEADGHDFBAFBDEBEEBGDCDDGDDHDAHDBH,True +58,9.0,8.0,9.0,9.0,4.0,9.0,12.0,13.0,CAGCGGCBAHDEFDHHGHDFDBFBBFGAFEBFECHABGGDGDEGDHGBHADGFDCACAACHBFHFGHCHHCHA,False +59,15.0,19.0,20.0,23.0,14.0,16.0,21.0,18.0,GDGGBGGCFGABBABFGEFGCDDCFBCDBEBACHABGEBCDCCDFDDFDAACEBCEGGGFHHFDHGGHFGADHFHHGDHDFFGHGGHDEBDCAACGACFADDHDDCBDBBFEBHDDHFCEGBEHCABEAHEAHEFCCHBAEBCEDC,False +60,9.0,8.0,2.0,6.0,8.0,11.0,5.0,10.0,FEBDCDFHFEHFEHEGHBHFBHFEDCHBBBAGEAGEAGHADABFHFFDBFAEFADAAHG,False +61,26.0,25.0,20.0,16.0,13.0,13.0,17.0,12.0,CBACHGCFDHEBHBBEBBFAHCCEAEEABDDBDGEGADGHDAHEABBBEFCFFDEFDAGDADBBHGGCEGBAADABCHGCHGBDBBGCBGCHFAEFCHFBFDDCAACHACFACAACABFEBFAAEGGCGBCGBAGBDDACAA,False +62,9.0,9.0,5.0,7.0,5.0,5.0,11.0,6.0,FAADDAGBGGBGBCHBCAGEADACGAHGACFECDABBFEFDGGDFGHBGHDEHBEHB,False +63,7.0,8.0,8.0,6.0,13.0,12.0,11.0,4.0,GGBDGFEGCEGCECHDCFGFGABGFEHFCGGBHFBHEGEEAEEAFEDBCFBDFDEADACBABFACFEEF,False +64,20.0,11.0,23.0,13.0,16.0,11.0,12.0,18.0,AEDAHACHEFAEFAHCAEDAEDCBAGGCBGFBCHCHFCEACHCEHCFHCEAEAAEAHCAGBDCDHCEHEGBFCHHCGHFBHFAAGEADHBDCADCFDGFDCHDCBGCGAAHCGFGDEBDEBECB,False +65,19.0,12.0,22.0,18.0,18.0,14.0,20.0,17.0,CCDCCAFHAECADDGDGACGADGHDFHEBGEFEAFDHBDGBCGCFHBGHEGAEGBDHFDFDCGDHGDAGDCBHEBHEBGBAFHGCGCCFEEFCDCCDCHECHFCFAAAGECHBBEEBHDAGAAEAAEAHEGHCFCEFGAD,False +66,26.0,13.0,22.0,33.0,10.0,21.0,25.0,20.0,CDFGDFAHFEHDHBBCDECDAHDGGGFBCDBADHHDGADEBDEGDHFFCFFDHDGADHCFHDAGEGCEACGBGGEAGFAGBBDABCABGADGAHADDADCADHAFCFGDGEFBEAHDCGDHDCADFADFGHCCHGFHCFHGDHGHGECCCCCADBFDGAABAFDAFDAFC,False +67,3.0,0.0,0.0,5.0,2.0,3.0,2.0,1.0,FDFEDHDGAFGADEAD,True +68,21.0,30.0,10.0,18.0,20.0,13.0,15.0,10.0,ABBHBEEEHDEHDGFFGDBDBBCABFGDCCDHFHHAAAAABFAEEDBEDBGBBEABEABFBBFBBDDAEEAGCFHEBAFAGDGGBBEDBHDFEFEEBEEBABDHBFBGCBGCGGBGCCGCEGAADAABCDDADEAHF,False +69,23.0,30.0,20.0,17.0,29.0,22.0,24.0,20.0,BHBBFBBEEAEGAEHBCABCBGCGEFHEGHFFBFCBFCHEEDEGCCGBCHFHBAACDGBFBEAEAFEHFEHGHGGACBEDDDBDFBGBAGBAGEDGEHAEDDHGDFEDFEHFACCAEHFBCGBCECFGFFAEGAEAHHBGABGAEGDCGDCHDBBEFAECDHCDHABAFBACBAFBFGEDEEHGB,False +70,16.0,21.0,23.0,21.0,35.0,31.0,21.0,19.0,FEGHEGHEHFBHEBDEGDABDAGFAGCDGCEAEABGGEFEBAEBHDFEFACFEHFHHEBFGGDGBAGBAEEAFBACBCBDFFDGEECFEDFEAFEFFEDFBBFHFFCGFBFCECEHCHFFHGFDGFHECEGCDDBDDEECCBDHADHADEEEECDBCBFHGFHGBCGFCHCCBGDEEAEHAECDCCF,False +71,21.0,21.0,25.0,23.0,34.0,29.0,19.0,27.0,CGCABAFBECCEGAEFEEHEDHEFBAFBFFGFDCBDFHDFDDHCCAEGAEGEECFCDFGDHCDAFDFFHBAEGDECFHHFHHEAABFABAAHCCCCHHGBBCBHGGHEFDFFCGFDGHDAHAGHCEEBBEDBEGEHBEGCHAEHDEHFEBDECFHABHABAAFDDFDDFBEFGHGCEECFDCDCEECEEAHEGHEFBBG,False +72,26.0,9.0,19.0,24.0,24.0,27.0,21.0,27.0,DDGBDCADHEDABHHHAEHAHDCHDBFFEEFAEFAHGACFFEEDHACFCCFGCDACDCCDCEDBADHFEGDHDFHGCHFAEFHDFGFGEFGEGGEHEHHAHFEHCAAEAFCHDCFFFGABAFEAGGBGHCHDFHDAAGAFCADGADHAGHBGBBEEEGEEFAEFAEFCGDCFDHGDH,False +73,24.0,24.0,23.0,19.0,22.0,18.0,26.0,30.0,HGFHGHHBBHDBAGCEDEHDHCDAAGCBCCHCCDGGHAGHGHHFAEFGEGBEBFDFAEAHBBHBDCBDCBCCDECHHFHDDHCGAAAAEAEEDBGDBGCFACGAHGDFGCGHABBACBAHGHHBHGBEDDACFACFEBFGHCAEBGEBGEDGEDHEFFECEEAEFGGHHFBBFCHFBAFGAEHACD,False +74,26.0,17.0,19.0,17.0,28.0,19.0,13.0,23.0,EGCAHEHHEHABADBADECBECEEABEACFACACFFBFGBFBDFCFCCACAHEBHEGHDBHBBAFEADEHBCHEEHEGBFGBFDCGDEFDEADEDHEAAFFEFFHHFACDCCEAHDADDEEEFAFGADBHEBEAGAGDAHBCHCGHCAHGACGEEFAHGHHD,False +75,3.0,1.0,2.0,0.0,2.0,1.0,0.0,4.0,EAHBCHCAHEAHF,True +76,10.0,5.0,4.0,6.0,10.0,5.0,10.0,8.0,HGHHAEEAEDAECGDCAHGFBGAGEFGFBEFAFCGCEAEEBGEBGDDHDBHDAHGAHA,False +77,6.0,2.0,4.0,1.0,4.0,1.0,1.0,0.0,AACCDECAEBAEBAGFECA,True +78,26.0,21.0,24.0,22.0,21.0,23.0,16.0,22.0,AEAFDAFGAFHAHCGFCGFHDCBDCBABADBCDGGFGHEBBDFBFFDCDEAEEGGFHAHDCDDBGEHCEFCHFGEFDADGFHFBDFCCCBCGBCABDFHAEBCHBCHBCDECEGFFAHFAHFCHFDDCAEHAGHBGHBAEECDDDDAABAHECHEBHEAHABGEBAEACEACEAF,False +79,23.0,23.0,29.0,21.0,13.0,23.0,22.0,17.0,CDHBACEAHEFDEGHAGAAGFAHFADFCBBBEFBCDGFBCDBDHGGGGCGFBDBBCFBFDEGEEHEGGBGEHFCCFCBDCEDAEABFDHHBFBBCAGDDCHDCHDAHBACAGCAGCADDBDFHAFCAFCGHDEBGHBCHGCHFBEGBFACFCCACAADACFACFCCFGFDG,False +80,12.0,12.0,23.0,9.0,27.0,13.0,18.0,19.0,EGFECEECHEBEEHHFBDCGCAACFBCGEHEEGCEACEGDEADAGBAGBCDBFBHFHACHCDHCDHCECCEGFHGFBABCGDCBDCEACHBCGGAEEAECFEHHAFFEEFHFCEFCHGGGGDHBEHGGHEEHE,False +81,25.0,15.0,14.0,17.0,20.0,16.0,15.0,15.0,DGDFFBFFCAFHADGAEEAFDABDEGGEBGDGEDEBAHAAEGABAHCACEACAHBAGGECFCDDEDBEFHEBGAFCAFCAHDEHDAFAGFCDBCHCCHCEDBGFGHBADBHGBEAAHAAHAEFECFEDFEDHEBHGB,False +82,23.0,16.0,15.0,28.0,9.0,16.0,15.0,26.0,FAHGHHFHGDHGDHDHCCHFBHEDGDGADGBDFDHFBBEDBADEDDBDHFDACDBFGBFAHCDDDGDBGBBGAAADCHFCHCDGABFHDDHDAEDCEDCGDFEAAEACHHGHDGCFFCHABHAHHAFCFHAAHAACBABBHFEAGEAC,False +83,16.0,17.0,21.0,14.0,11.0,17.0,24.0,19.0,EGHCBBCBBHFAHAAGAFGHBCDFAGFBDABDADEEDBCDBCHBCBGEGFFGFGGCHGCGGHHADHDHCDHAFGACCEHDGHFFCDFEDAHDFFAFFHEGBDGCGCBECECHBGHGGHCGBCHBCEGFGGFCACAABAE,False +84,25.0,24.0,34.0,20.0,21.0,23.0,18.0,22.0,GCCGAFHHFBGFBCFBDFBGFCGDEGCAHEBCAFCBFHEFEDCGFCAFCHCHBCHEAHAFBAFDAHBHBDGAABAFBACACHHCFDAFDGBAHBEBBEDFCFECAEBGFHECCCCCCHHEEHAAFDGFDHBDGBEFBEDDHDDEBHECCECCEBAEBAGACGEDGADCBCCGGCDEAGCADCAFHHD,False +85,14.0,17.0,15.0,14.0,15.0,14.0,16.0,10.0,GGCGDDEBFFHGFBGFBHFHHEDAACAABGFFFCDBGBEHBEDBFDBCDCDGCDEFBCHBEGBEGBEFHGFBAEBCEFAAGGCHCCFCCBCHEHEAACADDEDDAGDAGEAEBAG,False +86,5.0,2.0,1.0,1.0,1.0,1.0,3.0,1.0,ADFAGGAHGBEABCA,True +87,28.0,33.0,23.0,19.0,20.0,25.0,30.0,22.0,FFGDBGHBGEGAADDHGEEDEHBBACDFCGFCGEHFBBFHBFBCCGCCFHDFCGHBECBAAFFDBBCBECGGFEGECCAGABBABHAEHBBHBHDEFDCHDBAFFDDFAAHAAHCDFCAHEAHGAHFAHAGHAGAAGEEDFGBEBECBGCBAFBGCCGAFAAFHAGGFGGBGGBDEEGEGBFGBFHBCHBDDBDDBECCA,False +88,27.0,30.0,28.0,20.0,23.0,12.0,23.0,29.0,EGBCBBCEBCHHGDBECBCDBEDGEHGAGACGEHGCDACFECFCBHBBFDAHCACBACBEFGGAGGADAAEBAHDFHDCDBAHCHHBHABGCBEEDHGHHGFHAHDAEDABDGCDECDBADBHHGHHGFGECBEABDHFDGAHEACFGCAGCABCHBFECHCBFCBFAEABDAGEHEEAECABDHBHHCEBG,False +89,14.0,15.0,7.0,17.0,10.0,11.0,15.0,9.0,CHBADFABGHBGFGGAGGADGDEBHADHGHGFDFDDCDBGAAGHAGFAEEBBEDBEBCEBFAFDAFDFGDEADEGDFACCCGBHBBHABHDEDCBDFE,False +90,5.0,3.0,3.0,1.0,8.0,0.0,6.0,3.0,CCACEGHEGDEGBBAHEHGBAGEAEEAEG,True +91,0.0,0.0,4.0,2.0,4.0,2.0,2.0,1.0,GDCFDCEECGEHFEC,True +92,14.0,4.0,7.0,10.0,8.0,6.0,12.0,5.0,DCDAEFAFCECEEAFEDFEGCCGACBDGHFAHBGEBGAGGAGGDGAEGHHGAADAFDADDCBAHDA,False +93,10.0,8.0,8.0,3.0,8.0,14.0,16.0,15.0,FAGFDGHDHHEHEEGGFFACFHEHACCACHFGHFGHCGCAGCGBCFFEGFGBHABHFDHGBGBHABHAFFAGFEHEEBBAGG,True +94,21.0,25.0,21.0,30.0,27.0,13.0,12.0,17.0,HHBEBCAACEABDGDGBDFBGFCAEHGDCADCHDCEDFEDCEDGDCEDAEGEHAADBBDAADHCDHDFHBEEBEEBCEGAECDEBBCGAHEBBFFHEBHEHDAHDAECFFDFEDFBDABDCCACEDEBDHDDAGFAEABECBHGFDDFEDCCBHCBHGBEGBACBA,False +95,4.0,6.0,6.0,8.0,7.0,6.0,6.0,9.0,EDGEBHEFHACBBCFEGHCHDAHDEHDBHDBDDEHFCGECGFGBFACFAHGD,False +96,8.0,5.0,5.0,6.0,5.0,8.0,12.0,12.0,AFACCAGAGGFBEHEGHECFDFFDGFHGAHGHHFDGAGCAGEFGHBBHEBHDDHDHHGCBA,False +97,20.0,25.0,21.0,20.0,27.0,26.0,25.0,26.0,BFCFGDFBECHDCEBGEFGBABHGDDGAFBEBCEFEEFGDAHFBHEHHCHDDHGEFDFFBGBBAEGCCFDDABEBBEBFHBHHBCCECEDCAFCGFGHFCBGHBEAFCBFDEEAEEAFECEBBGGAGHBDHFHHFHHFHHFHHEEHGCDABGABGACGAFGAGGDDEDDCADCFGAFGDCAHEAHEAEGC,False +98,4.0,3.0,1.0,1.0,6.0,1.0,5.0,3.0,BBAHAEDECGEAGBAGEEGHEGHF,True +99,21.0,17.0,15.0,21.0,17.0,23.0,10.0,21.0,AHDDHEDGFFGCFHDHAGHGHHDDFADFABHDBCCACAAHGDDFDDFGBHEBHBHEEHEFCFFBBDDBAABCEEHDACDHCEEAAEBHBFABFABCABFFFFDFFDFEEFCEHCEBDEBFCAGAGGDGCHBCHAAHEFFECAADH,False +100,21.0,17.0,13.0,22.0,21.0,22.0,21.0,31.0,GCAADDGBDEBDABDGDGGEADEDDFHHHEHDGHFGHFDHGAFAHEHDCHDHFEBGEACDACGABGABGFGGDGBHEEHEFFGHFABDHEDAECBFHAGHAHBAEAAEAFEHFEBGGBCFDFEEAHCHHCFDAFDCFDBFHBAHCHHFFGEHDECCGCBHFHHFBHBE,False +101,3.0,4.0,2.0,2.0,2.0,1.0,2.0,2.0,BCFBEABEABHADGCHGD,False +102,3.0,5.0,4.0,4.0,2.0,1.0,3.0,10.0,BGHBGHCCHCDHEHHABDFHDBHEGCDAHBAH,True +103,22.0,16.0,17.0,17.0,11.0,10.0,13.0,12.0,DECDFCDFEDCCBCCBCADGAGFAEAAHHCGECAAFHAHBAGEFDEFHHGGFBFCBACBABDACDAHDAGDGBDBADHFDBCEHGEHGDHABGBCEDEEHBAABADCGGCFCABDABA,False +104,12.0,15.0,10.0,16.0,25.0,15.0,20.0,17.0,GBFDCFDGDDBHDAADEBGBDEBEEFGHFGHFGHCGHEGDEADHBDHGGBGHEDCFHAAHACHGGEGGEFEBFGADCCEBHEGFEHDEHEEFAGDCHFEEAEEBCEGEDBEDBECBFFBHHCAFAEGAFB,False +105,7.0,10.0,8.0,8.0,6.0,8.0,6.0,10.0,HBEHAGHFGHBGDBAAGCDEHFEBEHBEBCABAACDFHBCHDFGDFGDFHCHCCACBFDBEDF,False +106,17.0,20.0,9.0,15.0,13.0,17.0,14.0,15.0,FBEAGDAGAABAHBGEFFBFFEDHEGHEGHEFHFDBBCBBDBCHCAHGAHCHBEGFDGFAEBAEGADCAHBDFBDFDFBABHEFGBCDAFDBCAGCFBHFBAFAEDHEDCEDHBDGGHGA,False +107,5.0,5.0,1.0,5.0,1.0,5.0,5.0,2.0,FABAAGDGFDFHBFEBAGBAGBFDDHGDC,True +108,17.0,16.0,20.0,15.0,16.0,19.0,21.0,30.0,CBHCHHDDDGADGAFCEHEBHEFEAAEBHFHCBGFAEDHEFEFFCFFAHEHHAHBGCDCHFGHBGFCGFBEABFBHHGHHGCHEAHEADABGHBHHBDHGDHGAGGBGGEFCFFCDBGDFDAECEECGCAGCGDCFDFHHAHHDHBBCCACGAC,False +109,19.0,26.0,19.0,10.0,27.0,23.0,8.0,14.0,EBCAAAGFADFADFEFBBBCBEABEABEAEEHEEHEECEBGACCAFCBHCDCCECFBCAGGAFEAFEFBHHBDFAHEHFEGFHCFBBHCCABCHFFBFFBDGCEGEBAEGCFFEEDHFFBFBADBDBBDBBEHEEFCHACBAHDEE,False +110,19.0,10.0,10.0,17.0,15.0,14.0,13.0,9.0,EACEADEDDGDAEBCFACEAEBFHFFGDFEDBBGBHGCADCFBBBHCAHEAHFAHAAHCDGCDGAEGAEGEDDFGEAEBAGFCGDGDDABDFCDFGFFAAEDFEHAH,False +111,6.0,10.0,13.0,9.0,4.0,7.0,3.0,10.0,CCCAFBAFBEHDFBCCBCHBCBCGHDAHDAGDCDFCHCEHDAFDFHDHHDEEBFBAGBCHBC,True +112,14.0,15.0,18.0,9.0,20.0,11.0,10.0,7.0,DEFDEFBEACFGEFCACCBGGBHAAEBEHCEGGEDEEFEEDBECBABGADFADFADGCHCCHCHACEDHEGAFAEFBFBAEACCAEBBGBBGEBEBHCCDCCFC,False +113,18.0,25.0,13.0,24.0,29.0,22.0,19.0,30.0,HCAHEABDACHBBDDHADBEHEEHCABCFBHFBABBABDHBEHFGAFGFHCHGCAEFHEFHGHCGCEHDDFEBFEFFDDHDEEDGEFCBGBDGAHHCHDCFDEEDGCFHHFEEFGBGGEEHBFAGFDHBEGFEDCEDEBDEFHEAHEAHABBEDBGFBGEHGAHFADBADHADHEDBGGB,False +114,13.0,9.0,15.0,32.0,17.0,18.0,11.0,14.0,HDHDDAGGFDDFHBFBCAEDGEDCEACDDEEDFHFAGFDECDCCDFADECFECHDCHDGAGAHGHDFEDCEDCEHBHDAHDCFDBFHHGDBDAFCGFAHFDCCDAEDGEDEEFADFAGFBBDEBDEBDF,False +115,21.0,18.0,26.0,25.0,21.0,27.0,25.0,34.0,AACCECDFFBBDABHAGHGFHGHAFHBFHFEHCBHFDAGHAGEDBEACHDCAGCDCCDBEDBDDEGGEHGAHFAHDBFGHFGCDCCFCBFCBHCHHFFDFGEEEDHFHHFHDFEDFDCBHAGAAGHBEEDCFFCHEDAEBAGDEGDEDBFBGCBECHCGHCDAGGAHGHCGHCFHBFHCFHDADAEGEGHCGAFFEH,False +116,25.0,15.0,25.0,18.0,19.0,11.0,22.0,30.0,BGGBGDHGBAECHEFABDHBHHBHDADBEEGFGGDGCCGFCHHHAHAFHBFEEGEAHCGEAGDCCHCGDAGBAGBAEADBADHADFCGHEDHCABCHHEHDFHFAHEAHCHCAHBDHBGHFGEFCAGCHGAAACAACHHDHCCGECEDDFCDACDACBCCEEGEE,False +117,28.0,24.0,15.0,28.0,23.0,30.0,14.0,19.0,CHACHAGEBEFDCFAGFADDEDDBDGBDBFEBEDHHDGDECDEBFABFAFFABAAHHAHHDFHFBHDBEDADCBGHEDFFDEDDEBEBAGADDFFFBDFBFFBFFBHACFDBFDFAEBACBACGEGGCFAFEHEAHECHBDGGFCAECFEFHEHHAGACBDCBAHAAEAAEDECDAFGGFB,False +118,0.0,3.0,1.0,0.0,4.0,1.0,0.0,2.0,FHBBEEBEECH,True +119,15.0,14.0,10.0,15.0,7.0,12.0,18.0,9.0,BGDBGBFEBDCFAFFADCGGAGDABAAHHAHHACEBCDDCBDAGDGBBGDGDDACEFCFFCGFHGBEFCGACHAGAGHAGDABBEEFHGFBFDBEDGHDG,False +120,18.0,23.0,21.0,12.0,21.0,14.0,26.0,15.0,GBBHAAEBAEHEEFEGFGCAECABAGCADBEFAAGDABCAGGFGGCHGCHGAHEAHFFCEHCEBBFBBEHBCGECGACGDCGDHGCGGHGGDDGHACBBGDBDECDCFABECFEBFECEBGBBEDDEGFCDFEGBHGBHAHFACEBCHBF,False +121,18.0,17.0,15.0,11.0,14.0,12.0,17.0,17.0,AGGAFDDFCDBBHECHBCHADHCBACFACDDGFACEBCBBGBHAAHEAEEHGFGCFGBHEBAFHAHHADHBEGBHHCEFEEFGHFGFGCBDCADGBDHHEBEBBAADAAFCAGCGGEGGEC,False +122,19.0,12.0,14.0,16.0,13.0,13.0,22.0,12.0,DFAEFDEBHGFEEDAEDFGGCGGFGGFGGAGGAFFDEAGEAGDBBABDHHCHHBDHBDGCGGDHDAGCACCBFCBABHEFHCCHECBCGDDAHDCEEFACFBCAGDAGAAGAEFAGDBEHA,False +123,3.0,8.0,5.0,11.0,9.0,10.0,4.0,11.0,EBFFHHFADFCHFGHEGHFGFACDEDDEGHFAEDHBDEBDECDCDDFHBFEBHHBCEBHDB,True +124,4.0,5.0,6.0,11.0,9.0,6.0,5.0,8.0,ACEACEADEDEHDCFFCDCCEHHEHEBHGBDGHDFDFEGFEDBHDHDBBGFAGD,False +125,11.0,14.0,19.0,12.0,21.0,14.0,17.0,9.0,CCDCBDBEDHEGHAFEECDGCFGCEGCBGEFAEDACCHCDHGFEFFBBEABEAHHAFCCFBFFCFCBEGDACDGCAEBAEGGEDGEDCAGGEDHEBHBBACBHGFEGEGDEGEFCBF,False +126,7.0,15.0,16.0,15.0,17.0,19.0,21.0,17.0,CHHHDBCCEFEEBEGBHFEDGEBFFBGFGHHGHHGEHDHCDHCDFAFFDCABAFBHGBCGBFHBDHCEGAGGHHGDEAFECHDBFGBDBCDECGEFEEBECBDFFDECGGCGADGEDGFGCFGCFAF,False +127,1.0,2.0,2.0,2.0,3.0,3.0,7.0,2.0,BEGGGGACFHCFHEFDGGDEGB,True +128,24.0,27.0,28.0,25.0,25.0,12.0,31.0,20.0,GGGBGGBDBCDHGACGEHDCHDCBDCHHEHBGHADDADDEBGGHGDDEADFAHFAGGEGEEABEHDEHCEBAEBECBACBACGACGADFADBBBBFCCAEGHFBEBCAAHBCHFCEFCDFCDCCBAEGEGCAGCGCCGEHFEHGCCACAACBDDBHGBEBDAFGEFGBBGHHEDGDABCGFHDEGGEDEADB,False +129,8.0,19.0,18.0,15.0,11.0,19.0,15.0,9.0,BEEBFHGAACFBCEBFHFADFCDHCDBCGBGGEGBDAADFDCHECHECEGCFGCFGFBCFGCAGDFGFFHHBDDFCDFBBEDBFDGDBBFBHABCEBCDAEGCBFHBFCGECGD,False +130,19.0,16.0,11.0,13.0,12.0,17.0,19.0,19.0,AGFEGFGGEGDAFDBFDBCGACBHEHHAHHDFADABHAGHBFHDFCDCADEEFEGBDGBEGADBAHFGBDGBAEFAGFBCAECHGBGFBGBBFBHAHHAHDEGEFAHADCACCHCEHGAHFHGFCF,False +131,4.0,4.0,2.0,0.0,2.0,2.0,3.0,2.0,FBECAGHAHCAGBAGBEFB,True +132,21.0,22.0,26.0,22.0,19.0,22.0,19.0,31.0,HHACHAGHDFHCACFECAECGDFFDFCAACEBEDHHAHDCGBCBBCAHCAFCDBGFGDCHBHECHCFACFGCHECBBCFBGHDGHEGHDGFBAADFGBGGFCGHCBHAGHFEEEDAEDAHHABFABHAHHGHBFDAFDGDDFEDGBDFEDHDDHCEHEAHECEECEADBGCBFFHCFBBBBH,False +133,16.0,18.0,20.0,18.0,16.0,13.0,27.0,16.0,DGGBCEDCEFHDGHFBDCHFHHBACBADAAHADEACBGHFGEDGCBCABGAGFCGDCGDGBEGBEGBECEEHGEHGHHDAAGGACBDGBGCBACDEBDBGCFHFEHCEGCEAEFCHFABFEGGCDHFDCDDCDBFGBFGAGHAG,False +134,19.0,21.0,15.0,10.0,12.0,12.0,10.0,11.0,DAGDAGAAHHFHABCBBCEBCFBCGDCGEEACACBACEAFGBDAAFEAFEHBBBFECDEADGFFACGECBBCBBGEBFEBDAACHADHFEFBCHBFGBHDBCGBHADHAH,False +135,13.0,9.0,13.0,6.0,13.0,9.0,17.0,10.0,ACEEHFBHFBGFCHABEADHHCGACGDHBCABEGBEDBGGCGHHAHCEDAEFAEGCEACEAGGFCGCDGBFGAFGAFBEGCEGAFGECHD,False +136,12.0,12.0,9.0,6.0,6.0,6.0,7.0,12.0,DGFDCFBCHHHHHHHBHBBABEAFGBEGCFDFGCCBDABAAEAAHACCAGHADEACGHGEBEFBCDBHAB,False +137,8.0,7.0,7.0,10.0,12.0,16.0,11.0,8.0,EEHEGHGAHFFEFEDBGDBEBBGGFGDCGFCFCGFDDFHDFHAFCFDGAAFFAEHAEDFEGFEDCEGAEFBHBCDBCHA,False +138,16.0,20.0,15.0,26.0,16.0,10.0,21.0,11.0,BCEFDBCDBAHBEFBCAHCAEBDCCDHGHHCHDDDEGBFDFGCACAEEDGADGEDBEGCEHCHBGHBEDDADDGBDGBCGBDHCFGCGGFGGAAEAADAEDGEDBEBADDADGCDGBAGBDGBHGFFBEDAEFBF,False +139,13.0,8.0,3.0,6.0,6.0,4.0,5.0,4.0,EDGABAADGAECAGAAGAACHFFHABGFBABBEDBEHBAHCABDFDEED,True +140,3.0,7.0,9.0,8.0,11.0,8.0,12.0,4.0,FGFCGCCEEDFEBFEBDACHADEBCEDFBDEHEFBEHCEDCGGBGFBEFCGGDGHDGCGGAG,False +141,7.0,6.0,3.0,11.0,10.0,4.0,8.0,7.0,EEAAECEEGHEHDFDCHCGHEAAEHBDFBDBGDBADBEHFEAFGGDHDDGBDGADG,False +142,25.0,23.0,17.0,19.0,29.0,25.0,18.0,29.0,EEBEEBHHHHBCHEFDGCDECDEDBEFHAFGBFBHFBHFCHFEDFBBFEAEGBCBAAAADAHEEFAEFDFACHHCHBEHBHHDGECFEFBEGHEGHAFHCDBCAGHEGHGDHGEGGFAAFAHEEHBFABDACHABDCDAFGFFGCFECFHBFEEDDGDBFCAHAEDDEACEAGDBGAAGAHCBHB,False +143,1.0,2.0,2.0,3.0,4.0,5.0,2.0,3.0,CFDCBDHGEEGAEDFEFFBHFH,True +144,9.0,4.0,7.0,5.0,3.0,7.0,3.0,7.0,EFAFABHACHECHGCBADBADAADGCFFAHGHDFHDCHFCBECAF,False +145,21.0,27.0,26.0,22.0,15.0,22.0,16.0,17.0,FCDFDDECEHCFGCEGDABBGHCGBBFABAEFEEFACHBGFEABEDBHCCFGAFEEFHAFECFHCEBCDBCBAHFAHFCFFCFFBFAGGAECDCCBBDDCDDCABBAGGAGBAGHCHECDACBAFHECGBGGBAGBHBACCADDDDCHHHFHHBDDBDDBDBADBF,False +146,23.0,23.0,27.0,18.0,23.0,27.0,25.0,28.0,DEGHEGFDBFGHDEACECDFDDFDBBBGCEAFHFFHFEBGEBDEBFBBFHFFEFCGFCGCHGAHBCFGAAECGEGDDGCHGAHAAHAADDADCAFBFFBHBHEGCAHCHHBEACCBBABBDBHCBDFAHAEBCEGEGCBHEHFAGCAFCACEFHEFADBCGGCGHAGHGEHEFHCAHCGHDGHCEHCEFCGFDF,False +147,19.0,22.0,21.0,22.0,15.0,18.0,18.0,18.0,ADDADEFBADAHFBBFBBCHGCGBCBHEDCCDHDDACGEGBEACEBCGCFABFHEAHFGDCDDCGFCGHEHHEHBFHDFBFFBAFAABAADACDFCEFHADGADCCECDBHDBCGBAEBAHDHHDHACFCGFGEFHEGGCGEFGBDGBGBBDE,False +148,23.0,18.0,18.0,17.0,20.0,20.0,23.0,19.0,GHBGCBDAFDAFHCBEFGACAECHHGEGFEGDEDDBCAAGFAGCGECAEFBEACEHGEHAEAFEAFBCGCCFCBBGHBAFBFCBFAEHBEHBEGAACFABGEDGHAGBCGCEBDGDDHEAHCADFFGHAHDGHDGHDGBDABHAEDDFHDFCFFHGFE,False +149,11.0,9.0,14.0,14.0,12.0,13.0,8.0,11.0,CCFCGFCDFHHHGGHEDDFHDFEEGCEAHAHCADFEBBBCBFCAHBAHEACDDCDACDADDBDDBEGBDFFCEHEFBEFEAGEGFCGFCAHA,False +150,20.0,17.0,22.0,21.0,18.0,23.0,27.0,26.0,FDDHHBGAEAABAAFAHBGFFHEHCEBEBBEDBGDCGHCGHCFFEGFEDFCDACDAEBFEDAEDHHHFGHGDHGAEFCFGBEDAADCCGFGGAAGCHCDDBDCGGFGGFGGFHGFBGBCGECHFHHACHABDFHDHCAEBBEBGCCFHEHGFHFEHFEHBCACCACGAGHDDDD,False +151,25.0,32.0,23.0,18.0,29.0,30.0,21.0,16.0,CHFAFBDBCEHGEHEEFEACEFCFHHFCAGAEGBCABCAECHDDFDFFEFFGHABFFEHBBDBGABGACGACEDCGDEBDEBCEBFDCHBADBFDAADEFBFHGAACAACHDEADHCBGCAFBFFBFFBEBBGBEEBHDBFDGDAGFEGCABEEBEHBGHBGFBGBAGFGCEGCACFDGAEBEEFCEFAFHBCE,False +152,2.0,5.0,8.0,6.0,3.0,7.0,7.0,3.0,ECBDCEGFFGHCGCGGFBDFDDADDHEBFCBCCBFCGFGAH,True +153,20.0,20.0,31.0,26.0,22.0,23.0,14.0,22.0,GBGFBFFBHCBHCBHGBEFCGFHHHHEHDCHCCDGCFFCDDHFDEDGEGCHHADHCEECFECHECDGCDGADCAGAAHEDHCFBEFEDCHFFAADEADHADCGBCFBCFEEEEBGBCCCCBCDBDHBAHDABCAGCBCFBEHDEBDCFDHFEFDAACAEDADAFGEFABFDCEDAFAB,False +154,14.0,22.0,13.0,6.0,19.0,16.0,15.0,9.0,EEBFEFCBFDAAGAHBCCBGCEEAEEAEEAEEAEGGFHBCHBCBCHBCFACFGDECBAGFFDBHBBHGGFAGBGCBEHGADBFBBGGAFCAFCEGBEGBEFBDFBHEHEFDAFB,False +155,13.0,9.0,8.0,9.0,16.0,11.0,16.0,26.0,HGHDBHECHGCDGAEGFEHDEGGHHFBHFGHBGBEFEAHEAHBFHFDHADHBCHEAHEAHDGHDHHEFFACDCEBFGGEGAEHEGHEGCCGFHGAAAHAFHAHDEBBC,False +156,21.0,23.0,28.0,17.0,32.0,20.0,26.0,33.0,AGBGFFGFGGCEFCBFGBECECGECBECAGHDHEDHCBHEEAEEBFGGHEEHAGFFGFHHCCHADABEGBHGCHGCFBHEHHEHHGFHFFHEFAEHADCEDCHAADBADHEDAFHEDDCCDCFEHBHGGHEFHEBHEBHGBCGCADAAHACBDFBGCBECBCCEHEADEGEEAFCDBHGBCGBCDFAGEAEHAHDCBBCG,False +157,3.0,5.0,10.0,12.0,6.0,7.0,9.0,8.0,CDDCFDCHDGGFGDBGDHFHHEGCCHDCADCAGBFHEGEEGCEDEFDBFDHAHGCBFCBD,False +158,27.0,19.0,22.0,22.0,21.0,22.0,30.0,32.0,AEAADDGDGHBHDGHBGHBHHBCHCAHCABEEBDBDHGFHGHHGBBAHAGFGBAGAGGAGHHCFFBHHGDHAACAGCAHDADGAFHCCHGHHCHGCFGEEDEDBECGAFEDFEDBEGBCACHFCDFGDCDCCBGCFGDFGHFAAEDHFBHFGFFEAEEHEDBECFEABGAFEEEAFDCFDAFDBCGHCGHAEHAG,False +159,6.0,10.0,10.0,5.0,6.0,6.0,5.0,10.0,HCEECDECAFABHBBFADFCGACGABHFEHCBBCBBHFHCDCEDCHGGHEGHFBHABD,False +160,18.0,20.0,20.0,17.0,21.0,19.0,20.0,20.0,FEDBECCGDCDBGDBGDGGDCDFCAHCEHAGAABACFCFFCAACHADAACEGEEGBFBHEHHBGHBACGFDFCHFCHEAEBBEDFFGCFGBEBBEHDDHABGEEEEFABHABHGEHGEHGEHBFDFDHGDHGBEGBECCFCAFHFGCCDAFAHDB,False +161,12.0,21.0,28.0,20.0,19.0,21.0,30.0,23.0,BEBCAAFGAFGBFGEEEFCCHCGHFGHGDDCCHBCGACGEHGHCEHCFCBHCBHDAHDHHDCHEABGHFGBGGCGHCGCEGFDGDDEFGEAHBGEADDCFDGBDGDCFECFCGFCHEGAFCDFCDGDFFEHFBHFCCBECHEBHCBFDBFBBGBDAEDGECGBHEBDABGGGAH,False +162,21.0,14.0,18.0,20.0,18.0,17.0,19.0,20.0,GHBEAFEGBGGHDEEDEABEBBEFECFCCABAAEAAEACBAFBHFHHAEDBCDECDAFBAFBAGEHEHGDAAHGAEDCCDHDDHGAHAFCCECAFCHHCHEGBCDCCBFFEFFGBFDDDDDGGCGDAFDGCGFHHDHHDHGFHGAGG,False +163,7.0,8.0,10.0,9.0,10.0,6.0,9.0,12.0,FBCCDDCAHADHEHHAGCGGHECHECHGBFABFADFGDHBDHDDCDHCEBFHGECEEAEFHECEBGBGGBA,False +164,2.0,1.0,4.0,3.0,2.0,6.0,3.0,7.0,CHCFEGFCGHHEABGAHDFHDFHCFHFD,True +165,27.0,21.0,24.0,26.0,31.0,11.0,22.0,21.0,CAADGACHHEAHDFHCAHCFBCFBEBHGCEFCHCGECDEABEACDDGHDAFCCDCADCAGBDGBEGBCDEHAHHAEFBEGDEFCEABBDBGAHAACAAEACBFBBFGEEHEBDEGDEGDCCDCABHEEEGCDGCDGHEGEEGEHDEGDHDAEFEGBDGADHFDGCDGBAAAAHHEEHDEBABB,False +166,7.0,16.0,7.0,13.0,4.0,10.0,9.0,15.0,BDDEDDGCAHEFHCFHCBHAGFDBDDBDDGFFBAHAHHFGBBDFBDHACHBCEBFEHHGHHBADBCFBHDGABGHBGFBGC,False +167,15.0,15.0,9.0,10.0,9.0,15.0,18.0,14.0,GGABCADCGHHGEHBDHCDHDEGGGFGGAGAABECBCFBEABEBEGAACBBFEAFBHFBHFBGFCAFGHFGHDGCBCEHFFGBFEDFBDAHHAHHGFDDAGDAFA,False +168,21.0,14.0,14.0,15.0,25.0,21.0,7.0,17.0,FDABDAHCHHFDACBGCBGCHFAACGEEBCBFABAEEAEEAFEADDHFAHFEHAHHCEHEFDGFEHFEGFDFHCCAEAAEADBHCFHEBBCFACFDEADFAECAEBBEDBEGFDAFEFDHFDHFEEBCEBGEHD,False +169,11.0,25.0,11.0,15.0,12.0,14.0,16.0,19.0,CDFBBCHGCEBDBACBDCGHFHHFHDFHBEGBEDBFDAFCAHBACFAGGAGEAGBAGBHBBDEBHGHHGHFEABDHFCBECBFDFEGHDFHBFHAEHECHBHBGDBGBCEBABDEGDGGDFDB,False +170,11.0,10.0,15.0,10.0,14.0,10.0,14.0,13.0,EEGCEHAGADCDEADGBDBHDFGDHCDFCDHBAEAHEHCGFCGFCEFDHGHHGHFGCAACHACHAEGEBDCFGCFBBFBBEEBGACGFHEECEBCGA,False +171,15.0,14.0,17.0,21.0,14.0,11.0,20.0,12.0,CBGBFHBCEACEAGAACBDBBDCDDCDDAGGAFGFGDHADEDDEFFAFFCBFCBFCFAHDDBGGGEADHHBHBBDEEGEEGCAGCDCCGCEBHHCGGCDBCHHEAHGAEGHEFADGDGEDGDDA,False +172,6.0,4.0,6.0,6.0,3.0,10.0,5.0,4.0,GBFGHFGDEDFCDAGDHCDACBECDECAHAFFAFBCBHAFFGFF,False +173,2.0,0.0,4.0,3.0,0.0,0.0,1.0,0.0,DDGDCCACCA,True +174,3.0,6.0,8.0,12.0,9.0,8.0,4.0,7.0,FGBDDHHDCFABFABCBCCHDEHEFAEFEBFEDDHDBCDECFHCFGEGGEDDCDDHE,False +175,4.0,4.0,3.0,0.0,0.0,0.0,2.0,1.0,GACGABHBBAABCC,True +176,4.0,2.0,4.0,1.0,2.0,1.0,1.0,1.0,HCDACAAEABCFBCEG,True +177,22.0,20.0,10.0,18.0,13.0,13.0,19.0,20.0,CBHCGHGEHEEADBHGAEGFEGFBAEBCFAFEGHCBABFADFDDCHBCHDHAGGADBAHFEEFHBBHBGDDDHDGHGFHAFAAEGBBDAADHGBEGBAGBADBAHCHHADHDGGDFGDFDCABCABCABEFHEGA,False +178,22.0,19.0,25.0,28.0,26.0,27.0,22.0,13.0,CCCCCCCDCAGHEHCGDGHCADEADBADHFDGGGBDACFHCFHDGBDGDAGDCDDBBCEBFBAABDCDDEDFEFEECDEBAFBDDBFEHEEAEFGEFGEAGBFFBFFBCFCFDGHEFCAFCAHEEGEEBEAHDGEFBFHDFEDCDHCDACGGBGCAGDAFAAFEAFHDFEGECBBGFAEFAG,False +179,3.0,7.0,11.0,8.0,19.0,13.0,15.0,4.0,BEEBAEFHEBGCBCEBFHFDECDCGHGFEGEEBECGFCGFDGDDGFAFFAEGCEFCEFDECEEGDEGCGGFGEBDHCEGF,True +180,23.0,18.0,16.0,19.0,17.0,9.0,16.0,16.0,DACDHCDECEHCBACDAFDAFABCEDHDGHBCFFABCDDFDDHCAHBAEDABHABDGDFCBECAEAAHGEFABFGBGBHABHCEAEGAEGEHGFHEAAEAHGCEGCHGAEGCBGCDGDEGHHADBAGBEDBDBB,False +181,7.0,4.0,3.0,4.0,1.0,4.0,0.0,2.0,CDDAFABHAECADFHCFABFABDAB,True +182,7.0,17.0,14.0,12.0,11.0,8.0,17.0,16.0,ECEECHEGDCFDCFDCEDBBGBGECGBHGFFGCBHEBHABAGBHFBHDGHBECBEHHGCGCCGCFGHABADDDHGDHEBHBCGGFFACHAEADBHDGHBGDB,False +183,18.0,19.0,14.0,22.0,20.0,25.0,20.0,18.0,FBAHCEHGHHGAEDEDDHDHGFACFDBFGCCBHGHHGBHGECBHFDEFBEBHECHFGDFHDEHAGGEGDBGAADFADAADGADGHFFEGCABDGFDBDECDFAFAEFCEFCADGFDFFBFFBHFCECGEBGEBHEADBBDFBCFDCFAAEGBEABE,False +184,9.0,17.0,14.0,14.0,12.0,19.0,15.0,10.0,DBDDHCBBBBGGFEBFEAFGCFDCADCDFEFGHFDHBDCECCFDCAEBEDHFDCBDGBACACGECFEHDBACBFFBFFGGDEGHHGCHFBHFBEFAEAABGFBGEGGFGH,False +185,5.0,15.0,12.0,28.0,11.0,16.0,11.0,13.0,FBEBDDHEDCEGFGGBGEBDBBHCDGDDHBDHECBDFBDEGHEFHEFEDCDHGDADDABHABDCBDBFDHGDFDCGHCGDCHHGDADDEDDAFDFFHFFECDCBBFFCFFC,False +186,3.0,2.0,0.0,4.0,2.0,3.0,6.0,2.0,EGADGADADBGHFGBDGHFGEF,True +187,7.0,12.0,9.0,16.0,4.0,16.0,12.0,10.0,BDFDFFBBBEBBFCHHCHHFFEGDADDFDFHAFDAFBBGDBGDBDDGCDFFDGDGCBCADGEHGDHCCHACABHAHGCFGFFGEFG,False +188,9.0,14.0,12.0,11.0,9.0,6.0,5.0,4.0,DFBEFDCDCBAFBADEFDEGCEBCGFCECHDBADBADBEEBABGHBACBACBECGACBBCADDHFGHECD,False +189,15.0,22.0,16.0,23.0,11.0,18.0,13.0,25.0,CHGBHDEHBEHDGCDFHFHHCHHGHEDDBGHACHECHBHGDHDCHDEAGEABFAEFACBBDDBDBADACDABFAHDABACBHHDHCAHFFBBDBGAFGFFBBABCGEEFEDCCDCBDBFDBFEFGGFHHFHDCADBDGFCGFH,False +190,23.0,11.0,18.0,25.0,19.0,12.0,19.0,38.0,DEHHAGHADHGCHACEDCAGEGFDADHADHDDGEEEEHFHGCAGEDDFHHEHHDHDGBDADHECEEGAFHDBHGBHGBDAHAEHABHBBFDDCDAHHGHHEHFGHCHDDECBFCADCGDCGHCGHGAHGABFHFHHFHHEHHBBAEDAEDFCCECAAGACCACAF,False +191,5.0,6.0,1.0,7.0,12.0,13.0,5.0,13.0,HEEFEHAEHFFHFGDFEDGEGAFGFHGEHDBHAFHFFEAHEBEBDFADBHHHEHBECFDBFD,True +192,14.0,9.0,19.0,16.0,17.0,13.0,14.0,12.0,FBCCBDDFFDHDDHGEFGEFGFHGFBDFCEEHACCAEEDBFDEDCHFCBAEFCGGAHFADGAHEHHAHBACBCEDEEDCCDCGACGCCGCEGDECAECAFGABGBHGDDEAEHA,False +193,13.0,11.0,10.0,13.0,18.0,18.0,16.0,24.0,BFHBGDBGHEFHEGEEGAAFHDFECFEAHEAHDFHCHHEHFAGEGCCHHEDHEDCCDAGGAGGBDCBDAFHFFAFDAFHGCHGCFGHGHHCHDBHBFFADFEDEBHGGFBADHAEEEHEEBFB,False +194,4.0,3.0,4.0,0.0,0.0,3.0,1.0,3.0,HCHBAHBAGFABCAFCFC,True +195,5.0,5.0,1.0,2.0,4.0,4.0,7.0,2.0,EFBGHBGABGADGABHAGDBECGAFGFFEE,True +196,16.0,12.0,12.0,7.0,4.0,7.0,9.0,12.0,ACGACAHFFCEACGGDEADCAGCFHBFBEFDHDBHAAAAGHBBHCBHGBAGBACBDCBHCBACDECHHAGHFHBGADFA,False +197,11.0,6.0,8.0,7.0,7.0,10.0,12.0,14.0,GHFFHACEECGEGGDBGBBFAGFGCHGHDGAEGCCBHCBHAFHAHDAFGAFADCADHAHHBCDFGEAHEHHFDEF,False +198,21.0,16.0,17.0,15.0,22.0,24.0,21.0,20.0,AEFABCDCDABGHHEHDFBBFCAGGAEFCGGCGABGACGHHGDGBDBBCFACBDFHHEHFCHFCECHFCHGEHGBFFECFBHFGHFEDFDCFCEAEEADDGDEGFEGFABFHBFAEHEDDADAAGAACEACBHEBFEDFAAAGGEGGBHEEHFEHF,False +199,3.0,4.0,1.0,2.0,7.0,5.0,9.0,5.0,HFFFEGEEGAHGBHGAHDADCBGGEEGEGBEGBFFH,True +200,27.0,17.0,26.0,18.0,16.0,17.0,15.0,13.0,BDEBEEBCBBCDFCHCCABDEGCGACGACACFGDDGAACBACEEDBDDCCCHCDFAHBGEBCHGGFCGHHHABHBGAEHCBGCDAEDFEFBEAHEAFFGDFHDHHDFDBFEBAAGAAGAGFCBCCEACEACECFAFAAFAADCFDAFDA,False +201,14.0,18.0,22.0,18.0,23.0,25.0,18.0,25.0,EHGEHCBHCHHAEHDEHDEAEBCEBCEGFAHFAHCEHBFHBHHBHEBCFADGHFGCFBAFBDHCHCEHADGBDFBFFBHBGGEFFFDFEBCDFDHCDHBECDEHECBECEFAGFCGCAGEHGEDEFHFCGCCDACAAFDAHDFFDBGDGAFGCBCDFEGFGGE,False +202,6.0,4.0,6.0,6.0,4.0,7.0,2.0,1.0,BADGAEAACFACGEFBACCEFCEFBDHDDFDBFDCF,True +203,4.0,8.0,7.0,5.0,6.0,6.0,6.0,7.0,EHAECAEHBEHBFHBCDBAEFEGGCFGDGHHACBBCGBDHCDFCDFGBF,False +204,6.0,15.0,10.0,9.0,18.0,10.0,16.0,17.0,EHHEDFBDFGDGEDGHFEEDDBGFADFCBHCBHFEEFAECGHHGBCEDCEHFACGHEGHEGCBGHBCHBEFFEHADBAGBGHCHEEBEAGEBGBHGBHCBG,False +205,6.0,8.0,4.0,6.0,11.0,10.0,4.0,7.0,BDFBFFCHFBADBGFCGCCEEAAHFAHFGFEEFBEAHEBDEBDFHDHEGEEBEHDA,False +206,7.0,11.0,7.0,14.0,12.0,11.0,11.0,15.0,DFFHFBABAHBEHBEHDHGCHFDFAGCGHEBADHGDHCEHCEFCEFGFFGHGCDAADGBBGDBGEBFEDHABHDBCDHHEFDEGDEDE,False +207,14.0,19.0,19.0,16.0,15.0,16.0,25.0,15.0,BHBBDBDDGDAHEGEGGECDCCBCDAEBGEDGHDCHFEHACACCEDCGFGFEGDGGAGGAGGHFBEGCEGCEBCAFGHEBHDAEGAFHHCADFBBFBFFDHFCHFBBGBBCBACGFDAFHBCGFCGEDGADEAHFCHBG,False +208,14.0,24.0,23.0,25.0,20.0,23.0,13.0,19.0,CGFHBECCCACGAFFHDFHDAHCCFBDFBCCBGFDAHDABGABGHBFHCDGDDHBHEBCEDEFFEFFEFFCDDGGECDEFDADDHEACEAHEAEEBFBFGBDBBFCBDCFDGFHBBDBCGCDAHDCCDHCEEFEGGECBBABDCBDEFEHHEHHBHBADFA,False +209,5.0,7.0,7.0,12.0,11.0,5.0,6.0,4.0,BEEGAGCAHCFDCAHCEFCAFGGDDEDCBDBEFBEDDADDHDDBBDBEEEGCEGHEF,False +210,21.0,21.0,29.0,26.0,25.0,22.0,25.0,25.0,HGGGCBGCBGFDHCEGCBADBADBDFHCBHDBEBBEHBEFBCABCACCFCEFHAFHGFGDDGDDHHDEDDHCBEDDEDCBGGFAADADGACHAFDBEBEECDECEFGGHECHEFHEBHEDGCDCABCEFGEGHFGHEECDBHDFDFGCAEAGEAHCHFAHDGHACFACGHHGDHGCAAEFAFBCBECGFCFFCA,False +211,25.0,20.0,15.0,18.0,16.0,31.0,22.0,17.0,GDHFDBEDFEFGAHDFFDBECFDAFDBFGBDAEGAEGFDCFDCEACBAFHGHHFBFFBHHEAFBAFDCFBGAGGACBACFCEACEACHHGDHGCGFHGHAGABGBGDFHHFCACEBHEDDAFDAGCADBEGBFGBFEFFEAFGCFBHFEHGABAABAEGAFDFB,False +212,11.0,12.0,15.0,21.0,14.0,13.0,13.0,22.0,FDHBAHAHFDBFDFCHHEFHDFAGBADBADCHDFFDABDHCDHCGAGFHDDHEEHBHHEHBCBGDGCDCDECDEGEBHEHHGHDFBCFDAGCAGCACCEFCDBGEBGEDEFGHCGHEDHEA,False +213,26.0,25.0,22.0,24.0,22.0,21.0,23.0,28.0,DGGABBFFGEFGHFBHBHFAGAHGECGEBAACCADCHDBGDHCDFEDCCCFBFAHDEGGBGECFEABGHDEADGBGGFDEFAABAAHAAHCAHGFHBFABFAEHHCHHCFBEEDEEFEGDEHDHHDHCBEABAGGAFGDFDCBCHBCHBHEBAAGCADCHFCFDBBDBCDECHACHDBEDHEFGADGHDBE,False +214,17.0,18.0,21.0,25.0,26.0,17.0,17.0,17.0,FEFAEAHHABBGBGGCDGDEEDAEBGFHHCADDHDDEDDEAFECGGAGGEBGBACEEDEEDHDDHGBHEBCBHADFEDEGGCDDBDCFCHFEFAHFHDBHDBHAGCFEFFEBEEBEEDGEACFABBCBFDBFHFECGHCGACDCCDCCECFHAACADC,False +215,3.0,8.0,12.0,3.0,11.0,1.0,8.0,8.0,ECHEGGEHEEBCEHGGHBAADGCHBCBBCHBCHBCEDFEGHEDCGCCECEBCGA,True +216,3.0,7.0,2.0,4.0,7.0,5.0,4.0,9.0,EEBACHABHEFDEHHEBHAFHFCHEDGEBBDFBHGBHGFDG,True +217,24.0,19.0,23.0,32.0,19.0,19.0,18.0,19.0,BDFHFFHEAGCGGEHGAHGADAEDAEGACABCBFDEDDEHDGDDEDDGCDGAFBBEBHFBDEADCDDCHBCEAHDBHCBHCACBGCGFCGFCGDHFABCACCABHEEHDGBFFDFFBHADDDCAAHDAEFEEFBDFADGADHADFGDCGCCBECADAHHCFDCGBEFEEDHBA,False +218,15.0,9.0,15.0,14.0,9.0,15.0,10.0,14.0,EDDHBDCEDAHHCDHCDEFECFDDBDEGDCAFCAGCHCFHBFBDFCABCEGEEHHGFHAFCABHABDAFAHBHHGFCGFHGBAAFDAFAAFEDFAGGCCGC,False +219,24.0,26.0,20.0,28.0,17.0,21.0,17.0,23.0,FBGGAGHAGHGGBGGFFDAFDHDCFBFFHFDHDDHFDHFHCFGDHBEFCEACHFEHCBADHDBADCEBCDDAGDAFDAEDEHCAFDAFDFBBAGBGHBCHAFECHDCEBBEABGFHEBHDGCEFCBACBACBCCBHBFGDADAAHAHBGDBDEBGECEDHDAEBAEBAEHADCDBC,False +220,10.0,6.0,12.0,8.0,3.0,8.0,5.0,9.0,DEDDFFBCFCCAGBFHBACAACAHFAHBEGGAGCDCCDFCDFCAHCACDHEHHABGDBHFH,False +221,18.0,20.0,25.0,20.0,16.0,11.0,30.0,25.0,BFFBEGBGFBGHBEFEDHBDCAAHAGHFGDADCBDBBDECAEBAHGHGABBHHBGCGECEECADDDGHDGBBGBCGHHGCHCCHCFHGGHAAHAHGAHGEHGDHBEGFHFAHGADFEGBDHFDGCDGCFGAGCCGACGHEGDCCCABCECGEHDEDDCCECADCB,False +222,19.0,19.0,21.0,28.0,17.0,28.0,23.0,16.0,FFFFGGBAGBFCDFCBFDGDDEDDFDEFCHDCHACAAFFDGFHCFBCDGEGEECCCBBAHHDEHDECFGGGDDGDDGDDCBACBABHCDCFDCEBEGBCHEFHGBHABAGFGFADHAGFAEFHEBBFBEFCGFHAFGADGAFHBCABDEDDCHFEHFEGAEDCGDFADBAG,False +223,23.0,19.0,28.0,13.0,18.0,28.0,23.0,33.0,GHBCHBGHEHEAHDHGDCFBHGCHGCFGCBGBGCDHEFAGHEGAABBHECFCFGDEHCEHAFCADAGDFGDHACBACHACHCHFBEFCFGCHHHHCHBCBEDBFHBEHBAGEACHACFAGGHGDHFFAFEADEAHFAHCCHEFGEFBFCBHDFGFFGAFDACDECECBEBFHBAGCHGCAFFAFF,False +224,3.0,2.0,2.0,3.0,1.0,3.0,0.0,0.0,DAADFBDFBCACFE,True +225,18.0,28.0,26.0,15.0,16.0,22.0,28.0,24.0,CCBGHAGAEGAFGBHGCHGBBBHBBHCBDDBFDFGECEECAGHEBBGBAGBFGCHCCDGCDHEAGCBBFBBFCBGGAGBDGHGGHGHHFHDCEDAFGHBGABHBEAACGCCHCCHBHHFFFFGCFHCFEDACFGEFCAAGDCDDHDBAABFACDABEGCEGFEHFEFCEDBFHBEHF,False +226,0.0,1.0,4.0,5.0,1.0,5.0,5.0,2.0,DBGCFGDHGFCGDHGEFCFDCFD,True +227,9.0,11.0,5.0,9.0,13.0,8.0,7.0,11.0,DGHBGEBGHACBAFHAFHFHDDHCGEAGEDEEBEAGFDFBDFBHFHCDHCEEAFBABBEEBEBDHADHGEEAC,False +228,3.0,5.0,4.0,5.0,8.0,4.0,5.0,8.0,DCEDEHGEHGFCEFGBDHBDCBDHFFHEAHEACGBGHAEHEB,False +229,5.0,2.0,1.0,1.0,0.0,2.0,0.0,0.0,ABABFACFADA,True +230,17.0,15.0,18.0,10.0,25.0,10.0,12.0,11.0,ECCHCABEAEAABAEBGEBCEBGAAGBBDFHDEHDEHCHHCHCEHEEHCGBAFCDEEFGEGGCFDEFBBADBEEFHEAHECGFCDAAAFBBCCCACBGGBAEDDEGDECCEFAEFAEG,False +231,31.0,18.0,29.0,27.0,23.0,14.0,25.0,29.0,DGBAGHGHDGCGACBADBDDEADFCHGDBFEBHEBHEFHFCDFCDACFGHDDDDDCGCEAEEADCBDBGGHCAACAEDACHEHHAHDDFDEHCEHCECEHHEAFEABCGEGABHEDHEFAGCGGCGACDAGDACAAHACBBCDACAACHCDHGAHGFBDAACEACECFEHGGHBGHBCFFGDBGHBEFEHHAHBAG,False +232,9.0,27.0,30.0,27.0,17.0,16.0,18.0,20.0,HDBHDCCCHHCHECBBCGCEDCHCADGDBBEBGEGGFDFDDGDBBFHCEEDFFFHFHHDGCEBCABABDEHDHCDHFDHFDHBDHGGEECBEHBDFDDBCDCCBCCGCAHDBBBBFBEHBEGBEDDGAAHCBECBCCBCFFEDFEDCCGBAGACGDCAFCGFGG,False +233,13.0,14.0,9.0,12.0,10.0,11.0,7.0,12.0,CACBADGHDGHDFHDFHDEEDGEBBEDHACHABBFCFAEHACFDCEAHEABFFBFEAAEBCHDGBDBBGCBFEAFGDCDHHABHABGF,False +234,27.0,12.0,19.0,20.0,14.0,11.0,16.0,19.0,DCEACEBHDGHAGFBGABGABGABCHFEADDADAHDHDGBFAECCBCHHFADFEFAHDAEDCHCHADBFDCGDCHECGAAAAGBAEEHGCCGEAGEFCDFDGGCGACHCEHCEHDEHBCADAADADDFHGAHBAHBAF,False +235,10.0,14.0,16.0,10.0,22.0,13.0,14.0,12.0,BCEFFEFBBGBBGEDGEABFACCDCCDHEGHCBDGHEEEFAGBHGBEEHEEHDEFDEFCECDECHGGAGFFEDGHBECBHCGFEAAEAHGBHGBHEBAFACCEDCACFDCF,False +236,7.0,11.0,9.0,8.0,13.0,11.0,4.0,12.0,AEBEHFHFFGFHBFHFAHBHHBHFEFABBEBAEFCEACHHDGDEGABCCBCEBDEDCEACFHCFDCHDEEDBGDE,False +237,23.0,30.0,14.0,18.0,17.0,26.0,17.0,30.0,DGDDFCEFCGCBBHACAFCEEEEAADADEHFABBADHADHFDBFHHFHDFDAFEADBADCAFAFBEBBEBBCBBCFBEFBGFBHBBFFHFAHABHEFHBFHEGHAAHBAGBGFHAFABEGEGGDCGBHBCHGHFGHGHHCDEFFHCBHBBHGEHGDHFDHCDBDAHGHBEAACFG,False +238,19.0,27.0,27.0,14.0,19.0,23.0,28.0,21.0,CCCACCFBHFGEBABBGFFGBCHBFAAFBAHCAHCBGABGADDABDAFDBCGECFEHBCHGHHGHEGDEBFBBCGBGHBGFBCCBDGDCHACHADFADEHDEHEGADGAFBFGBEGHFHEADFCCGCCGFCEFGHFEFBCDBGHHECGBCFAEBBCDGAGCAGFFEHGEGFEGBECHE,False +239,12.0,6.0,10.0,11.0,16.0,6.0,12.0,10.0,DBDGGDGCDECGHCHEAHGDEFEEFEBBHABCCDACGFEGHECAFAEDAHAGCBGAHGAGFABFDEEDGEHEECEDCEAHDAH,False +240,12.0,11.0,10.0,12.0,15.0,7.0,12.0,8.0,EHCEBGEBCADCDFCEGBEBCEBHDGAAGDGHDCFDEEGBEFEEFGEHGHBEABEAFCFHCGHCBADAADADGAEBBDDHDFGACGA,False +241,24.0,20.0,23.0,18.0,18.0,16.0,33.0,12.0,DCADHACHFFHADCCDEEDCEDCFAAFGBCGACGAGGACHBBDBCCBEFBGCDGHFECABCACGAEFAECBFFFHGCAECAGHEHBFHBAGEFGECGHBABCADDGGDGGDGGCGCFFHGGEAGEGEEBBEGAGFFGDGGBGDBGDCGHAAABGEBEBDDBDAA,False +242,2.0,5.0,2.0,2.0,7.0,2.0,2.0,4.0,EHCHBDECDEGFEAHHABBEBFEBGE,True +243,5.0,8.0,9.0,5.0,11.0,13.0,13.0,9.0,ECEEGBGFFHFBEFHFDBGDBGFHFFHGHCGHEACEABBFEEEEGCGGCFBCDCCEHCDHGAFGABGHFGAFD,False +244,8.0,13.0,8.0,11.0,10.0,14.0,17.0,10.0,EGDHGCEDHEAHFBCGBAABGEDAEDAEGGDDFDCFGCEGCGFADFCFEBBCBFDGFAGFEDFBGFGHBBHEDHGGHBAFBFHCFHGBHGB,False +245,10.0,16.0,19.0,10.0,13.0,11.0,21.0,15.0,BEEBGHAGHCCFEDFGFHBHHDFDDHCFAGFAHABFABGAFAACBECGGGHGCAGCHCEFGEHBEHBGFGEFCHDHHDEBCABDGBGGCGGCBGEBGDCCCCDCBDEBGEBECCH,False +246,9.0,13.0,8.0,9.0,4.0,11.0,15.0,3.0,BDDBDDBAGAEGABGEDFCBCCFCDABHCBGDGGEGCEFAGBAFBGGBGGBDFFAFBCGDHGHFFCFAGFAB,False +247,24.0,29.0,19.0,27.0,21.0,19.0,25.0,36.0,AGGDCEDBEDGADBCBEDBHDFHDBEFHEFEEGEGDEABEFHDBHBHHFFAFBGGHCFFEAFDABEAFCHDCABBBCBEEBFBGAGHBGHCABCAFHDGHCHHCDGADHADGFHGFCGDBHBCHBDAEGHHGHHAHCAHDDBGHBGCEAHGADDHDECGEHHEDEGFEDABHABHABCABDABDACHGCBGDHHFHFFGC,False +248,23.0,15.0,19.0,20.0,20.0,17.0,12.0,20.0,AEDAEDAEFADFAHFAHEEHBBCBBDBCAFAAGCCGACEHEADFHDFCDAHGBEFFEFDAFGACGECEHHGADGBCAFCGCHDDDGCFFDBCHECFEHEABEABDCBHFDHECAFDABDAGEBGHGEHDBADBADCHCHHCFHEEH,False +249,5.0,8.0,8.0,6.0,8.0,12.0,5.0,4.0,DDADDFEDFHACECHGGHCDBBFFBEEBGEBCECCGBEAAGAEBFCFFHFFBFFCF,False +250,9.0,9.0,5.0,9.0,9.0,5.0,9.0,6.0,EBGEGDECAEBBGBFDBACGCBBCBBFDADDACDGEDGHDHDAHEFHFGAEGHFGAAEHAE,False +251,3.0,4.0,6.0,7.0,2.0,6.0,5.0,5.0,FCHFEBDGHDHADFGGFGFFEDBCCBCCHGCHDBDDAA,False +252,23.0,16.0,22.0,22.0,17.0,24.0,15.0,22.0,GDGADAHGFBBFBCHBDHBDCCDHEGADCHBBDFHCGGCEFBECHECEACFDBADEACEDFFDFFDFCEFCGFCHFGAFADGAFHAEABFDEDHHBAAAAHGABGDBFEHFHHFCHDCEAEEAEDCFFAFHCHHADHACHAEDABDCCGGCGFCBFGEHBD,False +253,28.0,21.0,24.0,17.0,16.0,23.0,19.0,22.0,HBGAFCHGAFDHGAHGHGDDGADGECAACFACBDGFCBAHBHDBFDEFABFACAEGFHGBDGBFHDFHCGBAGCABEGHEFHECCEAEHADHFDCCDCCEAFBDDBFHHFGHFCHCDHCFFCBAEFAEFEEAAEBFCBAABAAHEABBAFBGCBGCBDFGAGCCDECAHH,False +254,22.0,21.0,35.0,22.0,18.0,16.0,18.0,17.0,CGFCBBCBBCFBDHEGBFDEHCCAECAHAFDEEDAEHAEBCHFHBFHCHBGEACCCCDCABFABCDBDHCGCCGDCDDADDGGEHFEGCCBCBAFDEFDAADFAGGHECHECHECHAHGCFBBBBAGGEDBFDAFDCEDCEDCADCBHEFCAGCAGCBGFDACAACGGH,False +255,16.0,23.0,16.0,16.0,20.0,17.0,25.0,22.0,FBDCDGFHBEHADAEBABHAGDEEDGEAABDDEEFEEDBCGGDHHDHGDABBCBBCDHCDBGDBGCHGHAGFECEEBEHFGDFACHGHHGBHCEHCECABHADHACFBBAEFCEHAGHGEHGFHGFGGFGBFBFCBGCFGEFGEHBBGFCAFGAB,False +256,4.0,5.0,1.0,1.0,3.0,4.0,5.0,7.0,BHFAGFAFHABDAEHHGHHGEGBEGBCBHF,True +257,15.0,16.0,15.0,21.0,14.0,16.0,23.0,29.0,BBAHCCDBGFHGFGFFCFGCGHCGHDGAGHDCHDEABEBGGFDDFHDHHGHBAHDGCAGBGEBHBCHGEFGEHGEBFECHEDGEHBAHBEHDACDHHHBCHBCHAFHDCHAHGAGGDDBDDEACBAEEAHDDFFHGFHFFDAEDACDFG,False +258,25.0,18.0,28.0,20.0,16.0,20.0,26.0,30.0,GBDGBHAEEAHBAHBCHCCHCEBCECDEAAFHHCGGCFFDFBAGBHGFHDAHBACCADCAECAFFAFFGGEGCEACECCFCBEAAGFCFFGGHCDECBGHBHACAAFDGHDCHDCFDHFEHFDGDGHDCHAEADGGEADCHDHBGBDGAGGFFHHFHAGHCHHCDBGHBEHDEHGABBADBCG,False +259,10.0,4.0,2.0,8.0,6.0,7.0,4.0,6.0,BFAHHADDBDEBDAHFACEADEFDEHDGAGFDGFAEFBGFEAACHAH,False +260,17.0,18.0,20.0,22.0,23.0,26.0,23.0,18.0,CGCHEEDEBDHDGEGFEFFCAHGBHBEHBACAAFAFFDBFDCFAEFADFAEGBBHADAGGHFGCCGCGFBDFEEEEADHGDCEDFGDEBDHBGHBFFCAFCECGEDADDBHGBECFEBFEDFDDEGDHCAHCFFGFFGAHCDHADCBECBHHBHCGFGGABGCEGFE,False +261,27.0,24.0,20.0,19.0,30.0,32.0,21.0,26.0,GEHGECEEBEDACCACGBFGFCDBHEFEEFGEFBFACFACFAFFAGDACBAGDEBABFAEDAGHAHBAECAFDFEEBBBFEBDEFCHFHBFHFEHDGHBGHCCFDDAADEAEECGGHGFECFEDFEAFACHACEFBEFHHBHHFEAFHBFBBFBHFCAGHHFHHGHDCHDCHFGAGDDGCAGDEEAGEBEDAGHADBBB,False +262,24.0,26.0,23.0,23.0,21.0,23.0,28.0,24.0,CFDHHBBHEEHEHHEFHBDAADAFDBCDHDDFGAFCACEADGBEGCGCHEAHGADGABGADCFFBFEDDAFDCFHBBCFBGDGCHECBEBBCABDAECAHAHHAHEBHDHHFAHGEBEHFAAGBAGBGGCAFAFBAFBDCDCCDGGDGBHBBCBGFGEEGECGEHECDFCBFGBDGCACEFGEGGFHGFDGF,False +263,0.0,1.0,9.0,1.0,3.0,4.0,6.0,1.0,CHCCEFCGGBGFDGEGCECCFCFGC,True +264,6.0,5.0,5.0,2.0,0.0,4.0,6.0,0.0,CCAGBBGDBGDBACACGAGGFFFAFBAC,True +265,4.0,10.0,10.0,7.0,1.0,8.0,4.0,4.0,BEFBDFGDFABCABCHFCDGBHBCAFCAFDBDBGGBDFCCBCFHCDHC,True +266,22.0,29.0,31.0,16.0,20.0,28.0,16.0,14.0,EHAHCBHCBECFGBBCHEEBAFBHHAFGBFDBFCBFCBFCBFCGFGECBBGFCEFBEFDEDDGFCFCAGCAFCEGAAGAACDCFGAFGAFHBGABDAGAHCAECABBBCFBCDEAAEBFBBFCCFCCFABFDDFBEHBFGEDBEDEHAECBGCFHCDECACCDEFDADEHCGDBHH,False +267,19.0,18.0,7.0,10.0,13.0,13.0,13.0,11.0,HAHCGEBDCBCBBEGHFGBCGAAGBGGFDGCAEADBAHBFEFFEAGEHCHHBAHAADEFGEAGFFEFAEFCBAABAABEAFGAEGDEDBBABBFBHHDDHDBFD,False +268,17.0,10.0,10.0,7.0,8.0,5.0,14.0,9.0,DCADHDGHAGBAEHECHCGADHCGAEGBEGAEGAEGACAHGHDCBGHBGFBCAAAACBBEEBGBCFCAFDAFDHFGABGA,False +269,1.0,3.0,0.0,1.0,3.0,4.0,3.0,1.0,GHGGEBEFBFABFEDF,True +270,23.0,19.0,18.0,18.0,15.0,13.0,11.0,15.0,AHDAFCAECAFBHBCEFDEFCEFEDAADBADCDDFDAFGEHGEAGHADBBEACFGBDHADGCCABHHGHFBEDGHFEACEFCBAGAAEABEABGABHBEABGABFCBACGDDHFCHBCHBHHCEDCDDCDBC,False +271,7.0,9.0,4.0,6.0,4.0,10.0,14.0,6.0,GDDGADGAHAAHABDGFFFECFBHBEGEGHEGDCABGGFFHFFHFBGABGDBGCBGFGCB,False +272,9.0,5.0,1.0,2.0,6.0,2.0,1.0,1.0,EDAEAFECFGHAABAEDEBBEBAABAA,True +273,6.0,7.0,5.0,6.0,3.0,4.0,5.0,6.0,DBGDAGHAGECGFBHFBGDDFEDFHCBBEHHCAHBACBACAD,False +274,13.0,30.0,20.0,14.0,22.0,14.0,15.0,16.0,HBGBBDCBAHEFEBDBCABCGFGEHGECGCDECDBFDECGHBFHACDCBBHEHGGHFGBBBBHBBHBBGBEABHDBGDEGEFDECCFHEBHEHGEFCFBCFCDABAAHEECEECEDCEDGEBFEBAABGABCBCAAFDAFDHFC,False +275,5.0,8.0,10.0,12.0,2.0,10.0,10.0,5.0,HGDDCDFCDBGFCGDBGEAFACFDBDDBHDBCDCCFGCHGDFGCFDABHGBAGCGFABFEHF,True +276,5.0,1.0,0.0,3.0,1.0,2.0,0.0,3.0,BDDHFAHAAHAFEAD,True +277,24.0,23.0,18.0,24.0,16.0,33.0,19.0,28.0,ADCABCHCAHCAHEADEAHBGBCGFGFFGAFBDFGFBGDEGDGHHGHHACDDGFFAFFBFFEFADHDDADDFFAFGBFBBFHFCHBDADEAHECEDFDGFDFFDCBBHDAHBBHCEGEBHHBFFCCHHHHCHBBHDHAGCAGEDEHDGHDAFAFBBFABFAEAAGABGFEHCCBCHECFEDFGFE,False +278,12.0,29.0,23.0,26.0,19.0,18.0,23.0,13.0,BEBBEHBCAFAHEDDCDBBDBBDAFFAFCADCGGBGGCGHCFECEBDECGEHGEADBFDHFDGCDGCBCCHDBEABDCBDEBEEBDCGECBDHBEHEAGAFGHFHEFBBDBGEBFHGGHFGFDGCDGDDCFFFDFECCGCGGFBDBAACHEDBDDBGCAGBBC,False +279,16.0,11.0,17.0,16.0,19.0,22.0,19.0,14.0,GFAAFDCCEGCHGBEGDABFBDFEFEEBEBGFCGHHHFHAFDADEAHACBFCDFHFGCDACDFCGFEDFEGADGAFCEHCAHBBHEGCDDHDCAFCAFGEEGEEFBEFEHAHFDEFDBGDBGAFCAGCGGCGHE,False +280,10.0,14.0,13.0,11.0,22.0,14.0,17.0,12.0,EHCECEHBFGCGGCAHCDGCGGEDBBBFHCFBFBBFGHGHFABEAEGACGACBFDBCEECDEBFEBDGHDEBEGGECGEHGEDEEHFEHFEGFAADGADEHDAFDHFEEFCBA,False +281,32.0,31.0,18.0,18.0,36.0,28.0,25.0,12.0,GAHFABEGCGAEFADGADFABCADAEBAEFEHFGBGCBHDAHAABBBECFEAEEFEEFEDAEBAECADCDDBBBCBBEDBFAAFHEEGFCGEEGEFGEFAFDABCABDAFGFBGFEGBEACGGHFGAFHBBDEEEGGBHGFFAFFGEFGEBGDCHCHGBBGABEABEFEDADCEEFDCDHCDBGABAACAHCEFCEFBEB,False +282,19.0,24.0,17.0,28.0,20.0,14.0,18.0,11.0,CEGDBCDFGFGCADCEEGFABEDBDBBDEFDEADBGBEGBACDDFDHFBHGGCGAEGHEGHECDDGDFGEFABAEEHDFBDFBEEBHCDCCEHHDCGDBHDFDDADDEEDBBBBABHAHDABAAGADBCFBCBECDAGECGACGACFABFA,False +283,26.0,21.0,30.0,21.0,22.0,23.0,22.0,14.0,ABEAFHABHEFEEFBHDAHFBHFBAFBCBGGHGDHFDHFBEBBACCAECAECACGBCFFEFCEGGACBCDFAAHABGDEGDEGDACFEGDEGAFAACCBEABGAFDCFDFFGACHCEGCFGABCHGAHCDHCDCCDCGABDFBDEDCGFFBFEACCDCHDGGCGEEAEBAGDCDDCEEB,False +284,14.0,18.0,15.0,12.0,15.0,14.0,12.0,12.0,DHBFHFFADGAHCABFABEEFDEAGEAGDDBACBCCBGCBEEBEAHEHCFFCEFCBCGDCGDEGHGGABADBEEBEHCHHDBEGGFFEFDADHAHBBDFBCCBGABCFHCFA,False +285,16.0,15.0,17.0,12.0,11.0,20.0,18.0,11.0,HGHCBHCECFEHFEGDAFFGFEGFEAFGFBGABDBBGBACBGFBECAAFDAHHFGGAGGAEGCBDBBDHEFGGDGEHAHADEADEFCCFCFADDBCCBCABHAFFCFGCFDCFACDBCGH,False +286,11.0,13.0,7.0,7.0,10.0,17.0,12.0,13.0,FDGFDGFHABDDHFAHBHFFGCFHBGAGFFGFHHAGHEGHCGBCECDECDBHBEHBEHCAFGABAFBGFBEFGEABFBFDEFAEAHEABC,False +287,8.0,6.0,3.0,14.0,2.0,6.0,4.0,6.0,BGDFDCCDGAFBADBDHHDHCDHAAFAADBADBFDEFABDGHEGDDFHD,True +288,13.0,9.0,15.0,13.0,19.0,11.0,16.0,13.0,GGEDADGABGCBHAGACCFCHECDDCBAFEEHEBBEABEACFACEDHEAFEGFGDAEAAECDEFEHHEHBFFDCFDCDAGDHEBHCGHGGHCEFCGFEGEDGDCGHBGH,False +289,21.0,24.0,27.0,24.0,13.0,22.0,21.0,28.0,EBFBBCGBDHCAHFAHBBHBDHBDHADECDCAHCGHGFHADHDCHFBBAHBDHECABFBFFCDFGDFECBECBCHEAHFHHEHGGFAGBDCEHCFHCGGBEGFHBFGAFCADDFDDBDFCAFCHFDDACGACGDCGAGGHDEDECDAGHBFABABBEFBCCDEAHGAHGCCGCFAHDGHC,False +290,11.0,5.0,20.0,12.0,8.0,15.0,4.0,7.0,CBCCHDDHADEADEFDAACCCFFDFCAFCADCGDFEDCECCECFFHFFAGFCEDEBFFHCHGCDBHGCFDAFBAEHACCACB,True +291,20.0,16.0,14.0,23.0,25.0,13.0,17.0,18.0,GBEGBEGFEGFBFDBFDBADHAFBDFGDEGDGGECCECAEAADAACHHHHBHEGDADDBHAAAEHEBDEBGEAEHDGHAAHFABCEGDFGFCECDGDABDHBDECCABFBEEDEGFEHFEHGAHBDCDAEHAECDCFDCEDHGHEC,False +292,22.0,21.0,19.0,22.0,30.0,26.0,23.0,31.0,AHGAHGABADGFGGEEAEFDCABCFBCGBCBHCBCFEDFEDHADEFDFBHCBHAHEAHEHHEHEBGEAGEDCEHGACGDCFCEFDEBDEBDFHACEEHBDDGGEBCEBCGHFGEABFAEEBHABGAHGAHDHHDHEABEGBFAEGHEHCADFFDFGAFCDDGFHFFGFFDEBCHFEGFCDFHHCHFBEGHHADH,False +293,16.0,24.0,24.0,18.0,24.0,17.0,14.0,18.0,BDDACEACHABHABHECHGHEGEEFCHFAFAGFBBBGBEECEEHEFDBDDBDDGCGBCEHCEDCBFABFBBCCECCGBEBAABHECEGCEDDECFECFHCFHCGBCFFDDFADFAHHCGBBBCAFEBHGDGADGAHCBEAAFGDBHHEDCEDFEH,False +294,32.0,23.0,12.0,12.0,9.0,21.0,14.0,23.0,BCGBDHDCGGGDAFDFFBCABCABCFGGFAAFBHEBHGBGGDAFAACABHBFFDAFAHHBHHDHGDEADBHGBHBBHBBFACCBECAAAHABHAEAEDFGCCEAFFHEBHFHHEHDABAAGAGHADAAHAACEAHAAFFBFFBFFH,True +295,25.0,28.0,34.0,29.0,21.0,15.0,21.0,21.0,GBBDDFEAEADECDAGBCFBADECDBBDCCGCAGCDBCBBCBDCBGCEHCGACACFBHFDDBCHFCGAGGECFFABDEGDEFDHFHHBBHDAEDBEDCDDCDDCDAADFACEDHHGACGBBGAGAEGFGGHCACCDHGEHGEHGHCEACBHFEAAEACEACHHCHBCBECHHFEBBDCBFCBDDBDABAEFAHG,False +296,10.0,5.0,3.0,10.0,3.0,6.0,4.0,2.0,FCDBCACHBFABDAGEAGDADEBDFDAFGABAADEADHGDFFD,True +297,18.0,24.0,24.0,26.0,29.0,26.0,24.0,26.0,HAEHBEAEEHCACDDCFDHFGCBHCBCDHFDEADBBGCBGABFAFGGHGEAGDBCCGCBDFDDFBEFBEGDEGAADHADHBHADHCDFEFFEGGEBAHBCFGCEGEBGBFGEAAEDHFDAAGHFGEEGEEDHECGEDFEBBDCCDBDECFCBBEFHFCGFEHHEHHAGHCEHCDFCDFCDHCHGGHFEFFBFHBADB,False +298,13.0,9.0,11.0,21.0,12.0,21.0,9.0,8.0,DDADBAGGAGEAGECGEFHFCCFBCABCABHAEFABFDFCHHDDEDDHADHCHABFFFEAEDCFDEGGFDDFCDFEFFEDFEBADFDDFBDFCHBGFCEDDAFG,False +299,9.0,10.0,7.0,5.0,4.0,5.0,9.0,5.0,AEBFBGFGGAGGADCADGDHGHEBHBBGEBGFCHBCHAAFAABCECCFDDBCAB,False +300,9.0,10.0,14.0,12.0,10.0,5.0,22.0,10.0,GBDGFGGEGEHGDGGEGCCGACBDBBDABDAEFABBCEAEHAGCFHDGHGGDGADGHGGBFCDHCDGCGBDAACEHCEGCEGDHCHECHCBF,False +301,23.0,15.0,14.0,8.0,21.0,17.0,19.0,20.0,FGCEGAEGEDHEDBGGECFFHEBBBFDAHHEBAEBHCHEGAAHABEEFEEFGBHGCHCAHDAFGGHGDHGFAGBABFAFHEEGEAAEDAGFAEFACFACBHFDCEHBAHCAHGAHCCGCCGEAGEACFADFHBBHBF,False +302,27.0,23.0,30.0,20.0,17.0,18.0,24.0,20.0,AACCCBGDBFHBAECFFHBHHGHAACGCHDDBFBGGCHGAFGAGGAGGAHGCHGCDGCHBHABFDBDDEEDEEDBCFCCFCHBHFBAFBDFHFBAAAFCCGHCDBADAFCABEACGBFBEEBAEHAEGAHGACBBDACDFCDGCDGHDEEDEBCFFCAACHECGCBGCEGCDAAEEHGD,False +303,30.0,27.0,22.0,22.0,20.0,20.0,25.0,21.0,FCHFDBBDBGCAADEBGFBGABGFEGHAHBADAEDACBECFFCFFGDBGAHHAEHFCAFAACEDCFFBEFAEABHDGAEHDDBGCBGEBGEAEEFBEBDHDAAACCHCCHGDAGDFCFABFHBFHBGBBDHBDHEEHECHDCADAEDGBCCBAGEHGEBGFBGCCACCAGAADAHGHHGFDABGGGD,False +304,29.0,17.0,17.0,22.0,14.0,23.0,28.0,17.0,DABGFCFHAEGAFGFBCCBEDDHFCADEHDEHGHDGADGHGGCCFFFFCCEGHEGBDDDDDFDFGDFGCEABADBCHADBGDCDAHFFBGFGGHAGHAGAEGEGCAAHAAGAAEBAGBGFBHBBHBGDCGFCDFBAEBHCFEAAEAAHGAHGAGFACFDCFEAFDAB,False +305,11.0,12.0,13.0,10.0,10.0,17.0,17.0,13.0,BFDDADEGGFGEFBEAGHAGBACAECAFFBBFHBCHGFHGHGFFGCFCBBAGCDGDDGCGHCBHDGGFHFFHGDECDFCDEAGFAFBAECAECHBHHEHCEBF,False +306,7.0,10.0,4.0,3.0,5.0,2.0,7.0,5.0,BHBHADABBABGABHDGHDBCEFEEFCEBCEHGGCGBAABGAG,True +307,17.0,17.0,13.0,19.0,19.0,19.0,22.0,12.0,FDEAAHFFBFBGFBDFGDFGDBGDBGFBFFHFFABEGGGHAAHEAFEDFCBFCEDCDAGBAFBGHDHCGHGDEGDGCBBDHGABCDHCFHEGGDBCHECEECEADEAEGAGBAEEDDEGCEGCHACBAFBDEDAFGAE,False +308,16.0,19.0,32.0,19.0,25.0,21.0,28.0,24.0,BCGCCBFCFGGDHGDADAACACGGBADDGDDGFBCHHCFECDGGAEBAEGHCDBCHEEHAEHFEFFEGFEHDCCCEGHFHHGBGDEGFHCFBFHBGEGFCGFCBHGBHEBEEBGBAGEEGHEAHEBFEBHCBGGDGDCHCCACCADBAHEDFGCACCHHCHHFBAFAEEDCECCDFCDFCDFEG,False +309,12.0,7.0,7.0,14.0,8.0,9.0,9.0,23.0,HFHHBHGACFAHHHHHDHBGHCEHEHCFHCBHDAHDAHFGDDHEBGFDDHADHBDGEEGDACDAHDAHCGHAADAECBEGEFFAFBDFG,False +310,7.0,9.0,2.0,2.0,5.0,3.0,5.0,9.0,BBABAGEAHBGHFEHBEHBHHAHBEGBGGBDACFCHFDHAAE,True +311,26.0,28.0,24.0,21.0,11.0,21.0,26.0,17.0,BFBEHBHGFHFHDDGADGADGFDCFBCHGFAEAAEAAEAABDDGHDBEDCCGFCFFCBBGGBFHCGGGDBGDBDEBCFBCABGDBGDFGEGCCAAHBGHGGFFBAHBAEGCFBCECHFADGGCECCFCBACBGBBGCCDAEHABFADDADDAFBHFCHAAFAABHHCHBCDBGA,False +312,23.0,13.0,12.0,13.0,21.0,13.0,8.0,13.0,FBAFBAECDHHEEEEAACADHEDAEAEFAEFAEGAEGAEAAEAGGBCDDFHAHHFFHFCCACAEFAHFAECHEAEDDHDGBBCBDFEHEAHBAHBAGCCDDDFGEGEFBBDBBCCB,False +313,3.0,1.0,2.0,0.0,2.0,1.0,1.0,1.0,HACAACEFGEB,True +314,19.0,17.0,14.0,10.0,16.0,21.0,10.0,13.0,AHDAHEEFAEAGCADFEHCEBCGCCGADDADFADFAHAAHFEHFEHFEFFCBFEBAAHEHBEBCCGHEBHCBFCFFGEAHEACBABBABFFGFFGBBBFBGDGCCBEDADAFBFFCHEDG,False +315,3.0,8.0,4.0,7.0,12.0,10.0,4.0,14.0,DHEDBEDBECHEFFFCHDAEBAHHFHFEGFECEEDEGHBGFBAHBHEBEDCFHHFHFDHGBH,True +316,19.0,13.0,26.0,20.0,13.0,13.0,16.0,14.0,AFCBGBFCAFCEECHBBAGCDGCFGHEBHEDCCAHCFEAEDDEDAGCAFCACCADCGDEBFAGDHGDCBACHAGHBFHCGECDCAGCADADFGDCGDGEDFADCADFFDAEDHCCHCBHGBHEBFGBCABHHDE,False +317,16.0,18.0,21.0,25.0,22.0,16.0,21.0,17.0,GDDGDDEDFEGFEDEEDHBDHBCHDHBBBBBBCCBCCHFCHBCHEHADGCDGCBGAFABCEDFFAEBCHBDDEADCGDEFAEGAGCCDCCGFDFBDHCGHGAAFEADAAHEBHEAHFCCDCEAHEAFGBGEBGDGEFGFHGEHFAFDGEDGECEDG,False +318,23.0,22.0,20.0,24.0,12.0,20.0,16.0,25.0,AABCHBFHCDHCGFGHDHHFGAGHBGHBGCEECAEHGBCGDDDHCFHGBHGBHEBHDCCAHCAHAHCAFCDFHHEBDDBGDGEABBAEBCDDFDDFEDFACFABFCHHCHHGBFAEFBCGBDHFDBFDFDAADAFDCEHCBBDFAAAAGECDABDAEFABFG,False +319,9.0,5.0,11.0,3.0,6.0,3.0,10.0,12.0,HABHDEGCCCDFCBHCHHGHAGHCGHCDHCEGCGCEGHEAHFABAECGBBAAFGAEHAG,True +320,31.0,18.0,28.0,29.0,18.0,25.0,23.0,22.0,ADEFDADBAGBEGHEGDCAHAAHCFGCHGFEGFHGCGBFDAFDCFCEBABHDBAFAFFDGDAAHABGGCAFCACCDEBDCCGCCDCCAFGGCHBDHGCHAHBBBBBCCGAADCBDEFDHCAHCHHFHAECDCHDGHDEADEDFADBADEEDGCBGCBGDGEFHAFEAFAAFGEEDCFDHFAHFAFFAEFHEDGD,False +321,11.0,11.0,8.0,16.0,26.0,18.0,18.0,26.0,HFGEAHHHHDBHGEHDFAGGDEFDEFDEFAEFBDFHDEEDEEBGEHEHHEHACGGEBHEGHEFHEHAEGFDGDDGBCEAEGAECDHCGHFEHGAGFCHHEHHFGDFEFFHBFABHDGFFBCEBAECGDABDHBC,False +322,6.0,3.0,4.0,2.0,1.0,1.0,3.0,2.0,CAAFAEHAGBDHCDBCGBAGCA,True +323,10.0,11.0,20.0,18.0,16.0,14.0,16.0,14.0,FCGBEHDGCCHABGBCGACFEFEEFEDCCCBGCFHCDAGDAGDEDFHGBAGEDFECGACGEFGEFEHCDHCDEFHGBHGEFDEFDEADBAEHFCBGCHDCHDCBDCFHBDABGAHDHCD,False +324,14.0,16.0,12.0,17.0,15.0,23.0,16.0,14.0,HDEBDGFAFHDDHDHECHEBHGHEGEGFADHGEFGDFBCEBGAFFAGFHBDHGDCGDCACFECFEHFAFBCEHCFBEFCEADHABCBBCFBAFAGFAEEAGBBECBDGBFGHGBFDDFDDFGAFDAF,False +325,15.0,13.0,7.0,9.0,15.0,10.0,11.0,11.0,BDABDCBEEECAECHCFHBBHDHEAHEAGEDEABEDHEGGFGGFEFBEHEEFBHAAAAAADAADFAEFGHHDFHGAGBBBBCDCGBFGFCG,False +326,18.0,22.0,21.0,20.0,18.0,16.0,22.0,11.0,FAHEBHABFAHGAEGHHBBBCBGCBECAAGDACFBCFEHGDHDDCDDFFCEGHEBHCFCDFCDGCHBAGCEBCBDGBDCBDHGEFADGEFABFGCFCDBCGACGABFACDEDEBDAFAFFABGEBGEGEEDEGDAGAGGEBGCBDCED,False +327,13.0,17.0,20.0,5.0,21.0,19.0,14.0,10.0,CACCAECGEGAFABCCDFAFFHFCEFCHAHBGEECEECGEFDECDECEEABFBEAEEBEDHCAHAADBABFGFFGFGGFBGBHEBHGFGEFBBGCBCCBCBECBCGFEHFHBGHACEFF,False +328,21.0,20.0,17.0,13.0,23.0,15.0,20.0,19.0,HECGCCHADAADGADBEGBEABEHFGFGGFGCBECFHBAAEAHDFHFFBGEBGCBFHAABAABDCBDCAFAAHCGDCGEEGHGDEGCHGHBFHDHCDBCFEAGCAHCEHEEFEFBDHHDEBEEDEBGGAHGAHBEFBECEFABGABEC,False +329,24.0,23.0,29.0,30.0,30.0,21.0,23.0,19.0,HADHFBHFEHCEHDHCDFCBABEEBDEHDACBGDBCDBGDBADCCDABAGCEGBDGBEGCDFAFFGEFGAGEAGEADCGHGBDEDAADEHBAHCAEGBGFBFHBGEBDBBAEEDEEFAEDGCABCEDGFFGECCDACHBDGBDFCHECHECEACEADDDEDFADFAFHCFGCADCEECFCCFCCAEBGGHHCHFDHFEG,False +330,7.0,6.0,9.0,9.0,7.0,8.0,16.0,10.0,HGGAAGEEFBEDHFDAFBAEDFGHFAHGDHEECGHCGCCACGFGHFAHEBHCGGCBGDHGDCGDCGBGDBDF,False +331,15.0,22.0,24.0,18.0,22.0,22.0,16.0,24.0,ABAFBECDEDAHCCGCAAHHCHHGBBGBAGBDGEDEHAECACBBFHHEHHEHHFHDCHDCBGFHFFHAEBFEFGDHAECEECBEFEGCCFBCGBCDEGHBGHFAHFGDBGEAGFADCBCCHCFFDEFEEFBEFHEHDCDDBHDBGFAFFBCCBCFBDADCGDE,False +332,9.0,18.0,16.0,12.0,7.0,14.0,10.0,14.0,AADCABGADACDAEDCHGCBFHBFHBEHGEFGHGECFBCDDGDAECHBCEBCFBCHHFDHDHHFFDFBGFGHBGECCFDFHDBHGBCFFABBACBCBBCB,False +333,24.0,10.0,12.0,14.0,8.0,11.0,24.0,18.0,AHAAHAADADGFHEEGBECBDCEACAHEGHEFHADAADFHGBHGBGBCGAGADGADGAHCAHFHFGEGGBACDCCDGFGBHCFGAFGBGEHACHAGGCDDHDAADGHDGFCGAHBAHBGFF,False +334,17.0,19.0,16.0,21.0,12.0,28.0,7.0,21.0,BCEAFGACAHCFEBBDBBDFFDBCDBFDFFDHFABDGBDFFGFDHFCGFGHCBHAFCEFHHBHHAHFADFBFCBFCBDCHEHDCADFDDEHDECDFCAFAAHABFBDFHFCDGHDHHCHECBEAEHAEFABDEFAFBGHEA,False +335,5.0,1.0,17.0,8.0,5.0,13.0,6.0,9.0,HFEEFACCHDCHDCHFBHDDCACCFCCGCFFDEFAFGCFHAEGFEGFDCCAFCHCGDCGDCHFH,True +336,7.0,5.0,7.0,10.0,4.0,6.0,4.0,9.0,CABCEBDDFADCAFCFGCEGEHDDBFGBFHCHHGHHDFDEHDAACAADHBDH,False +337,17.0,14.0,20.0,15.0,14.0,12.0,26.0,25.0,FEFFADAGDAGFCHHBHHBAFEECECAFCDFDDGGCHGCHFCGDGGBBGDAHDHECHGCBBBHDEHCCHFGHFCHBCHDAHCAGCAGEBHEBAAACEECEGGDHCEBFEHGHCGHCGDABAGHGGBBGFGGDGHHEHDDAAGA,False +338,17.0,17.0,8.0,23.0,13.0,10.0,15.0,13.0,DFFDBGEBEBCDBFDBAEEAFGAHDDDBBDEBGEBGBAGBGBCGEDEAHHADHDDHEDHGGHADDBDHHDCHDAGAECADCHDFBBFABDAFCAGDFFCAEGAEGEFGBDGCHAHA,False +339,18.0,24.0,23.0,25.0,16.0,22.0,30.0,24.0,DGBDGDDCDGCBGFEHEAAFCACGBFEBGCGCABCAFAGEAGEAHDCHBFEGHEBDDBDDBGABGFDGFBHCAEEAGDHEHFEFEHFGHFBFFGCAGCACCDHDDHBDFGDFGEEGBFDHHBCHDFFDCCABGBDGECBEGGGHDCHACHBHHGGHBGABDABHFCHFHHDBABGFCGFCDC,False +340,2.0,2.0,13.0,7.0,3.0,3.0,2.0,4.0,ECCCDCCACCBDCDFCDGAHHFEDFBDCDCCHGCHE,True +341,4.0,3.0,4.0,1.0,4.0,2.0,6.0,4.0,GAEGBCHBCFGAHGAHBACEECEGHGDF,False +342,10.0,14.0,13.0,18.0,10.0,15.0,4.0,7.0,BFBBADBAGACCABFAECCFCCEDEHDABBAFGGBDBCEBFDBFDEHDGHFAEECCDCCFHBFDEDDFDDCDDEHDEFFBDFBDFACHAFH,False +343,2.0,3.0,3.0,5.0,8.0,5.0,2.0,1.0,EAFDCDDCHEBFEFDEFEABECBFGEDGE,True +344,16.0,17.0,10.0,12.0,19.0,14.0,18.0,24.0,DGDFEBGECFCBBGFFEFHEHBEHGCBACBEGFGGHCBHGBHAEFBFFBHHBEHAGAADFAGFAHFAHGACGAEHABFGEGHEHHEHCABDAHEABCDHGEHGAHDDHDDBEFBGDBADGCHECHDHEEE,False +345,12.0,6.0,8.0,11.0,11.0,7.0,6.0,8.0,EEABBCDDGADCAECADHABGABECBECFEFFECDEGHAFHDGHFHAFAABDAHCEHAEHFDCDEGDGD,False +346,14.0,12.0,14.0,18.0,13.0,23.0,16.0,8.0,ECHBFBAFEFGCCDDGFDBFEGFEAFECFEHFEGBDDCHDHAAGAAGFBDBGDADDHGDCFFHEEHCEBGDGCFECFEBFDACDFGDAGDGGCGBABDCBCBAFFAFFAFEAFDHFCG,False +347,13.0,9.0,9.0,6.0,6.0,16.0,14.0,5.0,GEACFCDFGAFGAFCFFDDGGDBGDEGBAAHGAHFFBFFEEFBFFBFCEGBGGCECCAAHAGHAFAAHACGGFBCBBD,False +348,2.0,2.0,2.0,3.0,4.0,6.0,4.0,5.0,EFGDDADHEFBAFECFECFHBFGGHHGH,True +349,25.0,25.0,26.0,14.0,12.0,22.0,23.0,17.0,GCCGCCGEEDFADFDCCEHCBHCBGBBCBFGBAGFGHBGABFAGFBFFACCHHFHABAABCABGHEGBCGBFFAFGACCDDCBFGFAAAAAEACEFCEFCADCAGHAFABFDGADHHGBBCHGEBGCBHCBFDHGHHCEHBBBBEFAFHDDGFDCAGCAGDEDE,False +350,26.0,15.0,7.0,12.0,18.0,16.0,17.0,8.0,GFECAAAAAHFADABEGCECDGDAGEABEGBGBBGBBGCHEFFDFFAAAGEAFBAGDHHFGGAGEADFAEEBEFCGFDDFGDFDBFBEHHAHEAGEABEABEBBADAADAFFCEGCHAE,False +351,19.0,24.0,27.0,20.0,25.0,23.0,28.0,19.0,HHCHFCDGDBGDFGCBGDFGBFEDFBGABHABCABGBGAHGBHGBABCCEEBDFGDHGDBGHFGCFGCBHFBHECGCCBCGBFGACGDCHEEDFBGABFAFFGHDAEAAHDAFDEFDEDEECFEGHECAGCECCFCBABFADCAEGEDDFHFECFEGABGAHDHECBACDGHEEEEHECBECGFC,False +352,11.0,14.0,21.0,19.0,18.0,15.0,12.0,19.0,CGFBDFCAEDFEHEHCEACEAEEFGDAGBACBFCBFABDDGHDEHFGADGHDHCBHCEHCDHBBEFGFBADCGBHEADECDCBDCBACBACBDCHFHHCHFDGCDECGHCEEGHEHFFFFGEHDCHDED,False +353,14.0,12.0,11.0,22.0,22.0,10.0,7.0,14.0,BDEBEHDFDDCDEADEHCFHCAACAABBCDBHHEDHEFBAFDACABGEEDEADFADFBGFAGCGHCFEAEDGDDFDEEBEEBEHHEHHEDEEBHHCADCACHDDGGBFEDDE,False +354,25.0,23.0,25.0,17.0,15.0,24.0,9.0,25.0,FHABBAFCCFBCFBEDDHCHGBAEHCEBDAADFADFHFHHFHBFBCHBHHEHDACDFFAGBGDEGHHGDDCCCAHCEECAEDECFBBHDFCEFBAHAAHAFHAFHBFAAFAGGACEAEDAFDHEGFCFFCDFHGFHACHABBABECCCCACCBBCDBEBBHDB,False +355,17.0,20.0,28.0,20.0,27.0,26.0,18.0,20.0,FCDHEAHEGECAEDAEFCHFEFCCCCBECHEHEDHDHHEGHEDFEHAEDGEDGEFEECECHGCDGCBEDDEDDFDDBGGCGBHHAACABGGBCGBCGDCFHCFBCFBHFAHFEFFCFFBDACFCHBHEEFBGFBHFDGGCECAAFACFBBBABBDBEHCAFFEGCADEADFFBCGA,False +356,11.0,9.0,19.0,9.0,17.0,23.0,24.0,22.0,DCFDCHHGFEAECFFCFFGEFGFFGAHGBHAADAACEFFGGEHCAHCBDFFDGGHHBFHBHHAHFFGGFEGFCGFCHCGGGGEEEFCDHCDECHECEBCFGCHBCHAEHCEGFDGCHBEHBGHBGHFAEAEGGD,False +357,15.0,19.0,23.0,15.0,30.0,8.0,15.0,12.0,EDGEGBEGAEFADGHEFEEDEDDEGGFDAEEAGDAEEADEAEBBCFBCGECBEGGACEFBGDHECHEAHEHGGABCEDDFDDEDBHDBCBACACCGCABEGHCHCCBCCAFCHBEHEHHCCBCEBCEBCEBFBBECA,False +358,8.0,10.0,3.0,16.0,6.0,11.0,10.0,8.0,EADHDFFDBFEGFGCCAFCBHDGEDHDDFBBFEBHHDAHDHEDHGDAGDAEDGDGFBGABGFDGFABBADBF,False +359,20.0,14.0,12.0,8.0,11.0,4.0,10.0,13.0,BAHGAEDBEDCADCAHBABAAFAACGBHGBHABHEHCCHBCGAEACGDCADCHGAECADFAEBDEHFCHEAADHAGHFBEBCEAGEBGBGHB,False +360,26.0,15.0,17.0,18.0,13.0,10.0,21.0,9.0,HCBGGBGGBCCDDCDCCHCHHEGGEAFEDFAGEBDHBGAFGDGAABCADCEGCFGAEABEADHABGAEGFEAFAFCACGADDBEAGAABAHGDCDEADECDBCDBCBHCFDDFAGAEGAHGAGAAFBDB,False +361,15.0,32.0,16.0,34.0,25.0,18.0,29.0,23.0,HDFHFFDABBBBEEBGEBGEDEEGAHGBGBBHDAEGCDACHECHBGDBGDBGDGDDFBGGDEBFAHHHHEHHAHDADDEDBEBBHABHAFGDDBEDHEDHDDHGCHCEFDGGDGGBCFCCFEHFGGFHAEDFDFFCAEGABDFEDGBAGBGDBCFBCHEDADDCDCBBBDEBDEBGHCGBEABFCGGEFCEG,False +362,22.0,28.0,20.0,25.0,21.0,16.0,11.0,16.0,BHCHFBFFBDDBHHBAHBADBAHBAHGCCFCBBDBBECAEFEDHHBCCFDCBBBEBHEBFGBHGDHCFFCFAHHAGAGDBFDGFDBCGEADBFBBAAFEDGEDFDAAGBAGAABEDDACBECBEFDAHCCCCGCEEHAEADEDDEDCEACEAEDDEDDE,False +363,11.0,11.0,7.0,6.0,9.0,8.0,12.0,8.0,FBADHHEHFGGCGAFEAFEGFGGHGHCCHCCBCABAEBAHDDCGFABEABFABABDEBDBHAGGFBGEEGDE,False +364,5.0,2.0,8.0,2.0,1.0,2.0,9.0,6.0,AHGACBAGHCGHGBEFDAFGACHCCGCDGCHGHGC,True +365,33.0,17.0,16.0,24.0,25.0,19.0,21.0,11.0,GDDGDDGBDBAABAFECGEDGEDFAGCACCFHCGHCDAADBACFCHEDAEHABGGHCEEEBAEFEDFDCFDHFDAFAGFBCDAFGEDDEHBEDBDCBHCAGFHFDACAGDABEABGABGAHCAGDAFFGEFDEFGFGEEEAEAAEAAEAEFBBAHBABCEGEDGAA,False +366,24.0,28.0,22.0,9.0,23.0,15.0,15.0,17.0,HEGHECCBBCBBFAEDHBFCBFBBFABGEGCFDCHCCBAAHAADABBBBAECHECEEHEEBAECDDAGDFGDFCDCGBCEBCABEABAAEHGCHEFHEDHFGGAGEHGCBBAFBAHCFEEGAEGABAABAHFHBCCCEHAEBBEGCGFFBHFA,False +367,22.0,19.0,28.0,25.0,31.0,21.0,23.0,26.0,HGHDGHDGEBCDDCAEEADEDEEHAHBDCEEBEFGAHAADGDHBHFCEGEDBFDEFEEBEBCEFCEFCBACBADHADEGDAHCCEDDEDHFAHECDDCBEFBEGBDCHCHAABAACCHCCHCDHAGCAGEBEEAFECHBCHGCGGHFCFAGGEDAFDCBECBEHDEFFGFDGFHGFGGFGFFBFHBCCGAGHAHH,False +368,19.0,23.0,22.0,14.0,18.0,18.0,13.0,20.0,GAHHDGFBGDBFFBHGADABEHCCFDCBDAGDBFBBFBBFBFFEFFAHCAFGAHADHEBFBAFBECCEBCDDAEDGEHBBBBACBAEBDECHEGFCHACFDBGCHHCHGEHCCHCGHCGECEAGACHFCHFCHDEEEEEBDACAAHA,False +369,8.0,9.0,10.0,4.0,11.0,7.0,17.0,8.0,GEHGEBGFGGFCGEHAFBBFCBHCFDCGEHAEGCCGAEGBBCHBHFEAFGBCGADGADEADCGCHGEBAEGHEG,False +370,14.0,14.0,22.0,16.0,19.0,13.0,17.0,12.0,AEAAGFACECCFHBFDEGEAGADCEHCECCADHDEGFGGCCGBHGBHGBAFDGECGECGHBDHBABFACDDEBFECFEFFCAFGEGEEGHGCBACBCBDABCGBDFEDEDDHDFBDHCCHCCHEADE,False +371,24.0,19.0,21.0,13.0,20.0,18.0,17.0,23.0,GEGEADCDGEHBDCBDHAHCEFCEFEEFCDFBEGAGFHGFCCHCCFFCFFAADAFCABBBHGCHDHEAAGCAGDABHHCHHCHGBEFAAFHAFHGHHGDADEABEGBCGCDBADEHHEHACDABGECFEFEEABEBBHBBABCAGCFGEFABHAH,False +372,3.0,3.0,3.0,4.0,0.0,2.0,1.0,2.0,DDFDDBCABHABACFGCH,True +373,11.0,27.0,14.0,16.0,27.0,12.0,14.0,25.0,BGEGGBDBADECHGHHEHADHDGAEAHEFHBFHEEDGEDECBHFEHEBHDDCEABEAHEAHEBEEBEGAHCHHCBBBBBBBCCGDFGEBBEFHFDHFDHFDEFDEDEHGEAEEFBBHBBADBCBCCBGFDGHEFABBGHCCCGCHH,False +374,3.0,9.0,10.0,10.0,8.0,7.0,11.0,11.0,GCGGBBHHCCGFDGFDHDDHFDBFEGEEBECDDAECCBBCHGCHGFHADHACBEFHEBHDBHDGGFGEC,False +375,23.0,33.0,18.0,22.0,30.0,18.0,26.0,23.0,EBDEBDHHGCCGCFGADGBCGHCEHFEHDEHBEGDDGBHGAHDAHDBCBAABCFBCHEFDADCAEBBBBHBAFBAEBAHBHFBCAGCFHDADEAFECEECEFBBGGCCGEHHBBHEDCAFAHEEFFEAGABGCDGBBGBDFBDFGDBEDBHFBGDDGAEBAGAFGEEBEECEABEHGGADGDGFHGFEAEHHE,False +376,26.0,12.0,16.0,23.0,9.0,18.0,21.0,30.0,ADDFFDFFDFFHCFCBFAGFBGHEDHEAHECHCABFAEAAGAAGDDDDCFGCAHABDEGFHBCBCADGHDGADGHEGHDGHFBHGDHCDEABHGEHBDADAACHHHHFHAGHEGHDGHDHHCCCAHDHHGGFAAAAFABFHCFGBHGAACBGCDD,False +377,14.0,10.0,11.0,6.0,8.0,8.0,6.0,11.0,FCEFBBABDCHECFBCGBHGFHECGCFAFAEFDBACADCABCHHEAHGAEBAHAAHAAGFDCBDCBDGAEHHEH,False +378,10.0,13.0,11.0,8.0,10.0,9.0,5.0,12.0,ADCHBEECEEADBACBGBBAHBGHCCHGBHCCACCFHCDBDDFFDFFBFEAEHABHDBDAFHECBAHEGHEGHEFBAF,False +379,26.0,14.0,13.0,28.0,14.0,24.0,18.0,23.0,ACEAFGAGABGAGGEHAFHDCDDFFCGHCDHAAAEFFEGABGAHHADFGDFBCAGCAGBACDDDBDDEADCCHGEAGEABHHFHCCBDABHFEEDGHBGBBHFDFCDFBDADDEDDEDHFDHFDHEDHAAFAHDGDBGEFFABAECAHHFFHFFHDFHFG,False +380,21.0,15.0,24.0,10.0,21.0,16.0,24.0,20.0,GBFFDHFBFGEFHHHHHECHEDEEBCAFAABGACGBCAECBCCBEDFCDGCEEEAEGAGGACDAFDCGBBGBBCAFFDFHBAGGDGGCCHEAFEAFCAFCAHCGGAHCACCAEGHEHEEGEEGDCHDHHGCEGAFHHEHACBCFGHBGBAG,False +381,15.0,21.0,27.0,23.0,28.0,27.0,27.0,20.0,BCBHCAFBBGEBDEDHCDGCGGCGDCFECDECEBCEBFEBFGCGGBGABFAEHCFDCHEGEFFFBGFECCEHCGFFGFHGBECCFCFAEDAGAHDAGEFFFAFDACCHCHBBHFCDAGDHGDEGDBDEHDHHFHFBHDBFDEAGCADBDDBDDEEFEEAGEGGBCGEFEEFDGHHCHFEHCAGGABCE,False +382,0.0,4.0,3.0,2.0,1.0,1.0,2.0,3.0,BCDBHDBHFEHGGCBC,True +383,1.0,2.0,2.0,6.0,6.0,2.0,4.0,2.0,CHDAEDGEDCEGEBGEFDEDGHDFB,True +384,12.0,14.0,12.0,10.0,21.0,16.0,19.0,20.0,GDHEBFGHDHCEABECBDCAHGAEGCEBCEHDEAEBHEBHFHHBBFFAFDCGHAGDCBFHGHCADBAHBGHBGADHFCHFDHCHECEECEGFEGEAGEGGEBFEGAEBAFFFEGFGGDGHFEHF,False +385,9.0,9.0,5.0,9.0,10.0,4.0,7.0,7.0,BCCBABGHBGDEGDACDBEFBHDGADGAEHHCFCEFDEBDBBDAAEEAEHADAGEHGFHE,False +386,15.0,9.0,11.0,11.0,15.0,15.0,12.0,13.0,EGCFFCFGCFHFDHCHCCHACHECAGHFFABEAHEFHEDDEBDHBDHBECDEADGFGFBGFAGFAFAHEEEBDCDGEHGAGGABAAGDFDBEABEHECFAA,False +387,17.0,16.0,9.0,11.0,9.0,4.0,15.0,11.0,DADCFEBAEAGCBBHBEGBDABFBDFDHCAFEGGEAGEACHABHAGHDGHBHHBGDEGHCAAGDAHACEGBBGABAACGACGBDGBDHBDCE,False +388,10.0,3.0,8.0,5.0,5.0,8.0,6.0,3.0,BDDGGCAECAFGAFCACADCEGCAHCADCBFFAFFHHFADEGFEGBEA,False +389,17.0,13.0,28.0,32.0,15.0,31.0,24.0,29.0,HGHCCHGBFDBGAAAAEDAFHHDEGFECFHGFCFFEHFDHGDCCFCHFCFDCFDGEHBEHGHHAACAEDAHDACGEGFEBHDHCFHEFHGFAGFACDACBHCDHCDCCDEFDEFDHFECDHDDCGDGBBCCFDHBDFBDFCGBBHAEHCDGGFHGHAGFBDBDCGFCGFDGDDFDHGHAFFAGDCEDCF,False +390,23.0,24.0,19.0,26.0,25.0,15.0,25.0,27.0,FADECFEGAEGHCFDCBGCBDDHDDHDDAGAHHAEBAGDAHBHGBFGBGGFGDCADCBHBEHDEAEHGEHDBHGBHEBDGBHECAEDADDAEHFFHFHGGCCHHEFECCGDEACEHHAHGAFAADBBDCBGABDACCADABFABEHFEBEEBDDACDEEDGGGGBHGBHCFGCFHFBHCBEGEE,False +391,4.0,5.0,5.0,5.0,10.0,9.0,7.0,10.0,FGGFGCEGEEHHDHGDCEDAHBFHFGDFEBHBHHAHFCCFACFGBFEEHEEDEAB,False +392,2.0,1.0,3.0,2.0,5.0,3.0,4.0,3.0,FBGCCGDCAHEFHFDHAGEEGEE,False +393,32.0,34.0,23.0,23.0,23.0,22.0,17.0,26.0,AABCCBCADCAHAAEFAFBABBHCCFBFGDHDHCAHFGBBCCBHCBHBFCDFBHBEABEAGEDGECBEBHEBAEFHEBEBDHAHHBGCCFDDFDFBDHBGAAACEACDACHADFAGFAGFHGFDFADFAHEAEEBEAGDDHCDEFDBHCGGDGDAHABHEBHEBEEBEHFABAHBGEBHCFDGFGFEDADCACHACBGBB,False +394,10.0,5.0,5.0,10.0,12.0,9.0,5.0,11.0,DCDEADHACFADFADABDHGHHDAHGAGEEBEFFCFAEDAGBAEBCEHDBHFFCEFHEHHEGEEDHF,False +395,9.0,8.0,7.0,6.0,6.0,3.0,2.0,9.0,BAGBECDECDCHEAHAFGBFHBAHDHHAACAACHHFHBDDBEEAEDBCCB,False +396,28.0,25.0,16.0,17.0,19.0,17.0,23.0,14.0,FBGFAAAHBHHGFCGDGGBGGEGGEFCEHCDGBBHEACEGBEADCADGEGHDGAAAAABFABFADFCCBHCADEFGEDDBDACAABAAHHHFACFBDAADBAGBGEHDEDBBFBBFBBCEAGEBHEBHEBEFBCFECFEGDGBAGDACDHCFCFGAGAE,False +397,11.0,7.0,11.0,10.0,5.0,9.0,10.0,7.0,BCHBAHFDBFCHFCDDBHGAGCHGCGGCGGFGEAEECDDFADEBFCHDCHBGABGEFDCFDFAAADAACA,False +398,21.0,30.0,21.0,28.0,27.0,13.0,18.0,24.0,CBDCAGAAEHGBHBHHFHHAHHCGHDBDABFBEHDEBCEDFDCFDCFBCEDCBAEBEDBEBBABEDGFBGFEEAEBGHBGCBACBDCEECBDCDDCAAGDGEAGEAFEGEEBEHFDHDGCEBFEBDGDFHAFHFDHECHGCDGHEGDBDBHEBHGBDAAAAEADDDCABHDCHCEHCHGBBA,False +399,8.0,12.0,5.0,5.0,7.0,5.0,5.0,13.0,HHGHBAEGABBCBBCBBCFBCBHADAAFBAEBEBFHDECEEFHGAHGHHDFHDGHAHHED,False +400,7.0,6.0,11.0,5.0,6.0,14.0,10.0,3.0,AEFAEBCFDCFCFAEFCGGCGECHFGADCBDFGCHCCABCAGGEFHEFGAFBFBGFDGFDBF,True +401,5.0,2.0,3.0,1.0,8.0,3.0,7.0,1.0,BAGCFGEEAEBHEGFAGFDGEEGECAEGAC,True +402,7.0,14.0,22.0,10.0,18.0,10.0,12.0,15.0,GHECCAABBCBBEEBEGBDCEECFGGHCHACHAHFBGGCCCCHCEFCFDCHDCHDFHECHACDBCBAEBDEBDGGEGHDCEGHECEECEEHBEHDFBFBAFHDFGFCG,False +403,14.0,14.0,19.0,22.0,20.0,22.0,14.0,19.0,ECCEDFDGEDEEBCBHDAFBAFAAECCFDCEBBEBDAHCADCFDHEBFEDFEFEGFEAFHAFHGCHEEHDDFEDFDCFDCFCBAHFAHFHHFBDFDDEHCGGBGHBAHCAGCEGAHBHCGCEDEFDFGDHGFCGBBGCHGHDDA,False +404,9.0,11.0,17.0,12.0,11.0,7.0,12.0,10.0,BCBDCEGCECEGCDCCDGGAHGEBGBHCFCAFHAFHADEAHFDHEBCCDCCDCBDHEDHADBAHCHDDGBEGFGGBECFEFEGBAGCAB,False +405,5.0,5.0,3.0,4.0,12.0,4.0,3.0,6.0,DBGAEGEEDAEHAEBBEBEEHFDCBEFGEFCAFCEHHAHEDH,False +406,15.0,17.0,23.0,27.0,15.0,22.0,16.0,20.0,EFCEGEFDBFHCCACBDDHDCFBHFHGFCECAEABGBGDHCDBCABGADFDDFECCACFAEFHDGHDBHDAHDHHDHBFEFDEADFADBDCHDEHFCHFGGFHGHHEAACAFCFBDDCEBCGBDGDEGDBGDHFCCFDEHCBBCBGDFGAFEAGC,False +407,11.0,16.0,12.0,20.0,16.0,15.0,13.0,15.0,HBGBDGBDGFGEFCCHCDHCDHFFCDBCFBEEECEFCEABEHDEDBEFHFDAFDBHBBHDACAHFAFBAEBDDDADDAFDGGGEEGHEGDFHBFHGDBGCBGBACDAHHCEAEEDHGF,False +408,16.0,12.0,20.0,13.0,15.0,13.0,22.0,14.0,HACHAGEAGFHHDDCEDCBFEDFEACBBFHBFHBCGBCACCBDDGDDBEFEGGHDBDDGGFHGAHFEGAEACDACGABAAHEABECECCECGGCAHFAHFGGFEECEHAFDGGGGCFHCGGCGBC,False +409,4.0,7.0,9.0,5.0,9.0,7.0,4.0,6.0,EFCBHCFAFFACFDHHBHCBGBBGBCEHGECBAGDCEFCDFCDEEHEEAED,False +410,12.0,11.0,9.0,6.0,6.0,6.0,2.0,5.0,DDCDHBBABBACFACEBDEHDHBFBAFBAGCAEAEEFHCBCCFHCAAEAABDABGFC,False +411,10.0,13.0,4.0,12.0,8.0,3.0,7.0,11.0,BBHBBDDDDDEEAAHAAHBAHGEHGHHAEDEEDACDBBDGCDBBABHHCGCFGFEGBAGBFDDAEHBH,True +412,2.0,7.0,4.0,0.0,2.0,6.0,5.0,2.0,BGBFGBFGBCGCEACFBHFEABHCBGFF,True +413,28.0,23.0,16.0,19.0,25.0,12.0,17.0,19.0,BHADEAEEHEEAGEFBBCDDAGHHGHAEBDFBAFBAHAEHBECBDCGDGBFGEEAEEDBDDBHDEHGECAACGACABCABFABCADEAHEDBCGFEBFEADEBEGADAAFAFHADBACHABHCCDCDBFABGAEGCGFHACDEGHHGHGDHFBHEBEGC,False +414,4.0,13.0,10.0,10.0,10.0,2.0,11.0,8.0,EEGCECCGBBGBCGDEEAGEDBHCHHADHDBHEHCFBDBGDBDDBDEADEHBCAGCBGEGCBGCBGFH,False +415,13.0,21.0,20.0,13.0,22.0,19.0,15.0,24.0,HFDBGDBHHBCCFHHFBHFBHFBHACEFEHFCBGBBFBHFDGECGFCAABGCFGCHHBHHEGFEABCBECEECGDCHHFEDAHBAEEDECDHDGHFGHFAECAFBAGBDECDCHBHHDCEFCAFEHEEGEAGEAFEDEBACBDCBGG,False +416,21.0,17.0,11.0,9.0,12.0,14.0,19.0,7.0,CGHHGBDBAGBAGBDGACGAHFFBFAGCACDAGAAEAEFCCAEFBCFGCAACGEFFBDAEDABDCEGEFCEBBHFBHEBHEAGGBGFAHFEBFBBDABFAGGAGGDGADE,False +417,6.0,8.0,8.0,1.0,1.0,6.0,7.0,5.0,BADAECHCCHCCHAAFCGFBGBBHBBGFCFHCGGBGGBFFAA,True +418,11.0,22.0,19.0,15.0,20.0,16.0,14.0,28.0,CCEHHDBHECHCGAGDCCABHFHHEHDEGBEGBDDBDEBHBBGFFCFFHBDHBCHBEHBAHFFGFCDHHDCHBEABHDBHCBAAEFDCBCCDFHEFGBDABGFBCADEFDGFAGEHGBHCBCGFAAHEEHEFHEGEEHEEHCGHC,False +419,25.0,19.0,13.0,15.0,18.0,30.0,15.0,15.0,FHCDCFBEHCABEAFAFHEFDGFDCDEHAFGAFBDBBFBBGBAHFAGFBFFBDBDDEGFBDEBHCBFCEFCEFAECAEFECGADBABAEHFDGFGGBGFBGDAAAHAAHDFHGCHFCAFEAEEDECDHBFAGHAGFEEFAFFAFAHCAHG,False +420,5.0,4.0,3.0,9.0,10.0,5.0,4.0,4.0,DEBDADFEFCEHEABEAEEFEDHGDHEDCFGCFDDGBDGBEAAH,False +421,21.0,22.0,19.0,21.0,16.0,23.0,24.0,24.0,BGGDDGBHHHHGHHDAGFAGFBBFGGFGEHBAHECFACAGHEFCEADEAEBAHBGBBACDACDHCDHCHBCDBDDGCFHHFHHAHEEHCGCBGAADFBGEGFCCFCGFDHHDHCBFDAADABBCBFCFGDECBEFDEGDEDFABFADFGBFGFAGFADHHEGABCFBGEE,False +422,5.0,3.0,3.0,1.0,0.0,2.0,1.0,4.0,ABCABCBGAHHHFHAFCAD,True +423,8.0,5.0,10.0,3.0,2.0,6.0,4.0,7.0,CAHCAGAAEDGFCGDCFHCAHCAHBBDFAFFGBFBBCCCHCEHAH,True +424,4.0,2.0,3.0,3.0,3.0,5.0,4.0,1.0,GDFGCGACDACDEBFEGHEFFAAFB,False +425,20.0,29.0,28.0,22.0,37.0,21.0,18.0,23.0,DCDEFDAGCHCHFDAFEFFEHDEDBEABEHBEBFCBEDBCDCCEGCEBCEAHDHHDAHGAHBBBFABFABACBADHEEHEEAEAAEACDCHBCEDEEBEGGEBEFDGCBBBAFDAFCAFCHEDBEDGECHBHGFGECEDGDFECFDCFGHECEEHFEBCABCADEAFEGBBHBFGBEHCCHBCGBEFCHHCHGGGGDF,False +426,3.0,6.0,6.0,5.0,11.0,8.0,8.0,8.0,ECEBAECEDDEBDGBGHDGEBGECGFHGFHACHFGHFCFBEFHHBHEADEFGCFE,False +427,9.0,21.0,17.0,17.0,18.0,17.0,9.0,12.0,BHBBHBBAFBCCHEBDECFECDEFFGHCEFCAFAEHDGHDBHABEEBEEDAECBDCECABDAFDHDGEDBBDBFAFFCCBHCDHDBFDGFGBFCHACDBCGGDGGCBFFBFEEFHECEED,False +428,13.0,9.0,6.0,7.0,7.0,9.0,7.0,6.0,HDAAECHEGFFGFGCFHCBGAADAADAAFABFBEEAFFBBCBBEABECGHDGEDGDABDAFHCH,False +429,8.0,15.0,19.0,18.0,20.0,20.0,16.0,22.0,FGDFDDFHDGAFGFHEBABCDBHFGHFCHACACCECEACEBCFGDBHFEHFBHGHHEHEBGEAFFHCFDEFDADDBDGHFBDFBCFBGAHFBECHECBECHECECCEDCHGEEGEGFDFEDBEHBHCDGDHCHHGGDG,False +430,13.0,25.0,20.0,21.0,26.0,17.0,24.0,16.0,EFFGFCDFCEHCGHDGEECAEBBEGBECFEGHAADDAFCAFCBCEECFFCFCAGDACHBHHBGDCGDGGDEEDBHHGCHEDBEGEECEEBEBBDBAEEFDGBGGBDAEDHEFCGBCGFCGAHGFHDBGGBFBFFHEHBCDBADCEDEBBGAAGHBGHBDBDD,False +431,13.0,21.0,18.0,12.0,10.0,10.0,17.0,15.0,GAFBBBBFHGFAFBGCGGBBCABCAGDHGDHBCHBHBAHGGHEGHDCDBCFBCGECAEDDHBAEBDHBDHBDACECGEGGDHADBEFCDBGACEAHBCFBEHAEHAFGCCGCCFFC,False +432,14.0,11.0,9.0,15.0,14.0,12.0,12.0,18.0,DFAFFAHDHEDFEHHEDHCFHCECBABBDGEFGEDCDCGDHHFCHFCGGCEGABGDBEABAAHAEBDEBHEGHFGHDHEBADGADBAEHCEHDDHBFAGAAFFGH,False +433,16.0,16.0,12.0,20.0,13.0,18.0,9.0,14.0,FDCFDADDBDDAHDCBDCDDCDAEHAFAABADBECFAFBCFADAGCAGCDBAFCFFEHFHBFBEHGCGGDFGDABDEECGGDFEFBHCBHBEHBEABEHBAHGAEFBEHHHFEHFDFD,False +434,15.0,21.0,15.0,6.0,12.0,5.0,12.0,17.0,CBBDBGABGCDGCEADBCCADEFCCAHCHCDHCAHCHHABHBBHABEFCGCBGAFAAHEAFGAEGAHGEEGHEGBFBEECHEBBAHHCHDBHBBHBBABBGEG,False +435,0.0,0.0,3.0,2.0,2.0,2.0,2.0,3.0,CHDCEDEHCGHFGF,True +436,22.0,21.0,21.0,13.0,7.0,14.0,20.0,13.0,BHBGDAADEDFGCFGDHGAGGAFDCCACCHEADBCFBCGBFABEHDCHCEGBGDAGAADCAHGHHGHFFDEHAGAGGABCAFAFFACHACGBDGBDCBDHAGCFEBFACHBCABCGFCAFGBEBBCBBCBB,False +437,18.0,12.0,15.0,15.0,9.0,15.0,19.0,9.0,BEAEFBCFAADCBFGDGGHFCADAADGADHCBHDGDBGDBGDCGAHEFHGFAEBAHBADGCDGCGFCHFDEFEHFCAAAFBAHAEGDEGFEDCCBCGBFGBFGACGCCADFG,False +438,9.0,15.0,11.0,10.0,6.0,5.0,12.0,8.0,CBBCECABBAHBHBCHGGEGGDAEBEDCDFADBGDBGDBGBBCDGABHCFGBFGHFGHFEAAEAABHDDCGCCDCH,False +439,21.0,34.0,13.0,20.0,9.0,14.0,18.0,22.0,DBGDFCCFEAGHBHHCHHCBHBGHBDABCCBAFBAGBDCBDBBGBAFFDHEHGCBACBAEFGHBGAFGCFBAGHAHHAGHGCDEAHABHBDFEDBDDADDHFBHFBEABEABADBHFHDBABBHBAEBGCDCFHGGGBBGFDGDABDABDE,False +440,5.0,7.0,4.0,9.0,2.0,7.0,1.0,7.0,DEBHHHHHHDFAAFGADHABBFFDFFDBEDCCCCFBDDBDAB,True +441,9.0,3.0,11.0,9.0,5.0,3.0,13.0,6.0,GCHGCHBCDDAEAHEAGAGGCGEAEHACDFBDBDGCDGDGGHGCFGCAHCACDGCAEFD,True +442,26.0,15.0,9.0,16.0,20.0,21.0,20.0,20.0,EEHEFAFDDHDDBDEEFFEDFCHFAAGHAEHADBAGHAGBADAAEABCGBCBBFGCFGEFGEFGHDEAEEAFHFGHDGFAGACGCHBCHEAHGABGBGADGFFGEEBCFDHAEBAGBADAABBHFHHCEEFFEDFHAHHAHADDGFG,False +443,5.0,11.0,13.0,10.0,14.0,14.0,10.0,14.0,FCEHCEHCEDGDBBDGEDHEABEFGAFGAFCCFHFFHFBAEEGDFFAHECHGCHDCHBGFEHFHFFBBCBBEHCHHBECDEDBEDCGGGDC,False +444,9.0,3.0,12.0,6.0,9.0,11.0,10.0,6.0,GACGCGACGBHABFCEFCEFCAFGFEGDCFBCHHHHGAAAEADCDGAGEEEEECFFCDFGDFCDFH,False +445,9.0,10.0,13.0,13.0,17.0,11.0,15.0,15.0,DGCDBCDFEFHEHHEDDEGCCFCFFCGDEECEFHHFAHFAEDGGBBGHHGCHGBACAAHEEHEEDGGDGGDGEEFEBGHBCDCAACAHDHBFEFCEDBHBBAG,False +446,4.0,1.0,6.0,9.0,11.0,4.0,5.0,7.0,GACEFGGACGDFDECDEHDEHDEHEEDAHDCDFCDBEHAGFCHEEHE,True +447,26.0,19.0,18.0,11.0,16.0,16.0,12.0,21.0,EEHFFHCBABHABHAEHAEHEFFGFAGHBHAEEAEEAGAAGCCGABDACECFHGHHEDHCBHCBHCBAGDABDCHAHEFHFHHDDFBFFAFCACABEDFEDAGDBFCBDAGFACEACAGHABBFBBEBACCCGHCDBAG,False +448,6.0,5.0,7.0,6.0,1.0,1.0,3.0,5.0,HADHAHCACGDGBDGBAECACBABDCHDBHDCCF,True +449,11.0,2.0,6.0,6.0,9.0,16.0,8.0,5.0,AGAAHAAGFDFEEFBEDGEGEEFEAFCCDEDFFGFFGFFCFAEFAFHDFCBHADHFGHACCAG,True +450,11.0,4.0,8.0,12.0,7.0,9.0,7.0,8.0,FDEFCADCGCEBAHBGECHEFHCDACDABHGBFFDFAEFAEADGADFEDHCAHGDHDFCDAGDAGH,False +451,31.0,20.0,20.0,33.0,22.0,23.0,32.0,17.0,BCCAGAAGFAGCEGDBGDACDHDHGFBGBBDBFGBHBAHECEECDEDHHDFADFEDCEGHAFBCCBFADGCBADDFEFGEHGEFGDHECAEAGEDDEBDEADAADBCBGEDHDDFCEAAHBGBGFAGFDGFDEFEGHBAHFAGFDGDDFDFABCABCAFCAFCAGCAHEGHGDAADAGEFGHDGCDGBGHCFAGDEGA,False +452,6.0,6.0,6.0,10.0,8.0,9.0,9.0,6.0,AFEABEBDGBAFEDHGFHGEDGEHCHAGHECHCCFDADDFEDFEBAGCFGFFGCBGDBDD,False +453,13.0,18.0,14.0,23.0,17.0,19.0,19.0,12.0,DCGDCDDCADEBFFBFFCAACDACDCCABCDDFDFAAEGFHFADCBGCDGEDAFGGEHHEFBFFBFFBGFCDFCGAGDDHDDHFEHGEBGHDGHAEHBGBDEFCBDDEABHAGEBEEBHEDEGBHGBFGBGEEGB,False +454,18.0,22.0,18.0,14.0,25.0,31.0,12.0,21.0,FHADBACFDHAHHDGHBFFFCFGCBGDHFFFGFFGFGGFAHCHEEHFHDFHFFHFAHAHEACEGEEBDEDFAFFBFFBFBEFDCBBEAEHDFDEEEBBGCBFCFCBGBBFEHGCDEHDECDECBADEAEEACEACECCABBECBECBFAFAGHEHHABHAB,False +455,8.0,7.0,7.0,9.0,13.0,7.0,12.0,7.0,AGEBFEADAAGFABFHDEAFFCGFDEHGABGCBHCBGBDHBDFDEGCEGCEDCEHEDHGDAGEHEEGCEG,False +456,26.0,25.0,17.0,12.0,23.0,17.0,8.0,10.0,BCAFCEBDBGCAAFAAFGCBEAEDDBADBADCHEFFEADEAEEFEEGAEGEHBEGAFHAFHDFBBAEACCAECBBBBBFABEABDBBDABDCEDFECACHFHAFHGHDCCAGFEEACEABFABFBEFAEBBGHBCHCC,False +457,17.0,13.0,15.0,8.0,13.0,12.0,8.0,11.0,HFCEBGABGABDAECBBCBBEBEEBFEAADACFHFEHFBACAACDAFHHFAHGAHAAEAHGHCGFCDFDAEEBDECCHCCFFGBEGCDFCBCAEDHG,False +458,4.0,0.0,3.0,1.0,6.0,6.0,4.0,0.0,FEEFEFFGCFAEAGCAGEADEFGC,True +459,21.0,25.0,18.0,16.0,17.0,17.0,23.0,17.0,HDAGCGGBBGBCEDCBBBEGFEGFEGFAFFCGFCBECBFFBEBBGBFABCAFAHEHEDHGDCCEAAGAAGBCGHCBHCAEDHHDFFDABEFECCABHABEDBEGBEGDGDFGAFEAGCDGCBHHDHCAHGABFDEADBADBHGAGAHFHGCHDB,False +460,10.0,14.0,5.0,9.0,15.0,9.0,9.0,8.0,EDEEGEAGEGBEDBDFGDEABFAFDAGEBBABDAGDBGFFHAEHDEABGBHABEACEFBDFBCHGCEBCEBEHHHFHCF,False +461,5.0,3.0,5.0,6.0,2.0,12.0,7.0,4.0,CEAFFGFFGFFDFHDFBDADACCGGCABAHGFBFFDGHDGHEFC,True +462,6.0,6.0,14.0,9.0,5.0,9.0,18.0,19.0,FGCDHCHHGHDGADGECGHCGCGHCEDGEFFHHFHFGBAHEFGBCGHFDHFHHCGHCGHEGBCCBDAHDHGBHACGCGFCDABDAG,True +463,3.0,5.0,4.0,8.0,5.0,3.0,5.0,5.0,DGAFBBFAHGEGGEGBECECCAHHDDDEDDHFDHBDCB,False +464,8.0,5.0,4.0,6.0,7.0,4.0,8.0,3.0,DACBACHAGHBEHDEFEADGGCFEDGEBGEAGBAGFDGFDAAEBC,False +465,13.0,13.0,10.0,12.0,11.0,18.0,10.0,10.0,DFBGFDFFDGBBBEDGEDBECEEDFHAAACAAHHHHHBGGAAAFHACDACEFFHFFHAGCBEFBEBAFGAHGDEGFFBFDBFDECCECCGBCDBFDF,False +466,1.0,7.0,5.0,6.0,4.0,4.0,5.0,8.0,DHBECBCDBGDBHDBHFHECAECFFGHDGBBGHCGHDHFE,False +467,8.0,10.0,7.0,7.0,13.0,10.0,14.0,7.0,GGBEGHAGEGBEDBCAFFBHEEAEFBEGCFGCFHBFEGFEBFHFCHFDGDDGHDGDCHAEGCEGAEDCEBAABABG,False +468,7.0,9.0,14.0,4.0,4.0,10.0,8.0,4.0,FECAECBDFBGFCCFECFDCBGCBGBFDAHGAFGBBEBCHBCAAHGAGCCCFHCFGCDAF,True +469,11.0,8.0,10.0,17.0,9.0,15.0,9.0,16.0,FHDFDDEACFHCFCAHDEHAGHACHDGBAGBEGBAGEHHDGHFEHADHAEFAGGCFECFBCDGDHHDADBCDBEDFFDFFCCBEDHFHAFHDFDB,False +470,1.0,3.0,1.0,1.0,2.0,1.0,2.0,3.0,CHADBEEBGHBGHF,True +471,17.0,15.0,26.0,18.0,19.0,21.0,23.0,27.0,GFFCCCHCDHAGAEGFGCBGCBFCFFHDFBDCHDGHFEAFEAEEAEGDHGHCGABGDCGDGGFFFACHBEAEEDEAHFAHDHHGCHFHHGGHBBECGECEEDAHCACCBBCFBCHGCHACFDCEDAHCAHFFFDABEEBCBAHFCHBHBGDGECGEHDHGDHGDFD,False +472,2.0,5.0,3.0,5.0,4.0,6.0,6.0,2.0,EGHFGBFEBFEDFHGCCFEABDADDBDGBGCFG,False +473,20.0,30.0,26.0,33.0,27.0,26.0,18.0,15.0,CGAHFAGFAFDBCDEGDEHBEGBEBFDGFECFHBFHBEEFEECCEFEFFHCDGAHABDFBAGBADBADBDGFGCDCABGAEGDDDDACFACEAFEBEGDCGCEFDEBEEDFEFFDABDHBDEBCHBHHFDDBCDFGDAGHBDABFBDDDFFBBACBCCBCABCACCHGCBFBDDEEBCGDCGDCEDCHFEHEAHE,False +474,19.0,17.0,14.0,18.0,11.0,17.0,20.0,12.0,GAGCCFFCGFEDEBFFAFCGDHGEHGEHGHGFDFAAFDADDADCACCBFBDGBGGBFEBCABDAGHGBDBBHFGEAGCDGFDCFCHFAGCBBABBABAEBCFCDEDHGHAEHAEDAEDGFDGDAHHAB,False +475,29.0,21.0,29.0,16.0,8.0,11.0,32.0,19.0,GGHBGAGFAHFBGAHFBHGBHGCEACHGBAAAFHHFHHCBGCGAHBDCCDGAAGHHDBDCBDFBDBEACAFCEDCBGABGAFEACGACGCCGBCGHAGADEAHGDCGCBBAFBADCGBEGBEGBAGCGGAGABCCHCDACGHDGEAHAADFCCHACDGCDGCDFC,True +476,1.0,0.0,5.0,0.0,0.0,3.0,1.0,0.0,CCCGCCFFAF,True +477,12.0,12.0,12.0,10.0,3.0,21.0,15.0,7.0,FDFAGACBDCBGCEFEFDGAGGBBDBBAFCADCADCFCGFCFFHFFHBFCCDAGAAGBFDCFCAFHDBBGHDGHFGBFBEFGFFAHGAGGFH,False +478,17.0,16.0,18.0,22.0,16.0,25.0,17.0,21.0,ACEFGEHAECACCHBGAFFBCFECADCEFAEDEFAECBCGBCHFGHGEBAEAADHGDGAFGDDCEHCHAEHDEFGHHHBHABFABFHCFHCFHCFBDFBHBEFFEDFCDBGDAFDGBHFBHAEDCFHBDDGADGDFCDFGDGBDGDFHDFHG,False +479,10.0,7.0,13.0,9.0,7.0,6.0,9.0,3.0,HGCDGCAGAEGAGCCBCCFCEFEAFEACGGCHDABDECHFABFEBEBADBDDBAACGCFDCDDG,False +480,1.0,0.0,4.0,0.0,2.0,0.0,5.0,0.0,GCEGEGGCCGCA,True +481,21.0,16.0,14.0,17.0,11.0,10.0,25.0,16.0,FDGEEGBBDHAHGDHBHGBGCBCCFACEAEGAHHDHBGFDGADAAEAAFHCFHDFABGCBGAGGADCHDCECEDBDACDAHDAGDBHHBAGFAEFGBFGBGHAGAAEDCBCEBHEGHDDBGGGGCAGCFG,False +482,12.0,17.0,21.0,17.0,21.0,22.0,20.0,24.0,HCBHEEHCEHCBHADGBCGBEEHHFGHFDHFCHCGHGGHBGCBCHGDDACDFFFFFGBACFECGCFHFAEDHDDBDDHDEGDECAGCAGHAEHAHFEFDEACCDGGGFGCEBCEDHFCHBHBEHDDABHFFFAFFBFEBEBBGAEGCEGCEBFE,False +483,19.0,21.0,17.0,13.0,22.0,21.0,20.0,24.0,GDGGEGFHAHAEHADHCEHDAACCBEFBEAAFFAFGHHBHDBFDFFACBGDDGDHHBACBFDHFDBFEFFGABDACDFFHGFCCAEBBHGBHBBEBGCDGCHGCHEFHEAHEHHGACCACGAHHEBGECGACFEEEBEFBCFEEGEHGEAGBFHBEB,False +484,14.0,17.0,19.0,19.0,23.0,9.0,30.0,14.0,DBADEECEEGGGCGGCHGAEDCGDCDDHDGGDEBHBBCAHHADGGGEGCECCACHAGHAEDABCHGGHAGDADBEFHHFBCEAGAGGDGGHGGACFFBFGCFGBBDBECBEDBGFEHDEBDEFHEBCEBAEGEECEGBGFCDECD,False +485,23.0,20.0,17.0,18.0,15.0,7.0,16.0,20.0,ADAADBBFAFFAFAAGCDHCHABGABCAGHBGHCAHEECBECGDHHAHDEFBGDGDBGDBAAEABGHBDCECCBGGHCEHBFABFABCACAECBCDDCBEEADEADHHDHDDGEHGEHGEDCBDCHAAGGBHHBHE,False +486,19.0,15.0,16.0,14.0,11.0,13.0,25.0,19.0,GDCGHFGHCBDBAAAAAACAGHBGADDCCHEGBCBDAFDBGDBDEAAGAHBAHADCDDEHHFHEAGCGGCGGBGHCGCBGCBDCGGGFEGBEDFHCFEBFEAFGAEGCFGCFGDEGAHFEHABFFBHHHHHH,False +487,17.0,28.0,19.0,19.0,12.0,13.0,19.0,22.0,DBDEFAHAGFBGHEGHDDBBEBHEBHDCHFEHGEHGBBACBAGAAGEBBHBDFBDFBDCCHCCAEBGDGDCEBCACFAEGAHDFCCBHCEHDEGCBGABGBDFHCFDDFDBFGAGGFHBCHCABDABHAHCAGCHGBBBCBHFDHADHG,False +488,11.0,5.0,10.0,9.0,17.0,10.0,8.0,12.0,HFEBAGAEFADDEHDEHAEHDEHAEDEEDGBCHCFECFBCHGCHGEDBEABGAHFAHFHEEGFHACECCADEDCEFCAFGFG,False +489,15.0,27.0,19.0,19.0,24.0,16.0,18.0,23.0,GDHCDCEEBEBBHABHFBGFEGDDHDFACCAGGADEBDEHABHAFHGBHAFCAFCBFCFHCHDEHDBBFABDEGCECHDDDDGEAGHAFHFEBBEAHCAHFGHABEFEHDHHDCGBEHBEBCCBGDGEBGEBEECEGBECBEBDEBFGHABHFFDGCCGBC,False +490,3.0,2.0,6.0,3.0,7.0,0.0,1.0,4.0,CBCEHEADEACEADEDBCGHHECHEC,True +491,14.0,16.0,16.0,14.0,17.0,13.0,22.0,10.0,FADFCGFCEFCEBCGBCBBCBBAFBGGBGBEEEFDBBDHEEHGHAGHAGDDGBEAAGDFCHADHGDHGHFBDEDDEFECCEGGGGGADGCBEEHDCGCCGABHDBFAFEEECCAGAFGAFCA,False +492,26.0,18.0,20.0,24.0,26.0,19.0,29.0,28.0,DCADFADCEHGDGGFGEAHEHHAHFCCCGHBAHEAECBBGGBHGBHDBAAFECHEBHGFHCAHDAHDAHACHCGHCAAEGGGDBGDGGDEGHHDCGEEGEDAEDCGFCDFEFFADHGBCABHDBEGBGBHCHFGDFEFFEBBEDBEAAEFEBFGBAHAAHECDGDDFDACCAFAEHGEDGEDCEHFGHFA,False +493,1.0,0.0,2.0,1.0,4.0,2.0,0.0,0.0,ECEECEAFFD,True +494,11.0,16.0,14.0,24.0,25.0,15.0,20.0,16.0,HFCEDHDDCEGCFADBEDCEDAFBACGFFGHDDDGBDFEAFCAFHDFHEFBAFBDEBEHCEDBHDGHDFAEFCECCBGGBFDBCDHAHBGEBEEHGGHABDGDGGDHADGAEEBFECEECGEGGEBEEBHGCHGDHGDEDE,False +495,15.0,21.0,13.0,15.0,18.0,25.0,20.0,12.0,GFGGDGBFFFDCCDGCDECAEFFFHCECCEDEEAEEBEFHDHBGGBGGEGHAGEAGBGEAFAHFACFCHGBBGBBCCDEGDFFFFABBBEBDAGDAHFACFAFDABDBBEFDEFAFBBFBBFEHHGHDDHBFGAFHEGC,False +496,14.0,17.0,8.0,12.0,24.0,10.0,23.0,11.0,GBFGBDGAFGBGEBFEHDGAFEBCGGGBABDAEDGEFBAFHEFHBFHEEBGEBAEGGEFGEABAHBGHBCFGEGCAGCEHEGHDDEBAGCAGBECDECDEGDEGDBDHEEHAEHDCAAE,False +497,8.0,11.0,13.0,8.0,7.0,15.0,9.0,16.0,EHBHFAFCAGEGGCCGCAGBAGHDFFCFHBHHDDHFCAECHDBHCBHAFFDFEHCGDFGAFCAFCGFEBBCBBCFHDHEDHFBHEBH,False +498,3.0,6.0,8.0,3.0,3.0,7.0,4.0,5.0,CHECBEABACCGCBGFHFFBGDBFDAFDEFCGBCHFHHC,False +499,7.0,4.0,9.0,5.0,5.0,8.0,3.0,3.0,ECEEFHFFACFAHAABEABDCCGFDGFCCFCCFGDABDCDEBAH,False +500,7.0,8.0,5.0,8.0,4.0,3.0,2.0,4.0,CAEFHGBDDBDDBDDBCGBCFDFDHCAEAEHBEABAAHACB,True +501,22.0,26.0,22.0,26.0,16.0,25.0,21.0,27.0,EBHCGHBFHBFBAEEAHFAHEADFGDFBFHCHCCHGAAAAAHAGBBBDBCHCEHBHHGDDFBEFDECDBFFHFFDDDDDFDAACHBDABDHGCEGCGHFGAFDCFGCFGBBGFACDAGHFGHEEAEEAHHBDDAABBCBCDDCDCGHFGHEBHABGFCGCEGCBCHBCHDGFFBFGEFDEHDBAD,False +502,10.0,11.0,12.0,13.0,8.0,15.0,13.0,13.0,GFHHEHDCHDEFDADGCDGBDFADFHFACFACACBFCGFCAFEECBECBACAFDEHBGGAAFDGHCBDCBHGBHDFHDHGEFGFHGFHDBEBGGB,False +503,5.0,6.0,10.0,4.0,4.0,8.0,9.0,0.0,FEDCEDCGBGGBCFCFEDBEGAACABCGCCGFFGFFDAGGBCABCF,True +504,7.0,14.0,10.0,11.0,12.0,9.0,6.0,15.0,BDBBGBFCEDCHDCHEFFECHGDEEHEDHDBCDHGABFABFBBDBBCEECHEGFAHCGFBHFAHFAHDCEAHBDCBDHGEHAEH,False +505,21.0,9.0,16.0,11.0,15.0,16.0,15.0,15.0,DFAGEAGEAFCCECCECFEGFHGDHAFBCHEDHEHBEAGFCHDHGAHFFCAAGAAGAAGAFEDGCDFHGEHFEDFBDCAHGAHBABEABGABEDFFHGFCEACHADEBCCBGFDCCHA,False +506,17.0,15.0,12.0,11.0,15.0,5.0,18.0,14.0,BHGDHFBGBBABHAEGAEDAEAEDBEDGCGHADCFEHAGHAHHAFADCBBGEGGBDBBDEHHHGGBGADGACHCEGCEHAABFAEHAECAECEECFBCGDCGBCGDG,False +507,23.0,16.0,18.0,17.0,15.0,30.0,19.0,16.0,CAHCHFAHFDGFDGEHAABDAFCAFBAGBHGHCDBAAFGFFGADAHDGDGGFEDFEDCCCCDHGFFGFFCHFAFEAFEFHGBEFEEFEECDBGGHHGHCEHEGCADCEBAFBFDBGBCHBFFBFFBCDBDGAGFABEAEAAFFCBFCADCADHA,False +508,2.0,2.0,6.0,5.0,8.0,2.0,3.0,4.0,AECAHCEDEEGEDCFFCBECDDGGDHECHEBH,True +509,10.0,15.0,13.0,10.0,20.0,25.0,8.0,14.0,BFFFFGHDGHBEECGECGEHFEFAGBHGBEDEGAEAHHFFHCFCFFHEFADFBCEHCEGFAHFHEFECBDCBDABDCBFCBDHBEFCEFCHFEBEBFEAFACFHFBAFEADDDBE,False +510,9.0,6.0,15.0,8.0,8.0,15.0,8.0,4.0,CGFCHFDFCDFADGADECCCFCAFBFFCCFEGFDGFCGCCEBBEAEEAEFGHDGDFCHFEFAGDABBCBCAHA,False +511,1.0,1.0,2.0,5.0,3.0,1.0,4.0,3.0,GDDGCBGCHDEEDHEDFAGH,True +512,16.0,13.0,8.0,20.0,20.0,20.0,19.0,18.0,GEEGAEDHBDFBGBGGHGEEDHEHEGFEGBEGFHGEDBBAHGFDAFDAEDGFFHFFHEEHDEHDGDGADCADFADABFHDFCEFCHFDGAGABHAFHGHCBFCHEHBEAAEAAEBCEDFGABDCHFCBFDFDDG,False +513,2.0,0.0,0.0,0.0,3.0,1.0,1.0,4.0,HHEHHEAGAFE,True +514,16.0,32.0,27.0,32.0,20.0,18.0,31.0,18.0,FFCEHGEAGHCGDDGHDFEDFDDBDCHDAABHAGDEGDEGEFCBDAEABBAGBCGHEEDCCBCCAECAGBDFBCHGHHDHADGGGCCFFAGBGFDGACBHCBDAEDBEDAGDHCDGCEGFGCEGDADDCHBGHBAHBEGBEFBFGBHDHGEBBDBBFCCCDEBDFBDBBGFBGFBGFBGFHDBCCCEBCGDCED,False +515,26.0,15.0,26.0,29.0,17.0,18.0,23.0,22.0,GFHDAEAAEGAEGCEDCDDCAHCABBAEBECGEBHHGAADFECFBCFECEDGDDCDCGDBDFGCGHDAHFADDAHCADDGDFGDEAAGAFDHGCHDCBDCGCBGCBFABGAHHBHDFHDFDDGDCFFAHBEHECCFCBACHACEGCEHHBHFGHCGDAGDAGECBFHAAGFFDEAH,False +516,12.0,12.0,20.0,17.0,22.0,17.0,13.0,11.0,EEBEADDAFDADAHHEEBGEBFFBEBCCDFCEFCEFCEFCABEFHEFCEFGFCGCGHCHDCGFBECACAGDAHDGGDHFDHADEADBFHBFABDHECFDCHCEGGDCDDCGBEAFEBECGECGE,False +517,17.0,18.0,11.0,13.0,13.0,9.0,14.0,20.0,BEFHACHEDBAAHAHHAGBAGCGGHAADEHDEHBBHGEHAEHGEDGEBCEBCHAAHBCHADHCDBGFBGHAABBFFFCCFACBGDBGDBFDCFDCBEHFHHEGBADEDHEGGABD,False +518,20.0,13.0,17.0,15.0,17.0,19.0,27.0,13.0,CFECBCGACDECDHCHAGGAGGAGGAGEAGHBGFFGHHDEHDHDDGAAGDDGDHBEFDAGBABEECEAABAAFAGFGDFCDCEFGECBCGGEGHEGHBGEFHFFDCCAFGAFEAEEFCFACFGBDCBCAHGBEGFDFHBFB,False +519,4.0,10.0,8.0,8.0,7.0,6.0,3.0,5.0,EABADFAHCBFGDFCDCCBACBEFDGBHGBHFEHFECEDHBCCBEDBEDBD,False +520,21.0,21.0,12.0,9.0,4.0,4.0,12.0,8.0,FAACBBBAABGAFADBABBDBBABHACGACBABBHHCECAACAHGDHGABCBDABAGBDGDAEDGCDGCABFEHEAHFBHGADGCCGBCGB,True +521,7.0,6.0,5.0,6.0,9.0,6.0,4.0,9.0,HDFFDAFDAFBFEAGABCHCHHBFHBGEBHEHHEHEDAECEEGACDECDBGA,False +522,7.0,13.0,6.0,12.0,9.0,15.0,17.0,9.0,FEHCDBCDGGDGGDHFBHAEFDEFDFGEAABAFBHCBEFBACDGBDGHHBFGDFEDEEGGBGGBHGFGFEGHCFBFFBGFGHBADCAD,False +523,13.0,18.0,26.0,23.0,24.0,18.0,20.0,22.0,HDCHAFHBBHAEFFCCGDFGAFCFDBHGFGEFBEGCEHDHHEGCEGEDBDDBGAFHCFHCAECHBFHADHFDHECFBCBBEEDGBCGEEEDGHFGECCECDACDGFBCACCDDGDDEBDGBDGAACABCABCFBEFEDHEDHDGHEFHECDECGAHGEHGCCBH,False +524,23.0,26.0,27.0,25.0,18.0,14.0,25.0,20.0,AHEABADDECBHGBEGDCHHCEDCECAFCACEFEEGGDGGDGEDGCFBAEAHFGDFCACHEBDDBADBADBDDACFAFAGCBBHBGGFDBFDGAAGAHGDHFBEEDCCDCBACHHCHECFDDHABAACAAGHHGBGGBGFBGFHDCBDCBHBHHCDFCDEBGHBGACGCCGECBBBEE,False +525,9.0,5.0,7.0,9.0,10.0,14.0,16.0,12.0,GDEGFEHFGFFECEBCBHHAHAGHAGDFCDHBDAFFFGFGGHBDHFDCFDCDGFEGEGCEGAGAAHAGEGHEHFEHFGCDBA,False +526,21.0,20.0,28.0,24.0,24.0,22.0,22.0,28.0,FBFFHFFDFEBCDDDFBEABCGECGECFHFFCFDAACAAHAHCDHGHHFHCBHBDHGDGDHAHCDHGABAABGCGAAFBGFCDFCDFCABEHDEAGHABHEBAEFHCAEABHGHHACFEGEEFEEGDFGDCCDCEDHHGBHGEHGECGDHDDAFCEBDHBGGECBDCBGCAGCEBCECEBCEHCDHEDF,False +527,20.0,11.0,8.0,13.0,17.0,8.0,13.0,14.0,DDHGDHCDHDDHEGFEDECAEHFFHAABEGBEHBCAGADGACFACECDEAHGABBCEAAEAGFABAABAHGFHEEGGDCEBAFGFHGAEDHEDHEABEABDHBG,False +528,9.0,13.0,8.0,10.0,8.0,6.0,9.0,7.0,ECDBCHEGHFFBEDBGDBHDBHDFHFEBBCDFDACACCBEHBAGBAGFDGADGACHABDAEABGGEGCEB,False +529,2.0,5.0,6.0,3.0,4.0,6.0,5.0,4.0,FCBFCBFCDCHDEHBFGFFGAEAHEGBCGCHDEBG,False +530,5.0,3.0,3.0,2.0,4.0,2.0,5.0,5.0,AFBAEGACGFGHCEHEBGEHGHDAHDACB,False +531,14.0,18.0,15.0,23.0,16.0,17.0,15.0,32.0,HBAHEDHGDHCDHDEHDEHDEHDHFAGADFEEHBBDFHDAEDEEHHHBHDFHDFHCFCFECABGGBEGCEBFBBDBDCCHCAACFACFHEEHCHHDHGFHGFHDCDDBEBGHAFFCGBAEBAHBGHAGFBGAHCFFBDGDCBDHGHGDHA,False +532,8.0,6.0,17.0,12.0,9.0,14.0,14.0,11.0,DEGAFHFDCCDGCHHBHCFDCFDCEGGFHHCAGEGBFGBDGDAGHCGCCGDCHDGEDBEFFCFDCGHCEHEGHACCAFAFFDFFAEBAEBC,False +533,15.0,11.0,12.0,12.0,16.0,22.0,21.0,18.0,GAAFFACGGFHDCBDFBAFBAGEAFEBFGGFDDEGFEACHFFBDFGEGDFFAHFHHAHHEHHFHFABECBDHHDCHDGGDGGEFGEHACGACGECEECEEBDBHDHHFHEFGGCABCAFEFCGGGBA,False +534,6.0,6.0,12.0,13.0,5.0,12.0,12.0,8.0,HDGAGHFGHFCHABHFEHFACCCBCEGCGDCDEADCFDHGDGFDGFBGCDCHFFEGFAFDDFDDGADCBECBGB,False +535,22.0,16.0,25.0,15.0,17.0,33.0,16.0,16.0,FBFFEECEEDFEFEEBGGDGFEAAEFCGFDGHDGDEGAAAHACFECDACDCHFCHFAFFAFEGFBDFECHHBACBCCACDAGFGDFEDFCCFHCBCCFACAAGADGHEFFCBFHDFCDHBHGECAFFGBGBFGAAAFBHFHHFEBFCDFCBACBHCBHAB,False +536,20.0,17.0,26.0,15.0,22.0,17.0,17.0,16.0,BHHBAFEEFAEFAEDBBDFEEBCEHHAAHAGBDGBHBECECCBFFAFEACEGCEFEECDDDGBDABEEBEHAAHCFCCEACDAHAGHBGFACFHCGHCFCCBCFGHDHCDHCDGCEAHGAFBADGGFCBFCGDCGCCFADECDGGEGAEB,False +537,13.0,10.0,5.0,5.0,10.0,8.0,9.0,7.0,EADEDEAAGAEEBGGHHBFFBFEBFBBDEAHEABCAHCAEFAGDAEDBFFGFAGAHGCHGHABCGBC,False +538,10.0,10.0,16.0,12.0,12.0,14.0,12.0,13.0,DFCGBCDFCDGBDCFCFFCFDAHDCBECEEBEDBEHECFECGAHGDHEAHAHHGFHGDHFFCGGCEGFGGCGCAAHHAEHCBDFBDEBAFADFAEBCBH,False +539,2.0,2.0,4.0,2.0,0.0,2.0,1.0,0.0,ACCFCAFCBDDBG,True +540,3.0,8.0,6.0,4.0,2.0,10.0,5.0,6.0,FGBFBFDBFDBFHFFGCEAFHCCBFCBECFABGDGHDGHBHHAC,True +541,4.0,4.0,3.0,5.0,9.0,9.0,6.0,7.0,HHFDFBDFAFFAEFEHGEHGEBGEAHFDEBCGHGGFEAFDDHCEBCE,False +542,1.0,6.0,4.0,1.0,3.0,1.0,2.0,0.0,EGEEDACCFCCBBBBBGB,True +543,11.0,8.0,11.0,8.0,8.0,12.0,13.0,10.0,CGFCHFHAFHGCGCCHCGHGACBDDBCDFADFADFBBEDAEGACFAHHGBHGDAEFGEAGEABHBGFBAEEGEHDFCGFCF,False +544,1.0,2.0,1.0,1.0,0.0,0.0,2.0,3.0,GDAHBCHBGH,True +545,20.0,18.0,24.0,26.0,24.0,22.0,18.0,33.0,CBHDDADAHFAEFCEHCEHEBHCBGCHAAHAFHFFEAFDAFBEEGHAGDDDACDHCEECEGDEGDEGBADBEDBAACEECHFBFCHFHHEEDBHHAEFCCHHFDBFDHCHHAHHAHGCHCCGFCGBGGFGDFBHFDGGDCEDADDADCFBCHBCBFHEHBEGAFHCCBEFFHDHGAEGDBGDEHD,False +546,29.0,23.0,21.0,19.0,21.0,27.0,25.0,20.0,BHEADFCDFGBFAFFACEAGFABFACFACFHEBHBFHDFGEGCEHCGDCDFCACAGDEBDEFAEFGEGGHCEHEAFEGECAAGAAEFFFFDFGGGCDGBGEBGHBGEBADFGCAGEADDBDDBACCCBDBBHAAABAHBACGECDDHGHHGBFEACHBFHEDCFDAHEAGCBGBAHFAHFBHFBH,False +547,8.0,14.0,13.0,15.0,21.0,12.0,10.0,20.0,CHCHGGHDDADDEGDBGFHCBECDEFBGHEECEGCFAEHHEHHCHHCHFFAAEDAHDEGBEHAAGBEHDEDBCFFEFCEFCHHEHBEHBEHEDDEGDGABCEBDBBCBFFBDF,False +548,5.0,4.0,1.0,2.0,4.0,2.0,2.0,2.0,ACBADGEEGEEBAFBFHDAHBA,True +549,14.0,13.0,9.0,11.0,17.0,24.0,19.0,14.0,EHAEHGEDBEDCEGGEHFBFBBGBGGFHAFHBFEACBACEADGFEACGFEGFADHGDAGCBGHGCFEBAHBGHAHADDAFDHGGHGFFGFFCFFEAFEGEEFFHFDBBDCBEHFFDFAEFC,False +550,8.0,20.0,16.0,21.0,30.0,20.0,19.0,15.0,FHEAEECEEGBBBBBHBBDDCDDCDBCBFFEGFBCEHEEHEEBEEHFDCEECGBBGAGAHCAFCAFGDEGCEFEHCDBEDHGCGFFGEEGEECBEFEHFHCDHBDFDDGGDHEFHGDECDEHEGACFAFFGFBGBGAFGDDDDDBEFBH,False +551,8.0,3.0,13.0,5.0,6.0,13.0,5.0,7.0,BDFEDFGCFCHFCGCAFFAFFHFGCAGHAEHCBCCEHCHDCADCFFAEFCCDHGEFAEBA,True +552,10.0,10.0,17.0,16.0,16.0,11.0,4.0,13.0,CABEDBDDCCDFHBACBAEEDFGACHECHECEDHDDBDDHAHCBHEFHEFHEDDGACAECHEFBEFDEDDHCBHCHFGBFEBDCFACEGCAACFCEF,False +553,29.0,25.0,19.0,15.0,29.0,33.0,22.0,26.0,EABECBEDDEFBHACGBHHEHFFAFFEDBAGFCHDGEDEHDGDDCADHAFFABHCFEEBAECAECHHHACCAEABEABCCECFECEGCHGCFFBFFBEFDGGAGAECHEHHDHHABDEHAEFFEAFAFFAGFHGEAGFFGFAACAEFFEGBAABFGBEGDFHDFHEFBBHDHHGHBCABABBFBBGBGGEAGBFGCFH,False +554,19.0,13.0,14.0,11.0,11.0,13.0,12.0,8.0,ABGABGBBFEBEDGCDFCEAGEAGHAGFAGHACHCDHADCADFGDCDDAFEGFEDHHAGCGCFDEHBEFCFFCFEABGABFCHEBABBACADEAFBABACC,False +555,4.0,7.0,2.0,2.0,5.0,4.0,2.0,1.0,ABBABDFBHFBEFEGBAGEAEEFDCCB,True +556,33.0,24.0,13.0,22.0,28.0,22.0,18.0,30.0,EEFABBCDBADEGEHHHCAHGEHABDDBDAGAABDGBABBAGBEBHEFDEDCHDAEDBFHEAHFAHFABFCBEHBEHAEHCHHFEHBEHFEFFHAFHAGHEGDDHBCEDGAFGECHHDHFAEFAECAGAGCEGADDAEBABAAHHAHGAHFEEECAACGFCDFDDFAFEBBGHBGBAFBEHDFGDCGDFA,False +557,21.0,20.0,17.0,15.0,9.0,13.0,11.0,17.0,FFFCCBHDBHDBDDBDDHDCGFBAHBHCCDAADHAHHADGADCCHBCFECEACECCFDABDCEHEHHEBHDFFABAABAGBEGAHGACGCGGFBBHBAFBABAGHAFHFGCGDEFBBCABAAE,False +558,17.0,17.0,12.0,11.0,13.0,15.0,10.0,21.0,AACABFAEFAEGCEBAFBFHBDHEAHEBEEHDHHBHCBFGAFGFCACBFBDFADFCDBHHBHDACECHHDABGBBGFGHDACEBCEBCAFHDEBDCAAHHFHHFGHEGAEGHFGHD,False +559,14.0,31.0,29.0,20.0,24.0,28.0,19.0,25.0,CBHCBFCBGABHAFHAGDBEEHABFAEDGEDECFFCBFDFFDEAEHDDCECEHCBACBDFBCEECGGCGFCFHEABDABDGBDAHFHHGADGEFHDGHEFHEBBEBGCBFBBDCEGFFAHGBHAFFGFFHEFHCCHBBHFEHGBDDHCBCFBCFBCADCDBCGCCBBCBECGDCHDFHBGHFGFCEEHEE,False +560,11.0,11.0,9.0,9.0,7.0,8.0,12.0,11.0,FDCFDGECEACDHCFAFGAFAFECFCHECHABHGBHBBHBGEGGAGGAFDBHDCHDBEDGABEAGACHBHDBDABGHG,False +561,17.0,20.0,22.0,24.0,12.0,25.0,33.0,19.0,GFGGFCGFGDHGBCGHGHHGHCGHDGCGCDDCHGCFGFAHCHFDFCDEBDEBGFCEFCFFGAFCCGCHACBFDFGEEBBDDBECAFGAFGADGADGDDGADGFDEBDBBDBGCAGHGGDGGBBDFHCCDCEFABHHBHEEHBDHAFAGEAGDABFAHHAFBFGDCEBCBFFA,False +562,11.0,10.0,11.0,8.0,5.0,15.0,7.0,5.0,GBAGDDBFDHFDGFAACAACBBGFGEBGFFCFFCEFBEFBCBACFFCAHCAHEEDBAHFCFFCDDAGCAHDB,False +563,20.0,11.0,17.0,13.0,14.0,9.0,14.0,23.0,BAGDHGEHCAGCGEFAEFBCCHCCBDADHBDHADHCGHAGAFEAHHAHHACGCEACAHCDHBDGGDFEBFHHDHHCAHGAHFEEDGFDECDHHEHACFGHFECEGBBCAACAABDABEGBE,False +564,25.0,13.0,20.0,11.0,13.0,16.0,8.0,5.0,AAAAFFCFFBBFABDAGEAGAHGACCFEFGEGAEAACACEFCFFCDCHFBBCBCCADFBHFDCCBGABGCBABBDFACAAFGACACDEEDECDBDAEDAHDAECAECEEHF,False +565,28.0,15.0,20.0,25.0,16.0,15.0,18.0,16.0,AADAACACCACGGBEGAEGBEGFHCHCCEBCEBDBBDBCDAEDEBDABDFFHHEAADAHHGHGBDGCAGFADAADADFHEFHFGDEBDFCAFEHFBBFDHCDADDACDHFHAGCGDAGCABADCADEAGEGCHDDBDCAGFHGHCGAEFFECE,False +566,7.0,8.0,2.0,9.0,6.0,8.0,0.0,5.0,HEFHDFDDHDBEDBEFBDBBECBAFBFDAFHAFEDDBCEAAAFHA,True +567,12.0,8.0,8.0,9.0,5.0,12.0,6.0,5.0,DADDAGBGGBCHFGFDAFCACAEFADFGBFABCDDFEDFECHECDBAEAHCAHBACBFFAFFBGH,False +568,27.0,25.0,25.0,24.0,19.0,25.0,34.0,18.0,GGBDADGGGAGEFFECFEBGEADDADDAFHBBHBCFBCGGEGEDHDHBDFBACBGCFACBCGBEGHHGCAGHGBAFAHHBFHAFECHCABFGHCDHEFEFCEDCEGBGGDAGFFGFFGAFBEFEAFEGFDBFCAGCAGCABAHHHCEACBGEBDEAACCFGGFGDBGDCCDBEGBCDFADBAGBADDADHCDHCDGA,False +569,17.0,19.0,19.0,27.0,20.0,24.0,19.0,16.0,DCECCEHDBFDEDGEAGFGFBCHBCAGAHGFDAFDBHAGEADCHDCDGCBHCEFCHFCGFAADABFABFEECGFHHDHBDEBDBCFEEFEEAECGDBFCBDHBDEBDAFDAHCGDEBDEHDFADFDDFGAFEFCAFHDBEBBDGGACDBCHGFFGFGGEGH,False +570,14.0,23.0,26.0,22.0,21.0,32.0,13.0,35.0,DEACHFHFDHEHFCHFCEFBFHBECFECHDGEDFFDEFHFBCCACCHGDFCHFEHCAHCHHCEHEEHCHHCAHDDGFBHCBEAGGDBGFBEHBHFBADBFDAFGGGABHAGHABDFBFHCFDCFDHEHCEAAEGCBGDFCFFEFDBFBBFBCHBHDBEDHDDBAFFCFHAEHCEHCBHDBCDEGFH,False +571,12.0,18.0,32.0,29.0,10.0,22.0,15.0,20.0,DAHAAEGCCHHEBCEBHDDGDDFFCCCCCHCFHDDHDHADBEFBECBCDBCDFEDGHDHCECGACDAEGGDGDBFHCFDGDDGAEFDCFDAADAADHBCBBCGEDBBHCFHCABFDHFBFCBCCBCCHCFFDGCGGCHCBFDFFDFFCFHHBHGFCGD,False +572,19.0,12.0,16.0,19.0,24.0,11.0,17.0,21.0,AEAGEAEEBDEGDECBBDAHDAFECHEFHGFGGDEHDECGGCAEHEHHCBHDDHDEGCEGAHGFEGEEGEECFADFEDEGCCABAGBAHAHHAEHACACHAFHBCBBAEAFBHDDADDGDBFHGCHFCHCCGFDHDDBE,False +573,5.0,2.0,3.0,2.0,1.0,4.0,3.0,2.0,ACEFDDFABGAGGACFAHFCHB,True +574,17.0,18.0,22.0,17.0,4.0,9.0,12.0,14.0,CCBCGGAHDAEDBCFCCHCFACFAEDAHDAHGBGDFDDCACAAFBBDDBDBBFCBECADDACBFCBHCHHABCAHGBBGBADDACHAGHDGHDHBEHBGBGGCFDAGCCCFHC,False +575,13.0,19.0,23.0,32.0,16.0,20.0,25.0,19.0,GGDDGDDCHDBGDFDDHBBHGBHBFHCEAFEHFGFEGEGGDGDFCHFAEFBCFGHDGDEGDBHDAAGHDDADEBCEGCEFCEFEDBACHAHFDEFCGFGHBBBABDCBFCHDCFFCHDDGDDGECGEDAAHAADDAFDCGCHBCGBCEHDEGFFHBDCBDBGCCGCC,False +576,9.0,9.0,12.0,4.0,5.0,6.0,12.0,11.0,BHFCHFGHEGHBGEFHADCDCGGCFGCBDABAEBACGHEGFBGBAHCDHCGHAGEAHHCCFCBGABCA,False +577,6.0,7.0,11.0,9.0,9.0,12.0,13.0,8.0,EDDGBABEGCGACGECECCBCCHGEFDEFGGFGBCGDAGHGCHBFGBFDEFCFFAGFDHBDADFADFHHFHEEHC,False +578,0.0,1.0,2.0,1.0,0.0,2.0,4.0,0.0,GCGDCGFFGB,True +579,5.0,1.0,1.0,3.0,1.0,1.0,1.0,4.0,HGAHAACAAEHDFDDHB,True +580,23.0,6.0,7.0,14.0,17.0,10.0,20.0,6.0,EEAEEHDHGCBEABGFBGEACAADADGADHCGFGGEHGAGGDEAFEAGEDEAAAAAAEGCFGDFGDEGAEAFBAHBAGDFGDFECCECGDBAAGDEGHAFDDF,True +581,26.0,18.0,18.0,18.0,15.0,22.0,19.0,23.0,FFFAFECGECGHCGACGACAFFGHGEHADHFDHBDHCACGABGAFHHGAFGABDABAFBHEBAEAHFAGCAGCGFAEDGHFGAEBAEHDDHBDFAFBHDBFCHEHHGFDDBAEHAECAHGHECDFDDHHBFHBFCBADFFDCCDBCABGEBCEBDEGAC,False +582,21.0,17.0,16.0,25.0,18.0,9.0,13.0,8.0,GAHDCGBCBACDDBDGADCEDBFDAFDADEAEEBEHADFAHEGDBGFHGHCBAAHDEHEEACDACDECFEAHAGGAEGAEFADBGEBGCDDCFDABDCCAGBADBDFFDGDECDBCDCCEEBBEBBA,False +583,3.0,13.0,7.0,7.0,6.0,7.0,7.0,14.0,CGGBGGBGFBHBBHCAEBHEBHFFFDFADCDBFEBGCBCHHHDHHDBHEGDECBAHFDHBEHCH,False +584,19.0,16.0,23.0,16.0,22.0,21.0,12.0,29.0,CGHFFHFFHCFGDFDEECFDCDDABFAEAADFBEAECAEGAECHHCHAEHFECCHGCHGEGGEDHBABFAHEEBGEHHHBHHCDBCDBADCACABCBCCBHBGHDFHBFHCABGDCFCCADHAHHEHHEHFEABEGGAFDFEEFEAFCDDEHFBHCHF,False +585,5.0,14.0,11.0,11.0,4.0,5.0,12.0,10.0,DGDBCBFGBDAEHACCEHCDCCBHFBHFBHCAHGGGCGGBGCBEDBGBAGHFCHDCGDBHABEFBDDBDDHG,False +586,11.0,24.0,18.0,11.0,8.0,6.0,17.0,13.0,GBBGABCCDDEGDFGAHEAHCAEGBEGAEABEAHHCHBBHCBHCBGGGGGGBHCBCCBDDDCGGBEFFADFGBCABGBBDCBDBHABHBBHFBDFCHCBGDHACCCEC,False +587,14.0,18.0,17.0,13.0,15.0,17.0,25.0,21.0,ECCAFEAGBAGCGFCGHADHEBGCGGCBDCGABDHBEGBCGHHGFHGHHGHDGCACAEHBBBABGFHGFDGFDBDGBAHHGGBCEFCFHHFEHFEFFAFFAGFCHCHGABCHEFHCFEBDEBDACGAEGEEHBBDEDDGD,False +588,13.0,15.0,14.0,18.0,15.0,14.0,13.0,9.0,EFAHGBHGDHGDCADGDDEEEECFACDGDGHCCFCEDCBHFBGDBCDBCGFCGBCEDDEAFEAECAFCDFDDBHABHFEEBBHBACBADBGDEABFGFFADGAGFAEFEBH,False +589,12.0,8.0,10.0,3.0,6.0,15.0,8.0,10.0,FDAFCFFHFGHFGBFHAHAADACFCCBBCBBHADHACFAHBBCGGEBECHGAHEAEEAFFFCFFHGFCGAEG,False +590,17.0,15.0,7.0,14.0,11.0,14.0,9.0,6.0,HEAFCADCHBHAFEFFEDAAFBABCGDDFAAGDGDCBEBFEBDEBAEAEBAEBAFBGFBHFCGCHGHDGFAAFCADBDDBDDGFAGFABEDBE,False +591,10.0,3.0,10.0,5.0,10.0,14.0,7.0,11.0,CFGCFEAFHGFCGAHACGFEADCAECAEBEDGFDHFEHFEHBEHFECFAAFHAECDHGDBFHHFAHCCFG,False +592,19.0,16.0,12.0,22.0,13.0,29.0,15.0,13.0,GHBEBBFBGFCCFDDECDGGDFGAFABCHFAFFABBCHBAFGHFBEFDEFGEFGDDGDDACDBCEAFEACEDDFFAHEAEDDHHFFDFBGFHGDBFHECCCFBDEBAHFAEFAGFBGDHADAFDAFDAFHAFGAGCHDB,False +593,7.0,6.0,8.0,6.0,8.0,9.0,6.0,6.0,DCHBFDCFDGACEACBBCBGHAGHFEHFEHDEGAEAACGFBFCHFCAEDFEBEDGF,False +594,30.0,31.0,17.0,16.0,20.0,23.0,18.0,23.0,ECHGCHGBBGFBGABGCDGHFFBFABDADAFEAFEHGBAABEABHABHACFACBEFADDADFBCGHHABFEBEGBCGEHFEFEBGEHGDAFBHDAFBAHBAHFAFACGDCHDCHDGBEBHEFEAFEDHACEBCFBCHBFHBAACFCBAHGHDDEADHAECACGBBABAFBFEBGEHGD,False +595,9.0,14.0,16.0,12.0,7.0,14.0,15.0,6.0,FEGFGGFDBAGEFGEFCCHCBEFBCGACBACFCCBCAFCAGGFFCBHGBHDBADADHADGBDGBDEBCHFCFCCGBDGDHEDADDFEBGGCFB,False +596,26.0,34.0,20.0,24.0,21.0,26.0,22.0,25.0,FEEBEHGEHEFHEFEEACGABBDHDDHGCGFDACBGBHGFHDADCFGCGBDAHHCFHGFEEFEAHEBHGBAABDABFAHFHDDADDFDBGGBFHBAEBAEBAHBAFACFADADDAGGBBGBBCCACFFBDFHDFHDBCBCABAECDFGDGHHEECCAFDBDEFCEFGDBBHBBHGGHFBHEGGEBCABCFBCFCAHBA,False +597,16.0,18.0,17.0,23.0,22.0,17.0,16.0,28.0,EECBEAGEDFCFADAHFCHFCHECDBGDBHDCHAAHDDBDDCDHHFHBAHBEHDEHAFHAHHEEGEEGDEBDEDDHBEBGEHGEHCACFHBDBACHECEBCACCGCGGEHHDHBFGEABFDFFDGFAHCGHCFHBGHGDABDAFGBEGFDFBDEHFA,False +598,14.0,9.0,12.0,11.0,20.0,14.0,7.0,8.0,EEAFAGFHFFBEAGHBCFFFFDFFBAFCEGEEGDCGDCBAADAHFFHAGHACDECBEDBEAACDGCEACHDDADBECBECHEAHFDEEEEEEEBC,False +599,31.0,15.0,28.0,34.0,25.0,28.0,16.0,23.0,EADADBADCDDCGEGGEAFEFGBDDCFACDECFECFBCHAEHABGFCCAECDEDGCDGCDGEAHDBBDBACEAFBFEBEDBEBEEFGAAGADGDFFCEFAFAABDFHDFHDGCDGHDFCDFHEFAEGCFDAFDAFDEFHBCDAFEECHHDDHDCFFAHHHHCHADEADADBADBCGCCHFAFCEHHAFHAHHAEGACCCH,False +600,10.0,11.0,5.0,10.0,8.0,10.0,7.0,10.0,HBFHBHGFGEFGEFAAFAGFGEBBHBDGBHHAHCDHEHBEAFDDBBABDFDCFHEBCECCADGADFADAED,False +601,1.0,4.0,4.0,5.0,1.0,4.0,5.0,0.0,EGCDDCBDCFDFBGBDGCAGFBGF,True +602,4.0,2.0,2.0,6.0,6.0,0.0,2.0,3.0,EDEEBAEDHEAGEABCHDCDDADGH,True +603,22.0,28.0,15.0,26.0,22.0,27.0,16.0,24.0,EADBBCFGEFEAGAFEACAHCDBABGHBHAEDGGDCGFBBFHFCEFCEFEDAEGEHGABFHBFDBGDBABGGCGBCGBABHAFDDFBDFBGFHFCHFCHFHECHDFFDFABFDBHDFDCFDCABHABHEHADCDDCDHFEEDAEDFEBHHAFHGBHBBEEBDHDHEDABDABAEGEEHAF,False +604,21.0,11.0,14.0,19.0,11.0,12.0,18.0,29.0,GHHGHHAHADHAHCGBCGBDGBDHDFAABAEHFCDDAACAFHBHHDEBEGAGGEBGEHDEGFGGCHGDBDHHDAAAACFACFHBHEAAEHADHGCHGHDBCFHEFHEFECDDHFDCGDFGAFHAHHCHBCGDCAD,False +605,9.0,11.0,6.0,10.0,8.0,6.0,9.0,4.0,DCGDAGDABEBBEBGEBGDDGHAHHBCCECAHAFFAEDCEFFEDCBGBBGEGDFGDBAAFDAB,False +606,28.0,22.0,23.0,19.0,24.0,23.0,22.0,23.0,GHDEEDGFDEHCEBCEBAGAAGEGGEGABFHGFAGAHGDCCDHFBADBDDBCDBFHFDGEEGCEHFFHCCHAGHABEACCACDFEEFAFGEFBCGBCBFAFFBFFDGEEGBEHBHHDCACFHCACAABAABAECCDFHHFHBDAEFHEFEECGFBGCDGEHCBGDBAAAHCAHDEHDBHABAAG,False +607,13.0,16.0,14.0,14.0,17.0,12.0,10.0,10.0,BGHBGADGDDGCECBEDBECAECGECGECFACFBEEBEADEDHFAHAAHBFEBHDCFDGDBFFBEGCAFADDHCABDACDABDHGFFGEEBFEBABCEFEHCHHCB,False +608,9.0,17.0,16.0,8.0,12.0,15.0,18.0,16.0,BGGGDCHHBHGBEACEACEGCEHFHCBGBBGFBGFAHCDGCFFCFGCBGBBGBFGBFAHFBGFBABCEGCEADHHEHHCHFEGEDHDDCDABGHECCFCFFGBADEAEHFH,False +609,34.0,28.0,25.0,20.0,27.0,20.0,18.0,15.0,FHGFEGEBBEGBEGHFHDFDAAEAAEDCFDBFEFCDCDDGEAFEADBCCACCDFHHBCHFEDABBABBABHAFGACGEEEACCACDDCBFCDHBFGBAGCGFADEADGABFABAGEEEBHBFDBFEBGEBEBHCCDCAGCAECAECAFCHGEEBFEAGEDECAHHABABBABDFDAHCABCAGHAGA,False +610,27.0,20.0,29.0,19.0,16.0,20.0,23.0,16.0,EDGGDCDCCDCCFAHFACFEEAAGGAHFADGADAEDCEACDAGDAHDCHFAFFHCGHCGDEBAEBAFHADHCBFBBDAECAECACGGGGFFCDGBHGECFBABDABGECGEFBFCBHDBHAHGACBAHEACCACHBHEFCBDCGDBGCBGHGCBFCADEFBFFGABGCEF,False +611,22.0,21.0,24.0,24.0,11.0,17.0,21.0,18.0,CGCHDBGDBABGACGAEAACCDDCDGCDGFDEHBABFCHACHAFGDEBDEBDABHGBCFBCBAHBDFBHFCFECFECGAGEAEBDGCGGCHGDFGDFCFBHFAFGAGHHFBHDAADCAHCAGEABCCBDDEDDHCCAAHFHHDADDBGHCGBFFBEDG,False +612,15.0,15.0,16.0,7.0,8.0,15.0,11.0,10.0,BBGABCABCFCHFCBCAGHHFHFFBFAAFAGBAGDEFFCFECACDACAFCABEEGCEGCAGDBCHBDDFDDFAFHACBGBHGBHCEEEGHCGFBHBA,False +613,1.0,6.0,10.0,13.0,4.0,6.0,8.0,9.0,GCDDCDCAHCHEDFDCCDGGDBHDCHDBHCGGFGCFGHFGFFHHCBBEEBDEDDBDH,True +614,10.0,16.0,11.0,12.0,14.0,10.0,10.0,10.0,DECEGBDAEDAEGGGHGAAEBAEHDGHGEBCHBCHBFEBCBFCBAHEDFEDFGAFDCFBCFBDFBCHCCHDHBDBBABFDGEEEDCEGAHBAF,False +615,1.0,1.0,2.0,4.0,6.0,3.0,0.0,3.0,HDEHFEDCEABEHFEDDECF,True +616,10.0,6.0,9.0,12.0,6.0,14.0,6.0,4.0,DFHDFBBECCFCCFBCDGAFFABDAGEADBDDACECFECGAAGHFHFFHFFDGDAFDEFDEBDAAGC,True +617,6.0,1.0,4.0,3.0,5.0,2.0,0.0,4.0,BDEHDAAFACHECHECDEFHCAAEA,True +618,22.0,16.0,36.0,14.0,21.0,16.0,20.0,16.0,BBGEBEHHHHHACECCGBEDBCDHHAHDCHDCECAFHAFDAFCAECGCCACCGFFDEGACGCCGCEGCGGEGACGACBDGGDEAEBAEGFECAECFBGECAEFFHBCCBCHEFADFDECDBCBFDHDECDGAABHCFGCAGCFGABEABCABCECCFFAHH,False +619,26.0,17.0,24.0,18.0,27.0,15.0,23.0,23.0,ADFABEBGDCGDEAEHBHDBCGECBECEEGAHGCCECGFCAFCHECFACBAHBACBAEBDEHFEDDEHGHHGHHGAHGAHFADAAGEAEDAFAADADHEGHEGHGBHDBCEECGFCHEBHBBFAHDCGAEGEEGECGHCFCFGCDDFDCBCFEAAAFEAHGBGDCDBEFCHAG,False +620,7.0,2.0,1.0,9.0,6.0,2.0,5.0,5.0,GBEGBDDHGCFGDGHEEHDEFAADAAHAAEAHEDDDD,True +621,16.0,26.0,22.0,21.0,29.0,29.0,17.0,19.0,EAFBDDEEGGEGGEGDFBBFADADCGDCBCCHCDDEDFEDFADFEDFGBFHBECAHCDBCGFCFECEEHAFHAFCGFBEHGFHEEHFEBCGBGGHABFGDAGCABFDBFDFFDEFBBBDHBEECFEHEACBFBDFHAHHEHHEHCCHGBAEBDCCEEFBBFAFCBDCBFBAFEACEGHE,False +622,7.0,7.0,8.0,11.0,8.0,4.0,10.0,8.0,DAGDCGDHGDACDBCFHHEGDEDEFHCBHEBHFDHEHBCGGEGBCGDCFDGEDCAABAABEAG,False +623,28.0,16.0,21.0,17.0,19.0,16.0,21.0,15.0,DEHGEHCAACGFGGBEFBEGGGBGFADAEDADDCCHGGACAACEBDGFCBDAAFBCCCCCAEEEECHDCEDAEFAHFABFACFGHHBEGCEFBAHCDHDBCEBCEAHAAHAABEDGECGFAGFABFAHFAHEAHDHBFCBDDAFDAGBGGDGG,False +624,3.0,1.0,2.0,2.0,0.0,4.0,3.0,0.0,GAAFDAFGGFCDFCB,True +625,2.0,3.0,2.0,8.0,3.0,1.0,2.0,1.0,DHDDBDABEGDDGBFAEDCEDC,True +626,25.0,22.0,16.0,18.0,24.0,24.0,24.0,13.0,EBGFHAFDBGEBGEFGEDHADHADAAFCAFCHGEAGACBDGBFBDFEDGEHGEHGDHGCFCEFBEACEBHGFHEBHEGFEBAECFBABCACCABAEDEDGEGCABEEDGEAGAAGCFFDBCGHAGCAFFGFDAFHFFGEBBBHBDAGDABDBDGBAFEDFCAFCEF,False +627,29.0,21.0,28.0,24.0,31.0,21.0,20.0,20.0,FAHFBGFACEAEHGHHCFHGAGFFCCDDBDGBDGBDBHEBHECCEHCAFEGEHGEHGEGGBCABADDACDEEBCHCGAAEAFCABCEBDABEABCAECAEAHHFCFGDFHDFHBCECEDCDFCDACEFBEDBFDBEBEHHECCEDAFDGFDHEEHEGHCDDADAAEGAFADCGCGFEGFEABACFAEBACBGDA,False +628,12.0,14.0,20.0,9.0,14.0,5.0,7.0,10.0,BAHEECEFDEACFADDABAECEHFDHCCCACBAEDHEBHEBHFHCFCCGCDACAADGEGCCGCGBCBBCGBCEBEHBEDCADBEGBCABHH,False +629,5.0,5.0,7.0,3.0,4.0,2.0,2.0,2.0,EFAECAECHGHFCDABDBCDBCBCABCGEA,True +630,23.0,22.0,17.0,29.0,22.0,31.0,12.0,12.0,CCDECDBBHBBHBGFACDAEHBFBGFCCEHGEHEECEFDDFDDBEDBAFEHBDHBFFFFFFFAFFAFHDFAEFACFCCGAFAAFGADGADFFEBHEGEAAFBDGBDADDAGEACECCFBBEEGGEBDBBCAADFEDCADFFDFAEFBHDDDDBCCBFGDAEHEHDDAD,False +631,27.0,22.0,17.0,34.0,24.0,29.0,22.0,24.0,FFDCFDCHHBFADFAGECGECGBFBAFBGGACBFCBACHEFEEFBEFEEFCBAEECEHAEGAEFACFADFDBFBHHDHAFHADDGHHEHDDGEBEEGFFDDGEDGADGBDHFDHFBHFHAABAADHAEHBHGDFGEAADDFDCCDCDDFBAGCFDCGDHBDHEAFDGBEGBADEFGCDBADGADHEHGFHBDHADGACB,False +632,14.0,22.0,9.0,14.0,13.0,13.0,20.0,23.0,BCFBCFAHGDHGAHEDGEBBCBHEGHDDDBAGBAGCECBBGBDABAGHDGHEFFBHEEEEHDEBDEFAAFAHGDGCDAFHAHGADGAGCDDHHFHGFHEBHBGHBFBBFGBFHHFAHCHHBECBGBGG,False +633,24.0,22.0,20.0,25.0,23.0,16.0,19.0,23.0,DBBDHHDHHEFEEFGABGFEGADFACHGEHGEHAFFAHECCEACEBBHBEFADDDDGGHGGHAABCFDCFBGFAECDGBDABEAFECFEHBAHFDBFDBDEFCBCCGDEACAAGBBGBDEAEAAGAAHBGHACCAECGCCDCGDEHAHGBDDEDDHDBHDHHFCHDBHEBCE,False +634,17.0,21.0,22.0,24.0,23.0,23.0,16.0,18.0,CBHDBHCEHCHBGDBECHEHFBCFDFBDFCGFCACCACCGDEAFGADEADFCDFBAHAGHGEBDDBDEBDHBGBDAEDBEDCEFCEFHBHCGDAHAAEDEEGGECBEHDGDBGEHFEFGEFBFFAFFCCFECEDHEGCAGBACFDGFDHFBABHADFBEFHADC,False +635,16.0,6.0,8.0,5.0,5.0,8.0,8.0,4.0,FFABFACAAFAAHAFHCEACEABFCDGCFACABGGDGCABAEBGEAGBAGHACHFEDDDG,False +636,0.0,0.0,0.0,2.0,3.0,1.0,3.0,2.0,EHGEHDEDGFG,True +637,9.0,16.0,10.0,10.0,13.0,11.0,8.0,12.0,FEDBEDBEBBEFBEHBFBFCBEGBAGBHGHDBDDEGBECEFHDDHCFHGBHEBCGBEFAACBDEFCGFAAHAHHFFAADAHDCHGCECC,False +638,12.0,9.0,9.0,12.0,9.0,15.0,8.0,15.0,EFGFDCDAGDHFCBFEAFHACHBGADEEHEFGEDHFDGDDGAECCFHBFHBCACHACHACFAFBGDBGDBHBHHBHDEHDAAAEFFFHF,False +639,14.0,20.0,11.0,14.0,9.0,16.0,14.0,14.0,BFBHEBAEDADCGDAGDAFBHCBACBAEAHHCGBCGFCGAABFCBFGADBFFFDFCDFEAGGDHDDEFFHGHHGHHEFEBHBBGDBCHBEHBEFBCABDGGDCGAFHBFABD,False +640,8.0,6.0,17.0,2.0,13.0,12.0,17.0,7.0,HCFFGFCHCCACAADFGBFCFFCGFCABGBEABGCEGCEGCACCFGDGECGHCAEGBEGEEGHBGEAFEHFEHGHGEECCGF,True +641,14.0,17.0,15.0,14.0,30.0,13.0,21.0,15.0,BBGEDAHDBBEHBCBEHAEGAFGECGACGADAFGFFGFEGDBCCBFCHDHABHEBGEDADDHEGHBBHEGCGCHEEHEEHGEHACACCEGCGGEDGFGAFDBFCAFBAFEEEHGEGFEBEEBHEFDECEEDEBGEDCAD,False +642,26.0,25.0,28.0,26.0,13.0,16.0,19.0,13.0,EBDECDGCAACBAHFACDCCBCDDHDFBDBDAHGAHGBHGBCFDEADGADGHFGBAHBCCDHBDFDFHAEEFDCGGCFCAFGACGCCFADBAEBGBGGBFGDFBFCAACAACECBBHBBGABGFCAHCDFGDCCEBCDACHBCAAEDEEDFEHEDABDACDAGDBB,False +643,14.0,19.0,17.0,9.0,14.0,22.0,18.0,8.0,GCCFBFFBEABEHDEBDGBDFAHFBHCBDEBDGBDHHFFGAFGCGHCACFBGGAGGFEGFCAFCADGGCFECECGFAGFAGACHAFHDCBBCBFABFEBCCBGFEAECDBBFFBAEEEEFG,False +644,15.0,27.0,16.0,22.0,21.0,27.0,27.0,18.0,EDFEFFDFBDGBEGBHCFHCFHFAHFGFFEHGEBGEBGABGCGEBGFFHADEDGEBFABGAEFEGFGGAGFDHFBHCBADAEFBCFCCHDFBEADEDBBBGDBDCACCFCEFDDFBHHAGHGGBGBEGCFCBFEGDAGDEHCEHEBHEBADHDHHDGCDGBAFBDCGAFGDBB,False +645,14.0,11.0,10.0,13.0,16.0,12.0,10.0,15.0,EEHEEHGEFGEDEDBGCBHHFHBFDBEEBEBAHBDGACGADGHEHHECDFHDFDFAEFACFBEBHEHAGDCHDCDGCFAAFAAGCDGCAAAHHFBCDBAFE,False +646,3.0,5.0,2.0,4.0,7.0,6.0,2.0,5.0,EEDEFDFHDFHGFHCBHFBEEEABHABFDBGCEA,True +647,17.0,19.0,20.0,19.0,12.0,18.0,17.0,19.0,HCFBAFBDFDHBCACEAFHCGGCAHBHHBHFECADGBGCDACAECGDCFDFEHBABGADGACGBEFHGFBDBCCBCFBDFADFGGFEGFHGFEBDDBDDADBFGCFGHECHCHHGGBECECCEBDEDHADHADHAFHAHAB,False +648,10.0,10.0,6.0,7.0,5.0,10.0,7.0,10.0,CHGDHGHAECAEAGBCGCEDFBGFCGBCFBHAEAFHDFBEHBGFAFFDDABDABDFBHFHHABHA,False +649,23.0,19.0,18.0,23.0,11.0,22.0,22.0,16.0,DFGDAGAEGAEDABBFDGADBHHAEGECAFDAEDACGBCGDCGHCGBCHEGACCAFDBFHBGGGDBGBFCBEGFHAHHCEDAEDBBAFAFFAFGAHCHCCDCCGBDEFHFFDBFBCFDCDDAAAGDEBDBBHBFHGFHFFHFAHGDGGDACDAF,False +650,4.0,5.0,4.0,4.0,6.0,3.0,2.0,5.0,DDHGDFGEFAECAFCDBCHEEAEEHHBACBHBB,False +651,29.0,15.0,14.0,25.0,15.0,16.0,23.0,19.0,GAFBABHAGGACGAGGAGHABDGFCGDEGEFDFACFBDAHAAHCGECDHFEHCDDEDDECGFDDFEDADAFDBFDBEGHFBAGBADBCDGAFFCEDEHAAHAACGAGDFDDFDAADCAFHBEHGEHGCGEBBHHBCDBCDHEBAEGGHGHHAAHAA,False +652,17.0,19.0,21.0,19.0,20.0,33.0,24.0,19.0,EBHGBHEFHAFCFFEAFEADEBHCBFCEFDEFHBGHGFDGDAHEGFEABBBBFBBFBBFAFEBDHBCBCGFEHACDCFDBGHGEFGACCFFFFDADGFDCFGEGHHGEHFFHEFHCFAGFBGCCGDCDDCGECGHAHEAGEDBCDEHDGHFGFCCDAAFAAFGAFDCGECGD,False +653,4.0,2.0,1.0,5.0,5.0,3.0,4.0,8.0,GBFEDEDGEDEADHGHHGHHDBHAHEFHCFAA,True +654,20.0,23.0,22.0,29.0,18.0,18.0,13.0,18.0,EDEBAEGHHFAHFBDDBGFBGDDABDABDADCCBBCEHGFCGFCDEHDFDGHDCBDHFDCBHBFHECCADGHGGEGBCBACHAEGEEFDEHDCHBEHFDBFCEACFAEDAFBGDBDDBDDBFDCFDCHDAACAABACGFCACDHHAFBAFBHEDCEBEEAC,False +655,7.0,8.0,11.0,11.0,11.0,5.0,11.0,11.0,CHBCHDCHBAHBCGDEGDACDEBAAAFBEFHFBGFEDEEAEEGDGGDGHDAHDHBEEGDECCBHCGCCGHCFHDG,False +656,23.0,22.0,23.0,10.0,19.0,19.0,24.0,14.0,FCGFCGAAEBHECHECHCGABAAFFEHBAHBCBBDEBEFDFADFGDFACFAFAHFBCEACECCDGBFEBFCCCCEGAAHAGEBGABCFBAAGFDFCEABEABECDGCGAHGHCCHBAFBHEEHCGBFGBAHBGGEGGEDBEDBDFGGGGGGACH,False +657,17.0,18.0,13.0,17.0,9.0,17.0,17.0,24.0,BDHBDGBFEBCHBDFBDHBAHBHHAAGABHACFFHHBBDDHHDHGFCFFCGHHBAHADGFDCFHCHCCBDFFGAFGAEEAGEHHBGFFGFAGHADHDCBDEFDECGAGADCAGCHGEHBEHFDABDGBCGAE,False +658,8.0,8.0,5.0,2.0,2.0,4.0,5.0,8.0,CEGBBGBHCFHBHBBABGEBHHGCFAAHADHAHGACFACFAD,True +659,34.0,21.0,21.0,17.0,21.0,20.0,30.0,25.0,HAFHDCDEGEEGAAGBGCBEAGEBGEAHCAHEAHCAHAAHFBHECECABCAHGGFGHHGEHDADFACFACFCGFCGFBBFAAHAAHBFFDAFDGFCAEAGFAEDBGBCEEFFFDEAGGADGCDFHGGHBCABCABCABHDGDGGEGGEGHEAHBDGBHHBCHDFAECGDBHAGHADABBACEFHBDEGC,False +660,14.0,30.0,12.0,19.0,8.0,11.0,20.0,13.0,DEBHHDCGGHGCHBFBFGBFDDFDDGDGBDBBABHDBHACECCACEABBAEBDBBGGGCGDAHCADCABHEFHBFDCDCGGFBGDBDBBGGBCGBEBBEBBHHBHFFHFAADGBBGBGADDFEAAGA,False +661,11.0,26.0,15.0,26.0,16.0,14.0,18.0,26.0,FEBHBBCBDCEDFABGAGEABBHBGCDGFDEBBEBBDBEGBEDDHHDHFBHEBEEGAHHDHHCBHCAHDHCAACEGBEGBDGBHBHDFHDHDFHECHCHEAHBGCFCFHDDHDDFDDAGEGGCCGDFGFAGFGDBBBHBDHFDACDCHFGDE,False +662,5.0,2.0,4.0,1.0,4.0,3.0,0.0,4.0,HCDFCFHCACAEEAEFBHABHAE,True +663,14.0,22.0,18.0,13.0,14.0,22.0,18.0,29.0,DHBHHBGHGDDFFFCBHCBFCHGCGGHHHHABCCBAFAEGBBDBFCFECFADFHBCHADBADGHDGCDACFHBFGFFBFGCFAAEACHAFHEEEEHGEHAEBGBGGBFCBFBGGBGAHDHHBECEHCHBFECFHAFHDCHDEHDEHGFHB,False +664,22.0,13.0,19.0,20.0,21.0,19.0,24.0,26.0,AACFEGGECAHDGHDGDBEHBGDGGCBEAGEFEAGBGGBFFBGGGGDCEEAAFFAHEBFEFACFECEABEFHGFHDAHCBHCFGDFHDAHGEHEAHEAGCCCHDAHFCEFCDCAFCGCHFCHGCHGCBGFBGHHDAHEAHDHHDHEEADEFDHADADDHDBADB,False +665,19.0,16.0,20.0,18.0,23.0,17.0,22.0,24.0,DAACFCEFCEHBFHAEHDBHBHABHABHAHCCGGCGCEDBDHBACCCCCAEDHEACEHEDGECGEFGCGDEFHCAHADFDEEDBECEACDGEDGFHFAEFAGBHHAHHDHAGBBFCGFEGHBHFDEFDHFHHABGABGEDGEDGEGGBCEBGDFGFFGA,False +666,21.0,15.0,10.0,14.0,9.0,13.0,18.0,9.0,ACFGBACCACCADCDGADGADGHBABGDFEDEGAGFADADDBEABDABEABAFBAFBGFGGACGBFEBFEHFHGACGCFEDGBGABCEHFGBAGFEDADBAFHHGHHDH,False +667,8.0,7.0,10.0,12.0,11.0,15.0,18.0,9.0,FAGEGGDGEAGDFCFFHBFDBGDFGBAGHCGFCDBCGBDFHGFHEACECCECAEFGCFGHFEDGHGBHFCHAEDAEDGDFGFGEBEDHAD,False +668,10.0,9.0,8.0,13.0,5.0,7.0,10.0,7.0,GFDGECCECCFHAGBGDBDFADGEDAADAADAADCGBGHBHBDHFGHFAHFACDEHBEBDDCGGCDFBB,False +669,7.0,12.0,7.0,12.0,9.0,2.0,15.0,14.0,HBGHAGHEGBCADABEEHFCCGHGGEGGCDGCHGEDGDBADBHDBGEAGAACEDDFBHBBHBDHBDHGCHGHDEEBHD,True +670,0.0,5.0,2.0,3.0,7.0,4.0,3.0,4.0,FGCFHFEDBHBBHFBGEBEEDEEGEHCD,True +671,5.0,12.0,12.0,3.0,8.0,4.0,5.0,4.0,BBCBBAECHCGHCHFCFCCBDBECBEBFEBCGHCEFGGBAGEAEEACCBDABD,True +672,11.0,18.0,12.0,10.0,18.0,18.0,25.0,17.0,AGBBGFGCFCEFCBHCADEBHCHDEBGGGGGAGGCGFHFBHDBFFAFHAEHFEFFAGBEDHHHHBBCFHAFCGCCBEHBEHGDBFEAGEHGEAGEAGEGDBGDCGDGGDFHEFEBBCBAGBEDHEFGEF,False +673,9.0,13.0,14.0,18.0,14.0,11.0,8.0,15.0,CGDBHCCHGBFGAFEEHEHCEHCACCADCDDCGBCDBHDHCBHEHABHEEGDFHDGACBAGDFEDFEDECDBDHFEHBEFFEBCEBDABAAGFHFDDFDDHB,False +674,8.0,13.0,7.0,9.0,11.0,13.0,8.0,11.0,GHHFHFCGFBEFDEDDBFDBAHFHHFCHEDGEHGCBDBHHAEGAEAAEBAGBAEFCFGCFAHBGEFECBCBBDBBDEFDF,False +675,1.0,9.0,5.0,1.0,4.0,4.0,4.0,4.0,BECBCFDGHHBEBBFBBFBCFBHGAHGCEECG,True +676,7.0,7.0,1.0,4.0,6.0,8.0,6.0,3.0,ECHEDFEAHHDFABGEBEABEDGFAGBAFBAFGFGGFABFDB,False +677,14.0,18.0,19.0,11.0,14.0,16.0,16.0,25.0,EEHFECBGCECHDBHGHHGHHGABBDFBDFBAFHAGDABCABFHHABGAEGDBHHGHFFHDFEDFHFGACBCCGCAAFFAHACDGCDBCHBFGBHEFHAFCCEBBDHCHFAHEGHEGCEHCECCHGEGBECBD,False +678,9.0,12.0,6.0,10.0,11.0,11.0,13.0,11.0,CDEAGGDGGCGBCGBAGBGEBDCAFGHFGBFEHEEACFAGFDEFGBHHFHHEHFCGDADHHDHEDAADFBFBBFBEEHEABBD,False +679,27.0,20.0,25.0,20.0,31.0,18.0,23.0,23.0,EFHEDHDDBECBDAFEEFEEAADGGCGEBGADEECEEFEECAFCGEGGBFCBFABGACDAEHBHCFGCHGCHGCFDCBHHBEABAHBABAHEAHGADGCCFECDHDFAGECHAFBADBGDBCABHADDBHCEHCEHBFHGFEEDCDHCEECGCDBCAHGHBGEAGEAFFAFGAEEAFAHGEHGDACD,False +680,27.0,26.0,27.0,28.0,20.0,19.0,14.0,25.0,GDCFDCFHCBAEGAFACFAGFDBEABDBCAHCGFFFCFBBBADBGFCDACDGDDHCEHAEHBFGBHECDEGAACBHCHEAHEFCGACDBHDACGACHAHHAHDEHFCBBABBABCHBFDCGBCHBCHFDHEEBDEHEEHGEFABHAHCAEDBCDBCDEEDCBDBHAFAGEADDADFADFDDHGDEC,False +681,3.0,1.0,1.0,3.0,4.0,8.0,7.0,1.0,HGFEDDABGFGGFGFFGCGAFDAFEEFE,True +682,15.0,12.0,11.0,14.0,15.0,27.0,23.0,14.0,FHFFHFCHGEDCEDGABGDBGFFGFHGDDFFDGCHECAEGEBCEFCEAAAAGACFAGGGBEGBFBAFBAGGAEHAEHBDGGDFDAHGGEGGHAFHGCEFDBFEHDDBGFBCFAFFEHFCHFHDFCFFDEFB,False +683,3.0,2.0,5.0,6.0,4.0,4.0,5.0,2.0,GGFDFADFADECDCGBCGEDHEDHGCBCAEF,False +684,13.0,18.0,21.0,19.0,20.0,13.0,21.0,11.0,FEEGGCAGBEGFECBEGBDHBDCCGACGFBFEHHEHBCHCCFDCDDCEACEAFHHFCFDEBBGBDCBDBADEDEGCFDHABEDGEGFDCFECDEAHEDGEAGFAEAAGHADABDBGCGGBGFBDCBDGBCGECGHC,False +685,10.0,7.0,12.0,11.0,9.0,18.0,8.0,9.0,HDHAGFAFFAFFAEBDCBDBEAFEACEACDGDDGFCHFCBCCACHGCFFCGDEFDFHEFHDCBEHGEGFFDFAAFBEFCDGHBH,False +686,6.0,12.0,8.0,11.0,9.0,7.0,20.0,10.0,BCEBCDBHAGDAGDHGDEDAGDGHBEHDDFGDGEDAEGGGCEBCBGGGCHECBFHHGGFGGFGGHGAHFBBCBECBHABFDEF,False +687,12.0,20.0,16.0,25.0,15.0,20.0,20.0,33.0,DFDHAGHAEHBHBFCFFDHFDBGGCCBDABHGGHBBCBFCHCEEADDACDFCAFBHBHDBHFBADGHDGHDGFEEBHHGGHGHFGDFCDHEEHCECCHDBDAGDABDCBFHAGEAHEHHEHFDHFDHFDEFDCCGBCHEDHBDGEHGBBGFDHAHHFEFGG,False +688,3.0,9.0,2.0,3.0,7.0,7.0,3.0,4.0,CFEHFBFBBEDBCHAFABFEBEEBDEHFEDFHBGGBGA,True +689,15.0,26.0,20.0,34.0,29.0,23.0,27.0,17.0,GAAGDABHABEGDEBDFFDHFEHFBFCBGCBCCDGFDEHDCFDBHEBEFBEBCGCDGADBDGGGAAFCEDCEDBHGBDDBEDFFGFEHBEFFCAHCHHGFDDBCDBDFEHFGAFHFFDBEABEFBGFAGHGGEECCGABDDBEEBECBEAGCHGDHGDEDHFDHDAECAECDEDGEDEBCEDDGGDEGBCG,False +690,2.0,5.0,5.0,7.0,3.0,8.0,3.0,2.0,GFGFFGFDHHAEBCCBCDFCDEADFDBFDCEDBBF,True +691,11.0,14.0,14.0,3.0,13.0,5.0,13.0,10.0,ABGFGEEGEEGEHAHBCHBDDGHBBABACBCEEGECGECGHCABCABCHBEGAEFCCGBFGCAEFGECBFHACHACHDHBGBA,False +692,17.0,27.0,23.0,13.0,20.0,16.0,15.0,12.0,BCCBCGFCGFADAABEDHEHBEADCFFEFFCABCGBABBEGBADBABBFCACGEDBEBBGFBGHBGHDEHBEHBCHACHFGEECHGFHGCCGECGDBBDGAEADFCGECDEFEFCCFAHFEHEABAFCCECEBDDBADBABBC,False +693,27.0,22.0,19.0,22.0,14.0,28.0,28.0,25.0,FCDFEDBEDFECFBHAAHEACBFDEGDCGFFHHFADGABFAFAAGGBHFECAECAGCGBDGBDHBHCBHFEHBBAFAAFAFFCHFGGFHAADCCGCCGBHGDDGFDGBDGBABHAGFDBFGBHAEFFDGFDGCAACAGGHDGAGCDEHDHBGHEFCEFADHEHABHAFHEHHDBGGBFCBGCHAD,False +694,18.0,13.0,19.0,10.0,11.0,15.0,13.0,6.0,GDGHAABAGDGHFBFGBCGACGAEAFDAFDECHECACBFCBACBEBDGBFACEEBEDCEACEBBDDBGFAFFDCFECDHCACCGBFGHGCEGCAAHAAFCAFCFF,False +695,10.0,11.0,11.0,10.0,20.0,12.0,15.0,5.0,DBDBFDEGDBGEEGEGFAAEGDFCFECEEAEEBHGGHCGHCFACGHEGEEGAEFCEFBAFBAEEACCGFDBFCHACEDFADFGBGCBDEBEGBD,False +696,11.0,15.0,9.0,15.0,19.0,14.0,16.0,14.0,BBEABEBFEDFHBEDCFCEDEFDECCEFGFGBHGBCGHGFHEBDGBFGCFGDGDACDAFBFHBHGECGEHDEHBBFDEEDGEFCAAHEABEHHEAHEAHDAHDGGDBGFAGAD,False +697,4.0,10.0,3.0,4.0,4.0,9.0,13.0,9.0,EFFBHHHHHCADDEGDFGBBGHFGBBBBHBACEHCFBEGDGGFGGFGAFGAGHFGB,True +698,8.0,6.0,6.0,10.0,3.0,3.0,10.0,9.0,CHGBHGEHGAAGHDGDAGDBDHADHBDHDAFACBCFBGEHCEFCGABGAGDCDDH,True +699,23.0,20.0,26.0,25.0,24.0,29.0,20.0,24.0,CDBFFGEGEACCACDGBDCHACHACHBGDBCFBHFHHFHHAGHAGHCHAEEGCEHEEFFCDFDDFDFAAEEFEEFBEDAEDFGDFGDHHDBCBBCEBEABADDAEDGGGCEHAGBEFBCFDHFBEFADFDCEHFEHFHADCFDAFHAFBFCEDDBCAHAACGCBFCDHBFHDAGFEGFGGCCGCBBCAHGE,False +700,29.0,20.0,21.0,24.0,24.0,23.0,13.0,26.0,EBHEBHBADGAHAAEEACGAFAAFBBFCHDBHAGCDEBDCDDAHHBCEAAFHAFCABDDEDEEDFHDFCDFBEGCFGEFAFGCHGDHFFEFHEDDEADBACACEFCBHCEHCAAEAECAEBFDAFHAHGAHGBGCBDHBDABDHBDHADFGEBABHFCFFAHFDECHHCHHCFCGDEGEE,False +701,3.0,7.0,7.0,3.0,6.0,6.0,4.0,11.0,CEFCFHGFHBHEAHECHEBBAHAEECHCDHCFFCHBGFBDDBGHBGH,False +702,9.0,6.0,16.0,15.0,12.0,8.0,10.0,9.0,FDCFDCDAHDGHFAACBCHDEHEGDEDDFDDEGCGCDBCDEAFCBCCBCGACGACHHEEHADDAEDCECFECFAGGBBEHFGHEG,False +703,6.0,1.0,3.0,5.0,2.0,9.0,6.0,6.0,DABEAHCFGGFAGFHHFCFFHDFHDCGFFGDEGDHAAA,True +704,4.0,1.0,0.0,2.0,2.0,1.0,3.0,0.0,BGGAAGEADEFDA,True +705,18.0,19.0,12.0,21.0,25.0,19.0,18.0,24.0,FDAHBFHDCHACHAEAEEBDDDDDGFHHFEHDDBDAAAFHAGGAGDABCHGCEGCFDBGCBEFHFDHFHHEGCFABHEBHCAHBBHEAEEAEGAEDEBGFCDHEEHGEFGEFBDFEGFGHFDHFBHDBGDACBAFBDFEHEECBEGBDGAEGEHBC,False +706,17.0,12.0,10.0,18.0,25.0,13.0,22.0,21.0,AGEHCDCDAEDAEBAGGHGGHDCHEHEFCEABEGBEBHAGABHABFFGGFGAFGDBGAEDAGFAHEEBFFAEFBEHCEFDEFEHDCHDCHDGAEGAHHFHEBEEGABGDHGDHBDHDHGCEDCHFCEEDDEHDGAGGE,False +707,18.0,24.0,22.0,26.0,29.0,18.0,27.0,19.0,HFHHGDEGFHCDHCEGFEGBDCEDEEFFBFCAEBBGABHADAAGABFDCGCBHABAGHDEDEEHBAHDAGDBGCBDHHDBEEGCFGCHCFHBFDEGDHDFHAEDAGDFGEFCEGGEBGCCCCECGECGCHACEGCEFCDFBDFBGBEABECBEBBGAHGDHDDAABGGBEGAEBEDFDDFEDE,False +708,20.0,10.0,10.0,16.0,13.0,13.0,19.0,23.0,FFHDFHCCACGGGHEEHDGGAGEAGHAEBAHDGHGGHBGAGFCBDCDDADDCEHADDDHBAHBAHBGGAFAAGAGGBGFHAHHDHGEHEFHCFHCBACEDBDDFCEFAHFAHEAEFHFABEDHE,False +709,5.0,8.0,2.0,9.0,7.0,8.0,16.0,8.0,CGDAGDFHDGABHDEFFBFFBEDGGAGGCEGHHGADEFDEDHEDGFBGHGGHGGBGBBAHEFB,False +710,2.0,0.0,1.0,2.0,0.0,3.0,1.0,3.0,FGHDDHAFHAFC,True +711,11.0,11.0,7.0,14.0,11.0,15.0,19.0,23.0,DHDDADGHBGFBGHHGDGAHHHGHHGBCEDCHDHDECGGFDDAGBHGBGDAHBFFBFFCHFCFFHBFHEHHGAFGAHGHDCDDAGEHGEHBFHEGBAGFAEFCEABEAEEF,False +712,22.0,16.0,19.0,9.0,22.0,12.0,19.0,16.0,HDGBAGAAGFEEFADBADHGCGCDBCABEACGHGEABEAFGHFEHFGHFGHCGEFGEFHHACDAHFCGECEABEAEEBBABHEFEAGEDGBCEHDEADCBDABCHCCHBCGAGHACEACHFCEEBAEBAGBGFCC,False +713,10.0,16.0,20.0,25.0,19.0,11.0,23.0,14.0,FDCDDBFDGCEFFEBBEBBFDBHCFAAHGDHDBFFGFDACDAEDGEGGDCADCDDGEDGEGCEGDADCGDCBBHEBDECEHCEHGBHACEGGDCGHHGHDGCGGCGCDHHDECCEBEEDABBAGBGEAGEFDHFBHCC,False +714,7.0,8.0,11.0,9.0,14.0,8.0,8.0,14.0,AADAFBHGCCGCDHHFHBCHDCHDEHEEBFBAFHDGHDHHEAFEFCEGDHBEHCCFCHBBEDEEAFEAECGECGEGDBG,False +715,4.0,5.0,2.0,4.0,4.0,2.0,5.0,7.0,BEEHHBHHCDHCGEBGDBDHEFHFAAGAAGBDG,False +716,2.0,4.0,4.0,2.0,5.0,4.0,1.0,3.0,GBACBHFFEFFDHBDHEAEECECCB,True +717,15.0,12.0,19.0,9.0,14.0,21.0,18.0,23.0,DBHAHHEFBFAGHAGHAEHFEAAGCGHBFHBAHDCHCCDAGGHGFDAFEEEGECHCCEBGDAGCAGHGFACDHBDGBAFCFFCDFCFFCEGCBGFBCHBHAGHFHCBHAFHCFGCEGCEHFEBEEFFHDFH,False +718,21.0,29.0,17.0,17.0,19.0,12.0,14.0,21.0,BHBBDDFDBFDBDHADHBCABAHFADGBECCFDBADGEHHBBEGHEDHCHEBHBHHBEEBCABFBBFBFDAFABDGCEGCEGBEACEBBBBCDCHGEDEEGGHGAFGABGABAAHAHHAHGAHGEHCDCFDCFEEDEBHCCCACAAFABE,False +719,15.0,18.0,17.0,14.0,22.0,18.0,20.0,22.0,GGECFCHFHBEHBEDBEFBEHBDHBGAGFAHFAFECFDFHGFBGDEHECDGCAEFHEFBDGHDGDBGBBGBHGCCGCCGCHHEBBBBEEAHHBFEACADDACGCFEHFEHFAGAHGEHFAAFCHDCEGCEFDEGBHGDHEECAADA,False +720,4.0,4.0,3.0,2.0,1.0,3.0,4.0,4.0,BFBBFHBCHAHDAGEAFCADCGGGH,False +721,22.0,14.0,33.0,22.0,22.0,16.0,25.0,18.0,EGACBDEEDAADHAHBABBAEGAEGBHCBADGFBCFBAACFEEFEDHBDCGECHHHAGEAFECFEGFGAFGHCGAFGEFECFGCABEEGGDAGDCCHCCHGDEGBEDBACAHDACCCBHCAHCHDGHAECDDCDHCFCDAHHCECGECGDCGFGECCCFCCDDGDDGDFGBF,False +722,15.0,12.0,9.0,7.0,14.0,11.0,9.0,13.0,HFDHFEHEGDBCFBCAAHFAEFGGDBADEAFEAHEAHFBGFHEAGEDGBBABHGEHGECCABCEHDBADCFEEFAHFGHEAHACCABCBB,False +723,25.0,27.0,19.0,19.0,29.0,24.0,29.0,27.0,CHBDGEDBEGCHBAGECBACBGCEACAGCAGEFHHHGHAGAEDHGCGBBACHDGDAGDAGBFFBGFBDFEAFBABACDEFFEAHHAEHGHHBFABFACHHHEBGBBEABEAHEDGEDBFDCHDBGGEHHEGHFCHFHAFDAFEGGHGECDFGGBGCFEAGECBECBECFEAFEBFEHFEHBDDAEDADDFCBFEBFGHG,False +724,7.0,6.0,4.0,4.0,2.0,2.0,7.0,4.0,BACDABGAGDBGHFGHFCHAEGADGBEGBAADCBHC,False +725,13.0,14.0,14.0,9.0,9.0,11.0,7.0,5.0,ADEDDFDEGBCACCABCADGAFGFGAEGAGBAFCFFHBBHCBDBFEGAEDBDFHCEECEAFBAFHCFCCDBCABCABHBBEC,False +726,6.0,1.0,2.0,1.0,0.0,2.0,3.0,0.0,ADAAGACFACFBGGA,True +727,22.0,23.0,26.0,27.0,23.0,28.0,17.0,22.0,ECCBCCADCDDGGAHBAHFHCGHEGHCAHGHHGBEFCAFBAFHDFAFCCBACDGCBGHGEAGCDECFEBEEDFDFBHGBAGBADFEDAHDACDGEFEEHGEHFAHFAEBDBBEBFEDAEDHDDCFDGDABEGDFHBCBFDFFACFAFHEFHABDCCEABEFFHCFBFFBFCBDCBDCEDGDAHDCHCE,False +728,0.0,0.0,3.0,1.0,3.0,4.0,2.0,2.0,CEHCFCGFHDFEGFE,True +729,17.0,19.0,22.0,26.0,19.0,16.0,18.0,23.0,GFHGAGFACDAEAGFDCBCCBCBBGBDGEGCEHDDADHEDBADHDEFBEDBDGBCGAHHAEAAEBDGDGGDGABBECDEFDEFHCAHBDHBHGGDFFEFDCCDACBAHEABCHEEFCEFHGFHDEBGEBHHHHCFHEAHBAHCDDDDCGFCHFCHCCFCD,False +730,10.0,12.0,10.0,12.0,5.0,3.0,7.0,9.0,GGBHAHCBEBDABDCEDEGDCGDAFAHGAHDADDACHACGECADHABCCGCBBCBBHHBFDEHDBDFB,False +731,8.0,9.0,15.0,9.0,17.0,19.0,15.0,6.0,BHGBCGBCDBCFBCBACFAFEGFECFEGFGCEGCGADEFECHEDEEFFEFFGFFGDFCEGCACBAFADCGEEGDBADFAHHDGHGFEEDCEHFFBGEC,True +732,15.0,25.0,16.0,23.0,8.0,23.0,16.0,19.0,CCGCCHDFHDFABAHDHGDBFDHDDBBDHBGHGFDDFGGHEHABDFCHFAFCACBBDDBDFBDABHABGBEDBEDAFCFBCFGEBBHCBABGABGHBGHFGCFGCFGEBEFADCHFHFFCDDCHAEHBDGADAADGFCFFBFEBH,False +733,26.0,12.0,25.0,16.0,6.0,12.0,11.0,16.0,DDEFFEHBCBCAGCHGBHAAHCAHAHHBHHGGHCFDCADCADABFCCGAFDAGHCCCACFADFADAHBGBCFFDBCHAFAAEDEBAHBAEFAFBADBDDADCCCCCCCACCGCDGADGAEAHGH,True +734,24.0,26.0,16.0,18.0,21.0,14.0,24.0,22.0,HGDGADCHDBBAEBDEBDEBEEDECFBCAGCBCHGDBGEBDEBEEBDGBGHHFCDDHGDAGHADEBDAAHBGBAHAEEGEBGEBAACFHCFACFHFAHFAHFDHCBEAHEHBCHAHAEDGFBGDBGFBHBEGDGGACEACACBACFAGGEGBFBHAGHAGCFGHF,False +735,22.0,22.0,29.0,19.0,27.0,26.0,31.0,18.0,FACFCCFCAHCGBBDADAGDFEEFAEFAHADEGDACBFCBFBHGCGGCFFBGFGFBBHHBCAADGCDECGGCGGCAGCEGEGGDDGAGHAGHFCFCEGDGCFFBDEBDFBFEEEHEHBEAEEAEEAGEFDEGDBBEHGAGFDGEDHBCHGAAAAABCECCECCHCCDFHBFCEGEDGFBFCBFHBFHDHHCGEB,False +736,3.0,2.0,3.0,3.0,1.0,1.0,2.0,0.0,DCBDCBGCAGADEAF,True +737,25.0,20.0,13.0,20.0,9.0,15.0,15.0,17.0,BBCBGDDHBCECEDCBDHGDAGDAEAACDBCDAAHFAEFDCFAFBAGAGBABHABDABFAFFDDHHHHBFHDFGGHDCFGGHHGAAEAABCAGCBGCEGABCADEBBEFBDFHGFHDFHCFHAADEBDGADABH,False +738,15.0,21.0,15.0,20.0,23.0,14.0,16.0,14.0,HBDCBCCDFDDBDABDABDFDHHBEGEFGEFGECGECGECABBEGFEGFGFBABDGBHGBHCAEBBEBEDDDBHDAFCACCEBHGGDEDAEACFBFFBGFGEEHHEHEAHADFCDCAFCDEBDCDEGEHGAHAHEABE,False +739,6.0,4.0,7.0,3.0,11.0,9.0,13.0,4.0,CEEGFEGFDGBBEFGGDEDHCCEAFEAFBAFGACCAGAFEBFEGFGCHGEHGECGHG,True +740,18.0,18.0,17.0,21.0,22.0,23.0,24.0,19.0,CHFCHDGHDGBDCFEEFEDGHDAHDAECAFGFFHFCDEGAHBDBEDHEGAEGAEFBEHAEHABBAHFGECAHBFCDFDEEDEGDACBFHDFBGFGFEEFAEFCFBCHBDFAGGAGGAGBAGBEGEGDDGCDBBDBGEFGDDGHBBECHFCHCCFAGHCFCAH,False +741,9.0,8.0,14.0,9.0,12.0,8.0,10.0,8.0,HHAGBAGCACBHFBHFDEADGBFGCDABDCEDCEFABGECCEBCDGEEEEECECCFACHAEFGGFCGFDGDACDHHBH,False +742,12.0,15.0,13.0,8.0,14.0,16.0,4.0,12.0,AFFFBFFBCEAFAAEBHDAEAHBCHFCHBDHBFHBDEBAHGFHFBEGCFHCEAFEAHABDBEDEEFECHECGECFHCFCCDCCGBDABDBBEFA,False +743,10.0,6.0,7.0,8.0,13.0,10.0,9.0,5.0,AFAAEBGEBEECEEDFCGGHDGDFCFGHFBHEHDDAADEDDECBEFBECHCGAAFFAFEAGEAGFBGC,False +744,4.0,4.0,4.0,5.0,4.0,3.0,5.0,8.0,FHDHHGAHBHDDHGDAFEACEACEGGFHBCHBCGEDB,False +745,5.0,2.0,6.0,1.0,2.0,4.0,4.0,5.0,CHHCFFGFGAAGAHGCHABEACEHCBFCD,True +746,6.0,7.0,9.0,8.0,5.0,5.0,6.0,0.0,GDGGFGCEDBEDACDCCFACFCDABDACAACBEBBCFBFEEGBDGD,False +747,23.0,21.0,27.0,20.0,27.0,21.0,28.0,26.0,DEADBCCGHHGHDBADBADBEEBFEBEBGGCAEDAHDFDGHEAHEAGEDGEFGBAGHFHECBCAEEBEGFFFHHHDHHGACGEEDCADBAFBHGBAFBDFCDCBGHFHAFCCDCGACGAFGCEGCHBBDGCHFDAFGGGBHGBHAAHCAGEDCCGCCHBCHFFHEFCEFAAGACGCEECECHEBHEGEDFEDF,False +748,3.0,5.0,1.0,5.0,3.0,2.0,3.0,3.0,DBGHEAHDADDADECFEGBGHBFBB,False +749,11.0,7.0,13.0,10.0,10.0,9.0,18.0,6.0,AGEGGFDHECGGCGBCGECBCCEFCADCGHCGEGBEBDECGGCAFHDDHGDAGDAEAEFDGADGAFCCFBAFEFDGFAGBAHBH,False +750,19.0,21.0,8.0,26.0,26.0,23.0,18.0,20.0,FEHFHBCHBCHAAHDGEABEDCECBDDAFFAFDGDHCDEGDFADCHDEDEEGHAGDFGCFGDFAEBDFBAGHAEEAEAAFAFBAFBEBBDDBDHEFHEHDEBDEFEBBAAEAEGBEDFHDHGBEGEFBHCHFBHEGGEFGEFGDFHFHGDBGDBFDBHDGA,False +751,10.0,15.0,9.0,6.0,11.0,12.0,12.0,15.0,GDEEDHHBBFGBHHBEHFHFBDCEGGEGCBCCAFCEFBECHEHEBHBAABFABFABFGFEGAEBDHCGHAGHAFCACGAHDHFDHGBBGF,False +752,16.0,16.0,21.0,19.0,22.0,24.0,24.0,17.0,HHEEFGDFCDFCDFGHFHABEGECBCGBCGBFGDFBCBAFFGCAGCAGBAGHGDHDDHGDHGEHAECADCEFFAFFDEGBAGBCEBAHFACCDCBGEHDEGAEFCEDBEHFHAEDBGAGFECFGGAGGEFHDHECHECFECFCBDCGABDBHDFEFFED,False +753,5.0,5.0,9.0,7.0,8.0,5.0,5.0,7.0,DHCDCBFEBACFGCHGCHGEDGDDEDHAGEACFACEAHEFCCFBDHBHBEE,False +754,1.0,1.0,2.0,5.0,0.0,0.0,2.0,1.0,GGBCDDCDDADH,True +755,3.0,4.0,2.0,11.0,7.0,7.0,7.0,3.0,DDGGDGFFEFFGGDECDEDFEDFBBHBGFBHDAGCADHDDEAEE,True +756,13.0,13.0,9.0,10.0,17.0,10.0,13.0,12.0,CGAEDBDFGGHCGBCFAEEAGFBFFBFFBEGEEBEEHEECDEGACGEHAFGADHABHAHHCGHFGHEHEAHGDDCAHFAEBAEDCBBCBBGBDEDDA,False +757,8.0,8.0,4.0,5.0,4.0,3.0,10.0,2.0,BDEBGHGGFDGFDAFCGGCEBBAACEDCADHABGGBGBAABGAE,True +758,26.0,19.0,23.0,17.0,12.0,22.0,20.0,22.0,DDGDEFCHCHHDHHCHGGHDBAFBFGBFEBCAFCAFHFFDCCDCEACACBFEGGHGGDFGDHCBGAFCAFEDBEAEEBDFGDAGBHBHHADGCDFCAHCHFCGFCGHCBHABDABAACHAFAAHCBHBFABFAGFDBFHBEECGAGAAGFAEDABACCEGH,False +759,4.0,1.0,4.0,4.0,4.0,6.0,8.0,4.0,GDFGAFGDGCFGCFCAHAHDFHEEHEEGDGAFGCB,False +760,2.0,2.0,0.0,1.0,4.0,1.0,5.0,1.0,ABEDBHAEGFGGEGGE,True +761,21.0,26.0,28.0,30.0,24.0,24.0,21.0,23.0,FDCHDHHDFHCCGFFAFAAGABBDGBCGBHGEHFHFBCEACEHEHBEABDBBABAGBFFBHDEEDBGFCGFCGFBBCBBDBGGGCDECDCFECFEABGCDAEHEHBEDDADFADGAEEAEFDCFHCFBCHBCHAEDDEBGEDGFHEDCBACDGFFCEGCDACABEGCDGHEECFCFHDFBDHADHADHACGDCDDHH,False +762,24.0,12.0,13.0,17.0,17.0,14.0,9.0,11.0,CEAAEBDEFDBCCBABBACBDBDDADGCGHAEHAEHBEFAEFAFCACHBHFEHADHFEFAGFGCDADDACDEDGEBGECAEBFEBEADGACFAHAACAAEADDFFGAFGCDHDHEFH,False +763,6.0,8.0,13.0,10.0,5.0,9.0,19.0,14.0,HGDFBDFGCHDCBGCEGCEGHGHHGACGFCAEEHBBGDHGCCGFAGHADHBCGDDBEAFDHFBHFDGCAGCGFFGHBGHCGHCD,False +764,27.0,23.0,30.0,22.0,19.0,28.0,33.0,17.0,AACCCCCCFBCDCCGCFBEFDGGDCGFCFFCAECBGBFCBGEHDEFGHFGHACHGFAGEAFFFCHFDGCHGDGCFGCFGCAGDBFFBECEGCGGBGHBDAEDABFABFDBDDBDAADGHHFBAECEBHAHHEFADFADFACAACGECEEAGEABADBDHEGEDGEDBFAHGAHGAGCDFBAGBGFFDCHBHEACGGBGB,False +765,18.0,15.0,16.0,11.0,14.0,19.0,16.0,15.0,CEFGFFADDDDCFAFGAFEEEAEHBEHCECAEBAECABHACHFCFGBGGBDABCFFFGFHGHGDEDABBABBAHFACGDFGDFGCBEEDFHACHGCHGBHFEGFAACECDGCHGBHCBHBAHAF,False +766,2.0,0.0,3.0,2.0,3.0,1.0,2.0,7.0,HHEHHCCHDGHDFCEHAEGA,True +767,17.0,7.0,6.0,11.0,18.0,9.0,7.0,8.0,HEEBEFBEBEEGHEFCEACFABFHBGEAEAACAADAADADDAFABDAGDEDAGDEDHCHFABEGDEFDEAEECEGHHHFGFAC,False +768,7.0,8.0,17.0,12.0,13.0,9.0,9.0,18.0,EBDDBCDHEEEGCEFDAFDABCBBHFGHGGHDCHFEHFAHAEHCFHCAHEHBEGECHEGDECCCCDCBHCGHCBFGECACHAFHDCDDHFDHG,False +769,20.0,21.0,9.0,15.0,21.0,8.0,21.0,20.0,HEDAEDGBFGHEDHEDHEBCGAEAAFAABHDHAEHGGGBEFDFFAAEAEHCHBCHACDBFGBGABHBBEBBAHBHHDABDAGDHEFEGBGGDCGEBGCHECHECHGBEDBEDBAAFGADBAGAHGBGDCGEEGEH,False +770,21.0,9.0,20.0,15.0,18.0,14.0,11.0,20.0,AGHAHEGHACBCDEHDEHEECGABBADBFCHFEABCBDEAGEAFEAFECFDCHDBDFADCAGCADCHDEADAAHFABFEDCEGCHFHHCEACGDDGHFGAFGAHHHECAEHDHHABCEFCHFCGCCEF,False +771,4.0,4.0,4.0,6.0,5.0,8.0,8.0,13.0,HGCHGCEBAEDFEDHAHHGEHDDBGDEGBHGFHGFCFFCHADFFBHGAHFHH,True +772,4.0,7.0,15.0,14.0,7.0,5.0,7.0,12.0,FCECCEHCHDDHEFHDDAEHECCGDDBDDBEDBFCGHHHBHHBCABCHBCDEDGCHFDACDFCDGCGGAGC,True +773,15.0,15.0,19.0,12.0,10.0,13.0,9.0,11.0,CDFCAAHAADAADBHCGEAHFBGCBCCEGCDCCDEAGHAGECHFHFFBFBHFBADCADEHBECBABBHFECAGCDDCFFFHDFHDFAEGAEGBCCBCEDGBBCB,False +774,17.0,15.0,18.0,13.0,14.0,14.0,9.0,11.0,BDADABGFCGHCGAGHAGFFDCCBAGFHDFHCFHCBACEACBAGBACBECFEBGABFBFFBHHBDEEDEAHEAGFDEFAFFBDHBECCCCDCEACEHCEAADDCBAEDDEH,False +775,12.0,10.0,12.0,10.0,14.0,18.0,9.0,17.0,FFDFGDFEBAEBHFHFFBFCBFCBACEGDDCHCHDGBEEAEHAEBACCCCCAHEAFFFFFHGBHDAADAHEFHGFHEDCAHHADHGFGCHGFEEHDEHBEGB,False +776,15.0,9.0,14.0,7.0,14.0,8.0,10.0,14.0,FGGCGFEGFEGEBBABCCDCHEHHCHGFDGAEHCEFCEGCAACEACADHABADBFDCEDAABEACDGCHHCHAFAGHEHBEFEAHBAHBEH,False +777,3.0,5.0,7.0,4.0,6.0,7.0,4.0,2.0,ACHDGDFECAEGAFGEBDFBCFCCFHCEECDBGFBEFB,False +778,13.0,16.0,17.0,23.0,18.0,12.0,11.0,15.0,HGEDGCCFHBDHDDECFEHAEBAEBHDCCDFCDCHGHFGHAABCAFCGHCGCEFFEBAEBABBEHBGHBFFDDGDAEDAEABBHBBHEDFEFCDCEDCEDHHCGDDDDDAGFEBBCDDADCAEEG,False +779,0.0,0.0,2.0,3.0,0.0,5.0,2.0,1.0,DCFGFFCDFHDFG,True +780,4.0,14.0,9.0,15.0,13.0,16.0,18.0,13.0,GFHBCDDGGEFBDFGDFEDHCBBGEFEAFEHBDHGFFECCDHGHCGBBGBEDHDDEDEEDBCFHGDHGFHGFHGFGGFGBFGAFHCDCAECAEBBEDBGFBH,False +781,14.0,11.0,9.0,17.0,16.0,19.0,16.0,13.0,AHAEEAEBDCFCAFEACDFGBGHHFBHDBFDCHDHHEHFDGFAFEABDGEEEFHFABFCGFGGBCHBEGBHACEADGACGCFGBFGAFDAGBAGFDHEDEEDEFDEFDGHDGDDF,False +782,17.0,30.0,15.0,20.0,20.0,24.0,22.0,25.0,GBEGHHGHFDDAEABGCBGDDCCHFEBFGBGDBGDBGCAAFGAFDEFGEFEFAEFACBGEBAEBHBBHBCHEHHEAHDDCBCFDADDHDGHFEHBHFBDBDHAFHFFHGGAFCFGCHEEHEDFAGBCHBFGBCGDCGBHBBCFBDBDEBFEFHHCBHGBEBAEBHEFAAFDAG,False +783,18.0,12.0,19.0,16.0,8.0,23.0,23.0,21.0,CAEAGEACHFBBCABCACFADGBFCCFGDFGFBGHEGHCCHABHGBHFBGEAGCCFDAFDCHBGHCGHDFEGEHGEHFDHBDFAHFAHCGGCGDBFAGFHHFHGFDDHGHFDAGBHFHEDDDDCCGCCGADFAFGAFAAF,False +784,26.0,24.0,29.0,15.0,21.0,16.0,22.0,14.0,GEEGAEGABFAFGEBBHCCCGGBHGBFDAADAAGAFGBEBBCCGCAAHAAHDBEEBGEDADDADDAECAECBEBHEFFADBCGECGCCDCGACBACFDCFHFDHGHBBHDBCECEGCBGEBCEFAECCCHFGECGCBACBFFBGFHCECAFBAHBHHAFDAGDECAG,False +785,1.0,0.0,2.0,2.0,2.0,6.0,1.0,1.0,FFFEFFEDFCDCGAH,True +786,20.0,28.0,18.0,25.0,30.0,17.0,20.0,19.0,ECEDCEBGECGBDDAGEBEEHHADHDECGEDEEFEADEAFEAGDBDFCEFBDHBHAGAAGCAGCHHCHDBDFFEECADBAGFCBBEBDEHHEBHFAHFBCEBFEGEHADBDHBDHCDBGDBHDCGBFEADEADHAEAGBBCBACEACFDCBDHBDGEGGEBGEFGBFCBGHFGFFAB,False +787,5.0,3.0,2.0,6.0,9.0,8.0,2.0,4.0,DAEDAECHGCHBEFFEFEDFEDADHEDAEFBFABFHFEG,True +788,5.0,9.0,7.0,1.0,4.0,3.0,1.0,5.0,EBABAACHBEHFACBBFBBEABCDECHGCHBCHFC,True +789,12.0,4.0,13.0,8.0,13.0,16.0,10.0,11.0,ADAAEBAEGDFGHFGEBGADFAFFAFFEFCECEEFEGFEDFCCECHHAFDCFGHEHBBFAGFGHACECGHCDCCHCCHDFHDGAAEH,False +790,6.0,10.0,8.0,9.0,9.0,8.0,9.0,13.0,CEAHHCFHCFHBEACFACDBGDBEHBGGCGGAFDHFCHFEHBABBHDHGDEAHGBEBEGBEDHEDGCDFHDF,False +791,8.0,14.0,12.0,15.0,11.0,8.0,8.0,8.0,EBHEBDCADCAGCABCGDEADEAEECBEDADFEHECHDBHGEGCFDCFBBBHBBDGHDFFDFFGBGHBACBFCHGCDCDDEBDA,False +792,10.0,22.0,18.0,14.0,21.0,20.0,16.0,23.0,DBGEHGFDGFECFHGFEGFBAECAHFHECBABHGFACEBDGBCGHCECAEGBBCDBEGEEGHEAAECGBFHBFHAFHCFBCDHCDHDBHEAEEBHHBCCBFHBCCBHCEDDEDDEFFHHFHFFHEFDAGBFEBHCBHDBFDGGG,False +793,23.0,21.0,27.0,21.0,31.0,27.0,29.0,18.0,AGFCEBGEFGHCGECBEFEGFCBFDBFHCCHCBEDDAGFBDCCDCCDEGHEGHAFHGGHDGDBADBAGEAEAGFFCDACFACFGCFGHFHEFHEDECBEBHFGDEGCEGDBAFCCFACEEBDDHCECDEADFGBBEABHACFAEFAEHAEHEGBFCAHGEFDEAAHACGDBEFBDBBCBCEHGEFGFGGFAGDAGEG,False +794,24.0,20.0,28.0,18.0,24.0,31.0,23.0,26.0,HHAHBAHDAHGAHECHECDEHEEGEFCECEFDEDDFCDFCHBBHBHFCGGEHCAHCDGAGADGCHGHFGEEGAEBABBAEFDGDHFFEGCBFBGHBGABDBCAGCEFEBFCFAAAGAGBABCAEAAFFBFFBEBDDFFCFFHFFECFHDFGCCACFAFHCFECECCFGHFGBAGBCDHHHCCHDCEDAEDGHFG,False +795,31.0,20.0,15.0,24.0,20.0,24.0,18.0,24.0,DDFDGFDGAGEBGEBGFHEDHBDBGHCFHBDCEACAGHADHGHFGBFHCDHDHEEHGGDGGEGDFGAEAEECGFCBFABFADAADAHGCFFHBFBAFDAFDBEBAAHAAHAAHAAFABCABEBEFDHDHEFHEDABHCDDDHBHCCGDHAECAEBEHAFBACEADFBFFEAFCAFC,False +796,6.0,5.0,4.0,8.0,8.0,11.0,14.0,10.0,AGGGDBHDBEDHHCHFAGFGEECFFAFFAEDAEFEGDBGHHFHDFGCGHAGHGGHGEBCEBDFGDF,False +797,13.0,13.0,14.0,16.0,20.0,20.0,14.0,14.0,FDCFDCDGCDGAFFFFHFBDGAEEFDHFGHGBFDAFHGFHGDEDDEADCHGBHGBACAHBECACHEEEEBBDFCEBBEBFEHAGCEBAEFCEFAGFAHFGHFGCFECADCGEADEHDEBDECHB,False +798,16.0,22.0,7.0,24.0,22.0,17.0,26.0,9.0,EFHFGCFGEDGFBGFBHACDACDAGBBGECEBBBDDADDADHGGGBGGBFEEDEFDEAGEAGEAFEDDBDGCDBBBGHGDHCDBDDEGEAFEADEABABBHFBFDBFDFEEFADGADECHBGEGFFGBBHEGGFDGAGAHGEE,False +799,20.0,13.0,23.0,31.0,20.0,22.0,27.0,27.0,ACCDDCDDCHDEGDBGEBHAHGDDDCDAHDGFAGHAEBFECFBCDECBAHEACGAEGFEFFGHADDGDDACEACECCFFFDFGHBHDBHDCFGCGACFCDHCBHEFDBDGCDCDEFDEFAGHAFHAHHCEGGDBGFEGHEHHAGFEBFGAHCBHCAHDADFGDEHDHHAGHFEHGEGGDGGBF,False +800,7.0,7.0,4.0,8.0,5.0,4.0,9.0,2.0,BFADCAGBDGDDGDDAEDEFBEABEBECGDGHAGHAGFGBABCGFC,True +801,27.0,24.0,11.0,26.0,22.0,20.0,24.0,21.0,FDEFHBBHDBDFECFEGGEGBBBFGBAGBGFBAEHFGHCAACHBBHBDHEABEFBAFGEDECDEGFGGHDGAGGAHCBHEEEFHEDHADFDHGEGFAAACDFDDFBDCEAHEBHEAAEFBDABAABHABDAGDADFAHFGHFGHCGDFGEBCDBDAGDBGHAHDADAGECDACDE,False +802,24.0,16.0,21.0,28.0,24.0,24.0,17.0,24.0,EHGDHECEADBDCGFCGDCFDEFDHFEEBHECAGBDHDDAAAAGEHGCCGBEGCEGEFDEBDAAGEFCAFABFBEAGEAFECCDDCDDHDHFDEFGAACEEEHGHHADHFHADHFCCAHGACGAHECBEBBDFBCFBHADDAGDCDFAHFAHFABFEBFECFHDBHDBHDGHFHFCDF,False +803,20.0,21.0,21.0,27.0,21.0,19.0,21.0,15.0,CHCDAADHHDHFEEFGGDBGABGCBCFAHFHFFGBDEBFEAFEHBEFDEFDAHCGGCDFCGCGECGEAGDBCEBGAADFADFCDAEDBDAHAEHAEGGEGAHGADFCHCCHBDBBGEADDADDBFDBCBBCBEGDDCEEAGDCGDFDEGBEBBFBAHCEHCFCFD,False +804,1.0,2.0,0.0,1.0,3.0,0.0,1.0,2.0,HBEHBEDEAG,True +805,17.0,17.0,12.0,11.0,12.0,11.0,11.0,14.0,CACCACHGBBBBABBDBGEGCAGFBEFAEBAECGBHHHHHHHFDEFGCGGBBBAFFAFFACAACGACDDEFEEDEADHAHCBHDGHABHEBGCFAHBEDDDFEDA,False +806,8.0,5.0,13.0,9.0,8.0,4.0,5.0,7.0,AABDACCACDACDBCBEEHEHCDHEDGEDADGFFCCBCGBEHCHHDGHECCFDCFAEGA,False +807,2.0,3.0,6.0,1.0,2.0,2.0,5.0,2.0,CCGFCGCAGEGGHBBHBDCFECA,True +808,8.0,11.0,13.0,11.0,20.0,5.0,10.0,7.0,EDGEBEBGEBGECCCADEEEBCEGEDBECBCCDAEDHECHAGHGCDDFDBFEBFEBEEGEFHAAGABGDFHDCHACBEDGECAHC,False +809,19.0,18.0,17.0,18.0,21.0,24.0,23.0,21.0,GGGGAGFDDEHDEHAEFAGHHHHCBECAGCEGEBGABGFBDCHDBHEHHGHFAHGCBGFDCFDCFBEFHHDAGFFGCEEDHGDCADAAHEEDEBHHFAFFABFACCBCABHGCGDBEDFEGFCGFBFBBCBBDFEGFECFAHDAEDAEAEEDCBGGFFFHA,False +810,20.0,16.0,11.0,12.0,13.0,19.0,22.0,18.0,AGFCHFDDFBEHGEHGBHGDCGFCHEGAGADFAGGAHAFBABBFBBGGAABAAEADEBDGCHHEBGCAEAHEGCAGFHDFHFEHAGDGFDBFBBFADCGDBGHFGHCCCGCDGBBAAFFAFHHFEHFEHEE,False +811,17.0,22.0,15.0,31.0,25.0,25.0,18.0,24.0,HAFEGGECCHDGGGHDGCDGDEAAEHGEFGBGGHGBEFEEBCHAEHCFHDFHDFGDGDBGDAFBFFBFHEECEDBEDHDBEDBFDBFABDEFCHAEFEDHCDAFDCBDABDABFCBCDHEHFCAFCDBEDACDEHFFHFFEEEBDEHEBHBHHAHGBHDHGDBCABDADDFDAFGAF,False +812,13.0,7.0,5.0,13.0,10.0,18.0,4.0,11.0,FGEADHABHAEHFCHFAAEEAFEAFDAFABEGGHFFBBDBHCAHADHBFADCCHEDFGDFDDBDFEDFEHFDAFDFFEHFC,True +813,30.0,25.0,17.0,27.0,18.0,16.0,23.0,20.0,DGAGBDGFDGFAAACAGCEFHDAHDBHCBACFACFGHFEFBHHBDHBAEDAHCEFDGCAADABGABDEGDGCAGCEGBABEABDFGDFADFABGBHGAFGDDGHDAHDCDDEDGECHEHGFBBFHBEBBCBDGGHHCEHBEGBCGADAADBHEFDEFHEAADCCHEDECAAABABB,False +814,24.0,14.0,14.0,18.0,16.0,18.0,16.0,21.0,ACBABDDGDGCCHAEHAEFDEFGHFGHFGDCGEBFDBGGBFACACFAGEHGBAFBAEAAEFHEGHCAEAADDHCABFHHEDHDHACHAGHACHGCHCHDDHABAAFADDBBABFHCFGCFEDDEDDHFEHFEGFBGEAFEB,False +815,13.0,9.0,13.0,16.0,13.0,6.0,10.0,11.0,EBHEDEGACDDCDGCDACHFCECCHGBHGBHCBEDAEDHFAFEAHEADAAEADDFFEGBDGEHHABGGHGCCADCDDCDHCABEFBEDBAG,False +816,3.0,7.0,5.0,5.0,0.0,0.0,5.0,2.0,DDCDBADBHGBGBBGCCCACBAGBDGH,True +817,5.0,5.0,2.0,2.0,3.0,8.0,12.0,6.0,HCHGCGFHGAEAFGHFGHFGFEADEHDFBGGGGGGFBFABABB,True +818,1.0,11.0,9.0,4.0,7.0,7.0,8.0,7.0,GABGHBHDBHCBECBFGHFGBCBBFEBECCEFCDFCGHCFCDHEFGEGBEBHDG,False +819,2.0,2.0,5.0,5.0,0.0,2.0,1.0,5.0,CDACFHHFAHDBHCCDCHDBGD,True +820,11.0,24.0,12.0,20.0,8.0,10.0,7.0,16.0,DDBDDECFEFFEBFBBABHAFHGGCCADEHHABDDDDCGHFABFABFHDCBDBGDBCDBFEHHCBHADHADBADCHDCBDHBEHBHABCGBEGBCDCGHBDAEFBBBH,False +821,9.0,5.0,8.0,7.0,7.0,2.0,8.0,6.0,DCDGGAGGCHGCHBBEEAGEGEFCEDADAADAAFCABCEHCBHBEHCAHDDG,False +822,4.0,6.0,4.0,6.0,8.0,10.0,6.0,8.0,DGEHGBHAFDDFEAHBFCBFCDFADFCDHGEHGBFCBHEHGEBEEHEFGFFA,False +823,11.0,21.0,15.0,29.0,14.0,28.0,25.0,13.0,GCBACBGFGGFADDGDDHCCBEGFEGBDBBDFFEFECFBCFBFFGFFGDDHHDFHEFDEDDAFAGFDEBEBBDDHDEHGCHFCGCAGCFGDGGHCFBBFBDCGGEGDEBAHFDEADEADFCDGABFDDFGDCGBFADABDGBHGHGFHFDHFEBCB,False +824,9.0,9.0,18.0,17.0,22.0,11.0,12.0,16.0,HDHHDBHCFHEEAEBDEDAEDBEDBHHAFFDDFCHGCHECDDCEEEFEDGADGCDCCHCAHCAHCEHGECGEGGHFDCCEECACBGCEGFGDEBAFFAGCGBEEEFDEFDBHBH,False +825,13.0,14.0,23.0,11.0,13.0,29.0,17.0,16.0,CFBCFDDFBDFBHFHGFAGEAFFBHFCCFCFACFACFDCAEBHFGGBAGDEEHBGFAGFHEDHGFEBFHHFGFDCFCBHEEGGCFGEFBCADHHDBFDBHDHACHCCGCEGAGGFFACCAECFHCGBCEFCEFCAB,False +826,5.0,8.0,5.0,6.0,10.0,4.0,3.0,7.0,DDEDAGAAGAHCDDBBHBGEEFHECEFHEBHEFHECEECBBCHBDFBA,False +827,20.0,17.0,26.0,28.0,18.0,27.0,26.0,26.0,ECFEGFEHFHHFABFABFEHABHAGDBHDBHDBGDGCDGHABHAFCEHDBHGCDCEFEEADECDAFBGFEGFBAAGDGDDEEDHDABDABFAGFDGDDADCBDAHGHHGHHFFFFFGCDEDGGCBCFEDGCCGCCDCEFFHHAHDBHAFCCFDGBCCHACHDEGGEGCCDCCHCBGFAAFEGFGCHHF,False +828,10.0,8.0,14.0,9.0,25.0,17.0,21.0,17.0,ECHGCHBCGEFDEFDECDEGBECBHBHHFFGGFGGHDGHACCAHHBDCFGAFGAGEEHEAHECEEHEEBEEGDECFEBFECFHFFGGGAEGHEGFCFBAGAHEEGDAAHFHCFGEEDFGDC,False +829,3.0,3.0,1.0,2.0,3.0,6.0,4.0,4.0,DHEHHDFHGGBAGAFEACEGFBFFBF,False +830,13.0,14.0,5.0,14.0,12.0,16.0,14.0,22.0,GDABFFCGFEHEGFFBHCBHEDHFGFBBFEDEHDHHGFHAEHAEHCEHABHADGEDGAFGHBCHAGHADHEFHFFGFGBAABAABDGBDCHDGBEAFHHDDBDHBFHDEG,False +831,30.0,21.0,25.0,25.0,16.0,20.0,17.0,32.0,ABDAGCAGBEEEEFEEFGBFGACGBHGBHCAACAACGCHGHADHACEECHDHACHFEGEAGDAHDAHDGBBHBFHGCHEHHAFGFFDDBGHHDHDEHABBACBHCADFDDHBDHBDCDCBDAHFFHDDBFHAGCDBFFEECCECCGHAHCAHBEHDACDAHDFCDAHDBBFFBAFCFFCAHAAGAC,False +832,25.0,27.0,23.0,20.0,26.0,20.0,20.0,27.0,AADBAGBCFACEEGDFBFFBFHCGDBHEFHCFBFBEEBHCCHCHBEBGABDAHDFHDHHFEHGECGFCBHDFHABBDDBDFHDGCGCCGCDGCHBHEEDEHDHBDEEHEGHBBHFBHFBGCEGEDAEGAECCEAAEACBAHDEBAEBFGACGAFAHDABAHDGCDEAHEAFECFGAACBACHAGBFGE,False +833,25.0,13.0,14.0,24.0,17.0,12.0,19.0,18.0,AEBDEBFCFGAEEHEAHBAHDCFDHFBFAGFAGAEGCCDCAAGAHEHHGAHEACFDEGDCFBAGGABGADGCDGFEBFEAAAGAAECBGDFCDBEDHEBCDDHDDHDGHDHHGCHGEBGHCAHDEEDCDDBADAAGABHDDF,False +834,15.0,10.0,18.0,19.0,15.0,14.0,14.0,17.0,GFDGHHGDHFHCFDBEBGADGACECCHHCHFAHCEHCHHDEHAEBADDGDBGDEEDECDFCAFEEFEDDHDCGAHBAGBDEADGHEFDFABCEBFGBCABCFGCFACGDHDEHACACCAFGF,False +835,20.0,10.0,18.0,14.0,16.0,28.0,23.0,12.0,CBFFGFCHEDBFHGFEGFEGFEDCEDAEHAGGGGFGGCCCDGCFGCFHAFBAFBDFCFFHAAGCEGAEGHEGDFAFFCDFADECHEAHGFGEHGEBDDBABFABABECHCFGCDDFFGFAACAAEDHGGHECDBAFCAFAF,False +836,30.0,20.0,19.0,16.0,19.0,13.0,25.0,21.0,GEHGEGBFGFCGFAGHHGFGGFDHAAHECBAGGAGHCGBCABFHBECAAHAFCEBCEACEADDADCGHBDHGFEDBCAEGAHGHCGHCGEBBHGDHEDHDFBEBBFADEAHEACBAEGFDCAABAABAABGAEACHBHDGADHAEBACHDGDAGCEDCEFCBF,False +837,11.0,6.0,11.0,21.0,12.0,11.0,14.0,20.0,CCGFFHDFDCHECHGCEGCGGDDGABGAEHDEHGGHGHDDHDABDHBHFFGEFHDAEDFEDFGFAHHHCFHAEDGEHCHFDADDGDBADAHDAHDCDCCBEHBEAE,False +838,2.0,11.0,5.0,5.0,5.0,11.0,2.0,7.0,HHAFDBFCBFHBFCBHCFEBHEBCFBFEBEHBDDDEDCABBFFGFFGH,True +839,10.0,18.0,12.0,15.0,22.0,22.0,14.0,20.0,GHGGHDGHEHCFHBHHGHGFDFFBHGBDFBCFBFEBAHAACAEBAFCEFHEABGAHCBCCADAEHFDHFEFFEHFEHCECGHFEBFGCFDBBDBDDCEDEEDEEFBFFGDBBEBGEAEHFDCEGEEDHGDHBF,False +840,6.0,5.0,3.0,4.0,8.0,4.0,5.0,6.0,HFAHFAGABEEHFEBBEABCGBGAFGAECDEDHEHHEDGDC,False +841,22.0,25.0,12.0,20.0,30.0,18.0,24.0,19.0,CFDABGGBGGDGGBGDBGDFEHGEHAEDEEDEEAEGABBABHABFEGAAAAFAAGHFEEEAHFBBFBDHEHAGHADHFDHEDHEDCFAHFEHGEHEEHCBBDBBGBGEBCEBFEHDCFAGFECABGDHEFFEBEACCHEGEGCAFDACECDGDBHEFCGFGGBBBDBDDA,False +842,26.0,32.0,18.0,28.0,33.0,16.0,26.0,21.0,BDFEACGAHGEHBEFBDDCDDEBGFBAHCGBBGCEDEHBAFGGFBDFDABCCBFCBHEBEAFGAEGFEGEDGAABBHBDCAAEAEEBEBGDGGDGHDHHCACBEGGDHADHGEFEBDEBDHBDHBEHBHDDCDFCDCGAGGEGGEGFECAEABEAHDAHCFFCDHAAHAACAABFEEEBDEBDGBDBCEEHDBGEBEAHF,False +843,17.0,15.0,21.0,18.0,10.0,19.0,19.0,11.0,GCGCCGCDBAAFCFFCGCCFCBGCBHBGADGFEEEBEDCFDCFBEFAEGDDDDDAGACDEFDBFGCFGEFDDHCGGGGGAFACHACHACGADGHHCHBFAAFDFFDABBEBFHBHEBHCAHBADGABFDC,False +844,28.0,20.0,25.0,32.0,29.0,10.0,34.0,16.0,GCBGCEAHBHHGHCGADBHDGAFGCFEEFDEAABAAFACGACHAGEEEEEBDBDDGEAEBGCFGAFGCGACGAGFEDAGDAGDBGDFEBECDGBDHBDBBDAEHADAAHGDCGDEBAHBEDCGBEGHEDHCCEDDEDCEGCDHDACAABADGEEFCEFGGAHGCCGCBECECBDHDCADAGDGGDGGDECHEBD,False +845,9.0,18.0,18.0,15.0,16.0,16.0,18.0,30.0,FHHFCHBCEBFEBFBHCGHEGFEDEHABHBHCEHCGGEGGCGGDGHDFHBFHAGACEDBBBBBFHEDHAHHBHEGHEHFDHEBHDDHCDCDHCACADBHDAAEGHFCCECCFHHBHGDHCDHFDGFBGFGGECAFBFCEG,False +846,25.0,21.0,20.0,25.0,14.0,20.0,19.0,27.0,DHHAHHGHBEBFFBHACHBCHFEAFHAGEAGEDFFDHACGDCGEBDDBGEAFAAGAAHAAFCFDCAEFBEGHGDCFAEDABDABHGBHGFHFDGDDGDDHFBABCADDACHBCHCGECACDBCGBCFHEHCCBBHHHFHFBHECEDHDAHDFDDFBBFDBEGACGACGADG,False +847,19.0,22.0,26.0,32.0,24.0,20.0,17.0,30.0,FFFFFBEBBCDDHBEHDHHFHCDHCDBCDAFBHDGHDECDEDGEDCBFEFEHAHHAEDBDGHDCHECDEFHHADHCHBCHCDDCHBBHBEECCDFEDFDBGDBDFBEBAEFAHAGFECCACDHCEHCGGCGGCAGABCAGAGCDBADGEDFEGAEGAEHACHCBHABDBEDEDDHADGGFBFFHEFHCAH,False +848,9.0,6.0,11.0,10.0,14.0,15.0,7.0,8.0,EBECBHGDFECFDGFDHFDCEAAGDEFDEFDFFHCAHGBDDHDHFEGEGBAFCEFCAFCACCACBAFHFEHEEFEGAEBC,False +849,4.0,12.0,3.0,4.0,4.0,6.0,9.0,4.0,BADBFBBDBCDAGGEGGAHFBHFECBBGGCGGBBGBDFFHFEHAEB,True +850,11.0,16.0,15.0,13.0,9.0,18.0,8.0,14.0,AHEFHEDHAHCBEFAEABEBBDHGAGCECCECCEDGADFFBFFBFFACACDFCDECHHFDFFHFFGFBAHBCDBGDBGHHGHFBDBHDBCCFHDACABDGBCBF,False +851,14.0,6.0,9.0,8.0,8.0,11.0,8.0,4.0,CADAAFAFGGBDGBECHEGAEGCEGHEAFCGCCAFCAFDBEHBAAAFAFFECEDADGACFBDFHDFBD,False +852,13.0,17.0,14.0,11.0,14.0,23.0,28.0,19.0,AHFBHFEDBHCBHGDHDDBEFGAFBEDCEDCGGCAGCHGCHGCDCEEGFBBFHCGHAGDCFEGABFCBECBAFBAFHHGHEBCFAEGGEGAFBFGGGDGBDBFAEEBGAGHAFHCFHFFAGFHGFHFFHGGBGGHDGFE,False +853,17.0,14.0,15.0,18.0,12.0,25.0,14.0,18.0,FEEDCEDAEDABFABGHCGEGBAFBAFADFDDFBDFGDGEEAEHDGHCFHCHGBHFHFACAEBGHHGHAGAAFFDCCDHCGGCFDCFHCGECADCFDBFEBFBDGHDCHCHDAFFFHFBBEAFADFHBFHFAB,False +854,4.0,8.0,7.0,9.0,7.0,13.0,4.0,5.0,HAHBAEBCEFDHFGBFDDFDDFCGFBBCBFCFFCAFEDFBCGCDGEHEEDFDHFEBA,False +855,8.0,9.0,7.0,8.0,14.0,11.0,8.0,11.0,FCGGHEGHCAHEGDGCDHEBHEGEEFAEFCEAAFAHDEHFEHBGFBFFBFEAHEADCBBCBBCEGDDHFDFBHEAD,False +856,15.0,19.0,19.0,21.0,20.0,23.0,9.0,21.0,EHCABCEDCEDCHDBADEFFEAHGADFHBFEBFEHFEGCHGBBFBDFDCFHCFCGHCDHEHADFFEFHCGHCBABEEBEFBCDBCEHDACDBBDCBACBAEBDDCADFAEFEEHDGHDEEFBFFDHGHFGAFAHFCGFHBHDADAHC,False +857,8.0,14.0,12.0,26.0,12.0,12.0,24.0,18.0,DDGDGFHGDEEDEHGEDDCHGCAGDGBBHHAHDBHDBGACHCCHFCHGGHDGHDBFABCHGHGFDCEAGEADEGDADEGHBCFBGFGDCGBFDFFDCBDCGDGBEGBFGEHHEFHDFGDAEDBDDB,False +858,3.0,12.0,7.0,10.0,7.0,11.0,5.0,6.0,EHBFDFFCEGCEBFAFCCFECFHDGCEHAEFDBFDBAHBGHBGEBCDFDDFBDBDGBHBBD,False +859,15.0,8.0,5.0,5.0,11.0,6.0,8.0,9.0,AFHEGGEGBEDBACAADADGGHGFEGCEHCDAFECBBABHHEHAECFHBAHGABDEBAEFAEFAHAA,False +860,24.0,23.0,16.0,29.0,25.0,13.0,28.0,31.0,ABDBGHHDBEAACAHBDDDDHHGAHBDHDAHCGHCAEGFECFECGHAGBBDBDDBDGBDBAEBACDAHDBGDBCEBGEDDEBDBBABGGGGGEHAEGGGDFHDAHAHFAFDCHDCHEFBEAGECHFCHGGEGGAGFDHADEGHAFHBGHEFBCAGCAEBHEDHEDEEDFEGFHCEHDHHFCHEAGECHA,False +861,19.0,16.0,16.0,18.0,22.0,19.0,15.0,18.0,HBDHADGAFFFCFDCFDHFAEEDEEABBABHHEAEDAHDEHCGFEECHECEFGHFDHFEEGCBDFDGHDGHDCBDCAECAHBACGEFBFFAFBAFBEDHDAHBBDGEGCEGBGDFGAFGAHCHGFECAEGABAHBACBECECD,False +862,23.0,28.0,34.0,23.0,21.0,19.0,19.0,23.0,AADEFDECBCFBFEGCHHCBCAHCAEDAEDFGBAHBGBBGEDGEFBAFBABEABFAHFAHADGBHAAHAAHCFCAECBEHBACDDCDCHDHHDAHDAHCFBCDHCBBGDEDEHFBCCCCCDGEDEEBCBHCDEBEHBCGCDECGCCGBCGBCFAGGACBHBFCAGCFBDHBFHFECFGHEGCEFDDFGDG,False +863,11.0,5.0,11.0,10.0,13.0,17.0,9.0,9.0,HGFAGHEGFFAEFGCHCCHCFACEAFEAFBFFBEEDDDGGDFEBHDFEDFEFCEHCDAAFBAFHCFECHEDDABDAGCCGAHGEF,False +864,8.0,4.0,8.0,5.0,6.0,11.0,2.0,13.0,CGDDADAFHFEHACHFFHAFHAGABEFBHHCHFCFBEHCEHDEFDCFEFHCAHCAHB,True +865,6.0,7.0,13.0,8.0,5.0,5.0,10.0,8.0,EBBEADDABHGBFBHDAHDFCCCCCGDCGACEFCEGCGGCDHHBGHCGCGBFDDFEAHCAHG,False +866,13.0,18.0,13.0,24.0,13.0,21.0,16.0,22.0,CECHEHGAHDBHAACGDDGDDGBGFBACBAFGCFGEBHHBHBBFBBFGDFEBHDBAEEAGEHFEDGEDFFHFADDADFHCHEADCFDBEDCDDFFBFFHFGEFGHCDFBHADHFDHFHCGCAGDACEBDHBDGDHGCHBH,False +867,3.0,4.0,1.0,1.0,0.0,0.0,2.0,1.0,BGHBGBAABACD,True +868,12.0,15.0,8.0,11.0,24.0,11.0,16.0,16.0,GBGAFGAHEABDAHEEHEGHFBEGHCHHCBDFECAADDGHFHFGEAGEBCDGEDBEFEEFGDGGAHGDHEEHBEHGEAGECGEAHECHBBEFBHBBDBBDCBFEFEEFECAAD,False +869,14.0,6.0,19.0,11.0,20.0,15.0,11.0,18.0,AFHAEHAEHGFHACHADFFGGFEGFEGDEDBAFBDECHHGHCCDBCFECHCHFBEDEECHACDGFDCHCEHFHCFACEACEACBCGBGEADECEEGFEHFACEDHEDHAGHFCA,False +870,7.0,10.0,10.0,16.0,6.0,4.0,11.0,16.0,HCBDCBHCBACDCCDHFHAGHCCDECGEDGDAFHGHGBDDFADHGDHBDHBGHFHEAABGBDHEDHEHHEGDDGADGCBB,False +871,6.0,1.0,1.0,3.0,2.0,4.0,9.0,6.0,AHCGEDGAHEAHAFGAGGBHGAHGFGDFGFHD,True +872,3.0,5.0,3.0,3.0,6.0,1.0,1.0,2.0,BBBDCBEGHEFHDBADAECAECEE,True +873,2.0,1.0,1.0,2.0,5.0,1.0,2.0,3.0,HEGAEHAEBCFDEHDEG,True +874,7.0,21.0,14.0,14.0,9.0,12.0,13.0,10.0,FDBFBBDBADBHBAGDHHCGEFDEBGEGGFGBCGEADAGGADHBDFCDECGBCEDFHFGHFEAFGHEDCEDCBFCBCCBHBBHBBDCBFGBCBHDBCAFC,False +875,6.0,6.0,10.0,12.0,5.0,8.0,13.0,6.0,GCGGCGGHBFDDADDBDFBDGCFGAEGAFBBCBHHFDHADHAGCDGEDEFGGCECCHDCEACGDFF,False +876,19.0,14.0,14.0,17.0,5.0,8.0,26.0,9.0,ADBACAGCHGCFGHDADABGEDABDABAFGCFDCADGGGGGGGGGBGGBACCHHAAGAADAGDAGDCGDBFFBCFBEBCEBGBBHEGDDCCCBHHAFGDGADGDDAFCGHHE,True +877,11.0,23.0,26.0,15.0,25.0,13.0,27.0,20.0,DHHEHGFGGCEHCGDGEDHCDHBFEDFEAFHBDGFCBHCEECEECBHCACGACACHGBHGBGGECGBDHCFEEEHCGHCGHCEBEFBGABCDDEGGEGGEGFEDBEBBGBCGBHABGEDCABCFECAHHBBCBDCAGBDGBAGCAHFHEBCEGCDFFDEF,False +878,10.0,21.0,12.0,20.0,16.0,27.0,18.0,16.0,EGCEHFAFAEBBGACGEEDEBDEFDBBDCBDEDFFAFGHBDFBHBGHBEBEGDDGDGBHGBHBFFGDFCFGCFAEGHEDEEDEAFFFFFFCHGGDGAFGAFHDBHEBCAGHBFDFFBHFCHFCHCCDCFDHBDGBDBHFA,False +879,13.0,7.0,15.0,3.0,11.0,11.0,9.0,9.0,CHBCFBFGEFEHCCAFAAFCEECBBHEEGEFBEABAADGAGGFGFCGACEHCHCFECADCACCACFAHFHDGHGAHEB,False +880,18.0,17.0,11.0,7.0,12.0,11.0,12.0,19.0,GACGHHGCCDAEAEBAFGHFGHEHABHBDHGCHGCHBABEEBECDDBABBHFHGCBGCBFAAGDAGHHHCAFCABAABAABHAFDAFBGDCHFEBEEHEFHEFBFHE,False +881,15.0,14.0,12.0,18.0,16.0,16.0,10.0,24.0,EFDEFDHBEHAEFFBHEBGEFABHGEHDFHAFEBCDGDAFDAHAACDACDGCEHDBBBBHDHEAEFAHGDFDABHABHAEHFEHFHHFHBFHAFHAEDCGBGGDDHDEHCBCCHCEFDGGHCDCC,False +882,1.0,3.0,4.0,5.0,7.0,5.0,2.0,5.0,HDHBCGDFACFECFEFBDFDGHEEHEBHEDCE,True +883,10.0,19.0,13.0,15.0,16.0,14.0,11.0,10.0,FDEBDAHCBEFHFHGGHGEBGCHCEECDACEFBAFHCBCEBAGBFGCEGBEHDDHBDHCDAFDEBDFBDEADBADBAECAGDABCGDCFBGFBDFBEFBFGBEHEECF,False +884,4.0,20.0,14.0,12.0,17.0,18.0,12.0,16.0,DHCFHCBHGFHFEDFEDBCDBFHHGCDFADCGHFBDCBDHAGEFBEHBEDCEGCABFHBHCCCCBHCGGFGFFBFBBEGFEBBBCGEGHHHFDAFDEFBEFHEGDEBEEBEEB,False +885,4.0,5.0,7.0,5.0,3.0,5.0,11.0,4.0,GBBEAFCABHGBGEFGDDCBDCFGCAGCDGCGHEGHFCHFGAGD,False +886,4.0,2.0,5.0,6.0,4.0,7.0,8.0,6.0,DEGFEGHBGCGHBGHDFAFFAFDADGCHECDECFFCHADHGG,False +887,7.0,10.0,2.0,12.0,7.0,8.0,10.0,7.0,HDGHAEDCDDBGDBAEBGCBDAEGFGFBGFBDDBFHBEHADFGDFHHFHEDGADGAFEAGEBB,False +888,22.0,21.0,26.0,15.0,24.0,25.0,19.0,23.0,HFHEFEAADAGDBCEBGEBEFHEGHAGEDGADFEBFCBFBBFCEHADFEHGHHFDFCHFCHDBGDHAAHFCFAEBAEGCEGCFFAHHGHHFHHCHCBABGDHHDFABGCFACFECDEAGEAGFBCFGCEGCBBBEBAGHGGCBAFACFDCDDCFCAHCACCBEEBEEBEADCCEF,False +889,14.0,18.0,14.0,7.0,16.0,10.0,10.0,16.0,FHAHHEDDECCCHBCBBFBFCBACDAGHAGHBFHBCHBEGEEGBBGBBGEAEAHHBEFFEAFEDHECEEGABGBDGCABEABAFCHCAACGBHHAHCDHFECFED,False +890,18.0,20.0,25.0,21.0,23.0,27.0,22.0,23.0,ECFEGEBFABFABCDBFHBHABHBDHGFGBFGECGCFHADHDEACCBHFEGFACHECHFBACCCBEBBDFDAEAABDAECCCFCFFCFFCEGCHBEGDEDFBDEGHFCHFCFDCFEGGEGDDGHDHHCGHFDFBDHGHHAAHAEHFGAFGAEADEFCEFBEGBGGHDAEDCEHCDGBDG,False +891,21.0,17.0,16.0,20.0,21.0,17.0,22.0,30.0,GEDGFABBHBBHFAGAEEAEAAECAEHHHBDDCABHGGHGCBAAFABFBFCGEBFEGEHHEHHDDHFGEEHDGHCAHFADBADCCGACHDGHAGHAFHAFBECBEDHGCHGAHGBDCEDCDBFDEGHGADGDHGFHCDGDFHBHHBHAECFECFEGFHFEDCED,False +892,2.0,4.0,1.0,8.0,1.0,2.0,5.0,5.0,HHHHBDABDGBDFFDCAHGGGBDGDDED,True +893,15.0,5.0,9.0,8.0,9.0,2.0,15.0,5.0,GGEGEEDAFGECACCAGFGEEDECDBAEGADGABAACCACCAHGAHADHGDGGHGBACBHBDEGAAGD,True +894,15.0,20.0,23.0,20.0,17.0,18.0,26.0,16.0,FGDFCFCCGBFEBEEDACGECGHCFFEDBBCHBFHBDAFHBGCFCCFAGHDGDGGBFEEGCEGAFGAEAFEDFEDBBDHBHGGGGCFDCEHBEHGCAAAAAGHCHHCHBGDDCDBGBBCABCABADBADBFDGGCCEDEEDGCGGDDGHCFHEFH,False +895,17.0,14.0,14.0,9.0,18.0,14.0,9.0,18.0,BGCDCCFADADBGDGCAEEAGEBEFBHHAEFFEHFEBEBCGCEBCEDAGGAHEABEABDAFDHBHHAAHBAHAHBAHCEHCAHFHBEHFCFFCEFCEHCHHCAEDFEDBGFGF,False +896,10.0,10.0,7.0,13.0,14.0,14.0,10.0,8.0,HCBCDHHGEAFHFCDGHEBDEAFBCFEDFADEADEADABBHCAEDGDDGFDAFHHFDGFGGFABFBCDBCEAGBBGEFGEFEEFEE,False +897,1.0,6.0,2.0,6.0,4.0,12.0,5.0,5.0,FBDGCGGDFEBFEFFEGFBGFHFFDFHBAHFEDFCHBBHDD,True +898,8.0,2.0,6.0,2.0,1.0,5.0,2.0,3.0,CFFCHDCFEHHAADAACCABAACGAFGBF,True +899,13.0,11.0,11.0,13.0,12.0,11.0,12.0,9.0,FCCGCABEBEEFCBGCDGCAECEEHAEGDCFFHDBCABDABEAFCBHABHADHGDFGDFBDFEDGHBGDGDAGAFECHEGDEGHFAHDABAF,False +900,11.0,8.0,16.0,15.0,15.0,12.0,12.0,10.0,HFDECDECFHCHGDEDEEBGHDAHDABCCDDFGDCGBCACCDGGFCGFEHEAGEAGEAFCCHCCAFEAFADEADHGDBFBBFBBFGCEAHFCDEEDHEG,False +901,6.0,5.0,13.0,12.0,14.0,4.0,0.0,2.0,DEEDEFCACAAEHEECDECAHCBDDECCBCFFDBFBCDECEECEDCADEDDEDACB,True +902,5.0,2.0,3.0,0.0,2.0,4.0,3.0,0.0,CFECFBAGAACAAGFFGBE,True +903,1.0,3.0,5.0,2.0,2.0,3.0,3.0,5.0,HEAGEFBCDBCBCFHCFHCDHGHG,False +904,8.0,10.0,8.0,10.0,10.0,10.0,8.0,8.0,HAEHAEDAEDGHFGFFAFFBFFGDABDECDEGGEGHBHBBCCFEDGECBCCBACHDCAFBDDEEDAHGBHBF,False +905,19.0,35.0,22.0,16.0,17.0,18.0,22.0,17.0,BEDEDGGBEBBDBGHBCBBCBHCAEAHBAGBCBHDBHDCHGCBGDAGDCCAGDGCDFCBFCBDBBDHAAEAGEGGEGBAFBHFGFGBFHEACECCGHCFFEFBCFBAFAABBBBBHDBEFBHFAGBEFCDGCFCDEEHBBFBDCGDEGFHGACAACAHHFGHEABE,False +906,6.0,6.0,11.0,1.0,5.0,2.0,8.0,3.0,GGECBACGCCGHCBFEGGAACAACDACBBCHCEFCEHBEGBG,True +907,10.0,11.0,15.0,22.0,12.0,15.0,10.0,11.0,CBDCFAHHHHCHDBDDBEDHCAECDFFDACDGBDABCFBCFBGDCFFCFEEHGGHGADGDFAFACGDCADFBCFGDFEDFDDADGAHEBHFCHDCDEEBEEDEGBE,False +908,4.0,0.0,2.0,5.0,3.0,0.0,2.0,3.0,GHACDADAEDAEDEGDHHC,True +909,1.0,4.0,0.0,5.0,2.0,3.0,1.0,1.0,FDHBDABFEBDDBDEGF,True +910,9.0,19.0,26.0,20.0,13.0,12.0,16.0,22.0,BHDCHGCHBCHDCBGCAEDFEBFBHDBHDGHEGECGCFDCHHGHHBHGFGCCBCCDCHAADFFDFFHEDCFBCEHCEHCDDFAGECGDBDBGFGEECBHCBACBACHCDEFDAHBCHCEGBGGCDDHDEHBAGBADB,False +911,5.0,1.0,2.0,3.0,2.0,3.0,0.0,2.0,HAHAADAFBAFEFCEDCD,True +912,26.0,20.0,25.0,15.0,11.0,21.0,19.0,28.0,BGFDDHABFAGCACFBCDBGDCCAAAHAAHFCHCEGGFFHHFBCABCGGGGBHEAHCAHBAHAHHACHFDHDAHABHCBFEBFADFGDCGFFHCGBCFBDFEDCHBBHBCGECGEHGFHAEHACHADAABHFDECEGBAGDHFDHCCFGAEGAECABFFBHCCHD,False +913,7.0,7.0,5.0,3.0,0.0,6.0,1.0,6.0,CDFCAFHACADCBBHBFHBFHFDGCABBABFHHAA,True +914,20.0,24.0,25.0,24.0,19.0,23.0,23.0,19.0,BDHFDGCHCAHFAHFGGCHBCHDFEDAEHCBFEBCGHCGFEACCAHDFGDFDBFBEFBEBGDBGDBCDECBFHEEEBCGBDDFDECHEHBFCAFADGADAHFCFFGFAGFEGEHGADDHDCHDBDDGEDBHABGGBEGBAHBHBDCFDCACCGEAACCACGAEGBEFBAFCCFGBAG,False +915,6.0,10.0,1.0,9.0,16.0,12.0,5.0,11.0,BFGFHGADDEEEEBEEHEHHEHFEBEGHFDHFBHFBDFDFFEBGDHCEBEEBEAGDADHAFAAFHBBEDF,True +916,19.0,25.0,17.0,15.0,26.0,25.0,27.0,16.0,EBBHBCGEEAEBCECGECHHCGDCECGECDBCDBAGCHGBFDBDBCEBFAAGAAHBGDFGAEGAEHEEHECGFFAFBEEAEEABEHBGHBFHDGCCFEFFCFFGFDHBAHAGFDGFDGHGGEDGEBGHGFFECBAFBHGEFBFGDFHDAADGGBAGBFCBFDEFAFBABE,False +917,1.0,1.0,0.0,2.0,5.0,1.0,1.0,0.0,DABDEEEEGFE,True +918,3.0,4.0,4.0,5.0,6.0,2.0,1.0,2.0,FCHDCBDCDEADEBDEBFBGACAEHEE,True +919,29.0,30.0,27.0,23.0,18.0,16.0,15.0,25.0,CECCDDBFGBEHCFACFCCAAAAABGDBDCBDABFBCEACABCGBHGDCGFBGHCDHCEHCBAFBFGHFHHDHFEHFEHCDBDDACBACGACGACFEDEBDHBDHAAEEGFBHHBHDAHBGBCGDAAHAFEBCCBDBEEAHEHFGHAHAABBABDHBDADDAECGBCEDCDCGEHAEHABBFF,False +920,6.0,8.0,6.0,2.0,10.0,1.0,2.0,2.0,ABABBFGBDGEECCEACECHEHBEABDBEEEACEACB,True +921,9.0,6.0,2.0,9.0,10.0,5.0,13.0,15.0,EBEDHGAHGFHGFBDEDDGCDGDHFAEABEGEGAHGAFEAGHAHHEHDEHDABDBGEGGBGHHACHFHH,True +922,0.0,4.0,4.0,4.0,5.0,3.0,8.0,5.0,BFCBHEBHDBCDFGGEGFEGEHGHCDHGDGGEC,False +923,9.0,18.0,18.0,28.0,20.0,33.0,20.0,19.0,FCFHEFDEBCBBCFACFDCDCAFCAHBDHBFGFHAFEAFEHGCHGDHCDHCFCGDCHBEGFFGDFGBHGDFGDFGFAHDBGGHHABEDFFDFFDFFEBFHDCEDFEFHEHHDGACFFGHBBHBADDDDCDEGDGGCEFCDBEBGEDEEBCEFGFFBEDGEDBFDE,False +924,2.0,5.0,0.0,7.0,6.0,1.0,0.0,3.0,EEDEEHEBAEBDDDADBHDFHBBD,True +925,12.0,20.0,17.0,18.0,18.0,15.0,13.0,21.0,GHHFHBACCFFHHFHHABHGDHFDEBABDDBCAEHABDEDCGDGDDGCDFFDHEBAEBAEBDCBGCEGBEHBFCEFDBGBFGBHBHHFFEEGECGECGECBHGBHDCHDAFDCFDEAHAHEAHACCEEFBBDCC,False 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+976,27.0,32.0,25.0,20.0,17.0,19.0,24.0,36.0,HCFABFDBGEFGFDCBDCAEBHEDADCADCGBCDACDBBHBBDAHAHHFFGEFHHBBHEFAEDHEHHBHHDAHCACCDDDAHCEECBBHBHHBGDBGBBGHCAHCFHFHGCHGAEGFFBBHCBHAAABACEGCGGCGACFACGHBDCBHCGGEHEBGAFFAEHHDFHDFEGFABDABGBBECBEBGAAFAACGHGHHGDH,False +977,21.0,23.0,33.0,29.0,26.0,21.0,26.0,19.0,BFCBCBEGFEGDEGFEBDACFGCDGADCDDCBBCGCDDCGCCGDDGBFBEEBAABAACFCCFHDDHDEBDEFCEBBGBEEDAEAHFCHFHHEBEEFFEFHEADEGEGGCGGADDFBCADDDCCGCCGCDGEDFADGDFGFFBCAAHAHEFHECAGFGDCEDCADBAHHHHEHHEFHBCCCCBBAABCAHHDGBEGCGG,False +978,7.0,8.0,10.0,5.0,10.0,5.0,5.0,1.0,DECDEBFCGFADFEBAECABABEGGECDFCGBEGCEHCBDCBCABCAEAFE,True +979,1.0,2.0,1.0,6.0,0.0,1.0,0.0,1.0,DCADFBDHDDBD,True +980,24.0,21.0,18.0,12.0,17.0,7.0,12.0,18.0,BBAHBHDDHBHFAHACBEBBCBAEEACHAHHEGBBGBCDCCAECAHCAGGAFFACFAHHEEAEHFGCACEACHFCHDDEDDEDDCBCCHEBHBAHEABBGBBADBGBBEAAGAADHEGEGGEGAFDACC,False +981,22.0,33.0,18.0,23.0,27.0,28.0,28.0,13.0,EAEDGBCFBAFBGFDAFAAGHAEBFHFFHFFGACDBDFCDFGDBEBBDHCFBEEGGDAGECGEFABFGBEDAEAHEGDDBEGCDABHBBGBDFBDHBGBBEBBHABAABDCEFGAFGAFBFCEFBGGHAGAFEDGEDCHFHBFGDHCFHCAGFDGCGECFECBECBECECABCAEFBEFEEGDBGDEGDBGD,False +982,22.0,20.0,15.0,16.0,27.0,17.0,27.0,21.0,GDFGHEGBEHCEBCHBEHBAHGCGGEGBBFDEADFFHADHEBHGDACDACDEBEEGEHBEGBEGHEBFAAFGFFGDFGDFABGHFHCEECHDGBDCBFFBGCBDDHDCGBCFAFHGGHEGACHECAEAAHCABAACAHEEDEADEFEGBGGEGAAGEBGFAHHAE,False +983,6.0,5.0,6.0,11.0,8.0,8.0,5.0,7.0,HBFHDFCEABBADECDEGDFCDFHBFEDECCFGHFAHGHHADEADFCDGDDGEBAE,False +984,9.0,13.0,13.0,13.0,32.0,25.0,15.0,18.0,EEAEEGEABEGHGFDADEEFAHHCBFGDCBBCHBCFDCFDCFDEFDEFCHFEFECFEHFHGFHGFHEBBCGECBDHHEEDEFCEGAADEFEHGEDFEHFEDFEGBHHFHGEEGEGAACFABFGFDGBEECEEFHBFHB,False +985,14.0,10.0,10.0,7.0,7.0,11.0,13.0,6.0,FAFAHGABAACAAGAFCDDCGCEFDBGBGACHECAECAEBAHDDFDBFDBFGBAGCHBEHBAGBECFFCEFGGGGGFH,False 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For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. +## Build and Run +## Skewed Random Generator -## Compile/Build +## Even Random Generator -To build code and compile use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). - -## Run - -To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: - -`sbt run` - -## Benchmarks - -To run a single benchmark use the following command: - -`sbt testOnly ` - -To run all benchmarks and generate respective reports run the following command: - -`sbt test` - - -`//TODO add list of benchmkarks` - - -## Documentations - -Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). - -You can comment there or inside codes if you have any idea :-). diff --git a/build.sbt b/build.sbt deleted file mode 100644 index f92a6be..0000000 --- a/build.sbt +++ /dev/null @@ -1,10 +0,0 @@ -name := "nback.markov" -organization := "org.xcit" - -version := "0.1" - -scalaVersion := "2.12.7" - - -//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" -libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/demo/nb_gm_002_demo.py b/demo/nb_gm_002_demo.py new file mode 100644 index 0000000..98b8358 --- /dev/null +++ b/demo/nb_gm_002_demo.py @@ -0,0 +1,52 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +# initialize three blocks +for b in range(2): + block = design.Block() + block.set_factor("index", b) + for tindex, item in enumerate(nback_sequence): + trial = design.Trial() + trial.set_factor("stimulus", item) + trial.set_factor("index", tindex) + for x in range(10): + stim = stimuli.TextLine(item, text_size=200, background_colour=[0,0,0], text_colour=[255,0,0]) + c = stimuli.Canvas(stim.surface_size) + stim.plot(c) + c._get_surface().set_alpha(x*25) + c.preload() + trial.add_stimulus(c) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +expyriment.control.start(exp) + +# present trials +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + for stim in trial.stimuli: + stim.present() + exp.clock.wait(5) + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("index"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_002_demo_sdt.py b/demo/nb_gm_002_demo_sdt.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_002_demo_sdt.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_003_demo.py b/demo/nb_gm_003_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_003_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/nb_gm_005_demo.py b/demo/nb_gm_005_demo.py new file mode 100644 index 0000000..776b951 --- /dev/null +++ b/demo/nb_gm_005_demo.py @@ -0,0 +1,44 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators import nb_gm_002 + +import benchmarks.common as common + +nback_sequence = nb_gm_002.SequenceGenerator(common.choices).generate(24, 8, 2, 2) + +exp = design.Experiment("Skewed N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt"] + + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + +# initialize three blocks +for b in range(0, 2): + block = design.Block() + block.set_factor("block", b) + for item in nback_sequence: + trial = design.Trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + stim.preload() + trial.add_stimulus(stim) + block.add_trial(trial, random_position=False) + exp.add_block(block) + +for block in exp.blocks: + for trial in block.trials: + exp.clock.wait(1000 - fixation.present()) + trial.stimuli[0].present() + pressed_key, rt = exp.keyboard.wait(response_keys) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - trial.stimuli[0].unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/demo/progressive_gen_demo.py b/demo/progressive_gen_demo.py new file mode 100644 index 0000000..2319d3d --- /dev/null +++ b/demo/progressive_gen_demo.py @@ -0,0 +1,55 @@ +import expyriment +from expyriment import design, control, stimuli, misc +from generators.nb_gm_004 import SequenceGenerator + +import benchmarks.common as common +num_of_blocks = 2 +trials_per_block = 8 +n = 2 +lures = 1 +targets = 2 + +control.defaults.window_mode = True +generators = [SequenceGenerator(common.choices, n) for b in range(0, num_of_blocks)] + +exp = design.Experiment("Progressive N-Back Task") +control.initialize(exp) +exp.data_variable_names = ["block", "stimulus", "pressed_key", "rt", "n", "difference_threshold", "performance"] + +fixation = stimuli.FixCross() +fixation.preload() + +# left and right arrow keys for responses +response_keys = [misc.constants.K_LEFT, misc.constants.K_RIGHT] + +expyriment.control.start(exp) + + +# initialize three blocks +for b in range(0, num_of_blocks): + block = design.Block() + block.set_factor("block", b) + block.set_factor("trials", trials_per_block) + exp.add_block(block) + +for block in exp.blocks: + trials = block.get_factor("trials") + block_index = block.get_factor("block") + # TODO present the N in an instruction + # TODO recalculate N based on performance + generators[block_index].reset(trials_per_block, targets, lures, n=n) + for i in range(0, trials): + trial = design.Trial() + item = generators[block_index].next_trial() + trial.set_factor("stimulus", item) + stim = stimuli.TextLine(item, text_size=200) + exp.clock.wait(1000 - fixation.present() - stim.preload()) + stim.present() + + # Wait for response, remove duration param for forced-choice. + pressed_key, rt = exp.keyboard.wait(response_keys, duration=2000) + exp.data.add([block.get_factor("block"), trial.get_factor("stimulus"), pressed_key, rt, n, 0, 0]) + exp.clock.wait(1000 - expyriment.stimuli.BlankScreen().present() - stim.unload()) + +expyriment.control.end("Goodbye!", goodbye_delay=1000) + diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..e69de29 --- /dev/null +++ b/generators/__init__.py diff --git a/generators/even_random.py b/generators/even_random.py new file mode 100644 index 0000000..fda40d8 --- /dev/null +++ b/generators/even_random.py @@ -0,0 +1,75 @@ +from constraint import * + +import itertools as it + +import Numberjack as nj + +class EvenRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials=64, tl=1): + self.tl, self.trials, self.choices = tl, trials, choices + + def generate(self): + seqs = self._generate_initial_sequences() + return self._find_optimal_sequence(seqs, 0.2) + + def _generate_initial_sequences(self): + """ + Generates initial sequence of items based on choices and number of desired trials. + In EvenRandom sequences, all stimuli have same number of appearances. + """ + + pool = it.product(self.choices, repeat=self.trials) + return pool + + def _find_optimal_sequence_numberjack(self,tl_ratio): + """Optimize with Numberjack""" + + cost = nj.Variable(0, 100, 'cost') + seqs = nj.Variable([]) # all sequences + + model = nj.Model( + seqs., + cost == self.calculate_tl_ratio(seq) - tl_ratio, + nj.Minimise(cost) + ) + solver = model.load('Mistral') + if solver.solve(): + solver.printStatistics() + else: + print("No solution with Numberjack") + + + def _find_optimal_sequence(self, sequences, tl_ratio): + """Optimize a sequence to match a desired tl ratio with python-constraints""" + + p = Problem() + + # TODO add all possible values for seq (its domain) + p.addVariable("seq", list(sequences)) + + p.addConstraint(lambda s: self.calculate_tl_ratio(s) - tl_ratio < 0.05) + + return p.getSolution() + + @staticmethod + def calculate_tl_ratio(seq): + """Calculates the T:L ratio of a sequence.""" + targets = 0 + lures = 0 + for index, item in seq: + if item == seq[index-2]: + targets += 1 + elif item == seq[index-1] or item == seq[index-3]: + lures += 1 + # avoid division by zero + if lures == 0: + lures = 1 + return targets/lures + + +if __name__ == '__main__': + generator = EvenRandomGenerator(['a', 'b', 'c'], trials = 4) + generated_seq = generator.generate() + print('Even Random Sequence: %s' % ''.join(generated_seq)) diff --git a/generators/nb_gm_001.py b/generators/nb_gm_001.py new file mode 100644 index 0000000..a0ec0b0 --- /dev/null +++ b/generators/nb_gm_001.py @@ -0,0 +1,31 @@ +import random + + +class SequenceGenerator: + """Generate N-Back sequences with random sampling, but increase matching probability over time.""" + + def __init__( + self, + choices: list, + n=2, + target_probability_start=0.33, + target_probability_end=0.50 + ): + self.n, self.choices = n, choices + self.target_probability_step = target_probability_end - target_probability_start + self.target_probability = target_probability_start + self.seq = [] + self.trials = 0 # init + + def generate(self, trials) -> list: + self.trials = trials + self.seq.clear() + for t in range(self.trials): + self.seq += self.random_sample() + return self.seq + + def random_sample(self): + show_target = (random.random() > self.target_probability) and len(self.seq) > self.n + self.target_probability += self.target_probability_step + nontargets = [c for c in self.choices if len(self.seq) <= self.n or c != self.seq[-self.n]] + return self.seq[-self.n] if show_target else random.choice(nontargets) diff --git a/generators/nb_gm_002.py b/generators/nb_gm_002.py new file mode 100644 index 0000000..46b51fa --- /dev/null +++ b/generators/nb_gm_002.py @@ -0,0 +1,56 @@ +import logging +import random +import csv + +import heapq + +import benchmarks.common as utils + +class SequenceGenerator: + """nb_gm_002 generator + Generates skewed random sequence of stimuli for the n-back task, based on Ralph (2014). + Each sequence contains specific fraction of matched trials (targets). + """ + + def __init__( + self, + choices: list, + n=2 + ): + self.n, self.choices = n, choices + self.seq = [] + self.trials = None + + def generate(self, trials, targets, lures1, lures2, debug=False) -> list: + + self.trials = trials + distractors = trials - targets - lures1 - lures2 - self.n + pool = ['T'] * targets + ['1'] * lures1 + ['2'] * lures2 + ['-'] * distractors + random.shuffle(pool) + pool = ['-'] * self.n + pool + if debug: + print(f"MASK : {''.join(pool)}") + self.seq.clear() + for i in range(len(pool)): + t = pool[i] + if t == 'T': + self.seq += self.seq[i-self.n] + elif t == '1': + self.seq += self.seq[i-self.n - 1] + elif t == '2': + self.seq += self.seq[i-self.n + 1] + else: # distractors + d = [c for c in self.choices if c not in self.seq[-self.n - 1:-self.n + 1]] if i > self.n else self.choices + self.seq += random.choices(d) + if debug: + print(f"RESULT: {''.join(self.seq)}", '(t,l)=', utils.count_targets_and_lures(self.seq, self.n)) + return self.seq + + +if __name__ == '__main__': + gen = SequenceGenerator(['A', 'B', 'C', 'D', 'E', 'F'], 2) + s =gen.generate(24, 8, 4, 0, debug=True) + + with open("seqs.txt") as fh: + for line in fh: + print(line) diff --git a/generators/nb_gm_003.py b/generators/nb_gm_003.py new file mode 100644 index 0000000..af4ad9e --- /dev/null +++ b/generators/nb_gm_003.py @@ -0,0 +1,99 @@ +import random +import scipy.stats + +import benchmarks.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - specific number of matching trials. + - even distribution of stimuli. + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.targets_norm = None + + def reset(self, trials, targets): + self.trials = trials + self.targets = targets + + self.targets_norm = scipy.stats.norm(targets, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + if self.seq: + self.seq.clear() + + def generate(self, trials, targets): + self.reset(trials, targets) + while not self.seq or len(self.seq) < self.trials: + # self.seq += self.best_choice() + chunk_size = self.n + 1 if len(self.seq) + self.n + 1 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(min(chunk_size, len(self.choices))) + return self.seq + + def best_chunk(self, chunk_size=3) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + chunks = list(permutations(self.choices, chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + # DEBUG print(self.matchratio_cost(seq), self.evendist_cost(seq)) + return self.skewness_cost(seq) + self.targets_ratio_cost(seq) + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + cost = 1.0 - (self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0)) + return cost + + def targets_ratio_cost(self, seq): + t, _ = common.count_targets_and_lures(seq, self.n) + return 1.0 - (self.targets_norm.pdf(t) / self.targets_norm.pdf(self.targets)) + + +if __name__ == '__main__': + import time + + n = 3 + gen = SequenceGenerator(['1','2','3','4','5','6'], n) + + st = time.time() + s = gen.generate(24, 4) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(48, 16) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") + st = time.time() + s = gen.generate(72, 8) + st = time.time() - st + print(f"{common.count_targets_and_lures(s,n)}") + print(f"time = {st:0.2f}s") diff --git a/generators/nb_gm_004.py b/generators/nb_gm_004.py new file mode 100644 index 0000000..b974c0f --- /dev/null +++ b/generators/nb_gm_004.py @@ -0,0 +1,97 @@ +import random +import scipy.stats + +import tests.common as common + +class SequenceGenerator: + """nb_gm_003: + - pseudo-random sampling. + - fixed number of targets. + - non-skewed stimulus distribution. + - fixed T:L ratio. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.lures_ratio, self.choices, self.n = None, None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_norm = None + self.targets_norm = None + + self.current_trial = None + + def reset(self, trials, targets, lures, **kwargs): + self.trials = trials + self.targets_ratio = targets / trials + self.lures_ratio = lures / trials + self.n = kwargs.get("n", self.n) + + self.targets_norm = scipy.stats.norm(self.targets_ratio, 1.0) + self.lures_norm = scipy.stats.norm(self.lures_ratio, 1.0) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.seq = [] + self.current_trial = 0 + + def next_trial(self): + while self.current_trial >= len(self.seq): + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + self.current_trial += 1 + print(self.current_trial) + return self.seq[self.current_trial-1] if self.current_trial<=self.trials else None + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets/len(seq)), self.lures_cost(lures/len(seq)) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_norm.pdf(targets_ratio) / self.targets_norm.pdf(self.targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_norm.pdf(lures_ratio) / self.lures_norm.pdf(self.lures_ratio) + diff --git a/generators/nb_gm_005.py b/generators/nb_gm_005.py new file mode 100644 index 0000000..dea5915 --- /dev/null +++ b/generators/nb_gm_005.py @@ -0,0 +1,104 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """nb_gm_005: + - pseudo-random sampling. + - fixed number of targets,lures, and distractors. + - all stimuli presented equally as target, lure, or distractor. + + """ + + def __init__( + self, + choices, + n + ): + self.trials, self.targets_ratio, self.choices, self.n = None, None, choices, n + self.seq = [] + + # create norm distributions for cost functions + self.skewness_norm = None + self.lures_ratio_norm = None + self.targets_ratio_norm = None + + def reset(self, trials, targets, lures): + self.trials = trials + + self.targets_ratio_norm = scipy.stats.norm(targets/trials, 0.2) + self.lures_ratio_norm = scipy.stats.norm(lures/trials, 0.2) + self.skewness_norm = scipy.stats.norm(0 , trials/len(self.choices)) + + print(self.skewness_norm.pdf(0)) + print(self.targets_ratio_norm.pdf(1.0/3.0)) + print(self.lures_ratio_norm.pdf(1.0/6.0)) + + self.seq = [] + + def generate(self, trials, targets, lures): + self.reset(trials, targets, lures) + while not self.seq or len(self.seq) < self.trials: + #self.seq += self.best_choice() + chunk_size = 3 if len(self.seq) + 3 <= self.trials else self.trials-len(self.seq) + self.seq += self.best_chunk(chunk_size) + return self.seq + + def best_chunk(self, chunk_size) -> list: + from itertools import permutations + min_cost, best_chunk = None, None + best_chunk_size = min(len(self.choices), chunk_size) + chunks = list(permutations(self.choices, best_chunk_size)) + random.shuffle(chunks) + for chunk in chunks: + cost = self.cost(self.seq + list(chunk)) + if min_cost is None or cost < min_cost: + min_cost, best_chunk = cost, chunk + return list(best_chunk) + + def best_choice(self) -> list: + best_choice, min_cost = None, None + random.shuffle(self.choices) # to avoid ordering effect + for choice in self.choices: + cost = self.cost(self.seq + [choice]) + if min_cost is None or cost < min_cost: + min_cost, best_choice = cost, choice + return [best_choice] + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, n) + targets_ratio, lures_ratio = targets/len(seq), lures/len(seq) + c1, c2, c3 = self.skewness_cost(seq), self.targets_cost(targets_ratio), self.lures_cost(lures_ratio) + # print(c1,c2,c3) + return c1+c2+c3 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) + + def targets_cost(self, targets_ratio): + return 1.0 - self.targets_ratio_norm.pdf(targets_ratio) + + def lures_cost(self, lures_ratio) -> float: + return 1.0 - self.lures_ratio_norm.pdf(lures_ratio) + + +if __name__ == '__main__': + import time + import numpy as np + + trials, targets, lures = 24, 8, 4 + choices = ['1', '2', '3', '4', '5', '6', '7', '8'] + print('alg,n,trials,time,targets,lures') + for s in range(1, common.sample_size): + n = np.random.randint(2, 8) + gen = SequenceGenerator(choices, n) + st = time.time() + s = gen.generate(trials, targets, lures) + st = time.time() - st + t, l = common.count_targets_and_lures(s, n) + print(f"nb_gm_004,{n},{trials},{st:0.2f},{t},{l}") diff --git a/generators/progressive_random.py b/generators/progressive_random.py new file mode 100644 index 0000000..6496761 --- /dev/null +++ b/generators/progressive_random.py @@ -0,0 +1,74 @@ +import random +import scipy.stats + +import benchmarks.common as common + + +class SequenceGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__( + self, + choices, + trials, + desired_tl=4.0, + n=3, + targets_ratio=0.33 + ): + self.desired_tl, self.choices, self.n, self.targets_ratio = desired_tl, choices, n, targets_ratio + self.sequence = list() + self.norm_even_dist = scipy.stats.norm(0, trials/2) + self.norm_targets_ratio_dist = scipy.stats.norm(targets_ratio, 0.5) + self.norm_tl_ratio_dist = scipy.stats.norm(desired_tl, trials/2) + self.trials = None + + def generate(self, trials): + self.trials = trials + while not self.sequence or len(self.sequence) < self.trials: + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence + + def next_trial(self): + if self.sequence and len(self.sequence) >= self.trials: + return None + self.sequence = self.sequence + self.__find_best_choice(self.sequence, self.choices) + return self.sequence[-1] + + def __find_best_choice(self, seq: list, choices: list) -> list: + import sys + min_cost, best_choice = sys.float_info.max, None + random.shuffle(choices) # to avoid ordering effect + for choice in choices: + cost = self.cost(seq + [choice]) + if cost < min_cost: + min_cost = cost + best_choice = choice + return best_choice + + def even_distribution_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio)/self.trials for c in self.choices} + max_dist = max(list(costs.values())) + return 1.0 - self.norm_even_dist.pdf(max_dist) + + def cost(self, seq): + """ + Calculate overall fitness of a sequence (block of trials). + Right now it's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + + targets, lures = common.count_targets_and_lures(seq, self.n) + targets_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials) + tl_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.tl(seq)) + even_cost = self.even_distribution_cost(seq) + return targets_cost + tl_cost + even_cost + + def tl(self, seq): + """Calculates the T/L ratio in a block of trials.""" + targets, lures = common.count_targets_and_lures(seq, self.n) + if lures < 0.01: # avoid division by zero + lures = 0.01 + return targets/lures + diff --git a/generators/progressive_random_block_ga.py b/generators/progressive_random_block_ga.py new file mode 100644 index 0000000..a7f454a --- /dev/null +++ b/generators/progressive_random_block_ga.py @@ -0,0 +1,118 @@ +import itertools as it +import random + +import benchmarks.common as common +import scipy.stats + +class ProgressiveGAGenerator: + """Generate a sequence progressively according to a predefined TL ratio and an even distribution""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + + self.tl_norm = scipy.stats.norm(self.tl, 0.5) + self.skewness_norm = scipy.stats.norm(0, 0.5) + + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __init_pool(self, pool_size) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + self.pool.clear() + all_comb = it.combinations_with_replacement(self.choices, self.trials) + sample = random.sample(list(all_comb), pool_size) + self.pool.extend(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, count=1): + """ + Find best gene(s) or parent(s) from the current pool. + :param count: Number of desired best parents to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(self.pool, key=lambda ss: self.cost(ss)) + return sorted_pool[:count] + + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + def cost(self, seq): + targets, lures = common.count_targets_and_lures(seq, self.n) + #print(seq, targets, lures) + tl = targets / lures if lures >0 else targets + c1, c2 = self.skewness_cost(seq), self.tl_cost(tl) + return c1+c2 + + def skewness_cost(self, seq): + even_ratio = self.trials / len(self.choices) + costs = {c: abs(seq.count(c) - even_ratio) for c in self.choices} + max_deviation_from_even_dist = max(list(costs.values())) + return 1.0 - self.skewness_norm.pdf(max_deviation_from_even_dist) / self.skewness_norm.pdf(0) + + def tl_cost(self, tl): + return 1.0 - self.tl_norm.pdf(tl) / self.tl_norm.pdf(self.tl) + + +if __name__ == '__main__': + + generator = ProgressiveGAGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=24, n=4) + sq = generator.generate() + + print('Progressively-Optimized Sequence: %s' % sq) diff --git a/generators/random_block_ga.py b/generators/random_block_ga.py new file mode 100644 index 0000000..56b7cc0 --- /dev/null +++ b/generators/random_block_ga.py @@ -0,0 +1,141 @@ +import itertools as it +import random + + +class GAOptimizedRandomGenerator: + """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" + + def __init__(self, choices, trials, tl=2.0, pool_size=100, n=3): + """Initialize the genetic algorithm optimizer for n-back sequences. + :param choices: + :param trials: + :param tl: + :param pool_size: + :param n: + """ + self.tl, self.trials, self.choices, self.pool_size, self.n = tl, trials, choices, pool_size, n + self.pool = [] + self.__init_pool(pool_size) + + def generate(self): + """Generate a sequence of trials based on passed parameters. TL ratio and distribution are expected to be + close to the desired ones but not exactly the same. + :return: a sequence of items in "list" format. + """ + generation = 0 + best_parent = self.__find_best_parents(1)[0] + while self.cost(best_parent) > 0.1 and generation < 1000: + generation += 1 + if random.random() > 0.5: + self.pool = list(map(lambda s: self.mutate(s), self.pool)) + self.pool = self.crossover_all() + best_parent = self.__find_best_parents(1)[0] + print(best_parent, 'cost=%f' % self.cost(best_parent)) + return best_parent + + def __append_chunk(self, prefix="", chunk_size=8): + chunk_generation = 0 + pool = [] + + def __init_pool(self, pool_size, chunk_size = 8) -> list: + """ + Initialize solution pool. + :param pool_size: Num of initial random solutions + :return: initial pool of + """ + print("Initializing the pool...") + population = it.combinations_with_replacement(self.choices, chunk_size) + sample = random.sample(list(population), pool_size) + self.pool = list(map(lambda _: ''.join(_), sample)) + return self.pool + + def __find_best_parents(self, pool: list, count=1) -> list: + """ + Find best available sequences from the current pool based on the cost function. + :param count: Number of desired best sequences to be returned. Default is 1. + :return: A list of most fit sequences. + """ + sorted_pool = sorted(pool, key=lambda _: self.cost(_)) + return sorted_pool[:count] + + def distribution_cost(self, seq): + """ + Calculate fitness according to the similarity to the desired uniform distribution. + :param seq: a string + :return: + """ + costs = {c: 0.0 for c in self.choices} + for c in list(seq): + costs[c] += 1.0 if costs.__contains__(c) else 0.0 + + # TODO instead of normalizing all, only normalize the max value + costs = {k: abs(1.0 - v*len(self.choices)/self.trials) for k, v in costs.items()} + return max(list(costs.values())) + + def cost(self, seq): + """ + Calculate overall fitness (or cost) of a sequence. + It's a cost function, so we try to minimize this cost. + :param seq: + :return: + """ + # add fitness for uniform distribution of all stimuli + # TODO merge different cost functions with weights + return abs(self.calculate_tl_ratio(seq, self.n) - self.tl) + self.__distribution_cost(seq) + + def crossover_all(self): + """ + Perform random crossover for all pairs. + :return: new pool + """ + new_pool = [] + for i in range(int(self.pool_size/2)): + seq1 = self.pool[i*2] # change to weighted random + seq2 = self.pool[i*2 + 1] # change to weighted random + new_pool.extend(self.crossover(seq1, seq2)) + + return new_pool + + def crossover(self, seq1, seq2): + """ + Crossover two sequences. + :param seq1: + :param seq2: + :return: + """ + pos = random.randint(0, self.trials) + return [seq1[:pos] + seq2[pos:], seq2[:pos] + seq1[pos:]] + + def mutate(self, seq): + if random.random() > 0.5: + pos = random.randint(0, len(seq)-1) + seq_list = list(seq) + seq_list[pos] = random.choice(self.choices) + return ''.join(seq_list) + return seq + + @staticmethod + def calculate_tl_ratio(seq, n: int): + """Calculates the T/L ratio in a block of trials.""" + targets = 0.0 + lures = 0.0 + for index in range(n, len(seq)): + item = seq[index] + if item == seq[index - n]: + targets += 1.0 + elif item == seq[index - (n-1)] or item == seq[index - (n+1)]: + lures += 1.0 + if lures - 0.0 < 0.001: # avoid division by zero + lures = 0.001 + return targets/lures + + +# Demo +if __name__ == '__main__': + + generator = GAOptimizedRandomGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=16, n=2) + sq = generator.generate() + tl_ratio = generator.calculate_tl_ratio(sq, n=2) + even_dist = generator.distribution_cost(sq) + + print('GA-Optimized Sequence: %s' % sq, 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist) diff --git a/markov/README.md b/markov/README.md new file mode 100644 index 0000000..623d3e4 --- /dev/null +++ b/markov/README.md @@ -0,0 +1,38 @@ +# N-Back Sequence Generators + +**Note #1:** It's a work in progress (WIP), and commits will be tagged with WIP if it's not expected to work! + +**Note #2:** All the following commands can be run inside `sbt` shell. For the sake of simplicity, it is assumed the developer is in her terminal when running the commands. + + +## Compile/Build + +All python classes include scripts to manage executing a sample code. Just use `python ` to the sample codes of a generator. + +To build Scala codes and compile them use `sbt compile` and `sbt build`. It's recommended to use `sbt clean` before running any of these commands :-). + +## Run + +To run default generator (with random sequence generator), and some other benchmarking and reporting outputs use the following command: + +`sbt run` + +## Benchmarks + +To run a single benchmark use the following command: + +`sbt testOnly ` + +To run all benchmarks and generate respective reports run the following command: + +`sbt test` + + +`//TODO add list of benchmkarks` + + +## Documentations + +Currently all respective documents and UML diagrams are available at our [Google Drive as document file](https://docs.google.com/document/d/1tASkipaysX7vnNUcFYJlWsJJTrBcSZteLFQZUPY4_6c/edit?usp=sharing). + +You can comment there or inside codes if you have any idea :-). diff --git a/markov/build.sbt b/markov/build.sbt new file mode 100644 index 0000000..f92a6be --- /dev/null +++ b/markov/build.sbt @@ -0,0 +1,10 @@ +name := "nback.markov" +organization := "org.xcit" + +version := "0.1" + +scalaVersion := "2.12.7" + + +//libraryDependencies += "org.scalactic" %% "scalactic" % "3.0.+" +libraryDependencies += "org.scalatest" %% "scalatest" % "3.0.+" % "test" diff --git a/markov/project/build.properties b/markov/project/build.properties new file mode 100644 index 0000000..e71780d --- /dev/null +++ b/markov/project/build.properties @@ -0,0 +1 @@ +sbt.version = 1.2.6 \ No newline at end of file diff --git a/markov/project/plugins.sbt b/markov/project/plugins.sbt new file mode 100644 index 0000000..0f102c4 --- /dev/null +++ b/markov/project/plugins.sbt @@ -0,0 +1 @@ +//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala new file mode 100644 index 0000000..021ea42 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala @@ -0,0 +1,34 @@ +package org.xcit.nback.generators + +import scala.collection.mutable +import scala.util.Random + +/** + * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. + * Reference: Ralph2014 + * + * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar + * characters). Default alphabet contains 20 characters. + * @param target target item (default is 'A'). + */ +class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { + /** + * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 64): String = { + var results = mutable.ListBuffer[String]() + val items = List.range(0, trials) + + // decide if target or non-target with 50/50 chance. + //TODO change probability according to a new class param + if (Random.nextBoolean) + results += target.toString + else + items.foreach( + results += alphabet.charAt(Random.nextInt(alphabet.length)).toString + ) + results.mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala new file mode 100644 index 0000000..d10e633 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala @@ -0,0 +1,6 @@ +package org.xcit.nback.generators + +//TODO +class MarkovChainSequenceGenerator { + +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala new file mode 100644 index 0000000..8488984 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.generators + +import scala.util.Random + +class RandomSequenceGenerator(N: Int) extends SequenceGenerator { + /** + * Generate simple alphanumeric string of size N + * + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(trials: Int = 0): String = { + Random.alphanumeric.take(trials).mkString("") + } +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala new file mode 100644 index 0000000..9cb0604 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala @@ -0,0 +1,28 @@ +package org.xcit.nback.generators + +/** + * Companion object and buiilders interface for Strategy pattern of the sequence generators. + * Params: + * "n": The "n" property in n-back (N items back must match the current stimuli). + * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement + * learning methods. + * + */ +object SequenceGenerator { + def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) + def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) + def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) +} + +/** + * Generic n-back class to generate a sequence of n-back items with HMM. + */ +trait SequenceGenerator { + + /** + * Generate simple alphanumeric string of size N + * @param trials number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + def generate(trials: Int = 0): String +} diff --git a/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala new file mode 100644 index 0000000..3549506 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala @@ -0,0 +1,89 @@ +package org.xcit.nback.generators + +import scala.collection.mutable.ListBuffer +import scala.util.Random + +/** + * Reference: Ralph2014 - Appendix A + * + * @param alphabet Alphabet used to generate the sequence, excluding the target item + * @param target Target item. It must not be included in [[alphabet]]. + * @param N The set size of stimuli to remember (n in n-back). Default is 3. + * @param T Number of target trials + * @param D Number of non-matching distractor trials. + * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). + * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). + */ +class SkewedSequenceGenerator( + alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 + target: Char = 'A', + N: Int = 3, + T: Int = 24, + D: Int = 32, + L1: Int = 4, + L2: Int = 4) + extends SequenceGenerator { + + + val trials = T + D + L1 + L2 + + /** + * Types of each trial (L1, L2, T, or D). + */ + private object TrialType extends Enumeration { + val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value + } + + /** + * Ignores trials. Trials' value is defined by N+T+D+L1+L2 + * @param t number of items in n-back sequence. + * @return string of size "trials" with random alphanumeric characters. + */ + override def generate(t: Int): String = { + // 1. Init buffer with empty list of items :-). Why am I explaining this? + var buffer = ListBuffer[String]() + + var trial = 0 + + while (trial < trials) { + trial += 1 + + // 2. For each trial, generate a random type (L1, L2, T, or D) + // 3. Based on the generated type, generate the item and append it to the buffer + buffer += {nextTrialType(trials-trial) match { + case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => + buffer(buffer.length - (N + 2)) + case TrialType.TARGET if buffer.length > N => + buffer(buffer.length - (N - 1)) + case TrialType.LURE_BEFORE_TARGET if buffer.length > N => + buffer(buffer.length - N) + case _ => + alphabet.charAt(Random.nextInt(alphabet.length)).toString + }} + + } + // 4. Convert buffer to string and return it as result + buffer.mkString("") + } + + /** + * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). + * Random range: [1, remaining_trials] (both are inclusive) + * @return a trial type to be used to generate an item for current trial + */ + private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { + case rnd if rnd <= L1 => + L1 -= 1 + TrialType.LURE_BEFORE_TARGET + case rnd if rnd > L1 && rnd <= L1 + L2 => + L2 -= 1 + TrialType.LURE_AFTER_TARGET + case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => + T -= 1 + TrialType.TARGET + case _ => + D -= 1 + TrialType.DISTRACTOR + + } +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/Main.scala b/markov/src/main/scala/org/xcit/nback/markov/Main.scala new file mode 100644 index 0000000..fdcb58b --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/Main.scala @@ -0,0 +1,10 @@ +package org.xcit.nback.markov + +/** + * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. + */ +class Main extends App { + //TODO create a MarkovChain object or use the singleton + //TODO train to set transitions + //TODO benchmark +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala new file mode 100644 index 0000000..5694371 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala @@ -0,0 +1,39 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * Represents a simple markov chain + * TODO: must be extended to HMM (add emission probability) + */ +class MarkovChain(startState: State) { + val states: mutable.MutableList[State] = mutable.MutableList[State]() + + var currentState: State = startState + + //TODO + def next(): State = ??? + + //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble + + def totalTransitions(): Int = { + var total = 0 + states.foreach(total += _.transitions.size) + total + } + + /** + * Add a transition from "from" state to "to" state with a defined probability. + * @param from origin node + * @param to destination node + * @param probability transition probability + */ + def addTransition(from: State, to: State, probability: Double): Unit = + states + .find(_.label == from.label) + .map(s => + s.transitions += Transition(to, probability) + ) + + +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/State.scala b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala new file mode 100644 index 0000000..fbbd844 --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/State.scala @@ -0,0 +1,15 @@ +package org.xcit.nback.markov.models + +import scala.collection.mutable + +/** + * A Single state with a label in Markov chain + * @param label A simple string label, representing the state and node + */ +class State(val label: String) { + + /** + * Keep track of transitions from this state to other states. + */ + val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() +} diff --git a/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala new file mode 100644 index 0000000..bc20a9e --- /dev/null +++ b/markov/src/main/scala/org/xcit/nback/markov/models/Transition.scala @@ -0,0 +1,8 @@ +package org.xcit.nback.markov.models + +/** + * A Single transition in Markov chain graph. It is stored in "from" node. + * @param to the ending node of the edge + * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). + */ +case class Transition(to: State, probability: Double = 0.0) diff --git a/markov/src/test/scala/ThreeBackBenchmark.scala b/markov/src/test/scala/ThreeBackBenchmark.scala new file mode 100644 index 0000000..0c7dad9 --- /dev/null +++ b/markov/src/test/scala/ThreeBackBenchmark.scala @@ -0,0 +1,7 @@ + +/** + * TODO Benchmark 3-back simple sequence generator + */ +class ThreeBackBenchmark { + +} diff --git a/project/build.properties b/project/build.properties deleted file mode 100644 index e71780d..0000000 --- a/project/build.properties +++ /dev/null @@ -1 +0,0 @@ -sbt.version = 1.2.6 \ No newline at end of file diff --git a/project/plugins.sbt b/project/plugins.sbt deleted file mode 100644 index 0f102c4..0000000 --- a/project/plugins.sbt +++ /dev/null @@ -1 +0,0 @@ -//addSbtPlugin("com.artima.supersafe" % "sbtplugin" % "1.1.3") diff --git a/py/.editorconfig b/py/.editorconfig deleted file mode 100644 index 5345e9e..0000000 --- a/py/.editorconfig +++ /dev/null @@ -1,6 +0,0 @@ -[*] -charset=utf-8 -end_of_line=lf -insert_final_newline=true -indent_style=space -indent_size=4 diff --git a/py/.vscode/settings.json b/py/.vscode/settings.json deleted file mode 100644 index f776680..0000000 --- a/py/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - 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-class EvenRandomGenerator: - """Generate even random sequences according to a predefined TL ration (Ralph, 2014)""" - - def __init__(self, choices, trials=64, tl=1): - self.tl, self.trials, self.choices = tl, trials, choices - - def generate(self): - seq = self._generate_initial_sequence() - return self._optimize_sequence(seq) - - def _generate_initial_sequence(self): - """ - Generates initial sequence of items based on choices and number of desired trials. - In EvenRandom sequences, all stimuli have same number of appearances. - """ - num_of_each_choice = int(self.trials / len(self.choices)) - seq = [] - for c in self.choices: - seq.append([c for t in range(num_of_each_choice)]) - - # if it's too short, add some new items - if len(seq) < self.trials: - seq += [self.choices[-1] for t in range(self.trials-len(seq))] - - return seq - - def _optimize_sequence(self, seq): - """Optimize a sequence based on a desired tl ratio""" - # TODO optimize sequence according to the fitness function w/ Branch&Bound or evolutionary algorithms. - return seq - - @staticmethod - def calculate_tl_ratio(seq): - """Calculates the T:L ratio of a sequence.""" - # TODO - targets = 0 - for index, item in seq: - if item == seq[index-2]: - targets += 1 - return 1.0 diff --git a/py/main.py b/py/main.py deleted file mode 100644 index 84f16d3..0000000 --- a/py/main.py +++ /dev/null @@ -1,5 +0,0 @@ -import requests - -response = requests.get('https://httpbin.org/ip') - -print('Testing connection... Your IP is %s.' % response.json()['origin']) \ No newline at end of file diff --git a/py/skewed_random_generator.py b/py/skewed_random_generator.py deleted file mode 100644 index 5cae6e8..0000000 --- a/py/skewed_random_generator.py +++ /dev/null @@ -1,50 +0,0 @@ -import logging -import random - -class SkewedRandomGenerator: - """Generates random sequence of stimuli for the n-back task. Implementation is based on Ralph (2014).""" - - seq = [] - - def __init__(self, - N = 2, - trials = 100, # Number of total trials - alphabet=['A','B','C','D','E','F'], - T = 20, # Number of targets - L1 = 10, # Number of lures (foil) similar to the (N+1)-back - L2 = 10 # Number of lures (foil) similar to the (N-1)-back - ): - self.N, self.alphabet, self.trials, self.T, self.L1, self.L2 = N, alphabet, trials, T, L1, L2 - self.D = trials - T - L1 - L2 - - def generate(self) -> list: - trial = 1 - self.seq = [] - while trial <= self.trials: - self.seq += self.random_stimulus(trial) - trial += 1 - return self.seq - - def random_stimulus(self, trial): - rnd = random.randint(1, self.trials - trial + 1) - T, L1, L2 = self.T, self.L1, self.L2 - if rnd <= T and len(self.seq) >= self.N: - self.T -= 1 - return self.seq[-self.N] - elif T < rnd <= T + L1 and len(self.seq) >= self.N+1: - self.L1 -= 1 - return self.seq[-(self.N+1)] - elif T + L1 < rnd <= T + L1 + L2 and len(self.seq) >= self.N-1: - self.L2 -= 1 - return self.seq[-(self.N-1)] - - # distract - self.D -= 1 - alphabet = [item for item in self.alphabet if item not in self.seq[-self.N-1:-self.N+1]] - return random.choice(alphabet) - - -if __name__ == '__main__': - generator = SkewedRandomGenerator() - seq = generator.generate() - print('Skewed Random Sequence: %s' % ''.join(seq)) diff --git a/run_tests.py b/run_tests.py new file mode 100644 index 0000000..1ab5567 --- /dev/null +++ b/run_tests.py @@ -0,0 +1,4 @@ +from tests.nb_gm_004_bm import run as nb_gm_004_bm + +nb_gm_004_bm() + diff --git a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala deleted file mode 100644 index 021ea42..0000000 --- a/src/main/scala/org/xcit/nback/generators/EvenSequenceGenerator.scala +++ /dev/null @@ -1,34 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable -import scala.util.Random - -/** - * Generate uniformly random alphanumeric string of size N, with target item evenly distributed. - * Reference: Ralph2014 - * - * @param alphabet All allowed alphabets (default is "BCDEFGJKLMNQRSQVWXYZ" excluding target and similar - * characters). Default alphabet contains 20 characters. - * @param target target item (default is 'A'). - */ -class EvenSequenceGenerator(alphabet: String = "BCDEFGJKLMNQRSQVWXYZ", target: Char = 'A') extends SequenceGenerator { - /** - * Generate the actual sequence as a string, takes only the length of desired sequence (num of trials) - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 64): String = { - var results = mutable.ListBuffer[String]() - val items = List.range(0, trials) - - // decide if target or non-target with 50/50 chance. - //TODO change probability according to a new class param - if (Random.nextBoolean) - results += target.toString - else - items.foreach( - results += alphabet.charAt(Random.nextInt(alphabet.length)).toString - ) - results.mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala deleted file mode 100644 index d10e633..0000000 --- a/src/main/scala/org/xcit/nback/generators/MarkovChainSequenceGenerator.scala +++ /dev/null @@ -1,6 +0,0 @@ -package org.xcit.nback.generators - -//TODO -class MarkovChainSequenceGenerator { - -} diff --git a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala deleted file mode 100644 index 8488984..0000000 --- a/src/main/scala/org/xcit/nback/generators/RandomSequenceGenerator.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.generators - -import scala.util.Random - -class RandomSequenceGenerator(N: Int) extends SequenceGenerator { - /** - * Generate simple alphanumeric string of size N - * - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(trials: Int = 0): String = { - Random.alphanumeric.take(trials).mkString("") - } -} diff --git a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala deleted file mode 100644 index 9cb0604..0000000 --- a/src/main/scala/org/xcit/nback/generators/SequenceGenerator.scala +++ /dev/null @@ -1,28 +0,0 @@ -package org.xcit.nback.generators - -/** - * Companion object and buiilders interface for Strategy pattern of the sequence generators. - * Params: - * "n": The "n" property in n-back (N items back must match the current stimuli). - * "offline": if it should generate the whole sequence at once of use MDP to consider rewards with reinforcement - * learning methods. - * - */ -object SequenceGenerator { - def random(N: Int = 3, trials: Int = 0): String = new RandomSequenceGenerator(N).generate(trials) - def even(N: Int = 3, trials: Int = 0, alphabet: String = "bcdg", target: Char = 'a'): String = new EvenSequenceGenerator().generate(trials) - def skewed() = new SkewedSequenceGenerator(T = 24, D = 32, L1 = 4, L2 = 4).generate(64) -} - -/** - * Generic n-back class to generate a sequence of n-back items with HMM. - */ -trait SequenceGenerator { - - /** - * Generate simple alphanumeric string of size N - * @param trials number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - def generate(trials: Int = 0): String -} diff --git a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala b/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala deleted file mode 100644 index 3549506..0000000 --- a/src/main/scala/org/xcit/nback/generators/SkewedSequenceGenerator.scala +++ /dev/null @@ -1,89 +0,0 @@ -package org.xcit.nback.generators - -import scala.collection.mutable.ListBuffer -import scala.util.Random - -/** - * Reference: Ralph2014 - Appendix A - * - * @param alphabet Alphabet used to generate the sequence, excluding the target item - * @param target Target item. It must not be included in [[alphabet]]. - * @param N The set size of stimuli to remember (n in n-back). Default is 3. - * @param T Number of target trials - * @param D Number of non-matching distractor trials. - * @param L1 Number of pre-lure trials; new trial matches with n-1 trial (pre-trial match). - * @param L2 Number of post-lure trials; trial matches with n+1 trial (post-trial match). - */ -class SkewedSequenceGenerator( - alphabet: String = "ABCDEFGH", // it's also called pool in ralph2014 - target: Char = 'A', - N: Int = 3, - T: Int = 24, - D: Int = 32, - L1: Int = 4, - L2: Int = 4) - extends SequenceGenerator { - - - val trials = T + D + L1 + L2 - - /** - * Types of each trial (L1, L2, T, or D). - */ - private object TrialType extends Enumeration { - val LURE_BEFORE_TARGET, LURE_AFTER_TARGET, TARGET, DISTRACTOR = Value - } - - /** - * Ignores trials. Trials' value is defined by N+T+D+L1+L2 - * @param t number of items in n-back sequence. - * @return string of size "trials" with random alphanumeric characters. - */ - override def generate(t: Int): String = { - // 1. Init buffer with empty list of items :-). Why am I explaining this? - var buffer = ListBuffer[String]() - - var trial = 0 - - while (trial < trials) { - trial += 1 - - // 2. For each trial, generate a random type (L1, L2, T, or D) - // 3. Based on the generated type, generate the item and append it to the buffer - buffer += {nextTrialType(trials-trial) match { - case TrialType.LURE_BEFORE_TARGET if buffer.length > N + 1 => - buffer(buffer.length - (N + 2)) - case TrialType.TARGET if buffer.length > N => - buffer(buffer.length - (N - 1)) - case TrialType.LURE_BEFORE_TARGET if buffer.length > N => - buffer(buffer.length - N) - case _ => - alphabet.charAt(Random.nextInt(alphabet.length)).toString - }} - - } - // 4. Convert buffer to string and return it as result - buffer.mkString("") - } - - /** - * Defines next trial types randomly. It returns L1, L2, T, or D (Ralph2014). - * Random range: [1, remaining_trials] (both are inclusive) - * @return a trial type to be used to generate an item for current trial - */ - private def nextTrialType(remainingTrials: Int): TrialType.Value = { Random.nextInt(remainingTrials + 1) + 1 } match { - case rnd if rnd <= L1 => - L1 -= 1 - TrialType.LURE_BEFORE_TARGET - case rnd if rnd > L1 && rnd <= L1 + L2 => - L2 -= 1 - TrialType.LURE_AFTER_TARGET - case rnd if rnd > L1 + L2 && rnd <= L1 + L2 + T => - T -= 1 - TrialType.TARGET - case _ => - D -= 1 - TrialType.DISTRACTOR - - } -} diff --git a/src/main/scala/org/xcit/nback/markov/Main.scala b/src/main/scala/org/xcit/nback/markov/Main.scala deleted file mode 100644 index fdcb58b..0000000 --- a/src/main/scala/org/xcit/nback/markov/Main.scala +++ /dev/null @@ -1,10 +0,0 @@ -package org.xcit.nback.markov - -/** - * Default application runner to run some benchmarks and demos. Use `sbt test` for the actual bechmarks. - */ -class Main extends App { - //TODO create a MarkovChain object or use the singleton - //TODO train to set transitions - //TODO benchmark -} diff --git a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala b/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala deleted file mode 100644 index 5694371..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/MarkovChain.scala +++ /dev/null @@ -1,39 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * Represents a simple markov chain - * TODO: must be extended to HMM (add emission probability) - */ -class MarkovChain(startState: State) { - val states: mutable.MutableList[State] = mutable.MutableList[State]() - - var currentState: State = startState - - //TODO - def next(): State = ??? - - //def currentProbability(): Double = currentState.transitions.size.toDouble / totalTransitions().toDouble - - def totalTransitions(): Int = { - var total = 0 - states.foreach(total += _.transitions.size) - total - } - - /** - * Add a transition from "from" state to "to" state with a defined probability. - * @param from origin node - * @param to destination node - * @param probability transition probability - */ - def addTransition(from: State, to: State, probability: Double): Unit = - states - .find(_.label == from.label) - .map(s => - s.transitions += Transition(to, probability) - ) - - -} diff --git a/src/main/scala/org/xcit/nback/markov/models/State.scala b/src/main/scala/org/xcit/nback/markov/models/State.scala deleted file mode 100644 index fbbd844..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/State.scala +++ /dev/null @@ -1,15 +0,0 @@ -package org.xcit.nback.markov.models - -import scala.collection.mutable - -/** - * A Single state with a label in Markov chain - * @param label A simple string label, representing the state and node - */ -class State(val label: String) { - - /** - * Keep track of transitions from this state to other states. - */ - val transitions: mutable.MutableList[Transition] = mutable.MutableList[Transition]() -} diff --git a/src/main/scala/org/xcit/nback/markov/models/Transition.scala b/src/main/scala/org/xcit/nback/markov/models/Transition.scala deleted file mode 100644 index bc20a9e..0000000 --- a/src/main/scala/org/xcit/nback/markov/models/Transition.scala +++ /dev/null @@ -1,8 +0,0 @@ -package org.xcit.nback.markov.models - -/** - * A Single transition in Markov chain graph. It is stored in "from" node. - * @param to the ending node of the edge - * @param probability the probability of this transition from starting node to the ending node (0.0 <= p <= 1.0). - */ -case class Transition(to: State, probability: Double = 0.0) diff --git a/src/test/scala/ThreeBackBenchmark.scala b/src/test/scala/ThreeBackBenchmark.scala deleted file mode 100644 index 0c7dad9..0000000 --- a/src/test/scala/ThreeBackBenchmark.scala +++ /dev/null @@ -1,7 +0,0 @@ - -/** - * TODO Benchmark 3-back simple sequence generator - */ -class ThreeBackBenchmark { - -} diff --git a/tests/benchmark_diagrams.py b/tests/benchmark_diagrams.py new file mode 100644 index 0000000..8fa448e --- /dev/null +++ b/tests/benchmark_diagrams.py @@ -0,0 +1,159 @@ +import pandas as pd +import numpy as np +from matplotlib import pyplot as plt + +import benchmarks.common as common + + +def tlratio(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2,ignore_index=True) + stats = [] + for trials in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == trials) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == trials) + targets2 = data[alg2].targets if alg2.shape[0] > 0 else np.nan + targets4 = data[alg4].targets if alg4.shape[0] > 0 else np.nan + lures2 = data[alg2].lures if alg2.shape[0] > 0 else np.nan + lures4 = data[alg4].lures if alg4.shape[0] > 0 else np.nan + stats.append([trials, (targets2/lures2).mean(), (targets4/lures4).mean()]) + stats = pd.DataFrame(stats, columns=['trials', 'tl2', 'tl4']) #.dropna(subset=['skewness']) + + plt.style.use('ggplot') + + plt.ylim(bottom=0, top=30) + plt.scatter(stats.trials, stats.tl2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl2[idx], 1)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.tl4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.tl4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.tl4[idx], 2)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('T:L Ratio') + plt.ylabel('T:L Ratio') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_tlratio.png', bbox_inches='tight') + plt.show() + + +def time_per_trial(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for t in range(common.trials_range[1]): + alg2 = (data.alg == 'nb_gm_002') & (data.trials == t) + alg4 = (data.alg == 'nb_gm_004') & (data.trials == t) + time2 = data[alg2].time.mean() * 1000 if alg2.shape[0] > 0 else np.nan + time4 = data[alg4].time.mean() * 1000 if alg4.shape[0] > 0 else np.nan + stats.append([t, time2, time4]) + stats = pd.DataFrame(stats, columns=['trials', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.trials, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time2) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time2[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='blue') + + plt.scatter(stats.trials, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + idx = np.isfinite(stats.trials) & np.isfinite(stats.time4) + p = np.poly1d(np.polyfit(stats.trials[idx], stats.time4[idx], 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('Trials') + + plt.legend() + + plt.savefig(f'benchmarks/results/2v4_time_trials.png', bbox_inches='tight') + plt.show() + +def time_profiles(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 8): + alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + time2 = data[alg2].time.mean() * 1000 + time4 = data[alg4].time.mean() * 1000 + stats.append([ni, time2, time4]) + stats = pd.DataFrame(stats, columns=['n', 'time2', 'time4']) #.dropna(subset=['skewness']) + + print(stats) + plt.style.use('ggplot') + plt.scatter(stats.n, stats.time2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.time2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + plt.scatter(stats.n, stats.time4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.time4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Time Profile') + plt.ylabel('Time (ms)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_time_n.png', bbox_inches='tight') + plt.show() + +def skewness(): + data = pd.read_csv('benchmarks/results/nb_gm_004_profile.csv') + data2 = pd.read_csv('benchmarks/results/nb_gm_002_profile.csv') + + data = data.append(data2) + stats = [] + for ni in range(2, 9): + all_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) + skewed_alg2 = (data.alg == 'nb_gm_002') & (data.n == ni) & data.skewed + all_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) + skewed_alg4 = (data.alg == 'nb_gm_004') & (data.n == ni) & data.skewed + num_of_sequences2 = data[all_alg2].shape[0] + skewed_sequences2 = data[skewed_alg2].shape[0] + num_of_sequences4 = data[all_alg4].shape[0] + skewed_sequences4 = data[skewed_alg4].shape[0] + skewness2 = skewed_sequences2 * 100.0 / num_of_sequences2 if (num_of_sequences2>0) else 0 + skewness4 = skewed_sequences4 * 100.0 / num_of_sequences4 if (num_of_sequences4>0) else 0 + stats.append([ni, skewness2, skewness4]) + stats = pd.DataFrame(stats, columns=['n', 'skewness2', 'skewness4']) #.dropna(subset=['skewness']) + + + plt.style.use('ggplot') + plt.scatter(stats.n, stats.skewness2, color='blue', alpha=0.2, label='nb_gm_002') + p = np.poly1d(np.polyfit(stats.n, stats.skewness2, 3)) + plt.plot(stats.n, p(stats.n), color='blue') + + + plt.scatter(stats.n, stats.skewness4, color='red', alpha=0.2, label='nb_gm_004') + p = np.poly1d(np.polyfit(stats.n, stats.skewness4, 3)) + plt.plot(stats.n, p(stats.n), color='red') + + # plt.title('Skewness') + plt.ylabel('Skewed Blocks (%)') + plt.xlabel('N') + + plt.legend() + + plt.savefig(f'benchmarks/results/2vs4_skewness.png', bbox_inches='tight') + plt.show() + +if __name__ == "__main__": + tlratio() + skewness() + time_profiles() + time_per_trial() diff --git a/tests/benchmark_skewness.py b/tests/benchmark_skewness.py new file mode 100644 index 0000000..f468b4d --- /dev/null +++ b/tests/benchmark_skewness.py @@ -0,0 +1,97 @@ +import random +import heapq +import csv + +# Common parameters +alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'] +trials_range = (10, 40) +n = 3 +sample_size = 100 + + +def to_benchmark_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [str(ralph_skewed)] + +def benchmark_nb_gm_001(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_001') + + +def benchmark_nb_gm_002(filename): + import generators.nb_gm_002 as nb_gm_002 + + generator = nb_gm_002.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + # print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_002') + + +def benchmark_nb_gm_003(filename): + import generators.nb_gm_003 as nb_gm_003 + + generator = nb_gm_003.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + print(f"sequence {i}/{sample_size}: {trials} trials") + seq = generator.generate(trials) + writer.writerow(to_benchmark_csv_row(i, seq)) + show_skweness_diagram(filename, alphabetic_choices, 'nb_gm_003') + + +def show_skweness_diagram(filename, choices, title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + print(filename) + data = pd.read_csv(filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) #.dropna(subset=['skewness']) + #print(stats.trials) + #plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'{title}.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + benchmark_nb_gm_003('../benchmarks/nb_gm_003_2back.csv') diff --git a/tests/common.py b/tests/common.py new file mode 100644 index 0000000..e40c0df --- /dev/null +++ b/tests/common.py @@ -0,0 +1,27 @@ + + +# Common benchmark parameters +choices = alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F'] +trials_range = (10, 65) +n = 4 +sample_size = 100 + + +def count_targets_and_lures(seq, n): + mask = 'D'*n + for index in range(n, len(seq)): + if seq[index] == seq[index - n]: + mask += 'T' + elif seq[index] in seq[index - n - 1:index - n + 1]: + mask += 'L' + else: + mask += 'D' + return mask.count('T'), mask.count('L') + + +def skewness(seq, choices): + import heapq + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return ralph_skewed diff --git a/tests/nb_gm_001_bm.py b/tests/nb_gm_001_bm.py new file mode 100644 index 0000000..54f6cb3 --- /dev/null +++ b/tests/nb_gm_001_bm.py @@ -0,0 +1,75 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in alphabetic_choices] + ralph_skewed = sum(heapq.nlargest(int(len(alphabetic_choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq) , str(ralph_skewed)] + + +def benchmark(filename): + import generators.nb_gm_001 as nb_gm_001 + + generator = nb_gm_001.SequenceGenerator(alphabetic_choices, n, trials_range[0]) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + alphabetic_choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets / s.trials, axis=1) + plt.scatter(data.trials, data.targets_ratio, alpha=0.2) + plt.show() + +if __name__ == '__main__': + alg = 'nb_gm_001' + fn = f'results/{alg}_{n}back.csv' + benchmark(fn) + # skewness_diagram(fn, alg) + targets_ratio_diagram(fn, alg) diff --git a/tests/nb_gm_002_bm.py b/tests/nb_gm_002_bm.py new file mode 100644 index 0000000..c8af543 --- /dev/null +++ b/tests/nb_gm_002_bm.py @@ -0,0 +1,105 @@ +import heapq +import csv +import random + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [''.join(seq), str(ralph_skewed)] + + +def benchmark(filename): + from generators.nb_gm_002 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + seq = generator.generate(trials, int(trials/3), 0, 0) + print(f"sequence {i}/{sample_size}: {trials} trials") + writer.writerow(to_csv_row(i, seq)) + + +def skewness_diagram(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + # print(stats.trials) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def targets_ratio_diagram(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +import time +import numpy as np +import pandas as pd + +import benchmarks.common as common + +def profile(): + from generators.nb_gm_002 import SequenceGenerator + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, int(lures/2), int(lures/2)) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('benchmarks/results/nb_gm_002_profile.csv', sep=',', encoding='utf-8') + +if __name__ == '__main__': + alg = 'nb_gm_002' + fn = f'results/{alg}_{n}back.csv' + profile() diff --git a/tests/nb_gm_003_bm.py b/tests/nb_gm_003_bm.py new file mode 100644 index 0000000..fa6c19a --- /dev/null +++ b/tests/nb_gm_003_bm.py @@ -0,0 +1,114 @@ +import heapq +import csv +import random +import time + +from benchmarks.common import * + + +def to_csv_row(sample_index, seq, time_per_block): + trials = len(seq) + freqs = [float(seq.count(c)) for c in choices] + ralph_skewed = sum(heapq.nlargest(int(len(choices) / 2), freqs)) > (trials * 2 / 3) + return [str(sample_index)] + freqs + [time_per_block, ''.join(seq), str(ralph_skewed)] + + +def benchmark_skewness(filename): + from generators.nb_gm_003 import SequenceGenerator + + generator = SequenceGenerator(choices, n) + + # TODO store timing details + with open(filename, mode='w') as benchmark_results_file: + writer = csv.writer(benchmark_results_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) + writer.writerow(['index'] + choices + ['time_per_block', 'seq', 'ralph_skewed']) + for i in range(sample_size): + trials = random.randint(trials_range[0], trials_range[1]) + targets = trials / 3 + t = time.time() + seq = generator.generate(trials, targets) + t = time.time() - t + print(f"sequence {i}/{sample_size}: {trials} trials, took {t}s.") + writer.writerow(to_csv_row(i, seq, t)) + plot_skewness(fn, 'nb_gm_003') + + +def plot_skewness(csv_filename, figure_title): + import pandas as pd + import numpy as np + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + max_trials = data['trials'].max() + min_trials = data['trials'].min() + stats = [] + for sequence_length in range(int(min_trials), int(max_trials) + 1): + num_of_sequences = np.sum(data[data.trials == sequence_length].trials) + skewed_sequences = np.sum(data[np.logical_and(data.trials == sequence_length, data.ralph_skewed)].trials) + if num_of_sequences == 0: + continue + skewness = skewed_sequences * 100.0 / num_of_sequences + stats.append([sequence_length, skewness]) + stats = pd.DataFrame(stats, columns=['trials', 'skewness']) # .dropna(subset=['skewness']) + plt.ylim([0, 110]) + plt.scatter(stats.trials, stats.skewness, alpha=0.1) + p = np.poly1d(np.polyfit(stats.trials, stats.skewness, 3)) + plt.plot(stats.trials, p(stats.trials), color='red') + plt.title(figure_title) + plt.ylabel('skewed blocks (%)') + plt.xlabel('# of trials') + plt.savefig(f'results/{figure_title}.png', bbox_inches='tight') + plt.show() + + +def plot_targets_ratio(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['targets'] = data.apply(lambda s: count_targets_and_lures(s.seq, n)[0], axis=1) + data['targets_ratio'] = data.apply(lambda s: s.targets * 100 / s.trials, axis=1) + plt.title(f"{figure_title} - expected targets ratio = 33%") + plt.ylabel('targets (%)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.targets_ratio, alpha=0.3) + plt.savefig(f'results/{figure_title}_targets_ratio.png', bbox_inches='tight') + plt.show() + + +def benchmark_targets_ratio(): + pass + +def benchmark_chunking(): + pass + + +def benchmark_n(): + pass + + +def plot_timing(csv_filename, figure_title): + import pandas as pd + from matplotlib import pyplot as plt + data = pd.read_csv(csv_filename) + data['trials'] = data[choices].sum(axis=1) + data['time_per_trial'] = data.apply(lambda s: s.time_per_block / s.trials, axis=1) + plt.style.use('ggplot') + plt.title(f"{figure_title} - average time to generate a trial") + plt.ylabel('time (s)') + plt.xlabel('# of trials') + plt.scatter(data.trials, data.time_per_trial, alpha=0.5) + + # draw fitted curve + # import numpy as np + # p = np.poly1d(np.polyfit(data.trials, data.time_per_trial, 3)) + # plt.plot(data.trials, p(data.trials), color='red') + + plt.savefig(f'results/{figure_title}_timing.png', bbox_inches='tight') + plt.show() + + +if __name__ == '__main__': + alg = 'nb_gm_003' + fn = f'results/{alg}_{n}back.csv' + benchmark_skewness(fn) diff --git a/tests/nb_gm_004_bm.py b/tests/nb_gm_004_bm.py new file mode 100644 index 0000000..b4ad4a8 --- /dev/null +++ b/tests/nb_gm_004_bm.py @@ -0,0 +1,26 @@ +import time +import numpy as np +import pandas as pd + +import tests.common as common +from generators.nb_gm_004 import SequenceGenerator + +def run(): + + res = [] + + for s in range(common.sample_size): + trials = np.random.randint(common.trials_range[0], common.trials_range[1]) + targets = int(trials / 3) + lures = int(targets / 6) # tl_ratio = 2.0 + n = np.random.randint(2, 8) + gen = SequenceGenerator(common.choices, n) + st = time.time() + seq = gen.generate(trials, targets, lures) + st = time.time() - st + t, lu = common.count_targets_and_lures(seq, n) + skewed = common.skewness(seq, common.choices) + res.append(['nb_gm_004', n, trials, st, t, lu, skewed, ''.join(seq)]) + print(f"sequence #{s+1} generated") + res_df = pd.DataFrame(res, columns=['alg', 'n', 'trials', 'time', 'targets', 'lures', 'skewed', 'sequence']) + res_df.to_csv('tests/results/nb_gm_004_profile.csv', sep=',', encoding='utf-8') diff --git a/tests/results/2v4_time_trials.png b/tests/results/2v4_time_trials.png new file mode 100644 index 0000000..9be91b4 --- /dev/null +++ b/tests/results/2v4_time_trials.png Binary files differ diff --git a/tests/results/2vs4_skewness.png b/tests/results/2vs4_skewness.png new file mode 100644 index 0000000..a488e1f --- /dev/null +++ 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+210,87.0,0.0,0.0,88.0,1.0,0.0,0.0,0.0,EDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +211,0.0,0.0,12.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCC,True +212,0.0,0.0,0.0,66.0,0.0,65.0,0.0,0.0,DFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +213,1.0,0.0,0.0,0.0,0.0,21.0,22.0,0.0,AGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFG,True +214,74.0,73.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +215,0.0,5.0,0.0,0.0,6.0,0.0,0.0,1.0,HEBEBEBEBEBE,True +216,0.0,1.0,0.0,0.0,0.0,53.0,0.0,54.0,BHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +217,70.0,0.0,0.0,0.0,0.0,70.0,0.0,0.0,AFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +218,0.0,0.0,0.0,0.0,0.0,0.0,36.0,35.0,GGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +219,0.0,90.0,90.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +220,0.0,0.0,0.0,0.0,0.0,0.0,37.0,38.0,HHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +221,0.0,0.0,44.0,0.0,0.0,1.0,44.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +222,0.0,0.0,0.0,67.0,67.0,0.0,0.0,1.0,HDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True 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+409,0.0,0.0,72.0,1.0,0.0,0.0,72.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +410,55.0,0.0,1.0,0.0,0.0,0.0,55.0,0.0,CAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +411,0.0,59.0,0.0,0.0,0.0,60.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +412,61.0,0.0,0.0,61.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +413,0.0,1.0,0.0,75.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +414,0.0,53.0,0.0,0.0,0.0,0.0,52.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +415,0.0,0.0,16.0,0.0,1.0,0.0,0.0,15.0,ECHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +416,0.0,0.0,0.0,39.0,0.0,0.0,0.0,38.0,DHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +417,96.0,0.0,1.0,95.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +418,28.0,0.0,1.0,27.0,0.0,0.0,0.0,0.0,CADADADADADADADADADADADADADADADADADADADADADADADADADADADA,True +419,0.0,1.0,92.0,92.0,0.0,0.0,0.0,0.0,BCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +420,1.0,0.0,20.0,0.0,20.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECE,True +421,0.0,90.0,0.0,0.0,0.0,0.0,89.0,0.0,BBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBG,True +422,10.0,0.0,0.0,0.0,0.0,1.0,11.0,0.0,FGAGAGAGAGAGAGAGAGAGAG,True +423,0.0,0.0,0.0,74.0,73.0,1.0,0.0,0.0,FDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +424,0.0,0.0,127.0,0.0,0.0,0.0,1.0,0.0,GCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +425,1.0,9.0,0.0,0.0,0.0,9.0,0.0,0.0,AFBFBFBFBFBFBFBFBFB,True +426,0.0,0.0,84.0,0.0,0.0,0.0,0.0,84.0,HCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +427,33.0,0.0,0.0,34.0,0.0,0.0,0.0,1.0,HDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +428,1.0,30.0,0.0,30.0,0.0,0.0,0.0,0.0,ABDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +429,0.0,0.0,67.0,0.0,1.0,67.0,0.0,0.0,EFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +430,62.0,0.0,0.0,63.0,0.0,0.0,1.0,0.0,GDADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADADAD,True +431,1.0,9.0,9.0,0.0,0.0,0.0,0.0,0.0,ABCBCBCBCBCBCBCBCBC,True +432,15.0,0.0,0.0,0.0,0.0,0.0,14.0,0.0,AAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True +433,0.0,1.0,0.0,65.0,66.0,0.0,0.0,0.0,BEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +434,0.0,160.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +435,0.0,0.0,1.0,0.0,42.0,42.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +436,0.0,0.0,55.0,0.0,55.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +437,0.0,0.0,0.0,1.0,0.0,73.0,0.0,73.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +438,79.0,0.0,0.0,0.0,78.0,0.0,0.0,0.0,AAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +439,0.0,0.0,67.0,0.0,0.0,0.0,66.0,1.0,HCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +440,0.0,0.0,77.0,0.0,0.0,1.0,0.0,76.0,FCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +441,0.0,0.0,0.0,0.0,153.0,0.0,0.0,1.0,HEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE,True +442,0.0,88.0,88.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +443,0.0,0.0,0.0,20.0,22.0,0.0,0.0,0.0,EEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +444,41.0,0.0,42.0,0.0,0.0,0.0,1.0,0.0,GCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +445,0.0,0.0,0.0,47.0,0.0,46.0,0.0,1.0,HDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +446,1.0,0.0,0.0,0.0,86.0,0.0,0.0,87.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +447,56.0,56.0,0.0,0.0,0.0,0.0,0.0,1.0,HABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +448,0.0,0.0,0.0,0.0,11.0,0.0,0.0,10.0,EEHEHEHEHEHEHEHEHEHEH,True +449,0.0,0.0,0.0,0.0,0.0,1.0,92.0,92.0,FGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +450,0.0,0.0,0.0,6.0,5.0,1.0,0.0,0.0,FDEDEDEDEDED,True +451,66.0,1.0,67.0,0.0,0.0,0.0,0.0,0.0,BCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +452,0.0,0.0,0.0,13.0,0.0,1.0,12.0,0.0,FDGDGDGDGDGDGDGDGDGDGDGDGD,True +453,1.0,0.0,0.0,0.0,56.0,0.0,56.0,0.0,AEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +454,15.0,0.0,0.0,0.0,0.0,0.0,0.0,16.0,HAHAHAHAHAHAHAHAHAHAHAHAHAHAHAH,True +455,0.0,21.0,1.0,0.0,21.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBE,True +456,93.0,0.0,1.0,0.0,92.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +457,1.0,0.0,0.0,0.0,35.0,0.0,0.0,35.0,AHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +458,13.0,0.0,0.0,0.0,1.0,0.0,13.0,0.0,EAGAGAGAGAGAGAGAGAGAGAGAGAG,True +459,0.0,0.0,65.0,0.0,1.0,0.0,65.0,0.0,ECGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +460,0.0,0.0,95.0,1.0,0.0,95.0,0.0,0.0,DFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +461,15.0,0.0,0.0,0.0,1.0,0.0,0.0,15.0,EHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +462,0.0,0.0,198.0,0.0,1.0,0.0,0.0,0.0,ECCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +463,84.0,84.0,0.0,0.0,1.0,0.0,0.0,0.0,EABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +464,0.0,0.0,0.0,0.0,0.0,60.0,0.0,61.0,HFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +465,0.0,179.0,0.0,1.0,0.0,0.0,0.0,0.0,DBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +466,1.0,0.0,90.0,0.0,89.0,0.0,0.0,0.0,ACECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +467,0.0,35.0,0.0,0.0,0.0,34.0,0.0,0.0,BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +468,0.0,0.0,0.0,1.0,7.0,0.0,0.0,7.0,DHEHEHEHEHEHEHE,True +469,0.0,0.0,0.0,0.0,92.0,0.0,91.0,0.0,EEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +470,0.0,0.0,46.0,0.0,0.0,1.0,46.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True +471,0.0,0.0,0.0,0.0,0.0,1.0,158.0,0.0,FGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +472,1.0,0.0,0.0,0.0,0.0,58.0,0.0,59.0,AHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +473,0.0,0.0,6.0,1.0,0.0,0.0,6.0,0.0,DCGCGCGCGCGCG,True +474,0.0,0.0,0.0,0.0,0.0,98.0,0.0,97.0,FFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +475,0.0,87.0,0.0,0.0,0.0,0.0,0.0,85.0,BBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +476,0.0,0.0,33.0,0.0,0.0,0.0,1.0,33.0,GHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +477,45.0,0.0,0.0,0.0,46.0,0.0,0.0,0.0,EAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +478,0.0,0.0,0.0,77.0,0.0,0.0,75.0,0.0,DDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +479,73.0,1.0,73.0,0.0,0.0,0.0,0.0,0.0,BACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACAC,True +480,0.0,1.0,0.0,0.0,37.0,37.0,0.0,0.0,BEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +481,0.0,92.0,93.0,0.0,0.0,1.0,0.0,0.0,FCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +482,0.0,0.0,0.0,1.0,0.0,0.0,0.0,24.0,DHHHHHHHHHHHHHHHHHHHHHHHH,True +483,25.0,0.0,0.0,1.0,0.0,25.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +484,0.0,0.0,0.0,0.0,0.0,37.0,0.0,36.0,FHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +485,21.0,0.0,0.0,1.0,0.0,20.0,0.0,0.0,DAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +486,0.0,35.0,0.0,36.0,0.0,0.0,0.0,1.0,HDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +487,0.0,0.0,1.0,0.0,97.0,98.0,0.0,0.0,CFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +488,0.0,93.0,0.0,0.0,0.0,1.0,0.0,94.0,FHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +489,0.0,1.0,0.0,93.0,0.0,0.0,93.0,0.0,BGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGD,True +490,0.0,0.0,0.0,70.0,0.0,0.0,72.0,0.0,GGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +491,86.0,0.0,0.0,0.0,1.0,86.0,0.0,0.0,EFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +492,0.0,65.0,1.0,0.0,0.0,65.0,0.0,0.0,CBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +493,0.0,0.0,0.0,69.0,0.0,0.0,0.0,1.0,HDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +494,0.0,0.0,144.0,1.0,0.0,0.0,0.0,0.0,DCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +495,0.0,45.0,0.0,0.0,0.0,1.0,0.0,0.0,FBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True 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+599,16.0,0.0,16.0,0.0,0.0,0.0,0.0,0.0,ACACACACACACACACACACACACACACACAC,True +600,0.0,21.0,0.0,22.0,0.0,0.0,0.0,0.0,DBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +601,70.0,71.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +602,0.0,0.0,0.0,1.0,0.0,0.0,53.0,0.0,DGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +603,45.0,0.0,0.0,0.0,0.0,45.0,0.0,0.0,FAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +604,0.0,1.0,56.0,0.0,0.0,0.0,56.0,0.0,BGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +605,0.0,1.0,0.0,0.0,0.0,0.0,0.0,195.0,BHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True 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+611,0.0,0.0,86.0,0.0,88.0,0.0,0.0,0.0,EECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +612,1.0,0.0,0.0,0.0,14.0,0.0,0.0,14.0,AEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +613,0.0,0.0,35.0,0.0,0.0,35.0,1.0,0.0,GCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCF,True +614,0.0,0.0,1.0,0.0,43.0,43.0,0.0,0.0,CEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +615,0.0,0.0,0.0,0.0,0.0,1.0,67.0,66.0,FGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +616,0.0,27.0,0.0,0.0,26.0,0.0,1.0,0.0,GBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +617,0.0,88.0,1.0,87.0,0.0,0.0,0.0,0.0,CBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +618,0.0,41.0,0.0,0.0,0.0,41.0,1.0,0.0,GFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +619,0.0,27.0,27.0,0.0,0.0,0.0,0.0,0.0,CBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +620,1.0,0.0,20.0,20.0,0.0,0.0,0.0,0.0,ADCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +621,0.0,0.0,1.0,24.0,24.0,0.0,0.0,0.0,CEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +622,1.0,0.0,0.0,0.0,55.0,55.0,0.0,0.0,AEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +623,1.0,0.0,0.0,0.0,26.0,0.0,26.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +624,0.0,0.0,15.0,0.0,0.0,0.0,0.0,13.0,CCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +625,0.0,0.0,1.0,67.0,67.0,0.0,0.0,0.0,CDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +626,0.0,0.0,65.0,0.0,0.0,1.0,0.0,64.0,FCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHC,True +627,0.0,0.0,0.0,0.0,89.0,1.0,90.0,0.0,FGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +628,0.0,0.0,0.0,0.0,1.0,0.0,51.0,0.0,EGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +629,0.0,0.0,41.0,0.0,0.0,40.0,0.0,0.0,CFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFCFC,True +630,0.0,0.0,93.0,0.0,0.0,0.0,1.0,0.0,GCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC,True +631,0.0,53.0,1.0,0.0,0.0,53.0,0.0,0.0,CBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +632,0.0,0.0,0.0,14.0,0.0,0.0,0.0,15.0,HHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +633,0.0,29.0,0.0,0.0,0.0,0.0,28.0,0.0,BGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +634,0.0,66.0,0.0,0.0,0.0,1.0,66.0,0.0,FGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +635,0.0,0.0,62.0,62.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +636,0.0,31.0,32.0,0.0,1.0,0.0,0.0,0.0,ECBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +637,0.0,0.0,0.0,0.0,0.0,0.0,48.0,49.0,HGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +638,1.0,0.0,0.0,0.0,0.0,0.0,54.0,53.0,AGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +639,59.0,0.0,1.0,0.0,59.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +640,0.0,0.0,0.0,0.0,1.0,0.0,27.0,27.0,EGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGH,True +641,0.0,0.0,0.0,23.0,24.0,0.0,0.0,0.0,EDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +642,0.0,0.0,0.0,91.0,0.0,0.0,91.0,0.0,DGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDGDG,True +643,0.0,0.0,0.0,0.0,48.0,49.0,0.0,1.0,HFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEF,True +644,14.0,0.0,0.0,0.0,0.0,14.0,1.0,0.0,GAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +645,0.0,96.0,0.0,0.0,1.0,0.0,0.0,96.0,EHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHB,True +646,0.0,0.0,0.0,50.0,48.0,0.0,0.0,0.0,DDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDED,True +647,0.0,0.0,0.0,99.0,0.0,99.0,0.0,0.0,FDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFDFD,True +648,49.0,0.0,1.0,0.0,0.0,0.0,0.0,48.0,CAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +649,0.0,0.0,52.0,0.0,1.0,0.0,53.0,0.0,EGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True 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+667,1.0,147.0,0.0,0.0,0.0,0.0,0.0,0.0,ABBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +668,0.0,0.0,97.0,0.0,97.0,0.0,0.0,1.0,HCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +669,0.0,0.0,1.0,0.0,0.0,0.0,53.0,52.0,CGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +670,0.0,0.0,94.0,0.0,96.0,0.0,0.0,0.0,EECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECE,True +671,99.0,0.0,1.0,0.0,98.0,0.0,0.0,0.0,CAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEA,True +672,68.0,0.0,0.0,0.0,0.0,0.0,67.0,1.0,HAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGA,True +673,0.0,0.0,0.0,26.0,27.0,0.0,1.0,0.0,GEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +674,31.0,0.0,0.0,0.0,32.0,0.0,0.0,1.0,HEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +675,0.0,0.0,0.0,0.0,42.0,0.0,41.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +676,0.0,0.0,50.0,0.0,0.0,0.0,1.0,50.0,GCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +677,0.0,25.0,0.0,24.0,0.0,0.0,0.0,0.0,BBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBD,True +678,0.0,0.0,0.0,0.0,1.0,10.0,9.0,0.0,EFGFGFGFGFGFGFGFGFGF,True +679,65.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,DAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA,True +680,0.0,23.0,0.0,0.0,0.0,0.0,23.0,1.0,HGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGBGB,True +681,0.0,1.0,58.0,0.0,0.0,0.0,57.0,0.0,BCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +682,0.0,0.0,0.0,0.0,0.0,68.0,1.0,68.0,GFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +683,0.0,0.0,0.0,0.0,96.0,0.0,96.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +684,1.0,0.0,0.0,0.0,66.0,0.0,66.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +685,0.0,0.0,0.0,0.0,0.0,1.0,0.0,21.0,FHHHHHHHHHHHHHHHHHHHHH,True +686,0.0,88.0,0.0,87.0,0.0,0.0,0.0,0.0,BDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDBDB,True +687,0.0,0.0,19.0,19.0,0.0,0.0,1.0,0.0,GDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +688,0.0,42.0,1.0,0.0,41.0,0.0,0.0,0.0,CBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEBEB,True +689,0.0,0.0,0.0,0.0,0.0,60.0,61.0,0.0,GGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +690,0.0,23.0,23.0,0.0,0.0,0.0,1.0,0.0,GBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +691,86.0,86.0,0.0,0.0,0.0,0.0,0.0,0.0,ABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABAB,True +692,35.0,35.0,0.0,0.0,0.0,1.0,0.0,0.0,FBABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABABA,True +693,57.0,0.0,0.0,0.0,0.0,58.0,1.0,0.0,GFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +694,0.0,0.0,30.0,30.0,1.0,0.0,0.0,0.0,EDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +695,19.0,18.0,0.0,1.0,0.0,0.0,0.0,0.0,DABABABABABABABABABABABABABABABABABABA,True +696,0.0,0.0,0.0,1.0,0.0,56.0,0.0,57.0,DHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFH,True +697,10.0,0.0,1.0,0.0,0.0,0.0,0.0,11.0,CHAHAHAHAHAHAHAHAHAHAH,True +698,0.0,0.0,89.0,0.0,88.0,0.0,1.0,0.0,GCECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +699,0.0,0.0,87.0,0.0,86.0,0.0,0.0,0.0,CECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +700,17.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,GAAAAAAAAAAAAAAAAA,True +701,0.0,0.0,66.0,65.0,0.0,0.0,1.0,0.0,GCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDC,True +702,0.0,0.0,1.0,0.0,0.0,0.0,123.0,0.0,CGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGG,True +703,0.0,118.0,0.0,0.0,1.0,0.0,0.0,0.0,EBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +704,0.0,0.0,0.0,0.0,0.0,0.0,0.0,132.0,HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH,True +705,0.0,0.0,0.0,0.0,0.0,23.0,1.0,23.0,GHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +706,0.0,0.0,0.0,0.0,6.0,5.0,0.0,0.0,EFEFEFEFEFE,True +707,18.0,0.0,0.0,16.0,0.0,0.0,0.0,0.0,AADADADADADADADADADADADADADADADADA,True +708,0.0,72.0,0.0,0.0,0.0,71.0,0.0,1.0,HBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFB,True +709,0.0,0.0,54.0,0.0,0.0,1.0,0.0,55.0,FHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +710,0.0,1.0,87.0,0.0,87.0,0.0,0.0,0.0,BECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECECEC,True +711,0.0,0.0,1.0,63.0,0.0,0.0,0.0,64.0,CHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDH,True +712,78.0,0.0,78.0,0.0,0.0,1.0,0.0,0.0,FCACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +713,0.0,80.0,0.0,0.0,0.0,81.0,0.0,1.0,HFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBF,True +714,0.0,1.0,0.0,0.0,0.0,0.0,40.0,39.0,BGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +715,0.0,0.0,7.0,0.0,6.0,0.0,0.0,0.0,CCECECECECECE,True +716,35.0,0.0,0.0,0.0,0.0,0.0,0.0,33.0,AAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA,True +717,0.0,0.0,0.0,1.0,73.0,0.0,0.0,72.0,DEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHE,True +718,0.0,0.0,90.0,0.0,0.0,1.0,89.0,0.0,FCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +719,1.0,0.0,0.0,67.0,0.0,0.0,0.0,66.0,ADHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHDHD,True +720,56.0,0.0,0.0,0.0,56.0,0.0,1.0,0.0,GAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAEAE,True +721,0.0,0.0,0.0,1.0,0.0,0.0,49.0,49.0,DHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +722,0.0,0.0,0.0,117.0,0.0,1.0,0.0,0.0,FDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +723,0.0,0.0,86.0,1.0,0.0,0.0,85.0,0.0,DCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True +724,0.0,0.0,31.0,0.0,0.0,0.0,0.0,30.0,CCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCHCH,True +725,1.0,0.0,0.0,0.0,98.0,0.0,98.0,0.0,AGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGE,True +726,1.0,84.0,84.0,0.0,0.0,0.0,0.0,0.0,ACBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +727,0.0,56.0,56.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCB,True +728,0.0,1.0,0.0,24.0,24.0,0.0,0.0,0.0,BDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDEDE,True +729,37.0,0.0,0.0,0.0,0.0,37.0,0.0,0.0,FAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +730,0.0,0.0,91.0,0.0,0.0,0.0,91.0,0.0,GCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGC,True 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+772,0.0,68.0,0.0,0.0,0.0,0.0,0.0,67.0,BBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBHBH,True +773,60.0,1.0,0.0,0.0,0.0,61.0,0.0,0.0,BFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAF,True +774,0.0,1.0,0.0,57.0,0.0,0.0,0.0,0.0,BDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD,True +775,0.0,78.0,0.0,0.0,1.0,0.0,0.0,0.0,EBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB,True +776,1.0,0.0,0.0,0.0,0.0,96.0,96.0,0.0,AGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGFGF,True +777,43.0,0.0,0.0,0.0,0.0,1.0,44.0,0.0,FGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG,True 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+989,93.0,0.0,92.0,0.0,0.0,0.0,0.0,1.0,HACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACACA,True +990,0.0,1.0,0.0,0.0,60.0,0.0,0.0,61.0,BHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEHEH,True +991,0.0,1.0,0.0,0.0,0.0,0.0,32.0,32.0,BHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHGHG,True +992,0.0,0.0,34.0,35.0,0.0,0.0,1.0,0.0,GDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCDCD,True +993,0.0,0.0,0.0,0.0,54.0,0.0,54.0,0.0,EGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEGEG,True +994,0.0,0.0,0.0,1.0,0.0,39.0,0.0,38.0,DFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHFHF,True +995,0.0,0.0,0.0,0.0,99.0,98.0,0.0,1.0,HEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFEFE,True +996,86.0,1.0,0.0,0.0,0.0,86.0,0.0,0.0,BFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFAFA,True +997,0.0,76.0,77.0,0.0,0.0,0.0,0.0,1.0,HCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBCBC,True +998,0.0,0.0,19.0,0.0,0.0,0.0,0.0,1.0,HCCCCCCCCCCCCCCCCCCC,True +999,0.0,0.0,37.0,1.0,0.0,0.0,38.0,0.0,DGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCGCG,True diff --git a/tests/results/nb_gm_001_3back.csv b/tests/results/nb_gm_001_3back.csv new file mode 100644 index 0000000..b2f89a4 --- /dev/null +++ b/tests/results/nb_gm_001_3back.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,seq,ralph_skewed +0,0.0,65.0,132.0,0.0,0.0,0.0,0.0,1.0,HCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCCBCC,True +1,51.0,0.0,52.0,52.0,0.0,0.0,0.0,1.0,HCDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACDACD,True +2,0.0,61.0,0.0,62.0,0.0,0.0,61.0,1.0,HDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGDBGD,True +3,40.0,0.0,0.0,1.0,0.0,0.0,0.0,80.0,DHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHAHHA,True +4,4.0,0.0,1.0,0.0,0.0,6.0,0.0,0.0,CAFFAFFAFFA,True 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+401,0.0,55.0,55.0,0.0,0.0,1.0,54.0,0.0,FCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCBGCB,True +402,47.0,0.0,0.0,0.0,1.0,47.0,0.0,47.0,EAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFHAFH,True +403,56.0,0.0,0.0,0.0,58.0,0.0,0.0,56.0,EEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAEHAE,True +404,0.0,39.0,0.0,0.0,39.0,1.0,40.0,0.0,FGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEGBEG,True 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+3,12.0,15.0,11.0,20.0,13.0,17.0,17.0,22.0,AFAHGHGHGBEBCDDDDHHHABCEHEHEBBBAHADADCFHHHHHFEFCBDDFDGDEFCAGGFEFBDGEHECCBCFFFFFFHGEBBHHCBCACHHDDBFGGGGEGEAFDGDADGDGDGBEBAAHDDFH,False +4,4.0,4.0,8.0,8.0,5.0,7.0,4.0,2.0,FGDGECDCECGCDADAHFDFCFCGAFCDDDABEBHBEFEFBC,False +5,15.0,15.0,15.0,16.0,16.0,14.0,9.0,13.0,HGDGBFDHDADHBBBBBHBAAGBCEABCGFAFAFBGBCBFGDDDEAAAHDFACECECHFHFHFCFHEGEFEFDFDAAHDEECDABFCCCCGBEBDAHCECHCHEDEDEDAGEE,False +6,17.0,17.0,9.0,6.0,15.0,13.0,15.0,12.0,BEBEBHAGCFEHHABAHDEDGHFBFGFCAABAGFFFAFGECEBEAEAFBFCEBEGHGDBEFABABEGEHEHBGBGDADACAGHGHGBGBACGCAHFFBHAECDC,False +7,12.0,7.0,7.0,6.0,9.0,8.0,5.0,6.0,CEGBFEFEFEHCCDEBCCHBBBGAHACBGGDBDADACADHDHFEAEAEFGFAAEAHAFAF,False +8,9.0,13.0,10.0,11.0,12.0,15.0,11.0,12.0,CGCFDBDFHHEHFFGCDHEHCFCFAAEGDCEGHGCFCBBBCBGFGHGDFDBDADHBBEGAGABABHBEBEHGHADAFEFCFDBDEFEHEFEFA,False +9,13.0,26.0,23.0,14.0,20.0,18.0,19.0,27.0,HECEBEFFHFDCCFGBCBDBAHGHGCBBABHEFAFEBEBHBHGGCHBGGCCCCCFCBDDDEDHDEEEAAFAFGFDFCGBGHEHDHGHAFABCGGEHEHFBGBADEBEBEAAHBDCCFGGHHHBHBHGHBDBEEAEGCGCBCHCEFFFFCHDHCHDHABCB,False +10,14.0,18.0,15.0,13.0,15.0,19.0,18.0,11.0,AFACABDDFBBBEBECECGHFBFBECDCEEEDGDBHHGCBDDAFCBAAAGHCHCHEAFBFDHAHCFFAAAHBBBFBFBHGFBCBCFGGGHGDGDFEGEFCFEDGDGAGEGCGEGEFEFAFDGC,False +11,21.0,20.0,21.0,13.0,15.0,26.0,21.0,21.0,EECEFFHGCADHGEGEABCCFDEBABEBGGCACHFHFBFBFBAHGBGCGHDCDABHHAGABFHEBCFEGDFDFDFAFBCBCAHACFGFBFBFBFBDACCBCHFHEGEDFDFCAAAGGEBFAAACACHCHFGFBFGHGHAEAGCCEDDFHHHGHGHGDE,False +12,17.0,26.0,17.0,23.0,17.0,11.0,26.0,21.0,ABGCACGDDFHFHBCEHEAGBGBEBAHEBEBFAAHAFBCEGDGBAHGGGGFGDDDBABABHGGGCGDGHGHDACAEDEFECHGEGDABGCHCDDDDCBCBADAHCHGBGBGEHDCDBBFBABHBHBFBACHDEEHGHECDCDHDEFEDECFGHGBFBD,False +13,24.0,21.0,23.0,20.0,15.0,14.0,30.0,24.0,AHHHHAFEDHAFBFGFCFGADADCDGBBBBGDGEGBCBHGGGGCGFBFAGGGGHEEFEGHGHABCBFHGAGACBBDEDHDHDGBCACAHGCACEHECACHBHDCGCECADGDGDABADHFGCGAGAHHBGFDCHBHCAAABEEFDFDBDBEADAHGEGEHECCCBCFCAHD,False +14,1.0,0.0,2.0,1.0,1.0,1.0,2.0,2.0,DECGCGAHFH,True +15,7.0,7.0,10.0,5.0,8.0,4.0,8.0,9.0,HBABHHEEGAGAGEGHCDEECHCHGBCBCDDAEGCBCGEAEFDFBFBFAGCHCHCHAD,False +16,14.0,19.0,14.0,7.0,10.0,15.0,19.0,7.0,CEAFFGHGEGFDFDCACAGBDEAFCEDDFAHHFDFGBEACGCGBGAFECECFGHCEBAFGEGCBABEBHBHBACAGAGDGHBABCBCBGFGFGFGBBBBFBCBGA,False +17,17.0,15.0,14.0,12.0,10.0,9.0,17.0,6.0,EBACADACGBGBAFGHGHADCDGAAFFFADABAHGDGABBCBCACACECHFBFHDCACDGEBADDEGGGEDADFGFGCGFBBABCBEBDBCHGEGEGECE,False +18,14.0,22.0,17.0,9.0,14.0,10.0,25.0,20.0,EHCHAHEHAHCHCGBGCGCGAEBFBFGGCEFGBGHAHCBABABHHGHGCACHDEDBBABGGDGDEBBBHHGCAEGBFHGEGEGBCCGCDFBBGBFBDAEEHHHCFEFECEHGCGCBHDADFDAGAGAGFBB,False +19,13.0,27.0,12.0,18.0,19.0,17.0,20.0,18.0,BFGCGBHAHAHEFEDBABEBEDADGGGGBAFCGEBDFHBHGHGCBBEGEGBHDHDHBCBCACDBFHHCHBGAGAGEDADADCDCACGHEEEEBDFDFDHDCGGBGDEBBBABEHFHGEFFFBADHEFFCFDEBEBFFEBHBFBG,False +20,11.0,10.0,7.0,8.0,8.0,7.0,11.0,4.0,BGBABGHGCGFBFAEBGGEDEFAHEHACDCDADBGGAGAGADFBFBCBCEFBFDHDACCDAGAEEE,False +21,22.0,20.0,18.0,24.0,13.0,11.0,16.0,21.0,DADADHCACFCHEDAAAHGDDHAGCDEDEGBHAHBDBDBGHHHCHCECAAAEFEDECEDBHFABGBCAGDBEGEBABHFCBBABDFDGHGCBFBCCDHDHDGDHDHCHBGADAFACHEHBDCDAFAFAFAGGCGCFHGBDBEBEG,False +22,8.0,10.0,11.0,7.0,8.0,15.0,4.0,11.0,CBAEGDGEHEBGBFBFBDHCHFHBAEHFFGFCFBFCFEEHABECFFFFACAEHHDCDCDHDHAHCFCBCBAADF,False +23,32.0,19.0,21.0,23.0,13.0,27.0,21.0,27.0,GHCABDGDFFFAHHHEAEHGAGAGHEFEGBCFAFBFGCHCHFHBGCAFFDFDBACACHCHCHBFGFEACAFABEBEBHHGHFHAHGGAGAHAFCGDHDHAFGCBCHDAAAAAAFCFHGEFFBEBEDDDFDBCBDDDCGFAFADBDBEBCAGGHDFDFBCDEAGAHCCEHGHAHCDDDDABAFA,False +24,26.0,30.0,18.0,21.0,29.0,16.0,21.0,21.0,GDGDADAGAGDEHCDBDHAHEHFHAHAFBHBHGCEBHBDBHBHBEEABABABAEECEGEGAGADHDBEEGBCAADHGBFBCEAAHDEBEBFBFBFCCGCEFBABAEDBGFGBGCFCGEACDFEFBHDADFHCEAEBDHDCGBEFGCDCACDEBEGAGAEAEFDFBBEHEGEGHCACEFBHDH,False +25,17.0,15.0,10.0,21.0,16.0,11.0,16.0,22.0,BDBDBHHHAAGAEHEHCHCDADEBGHDAGEBHGAABADADEDECEHAHFBGCGBEHCGADFBHECGHHFFFHFBDDDDDFDFDFHFEDEDACAEAEBDCHHBFBABCBGDGEAECHHGHGEGHDAGGG,False +26,12.0,13.0,16.0,11.0,17.0,10.0,17.0,12.0,GEECBGFEEDHCEFGFEAEAHGEGEDDDHDCDCBHBCBCFCECEGAGAGAHECFCEAAFGFGCEHGHBBBGBGBCBDHEAEFHFHGBCDGGACHCGCDADAEBFBADH,False +27,14.0,11.0,17.0,13.0,14.0,21.0,16.0,19.0,AAECGGEGHCACACACHBHADCECBDHDHDFCFGHGDDEDHHHAHDFDACHBHAFBHHAEEECGGFGEGEBEFCFAEAEFFBFBFDGDGDGHFACCDFHFCGBBHBCGGFGEHEFFFFHFCBCAF,False +28,14.0,15.0,12.0,21.0,15.0,9.0,13.0,21.0,GGHGEDHFCFCACBCADAEEEEAHDGAGHGHEHEHBBECEDBBBDBEGDGBAEABCCABBECDDDFDFHGHGHDHGHGHDADHHCHBHCCBAFHFDDDEDHFHAABDFDFEGEAADBDCH,False +29,18.0,19.0,27.0,26.0,29.0,30.0,16.0,16.0,DEFFFAFAGDGEEBFBFGEBADACADFDCEEDEDFDCDEBBGDGHGHGFFFDFBEBEHCHFDCDCEGFGFHFEFCGBBDCHCGCDADEGEGCFAAEHEHFDACGCEABBDECBCBCEFEFBFCFCFEHEHDGACEBAGCEFEBACCCAEDHDHBCFCDEFFHDHDHDCFCAAAEBEBFDHA,False +30,5.0,11.0,5.0,8.0,3.0,2.0,5.0,1.0,BBFGGBABFGCCCDADAHBEDCDBABGEAECBDBDBDBDG,True +31,28.0,17.0,19.0,16.0,18.0,11.0,17.0,33.0,DHAFAHAEAHDHFHFAFADHCGGGDGDGHEBDHCHBHAEBCBCFEGHHHBHCAFDHEHEHCDAGBCBAAAGACCBCAFGBHEHBBEAHAHAFAEACGGEHAFABEDEDFDCGHEBGAGEEAEBBHDEDECHCGABHGHAHAHBHCHCHCHDGACACDFD,False +32,5.0,10.0,12.0,17.0,19.0,17.0,17.0,11.0,EEBHBFFFDDEDCCAGEFEGGDGDFFGEGEAEDEFCFCGCGCGFAEGECDHHCEFDDHDFDABFDECECEHEFDDGDGBBFBFHHGCECEFEHAHDHDGBBFBGHGBG,False +33,4.0,13.0,10.0,7.0,4.0,8.0,11.0,7.0,CGBHBCBCBHFHFECBADGBGBGBDBCFAGDBHGFGECEHBGBCCACFGFGFGDDDFCADHEHB,False +34,22.0,27.0,22.0,21.0,21.0,28.0,21.0,21.0,BABFBCCCCGCDCAGABAHFBAHCBDBDHDCDCDEFFHBHBCBCBEHDAGAEFBBEEEBEGAGHGDGCGEBFBDEAECCFCFGDGDGHBHAEFFFECCADHFFBGHDHEGAAEDEFEFCDCDCDEFCHADAEHFDFHBBEBEBFBFAFGFAAHGHGFFAFGGBABGHGBFBFDFHCHAHEGDA,False +35,24.0,23.0,21.0,17.0,28.0,15.0,20.0,21.0,EGHGAGEGCGDFFCEEEEEAHGEGFGFBCBGBDBACHCAGDDDDEDEHACGCECAFAFEFHCHCEFHDHEHBAEADBDBAFCHCEEEEHBHBECEAEAFGGGGCCHBHAAACABBEHFHBDFHHDHBGCAABEBGAGABBFADADEBBBBCDCACFGFHDCEHEBGADE,False +36,16.0,12.0,18.0,16.0,29.0,20.0,25.0,11.0,EEEBCFFDHDBBGHGHGEFDFACCCFCGAECECEAGFFFCFDAHAEEHGGGBGBGADDGDGEGCCBFEHEGEHACDGDGCCCFCEAFAEGEGBGFGBBBHFGDGFGAAHADADCEEEEDEAEFEAEBFFFHEGECEGEHECAFDDDB,False +37,1.0,6.0,2.0,11.0,2.0,11.0,4.0,7.0,DBFFFHHADFFEFBDBFBGDFFEBHBHFHGDGDGCCDDDDHDHF,True +38,11.0,12.0,15.0,5.0,3.0,15.0,15.0,13.0,HCCCCAEBGFCFBGAHHHHBAFGCGCGCGFGCAABFBABHBFBCAFHFAFGCDBGBGAGFCBBAADHDHDCGEGHGCGFFHFHDEFHFC,False +39,33.0,14.0,21.0,23.0,21.0,18.0,25.0,28.0,DHAHAHADGDAFAFGCHCHEHCHABACEDDDCGBHAEFFGCADADGBGCFFFGGHBAAFGGHFHFHECFCHCHBDEFGADDCGGGHEBEDEBEBEDFHCAAAACFGFBFBFADAEGBDCAGACACAFGEEECDDDDCGGGEEEEEGCADHHHHAHABAHGBBCACHEGGHDADADAHAHEHAH,False +40,9.0,21.0,8.0,6.0,13.0,11.0,9.0,15.0,HEBEGEGAGEBBBHFAFABCBCBEBCBEAFHGGGHEHCHBEDFFAFAHDBFBFBEBDFHHDHBHCHBHBDEFABGBCEDEBCACHHEAGBGF,False +41,13.0,18.0,18.0,16.0,8.0,20.0,16.0,13.0,AGDGBCDHFADAGFFFHHCFCFEBGBGFGFGCGCHHHHCGFBFGDHABCBCGDGECEFBFCACBDBDCFAFBDEDCFFBHGHBEBABDFDFDHDHACABDBAFAFDHEGACACBEECGCBDG,False +42,21.0,15.0,14.0,22.0,14.0,22.0,16.0,21.0,ACFDFDEDFDBAFDCDCDFFFFFACHCHGEDFCFEHADACEHEDEBAFAGGHGEDADFDHDHDHGADAGCCCFHBDBGBDEGEBHGFGHAHFBFBFEAABABACDDAHHGFGBGEGHFEABHBFEHHHGDFDCACABABGECHAH,False +43,17.0,19.0,23.0,19.0,19.0,21.0,20.0,22.0,GDGFGEDDDDDDFDFDFEHBHDGAECBHDEGHGEEDEBEDECGGAADAFAFADECFCDGDGFBHGCBHBACAGACFCGGGBGCHFHEHECECAHFHFGCGHBFCGCBCFEHEGEHBBAAABDHFBCCCCFFFHFCABFBHBHBEDAFEHBHACABECHCH,False +44,2.0,1.0,3.0,4.0,5.0,3.0,6.0,5.0,CHCHFGBGEHFDAGADEDEGGFGEDEHCH,True +45,17.0,20.0,26.0,20.0,18.0,24.0,15.0,12.0,BDEFBBBHHECFCFCBBFEDDADADGECEHEFCGCAFDCGCFFEDDGGHHHHHAFAFEFAFDFDFDEDFAACFCFCDCBBBCGCGDGDFCGCGBDCACBHDHEECBBEBECFCHGBGEGABCDCEFHFGACDFAFAECEBEBDACABAGFBA,False +46,5.0,7.0,11.0,5.0,5.0,3.0,8.0,10.0,CBDHFHCDCEGEHCHCHCHEGCGCGBBBBADAHGDGBACGEAHBHFGFCECAHD,False +47,5.0,4.0,4.0,5.0,0.0,1.0,5.0,3.0,ACABGBHBHBGDCACHCDAGFGAGDDD,True +48,21.0,22.0,13.0,24.0,16.0,18.0,24.0,19.0,DBDGAGBGFHFCABGFECEGBGHHEACDFDGCGBEBGDAFAHADADAHHBHBHAGABADEBFDGDBDGDGCFAFAFDDDDECGFEFEAHAHEHEHCBCDADGBFBFAEBCAHFHEDEGBBFDEHEBDHFGCGHGHGBGCDABCBDGHGBGDCEAFAF,False +49,5.0,12.0,11.0,8.0,8.0,7.0,11.0,9.0,FCFDGDHBEBECFBBHFCFCGDBCCCGCECECBDBGBEHDDBCAGAEHEDFDHGEGAHBHGAGAGFHBHBG,False +50,2.0,7.0,7.0,4.0,6.0,13.0,10.0,11.0,BBFEFEFHAHFDFGHEBABDFHBHEFGFGHEHGGGFDFEHCBGBFDFHFHCCGCGHGCCC,True +51,5.0,7.0,11.0,12.0,13.0,9.0,8.0,13.0,EFFBFDAAECCCHDHBHFEDBHBHDHDGGGGECDGHCFEFEDEDCDCDEDCCHFEFEGCGBHEHBHAHAGDFCEAEHB,False +52,15.0,6.0,11.0,6.0,11.0,16.0,3.0,8.0,BAEGCCEAHBFCCHFABEHEFDCHEBECACECEAFGFEFEFBFBFAFADADACACDFGFAFAFEFDAAHFDCAHHH,True +53,20.0,14.0,19.0,11.0,13.0,12.0,10.0,17.0,CHCECEHEGAHBFGHCHABCBCDCECEDAHACGCADDBBGFGFGFHAAACACFBEGGAGAEHCAAAFDFDCHBDBHGDFDHCBEFEBCBABHHHHDHCHDFEFABEBECAAAEACF,False +54,18.0,14.0,15.0,22.0,24.0,20.0,25.0,23.0,EGGCGCGDEDEBCBFDDDBFHDDGFBFEEEGDBDBEHFDFEACACADABEFDCECGGHBDCDBAGHGFBFECHCFEDEHEHAHEEAGCEEEEFGFHFAAGEEHHHHAHAHDEFGDGDBCGAGHFHFHAHAHDHDBFBFCEGGGGGGGHAADAGCDFFAHCB,False +55,3.0,4.0,2.0,5.0,2.0,5.0,3.0,1.0,EHAABABGBFDFGFGEDDFDCBCDF,True +56,9.0,9.0,8.0,11.0,11.0,13.0,8.0,11.0,ECFFFBCDEDAFEBEAFGFHFHFDEHEBEHEGBFEFHBABCCAGAGBGBDFHAHGHFCFDHDABADEDEDAHGGCDCHCD,False +57,10.0,13.0,10.0,15.0,7.0,9.0,16.0,11.0,HHCFEGEGEDFGABEHEADCHGHBDFDGDGHGCGBBDDCDCDBDBHCDEBAHACCFDGDFAFAFDDAGAGHGCGBGBHACBGBGAHEBFBF,False +58,15.0,15.0,14.0,21.0,27.0,24.0,20.0,28.0,FAFEFAADAGFBFACBCBHHCGFGFAFHCEGEGHHBDBFHFHBEGDGDAEEHEGCGDGHCDGDEHFHGCEEEGEGEDBDEEEEHHHHCHDAGFEBHFHAHFHFDDDCACHFBDDHDGDFDAGGEAEFBHEEEEBEHEFFCFCFDBHAFADCGCGFHDHEBABHB,False +59,11.0,16.0,18.0,17.0,22.0,31.0,15.0,17.0,FCECFCFCFBHCHBGBFHGEDADADEFEFHFDFDADEEADHGAEAECGDGCCFHFGFHFHFHFBFBFCEEEBEFFDEGGBHBEBHFCDDDDGHAFBFBFCACHCAFGCGHHEDCBFEFABCDCEGGGDAEBBBEDEFFFFECGHEHF,False +60,11.0,9.0,7.0,2.0,10.0,10.0,11.0,9.0,HGHCDCHCACBCEGEGEGEBBHCFGABEBFAEHHFBFAAGHGHFHABABCGEGFDEAAABFEFEFGFGA,False +61,23.0,23.0,21.0,24.0,24.0,17.0,27.0,24.0,EDGGCBCFCGCGCFCGCDCBAACHFHFHECACAGAHFHDBDEHAGADHGEGEBCAEAGDHAADDDDCEAEADBGFDBBBBDHDGDBBGCAAEHEGDGBGBFHCGCDBBBEFHFDAGHCDCHFHFGEHEGEGHGBEFACADAFCBGBGBFHDEDEDFBFEGHGHAHAEEEEGEDHAHACEFBHB,False +62,21.0,13.0,9.0,12.0,17.0,15.0,25.0,10.0,HFGFGBGEDEHGHAHFHGAAAFGHBFACGDBEBGAAFEGEFEFBGAHDEDECBCBFBEGAGAFCCBBDBAGABAGGGGGECDADAGAEFEDGACADDCDHDEAFHFHFGGGFGCABAEEEGE,False +63,6.0,6.0,3.0,12.0,7.0,8.0,6.0,13.0,FHEBEBHGHDAGHDCDEDEAFCFCHEEBAAFDDDFDHDAGBGFDHGHAHDHEHFHFHBDBG,False +64,6.0,15.0,15.0,8.0,14.0,13.0,8.0,8.0,CCEDEDBHHGDCBEFEFCCGCEAGFGEGECAHAHGBCFHACEBEBEGEFFFFBDBFBHBDDEDCBCBHBFGFHEAEBCBCFCBCAFD,False +65,6.0,4.0,3.0,4.0,6.0,8.0,5.0,5.0,CGCFEFAFAEEDEHCHBBDAAFAGHEHEBFDHDBAGFGFGF,False +66,17.0,8.0,15.0,6.0,16.0,16.0,11.0,12.0,AFGFGFGHGFECECECHAECCCFAHAFAEHGGCEBAFAEAEFGGHCBFAAEHFHFGBHEHGAFBFHCECEADFDBDBCACACAEAEBEDDACBDFHFHEGC,False +67,24.0,12.0,23.0,14.0,18.0,18.0,15.0,12.0,CCCFCFBHAEEDFDBAADAEAEABDBDGEHEGCCCACECHGEGEDECACFCFCHBFBAGAFFGHADBEBAAAAFAEECEDHDHECGGBHHCHDBGBABAGEFFGFAFADACADAGADCHFECGFGFHFCDCEGFCC,False +68,31.0,17.0,27.0,38.0,29.0,28.0,14.0,16.0,ACACBCFDGBHBDEGEAHDDEFEFEFEFDDHECEBDFDAEAEFECECGCHAHAHCBCDAHBDDDDEDEBEHGDDAFEFCFDDBCGAGACCECAADADABAFEDACGCAFAHDFDBDGCECBGBFFCHCGAEDFFFHADFDADGFAFADEDHABAGAGEHEFBFECEDEDCGEADADFDHBHDFDCBCFCDAFAECFCEHB,False +69,5.0,4.0,3.0,4.0,2.0,3.0,6.0,4.0,DAHAGAHAHAHFGCGEBDFDEDGGCFBBGBC,False +70,5.0,7.0,9.0,5.0,2.0,11.0,6.0,10.0,HAHDHDHBGBFCACDCHFBBHBHGDEACACEGFCDHBGFGFGFCCHBFFHFCFAF,True +71,11.0,10.0,6.0,19.0,14.0,23.0,11.0,9.0,FHFEADABECHFFDFDFHFEDECEFEFEFAFHDADAEADDCAGFGBBHGDGABDDFFFFDDDADEEGFGDABCDGGBHDHFGAGBHBHBEBEGFFFFFCCEDE,False +72,25.0,17.0,20.0,19.0,16.0,13.0,17.0,22.0,GDCDHGBEAEGDGEBDBDHDCDCBHDEAEHDCEFAAABCDCDABAGADADCFAFCGCACAFFBAHGCGCGEGEACHHECACECEHEGGFBDHFHAHAHGGDGFCECHFHFHCHFABABFDGABDEDABABHEACAFDHHGHAHBBBBEH,False +73,15.0,19.0,20.0,23.0,23.0,21.0,22.0,23.0,GFGFECGCEEGHFCBCFDDDHHGBGHGHDCDCFHAHCCCFHAADEBEHEDEDADCDCABEGEFDFHCHGGAHAHFCFCEADFFECGBDBDBDCCACADHGCGEGHFHGHGBFADEBEBEDGDBBACEEEHGBDBFFFFDGEGDGDGFBEHHHHAAEAEFBBBBEFH,False +74,3.0,11.0,6.0,11.0,10.0,12.0,5.0,7.0,ECHFHDHEFFHHDCFGEGFDBEBEFFFDBCBFEDCDCFEBBFADDBDBGBGBGBAHAHFDEDECE,True +75,21.0,13.0,22.0,19.0,30.0,19.0,18.0,19.0,HAHEEEFEDHDFDBHBGCCEEFEGGHGHCCCCCHGECEAHDBDBEFGHCACGBEFEHAFDFACAFEEEHABAGAFDGDADADAGBCBAEADAEFHCDCFGEHFHDEDCDFEFCCCEAEAEGGABFGEDBDBHBCCECEHEAEFGHGHDDAEAEHCFGFGFB,False +76,14.0,30.0,18.0,20.0,25.0,19.0,27.0,30.0,FCFBAEDEGEHEBGHGFEFCGDBDGGCGCGBEBHBHEAAAEECBCBCFHFCFDGAEHHFGGGGGHCHEHBABGBGHHDFAEBDBDBDBCCHAGGEGDGCCBCHFGFGHGHBHEFGHBFBCBHEHBBABCBHBCGEHEADDDBHFHAADEDBFHFEEGEDHDHDEDBDFEFEHCHAEGDHBFBA,False +77,25.0,17.0,30.0,29.0,22.0,22.0,23.0,24.0,CCHEAEHBBCBDADBDBDHGFEECBDFGFEAHDCGCDHHEHEHCGCFHGDGAGAGACACDDDFDFDGECCHDHCCEFAFEBAFGGHDCCGEDBDBDBCHCACDBAHCGCGAHAHAFFFHADCDCFCFHHCDCAEAGAGAGABFHGEGBGDFHEBEFCFAGBEEAABAGDGDFDFEABHCDEDEHEHEFCFCD,False +78,9.0,16.0,9.0,5.0,4.0,15.0,4.0,5.0,BCEADCBBBBABABCCEHFBDHFAAGAGHCFCBCBFDFAGAGBFBDBABFFFFFCEHEBDHFFFBFC,True +79,19.0,17.0,10.0,29.0,13.0,8.0,14.0,14.0,DEDEAEAEDDDDDDDHDGEBEFADAGBFFHDGFBBBBGBABFCHGDFDEACBBBAHADAHCGCAHDHEHABAGCGCGEDAGBDAACAHDBCBGBGBEDDDDDADGDFDHHFDAHAEEEHCDCHG,False +80,9.0,11.0,7.0,9.0,14.0,3.0,11.0,16.0,HEHEACBHBHAGEBEAEBHBHBDEDCFABCGAEABHEHDADABABGGGDGHECEHHDGDHHCHCDGFFHCBEDEGEGHGE,False +81,4.0,9.0,4.0,9.0,3.0,6.0,6.0,5.0,BGBACACHDGDFDFBFEAHFBDDEDEGHGHBBBFBADHDGCGDBFC,False +82,11.0,21.0,22.0,24.0,26.0,28.0,21.0,21.0,EDGDCDCFGEDEFFFFGEEEDEDEDADACHCEBAFAFCHEDBFEDHDCCAHGFDFDGAGEFECEDBHCECDGGGGGBGFGBHCGDGFFDCAGDBCEHEGBBBBHFHADFHCHCHCACHCBBEFAGBGBEBFFFHFBCEDFFEFHDHFHFCCECBHBDBDEDEHBHEHFBFEGAG,False +83,2.0,4.0,1.0,3.0,2.0,4.0,2.0,1.0,CBFHFBBDGDFDFEGEABA,True +84,18.0,13.0,21.0,13.0,16.0,19.0,15.0,8.0,CBCEEADAFGDCFHFHDHFACACEDGACFGGGCBABDCCCCCCBABABABDBDFACGCGCFCAGEFEFBDBCFEFEAGFDBEFEHEHBAEADAFAFGEGECAHFEDGDHHCAEDEFCFGGGBF,False +85,14.0,12.0,10.0,10.0,16.0,19.0,9.0,12.0,FGBGHDEEEGBFAEAEDHGHGFEDEFEGEDEFEFCBAHCHCFBFDGECFFFGAECBBBDGFAFACACBEDABEBFHFHFHAHAHFEDCDCFCAAHBHADAFB,False +86,14.0,13.0,10.0,16.0,18.0,7.0,14.0,15.0,GGGGHADGCGCEEEDEDBAAGBCDAEABAGAFFFDBEFEAHAHBDBDBDBGHAACDHHGHGHDHEFBCDCHCHDEEBEBDADABEFECCGHGHFHDGEEEADBEEHC,False +87,9.0,13.0,17.0,12.0,12.0,23.0,13.0,12.0,EHCHBDDCECFCFCFABABGBFDFDCDHBGDHDGBGCGCGCFCDHEHEFCHGEAFBFBFDFHCEBAFEDEDFFGHCFGBGFGCDCEBGFHFAFBEEEBGFFCFAACAHAHF,False +88,6.0,3.0,0.0,1.0,3.0,3.0,5.0,4.0,GBGAGBHAGAGFEBEFEHHAHAFAD,True +89,11.0,11.0,12.0,15.0,16.0,12.0,7.0,10.0,BHBHDDADCGCAEHHDCEAFAFBFCDEDECBGFCECHAHGCAEDDBDEAFAFHFDCHEBEGEGADBDBHEHDFGFGFDECECECAAEBEBDBFF,False +90,18.0,21.0,18.0,8.0,15.0,18.0,18.0,10.0,BCBDGCBCHGHAAFAFEFAFDFHGGGCCECEHBHFCADAFAFEGBAAAGAFBEBEBEGCBHBFADAECDGHGBGECCBCBABHFFDCEFEHGBGBGBEFGABCBFBDBEEAHACGCGEGFCFCFDA,False +91,21.0,22.0,23.0,29.0,25.0,21.0,20.0,16.0,EDECECBBDBGGGDHDFCFDFAFGBACHDHDADFDHBEAACACACEDECEDGDGEGEGEDEAFCFEGGBEBGFGEDECGFAFAFGHEDFHFCFBFBDEDFDGBHEADHDCCFBABABACGEHAHFHCEGEGHBHDACADFCCHBHDCDCFBHAGDBABEBFBGCDBEBCDDADAEEC,False +92,22.0,26.0,23.0,24.0,20.0,30.0,22.0,18.0,ADAFEGHDHFFFFDFECADDDFHBHDCBFAHCHCACHEGFBFBCDHEFEGABAFAEBGBFFFBFCFGBHBEBAACAHAEDEDEGCDCDCDCGHACFCFHFHGCFCEHEHCGCDCEFGDGBGBGEGBABGBGCCABBBDBAFGDABFBFEFEDADBFEFDBHGHDFEFECBAGGCGADDDGBHAEA,False +93,2.0,2.0,1.0,3.0,0.0,2.0,1.0,2.0,DBDCDGFFAHAHB,True +94,18.0,8.0,12.0,13.0,10.0,9.0,12.0,11.0,HHFAEHCHCHCDDAFACACACGGFEFGCHDEEGCGCGFDDADGDFDEBHCDABGBABDGAGEEBAFABGBDAHAFAFADADEHHCHCBGEAEA,False +95,4.0,5.0,6.0,3.0,5.0,4.0,4.0,3.0,AHBFEADADAGFHFGGCBCBCBCFCEHEBDCEEG,False +96,6.0,10.0,15.0,4.0,14.0,9.0,14.0,11.0,ECECEGHGHEHGDACGHHHFGFGCCCGFEEHEAAACCHCFCFEGEDHFHFDFGEABBBBEBHGCGBEBGCACBEBEGCCDBFG,False +97,3.0,4.0,3.0,4.0,3.0,2.0,2.0,6.0,BGHFHDHDCDBDECAHAHAEGBFBHCE,False +98,14.0,9.0,9.0,12.0,16.0,15.0,11.0,5.0,BGGACFEGEGEAFGFGFGFAADADACBCFDADGEBHBFDFGBBDCGAFAEEFECHCDCBFEAEAEADADCEBDDHDBGEFCHEHEFEAEFF,False +99,24.0,22.0,16.0,19.0,18.0,22.0,22.0,17.0,BABDFDEDEDEHAACABAEAFFGBHFGAHDBCAGADEDCHBBGEGAGAGAGAGFGABEDEDEFCBABDBECECEAGFGEGBGACBFEHEHAHAFBFBCHEFGDADAEEBCBHHHFHFBAGGGFFFFGHDCCHAHBCBCHFGDBCCAFBDGGFDHDFDFDC,False +100,10.0,7.0,6.0,7.0,6.0,11.0,8.0,15.0,GGHGHGFEFDCHAHFHEHEBACCBCHFHFBCBEBFFEFHAHGHDAGADAEGBGHHBAAADCFHFDADFDH,False +101,21.0,23.0,9.0,23.0,25.0,21.0,22.0,21.0,EEEEEACAHEHDDADHFBFBAHGHGBGDGFECGBBBBFBFEFHFGFGFAEHDHAHAHBHGHFBBHGGGGGEHDDDDHEAFBHHDEFEHEDDGBCDCHBGDDFFCAHADEDEGEGEAABBEBDFGEBABCDFEACFDADAGAGEGBAFABHBDGDCEEEAFAFBFC,False +102,1.0,8.0,5.0,3.0,5.0,5.0,6.0,8.0,HCGCHDEBGFEFECBBBFBFGHGHGDGBAHCFCHHHEDEBB,False +103,29.0,22.0,27.0,17.0,23.0,16.0,31.0,26.0,GGHCFGEBEDGCCDEBFFFEFHGCDCBCBCECFCHCHCHGHCEGAGCECABHEEEBEBEGAGBBBABABFBHBHDHGGDADCCFAFEDECEABGBFAFHDAGHGHADEFGBDCHHDEDCHGABABFGDEAAAEBGAAEGGGGFGHAHDBDCCHGHBDGEGHGEAEACCHCACAHGHGHAHDCACAFAGAFA,False +104,7.0,6.0,18.0,7.0,11.0,12.0,24.0,18.0,GDGEHCGGGEFECEBECGCGHGCFHFHFHCDFDFGACHHHGBGHACDCGAGADBCAHECACGHGHBBCFGHEDEFEHGHBHGGCGCGCHCEGGDGEAFFHFCF,True +105,16.0,23.0,21.0,18.0,22.0,17.0,10.0,18.0,ACEGEHEHAFACDCDCHFBFBGBHDFFFCAGHBBBHBHFABABABAHEGCAEEEFGBGBADGEBCDEHEBCFCHBHEFEBDDDDDDDGFEDEFEHAHBCACACBDBDHDCBCEDEHEGCCFEEEDHHAABCFCHAECBCBFFCFG,False +106,9.0,10.0,12.0,6.0,8.0,7.0,13.0,7.0,FABABHCEGEGBGBGCCCHCAAABGEGDGFGFAFCBCGCEHDCCAGHDHCAEHFBFAGBGBGHFDCDBEEDE,False +107,17.0,15.0,17.0,17.0,16.0,26.0,15.0,17.0,EFBHGEAFDGCGFGFGDEEAEGBDEFBGGFAHHCAFAFHBHBDGDGEGEGDFFFDFHHHAHBCDADBCBFGFCBCBGBFEHADAHCECFCECHBFFFFCDEDEDCDEFEFCHHHCACAEBCGAAAAHADAFHFBDBCFDF,False +108,20.0,24.0,27.0,23.0,19.0,28.0,19.0,18.0,AFAEGFGFGAHFCFEHEGDBBBEBEBEBCDDDHDFGFDCDCECFAFAHAGBBBEBFDEBCBAHGFGAGABDBEAGFCCCBEBHCDBDFDFBBHCHGGCDCDFHEHECGCFFFADAHHHDCDAEEBFGAEHCDDGACACACFCBEFFHAGCCCCEFEFCABDBFFFGHCHDHDFDGBGA,False +109,9.0,16.0,17.0,17.0,16.0,16.0,12.0,24.0,EGDDDAHBEAEABDCEBFFHFHFHCDGHAHCCFDFDFDFBBEBFBFEHGHGDCFCGHGHGCBCEDHBCDHFHFBFGDGACCCGAEBHBABCHHEHBDDEHEDEDEGEAHDHCECFCFCBHAHEGBHH,False +110,5.0,7.0,7.0,3.0,11.0,14.0,10.0,14.0,AHEHDHGFEFGCHFGFBBCAEFEFEFECEHFHBHAHFCBGFABHBEDEGCGFDFACGCGBFEFGHHHHEHG,True +111,20.0,16.0,22.0,22.0,11.0,17.0,13.0,10.0,ACAFFCDCDCACBFAFGDAACDCDEDEFFCBHDGDCDGDEABFEAADDCAHHDHEGACEFBCBCACACABBHDHDHEHCAAFAFCDDEDFDFBFCFBFDEDFFGGAGCCBEBCBHBAGGGGGEGACBHBDB,False +112,26.0,22.0,28.0,29.0,20.0,26.0,21.0,19.0,GCDCBAEHEHGGFABGFFFFBDBDBHCHCHAAADGFCBCDCFFFDCHCECEDEAFBFEFEGGCDCDAEAECFCEEACCBABGFDABADAFHBHFEFEAHAEADFCFHHBHAHAGGDHCCCDHBCADABHBDCGHGAGAGDDDFCAGBCBDBCFCFEHEDEBGGFGFDBCGAGDCDEDGDBDBEFEHAFADD,False +113,4.0,0.0,3.0,3.0,1.0,0.0,3.0,3.0,HAHADDGDHAGAECCCG,True +114,15.0,25.0,14.0,19.0,17.0,16.0,17.0,18.0,GDGCHHEBEBHBEFAFEFBFHFBGHEFEFEBAAAGFGDDFDFDFDBDBDBABABDHCBGDHCEBBGBCBEBAGHCHBEBGHEHEHEACACACACBBGGFGHCHDGBCDGEFDFDBEHECDGBCEHAHDHACFGADFDBAGD,False +115,4.0,7.0,3.0,5.0,3.0,0.0,6.0,6.0,HGHBHBDBABACEGDGEAHBHADGEGCHCBDGDB,True +116,18.0,19.0,11.0,27.0,26.0,22.0,18.0,28.0,FDFEHEBGBGBCFDFDFBEGFABHCHEEFAFAFAFBDHEHEABBDCHCDDGEHEADAFAFBHHCHBFBEDHGHGBFDFGECHHABDEGECEDADEHEDCAHAGEBABCDCDAHEDEDEDFFFFFBFHGAFEGEGDHDHGHGHGEDHDGEGDAHABBHHDHBCDADHEGE,False +117,9.0,10.0,11.0,5.0,12.0,11.0,5.0,12.0,HFBFCFBAAEABGHCHAFABBBBCCCHCECECHCGEHEHEHFHAHCEDDFDCEEBFFFFGEBEAFAHDGBGDEHA,False +118,1.0,8.0,6.0,3.0,6.0,11.0,9.0,8.0,BEBFGFGFBFBGBCDFEHBHAGEFHGDEFBFHHCGCDBGFGFGHCHFHCECE,True +119,16.0,21.0,23.0,14.0,8.0,20.0,24.0,21.0,EEGFBBADAFCBHFACCCFCFEFDGAFHFDABHBCGHHHBHGHCHEGCAABBGDHBHBGFGCGCGCGHFEFCFGABAGGCGAGACFCBCBHBFCFADHDHGHGFDEBEGCGCDBHBEAACHDDFDCDCFBFBGGGGCBHDHDHFABA,False +120,23.0,16.0,16.0,25.0,12.0,20.0,24.0,21.0,DFHFBBDGFFEDCHEEGGGEEADAGAGDBDAABFDFCGDGAABABABABACAGGHDHFACECBDDFDHGHGHBCBCAGFGBGCFFFDFDCGHGDEEHBCDCBHBCFGFDFDHAGCHHHHHGAFADDHEHEAGAGAGHCBAEAEDCDADCFGFDHDHF,False +121,19.0,17.0,15.0,20.0,28.0,24.0,23.0,17.0,DCDFFGAAFFFBGAGDGCACHEHDADADFEHEGGFFEFAABBHGGGFHEHACACBEEEHBAGAGFDFEBEGEBECECDCHBHGDGBEFEAEAEAECCGCEHBHCFFGBDBDCDAEEEAEFFFBHAHGEDEBGFGFGHGBGBDFDCDHEHDDDEBAFDFEGCFH,False +122,24.0,21.0,31.0,19.0,20.0,33.0,21.0,17.0,CBDGEGCBFGFHFHFEFBDAECCCBCBGHDCCCAFADHDHDEDACBDBGAHABFDGEGCHEECECDAFBGBGBFFFFHEAECHFHFHGEEBCFCFDGEGFFFFGCDCGBGBGFFBFBFAAAAAFGBAFABECAGEGBGFHFCADDCECHFAFADAHFHEDEHCFBACAEAEFDCCCCCBCHDADCG,False +123,23.0,22.0,33.0,26.0,18.0,14.0,26.0,19.0,DGDGCACABHFCADADGHGEEHGACAHAGACEDEDEDGDFCHDECFCBCGHGECHCHBEEDEDEDEDCBGBGBABCBCBHAGDGECAGDCCCFCDCFHFDABECGBGFHBBFBEBEBACEDBHHCCGCDAGGGFCCCGDDFCBCBGBGHGHGCBADHFFAHDGAAAAABAFDHDHCFCEAD,False +124,14.0,14.0,13.0,14.0,9.0,17.0,19.0,18.0,DCBFBFAFAHBHGFBABECACGGBGCGCFAFHHDGDGEBDADFFHHHHDAABHFFEGAGFDBGHGAGBGHFHFGCHCDGEGEFCGDGDCDCDCECBFAFCFHAHEBEGHBEBHHADAD,False +125,22.0,17.0,18.0,14.0,19.0,23.0,19.0,20.0,AFFEGCACEHAHBHFHECADBDEDHDHDACHCBCBHFDDAGHGHCECEAEAHBHGGCEAFAFBDGFFFFBAGAFAFHHCGDFFAEBBABADADBCGHHHGACACFCFDFBCGHGEGEGBGBCBEEAFHEBBGGECEFECEHGGEAFDFDFAF,False +126,2.0,2.0,5.0,1.0,2.0,0.0,0.0,0.0,CBABCCCECEAD,True +127,9.0,13.0,13.0,20.0,8.0,15.0,15.0,18.0,GGEFDFEHDHDHBAGABBBFFHFCFHGHGHGHGDADHDEDFCEDAGAGCBDFDHDHCBCDFDBHFHGHFBCGDDDDDABGHDHCHAAECFBDBEBCBCEGECCFFHCGAGF,False +128,26.0,16.0,20.0,13.0,15.0,14.0,8.0,14.0,AFAFGCBFDCCGCBCACACAFACECBAFAFDBBABABHECBGAHADEDCBADABABAHEHCHCHGECDHDHBHBAEDEAEAHBGFAHBBCACACAFEDCAHHEADGEGECEFFFCGHDFDEAEFFD,False +129,3.0,2.0,3.0,1.0,2.0,1.0,0.0,1.0,AHABFBEAECCDC,True +130,3.0,10.0,5.0,11.0,10.0,4.0,3.0,9.0,DBGBHBAEDEBCCEBAAFHHDHDCBEDHBHBHBDECECEDDDFDGDFBEGEHEHF,True +131,18.0,19.0,23.0,22.0,20.0,20.0,15.0,23.0,FGBCAABCBCDCDCBBAAADCEGHAFDFEBHBHAHGDAEAEAHGECHCDDFDBEBHHHDBCFCABFHHHABFHHEGEHBAFAFCDCHGEGEFBFEFEDEHCHCHDHDGFAFEBEBGBGFCDCAEDEGFFFHFBEAGACFDDDDHDCCCCDCDGEGBGCEH,False +132,27.0,13.0,16.0,13.0,20.0,12.0,27.0,15.0,HAACDHGHEBFFCDAGADAEABAGHFHDHCCAEHFHBGBECGGGGAGABACDEDCACACFGFGFHBBEBHGGGDABGGGEDECEAEAEAFCEGBBBAGAEAEABHEAEGGGCEHFHDGAGEDEDFDHDEAAGAHAFFGCCCCG,False +133,5.0,7.0,9.0,1.0,6.0,7.0,8.0,7.0,BGCFEBHHHHACABFBFHFCFGGGCCECGCGCHAEBBHFGCGDAEAEBEF,False +134,14.0,15.0,11.0,16.0,21.0,17.0,16.0,20.0,HBHDHFHDDEFEGEFEBGDFDFBBHBAGEGCFHBHDADHHFAFAHECEFADECEDDDBDBDACBEAFHFHGEGCGDECECBAGACHBHGHFHFHGEGFFHEHCHCEGEGEAEGDGEABDBABFFGECABA,False +135,8.0,3.0,1.0,2.0,4.0,6.0,9.0,3.0,GFGEGHGFEFGCGDBAHAFDEAEGBGBAAAFAGAHF,True +136,14.0,29.0,20.0,23.0,25.0,22.0,18.0,18.0,DGDCEBGFHDBFBECHFEFBDEDCACGCGHEFEFEFAFGGGDCFGFHFHAHADEBBCBCEEEFEBABCBEBACACBHHCFCEAEAGBGDCDBDEDGBACECBHEHBDGDFDGCGAFEFDBHBEBEAHGFCFBFBHEDFDGDBBBBACDBDHGBEAEGFCHBHEHDHDFD,False +137,3.0,5.0,1.0,6.0,8.0,6.0,3.0,5.0,FDFDBBBEDEHEHEFEACFFGDHDFGBHAEAEBEGDH,True +138,17.0,19.0,28.0,23.0,19.0,29.0,14.0,27.0,EEHFCDHDHBAADFECECFFFCDGBAHAHFHBCDDFDGDADBCAAHABAEGFHFHDHDEGCGHGHCFDFEFGBHAHBCBABEEECDCDEHFHFBABHCCCACHEACHDGDFHFHBHFGDGDGDFBCDCGABFFDFECHCFFFHFCDGEFCACHCHCHEGACFCFBFEEECEBBBBD,False +139,18.0,10.0,15.0,7.0,19.0,9.0,15.0,15.0,BCDGAGEBBAAFCBEFDFHCAAHABFEADAHGCCCACEDEDEDEDEHCBCFEHCHEACACHGGGGBGEGFGFEHECGFEAHGHEHEHEHACAFBGGABABHGHEAEAC,False +140,12.0,11.0,10.0,15.0,15.0,9.0,10.0,21.0,GGDEDEDHDABGBDCAFADADEEFHFEEBBAHECFCAHGHGHEBBCBABAFHHHHAFADHECEGGBGECECHBHECFCDDDEEHHHHHDHDHDHFACGDABFG,False +141,6.0,7.0,16.0,10.0,19.0,4.0,7.0,3.0,GAGEECEDBGBGFCFCHCFBDBDECEAEDBDCHBEEFAHAEAEGCBCEADDDDEGCCEEEECCCECDCGCEE,True +142,17.0,14.0,17.0,18.0,21.0,18.0,15.0,9.0,BADAGADHDGDGFHFAFDFGEEDDDADCCCGGECCCGEHAHAHEEEEAECFCDHDFABABFBGBCACEFFDADAEEHBHFDFCBEBGHGCFCDAGFDBEFFGFGEGCBAEDEBCBAACDCBEBEFEFEG,False +143,1.0,3.0,4.0,4.0,2.0,3.0,3.0,3.0,DHDCCGCGAGHBBFEFCFDHDEB,False +144,3.0,1.0,7.0,1.0,1.0,3.0,7.0,2.0,CDCFHGGFBCCCCGAGAGAEHFGCG,True +145,3.0,5.0,7.0,4.0,3.0,11.0,6.0,3.0,DHGEGBGBGCCFDFAFHCBEBEBDFCFCFGFCCAHFFFDGAF,True +146,4.0,13.0,6.0,8.0,6.0,15.0,9.0,3.0,FABGBGFGFDBBBCGEEEEBFGCBFBDBCFDFGFGFAFECCDDADAFBDGHGBFBFHFEFHCBD,True +147,16.0,16.0,22.0,23.0,21.0,20.0,35.0,29.0,FBFEECGAGFGFGHDHDFAGEGEHFHFHFEGHGCEEAHDGDEHEGEFHFCFHGHBECDBDBHHGGGGGGCBHAHACAHAGEBDCEAGGHGHGEGEBDAHHHCHADGCFBFHGBGCHDFDFDGHCBCHHAGBEBDACHCFFGGGDADEEAGCEDEDCCCGDFDBDGFBFBGBDEACACDCDCH,False +148,16.0,20.0,20.0,23.0,21.0,16.0,31.0,18.0,EBEHGGGHCACFDDDDDAFCHEGCACFCFDFAGADEGGGAGEECEGEGEGAFFDCBHBHDHEGCDCGBGBGCCCCCBDGEBCGFHCHGHAHBBCEGEGEBFBGAHABDBDAGAGFGBEEEFEDGDAFCHBABGBADADEGFFDHDCFGGDHBFBDEDEDGHHHBH,False +149,3.0,7.0,4.0,6.0,10.0,7.0,3.0,5.0,EBEHEBEDCFCBBADCHFHFGBGBDEEEECHBDADADEFFFGFHE,False +150,6.0,2.0,7.0,6.0,2.0,3.0,8.0,0.0,DDDCGCADFDFGGGACACAGBECGGDGABACFCE,True +151,5.0,2.0,2.0,0.0,5.0,4.0,2.0,3.0,GAGAFBFEFECEFHABAEHEACH,True +152,14.0,12.0,9.0,7.0,12.0,11.0,10.0,17.0,FDHDFEHDHCFCBCDGHGCFFFBFHACCHBGAGAHEHEBEAADAHBGBFBFBABABAHAHEEAFHEHBHEHABGGECDCECEAGDHAHEFGG,False +153,19.0,24.0,27.0,19.0,23.0,23.0,26.0,24.0,CDCGGGFAAGACHFHDHDHBBCCHCGFAHABGBEDHBGBGBABADECFFFFAGGCHDDGDGCGHGHGDCFHDHAFEFEFEHDCCGGBGEGAAFCEEDFDFGBEAFHFCGEBCBHBFBDCDGBCBEHADABCHCHEHEHBHDGFGAGEGBBEBHDEEHAHAEAECCFFFCCCECECEFBFBDECBA,False +154,13.0,10.0,11.0,9.0,11.0,8.0,12.0,4.0,GEAEAFAGADADAEFCGCGCGCAFBFBEECEGADADACBGBCHHBFEECACBEHEFBFBDADEDBCGGGBDFHCAGGD,False +155,23.0,15.0,20.0,21.0,22.0,13.0,16.0,23.0,FEBEBEBFDHDHCCDDBCBEGFDFGBHCHFDAEBCBFHAHGHDADCBGDHDHDFCAHHHDBCEHDFDAAECDCDCBCAFEEEEEAEAGACHCEGEAEGGGGAEABAFAFHHGEAAACHFHAHFGEAEDEDEDADHDBCGAGACBCHHBGGCHC,False +156,1.0,2.0,8.0,2.0,1.0,1.0,0.0,3.0,CCCCCHCHBACDCBHEDF,True +157,11.0,6.0,5.0,14.0,10.0,10.0,2.0,6.0,EFAHAHFBFGGABADFCBEDEDADAHAFAHBFEDEDCDEDEDEDFFCBEDFDFBACDDAEHCHA,True +158,15.0,22.0,16.0,16.0,9.0,21.0,17.0,9.0,CFCFCAEBDGDHBBFBHCAAGFFFAGGGGFGHCHDBDBECECECFHBBCBAFHFDFBCACHCAAAEFDBDBCFGAADADAGGBBBGCGBGCFBEEGHGFGFDFDFABABDFHFDBDCEFEBGDDB,False +159,3.0,6.0,10.0,6.0,2.0,3.0,4.0,5.0,GGGFDFDBCBHBHBCCHCBCEHHFCACDCBEDDDACGCA,True +160,7.0,12.0,7.0,6.0,6.0,8.0,8.0,5.0,AEFEFEBCBADCEFHHCHGBBECAABFBFBDBGBHECGDADADGBGAHFFCFCGDGBGB,False +161,25.0,18.0,13.0,27.0,15.0,21.0,17.0,28.0,HFHGDDBDFDGHGADHGFBHGCFDAECCHHEFEFEDDBEBAHAHFHFBFHAHDFDFAEDFBBCEHADGFGAHDGDGDGDFCBCEAEBCBHDHDHAHAEADHHFHFHEGBHEDABABACDCAEFDDGFGAGABAHDHDGDGDBHBFAABAGAECECHCACBFAFH,False +162,18.0,23.0,16.0,12.0,17.0,23.0,24.0,31.0,AEABABCBCHCHCFFFBHHEGBABDDDDDHHFHEECFCFCBEDDBHBHBCGHDFAFHCHFGCHHHHHHHCFGFGEHDBAAEGGHEBBHGDAHFHBHBECGFAFBGCAHEHGBBFBDCHHGEAEHGFFFADGEGBGBGCGFFCHGEGEGAGAFABABAEAEGFGF,False +163,24.0,23.0,17.0,16.0,25.0,31.0,34.0,30.0,FHFHFEFGFBAEHHHDHDHFGGDGDGFGDHACAFGDGDECECHCGAHAHBBBBBFFFCGBGEFFHFEAECGGBBAGABABAFHFHECGDECFCHDBACDEHBFBHBFEFDDGCHBHGHGHBEAGFGCEHFBAHACEHEACFCFEAEGEGAGACFEAEBGGFDBDBGEGECEAHHHAGBGHAFDFAFDFGBGHGFGAGHEE,False +164,16.0,17.0,19.0,27.0,19.0,29.0,35.0,19.0,GDGBCCGCAFBFGFDHGHBFAFGFGDDECECDGDCDFHFGFCFHFEABACFHFBFHEEECEDFDEDGGGDGCCBBDBFBABFBGDEDEGBHBDDDGGGGCFHFGFGFHFEABBDCDCHCGGGDGFGEDADHDECEAGAFAHEHADAFFGGGCABEGHCAEFGFGAGDDHDHBCEHGAEHFH,False +165,10.0,7.0,7.0,12.0,6.0,6.0,5.0,8.0,DGFFDCDCDAEGDBDCEBGACECHCECDBABDEAHDHGAAHHHFHFBFBGBHDADADAFAE,False +166,17.0,18.0,17.0,16.0,20.0,19.0,17.0,15.0,CACAHAFBDAAADADHBGFAFDGDGDGHHFHFGFGFHHCAAEBFBFCFAHEBABEEGEGEGEBAHGDCDGEBCHEGDGCFCEEFECBCFHBHBHBADDFBFBGDCBCFFEGCAEGEFBACDCECECFDDADEEEGHBHB,False +167,15.0,4.0,11.0,15.0,21.0,12.0,17.0,17.0,HHAHDEDGHFHEHCHGFGFCECEGEACFGDGDCDCHADCEHEGGAEEBEBFHHHCHCHCFDAHAGDGFGDDHEEGCAEDEABAEGEGHGDDFAAEFGAGAEAFAFDFEEBED,False +168,8.0,4.0,9.0,2.0,9.0,7.0,3.0,7.0,ECECBCHFHCGFGFEEEHEHECAAHAFFBAEAFHBGAEAHDBDACCCFC,True +169,16.0,14.0,9.0,11.0,11.0,11.0,12.0,11.0,DFDFDGAGAGAGFGHHACBHBHGFFDFGBCEAHBDAEADACCECAAEABBHEAEAEDEDCABABCBGGGGFFACHHBDBFFDFEEGBCDHEHBHB,False +170,4.0,2.0,1.0,1.0,6.0,4.0,5.0,2.0,GGDBEEEEBEAGFFCFGFHAHAEAG,True +171,28.0,14.0,20.0,10.0,8.0,25.0,20.0,36.0,HCHCDCGCDAGAGHGBABAFAFCFAFDFGFGEGHFEFHBHGFGCHEHABFGFHHHCFDACHEFBHHHCHAHGBAADCHBHBFAAAHHHFEGCGDAHAGFBFAADAEACFFGAEAGABFCHCBFDEAGAHBHBAAHHHFHFHCCACGHGHDHDHCHCFCBGF,True +172,3.0,11.0,4.0,4.0,5.0,7.0,5.0,5.0,BBBEBHHCCFEFGFGHGBBBGBDFAFACEHFGFHDBDBABCDEE,False +173,8.0,13.0,6.0,15.0,4.0,10.0,15.0,7.0,ACDCGBGFFFGEGBGFHBHDADHDFGBGBGHCDAGGGCHDHGADDDDDDEBBHBFBFGFAEADGCCBDBDGAAEFBFB,True +174,10.0,11.0,8.0,10.0,13.0,7.0,14.0,11.0,GCGCGCGFGEBCAAEEHEAEHDHDGAADADADFBEDECHCGGGHGEEHBHAHABFBEBHFADGDHEECHBBFBGEGBGDCFBFD,False +175,23.0,12.0,12.0,24.0,26.0,34.0,26.0,24.0,CDBFHAHBGAAFEGHAFGCAFGFGBGBEBEAFGDGDFDADCFGEGBFCHABFCGADHFFEFHFEFEFEDHFGCGEGEAABEGAGHGEAFAFAFCFAEDEDEDHDHDHFFFGFHACEFHHHDHDAGFDFGEGBGDHDBABAFEEEHEBGFGEEAEAHHFDDDGHGHDFCFCACHDDEDEFHC,False +176,18.0,8.0,20.0,16.0,15.0,17.0,11.0,11.0,FCFBECGAFAFABAEEEEDCDAECEDGAAADFHBDBECEHEABABCDCHBGEHAHAGAECHHHADCCCCFCDCDAGCFFEEAFAFGDDFHFHFHDBGGDGDADFGCECFCGCDCFF,False +177,13.0,12.0,13.0,12.0,6.0,11.0,5.0,9.0,DABFHGHCBDBDCFFGABAFEBACAHECGDFFHFHFDFEFCHCBCBAECGCGCHEAEADDDBDADAHHBACABACDCDBFB,False +178,7.0,14.0,10.0,12.0,19.0,22.0,10.0,9.0,FDECFBFDFDFHFGCEDEDEFHGBACCEGGAEBEGABFDFDFCHGHFFEDBFBFBFEGEHADAEFEFEFEABCFHDHDAECFCGBFBGBFBEECECDBEBHGH,False +179,2.0,2.0,2.0,1.0,5.0,4.0,1.0,6.0,HGFEHEHEFEDAFHFEABBCHCH,True +180,2.0,5.0,1.0,3.0,3.0,4.0,0.0,0.0,FAADBBBBEBEFEFDDCF,True +181,6.0,7.0,5.0,2.0,1.0,4.0,3.0,6.0,BHBDBAAGAHCHFHACAHEHBBBFCFCACGGDBF,True +182,2.0,3.0,10.0,6.0,8.0,6.0,4.0,4.0,BCBCECEAEDEDHCCCCHEHEGDGCFFFAHGBFFFECDDECGD,True +183,27.0,20.0,35.0,20.0,19.0,18.0,17.0,19.0,CHCHCFCBDEHBHEHCCCCBDBAADFFECCGCAEAFAHCFGDGAGACABFEAHCBDBDBDACGDEDEDEHEBGDGDCAGABEBEAECEGAGFGCABFGFCEAEAGACFCDCFFGFEHBDBDECACAFHBHCHBHBFAHDBCADHEHACAGDDDGCEBFBFCCCCGAHCFCACAHH,False +184,21.0,29.0,29.0,14.0,13.0,23.0,22.0,20.0,HBBEFAHAHDHCHCGCBCAFABDDHDFAAADBDBEBCBCBEACGCGFFBFAFHGHFCFEHCHDADFCFCEDBGBCCFCFGFHCHCACBEAFBECFCDAGGCGFGHGFGEGACCDCBHBACGFGFHFBFGEGBCHCBCDEBBCHGGBGBDDFAAAEBEBABHBABHGEGBHA,False +185,16.0,21.0,7.0,5.0,16.0,12.0,3.0,15.0,BBBHGHBACDBEAAAFDHEHAGAGAEEEHHCAEAFBBABFBCECAFAFBFHFEDABBBFBEBEBEBACHFHFHDHBFEAEBHAFCHEDECEHBHB,True +186,26.0,34.0,20.0,22.0,24.0,21.0,26.0,17.0,HFACACHCBBBBHBGBEHFHFEAHAEAEFDBHECAHAHDDBGEDCBEGGFGECAAADBEBGCGCFCFCFBFBFBAGCBBABEHGCGCGFGBBCHCEDAHBCEAEHDBAHGGDDDDHEADDDDDFFGBGAGBGBEBABDBDGDGBFBDBDBDHEFEFCFEAAFGEBCGEGBFFGCGAABAGCHEEEAFAEA,False +187,3.0,5.0,0.0,1.0,1.0,2.0,2.0,4.0,DEBGHGAFBFHHBHBABA,True +188,8.0,11.0,10.0,11.0,8.0,19.0,14.0,12.0,HGFBFHFBFGGAHDDEBAHFHFHFCEGFGFGFGBGEGBCEEAFDBBBHFHDBDBGACHCHFGCGFGCGFBCDCDFFAEAHAEFDFDHAECDCD,False +189,24.0,32.0,23.0,32.0,21.0,21.0,20.0,22.0,BBBABAEECDDDEDEHEBECEDEDHHHFHFDFHCDAHAHDBGBGEGFGFGFGFBAGCGDFBFHDHBBCHGHGFAEBEDCAAGFDDADADBDCFGHBABDHECBDBAAHADAGCDCBABABGBHDCGCBCGFEBDCHAHCCCFCFEBABHDDBGBHHCCCGBABDBCEEGHAFEFEDDBAFFFDFDCEAEAEGDBD,False +190,13.0,10.0,11.0,9.0,7.0,16.0,9.0,11.0,AGCHAGCBAHCBGBEBEACADADHDBFBDDAGEFCFCBHDEFEFHFHGHDFGFACAEFHAEAGGBGFCFCFHFDFCFCBBFDAHAH,False +191,14.0,3.0,6.0,9.0,14.0,7.0,4.0,6.0,EAEFDGEEFCCCFCFEAAAEADCDAEAEGGAFHHHHEAAADADEFEBDBAEGECEADFDHDHB,True +192,6.0,4.0,7.0,3.0,3.0,3.0,1.0,4.0,CFGEHCCFCBCEAEHCHDADADABBBACAFH,True +193,29.0,36.0,21.0,12.0,18.0,14.0,23.0,24.0,BBHFFFCEHEGEHDHBGBHBHDEBHBHBEAEBDBFHFHEHABADACGGGADBBHHFBBBAAAAABECDCACHCAGACFCFAEAFAFAGGDAEBDBHBEBGACBHFAFGFGBBCAGGBGHDCBBDGEHEGEACACACEBEBCACAEGDGHCBDGHGHBBABCCHCHCHGBAEAGBFBG,False +194,6.0,3.0,5.0,1.0,2.0,4.0,8.0,5.0,HBHGGFCFCACAEABGEACDCHBGGHGAGAFHFG,True +195,3.0,6.0,4.0,7.0,9.0,15.0,5.0,10.0,HAHEHFGFHHGHGFFCFCEDEFEDBGBDEDACBDFHEBFHFHFEFDFCFDFABEBGHFE,True +196,2.0,2.0,8.0,2.0,3.0,5.0,4.0,4.0,CCECHCDCDCEBHCGEHBHGAAFFFFGFGC,True +197,0.0,3.0,4.0,2.0,1.0,2.0,3.0,2.0,DBHBDFCCCGCGBGEFH,True +198,9.0,8.0,9.0,4.0,11.0,7.0,12.0,11.0,AAAFADHGGGFGCBCBCHEGEFEHDCABDHGEGEGDACBFHFBEBGBECEHAHAHGBECFCGEGAHEHCHF,False +199,9.0,8.0,10.0,11.0,7.0,10.0,5.0,6.0,ACADDFDHDABGCDEBEHAFFBECECDBBABAFAFAEAFHDDDHCCDCGCGHGDGHFCBCBFFEFE,False +200,15.0,9.0,5.0,13.0,12.0,23.0,15.0,22.0,CHGFEHBDGDHEHAHDFDFAEBDAHEFEFEGGGGAAAGEDAHGHGHECEGFGFGAGBFEFAFBFBGBDFAFHDHBHFHFHGDEDHFFCFEDBDHFFFAAHBHAHFCFDHHCHAA,False +201,8.0,4.0,6.0,6.0,2.0,3.0,2.0,2.0,AGCFBBCBCDAHABACEHDADADCDADAEFGFC,True +202,15.0,30.0,30.0,30.0,15.0,29.0,25.0,23.0,DFBBDGHBCEDBFBHBHBCBHEGGGEBEBHHEHCFFHFGBHEGBDFDFGBGDFDFHCEFHCGCFDHDFDEHADADEBCFEFDFEFECDAAHFGDDDCACACACACDBABGGEDAABBBGCACABFBGDCDAGGGGDCDFFFGFCBBBDBDHECGHGDGCGCHCHFBFHHHDHCEBFDFDFCFCGCBCBCFCDABHCG,False +203,14.0,19.0,19.0,3.0,12.0,14.0,16.0,22.0,CHAEADAHBHBHBHBGGDBHFHEAAABCBGEFCCHFEBHCHABABFHCCCHBHAGAFCFBFAAAHCFCGEGEHEHEHFHBHEGFGHBEGGGCCFGFGCDAECGCBBGBFBCHCHCGBFE,False +204,9.0,15.0,19.0,11.0,9.0,19.0,20.0,15.0,FAAACCHEGCGDGBHDCCCEBAHDGDFDBDBHCFGFCFCBCBFGFGHGBFBHHHFHEGBGBCAEBCCCFCFCHGAEFEAGCDHGHGFGFGCGBGBGFDACEBFDFDEHEDGHABFHF,False +205,20.0,16.0,16.0,34.0,30.0,20.0,29.0,29.0,CDCFGDGDEFHGHEHEGGBGBGBHBGEFECDCEBGDAHGCBDDGDHDHEBEDDDDHAFAFDEGCHEGFHFADBEEGAGDGDHFHBDEAEAHAHDDDECGBADEHEFEFDACAGEGFGBDEDECHHHEAEFFBADDDDAEAHHDHDCCFCAAAHCFCFEGHHHHGBGBDCHCHDFDGGEGBFBGHFAFEGEGEAE,False +206,20.0,18.0,16.0,14.0,21.0,4.0,6.0,11.0,ABABAFADEDBAECHGDDAAHEBBDBACECGAAAACHEFEBCDHGBCECECEBEFEAECBCEHEDGAHACADAHACECGDDEEECEHHHFECBCBEBHBDBDBDBAGDBA,True +207,1.0,3.0,2.0,6.0,1.0,4.0,1.0,1.0,FCADBDBGBFEFDFHCDDD,True +208,5.0,3.0,5.0,6.0,4.0,0.0,1.0,2.0,DCCBCDCDCAAAAHDHBGAEEDBDEE,True +209,9.0,6.0,7.0,6.0,5.0,8.0,3.0,2.0,FCFEAEGDADABCBCFGAGCFAFABABCBDHCFDFEFEACBDHEAD,False +210,21.0,21.0,15.0,16.0,11.0,15.0,20.0,12.0,CACFFACCCEHFDBGBGBFHFAGDGDADACGGDGBAACABBECECEGEDHDHCABDFDFDAGHGHGBGBFBGEGBFDFAGAEHFDAHEGABABFGAGEBCCGCHBDEDGBCACFBFAFHDBEBHBABADAH,False +211,10.0,24.0,13.0,13.0,14.0,11.0,16.0,23.0,EDEABACHGHAEGGBBBBECECEBBBAHGHGHCBCECDCBFBHBHFHFHFBBDAGFEBHAHDHGCFAGABCDDBEBEDHGHBCCACFDDBAHHHGBGBGEGEGHGFEFHHHDDBBCDEFGFHDH,False +212,19.0,7.0,17.0,13.0,17.0,11.0,21.0,24.0,FGCAHAHFGEHAAAAAHGDGHGFEEGDHHAEAEDCDFGBGDHDGFECECGGEEHGHGHCFBBHBFEEHGHGHDHFHDHDAAAHDECAAACBCECACAHFDFCCCCCCGGGGGEEEDHBHEFCGDHAHAB,False +213,10.0,20.0,7.0,7.0,13.0,11.0,10.0,5.0,HACBEBEBAGEEHEDAFABBFEEEBGBGBGBAAEBBDDFDFDFHCHDDAFECHBBAFAGGGFAFCGBEBEBEGGBFFCBCBCB,False +214,6.0,9.0,11.0,6.0,13.0,4.0,11.0,19.0,ECECBCFDGEGBHEDDHGEBHHGCGCBHHHHHEHEGACABADHFFGCGBGHDDCEEEEBEFHAECBCHGHGHBHAHAHC,True +215,3.0,0.0,0.0,3.0,3.0,2.0,6.0,5.0,HDFDHEHGGGGHAHAEGEAFDG,True +216,1.0,8.0,11.0,12.0,14.0,8.0,9.0,12.0,GEBDBDCCADDBGFGFEEGEGCDCEFEGEBEDCCFBHCEDDGEHEHDDFCHHHBHBHBCDFDEGEGCHCHEHFHF,False +217,10.0,10.0,22.0,13.0,14.0,8.0,15.0,10.0,DCHGECECEAGHEFGACFBGBECGCAEBEHHAGEGFDFDFHEDDCDBFBABACDDHDBDGCCCGHGACFCFDGCGCBCBGAGACECACBCECGDHEHEHECD,False +218,7.0,10.0,14.0,5.0,9.0,7.0,7.0,16.0,CFCECECDHHHHHHHHBBBHEFCCEBDBABAGDFDHCHGACCHCHEFEGHGDACFBGBCEEEFGHGFCBCHAAAB,False +219,15.0,20.0,16.0,12.0,13.0,12.0,14.0,14.0,AGAEAEAHGHFBFEHBHFGGEEHCFCDADACBDBFBCBFGFBBBCCAEGDGFAACAHBCBCDAFHFHECAFFEGEBCBGGCDCDCDEBBDBDBHHHHHDGAGDCHCAGEGABBEBE,False +220,0.0,1.0,1.0,0.0,3.0,3.0,1.0,3.0,HEHEHFFFGCBE,True +221,4.0,7.0,18.0,11.0,9.0,20.0,14.0,16.0,GGGBFCCCFBFDGCFCFDFHFHCDCDHHHGHFDCAGHCBAEEFEFEFHAEFCHCGEFCCCHCHEHCDCDAGBGBGCDDFDFGFHEHDHFGEGFHFGFBB,True +222,19.0,32.0,14.0,24.0,24.0,23.0,30.0,29.0,EAEAGFDFDCBHFAFADGBHBDAGCDEABDFGEEFFFEEAECHDHBHDGAHHGBGBGBGHCDFDBDBDEDADHFFAFEFGBHBGDCHEDABGBEBCDCHCBFAFBGBAHFHFGEDFHHHBBBBDBDBDBGEGBHEACCHEGEGEDEHECGHGFBHGHCBGAGHGHGEGEGEHAHAHFCCEFHFAGBGBGDADFBB,False +223,6.0,4.0,7.0,6.0,14.0,14.0,8.0,15.0,CEEFAGEBDFAHHDHFAFAHBFFHFCFEHHHHFDEGEGEDEDGAGHDFGBGBEFGFHHCHCHEHECFCACEEFE,True +224,11.0,10.0,13.0,13.0,21.0,14.0,25.0,19.0,CGBAEGEGEHHCGGHGCCBCAEBEGHCHDFDFDFEGBDFDFEFAGDGAGEGCGBHEEGCGBEEGEADACECABEDCDFFFDCAGAGHFHAHGEGEGEGBGBGHHHHHHDABCEDHHFFDHEHEGFF,False +225,6.0,19.0,5.0,11.0,12.0,6.0,9.0,5.0,GBHBDBABHBCBDEDBGBGBEBEBCCFDHDFEBBDDEAEAEAECFGFGEGABCFGBBDHDEFBGBGEEABHDD,True +226,11.0,18.0,23.0,14.0,12.0,26.0,20.0,26.0,EFEFEFGDCDFBHBHADECHHEHEFGFGHCBGACBGACFDFGFCFGFCCCHHHBHFHFHDADFFEBGFFFFFDBCCFCFHFCDGEHDFDBDCAGGHHHHHHBACGCGAGBGHAAAFFCHGBGCADGBBBCGDHEBEBEBEBHCHDHCCCG,False +227,23.0,20.0,28.0,18.0,25.0,23.0,23.0,21.0,FCCBCEFEDAGGBEHCHCHAFCCADFFHFEFAHCHDGCCHAEDEDFDGAGAGAGEFEBEBHHEFEFHFCGDFBGBDHAHBGAHFFFBFCDDADCDEEAGABHBHGHCHCABADABCHCHCDFGHGHBAFFEGECBGADCECGCGCBFEFDFCGCGDEECAGAEAGAGBBBBBCEEAEDECE,False +228,5.0,3.0,9.0,5.0,8.0,2.0,3.0,5.0,DDDACEHGFBCEAECCCCCFCEHEHEHEBCDAEBDHAGAG,True +229,15.0,19.0,18.0,23.0,23.0,15.0,10.0,23.0,HHFHGHEBFHHBCBDEEHCBGBAHAEDEDCGCGEBBDDDDEDBDHDFDEDACCEEDFCEEECBCBCBCDAFEHCFAHBEDACAGHHHHHHHAHGFACACAFBEBEFFFFFDEBEAEGCBEEDADACBHGCGBGDHDHDFDHDEABF,False +230,15.0,10.0,14.0,14.0,7.0,9.0,3.0,6.0,EDADBFADCDCDEBFBFAFEFEDCBADFBFBAHACCBCGEHEHBCCAGDCFFBAAABAGACHCHDDCCCEDHDADADA,True +231,21.0,19.0,19.0,16.0,21.0,13.0,13.0,23.0,EHBFBHBCDAEACABABEHCAAAAAEBDHDCECACAHGFCFBFBDCCBDBDECHCGCAAHHDDCDCDEEHHHADAFBFGFGDGFGHGAGEEFEHBBDBGHAHGHEBCCACACGEDEAABDBCEDEFEHBHEEEHGHFHEHFFGHB,False +232,10.0,11.0,13.0,7.0,8.0,12.0,12.0,9.0,EFGGGHCHBAEHFDFEADAHBBFBCGFGBCBCBCFHFAFAGCGCEBEDCCCHCHDGGGCGCADFEBEBDAFAFAHEFGBHDA,False +233,16.0,18.0,26.0,21.0,12.0,11.0,22.0,9.0,GBGCHBGDHEHDGAFCFCGCBBDDDHHGCEDEDCDBGBEBCCCCDBGBCACBGGEHEDGGAGACFCFCHCGGDGABDCCCGDBDEDEBBCHCDCDBDAGECECAFEFBFEAGAFAGBGAGDDDACAFAFAFCHBA,False +234,8.0,5.0,2.0,10.0,3.0,5.0,9.0,5.0,GAGBBEDFDFDBDGDAEADHGAGHBDGDFDFCGAGACABAGHHHFED,True +235,28.0,16.0,21.0,19.0,24.0,21.0,12.0,20.0,EDHFBEAFADABHFHFCFHFACCBBBHAHDHBADGDBCBDFEFDHHADACBHBEAEDDDGAGACAEHECFCECHHHEABFCFEEHGAFFFADADCDGEEEGEBECEBBCACAHAHADADFFAFAFHGDEEFEBCGCGCGCDCAHBGEEFGADECECAFAHA,False +236,13.0,6.0,14.0,8.0,9.0,13.0,7.0,14.0,FCFAFAFAHAHCDCDGFFEFECEDBCECDCFHEEFAFACHCHCEBGDHEHFHAHBHDHFCGGAGDHHACCBHDCGFGBAAEABA,False +237,4.0,7.0,4.0,12.0,6.0,4.0,7.0,10.0,DGGHBHDDDGDGCGCGADBHEDEDAGFCFEBDHDEBAHAFEHEHCHDBDBHFHB,False +238,25.0,27.0,17.0,20.0,11.0,20.0,27.0,24.0,BGGGHACECEFEAEDBDBHCGDGDHDHBHBHAHAHFBFGCGCAHFHABABEFFDDAAFHFHDAGADFDGBACCCHGHDAACHCHGBEBCCCBDAFAEGHAHGHGEDBDBCBHBGFEAGAGBGBABDHDGAGADFBFGFGCAEBGFFEHBBGDGBBBFFHFBFCDAGCGHDA,False +239,27.0,19.0,14.0,12.0,26.0,20.0,17.0,18.0,CACHFHBABHBABAHEGBDDEBFAFAEACABAFAHAHGHDFEGEFEBEBEAFCDCHABAGEGEDFBGBACAFDCDCAEHEHFHFEEEFABABCGEEEGHDHAHBHDFGEGBAAAFDHECEAGCGEBEDCDHFAFAGAGBGFFCGCEHGFEBEF,False +240,13.0,5.0,13.0,8.0,10.0,9.0,13.0,11.0,HCHAGAEFGBGAGFGCDCAGAECGCGEFEDHGFADADACHDFDGBCBCFEDEFEFBAHHHHHHAAFGCECACBCGEHEADCG,False +241,15.0,13.0,22.0,21.0,14.0,24.0,13.0,15.0,CECEBACABEFHFGBEFDCDBABGDAEADCDHGFGFDDDFDFDFGFEFGCGEAHGHGHCFCDABFEHHABCECBCHFHCACFBFBHBADFEFEFDFDHDHCHCDEDAGGECHAFDHCABFCFDFDGBGCFCACDCEA,False +242,10.0,3.0,9.0,4.0,10.0,22.0,6.0,6.0,CBAAFFFFGBDAFFFFFFFDGAGEHFGECEFEFHCHCEEEDCFAFAHAFBDEHGHCFEFCFCFEAAFAGC,True +243,16.0,18.0,13.0,25.0,8.0,14.0,16.0,17.0,CFHGHAFGFCFEDAGEBBFDGBGHDHAHBGBGBDCHHEBDBDBDCDHDHFAGGHGHABADDCDFBHAGDDDBCACECAGEGDDHDFDFHFHCGCGCDBAFAFDBDEFEACADADADBCFAHBHGEBB,False +244,14.0,10.0,26.0,18.0,17.0,28.0,19.0,21.0,HEHEHDFDFEGEGFGDCBBDAFHFHFDCEGBBDHFAGBHFHCECHCGAFCCDDADGHGCGAGBDCDHDHDACFCFGACEHEGDGFCFCFCAEFHHHFBFDFDCBCFEFCDGAGDEEFEFHFHFEECCCAAABECFHACECFAFGFCBCGHGHG,False +245,30.0,27.0,23.0,25.0,28.0,19.0,14.0,26.0,AAACACBCAEDEBEFCCHCAEGEDEFGAGCEAEADFEBBBEFAGBBBFDAEAEHHHHCFCHCHADFDEBHFACBFBGBFBCHHAHAEEGHHEAEGHGHGHGCAHADADAEAEAGDGBECHDDDDEFFDCDCACAFBFHCHEHEADFBFBGBDBCGABHBHDACCECDDBDBDFDBEEEEHCBAFHHDBBADF,False +246,9.0,17.0,16.0,9.0,17.0,6.0,11.0,16.0,HGEGACAHDHDCDEGFHBHDHECEDEDFDEEHCFCFHBEGGFABEHHHHGAABCCDBEBECHCHFBAHGCGABCBEBECCCCCEGEBBBBDBABEBHGEGA,False +247,10.0,6.0,15.0,20.0,23.0,16.0,16.0,6.0,AFDGEGEFEDCDFHEGEGFGBCACECEAEHEDDHEGEDEFGDDDCCCCGAGEDBABEFEFDGDHDGDCBHBGFFCFCEEEEFCHEFGDGFCDADCFCAEGFGBEFDADADAE,True +248,1.0,1.0,5.0,2.0,5.0,7.0,7.0,2.0,EFCFDAGFCFGFCHEHECEGGCGDGFGFBE,True +249,20.0,25.0,23.0,25.0,18.0,22.0,28.0,20.0,DGDBDAABACHGHEBDCCABFBAHGGBGEAAGDDFGFAHADADEDFHFHGGGFGFDHDEDBACDGDGBFACABBGBGEGEGECFFFEABDEDHFAFGBCBCACHHFHFBFBFHCHCHCECDGDCEHEGCGBBFBGEFEFHCGCBHGDGFHFEABCCEBDBHGDGDGBHCEDADCDCBAEAC,False +250,27.0,24.0,20.0,16.0,26.0,17.0,25.0,11.0,CHCBCACHBABAGHFEEBEGECEBEBEACDGDHHGAAFGEGABEGAGEGADADABAECFGBGAGAEBEADFGFECACGGFGEGDGFBFGCGBFBFEAEBEFAFAFEDEAAAAGBBBCDCDGECCCBCFADABHDEDEGEAHHBDEDFDFGCCCDBBHAHGBCBEHF,False +251,23.0,19.0,20.0,25.0,22.0,22.0,28.0,26.0,ACACGEBFHHCAGAGHGHGCGCGBEHFHFCAGFGCGHEHAHADDDDAEEEECCFBGHAHAHGBDECFADGCECEGEGDGAADBEAEFHFDGDGAEAFDECBGECCHDEEBGBABEHHAFFFFEFDADHBHBDDGGCGCBAGAHABDBDEFEBCBDHGHGFDFDFDFHBAFCBDBDFFGGCHHHDH,False +252,22.0,23.0,23.0,11.0,21.0,24.0,27.0,23.0,CGGAGEGECECECDBFFFHAHGEGCGAGACEDBBBFGFGHGHFCBGHFHBHGEAHAHABDHABABDBECHAHFCFEFAAGGGBGFCDCBEADADHFHDHCEABCGGGFGAHEEAECCCCGBBEHEHBHBHDCDFFAFBFCEBAGAGCCBCAGFDHHEHFFFCFEFBBEBFGEGA,False +253,21.0,15.0,11.0,10.0,10.0,18.0,15.0,19.0,CFCEEFHBGDEEFEFDAGAHAHGHFHFHGHAHAHGFFFGBDBGAAAABABGBFBFBEACGCEDHFACCFFFGECBAECDGGAFAHDHDHBCCGHAHAFAEDHDHGBBABDFCAGABHBH,False +254,16.0,7.0,14.0,11.0,13.0,17.0,11.0,13.0,CDFHFHECACEDEAECCHFHFHGHGCAHAGAGDEDFDCHCFDADFEGAAEAFFDEDCCEDBFCGCGEBEBHGAGFBABAGFHDHAHAEFFFFFBEBCGHACA,False +255,14.0,24.0,17.0,17.0,23.0,22.0,12.0,11.0,EDGFFFGBBBCACDDDBDCFCFCEEAFGFGFGFDBBBFBDCFEFADAHEDBDFHAAGHCHFGACABEDEDEAECEFEFDAABHHAHCECBFBCBFFDBDGHGHFBCDCECEDEAAGEGFBEBCBEEGEBEBEBHCEFBBH,False +256,15.0,18.0,13.0,27.0,17.0,28.0,20.0,24.0,FBDBCHCGDEDCGAGAGDDFBBBFFFFEDACGCHAGGGEGEBABFHFEDHFHFCBDGHGBGDHBCBGAEHFAFHHHDBDCHBFGFGFHFHEGEBDFFFHAHGHCHAHDHEBEFEDGDGAFABDBEHACFCFCEDADEFBDDEAEADFDFHFHFDGHEDDDDC,False +257,6.0,7.0,12.0,13.0,9.0,11.0,8.0,10.0,DDACHGHGHDHEFCCEGEGACCDCDCDADHBFEFEDEGCFBFDFBFEHCHDAGEDECBCBHFGFDFHAHCGABDBF,False +258,17.0,20.0,27.0,16.0,18.0,18.0,19.0,20.0,AGEHCDAGCGFGDCDCHCACDFEAGFGAAAADADCCHGHGHCCEEEGCADACAHECEGDGFBFBFCHCHCBBDBDBDEFCGCBBBEHFHACAGBCHFFBCBCGGGGHDBECEHEHGHBCAGEDEBFCEEBEBDFCFAFHBADDHFHFHFHECFBB,False +259,1.0,5.0,4.0,1.0,1.0,0.0,6.0,2.0,GGGGBGAHBHCGDBECCBCB,True +260,2.0,3.0,4.0,1.0,3.0,5.0,1.0,3.0,BFBCBFHEEGEHCACACHFFDF,True +261,2.0,4.0,3.0,2.0,3.0,2.0,6.0,2.0,CDCABEHHGFGFGEBABCBGDGEG,False +262,17.0,17.0,32.0,25.0,20.0,22.0,15.0,15.0,DHDCDCDGEHCBGBEBACGDFDCBCFCBCEAEAFCDEBAAEADHCEAEHECDDDBDCDBBFFEFGFBCBHAHFCCECGHDHFHAHACDEHECFCDEAAHABBCHGEGDGFHDDCDGDCCCGCACACFCFDADFGFBFBFEGEGEHDACGDFCFCFGBEBEFCF,False +263,7.0,4.0,7.0,4.0,5.0,5.0,7.0,12.0,GCACAHGHECGCHFGFEDHDHDHGHBAEAHBHFHGCCBCHEGEBHAFADAF,False +264,6.0,6.0,13.0,6.0,11.0,2.0,9.0,8.0,DCFBDBEEEEEEADAHGHGCGDHCHGEACBCGCAHEHGGAFAGCCCCCBEBHDCBCEGEHD,True +265,20.0,25.0,22.0,32.0,26.0,23.0,23.0,27.0,DCHBHBCEHHGHDCGCAHHGHDEEHEHBBECDCGBBACACADDDDDFCGEABGBABEBEBEACFHFBEGHFBABCGHGEGDDDEGAHAEFBFDGDHBFGFCDCDCDFGFHEBEHEHBDEAEACBDADHFBDDDDAFEFBGGGGHGHCHEHFCFGFGADDDDBDADHFEBEBECEADACBCFAFHFDFGFAEGHHCCFE,False +266,7.0,6.0,7.0,3.0,4.0,2.0,13.0,8.0,BGHCABHHCHGGBDBABAFCGEGDGAHCEEGEGBGCAHAHACGCGHGFGD,True +267,8.0,8.0,22.0,12.0,15.0,14.0,10.0,10.0,DCBAAGBEBEHECCCCFEDDDFGHGDEDCBCGEGEGEBFFAEHECFCHCHFHDCDCBHGGCCBCFCHHFAFGHGDFCEADCDCDCEBFAFACECAFEFE,False +268,20.0,11.0,17.0,15.0,11.0,11.0,19.0,11.0,FACAFGDHCEFHAECBCBEBEAEGBGBGFHCCBCAHDCFCDGDAEEEFBACADABACECHGGDBDGGGFHEHADAFGFGFGHGHGCFCDCDEGAAAABDDDGHBACACDGDHAGA,False +269,6.0,1.0,7.0,4.0,8.0,4.0,3.0,3.0,DBGECEAEAEAEAGDGFCHCECFAAHHFEFCCDEDC,True +270,18.0,16.0,20.0,26.0,19.0,21.0,22.0,23.0,BFBCDDGAGACDBDGDGDADHCAEACGCGDEBGDFDCDBDGHEHCFFFFFHFBFAFHDDGBHHHHFEFABGGDGDEFCDGHCHEFCFHBADHHCFCBGBFEEEEEFEDEDAFGHGDGCACDEAEACDEDHBHGHBHBHCDGAEACCEHGHAHACAGACBEBGFDF,False +271,0.0,3.0,1.0,4.0,2.0,4.0,2.0,3.0,HFHFEFDBEBHFDDBDGCG,True +272,16.0,16.0,17.0,14.0,11.0,14.0,8.0,16.0,FCHEHAFAFBFBDHGAFABBCDCDHBHEFABCHCHDAGABEBAHDHDFCEBGDFECECECEHECACDBDBDCGAGAGACAGBFBGDDACCDDBHEHBACFBFHHHFHFCFAE,False +273,13.0,11.0,14.0,14.0,11.0,17.0,18.0,16.0,CDFDGBHBFGFGFGEDABABCHHDDEDCHCGAGFBFDADHDCDCECAGEFEBEAFAEHEHGGEFBHCHFHFAFDFACGGFGHHDHGHAHCFAFGEBCBGBGCACDCDEHGFBAG,False +274,30.0,26.0,12.0,16.0,14.0,36.0,17.0,16.0,GGHCBABACFGFHFBBHAEAEACADADABABFFDABBFFEFBAGFHFBFCFBAHHHHGGDGFGBHBFEECEFDCHCHBHGEAHADDGAFAFDDBDGFGBEFFFFFGFACABGFFFAABAFACAGAGHDABABGDACFEAEADBBFBEDEAFFBFBFCFCDBHEHEDF,False +275,6.0,13.0,13.0,9.0,7.0,9.0,12.0,6.0,CEFBGCCCCHDBDBCAFDFDFGFHHCCGCGBGDGDBCBCBHFGAAEGBGBFBGBGECHCDAEGEFADAHEDEBBF,False +276,7.0,5.0,3.0,5.0,6.0,7.0,3.0,5.0,BCCDFEFEFEBADABCFDDHDHAAEAGFGFHFBAEAGHBHE,False +277,6.0,5.0,1.0,2.0,3.0,3.0,6.0,7.0,HBBFBFDHCGEGAHAHGHGFEBHBGGAEAHADA,True +278,4.0,8.0,15.0,16.0,12.0,11.0,10.0,10.0,DHCHAEEEHEHEFEHGFBHEDEGEGFCDCFCGCDCBFFFCEGDBHFDDADGGCGDEDEDGACDCFCFBGBHBDBCFCHCDDDHCAB,False +279,15.0,15.0,14.0,9.0,20.0,30.0,10.0,19.0,EAFFEFEFHBHBHBHCHCFAAACFCAHGBGBFEEBECEGEFDCEFEGCBFHFBEAFDBBGDDCGFDCBBHBHFEFEHCHFBFDGCHFHFHFGFGAAAAEECEFDBEFECEHDFCFHDHFFEAAAAAFGFHFH,False +280,20.0,27.0,17.0,23.0,26.0,20.0,26.0,25.0,AEDGCEBACABABGBGFDCEBHBCBCGHBAEACBHHHCDDEGFHAAFABCEHDBDBDFFGFCBGGGFGEEFEDEAEDEDHHHFHEEEGEGCBCBHBEBGBGECEAEHGHABBBFHEAFGBGDGFFEFDGDGDGHGDAFAGDHDECEHHHAHDDGHGCGEBEFABCBDBFCFCFHBADADFDAHH,False +281,10.0,6.0,6.0,8.0,8.0,11.0,10.0,7.0,GBFFDHAEAECDDBEGDGAEECGGGDHDAFADAEAHBHDEFFFFBCBCECAFABAHGFGFGFGHCH,False +282,21.0,33.0,19.0,20.0,21.0,12.0,19.0,26.0,CAADABABCEABHBABDCHEAEGHBBCCCCCHCBGGGGHHDHGHGDGDGDBDAAGCBHDFEEEEEEBEBAHHGHEHCCGHFBFBFBFGHBDBHAFAGACCHAHFBCCFDEDEHCHABDBEGADBBCBHEHEDDDDBDEDBBHAHBEEEDBBBBHGGGCEFBFAFBGAHAFA,False +283,12.0,9.0,6.0,10.0,12.0,16.0,15.0,10.0,CFCEDFGCGFHFBGCGFGABEGAGAGAGAFADBHGHDEFHHDGCADEGBBCHDAAAGEBEBABFDFEFEFHFHFHFHGBFEGEDDDEFEA,False +284,0.0,7.0,2.0,2.0,5.0,4.0,3.0,5.0,FBBHBHECBFDFGEHCHEHEBEBDGFGB,True +285,18.0,10.0,10.0,8.0,8.0,13.0,19.0,13.0,HHHFGFAHCCBCHCBFAGCGBABDBDGAFDCDAEAEHDADBHBAGFGFGHEFFGHGHBHAFFBFCFCAAABEEEAGGGAGCGFGAGADAGEHAHCDGEG,False +286,17.0,19.0,13.0,13.0,17.0,16.0,12.0,9.0,DBDADABCGDAFEFEFEDABCBEBGDGFEBEBEBEADBDGHCADABFDADADABGFGFCBCDCFBGGEEFCFAFEFBAGGEFHCGAFAHBHBFFEBACECACBCHAHEHEHCGBEH,False +287,11.0,13.0,8.0,14.0,5.0,10.0,1.0,11.0,ADDCHBHFDEACFDBDBABCBCDDDBAAADHFBFBABEHEHBHBCCHFDABAHCDDDCDAFHFEFEFHFHGAB,True +288,21.0,32.0,21.0,22.0,23.0,17.0,23.0,21.0,CFCBBDADEDEDBDHDADCCCEHEHBFBHADADBGBGDCBBHFAEBDHDFDFBEBHDEDBCECEGABCFGFHDHGHEHAAGHGEDEAEABGFCCBEBCFDFAEGGAGADECFFGFBBHCGEBEGAFABDBHFFAHAHAHBHBEBEBCBABDEGCGCHCHBHBGEGEGCAAGGBBFCCGDG,False +289,10.0,13.0,5.0,12.0,9.0,19.0,21.0,12.0,GBFAEDDDGGFEFDHHGHGFGFGDGFGHHHHEGDBHFGGHECBAGAEACFBBDBCADFGEGDBBBBCBHHFFBFBFDAAAEFGFAFAFDFDFHGGGGGECE,False +290,10.0,11.0,9.0,13.0,3.0,16.0,8.0,5.0,DBDBDCFFGFGABEBEDEFFGFGFAFABHCAFABCDHDADAHBGBDDDADFHCBCDCAAGHBFGFGFCCBFFCFD,False +291,22.0,19.0,25.0,28.0,18.0,24.0,23.0,17.0,FCFEFEFAGEGCGEAAAEGEHFHEGFGDGDEDBDEEECBBBEDFHFAGHCAGAFAHABFBFDDGECEBGFDFCFCDBEFABGEDACACDHDHDFFCDCACHCDBBGCDBHBHCFCDHHHBHBGFGFADDGDCDCHCDCACAGAGCDDABCEGHDHFGGDDEAFBFACACABGBGFD,False +292,22.0,21.0,17.0,19.0,16.0,16.0,15.0,29.0,EFHHAHDCDEBEHEHEHEHEHCFDBCBDHCAFEGGHDDBDFGFGHCFDDDDAFADCGCFDFBFBHGAFCCBBEEAAGAGDEDAHAHAHBHBHBHEHCABABHBCCCHCBBBDAHGFDEAEAFHGBGEHAFBGHAFAFAHABCDDECGCHHGHGAB,False +293,14.0,10.0,22.0,19.0,17.0,10.0,11.0,13.0,FDGGCACGCDCACBCDCDGHHDHBHFGGCCFBFBCBDFDAGEHAHEFECBHGDDDCEBBADCDFDADEEEEDEBHAHAGCGCBDGECEHEHAACADAHFHFEFCCECEDECCDAEA,False +294,21.0,23.0,11.0,16.0,19.0,13.0,19.0,13.0,ECDFDEAGAEAGHBFEFGHBBGBABABGDGCCAGHBHFEFGGCBDGDGDGHFHABAECEAGHFDFEFBFECECEFDHGFGABAEHEGEBBBBEBADFEHEHBDBDADADGBHADADHGAEBBBDCACECBCAAGA,False +295,16.0,21.0,15.0,23.0,14.0,18.0,17.0,12.0,DDBBHFDFGBGBHBFFFFFFFGEBCFCGHABBEHDDDDBBBBDGFHFAEDHDHCFCHCECBAHACDCDHAAADDECACAGABAGEFEBCAEACGDGFEFBGBDBCBGGDDAEFEDGCGEGEDEDGDBABADFHCHG,False +296,2.0,5.0,5.0,3.0,8.0,3.0,7.0,5.0,GHDHFBBGGCGBHEHBCACHCGCGEEEEFDADBEGEFE,False +297,8.0,7.0,6.0,6.0,3.0,4.0,7.0,7.0,GDGFBFEFAAEBDBDBAGAEHBDBHCHDGBGCGHGHAAACHCHAFCCD,False +298,10.0,8.0,9.0,8.0,12.0,10.0,12.0,8.0,AAAAAADGHGAEEEHFHEHEFFAGAFHCDCGEBCBCBFBFAFHFGGCGHEDGDFDBGEDEDCBEGEGHCBEBCCDGF,False +299,2.0,2.0,2.0,2.0,1.0,0.0,0.0,1.0,CHCEABDBDA,True +300,21.0,16.0,12.0,20.0,12.0,15.0,16.0,21.0,HFHGDDEFBFBFAGCFAGBGDHEHBHBHAEFBDGACHGHAHFFDFHFHEBBCBDBDBCFCDCACAEDEDHAHBHECABAGCEBHBGEDEGAAHAFAHADCDEGEGADFGAGAHCDAGADAHCHDDGDGDHFBF,False +301,18.0,17.0,21.0,18.0,14.0,17.0,20.0,23.0,BEBFFCAGAGAGHGHFHDHCFDFDEDEBEBEAGFBCCHCDCBCHHGHEACAEFGBGBEDEBCDADHFAADBHBHCHFDFDFHGBGBAEFGFAAEHEHEHCCGHDDDGHCCCCAABCGCGCADACABFEHDBCFHGHGDAHHDFGBGFG,False +302,17.0,9.0,16.0,15.0,18.0,20.0,16.0,20.0,CFEHGDGCGHFADAFGFBFHABACDEDEDGAEHEHCCCBCEFHGHAEAEAHAHEHEHCDFFAHDEAFDFGBGDHHFHFAGGFFBEHEAEAFFFDGBGCGEECAFFHEHEHDACBCFCDDDDCBCBHGAGCG,False +303,17.0,9.0,12.0,14.0,11.0,11.0,11.0,15.0,DFDFAGHHDEDEHEHECGFACAEADDHDEDCHCECFHBBBEGHBACGGGAGAHDHAAADEHEAFADGDBDFHFGBABABHBFCHAHACCFCGCEADFCFG,False +304,32.0,22.0,21.0,20.0,17.0,21.0,22.0,16.0,HABACGCBCGHGHADEGABAFHHGFCCGFFFHFHAHAGACFGEEAHAHABABFBAEAEDGDBDFFFFEGHGDDDCHFAFGECACECECEDFBEAAFBCGAGECECFCFCBGGADADGHACAEBHAHABGGDDADCDADBBBGHEFEDDDGEFBDBDBCBABCBAAAACFGB,False +305,22.0,14.0,10.0,9.0,20.0,15.0,19.0,12.0,GAGABHEFGHGABAEDECGAFABBEFEAECCAAHGHBEEEEEFHFGFGAEAGAGDGHGFAAAHAGAGFBECEFFBBGHGFCBCGCADEDBDBDBDFEECEBEDGAAEAFAHHBFCFCDHGH,False +306,7.0,13.0,6.0,7.0,4.0,5.0,5.0,12.0,BABAFAHDFDGBHHEHBDACHGHGDDBDHFFAFACEBEBEBHBCAHBHDHCGBHBCGCB,False +307,27.0,19.0,23.0,17.0,31.0,29.0,21.0,17.0,FADCDEGEBEGHDAEFEAEBHBCBAFAHAFGEGFBFCAHAHCCBDFHGCEFFCFEFEAEAFCBDADADHDFBFBEBADFCFEFBFBFDFCFGFEAHBBCCCCHHBHAAEGEBECEGDAEFDGECEFEHGAGEFEDGBABABHDHDCDCGHAEACAGFCECGGHEDCFAAAGAGCEHEGEGFGFE,False +308,16.0,23.0,23.0,25.0,22.0,21.0,28.0,27.0,BHGEFEDACAGADADGDGDBBFBCGGHGFCFCEHHDCDCEGFCFBEBEHDHCHCBEDDHBBEBGGFDECHCHCBFDFBGEHEGEDEGAHDBDAHGBGDGBCFCGCGBBAFAFABBBFGFHAHAEAGFFFGDDCABHECEDEBEHDGDEDEGCHCDCACHCAFGGGHFHFHGHGCAEHHHHDDBEF,False +309,11.0,10.0,14.0,4.0,9.0,15.0,8.0,17.0,CECHBGAHBHAHGCACBEFEFDCCCCCBCDCGAFFFFFBCBAFHFHFHDAEAHGHBHBHEHBHCGFBHAAGEFEFEGHAHDFFCAEHG,False +310,7.0,7.0,11.0,8.0,8.0,14.0,8.0,4.0,AFACGFEEDBGHDDADFCFCFCFDBGBHEHFAGDCACFCFEFBDBGBEBFCFCFCADGEGEAHCFGE,False +311,1.0,3.0,3.0,4.0,1.0,4.0,5.0,3.0,DHHBHDGDGCFAFGEBCBCGFGFD,False +312,9.0,6.0,12.0,3.0,7.0,3.0,4.0,5.0,AAEAECGCDFDHACECEAEBHBACCHCHEGCGCHCACBBAFAFCDGEBB,True +313,10.0,20.0,11.0,11.0,10.0,21.0,14.0,10.0,FHEBEBCAHAHBFGFGHGFAFCFDBDFDCHBECCCHEACABDGFBFEFAFAHGBFBDBDBFCCCEBFGGBGFAFABEEAEGBBFFDFBFBDBGBGCGDEDHFHDGGH,False +314,11.0,11.0,19.0,12.0,11.0,7.0,10.0,11.0,GBHBFGDABADADBDCDADHBGCECHCHCGCEAGCGCDCFEAGAEAEHECEFFBECDCGEHCBBBCGDHDBDADCFFEFCACAEBHHCHGHC,False +315,15.0,20.0,19.0,23.0,12.0,16.0,12.0,15.0,CCCCEFDBDHDCDFDCHFHFDEBACECHCGGFGAHDDDBACFFFDFBBABABDBACADAHCHDGCFFBHHDHDHGCCACEDBDECEHEBABHFDDDDGEFBFBGBEBFAGAGBGHEHDFEBABAEADBCGCG,False +316,6.0,8.0,6.0,3.0,8.0,2.0,0.0,9.0,CBCDFDHABAFEHBHBHECEBECHHBEEECEHAHCDAHABAB,True +317,5.0,12.0,12.0,7.0,8.0,8.0,7.0,11.0,CHGBGBFBFDABACAFFFCECHCEGDBBGHCCBGDGFGHEHDHCHBBCCECEBEAEAEHDCDHHBHBDFF,False +318,19.0,29.0,24.0,19.0,24.0,39.0,20.0,15.0,CFEFGHBHFHCEABFCCCFFEFEGBGBAHAHDBABCBGBGBGAGAGABHCCCFFFEHEDGBHEEDHDEDBHFDBCBGBFCFBEDFAFCFGACEFGFGAAFFFFDFEFECCGEGBDAAECECABEFDFCEAEAHFDBABDCHGBGBGBCACBCBEFGFGFCFHDDFAEHDFFEDDFDFBFBEBEBFHFCD,False +319,8.0,5.0,5.0,2.0,5.0,4.0,3.0,7.0,HAAEAHDHCBDEAHCGFGCEABAEAFAFHFHBHBCBCEG,False +320,4.0,0.0,2.0,0.0,3.0,0.0,0.0,1.0,CACAEAHAEE,True +321,19.0,25.0,20.0,14.0,21.0,25.0,19.0,10.0,ECEAHAGAGDCFHAHAHABEGAGBEBFFFFFGFDFDFGCDCBABEBGBFFFAGADFDGHGABAHAGCBABGDGEEACAEDBCBCEEFHGDDCBCEGEFEBEBFGCHBHBEDFHBCGEBCDCFCEBEFEBCBCBCBAGFFAFAFDCGEEFDCBF,False +322,4.0,3.0,7.0,8.0,3.0,3.0,6.0,6.0,AGDFDFDAGECEDDHCHGHCBFDEBCBCHCHCDDAHAGGG,True +323,20.0,23.0,10.0,13.0,14.0,23.0,24.0,21.0,AGAFFGHGEBBCDCEEEGBFAHAEGEGCGFGAAEBGHEBDGAGEBABEFCHAHADFBFDFBHBHBGBEBFBFHCACGCGBFBFAHAHFEFDBGGGBGFGBBEDHGHGHFHDHDGDHBFBFDFHFHFACADAGEFHCAADHBHCADFGA,False +324,6.0,10.0,13.0,15.0,5.0,10.0,12.0,7.0,ABBDDDDGDHDCBBHCHGDGBAEGEGHDBCFGFBEBADGCGCGHFFFFFCFCBDBDGDCAAAFDHCCCECDFDHCGEG,False +325,14.0,17.0,16.0,18.0,24.0,25.0,25.0,12.0,EAGDFBFEHEFGADABCCEGEAEGEGHGBFBDEAEDHDFEFDHCHGBGEECDCDCDCHCDEAEACCBEGAGEBFBFBFCCGFBEBCCDEDFDHHGAGAGEEFFFFFBGHGHBDECEBAFAFDFDGGGAHBEFGFGFHDGDEFGCABFBFGG,False +326,10.0,8.0,13.0,7.0,11.0,10.0,9.0,12.0,HGFCFAFCFAGADEDBHFCFCHHAHACEBECCCCEGEFEFGDBFBHBGBCEEABCECAADDEDHDHBGEGAHCHFHGAGH,False +327,13.0,9.0,7.0,7.0,11.0,9.0,9.0,4.0,EFEGEFABAFHDBFAFGGEBEFECCCEFFDADBDGEGAGABABABFBDDAEAHAHGHEAAGDECCCGCB,False +328,11.0,7.0,14.0,13.0,15.0,16.0,11.0,12.0,HHHHFDGEGFHFHGDGCCHFBFEDBAHGFCDCGGDDACACEDBGEDEHHGHEFEFCFGFAAACADHFAFCFCFCBDBAEEEEGDFBFAEAEDEDEBCCC,False +329,14.0,9.0,16.0,7.0,13.0,4.0,16.0,18.0,GCAEFCFCACAEDGGEGBGBGBHBHAHECAAAAHAHECECHGHADDCBCFCHHGAGEGDGEAECGBHDACECBHDCDGHCHGEBHBHEHCFGEGHHA,False +330,6.0,12.0,18.0,17.0,8.0,10.0,10.0,6.0,GGFCECDCDCAABEBEHEFDDADGDBDHGFBFBEDHDFBHGGCBCBCDCBCHDGCBCBEDCDGDBECADACCCFEFGFGFHDADFCC,False +331,11.0,25.0,21.0,16.0,17.0,27.0,21.0,23.0,FFFCHCBCGHHHGGCEBEDFCHAEFCFHDBDBABFBFEFBFHDHFBGCACHHFBFDFGFBHHDBEFAFAFHFEEEGEGEGEDBHCDCACHHGFGFHHBDBDBHCHGEDBDECECECFGBDBCEGGGGCCBCAAADAHBBBGBGFGHDAEFGFBBGHDCFCF,False +332,31.0,34.0,15.0,23.0,18.0,19.0,14.0,23.0,HBFBAAACBDEABCHDHAHDFEFHAAACDEBHBHBHBCBHBHBGCAFGBGBFFDFGAEAEBDFFADADACADDDHAHAEEBFDFGCCCFCAEGBCBAHCGEEEEEEBFDFEHBBBABAHADBDEDFGHHBHBDDABBHBHDHFCFCGEBAAAEGFDFDGDBBBAGAGABAGHBHCAD,False +333,20.0,17.0,9.0,14.0,13.0,13.0,13.0,14.0,ABGCECACBHDHGEEHEHBDAAAFDEDGDFAFABCCGHBABEBEGADADFDEHEHEGBGAHADDHHGHGCGFFABAFDBDHABEFDCDFFAFBEBHBAFAFABABGCECHGBG,False +334,7.0,5.0,2.0,4.0,6.0,6.0,4.0,9.0,GCGBFBHAHEBEAEDCGEAEHHFHAHABFGFHFHDEDADAFHB,False +335,17.0,13.0,10.0,10.0,9.0,12.0,9.0,20.0,AGHHAHAHCBABFGADADEFEFEDBBBBHHGHDHBCECEHFHFHBHAHDEAEAEBEHACAGADHCHBGGFFFHACBDFDAGHCDGDCFCACFHFBBHGAA,False +336,10.0,13.0,6.0,5.0,11.0,4.0,11.0,9.0,EGEBEBEGEBAHEFBCBEHGDFHFAFCBHBGDABHGGGBGCGBABADHDCEABABADAEEGAGCHCHEH,False +337,17.0,16.0,15.0,8.0,14.0,17.0,17.0,24.0,HBGBABHBHDFFAHAHAGAEAEAFACGCBCECFGDGCCEFEFHHHABGFCHDHGBCBHBDGDHEHGHCFCHGHDHFHFBFDABHBGBAFHEEGEGECBAGEHBHCHEFEADCBFGHCEFGCGFAAAAF,False +338,18.0,20.0,22.0,16.0,18.0,27.0,14.0,22.0,AEAEAEAFHDHAAEFBDHGFGFCAAAGADFFEFBADCHCHEGBBEBGFGFGEHEDCFHAEBHCDCBCGAECGCHCHBFBEBHHHGCBHFDDGHHHCHBDEDECBDFEFBFGFCFBFBCBFBFCDEAFDGABADADBFFFFECECADHHHCHCFCFCG,False +339,24.0,25.0,25.0,23.0,21.0,21.0,28.0,25.0,ABAFDFCFCGHGCDBDGEGEGCAAEBHBHGHGHDADCGCHFECEBDHDABHGCGHDHEEEBFBFBDDCDGEEEHBFFCFBFAFAFGCCCHGGFGCACHEDEHGDDBHEHDACAFHEABGCACABDBEBFDGHGHFHEAEAEADACGGBBBCGCGDGBGBFCHAHAHFBABFCEHBADGDEBACGCGFAFDHD,False +340,14.0,19.0,9.0,8.0,9.0,16.0,11.0,11.0,CAADABAEACBCBGAADHBFFFBDBDEGABHHHAEFHBCFHBEBGFDFBFBDBDBDAEGEGEFCGBFBAEGBGFGFHFHFGFCBCAAGAFEHHHCBC,False +341,2.0,6.0,2.0,4.0,1.0,4.0,1.0,1.0,ECBDBFAFDFDBGBHBCBAFD,True +342,10.0,9.0,6.0,7.0,9.0,12.0,7.0,13.0,AEAHAHFEGEGBGAEBBHFDBGBHHGHAFAFAFHFDDCDHECFCACFHFHCDCDHBEBFAFGFABEEEGBDHH,False +343,12.0,23.0,13.0,17.0,19.0,18.0,25.0,20.0,GCGCGCFABHCGAFCFDFBHBHEECDDBEHEAEABABAHHFFDFGEBEBGCABAGGEGEDEDHBCFDHDGBGDGHAEAGDHAEEECHHFBDGCFCDBDHFHBBBDHHCBEHFHGGGFGFBEBEFEFCFGFGHGDGDBHBGBABDGEG,False +344,8.0,19.0,17.0,14.0,18.0,17.0,16.0,26.0,BFBHCHCACDDFCHEHAFAFEEEDHGHBEEFADGGFGEEDEDEFEFBFBHHGHGHDEFCGCGHDHDBCHDBCFCGEBHBHEHFDEAEBEGCGBHBFBHBCBCBCBGACCHHHGHFDFCFHGDGHEHDCBAAFHBG,False +345,14.0,25.0,9.0,16.0,24.0,29.0,24.0,20.0,BDBDFDFEGEDADGGGGDFAABHGFGFEBHFECHCEDBABFBEDGGCFCEAAHGHFBBHHHHHHEBEBFAEEBEDGDCHEFBFBFBHEGEGEAEBGGCAFFGDGAGAGHFFFFFGCHAHBHDEDEFHBBBFDFHFBFBFBHDEFGBEDEGEGBAFFCACEG,False +346,20.0,21.0,26.0,20.0,28.0,15.0,21.0,20.0,EDEDFHFHEDCCECEHEHCGBBAEFDDHBGBEBGAEHECGCACECGCGCDEHCAFAECHBBDGDFCFBBHBEBEHDGDBDCAGACAHAHDHCEBEHEACDDDFFAGAFAFCGEACACGEEAHAGAGAGEFEFHFBGCHBDBHBCGDGCECHDHFBFDCGCBBEBDAEGEGE,False +347,9.0,10.0,7.0,7.0,9.0,11.0,7.0,1.0,DAFCBCBAFDEGEGEFAADGEGEAEAFGFBFEFCFGFCFHEDCBGBEBAFDDABCBABDBC,False +348,23.0,21.0,22.0,23.0,12.0,21.0,19.0,12.0,DBGBGFCCGCDHGFGFGFDCDEAEAFBFBHGHBCBABAFFFBBAFHFCDBFECCDCACAEADFDEDGCFCHBBBBDFDCGAHFGEADDGHFFDADEGEAEFEDECACACAFADCFCAGBBABEDGDHCGCACACHBDGGAGBGBHAHADDDHB,False +349,24.0,18.0,28.0,33.0,14.0,23.0,32.0,22.0,DBDACACDEGGCFCBGBHFGDGDEDHHADCFBFDFDAAFAGDGCFCECEGDGFBAGHDDCDCDGHCFFAFGDGDHDHFGGBGHDCDCAHFEDBFBFCDDEDGHAHADABHBEAAACADGBGAGAFHCCGFGCGDGAEAGDGHFHFEBAHCFCFGGGEGEGAGHBBBDCCHCHFHCHDFDBDCDEHECBCEAABC,False +350,8.0,4.0,6.0,7.0,7.0,4.0,16.0,7.0,EDGFGACAGBHBEBAGACAGEEEEEGGAGCGCDAFHGDCDHGHCHGBGAFDFDGGGDHH,False +351,14.0,22.0,13.0,15.0,4.0,11.0,14.0,13.0,ABCCHHFHCDBDBDBCCGCGFFDFBFGGBAHADDGDCDCBAHABEFHBBDBDBDBEBEBGDAEABDGFHBHGAGCBFHHHHHACGBGACFBBDGDBFAGAGACACF,False +352,23.0,10.0,18.0,19.0,18.0,25.0,14.0,15.0,GFADHDHFCGCBFFFHHEDFDHAEEFECAGBGEAHAHADAEGCBFBFEGEFHHEGGCFCHHAHAHEBAADAGBEBEDEDGFEFAFADADFGFAFCECECFFAFACACHCDFDADCDGGFDHCCCCDGDAFBFBEADBDAECF,False +353,28.0,26.0,15.0,29.0,24.0,17.0,31.0,29.0,EFGDADGCGBGBGBEAEHGHFDDEDEDEGHGEGEGHGHEHGDGBGFEAEGDCHCHDHFHEHAGDHDFEBEBEBEDCDCACAFGFCABFEGBGAGHHBDBABABHHAHAECEAGBGBHBFEDHCFCDGAFDHBEACFHHGDADHCFCBAAHFFGFDADBBEBHACABAHGDGBEAFABDBGGGGDDDAAHDDDHCHAABE,False +354,2.0,5.0,6.0,7.0,4.0,6.0,4.0,6.0,BHGHAECCCFADBDHDEDBFBHDCDCDFGCGFGFHHEFEB,False +355,6.0,5.0,6.0,6.0,6.0,7.0,2.0,4.0,HFHCGCGBFEAAAHAFBCBDEDEDEDCDFFABBCFCADFEHE,False +356,6.0,7.0,14.0,10.0,18.0,19.0,15.0,16.0,FBEHFGEHFDCDGGGEHCDCDFFFHBABDFDFHCCFEFECEHEFCAAGFGBCBFGFEBCACACDFFGHGBEHEHEHFHCCEGEGEGECAHEDEDGDGEHHHGHFF,False +357,14.0,24.0,11.0,19.0,13.0,13.0,20.0,12.0,CAHGEBBDBFBEGHAEDBDHDGDGECACACEFBDBFFGADBHBCCDCDHDEGEAFAFEGBFBABHFHAEDEDGHGBEBGBGBGFFBCGEGDAFAFAHAEBCGDDAGHHBCBDBDBFBDBDCGGGGH,False +358,14.0,23.0,16.0,16.0,14.0,16.0,6.0,16.0,HBCBHFHFHDBAGAEDCCCBFDFHFHDHDHGHABCFCFAGEGBBBFDADADBEBHFCFDFCBADDBCBCBCAEGEFCBABAFAHBFBEBEBCCEEHEDECBFAEHGADHDHEHBDEFBCDA,False +359,13.0,21.0,20.0,21.0,14.0,16.0,20.0,15.0,GFDBDCACAEBEBEBHBCBCECEGACHCHAHAGGBADADBDFCFHGDGDGEBHBDGGFGFGDBDAGABDGDGEHFDAEFFGFDHEBCCDCHCFCECHGDBCEHEFDFDABEBGDGHACFFBDCEAFGDBCGCBCFHBHBH,False +360,2.0,2.0,1.0,1.0,3.0,6.0,2.0,3.0,GFFFEFEBDBEHGCAHAHFF,True +361,14.0,17.0,14.0,17.0,23.0,22.0,11.0,18.0,DHACABDDDFEFBCAEAEAEFCFEFCFDFHFAFBCBCHGHFHEAEGBHBGCFCHAEBEFECECGFEDEFCCHAFAFAFADGHGBGDHDEDAHBHBHGEEBDHDBEEHGDEDEFBFBFHFGFBDAEBDGCHEEDCHB,False +362,7.0,7.0,14.0,4.0,6.0,6.0,6.0,3.0,CCBCGEGCAFAEADAGFGFCFCBCGHBBDBCGEAHAFCDCACBCHCEEFECBD,False +363,10.0,8.0,17.0,16.0,17.0,20.0,8.0,12.0,FEADABEGEHEBEBECFCDCHBHCAEEGHCFGFGFHHEFEFDFGFDECCACHFFFCDCGADAFGDCDCDCEFFFFAHAHBEECCDADAFFBEDEDEDHCFCDBHGHDB,False +364,8.0,4.0,4.0,12.0,13.0,9.0,10.0,11.0,FFHEHDFFAGEGEHEHFGDDDEDECEDABHFGFGDGAFADAEECGGABDBGHHCDCBGFDHDHAEAEHEHE,False +365,6.0,2.0,5.0,1.0,4.0,5.0,1.0,5.0,FEACAGFEFHCEABABAHFFEHAHCHCDC,True +366,11.0,5.0,9.0,15.0,4.0,9.0,12.0,5.0,CCFDEDFDFEFEHDBDCDHGGGGDFDAACADABFGCBCAGAFDFCGCGAHAGAHDBDHCGEBFDADADGG,True +367,22.0,11.0,14.0,10.0,20.0,19.0,35.0,19.0,DGGGBCECGDADABABHEHBHGAGHGFAFAGBGBGEEACACFEFGGGEFHCDEEBEBAHCEFFFFHAHAHGFECBHGGEGEHAHFGBDFHEEGCGFDAAAGEGAGFEFHFGAGAGDHAACAGHGCGAGDGBFHFGCGCECEHFHDGEGCD,False +368,2.0,3.0,4.0,0.0,3.0,2.0,2.0,2.0,BCECECHFHFAGEGBBCA,False +369,2.0,7.0,10.0,3.0,12.0,8.0,6.0,9.0,HHDHDCCEGEFFFHCBBHDEGEHEFEFEFEFBCBEBHBCCGCHEHBGGACECEFGAC,True +370,17.0,20.0,13.0,14.0,12.0,20.0,18.0,16.0,HEFEBECCHDECGCEBBGCDBDBDGFGFAFHGDDFDHBBBFAGDFAGACEFHGBFDFHFHFHCGBEDHFCFCFGAAEDECEFBFAHABACAGAGACAHABFBFGEGDBFBHBHDHDGBABAGCGEBAHGH,False +371,14.0,16.0,16.0,7.0,13.0,5.0,11.0,14.0,GBGBEHFHFBBBECAABDEABAGAEDEDBCEGECCACAGACACBCHCECEGABDBEBHBHFHCDAEADHCHCHFHCEABBCDHEGFGCHBGGHGHA,False +372,9.0,15.0,11.0,10.0,12.0,17.0,13.0,14.0,BEBEBGFFBFGFDFGCGCGFHDGGCFAFAFBFDHDEAEHEHAFBFEGHHEBGAGCHHHDDCECGCABFBFHFEDEDHBBCBGBCAGACAHBECEDDHBHFF,False +373,14.0,9.0,8.0,14.0,6.0,19.0,18.0,14.0,BHEFAHAHDDDDFBFDFGFEFHGBBFAAAGADHGBFCDGBEFGFCHHGFGHGHFHGEGAGEEAGDDABGGCCCBHBHCHDFAFAFAFGFDFDADADCGCGHF,False +374,13.0,6.0,13.0,5.0,8.0,10.0,12.0,6.0,CBGADAHAHAFAFGCGFGCDEAEADADCBHDFAACCCAFHBBCEGEGECFHAEBEHCGFGFGEGCGCFCGABF,False +375,8.0,5.0,6.0,3.0,11.0,9.0,8.0,4.0,EEEEHFFBFGGCGHGEBABEEFCFCBHGDBHFAFAFDFGAGDGAECECECAAAE,False +376,6.0,8.0,6.0,9.0,8.0,5.0,12.0,5.0,AEGEBACACHCGGHDBDBCEGEBEBHFDDGDCDBDBEGCAFBFGGGEHEAADFDFHGGG,False +377,2.0,3.0,2.0,5.0,6.0,4.0,2.0,2.0,EDEDECEBHBGFGAEADFHBDFEFDC,True +378,18.0,11.0,12.0,20.0,13.0,19.0,14.0,21.0,GAEHGHAADADADBFCECDCFCGDDFCGHAADFFFGHBHFDCDBFHFHGHFAGAGABADDHAEDECFFFAFAFDEDEBABFBGGHBCBAACBHHHFFEDEDADBEHFHGCGEEDHDCDGHGHEHEHCH,False +379,15.0,10.0,10.0,14.0,7.0,13.0,13.0,11.0,FHGHGHBBCDDDDABABGCEDADCHGAAHAFCFBDBDADFCFDDHCHFHAHCHCBCGGAACAHGGGGAGBEDFDFEAGDGFEBEFFAFAEBEF,False +380,20.0,20.0,27.0,28.0,18.0,28.0,19.0,15.0,FAEAEHHHHHHECBHFFFCFCDAGFGDEDCDCBGFFCGBGEGBAEAGFCADGGBEBEFHFDCBAEFDFDEDAHAHGEDAGBGFEBEGFDDDFDFAFCCCCCCBCBCGCGCACDDBFAFBCDADCDEDBCBCGHGFGBBAFDCDHBHDDBDCECACDFDGABFEDEAEFHHAAFFF,False +381,9.0,4.0,8.0,8.0,10.0,3.0,5.0,2.0,DEDECFCECEDAAACHEGDDFDFCACECGAABDGCHBEBGDGBAEAEAE,True +382,28.0,23.0,23.0,25.0,22.0,19.0,22.0,24.0,EBAHHEDEDBDHHGADFEFEHDHDGFFDFDADHDGEACBEHEFGDGAGAGEBCDCBBAFECHGGBHCHCGGGCGAFCHCHBBEBFBFHFCGCGEDEAAADABABADFEFDCDCECDCHCHCBAAAAAAHAFEGEADCCFHFEBEBFHDHFAAAGCBBBCDHDEDFBEGHCBDBGHGCGHDEAGABA,False +383,4.0,5.0,2.0,2.0,4.0,7.0,4.0,2.0,FAFBFGCGAGAGFBDEFEFHABFBDCHEBE,False +384,23.0,10.0,11.0,21.0,17.0,14.0,20.0,15.0,CBEFFDDBFAGHDAGAGAGDDBEGCCCDCBHHEAEFGFEEEHEACACAGAGBDAAHFHFAFADEHCACGDAEEFGGHEHBCDAGAEDEBFGHDHEHDHFHAGAGAGAFAFABBCDGGGDBDGDEDEDFDHD,False +385,16.0,15.0,15.0,12.0,17.0,20.0,20.0,23.0,FGBHBHAHAHBDFEFEBCAEEDEAHBHBHEFDCBAFCFAFAGHGHGACDHBCAEHGHBABFCFDGDFDFHFDBGFGHHACADACHCGBEBEHEACGEGFGFGDGEGEGECEADACBGFHHDFFHFHFGGBHCGCEEHC,False +386,22.0,28.0,19.0,25.0,19.0,24.0,12.0,27.0,BHDGBHDFDFDBABGDHAFAECECBCBCFCBEBHHHEEEBAFDFAFADECBDFDFAEHBHEHEGEADHHHFHFHDBFHAHADADFDFCAHBCGCDCBBBGBFAFCFHAGADDBFEFEAAHCDCECBDFFHFHBHBFEDCACAGEFDHGBEHGBCBHEEGAGHBDBDGHADADCBCB,False +387,16.0,23.0,23.0,12.0,27.0,6.0,20.0,14.0,EDEBGBEBCGGHCACBHBEGAGHGCGEGFCHBDCHGHBHGDADADBBCHCBEBACGEGEGEBABABDEEHECCCCBBBGAGAEAGFGHACCBBABAGFBEEEEEECGDDCDHEEEAEAECDCECGCFHFCBCEADDHEBFH,False +388,29.0,22.0,29.0,26.0,26.0,22.0,19.0,18.0,CECEGHFBFDDCDHGAFBGDFAAHACACAEEBEACFCAEECCGCGCFFFABGBGDCDGDEAEABHBHBFBHAHDCECECHFEFBACDDDEHAGABADFDFDBDBDECECEDHDAAAAEBEGAAADGFBFADACHEAACFGFGCGEHFHFCCCDGGBCEGFAFEBHCDAGBCBCDCEEGDBDBDHFHEBEHH,False +389,6.0,5.0,9.0,6.0,6.0,10.0,3.0,6.0,AFFFACCCEHHHHACDFDEGCBCDEDCFBFBDBFHFHADGCGCEFAFAEBE,False +390,5.0,5.0,8.0,6.0,3.0,4.0,2.0,9.0,CHCGBFDADACBFDFCHHDHDHCGCBFAEAEAECHCHBBDHH,False +391,17.0,18.0,29.0,20.0,13.0,16.0,17.0,22.0,GDCDGHHBEBFCFHGHAAAHBCDCDHFHEHBDDDDDCDCACHEBDBCBFDACBCBHACCDCGGGGCBCFCFBACADHHCFCADHHHGCBBGDGCGEEHEACAGGFGCABABDBEECECECFAFAGHHDHDFBFGFHECEFDFAHBHFGCACE,False +392,4.0,11.0,10.0,5.0,8.0,5.0,3.0,15.0,HHHHEEDDBGHGFABEBECCBHBCBEDECBCHCBEFEHDBDHAHBHFAGCHCHCBCAHFHF,True +393,5.0,6.0,6.0,2.0,4.0,4.0,5.0,6.0,HGFGHHHAGCGEFEBDFDAAHAFCBCBCECBGBEBHCA,False +394,21.0,28.0,17.0,22.0,17.0,15.0,15.0,14.0,DHAAAAFCDBDBDGGABBBCHCACGHFBBBBBBBAAAAFBBBBBEGEABCGFDHEHEDBAADEDEDEHCFEBEGDHFGGECDCHCHBDCEFEHDBDBDBDCECGCBFDGBADHGGFAFAFACEGEFDFBABFFEGDAACACHEHDHDCG,False +395,17.0,17.0,23.0,13.0,25.0,16.0,32.0,27.0,ACFCFGGGEEHEGGDEHBACACECEFEFHDEDFDGEGBGFHCCACEEFDACHGHGHBEEHBACCCCHCEFDAGAGEGCBHBHBGGGDGCFAHGHGHCAEFBBBHBGBHHEHEBGGEGEFHFHFHGHGCFCGHGDEDAAAGCBBBCHAEAHDHDFGGGEGBAHECDFDCAE,False +396,2.0,4.0,1.0,7.0,6.0,10.0,8.0,9.0,GCGFGFGHBFAEGFHFHGBDHEFEDHDEFEFDFEFBGHHAHGDBDHD,True +397,12.0,14.0,13.0,17.0,13.0,20.0,12.0,15.0,CEBHFCBGHGEGEACAHBHBDBGBADFDHDFDADHHEHFHBAAFACECECEDDGDGDCCCHCGBBDGFBECGDGACFFFFFFDHDHAEFEFBBGBFHFHECAFDBEHDFAFAEGFD,False +398,28.0,19.0,7.0,24.0,27.0,19.0,20.0,15.0,DHEAEADDHGAAHAGEHEBDBDHFCFEFEFEGAGHGBFHECAAGDCDADFCHDADADFDHGBGAEHDGFBFAFAFEFEFEHCAAAGGBBABDBCEADADFEGEFHADEGGGEGEGBGBDADEEBDBDHEEEDADEBBFHEEFCFEFAAAGABABDBHBG,False +399,0.0,3.0,1.0,3.0,3.0,3.0,0.0,4.0,DDHFBFEFDHBHCHEBE,True +400,14.0,15.0,8.0,10.0,12.0,16.0,15.0,13.0,BABABGHFHEHEAEBFGHDBCBGDCFFGAGDGFEFEFEFHDCAGAGHHAHACBCBGAGEGEDBDHDEBCACBHAHCFAFEBEDFFFBFGEGFABHGDADFBHG,False +401,11.0,5.0,16.0,15.0,7.0,18.0,6.0,17.0,EGDHHBGCGFFFFECHDAFAFBFDHGHAACFFFAEHBFDFHEHDFDFDABBEAFCCCCCCCFHAGADDDCCEHEHCHDHAHFHCCCFDHDHDADG,True +402,3.0,10.0,24.0,13.0,15.0,13.0,11.0,19.0,CBBEDHAHBDBDBGCECHHDHGHDCGCGEHCHCGCEEEEHFHFECEGBDDFBHEDBDADGFHCHCGCBCDCEAFGFGHGHCECFDECCCCCDHHEBFHFCFCEHFFCF,False +403,1.0,2.0,2.0,2.0,0.0,1.0,2.0,2.0,DGDABGBCHCHF,False +404,5.0,16.0,6.0,12.0,8.0,5.0,12.0,9.0,DGDHBCBCHGEEHEFGFBAGABADDCDBBBBBGAGEEDCDGHGHFHBHGGCEEDBDBDBCBDBGFAEBHFHGD,True +405,21.0,16.0,12.0,16.0,13.0,10.0,25.0,18.0,GFEFBFGGBGBGBHFHEBEBGBGFGFCEAGCDHAABHBEGCGHDHAHDCEGDGDBFGCAAAAEAGADFDGDAACACECEBFDHBAEACHGHAHDEDEFHHHBGEGACDBAGGBCBHHCDGAGDGHGHADAD,False +406,4.0,4.0,3.0,5.0,1.0,0.0,4.0,3.0,GBDDABCBCGDGDCHBHDHAGAEA,True +407,16.0,7.0,6.0,14.0,13.0,6.0,14.0,8.0,BFCAAAAAEFEBDFCFCADGDBDBDAGAHAEDEGHGHGFDBDGAEHEAEAGCEDHAEADGDAFADGGEGHGHDEBEHDGBGCCE,True +408,12.0,15.0,11.0,21.0,18.0,14.0,12.0,11.0,DBDBDBDBCBGGABCEFEFGGDBDAAAEHEFEBGBECCFCBGEEAEHCBFEFHFCEBFBHGADFDACABEBEAECDCGFDDDDDDHGEGFDHDHDHFCDDEDGAAFAFHHGHEE,False +409,20.0,21.0,28.0,22.0,20.0,26.0,20.0,22.0,FCFDFHADGDHDHBBCCHHDHDHDGAABAGCGCDCDFFFAEAFBHHGHCHEFEGBDCDAAHABBCFHFEEGEFFFCHCDBDEDEFEDAFAFABEHCCCEBHBDGDECCAAACDGFFEDHDFBHBAGAEAEFECGGGCHCDAHBGBDBCBEHGFCFCFCFCEGEGHFCBGFGCGCEABBB,False +410,3.0,1.0,3.0,3.0,0.0,0.0,1.0,2.0,DGACBHDHDCACA,True +411,10.0,24.0,18.0,15.0,16.0,10.0,24.0,18.0,HHFBFECHGHAHFGGDCBCBCEGHGBBAAGCCHCBDBGBDHHHBFBDBGGCGHGABABACEHEHCDGDECBAAEFGGDGEADDDHDHBEBEGEFEGEGCGDGDEDBCCCHCEBEDCGFGHGEGFBFBACHBBBBF,False +412,7.0,7.0,14.0,10.0,10.0,6.0,9.0,5.0,GEDFDFBAGCDABADDGAHEDEDFDCDCDFHCBCBCGCHBGCFCAEEEEEGEGCCCHHGCBEBCAGAF,False +413,1.0,1.0,2.0,0.0,2.0,2.0,3.0,2.0,FGCGCHEHEABGF,True +414,3.0,7.0,4.0,3.0,7.0,6.0,6.0,8.0,HCHGEEBABABFBEGFGAGBDFDEHEFCFBHHHFHCHCBEEGGD,False +415,17.0,22.0,23.0,22.0,24.0,17.0,20.0,16.0,BCBGBADDEHEBECCCCDGAGEGEAACEHEHGFABAEHECECFCGCECDBACAHADECGCBBFGFEHEFGDGEGCGFGDHDCBCAFGDGDAEFHFCFBEEHEBDDFHHHBAFAHDEDGDBDEDECFCFHFAGCFFAEGDGDADCBBBBCGHHABBBBBDED,False +416,23.0,23.0,29.0,23.0,28.0,15.0,36.0,18.0,HDFEEHAHFECBCGDFDFBAGABBGGADFDGEGECECGDHCECECEDEDACACGEGCGFBCBCACEEDEGGABHEDCHBGGGHGCGCBDBCCCEHEBGBCDDGGHGEFEGBBBDBAFAFAGBFFHHADEGEDBCCCACGCDCGEAHAEADGGGDGDBFBFCGCGBGBGACAHAHGEFDADEHEHAFGHBHDEAEA,False +417,6.0,3.0,6.0,6.0,13.0,9.0,7.0,12.0,HGCCECEAEHGHGCFAFHDDBDEGBGHHEEDAFGFHEHAAADBCHCGFEEEHEHEFEFDFHF,False +418,7.0,7.0,9.0,13.0,10.0,16.0,6.0,11.0,HEFFFEDECCHHBHFDFACACEDHDBDBDBDFCFDEDEBHGEFFAFADAFHGBGCGCFDEAHDFDHGHFHCGEFEFABC,False +419,6.0,2.0,4.0,3.0,3.0,0.0,2.0,0.0,EEBDBAAAACACEGGCCDAD,True +420,20.0,21.0,13.0,17.0,21.0,27.0,25.0,13.0,HAGAGAECCFDBEADDGAGFFDCBFFCABGBEBAGCGBFBGEGEFDCDEBFBEDCAHBHBDFDFBADGFFEGEGEFEFEFHFBBABAHHDGDGBGAGFGFGEEDEDAFAGDHEACACFFGFGFGEDECBFBFHHHGEAFAEAHFBEBGBCHCHGADC,False +421,9.0,14.0,14.0,8.0,6.0,14.0,12.0,12.0,FHFDFDBBBGBEBCBFDGDHFGABCGABBGEAFAHACACHDDFHCBBFHFHFGCHCHGBBHHGCGCACACHCEFEFADDFEFEGGCGCB,False +422,2.0,4.0,4.0,2.0,2.0,3.0,4.0,6.0,HFCFCECBGGGDGBEHFBAHAHBHDHC,False +423,19.0,10.0,8.0,8.0,6.0,9.0,8.0,8.0,DEABABCFEFDAAABFHFAFAFADACCGBABAGHBABABAGHEHCGDGDCDCGEHEGDAABAEHBAGACDFFCFHH,False +424,22.0,16.0,21.0,30.0,13.0,19.0,17.0,12.0,BCBEBDAEAEAHAHGHCBCAAEADGFGDGDCACFCDEGCDHBCADDDDDEABADADADAEGBGBHCGFAFDCDBDFACDBDBCFEHEHAHGFGFGFGECHFHCCGDGACDFDECFDADEBHFFDFDFBFBEHAGCGDFCBGDACBCFDAD,False +425,12.0,15.0,7.0,11.0,10.0,19.0,9.0,9.0,CADACAFHFDDCDBFBDBEBEDEHFABACFFHHGFDFDGDGHAHACCBEFDFGEGEADFFCEGBABAEHHBHBGBEBABGBEFFFFABGFFF,False +426,10.0,14.0,11.0,11.0,11.0,17.0,18.0,9.0,BFBAAEFEHCHGAFEBCFCGCGBGFHFCGGAFAFBFCFHBBFEFEFEBGCECBGBGCDFDBDBDGAGEFEGHGHAADEGCGHDBAEGDDDDCDFGFGABHH,False +427,37.0,20.0,35.0,16.0,24.0,26.0,23.0,17.0,AGAEEHGHGCCCGBGCHCHCHFGGAAAEAEAFHCHCGCACADEEECBABEFEHDFBFEEBBBCEFAFADACAFFCFDHDGBFFACDGDFDBBBCGCBAAAEAECGCDHFBDBCAAGACACAFAGGBEHECECEABFEGDFDHHAAAACHCHGHCHABEGCGFACCECFFBFBABAGFFDAECEDEFFACGCGAGCDFD,False +428,16.0,17.0,31.0,28.0,15.0,17.0,26.0,26.0,FGFCCACBEDEDBCGCGFDCAAECEAAFFGGGGHCHCAGDGDBHBHFHFHFHDHAGGDDADHDHBACGCGEDHBCDFDGDHDCCCBBBBGCCCCFBDDDBCCCHCFEHHGFBFCCAAGGDADGDHEHAGCGCBDBFBFEGAGEGHCFDHHHHEHEBEHDFDGDHAAECCCEDEDGH,False +429,8.0,4.0,6.0,7.0,12.0,5.0,7.0,6.0,AAHAGBFHFCEAEBECGFGFGEEECBCDCAEHEAEDEDHGHBCFDGEGDHDEDAA,False +430,5.0,7.0,8.0,4.0,4.0,3.0,11.0,4.0,HGDCHCBCBFGAGBGBEDHAEAEGFGCGEGAFCGCGDHDBBBCCGA,True +431,8.0,19.0,9.0,16.0,16.0,15.0,11.0,12.0,FABCEHHCGDGDFDFHFAEDGDFDFBBBBFEDEAGBEEEFEGEBEFDDGBBAAAFHFHEEDCDCGEDBDAEHEHBHBHBFGCDCHEDBFBGHGFBFBCBCGCBAHD,False +432,25.0,23.0,17.0,34.0,27.0,19.0,18.0,34.0,GBHHHFEGGFGFGHBABDBDBHGGEBBDEDHHHHAHFHEHFFFGBDDEAAAAADCDHACAFDBDCGCGDDDHAGBDHGHCHABAFEFEFEFDDBDBABGFAFEEDEDEAEBFDFDHAHABEBEDDDFHCEFEAAAECCBABHDADHCBFGDHEHAGBDHHEHEDEAECEDGCEEHDDGHCHCHEDDHBHCHCACBCG,False +433,11.0,10.0,8.0,8.0,5.0,5.0,7.0,5.0,GEEEBADHCHEBEACABDBDAHABABABCDCGCDABFDCACABGGAGHCHFFDDGFGFB,False +434,8.0,2.0,9.0,3.0,9.0,11.0,9.0,7.0,CECFFFHGHBHCFCFBFHDACEEFCGEDEDAAAGCGCEFFAAGGGHFHFHEGEGECAA,False +435,15.0,9.0,12.0,17.0,12.0,13.0,11.0,8.0,FEFHFAFEDEDBCGGFBHACGCFCHADADAFAEAEADHDBDFHEDEDBBGBDADAGAGEGECCHEAACBCDCEGFGFDADGHHFDFCCCBDGEFADB,False +436,9.0,4.0,4.0,2.0,2.0,7.0,7.0,7.0,HEFBABCEFAFABGGAAACFCFGHBHACGFGAGAGHHDHDHF,True +437,13.0,14.0,15.0,27.0,27.0,6.0,29.0,26.0,DDDEHABAHEHAHDCBGDHFCEGBBHBHADDEAGGEGDGDGCCDCDBDBHBHBAAHGGGGACECEGGGECCDGDGEGADADGFHEEDEGACAGHDDDFDFBEHCHGHFHEEEHEHEHEHEGEFDGDGHBCCEDHBCGDHEEBAGHGEGEGEDHBHCD,True +438,22.0,9.0,13.0,21.0,26.0,17.0,18.0,21.0,GAGEHFHCEGEDAFAHAHEDBDFDABAHEDGDBCAEGDDDGGGGAGEHHHGCCFHHBHBHBHAGECAGDGDGDGEHDFAGCEEFEHEAEAEFFCECFFFBDADFDADADAFEEEEAFAEEBABAHEFDGHEHFCDCDCECHCHFEAH,False +439,24.0,19.0,22.0,19.0,24.0,22.0,19.0,24.0,DCDCAAAAABAFGFDFDHGCGCGBDACCCCEHFACHEDAAEABAHABAEFHFCFCFBBHFHEHEGCGDHFECBBBGBEHEAEAHDGDGHCHFBFEFEBEDFAACDHDFBHADCCEHEHDBFGFHDHDGEGADADEDEBECHFGGAGEFCCBCGFBBAGEHFHGHEHEFECBGA,False +440,23.0,14.0,11.0,16.0,9.0,11.0,13.0,16.0,DCDGBGBAAHECEFGFGAGHHEDGBCFDFGHGEEFADAEGFBAAAABFBFDAACCCEDHHHDDAAEBHCHABCHAHAHABEDGFGBGDDDDDDGAAHACACACABFFHBHBHB,False +441,5.0,9.0,7.0,7.0,5.0,6.0,6.0,2.0,CFDBDGCADBDBDGAAEAEBFBCBFGHBEGDHDECECBCGFGFBFAC,False +442,21.0,17.0,17.0,31.0,26.0,21.0,12.0,20.0,AAAGDEAFCHCBEDDBDBDHCAAHBDBDADHFHFHFHFHFDFEADADHHCHDDCFBFACHDEEEDABADAFEFHCACFFFEFBBEHGDGEGFDDCDGEGECCCCCFCHDEEECGCFDEDGBBDBGGHBFAFEDADFDHEHDHAGDGDBAEEEBEDAHAEBEBEAE,False +443,22.0,20.0,27.0,22.0,26.0,31.0,22.0,17.0,EDEAHFDFEBGFEFHGAFAFEDEAHDFBEDACCCBCBAFADAHFCGHGHDCDCGGHBBGACADFEFEFBFBFBHBHAHAGGGEGAGACECECBAEFFDEECDFECECBCEHDFCABHBCGDHBFBFBFAEDCFFHFCFGFDEDEDGFGFGFBCHEGGCEDGCCHDGFGCCCACEDEAEABABADFDH,False +444,25.0,15.0,17.0,18.0,21.0,13.0,21.0,25.0,GCAFBBBBAFGHBACAFHCECHBEDEHHHEDAHABCGDEAAABDBHAHBEGGDGACDBGGGGHGHGCECEFHFCCGBEEEEEDFCGDGDADADCECBFFCAEAEADGDHAHAHEHDHAHEFEHDGFHFHBDDAHAGAGAGAGEFBHECFCACHDH,False +445,4.0,5.0,1.0,1.0,6.0,3.0,0.0,1.0,FEBBABEBEAFHFEAEAEBDC,True +446,3.0,5.0,3.0,4.0,0.0,2.0,5.0,1.0,DBDAGBGCGCGCBBBAGFDHDFA,True +447,27.0,17.0,19.0,29.0,21.0,26.0,19.0,16.0,AAEEEEFDFHEADAGFGFGAGHFABBBBDADAHFDGCHFDFAFGCCBFFHDHDADEBHGCAHAFCCGCHEEADCBFFDFAFACAEECDCDBHBDCCEDEAGABDBDGGGGHFHFHDEAFDCDAAABAGCGFDFEEEBGAGAHBGDGDFDFDHHACCDCEBEAECEFEFDFDBDB,False +448,12.0,3.0,7.0,7.0,6.0,6.0,10.0,15.0,GCACACAFHFHGHDHAHDDEDCFAHACAHGEFHBHBFGDEHEAAAGAGCDAEGEBHDGFGHHCHGH,False +449,27.0,20.0,31.0,20.0,16.0,31.0,25.0,16.0,CCFCACAHBDGCGCBCGCDCBBEBAGFFFCFCDCBHBEFDFDHGGDCFEDBDFDCDCFFDBAECHADBCHCHCAAAAFAFADDGFCECGCGDDEHGHFFEHGHGFGFGAEFBFEFDBHAFDGGCFAFHHHBHEAGAEAEABGHFAFACACBCACGBBAGACAFFGFGFDBCBCGEEEECFADGBGA,False +450,2.0,7.0,4.0,2.0,6.0,1.0,3.0,3.0,DGCGCBDBHCECHBEGEABFBHEAEBEB,True +451,8.0,7.0,6.0,1.0,2.0,4.0,4.0,3.0,FGFHEABCCCDBABAHCHEAGCGCBAAAABBBFGF,True +452,12.0,16.0,17.0,11.0,29.0,15.0,19.0,16.0,EGDGEGHCFCFDDBECFHFHGEBEBEBEBDBAHAHADCEEEEEEEBECCBBBGDCDCFGHHEACAGBGHFEGEAECFDEGFHCEDFDFDCBHEAEAEFBGCGBAHFHGGEEBFGFGEHAGAGAFCBHHHCCECEG,False +453,4.0,3.0,6.0,2.0,6.0,8.0,4.0,3.0,CCFCEEHCHBDEFAFAFHGDFEGEFBFBFCECGAGA,False +454,17.0,13.0,25.0,22.0,19.0,16.0,28.0,27.0,AGAHHCDEDGGGDHHFEEGEHHCGGHGABCDCDAAFCFCGAGCFFFHEEEHEBGBCFHDAEEBDCDCGCGCBHBFCFHDHGBGDHCHFHBHDHBEAFCCDEDAGCGCDCFFHGHGHGAGADACAEABFCECECEBEHAGAHHDGDGHGHGFDFDEBCHDDCDGBGEA,False +455,3.0,8.0,5.0,6.0,3.0,3.0,1.0,4.0,ADHHHDFFACBCBCHCBDDGDBDBEBEAEFCBB,True +456,17.0,25.0,25.0,21.0,21.0,26.0,24.0,21.0,GEGBFBFBFBGAHAFACDEDCCHFFGBGAACFCHGFCFGHDAEFEFGFGHEBEBDAFGFAFCCBABEHCGFEDEDGBGBFBEHEGGCDCDCBGHDCCCDFAGBHBDEDHCHCHEHCBCDDDDFBEEEEGGBFCFCHAHACGFBBHDHBABGBGDGDFAFAECECEFDFDBGCHBAAHHEH,False +457,12.0,10.0,8.0,8.0,4.0,11.0,8.0,8.0,DBDFDFCCCHBEGFBHEFACBDBGHGBFAFGHAHAHGDDDCCACGCEHGFGFBFBABABDHFAAAEAFA,False +458,20.0,11.0,18.0,22.0,26.0,28.0,20.0,28.0,BFGHCHEAEAFFFFGABCFGFECECECECHCHGHDHAHEEEFHAAFBCGHDHDHCABGHCFDGHGACFDDDBCGDDFGGGGEEABGFAFEHAFEHAFAEAEABAGFDFEEHEFECDADHDHBHEHDHCHFHDHFHGDDDDEDEFEFGDCHCECEFHFAGBFFEFCADGBGBHA,False +459,18.0,25.0,19.0,16.0,13.0,17.0,21.0,14.0,CACACDEDBCBHAAGHBHBCEDEDAGGHDFDEDCHFHECFBFACAHAGGGGGAGDFBABFFGFBHBHBGBHBACABHBGCGBGEFADCDCHAHDHDBACABBBGEGEFCFBGBEFDFABABFCEGECDCBCGDBEGFFCFDGE,False +460,21.0,19.0,19.0,30.0,29.0,19.0,23.0,32.0,FDEDECCDEEHFDFEFEFHAHDCGCGCFDDDCGAGAECDHBEBAHGCGEFEDHDHDGDBHBADCDCHHFECHBGBEHADBDHGHGHGHDHFBGAGHBFBAECGGFEFEFDGDCDAEGEBACHGGDDADFHAEABBGBABDFDFABEDAHBHAHAEDEAEHEHCFCHEHEHBHBHGGCACAHEEEEFDFCGDH,False +461,9.0,19.0,19.0,25.0,19.0,17.0,20.0,16.0,BEGCGDAEHEDBDCEHECACAEAEAFCEGHGHFHGHCEDDDHDEGGFEHEFDFGFDBDBDGDEDCFCFHECBDHACCBCBFGDGCHBHDDBGBGFCBCDDGDACFGGGGFGBEBEGHDBDFCFBFDFDBHHAHAEDFBCBEBEC,False +462,9.0,14.0,11.0,15.0,9.0,10.0,15.0,17.0,CHCHCGCBEBDHEHFBGDGDGDGDBDGEGCHHBDBDACFCHGFEAHFFDCGAGBFHEDEHHAHAEBHBHGAGBFBDBCFCBCBADAGEGHHEFDFDGDAH,False +463,15.0,16.0,16.0,16.0,13.0,12.0,15.0,14.0,EDEGEDHBHDHDACHCBCAHADGDGAEEHFGFGFAEGEDECGGAFAFDBCHCGCEBABABABDEACHCBABAFGEACFDBBCBEGEGCDCDADBDFHHHHHBDCDGBFFGFHCBCFG,False +464,20.0,13.0,10.0,7.0,14.0,12.0,14.0,15.0,HHHBDFFCHCGCGAGDFDGEBFBABAFAFHGHBAGEGEHBACFCEDBACCCABADAGBGAGEEAAFAFACGCFAHEHEDEBAGEHEHEGAGAEFHHHHABEBDBF,False +465,32.0,28.0,23.0,18.0,15.0,22.0,28.0,21.0,CAHHBFBGCACEGFGAAABABAGGCGCGEAAGCGEEDBDGDCDHDBBABAFABAEDBGCEDBDBAHABFHEDEDBFFGAGHHEGAGHEECDCFBHCGBDBDBFGFDFCFAAACACFGHGAGDCFGAGFFBHCHCEABHBFBFHFAFHFEFBABGBGBGHHHAHAGEFCCHBHCAGBCDCECADADAG,False +466,14.0,31.0,26.0,20.0,17.0,27.0,15.0,13.0,BBBBBCGFEFDFDFCCDCHHDAFADACCEAGGCGCACFFEGECEFECCACGEBAGDGHBABDBHBHFCBHFCFCAHDCDHBGFEEDEDFAFHHGBBFAFCCCFAFDFEBBABACHHBDBDBFBCCFFFFFFDBBBBBEBECEGEGDGDGEGCHEBCDFBBBDD,False +467,15.0,12.0,15.0,11.0,17.0,18.0,18.0,13.0,HAGECCBCFHEGGGGBGBDBGBAFACCFCFCBDFAAAAACEEEFECDFDCDCDHBGGGFGDABAGAFFEAEFHBEDEDEFBAHGCGCHFGFGFHHDHECEAEGFAFHHEHEBBGEHFDC,False +468,22.0,12.0,14.0,17.0,19.0,18.0,16.0,15.0,DADADADAHAGABAEHFGFGEGBHBGADHDGGACHEHCHGEFFBCGCAFGDGAEHEAAFCFGAHAHEDDFDCHFEFEDEBECABEFGBGAGCCECFCBBBBHAEBECCADEDHHHEDEDEDFFFFGDAAAFCF,False +469,18.0,26.0,29.0,20.0,29.0,19.0,16.0,15.0,CGCGCHCFCGHHCHCHCHCFAEAFFECEBFGDHDCECECHCFFDBDEDBGGEGAGEHBBCCACABEEEAEBEBACECGADBBHBDBEFEFEFCDDGCCBAHHFCBHBADAGFDBEFEFEAECBFFHABDBAEDECECEDBFBDBDBDACGEGEBADCDGBGDGACFEFBAEH,False +470,6.0,1.0,5.0,5.0,3.0,4.0,4.0,6.0,CBCAGGHDHDHDHFHFEECACADHCAFAFGEADG,False +471,8.0,12.0,3.0,4.0,7.0,8.0,8.0,2.0,GAAFBEGEFDAGEGEFEHGBCFFFFGBBBEBABABDBDBEBDHGCABACAGF,True +472,9.0,4.0,9.0,5.0,3.0,6.0,1.0,7.0,HACGCABHCEAFHBHDAAACFCBEDEDADAHFHFCFAFBCDCHC,True +473,2.0,1.0,5.0,2.0,7.0,3.0,2.0,10.0,CCHCDDGFHAEBEHHFACHHFHEHEHEHECEG,True +474,8.0,7.0,5.0,9.0,9.0,4.0,1.0,12.0,BCDHBCBADCDHHAHDHAHEDEDBHEEDHCHAFAHAHCEGDADEFEFEFABHBEB,True +475,11.0,5.0,2.0,1.0,3.0,2.0,5.0,4.0,AACDCFHAGAGAEBGBHBFEAGBGAAAHAHABE,True +476,25.0,30.0,25.0,21.0,26.0,22.0,25.0,24.0,HGHEDBDBCHEHEDEDEDEDCAHDCGCFDFGEGDGAGAGHGDGDCAAHABAFACBCBCEDEAEDEAGDFEBEBEHGHFHFCBBFGHGFEFBBBFHGBCFCEBABADHBCACGFHFACACDFABHEAEHHDGACHFBFBHBHBABGGDBABGFEFBHGHAHEBGBGCFBEBECGCACEFAGECACFDFEAECCBGHCDD,False +477,15.0,14.0,22.0,19.0,17.0,22.0,25.0,22.0,DFGGGFHHCHEHBGDEEBFBAAHGFGFGACCCGHFHBHCDEEFEFBFAFBFCGCEDEHEHEBFAFAFAFGCGCGDBCBFFCHCDDDEAEAGDEDECGDGABBHDHDFDFDGCGAHEHFHCHAACDDBHHACBGBGAGFFHCCGHHCCGDGDGCGEE,False +478,14.0,12.0,9.0,13.0,13.0,17.0,7.0,13.0,AFAFBFBDAAADFFBFBEHGFEFHAHFGDDFDHAHADABFBFHEHECCACGFBDBGAEHCDCHGHGEAECECEFECADFDBGBHBHEHDDFEFDBEAC,False +479,29.0,20.0,16.0,24.0,27.0,18.0,17.0,26.0,GEHHHAHEGBGCHCBCFGDGBFDHCCBCHFHAEFEGGDHDACEDDDCDFDFDHBAADHFHBEFEHCHCDFAFABAEGBHBABABAEHEAEAEDEAFHEDAGEBEFGCEDEFEDHBFFDFAHHDBDGDHEAEGCBDEDBAGAGAGAEAHACACAEAEBHAHGFGEBEADADBHBHFCC,False +480,11.0,14.0,7.0,9.0,18.0,15.0,6.0,9.0,FAFEGDGBBEFEDEFEFABAGEGEFFFBBCBEDABEGAAAFHFDEHHFBFDFAFCDCDEGHHCHBABCBEHEHEBEBEDEHABEFACDC,False +481,8.0,4.0,7.0,16.0,11.0,8.0,9.0,4.0,EEADADFDEAFBFGEGFGDGCHDDCDEBEGEGCFCHDAGCGDGAECFCEDDFDEABABADDDDEHFH,False +482,11.0,7.0,25.0,5.0,16.0,24.0,10.0,11.0,EAEAEACFCBCEFEGAGAGCCFFEFGBCFFHFCFAHACFCEEHCCFDFEEHBHFHAGFFEFEBDAGCGFAFEFEHECGCGCFCFHFHCCCBCDDBCCCCFDFHAECBHG,True +483,24.0,31.0,31.0,29.0,20.0,23.0,19.0,21.0,HAHEECBBBBGBECEFBFHHCHFHDBGBHEGEADAEAEBBFBCECFCACABHCHCEBFDFCFCFBFHHHEGCDCDCDHDCECGABADDDBAGAGAHEDEBBDGCBCFAFABAHCBCFHGHBDEDGBGEHCDCFCFCAHFBCDCDGDHABGFEBDBDBDGAFAGAFDDCEFABAFDDGAFEFDGCBABHCGDGDCDCAE,False +484,10.0,14.0,9.0,7.0,6.0,9.0,6.0,9.0,HCACBFBFCFCFHAHADACABDCHGHGCBFDHCBGBABFBDBFBEEHADADHBBEBADAGECEFHBGEGF,False +485,10.0,4.0,11.0,5.0,13.0,7.0,15.0,10.0,AEAEHCHCGCGCBEGEGFGBGAGFGEHAFGCHDECCAHADDFDFHFHEGEGACCBHDHAEGEGCGHBEEEGAFAC,False +486,10.0,4.0,4.0,3.0,10.0,7.0,9.0,8.0,HGHCFDHAFAECEFHFHEGECHDDACABAEEEGGAEAGAGAGAHFGFEHEFGBBB,True +487,5.0,6.0,9.0,7.0,10.0,8.0,5.0,12.0,FCFCFHFAFAFGEDCBEHHGGEHEHAGBHCHFEAEDEDBHADCBCDHDHDFBEBCCHCGEHE,False +488,11.0,11.0,11.0,8.0,15.0,8.0,13.0,12.0,CBABEBFHFGEGHCDCAGDGEABBCGGBBHEFBBABGBADEHCHCEAEAEGEFFFCGCEHDHDHECDCAFAGAGAGEHEGFDHCHEHED,False +489,22.0,25.0,26.0,26.0,18.0,25.0,28.0,23.0,BEBEBEBFFHDHDHCHDHCCGCFAGCHCHCDCGCABABAFCHEHBCBCDCGCEHAHAEGGABFDHEBECGCHCHFDADAHHEGFBHAHFDGDCCCHFFGGGGBFAFABGFEFAGGFGDBAHFEGEGEDBBEDDBHBDFDFGGCEFGFBFHGADADHCEGEGDGDFDBBCBCDGBADABAFCFAFADDDBCGAE,False +490,19.0,24.0,22.0,16.0,30.0,19.0,23.0,31.0,FGGAFEFECGHHEGEHEDEFEHAGFBFBFHAEAHAEAEACDEBBHCECACEGBBFBDBCHDHGCFEHHAHAHBEBECGGDGCHBHGFGBDFCGHGHDHBHBACACHBEAABDHEHDHFFBFHFHEBCDEDEDFDGEGAGADBCHFHABDBDCFAEAEBEBECGCGEHHCCBCHCEGEGHFCGEG,False +491,16.0,23.0,19.0,29.0,31.0,20.0,28.0,25.0,DHDBCECECAGFGBBEEEECEDEGHCDGGAFDFGFGCGCEHGHGEDFGCDFGFDDDCDEFEABDEDEBEBHBHBGGHBDBHAFABDGHCECGAEAEAGABHDHDHDHBBBGEHEFEDHBEEEGGCDEFGHGHAHAFCFGFEDCFEABHFHEBEBDHDHACBCFGAGFGHEHBGBCHFGDDADCDADFDECB,False +492,2.0,8.0,8.0,4.0,4.0,4.0,9.0,3.0,GEGFACBGAGECCHCHCBFDGHCCGCGBDBDBEBEFDFBGBG,True +493,21.0,13.0,20.0,26.0,11.0,13.0,10.0,15.0,AACGHHEEDBDBDCDCDBEBFBFEGDCEADDDFAFAEAHHHFAFADEDCHCBCAAGACDDDDDBCAGDCDBEHGHGFGABDHDHCCCCHADAEAEDHDAACAFAFBFEDGBHCCADHBGBDFCFCHCFG,False +494,4.0,3.0,5.0,3.0,3.0,7.0,4.0,3.0,AHFEBAHCHGFGFEFDADBFFCFCGCGCBEAD,False +495,0.0,4.0,1.0,1.0,4.0,0.0,2.0,1.0,BDEEBEGEGHBCB,True +496,6.0,16.0,13.0,12.0,12.0,13.0,12.0,10.0,DHFEEBAFCHCHCEFHABBCBCFGECECEGEBDCDCBBBBFAFEBEGGCGAGFHEDGBGEGCHEBDBHBHCGBHAGDFDFDFDFDHCADFDFGB,False +497,19.0,9.0,12.0,22.0,14.0,24.0,20.0,18.0,DEDAHEBAAGDBHHGABAGCHCDCACFCGCEEACBFAFAGEDDDHHHCHCGFGHBAGAFAHDDDDDGDFDFHFEEDEHFHEBFDFHBAGHGHFHFEDEDFDFDCGBFACAGAFHFEABGEGFGFGFECADAGGDGFFF,False +498,8.0,3.0,6.0,14.0,8.0,17.0,6.0,15.0,GFFDFEGGBEBHAEDGFAFEFDDDAFHCHCDCDGFHAHFHFGDHCEFHCHCFDHDHAFDFEFAFABAEHFHDHDEDH,True +499,0.0,6.0,1.0,2.0,2.0,3.0,3.0,4.0,EDECHDBGBGBHBHFGFBHBF,True +500,9.0,11.0,8.0,10.0,19.0,12.0,9.0,5.0,GCFDBACGFBFAAAAGBFAEGFGCGHEAGHDFFCEDEDEDEDECHBEGDDEAEFDFAFEBEHEHEDEBEBEBCBCBFFEGBCE,False +501,8.0,14.0,12.0,11.0,8.0,12.0,9.0,4.0,DBDBEBDBDFDAGCGFBCBCFFGCDCDEDBBBECECFBFECABDDAFAFAGEFBHAGAFCHCDCGHGHBFBEGEFCAG,False +502,5.0,5.0,5.0,5.0,9.0,6.0,4.0,8.0,FEFEBHHHAHABEBDDFDHDCAFFECEAHCBCEAEBHGHGCGFDEGE,False +503,12.0,12.0,13.0,25.0,16.0,10.0,18.0,21.0,GBGBDECCCFHHBACGDGDGDADCGCBBHDHDHDBDFDFDHEHGCEDEGEFAFHBEFFGCEHFFDDHDHGHGDAACAGBDHGHEDEDGAHCGDGDACEGAHAHDHEHEBEBCBFBEHEADDGDCAHE,False +504,10.0,15.0,9.0,13.0,14.0,7.0,8.0,9.0,CBEEFBBGBGBDBABADFBAAHEBEDEDGFCEBDBHAHBCBCBGGFDFCAGAFDGDHDHGEBEHFHECECEAHCDDEHEAEADCD,False +505,18.0,16.0,17.0,23.0,12.0,18.0,20.0,12.0,FGFABEFDHDHFHGDBDBGBGCACDDDHAHBHFFFBGCGEAEAGABHBGDGCECEDHFAGBDEAAHCEGHDEDEDFGHDDDDEFFAFGDGCFCFDFDACFCEAABGBABCBCFHGGBGEGAACCCCFCGBADADBD,False +506,22.0,16.0,25.0,22.0,25.0,11.0,27.0,18.0,AGCDCDHDBGCGAGDDCDGBGDCBCGFGHCECGHGAEFEDEAEGEFHGBCBCAAAAGGDGEHEAEDEDEBCBGFCFGDDEDECFDHDBEAEDEHGHCCCCABAFABCBAHCHGHCCDCEFAGEHAGAGHEBCHEGBHBHDHFEEEACACDEDEHGGGFBFBGDAAA,False +507,13.0,17.0,22.0,10.0,17.0,14.0,17.0,13.0,GGGCBBBEBHAEAGHDCGCDHFEAEABHCHGFGHGCCFFBCAAHEHEDCGCGCDADEHAHFDFAFCHCFCBDEEAEFHAHFCFABBDBDEGECEBGBGCGCDEEBEBFBEACBCGCGBGCFCF,False +508,17.0,21.0,24.0,12.0,17.0,20.0,19.0,17.0,ECHCHCHCGCFBGAGEBEBEBDCCFHFGCDFFHHBGBGDDDGFCFCGDGFAACACGFHDHGAAHAEBEGCCCFGFADADHBBBBABEBEBCGCHDHBGEHCACECEDDCFFAFEBACAEHEHBGBHEFAFBGHGFBCBEAEAGFFCF,False +509,4.0,0.0,5.0,5.0,1.0,0.0,3.0,4.0,GHDCDCDCDCAEHGCDHHAAAG,True +510,10.0,11.0,3.0,4.0,7.0,2.0,18.0,3.0,HAGGGGAFAGCGEGBGAEBGGEBEBDCEGDBDADEBEGAGAGBBBCGGBGAGHBHAFA,True +511,2.0,4.0,2.0,2.0,1.0,2.0,3.0,1.0,DEDFHGABBBBFAGCGC,False +512,2.0,4.0,2.0,1.0,1.0,1.0,0.0,1.0,HDBABCBCBFEA,True +513,4.0,5.0,8.0,7.0,6.0,8.0,11.0,4.0,GGHGHGDBCECECEGFHDABADEGGCGCECBFEGACFFFFBFCFHBAGGDDDD,False +514,20.0,26.0,19.0,15.0,24.0,22.0,24.0,21.0,FGFEFEFBHGHBEDHHHHEDCDEHEHCBFHGAFAFBFDCACAGGGGGGGHBBABFBFBCHGGBACGCGDFEEEEAEFFFFDECECFCBCBEAHCBADEDAGFDEDBBEBEHACAFAFABHEEDCFGHDAABEBEDGGHGHGDDFEFAHAHBGCGBGCCCABBHBAGCBHBE,False +515,22.0,23.0,26.0,33.0,16.0,30.0,25.0,23.0,GGGGCBEHCBCFEGGFADHDHCGDACCDBDGFCFHBHGAABFBAHAHDGDBDADACGCFDFGFDDHBGGGEBEBEFGFHBEFABEGCGCGHAHFHFHDBDBDCDCDCHFFFHFDFAGEGBABFEDBDCECBCDDHDBGECADEDEFFFFAFDFDECGHDFDFBCGFECHHAHAHGCBCDADAEAFCFCDHDABAHABC,False +516,17.0,13.0,13.0,12.0,15.0,20.0,10.0,20.0,FDFAGABHFHCEEAFCEGGBEBCBCBEBDHFACGHGCACACAHFHDBGFGDAEAEABFDEDHDFAFEBDHHHFHFHFHAHAHAEAFADCCFBBCEHFFFDGDGBEHHHHGCBEFEAEDFC,False +517,26.0,21.0,23.0,17.0,23.0,30.0,24.0,22.0,ABAEAEAEBGGGGGAECECEDFCEBAGHFHAEADCCGGGAGBEBEBEDCDFAFHFHGCCBHAFAFAFHFGBCDDFACGFGHDEEGEFEGBGFGADFCFCFCBAEABCDHHHCHFHFHBHAEFFFCFBECCCFFDFDBCHCADAFHBABDFDBBAHGGEAEHCGEGCDAGAHDGDFHFHFEBABEBH,False +518,7.0,13.0,9.0,12.0,7.0,6.0,7.0,5.0,CGCECBHDEBGBAFCDBDBDACEBDDGDGEGEFAFAFAHCFEHEDBCBDBDCDBBBDCHFBAGAGH,False +519,15.0,23.0,14.0,11.0,17.0,17.0,14.0,16.0,AFGEDCHBBBBBBGGECEFFBACACBCGCBHFAAABCCEEDDDHBBFBFBGEHEFDAEAFFFEHAGABAFHFBDBHHHBEBEACGCGCACDCHEEBEGGDGHGHGDDDCBGAEBEFEFAFHHHFHFB,False +520,18.0,12.0,17.0,12.0,18.0,12.0,16.0,36.0,EGEHCHDHDGDGCADAHAHFCEEBACEEEADAHHBCBEHEHEBAHCEEGCFEFAFABHBHGHDCGCGDHDHFHDHDHAHCHABCGCFBHHAHFHFHFCEHEAAHHBHGEAHHBFCCGBGFHAEAEGCHBHGDGDGAGFHHC,False +521,4.0,11.0,9.0,6.0,9.0,15.0,6.0,12.0,FFFCCHBHCFCBCBFDDGDGBFAGCFEFCHCGFBBBHCHDEDEAEBHBHGAEAFFBEGEHEHEHBHFFFFHD,False +522,17.0,10.0,12.0,14.0,22.0,13.0,17.0,18.0,EEEEDEABAGFEFEHGHBDAAABDBDAEHHAHGHGHDHAEABHHHHHBCGCFCFCDBAGACEEGCGAADGDHAFCFCEBEFDFEEACGHBEFEFEFEDCGFGHGEGDBAEGEDCHAHGDFDGC,False +523,0.0,4.0,3.0,2.0,1.0,0.0,4.0,2.0,DDEBCHCGBGCGBGBH,True +524,25.0,20.0,21.0,11.0,21.0,16.0,21.0,28.0,FGHGHEHEHBHFHFBFBDBEGDCHCGAEAFCDEAAACHEHEHBFFFFAAHCGGHGBGBHCHCDCGAGAGBHHHFDCDAEABBBCECBGGFACHCECEAFAGHFAEHGGEDEDEBHHACCCACBCHDGDGAAABAGFEBHAGBGCFEEDEAEAFBECHHAHBHB,False +525,5.0,5.0,3.0,6.0,5.0,16.0,3.0,8.0,DHFHFEFEADAGEGECBDFCBDDFHCHFAAAFEHHFBBBGDFFFFFFFHFH,True +526,1.0,0.0,1.0,1.0,2.0,0.0,4.0,6.0,HGHCHEHEGGHGDAH,True +527,14.0,26.0,15.0,11.0,16.0,18.0,25.0,17.0,BHFABADGFABCDGGECEBEFEDBDHGFCFDBDBCEFBFHAGBFEFGFHFHCHBHEHFHFHCHCEDBDBEGHGHGCBCBGDEEFCFBGBGBGBCBDBGAEAGBGAGECEAFGGGHGCCAFGGEAEDBHAGABAFAGHHCBBB,False +528,26.0,33.0,22.0,21.0,21.0,26.0,21.0,23.0,HDBFBDGDGHHEBFFCECFBABGGEBEGGAHEHABGBCCCABDFEFGFADACCGABDBFBADADBDAHAHBEGHFHBEGEBCBCBHAHABADCHBGCDEDEDHGGGGGCDBFFFFFAEECHCHCFEBEAADFBFBABDBGEEHEGEFCFCFEAEADCGFADHHFBDBAHAHACABABFBFCFHBHBHCDFGCD,False +529,19.0,28.0,16.0,26.0,16.0,17.0,19.0,17.0,ABADGCGBHDFFFGFGDGFBDGGFAFCGGFHHAAFFFEAAHAHCBCBABADDFFFABDBDBHGDACHCHGBBBBBGEDADAGCBEBHHEDBCBCBDEEGADABABADADCCBCBDFDFCBCHFEEEDEHHHGHBHDEECHGDGDBEEEDEDGDGCBBD,False +530,10.0,4.0,8.0,6.0,5.0,11.0,7.0,6.0,FFBFCDCGAGFEDCDBEGEGFCFCFCBAFDBHAHAHAGACAHAHEGDFCFADEGAFH,False +531,13.0,7.0,11.0,9.0,7.0,13.0,13.0,17.0,GCABEBFBAHHHGHGAAHCHBEBCDAFHFHBCDCDCDFGEGCHAHEHCHDFFFGFGCGAAAHGGGHFCECHHHGAAEADFBFDFDEDAGF,False +532,6.0,4.0,4.0,4.0,4.0,11.0,3.0,7.0,ABCDHFHFECEDADFGHAFCFCFBFBGADEHGBFHEHFHFAFA,False +533,14.0,30.0,24.0,27.0,22.0,23.0,21.0,29.0,CEBEDGCHDGAAABHEHGCGBFBEGDDDCDCHHDEGFHCEFBGBCCFBAEAGABEDFDCDCDHDHGFGHGCGDDFBBBBBDFDADCDGBFEFDBCFCFBDHDGFACAGFDFDEAECFBBHBHCACAHFDEHEHBDBGBHBFBEDCFEEHBHBCBCBHEFEFCHCHEAFHBHBHEHFGCAEGHGHGHGHED,False +534,7.0,14.0,11.0,10.0,12.0,6.0,11.0,7.0,ABADCBEGAGABDBHCECDBEHGCBCBCGCFCFHFHFBBCBGEGHGDGEGEDDDCDEDABAHCFEEAEFEBBGDEHBG,False +535,1.0,8.0,7.0,5.0,5.0,7.0,1.0,7.0,BHBGFHEDDFCBBBBHHHFEFHFCFCACBDBDEHEFECCCD,True +536,5.0,4.0,11.0,11.0,13.0,6.0,6.0,8.0,CDDDEBHHGHDFGCCACEDEDECEGEACACHEBFFEFEFGFGDGDHAEEEABCBHEDCDCHHDC,True +537,28.0,21.0,11.0,18.0,13.0,11.0,21.0,19.0,HGAGAGFDDHGEBDCGAAHGHEDBDFDEGAGHDECCAAAADDGBBCBHBHBHGCGCBBBFBFGABAGCHBGAFHFAACAGDFEFEGGBFHAADADFDADBBBDAEAFHGHEHEHAHAHAHAGEGDCDCHBABABECDGAEBE,False +538,3.0,5.0,4.0,4.0,5.0,2.0,1.0,6.0,HCHGHAFBEBEAEACDCHBEBFCEHBHDDD,False +539,6.0,6.0,7.0,4.0,9.0,4.0,6.0,1.0,CCAGDGDGEFBCACBCGDDBFEFCFEABABCEEEABAEGEGEH,False +540,4.0,1.0,2.0,4.0,0.0,6.0,5.0,0.0,FDDGAGFGCGAGAFFFBCDADF,True +541,9.0,14.0,13.0,6.0,8.0,6.0,10.0,5.0,CBCGEGEFEHAGEDBGEGAGHDCBCGAGAGHDFGAACBBDBDFFCFHFDACACBBEBECCCCHEACBBBBB,False +542,16.0,16.0,8.0,16.0,13.0,11.0,10.0,17.0,EAHAGFDCGCGDEHCHBAAADHDHEHEFBGBABFDAAADBDADADHDGEGCGHGBFAFEBBBBHFDFDEBEFAHEBDGFHCHCHGDFABABDHHHAEBEHEDEBCCF,False +543,21.0,26.0,17.0,27.0,29.0,23.0,26.0,18.0,GDEHHBFFAHDHDCBHBGEDBDGAGDHCEEEBFFACBBEDGFCFBEBECAFDDHBHDEFEFEFEGGCGBHFFCFEHBHEFBHBADAEAGAFBFGEGEGCGDEDEGCGCBDFDFDADABCFEBBBDBGGGFGCDCDCACFEDBGEGEGHABGEGEAAAACCHEBEDEHBABFGFHHEHADGDADADAD,False +544,22.0,22.0,21.0,19.0,23.0,23.0,21.0,20.0,CGDGDBCFDADCCGDBDHAHCHCEDFFGGGECECEAFAHCFDDEDAGCGCBDEDEAEHCHCEEECEFBFHDHGHGEGCHFEAEAEFFCFEDEABHHHGFBAGAGBDEGECECECHBHAHGBBFBGBDFDGAAFAFGBBCBGBFHEHCBDFFFHFBAAHBFBAAAFAGABDB,False +545,23.0,25.0,25.0,15.0,25.0,17.0,21.0,33.0,GAGAGEEHHHFHFHFHEHDCFHABBHBHBEBHFGBCCACACACGHBADHBECECEBABECCHCFEGHDCEBGGEBEBEFHHADCDCDFDHBHCAEEHEHFHGHGHFADCGFHCACACACBCEGDFHCABGDGEGFCDHGHAAAHBHBHBEBHBHAGABEEGEDEGFBFCGEDAGADDBBEAFCF,False +546,3.0,2.0,2.0,4.0,0.0,4.0,0.0,0.0,ADADAFCFDBBFCFD,True +547,13.0,21.0,3.0,11.0,13.0,5.0,12.0,11.0,GHBADHBHBGBEHDHEEFGHDHGFEDDDEGEAEDFAAGBBCBAGAGAEDEHBHBABABAGADBEBECEAEBBBBGBHBDFGCADBFBHG,False +548,25.0,24.0,22.0,17.0,28.0,18.0,39.0,21.0,CDCABDBHBGBGBGBCECBABGBGAHAHBFEEAEBGAGEHFACACDEGEGECHAEGEHFHFABEGHFHAHGHCDCEBEGDBFAFHGEGBGAGDBDBDBEFECHFHEBFGEGEGECAFABEBGBGHGFGEGCCCCHGFACGBHAHAECFGAEDHGHGDDDEAFADGDGDCAEGGACFBFAGEGACCEHDCDGGFG,False +549,3.0,2.0,4.0,4.0,5.0,8.0,5.0,2.0,HFEFGDGFBFDFEEEFEFGBGCCACDCAGAHFD,False +550,1.0,3.0,4.0,3.0,7.0,2.0,2.0,6.0,ECEBHBHGHBECEFDHAHECEDEDGCHF,True +551,16.0,22.0,21.0,26.0,28.0,20.0,19.0,21.0,EGEDEBEAEADDDCFCABGEFFHDBECHBBBBAHAFFCCDDDDDDHGHEFAAAAAGGBGFGBGCCHEHFBFHHDCDFFBFDGEGFCABBEBEBECDGFEECACDDBCFEDEHHDBDFHFHCHCEGGGEGEADCDCEGEFFHHGCCBCBDBEBEAEAEAGDFHCDGDHBHEHEH,False +552,4.0,5.0,6.0,11.0,3.0,11.0,11.0,5.0,GCCDFHFBDDEDECGCGDGHABDDGGGDHAHAFGFGEGFGFABDFHFCFDBDBFFC,True +553,5.0,13.0,12.0,7.0,6.0,1.0,8.0,8.0,BGDACECGDGCCCBCHCGCDBHHGBEAEAEFBCBEBDGCGDGCBABABEDCHHHHHBBDB,True +554,21.0,23.0,19.0,23.0,24.0,21.0,32.0,21.0,FAGAHAHFHGHBEEFGADABCBGBGFAHEDEFGFBHCECEHEHDGDEAAHGGGEGFFDFBCHGAGHCDGGGABDGDADHFEBHBHGGCACBCBCBGBCFADADGDEDACBGHEFDFHFHFBDDDDBHBGGGCDEFEGEGECHCBCBEBEBEFFAGBBFACECECDAEFECGAGEFDGGAADHDH,False +555,11.0,14.0,17.0,9.0,22.0,14.0,9.0,22.0,CGEEDCDADADBDBFFFHCAAEHHHEHEHAHEFFCFBGHHHFHCHDHEBGFGFBEECFCEEECGCGHEEEEADHBHAABCCACFCEDHCHCHBHBDBECGCEFFGFABBEBEGHAHBE,False +556,4.0,3.0,4.0,4.0,4.0,1.0,0.0,1.0,BABHECAAFBDCDEDEDECAC,True +557,11.0,15.0,15.0,16.0,14.0,18.0,14.0,14.0,BCBCBGDGCGEAHHEHGAFFCFHFCGAGACEBEBEBAFGCCDGBCEFDFDAEADDFDCEBFBFBEHDHEHEGEGBGHFHDDDDCCBGBCBHAHDEFFFGGCHBEAAAHFFDFDFDHC,False +558,5.0,2.0,3.0,3.0,1.0,2.0,3.0,2.0,DGDGACBFHFHAEACABACDG,False +559,29.0,26.0,17.0,17.0,20.0,26.0,24.0,23.0,DADCDFFHFAFACAFBDBACAGABFGFBHCHCFFEFEFGHGCBCAEGGGDBDBABFHFAEADDDEDEHAAGGDBHGFFFFCGAHBBGBGECEGEGEGEBEDCFFDFCCEAAFDHAEBFBFAHAGFHCCGBGBGBGAGABEDADHEBEHHAEFHAHABCBCHAEAFAEBHGHBBBAGDHHHHC,False +560,7.0,9.0,14.0,11.0,8.0,12.0,13.0,5.0,FCDCEFEFGHDAABACGCGCGDEBAHHBCCFCFGEGDBDBDBAFECDFDFEGGCAFABCFGFGEGHCDEDGDGFCBCBH,False +561,16.0,32.0,21.0,19.0,21.0,20.0,22.0,22.0,AFBGBGHGEDFAACDCDCEFEBCFCGHGHFDABABAHCCEAHBEDEDBDCCHGHEBEBEBCDEFGDGFBFEDHDHDBBBFFEGBGHEDGDFBGBACDGEBEBHBHCCGHGHGDGDGHGHBCAFHGHGFABAFAHAFCBCBFAHDHBBCBGFEBABCBCFCFEEBCFEDEAHBE,False +562,18.0,21.0,6.0,6.0,14.0,3.0,15.0,20.0,DGAAHCHBAFHBHBGCAEAEAHAEAHHHBCBGGEBDFAHAEAEBGAGAHDEGHAHBEAEGHGHBABHBHEDCGHGBEDGBGEGBGBABDBAEEHFHBCBCBHB,True +563,19.0,18.0,15.0,19.0,14.0,16.0,17.0,24.0,FAFAFABBHDCDCDFDCAABFCEDBBECDCDFFAGADBCHGGFHDHGHEECEGDADABEHHHHCHDHDFAHGFGFBDBCBFHAGABDBGBFDGGFCFCBHBHFHEHEHEGAGAHAGABAGABEECDCHHEBEDEHAGCGHDH,False +564,3.0,3.0,2.0,1.0,0.0,0.0,0.0,2.0,BABCBDAHCHA,True +565,8.0,12.0,12.0,9.0,13.0,13.0,12.0,17.0,BFBFEEHBFAFGGGCHDHDHGCDCGEHAHEEBBAEFGCGCHCFCFDBBBHCEBEHEHFGAGFFHFHABDGDFDFBHAHDHEAABCEGEGEDCHCHC,False +566,24.0,19.0,7.0,22.0,15.0,14.0,18.0,21.0,AEADAHECBGBFHGHDHAGDGHGBGBHFHBDDDHGHDHDADHDHAHDEDADGFEFGFBDBDFAAAAABEFDHHHEGBGAAEDEGEGAFAFHHBEEHCGBEADAEFFBFDFDBDBGBHAGBCBEFDHGCACBCBAAACAGE,False +567,18.0,34.0,25.0,23.0,26.0,29.0,16.0,24.0,CHFDFHBCBDBFBHEEAEABABCGAFDFDADADADBBBCBDBFCEEEFFAFDBDBGHDHBBBFFFDABFHGCABABABAHHHHDFBFEFHBCDCFCFBFEEGECFHEGEGBBDDHDEDHFHDHDFBAECCBHBEBHBCCCBDBEGHGCFCACEFAGEGEGCCFBFEHEHCGFECGFDAGFGHCCCEEEBEHAHDG,False +568,10.0,3.0,8.0,11.0,10.0,4.0,2.0,8.0,EGEDEHEHCDCEAEAEAFFEHCDDDCACHBHBDDDHAAACAEBFAGAHDCCFEDHD,True +569,16.0,11.0,9.0,12.0,15.0,17.0,17.0,12.0,EAEDEACHEAGBHHFFAGGDADADHBHAFFGDEDEHFBFCGBGFFDGHAEAFBCBEAECDADCGCGFGEGEGAGDEDBFFAFAFCBHAEAEGEGFGFDCHCGFBHBHBH,False +570,5.0,3.0,10.0,3.0,5.0,7.0,4.0,6.0,DADCHHGACACECHCFCFHDEGABAFFFFECECFGGHBCBCEH,False +571,19.0,19.0,10.0,25.0,20.0,11.0,12.0,21.0,EGEGEDDDADCBFBFCHCHGAGDHDHDADGHEDDDDHBHBHCADEEEDDHDBCEAABABFEEAEGHGHFEADDDCABHBHBHFHFEEEEFDCEEGCBCHGAEAGABFBHAHEHAFABHBFDDDBDBHAAFBBAGGCD,False +572,9.0,14.0,14.0,11.0,15.0,15.0,19.0,10.0,EFEAEGGGDGDADFHFGFBFBFGDGBBEBEADHGCBCBCGCECGFDCBCBFDFGEDBDHCAFEFEBGCHAFGFGEEHBGCGCEEEBHCHBADCCGGHAHADAGFHFE,False +573,4.0,10.0,13.0,15.0,11.0,8.0,6.0,4.0,AFCCGEEDEBEBAHAHADFBCBCBEFDGHBEGEFFBFDDBCECDCDCECEDDDDDGDCDCEBBGDHFCCGF,True +574,15.0,27.0,18.0,27.0,33.0,20.0,18.0,26.0,FACGCDEDBABABADHDBEFECGDFHHEBCBCGHHAEBHBHGDADGDGDEEEDEBCBDBEAFHFEDGDGDBCHEAADEDEAEDHCHAFDEDHDACHBHBHEHECFBABHDEEEFEGBGDDHGFBFBFCFCEBEBFFCECEGEFEDGDCBGEGHFCECEBGBHBHDHCEFFFBGBHHHEFAAHDG,False +575,16.0,17.0,13.0,14.0,16.0,19.0,22.0,14.0,HBCFCFDFEGAGAHHGEGBGDGFHEHAFBDBDCHCHGFDEDEFHFBEBHBHBEBHBDFDEDEHEGEFFACACGFHADGFADGBAEADAFBCHEFFBEBGBGBACGGFGFAABGGDGFCCACAEAECDGGGC,False +576,21.0,18.0,24.0,12.0,15.0,14.0,8.0,14.0,CDCDFBACHGHECECEDECECHHAHBGFAAHAGFEBCHAGBBBABCBADCFEGABABCGCFAFEBHAHDHECACHHFCBBBEBECFCFAFAHAFCGDFDFDBEBDCACACADBDEHEFEDGCACAC,False +577,11.0,6.0,10.0,4.0,4.0,6.0,15.0,11.0,HHGHAHGDGCEBABABGCHCGCECHCACHDFBABFHFCAHAHFFBFGGGGGGGACAGECDGAADEHG,True +578,13.0,11.0,13.0,13.0,10.0,10.0,11.0,13.0,HDHDFAHCHGEAAAACGBEEHHDEEEDADCDCACACDGDBDBCFEAGHCFCABFBFGCEFBHHHHGBGCGCGEEHAHFBFDDBDBCGDGAFAFB,False +579,16.0,20.0,17.0,10.0,16.0,13.0,17.0,18.0,HBHCDAHECCCCBHGEFCBCGFFAFACBDGDCHBHBCBEBEDGDFEHGHBHECCCEFAGAEHDGDGHBFAFAGAGBGBGBEECCAFAFDBBHFECBGHCHBHDHBHBAEEEAEHEAGAGFGFGDABA,False +580,19.0,23.0,27.0,23.0,24.0,28.0,24.0,26.0,FGFGCHDADGDHFFDCDABFFFFBCEAECEHADCDFDFABAHABDEDBAHCCCHBAAFAEGEGFGHDHGHBHGHDCFCFCADEFEHBAEEFGCDCGGGGGEHFGCGCFFHFHGHBCBDBDCCCGEBEHFBFCFEECFGHGHFHCAEBEBEGHGHFEFDCHCBCBGBDBEAAABCCEAFBHBHDHEEGABDDDED,False +581,14.0,16.0,19.0,20.0,20.0,20.0,13.0,20.0,ACAFBEAHDHEHBHCABBCHFHCEEGCHHFCDCBBEBHFABGDHFHFHBHBHBGDDDCFFHFBFGFECDCEAGAGACCCGCDCDEDEDADADFFFAFAGHCDAGHFEEGHCEEEHECECEGEFDFEEGDDDGDBBFBFBADH,False +582,13.0,15.0,13.0,20.0,21.0,19.0,19.0,16.0,EGGAGAHBFFEFEHECDCFCBGHFFGAGAGEGCGAGBFCFDDDEBEHEHCFBDDDDDDADAFAHHCFDEDBFFFFHAGCBDAFBHBEDGFGCBCBGEGEDCDCDCFHEHGHBDGEHABEGAGHFEDAHEEEEEBHB,False +583,6.0,13.0,10.0,9.0,17.0,8.0,10.0,9.0,FHFGBBBBABCCDHBEDHGFDEHCGCBEBEHCFCFBFBDBACFHGHGEEECECEDEDEHEDGCAEADFDGEAEGGGEBABEH,False +584,18.0,27.0,27.0,16.0,19.0,28.0,14.0,16.0,FHFCFAFHHBEBFBDCHBGEDBAFFCBHBCFGFGCGCEEEDEDBABGEFBGBAFAFHEGCGCDCDBHHCHAHAHGCECAHFHFDEGHBBCACABABFBFBFAFCDCDBABEBECFFGBECCCHCFAFDDDDFDBECEAEDBFCDCEFGFABABCCGEHCABGFEF,False +585,26.0,16.0,22.0,22.0,20.0,21.0,22.0,26.0,FHDHDHFCEBBDBAAAAGFGCBEDHDHGHAEAECDCBEBHCHAHGGFDAEFCFHHHEECCCDCDCDHAHABBECACADAHCDCDFBBEDAAGAFFHCEEEAFAFGFCECEFACAEAFFHEGFHCAGECFFGBGFGDBDBABAGGGGGHHHAHDDDHHHAHDGEGFGBGBFCEDGD,False +586,8.0,5.0,12.0,4.0,4.0,13.0,13.0,7.0,DFDCCCCCCFEBEBDFFAFGCGCBFDFBAAFHGHGCGAAHGFAFGFGCGAGBCHFHCGGHFHEAEG,True +587,4.0,3.0,2.0,3.0,2.0,5.0,3.0,1.0,BGGGDBDHDFCAEAFCFBFEFAA,False +588,7.0,14.0,10.0,16.0,16.0,9.0,9.0,13.0,BCDFHCGFGAEFFFDDBBHBFBHHGAEDDFDEHEGEGEHADFEEHEGEDEDEDEHHBHBDBHBDCDCDBBFBABACACEHECGHEBDGDCCCAG,False +589,41.0,28.0,27.0,20.0,22.0,14.0,25.0,23.0,EDEHHHEACAEAEGECBBHBHBEFAFEBAFHHGHAHACAGBDBEGCDEHAHADACACGEDCCCFBBBBBFAADACAGECDFHGDDBDCDCECDABAFCBEGEDFCGBGDHACABGHECBGGCDCGEFEAGCGDAAABABABDHGEAHBGAEHGBGBFCFCFEFBHGHBAAAAHABABADAGACACGCACHDHDHAFAGEG,False +590,25.0,17.0,16.0,9.0,20.0,24.0,14.0,17.0,HDFDEGEFBBECCBDBABFFAFDFCECBAGAEABGFHCACAFAFAFHEHEHECFCHEHEHECGBDBAFEBCFAFCFAGGCFCABHGABFFEGAHAGAGCHHEHFDFBEBCBEFAFAHAEFEAAHAHBHBGDGDGCEADAGEF,False +591,17.0,13.0,25.0,18.0,20.0,19.0,18.0,19.0,ADCFCHDBAEHEHEFEACAFAFDFEFECEGADHDHEBCCCCEHHGBDBDGCCFBGDDCGABAEAEDEAFAFCGCFHFEGAGDGFHCGCEHEAGCHCBDEDCFEDHCBEBFBAGEGAHCHCBCBAHACDBDCDCHFHEGFGFGDGHGFFH,False +592,4.0,14.0,3.0,5.0,17.0,15.0,9.0,5.0,HGFEEHBHFFEFHFEGBABFBGDFBBEFEDGDEDECEBEFEAEBBBBEBFAHAGFDFEFEBGCGFGBGFECE,True +593,13.0,8.0,10.0,11.0,8.0,10.0,5.0,8.0,EAEADADGFGCDDFBFHHGADABAFHHBAEABHHGBCFCFDFAFDHDCDCBFBCCCBCEEEAEAEFDAHACDG,False +594,16.0,13.0,15.0,7.0,3.0,9.0,20.0,22.0,BGBGCGHHHEHGAAFGCGBDFAFBHCHBDBCCCFDAHHBGBAAABHHHGHGBABABCCCCCDGHGHCHAHGEGDBFGFGCGAHAGFCHGGGAHAHCHFEDHDAAF,True +595,12.0,10.0,9.0,7.0,8.0,10.0,12.0,10.0,AEFDFGFGABHBHBACAHFFEECEFDFGBCAABBCDCGEBEBHHHHFBAEADGDGHGDGDCACGCACAEFHAHGGGBF,False +596,12.0,14.0,7.0,5.0,7.0,8.0,16.0,11.0,DBGBABFCGCGEGBGCHCABEEHGGGHGHFBEBABFBFBGGGGFDFCGABABAFAHHHHBEAAADDHCFEHAHBGACDGE,False +597,12.0,31.0,25.0,23.0,29.0,22.0,19.0,20.0,GBCAEDEGEDHCHGFBEGCCDCGAFBFAFEGBBDBDBDGGCEHEHFHDCDCDEDFHHBGBGCHABGCGCFHFDEBCDHDAABFBGBHDCDCEHEBFBFEFBFHEHEGEBBDBEBABCDGDBHBDFDFDACCEFBCBFHFGCEAEDFCCDCFGGEEEAEAFAFBHBEBCBCHEHCHGEEEBE,False +598,3.0,2.0,2.0,2.0,0.0,4.0,2.0,0.0,DADAGFCFCBGAFBF,True +599,18.0,18.0,17.0,19.0,19.0,25.0,24.0,26.0,EFEFADADEGEGBBHHABBHCCGAFDHDFEHHHHHHGAAADGHFHGGGGDEACHCHCFCGEGEFABEEGEHFCFDFEBGAHCHGFGFGFGFDDHEFCFEBDFEACAFHCHFBADGCGBADGDAFCHCHDDDFDFHCHBHEEEBEBGBABABABCBFFHFDGCGBGD,False +600,18.0,13.0,8.0,18.0,9.0,20.0,11.0,10.0,FAHEFAFAHDGGGGHCBEGABABFEFAAGAGAGAGAGBHBHCFFDHBHDEDEDABCFCEDEBEFADDBFFCFHFAAGDDDDDDFFFFHADFFFBBBCDADCCADHBE,False +601,28.0,16.0,18.0,22.0,25.0,31.0,31.0,28.0,DHDHCHCEGGGGGGHGHGABHGABAGDGEGBACHDHBGADFBHGAGFGDDADGEAEACHBBFFHFEGEFFAFAFGFEFAGADDFAFCFGHBFFEDBACABFHFCCCEEDFDCDAAHFHEHDDEDGHEFCAHFFBCGCGCACABAEAEHDHFHFHFCEDEDGAGAEEEEEFDAGGGHGHFHAGEBHBAEFCFBFCEHBHD,False +602,19.0,22.0,22.0,6.0,18.0,28.0,18.0,32.0,BEHEHCBFBFGAGFFFHEEGEFFGCHCHFABHHCCBFHFABBEBCACAEAFHFABHCHGBBAHEEEEAHAHBHECACAHEHEHCGBFFHFGAGCCBCBEFEGHDDGDHFHCDAHHHHDAFBFAFHFHGHGACCCACBHBGBGBCFGFHFHFGFGFAEBCGCBDEF,False +603,6.0,3.0,3.0,0.0,3.0,1.0,2.0,3.0,AAAAHHHEAEBFCEGAGCBCB,True +604,20.0,12.0,4.0,14.0,4.0,16.0,10.0,13.0,BHADGGGBAFFHAEDBAFGFCFHFHDHBHBGFFHADDEHFFBFGHAHAHABACADFFAAGADAGAGACADDEFEFDADAHBGBABDBDBDCHF,True +605,13.0,12.0,3.0,10.0,9.0,12.0,19.0,5.0,BFBFCDGDBDAGAFCHBBBDHGADCEAABAGFGFGEGEGDGFAFEGBGAGEFFGFGEDADBBGAGAGEFEBBHGHGEDDAFAH,True +606,25.0,22.0,15.0,23.0,20.0,14.0,29.0,17.0,ABABABGDEFEFEHBAAAFDDBDGDGAGEEBHFFCAHAGABACACHEGDGDFDHGGFFHFBEDECFGHCBAGDGCHBGBGCGFDADECEBEAEADAFEBEAEFCBCBCBHBABGBHAHAGAGDDEEEHBCEADGDGDHHFDGABDBDGGCGCADGGHHDHGGEGC,False +607,7.0,12.0,19.0,9.0,3.0,6.0,12.0,7.0,CHGGCADECECGBGCGCEHDAFACDBGGFABCBCBCBCBFBCGCBCBCBFHADACADHDCGGGDFCHGFCHDHDB,True +608,15.0,15.0,12.0,14.0,12.0,4.0,21.0,15.0,BGBEFEGDBCGCGHHEGCFAGEBFGHBCCEGAHACGBDBGBHAHGHGHEHEHACABADADAHACBGDAEHGHBDBDBEBAAAFCGCGDEDCDEDHDAGHGDGBGEGDC,False +609,11.0,19.0,6.0,5.0,9.0,14.0,11.0,10.0,BBBBGBFBFBABDHAHFBBAHEHFCAHGGDGDFCBCFCGAHBDBGBGFGHAHGBEEAFFFBFEFEACACEEGEAEDGFHAHBBBF,False +610,7.0,6.0,1.0,2.0,7.0,8.0,15.0,3.0,GGGGGDGFBAEAEBFHGHDFAGBEFEFGFGBHAGAGBCEAEGBGEGAFF,True +611,9.0,11.0,18.0,12.0,13.0,14.0,18.0,18.0,DABAEGBGEGEGEGFDHCGCHAHFHFCCCCHHGADFBGEHAHEHECFHEHEAGABDGEBCBFFFGDGBGACHHHDHCFCDCHHGDCHCBCDCGCBBDADGGGEDECBFFFFEF,False +612,1.0,6.0,5.0,8.0,3.0,4.0,3.0,4.0,BEBEBGBFBFDDCHBDFCHDGACHFHGDCDCDED,True +613,5.0,7.0,4.0,9.0,3.0,12.0,4.0,8.0,DEEHBFGFCHBHDHFAGDBDHDFCFEBHHHBFBABAGAGDFDCDFFFFCFDA,True +614,5.0,4.0,10.0,9.0,2.0,6.0,6.0,7.0,GCBCBCGGBFHHCFCHHDDDDCBGAEACACFDADCCAFHFHDHDEDGFG,False +615,20.0,20.0,21.0,19.0,32.0,21.0,14.0,26.0,FCCGGEHECEDEDBBECHCHCFGBEHECCCCCHCGCDCDEHAGCECEDDBEBABABEBEAAAAHAHEFAFHFEFBFBFAFGEEEAEHEBGHEHDBCBDAAEFFHCGFHHHGCEAGDBEHEFEGDFBFAHHDBCHFFBEGEGFHECEADADADBHFHAHDDFDFHEAEBDBDGH,False +616,4.0,1.0,4.0,5.0,3.0,3.0,4.0,3.0,AGAHCHBGDFDCHEDEDEFCFCDAGAG,False +617,14.0,17.0,16.0,17.0,18.0,16.0,11.0,15.0,EFEFHFABEBEGEAEBEAECBDHFEEGEGBGDHHHHHBHBHBHAFAHDBFHABDDFDHBGDECECEFEFGDABAFAFABDHFBFCGCGBEFCDCEADDDFACAHDCCGDDCBCGCFCABECGCD,False +618,29.0,30.0,26.0,14.0,18.0,25.0,13.0,17.0,HACCBHBFAFBFBFHFCBAAGAEBEFDDBDAAACACACEEDDAEFGBGFEFCABAGAGAGFGCHCAGFBBDFHAABFCFCFDHEHCFBFBHADBBBBHDDBCFABBEBFBADAEBCBHBHFHCBDDHCHGHCACAGAGDFCFEAEBECECECFCECECGHEBAFAEAGHBCF,False +619,31.0,22.0,24.0,19.0,30.0,25.0,19.0,29.0,CFHEHCGFFACEHBDEEGGACFCACAGAHAEAFDCGBACEFGAECCAGHBHBDBAEAGFBABAGACAHHHAHCHCDCDAGGGAHAEAEDGGCEHFHFHFDGBHBCEHEDEFEFEFEAADACHFBDBDBDBFBFAEHFHBHEHEGEDEDCCEBFBFCFCAHDBFEAEFEACAFADEBEHHDEGEAHBHCHDBGBCDHFGF,False +620,18.0,17.0,15.0,24.0,21.0,15.0,18.0,13.0,ECDGDBDGDGDEAEBEBCFGFGAGAGHCDEHEHBGGGFEAAFBBDFHCDCEEEEGAGAGEDFDHDHAFAFHEHDADADBDECACEDDBHFEGECADDCFHBCBCHCDDFDGBBBEAECEDEFABAHCHGDABFBFGFCBGA,False +621,0.0,2.0,1.0,1.0,4.0,1.0,0.0,1.0,FEEDEBEBHC,True +622,14.0,20.0,14.0,20.0,27.0,29.0,12.0,26.0,CDCACEHFHFHBHEFEDEBBFFFFBFECHHAHEHEDGDEEBFHFHAACEDECCCCEFEHAHBHDHFHFAFABEEEGEGEBDAHEEEEFHDDDGDEDABHBAFGFEHABFBABDBFFFHFCFHFBGCABBGBHFHFDDAHGFEFEDHCHDEBGGGBCDDDCGF,False +623,16.0,25.0,17.0,19.0,21.0,19.0,21.0,15.0,BFDFDFGBGDHBHEDCACFCEHEDEBCFDEDADBDACADDEGEGHAHBHFEBCCCAHEHEBEBAAAAGCFCFGFBEEEHBHEHGBDBDAGAEAGBDBGFEFGBCBCFGEGBGHDHGCCAADCDCBFBAGGFGEHDFBEBFBFDFCFHBGGGEB,False +624,23.0,27.0,21.0,27.0,12.0,19.0,33.0,26.0,DHAGAGFBFCCHHGGBCBFDFACGBGBGHCABACAHFHCDCDGFGFCFGFCAEGHGABABEDEDHFHFDFBGHGEGHAHBHCDAGAGAGBBAEAFGCACBFBDDHGHBHDGDGBGDAAAAEBBGBDBDCACFCHCBDBCCCBGFFHDHDHEGEDEHHDDDHBGBHDFFEBDDEEGGGGAGHCHDBAGD,False +625,17.0,22.0,27.0,7.0,24.0,19.0,26.0,18.0,GHECEGFGAGCBEEGBGHGBEBEAEFGFAFCFHGGGGEEECBFBDGGCGCEDGFBHBCBCBCAGABEGEAEABFFFBFBFHEGFGACAEFDBCBCAGAGAGFFCCBEHCCBCBDHCBEHCHCACEBFBCGDAHFCECEDACAEHHHHHDAFGHCHCEGEH,False +626,21.0,20.0,18.0,14.0,19.0,24.0,20.0,19.0,FGFGDBFGAAHHDABADDECCHFBGCEEHGHGHGAFHCHAHBCBFAFAFABBBABADDGEBBFCFCFCFCBCDCDHFAGGHGHGAGEHBFAFCHHEGEFBHDHAHAEDGAGAGEGCDEHECCCBBBAFFFEFDADBBEDEGCFBFCGAEEEEFEF,False +627,22.0,20.0,15.0,21.0,16.0,16.0,15.0,16.0,GBGEFDACFGFGHBHECCFAAAEEGBCHCBCFADHDHDBDBDFDADABAEDFBADACBCFCFEHGCEFEAEBHDHDFDEEBBHBGAGDGAEAEGGHAHDDDDFDGBBBAAAABDHGHFAFECCCECHBDBCBFEFGAGAHH,False +628,7.0,15.0,8.0,13.0,14.0,12.0,11.0,8.0,DEDBDHFHDCDCBBBCBDBFBFCGHGAGEFAFAEADBFBGBGHGDCFADBDFEFEDECEFHHCBEAGGGDEBECEABBGHGFDHEEFE,False +629,1.0,3.0,3.0,8.0,6.0,2.0,4.0,5.0,HEHDHDHDEFBGBGDDCDHBEDECGCEEFGAD,True +630,11.0,10.0,7.0,6.0,8.0,14.0,8.0,5.0,CAHAHABFCFCACFCAHAGDBCEGHFHEBDFAGAGABBBEBCFEFEFBFAFBDEDEGGDFDABFFEFGG,False +631,14.0,11.0,20.0,21.0,13.0,15.0,14.0,16.0,HCFAAHBFCFAFHFGDHFCFBBBEBEAEAEHEHGDDBHHHFHDCDEGECFHFDFDADACADHGEDADHDHDCDCGADDECEAGBBCECDGGCGCABAHFGCDCGFBHBDCDGAGCCCDCGEFEF,False +632,4.0,8.0,5.0,12.0,1.0,8.0,6.0,3.0,CAHAEDBCCFGDBDFFBFBHDDDDDADCGBGBCFAGDGFGFHDBDBF,True +633,3.0,4.0,7.0,2.0,2.0,6.0,5.0,5.0,CBCECACAFEFDAHBCGFGFBHCHDHCHGGFBFG,True +634,15.0,14.0,8.0,23.0,21.0,16.0,17.0,8.0,GDDDADADACBFGFGFAFACADAEEBEBFCGBFHFHGEDDDFCGABCBDHDHEEFHAHGEFDFEFBFAGAFEGDGDGBGDEDEBHBDCEEEEGEBCDDEAECDDDEGGGAFAEBFBGHEDAB,False +635,16.0,23.0,27.0,12.0,33.0,22.0,20.0,34.0,HEHACECAHFBGBEBHHHHFFCECEHEAEGDGDHAHBFFFFFFFGABCEFEBECECHABGCGFHEEEEEEGBCAHEHCHDFBGBCBCBHHGFBHDHCHEHEHCFCGCGEFHHHCDGDEDECBCAFEFAGHDCABHDAEACCHGHFBBHDEAGBGAFDDGCACEFEFEHEHEBEGCCEGBGBCAHBHB,False +636,18.0,21.0,19.0,22.0,14.0,15.0,21.0,26.0,GHABCDDDAGGFFEFDFHBACHDHDECGBFBFAAGECECDAFBHCDCEBGBAAAGHHEHEHEHEBAFDFCACECECEHHHCHDHAHAHCDBDGGGDHDBCCFCGHHHGDDDBEBFCFDGAFBFBDBDBGBGBABHHCHGHGDBEGAAHDCGAGBGF,False +637,7.0,11.0,15.0,9.0,7.0,9.0,10.0,13.0,DAFBFHGDGAGCDCDGHBCECFCGCDEDHDHBHBFBEGEHDADBBBBGFHHAECHGHGHBFCFAACCCFFHGACHCBCECE,False +638,23.0,18.0,27.0,21.0,18.0,14.0,17.0,30.0,DEDCHCBFEAEAEABAHGDGDADEBEHCFDGGCCCCDCBFGFCCHDHDHFBABDHEHAHFHCAFAEADHDHCHEDACCGCGCGCBAFHHHECDDDBGHHHCHBHAHECFBBGBDBFHAHGHCDGHGCGCBBBGBABFGCGAEEDFDAEHFHDHEEACAEFEACHCAAA,False +639,8.0,5.0,5.0,6.0,7.0,4.0,6.0,5.0,FGEBDBDBGHGDGCAHAHCDAGAFAFBEBEGEFDCHAEECEDACAH,False +640,25.0,30.0,19.0,18.0,18.0,25.0,21.0,28.0,DBGBFBFHFHCAFAFACGCHCHEHEGFGADHHFEAEGEGHGEAEBDADHBABDGGGGHBHDDGAEBDFCGCFFGACDHBHFHCHFAGHEDACAHBDDDAHHEBEBABACAGBDEDGHBHFHFCGCDFBFBFAHGCBDDCBAEAEFCABABACACEFHFBAEHEGBGBHBFFHBEBFBFBFHCBC,False +641,10.0,7.0,19.0,15.0,18.0,26.0,16.0,17.0,EBEBEADCFGFGAADCEFHCAEDEAEFBHEHDGDGDBHCGCFHFHCHFEFGFGCECFCGCEDAFEGDFCAEADCFEFHHHFDFGFGAGDGDFHHGACFBHDHCGFGFCHCHCHCDEECFFFFEBEBFD,False +642,17.0,19.0,31.0,20.0,20.0,27.0,31.0,22.0,EFGFHEBFAHAHFHGCFCFGFHFBFDHDAGAGBECCHCBGBFEABDEGEGFCBDDFEFADADBFEGEBBAEHEHAHAFGCGCGCBCBFGFCACHCECGCBCAGFHDBDCAFGCGCGCGCDDDCDGDGFBHGFFAHCFCFHECDGDBECCCDCEGEFBFEHHGAGCGDHAHGHEFDHAGBGBGHDECE,False +643,10.0,16.0,8.0,13.0,16.0,18.0,19.0,19.0,DBDFCEGABABHBFGAHEGFFDHCFCFBDHHACAFECHHHHGFGBEHEGEGEGFGBBDBFEFHFCEDECFAAGFGFEBAGHEHEHEGDBDFDFBEBDBDFDBGEHCAAGHGHGBGHGHD,False +644,23.0,23.0,24.0,17.0,10.0,17.0,18.0,14.0,BGGGGGEGBACCECHCHCACDBAEFEFHAHACFGGADDCDCDCDGHGCBHBAAFGFGFABBBBFBHGFAAADADCDEACDEACBHEEFCCHCHAFBCHGEGBFDFHEBBHBDBCHDBDBGFCFBDCGFGFACABBBAAAAAFDCDC,False +645,19.0,20.0,19.0,12.0,21.0,19.0,19.0,26.0,BCHEHEABABAHAHDHBEDEAEGECEBECAHDGCFEFCHHAHDHDHFBDACABGCEBHBCFHGCCCAEEDAACABBHGHGHFHBEBHDECEBDBCBFEFHHHGHGHGHFHFBDGEGACEFDFHFEFCGGGAEFDFGCGABFFCFCGBGAGFBAEA,False +646,24.0,19.0,25.0,16.0,26.0,22.0,27.0,28.0,DADGFHCDDBDHDHGGAEECHHHFCAGACFCFEDCCECEGFBFBCBGEHEACBCBGGHGAGFHCGCGEFEDAHAHFHEBBBHHAAEAECBGAAFBGBHBHAAFEEAECEGHGFCDCHHHHBDFGFGFGBEAFHFDAHAHCBCEHGHGFCDGDGCGEFABDBFBAAAHADEDEGCGHECEFEFECECG,False +647,19.0,19.0,11.0,23.0,12.0,13.0,15.0,22.0,FGFAADEGEAEADGDFHAHBHDGGGHDFBHBDDGDCDHBHBHEHECEDBDBEBHHDHEABCCGFAHGGEADAGFDAHEHDHDCDGDHHEHFFFGEGBDCACACDFDHBBBBDCGAAFAHABABACACFDFBBHB,False +648,14.0,18.0,21.0,17.0,4.0,13.0,14.0,14.0,HDCCBGAGBGFGFHCCACHCGCBCBEDEBCBDBHFCFCFGAGACBGFDFBHBADAGHCHBHFCACDFDBABAEGCHHDBDCFBECGCGBDAFFGHDBDBDADADACFDADCHHGH,False +649,18.0,10.0,20.0,21.0,15.0,23.0,20.0,19.0,CDCFFDAABAFGFDBHFHGADADAHGHGBDFCHHHCDCHAHADCDGDGDGCEFGFCECFCFCGCAAAAEAEDBDBFFHHHFECECGGEGAABHECFHDEDGHGAEADFFHGDGDGEEBDCFGEHFCGCECEDDFFFFBFBCBHHAG,False +650,2.0,8.0,12.0,4.0,7.0,2.0,3.0,2.0,BECADGCCCCCBCBCBDGGFECECDBDBHECEFABHBCEE,True +651,23.0,17.0,14.0,13.0,18.0,7.0,9.0,12.0,HGFCACACFCDEEAGBGBADADABCGDAEADGDBACFHBEDAABHBHGHCAAEBECECACEDECEGFGAAHABAEAHDHABABADEBCFCFBEEEHEBFBAEHEHDCDBGBHD,False +652,9.0,5.0,7.0,3.0,3.0,4.0,7.0,7.0,FHAHAGGGGHGCGCEHEAFAFCHDECHBABCFGBHBACDCDAABA,False +653,17.0,14.0,10.0,12.0,16.0,15.0,12.0,13.0,FFDCCCGHBHEFBAEAHDFFFHBBBBGAFABABAEADAEFCBDEEHFDACHCHDAFCFEDGBCBCBEBEGGGCHHDDAGAEAEDEDEBEHDHAHEFGFGFGHGAAEAFG,False +654,18.0,23.0,28.0,27.0,18.0,13.0,30.0,25.0,CGCBCACGBGHACACADFEBGBCAEHBDBCHAEDGDFDCCAEHDGDFDFAFBGBGEDCFBFBFDAHGCCCBGBHEHAHGGGCECEHEAGCGDGDHBBDGCECHAHDFDGEGAGDGEADHCACBGBCHAHAGBGHHCHCHGEBEAEDECHBGBGDGFGEGHCHBDDDCDHDFDHCFEHDBDBF,False +655,15.0,11.0,8.0,7.0,7.0,6.0,7.0,13.0,EFAFACBEEDCAHAHGEAEFFHBHBFBFHGAAHGHGAGDCBHHHABDBEBAGAGDDDADHBCBEACHCACACHB,False +656,23.0,17.0,14.0,15.0,23.0,23.0,21.0,14.0,DBBBEEGCGFABAGAHAHFDEEHECBHBFBEAEADGDACGFGFCFDFGFGFGBEBEDEHHCFEHAHAFAHEBABEDEFGFGBGAAECFCHCEAGDGDCBCAFHFDFDFCFEEEEECFDBGGGAAADBGBHDAGEEBHDAAAHFGCGFAFC,False +657,22.0,13.0,20.0,11.0,19.0,20.0,13.0,19.0,AAAEEECFGGCCCDBDAFHFAFCCBAAHBBBEBFBAGCGEGHCAEACDCEADBDEAFCDGECEGGAGABAHAEBHHHHHCFCFEHCHFHGHCHCFAFDFDFDHBEGEFFFFAEAECEDEDHFGABFEGCHCHAHABF,False +658,13.0,8.0,9.0,8.0,6.0,14.0,16.0,11.0,DFDAACADGHGFECCGBFFFHEAAFACAGFHCGCFAFDFBBHHFGAGABABAGEFEFGDEBFBDBGACHCHCHGDGHGHGEGDGH,False +659,24.0,22.0,11.0,20.0,12.0,19.0,20.0,10.0,ECECBBAAAFHDHDHCBGFGFACABAGGHADBEAFFDFDFDEGCGCBBBFAGABBEDGGAGFDAGHGDDAEABBGBHDGEBFBHDFGCBCBEBFDFDADADBBFEHEFEFDFHFEGDCDCDCGBGAAAAAGAFAHBGA,False +660,9.0,8.0,11.0,8.0,16.0,14.0,26.0,11.0,FEGEHCHBGBGEGHGHGEGHDEBHAFACGDGFGACHHGAFCGGFEHDFDEEGBGBGFGFGCCECFAFDFDHBGDAAHAGEGDGEGFGAGEBCCCCBEEGEFEF,False +661,21.0,16.0,26.0,12.0,16.0,24.0,13.0,16.0,AHBFGAHHBCBABABCCGBEFACECGHGFDAHHCCECFFFDFAHACACBCBGBDFEFEHEDACAEDEDEGEGDGBBBGCGAHACACEFAFDFAFBDACAFFHFCFCAGEGBFDFBFEGCFCBCFHACADDCHFHFCECEHHHCE,False +662,19.0,21.0,19.0,34.0,20.0,23.0,22.0,19.0,AFAFBGBGBABGDDADCFCECGGEAEACHDHDEFCFDFDECHHGDEDEGGFEBBBBBEFEDDFAHCBEDDBACDCDAHAHGHDCFCFDFEFEDHCHDDADBGCABDHEBBFBDCDHDEDEABDHEBFBCEAGGHFHEAGFGFGCGDGFGDGAGAGABFBFDDHDCDHHGHECDCFAF,False +663,30.0,32.0,21.0,26.0,25.0,15.0,23.0,18.0,GBDHGHGHGBGFGABAEEDBCBCAHAEEDFDADEGCCCGHDBBBEDHGGFCBBHEAACDBGAGBGFEAAAAAABADGGBGCDCFCFDFCBHAHBBBHBHGDBDEHBHBHBEAABABDDEAEDFDEBEBECEGEFAFCFCADEGCGBABABFBCEADAEGEGDCDGBFHAEAEFCDDHEHAHFDCDEDCAC,False +664,14.0,12.0,16.0,18.0,20.0,25.0,19.0,23.0,GFFDFGFDEAHBCEEHCFEEEABFGFGHGAGAGCGCFDBDBDEDEABABDBHFCFHDGAGEHEHEGDCDCFAAGAEEHFGFEDCHFHGGEHDDGBADDGHFHEHEHECFCFCDCAEFFFGFGCBHHCCFCFBFHFHEDADHHHHABB,False +665,1.0,1.0,5.0,0.0,2.0,0.0,2.0,0.0,CCCBGGAECEC,True +666,13.0,18.0,8.0,9.0,12.0,13.0,18.0,15.0,FADABCFAFAFGFGFBCBGGGFGDCDCABDHDAEHEDGDGEFFHCGEHHFHBGAGAHEGEGABFCGBGEEBEHFHBHBHBHBFBHCABBHGEEDCDBABABHGGAE,False +667,12.0,9.0,6.0,10.0,3.0,13.0,8.0,9.0,CBCHGHFADHGAGBCFDFAADDFCFHDAAAAAFCFEAAFADCDGDGHFHFHGBFBFBEBHGHGBBDFDEB,False +668,25.0,23.0,24.0,17.0,11.0,21.0,16.0,12.0,GDAFFFFHBBGCACGCECBHAEDBBFFFBCBCACACGBABEBEDDBFAHBHDAGAGBGBGAGBGAGEDBAFCCDCGAGHCDADACAEDFHACBEAACFDDBDBHBDBDFFFCFCFCFCAAAEDHFAFHCHCACHCGAGFFCEEBEBGDH,False +669,3.0,6.0,1.0,5.0,4.0,4.0,3.0,1.0,EABGBEBGBFBGDFDFDADEDBFHEAC,True +670,5.0,9.0,11.0,15.0,8.0,21.0,12.0,11.0,DFDCHCFFDHHAHACGGFBDBDCDCDAHEFFFHBDBDBEECFGDGHGBFCDADABHBHGGEGCCFFFFFDFHEBGCEFDFGFEFEHDGFGFC,False +671,9.0,14.0,11.0,13.0,12.0,14.0,11.0,23.0,HDHCHCFCFCHCFCDADADEHFHBAEGFGHCEDHFCCDEHAHFEBBBADCHHHHDHBHEDDDADHDBGBGBCBFHEBEFGBGHGFFHAHGHBAFAGBEFEBEHEGFG,False +672,3.0,4.0,0.0,0.0,2.0,6.0,4.0,2.0,HFHFAAGEGFGFABBFGFBEB,True +673,17.0,21.0,20.0,5.0,12.0,13.0,17.0,15.0,BCBDBECHCAAADCGGGGFBABABEBCBCACAGHBHDHBFEEEEAABCBCBAAHBGGCGBGHGFGAGFFCHGHGHBABFBFHCHADDFCCCECECHHEAFBFBCHHBCEGGCFAEAEGFF,False +674,14.0,34.0,17.0,24.0,19.0,23.0,30.0,24.0,BBGEGHHHEHEFABDCHCFBDAGBBBBDBFCFCFAHHEHAFGHGEGEDBDBDHCFCHCEDEDEDGCGCDDDGDGAGAGEGBHHCHADFDBBBCDDACGHGEGEHBGBGHFEFGFBBDBHBFBDGGCGCDFGCBBBDADGHFCFADGEHFCFAFGBHFHBGEAEBBBAFGGDGFEFBBHEHEBABF,False +675,22.0,22.0,20.0,24.0,22.0,17.0,36.0,34.0,CHGHGHAHAHCECDBGCADHEEGECDGBFCCHCHFGFGBBHFHFHEGFGAGCGCGDGDCBFBFEFEHEDECCHBGBDADHFHEBDBGFGBAHGHGEACGGAEAHGBDCDGDHFHBHCECBDHGGGGHBBDFDFHAAAAAHADADHGHEHAGFGDGAEDGDEEBHACFGHBHBHCGGGCAHEEAEHEFDDDGDBBBAE,False +676,5.0,3.0,7.0,7.0,6.0,1.0,5.0,6.0,EHCHEBAGEGDGDCCCCABHEGBAEDEDCDFDADAHHCHG,False +677,14.0,12.0,18.0,20.0,14.0,12.0,11.0,15.0,CCADHGFACAHGHDDDDDGFGHBADGBEBCCDDDADADABBHCFCFHBHGAGEEEEEEEGEFHCDFAFCCADBDCDCDCBBBBCHCBDAGAEHDHAHAEEHEHFFCGCDFGECFFH,False +678,20.0,18.0,16.0,16.0,18.0,22.0,18.0,25.0,DFFHFHFGFBADAGHCBCAGBCBFGFACBEFEGABBBEGHHFHFDFHEEGEBECFCEBEGGADEDEAEACHCHABEHAHAFAHAHAFBFAECECHCHGHAHBHCHFHGDCHGHEBDBDGCADEDGGFBFGDBDCFFEHDFDFDGDHCHBGAAA,False +679,13.0,13.0,11.0,11.0,12.0,13.0,13.0,10.0,DADAHACGEBDGEGEDEAACHFGEGEGFGFCFAFEBCBFEFHCCFCHCHEHAFFDBBBHGCEBGBGAAHFHGHBFDEGAGBBBBDDADADEDACFC,False +680,21.0,9.0,11.0,23.0,10.0,11.0,13.0,22.0,BHEFDAEAEGGAGBCHCBAAHAFDFGGGGBHADEDACFCFAEABHBHBAAADFFACDDDHDHCBCFHDHCHGDAHAHDDDCDADEHFFAFDEHHDHECDADAGAGBHHGHEHEHCDGDGD,False +681,29.0,26.0,19.0,24.0,29.0,20.0,27.0,23.0,AAHAECBCBAADACAFFGCEADCBGHGFEFEAEDEDBDHDEBHDHAACAHAEBCBDFFHFBFBFBFGFBEAHBCAEAGAGBEEEEEEEEDCABFGFBDHFAFAGBGHGCGEGDADHDFGBCBHBHACEBDADEDEDGGGGGGGBHBHDHCFGBBEHCCAHHFABDCGGECFBAHGDGDCEAEHECEGHDFDEDGAHA,False +682,12.0,18.0,15.0,23.0,25.0,24.0,20.0,8.0,DADHGFBFDADAEECECBFDHDBCBABAHFFFFEFEFBFBFBEDFDEAFCCHEBBGECCCCFAGBBDBGCEEDHGGEGEAEAEFDDDGDAFEGCGCGCFEDDGDFHEDGGGGGEBEDFDEDHBEBDCCEFFFEFEBABFGAGHGD,False +683,10.0,19.0,7.0,19.0,5.0,6.0,8.0,11.0,CHCGBDFEGADBBBBBEGHAFAHBGFACAGAHDBDBDADHDGDBDCCCEDDHDADADCDBBBHBFBDBDFDADEHHHBHGGEFBB,True +684,10.0,3.0,3.0,5.0,2.0,4.0,6.0,12.0,DBCHHBHEDEGAGAHFGGHFAAAGAGADBCHAHAFDFDACHHHHH,True +685,10.0,19.0,16.0,24.0,9.0,16.0,18.0,17.0,DGDFEBDHDADCDBDHFHFHAGCHCHAGEEBGBGBAFDHCBADCDHAHEEABDDFDFABBCDDADCDFDFBBGBGHECCGCGDECGDBFGGEGECHCGFFBFBDGFHBHBHBCGCGCGBDDDFHFHFHA,False +686,11.0,7.0,14.0,17.0,14.0,20.0,12.0,14.0,HDHABCEFFBEHCGCACACBHBGEGEFFFBGCECDCDEHEDEGFGFDDDDGDGAHDHDADADFFFAHAEDHFBADEDBCCGHAEEECFFEFCFHFGCGAHDFGFHFCFH,False +687,19.0,24.0,19.0,21.0,13.0,20.0,17.0,22.0,GBGCDCDHFCAHAHBFFDCAGBFBABCFFBFACBGHGHBFFGHDDADHFHFHBGGHGAFDFCGAGEDEGEADDFCBABFBABAHEDEGFGFCBCFDDADACECEBEBCHCACFEGCHBBBDDDGHHDHAHAFABDHEHEHEGEDBABCBDBHCHC,False +688,11.0,6.0,12.0,7.0,7.0,10.0,7.0,5.0,CCBGGGGFABECFADHEACFCFGFGEDFCFAFBHBCBHBDCCHCAAAAAEDDDDAFCFCEGEAEH,False +689,1.0,5.0,2.0,2.0,0.0,1.0,2.0,2.0,DHDGFGCBBBBBCHA,True +690,15.0,19.0,20.0,21.0,26.0,23.0,15.0,18.0,GBGBGEFEGECEDHDHDHDHDCGAEACGCFBFECCACGCDEDFDHDFBBBEBDHGHDCBAAAFBHADFBFHFHFHFEDDADEDEFCBBAEEGEACCHCEGACEDECECFFFFHAHEGEBABEDFBHEDEAEADFDCHFHFCGEBHCFFFGBBECGBG,False +691,16.0,20.0,16.0,13.0,21.0,17.0,19.0,17.0,EEBEDECEAEBBBBEHFBFBFDCDCBCBCAFGHGCECGGDHAHCDCFCEHDHDBBFHFGEECBGBFHDHGHEBEBEAEFBAAAAEAGGGFEFCFBABDFGFDFHAEEGHHHGDFHFGCGCGDAAACADEGBBCAHGEGH,False +692,15.0,18.0,25.0,15.0,20.0,16.0,23.0,15.0,DCAGACABGEGHGBBCAEGHHDAAAFGCBCBCGGDGCGCHCDCDAFCFGHGCGCEEEHBGGECACADEDFDFGFDBBFBCDCFCDCEEHEHFDBDBGEGFFBFBFEECHGHBAGABABEHEHGCEHBFDCCGDHEHEGBFAFAECEC,False +693,18.0,15.0,17.0,18.0,19.0,18.0,17.0,13.0,DAEAFACADHDHCFCBBBDFDEGEGEFDGBEFEBGHGHEHGGAFAFAGAEDEBHDADAEAEDEAHGHAHCECEHFHBGFAEAFBCGFDFGCACADFCGCBCBDAHFBCDEBCFCFGECDBDBGBGECECFDDHFG,False +694,7.0,11.0,9.0,10.0,9.0,4.0,5.0,10.0,CDDDBBCGFGDHDHEHBHEHEBEBEAEAFHDEGEDHBAAFHCBFEGCBCBCBAAHACCCGBHDDD,False +695,9.0,7.0,7.0,14.0,15.0,8.0,16.0,16.0,DFDCDCDEAHDDDBHHFHFCDCHCFBAEEDGAEAGGFGHAEECHGHGHEEGDGFEFEDEGBGEDDBHBHGEGFAHAEAHAHGBGHGHGDECB,False +696,24.0,23.0,24.0,22.0,20.0,19.0,26.0,26.0,ADGDAEBHCGCHCEADABGBGBFEEGFAFAFBFGDGDHHACDCHFACHCGGHGHDHCBGDHBACHBHGHGAAEBFAHGGDGHGFGDCDCGCDCAEGGGEEEEEHDFDAAAHADAFADEBBBHEHECACBEEEBABFCFCFCECFCHBHBAGABHHFHBHFCDEBCDGDFDFDCBFBCBEAGDGH,False +697,19.0,24.0,22.0,23.0,29.0,24.0,25.0,34.0,FCFEAEAHCGEDABFEFDHCHCGCGCFHABDGEGFGFGBHBCAEEHGBCBCBCGHDHFHABGHDHCCCAADDFDHDCDHFBEHEHEGFBBHHHADEEEBEBFACHHHHGHGABBBBEDCBBBEDEDFFFFFFHCHDAEFEGDGHFBDGEHHGFBDADECEDEDGFBFEGCGHHCHCHGHEFEAAGAGEGDGCAHAEAEBD,False +698,13.0,19.0,14.0,18.0,18.0,16.0,11.0,16.0,BDBFFDFDFGGHAHBHBHBHFGAGAHDHBEBDBHBFBFHCBEGEGEDCCCCBGHECDCACDBFCEDBDFDFDHDFEFHFHEHEFEBABDEHBCDDHAAADEBAGAEACGEAEFBCEGEDFCCAGE,False +699,20.0,17.0,18.0,13.0,20.0,22.0,16.0,23.0,ADHHHHFDFBFAGADBEFFFEFEGCFBDHCAEABAEAEBHFECCFDFHHHHHFHCHCHEHEAEBGHACABFCFGAGDFDFCBHGCFCBCHDEDHGHAFDFAGECECEFAGCDEGEHEAABCBGBGBGBABGEAHGEAFHFGCECADBDB,False +700,7.0,10.0,13.0,7.0,8.0,14.0,8.0,3.0,FAAEFBFCFBFBEDGHCCCCCEDEDFHECDBDGFGFADGBEFCFCGAAAHEDECACFBFBGGGFCFCBBB,False +701,16.0,27.0,21.0,29.0,23.0,22.0,14.0,18.0,ABAEADACBDBFAFDCGBDEDBBFBFADHHAABHDGABACDBDEAFCHCECHDDACAFDFDFEAEDHDFBFBFCEEBECDCDHABFBGEGFHFHGBDEDEDEDCDHDHFAGDGHGHGHBCBCBFHCEBEHCCDCBFBFBECFDGGGFCECEDHBGBCFEEDGBFBEHEDE,False +702,22.0,31.0,14.0,20.0,15.0,20.0,18.0,12.0,GHADBDAFCHAEBDBDBDFDEAAABADEDCAABBEGEGFGEGFDFBFBAEGBBCBCBEGDCDAHCHBADADGFBFBHBGBDCFGDGHCDCFCBEAGFGFHFEBECAFBFBHBHBFBEGEGEBEDAHABADABBGBCAAGDFBAGHCCFDFHF,False +703,21.0,26.0,13.0,16.0,14.0,14.0,14.0,17.0,CHABCBFGFAABAGAHAHAHACBDFHAHEHGCACDBEHDGBHCECEHFAACABHBABABECGBGAGEFCGDEFHBBFAFHFHAHEBEFEGBGBEBEDDDDDDDAHHCBCDDGEADABGBDBFGFBFBFBGEDCBB,False +704,1.0,0.0,1.0,1.0,3.0,1.0,3.0,0.0,DEECEGFGAG,True +705,7.0,6.0,9.0,6.0,4.0,3.0,8.0,5.0,AGABCBCEHFACGFHHCHEACADDDDGBGBGBCEFHBDEDACGCGCGA,False +706,6.0,5.0,9.0,7.0,4.0,10.0,8.0,4.0,BGHGEDCHCHCGCFFGDGDGCBCBAADFFAFEFGAGADFHBAFCBCEDEFCFD,False +707,10.0,10.0,4.0,9.0,12.0,8.0,9.0,7.0,EECFAEAHAHAEAEBEHFDFDAGCDHBHGGEGEGFDFDEBADDCHFDDBFGEGBGBEBEAHAGBFBABC,False +708,11.0,14.0,22.0,17.0,26.0,26.0,22.0,25.0,ADBFFHCHCHCDGFCFBHBHBAGACHDFEFHCBGECDDGEHEHDHEGEGEGECBHAECDHDCDEEFHFDFDABHGDEHEGDHDGFCCCHCHDHDHBAEEGEHEHGGGBBFEFEDEFHFCFAEHECGCAFFFCFBBCAFBCHEEGEGFFECGCGFGFGFAFAGB,False +709,20.0,25.0,16.0,17.0,13.0,14.0,18.0,22.0,CDEHBHBHAHBHBGDGEGBACAHAHGBGBGBAAAGFDEEBGBABABFGACACHGHDFDADHEFDHHECFDACABGHFHDDDAEAEDGDCDCFCBCFHBCBEBEBEBFCGCHFEGGDDBBBCEHGDACABGHGAFHHHBFAFCFHB,False +710,30.0,23.0,16.0,22.0,21.0,35.0,15.0,23.0,FAFAFAFEFEHAHAEBEFDFDBDHFCEAHHHHBEFDADHEHBCCCADEHFHFHFCGGDECGCBDBGAFAFBCDAHADBECEFHCBCBAAAFAGBFADDFDFHBGAAEABFDEDFHAGAHAGAGEGHFEFCABAFCBEBEBHFDDDFDADEEEFBFDACEGFBDBHBHBFGFBFCFGGHAHAFGFC,False +711,6.0,6.0,12.0,7.0,12.0,9.0,12.0,10.0,HGEDHDGCGCGBHBHGCFAGABCBGGEBCHCHFGDEEEHEHAHFHCGDFEFAFAFDECECDCFABCGEGFCEDE,False +712,23.0,31.0,32.0,27.0,25.0,14.0,31.0,14.0,CGABCFCEHDFDHEHBDBDECCFBDGHGAGBGCHCBAEHEHDFDBDCEFGCGCFBAGGGEFEABFBGEAAAAHAGACACECACBGDGDBHBCFGHGBCAAAFBDDDDDDFGFCECBBEEGDADCBEAEAFDGEGCCBCBCBDGCECGCGCGCECECBFBDBABDBDHDCEHEBECGAABDBGGGDEEGEBBAHGGDH,False +713,4.0,5.0,5.0,9.0,4.0,5.0,6.0,6.0,BEFEACAHDHDHGHBDCHCDEDFDGDBEFGDGDFAFBBGACHCG,False +714,18.0,19.0,22.0,14.0,25.0,27.0,18.0,19.0,GEHFCECFCAEFBFAHBCCEBFFEFECDADEDEAEFEBECECGHGAAADAGHBFGFAFHDEABBDGDEHEFEFDBCHEGCCEFBFEHHHHGHGCAFAFHFHFGEHEHCGDFEAEAGFFBADAFFCFABGBABFBCBGBGCDCDHFHCECECDHDBGBCBCGG,False +715,17.0,8.0,11.0,12.0,13.0,12.0,12.0,14.0,BAGDHBHDHABAEGHFDADFECDCGCGADHDHDHABCBHGAAFBFBEHEAFCFAGHEBCDFDFDCHCHCADAEHEGEAEGCGCFEHAGGFAFEFEAEAG,False +716,16.0,17.0,24.0,24.0,21.0,17.0,16.0,24.0,FCBCBHBCBCECDCDAFFHHHCHDBEFABAEDEDEDECFDGGGAEFEFEHCADAFACEEECFCGAEDEDGHGDGAGFBHDHFHCCGEGBDHGEBHHHEHACAEGFDFDHCECBADECHHHBBBFBFBDADCCFCDCBCDEDHHCGDDAAAHBHGHGDGF,False +717,30.0,23.0,30.0,24.0,12.0,21.0,21.0,16.0,ECEDACAHEHCACECDCGCBHAGDFACBCBAFGFGBACCCCACFGEGFHHAHABGBEFFBFDFCGABCDCBBBBBAADADGDFDFHFDCDCHFBFAAGAGAGAGFCCCHABGDGDBDCDEBHDCDCDBGFFHHGBEAAHAHDFDEDAHAGDCDBHAFGGGBABDFCACACBCFEEAE,False +718,8.0,9.0,11.0,13.0,10.0,18.0,7.0,15.0,BHBGDHDHDEAEFFAGAGABHFFFADHDHDGAFCDCAHBDECFAHDHCCBGHFCECEHEFDBDCDGEGDBHBECFCFCFHBEFFFFFHFHE,False +719,12.0,23.0,32.0,23.0,25.0,25.0,24.0,32.0,ACHDECHBHFHGHGHDADAGHCCEBEBCCGHFFGFCBEGCCDDDBGFDHDHDHGFGBCFCGCDCDCDCFGEDBDBEGGCFEFEHEBEHECBFDCDGBGEGBGEGCFEEECGFGADCFEAEADBBCECEHEBEDFHFCFCAABGHHHHHFAFABCCHCFCAHEHFBFBFHCGFBDGDEBHBHCECGDBAFHHHHHDH,False +720,9.0,6.0,1.0,2.0,6.0,3.0,3.0,2.0,AAABABDBGEHAGABCBGFHEAEDEAEFEFBA,True +721,4.0,4.0,5.0,4.0,1.0,4.0,3.0,0.0,BGBCACGCDDFDFABACECBFAFDG,True +722,16.0,8.0,13.0,19.0,18.0,17.0,9.0,17.0,DFEFCHCGADHDEDAHEDEBFHFEFEAEDEDHAHADCBAFACAHEHDCGCGCDCDHDFECEBEDEDEFGGABFBFGCACFDFAFBDGFHCADHEHEGDAEAHHHBHFHFADCFEBGA,False +723,20.0,21.0,15.0,7.0,15.0,20.0,22.0,15.0,AFCDCFCFGFGAGBCACBHAAFGFBBEEAEGHDEDBHBHEHBCGEGFACEGHGHGCGEGECAFFGEGEGEGBBFAFDCBCFCFADADBHEAEHGBGHGBAFAHCBADFBHBCBFAFHBABABAFABHFGFGEHCG,False +724,22.0,23.0,14.0,13.0,20.0,26.0,11.0,21.0,DEBABADADEGBGBEBHBCCAAEAFFDAAAAFEFAFGFCFCBHBCFFFCFBFDFEHHDHCHCFDEDHBHBGAACEFAHHFABAEEEEGBCHCECACGDHAFDFHFHFEFHAGGGFCHBBDBHBEBFBFHHEHBBBABEEFGFEDGDAHAE,False +725,21.0,25.0,25.0,29.0,21.0,32.0,25.0,20.0,FGGGCGEGDFAHHHCCCGAEABFBEBDBDHDCDEDAFGDGAEFCFCEAEADABCBGGGGGCDCDCFFFEHACBCBCGCFCFDBDFCFAHBDDFDFBEHEADCDFHEHFFEGGDGFHEGEBBBDHEAEAGAGAHBHAAGAHAHDDCBCFFFHFEDGDHDBFBEAHBFBEDFCHGFGDCFEGCHCFBFDEDFDABBFBCB,False +726,16.0,20.0,16.0,17.0,10.0,18.0,13.0,17.0,BBBBGCACACBFBABFBCDHGBCHCBADABFCFCFGAHEGBGEEEFDGDFAGAGCBCEFHFHGHFHAHFDFCHAHAGEBDBDGDCDCHFHBDDADCBFADEEEHHDGFGFHADEDHFHCBCBABADF,False +727,10.0,29.0,22.0,26.0,22.0,17.0,21.0,19.0,BCBCBCBDAFHFCECDCDCBHECFCGAGDGBHFDGDGBGBEDEDEDBCBAFAGHBHDHAADBDCGFGHDBDEGEFBBBCBEBEHECDHEGDADCDHDBBGCEHFGCAEAEBEBFBHADCECFCFEDGHGHBHFHGHBCFGBCEFDHGBGFGEBEHEFFDDBDECGD,False +728,11.0,13.0,13.0,11.0,13.0,20.0,15.0,18.0,EFFFEBCDCHCAAAADFHFHGAFDFHFCFBEBGCGAFBCACAHAHEDBBGEDEDCDGBGFGFGCHCFFDHEBBCGGGGGDFHAHDHBFFCHHDHEHEFBHBHECAGEGEFEFBH,False +729,26.0,25.0,13.0,24.0,26.0,16.0,21.0,19.0,DBDFABGGFGHEHAAAAABFBFBGBDBABAGEGCGFEEGEBEDHAEDCHABCDEFAFAGDHHAHADAFAFGBGAGHBDGCHHHBFFEAEDBDBEHDBBEDDHDHDCBCBEHCACDHFCGAGEGDDBEBEBEAGAEADABAFFFFEHGCGCEEEEBEGDHDGECEABHDCD,False +730,16.0,17.0,13.0,13.0,6.0,15.0,8.0,16.0,CCHDADACCDBABEBHDFBEAGBGFCECHBAAEAEDEGCHCHAFBHGHDBDADAFBDBGBHCHCAGAGHHCDCFFDFBFBADFBFBFHAAADBFCFGFBFHHHH,False +731,16.0,23.0,24.0,23.0,24.0,17.0,32.0,25.0,FFFFFFFDDEDGGHGHGHGFDHBCACGEGEBEBECFFBFBDECCDEHCFGEACHDHDHCFDHEGABHEGBGEAEHBAGCGHGHEEEDEDHFCGDGBAHAGAGDGBACCEAGAGAGAHFBCHCGCDCHCHBDBGBEBGCDFDBCBHEHEHGCGHBCBCGCAADDDGHGBDEDEGBBDFEAEGBCH,False +732,2.0,3.0,2.0,0.0,1.0,3.0,2.0,1.0,FCFGFHCBGBAEAB,True +733,6.0,2.0,3.0,2.0,1.0,4.0,1.0,4.0,BFFCHCHCHAAFADBGFDAHAEA,True +734,5.0,4.0,6.0,8.0,4.0,8.0,3.0,7.0,DGHGDEDEFAFBFBDDEAADFDHCHFAFBDGHHHHCCCCFCFBEA,False +735,11.0,7.0,8.0,6.0,4.0,4.0,8.0,5.0,CHCACAGAEDFDCBHDHFHBCDDHAFGGGCACAGAGBBBGBEBDFAAGAECEA,False +736,20.0,16.0,16.0,26.0,10.0,23.0,15.0,12.0,BDBHCCEBDBACHCDFGFCADHDFDHAECDAGAGCFEFCFEDDDDDDDCFHHADFDABEGGGAGAGADABAFCFAFDBEBEGACADDDHAHBECHDGBGBDDEGEGDBFCFHBADGHGHFFFBFAFAFCFCFBFCFBA,False +737,23.0,11.0,24.0,14.0,10.0,9.0,22.0,11.0,FHADCDEAAAABDBHAFADADFCGGGHGAEAHCGDDCDCDHAHCGGGGCACFCBCBCGCHAAFAHEBADAECGCGCGDGECEDGBFCDBAGACFHAEGCGEGBGCECHGGFHFABABABCCDCE,True +738,26.0,23.0,28.0,29.0,22.0,16.0,18.0,26.0,EHDFFHFHEAFFBBEHDBBBDBDCGEGEGCBCDGHAHDEDEDFAFGCCCACBDAGAEFHFHADAFHCDCDBDHAAAAAHCHCHFHFEFHCHFBAEDHCBCBCBEBDADGDAHAGACACBHEDDDEHCHBDECCGBGBHDCDHDBGCCBGDGCHHGFBAEGEAFACACBCEEEEHEGCGAADAEBGDDD,False +739,8.0,2.0,10.0,6.0,9.0,6.0,10.0,6.0,CGBDCDCHHEEAEACAEEGFHFDDDDFGFEAHCCCCCBFGAGAGEFAGAGHCEGEGH,False +740,11.0,8.0,17.0,13.0,9.0,9.0,18.0,8.0,BGAGBECGDGHFHBHBGDGDGCCCCCCFCFDFAFHBDADGDGBBCACAFEDGDHCECHAEEEBDCGGAGFGCGDAAEDEACHEHCCFGAGDGF,False +741,4.0,2.0,8.0,8.0,5.0,1.0,3.0,4.0,CECEAEHCCADDHDHGGEBHBECFCDDDDCDAGAC,True +742,2.0,9.0,1.0,2.0,5.0,5.0,1.0,4.0,CBHEDBAFFDBABEBEBHFHBHBFBGEFE,True +743,18.0,19.0,21.0,21.0,22.0,11.0,26.0,21.0,EAACDDDHDGEGBHHHHEBEBABHEHBFGCGDGEGCDCDGGCGHFFDFBBGACADADHHADCDGDGBCCCBEDECAGHGHBFCFEDEDEGGCBEFEBEBEHADBHBGGGADADFGFDAEAGBBHGDBHGHCHCACACAEFEGHCECEAFHCHBGEGECA,False +744,31.0,23.0,20.0,24.0,21.0,22.0,28.0,21.0,DADEBEBEDADABCBFGGGGGHGHAFFGBGBGCGDGFGHBCCFDEHEADABAGGBGFCFCAGAHHEDBHBHFFEHAGAGBCDFAEBHDDDDEHHACFBHDGDGACFFBDBAAADAHAHCHCEGAHAGEEEEEBHFFGADABABEBEBCDCBHFHFAADFCGCGBAADDDFCCCHFEFECEAGACAGDGFE,False +745,5.0,11.0,15.0,7.0,10.0,9.0,7.0,16.0,EFHFBCACFCEHBCBABABCECFHHHHFEFHCHCFCBHHGGEGEDDDHAFGEGCBDDDHEEAFBBCHCHEHGHBCBCDCG,False +746,1.0,0.0,6.0,5.0,2.0,2.0,2.0,0.0,GDCDCACECEDFDGCCFD,True +747,14.0,8.0,8.0,12.0,14.0,15.0,12.0,12.0,HCHDFEEGCBCDCAEEEBEFEFCABABFBFDEGFAHEHAHCHGGFCFDEDAHCHDFDGDGABHEAAFAFHFEEGAGDDFBHBHGDGEGAGAFAFD,False +748,23.0,22.0,15.0,27.0,27.0,24.0,31.0,19.0,CFEFAHGBGDEAEBEAEBHBDDGBFAHCGFHFHGEGFAFADBEFHBEBCCFCGEGADBBGGCGBGHHBEGEGABBEEEAHAGEGFGAGFCCBFAGBGFGFGFADDBDBGBFEFGFAAAABHCDDDDDDFDFHFHBGDEAEDDDEDEGEDEDECHDHCFAGAHAEAGADFGHEHDHCCGEGEDBDFCHC,False +749,18.0,23.0,17.0,19.0,17.0,23.0,21.0,21.0,EAADEDBDBFBEECFCDEGFDFHBDAFFBCCCGCHCHAFAFAGGHGECECEBEGAGDGDHEFEHCBAADAFBFBHBABGBGCFCDHFBDEDECFGFBCHHDBBCHDGDFFBFBGDGBHHAHABADADEEGHGHBHFFFFEFGCGCDEHHGHGAAAGBBH,False +750,26.0,15.0,24.0,31.0,22.0,18.0,27.0,36.0,HFCEEEDBCEHFDCDCDGDAHEDGBCCDCGHDEECFHFAFADHFCGEEAEHEHECGABAHFBFBFDACBDBDCDHDHGFBFACAHAHABAHHHCDGHGHGHAABFHFGGHADDDDDADCDEDGDEAGGGGAGBGACCHBHBFDDEEHEDDHCHCHCHGFGAHHHBHFGCGHEEDEDFBAGHGHCECGCAHAGFEADAGA,False +751,2.0,2.0,6.0,6.0,5.0,4.0,2.0,6.0,DCHAHGHCHCEBEGDFCHCDCFEFEDEFHADBD,True +752,12.0,16.0,4.0,9.0,13.0,13.0,11.0,4.0,EBEBDBDBFAHAHADAGBCBFHEEAFAEEBEFGFEFAAAGGGBAFCFCFDGEBBBBBBGAFEEDDDGAGFGCEFEGBDDFHB,False +753,20.0,22.0,13.0,25.0,23.0,25.0,27.0,11.0,DBDAFFDEDEDEFEFDBCFFHDDEEEBEFDFEFEGBGCHCEBEHEHAABAGGGDEAFDFBGGGDFAFAFACHEEBHACBFECCGGGGGGFDFAFCGEGEFHBDBACAHAEFDBDFGABFBEGCGCDHDHDGDBDBDGCFBGCAHGDGBBFAFABEGEGABADADGB,False +754,13.0,24.0,24.0,21.0,25.0,16.0,20.0,11.0,BHBDGCGFGFGFGHGHBFGCEEFEFBAHEHEHEBCDEDEDBBCBCEFECGCDBACAGDGDBBHCCGDAAEAHCEFECABABDGDGCBEDHGFEDEDBGGCACDDBEBCBDFGGGEEHECECEFDFDBBBDCHAFDCBCBCGCFFACAEAEDBFE,False +755,21.0,23.0,12.0,20.0,22.0,23.0,13.0,24.0,FBFBCBFBFECEBHBHDHBBBFBACGBGBDAGFDACHHGCGHFDBHEEEFEAEBEBFGAGAGEDDFDFEFBCAFDFEAEAEDFDBDHECDCFCEAHAFEEHAHGHGHCBDAEGHBDDDBDEHGBAHAFCHGBFHFHEHEADHFHFHFDEBCAAAAHAD,False +756,9.0,16.0,8.0,17.0,8.0,7.0,7.0,4.0,EFEFGFGCCBABHBDDDDGDABBGBFBFEACDBDEDHCGEGBCBCBFDDDEAFABADAHEBADHDCCEDGDBBBAD,False +757,15.0,20.0,18.0,27.0,18.0,16.0,16.0,19.0,GHFBGBCEEAHDBDAHAHEBFFDDDDBFBEEAGBDHDBEGHAHADDEDCFCFBHAHBHDDGDGDECECGHGFGDADEFCFCFDADBGEEBCDEDGABABHBHBHCDCECECEGACCEABFBFBCCHABGHFHFACDDDDDGHECGFGFH,False +758,24.0,10.0,20.0,10.0,13.0,18.0,25.0,18.0,HEHAHAFAHCGCGCHEBGCGHGHGFGCGEABGHGFGHCHEAACABAHACFEAGCECBGGGGGACDFHFAFDFDFDFBEEAEAECFCAADAGFCHHECFHGAGHGEAHFGCCDBDBGACAGADABBDBDCFAFHGEFCF,False +759,5.0,2.0,3.0,3.0,1.0,2.0,7.0,3.0,CFAGGHGHGHBDGDGACEDACAGABF,True +760,23.0,15.0,19.0,10.0,31.0,25.0,21.0,16.0,FGFGHGDGBHACAFAFEFEGEBFGFGFECEDBFEFEHHCFAEACFBBBAFEDCGCEAECFCBBHEGEDEAEFBFGFGADCCCBHAAEEBABAHAHACECFHFEDEABFEDEAEBECACECGFGFEAGAFEFACHGDGAEAEGHHHHGDCBEDEHFHGGCG,False +761,4.0,5.0,6.0,6.0,5.0,5.0,6.0,6.0,EFBFBFGDHCHFEFGGBDAGACHCHDHBAAECCBCDEDEDGHG,False +762,5.0,7.0,14.0,5.0,9.0,9.0,6.0,9.0,EGEFHBHFGFHCEDEBEFACAEAECHCHCHCHBGCFDFCCACBCDHDFGABHBCECDGGEFCFB,False +763,7.0,10.0,9.0,14.0,6.0,13.0,15.0,4.0,FHBHAHAFAEDCDEAEHFDDGFBFBFDGGFGBGBCBFDGDBCGEGECAGAGDGDFDCDCDFGCGEBDGFBACFBFDCG,False +764,18.0,17.0,21.0,10.0,17.0,19.0,30.0,14.0,GFCBGAFBBEFFCGHGEADAHFHEAEAHAHFGGGEGECCFAGAGFFCACBFAFAFGGGAEHGHFHBHCACHFAFDEDHGEGDFBCGCAHGCEBEHCBGBDDCAGBDAGECECACBCBCGGGBBBBBECFCFEFHGDGDGDGEGEGC,False +765,16.0,9.0,24.0,14.0,21.0,12.0,17.0,12.0,FCCCCEGDGDFBEGCBCDDDDCHFGACDHECCCEEAHGHGCCCFEAAADAHGEBEFDDDCDCEAGCGDHEAEAGADAGEFCFCFGFGEAFHEECECEGHGBFCECEBFBCAEBGBGHAHAHAHBE,False +766,2.0,5.0,3.0,5.0,5.0,3.0,5.0,14.0,GCCBCDHEEEFHHEBEHGHBHDHDHAHFGAHDGDGHHHHBFB,True +767,25.0,19.0,25.0,19.0,30.0,21.0,34.0,24.0,AABAGCCCGCDFDAEECGCHBHGHGHDAGCGDFDCEGEBAGFEEEHHAGAGAGFECEHGCECEHFHABEEEBEFEBEFEBCGGGDGABEDEDADGFGFCHHHHDDFBFBAEAEAHGFCFAAAAABAFHECGCDCGFADDBHBGCEHFBBGDHFAFHBHCHFHAGGGGGGAGCGEDEBEDECHFHGBDEDBFGCCCCE,False +768,25.0,18.0,18.0,14.0,17.0,14.0,28.0,21.0,DBBECABABAFFCHGBFEAEHGGEEEHGHGAGADAHGCCFDFDGAFCECECDBBBFBDHHGHEHBHAHGCGFGHHCCFAEAECGAGFHHCEGGGCDCEHEHEDGDHDAGABACCBCBGFFBBHBABADAGGGGHGAGAGAECFBAGAFADAEHDD,False +769,1.0,3.0,1.0,7.0,6.0,6.0,6.0,3.0,EFGFHFCEBGHFBDEDEHEAFDDGDGDGDGBEF,True +770,10.0,20.0,19.0,21.0,15.0,21.0,16.0,16.0,CDHDGGGCGEGECDCDCDABFBDBFBFDFHFHDDBEAEHBGBGCDBGBCHHDGFGCHDHCGCAAHABAFHHBDEFEFCFDFCFCFAHEFBFBGHGDDDCBEGGFEBEAEBDBHCHAEFCDCBFEFEBHCGCBFDFDEA,False +771,4.0,6.0,5.0,4.0,2.0,2.0,2.0,5.0,DBACDGDBBHBHCFDECECACAHAHGBFBH,False +772,20.0,21.0,27.0,26.0,23.0,24.0,13.0,18.0,HHGDAACADHDEDCABDHDFCFDBCFCABDCCCCFFFDFBCBHBGEGHGADACFDGAADDDDDECEHEHDFEBEFCFHFAFCFCFAFCHHHCEBEBEGECECFCHEFDCGBAFADAEAEDEDEFEHEGDAAEBCAEABBFBFBEADGCHDBGBDCDFGGBCBCBEHGHCHBF,False +773,23.0,11.0,12.0,12.0,15.0,10.0,15.0,14.0,HHBEBEDEBGBDFCECGCGEGCHDHGHGBCHAGAGAFAFAHAEEEAEAGBGEGCGAACABBHDABFDFAHADGHFBCDDHAAEAEAEAEACDFDEAAAHFDCCGCHHGDBFF,False +774,17.0,24.0,28.0,15.0,15.0,16.0,18.0,18.0,EFEFEBGCDADCEHBHBHBFBECECBFBFCGCEDEDCCFCGCGFGFACCDFHAHGHBHCHEHECCCGGFCHCADBBBGHHEGCCCGCBHGEGBBBAADCDCDCDADADABFHFAGBDBAHGBBABFEFGBEAHBGCCHFHGDABACAFDEA,False +775,3.0,0.0,2.0,1.0,0.0,2.0,2.0,3.0,AGHGHFDFCHCAA,True +776,17.0,9.0,11.0,6.0,12.0,12.0,17.0,14.0,GCGDABAFGFGCCECFABAEAEBGADHHEHAAAEDEAEABDFCGBADAEHGHFFFGAGFCFDBHBFGHHCGAGHGEGHBHCECEAEAGFCFCBHGHGH,False +777,4.0,6.0,1.0,5.0,7.0,2.0,6.0,4.0,HEFEAEAEDBBGDCDHDFEBAAHEHEDGBBBGGGG,True +778,6.0,7.0,4.0,4.0,5.0,13.0,4.0,5.0,HEHEAFGFAFAFBGBAFFFDEDECBCFGDBEHFAFBFDFHFHGBACCB,False +779,9.0,7.0,5.0,6.0,9.0,8.0,7.0,9.0,DGBEBEDHAFAFHFHFCFCEDEGEDEDGHAFBHBAGAFBCBHFAGADAECCBGEGHHEHA,False +780,19.0,21.0,16.0,16.0,23.0,19.0,26.0,22.0,FFCAGEGEGAHBBEBEGCDFEFCFGHHDHDHDBEFFAGEGAGAGAHEHFAEDBACCCEDGBEACFCFEDEABABABFHFBGBGAGEHHACBCGCHCHGHEABACDBDHEGFGEADHFBDCDCEBBAGHGHEHEHGHDHDGDGFHABECEBDGGFGBGBEFFF,False +781,15.0,24.0,23.0,18.0,23.0,14.0,17.0,21.0,FEAGCCBABABAFAHCDGHFCAEGBGBGHHBBCBFBABAEDEDADHFECGDGAHEBEBECCGCHCHEBCFEDDDCGCGDGDHEFGGCHCBEFECAHDEDFDEHEGEFBBHGGCECECFBDBDBAHAHEHDHECFBFDCECABABHBGBCHFHDHE,False +782,14.0,24.0,23.0,18.0,18.0,17.0,19.0,17.0,GAECGCBBAGAGAGFEEDDFBEEEBBGGEECCCCBEGEGFGDGCHCHCHEADBDBHBHFGADBFGDHHGAGADDDDDCBCDHFBFHDAGFHFHFHCBCFEHHHBFCFHFCGCBCAGFEBDFCECHCACBDBCEAGDBDBEBEBEBABAFC,False +783,17.0,21.0,14.0,26.0,20.0,11.0,14.0,15.0,CHAHEHDHGCCADABAEDBDBFAEABGDDCGADADBBAFCEGDBEBDHGEGFHEHEHEFCFDGHADADBDBDCDCGBABDECEDEDFDCDCDADEDBDHGBGBECDHEHFFBAEAEBEBGHGEBCGGBEFHBHCFAFA,False +784,9.0,13.0,21.0,19.0,11.0,19.0,13.0,15.0,ADHDFGEBBCCDCDCFHAGDBCBCECEAGAHCDEAHBHEFEAHHGDCHCHDHDHFBEADFCGCHDHAFBGBGBEFDFGFECACFEFGFDCDEBGBGCFBFCDGDGCFDFHFHFCFCDCDB,False +785,3.0,4.0,10.0,4.0,5.0,8.0,5.0,7.0,FCFCGCGEAAGFCECECHFFDHCACGCGEBHFEFHBHDFDBDBHHC,False +786,13.0,15.0,20.0,21.0,12.0,14.0,14.0,18.0,BFDGDGDADECHCHCEDGDBDGHCHDGCABEEFEFGGDDBDHDHDGCCEBDFDFBHBHBHFHFAECEBAAAFAEAHBHGHDFEFBHBABECCCCCDEGHGBFFGHCDCBGDCCCFHDCACAFGHADA,False +787,12.0,21.0,22.0,19.0,22.0,24.0,29.0,14.0,CGCGEECEGGBEAGCFFFCDCEEACFBFBGBGDGDHDHCBCGADEHGHBFGFGFDFDBGEGEBFCFCFCFABDBCAFFGDGBFHCHEECDFDFCBEBFHGCGEGAGAFDFCEGEGEAAHHHBGCGCGAGDGDBDFGEDBDFDBCHADEEGEHEHABBFEHBCB,False +788,17.0,13.0,19.0,20.0,16.0,16.0,19.0,15.0,BDCEGHGDAFFHFHDADAHEEEECFCGDHBHGGGAGAEFGBCADGCCCCCCGCDCBEFEFDFECADABAFEBGBGAADGEGHADABHFHFCEDHDGGCDCDFDADGHCFBBCBCEHBHFHDEDEDEGHGAAAFBF,False +789,28.0,17.0,13.0,32.0,28.0,13.0,27.0,17.0,AEADADBGBAFAEADGBAAGDDEGEBEFCFCFHFHAEGEHDHAADEDHDCFCBAEGEGDGCGAGBGBGBFDDDEDGBGBGBDDGGADCDBGAEAGDBCADEDHBABAECHCECAFEHAFACDCDGEHEHFBEHDDDDFEAABDHGHGHDAGECEGEGDHEAEGEGEAFHDHDFAE,False +790,20.0,14.0,14.0,14.0,17.0,15.0,16.0,18.0,FCFDDDHCHCEGHADCBGFEFCFEEEEBEADABHBDEFCABABAGAGEHHBHBDAECGDEAAAFAEADBHCGGBGBGBEFEFEFABAGFHHGACDBDHHGFDACEHDHGHFCFDHCHCHCEFAGAGAG,False +791,18.0,17.0,18.0,19.0,20.0,20.0,6.0,18.0,FHFHFDEAADAFBBACGHDCDFAGGFEFADEDBFBFECEAFAFACCCEFHBHFHBBACHFDGDCDHDHGBAHCDCBHBEEEEAECBABCBCEDHDFDEDEDEAEADACAHFHFHEDCCABEHEBEHCFBFGFBDHC,False +792,14.0,17.0,13.0,12.0,11.0,16.0,16.0,11.0,DDBDBDAFBDBFAFAGBDEGCCECHCHCGFABGBCFEFECHFBABAEECBDHDGDGHGHGFCFHEAEGDHBCBEFHBGAGACAHAFGFGFDEABFBABGFGFGBHCAEDC,False +793,9.0,19.0,17.0,11.0,13.0,16.0,16.0,13.0,DCGHBFFCGEEBEGGAGFDEEBFGHCHCDFDBCBCFCFCGCGBBBCBCBFHFGCAEABHBABGBDBDFDHAHFGFHBBBGHGHECFDECEGHGHDAAGDBCECDAEAEFEFCFH,False +794,18.0,14.0,23.0,18.0,18.0,15.0,28.0,20.0,GBGBGFGAEFECEBGBECECFGDEDGFCFGGHCHCFGDAHHCHCFCFCGCGCEAHAEABACDBDBAGGCGHAHBDFDHEHEGAGEGEHHDCDGFHBHGHFADECACAEABFCAHGHGBDCDFDFBAGACDGGCDBGGADHDBFHEHEAEGDCEC,False +795,2.0,6.0,5.0,6.0,3.0,1.0,4.0,1.0,GDGECBCHDEDECBBFBCBABDGDGACD,True +796,20.0,15.0,22.0,19.0,22.0,17.0,35.0,28.0,EHGHCDCDAEBCBFBACHCGEFEFEFDFHGHDCGAHDCGCDCACBGEEHEHGGGEHEFEGGAAAAHAFFECCAGHGHGHBACACDCFEAGGGGGGGCGAFCBEHHGDGHGADAHGHBDGAGBCDCABAHDDEEFGGEHHHBBBDBDHDHDHFHEHBCDCGFGECEFFGFGEGHFBEDA,False +797,22.0,14.0,14.0,13.0,13.0,14.0,15.0,9.0,HCHGGBDEFAFAGAHDCGCGCHCGFAADEDEABAGABFEFEFEBDFGABHFDAABCHCFCADBBAGDGDGDCDFEFGBDBDFFGCBCBEBGAAAAAAHEHEBEGCAAAFHECEC,False +798,15.0,14.0,14.0,26.0,14.0,22.0,16.0,23.0,DCGAADDDHDHFFDBGGFGEGBBDHAHFFFFAFCFBDDFEAEDHDHGHGDCHCFAGBDFCFEFGAGHECFCEDAHAGEBFBABDEDADCDHAFCFAFHBDFAFADEGEHEHBHGFGCGHGCDCDBBHHHHBCBCHDEDEDEDHH,False +799,27.0,20.0,19.0,24.0,17.0,17.0,26.0,21.0,GFGDGDCDFGBGBEBGBHHFDADAHEHEBBBHFFGGCADACAGHBHAAFACACHBECEFAHADGDAEHECFABCGCAHBHAHDGEEHFDFHFDFCAHDBDBFEGDGDGHBDBGAGEGBGCCECEBEHAGABADADADECGCGCAFHGHBFACACFDEDEBGACAGHGFDDD,False +800,14.0,22.0,27.0,22.0,29.0,27.0,20.0,20.0,BCBCBCACACAHDBFCHEHEFBGGCGCABBHBEEEBECECBDHDEBAACGCGFGFDFGBCDAHHHHFFEDDDDEFFHFDEGGGHEAEDEGBBDFEADFCGCGCHFHGHGEDCHFFFDFDCHFBCBCBCEEEGACAEHEFGFDFCFBAEHECGDEFGHGAFAEBBBBDCEHFCFEFDCDEDE,False +801,5.0,1.0,4.0,0.0,2.0,1.0,0.0,1.0,HCAEACAFBEACAC,True +802,15.0,14.0,17.0,11.0,11.0,11.0,14.0,5.0,DGAEAFAFCFDADEFEFCACGEHEFGCHABACABHBADDFDFCGEGEAAACHCGDGCGBEBFDCABBBBDBABFGGCCCEGFBBBEDAHCGCGCGCED,False +803,19.0,24.0,22.0,27.0,21.0,24.0,25.0,26.0,HFAFEFEFCCCHCHGDDHEHEDEACCFAFBHDEDEBGCGBFAHAHAHFGDBAGAHBHFEFBFEFABCDHDGACACBGDGHAFBDBCFHFHDHDGDADBCFGGBDACGHGCECEGGAGDGDGEGECADHDABGBDDCECEHFHBGGEGEHBFBDHFACAFBBBBHEEEGCDHGFDFDFEFHDHDCBBBC,False +804,14.0,12.0,12.0,16.0,9.0,14.0,9.0,8.0,ABCBAFDEDFDHDCDBAFCBGBDBEAEGEBCDGAACABDECECEHEAGHGDBHFFFCGDADFFFGFDBDFAHCHCHCHCBADADADABFFGGEF,False +805,10.0,5.0,7.0,4.0,17.0,8.0,9.0,3.0,AAGAGAGAGAHECEFEGEHEBEAEFDADFEEEECEDECHGFEFAFBEDFGBEACBCEFBCCGG,True +806,16.0,25.0,13.0,17.0,23.0,16.0,21.0,18.0,CBGEEFEGBBBCHGHBAAAAGAGEGCHCEDBBBBBHHHHDAFFEEDEDAAADFEBHGHDHEGEGHCECEBBDADGGGGGDGHEHEHEBBBFGFAFDFEFEBEBCFFEBHBECDBDFAFAGHDFDGBHDCFCAABCBHEGDGDEBGCCAF,False +807,3.0,8.0,5.0,8.0,9.0,8.0,9.0,9.0,HFFFBHCHEBEBEBGBDCGCECEFDFBFGAGHHDHFACHDHDEFBGDGEHEADGDBEGG,False +808,18.0,19.0,24.0,19.0,15.0,25.0,23.0,17.0,CDGFCFCAGHEAEADCGEGACBGFGDHEEECACECECFAHAFDCDHDFEBEHDFDFHFGBEBGGGBBBHBHFAEAFGFAHAGAFCGCHCHGHBCDDFDFDGDFBEBEBFAFCFGDCCHGHADCBFBGBGHFCGDGBCAHFDFCFCBCBDAEABADGFGHC,False +809,24.0,16.0,20.0,18.0,20.0,16.0,26.0,18.0,HBEFGCGHAHADGCACAFBFAFCEBGBFDGAGAEHHCDDHDFDHDHDEECGABCBFEAEHDGGGGBABGFEBCAEGBCFCHGHBHBABGBHFEFCCCCAHGEGEFHFDGAEBHDADCGHEAEAEAEAEGEDCDADGDGAGAGAEHDGCCFCFCADBGF,False +810,7.0,10.0,7.0,14.0,17.0,13.0,14.0,8.0,DEAEGEFECACABGEGEAHGHGHAEFEFECHDDFDBDBCBDBDFGCGEBECEDDDADBEFEBDFGBDFHGCFFDGGFEHEHFHBGAGEGF,False +811,11.0,12.0,11.0,18.0,16.0,11.0,15.0,16.0,EBEBABDHDHDHEHGHFAAGGCAFEDDGEFAFHDBDBDHEGGGGBCBCFDDDDDEDBHFEBHCHABEFEFGHECECBFGGGEDHCHCGEGACAEAECHABCHDADFDFHG,False +812,7.0,8.0,5.0,1.0,6.0,6.0,5.0,5.0,HHHHAEACACBEBCCAFAGEFCFDBHBFBFEGAGEGBGFABBE,False +813,7.0,6.0,14.0,17.0,20.0,8.0,11.0,16.0,BCHCAFAGAHCEFEDEHEDCHGHAEDGDFCFHGHGHAEGEGFHBBDFEHEDEDHDEDEBGDDFBEHGABCEDECCCADGHEHEHCHCDCDCDCEEGEFD,True +814,27.0,14.0,15.0,25.0,17.0,16.0,12.0,25.0,HFFCACAHFFCBCFFGDDECEFEHCBCBCDAAAGAHAHDECEFHAHAHDEABBEBCFGBGDEAEAEADGHAHACDHHHBCBEDFFAFHFEEGAAAAAHAHEHEDDDDGAGDHDBDFFAHDBACACAGHHDGBGBEDDBDHFHECGDDDHDH,False +815,9.0,8.0,11.0,6.0,5.0,16.0,9.0,7.0,DDGCCHAAADDFEFBHDFFFDFCFCFCFEBEGGGCFCGHGHEAAAFFHBCBGBEBCBFFFCFCAAGAHHGB,False +816,27.0,23.0,14.0,24.0,26.0,27.0,25.0,22.0,DABHHHEHAHAEFDBAGABDBGHDAAGAGFBAHAHEEDABFGGEEADAFBCACGCGCEFEBEBDFDCDGDEFEHEHFAGAGCBCGCBCBEDAGGBABHDFBFBDEHEHGBFEFEBDFHFHFDEECAFGFGFEADHDAGAGADCDCHFHCEADFDGEAFBFCFDBEEDGAGBEFEHDHGAGHGHFBFBF,False +817,1.0,1.0,2.0,2.0,3.0,7.0,3.0,4.0,FFFFADHDHEHEGCFBGECFHFG,True +818,10.0,14.0,17.0,5.0,12.0,5.0,16.0,9.0,CACBHAACABGDCAEAFGBEHEGCGCGEGEDBGAGFHBGCECEFEGEGBHBFGAGHEABDFDBCBCBHEHGHGBDCACBGBECCCCCH,True +819,20.0,12.0,13.0,11.0,16.0,13.0,21.0,6.0,ADCECACDCEGDFFAFBGBGBGBAAAEBEBGFDADEDAACACDCHHBGGGGGGGEGAAHFEFCGDGBCFABAFEGCDHFECEDEHABCDAHFGAGEGAGAEAGBFBCEFEFE,False +820,24.0,22.0,18.0,21.0,20.0,19.0,14.0,22.0,ECFBHAHAHAEAFBFGDGDCBCGAEAHABCBHFEDEDGBCDCDADABAEAEBHDGDHCBAHFDCDHHBHEGAAFAFCHCDDEHBFBFDGDGHBAFCEDEHFCEHEHEHGCGAHABCBEFHFGCDCDFBFBFAFGBDEDAGCHBEBCBADAGEBEAEAFFH,False +821,24.0,21.0,19.0,22.0,19.0,13.0,20.0,29.0,DAHAHAFEGCDEECECAAEHEFDDDGAGAGAGABHBGEHDHFHEHAHAHAFBHBHCAADCEBBGDECHGFGHGAGEDFDFDHHHCGAEABFDGBECECAHACFCHGFBDHGFDHBHDDDDGGHEHAHBGBGBHEABBFBDBFBDAEEBECCCCCACHCBCHAHDGDB,False +822,16.0,25.0,27.0,23.0,14.0,15.0,16.0,28.0,BHCHCDCAGFGAGBFHEHBABGDHBABFBGBDCHCHCHEHAHEHCHDBGBHACADADAFFHAADACBCBEGEFDFDFDFCHEHDDBDEGEDHHHCDEGHCFGFDEDBBGFGCGHAHBDCECHCABHFCCHCDEDCDCGBBEHDHBGBFEFCACHCBBABCBDGC,False +823,19.0,16.0,17.0,19.0,13.0,21.0,12.0,12.0,AAFGBDHDCDFDEHBBFHFCDCABBFDFGEGEBCHDDDBDGDACAGABEGECECECEFEHCHAGDDHCCDAEFFAFBFBGDAEHHBABAHADABGBFCFGDCDFHFHAGAFAFDFBACACFGFEFECBC,False +824,23.0,14.0,24.0,16.0,17.0,21.0,26.0,11.0,EEEECEBHDFDBDCFAABFDEEGGCGEGFHDGAGBCFCHCFAFAGAGFFBGAFAEABCGAEADADAHBBEHCHCBCBCDCECGHBHAFDEDEAAACACFFECEFFGACCDCFGGCGCGFDFHFGCGCGAEAGGHHFBFDADABBCGGGDGDG,False +825,16.0,23.0,19.0,19.0,25.0,21.0,19.0,16.0,BCECEGEHBGBGDACADFFBABGGEBEGCGAGDBCFCEADAEFEDDCHCDEDGBGCFHFGBEBEBEHCHCEBEDEBFBFEFHFHFGDEAEBGBEDDCBHDFGFCACAGAHBDBDBCCFCFAFDDDADHEEEFHAEAGBGCAHHHEHFGFBFGECHABF,False +826,8.0,5.0,4.0,4.0,6.0,3.0,1.0,4.0,CDGDCFEEEEABABADAHBFBHACAFHEAEAHCBD,False +827,24.0,26.0,18.0,19.0,16.0,34.0,27.0,29.0,CFAFCHHGFDHDBDBDCDCHEFBGBGBHBDADCGCGHGFDFBAHDDAFECBFFFHFAGECAHAEBEAAACGEGHGEABAFGCEAGFFHFGACBGHGAFHCHGHGBFAHGHBHBGBGAGCFBEDHBFBHEHEBFGECEADHFHFHFDABFEFHFEFBFBABDBDFDADGDGCAEAFCFCFCDAGGFGFBHHHHB,False +828,2.0,3.0,1.0,7.0,4.0,6.0,1.0,1.0,ADDDFDFEFEDEBFBEGFDADFHCB,True +829,18.0,8.0,19.0,22.0,14.0,21.0,12.0,12.0,EGEGCHAFEECHDBDBDCFAFEFDFEGEAFCFDADADCHFHEADAEHDHCCFCFDFHFDFDACACACEFDFDGBFBCGEGFGCGCAHADACEDDGCCACHBABDBHAHFFFDDHACBDEAEGGGFD,False +830,14.0,17.0,12.0,13.0,7.0,7.0,14.0,9.0,EGEBHBDCDGECBABADDGCABACFCEBDCCADADFGHGHGFGBGBGHGFDDCDAGABACHHDHDFDCBBGBAAFACEHAGAGBEBHBCBEBF,False +831,13.0,21.0,11.0,11.0,12.0,12.0,12.0,8.0,EAEDGBFBDBCHEBEBEBCHCHAFGGBCDDDCDCBADAFAFABADFCBCGEAEDBAFAEHEHADFHBBEHEFBFGEBHFGBCBCBFGGAGAGBGCGFBDB,False +832,14.0,20.0,21.0,16.0,26.0,24.0,30.0,17.0,BGGGEEEBFFFEFCDGGGGGCGABDFGHCAFFFDFEHDHAGAGAEBEBCBCAGBBDBFBFEEEDDFCCGCGEGBBDBHEDCFCHGFEEBGCFAEGEGECFCGCHEDDCBEDDDHHHCGBGEHEHGDDCGCGBGEGEBEHECGGAEABAFAHAFAFHFHCHCFFFHFBA,False +833,0.0,0.0,2.0,1.0,0.0,7.0,1.0,2.0,GFFCFHDHCFFFF,True +834,15.0,17.0,13.0,12.0,21.0,19.0,18.0,23.0,DEFBAGHEHEABHDFGFHFHCHDHECEHBHDGDGFFCGBFBEEHHCDEFECEDEBCBGEGEGACAGHGHAHDFCBHGFFFFDACEHEBFBHBHGAAEADGGADHHHHGHGFAFCFCGEDFFABABGECACABEBEBEB,False +835,9.0,17.0,15.0,12.0,13.0,15.0,12.0,18.0,AEAFDHGHGFDEDBFBABACCCFCHEHCFEDHFGFDHBHBHEFAACHEDECFCGCBCECEGHBHCABDBEGFDFDBDBEGEFFCCGHAHAHGHDFBBGBGDGHBHBCBFHE,False +836,24.0,27.0,17.0,31.0,24.0,22.0,21.0,23.0,DCGBEBCDEDADFBFEDADADBDCDCDEDFDGBGCGBHBHBHEHEDEDAGBGFDAHGHBCECADBDEDBFFAFAFAFEHHGCGFEFDDGDGFBFGEGEBAHAFDDHFABBBDADAHAGAFFFCGGEECHGAGAEECEBFBCBHHGEFDAAECFADHGHCHBBBBDEDHBBBEHHAHCHCAEFEHADGDC,False +837,8.0,2.0,11.0,12.0,11.0,8.0,3.0,11.0,BHCHEDEHFAFHDHCHFDCDFDFDAAHCFDDADHDECECACECAFEHEGDGEHEDEHFCBCGCAEA,True +838,12.0,19.0,12.0,11.0,20.0,17.0,13.0,16.0,DEFEFEHEFBFECEAEAGBGAFEBEDFGFGAHFHFCGBBBBBBHEFEBHBGBGHCHFBCDFHAACCHEHACDBFEGEDFBCBABHHCHEHACACEDDDDFDGHGHCAGFDFBEEEGEGBA,False +839,1.0,4.0,3.0,4.0,6.0,6.0,4.0,1.0,GBEECAGBFBFBEDCDFDFEEHEDGFGFC,True +840,5.0,4.0,4.0,1.0,6.0,4.0,2.0,2.0,GEBEFEHEAADACACFCFBBHCAGEBEF,True +841,15.0,12.0,13.0,8.0,18.0,15.0,11.0,15.0,FHFHFEAAHFEFCGEHEHCHCBCAEBBBCHAHAEGFGABHBEBEFCBCAHDHBEAFGBHAFEFBGCFEFCDADBDEDEDEGEFEFAACHDHAEACGEGHGCGAGFDC,False +842,17.0,27.0,15.0,15.0,25.0,21.0,18.0,18.0,DBEBDBEEGGGBGEHCACBCBABGEDEDGFAFCCBEDCGGFGBHAHDBBHBHECACEDBDHAAFAEBEDCDCHGBEDECHAFAFECECEFHGHGHBEBGBGBFFFFHFEFHFHEBEGEAEFFAFGBBBFHCHADFDFBABCGAEAGFHDADEBHBE,False +843,20.0,14.0,16.0,25.0,17.0,16.0,12.0,24.0,HBHEDGBFBCADADACHHDHDAEAHDDDDDHFFDHDGCGCBHEGABAHEDEABACDCEFGFHAGGBACGHAFFGDCAAGHDEGEGEDABACABHFDEEBEBDBDBDHDADAHCHBEFEDEDCFCFCHCHFHFHFHFCAEHHFCE,False +844,6.0,6.0,6.0,6.0,7.0,4.0,7.0,2.0,GCECFBDBDBEGHDEAEAFFECECACBGBDADGDGHFABGEGCA,False +845,14.0,10.0,13.0,17.0,13.0,16.0,16.0,22.0,DADFGHGHFHCBGAFEFCFCGDGDEDBABABECDCDBBGAFAGAHDDDDFDGDGDCEGGFHFHCHGAGDHHHFFCGCHHEFEAHHHFHGEGDAHECDCHHAHAEAEBCFHFBFCEHBBEEA,False +846,13.0,21.0,15.0,9.0,8.0,13.0,6.0,10.0,AGBCBCBDGCBFGHABCBCBEBABCGHEHBAFAFDFECDBBAAHBHBHCFCFDBABDCDFFCGHAHBHBEBEBCFCACDEHACEBFDFGFAFAED,False +847,8.0,14.0,10.0,15.0,9.0,10.0,9.0,7.0,DECFAHHBGBCEAACBCBADDEBHDHDEDFFFGEAEBGCGBGDGDFDADBDBDCFCGCBCHABFBDEDGDGBHBFFCFEAEH,False +848,10.0,5.0,6.0,10.0,12.0,17.0,10.0,11.0,DHDEDCDFDFAFAHCFGABAGFCFBGGGGAHCFDFAFEEEEBBABHFAFGFEEHDHECEHFHFEAHAHEDFDFHFDGGGEC,False +849,22.0,14.0,13.0,19.0,14.0,18.0,13.0,19.0,AACFCFBBHBGFDADADAHHCGFBCHHFHBHDGDCAHAHABDEDBDAHAGFGEBEBACHCDEGAFFDGBHFCFDDBABAEEDEGEFEAAGAGABADAHFGFCFAAGCFHEHFGFBFEEDEHEDCDCDCDHHH,False +850,12.0,11.0,24.0,25.0,18.0,37.0,27.0,36.0,GEGEAEAEDHDEDECECGGGEFEFEGCBFBFCFCDCHEHDDGEGFGDHFGEGAGCGFDHCHFHDGCCHEBBDACHCFCHGHCHCHGDFFFFDFHGHDFFFGFGHHHGCDFBFCHHFHDDBACHEEFDCAHDHBHFFFHHCHBHFHDGFGFGBEAHFHFHFCAGGDCBGDGDFFAACDCAFDFDFBHHAHE,False +851,8.0,20.0,9.0,10.0,16.0,10.0,11.0,18.0,GAGAGFFHFHCHGHEFEGADABHBHBFEEEBAHCHCEEHEDCAGGBBDBFGFHFHAHFHBABEHEBFBCHEBBBDDDCDBECEGDBCBEBEBHBGCHEDDHG,False +852,8.0,4.0,3.0,3.0,5.0,4.0,5.0,3.0,CEHEHBGFGBABDCGAGHFDCGAAAAEADAFEFEB,False +853,2.0,2.0,4.0,5.0,2.0,8.0,1.0,9.0,BHFHFHFADCCGFDFDBDEFAHHHHHFHECCFD,True +854,0.0,3.0,1.0,7.0,1.0,4.0,3.0,3.0,BGEDFDHDHGFBDBCGHDFDFD,True +855,13.0,9.0,23.0,8.0,13.0,14.0,12.0,14.0,CFCFCGHEACCCEEEGDHHAHBGBCFCDCDCFFGCAFDCABHCHCDFFCECGCGCAABFDEDACCHHAFAEBEBHGHBHFGEGCGCGAEBCBAGEFEFEFDHAHAH,False +856,10.0,14.0,21.0,25.0,13.0,22.0,18.0,15.0,HDAFAFDFBGDDCEEGEDFGBDBGCCCCDDDGDGHFDGHEFECHCHCFEDBDBACGFBFBFDCGEGCABABDEGCGCECEBAFGHHBDDDHHHGGDCDCACAFBEBECFCFAEHHFFFDGDGHGHDDFDFHFCFCBAF,False +857,5.0,7.0,6.0,6.0,3.0,6.0,3.0,6.0,HBHCDAHAFGBACABHBDBDEFGCHCHCBEFEFGFCFDDBDA,False +858,5.0,6.0,10.0,9.0,8.0,7.0,3.0,10.0,BGCHCHCBDDHDGDGABCBABFECECECDCDFHHCEDDFFFHHEHEAEAFHBEDHCAF,False +859,5.0,3.0,3.0,10.0,1.0,2.0,6.0,6.0,DADADBGHEADDDCDGHGHGCDCDBFAHHFHAGDGB,True +860,23.0,20.0,27.0,31.0,27.0,21.0,22.0,20.0,GBHCDCFCFDEDHCHGEFEFECCCCCADABAHFHFHFDGDAEEHACDDGBADFDEECFAFCFEGCGEEHFAFEFBABCDADEDEHBHGHBBAECECGBHAGFHHBGECCDEDBFHCACGCDAGAGADDDDDCDGFCFCEEEDEBHGHGHGCGCBDADHBGDDEDABABAEDEBFCDEBABGBDAFAFGEGH,False +861,7.0,7.0,14.0,4.0,11.0,5.0,11.0,5.0,GCGFGBGCCCGFAAEAECECECGBABHHCAEAHAEFEBEHDCDCGFGFBCGCGCDBEEHDGECB,True +862,12.0,3.0,10.0,5.0,8.0,8.0,5.0,6.0,GFCAHAHAGACCEHDBBAAAHADECEDECGCBCECFCFHFHAGGEDEFFCFAEAFAD,False +863,24.0,14.0,29.0,24.0,18.0,18.0,12.0,25.0,ACACHBEBEDABHBGCDCFCEDFCGCACGFADCCCCBCDEAEBDHEEGAGCDFDFDFGEHAHFEEAEHCCFHFEFCHCHDAAHGDCDAHFHEHDHDHAHADEBEBEGADAHEBFHFHACGFGCGCBCDCDCACFCFABCBADDBCBHHDHGAAHAHFFDHDEDA,False +864,12.0,14.0,8.0,8.0,15.0,8.0,10.0,15.0,EBEBGHCABAFAFDFDADGBHCEBGBGBCFCAEEDHCHGHBHDGDHEHEHEHCFGFBEEHAAAHGHGEGBFCABHFHEEBADCDABEBEA,False +865,3.0,2.0,2.0,3.0,0.0,3.0,0.0,4.0,BHDHBCFDFCAHAHAFD,True +866,5.0,8.0,8.0,6.0,13.0,7.0,15.0,8.0,FHCDEDADBEBGAGCCCEBGGFGEGEGAGAGHDHGBEHEDGAGEBECHCGFEEHEHGGFBFBFCFHEBCD,False +867,15.0,8.0,10.0,4.0,10.0,7.0,12.0,11.0,GCHHEHGBDBCGCBCFEAAHAHADFCFCFGAGAFBGAHAEGFBECEABHCHAEAEHGHGFBDCHGEGEGDACABAEA,False +868,13.0,19.0,24.0,20.0,14.0,16.0,12.0,20.0,HCHAHAGDDCDBGGHGHGCEEAEGFBFDEAEFCFHDHGFAFGEHDBDBDCECDFECHCDCFCHCHBBBBGAFDCACEDBFFAFAFBEHCACDHBCBCBHBCADDDBDHDHCHCBABHHEFGAECGCGCBDBDCFHFEE,False +869,11.0,10.0,12.0,15.0,14.0,12.0,10.0,5.0,CBGECDGDGDADCGAHDBDFFFFEAHFEFDBDGDGECECDDFDADBEACGFEBEBECCCGCBCBEAEAFGBAAAEDEGHHDHCFAFEFB,False +870,8.0,16.0,15.0,5.0,12.0,6.0,10.0,5.0,GEGAAFBCBCEGAAEBEBEFHHCBAAGACBBBBEBCGCGCECECBABCFCGCFEDEHCCDGBGFDFDEHCHBBGBDE,True +871,7.0,10.0,13.0,4.0,10.0,7.0,7.0,8.0,GAAHGCBADEDHDCCCACAFHEBBBBBCBEGEGFCHCBEGEGEHDHCFFABCFCFHGHABFECECE,False +872,5.0,6.0,11.0,4.0,5.0,6.0,7.0,6.0,FCCCACBDAFCCCFGBBHBGAGEGDGCGHGHDHDEBHCCFCBAEFEFEHA,False +873,6.0,3.0,2.0,8.0,3.0,5.0,4.0,1.0,AADDDCDCGGFFEBADADADEDGBGFFEFAHB,True +874,16.0,16.0,9.0,13.0,16.0,16.0,11.0,18.0,DGAGHBHCEFGDAAEAFAFBBDFHEDEDHBHGHGHDDEDFCFCAAADAHFBCBCGEHEBFDFAFCFAFAFBECCBEDHHEHEGBGCDFGFHHHBHBEBEBHAEADBEBAAGEGHF,False +875,10.0,10.0,11.0,9.0,10.0,8.0,13.0,16.0,AFADADEDEFHCHCFGBGEHDFGHCHEGBGHFABHEACHBHBHBHGDGBAAAHAHCHCGGGCGEDEBCDDGBGAECEFFFBCHCHDE,False +876,10.0,18.0,8.0,11.0,7.0,15.0,11.0,9.0,FCHDHBFBGCDHAGCCHDHAGFFHBHEFAFAFDBBBDBDEACGGGBGFECECACHDBABFBDBDGEADADFFFGEGEBBBFBFBGBFAH,False +877,4.0,5.0,14.0,13.0,6.0,8.0,11.0,11.0,ACACGHADGCECGGGDCCCFCFBFDFDHDHDADHDHFFBHGHCHCGCDCDHDEEBGFDEHBHGEEBDFCCGG,True +878,22.0,17.0,15.0,16.0,16.0,19.0,13.0,15.0,CCFCHHDBEGEGDCFHFBAGFEDDFDCECEGBCBABADADBGGDBACAFAEABHHHFHCHDBFBDBDBEHHCHCHEEGFGFHAEAEAEADFEAABCFCEAHFGAAADFDFBFBEGCGCDAFAFAEDGBHBGFA,False +879,11.0,12.0,5.0,10.0,10.0,9.0,11.0,9.0,BCBCEAFGFGHBHBHDDFEFGBGHGFBDCAAGEHDBDGHGHFADAEEFEDEDEAHABABACAGHEDFAGEDBGBCBF,False +880,22.0,23.0,20.0,22.0,17.0,22.0,27.0,22.0,AFEFEHDHDHDBFBGBGEGBGFGFGEHEABABGGGABAHDHEBCGCGCFCDBDFEEAAAFDCBFHGHBCGAEDFDFDBCECFBAGAGAFEHGGCGDBBCCGBDDCDBDCFCAHDBAFFHCHDHFHCEEDHDHBHCCBFBAEAEAFGDCDHAHFHEHADAGAGAFBGCGHGFBEGG,False +881,26.0,17.0,21.0,13.0,20.0,12.0,23.0,19.0,BAEAGCGHGAEADABEEEGAAHHDDBDFGAGACCHHEHEBFBHEEEDFGFEAGHCCACGEFEDCGCHCGFHHBHBGBCCCDCGBGBABABFDDHEAEFEGGGGEHAHACACDGBGBGBEAFACEHFAAAHGHGDCCECFCBCBHDAAAFAD,False +882,1.0,1.0,3.0,2.0,1.0,1.0,0.0,5.0,DHHFADEBCHCHCH,True +883,7.0,3.0,8.0,7.0,4.0,4.0,4.0,4.0,GDEDCFHFHDHDEGEACDCABBGFACACGCFCDADBCAEAH,False +884,21.0,12.0,14.0,11.0,9.0,9.0,15.0,13.0,EHEAEGDDAGGBGFFAGHDHDCDCDCFCGGGGGAAEGCHEDEAEFHFAFGCBHBCCCCADBBAGAGHBCACAHAHBFEDBGBCBEDDHHABAFAHAHFBCAAAA,False +885,16.0,26.0,24.0,20.0,25.0,24.0,19.0,20.0,DFDGGAEAEAEDHGHGCCABBEECFCFGBGBDCGFFDBDECEADADHGHFDBDCEEBCGCGAFBFBCHDFDFEFEFHFHFHBHFEFHCHCBAFDFBFCAGAECBBBBEAEBGCECFHEHDCCEGBGBGFGFHHEHCHBDACECABABDBHAEDDCGGBBEFDFDCBAEHEHECG,False +886,13.0,28.0,17.0,8.0,23.0,25.0,17.0,16.0,GFFBFBHCFBBBCGCGEEBCBABFDEBGBGCACEHFHFHBADDCGEGEBHAAACFCEHBHBDAEFFFFDFDFEFEFECEBBBHFGBBHBEGCBEAEDCHEEEFBGHGECEHFHBABFCFCFCGCEAGDGAGAFBGGAFHHHBEBEBF,False +887,12.0,16.0,10.0,18.0,15.0,11.0,14.0,8.0,EEHEFGDCAFDGDCBFBFGFBEAFBBBAGFGBGCHCHCAGADCFCDBDEHEAEDGDBHBFGEBEBDBDADCDHDEABDDEDFCAGDGAGAFDEAGCGBEBEHEH,False +888,18.0,13.0,17.0,15.0,11.0,10.0,18.0,15.0,DEGEDEFAHAHAHGHGHGCGCFDDDADFCBGDGDCBABCBEACAGAGCEDBABDHFGAGAGDEEHAFCDCBCACBEBHCGBFAHAHCDFHBGBGHFHGHFBACEGEGCHAECFCDAD,False +889,22.0,5.0,11.0,9.0,14.0,19.0,10.0,13.0,HEHFADEFGFCEHEFDFHFAFGGGGAGAFADGDFAEAHBCECEDFCFHFCFDFDAACACABBFGCHEAAABCDHEAEABFHFHEGEFHAAAAACAGDHCHEFE,False +890,27.0,36.0,17.0,27.0,26.0,14.0,25.0,25.0,FHDGFABEECADAEBECEABAGHECDCDADGDADADEHEHGHBFBCBGDEEEEEBABABHBHAGCEDEDEHAHAGGCDCDHBABHBCACAGFCFGHHFDFDGBGHGAGCGFFBHADFCECEHBDBGBABACAHEBBHGHEHBBEDEFEBGBDBCGEDBBBBBEBDHDBAHGFGAEBHAADGHGDABFCFDAGBGDHD,False +891,18.0,15.0,22.0,14.0,25.0,27.0,18.0,19.0,FHFHEHAHCFEDCDHFFFHCCCCCCFAFGEAHAFGGEGEGEGFGFAEHDCDFHGAGEBHFHCHBHBEDHDCFCACGBFCDDEHBCEGAFABEBFDEGAFDCACFEFEDEAAGAGAGCBCDFEHAHEHBCBCBFBEEFEHGGGCEFEFEBEAFFBDADB,False +892,15.0,15.0,17.0,14.0,25.0,21.0,15.0,21.0,EGAHHHDHDFEAEDEGGGGAGFHFAFEEEHHBCBGHGBGDFAAEAECEFEDDBFCFCAGFFHFHFHBCFCDHFHCHADBHFGFGBEBHHEEDDCDGBCEEEBGBHEHEDEAFCBCECEBGAAAEDCDCACABEHHCFEFCFBF,False +893,5.0,2.0,1.0,1.0,3.0,2.0,5.0,2.0,BHAHAEEEGFGFACGBDAGAG,True +894,1.0,2.0,2.0,3.0,4.0,6.0,4.0,3.0,FCFCHHEFEFGGGGHDBEBFAFDDE,True +895,12.0,25.0,10.0,17.0,18.0,19.0,18.0,17.0,CECBHFGFGEBBHFEFDBDBABDGAGAEABCBGAGAHCEEHEHEHDDCDBFHFHEDFCFBFBFAGGGGGFGEHBBBHDHBHDEBEFGDCBBBDBGCAHHEGBGBCDFDEEEDEACAFFGBBHFHFDFAFHGBADED,False +896,16.0,8.0,11.0,13.0,10.0,11.0,7.0,7.0,GEDEHEHBBDADFDADCDCAAAHFHFGFECACAEDCDGAEAEBBCBGEACAHDBDEGFHFBCDCFAADACBCHFAFAFEGGDF,False +897,11.0,6.0,9.0,7.0,10.0,14.0,15.0,10.0,HDBFBGCFCGCGBGDEDGHAHGHAAFHFCGBGCAHHGFCFAFEBGHGBDCHCHDEEFEFEAEAEFEFGDGFAFACGEFDAGA,False +898,17.0,13.0,21.0,30.0,28.0,20.0,12.0,19.0,EDDBGCECEDBCBCDHGFECBGBEHHHEHFHDGDHHAFAHCHDBEFDADCDHEEEHEGDGDGFEDCACEDEAEAEFDFDFDADCCACFEFCFEFCBBHCCFEEDHDFGEGAFCFCACABABCGDEDAHEDDDDGDGFHDHDABFCFDFAHEEBEBEHEAA,False +899,3.0,3.0,2.0,3.0,3.0,3.0,8.0,3.0,BCEFGHGHGAGBGBGDFDCHEGEFAADG,False +900,16.0,24.0,17.0,15.0,11.0,13.0,13.0,18.0,DDCDADAECDHHHCHADDHCHCBCADAECGHGEAHFHGBBHDADAEHHFHGACACFCFBEBEDCGCGBBBBGEFFHFBBGCGBABABAHFEFBBECCHGFDFBFAFAHBBEBEACDGDGCBHBGBDB,False +901,25.0,30.0,29.0,16.0,34.0,19.0,24.0,19.0,FFGCECEBBBCDCBFEEEECGCABAFEFGHBDAACECGHDFCHBFBGGGBGHCHCBCECBGBEFDHBHBHCHAHAGABABGEGFCFBEGEBBCBCDHHHCHCHDBDCFCAEDHGAGEBEGEBEDEFFDBDEFBCEFEAGGFGEGFBFHHACACAEAEAEBEHEBAGAEAECGABADDDAECECFAAEDDAGCECBG,False +902,24.0,23.0,19.0,24.0,26.0,27.0,19.0,14.0,FAAAEACAEEEGEDAHEBADAGGHEDCABGFFDFDFEBEBEDEDGAHFDGBCBFDFGECFBFGFBFEFCFEDADBEFEFACACACAHADBBBEHAHBGBFAGBEEGGFGCGCFAFDFEBHGCAAGDGFHFCFCHCDCBFBGBCBEHFHCHCBEDGDACAEBDBHFHEDDDDDEAED,False +903,29.0,29.0,25.0,18.0,19.0,26.0,26.0,24.0,GABBEDADAGFHBHFHGCBCBDADGBGDGHEDBGBGDAEBEAGFGACEBEDADFFFBBBCFCGAFAHEHEHGBAAAAAAGGCCHBGBABHEEFHFHAHFBGCHDHFEBEGEAEDFGCHBHACADBHGDGCEDFFHFEFBCBABAHAEAGGFFCFAHADGDGCBCBCGCGCBCBCFHEHDFFEFHFCFABCHCDCAC,False +904,6.0,3.0,10.0,6.0,5.0,4.0,4.0,1.0,ACGCFCACDCHCDDDEDCGGEFBCBCBFGFEEAEDCAAA,True +905,3.0,18.0,9.0,11.0,14.0,16.0,4.0,13.0,DCFBBCBEBDBFFEFDCGHBHGDCFBFDEHEFBHBFEFHFHFGCAEHFAFBEHEHEHCACHGFDCBEFEHEBDBDBHBDEDEDBCBFB,True +906,16.0,25.0,37.0,22.0,24.0,10.0,28.0,28.0,DFDCDCEAEHCHEACBHBGBHCCGCECADDDDDDCHHHAHCCCGDECECEBECHCFCFBHBACGCBABCBHGEBBBHGHGBCBCDEEAAGAGDHFCCEDEDGDGDGBGHHDFFGEEBFAGHGFCBBGEHHBCBDBABCEAGACACGBEHEHCFDHAHEGGGHGHGACEDECHCGCGCDHFHBEGEDBCGC,False +907,25.0,18.0,28.0,21.0,19.0,32.0,30.0,20.0,GCGCEBHGCGCEDDHHGCCCCGHGHDHEHACGGGBGFGBEACGHGCFDFDCCCHCFDFAFAEAGABACAGACEBHBFGFBFBDHCFAFGFACAGDEHCDBGHAHBBDFDFCFAEBDCGFAHGHGFGFGBADFEFHBDADABBEAFHDDFDFGBGDEDEFAFEFEFGFAFDFEFCACHFHBEEECGCGCAAEAC,False +908,28.0,27.0,16.0,15.0,23.0,29.0,25.0,24.0,FAFEFGFBABHFFBHDCCGAABEBCACAEFFCFAGAEEGEGFGFDFHFHBAGFGBGDHBHBHBCGEGFAAHAHAHAEGEBEAHABCBDFGFGEGBFBHBDBFBFGFGHGHBEBEBDGHGFAFCHADEEECECFBACCBCDDHGGEHEGCAAFAFBDHHHDHDFDADGFAAEAFABEECGHHDBEACB,False +909,22.0,23.0,20.0,21.0,31.0,23.0,29.0,28.0,EAGGGDCHHHHCDDEDBCHAEDGBGAGADBHAFFHGBGBDEGEGHGAGDBEGAGCCHFHFGEGHHEAEBDDDDADHCBBBCACFCGAGECEAEFEGEDDAAEFEHBHBGBFCFCHGBBDBFBFDEAEAEFCDDEGFGFCECAGHGFGFEHHDAFHFHGHGHFHFEEEHAFBBBEAECGCBCBCEEAHACBFDFEHEH,False +910,35.0,20.0,17.0,22.0,15.0,17.0,23.0,20.0,BABABADGDFFFFFADHEEAEHCBGBGDGEGCACHEFAAHAHAHBHGHBABCBCGCFDFAFCFCEAEHEDGFGBAAADBGADADBDBECGGFCBDBHCAADAHAGADCGFGFGCGCEDAAEAHDEDBAGFGBADDDCDHHHCHAHDEAHGFAEAFBDHAGAEHBBGCGA,False +911,20.0,22.0,16.0,16.0,19.0,34.0,24.0,21.0,HHBBFFAHAHEFAFCDBDBDGCEEBFBDCCBCHDFAFDBDBFCFAHGEDBGFFFDFHACEDGDBFBFCECHCHBFAFADAFFFFFFFGFBHGHGHGHAFABACHCFGGGAFHFHGGGGFAFEEGHGEEEGECDGECBCBHDGDGHEHDBAGEBEAEABABFEGACHEBGFAF,False +912,14.0,22.0,22.0,16.0,10.0,16.0,13.0,11.0,GABHDHAHACDCBFFFECHFHEBEGABCEHEBBFBACHCHCACABEFFDBACDHFADAFBFBGGCGCGCHFBFCGDFAFGBCBCBDHDGDCBCBCGDGCGAGABCBCACEDFDEEFBBDDDEDB,False +913,20.0,27.0,29.0,23.0,22.0,31.0,29.0,18.0,GFGEECFDFAGEFHFACDEGCGCGHGHDHDCGCFDBAGAGAGDGHFDFBFGFGAGHDAGAFABDCFFECECEFFDCDCBCGDBABFFHFDDDGACHHDBEBEBFCEEBEHAHECBABGGAGDHDCEEGFCFBDECACAFHFAFACBEAGGGBGBCBHFCFCFCFCHDFAEBBBHBEBECFCHEEGBGBFCDBDBDBHGC,False +914,12.0,9.0,6.0,2.0,6.0,6.0,2.0,13.0,BFBHEHEHBADCHBAGFHFEBHAAACABHBHAAACECBBACGCHFHAHAHEHEFFD,True +915,10.0,12.0,24.0,13.0,16.0,14.0,13.0,16.0,CEBDBDBDCDCDCDBDAHHBFBFCFGFGEDFHCBCFGECFCEBEBHBCCFCFDFEHAFBHAHAHFCACHCECEHACBCHCFEDEAGACDCHCGAHCDEGGHEEFHAGGGECEGEHDGG,False +916,4.0,4.0,9.0,4.0,6.0,12.0,3.0,4.0,CECDADFBACFCFDFBFGFCFGHCCGBEHEHEHEFFCACBEFFFAD,True +917,15.0,18.0,12.0,11.0,16.0,11.0,18.0,15.0,AEAEAEAEAHAHAGEEFHGHBHBEDABABADHGFGDHBCDDFHGBEFFFAFGGHBDFCBEHECECGFHBHEEGDBEGEBBGDCDHDCACGFGHGCABABHFACCCCBGBGBGDGBE,False +918,14.0,16.0,12.0,30.0,16.0,18.0,12.0,16.0,DHDAEBFADADADADADGDFAFHFHDEFGBGBGBGFHCGEHECEAACACGCDDDFEBEBHBFAFHCDDDDFCFDFGHCFDHEFEFDCHBBBHAEDEDBAAHCEFDCDBDFDBEEDBDHEBDHDGFHDHEGGGCB,False +919,5.0,11.0,3.0,9.0,10.0,8.0,8.0,5.0,BFBHEEEBCBHEHGAGAGDDBDEEEHABFCFBAGDCDGDBDGAFEFEFDBDGGFBFBHE,False +920,5.0,0.0,5.0,4.0,1.0,1.0,4.0,2.0,CGAAFADHDCACGCECGDGDHA,True +921,24.0,17.0,18.0,26.0,23.0,31.0,24.0,25.0,EDEDCDADFGBABAGGFCFDFEGCGBHHECEADGDEDFDFDBEGEFCAGFEFEFDHEADHCHAHFHFHEGEDDDDBGEGEFBCDCEAAHDBAGHDHFGGHEHAHAHAHFHFDFBGBHCGAGFEFEFADACAFEBGCCDBEBADAFBGCFAFCHCHAFEFGCGBGCAFABCDAFBFBHDHFHEGDGHFH,False +922,12.0,3.0,17.0,8.0,6.0,8.0,19.0,16.0,GDFCHCHAADGBHCHAFEHCHCBGBCHFACAFADGGGGGGCGCAADHEHECEAEDDCCEGFGFGAGAHHGHGCDADCCHHGCGFHFHGC,True +923,13.0,7.0,15.0,17.0,15.0,11.0,14.0,5.0,GDDDHCCBCDADAEABADADGHFDCCACAEAGGDEEEDFHFBDGCHBFBFDGGBCDDDFCFCFEEGCFEFADADACAGGGGEGCCAEBEHEGEFECE,False +924,19.0,22.0,14.0,20.0,28.0,12.0,19.0,18.0,CGCDHBFBHGEBEADBDGDGDCBCDCHCEBHGEGEHEGDFFCEAEDGCGEGFDEEEEEBABCBCBCBCBGFDFAEAFDHDHEHFDAAHHHHEAEADAFEFEDBABDHEFEAGCBBFHDHBHBGBADHEEDBDEGBAEAGGCGHBEGGAAAEA,False +925,20.0,23.0,18.0,19.0,19.0,27.0,21.0,22.0,FEHEHEGDGCBDBHBEBCAGACHFEFHAHADAFGBGFFEGECEHDGDAHAHEDCCEAGFDFEGCCBGBFBFHDADCBCBFBCCHBHAHBDCECDFHFGFADCFFFFBFADBGGHADFDBBCBGHHHEHEHBAEAEFGBHBHGAGEFEFGFGFDCDFBFACAGAEADGDB,False +926,8.0,4.0,5.0,5.0,6.0,5.0,4.0,8.0,FGFDECECEADFBFBHEHAHADAHAEACGDADHHHBHFACBEGCG,False +927,4.0,9.0,2.0,4.0,9.0,4.0,11.0,2.0,GHGBGDGBGBEAGFGBBBBDDEBGFGEGEDECEAEAGBFCEHFAE,True +928,19.0,13.0,20.0,26.0,25.0,21.0,11.0,20.0,DDDFAGCFCHADFCCECECFBEHDBEBEDEHEHCFAEAEAEFDFBFADAEAEAEADHDFDFGBGBADEDBHCGCFCBEEAEHECFHAGACCCDDEDHHHHAHDDDACGHBACFCFGDEFEBHFHFCDDDHDACECBDHGHEEFGBGFGFEDHFBA,False +929,31.0,26.0,25.0,22.0,30.0,19.0,16.0,16.0,GADBEEEAEAHACCCCFGFEHBGBGCFCFDDADGBAAAFEFAABEHADFDFACAHBHGEFBAAACFCGABEGFABGFGEGFBFBEBFDEDEHGFEECHAHADADADCHEHEBEDABHBEACADBDBDGDGDCDCACHEHGCEHDCEABCFAEDFDGCEBFBAAEHEDEBCBCBCBCBEEAEBCHC,False +930,5.0,6.0,16.0,9.0,2.0,8.0,6.0,8.0,FCFCBBGDGDBABHCHCGEBEDDGACFCFCFCHCGCABHCCCCHFHCAGFHHCAFDDDDD,True +931,13.0,10.0,13.0,5.0,17.0,8.0,8.0,11.0,AEAEAHAEECBHBHGHAEBFCEEAEBEGCHBFBGEGFACADAEGEDBFCCHHBHBHFHCGEGHDDCDCACAEAFBCGCFEFECEA,False +932,13.0,15.0,7.0,16.0,20.0,10.0,5.0,18.0,AEABBCHEBEHEFEDEAFBHBADFHHDBDEHBABABABACDCFEFHFEGGACEDEHEBBAFGHCEDEDBGCHHDBDBEHCHDADGDEDEDHFEEEAHAHFHFHD,False +933,4.0,6.0,3.0,4.0,2.0,6.0,4.0,5.0,AGAGAHBEEDCGBGBCBDFDFDHHAFBFHFCBHF,False +934,5.0,12.0,3.0,2.0,5.0,4.0,9.0,11.0,CEDBABACFFGFAEAGCGBGHGHBHGHEBBHBHGDFHHHHBEBEAGBBBGH,True +935,8.0,6.0,1.0,11.0,7.0,1.0,14.0,7.0,GEBHGHGDBAEEDAGGEGDGBGBHHHHDDAAAAGDGDGDADABCEGEHEDDFGGB,True +936,12.0,13.0,17.0,16.0,15.0,22.0,16.0,19.0,HHEDDDDGDGAFACACHCFEEECACADBGHGFFFFFFEHEHCAGBDFEFDFEFEHEFFBBABFCHEGFGDHBCBCBEEAHCCECDDBFBHCHFHFHDEDGGGDGBGHCBGAFDGDGCAHBCCHGHFHFAA,False +937,3.0,4.0,1.0,4.0,2.0,0.0,0.0,2.0,ADDEDEHBHBACADBB,True +938,5.0,10.0,7.0,7.0,2.0,7.0,13.0,13.0,FCGGGHHAFEFBFBGBABAEGGGGCFCFHBABHHDHDHFHACDBBGHGDGDHCBDHCHGBGDHC,True +939,0.0,2.0,2.0,0.0,2.0,1.0,2.0,1.0,CGEGEBFBHC,True +940,15.0,12.0,17.0,12.0,18.0,16.0,21.0,10.0,DADACBCEGEGCCAHFCDCDAEACDCFGDAEBEBEACABEGGGABACDFDCGGFDDHCGFGEGBCBDEDGHGFEFBFGGCBCEEFAFGFHFAFHGHGCEFEBHBHGEGEGEFAFAHACBHE,False +941,21.0,9.0,18.0,19.0,23.0,21.0,20.0,26.0,EGEDHBHBHGHGHCEAAGBHBDDDGGGDGFGFEFGFGADHEFEAEAFAHAEAHBFECDCAAGDFAFHEHCCDCEFHFHFAEAHACFCFCHCECEHDDGDHDHDADEBHFEGAAEAFBHCCEGGDEDBCHADAHFBFCFCGGEDECFHGAGHECEHFH,False +942,23.0,23.0,25.0,23.0,16.0,18.0,18.0,24.0,CAHDBDHDEGCADHGHGHGHFCDCHCDFGEDEDHDHBHFDFEEADAEABFFGFGACFBBCFCBBFAHCHCEEDCCFHACACABHBFFFDFECACHHEGDGDEDBHBCBHBHADABHBHBCGHACBCBEBABCGEEFEAEAGGCDDDDAGAGAHBHDGBCFGFDCAGACAB,False +943,9.0,5.0,6.0,3.0,2.0,3.0,4.0,6.0,DBDHCFFHCEAEGBGBGAHCHBBAGFCAHAHACADACA,True +944,1.0,5.0,5.0,2.0,2.0,3.0,5.0,5.0,EGGDGHCBBAEGHGCFCFBHBHBHCFCD,True +945,23.0,12.0,17.0,23.0,21.0,25.0,31.0,23.0,AHAHBHBHCHCEDDFCACDCDFGFBHBCCGFGHGAAHDEEGECFAHAHFHDHEADFGCGCGFGEADBEAEBEDDBCBHAAFAFAFDGDHABAEHDHGEEEHDADGFGHGFEFGFCFAFHFEFADGGEGEGECFDHCHDFGHGDGCAAGAGEGFDBGCEBGBGDEDHFFCFGAGDG,False +946,7.0,6.0,9.0,5.0,3.0,13.0,9.0,7.0,BEBECFHFHAHGCAABCCFGBGFFCFGFBFDFGGAGHGFFFFDBCGHHCHCDDADAEAC,False +947,12.0,14.0,22.0,9.0,8.0,15.0,19.0,16.0,GGGGGADFDBBBCHGACAHBFGHGHGFGCCFDACHGHEFFBCBGEGDGFHHHBHDGDCCCCGBFHACACECDCFGBHBHBCEFECHCBCBCHGFGDAAAADAEEFCFCACFFEHB,False +948,23.0,29.0,24.0,18.0,9.0,25.0,25.0,32.0,BBBHGFAEAEBEBCFCFAFAFCFDFBHBGCHFAEGDACAGBHCHFDBCBGGCCBBHHABDCFGHBDCDBDGFBCAFAHHGHFHEHACEGDABGBGHABABGHHHFBFCFHFABAEAGACBCFHHBABCBCBCACFCHGHCHBGBHDDFGAAFFFEDDDGDHDHGHGHGHDHGHGHDCDCGFGFEA,False +949,7.0,6.0,5.0,7.0,7.0,6.0,6.0,12.0,HHCHADDCGBGFFHDHBBCHCHBFADAEAGAFAEAHBHEEEEHHHBGDGEGCDFDF,False +950,24.0,23.0,22.0,11.0,20.0,30.0,30.0,14.0,EHFBFBFBCCFCAAACEGBFAEEBHCHFHEAEAGBGHGHGCGCFEFAFBEAGAEBGDGCGHGHBBGBGBFBFDFECAGGFEBEGCAEBEDGHAFBHBFBDGDGFGDACCGCECACAGFCECHDFBCGCGFFFGFGCBCGABADFBHGGFGDHDEFBHCAAAAAAFFFFFDEEAE,False +951,16.0,19.0,15.0,15.0,20.0,28.0,15.0,17.0,DGGFECEHGHFHCBCEHGDGCBCGCEEFAFAFAHEHFAABHEGDGAGBGEEBHDHBBCBCHFBDBDBHEDFCAEAFFFDFDFAGBCBDECFFFEFDFBFGFGEECECEFEFEDHGCDAHAEABBDGFBFHHBHDAFHFCFAFABA,False +952,9.0,0.0,6.0,3.0,8.0,5.0,2.0,3.0,EFACCCFAAAAHFFFDGAAEAEHGHECECEDECEAD,True +953,2.0,1.0,1.0,1.0,6.0,2.0,3.0,1.0,ECEHDAAGBGEEEEFGF,True +954,11.0,9.0,7.0,13.0,13.0,4.0,8.0,8.0,CADHDHDFDABBEACAFDBBHFHGAGECBGEGEGEBEHEDEAHBGDADADADFDEBEDDCAABHEHCGEGECC,False +955,17.0,19.0,17.0,18.0,12.0,19.0,16.0,32.0,GFGFAAGFGAHADGGHGEBABFEDBHBDFHHHHBGBHDHDEAACBFBFBEAEHCDDGDFHHEDGHGBGBGADHFHDHCCGAEACDCDCAHAHFHFHFHDBDADHCCCHBACACBHFHFEFECACGEBBFDHCHDHBHEFGCECHFFBHBH,False +956,21.0,23.0,17.0,24.0,20.0,16.0,15.0,22.0,DADEHFHDCBCBCAHGBGFDFDGBAFDFDHHFDBDBACACFEHEAEAHAEEBAGCHCFCFAHAGDGDADADHHGHGECCFCFGFCHAHGDGBCCHADBDEAHGCFBHBHBHEEEEEHEBEAEGDBBFBHHCDCEBBBDBDBAADGFABADFEEGEDDB,False +957,10.0,10.0,8.0,10.0,12.0,10.0,10.0,2.0,FGFBFDFCGGFGABBBDGAAAFHFDGDBDGDEDECECECECGBAEHECGDACEBGBDFCAEAFFEDEBABAE,False +958,23.0,37.0,29.0,27.0,20.0,20.0,23.0,19.0,ADBDBAFABHBADGGCCCHFHGBBDDCACACBBAGDHDHCHFECBHFEGEBEDCCFEDEFBFBCBCBHEHBGDCDGBGAGAFFGCGEGAADACADBGFEDGBGFDBHBCAHEEFFDCDADBDBACDCDCDBHBHFEFHFDBGBGEFHFHBACECEDEBCBCBCGCGBBACAGEFBFBABGDGDHEHEGBCDCBHEAAA,False +959,12.0,18.0,18.0,8.0,12.0,10.0,17.0,15.0,BEBEBGBGBHBCBCECGCGCDCFGGHGBCHEACCCEFGAAAEHBHEHBGBHAEABHGFCFCDCEABACAHEHCGCHFEAEGDBDHDCGFDCDAHBHGFDFGGGHFBBBAF,False +960,6.0,8.0,14.0,11.0,10.0,8.0,6.0,15.0,EADADHGFDEEHFHDHBHBHCECDFDBDECHFFAFGFBEDECBCECHHHHGCGDGDHCCCCCCEEDHHAHABCGFABB,False +961,20.0,29.0,25.0,20.0,25.0,26.0,26.0,18.0,BHBEFEABGFAEGDGDFFBDHDGBGBFFFHEEEEEDFAFADABGGCGCBCBAFCFABCCHEHGDDEDEGFFAAEEEEAGCGAGHGFDCCBCHGACACEDHGHGAFBFBFAHEBEBEDGBHCCEAEADDDHDCBCFHAHCHBHBFBFBGGGBHECGFGECBCBCDHDBBFDCACACBFGFGEGCDEBFBF,False +962,27.0,19.0,27.0,18.0,20.0,32.0,29.0,28.0,GEGECAFAHHHHEAEBDBDCHHGHFEFHDBFAFBFDGDBCBCGHGHFCFCFCFDEGADHHCCADADAGEHEHGACCHGHBHEHCHCHFECGCFAFBFAFGFBCAEFCDHAGFBFHGEGAAHGFGEDEACDCFHDDCDCFCHCGCEDGHBDAAFAGBFBFHEGAFACADEFEBEGGGCGCBBFBFGAGAGAFABAGFBEHF,False +963,18.0,20.0,27.0,19.0,14.0,17.0,15.0,25.0,FFACCGCGCDDHCHCDGGGEHFBCBHFCAAAAHAGFGDGAGDGHFBDEDHCBCACACGCGAFEBBCECEAEHEHBBCHHHHAACDCDBDFCFBFBHCHBHDGCEEEHEDGBBBFEFHFHDCDBDADAHFBCBABDCEAHHDACFCGHBHFHDCFE,False +964,12.0,10.0,8.0,9.0,12.0,10.0,10.0,9.0,FGFAEAEAGADFEECEHBBBAHAEBECECAGGHBAAGEHFHDHAEFDFECDCBFBFBABDDFDGGFGCCCEHAHBHGDGD,False +965,17.0,22.0,24.0,31.0,26.0,22.0,22.0,27.0,CGCEHFCFCEBDBDBEHEHGHGHFABABHEHFBEBGHDHDFCBDBEBGGCHCFDFHEHDHDGDFFBCAHAHGEEFHBHBEBADFFAFAHDHGAGAHEDDHDEBEFEBEFHFHACADDDFDEEEECCCDAGADBGAGFEHBGGHDCCCDEDGHCECDDABFBEBCGEGCGCFCDCAAEDCBGHGDFDGDCDF,False +966,27.0,18.0,26.0,14.0,26.0,27.0,37.0,24.0,AACDCHCFGHAHAGAGACFHEHABFHFAGHBCBDBFBFBABFHHHFHFCEDEFACHCECFGFEFECGDGHGCGFGEHECDCBCBGBECEDFAEECAGGFAFBHEFDGBGEGHFEEGEHCGEGDGDGDFCCCCHBAEACHGHGAGHGAGEHEGEGBCAGGGFABHDADADAGAFHBEDCFAEECFGFGFGCGABEFGABA,False +967,19.0,30.0,23.0,20.0,26.0,19.0,25.0,21.0,BBABCBGGAGFDFGHDHEGBGCGBBAFDCBCEFHDCDFBCBGEFBHBEEEEEBADAHAHBGGGEDBFBHCCCECBGHDHDFGBDCDFBEHECGBGBGFCFAHEHDGEGEFDFDECCCHCHEGEGHGBCEAGABEBABABABADADABAEADCCEFBABFECDFHFHCHFEFCGGEHEHGDADH,False +968,22.0,15.0,29.0,26.0,37.0,20.0,22.0,24.0,AEGBABEFGGEGDHDHAHEFECEFACEEACHBECFBABCDCACAHGHDEEFECECDAAAEHGHGHDHDFGFHCADFDBDEDEAEDEDEDEDGGECEABBGFADADEHGHFECBCAEAEGECECAGDBEGAACCCCCCBHEGECDCDFHFHFHFHFCGEGHBDFEBBBGECHDEFEHHGDADCGHGDDCEFHFCFC,False +969,16.0,6.0,14.0,15.0,9.0,8.0,13.0,13.0,HHHHFEFDDCAHGGEGDGDCBBHCCDADGGHAAADADFDFDGDGDGABEBAFABECDHAAFAFEFGDGCHEHCDCGCEEHHHAEACCCCBCGAA,False +970,21.0,25.0,9.0,17.0,8.0,13.0,18.0,16.0,GBGHGACACAFHFBCADGGGFGFGAGAGBBDBGCHHEHEBFDEABGDGDGBHBCDFFFFHFHAHBDACAHDHCCGAEADBHBDFABABABEBEAECGGBHBHDFBBBBAFDDAGBHHABDDADADBE,False +971,9.0,10.0,11.0,9.0,15.0,9.0,14.0,12.0,EAEDFCFBFBAGHGHGDGBHBGFHEHCFAFAGHECGCHCADAHCEGDGCGBBBBDBDEGFGCCFHEEEHEDEAEDBCGHGCADHEFEAE,False +972,18.0,16.0,12.0,13.0,15.0,19.0,12.0,21.0,BEHFBBABAHGEEAEAFAFCDEHFHAHCGCFBEAAFGCABHHFHFHCHBGADCDHDHCHCEEAGBFDFGADFFFFBFBGDGAGAEADHDHDAEEEBCBCBHBDEEHGFGFBFBDEHCHGHAHFCAD,False +973,27.0,25.0,26.0,28.0,24.0,17.0,20.0,27.0,HCHEFEACGCFDFGCBCHADFCFBADCGHBHCDDDCBAAHAEEDADGDGHGHGHGDAAEBEHAHGDADADEBEHHCEBADAHHHHCHCAAAHBFBDCGBFCHEEFBFBFHAEADDBFBFBDGDEHEHBHGCGAHACECAFBFBEEEBECEFDCCABDBDEDEGAGADEDEDCFBBACHGGFGBGCGDADCHCBC,False +974,2.0,9.0,5.0,14.0,10.0,16.0,13.0,8.0,HBEGFBDBDHEEFHFEGDBFBFBGHFAFDFGFCFDBDBDHDHBGGCFFEGEGECADGFECEHFGDCDHDEDGFGFGD,True +975,7.0,10.0,11.0,8.0,6.0,8.0,11.0,11.0,CECFCDCHGGGGHGAFCECEAECDCGHHBADHDHDBDBFBFDAHGBBBBBBGCFFFAAEHDFCHGAGHCHGE,False +976,22.0,16.0,20.0,24.0,18.0,27.0,21.0,14.0,GDBDHEGEBFHFHDDCFCDAAGEFBFEDBAHGBGBGDFEBBADGHGFABAFAFDCDCBCAHADDDCAHECCDAAFAFGHCCECFGECECEFDHCHAHGBGBGDECECECEAEAEBFBFGHGHAADDFDBDGAFCFBHACAEEFGFAFDFDFGFGDCDGGFFF,False +977,16.0,17.0,23.0,22.0,27.0,15.0,19.0,22.0,EEGGFDFHCHEEAEDEHEHGCEFGBEBEBHBDDCBAHAHDGDAEGEGDHFECBDDDHDCGCFAAAAAFCEHBBEECEFDFDBDBCCCCEFEGAFFCFCFCEBEAHAHAHAGGHGHCHCBGEDBDGEEHCDGHBCBDAHFHBHFGGDHDEDAGECECBCDCG,False +978,5.0,8.0,11.0,18.0,14.0,13.0,11.0,18.0,HFHDBAGHGEFEHCGGEGDAAFHFEFEFDHDGCECHHEHEDEDHGHDFBFCDHHHAHEHBCBCBCDCDGDECEDGDEBFGDCDEBGHFBFDCDFHFDA,False +979,22.0,10.0,19.0,14.0,19.0,26.0,19.0,18.0,HBGDGHGCGBGEFEAEFBDEHEAAHGGGGHDHDHFGEABAFAHEHCACFFDFDFAFECGCDCDCDCFCHCFCHAHFDCBGAGDEHBGEAFAHAHEFAGHEAGACEEEFFFFEFHFBFCFBACGCAFAFCBEFEGEFCGBDDDCAAAH,False +980,9.0,10.0,16.0,13.0,13.0,13.0,17.0,6.0,CDCEBDGFGFACEBDHFCEHACADBDBHBCBGACCECEFEFGFGACHCACDEEGGGEGEGDGCFFFGFDBDFGGAGAHACDDDDGEGFCFCEHBBEB,False +981,19.0,23.0,15.0,12.0,16.0,18.0,17.0,17.0,ECEDHFHFHFAGAHBHDAEFGFBEHGBGBCBHBCEDGDCBHEAGADEGHFHDBBABEBAGAGCCDADHDCGBBBEGAGAGEBBBGFGFCCBFBFEGHAEGHFCFCFCACEDHDAAAAAHDBFFHFEFCBCBEBEFHA,False +982,21.0,16.0,13.0,14.0,20.0,12.0,19.0,12.0,EBEBGBGDGEGECHCHFAAEHBCAEBHBECECACGCDCDCDBABAFABGHGHAAEAHABDEDEFHFGBCDAEAGFGECDHGFGDDDEHAGGGEGBCFDFAFBEGECEHAFDFGABADAGAEBHFAEB,False +983,22.0,16.0,20.0,28.0,16.0,18.0,28.0,14.0,CGCGBDCDCGHACGFDFDGDBDCFEFEFADAECBDDDEAEAEAHAHABGDFAAGFGFGCAAGEDEGFDFDCGBGAGBGHHHGABCBDBDFDFCFDFGCAHAGACABAFEFAGEEDEHBCCHEGBBBDBDHGEDCHCEFAHHGCDHGGFGDGDGDBEGACDCD,False +984,26.0,22.0,19.0,22.0,24.0,27.0,32.0,24.0,ADHHEFAFADABADAFABCGCGAGFGFEDADABEFHFHGHDFGEGADCCFHHHGHGEFCFCEBDGEFEFEGAFBFBFAHGBEBEAGDFAHABAEGHGCECEHBHBDCFFHBAAGAEAGBCCDCDHDHDBDBGBEDDDCBBFBGEDFDHGEGEGEAFAGGBGBHEGBGFGDECHFAFEHHFCGCGEGCCHCHAAFDG,False +985,7.0,9.0,7.0,9.0,13.0,11.0,7.0,5.0,FCBCHEDFAFHEGBGFAEAEAEAFGDGDBDBABAFGEGDCHCHEEBFCEEHEBEDEFFDFGBDBCCFD,False +986,8.0,13.0,17.0,13.0,13.0,11.0,14.0,10.0,HGEDFDFDFDHDHDHDBFEFAGAEBEDGDHHFBBEEABBBFBHGHCCBCEEGECFBACDCDAAGCFCGBGFFEAGDGHCCDGEGCGCGCHCECBCACEB,False +987,20.0,12.0,18.0,25.0,18.0,18.0,21.0,30.0,AAADFHFAADFECBCECEHEHADCDGDGDCFHFHGCGCGFGFCFHDCAHEEGDGCECHCHEBFBHGHGEFHBHFGDADEDHDAFADEHBBBEGEFHADFDBCGDHHGHGHGDGDHDGDFCFEGGFGCAAEAEBHAHADBHEAADHDCECHDADHCHBHFHAB,False +988,20.0,13.0,12.0,16.0,10.0,14.0,25.0,12.0,BBBCHGHGAGFGHGDCACHCHCAAAAAAEHBDBAFDGDGDFCGGEBAFDEDEHEDGDEDADABCBFDGAGAGHGAEDBGGGGDGBFBHAAGBGHDFEFGAEECCGFFBFGFGHCHAFFCACD,False +989,12.0,14.0,12.0,10.0,10.0,5.0,11.0,8.0,AEFEBABAHACGFBABGBGDEDGDEBBCBCHCECBCACDCGHGHGEACFCBBBEFGDDDCDBDADGEHAACHEGAGFBEHAH,False +990,22.0,22.0,18.0,21.0,13.0,23.0,11.0,18.0,AHAHEFFDDCDFGHDFDECHDHABEBCBCEAFBGGGGFCHCBCHHBEDFAFABCHCBCBCBABDDGHHDBFGEEDADFECGBAECEADADADAFFDFBFBFBFAHDFDBHBDEAEFHFGAHAHAHACCBBABGCGCFHFAFDFDEBCA,False +991,10.0,6.0,7.0,9.0,6.0,4.0,5.0,5.0,FDCBCGFHFHBBBABGDFDAGACACEEECAHDDGDEAAADADAECECHDBGH,False +992,9.0,13.0,4.0,15.0,7.0,15.0,17.0,13.0,DEAHFHGHBEGEBBGFFFAFDFDHDGDGHGHFHFDDDCEGBACGDBDGDEHEHGHGBGBGHFBABABFFFAGADHDGGGHFACBFEDDBCAFB,False +993,1.0,1.0,4.0,3.0,4.0,6.0,1.0,3.0,EFEFEFAFCEGDFHHHDFCBCDC,True +994,16.0,14.0,21.0,15.0,11.0,19.0,16.0,24.0,AHACCCDCAAFBFEFBDBAAGAHHCHDHEHAHEHEBGAGAFHFCGCEFEFEDACHCHCGGGFDFCHCDDDHDHAECHGBGBEHCFBDBGGFHFGBAFHFCDADCFCBCBCEHAHFHBCEGGGFAHBHDCDFHFGDB,False +995,7.0,6.0,13.0,6.0,12.0,13.0,4.0,9.0,CEAFHCHFHECCHEACFCFGGAGFCHCHFAFEDHHCECFBDBDGECHDFEEEEEEBABACFCFDFDFBAB,True +996,4.0,9.0,13.0,8.0,5.0,3.0,3.0,5.0,AGAEADDCACBCBCDCDEHECCFHEDBCBCDDDFEBHBHCCCBBFHGCGB,True +997,3.0,1.0,1.0,6.0,4.0,5.0,7.0,3.0,DDDFHEHCGFGFGFGEDAGAEHFDEDBGAG,True +998,18.0,17.0,15.0,15.0,11.0,15.0,12.0,20.0,EBCFCHHAACHCHCHGBCBCBCHDADAFAFEFDFDGHGHCBCFFHCACDFAFAHAEAEAEFEBCHAFBHBFGAEDBDHDHFBCDEAGABBHGADDBDBDHHHEBAGCEEHFHBGGDGFGAGDB,False +999,6.0,13.0,8.0,13.0,6.0,19.0,12.0,12.0,GDGCGCHCAFGFEFBFDEDHFBFBDBGFDADBFBACGBGDGEFBHHHHBDAFGFGBGHCFFECEFEFBAHFDFBFDAHCHDHCHDFDGB,False diff --git a/tests/results/nb_gm_002_2back_240trials.csv b/tests/results/nb_gm_002_2back_240trials.csv new file mode 100644 index 0000000..1c50201 --- /dev/null +++ b/tests/results/nb_gm_002_2back_240trials.csv @@ -0,0 +1,1001 @@ +index,A,B,C,D,E,F,G,H,ralph_skewed +0,30.0,39.0,31.0,30.0,32.0,24.0,27.0,27.0,False +1,33.0,23.0,27.0,32.0,37.0,34.0,25.0,29.0,False +2,31.0,20.0,37.0,28.0,31.0,32.0,26.0,35.0,False +3,27.0,32.0,39.0,24.0,25.0,34.0,35.0,24.0,False +4,34.0,24.0,38.0,28.0,31.0,29.0,28.0,28.0,False +5,29.0,24.0,36.0,31.0,32.0,32.0,31.0,25.0,False +6,25.0,38.0,28.0,30.0,33.0,30.0,26.0,30.0,False +7,27.0,30.0,30.0,29.0,32.0,26.0,33.0,33.0,False +8,24.0,36.0,32.0,23.0,30.0,29.0,35.0,31.0,False +9,35.0,34.0,30.0,29.0,35.0,26.0,23.0,28.0,False +10,30.0,25.0,33.0,31.0,27.0,37.0,30.0,27.0,False +11,28.0,28.0,29.0,26.0,28.0,27.0,34.0,40.0,False +12,35.0,27.0,30.0,29.0,26.0,30.0,36.0,27.0,False +13,38.0,27.0,31.0,27.0,34.0,23.0,27.0,33.0,False +14,29.0,30.0,28.0,35.0,19.0,30.0,37.0,32.0,False 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+9,11.0,23.0,19.0,24.0,13.0,20.0,28.0,13.0,DFDDFDGFDGCDFFDFEDCCDEGDAHEEDGGGGDAGHFBHFGEDAFGCHGFDBCDBDEBCHDEBGEAFBCHEFEAFBHFCCGEDGADGBCBCDACGCCGFAGBBDCGDBBBEBBECHACFAGFBGABCBBGFHHFHHFGHGGDGGBGBCDB,False +10,10.0,15.0,13.0,9.0,5.0,13.0,10.0,23.0,CAHCFDCFBGFGCFHBHAGHABAAHGFBAFDFBDBHDHCBGEFGDCBDHDEABHHHHGCFCEFCDHCFHBHHGHHGFHGBBABCABCABHEHEFHDCH,False +11,29.0,21.0,32.0,27.0,25.0,25.0,8.0,18.0,HEFAEFGCBEBDCBEADAADADCADABDHHFFEDFBCHACAAFBAFDAFDBCCCFDCEACAACEABFDCFDCFHHFBHDEFDAFCABGAEFDCDCCBCCDCDFAEFDCGCCECCBCBHDEGACBAHBEBEEFDBDHAFHAEAEECEGGHDBHDHCDEADEAHEHFEBFCBAHBHDEGAEFFCFCG,False +12,28.0,27.0,32.0,14.0,15.0,33.0,26.0,13.0,FFFAAFBAHCHHDHGCBBCEBFDGEGBFAACBACBACBAGBGBAGFFGFAHDGHEEFCAAHAHHECFBBFACFACAACDBCAEAHDFHFFCFFEFCAFBEFBFCBCABDBGGFECFGCBCDGGBGFDGDABBCCBEFBEFBAFDACGCCEHGAFCABDGEDFFDCFDGFGGCGGEEGCBGAAGCCCHC,False +13,29.0,16.0,17.0,15.0,16.0,11.0,15.0,11.0,CBECBEFBDDCDCAACAABFAGFEGACCECBEHBEGADFADFBBABCAHCABAABHEEEACEHHAGHABACGDHGDFGCHGCAGDAFAAFCCFEAEBAEDFDDGEABHAGAAGDGBAEDHHGABFEGDCD,False +14,17.0,24.0,25.0,11.0,18.0,20.0,15.0,30.0,DDCDHHAABGECDACBCCFHGEDGAHBABBHFBFFBCFHCHECHECACABHHBHEBHBHDCHCFBAHBFHBEBEDCEDEABCHCHFCHCAFBFBBHGEHGEHGHFCHACHCGGCGCDECFEGHEDFBAFGEFDAAHAHHGFHFABGEBGABGFFEFCEBC,False +15,8.0,6.0,1.0,3.0,4.0,2.0,2.0,6.0,EHBEDEHGEGFABBADBAHCAHAABDAHHABF,True +16,20.0,17.0,20.0,17.0,21.0,21.0,26.0,21.0,DEHCHAEHFEDFDHFCHGCGGCGAFBDDBDCFGEFGEFCEFHDHEFFAGDGDEGAHGFECFACFEEHBEHBGHBGHBGCECEDAHHBGFCCCADHAGHDEDBADGHEBDCHCCFAGEAFAABGABAHBAHBGHCACBEFEGAEFCECBGFDGFDGAGBAGBFG,False +17,12.0,3.0,7.0,9.0,7.0,12.0,9.0,8.0,ADGAGCADCFDFHEFDGHCEHAGGCDAHDCHDAHAFDAFEGFACFECFEBFGBAGAFFAEBDEHGHF,False +18,18.0,19.0,24.0,16.0,21.0,13.0,23.0,20.0,GGEGFBDFGDGEDAHGFBGHAGCDGCAAAHACECDECEBBEDEEDECDFDHBCCDHBHHACBACFHEAEEGHEGDEGAHBAFBEEHCBHCBGGFCGECGECBCAFCGHCBHFHHFHDGGAAEBFCBFDBCBECDCADCACGBHGEHGBFGADHA,False +19,10.0,14.0,15.0,8.0,25.0,14.0,11.0,20.0,EEEEBEEFHEHEEFEEGHEAFFAFHACGDCDDCFDCBDCBFFBCEAHEAHGCGGHGCHEEAEAHEAHEHHCCFGHABHGFGCHGCFDFHEHBBBDFBFBCEAEBHCDGCEEEHBBHB,False +20,16.0,9.0,19.0,17.0,10.0,22.0,10.0,24.0,HFGDDAFEAFEDCGHAADEHDBHAHDCGBAHBECEFFFFFEFEEDHEDCACEGHBGCFGAGGABDHFCHFCHCCDCFHHADFCFFCFFCBFCDHHHHDFFGHHDACDAFDACDCBHCHHAGHABHAB,False +21,6.0,10.0,3.0,4.0,7.0,3.0,3.0,4.0,EABBAEFHEFABAACHDCDDEFBEGHEGBDABHBBCBGEB,True +22,6.0,11.0,12.0,6.0,9.0,6.0,9.0,10.0,AEDBCDECBCHBCBBGFBGFHGEHACHAGAEFBDAECHCFHFDCCECGBCGECGAHGBHBHEBHDFGDE,False +23,11.0,8.0,12.0,13.0,7.0,5.0,13.0,9.0,EAAGACDACDHEEGGGGGBEGEABEAHGCHCCAFCFFGDHGDGCBGBDDEAFAADCDDCDDHBCGBCAFCBDDHHBHH,False +24,36.0,26.0,18.0,26.0,33.0,19.0,21.0,15.0,GBCHFHAAHAFFGBBEFBCFAEFDFGEGEEBECBEBBABBAEBEEAEEABGDBADBACFFBEFCECGACFADABCFDCDBCBBHDHHACGGEHDEGDEGAHAAFAAEDCCHHDDGDDBDGBDBDDCDAGAAFHEDHGDACDACDBGEEACGAEEBEHAFHBGAAAAAAAEEFBEDCDAEEEFGEGGHGFEAFED,False +25,11.0,17.0,16.0,9.0,15.0,15.0,6.0,9.0,CEEFABDBGDBFDFFDGADECBFCBCCACFABEABFABEGBEHBAHEAHEAECCFFCHDCBBBFGBAGCDFHHFBDFDCCHHEHAEBEGCCBFEECEF,False +26,8.0,5.0,15.0,9.0,10.0,7.0,11.0,5.0,ECAGCHDBBDCCDCGHBBEEFDHFEEEHBHGADADGFDEFGAFGAFCCCCCACCDCDGGECGECGEAGFA,False +27,9.0,11.0,8.0,5.0,8.0,4.0,2.0,4.0,FCAFDBEDBABAABAEEAEHDBHCEHCDBCFBABEEGECGBDABFCCAHCB,True +28,6.0,8.0,11.0,7.0,10.0,5.0,9.0,9.0,CFBCBCCBACBEHBEGCADHDGFEGFHGHDAFBAFBEDCDGCHGAACHCHBCEEEEDHEDGEGGH,False +29,24.0,16.0,18.0,25.0,13.0,19.0,26.0,18.0,HEFHCDEGDHFBACGGDEHDGHDGFDEAHFDHGBHEBGEGADFFGCCGDHFBFABDACDABAGFGDAGDAGCAFFAGHHCDHCHACEDDAFDCCDCAECAEDGEDGAFGFCGFAGBBGFBDBBAABAAGADGAFCHBEEGHBGCBFCGFAHHCHDBDDE,False +30,6.0,5.0,2.0,9.0,2.0,4.0,3.0,8.0,DADBAFBDFHDHHBAHEADGFBHFGHEAHDHBDGDCADC,True +31,19.0,18.0,16.0,13.0,19.0,13.0,14.0,15.0,FCHGCAEHAEBDEBABAABHAFEBDCBDCBHCGEAGEFBAFCCECCBCFHEHGEGAEDAECBECEAFEBDHBDEAGFGHDGCDGADFAHGCFCBFDEHEGCEABFADHAFHGBHABHBHDAEBGDFG,False +32,7.0,12.0,12.0,10.0,7.0,5.0,5.0,9.0,EBDGBGBBDCBACGHBDAAHEBGCBFHBFGAFEHFCCCHDCHDCHDAHDCDDEBDEAFECBAHBECC,False +33,1.0,4.0,8.0,1.0,4.0,4.0,5.0,3.0,GAECEGFBHFGHBGCBFCECCECCBCHDGF,True +34,5.0,4.0,6.0,9.0,13.0,13.0,5.0,7.0,CHHEFFDFFDFFDFDGGDFGDHCEAEAHEAFEBFCFEEFEECAECHCHFDEBDBGEGABDEH,True +35,3.0,2.0,3.0,3.0,5.0,4.0,0.0,6.0,CBDEEHHEAHCAEBDFADFHFCHFEH,True +36,13.0,2.0,13.0,8.0,7.0,6.0,16.0,9.0,DEGDECDHGAHGEDGEGACAFCADGACGACHFDACHCCHCEECGHDHBEGGGGCADCAFAGFGGBAGCAHFHFA,True +37,18.0,19.0,17.0,17.0,13.0,17.0,15.0,23.0,HBCABCGHCEEADEDCEDGAGFFFHDFADHHBHHGCHFHHAGHEHEBBBDEFECFEBHCDAADFGDFHDCDCCDCCFACAACHGGBGGBFBCFBFFCFGEDABDBBDAAGAABACBEGBAHAHHFGEDGHDHHEBHBHF,False +38,4.0,6.0,5.0,9.0,6.0,4.0,4.0,6.0,AGDAGHABHCEEFBEFDEHDBHDECDFCDBHDEGBBGCCADFDH,False +39,3.0,5.0,6.0,8.0,8.0,2.0,8.0,6.0,DCEDEEGEEGAAFEHFGHDGDBHDBGBBGECECDGHBGCDDCHCAH,False +40,0.0,0.0,1.0,3.0,1.0,3.0,5.0,1.0,GDGGDCEHFGFDGF,True +41,20.0,19.0,22.0,21.0,30.0,22.0,10.0,26.0,BADBABGCFGFDDDADEFHAAHAAHEAHBBHECFGFDEHDCDBBBHGEDEECCDCCDGCHHBGHCHACFDCFCFEDFEDAHHHBHAECABDABAAEHFEADCFEBFAGFGEABECFEFFECEEFEHFEHEEHDHDCHBBHBDHCEHCDHBDCFAEFAGHEGECBCFEEFE,False +42,3.0,7.0,4.0,4.0,5.0,2.0,5.0,3.0,EBBEAEEHDCHDCGDGGBACBEHBDGBAFBFCG,False +43,21.0,15.0,21.0,27.0,18.0,33.0,14.0,23.0,DDDDDDBCGFEFFABFDHDAGCEFHHACHGBHGBEFEHFEHFCFFCHDGHDFHDAGFECCCAAEAAGHGDFCHFCHBBBFABDEFDFFBBDBAAFDAFAGHACHACEFFEFDHABCAFGDFEDCGACFADFDDFBHFAFFBEHBEHFCHEADEGHEGCDGHDHDEECCFCCD,False +44,27.0,34.0,20.0,19.0,15.0,29.0,27.0,26.0,FGCFGADGADGDDBDBAFGAFDHHHAFBAEEAGGBDBFCEFAHFAHFAECDCBBCGBHAFHABHDCHAHHGBCGECFDCEHCFBCHBGHCABFBCFBEHBECBAHBGDECHFDFBDEAFBBGECGEBBHDBHDBEABEBFCDFHHFGHFAFFGCACFGDGGHGAABCDBHBGGBGGFHGHGGBEADABFABAAFAFF,False +45,15.0,12.0,15.0,7.0,7.0,15.0,11.0,5.0,CAFCDGCFACFCCFACGBBGCAEAEGAHFADBCHACHFCFBEFGEGBDGBDGBEGEHAEFGBFCDFBFBHACAFCAFGABDAFACDB,False +46,12.0,10.0,7.0,5.0,4.0,11.0,11.0,13.0,ECFFHGFGGFCGACGFGGAHFABBHDEDCHABFBHGAHGAHCAHDABDFHDFGCHGBEABAHEHBFHBFCBAA,False +47,15.0,6.0,13.0,11.0,17.0,21.0,13.0,9.0,EDCEFAEFAFFAGHCFCEEAFGFFHFDECECCEGCDGHDGHDGHACFFCFFCDFEHEEFEEGHEDAFBGEAAHAAGCABAEFAFDABGFCFHCDEDBABFGBGGD,False +48,11.0,17.0,17.0,9.0,17.0,17.0,13.0,15.0,GAFGHHGCHBCACCFBCFHHECHBHAFHEEGBAFCAGHGEFGEDGFCBBEBGABCFDCFDCFDBEEEGAAHDAEDFECBGCBHDBFEGHHBFGBFEBFCBCCHEFAEDAEDCEFHB,False +49,13.0,16.0,15.0,12.0,16.0,9.0,12.0,15.0,BGCBAEBCDBEDBECBDCBABDCDFCDBCEGDABDFFEHCEDGECHACHEBDECDGHFFHFHEAHAHHEFFBAGAGHCHCCHGCEEAAAAGEEGDEGBFGBAGBHHBH,False +50,13.0,6.0,16.0,14.0,12.0,13.0,9.0,12.0,DAEAAGAAGCHCCHDFHEFCCBEGFEGFHAHEAGBGCBFCBFCDACDAFDCHECEBFBAFCFFDEHAGHDEFDGCDECEHCHDGADEHHFADCDD,False +51,22.0,27.0,26.0,19.0,24.0,22.0,28.0,20.0,FDCGDAACFACHGCDGEBFCBDCBGBEGBEGAGGFGGCHGDHGDCAACHADHCFHAAEEBBCBCCBAEDAGBFGAFGEGGDGHCEEEDEHCBBCDECEBGEFCCHCFBCFBHFEABEBDEDHABHDBFFFCEFCEDHFFHBFABHAGGECAEADBGGEGAABHAGHAGEFGBFBFHHDHBEGBFCCDD,False +52,19.0,24.0,24.0,17.0,11.0,20.0,12.0,18.0,FBDFCFECGDCFBBFHBFHBAHECHAAHAFCAHCHCFBDFCDHCDBDDBAGAAGAGHFGBDABCFEEAHHGDHBDCCGCCDAEBAEFEBCHBHECHDABFFBHECFDCBDBFDGGDBFABGHBGFCFCBDCBACBFGHEACEACA,False +53,11.0,13.0,7.0,11.0,11.0,7.0,5.0,12.0,HABDABEADFFDABBHBEDAEDACBEHBEGBDDEAAHAHGBHBDEBAEDECCHFDHFGHFGHFDCCEBHEBHGCACF,False +54,11.0,20.0,14.0,17.0,12.0,15.0,15.0,22.0,DFABFDGCDCDDCBHCBECBDHHHBEFBGFEGHGFHEFEAFAHDBHDGDGEDFBAFBGFBGAGGHHCHHEDBDDBCFFCGFCHEEECDDADHBHHCDHCBHFAEGBCBBAHBAGEFGAHABHCBHG,False +55,17.0,24.0,24.0,12.0,23.0,20.0,17.0,26.0,GAECBGBFHAHHEFEGCGFBGBCHHADCACHBGGBHBAHBAEFAFGGFBCCAFCFHCGHCFHCBEFBEFBCHBGFECFGDHBEHCCACGFHEDAEBAEDDEDCEHBEBBEGEEHHACHECBDFFDFADFAEFHCFHCBECDEHDEHCBAGBAGADGBCBHHEH,False +56,17.0,25.0,29.0,22.0,21.0,19.0,27.0,22.0,FFFFFGGHDEHDFGAFGEEAFEGCEADDBBDHDCHECDGCDAAFCDHBGCBGBBECCDCCDAHGBHCBGCHCCEFEGFAABBEHFEHBCGFHGCHBDHCDHCFBDEBEABEDBCDGCHCCFGCFDAGGBGBBCBFABFEGGADGHEGHEDFBBCBCGACDAEEABDADGGEGHEGCCHHAHH,False +57,12.0,11.0,4.0,15.0,9.0,3.0,6.0,8.0,HABCEHAECBEDEDDHBDGAAFHAGCBGBEAAABADEADGHDFBAFBDEBEEBGDCDDGDDHDAHDBH,True +58,9.0,8.0,9.0,9.0,4.0,9.0,12.0,13.0,CAGCGGCBAHDEFDHHGHDFDBFBBFGAFEBFECHABGGDGDEGDHGBHADGFDCACAACHBFHFGHCHHCHA,False +59,15.0,19.0,20.0,23.0,14.0,16.0,21.0,18.0,GDGGBGGCFGABBABFGEFGCDDCFBCDBEBACHABGEBCDCCDFDDFDAACEBCEGGGFHHFDHGGHFGADHFHHGDHDFFGHGGHDEBDCAACGACFADDHDDCBDBBFEBHDDHFCEGBEHCABEAHEAHEFCCHBAEBCEDC,False +60,9.0,8.0,2.0,6.0,8.0,11.0,5.0,10.0,FEBDCDFHFEHFEHEGHBHFBHFEDCHBBBAGEAGEAGHADABFHFFDBFAEFADAAHG,False +61,26.0,25.0,20.0,16.0,13.0,13.0,17.0,12.0,CBACHGCFDHEBHBBEBBFAHCCEAEEABDDBDGEGADGHDAHEABBBEFCFFDEFDAGDADBBHGGCEGBAADABCHGCHGBDBBGCBGCHFAEFCHFBFDDCAACHACFACAACABFEBFAAEGGCGBCGBAGBDDACAA,False +62,9.0,9.0,5.0,7.0,5.0,5.0,11.0,6.0,FAADDAGBGGBGBCHBCAGEADACGAHGACFECDABBFEFDGGDFGHBGHDEHBEHB,False +63,7.0,8.0,8.0,6.0,13.0,12.0,11.0,4.0,GGBDGFEGCEGCECHDCFGFGABGFEHFCGGBHFBHEGEEAEEAFEDBCFBDFDEADACBABFACFEEF,False +64,20.0,11.0,23.0,13.0,16.0,11.0,12.0,18.0,AEDAHACHEFAEFAHCAEDAEDCBAGGCBGFBCHCHFCEACHCEHCFHCEAEAAEAHCAGBDCDHCEHEGBFCHHCGHFBHFAAGEADHBDCADCFDGFDCHDCBGCGAAHCGFGDEBDEBECB,False +65,19.0,12.0,22.0,18.0,18.0,14.0,20.0,17.0,CCDCCAFHAECADDGDGACGADGHDFHEBGEFEAFDHBDGBCGCFHBGHEGAEGBDHFDFDCGDHGDAGDCBHEBHEBGBAFHGCGCCFEEFCDCCDCHECHFCFAAAGECHBBEEBHDAGAAEAAEAHEGHCFCEFGAD,False +66,26.0,13.0,22.0,33.0,10.0,21.0,25.0,20.0,CDFGDFAHFEHDHBBCDECDAHDGGGFBCDBADHHDGADEBDEGDHFFCFFDHDGADHCFHDAGEGCEACGBGGEAGFAGBBDABCABGADGAHADDADCADHAFCFGDGEFBEAHDCGDHDCADFADFGHCCHGFHCFHGDHGHGECCCCCADBFDGAABAFDAFDAFC,False +67,3.0,0.0,0.0,5.0,2.0,3.0,2.0,1.0,FDFEDHDGAFGADEAD,True +68,21.0,30.0,10.0,18.0,20.0,13.0,15.0,10.0,ABBHBEEEHDEHDGFFGDBDBBCABFGDCCDHFHHAAAAABFAEEDBEDBGBBEABEABFBBFBBDDAEEAGCFHEBAFAGDGGBBEDBHDFEFEEBEEBABDHBFBGCBGCGGBGCCGCEGAADAABCDDADEAHF,False +69,23.0,30.0,20.0,17.0,29.0,22.0,24.0,20.0,BHBBFBBEEAEGAEHBCABCBGCGEFHEGHFFBFCBFCHEEDEGCCGBCHFHBAACDGBFBEAEAFEHFEHGHGGACBEDDDBDFBGBAGBAGEDGEHAEDDHGDFEDFEHFACCAEHFBCGBCECFGFFAEGAEAHHBGABGAEGDCGDCHDBBEFAECDHCDHABAFBACBAFBFGEDEEHGB,False +70,16.0,21.0,23.0,21.0,35.0,31.0,21.0,19.0,FEGHEGHEHFBHEBDEGDABDAGFAGCDGCEAEABGGEFEBAEBHDFEFACFEHFHHEBFGGDGBAGBAEEAFBACBCBDFFDGEECFEDFEAFEFFEDFBBFHFFCGFBFCECEHCHFFHGFDGFHECEGCDDBDDEECCBDHADHADEEEECDBCBFHGFHGBCGFCHCCBGDEEAEHAECDCCF,False +71,21.0,21.0,25.0,23.0,34.0,29.0,19.0,27.0,CGCABAFBECCEGAEFEEHEDHEFBAFBFFGFDCBDFHDFDDHCCAEGAEGEECFCDFGDHCDAFDFFHBAEGDECFHHFHHEAABFABAAHCCCCHHGBBCBHGGHEFDFFCGFDGHDAHAGHCEEBBEDBEGEHBEGCHAEHDEHFEBDECFHABHABAAFDDFDDFBEFGHGCEECFDCDCEECEEAHEGHEFBBG,False +72,26.0,9.0,19.0,24.0,24.0,27.0,21.0,27.0,DDGBDCADHEDABHHHAEHAHDCHDBFFEEFAEFAHGACFFEEDHACFCCFGCDACDCCDCEDBADHFEGDHDFHGCHFAEFHDFGFGEFGEGGEHEHHAHFEHCAAEAFCHDCFFFGABAFEAGGBGHCHDFHDAAGAFCADGADHAGHBGBBEEEGEEFAEFAEFCGDCFDHGDH,False +73,24.0,24.0,23.0,19.0,22.0,18.0,26.0,30.0,HGFHGHHBBHDBAGCEDEHDHCDAAGCBCCHCCDGGHAGHGHHFAEFGEGBEBFDFAEAHBBHBDCBDCBCCDECHHFHDDHCGAAAAEAEEDBGDBGCFACGAHGDFGCGHABBACBAHGHHBHGBEDDACFACFEBFGHCAEBGEBGEDGEDHEFFECEEAEFGGHHFBBFCHFBAFGAEHACD,False +74,26.0,17.0,19.0,17.0,28.0,19.0,13.0,23.0,EGCAHEHHEHABADBADECBECEEABEACFACACFFBFGBFBDFCFCCACAHEBHEGHDBHBBAFEADEHBCHEEHEGBFGBFDCGDEFDEADEDHEAAFFEFFHHFACDCCEAHDADDEEEFAFGADBHEBEAGAGDAHBCHCGHCAHGACGEEFAHGHHD,False +75,3.0,1.0,2.0,0.0,2.0,1.0,0.0,4.0,EAHBCHCAHEAHF,True +76,10.0,5.0,4.0,6.0,10.0,5.0,10.0,8.0,HGHHAEEAEDAECGDCAHGFBGAGEFGFBEFAFCGCEAEEBGEBGDDHDBHDAHGAHA,False +77,6.0,2.0,4.0,1.0,4.0,1.0,1.0,0.0,AACCDECAEBAEBAGFECA,True +78,26.0,21.0,24.0,22.0,21.0,23.0,16.0,22.0,AEAFDAFGAFHAHCGFCGFHDCBDCBABADBCDGGFGHEBBDFBFFDCDEAEEGGFHAHDCDDBGEHCEFCHFGEFDADGFHFBDFCCCBCGBCABDFHAEBCHBCHBCDECEGFFAHFAHFCHFDDCAEHAGHBGHBAEECDDDDAABAHECHEBHEAHABGEBAEACEACEAF,False +79,23.0,23.0,29.0,21.0,13.0,23.0,22.0,17.0,CDHBACEAHEFDEGHAGAAGFAHFADFCBBBEFBCDGFBCDBDHGGGGCGFBDBBCFBFDEGEEHEGGBGEHFCCFCBDCEDAEABFDHHBFBBCAGDDCHDCHDAHBACAGCAGCADDBDFHAFCAFCGHDEBGHBCHGCHFBEGBFACFCCACAADACFACFCCFGFDG,False +80,12.0,12.0,23.0,9.0,27.0,13.0,18.0,19.0,EGFECEECHEBEEHHFBDCGCAACFBCGEHEEGCEACEGDEADAGBAGBCDBFBHFHACHCDHCDHCECCEGFHGFBABCGDCBDCEACHBCGGAEEAECFEHHAFFEEFHFCEFCHGGGGDHBEHGGHEEHE,False +81,25.0,15.0,14.0,17.0,20.0,16.0,15.0,15.0,DGDFFBFFCAFHADGAEEAFDABDEGGEBGDGEDEBAHAAEGABAHCACEACAHBAGGECFCDDEDBEFHEBGAFCAFCAHDEHDAFAGFCDBCHCCHCEDBGFGHBADBHGBEAAHAAHAEFECFEDFEDHEBHGB,False +82,23.0,16.0,15.0,28.0,9.0,16.0,15.0,26.0,FAHGHHFHGDHGDHDHCCHFBHEDGDGADGBDFDHFBBEDBADEDDBDHFDACDBFGBFAHCDDDGDBGBBGAAADCHFCHCDGABFHDDHDAEDCEDCGDFEAAEACHHGHDGCFFCHABHAHHAFCFHAAHAACBABBHFEAGEAC,False +83,16.0,17.0,21.0,14.0,11.0,17.0,24.0,19.0,EGHCBBCBBHFAHAAGAFGHBCDFAGFBDABDADEEDBCDBCHBCBGEGFFGFGGCHGCGGHHADHDHCDHAFGACCEHDGHFFCDFEDAHDFFAFFHEGBDGCGCBECECHBGHGGHCGBCHBCEGFGGFCACAABAE,False +84,25.0,24.0,34.0,20.0,21.0,23.0,18.0,22.0,GCCGAFHHFBGFBCFBDFBGFCGDEGCAHEBCAFCBFHEFEDCGFCAFCHCHBCHEAHAFBAFDAHBHBDGAABAFBACACHHCFDAFDGBAHBEBBEDFCFECAEBGFHECCCCCCHHEEHAAFDGFDHBDGBEFBEDDHDDEBHECCECCEBAEBAGACGEDGADCBCCGGCDEAGCADCAFHHD,False +85,14.0,17.0,15.0,14.0,15.0,14.0,16.0,10.0,GGCGDDEBFFHGFBGFBHFHHEDAACAABGFFFCDBGBEHBEDBFDBCDCDGCDEFBCHBEGBEGBEFHGFBAEBCEFAAGGCHCCFCCBCHEHEAACADDEDDAGDAGEAEBAG,False +86,5.0,2.0,1.0,1.0,1.0,1.0,3.0,1.0,ADFAGGAHGBEABCA,True +87,28.0,33.0,23.0,19.0,20.0,25.0,30.0,22.0,FFGDBGHBGEGAADDHGEEDEHBBACDFCGFCGEHFBBFHBFBCCGCCFHDFCGHBECBAAFFDBBCBECGGFEGECCAGABBABHAEHBBHBHDEFDCHDBAFFDDFAAHAAHCDFCAHEAHGAHFAHAGHAGAAGEEDFGBEBECBGCBAFBGCCGAFAAFHAGGFGGBGGBDEEGEGBFGBFHBCHBDDBDDBECCA,False +88,27.0,30.0,28.0,20.0,23.0,12.0,23.0,29.0,EGBCBBCEBCHHGDBECBCDBEDGEHGAGACGEHGCDACFECFCBHBBFDAHCACBACBEFGGAGGADAAEBAHDFHDCDBAHCHHBHABGCBEEDHGHHGFHAHDAEDABDGCDECDBADBHHGHHGFGECBEABDHFDGAHEACFGCAGCABCHBFECHCBFCBFAEABDAGEHEEAECABDHBHHCEBG,False +89,14.0,15.0,7.0,17.0,10.0,11.0,15.0,9.0,CHBADFABGHBGFGGAGGADGDEBHADHGHGFDFDDCDBGAAGHAGFAEEBBEDBEBCEBFAFDAFDFGDEADEGDFACCCGBHBBHABHDEDCBDFE,False +90,5.0,3.0,3.0,1.0,8.0,0.0,6.0,3.0,CCACEGHEGDEGBBAHEHGBAGEAEEAEG,True +91,0.0,0.0,4.0,2.0,4.0,2.0,2.0,1.0,GDCFDCEECGEHFEC,True +92,14.0,4.0,7.0,10.0,8.0,6.0,12.0,5.0,DCDAEFAFCECEEAFEDFEGCCGACBDGHFAHBGEBGAGGAGGDGAEGHHGAADAFDADDCBAHDA,False +93,10.0,8.0,8.0,3.0,8.0,14.0,16.0,15.0,FAGFDGHDHHEHEEGGFFACFHEHACCACHFGHFGHCGCAGCGBCFFEGFGBHABHFDHGBGBHABHAFFAGFEHEEBBAGG,True +94,21.0,25.0,21.0,30.0,27.0,13.0,12.0,17.0,HHBEBCAACEABDGDGBDFBGFCAEHGDCADCHDCEDFEDCEDGDCEDAEGEHAADBBDAADHCDHDFHBEEBEEBCEGAECDEBBCGAHEBBFFHEBHEHDAHDAECFFDFEDFBDABDCCACEDEBDHDDAGFAEABECBHGFDDFEDCCBHCBHGBEGBACBA,False +95,4.0,6.0,6.0,8.0,7.0,6.0,6.0,9.0,EDGEBHEFHACBBCFEGHCHDAHDEHDBHDBDDEHFCGECGFGBFACFAHGD,False +96,8.0,5.0,5.0,6.0,5.0,8.0,12.0,12.0,AFACCAGAGGFBEHEGHECFDFFDGFHGAHGHHFDGAGCAGEFGHBBHEBHDDHDHHGCBA,False +97,20.0,25.0,21.0,20.0,27.0,26.0,25.0,26.0,BFCFGDFBECHDCEBGEFGBABHGDDGAFBEBCEFEEFGDAHFBHEHHCHDDHGEFDFFBGBBAEGCCFDDABEBBEBFHBHHBCCECEDCAFCGFGHFCBGHBEAFCBFDEEAEEAFECEBBGGAGHBDHFHHFHHFHHFHHEEHGCDABGABGACGAFGAGGDDEDDCADCFGAFGDCAHEAHEAEGC,False +98,4.0,3.0,1.0,1.0,6.0,1.0,5.0,3.0,BBAHAEDECGEAGBAGEEGHEGHF,True +99,21.0,17.0,15.0,21.0,17.0,23.0,10.0,21.0,AHDDHEDGFFGCFHDHAGHGHHDDFADFABHDBCCACAAHGDDFDDFGBHEBHBHEEHEFCFFBBDDBAABCEEHDACDHCEEAAEBHBFABFABCABFFFFDFFDFEEFCEHCEBDEBFCAGAGGDGCHBCHAAHEFFECAADH,False +100,21.0,17.0,13.0,22.0,21.0,22.0,21.0,31.0,GCAADDGBDEBDABDGDGGEADEDDFHHHEHDGHFGHFDHGAFAHEHDCHDHFEBGEACDACGABGABGFGGDGBHEEHEFFGHFABDHEDAECBFHAGHAHBAEAAEAFEHFEBGGBCFDFEEAHCHHCFDAFDCFDBFHBAHCHHFFGEHDECCGCBHFHHFBHBE,False +101,3.0,4.0,2.0,2.0,2.0,1.0,2.0,2.0,BCFBEABEABHADGCHGD,False +102,3.0,5.0,4.0,4.0,2.0,1.0,3.0,10.0,BGHBGHCCHCDHEHHABDFHDBHEGCDAHBAH,True +103,22.0,16.0,17.0,17.0,11.0,10.0,13.0,12.0,DECDFCDFEDCCBCCBCADGAGFAEAAHHCGECAAFHAHBAGEFDEFHHGGFBFCBACBABDACDAHDAGDGBDBADHFDBCEHGEHGDHABGBCEDEEHBAABADCGGCFCABDABA,False +104,12.0,15.0,10.0,16.0,25.0,15.0,20.0,17.0,GBFDCFDGDDBHDAADEBGBDEBEEFGHFGHFGHCGHEGDEADHBDHGGBGHEDCFHAAHACHGGEGGEFEBFGADCCEBHEGFEHDEHEEFAGDCHFEEAEEBCEGEDBEDBECBFFBHHCAFAEGAFB,False +105,7.0,10.0,8.0,8.0,6.0,8.0,6.0,10.0,HBEHAGHFGHBGDBAAGCDEHFEBEHBEBCABAACDFHBCHDFGDFGDFHCHCCACBFDBEDF,False +106,17.0,20.0,9.0,15.0,13.0,17.0,14.0,15.0,FBEAGDAGAABAHBGEFFBFFEDHEGHEGHEFHFDBBCBBDBCHCAHGAHCHBEGFDGFAEBAEGADCAHBDFBDFDFBABHEFGBCDAFDBCAGCFBHFBAFAEDHEDCEDHBDGGHGA,False +107,5.0,5.0,1.0,5.0,1.0,5.0,5.0,2.0,FABAAGDGFDFHBFEBAGBAGBFDDHGDC,True +108,17.0,16.0,20.0,15.0,16.0,19.0,21.0,30.0,CBHCHHDDDGADGAFCEHEBHEFEAAEBHFHCBGFAEDHEFEFFCFFAHEHHAHBGCDCHFGHBGFCGFBEABFBHHGHHGCHEAHEADABGHBHHBDHGDHGAGGBGGEFCFFCDBGDFDAECEECGCAGCGDCFDFHHAHHDHBBCCACGAC,False +109,19.0,26.0,19.0,10.0,27.0,23.0,8.0,14.0,EBCAAAGFADFADFEFBBBCBEABEABEAEEHEEHEECEBGACCAFCBHCDCCECFBCAGGAFEAFEFBHHBDFAHEHFEGFHCFBBHCCABCHFFBFFBDGCEGEBAEGCFFEEDHFFBFBADBDBBDBBEHEEFCHACBAHDEE,False +110,19.0,10.0,10.0,17.0,15.0,14.0,13.0,9.0,EACEADEDDGDAEBCFACEAEBFHFFGDFEDBBGBHGCADCFBBBHCAHEAHFAHAAHCDGCDGAEGAEGEDDFGEAEBAGFCGDGDDABDFCDFGFFAAEDFEHAH,False +111,6.0,10.0,13.0,9.0,4.0,7.0,3.0,10.0,CCCAFBAFBEHDFBCCBCHBCBCGHDAHDAGDCDFCHCEHDAFDFHDHHDEEBFBAGBCHBC,True +112,14.0,15.0,18.0,9.0,20.0,11.0,10.0,7.0,DEFDEFBEACFGEFCACCBGGBHAAEBEHCEGGEDEEFEEDBECBABGADFADFADGCHCCHCHACEDHEGAFAEFBFBAEACCAEBBGBBGEBEBHCCDCCFC,False +113,18.0,25.0,13.0,24.0,29.0,22.0,19.0,30.0,HCAHEABDACHBBDDHADBEHEEHCABCFBHFBABBABDHBEHFGAFGFHCHGCAEFHEFHGHCGCEHDDFEBFEFFDDHDEEDGEFCBGBDGAHHCHDCFDEEDGCFHHFEEFGBGGEEHBFAGFDHBEGFEDCEDEBDEFHEAHEAHABBEDBGFBGEHGAHFADBADHADHEDBGGB,False +114,13.0,9.0,15.0,32.0,17.0,18.0,11.0,14.0,HDHDDAGGFDDFHBFBCAEDGEDCEACDDEEDFHFAGFDECDCCDFADECFECHDCHDGAGAHGHDFEDCEDCEHBHDAHDCFDBFHHGDBDAFCGFAHFDCCDAEDGEDEEFADFAGFBBDEBDEBDF,False +115,21.0,18.0,26.0,25.0,21.0,27.0,25.0,34.0,AACCECDFFBBDABHAGHGFHGHAFHBFHFEHCBHFDAGHAGEDBEACHDCAGCDCCDBEDBDDEGGEHGAHFAHDBFGHFGCDCCFCBFCBHCHHFFDFGEEEDHFHHFHDFEDFDCBHAGAAGHBEEDCFFCHEDAEBAGDEGDEDBFBGCBECHCGHCDAGGAHGHCGHCFHBFHCFHDADAEGEGHCGAFFEH,False +116,25.0,15.0,25.0,18.0,19.0,11.0,22.0,30.0,BGGBGDHGBAECHEFABDHBHHBHDADBEEGFGGDGCCGFCHHHAHAFHBFEEGEAHCGEAGDCCHCGDAGBAGBAEADBADHADFCGHEDHCABCHHEHDFHFAHEAHCHCAHBDHBGHFGEFCAGCHGAAACAACHHDHCCGECEDDFCDACDACBCCEEGEE,False +117,28.0,24.0,15.0,28.0,23.0,30.0,14.0,19.0,CHACHAGEBEFDCFAGFADDEDDBDGBDBFEBEDHHDGDECDEBFABFAFFABAAHHAHHDFHFBHDBEDADCBGHEDFFDEDDEBEBAGADDFFFBDFBFFBFFBHACFDBFDFAEBACBACGEGGCFAFEHEAHECHBDGGFCAECFEFHEHHAGACBDCBAHAAEAAEDECDAFGGFB,False +118,0.0,3.0,1.0,0.0,4.0,1.0,0.0,2.0,FHBBEEBEECH,True +119,15.0,14.0,10.0,15.0,7.0,12.0,18.0,9.0,BGDBGBFEBDCFAFFADCGGAGDABAAHHAHHACEBCDDCBDAGDGBBGDGDDACEFCFFCGFHGBEFCGACHAGAGHAGDABBEEFHGFBFDBEDGHDG,False +120,18.0,23.0,21.0,12.0,21.0,14.0,26.0,15.0,GBBHAAEBAEHEEFEGFGCAECABAGCADBEFAAGDABCAGGFGGCHGCHGAHEAHFFCEHCEBBFBBEHBCGECGACGDCGDHGCGGHGGDDGHACBBGDBDECDCFABECFEBFECEBGBBEDDEGFCDFEGBHGBHAHFACEBCHBF,False +121,18.0,17.0,15.0,11.0,14.0,12.0,17.0,17.0,AGGAFDDFCDBBHECHBCHADHCBACFACDDGFACEBCBBGBHAAHEAEEHGFGCFGBHEBAFHAHHADHBEGBHHCEFEEFGHFGFGCBDCADGBDHHEBEBBAADAAFCAGCGGEGGEC,False +122,19.0,12.0,14.0,16.0,13.0,13.0,22.0,12.0,DFAEFDEBHGFEEDAEDFGGCGGFGGFGGAGGAFFDEAGEAGDBBABDHHCHHBDHBDGCGGDHDAGCACCBFCBABHEFHCCHECBCGDDAHDCEEFACFBCAGDAGAAGAEFAGDBEHA,False +123,3.0,8.0,5.0,11.0,9.0,10.0,4.0,11.0,EBFFHHFADFCHFGHEGHFGFACDEDDEGHFAEDHBDEBDECDCDDFHBFEBHHBCEBHDB,True +124,4.0,5.0,6.0,11.0,9.0,6.0,5.0,8.0,ACEACEADEDEHDCFFCDCCEHHEHEBHGBDGHDFDFEGFEDBHDHDBBGFAGD,False +125,11.0,14.0,19.0,12.0,21.0,14.0,17.0,9.0,CCDCBDBEDHEGHAFEECDGCFGCEGCBGEFAEDACCHCDHGFEFFBBEABEAHHAFCCFBFFCFCBEGDACDGCAEBAEGGEDGEDCAGGEDHEBHBBACBHGFEGEGDEGEFCBF,False +126,7.0,15.0,16.0,15.0,17.0,19.0,21.0,17.0,CHHHDBCCEFEEBEGBHFEDGEBFFBGFGHHGHHGEHDHCDHCDFAFFDCABAFBHGBCGBFHBDHCEGAGGHHGDEAFECHDBFGBDBCDECGEFEEBECBDFFDECGGCGADGEDGFGCFGCFAF,False +127,1.0,2.0,2.0,2.0,3.0,3.0,7.0,2.0,BEGGGGACFHCFHEFDGGDEGB,True +128,24.0,27.0,28.0,25.0,25.0,12.0,31.0,20.0,GGGBGGBDBCDHGACGEHDCHDCBDCHHEHBGHADDADDEBGGHGDDEADFAHFAGGEGEEABEHDEHCEBAEBECBACBACGACGADFADBBBBFCCAEGHFBEBCAAHBCHFCEFCDFCDCCBAEGEGCAGCGCCGEHFEHGCCACAACBDDBHGBEBDAFGEFGBBGHHEDGDABCGFHDEGGEDEADB,False +129,8.0,19.0,18.0,15.0,11.0,19.0,15.0,9.0,BEEBFHGAACFBCEBFHFADFCDHCDBCGBGGEGBDAADFDCHECHECEGCFGCFGFBCFGCAGDFGFFHHBDDFCDFBBEDBFDGDBBFBHABCEBCDAEGCBFHBFCGECGD,False +130,19.0,16.0,11.0,13.0,12.0,17.0,19.0,19.0,AGFEGFGGEGDAFDBFDBCGACBHEHHAHHDFADABHAGHBFHDFCDCADEEFEGBDGBEGADBAHFGBDGBAEFAGFBCAECHGBGFBGBBFBHAHHAHDEGEFAHADCACCHCEHGAHFHGFCF,False +131,4.0,4.0,2.0,0.0,2.0,2.0,3.0,2.0,FBECAGHAHCAGBAGBEFB,True +132,21.0,22.0,26.0,22.0,19.0,22.0,19.0,31.0,HHACHAGHDFHCACFECAECGDFFDFCAACEBEDHHAHDCGBCBBCAHCAFCDBGFGDCHBHECHCFACFGCHECBBCFBGHDGHEGHDGFBAADFGBGGFCGHCBHAGHFEEEDAEDAHHABFABHAHHGHBFDAFDGDDFEDGBDFEDHDDHCEHEAHECEECEADBGCBFFHCFBBBBH,False +133,16.0,18.0,20.0,18.0,16.0,13.0,27.0,16.0,DGGBCEDCEFHDGHFBDCHFHHBACBADAAHADEACBGHFGEDGCBCABGAGFCGDCGDGBEGBEGBECEEHGEHGHHDAAGGACBDGBGCBACDEBDBGCFHFEHCEGCEAEFCHFABFEGGCDHFDCDDCDBFGBFGAGHAG,False +134,19.0,21.0,15.0,10.0,12.0,12.0,10.0,11.0,DAGDAGAAHHFHABCBBCEBCFBCGDCGEEACACBACEAFGBDAAFEAFEHBBBFECDEADGFFACGECBBCBBGEBFEBDAACHADHFEFBCHBFGBHDBCGBHADHAH,False +135,13.0,9.0,13.0,6.0,13.0,9.0,17.0,10.0,ACEEHFBHFBGFCHABEADHHCGACGDHBCABEGBEDBGGCGHHAHCEDAEFAEGCEACEAGGFCGCDGBFGAFGAFBEGCEGAFGECHD,False +136,12.0,12.0,9.0,6.0,6.0,6.0,7.0,12.0,DGFDCFBCHHHHHHHBHBBABEAFGBEGCFDFGCCBDABAAEAAHACCAGHADEACGHGEBEFBCDBHAB,False +137,8.0,7.0,7.0,10.0,12.0,16.0,11.0,8.0,EEHEGHGAHFFEFEDBGDBEBBGGFGDCGFCFCGFDDFHDFHAFCFDGAAFFAEHAEDFEGFEDCEGAEFBHBCDBCHA,False +138,16.0,20.0,15.0,26.0,16.0,10.0,21.0,11.0,BCEFDBCDBAHBEFBCAHCAEBDCCDHGHHCHDDDEGBFDFGCACAEEDGADGEDBEGCEHCHBGHBEDDADDGBDGBCGBDHCFGCGGFGGAAEAADAEDGEDBEBADDADGCDGBAGBDGBHGFFBEDAEFBF,False +139,13.0,8.0,3.0,6.0,6.0,4.0,5.0,4.0,EDGABAADGAECAGAAGAACHFFHABGFBABBEDBEHBAHCABDFDEED,True +140,3.0,7.0,9.0,8.0,11.0,8.0,12.0,4.0,FGFCGCCEEDFEBFEBDACHADEBCEDFBDEHEFBEHCEDCGGBGFBEFCGGDGHDGCGGAG,False +141,7.0,6.0,3.0,11.0,10.0,4.0,8.0,7.0,EEAAECEEGHEHDFDCHCGHEAAEHBDFBDBGDBADBEHFEAFGGDHDDGBDGADG,False +142,25.0,23.0,17.0,19.0,29.0,25.0,18.0,29.0,EEBEEBHHHHBCHEFDGCDECDEDBEFHAFGBFBHFBHFCHFEDFBBFEAEGBCBAAAADAHEEFAEFDFACHHCHBEHBHHDGECFEFBEGHEGHAFHCDBCAGHEGHGDHGEGGFAAFAHEEHBFABDACHABDCDAFGFFGCFECFHBFEEDDGDBFCAHAEDDEACEAGDBGAAGAHCBHB,False +143,1.0,2.0,2.0,3.0,4.0,5.0,2.0,3.0,CFDCBDHGEEGAEDFEFFBHFH,True +144,9.0,4.0,7.0,5.0,3.0,7.0,3.0,7.0,EFAFABHACHECHGCBADBADAADGCFFAHGHDFHDCHFCBECAF,False +145,21.0,27.0,26.0,22.0,15.0,22.0,16.0,17.0,FCDFDDECEHCFGCEGDABBGHCGBBFABAEFEEFACHBGFEABEDBHCCFGAFEEFHAFECFHCEBCDBCBAHFAHFCFFCFFBFAGGAECDCCBBDDCDDCABBAGGAGBAGHCHECDACBAFHECGBGGBAGBHBACCADDDDCHHHFHHBDDBDDBDBADBF,False +146,23.0,23.0,27.0,18.0,23.0,27.0,25.0,28.0,DEGHEGFDBFGHDEACECDFDDFDBBBGCEAFHFFHFEBGEBDEBFBBFHFFEFCGFCGCHGAHBCFGAAECGEGDDGCHGAHAAHAADDADCAFBFFBHBHEGCAHCHHBEACCBBABBDBHCBDFAHAEBCEGEGCBHEHFAGCAFCACEFHEFADBCGGCGHAGHGEHEFHCAHCGHDGHCEHCEFCGFDF,False +147,19.0,22.0,21.0,22.0,15.0,18.0,18.0,18.0,ADDADEFBADAHFBBFBBCHGCGBCBHEDCCDHDDACGEGBEACEBCGCFABFHEAHFGDCDDCGFCGHEHHEHBFHDFBFFBAFAABAADACDFCEFHADGADCCECDBHDBCGBAEBAHDHHDHACFCGFGEFHEGGCGEFGBDGBGBBDE,False +148,23.0,18.0,18.0,17.0,20.0,20.0,23.0,19.0,GHBGCBDAFDAFHCBEFGACAECHHGEGFEGDEDDBCAAGFAGCGECAEFBEACEHGEHAEAFEAFBCGCCFCBBGHBAFBFCBFAEHBEHBEGAACFABGEDGHAGBCGCEBDGDDHEAHCADFFGHAHDGHDGHDGBDABHAEDDFHDFCFFHGFE,False +149,11.0,9.0,14.0,14.0,12.0,13.0,8.0,11.0,CCFCGFCDFHHHGGHEDDFHDFEEGCEAHAHCADFEBBBCBFCAHBAHEACDDCDACDADDBDDBEGBDFFCEHEFBEFEAGEGFCGFCAHA,False +150,20.0,17.0,22.0,21.0,18.0,23.0,27.0,26.0,FDDHHBGAEAABAAFAHBGFFHEHCEBEBBEDBGDCGHCGHCFFEGFEDFCDACDAEBFEDAEDHHHFGHGDHGAEFCFGBEDAADCCGFGGAAGCHCDDBDCGGFGGFGGFHGFBGBCGECHFHHACHABDFHDHCAEBBEBGCCFHEHGFHFEHFEHBCACCACGAGHDDDD,False +151,25.0,32.0,23.0,18.0,29.0,30.0,21.0,16.0,CHFAFBDBCEHGEHEEFEACEFCFHHFCAGAEGBCABCAECHDDFDFFEFFGHABFFEHBBDBGABGACGACEDCGDEBDEBCEBFDCHBADBFDAADEFBFHGAACAACHDEADHCBGCAFBFFBFFBEBBGBEEBHDBFDGDAGFEGCABEEBEHBGHBGFBGBAGFGCEGCACFDGAEBEEFCEFAFHBCE,False +152,2.0,5.0,8.0,6.0,3.0,7.0,7.0,3.0,ECBDCEGFFGHCGCGGFBDFDDADDHEBFCBCCBFCGFGAH,True +153,20.0,20.0,31.0,26.0,22.0,23.0,14.0,22.0,GBGFBFFBHCBHCBHGBEFCGFHHHHEHDCHCCDGCFFCDDHFDEDGEGCHHADHCEECFECHECDGCDGADCAGAAHEDHCFBEFEDCHFFAADEADHADCGBCFBCFEEEEBGBCCCCBCDBDHBAHDABCAGCBCFBEHDEBDCFDHFEFDAACAEDADAFGEFABFDCEDAFAB,False +154,14.0,22.0,13.0,6.0,19.0,16.0,15.0,9.0,EEBFEFCBFDAAGAHBCCBGCEEAEEAEEAEEAEGGFHBCHBCBCHBCFACFGDECBAGFFDBHBBHGGFAGBGCBEHGADBFBBGGAFCAFCEGBEGBEFBDFBHEHEFDAFB,False +155,13.0,9.0,8.0,9.0,16.0,11.0,16.0,26.0,HGHDBHECHGCDGAEGFEHDEGGHHFBHFGHBGBEFEAHEAHBFHFDHADHBCHEAHEAHDGHDHHEFFACDCEBFGGEGAEHEGHEGCCGFHGAAAHAFHAHDEBBC,False +156,21.0,23.0,28.0,17.0,32.0,20.0,26.0,33.0,AGBGFFGFGGCEFCBFGBECECGECBECAGHDHEDHCBHEEAEEBFGGHEEHAGFFGFHHCCHADABEGBHGCHGCFBHEHHEHHGFHFFHEFAEHADCEDCHAADBADHEDAFHEDDCCDCFEHBHGGHEFHEBHEBHGBCGCADAAHACBDFBGCBECBCCEHEADEGEEAFCDBHGBCGBCDFAGEAEHAHDCBBCG,False +157,3.0,5.0,10.0,12.0,6.0,7.0,9.0,8.0,CDDCFDCHDGGFGDBGDHFHHEGCCHDCADCAGBFHEGEEGCEDEFDBFDHAHGCBFCBD,False +158,27.0,19.0,22.0,22.0,21.0,22.0,30.0,32.0,AEAADDGDGHBHDGHBGHBHHBCHCAHCABEEBDBDHGFHGHHGBBAHAGFGBAGAGGAGHHCFFBHHGDHAACAGCAHDADGAFHCCHGHHCHGCFGEEDEDBECGAFEDFEDBEGBCACHFCDFGDCDCCBGCFGDFGHFAAEDHFBHFGFFEAEEHEDBECFEABGAFEEEAFDCFDAFDBCGHCGHAEHAG,False +159,6.0,10.0,10.0,5.0,6.0,6.0,5.0,10.0,HCEECDECAFABHBBFADFCGACGABHFEHCBBCBBHFHCDCEDCHGGHEGHFBHABD,False +160,18.0,20.0,20.0,17.0,21.0,19.0,20.0,20.0,FEDBECCGDCDBGDBGDGGDCDFCAHCEHAGAABACFCFFCAACHADAACEGEEGBFBHEHHBGHBACGFDFCHFCHEAEBBEDFFGCFGBEBBEHDDHABGEEEEFABHABHGEHGEHGEHBFDFDHGDHGBEGBECCFCAFHFGCCDAFAHDB,False +161,12.0,21.0,28.0,20.0,19.0,21.0,30.0,23.0,BEBCAAFGAFGBFGEEEFCCHCGHFGHGDDCCHBCGACGEHGHCEHCFCBHCBHDAHDHHDCHEABGHFGBGGCGHCGCEGFDGDDEFGEAHBGEADDCFDGBDGDCFECFCGFCHEGAFCDFCDGDFFEHFBHFCCBECHEBHCBFDBFBBGBDAEDGECGBHEBDABGGGAH,False +162,21.0,14.0,18.0,20.0,18.0,17.0,19.0,20.0,GHBEAFEGBGGHDEEDEABEBBEFECFCCABAAEAAEACBAFBHFHHAEDBCDECDAFBAFBAGEHEHGDAAHGAEDCCDHDDHGAHAFCCECAFCHHCHEGBCDCCBFFEFFGBFDDDDDGGCGDAFDGCGFHHDHHDHGFHGAGG,False +163,7.0,8.0,10.0,9.0,10.0,6.0,9.0,12.0,FBCCDDCAHADHEHHAGCGGHECHECHGBFABFADFGDHBDHDDCDHCEBFHGECEEAEFHECEBGBGGBA,False +164,2.0,1.0,4.0,3.0,2.0,6.0,3.0,7.0,CHCFEGFCGHHEABGAHDFHDFHCFHFD,True +165,27.0,21.0,24.0,26.0,31.0,11.0,22.0,21.0,CAADGACHHEAHDFHCAHCFBCFBEBHGCEFCHCGECDEABEACDDGHDAFCCDCADCAGBDGBEGBCDEHAHHAEFBEGDEFCEABBDBGAHAACAAEACBFBBFGEEHEBDEGDEGDCCDCABHEEEGCDGCDGHEGEEGEHDEGDHDAEFEGBDGADHFDGCDGBAAAAHHEEHDEBABB,False +166,7.0,16.0,7.0,13.0,4.0,10.0,9.0,15.0,BDDEDDGCAHEFHCFHCBHAGFDBDDBDDGFFBAHAHHFGBBDFBDHACHBCEBFEHHGHHBADBCFBHDGABGHBGFBGC,False +167,15.0,15.0,9.0,10.0,9.0,15.0,18.0,14.0,GGABCADCGHHGEHBDHCDHDEGGGFGGAGAABECBCFBEABEBEGAACBBFEAFBHFBHFBGFCAFGHFGHDGCBCEHFFGBFEDFBDAHHAHHGFDDAGDAFA,False +168,21.0,14.0,14.0,15.0,25.0,21.0,7.0,17.0,FDABDAHCHHFDACBGCBGCHFAACGEEBCBFABAEEAEEAFEADDHFAHFEHAHHCEHEFDGFEHFEGFDFHCCAEAAEADBHCFHEBBCFACFDEADFAECAEBBEDBEGFDAFEFDHFDHFEEBCEBGEHD,False +169,11.0,25.0,11.0,15.0,12.0,14.0,16.0,19.0,CDFBBCHGCEBDBACBDCGHFHHFHDFHBEGBEDBFDAFCAHBACFAGGAGEAGBAGBHBBDEBHGHHGHFEABDHFCBECBFDFEGHDFHBFHAEHECHBHBGDBGBCEBABDEGDGGDFDB,False +170,11.0,10.0,15.0,10.0,14.0,10.0,14.0,13.0,EEGCEHAGADCDEADGBDBHDFGDHCDFCDHBAEAHEHCGFCGFCEFDHGHHGHFGCAACHACHAEGEBDCFGCFBBFBBEEBGACGFHEECEBCGA,False +171,15.0,14.0,17.0,21.0,14.0,11.0,20.0,12.0,CBGBFHBCEACEAGAACBDBBDCDDCDDAGGAFGFGDHADEDDEFFAFFCBFCBFCFAHDDBGGGEADHHBHBBDEEGEEGCAGCDCCGCEBHHCGGCDBCHHEAHGAEGHEFADGDGEDGDDA,False +172,6.0,4.0,6.0,6.0,3.0,10.0,5.0,4.0,GBFGHFGDEDFCDAGDHCDACBECDECAHAFFAFBCBHAFFGFF,False +173,2.0,0.0,4.0,3.0,0.0,0.0,1.0,0.0,DDGDCCACCA,True +174,3.0,6.0,8.0,12.0,9.0,8.0,4.0,7.0,FGBDDHHDCFABFABCBCCHDEHEFAEFEBFEDDHDBCDECFHCFGEGGEDDCDDHE,False +175,4.0,4.0,3.0,0.0,0.0,0.0,2.0,1.0,GACGABHBBAABCC,True +176,4.0,2.0,4.0,1.0,2.0,1.0,1.0,1.0,HCDACAAEABCFBCEG,True +177,22.0,20.0,10.0,18.0,13.0,13.0,19.0,20.0,CBHCGHGEHEEADBHGAEGFEGFBAEBCFAFEGHCBABFADFDDCHBCHDHAGGADBAHFEEFHBBHBGDDDHDGHGFHAFAAEGBBDAADHGBEGBAGBADBAHCHHADHDGGDFGDFDCABCABCABEFHEGA,False +178,22.0,19.0,25.0,28.0,26.0,27.0,22.0,13.0,CCCCCCCDCAGHEHCGDGHCADEADBADHFDGGGBDACFHCFHDGBDGDAGDCDDBBCEBFBAABDCDDEDFEFEECDEBAFBDDBFEHEEAEFGEFGEAGBFFBFFBCFCFDGHEFCAFCAHEEGEEBEAHDGEFBFHDFEDCDHCDACGGBGCAGDAFAAFEAFHDFEGECBBGFAEFAG,False +179,3.0,7.0,11.0,8.0,19.0,13.0,15.0,4.0,BEEBAEFHEBGCBCEBFHFDECDCGHGFEGEEBECGFCGFDGDDGFAFFAEGCEFCEFDECEEGDEGCGGFGEBDHCEGF,True +180,23.0,18.0,16.0,19.0,17.0,9.0,16.0,16.0,DACDHCDECEHCBACDAFDAFABCEDHDGHBCFFABCDDFDDHCAHBAEDABHABDGDFCBECAEAAHGEFABFGBGBHABHCEAEGAEGEHGFHEAAEAHGCEGCHGAEGCBGCDGDEGHHADBAGBEDBDBB,False +181,7.0,4.0,3.0,4.0,1.0,4.0,0.0,2.0,CDDAFABHAECADFHCFABFABDAB,True +182,7.0,17.0,14.0,12.0,11.0,8.0,17.0,16.0,ECEECHEGDCFDCFDCEDBBGBGECGBHGFFGCBHEBHABAGBHFBHDGHBECBEHHGCGCCGCFGHABADDDHGDHEBHBCGGFFACHAEADBHDGHBGDB,False +183,18.0,19.0,14.0,22.0,20.0,25.0,20.0,18.0,FBAHCEHGHHGAEDEDDHDHGFACFDBFGCCBHGHHGBHGECBHFDEFBEBHECHFGDFHDEHAGGEGDBGAADFADAADGADGHFFEGCABDGFDBDECDFAFAEFCEFCADGFDFFBFFBHFCECGEBGEBHEADBBDFBCFDCFAAEGBEABE,False +184,9.0,17.0,14.0,14.0,12.0,19.0,15.0,10.0,DBDDHCBBBBGGFEBFEAFGCFDCADCDFEFGHFDHBDCECCFDCAEBEDHFDCBDGBACACGECFEHDBACBFFBFFGGDEGHHGCHFBHFBEFAEAABGFBGEGGFGH,False +185,5.0,15.0,12.0,28.0,11.0,16.0,11.0,13.0,FBEBDDHEDCEGFGGBGEBDBBHCDGDDHBDHECBDFBDEGHEFHEFEDCDHGDADDABHABDCBDBFDHGDFDCGHCGDCHHGDADDEDDAFDFFHFFECDCBBFFCFFC,False +186,3.0,2.0,0.0,4.0,2.0,3.0,6.0,2.0,EGADGADADBGHFGBDGHFGEF,True +187,7.0,12.0,9.0,16.0,4.0,16.0,12.0,10.0,BDFDFFBBBEBBFCHHCHHFFEGDADDFDFHAFDAFBBGDBGDBDDGCDFFDGDGCBCADGEHGDHCCHACABHAHGCFGFFGEFG,False +188,9.0,14.0,12.0,11.0,9.0,6.0,5.0,4.0,DFBEFDCDCBAFBADEFDEGCEBCGFCECHDBADBADBEEBABGHBACBACBECGACBBCADDHFGHECD,False +189,15.0,22.0,16.0,23.0,11.0,18.0,13.0,25.0,CHGBHDEHBEHDGCDFHFHHCHHGHEDDBGHACHECHBHGDHDCHDEAGEABFAEFACBBDDBDBADACDABFAHDABACBHHDHCAHFFBBDBGAFGFFBBABCGEEFEDCCDCBDBFDBFEFGGFHHFHDCADBDGFCGFH,False +190,23.0,11.0,18.0,25.0,19.0,12.0,19.0,38.0,DEHHAGHADHGCHACEDCAGEGFDADHADHDDGEEEEHFHGCAGEDDFHHEHHDHDGBDADHECEEGAFHDBHGBHGBDAHAEHABHBBFDDCDAHHGHHEHFGHCHDDECBFCADCGDCGHCGHGAHGABFHFHHFHHEHHBBAEDAEDFCCECAAGACCACAF,False +191,5.0,6.0,1.0,7.0,12.0,13.0,5.0,13.0,HEEFEHAEHFFHFGDFEDGEGAFGFHGEHDBHAFHFFEAHEBEBDFADBHHHEHBECFDBFD,True +192,14.0,9.0,19.0,16.0,17.0,13.0,14.0,12.0,FBCCBDDFFDHDDHGEFGEFGFHGFBDFCEEHACCAEEDBFDEDCHFCBAEFCGGAHFADGAHEHHAHBACBCEDEEDCCDCGACGCCGCEGDECAECAFGABGBHGDDEAEHA,False +193,13.0,11.0,10.0,13.0,18.0,18.0,16.0,24.0,BFHBGDBGHEFHEGEEGAAFHDFECFEAHEAHDFHCHHEHFAGEGCCHHEDHEDCCDAGGAGGBDCBDAFHFFAFDAFHGCHGCFGHGHHCHDBHBFFADFEDEBHGGFBADHAEEEHEEBFB,False +194,4.0,3.0,4.0,0.0,0.0,3.0,1.0,3.0,HCHBAHBAGFABCAFCFC,True +195,5.0,5.0,1.0,2.0,4.0,4.0,7.0,2.0,EFBGHBGABGADGABHAGDBECGAFGFFEE,True +196,16.0,12.0,12.0,7.0,4.0,7.0,9.0,12.0,ACGACAHFFCEACGGDEADCAGCFHBFBEFDHDBHAAAAGHBBHCBHGBAGBACBDCBHCBACDECHHAGHFHBGADFA,False +197,11.0,6.0,8.0,7.0,7.0,10.0,12.0,14.0,GHFFHACEECGEGGDBGBBFAGFGCHGHDGAEGCCBHCBHAFHAHDAFGAFADCADHAHHBCDFGEAHEHHFDEF,False +198,21.0,16.0,17.0,15.0,22.0,24.0,21.0,20.0,AEFABCDCDABGHHEHDFBBFCAGGAEFCGGCGABGACGHHGDGBDBBCFACBDFHHEHFCHFCECHFCHGEHGBFFECFBHFGHFEDFDCFCEAEEADDGDEGFEGFABFHBFAEHEDDADAAGAACEACBHEBFEDFAAAGGEGGBHEEHFEHF,False +199,3.0,4.0,1.0,2.0,7.0,5.0,9.0,5.0,HFFFEGEEGAHGBHGAHDADCBGGEEGEGBEGBFFH,True +200,27.0,17.0,26.0,18.0,16.0,17.0,15.0,13.0,BDEBEEBCBBCDFCHCCABDEGCGACGACACFGDDGAACBACEEDBDDCCCHCDFAHBGEBCHGGFCGHHHABHBGAEHCBGCDAEDFEFBEAHEAFFGDFHDHHDFDBFEBAAGAAGAGFCBCCEACEACECFAFAAFAADCFDAFDA,False +201,14.0,18.0,22.0,18.0,23.0,25.0,18.0,25.0,EHGEHCBHCHHAEHDEHDEAEBCEBCEGFAHFAHCEHBFHBHHBHEBCFADGHFGCFBAFBDHCHCEHADGBDFBFFBHBGGEFFFDFEBCDFDHCDHBECDEHECBECEFAGFCGCAGEHGEDEFHFCGCCDACAAFDAHDFFDBGDGAFGCBCDFEGFGGE,False +202,6.0,4.0,6.0,6.0,4.0,7.0,2.0,1.0,BADGAEAACFACGEFBACCEFCEFBDHDDFDBFDCF,True +203,4.0,8.0,7.0,5.0,6.0,6.0,6.0,7.0,EHAECAEHBEHBFHBCDBAEFEGGCFGDGHHACBBCGBDHCDFCDFGBF,False +204,6.0,15.0,10.0,9.0,18.0,10.0,16.0,17.0,EHHEDFBDFGDGEDGHFEEDDBGFADFCBHCBHFEEFAECGHHGBCEDCEHFACGHEGHEGCBGHBCHBEFFEHADBAGBGHCHEEBEAGEBGBHGBHCBG,False +205,6.0,8.0,4.0,6.0,11.0,10.0,4.0,7.0,BDFBFFCHFBADBGFCGCCEEAAHFAHFGFEEFBEAHEBDEBDFHDHEGEEBEHDA,False +206,7.0,11.0,7.0,14.0,12.0,11.0,11.0,15.0,DFFHFBABAHBEHBEHDHGCHFDFAGCGHEBADHGDHCEHCEFCEFGFFGHGCDAADGBBGDBGEBFEDHABHDBCDHHEFDEGDEDE,False +207,14.0,19.0,19.0,16.0,15.0,16.0,25.0,15.0,BHBBDBDDGDAHEGEGGECDCCBCDAEBGEDGHDCHFEHACACCEDCGFGFEGDGGAGGAGGHFBEGCEGCEBCAFGHEBHDAEGAFHHCADFBBFBFFDHFCHFBBGBBCBACGFDAFHBCGFCGEDGADEAHFCHBG,False +208,14.0,24.0,23.0,25.0,20.0,23.0,13.0,19.0,CGFHBECCCACGAFFHDFHDAHCCFBDFBCCBGFDAHDABGABGHBFHCDGDDHBHEBCEDEFFEFFEFFCDDGGECDEFDADDHEACEAHEAEEBFBFGBDBBFCBDCFDGFHBBDBCGCDAHDCCDHCEEFEGGECBBABDCBDEFEHHEHHBHBADFA,False +209,5.0,7.0,7.0,12.0,11.0,5.0,6.0,4.0,BEEGAGCAHCFDCAHCEFCAFGGDDEDCBDBEFBEDDADDHDDBBDBEEEGCEGHEF,False +210,21.0,21.0,29.0,26.0,25.0,22.0,25.0,25.0,HGGGCBGCBGFDHCEGCBADBADBDFHCBHDBEBBEHBEFBCABCACCFCEFHAFHGFGDDGDDHHDEDDHCBEDDEDCBGGFAADADGACHAFDBEBEECDECEFGGHECHEFHEBHEDGCDCABCEFGEGHFGHEECDBHDFDFGCAEAGEAHCHFAHDGHACFACGHHGDHGCAAEFAFBCBECGFCFFCA,False +211,25.0,20.0,15.0,18.0,16.0,31.0,22.0,17.0,GDHFDBEDFEFGAHDFFDBECFDAFDBFGBDAEGAEGFDCFDCEACBAFHGHHFBFFBHHEAFBAFDCFBGAGGACBACFCEACEACHHGDHGCGFHGHAGABGBGDFHHFCACEBHEDDAFDAGCADBEGBFGBFEFFEAFGCFBHFEHGABAABAEGAFDFB,False +212,11.0,12.0,15.0,21.0,14.0,13.0,13.0,22.0,FDHBAHAHFDBFDFCHHEFHDFAGBADBADCHDFFDABDHCDHCGAGFHDDHEEHBHHEHBCBGDGCDCDECDEGEBHEHHGHDFBCFDAGCAGCACCEFCDBGEBGEDEFGHCGHEDHEA,False +213,26.0,25.0,22.0,24.0,22.0,21.0,23.0,28.0,DGGABBFFGEFGHFBHBHFAGAHGECGEBAACCADCHDBGDHCDFEDCCCFBFAHDEGGBGECFEABGHDEADGBGGFDEFAABAAHAAHCAHGFHBFABFAEHHCHHCFBEEDEEFEGDEHDHHDHCBEABAGGAFGDFDCBCHBCHBHEBAAGCADCHFCFDBBDBCDECHACHDBEDHEFGADGHDBE,False +214,17.0,18.0,21.0,25.0,26.0,17.0,17.0,17.0,FEFAEAHHABBGBGGCDGDEEDAEBGFHHCADDHDDEDDEAFECGGAGGEBGBACEEDEEDHDDHGBHEBCBHADFEDEGGCDDBDCFCHFEFAHFHDBHDBHAGCFEFFEBEEBEEDGEACFABBCBFDBFHFECGHCGACDCCDCCECFHAACADC,False +215,3.0,8.0,12.0,3.0,11.0,1.0,8.0,8.0,ECHEGGEHEEBCEHGGHBAADGCHBCBBCHBCHBCEDFEGHEDCGCCECEBCGA,True +216,3.0,7.0,2.0,4.0,7.0,5.0,4.0,9.0,EEBACHABHEFDEHHEBHAFHFCHEDGEBBDFBHGBHGFDG,True +217,24.0,19.0,23.0,32.0,19.0,19.0,18.0,19.0,BDFHFFHEAGCGGEHGAHGADAEDAEGACABCBFDEDDEHDGDDEDDGCDGAFBBEBHFBDEADCDDCHBCEAHDBHCBHCACBGCGFCGFCGDHFABCACCABHEEHDGBFFDFFBHADDDCAAHDAEFEEFBDFADGADHADFGDCGCCBECADAHHCFDCGBEFEEDHBA,False +218,15.0,9.0,15.0,14.0,9.0,15.0,10.0,14.0,EDDHBDCEDAHHCDHCDEFECFDDBDEGDCAFCAGCHCFHBFBDFCABCEGEEHHGFHAFCABHABDAFAHBHHGFCGFHGBAAFDAFAAFEDFAGGCCGC,False +219,24.0,26.0,20.0,28.0,17.0,21.0,17.0,23.0,FBGGAGHAGHGGBGGFFDAFDHDCFBFFHFDHDDHFDHFHCFGDHBEFCEACHFEHCBADHDBADCEBCDDAGDAFDAEDEHCAFDAFDFBBAGBGHBCHAFECHDCEBBEABGFHEBHDGCEFCBACBACBCCBHBFGDADAAHAHBGDBDEBGECEDHDAEBAEBAEHADCDBC,False +220,10.0,6.0,12.0,8.0,3.0,8.0,5.0,9.0,DEDDFFBCFCCAGBFHBACAACAHFAHBEGGAGCDCCDFCDFCAHCACDHEHHABGDBHFH,False +221,18.0,20.0,25.0,20.0,16.0,11.0,30.0,25.0,BFFBEGBGFBGHBEFEDHBDCAAHAGHFGDADCBDBBDECAEBAHGHGABBHHBGCGECEECADDDGHDGBBGBCGHHGCHCCHCFHGGHAAHAHGAHGEHGDHBEGFHFAHGADFEGBDHFDGCDGCFGAGCCGACGHEGDCCCABCECGEHDEDDCCECADCB,False +222,19.0,19.0,21.0,28.0,17.0,28.0,23.0,16.0,FFFFGGBAGBFCDFCBFDGDDEDDFDEFCHDCHACAAFFDGFHCFBCDGEGEECCCBBAHHDEHDECFGGGDDGDDGDDCBACBABHCDCFDCEBEGBCHEFHGBHABAGFGFADHAGFAEFHEBBFBEFCGFHAFGADGAFHBCABDEDDCHFEHFEGAEDCGDFADBAG,False +223,23.0,19.0,28.0,13.0,18.0,28.0,23.0,33.0,GHBCHBGHEHEAHDHGDCFBHGCHGCFGCBGBGCDHEFAGHEGAABBHECFCFGDEHCEHAFCADAGDFGDHACBACHACHCHFBEFCFGCHHHHCHBCBEDBFHBEHBAGEACHACFAGGHGDHFFAFEADEAHFAHCCHEFGEFBFCBHDFGFFGAFDACDECECBEBFHBAGCHGCAFFAFF,False +224,3.0,2.0,2.0,3.0,1.0,3.0,0.0,0.0,DAADFBDFBCACFE,True +225,18.0,28.0,26.0,15.0,16.0,22.0,28.0,24.0,CCBGHAGAEGAFGBHGCHGBBBHBBHCBDDBFDFGECEECAGHEBBGBAGBFGCHCCDGCDHEAGCBBFBBFCBGGAGBDGHGGHGHHFHDCEDAFGHBGABHBEAACGCCHCCHBHHFFFFGCFHCFEDACFGEFCAAGDCDDHDBAABFACDABEGCEGFEHFEFCEDBFHBEHF,False +226,0.0,1.0,4.0,5.0,1.0,5.0,5.0,2.0,DBGCFGDHGFCGDHGEFCFDCFD,True +227,9.0,11.0,5.0,9.0,13.0,8.0,7.0,11.0,DGHBGEBGHACBAFHAFHFHDDHCGEAGEDEEBEAGFDFBDFBHFHCDHCEEAFBABBEEBEBDHADHGEEAC,False +228,3.0,5.0,4.0,5.0,8.0,4.0,5.0,8.0,DCEDEHGEHGFCEFGBDHBDCBDHFFHEAHEACGBGHAEHEB,False +229,5.0,2.0,1.0,1.0,0.0,2.0,0.0,0.0,ABABFACFADA,True +230,17.0,15.0,18.0,10.0,25.0,10.0,12.0,11.0,ECCHCABEAEAABAEBGEBCEBGAAGBBDFHDEHDEHCHHCHCEHEEHCGBAFCDEEFGEGGCFDEFBBADBEEFHEAHECGFCDAAAFBBCCCACBGGBAEDDEGDECCEFAEFAEG,False +231,31.0,18.0,29.0,27.0,23.0,14.0,25.0,29.0,DGBAGHGHDGCGACBADBDDEADFCHGDBFEBHEBHEFHFCDFCDACFGHDDDDDCGCEAEEADCBDBGGHCAACAEDACHEHHAHDDFDEHCEHCECEHHEAFEABCGEGABHEDHEFAGCGGCGACDAGDACAAHACBBCDACAACHCDHGAHGFBDAACEACECFEHGGHBGHBCFFGDBGHBEFEHHAHBAG,False +232,9.0,27.0,30.0,27.0,17.0,16.0,18.0,20.0,HDBHDCCCHHCHECBBCGCEDCHCADGDBBEBGEGGFDFDDGDBBFHCEEDFFFHFHHDGCEBCABABDEHDHCDHFDHFDHBDHGGEECBEHBDFDDBCDCCBCCGCAHDBBBBFBEHBEGBEDDGAAHCBECBCCBCFFEDFEDCCGBAGACGDCAFCGFGG,False +233,13.0,14.0,9.0,12.0,10.0,11.0,7.0,12.0,CACBADGHDGHDFHDFHDEEDGEBBEDHACHABBFCFAEHACFDCEAHEABFFBFEAAEBCHDGBDBBGCBFEAFGDCDHHABHABGF,False +234,27.0,12.0,19.0,20.0,14.0,11.0,16.0,19.0,DCEACEBHDGHAGFBGABGABGABCHFEADDADAHDHDGBFAECCBCHHFADFEFAHDAEDCHCHADBFDCGDCHECGAAAAGBAEEHGCCGEAGEFCDFDGGCGACHCEHCEHDEHBCADAADADDFHGAHBAHBAF,False +235,10.0,14.0,16.0,10.0,22.0,13.0,14.0,12.0,BCEFFEFBBGBBGEDGEABFACCDCCDHEGHCBDGHEEEFAGBHGBEEHEEHDEFDEFCECDECHGGAGFFEDGHBECBHCGFEAAEAHGBHGBHEBAFACCEDCACFDCF,False +236,7.0,11.0,9.0,8.0,13.0,11.0,4.0,12.0,AEBEHFHFFGFHBFHFAHBHHBHFEFABBEBAEFCEACHHDGDEGABCCBCEBDEDCEACFHCFDCHDEEDBGDE,False +237,23.0,30.0,14.0,18.0,17.0,26.0,17.0,30.0,DGDDFCEFCGCBBHACAFCEEEEAADADEHFABBADHADHFDBFHHFHDFDAFEADBADCAFAFBEBBEBBCBBCFBEFBGFBHBBFFHFAHABHEFHBFHEGHAAHBAGBGFHAFABEGEGGDCGBHBCHGHFGHGHHCDEFFHCBHBBHGEHGDHFDHCDBDAHGHBEAACFG,False +238,19.0,27.0,27.0,14.0,19.0,23.0,28.0,21.0,CCCACCFBHFGEBABBGFFGBCHBFAAFBAHCAHCBGABGADDABDAFDBCGECFEHBCHGHHGHEGDEBFBBCGBGHBGFBCCBDGDCHACHADFADEHDEHEGADGAFBFGBEGHFHEADFCCGCCGFCEFGHFEFBCDBGHHECGBCFAEBBCDGAGCAGFFEHGEGFEGBECHE,False +239,12.0,6.0,10.0,11.0,16.0,6.0,12.0,10.0,DBDGGDGCDECGHCHEAHGDEFEEFEBBHABCCDACGFEGHECAFAEDAHAGCBGAHGAGFABFDEEDGEHEECEDCEAHDAH,False +240,12.0,11.0,10.0,12.0,15.0,7.0,12.0,8.0,EHCEBGEBCADCDFCEGBEBCEBHDGAAGDGHDCFDEEGBEFEEFGEHGHBEABEAFCFHCGHCBADAADADGAEBBDDHDFGACGA,False +241,24.0,20.0,23.0,18.0,18.0,16.0,33.0,12.0,DCADHACHFFHADCCDEEDCEDCFAAFGBCGACGAGGACHBBDBCCBEFBGCDGHFECABCACGAEFAECBFFFHGCAECAGHEHBFHBAGEFGECGHBABCADDGGDGGDGGCGCFFHGGEAGEGEEBBEGAGFFGDGGBGDBGDCGHAAABGEBEBDDBDAA,False +242,2.0,5.0,2.0,2.0,7.0,2.0,2.0,4.0,EHCHBDECDEGFEAHHABBEBFEBGE,True +243,5.0,8.0,9.0,5.0,11.0,13.0,13.0,9.0,ECEEGBGFFHFBEFHFDBGDBGFHFFHGHCGHEACEABBFEEEEGCGGCFBCDCCEHCDHGAFGABGHFGAFD,False +244,8.0,13.0,8.0,11.0,10.0,14.0,17.0,10.0,EGDHGCEDHEAHFBCGBAABGEDAEDAEGGDDFDCFGCEGCGFADFCFEBBCBFDGFAGFEDFBGFGHBBHEDHGGHBAFBFHCFHGBHGB,False +245,10.0,16.0,19.0,10.0,13.0,11.0,21.0,15.0,BEEBGHAGHCCFEDFGFHBHHDFDDHCFAGFAHABFABGAFAACBECGGGHGCAGCHCEFGEHBEHBGFGEFCHDHHDEBCABDGBGGCGGCBGEBGDCCCCDCBDEBGEBECCH,False +246,9.0,13.0,8.0,9.0,4.0,11.0,15.0,3.0,BDDBDDBAGAEGABGEDFCBCCFCDABHCBGDGGEGCEFAGBAFBGGBGGBDFFAFBCGDHGHFFCFAGFAB,False +247,24.0,29.0,19.0,27.0,21.0,19.0,25.0,36.0,AGGDCEDBEDGADBCBEDBHDFHDBEFHEFEEGEGDEABEFHDBHBHHFFAFBGGHCFFEAFDABEAFCHDCABBBCBEEBFBGAGHBGHCABCAFHDGHCHHCDGADHADGFHGFCGDBHBCHBDAEGHHGHHAHCAHDDBGHBGCEAHGADDHDECGEHHEDEGFEDABHABHABCABDABDACHGCBGDHHFHFFGC,False +248,23.0,15.0,19.0,20.0,20.0,17.0,12.0,20.0,AEDAEDAEFADFAHFAHEEHBBCBBDBCAFAAGCCGACEHEADFHDFCDAHGBEFFEFDAFGACGECEHHGADGBCAFCGCHDDDGCFFDBCHECFEHEABEABDCBHFDHECAFDABDAGEBGHGEHDBADBADCHCHHCFHEEH,False +249,5.0,8.0,8.0,6.0,8.0,12.0,5.0,4.0,DDADDFEDFHACECHGGHCDBBFFBEEBGEBCECCGBEAAGAEBFCFFHFFBFFCF,False +250,9.0,9.0,5.0,9.0,9.0,5.0,9.0,6.0,EBGEGDECAEBBGBFDBACGCBBCBBFDADDACDGEDGHDHDAHEFHFGAEGHFGAAEHAE,False +251,3.0,4.0,6.0,7.0,2.0,6.0,5.0,5.0,FCHFEBDGHDHADFGGFGFFEDBCCBCCHGCHDBDDAA,False +252,23.0,16.0,22.0,22.0,17.0,24.0,15.0,22.0,GDGADAHGFBBFBCHBDHBDCCDHEGADCHBBDFHCGGCEFBECHECEACFDBADEACEDFFDFFDFCEFCGFCHFGAFADGAFHAEABFDEDHHBAAAAHGABGDBFEHFHHFCHDCEAEEAEDCFFAFHCHHADHACHAEDABDCCGGCGFCBFGEHBD,False +253,28.0,21.0,24.0,17.0,16.0,23.0,19.0,22.0,HBGAFCHGAFDHGAHGHGDDGADGECAACFACBDGFCBAHBHDBFDEFABFACAEGFHGBDGBFHDFHCGBAGCABEGHEFHECCEAEHADHFDCCDCCEAFBDDBFHHFGHFCHCDHCFFCBAEFAEFEEAAEBFCBAABAAHEABBAFBGCBGCBDFGAGCCDECAHH,False +254,22.0,21.0,35.0,22.0,18.0,16.0,18.0,17.0,CGFCBBCBBCFBDHEGBFDEHCCAECAHAFDEEDAEHAEBCHFHBFHCHBGEACCCCDCABFABCDBDHCGCCGDCDDADDGGEHFEGCCBCBAFDEFDAADFAGGHECHECHECHAHGCFBBBBAGGEDBFDAFDCEDCEDCADCBHEFCAGCAGCBGFDACAACGGH,False +255,16.0,23.0,16.0,16.0,20.0,17.0,25.0,22.0,FBDCDGFHBEHADAEBABHAGDEEDGEAABDDEEFEEDBCGGDHHDHGDABBCBBCDHCDBGDBGCHGHAGFECEEBEHFGDFACHGHHGBHCEHCECABHADHACFBBAEFCEHAGHGEHGFHGFGGFGBFBFCBGCFGEFGEHBBGFCAFGAB,False +256,4.0,5.0,1.0,1.0,3.0,4.0,5.0,7.0,BHFAGFAFHABDAEHHGHHGEGBEGBCBHF,True +257,15.0,16.0,15.0,21.0,14.0,16.0,23.0,29.0,BBAHCCDBGFHGFGFFCFGCGHCGHDGAGHDCHDEABEBGGFDDFHDHHGHBAHDGCAGBGEBHBCHGEFGEHGEBFECHEDGEHBAHBEHDACDHHHBCHBCHAFHDCHAHGAGGDDBDDEACBAEEAHDDFFHGFHFFDAEDACDFG,False +258,25.0,18.0,28.0,20.0,16.0,20.0,26.0,30.0,GBDGBHAEEAHBAHBCHCCHCEBCECDEAAFHHCGGCFFDFBAGBHGFHDAHBACCADCAECAFFAFFGGEGCEACECCFCBEAAGFCFFGGHCDECBGHBHACAAFDGHDCHDCFDHFEHFDGDGHDCHAEADGGEADCHDHBGBDGAGGFFHHFHAGHCHHCDBGHBEHDEHGABBADBCG,False +259,10.0,4.0,2.0,8.0,6.0,7.0,4.0,6.0,BFAHHADDBDEBDAHFACEADEFDEHDGAGFDGFAEFBGFEAACHAH,False +260,17.0,18.0,20.0,22.0,23.0,26.0,23.0,18.0,CGCHEEDEBDHDGEGFEFFCAHGBHBEHBACAAFAFFDBFDCFAEFADFAEGBBHADAGGHFGCCGCGFBDFEEEEADHGDCEDFGDEBDHBGHBFFCAFCECGEDADDBHGBECFEBFEDFDDEGDHCAHCFFGFFGAHCDHADCBECBHHBHCGFGGABGCEGFE,False +261,27.0,24.0,20.0,19.0,30.0,32.0,21.0,26.0,GEHGECEEBEDACCACGBFGFCDBHEFEEFGEFBFACFACFAFFAGDACBAGDEBABFAEDAGHAHBAECAFDFEEBBBFEBDEFCHFHBFHFEHDGHBGHCCFDDAADEAEECGGHGFECFEDFEAFACHACEFBEFHHBHHFEAFHBFBBFBHFCAGHHFHHGHDCHDCHFGAGDDGCAGDEEAGEBEDAGHADBBB,False +262,24.0,26.0,23.0,23.0,21.0,23.0,28.0,24.0,CFDHHBBHEEHEHHEFHBDAADAFDBCDHDDFGAFCACEADGBEGCGCHEAHGADGABGADCFFBFEDDAFDCFHBBCFBGDGCHECBEBBCABDAECAHAHHAHEBHDHHFAHGEBEHFAAGBAGBGGCAFAFBAFBDCDCCDGGDGBHBBCBGFGEEGECGEHECDFCBFGBDGCACEFGEGGFHGFDGF,False +263,0.0,1.0,9.0,1.0,3.0,4.0,6.0,1.0,CHCCEFCGGBGFDGEGCECCFCFGC,True +264,6.0,5.0,5.0,2.0,0.0,4.0,6.0,0.0,CCAGBBGDBGDBACACGAGGFFFAFBAC,True +265,4.0,10.0,10.0,7.0,1.0,8.0,4.0,4.0,BEFBDFGDFABCABCHFCDGBHBCAFCAFDBDBGGBDFCCBCFHCDHC,True +266,22.0,29.0,31.0,16.0,20.0,28.0,16.0,14.0,EHAHCBHCBECFGBBCHEEBAFBHHAFGBFDBFCBFCBFCBFCGFGECBBGFCEFBEFDEDDGFCFCAGCAFCEGAAGAACDCFGAFGAFHBGABDAGAHCAECABBBCFBCDEAAEBFBBFCCFCCFABFDDFBEHBFGEDBEDEHAECBGCFHCDECACCDEFDADEHCGDBHH,False +267,19.0,18.0,7.0,10.0,13.0,13.0,13.0,11.0,HAHCGEBDCBCBBEGHFGBCGAAGBGGFDGCAEADBAHBFEFFEAGEHCHHBAHAADEFGEAGFFEFAEFCBAABAABEAFGAEGDEDBBABBFBHHDDHDBFD,False +268,17.0,10.0,10.0,7.0,8.0,5.0,14.0,9.0,DCADHDGHAGBAEHECHCGADHCGAEGBEGAEGAEGACAHGHDCBGHBGFBCAAAACBBEEBGBCFCAFDAFDHFGABGA,False +269,1.0,3.0,0.0,1.0,3.0,4.0,3.0,1.0,GHGGEBEFBFABFEDF,True +270,23.0,19.0,18.0,18.0,15.0,13.0,11.0,15.0,AHDAFCAECAFBHBCEFDEFCEFEDAADBADCDDFDAFGEHGEAGHADBBEACFGBDHADGCCABHHGHFBEDGHFEACEFCBAGAAEABEABGABHBEABGABFCBACGDDHFCHBCHBHHCEDCDDCDBC,False +271,7.0,9.0,4.0,6.0,4.0,10.0,14.0,6.0,GDDGADGAHAAHABDGFFFECFBHBEGEGHEGDCABGGFFHFFHFBGABGDBGCBGFGCB,False +272,9.0,5.0,1.0,2.0,6.0,2.0,1.0,1.0,EDAEAFECFGHAABAEDEBBEBAABAA,True +273,6.0,7.0,5.0,6.0,3.0,4.0,5.0,6.0,DBGDAGHAGECGFBHFBGDDFEDFHCBBEHHCAHBACBACAD,False +274,13.0,30.0,20.0,14.0,22.0,14.0,15.0,16.0,HBGBBDCBAHEFEBDBCABCGFGEHGECGCDECDBFDECGHBFHACDCBBHEHGGHFGBBBBHBBHBBGBEABHDBGDEGEFDECCFHEBHEHGEFCFBCFCDABAAHEECEECEDCEDGEBFEBAABGABCBCAAFDAFDHFC,False +275,5.0,8.0,10.0,12.0,2.0,10.0,10.0,5.0,HGDDCDFCDBGFCGDBGEAFACFDBDDBHDBCDCCFGCHGDFGCFDABHGBAGCGFABFEHF,True +276,5.0,1.0,0.0,3.0,1.0,2.0,0.0,3.0,BDDHFAHAAHAFEAD,True +277,24.0,23.0,18.0,24.0,16.0,33.0,19.0,28.0,ADCABCHCAHCAHEADEAHBGBCGFGFFGAFBDFGFBGDEGDGHHGHHACDDGFFAFFBFFEFADHDDADDFFAFGBFBBFHFCHBDADEAHECEDFDGFDFFDCBBHDAHBBHCEGEBHHBFFCCHHHHCHBBHDHAGCAGEDEHDGHDAFAFBBFABFAEAAGABGFEHCCBCHECFEDFGFE,False +278,12.0,29.0,23.0,26.0,19.0,18.0,23.0,13.0,BEBBEHBCAFAHEDDCDBBDBBDAFFAFCADCGGBGGCGHCFECEBDECGEHGEADBFDHFDGCDGCBCCHDBEABDCBDEBEEBDCGECBDHBEHEAGAFGHFHEFBBDBGEBFHGGHFGFDGCDGDDCFFFDFECCGCGGFBDBAACHEDBDDBGCAGBBC,False +279,16.0,11.0,17.0,16.0,19.0,22.0,19.0,14.0,GFAAFDCCEGCHGBEGDABFBDFEFEEBEBGFCGHHHFHAFDADEAHACBFCDFHFGCDACDFCGFEDFEGADGAFCEHCAHBBHEGCDDHDCAFCAFGEEGEEFBEFEHAHFDEFDBGDBGAFCAGCGGCGHE,False +280,10.0,14.0,13.0,11.0,22.0,14.0,17.0,12.0,EHCECEHBFGCGGCAHCDGCGGEDBBBFHCFBFBBFGHGHFABEAEGACGACBFDBCEECDEBFEBDGHDEBEGGECGEHGEDEEHFEHFEGFAADGADEHDAFDHFEEFCBA,False +281,32.0,31.0,18.0,18.0,36.0,28.0,25.0,12.0,GAHFABEGCGAEFADGADFABCADAEBAEFEHFGBGCBHDAHAABBBECFEAEEFEEFEDAEBAECADCDDBBBCBBEDBFAAFHEEGFCGEEGEFGEFAFDABCABDAFGFBGFEGBEACGGHFGAFHBBDEEEGGBHGFFAFFGEFGEBGDCHCHGBBGABEABEFEDADCEEFDCDHCDBGABAACAHCEFCEFBEB,False +282,19.0,24.0,17.0,28.0,20.0,14.0,18.0,11.0,CEGDBCDFGFGCADCEEGFABEDBDBBDEFDEADBGBEGBACDDFDHFBHGGCGAEGHEGHECDDGDFGEFABAEEHDFBDFBEEBHCDCCEHHDCGDBHDFDDADDEEDBBBBABHAHDABAAGADBCFBCBECDAGECGACGACFABFA,False +283,26.0,21.0,30.0,21.0,22.0,23.0,22.0,14.0,ABEAFHABHEFEEFBHDAHFBHFBAFBCBGGHGDHFDHFBEBBACCAECAECACGBCFFEFCEGGACBCDFAAHABGDEGDEGDACFEGDEGAFAACCBEABGAFDCFDFFGACHCEGCFGABCHGAHCDHCDCCDCGABDFBDEDCGFFBFEACCDCHDGGCGEEAEBAGDCDDCEEB,False +284,14.0,18.0,15.0,12.0,15.0,14.0,12.0,12.0,DHBFHFFADGAHCABFABEEFDEAGEAGDDBACBCCBGCBEEBEAHEHCFFCEFCBCGDCGDEGHGGABADBEEBEHCHHDBEGGFFEFDADHAHBBDFBCCBGABCFHCFA,False +285,16.0,15.0,17.0,12.0,11.0,20.0,18.0,11.0,HGHCBHCECFEHFEGDAFFGFEGFEAFGFBGABDBBGBACBGFBECAAFDAHHFGGAGGAEGCBDBBDHEFGGDGEHAHADEADEFCCFCFADDBCCBCABHAFFCFGCFDCFACDBCGH,False +286,11.0,13.0,7.0,7.0,10.0,17.0,12.0,13.0,FDGFDGFHABDDHFAHBHFFGCFHBGAGFFGFHHAGHEGHCGBCECDECDBHBEHBEHCAFGABAFBGFBEFGEABFBFDEFAEAHEABC,False +287,8.0,6.0,3.0,14.0,2.0,6.0,4.0,6.0,BGDFDCCDGAFBADBDHHDHCDHAAFAADBADBFDEFABDGHEGDDFHD,True +288,13.0,9.0,15.0,13.0,19.0,11.0,16.0,13.0,GGEDADGABGCBHAGACCFCHECDDCBAFEEHEBBEABEACFACEDHEAFEGFGDAEAAECDEFEHHEHBFFDCFDCDAGDHEBHCGHGGHCEFCGFEGEDGDCGHBGH,False +289,21.0,24.0,27.0,24.0,13.0,22.0,21.0,28.0,EBFBBCGBDHCAHFAHBBHBDHBDHADECDCAHCGHGFHADHDCHFBBAHBDHECABFBFFCDFGDFECBECBCHEAHFHHEHGGFAGBDCEHCFHCGGBEGFHBFGAFCADDFDDBDFCAFCHFDDACGACGDCGAGGHDEDECDAGHBFABABBEFBCCDEAHGAHGCCGCFAHDGHC,False +290,11.0,5.0,20.0,12.0,8.0,15.0,4.0,7.0,CBCCHDDHADEADEFDAACCCFFDFCAFCADCGDFEDCECCECFFHFFAGFCEDEBFFHCHGCDBHGCFDAFBAEHACCACB,True +291,20.0,16.0,14.0,23.0,25.0,13.0,17.0,18.0,GBEGBEGFEGFBFDBFDBADHAFBDFGDEGDGGECCECAEAADAACHHHHBHEGDADDBHAAAEHEBDEBGEAEHDGHAAHFABCEGDFGFCECDGDABDHBDECCABFBEEDEGFEHFEHGAHBDCDAEHAECDCFDCEDHGHEC,False +292,22.0,21.0,19.0,22.0,30.0,26.0,23.0,31.0,AHGAHGABADGFGGEEAEFDCABCFBCGBCBHCBCFEDFEDHADEFDFBHCBHAHEAHEHHEHEBGEAGEDCEHGACGDCFCEFDEBDEBDFHACEEHBDDGGEBCEBCGHFGEABFAEEBHABGAHGAHDHHDHEABEGBFAEGHEHCADFFDFGAFCDDGFHFFGFFDEBCHFEGFCDFHHCHFBEGHHADH,False +293,16.0,24.0,24.0,18.0,24.0,17.0,14.0,18.0,BDDACEACHABHABHECHGHEGEEFCHFAFAGFBBBGBEECEEHEFDBDDBDDGCGBCEHCEDCBFABFBBCCECCGBEBAABHECEGCEDDECFECFHCFHCGBCFFDDFADFAHHCGBBBCAFEBHGDGADGAHCBEAAFGDBHHEDCEDFEH,False +294,32.0,23.0,12.0,12.0,9.0,21.0,14.0,23.0,BCGBDHDCGGGDAFDFFBCABCABCFGGFAAFBHEBHGBGGDAFAACABHBFFDAFAHHBHHDHGDEADBHGBHBBHBBFACCBECAAAHABHAEAEDFGCCEAFFHEBHFHHEHDABAAGAGHADAAHAACEAHAAFFBFFBFFH,True +295,25.0,28.0,34.0,29.0,21.0,15.0,21.0,21.0,GBBDDFEAEADECDAGBCFBADECDBBDCCGCAGCDBCBBCBDCBGCEHCGACACFBHFDDBCHFCGAGGECFFABDEGDEFDHFHHBBHDAEDBEDCDDCDDCDAADFACEDHHGACGBBGAGAEGFGGHCACCDHGEHGEHGHCEACBHFEAAEACEACHHCHBCBECHHFEBBDCBFCBDDBDABAEFAHG,False +296,10.0,5.0,3.0,10.0,3.0,6.0,4.0,2.0,FCDBCACHBFABDAGEAGDADEBDFDAFGABAADEADHGDFFD,True +297,18.0,24.0,24.0,26.0,29.0,26.0,24.0,26.0,HAEHBEAEEHCACDDCFDHFGCBHCBCDHFDEADBBGCBGABFAFGGHGEAGDBCCGCBDFDDFBEFBEGDEGAADHADHBHADHCDFEFFEGGEBAHBCFGCEGEBGBFGEAAEDHFDAAGHFGEEGEEDHECGEDFEBBDCCDBDECFCBBEFHFCGFEHHEHHAGHCEHCDFCDFCDHCHGGHFEFFBFHBADB,False +298,13.0,9.0,11.0,21.0,12.0,21.0,9.0,8.0,DDADBAGGAGEAGECGEFHFCCFBCABCABHAEFABFDFCHHDDEDDHADHCHABFFFEAEDCFDEGGFDDFCDFEFFEDFEBADFDDFBDFCHBGFCEDDAFG,False +299,9.0,10.0,7.0,5.0,4.0,5.0,9.0,5.0,AEBFBGFGGAGGADCADGDHGHEBHBBGEBGFCHBCHAAFAABCECCFDDBCAB,False +300,9.0,10.0,14.0,12.0,10.0,5.0,22.0,10.0,GBDGFGGEGEHGDGGEGCCGACBDBBDABDAEFABBCEAEHAGCFHDGHGGDGADGHGGBFCDHCDGCGBDAACEHCEGCEGDHCHECHCBF,False +301,23.0,15.0,14.0,8.0,21.0,17.0,19.0,20.0,FGCEGAEGEDHEDBGGECFFHEBBBFDAHHEBAEBHCHEGAAHABEEFEEFGBHGCHCAHDAFGGHGDHGFAGBABFAFHEEGEAAEDAGFAEFACFACBHFDCEHBAHCAHGAHCCGCCGEAGEACFADFHBBHBF,False +302,27.0,23.0,30.0,20.0,17.0,18.0,24.0,20.0,AACCCBGDBFHBAECFFHBHHGHAACGCHDDBFBGGCHGAFGAGGAGGAHGCHGCDGCHBHABFDBDDEEDEEDBCFCCFCHBHFBAFBDFHFBAAAFCCGHCDBADAFCABEACGBFBEEBAEHAEGAHGACBBDACDFCDGCDGHDEEDEBCFFCAACHECGCBGCEGCDAAEEHGD,False +303,30.0,27.0,22.0,22.0,20.0,20.0,25.0,21.0,FCHFDBBDBGCAADEBGFBGABGFEGHAHBADAEDACBECFFCFFGDBGAHHAEHFCAFAACEDCFFBEFAEABHDGAEHDDBGCBGEBGEAEEFBEBDHDAAACCHCCHGDAGDFCFABFHBFHBGBBDHBDHEEHECHDCADAEDGBCCBAGEHGEBGFBGCCACCAGAADAHGHHGFDABGGGD,False +304,29.0,17.0,17.0,22.0,14.0,23.0,28.0,17.0,DABGFCFHAEGAFGFBCCBEDDHFCADEHDEHGHDGADGHGGCCFFFFCCEGHEGBDDDDDFDFGDFGCEABADBCHADBGDCDAHFFBGFGGHAGHAGAEGEGCAAHAAGAAEBAGBGFBHBBHBGDCGFCDFBAEBHCFEAAEAAHGAHGAGFACFDCFEAFDAB,False +305,11.0,12.0,13.0,10.0,10.0,17.0,17.0,13.0,BFDDADEGGFGEFBEAGHAGBACAECAFFBBFHBCHGFHGHGFFGCFCBBAGCDGDDGCGHCBHDGGFHFFHGDECDFCDEAGFAFBAECAECHBHHEHCEBF,False +306,7.0,10.0,4.0,3.0,5.0,2.0,7.0,5.0,BHBHADABBABGABHDGHDBCEFEEFCEBCEHGGCGBAABGAG,True +307,17.0,17.0,13.0,19.0,19.0,19.0,22.0,12.0,FDEAAHFFBFBGFBDFGDFGDBGDBGFBFFHFFABEGGGHAAHEAFEDFCBFCEDCDAGBAFBGHDHCGHGDEGDGCBBDHGABCDHCFHEGGDBCHECEECEADEAEGAGBAEEDDEGCEGCHACBAFBDEDAFGAE,False +308,16.0,19.0,32.0,19.0,25.0,21.0,28.0,24.0,BCGCCBFCFGGDHGDADAACACGGBADDGDDGFBCHHCFECDGGAEBAEGHCDBCHEEHAEHFEFFEGFEHDCCCEGHFHHGBGDEGFHCFBFHBGEGFCGFCBHGBHEBEEBGBAGEEGHEAHEBFEBHCBGGDGDCHCCACCADBAHEDFGCACCHHCHHFBAFAEEDCECCDFCDFCDFEG,False +309,12.0,7.0,7.0,14.0,8.0,9.0,9.0,23.0,HFHHBHGACFAHHHHHDHBGHCEHEHCFHCBHDAHDAHFGDDHEBGFDDHADHBDGEEGDACDAHDAHCGHAADAECBEGEFFAFBDFG,False +310,7.0,9.0,2.0,2.0,5.0,3.0,5.0,9.0,BBABAGEAHBGHFEHBEHBHHAHBEGBGGBDACFCHFDHAAE,True +311,26.0,28.0,24.0,21.0,11.0,21.0,26.0,17.0,BFBEHBHGFHFHDDGADGADGFDCFBCHGFAEAAEAAEAABDDGHDBEDCCGFCFFCBBGGBFHCGGGDBGDBDEBCFBCABGDBGDFGEGCCAAHBGHGGFFBAHBAEGCFBCECHFADGGCECCFCBACBGBBGCCDAEHABFADDADDAFBHFCHAAFAABHHCHBCDBGA,False +312,23.0,13.0,12.0,13.0,21.0,13.0,8.0,13.0,FBAFBAECDHHEEEEAACADHEDAEAEFAEFAEGAEGAEAAEAGGBCDDFHAHHFFHFCCACAEFAHFAECHEAEDDHDGBBCBDFEHEAHBAHBAGCCDDDFGEGEFBBDBBCCB,False +313,3.0,1.0,2.0,0.0,2.0,1.0,1.0,1.0,HACAACEFGEB,True +314,19.0,17.0,14.0,10.0,16.0,21.0,10.0,13.0,AHDAHEEFAEAGCADFEHCEBCGCCGADDADFADFAHAAHFEHFEHFEFFCBFEBAAHEHBEBCCGHEBHCBFCFFGEAHEACBABBABFFGFFGBBBFBGDGCCBEDADAFBFFCHEDG,False +315,3.0,8.0,4.0,7.0,12.0,10.0,4.0,14.0,DHEDBEDBECHEFFFCHDAEBAHHFHFEGFECEEDEGHBGFBAHBHEBEDCFHHFHFDHGBH,True +316,19.0,13.0,26.0,20.0,13.0,13.0,16.0,14.0,AFCBGBFCAFCEECHBBAGCDGCFGHEBHEDCCAHCFEAEDDEDAGCAFCACCADCGDEBFAGDHGDCBACHAGHBFHCGECDCAGCADADFGDCGDGEDFADCADFFDAEDHCCHCBHGBHEBFGBCABHHDE,False +317,16.0,18.0,21.0,25.0,22.0,16.0,21.0,17.0,GDDGDDEDFEGFEDEEDHBDHBCHDHBBBBBBCCBCCHFCHBCHEHADGCDGCBGAFABCEDFFAEBCHBDDEADCGDEFAEGAGCCDCCGFDFBDHCGHGAAFEADAAHEBHEAHFCCDCEAHEAFGBGEBGDGEFGFHGEHFAFDGEDGECEDG,False +318,23.0,22.0,20.0,24.0,12.0,20.0,16.0,25.0,AABCHBFHCDHCGFGHDHHFGAGHBGHBGCEECAEHGBCGDDDHCFHGBHGBHEBHDCCAHCAHAHCAFCDFHHEBDDBGDGEABBAEBCDDFDDFEDFACFABFCHHCHHGBFAEFBCGBDHFDBFDFDAADAFDCEHCBBDFAAAAGECDABDAEFABFG,False +319,9.0,5.0,11.0,3.0,6.0,3.0,10.0,12.0,HABHDEGCCCDFCBHCHHGHAGHCGHCDHCEGCGCEGHEAHFABAECGBBAAFGAEHAG,True +320,31.0,18.0,28.0,29.0,18.0,25.0,23.0,22.0,ADEFDADBAGBEGHEGDCAHAAHCFGCHGFEGFHGCGBFDAFDCFCEBABHDBAFAFFDGDAAHABGGCAFCACCDEBDCCGCCDCCAFGGCHBDHGCHAHBBBBBCCGAADCBDEFDHCAHCHHFHAECDCHDGHDEADEDFADBADEEDGCBGCBGDGEFHAFEAFAAFGEEDCFDHFAHFAFFAEFHEDGD,False +321,11.0,11.0,8.0,16.0,26.0,18.0,18.0,26.0,HFGEAHHHHDBHGEHDFAGGDEFDEFDEFAEFBDFHDEEDEEBGEHEHHEHACGGEBHEGHEFHEHAEGFDGDDGBCEAEGAECDHCGHFEHGAGFCHHEHHFGDFEFFHBFABHDGFFBCEBAECGDABDHBC,False +322,6.0,3.0,4.0,2.0,1.0,1.0,3.0,2.0,CAAFAEHAGBDHCDBCGBAGCA,True +323,10.0,11.0,20.0,18.0,16.0,14.0,16.0,14.0,FCGBEHDGCCHABGBCGACFEFEEFEDCCCBGCFHCDAGDAGDEDFHGBAGEDFECGACGEFGEFEHCDHCDEFHGBHGEFDEFDEADBAEHFCBGCHDCHDCBDCFHBDABGAHDHCD,False +324,14.0,16.0,12.0,17.0,15.0,23.0,16.0,14.0,HDEBDGFAFHDDHDHECHEBHGHEGEGFADHGEFGDFBCEBGAFFAGFHBDHGDCGDCACFECFEHFAFBCEHCFBEFCEADHABCBBCFBAFAGFAEEAGBBECBDGBFGHGBFDDFDDFGAFDAF,False +325,15.0,13.0,7.0,9.0,15.0,10.0,11.0,11.0,BDABDCBEEECAECHCFHBBHDHEAHEAGEDEABEDHEGGFGGFEFBEHEEFBHAAAAAADAADFAEFGHHDFHGAGBBBBCDCGBFGFCG,False +326,18.0,22.0,21.0,20.0,18.0,16.0,22.0,11.0,FAHEBHABFAHGAEGHHBBBCBGCBECAAGDACFBCFEHGDHDDCDDFFCEGHEBHCFCDFCDGCHBAGCEBCBDGBDCBDHGEFADGEFABFGCFCDBCGACGABFACDEDEBDAFAFFABGEBGEGEEDEGDAGAGGEBGCBDCED,False +327,13.0,17.0,20.0,5.0,21.0,19.0,14.0,10.0,CACCAECGEGAFABCCDFAFFHFCEFCHAHBGEECEECGEFDECDECEEABFBEAEEBEDHCAHAADBABFGFFGFGGFBGBHEBHGFGEFBBGCBCCBCBECBCGFEHFHBGHACEFF,False +328,21.0,20.0,17.0,13.0,23.0,15.0,20.0,19.0,HECGCCHADAADGADBEGBEABEHFGFGGFGCBECFHBAAEAHDFHFFBGEBGCBFHAABAABDCBDCAFAAHCGDCGEEGHGDEGCHGHBFHDHCDBCFEAGCAHCEHEEFEFBDHHDEBEEDEBGGAHGAHBEFBECEFABGABEC,False +329,24.0,23.0,29.0,30.0,30.0,21.0,23.0,19.0,HADHFBHFEHCEHDHCDFCBABEEBDEHDACBGDBCDBGDBADCCDABAGCEGBDGBEGCDFAFFGEFGAGEAGEADCGHGBDEDAADEHBAHCAEGBGFBFHBGEBDBBAEEDEEFAEDGCABCEDGFFGECCDACHBDGBDFCHECHECEACEADDDEDFADFAFHCFGCADCEECFCCFCCAEBGGHHCHFDHFEG,False +330,7.0,6.0,9.0,9.0,7.0,8.0,16.0,10.0,HGGAAGEEFBEDHFDAFBAEDFGHFAHGDHEECGHCGCCACGFGHFAHEBHCGGCBGDHGDCGDCGBGDBDF,False +331,15.0,22.0,24.0,18.0,22.0,22.0,16.0,24.0,ABAFBECDEDAHCCGCAAHHCHHGBBGBAGBDGEDEHAECACBBFHHEHHEHHFHDCHDCBGFHFFHAEBFEFGDHAECEECBEFEGCCFBCGBCDEGHBGHFAHFGDBGEAGFADCBCCHCFFDEFEEFBEFHEHDCDDBHDBGFAFFBCCBCFBDADCGDE,False +332,9.0,18.0,16.0,12.0,7.0,14.0,10.0,14.0,AADCABGADACDAEDCHGCBFHBFHBEHGEFGHGECFBCDDGDAECHBCEBCFBCHHFDHDHHFFDFBGFGHBGECCFDFHDBHGBCFFABBACBCBBCB,False +333,24.0,10.0,12.0,14.0,8.0,11.0,24.0,18.0,AHAAHAADADGFHEEGBECBDCEACAHEGHEFHADAADFHGBHGBGBCGAGADGADGAHCAHFHFGEGGBACDCCDGFGBHCFGAFGBGEHACHAGGCDDHDAADGHDGFCGAHBAHBGFF,False +334,17.0,19.0,16.0,21.0,12.0,28.0,7.0,21.0,BCEAFGACAHCFEBBDBBDFFDBCDBFDFFDHFABDGBDFFGFDHFCGFGHCBHAFCEFHHBHHAHFADFBFCBFCBDCHEHDCADFDDEHDECDFCAFAAHABFBDFHFCDGHDHHCHECBEAEHAEFABDEFAFBGHEA,False +335,5.0,1.0,17.0,8.0,5.0,13.0,6.0,9.0,HFEEFACCHDCHDCHFBHDDCACCFCCGCFFDEFAFGCFHAEGFEGFDCCAFCHCGDCGDCHFH,True +336,7.0,5.0,7.0,10.0,4.0,6.0,4.0,9.0,CABCEBDDFADCAFCFGCEGEHDDBFGBFHCHHGHHDFDEHDAACAADHBDH,False +337,17.0,14.0,20.0,15.0,14.0,12.0,26.0,25.0,FEFFADAGDAGFCHHBHHBAFEECECAFCDFDDGGCHGCHFCGDGGBBGDAHDHECHGCBBBHDEHCCHFGHFCHBCHDAHCAGCAGEBHEBAAACEECEGGDHCEBFEHGHCGHCGDABAGHGGBBGFGGDGHHEHDDAAGA,False +338,17.0,17.0,8.0,23.0,13.0,10.0,15.0,13.0,DFFDBGEBEBCDBFDBAEEAFGAHDDDBBDEBGEBGBAGBGBCGEDEAHHADHDDHEDHGGHADDBDHHDCHDAGAECADCHDFBBFABDAFCAGDFFCAEGAEGEFGBDGCHAHA,False +339,18.0,24.0,23.0,25.0,16.0,22.0,30.0,24.0,DGBDGDDCDGCBGFEHEAAFCACGBFEBGCGCABCAFAGEAGEAHDCHBFEGHEBDDBDDBGABGFDGFBHCAEEAGDHEHFEFEHFGHFBFFGCAGCACCDHDDHBDFGDFGEEGBFDHHBCHDFFDCCABGBDGECBEGGGHDCHACHBHHGGHBGABDABHFCHFHHDBABGFCGFCDC,False +340,2.0,2.0,13.0,7.0,3.0,3.0,2.0,4.0,ECCCDCCACCBDCDFCDGAHHFEDFBDCDCCHGCHE,True +341,4.0,3.0,4.0,1.0,4.0,2.0,6.0,4.0,GAEGBCHBCFGAHGAHBACEECEGHGDF,False +342,10.0,14.0,13.0,18.0,10.0,15.0,4.0,7.0,BFBBADBAGACCABFAECCFCCEDEHDABBAFGGBDBCEBFDBFDEHDGHFAEECCDCCFHBFDEDDFDDCDDEHDEFFBDFBDFACHAFH,False +343,2.0,3.0,3.0,5.0,8.0,5.0,2.0,1.0,EAFDCDDCHEBFEFDEFEABECBFGEDGE,True +344,16.0,17.0,10.0,12.0,19.0,14.0,18.0,24.0,DGDFEBGECFCBBGFFEFHEHBEHGCBACBEGFGGHCBHGBHAEFBFFBHHBEHAGAADFAGFAHFAHGACGAEHABFGEGHEHHEHCABDAHEABCDHGEHGAHDDHDDBEFBGDBADGCHECHDHEEE,False +345,12.0,6.0,8.0,11.0,11.0,7.0,6.0,8.0,EEABBCDDGADCAECADHABGABECBECFEFFECDEGHAFHDGHFHAFAABDAHCEHAEHFDCDEGDGD,False +346,14.0,12.0,14.0,18.0,13.0,23.0,16.0,8.0,ECHBFBAFEFGCCDDGFDBFEGFEAFECFEHFEGBDDCHDHAAGAAGFBDBGDADDHGDCFFHEEHCEBGDGCFECFEBFDACDFGDAGDGGCGBABDCBCBAFFAFFAFEAFDHFCG,False +347,13.0,9.0,9.0,6.0,6.0,16.0,14.0,5.0,GEACFCDFGAFGAFCFFDDGGDBGDEGBAAHGAHFFBFFEEFBFFBFCEGBGGCECCAAHAGHAFAAHACGGFBCBBD,False +348,2.0,2.0,2.0,3.0,4.0,6.0,4.0,5.0,EFGDDADHEFBAFECFECFHBFGGHHGH,True +349,25.0,25.0,26.0,14.0,12.0,22.0,23.0,17.0,GCCGCCGEEDFADFDCCEHCBHCBGBBCBFGBAGFGHBGABFAGFBFFACCHHFHABAABCABGHEGBCGBFFAFGACCDDCBFGFAAAAAEACEFCEFCADCAGHAFABFDGADHHGBBCHGEBGCBHCBFDHGHHCEHBBBBEFAFHDDGFDCAGCAGDEDE,False +350,26.0,15.0,7.0,12.0,18.0,16.0,17.0,8.0,GFECAAAAAHFADABEGCECDGDAGEABEGBGBBGBBGCHEFFDFFAAAGEAFBAGDHHFGGAGEADFAEEBEFCGFDDFGDFDBFBEHHAHEAGEABEABEBBADAADAFFCEGCHAE,False +351,19.0,24.0,27.0,20.0,25.0,23.0,28.0,19.0,HHCHFCDGDBGDFGCBGDFGBFEDFBGABHABCABGBGAHGBHGBABCCEEBDFGDHGDBGHFGCFGCBHFBHECGCCBCGBFGACGDCHEEDFBGABFAFFGHDAEAAHDAFDEFDEDEECFEGHECAGCECCFCBABFADCAEGEDDFHFECFEGABGAHDHECBACDGHEEEEHECBECGFC,False +352,11.0,14.0,21.0,19.0,18.0,15.0,12.0,19.0,CGFBDFCAEDFEHEHCEACEAEEFGDAGBACBFCBFABDDGHDEHFGADGHDHCBHCEHCDHBBEFGFBADCGBHEADECDCBDCBACBACBDCHFHHCHFDGCDECGHCEEGHEHFFFFGEHDCHDED,False +353,14.0,12.0,11.0,22.0,22.0,10.0,7.0,14.0,BDEBEHDFDDCDEADEHCFHCAACAABBCDBHHEDHEFBAFDACABGEEDEADFADFBGFAGCGHCFEAEDGDDFDEEBEEBEHHEHHEDEEBHHCADCACHDDGGBFEDDE,False +354,25.0,23.0,25.0,17.0,15.0,24.0,9.0,25.0,FHABBAFCCFBCFBEDDHCHGBAEHCEBDAADFADFHFHHFHBFBCHBHHEHDACDFFAGBGDEGHHGDDCCCAHCEECAEDECFBBHDFCEFBAHAAHAFHAFHBFAAFAGGACEAEDAFDHEGFCFFCDFHGFHACHABBABECCCCACCBBCDBEBBHDB,False +355,17.0,20.0,28.0,20.0,27.0,26.0,18.0,20.0,FCDHEAHEGECAEDAEFCHFEFCCCCBECHEHEDHDHHEGHEDFEHAEDGEDGEFEECECHGCDGCBEDDEDDFDDBGGCGBHHAACABGGBCGBCGDCFHCFBCFBHFAHFEFFCFFBDACFCHBHEEFBGFBHFDGGCECAAFACFBBBABBDBEHCAFFEGCADEADFFBCGA,False +356,11.0,9.0,19.0,9.0,17.0,23.0,24.0,22.0,DCFDCHHGFEAECFFCFFGEFGFFGAHGBHAADAACEFFGGEHCAHCBDFFDGGHHBFHBHHAHFFGGFEGFCGFCHCGGGGEEEFCDHCDECHECEBCFGCHBCHAEHCEGFDGCHBEHBGHBGHFAEAEGGD,False +357,15.0,19.0,23.0,15.0,30.0,8.0,15.0,12.0,EDGEGBEGAEFADGHEFEEDEDDEGGFDAEEAGDAEEADEAEBBCFBCGECBEGGACEFBGDHECHEAHEHGGABCEDDFDDEDBHDBCBACACCGCABEGHCHCCBCCAFCHBEHEHHCCBCEBCEBCEBFBBECA,False +358,8.0,10.0,3.0,16.0,6.0,11.0,10.0,8.0,EADHDFFDBFEGFGCCAFCBHDGEDHDDFBBFEBHHDAHDHEDHGDAGDAEDGDGFBGABGFDGFABBADBF,False +359,20.0,14.0,12.0,8.0,11.0,4.0,10.0,13.0,BAHGAEDBEDCADCAHBABAAFAACGBHGBHABHEHCCHBCGAEACGDCADCHGAECADFAEBDEHFCHEAADHAGHFBEBCEAGEBGBGHB,False +360,26.0,15.0,17.0,18.0,13.0,10.0,21.0,9.0,HCBGGBGGBCCDDCDCCHCHHEGGEAFEDFAGEBDHBGAFGDGAABCADCEGCFGAEABEADHABGAEGFEAFAFCACGADDBEAGAABAHGDCDEADECDBCDBCBHCFDDFAGAEGAHGAGAAFBDB,False +361,15.0,32.0,16.0,34.0,25.0,18.0,29.0,23.0,HDFHFFDABBBBEEBGEBGEDEEGAHGBGBBHDAEGCDACHECHBGDBGDBGDGDDFBGGDEBFAHHHHEHHAHDADDEDBEBBHABHAFGDDBEDHEDHDDHGCHCEFDGGDGGBCFCCFEHFGGFHAEDFDFFCAEGABDFEDGBAGBGDBCFBCHEDADDCDCBBBDEBDEBGHCGBEABFCGGEFCEG,False +362,22.0,28.0,20.0,25.0,21.0,16.0,11.0,16.0,BHCHFBFFBDDBHHBAHBADBAHBAHGCCFCBBDBBECAEFEDHHBCCFDCBBBEBHEBFGBHGDHCFFCFAHHAGAGDBFDGFDBCGEADBFBBAAFEDGEDFDAAGBAGAABEDDACBECBEFDAHCCCCGCEEHAEADEDDEDCEACEAEDDEDDE,False +363,11.0,11.0,7.0,6.0,9.0,8.0,12.0,8.0,FBADHHEHFGGCGAFEAFEGFGGHGHCCHCCBCABAEBAHDDCGFABEABFABABDEBDBHAGGFBGEEGDE,False +364,5.0,2.0,8.0,2.0,1.0,2.0,9.0,6.0,AHGACBAGHCGHGBEFDAFGACHCCGCDGCHGHGC,True +365,33.0,17.0,16.0,24.0,25.0,19.0,21.0,11.0,GDDGDDGBDBAABAFECGEDGEDFAGCACCFHCGHCDAADBACFCHEDAEHABGGHCEEEBAEFEDFDCFDHFDAFAGFBCDAFGEDDEHBEDBDCBHCAGFHFDACAGDABEABGABGAHCAGDAFFGEFDEFGFGEEEAEAAEAAEAEFBBAHBABCEGEDGAA,False +366,24.0,28.0,22.0,9.0,23.0,15.0,15.0,17.0,HEGHECCBBCBBFAEDHBFCBFBBFABGEGCFDCHCCBAAHAADABBBBAECHECEEHEEBAECDDAGDFGDFCDCGBCEBCABEABAAEHGCHEFHEDHFGGAGEHGCBBAFBAHCFEEGAEGABAABAHFHBCCCEHAEBBEGCGFFBHFA,False +367,22.0,19.0,28.0,25.0,31.0,21.0,23.0,26.0,HGHDGHDGEBCDDCAEEADEDEEHAHBDCEEBEFGAHAADGDHBHFCEGEDBFDEFEEBEBCEFCEFCBACBADHADEGDAHCCEDDEDHFAHECDDCBEFBEGBDCHCHAABAACCHCCHCDHAGCAGEBEEAFECHBCHGCGGHFCFAGGEDAFDCBECBEHDEFFGFDGFHGFGGFGFFBFHBCCGAGHAHH,False +368,19.0,23.0,22.0,14.0,18.0,18.0,13.0,20.0,GAHHDGFBGDBFFBHGADABEHCCFDCBDAGDBFBBFBBFBFFEFFAHCAFGAHADHEBFBAFBECCEBCDDAEDGEHBBBBACBAEBDECHEGFCHACFDBGCHHCHGEHCCHCGHCGECEAGACHFCHFCHDEEEEEBDACAAHA,False +369,8.0,9.0,10.0,4.0,11.0,7.0,17.0,8.0,GEHGEBGFGGFCGEHAFBBFCBHCFDCGEHAEGCCGAEGBBCHBHFEAFGBCGADGADEADCGCHGEBAEGHEG,False +370,14.0,14.0,22.0,16.0,19.0,13.0,17.0,12.0,AEAAGFACECCFHBFDEGEAGADCEHCECCADHDEGFGGCCGBHGBHGBAFDGECGECGHBDHBABFACDDEBFECFEFFCAFGEGEEGHGCBACBCBDABCGBDFEDEDDHDFBDHCCHCCHEADE,False +371,24.0,19.0,21.0,13.0,20.0,18.0,17.0,23.0,GEGEADCDGEHBDCBDHAHCEFCEFEEFCDFBEGAGFHGFCCHCCFFCFFAADAFCABBBHGCHDHEAAGCAGDABHHCHHCHGBEFAAFHAFHGHHGDADEABEGBCGCDBADEHHEHACDABGECFEFEEABEBBHBBABCAGCFGEFABHAH,False +372,3.0,3.0,3.0,4.0,0.0,2.0,1.0,2.0,DDFDDBCABHABACFGCH,True +373,11.0,27.0,14.0,16.0,27.0,12.0,14.0,25.0,BGEGGBDBADECHGHHEHADHDGAEAHEFHBFHEEDGEDECBHFEHEBHDDCEABEAHEAHEBEEBEGAHCHHCBBBBBBBCCGDFGEBBEFHFDHFDHFDEFDEDEHGEAEEFBBHBBADBCBCCBGFDGHEFABBGHCCCGCHH,False +374,3.0,9.0,10.0,10.0,8.0,7.0,11.0,11.0,GCGGBBHHCCGFDGFDHDDHFDBFEGEEBECDDAECCBBCHGCHGFHADHACBEFHEBHDBHDGGFGEC,False +375,23.0,33.0,18.0,22.0,30.0,18.0,26.0,23.0,EBDEBDHHGCCGCFGADGBCGHCEHFEHDEHBEGDDGBHGAHDAHDBCBAABCFBCHEFDADCAEBBBBHBAFBAEBAHBHFBCAGCFHDADEAFECEECEFBBGGCCGEHHBBHEDCAFAHEEFFEAGABGCDGBBGBDFBDFGDBEDBHFBGDDGAEBAGAFGEEBEECEABEHGGADGDGFHGFEAEHHE,False +376,26.0,12.0,16.0,23.0,9.0,18.0,21.0,30.0,ADDFFDFFDFFHCFCBFAGFBGHEDHEAHECHCABFAEAAGAAGDDDDCFGCAHABDEGFHBCBCADGHDGADGHEGHDGHFBHGDHCDEABHGEHBDADAACHHHHFHAGHEGHDGHDHHCCCAHDHHGGFAAAAFABFHCFGBHGAACBGCDD,False +377,14.0,10.0,11.0,6.0,8.0,8.0,6.0,11.0,FCEFBBABDCHECFBCGBHGFHECGCFAFAEFDBACADCABCHHEAHGAEBAHAAHAAGFDCBDCBDGAEHHEH,False +378,10.0,13.0,11.0,8.0,10.0,9.0,5.0,12.0,ADCHBEECEEADBACBGBBAHBGHCCHGBHCCACCFHCDBDDFFDFFBFEAEHABHDBDAFHECBAHEGHEGHEFBAF,False +379,26.0,14.0,13.0,28.0,14.0,24.0,18.0,23.0,ACEAFGAGABGAGGEHAFHDCDDFFCGHCDHAAAEFFEGABGAHHADFGDFBCAGCAGBACDDDBDDEADCCHGEAGEABHHFHCCBDABHFEEDGHBGBBHFDFCDFBDADDEDDEDHFDHFDHEDHAAFAHDGDBGEFFABAECAHHFFHFFHDFHFG,False +380,21.0,15.0,24.0,10.0,21.0,16.0,24.0,20.0,GBFFDHFBFGEFHHHHHECHEDEEBCAFAABGACGBCAECBCCBEDFCDGCEEEAEGAGGACDAFDCGBBGBBCAFFDFHBAGGDGGCCHEAFEAFCAFCAHCGGAHCACCAEGHEHEEGEEGDCHDHHGCEGAFHHEHACBCFGHBGBAG,False +381,15.0,21.0,27.0,23.0,28.0,27.0,27.0,20.0,BCBHCAFBBGEBDEDHCDGCGGCGDCFECDECEBCEBFEBFGCGGBGABFAEHCFDCHEGEFFFBGFECCEHCGFFGFHGBECCFCFAEDAGAHDAGEFFFAFDACCHCHBBHFCDAGDHGDEGDBDEHDHHFHFBHDBFDEAGCADBDDBDDEEFEEAGEGGBCGEFEEFDGHHCHFEHCAGGABCE,False +382,0.0,4.0,3.0,2.0,1.0,1.0,2.0,3.0,BCDBHDBHFEHGGCBC,True +383,1.0,2.0,2.0,6.0,6.0,2.0,4.0,2.0,CHDAEDGEDCEGEBGEFDEDGHDFB,True +384,12.0,14.0,12.0,10.0,21.0,16.0,19.0,20.0,GDHEBFGHDHCEABECBDCAHGAEGCEBCEHDEAEBHEBHFHHBBFFAFDCGHAGDCBFHGHCADBAHBGHBGADHFCHFDHCHECEECEGFEGEAGEGGEBFEGAEBAFFFEGFGGDGHFEHF,False +385,9.0,9.0,5.0,9.0,10.0,4.0,7.0,7.0,BCCBABGHBGDEGDACDBEFBHDGADGAEHHCFCEFDEBDBBDAAEEAEHADAGEHGFHE,False +386,15.0,9.0,11.0,11.0,15.0,15.0,12.0,13.0,EGCFFCFGCFHFDHCHCCHACHECAGHFFABEAHEFHEDDEBDHBDHBECDEADGFGFBGFAGFAFAHEEEBDCDGEHGAGGABAAGDFDBEABEHECFAA,False +387,17.0,16.0,9.0,11.0,9.0,4.0,15.0,11.0,DADCFEBAEAGCBBHBEGBDABFBDFDHCAFEGGEAGEACHABHAGHDGHBHHBGDEGHCAAGDAHACEGBBGABAACGACGBDGBDHBDCE,False +388,10.0,3.0,8.0,5.0,5.0,8.0,6.0,3.0,BDDGGCAECAFGAFCACADCEGCAHCADCBFFAFFHHFADEGFEGBEA,False +389,17.0,13.0,28.0,32.0,15.0,31.0,24.0,29.0,HGHCCHGBFDBGAAAAEDAFHHDEGFECFHGFCFFEHFDHGDCCFCHFCFDCFDGEHBEHGHHAACAEDAHDACGEGFEBHDHCFHEFHGFAGFACDACBHCDHCDCCDEFDEFDHFECDHDDCGDGBBCCFDHBDFBDFCGBBHAEHCDGGFHGHAGFBDBDCGFCGFDGDDFDHGHAFFAGDCEDCF,False +390,23.0,24.0,19.0,26.0,25.0,15.0,25.0,27.0,FADECFEGAEGHCFDCBGCBDDHDDHDDAGAHHAEBAGDAHBHGBFGBGGFGDCADCBHBEHDEAEHGEHDBHGBHEBDGBHECAEDADDAEHFFHFHGGCCHHEFECCGDEACEHHAHGAFAADBBDCBGABDACCADABFABEHFEBEEBDDACDEEDGGGGBHGBHCFGCFHFBHCBEGEE,False +391,4.0,5.0,5.0,5.0,10.0,9.0,7.0,10.0,FGGFGCEGEEHHDHGDCEDAHBFHFGDFEBHBHHAHFCCFACFGBFEEHEEDEAB,False +392,2.0,1.0,3.0,2.0,5.0,3.0,4.0,3.0,FBGCCGDCAHEFHFDHAGEEGEE,False +393,32.0,34.0,23.0,23.0,23.0,22.0,17.0,26.0,AABCCBCADCAHAAEFAFBABBHCCFBFGDHDHCAHFGBBCCBHCBHBFCDFBHBEABEAGEDGECBEBHEBAEFHEBEBDHAHHBGCCFDDFDFBDHBGAAACEACDACHADFAGFAGFHGFDFADFAHEAEEBEAGDDHCDEFDBHCGGDGDAHABHEBHEBEEBEHFABAHBGEBHCFDGFGFEDADCACHACBGBB,False +394,10.0,5.0,5.0,10.0,12.0,9.0,5.0,11.0,DCDEADHACFADFADABDHGHHDAHGAGEEBEFFCFAEDAGBAEBCEHDBHFFCEFHEHHEGEEDHF,False +395,9.0,8.0,7.0,6.0,6.0,3.0,2.0,9.0,BAGBECDECDCHEAHAFGBFHBAHDHHAACAACHHFHBDDBEEAEDBCCB,False +396,28.0,25.0,16.0,17.0,19.0,17.0,23.0,14.0,FBGFAAAHBHHGFCGDGGBGGEGGEFCEHCDGBBHEACEGBEADCADGEGHDGAAAAABFABFADFCCBHCADEFGEDDBDACAABAAHHHFACFBDAADBAGBGEHDEDBBFBBFBBCEAGEBHEBHEBEFBCFECFEGDGBAGDACDHCFCFGAGAE,False +397,11.0,7.0,11.0,10.0,5.0,9.0,10.0,7.0,BCHBAHFDBFCHFCDDBHGAGCHGCGGCGGFGEAEECDDFADEBFCHDCHBGABGEFDCFDFAAADAACA,False +398,21.0,30.0,21.0,28.0,27.0,13.0,18.0,24.0,CBDCAGAAEHGBHBHHFHHAHHCGHDBDABFBEHDEBCEDFDCFDCFBCEDCBAEBEDBEBBABEDGFBGFEEAEBGHBGCBACBDCEECBDCDDCAAGDGEAGEAFEGEEBEHFDHDGCEBFEBDGDFHAFHFDHECHGCDGHEGDBDBHEBHGBDAAAAEADDDCABHDCHCEHCHGBBA,False +399,8.0,12.0,5.0,5.0,7.0,5.0,5.0,13.0,HHGHBAEGABBCBBCBBCFBCBHADAAFBAEBEBFHDECEEFHGAHGHHDFHDGHAHHED,False +400,7.0,6.0,11.0,5.0,6.0,14.0,10.0,3.0,AEFAEBCFDCFCFAEFCGGCGECHFGADCBDFGCHCCABCAGGEFHEFGAFBFBGFDGFDBF,True +401,5.0,2.0,3.0,1.0,8.0,3.0,7.0,1.0,BAGCFGEEAEBHEGFAGFDGEEGECAEGAC,True +402,7.0,14.0,22.0,10.0,18.0,10.0,12.0,15.0,GHECCAABBCBBEEBEGBDCEECFGGHCHACHAHFBGGCCCCHCEFCFDCHDCHDFHECHACDBCBAEBDEBDGGEGHDCEGHECEECEEHBEHDFBFBAFHDFGFCG,False +403,14.0,14.0,19.0,22.0,20.0,22.0,14.0,19.0,ECCEDFDGEDEEBCBHDAFBAFAAECCFDCEBBEBDAHCADCFDHEBFEDFEFEGFEAFHAFHGCHEEHDDFEDFDCFDCFCBAHFAHFHHFBDFDDEHCGGBGHBAHCAGCEGAHBHCGCEDEFDFGDHGFCGBBGCHGHDDA,False +404,9.0,11.0,17.0,12.0,11.0,7.0,12.0,10.0,BCBDCEGCECEGCDCCDGGAHGEBGBHCFCAFHAFHADEAHFDHEBCCDCCDCBDHEDHADBAHCHDDGBEGFGGBECFEFEGBAGCAB,False +405,5.0,5.0,3.0,4.0,12.0,4.0,3.0,6.0,DBGAEGEEDAEHAEBBEBEEHFDCBEFGEFCAFCEHHAHEDH,False +406,15.0,17.0,23.0,27.0,15.0,22.0,16.0,20.0,EFCEGEFDBFHCCACBDDHDCFBHFHGFCECAEABGBGDHCDBCABGADFDDFECCACFAEFHDGHDBHDAHDHHDHBFEFDEADFADBDCHDEHFCHFGGFHGHHEAACAFCFBDDCEBCGBDGDEGDBGDHFCCFDEHCBBCBGDFGAFEAGC,False +407,11.0,16.0,12.0,20.0,16.0,15.0,13.0,15.0,HBGBDGBDGFGEFCCHCDHCDHFFCDBCFBEEECEFCEABEHDEDBEFHFDAFDBHBBHDACAHFAFBAEBDDDADDAFDGGGEEGHEGDFHBFHGDBGCBGBACDAHHCEAEEDHGF,False +408,16.0,12.0,20.0,13.0,15.0,13.0,22.0,14.0,HACHAGEAGFHHDDCEDCBFEDFEACBBFHBFHBCGBCACCBDDGDDBEFEGGHDBDDGGFHGAHFEGAEACDACGABAAHEABECECCECGGCAHFAHFGGFEECEHAFDGGGGCFHCGGCGBC,False +409,4.0,7.0,9.0,5.0,9.0,7.0,4.0,6.0,EFCBHCFAFFACFDHHBHCBGBBGBCEHGECBAGDCEFCDFCDEEHEEAED,False +410,12.0,11.0,9.0,6.0,6.0,6.0,2.0,5.0,DDCDHBBABBACFACEBDEHDHBFBAFBAGCAEAEEFHCBCCFHCAAEAABDABGFC,False +411,10.0,13.0,4.0,12.0,8.0,3.0,7.0,11.0,BBHBBDDDDDEEAAHAAHBAHGEHGHHAEDEEDACDBBDGCDBBABHHCGCFGFEGBAGBFDDAEHBH,True +412,2.0,7.0,4.0,0.0,2.0,6.0,5.0,2.0,BGBFGBFGBCGCEACFBHFEABHCBGFF,True +413,28.0,23.0,16.0,19.0,25.0,12.0,17.0,19.0,BHADEAEEHEEAGEFBBCDDAGHHGHAEBDFBAFBAHAEHBECBDCGDGBFGEEAEEDBDDBHDEHGECAACGACABCABFABCADEAHEDBCGFEBFEADEBEGADAAFAFHADBACHABHCCDCDBFABGAEGCGFHACDEGHHGHGDHFBHEBEGC,False +414,4.0,13.0,10.0,10.0,10.0,2.0,11.0,8.0,EEGCECCGBBGBCGDEEAGEDBHCHHADHDBHEHCFBDBGDBDDBDEADEHBCAGCBGEGCBGCBGFH,False +415,13.0,21.0,20.0,13.0,22.0,19.0,15.0,24.0,HFDBGDBHHBCCFHHFBHFBHFBHACEFEHFCBGBBFBHFDGECGFCAABGCFGCHHBHHEGFEABCBECEECGDCHHFEDAHBAEEDECDHDGHFGHFAECAFBAGBDECDCHBHHDCEFCAFEHEEGEAGEAFEDEBACBDCBGG,False +416,21.0,17.0,11.0,9.0,12.0,14.0,19.0,7.0,CGHHGBDBAGBAGBDGACGAHFFBFAGCACDAGAAEAEFCCAEFBCFGCAACGEFFBDAEDABDCEGEFCEBBHFBHEBHEAGGBGFAHFEBFBBDABFAGGAGGDGADE,False +417,6.0,8.0,8.0,1.0,1.0,6.0,7.0,5.0,BADAECHCCHCCHAAFCGFBGBBHBBGFCFHCGGBGGBFFAA,True +418,11.0,22.0,19.0,15.0,20.0,16.0,14.0,28.0,CCEHHDBHECHCGAGDCCABHFHHEHDEGBEGBDDBDEBHBBGFFCFFHBDHBCHBEHBAHFFGFCDHHDCHBEABHDBHCBAAEFDCBCCDFHEFGBDABGFBCADEFDGFAGEHGBHCBCGFAAHEEHEFHEGEEHEEHCGHC,False +419,25.0,19.0,13.0,15.0,18.0,30.0,15.0,15.0,FHCDCFBEHCABEAFAFHEFDGFDCDEHAFGAFBDBBFBBGBAHFAGFBFFBDBDDEGFBDEBHCBFCEFCEFAECAEFECGADBABAEHFDGFGGBGFBGDAAAHAAHDFHGCHFCAFEAEEDECDHBFAGHAGFEEFAFFAFAHCAHG,False +420,5.0,4.0,3.0,9.0,10.0,5.0,4.0,4.0,DEBDADFEFCEHEABEAEEFEDHGDHEDCFGCFDDGBDGBEAAH,False +421,21.0,22.0,19.0,21.0,16.0,23.0,24.0,24.0,BGGDDGBHHHHGHHDAGFAGFBBFGGFGEHBAHECFACAGHEFCEADEAEBAHBGBBACDACDHCDHCHBCDBDDGCFHHFHHAHEEHCGCBGAADFBGEGFCCFCGFDHHDHCBFDAADABBCBFCFGDECBEFDEGDEDFABFADFGBFGFAGFADHHEGABCFBGEE,False +422,5.0,3.0,3.0,1.0,0.0,2.0,1.0,4.0,ABCABCBGAHHHFHAFCAD,True +423,8.0,5.0,10.0,3.0,2.0,6.0,4.0,7.0,CAHCAGAAEDGFCGDCFHCAHCAHBBDFAFFGBFBBCCCHCEHAH,True +424,4.0,2.0,3.0,3.0,3.0,5.0,4.0,1.0,GDFGCGACDACDEBFEGHEFFAAFB,False +425,20.0,29.0,28.0,22.0,37.0,21.0,18.0,23.0,DCDEFDAGCHCHFDAFEFFEHDEDBEABEHBEBFCBEDBCDCCEGCEBCEAHDHHDAHGAHBBBFABFABACBADHEEHEEAEAAEACDCHBCEDEEBEGGEBEFDGCBBBAFDAFCAFCHEDBEDGECHBHGFGECEDGDFECFDCFGHECEEHFEBCABCADEAFEGBBHBFGBEHCCHBCGBEFCHHCHGGGGDF,False +426,3.0,6.0,6.0,5.0,11.0,8.0,8.0,8.0,ECEBAECEDDEBDGBGHDGEBGECGFHGFHACHFGHFCFBEFHHBHEADEFGCFE,False +427,9.0,21.0,17.0,17.0,18.0,17.0,9.0,12.0,BHBBHBBAFBCCHEBDECFECDEFFGHCEFCAFAEHDGHDBHABEEBEEDAECBDCECABDAFDHDGEDBBDBFAFFCCBHCDHDBFDGFGBFCHACDBCGGDGGCBFFBFEEFHECEED,False +428,13.0,9.0,6.0,7.0,7.0,9.0,7.0,6.0,HDAAECHEGFFGFGCFHCBGAADAADAAFABFBEEAFFBBCBBEABECGHDGEDGDABDAFHCH,False +429,8.0,15.0,19.0,18.0,20.0,20.0,16.0,22.0,FGDFDDFHDGAFGFHEBABCDBHFGHFCHACACCECEACEBCFGDBHFEHFBHGHHEHEBGEAFFHCFDEFDADDBDGHFBDFBCFBGAHFBECHECBECHECECCEDCHGEEGEGFDFEDBEHBHCDGDHCHHGGDG,False +430,13.0,25.0,20.0,21.0,26.0,17.0,24.0,16.0,EFFGFCDFCEHCGHDGEECAEBBEGBECFEGHAADDAFCAFCBCEECFFCFCAGDACHBHHBGDCGDGGDEEDBHHGCHEDBEGEECEEBEBBDBAEEFDGBGGBDAEDHEFCGBCGFCGAHGFHDBGGBFBFFHEHBCDBADCEDEBBGAAGHBGHBDBDD,False +431,13.0,21.0,18.0,12.0,10.0,10.0,17.0,15.0,GAFBBBBFHGFAFBGCGGBBCABCAGDHGDHBCHBHBAHGGHEGHDCDBCFBCGECAEDDHBAEBDHBDHBDACECGEGGDHADBEFCDBGACEAHBCFBEHAEHAFGCCGCCFFC,False +432,14.0,11.0,9.0,15.0,14.0,12.0,12.0,18.0,DFAFFAHDHEDFEHHEDHCFHCECBABBDGEFGEDCDCGDHHFCHFCGGCEGABGDBEABAAHAEBDEBHEGHFGHDHEBADGADBAEHCEHDDHBFAGAAFFGH,False +433,16.0,16.0,12.0,20.0,13.0,18.0,9.0,14.0,FDCFDADDBDDAHDCBDCDDCDAEHAFAABADBECFAFBCFADAGCAGCDBAFCFFEHFHBFBEHGCGGDFGDABDEECGGDFEFBHCBHBEHBEABEHBAHGAEFBEHHHFEHFDFD,False +434,15.0,21.0,15.0,6.0,12.0,5.0,12.0,17.0,CBBDBGABGCDGCEADBCCADEFCCAHCHCDHCAHCHHABHBBHABEFCGCBGAFAAHEAFGAEGAHGEEGHEGBFBEECHEBBAHHCHDBHBBHBBABBGEG,False +435,0.0,0.0,3.0,2.0,2.0,2.0,2.0,3.0,CHDCEDEHCGHFGF,True +436,22.0,21.0,21.0,13.0,7.0,14.0,20.0,13.0,BHBGDAADEDFGCFGDHGAGGAFDCCACCHEADBCFBCGBFABEHDCHCEGBGDAGAADCAHGHHGHFFDEHAGAGGABCAFAFFACHACGBDGBDCBDHAGCFEBFACHBCABCGFCAFGBEBBCBBCBB,False +437,18.0,12.0,15.0,15.0,9.0,15.0,19.0,9.0,BEAEFBCFAADCBFGDGGHFCADAADGADHCBHDGDBGDBGDCGAHEFHGFAEBAHBADGCDGCGFCHFDEFEHFCAAAFBAHAEGDEGFEDCCBCGBFGBFGACGCCADFG,False +438,9.0,15.0,11.0,10.0,6.0,5.0,12.0,8.0,CBBCECABBAHBHBCHGGEGGDAEBEDCDFADBGDBGDBGBBCDGABHCFGBFGHFGHFEAAEAABHDDCGCCDCH,False +439,21.0,34.0,13.0,20.0,9.0,14.0,18.0,22.0,DBGDFCCFEAGHBHHCHHCBHBGHBDABCCBAFBAGBDCBDBBGBAFFDHEHGCBACBAEFGHBGAFGCFBAGHAHHAGHGCDEAHABHBDFEDBDDADDHFBHFBEABEABADBHFHDBABBHBAEBGCDCFHGGGBBGFDGDABDABDE,False +440,5.0,7.0,4.0,9.0,2.0,7.0,1.0,7.0,DEBHHHHHHDFAAFGADHABBFFDFFDBEDCCCCFBDDBDAB,True +441,9.0,3.0,11.0,9.0,5.0,3.0,13.0,6.0,GCHGCHBCDDAEAHEAGAGGCGEAEHACDFBDBDGCDGDGGHGCFGCAHCACDGCAEFD,True +442,26.0,15.0,9.0,16.0,20.0,21.0,20.0,20.0,EEHEFAFDDHDDBDEEFFEDFCHFAAGHAEHADBAGHAGBADAAEABCGBCBBFGCFGEFGEFGHDEAEEAFHFGHDGFAGACGCHBCHEAHGABGBGADGFFGEEBCFDHAEBAGBADAABBHFHHCEEFFEDFHAHHAHADDGFG,False +443,5.0,11.0,13.0,10.0,14.0,14.0,10.0,14.0,FCEHCEHCEDGDBBDGEDHEABEFGAFGAFCCFHFFHFBAEEGDFFAHECHGCHDCHBGFEHFHFFBBCBBEHCHHBECDEDBEDCGGGDC,False +444,9.0,3.0,12.0,6.0,9.0,11.0,10.0,6.0,GACGCGACGBHABFCEFCEFCAFGFEGDCFBCHHHHGAAAEADCDGAGEEEEECFFCDFGDFCDFH,False +445,9.0,10.0,13.0,13.0,17.0,11.0,15.0,15.0,DGCDBCDFEFHEHHEDDEGCCFCFFCGDEECEFHHFAHFAEDGGBBGHHGCHGBACAAHEEHEEDGGDGGDGEEFEBGHBCDCAACAHDHBFEFCEDBHBBAG,False +446,4.0,1.0,6.0,9.0,11.0,4.0,5.0,7.0,GACEFGGACGDFDECDEHDEHDEHEEDAHDCDFCDBEHAGFCHEEHE,True +447,26.0,19.0,18.0,11.0,16.0,16.0,12.0,21.0,EEHFFHCBABHABHAEHAEHEFFGFAGHBHAEEAEEAGAAGCCGABDACECFHGHHEDHCBHCBHCBAGDABDCHAHEFHFHHDDFBFFAFCACABEDFEDAGDBFCBDAGFACEACAGHABBFBBEBACCCGHCDBAG,False +448,6.0,5.0,7.0,6.0,1.0,1.0,3.0,5.0,HADHAHCACGDGBDGBAECACBABDCHDBHDCCF,True +449,11.0,2.0,6.0,6.0,9.0,16.0,8.0,5.0,AGAAHAAGFDFEEFBEDGEGEEFEAFCCDEDFFGFFGFFCFAEFAFHDFCBHADHFGHACCAG,True +450,11.0,4.0,8.0,12.0,7.0,9.0,7.0,8.0,FDEFCADCGCEBAHBGECHEFHCDACDABHGBFFDFAEFAEADGADFEDHCAHGDHDFCDAGDAGH,False +451,31.0,20.0,20.0,33.0,22.0,23.0,32.0,17.0,BCCAGAAGFAGCEGDBGDACDHDHGFBGBBDBFGBHBAHECEECDEDHHDFADFEDCEGHAFBCCBFADGCBADDFEFGEHGEFGDHECAEAGEDDEBDEADAADBCBGEDHDDFCEAAHBGBGFAGFDGFDEFEGHBAHFAGFDGDDFDFABCABCAFCAFCAGCAHEGHGDAADAGEFGHDGCDGBGHCFAGDEGA,False +452,6.0,6.0,6.0,10.0,8.0,9.0,9.0,6.0,AFEABEBDGBAFEDHGFHGEDGEHCHAGHECHCCFDADDFEDFEBAGCFGFFGCBGDBDD,False +453,13.0,18.0,14.0,23.0,17.0,19.0,19.0,12.0,DCGDCDDCADEBFFBFFCAACDACDCCABCDDFDFAAEGFHFADCBGCDGEDAFGGEHHEFBFFBFFBGFCDFCGAGDDHDDHFEHGEBGHDGHAEHBGBDEFCBDDEABHAGEBEEBHEDEGBHGBFGBGEEGB,False +454,18.0,22.0,18.0,14.0,25.0,31.0,12.0,21.0,FHADBACFDHAHHDGHBFFFCFGCBGDHFFFGFFGFGGFAHCHEEHFHDFHFFHFAHAHEACEGEEBDEDFAFFBFFBFBEFDCBBEAEHDFDEEEBBGCBFCFCBGBBFEHGCDEHDECDECBADEAEEACEACECCABBECBECBFAFAGHEHHABHAB,False +455,8.0,7.0,7.0,9.0,13.0,7.0,12.0,7.0,AGEBFEADAAGFABFHDEAFFCGFDEHGABGCBHCBGBDHBDFDEGCEGCEDCEHEDHGDAGEHEEGCEG,False +456,26.0,25.0,17.0,12.0,23.0,17.0,8.0,10.0,BCAFCEBDBGCAAFAAFGCBEAEDDBADBADCHEFFEADEAEEFEEGAEGEHBEGAFHAFHDFBBAEACCAECBBBBBFABEABDBBDABDCEDFECACHFHAFHGHDCCAGFEEACEABFABFBEFAEBBGHBCHCC,False +457,17.0,13.0,15.0,8.0,13.0,12.0,8.0,11.0,HFCEBGABGABDAECBBCBBEBEEBFEAADACFHFEHFBACAACDAFHHFAHGAHAAEAHGHCGFCDFDAEEBDECCHCCFFGBEGCDFCBCAEDHG,False +458,4.0,0.0,3.0,1.0,6.0,6.0,4.0,0.0,FEEFEFFGCFAEAGCAGEADEFGC,True +459,21.0,25.0,18.0,16.0,17.0,17.0,23.0,17.0,HDAGCGGBBGBCEDCBBBEGFEGFEGFAFFCGFCBECBFFBEBBGBFABCAFAHEHEDHGDCCEAAGAAGBCGHCBHCAEDHHDFFDABEFECCABHABEDBEGBEGDGDFGAFEAGCDGCBHHDHCAHGABFDEADBADBHGAGAHFHGCHDB,False +460,10.0,14.0,5.0,9.0,15.0,9.0,9.0,8.0,EDEEGEAGEGBEDBDFGDEABFAFDAGEBBABDAGDBGFFHAEHDEABGBHABEACEFBDFBCHGCEBCEBEHHHFHCF,False +461,5.0,3.0,5.0,6.0,2.0,12.0,7.0,4.0,CEAFFGFFGFFDFHDFBDADACCGGCABAHGFBFFDGHDGHEFC,True +462,6.0,6.0,14.0,9.0,5.0,9.0,18.0,19.0,FGCDHCHHGHDGADGECGHCGCGHCEDGEFFHHFHFGBAHEFGBCGHFDHFHHCGHCGHEGBCCBDAHDHGBHACGCGFCDABDAG,True +463,3.0,5.0,4.0,8.0,5.0,3.0,5.0,5.0,DGAFBBFAHGEGGEGBECECCAHHDDDEDDHFDHBDCB,False +464,8.0,5.0,4.0,6.0,7.0,4.0,8.0,3.0,DACBACHAGHBEHDEFEADGGCFEDGEBGEAGBAGFDGFDAAEBC,False +465,13.0,13.0,10.0,12.0,11.0,18.0,10.0,10.0,DFBGFDFFDGBBBEDGEDBECEEDFHAAACAAHHHHHBGGAAAFHACDACEFFHFFHAGCBEFBEBAFGAHGDEGFFBFDBFDECCECCGBCDBFDF,False +466,1.0,7.0,5.0,6.0,4.0,4.0,5.0,8.0,DHBECBCDBGDBHDBHFHECAECFFGHDGBBGHCGHDHFE,False +467,8.0,10.0,7.0,7.0,13.0,10.0,14.0,7.0,GGBEGHAGEGBEDBCAFFBHEEAEFBEGCFGCFHBFEGFEBFHFCHFDGDDGHDGDCHAEGCEGAEDCEBAABABG,False +468,7.0,9.0,14.0,4.0,4.0,10.0,8.0,4.0,FECAECBDFBGFCCFECFDCBGCBGBFDAHGAFGBBEBCHBCAAHGAGCCCFHCFGCDAF,True +469,11.0,8.0,10.0,17.0,9.0,15.0,9.0,16.0,FHDFDDEACFHCFCAHDEHAGHACHDGBAGBEGBAGEHHDGHFEHADHAEFAGGCFECFBCDGDHHDADBCDBEDFFDFFCCBEDHFHAFHDFDB,False +470,1.0,3.0,1.0,1.0,2.0,1.0,2.0,3.0,CHADBEEBGHBGHF,True +471,17.0,15.0,26.0,18.0,19.0,21.0,23.0,27.0,GFFCCCHCDHAGAEGFGCBGCBFCFFHDFBDCHDGHFEAFEAEEAEGDHGHCGABGDCGDGGFFFACHBEAEEDEAHFAHDHHGCHFHHGGHBBECGECEEDAHCACCBBCFBCHGCHACFDCEDAHCAHFFFDABEEBCBAHFCHBHBGDGECGEHDHGDHGDFD,False +472,2.0,5.0,3.0,5.0,4.0,6.0,6.0,2.0,EGHFGBFEBFEDFHGCCFEABDADDBDGBGCFG,False +473,20.0,30.0,26.0,33.0,27.0,26.0,18.0,15.0,CGAHFAGFAFDBCDEGDEHBEGBEBFDGFECFHBFHBEEFEECCEFEFFHCDGAHABDFBAGBADBADBDGFGCDCABGAEGDDDDACFACEAFEBEGDCGCEFDEBEEDFEFFDABDHBDEBCHBHHFDDBCDFGDAGHBDABFBDDDFFBBACBCCBCABCACCHGCBFBDDEEBCGDCGDCEDCHFEHEAHE,False +474,19.0,17.0,14.0,18.0,11.0,17.0,20.0,12.0,GAGCCFFCGFEDEBFFAFCGDHGEHGEHGHGFDFAAFDADDADCACCBFBDGBGGBFEBCABDAGHGBDBBHFGEAGCDGFDCFCHFAGCBBABBABAEBCFCDEDHGHAEHAEDAEDGFDGDAHHAB,False +475,29.0,21.0,29.0,16.0,8.0,11.0,32.0,19.0,GGHBGAGFAHFBGAHFBHGBHGCEACHGBAAAFHHFHHCBGCGAHBDCCDGAAGHHDBDCBDFBDBEACAFCEDCBGABGAFEACGACGCCGBCGHAGADEAHGDCGCBBAFBADCGBEGBEGBAGCGGAGABCCHCDACGHDGEAHAADFCCHACDGCDGCDFC,True +476,1.0,0.0,5.0,0.0,0.0,3.0,1.0,0.0,CCCGCCFFAF,True +477,12.0,12.0,12.0,10.0,3.0,21.0,15.0,7.0,FDFAGACBDCBGCEFEFDGAGGBBDBBAFCADCADCFCGFCFFHFFHBFCCDAGAAGBFDCFCAFHDBBGHDGHFGBFBEFGFFAHGAGGFH,False +478,17.0,16.0,18.0,22.0,16.0,25.0,17.0,21.0,ACEFGEHAECACCHBGAFFBCFECADCEFAEDEFAECBCGBCHFGHGEBAEAADHGDGAFGDDCEHCHAEHDEFGHHHBHABFABFHCFHCFHCFBDFBHBEFFEDFCDBGDAFDGBHFBHAEDCFHBDDGADGDFCDFGDGBDGDFHDFHG,False +479,10.0,7.0,13.0,9.0,7.0,6.0,9.0,3.0,HGCDGCAGAEGAGCCBCCFCEFEAFEACGGCHDABDECHFABFEBEBADBDDBAACGCFDCDDG,False +480,1.0,0.0,4.0,0.0,2.0,0.0,5.0,0.0,GCEGEGGCCGCA,True +481,21.0,16.0,14.0,17.0,11.0,10.0,25.0,16.0,FDGEEGBBDHAHGDHBHGBGCBCCFACEAEGAHHDHBGFDGADAAEAAFHCFHDFABGCBGAGGADCHDCECEDBDACDAHDAGDBHHBAGFAEFGBFGBGHAGAAEDCBCEBHEGHDDBGGGGCAGCFG,False +482,12.0,17.0,21.0,17.0,21.0,22.0,20.0,24.0,HCBHEEHCEHCBHADGBCGBEEHHFGHFDHFCHCGHGGHBGCBCHGDDACDFFFFFGBACFECGCFHFAEDHDDBDDHDEGDECAGCAGHAEHAHFEFDEACCDGGGFGCEBCEDHFCHBHBEHDDABHFFFAFFBFEBEBBGAEGCEGCEBFE,False +483,19.0,21.0,17.0,13.0,22.0,21.0,20.0,24.0,GDGGEGFHAHAEHADHCEHDAACCBEFBEAAFFAFGHHBHDBFDFFACBGDDGDHHBACBFDHFDBFEFFGABDACDFFHGFCCAEBBHGBHBBEBGCDGCHGCHEFHEAHEHHGACCACGAHHEBGECGACFEEEBEFBCFEEGEHGEAGBFHBEB,False +484,14.0,17.0,19.0,19.0,23.0,9.0,30.0,14.0,DBADEECEEGGGCGGCHGAEDCGDCDDHDGGDEBHBBCAHHADGGGEGCECCACHAGHAEDABCHGGHAGDADBEFHHFBCEAGAGGDGGHGGACFFBFGCFGBBDBECBEDBGFEHDEBDEFHEBCEBAEGEECEGBGFCDECD,False +485,23.0,20.0,17.0,18.0,15.0,7.0,16.0,20.0,ADAADBBFAFFAFAAGCDHCHABGABCAGHBGHCAHEECBECGDHHAHDEFBGDGDBGDBAAEABGHBDCECCBGGHCEHBFABFABCACAECBCDDCBEEADEADHHDHDDGEHGEHGEDCBDCHAAGGBHHBHE,False +486,19.0,15.0,16.0,14.0,11.0,13.0,25.0,19.0,GDCGHFGHCBDBAAAAAACAGHBGADDCCHEGBCBDAFDBGDBDEAAGAHBAHADCDDEHHFHEAGCGGCGGBGHCGCBGCBDCGGGFEGBEDFHCFEBFEAFGAEGCFGCFGDEGAHFEHABFFBHHHHHH,False +487,17.0,28.0,19.0,19.0,12.0,13.0,19.0,22.0,DBDEFAHAGFBGHEGHDDBBEBHEBHDCHFEHGEHGBBACBAGAAGEBBHBDFBDFBDCCHCCAEBGDGDCEBCACFAEGAHDFCCBHCEHDEGCBGABGBDFHCFDDFDBFGAGGFHBCHCABDABHAHCAGCHGBBBCBHFDHADHG,False +488,11.0,5.0,10.0,9.0,17.0,10.0,8.0,12.0,HFEBAGAEFADDEHDEHAEHDEHAEDEEDGBCHCFECFBCHGCHGEDBEABGAHFAHFHEEGFHACECCADEDCEFCAFGFG,False +489,15.0,27.0,19.0,19.0,24.0,16.0,18.0,23.0,GDHCDCEEBEBBHABHFBGFEGDDHDFACCAGGADEBDEHABHAFHGBHAFCAFCBFCFHCHDEHDBBFABDEGCECHDDDDGEAGHAFHFEBBEAHCAHFGHABEFEHDHHDCGBEHBEBCCBGDGEBGEBEECEGBECBEBDEBFGHABHFFDGCCGBC,False +490,3.0,2.0,6.0,3.0,7.0,0.0,1.0,4.0,CBCEHEADEACEADEDBCGHHECHEC,True +491,14.0,16.0,16.0,14.0,17.0,13.0,22.0,10.0,FADFCGFCEFCEBCGBCBBCBBAFBGGBGBEEEFDBBDHEEHGHAGHAGDDGBEAAGDFCHADHGDHGHFBDEDDEFECCEGGGGGADGCBEEHDCGCCGABHDBFAFEEECCAGAFGAFCA,False +492,26.0,18.0,20.0,24.0,26.0,19.0,29.0,28.0,DCADFADCEHGDGGFGEAHEHHAHFCCCGHBAHEAECBBGGBHGBHDBAAFECHEBHGFHCAHDAHDAHACHCGHCAAEGGGDBGDGGDEGHHDCGEEGEDAEDCGFCDFEFFADHGBCABHDBEGBGBHCHFGDFEFFEBBEDBEAAEFEBFGBAHAAHECDGDDFDACCAFAEHGEDGEDCEHFGHFA,False +493,1.0,0.0,2.0,1.0,4.0,2.0,0.0,0.0,ECEECEAFFD,True +494,11.0,16.0,14.0,24.0,25.0,15.0,20.0,16.0,HFCEDHDDCEGCFADBEDCEDAFBACGFFGHDDDGBDFEAFCAFHDFHEFBAFBDEBEHCEDBHDGHDFAEFCECCBGGBFDBCDHAHBGEBEEHGGHABDGDGGDHADGAEEBFECEECGEGGEBEEBHGCHGDHGDEDE,False +495,15.0,21.0,13.0,15.0,18.0,25.0,20.0,12.0,GFGGDGBFFFDCCDGCDECAEFFFHCECCEDEEAEEBEFHDHBGGBGGEGHAGEAGBGEAFAHFACFCHGBBGBBCCDEGDFFFFABBBEBDAGDAHFACFAFDABDBBEFDEFAFBBFBBFEHHGHDDHBFGAFHEGC,False +496,14.0,17.0,8.0,12.0,24.0,10.0,23.0,11.0,GBFGBDGAFGBGEBFEHDGAFEBCGGGBABDAEDGEFBAFHEFHBFHEEBGEBAEGGEFGEABAHBGHBCFGEGCAGCEHEGHDDEBAGCAGBECDECDEGDEGDBDHEEHAEHDCAAE,False +497,8.0,11.0,13.0,8.0,7.0,15.0,9.0,16.0,EHBHFAFCAGEGGCCGCAGBAGHDFFCFHBHHDDHFCAECHDBHCBHAFFDFEHCGDFGAFCAFCGFEBBCBBCFHDHEDHFBHEBH,False +498,3.0,6.0,8.0,3.0,3.0,7.0,4.0,5.0,CHECBEABACCGCBGFHFFBGDBFDAFDEFCGBCHFHHC,False +499,7.0,4.0,9.0,5.0,5.0,8.0,3.0,3.0,ECEEFHFFACFAHAABEABDCCGFDGFCCFCCFGDABDCDEBAH,False +500,7.0,8.0,5.0,8.0,4.0,3.0,2.0,4.0,CAEFHGBDDBDDBDDBCGBCFDFDHCAEAEHBEABAAHACB,True +501,22.0,26.0,22.0,26.0,16.0,25.0,21.0,27.0,EBHCGHBFHBFBAEEAHFAHEADFGDFBFHCHCCHGAAAAAHAGBBBDBCHCEHBHHGDDFBEFDECDBFFHFFDDDDDFDAACHBDABDHGCEGCGHFGAFDCFGCFGBBGFACDAGHFGHEEAEEAHHBDDAABBCBCDDCDCGHFGHEBHABGFCGCEGCBCHBCHDGFFBFGEFDEHDBAD,False +502,10.0,11.0,12.0,13.0,8.0,15.0,13.0,13.0,GFHHEHDCHDEFDADGCDGBDFADFHFACFACACBFCGFCAFEECBECBACAFDEHBGGAAFDGHCBDCBHGBHDFHDHGEFGFHGFHDBEBGGB,False +503,5.0,6.0,10.0,4.0,4.0,8.0,9.0,0.0,FEDCEDCGBGGBCFCFEDBEGAACABCGCCGFFGFFDAGGBCABCF,True +504,7.0,14.0,10.0,11.0,12.0,9.0,6.0,15.0,BDBBGBFCEDCHDCHEFFECHGDEEHEDHDBCDHGABFABFBBDBBCEECHEGFAHCGFBHFAHFAHDCEAHBDCBDHGEHAEH,False +505,21.0,9.0,16.0,11.0,15.0,16.0,15.0,15.0,DFAGEAGEAFCCECCECFEGFHGDHAFBCHEDHEHBEAGFCHDHGAHFFCAAGAAGAAGAFEDGCDFHGEHFEDFBDCAHGAHBABEABGABEDFFHGFCEACHADEBCCBGFDCCHA,False +506,17.0,15.0,12.0,11.0,15.0,5.0,18.0,14.0,BHGDHFBGBBABHAEGAEDAEAEDBEDGCGHADCFEHAGHAHHAFADCBBGEGGBDBBDEHHHGGBGADGACHCEGCEHAABFAEHAECAECEECFBCGDCGBCGDG,False +507,23.0,16.0,18.0,17.0,15.0,30.0,19.0,16.0,CAHCHFAHFDGFDGEHAABDAFCAFBAGBHGHCDBAAFGFFGADAHDGDGGFEDFEDCCCCDHGFFGFFCHFAFEAFEFHGBEFEEFEECDBGGHHGHCEHEGCADCEBAFBFDBGBCHBFFBFFBCDBDGAGFABEAEAAFFCBFCADCADHA,False +508,2.0,2.0,6.0,5.0,8.0,2.0,3.0,4.0,AECAHCEDEEGEDCFFCBECDDGGDHECHEBH,True +509,10.0,15.0,13.0,10.0,20.0,25.0,8.0,14.0,BFFFFGHDGHBEECGECGEHFEFAGBHGBEDEGAEAHHFFHCFCFFHEFADFBCEHCEGFAHFHEFECBDCBDABDCBFCBDHBEFCEFCHFEBEBFEAFACFHFBAFEADDDBE,False +510,9.0,6.0,15.0,8.0,8.0,15.0,8.0,4.0,CGFCHFDFCDFADGADECCCFCAFBFFCCFEGFDGFCGCCEBBEAEEAEFGHDGDFCHFEFAGDABBCBCAHA,False +511,1.0,1.0,2.0,5.0,3.0,1.0,4.0,3.0,GDDGCBGCHDEEDHEDFAGH,True +512,16.0,13.0,8.0,20.0,20.0,20.0,19.0,18.0,GEEGAEDHBDFBGBGGHGEEDHEHEGFEGBEGFHGEDBBAHGFDAFDAEDGFFHFFHEEHDEHDGDGADCADFADABFHDFCEFCHFDGAGABHAFHGHCBFCHEHBEAAEAAEBCEDFGABDCHFCBFDFDDG,False +513,2.0,0.0,0.0,0.0,3.0,1.0,1.0,4.0,HHEHHEAGAFE,True +514,16.0,32.0,27.0,32.0,20.0,18.0,31.0,18.0,FFCEHGEAGHCGDDGHDFEDFDDBDCHDAABHAGDEGDEGEFCBDAEABBAGBCGHEEDCCBCCAECAGBDFBCHGHHDHADGGGCCFFAGBGFDGACBHCBDAEDBEDAGDHCDGCEGFGCEGDADDCHBGHBAHBEGBEFBFGBHDHGEBBDBBFCCCDEBDFBDBBGFBGFBGFBGFHDBCCCEBCGDCED,False +515,26.0,15.0,26.0,29.0,17.0,18.0,23.0,22.0,GFHDAEAAEGAEGCEDCDDCAHCABBAEBECGEBHHGAADFECFBCFECEDGDDCDCGDBDFGCGHDAHFADDAHCADDGDFGDEAAGAFDHGCHDCBDCGCBGCBFABGAHHBHDFHDFDDGDCFFAHBEHECCFCBACHACEGCEHHBHFGHCGDAGDAGECBFHAAGFFDEAH,False +516,12.0,12.0,20.0,17.0,22.0,17.0,13.0,11.0,EEBEADDAFDADAHHEEBGEBFFBEBCCDFCEFCEFCEFCABEFHEFCEFGFCGCGHCHDCGFBECACAGDAHDGGDHFDHADEADBFHBFABDHECFDCHCEGGDCDDCGBEAFEBECGECGE,False +517,17.0,18.0,11.0,13.0,13.0,9.0,14.0,20.0,BEFHACHEDBAAHAHHAGBAGCGGHAADEHDEHBBHGEHAEHGEDGEBCEBCHAAHBCHADHCDBGFBGHAABBFFFCCFACBGDBGDBFDCFDCBEHFHHEGBADEDHEGGABD,False +518,20.0,13.0,17.0,15.0,17.0,19.0,27.0,13.0,CFECBCGACDECDHCHAGGAGGAGGAGEAGHBGFFGHHDEHDHDDGAAGDDGDHBEFDAGBABEECEAABAAFAGFGDFCDCEFGECBCGGEGHEGHBGEFHFFDCCAFGAFEAEEFCFACFGBDCBCAHGBEGFDFHBFB,False +519,4.0,10.0,8.0,8.0,7.0,6.0,3.0,5.0,EABADFAHCBFGDFCDCCBACBEFDGBHGBHFEHFECEDHBCCBEDBEDBD,False +520,21.0,21.0,12.0,9.0,4.0,4.0,12.0,8.0,FAACBBBAABGAFADBABBDBBABHACGACBABBHHCECAACAHGDHGABCBDABAGBDGDAEDGCDGCABFEHEAHFBHGADGCCGBCGB,True +521,7.0,6.0,5.0,6.0,9.0,6.0,4.0,9.0,HDFFDAFDAFBFEAGABCHCHHBFHBGEBHEHHEHEDAECEEGACDECDBGA,False +522,7.0,13.0,6.0,12.0,9.0,15.0,17.0,9.0,FEHCDBCDGGDGGDHFBHAEFDEFDFGEAABAFBHCBEFBACDGBDGHHBFGDFEDEEGGBGGBHGFGFEGHCFBFFBGFGHBADCAD,False +523,13.0,18.0,26.0,23.0,24.0,18.0,20.0,22.0,HDCHAFHBBHAEFFCCGDFGAFCFDBHGFGEFBEGCEHDHHEGCEGEDBDDBGAFHCFHCAECHBFHADHFDHECFBCBBEEDGBCGEEEDGHFGECCECDACDGFBCACCDDGDDEBDGBDGAACABCABCFBEFEDHEDHDGHEFHECDECGAHGEHGCCBH,False +524,23.0,26.0,27.0,25.0,18.0,14.0,25.0,20.0,AHEABADDECBHGBEGDCHHCEDCECAFCACEFEEGGDGGDGEDGCFBAEAHFGDFCACHEBDDBADBADBDDACFAFAGCBBHBGGFDBFDGAAGAHGDHFBEEDCCDCBACHHCHECFDDHABAACAAGHHGBGGBGFBGFHDCBDCBHBHHCDFCDEBGHBGACGCCGECBBBEE,False +525,9.0,5.0,7.0,9.0,10.0,14.0,16.0,12.0,GDEGFEHFGFFECEBCBHHAHAGHAGDFCDHBDAFFFGFGGHBDHFDCFDCDGFEGEGCEGAGAAHAGEGHEHFEHFGCDBA,False +526,21.0,20.0,28.0,24.0,24.0,22.0,22.0,28.0,FBFFHFFDFEBCDDDFBEABCGECGECFHFFCFDAACAAHAHCDHGHHFHCBHBDHGDGDHAHCDHGABAABGCGAAFBGFCDFCDFCABEHDEAGHABHEBAEFHCAEABHGHHACFEGEEFEEGDFGDCCDCEDHHGBHGEHGECGDHDDAFCEBDHBGGECBDCBGCAGCEBCECEBCEHCDHEDF,False +527,20.0,11.0,8.0,13.0,17.0,8.0,13.0,14.0,DDHGDHCDHDDHEGFEDECAEHFFHAABEGBEHBCAGADGACFACECDEAHGABBCEAAEAGFABAABAHGFHEEGGDCEBAFGFHGAEDHEDHEABEABDHBG,False +528,9.0,13.0,8.0,10.0,8.0,6.0,9.0,7.0,ECDBCHEGHFFBEDBGDBHDBHDFHFEBBCDFDACACCBEHBAGBAGFDGADGACHABDAEABGGEGCEB,False +529,2.0,5.0,6.0,3.0,4.0,6.0,5.0,4.0,FCBFCBFCDCHDEHBFGFFGAEAHEGBCGCHDEBG,False +530,5.0,3.0,3.0,2.0,4.0,2.0,5.0,5.0,AFBAEGACGFGHCEHEBGEHGHDAHDACB,False +531,14.0,18.0,15.0,23.0,16.0,17.0,15.0,32.0,HBAHEDHGDHCDHDEHDEHDEHDHFAGADFEEHBBDFHDAEDEEHHHBHDFHDFHCFCFECABGGBEGCEBFBBDBDCCHCAACFACFHEEHCHHDHGFHGFHDCDDBEBGHAFFCGBAEBAHBGHAGFBGAHCFFBDGDCBDHGHGDHA,False +532,8.0,6.0,17.0,12.0,9.0,14.0,14.0,11.0,DEGAFHFDCCDGCHHBHCFDCFDCEGGFHHCAGEGBFGBDGDAGHCGCCGDCHDGEDBEFFCFDCGHCEHEGHACCAFAFFDFFAEBAEBC,False +533,15.0,11.0,12.0,12.0,16.0,22.0,21.0,18.0,GAAFFACGGFHDCBDFBAFBAGEAFEBFGGFDDEGFEACHFFBDFGEGDFFAHFHHAHHEHHFHFABECBDHHDCHDGGDGGEFGEHACGACGECEECEEBDBHDHHFHEFGGCABCAFEFCGGGBA,False +534,6.0,6.0,12.0,13.0,5.0,12.0,12.0,8.0,HDGAGHFGHFCHABHFEHFACCCBCEGCGDCDEADCFDHGDGFDGFBGCDCHFFEGFAFDDFDDGADCBECBGB,False +535,22.0,16.0,25.0,15.0,17.0,33.0,16.0,16.0,FBFFEECEEDFEFEEBGGDGFEAAEFCGFDGHDGDEGAAAHACFECDACDCHFCHFAFFAFEGFBDFECHHBACBCCACDAGFGDFEDFCCFHCBCCFACAAGADGHEFFCBFHDFCDHBHGECAFFGBGBFGAAAFBHFHHFEBFCDFCBACBHCBHAB,False +536,20.0,17.0,26.0,15.0,22.0,17.0,17.0,16.0,BHHBAFEEFAEFAEDBBDFEEBCEHHAAHAGBDGBHBECECCBFFAFEACEGCEFEECDDDGBDABEEBEHAAHCFCCEACDAHAGHBGFACFHCGHCFCCBCFGHDHCDHCDGCEAHGAFBADGGFCBFCGDCGCCFADECDGGEGAEB,False +537,13.0,10.0,5.0,5.0,10.0,8.0,9.0,7.0,EADEDEAAGAEEBGGHHBFFBFEBFBBDEAHEABCAHCAEFAGDAEDBFFGFAGAHGCHGHABCGBC,False +538,10.0,10.0,16.0,12.0,12.0,14.0,12.0,13.0,DFCGBCDFCDGBDCFCFFCFDAHDCBECEEBEDBEHECFECGAHGDHEAHAHHGFHGDHFFCGGCEGFGGCGCAAHHAEHCBDFBDEBAFADFAEBCBH,False +539,2.0,2.0,4.0,2.0,0.0,2.0,1.0,0.0,ACCFCAFCBDDBG,True +540,3.0,8.0,6.0,4.0,2.0,10.0,5.0,6.0,FGBFBFDBFDBFHFFGCEAFHCCBFCBECFABGDGHDGHBHHAC,True +541,4.0,4.0,3.0,5.0,9.0,9.0,6.0,7.0,HHFDFBDFAFFAEFEHGEHGEBGEAHFDEBCGHGGFEAFDDHCEBCE,False +542,1.0,6.0,4.0,1.0,3.0,1.0,2.0,0.0,EGEEDACCFCCBBBBBGB,True +543,11.0,8.0,11.0,8.0,8.0,12.0,13.0,10.0,CGFCHFHAFHGCGCCHCGHGACBDDBCDFADFADFBBEDAEGACFAHHGBHGDAEFGEAGEABHBGFBAEEGEHDFCGFCF,False +544,1.0,2.0,1.0,1.0,0.0,0.0,2.0,3.0,GDAHBCHBGH,True +545,20.0,18.0,24.0,26.0,24.0,22.0,18.0,33.0,CBHDDADAHFAEFCEHCEHEBHCBGCHAAHAFHFFEAFDAFBEEGHAGDDDACDHCEECEGDEGDEGBADBEDBAACEECHFBFCHFHHEEDBHHAEFCCHHFDBFDHCHHAHHAHGCHCCGFCGBGGFGDFBHFDGGDCEDADDADCFBCHBCBFHEHBEGAFHCCBEFFHDHGAEGDBGDEHD,False +546,29.0,23.0,21.0,19.0,21.0,27.0,25.0,20.0,BHEADFCDFGBFAFFACEAGFABFACFACFHEBHBFHDFGEGCEHCGDCDFCACAGDEBDEFAEFGEGGHCEHEAFEGECAAGAAEFFFFDFGGGCDGBGEBGHBGEBADFGCAGEADDBDDBACCCBDBBHAAABAHBACGECDDHGHHGBFEACHBFHEDCFDAHEAGCBGBAHFAHFBHFBH,False +547,8.0,14.0,13.0,15.0,21.0,12.0,10.0,20.0,CHCHGGHDDADDEGDBGFHCBECDEFBGHEECEGCFAEHHEHHCHHCHFFAAEDAHDEGBEHAAGBEHDEDBCFFEFCEFCHHEHBEHBEHEDDEGDGABCEBDBBCBFFBDF,False +548,5.0,4.0,1.0,2.0,4.0,2.0,2.0,2.0,ACBADGEEGEEBAFBFHDAHBA,True +549,14.0,13.0,9.0,11.0,17.0,24.0,19.0,14.0,EHAEHGEDBEDCEGGEHFBFBBGBGGFHAFHBFEACBACEADGFEACGFEGFADHGDAGCBGHGCFEBAHBGHAHADDAFDHGGHGFFGFFCFFEAFEGEEFFHFDBBDCBEHFFDFAEFC,False +550,8.0,20.0,16.0,21.0,30.0,20.0,19.0,15.0,FHEAEECEEGBBBBBHBBDDCDDCDBCBFFEGFBCEHEEHEEBEEHFDCEECGBBGAGAHCAFCAFGDEGCEFEHCDBEDHGCGFFGEEGEECBEFEHFHCDHBDFDDGGDHEFHGDECDEHEGACFAFFGFBGBGAFGDDDDDBEFBH,False +551,8.0,3.0,13.0,5.0,6.0,13.0,5.0,7.0,BDFEDFGCFCHFCGCAFFAFFHFGCAGHAEHCBCCEHCHDCADCFFAEFCCDHGEFAEBA,True +552,10.0,10.0,17.0,16.0,16.0,11.0,4.0,13.0,CABEDBDDCCDFHBACBAEEDFGACHECHECEDHDDBDDHAHCBHEFHEFHEDDGACAECHEFBEFDEDDHCBHCHFGBFEBDCFACEGCAACFCEF,False +553,29.0,25.0,19.0,15.0,29.0,33.0,22.0,26.0,EABECBEDDEFBHACGBHHEHFFAFFEDBAGFCHDGEDEHDGDDCADHAFFABHCFEEBAECAECHHHACCAEABEABCCECFECEGCHGCFFBFFBEFDGGAGAECHEHHDHHABDEHAEFFEAFAFFAGFHGEAGFFGFAACAEFFEGBAABFGBEGDFHDFHEFBBHDHHGHBCABABBFBBGBGGEAGBFGCFH,False +554,19.0,13.0,14.0,11.0,11.0,13.0,12.0,8.0,ABGABGBBFEBEDGCDFCEAGEAGHAGFAGHACHCDHADCADFGDCDDAFEGFEDHHAGCGCFDEHBEFCFFCFEABGABFCHEBABBACADEAFBABACC,False +555,4.0,7.0,2.0,2.0,5.0,4.0,2.0,1.0,ABBABDFBHFBEFEGBAGEAEEFDCCB,True +556,33.0,24.0,13.0,22.0,28.0,22.0,18.0,30.0,EEFABBCDBADEGEHHHCAHGEHABDDBDAGAABDGBABBAGBEBHEFDEDCHDAEDBFHEAHFAHFABFCBEHBEHAEHCHHFEHBEHFEFFHAFHAGHEGDDHBCEDGAFGECHHDHFAEFAECAGAGCEGADDAEBABAAHHAHGAHFEEECAACGFCDFDDFAFEBBGHBGBAFBEHDFGDCGDFA,False +557,21.0,20.0,17.0,15.0,9.0,13.0,11.0,17.0,FFFCCBHDBHDBDDBDDHDCGFBAHBHCCDAADHAHHADGADCCHBCFECEACECCFDABDCEHEHHEBHDFFABAABAGBEGAHGACGCGGFBBHBAFBABAGHAFHFGCGDEFBBCABAAE,False +558,17.0,17.0,12.0,11.0,13.0,15.0,10.0,21.0,AACABFAEFAEGCEBAFBFHBDHEAHEBEEHDHHBHCBFGAFGFCACBFBDFADFCDBHHBHDACECHHDABGBBGFGHDACEBCEBCAFHDEBDCAAHHFHHFGHEGAEGHFGHD,False +559,14.0,31.0,29.0,20.0,24.0,28.0,19.0,25.0,CBHCBFCBGABHAFHAGDBEEHABFAEDGEDECFFCBFDFFDEAEHDDCECEHCBACBDFBCEECGGCGFCFHEABDABDGBDAHFHHGADGEFHDGHEFHEBBEBGCBFBBDCEGFFAHGBHAFFGFFHEFHCCHBBHFEHGBDDHCBCFBCFBCADCDBCGCCBBCBECGDCHDFHBGHFGFCEEHEE,False +560,11.0,11.0,9.0,9.0,7.0,8.0,12.0,11.0,FDCFDGECEACDHCFAFGAFAFECFCHECHABHGBHBBHBGEGGAGGAFDBHDCHDBEDGABEAGACHBHDBDABGHG,False +561,17.0,20.0,22.0,24.0,12.0,25.0,33.0,19.0,GFGGFCGFGDHGBCGHGHHGHCGHDGCGCDDCHGCFGFAHCHFDFCDEBDEBGFCEFCFFGAFCCGCHACBFDFGEEBBDDBECAFGAFGADGADGDDGADGFDEBDBBDBGCAGHGGDGGBBDFHCCDCEFABHHBHEEHBDHAFAGEAGDABFAHHAFBFGDCEBCBFFA,False +562,11.0,10.0,11.0,8.0,5.0,15.0,7.0,5.0,GBAGDDBFDHFDGFAACAACBBGFGEBGFFCFFCEFBEFBCBACFFCAHCAHEEDBAHFCFFCDDAGCAHDB,False +563,20.0,11.0,17.0,13.0,14.0,9.0,14.0,23.0,BAGDHGEHCAGCGEFAEFBCCHCCBDADHBDHADHCGHAGAFEAHHAHHACGCEACAHCDHBDGGDFEBFHHDHHCAHGAHFEEDGFDECDHHEHACFGHFECEGBBCAACAABDABEGBE,False +564,25.0,13.0,20.0,11.0,13.0,16.0,8.0,5.0,AAAAFFCFFBBFABDAGEAGAHGACCFEFGEGAEAACACEFCFFCDCHFBBCBCCADFBHFDCCBGABGCBABBDFACAAFGACACDEEDECDBDAEDAHDAECAECEEHF,False +565,28.0,15.0,20.0,25.0,16.0,15.0,18.0,16.0,AADAACACCACGGBEGAEGBEGFHCHCCEBCEBDBBDBCDAEDEBDABDFFHHEAADAHHGHGBDGCAGFADAADADFHEFHFGDEBDFCAFEHFBBFDHCDADDACDHFHAGCGDAGCABADCADEAGEGCHDDBDCAGFHGHCGAEFFECE,False +566,7.0,8.0,2.0,9.0,6.0,8.0,0.0,5.0,HEFHDFDDHDBEDBEFBDBBECBAFBFDAFHAFEDDBCEAAAFHA,True +567,12.0,8.0,8.0,9.0,5.0,12.0,6.0,5.0,DADDAGBGGBCHFGFDAFCACAEFADFGBFABCDDFEDFECHECDBAEAHCAHBACBFFAFFBGH,False +568,27.0,25.0,25.0,24.0,19.0,25.0,34.0,18.0,GGBDADGGGAGEFFECFEBGEADDADDAFHBBHBCFBCGGEGEDHDHBDFBACBGCFACBCGBEGHHGCAGHGBAFAHHBFHAFECHCABFGHCDHEFEFCEDCEGBGGDAGFFGFFGAFBEFEAFEGFDBFCAGCAGCABAHHHCEACBGEBDEAACCFGGFGDBGDCCDBEGBCDFADBAGBADDADHCDHCDGA,False +569,17.0,19.0,19.0,27.0,20.0,24.0,19.0,16.0,DCECCEHDBFDEDGEAGFGFBCHBCAGAHGFDAFDBHAGEADCHDCDGCBHCEFCHFCGFAADABFABFEECGFHHDHBDEBDBCFEEFEEAECGDBFCBDHBDEBDAFDAHCGDEBDEHDFADFDDFGAFEFCAFHDBEBBDGGACDBCHGFFGFGGEGH,False +570,14.0,23.0,26.0,22.0,21.0,32.0,13.0,35.0,DEACHFHFDHEHFCHFCEFBFHBECFECHDGEDFFDEFHFBCCACCHGDFCHFEHCAHCHHCEHEEHCHHCAHDDGFBHCBEAGGDBGFBEHBHFBADBFDAFGGGABHAGHABDFBFHCFDCFDHEHCEAAEGCBGDFCFFEFDBFBBFBCHBHDBEDHDDBAFFCFHAEHCEHCBHDBCDEGFH,False +571,12.0,18.0,32.0,29.0,10.0,22.0,15.0,20.0,DAHAAEGCCHHEBCEBHDDGDDFFCCCCCHCFHDDHDHADBEFBECBCDBCDFEDGHDHCECGACDAEGGDGDBFHCFDGDDGAEFDCFDAADAADHBCBBCGEDBBHCFHCABFDHFBFCBCCBCCHCFFDGCGGCHCBFDFFDFFCFHHBHGFCGD,False +572,19.0,12.0,16.0,19.0,24.0,11.0,17.0,21.0,AEAGEAEEBDEGDECBBDAHDAFECHEFHGFGGDEHDECGGCAEHEHHCBHDDHDEGCEGAHGFEGEEGEECFADFEDEGCCABAGBAHAHHAEHACACHAFHBCBBAEAFBHDDADDGDBFHGCHFCHCCGFDHDDBE,False +573,5.0,2.0,3.0,2.0,1.0,4.0,3.0,2.0,ACEFDDFABGAGGACFAHFCHB,True +574,17.0,18.0,22.0,17.0,4.0,9.0,12.0,14.0,CCBCGGAHDAEDBCFCCHCFACFAEDAHDAHGBGDFDDCACAAFBBDDBDBBFCBECADDACBFCBHCHHABCAHGBBGBADDACHAGHDGHDHBEHBGBGGCFDAGCCCFHC,False +575,13.0,19.0,23.0,32.0,16.0,20.0,25.0,19.0,GGDDGDDCHDBGDFDDHBBHGBHBFHCEAFEHFGFEGEGGDGDFCHFAEFBCFGHDGDEGDBHDAAGHDDADEBCEGCEFCEFEDBACHAHFDEFCGFGHBBBABDCBFCHDCFFCHDDGDDGECGEDAAHAADDAFDCGCHBCGBCEHDEGFFHBDCBDBGCCGCC,False +576,9.0,9.0,12.0,4.0,5.0,6.0,12.0,11.0,BHFCHFGHEGHBGEFHADCDCGGCFGCBDABAEBACGHEGFBGBAHCDHCGHAGEAHHCCFCBGABCA,False +577,6.0,7.0,11.0,9.0,9.0,12.0,13.0,8.0,EDDGBABEGCGACGECECCBCCHGEFDEFGGFGBCGDAGHGCHBFGBFDEFCFFAGFDHBDADFADFHHFHEEHC,False +578,0.0,1.0,2.0,1.0,0.0,2.0,4.0,0.0,GCGDCGFFGB,True +579,5.0,1.0,1.0,3.0,1.0,1.0,1.0,4.0,HGAHAACAAEHDFDDHB,True +580,23.0,6.0,7.0,14.0,17.0,10.0,20.0,6.0,EEAEEHDHGCBEABGFBGEACAADADGADHCGFGGEHGAGGDEAFEAGEDEAAAAAAEGCFGDFGDEGAEAFBAHBAGDFGDFECCECGDBAAGDEGHAFDDF,True +581,26.0,18.0,18.0,18.0,15.0,22.0,19.0,23.0,FFFAFECGECGHCGACGACAFFGHGEHADHFDHBDHCACGABGAFHHGAFGABDABAFBHEBAEAHFAGCAGCGFAEDGHFGAEBAEHDDHBDFAFBHDBFCHEHHGFDDBAEHAECAHGHECDFDDHHBFHBFCBADFFDCCDBCABGEBCEBDEGAC,False +582,21.0,17.0,16.0,25.0,18.0,9.0,13.0,8.0,GAHDCGBCBACDDBDGADCEDBFDAFDADEAEEBEHADFAHEGDBGFHGHCBAAHDEHEEACDACDECFEAHAGGAEGAEFADBGEBGCDDCFDABDCCAGBADBDFFDGDECDBCDCCEEBBEBBA,False +583,3.0,13.0,7.0,7.0,6.0,7.0,7.0,14.0,CGGBGGBGFBHBBHCAEBHEBHFFFDFADCDBFEBGCBCHHHDHHDBHEGDECBAHFDHBEHCH,False +584,19.0,16.0,23.0,16.0,22.0,21.0,12.0,29.0,CGHFFHFFHCFGDFDEECFDCDDABFAEAADFBEAECAEGAECHHCHAEHFECCHGCHGEGGEDHBABFAHEEBGEHHHBHHCDBCDBADCACABCBCCBHBGHDFHBFHCABGDCFCCADHAHHEHHEHFEABEGGAFDFEEFEAFCDDEHFBHCHF,False +585,5.0,14.0,11.0,11.0,4.0,5.0,12.0,10.0,DGDBCBFGBDAEHACCEHCDCCBHFBHFBHCAHGGGCGGBGCBEDBGBAGHFCHDCGDBHABEFBDDBDDHG,False +586,11.0,24.0,18.0,11.0,8.0,6.0,17.0,13.0,GBBGABCCDDEGDFGAHEAHCAEGBEGAEABEAHHCHBBHCBHCBGGGGGGBHCBCCBDDDCGGBEFFADFGBCABGBBDCBDBHABHBBHFBDFCHCBGDHACCCEC,False +587,14.0,18.0,17.0,13.0,15.0,17.0,25.0,21.0,ECCAFEAGBAGCGFCGHADHEBGCGGCBDCGABDHBEGBCGHHGFHGHHGHDGCACAEHBBBABGFHGFDGFDBDGBAHHGGBCEFCFHHFEHFEFFAFFAGFCHCHGABCHEFHCFEBDEBDACGAEGEEHBBDEDDGD,False +588,13.0,15.0,14.0,18.0,15.0,14.0,13.0,9.0,EFAHGBHGDHGDCADGDDEEEECFACDGDGHCCFCEDCBHFBGDBCDBCGFCGBCEDDEAFEAECAFCDFDDBHABHFEEBBHBACBADBGDEABFGFFADGAGFAEFEBH,False +589,12.0,8.0,10.0,3.0,6.0,15.0,8.0,10.0,FDAFCFFHFGHFGBFHAHAADACFCCBBCBBHADHACFAHBBCGGEBECHGAHEAEEAFFFCFFHGFCGAEG,False +590,17.0,15.0,7.0,14.0,11.0,14.0,9.0,6.0,HEAFCADCHBHAFEFFEDAAFBABCGDDFAAGDGDCBEBFEBDEBAEAEBAEBAFBGFBHFCGCHGHDGFAAFCADBDDBDDGFAGFABEDBE,False +591,10.0,3.0,10.0,5.0,10.0,14.0,7.0,11.0,CFGCFEAFHGFCGAHACGFEADCAECAEBEDGFDHFEHFEHBEHFECFAAFHAECDHGDBFHHFAHCCFG,False +592,19.0,16.0,12.0,22.0,13.0,29.0,15.0,13.0,GHBEBBFBGFCCFDDECDGGDFGAFABCHFAFFABBCHBAFGHFBEFDEFGEFGDDGDDACDBCEAFEACEDDFFAHEAEDDHHFFDFBGFHGDBFHECCCFBDEBAHFAEFAGFBGDHADAFDAFDAFHAFGAGCHDB,False +593,7.0,6.0,8.0,6.0,8.0,9.0,6.0,6.0,DCHBFDCFDGACEACBBCBGHAGHFEHFEHDEGAEAACGFBFCHFCAEDFEBEDGF,False +594,30.0,31.0,17.0,16.0,20.0,23.0,18.0,23.0,ECHGCHGBBGFBGABGCDGHFFBFABDADAFEAFEHGBAABEABHABHACFACBEFADDADFBCGHHABFEBEGBCGEHFEFEBGEHGDAFBHDAFBAHBAHFAFACGDCHDCHDGBEBHEFEAFEDHACEBCFBCHBFHBAACFCBAHGHDDEADHAECACGBBABAFBFEBGEHGD,False +595,9.0,14.0,16.0,12.0,7.0,14.0,15.0,6.0,FEGFGGFDBAGEFGEFCCHCBEFBCGACBACFCCBCAFCAGGFFCBHGBHDBADADHADGBDGBDEBCHFCFCCGBDGDHEDADDFEBGGCFB,False +596,26.0,34.0,20.0,24.0,21.0,26.0,22.0,25.0,FEEBEHGEHEFHEFEEACGABBDHDDHGCGFDACBGBHGFHDADCFGCGBDAHHCFHGFEEFEAHEBHGBAABDABFAHFHDDADDFDBGGBFHBAEBAEBAHBAFACFADADDAGGBBGBBCCACFFBDFHDFHDBCBCABAECDFGDGHHEECCAFDBDEFCEFGDBBHBBHGGHFBHEGGEBCABCFBCFCAHBA,False +597,16.0,18.0,17.0,23.0,22.0,17.0,16.0,28.0,EECBEAGEDFCFADAHFCHFCHECDBGDBHDCHAAHDDBDDCDHHFHBAHBEHDEHAFHAHHEEGEEGDEBDEDDHBEBGEHGEHCACFHBDBACHECEBCACCGCGGEHHDHBFGEABFDFFDGFAHCGHCFHBGHGDABDAFGBEGFDFBDEHFA,False +598,14.0,9.0,12.0,11.0,20.0,14.0,7.0,8.0,EEAFAGFHFFBEAGHBCFFFFDFFBAFCEGEEGDCGDCBAADAHFFHAGHACDECBEDBEAACDGCEACHDDADBECBECHEAHFDEEEEEEEBC,False +599,31.0,15.0,28.0,34.0,25.0,28.0,16.0,23.0,EADADBADCDDCGEGGEAFEFGBDDCFACDECFECFBCHAEHABGFCCAECDEDGCDGCDGEAHDBBDBACEAFBFEBEDBEBEEFGAAGADGDFFCEFAFAABDFHDFHDGCDGHDFCDFHEFAEGCFDAFDAFDEFHBCDAFEECHHDDHDCFFAHHHHCHADEADADBADBCGCCHFAFCEHHAFHAHHAEGACCCH,False +600,10.0,11.0,5.0,10.0,8.0,10.0,7.0,10.0,HBFHBHGFGEFGEFAAFAGFGEBBHBDGBHHAHCDHEHBEAFDDBBABDFDCFHEBCECCADGADFADAED,False +601,1.0,4.0,4.0,5.0,1.0,4.0,5.0,0.0,EGCDDCBDCFDFBGBDGCAGFBGF,True +602,4.0,2.0,2.0,6.0,6.0,0.0,2.0,3.0,EDEEBAEDHEAGEABCHDCDDADGH,True +603,22.0,28.0,15.0,26.0,22.0,27.0,16.0,24.0,EADBBCFGEFEAGAFEACAHCDBABGHBHAEDGGDCGFBBFHFCEFCEFEDAEGEHGABFHBFDBGDBABGGCGBCGBABHAFDDFBDFBGFHFCHFCHFHECHDFFDFABFDBHDFDCFDCABHABHEHADCDDCDHFEEDAEDFEBHHAFHGBHBBEEBDHDHEDABDABAEGEEHAF,False +604,21.0,11.0,14.0,19.0,11.0,12.0,18.0,29.0,GHHGHHAHADHAHCGBCGBDGBDHDFAABAEHFCDDAACAFHBHHDEBEGAGGEBGEHDEGFGGCHGDBDHHDAAAACFACFHBHEAAEHADHGCHGHDBCFHEFHEFECDDHFDCGDFGAFHAHHCHBCGDCAD,False +605,9.0,11.0,6.0,10.0,8.0,6.0,9.0,4.0,DCGDAGDABEBBEBGEBGDDGHAHHBCCECAHAFFAEDCEFFEDCBGBBGEGDFGDBAAFDAB,False +606,28.0,22.0,23.0,19.0,24.0,23.0,22.0,23.0,GHDEEDGFDEHCEBCEBAGAAGEGGEGABFHGFAGAHGDCCDHFBADBDDBCDBFHFDGEEGCEHFFHCCHAGHABEACCACDFEEFAFGEFBCGBCBFAFFBFFDGEEGBEHBHHDCACFHCACAABAABAECCDFHHFHBDAEFHEFEECGFBGCDGEHCBGDBAAAHCAHDEHDBHABAAG,False +607,13.0,16.0,14.0,14.0,17.0,12.0,10.0,10.0,BGHBGADGDDGCECBEDBECAECGECGECFACFBEEBEADEDHFAHAAHBFEBHDCFDGDBFFBEGCAFADDHCABDACDABDHGFFGEEBFEBABCEFEHCHHCB,False +608,9.0,17.0,16.0,8.0,12.0,15.0,18.0,16.0,BGGGDCHHBHGBEACEACEGCEHFHCBGBBGFBGFAHCDGCFFCFGCBGBBGBFGBFAHFBGFBABCEGCEADHHEHHCHFEGEDHDDCDABGHECCFCFFGBADEAEHFH,False +609,34.0,28.0,25.0,20.0,27.0,20.0,18.0,15.0,FHGFEGEBBEGBEGHFHDFDAAEAAEDCFDBFEFCDCDDGEAFEADBCCACCDFHHBCHFEDABBABBABHAFGACGEEEACCACDDCBFCDHBFGBAGCGFADEADGABFABAGEEEBHBFDBFEBGEBEBHCCDCAGCAECAECAFCHGEEBFEAGEDECAHHABABBABDFDAHCABCAGHAGA,False +610,27.0,20.0,29.0,19.0,16.0,20.0,23.0,16.0,EDGGDCDCCDCCFAHFACFEEAAGGAHFADGADAEDCEACDAGDAHDCHFAFFHCGHCGDEBAEBAFHADHCBFBBDAECAECACGGGGFFCDGBHGECFBABDABGECGEFBFCBHDBHAHGACBAHEACCACHBHEFCBDCGDBGCBGHGCBFCADEFBFFGABGCEF,False +611,22.0,21.0,24.0,24.0,11.0,17.0,21.0,18.0,CGCHDBGDBABGACGAEAACCDDCDGCDGFDEHBABFCHACHAFGDEBDEBDABHGBCFBCBAHBDFBHFCFECFECGAGEAEBDGCGGCHGDFGDFCFBHFAFGAGHHFBHDAADCAHCAGEABCCBDDEDDHCCAAHFHHDADDBGHCGBFFBEDG,False +612,15.0,15.0,16.0,7.0,8.0,15.0,11.0,10.0,BBGABCABCFCHFCBCAGHHFHFFBFAAFAGBAGDEFFCFECACDACAFCABEEGCEGCAGDBCHBDDFDDFAFHACBGBHGBHCEEEGHCGFBHBA,False +613,1.0,6.0,10.0,13.0,4.0,6.0,8.0,9.0,GCDDCDCAHCHEDFDCCDGGDBHDCHDBHCGGFGCFGHFGFFHHCBBEEBDEDDBDH,True +614,10.0,16.0,11.0,12.0,14.0,10.0,10.0,10.0,DECEGBDAEDAEGGGHGAAEBAEHDGHGEBCHBCHBFEBCBFCBAHEDFEDFGAFDCFBCFBDFBCHCCHDHBDBBABFDGEEEDCEGAHBAF,False +615,1.0,1.0,2.0,4.0,6.0,3.0,0.0,3.0,HDEHFEDCEABEHFEDDECF,True +616,10.0,6.0,9.0,12.0,6.0,14.0,6.0,4.0,DFHDFBBECCFCCFBCDGAFFABDAGEADBDDACECFECGAAGHFHFFHFFDGDAFDEFDEBDAAGC,True +617,6.0,1.0,4.0,3.0,5.0,2.0,0.0,4.0,BDEHDAAFACHECHECDEFHCAAEA,True +618,22.0,16.0,36.0,14.0,21.0,16.0,20.0,16.0,BBGEBEHHHHHACECCGBEDBCDHHAHDCHDCECAFHAFDAFCAECGCCACCGFFDEGACGCCGCEGCGGEGACGACBDGGDEAEBAEGFECAECFBGECAEFFHBCCBCHEFADFDECDBCBFDHDECDGAABHCFGCAGCFGABEABCABCECCFFAHH,False +619,26.0,17.0,24.0,18.0,27.0,15.0,23.0,23.0,ADFABEBGDCGDEAEHBHDBCGECBECEEGAHGCCECGFCAFCHECFACBAHBACBAEBDEHFEDDEHGHHGHHGAHGAHFADAAGEAEDAFAADADHEGHEGHGBHDBCEECGFCHEBHBBFAHDCGAEGEEGECGHCFCFGCDDFDCBCFEAAAFEAHGBGDCDBEFCHAG,False +620,7.0,2.0,1.0,9.0,6.0,2.0,5.0,5.0,GBEGBDDHGCFGDGHEEHDEFAADAAHAAEAHEDDDD,True +621,16.0,26.0,22.0,21.0,29.0,29.0,17.0,19.0,EAFBDDEEGGEGGEGDFBBFADADCGDCBCCHCDDEDFEDFADFEDFGBFHBECAHCDBCGFCFECEEHAFHAFCGFBEHGFHEEHFEBCGBGGHABFGDAGCABFDBFDFFDEFBBBDHBEECFEHEACBFBDFHAHHEHHEHCCHGBAEBDCCEEFBBFAFCBDCBFBAFEACEGHE,False +622,7.0,7.0,8.0,11.0,8.0,4.0,10.0,8.0,DAGDCGDHGDACDBCFHHEGDEDEFHCBHEBHFDHEHBCGGEGBCGDCFDGEDCAABAABEAG,False +623,28.0,16.0,21.0,17.0,19.0,16.0,21.0,15.0,DEHGEHCAACGFGGBEFBEGGGBGFADAEDADDCCHGGACAACEBDGFCBDAAFBCCCCCAEEEECHDCEDAEFAHFABFACFGHHBEGCEFBAHCDHDBCEBCEAHAAHAABEDGECGFAGFABFAHFAHEAHDHBFCBDDAFDAGBGGDGG,False +624,3.0,1.0,2.0,2.0,0.0,4.0,3.0,0.0,GAAFDAFGGFCDFCB,True +625,2.0,3.0,2.0,8.0,3.0,1.0,2.0,1.0,DHDDBDABEGDDGBFAEDCEDC,True +626,25.0,22.0,16.0,18.0,24.0,24.0,24.0,13.0,EBGFHAFDBGEBGEFGEDHADHADAAFCAFCHGEAGACBDGBFBDFEDGEHGEHGDHGCFCEFBEACEBHGFHEBHEGFEBAECFBABCACCABAEDEDGEGCABEEDGEAGAAGCFFDBCGHAGCAFFGFDAFHFFGEBBBHBDAGDABDBDGBAFEDFCAFCEF,False +627,29.0,21.0,28.0,24.0,31.0,21.0,20.0,20.0,FAHFBGFACEAEHGHHCFHGAGFFCCDDBDGBDGBDBHEBHECCEHCAFEGEHGEHGEGGBCABADDACDEEBCHCGAAEAFCABCEBDABEABCAECAEAHHFCFGDFHDFHBCECEDCDFCDACEFBEDBFDBEBEHHECCEDAFDGFDHEEHEGHCDDADAAEGAFADCGCGFEGFEABACFAEBACBGDA,False +628,12.0,14.0,20.0,9.0,14.0,5.0,7.0,10.0,BAHEECEFDEACFADDABAECEHFDHCCCACBAEDHEBHEBHFHCFCCGCDACAADGEGCCGCGBCBBCGBCEBEHBEDCADBEGBCABHH,False +629,5.0,5.0,7.0,3.0,4.0,2.0,2.0,2.0,EFAECAECHGHFCDABDBCDBCBCABCGEA,True +630,23.0,22.0,17.0,29.0,22.0,31.0,12.0,12.0,CCDECDBBHBBHBGFACDAEHBFBGFCCEHGEHEECEFDDFDDBEDBAFEHBDHBFFFFFFFAFFAFHDFAEFACFCCGAFAAFGADGADFFEBHEGEAAFBDGBDADDAGEACECCFBBEEGGEBDBBCAADFEDCADFFDFAEFBHDDDDBCCBFGDAEHEHDDAD,False +631,27.0,22.0,17.0,34.0,24.0,29.0,22.0,24.0,FFDCFDCHHBFADFAGECGECGBFBAFBGGACBFCBACHEFEEFBEFEEFCBAEECEHAEGAEFACFADFDBFBHHDHAFHADDGHHEHDDGEBEEGFFDDGEDGADGBDHFDHFBHFHAABAADHAEHBHGDFGEAADDFDCCDCDDFBAGCFDCGDHBDHEAFDGBEGBADEFGCDBADGADHEHGFHBDHADGACB,False +632,14.0,22.0,9.0,14.0,13.0,13.0,20.0,23.0,BCFBCFAHGDHGAHEDGEBBCBHEGHDDDBAGBAGCECBBGBDABAGHDGHEFFBHEEEEHDEBDEFAAFAHGDGCDAFHAHGADGAGCDDHHFHGFHEBHBGHBFBBFGBFHHFAHCHHBECBGBGG,False +633,24.0,22.0,20.0,25.0,23.0,16.0,19.0,23.0,DBBDHHDHHEFEEFGABGFEGADFACHGEHGEHAFFAHECCEACEBBHBEFADDDDGGHGGHAABCFDCFBGFAECDGBDABEAFECFEHBAHFDBFDBDEFCBCCGDEACAAGBBGBDEAEAAGAAHBGHACCAECGCCDCGDEHAHGBDDEDDHDBHDHHFCHDBHEBCE,False +634,17.0,21.0,22.0,24.0,23.0,23.0,16.0,18.0,CBHDBHCEHCHBGDBECHEHFBCFDFBDFCGFCACCACCGDEAFGADEADFCDFBAHAGHGEBDDBDEBDHBGBDAEDBEDCEFCEFHBHCGDAHAAEDEEGGECBEHDGDBGEHFEFGEFBFFAFFCCFECEDHEGCAGBACFDGFDHFBABHADFBEFHADC,False +635,16.0,6.0,8.0,5.0,5.0,8.0,8.0,4.0,FFABFACAAFAAHAFHCEACEABFCDGCFACABGGDGCABAEBGEAGBAGHACHFEDDDG,False +636,0.0,0.0,0.0,2.0,3.0,1.0,3.0,2.0,EHGEHDEDGFG,True +637,9.0,16.0,10.0,10.0,13.0,11.0,8.0,12.0,FEDBEDBEBBEFBEHBFBFCBEGBAGBHGHDBDDEGBECEFHDDHCFHGBHEBCGBEFAACBDEFCGFAAHAHHFFAADAHDCHGCECC,False +638,12.0,9.0,9.0,12.0,9.0,15.0,8.0,15.0,EFGFDCDAGDHFCBFEAFHACHBGADEEHEFGEDHFDGDDGAECCFHBFHBCACHACHACFAFBGDBGDBHBHHBHDEHDAAAEFFFHF,False +639,14.0,20.0,11.0,14.0,9.0,16.0,14.0,14.0,BFBHEBAEDADCGDAGDAFBHCBACBAEAHHCGBCGFCGAABFCBFGADBFFFDFCDFEAGGDHDDEFFHGHHGHHEFEBHBBGDBCHBEHBEFBCABDGGDCGAFHBFABD,False +640,8.0,6.0,17.0,2.0,13.0,12.0,17.0,7.0,HCFFGFCHCCACAADFGBFCFFCGFCABGBEABGCEGCEGCACCFGDGECGHCAEGBEGEEGHBGEAFEHFEHGHGEECCGF,True +641,14.0,17.0,15.0,14.0,30.0,13.0,21.0,15.0,BBGEDAHDBBEHBCBEHAEGAFGECGACGADAFGFFGFEGDBCCBFCHDHABHEBGEDADDHEGHBBHEGCGCHEEHEEHGEHACACCEGCGGEDGFGAFDBFCAFBAFEEEHGEGFEBEEBHEFDECEEDEBGEDCAD,False +642,26.0,25.0,28.0,26.0,13.0,16.0,19.0,13.0,EBDECDGCAACBAHFACDCCBCDDHDFBDBDAHGAHGBHGBCFDEADGADGHFGBAHBCCDHBDFDFHAEEFDCGGCFCAFGACGCCFADBAEBGBGGBFGDFBFCAACAACECBBHBBGABGFCAHCDFGDCCEBCDACHBCAAEDEEDFEHEDABDACDAGDBB,False +643,14.0,19.0,17.0,9.0,14.0,22.0,18.0,8.0,GCCFBFFBEABEHDEBDGBDFAHFBHCBDEBDGBDHHFFGAFGCGHCACFBGGAGGFEGFCAFCADGGCFECECGFAGFAGACHAFHDCBBCBFABFEBCCBGFEAECDBBFFBAEEEEFG,False +644,15.0,27.0,16.0,22.0,21.0,27.0,27.0,18.0,EDFEFFDFBDGBEGBHCFHCFHFAHFGFFEHGEBGEBGABGCGEBGFFHADEDGEBFABGAEFEGFGGAGFDHFBHCBADAEFBCFCCHDFBEADEDBBBGDBDCACCFCEFDDFBHHAGHGGBGBEGCFCBFEGDAGDEHCEHEBHEBADHDHHDGCDGBAFBDCGAFGDBB,False +645,14.0,11.0,10.0,13.0,16.0,12.0,10.0,15.0,EEHEEHGEFGEDEDBGCBHHFHBFDBEEBEBAHBDGACGADGHEHHECDFHDFDFAEFACFBEBHEHAGDCHDCDGCFAAFAAGCDGCAAAHHFBCDBAFE,False +646,3.0,5.0,2.0,4.0,7.0,6.0,2.0,5.0,EEDEFDFHDFHGFHCBHFBEEEABHABFDBGCEA,True +647,17.0,19.0,20.0,19.0,12.0,18.0,17.0,19.0,HCFBAFBDFDHBCACEAFHCGGCAHBHHBHFECADGBGCDACAECGDCFDFEHBABGADGACGBEFHGFBDBCCBCFBDFADFGGFEGFHGFEBDDBDDADBFGCFGHECHCHHGGBECECCEBDEDHADHADHAFHAHAB,False +648,10.0,10.0,6.0,7.0,5.0,10.0,7.0,10.0,CHGDHGHAECAEAGBCGCEDFBGFCGBCFBHAEAFHDFBEHBGFAFFDDABDABDFBHFHHABHA,False +649,23.0,19.0,18.0,23.0,11.0,22.0,22.0,16.0,DFGDAGAEGAEDABBFDGADBHHAEGECAFDAEDACGBCGDCGHCGBCHEGACCAFDBFHBGGGDBGBFCBEGFHAHHCEDAEDBBAFAFFAFGAHCHCCDCCGBDEFHFFDBFBCFDCDDAAAGDEBDBBHBFHGFHFFHFAHGDGGDACDAF,False +650,4.0,5.0,4.0,4.0,6.0,3.0,2.0,5.0,DDHGDFGEFAECAFCDBCHEEAEEHHBACBHBB,False +651,29.0,15.0,14.0,25.0,15.0,16.0,23.0,19.0,GAFBABHAGGACGAGGAGHABDGFCGDEGEFDFACFBDAHAAHCGECDHFEHCDDEDDECGFDDFEDADAFDBFDBEGHFBAGBADBCDGAFFCEDEHAAHAACGAGDFDDFDAADCAFHBEHGEHGCGEBBHHBCDBCDHEBAEGGHGHHAAHAA,False +652,17.0,19.0,21.0,19.0,20.0,33.0,24.0,19.0,EBHGBHEFHAFCFFEAFEADEBHCBFCEFDEFHBGHGFDGDAHEGFEABBBBFBBFBBFAFEBDHBCBCGFEHACDCFDBGHGEFGACCFFFFDADGFDCFGEGHHGEHFFHEFHCFAGFBGCCGDCDDCGECGHAHEAGEDBCDEHDGHFGFCCDAAFAAFGAFDCGECGD,False +653,4.0,2.0,1.0,5.0,5.0,3.0,4.0,8.0,GBFEDEDGEDEADHGHHGHHDBHAHEFHCFAA,True +654,20.0,23.0,22.0,29.0,18.0,18.0,13.0,18.0,EDEBAEGHHFAHFBDDBGFBGDDABDABDADCCBBCEHGFCGFCDEHDFDGHDCBDHFDCBHBFHECCADGHGGEGBCBACHAEGEEFDEHDCHBEHFDBFCEACFAEDAFBGDBDDBDDBFDCFDCHDAACAABACGFCACDHHAFBAFBHEDCEBEEAC,False +655,7.0,8.0,11.0,11.0,11.0,5.0,11.0,11.0,CHBCHDCHBAHBCGDEGDACDEBAAAFBEFHFBGFEDEEAEEGDGGDGHDAHDHBEEGDECCBHCGCCGHCFHDG,False +656,23.0,22.0,23.0,10.0,19.0,19.0,24.0,14.0,FCGFCGAAEBHECHECHCGABAAFFEHBAHBCBBDEBEFDFADFGDFACFAFAHFBCEACECCDGBFEBFCCCCEGAAHAGEBGABCFBAAGFDFCEABEABECDGCGAHGHCCHBAFBHEEHCGBFGBAHBGGEGGEDBEDBDFGGGGGGACH,False +657,17.0,18.0,13.0,17.0,9.0,17.0,17.0,24.0,BDHBDGBFEBCHBDFBDHBAHBHHAAGABHACFFHHBBDDHHDHGFCFFCGHHBAHADGFDCFHCHCCBDFFGAFGAEEAGEHHBGFFGFAGHADHDCBDEFDECGAGADCAGCHGEHBEHFDABDGBCGAE,False +658,8.0,8.0,5.0,2.0,2.0,4.0,5.0,8.0,CEGBBGBHCFHBHBBABGEBHHGCFAAHADHAHGACFACFAD,True +659,34.0,21.0,21.0,17.0,21.0,20.0,30.0,25.0,HAFHDCDEGEEGAAGBGCBEAGEBGEAHCAHEAHCAHAAHFBHECECABCAHGGFGHHGEHDADFACFACFCGFCGFBBFAAHAAHBFFDAFDGFCAEAGFAEDBGBCEEFFFDEAGGADGCDFHGGHBCABCABCABHDGDGGEGGEGHEAHBDGBHHBCHDFAECGDBHAGHADABBACEFHBDEGC,False +660,14.0,30.0,12.0,19.0,8.0,11.0,20.0,13.0,DEBHHDCGGHGCHBFBFGBFDDFDDGDGBDBBABHDBHACECCACEABBAEBDBBGGGCGDAHCADCABHEFHBFDCDCGGFBGDBDBBGGBCGBEBBEBBHHBHFFHFAADGBBGBGADDFEAAGA,False +661,11.0,26.0,15.0,26.0,16.0,14.0,18.0,26.0,FEBHBBCBDCEDFABGAGEABBHBGCDGFDEBBEBBDBEGBEDDHHDHFBHEBEEGAHHDHHCBHCAHDHCAACEGBEGBDGBHBHDFHDHDFHECHCHEAHBGCFCFHDDHDDFDDAGEGGCCGDFGFAGFGDBBBHBDHFDACDCHFGDE,False +662,5.0,2.0,4.0,1.0,4.0,3.0,0.0,4.0,HCDFCFHCACAEEAEFBHABHAE,True +663,14.0,22.0,18.0,13.0,14.0,22.0,18.0,29.0,DHBHHBGHGDDFFFCBHCBFCHGCGGHHHHABCCBAFAEGBBDBFCFECFADFHBCHADBADGHDGCDACFHBFGFFBFGCFAAEACHAFHEEEEHGEHAEBGBGGBFCBFBGGBGAHDHHBECEHCHBFECFHAFHDCHDEHDEHGFHB,False +664,22.0,13.0,19.0,20.0,21.0,19.0,24.0,26.0,AACFEGGECAHDGHDGDBEHBGDGGCBEAGEFEAGBGGBFFBGGGGDCEEAAFFAHEBFEFACFECEABEFHGFHDAHCBHCFGDFHDAHGEHEAHEAGCCCHDAHFCEFCDCAFCGCHFCHGCHGCBGFBGHHDAHEAHDHHDHEEADEFDHADADDHDBADB,False +665,19.0,16.0,20.0,18.0,23.0,17.0,22.0,24.0,DAACFCEFCEHBFHAEHDBHBHABHABHAHCCGGCGCEDBDHBACCCCCAEDHEACEHEDGECGEFGCGDEFHCAHADFDEEDBECEACDGEDGFHFAEFAGBHHAHHDHAGBBFCGFEGHBHFDEFDHFHHABGABGEDGEDGEGGBCEBGDFGFFGA,False +666,21.0,15.0,10.0,14.0,9.0,13.0,18.0,9.0,ACFGBACCACCADCDGADGADGHBABGDFEDEGAGFADADDBEABDABEABAFBAFBGFGGACGBFEBFEHFHGACGCFEDGBGABCEHFGBAGFEDADBAFHHGHHDH,False +667,8.0,7.0,10.0,12.0,11.0,15.0,18.0,9.0,FAGEGGDGEAGDFCFFHBFDBGDFGBAGHCGFCDBCGBDFHGFHEACECCECAEFGCFGHFEDGHGBHFCHAEDAEDGDFGFGEBEDHAD,False +668,10.0,9.0,8.0,13.0,5.0,7.0,10.0,7.0,GFDGECCECCFHAGBGDBDFADGEDAADAADAADCGBGHBHBDHFGHFAHFACDEHBEBDDCGGCDFBB,False +669,7.0,12.0,7.0,12.0,9.0,2.0,15.0,14.0,HBGHAGHEGBCADABEEHFCCGHGGEGGCDGCHGEDGDBADBHDBGEAGAACEDDFBHBBHBDHBDHGCHGHDEEBHD,True +670,0.0,5.0,2.0,3.0,7.0,4.0,3.0,4.0,FGCFHFEDBHBBHFBGEBEEDEEGEHCD,True +671,5.0,12.0,12.0,3.0,8.0,4.0,5.0,4.0,BBCBBAECHCGHCHFCFCCBDBECBEBFEBCGHCEFGGBAGEAEEACCBDABD,True +672,11.0,18.0,12.0,10.0,18.0,18.0,25.0,17.0,AGBBGFGCFCEFCBHCADEBHCHDEBGGGGGAGGCGFHFBHDBFFAFHAEHFEFFAGBEDHHHHBBCFHAFCGCCBEHBEHGDBFEAGEHGEAGEAGEGDBGDCGDGGDFHEFEBBCBAGBEDHEFGEF,False +673,9.0,13.0,14.0,18.0,14.0,11.0,8.0,15.0,CGDBHCCHGBFGAFEEHEHCEHCACCADCDDCGBCDBHDHCBHEHABHEEGDFHDGACBAGDFEDFEDECDBDHFEHBEFFEBCEBDABAAGFHFDDFDDHB,False +674,8.0,13.0,7.0,9.0,11.0,13.0,8.0,11.0,GHHFHFCGFBEFDEDDBFDBAHFHHFCHEDGEHGCBDBHHAEGAEAAEBAGBAEFCFGCFAHBGEFECBCBBDBBDEFDF,False +675,1.0,9.0,5.0,1.0,4.0,4.0,4.0,4.0,BECBCFDGHHBEBBFBBFBCFBHGAHGCEECG,True +676,7.0,7.0,1.0,4.0,6.0,8.0,6.0,3.0,ECHEDFEAHHDFABGEBEABEDGFAGBAFBAFGFGGFABFDB,False +677,14.0,18.0,19.0,11.0,14.0,16.0,16.0,25.0,EEHFECBGCECHDBHGHHGHHGABBDFBDFBAFHAGDABCABFHHABGAEGDBHHGHFFHDFEDFHFGACBCCGCAAFFAHACDGCDBCHBFGBHEFHAFCCEBBDHCHFAHEGHEGCEHCECCHGEGBECBD,False +678,9.0,12.0,6.0,10.0,11.0,11.0,13.0,11.0,CDEAGGDGGCGBCGBAGBGEBDCAFGHFGBFEHEEACFAGFDEFGBHHFHHEHFCGDADHHDHEDAADFBFBBFBEEHEABBD,False +679,27.0,20.0,25.0,20.0,31.0,18.0,23.0,23.0,EFHEDHDDBECBDAFEEFEEAADGGCGEBGADEECEEFEECAFCGEGGBFCBFABGACDAEHBHCFGCHGCHGCFDCBHHBEABAHBABAHEAHGADGCCFECDHDFAGECHAFBADBGDBCABHADDBHCEHCEHBFHGFEEDCDHCEECGCDBCAHGHBGEAGEAFFAFGAEEAFAHGEHGDACD,False +680,27.0,26.0,27.0,28.0,20.0,19.0,14.0,25.0,GDCFDCFHCBAEGAFACFAGFDBEABDBCAHCGFFFCFBBBADBGFCDACDGDDHCEHAEHBFGBHECDEGAACBHCHEAHEFCGACDBHDACGACHAHHAHDEHFCBBABBABCHBFDCGBCHBCHFDHEEBDEHEEHGEFABHAHCAEDBCDBCDEEDCBDBHAFAGEADDADFADFDDHGDEC,False +681,3.0,1.0,1.0,3.0,4.0,8.0,7.0,1.0,HGFEDDABGFGGFGFFGCGAFDAFEEFE,True +682,15.0,12.0,11.0,14.0,15.0,27.0,23.0,14.0,FHFFHFCHGEDCEDGABGDBGFFGFHGDDFFDGCHECAEGEBCEFCEAAAAGACFAGGGBEGBFBAFBAGGAEHAEHBDGGDFDAHGGEGGHAFHGCEFDBFEHDDBGFBCFAFFEHFCHFHDFCFFDEFB,False +683,3.0,2.0,5.0,6.0,4.0,4.0,5.0,2.0,GGFDFADFADECDCGBCGEDHEDHGCBCAEF,False +684,13.0,18.0,21.0,19.0,20.0,13.0,21.0,11.0,FEEGGCAGBEGFECBEGBDHBDCCGACGFBFEHHEHBCHCCFDCDDCEACEAFHHFCFDEBBGBDCBDBADEDEGCFDHABEDGEGFDCFECDEAHEDGEAGFAEAAGHADABDBGCGGBGFBDCBDGBCGECGHC,False +685,10.0,7.0,12.0,11.0,9.0,18.0,8.0,9.0,HDHAGFAFFAFFAEBDCBDBEAFEACEACDGDDGFCHFCBCCACHGCFFCGDEFDFHEFHDCBEHGEGFFDFAAFBEFCDGHBH,False +686,6.0,12.0,8.0,11.0,9.0,7.0,20.0,10.0,BCEBCDBHAGDAGDHGDEDAGDGHBEHDDFGDGEDAEGGGCEBCBGGGCHECBFHHGGFGGFGGHGAHFBBCBECBHABFDEF,False +687,12.0,20.0,16.0,25.0,15.0,20.0,20.0,33.0,DFDHAGHAEHBHBFCFFDHFDBGGCCBDABHGGHBBCBFCHCEEADDACDFCAFBHBHDBHFBADGHDGHDGFEEBHHGGHGHFGDFCDHEEHCECCHDBDAGDABDCBFHAGEAHEHHEHFDHFDHFDEFDCCGBCHEDHBDGEHGBBGFDHAHHFEFGG,False +688,3.0,9.0,2.0,3.0,7.0,7.0,3.0,4.0,CFEHFBFBBEDBCHAFABFEBEEBDEHFEDFHBGGBGA,True +689,15.0,26.0,20.0,34.0,29.0,23.0,27.0,17.0,GAAGDABHABEGDEBDFFDHFEHFBFCBGCBCCDGFDEHDCFDBHEBEFBEBCGCDGADBDGGGAAFCEDCEDBHGBDDBEDFFGFEHBEFFCAHCHHGFDDBCDBDFEHFGAFHFFDBEABEFBGFAGHGGEECCGABDDBEEBECBEAGCHGDHGDEDHFDHDAECAECDEDGEDEBCEDDGGDEGBCG,False +690,2.0,5.0,5.0,7.0,3.0,8.0,3.0,2.0,GFGFFGFDHHAEBCCBCDFCDEADFDBFDCEDBBF,True +691,11.0,14.0,14.0,3.0,13.0,5.0,13.0,10.0,ABGFGEEGEEGEHAHBCHBDDGHBBABACBCEEGECGECGHCABCABCHBEGAEFCCGBFGCAEFGECBFHACHACHDHBGBA,False +692,17.0,27.0,23.0,13.0,20.0,16.0,15.0,12.0,BCCBCGFCGFADAABEDHEHBEADCFFEFFCABCGBABBEGBADBABBFCACGEDBEBBGFBGHBGHDEHBEHBCHACHFGEECHGFHGCCGECGDBBDGAEADFCGECDEFEFCCFAHFEHEABAFCCECEBDDBADBABBC,False +693,27.0,22.0,19.0,22.0,14.0,28.0,28.0,25.0,FCDFEDBEDFECFBHAAHEACBFDEGDCGFFHHFADGABFAFAAGGBHFECAECAGCGBDGBDHBHCBHFEHBBAFAAFAFFCHFGGFHAADCCGCCGBHGDDGFDGBDGBABHAGFDBFGBHAEFFDGFDGCAACAGGHDGAGCDEHDHBGHEFCEFADHEHABHAFHEHHDBGGBFCBGCHAD,False +694,18.0,13.0,19.0,10.0,11.0,15.0,13.0,6.0,GDGHAABAGDGHFBFGBCGACGAEAFDAFDECHECACBFCBACBEBDGBFACEEBEDCEACEBBDDBGFAFFDCFECDHCACCGBFGHGCEGCAAHAAFCAFCFF,False +695,10.0,11.0,11.0,10.0,20.0,12.0,15.0,5.0,DBDBFDEGDBGEEGEGFAAEGDFCFECEEAEEBHGGHCGHCFACGHEGEEGAEFCEFBAFBAEEACCGFDBFCHACEDFADFGBGCBDEBEGBD,False +696,11.0,15.0,9.0,15.0,19.0,14.0,16.0,14.0,BBEABEBFEDFHBEDCFCEDEFDECCEFGFGBHGBCGHGFHEBDGBFGCFGDGDACDAFBFHBHGECGEHDEHBBFDEEDGEFCAAHEABEHHEAHEAHDAHDGGDBGFAGAD,False +697,4.0,10.0,3.0,4.0,4.0,9.0,13.0,9.0,EFFBHHHHHCADDEGDFGBBGHFGBBBBHBACEHCFBEGDGGFGGFGAFGAGHFGB,True +698,8.0,6.0,6.0,10.0,3.0,3.0,10.0,9.0,CHGBHGEHGAAGHDGDAGDBDHADHBDHDAFACBCFBGEHCEFCGABGAGDCDDH,True +699,23.0,20.0,26.0,25.0,24.0,29.0,20.0,24.0,CDBFFGEGEACCACDGBDCHACHACHBGDBCFBHFHHFHHAGHAGHCHAEEGCEHEEFFCDFDDFDFAAEEFEEFBEDAEDFGDFGDHHDBCBBCEBEABADDAEDGGGCEHAGBEFBCFDHFBEFADFDCEHFEHFHADCFDAFHAFBFCEDDBCAHAACGCBFCDHBFHDAGFEGFGGCCGCBBCAHGE,False +700,29.0,20.0,21.0,24.0,24.0,23.0,13.0,26.0,EBHEBHBADGAHAAEEACGAFAAFBBFCHDBHAGCDEBDCDDAHHBCEAAFHAFCABDDEDEEDFHDFCDFBEGCFGEFAFGCHGDHFFEFHEDDEADBACACEFCBHCEHCAAEAECAEBFDAFHAHGAHGBGCBDHBDABDHBDHADFGEBABHFCFFAHFDECHHCHHCFCGDEGEE,False +701,3.0,7.0,7.0,3.0,6.0,6.0,4.0,11.0,CEFCFHGFHBHEAHECHEBBAHAEECHCDHCFFCHBGFBDDBGHBGH,False +702,9.0,6.0,16.0,15.0,12.0,8.0,10.0,9.0,FDCFDCDAHDGHFAACBCHDEHEGDEDDFDDEGCGCDBCDEAFCBCCBCGACGACHHEEHADDAEDCECFECFAGGBBEHFGHEG,False +703,6.0,1.0,3.0,5.0,2.0,9.0,6.0,6.0,DABEAHCFGGFAGFHHFCFFHDFHDCGFFGDEGDHAAA,True +704,4.0,1.0,0.0,2.0,2.0,1.0,3.0,0.0,BGGAAGEADEFDA,True +705,18.0,19.0,12.0,21.0,25.0,19.0,18.0,24.0,FDAHBFHDCHACHAEAEEBDDDDDGFHHFEHDDBDAAAFHAGGAGDABCHGCEGCFDBGCBEFHFDHFHHEGCFABHEBHCAHBBHEAEEAEGAEDEBGFCDHEEHGEFGEFBDFEGFGHFDHFBHDBGDACBAFBDFEHEECBEGBDGAEGEHBC,False +706,17.0,12.0,10.0,18.0,25.0,13.0,22.0,21.0,AGEHCDCDAEDAEBAGGHGGHDCHEHEFCEABEGBEBHAGABHABFFGGFGAFGDBGAEDAGFAHEEBFFAEFBEHCEFDEFEHDCHDCHDGAEGAHHFHEBEEGABGDHGDHBDHDHGCEDCHFCEEDDEHDGAGGE,False +707,18.0,24.0,22.0,26.0,29.0,18.0,27.0,19.0,HFHHGDEGFHCDHCEGFEGBDCEDEEFFBFCAEBBGABHADAAGABFDCGCBHABAGHDEDEEHBAHDAGDBGCBDHHDBEEGCFGCHCFHBFDEGDHDFHAEDAGDFGEFCEGGEBGCCCCECGECGCHACEGCEFCDFBDFBGBEABECBEBBGAHGDHDDAABGGBEGAEBEDFDDFEDE,False +708,20.0,10.0,10.0,16.0,13.0,13.0,19.0,23.0,FFHDFHCCACGGGHEEHDGGAGEAGHAEBAHDGHGGHBGAGFCBDCDDADDCEHADDDHBAHBAHBGGAFAAGAGGBGFHAHHDHGEHEFHCFHCBACEDBDDFCEFAHFAHEAEFHFABEDHE,False +709,5.0,8.0,2.0,9.0,7.0,8.0,16.0,8.0,CGDAGDFHDGABHDEFFBFFBEDGGAGGCEGHHGADEFDEDHEDGFBGHGGHGGBGBBAHEFB,False +710,2.0,0.0,1.0,2.0,0.0,3.0,1.0,3.0,FGHDDHAFHAFC,True +711,11.0,11.0,7.0,14.0,11.0,15.0,19.0,23.0,DHDDADGHBGFBGHHGDGAHHHGHHGBCEDCHDHDECGGFDDAGBHGBGDAHBFFBFFCHFCFFHBFHEHHGAFGAHGHDCDDAGEHGEHBFHEGBAGFAEFCEABEAEEF,False +712,22.0,16.0,19.0,9.0,22.0,12.0,19.0,16.0,HDGBAGAAGFEEFADBADHGCGCDBCABEACGHGEABEAFGHFEHFGHFGHCGEFGEFHHACDAHFCGECEABEAEEBBABHEFEAGEDGBCEHDEADCBDABCHCCHBCGAGHACEACHFCEEBAEBAGBGFCC,False +713,10.0,16.0,20.0,25.0,19.0,11.0,23.0,14.0,FDCDDBFDGCEFFEBBEBBFDBHCFAAHGDHDBFFGFDACDAEDGEGGDCADCDDGEDGEGCEGDADCGDCBBHEBDECEHCEHGBHACEGGDCGHHGHDGCGGCGCDHHDECCEBEEDABBAGBGEAGEFDHFBHCC,False +714,7.0,8.0,11.0,9.0,14.0,8.0,8.0,14.0,AADAFBHGCCGCDHHFHBCHDCHDEHEEBFBAFHDGHDHHEAFEFCEGDHBEHCCFCHBBEDEEAFEAECGECGEGDBG,False +715,4.0,5.0,2.0,4.0,4.0,2.0,5.0,7.0,BEEHHBHHCDHCGEBGDBDHEFHFAAGAAGBDG,False +716,2.0,4.0,4.0,2.0,5.0,4.0,1.0,3.0,GBACBHFFEFFDHBDHEAEECECCB,True +717,15.0,12.0,19.0,9.0,14.0,21.0,18.0,23.0,DBHAHHEFBFAGHAGHAEHFEAAGCGHBFHBAHDCHCCDAGGHGFDAFEEEGECHCCEBGDAGCAGHGFACDHBDGBAFCFFCDFCFFCEGCBGFBCHBHAGHFHCBHAFHCFGCEGCEHFEBEEFFHDFH,False +718,21.0,29.0,17.0,17.0,19.0,12.0,14.0,21.0,BHBBDDFDBFDBDHADHBCABAHFADGBECCFDBADGEHHBBEGHEDHCHEBHBHHBEEBCABFBBFBFDAFABDGCEGCEGBEACEBBBBCDCHGEDEEGGHGAFGABGABAAHAHHAHGAHGEHCDCFDCFEEDEBHCCCACAAFABE,False +719,15.0,18.0,17.0,14.0,22.0,18.0,20.0,22.0,GGECFCHFHBEHBEDBEFBEHBDHBGAGFAHFAFECFDFHGFBGDEHECDGCAEFHEFBDGHDGDBGBBGBHGCCGCCGCHHEBBBBEEAHHBFEACADDACGCFEHFEHFAGAHGEHFAAFCHDCEGCEFDEGBHGDHEECAADA,False +720,4.0,4.0,3.0,2.0,1.0,3.0,4.0,4.0,BFBBFHBCHAHDAGEAFCADCGGGH,False +721,22.0,14.0,33.0,22.0,22.0,16.0,25.0,18.0,EGACBDEEDAADHAHBABBAEGAEGBHCBADGFBCFBAACFEEFEDHBDCGECHHHAGEAFECFEGFGAFGHCGAFGEFECFGCABEEGGDAGDCCHCCHGDEGBEDBACAHDACCCBHCAHCHDGHAECDDCDHCFCDAHHCECGECGDCGFGECCCFCCDDGDDGDFGBF,False +722,15.0,12.0,9.0,7.0,14.0,11.0,9.0,13.0,HFDHFEHEGDBCFBCAAHFAEFGGDBADEAFEAHEAHFBGFHEAGEDGBBABHGEHGECCABCEHDBADCFEEFAHFGHEAHACCABCBB,False +723,25.0,27.0,19.0,19.0,29.0,24.0,29.0,27.0,CHBDGEDBEGCHBAGECBACBGCEACAGCAGEFHHHGHAGAEDHGCGBBACHDGDAGDAGBFFBGFBDFEAFBABACDEFFEAHHAEHGHHBFABFACHHHEBGBBEABEAHEDGEDBFDCHDBGGEHHEGHFCHFHAFDAFEGGHGECDFGGBGCFEAGECBECBECFEAFEBFEHFEHBDDAEDADDFCBFEBFGHG,False +724,7.0,6.0,4.0,4.0,2.0,2.0,7.0,4.0,BACDABGAGDBGHFGHFCHAEGADGBEGBAADCBHC,False +725,13.0,14.0,14.0,9.0,9.0,11.0,7.0,5.0,ADEDDFDEGBCACCABCADGAFGFGAEGAGBAFCFFHBBHCBDBFEGAEDBDFHCEECEAFBAFHCFCCDBCABCABHBBEC,False +726,6.0,1.0,2.0,1.0,0.0,2.0,3.0,0.0,ADAAGACFACFBGGA,True +727,22.0,23.0,26.0,27.0,23.0,28.0,17.0,22.0,ECCBCCADCDDGGAHBAHFHCGHEGHCAHGHHGBEFCAFBAFHDFAFCCBACDGCBGHGEAGCDECFEBEEDFDFBHGBAGBADFEDAHDACDGEFEEHGEHFAHFAEBDBBEBFEDAEDHDDCFDGDABEGDFHBCBFDFFACFAFHEFHABDCCEABEFFHCFBFFBFCBDCBDCEDGDAHDCHCE,False +728,0.0,0.0,3.0,1.0,3.0,4.0,2.0,2.0,CEHCFCGFHDFEGFE,True +729,17.0,19.0,22.0,26.0,19.0,16.0,18.0,23.0,GFHGAGFACDAEAGFDCBCCBCBBGBDGEGCEHDDADHEDBADHDEFBEDBDGBCGAHHAEAAEBDGDGGDGABBECDEFDEFHCAHBDHBHGGDFFEFDCCDACBAHEABCHEEFCEFHGFHDEBGEBHHHHCFHEAHBAHCDDDDCGFCHFCHCCFCD,False +730,10.0,12.0,10.0,12.0,5.0,3.0,7.0,9.0,GGBHAHCBEBDABDCEDEGDCGDAFAHGAHDADDACHACGECADHABCCGCBBCBBHHBFDEHDBDFB,False +731,8.0,9.0,15.0,9.0,17.0,19.0,15.0,6.0,BHGBCGBCDBCFBCBACFAFEGFECFEGFGCEGCGADEFECHEDEEFFEFFGFFGDFCEGCACBAFADCGEEGDBADFAHHDGHGFEEDCEHFFBGEC,True +732,15.0,25.0,16.0,23.0,8.0,23.0,16.0,19.0,CCGCCHDFHDFABAHDHGDBFDHDDBBDHBGHGFDDFGGHEHABDFCHFAFCACBBDDBDFBDABHABGBEDBEDAFCFBCFGEBBHCBABGABGHBGHFGCFGCFGEBEFADCHFHFFCDDCHAEHBDGADAADGFCFFBFEBH,False +733,26.0,12.0,25.0,16.0,6.0,12.0,11.0,16.0,DDEFFEHBCBCAGCHGBHAAHCAHAHHBHHGGHCFDCADCADABFCCGAFDAGHCCCACFADFADAHBGBCFFDBCHAFAAEDEBAHBAEFAFBADBDDADCCCCCCCACCGCDGADGAEAHGH,True +734,24.0,26.0,16.0,18.0,21.0,14.0,24.0,22.0,HGDGADCHDBBAEBDEBDEBEEDECFBCAGCBCHGDBGEBDEBEEBDGBGHHFCDDHGDAGHADEBDAAHBGBAHAEEGEBGEBAACFHCFACFHFAHFAHFDHCBEAHEHBCHAHAEDGFBGDBGFBHBEGDGGACEACACBACFAGGEGBFBHAGHAGCFGHF,False +735,22.0,22.0,29.0,19.0,27.0,26.0,31.0,18.0,FACFCCFCAHCGBBDADAGDFEEFAEFAHADEGDACBFCBFBHGCGGCFFBGFGFBBHHBCAADGCDECGGCGGCAGCEGEGGDDGAGHAGHFCFCEGDGCFFBDEBDFBFEEEHEHBEAEEAEEAGEFDEGDBBEHGAGFDGEDHBCHGAAAAABCECCECCHCCDFHBFCEGEDGFBFCBFHBFHDHHCGEB,False +736,3.0,2.0,3.0,3.0,1.0,1.0,2.0,0.0,DCBDCBGCAGADEAF,True +737,25.0,20.0,13.0,20.0,9.0,15.0,15.0,17.0,BBCBGDDHBCECEDCBDHGDAGDAEAACDBCDAAHFAEFDCFAFBAGAGBABHABDABFAFFDDHHHHBFHDFGGHDCFGGHHGAAEAABCAGCBGCEGABCADEBBEFBDFHGFHDFHCFHAADEBDGADABH,False +738,15.0,21.0,15.0,20.0,23.0,14.0,16.0,14.0,HBDCBCCDFDDBDABDABDFDHHBEGEFGEFGECGECGECABBEGFEGFGFBABDGBHGBHCAEBBEBEDDDBHDAFCACCEBHGGDEDAEACFBFFBGFGEEHHEHEAHADFCDCAFCDEBDCDEGEHGAHAHEABE,False +739,6.0,4.0,7.0,3.0,11.0,9.0,13.0,4.0,CEEGFEGFDGBBEFGGDEDHCCEAFEAFBAFGACCAGAFEBFEGFGCHGEHGECGHG,True +740,18.0,18.0,17.0,21.0,22.0,23.0,24.0,19.0,CHFCHDGHDGBDCFEEFEDGHDAHDAECAFGFFHFCDEGAHBDBEDHEGAEGAEFBEHAEHABBAHFGECAHBFCDFDEEDEGDACBFHDFBGFGFEEFAEFCFBCHBDFAGGAGGAGBAGBEGEGDDGCDBBDBGEFGDDGHBBECHFCHCCFAGHCFCAH,False +741,9.0,8.0,14.0,9.0,12.0,8.0,10.0,8.0,HHAGBAGCACBHFBHFDEADGBFGCDABDCEDCEFABGECCEBCDGEEEEECECCFACHAEFGGFCGFDGDACDHHBH,False +742,12.0,15.0,13.0,8.0,14.0,16.0,4.0,12.0,AFFFBFFBCEAFAAEBHDAEAHBCHFCHBDHBFHBDEBAHGFHFBEGCFHCEAFEAHABDBEDEEFECHECGECFHCFCCDCCGBDABDBBEFA,False +743,10.0,6.0,7.0,8.0,13.0,10.0,9.0,5.0,AFAAEBGEBEECEEDFCGGHDGDFCFGHFBHEHDDAADEDDECBEFBECHCGAAFFAFEAGEAGFBGC,False +744,4.0,4.0,4.0,5.0,4.0,3.0,5.0,8.0,FHDHHGAHBHDDHGDAFEACEACEGGFHBCHBCGEDB,False +745,5.0,2.0,6.0,1.0,2.0,4.0,4.0,5.0,CHHCFFGFGAAGAHGCHABEACEHCBFCD,True +746,6.0,7.0,9.0,8.0,5.0,5.0,6.0,0.0,GDGGFGCEDBEDACDCCFACFCDABDACAACBEBBCFBFEEGBDGD,False +747,23.0,21.0,27.0,20.0,27.0,21.0,28.0,26.0,DEADBCCGHHGHDBADBADBEEBFEBEBGGCAEDAHDFDGHEAHEAGEDGEFGBAGHFHECBCAEEBEGFFFHHHDHHGACGEEDCADBAFBHGBAFBDFCDCBGHFHAFCCDCGACGAFGCEGCHBBDGCHFDAFGGGBHGBHAAHCAGEDCCGCCHBCHFFHEFCEFAAGACGCEECECHEBHEGEDFEDF,False +748,3.0,5.0,1.0,5.0,3.0,2.0,3.0,3.0,DBGHEAHDADDADECFEGBGHBFBB,False +749,11.0,7.0,13.0,10.0,10.0,9.0,18.0,6.0,AGEGGFDHECGGCGBCGECBCCEFCADCGHCGEGBEBDECGGCAFHDDHGDAGDAEAEFDGADGAFCCFBAFEFDGFAGBAHBH,False +750,19.0,21.0,8.0,26.0,26.0,23.0,18.0,20.0,FEHFHBCHBCHAAHDGEABEDCECBDDAFFAFDGDHCDEGDFADCHDEDEEGHAGDFGCFGDFAEBDFBAGHAEEAEAAFAFBAFBEBBDDBDHEFHEHDEBDEFEBBAAEAEGBEDFHDHGBEGEFBHCHFBHEGGEFGEFGDFHFHGDBGDBFDBHDGA,False +751,10.0,15.0,9.0,6.0,11.0,12.0,12.0,15.0,GDEEDHHBBFGBHHBEHFHFBDCEGGEGCBCCAFCEFBECHEHEBHBAABFABFABFGFEGAEBDHCGHAGHAFCACGAHDHFDHGBBGF,False +752,16.0,16.0,21.0,19.0,22.0,24.0,24.0,17.0,HHEEFGDFCDFCDFGHFHABEGECBCGBCGBFGDFBCBAFFGCAGCAGBAGHGDHDDHGDHGEHAECADCEFFAFFDEGBAGBCEBAHFACCDCBGEHDEGAEFCEDBEHFHAEDBGAGFECFGGAGGEFHDHECHECFECFCBDCGABDBHDFEFFED,False +753,5.0,5.0,9.0,7.0,8.0,5.0,5.0,7.0,DHCDCBFEBACFGCHGCHGEDGDDEDHAGEACFACEAHEFCCFBDHBHBEE,False +754,1.0,1.0,2.0,5.0,0.0,0.0,2.0,1.0,GGBCDDCDDADH,True +755,3.0,4.0,2.0,11.0,7.0,7.0,7.0,3.0,DDGGDGFFEFFGGDECDEDFEDFBBHBGFBHDAGCADHDDEAEE,True +756,13.0,13.0,9.0,10.0,17.0,10.0,13.0,12.0,CGAEDBDFGGHCGBCFAEEAGFBFFBFFBEGEEBEEHEECDEGACGEHAFGADHABHAHHCGHFGHEHEAHGDDCAHFAEBAEDCBBCBBGBDEDDA,False +757,8.0,8.0,4.0,5.0,4.0,3.0,10.0,2.0,BDEBGHGGFDGFDAFCGGCEBBAACEDCADHABGGBGBAABGAE,True +758,26.0,19.0,23.0,17.0,12.0,22.0,20.0,22.0,DDGDEFCHCHHDHHCHGGHDBAFBFGBFEBCAFCAFHFFDCCDCEACACBFEGGHGGDFGDHCBGAFCAFEDBEAEEBDFGDAGBHBHHADGCDFCAHCHFCGFCGHCBHABDABAACHAFAAHCBHBFABFAGFDBFHBEECGAGAAGFAEDABACCEGH,False +759,4.0,1.0,4.0,4.0,4.0,6.0,8.0,4.0,GDFGAFGDGCFGCFCAHAHDFHEEHEEGDGAFGCB,False +760,2.0,2.0,0.0,1.0,4.0,1.0,5.0,1.0,ABEDBHAEGFGGEGGE,True +761,21.0,26.0,28.0,30.0,24.0,24.0,21.0,23.0,FDCHDHHDFHCCGFFAFAAGABBDGBCGBHGEHFHFBCEACEHEHBEABDBBABAGBFFBHDEEDBGFCGFCGFBBCBBDBGGGCDECDCFECFEABGCDAEHEHBEDDADFADGAEEAEFDCFHCFBCHBCHAEDDEBGEDGFHEDCBACDGFFCEGCDACABEGCDGHEECFCFHDFBDHADHADHACGDCDDHH,False +762,24.0,12.0,13.0,17.0,17.0,14.0,9.0,11.0,CEAAEBDEFDBCCBABBACBDBDDADGCGHAEHAEHBEFAEFAFCACHBHFEHADHFEFAGFGCDADDACDEDGEBGECAEBFEBEADGACFAHAACAAEADDFFGAFGCDHDHEFH,False +763,6.0,8.0,13.0,10.0,5.0,9.0,19.0,14.0,HGDFBDFGCHDCBGCEGCEGHGHHGACGFCAEEHBBGDHGCCGFAGHADHBCGDDBEAFDHFBHFDGCAGCGFFGHBGHCGHCD,False +764,27.0,23.0,30.0,22.0,19.0,28.0,33.0,17.0,AACCCCCCFBCDCCGCFBEFDGGDCGFCFFCAECBGBFCBGEHDEFGHFGHACHGFAGEAFFFCHFDGCHGDGCFGCFGCAGDBFFBECEGCGGBGHBDAEDABFABFDBDDBDAADGHHFBAECEBHAHHEFADFADFACAACGECEEAGEABADBDHEGEDGEDBFAHGAHGAGCDFBAGBGFFDCHBHEACGGBGB,False +765,18.0,15.0,16.0,11.0,14.0,19.0,16.0,15.0,CEFGFFADDDDCFAFGAFEEEAEHBEHCECAEBAECABHACHFCFGBGGBDABCFFFGFHGHGDEDABBABBAHFACGDFGDFGCBEEDFHACHGCHGBHFEGFAACECDGCHGBHCBHBAHAF,False +766,2.0,0.0,3.0,2.0,3.0,1.0,2.0,7.0,HHEHHCCHDGHDFCEHAEGA,True +767,17.0,7.0,6.0,11.0,18.0,9.0,7.0,8.0,HEEBEFBEBEEGHEFCEACFABFHBGEAEAACAADAADADDAFABDAGDEDAGDEDHCHFABEGDEFDEAEECEGHHHFGFAC,False +768,7.0,8.0,17.0,12.0,13.0,9.0,9.0,18.0,EBDDBCDHEEEGCEFDAFDABCBBHFGHGGHDCHFEHFAHAEHCFHCAHEHBEGECHEGDECCCCDCBHCGHCBFGECACHAFHDCDDHFDHG,False +769,20.0,21.0,9.0,15.0,21.0,8.0,21.0,20.0,HEDAEDGBFGHEDHEDHEBCGAEAAFAABHDHAEHGGGBEFDFFAAEAEHCHBCHACDBFGBGABHBBEBBAHBHHDABDAGDHEFEGBGGDCGEBGCHECHECHGBEDBEDBAAFGADBAGAHGBGDCGEEGEH,False +770,21.0,9.0,20.0,15.0,18.0,14.0,11.0,20.0,AGHAHEGHACBCDEHDEHEECGABBADBFCHFEABCBDEAGEAFEAFECFDCHDBDFADCAGCADCHDEADAAHFABFEDCEGCHFHHCEACGDDGHFGAFGAHHHECAEHDHHABCEFCHFCGCCEF,False +771,4.0,4.0,4.0,6.0,5.0,8.0,8.0,13.0,HGCHGCEBAEDFEDHAHHGEHDDBGDEGBHGFHGFCFFCHADFFBHGAHFHH,True +772,4.0,7.0,15.0,14.0,7.0,5.0,7.0,12.0,FCECCEHCHDDHEFHDDAEHECCGDDBDDBEDBFCGHHHBHHBCABCHBCDEDGCHFDACDFCDGCGGAGC,True +773,15.0,15.0,19.0,12.0,10.0,13.0,9.0,11.0,CDFCAAHAADAADBHCGEAHFBGCBCCEGCDCCDEAGHAGECHFHFFBFBHFBADCADEHBECBABBHFECAGCDDCFFFHDFHDFAEGAEGBCCBCEDGBBCB,False +774,17.0,15.0,18.0,13.0,14.0,14.0,9.0,11.0,BDADABGFCGHCGAGHAGFFDCCBAGFHDFHCFHCBACEACBAGBACBECFEBGABFBFFBHHBDEEDEAHEAGFDEFAFFBDHBECCCCDCEACEHCEAADDCBAEDDEH,False +775,12.0,10.0,12.0,10.0,14.0,18.0,9.0,17.0,FFDFGDFEBAEBHFHFFBFCBFCBACEGDDCHCHDGBEEAEHAEBACCCCCAHEAFFFFFHGBHDAADAHEFHGFHEDCAHHADHGFGCHGFEEHDEHBEGB,False +776,15.0,9.0,14.0,7.0,14.0,8.0,10.0,14.0,FGGCGFEGFEGEBBABCCDCHEHHCHGFDGAEHCEFCEGCAACEACADHABADBFDCEDAABEACDGCHHCHAFAGHEHBEFEAHBAHBEH,False +777,3.0,5.0,7.0,4.0,6.0,7.0,4.0,2.0,ACHDGDFECAEGAFGEBDFBCFCCFHCEECDBGFBEFB,False +778,13.0,16.0,17.0,23.0,18.0,12.0,11.0,15.0,HGEDGCCFHBDHDDECFEHAEBAEBHDCCDFCDCHGHFGHAABCAFCGHCGCEFFEBAEBABBEHBGHBFFDDGDAEDAEABBHBBHEDFEFCDCEDCEDHHCGDDDDDAGFEBBCDDADCAEEG,False +779,0.0,0.0,2.0,3.0,0.0,5.0,2.0,1.0,DCFGFFCDFHDFG,True +780,4.0,14.0,9.0,15.0,13.0,16.0,18.0,13.0,GFHBCDDGGEFBDFGDFEDHCBBGEFEAFEHBDHGFFECCDHGHCGBBGBEDHDDEDEEDBCFHGDHGFHGFHGFGGFGBFGAFHCDCAECAEBBEDBGFBH,False +781,14.0,11.0,9.0,17.0,16.0,19.0,16.0,13.0,AHAEEAEBDCFCAFEACDFGBGHHFBHDBFDCHDHHEHFDGFAFEABDGEEEFHFABFCGFGGBCHBEGBHACEADGACGCFGBFGAFDAGBAGFDHEDEEDEFDEFDGHDGDDF,False +782,17.0,30.0,15.0,20.0,20.0,24.0,22.0,25.0,GBEGHHGHFDDAEABGCBGDDCCHFEBFGBGDBGDBGCAAFGAFDEFGEFEFAEFACBGEBAEBHBBHBCHEHHEAHDDCBCFDADDHDGHFEHBHFBDBDHAFHFFHGGAFCFGCHEEHEDFAGBCHBFGBCGDCGBHBBCFBDBDEBFEFHHCBHGBEBAEBHEFAAFDAG,False +783,18.0,12.0,19.0,16.0,8.0,23.0,23.0,21.0,CAEAGEACHFBBCABCACFADGBFCCFGDFGFBGHEGHCCHABHGBHFBGEAGCCFDAFDCHBGHCGHDFEGEHGEHFDHBDFAHFAHCGGCGDBFAGFHHFHGFDDHGHFDAGBHFHEDDDDCCGCCGADFAFGAFAAF,False +784,26.0,24.0,29.0,15.0,21.0,16.0,22.0,14.0,GEEGAEGABFAFGEBBHCCCGGBHGBFDAADAAGAFGBEBBCCGCAAHAAHDBEEBGEDADDADDAECAECBEBHEFFADBCGECGCCDCGACBACFDCFHFDHGHBBHDBCECEGCBGEBCEFAECCCHFGECGCBACBFFBGFHCECAFBAHBHHAFDAGDECAG,False +785,1.0,0.0,2.0,2.0,2.0,6.0,1.0,1.0,FFFEFFEDFCDCGAH,True +786,20.0,28.0,18.0,25.0,30.0,17.0,20.0,19.0,ECEDCEBGECGBDDAGEBEEHHADHDECGEDEEFEADEAFEAGDBDFCEFBDHBHAGAAGCAGCHHCHDBDFFEECADBAGFCBBEBDEHHEBHFAHFBCEBFEGEHADBDHBDHCDBGDBHDCGBFEADEADHAEAGBBCBACEACFDCBDHBDGEGGEBGEFGBFCBGHFGFFAB,False +787,5.0,3.0,2.0,6.0,9.0,8.0,2.0,4.0,DAEDAECHGCHBEFFEFEDFEDADHEDAEFBFABFHFEG,True +788,5.0,9.0,7.0,1.0,4.0,3.0,1.0,5.0,EBABAACHBEHFACBBFBBEABCDECHGCHBCHFC,True +789,12.0,4.0,13.0,8.0,13.0,16.0,10.0,11.0,ADAAEBAEGDFGHFGEBGADFAFFAFFEFCECEEFEGFEDFCCECHHAFDCFGHEHBBFAGFGHACECGHCDCCHCCHDFHDGAAEH,False +790,6.0,10.0,8.0,9.0,9.0,8.0,9.0,13.0,CEAHHCFHCFHBEACFACDBGDBEHBGGCGGAFDHFCHFEHBABBHDHGDEAHGBEBEGBEDHEDGCDFHDF,False +791,8.0,14.0,12.0,15.0,11.0,8.0,8.0,8.0,EBHEBDCADCAGCABCGDEADEAEECBEDADFEHECHDBHGEGCFDCFBBBHBBDGHDFFDFFGBGHBACBFCHGCDCDDEBDA,False +792,10.0,22.0,18.0,14.0,21.0,20.0,16.0,23.0,DBGEHGFDGFECFHGFEGFBAECAHFHECBABHGFACEBDGBCGHCECAEGBBCDBEGEEGHEAAECGBFHBFHAFHCFBCDHCDHDBHEAEEBHHBCCBFHBCCBHCEDDEDDEFFHHFHFFHEFDAGBFEBHCBHDBFDGGG,False +793,23.0,21.0,27.0,21.0,31.0,27.0,29.0,18.0,AGFCEBGEFGHCGECBEFEGFCBFDBFHCCHCBEDDAGFBDCCDCCDEGHEGHAFHGGHDGDBADBAGEAEAGFFCDACFACFGCFGHFHEFHEDECBEBHFGDEGCEGDBAFCCFACEEBDDHCECDEADFGBBEABHACFAEFAEHAEHEGBFCAHGEFDEAAHACGDBEFBDBBCBCEHGEFGFGGFAGDAGEG,False +794,24.0,20.0,28.0,18.0,24.0,31.0,23.0,26.0,HHAHBAHDAHGAHECHECDEHEEGEFCECEFDEDDFCDFCHBBHBHFCGGEHCAHCDGAGADGCHGHFGEEGAEBABBAEFDGDHFFEGCBFBGHBGABDBCAGCEFEBFCFAAAGAGBABCAEAAFFBFFBEBDDFFCFFHFFECFHDFGCCACFAFHCFECECCFGHFGBAGBCDHHHCCHDCEDAEDGHFG,False +795,31.0,20.0,15.0,24.0,20.0,24.0,18.0,24.0,DDFDGFDGAGEBGEBGFHEDHBDBGHCFHBDCEACAGHADHGHFGBFHCDHDHEEHGGDGGEGDFGAEAEECGFCBFABFADAADAHGCFFHBFBAFDAFDBEBAAHAAHAAHAAFABCABEBEFDHDHEFHEDABHCDDDHBHCCGDHAECAEBEHAFBACEADFBFFEAFCAFC,False +796,6.0,5.0,4.0,8.0,8.0,11.0,14.0,10.0,AGGGDBHDBEDHHCHFAGFGEECFFAFFAEDAEFEGDBGHHFHDFGCGHAGHGGHGEBCEBDFGDF,False +797,13.0,13.0,14.0,16.0,20.0,20.0,14.0,14.0,FDCFDCDGCDGAFFFFHFBDGAEEFDHFGHGBFDAFHGFHGDEDDEADCHGBHGBACAHBECACHEEEEBBDFCEBBEBFEHAGCEBAEFCEFAGFAHFGHFGCFECADCGEADEHDEBDECHB,False +798,16.0,22.0,7.0,24.0,22.0,17.0,26.0,9.0,EFHFGCFGEDGFBGFBHACDACDAGBBGECEBBBDDADDADHGGGBGGBFEEDEFDEAGEAGEAFEDDBDGCDBBBGHGDHCDBDDEGEAFEADEABABBHFBFDBFDFEEFADGADECHBGEGFFGBBHEGGFDGAGAHGEE,False +799,20.0,13.0,23.0,31.0,20.0,22.0,27.0,27.0,ACCDDCDDCHDEGDBGEBHAHGDDDCDAHDGFAGHAEBFECFBCDECBAHEACGAEGFEFFGHADDGDDACEACECCFFFDFGHBHDBHDCFGCGACFCDHCBHEFDBDGCDCDEFDEFAGHAFHAHHCEGGDBGFEGHEHHAGFEBFGAHCBHCAHDADFGDEHDHHAGHFEHGEGGDGGBF,False +800,7.0,7.0,4.0,8.0,5.0,4.0,9.0,2.0,BFADCAGBDGDDGDDAEDEFBEABEBECGDGHAGHAGFGBABCGFC,True +801,27.0,24.0,11.0,26.0,22.0,20.0,24.0,21.0,FDEFHBBHDBDFECFEGGEGBBBFGBAGBGFBAEHFGHCAACHBBHBDHEABEFBAFGEDECDEGFGGHDGAGGAHCBHEEEFHEDHADFDHGEGFAAACDFDDFBDCEAHEBHEAAEFBDABAABHABDAGDADFAHFGHFGHCGDFGEBCDBDAGDBGHAHDADAGECDACDE,False +802,24.0,16.0,21.0,28.0,24.0,24.0,17.0,24.0,EHGDHECEADBDCGFCGDCFDEFDHFEEBHECAGBDHDDAAAAGEHGCCGBEGCEGEFDEBDAAGEFCAFABFBEAGEAFECCDDCDDHDHFDEFGAACEEEHGHHADHFHADHFCCAHGACGAHECBEBBDFBCFBHADDAGDCDFAHFAHFABFEBFECFHDBHDBHDGHFHFCDF,False +803,20.0,21.0,21.0,27.0,21.0,19.0,21.0,15.0,CHCDAADHHDHFEEFGGDBGABGCBCFAHFHFFGBDEBFEAFEHBEFDEFDAHCGGCDFCGCGECGEAGDBCEBGAADFADFCDAEDBDAHAEHAEGGEGAHGADFCHCCHBDBBGEADDADDBFDBCBBCBEGDDCEEAGDCGDFDEGBEBBFBAHCEHCFCFD,False +804,1.0,2.0,0.0,1.0,3.0,0.0,1.0,2.0,HBEHBEDEAG,True +805,17.0,17.0,12.0,11.0,12.0,11.0,11.0,14.0,CACCACHGBBBBABBDBGEGCAGFBEFAEBAECGBHHHHHHHFDEFGCGGBBBAFFAFFACAACGACDDEFEEDEADHAHCBHDGHABHEBGCFAHBEDDDFEDA,False +806,8.0,5.0,13.0,9.0,8.0,4.0,5.0,7.0,AABDACCACDACDBCBEEHEHCDHEDGEDADGFFCCBCGBEHCHHDGHECCFDCFAEGA,False +807,2.0,3.0,6.0,1.0,2.0,2.0,5.0,2.0,CCGFCGCAGEGGHBBHBDCFECA,True +808,8.0,11.0,13.0,11.0,20.0,5.0,10.0,7.0,EDGEBEBGEBGECCCADEEEBCEGEDBECBCCDAEDHECHAGHGCDDFDBFEBFEBEEGEFHAAGABGDFHDCHACBEDGECAHC,False +809,19.0,18.0,17.0,18.0,21.0,24.0,23.0,21.0,GGGGAGFDDEHDEHAEFAGHHHHCBECAGCEGEBGABGFBDCHDBHEHHGHFAHGCBGFDCFDCFBEFHHDAGFFGCEEDHGDCADAAHEEDEBHHFAFFABFACCBCABHGCGDBEDFEGFCGFBFBBCBBDFEGFECFAHDAEDAEAEEDCBGGFFFHA,False +810,20.0,16.0,11.0,12.0,13.0,19.0,22.0,18.0,AGFCHFDDFBEHGEHGBHGDCGFCHEGAGADFAGGAHAFBABBFBBGGAABAAEADEBDGCHHEBGCAEAHEGCAGFHDFHFEHAGDGFDBFBBFADCGDBGHFGHCCCGCDGBBAAFFAFHHFEHFEHEE,False +811,17.0,22.0,15.0,31.0,25.0,25.0,18.0,24.0,HAFEGGECCHDGGGHDGCDGDEAAEHGEFGBGGHGBEFEEBCHAEHCFHDFHDFGDGDBGDAFBFFBFHEECEDBEDHDBEDBFDBFABDEFCHAEFEDHCDAFDCBDABDABFCBCDHEHFCAFCDBEDACDEHFFHFFEEEBDEHEBHBHHAHGBHDHGDBCABDADDFDAFGAF,False +812,13.0,7.0,5.0,13.0,10.0,18.0,4.0,11.0,FGEADHABHAEHFCHFAAEEAFEAFDAFABEGGHFFBBDBHCAHADHBFADCCHEDFGDFDDBDFEDFEHFDAFDFFEHFC,True +813,30.0,25.0,17.0,27.0,18.0,16.0,23.0,20.0,DGAGBDGFDGFAAACAGCEFHDAHDBHCBACFACFGHFEFBHHBDHBAEDAHCEFDGCAADABGABDEGDGCAGCEGBABEABDFGDFADFABGBHGAFGDDGHDAHDCDDEDGECHEHGFBBFHBEBBCBDGGHHCEHBEGBCGADAADBHEFDEFHEAADCCHEDECAAABABB,False +814,24.0,14.0,14.0,18.0,16.0,18.0,16.0,21.0,ACBABDDGDGCCHAEHAEFDEFGHFGHFGDCGEBFDBGGBFACACFAGEHGBAFBAEAAEFHEGHCAEAADDHCABFHHEDHDHACHAGHACHGCHCHDDHABAAFADDBBABFHCFGCFEDDEDDHFEHFEGFBGEAFEB,False +815,13.0,9.0,13.0,16.0,13.0,6.0,10.0,11.0,EBHEDEGACDDCDGCDACHFCECCHGBHGBHCBEDAEDHFAFEAHEADAAEADDFFEGBDGEHHABGGHGCCADCDDCDHCABEFBEDBAG,False +816,3.0,7.0,5.0,5.0,0.0,0.0,5.0,2.0,DDCDBADBHGBGBBGCCCACBAGBDGH,True +817,5.0,5.0,2.0,2.0,3.0,8.0,12.0,6.0,HCHGCGFHGAEAFGHFGHFGFEADEHDFBGGGGGGFBFABABB,True +818,1.0,11.0,9.0,4.0,7.0,7.0,8.0,7.0,GABGHBHDBHCBECBFGHFGBCBBFEBECCEFCDFCGHCFCDHEFGEGBEBHDG,False +819,2.0,2.0,5.0,5.0,0.0,2.0,1.0,5.0,CDACFHHFAHDBHCCDCHDBGD,True +820,11.0,24.0,12.0,20.0,8.0,10.0,7.0,16.0,DDBDDECFEFFEBFBBABHAFHGGCCADEHHABDDDDCGHFABFABFHDCBDBGDBCDBFEHHCBHADHADBADCHDCBDHBEHBHABCGBEGBCDCGHBDAEFBBBH,False +821,9.0,5.0,8.0,7.0,7.0,2.0,8.0,6.0,DCDGGAGGCHGCHBBEEAGEGEFCEDADAADAAFCABCEHCBHBEHCAHDDG,False +822,4.0,6.0,4.0,6.0,8.0,10.0,6.0,8.0,DGEHGBHAFDDFEAHBFCBFCDFADFCDHGEHGBFCBHEHGEBEEHEFGFFA,False +823,11.0,21.0,15.0,29.0,14.0,28.0,25.0,13.0,GCBACBGFGGFADDGDDHCCBEGFEGBDBBDFFEFECFBCFBFFGFFGDDHHDFHEFDEDDAFAGFDEBEBBDDHDEHGCHFCGCAGCFGDGGHCFBBFBDCGGEGDEBAHFDEADEADFCDGABFDDFGDCGBFADABDGBHGHGFHFDHFEBCB,False +824,9.0,9.0,18.0,17.0,22.0,11.0,12.0,16.0,HDHHDBHCFHEEAEBDEDAEDBEDBHHAFFDDFCHGCHECDDCEEEFEDGADGCDCCHCAHCAHCEHGECGEGGHFDCCEECACBGCEGFGDEBAFFAGCGBEEEFDEFDBHBH,False +825,13.0,14.0,23.0,11.0,13.0,29.0,17.0,16.0,CFBCFDDFBDFBHFHGFAGEAFFBHFCCFCFACFACFDCAEBHFGGBAGDEEHBGFAGFHEDHGFEBFHHFGFDCFCBHEEGGCFGEFBCADHHDBFDBHDHACHCCGCEGAGGFFACCAECFHCGBCEFCEFCAB,False +826,5.0,8.0,5.0,6.0,10.0,4.0,3.0,7.0,DDEDAGAAGAHCDDBBHBGEEFHECEFHEBHEFHECEECBBCHBDFBA,False +827,20.0,17.0,26.0,28.0,18.0,27.0,26.0,26.0,ECFEGFEHFHHFABFABFEHABHAGDBHDBHDBGDGCDGHABHAFCEHDBHGCDCEFEEADECDAFBGFEGFBAAGDGDDEEDHDABDABFAGFDGDDADCBDAHGHHGHHFFFFFGCDEDGGCBCFEDGCCGCCDCEFFHHAHDBHAFCCFDGBCCHACHDEGGEGCCDCCHCBGFAAFEGFGCHHF,False +828,10.0,8.0,14.0,9.0,25.0,17.0,21.0,17.0,ECHGCHBCGEFDEFDECDEGBECBHBHHFFGGFGGHDGHACCAHHBDCFGAFGAGEEHEAHECEEHEEBEEGDECFEBFECFHFFGGGAEGHEGFCFBAGAHEEGDAAHFHCFGEEDFGDC,False +829,3.0,3.0,1.0,2.0,3.0,6.0,4.0,4.0,DHEHHDFHGGBAGAFEACEGFBFFBF,False +830,13.0,14.0,5.0,14.0,12.0,16.0,14.0,22.0,GDABFFCGFEHEGFFBHCBHEDHFGFBBFEDEHDHHGFHAEHAEHCEHABHADGEDGAFGHBCHAGHADHEFHFFGFGBAABAABDGBDCHDGBEAFHHDDBDHBFHDEG,False +831,30.0,21.0,25.0,25.0,16.0,20.0,17.0,32.0,ABDAGCAGBEEEEFEEFGBFGACGBHGBHCAACAACGCHGHADHACEECHDHACHFEGEAGDAHDAHDGBBHBFHGCHEHHAFGFFDDBGHHDHDEHABBACBHCADFDDHBDHBDCDCBDAHFFHDDBFHAGCDBFFEECCECCGHAHCAHBEHDACDAHDFCDAHDBBFFBAFCFFCAHAAGAC,False +832,25.0,27.0,23.0,20.0,26.0,20.0,20.0,27.0,AADBAGBCFACEEGDFBFFBFHCGDBHEFHCFBFBEEBHCCHCHBEBGABDAHDFHDHHFEHGECGFCBHDFHABBDDBDFHDGCGCCGCDGCHBHEEDEHDHBDEEHEGHBBHFBHFBGCEGEDAEGAECCEAAEACBAHDEBAEBFGACGAFAHDABAHDGCDEAHEAFECFGAACBACHAGBFGE,False +833,25.0,13.0,14.0,24.0,17.0,12.0,19.0,18.0,AEBDEBFCFGAEEHEAHBAHDCFDHFBFAGFAGAEGCCDCAAGAHEHHGAHEACFDEGDCFBAGGABGADGCDGFEBFEAAAGAAECBGDFCDBEDHEBCDDHDDHDGHDHHGCHGEBGHCAHDEEDCDDBADAAGABHDDF,False +834,15.0,10.0,18.0,19.0,15.0,14.0,14.0,17.0,GFDGHHGDHFHCFDBEBGADGACECCHHCHFAHCEHCHHDEHAEBADDGDBGDEEDECDFCAFEEFEDDHDCGAHBAGBDEADGHEFDFABCEBFGBCABCFGCFACGDHDEHACACCAFGF,False +835,20.0,10.0,18.0,14.0,16.0,28.0,23.0,12.0,CBFFGFCHEDBFHGFEGFEGFEDCEDAEHAGGGGFGGCCCDGCFGCFHAFBAFBDFCFFHAAGCEGAEGHEGDFAFFCDFADECHEAHGFGEHGEBDDBABFABABECHCFGCDDFFGFAACAAEDHGGHECDBAFCAFAF,False +836,30.0,20.0,19.0,16.0,19.0,13.0,25.0,21.0,GEHGEGBFGFCGFAGHHGFGGFDHAAHECBAGGAGHCGBCABFHBECAAHAFCEBCEACEADDADCGHBDHGFEDBCAEGAHGHCGHCGEBBHGDHEDHDFBEBBFADEAHEACBAEGFDCAABAABAABGAEACHBHDGADHAEBACHDGDAGCEDCEFCBF,False +837,11.0,6.0,11.0,21.0,12.0,11.0,14.0,20.0,CCGFFHDFDCHECHGCEGCGGDDGABGAEHDEHGGHGHDDHDABDHBHFFGEFHDAEDFEDFGFAHHHCFHAEDGEHCHFDADDGDBADAHDAHDCDCCBEHBEAE,False +838,2.0,11.0,5.0,5.0,5.0,11.0,2.0,7.0,HHAFDBFCBFHBFCBHCFEBHEBCFBFEBEHBDDDEDCABBFFGFFGH,True +839,10.0,18.0,12.0,15.0,22.0,22.0,14.0,20.0,GHGGHDGHEHCFHBHHGHGFDFFBHGBDFBCFBFEBAHAACAEBAFCEFHEABGAHCBCCADAEHFDHFEFFEHFEHCECGHFEBFGCFDBBDBDDCEDEEDEEFBFFGDBBEBGEAEHFDCEGEEDHGDHBF,False +840,6.0,5.0,3.0,4.0,8.0,4.0,5.0,6.0,HFAHFAGABEEHFEBBEABCGBGAFGAECDEDHEHHEDGDC,False +841,22.0,25.0,12.0,20.0,30.0,18.0,24.0,19.0,CFDABGGBGGDGGBGDBGDFEHGEHAEDEEDEEAEGABBABHABFEGAAAAFAAGHFEEEAHFBBFBDHEHAGHADHFDHEDHEDCFAHFEHGEHEEHCBBDBBGBGEBCEBFEHDCFAGFECABGDHEFFEBEACCHEGEGCAFDACECDGDBHEFCGFGGBBBDBDDA,False +842,26.0,32.0,18.0,28.0,33.0,16.0,26.0,21.0,BDFEACGAHGEHBEFBDDCDDEBGFBAHCGBBGCEDEHBAFGGFBDFDABCCBFCBHEBEAFGAEGFEGEDGAABBHBDCAAEAEEBEBGDGGDGHDHHCACBEGGDHADHGEFEBDEBDHBDHBEHBHDDCDFCDCGAGGEGGEGFECAEABEAHDAHCFFCDHAAHAACAABFEEEBDEBDGBDBCEEHDBGEBEAHF,False +843,17.0,15.0,21.0,18.0,10.0,19.0,19.0,11.0,GCGCCGCDBAAFCFFCGCCFCBGCBHBGADGFEEEBEDCFDCFBEFAEGDDDDDAGACDEFDBFGCFGEFDDHCGGGGGAFACHACHACGADGHHCHBFAAFDFFDABBEBFHBHEBHCAHBADGABFDC,False +844,28.0,20.0,25.0,32.0,29.0,10.0,34.0,16.0,GCBGCEAHBHHGHCGADBHDGAFGCFEEFDEAABAAFACGACHAGEEEEEBDBDDGEAEBGCFGAFGCGACGAGFEDAGDAGDBGDFEBECDGBDHBDBBDAEHADAAHGDCGDEBAHBEDCGBEGHEDHCCEDDEDCEGCDHDACAABADGEEFCEFGGAHGCCGCBECECBDHDCADAGDGGDGGDECHEBD,False +845,9.0,18.0,18.0,15.0,16.0,16.0,18.0,30.0,FHHFCHBCEBFEBFBHCGHEGFEDEHABHBHCEHCGGEGGCGGDGHDFHBFHAGACEDBBBBBFHEDHAHHBHEGHEHFDHEBHDDHCDCDHCACADBHDAAEGHFCCECCFHHBHGDHCDHFDGFBGFGGECAFBFCEG,False +846,25.0,21.0,20.0,25.0,14.0,20.0,19.0,27.0,DHHAHHGHBEBFFBHACHBCHFEAFHAGEAGEDFFDHACGDCGEBDDBGEAFAAGAAHAAFCFDCAEFBEGHGDCFAEDABDABHGBHGFHFDGDDGDDHFBABCADDACHBCHCGECACDBCGBCFHEHCCBBHHHFHFBHECEDHDAHDFDDFBBFDBEGACGACGADG,False +847,19.0,22.0,26.0,32.0,24.0,20.0,17.0,30.0,FFFFFBEBBCDDHBEHDHHFHCDHCDBCDAFBHDGHDECDEDGEDCBFEFEHAHHAEDBDGHDCHECDEFHHADHCHBCHCDDCHBBHBEECCDFEDFDBGDBDFBEBAEFAHAGFECCACDHCEHCGGCGGCAGABCAGAGCDBADGEDFEGAEGAEHACHCBHABDBEDEDDHADGGFBFFHEFHCAH,False +848,9.0,6.0,11.0,10.0,14.0,15.0,7.0,8.0,EBECBHGDFECFDGFDHFDCEAAGDEFDEFDFFHCAHGBDDHDHFEGEGBAFCEFCAFCACCACBAFHFEHEEFEGAEBC,False +849,4.0,12.0,3.0,4.0,4.0,6.0,9.0,4.0,BADBFBBDBCDAGGEGGAHFBHFECBBGGCGGBBGBDFFHFEHAEB,True +850,11.0,16.0,15.0,13.0,9.0,18.0,8.0,14.0,AHEFHEDHAHCBEFAEABEBBDHGAGCECCECCEDGADFFBFFBFFACACDFCDECHHFDFFHFFGFBAHBCDBGDBGHHGHFBDBHDBCCFHDACABDGBCBF,False +851,14.0,6.0,9.0,8.0,8.0,11.0,8.0,4.0,CADAAFAFGGBDGBECHEGAEGCEGHEAFCGCCAFCAFDBEHBAAAFAFFECEDADGACFBDFHDFBD,False +852,13.0,17.0,14.0,11.0,14.0,23.0,28.0,19.0,AHFBHFEDBHCBHGDHDDBEFGAFBEDCEDCGGCAGCHGCHGCDCEEGFBBFHCGHAGDCFEGABFCBECBAFBAFHHGHEBCFAEGGEGAFBFGGGDGBDBFAEEBGAGHAFHCFHFFAGFHGFHFFHGGBGGHDGFE,False +853,17.0,14.0,15.0,18.0,12.0,25.0,14.0,18.0,FEEDCEDAEDABFABGHCGEGBAFBAFADFDDFBDFGDGEEAEHDGHCFHCHGBHFHFACAEBGHHGHAGAAFFDCCDHCGGCFDCFHCGECADCFDBFEBFBDGHDCHCHDAFFFHFBBEAFADFHBFHFAB,False +854,4.0,8.0,7.0,9.0,7.0,13.0,4.0,5.0,HAHBAEBCEFDHFGBFDDFDDFCGFBBCBFCFFCAFEDFBCGCDGEHEEDFDHFEBA,False +855,8.0,9.0,7.0,8.0,14.0,11.0,8.0,11.0,FCGGHEGHCAHEGDGCDHEBHEGEEFAEFCEAAFAHDEHFEHBGFBFFBFEAHEADCBBCBBCEGDDHFDFBHEAD,False +856,15.0,19.0,19.0,21.0,20.0,23.0,9.0,21.0,EHCABCEDCEDCHDBADEFFEAHGADFHBFEBFEHFEGCHGBBFBDFDCFHCFCGHCDHEHADFFEFHCGHCBABEEBEFBCDBCEHDACDBBDCBACBAEBDDCADFAEFEEHDGHDEEFBFFDHGHFGAFAHFCGFHBHDADAHC,False +857,8.0,14.0,12.0,26.0,12.0,12.0,24.0,18.0,DDGDGFHGDEEDEHGEDDCHGCAGDGBBHHAHDBHDBGACHCCHFCHGGHDGHDBFABCHGHGFDCEAGEADEGDADEGHBCFBGFGDCGBFDFFDCBDCGDGBEGBFGEHHEFHDFGDAEDBDDB,False +858,3.0,12.0,7.0,10.0,7.0,11.0,5.0,6.0,EHBFDFFCEGCEBFAFCCFECFHDGCEHAEFDBFDBAHBGHBGEBCDFDDFBDBDGBHBBD,False +859,15.0,8.0,5.0,5.0,11.0,6.0,8.0,9.0,AFHEGGEGBEDBACAADADGGHGFEGCEHCDAFECBBABHHEHAECFHBAHGABDEBAEFAEFAHAA,False +860,24.0,23.0,16.0,29.0,25.0,13.0,28.0,31.0,ABDBGHHDBEAACAHBDDDDHHGAHBDHDAHCGHCAEGFECFECGHAGBBDBDDBDGBDBAEBACDAHDBGDBCEBGEDDEBDBBABGGGGGEHAEGGGDFHDAHAHFAFDCHDCHEFBEAGECHFCHGGEGGAGFDHADEGHAFHBGHEFBCAGCAEBHEDHEDEEDFEGFHCEHDHHFCHEAGECHA,False +861,19.0,16.0,16.0,18.0,22.0,19.0,15.0,18.0,HBDHADGAFFFCFDCFDHFAEEDEEABBABHHEAEDAHDEHCGFEECHECEFGHFDHFEEGCBDFDGHDGHDCBDCAECAHBACGEFBFFAFBAFBEDHDAHBBDGEGCEGBGDFGAFGAHCHGFECAEGABAHBACBECECD,False +862,23.0,28.0,34.0,23.0,21.0,19.0,19.0,23.0,AADEFDECBCFBFEGCHHCBCAHCAEDAEDFGBAHBGBBGEDGEFBAFBABEABFAHFAHADGBHAAHAAHCFCAECBEHBACDDCDCHDHHDAHDAHCFBCDHCBBGDEDEHFBCCCCCDGEDEEBCBHCDEBEHBCGCDECGCCGBCGBCFAGGACBHBFCAGCFBDHBFHFECFGHEGCEFDDFGDG,False +863,11.0,5.0,11.0,10.0,13.0,17.0,9.0,9.0,HGFAGHEGFFAEFGCHCCHCFACEAFEAFBFFBEEDDDGGDFEBHDFEDFEFCEHCDAAFBAFHCFECHEDDABDAGCCGAHGEF,False +864,8.0,4.0,8.0,5.0,6.0,11.0,2.0,13.0,CGDDADAFHFEHACHFFHAFHAGABEFBHHCHFCFBEHCEHDEFDCFEFHCAHCAHB,True +865,6.0,7.0,13.0,8.0,5.0,5.0,10.0,8.0,EBBEADDABHGBFBHDAHDFCCCCCGDCGACEFCEGCGGCDHHBGHCGCGBFDDFEAHCAHG,False +866,13.0,18.0,13.0,24.0,13.0,21.0,16.0,22.0,CECHEHGAHDBHAACGDDGDDGBGFBACBAFGCFGEBHHBHBBFBBFGDFEBHDBAEEAGEHFEDGEDFFHFADDADFHCHEADCFDBEDCDDFFBFFHFGEFGHCDFBHADHFDHFHCGCAGDACEBDHBDGDHGCHBH,False +867,3.0,4.0,1.0,1.0,0.0,0.0,2.0,1.0,BGHBGBAABACD,True +868,12.0,15.0,8.0,11.0,24.0,11.0,16.0,16.0,GBGAFGAHEABDAHEEHEGHFBEGHCHHCBDFECAADDGHFHFGEAGEBCDGEDBEFEEFGDGGAHGDHEEHBEHGEAGECGEAHECHBBEFBHBBDBBDCBFEFEEFECAAD,False +869,14.0,6.0,19.0,11.0,20.0,15.0,11.0,18.0,AFHAEHAEHGFHACHADFFGGFEGFEGDEDBAFBDECHHGHCCDBCFECHCHFBEDEECHACDGFDCHCEHFHCFACEACEACBCGBGEADECEEGFEHFACEDHEDHAGHFCA,False +870,7.0,10.0,10.0,16.0,6.0,4.0,11.0,16.0,HCBDCBHCBACDCCDHFHAGHCCDECGEDGDAFHGHGBDDFADHGDHBDHBGHFHEAABGBDHEDHEHHEGDDGADGCBB,False +871,6.0,1.0,1.0,3.0,2.0,4.0,9.0,6.0,AHCGEDGAHEAHAFGAGGBHGAHGFGDFGFHD,True +872,3.0,5.0,3.0,3.0,6.0,1.0,1.0,2.0,BBBDCBEGHEFHDBADAECAECEE,True +873,2.0,1.0,1.0,2.0,5.0,1.0,2.0,3.0,HEGAEHAEBCFDEHDEG,True +874,7.0,21.0,14.0,14.0,9.0,12.0,13.0,10.0,FDBFBBDBADBHBAGDHHCGEFDEBGEGGFGBCGEADAGGADHBDFCDECGBCEDFHFGHFEAFGHEDCEDCBFCBCCBHBBHBBDCBFGBCBHDBCAFC,False +875,6.0,6.0,10.0,12.0,5.0,8.0,13.0,6.0,GCGGCGGHBFDDADDBDFBDGCFGAEGAFBBCBHHFDHADHAGCDGEDEFGGCECCHDCEACGDFF,False +876,19.0,14.0,14.0,17.0,5.0,8.0,26.0,9.0,ADBACAGCHGCFGHDADABGEDABDABAFGCFDCADGGGGGGGGGBGGBACCHHAAGAADAGDAGDCGDBFFBCFBEBCEBGBBHEGDDCCCBHHAFGDGADGDDAFCGHHE,True +877,11.0,23.0,26.0,15.0,25.0,13.0,27.0,20.0,DHHEHGFGGCEHCGDGEDHCDHBFEDFEAFHBDGFCBHCEECEECBHCACGACACHGBHGBGGECGBDHCFEEEHCGHCGHCEBEFBGABCDDEGGEGGEGFEDBEBBGBCGBHABGEDCABCFECAHHBBCBDCAGBDGBAGCAHFHEBCEGCDFFDEF,False +878,10.0,21.0,12.0,20.0,16.0,27.0,18.0,16.0,EGCEHFAFAEBBGACGEEDEBDEFDBBDCBDEDFFAFGHBDFBHBGHBEBEGDDGDGBHGBHBFFGDFCFGCFAEGHEDEEDEAFFFFFFCHGGDGAFGAFHDBHEBCAGHBFDFFBHFCHFCHCCDCFDHBDGBDBHFA,False +879,13.0,7.0,15.0,3.0,11.0,11.0,9.0,9.0,CHBCFBFGEFEHCCAFAAFCEECBBHEEGEFBEABAADGAGGFGFCGACEHCHCFECADCACCACFAHFHDGHGAHEB,False +880,18.0,17.0,11.0,7.0,12.0,11.0,12.0,19.0,GACGHHGCCDAEAEBAFGHFGHEHABHBDHGCHGCHBABEEBECDDBABBHFHGCBGCBFAAGDAGHHHCAFCABAABAABHAFDAFBGDCHFEBEEHEFHEFBFHE,False +881,15.0,14.0,12.0,18.0,16.0,16.0,10.0,24.0,EFDEFDHBEHAEFFBHEBGEFABHGEHDFHAFEBCDGDAFDAHAACDACDGCEHDBBBBHDHEAEFAHGDFDABHABHAEHFEHFHHFHBFHAFHAEDCGBGGDDHDEHCBCCHCEFDGGHCDCC,False +882,1.0,3.0,4.0,5.0,7.0,5.0,2.0,5.0,HDHBCGDFACFECFEFBDFDGHEEHEBHEDCE,True +883,10.0,19.0,13.0,15.0,16.0,14.0,11.0,10.0,FDEBDAHCBEFHFHGGHGEBGCHCEECDACEFBAFHCBCEBAGBFGCEGBEHDDHBDHCDAFDEBDFBDEADBADBAECAGDABCGDCFBGFBDFBEFBFGBEHEECF,False +884,4.0,20.0,14.0,12.0,17.0,18.0,12.0,16.0,DHCFHCBHGFHFEDFEDBCDBFHHGCDFADCGHFBDCBDHAGEFBEHBEDCEGCABFHBHCCCCBHCGGFGFFBFBBEGFEBBBCGEGHHHFDAFDEFBEFHEGDEBEEBEEB,False +885,4.0,5.0,7.0,5.0,3.0,5.0,11.0,4.0,GBBEAFCABHGBGEFGDDCBDCFGCAGCDGCGHEGHFCHFGAGD,False +886,4.0,2.0,5.0,6.0,4.0,7.0,8.0,6.0,DEGFEGHBGCGHBGHDFAFFAFDADGCHECDECFFCHADHGG,False +887,7.0,10.0,2.0,12.0,7.0,8.0,10.0,7.0,HDGHAEDCDDBGDBAEBGCBDAEGFGFBGFBDDBFHBEHADFGDFHHFHEDGADGAFEAGEBB,False +888,22.0,21.0,26.0,15.0,24.0,25.0,19.0,23.0,HFHEFEAADAGDBCEBGEBEFHEGHAGEDGADFEBFCBFBBFCEHADFEHGHHFDFCHFCHDBGDHAAHFCFAEBAEGCEGCFFAHHGHHFHHCHCBABGDHHDFABGCFACFECDEAGEAGFBCFGCEGCBBBEBAGHGGCBAFACFDCDDCFCAHCACCBEEBEEBEADCCEF,False +889,14.0,18.0,14.0,7.0,16.0,10.0,10.0,16.0,FHAHHEDDECCCHBCBBFBFCBACDAGHAGHBFHBCHBEGEEGBBGBBGEAEAHHBEFFEAFEDHECEEGABGBDGCABEABAFCHCAACGBHHAHCDHFECFED,False +890,18.0,20.0,25.0,21.0,23.0,27.0,22.0,23.0,ECFEGEBFABFABCDBFHBHABHBDHGFGBFGECGCFHADHDEACCBHFEGFACHECHFBACCCBEBBDFDAEAABDAECCCFCFFCFFCEGCHBEGDEDFBDEGHFCHFCFDCFEGGEGDDGHDHHCGHFDFBDHGHHAAHAEHFGAFGAEADEFCEFBEGBGGHDAEDCEHCDGBDG,False +891,21.0,17.0,16.0,20.0,21.0,17.0,22.0,30.0,GEDGFABBHBBHFAGAEEAEAAECAEHHHBDDCABHGGHGCBAAFABFBFCGEBFEGEHHEHHDDHFGEEHDGHCAHFADBADCCGACHDGHAGHAFHAFBECBEDHGCHGAHGBDCEDCDBFDEGHGADGDHGFHCDGDFHBHHBHAECFECFEGFHFEDCED,False +892,2.0,4.0,1.0,8.0,1.0,2.0,5.0,5.0,HHHHBDABDGBDFFDCAHGGGBDGDDED,True +893,15.0,5.0,9.0,8.0,9.0,2.0,15.0,5.0,GGEGEEDAFGECACCAGFGEEDECDBAEGADGABAACCACCAHGAHADHGDGGHGBACBHBDEGAAGD,True +894,15.0,20.0,23.0,20.0,17.0,18.0,26.0,16.0,FGDFCFCCGBFEBEEDACGECGHCFFEDBBCHBFHBDAFHBGCFCCFAGHDGDGGBFEEGCEGAFGAEAFEDFEDBBDHBHGGGGCFDCEHBEHGCAAAAAGHCHHCHBGDDCDBGBBCABCABADBADBFDGGCCEDEEDGCGGDDGHCFHEFH,False +895,17.0,14.0,14.0,9.0,18.0,14.0,9.0,18.0,BGCDCCFADADBGDGCAEEAGEBEFBHHAEFFEHFEBEBCGCEBCEDAGGAHEABEABDAFDHBHHAAHBAHAHBAHCEHCAHFHBEHFCFFCEFCEHCHHCAEDFEDBGFGF,False +896,10.0,10.0,7.0,13.0,14.0,14.0,10.0,8.0,HCBCDHHGEAFHFCDGHEBDEAFBCFEDFADEADEADABBHCAEDGDDGFDAFHHFDGFGGFABFBCDBCEAGBBGEFGEFEEFEE,False +897,1.0,6.0,2.0,6.0,4.0,12.0,5.0,5.0,FBDGCGGDFEBFEFFEGFBGFHFFDFHBAHFEDFCHBBHDD,True +898,8.0,2.0,6.0,2.0,1.0,5.0,2.0,3.0,CFFCHDCFEHHAADAACCABAACGAFGBF,True +899,13.0,11.0,11.0,13.0,12.0,11.0,12.0,9.0,FCCGCABEBEEFCBGCDGCAECEEHAEGDCFFHDBCABDABEAFCBHABHADHGDFGDFBDFEDGHBGDGDAGAFECHEGDEGHFAHDABAF,False +900,11.0,8.0,16.0,15.0,15.0,12.0,12.0,10.0,HFDECDECFHCHGDEDEEBGHDAHDABCCDDFGDCGBCACCDGGFCGFEHEAGEAGEAFCCHCCAFEAFADEADHGDBFBBFBBFGCEAHFCDEEDHEG,False +901,6.0,5.0,13.0,12.0,14.0,4.0,0.0,2.0,DEEDEFCACAAEHEECDECAHCBDDECCBCFFDBFBCDECEECEDCADEDDEDACB,True +902,5.0,2.0,3.0,0.0,2.0,4.0,3.0,0.0,CFECFBAGAACAAGFFGBE,True +903,1.0,3.0,5.0,2.0,2.0,3.0,3.0,5.0,HEAGEFBCDBCBCFHCFHCDHGHG,False +904,8.0,10.0,8.0,10.0,10.0,10.0,8.0,8.0,HAEHAEDAEDGHFGFFAFFBFFGDABDECDEGGEGHBHBBCCFEDGECBCCBACHDCAFBDDEEDAHGBHBF,False +905,19.0,35.0,22.0,16.0,17.0,18.0,22.0,17.0,BEDEDGGBEBBDBGHBCBBCBHCAEAHBAGBCBHDBHDCHGCBGDAGDCCAGDGCDFCBFCBDBBDHAAEAGEGGEGBAFBHFGFGBFHEACECCGHCFFEFBCFBAFAABBBBBHDBEFBHFAGBEFCDGCFCDEEHBBFBDCGDEGFHGACAACAHHFGHEABE,False +906,6.0,6.0,11.0,1.0,5.0,2.0,8.0,3.0,GGECBACGCCGHCBFEGGAACAACDACBBCHCEFCEHBEGBG,True +907,10.0,11.0,15.0,22.0,12.0,15.0,10.0,11.0,CBDCFAHHHHCHDBDDBEDHCAECDFFDACDGBDABCFBCFBGDCFFCFEEHGGHGADGDFAFACGDCADFBCFGDFEDFDDADGAHEBHFCHDCDEEBEEDEGBE,False +908,4.0,0.0,2.0,5.0,3.0,0.0,2.0,3.0,GHACDADAEDAEDEGDHHC,True +909,1.0,4.0,0.0,5.0,2.0,3.0,1.0,1.0,FDHBDABFEBDDBDEGF,True +910,9.0,19.0,26.0,20.0,13.0,12.0,16.0,22.0,BHDCHGCHBCHDCBGCAEDFEBFBHDBHDGHEGECGCFDCHHGHHBHGFGCCBCCDCHAADFFDFFHEDCFBCEHCEHCDDFAGECGDBDBGFGEECBHCBACBACHCDEFDAHBCHCEGBGGCDDHDEHBAGBADB,False +911,5.0,1.0,2.0,3.0,2.0,3.0,0.0,2.0,HAHAADAFBAFEFCEDCD,True +912,26.0,20.0,25.0,15.0,11.0,21.0,19.0,28.0,BGFDDHABFAGCACFBCDBGDCCAAAHAAHFCHCEGGFFHHFBCABCGGGGBHEAHCAHBAHAHHACHFDHDAHABHCBFEBFADFGDCGFFHCGBCFBDFEDCHBBHBCGECGEHGFHAEHACHADAABHFDECEGBAGDHFDHCCFGAEGAECABFFBHCCHD,False +913,7.0,7.0,5.0,3.0,0.0,6.0,1.0,6.0,CDFCAFHACADCBBHBFHBFHFDGCABBABFHHAA,True +914,20.0,24.0,25.0,24.0,19.0,23.0,23.0,19.0,BDHFDGCHCAHFAHFGGCHBCHDFEDAEHCBFEBCGHCGFEACCAHDFGDFDBFBEFBEBGDBGDBCDECBFHEEEBCGBDDFDECHEHBFCAFADGADAHFCFFGFAGFEGEHGADDHDCHDBDDGEDBHABGGBEGBAHBHBDCFDCACCGEAACCACGAEGBEFBAFCCFGBAG,False +915,6.0,10.0,1.0,9.0,16.0,12.0,5.0,11.0,BFGFHGADDEEEEBEEHEHHEHFEBEGHFDHFBHFBDFDFFEBGDHCEBEEBEAGDADHAFAAFHBBEDF,True +916,19.0,25.0,17.0,15.0,26.0,25.0,27.0,16.0,EBBHBCGEEAEBCECGECHHCGDCECGECDBCDBAGCHGBFDBDBCEBFAAGAAHBGDFGAEGAEHEEHECGFFAFBEEAEEABEHBGHBFHDGCCFEFFCFFGFDHBAHAGFDGFDGHGGEDGEBGHGFFECBAFBHGEFBFGDFHDAADGGBAGBFCBFDEFAFBABE,False +917,1.0,1.0,0.0,2.0,5.0,1.0,1.0,0.0,DABDEEEEGFE,True +918,3.0,4.0,4.0,5.0,6.0,2.0,1.0,2.0,FCHDCBDCDEADEBDEBFBGACAEHEE,True +919,29.0,30.0,27.0,23.0,18.0,16.0,15.0,25.0,CECCDDBFGBEHCFACFCCAAAAABGDBDCBDABFBCEACABCGBHGDCGFBGHCDHCEHCBAFBFGHFHHDHFEHFEHCDBDDACBACGACGACFEDEBDHBDHAAEEGFBHHBHDAHBGBCGDAAHAFEBCCBDBEEAHEHFGHAHAABBABDHBDADDAECGBCEDCDCGEHAEHABBFF,False +920,6.0,8.0,6.0,2.0,10.0,1.0,2.0,2.0,ABABBFGBDGEECCEACECHEHBEABDBEEEACEACB,True +921,9.0,6.0,2.0,9.0,10.0,5.0,13.0,15.0,EBEDHGAHGFHGFBDEDDGCDGDHFAEABEGEGAHGAFEAGHAHHEHDEHDABDBGEGGBGHHACHFHH,True +922,0.0,4.0,4.0,4.0,5.0,3.0,8.0,5.0,BFCBHEBHDBCDFGGEGFEGEHGHCDHGDGGEC,False +923,9.0,18.0,18.0,28.0,20.0,33.0,20.0,19.0,FCFHEFDEBCBBCFACFDCDCAFCAHBDHBFGFHAFEAFEHGCHGDHCDHCFCGDCHBEGFFGDFGBHGDFGDFGFAHDBGGHHABEDFFDFFDFFEBFHDCEDFEFHEHHDGACFFGHBBHBADDDDCDEGDGGCEFCDBEBGEDEEBCEFGFFBEDGEDBFDE,False +924,2.0,5.0,0.0,7.0,6.0,1.0,0.0,3.0,EEDEEHEBAEBDDDADBHDFHBBD,True +925,12.0,20.0,17.0,18.0,18.0,15.0,13.0,21.0,GHHFHBACCFFHHFHHABHGDHFDEBABDDBCAEHABDEDCGDGDDGCDFFDHEBAEBAEBDCBGCEGBEHBFCEFDBGBFGBHBHHFFEEGECGECGECBHGBHDCHDAFDCFDEAHAHEAHACCEEFBBDCC,False 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+976,27.0,32.0,25.0,20.0,17.0,19.0,24.0,36.0,HCFABFDBGEFGFDCBDCAEBHEDADCADCGBCDACDBBHBBDAHAHHFFGEFHHBBHEFAEDHEHHBHHDAHCACCDDDAHCEECBBHBHHBGDBGBBGHCAHCFHFHGCHGAEGFFBBHCBHAAABACEGCGGCGACFACGHBDCBHCGGEHEBGAFFAEHHDFHDFEGFABDABGBBECBEBGAAFAACGHGHHGDH,False +977,21.0,23.0,33.0,29.0,26.0,21.0,26.0,19.0,BFCBCBEGFEGDEGFEBDACFGCDGADCDDCBBCGCDDCGCCGDDGBFBEEBAABAACFCCFHDDHDEBDEFCEBBGBEEDAEAHFCHFHHEBEEFFEFHEADEGEGGCGGADDFBCADDDCCGCCGCDGEDFADGDFGFFBCAAHAHEFHECAGFGDCEDCADBAHHHHEHHEFHBCCCCBBAABCAHHDGBEGCGG,False +978,7.0,8.0,10.0,5.0,10.0,5.0,5.0,1.0,DECDEBFCGFADFEBAECABABEGGECDFCGBEGCEHCBDCBCABCAEAFE,True +979,1.0,2.0,1.0,6.0,0.0,1.0,0.0,1.0,DCADFBDHDDBD,True +980,24.0,21.0,18.0,12.0,17.0,7.0,12.0,18.0,BBAHBHDDHBHFAHACBEBBCBAEEACHAHHEGBBGBCDCCAECAHCAGGAFFACFAHHEEAEHFGCACEACHFCHDDEDDEDDCBCCHEBHBAHEABBGBBADBGBBEAAGAADHEGEGGEGAFDACC,False +981,22.0,33.0,18.0,23.0,27.0,28.0,28.0,13.0,EAEDGBCFBAFBGFDAFAAGHAEBFHFFHFFGACDBDFCDFGDBEBBDHCFBEEGGDAGECGEFABFGBEDAEAHEGDDBEGCDABHBBGBDFBDHBGBBEBBHABAABDCEFGAFGAFBFCEFBGGHAGAFEDGEDCHFHBFGDHCFHCAGFDGCGECFECBECBECECABCAEFBEFEEGDBGDEGDBGD,False +982,22.0,20.0,15.0,16.0,27.0,17.0,27.0,21.0,GDFGHEGBEHCEBCHBEHBAHGCGGEGBBFDEADFFHADHEBHGDACDACDEBEEGEHBEGBEGHEBFAAFGFFGDFGDFABGHFHCEECHDGBDCBFFBGCBDDHDCGBCFAFHGGHEGACHECAEAAHCABAACAHEEDEADEFEGBGGEGAAGEBGFAHHAE,False +983,6.0,5.0,6.0,11.0,8.0,8.0,5.0,7.0,HBFHDFCEABBADECDEGDFCDFHBFEDECCFGHFAHGHHADEADFCDGDDGEBAE,False +984,9.0,13.0,13.0,13.0,32.0,25.0,15.0,18.0,EEAEEGEABEGHGFDADEEFAHHCBFGDCBBCHBCFDCFDCFDEFDEFCHFEFECFEHFHGFHGFHEBBCGECBDHHEEDEFCEGAADEFEHGEDFEHFEDFEGBHHFHGEEGEGAACFABFGFDGBEECEEFHBFHB,False +985,14.0,10.0,10.0,7.0,7.0,11.0,13.0,6.0,FAFAHGABAACAAGAFCDDCGCEFDBGBGACHECAECAEBAHDDFDBFDBFGBAGCHBEHBAGBECFFCEFGGGGGFH,False 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